Graph Builder

Example 1

Summary: Visualizes a spaghetti plot to analyze scores over time, utilizing Graph Builder with nested X variables and customized legend properties.

Code:

// Spaghetti Plot
// Open data table
dt = Open("data_table.jmp");
// Spaghetti Plot
Graph Builder(
    Size( 528, 450 ),
    Show Control Panel( 0 ),
    Variables(
        X( :Multiple Choice Year1 ),
        X(
            :Multiple Choice Year2,
            Position( 1 )
        ),
        X(
            :Multiple Choice Year3,
            Position( 1 )
        ),
        X(
            :Multiple Choice Year4,
            Position( 1 )
        )
    ),
    Elements(
        Parallel(
            X( 1 ),
            X( 2 ),
            X( 3 ),
            X( 4 ),
            Legend( 3 ),
            Curve Lines( 0 )
        ),
        Box Plot(
            X( 1 ),
            X( 2 ),
            X( 3 ),
            X( 4 ),
            Legend( 7 ),
            Box Style( "Solid" ),
            Width Proportion( 0.2 )
        ),
        Points(
            X( 1 ),
            X( 2 ),
            X( 3 ),
            X( 4 ),
            Legend( 5 )
        )
    ),
    SendToReport(
        Dispatch( {}, "400", ScaleBox,
            {
            Legend Model(
                7,
                Properties(
                    0,
                    {Line Color( 32 ),
                    Fill Color( 32 ),
                    Transparency( 0.7 )},
                    Item ID(
                        "Box Plot", 1
                    )
                )
            ),
            Legend Model(
                5,
                Properties(
                    0,
                    {Line Color( 62 ),
                    Marker Size( 1 ),
                    Transparency( 0.7 )},
                    Item ID(
                        "Marker", 1
                    )
                )
            )}
        ),
        Dispatch( {}, "graph title",
            TextEditBox,
            {
            Set Text(
                "Spaghetti Plot of Scores Over Time (each line represents an ID)"
            )}
        ),
        Dispatch( {}, "X title",
            TextEditBox,
            {Set Text( "" )}
        ),
        Dispatch( {}, "", AxisBox( 2 ),
            {Add Axis Label( "Score" )}
        ),
        Dispatch( {}, "400", LegendBox,
            {
            Legend Position(
                {3, [-4], 7, [1, -3], 5,
                [0]}
            )}
        )
    )
);

Code Explanation:

1. Open data table.
2. Create Graph Builder window.
3. Set window size.
4. Hide control panel.
5. Define X variables.
6. Add parallel lines element.
7. Add box plot element.
8. Add points element.
9. Customize legend properties.
10. Set graph title.

Example 2

Summary: Visualizes a spaghetti plot by sex, displaying parallel lines and points for multiple years, with interactive features like legend models and axis labels.

Code:

// Spaghetti Plot by Sex
// Open data table
dt = Open("data_table.jmp");
// Spaghetti Plot by Sex
Graph Builder(
    Size( 528, 449 ),
    Show Control Panel( 0 ),
    Variables(
        X( :Multiple Choice Year1 ),
        X(
            :Multiple Choice Year2,
            Position( 1 )
        ),
        X(
            :Multiple Choice Year3,
            Position( 1 )
        ),
        X(
            :Multiple Choice Year4,
            Position( 1 )
        ),
        Overlay( :Sex ),
        Color( :Sex )
    ),
    Elements(
        Parallel(
            X( 1 ),
            X( 2 ),
            X( 3 ),
            X( 4 ),
            Legend( 3 ),
            Smoothness( 0 )
        ),
        Points(
            X( 1 ),
            X( 2 ),
            X( 3 ),
            X( 4 ),
            Legend( 5 ),
            Jitter( "None" )
        ),
        Line(
            X( 1 ),
            X( 2 ),
            X( 3 ),
            X( 4 ),
            Legend( 6 )
        )
    ),
    SendToReport(
        Dispatch( {}, "400", ScaleBox,
            {
            Legend Model(
                3,
                Base(
                    0,
                    0,
                    0,
                    Item ID( "Male", 1 )
                ),
                Base(
                    1,
                    0,
                    0,
                    Item ID(
                        "Female", 1
                    )
                )
            ),
            Legend Model(
                5,
                Properties(
                    -1,
                    {Line Color( 62 ),
                    Marker Size( 1 ),
                    Transparency( 0.7 )},
                    Item ID(
                        "Marker", 1
                    )
                )
            )}
        ),
        Dispatch( {}, "graph title",
            TextEditBox,
            {
            Set Text(
                "Spaghetti Plot of Scores Over Time (each line represents an ID)"
            )}
        ),
        Dispatch( {}, "X title",
            TextEditBox,
            {Set Text( "" )}
        ),
        Dispatch( {}, "", AxisBox( 2 ),
            {Add Axis Label( "Score" )}
        ),
        Dispatch( {}, "400", LegendBox,
            {
            Legend Position(
                {3, [-4, -1], 5, [0, 1],
                6, [2, 3]}
            )}
        )
    )
);

Code Explanation:

1. Open data table.
2. Create Graph Builder window.
3. Set graph size.
4. Hide control panel.
5. Define X variables.
6. Overlay by Sex.
7. Color by Sex.
8. Add parallel lines.
9. Add points.
10. Add connecting lines.

Example 3

Summary: Visualizes geographic data by creating a Graph Builder map with points representing Longitude and Latitude, utilizing Geodesic US scales for both axes.

Code:

// Graph Builder Map
// Open data table
dt = Open("data_table.jmp");
// Graph Builder Map
Graph Builder(
    Size( 528, 453 ),
    Show Control Panel( 0 ),
    Variables(
        X( :Longitude ),
        Y( :Latitude )
    ),
    Elements(
        Points( X, Y, Legend( 8 ) )
    ),
    SendToReport(
        Dispatch( {}, "Longitude",
            ScaleBox,
            {Scale( "Geodesic US" ),
            Format( "Best", 10 ),
            Min( -130.465133704084 ),
            Max( -65.2794320942478 ),
            Inc( 5 ), Minor Ticks( 1 )}
        ),
        Dispatch( {}, "Latitude",
            ScaleBox,
            {Scale( "Geodesic US" ),
            Format( "Best", 10 ),
            Min( 15.9446169772257 ),
            Max( 68.7396480331263 ),
            Inc( 5 ), Minor Ticks( 1 )}
        ),
        Dispatch( {}, "Graph Builder",
            FrameBox,
            {
            Background Map(
                Images( "Simple Earth" )
            ), Grid Line Order( 2 ),
            Reference Line Order( 3 )}
        )
    )
);

Code Explanation:

1. Open table.
2. Create Graph Builder.
3. Set size.
4. Hide control panel.
5. Define X variable.
6. Define Y variable.
7. Add points element.
8. Configure Longitude scale.
9. Configure Latitude scale.
10. Add background map.

Example 4

Summary: Visualizes a street map of fatal accidents using Graph Builder, with Longitude and Latitude variables, and formats the scales for better visualization.

Code:

// Street Map of Fatal Accidents
// Open data table
dt = Open("data_table.jmp");
// Street Map of Fatal Accidents
Graph Builder(
    Size( 534, 454 ),
    Show Control Panel( 0 ),
    Variables(
        X( :Longitude ),
        Y( :Latitude ),
        Color( :Fatal )
    ),
    Elements(
        Points( X, Y, Legend( 3 ) )
    ),
    SendToReport(
        Dispatch( {}, "Longitude",
            ScaleBox,
            {
            Format(
                "Longitude DDD",
                "PUNDIR",
                16,
                2
            ), Min( -80.47 ),
            Max( -79.8904647541929 ),
            Inc( 0.1 ), Minor Ticks( 1 )}
        ),
        Dispatch( {}, "Latitude",
            ScaleBox,
            {
            Format(
                "Latitude DDD",
                "PUNDIR",
                16,
                2
            ), Min( 25.9668812835944 ),
            Max( 26.4639881027549 ),
            Inc( 0.1 ), Minor Ticks( 1 )}
        ),
        Dispatch( {}, "Graph Builder",
            FrameBox,
            {
            Background Map(
                Images(
                    "Street Map Service"
                )
            ), Grid Line Order( 2 ),
            Reference Line Order( 3 )}
        )
    )
);

Code Explanation:

1. Open table.
2. Create Graph Builder.
3. Set size.
4. Hide control panel.
5. Define variables.
6. Add points element.
7. Format Longitude scale.
8. Set Longitude min and max.
9. Format Latitude scale.
10. Set Latitude min and max.

Example 5

Summary: Visualizes arrival delays by day and month using a Graph Builder Heatmap, with customized X-axis, Y-axis, and color legend.

Code:

// Graph Builder Heatmap
// Open data table
dt = Open("data_table.jmp");
// Graph Builder Heatmap
Graph Builder(
    Size( 1033, 428 ),
    Show Control Panel( 0 ),
    Variables(
        X( :Day of Month ),
        Y( :Month ),
        Color( :Arrival Delay )
    ),
    Elements(
        Heatmap(
            X,
            Y,
            Color,
            Legend( 5 )
        )
    ),
    SendToReport(
        Dispatch( {}, "Day Of Month",
            ScaleBox,
            {Show Major Ticks( 0 )}
        ),
        Dispatch( {}, "Month", ScaleBox,
            {Min( 11.5 ), Max( -0.5 ),
            Inc( 1 ), Minor Ticks( 0 ),
            Show Major Ticks( 0 ),
            Show Minor Ticks( 0 )}
        ),
        Dispatch( {}, "400", ScaleBox,
            {
            Legend Model(
                5,
                Properties(
                    0,
                    {
                    gradient(
                        {
                        Label Levels(
                            [-10 2.5 15
                            27.5 40]
                        ),
                        Label Format(
                            "Fixed Dec",
                            15, 0
                        ),
                        Reverse Colors(
                            1
                        ),
                        Reverse Scale(
                            1
                        )}
                    )}
                )
            )}
        ),
        Dispatch( {}, "graph title",
            TextEditBox,
            {
            Set Text(
                "Arrival Delays by Day"
            )}
        )
    )
);

Code Explanation:

1. Open table.
2. Create Graph Builder.
3. Set size.
4. Hide control panel.
5. Define variables.
6. Add heatmap element.
7. Configure X-axis.
8. Configure Y-axis.
9. Customize legend.
10. Set graph title.

Example 6

Summary: Generates a Graph Builder Bar chart to visualize the mean number of flights by airline and day of week, with side-by-side bars for each combination.

Code:

// Graph Builder Bar
// Open data table
dt = Open("data_table.jmp");
// Graph Builder Bar
Graph Builder(
    Show Control Panel( 0 ),
    Variables(
        X( :Day of Week ),
        Overlay( :Airline )
    ),
    Elements(
        Bar(
            X,
            Legend( 2 ),
            Bar Style( "Side by side" ),
            Summary Statistic( "Mean" )
        )
    ),
    SendToReport(
        Dispatch( {}, "graph title",
            TextEditBox,
            {
            Set Text(
                "Flights by Airline and Day of Week"
            )}
        )
    )
);

Code Explanation:

1. Open table.
2. Create Graph Builder.
3. Hide control panel.
4. Set X variable.
5. Set overlay variable.
6. Add bar element.
7. Set legend position.
8. Set bar style.
9. Set summary statistic.
10. Set graph title.

Example 7

Summary: Generates a histogram to visualize the distribution of flight distances by airline, with customized scale and title settings.

Code:

// Graph Builder Histogram
// Open data table
dt = Open("data_table.jmp");
// Graph Builder Histogram
gb =
Graph Builder(
    Show Control Panel( 0 ),
    Variables(
        X( :Distance ),
        Wrap( :Airline )
    ),
    Elements(
        Histogram( X, Legend( 9 ) )
    ),
    SendToReport(
        Dispatch( {}, "Distance",
            ScaleBox,
            {Min( -6.07535604831441 ),
            Max( 2900 ), Inc( 500 ),
            Minor Ticks( 0 )}
        ),
        Dispatch( {}, "graph title",
            TextEditBox,
            {
            Set Text(
                "Flight Distance by Airline"
            )}
        )
    )
);
rotate = gb << report;
axisbox = rotate[axis box( 1 )];
axisbox << Rotated Labels( "Angled" );

Code Explanation:

1. Open table.
2. Create Graph Builder object.
3. Hide control panel.
4. Set X variable to Distance.
5. Wrap Airline variable.
6. Add histogram element.
7. Set distance scale.
8. Set graph title.
9. Rotate report.
10. Set axis labels to angled.

Example 8

Summary: Visualizes a contour plot to analyze the relationship between Distance and Arrival Delay, with Airline as a wrap variable, using Graph Builder in JMP.

Code:

// Graph Builder Contour Plot
// Open data table
dt = Open("data_table.jmp");
// Graph Builder Contour Plot
Graph Builder(
    Show Control Panel( 0 ),
    Variables(
        X( :Distance ),
        Y( :Arrival Delay ),
        Wrap( :Airline )
    ),
    Elements(
        Contour(
            X,
            Y,
            Legend( 6 ),
            Number of Levels( 6 )
        )
    )
);

Code Explanation:

1. Open data table.
2. Create Graph Builder.
3. Hide control panel.
4. Set X variable: Distance.
5. Set Y variable: Arrival Delay.
6. Set wrap variable: Airline.
7. Add Contour element.
8. Set Contour X axis.
9. Set Contour Y axis.
10. Configure legend and levels.

Example 9

Summary: Visualizes airline flight count data using a Treemap element in Graph Builder, with color-coded by average delay and displaying summary statistics.

Code:

// Graph Builder Treemap
// Open data table
dt = Open("data_table.jmp");
// Graph Builder Treemap
Graph Builder(
    Show Control Panel( 0 ),
    Variables(
        X( :Airline ),
        Color( :Arrival Delay )
    ),
    Elements(
        Treemap(
            X,
            Color,
            Legend( 5 ),
            Summary Statistic(
                "Sum Wgt"
            )
        )
    ),
    SendToReport(
        Dispatch( {}, "graph title",
            TextEditBox,
            {
            Set Text(
                "Airline Flight Count colored by Average Delay"
            )}
        ),
        Dispatch( {}, "Graph Builder",
            FrameBox,
            {
            DispatchSeg(
                TreemapSeg( 1 ),
                Frame Size( 559, 452 )
            )}
        )
    )
);

Code Explanation:

1. Open table.
2. Create Graph Builder.
3. Hide control panel.
4. Set X variable.
5. Set color variable.
6. Add Treemap element.
7. Configure legend position.
8. Set summary statistic.
9. Rename graph title.
10. Adjust frame size.

Example 10

Summary: Visualizes QRS duration by Age, with Sex as a wrapping factor, using Graph Builder to create a variability chart with nested factors and display standard deviation charts.

Code:

// Graph Builder: QRS duration by Age
// Open data table
dt = Open("data_table.jmp");
// Graph Builder: QRS duration by Age
Graph Builder(
    Show Control Panel( 0 ),
    Variables(
        X( :Age ),
        Y( :QRS duration ),
        Wrap( :Sex )
    ),
    Elements(
        Smoother( X, Y, Legend( 34 ) ),
        Points( X, Y, Legend( 35 ) )
    ),
    SendToReport(
        Dispatch( {}, "Age", ScaleBox,
            {Min( -16 )}
        ),
        Dispatch( {}, "", ScaleBox,
            {
            Label Row(
                {Automatic Font Size( 1 ),
                Label Orientation(
                    "Automatic"
                ),
                Automatic Tick Marks( 1 )
                }
            )}
        ),
        Dispatch( {}, "", ScaleBox( 2 ),
            {
            Label Row(
                {Automatic Font Size( 1 ),
                Label Orientation(
                    "Automatic"
                ),
                Automatic Tick Marks( 1 )
                }
            )}
        )
    )
);

Code Explanation:

1. Open table.
2. Create Graph Builder.
3. Hide control panel.
4. Set X variable to Age.
5. Set Y variable to QRS duration.
6. Wrap by Sex.
7. Add smoother element.
8. Add points element.
9. Set X axis minimum.
10. Adjust scale labels.

Example 11

Summary: Creates a Graph Builder object to visualize three variables (Revenue, Bed occupancy rate, and Average length of stay) over time, with each variable displayed on a separate axis. The script also formats the date scale and sets the graph title.

Code:

// Graph Builder Smoother 1
// Open data table
dt = Open("data_table.jmp");
// Graph Builder Smoother 1
Graph Builder(
    Show Control Panel( 0 ),
    Show Legend( 0 ),
    Variables(
        X( :Date ),
        Y( :"Revenue ($'000)"n ),
        Y( :"Bed occupancy rate (%)"n ),
        Y(
            :
            "Average length of stay (days)"n
        )
    ),
    Elements(
        Position( 1, 1 ),
        Points( X, Y, Legend( 4 ) ),
        Smoother( X, Y, Legend( 3 ) )
    ),
    Elements(
        Position( 1, 2 ),
        Points( X, Y, Legend( 1 ) ),
        Smoother( X, Y, Legend( 2 ) )
    ),
    Elements(
        Position( 1, 3 ),
        Points( X, Y, Legend( 6 ) ),
        Smoother( X, Y, Legend( 5 ) )
    ),
    SendToReport(
        Dispatch( {}, "Date", ScaleBox,
            {Format( "yyyyQq", 6 ),
            Min( 2953282344.82759 ),
            Max( 3408220800 ),
            Interval( "Year" ), Inc( 2 ),
            Minor Ticks( 0 )}
        ),
        Dispatch( {}, "graph title",
            TextEditBox,
            {Set Text( "Tourism Trends" )
            }
        )
    )
);

Code Explanation:

1. Open data table.
2. Create Graph Builder object.
3. Hide control panel.
4. Hide legend.
5. Set X variable.
6. Set first Y variable.
7. Set second Y variable.
8. Set third Y variable.
9. Add points and smoother for first Y.
10. Add points and smoother for second Y.
11. Add points and smoother for third Y.
12. Format date scale.
13. Set graph title.

Example 12

Summary: Generates a Graph Builder object to visualize the relationship between Date, Revenue ($'000), and Persons Employed using points and smoothers.

Code:

// Graph Builder Smoother 2
// Open data table
dt = Open("data_table.jmp");
// Graph Builder Smoother 2
Graph Builder(
    Show Control Panel( 0 ),
    Variables(
        X( :Date ),
        Y( :"Revenue ($'000)"n ),
        Y(
            :Persons Employed,
            Position( 1 ),
            Side( "Right" )
        )
    ),
    Elements(
        Points( X, Y( 1 ), Legend( 1 ) ),
        Smoother(
            X,
            Y( 1 ),
            Legend( 4 )
        ),
        Points( X, Y( 2 ), Legend( 5 ) ),
        Smoother(
            X,
            Y( 2 ),
            Legend( 6 )
        )
    )
);

Code Explanation:

1. Open data table.
2. Create Graph Builder object.
3. Hide control panel.
4. Set X variable: Date.
5. Set primary Y variable: Revenue.
6. Set secondary Y variable: Persons Employed.
7. Add primary Y points element.
8. Add primary Y smoother element.
9. Add secondary Y points element.
10. Add secondary Y smoother element.

Example 13

Summary: Generates a line chart using Graph Builder to visualize the relationship between year, room occupancy rate, and quarter. The script customizes the x-axis, y-axis, and legend, and adds a title to the graph.

Code:

// Graph Builder Line Chart
// Open data table
dt = Open("data_table.jmp");
// Graph Builder Line Chart
Graph Builder(
    Show Control Panel( 0 ),
    Variables(
        X( :Year ),
        Y( :"Room occupancy rate (%)"n ),
        Overlay( :Quarter )
    ),
    Elements(
        Line(
            X,
            Y,
            Legend( 7 ),
            Row order( 0 ),
            Summary Statistic( "Mean" )
        )
    ),
    SendToReport(
        Dispatch( {}, "Year", ScaleBox,
            {Show Major Ticks( 0 )}
        ),
        Dispatch( {},
            "Room occupancy rate (%)",
            ScaleBox,
            {Min( 54.5305429864253 ),
            Max( 75 ), Inc( 5 ),
            Minor Ticks( 1 )}
        ),
        Dispatch( {}, "400", ScaleBox,
            {
            Legend Model(
                7,
                Properties(
                    0,
                    {Line Width( 2 )}
                ),
                Properties(
                    1,
                    {Line Width( 2 )}
                ),
                Properties(
                    2,
                    {Line Width( 2 )}
                ),
                Properties(
                    3,
                    {Line Width( 2 )}
                )
            )}
        ),
        Dispatch( {}, "graph title",
            TextEditBox,
            {
            Set Text(
                "Room occupancy rate vs. Year and Quarter"
            )}
        )
    )
);

Code Explanation:

1. Open table.
2. Create Graph Builder.
3. Hide control panel.
4. Set X variable.
5. Set Y variable.
6. Set overlay variable.
7. Add line element.
8. Customize X scale.
9. Customize Y scale.
10. Customize legend and title.

Example 14

Summary: Generates a Graph Builder with Pictures to visualize the relationship between height and weight, including points and a line of fit, while also customizing scales for both variables.

Code:

// Graph Builder with Pictures
// Open data table
dt = Open("data_table.jmp");
// Graph Builder with Pictures
Graph Builder(
    Size( 535, 455 ),
    Show Control Panel( 0 ),
    Variables(
        X( :height ),
        Y( :weight )
    ),
    Elements(
        Points( X, Y, Legend( 4 ) ),
        Line Of Fit( X, Y, Legend( 6 ) )
    ),
    SendToReport(
        Dispatch( {}, "height", ScaleBox,
            {Max( 76.9635779034077 )}
        ),
        Dispatch( {}, "weight", ScaleBox,
            {Min( 5.25227987752102 ),
            Max( 201.373603652071 ),
            Inc( 25 ), Minor Ticks( 0 )}
        ),
        Dispatch( {}, "Graph Builder",
            FrameBox,
            {Marker Size( 2 ),
            {Add Pin Annotation(
                Seg( Marker Seg( 1 ) ),
                Index( 39 ),
                Index Row( 39 ),
                UniqueID( 1180683047 ),
                FoundPt( {717, 157} ),
                Origin(
                    {70.1036850751071,
                    172.033784817876}
                ),
                Offset( {8, 9} ),
                Tag Line
            ),
            Add Pin Annotation(
                Seg( Marker Seg( 1 ) ),
                Index( 7 ),
                Index Row( 7 ),
                UniqueID( 691854391 ),
                FoundPt( {124, 311} ),
                Origin(
                    {51.0074683737235,
                    80.0858968472606}
                ),
                Offset( {-57, -95} ),
                Tag Line
            ),
            Add Pin Annotation(
                Seg( Marker Seg( 1 ) ),
                Index( 4 ),
                Index Row( 4 ),
                UniqueID( 691854388 ),
                FoundPt( {143, 354} ),
                Origin(
                    {52.0652762959576,
                    62.2761707988982}
                ),
                Offset( {74, 44} ),
                Tag Line
            ),
            Add Pin Annotation(
                Seg( Marker Seg( 1 ) ),
                Index( 11 ),
                Index Row( 11 ),
                UniqueID( 1452711899 ),
                FoundPt( {347, 257} ),
                Origin(
                    {64.8386487250506,
                    97.865127215503}
                ),
                Offset( {6, 65} ),
                Tag Line
            ),
            Add Pin Annotation(
                Seg( Marker Seg( 1 ) ),
                Index( 37 ),
                Index Row( 37 ),
                UniqueID( 570414821 ),
                FoundPt( {305, 222} ),
                Origin(
                    {62.2317889517039,
                    117.036444064542}
                ),
                Offset( {-139, -88} ),
                Tag Line
            )}}
        )
    )
);

Code Explanation:

1. Open table.
2. Create Graph Builder.
3. Set size.
4. Hide control panel.
5. Define X variable.
6. Define Y variable.
7. Add points element.
8. Add line of fit element.
9. Set height scale max.
10. Set weight scale min, max, increment, minor ticks.
11. Add pin annotations.

Example 15

Summary: Visualizes the relationship between height and weight, with sex as an overlay, using Graph Builder's Points and Smoother elements.

Code:

// Graph Builder Smoother Line
// Open data table
dt = Open("data_table.jmp");
// Graph Builder Smoother Line
Graph Builder(
    Show Control Panel( 0 ),
    Variables(
        X( :height ),
        Y( :weight ),
        Overlay( :sex )
    ),
    Elements(
        Points( X, Y, Legend( 1 ) ),
        Smoother( X, Y, Legend( 2 ) )
    )
);

Code Explanation:

1. Open data table.
2. Create Graph Builder object.
3. Hide control panel.
4. Set X variable to height.
5. Set Y variable to weight.
6. Overlay by sex.
7. Add points element.
8. Add smoother element.
9. Assign points legend.
10. Assign smoother legend.

Example 16

Summary: Visualizes the relationship between age, height, and weight using Graph Builder, creating a line chart with mean summary statistics for height and weight, and a bar chart in side-by-side style also showing mean summary statistics.

Code:

// Graph Builder Line and Bar Charts
// Open data table
dt = Open("data_table.jmp");
// Graph Builder Line and Bar Charts
Graph Builder(
    Show Control Panel( 0 ),
    Variables(
        X( :age, Size( 15, 20 ) ),
        Y( :height, Size( 38, 36 ) ),
        Y( :weight )
    ),
    Elements(
        Position( 1, 1 ),
        Line(
            X,
            Y,
            Legend( 1 ),
            Row order( 0 ),
            Summary Statistic( "Mean" )
        )
    ),
    Elements(
        Position( 1, 2 ),
        Bar(
            X,
            Y,
            Legend( 2 ),
            Bar Style( "Side by side" ),
            Summary Statistic( "Mean" )
        )
    )
);

Code Explanation:

1. Open data table.
2. Create Graph Builder.
3. Hide control panel.
4. Set X variable: age.
5. Set Y variable: height.
6. Set Y variable: weight.
7. Add line element to position 1,1.
8. Configure line for mean summary statistic.
9. Add bar element to position 1,2.
10. Configure bar for side-by-side style and mean summary statistic.

Example 17

Summary: Generates a Graph Builder line chart with nested factors, displaying the mean summary statistic and applying jitter effect to points. The chart overlays sex by age and height.

Code:

// Graph Builder Line Chart
// Open data table
dt = Open("data_table.jmp");
// Graph Builder Line Chart
Graph Builder(
    Show Control Panel( 0 ),
    Variables(
        X( :age ),
        Y( :height ),
        Overlay( :sex )
    ),
    Elements(
        Line(
            X,
            Y,
            Legend( 3 ),
            Row order( 0 ),
            Summary Statistic( "Mean" )
        ),
        Points(
            X,
            Y,
            Legend( 4 ),
            Jitter( 1 )
        )
    ),
    SendToReport(
        Dispatch( {}, "400", ScaleBox,
            {
            Legend Model(
                4,
                Base( 0, 0, 0 ),
                Base( 1, 0, 1 ),
                Properties(
                    0,
                    {Marker( "Plus" )}
                ),
                Properties(
                    1,
                    {Marker( "Square" )}
                )
            )}
        )
    )
);

Code Explanation:

1. Open data table.
2. Create Graph Builder.
3. Hide control panel.
4. Set X variable to age.
5. Set Y variable to height.
6. Overlay by sex.
7. Add line element.
8. Calculate mean summary statistic.
9. Add points element.
10. Apply jitter effect.

Example 18

Summary: Visualizes a heatmap to analyze the relationship between age and sex, utilizing Graph Builder with a Heatmap element.

Code:

// Graph Builder Heatmap
// Open data table
dt = Open("data_table.jmp");
// Graph Builder Heatmap
Graph Builder(
    Show Control Panel( 0 ),
    Variables( X( :age ), Y( :sex ) ),
    Elements(
        Heatmap( X, Y, Legend( 2 ) )
    )
);

Code Explanation:

1. Open data table.
2. Create Graph Builder object.
3. Hide control panel.
4. Set X variable to age.
5. Set Y variable to sex.
6. Add Heatmap element.
7. Position legend at 2.

Example 19

Summary: Visualizes a packed bar chart to display the unique events (Y-axis) against their corresponding costs (X-axis) from a data table, with customized formatting for cost values and a title.

Code:

// Packed Bar Chart
// Open data table
dt = Open("data_table.jmp");
// Packed Bar Chart
Graph Builder(
    Size( 813, 484 ),
    Show Control Panel( 0 ),
    Show Legend( 0 ),
    Title Alignment( "Left" ),
    Title Span( "Graph contents" ),
    Subtitle Alignment( "Left" ),
    Subtitle Span( "Graph contents" ),
    Show Subtitle( 1 ),
    Show Footer( 0 ),
    Variables(
        X( :Cost ),
        Y( :Unique Event )
    ),
    Elements(
        Bar(
            X,
            Y,
            Legend( 6 ),
            Bar Style( "Packed" ),
            Packed Primaries( 10 ),
            Packed Labeling( 0.4091 )
        )
    ),
    SendToReport(
        Dispatch( {}, "Cost", ScaleBox,
            {
            Format(
                "Custom",
                Formula(
                    If( value == 0,
                        "0",
                        "$" ||
                        Format(
                            value,
                            "precision",
                            Keep trailing zeroes(
                                0
                            ),
                            3
                        ) || "B"
                    )
                ),
                17
            ), Min( 0 ),
            Max( 164.265890870419 ),
            Inc( 20 ), Minor Ticks( 0 )}
        ),
        Dispatch( {}, "graph title",
            TextEditBox,
            {Set Font Size( 18 ),
            Set Font Style( "Plain" ),
            Set Text(
                "Billion-dollar disasters in the US, 1980-2017"
            )}
        ),
        Dispatch( {}, "graph 1 title",
            TextEditBox,
            {Set Font Size( 15 ),
            Set Text(
                "CPI-adjusted estimated costs from NOAA, www.ncdc.noaa.gov/billions/"
            )}
        ),
        Dispatch( {}, "X title",
            TextEditBox,
            {Set Text( "" )}
        ),
        Dispatch( {}, "Y title",
            TextEditBox,
            {Set Text( "" )}
        ),
        Dispatch( {}, "400", LegendBox,
            {Set Title( "" ),
            font( "Arial", 16, "Plain" )}
        )
    )
);

Code Explanation:

1. Open data table.
2. Create Graph Builder.
3. Set graph size.
4. Hide control panel.
5. Hide legend.
6. Align title left.
7. Span title.
8. Show subtitle.
9. Hide footer.
10. Define variables X and Y.
11. Add packed bar element.
12. Customize cost scale format.
13. Set cost scale range.
14. Set cost scale increment.
15. Set main graph title.
16. Set X axis title.
17. Set Y axis title.
18. Customize legend title.

Example 20

Summary: Generates a variability chart with nested factors using operator and part configurations, displaying standard deviation charts.

Code:

// Bullets
// Open data table
dt = Open("data_table.jmp");
// Bullets
Graph Builder(
    Size( 518, 456 ),
    Show Control Panel( 0 ),
    Legend Position( "Bottom" ),
    Variables(
        X( :Actual ),
        X( :Target, Position( 1 ) ),
        X( :Minimum, Position( 1 ) ),
        Y(
            :Product,
            Order By(
                :Target,
                Ascending,
                Order Statistic( "Mean" )
            )
        )
    ),
    Elements(
        Bar(
            X( 1 ),
            X( 3 ),
            X( 2 ),
            Y,
            Legend( 4 ),
            Bar Style( "Bullet" )
        )
    ),
    SendToReport(
        Dispatch( {}, "400", ScaleBox,
            {
            Legend Model(
                4,
                Properties(
                    1,
                    {Fill Color( 16 )},
                    Item ID(
                        "Minimum", 1
                    )
                ),
                Properties(
                    2,
                    {Fill Color( 32 )},
                    Item ID(
                        "Target", 1
                    )
                )
            )}
        )
    )
);

Code Explanation:

1. Open data table.
2. Create Graph Builder object.
3. Set graph size.
4. Hide control panel.
5. Position legend at bottom.
6. Define X variables.
7. Define Y variable.
8. Add bar element.
9. Customize bar style.
10. Set legend properties.

Example 21

Summary: Visualizes a box plot to compare the distribution of Gas Tank Size across different Type categories, using Graph Builder and configuring various settings such as legend, jitter, outliers, and box style.

Code:

// Graph Builder Box Plot
// Open data table
dt = Open("data_table.jmp");
// Graph Builder Box Plot
Graph Builder(
    Show Control Panel( 0 ),
    Variables(
        X( :Gas Tank Size ),
        Y( :Type )
    ),
    Elements(
        Box Plot(
            X,
            Y,
            Legend( 8 ),
            Jitter( 1 ),
            Outliers( 1 ),
            Box Style( "Outlier" )
        )
    )
);

Code Explanation:

1. Open table.
2. Set graph builder options.
3. Add variables to axes.
4. Create box plot element.
5. Configure box plot settings.
6. Enable jitter.
7. Show outliers.
8. Set box style.
9. Build graph.

Example 22

Summary: Generates a Graph Builder Contour Plot with multiple elements to visualize the relationship between Type, Country, Horsepower, and Turning Circle in a data table. The script customizes the plot by setting marker sizes and hiding the control panel.

Code:

// Graph Builder Contour Plot
// Open data table
dt = Open("data_table.jmp");
// Graph Builder Contour Plot
Graph Builder(
    Variables(
        X( :Type ),
        X( :Country ),
        Y( :Horsepower ),
        Y( :Turning Circle )
    ),
    Show Control Panel( 0 ),
    Elements(
        Position( 1, 1 ),
        Contour(
            X,
            Y,
            Legend( 21 ),
            Number of Levels( 0 )
        )
    ),
    Elements(
        Position( 1, 2 ),
        Contour(
            X,
            Y,
            Legend( 35 ),
            Number of Levels( 0 )
        )
    ),
    Elements(
        Position( 2, 1 ),
        Contour(
            X,
            Y,
            Legend( 26 ),
            Number of Levels( 0 )
        )
    ),
    Elements(
        Position( 2, 2 ),
        Contour(
            X,
            Y,
            Legend( 36 ),
            Number of Levels( 0 )
        )
    ),
    SendToReport(
        Dispatch( {}, "Type", ScaleBox,
            {Show Major Ticks( 0 ),
            Show Minor Ticks( 0 ),
            Rotated Labels( "Automatic" )
            }
        ),
        Dispatch( {}, "Graph Builder",
            FrameBox,
            {Marker Size( 5 )}
        ),
        Dispatch( {}, "Graph Builder",
            FrameBox( 2 ),
            {Marker Size( 5 )}
        ),
        Dispatch( {}, "Graph Builder",
            FrameBox( 3 ),
            {Marker Size( 5 )}
        ),
        Dispatch( {}, "Graph Builder",
            FrameBox( 4 ),
            {Marker Size( 5 )}
        )
    )
);

Code Explanation:

1. Open table.
2. Set variables for plot.
3. Hide control panel.
4. Add first contour element.
5. Add second contour element.
6. Add third contour element.
7. Add fourth contour element.
8. Customize Type axis.
9. Set marker size for first frame.
10. Set marker size for remaining frames.

Example 23

Summary: Visualizes a mosaic plot to analyze the relationship between urban/rural areas and goals, utilizing Graph Builder's Variables and Elements features.

Code:

// Graph Builder Mosaic Plot
// Open data table
dt = Open("data_table.jmp");
// Graph Builder Mosaic Plot
Graph Builder(
    Show Control Panel( 0 ),
    Variables(
        X( :"Urban/Rural"n ),
        Y( :Goals )
    ),
    Elements(
        Mosaic(
            X,
            Y,
            Legend( 6 ),
            Vertical( 1 )
        )
    )
);

Code Explanation:

1. Open table.
2. Create Graph Builder.
3. Hide control panel.
4. Set X variable.
5. Set Y variable.
6. Add Mosaic element.
7. Configure X axis.
8. Configure Y axis.
9. Add legend.
10. Set vertical orientation.

Example 24

Summary: Visualizes US cities on a map, colored by maximum temperature in January and sized by lead levels, using Graph Builder.

Code:

// Graph Builder Map Lead Levels
// Open data table
dt = Open("data_table.jmp");
// Graph Builder Map Lead Levels
Graph Builder(
    Size( 733, 396 ),
    Show Control Panel( 0 ),
    Variables(
        X( :Longitude ),
        Y( :Latitude ),
        Color( :Max deg. F Jan ),
        Size( :Lead )
    ),
    Elements(
        Points( X, Y, Legend( 1 ) )
    ),
    SendToReport(
        Dispatch( {}, "graph title",
            TextEditBox,
            {
            Set Text(
                "US Cities Colored by Max deg. F Jan, Sized by Lead Levels"
            )}
        ),
        Dispatch( {}, "Graph Builder",
            FrameBox,
            {
            Background Map(
                Boundaries( "US States" )
            ), Grid Line Order( 2 ),
            Reference Line Order( 3 )}
        )
    )
);

Code Explanation:

1. Open table.
2. Create Graph Builder.
3. Set size.
4. Hide control panel.
5. Define variables.
6. Add points element.
7. Set graph title.
8. Add background map.
9. Set grid line order.
10. Set reference line order.

Example 25

Summary: Visualizes a treemap representation of US cities, colored by maximum degree Fahrenheit in January and sized by population, using Graph Builder.

Code:

// Graph Builder Treemap
// Open data table
dt = Open("data_table.jmp");
// Graph Builder Treemap
Graph Builder(
    Show Control Panel( 0 ),
    Variables(
        X( :city ),
        Color( :OZONE ),
        Size( :POP )
    ),
    Elements(
        Treemap(
            X,
            Legend( 4 ),
            Summary Statistic( "Sum" )
        )
    ),
    SendToReport(
        Dispatch( {}, "graph title",
            TextEditBox,
            {
            Set Text(
                "US Cities Colored by Max deg. F Jan, Sized by Lead Levels"
            )}
        )
    )
);

Code Explanation:

1. Open data table.
2. Create Graph Builder object.
3. Hide control panel.
4. Set X variable to city.
5. Set color variable to OZONE.
6. Set size variable to POP.
7. Add Treemap element.
8. Configure Treemap X axis.
9. Set legend position.
10. Set summary statistic to Sum.

Example 26

Summary: Visualizes a street map with CO levels, utilizing Graph Builder to create a geographic representation of data table variables.

Code:

// Street Map of CO Levels
// Open data table
dt = Open("data_table.jmp");
// Street Map of CO Levels
Graph Builder(
    Size( 534, 454 ),
    Show Control Panel( 0 ),
    Variables(
        X( :Longitude ),
        Y( :Latitude ),
        Color( :CO ),
        Size( :CO )
    ),
    Elements(
        Points( X, Y, Legend( 3 ) )
    ),
    SendToReport(
        Dispatch( {}, "Longitude",
            ScaleBox,
            {
            Format(
                "Longitude DMM",
                "PUNDIR",
                16,
                2
            ), Min( -118.541305514709 ),
            Max( -118.214656222605 ),
            Inc( 0.05 ), Minor Ticks( 0 )
            }
        ),
        Dispatch( {}, "Latitude",
            ScaleBox,
            {
            Format(
                "Latitude DMM",
                "PUNDIR",
                16,
                2
            ), Min( 33.9545722020228 ),
            Max( 34.2442702167396 ),
            Inc( 0.05 ), Minor Ticks( 1 )
            }
        ),
        Dispatch( {}, "Graph Builder",
            FrameBox,
            {
            Background Map(
                Images(
                    "Street Map Service"
                )
            ), Grid Line Order( 2 ),
            Reference Line Order( 3 )}
        )
    )
);

Code Explanation:

1. Open table.
2. Create Graph Builder.
3. Set size and control panel.
4. Define variables.
5. Add points element.
6. Send report dispatch for Longitude.
7. Format Longitude scale.
8. Set Longitude range and increments.
9. Send report dispatch for Latitude.
10. Format Latitude scale.

Example 27

Summary: Visualizes street map data with lead levels, utilizing Graph Builder to create a geographic map with color-coded points and size variation.

Code:

// Street Map of Lead Levels
// Open data table
dt = Open("data_table.jmp");
// Street Map of Lead Levels
Graph Builder(
    Size( 794, 631 ),
    Show Control Panel( 0 ),
    Variables(
        X( :Longitude ),
        Y( :Latitude ),
        Color( :Lead ),
        Size( :Lead )
    ),
    Elements(
        Points( X, Y, Legend( 9 ) )
    ),
    SendToReport(
        Dispatch( {}, "Longitude",
            ScaleBox,
            {
            Format(
                "Longitude DMM",
                "PUNDIR",
                16,
                1
            ), Min( -95.5529420307842 ),
            Max( -94.6858125750935 ),
            Inc( 0.1 ), Minor Ticks( 0 )}
        ),
        Dispatch( {}, "Latitude",
            ScaleBox,
            {
            Format(
                "Latitude DMM",
                "PUNDIR",
                16,
                3
            ), Min( 29.1629328457319 ),
            Max( 29.8728560979449 ),
            Inc( 0.1 ), Minor Ticks( 0 )}
        ),
        Dispatch( {}, "Graph Builder",
            FrameBox,
            {
            Background Map(
                Images(
                    "Street Map Service"
                )
            ), Grid Line Order( 2 ),
            Reference Line Order( 3 )}
        )
    )
);

Code Explanation:

1. Open table.
2. Create Graph Builder.
3. Set size.
4. Hide control panel.
5. Define X variable.
6. Define Y variable.
7. Define color variable.
8. Define size variable.
9. Add points element.
10. Configure longitude scale.
11. Configure latitude scale.
12. Add background map.
13. Set grid line order.
14. Set reference line order.

Example 28

Summary: Generates a variability chart with nested factors using Graph Builder, displaying standard deviation charts and overlaying data by testers.

Code:

// Graph Builder
// Open data table
dt = Open("data_table.jmp");
// Graph Builder
Graph Builder(
    Show Control Panel( 0 ),
    Variables(
        X(
            :"Time (Numeric)"n,
            Size( 0, 22 )
        ),
        Y( :Heart Rate, Size( 0, 23 ) ),
        Group X( :Drink ),
        Overlay( :Testers )
    ),
    Elements(
        Points( X, Y, Legend( 88 ) ),
        Line(
            X,
            Y,
            Legend( 90 ),
            Row order( 0 ),
            Summary Statistic( "Mean" )
        )
    )
);

Code Explanation:

1. Open data table.
2. Create Graph Builder object.
3. Hide control panel.
4. Set X variable.
5. Set Y variable.
6. Group by Drink.
7. Overlay by Testers.
8. Add points element.
9. Add line element.
10. Display graph.

Example 29

Summary: Creates a variability chart with nested factors using Graph Builder, displaying standard deviation charts and overlaying data by testers.

Code:

// Graph Builder 2
// Open data table
dt = Open("data_table.jmp");
// Graph Builder 2
Graph Builder(
    Show Control Panel( 0 ),
    Variables(
        X(
            :"Time (Numeric)"n,
            Size( 0, 22 )
        ),
        Y( :Heart Rate, Size( 0, 23 ) ),
        Group X( :Brand ),
        Group X( :Type ),
        Overlay( :Testers )
    ),
    Elements(
        Points( X, Y, Legend( 88 ) ),
        Line(
            X,
            Y,
            Legend( 90 ),
            Row order( 0 ),
            Summary Statistic( "Mean" )
        )
    )
);

Code Explanation:

1. Open data table.
2. Create Graph Builder.
3. Hide control panel.
4. Set X variable.
5. Set Y variable.
6. Group by Brand.
7. Group by Type.
8. Overlay by Testers.
9. Add points element.
10. Add line element.

Example 30

Summary: Creates a variability chart with nested factors using Graph Builder, displaying standard deviation charts and overlaying data by testers.

Code:

// Graph Builder 3
// Open data table
dt = Open("data_table.jmp");
// Graph Builder 3
Graph Builder(
    Show Control Panel( 0 ),
    Variables(
        X(
            :"Time (Numeric)"n,
            Size( 0, 22 )
        ),
        Y( :Heart Rate, Size( 0, 23 ) ),
        Group X( :Brand ),
        Group Y( :Type ),
        Overlay( :Testers )
    ),
    Elements(
        Points( X, Y, Legend( 88 ) ),
        Line(
            X,
            Y,
            Legend( 90 ),
            Row order( 0 ),
            Summary Statistic( "Mean" )
        )
    )
);

Code Explanation:

1. Open data table.
2. Create Graph Builder object.
3. Hide control panel.
4. Set X variable.
5. Set Y variable.
6. Group X by Brand.
7. Group Y by Type.
8. Overlay by Testers.
9. Add points element.
10. Add line element with mean summary.

Example 31

Summary: Visualizes a variability chart with nested factors using Graph Builder, displaying standard deviation charts and overlaying data by 'Testers'.

Code:

// Graph Builder 4
// Open data table
dt = Open("data_table.jmp");
// Graph Builder 4
Graph Builder(
    Size( 686, 540 ),
    Variables(
        X(
            :"Time (Numeric)"n,
            Size( 0, 25 )
        ),
        Y(
            :"Rate/Baseline"n,
            Size( 0, 26 )
        ),
        Group X( :Type ),
        Group X( :Brand ),
        Group Y( :Gender ),
        Overlay( :Testers )
    ),
    Elements(
        Points( X, Y, Legend( 18 ) ),
        Line(
            X,
            Y,
            Legend( 20 ),
            Row order( 0 ),
            Summary Statistic( "Mean" )
        )
    )
);

Code Explanation:

1. Open table.
2. Create Graph Builder.
3. Set size to 686x540.
4. Define X variable: "Time (Numeric)".
5. Define Y variable: "Rate/Baseline".
6. Group X by "Type".
7. Group X by "Brand".
8. Group Y by "Gender".
9. Overlay by "Testers".
10. Add points element.
11. Add line element with mean summary statistic.

Example 32

Summary: Visualizes state-level data colored by median commodity acres planted, utilizing Graph Builder to create a map with customized legend and gradient.

Code:

// State Colored by Median Commodity Acres Planted
// Open data table
dt = Open("data_table.jmp");
// State Colored by Median Commodity Acres Planted
Graph Builder(
    Size( 466, 445 ),
    Show Control Panel( 0 ),
    Fit to Window( "Off" ),
    Variables(
        Color( :Commodity Acres Planted ),
        Shape( :State )
    ),
    Elements(
        Map Shapes(
            Legend( 5 ),
            Summary Statistic( "Median" )
        )
    ),
    SendToReport(
        Dispatch( {}, "400", ScaleBox,
            {
            Legend Model(
                5,
                Properties(
                    0,
                    {
                    gradient(
                        {
                        Color Theme(
                            "White to Blue"
                        ), Width( 12 ),
                        Scale Type(
                            "Quantile"
                        )}
                    )},
                    Item ID(
                        "Commodity Acres Planted",
                        1
                    )
                )
            )}
        ),
        Dispatch( {}, "graph title",
            TextEditBox,
            {
            Set Text(
                "State Colored by Median Commodity Acres Planted"
            )}
        )
    )
);

Code Explanation:

1. Open data table.
2. Create Graph Builder object.
3. Set graph size.
4. Hide control panel.
5. Disable fit to window.
6. Define color variable.
7. Define shape variable.
8. Add map shapes element.
9. Set summary statistic to median.
10. Customize legend and gradient.

Example 33

Summary: Visualizes the sum of commodity acres planted by year, utilizing Graph Builder to create a line chart with nested factors and displaying standard deviation charts.

Code:

// Sum Commodity Acres Planted vs. Year
// Open data table
dt = Open("data_table.jmp");
// Sum Commodity Acres Planted vs. Year
Graph Builder(
    Size( 795, 491 ),
    Show Control Panel( 0 ),
    Show Footer( 0 ),
    Fit to Window( "Off" ),
    Variables(
        X( :Year ),
        Y( :Commodity Acres Planted ),
        Overlay( :Commodity )
    ),
    Elements(
        Line(
            X,
            Y,
            Legend( 5 ),
            Smoothness( 0.5 ),
            Summary Statistic( "Sum" )
        )
    ),
    SendToReport(
        Dispatch( {}, "Year", ScaleBox,
            {Format( "Best", 12 ),
            Min( 1999.54946996466 ),
            Max( 2017.8106023844 ),
            Inc( 1 ), Minor Ticks( 1 ),
            Label Row(
                {
                Label Orientation(
                    "Perpendicular"
                ), Show Major Grid( 1 )}
            )}
        ),
        Dispatch( {},
            "Commodity Acres Planted",
            ScaleBox,
            {Min( 27975648.5662737 ),
            Max( 102822354.646192 ),
            Inc( 10000000 ),
            Minor Ticks( 1 ),
            Label Row(
                Show Major Grid( 1 )
            )}
        ),
        Dispatch( {}, "400", ScaleBox,
            {
            Legend Model(
                5,
                Properties(
                    0,
                    {Line Color( 25 ),
                    Line Width( 10 ),
                    Fill Color( 0 )},
                    Item ID( "CORN", 1 )
                ),
                Properties(
                    1,
                    {Line Color( 20 ),
                    Line Width( 10 ),
                    Fill Color( 0 )},
                    Item ID(
                        "SOYBEANS", 1
                    )
                ),
                Properties(
                    2,
                    {Line Color( 22 ),
                    Line Width( 10 ),
                    Fill Color( 0 )},
                    Item ID( "WHEAT", 1 )
                )
            )}
        ),
        Dispatch( {}, "graph title",
            TextEditBox,
            {
            Set Text(
                "Sum Commodity Acres Planted vs. Year"
            )}
        )
    )
);

Code Explanation:

1. Open table.
2. Create Graph Builder.
3. Set graph size.
4. Hide control panel.
5. Hide footer.
6. Disable fit to window.
7. Set X variable.
8. Set Y variable.
9. Set overlay variable.
10. Add line element with summary statistic.

Example 34

Summary: Visualizes Corn Belt State Commodity Acres Planted vs. Year, utilizing Graph Builder to create a line chart with nested factors and interactive local data filter for states.

Code:

// Corn Belt State Commodity Acres Planted vs. Year
// Open data table
dt = Open("data_table.jmp");
// Corn Belt State Commodity Acres Planted vs. Year
Graph Builder(
    Size( 6768, 655 ),
    Show Control Panel( 0 ),
    Legend Position( "Bottom" ),
    Show Footer( 0 ),
    Fit to Window( "Off" ),
    Variables(
        X( :Year ),
        Y( :Commodity Acres Planted ),
        Group X( :State ),
        Overlay( :Commodity )
    ),
    Elements( Line( X, Y, Legend( 3 ) ) ),
    Local Data Filter(
        Add Filter(
            columns( :State ),
            Where(
                :State == {"ILLINOIS",
                "INDIANA", "IOWA",
                "KANSAS", "MICHIGAN",
                "MINNESOTA", "MISSOURI",
                "NEBRASKA",
                "NORTH DAKOTA", "OHIO",
                "SOUTH DAKOTA",
                "WISCONSIN"}
            ),
            Display(
                :State,
                Size( 266, 375 ),
                List Display
            )
        ),
        Favorites(
            "Corn Belt"(
            Match( columns( :State ),
                Where(
                    :State == {"ILLINOIS",
                    "INDIANA", "IOWA",
                    "KANSAS", "MICHIGAN",
                    "MINNESOTA",
                    "MISSOURI",
                    "NEBRASKA",
                    "NORTH DAKOTA",
                    "OHIO",
                    "SOUTH DAKOTA",
                    "WISCONSIN"}
                )
            ))
        )
    ),
    SendToReport(
        Dispatch( {}, "Year", ScaleBox,
            {Min( 1999 ), Max( 2018 ),
            Inc( 1 ), Minor Ticks( 1 ),
            Label Row(
                Label Orientation(
                    "Vertical"
                )
            )}
        ),
        Dispatch( {},
            "Commodity Acres Planted",
            ScaleBox,
            {Min( -118184.51359196 ),
            Max( 15175925.9348052 ),
            Inc( 2000000 ),
            Minor Ticks( 1 )}
        ),
        Dispatch( {}, "400", ScaleBox,
            {
            Legend Model(
                3,
                Properties(
                    0,
                    {Line Color( 25 ),
                    Line Width( 10 ),
                    Fill Color( 0 )},
                    Item ID( "CORN", 1 )
                ),
                Properties(
                    1,
                    {Line Color( 20 ),
                    Line Width( 10 ),
                    Fill Color( 0 )},
                    Item ID(
                        "SOYBEANS", 1
                    )
                ),
                Properties(
                    2,
                    {Line Color( 22 ),
                    Line Width( 10 ),
                    Fill Color( 0 )},
                    Item ID( "WHEAT", 1 )
                )
            )}
        )
    )
);

Code Explanation:

1. Open data table.
2. Create Graph Builder window.
3. Set graph size.
4. Hide control panel.
5. Place legend at bottom.
6. Hide footer.
7. Disable fit to window.
8. Define X, Y, Group X, and Overlay variables.
9. Add line element.
10. Configure local data filter for states.

Example 35

Summary: Generates a variability chart with nested factors using operator and part configurations, displaying standard deviation charts in Graph Builder.

Code:

// Graph Builder
// Open data table
dt = Open("data_table.jmp");
// Graph Builder
Graph Builder(
    Size( 660, 500 ),
    Show Control Panel( 0 ),
    Variables(
        X( :Date ),
        Y( :Moving Average ),
        Y( :Close, Position( 1 ) )
    ),
    Elements(
        Line(
            X,
            Y( 1 ),
            Y( 2 ),
            Legend( 5 ),
            Row order( 0 ),
            Summary Statistic( "Mean" )
        ),
        Points(
            X,
            Y( 1 ),
            Y( 2 ),
            Legend( 6 )
        )
    ),
    SendToReport(
        Dispatch( {}, "Date", ScaleBox,
            {Min( 3400710353.09561 ),
            Max( 3408540290.55472 ),
            Interval( "Week" ),
            Inc( 1.65343915343915 ),
            Minor Ticks( 0 ),
            Show Minor Grid( 1 ),
            Show Minor Ticks( 0 ),
            Rotated Labels( "Angled" )}
        )
    )
);

Code Explanation:

1. Open data table.
2. Create Graph Builder window.
3. Set graph size.
4. Hide control panel.
5. Define X variable: Date.
6. Define first Y variable: Moving Average.
7. Define second Y variable: Close.
8. Add line element for both Y variables.
9. Add points element for both Y variables.
10. Configure date axis settings.

Example 36

Summary: Creates a graph builder with nested factors using operator and part configurations, displaying standard deviation charts.

Code:

// Graph Builder
// Open data table
dt = Open("data_table.jmp");
// Graph Builder
Graph Builder(
    Show Control Panel( 0 ),
    Variables(
        X( :Specific Gravity ),
        Y( :Tensile Strength ),
        Color( :Supplier )
    ),
    Elements(
        Points( X, Y, Legend( 2 ) ),
        Line Of Fit( X, Y, Legend( 4 ) )
    )
);

Code Explanation:

1. Open table.
2. Create graph builder.
3. Hide control panel.
4. Set X variable.
5. Set Y variable.
6. Set color variable.
7. Add points element.
8. Add line of fit element.
9. Display graph.

Example 37

Summary: Generates a parallel plot using Graph Builder to visualize the relationships between multiple variables, including nested factors, and applies local data filtering for interactive analysis.

Code:

// Parallel Plot
// Open data table
dt = Open("data_table.jmp");
// Parallel Plot
Graph Builder(
    Size( 856, 1402 ),
    Show Control Panel( 0 ),
    Variables(
        X( :Handedness ),
        X( :Analysis, Position( 1 ) ),
        X( :BBQ, Position( 1 ) ),
        X( :Pie, Position( 1 ) ),
        X( :Discoveries, Position( 1 ) ),
        X( :OS, Position( 1 ) ),
        X( :Age, Position( 1 ) ),
        X( :Usage, Position( 1 ) ),
        X( :Boy Band, Position( 1 ) ),
        X( :DGA, Position( 1 ) ),
        X( :Type, Position( 1 ) )
    ),
    Elements(
        Parallel(
            X( 1 ),
            X( 2 ),
            X( 3 ),
            X( 4 ),
            X( 5 ),
            X( 6 ),
            X( 7 ),
            X( 8 ),
            X( 9 ),
            X( 10 ),
            X( 11 ),
            Legend( 6 ),
            Combine Sets( 1 )
        )
    ),
    Local Data Filter(
        Add Filter(
            columns(
                :Handedness, :Analysis,
                :BBQ, :Pie, :Discoveries,
                :OS, :Age, :Usage,
                :Boy Band, :DGA, :Type
            ),
            Display(
                :Handedness,
                Size( 160, 51 ),
                "List Display"
            ),
            Display(
                :Analysis,
                Size( 160, 119 ),
                "List Display"
            ),
            Display(
                :Pie,
                Size( 160, 102 ),
                "List Display"
            ),
            Display(
                :Discoveries,
                Size( 160, 68 ),
                "List Display"
            ),
            Display(
                :OS,
                Size( 160, 68 ),
                "List Display"
            ),
            Display(
                :Age,
                Size( 0, 0 ),
                "List Display"
            ),
            Display(
                :Usage,
                Size( 0, 0 ),
                "List Display"
            ),
            Display(
                :Boy Band,
                Size( 0, 0 ),
                "List Display"
            ),
            Display(
                :DGA,
                Size( 0, 0 ),
                "List Display"
            ),
            Display(
                :Type,
                Size( 0, 0 ),
                "List Display"
            )
        )
    )
);

Code Explanation:

1. Open data table.
2. Create Graph Builder window.
3. Set window size.
4. Hide control panel.
5. Define X variables.
6. Add parallel plot element.
7. Configure legend position.
8. Combine data sets.
9. Add local data filter.
10. Configure filter displays.

Example 38

Summary: Visualizes the relationship between Analysis and Discoveries using a Mosaic element in Graph Builder, displaying cell labels by percent.

Code:

// Analysis vs. Discoveries
// Open data table
dt = Open("data_table.jmp");
// Analysis vs. Discoveries
Graph Builder(
    Size( 534, 450 ),
    Show Control Panel( 0 ),
    Variables(
        X( :Discoveries ),
        Y( :Analysis )
    ),
    Elements(
        Mosaic(
            X,
            Y,
            Legend( 18 ),
            Cell Labeling(
                "Label by Percent"
            )
        )
    )
);

Code Explanation:

1. Open table.
2. Create Graph Builder.
3. Set size to 534x450.
4. Hide control panel.
5. Define X variable.
6. Define Y variable.
7. Add Mosaic element.
8. Label cells by percent.
9. Display graph.

Example 39

Summary: Generates a Treemap visualization in Graph Builder to display the relationship between Meal and Calories, with customizable X-axis labels and frame size.

Code:

// Graph Builder: Calories by Meal
// Open data table
dt = Open("data_table.jmp");
// Graph Builder: Calories by Meal
Graph Builder(
    Show Control Panel( 0 ),
    Variables(
        X( :Meal ),
        Y( :Calories )
    ),
    Elements(
        Treemap( X, Y, Legend( 10 ) )
    ),
    SendToReport(
        Dispatch( {}, "", ScaleBox,
            {
            Label Row(
                {Automatic Font Size( 1 ),
                Label Orientation(
                    "Automatic"
                ),
                Automatic Tick Marks( 1 )
                }
            )}
        ),
        Dispatch( {}, "", ScaleBox( 2 ),
            {
            Label Row(
                {Automatic Font Size( 1 ),
                Label Orientation(
                    "Automatic"
                ),
                Automatic Tick Marks( 1 )
                }
            )}
        ),
        Dispatch( {}, "Graph Builder",
            FrameBox,
            {
            DispatchSeg(
                TreeMapSeg( 1 ),
                Frame Size( 536, 452 )
            )}
        )
    )
);

Code Explanation:

1. Open table.
2. Create Graph Builder.
3. Hide control panel.
4. Set X variable.
5. Set Y variable.
6. Add Treemap element.
7. Configure X axis labels.
8. Configure Y axis labels.
9. Set frame size.
10. Display graph.

Example 40

Summary: Visualizes calories by food category using Graph Builder, with a bar element and customized legend properties.

Code:

// Graph Builder: Calories by Food Category
// Open data table
dt = Open("data_table.jmp");
// Graph Builder: Calories by Food Category
Graph Builder(
    Size( 768, 592 ),
    Show Control Panel( 0 ),
    Variables(
        X( :Food Category ),
        Y( :Calories ),
        Color( :Calories )
    ),
    Elements(
        Bar(
            X,
            Y,
            Legend( 7 ),
            Summary Statistic( "Sum" )
        )
    ),
    SendToReport(
        Dispatch( {}, Column( 8 ),
            ScaleBox,
            {
            Label Row(
                {Automatic Font Size( 0 ),
                Automatic Tick Marks( 0 ),
                Show Major Ticks( 0 )}
            )}
        ),
        Dispatch( {}, "Calories",
            ScaleBox,
            {
            Label Row(
                Automatic Tick Marks( 0 )
            )}
        ),
        Dispatch( {}, "", ScaleBox,
            {
            Label Row(
                {Automatic Font Size( 1 ),
                Label Orientation(
                    "Automatic"
                ),
                Automatic Tick Marks( 1 )
                }
            )}
        ),
        Dispatch( {}, "", ScaleBox( 2 ),
            {
            Label Row(
                {Automatic Font Size( 1 ),
                Label Orientation(
                    "Automatic"
                ),
                Automatic Tick Marks( 1 )
                }
            )}
        ),
        Dispatch( {}, "400", ScaleBox,
            {
            Legend Model(
                7,
                Properties(
                    0,
                    {
                    gradient(
                        {
                        Color Theme(
                            "Muted Yellow to Red"
                        )}
                    )}
                )
            )}
        )
    )
);

Code Explanation:

1. Open data table.
2. Set graph size.
3. Hide control panel.
4. Define X variable.
5. Define Y variable.
6. Define color variable.
7. Add bar element.
8. Customize legend.
9. Configure scale labels.
10. Adjust legend properties.

Example 41

Summary: Visualizes a treemap chart to analyze meal categories and item names, utilizing the Graph Builder platform with nested filters.

Code:

// Graph Builder: Item Name and Meal Category
// Open data table
dt = Open("data_table.jmp");
// Graph Builder: Item Name and Meal Category
Graph Builder(
    Size( 1001, 702 ),
    Show Control Panel( 0 ),
    Variables(
        X( :Meal ),
        X( :Item Name, Position( 1 ) ),
        Color( :Meal )
    ),
    Elements(
        Treemap(
            X( 1 ),
            X( 2 ),
            Legend( 3 ),
            Layout( "Squarify" )
        )
    ),
    Local Data Filter(
        Add Filter(
            columns( :Calories, :Meal ),
            Display(
                :Meal,
                N Items( 6 )
            )
        )
    )
);

Code Explanation:

1. Open data table.
2. Create Graph Builder window.
3. Set graph size.
4. Hide control panel.
5. Define X variables.
6. Define secondary X variable.
7. Define color variable.
8. Add Treemap element.
9. Set Treemap layout.
10. Add local data filter.

Example 42

Summary: Visualizes the relationship between part, lot, and ship event using Graph Builder to create a points chart with nested factors.

Code:

// lots, parts, and shipping
// Open data table
dt = Open("data_table.jmp");
// lots, parts, and shipping
Graph Builder(
    Size( 515, 491 ),
    Show Control Panel( 0 ),
    Variables(
        X( :Part ),
        Y( :Lot ),
        Group X( :Ship event )
    ),
    Elements(
        Points( X, Y, Legend( 8 ) )
    )
);

Code Explanation:

1. Open data table.
2. Create Graph Builder.
3. Set size to 515x491.
4. Hide control panel.
5. Set X variable to Part.
6. Set Y variable to Lot.
7. Group X by Ship event.
8. Add points element.
9. Assign legend to points.

Example 43

Summary: Generates a Graph Builder visualization with nested factors, displaying points, ellipses, and a line of fit, while also overlaying by surface quality.

Code:

// Graph Builder 4
// Open data table
dt = Open("data_table.jmp");
// Graph Builder 4
Graph Builder(
    Variables(
        X( :X ),
        Y( :Y ),
        Overlay( :surface quality )
    ),
    Elements(
        Points(
            X,
            Y,
            Legend( 1 ),
            Jitter( 1 )
        ),
        Ellipse(
            X,
            Y,
            Legend( 3 ),
            Coverage( "90%" )
        ),
        Line Of Fit(
            X,
            Y,
            Legend( 4 ),
            Confidence of Fit( 1 ),
            Confidence of Prediction( 0 ),
            Degree( "Linear" ),
            Equation( 0 ),
            Root Mean Square Error( 0 ),
            R²( 0 )
        )
    ),
    SendToReport(
        Dispatch( {}, "400", ScaleBox,
            {
            Legend Model(
                1,
                Base( 0, 4, 0 ),
                Base( 1, 4, 1 ),
                Base( 2, 4, 2 ),
                Base( 3, 4, 3 )
            )}
        )
    )
);

Code Explanation:

1. Open data table.
2. Launch Graph Builder.
3. Set X variable.
4. Set Y variable.
5. Overlay by surface quality.
6. Add points element.
7. Enable jitter for points.
8. Add ellipse element.
9. Set coverage to 90%.
10. Add line of fit element.

Example 44

Summary: Visualizes a variability chart with nested factors using Graph Builder, displaying standard deviation charts and configuring box plot elements for jitter, outliers, and style.

Code:

// Graph Builder 5
// Open data table
dt = Open("data_table.jmp");
// Graph Builder 5
Graph Builder(
    Variables(
        X( :surface quality ),
        Y( :Y )
    ),
    Elements(
        Box Plot(
            X,
            Y,
            Legend( 2 ),
            Jitter( 1 ),
            Outliers( 1 ),
            Box Style( "Outlier" )
        ),
        Line(
            X,
            Y,
            Legend( 3 ),
            Row order( 0 ),
            Summary Statistic( "Mean" )
        )
    )
);

Code Explanation:

1. Open data table.
2. Launch Graph Builder.
3. Set X variable.
4. Set Y variable.
5. Add Box Plot element.
6. Configure Box Plot jitter.
7. Enable Box Plot outliers.
8. Set Box Style to "Outlier".
9. Add Line element.
10. Set Line summary statistic to "Mean".

Example 45

Summary: Generates a Graph Builder visualization with filters to analyze the relationship between color and surface quality, wrapped by Lot, using a Mosaic element. The local data filter allows for interactive selection of specific Lots and Parts.

Code:

// Graph Builder with filters
// Open data table
dt = Open("data_table.jmp");
// Graph Builder with filters
Graph Builder(
    Size( 570, 910 ),
    Variables(
        X( :color ),
        Y( :surface quality ),
        Wrap( :Lot ),
        Overlay( :Y )
    ),
    Elements(
        Mosaic(
            X,
            Y,
            Legend( 4 ),
            Vertical( 1 )
        )
    ),
    Local Data Filter(
        Location( {297, 118} ),
        Mode(
            Select( 0 ),
            Show( 1 ),
            Include( 1 )
        ),
        Add Filter(
            columns( :Lot, :Part ),
            Where( :Lot == 3 ),
            Display(
                :Lot,
                Size( 182, 160 ),
                List Display
            ),
            Display(
                :Part,
                Size( 70, 609 ),
                Check Box Display
            )
        )
    )
);

Code Explanation:

1. Open data table.
2. Create Graph Builder window.
3. Set window size.
4. Define X variable.
5. Define Y variable.
6. Wrap by Lot variable.
7. Overlay Y variable.
8. Add Mosaic element.
9. Configure Mosaic legend.
10. Add local data filter.

Example 46

Summary: Visualizes a variability chart with nested factors using operator and part configurations, displaying standard deviation charts in Graph Builder.

Code:

// Graph Builder 2
// Open data table
dt = Open("data_table.jmp");
// Graph Builder 2
Graph Builder(
    Size( 507, 444 ),
    Show Control Panel( 0 ),
    Variables(
        X( :surface quality ),
        Y( :Part )
    ),
    Elements(
        Points( X, Y, Legend( 7 ) )
    )
);

Code Explanation:

1. Open data table.
2. Launch Graph Builder.
3. Set window size.
4. Hide control panel.
5. Define X variable.
6. Define Y variable.
7. Add points element.
8. Assign legend to points.

Example 47

Summary: Visualizes a variability chart with nested factors using operator and part configurations, displaying standard deviation charts in Graph Builder 3.

Code:

// Graph Builder 3
// Open data table
dt = Open("data_table.jmp");
// Graph Builder 3
Graph Builder(
    Size( 569, 500 ),
    Variables(
        X( :surface quality ),
        Y( :Part ),
        Wrap( :Ship event )
    ),
    Elements(
        Points( X, Y, Legend( 7 ) )
    )
);

Code Explanation:

1. Open data table.
2. Create Graph Builder object.
3. Set window size.
4. Define X variable.
5. Define Y variable.
6. Define Wrap variable.
7. Add Points element.
8. Set legend for Points.

Example 48

Summary: Visualizes scores by opening weekend using Graph Builder, with points and smoother elements to display audience score and rotten tomatoes score, while coloring by theaters opening weekend.

Code:

// Graph Builder: Scores by Opening Weekend
// Open data table
dt = Open("data_table.jmp");
// Graph Builder: Scores by Opening Weekend
Graph Builder(
    Size( 534, 453 ),
    Show Control Panel( 0 ),
    Variables(
        X( :Audience Score ),
        Y( :Rotten Tomatoes Score ),
        Color( :Theaters Opening Wknd )
    ),
    Elements(
        Points( X, Y, Legend( 11 ) ),
        Smoother( X, Y, Legend( 12 ) )
    )
);

Code Explanation:

1. Open table.
2. Set size.
3. Hide control panel.
4. Define X variable.
5. Define Y variable.
6. Define color variable.
7. Add points element.
8. Add smoother element.
9. Display graph.

Example 49

Summary: Creates a Graph Builder visualization to compare the world and domestic gross by genre, utilizing nested variables and displaying standard deviation charts.

Code:

// Graph Builder: World and Domestic Gross by Genre
// Open data table
dt = Open("data_table.jmp");
// Graph Builder: World and Domestic Gross by Genre
Graph Builder(
    Variables(
        X( :Genre ),
        Y( :Domestic Gross ),
        Y(
            :Foreign Gross,
            Position( 1 )
        )
    ),
    Show control panel( 0 ),
    Elements(
        Bar(
            X,
            Y( 1 ),
            Y( 2 ),
            Legend( 2 ),
            Bar Style( "Side by side" ),
            Summary Statistic( "Mean" )
        )
    )
);

Code Explanation:

1. Open table.
2. Create graph builder.
3. Set X variable.
4. Set first Y variable.
5. Set second Y variable.
6. Hide control panel.
7. Add bar element.
8. Set bar style.
9. Use mean summary statistic.
10. Display graph.

Example 50

Summary: Visualizes a graph builder with a bar element and column switcher to analyze the relationship between movie genres and opening weekend gross, allowing for interactive exploration of additional columns.

Code:

// Graph Builder and Column Switcher
// Open data table
dt = Open("data_table.jmp");
// Graph Builder and Column Switcher
Graph Builder(
    Size( 686, 572 ),
    Variables(
        X( :Genre ),
        Y( :Opening Wknd Gross )
    ),
    Show Control Panel( 0 ),
    Elements(
        Bar(
            X,
            Y,
            Legend( 7 ),
            Bar Style( "Side by side" ),
            Summary Statistic( "Mean" )
        )
    ),
    Column Switcher(
        Opening Wknd Gross,
        {Rotten Tomatoes Score,
        Audience Score, Domestic Gross,
        Foreign Gross, World Gross,
        Production Budget, Profitability,
        Opening Wknd Gross}
    )
);

Code Explanation:

1. Open data table.
2. Create Graph Builder window.
3. Set window size.
4. Assign X variable.
5. Assign Y variable.
6. Hide control panel.
7. Add bar element.
8. Set X axis.
9. Set Y axis.
10. Configure column switcher.

Example 51

Summary: Visualizes the relationship between Highway MPG and City MPG for cars with hybrid versions using Graph Builder, including a line of fit and customized axis scales.

Code:

// Graph Builder Line of Fit
// Open data table
dt = Open("data_table.jmp");
// Graph Builder Line of Fit
Graph Builder(
    Show Control Panel( 0 ),
    Variables(
        X( :Hwy MPG ),
        Y( :City MPG ),
        Overlay( :Engine )
    ),
    Elements(
        Points( X, Y, Legend( 1 ) ),
        Line Of Fit(
            X,
            Y,
            Legend( 3 ),
            Confidence of Fit( 1 ),
            Confidence of Prediction( 0 ),
            Degree( "Linear" ),
            Root Mean Square Error( 0 )
        )
    ),
    SendToReport(
        Dispatch( {}, "Hwy MPG", ScaleBox,
            {Min( 15.6907762658174 ),
            Max( 45.7444636285837 ),
            Inc( 10 ), Minor Ticks( 0 )}
        ),
        Dispatch( {}, "City MPG",
            ScaleBox,
            {Min( 10 ),
            Max( 51.865695479371 ),
            Inc( 10 ), Minor Ticks( 0 )}
        ),
        Dispatch( {}, "graph title",
            TextEditBox,
            {
            Set Text(
                "City vs. Hwy MPG for Cars with Hybrid Versions"
            )}
        )
    )
);

Code Explanation:

1. Open data table.
2. Create Graph Builder.
3. Hide control panel.
4. Set X variable.
5. Set Y variable.
6. Add overlay variable.
7. Add points element.
8. Add line of fit element.
9. Configure line of fit options.
10. Set axis scales and title.

Example 52

Summary: Generates a Graph Builder Line Chart to visualize the relationship between Highway MPG and City MPG, with an overlay of Base data. The chart includes points and a line with mean summary statistics.

Code:

// Graph Builder Line Chart
// Open data table
dt = Open("data_table.jmp");
// Graph Builder Line Chart
Graph Builder(
    Show Control Panel( 0 ),
    Variables(
        X( :Hwy MPG ),
        Y( :City MPG ),
        Overlay( :Base )
    ),
    Elements(
        Points( X, Y, Legend( 1 ) ),
        Line(
            X,
            Y,
            Legend( 3 ),
            Row order( 0 ),
            Summary Statistic( "Mean" )
        )
    ),
    SendToReport(
        Dispatch( {}, "Graph Builder",
            FrameBox,
            {Marker Size( 3 )}
        )
    )
);

Code Explanation:

1. Open data table.
2. Initialize Graph Builder.
3. Hide control panel.
4. Set X variable.
5. Set Y variable.
6. Set overlay variable.
7. Add points element.
8. Add line element.
9. Set row order.
10. Set summary statistic.

Example 53

Summary: Generates a Graph Builder Variability Chart with nested factors, displaying standard deviation charts and customizing graph appearance.

Code:

// Graph Builder Variability Chart
// Open data table
dt = Open("data_table.jmp");
// Graph Builder Variability Chart
Graph Builder(
    Variables(
        X( :Temperature ),
        X( :Casting, Position( 1 ) ),
        Y( :Shrinkage )
    ),
    Elements(
        Points(
            X( 1 ),
            X( 2 ),
            Y,
            Legend( 1 ),
            Jitter( 1 ),
            Error Bars( "Range" ),
            Summary Statistic( "Mean" )
        ),
        Points(
            X( 1 ),
            X( 2 ),
            Y,
            Legend( 2 ),
            Jitter( 0 )
        )
    ),
    SendToReport(
        Dispatch( {}, "Temperature",
            ScaleBox,
            {
            Add Ref Line(
                3.5, "Solid",
                "Medium Light Gray"
            ), Show Major Ticks( 0 ),
            Show Minor Ticks( 0 )}
        ),
        Dispatch( {}, "400", ScaleBox,
            {
            Legend Model(
                1,
                Properties(
                    0,
                    {Marker( "Minus" ),
                    Fill Color( 0 )}
                )
            )}
        ),
        Dispatch( {}, "graph title",
            TextEditBox,
            {
            Set Text(
                "Variability Chart for Shrinkage"
            )}
        ),
        Dispatch( {}, "X title",
            TextEditBox,
            {
            Set Text(
                "Casting within Temperature"
            )}
        ),
        Dispatch( {}, "Graph Builder",
            FrameBox,
            {Marker Size( 2 ),
            DispatchSeg(
                Marker Seg( 2 ),
                {Color( "Red" )}
            )}
        )
    )
);

Code Explanation:

1. Open table.
2. Create Graph Builder.
3. Set X variables.
4. Set Y variable.
5. Add points element.
6. Configure jitter and error bars.
7. Add summary statistic.
8. Add second points element.
9. Configure legend properties.
10. Customize graph appearance.

Example 54

Summary: Visualizes a contour plot to analyze the relationship between Sepal length and Sepal width, with Species as an overlay, using Graph Builder in JMP.

Code:

// Graph Builder Contour Plot
// Open data table
dt = Open("data_table.jmp");
// Graph Builder Contour Plot
Graph Builder(
    Show Control Panel( 0 ),
    Variables(
        X( :Sepal length ),
        Y( :Sepal width ),
        Overlay( :Species )
    ),
    Elements(
        Contour(
            X,
            Y,
            Legend( 3 ),
            Number of Levels( 3 )
        ),
        Points( X, Y, Legend( 4 ) )
    ),
    SendToReport(
        Dispatch( {}, "Sepal length",
            ScaleBox,
            {Min( 4.02451368343195 ),
            Max( 8.24903846153846 ),
            Inc( 1 ), Minor Ticks( 0 )}
        ),
        Dispatch( {}, "Sepal width",
            ScaleBox,
            {Min( 1.75 ),
            Max( 5.00400457665904 ),
            Inc( 1 ), Minor Ticks( 0 )}
        ),
        Dispatch( {}, "400", LegendBox,
            {
            Legend Position(
                {0, 1, 2, -1, -1, -1}
            )}
        )
    )
);

Code Explanation:

1. Open data table;
2. Create Graph Builder window.
3. Hide control panel.
4. Set X variable: Sepal length.
5. Set Y variable: Sepal width.
6. Overlay by Species.
7. Add contour plot element.
8. Configure contour legend.
9. Set number of contour levels to 3.
10. Add points element for overlay.

Example 55

Summary: Generates a Graph Builder Violin Plot to visualize the relationship between Sepal length and Species in a data table, with a custom graph title.

Code:

// Graph Builder Violin Plot
// Open data table
dt = Open("data_table.jmp");
// Graph Builder Violin Plot
Graph Builder(
    Show Control Panel( 0 ),
    Show Legend( 0 ),
    Variables(
        X( :Sepal length ),
        Y( :Species )
    ),
    Elements(
        Contour(
            X,
            Y,
            Legend( 2 ),
            Number of Levels( 0 )
        )
    ),
    SendToReport(
        Dispatch( {}, "graph title",
            TextEditBox,
            {
            Set Text(
                "Sepal length vs. Species"
            )}
        )
    )
);

Code Explanation:

1. Open table.
2. Create Graph Builder.
3. Hide control panel.
4. Hide legend.
5. Set X variable.
6. Set Y variable.
7. Add contour element.
8. Configure contour legend.
9. Set number of levels.
10. Update graph title.

Example 56

Summary: Visualizes a box plot to compare Sepal length across different Species, utilizing Graph Builder and specifying custom legend, jitter, and outlier settings.

Code:

// Graph Builder Box Plot
// Open data table
dt = Open("data_table.jmp");
// Graph Builder Box Plot
Graph Builder(
    Show Control Panel( 0 ),
    Show Legend( 0 ),
    Variables(
        X( :Sepal length ),
        Y( :Species )
    ),
    Elements(
        Box Plot(
            X,
            Y,
            Legend( 4 ),
            Jitter( 1 ),
            Outliers( 1 ),
            Box Style( "Outlier" )
        )
    ),
    SendToReport(
        Dispatch( {}, "graph title",
            TextEditBox,
            {
            Set Text(
                "Sepal length vs. Species"
            )}
        )
    )
);

Code Explanation:

1. Open data table.
2. Create Graph Builder object.
3. Hide control panel.
4. Hide legend.
5. Set X variable.
6. Set Y variable.
7. Add box plot element.
8. Enable jitter.
9. Show outliers.
10. Set box style.

Example 57

Summary: Generates a variability chart with nested factors using operator and part configurations, displaying standard deviation charts. It opens a data table, creates a Graph Builder window, and adds various elements to visualize the data.

Code:

// Animated GIF
// Open data table
dt = Open("data_table.jmp");
// Animated GIF
Graph Builder(
    Size( 679, 654 ),
    Show Control Panel( 0 ),
    Lock Scales( 1 ),
    Variables( X( :X ), Y( :Y ) ),
    Elements(
        Points( X, Y, Legend( 3 ) ),
        Caption Box(
            X,
            Legend( 7 ),
            Y Position( "Bottom" )
        ),
        Caption Box(
            X,
            Legend( 8 ),
            Summary Statistic(
                "Std Dev"
            ),
            Y Position( "Bottom" )
        ),
        Caption Box(
            Y,
            Legend( 9 ),
            X Position( "Left" )
        ),
        Caption Box(
            Y,
            Legend( 10 ),
            X Position( "Left" )
        ),
        Line Of Fit( X, Y, Legend( 16 ) )
    ),
    Local Data Filter(
        Add Filter(
            columns( :Data Set ),
            Where(
                :Data Set == "jmpman"
            ),
            Display(
                :Data Set,
                Size( 160, 195 ),
                List Display
            )
        ),
        Animation(
            Animate Column( :Data Set )
        )
    ),
    SendToReport(
        Dispatch( {}, "x", ScaleBox,
            {Min( 0 ), Max( 95 ),
            Inc( 10 ), Minor Ticks( 1 )}
        ),
        Dispatch( {}, "y", ScaleBox,
            {Min( 0 ), Max( 95 ),
            Inc( 10 ), Minor Ticks( 1 )}
        )
    )
);

Code Explanation:

1. Open data table.
2. Create Graph Builder window.
3. Set window size.
4. Hide control panel.
5. Lock scales.
6. Define X and Y variables.
7. Add points element.
8. Add X caption box.
9. Add Y caption box.
10. Add line of fit.

Example 58

Summary: Creates a Trellis with Summaries chart using Graph Builder, displaying standard deviation charts for nested factors in an operator and part configuration.

Code:

// Trellis with Summaries
// Open data table
dt = Open("data_table.jmp");
// Trellis with Summaries
Graph Builder(
    Size( 679, 690 ),
    Show Control Panel( 0 ),
    Lock Scales( 1 ),
    Variables(
        X( :X ),
        Y( :Y ),
        Wrap( :Data Set )
    ),
    Elements(
        Points( X, Y, Legend( 3 ) ),
        Caption Box(
            X,
            Legend( 7 ),
            Y Position( "Bottom" )
        ),
        Caption Box(
            X,
            Legend( 8 ),
            Summary Statistic(
                "Std Dev"
            ),
            Y Position( "Bottom" )
        ),
        Caption Box(
            Y,
            Legend( 9 ),
            Summary Statistic(
                "Std Dev"
            ),
            X Position( "Left" )
        ),
        Caption Box(
            Y,
            Legend( 10 ),
            X Position( "Left" )
        ),
        Line Of Fit( X, Y, Legend( 16 ) )
    ),
    SendToReport(
        Dispatch( {}, "x", ScaleBox,
            {Min( 0 ), Max( 95 ),
            Inc( 10 ), Minor Ticks( 1 )}
        ),
        Dispatch( {}, "y", ScaleBox,
            {Min( 0 ), Max( 95 ),
            Inc( 10 ), Minor Ticks( 1 )}
        )
    )
);

Code Explanation:

1. Open data table.
2. Create Graph Builder window.
3. Set graph size.
4. Hide control panel.
5. Lock scales.
6. Assign X variable.
7. Assign Y variable.
8. Wrap by Data Set.
9. Add points element.
10. Add caption for X variable.
11. Add caption for X standard deviation.
12. Add caption for Y standard deviation.
13. Add caption for Y variable.
14. Add line of fit.
15. Set X axis properties.
16. Set Y axis properties.

Example 59

Summary: Generates a bar chart with graphlet to visualize variability data, featuring nested factors and standard deviation charts. It utilizes Graph Builder to create the visualization.

Code:

// Bar Chart with Graphlet
// Open data table
dt = Open("data_table.jmp");
// Bar Chart with Graphlet
Graph Builder(
    Size( 529, 466 ),
    Show Control Panel( 0 ),
    Variables(
        X( :Data Set ),
        Y( :X ),
        Y( :Y, Position( 1 ) )
    ),
    Elements(
        Bar(
            X,
            Y( 1 ),
            Y( 2 ),
            Legend( 12 ),
            Error Interval(
                "Standard Deviation"
            )
        )
    ),
    SendToReport(
        Dispatch( {}, "Graph Builder",
            FrameBox,
            {
            Set Textlet(
                Markup(
                    "<font size='12'>Showing points for data set <i>{local:_dataset}</i></font>."
                )
            ),
            Set Gridlet(
                Expunge(
                    {{Matcher( 1 )},
                    {Matcher( 2 )}}
                ),
                Reformat(
                    {{Matcher( 3 ),
                    Format(
                        "Fixed Dec",
                        80,
                        2
                    ), 80}}
                )
            ),
            Set Graphlet(
                Picture(
                    Graph Builder(
                        Show Control Panel(
                            0
                        ),
                        Show Legend( 0 ),
                        Variables(
                            X( :X ),
                            Y( :Y )
                        ),
                        Elements(
                            Points(
                                X,
                                Y,
                                Legend(
                                    1
                                )
                            ),
                            Line Of Fit(
                                X,
                                Y,
                                Legend(
                                    3
                                )
                            )
                        )
                    )
                ),
                Title(
                    "JMP Man Graphlet"
                )
            )}
        )
    )
);

Code Explanation:

1. Open data table.
2. Create Graph Builder.
3. Set graph size.
4. Hide control panel.
5. Assign variables.
6. Add bar element.
7. Configure error interval.
8. Add textlet to report.
9. Remove gridlets.
10. Add graphlet with points and line of fit.

Example 60

Summary: Generates a stacked bar chart using Graph Builder to visualize the distribution of responses across different categories, with customized scale boxes and legend properties.

Code:

// Graph Builder
// Open data table
dt = Open("data_table.jmp");
// Graph Builder
Graph Builder(
    Size( 531, 456 ),
    Show Control Panel( 0 ),
    Legend Position( "Bottom" ),
    Variables(
        X( :agree ),
        X(
            :strongly agree,
            Position( 1 )
        ),
        X(
            :"-strongly disagree"n,
            Position( 1 )
        ),
        X( :"-disagree"n, Position( 1 ) ),
        X( :"-neutral"n, Position( 1 ) ),
        X( :"+neutral"n, Position( 1 ) ),
        Y( :Question )
    ),
    Elements(
        Bar(
            X( 5 ),
            X( 4 ),
            X( 3 ),
            X( 6 ),
            X( 1 ),
            X( 2 ),
            Y,
            Legend( 4 ),
            Bar Style( "Stacked" )
        )
    ),
    SendToReport(
        Dispatch( {}, "agree", ScaleBox,
            {
            Label Row(
                Show Major Grid( 1 )
            )}
        ),
        Dispatch( {}, "question",
            ScaleBox,
            {Reversed Scale}
        ),
        Dispatch( {}, "400", ScaleBox,
            {
            Legend Model(
                4,
                Level Name(
                    1,
                    "disagree",
                    Item ID(
                        "-disagree", 1
                    )
                ),
                Level Name(
                    2,
                    "strongly disagree",
                    Item ID(
                        "-strongly disagree",
                        1
                    )
                ),
                Level Name(
                    3,
                    "neutral",
                    Item ID(
                        "+neutral", 1
                    )
                ),
                Properties(
                    0,
                    {Fill Color( 32 )},
                    Item ID(
                        "-neutral", 1
                    )
                ),
                Properties(
                    1,
                    {Fill Color( 67 )},
                    Item ID(
                        "-disagree", 1
                    )
                ),
                Properties(
                    2,
                    {Fill Color( 19 )},
                    Item ID(
                        "-strongly disagree",
                        1
                    )
                ),
                Properties(
                    3,
                    {Fill Color( 32 )},
                    Item ID(
                        "+neutral", 1
                    )
                ),
                Properties(
                    4,
                    {Fill Color( 12 )},
                    Item ID( "agree", 1 )
                ),
                Properties(
                    5,
                    {Fill Color( 52 )},
                    Item ID(
                        "strongly agree",
                        1
                    )
                )
            )}
        ),
        Dispatch( {}, "400", LegendBox,
            {
            Legend Position(
                {4, [-1, 1, 0, 2, 3, 4]}
            )}
        )
    )
);

Code Explanation:

1. Open data table.
2. Launch Graph Builder.
3. Set window size.
4. Hide control panel.
5. Place legend at bottom.
6. Assign variables for X and Y axes.
7. Create stacked bar elements.
8. Customize "agree" scale box.
9. Reverse "question" scale.
10. Configure legend properties and colors.

Example 61

Summary: Visualizes the relationship between Gender and Genre using a Graph Builder Virtual Join, with local data filtering enabled for Name. The script opens a data table, sets up the graph builder window, defines variables, adds points elements, and enables filtering.

Code:

// Graph Builder Virtual Join: Gender vs. Genre, Local Data Filter
// Open data table
dt = Open("data_table.jmp");
// Graph Builder Virtual Join: Gender vs. Genre, Local Data Filter
Graph Builder(
    Size( 517, 464 ),
    Show Control Panel( 0 ),
    Variables(
        X(
            Referenced Column(
                "Genre[Item Number]",
                Reference(
                    Column(
                        :Item Number
                    ),
                    Reference(
                        Column( :Genre )
                    )
                )
            )
        ),
        Y(
            Referenced Column(
                "Gender[Customer ID]",
                Reference(
                    Column(
                        :Customer ID
                    ),
                    Reference(
                        Column( :Gender )
                    )
                )
            )
        ),
        Color(
            Referenced Column(
                "Gender[Customer ID]",
                Reference(
                    Column(
                        :Customer ID
                    ),
                    Reference(
                        Column( :Gender )
                    )
                )
            )
        )
    ),
    Elements(
        Points( X, Y, Legend( 10 ) )
    ),
    Local Data Filter(
        Add Filter(
            columns(
                Referenced Column(
                    "Name[Item Number]",
                    Reference(
                        Column(
                            :Item Number
                        ),
                        Reference(
                            Column(
                                :Name
                            )
                        )
                    )
                )
            ),
            Display(
                Referenced Column(
                    "Name[Item Number]",
                    Reference(
                        Column(
                            :Item Number
                        ),
                        Reference(
                            Column(
                                :Name
                            )
                        )
                    )
                ),
                Size( 181, 225 ),
                List Display
            )
        )
    )
);

Code Explanation:

1. Open data table;
2. Create Graph Builder window.
3. Set window size to 517x464.
4. Hide control panel.
5. Define X variable as Genre[Item Number].
6. Define Y variable as Gender[Customer ID].
7. Set color by Gender[Customer ID].
8. Add points element.
9. Enable local data filter.
10. Add filter for Name[Item Number].

Example 62

Summary: Visualizes a line chart with nested factors using Graph Builder, displaying the mean of Latitude and Longitude variables while color-coded by Direction and sized by Army Size.

Code:

// Graph Builder Line Chart
// Open data table
dt = Open("data_table.jmp");
// Graph Builder Line Chart
Graph Builder(
    Size( 481, 190 ),
    Show Control Panel( 0 ),
    Variables(
        X( :Longitude ),
        Y( :Latitude ),
        Overlay( :Group ),
        Color( :Direction ),
        Size( :Army Size )
    ),
    Elements(
        Line(
            X,
            Y,
            Legend( 3 ),
            Row order( 1 ),
            Summary Statistic( "Mean" )
        )
    ),
    SendToReport(
        Dispatch( {}, "Longitude",
            ScaleBox,
            {Scale( "Geodesic" ),
            Min( 26.7099056603774 ),
            Max( 34.9246254178505 ),
            Inc( 2.5 ), Minor Ticks( 0 ),
            Show Major Grid( 1 )}
        ),
        Dispatch( {}, "Latitude",
            ScaleBox,
            {Scale( "Geodesic" ),
            Min( 53.7911585365854 ),
            Max( 56.140243902439 ),
            Inc( 0.5 ), Minor Ticks( 1 ),
            Show Major Grid( 1 )}
        ),
        Dispatch( {}, "400", ScaleBox,
            {
            Legend Model(
                3,
                Properties(
                    0,
                    {Line Width( 8 ),
                    Marker Size( "XXL" )}
                ),
                Properties(
                    1,
                    {Line Color( 70 )}
                ),
                Properties(
                    2,
                    {Line Color( 1 )}
                )
            )}
        ),
        Dispatch( {}, "graph title",
            TextEditBox,
            {
            Set Text(
                "Napoleon's March to Moscow"
            )}
        )
    )
);

Code Explanation:

1. Open data table.
2. Create Graph Builder.
3. Set graph size.
4. Hide control panel.
5. Define X variable.
6. Define Y variable.
7. Define overlay variable.
8. Define color variable.
9. Define size variable.
10. Add line element.

Example 63

Summary: Visualizes a stacked bar chart with nested factors using Graph Builder, displaying the total count of each factor in descending order and overlaying Serious Event data.

Code:

// Dictionary-Derived Term
// Open data table
dt = Open("data_table.jmp");
// Dictionary-Derived Term
Graph Builder(
    Size( 694, 642 ),
    Show Control Panel( 0 ),
    Variables(
        X(
            :"Dictionary-Derived Term"n,
            Order By(
                :Total Count,
                Descending,
                Order Statistic( "Mean" )
            )
        ),
        Group Y(
            Referenced Column(
                :
                Description of Planned Arm,
                Reference(
                    Column(
                        :
                        Unique Subject Identifier
                    ),
                    Reference(
                        Column(
                            :
                            Description of Planned Arm
                        )
                    )
                )
            )
        ),
        Overlay( :Serious Event )
    ),
    Elements(
        Bar(
            X,
            Legend( 43 ),
            Bar Style( "Stacked" )
        )
    )
);

Code Explanation:

1. Open data table.
2. Create Graph Builder window.
3. Set window size.
4. Hide control panel.
5. Define X variable.
6. Sort X by total count descending.
7. Define Group Y variable.
8. Use referenced column for grouping.
9. Overlay Serious Event data.
10. Add stacked bar element.

Example 64

Summary: Visualizes lab results at each study visit using Graph Builder, with nested factors and operator configurations to display standard deviation charts.

Code:

// Lab Results at Each Study Visit
// Open data table
dt = Open("data_table.jmp");
// Lab Results at Each Study Visit
Graph Builder(
    Size( 724, 534 ),
    Show Control Panel( 0 ),
    Variables(
        X(
            :Visit,
            Order By(
                :Visit Number,
                Ascending,
                Order Statistic( "Mean" )
            )
        ),
        Wrap(
            :Lab Test or Examination Name
        ),
        Overlay(
            :Reference Range Indicator
        )
    ),
    Elements(
        Bar(
            X,
            Legend( 25 ),
            Bar Style( "Stacked" )
        )
    )
);

Code Explanation:

1. Open data table.
2. Set graph size.
3. Hide control panel.
4. Define X variable.
5. Order X by visit number.
6. Wrap lab test names.
7. Overlay reference range indicator.
8. Add bar element.
9. Set legend position.
10. Use stacked bar style.

Example 65

Summary: Visualizes adverse event data by treatment and body system using a treemap element in Graph Builder, with X-axis ordered by mean and grouped by planned treatment.

Code:

// Graph Builder: Adverse Event by Treatment
// Open data table
dt = Open("data_table.jmp");
// Graph Builder: Adverse Event by Treatment
Graph Builder(
    Show Control Panel( 0 ),
    Show Legend( 0 ),
    Fit to Window( "Off" ),
    Variables(
        X(
            :
            Reported Term for the Adverse Event,
            Order By(
                Empty(),
                Descending,
                Order Statistic( "Mean" )
            )
        ),
        Group X(
            :
            Planned Treatment for Period 01
        ),
        Color(
            :Body System or Organ Class
        )
    ),
    Elements(
        Treemap(
            X,
            Legend( 1 ),
            Layout( "Squarify" )
        )
    )
);

Code Explanation:

1. Open data table.
2. Set up Graph Builder.
3. Hide control panel.
4. Hide legend.
5. Disable fit to window.
6. Define X variable.
7. Order X by mean.
8. Group X by treatment.
9. Color by body system.
10. Add treemap element.

Example 66

Summary: Generates a regular bar chart with nested factors using Graph Builder, displaying standard deviation charts and applying local data filtering.

Code:

// Regular Bar Charts
// Open data table
dt = Open("data_table.jmp");
// Regular Bar Charts
Graph Builder(
    Size( 525, 526 ),
    Show Control Panel( 0 ),
    Fit to Window( "Off" ),
    Variables(
        X(
            :Pie Type,
            Order By(
                :"Sales (K)"n,
                Descending,
                Order Statistic( "Mean" )
            )
        ),
        Y( :"Sales (K)"n ),
        Y( :Outlets ),
        Color( :Pie Type )
    ),
    Elements(
        Position( 1, 1 ),
        Bar(
            X,
            Y,
            Legend( 7 ),
            Summary Statistic( "Sum" )
        )
    ),
    Elements(
        Position( 1, 2 ),
        Bar(
            X,
            Y,
            Legend( 6 ),
            Summary Statistic( "Sum" )
        )
    ),
    Local Data Filter(
        Add Filter(
            columns( :Pair ),
            Where( :Pair == 2 )
        )
    ),
    SendToReport(
        Dispatch( {}, "400", ScaleBox,
            {
            Legend Model(
                7,
                Properties(
                    0,
                    {Fill Color( 3 )},
                    Item ID( "Apple", 1 )
                ),
                Properties(
                    1,
                    {Fill Color( 51 )},
                    Item ID(
                        "Cherry", 1
                    )
                ),
                Properties(
                    3,
                    {Fill Color( 38 )},
                    Item ID( "Peach", 1 )
                )
            )}
        )
    )
);

Code Explanation:

1. Open table.
2. Set Graph Builder size.
3. Hide control panel.
4. Disable fit to window.
5. Define X variable.
6. Define Y variables.
7. Set color variable.
8. Add first bar element.
9. Add second bar element.
10. Apply local data filter.

Example 67

Summary: Visualizes a variable width bar chart to compare sales across outlets, with pie type overlay and overlaid area style.

Code:

// Variable Width Bar Chart
// Open data table
dt = Open("data_table.jmp");
// Variable Width Bar Chart
Graph Builder(
    Size( 514, 444 ),
    Show Control Panel( 0 ),
    Fit to Window( "Off" ),
    Variables(
        X( :Outlets ),
        Y( :"Sales (K)"n ),
        Overlay( :Pie Type )
    ),
    Elements(
        Area(
            X,
            Y,
            Legend( 7 ),
            Area Style( "Overlaid" )
        )
    )
);

Code Explanation:

1. Open data table.
2. Set graph size.
3. Hide control panel.
4. Disable fit to window.
5. Define X variable.
6. Define Y variable.
7. Define overlay variable.
8. Create area element.
9. Set area style.
10. Display graph.

Example 68

Summary: Generates a Graph Builder object to visualize the relationship between three variables: std_Tmax2, std_z2, and std_Fi2. The script uses nested Y variables and displays standard deviation charts.

Code:

// Graph Builder_Tmax2_Z2_Fi2
// Open data table
dt = Open("data_table.jmp");
// Graph Builder_Tmax2_Z2_Fi2
Graph Builder(
    Size( 730, 500 ),
    Show Control Panel( 0 ),
    Variables(
        X( :Id ),
        Y( :std_Tmax2 ),
        Y( :std_z2, Position( 1 ) ),
        Y( :std_Fi2, Position( 1 ) )
    ),
    Elements(
        Points(
            X,
            Y( 1 ),
            Y( 2 ),
            Y( 3 ),
            Legend( 9 )
        ),
        Line(
            X,
            Y( 1 ),
            Y( 2 ),
            Y( 3 ),
            Legend( 11 )
        )
    ),
    SendToReport(
        Dispatch( {}, "400", ScaleBox,
            {
            Legend Model(
                9,
                Base(
                    0,
                    0,
                    0,
                    Item ID(
                        "std_Tmax2", 1
                    )
                ),
                Base(
                    1,
                    0,
                    0,
                    Item ID(
                        "std_z2", 1
                    )
                ),
                Base(
                    2,
                    0,
                    0,
                    Item ID(
                        "std_Fi2", 1
                    )
                )
            )}
        )
    )
);

Code Explanation:

1. Open data table.
2. Create Graph Builder object.
3. Set graph size.
4. Hide control panel.
5. Define X variable.
6. Define Y variables.
7. Add points element.
8. Add line element.
9. Configure legend for points.
10. Configure legend for lines.

Example 69

Summary: Generates a box plot chart using Graph Builder to visualize the relationship between popcorn yield and batch, with jittering and outliers enabled.

Code:

// Graph Builder Box Plots
// Open data table
dt = Open("data_table.jmp");
// Graph Builder Box Plots
Graph Builder(
    Show Control Panel( 0 ),
    Variables(
        X( :popcorn ),
        X( :batch, Position( 1 ) ),
        Y( :yield )
    ),
    Elements(
        Box Plot(
            X( 1 ),
            X( 2 ),
            Y,
            Legend( 2 ),
            Jitter( 1 ),
            Outliers( 1 ),
            Box Style( "Outlier" )
        )
    )
);

Code Explanation:

1. Open data table.
2. Set up Graph Builder.
3. Hide control panel.
4. Define X variables.
5. Define second X variable.
6. Define Y variable.
7. Add Box Plot element.
8. Set first X for Box Plot.
9. Set second X for Box Plot.
10. Set Y for Box Plot.

Example 70

Summary: Generates a geographic map to analyze the change in population across metropolitan statistical areas, utilizing Graph Builder and customizing various settings such as color, shape, legend, and scales.

Code:

// Graph Builder
// Open data table
dt = Open("data_table.jmp");
// Graph Builder
Graph Builder(
    Show Control Panel( 0 ),
    Variables(
        Color( :Change in Population ),
        Shape(
            :
            Metropolitan Statistical Area
        )
    ),
    Elements(
        Map Shapes(
            Legend( 2 ),
            Summary Statistic( "Mean" ),
            Show Missing Shapes( 0 )
        )
    ),
    SendToReport(
        Dispatch( {}, "", ScaleBox,
            {Min( -124.862821911553 ),
            Max( -67.2295339264016 ),
            Inc( 10 ), Minor Ticks( 0 )}
        ),
        Dispatch( {}, "", ScaleBox( 2 ),
            {Min( 14.572885454726 ),
            Max( 62.7291891822812 ),
            Inc( 10 ), Minor Ticks( 0 )}
        )
    )
);
:Metropolitan Statistical Area <<
Set Property(
    "Map Role",
    {
    Shape Name Use(
        "$SAMPLE_DATA/US-MSA-Name.jmp",
        "MSA_Name"
    )}
);

Code Explanation:

1. Open table.
2. Create Graph Builder.
3. Hide control panel.
4. Set color variable.
5. Set shape variable.
6. Add map shapes element.
7. Configure legend for map shapes.
8. Set summary statistic to mean.
9. Hide missing shapes.
10. Adjust x-axis scale.
11. Adjust y-axis scale.
12. Set map role properties.

Example 71

Summary: Visualizes a nested factors variability chart with operator and part configurations, displaying standard deviation charts using Graph Builder and Column Switcher in JMP.

Code:

// Graph Builder Map and Column Switcher
// Open data table
dt = Open("data_table.jmp");
// Graph Builder Map and Column Switcher
obj =
Graph Builder(
    Show Control Panel( 0 ),
    Lock Scales( 1 ),
    Variables(
        Color( :"1980"n ),
        Shape( :State )
    ),
    Elements(
        Map Shapes(
            Legend( 2 ),
            Summary Statistic( "Mean" ),
            Show Missing Shapes( 0 )
        )
    ),
    Column Switcher(
        "1980"n,
        {"1980"n, "1984"n, "1988"n,
        "1992"n, "1996"n, "2000"n,
        "2004"n, "2008"n, "2012"n}
    ),
    SendToReport(
        Dispatch( {}, "", ScaleBox,
            {Min( -119.9 ), Max( -75.1 ),
            Inc( 10 ), Minor Ticks( 0 )}
        ),
        Dispatch( {}, "", ScaleBox( 2 ),
            {Min( 17.7 ), Max( 58.3 ),
            Inc( 5 ), Minor Ticks( 0 )}
        ),
        Dispatch( {}, "", ScaleBox( 3 ),
            {Min( 0 ), Max( 0 ), Inc( 1 ),
            Minor Ticks( 0 )}
        ),
        Dispatch( {}, "", ScaleBox( 4 ),
            {Min( 0 ), Max( 0 ), Inc( 1 ),
            Minor Ticks( 0 )}
        ),
        Dispatch( {}, "400", ScaleBox,
            {
            Legend Model(
                2,
                Properties(
                    0,
                    {
                    Line Color(
                        -13421772
                    ),
                    gradient(
                        {
                        Color Theme(
                            "White to Blue"
                        ),
                        Label Levels(
                            [20 25 30 35
                            40 45 50 55
                            60]
                        ),
                        Label Format(
                            "Fixed Dec",
                            15, 1
                        ),
                        Reverse Gradient(
                            0
                        )}
                    )}
                )
            )}
        )
    )
);
obj << Reverse Colors( 1 );

Code Explanation:

1. Open table.
2. Create Graph Builder object.
3. Hide control panel.
4. Lock scales.
5. Set color variable.
6. Set shape variable.
7. Add map shapes element.
8. Configure map legend.
9. Set summary statistic.
10. Hide missing shapes.

Example 72

Summary: Generates a Graph Builder map with nested factors, utilizing a Column Switcher to display mean statistics for multiple years. The script also hides the control panel and disables auto stretching.

Code:

// Graph Builder Map and Column Switcher 2
// Open data table
dt = Open("data_table.jmp");
// Graph Builder Map and Column Switcher 2
Graph Builder(
    Show Control Panel( 0 ),
    Auto Stretching( 0 ),
    Variables(
        Color( :"2012 Winner"n ),
        Shape( :State )
    ),
    Elements(
        Map Shapes(
            Legend( 2 ),
            Summary Statistic( "Mean" ),
            Show Missing Shapes( 0 )
        )
    ),
    Column Switcher(
        "2012 Winner"n,
        {"1980 Winner"n, "1984 Winner"n,
        "1988 Winner"n, "1992 Winner"n,
        "1996 Winner"n, "2000 Winner"n,
        "2004 Winner"n, "2008 Winner"n,
        "2012 Winner"n}
    )
);

Code Explanation:

1. Open table.
2. Create Graph Builder.
3. Hide control panel.
4. Disable auto stretching.
5. Set color variable.
6. Set shape variable.
7. Add map shapes element.
8. Enable legend for map.
9. Use mean summary statistic.
10. Disable missing shapes.

Example 73

Summary: Generates a Graph Builder bar chart to visualize the relationship between Product Line and Profit, with Quarter as a grouping factor. The chart displays mean values for each product line in each quarter.

Code:

// Graph Builder Bar Chart
// Open data table
dt = Open("data_table.jmp");
// Graph Builder Bar Chart
Graph Builder(
    Size( 570, 481 ),
    Show Control Panel( 0 ),
    Variables(
        X( :Product Line ),
        Y( :Profit ),
        Group X( :Quarter )
    ),
    Elements(
        Bar(
            X,
            Y,
            Legend( 17 ),
            Bar Style( "Side by side" ),
            Summary Statistic( "Mean" )
        )
    ),
    SendToReport(
        Dispatch( {}, "Product Line",
            ScaleBox,
            {Show Major Ticks( 0 ),
            Show Minor Ticks( 0 ),
            Rotated Labels( "Automatic" )
            }
        )
    )
);

Code Explanation:

1. Open table.
2. Create Graph Builder.
3. Set size.
4. Hide control panel.
5. Define variables.
6. Add bar element.
7. Configure bar style.
8. Set summary statistic.
9. Adjust X-axis ticks.
10. Rotate labels automatically.

Example 74

Summary: Generates a Graph Builder Line Chart to visualize the relationship between Product Cost and Profit, with adjustable scales and gridlines.

Code:

// Graph Builder Line Chart
// Open data table
dt = Open("data_table.jmp");
// Graph Builder Line Chart
Graph Builder(
    Size( 519, 500 ),
    Variables(
        X( :Product Cost ),
        Y( :Profit )
    ),
    Elements(
        Smoother( X, Y, Legend( 16 ) )
    ),
    show control panel( 0 ),
    SendToReport(
        Dispatch( {}, "Product Cost",
            ScaleBox,
            {Min( -250 ), Max( 9500 ),
            Inc( 1000 ), Minor Ticks( 0 ),
            Show Major Grid( 1 ),
            Show Minor Ticks( 0 )}
        ),
        Dispatch( {}, "Profit", ScaleBox,
            {Min( -4500 ), Max( 4000 ),
            Inc( 1000 ), Minor Ticks( 0 ),
            Show Minor Ticks( 0 )}
        ),
        Dispatch( {}, "Graph Builder",
            FrameBox,
            {Line Width Scale( 2 )}
        )
    )
);

Code Explanation:

1. Open data table.
2. Create Graph Builder.
3. Set graph size.
4. Define X and Y variables.
5. Add Smoother element.
6. Hide control panel.
7. Adjust X axis scale.
8. Adjust Y axis scale.
9. Set major grid for X.
10. Set line width scale.

Example 75

Summary: Generates a Graph Builder line chart by quarter, displaying revenue, product cost, and profit for each product line, with mean summary statistics.

Code:

// Graph Builder Line Chart by Quarter
// Open data table
dt = Open("data_table.jmp");
// Graph Builder Line Chart by Quarter
Graph Builder(
    Show Control Panel( 0 ),
    Variables(
        X( :Quarter ),
        Y( :Revenue ),
        Y( :Product Cost, Position( 1 ) ),
        Y( :Profit, Position( 1 ) ),
        Wrap( :Product Line )
    ),
    Elements(
        Line(
            X,
            Y( 1 ),
            Y( 2 ),
            Y( 3 ),
            Legend( 6 ),
            Row order( 0 ),
            Summary Statistic( "Mean" )
        )
    )
);

Code Explanation:

1. Open data table.
2. Create Graph Builder.
3. Hide control panel.
4. Set X variable to Quarter.
5. Set Y variables: Revenue, Product Cost, Profit.
6. Position Product Cost and Profit on left.
7. Wrap by Product Line.
8. Add Line element.
9. Plot Revenue, Product Cost, Profit.
10. Use mean summary statistic.

Example 76

Summary: Generates a variability chart with nested factors using operator and part configurations, displaying standard deviation charts in Graph Builder.

Code:

// Graph Builder
// Open data table
dt = Open("data_table.jmp");
// Graph Builder
Graph Builder(
    Show Control Panel( 0 ),
    Variables(
        X( :Bar ),
        Y( :Thickness 01 ),
        Y( :Thickness 02, Position( 1 ) ),
        Y( :Thickness 03, Position( 1 ) ),
        Y( :Thickness 04, Position( 1 ) ),
        Y( :Thickness 05, Position( 1 ) ),
        Y( :Thickness 06, Position( 1 ) ),
        Y( :Thickness 07, Position( 1 ) ),
        Y( :Thickness 08, Position( 1 ) ),
        Y( :Thickness 09, Position( 1 ) ),
        Y( :Thickness 10, Position( 1 ) ),
        Y( :Thickness 11, Position( 1 ) ),
        Y( :Thickness 12, Position( 1 ) )
    ),
    Elements(
        Points(
            X,
            Y( 1 ),
            Y( 2 ),
            Y( 3 ),
            Y( 4 ),
            Y( 5 ),
            Y( 6 ),
            Y( 7 ),
            Y( 8 ),
            Y( 9 ),
            Y( 10 ),
            Y( 11 ),
            Y( 12 ),
            Legend( 6 )
        ),
        Smoother(
            X,
            Y( 1 ),
            Y( 2 ),
            Y( 3 ),
            Y( 4 ),
            Y( 5 ),
            Y( 6 ),
            Y( 7 ),
            Y( 8 ),
            Y( 9 ),
            Y( 10 ),
            Y( 11 ),
            Y( 12 ),
            Legend( 7 )
        )
    ),
    SendToReport(
        Dispatch( {}, "Bar", ScaleBox,
            {Max( 50.2399577167019 ),
            Label Row(
                Label Orientation(
                    "Vertical"
                )
            )}
        ),
        Dispatch( {}, "", ScaleBox,
            {
            Label Row(
                {Automatic Font Size( 1 ),
                Automatic Label Orientation(
                    1
                ),
                Automatic Tick Marks( 1 )
                }
            )}
        ),
        Dispatch( {}, "", ScaleBox( 2 ),
            {
            Label Row(
                {Automatic Font Size( 1 ),
                Automatic Label Orientation(
                    1
                ),
                Automatic Tick Marks( 1 )
                }
            )}
        )
    )
);

Code Explanation:

1. Open table.
2. Initialize Graph Builder.
3. Hide control panel.
4. Set X variable.
5. Set multiple Y variables.
6. Add points element.
7. Add smoother element.
8. Set X axis max.
9. Set vertical labels.
10. Adjust label settings.

Example 77

Summary: Visualizes the proportion of predicted formula values against dose levels, with treatment as an overlay, using Graph Builder in JMP.

Code:

// Graph Builder - Pred Formula Proportion vs. Dose
// Open data table
dt = Open("data_table.jmp");
// Graph Builder - Pred Formula Proportion vs. Dose
Graph Builder(
    Size( 531, 456 ),
    Show Control Panel( 0 ),
    Variables(
        X( :Dose ),
        Y( :Pred Formula Proportion ),
        Overlay( :Treatment )
    ),
    Elements(
        Points( X, Y, Legend( 12 ) ),
        Smoother( X, Y, Legend( 13 ) )
    )
);

Code Explanation:

1. Open data table.
2. Create Graph Builder window.
3. Set window size.
4. Hide control panel.
5. Define X variable.
6. Define Y variable.
7. Define overlay variable.
8. Add points element.
9. Add smoother element.
10. Display graph.

Example 78

Summary: Visualizes geographic data by creating a graph builder object with points elements and scale properties, utilizing the Graph Builder platform to display Latitude and Longitude coordinates.

Code:

// Graph Builder
// Open data table
dt = Open("data_table.jmp");
// Graph Builder
Graph Builder(
    Size( 1101, 603 ),
    Show Control Panel( 0 ),
    Variables(
        X( :Longitude ),
        Y( :Latitude )
    ),
    Elements(
        Points( X, Y, Legend( 8 ) )
    ),
    SendToReport(
        Dispatch( {}, "Longitude",
            ScaleBox,
            {Min( -232.054277061219 ),
            Max( 83.1855264296051 ),
            Inc( 50 ), Minor Ticks( 0 ),
            Label Row Nesting( 1 ),
            Label Row(
                {Automatic Font Size( 1 ),
                Label Orientation(
                    "Automatic"
                ),
                Automatic Tick Marks( 1 )
                }
            )}
        ),
        Dispatch( {}, "Latitude",
            ScaleBox,
            {Min( -76.7682759286376 ),
            Max( 90.4136942201167 ),
            Inc( 20 ), Minor Ticks( 0 ),
            Label Row Nesting( 1 ),
            Label Row(
                {Automatic Font Size( 1 ),
                Label Orientation(
                    "Automatic"
                ),
                Automatic Tick Marks( 1 )
                }
            )}
        ),
        Dispatch( {}, "Graph Builder",
            FrameBox,
            {
            Background Map(
                Images( "Simple Earth" ),
                Boundaries( "World" )
            ), Grid Line Order( 3 ),
            Reference Line Order( 4 )}
        )
    )
);

Code Explanation:

1. Open data table.
2. Create Graph Builder object.
3. Set size to 1101x603.
4. Hide control panel.
5. Assign X variable: Longitude.
6. Assign Y variable: Latitude.
7. Add points element.
8. Set Longitude scale properties.
9. Set Latitude scale properties.
10. Add background map and grid lines.

Example 79

Summary: Visualizes a street map of Sao Paulo, utilizing Graph Builder to plot points based on Longitude and Latitude coordinates.

Code:

// Street Map of Sao Paulo
// Open data table
dt = Open("data_table.jmp");
// Street Map of Sao Paulo
Graph Builder(
    Size( 707, 576 ),
    Show Control Panel( 0 ),
    Variables(
        X( :Longitude ),
        Y( :Latitude )
    ),
    Elements(
        Points( X, Y, Legend( 3 ) )
    ),
    SendToReport(
        Dispatch( {}, "Longitude",
            ScaleBox,
            {
            Format(
                "Longitude DMM",
                "PUNDIR",
                16,
                3
            ), Min( -46.6839308931116 ),
            Max( -46.6750639505795 ),
            Inc( 0.001 ),
            Minor Ticks( 0 )}
        ),
        Dispatch( {}, "Latitude",
            ScaleBox,
            {
            Format(
                "Latitude DMM",
                "PUNDIR",
                16,
                3
            ), Min( -23.5920590857893 ),
            Max( -23.5845998248049 ),
            Inc( 0.001 ),
            Minor Ticks( 0 )}
        ),
        Dispatch( {}, "Graph Builder",
            FrameBox,
            {
            Background Map(
                Images(
                    "Street Map Service"
                )
            ), Grid Line Order( 2 ),
            Reference Line Order( 3 )}
        )
    )
);

Code Explanation:

1. Open table.
2. Create Graph Builder.
3. Set size to 707x576.
4. Hide control panel.
5. Assign Longitude to X.
6. Assign Latitude to Y.
7. Add points element.
8. Format Longitude scale.
9. Set Longitude min and max.
10. Format Latitude scale.
11. Set Latitude min and max.
12. Add background map.
13. Set grid line order.
14. Set reference line order.

Example 80

Summary: Visualizes a hexagonal heatmap with hover label viewer preset to display geographic data, utilizing Graph Builder and SendToReport features in JMP.

Code:

// Hexagonal Heatmap with Hover Label Viewer Preset
// Open data table
dt = Open("data_table.jmp");
// Hexagonal Heatmap with Hover Label Viewer Preset
Graph Builder(
    Size( 534, 456 ),
    Show Control Panel( 0 ),
    Variables(
        X( :Longitude ),
        Y( :Latitude )
    ),
    Elements(
        Heatmap(
            X,
            Y,
            Legend( 4 ),
            Bin Shape( "Hexagonal" )
        )
    ),
    SendToReport(
        Dispatch( {}, "400", ScaleBox,
            {
            Legend Model(
                4,
                Properties(
                    0,
                    {
                    gradient(
                        {
                        Color Theme(
                            "White to Blue"
                        ),
                        Discrete Colors(
                            1
                        ), Width( 12 )}
                    )},
                    Item ID( "Count", 1 )
                )
            )}
        ),
        Dispatch( {}, "Graph Builder",
            FrameBox,
            {
            Set Graphlet(
                Picture(
                    Try(
                        loader =
                        If(
                            Class Exists(
                                "hllLoader"
                            ),
                            New Object(
                                "hllLoader"
                            ),
                            Include(
                                "$BUILTIN_SCRIPTS/hllib.jsl"
                            )
                        );
                        loader
                        :setDebug( 0 );
                        hlp = loader
                        :lazyLoad(
                            "hllPresets"
                        );
                        hlp
                        :launchLabel Viewer();
                    ,
                        Write(
                            "
Hover Label: Unable to launch Preset. Please verify that the Preset library is available at $BUILTIN_SCRIPTS/hllib.jsl."
                        );
                        Write(
                            Eval Insert(
                                "
Exception: ^exception_msg^"
                            )
                        );
                        Empty();
                    )
                ),
                Reapply( 1 )
            ),
            {Add Pin Annotation(
                Seg( HexSeg( 1 ) ),
                Index( 5 ),
                Index Row( 1 ),
                UniqueID( -292745627 ),
                FoundPt( {264, 212} ),
                Origin(
                    {-0.212411375325768,
                    39.3436049784777}
                ),
                Offset( {-47, 150} ),
                Tag Line( 1 )
            )}}
        )
    )
);

Code Explanation:

1. Open data table.
2. Create Graph Builder object.
3. Set size of graph.
4. Hide control panel.
5. Define X and Y variables.
6. Add heatmap element.
7. Set legend properties.
8. Configure bin shape to hexagonal.
9. Customize legend appearance.
10. Launch hover label viewer preset.

Example 81

Summary: Creates a Graph Builder map to visualize the relationship between '% Taking (2004)' and 'State' using color and shape variables, with mean summary statistics and geodesic scales on both axes.

Code:

// Graph Builder Map
// Open data table
dt = Open("data_table.jmp");
// Graph Builder Map
Graph Builder(
    Show Control Panel( 0 ),
    Variables(
        Color( :"% Taking (2004)"n ),
        Shape( :State )
    ),
    Elements(
        Map Shapes(
            Legend( 2 ),
            Summary Statistic( "Mean" ),
            Show Missing Shapes( 0 )
        )
    ),
    SendToReport(
        Dispatch( {}, "", ScaleBox,
            {Scale( "Geodesic" ),
            Min( -137.654643872302 ),
            Max( -63.2427990180921 ),
            Inc( 10 ), Minor Ticks( 0 )}
        ),
        Dispatch( {}, "", ScaleBox( 2 ),
            {Scale( "Geodesic" ),
            Min( 16.7170042692343 ),
            Max( 80.0833409028976 ),
            Inc( 10 ), Minor Ticks( 0 )}
        )
    )
);

Code Explanation:

1. Open data table.
2. Create Graph Builder.
3. Hide control panel.
4. Set color variable.
5. Set shape variable.
6. Add map shapes element.
7. Configure legend for shapes.
8. Use mean summary statistic.
9. Do not show missing shapes.
10. Adjust X-axis scale.
11. Adjust Y-axis scale.

Example 82

Summary: Generates a Graph Builder map with nested factors, utilizing a Column Switcher to display mean statistics across multiple years. The script also configures geodesic scales for both horizontal and vertical axes.

Code:

// Graph Builder Map and Column Switcher
// Open data table
dt = Open("data_table.jmp");
// Graph Builder Map and Column Switcher
Graph Builder(
    Show Control Panel( 0 ),
    Variables(
        Color( :"1992 Math"n ),
        Shape( :State )
    ),
    Elements(
        Map Shapes(
            Legend( 2 ),
            Summary Statistic( "Mean" ),
            Show Missing Shapes( 0 )
        )
    ),
    Column Switcher(
        "1992 Math"n,
        {"2004 Math"n, "2003 Math"n,
        "2002 Math"n, "2001 Math"n,
        "1999 Math"n, "1994 Math"n,
        "1997 Math"n}
    ),
    SendToReport(
        Dispatch( {}, "", ScaleBox,
            {Scale( "Geodesic" ),
            Min( -138 ), Max( -63 ),
            Inc( 10 ), Minor Ticks( 0 )}
        ),
        Dispatch( {}, "", ScaleBox( 2 ),
            {Scale( "Geodesic" ),
            Min( 16.56640625 ),
            Max( 80.43359375 ), Inc( 10 ),
            Minor Ticks( 0 )}
        )
    )
);

Code Explanation:

1. Open table.
2. Create Graph Builder.
3. Hide control panel.
4. Set color variable.
5. Set shape variable.
6. Add map shapes element.
7. Configure legend for shapes.
8. Use mean summary statistic.
9. Hide missing shapes.
10. Add column switcher.
11. Set initial column.
12. Define switchable columns.
13. Adjust horizontal scale.
14. Set geodesic scale.
15. Define horizontal min.
16. Define horizontal max.
17. Set horizontal increment.
18. Hide minor ticks horizontally.
19. Adjust vertical scale.
20. Set geodesic scale vertically.
21. Define vertical min.
22. Define vertical max.
23. Set vertical increment.
24. Hide minor ticks vertically.

Example 83

Summary: Creates a variability chart with nested factors using operator and part configurations, displaying standard deviation charts. It opens a data table, sets up a Graph Builder object, and configures various elements to visualize the data.

Code:

// Graph Builder Map
// Open data table
dt = Open("data_table.jmp");
// Graph Builder Map
Graph Builder(
    Size( 570, 534 ),
    Variables(
        Color( :"Expenditure (1997)"n ),
        Shape( :State )
    ),
    Show Control Panel( 0 ),
    Elements(
        Map Shapes(
            Legend( 2 ),
            Summary Statistic( "Mean" ),
            Show Missing Shapes( 0 )
        )
    ),
    SendToReport(
        Dispatch( {}, "", ScaleBox( 2 ),
            {Min( 17.1625267665953 ),
            Max( 57.8374732334047 ),
            Inc( 10 ), Minor Ticks( 1 )}
        ),
        Dispatch( {}, "400", ScaleBox,
            {
            Legend Model(
                2,
                Properties(
                    0,
                    {
                    gradient(
                        {
                        Color Theme(
                            "White to Green"
                        ),
                        Label Levels(
                            [3.5 4.8 6.1
                            7.4 8.7 10]
                        ),
                        Label Format(
                            "Fixed Dec",
                            15, 0
                        )}
                    )}
                )
            )}
        )
    )
);

Code Explanation:

1. Open data table.
2. Create Graph Builder object.
3. Set size to 570x534.
4. Define color variable.
5. Define shape variable.
6. Hide control panel.
7. Add map shapes element.
8. Set legend for map shapes.
9. Use mean as summary statistic.
10. Configure scale box properties.

Example 84

Summary: Visualizes the relationship between Belonging and Interest, grouped by Autonomy, using a Scatterplot with a Line of Fit and Points elements in JMP.

Code:

// Scatterplot, Belonging vs Interest grouped by Autonomy
// Open data table
dt = Open("data_table.jmp");
// Scatterplot, Belonging vs Interest grouped by Autonomy
Graph Builder(
    Size( 1478, 838 ),
    Show Control Panel( 0 ),
    Variables(
        X( :Belonging ),
        Y( :Interest ),
        Group X( :Autonomy )
    ),
    Elements(
        Line Of Fit( X, Y, Legend( 16 ) ),
        Points( X, Y, Legend( 15 ) )
    ),
    SendToReport(
        Dispatch( {}, "graph title",
            TextEditBox,
            {
            Set Text(
                "Interest vs. Belonging Grouped by Autonomy"
            )}
        ),
        Dispatch( {}, "400", LegendBox,
            {
            Legend Position(
                {16, [1, -3], 15, [0]}
            )}
        )
    )
);

Code Explanation:

1. Open data table.
2. Create Graph Builder.
3. Set graph size.
4. Hide control panel.
5. Define X variable.
6. Define Y variable.
7. Define group variable.
8. Add line of fit.
9. Add points element.
10. Set graph title.

Example 85

Summary: Visualizes age cohort counts by ethnicity using Graph Builder, with a local data filter applied to display only Hispanic and White not Hispanic ethnicities.

Code:

// Graph Builder: Age Cohort Counts by Ethnicity
// Open data table
dt = Open("data_table.jmp");
// Graph Builder: Age Cohort Counts by Ethnicity
Graph Builder(
    Size( 534, 450 ),
    Show Control Panel( 0 ),
    Variables(
        X( :Age Cohort ),
        Overlay( :Ethnicity )
    ),
    Elements( Bar( X, Legend( 5 ) ) ),
    Local Data Filter(
        Close Outline( 1 ),
        Add Filter(
            columns( :Ethnicity ),
            Where(
                :Ethnicity == {"Hispanic",
                "White not Hispanic"}
            ),
            Display(
                :Ethnicity,
                N Items( 8 )
            )
        )
    )
);

Code Explanation:

1. Open data table.
2. Create Graph Builder.
3. Set size 534x450.
4. Hide control panel.
5. Set X variable: Age Cohort.
6. Set overlay variable: Ethnicity.
7. Add bar element.
8. Add local data filter.
9. Close outline.
10. Filter Ethnicity: Hispanic, White not Hispanic.

Example 86

Summary: Generates a stacked area chart with nested factors using Graph Builder, displaying the mean market share for each operating system over time.

Code:

// Graph Builder Area Chart
// Open data table
dt = Open("data_table.jmp");
// Graph Builder Area Chart
Graph Builder(
    Show Control Panel( 0 ),
    Variables(
        X( :Year ),
        Y( :Market Share ),
        Overlay( :Operating System )
    ),
    Elements(
        Area(
            X,
            Y,
            Legend( 4 ),
            Area Style( "Stacked" ),
            Summary Statistic( "Mean" )
        )
    ),
    SendToReport(
        Dispatch( {}, "Market Share",
            ScaleBox,
            {Format( "Percent", 12, 0 )}
        ),
        Dispatch( {}, "graph title",
            TextEditBox,
            {
            Set Text(
                "SmartPhone OS Market Share"
            )}
        )
    )
);

Code Explanation:

1. Open data table.
2. Create Graph Builder.
3. Hide control panel.
4. Set X variable.
5. Set Y variable.
6. Set overlay variable.
7. Add area element.
8. Stack areas.
9. Use mean summary statistic.
10. Format Y axis as percent.
11. Set graph title.

Example 87

Summary: Generates a stacked bar chart using Graph Builder to visualize market share by year and operating system, with the mean as the summary statistic.

Code:

// Graph Builder Bar Chart
// Open data table
dt = Open("data_table.jmp");
// Graph Builder Bar Chart
Graph Builder(
    Show Control Panel( 0 ),
    Variables(
        X( :Year ),
        Y( :Market Share ),
        Overlay( :Operating System )
    ),
    Elements(
        Bar(
            X,
            Y,
            Legend( 8 ),
            Bar Style( "Stacked" ),
            Summary Statistic( "Mean" )
        )
    ),
    SendToReport(
        Dispatch( {}, "graph title",
            TextEditBox,
            {
            Set Text(
                "SmartPhone OS Market Share"
            )}
        )
    )
);

Code Explanation:

1. Open data table.
2. Create Graph Builder.
3. Hide control panel.
4. Set X variable: Year.
5. Set Y variable: Market Share.
6. Set overlay variable: Operating System.
7. Add bar element.
8. Set bar style to stacked.
9. Use mean for summary statistic.
10. Set graph title.

Example 88

Summary: Visualizes a pie chart to display the market share of different operating systems, utilizing Graph Builder with nested variables and formatting options.

Code:

// Graph Builder Pie Chart
// Open data table
dt = Open("data_table.jmp");
// Graph Builder Pie Chart
Graph Builder(
    Transform Column(
        "Market Share freq",
        Format( "Percent", 12, 0 ),
        Formula(
            Round( :Market Share * 1000 )
        )
    ),
    Size( 645, 524 ),
    Show Footer( 0 ),
    Variables(
        X( :Operating System ),
        Wrap( :Year ),
        Frequency( :Market Share freq )
    ),
    Elements( Pie( X, Legend( 6 ) ) ),
    SendToReport(
        Dispatch( {}, "graph title",
            TextEditBox,
            {
            Set Text(
                "SmartPhone OS Market Share"
            )}
        )
    )
);

Code Explanation:

1. Open data table.
2. Transform column.
3. Format as percent.
4. Apply formula.
5. Create Graph Builder.
6. Set size.
7. Hide footer.
8. Define variables.
9. Add pie chart element.
10. Set graph title.

Example 89

Summary: Visualizes smartphone OS market share over time, with operating system as an overlay, using Graph Builder and displaying the mean value for each line.

Code:

// Graph Builder Line Chart 1
// Open data table
dt = Open("data_table.jmp");
// Graph Builder Line Chart 1
Graph Builder(
    Show Control Panel( 0 ),
    Variables(
        X( :Year ),
        Y( :Market Share ),
        Overlay( :Operating System )
    ),
    Elements(
        Line(
            X,
            Y,
            Legend( 5 ),
            Row order( 0 ),
            Summary Statistic( "Mean" )
        )
    ),
    SendToReport(
        Dispatch( {}, "graph title",
            TextEditBox,
            {
            Set Text(
                "Smartphone OS Market Share"
            )}
        )
    )
);

Code Explanation:

1. Open data table.
2. Create Graph Builder.
3. Hide control panel.
4. Set X variable to Year.
5. Set Y variable to Market Share.
6. Overlay by Operating System.
7. Add line element.
8. Use mean summary statistic.
9. Set row order to 0.
10. Title graph "Smartphone OS Market Share".

Example 90

Summary: Generates a line chart with nested factors using Graph Builder, displaying the relationship between Year and Market Share for different Operating Systems.

Code:

// Graph Builder Line Chart 2
// Open data table
dt = Open("data_table.jmp");
// Graph Builder Line Chart 2
Graph Builder(
    Show Control Panel( 0 ),
    Variables(
        X( :Year ),
        Y( :Market Share ),
        Group X( :Operating System ),
        Color( :Operating System )
    ),
    Elements(
        Smoother(
            X,
            Y,
            Color,
            Legend( 13 )
        ),
        Points(
            X,
            Y,
            Color,
            Legend( 14 )
        )
    ),
    SendToReport(
        Dispatch( {}, "graph title",
            TextEditBox,
            {
            Set Text(
                "Smartphone OS Market Share"
            )}
        )
    )
);

Code Explanation:

1. Open table.
2. Set up Graph Builder.
3. Hide control panel.
4. Define X variable.
5. Define Y variable.
6. Group by X variable.
7. Color by group.
8. Add smoother element.
9. Add points element.
10. Set graph title.

Example 91

Summary: Visualizes a bar chart with two nested factors using Graph Builder, displaying the relationship between date and Humid1:PM and Humid4:PM.

Code:

// Graph Builder Bar Chart
// Open data table
dt = Open("data_table.jmp");
// Graph Builder Bar Chart
Graph Builder(
    Show Control Panel( 0 ),
    Variables(
        X( :date ),
        Y( :"Humid1:PM"n ),
        Y( :"Humid4:PM"n, Position( 1 ) )
    ),
    Elements(
        Bar(
            X,
            Y( 1 ),
            Y( 2 ),
            Legend( 1 )
        )
    )
);

Code Explanation:

1. Open data table.
2. Create Graph Builder object.
3. Hide control panel.
4. Set X variable.
5. Set first Y variable.
6. Set second Y variable.
7. Add Bar element.
8. Assign X to Bar.
9. Assign first Y to Bar.
10. Assign second Y to Bar.

Example 92

Summary: Generates a Graph Builder overlay plot to visualize two Y variables (Humid1:PM and Humid4:PM) with respect to the X variable (April), displaying points for each combination of values.

Code:

// Graph Builder Overlay Plot
// Open data table
dt = Open("data_table.jmp");
// Graph Builder Overlay Plot
Graph Builder(
    Show Control Panel( 0 ),
    Legend Position( "Bottom" ),
    Variables(
        X( :April ),
        Y( :"Humid1:PM"n ),
        Y( :"Humid4:PM"n, Position( 1 ) )
    ),
    Elements(
        Points(
            X,
            Y( 1 ),
            Y( 2 ),
            Legend( 1 )
        )
    )
);

Code Explanation:

1. Open table.
2. Create Graph Builder.
3. Hide control panel.
4. Set legend position.
5. Define X variable.
6. Define first Y variable.
7. Define second Y variable.
8. Add points element.
9. Assign X to points.
10. Assign first Y to points.

Example 93

Summary: Visualizes a bar chart to analyze the relationship between Degree and Percent, with Job Type as an overlay and Degree Type as a color variable, using Graph Builder.

Code:

// Graph Builder Bars
// Open data table
dt = Open("data_table.jmp");
// Graph Builder Bars
Graph Builder(
    Size( 570, 502 ),
    Show Control Panel( 0 ),
    Variables(
        X(
            :Degree,
            Order By(
                :Percent,
                Descending,
                Order Statistic( "Mean" )
            )
        ),
        Y( :Percent ),
        Overlay( :Job Type ),
        Color( :Degree Type )
    ),
    Elements( Bar( X, Y, Legend( 2 ) ) ),
    Local Data Filter(
        Add Filter(
            columns( :Job Type ),
            Where( :Job Type == "STEM" )
        )
    ),
    SendToReport(
        Dispatch( {}, "Percent", ScaleBox,
            {Min( 0 ), Max( 1 ),
            Inc( 0.2 ), Minor Ticks( 0 )}
        ),
        Dispatch( {}, "400", ScaleBox,
            {
            Legend Model(
                2,
                Properties(
                    0,
                    {Fill Color( 40 )},
                    Item ID( "STEM", 1 )
                ),
                Properties(
                    1,
                    {Fill Color( 9 )},
                    Item ID(
                        "Non-STEM", 1
                    )
                )
            )}
        )
    )
);

Code Explanation:

1. Open data table.
2. Launch Graph Builder.
3. Set graph size to 570x502.
4. Hide control panel.
5. Set X variable: Degree.
6. Sort Degree by Percent descending.
7. Set Y variable: Percent.
8. Overlay by Job Type.
9. Color by Degree Type.
10. Add bar element with legend.

Example 94

Summary: Visualizes a line chart with two Y variables, Moving Average and Close, using Graph Builder to display the relationship between Date and these metrics.

Code:

// Graph Builder Line Chart
// Open data table
dt = Open("data_table.jmp");
// Graph Builder Line Chart
Graph Builder(
    Size( 660, 500 ),
    Show Control Panel( 0 ),
    Variables(
        X( :Date ),
        Y( :Moving Average ),
        Y( :Close, Position( 1 ) )
    ),
    Elements(
        Line(
            X,
            Y( 1 ),
            Y( 2 ),
            Legend( 5 ),
            Row order( 0 ),
            Summary Statistic( "Mean" )
        ),
        Points(
            X,
            Y( 1 ),
            Y( 2 ),
            Legend( 6 )
        )
    ),
    SendToReport(
        Dispatch( {}, "Date", ScaleBox,
            {Min( 3400710353.09561 ),
            Max( 3408134400 ),
            Interval( "Week" ), Inc( 1 ),
            Minor Ticks( 0 ),
            Show Minor Grid( 1 ),
            Show Minor Ticks( 0 ),
            Rotated Labels( "Angled" )}
        ),
        Dispatch( {}, "400", ScaleBox,
            {
            Legend Model(
                5,
                Properties(
                    0,
                    {Line Width( 2 )}
                ),
                Properties(
                    1,
                    {Line Width( 2 )}
                )
            )}
        )
    )
);

Code Explanation:

1. Open data table.
2. Create Graph Builder object.
3. Set size to 660x500.
4. Hide control panel.
5. Define X variable as Date.
6. Define Y variables: Moving Average and Close.
7. Add Line element with two Ys.
8. Add Points element with two Ys.
9. Set date scale properties.
10. Customize legend properties.

Example 95

Summary: Visualizes stock price data using Graph Builder, creating a bar chart with multiple Y variables and adjusting date scale settings.

Code:

// Graph Builder Bar Chart 1
// Open data table
dt = Open("data_table.jmp");
// Graph Builder Bar Chart 1
Graph Builder(
    Show Control Panel( 0 ),
    Variables(
        X( :Date ),
        Y( :Close ),
        Y( :Low, Position( 1 ) ),
        Y( :High, Position( 1 ) ),
        Y( :Open, Position( 1 ) )
    ),
    Elements(
        Bar(
            X,
            Y( 1 ),
            Y( 2 ),
            Y( 3 ),
            Y( 4 ),
            Legend( 3 ),
            Bar Style( "Stock" ),
            Summary Statistic( "Mean" )
        )
    ),
    SendToReport(
        Dispatch( {}, "Date", ScaleBox,
            {Min( 3400704000 ),
            Max( 3408134400 ),
            Interval( "Week" ), Inc( 1 ),
            Minor Ticks( 0 ),
            Rotated Labels( "Automatic" )
            }
        ),
        Dispatch( {}, "graph title",
            TextEditBox,
            {
            Set Text(
                "Stock Price (Open/High/Low/Close)"
            )}
        ),
        Dispatch( {}, "Y title",
            TextEditBox,
            {Set Text( "Price" )}
        )
    )
);

Code Explanation:

1. Open data table.
2. Create Graph Builder object.
3. Hide control panel.
4. Set X variable to Date.
5. Set Y variables to Close, Low, High, Open.
6. Add Bar element.
7. Configure Bar style to "Stock".
8. Set summary statistic to Mean.
9. Adjust Date scale settings.
10. Set graph title and Y axis title.

Example 96

Summary: Generates a Graph Builder bar chart to visualize the range of stock prices over time, with mean values displayed for each week. The chart is customized with a specific date scale and titles.

Code:

// Graph Builder Bar Chart 2
// Open data table
dt = Open("data_table.jmp");
// Graph Builder Bar Chart 2
Graph Builder(
    Show Control Panel( 0 ),
    Variables(
        X( :Date ),
        Y( :Low ),
        Y( :High, Position( 1 ) )
    ),
    Elements(
        Bar(
            X,
            Y( 1 ),
            Y( 2 ),
            Legend( 3 ),
            Bar Style( "Range" ),
            Summary Statistic( "Mean" )
        )
    ),
    SendToReport(
        Dispatch( {}, "Date", ScaleBox,
            {Min( 3400704000 ),
            Max( 3408134400 ),
            Interval( "Week" ), Inc( 1 ),
            Minor Ticks( 0 ),
            Rotated Labels( "Automatic" )
            }
        ),
        Dispatch( {}, "graph title",
            TextEditBox,
            {
            Set Text(
                "Stock Price Range"
            )}
        ),
        Dispatch( {}, "Y title",
            TextEditBox,
            {Set Text( "Price" )}
        )
    )
);

Code Explanation:

1. Open data table.
2. Create Graph Builder.
3. Hide control panel.
4. Set X variable: Date.
5. Set Y variables: Low, High.
6. Add bar element.
7. Configure bar style: Range.
8. Set summary statistic: Mean.
9. Adjust date scale: Week interval.
10. Set graph title: Stock Price Range.
11. Set Y axis title: Price.

Example 97

Summary: Generates a Graph Builder Overlay Plot to visualize the high and low values of a data set over time, with customizable legend orientation and marker size.

Code:

// Graph Builder Overlay Plot
// Open data table
dt = Open("data_table.jmp");
// Graph Builder Overlay Plot
Graph Builder(
    Size( 568, 407 ),
    Show Control Panel( 0 ),
    Legend Position( "Bottom" ),
    Variables(
        X( :Date ),
        Y( :High ),
        Y( :Low, Position( 1 ) )
    ),
    Elements(
        Points(
            X,
            Y( 1 ),
            Y( 2 ),
            Legend( 1 )
        )
    ),
    SendToReport(
        Dispatch( {}, "Date", ScaleBox,
            {
            Label Row(
                Show Major Grid( 1 )
            )}
        ),
        Dispatch( {}, "Graph Builder",
            FrameBox,
            {Marker Size( 2 )}
        ),
        Dispatch( {}, "400", LegendBox,
            {Orientation( "Horizontal" ),
            Sides( "Left" )}
        )
    )
);

Code Explanation:

1. Open data table.
2. Set Graph Builder size.
3. Hide control panel.
4. Set legend position.
5. Define X variable.
6. Define first Y variable.
7. Define second Y variable.
8. Add points element.
9. Configure date scale.
10. Adjust marker size.
11. Customize legend orientation.

Example 98

Summary: Visualizes a graph builder overlay plot to display high, low, and close prices with volume data, utilizing Graph Builder's Variables and Elements features.

Code:

// Graph Builder Overlay Plot
// Open data table
dt = Open("data_table.jmp");
// Graph Builder Overlay Plot
Graph Builder(
    Show Control Panel( 0 ),
    Legend Position( "Bottom" ),
    Variables(
        X( :Date ),
        Y( :High ),
        Y( :Low, Position( 1 ) ),
        Y( :Close, Position( 1 ) ),
        Y(
            :Volume,
            Position( 1 ),
            Side( "Right" )
        )
    ),
    Elements(
        Points(
            X,
            Y( 1 ),
            Y( 2 ),
            Y( 3 ),
            Legend( 1 )
        ),
        Points( X, Y( 4 ), Legend( 5 ) )
    ),
    SendToReport(
        Dispatch( {}, "High", ScaleBox,
            {Format( "Best", 15 ),
            Min( 0 ), Max( 60 ),
            Inc( 10 ), Minor Ticks( 0 )}
        ),
        Dispatch( {}, "Volume", ScaleBox,
            {Format( "Best", 15 ),
            Min( 0 ), Max( 800000000 ),
            Inc( 100000000 ),
            Minor Ticks( 0 )}
        ),
        Dispatch( {}, "400", LegendBox,
            {Orientation( "Horizontal" ),
            Sides( "Left" )}
        )
    )
);

Code Explanation:

1. Open table.
2. Create Graph Builder.
3. Hide control panel.
4. Set legend position.
5. Define X variable.
6. Define Y variables.
7. Add points for High, Low, Close.
8. Add points for Volume.
9. Format High scale.
10. Format Volume scale.

Example 99

Summary: Generates a Graph Builder bar chart to visualize the high, low, and close values of a dataset over time, with each bar representing a year-week combination.

Code:

// Graph Builder Bar Chart
// Open data table
dt = Open("data_table.jmp");
// Graph Builder Bar Chart
Graph Builder(
    Show Control Panel( 0 ),
    Variables(
        X( :YearWeek ),
        Y( :High ),
        Y( :Low, Position( 1 ) ),
        Y( :Close, Position( 1 ) )
    ),
    Elements(
        Bar(
            X,
            Y( 1 ),
            Y( 2 ),
            Y( 3 ),
            Legend( 1 ),
            Bar Style( "Interval" ),
            Summary Statistic( "Max" )
        )
    )
);

Code Explanation:

1. Open data table.
2. Set up Graph Builder.
3. Hide control panel.
4. Assign X variable.
5. Assign first Y variable.
6. Assign second Y variable.
7. Assign third Y variable.
8. Create bar chart element.
9. Specify X for bars.
10. Specify Y1, Y2, Y3 for bars.

Example 100

Summary: Generates a variability chart with nested factors using operator and part configurations, displaying standard deviation charts for High and Volume variables.

Code:

// Graph Builder
// Open data table
dt = Open("data_table.jmp");
// Graph Builder
Graph Builder(
    Show Control Panel( 0 ),
    Legend Position( "Bottom" ),
    Variables(
        X( :Date ),
        Y( :High ),
        Y( :Low, Position( 1 ) ),
        Y( :Close, Position( 1 ) ),
        Y(
            :Volume,
            Position( 1 ),
            Side( "Right" )
        )
    ),
    Elements(
        Points(
            X,
            Y( 1 ),
            Y( 2 ),
            Y( 3 ),
            Legend( 1 )
        ),
        Points( X, Y( 4 ), Legend( 5 ) )
    ),
    SendToReport(
        Dispatch( {}, "High", ScaleBox,
            {Format( "Best", 15 ),
            Min( 0 ), Max( 60 ),
            Inc( 10 ), Minor Ticks( 0 )}
        ),
        Dispatch( {}, "Volume", ScaleBox,
            {Format( "Best", 15 ),
            Min( 0 ), Max( 800000000 ),
            Inc( 100000000 ),
            Minor Ticks( 0 )}
        ),
        Dispatch( {}, "400", LegendBox,
            {Orientation( "Horizontal" ),
            Sides( "Left" )}
        )
    )
);

Code Explanation:

1. Open table.
2. Create Graph Builder.
3. Hide control panel.
4. Set legend position.
5. Define X variable.
6. Define Y variables.
7. Add points element for first three Ys.
8. Add points element for Volume.
9. Format High scale.
10. Format Volume scale.
11. Adjust legend orientation and sides.

Example 101

Summary: Visualizes a multi-faceted graph with nested factors, using Graph Builder to display high, low, and close prices over time, along with volume data, and customizing scales and legend orientation.

Code:

// Graph Builder 2
// Open data table
dt = Open("data_table.jmp");
// Graph Builder 2
Graph Builder(
    Size( 734, 290 ),
    Show Control Panel( 0 ),
    Legend Position( "Bottom" ),
    Variables(
        X( :Date ),
        Y( :High ),
        Y( :Low, Position( 1 ) ),
        Y( :Close, Position( 1 ) ),
        Y(
            :Volume,
            Position( 1 ),
            Side( "Right" )
        )
    ),
    Elements(
        Points(
            X,
            Y( 1 ),
            Y( 2 ),
            Legend( 1 )
        ),
        Line( X, Y( 3 ), Legend( 4 ) ),
        Points( X, Y( 3 ), Legend( 1 ) ),
        Bar(
            X,
            Y( 4 ),
            Legend( 6 ),
            Bar Style( "Needle" )
        ),
        Points( X, Y( 4 ), Legend( 5 ) )
    ),
    SendToReport(
        Dispatch( {}, "Date", ScaleBox,
            {Min( 3058214400 ),
            Max( 3066163200 ),
            Interval( "Month" ), Inc( 1 ),
            Minor Ticks( 3 )}
        ),
        Dispatch( {}, "High", ScaleBox,
            {Format( "Best", 15 ),
            Min( 0 ), Max( 60 ),
            Inc( 10 ), Minor Ticks( 0 )}
        ),
        Dispatch( {}, "Volume", ScaleBox,
            {Format( "Best", 15 ),
            Min( 0 ), Max( 800000000 ),
            Inc( 100000000 ),
            Minor Ticks( 0 )}
        ),
        Dispatch( {}, "400", LegendBox,
            {Orientation( "Horizontal" ),
            Sides( "Left" ),
            Legend Position(
                {1, [3, 0], 4, [1], 1, [2
                ], 6, [3], 5, [4]}
            )}
        )
    )
);

Code Explanation:

1. Open data table.
2. Create Graph Builder.
3. Set graph size.
4. Hide control panel.
5. Set legend position.
6. Define X variable.
7. Define Y variables.
8. Add points element.
9. Add line element.
10. Customize date scale.
11. Customize high scale.
12. Customize volume scale.
13. Customize legend orientation.

Example 102

Summary: Generates a variability chart with nested factors using Graph Builder, displaying standard deviation charts and utilizing operator and part configurations.

Code:

// Graph Builder 3
// Open data table
dt = Open("data_table.jmp");
// Graph Builder 3
Graph Builder(
    Show Control Panel( 0 ),
    Variables(
        X( :YearWeek ),
        Y( :High ),
        Y( :Low, Position( 1 ) ),
        Y( :Close, Position( 1 ) )
    ),
    Elements(
        Bar(
            X,
            Y( 1 ),
            Y( 2 ),
            Y( 3 ),
            Legend( 1 ),
            Bar Style( "Interval" )
        )
    )
);

Code Explanation:

1. Open data table.
2. Create Graph Builder.
3. Hide control panel.
4. Set X variable.
5. Set first Y variable.
6. Set second Y variable.
7. Set third Y variable.
8. Add bar element.
9. Assign X axis.
10. Assign Y axes.

Example 103

Summary: Visualizes the relationship between Passenger Class, Survived status, and Sex using a Graph Builder Mosaic Plot, with customized legend colors and vertical orientation.

Code:

// Graph Builder Mosaic Plot
// Open data table
dt = Open("data_table.jmp");
// Graph Builder Mosaic Plot
Graph Builder(
    Show Control Panel( 0 ),
    Variables(
        X( :Passenger Class ),
        Y( :Survived ),
        Group X( :Sex )
    ),
    Elements(
        Mosaic(
            X,
            Y,
            Legend( 4 ),
            Vertical
        )
    ),
    SendToReport(
        Dispatch( {}, "400", ScaleBox,
            {
            Legend Model(
                4,
                Properties(
                    0,
                    {Fill Color( 72 )}
                ),
                Properties(
                    1,
                    {Fill Color( 69 )}
                )
            )}
        ),
        Dispatch( {}, "graph title",
            TextEditBox,
            {
            Set Text(
                "Survived vs. Passenger Class and Sex"
            )}
        )
    )
);

Code Explanation:

1. Open data table.
2. Create Graph Builder.
3. Hide control panel.
4. Set X variable.
5. Set Y variable.
6. Set group X variable.
7. Add Mosaic element.
8. Configure legend colors.
9. Set vertical orientation.
10. Add graph title.

Example 104

Summary: Visualizes net costs using Graph Builder, with points plotted on the x-axis and legend positioned at third position, while enabling jittering for added clarity.

Code:

// Graph Builder - Net Costs
// Open data table
dt = Open("data_table.jmp");
// Graph Builder - Net Costs
Graph Builder(
    Variables( X( :Net Cost ) ),
    Elements(
        Points(
            X,
            Legend( 3 ),
            Jitter( 1 )
        )
    )
);

Code Explanation:

1. Open data table.
2. Create Graph Builder object.
3. Set X variable to Net Cost.
4. Add Points element.
5. Assign legend to third position.
6. Enable jittering for points.

Example 105

Summary: Visualizes the relationship between Net Cost and Departure Day of Week, grouped by Class of Service, with Airline as an overlay, using Graph Builder in JMP.

Code:

// Graph Builder - Root Cause
// Open data table
dt = Open("data_table.jmp");
// Graph Builder - Root Cause
Graph Builder(
    Variables(
        X( :Net Cost ),
        Y(
            :Departure Day of Week,
            Size( 74 )
        ),
        Group Y( :Class of Service ),
        Overlay( :Airline )
    ),
    Elements(
        Points(
            X,
            Y,
            Legend( 6 ),
            Jitter( 1 )
        )
    )
);

Code Explanation:

1. Open table.
2. Assign data table to dt.
3. Launch Graph Builder.
4. Set X variable.
5. Set Y variable.
6. Adjust Y size.
7. Group Y by class.
8. Overlay by airline.
9. Add points element.
10. Enable jitter.

Example 106

Summary: Creates a Graph Builder bar chart to compare 95% confidence intervals for different treatment groups, overlayed by sex, and customizes the graph title and Y-axis label.

Code:

// Graph Builder Bar Chart 1
// Open data table
dt = Open("data_table.jmp");
// Graph Builder Bar Chart 1
Graph Builder(
    Show Control Panel( 0 ),
    Variables(
        X( :Treatment ),
        Y( :Lower 95% ),
        Y( :Upper 95%, Position( 1 ) ),
        Y( :Mean, Position( 1 ) ),
        Overlay( :Sex )
    ),
    Elements(
        Bar(
            X,
            Y( 1 ),
            Y( 2 ),
            Y( 3 ),
            Legend( 3 ),
            Bar Style( "Interval" ),
            Summary Statistic( "Mean" )
        )
    ),
    SendToReport(
        Dispatch( {}, "graph title",
            TextEditBox,
            {
            Set Text(
                "Comparing 95% Confidence Intervals"
            )}
        ),
        Dispatch( {}, "Y title",
            TextEditBox,
            {Set Text( "Measure" )}
        )
    )
);

Code Explanation:

1. Open table.
2. Create Graph Builder.
3. Hide control panel.
4. Set X variable.
5. Set Y variables.
6. Overlay by Sex.
7. Add bar element.
8. Set bar style.
9. Set summary statistic.
10. Customize graph title.

Example 107

Summary: Visualizes a bar chart with nested factors using Graph Builder, displaying 95% confidence intervals and means for each treatment group, while also overlaying sex as an additional dimension.

Code:

// Graph Builder Bar Chart 2
// Open data table
dt = Open("data_table.jmp");
// Graph Builder Bar Chart 2
Graph Builder(
    Show Control Panel( 0 ),
    Variables(
        X( :Treatment ),
        Y( :Lower 95% ),
        Y( :Upper 95%, Position( 1 ) ),
        Y( :Mean, Position( 1 ) ),
        Overlay( :Sex )
    ),
    Elements(
        Bar(
            X,
            Y( 1 ),
            Y( 2 ),
            Y( 3 ),
            Legend( 3 ),
            Bar Style( "Range" ),
            Summary Statistic( "Mean" )
        )
    ),
    SendToReport(
        Dispatch( {}, "400", ScaleBox,
            {
            Legend Model(
                3,
                Properties(
                    0,
                    {Fill Color( 35 )}
                ),
                Properties(
                    1,
                    {Line Color( 51 ),
                    Line Width( 2 )}
                ),
                Properties(
                    3,
                    {Line Color( 21 ),
                    Line Width( 2 )}
                )
            )}
        ),
        Dispatch( {}, "graph title",
            TextEditBox,
            {
            Set Text(
                "Comparing 95% Confidence Intervals"
            )}
        ),
        Dispatch( {}, "Y title",
            TextEditBox,
            {Set Text( "Measure" )}
        )
    )
);

Code Explanation:

1. Open data table.
2. Create Graph Builder object.
3. Hide control panel.
4. Define X variable.
5. Define first Y variable.
6. Define second Y variable.
7. Define third Y variable.
8. Overlay variable.
9. Add bar element.
10. Customize legend and titles.

Example 108

Summary: Generates a geographic map using Graph Builder to analyze physical activity levels across US states, with a Column Switcher allowing for the selection of additional variables. The map displays mean values and includes a background map of US states.

Code:

// Graph Builder Map and Column Switcher
// Open data table
dt = Open("data_table.jmp");
// Graph Builder Map and Column Switcher
Graph Builder(
    Show Control Panel( 0 ),
    Variables(
        Color( :Physical Activity ),
        Shape( :State )
    ),
    Elements(
        Map Shapes(
            Legend( 2 ),
            Summary Statistic( "Mean" ),
            Show Missing Shapes( 0 )
        )
    ),
    Column Switcher(
        Physical Activity,
        {Vegetable Consumption, Smokers,
        Obese, Alcohol Consumption}
    ),
    SendToReport(
        Dispatch( {}, "Graph Builder",
            FrameBox,
            {
            Background Map(
                Boundaries( "US States" )
            ), Grid Line Order( 2 ),
            Reference Line Order( 3 )}
        )
    )
);

Code Explanation:

1. Open data table;
2. Create Graph Builder.
3. Hide control panel.
4. Set color variable.
5. Set shape variable.
6. Add map shapes element.
7. Use mean for summary statistic.
8. Disable missing shapes display.
9. Add column switcher.
10. Configure background map to US states.

Example 109

Summary: Visualizes a graph builder with multiple Y variables and a column switcher, allowing for interactive exploration of relationships between Household Income and other categorical variables.

Code:

// Graph Builder Smoother and Column Switcher
// Open data table
dt = Open("data_table.jmp");
// Graph Builder Smoother and Column Switcher
Graph Builder(
    Show Control Panel( 0 ),
    Show Legend( 0 ),
    Variables(
        X( :Household Income ),
        Y( :Obese ),
        Y( :Smokers ),
        Y( :Vegetable Consumption ),
        Y( :Alcohol Consumption )
    ),
    Column Switcher(
        Household Income,
        {Household Income,
        High School Graduates,
        Gross State Product,
        College Degrees}
    )
);

Code Explanation:

1. Open table.
2. Launch Graph Builder.
3. Hide control panel.
4. Hide legend.
5. Set X variable.
6. Add Y variable.
7. Add another Y variable.
8. Add third Y variable.
9. Add fourth Y variable.
10. Configure column switcher.

Example 110

Summary: Visualizes the 2008 US presidential election results by creating a Graph Builder map sized by the number of electors, with color, size, and shape variables set accordingly.

Code:

// Graph Builder Map Sized by Number of Electors
// Open data table
dt = Open("data_table.jmp");
// Graph Builder Map Sized by Number of Electors
Graph Builder(
    Show Control Panel( 0 ),
    Variables(
        Color( :Winner ),
        Size( :Electors ),
        Shape( :State )
    ),
    Elements(
        Map Shapes(
            Legend( 2 ),
            Summary Statistic( "Mean" ),
            Show Missing Shapes( 0 )
        )
    ),
    SendToReport(
        Dispatch( {}, "400", ScaleBox,
            {
            Legend Model(
                2,
                Properties(
                    0,
                    {Line Color( 1 )}
                )
            )}
        ),
        Dispatch( {}, "graph title",
            TextEditBox,
            {
            Set Text(
                "2008 Election State Winners sized by Number of Electors"
            )}
        )
    )
);

Code Explanation:

1. Open data table.
2. Create Graph Builder.
3. Hide control panel.
4. Set color variable.
5. Set size variable.
6. Set shape variable.
7. Add map shapes element.
8. Use mean summary statistic.
9. Hide missing shapes.
10. Customize legend and title.

Example 111

Summary: Visualizes a geographic map colored by winner, utilizing Graph Builder to display mean values for each state.

Code:

// Graph Builder Map Colored by Winner
// Open data table
dt = Open("data_table.jmp");
// Graph Builder Map Colored by Winner
Graph Builder(
    Show Control Panel( 0 ),
    Variables(
        Color( :Winner ),
        Shape( :State )
    ),
    Elements(
        Map Shapes(
            Legend( 1 ),
            Summary Statistic( "Mean" ),
            Show Missing Shapes( 0 )
        )
    ),
    SendToReport(
        Dispatch( {}, "Graph Builder",
            FrameBox,
            {
            DispatchSeg(
                Shape Seg( 1 ),
                {
                Label Position(
                    6, -71.7237864795722,
                    39.3621508503462
                ),
                Label Position(
                    7, -70.904462207875,
                    36.6865045425399
                ),
                Label Position(
                    8, -73.6160837611531,
                    34.6142933830486
                ),
                Label Position(
                    9, -81.645836117976,
                    28.2177828370025
                ),
                Label Position(
                    11, -156.749736857908,
                    19.7022502849684
                ),
                Label Position(
                    18, -92.2764237926373,
                    31.0930822843219
                ),
                Label Position(
                    20, -73.7226186550729,
                    36.5851732975433
                ),
                Label Position(
                    21, -68.5974119052985,
                    42.4262022940632
                ),
                Label Position(
                    30, -71.6654917960324,
                    38.1038585889128
                ),
                Label Position(
                    39, -70.0972637554873,
                    39.8075234760288
                )}
            )}
        )
    )
);

Code Explanation:

1. Open data table.
2. Create Graph Builder.
3. Set control panel visibility.
4. Assign color variable.
5. Assign shape variable.
6. Add map shapes element.
7. Configure legend.
8. Set summary statistic.
9. Hide missing shapes.
10. Customize label positions.

Example 112

Summary: Visualizes the 2008 US Presidential Election Results by creating a geographic map colored by elector margin, utilizing Graph Builder to display mean values and customize legend properties.

Code:

// Graph Builder Map Colored by Elector Margin
// Open data table
dt = Open("data_table.jmp");
// Graph Builder Map Colored by Elector Margin
Graph Builder(
    Show Control Panel( 0 ),
    Variables(
        Color( :Elector Margin ),
        Shape( :State )
    ),
    Elements(
        Map Shapes(
            Legend( 2 ),
            Summary Statistic( "Mean" ),
            Show Missing Shapes( 0 )
        )
    ),
    SendToReport(
        Dispatch( {}, "400", ScaleBox,
            {
            Legend Model(
                2,
                Properties(
                    0,
                    {
                    gradient(
                        {
                        Label Levels(
                            [-40 -30 -20
                             -10 0 10 20
                            30 40]
                        ),
                        Label Format(
                            "Fixed Dec",
                            15, 0
                        ),
                        Reverse Colors(
                            1
                        ),
                        Reverse Scale(
                            1
                        )}
                    )}
                )
            )}
        ),
        Dispatch( {}, "400", LegendBox,
            {Set Title( "Electors" )}
        ),
        Dispatch( {}, "graph title",
            TextEditBox,
            {
            Set Text(
                "2008 US Presidential Election Results"
            )}
        )
    )
);

Code Explanation:

1. Open table.
2. Create Graph Builder object.
3. Hide control panel.
4. Set color variable.
5. Set shape variable.
6. Add map shapes element.
7. Configure legend properties.
8. Set summary statistic to mean.
9. Hide missing shapes.
10. Customize legend, scale, and title.

Example 113

Summary: Generates a Graph Builder visualization to analyze the relationship between Instrument, Operator, and Part configurations, displaying standard deviation charts for 'new Y' variable.

Code:

// Graph Builder
// Open data table
dt = Open("data_table.jmp");
// Graph Builder
Graph Builder(
    Size( 542, 485 ),
    Show Control Panel( 0 ),
    Variables(
        X( :Instrument ),
        X( :Operator, Position( 1 ) ),
        X( :Part, Position( 1 ) ),
        Y( :new Y ),
        Color( :Instrument )
    ),
    Elements(
        Points(
            X( 1 ),
            X( 2 ),
            X( 3 ),
            Y,
            Legend( 21 )
        )
    )
);

Code Explanation:

1. Open data table.
2. Create Graph Builder.
3. Set size to 542x485.
4. Hide control panel.
5. Define variables.
6. Set X-axis: Instrument.
7. Set X-axis: Operator.
8. Set X-axis: Part.
9. Set Y-axis: new Y.
10. Color by Instrument.

Example 114

Summary: Visualizes the relationship between Horizontal and Vertical variables using Graph Builder, creating a scatter plot with color-coded points.

Code:

// Vertical vs. Horizontal
// Open data table
dt = Open("data_table.jmp");
// Vertical vs. Horizontal
Graph Builder(
    Size( 532, 482 ),
    Show Control Panel( 0 ),
    Variables(
        X( :Horizontal ),
        Y( :Vertical ),
        Wrap( :Layout ),
        Color( :Y )
    ),
    Elements(
        Points( X, Y, Legend( 34 ) )
    )
);

Code Explanation:

1. Open data table.
2. Create Graph Builder window.
3. Set window size.
4. Hide control panel.
5. Assign X variable.
6. Assign Y variable.
7. Assign wrap variable.
8. Assign color variable.
9. Add points element.
10. Display graph.

Example 115

Summary: Generates a Graph Builder visualization to analyze the relationship between Moisture and Yield, with Variety as a group variable, using points and smoother elements.

Code:

// Graph Builder
// Open data table
dt = Open("data_table.jmp");
// Graph Builder
Graph Builder(
    Size( 825, 460 ),
    Show Control Panel( 0 ),
    Show Legend( 0 ),
    Variables(
        X( :Moisture ),
        Y( :Yield ),
        Group X( :Variety )
    ),
    Elements(
        Points(
            X,
            Y,
            Legend( 1 ),
            Jitter( 1 )
        ),
        Smoother( X, Y, Legend( 3 ) )
    )
);

Code Explanation:

1. Open data table.
2. Create Graph Builder window.
3. Set window size.
4. Hide control panel.
5. Hide legend.
6. Define X variable.
7. Define Y variable.
8. Define group variable.
9. Add points element.
10. Add smoother element.

Example 116

Summary: Visualizes a smoothed line graph with nested factors using Graph Builder, displaying points and a smoother overlay for height (in.) vs. weight (lb.) by sex.

Code:

// Graph Builder Smoother Line
// Open data table
dt = Open("data_table.jmp");
// Graph Builder Smoother Line
Graph Builder(
    Show Control Panel( 0 ),
    Variables(
        X( :"height (in.)"n ),
        Y( :"weight (lb.)"n ),
        Overlay( :sex )
    ),
    Elements(
        Points( X, Y, Legend( 1 ) ),
        Smoother( X, Y, Legend( 2 ) )
    )
);

Code Explanation:

1. Open data table.
2. Create Graph Builder object.
3. Hide control panel.
4. Set X variable.
5. Set Y variable.
6. Set overlay variable.
7. Add points element.
8. Add smoother element.
9. Assign legend to points.
10. Assign legend to smoother.

Example 117

Summary: Generates a Graph Builder chart with line and bar elements to visualize the relationship between age, height, and weight. It opens a data table, defines variables, and adds elements to create a nested graph.

Code:

// Graph Builder Line and Bar Charts
// Open data table
dt = Open("data_table.jmp");
// Graph Builder Line and Bar Charts
Graph Builder(
    Show Control Panel( 0 ),
    Variables(
        X( :age, Size( 15, 20 ) ),
        Y(
            :"height (in.)"n,
            Size( 38, 36 )
        ),
        Y( :"weight (lb.)"n )
    ),
    Elements(
        Position( 1, 1 ),
        Line(
            X,
            Y,
            Legend( 1 ),
            Row order( 0 ),
            Summary Statistic( "Mean" )
        )
    ),
    Elements(
        Position( 1, 2 ),
        Bar(
            X,
            Y,
            Legend( 2 ),
            Bar Style( "Side by side" ),
            Summary Statistic( "Mean" )
        )
    )
);

Code Explanation:

1. Open data table.
2. Set up Graph Builder.
3. Hide control panel.
4. Define X variable.
5. Define first Y variable.
6. Define second Y variable.
7. Add line element.
8. Set line position.
9. Add bar element.
10. Set bar position.

Example 118

Summary: Generates a Graph Builder line chart with nested factors, displaying the mean of 'height (in.)' by 'age' and 'sex', with points jittered for visualization. The script also includes a legend and sends the report to dispatch.

Code:

// Graph Builder Line Chart
// Open data table
dt = Open("data_table.jmp");
// Graph Builder Line Chart
Graph Builder(
    Show Control Panel( 0 ),
    Variables(
        X( :age ),
        Y( :"height (in.)"n ),
        Overlay( :sex )
    ),
    Elements(
        Line(
            X,
            Y,
            Legend( 3 ),
            Row order( 0 ),
            Summary Statistic( "Mean" )
        ),
        Points(
            X,
            Y,
            Legend( 4 ),
            Jitter( 1 )
        )
    ),
    SendToReport(
        Dispatch( {}, "400", ScaleBox,
            {
            Legend Model(
                4,
                Base( 0, 0, 0 ),
                Base( 1, 0, 1 ),
                Properties(
                    0,
                    {Marker( "Plus" )}
                ),
                Properties(
                    1,
                    {Marker( "Square" )}
                )
            )}
        )
    )
);

Code Explanation:

1. Open data table.
2. Create Graph Builder.
3. Hide control panel.
4. Set X variable.
5. Set Y variable.
6. Set overlay variable.
7. Add line element.
8. Configure line legend.
9. Add points element.
10. Configure points legend.

Example 119

Summary: Visualizes GDP per capita data on a geographic map, utilizing a Column Switcher to enable exploration of additional variables and a Dispatch element for customized scales and legends.

Code:

// Graph Builder Map GDP per Capita and Column Switcher
// Open data table
dt = Open("data_table.jmp");
// Graph Builder Map GDP per Capita and Column Switcher
Graph Builder(
    Size( 748, 527 ),
    Show Control Panel( 0 ),
    Variables(
        Color( :GDP per Capita ),
        Shape( :Territory )
    ),
    Elements(
        Map Shapes(
            Legend( 2 ),
            Summary Statistic( "Mean" ),
            Show Missing Shapes( 0 )
        )
    ),
    Column Switcher(
        GDP per Capita,
        {"Population (1000)"n,
        "Crude Death Rate (1000)"n,
        "Crude Birth Rate (1000)"n,
        Infant Mortality Rate,
        Infant Mortality Ranking,
        "Five-Year Mortality Rate"n,
        "Five-Year Mortality Ranking"n,
        "M/F at Birth"n, "M/F under 15"n,
        "M/F 15–30"n, "M/F over 65"n,
        "M/F Total"n, Total Median Age,
        Male Median Age,
        Female Median Age,
        Overall Life Expectancy at Birth,
        Male Life Expectancy at Birth,
        Female Life Expectancy at Birth,
        "GDP (PPP) $M"n,
        Average Years of Education of Adults,
        Years of Compulsory Education,
        HDI, HDI Ranking, Literacy Rate,
        Literacy Ranking, GER,
        Health Expenditure per Capita,
        Health Expenditure per Capita Ranking
        }
    ),
    SendToReport(
        Dispatch( {}, "", ScaleBox,
            {Min( -176.850730500657 ),
            Max( 176.850730500657 ),
            Inc( 50 ), Minor Ticks( 0 ),
            Show Major Grid( 1 )}
        ),
        Dispatch( {}, "", ScaleBox( 2 ),
            {Min( -124.399751108895 ),
            Max( 116.618058599965 ),
            Inc( 50 ), Minor Ticks( 1 ),
            Show Major Grid( 1 )}
        ),
        Dispatch( {}, "400", ScaleBox,
            {
            Legend Model(
                2,
                Properties(
                    0,
                    {
                    gradient(
                        {
                        Color Theme(
                            "White to Green"
                        )}
                    )}
                )
            )}
        )
    )
);

Code Explanation:

1. Open data table.
2. Create Graph Builder.
3. Set size to 748x527.
4. Hide control panel.
5. Set color variable to GDP per Capita.
6. Set shape variable to Territory.
7. Add Map Shapes element.
8. Configure Map Shapes legend and summary statistic.
9. Enable Column Switcher for GDP per Capita.
10. Customize report scales and legends.

Example 120

Summary: Generates a Graph Builder map to visualize the relationship between years of compulsory education and territory, using color and shape variables. The map displays mean values for each territory with standard deviation charts.

Code:

// Graph Builder Map Compulsory Education
// Open data table
dt = Open("data_table.jmp");
// Graph Builder Map Compulsory Education
Graph Builder(
    Size( 748, 534 ),
    Show Control Panel( 0 ),
    Variables(
        Color(
            :
            Years of Compulsory Education
        ),
        Shape( :Territory )
    ),
    Elements(
        Map Shapes(
            Legend( 2 ),
            Summary Statistic( "Mean" ),
            Show Missing Shapes( 0 )
        )
    ),
    SendToReport(
        Dispatch( {}, "", ScaleBox,
            {Min( -189.830027384101 ),
            Max( 189.830027384101 ),
            Inc( 50 ), Minor Ticks( 0 ),
            Show Major Grid( 1 )}
        ),
        Dispatch( {}, "", ScaleBox( 2 ),
            {Min( -135.958708732916 ),
            Max( 128.177016223987 ),
            Inc( 50 ), Minor Ticks( 1 ),
            Show Major Grid( 1 )}
        ),
        Dispatch( {}, "400", ScaleBox,
            {
            Legend Model(
                2,
                Properties(
                    0,
                    {
                    gradient(
                        {
                        Color Theme(
                            "White to Green"
                        ),
                        Label Format(
                            "Fixed Dec",
                            15, 0
                        ),
                        Reverse Colors(
                            1
                        ),
                        Reverse Scale(
                            1
                        )}
                    )}
                )
            )}
        ),
        Dispatch( {}, "400", LegendBox,
            {Set Title( "Years" )}
        ),
        Dispatch( {}, "graph title",
            TextEditBox,
            {
            Set Text(
                "Years of Compulsory Education"
            )}
        )
    )
);

Code Explanation:

1. Open data table.
2. Create Graph Builder window.
3. Set window size.
4. Hide control panel.
5. Define color variable.
6. Define shape variable.
7. Add map shapes element.
8. Set summary statistic to mean.
9. Configure x-axis scale.
10. Configure y-axis scale.

Example 121

Summary: Visualizes the crude birth rate across territories using a Graph Builder map, with customizable scales and legends.

Code:

// Graph Builder Map Crude Birth Rate
// Open data table
dt = Open("data_table.jmp");
// Graph Builder Map Crude Birth Rate
Graph Builder(
    Size( 748, 534 ),
    Show Control Panel( 0 ),
    Variables(
        Color(
            :"Crude Birth Rate (1000)"n
        ),
        Shape( :Territory )
    ),
    Elements(
        Map Shapes(
            Legend( 2 ),
            Summary Statistic( "Mean" ),
            Show Missing Shapes( 0 )
        )
    ),
    SendToReport(
        Dispatch( {}, "", ScaleBox,
            {Min( -199.036236140874 ),
            Max( 199.036236140874 ),
            Inc( 50 ), Minor Ticks( 0 ),
            Show Major Grid( 1 )}
        ),
        Dispatch( {}, "", ScaleBox( 2 ),
            {Min( -142.363619108751 ),
            Max( 134.581926599822 ),
            Inc( 50 ), Minor Ticks( 1 ),
            Show Major Grid( 1 )}
        ),
        Dispatch( {}, "400", ScaleBox,
            {
            Legend Model(
                2,
                Properties(
                    0,
                    {
                    gradient(
                        {
                        Color Theme(
                            "White to Green"
                        ),
                        Label Format(
                            "Fixed Dec",
                            15, 0
                        ),
                        Reverse Colors(
                            1
                        ),
                        Reverse Scale(
                            1
                        )}
                    )}
                )
            )}
        ),
        Dispatch( {}, "400", LegendBox,
            {
            Set Title(
                "Births per 1000"
            )}
        ),
        Dispatch( {}, "graph title",
            TextEditBox,
            {Set Text( "Birth Rate" )}
        ),
        Dispatch( {}, "X title",
            TextEditBox,
            {Set Text( "" )}
        )
    )
);

Code Explanation:

1. Open table.
2. Create Graph Builder.
3. Set size.
4. Hide control panel.
5. Define color variable.
6. Define shape variable.
7. Add map shapes element.
8. Set legend position.
9. Set summary statistic.
10. Customize scales and legends.

Example 122

Summary: Opens a data table and creates a Graph Builder window with a bar element to visualize nested factors using operator and part configurations, displaying standard deviation charts.

Code:

dt = Open("data_table.jmp");
dt << Graph Builder(
    Size( 534, 464 ),
    Show Control Panel( 0 ),
    Variables( X( :Body System or Organ Class ) ),
    Elements( Bar( X, Legend( 2 ) ) ),
    SendToReport( Dispatch( {}, "Body System or Organ Class", ScaleBox, {Label Row( Label Orientation( "Angled" ) )} ) )
);

Code Explanation:

1. Open data table;
2. Create Graph Builder window.
3. Set window size.
4. Hide control panel.
5. Assign X variable.
6. Add bar element.
7. Configure legend.
8. Send report dispatch.
9. Adjust label orientation.

Example 123

Summary: Visualizes a graph builder with nested factors, using the Graph Builder platform to create a points element and display standard deviation charts.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 534, 464 ),
    Show Control Panel( 0 ),
    Variables( X( :name ), Y( :height ), Y( :weight, Position( 1 ) ) ),
    Elements( Points( X, Y( 1 ), Y( 2 ), Legend( 4 ) ) ),
    Local Data Filter(
        Add Filter( columns( :age ), Where( :age == 14 ), Display( :age, Height( 68 ) ) ),
        Animation( Animate Column( :age ) )
    ),
    SendToReport( Dispatch( {}, "Graph Builder", OutlineBox, {Close( 1 )} ) )
);

Code Explanation:

1. Open data table.
2. Create Graph Builder window.
3. Set window size.
4. Hide control panel.
5. Define X and Y variables.
6. Add points element.
7. Add local data filter.
8. Filter by age 14.
9. Enable age animation.
10. Close legend outline box.

Example 124

Summary: Opens a data table, filters rows by age 12, excludes and hides selected rows, and then generates a heatmap using Graph Builder to visualize the relationship between age and height.

Code:

dt = Open("data_table.jmp");
myrows = dt << get rows where( :age == 12 );
dt << select rows( myrows );
dt << exclude( 1 );
dt << hide( 1 );
Graph Builder(
    Size( 422, 290 ),
    Show Control Panel( 0 ),
    Variables( X( :age ), Y( :height ) ),
    Elements( Heatmap( X, Y, Legend( 1 ) ) ),
    Local Data Filter( Width( 160 ), Add Filter( columns( :sex, :weight ), Where( :weight >= 75.68 & :weight <= 138.44 ), ) )
);

Code Explanation:

1. Open data table.
2. Select rows where age is 12.
3. Exclude selected rows.
4. Hide excluded rows.
5. Launch Graph Builder.
6. Set graph size.
7. Hide control panel.
8. Define X and Y variables.
9. Add heatmap element.
10. Add local data filter.

Example 125

Summary: Generates a bar chart to visualize the relationship between age and height, with interactive filtering capabilities for sex and weight.

Code:

dt = Open("data_table.jmp");
myrows = dt << get rows where( :age == 12 );
dt << select rows( myrows );
dt << exclude( 1 );
dt << hide( 1 );
Graph Builder(
    Size( 422, 290 ),
    Show Control Panel( 0 ),
    Variables( X( :age ), Y( :height ) ),
    Elements( Bar( X, Y, Legend( 1 ) ) ),
    Local Data Filter( Add Filter( columns( :sex, :weight ), Where( :weight >= 65.29 & :weight <= 130.21 ) ) )
);

Code Explanation:

1. Open data table.
2. Identify age 12 rows.
3. Select identified rows.
4. Exclude selected rows.
5. Hide excluded rows.
6. Create Graph Builder.
7. Set graph size.
8. Hide control panel.
9. Define X and Y variables.
10. Add bar element.

Example 126

Summary: Visualizes the height distribution of individuals named LAWRENCE using a bar chart in Graph Builder, with interactive filtering capabilities.

Code:

dt = Open("data_table.jmp");
rs = dt << get rows where( :name == "LAWRENCE" );
:name[rs] = "";
Graph Builder(
    Size( 300, 200 ),
    Show Control Panel( 0 ),
    Include Missing Categories( 1 ),
    Variables( X( :name ), Y( :height ) ),
    Elements( Bar( X, Y, Legend( 1 ) ) ),
    Local Data Filter( Add Filter( columns( :name ), Where( :name == "" ) ) )
);

Code Explanation:

1. Open data table.
2. Get rows where name is LAWRENCE.
3. Set those names to missing.
4. Create Graph Builder.
5. Set size to 300x200.
6. Hide control panel.
7. Include missing categories.
8. Set X variable to name.
9. Set Y variable to height.
10. Add bar element with legend.

Example 127

Summary: Generates a variability chart with nested factors using Graph Builder, displaying standard deviation charts and customizing legend settings.

Code:

Open("data_table.jmp");
Graph Builder(
    Show Control Panel( 0 ),
    Legend Position( "Bottom" ),
    Variables( X( :Date ), Y( :DJI High ), Y( :DJI Close, Position( 1 ) ), Y( :DJI Low, Position( 1 ) ) ),
    Elements( Bar( X, Y( 1 ), Y( 2 ), Y( 3 ), Legend( 2 ), Bar Style( "Interval" ) ) ),
    SendToReport(
        Dispatch( {}, "400", ScaleBox,
            {Legend Model(
                2,
                Properties( 1, {Marker( "Diamond" )}, Item ID( "DJI Low", 1 ) ),
                "Properties"(-1, {"", "Marker"(8)}, "Item ID"("DJI High", 1)),
                "Properties"(-1, {"", "Marker"(1)}, "Item ID"("DJI Close", 1))
            )}
        ),
        Dispatch( {}, "400", LegendBox, {Orientation( "Horizontal" ), Sides( "Left" )} )
    )
);

Code Explanation:

1. Open data table.
2. Launch Graph Builder.
3. Hide control panel.
4. Set legend position bottom.
5. Define variables for axes.
6. Add bar element with interval style.
7. Customize legend for DJI Low.
8. Customize legend for DJI High.
9. Customize legend for DJI Close.
10. Set legend orientation and sides.

Example 128

Summary: Visualizes a variability chart with nested factors using operator and part configurations, displaying standard deviation charts in Graph Builder.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 534, 404 ),
    Show Control Panel( 0 ),
    Include Missing Categories( 1 ),
    Variables( X( :Time Cycles ), Y( :Censor ) ),
    Elements( Points( X, Y, Legend( 3 ) ), Smoother( X, Y, Legend( 4 ) ) ),
    SendToReport( Dispatch( {}, "Censor", ScaleBox, {Min( -0.25 ), Max( 1.25 ), Inc( 1 ), Minor Ticks( 0 )} ) )
);

Code Explanation:

1. Open data table;
2. Launch Graph Builder.
3. Set graph size.
4. Hide control panel.
5. Include missing categories.
6. Define X and Y variables.
7. Add points element.
8. Add smoother element.
9. Configure X-axis minimum.
10. Configure X-axis maximum.
11. Set X-axis increment.
12. Disable minor ticks.

Example 129

Summary: Generates a heatmap visualization of high and low values over time, utilizing the Graph Builder platform in JMP. The script configures the date axis with specific intervals and minor ticks.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 388, 291 ),
    Show Control Panel( 0 ),
    Show Legend( 0 ),
    Legend Position( "Bottom" ),
    Variables( X( :Date ), Y( :High ), Y( :Low, Position( 1 ) ) ),
    Elements( Heatmap( X, Y( 1 ), Y( 2 ), Legend( 3 ) ) ),
    SendToReport(
        Dispatch( {}, "Date", ScaleBox,
            {Min( 3400310610 ), Max( 3410633520 ), Interval( "Day" ), Inc( 30 ), Minor Ticks( 0 ), Label Row( Show Major Grid( 1 ) )}
        ),
        Dispatch( {}, "Graph Builder", FrameBox, {Marker Size( 2 )} )
    )
);

Code Explanation:

1. Open data table.
2. Launch Graph Builder.
3. Set window size.
4. Hide control panel.
5. Hide legend.
6. Position legend bottom.
7. Define X and Y variables.
8. Add heatmap element.
9. Configure date axis.
10. Adjust marker size.

Example 130

Summary: Creates a Graph Builder window to visualize the relationship between height and weight, using log scales for both axes and displaying standard deviation charts.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 280, 219 ),
    Show Control Panel( 0 ),
    Variables( X( :height ), Y( :weight ) ),
    Elements( Points( X, Y, Legend( 2 ) ), Smoother( X, Y, Legend( 3 ) ) ),
    SendToReport(
        Dispatch( {}, "height", ScaleBox, {Scale( "Log" ), Format( "Best", 6 ), Min( 1 ), Max( 111 ), Inc( 1 ), Minor Ticks( 1 )} ),
        Dispatch( {}, "weight", ScaleBox, {Scale( "Log" ), Format( "Best", 6 ), Min( 1 ), Max( 200 ), Inc( 1 ), Minor Ticks( 1 )} )
    )
);

Code Explanation:

1. Open data table;
2. Create Graph Builder window.
3. Set window size.
4. Hide control panel.
5. Define X and Y variables.
6. Add points element.
7. Add smoother element.
8. Log scale X axis.
9. Log scale Y axis.
10. Enable minor ticks.

Example 131

Summary: Visualizes the relationship between 'sex' and 'height' using a Graph Builder, with interactive features like legend and scale customization.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 368, 245 ),
    Show Control Panel( 0 ),
    Variables( X( :sex ), Y( :height ) ),
    Elements( Points( X, Y, Legend( 3 ) ) ),
    SendToReport(
        Dispatch( {}, "height", ScaleBox,
            {Scale( "Power", {Power( 3 )} ), Format( "Best", 12 ), Min( 47 ), Max( 71 ), Inc( 250 ), Minor Ticks( 1 )}
        )
    )
);

Code Explanation:

1. Open data table;
2. Create Graph Builder window.
3. Set graph size.
4. Hide control panel.
5. Define X and Y variables.
6. Add points element.
7. Send report settings.
8. Dispatch to height scale box.
9. Set scale to power.
10. Set power value.

Example 132

Summary: Creates a graph builder object to visualize the relationship between height and weight, with points and smoother elements, and changes the scale of the second axis box to log.

Code:

Open("data_table.jmp");
gb = Graph Builder( Variables( X( :height ), Y( :weight ) ), Elements( Points( X, Y, Legend( 2 ) ), Smoother( X, Y, Legend( 3 ) ) ) );
rgb = gb << report;
axisbox = rgb[axis box( 2 )];
axisbox << Scale( "Log" );

Code Explanation:

1. Open data table;
2. Create Graph Builder object.
3. Set X variable to height.
4. Set Y variable to weight.
5. Add points element.
6. Add smoother element.
7. Retrieve graph report.
8. Access second axis box.
9. Change scale to log.

Example 133

Summary: Generates a variability chart with nested factors using operator and part configurations, displaying standard deviation charts.

Code:

Open("data_table.jmp");
gb = Graph Builder( Variables( X( :height ), Y( :weight ) ), Elements( Points( X, Y, Legend( 2 ) ), Smoother( X, Y, Legend( 3 ) ) ) );
rgb = gb << report;
axisbox = rgb[axis box( 2 )];
axisbox << Scale( "Log" );
Data Table("data_table") << Clear Select << Select Rows(
    [2, 4, 7, 10, 12, 13, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 37, 38, 39, 40]
) << Hide and Exclude;

Code Explanation:

1. Open data table.
2. Create graph builder object.
3. Set X and Y variables.
4. Add points and smoother elements.
5. Retrieve graph report.
6. Access second axis box.
7. Change axis scale to log.
8. Clear previous selections.
9. Select specified rows.
10. Hide and exclude selected rows.

Example 134

Summary: Generates two variability charts with nested factors using Graph Builder, displaying standard deviation charts and setting label orientations to angled and vertical.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 317, 332 ),
    Show Control Panel( 0 ),
    Show Legend( 0 ),
    Variables( X( :Airline ) ),
    Elements( Bar( X, Legend( 2 ) ) ),
    SendToReport( Dispatch( {}, "Airline", ScaleBox, {Label Row( Label Orientation( "Angled" ) )} ) )
);
Graph Builder(
    Size( 264, 331 ),
    Show Control Panel( 0 ),
    Show Legend( 0 ),
    Variables( X( :Airline ) ),
    Elements( Bar( X, Legend( 2 ) ) ),
    SendToReport( Dispatch( {}, "Airline", ScaleBox, {Label Row( Label Orientation( "Vertical" ) )} ) )
);

Code Explanation:

1. Open data table.
2. Create first Graph Builder.
3. Set graph size.
4. Hide control panel.
5. Hide legend.
6. Set X variable.
7. Add bar element.
8. Set label orientation to angled.
9. Create second Graph Builder.
10. Set label orientation to vertical.

Example 135

Summary: Visualizes a bar chart with nested factors using Graph Builder, displaying the Airline variable on the x-axis and hiding the control panel and legend.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 264, 331 ),
    Show Control Panel( 0 ),
    Show Legend( 0 ),
    Variables( X( :Airline ) ),
    Elements( Bar( X, Legend( 2 ) ) ),
    SendToReport( Dispatch( {}, "Airline", ScaleBox, {Label Row( Label Orientation( "Vertical" ) )} ) )
);

Code Explanation:

1. Open data table;
2. Create Graph Builder window.
3. Set window size.
4. Hide control panel.
5. Hide legend.
6. Set X variable to Airline.
7. Add bar element.
8. Assign legend to bar.
9. Adjust label orientation.
10. Set labels to vertical.

Example 136

Summary: Generates a variability chart with nested factors using operator and part configurations, displaying standard deviation charts across multiple Graph Builder windows.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 522, 452 ),
    Show Control Panel( 0 ),
    Variables( X( Transform Column( "Log10[height]", Formula( Log10( :height ) ) ) ), Y( :height ) ),
    Elements( Bar( X, Y, Legend( 10 ) ) ),
    SendToReport(
        Dispatch( {}, "Log10[height]", ScaleBox,
            {Scale( "Log" ), Format( "Best", 6 ), Min( 1.70228756025304 ), Max( 2 ), Inc( 1 ), Minor Ticks( 1 )}
        )
    )
);
Graph Builder(
    Size( 522, 452 ),
    Show Control Panel( 0 ),
    Variables( X( Transform Column( "Log10[height]", Formula( Log10( :height ) ) ) ), Y( :height ) ),
    Elements( Bar( X, Y, Legend( 10 ) ) ),
    SendToReport(
        Dispatch( {}, "Log10[height]", ScaleBox,
            {Scale( "Power" ), Format( "Best", 10 ), Min( 1.7 ), Max( 1.85103291815671 ), Inc( 0.05 ), Minor Ticks( 1 )}
        )
    )
);

Graph Builder(
    Size( 522, 452 ),
    Show Control Panel( 0 ),
    Variables( X( Transform Column( "Log10[height]", Formula( Log10( :height ) ) ) ), Y( :height ) ),
    Elements( Box Plot( X, Y, Legend( 10 ) ) ),
    SendToReport(
        Dispatch( {}, "Log10[height]", ScaleBox,
            {Scale( "Log" ), Format( "Best", 6 ), Min( 1.70228756025304 ), Max( 2 ), Inc( 1 ), Minor Ticks( 1 )}
        )
    )
);
Graph Builder(
    Size( 522, 452 ),
    Show Control Panel( 0 ),
    Variables( X( Transform Column( "Log10[height]", Formula( Log10( :height ) ) ) ), Y( :height ) ),
    Elements( Box Plot( X, Y, Legend( 10 ) ) ),
    SendToReport(
        Dispatch( {}, "Log10[height]", ScaleBox,
            {Scale( "Power" ), Format( "Best", 10 ), Min( 1.7 ), Max( 1.84871699755653 ), Inc( 0.02 ), Minor Ticks( 0 )}
        )
    )
);

Code Explanation:

1. Open data table.
2. Create first Graph Builder window.
3. Set window size.
4. Hide control panel.
5. Define X variable with log transformation.
6. Set Y variable.
7. Add bar element.
8. Configure log scale for X axis.
9. Create second Graph Builder window.
10. Set window size.
11. Hide control panel.
12. Define X variable with log transformation.
13. Set Y variable.
14. Add bar element.
15. Configure power scale for X axis.
16. Create third Graph Builder window.
17. Set window size.
18. Hide control panel.
19. Define X variable with log transformation.
20. Set Y variable.
21. Add box plot element.
22. Configure log scale for X axis.
23. Create fourth Graph Builder window.
24. Set window size.
25. Hide control panel.
26. Define X variable with log transformation.
27. Set Y variable.
28. Add box plot element.
29. Configure power scale for X axis.

Example 137

Summary: Generates a box plot chart using Graph Builder, displaying the distribution of values over time (Date) from a data table.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 489, 456 ),
    Show Control Panel( 0 ),
    Variables( X( :Date ) ),
    Elements( Box Plot( X, Legend( 4 ) ) ),
    SendToReport( Dispatch( {}, "Date", ScaleBox, {Label Row( Label Orientation( "Vertical" ) )} ) )
);

Code Explanation:

1. Open data table;
2. Launch Graph Builder.
3. Set graph size.
4. Hide control panel.
5. Assign Date variable to X-axis.
6. Add box plot element.
7. Send report command.
8. Dispatch to Date scale box.
9. Set label orientation to vertical.
10. Display graph.

Example 138

Summary: Visualizes a variability chart with nested factors using Graph Builder, displaying standard deviation charts and leveraging the operator and part configurations.

Code:

Open("data_table.jmp");
Graph Builder( Size( 777, 452 ), Show Control Panel( 0 ), Variables( X( :name ), Y( :height ) ), Elements( Points( X, Y, Legend( 11 ) ) ) );

Code Explanation:

1. Open data table;
2. Launch Graph Builder.
3. Set window size.
4. Hide control panel.
5. Define X variable.
6. Define Y variable.
7. Add points element.
8. Set legend index.

Example 139

Summary: Visualizes a variability chart with nested factors using Graph Builder, displaying standard deviation charts for Revenue and Persons Employed.

Code:

dt = Open("data_table.jmp");
gb = dt << Graph Builder(
    Show Control Panel( 0 ),
    Variables(
        X(
            Transform Column(
                "Quarter[Date within Year]",
                Format( "Format Pattern", "<Q#>", 15 ),
                Formula( Date Increment( Date MDY( Month( :Date ), Day( :Date ), 2000 ) + Time Of Day( :Date ), "Quarter", 0 ) )
            )
        ),
        Y( :"Revenue ($'000)"n ),
        Y( :Persons Employed, Position( 1 ), Side( "Right" ) )
    ),
    Elements(
        Points( X, Y( 1 ), Legend( 1 ), Summary Statistic( "Mean" ) ),
        Smoother( X, Y( 1 ), Legend( 4 ) ),
        Points( X, Y( 2 ), Legend( 5 ), Summary Statistic( "Mean" ) ),
        Smoother( X, Y( 2 ), Legend( 6 ) )
    ),
    SendToReport(
        Dispatch( {}, "400", ScaleBox, {Legend Model( 1, Base( -1, 0, 0, Item ID( "Revenue ($'000)", 1 ) ) )} ),
        Dispatch( {}, "400", LegendBox, {Legend Position( {1, [-1], 4, [0], 5, [-1], 6, [1]} ), Legend Position( {-1, 0, -1, 1} )} )
    )
);

Code Explanation:

1. Open data table.
2. Create Graph Builder object.
3. Hide control panel.
4. Define X variable with transformation.
5. Set X axis format to quarter.
6. Define Y variables: Revenue and Persons Employed.
7. Add points and smoother for Revenue.
8. Add points and smoother for Persons Employed.
9. Adjust legend position for Revenue.
10. Adjust overall legend position.

Example 140

Summary: Visualizes a box plot to analyze the relationship between Zone and Age on Premium USD, utilizing Graph Builder's Variables and Elements features.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 469, 301 ),
    Show Control Panel( 0 ),
    Show Legend( 0 ),
    Variables( X( :Zone ), X( :Age, Position( 1 ) ), Y( :Premium USD ) ),
    Elements( Box Plot( X( 2 ), X( 1 ), Y, Legend( 3 ) ) )
);

Code Explanation:

1. Open data table.
2. Launch Graph Builder.
3. Set window size.
4. Hide control panel.
5. Hide legend.
6. Assign variables to axes.
7. Add box plot element.
8. Set X-axis order.
9. Configure plot appearance.
10. Display graph.

Example 141

Summary: Visualizes the distribution of height data using a histogram in Graph Builder, with custom report settings and normal probability scale.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 433, 366 ),
    Show Control Panel( 0 ),
    Variables( Y( :height ) ),
    Elements( Histogram( Y, Legend( 3 ) ) ),
    SendToReport(
        Dispatch( {}, "height", ScaleBox,
            {Scale( "Normal Probability" ), Format( "Best", 12 ), Min( 1 ), Max( 1 ), Inc( 1 ), Minor Ticks( 1 ),
            Label Row( Show Major Grid( 1 ) )}
        )
    )
);

Code Explanation:

1. Open data table;
2. Create Graph Builder window.
3. Set window size.
4. Hide control panel.
5. Assign height variable to Y-axis.
6. Add histogram element.
7. Configure report settings.
8. Change scale to normal probability.
9. Set axis format and limits.
10. Display major grid lines.

Example 142

Summary: Visualizes the distribution of sex using a histogram in Graph Builder, with custom scale settings for normal probability.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 456, 293 ),
    Show Control Panel( 0 ),
    Variables( Y( :sex ) ),
    Elements( Histogram( Y, Legend( 3 ) ) ),
    SendToReport(
        Dispatch( {}, "sex", ScaleBox,
            {Scale( "Normal Probability" ), Min( 2.22044604925034e-16 ), Max( 1 ), Inc( 1 ), Minor Ticks( 0 ),
            Label Row( Show Major Grid( 1 ) )}
        )
    )
);

Code Explanation:

1. Open data table;
2. Create Graph Builder window.
3. Set window size.
4. Hide control panel.
5. Set Y variable to sex.
6. Add histogram element.
7. Configure legend for histogram.
8. Send report settings.
9. Adjust scale box for sex.
10. Set scale type to normal probability.

Example 143

Summary: Visualizes the relationship between height and weight using Graph Builder, filtering data by name 'AMY' with a Local Data Filter.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 534, 453 ),
    Show Control Panel( 0 ),
    Variables( X( :height ), Y( :weight ) ),
    Elements( Points( X, Y, Legend( 8 ) ), Smoother( X, Y, Legend( 9 ) ) ),
    Local Data Filter( Add Filter( columns( :name ), Where( :name == "AMY" ), Display( :name, Size( 221, 229 ), List Display ) ) )
);

Code Explanation:

1. Open data table;
2. Create Graph Builder window.
3. Set window size.
4. Hide control panel.
5. Assign X and Y variables.
6. Add points element.
7. Add smoother element.
8. Enable local data filter.
9. Filter by name "AMY".
10. Display filter list.

Example 144

Summary: Visualizes a nested variability chart using Graph Builder, with points and smoother elements to display the relationship between year and population.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 526, 454 ),
    Show Control Panel( 0 ),
    Variables( X( :year ), Y( :pop ) ),
    Elements( Points( X, Y, Legend( 1 ) ), Smoother( X, Y, Legend( 2 ) ) ),
    SendToReport( Dispatch( {}, "pop", ScaleBox, {Scale( "Log" ), Format( "Best", 6 ), Minor Ticks( 1 )} ) )
);

Code Explanation:

1. Open data table;
2. Launch Graph Builder.
3. Set window size.
4. Hide control panel.
5. Define X and Y variables.
6. Add points element.
7. Add smoother element.
8. Log scale Y axis.
9. Set format for Y axis.
10. Enable minor ticks on Y axis.

Example 145

Summary: Visualizes the relationship between height and weight using a Graph Builder, adding points and smoother elements to the plot. It also includes reference lines at specific values (55 and 65) and a range of values (55-65).

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 534, 456 ),
    Show Control Panel( 0 ),
    Show X Axis( 0 ),
    Variables( X( :height ), Y( :weight ) ),
    Elements( Points( X, Y, Legend( 2 ) ), Smoother( X, Y, Legend( 3 ) ) ),
    SendToReport(
        Dispatch( {}, "height", ScaleBox,
            {Add Ref Line( 55, "Solid", "Black", "", 1 ), Add Ref Line( 65, "Solid", "Black", "", 1 ),
            Add Ref Line( {55, 65}, "Solid", "Black", "", 1, 0.25 )}
        )
    )
);

Code Explanation:

1. Open data table;
2. Create Graph Builder window.
3. Set window size to 534x456.
4. Hide control panel.
5. Hide X axis.
6. Set X variable to height.
7. Set Y variable to weight.
8. Add points element.
9. Add smoother element.
10. Add reference lines at 55, 65, and range 55-65.

Example 146

Summary: Creates a Graph Builder object to visualize the relationship between height, sex, and age in a data table, with customized axis labels and label orientation.

Code:

dt = Open("data_table.jmp");
gb = dt << Graph Builder(
    Size( 500, 600 ),
    Show Control Panel( 0 ),
    Variables( X( :height ), Y( :sex ), Y( :age, Position( 1 ) ) ),
    Elements( Points( X, Y( 1 ), Y( 2 ), Legend( 4 ) ) ),
    SendToReport(
        Dispatch( {}, "sex", ScaleBox,
            {Label Row(
                1,
                {Tick Mark( Label( "12" ), Label( "12
(twelve)" ) ), Tick Mark( Label( "13" ), Label( "13
(thirteen)" ) ),
                Tick Mark( Label( "14" ), Label( "14
(fourteen)" ) ), Tick Mark( Label( "15" ), Label( "15
(fifteen)" ) ),
                Tick Mark( Label( "16" ), Label( "16
(sixteen)" ) ), Tick Mark( Label( "17" ), Label( "17
(seventeen)" ) )}
            ), Label Row( 2, Label Orientation( "Parallel" ) )}
        )
    )
);
gb << Save Picture( "$DESKTOP/AxisGBPointsX2YLabelRowLabelOrientationNewline_S1136856.png", PNG );

Code Explanation:

1. Open data table.
2. Create Graph Builder object.
3. Set graph size.
4. Hide control panel.
5. Define X and Y variables.
6. Add points element.
7. Customize sex axis labels.
8. Set age label orientation.
9. Save graph as PNG.

Example 147

Summary: Generates a Graph Builder visualization with nested factors, displaying points and customizing axis labels. It also saves the graph as a PNG file on the desktop.

Code:

dt = Open("data_table.jmp");
gb = dt << Graph Builder(
    Size( 500, 600 ),
    Show Control Panel( 0 ),
    Variables( X( :height ), Y( :sex ), Y( :age, Position( 1 ) ) ),
    Elements( Points( X, Y( 1 ), Y( 2 ), Legend( 4 ) ) ),
    SendToReport(
        Dispatch( {}, "sex", ScaleBox,
            {Label Row(
                1,
                {Tick Mark( Label( "12" ), Label( "12
(twelve)" ) ), Tick Mark( Label( "13" ), Label( "13
(thirteen)" ) ),
                Tick Mark( Label( "14" ), Label( "14
(fourteen)" ) ), Tick Mark( Label( "15" ), Label( "15
(fifteen)" ) ),
                Tick Mark( Label( "16" ), Label( "16
(sixteen)" ) ), Tick Mark( Label( "17" ), Label( "17
(seventeen)" ) )}
            ), Label Row( 2, Label Orientation( "Parallel" ) )}
        )
    )
);
gb << Save Picture( "$DESKTOP/AxisGBPointsX2YLabelRowLabelOrientationNewline_S1136856.png", PNG );
Open( "$DESKTOP/AxisGBPointsX2YLabelRowLabelOrientationNewline_S1136856.png" );

Code Explanation:

1. Open data table;
2. Create Graph Builder window.
3. Set window size to 500x600.
4. Hide control panel.
5. Assign variables: X=height, Y1=sex, Y2=age.
6. Add points element with X, Y1, Y2.
7. Customize sex axis labels with newline.
8. Set age axis label orientation to parallel.
9. Save graph as PNG on desktop.
10. Open saved PNG file.

Example 148

Summary: Visualizes a variability chart with nested factors using operator and part configurations, displaying standard deviation charts in Graph Builder.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 531, 271 ),
    Show Control Panel( 0 ),
    Page Gap Size( 111 ),
    Variables( X( :Begin Date ) ),
    Elements( Points( X, Legend( 2 ) ) ),
    SendToReport(
        Dispatch( {}, "Begin Date", ScaleBox,
            {Min( 3361737600 ), Max( 3471790342.57988 ), Interval( "Year" ), Inc( 1 ), Minor Ticks( 0 ), Label Row Nesting( 3 ),
            Label Row( 1, {Show Major Labels( 0 ), Show Major Ticks( 0 ), Show Minor Ticks( 0 )} ),
            Label Row( 2, {Show Major Labels( 0 ), Show Major Ticks( 0 ), Show Minor Ticks( 0 )} )}
        )
    )
);

Code Explanation:

1. Open data table;
2. Create Graph Builder.
3. Set window size.
4. Hide control panel.
5. Set page gap size.
6. Add X variable.
7. Add points element.
8. Customize scale box.
9. Set X axis minimum.
10. Set X axis maximum.

Example 149

Summary: Visualizes the relationship between sex and height using Graph Builder, with customized legend and axis settings.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 528, 448 ),
    Show Control Panel( 0 ),
    Variables( X( :sex ), Y( :height ) ),
    Elements( Points( X, Y, Legend( 3 ) ) ),
    SendToReport( Dispatch( {}, "sex", ScaleBox, {Min( -1e20 ), Max( 1e20 ), Inc( 1 ), Minor Ticks( 0 )} ) )
);

Code Explanation:

1. Open data_table data
2. Launch Graph Builder.
3. Set window size.
4. Hide control panel.
5. Assign sex to X-axis.
6. Assign height to Y-axis.
7. Add points element.
8. Customize legend.
9. Adjust sex axis min.
10. Adjust sex axis max.

Example 150

Summary: Creates a Graph Builder window with a line and points element to visualize the relationship between age, height, and sex, while customizing the legend and y-axis text color.

Code:

Open("data_table.jmp");
Graph Builder(
    Show Control Panel( 0 ),
    Variables( X( :age ), Y( :height ), Overlay( :sex ) ),
    Elements( Line( X, Y, Legend( 3 ) ), Points( X, Y, Legend( 4 ) ) ),
    SendToReport(
        Dispatch( {}, "400", ScaleBox,
            {Legend Model(
                4,
                Base( 0, 0, 0, Item ID( "F", 1 ) ),
                Base( 1, 0, 1, Item ID( "M", 1 ) ),
                Properties( 0, {Marker( "Plus" )}, Item ID( "F", 1 ) ),
                Properties( 1, {Marker( "Square" )}, Item ID( "M", 1 ) )
            )}
        ),
        Dispatch( {}, "", AxisBox( 2 ), {Text Color( "Medium Dark Green" )} )
    )
);

Code Explanation:

1. Open data table.
2. Create Graph Builder window.
3. Hide control panel.
4. Set X variable to age.
5. Set Y variable to height.
6. Overlay by sex.
7. Add line element.
8. Add points element.
9. Customize legend for females.
10. Customize legend for males.
11. Change y-axis text color.

Example 151

Summary: Creates a variability chart with nested factors using Graph Builder, displaying standard deviation charts and handling missing values.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 552, 393 ),
    Show Control Panel( 0 ),
    Show Legend( 0 ),
    Variables( X( :Position2 ), Y( :Weight ), Y( :Height, Position( 1 ) ), Group X( :Speed ), Group Y( :Bench ) ),
    Elements( Line( X, Y( 1 ), Y( 2 ), Legend( 14 ), Missing Factors( "Treat as Zero" ), Missing Values( "No Connection" ) ) )
);

Code Explanation:

1. Open data table;
2. Create Graph Builder object.
3. Set graph size.
4. Hide control panel.
5. Hide legend.
6. Define X and Y variables.
7. Define grouped X and Y variables.
8. Add line element.
9. Set legend position.
10. Handle missing factors and values.

Example 152

Summary: Visualizes a geographic map to analyze the relationship between Longitude and Latitude, utilizing Graph Builder's Points element with Legend.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 534, 453 ),
    Show Control Panel( 0 ),
    Variables( X( :Longitude ), Y( :Latitude ) ),
    Elements( Points( X, Y, Legend( 4 ) ) ),
    SendToReport(
        Dispatch( {}, "Graph Builder", FrameBox,
            {Background Map( Boundaries( {"Canadian Provinces"} ) ), DispatchSeg( Shape Seg( 1 ), {Color( "Black" )} )}
        )
    )
);

Code Explanation:

1. Open data table;
2. Launch Graph Builder.
3. Set graph size.
4. Hide control panel.
5. Assign variables.
6. Add points element.
7. Send report.
8. Dispatch graph builder.
9. Set frame box properties.
10. Add background map.

Example 153

Summary: Visualizes a nested variability chart with two factors using Graph Builder, displaying standard deviation charts and configuring response axes.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 600, 485 ),
    Show Control Panel( 0 ),
    Variables( X( :Strength ), Y( :Degrees ), Group X( :Weeks ), Group Y( :Censor ) ),
    Elements( Mosaic( X, Y, Legend( 16 ), Response Axis( "X" ) ) )
);

Code Explanation:

1. Open data table;
2. Launch Graph Builder.
3. Set window size.
4. Hide control panel.
5. Define X variable.
6. Define Y variable.
7. Define group X variable.
8. Define group Y variable.
9. Add mosaic element.
10. Configure response axis.

Example 154

Summary: Visualizes a variability chart with nested factors using Graph Builder, displaying standard deviation charts and adding reference lines for age.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 534, 435 ),
    Show Control Panel( 0 ),
    Variables( X( :age ), X( :sex, Position( 1 ) ), Y( :weight ) ),
    Elements( Points( X( 1 ), X( 2 ), Y, Legend( 10 ) ) ),
    SendToReport( Dispatch( {}, "age", ScaleBox, {Add Ref Line( 1, "Solid", "Red", "male", 1 )} ) )
);

Code Explanation:

1. Open data_table data
2. Launch Graph Builder.
3. Set window size.
4. Hide control panel.
5. Define X, X, and Y variables.
6. Add points element.
7. Send report to Graph Builder.
8. Add reference line for age.
9. Set reference line properties.
10. Label reference line with "male".

Example 155

Summary: Creates a Graph Builder object with points and smoother elements to visualize the relationship between age and height, while also saving the report as a journal file.

Code:

dt = Open("data_table.jmp");
dt << run script( "Set Age Value Labels" );
dt << Graph Builder( Variables( X( :age ), Y( :height ) ), Elements( Points( X, Y, Legend( 4 ) ), Smoother( X, Y, Legend( 5 ) ) ) );
Current Report() << save journal( "$TEMP\GB.jrn" );
dt << close window( "No Save" );

Code Explanation:

1. Open data table;
2. Run script for age value labels.
3. Create Graph Builder object.
4. Set X variable as age.
5. Set Y variable as height.
6. Add points element to graph.
7. Add smoother element to graph.
8. Save report as journal file.
9. Close data table without saving.

Example 156

Summary: Visualizes a variability chart with nested factors using Graph Builder, displaying standard deviation charts and customizing the age axis.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 573, 333 ),
    Show Control Panel( 0 ),
    Variables( X( :age ), X( :sex, Position( 1 ) ), Y( :weight ) ),
    Elements( Points( X( 1 ), X( 2 ), Y, Legend( 3 ) ) ),
    SendToReport(
        Dispatch( {}, "age", ScaleBox,
            {Add Ref Line( {5.5, 8}, "Solid", "Black", "", 1, 0.25 ), Label Row( 1, {Automatic Tick Marks( 0 ), Show Major Labels( 0 )} )}
        )
    )
);

Code Explanation:

1. Open data table.
2. Create Graph Builder window.
3. Set graph size.
4. Hide control panel.
5. Assign variables: age, sex, weight.
6. Add points element.
7. Customize age axis.
8. Add reference lines at 5.5 and 8.
9. Set reference line style and color.
10. Hide tick marks and labels on age axis.

Example 157

Summary: Visualizes a variability chart with nested factors using Graph Builder, displaying standard deviation charts and adding reference lines on the Y-axis.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 522, 452 ),
    Show Control Panel( 0 ),
    Variables( X( :weight ), Y( :height ) ),
    Elements( Points( X, Y, Legend( 3 ) ), Smoother( X, Y, Legend( 4 ) ) ),
    SendToReport(
        Dispatch( {}, "height", ScaleBox,
            {Add Ref Line( 60, "Solid", "Black", "YYY", 1 ), Add Ref Line( {60, 100}, "Solid", "Dark Green", "XXX", 1, 0.25 )}
        )
    )
);

Code Explanation:

1. Open data table;
2. Launch Graph Builder.
3. Set window size.
4. Hide control panel.
5. Define X and Y variables.
6. Add points element.
7. Add smoother element.
8. Send report to Graph Builder.
9. Add reference line at 60 on Y-axis.
10. Add range reference line from 60 to 100 on Y-axis.

Example 158

Summary: Visualizes the relationship between ozone concentration and date using Graph Builder, with a points element and smoother element to display trends. The report settings include formatting the date axis and setting a specific date range.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 526, 454 ),
    Show Control Panel( 0 ),
    Variables( X( :Ozone Concentration ), Y( :date ) ),
    Elements( Points( X, Y, Legend( 3 ) ), Smoother( X, Y, Legend( 4 ) ) ),
    SendToReport(
        Dispatch( {}, "date", ScaleBox,
            {Format( "m/d/y", 10 ), Min( 1893456000 ), Max( 2209032000 ), Interval( "Year" ), Inc( 1 ), Minor Ticks( 1 ),
            Label Row( Show Minor Labels( 1 ) )}
        )
    )
);

Code Explanation:

1. Open data table;
2. Launch Graph Builder.
3. Set window size.
4. Hide control panel.
5. Assign X and Y variables.
6. Add points element.
7. Add smoother element.
8. Send report settings.
9. Format date axis.
10. Set date range and interval.

Example 159

Summary: Opens a data table, creates a Graph Builder window with customized settings, and adds points and smoother elements to visualize the relationship between weight and height.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 641, 448 ),
    Show Control Panel( 0 ),
    Variables( X( :weight ), Y( :height ) ),
    Elements( Points( X, Y, Legend( 3 ) ), Smoother( X, Y, Legend( 4 ) ) ),
    SendToReport(
        Dispatch( {}, "weight", ScaleBox,
            {Scale( "Geodesic" ), Min( -122.734876954782 ), Max( -67.4190811007395 ), Inc( 20 ), Minor Ticks( 0 )}
        ),
        Dispatch( {}, "height", ScaleBox,
            {Scale( "Geodesic" ), Min( 15.6244048663589 ), Max( 53.7527927228953 ), Inc( 10 ), Minor Ticks( 0 ),
            Add Ref Line( {34.6885986180143, 50}, "Solid", "Black", "my range", 1, 0.25 )}
        ),
        Dispatch( {}, "Graph Builder", FrameBox,
            {Background Map( Images( "Simple Earth" ) ), Grid Line Order( 2 ), Reference Line Order( 3 )}
        )
    )
);

Code Explanation:

1. Open data table;
2. Create Graph Builder window.
3. Set window size to 641x448.
4. Hide control panel.
5. Assign weight to X-axis.
6. Assign height to Y-axis.
7. Add points element to graph.
8. Add smoother element to graph.
9. Configure weight axis scale.
10. Configure height axis scale with reference line.

Example 160

Summary: Generates three Graph Builder windows to visualize the relationship between height and weight, name and weight, and weight and name in a nested factor configuration. The script uses various elements such as points and smoother, and customizes scales for each graph.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 534, 444 ),
    Show Control Panel( 0 ),
    Variables( X( :height ), Y( :weight ) ),
    Elements( Points( X, Y, Legend( 2 ) ), Smoother( X, Y, Legend( 3 ) ) ),
    SendToReport( Dispatch( {}, "height", ScaleBox, {Reversed Scale} ), Dispatch( {}, "weight", ScaleBox, {Reversed Scale} ) )
);
Graph Builder(
    Size( 534, 452 ),
    Show Control Panel( 0 ),
    Variables( X( :name ), Y( :weight ) ),
    Elements( Points( X, Y, Legend( 2 ) ), Smoother( X, Y, Legend( 3 ) ) ),
    SendToReport( Dispatch( {}, "name", ScaleBox, {Reversed Scale} ), Dispatch( {}, "weight", ScaleBox, {Reversed Scale} ) )
);
Graph Builder(
    Size( 551, 344 ),
    Show Control Panel( 0 ),
    Variables( X( :weight ), Y( :name ) ),
    Elements( Points( X, Y, Legend( 2 ) ), Smoother( X, Y, Legend( 3 ) ) ),
    SendToReport(
        Dispatch( {}, "weight", ScaleBox, {Reversed Scale} ),
        Dispatch( {}, "name", ScaleBox, {Min( 38.6640206185567 ), Max( -0.507975773195874 ), Inc( 1 ), Minor Ticks( 0 )} )
    )
);

Code Explanation:

1. Open data table;
2. Create Graph Builder window.
3. Set size to 534x444.
4. Hide control panel.
5. Set X variable to height.
6. Set Y variable to weight.
7. Add points element.
8. Add smoother element.
9. Reverse X scale.
10. Reverse Y scale.
11. Create another Graph Builder window.
12. Set size to 534x452.
13. Hide control panel.
14. Set X variable to name.
15. Set Y variable to weight.
16. Add points element.
17. Add smoother element.
18. Reverse X scale.
19. Reverse Y scale.
20. Create third Graph Builder window.
21. Set size to 551x344.
22. Hide control panel.
23. Set X variable to weight.
24. Set Y variable to name.
25. Add points element.
26. Add smoother element.
27. Reverse X scale.
28. Set Y axis minimum.
29. Set Y axis maximum.
30. Set Y axis increment.
31. Disable minor ticks on Y axis.

Example 161

Summary: Generates four Graph Builder windows to visualize the relationship between different variables in a data table, including nested factors and operator configurations.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 534, 444 ),
    Show Control Panel( 0 ),
    Variables( X( :height ), Y( :weight ) ),
    Elements( Points( X, Y, Legend( 2 ) ), Smoother( X, Y, Legend( 3 ) ) ),
    SendToReport( Dispatch( {}, "height", ScaleBox, {Reversed Scale} ), Dispatch( {}, "weight", ScaleBox, {Reversed Scale} ) )
);
Graph Builder(
    Size( 534, 452 ),
    Show Control Panel( 0 ),
    Variables( X( :name ), Y( :weight ) ),
    Elements( Points( X, Y, Legend( 2 ) ), Smoother( X, Y, Legend( 3 ) ) ),
    SendToReport( Dispatch( {}, "name", ScaleBox, {Reversed Scale} ), Dispatch( {}, "weight", ScaleBox, {Reversed Scale} ) )
);
Graph Builder(
    Size( 551, 344 ),
    Show Control Panel( 0 ),
    Variables( X( :weight ), Y( :name ) ),
    Elements( Points( X, Y, Legend( 2 ) ), Smoother( X, Y, Legend( 3 ) ) ),
    SendToReport(
        Dispatch( {}, "weight", ScaleBox, {Reversed Scale} ),
        Dispatch( {}, "name", ScaleBox, {Min( 38.6640206185567 ), Max( -0.507975773195874 ), Inc( 1 ), Minor Ticks( 0 )} )
    )
);
Graph Builder(
    Size( 525, 438 ),
    Show Control Panel( 0 ),
    Variables( X( :sex ), Y( :age ) ),
    Elements( Points( X, Y, Legend( 2 ) ), Smoother( X, Y, Legend( 3 ) ) ),
    SendToReport( Dispatch( {}, "sex", ScaleBox, {Reversed Scale} ), Dispatch( {}, "age", ScaleBox, {Reversed Scale} ) )
);

Code Explanation:

1. Open data table.
2. Create first Graph Builder window.
3. Set window size.
4. Hide control panel.
5. Assign variables for X and Y axes.
6. Add points and smoother elements.
7. Reverse scales for both axes.
8. Create second Graph Builder window.
9. Set window size.
10. Hide control panel.
11. Assign variables for X and Y axes.
12. Add points and smoother elements.
13. Reverse scales for both axes.
14. Create third Graph Builder window.
15. Set window size.
16. Hide control panel.
17. Assign variables for X and Y axes.
18. Add points and smoother elements.
19. Reverse scale for X axis.
20. Set specific range and increment for Y axis.
21. Create fourth Graph Builder window.
22. Set window size.
23. Hide control panel.
24. Assign variables for X and Y axes.
25. Add points and smoother elements.
26. Reverse scales for both axes.

Example 162

Summary: Visualizes a variability chart with nested factors using Graph Builder, displaying standard deviation charts for height and weight, while customizing label colors and font styles.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 582, 376 ),
    Show Control Panel( 0 ),
    Variables( X( :age ), Y( :height, Side( "Right" ) ), Y( :weight, Position( 1 ) ) ),
    Elements( Points( X, Y( 2 ), Legend( 5 ) ), Points( X, Y( 1 ), Legend( 6 ) ) ),
    SendToReport(
        Dispatch( {}, "weight", ScaleBox, {Label Row( Line Color( "Red" ) )} ),
        Dispatch( {}, "height", ScaleBox, {Label Row( Line Color( "Blue" ) )} ),
        Dispatch( {}, "Y title", TextEditBox, {Font Color( "Red" )} ),
        Dispatch( {}, "", AxisBox( 2 ), {Text Color( "Red" )} ),
        Dispatch( {}, "Y r title", TextEditBox, {Font Color( "Blue" )} ),
        Dispatch( {}, "", AxisBox( 3 ), {Text Color( "Blue" )} )
    )
);

Code Explanation:

1. Open data table.
2. Create Graph Builder window.
3. Set window size.
4. Hide control panel.
5. Define X and Y variables.
6. Add points for height and weight.
7. Change weight label line color.
8. Change height label line color.
9. Change height title font color.
10. Change height axis text color.

Example 163

Summary: Generates a Graph Builder visualization with nested factors, displaying standard deviation charts and adding reference lines to the report.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 522, 452 ),
    Show Control Panel( 0 ),
    Variables( X( :weight ), Y( :height ) ),
    Elements( Points( X, Y, Legend( 3 ) ), Smoother( X, Y, Legend( 4 ) ) ),
    SendToReport(
        Dispatch( {}, "height", ScaleBox,
            {Add Ref Line( 60, "Solid", "Black", "YYY", 1 ), Add Ref Line( {60, 100}, "Solid", "Medium Dark Blue", "XXX", 1, 0.25 )}
        )
    )
);

Code Explanation:

1. Open data table;
2. Launch Graph Builder.
3. Set graph size.
4. Hide control panel.
5. Assign X and Y variables.
6. Add point elements.
7. Add smoother elements.
8. Send report to Graph Builder.
9. Add reference line at Y=60.
10. Add range reference line from Y=60 to Y=100.

Example 164

Summary: Visualizes a graph builder with nested factors using operator and part configurations, displaying standard deviation charts.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 678, 507 ),
    Show Control Panel( 0 ),
    Variables(
        X( Transform Column( "SAT Verbal+SAT Math", Formula( :SAT Verbal + :SAT Math ) ) ),
        Y( :Name( "Student/Faculty Ratio (1997)" ) ),
        Group X( :Region ),
        Color( :Region )
    ),
    Elements( Points( X, Y, Legend( 10 ) ) ),
    SendToReport( Dispatch( {}, "Graph Builder", OutlineBox, {Set Title( "Graph Builder Points/Caption Box with Transform Column" )} ) )
);

Code Explanation:

1. Open data_table data
2. Create Graph Builder window.
3. Set window size.
4. Hide control panel.
5. Define X variable.
6. Define Y variable.
7. Group by Region.
8. Color by Region.
9. Add points element.
10. Set graph title.

Example 165

Summary: Opens a data table and creates a Graph Builder window to visualize the relationship between two variables, with points plotted on a scale box.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 538, 782 ),
    Show Control Panel( 0 ),
    Variables( X( :weight ), Y( :name ) ),
    Elements( Points( X, Y, Legend( 3 ) ) ),
    SendToReport( Dispatch( {}, "name", ScaleBox, {Label Row( Label Alignment( "Far" ) )} ) )
);

Code Explanation:

1. Open data table.
2. Create Graph Builder window.
3. Set graph size.
4. Hide control panel.
5. Define X variable.
6. Define Y variable.
7. Add points element.
8. Send report command.
9. Dispatch to name scale box.
10. Align label row far.

Example 166

Summary: Generates a graph that visualizes the relationship between 'Theme' and 'Rotten Tomatoes Score', with an angled label orientation, and saves it as a PNG image.

Code:

Open("data_table.jmp");
gb = Graph Builder(
    Size( 670, 300 ),
    Show Control Panel( 0 ),
    Show Legend( 0 ),
    Variables( X( :Theme ), Y( :Rotten Tomatoes Score ) ),
    Elements( Points( X, Y, Legend( 4 ) ) ),
    SendToReport( Dispatch( {}, "Theme", ScaleBox, {Label Row( Label Orientation( "Angled" ) )} ) )
);
r = Report( gb );
r << save picture( "$TEMP/savepicture.png", "png" );

Code Explanation:

1. Open data table;
2. Create Graph Builder object.
3. Set graph size.
4. Hide control panel.
5. Hide legend.
6. Assign X and Y variables.
7. Add points element.
8. Set label orientation to angled.
9. Generate report object.
10. Save graph as PNG.

Example 167

Summary: Generates a graph builder object to visualize the relationship between 'Theme' and 'Rotten Tomatoes Score', saving the resulting image as a PNG file.

Code:

Open("data_table.jmp");
gb = Graph Builder(
    Size( 670, 300 ),
    Show Control Panel( 0 ),
    Show Legend( 0 ),
    Variables( X( :Theme ), Y( :Rotten Tomatoes Score ) ),
    Elements( Points( X, Y, Legend( 4 ) ) ),
    SendToReport( Dispatch( {}, "Theme", ScaleBox, {Label Row( Label Orientation( "Angled" ) )} ) )
);
r = Report( gb );
r << save picture( "$TEMP/savepicture.png", "png" );
img = Open( "$TEMP/savepicture.png", "png" );
sz = img << get size();

Code Explanation:

1. Open data table.
2. Create graph builder object.
3. Set graph size.
4. Hide control panel.
5. Hide legend.
6. Define X and Y variables.
7. Add points element.
8. Set label orientation to angled.
9. Save graph as PNG.
10. Open saved PNG image.
11. Get image size.

Example 168

Summary: Generates a graph builder object to visualize the relationship between 'Theme' and 'Rotten Tomatoes Score', saving the output as a PNG image.

Code:

Open("data_table.jmp");
gb = Graph Builder(
    Size( 670, 300 ),
    Show Control Panel( 0 ),
    Show Legend( 0 ),
    Variables( X( :Theme ), Y( :Rotten Tomatoes Score ) ),
    Elements( Points( X, Y, Legend( 4 ) ) ),
    SendToReport( Dispatch( {}, "Theme", ScaleBox, {Label Row( Label Orientation( "Angled" ) )} ) )
);
r = Report( gb );
r << save picture( "$TEMP/savepicture.png", "png" );
img = Open( "$TEMP/savepicture.png", "png" );

Code Explanation:

1. Open data table;
2. Create graph builder object.
3. Set graph size.
4. Hide control panel.
5. Hide legend.
6. Define X and Y variables.
7. Add points element.
8. Set label orientation to angled.
9. Save graph as PNG.
10. Open saved PNG image.

Example 169

Summary: Creates a graph builder with nested factors, utilizing Graph Builder to visualize data and SendToReport for report generation.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 628, 319 ),
    Show Control Panel( 0 ),
    Variables( X( :height ), Y( :name ) ),
    Elements( Points( X, Y, Legend( 3 ) ) ),
    SendToReport( Dispatch( {}, "name", ScaleBox, {Label Row( Lower Frame( 1 ) )} ) )
);

Code Explanation:

1. Open data table;
2. Launch Graph Builder.
3. Set window size.
4. Hide control panel.
5. Assign variables X and Y.
6. Add points element.
7. Send report command.
8. Access name scale box.
9. Modify label row.
10. Place lower frame label.

Example 170

Summary: Creates a variability chart with nested factors using operator and part configurations, displaying standard deviation charts in JMP.

Code:

Open("data_table.jmp");
Graph Builder( Size( 526, 411 ), Show Control Panel( 0 ), Variables( Y( :name ) ), Elements( Points( Y, Legend( 2 ) ) ) );

Code Explanation:

1. Open data table;
2. Launch Graph Builder.
3. Set window size.
4. Hide control panel.
5. Define Y variable.
6. Add points element.
7. Assign legend position.

Example 171

Summary: Creates two Graph Builder windows to visualize nested factors using operator and part configurations, displaying standard deviation charts.

Code:

Open("data_table.jmp");
Graph Builder( Size( 526, 411 ), Show Control Panel( 0 ), Variables( Y( :name ) ), Elements( Points( Y, Legend( 2 ) ) ) );
Graph Builder( Size( 489, 456 ), Show Control Panel( 0 ), Variables( X( :name ) ), Elements( Points( X, Legend( 6 ) ) ) );

Code Explanation:

1. Open data table.
2. Create Graph Builder window.
3. Set graph size.
4. Hide control panel.
5. Assign Y variable.
6. Add points element.
7. Set legend for Y.
8. Create second Graph Builder window.
9. Set graph size.
10. Hide control panel.

Example 172

Summary: Creates a variability chart with nested factors using operator and part configurations, displaying standard deviation charts in Graph Builder.

Code:

Open("data_table.jmp");
Graph Builder( Size( 326, 379 ), Show Control Panel( 0 ), Variables( X( :name ), Y( :name ) ), Elements( Points( X, Y, Legend( 3 ) ) ) );

Code Explanation:

1. Open data table;
2. Create Graph Builder window.
3. Set window size.
4. Hide control panel.
5. Define X variable.
6. Define Y variable.
7. Add points element.
8. Assign legend to points.

Example 173

Summary: Creates a graph builder with nested factors using operator and part configurations, displaying standard deviation charts.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 489, 448 ),
    Show Control Panel( 0 ),
    Variables( X( :age ) ),
    Elements( Points( X, Legend( 4 ) ) ),
    SendToReport( Dispatch( {}, "age", ScaleBox, {Add Ref Line( {1, 2}, "Solid", "Black", "Early Teen", 1, 0.25 )} ) )
);

Code Explanation:

1. Open data table.
2. Launch Graph Builder.
3. Set window size.
4. Hide control panel.
5. Assign X variable.
6. Add points element.
7. Send report message.
8. Dispatch to "age" scale box.
9. Add reference line.
10. Configure reference line properties.

Example 174

Summary: Creates a variability chart with nested factors using Graph Builder, configuring reference lines and labels to display standard deviation charts.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 524, 411 ),
    Show Control Panel( 0 ),
    Title Alignment( "Left" ),
    Variables( Y( :age ) ),
    Elements( Points( Y, Legend( 2 ) ) ),
    SendToReport(
        Dispatch( {}, "age", ScaleBox,
            {Min( -0.5 ), Max( 6 ), Inc( 1 ), Minor Ticks( 0 ), Add Ref Line( 0, "Solid", "Black", "Outside ", 1 ),
            Add Ref Line( 2, "Solid", "Black", "Inside Above", 1, 1, Label Settings( {Label Position( "Inside Above" )} ) ),
            Add Ref Line( 4, "Solid", "Black", "Inside Below", 1, 1, Label Settings( {Label Position( "Inside Below" )} ) ),
            Add Ref Line( 5, "Solid", "Black", "Inside Inline", 1, 1, Label Settings( {Label Position( "Inside Inline" )} ) )}
        ),
        Dispatch( {}, "graph title", TextEditBox, {Set Text( "Reference Line Labels Opposite Side" )} )
    )
);
Graph Builder(
    Size( 524, 411 ),
    Show Control Panel( 0 ),
    Variables( Y( :age ) ),
    Elements( Points( Y, Legend( 2 ) ) ),
    SendToReport(
        Dispatch( {}, "age", ScaleBox,
            {Min( -0.5 ), Max( 6 ), Inc( 1 ), Minor Ticks( 0 ), Add Ref Line(
                0,
                "Solid",
                "Black",
                "Outside ",
                1,
                1,
                Label Settings( {Opposite Axis( 1 )} )
            ), Add Ref Line(
                2,
                "Solid",
                "Black",
                "Inside Above",
                1,
                1,
                Label Settings( {Label Position( "Inside Above" ), Opposite Axis( 1 )} )
            ), Add Ref Line(
                4,
                "Solid",
                "Black",
                "Inside Below",
                1,
                1,
                Label Settings( {Label Position( "Inside Below" ), Opposite Axis( 1 )} )
            ), Add Ref Line(
                5,
                "Solid",
                "Black",
                "Inside Inline",
                1,
                1,
                Label Settings( {Label Position( "Inside Inline" ), Opposite Axis( 1 )} )
            )}
        ),
        Dispatch( {}, "graph title", TextEditBox, {Set Text( "Reference Line Labels Opposite Side" )} )
    )
);

Code Explanation:

1. Open data table;
2. Create first Graph Builder window.
3. Set graph size.
4. Hide control panel.
5. Align title to left.
6. Set Y variable to age.
7. Add points element.
8. Configure Y axis scale.
9. Add reference lines with labels.
10. Set graph title.
11. Create second Graph Builder window.
12. Repeat steps 3-10.
13. Adjust reference line labels to opposite side.

Example 175

Summary: Creates a variability chart with nested factors using Graph Builder, displaying standard deviation charts and adding reference lines for age, weight, and height.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 534, 448 ),
    Show Control Panel( 0 ),
    Variables( X( :age ), Y( :height, Side( "Right" ) ), Y( :weight, Position( 1 ) ) ),
    Elements( Points( X, Y( 2 ), Legend( 6 ) ), Line( X, Y( 1 ), Legend( 9 ) ), Smoother( X, Y( 2 ), Legend( 8 ) ) ),
    SendToReport(
        Dispatch( {}, "age", ScaleBox, {Add Ref Line( 2.5, "Solid", "Red", "", 1 )} ),
        Dispatch( {}, "weight", ScaleBox, {Add Ref Line( 140, "Solid", "Cyan", "", 1 )} ),
        Dispatch( {}, "height", ScaleBox, {Add Ref Line( 63, "Solid", "Green", "", 1 )} )
    )
);

Code Explanation:

1. Open data table;
2. Create Graph Builder window.
3. Set window size.
4. Hide control panel.
5. Define X and Y variables.
6. Add points element.
7. Add line element.
8. Add smoother element.
9. Add reference line for age.
10. Add reference line for weight.
11. Add reference line for height.

Example 176

Summary: Creates a geographic map to visualize years of compulsory education across territories, utilizing Graph Builder and customizing legend properties.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 748, 534 ),
    Show Control Panel( 0 ),
    Variables( Color( :Years of Compulsory Education ), Shape( :Territory ) ),
    Elements( Map Shapes( Legend( 2 ) ) ),
    SendToReport(
        Dispatch( {}, "", ScaleBox,
            {Min( 192.933920838086 ), Max( -192.933920838086 ), Inc( 50 ), Minor Ticks( 0 ), Label Row( Show Major Grid( 1 ) )}
        ),
        Dispatch( {}, "", ScaleBox( 2 ),
            {Min( 128.177016223987 ), Max( -135.958708732916 ), Inc( 50 ), Minor Ticks( 1 ), Label Row( Show Major Grid( 1 ) )}
        ),
        Dispatch( {}, "400", ScaleBox,
            {Legend Model(
                2,
                Properties(
                    0,
                    {gradient( {Color Theme( "White to Green" ), Label Format( "Fixed Dec", 15, 0 )} )},
                    Item ID( "Years of Compulsory Education", 1 )
                )
            )}
        ),
        Dispatch( {}, "graph title", TextEditBox, {Set Text( "Years of Compulsory Education" )} ),
        Dispatch( {}, "400", LegendBox, {Set Title( "Years" )} )
    )
);

Code Explanation:

1. Open data table.
2. Create Graph Builder window.
3. Set graph size.
4. Hide control panel.
5. Assign color and shape variables.
6. Add map shapes element.
7. Configure first scale box.
8. Configure second scale box.
9. Customize legend properties.
10. Set graph title.

Example 177

Summary: Creates a variability chart with nested factors using Graph Builder, displaying standard deviation charts and configuring Y-axis scale to power.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 534, 464 ),
    Show Control Panel( 0 ),
    Variables( X( :name ), Y( :height ) ),
    Elements( Points( X, Y, Legend( 8 ) ) ),
    SendToReport(
        Dispatch( {}, "height", ScaleBox,
            {Scale( "Power" ), Format( "Best", 12 ), Min( -5.91169772950084 ), Max( 74.7933530144302 ), Inc( 20 ), Minor Ticks( 1 )}
        )
    )
);

Code Explanation:

1. Open data table.
2. Launch Graph Builder.
3. Set graph size.
4. Hide control panel.
5. Define X and Y variables.
6. Add points element.
7. Send report settings.
8. Set Y axis scale to power.
9. Format Y axis numbers.
10. Set Y axis min, max, increment, minor ticks.

Example 178

Summary: Creates multiple Weibull, Frechet, Logistic, Exponential, and Gamma probability distribution charts for a dataset with nested factors using Graph Builder in JMP.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 534, 448 ),
    Show Control Panel( 0 ),
    Variables( X( :Meal ), Y( :Calories ) ),
    Elements( Points( X, Y, Legend( 3 ) ) ),
    SendToReport(
        Dispatch( {}, "Calories", ScaleBox,
            {Scale( "Weibull Probability" ), Format( "Best", 12 ), Min( 2.22044604925031e-16 ), Max( 1 ), Inc( 1 ), Minor Ticks( 1 ),
            Label Row( Show Major Grid( 1 ) )}
        )
    )
);
Graph Builder(
    Size( 534, 448 ),
    Show Control Panel( 0 ),
    Variables( X( :Meal ), Y( :Calories ) ),
    Elements( Points( X, Y, Legend( 3 ) ) ),
    SendToReport(
        Dispatch( {}, "Calories", ScaleBox,
            {Scale( "Frechet Probability" ), Format( "Best", 12 ), Min( 2.22044604925031e-16 ), Max( 1 ), Inc( 1 ), Minor Ticks( 1 ),
            Label Row( Show Major Grid( 1 ) )}
        )
    )
);
Graph Builder(
    Size( 534, 448 ),
    Show Control Panel( 0 ),
    Variables( X( :Meal ), Y( :Calories ) ),
    Elements( Points( X, Y, Legend( 3 ) ) ),
    SendToReport(
        Dispatch( {}, "Calories", ScaleBox,
            {Scale( "Logistic Probability" ), Format( "Best", 12 ), Min( 2.22044604925031e-16 ), Max( 1 ), Inc( 1 ), Minor Ticks( 1 ),
            Label Row( Show Major Grid( 1 ) )}
        )
    )
);
Graph Builder(
    Size( 534, 448 ),
    Show Control Panel( 0 ),
    Variables( X( :Meal ), Y( :Calories ) ),
    Elements( Points( X, Y, Legend( 3 ) ) ),
    SendToReport(
        Dispatch( {}, "Calories", ScaleBox,
            {Scale( "Exponential Probability" ), Format( "Best", 12 ), Min( 2.22044604925031e-16 ), Max( 1 ), Inc( 1 ), Minor Ticks( 1 ),
            Label Row( Show Major Grid( 1 ) )}
        )
    )
);
Graph Builder(
    Size( 534, 448 ),
    Show Control Panel( 0 ),
    Variables( X( :Meal ), Y( :Calories ) ),
    Elements( Points( X, Y, Legend( 3 ) ) ),
    SendToReport(
        Dispatch( {}, "Calories", ScaleBox,
            {Scale( "Gamma Probability" ), Format( "Best", 12 ), Min( 2.22044604925031e-16 ), Max( 1 ), Inc( 1 ), Minor Ticks( 1 ),
            Label Row( Show Major Grid( 1 ) )}
        )
    )
);

Code Explanation:

1. Open data table;
2. Create Graph Builder window.
3. Set graph size to 534x448.
4. Hide control panel.
5. Assign Meal to X-axis, Calories to Y-axis.
6. Add points element to graph.
7. Set Y-axis scale to Weibull Probability.
8. Repeat steps 2-7 for Frechet Probability.
9. Repeat steps 2-7 for Logistic Probability.
10. Repeat steps 2-7 for Exponential Probability.
11. Repeat steps 2-7 for Gamma Probability.

Example 179

Summary: Creates a graph builder with nested factors using operator and part configurations, displaying standard deviation charts.

Code:

Open("data_table.jmp");
gb = Graph Builder(
    Size( 425, 425 ),
    Show Control Panel( 0 ),
    Variables( X( :weight ), Y( :height ) ),
    Elements( Points( X, Y, Legend( 3 ) ), Smoother( X, Y, Legend( 4 ) ) )
);
rpt = gb << report;
xaxisbox = rpt[axis box( 1 )];

Code Explanation:

1. Open data_table data
2. Create Graph Builder object.
3. Set graph size.
4. Hide control panel.
5. Assign weight to X-axis.
6. Assign height to Y-axis.
7. Add points element.
8. Add smoother element.
9. Generate report object.
10. Access X-axis settings.

Example 180

Summary: Creates a graph report with points and smoother elements to visualize the relationship between weight and height, utilizing Graph Builder.

Code:

dt = Open("data_table.jmp");
gb = Graph Builder(
    Size( 425, 425 ),
    Show Control Panel( 0 ),
    Variables( X( :weight ), Y( :height ) ),
    Elements( Points( X, Y, Legend( 3 ) ), Smoother( X, Y, Legend( 4 ) ) )
);
rpt = gb << report;
xaxisbox = rpt[axis box( 1 )];

Code Explanation:

1. Open data table;
2. Create Graph Builder.
3. Set graph size.
4. Hide control panel.
5. Assign variables X and Y.
6. Add points and smoother elements.
7. Generate graph report.
8. Access X-axis box.

Example 181

Summary: Creates a graph builder object to visualize relationships between weight and height, with interactive features for smoother lines and reference lines.

Code:

Open("data_table.jmp");
gb = Graph Builder(
    Size( 425, 425 ),
    Show Control Panel( 0 ),
    Variables( X( :weight ), Y( :height ) ),
    Elements( Points( X, Y, Legend( 3 ) ), Smoother( X, Y, Legend( 4 ) ) )
);
rpt = gb << report;
xaxisbox = rpt[axis box( 1 )];
xaxisbox << Add Ref Line( 130, "Dashed", black, "Test", 2 );

Code Explanation:

1. Open data table.
2. Create graph builder object.
3. Set graph size.
4. Hide control panel.
5. Assign variables X and Y.
6. Add points and smoother elements.
7. Generate report object.
8. Access X-axis box.
9. Add reference line at 130.
10. Set line style, color, and label.

Example 182

Summary: Creates a graph builder object with points and smoother elements, displaying standard deviation charts for a nested factors analysis.

Code:

dt = Open("data_table.jmp");
gb = Graph Builder(
    Size( 425, 425 ),
    Show Control Panel( 0 ),
    Variables( X( :weight ), Y( :height ) ),
    Elements( Points( X, Y, Legend( 3 ) ), Smoother( X, Y, Legend( 4 ) ) )
);
rpt = gb << report;
xaxisbox = rpt[axis box( 1 )];
xaxisbox << Add Ref Line( 130, "Dashed", black, "Test", 2 );

Code Explanation:

1. Open data table;
2. Create Graph Builder object.
3. Set graph size.
4. Hide control panel.
5. Define X and Y variables.
6. Add points and smoother elements.
7. Generate report object.
8. Access X-axis box.
9. Add reference line at 130.
10. Set line style, color, label, and width.

Example 183

Summary: Creates a variability chart with nested factors using Graph Builder, displaying points and smoother elements, and adjusting label orientation for X-axis.

Code:

Open("data_table.jmp");
gb = Graph Builder(
    Size( 425, 425 ),
    Show Control Panel( 0 ),
    Variables( X( :weight ), Y( :height ) ),
    Elements( Points( X, Y, Legend( 3 ) ), Smoother( X, Y, Legend( 4 ) ) ),
    SendToReport( Dispatch( {}, "weight", ScaleBox, {Label Row( Label Orientation( "Vertical" ) )} ) )
);
rpt = gb << report;
xaxisbox = rpt[axis box( 1 )];

Code Explanation:

1. Open data table.
2. Create Graph Builder object.
3. Set graph size.
4. Hide control panel.
5. Assign variables for axes.
6. Add points and smoother elements.
7. Adjust label orientation for X-axis.
8. Generate report object.
9. Access X-axis box from report.

Example 184

Summary: Creates a variability chart with nested factors using operator and part configurations, displaying standard deviation charts.

Code:

dt = Open("data_table.jmp");
gb = Graph Builder(
    Size( 425, 425 ),
    Show Control Panel( 0 ),
    Variables( X( :weight ), Y( :height ) ),
    Elements( Points( X, Y, Legend( 3 ) ), Smoother( X, Y, Legend( 4 ) ) ),
    SendToReport( Dispatch( {}, "weight", ScaleBox, {Label Row( Label Orientation( "Vertical" ) )} ) )
);
rpt = gb << report;
xaxisbox = rpt[axis box( 1 )];

Code Explanation:

1. Open data table.
2. Create Graph Builder object.
3. Set graph size.
4. Hide control panel.
5. Define X and Y variables.
6. Add points and smoother elements.
7. Set vertical label orientation.
8. Generate graph report.
9. Access X-axis box.

Example 185

Summary: Creates a variability chart with nested factors using Graph Builder, displaying standard deviation charts and axis box configurations.

Code:

Open("data_table.jmp");
gb = Graph Builder(
    Size( 425, 425 ),
    Show Control Panel( 0 ),
    Variables( X( :age ), Y( :height, Side( "Right" ) ), Y( :weight, Position( 1 ) ) ),
    Elements( Points( X, Y( 2 ), Legend( 32 ) ), Points( X, Y( 1 ), Legend( 33 ) ) )
);
rpt = gb << report;
xaxisbox = rpt[axis box( 3 )];

Code Explanation:

1. Open data table;
2. Create Graph Builder object.
3. Set graph size.
4. Hide control panel.
5. Define X and Y variables.
6. Add points elements.
7. Generate report object.
8. Access axis box.

Example 186

Summary: Creates a graph builder report with nested factors, displaying standard deviation charts and accessing axis boxes.

Code:

dt = Open("data_table.jmp");
gb = Graph Builder(
    Size( 425, 425 ),
    Show Control Panel( 0 ),
    Variables( X( :age ), Y( :height, Side( "Right" ) ), Y( :weight, Position( 1 ) ) ),
    Elements( Points( X, Y( 2 ), Legend( 32 ) ), Points( X, Y( 1 ), Legend( 33 ) ) )
);
rpt = gb << report;
xaxisbox = rpt[axis box( 3 )];

Code Explanation:

1. Open data table.
2. Create graph builder object.
3. Set graph size.
4. Hide control panel.
5. Define X and Y variables.
6. Add points for height and weight.
7. Generate report from graph builder.
8. Access third axis box.

Example 187

Summary: Creates a graph builder object to visualize relationships between 'weight' and 'height', utilizing points and smoother elements.

Code:

Open("data_table.jmp");
gb = Graph Builder(
    Size( 425, 425 ),
    Show Control Panel( 0 ),
    Variables( X( :weight ), Y( :height ) ),
    Elements( Points( X, Y, Legend( 3 ) ), Smoother( X, Y, Legend( 4 ) ) )
);
rpt = gb << report;
xaxisbox = rpt[axis box( 2 )];

Code Explanation:

1. Open data table.
2. Create graph builder object.
3. Set graph size.
4. Hide control panel.
5. Define X and Y variables.
6. Add points and smoother elements.
7. Generate graph report.
8. Access X-axis settings.

Example 188

Summary: Creates a graph builder object to visualize the relationship between weight and height, utilizing points and smoother elements.

Code:

dt = Open("data_table.jmp");
gb = Graph Builder(
    Size( 425, 425 ),
    Show Control Panel( 0 ),
    Variables( X( :weight ), Y( :height ) ),
    Elements( Points( X, Y, Legend( 3 ) ), Smoother( X, Y, Legend( 4 ) ) )
);
rpt = gb << report;
xaxisbox = rpt[axis box( 2 )];

Code Explanation:

1. Open data table;
2. Create graph builder object.
3. Set graph size.
4. Hide control panel.
5. Define X and Y variables.
6. Add points and smoother elements.
7. Generate report from graph.
8. Access axis box for X-axis.

Example 189

Summary: Creates a graph builder with nested factors using operator and part configurations, displaying standard deviation charts.

Code:

Open("data_table.jmp");
gb = Graph Builder(
    Size( 867, 444 ),
    Show Control Panel( 0 ),
    Variables( X( :weight ), Y( :height ) ),
    Elements( Points( X, Y, Legend( 3 ) ), Smoother( X, Y, Legend( 4 ) ) )
);
rpt = gb << report;
xaxisbox = rpt[axis box( 1 )];

Code Explanation:

1. Open data table;
2. Create Graph Builder.
3. Set size to 867x444.
4. Hide control panel.
5. Set X variable to :weight.
6. Set Y variable to :height.
7. Add points element.
8. Add smoother element.
9. Get report object.
10. Select X-axis box.

Example 190

Summary: Creates a graph builder object to visualize the relationship between weight and height, with interactive elements for smoother curves and axis control.

Code:

dt = Open("data_table.jmp");
gb = Graph Builder(
    Size( 867, 444 ),
    Show Control Panel( 0 ),
    Variables( X( :weight ), Y( :height ) ),
    Elements( Points( X, Y, Legend( 3 ) ), Smoother( X, Y, Legend( 4 ) ) )
);
rpt = gb << report;
xaxisbox = rpt[axis box( 1 )];

Code Explanation:

1. Open data table.
2. Create graph builder object.
3. Set graph size.
4. Hide control panel.
5. Define X and Y variables.
6. Add points and smoother elements.
7. Generate report from graph.
8. Access X-axis box from report.

Example 191

Summary: Creates a variability chart with nested factors using Graph Builder, adjusting Y-axis settings and displaying standard deviation charts.

Code:

Names Default To Here( 1 );
dt = Open("data_table.jmp");
Graph Builder(
    Show Control Panel( 0 ),
    Variables( X( :age ), Y( :name ) ),
    Elements( Points( X, Y, Legend( 1 ), Jitter( 1 ) ) ),
    SendToReport(
        Dispatch( {}, "name", ScaleBox,
            {Min( 1.89318178413223 ), Max( 40.8931818204959 ), Inc( 1 ), Minor Ticks( 0 ), Rotated Labels( "Parallel" )}
        )
    )
);
Graph Builder(
    Show Control Panel( 0 ),
    Variables( X( :age ), Y( :name ) ),
    Elements( Points( X, Y, Legend( 1 ), Jitter( 1 ) ) ),
    SendToReport( Dispatch( {}, "name", ScaleBox, {Show Major Ticks( 0 )} ) )
);
Graph Builder(
    Show Control Panel( 0 ),
    Variables( X( :age ), Y( :name ) ),
    Elements( Points( X, Y, Legend( 1 ), Jitter( 1 ) ) ),
    SendToReport(
        Dispatch( {}, "name", ScaleBox,
            {Min( 2.33636363636364 ), Max( 41.3363636363636 ), Inc( 1 ), Minor Ticks( 0 ), Show Major Ticks( 0 )}
        )
    )
);

Code Explanation:

1. Set default names.
2. Open data table;
3. Create Graph Builder.
4. Hide control panel.
5. Set X to age, Y to name.
6. Add points element with jitter.
7. Adjust Y axis settings.
8. Create second Graph Builder.
9. Hide control panel.
10. Set X to age, Y to name.
11. Add points element with jitter.
12. Hide major ticks on Y axis.
13. Create third Graph Builder.
14. Hide control panel.
15. Set X to age, Y to name.
16. Add points element with jitter.
17. Adjust Y axis settings again.

Example 192

Summary: Creates a variability chart with nested factors using operator and part configurations, displaying standard deviation charts in Graph Builder.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 534, 454 ),
    Show Control Panel( 0 ),
    Variables( X( :weight ), Y( :height ) ),
    Elements( Points( X, Y, Legend( 6 ) ), Line Of Fit( X, Y, Legend( 8 ) ) ),
    SendToReport(
        Dispatch( {}, "height", ScaleBox,
            {Min( 50 ), Max( 75 ), Inc( 1 ), Minor Ticks( 0 ), LabelRow(), Label Row(
                {Label Orientation( "Angled" ), Automatic Font Size( 0 ), Automatic Tick Marks( 0 )}
            ), Tick Label List( {"sqrt2", "sqrt3", "e", "pi"}, {51.41, 61.73, 65.72, 73.14} )}
        ),
        Dispatch( {}, "weight", ScaleBox,
            {Min( 60 ), Max( 180 ), Inc( 1 ), Minor Ticks( 0 ), LabelRow(), Label Row(
                {Label Orientation( "Vertical" ), Automatic Font Size( 0 ), Automatic Tick Marks( 0 )}
            ), Tick Label List( {"abc", "defghi", "jkl", "mnop", "qrstuv"}, {65, 90, 105, 150, 160} )}
        )
    )
);

Code Explanation:

1. Open data table;
2. Launch Graph Builder.
3. Set window size.
4. Hide control panel.
5. Assign variables X and Y.
6. Add points element.
7. Add line of fit element.
8. Configure height axis.
9. Set height axis limits.
10. Configure weight axis.

Example 193

Summary: Creates a mosaic chart with nested factors using Graph Builder, displaying the relationship between Passenger Class and Survived based on Sex.

Code:

Open("data_table.jmp");
Graph Builder(
    Show Control Panel( 0 ),
    Variables( X( :Passenger Class ), Y( :Survived ), Group X( :Sex ) ),
    Elements( Mosaic( X, Y, Legend( 14 ) ) )
);

Code Explanation:

1. Open data table;
2. Create new Graph Builder window.
3. Hide control panel.
4. Set X variable to Passenger Class.
5. Set Y variable to Survived.
6. Set Group X variable to Sex.
7. Add Mosaic element to graph.
8. Assign legend to element 14.

Example 194

Summary: Creates a mosaic chart with nested factors using Graph Builder, displaying standard deviation charts for analysis.

Code:

Open("data_table.jmp");
Graph Builder(
    Show Control Panel( 0 ),
    Variables( X( :Sex ), X( :Class, Position( 1 ) ), Y( :Survived ), Group X( :Age ) ),
    Elements( Mosaic( X( 1 ), X( 2 ), Y, Legend( 12 ) ) )
);

Code Explanation:

1. Open data table;
2. Launch Graph Builder.
3. Hide control panel.
4. Set X variable: Sex.
5. Set second X variable: Class.
6. Set Y variable: Survived.
7. Set Group X variable: Age.
8. Add Mosaic element.
9. Configure Mosaic for X1.
10. Configure Mosaic for X2 and Y.

Example 195

Summary: Creates three mosaic plots using Graph Builder, with varying variables and groupings to analyze relationships in a data table.

Code:

Open("data_table.jmp");
Graph Builder(
    Show Control Panel( 0 ),
    Variables( X( :Passenger Class ), Y( :Survived ), Group X( :Sex ) ),
    Elements( Mosaic( X, Y, Legend( 14 ) ) )
);
Open("data_table.jmp");
Graph Builder(
    Show Control Panel( 0 ),
    Variables( X( :Sex ), X( :Class, Position( 1 ) ), Y( :Survived ), Group X( :Age ) ),
    Elements( Mosaic( X( 1 ), X( 2 ), Y, Legend( 12 ) ) )
);
Open("data_table.jmp");
Graph Builder( Show Control Panel( 0 ), Variables( X( :Rating ), Y( :Type ), Page( :Year ) ), Elements( Mosaic( X, Y, Legend( 4 ) ) ) );

Code Explanation:

1. Open data_table data
2. Create mosaic plot for Passenger Class vs Survived, grouped by Sex.
3. Open data_table data
4. Create mosaic plot for Sex vs Class vs Survived, grouped by Age.
5. Open data_table data
6. Create mosaic plot for Rating vs Type, paged by Year.

Example 196

Summary: Creates two mosaic plots using Graph Builder, with nested factors and interactive features.

Code:

Open("data_table.jmp");
Graph Builder(
    Show Control Panel( 0 ),
    Variables( X( :Passenger Class ), Y( :Survived ), Group X( :Sex ) ),
    Elements( Mosaic( X, Y, Legend( 14 ) ) )
);
Open("data_table.jmp");
Graph Builder(
    Show Control Panel( 0 ),
    Variables( X( :Sex ), X( :Class, Position( 1 ) ), Y( :Survived ), Group X( :Age ) ),
    Elements( Mosaic( X( 1 ), X( 2 ), Y, Legend( 12 ) ) )
);
Open("data_table.jmp");

Code Explanation:

1. Open data table;
2. Create mosaic plot for Passenger Class vs Survived grouped by Sex.
3. Open data table;
4. Create mosaic plot for Sex, Class, and Survived grouped by Age.
5. Open data table;

Example 197

Summary: Creates a box plot variability chart with nested factors using Graph Builder, displaying standard deviation charts and setting label row nesting for the Y axis.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 534, 418 ),
    Show Control Panel( 0 ),
    Variables( Y( :Time ) ),
    Elements( Box Plot( Y, Legend( 2 ) ) ),
    SendToReport( Dispatch( {}, "Time", ScaleBox, {Label Row Nesting( 6 )} ), Dispatch( {}, "X title", TextEditBox, {Set Wrap( 2 )} ) )
);

Code Explanation:

1. Open data table;
2. Create Graph Builder window.
3. Set window size.
4. Hide control panel.
5. Define Y variable.
6. Add box plot element.
7. Nest label rows for Y axis.
8. Wrap X axis title text.

Example 198

Summary: Creates a variability chart with nested factors using Graph Builder, featuring points and smoother elements, and formats date axis for label row nesting.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 528, 464 ),
    Show Control Panel( 0 ),
    Variables( X( :Date ), Y( :Open ) ),
    Elements( Points( X, Y, Legend( 3 ) ), Smoother( X, Y, Legend( 4 ) ) ),
    SendToReport( Dispatch( {}, "Date", ScaleBox, {Format( "ddMonyyyy", 10 ), Label Row Nesting( 3 )} ) )
);

Code Explanation:

1. Open data table;
2. Create Graph Builder window.
3. Set graph size.
4. Hide control panel.
5. Assign X and Y variables.
6. Add points element.
7. Add smoother element.
8. Format date axis.
9. Set label row nesting.

Example 199

Summary: Creates four variability charts with nested factors using Graph Builder, configuring scale settings and adding points and smoother elements.

Code:

Open("data_table.jmp");
Graph Builder(
    Show Control Panel( 0 ),
    Variables( X( :height ), Y( :weight ), Group Y( :sex ) ),
    Elements( Points( X, Y, Legend( 8 ) ), Smoother( X, Y, Legend( 9 ) ) ),
    SendToReport( Dispatch( {}, "weight", ScaleBox, {Min( 50 ), Max( 150 ), Inc( 50 ), Minor Ticks( 0 )} ) )
);
Graph Builder(
    Show Control Panel( 0 ),
    Variables( X( :height ), Y( :weight ) ),
    Elements( Points( X, Y, Legend( 8 ) ), Smoother( X, Y, Legend( 9 ) ) ),
    SendToReport( Dispatch( {}, "weight", ScaleBox, {Min( 50 ), Max( 149 ), Inc( 50 ), Minor Ticks( 0 )} ) )
);
Graph Builder(
    Show Control Panel( 0 ),
    Variables( X( :height ), Y( :weight ), Group Y( :age ) ),
    Elements( Points( X, Y, Legend( 18 ) ), Smoother( X, Y, Legend( 19 ) ) ),
    SendToReport( Dispatch( {}, "weight", ScaleBox, {Min( 0 ), Max( 220 ), Inc( 100 ), Minor Ticks( 0 )} ) )
);
Graph Builder(
    Show Control Panel( 0 ),
    Variables( X( :height ), Y( :weight ), Group Y( :age ) ),
    Elements( Points( X, Y, Legend( 18 ) ), Smoother( X, Y, Legend( 19 ) ) ),
    SendToReport( Dispatch( {}, "weight", ScaleBox, {Min( 0 ), Max( 220 ), Inc( 200 ), Minor Ticks( 0 )} ) )
);

Code Explanation:

1. Open data table.
2. Create first Graph Builder.
3. Hide control panel.
4. Set X, Y, and group Y variables.
5. Add points and smoother elements.
6. Configure weight scale settings.
7. Create second Graph Builder.
8. Hide control panel.
9. Set X and Y variables.
10. Add points and smoother elements.
11. Configure weight scale settings.
12. Create third Graph Builder.
13. Hide control panel.
14. Set X, Y, and group Y variables.
15. Add points and smoother elements.
16. Configure weight scale settings.
17. Create fourth Graph Builder.
18. Hide control panel.
19. Set X, Y, and group Y variables.
20. Add points and smoother elements.
21. Configure weight scale settings.

Example 200

Summary: Creates a nested variability chart with standard deviation charts, utilizing Graph Builder to visualize data from a specified JMP data table.

Code:

dt = Open("data_table.jmp");
Graph Builder(
    Size( 569, 447 ),
    Show Control Panel( 0 ),
    Variables( X( :Period ), Group Y( :Activity ), Frequency( :Groups ) ),
    Elements( Bar( X, Legend( 12 ) ) )
);

Code Explanation:

1. Open data table;
2. Create Graph Builder.
3. Set window size.
4. Hide control panel.
5. Define X variable.
6. Define Group Y variable.
7. Define Frequency variable.
8. Add Bar element.
9. Assign legend to Bar.

Example 201

Summary: Creates a graph builder with nested factors using operator and part configurations, displaying standard deviation charts.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 880, 396 ),
    Show Control Panel( 0 ),
    Variables( X( :Date ), Y( :High ) ),
    Elements( Points( X, Y, Legend( 3 ) ) ),
    SendToReport(
        Dispatch( {}, "Date", ScaleBox, {Min( 3400272000 ), Max( 3408338304 ), Interval( "Week" ), Inc( 2 ), Minor Ticks( 0 )} )
    )
);

Code Explanation:

1. Open data table;
2. Launch Graph Builder.
3. Set graph size.
4. Hide control panel.
5. Assign variables X and Y.
6. Add points element.
7. Send report to Graph Builder.
8. Configure Date axis scale.
9. Set minimum and maximum values.
10. Define interval as weeks.

Example 202

Summary: Creates a mosaic chart with nested factors using Graph Builder, displaying standard deviation charts for analysis.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 534, 500 ),
    Show Control Panel( 0 ),
    Variables( X( :Sex ), X( :Class, Position( 1 ) ), Y( :Survived ), Group X( :Age ) ),
    Elements( Mosaic( X( 1 ), X( 2 ), Y, Legend( 11 ) ) )
);

Code Explanation:

1. Open data table;
2. Launch Graph Builder.
3. Set window size.
4. Hide control panel.
5. Define X variables: Sex, Class.
6. Define Y variable: Survived.
7. Define Group X variable: Age.
8. Add Mosaic element.
9. Position Class on axis 1.
10. Position Sex on axis 2.

Example 203

Summary: Creates a graph builder with nested factors using operator and part configurations, displaying standard deviation charts.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 492, 460 ),
    Show Control Panel( 0 ),
    Variables( X( :Heart History ), X( :Alcohol use, Position( 1 ) ) ),
    Elements( Points( X( 1 ), X( 2 ), Legend( 21 ) ) )
);

Code Explanation:

1. Open data table;
2. Launch Graph Builder.
3. Set graph size.
4. Hide control panel.
5. Define X-axis variables.
6. Add Alcohol use axis.
7. Plot points element.
8. Assign axes to points.
9. Add legend to points.

Example 204

Summary: Creates a variability chart with nested factors using Graph Builder, displaying standard deviation charts and reference lines.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 534, 464 ),
    Show Control Panel( 0 ),
    Variables( X( :Date ), Y( :Establishments ) ),
    Elements( Points( X, Y, Legend( 3 ) ), Smoother( X, Y, Legend( 4 ) ) ),
    SendToReport(
        Dispatch( {}, "Date", ScaleBox,
            {Label Row Nesting( 2 ), Add Ref Line( 3170101326.70807, "Solid", "Black", "", 1 ), Label Row( 1, Show Major Labels( 0 ) )}
        )
    )
);

Code Explanation:

1. Open data table;
2. Create Graph Builder window.
3. Set graph size.
4. Hide control panel.
5. Assign X and Y variables.
6. Add points element.
7. Add smoother element.
8. Send report settings.
9. Nest date labels.
10. Add reference line.

Example 205

Summary: Creates a variability chart with nested factors using Graph Builder, configuring scale boxes and displaying standard deviation charts.

Code:

Open("data_table.jmp");
Graph Builder(
    show control panel( 0 ),
    Variables(
        X( :age ),
        X( :sex, Position( 1 ) ),
        X( :name, Position( 1 ) ),
        Y( :age ),
        Y( :sex, Position( 1 ) ),
        Y( :name, Position( 1 ) )
    ),
    Elements( Points( X( 1 ), X( 2 ), X( 3 ), Y( 1 ), Y( 2 ), Y( 3 ), Legend( 1 ), Jitter( 1 ) ) ),
    SendToReport(
        Dispatch( {}, "age", ScaleBox, {Show Major Ticks( 1 ), Show Minor Ticks( 0 ), Rotated Labels( "Automatic" )} ),
        Dispatch( {}, "age", ScaleBox( 2 ), {Show Major Ticks( 1 ), Show Minor Ticks( 0 )} )
    )
);

Code Explanation:

1. Open data table;
2. Create Graph Builder window.
3. Hide control panel.
4. Set X variables: age, sex, name.
5. Set Y variables: age, sex, name.
6. Add points element with jitter.
7. Configure age scale box.
8. Configure age scale box (second instance).
9. Show major ticks on age.
10. Hide minor ticks on age.

Example 206

Summary: Creates a graph builder with points and smoother elements to visualize the relationship between height and weight, utilizing Graph Builder.

Code:

dt = Open("data_table.jmp");
dt << Graph Builder(
    Show Control Panel( 0 ),
    Variables( X( :height ), Y( :weight ) ),
    Elements( Points( X, Y, Legend( 2 ) ), Smoother( X, Y, Legend( 3 ) ) )
);

Code Explanation:

1. Open data table.
2. Create Graph Builder object.
3. Hide control panel.
4. Set X variable to height.
5. Set Y variable to weight.
6. Add points element.
7. Add smoother element.
8. Assign legend for points.
9. Assign legend for smoother.
10. Display graph.

Example 207

Summary: Creates a variability chart with nested factors using Graph Builder, displaying standard deviation charts and customizing the Censor axis.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 534, 454 ),
    Show Control Panel( 0 ),
    Variables( X( :Time Cycles ), Y( :Censor ) ),
    Elements( Points( X, Y, Legend( 3 ) ), Smoother( X, Y, Legend( 4 ) ) ),
    SendToReport( Dispatch( {}, "Censor", ScaleBox, {Min( -0.1 ), Max( 1.1 ), Inc( 1 ), Minor Ticks( 1 )} ) )
);

Code Explanation:

1. Open data table;
2. Create Graph Builder window.
3. Set window size.
4. Hide control panel.
5. Define X and Y variables.
6. Add points element.
7. Add smoother element.
8. Customize Censor axis.
9. Set minimum value.
10. Set maximum value.
11. Set increment.
12. Enable minor ticks.

Example 208

Summary: Creates a variability chart with nested factors using Graph Builder, displaying standard deviation charts and customizing the Phase scale.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 534, 470 ),
    Show Control Panel( 0 ),
    Variables( X( :Phase ), Y( :Hours ) ),
    Elements( Bar( X, Y, Legend( 8 ), Label( "Label by Value" ) ) ),
    SendToReport( Dispatch( {}, "Phase", ScaleBox, {Min( 0.5 ), Max( 3.5 ), Inc( 1 ), Minor Ticks( 1 )} ) )
);

Code Explanation:

1. Open data table.
2. Launch Graph Builder.
3. Set graph size.
4. Hide control panel.
5. Assign variables X and Y.
6. Add bar element.
7. Label bars by value.
8. Send report to front.
9. Adjust Phase scale minimum.
10. Adjust Phase scale maximum.
11. Set Phase scale increment.
12. Enable minor ticks on Phase scale.

Example 209

Summary: Creates a variability chart with nested factors using operator and part configurations, displaying standard deviation charts in Graph Builder.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 526, 451 ),
    Show Control Panel( 0 ),
    Variables( X( :age ), Y( :height, Side( "Right" ) ), Y( :weight, Position( 1 ) ) ),
    Elements( Line( X, Y( 2 ), Legend( 8 ) ), Line( X, Y( 1 ), Legend( 9 ) ) ),
    SendToReport(
        Dispatch( {}, "age", ScaleBox, {Label Row( {Automatic Tick Marks( 0 ), Inside Ticks( 1 ), Show Major Ticks( 1 )} )} ),
        Dispatch( {}, "weight", ScaleBox, {Label Row( Inside Ticks( 1 ) )} ),
        Dispatch( {}, "height", ScaleBox, {Label Row( Inside Ticks( 1 ) )} )
    )
);

Code Explanation:

1. Open data table;
2. Create Graph Builder window.
3. Set window size.
4. Hide control panel.
5. Define X variable: age.
6. Define Y variables: height, weight.
7. Plot height on right side.
8. Plot weight on left side.
9. Add line for height.
10. Add line for weight.

Example 210

Summary: Creates a variability chart with nested factors using Graph Builder, displaying standard deviation charts and formatting the date axis.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 526, 454 ),
    Show Control Panel( 0 ),
    Variables( X( :Ozone Concentration ), Y( :date ) ),
    Elements( Points( X, Y, Legend( 3 ) ), Smoother( X, Y, Legend( 4 ) ) ),
    SendToReport(
        Dispatch( {}, "date", ScaleBox,
            {Format( "m/d/y", 10 ), Min( 1893456000 ), Max( 2209032000 ), Interval( "Year" ), Inc( 1 ), Minor Ticks( 1 )}
        )
    )
);

Code Explanation:

1. Open data table;
2. Launch Graph Builder.
3. Set graph size.
4. Hide control panel.
5. Assign variables to axes.
6. Add points element.
7. Add smoother element.
8. Format date axis.
9. Set date axis min.
10. Set date axis max.

Example 211

Summary: Creates two graph builders to visualize and analyze data with nested factors, utilizing Graph Builder's histogram and heatmap elements.

Code:

dt = Open("data_table.jmp");
gb1 = dt << Graph Builder(
    Size( 832, 407 ),
    Show Control Panel( 0 ),
    Variables( X( :"Start Date/Time of Adverse Event"n ) ),
    Elements( Histogram( X, Legend( 3 ) ) ),
    SendToReport(
        Dispatch( {}, "Start Date/Time of Adverse Event", ScaleBox,
            {Min( 2641310733.3532 ), Max( 2710659652.16246 ), Interval( "Year" ), Inc( 1 ), Minor Ticks( 11 )}
        )
    )
);
gb2 = dt << Graph Builder(
    Size( 832, 407 ),
    Show Control Panel( 0 ),
    Variables( X( :"Start Date/Time of Adverse Event"n ) ),
    Elements( Heatmap( X, Legend( 4 ) ) ),
    SendToReport(
        Dispatch( {}, "Start Date/Time of Adverse Event", ScaleBox,
            {Min( 2641310733.3532 ), Max( 2710659652.16246 ), Interval( "Year" ), Inc( 1 ), Minor Ticks( 11 )}
        )
    )
);

Code Explanation:

1. Open data table;
2. Create first graph builder object.
3. Set graph size.
4. Hide control panel.
5. Add X variable.
6. Add histogram element.
7. Customize axis settings.
8. Create second graph builder object.
9. Set graph size.
10. Hide control panel.
11. Add X variable.
12. Add heatmap element.
13. Customize axis settings.

Example 212

Summary: Creates a variability chart with nested factors using Graph Builder, displaying standard deviation charts and configuring legend position.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 613, 324 ),
    Show Control Panel( 0 ),
    Variables( X( :sex ), Y( :height ), Group X( :age ), Overlay( :age ) ),
    Elements( Area( X, Y, Legend( 6 ), Summary Statistic( "N" ) ) )
);

Code Explanation:

1. Open data table;
2. Launch Graph Builder.
3. Set window size.
4. Hide control panel.
5. Assign variables: X, Y, Group X, Overlay.
6. Add area element.
7. Set summary statistic to "N".
8. Configure legend position.

Example 213

Summary: Creates a graph builder with nested factors using operator and part configurations, displaying standard deviation charts.

Code:

dt = Open("data_table.jmp");
gb = dt << Graph Builder(
    Show Control Panel( 0 ),
    Show Legend( 0 ),
    Show Title( 0 ),
    Show Footer( 0 ),
    Show X Axis( 0 ),
    Show Y Axis( 0 ),
    Show X Axis Title( 0 ),
    Show Y Axis Title( 0 ),
    Variables( X( :height ), Y( :weight ), Overlay( :sex ) ),
    Elements( Points( X, Y, Legend( 1 ) ), Smoother( X, Y, Legend( 2 ) ) ),
    Local Data Filter( Add Filter( columns( :age ), Where( :age == 13 ), Display( :age, N Items( 6 ) ) ) )
);
gb << Save Picture( "$TEMP/gb.png", "png" );
gb << close window;

Code Explanation:

1. Open data table.
2. Create Graph Builder object.
3. Hide control panel.
4. Hide legend.
5. Hide title.
6. Hide footer.
7. Hide X axis.
8. Hide Y axis.
9. Hide X axis title.
10. Hide Y axis title.

Example 214

Summary: Creates a contour chart with nested factors using Graph Builder, applying a local data filter for Cut and saving the graph as a PNG image.

Code:

dt3 = Open("data_table.jmp");
gb3 = dt3 << Graph Builder(
    Size( 502, 432 ),
    Show Control Panel( 0 ),
    Show Title( 0 ),
    Show X Axis( 0 ),
    Show Y Axis( 0 ),
    Variables( X( :Carat Weight ), Y( :Price ), Color( :Color ) ),
    Elements( Contour( X, Y, Legend( 3 ) ) ),
    Local Data Filter( Add Filter( columns( :Cut ), Where( :Cut == "Excellent" ), Display( :Cut, N Items( 4 ) ) ) )
);
gb3 << Save Picture( "$TEMP/gb3.png", "png" );
gb3 << close window;

Code Explanation:

1. Open data table;
2. Create Graph Builder object.
3. Set graph size.
4. Hide control panel.
5. Hide title.
6. Hide X axis.
7. Hide Y axis.
8. Define variables: Carat Weight, Price, Color.
9. Add contour element.
10. Apply local data filter for Cut.
11. Save graph as PNG.
12. Close graph window.

Example 215

Summary: Creates a mosaic chart with nested factors using Graph Builder, displaying a standard deviation chart and saving it as a PNG image.

Code:

dt4 = Open("data_table.jmp");
gb4 = dt4 << Graph Builder(
    Size( 534, 450 ),
    Show Control Panel( 0 ),
    Show Legend( 0 ),
    Show Y Axis( 0 ),
    Variables( X( :Type ), Y( :Country ) ),
    Elements( Mosaic( X, Y, Legend( 8 ) ) )
);
gb4 << Save Picture( "$TEMP/gb4.png", "png" );
gb4 << close window;

Code Explanation:

1. Open data table.
2. Create Graph Builder object.
3. Set graph size.
4. Hide control panel.
5. Hide legend.
6. Hide Y axis.
7. Define X and Y variables.
8. Add mosaic element.
9. Save graph as PNG.
10. Close graph window.

Example 216

Summary: Creates a graph builder with age vs. height, utilizing Graph Builder and Points elements.

Code:

dt = Open("data_table.jmp");
dt << run script( "Set Age Value Labels" );
dt << Graph Builder( Variables( X( :age ), Y( :height ) ), Elements( Points( X, Y, Legend( 4 ) ), Smoother( X, Y, Legend( 5 ) ) ) );
jnlFile = "$temp\Example.jrn";
Try( If( exits( jnlFile ), delete( jnlFile ) ) );
Current Report() << save journal( jnlFile );
dt << close window( "No Save" );

Code Explanation:

1. Open data table;
2. Run "Set Age Value Labels" script.
3. Create Graph Builder with age vs. height.
4. Add points and smoother elements.
5. Define journal file path.
6. Delete existing journal file if exists.
7. Save current report as journal.
8. Close dataset without saving.

Example 217

Summary: Creates a Graph Builder plot with points and smoother elements, utilizing X and Y variables from a data table, while also saving a journal file.

Code:

dt = Open("data_table.jmp");
dt << run script( "Set Age Value Labels" );
dt << Graph Builder( Variables( X( :age ), Y( :height ) ), Elements( Points( X, Y, Legend( 4 ) ), Smoother( X, Y, Legend( 5 ) ) ) );
jnlFile = "$temp\Example.jrn";
Try( If( exits( jnlFile ), delete( jnlFile ) ) );
Current Report() << save journal( jnlFile );
dt << close window( "No Save" );
Open( jnlFile );

Code Explanation:

1. Open data table.
2. Run script for age value labels.
3. Create Graph Builder plot.
4. Define X and Y variables.
5. Add points element to plot.
6. Add smoother element to plot.
7. Set journal file path.
8. Delete existing journal file if exists.
9. Save current report as journal.
10. Close data table without saving.
11. Open saved journal file.

Example 218

Summary: Creates a variability chart with nested factors using operator and part configurations, displaying standard deviation charts for better analysis.

Code:

Open("data_table.jmp");
Graph Builder(
    Show Control Panel( 0 ),
    Size( 567, 502 ),
    Parallel Axes( "Y Only" ),
    Variables( X( :Head IC ), Y( :R Leg ), Y( :L Leg ) ),
    Elements( Position( 1, 1 ), Points( X, Y, Legend( 7 ) ), Caption Box( X, Y, Legend( 11 ), Summary Statistic( "Mean" ) ) ),
    Elements( Position( 1, 2 ), Points( X, Y, Legend( 9 ) ), Caption Box( X, Y, Legend( 12 ), Summary Statistic( "Mean" ) ) )
);

Code Explanation:

1. Open data table;
2. Launch Graph Builder.
3. Hide control panel.
4. Set window size.
5. Enable parallel axes.
6. Assign variables: X, Y1, Y2.
7. Add points for Y1 with legend.
8. Add caption box for Y1 mean.
9. Add points for Y2 with legend.
10. Add caption box for Y2 mean.

Example 219

Summary: Creates a variability chart with nested factors using operator and part configurations, displaying standard deviation charts in Graph Builder.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 755, 562 ),
    Show Control Panel( 0 ),
    Parallel Axes( "Y Only" ),
    Variables( X( :Depth ), Y( :Cut ), Y( :Price ) ),
    Elements( Position( 1, 1 ), Points( X, Y, Legend( 29 ) ) ),
    Elements(
        Position( 1, 2 ),
        Points( X, Y, Legend( 6 ), Summary Statistic( "Sum" ) ),
        Smoother( X, Y, Legend( 7 ), Summary Statistic( "Sum" ) )
    ),
    SendToReport(
        Dispatch( {}, "Cut", ScaleBox,
            {Add Ref Line( 1, "Solid", "Black", "", 1 ), Add Ref Line( 2, "Solid", "Black", "", 1 ),
            Add Ref Line( 3, "Solid", "Black", "", 1 ), Add Ref Line( 0, "Solid", "Black", "", 1 )}
        )
    )
);

Code Explanation:

1. Open data table;
2. Create Graph Builder window.
3. Set size 755x562.
4. Hide control panel.
5. Enable parallel axes for Y.
6. Assign variables: Depth (X), Cut (Y), Price (Y).
7. Add points element at position 1,1.
8. Add points and smoother elements at position 1,2.
9. Summarize data with "Sum".
10. Add reference lines to "Cut" scale.

Example 220

Summary: Creates a variability chart with nested factors using Graph Builder, displaying standard deviation charts for TMIN, TMAX, and TAVG.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 762, 546 ),
    Show Control Panel( 0 ),
    Parallel Axes( "Y Only" ),
    Variables( X( :Week of Year ), Y( :TMIN ), Y( :TMAX ), Y( :TAVG ) ),
    Elements( Position( 1, 1 ), Points( X, Y, Legend( 102 ) ), Smoother( X, Y, Legend( 103 ) ) ),
    Elements( Position( 1, 2 ), Points( X, Y, Legend( 104 ) ), Smoother( X, Y, Legend( 105 ) ) ),
    Elements( Position( 1, 3 ), Points( X, Y, Legend( 106 ) ), Smoother( X, Y, Legend( 107 ) ) )
);

Code Explanation:

1. Open data table;
2. Launch Graph Builder.
3. Set window size.
4. Hide control panel.
5. Enable parallel axes for Y.
6. Define X variable.
7. Define first Y variable.
8. Define second Y variable.
9. Define third Y variable.
10. Add points and smoother for TMIN.
11. Add points and smoother for TMAX.
12. Add points and smoother for TAVG.

Example 221

Summary: Creates a Graph Builder window with parallel axes, displaying points for two Y variables and size role, utilizing the Graph Builder platform.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 534, 452 ),
    Show Control Panel( 0 ),
    Parallel Axes( "Y Only" ),
    Variables( X( :Country ), Y( :Horsepower ), Y( :Displacement ), Size( :Weight ) ),
    Elements( Position( 1, 1 ), Points( X, Y, Legend( 49 ) ) ),
    Elements( Position( 1, 2 ), Points( X, Y, Legend( 50 ) ) )
);

Code Explanation:

1. Open data table.
2. Create Graph Builder window.
3. Set window size.
4. Hide control panel.
5. Enable parallel axes.
6. Define X variable.
7. Define first Y variable.
8. Define second Y variable.
9. Define size role.
10. Add points for first Y.
11. Add points for second Y.

Example 222

Summary: Creates a variability chart with nested factors using Graph Builder, displaying standard deviation charts for Calories, Fat, and Carbohydrates.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 645, 460 ),
    Show Control Panel( 0 ),
    Legend Position( "Inside Left" ),
    Parallel Axes( "Y Only" ),
    Variables( X( :Protein ), Y( :Calories ), Y( :Fat ), Y( :Carbohydrates ) ),
    Elements(
        Position( 1, 1 ),
        Smoother( X, Y, Legend( 29 ), Summary Statistic( "Mean" ) ),
        Points( X, Y, Legend( 34 ), Summary Statistic( "Mean" ) )
    ),
    Elements(
        Position( 1, 2 ),
        Smoother( X, Y, Legend( 31 ), Summary Statistic( "Mean" ) ),
        Points( X, Y, Legend( 35 ), Summary Statistic( "Mean" ) )
    ),
    Elements(
        Position( 1, 3 ),
        Smoother( X, Y, Legend( 33 ), Summary Statistic( "Mean" ) ),
        Points( X, Y, Legend( 36 ), Summary Statistic( "Mean" ) )
    ),
    SendToReport( Dispatch( {}, "graph title", TextEditBox, {Set Text( "" )} ) )
);

Code Explanation:

1. Open data_table data
2. Create Graph Builder window.
3. Set window size.
4. Hide control panel.
5. Place legend inside left.
6. Enable parallel Y axes.
7. Define X and Y variables.
8. Add smoother and points for Calories.
9. Add smoother and points for Fat.
10. Add smoother and points for Carbohydrates.

Example 223

Summary: Creates a variability chart with nested factors using operator and part configurations, displaying standard deviation charts in JMP.

Code:

dt = Open("data_table.jmp");
gb = dt << Graph Builder(
    Size( 534, 456 ),
    Show Control Panel( 0 ),
    Variables( X( :Process 1 ), Y( :Process 2 ) ),
    Elements( Points( X, Y, Legend( 2 ) ) ),
    SendToReport(
        Dispatch( {}, "Process 1", ScaleBox,
            {Min( -0.5 ), Max( 22.5 ), Inc( 5 ), Minor Ticks( 4 ), Add Ref Line( 11, "Solid", "Red", "", 2 )}
        )
    )
);
cs = gb << Column Switcher(
    :Process 1,
    {:Process 1, :Process 3, :Process 4, :Process 5, :Process 6, :Process 7},
    Retain Axis Settings( 1 )
);

Code Explanation:

1. Open data table.
2. Create Graph Builder object.
3. Set graph size.
4. Hide control panel.
5. Define X and Y variables.
6. Add points element.
7. Send report settings.
8. Configure X-axis scale.
9. Add reference line to X-axis.
10. Enable column switcher with axis retention.

Example 224

Summary: Creates a variability chart with nested factors using operator and part configurations, displaying standard deviation charts through Graph Builder and Column Switcher.

Code:

dt = Open("data_table.jmp");
gb = dt << Graph Builder(
    Size( 534, 456 ),
    Show Control Panel( 0 ),
    Variables( X( :Process 1 ), Y( :Process 2 ) ),
    Elements( Points( X, Y, Legend( 2 ) ) ),
    SendToReport(
        Dispatch( {}, "Process 1", ScaleBox,
            {Min( -0.5 ), Max( 22.5 ), Inc( 5 ), Minor Ticks( 4 ), Add Ref Line( 11, "Solid", "Red", "", 2 )}
        )
    )
);
cs = gb << Column Switcher(
    :Process 1,
    {:Process 1, :Process 3, :Process 4, :Process 5, :Process 6, :Process 7},
    Retain Axis Settings( 1 )
);
cs << Next;

Code Explanation:

1. Open table.
2. Create graph builder.
3. Set size and hide control panel.
4. Define X and Y variables.
5. Add points element.
6. Configure Process 1 scale.
7. Enable column switcher.
8. Set available columns.
9. Retain axis settings.
10. Move to next column.

Example 225

Summary: Creates a variability chart with nested factors using operator and part configurations, displaying standard deviation charts.

Code:

dt = Open("data_table.jmp");
gb = dt << Graph Builder(
    Size( 534, 456 ),
    Show Control Panel( 0 ),
    Variables( X( :Process 1 ), Y( :Process 2 ) ),
    Elements( Points( X, Y, Legend( 2 ) ) ),
    SendToReport(
        Dispatch( {}, "Process 1", ScaleBox,
            {Min( -0.5 ), Max( 22.5 ), Inc( 5 ), Minor Ticks( 4 ), Add Ref Line( 11, "Solid", "Red", "", 2 )}
        )
    )
);
cs = gb << Column Switcher( :Process 1, {:Process 1, :Process 3, :Process 4, :Process 5, :Process 6, :Process 7} );

Code Explanation:

1. Open data table.
2. Create Graph Builder object.
3. Set graph size.
4. Hide control panel.
5. Define X and Y variables.
6. Add points element.
7. Adjust X-axis settings.
8. Add reference line to X-axis.
9. Enable Column Switcher.
10. Set switchable columns.

Example 226

Summary: Creates a variability chart with nested factors using operator and part configurations, displaying standard deviation charts through Graph Builder.

Code:

dt = Open("data_table.jmp");
gb = dt << Graph Builder(
    Size( 534, 456 ),
    Show Control Panel( 0 ),
    Variables( X( :Process 1 ), Y( :Process 2 ) ),
    Elements( Points( X, Y, Legend( 2 ) ) ),
    SendToReport(
        Dispatch( {}, "Process 1", ScaleBox,
            {Min( -0.5 ), Max( 22.5 ), Inc( 5 ), Minor Ticks( 4 ), Add Ref Line( 11, "Solid", "Red", "", 2 )}
        )
    )
);
cs = gb << Column Switcher( :Process 1, {:Process 1, :Process 3, :Process 4, :Process 5, :Process 6, :Process 7} );
cs << Next;

Code Explanation:

1. Open data table.
2. Create Graph Builder object.
3. Set graph size.
4. Hide control panel.
5. Define X and Y variables.
6. Add points element.
7. Configure X-axis settings.
8. Enable Column Switcher.
9. Set switchable columns.
10. Switch to next column.

Example 227

Summary: Creates a variability chart with nested factors using Graph Builder, featuring a bar element and Column Switchers for Color and Carat Weight.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 531, 450 ),
    Show Control Panel( 0 ),
    Variables( X( :Color ), Y( :Carat Weight ) ),
    Elements( Bar( X, Y, Legend( 4 ) ) ),
    Column Switcher( :Color, {:Color, :Clarity, :Cut, :Report} ),
    Column Switcher( :Carat Weight, {:Carat Weight, :Depth, :Price}, Layout( 1 ) )
);

Code Explanation:

1. Open data table;
2. Create Graph Builder window.
3. Set window size to 531x450.
4. Hide control panel.
5. Set X variable to Color.
6. Set Y variable to Carat Weight.
7. Add bar element.
8. Enable Column Switcher for Color.
9. Configure Column Switcher options for Color.
10. Configure Column Switcher options for Carat Weight.

Example 228

Summary: Creates a variability chart with nested factors using Graph Builder, Column Switchers, and contour elements to display standard deviation charts.

Code:

dt = Open("data_table.jmp");
gb = dt << Graph Builder(
    Size( 522, 456 ),
    Show Control Panel( 0 ),
    Variables( X( :Sepal width ), Y( :Sepal length ), Overlay( :Species ) ),
    Elements( Contour( X, Y, Legend( 6 ), Contour Type 2D( "HDR" ) ) )
);
cs1 = gb << Column Switcher( :Sepal length, {:Sepal length, :Petal length} );
cs2 = gb << Column Switcher( :Sepal width, {:Sepal width, :Petal width} );
cs1 << Remove Column Switcher();

Code Explanation:

1. Open data table;
2. Create Graph Builder window.
3. Set graph size.
4. Hide control panel.
5. Define X, Y, and overlay variables.
6. Add contour element.
7. Switch X column to Sepal length.
8. Add second Column Switcher.
9. Remove first Column Switcher.

Example 229

Summary: Creates a treemap visualization in JMP, using Graph Builder to display US cities colored by maximum degree Fahrenheit in January and sized by lead levels, with interactive filtering capabilities.

Code:

dt = Open("data_table.jmp");
GB1 = dt << Graph Builder(
    Show Control Panel( 0 ),
    Variables( X( :city ), Color( :OZONE ), Size( :POP ) ),
    Elements( Treemap( X, Legend( 4 ) ) ),
    SendToReport(
        Dispatch( {}, "Graph Builder", OutlineBox, {Close( 1 )} ),
        Dispatch( {}, "graph title", TextEditBox, {Set Text( "US Cities Colored by Max deg. F Jan, Sized by Lead Levels" )} )
    )
);
ldf1 = GB1 << Local Data Filter(
    show controls( 1 ),
    show counts( 1 ),
    no outline box( 1 ),
    Add Filter( columns( :Region ), Display( :Region, Height( 102 ) ) ),
    Mode( Select( 0 ), Show( 0 ), Include( 1 ) )
);

Code Explanation:

1. Open table.
2. Create graph builder.
3. Hide control panel.
4. Set X variable.
5. Set color variable.
6. Set size variable.
7. Add treemap element.
8. Close legend box.
9. Set graph title.
10. Add local data filter.

Example 230

Summary: Creates a treemap visualization with nested factors using Graph Builder, and configures a Local Data Filter to filter data by region.

Code:

dt = Open("data_table.jmp");
GB1 = dt << Graph Builder(
    Show Control Panel( 0 ),
    Variables( X( :city ), Color( :OZONE ), Size( :POP ) ),
    Elements( Treemap( X, Legend( 4 ) ) ),
    SendToReport(
        Dispatch( {}, "Graph Builder", OutlineBox, {Close( 1 )} ),
        Dispatch( {}, "graph title", TextEditBox, {Set Text( "US Cities Colored by Max deg. F Jan, Sized by Lead Levels" )} )
    )
);
ldf1 = GB1 << Local Data Filter(
    show controls( 1 ),
    show counts( 1 ),
    no outline box( 1 ),
    Add Filter( columns( :Region ), Display( :Region, Height( 102 ) ) ),
    Mode( Select( 0 ), Show( 0 ), Include( 1 ) )
);
ldf1 << show counts( 0 );
ldf1 << show controls( 0 );

Code Explanation:

1. Open data table.
2. Create Graph Builder object.
3. Hide control panel.
4. Set X, Color, and Size variables.
5. Add Treemap element.
6. Customize graph title.
7. Close graph outline.
8. Add Local Data Filter.
9. Show filter controls and counts.
10. Configure filter for Region column.

Example 231

Summary: Creates a bar chart with nested factors using Graph Builder, featuring a local data filter for sex and customized height scale.

Code:

dt = Open("data_table.jmp");
Graph Builder(
    Size( 449, 250 ),
    Show Control Panel( 0 ),
    Variables( X( :age ), Y( :height ) ),
    Elements( Bar( X, Y, Legend( 8 ) ) ),
    Local Data Filter( Add Filter( columns( :sex ) ) ),
    SendToReport(
        Dispatch( {}, "height", ScaleBox, {Scale( "Log" ), Format( "Best", 12 ), Min( 50 ), Max( 70.38 ), Inc( 1 ), Minor Ticks( 1 )} )
    )
);

Code Explanation:

1. Open data table.
2. Create Graph Builder window.
3. Set window size.
4. Hide control panel.
5. Define X and Y variables.
6. Add bar element.
7. Include local data filter.
8. Add filter for sex column.
9. Modify height scale.
10. Set scale properties.

Example 232

Summary: Creates a variability chart with nested factors using operator and part configurations, displaying standard deviation charts in Graph Builder.

Code:

Open("data_table.jmp") << Graph Builder(
    Size( 633, 539 ),
    Show Control Panel( 0 ),
    Variables( X( :AgeClass ), X( :Gender, Position( 1 ) ), X( :Region, Position( 1 ) ), Y( :Premium USD ) ),
    Elements( Bar( X( 1 ), X( 2 ), X( 3 ), Y, Legend( 3 ) ) ),
    Local Data Filter(
        Width( 160 ),
        Mode( Include( 0 ) ),
        Add Filter(
            columns( :Rating Class, :Branch, :Zone, :Region, :Name( "City(Y/N)" ) ),
            Display( :Rating Class, Size( 160, 68 ) ),
            Display( :Branch, Size( 160, 68 ) ),
            Display( :Zone, Size( 160, 19 ) ),
            Display( :Region, Size( 160, 102 ) ),
            Display( :Name( "City(Y/N)" ), Size( 160, 19 ) ),
            Order By Count( :Rating Class, :Branch, :Region, :Name( "City(Y/N)" ) )
        )
    ),
    Column Switcher( :Premium USD, {:Sample #, :Premium USD, :Claim USD} ),
    SendToReport(
        Dispatch( {}, "Graph Builder", FrameBox,
            {Add Pin Annotation(
                Seg( BarSeg( 1 ) ),
                Index( {9, 9} ),
                Index Row( {2457, 2457} ),
                UniqueID( 648204745 ),
                FoundPt( {660, 247} ),
                Origin( {9.16666666666667, 528.260869565217} ),
                Tag Line( 1 )
            )}
        )
    )
);

Code Explanation:

1. Open data table;
2. Create Graph Builder window.
3. Set window size.
4. Hide control panel.
5. Define X and Y variables.
6. Add bar element.
7. Enable local data filter.
8. Configure filter columns and display settings.
9. Order filters by count.
10. Add column switcher for Premium USD.

Example 233

Summary: Creates a variability chart with nested factors using operator and part configurations, displaying standard deviation charts in Graph Builder.

Code:

Open("data_table.jmp") << Graph Builder(
    Size( 570, 521 ),
    Show Control Panel( 0 ),
    Variables( X( :Year ), Y( :Name( "Room occupancy rate (%)" ) ), Overlay( :Quarter ) ),
    Elements( Line( X, Y, Legend( 7 ) ) ),
    Local Data Filter(
        Conditional,
        Add Filter(
            columns( :Date, :Establishments, :Bed spaces, :Rooms ),
            Where( :Date > 01Mar1998 & :Date <= 01Jun2011 ),
            Where( :Establishments >= 733 & :Establishments < 863 ),
            Where( :Bed spaces > 182022 & :Bed spaces < 224994 )
        )
    ),
    Column Switcher(
        :Name( "Room occupancy rate (%)" ),
        {:Name( "Guest arrivals ('000)" ), :Name( "Guest nights ('000)" ), :Name( "Room nights occupied ('000)" ),
        :Name( "Revenue ($'000)" ), :Name( "Room occupancy rate (%)" ), :Name( "Bed occupancy rate (%)" ),
        :Name( "Average length of stay (days)" )}
    ),
    SendToReport(
        Dispatch( {}, "Year", ScaleBox, {Label Row( Show Major Ticks( 0 ) )} ),
        Dispatch( {}, "Room occupancy rate (%)", ScaleBox, {Min( 54.5305429864253 ), Max( 75 ), Inc( 5 ), Minor Ticks( 1 )} ),
        Dispatch( {}, "graph title", TextEditBox, {Set Text( "Room occupancy rate vs. Year and Quarter" )} )
    )
);

Code Explanation:

1. Open data_table data
2. Launch Graph Builder.
3. Set graph size.
4. Hide control panel.
5. Define variables: X, Y, Overlay.
6. Add line element.
7. Create local data filter.
8. Add conditional filter.
9. Set filter conditions for Date.
10. Set filter conditions for Establishments.
11. Set filter conditions for Bed spaces.
12. Add column switcher.
13. Configure axis labels.
14. Set Y-axis min, max, increment.
15. Set graph title.

Example 234

Summary: Creates a geographic map to visualize data with nested factors, utilizing Graph Builder and Local Data Filter features.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 544, 483 ),
    Show Control Panel( 0 ),
    Variables( X( :Longitude ), Y( :Latitude ), Color( :Max deg. F Jan ), Size( :Lead ) ),
    Elements( Points( X, Y, Legend( 1 ) ) ),
    Local Data Filter( Add Filter( columns( :Lead ), Select Missing( :Lead ) ) ),
    SendToReport(
        Dispatch( {}, "Graph Builder", FrameBox,
            {Background Map( Boundaries( "US States" ) ), Grid Line Order( 2 ), Reference Line Order( 3 )}
        )
    )
);

Code Explanation:

1. Open data table.
2. Create Graph Builder window.
3. Set window size.
4. Hide control panel.
5. Define X, Y, Color, Size variables.
6. Add points element.
7. Apply local data filter.
8. Filter missing values in Lead column.
9. Send report to Graph Builder.
10. Configure background map and grid lines.

Example 235

Summary: Creates a variability chart with nested factors using operator and part configurations, displaying standard deviation charts in Graph Builder.

Code:

Open("data_table.jmp");
Graph Builder(
    Show Control Panel( 0 ),
    Lock Scales( 1 ),
    Variables( X( :Month Number ), Y( :Predicted Temperature ), Y( :Temperature ) ),
    Elements( Position( 1, 1 ), Bar( X, Y, Legend( 37 ) ) ),
    Elements( Position( 1, 2 ), Bar( X, Y, Legend( 38 ) ) ),
    Local Data Filter( Add Filter( columns( :Month Number ), Where( :Month Number >= 1 & :Month Number <= 130.65 ) ) ),
    SendToReport(
        Dispatch( {}, "Month Number", ScaleBox, {Format( "Fixed Dec", 10, 0 ), Min( 0 ), Max( 50 ), Inc( 10 ), Minor Ticks( 1 )} ),
        Dispatch( {}, "Predicted Temperature", ScaleBox,
            {Format( "Fixed Dec", 10, 0 ), Min( 0 ), Max( 100 ), Inc( 20 ), Minor Ticks( 1 )}
        ),
        Dispatch( {}, "Temperature", ScaleBox, {Format( "Fixed Dec", 15, 0 ), Min( 0 ), Max( 100 ), Inc( 20 ), Minor Ticks( 1 )} )
    )
);

Code Explanation:

1. Open data table;
2. Launch Graph Builder.
3. Hide control panel.
4. Lock axis scales.
5. Set X and Y variables.
6. Add first bar element.
7. Add second bar element.
8. Create local data filter.
9. Format Month Number scale.
10. Format Predicted Temperature scale.
11. Format Temperature scale.

Example 236

Summary: Creates a bar chart with nested factors using Graph Builder, enabling local data filtering and displaying age-specific results.

Code:

Open("data_table.jmp");
Graph Builder(
    Variables( X( :sex ), Y( :height ) ),
    Elements( Bar( X, Y, Legend( 5 ) ) ),
    Local Data Filter( Inverse( 1 ), Add Filter( columns( :age ), Where( :age == 15 ), Display( :age, Size( 160, 90 ), List Display ) ) )
);

Code Explanation:

1. Open data table;
2. Create Graph Builder window.
3. Set X variable to sex.
4. Set Y variable to height.
5. Add bar element to graph.
6. Enable local data filter.
7. Invert filter selection.
8. Add age column to filter.
9. Filter for age equal to 15.
10. Display age filter with specific size.

Example 237

Summary: Creates a variability chart with nested factors using Graph Builder, applying local data filters to display standard deviation charts.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 687, 460 ),
    Show Control Panel( 0 ),
    Fit to Window( "Off" ),
    Variables(
        X( :Reported Term for the Adverse Event ),
        Group X( :Planned Treatment for Period 01 ),
        Color( :Body System or Organ Class )
    ),
    Elements( Bar( X, Legend( 2 ) ) ),
    Local Data Filter(
        Add Filter(
            columns( :Body System or Organ Class, :Name( "Severity/Intensity" ), :Serious Event, :Age, :Sex, :Race, :Death Description ),
            Where( :Body System or Organ Class == "BLOOD AND LYMPHATIC SYSTEM DISORDERS" ),
            Where( :Name( "Severity/Intensity" ) == "MILD" ),
            Where( :Serious Event == "N" ),
            Where( :Age >= 46.75 & :Age <= 108 ),
            Where( :Sex == "F" ),
            Where( :Race == "WHITE" ),
            Where( :Death Description == "" ),
            Display( :Body System or Organ Class, Size( 160, 195 ), List Display ),
            Display( :Name( "Severity/Intensity" ), Size( 160, 45 ), List Display ),
            Display( :Race, Size( 160, 60 ), List Display ),
            Display( :Death Description, Size( 160, 225 ), List Display )
        )
    )
);

Code Explanation:

1. Open data table;
2. Create Graph Builder window.
3. Set window size to 687x460.
4. Hide control panel.
5. Disable fit to window.
6. Set X variable to Reported Term for the Adverse Event.
7. Set Group X variable to Planned Treatment for Period 01.
8. Set Color variable to Body System or Organ Class.
9. Add Bar element to graph.
10. Apply local data filter with specified conditions.

Example 238

Summary: Creates a graph builder window with a bar element and local data filter to visualize age distribution by sex and name, utilizing Graph Builder.

Code:

dt = Open("data_table.jmp");
Graph Builder(
    Size( 491, 466 ),
    Variables( X( :age ) ),
    Elements( Bar( X, Legend( 6 ) ) ),
    Local Data Filter(
        Conditional,
        Add Filter(
            columns( :sex, :name ),
            Where( :sex == "F" ),
            Where( :name == {"ALICE", "ELIZABETH", "KATIE", "LOUISE", "MARY", "SUSAN"} ),
            Display( :name, Size( 160, 225 ), List Display )
        )
    )
);

Code Explanation:

1. Open data table.
2. Create Graph Builder window.
3. Set window size.
4. Define X variable as age.
5. Add bar element to graph.
6. Enable local data filter.
7. Set filter condition to AND.
8. Add filter for sex column.
9. Filter for female gender.
10. Add filter for name column.
11. Filter specific names.
12. Display name filter as list.

Example 239

Summary: Creates a bar chart with nested factors using Graph Builder, displaying standard deviation charts and enabling local data filtering by age.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 445, 271 ),
    Show Control Panel( 0 ),
    Variables( X( :sex ) ),
    Elements( Bar( X, Legend( 3 ), Label( "Label by Value" ) ) ),
    Local Data Filter( Add Filter( columns( :age ), Display( :age, Size( 160, 90 ), List Display ) ) )
);

Code Explanation:

1. Open data table;
2. Launch Graph Builder.
3. Set window size.
4. Hide control panel.
5. Assign X variable.
6. Add bar element.
7. Label bars by value.
8. Enable local data filter.
9. Add age column filter.
10. Configure age filter display.

Example 240

Summary: Creates a variability chart with nested factors using Graph Builder, overlaying by sex and filtering data by age 12.

Code:

dt = Open("data_table.jmp");
Graph Builder(
    Size( 416, 259 ),
    Show Control Panel( 0 ),
    Variables( Overlay( :sex ) ),
    Elements( Bar( Legend( 6 ), Label( "Label by Value" ) ) ),
    Local Data Filter( Add Filter( columns( :age ), Where( :age == 12 ), Display( :age, Size( 160, 90 ), List Display ) ) )
);

Code Explanation:

1. Open data table.
2. Launch Graph Builder.
3. Set window size.
4. Hide control panel.
5. Overlay by sex.
6. Add bar element.
7. Label bars by value.
8. Add local data filter.
9. Filter by age 12.
10. Display age filter.

Example 241

Summary: Creates a variability chart with nested factors using Graph Builder, displaying standard deviation charts and configuring graph size, control panel visibility, and legend assignment.

Code:

dt = Open("data_table.jmp");
gb = dt << Graph Builder(
    Size( 522, 492 ),
    Show Control Panel( 0 ),
    Variables( X( :month ), Y( :Ozone Concentration ), Group X( :Summer Months Intervention ) ),
    Elements( Points( X, Y, Legend( 10 ) ), Smoother( X, Y, Legend( 11 ) ) ), 
);

Code Explanation:

1. Open data table.
2. Create Graph Builder object.
3. Set graph size.
4. Hide control panel.
5. Define X, Y, and Group X variables.
6. Add points element.
7. Add smoother element.
8. Assign legend to points.
9. Assign legend to smoother.
10. Display graph.

Example 242

Summary: Creates a variability chart with nested factors using Graph Builder, Local Data Filter, and date range filtering.

Code:

dt = Open("data_table.jmp");
gb = dt << Graph Builder(
    Size( 522, 492 ),
    Show Control Panel( 0 ),
    Variables( X( :month ), Y( :Ozone Concentration ), Group X( :Summer Months Intervention ) ),
    Elements( Points( X, Y, Legend( 10 ) ), Smoother( X, Y, Legend( 11 ) ) ), 
);
ldf = gb << Local Data Filter( Add Filter( columns( :date ), Where( :date >= 16Oct1965 & :date <= 31Aug1968 ) ) );

Code Explanation:

1. Open data table.
2. Create Graph Builder object.
3. Set graph size.
4. Hide control panel.
5. Define X, Y, and Group X variables.
6. Add points and smoother elements.
7. Create local data filter.
8. Add date column filter.
9. Set date range filter criteria.

Example 243

Summary: Creates a bar chart with nested factors using Graph Builder, filtering for females and displaying standard deviation charts.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 424, 374 ),
    Show Control Panel( 0 ),
    Variables( X( :name ), Y( :height ) ),
    Elements( Bar( X, Y, Legend( 4 ) ) ),
    Local Data Filter( Mode( Include( 0 ) ), Add Filter( columns( :sex ), Where( :sex == "F" ), Display( :sex, Check Box Display ) ) )
);

Code Explanation:

1. Open data table;
2. Launch Graph Builder.
3. Set window size.
4. Hide control panel.
5. Assign X variable.
6. Assign Y variable.
7. Add bar element.
8. Configure legend.
9. Enable local data filter.
10. Filter for females.

Example 244

Summary: Creates a heatmap and points graph to visualize age vs. height data, with filtering options for sex.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 445, 273 ),
    Show Control Panel( 0 ),
    Variables( X( :age ), Y( :height ) ),
    Elements( Heatmap( X, Y, Legend( 5 ) ), Points( X, Y, Legend( 6 ) ) ),
    Local Data Filter( Mode( Include( 0 ) ), Add Filter( columns( :sex ), Where( :sex == "F" ) ) )
);

Code Explanation:

1. Open data table.
2. Create Graph Builder window.
3. Set window size.
4. Hide control panel.
5. Define X variable.
6. Define Y variable.
7. Add heatmap element.
8. Add points element.
9. Configure legend for heatmap.
10. Configure legend for points.

Example 245

Summary: Creates a heatmap visualization to analyze height data for individuals with age 12, utilizing Graph Builder and hiding control panel.

Code:

dt = Open("data_table.jmp");
myrows = dt << get rows where( :age == 12 );
dt << select rows( myrows );
dt << exclude( 1 );
dt << hide( 1 );
Graph Builder(
    Size( 422, 194 ),
    Show Control Panel( 0 ),
    Variables( X( :age ), Y( :height ) ),
    Elements( Heatmap( X, Y, Legend( 1 ) ) ),
    Local Data Filter( Add Filter( columns( :sex ) ) )
);

Code Explanation:

1. Open data table.
2. Get rows where age is 12.
3. Select those specific rows.
4. Exclude selected rows.
5. Hide excluded rows.
6. Create Graph Builder window.
7. Set graph size.
8. Hide control panel.
9. Assign X and Y variables.
10. Add heatmap element with legend.

Example 246

Summary: Creates a graph builder with nested factors using operator and part configurations, displaying standard deviation charts for filtered data.

Code:

dt = Open("data_table.jmp");
GB = dt << Graph Builder(
    Size( 522, 648 ),
    Show Control Panel( 0 ),
    Variables( Color( :Name( "Expenditure (1997)" ) ), Shape( :State ) ),
    Elements( Map Shapes( Legend( 2 ) ) ),
    Local Data Filter(
        Add Filter(
            columns( :State, :Name( "Expenditure (1997)" ), :Name( "Student/Faculty Ratio (1997)" ), :Name( "Salary (1997)" ) ),
            Where(
                :State == {"Alaska", "Arizona", "Arkansas", "California", "Colorado", "Connecticut", "Delaware", "District of Columbia",
                "Florida", "Georgia", "Hawaii", "Idaho"}
            ),
            Where( :Name( "Expenditure (1997)" ) <= 4.9561 | :Name( "Expenditure (1997)" ) > 8.4357 ),
            Where( :Name( "Student/Faculty Ratio (1997)" ) >= 13.2 & :Name( "Student/Faculty Ratio (1997)" ) < 21.248 ),
            Display( :State, Size( 149, 170 ), Find( Set Text( "" ) ) )
        )
    )
);
(Report( GB ) << top parent) << journal();

Code Explanation:

1. Open data table;
2. Create Graph Builder object.
3. Set size to 522x648.
4. Hide control panel.
5. Define color and shape variables.
6. Add map shapes element.
7. Enable local data filter.
8. Filter by specified states.
9. Filter by expenditure range.
10. Filter by student/faculty ratio.
11. Display filtered state data.
12. Generate report journal.

Example 247

Summary: Creates a graph builder with nested factors, utilizing local data filters and map shapes to visualize expenditure data across states.

Code:

dt = Open("data_table.jmp");
GB = dt << Graph Builder(
    Size( 522, 648 ),
    Show Control Panel( 0 ),
    Variables( Color( :Name( "Expenditure (1997)" ) ), Shape( :State ) ),
    Elements( Map Shapes( Legend( 2 ) ) ),
    Local Data Filter(
        Add Filter(
            columns( :State, :Name( "Expenditure (1997)" ), :Name( "Student/Faculty Ratio (1997)" ), :Name( "Salary (1997)" ) ),
            Where(
                :State == {"Alaska", "Arizona", "Arkansas", "California", "Colorado", "Connecticut", "Delaware", "District of Columbia",
                "Florida", "Georgia", "Hawaii", "Idaho"}
            ),
            Where( :Name( "Expenditure (1997)" ) <= 4.9561 | :Name( "Expenditure (1997)" ) > 8.4357 ),
            Where( :Name( "Student/Faculty Ratio (1997)" ) >= 13.2 & :Name( "Student/Faculty Ratio (1997)" ) < 21.248 ),
            Display( :State, Size( 149, 170 ), Find( Set Text( "" ) ) )
        )
    )
);
(Report( GB ) << top parent) << journal();
Close( dt, "NoSave" );

Code Explanation:

1. Open table.
2. Create graph builder.
3. Set size and hide control panel.
4. Define color and shape variables.
5. Add map shapes element.
6. Add local data filter.
7. Specify filter columns.
8. Apply state filter.
9. Apply expenditure filter.
10. Apply student/faculty ratio filter.
11. Display state in filter.
12. Save report to journal.
13. Close table without saving.

Example 248

Summary: Creates a bar chart with nested factors using Graph Builder, including missing categories and displaying standard deviation charts.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 451, 344 ),
    Show Control Panel( 0 ),
    Include Missing Categories( 1 ),
    Variables( X( :REASON ) ),
    Elements( Bar( X, Legend( 5 ), Label( "Label by Value" ) ) ),
    Local Data Filter( Add Filter( columns( :JOB ), Display( :JOB, Size( 149, 119 ) ) ) )
);

Code Explanation:

1. Open data table;
2. Launch Graph Builder.
3. Set window size.
4. Hide control panel.
5. Include missing categories.
6. Set X variable.
7. Add bar element.
8. Label by value.
9. Add local data filter.
10. Set filter for JOB column.

Example 249

Summary: Creates a graph builder with nested factors, utilizing local data filters and legend configurations to visualize age and sex values.

Code:

dt = Open("data_table.jmp");
dt << run script( "Set Sex Value Labels" );
dt << run script( "Set Age Value Labels" );
Graph Builder(
    Size( 521, 455 ),
    Variables,
    Elements( Points( Legend( 2 ) ) ),
    Local Data Filter( Add Filter( columns( :age, :sex ), Display( :age, Size( 160, 90 ), List Display ) ) )
);

Code Explanation:

1. Open data table.
2. Run "Set Sex Value Labels" script.
3. Run "Set Age Value Labels" script.
4. Create Graph Builder.
5. Set graph size.
6. Define variables.
7. Add points element.
8. Configure legend for points.
9. Add local data filter.
10. Set filter for age and sex.

Example 250

Summary: Creates a bar chart to visualize the relationship between age and height, filtered by sex, using Graph Builder.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 595, 372 ),
    Show Control Panel( 0 ),
    Variables( X( :age ), Y( :height ) ),
    Elements( Bar( X, Y, Legend( 1 ) ) ),
    Local Data Filter( Add Filter( columns( :sex ), Where( :sex == "F" ), Display( :sex, Check Box Display ), Order By Count( :sex ) ) )
);

Code Explanation:

1. Open data table;
2. Launch Graph Builder.
3. Set graph size.
4. Hide control panel.
5. Assign variables: age, height.
6. Add bar element.
7. Create local data filter.
8. Filter by sex column.
9. Set filter condition: sex = "F".
10. Display filter as checkboxes.

Example 251

Summary: Creates a bar chart with nested factors using Graph Builder, displaying standard deviation charts and filtering data by name and age.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 478, 546 ),
    Show Control Panel( 0 ),
    Variables( X( :sex ), X( :age, Position( 1 ) ) ),
    Elements( Bar( X( 1 ), X( 2 ), Legend( 4 ) ) ),
    Local Data Filter(
        Add Filter(
            columns( :name, :age, :sex ),
            Display( :name, Size( 160, 225 ), List Display ),
            Display( :age, Size( 160, 90 ), List Display )
        )
    )
);

Code Explanation:

1. Open data table.
2. Launch Graph Builder.
3. Set graph size.
4. Hide control panel.
5. Define X variables.
6. Create bar elements.
7. Add local data filter.
8. Configure name filter display.
9. Configure age filter display.
10. Display graph.

Example 252

Summary: Creates a variability chart with nested factors using Graph Builder, assigning X and Y variables, adding points and smoother elements, and applying local data filters to display standard deviation charts.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 445, 563 ),
    Show Control Panel( 0 ),
    Variables( X( :height ), Y( :weight ) ),
    Elements( Points( X, Y, Legend( 30 ) ), Smoother( X, Y, Legend( 31 ) ) ),
    Local Data Filter(
        Add Filter(
            columns( :sibling ages, :countries visited ),
            Match Any( Where( Is Missing( :sibling ages ) | :sibling ages == {"0", "1", "2"} ) ),
            Match At Least( 1.5, Where( Is Missing( :countries visited ) | :countries visited == "Canada" ) ),
            Display( :countries visited, Find( Set Text( "" ) ) )
        )
    )
);

Code Explanation:

1. Open data table.
2. Launch Graph Builder.
3. Set graph size.
4. Hide control panel.
5. Assign X and Y variables.
6. Add points element.
7. Add smoother element.
8. Create local data filter.
9. Add sibling ages filter.
10. Add countries visited filter.

Example 253

Summary: Creates a bar chart with nested factors using Graph Builder, displaying standard deviation charts and filtering data by month, day of week, and airline.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 534, 586 ),
    Show Control Panel( 0 ),
    Variables( X( :Airline ) ),
    Elements( Bar( X, Legend( 7 ) ) ),
    Local Data Filter( Add Filter( columns( :Month, :Day of Week, :Airline ) ) )
);

Code Explanation:

1. Open data table;
2. Launch Graph Builder.
3. Set window size.
4. Hide control panel.
5. Assign X variable.
6. Create bar element.
7. Add legend.
8. Initialize local data filter.
9. Add month filter.
10. Add day of week filter.
11. Add airline filter.

Example 254

Summary: Creates a variability chart with nested factors using Graph Builder, Local Data Filter, and zooming to selection.

Code:

dt = Open("data_table.jmp");
GB1 = dt << Graph Builder(
    Size( 522, 492 ),
    Show Control Panel( 0 ),
    Variables( X( :month ), Y( :Ozone Concentration ), Group X( :Summer Months
Intervention ) ),
    Elements( Points( X, Y, Legend( 10 ) ), Smoother( X, Y, Legend( 11 ) ) ), 
);
LDF1 = GB1 << Local Data Filter( Add Filter( columns( :date ), Where( :date >= 28Jan1961:19:13:20 & :date <= 01Dec1973 ) ) );
obj1 = LDF1 << Get Filter Column( :date );
obj1 << zoom to selection;

Code Explanation:

1. Open data table;
2. Create Graph Builder.
3. Set graph size.
4. Hide control panel.
5. Define X, Y, Group X variables.
6. Add points and smoother elements.
7. Add local data filter.
8. Set date filter criteria.
9. Get filter column object.
10. Zoom to selected date range.

Example 255

Summary: Creates a graph builder object to visualize ozone concentration data, filtered by date range and zoomed in for selected data.

Code:

dt = Open("data_table.jmp");
GB1 = dt << Graph Builder(
    Size( 522, 492 ),
    Show Control Panel( 0 ),
    Variables( X( :month ), Y( :Ozone Concentration ), Group X( :Summer Months
Intervention ) ),
    Elements( Points( X, Y, Legend( 10 ) ), Smoother( X, Y, Legend( 11 ) ) ), 
);
LDF1 = GB1 << Local Data Filter( Add Filter( columns( :date ), Where( :date >= 28Jan1961:19:13:20 & :date <= 01Dec1973 ) ) );
obj1 = LDF1 << Get Filter Column( :date );
obj1 << zoom to selection;
obj1 << reset zoom;

Code Explanation:

1. Open data table.
2. Create graph builder object.
3. Set graph size and hide control panel.
4. Define X, Y, and group variables.
5. Add points and smoother elements.
6. Add local data filter.
7. Set date filter criteria.
8. Get filter column object.
9. Zoom to selected data.
10. Reset zoom to original view.

Example 256

Summary: Creates a variability chart with nested factors using operator and part configurations, displaying standard deviation charts in Graph Builder.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 527, 551 ),
    Show Control Panel( 0 ),
    Variables( X( :weight ), Y( :height ) ),
    Elements( Bar( X, Y, Legend( 7 ), Summary Statistic( "Range" ), Label( "Label by Value" ) ) ),
    Local Data Filter(
        Grouped by AND( 1 ),
        Add Filter(
            columns( :height, :age ),
            Where( :height >= 52.5 & :height <= 59.2 ),
            Where( :age == 12 ),
            Display( :age, Size( 160, 90 ), List Display )
        ),
        Add Filter( columns( :name ), Where( :name == "BARBARA" ), Display( :name, Size( 160, 225 ), List Display ) )
    )
);

Code Explanation:

1. Open data table;
2. Launch Graph Builder.
3. Set graph size.
4. Hide control panel.
5. Define X and Y variables.
6. Add bar element.
7. Configure summary statistic.
8. Enable label by value.
9. Initialize local data filter.
10. Apply height and age filters.

Example 257

Summary: Creates a variability chart with nested factors using operator and part configurations, displaying standard deviation charts in Graph Builder.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 527, 551 ),
    Show Control Panel( 0 ),
    Variables( X( :weight ), Y( :height ) ),
    Elements( Bar( X, Y, Legend( 7 ), Summary Statistic( "Range" ), Label( "Label by Value" ) ) ),
    Local Data Filter(
        Grouped by AND( 1 ),
        Add Filter(
            columns( :height, :age ),
            Where( :height >= 52.5 & :height <= 59.2 ),
            Where( :age == 13 ),
            Display( :age, Size( 160, 90 ), List Display )
        ),
        Add Filter( columns( :name ), Where( :name == "BARBARA" ), Display( :name, Size( 160, 225 ), List Display ) )
    )
);

Code Explanation:

1. Open data table;
2. Create Graph Builder window.
3. Set window size.
4. Hide control panel.
5. Define X and Y variables.
6. Add bar element.
7. Configure summary statistic.
8. Label bars by value.
9. Initialize local data filter.
10. Apply filters for height, age, and name.

Example 258

Summary: Creates a bar chart with nested factors using Graph Builder, configuring local data filters and setting variables for sex.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 331, 316 ),
    Show Control Panel( 0 ),
    Show Legend( 0 ),
    Show Footer( 0 ),
    Variables( X( :sex ) ),
    Elements( Bar( X, Legend( 2 ) ) ),
    Local Data Filter(
        Count Excluded Rows( 0 ),
        Add Filter( columns( :age ), Where( :age == 14 ), Display( :age, Size( 160, 90 ), List Display ) )
    )
);

Code Explanation:

1. Open data table.
2. Launch Graph Builder.
3. Set window size.
4. Hide control panel.
5. Hide legend.
6. Hide footer.
7. Set X variable to sex.
8. Add bar element.
9. Enable local data filter.
10. Configure age filter for 14.

Example 259

Summary: Creates a bar chart with nested factors using Graph Builder, featuring local data filtering and labeling by value.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 528, 465 ),
    Show Control Panel( 0 ),
    Variables( X( :name ), Y( :height ) ),
    Elements( Bar( X, Y, Legend( 17 ), Label( "Label by Value" ) ) ),
    Local Data Filter( Inverse( 1 ), Add Filter( columns( :height ), Where( :height >= 55 & :height <= 70 ) ) )
);

Code Explanation:

1. Open data table.
2. Create Graph Builder window.
3. Set window size.
4. Hide control panel.
5. Define X variable.
6. Define Y variable.
7. Add bar element.
8. Enable legend for bars.
9. Label bars by value.
10. Apply local data filter.

Example 260

Summary: Creates a bar chart with summary statistic N, filtering data by age and height ranges using Local Data Filter in Graph Builder.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 522, 451 ),
    Show Control Panel( 0 ),
    Variables( X( :age ), Y( :height ) ),
    Elements( Bar( X, Y, Legend( 8 ), Summary Statistic( "N" ) ) ),
    Local Data Filter(
        Grouped by AND( 1 ),
        Add Filter( columns( :age ), Where( :age == {12, 15, 16, 17} ), Display( :age, Size( 160, 102 ), "List Display" ) ),
        Add Filter( columns( :height ), Where( :height >= 51 & :height <= 62.7 ) )
    )
);

Code Explanation:

1. Open data table;
2. Create Graph Builder window.
3. Set window size to 522x451.
4. Hide control panel.
5. Set X variable to age.
6. Set Y variable to height.
7. Add bar element with summary statistic N.
8. Enable local data filter.
9. Filter age for specific values.
10. Filter height within range.

Example 261

Summary: Creates a graph builder with nested factors using local data filters and display properties, visualizing manufacturer information.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 525, 456 ),
    Show Control Panel( 0 ),
    Variables( X( :Manufacturer ), Y( :Sugars ) ),
    Elements( Points( X, Y, Legend( 4 ) ) ),
    Local Data Filter(
        Add Filter( columns( :Manufacturer ), Display( :Manufacturer, Size( 202, 114 ), List Display ), Order By Count( :Manufacturer ) )
    )
);

Code Explanation:

1. Open data table;
2. Launch Graph Builder.
3. Set window size.
4. Hide control panel.
5. Assign X variable.
6. Assign Y variable.
7. Add points element.
8. Create local data filter.
9. Add manufacturer filter.
10. Set display properties.

Example 262

Summary: Creates a variability chart with nested factors using Graph Builder, applying local data filters and displaying standard deviation charts.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 600, 544 ),
    Show Control Panel( 0 ),
    Include Missing Categories( 1 ),
    Variables( X( :Position ), Y( :Weight ), Group Y( :Bench ), Overlay( :Fat ) ),
    Elements( Bar( X, Y, Legend( 31 ), Bar Style( "Interval" ) ) ),
    Local Data Filter( Add Filter( columns( :Height ), Where( :Height >= 66 & :Height <= 72.375 ) ) ),
    SendToReport( Dispatch( {}, "400", LegendBox, {Set Title( "" )} ) )
);

Code Explanation:

1. Open data_table data
2. Create Graph Builder window.
3. Set graph size.
4. Hide control panel.
5. Include missing categories.
6. Define X, Y, Group Y, Overlay variables.
7. Add bar element.
8. Apply local data filter.
9. Set legend title to empty.

Example 263

Summary: Creates a bar chart with nested factors using Graph Builder, selecting rows where age is 12 and excluding/hiding unnecessary data.

Code:

dt = Open("data_table.jmp");
myrows = dt << get rows where( :age == 12 );
dt << select rows( myrows );
dt << exclude( 1 );
dt << hide( 1 );
Graph Builder(
    Size( 422, 194 ),
    Show Control Panel( 0 ),
    Variables( X( :age ), Y( :height ) ),
    Elements( Bar( X, Y, Legend( 1 ) ) ),
    Local Data Filter( Add Filter( columns( :sex ) ) )
);

Code Explanation:

1. Open data table;
2. Get rows where age is 12.
3. Select those rows.
4. Exclude selected rows.
5. Hide excluded rows.
6. Create Graph Builder.
7. Set graph size.
8. Hide control panel.
9. Set X variable to age.
10. Set Y variable to height.

Example 264

Summary: Creates a variability chart with nested factors using operator and part configurations, displaying standard deviation charts in Graph Builder.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 845, 545 ),
    Show Control Panel( 0 ),
    Variables( X( :Reported Term for the Adverse Event ), ),
    Elements( Bar( X, Legend( 2 ) ) ),
    Local Data Filter(
        Grouped by AND( 1 ),
        Add Filter(
            columns( :Body System or Organ Class, :Name( "Severity/Intensity" ), :Serious Event ),
            Display( :Body System or Organ Class, Size( 160, 210 ), List Display ),
            Display( :Name( "Severity/Intensity" ), Size( 160, 45 ), List Display )
        ),
        Add Filter( columns( :Age, :Sex, :Race ), Display( :Race, Size( 160, 60 ), List Display ) ),
        Add Filter( columns( :Death Description ), Display( :Death Description, Size( 160, 225 ), List Display ) )
    )
);

Code Explanation:

1. Open data table;
2. Create Graph Builder window.
3. Set window size.
4. Hide control panel.
5. Define X variable.
6. Add bar element.
7. Enable local data filter.
8. Group filters using AND logic.
9. Add first filter group.
10. Add second filter group.
11. Add third filter group.

Example 265

Summary: Creates a variability chart with nested factors using Graph Builder, displaying standard deviation charts and enabling error intervals.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 534, 450 ),
    Show Control Panel( 0 ),
    Variables( X( :sex ), Y( :height ), Y( :weight, Position( 1 ) ), Overlay( :age ) ),
    Elements( Bar( X, Y( 1 ), Y( 2 ), Legend( 6 ), Error Interval( "Range" ) ) ),
    Local Data Filter( Inverse( 1 ), Add Filter( columns( :sex ), Where( :sex == "F" ) ) )
);

Code Explanation:

1. Open data table;
2. Launch Graph Builder.
3. Set window size.
4. Hide control panel.
5. Define X, Y variables.
6. Add overlay variable.
7. Create bar elements.
8. Enable error intervals.
9. Add local data filter.
10. Set filter condition.

Example 266

Summary: Creates a variability chart with nested factors using operator and part configurations, displaying standard deviation charts.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 534, 454 ),
    Show Control Panel( 0 ),
    Variables( X( :height ), Y( :weight ), Overlay( :age ) ),
    Elements(
        Bar( X, Y, Legend( 13 ), Bar Style( "Bullet" ), Summary Statistic( "% of Total" ), Label( "Label by Percent of Total Values" ) )
    ),
    Local Data Filter(
        Mode( Include( 0 ) ),
        Inverse( 1 ),
        Add Filter( columns( :age ), Where( :age == 14 ), Display( :age, Size( 160, 90 ), List Display ) )
    )
);

Code Explanation:

1. Open data table;
2. Create Graph Builder window.
3. Set window size.
4. Hide control panel.
5. Define X, Y, and overlay variables.
6. Add bar element.
7. Set bar style to bullet.
8. Use percent of total summary statistic.
9. Label bars by percent of total values.
10. Add local data filter.

Example 267

Summary: Creates a stacked bar chart with nested factors using Graph Builder, displaying standard deviation charts and enabling local data filtering for specific age values.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 534, 454 ),
    Show Control Panel( 0 ),
    Variables( X( :height ), Y( :weight ), Overlay( :age ) ),
    Elements( Bar( X, Y, Legend( 13 ), Bar Style( "Stacked" ), Summary Statistic( "Sum" ), Label( "Label by Value" ) ) ),
    Local Data Filter(
        Mode( Include( 0 ) ),
        Inverse( 1 ),
        Add Filter( columns( :age ), Where( :age == 13 ), Display( :age, Size( 160, 76 ), List Display ) )
    )
);

Code Explanation:

1. Open data table;
2. Launch Graph Builder.
3. Set window size.
4. Hide control panel.
5. Assign variables: height, weight, age.
6. Create stacked bar chart.
7. Enable local data filter.
8. Set filter mode to include.
9. Apply inverse filter.
10. Add age filter for value 13.

Example 268

Summary: Creates a variability chart with nested factors using operator and part configurations, displaying standard deviation charts in Graph Builder.

Code:

Open("data_table.jmp") << Graph Builder(
    Size( 768, 592 ),
    Show Control Panel( 0 ),
    Variables( X( :Food Category ), Y( :Calories ), Color( :Calories ) ),
    Elements( Bar( X, Y, Legend( 7 ), Summary Statistic( "Sum" ) ) ),
    Local Data Filter( Add Filter( columns( :Item Name ), Display( :Item Name, Size( 160, 225 ), List
Display ) ) ),
    SendToReport(
        Dispatch( {}, "Calories", ScaleBox, {Label Row( Automatic Tick Marks( 0 ) )} ),
        Dispatch( {}, "", ScaleBox, {Label Row( Show Major Ticks( 0 ) )} ),
        Dispatch( {}, "400", ScaleBox,
            {Legend Model( 7, Properties( 0, {gradient( {Color Theme( "Muted Yellow to Red" ), Width( 12 )} )} ) )}
        )
    )
);

Code Explanation:

1. Open data table;
2. Create Graph Builder window.
3. Set window size.
4. Hide control panel.
5. Define X, Y, and color variables.
6. Add bar element with summary statistic.
7. Add local data filter for item names.
8. Configure Calories scale label row.
9. Hide major ticks on scale.
10. Customize legend gradient and width.

Example 269

Summary: Creates a mosaic graph with nested factors, utilizing Graph Builder to visualize data from 'data_table.jmp', and enables local data filtering by color.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 256, 315 ),
    Show Control Panel( 0 ),
    Variables( X( :Cut ), Y( :Clarity ) ),
    Elements( Mosaic( X, Y, Legend( 4 ) ) ),
    Local Data Filter(
        Mode( Show( 0 ) ),
        Add Filter( columns( :Color ), Where( :Color == {"K", "J", "I", "H"} ), Display( :Color, Size( 160, 120 ), List Display ) )
    ),
    SendToReport( Dispatch( {}, "Clarity", ScaleBox, {Reversed Scale} ) )
);

Code Explanation:

1. Open data_table data
2. Create graph builder window.
3. Set window size.
4. Hide control panel.
5. Assign variables for X and Y.
6. Add mosaic element.
7. Enable local data filter.
8. Configure filter mode.
9. Add color filter with conditions.
10. Adjust clarity scale direction.

Example 270

Summary: Creates a mosaic chart with nested factors using Graph Builder, displaying age-based sex distribution.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 534, 448 ),
    Show Control Panel( 0 ),
    Variables( X( :age ), Y( :sex ) ),
    Elements( Mosaic( X, Y, Legend( 4 ) ) ),
    Local Data Filter(
        Inverse( 1 ),
        Add Filter( columns( :age ), Where( :age == {12, 17} ), Display( :age, Size( 160, 90 ), List Display ) )
    )
);

Code Explanation:

1. Open data table.
2. Launch Graph Builder.
3. Set graph size.
4. Hide control panel.
5. Assign variables X and Y.
6. Create mosaic element.
7. Add local data filter.
8. Invert filter logic.
9. Add age filter.
10. Configure age display.

Example 271

Summary: Creates a bar chart with nested factors using Graph Builder, filtering data by height and weight conditions.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 223, 238 ),
    Show Control Panel( 0 ),
    Variables( X( :age ) ),
    Elements( Bar( X, Legend( 3 ) ) ),
    Local Data Filter(
        Mode( Include( 0 ) ),
        Add Filter( columns( :height ) ),
        Add Filter( columns( :weight ), Where( :weight >= 110.5 & :weight <= 172 ) )
    )
);

Code Explanation:

1. Open data table;
2. Create Graph Builder window.
3. Set window size.
4. Hide control panel.
5. Set X-axis variable to age.
6. Add bar element.
7. Enable local data filter.
8. Set filter mode to include.
9. Add height filter.
10. Add weight filter with conditions.

Example 272

Summary: Creates a variability chart with nested factors using operator and part configurations, displaying standard deviation charts.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 376, 289 ),
    Show Control Panel( 0 ),
    Show Legend( 0 ),
    Variables( Color( :Name( "Expenditure (1997)" ) ), Shape( :State ) ),
    Elements( Map Shapes( Legend( 2 ) ) ),
    Local Data Filter(
        Mode( Include( 0 ) ),
        Add Filter(
            columns( :Name( "% Taking (2004)" ) ),
            Where( :Name( "% Taking (2004)" ) < 0.31764 | :Name( "% Taking (2004)" ) > 0.69917 )
        )
    ),
    SendToReport(
        Dispatch( {}, "", ScaleBox, {Min( -122.17689294513 ), Max( -74.6721612970595 ), Inc( 10 ), Minor Ticks( 0 )} ),
        Dispatch( {}, "", ScaleBox( 2 ), {Min( 19.7053232935444 ), Max( 55.2946767064556 ), Inc( 10 ), Minor Ticks( 1 )} ),
        Dispatch( {}, "400", ScaleBox,
            {Legend Model(
                2,
                Properties(
                    0,
                    {gradient(
                        {Color Theme( "White to Green" ), Scale Values( [3.5 4.8 6.1 7.4 8.7 10] ), Label Format( "Fixed Dec", 15, 0 )}
                    )}
                )
            )}
        )
    )
);

Code Explanation:

1. Open data table;
2. Create Graph Builder.
3. Set graph size.
4. Hide control panel.
5. Hide legend.
6. Set color variable.
7. Set shape variable.
8. Add map shapes element.
9. Enable local data filter.
10. Add filter for percentage column.
11. Set x-axis scale properties.
12. Set y-axis scale properties.
13. Customize legend gradient colors.

Example 273

Summary: Creates a bar chart with nested factors using Graph Builder, displaying standard deviation charts and allowing for local data filtering by Brand and Name.

Code:

dt1 = Open("data_table.jmp");
gb1 = dt1 << Graph Builder(
    Size( 528, 631 ),
    Show Control Panel( 0 ),
    Variables( X( :Brand ) ),
    Elements( Bar( X, Legend( 3 ), Label( "Label by Value" ) ) ),
    Local Data Filter( Add Filter( columns( :Brand, :Name ) ) )
);

Code Explanation:

1. Open data table;
2. Create Graph Builder.
3. Set size to 528x631.
4. Hide control panel.
5. Set X variable to Brand.
6. Add bar element.
7. Label bars by value.
8. Add local data filter.
9. Include Brand and Name columns in filter.

Example 274

Summary: Creates two variability charts with nested factors using Graph Builder, displaying standard deviation charts and utilizing local data filters.

Code:

dt1 = Open("data_table.jmp");
gb1 = dt1 << Graph Builder(
    Size( 528, 631 ),
    Show Control Panel( 0 ),
    Variables( X( :Brand ) ),
    Elements( Bar( X, Legend( 3 ), Label( "Label by Value" ) ) ),
    Local Data Filter( Add Filter( columns( :Brand, :Name ) ) )
);
dt2 = Open("data_table.jmp");
gb2 = dt2 << Graph Builder(
    Size( 534, 1079 ),
    Show Control Panel( 0 ),
    Variables( Y( :Meal ) ),
    Elements( Bar( Y, Legend( 2 ), Response Axis( "X" ), Summary Statistic( "N" ), Label( "Label by Percent of Total Values" ) ) ),
    Local Data Filter( Add Filter( columns( :Meal, :Item Name, :Food Category ) ) )
);

Code Explanation:

1. Open data table;
2. Create Graph Builder object.
3. Set graph size.
4. Hide control panel.
5. Set X variable to Brand.
6. Add bar element.
7. Configure bar label.
8. Add local data filter.
9. Open data table;
10. Create second Graph Builder object.

Example 275

Summary: Creates a bar chart with median summary statistics, filtered by Brand and Name, using Graph Builder in JMP.

Code:

dt1 = Open("data_table.jmp");
gb1 = dt1 << Graph Builder(
    Size( 528, 631 ),
    Show Control Panel( 0 ),
    Variables( X( :Brand ) ),
    Elements( Bar( X, Legend( 3 ), Summary Statistic( "Median" ), Label( "Label by Value" ) ) ),
    Local Data Filter( Add Filter( columns( :Brand, :Name ) ) )
);

Code Explanation:

1. Open data table.
2. Create graph builder object.
3. Set graph size.
4. Hide control panel.
5. Set X variable to Brand.
6. Add bar element.
7. Use median summary statistic.
8. Label bars by value.
9. Add local data filter.
10. Filter by Brand and Name.

Example 276

Summary: Creates two variability charts with nested factors using operator and part configurations, displaying standard deviation charts for :Brand and :Meal variables.

Code:

dt1 = Open("data_table.jmp");
gb1 = dt1 << Graph Builder(
    Size( 528, 631 ),
    Show Control Panel( 0 ),
    Variables( X( :Brand ) ),
    Elements( Bar( X, Legend( 3 ), Summary Statistic( "Median" ), Label( "Label by Value" ) ) ),
    Local Data Filter( Add Filter( columns( :Brand, :Name ) ) )
);
dt2 = Open("data_table.jmp");
gb2 = dt2 << Graph Builder(
    Size( 534, 1079 ),
    Show Control Panel( 0 ),
    Variables( Y( :Meal ) ),
    Elements( Bar( Y, Legend( 2 ), Response Axis( "X" ), Summary Statistic( "Max" ), Label( "Label by Percent of Total Values" ) ) ),
    Local Data Filter( Add Filter( columns( :Meal, :Item Name, :Food Category ) ) )
);

Code Explanation:

1. Open data table;
2. Create Graph Builder.
3. Set size to 528x631.
4. Hide control panel.
5. Set X variable to :Brand.
6. Add bar element with median summary.
7. Label bars by value.
8. Add local data filter for :Brand and :Name.
9. Open data table;
10. Create Graph Builder.
11. Set size to 534x1079.
12. Hide control panel.
13. Set Y variable to :Meal.
14. Add bar element with max summary.
15. Label bars by percent of total values.
16. Add local data filter for :Meal, :Item Name, and :Food Category.

Example 277

Summary: Creates a variability chart with nested factors using Graph Builder, utilizing operator and part configurations to display standard deviation charts.

Code:

dt = Open("data_table.jmp");
Graph Builder(
    Size( 541, 519 ),
    Show Control Panel( 0 ),
    Variables( X( :Position Tenure ), Y( :Salary ) ),
    Elements( Points( X, Y, Legend( 19 ), Summary Statistic( "Mean" ) ), Smoother( X, Y, Legend( 20 ) ) ),
    Local Data Filter(
        Add Filter( columns( :Brush Delimited ), Modeling Type( :Brush Delimited, Nominal ), Display( :Brush Delimited, N Items( 12 ) ) )
    )
);

Code Explanation:

1. Open data table.
2. Create Graph Builder window.
3. Set window size.
4. Hide control panel.
5. Assign X and Y variables.
6. Add points element.
7. Add smoother element.
8. Enable local data filter.
9. Add brush delimited filter.
10. Set display options for filter.

Example 278

Summary: Creates a bar chart with nested factors using Graph Builder, enabling local data filtering by sex.

Code:

dt = Open("data_table.jmp");
Graph Builder(
    Size( 595, 372 ),
    Show Control Panel( 0 ),
    Variables( X( :age ), Y( :height ) ),
    Elements( Bar( X, Y, Legend( 1 ) ) ),
    Local Data Filter( Add Filter( columns( :sex ), Display( :sex, Check Box Display ) ) )
);

Code Explanation:

1. Open data table.
2. Launch Graph Builder.
3. Set window size.
4. Hide control panel.
5. Define X and Y variables.
6. Add bar element.
7. Enable local data filter.
8. Add sex column filter.
9. Display sex as checkboxes.

Example 279

Summary: Creates a bar chart with nested factors using Graph Builder, filtering data by sex and displaying standard deviation charts.

Code:

dt = Open("data_table.jmp");
Graph Builder(
    Size( 595, 372 ),
    Show Control Panel( 0 ),
    Variables( X( :age ), Y( :height ) ),
    Elements( Bar( X, Y, Legend( 1 ) ) ),
    Local Data Filter( Add Filter( columns( :sex ), Where( :sex == "F" ), Display( :sex, Check Box Display ) ) )
);

Code Explanation:

1. Open data table.
2. Create Graph Builder window.
3. Set window size.
4. Hide control panel.
5. Assign X variable.
6. Assign Y variable.
7. Add bar element.
8. Create local data filter.
9. Filter by sex column.
10. Display filtered rows.

Example 280

Summary: Creates a graph builder object with points and smoother elements, adding text annotation to frame and displaying picture at scale 1 and 2.

Code:

dt = Open("data_table.jmp");
gb = dt << Graph Builder( Variables( X( :height ), Y( :weight ) ), Elements( Points( X, Y, Legend( 2 ) ), Smoother( X, Y, Legend( 3 ) ) ) );
rgb = gb << report;
annot = rgb[FrameBox( 1 )] << Add Text Annotation( Text( "We need to discuss this at the next meeting." ), Text Box( {65, 35, 200, 77} ) );
annot << select;
New Window( "Example1", rgb << Get Picture( scale( 1 ) ) );
New Window( "Example2", rgb << Get Picture( scale( 2 ) ) );

Code Explanation:

1. Open data table.
2. Create graph builder object.
3. Add X and Y variables.
4. Add points and smoother elements.
5. Retrieve graph report.
6. Add text annotation to frame.
7. Select the annotation.
8. Create new window for picture at scale 1.
9. Create new window for picture at scale 2.

Example 281

Summary: Creates a graph builder with points and smoother, adds text annotation, and generates two new windows with scaled pictures.

Code:

Names Default To Here( 1 );
dt = Open("data_table.jmp");
gb = dt << Graph Builder( Variables( X( :height ), Y( :weight ) ), Elements( Points( X, Y, Legend( 2 ) ), Smoother( X, Y, Legend( 3 ) ) ) );
rgb = gb << report;
annot = rgb[FrameBox( 1 )] << Add Text Annotation( Text( "We need to discuss this at the next meeting." ), Text Box( {65, 35, 200, 77} ) );
annot << select;
New Window( "Example1", rgb << Get Picture( scale( 1 ) ) );
New Window( "Example2", rgb << Get Picture( scale( 2 ) ) );
dt << closewindow();

Code Explanation:

1. Set default names.
2. Open data table;
3. Create Graph Builder.
4. Add X and Y variables.
5. Plot points and smoother.
6. Retrieve report object.
7. Add text annotation.
8. Select annotation.
9. Create new window with picture (scale 1).
10. Create new window with picture (scale 2).
11. Close data table.

Example 282

Summary: Creates a variability chart with nested factors using Graph Builder, assigning variables for sex and height, and customizing legend properties.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 302, 244 ),
    Show Control Panel( 0 ),
    Variables( X( :sex ), Y( :height ), Color( :sex ) ),
    Elements( Bar( X, Y, Legend( 6 ) ) ),
    SendToReport(
        Dispatch( {}, "400", ScaleBox,
            {Legend Model(
                6,
                Properties( 0, {Fill Pattern( "grid dots" )}, Item ID( "F", 1 ) ),
                Properties( 1, {Fill Pattern( "triangle right" )}, Item ID( "M", 1 ) ), 
            )}
        )
    )
);

Code Explanation:

1. Open data table.
2. Create Graph Builder window.
3. Set graph size.
4. Hide control panel.
5. Assign variables: X=sex, Y=height, Color=sex.
6. Add bar element.
7. Customize legend properties.
8. Set fill pattern for "F".
9. Set fill pattern for "M".
10. Send report to display.

Example 283

Summary: Creates a graph with nested factors using Graph Builder, customizing titles and legends, and displaying standard deviation charts.

Code:

dt = Open("data_table.jmp");
dt << Graph Builder(
    Size( 528, 450 ),
    Show Control Panel( 0 ),
    Variables( X( :height ), Y( :weight ) ),
    Elements( Points( X, Y, Legend( 2 ) ), Smoother( X, Y, Legend( 3 ) ) ),
    SendToReport(
        Dispatch( {}, "graph title", TextEditBox,
            {Markup( 1 ), Set Text( "<b></b>plain and <b>boldy</b> and <font color='green'>green</font>" )}
        ),
        Dispatch( {}, "X title", TextEditBox, {Markup( 1 ), Set Text( "plain and
<b>boldy</b> and <font color='green'>green</font>" )} ),
        Dispatch( {}, "Y title", TextEditBox, {Markup( 1 ), Set Text( "plain and
<b>boldy</b> and <font color='green'>green</font>" )} )
    )
);

Code Explanation:

1. Open data table;
2. Launch Graph Builder.
3. Set graph size to 528x450.
4. Hide control panel.
5. Assign height to X axis.
6. Assign weight to Y axis.
7. Add points element.
8. Add smoother element.
9. Customize graph title with markup.
10. Customize X title with markup.
11. Customize Y title with markup.

Example 284

Summary: Creates a graph builder object to visualize the relationship between height and weight, including a cubic line of fit with confidence intervals and root mean square error.

Code:

dt = Open("data_table.jmp");
gb = dt << Graph Builder(
    show control panel( 0 ),
    Variables( X( :height, Size( 23 ) ), Y( :weight, Size( 37 ) ) ),
    Elements(
        Points( X, Y, Legend( 1 ) ),
        Line Of Fit(
            X,
            Y,
            Legend( 4 ),
            Confidence of Fit( 1 ),
            Confidence of Prediction( 1 ),
            Degree( "Cubic" ),
            Root Mean Square Error( 1 ),
            R?( 1 ),
            Equation( 1 )
        )
    )
);
seg = Report( gb )[Framebox( 1 )] << Find Seg( "TextSeg" );

Code Explanation:

1. Open data table.
2. Create graph builder object.
3. Hide control panel.
4. Set X and Y variables.
5. Add points element.
6. Add cubic line of fit.
7. Show confidence intervals.
8. Display root mean square error.
9. Show R-squared value.
10. Display equation.

Example 285

Summary: Creates a graph builder with nested factors using operator and part configurations, displaying standard deviation charts.

Code:

dt = Open("data_table.jmp");
gb = dt << Graph Builder(
    show control panel( 0 ),
    Variables( X( :height, Size( 23 ) ), Y( :weight, Size( 37 ) ) ),
    Elements(
        Points( X, Y, Legend( 1 ) ),
        Line Of Fit(
            X,
            Y,
            Legend( 4 ),
            Confidence of Fit( 1 ),
            Confidence of Prediction( 1 ),
            Degree( "Cubic" ),
            Root Mean Square Error( 1 ),
            R?( 1 ),
            Equation( 1 )
        )
    )
);
seg = Report( gb )[Framebox( 1 )] << Find Seg( "TextSeg" );
seg << Set Text( (seg << Get Text) || " + additional test text" );

Code Explanation:

1. Open data table.
2. Create Graph Builder object.
3. Hide control panel.
4. Set X and Y variables.
5. Add points element.
6. Add cubic line of fit.
7. Enable confidence intervals.
8. Display root mean square error.
9. Show R-squared value.
10. Display equation.
11. Find text segment.
12. Append additional text.

Example 286

Summary: Creates a graph builder with nested factors, displaying an oval annotation and text annotations using Graph Builder.

Code:

dt = Open("data_table.jmp");
aGraphBuilder = dt << Graph Builder(
    Show Control Panel( 0 ),
    Variables( X( :age ) ),
    Elements( Points( X, Legend( 4 ) ) ),
    SendToReport(
        Dispatch( {}, "Graph Builder", FrameBox, Add Simple Shape Annotation( Oval( {156, 141, 257, 288} ), Color( "Blue" ) ) ),
        Dispatch( {}, "Graph Builder", FrameBox,
            Add Text Annotation( Text( "" ), Fixed Size( 0 ), Text Box( {29, 235, 29, 235} ), Filled( 0 ) )
        )
    )
);
aGraphBuilder << Dispatch( {}, "Graph Builder", FrameBox,
    Add Text Annotation(
        Text Box( {480, 227, 472, 251} ),
        Text( "17" ),
        Fixed Size( 0 ), 

        Filled( 0 )
    )
);

Code Explanation:

1. Open data table.
2. Create Graph Builder object.
3. Hide control panel.
4. Set X variable to age.
5. Add points element.
6. Add oval annotation.
7. Add text annotation.
8. Dispatch to add text annotation.
9. Position text annotation.
10. Set text annotation properties.

Example 287

Summary: Creates a graph builder with nested factors, using Graph Builder to display a line element and add text annotation.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 534, 450 ),
    Show Control Panel( 0 ),
    Variables( X( :Cut ), Y( :Price ) ),
    Elements( Line( X, Y, Legend( 8 ) ) ),
    SendToReport(
        Dispatch( {}, "Graph Builder", FrameBox,
            Add Text Annotation(
                Text( "No Fill Annotation" ),
                Fixed Size( 0 ),
                Text Box( {43, 112, 208, 138} ),
                Text Color( "Medium Dark Purple" ),
                Background Color( "Red" ),
                Font( "Sitka Small", 12, "Italic" ),
                Filled( 0 )
            )
        )
    )
);

Code Explanation:

1. Open data table;
2. Create Graph Builder.
3. Set size to 534x450.
4. Hide control panel.
5. Set X variable to Cut.
6. Set Y variable to Price.
7. Add line element.
8. Add text annotation.
9. Set text to "No Fill Annotation".
10. Configure annotation appearance.

Example 288

Summary: Creates a graph builder object with nested factors, displaying points and smoother elements, and adding text annotations to a report.

Code:

Open("data_table.jmp");
gb = Graph Builder(
    Variables( X( :height ), Y( :weight ) ),
    Elements( Points( X, Y, Legend( 2 ) ), Smoother( X, Y, Legend( 3 ) ) ),
    SendToReport(
        Dispatch( {}, "Graph Builder", FrameBox,
            Add Text Annotation(
                Text( "this annotation's background is orange" ),
                Fixed Size( 0 ),
                Text Box( {17, 42, 52, 66} ),
                Background Color( "orange" )
            )
        )
    )
);
gb << save journal( "$temp\JMP258.jrn" );
gb << close window;

Code Explanation:

1. Open data table.
2. Create graph builder object.
3. Set X and Y variables.
4. Add points element.
5. Add smoother element.
6. Send report commands.
7. Add text annotation.
8. Set annotation text.
9. Set fixed size.
10. Set text box coordinates.
11. Set background color.
12. Save graph as journal.
13. Close graph window.

Example 289

Summary: Creates a graph builder with nested factors using operator and part configurations, displaying standard deviation charts.

Code:

Open("data_table.jmp");
gb = Graph Builder(
    Variables( X( :height ), Y( :weight ) ),
    Elements( Points( X, Y, Legend( 2 ) ), Smoother( X, Y, Legend( 3 ) ) ),
    SendToReport(
        Dispatch( {}, "Graph Builder", FrameBox,
            Add Text Annotation(
                Text( "this annotation's background is orange" ),
                Fixed Size( 0 ),
                Text Box( {17, 42, 52, 66} ),
                Background Color( "orange" )
            )
        )
    )
);
gb << save journal( "$temp\JMP258.jrn" );
gb << close window;
Open( "$temp\JMP258.jrn" );

Code Explanation:

1. Open data table.
2. Create Graph Builder object.
3. Set X and Y variables.
4. Add points and smoother elements.
5. Send report to dispatch.
6. Add text annotation.
7. Set annotation text.
8. Set annotation size.
9. Set annotation position.
10. Set annotation background color.
11. Save graph builder as journal.
12. Close graph builder window.
13. Open saved journal file.

Example 290

Summary: Creates a variability chart with nested factors using Graph Builder, displaying standard deviation charts and text annotations.

Code:

dt = Open("data_table.jmp");
gb = dt << Graph Builder(
    Size( 700, 557 ),
    Show Control Panel( 0 ),
    Variables( X( :height ), Y( :weight ), Overlay( :age ) ),
    Elements( Points( X, Y, Legend( 12 ) ), Smoother( X, Y, Legend( 13 ) ) ),
    SendToReport(
        Dispatch( {}, "Graph Builder", FrameBox,
            Add Text Annotation( Text( "Preferences: Annotation Font" ), Fixed Size( 1 ), Text Box( {28, 42, 497, 101} ), Filled( 0 ) )
        )
    )
);

Code Explanation:

1. Open data table.
2. Create Graph Builder object.
3. Set graph size.
4. Hide control panel.
5. Define X, Y, and overlay variables.
6. Add points element.
7. Add smoother element.
8. Send report to Graph Builder.
9. Dispatch to frame box.
10. Add text annotation.

Example 291

Summary: Creates a variability chart with nested factors using operator and part configurations, displaying standard deviation charts in Graph Builder.

Code:

dt = Open("data_table.jmp");
gb = dt << Graph Builder(
    Size( 700, 557 ),
    Show Control Panel( 0 ),
    Variables( X( :height ), Y( :weight ), Overlay( :age ) ),
    Elements( Points( X, Y, Legend( 12 ) ), Smoother( X, Y, Legend( 13 ) ) ),
    SendToReport(
        Dispatch( {}, "Graph Builder", FrameBox,
            Add Text Annotation( Text( "Preferences: Annotation Font" ), Fixed Size( 1 ), Text Box( {28, 42, 497, 101} ), Filled( 0 ) )
        )
    )
);
Set Preferences( Fonts( English( Annotation Font( "Papyrus", 20, "Bold", "Italic" ) ) ) );

Code Explanation:

1. Open data table;
2. Launch Graph Builder.
3. Set graph size.
4. Hide control panel.
5. Define variables: height, weight, age.
6. Add points and smoother elements.
7. Send report to Graph Builder.
8. Add text annotation.
9. Set fixed size for annotation.
10. Specify annotation font preferences.

Example 292

Summary: Creates two Graph Builders to visualize the relationship between height, weight, and sex in a data table, with interactive text annotations.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 570, 556 ),
    Show Control Panel( 0 ),
    Variables( X( :height ), Y( :weight ), Overlay( :sex ) ),
    Elements( Points( X, Y, Legend( 1 ) ), Smoother( X, Y, Legend( 2 ) ) ),
    SendToReport(
        Dispatch( {}, "Graph Builder", FrameBox,
            Add Text Annotation(
                Text( "tallthin123456789101112131415" ),
                Fixed Size( 1 ),
                Text Box( {-34, -104, 4, 207} ),
                Tag Anchor( 310, 294 )
            )
        )
    )
);
Graph Builder(
    Size( 570, 584 ),
    Show Control Panel( 0 ),
    Variables( X( :height ), Y( :weight ), Overlay( :sex ) ),
    Elements( Points( X, Y, Legend( 1 ) ), Smoother( X, Y, Legend( 2 ) ), Caption Box( X, Y, Legend( 3 ), Summary Statistic( "Mean" ) ) ),
    SendToReport(
        Dispatch( {}, "Graph Builder", FrameBox,
            {Add Text Annotation(
                Text( "tag Line Wide border Bottom" ),
                Fixed Size( 1 ),
                Text Box( {103, -12, 568, 8} ),
                Tag Anchor( 273, 153 )
            ), Add Text Annotation(
                Text( "tag
line
tall
right
" ),
                Fixed Size( 1 ),
                Text Box( {-3, -11, 39, 505} ),
                Tag Anchor( 254, 252 )
            ), Add Text Annotation(
                Text( "tagLine wide border top" ),
                Fixed Size( 1 ),
                Text Box( {-10, 521, 560, 541} ),
                Tag Anchor( 160, -100 )
            ), Add Text Annotation(
                Text( "tag
line
tall
left
side
" ),
                Fixed Size( 1 ),
                Text Box( {526, 107, 566, 510} ),
                Tag Anchor( -126, 173 )
            ), Add Text Annotation( Text( "tag line wide tall" ), Fixed Size( 1 ), Text Box( {55, 14, 251, 167} ), Tag Anchor( 221, 179 ) ),
            Add Text Annotation( Text( "tag line wide tall 2" ), Fixed Size( 1 ), Text Box( {270, 321, 511, 502} ), Tag Anchor( 6, -49 ) )}
        )
    )
);

Code Explanation:

1. Open data table.
2. Create first Graph Builder.
3. Set graph size.
4. Hide control panel.
5. Define variables: X(height), Y(weight), Overlay(sex).
6. Add points and smoother elements.
7. Send report with text annotations.
8. Create second Graph Builder.
9. Set graph size.
10. Hide control panel.

Example 293

Summary: Creates a variability chart with nested factors using Graph Builder, configuring the graph size, variables, and element settings to display standard deviation charts.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 552, 493 ),
    Show Control Panel( 0 ),
    Variables( X( :Response ), Y( :"ln(dose)"n ), Group X( :Dose ) ),
    Elements( Bar( X, Y, Legend( 15 ), Error Interval( "None" ) ) ),
    SendToReport(
        Dispatch( {}, "ln(dose)", ScaleBox,
            {Format( "Best", 12 ), Min( -0.0000345389531837771 ), Max( 0.0000473965259385227 ), Inc( 0.00002 ), Minor Ticks( 0 )}
        )
    )
);

Code Explanation:

1. Open data table;
2. Create Graph Builder window.
3. Set graph size.
4. Hide control panel.
5. Assign variables: Response (X), ln(dose) (Y), Dose (Group X).
6. Add bar element.
7. Configure legend and error interval.
8. Adjust ln(dose) scale.
9. Set format to "Best".
10. Define min, max, increment, and minor ticks.

Example 294

Summary: Creates a variability chart with nested factors using Graph Builder, specifying X and Y variables, adding a contour element, and fitting the graph to the window.

Code:

dt = Open("data_table.jmp");
obj = dt << Graph Builder(
    Size( 522, 452 ),
    Show Control Panel( 0 ),
    Variables( X( :Z ), Y( :X ), Y( :Y, Position( 1 ) ) ),
    Elements( Contour( X, Y( 1 ), Y( 2 ), Legend( 5 ) ) )
);
obj << Fit to Window( "Auto" );
Names Default To Here( 1 );

Code Explanation:

1. Open data table;
2. Create Graph Builder object.
3. Set graph size.
4. Hide control panel.
5. Define X and Y variables.
6. Add contour element.
7. Fit graph to window.
8. Set default names scope.

Example 295

Summary: Creates a variability chart with nested factors using Graph Builder, configuring X and Y variables, adding contour elements, and fitting to window.

Code:

dt = Open("data_table.jmp");
obj = dt << Graph Builder(
    Size( 522, 452 ),
    Show Control Panel( 0 ),
    Variables( X( :Z ), Y( :X ), Y( :Y, Position( 1 ) ) ),
    Elements( Contour( X, Y( 1 ), Y( 2 ), Legend( 5 ) ) )
);
obj << Fit to Window( "On" );
Names Default To Here( 1 );

Code Explanation:

1. Open data table;
2. Create Graph Builder object.
3. Set graph size.
4. Hide control panel.
5. Define X, Y variables.
6. Add contour element.
7. Fit graph to window.
8. Set names scope.

Example 296

Summary: Creates a variability chart with nested factors using Graph Builder, displaying standard deviation charts and configuring graph size and control panel settings.

Code:

dt = Open("data_table.jmp");
obj = dt << Graph Builder(
    Size( 522, 452 ),
    Show Control Panel( 0 ),
    Variables( X( :Z ), Y( :X ), Y( :Y, Position( 1 ) ) ),
    Elements( Contour( X, Y( 1 ), Y( 2 ), Legend( 5 ) ) )
);
obj << Fit to Window( "Off" );
Names Default To Here( 1 );

Code Explanation:

1. Open table.
2. Create Graph Builder object.
3. Set graph size.
4. Hide control panel.
5. Define X and Y variables.
6. Add contour element.
7. Disable fit to window.
8. Set names default to here.

Example 297

Summary: Creates a variability chart with nested factors using Graph Builder, displaying standard deviation charts and mapping X to multiple Y variables.

Code:

dt = Open("data_table.jmp");
obj = dt << Graph Builder(
    Size( 522, 452 ),
    Show Control Panel( 0 ),
    Variables( X( :Z ), Y( :X ), Y( :Y, Position( 1 ) ) ),
    Elements( Contour( X, Y( 1 ), Y( 2 ), Legend( 5 ) ) )
);

Code Explanation:

1. Open data table;
2. Create new graph builder.
3. Set size to 522x452.
4. Hide control panel.
5. Set X variable to :Z.
6. Set first Y variable to :X.
7. Set second Y variable to :Y.
8. Add contour element.
9. Map X to first Y.
10. Map X to second Y.

Example 298

Summary: Creates a variability chart with nested factors using Graph Builder, displaying standard deviation charts and custom formatting.

Code:

dt = Open("data_table.jmp");
Graph Builder(
    Show Control Panel( 0 ),
    Variables( X( :Day of Week ), Overlay( :Airline ) ),
    Elements( Bar( X, Legend( 2 ) ) ),
    SendToReport( Dispatch( {}, "", ScaleBox, {Format( "Custom", Formula( Length( Char( value ) ) ), 12 )} ) )
);

Code Explanation:

1. Open data_table data
2. Create Graph Builder object.
3. Hide control panel.
4. Set X variable: Day of Week.
5. Set overlay variable: Airline.
6. Add bar element.
7. Set legend for bars.
8. Send report message.
9. Dispatch to scale box.
10. Format using custom formula.

Example 299

Summary: Creates a box plot graph with nested factors using Graph Builder, displaying standard deviation charts for data analysis.

Code:

Names Default To Here( 1 );
dt = Open("data_table.jmp");
obj = Graph Builder( show control panel( 0 ), Variables( X( :Sex ), Y( :Height ), Group X( :Age ) ), Elements( Box Plot( X, Y ) ) );

Code Explanation:

1. Set default name context.
2. Open data table.
3. Create Graph Builder object.
4. Hide control panel.
5. Define X variable.
6. Define Y variable.
7. Define Group X variable.
8. Add Box Plot element.
9. Assign X and Y roles.
10. Display graph.

Example 300

Summary: Creates a variability chart with nested factors using operator and part configurations, displaying standard deviation charts.

Code:

Names Default To Here( 1 );
dt = Open("data_table.jmp");
obj = Graph Builder(
    Show Control Panel( 0 ),
    Variables( X( :Age ), Y( :Height ), Y( :weight, Position( 1 ) ) ),
    Summary Statistic( "Sum" ),
    Elements( Bar( X, Y( 1 ), Y( 2 ), Legend( 2 ) ) )
);

Code Explanation:

1. Set default names scope.
2. Open data table.
3. Create Graph Builder object.
4. Hide control panel.
5. Define X variable: Age.
6. Define Y variables: Height, Weight.
7. Set summary statistic to Sum.
8. Add bar element.
9. Assign X to bar.
10. Assign Y1 (Height) to bar.

Example 301

Summary: Creates a variability chart with nested factors using Graph Builder, displaying points and smoother elements for height and weight data grouped by sex.

Code:

Open("data_table.jmp");
gb = Graph Builder(
    Size( 534, 489 ),
    Show Control Panel( 0 ),
    Graph Spacing( 0 ),
    Variables( X( :height ), Y( :weight ), Group X( :sex ) ),
    Elements( Points( X, Y, Legend( 1 ) ), Smoother( X, Y, Legend( 2 ) ) )
);

Code Explanation:

1. Open data table;
2. Create graph builder object.
3. Set graph size.
4. Hide control panel.
5. Set graph spacing zero.
6. Define X variable.
7. Define Y variable.
8. Group by sex.
9. Add points element.
10. Add smoother element.

Example 302

Summary: Creates a variability chart with nested factors using Graph Builder, displaying standard deviation charts and configuring graph spacing.

Code:

Open("data_table.jmp");
gb = Graph Builder(
    Size( 534, 489 ),
    Show Control Panel( 0 ),
    Graph Spacing( 0 ),
    Variables( X( :height ), Y( :weight ), Group X( :sex ) ),
    Elements( Points( X, Y, Legend( 1 ) ), Smoother( X, Y, Legend( 2 ) ) )
);
gb << Graph Spacing( 0 );

Code Explanation:

1. Open data table.
2. Create Graph Builder object.
3. Set graph size.
4. Hide control panel.
5. Set graph spacing to zero.
6. Define X, Y, and group variables.
7. Add points element.
8. Add smoother element.
9. Update graph spacing to zero.
10. Display graph.

Example 303

Summary: Creates a graph with nested factors using Graph Builder, setting graph spacing to 5 and displaying points and smoother elements.

Code:

dt = Open("data_table.jmp");
gb = dt << Graph Builder(
    Graph Spacing( 5 ),
    Variables( X( :height ), Y( :weight ), Wrap( :age ) ),
    Elements( Points( X, Y ), Smoother( X, Y ) )
);
gb << Grid Color( "Red" );

Code Explanation:

1. Open data table;
2. Create Graph Builder object.
3. Set graph spacing to 5.
4. Assign height to X axis.
5. Assign weight to Y axis.
6. Wrap age variable.
7. Add points element.
8. Add smoother element.
9. Change grid color to red.

Example 304

Summary: Creates a graph builder object with nested factors, displaying points and smoother elements, and customizing grid settings.

Code:

dt = Open("data_table.jmp");
gb = dt << Graph Builder(
    Graph Spacing( 5 ),
    Variables( X( :height ), Y( :weight ), Wrap( :age ) ),
    Elements( Points( X, Y ), Smoother( X, Y ) )
);
gb << Grid Color( "Red" );
gb << Grid Transparency( 0.5 );

Code Explanation:

1. Open data table.
2. Create graph builder object.
3. Set graph spacing.
4. Assign variables to axes.
5. Add wrap variable.
6. Add points element.
7. Add smoother element.
8. Set grid color to red.
9. Set grid transparency to 0.5.

Example 305

Summary: Creates a variability chart with nested factors using operator and part configurations, displaying standard deviation charts in Graph Builder.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 489, 332 ),
    Show Control Panel( 0 ),
    Variables( X( :height ), Y( :weight ), Color( :weight, Summary Statistic( "Mean" ) ) ),
    Elements( Box Plot( X, Y, Legend( 8 ) ) ),
    SendToReport(
        Dispatch( {}, "Graph Builder", FrameBox,
            Add Pin Annotation(
                Seg( Box Plot Seg( 12 ) ),
                Index( {1, 1} ),
                Index Row( {1, 1} ),
                UniqueID( -1508188671 ),
                FoundPt( {384, 192} ),
                Origin( {65.0758216692074, 106.982735701493} ),
                RightOfCenter( 1 ),
                Tag Line( 1 )
            )
        )
    )
);

Code Explanation:

1. Open data table;
2. Create Graph Builder window.
3. Set window size.
4. Hide control panel.
5. Define X and Y variables.
6. Color by weight mean.
7. Add box plot element.
8. Send report to Graph Builder.
9. Add pin annotation.
10. Position pin annotation.

Example 306

Summary: Creates a box plot graph to visualize the relationship between sex and height, utilizing Graph Builder's Variables and Elements features.

Code:

dt = Open("data_table.jmp");
:age << set selected( 1 );
dt << move selected columns( To First );
gb = dt << Graph Builder(
    Show Control Panel( 0 ),
    Variables( X( :sex ), Y( :height ) ),
    Elements( Box Plot( X, Y, Legend( 2 ) ) ),
    SendToReport(
        Dispatch( {}, "Graph Builder", FrameBox,
            {Set Graphlet(
                Picture(
                    Try(
                        loader = If( Class Exists( "hllLoader" ),
                            New Object( "hllLoader" ),
                            Include( "$BUILTIN_SCRIPTS/hllib.jsl" )
                        );
                        loader:setDebug( 0 );
                        hlp = loader:lazyLoad( "hllPresets" );
                        hlp:launchBar();
                    )
                ),
                Title( "Bar Preset" ),
                Reapply( 1 )
            ), Add Pin Annotation(
                Seg( Box Plot Seg( 1 ) ),
                Index( {1, 1} ),
                Index Row( {1, 1} ),
                UniqueID( 1581195537 ),
                FoundPt( {223, 238} ),
                Origin( {0.134980988593156, 62.1313303167421} ),
                RightOfCenter( 0 ),
                Tag Line( 1 )
            )}
        )
    )
);

Code Explanation:

1. Open data table;
2. Select age column.
3. Move age to first position.
4. Create Graph Builder.
5. Hide control panel.
6. Set X variable to sex.
7. Set Y variable to height.
8. Add box plot element.
9. Load and configure hover labels script.
10. Add pin annotation to graph.

Example 307

Summary: Creates a Graph Builder with nested factors using operator and part configurations, displaying standard deviation charts.

Code:

dt = Open("data_table.jmp");
:age << set selected( 1 );
dt << move selected columns( To First );
gb = dt << Graph Builder(
    Show Control Panel( 0 ),
    Variables( X( :sex ), Y( :height ) ),
    Elements( Box Plot( X, Y, Legend( 2 ) ) ),
    SendToReport(
        Dispatch( {}, "Graph Builder", FrameBox,
            {Set Graphlet(
                Picture(
                    Try(
                        loader = If( Class Exists( "hllLoader" ),
                            New Object( "hllLoader" ),
                            Include( "$BUILTIN_SCRIPTS/hllib.jsl" )
                        );
                        loader:setDebug( 0 );
                        hlp = loader:lazyLoad( "hllPresets" );
                        hlp:launchBar();
                    )
                ),
                Title( "Bar Preset" ),
                Reapply( 1 )
            ), Add Pin Annotation(
                Seg( Box Plot Seg( 1 ) ),
                Index( {1, 1} ),
                Index Row( {1, 1} ),
                UniqueID( 1581195537 ),
                FoundPt( {223, 238} ),
                Origin( {0.134980988593156, 62.1313303167421} ),
                RightOfCenter( 0 ),
                Tag Line( 1 )
            )}
        )
    )
);
dt2 = Open("data_table.jmp");
gb1 = dt2 << Graph Builder(
    Size( 534, 450 ),
    Show Control Panel( 0 ),
    Variables( X( :Gender ), Y( :Glucose ) ),
    Elements( Box Plot( X, Y, Legend( 4 ) ) ),
    SendToReport(
        Dispatch( {}, "Graph Builder", FrameBox,
            {Set Graphlet(
                Picture(
                    Try(
                        loader = If( Class Exists( "hllLoader" ),
                            New Object( "hllLoader" ),
                            Include( "$BUILTIN_SCRIPTS/hllib.jsl" )
                        );
                        loader:setDebug( 0 );
                        hlp = loader:lazyLoad( "hllPresets" );
                        hlp:launchHistogram();
                    )
                ),
                Title( "Histogram Preset" ),
                Reapply( 1 )
            ), Add Pin Annotation(
                Seg( Box Plot Seg( 1 ) ),
                Index( {1, 1} ),
                Index Row( {1, 1} ),
                UniqueID( 1580855777 ),
                FoundPt( {202, 249} ),
                Origin( {0.0755693581780539, 85.516} ),
                RightOfCenter( 0 ),
                Tag Line( 1 )
            )}
        )
    )
);

Code Explanation:

1. Open data table;
2. Select age column.
3. Move selected columns to first.
4. Create Graph Builder for data_table.
5. Disable control panel.
6. Set X as sex, Y as height.
7. Add box plot element.
8. Customize graph with picture and annotation.
9. Open data table;
10. Create Graph Builder for data_table.

Example 308

Summary: Creates a variability chart with nested factors using operator and part configurations, displaying standard deviation charts in Graph Builder.

Code:

dt = Open("data_table.jmp");
Graph Builder(
    Size( 534, 449 ),
    Show Control Panel( 0 ),
    Variables( X( :Type ), Y( :Country ) ),
    Elements( Mosaic( X, Y, Legend( 7 ) ) ),
    SendToReport(
        Dispatch( {}, "Graph Builder", FrameBox,
            {Set Graphlet( Picture( Multiple Correspondence Analysis( Y( :Type ), Cross Table( Show Total( 1 ) ) ) ) ),
            Add Pin Annotation(
                Seg( MosaicSeg( 1 ) ),
                Index( {0, 2} ),
                Index Row( {0, 2} ),
                UniqueID( 1556453402 ),
                FoundPt( {124, 183} ),
                Origin( {0.107822410147992, 0.659033078880407} ),
                RightOfCenter( 0 ),
                Tag Line( 1 )
            )}
        )
    )
);

Code Explanation:

1. Open data table.
2. Create Graph Builder window.
3. Set graph size to 534x449.
4. Hide control panel.
5. Assign X and Y variables.
6. Add mosaic element with legend.
7. Set graphlet to picture.
8. Perform multiple correspondence analysis.
9. Add pin annotation to mosaic segment.
10. Configure annotation properties.

Example 309

Summary: Creates a Graph Builder window with nested factors, displaying standard deviation charts and configuring pin annotations.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 534, 450 ),
    Show Control Panel( 0 ),
    Variables( X( :age ), Y( :height ), Overlay( :weight ) ),
    Elements( Area( X, Y, Legend( 8 ) ) ),
    SendToReport(
        Dispatch( {}, "Graph Builder", FrameBox,
            {Add Pin Annotation(
                Seg( Line Seg( 5 ) ),
                Index( {4, 4} ),
                Index Row( {36, 36} ),
                UniqueID( 692978152 ),
                FoundPt( {691, 368} ),
                Origin( {4.02173913043478, 131.25} ),
                Offset( {-59, -183} ),
                Tag Line( 1 )
            ), Add Pin Annotation(
                Seg( Line Seg( 1 ) ),
                Index( {2, 2} ),
                Index Row( {15, 15} ),
                UniqueID( 686316932 ),
                FoundPt( {525, 445} ),
                Origin( {1.95962732919255, 62.5} ),
                Tag Line( 1 )
            )}
        )
    )
);

Code Explanation:

1. Open data table.
2. Create Graph Builder window.
3. Set window size.
4. Hide control panel.
5. Define variables: X, Y, Overlay.
6. Add area element.
7. Send report to Graph Builder.
8. Add first pin annotation.
9. Configure first annotation properties.
10. Add second pin annotation.
11. Configure second annotation properties.

Example 310

Summary: Creates a variability chart with nested factors using operator and part configurations, displaying standard deviation charts in Graph Builder.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 534, 450 ),
    Show Control Panel( 0 ),
    Variables( X( :age ), Y( :height ), Overlay( :weight ), Size( :weight ) ),
    Elements( Area( X, Y, Legend( 8 ) ) ),
    SendToReport(
        Dispatch( {}, "Graph Builder", FrameBox,
            {Add Pin Annotation(
                Seg( Line Seg( 5 ) ),
                Index( {4, 4} ),
                Index Row( {36, 36} ),
                UniqueID( 692978152 ),
                FoundPt( {691, 368} ),
                Origin( {4.02173913043478, 131.25} ),
                Offset( {-59, -183} ),
                Tag Line( 1 )
            ), Add Pin Annotation(
                Seg( Line Seg( 1 ) ),
                Index( {2, 2} ),
                Index Row( {15, 15} ),
                UniqueID( 686316932 ),
                FoundPt( {525, 445} ),
                Origin( {1.95962732919255, 62.5} ),
                Tag Line( 1 )
            )}
        )
    )
);

Code Explanation:

1. Open data table;
2. Create Graph Builder window.
3. Set window size.
4. Hide control panel.
5. Assign variables: X=age, Y=height, Overlay=weight, Size=weight.
6. Add area element.
7. Send report to Graph Builder.
8. Add pin annotation for first point.
9. Specify segment type for first annotation.
10. Add second pin annotation for another point.

Example 311

Summary: Creates a variability chart with nested factors using Graph Builder, displaying standard deviation charts and configuring bar elements for visualization.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 498, 448 ),
    Show Control Panel( 0 ),
    Variables( X( :age ), Overlay( :sex ) ),
    Elements( Bar( X, Legend( 8 ), Bar Style( "Bullet" ), Response Axis( "X" ), Label( "Label by Value" ) ) ),
    SendToReport(
        Dispatch( {}, "Graph Builder", FrameBox,
            {Add Pin Annotation(
                Seg( BarSeg( 1 ) ),
                Index( {1, 1} ),
                Index Row( {5, 5} ),
                UniqueID( 1 ),
                FoundPt( {241, 282} ),
                Origin( {2.1611909650924, -0.0913846153846154} ),
                Offset( {-66, 121} ),
                RightOfCenter( 0 ),
                Tag Line( 1 )
            ), Add Pin Annotation(
                Seg( BarSeg( 1 ) ),
                Index( {0, 0} ),
                Index Row( {0, 0} ),
                UniqueID( 0 ),
                FoundPt( {213, 226} ),
                Origin( {1.81622176591376, 0.0636923076923077} ),
                Offset( {-76, -133} ),
                RightOfCenter( 0 ),
                Tag Line( 1 )
            )}
        )
    )
);

Code Explanation:

1. Open data table;
2. Launch Graph Builder.
3. Set graph size.
4. Hide control panel.
5. Define X variable as age.
6. Overlay sex variable.
7. Add bar element.
8. Configure bullet style.
9. Set response axis to X.
10. Label bars by value.

Example 312

Summary: Creates a variability chart with nested factors using Graph Builder, displaying standard deviation charts and pin annotations.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 534, 448 ),
    Show Control Panel( 0 ),
    Variables( X( :Position Tenure ), Color( :Salary ) ),
    Elements( Bar( X, Legend( 1 ) ) ),
    SendToReport(
        Dispatch( {}, "Graph Builder", FrameBox,
            Add Pin Annotation(
                Seg( BarSeg( 1 ) ),
                Index( {0, 0} ),
                Index Row( {6, 6} ),
                UniqueID( 757302336 ),
                FoundPt( {133, 131} ),
                Origin( {0.0797101449275363, 200.255102040816} )
            )
        )
    )
);

Code Explanation:

1. Open data table;
2. Create Graph Builder window.
3. Set window size.
4. Hide control panel.
5. Assign X and Color variables.
6. Add bar element.
7. Send report to Graph Builder.
8. Add pin annotation.
9. Specify segment for annotation.
10. Set annotation indices and positions.

Example 313

Summary: Creates a bar graph with nested factors using Graph Builder, displaying standard deviation charts and pin annotations.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 524, 446 ),
    Show Control Panel( 0 ),
    Variables( X( :sex ) ),
    Elements( Bar( X, Legend( 16 ) ) ),
    SendToReport(
        Dispatch( {}, "Graph Builder", FrameBox,
            Add Pin Annotation(
                Seg( BarSeg( 1 ) ),
                Index( {0, 0} ),
                Index Row( {0, 0} ),
                UniqueID( 798863248 ),
                FoundPt( {436, 275} ),
                Origin( {-0.0355648535564854, 15.7552083333333} )
            )
        )
    )
);

Code Explanation:

1. Open data table;
2. Launch Graph Builder.
3. Set graph size.
4. Hide control panel.
5. Assign sex variable to X-axis.
6. Add bar element.
7. Configure legend for bar.
8. Send report to Graph Builder.
9. Add pin annotation.
10. Specify annotation properties.

Example 314

Summary: Creates a variability chart with nested factors using operator and part configurations, displaying standard deviation charts in JMP's Graph Builder.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 552, 496 ),
    Show Control Panel( 0 ),
    Include Missing Categories( 1 ),
    Variables( X( :Date ), Y( :Delay ), Color( :Reason ) ),
    Elements( Bar( X, Y, Legend( 9 ) ) ),
    SendToReport(
        Dispatch( {}, "Graph Builder", FrameBox,
            Add Pin Annotation(
                Seg( BarSeg( 1 ) ),
                Index( {5, 5} ),
                Index Row( {125, 125} ),
                UniqueID( 670285493 ),
                FoundPt( {544, 514} ),
                Origin( {4.79545454545455, 3.37037037037037} ),
                Offset( {-208, -201} ),
                Tag Line,
                Use Gradient( 0 )
            )
        )
    )
);

Code Explanation:

1. Open data table.
2. Create Graph Builder window.
3. Set window size.
4. Hide control panel.
5. Include missing categories.
6. Assign variables: X=Date, Y=Delay, Color=Reason.
7. Add bar element.
8. Send report to Graph Builder.
9. Add pin annotation to graph.
10. Configure pin annotation properties.

Example 315

Summary: Creates a variability chart with nested factors using operator and part configurations, displaying standard deviation charts in JMP.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 598, 448 ),
    Show Control Panel( 0 ),
    Variables( X( :sex ), Y( :name ), Y( :age, Position( 1 ) ) ),
    Elements( Bar( X, Y( 2 ), Y( 1 ), Legend( 6 ) ) ),
    SendToReport(
        Dispatch( {}, "Graph Builder", FrameBox,
            {Add Pin Annotation(
                Seg( BarSeg( 1 ) ),
                Index( {0, 0} ),
                Index Row( {0, 0} ),
                UniqueID( 1561610752 ),
                FoundPt( {204, 251} ),
                Origin( {-0.0952848722986248, 19.1923076923077} ),
                Offset( {-63, 109} ),
                Tag Line( 1 )
            ), Add Pin Annotation(
                Seg( BarSeg( 1 ) ),
                Index( {1, 1} ),
                Index Row( {13, 13} ),
                UniqueID( 1561610753 ),
                FoundPt( {492, 249} ),
                Origin( {1.03634577603143, 19.3974358974359} ),
                Offset( {-277, -92} ),
                Tag Line( 1 )
            )}
        )
    )
);

Code Explanation:

1. Open data table;
2. Launch Graph Builder.
3. Set graph size.
4. Hide control panel.
5. Assign variables: X(sex), Y(name), Y(age).
6. Create bar chart.
7. Add pin annotation for first bar segment.
8. Specify annotation details for first pin.
9. Add another pin annotation for second bar segment.
10. Specify annotation details for second pin.

Example 316

Summary: Creates three bar graphs using Graph Builder, with varying factors and configurations to display standard deviation charts.

Code:

bc = Open("data_table.jmp");
bc << Graph Builder(
    Size( 528, 448 ),
    Show Control Panel( 0 ),
    Variables( X( :age ) ),
    Elements( Bar( X, Legend( 3 ) ) ),
    SendToReport(
        Dispatch( {}, "Graph Builder", FrameBox,
            Add Pin Annotation(
                Seg( BarSeg( 1 ) ),
                Index( {2, 2} ),
                Index Row( {15, 15} ),
                UniqueID( 726565858 ),
                FoundPt( {505, 179} ),
                Origin( {1.90495867768595, 10.7142857142857} )
            )
        )
    )
);
bc << Graph Builder(
    Size( 533, 448 ),
    Show Control Panel( 0 ),
    Variables( X( :age ), Y( :height ) ),
    Elements( Bar( X, Y, Legend( 3 ) ) ),
    SendToReport(
        Dispatch( {}, "Graph Builder", FrameBox,
            Add Pin Annotation(
                Seg( BarSeg( 1 ) ),
                Index( {0, 0} ),
                Index Row( {0, 0} ),
                UniqueID( 735471392 ),
                FoundPt( {338, 359} ),
                Origin( {-0.165289256198347, 27.8571428571429} )
            )
        )
    )
);
bc << Graph Builder(
    Size( 665, 440 ),
    Show Control Panel( 0 ),
    Variables( X( :sex ), Y( :age ) ),
    Elements( Bar( X, Y, Legend( 13 ) ) ),
    SendToReport(
        Dispatch( {}, "Graph Builder", FrameBox,
            Add Pin Annotation(
                Seg( BarSeg( 1 ) ),
                Index( {1, 1} ),
                Index Row( {13, 13} ),
                UniqueID( 1688226945 ),
                FoundPt( {478, 266} ),
                Origin( {0.862179487179487, 2.1544502617801} ),
                Offset( {-213, -89} ),
                Tag Line( 1 )
            )
        )
    )
);

Code Explanation:

1. Open data_table data
2. Create bar graph by age.
3. Hide control panel.
4. Set graph size.
5. Add pin annotation.
6. Create bar graph by age and height.
7. Hide control panel.
8. Set graph size.
9. Add pin annotation.
10. Create bar graph by sex and age.
11. Hide control panel.
12. Set graph size.
13. Add pin annotation.

Example 317

Summary: Creates a variability chart with nested factors using operator and part configurations, displaying standard deviation charts.

Code:

pd = Open("data_table.jmp");
pd << Graph Builder(
    Size( 489, 349 ),
    Show Control Panel( 0 ),
    Variables( X( :Country ), Y( :Type ) ),
    Elements( Bar( X, Y, Legend( 9 ) ) ),
    SendToReport(
        Dispatch( {}, "Graph Builder", FrameBox,
            Add Pin Annotation(
                Seg( BarSeg( 1 ) ),
                Index( {0, 0} ),
                Index Row( {0, 0} ),
                UniqueID( 1692242128 ),
                FoundPt( {151, 227} ),
                Origin( {-0.0240384615384616, 1.51030927835052} ),
                Offset( {-22, 55} ),
                Tag Line( 1 )
            )
        )
    )
);

Code Explanation:

1. Open data table;
2. Create Graph Builder object.
3. Set graph size.
4. Hide control panel.
5. Define X and Y variables.
6. Add bar element.
7. Send report message.
8. Dispatch to Graph Builder frame.
9. Add pin annotation.
10. Specify annotation properties.

Example 318

Summary: Creates a variability chart with nested factors using operator and part configurations, displaying standard deviation charts in Graph Builder.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 482, 461 ),
    Show Control Panel( 0 ),
    Variables( X( :sex ), Y( :height ), Y( :weight, Position( 1 ) ), Overlay( :age ) ),
    Elements( Bar( X, Y( 1 ), Y( 2 ), Legend( 7 ), Bar Style( "Interval" ) ) ),
    SendToReport(
        Dispatch( {}, "Graph Builder", FrameBox,
            Add Pin Annotation(
                Seg( BarSeg( 1 ) ),
                Index( {5, 10} ),
                Index Row( {37, 36} ),
                UniqueID( 697528853 ),
                FoundPt( {311, 248} ),
                Origin( {0.387298747763864, 116.578947368421} )
            )
        )
    )
);

Code Explanation:

1. Open data table;
2. Launch Graph Builder.
3. Set graph size.
4. Hide control panel.
5. Define X, Y, and overlay variables.
6. Create bar elements.
7. Send report commands.
8. Add pin annotation.
9. Specify segment and indices.
10. Set unique ID and found point.

Example 319

Summary: Creates a variability chart with nested factors using operator and part configurations, displaying standard deviation charts in Graph Builder.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 534, 448 ),
    Show Control Panel( 0 ),
    Variables( X( :age ), Y( :height ) ),
    Elements( Bar( X, Y, Legend( 1 ), Summary Statistic( "% of Total" ), Label( "Label by Value" ) ) ),
    SendToReport(
        Dispatch( {}, "Graph Builder", FrameBox,
            Add Pin Annotation(
                Seg( BarSeg( 1 ) ),
                Index( {3, 3} ),
                Index Row( {27, 27} ),
                UniqueID( 735371267 ),
                FoundPt( {593, 365} ),
                Origin( {2.975, 0.133928571428571} )
            )
        )
    )
);

Code Explanation:

1. Open data table;
2. Create Graph Builder window.
3. Set graph size.
4. Hide control panel.
5. Assign X and Y variables.
6. Add bar element.
7. Configure summary statistic.
8. Label bars by value.
9. Send report to Graph Builder.
10. Add pin annotation to graph.

Example 320

Summary: Creates a variability chart with nested factors using Graph Builder, displaying standard deviation charts and adding pin annotations to the graph.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 518, 396 ),
    Show Control Panel( 0 ),
    Variables( X( :sex ) ),
    Elements( Bar( X, Legend( 5 ), Summary Statistic( "% of Total" ), Label( "Label by Value" ) ) ),
    SendToReport(
        Dispatch( {}, "Graph Builder", FrameBox,
            Add Pin Annotation(
                Seg( BarSeg( 1 ) ),
                Index( {0, 0} ),
                Index Row( {0, 0} ),
                UniqueID( 952660592 ),
                FoundPt( {163, 215} ),
                Origin( {-0.081896551724138, 0.312426035502959} ),
                Tag Line( 1 )
            )
        )
    )
);

Code Explanation:

1. Open data table;
2. Launch Graph Builder.
3. Set graph size.
4. Hide control panel.
5. Assign X variable.
6. Create bar element.
7. Configure summary statistic.
8. Label bars by value.
9. Send report to Graph Builder.
10. Add pin annotation to graph.

Example 321

Summary: Creates a bar chart with range style to visualize nested factors using Graph Builder, while also displaying standard deviation charts.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 534, 454 ),
    Show Control Panel( 0 ),
    Variables( X( :height ), X( :weight, Position( 1 ) ), Y( :name ) ),
    Elements( Bar( X( 1 ), X( 2 ), Y, Legend( 4 ), Bar Style( "Range" ) ) ),
    SendToReport(
        Dispatch( {}, "Graph Builder", FrameBox,
            Add Pin Annotation(
                Seg( BarSeg( 1 ) ),
                Index( {34, 68} ),
                Index Row( 36 ),
                UniqueID( 499052802 ),
                FoundPt( {381, 98} ),
                Origin( {127.972972972973, 34.0229591836735} )
            )
        )
    )
);

Code Explanation:

1. Open data table;
2. Launch Graph Builder.
3. Set graph size.
4. Hide control panel.
5. Assign variables: height, weight, name.
6. Create bar chart with range style.
7. Send report to Graph Builder.
8. Add pin annotation to graph.
9. Specify segment for annotation.
10. Set annotation index and row.

Example 322

Summary: Creates a variability chart with nested factors using operator and part configurations, displaying standard deviation charts in Graph Builder.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 534, 448 ),
    Show Control Panel( 0 ),
    Variables( X( :age ), Y( :weight ) ),
    Elements( Bar( X, Y, Legend( 7 ), Summary Statistic( "% of Total" ), Label( "Label by Value" ) ) ),
    SendToReport(
        Dispatch( {}, "Graph Builder", FrameBox,
            Add Pin Annotation(
                Seg( BarSeg( 1 ) ),
                Index( {3, 3} ),
                Index Row( {27, 27} ),
                UniqueID( 501395459 ),
                FoundPt( {603, 307} ),
                Origin( {3.1, 0.159183673469388} )
            )
        )
    )
);

Code Explanation:

1. Open data_table data
2. Create Graph Builder window.
3. Set size to 534x448 pixels.
4. Hide control panel.
5. Assign age to X-axis.
6. Assign weight to Y-axis.
7. Add bar element with summary statistic.
8. Label bars by value.
9. Add pin annotation to graph.
10. Position annotation at specific coordinates.

Example 323

Summary: Creates a variability chart with nested factors using operator and part configurations, displaying standard deviation charts in Graph Builder.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 495, 456 ),
    Show Control Panel( 0 ),
    Variables( X( :height ), X( :weight, Position( 1 ) ) ),
    Elements( Box Plot( X( 1 ), X( 2 ), Legend( 4 ) ) ),
    SendToReport(
        Dispatch( {}, "Graph Builder", FrameBox,
            {Add Pin Annotation(
                Seg( Marker Seg( 1 ) ),
                Index( 0 ),
                Index Row( 4 ),
                UniqueID( 643649600 ),
                FoundPt( {417, 384} ),
                Origin( {53.202479338843, -0.165816326530612} ),
                Offset( {105, 20} ),
                Tag Line( 1 )
            ), Add Pin Annotation(
                Seg( Marker Seg( 2 ) ),
                Index( 0 ),
                Index Row( 39 ),
                UniqueID( 643664704 ),
                FoundPt( {804, 252} ),
                Origin( {173.140495867769, 0.170918367346939} ),
                Offset( {-177, -34} ),
                Tag Line( 1 )
            )}
        )
    )
);

Code Explanation:

1. Open data table;
2. Create Graph Builder window.
3. Set window size.
4. Hide control panel.
5. Assign variables for axes.
6. Add box plot element.
7. Send report to Graph Builder.
8. Add pin annotation to first outlier.
9. Specify annotation details for first outlier.
10. Add pin annotation to second outlier.

Example 324

Summary: Creates a variability chart with nested factors using Graph Builder, displaying standard deviation charts and pin annotations.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 534, 450 ),
    Show Control Panel( 0 ),
    Variables( X( :sex ), Y( :weight ), Overlay( :age ) ),
    Elements( Box Plot( X, Y, Legend( 12 ) ) ),
    SendToReport(
        Dispatch( {}, "Graph Builder", FrameBox,
            Add Pin Annotation(
                Seg( Box Plot Seg( 1 ) ),
                Index( {1, 1} ),
                Index Row( {1, 1} ),
                UniqueID( 649153745 ),
                FoundPt( {367, 312} ),
                Origin( {-0.334368530020704, 109.626703929344} ),
                Tag Line( 1 )
            )
        )
    )
);

Code Explanation:

1. Open data table;
2. Launch Graph Builder.
3. Set graph size.
4. Hide control panel.
5. Define X, Y, and overlay variables.
6. Add box plot element.
7. Send report to Graph Builder.
8. Dispatch to frame box.
9. Add pin annotation.
10. Configure annotation properties.

Example 325

Summary: Creates a variability chart with nested factors using Graph Builder, displaying standard deviation charts and adding pin annotations.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 534, 464 ),
    Show Control Panel( 0 ),
    Variables(
        X( :species ),
        Y( :skull length ),
        Y( :teeth row, Position( 1 ) ),
        Y( :palatine foramen, Position( 1 ) ),
        Y( :jaw length, Position( 1 ) )
    ),
    Elements( Box Plot( X, Y( 1 ), Y( 2 ), Y( 3 ), Y( 4 ), Legend( 5 ) ) ),
    SendToReport(
        Dispatch( {}, "Graph Builder", FrameBox,
            Add Pin Annotation(
                Seg( Marker Seg( 2 ) ),
                Index( 0 ),
                Index Row( 123 ),
                UniqueID( 837129808 ),
                FoundPt( {373, 310} ),
                Origin( {0.320083682008368, 228.448275862069} )
            )
        )
    )
);

Code Explanation:

1. Open data table;
2. Create Graph Builder window.
3. Set graph size.
4. Hide control panel.
5. Define X variable.
6. Define multiple Y variables.
7. Add box plot element.
8. Send report commands.
9. Add pin annotation.
10. Specify annotation details.

Example 326

Summary: Creates a variability chart with nested factors using Graph Builder, displaying standard deviation charts and pin annotations.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 534, 464 ),
    Show Control Panel( 0 ),
    Variables(
        X( :species ),
        Y( :skull length ),
        Y( :teeth row, Position( 1 ) ),
        Y( :palatine foramen, Position( 1 ) ),
        Y( :jaw length, Position( 1 ) )
    ),
    Elements( Box Plot( X, Y( 1 ), Y( 2 ), Y( 3 ), Y( 4 ), Legend( 4 ) ) ),
    SendToReport(
        Dispatch( {}, "Graph Builder", FrameBox,
            {Add Pin Annotation(
                Seg( Marker Seg( 2 ) ),
                Index( 0 ),
                Index Row( 123 ),
                UniqueID( 734299760 ),
                FoundPt( {387, 316} ),
                Origin( {0.305439330543933, 222.701149425287} )
            ), Add Pin Annotation(
                Seg( Marker Seg( 3 ) ),
                Index( 1 ),
                Index Row( 40 ),
                UniqueID( 703599153 ),
                FoundPt( {415, 160} ),
                Origin( {0.715481171548117, 446.83908045977} )
            )}
        )
    )
);

Code Explanation:

1. Open data table;
2. Launch Graph Builder.
3. Set graph size.
4. Hide control panel.
5. Define X variable.
6. Define Y variables.
7. Add box plot element.
8. Send report to Graph Builder.
9. Add first pin annotation.
10. Add second pin annotation.

Example 327

Summary: Creates a box plot variability chart with nested factors using Graph Builder, displaying standard deviation charts and adding pin annotations.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 686, 423 ),
    Show Control Panel( 0 ),
    Variables( X( :height ), X( :weight, Position( 1 ) ), Y( :sex ) ),
    Elements( Box Plot( X( 1 ), X( 2 ), Y, Legend( 8 ) ) ),
    SendToReport(
        Dispatch( {}, "Graph Builder", FrameBox,
            Add Pin Annotation(
                Seg( Marker Seg( 3 ) ),
                Index( 0 ),
                Index Row( 39 ),
                UniqueID( 495748496 ),
                FoundPt( {505, 121} ),
                Origin( {172.479338842975, 1.1530612244898} )
            )
        )
    )
);

Code Explanation:

1. Open data table.
2. Launch Graph Builder.
3. Set window size.
4. Hide control panel.
5. Define variables for axes.
6. Add box plot element.
7. Send report to Graph Builder.
8. Add pin annotation.
9. Specify marker segment.
10. Set annotation properties.

Example 328

Summary: Creates a box plot chart with nested factors using Graph Builder, displaying standard deviation charts and adding pin annotations to specific points.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 489, 355 ),
    Show Control Panel( 0 ),
    Variables( X( :Gas Tank Size ), Y( :Type ) ),
    Elements( Box Plot( X, Y, Legend( 8 ), Jitter( 0 ) ) ),
    SendToReport(
        Dispatch( {}, "Graph Builder", FrameBox,
            Add Pin Annotation(
                Seg( Marker Seg( 2 ) ),
                Index( 1 ),
                Index Row( 100 ),
                UniqueID( 772066097 ),
                FoundPt( {512, 330} ),
                Origin( {16.0851318944844, 0.967576791808874} )
            )
        )
    )
);

Code Explanation:

1. Open data table;
2. Create Graph Builder window.
3. Set graph size to 489x355.
4. Hide control panel.
5. Assign variables: X = Gas Tank Size, Y = Type.
6. Add box plot element.
7. Configure box plot with legend and no jitter.
8. Send report to Graph Builder.
9. Add pin annotation to graph.
10. Position annotation on specific point.

Example 329

Summary: Creates a box plot chart with nested factors using Graph Builder, displaying standard deviation charts and adding pin annotations to specific points.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 489, 355 ),
    Show Control Panel( 0 ),
    Variables( X( :Gas Tank Size ), Y( :Type ) ),
    Elements( Box Plot( X, Y, Legend( 8 ) ) ),
    SendToReport(
        Dispatch( {}, "Graph Builder", FrameBox,
            Add Pin Annotation(
                Seg( Marker Seg( 2 ) ),
                Index( 1 ),
                Index Row( 100 ),
                UniqueID( 817390177 ),
                FoundPt( {292, 357} ),
                Origin( {15.8534136546185, 1.01480637813212} )
            )
        )
    )
);

Code Explanation:

1. Open data table;
2. Create Graph Builder window.
3. Set graph size to 489x355.
4. Hide control panel.
5. Assign variables: X=Gas Tank Size, Y=Type.
6. Add box plot element.
7. Customize legend position.
8. Send report to Graph Builder.
9. Add pin annotation to graph.
10. Position annotation on specific point.

Example 330

Summary: Creates a graph builder object with nested factors using operator and part configurations, displaying standard deviation charts.

Code:

dt = Open("data_table.jmp");
:age << set selected( 1 );
dt << move selected columns( To First );
gb = dt << Graph Builder(
    Size( 528, 450 ),
    Show Control Panel( 0 ),
    Variables( X( :sex ), Y( :height ), Color( :sex ) ),
    Elements( Bar( X, Y, Legend( 4 ) ) ),
    SendToReport(
        Dispatch( {}, "Graph Builder", FrameBox,
            {Set Graphlet(
                Picture(
                    Try(
                        loader = If( Class Exists( "hllLoader" ),
                            New Object( "hllLoader" ),
                            Include( "$BUILTIN_SCRIPTS/hllib.jsl" )
                        );
                        loader:setDebug( 0 );
                        hlp = loader:lazyLoad( "hllPresets" );
                        hlp:launchBox Plot();
                    )
                ),
                Title( "Box Plot Preset" ),
                Reapply( 1 )
            ), Add Pin Annotation(
                Seg( BarSeg( 1 ) ),
                Index( {0, 0} ),
                Index Row( {0, 0} ),
                UniqueID( -514348256 ),
                FoundPt( {422, 340} ),
                Origin( {-0.103305785123967, 31.25} ),
                Tag Line( 1 )
            )}
        )
    )
);

Code Explanation:

1. Open data table.
2. Select age column.
3. Move selected columns to first.
4. Create graph builder object.
5. Set graph size.
6. Hide control panel.
7. Define variables for X, Y, and color.
8. Add bar element to graph.
9. Send report with graphlet settings.
10. Add pin annotation to graph.

Example 331

Summary: Creates a variability chart with nested factors using operator and part configurations, displaying standard deviation charts.

Code:

dt = Open("data_table.jmp");
dt << Graph Builder(
    Size( 528, 450 ),
    Show Control Panel( 0 ),
    Variables( X( :age ) ),
    Elements( Line( X, Legend( 3 ) ) ),
    SendToReport(
        Dispatch( {}, "Graph Builder", FrameBox,
            {Add Pin Annotation(
                Seg( Line Seg( 1 ) ),
                Index( {1, 1} ),
                Index Row( {8, 8} ),
                UniqueID( 648248578 ),
                FoundPt( {448, 298} ),
                Origin( {1.01239669421488, 6.94178571428572} ),
                Tag Line( 1 )
            ), Add Pin Annotation(
                Seg( Line Seg( 1 ) ),
                Index( {4, 4} ),
                Index Row( {34, 34} ),
                UniqueID( 642805224 ),
                FoundPt( {416, 348} ),
                Origin( {3.96280991735537, 3.10301020408163} ),
                Offset( {-274, 21} ),
                Tag Line( 1 )
            )}
        )
    )
);

Code Explanation:

1. Open data table.
2. Launch Graph Builder.
3. Set graph size to 528x450.
4. Hide control panel.
5. Assign age to X-axis.
6. Add line element.
7. Send report to Graph Builder.
8. Add first pin annotation.
9. Add second pin annotation.

Example 332

Summary: Creates a variability chart with nested factors using Graph Builder, displaying points and smoother elements, and adding a pin annotation with specified properties.

Code:

Open( “$SAMPLE_DATA/data_table.jmp” );
Graph Builder(
    Show Control Panel( 0 ),
    Variables( X( :height ), Y( :weight ), Overlay( :sex ) ),
    Elements( Points( X, Y, Legend( 1 ) ), Smoother( X, Y, Legend( 2 ) ) ),
    SendToReport(
        Dispatch( {}, "Graph Builder", FrameBox,
            Add Pin Annotation(
                Seg( Marker Seg( 2 ) ),
                Index( 1 ),
                Index Row( 6 ),
                UniqueID( 600861601 ),
                FoundPt( {334, 217} ),
                Origin( {60.84, 127.402938024123} ),
                Offset( {-213, -61} ),
                Tag Line( 1 ),
                Filled( 0 ),
                Frame Color( "Dark Blue" ),
                Text Color( "Dark Purple" ),
                Background Color( "YellowGreen" ),
                "Font"("Gabriola", 14, "Italic")
            )
        )
    )
);

Code Explanation:

1. Open data table;
2. Create Graph Builder.
3. Hide control panel.
4. Set X to height.
5. Set Y to weight.
6. Overlay by sex.
7. Add points element.
8. Add smoother element.
9. Send report to Graph Builder.
10. Add pin annotation with specified properties.

Example 333

Summary: Creates a variability chart with nested factors using operator and part configurations, displaying standard deviation charts in JMP.

Code:

Open("data_table.jmp");
gb = Graph Builder(
    Show Control Panel( 0 ),
    Variables( X( :brand ), Y( :count ), Overlay( :softness ) ),
    Elements( Bar( X, Y, Legend( 5 ) ) ),
    SendToReport(
        Dispatch( {}, "Graph Builder", FrameBox,
            {DispatchSeg(
                BarSeg( 1 ),
                {Set Graphlet(
                    Picture(
                        Graph Builder(
                            Size( 400, 200 ),
                            Show Control Panel( 0 ),
                            Show Legend( 0 ),
                            Variables( X( :count ) ),
                            Elements( Histogram( X ) )
                        )
                    ),
                    Title( "Overlay Graphlet" )
                )}
            ), Add Pin Annotation(
                Seg( BarSeg( 1 ) ),
                Index( {2, 2} ),
                Index Row( {4, 4} ),
                UniqueID( 764845522 ),
                FoundPt( {230, 234} ),
                Origin( {0.161596958174905, 27.8493495475113} ),
                Tag Line( 1 )
            )}
        )
    )
);
frame = Try( (gb << report)[FrameBox( 1 )], Empty() );
gpin = frame << Get Annotation();

Code Explanation:

1. Open data_table data
2. Create Graph Builder object.
3. Hide control panel.
4. Set X variable to brand.
5. Set Y variable to count.
6. Overlay softness variable.
7. Add bar element.
8. Configure graphlet settings.
9. Add pin annotation to bar segment.
10. Retrieve frame box from report.

Example 334

Summary: Creates a variability chart with nested factors using operator and part configurations, displaying standard deviation charts.

Code:

dt = Open("data_table.jmp");
gb = Graph Builder(
    Show Control Panel( 0 ),
    Variables( X( :brand ), Y( :count ), Overlay( :softness ) ),
    Elements( Bar( X, Y, Legend( 5 ) ) ),
    SendToReport(
        Dispatch( {}, "Graph Builder", FrameBox,
            {DispatchSeg(
                BarSeg( 1 ),
                {Set Graphlet(
                    Picture(
                        Graph Builder(
                            Size( 400, 200 ),
                            Show Control Panel( 0 ),
                            Show Legend( 0 ),
                            Variables( X( :count ) ),
                            Elements( Histogram( X ) )
                        )
                    ),
                    Title( "Overlay Graphlet" )
                )}
            ), Add Pin Annotation(
                Seg( BarSeg( 1 ) ),
                Index( {2, 2} ),
                Index Row( {4, 4} ),
                UniqueID( 764845522 ),
                FoundPt( {230, 234} ),
                Origin( {0.161596958174905, 27.8493495475113} ),
                Tag Line( 1 )
            )}
        )
    )
);
frame = Try( (gb << report)[FrameBox( 1 )], Empty() );
gpin = frame << Get Annotation();
gpin << Launch Graphlet;

Code Explanation:

1. Open data table;
2. Create graph builder object.
3. Hide control panel.
4. Set X, Y, and overlay variables.
5. Add bar element with legend.
6. Send report with graphlet settings.
7. Create picture graphlet with histogram.
8. Set graphlet title.
9. Add pin annotation to graph.
10. Launch graphlet from annotation.

Example 335

Summary: Creates a variability chart with nested factors using operator and part configurations, displaying standard deviation charts in JMP.

Code:

Open("data_table.jmp");
gb = Graph Builder(
    Show Control Panel( 0 ),
    Variables( X( :Meal, Order By( :Calories, Descending, Order Statistic( "Mean" ) ) ), Y( :Calories ) ),
    Elements( Bar( X, Y, Legend( 1 ) ) ),
    SendToReport(
        Dispatch( {}, "Graph Builder", FrameBox,
            {DispatchSeg(
                BarSeg( 1 ),
                {Set Graphlet(
                    Picture(
                        Tabulate(
                            Show Control Panel( 0 ),
                            Set Format( Uniform Format( 10, 2 ) ),
                            Add Table(
                                Column Table( Analysis Columns( :Calories, :Fat, :Carbohydrates, :Protein ), Statistics( Mean ) ),
                                Row Table( Grouping Columns( :Food Category ) )
                            )
                        )
                    )
                )}
            ), Add Pin Annotation(
                Seg( BarSeg( 1 ) ),
                Index( {1, 1} ),
                Index Row( {176, 176} ),
                UniqueID( 764841153 ),
                FoundPt( {185, 272} ),
                Origin( {0.910404624277457, 60.5429864253394} ),
                Tag Line( 1 )
            )}
        )
    )
);
frame = Try( (gb << report)[FrameBox( 1 )], Empty() );
gpin = frame << Get Annotation();

Code Explanation:

1. Open data table;
2. Create Graph Builder object.
3. Hide control panel.
4. Set X variable with ordering.
5. Set Y variable.
6. Add bar element.
7. Send report settings.
8. Dispatch to Graph Builder.
9. Set graphlet with tabulate.
10. Add pin annotation.

Example 336

Summary: Creates a variability chart with nested factors using operator and part configurations, displaying standard deviation charts.

Code:

dt = Open("data_table.jmp");
gb = Graph Builder(
    Show Control Panel( 0 ),
    Variables( X( :Meal, Order By( :Calories, Descending, Order Statistic( "Mean" ) ) ), Y( :Calories ) ),
    Elements( Bar( X, Y, Legend( 1 ) ) ),
    SendToReport(
        Dispatch( {}, "Graph Builder", FrameBox,
            {DispatchSeg(
                BarSeg( 1 ),
                {Set Graphlet(
                    Picture(
                        Tabulate(
                            Show Control Panel( 0 ),
                            Set Format( Uniform Format( 10, 2 ) ),
                            Add Table(
                                Column Table( Analysis Columns( :Calories, :Fat, :Carbohydrates, :Protein ), Statistics( Mean ) ),
                                Row Table( Grouping Columns( :Food Category ) )
                            )
                        )
                    )
                )}
            ), Add Pin Annotation(
                Seg( BarSeg( 1 ) ),
                Index( {1, 1} ),
                Index Row( {176, 176} ),
                UniqueID( 764841153 ),
                FoundPt( {185, 272} ),
                Origin( {0.910404624277457, 60.5429864253394} ),
                Tag Line( 1 )
            )}
        )
    )
);
frame = Try( (gb << report)[FrameBox( 1 )], Empty() );
gpin = frame << Get Annotation();
gpin << Launch Graphlet;

Code Explanation:

1. Open data_table data
2. Create Graph Builder object.
3. Hide control panel.
4. Set X variable: Meal, ordered by Calories descending.
5. Set Y variable: Calories.
6. Add bar element to graph.
7. Send report settings.
8. Dispatch graph builder settings.
9. Set graphlet with tabulate.
10. Add pin annotation.
11. Get frame from graph builder.
12. Get annotation from frame.
13. Launch graphlet.

Example 337

Summary: Creates a box plot preset in Graph Builder, utilizing hllLoader to launch and configure the graphlet.

Code:

Open("data_table.jmp");
gb = Graph Builder(
    Size( 534, 450 ),
    Show Control Panel( 0 ),
    Variables( X( :Type ) ),
    Elements( Line( X, Legend( 3 ) ) ),
    SendToReport(
        Dispatch( {}, "Graph Builder", FrameBox,
            {Set Graphlet(
                Picture(
                    Try(
                        loader = If( Class Exists( "hllLoader" ),
                            New Object( "hllLoader" ),
                            Include( "$BUILTIN_SCRIPTS/hllib.jsl" )
                        );
                        loader:setDebug( 0 );
                        hlp = loader:lazyLoad( "hllPresets" );
                        hlp:launchBox Plot();
                    )
                ),
                Title( "Box Plot Preset" ),
                Reapply( 1 )
            ), Add Pin Annotation(
                Seg( Line Seg( 1 ) ),
                Index( {1, 1} ),
                Index Row( {70, 70} ),
                UniqueID( 866767922 ),
                FoundPt( {477, 333} ),
                Origin( {1.03125, 22.0328571428571} ),
                Tag Line( 1 )
            )}
        )
    )
);
frame = Try( (gb << report)[FrameBox( 1 )], Empty() );
gpin = frame << Get Annotation();
gpin << Launch Graphlet;
frame = Try( (gb << report)[FrameBox( 1 )], Empty() );
gpin = frame << Get Annotation();

Code Explanation:

1. Open data table;
2. Create Graph Builder object.
3. Set graph size and hide control panel.
4. Assign X variable.
5. Add line element to graph.
6. Send report settings.
7. Set graphlet with picture.
8. Load and initialize hllLoader.
9. Launch box plot preset.
10. Get and launch annotation.

Example 338

Summary: Creates a box plot preset graph with nested factors using Graph Builder, showcasing standard deviation charts and interactive features.

Code:

Open("data_table.jmp");
gb = Graph Builder(
    Size( 534, 450 ),
    Show Control Panel( 0 ),
    Variables( X( :Type ) ),
    Elements( Line( X, Legend( 3 ) ) ),
    SendToReport(
        Dispatch( {}, "Graph Builder", FrameBox,
            {Set Graphlet(
                Picture(
                    Try(
                        loader = If( Class Exists( "hllLoader" ),
                            New Object( "hllLoader" ),
                            Include( "$BUILTIN_SCRIPTS/hllib.jsl" )
                        );
                        loader:setDebug( 0 );
                        hlp = loader:lazyLoad( "hllPresets" );
                        hlp:launchBox Plot();
                    )
                ),
                Title( "Box Plot Preset" ),
                Reapply( 1 )
            ), Add Pin Annotation(
                Seg( Line Seg( 1 ) ),
                Index( {1, 1} ),
                Index Row( {70, 70} ),
                UniqueID( 866767922 ),
                FoundPt( {477, 333} ),
                Origin( {1.03125, 22.0328571428571} ),
                Tag Line( 1 )
            )}
        )
    )
);
frame = Try( (gb << report)[FrameBox( 1 )], Empty() );
gpin = frame << Get Annotation();
gpin << Launch Graphlet;
frame = Try( (gb << report)[FrameBox( 1 )], Empty() );
gpin = frame << Get Annotation();
gpin << Launch Graphlet;

Code Explanation:

1. Open data table.
2. Create Graph Builder object.
3. Set size and hide control panel.
4. Define X variable.
5. Add line element.
6. Send report settings.
7. Set graphlet with box plot preset.
8. Add pin annotation.
9. Try to get frame box.
10. Launch graphlet on annotation.

Example 339

Summary: Creates a variability chart with nested factors using Graph Builder, displaying standard deviation charts and leveraging operator and part configurations.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 791, 692 ),
    Show Control Panel( 0 ),
    Variables( X( :Group ), Y( :Time Cycles ), Overlay( :Group ) ),
    Elements( Box Plot( X, Y, Legend( 10 ) ) ),
    SendToReport(
        Dispatch( {}, "Graph Builder", FrameBox,
            {Set Graphlet(
                Picture(
                    Try(
                        loader = If( Class Exists( "hllLoader" ),
                            New Object( "hllLoader" ),
                            Include( "$BUILTIN_SCRIPTS/hllib.jsl" )
                        );
                        loader:setDebug( 0 );
                        hlp = loader:lazyLoad( "hllPresets" );
                        hlp:launchBar();
                    )
                ),
                Title( "Bar Preset" ),
                Reapply( 1 )
            ), {Add Pin Annotation(
                Seg( Box Plot Seg( 1 ) ),
                Index( {1, 1} ),
                Index Row( {1, 1} ),
                UniqueID( 1193273585 ),
                FoundPt( {483, 669} ),
                Origin( {-0.106602475928473, 1857.39215052847} ),
                Offset( {96, -234} ),
                Tag Line( 1 )
            )}}
        )
    )
);

Code Explanation:

1. Open data table;
2. Launch Graph Builder.
3. Set window size.
4. Hide control panel.
5. Define X and Y variables.
6. Add box plot element.
7. Send report commands.
8. Load graphlet library.
9. Initialize preset loader.
10. Launch bar preset.

Example 340

Summary: Creates a variability chart with nested factors using operator and part configurations, displaying standard deviation charts.

Code:

Open("data_table.jmp");
gb = Graph Builder(
    Size( 534, 450 ),
    Show Control Panel( 0 ),
    Variables( X( :sex ), Y( :height ) ),
    Elements( Bar( X, Y, Legend( 4 ) ) ),
    Column Switcher( :height, {:height, :weight} ),
    SendToReport(
        Dispatch( {}, "Graph Builder", FrameBox,
            {Set Graphlet(
                Picture( Graph Builder( Show Control Panel( 0 ), Variables( Y( local:_measurements[1] ) ), Elements( Histogram( Y ) ) ) )
            ), Add Pin Annotation(
                Seg( BarSeg( 1 ) ),
                Index( {0, 0} ),
                Index Row( {0, 0} ),
                UniqueID( 764915408 ),
                FoundPt( {325, 247} ),
                Origin( {-0.104081632653061, 35.3571428571429} ),
                Tag Line( 1 )
            )}
        )
    )
);
frame = Try( (gb << report)[FrameBox( 1 )], Empty() );
gpin = frame << Get Annotation();

Code Explanation:

1. Open data table.
2. Create Graph Builder object.
3. Set graph size.
4. Hide control panel.
5. Define X and Y variables.
6. Add bar element.
7. Enable column switcher.
8. Send report commands.
9. Set graphlet with histogram.
10. Add pin annotation.

Example 341

Summary: Creates a variability chart with nested factors using operator and part configurations, displaying standard deviation charts.

Code:

dt = Open("data_table.jmp");
gb = Graph Builder(
    Size( 534, 450 ),
    Show Control Panel( 0 ),
    Variables( X( :sex ), Y( :height ) ),
    Elements( Bar( X, Y, Legend( 4 ) ) ),
    Column Switcher( :height, {:height, :weight} ),
    SendToReport(
        Dispatch( {}, "Graph Builder", FrameBox,
            {Set Graphlet(
                Picture( Graph Builder( Show Control Panel( 0 ), Variables( Y( local:_measurements[1] ) ), Elements( Histogram( Y ) ) ) )
            ), Add Pin Annotation(
                Seg( BarSeg( 1 ) ),
                Index( {0, 0} ),
                Index Row( {0, 0} ),
                UniqueID( 764915408 ),
                FoundPt( {325, 247} ),
                Origin( {-0.104081632653061, 35.3571428571429} ),
                Tag Line( 1 )
            )}
        )
    )
);
frame = Try( (gb << report)[FrameBox( 1 )], Empty() );
gpin = frame << Get Annotation();
gpin << Launch Graphlet;

Code Explanation:

1. Open data table.
2. Create Graph Builder object.
3. Set size and hide control panel.
4. Define X and Y variables.
5. Add bar element with legend.
6. Enable column switcher for height.
7. Send report commands.
8. Set graphlet with histogram.
9. Add pin annotation to graph.
10. Retrieve and launch graphlet annotation.

Example 342

Summary: Creates a variability chart with nested factors using Graph Builder, displaying standard deviation charts and utilizing graphlet settings.

Code:

Open("data_table.jmp");
gb = Graph Builder(
    Size( 524, 451 ),
    Show Control Panel( 0 ),
    Variables( X( :sex ), Y( :age ), Color( :height ) ),
    Elements( Heatmap( X, Y, Legend( 6 ) ) ),
    SendToReport(
        Dispatch( {}, "Graph Builder", FrameBox,
            {Set Graphlet(
                Picture(
                    Graph Builder(
                        Size( 400, 200 ),
                        Show Control Panel( 0 ),
                        Show Legend( 0 ),
                        Variables( Y( :height ) ),
                        Elements( Histogram( Y ) )
                    )
                ),
                Title( "Graphlet" )
            ), Add Pin Annotation(
                Seg( RectSeg( 1 ) ),
                Index( 2 ),
                Index Row( 15 ),
                UniqueID( 767369682 ),
                FoundPt( {135, 283} ),
                Origin( {-0.160455486542443, 1.98854961832061} ),
                Tag Line( 1 )
            )}
        )
    )
);
frame = Try( (gb << report)[FrameBox( 1 )], Empty() );
gpin = frame << Get Annotation();

Code Explanation:

1. Open data table.
2. Create Graph Builder object.
3. Set graph size and hide control panel.
4. Define X, Y, and color variables.
5. Add heatmap element with legend.
6. Send report with graphlet settings.
7. Insert nested Graph Builder for histogram.
8. Set nested graph size and hide control panel and legend.
9. Define Y variable for histogram.
10. Add histogram element to nested Graph Builder.

Example 343

Summary: Creates a variability chart with nested factors using operator and part configurations, displaying standard deviation charts.

Code:

dt = Open("data_table.jmp");
gb = Graph Builder(
    Size( 524, 451 ),
    Show Control Panel( 0 ),
    Variables( X( :sex ), Y( :age ), Color( :height ) ),
    Elements( Heatmap( X, Y, Legend( 6 ) ) ),
    SendToReport(
        Dispatch( {}, "Graph Builder", FrameBox,
            {Set Graphlet(
                Picture(
                    Graph Builder(
                        Size( 400, 200 ),
                        Show Control Panel( 0 ),
                        Show Legend( 0 ),
                        Variables( Y( :height ) ),
                        Elements( Histogram( Y ) )
                    )
                ),
                Title( "Graphlet" )
            ), Add Pin Annotation(
                Seg( RectSeg( 1 ) ),
                Index( 2 ),
                Index Row( 15 ),
                UniqueID( 767369682 ),
                FoundPt( {135, 283} ),
                Origin( {-0.160455486542443, 1.98854961832061} ),
                Tag Line( 1 )
            )}
        )
    )
);
frame = Try( (gb << report)[FrameBox( 1 )], Empty() );
gpin = frame << Get Annotation();
gpin << Launch Graphlet;

Code Explanation:

1. Open data table;
2. Create Graph Builder.
3. Set size 524x451.
4. Hide control panel.
5. Set X to :sex, Y to :age, Color to :height.
6. Add heatmap element.
7. Send report to Graph Builder.
8. Set graphlet with histogram.
9. Add pin annotation.
10. Launch graphlet.

Example 344

Summary: Creates a variability chart with nested factors using operator and part configurations, displaying standard deviation charts in JMP.

Code:

Open("data_table.jmp");
gb = Graph Builder(
    Size( 535, 457 ),
    Show Control Panel( 0 ),
    Variables( X( :Bench ), Y( :Squat ) ),
    Elements( Heatmap( X, Y, Legend( 5 ) ) ),
    SendToReport(
        Dispatch( {}, "Graph Builder", FrameBox,
            {Set Graphlet(
                Picture(
                    Graph Builder(
                        Size( 496, 457 ),
                        Show Control Panel( 0 ),
                        Variables( X( :Bench ), X( :Squat, Position( 1 ) ) ),
                        Elements( Box Plot( X( 1 ), X( 2 ), Legend( 2 ) ) )
                    )
                ),
                Title( "Graphlet" )
            ), Add Pin Annotation(
                Seg( RectSeg( 1 ) ),
                Index( 5 ),
                Index Row( 24 ),
                UniqueID( 757235509 ),
                FoundPt( {186, 277} ),
                Origin( {263.53305785124, 429.007633587786} ),
                Tag Line( 1 )
            )}
        )
    )
);
frame = Try( (gb << report)[FrameBox( 1 )], Empty() );
gpin = frame << Get Annotation();

Code Explanation:

1. Open data table;
2. Create Graph Builder object.
3. Set graph size.
4. Hide control panel.
5. Define X and Y variables.
6. Add heatmap element.
7. Send report to Graph Builder.
8. Set graphlet with nested Graph Builder.
9. Add box plot to graphlet.
10. Add pin annotation to heatmap.

Example 345

Summary: Creates a nested variability chart with standard deviation charts, utilizing Graph Builder and SendToReport to generate interactive visualizations.

Code:

dt = Open("data_table.jmp");
gb = Graph Builder(
    Size( 535, 457 ),
    Show Control Panel( 0 ),
    Variables( X( :Bench ), Y( :Squat ) ),
    Elements( Heatmap( X, Y, Legend( 5 ) ) ),
    SendToReport(
        Dispatch( {}, "Graph Builder", FrameBox,
            {Set Graphlet(
                Picture(
                    Graph Builder(
                        Size( 496, 457 ),
                        Show Control Panel( 0 ),
                        Variables( X( :Bench ), X( :Squat, Position( 1 ) ) ),
                        Elements( Box Plot( X( 1 ), X( 2 ), Legend( 2 ) ) )
                    )
                ),
                Title( "Graphlet" )
            ), Add Pin Annotation(
                Seg( RectSeg( 1 ) ),
                Index( 5 ),
                Index Row( 24 ),
                UniqueID( 757235509 ),
                FoundPt( {186, 277} ),
                Origin( {263.53305785124, 429.007633587786} ),
                Tag Line( 1 )
            )}
        )
    )
);
frame = Try( (gb << report)[FrameBox( 1 )], Empty() );
gpin = frame << Get Annotation();
gpin << Launch Graphlet;

Code Explanation:

1. Open data table.
2. Create Graph Builder object.
3. Set graph size to 535x457.
4. Hide control panel.
5. Assign Bench to X-axis, Squat to Y-axis.
6. Add heatmap element with legend at position 5.
7. Send report with graphlet and annotations.
8. Create inner Graph Builder for graphlet.
9. Set inner graph size to 496x457.
10. Hide inner control panel.
11. Assign Bench to X1, Squat to X2.
12. Add box plot element with legend at position 2.
13. Retrieve first frame from report.
14. Get annotation from frame.
15. Launch graphlet annotation.

Example 346

Summary: Creates a variability chart with nested factors using operator and part configurations, displaying standard deviation charts.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 528, 418 ),
    Show Control Panel( 0 ),
    Variables( Y( :Depth ), Y( :Table, Position( 1 ) ) ),
    Elements( Histogram( Y( 1 ), Y( 2 ), Legend( 8 ), Response Scale( "Fill" ) ) ),
    SendToReport(
        Dispatch( {}, "Graph Builder", FrameBox,
            {Set Graphlet(
                Picture(
                    Try(
                        loader = If( Class Exists( "hllLoader" ),
                            New Object( "hllLoader" ),
                            Include( "$BUILTIN_SCRIPTS/hllib.jsl" )
                        );
                        loader:setDebug( 0 );
                        hlp = loader:lazyLoad( "hllPresets" );
                        hlp:launchHistogram();
                    )
                ),
                Title( "Histogram Preset" ),
                Reapply( 1 )
            ), Reference Line Order( 3 ), Grid Line Order( 2 ), Add Pin Annotation(
                Seg( Hist Seg( 2 ) ),
                Index( {48, 60} ),
                Index Row( {48, 60} ),
                UniqueID( 1047647808 ),
                FoundPt( {563, 382} ),
                Origin( {-0.0103305785123967, 57.30625} ),
                Offset( {21, 11} ),
                Tag Line( 1 )
            )}
        ),
        Dispatch( {}, "400", LegendBox, {Set Title( "" )} )
    )
);

Code Explanation:

1. Open data table;
2. Create Graph Builder window.
3. Set graph size to 528x418.
4. Hide control panel.
5. Assign Depth to Y axis.
6. Assign Table to second Y axis.
7. Add histogram element.
8. Configure histogram response scale to fill.
9. Load and set up histogram preset script.
10. Add pin annotation to histogram.

Example 347

Summary: Creates a variability chart with nested factors using operator and part configurations, displaying standard deviation charts.

Code:

Open("data_table.jmp");
gb = Graph Builder(
    Show Control Panel( 0 ),
    Variables( X( :age ), Y( :height ), Y( :weight, Position( 1 ) ) ),
    Elements( Bar( X, Y( 1 ), Y( 2 ), Legend( 5 ) ) ),
    SendToReport(
        Dispatch( {}, "Graph Builder", FrameBox,
            {DispatchSeg(
                BarSeg( 1 ),
                {Set Graphlet(
                    Picture(
                        Graph Builder(
                            Size( 400, 200 ),
                            Show Control Panel( 0 ),
                            Show Legend( 0 ),
                            Variables( X( local:_measurements[1] ) ),
                            Elements( Histogram( X ) )
                        )
                    )
                )}
            ), Add Pin Annotation(
                Seg( BarSeg( 1 ) ),
                Index( {1, 3} ),
                Index Row( {8, 27} ),
                UniqueID( 764858625 ),
                FoundPt( {195, 278} ),
                Origin( {1.02601156069364, 74.4470377073907} ),
                Tag Line( 1 )
            )}
        )
    )
);
frame = Try( (gb << report)[FrameBox( 1 )], Empty() );
gpin = frame << Get Annotation();

Code Explanation:

1. Open data table.
2. Create Graph Builder object.
3. Hide control panel.
4. Set X and Y variables.
5. Add bar element with two Ys.
6. Send report to Graph Builder.
7. Dispatch segment for bar graph.
8. Set graphlet with histogram.
9. Add pin annotation to bar segments.
10. Retrieve frame box from report.

Example 348

Summary: Creates a variability chart with nested factors using operator and part configurations, displaying standard deviation charts.

Code:

dt = Open("data_table.jmp");
gb = Graph Builder(
    Show Control Panel( 0 ),
    Variables( X( :age ), Y( :height ), Y( :weight, Position( 1 ) ) ),
    Elements( Bar( X, Y( 1 ), Y( 2 ), Legend( 5 ) ) ),
    SendToReport(
        Dispatch( {}, "Graph Builder", FrameBox,
            {DispatchSeg(
                BarSeg( 1 ),
                {Set Graphlet(
                    Picture(
                        Graph Builder(
                            Size( 400, 200 ),
                            Show Control Panel( 0 ),
                            Show Legend( 0 ),
                            Variables( X( local:_measurements[1] ) ),
                            Elements( Histogram( X ) )
                        )
                    )
                )}
            ), Add Pin Annotation(
                Seg( BarSeg( 1 ) ),
                Index( {1, 3} ),
                Index Row( {8, 27} ),
                UniqueID( 764858625 ),
                FoundPt( {195, 278} ),
                Origin( {1.02601156069364, 74.4470377073907} ),
                Tag Line( 1 )
            )}
        )
    )
);
frame = Try( (gb << report)[FrameBox( 1 )], Empty() );
gpin = frame << Get Annotation();
gpin << Launch Graphlet;

Code Explanation:

1. Open data table.
2. Create Graph Builder object.
3. Configure Graph Builder settings.
4. Add variables to Graph Builder.
5. Add bar elements to Graph Builder.
6. Send report settings to Graph Builder.
7. Set graphlet for bar segment.
8. Add pin annotation to Graph Builder.
9. Retrieve frame box from report.
10. Launch graphlet from annotation.

Example 349

Summary: Creates a nested variability chart with standard deviation charts, using Graph Builder to visualize the relationship between sex and age.

Code:

Open("data_table.jmp");
Graph Builder(
    Show Control Panel( 0 ),
    Variables( X( :sex ), Y( :age ) ),
    Elements( Mosaic( X, Y, Legend( 6 ) ) ),
    SendToReport(
        Dispatch( {}, "Graph Builder", FrameBox,
            {Set Graphlet(
                Picture(
                    Graph Builder(
                        Variables( X( :name ), Y( :height ), Y( :weight, Position( 1 ) ) ),
                        Elements( Bar( X, Y( 1 ), Y( 2 ), Legend( 10 ) ) )
                    )
                )
            ), {Add Pin Annotation(
                Seg( MosaicSeg( 1 ) ),
                Index( {1, 3} ),
                Index Row( {1, 3} ),
                UniqueID( 1385404449 ),
                FoundPt( {561, 134} ),
                Origin( {0.958579881656805, 0.808558558558559} ),
                RightOfCenter( 1 ),
                Tag Line( 1 )
            ), Add Pin Annotation(
                Seg( MosaicSeg( 1 ) ),
                Index( {0, 2} ),
                Index Row( {0, 2} ),
                UniqueID( 1385404442 ),
                FoundPt( {90, 282} ),
                Origin( {0.029585798816568, 0.475225225225225} ),
                RightOfCenter( 0 ),
                Tag Line( 1 )
            )}}
        )
    )
);

Code Explanation:

1. Open data table;
2. Launch Graph Builder.
3. Hide control panel.
4. Set X variable to sex.
5. Set Y variable to age.
6. Create mosaic element.
7. Insert nested Graph Builder.
8. Set X variable to name.
9. Set Y variables to height and weight.
10. Create bar element.

Example 350

Summary: Creates a variability chart with nested factors using Graph Builder, displaying standard deviation charts and adding pin annotations to mosaic segments.

Code:

Open("data_table.jmp");
Graph Builder(
    Show Control Panel( 0 ),
    Variables( X( :sex ), Y( :age ) ),
    Elements( Mosaic( X, Y, Legend( 6 ) ) ),
    SendToReport(
        Dispatch( {}, "Graph Builder", FrameBox,
            {Set Graphlet(
                Picture(
                    Graph Builder(
                        Variables( X( :name ), Y( :height ), Y( :weight, Position( 1 ) ) ),
                        Elements( Bar( X, Y( 1 ), Y( 2 ), Legend( 10 ) ) )
                    )
                )
            ), Add Pin Annotation(
                Seg( MosaicSeg( 1 ) ),
                Index( {0, 2} ),
                Index Row( {0, 2} ),
                UniqueID( 640933346 ),
                FoundPt( {420, 313} ),
                Origin( {0.170212765957447, 0.51530612244898} ),
                Tag Line( 1 )
            )}
        )
    )
);

Code Explanation:

1. Open data table.
2. Create Graph Builder object.
3. Hide control panel.
4. Set X and Y variables.
5. Add mosaic element.
6. Send report to Graph Builder.
7. Set graphlet with nested Graph Builder.
8. Add picture to graphlet.
9. Add bar element to nested Graph Builder.
10. Add pin annotation to mosaic segment.

Example 351

Summary: Creates a variability chart with nested factors using operator and part configurations, displaying standard deviation charts.

Code:

Open("data_table.jmp");
gb = Graph Builder(
    Show Control Panel( 0 ),
    Variables( X( :softness ), X( :previous use, Position( 1 ) ), Y( :count ) ),
    Elements( Bar( X( 1 ), X( 2 ), Y, Legend( 7 ), Summary Statistic( "Sum" ) ) ),
    SendToReport(
        Dispatch( {}, "Graph Builder", FrameBox,
            {DispatchSeg(
                BarSeg( 1 ),
                {Set Graphlet(
                    Picture(
                        Graph Builder(
                            Size( 400, 200 ),
                            Show Control Panel( 0 ),
                            Variables( X( :temperature ), Y( :count ) ),
                            Elements( Bar( X, Y, Summary Statistic( "Sum" ) ) )
                        )
                    )
                )}
            ), Add Pin Annotation(
                Seg( BarSeg( 1 ) ),
                Index( {1, 1} ),
                Index Row( {16, 16} ),
                UniqueID( 764880465 ),
                FoundPt( {197, 192} ),
                Origin( {1.04913294797688, 133.809523809524} ),
                Tag Line( 1 )
            )}
        )
    )
);
frame = Try( (gb << report)[FrameBox( 1 )], Empty() );
gpin = frame << Get Annotation();

Code Explanation:

1. Open data table;
2. Create Graph Builder object.
3. Hide control panel.
4. Set X variables: softness, previous use.
5. Set Y variable: count.
6. Add bar element with summary statistic "Sum".
7. Send report dispatch for graphlet.
8. Add picture graphlet with nested Graph Builder.
9. Set size for nested Graph Builder.
10. Add pin annotation to graph.

Example 352

Summary: Creates a variability chart with nested factors using Graph Builder, displaying standard deviation charts and configuring interactive elements.

Code:

dt = Open("data_table.jmp");
gb = Graph Builder(
    Show Control Panel( 0 ),
    Variables( X( :softness ), X( :previous use, Position( 1 ) ), Y( :count ) ),
    Elements( Bar( X( 1 ), X( 2 ), Y, Legend( 7 ), Summary Statistic( "Sum" ) ) ),
    SendToReport(
        Dispatch( {}, "Graph Builder", FrameBox,
            {DispatchSeg(
                BarSeg( 1 ),
                {Set Graphlet(
                    Picture(
                        Graph Builder(
                            Size( 400, 200 ),
                            Show Control Panel( 0 ),
                            Variables( X( :temperature ), Y( :count ) ),
                            Elements( Bar( X, Y, Summary Statistic( "Sum" ) ) )
                        )
                    )
                )}
            ), Add Pin Annotation(
                Seg( BarSeg( 1 ) ),
                Index( {1, 1} ),
                Index Row( {16, 16} ),
                UniqueID( 764880465 ),
                FoundPt( {197, 192} ),
                Origin( {1.04913294797688, 133.809523809524} ),
                Tag Line( 1 )
            )}
        )
    )
);
frame = Try( (gb << report)[FrameBox( 1 )], Empty() );
gpin = frame << Get Annotation();
gpin << Launch Graphlet;

Code Explanation:

1. Open data table;
2. Create Graph Builder object.
3. Hide control panel.
4. Set X variables: softness, previous use.
5. Set Y variable: count.
6. Add bar element with sum summary.
7. Configure hover label with nested graph.
8. Set nested graph size.
9. Hide nested graph control panel.
10. Set nested graph variables: temperature, count.
11. Add bar element to nested graph.
12. Add pin annotation to main graph.
13. Retrieve frame box from report.
14. Get annotation from frame.
15. Launch graphlet from annotation.

Example 353

Summary: Creates a variability chart with nested factors using Graph Builder, displaying standard deviation charts and customizing graphlets for specific marker segments.

Code:

Open("data_table.jmp");
gb = Graph Builder(
    Size( 521, 451 ),
    Show Control Panel( 0 ),
    Variables( X( :age ), Y( :sex ), Overlay( :height ) ),
    Elements( Points( X, Y, Legend( 11 ) ) ),
    SendToReport(
        Dispatch( {}, "Graph Builder", FrameBox,
            {DispatchSeg(
                Marker Seg( "Marker (51 - 61)" ),
                {Set Graphlet(
                    Picture(
                        Graph Builder( Size( 496, 457 ), Show Control Panel( 0 ), Variables( X( :height ) ), Elements( Box Plot( X ) ) )
                    ),
                    Title( "Graphlet" )
                )}
            ), DispatchSeg(
                Marker Seg( "Marker (61 - 63)" ),
                {Set Graphlet(
                    Picture(
                        Graph Builder( Size( 496, 457 ), Show Control Panel( 0 ), Variables( X( :height ) ), Elements( Box Plot( X ) ) )
                    ),
                    Title( title || " Graphlet" )
                )}
            ), DispatchSeg(
                Marker Seg( "Marker (63 - 65)" ),
                {Set Graphlet(
                    Picture(
                        Graph Builder( Size( 496, 457 ), Show Control Panel( 0 ), Variables( X( :height ) ), Elements( Box Plot( X ) ) )
                    ),
                    Title( title || " Graphlet" )
                )}
            ), DispatchSeg(
                Marker Seg( "Marker (65 - 67)" ),
                {Set Graphlet(
                    Picture(
                        Graph Builder( Size( 496, 457 ), Show Control Panel( 0 ), Variables( X( :height ) ), Elements( Box Plot( X ) ) )
                    ),
                    Title( title || " Graphlet" )
                )}
            ), DispatchSeg(
                Marker Seg( "Marker (67 - 70)" ),
                {Set Graphlet(
                    Picture(
                        Graph Builder( Size( 496, 457 ), Show Control Panel( 0 ), Variables( X( :height ) ), Elements( Box Plot( X ) ) )
                    ),
                    Title( title || " Graphlet" )
                )}
            ), Add Pin Annotation(
                Seg( Marker Seg( 1 ) ),
                Index( 7 ),
                Index Row( 13 ),
                UniqueID( 814829975 ),
                FoundPt( {176, 161} ),
                Origin( {1.08350515463918, 0.950381679389313} ),
                Tag Line( 1 )
            )}
        )
    )
);
frame = Try( (gb << report)[FrameBox( 1 )], Empty() );
gpin = frame << Get Annotation();

Code Explanation:

1. Open data table;
2. Create Graph Builder object.
3. Set graph size and hide control panel.
4. Define X, Y, and overlay variables.
5. Add points element with legend.
6. Dispatch to report for graph customization.
7. Set graphlets for specific marker segments.
8. Customize graphlet titles.
9. Add pin annotation to graph.
10. Retrieve frame and annotations.

Example 354

Summary: Creates a variability chart with nested factors using operator and part configurations, displaying standard deviation charts in JMP.

Code:

dt = Open("data_table.jmp");
gb = Graph Builder(
    Size( 521, 451 ),
    Show Control Panel( 0 ),
    Variables( X( :age ), Y( :sex ), Overlay( :height ) ),
    Elements( Points( X, Y, Legend( 11 ) ) ),
    SendToReport(
        Dispatch( {}, "Graph Builder", FrameBox,
            {DispatchSeg(
                Marker Seg( "Marker (51 - 61)" ),
                {Set Graphlet(
                    Picture(
                        Graph Builder( Size( 496, 457 ), Show Control Panel( 0 ), Variables( X( :height ) ), Elements( Box Plot( X ) ) )
                    ),
                    Title( "Graphlet" )
                )}
            ), DispatchSeg(
                Marker Seg( "Marker (61 - 63)" ),
                {Set Graphlet(
                    Picture(
                        Graph Builder( Size( 496, 457 ), Show Control Panel( 0 ), Variables( X( :height ) ), Elements( Box Plot( X ) ) )
                    ),
                    Title( title || " Graphlet" )
                )}
            ), DispatchSeg(
                Marker Seg( "Marker (63 - 65)" ),
                {Set Graphlet(
                    Picture(
                        Graph Builder( Size( 496, 457 ), Show Control Panel( 0 ), Variables( X( :height ) ), Elements( Box Plot( X ) ) )
                    ),
                    Title( title || " Graphlet" )
                )}
            ), DispatchSeg(
                Marker Seg( "Marker (65 - 67)" ),
                {Set Graphlet(
                    Picture(
                        Graph Builder( Size( 496, 457 ), Show Control Panel( 0 ), Variables( X( :height ) ), Elements( Box Plot( X ) ) )
                    ),
                    Title( title || " Graphlet" )
                )}
            ), DispatchSeg(
                Marker Seg( "Marker (67 - 70)" ),
                {Set Graphlet(
                    Picture(
                        Graph Builder( Size( 496, 457 ), Show Control Panel( 0 ), Variables( X( :height ) ), Elements( Box Plot( X ) ) )
                    ),
                    Title( title || " Graphlet" )
                )}
            ), Add Pin Annotation(
                Seg( Marker Seg( 1 ) ),
                Index( 7 ),
                Index Row( 13 ),
                UniqueID( 814829975 ),
                FoundPt( {176, 161} ),
                Origin( {1.08350515463918, 0.950381679389313} ),
                Tag Line( 1 )
            )}
        )
    )
);
frame = Try( (gb << report)[FrameBox( 1 )], Empty() );
gpin = frame << Get Annotation();
gpin << Launch Graphlet;

Code Explanation:

1. Open data table;
2. Create Graph Builder window.
3. Set size to 521x451.
4. Hide control panel.
5. Assign variables: age, sex, height.
6. Add points element.
7. Dispatch for Marker Seg "51 - 61".
8. Set graphlet with box plot.
9. Repeat steps 7-8 for other marker segments.
10. Add pin annotation to first segment.

Example 355

Summary: Creates a variability chart with nested factors using operator and part configurations, displaying standard deviation charts.

Code:

Open("data_table.jmp");
gb = Graph Builder(
    Size( 523, 451 ),
    Show Control Panel( 0 ),
    Variables( X( :age ), Overlay( :height ) ),
    Elements( Bar( X, Legend( 10 ) ) ),
    SendToReport(
        Dispatch( {}, "Graph Builder", FrameBox,
            {DispatchSeg(
                BarSeg( 1 ),
                {Set Graphlet(
                    Picture(
                        Graph Builder( Size( 496, 457 ), Show Control Panel( 0 ), Variables( X( :height ) ), Elements( Box Plot( X ) ) )
                    ),
                    Title( "Graphlet" )
                )}
            ), Add Pin Annotation(
                Seg( BarSeg( 1 ) ),
                Index( {12, 12} ),
                Index Row( {18, 18} ),
                UniqueID( 764867372 ),
                FoundPt( {254, 200} ),
                Origin( {2.02371134020619, 3.37389312977099} ),
                Tag Line( 1 )
            )}
        )
    )
);
frame = Try( (gb << report)[FrameBox( 1 )], Empty() );
gpin = frame << Get Annotation();

Code Explanation:

1. Open data table;
2. Create Graph Builder object.
3. Set graph size to 523x451.
4. Hide control panel.
5. Set X variable to age.
6. Overlay height on age.
7. Add bar element.
8. Configure hover label for bar segment.
9. Insert box plot graphlet.
10. Add pin annotation to bar segment.

Example 356

Summary: Creates a variability chart with nested factors using operator and part configurations, displaying standard deviation charts.

Code:

dt = Open("data_table.jmp");
gb = Graph Builder(
    Size( 523, 451 ),
    Show Control Panel( 0 ),
    Variables( X( :age ), Overlay( :height ) ),
    Elements( Bar( X, Legend( 10 ) ) ),
    SendToReport(
        Dispatch( {}, "Graph Builder", FrameBox,
            {DispatchSeg(
                BarSeg( 1 ),
                {Set Graphlet(
                    Picture(
                        Graph Builder( Size( 496, 457 ), Show Control Panel( 0 ), Variables( X( :height ) ), Elements( Box Plot( X ) ) )
                    ),
                    Title( "Graphlet" )
                )}
            ), Add Pin Annotation(
                Seg( BarSeg( 1 ) ),
                Index( {12, 12} ),
                Index Row( {18, 18} ),
                UniqueID( 764867372 ),
                FoundPt( {254, 200} ),
                Origin( {2.02371134020619, 3.37389312977099} ),
                Tag Line( 1 )
            )}
        )
    )
);
frame = Try( (gb << report)[FrameBox( 1 )], Empty() );
gpin = frame << Get Annotation();
gpin << Launch Graphlet;

Code Explanation:

1. Open data_table data
2. Create Graph Builder window.
3. Set graph size.
4. Hide control panel.
5. Assign variables: age (X), height (Overlay).
6. Add bar element with legend.
7. Send report to Graph Builder.
8. Dispatch segment for bar graph.
9. Set graphlet with picture and title.
10. Add pin annotation to bar segment.

Example 357

Summary: Creates a variability chart with nested factors using Graph Builder, displaying standard deviation charts and adding pin annotations to specific segments.

Code:

Open("data_table.jmp");
gb = Graph Builder(
    Size( 523, 451 ),
    Show Control Panel( 0 ),
    Variables( X( :sex ), Overlay( :age ) ),
    Elements( Bar( X, Legend( 10 ) ) ),
    SendToReport(
        Dispatch( {}, "Graph Builder", FrameBox,
            {DispatchSeg(
                BarSeg( 1 ),
                {Set Graphlet(
                    Picture(
                        Graph Builder( Size( 496, 457 ), Show Control Panel( 0 ), Variables( X( :height ) ), Elements( Box Plot( X ) ) )
                    ),
                    Title( "Graphlet" )
                )}
            ), Add Pin Annotation(
                Seg( BarSeg( 1 ) ),
                Index( {2, 2} ),
                Index Row( {18, 18} ),
                UniqueID( 764897938 ),
                FoundPt( {170, 242} ),
                Origin( {-0.00515463917525771, 3.91700763358779} ),
                Tag Line( 1 )
            )}
        )
    )
);
frame = Try( (gb << report)[FrameBox( 1 )], Empty() );
gpin = frame << Get Annotation();

Code Explanation:

1. Open data table;
2. Create Graph Builder window.
3. Set size to 523x451.
4. Hide control panel.
5. Set X variable to sex.
6. Overlay age variable.
7. Add bar element.
8. Send report commands.
9. Set graphlet for first bar segment.
10. Add pin annotation to first bar segment.

Example 358

Summary: Creates a variability chart with nested factors using operator and part configurations, displaying standard deviation charts.

Code:

dt = Open("data_table.jmp");
gb = Graph Builder(
    Size( 523, 451 ),
    Show Control Panel( 0 ),
    Variables( X( :sex ), Overlay( :age ) ),
    Elements( Bar( X, Legend( 10 ) ) ),
    SendToReport(
        Dispatch( {}, "Graph Builder", FrameBox,
            {DispatchSeg(
                BarSeg( 1 ),
                {Set Graphlet(
                    Picture(
                        Graph Builder( Size( 496, 457 ), Show Control Panel( 0 ), Variables( X( :height ) ), Elements( Box Plot( X ) ) )
                    ),
                    Title( "Graphlet" )
                )}
            ), Add Pin Annotation(
                Seg( BarSeg( 1 ) ),
                Index( {2, 2} ),
                Index Row( {18, 18} ),
                UniqueID( 764897938 ),
                FoundPt( {170, 242} ),
                Origin( {-0.00515463917525771, 3.91700763358779} ),
                Tag Line( 1 )
            )}
        )
    )
);
frame = Try( (gb << report)[FrameBox( 1 )], Empty() );
gpin = frame << Get Annotation();
gpin << Launch Graphlet;

Code Explanation:

1. Open data table;
2. Create Graph Builder object.
3. Set graph size and control panel visibility.
4. Define X and overlay variables.
5. Add bar element with legend.
6. Send report settings.
7. Dispatch graph builder for customization.
8. Set graphlet with box plot.
9. Add pin annotation to graph.
10. Launch graphlet from annotation.

Example 359

Summary: Creates a variability chart with nested factors using operator and part configurations, displaying standard deviation charts.

Code:

Open("data_table.jmp");
gb = Graph Builder(
    Show Control Panel( 0 ),
    Variables( X( :softness ), X( :previous use, Position( 1 ) ), Y( :count ) ),
    Elements( Bar( X( 1 ), X( 2 ), Y, Legend( 7 ), Summary Statistic( "Sum" ) ) ),
    Local Data Filter( Close Outline( 1 ), Add Filter( columns( :brand ), Where( :brand == "x" ) ) ),
    SendToReport(
        Dispatch( {}, "Graph Builder", FrameBox,
            {DispatchSeg(
                BarSeg( 1 ),
                {Set Graphlet(
                    Picture(
                        Graph Builder(
                            Size( 400, 200 ),
                            Show Control Panel( 0 ),
                            Variables( X( :temperature ), Y( :count ) ),
                            Elements( Bar( X, Y, Summary Statistic( "Sum" ) ) )
                        )
                    )
                )}
            ), Add Pin Annotation(
                Seg( BarSeg( 1 ) ),
                Index( {1, 1} ),
                Index Row( {16, 16} ),
                UniqueID( 764862993 ),
                FoundPt( {233, 299} ),
                Origin( {1.13005780346821, 49.7142857142857} ),
                Tag Line( 1 )
            )}
        )
    )
);
frame = Try( (gb << report)[FrameBox( 1 )], Empty() );
gpin = frame << Get Annotation();

Code Explanation:

1. Open data table;
2. Create Graph Builder object.
3. Hide control panel.
4. Set X and Y variables.
5. Add bar element.
6. Apply local data filter.
7. Send report to Graph Builder.
8. Dispatch to graph builder frame.
9. Set graphlet picture.
10. Add pin annotation.

Example 360

Summary: Creates a variability chart with nested factors using operator and part configurations, displaying standard deviation charts.

Code:

dt = Open("data_table.jmp");
gb = Graph Builder(
    Show Control Panel( 0 ),
    Variables( X( :softness ), X( :previous use, Position( 1 ) ), Y( :count ) ),
    Elements( Bar( X( 1 ), X( 2 ), Y, Legend( 7 ), Summary Statistic( "Sum" ) ) ),
    Local Data Filter( Close Outline( 1 ), Add Filter( columns( :brand ), Where( :brand == "x" ) ) ),
    SendToReport(
        Dispatch( {}, "Graph Builder", FrameBox,
            {DispatchSeg(
                BarSeg( 1 ),
                {Set Graphlet(
                    Picture(
                        Graph Builder(
                            Size( 400, 200 ),
                            Show Control Panel( 0 ),
                            Variables( X( :temperature ), Y( :count ) ),
                            Elements( Bar( X, Y, Summary Statistic( "Sum" ) ) )
                        )
                    )
                )}
            ), Add Pin Annotation(
                Seg( BarSeg( 1 ) ),
                Index( {1, 1} ),
                Index Row( {16, 16} ),
                UniqueID( 764862993 ),
                FoundPt( {233, 299} ),
                Origin( {1.13005780346821, 49.7142857142857} ),
                Tag Line( 1 )
            )}
        )
    )
);
frame = Try( (gb << report)[FrameBox( 1 )], Empty() );
gpin = frame << Get Annotation();
gpin << Launch Graphlet;

Code Explanation:

1. Open data table.
2. Create Graph Builder object.
3. Hide control panel.
4. Set X variables: softness, previous use.
5. Set Y variable: count.
6. Add bar element with sum summary statistic.
7. Add local data filter for brand "x".
8. Send report commands.
9. Set graphlet with nested Graph Builder.
10. Add pin annotation.
11. Get frame box from report.
12. Get annotation from frame.
13. Launch graphlet.

Example 361

Summary: Creates a variability chart with nested factors using operator and part configurations, displaying standard deviation charts in Graph Builder.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 528, 450 ),
    Show Control Panel( 0 ),
    Variables( X( :sex ) ),
    Elements( Bar( X, Legend( 3 ) ) ),
    SendToReport(
        Dispatch( {}, "Graph Builder", FrameBox,
            {Set Graphlet(
                Picture(
                    local:analysisCols = If( N Items( local:_measurements ),
                        local:statsDef = If( !Is Missing( local:_summaryStatistic ),
                            Eval Insert( ", Statistics( {local:_summaryStatistic} )", "{", "}" ),
                            ""
                        );
                        Eval Insert(
                            "     
Column Table( 
            Analysis Columns( {local:_measurements} )
            {local:statsDef}
        ),",
                            "{",
                            "}"
                        );
                    ,
                        ""
                    );
                    local:template =
                    "
    Tabulate(
    Show Control Panel( 0 ),
    Add Table(
{local:analysisCols}
        Row Table(
            Grouping Columns( {local:_groupings} )
        )
    )
)
";
                    Eval Insert Into( local:template, "{", "}" );
                    Parse( local:template );
                ),
                Title( "Tabulate Preset" ),
                Reapply( 1 )
            ), Add Pin Annotation(
                Seg( BarSeg( 1 ) ),
                Index( {0, 0} ),
                Index Row( {0, 0} ),
                UniqueID( 927827568 ),
                FoundPt( {455, 294} ),
                Origin( {0.0330578512396694, 14.094387755102} ),
                Tag Line( 1 )
            )}
        )
    )
);

Code Explanation:

1. Open data table;
2. Create new Graph Builder window.
3. Set window size.
4. Hide control panel.
5. Assign X variable.
6. Add bar element.
7. Send report commands.
8. Set graphlet picture.
9. Define analysis columns.
10. Insert statistics definition.
11. Construct column table.
12. Define tabulate template.
13. Insert into template.
14. Parse template.
15. Set graphlet title.
16. Reapply settings.
17. Add pin annotation.

Example 362

Summary: Creates a variability chart with nested factors using operator and part configurations, displaying standard deviation charts in Graph Builder.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 532, 456 ),
    Show Control Panel( 0 ),
    Variables( X( :Weight ), Y( :Oxy ) ),
    Elements( Points( X, Y, Legend( 254 ) ), Smoother( X, Y, Legend( 255 ) ) ),
    SendToReport(
        Dispatch( {}, "Graph Builder", FrameBox,
            {Set Gridlet(
                Annex(
                    {{Matcher( "Weight" ), value( :Weight[local:_firstRow] )}, {Matcher( "Runtime" ), value( :Runtime[local:_firstRow] )},
                    {Matcher( "RunPulse" ), value( :RunPulse[local:_firstRow] )}, {Matcher( "RstPulse" ),
                    value( :RstPulse[local:_firstRow] )}, {Matcher( "MaxPulse" ), value( :MaxPulse[local:_firstRow] )}}
                )
            ), Add Pin Annotation(
                Seg( Marker Seg( 1 ) ),
                Index( 3 ),
                Index Row( 3 ),
                UniqueID( 1010761747 ),
                FoundPt( {510, 215} ),
                Origin( {71.1423305785124, 54.7435829805102} ),
                Tag Line( 1 )
            )}
        )
    )
);

Code Explanation:

1. Open data_table data
2. Create Graph Builder window.
3. Set window size.
4. Hide control panel.
5. Assign X and Y variables.
6. Add points and smoother elements.
7. Configure gridlet settings.
8. Append additional gridlet items.
9. Add pin annotation.
10. Position annotation on graph.

Example 363

Summary: Creates a variability chart with nested factors using Graph Builder, displaying standard deviation charts and hover labels for selected columns.

Code:

dt = Open("data_table.jmp");
dt << Graph Builder(
    Size( 472, 396 ),
    Show Control Panel( 0 ),
    Variables( X( :sex ), Y( Transform Column( "Log[weight]", Formula( Log( :weight ) ) ) ) ),
    Elements( Bar( X, Y, Legend( 4 ) ) ),
    SendToReport(
        Dispatch( {}, "Graph Builder", FrameBox,
            {Set Textlet(
                Setup(
                    local:r = local:_dataTable << Get Rows Where( local:_whereExpr );
                    local:ss = local:_dataTable << Subset( Private, Invisible, Rows( local:r ) );
                    If( N Items( local:_measurements ) > 0,
                        local:colName = Char( local:_measurements[1] );
                        Show( colName );
                        If( Starts With( local:colName, "Transform Column" ),
                            local:colName = Words( local:colName, "\!"" )[2]
                        );
                        Summarize(
                            local:ss,
                            local:c = Count( local:_measurements[1] ),
                            local:s = Sum( local:_measurements[1] ),
                            local:m = Mean( local:_measurements[1] ),
                            local:d = Quantile( local:_measurements[1], 0.5 ),
                            local:n = Min( local:_measurements[1] ),
                            local:x = Max( local:_measurements[1] ),
                            local:v = Std Dev( local:_measurements[1] )
                        );
                        local:markup =
                        "Summary Statistics for <b>{local:colName}</b>: 
<i>Count</i>  = {Round(local:c, 2)}
<i>Mean</i>   = {Round(local:m, 2)}
<i>Median</i> = {Round(local:d, 2)}
<i>StdDev</i> = {Round(local:v, 2)}
<i>Min</i>    = {Round(local:n, 2)}
<i>Max</i>    = {Round(local:x, 2)}
<i>Sum</i>    = {Round(local:s, 2)}
";
                    ,
                        Summarize( local:ss, local:c = Count() );
                        local:markup = "<i>Count</i>  = {Round(local:c, 2)}";
                    );
                ),
                Markup( local:markup )
            ), Add Pin Annotation(
                Seg( BarSeg( 1 ) ),
                Index( {0, 0} ),
                Index Row( {0, 0} ),
                UniqueID( 930485424 ),
                FoundPt( {175, 244} ),
                Origin( {0.076036866359447, 2.18870828520083} ),
                Tag Line( 1 )
            )}
        )
    )
);

Code Explanation:

1. Open data table.
2. Create Graph Builder object.
3. Set graph size.
4. Hide control panel.
5. Define X and Y variables.
6. Add bar element.
7. Configure report settings.
8. Set up textlet for hover labels.
9. Retrieve filtered data rows.
10. Summarize statistics for selected column.

Example 364

Summary: Creates a heatmap with nested factors using Graph Builder, displaying standard deviation charts and applying marker presets.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 534, 492 ),
    Show Control Panel( 0 ),
    Continuous Color Theme( "Blue White Red" ),
    Variables( X( :Turning Circle ), Y( :Weight ), Wrap( :Country ) ),
    Elements( Heatmap( X, Y, Legend( 4 ), Bin Shape( "Hexagonal" ) ) ),
    SendToReport(
        Dispatch( {}, "Graph Builder", FrameBox( 3 ),
            {Set Graphlet(
                Picture(
                    Try(
                        loader = If( Class Exists( "hllLoader" ),
                            New Object( "hllLoader" ),
                            Include( "$BUILTIN_SCRIPTS/hllib.jsl" )
                        );
                        loader:setDebug( 0 );
                        hlp = loader:lazyLoad( "hllPresets" );
                        hlp:launchMarker();
                    )
                ),
                Title( "Marker Preset" ),
                Reapply( 1 )
            ), Add Pin Annotation(
                Seg( HexSeg( 1 ) ),
                Index( 10 ),
                Index Row( 11 ),
                UniqueID( -1055720534 ),
                FoundPt( {185, 411} ),
                Origin( {38.5635407183664, 2635.13513513514} ),
                Offset( {24, -156} ),
                Tag Line( 1 )
            )}
        ),
        Dispatch( {}, "400", LegendBox, {Set Title( "Count" )} )
    )
);

Code Explanation:

1. Open data table.
2. Create Graph Builder window.
3. Set graph size.
4. Hide control panel.
5. Choose color theme.
6. Define variables for X, Y, and wrap.
7. Add heatmap element.
8. Send report to Graph Builder.
9. Load external script.
10. Apply marker preset and add annotation.

Example 365

Summary: Creates a heatmap with hexagonal bin shape to visualize the relationship between Turning Circle and Weight, using Graph Builder in JMP.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 534, 456 ),
    Show Control Panel( 0 ),
    Variables( X( :Turning Circle ), Y( :Weight ) ),
    Elements( Heatmap( X, Y, Legend( 4 ), Bin Shape( "Hexagonal" ) ) ),
    SendToReport(
        Dispatch( {}, "Graph Builder", FrameBox,
            {Add Pin Annotation(
                Seg( HexSeg( 1 ) ),
                Index( 28 ),
                Index Row( 71 ),
                UniqueID( 1303317468 ),
                FoundPt( {411, 327} ),
                Origin( {33.7318059299191, 2936.5737833595} ),
                Tag Line( 1 )
            ), Add Pin Annotation(
                Seg( HexSeg( 1 ) ),
                Index( 20 ),
                Index Row( 1 ),
                UniqueID( 1303317460 ),
                FoundPt( {636, 265} ),
                Origin( {41.4550763701707, 3413.26530612245} ),
                Offset( {-296, -88} ),
                Tag Line( 1 )
            )}
        )
    )
);

Code Explanation:

1. Open data table.
2. Create Graph Builder window.
3. Set graph size to 534x456.
4. Hide control panel.
5. Assign X variable: Turning Circle.
6. Assign Y variable: Weight.
7. Add heatmap element.
8. Use hexagonal bin shape.
9. Add first pin annotation.
10. Add second pin annotation.

Example 366

Summary: Creates a heatmap in Graph Builder to visualize data from a nested factor configuration, with standard deviation charts displayed.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 570, 449 ),
    Show Control Panel( 0 ),
    Variables( X( :Region ) ),
    Elements( Heatmap( X, Legend( 2 ) ) ),
    SendToReport(
        Dispatch( {}, "Graph Builder", FrameBox,
            Add Pin Annotation(
                Seg( RectSeg( 1 ) ),
                Index( 1 ),
                Index Row( 1 ),
                UniqueID( 858949137 ),
                FoundPt( {179, 204} ),
                Origin( {1.17441860465116, 0.115776081424936} )
            )
        )
    )
);

Code Explanation:

1. Open data_table data
2. Create Graph Builder window.
3. Set graph size.
4. Hide control panel.
5. Assign Region to X-axis.
6. Add heatmap element.
7. Configure legend with 2 items.
8. Send report to Graph Builder.
9. Add pin annotation.
10. Position pin annotation.

Example 367

Summary: Creates a heatmap to visualize nested factors using Graph Builder, with interactive features for customization and analysis.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 464, 371 ),
    Show Control Panel( 0 ),
    Variables( X( :age ), Y( :height ), Y( :sex, Position( 1 ) ), Color( :weight ) ),
    Elements( Heatmap( X, Y( 1 ), Y( 2 ), Legend( 2 ) ) ),
    SendToReport(
        Dispatch( {}, "Graph Builder", FrameBox,
            {Add Pin Annotation(
                Seg( RectSeg( 1 ) ),
                Index( 7 ),
                Index Row( 15 ),
                UniqueID( 757232551 ),
                FoundPt( {216, 204} ),
                Origin( {1.78571428571429, 62.9392971246006} ),
                Tag Line( 1 )
            ), Add Pin Annotation(
                Seg( RectSeg( 1 ) ),
                Index( 2 ),
                Index Row( 1 ),
                UniqueID( 757232546 ),
                FoundPt( {91, 202} ),
                Origin( {0, 63.0990415335463} ),
                Offset( {62, 82} ),
                Tag Line( 1 )
            ), Add Pin Annotation(
                Seg( RectSeg( 1 ) ),
                Index( 0 ),
                Index Row( 4 ),
                UniqueID( 757232544 ),
                FoundPt( {95, 341} ),
                Origin( {0.0571428571428572, 51.9968051118211} ),
                Offset( {46, 26} ),
                Tag Line( 1 )
            )}
        ),
        Dispatch( {}, "400", LegendBox, {Set Title( "weight" )} )
    )
);

Code Explanation:

1. Open data table;
2. Launch Graph Builder.
3. Set graph size.
4. Hide control panel.
5. Define X, Y, and Color variables.
6. Add heatmap element.
7. Add first pin annotation.
8. Add second pin annotation.
9. Add third pin annotation.
10. Set legend title.

Example 368

Summary: Creates a heatmap to visualize the relationship between age, height, and sex, with weight as a color variable, using Graph Builder.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 464, 371 ),
    Show Control Panel( 0 ),
    Variables( X( :age ), Y( :height ), Y( :sex, Position( 1 ) ), Color( :weight ) ),
    Elements( Heatmap( X, Y( 1 ), Y( 2 ), Legend( 2 ) ) ),
    SendToReport(
        Dispatch( {}, "Graph Builder", FrameBox,
            {Add Pin Annotation(
                Seg( RectSeg( 1 ) ),
                Index( 23 ),
                Index Row( 23 ),
                UniqueID( 619277191 ),
                FoundPt( {472, 249} ),
                Origin( {1.8, 63.3860759493671} )
            ), Add Pin Annotation(
                Seg( RectSeg( 1 ) ),
                Index( 4 ),
                Index Row( 4 ),
                UniqueID( 619277172 ),
                FoundPt( {80, 209} ),
                Origin( {-0.157142857142857, 61.25} ),
                Offset( {47, 60} ),
                Tag Line
            ), Add Pin Annotation(
                Seg( RectSeg( 1 ) ),
                Index( 0 ),
                Index Row( 0 ),
                UniqueID( 619277168 ),
                FoundPt( {84, 348} ),
                Origin( {-0.1, 51.3528481012658} ),
                Offset( {11, 13} ),
                Tag Line
            )}
        )
    )
);

Code Explanation:

1. Open data table.
2. Create Graph Builder.
3. Set graph size.
4. Hide control panel.
5. Assign variables: age, height, sex, weight.
6. Add heatmap element.
7. Send report to Graph Builder.
8. Add first pin annotation.
9. Add second pin annotation.
10. Add third pin annotation.

Example 369

Summary: Creates a heatmap to visualize fiber levels based on hot/cold temperatures, with color-coded variance for calories.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 739, 517 ),
    Show Control Panel( 0 ),
    Variables( X( :"Hot/Cold"n ), Y( :Fiber ), Color( :Calories, Summary Statistic( "Variance" ) ) ),
    Elements( Heatmap( X, Y, Legend( 4 ) ) ),
    SendToReport(
        Dispatch( {}, "Graph Builder", FrameBox,
            {Add Pin Annotation(
                Seg( RectSeg( 1 ) ),
                Index( 3 ),
                Index Row( 0 ),
                UniqueID( 757232547 ),
                FoundPt( {198, 240} ),
                Origin( {-0.0913669064748202, 8.88888888888889} ),
                RightOfCenter( 0 ),
                Tag Line( 1 )
            ), Add Pin Annotation(
                Seg( RectSeg( 1 ) ),
                Index( 7 ),
                Index Row( 46 ),
                UniqueID( 822654327 ),
                FoundPt( {621, 385} ),
                Origin( {1.12589928057554, 4.15032679738562} ),
                RightOfCenter( 1 ),
                Tag Line( 1 )
            )}
        )
    )
);

Code Explanation:

1. Open data_table data
2. Create Graph Builder window.
3. Set size to 739x517.
4. Hide control panel.
5. Assign X variable: Hot/Cold.
6. Assign Y variable: Fiber.
7. Assign Color variable: Calories.
8. Calculate variance for calories.
9. Add heatmap element.
10. Add two pin annotations.

Example 370

Summary: Creates a heatmap to visualize fiber content across hot and cold temperatures, utilizing Graph Builder's Heatmap element and color-coded by variance.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 739, 517 ),
    Show Control Panel( 0 ),
    Variables( X( :"Hot/Cold"n ), Y( :Fiber ), Color( :Calories, Summary Statistic( "Variance" ) ) ),
    Elements( Heatmap( X, Y, Legend( 4 ) ) ),
    SendToReport(
        Dispatch( {}, "Graph Builder", FrameBox,
            {Add Pin Annotation(
                Seg( RectSeg( 1 ) ),
                Index( 5 ),
                Index Row( 0 ),
                UniqueID( 641721397 ),
                FoundPt( {461, 285} ),
                Origin( {-0.111510791366906, 9.05882352941176} ),
                Tag Line( 1 )
            ), Add Pin Annotation(
                Seg( RectSeg( 1 ) ),
                Index( 11 ),
                Index Row( 57 ),
                UniqueID( 641721403 ),
                FoundPt( {719, 406} ),
                Origin( {0.630935251798561, 5.3681917211329} ),
                Tag Line( 1 )
            )}
        )
    )
);

Code Explanation:

1. Open data table.
2. Launch Graph Builder.
3. Set graph size.
4. Hide control panel.
5. Define X, Y, and Color variables.
6. Add Heatmap element.
7. Send report to Graph Builder.
8. Add first pin annotation.
9. Specify segment and index for first pin.
10. Add second pin annotation.

Example 371

Summary: Creates a heatmap in Graph Builder to visualize the relationship between sex and age, with a pin annotation added for further analysis.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 536, 398 ),
    Show Control Panel( 0 ),
    Variables( X( :sex ), Y( :age ) ),
    Elements( Heatmap( X, Y, Legend( 10 ) ) ),
    SendToReport(
        Dispatch( {}, "Graph Builder", FrameBox,
            Add Pin Annotation(
                Seg( RectSeg( 1 ) ),
                Index( 8 ),
                Index Row( 8 ),
                UniqueID( 688147512 ),
                FoundPt( {355, 250} ),
                Origin( {0.721774193548387, 2.01895043731778} ),
                Offset( {-236, -78} ),
                Tag Line
            )
        )
    )
);

Code Explanation:

1. Open data table;
2. Launch Graph Builder.
3. Set graph size.
4. Hide control panel.
5. Assign X and Y variables.
6. Create heatmap element.
7. Add legend to heatmap.
8. Send report to Graph Builder.
9. Add pin annotation.
10. Configure pin annotation properties.

Example 372

Summary: Creates a heatmap in Graph Builder to visualize the relationship between sex, height, and age, with interactive features for customization.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 524, 453 ),
    Show Control Panel( 0 ),
    Variables( X( :sex ), X( :height, Position( 1 ) ), Y( :age ) ),
    Elements( Heatmap( X( 1 ), X( 2 ), Y, Legend( 4 ) ) ),
    SendToReport(
        Dispatch( {}, "Graph Builder", FrameBox,
            Add Pin Annotation(
                Seg( RectSeg( 1 ) ),
                Index( 2 ),
                Index Row( 2 ),
                UniqueID( 731882946 ),
                FoundPt( {145, 290} ),
                Origin( {-0.115702479338843, 1.84183673469388} )
            )
        )
    )
);

Code Explanation:

1. Open data table;
2. Create new Graph Builder window.
3. Set window size.
4. Hide control panel.
5. Define X and Y variables.
6. Add heatmap element.
7. Customize heatmap legend.
8. Send report to Graph Builder.
9. Add pin annotation to graph.
10. Specify annotation properties.

Example 373

Summary: Creates a heatmap in Graph Builder to visualize data from 'data_table.jmp', with nested factors and operator configurations, and displays standard deviation charts.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 495, 448 ),
    Show Control Panel( 0 ),
    Variables( X( :Age Group ), Color( :Salary ) ),
    Elements( Heatmap( X, Legend( 1 ) ) ),
    SendToReport(
        Dispatch( {}, "Graph Builder", FrameBox,
            Add Pin Annotation(
                Seg( RectSeg( 1 ) ),
                Index( 1 ),
                Index Row( 1 ),
                UniqueID( 496357505 ),
                FoundPt( {126, 135} ),
                Origin( {0.989669421487603, 0.290816326530612} )
            )
        )
    )
);

Code Explanation:

1. Open data table;
2. Launch Graph Builder.
3. Set graph size.
4. Hide control panel.
5. Assign variables to axes.
6. Create heatmap element.
7. Send report to Graph Builder.
8. Add pin annotation to graph.
9. Specify annotation segment.
10. Define annotation properties.

Example 374

Summary: Creates a variability chart with nested factors using operator and part configurations, displaying standard deviation charts in Graph Builder.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 534, 456 ),
    Show Control Panel( 0 ),
    Variables( Y( :Price ) ),
    Elements( Histogram( Y, Legend( 5 ) ) ),
    SendToReport(
        Dispatch( {}, "Price", ScaleBox,
            {Scale( "Log", {Log Base( 2 )} ), Format( "Best", 12 ), Min( 1 ), Max( 12000 ), Inc( 1 ), Minor Ticks( 1 )}
        ),
        Dispatch( {}, "Graph Builder", FrameBox,
            Add Pin Annotation(
                Seg( Hist Seg( 1 ) ),
                Index( {120, 132} ),
                Index Row( {120, 132} ),
                UniqueID( 2139384184 ),
                FoundPt( {408, 209} ),
                Origin( {177.279874213836, 1528.4767248731} ),
                Offset( {15, 60} ),
                Tag Line( 1 )
            )
        )
    )
);

Code Explanation:

1. Open data table;
2. Create Graph Builder window.
3. Set size to 534x456.
4. Hide control panel.
5. Set Y variable to Price.
6. Add histogram element.
7. Set Y scale to log base 2.
8. Format Y axis with best display.
9. Set Y axis min to 1.
10. Set Y axis max to 12000.

Example 375

Summary: Creates a graph builder window with a histogram element to visualize height data grouped by sex, utilizing Graph Builder and SendToReport functions.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 528, 454 ),
    Show Control Panel( 0 ),
    Variables( Y( :height ), Group X( :sex ) ),
    Elements( Histogram( Y, Legend( 5 ) ) ),
    SendToReport(
        Dispatch( {}, "Graph Builder", FrameBox( 2 ),
            Add Pin Annotation(
                Seg( Hist Seg( 1 ) ),
                Index( {96, 108} ),
                Index Row( {96, 108} ),
                UniqueID( 823954560 ),
                FoundPt( {316, 110} ),
                Origin( {-0.429460580912863, 71.2946428571429} )
            )
        )
    )
);

Code Explanation:

1. Open data table;
2. Create Graph Builder window.
3. Set window size.
4. Hide control panel.
5. Define Y variable as height.
6. Define Group X variable as sex.
7. Add histogram element.
8. Send report to Graph Builder.
9. Dispatch to Graph Builder frame.
10. Add pin annotation to histogram.

Example 376

Summary: Creates a graph builder with a histogram element, filtered by age ranges 12 to 17, and adds a pin annotation for further analysis.

Code:

dt = Open("data_table.jmp");
gb = dt << Graph Builder(
    Show Control Panel( 0 ),
    Variables( Y( :height ) ),
    Elements( Histogram( Y, Legend( 2 ) ) ),
    Local Data Filter( Add Filter( columns( :age ), Where( :age == {12, 13, 14, 15, 16, 17} ), Display( :age, N Items( 6 ) ) ) ),
    SendToReport(
        Dispatch( {}, "Graph Builder", FrameBox,
            Add Pin Annotation(
                Seg( Hist Seg( 1 ) ),
                Index( {96, 108} ),
                Index Row( {96, 108} ),
                UniqueID( -1416483840 ),
                FoundPt( {554, 151} ),
                Origin( {0.681921487603306, 71.375} ),
                RightOfCenter( 0 ),
                Tag Line( 1 )
            )
        )
    )
);

Code Explanation:

1. Open table.
2. Create graph builder.
3. Hide control panel.
4. Set Y variable.
5. Add histogram element.
6. Apply local data filter.
7. Filter ages 12 to 17.
8. Send report to Graph Builder.
9. Add pin annotation.
10. Configure annotation settings.

Example 377

Summary: Creates a variability chart with nested factors using operator and part configurations, displaying standard deviation charts.

Code:

dt = Open("data_table.jmp");
gb = dt << Graph Builder(
    Show Control Panel( 0 ),
    Variables( Y( :height ) ),
    Elements( Histogram( Y, Legend( 2 ) ) ),
    Local Data Filter( Add Filter( columns( :age ), Where( :age == {12, 13, 14, 15, 16, 17} ), Display( :age, N Items( 6 ) ) ) ),
    SendToReport(
        Dispatch( {}, "Graph Builder", FrameBox,
            Add Pin Annotation(
                Seg( Hist Seg( 1 ) ),
                Index( {96, 108} ),
                Index Row( {96, 108} ),
                UniqueID( -1416483840 ),
                FoundPt( {554, 151} ),
                Origin( {0.681921487603306, 71.375} ),
                RightOfCenter( 0 ),
                Tag Line( 1 )
            )
        )
    )
);
Data Table("data_table") << Clear Select << Select Rows( Index( 1, 15 ) ) << Hide and Exclude;

Code Explanation:

1. Open data table;
2. Create Graph Builder.
3. Set Y variable to :height.
4. Add Histogram element.
5. Disable Control Panel.
6. Add Local Data Filter.
7. Filter age for specific values.
8. Send report to Graph Builder.
9. Add pin annotation to histogram.
10. Hide and exclude rows 1 to 15.

Example 378

Summary: Creates a variability chart with nested factors using operator and part configurations, displaying standard deviation charts in JMP.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 534, 450 ),
    Show Control Panel( 0 ),
    Variables( X( :age ), Y( :weight ), Color( :height ) ),
    Elements( Box Plot( X, Y, Legend( 3 ) ) ),
    SendToReport(
        Dispatch( {}, "Graph Builder", FrameBox,
            {Set Graphlet(
                Picture(
                    Try(
                        loader = If( Class Exists( "hllLoader" ),
                            New Object( "hllLoader" ),
                            Include( "$BUILTIN_SCRIPTS/hllib.jsl" )
                        );
                        loader:setDebug( 0 );
                        hlp = loader:lazyLoad( "hllPresets" );
                        hlp:launchLabel Viewer();
                    )
                ),
                Title( "Label Viewer Preset" ),
                Reapply( 1 ),
                Thumbnail( {200, 200} )
            ), Add Pin Annotation(
                Seg( Box Plot Seg( 2 ) ),
                Index( {1, 1} ),
                Index Row( {1, 1} ),
                UniqueID( 522683969 ),
                FoundPt( {445, 333} ),
                Origin( {0.96583850931677, 104.076148714286} ),
                Tag Line( 1 )
            )}
        )
    )
);

Code Explanation:

1. Open data table;
2. Create Graph Builder window.
3. Set window size.
4. Hide control panel.
5. Assign variables to axes.
6. Add box plot element.
7. Send report commands.
8. Initialize loader object.
9. Load label viewer preset.
10. Launch label viewer.

Example 379

Summary: Creates a variability chart with nested factors using operator and part configurations, displaying standard deviation charts in Graph Builder.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 662, 513 ),
    Show Control Panel( 0 ),
    Variables( X( :Mfr ), Y( :Sugars ), Overlay( :Calories, Levels( 4 ) ) ),
    Elements( Line( X, Y, Legend( 6 ), Summary Statistic( "Variance" ), Stack( 1 ) ) ),
    SendToReport(
        Dispatch( {}, "Graph Builder", FrameBox,
            Add Pin Annotation(
                Seg( Line Seg( 1 ) ),
                Index( {3, 3} ),
                Index Row( {11, 11} ),
                UniqueID( 838809542 ),
                FoundPt( {1418, 738} ),
                Origin( {4.00826446280992, 21.3368983957219} ),
                Offset( {-164, -128} ),
                Tag Line( 1 )
            )
        )
    )
);

Code Explanation:

1. Open data table;
2. Launch Graph Builder.
3. Set graph size to 662x513.
4. Hide control panel.
5. Assign Mfr to X-axis.
6. Assign Sugars to Y-axis.
7. Overlay Calories with 4 levels.
8. Add line element with variance summary.
9. Stack line element.
10. Add pin annotation to graph.

Example 380

Summary: Creates a variability chart with nested factors using operator and part configurations, displaying standard deviation charts in Graph Builder.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 470, 393 ),
    Show Control Panel( 0 ),
    Variables( X( :weight ), Y( :height ), Overlay( :sex ), Color( :height ) ),
    Elements( Line( X, Y, Legend( 11 ), Smoothness( 0.5 ), Summary Statistic( "% of Total" ), Missing Values( "No Connection" ) ) ),
    SendToReport(
        Dispatch( {}, "Graph Builder", FrameBox,
            {DispatchSeg( Line Seg( "Line (F)" ), {Line Style( "Smooth" )} ), DispatchSeg(
                Line Seg( "Line (M)" ),
                {Line Style( "Smooth" )}
            ), {Add Pin Annotation(
                Seg( Line Seg( 1 ) ),
                Index( 11 ),
                Index Row( 35 ),
                UniqueID( 761180470 ),
                FoundPt( {511, 385} ),
                Origin( {115.135135135135, 0.0562688821752266} )
            ), Add Pin Annotation(
                Seg( Line Seg( 1 ) ),
                Index( 10 ),
                Index Row( 8 ),
                UniqueID( 761180468 ),
                FoundPt( {502, 130} ),
                Origin( {112.481572481572, 0.171827794561934} )
            )}}
        )
    )
);

Code Explanation:

1. Open data table.
2. Create Graph Builder window.
3. Set window size.
4. Hide control panel.
5. Assign variables to axes and overlay.
6. Add line element with smoothing.
7. Use percentage of total summary statistic.
8. Handle missing values without connection.
9. Customize line styles for each sex.
10. Add pin annotations at specified points.

Example 381

Summary: Creates a variability chart with nested factors using operator and part configurations, displaying standard deviation charts in Graph Builder.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 534, 454 ),
    Show Control Panel( 0 ),
    Variables( X( :height ), Y( :weight ), Y( :age, Position( 1 ) ) ),
    Elements( Line( X, Y( 1 ), Y( 2 ), Legend( 7 ) ) ),
    SendToReport(
        Dispatch( {}, "Graph Builder", FrameBox,
            {Add Pin Annotation(
                Seg( Line Seg( 2 ) ),
                Index( 8 ),
                Index Row( 16 ),
                UniqueID( 761710688 ),
                FoundPt( {322, 390} ),
                Origin( {62.0652173913043, 3.06122448979592} )
            ), Add Pin Annotation(
                Seg( Line Seg( 1 ) ),
                Index( 7 ),
                Index Row( 1 ),
                UniqueID( 691673278 ),
                FoundPt( {301, 183} ),
                Origin( {61.0869565217391, 108.673469387755} )
            )}
        )
    )
);

Code Explanation:

1. Open data table;
2. Create Graph Builder window.
3. Set graph size.
4. Hide control panel.
5. Define X and Y variables.
6. Add second Y variable.
7. Plot line element.
8. Send report commands.
9. Add pin annotation for line segment 2.
10. Add pin annotation for line segment 1.

Example 382

Summary: Creates a variability chart with nested factors using operator and part configurations, displaying standard deviation charts in JMP.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 422, 517 ),
    Show Control Panel( 0 ),
    Variables( Color( :Name( "Mean(X)" ) ), Shape( :State ) ),
    Elements( Map Shapes( Legend( 1 ) ) ),
    SendToReport(
        Dispatch( {}, "Graph Builder", FrameBox,
            Add Pin Annotation(
                Seg( Shape Seg( 1 ) ),
                Index( 10 ),
                Index Row( 10 ),
                UniqueID( 687501146 ),
                FoundPt( {599, 384} ),
                Origin( {-82.9728353808354, 32.9044560889923} )
            )
        )
    )
);

Code Explanation:

1. Open data table;
2. Create new Graph Builder window.
3. Set window size to 422x517.
4. Hide control panel.
5. Set color variable to "Mean(X)".
6. Set shape variable to "State".
7. Add map shapes element.
8. Enable legend for map shapes.
9. Add pin annotation to graph.
10. Position pin at specific coordinates.

Example 383

Summary: Creates a variability chart with nested factors using operator and part configurations, displaying standard deviation charts in Graph Builder.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 528, 449 ),
    Show Control Panel( 0 ),
    Variables( X( :Country ) ),
    Elements( Bar( X, Legend( 6 ) ) ),
    SendToReport(
        Dispatch( {}, "Graph Builder", FrameBox,
            {Set Graphlet( Picture( Multiple Correspondence Analysis( Y( :Type ), Cross Table( Show Total( 1 ) ) ) ) ),
            Add Pin Annotation(
                Seg( BarSeg( 1 ) ),
                Index( {0, 0} ),
                Index Row( {0, 0} ),
                UniqueID( 670224992 ),
                FoundPt( {123, 244} ),
                Origin( {-0.0847107438016529, 27.0189258312021} ),
                Tag Line( 1 )
            )}
        )
    )
);

Code Explanation:

1. Open data table.
2. Create Graph Builder window.
3. Set window size.
4. Hide control panel.
5. Set X variable to Country.
6. Add bar element.
7. Send report to Graph Builder.
8. Set graphlet to Multiple Correspondence Analysis.
9. Add pin annotation to graph.
10. Configure annotation properties.

Example 384

Summary: Creates a mosaic plot with nested factors using Graph Builder, displaying standard deviation charts and pin annotations.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 496, 366 ),
    Show Control Panel( 0 ),
    Variables( X( :age ), Y( :sex ), Frequency( Transform Column( "ww", Formula( :weight / 100 ) ) ) ),
    Elements( Mosaic( X, Y, Legend( 5 ) ) ),
    SendToReport(
        Dispatch( {}, "Graph Builder", FrameBox,
            Add Pin Annotation(
                Seg( MosaicSeg( 1 ) ),
                Index( {1, 1} ),
                Index Row( {1, 1} ),
                UniqueID( 685142067 ),
                FoundPt( {196, 135} ),
                Origin( {0.297297297297297, 0.729032258064516} )
            )
        )
    )
);

Code Explanation:

1. Open data table;
2. Launch Graph Builder.
3. Set graph size.
4. Hide control panel.
5. Assign variables: age, sex, weight.
6. Create mosaic plot.
7. Send report to Graph Builder.
8. Add pin annotation.
9. Specify segment for annotation.
10. Define annotation properties.

Example 385

Summary: Creates a mosaic graph with nested factors using Graph Builder, displaying standard deviation charts and pin annotations.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 534, 448 ),
    Show Control Panel( 0 ),
    Variables( X( :Type ), Y( :Country ) ),
    Elements( Mosaic( X, Y, Legend( 4 ) ) ),
    SendToReport(
        Dispatch( {}, "Graph Builder", FrameBox,
            Add Pin Annotation(
                Seg( MosaicSeg( 1 ) ),
                Index( {1, 1} ),
                Index Row( {1, 1} ),
                UniqueID( 720943300 ),
                FoundPt( {182, 216} ),
                Origin( {0.272, 0.613513513513513} )
            )
        )
    )
);

Code Explanation:

1. Open data table;
2. Launch Graph Builder.
3. Set graph size.
4. Hide control panel.
5. Assign X and Y variables.
6. Create mosaic element.
7. Send report to Graph Builder.
8. Dispatch to Graph Builder frame.
9. Add pin annotation.
10. Specify annotation details.

Example 386

Summary: Creates a pie chart with nested factors using Graph Builder, displaying summary statistics and standard deviation charts.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 507, 440 ),
    Show Control Panel( 0 ),
    Variables( X( :age ), Y( :height ) ),
    Elements( Pie( X, Y, Legend( 4 ) ) ),
    SendToReport(
        Dispatch( {}, "Graph Builder", FrameBox,
            {Set Graphlet(
                Picture(
                    local:_GetSummaryStatistic_ = Function( {stat},
                        {isTabulate, keyword, theStat},
                        If( !Is Missing( stat ),
                            isTabulate = "Tabulate" == "Tabulate";
                            If( isTabulate,
                                keyword = "Statistics";
                                theStat = Match( stat,
                                    "First Quartile", "Quantiles(25)",
                                    "Third Quartile", "Quantiles(75)",
                                    "% of Factor", "",
                                    "% of Grand Total", "",
                                    "\!"" || stat || "\!""
                                );
                            ,
                                keyword = "Summary Statistic";
                                theStat = "\!"" || stat || "\!"";
                            );
                            If( !Is Missing( theStat ),
                                ", " || keyword || "(" || theStat || ")",
                                ""
                            );
                        ,
                            ""
                        )
                    );
                    local:statsDef = local:_GetSummaryStatistic_( local:_summaryStatistic );
                    local:analysisCols = If( N Items( local:_measurements ),
                        Eval Insert(
                            "     
Column Table( 
            Analysis Columns( {local:_measurements} )
            {local:statsDef}
        ),",
                            "{",
                            "}"
                        ),
                        ""
                    );
                    local:template =
                    "
    Tabulate(
    Show Control Panel( 0 ),
    Add Table(
{local:analysisCols}
        Row Table(
            Grouping Columns( {local:_groupings} )
        )
    )
)
";
                    Eval Insert Into( local:template, "{", "}" );
                    Parse( local:template );
                ),
                Title( "Tabulate Preset" ),
                Reapply( 1 )
            ), Add Pin Annotation(
                Seg( Pie Seg( 1 ) ),
                Index( {4, 0} ),
                Index Row( {34, 0} ),
                UniqueID( 675673252 ),
                FoundPt( {475, 327} ),
                Origin( {-0.498214285714286, -0.0428571428571429} ),
                Tag Line( 1 )
            )}
        )
    )
);

Code Explanation:

1. Open data table;
2. Launch Graph Builder.
3. Set graph size.
4. Hide control panel.
5. Assign age to X-axis.
6. Assign height to Y-axis.
7. Create pie chart element.
8. Configure hover labels.
9. Define summary statistic function.
10. Apply tabulate preset.

Example 387

Summary: Creates a treemap visualization with nested factors using Graph Builder, displaying standard deviation charts and enabling interactive exploration.

Code:

dt = Open("data_table.jmp");
obj = Graph Builder(
    Size( 573, 390 ),
    Show Control Panel( 0 ),
    Variables( X( :sex ), X( :age, Position( 1 ) ), Color( :height ), Size( :height ) ),
    Elements( Treemap( X( 1 ), X( 2 ), Legend( 12 ), Summary Statistic( "% of Total" ) ) ),
    SendToReport(
        Dispatch( {}, "Graph Builder", FrameBox,
            Add Pin Annotation(
                Seg( TreeMapSeg( 1 ) ),
                Index( 8 ),
                Index Row( 20 ),
                UniqueID( 703552568 ),
                FoundPt( {299, 260} ),
                Origin( {321.464226289517, 182.291666666667} ),
                Offset( {-300, -74} ),
                RightOfCenter( 0 ),
                Tag Line( 1 )
            )
        )
    )
);

Code Explanation:

1. Open data table.
2. Create Graph Builder object.
3. Set graph size.
4. Hide control panel.
5. Define X and Y variables.
6. Set color and size by height.
7. Add treemap element.
8. Use percentage of total summary statistic.
9. Send report to Graph Builder.
10. Add pin annotation to treemap.

Example 388

Summary: Creates a variability chart with nested factors using Graph Builder, displaying standard deviation charts and pin annotations.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 367, 302 ),
    Show Control Panel( 0 ),
    Variables( X( :Day of Week ), Y( :Tip Amount ), Color( :Number of Guests ) ),
    Elements( Points( X, Y, Legend( 10 ), Summary Statistic( "Sum" ) ) ),
    SendToReport(
        Dispatch( {}, "Graph Builder", FrameBox,
            Add Pin Annotation(
                Seg( Marker Seg( 1 ) ),
                Index( 0 ),
                Index Row( 106 ),
                UniqueID( 802850288 ),
                FoundPt( {102, 268} ),
                Origin( {0.032258064516129, 75.2032520325203} )
            )
        )
    )
);

Code Explanation:

1. Open data table.
2. Launch Graph Builder.
3. Set window size.
4. Hide control panel.
5. Assign variables.
6. Add points element.
7. Summarize statistic as sum.
8. Send report to Graph Builder.
9. Add pin annotation.
10. Configure pin annotation properties.

Example 389

Summary: Creates a variability chart with nested factors using operator and part configurations, displaying standard deviation charts in Graph Builder.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 488, 400 ),
    Show Control Panel( 0 ),
    Variables( X( :Day of Week ), Y( :Tip Amount ), Color( :Number of Guests ) ),
    Elements( Points( X, Y, Legend( 10 ), Summary Statistic( "Sum" ) ) ),
    SendToReport(
        Dispatch( {}, "Graph Builder", FrameBox,
            Add Pin Annotation(
                Seg( Marker Seg( 1 ) ),
                Index( 4 ),
                Index Row( 0 ),
                UniqueID( 833431028 ),
                FoundPt( {457, 329} ),
                Origin( {4.00116009280743, 89.5348837209302} )
            )
        )
    )
);

Code Explanation:

1. Open data table;
2. Create Graph Builder.
3. Set graph size.
4. Hide control panel.
5. Define X, Y, and color variables.
6. Add points element.
7. Use summary statistic "Sum".
8. Send report to Graph Builder.
9. Add pin annotation.
10. Specify annotation details.

Example 390

Summary: Creates a variability chart with nested factors using operator and part configurations, displaying standard deviation charts in Graph Builder.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 568, 398 ),
    Show Control Panel( 0 ),
    Variables( X( :Color ), Y( :Price ) ),
    Elements( Points( X, Y, Legend( 19 ), Summary Statistic( "Mean" ) ) ),
    SendToReport(
        Dispatch( {}, "Graph Builder", FrameBox,
            Add Pin Annotation(
                Seg( Marker Seg( 1 ) ),
                Index( 0 ),
                Index Row( 3 ),
                UniqueID( 581065984 ),
                FoundPt( {111, 174} ),
                Origin( {0.0258964143426295, 4148.53801169591} )
            )
        )
    )
);

Code Explanation:

1. Open data table;
2. Create Graph Builder.
3. Set size 568x398.
4. Hide control panel.
5. Set X variable: Color.
6. Set Y variable: Price.
7. Add points element.
8. Use mean summary statistic.
9. Add pin annotation.
10. Position pin at specific coordinates.

Example 391

Summary: Creates a variability chart with nested factors using Graph Builder, displaying standard deviation charts for weight and height.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 403, 342 ),
    Show Control Panel( 0 ),
    Variables( X( :sex ), X( :age, Position( 1 ) ), Y( :weight ), Y( :height, Position( 1 ), Side( "Right" ) ) ),
    Elements( Points( X( 1 ), X( 2 ), Y( 1 ), Legend( 9 ) ), Points( X( 1 ), X( 2 ), Y( 2 ), Legend( 10 ) ) ),
    SendToReport(
        Dispatch( {}, "Graph Builder", FrameBox,
            {Add Pin Annotation(
                Seg( Marker Seg( 1 ) ),
                Index( 39 ),
                Index Row( 39 ),
                UniqueID( 701925159 ),
                FoundPt( {347, 69} ),
                Origin( {10.8222591362126, 171.940298507463} ),
                Offset( {-201, 35} ),
                Tag Line
            ), Add Pin Annotation(
                Seg( Marker Seg( 2 ) ),
                Index( 39 ),
                Index Row( 39 ),
                UniqueID( 701217975 ),
                FoundPt( {352, 78} ),
                Origin( {11.0215946843854, 70.2332089552239} ),
                Offset( {-183, 140} ),
                Tag Line
            )}
        )
    )
);

Code Explanation:

1. Open data table;
2. Create Graph Builder window.
3. Set graph size.
4. Hide control panel.
5. Define X and Y variables.
6. Add points for weight.
7. Add points for height.
8. Send report to Graph Builder.
9. Add pin annotation for weight.
10. Add pin annotation for height.

Example 392

Summary: Creates a graph builder with nested factors using operator and part configurations, displaying standard deviation charts.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 659, 331 ),
    Show Control Panel( 0 ),
    Variables( X( :height ), Y( :weight ) ),
    Elements( Points( X, Y, Legend( 33 ) ), Smoother( X, Y, Legend( 34 ) ) ),
    SendToReport(
        Dispatch( {}, "Graph Builder", FrameBox,
            Add Pin Annotation(
                Seg( Marker Seg( 1 ) ),
                Index( 11 ),
                Index Row( 11 ),
                UniqueID( 712580683 ),
                FoundPt( {331, 165} ),
                Origin( {65.075, 97.5460122699387} )
            )
        )
    )
);

Code Explanation:

1. Open data table;
2. Create graph builder.
3. Set graph size.
4. Hide control panel.
5. Assign variables to axes.
6. Add points element.
7. Add smoother element.
8. Send report to graph.
9. Add pin annotation.
10. Specify annotation details.

Example 393

Summary: Creates a graph builder with nested factors using operator and part configurations, displaying standard deviation charts.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 534, 464 ),
    Show Control Panel( 0 ),
    Variables( X( :name ), Y( :countries visited ) ),
    Elements( Points( X, Y, Legend( 3 ) ) ),
    SendToReport(
        Dispatch( {}, "Graph Builder", FrameBox,
            Add Pin Annotation(
                Seg( Marker Seg( 1 ) ),
                Index( 38 ),
                Index Row( 38 ),
                UniqueID( 21 ),
                FoundPt( {460, 243} ),
                Origin( {8.03125, 20.0322282666667} ),
                RightOfCenter( 0 ),
                Tag Line( 1 )
            )
        )
    )
);

Code Explanation:

1. Open data table.
2. Launch Graph Builder.
3. Set graph size.
4. Hide control panel.
5. Assign X and Y variables.
6. Add points element.
7. Send report to Graph Builder.
8. Dispatch to Graph Builder frame.
9. Add pin annotation.
10. Specify annotation properties.

Example 394

Summary: Creates a variability chart with nested factors using operator and part configurations, displaying standard deviation charts in Graph Builder.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 434, 342 ),
    Show Control Panel( 0 ),
    Variables( X( :height ), X( :age, Position( 1 ) ), Y( :weight ) ),
    Elements( Points( X( 1 ), X( 2 ), Y, Legend( 5 ) ) ),
    SendToReport(
        Dispatch( {}, "400", ScaleBox, {Legend Model( 5, Base( 0, 0, 0 ), Base( 1, 0, 0 ) )} ),
        Dispatch( {}, "Graph Builder", FrameBox,
            {Add Pin Annotation(
                Seg( Marker Seg( 1 ) ),
                Index( 39 ),
                Index Row( 39 ),
                UniqueID( 482865623 ),
                FoundPt( {493, 75} ),
                Origin( {70.1242236024845, 172.65306122449} ),
                Offset( {-165, 34} ),
                Tag Line
            ), Add Pin Annotation(
                Seg( Marker Seg( 2 ) ),
                Index( 39 ),
                Index Row( 39 ),
                UniqueID( 482850935 ),
                FoundPt( {145, 76} ),
                Origin( {5.27950310559006, 172.34693877551} ),
                Offset( {2, 33} ),
                Tag Line
            )}
        )
    )
);

Code Explanation:

1. Open data table;
2. Create Graph Builder window.
3. Set graph size.
4. Hide control panel.
5. Define X variables: height, age.
6. Define Y variable: weight.
7. Add points element with two X variables.
8. Configure legend for points.
9. Add first pin annotation.
10. Add second pin annotation.

Example 395

Summary: Creates a variability chart with nested factors using operator and part configurations, displaying standard deviation charts in Graph Builder.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 511, 416 ),
    Show Control Panel( 0 ),
    Variables(
        X( :sex ),
        X( :age, Position( 1 ) ),
        Y( :weight, Side( "Right" ) ),
        Y( :height, Position( 1 ) ),
        Y( :weight, Position( 1 ) )
    ),
    Elements(
        Area( X( 2 ), X( 1 ), Y( 2 ), Y( 3 ), Legend( 5 ), Area Style( "Range" ), Summary Statistic( "Sum" ) ),
        Points( X( 1 ), X( 2 ), Y( 2 ), Y( 3 ), Legend( 9 ) )
    ),
    SendToReport(
        Dispatch( {}, "Graph Builder", FrameBox,
            {Add Pin Annotation(
                Seg( Marker Seg( 2 ) ),
                Index( 39 ),
                Index Row( 39 ),
                UniqueID( 686018807 ),
                FoundPt( {452, 322} ),
                Origin( {11.0488721804511, 166.081871345029} ),
                Offset( {-196, -53} ),
                Tag Line
            ), Add Pin Annotation(
                Seg( Marker Seg( 1 ) ),
                Index( 39 ),
                Index Row( 39 ),
                UniqueID( 697750567 ),
                FoundPt( {446, 363} ),
                Origin( {10.8684210526316, 70.1754385964912} ),
                Offset( {47, -20} ),
                Tag Line
            )}
        )
    )
);

Code Explanation:

1. Open data table;
2. Launch Graph Builder.
3. Set window size.
4. Hide control panel.
5. Define X variables.
6. Define Y variables.
7. Create area element.
8. Create points element.
9. Add pin annotation.
10. Add another pin annotation.

Example 396

Summary: Creates a variability chart with nested factors using operator and part configurations, displaying standard deviation charts in Graph Builder.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 528, 456 ),
    Show Control Panel( 0 ),
    Variables( X( :Table ), Y( :Depth ), Overlay( :Cut ) ),
    Elements( Points( X, Y, Legend( 24 ) ), Smoother( X, Y, Legend( 25 ) ) ),
    SendToReport(
        Dispatch( {}, "Graph Builder", FrameBox,
            {Add Pin Annotation(
                Seg( Marker Seg( 3 ) ),
                Index( 888 ),
                Index Row( 1954 ),
                UniqueID( 791165096 ),
                FoundPt( {381, 352} ),
                Origin( {53.9927272727273, 59.0444790816326} ),
                Offset( {8, -40} ),
                Tag Line( 1 )
            ), Add Pin Annotation(
                Seg( Marker Seg( 1 ) ),
                Index( 41 ),
                Index Row( 691 ),
                UniqueID( 790666457 ),
                FoundPt( {641, 428} ),
                Origin( {60.9547107438017, 57.1587096938775} ),
                Offset( {15, -63} ),
                Tag Line( 1 )
            ), Add Pin Annotation(
                Seg( Marker Seg( 2 ) ),
                Index( 957 ),
                Index Row( 2345 ),
                UniqueID( 993272029 ),
                FoundPt( {569, 167} ),
                Origin( {59.0267768595041, 63.6348387755102} ),
                Offset( {-27, 46} ),
                Tag Line( 1 )
            )}
        ),
        Dispatch( {}, "400", LegendBox, {Set Title( "" )} )
    )
);

Code Explanation:

1. Open data table;
2. Create Graph Builder.
3. Set size to 528x456.
4. Hide control panel.
5. Set X to Table.
6. Set Y to Depth.
7. Overlay by Cut.
8. Add points element.
9. Add smoother element.
10. Add pin annotations.

Example 397

Summary: Creates a variability chart with nested factors using Graph Builder, displaying standard deviation charts and pin annotations.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 534, 448 ),
    Show Control Panel( 0 ),
    Variables( X( :sex ), Y( :height ) ),
    Elements( Points( X, Y, Legend( 5 ), Summary Statistic( "% of Total" ) ) ),
    SendToReport(
        Dispatch( {}, "Graph Builder", FrameBox,
            Add Pin Annotation(
                Seg( Marker Seg( 1 ) ),
                Index( 0 ),
                Index Row( 0 ),
                UniqueID( 812227056 ),
                FoundPt( {444, 480} ),
                Origin( {0.00955414012738853, 0.438392857142857} )
            )
        )
    )
);

Code Explanation:

1. Open data table;
2. Launch Graph Builder.
3. Set graph size.
4. Hide control panel.
5. Assign variables.
6. Add points element.
7. Set summary statistic.
8. Send report.
9. Add pin annotation.
10. Configure annotation properties.

Example 398

Summary: Creates a graph builder with nested factors using operator and part configurations, displaying standard deviation charts.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 441, 261 ),
    Show Control Panel( 0 ),
    Variables( X( :sex ), Y( :age ) ),
    Elements( Points( X, Y, Legend( 3 ), Summary Statistic( "Mean" ) ) ),
    SendToReport(
        Dispatch( {}, "Graph Builder", FrameBox,
            Add Pin Annotation(
                Seg( Marker Seg( 1 ) ),
                Index( 1 ),
                Index Row( 5 ),
                UniqueID( 768227313 ),
                FoundPt( {614, 240} ),
                Origin( {1.01122194513716, 2.07560975609756} ),
                Offset( {-206, -36} )
            )
        )
    )
);

Code Explanation:

1. Open data table;
2. Create graph builder.
3. Set window size.
4. Hide control panel.
5. Assign variables.
6. Add points element.
7. Apply summary statistic.
8. Send report.
9. Add pin annotation.
10. Configure annotation properties.

Example 399

Summary: Creates a variability chart with nested factors using operator and part configurations, displaying standard deviation charts in Graph Builder.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 471, 337 ),
    Show Control Panel( 0 ),
    Variables( X( :height ), Size( :name ) ),
    Elements( Points( X, Legend( 21 ) ) ),
    SendToReport(
        Dispatch( {}, "Y title", TextEditBox, {Set Wrap( 2 )} ),
        Dispatch( {}, "Graph Builder", FrameBox,
            Add Pin Annotation(
                Seg( Marker Seg( 1 ) ),
                Index( 13 ),
                Index Row( 13 ),
                UniqueID( 688689421 ),
                FoundPt( {486, 274} ),
                Origin( {58.1353305785124, 0.114609571788413} )
            )
        )
    )
);

Code Explanation:

1. Open data table;
2. Launch Graph Builder.
3. Set window size.
4. Hide control panel.
5. Assign height to X-axis.
6. Assign name to size.
7. Add points element.
8. Adjust Y title wrap.
9. Add pin annotation.
10. Specify annotation details.

Example 400

Summary: Creates a Graph Builder window with nested factors, displaying points and smoother elements to visualize relationships between height (in.) and weight (lb.).

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 770, 420 ),
    Show Control Panel( 0 ),
    Variables( X( :Name( "height (in.)" ) ), Y( :Name( "weight (lb.)" ) ) ),
    Elements( Points( X, Y, Legend( 3 ) ), Smoother( X, Y, Legend( 4 ) ) ),
    SendToReport(
        Dispatch( {}, "Graph Builder", FrameBox,
            Add Pin Annotation(
                Seg( Marker Seg( 1 ) ),
                Index( 26 ),
                Index Row( 26 ),
                UniqueID( 818704282 ),
                FoundPt( {411, 209} ),
                Origin( {60.8901251738526, 127.039106145251} )
            )
        )
    )
);

Code Explanation:

1. Open data table;
2. Create Graph Builder window.
3. Set window size to 770x420.
4. Hide control panel.
5. Define X variable: height (in.).
6. Define Y variable: weight (lb.).
7. Add points element to graph.
8. Add smoother element to graph.
9. Send report to Graph Builder.
10. Add pin annotation to graph.

Example 401

Summary: Creates a variability chart with nested factors using operator and part configurations, displaying standard deviation charts in Graph Builder.

Code:

dt = Open("data_table.jmp");
Graph Builder(
    Size( 481, 326 ),
    Show Control Panel( 0 ),
    Variables( X( :age ), Y( :height ) ),
    Elements( Points( X, Y, Legend( 19 ), Summary Statistic( "% of Total" ) ) ),
    SendToReport(
        Dispatch( {}, "Graph Builder", FrameBox,
            Add Pin Annotation(
                Seg( Marker Seg( 1 ) ),
                Index( 1 ),
                Index Row( 8 ),
                UniqueID( 712654945 ),
                FoundPt( {448, 319} ),
                Origin( {0.972324723247233, 0.168313953488372} )
            )
        ),
        Dispatch( {}, "400", LegendBox, {Legend Position( {19, [0]} )} )
    )
);

Code Explanation:

1. Open data table.
2. Create Graph Builder window.
3. Set graph size.
4. Hide control panel.
5. Assign X and Y variables.
6. Add points element.
7. Set summary statistic.
8. Send report to Graph Builder.
9. Add pin annotation.
10. Adjust legend position.

Example 402

Summary: Creates a variability chart with nested factors using operator and part configurations, displaying standard deviation charts in Graph Builder.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 495, 448 ),
    Show Control Panel( 0 ),
    Variables( X( :Age Group ), Color( :Salary ) ),
    Elements( Points( X, Legend( 1 ) ) ),
    SendToReport(
        Dispatch( {}, "Graph Builder", FrameBox,
            Add Pin Annotation(
                Seg( Marker Seg( 1 ) ),
                Index( 135 ),
                Index Row( 135 ),
                UniqueID( 768615319 ),
                FoundPt( {123, 298} ),
                Origin( {0.946280991735537, -0.125} )
            )
        )
    )
);

Code Explanation:

1. Open data table;
2. Launch Graph Builder.
3. Set graph size.
4. Hide control panel.
5. Assign X and Color variables.
6. Add points element.
7. Send report to Graph Builder.
8. Dispatch to Graph Builder frame.
9. Add pin annotation.
10. Specify annotation details.

Example 403

Summary: Creates a variability chart with nested factors using Graph Builder, displaying standard deviation charts and pin annotations.

Code:

dt = Open("data_table.jmp");
r = dt << select where( :sex == "F" );
r << exclude;
Graph Builder(
    Size( 659, 374 ),
    Show Control Panel( 0 ),
    Variables( X( :sex ), Y( :height ) ),
    Elements( Points( X, Y, Legend( 7 ), Summary Statistic( "Mean" ) ) ),
    SendToReport(
        Dispatch( {}, "Graph Builder", FrameBox,
            Add Pin Annotation(
                Seg( Marker Seg( 1 ) ),
                Index( 0 ),
                Index Row( 5 ),
                UniqueID( 1014750944 ),
                FoundPt( {559, 325} ),
                Origin( {-0.00427350427350426, 63.9091243654822} )
            )
        )
    )
);

Code Explanation:

1. Open data table;
2. Select rows where sex is "F".
3. Exclude selected rows.
4. Launch Graph Builder.
5. Set graph size to 659x374.
6. Hide control panel.
7. Assign sex to X-axis, height to Y-axis.
8. Add points element with mean summary statistic.
9. Send report to Graph Builder.
10. Add pin annotation at specified coordinates.

Example 404

Summary: Creates a variability chart with nested factors using operator and part configurations, displaying standard deviation charts in Graph Builder.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 534, 464 ),
    Show Control Panel( 0 ),
    Variables( X( :Territory ), Y( :Name( "Population (1000)" ) ) ),
    Elements( Points( X, Y, Legend( 3 ) ) ),
    SendToReport(
        Dispatch( {}, "Graph Builder", FrameBox,
            Add Pin Annotation(
                Seg( Marker Seg( 1 ) ),
                Index( 47 ),
                Index Row( 47 ),
                UniqueID( 798659471 ),
                FoundPt( {532, 309} ),
                Origin( {44.5209302325581, 1235537.19008264} )
            )
        )
    )
);

Code Explanation:

1. Open data table.
2. Create Graph Builder window.
3. Set graph size.
4. Hide control panel.
5. Assign X and Y variables.
6. Add points element.
7. Send report to Graph Builder.
8. Dispatch to frame box.
9. Add pin annotation.
10. Configure annotation properties.

Example 405

Summary: Creates two Graph Builder windows to visualize the relationship between height and age, with each window displaying a different summary statistic (max and mean) and formatted scales.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 501, 233 ),
    Show Control Panel( 0 ),
    Lock Scales( 1 ),
    Variables( X( :height ), Y( :age ) ),
    Elements( Points( X, Y, Legend( 3 ), Summary Statistic( "Max" ) ) ),
    SendToReport(
        Dispatch( {}, "height", ScaleBox, {Format( "Fixed Dec", 12, 0 ), Min( 64 ), Max( 70.3 ), Inc( 1 ), Minor Ticks( 0 )} ),
        Dispatch( {}, "age", ScaleBox, {Format( "Fixed Dec", 12, 0 ), Min( -0.5 ), Max( 5.5 ), Inc( 1 ), Minor Ticks( 0 )} ),
        Dispatch( {}, "Graph Builder", FrameBox,
            Add Pin Annotation(
                Seg( Marker Seg( 1 ) ),
                Index( 1 ),
                Index Row( 8 ),
                UniqueID( 766039329 ),
                FoundPt( {126, 177} ),
                Origin( {64.9997826086957, 1.09763313609467} ),
                Tag Line( 1 )
            )
        )
    )
);
Graph Builder(
    Size( 501, 232 ),
    Show Control Panel( 0 ),
    Lock Scales( 1 ),
    Variables( X( :height ), Y( :age ) ),
    Elements( Points( X, Y, Legend( 3 ), Summary Statistic( "Mean" ) ) ),
    SendToReport(
        Dispatch( {}, "height", ScaleBox, {Format( "Fixed Dec", 12, 0 ), Min( 56 ), Max( 67.1791666666667 ), Inc( 2 ), Minor Ticks( 0 )} ),
        Dispatch( {}, "age", ScaleBox, {Format( "Fixed Dec", 12, 0 ), Min( -0.5 ), Max( 5.5 ), Inc( 1 ), Minor Ticks( 0 )} ),
        Dispatch( {}, "Graph Builder", FrameBox,
            Add Pin Annotation(
                Seg( Marker Seg( 1 ) ),
                Index( 1 ),
                Index Row( 8 ),
                UniqueID( 766057329 ),
                FoundPt( {231, 177} ),
                Origin( {60.3258514492754, 1.07142857142857} ),
                Tag Line( 1 )
            )
        )
    )
);

Code Explanation:

1. Open data table.
2. Create first Graph Builder window.
3. Set graph size.
4. Hide control panel.
5. Lock scales.
6. Set X and Y variables.
7. Add points element with max summary statistic.
8. Format X axis scale.
9. Format Y axis scale.
10. Add pin annotation to graph.
11. Create second Graph Builder window.
12. Set graph size.
13. Hide control panel.
14. Lock scales.
15. Set X and Y variables.
16. Add points element with mean summary statistic.
17. Format X axis scale.
18. Format Y axis scale.
19. Add pin annotation to graph.

Example 406

Summary: Creates a variability chart with nested factors using operator and part configurations, displaying standard deviation charts in Graph Builder.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 474, 292 ),
    Show Control Panel( 0 ),
    Variables( X( :height ), Y( :weight ), Color( :weight, Summary Statistic( "Range" ) ) ),
    Elements( Box Plot( X, Y, Legend( 8 ) ) ),
    SendToReport(
        Dispatch( {}, "Graph Builder", FrameBox,
            Add Pin Annotation(
                Seg( Box Plot Seg( 12 ) ),
                Index( {1, 1} ),
                Index Row( {1, 1} ),
                UniqueID( 826593057 ),
                FoundPt( {636, 183} ),
                Origin( {65.035303680175, 141.691981686427} ),
                Tag Line( 1 )
            )
        )
    )
);

Code Explanation:

1. Open data table;
2. Create Graph Builder window.
3. Set window size.
4. Hide control panel.
5. Define X, Y, and Color variables.
6. Add box plot element.
7. Send report to Graph Builder.
8. Add pin annotation to graph.
9. Specify segment for annotation.
10. Position annotation on graph.

Example 407

Summary: Creates a variability chart with nested factors using operator and part configurations, displaying standard deviation charts in Graph Builder.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 604, 504 ),
    Show Control Panel( 0 ),
    Variables( X( :height ), Y( :weight ), Overlay( :sex ) ),
    Elements( Smoother( X, Y, Legend( 2 ) ) ),
    SendToReport(
        Dispatch( {}, "Graph Builder", FrameBox,
            Add Pin Annotation(
                Seg( Line Seg( 1 ) ),
                Index( 0 ),
                Index Row( 0 ),
                UniqueID( 498317064 ),
                FoundPt( {270, 365} ),
                Origin( {58.4222423146474, 95.2941176470588} )
            )
        )
    )
);

Code Explanation:

1. Open data table;
2. Create Graph Builder window.
3. Set window size.
4. Hide control panel.
5. Define variables: X=height, Y=weight, Overlay=sex.
6. Add smoother element.
7. Send report to Graph Builder.
8. Dispatch to Graph Builder frame box.
9. Add pin annotation.
10. Set annotation properties.

Example 408

Summary: Configures a geographic map to display the relationship between Longitude and Latitude, utilizing Graph Builder's SendToReport feature for customized scale settings and textlet formatting.

Code:

Open("data_table.jmp");
gb = Graph Builder(
    Size( 1101, 603 ),
    Show Control Panel( 0 ),
    Variables( X( :Longitude ), Y( :Latitude ) ),
    Elements( Points( X, Y, Legend( 8 ) ) ),
    SendToReport(
        Dispatch( {}, "Longitude", ScaleBox,
            {Min( -233.721641318648 ), Max( 84.852890687034 ), Inc( 50 ), Minor Ticks( 0 ), Label Row(
                {Automatic Font Size( 1 ), Automatic Tick Marks( 1 ), Label Orientation( "Automatic" )}
            )}
        ),
        Dispatch( {}, "Latitude", ScaleBox,
            {Min( -77.0208810647403 ), Max( 90.6662993562194 ), Inc( 20 ), Minor Ticks( 0 ), Label Row(
                {Automatic Font Size( 1 ), Automatic Tick Marks( 1 ), Label Orientation( "Automatic" )}
            )}
        ),
        Dispatch( {}, "Graph Builder", FrameBox,
            {Background Map( Images( "Simple Earth" ), Boundaries( "World" ) ), Set Textlet(
                Setup(
                    NS = "blue";
                    EW = "red";
                    LT = Format( local:_Latitude, "Latitude DDD" );
                    LG = Format( local:_Longitude, "Longitude DDD" );
                ),
                Markup( "<font color=\!"{NS}\!">{LT}</font> - <font color=\!"{EW}\!">{LG}</font>" )
            ), Grid Line Order( 3 ), Reference Line Order( 4 ), Add Pin Annotation(
                Seg( Marker Seg( 1 ) ),
                Index( 21 ),
                Index Row( 21 ),
                UniqueID( 937082997 ),
                FoundPt( {588, 230} ),
                Origin( {-78.7392453583483, 35.600193726331} ),
                Tag Line( 1 )
            )}
        )
    )
);

Code Explanation:

1. Open data table;
2. Create Graph Builder object.
3. Set graph size.
4. Hide control panel.
5. Define X and Y variables.
6. Add points element.
7. Configure Longitude scale.
8. Configure Latitude scale.
9. Set background map.
10. Add textlet with formatted coordinates.

Example 409

Summary: Creates a report with dynamic text content, using Graph Builder to visualize data and set up variables for display.

Code:

dt = Open("data_table.jmp");
gb = dt << Graph Builder(
    Size( 534, 456 ),
    Show Control Panel( 0 ),
    Variables( X( :Age ), Y( :LDL ), Overlay( :Y Ordinal ) ),
    Elements( Points( X, Y, Legend( 8 ) ), Line Of Fit( X, Y, Legend( 10 ) ) )
);
rpt = gb << Report;
frame = rpt[Framebox( 1 )];
frame << Set Textlet(
    Setup(
        local:gender = If( Column( local:_dataTable, "Gender" )[local:_firstRow] == "1",
            "Male",
            "Female"
        );
        local:color = Match( local:_Y Ordinal, "Low", "Medium Dark Blue", "Medium", "Medium Dark Red", "High", "Medium Dark Green" );
        local:progression = Column( local:_dataTable, "Y" )[local:_firstRow];
        local:BMI = Column( local:_dataTable, "BMI" )[local:_firstRow];
    ),
    Markup(
        "{local:gender} patient, {local:_age} years old, {local:BMI} BMI,
has <font color='{local:color}'><b>{local:_Y Ordinal}</b></font>
disease progression (<i>{local:progression}</i>)"
    )
);

Code Explanation:

1. Open data table;
2. Create Graph Builder object.
3. Set graph size.
4. Hide control panel.
5. Define variables for graph.
6. Add points and line of fit elements.
7. Generate report from graph.
8. Access first framebox in report.
9. Set textlet with dynamic content.
10. Define setup for textlet variables.

Example 410

Summary: Creates a report with dynamic text and pin annotation using Graph Builder, Variables, Elements, and Report in JMP.

Code:

Names Default To Here( 1 );
dt = Open("data_table.jmp");
gb = dt << Graph Builder(
    Size( 534, 456 ),
    Show Control Panel( 0 ),
    Variables( X( :Age ), Y( :LDL ), Overlay( :Y Ordinal ) ),
    Elements( Points( X, Y, Legend( 8 ) ), Line Of Fit( X, Y, Legend( 10 ) ) )
);
rpt = gb << Report;
frame = rpt[Framebox( 1 )];
frame << Set Textlet(
    Setup(
        local:gender = If( Column( local:_dataTable, "Gender" )[local:_firstRow] == "1",
            "Male",
            "Female"
        );
        local:color = Match( local:_Y Ordinal, "Low", "Medium Dark Blue", "Medium", "Medium Dark Red", "High", "Medium Dark Green" );
        local:progression = Column( local:_dataTable, "Y" )[local:_firstRow];
        local:BMI = Column( local:_dataTable, "BMI" )[local:_firstRow];
    ),
    Markup(
        "{local:gender} patient, {local:_age} years old, {local:BMI} BMI,
has <font color='{local:color}'><b>{local:_Y Ordinal}</b></font>
disease progression (<i>{local:progression}</i>)"
    )
);
frame << Add Pin Annotation(
    Seg( Marker Seg( 2 ) ),
    Index( 64 ),
    Index Row( 344 ),
    UniqueID( 568154464 ),
    FoundPt( {96, 222} ),
    Origin( {18.68125, 156.93706122449} ),
    Tag Line( 1 )
);

Code Explanation:

1. Open data table;
2. Create Graph Builder object.
3. Set graph size.
4. Hide control panel.
5. Assign variables for X, Y, and overlay.
6. Add points and line of fit elements.
7. Generate report from graph builder.
8. Access first frame box.
9. Set textlet with dynamic content.
10. Add pin annotation at specified location.

Example 411

Summary: Creates a variability chart with nested factors using operator and part configurations, displaying standard deviation charts in Graph Builder.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 531, 451 ),
    Show Control Panel( 0 ),
    Variables( X( :Species ), Y( :Sepal width ) ),
    Elements( Bar( X, Y, Legend( 4 ) ) ),
    SendToReport(
        Dispatch( {}, "Graph Builder", FrameBox,
            {DispatchSeg(
                BarSeg( 1 ),
                {Set Graphlet(
                    Picture(
                        Graph Builder(
                            Size( 400, 200 ),
                            Show Control Panel( 0 ),
                            Show Legend( 0 ),
                            Variables( Y( :Sepal width ) ),
                            Elements( Histogram( Y ) )
                        )
                    ),
                    Title( "Bar > Hist > GB Graphlet" )
                )}
            ), Add Pin Annotation(
                Seg( BarSeg( 1 ) ),
                Index( {0, 0} ),
                Index Row( {0, 0} ),
                UniqueID( 753682192 ),
                FoundPt( {127, 258} ),
                Origin( {-0.0945945945945946, 1.68217054263566} ),
                Tag Line( 1 )
            )}
        ),
        Dispatch( {}, "400", LegendBox, {font( "Segoe UI", 9, "Plain" )} )
    )
);

Code Explanation:

1. Open data table;
2. Create Graph Builder window.
3. Set graph size.
4. Hide control panel.
5. Define X and Y variables.
6. Add bar element.
7. Send report commands.
8. Dispatch to Graph Builder frame.
9. Set graphlet picture.
10. Add pin annotation.

Example 412

Summary: Creates a variability chart with nested factors using operator and part configurations, displaying standard deviation charts in JMP.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 550, 482 ),
    Show Control Panel( 0 ),
    Variables( X( :Data Set ), Y( :X ), Y( :Y, Position( 1 ) ) ),
    Elements( Bar( X, Y( 1 ), Y( 2 ), Legend( 12 ), Error Interval( "Standard Deviation" ) ) ),
    SendToReport(
        Dispatch( {}, "Graph Builder", FrameBox,
            {DispatchSeg(
                BarSeg( 1 ),
                {Set Graphlet(
                    Picture(
                        Graph Builder(
                            Size( 256, 256 ),
                            Show Control Panel( 0 ),
                            Show Legend( 0 ),
                            Variables( X( :X ), Y( :Y ) ),
                            Elements( Points( X, Y, Legend( 1 ) ), Line Of Fit( X, Y, Legend( 3 ) ) )
                        )
                    ),
                    Title( "Bar to Points Line of Fit Graphlet" )
                )}
            ), Add Pin Annotation(
                Seg( BarSeg( 1 ) ),
                Index( {0, 1} ),
                Index Row( {649, 0} ),
                UniqueID( 764997808 ),
                FoundPt( {82, 287} ),
                Origin( {0.120331950207469, 28.314606741573} ),
                Offset( {102, -47} ),
                Tag Line( 1 )
            )}
        ),
        Dispatch( {}, "400", LegendBox, {font( "Segoe UI", 9, "Plain" )} )
    )
);

Code Explanation:

1. Open data table;
2. Launch Graph Builder.
3. Set graph size.
4. Hide control panel.
5. Define X and Y variables.
6. Add bar element with error intervals.
7. Create nested Graph Builder for graphlet.
8. Set nested graph size.
9. Hide control panel and legend.
10. Add points and line of fit elements.
11. Assign graphlet to bar segment.
12. Add pin annotation to bar segment.
13. Set legend font properties.

Example 413

Summary: Creates a variability chart with nested factors using operator and part configurations, displaying standard deviation charts in Graph Builder.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 536, 446 ),
    Show Control Panel( 0 ),
    Variables( Y( :Sepal width ) ),
    Elements( Histogram( Y, Legend( 1 ) ) ),
    SendToReport(
        Dispatch( {}, "Graph Builder", FrameBox,
            {DispatchSeg(
                Hist Seg( 1 ),
                {Set Graphlet(
                    Picture(
                        Graph Builder(
                            Size( 250, 150 ),
                            Show Control Panel( 0 ),
                            Show Legend( 0 ),
                            Variables( Y( :Sepal width ) ),
                            Elements( Histogram( Y ) )
                        )
                    )
                )}
            ), Add Pin Annotation(
                Seg( Hist Seg( 1 ) ),
                Index( {72, 84} ),
                Index Row( {72, 84} ),
                UniqueID( 652860744 ),
                FoundPt( {156, 199} ),
                Origin( {-0.306584362139918, 3.64868105515588} ),
                Offset( {93, -35} ),
                Tag Line( 1 )
            )}
        )
    )
);

Code Explanation:

1. Open data table;
2. Create Graph Builder window.
3. Set graph size.
4. Hide control panel.
5. Set Y variable.
6. Add histogram element.
7. Send report to Graph Builder.
8. Dispatch graph builder settings.
9. Set graphlet picture.
10. Add pin annotation.

Example 414

Summary: Creates a hexagonal heatmap to visualize geographic data, utilizing Graph Builder and displaying background map with US states boundaries.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 534, 456 ),
    Show Control Panel( 0 ),
    Variables( X( :Longitude ), Y( :Latitude ) ),
    Elements( Heatmap( X, Y, Legend( 5 ), Bin Shape( "Hexagonal" ), Hex Bin Radius( 10.15 ) ) ),
    SendToReport(
        Dispatch( {}, "Graph Builder", FrameBox,
            {Background Map( Boundaries( "US States" ) ), Set Graphlet(
                Picture(
                    Try(
                        loader = If( Class Exists( "hllLoader" ),
                            New Object( "hllLoader" ),
                            Include( "$BUILTIN_SCRIPTS/hllib.jsl" )
                        );
                        loader:setDebug( 0 );
                        hlp = loader:lazyLoad( "hllPresets" );
                        hlp:launchMarker();
                    ,
                        Write(
                            "Hover Label: Unable to launch Preset, please check that
the Preset library is available at $BUILTIN_SCRIPTS/hllib.jsl"
                        );
                        Write( Eval Insert( "Exception: ^exception_msg^" ) );
                        Empty();
                    )
                ),
                Title( "Marker Preset" ),
                Reapply( 1 )
            ), Grid Line Order( 2 ), Reference Line Order( 4 ), Add Pin Annotation(
                Seg( HexSeg( 1 ) ),
                Index( 9 ),
                Index Row( 6 ),
                UniqueID( 2056825817 ),
                FoundPt( {712, 291} ),
                Origin( {-73.2070726510337, 40.2847186047671} ),
                Offset( {-289, 86} ),
                RightOfCenter( 1 ),
                Tag Line( 1 )
            )}
        )
    )
);

Code Explanation:

1. Open data table;
2. Launch Graph Builder.
3. Set graph size to 534x456.
4. Hide control panel.
5. Assign Longitude to X-axis.
6. Assign Latitude to Y-axis.
7. Create hexagonal heatmap element.
8. Set legend position to 5.
9. Set hex bin radius to 10.15.
10. Display background map with US states boundaries.

Example 415

Summary: Creates a mosaic plot with nested factors using Graph Builder, displaying standard deviation charts and adjusting label orientation.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 496, 366 ),
    Show Control Panel( 0 ),
    Variables( X( :age ), Y( :sex ) ),
    Elements( Mosaic( X, Y, Legend( 4 ) ) ),
    SendToReport(
        Dispatch( {}, "age", ScaleBox, {Label Row( Label Orientation( "Angled" ) )} ),
        Dispatch( {}, "Graph Builder", FrameBox,
            Add Pin Annotation(
                Seg( MosaicSeg( 1 ) ),
                Index( {0, 1} ),
                Index Row( {0, 1} ),
                UniqueID( 686493537 ),
                FoundPt( {106, 129} ),
                Origin( {0.0945945945945946, 0.746753246753247} )
            )
        )
    )
);

Code Explanation:

1. Open data table;
2. Create Graph Builder window.
3. Set graph size.
4. Hide control panel.
5. Assign age to X-axis.
6. Assign sex to Y-axis.
7. Add mosaic plot element.
8. Adjust age label orientation.
9. Add pin annotation to mosaic.
10. Position annotation on graph.

Example 416

Summary: Creates a graph builder window with nested factors, displaying standard deviation charts and annotating frames with pin annotations.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 401, 279 ),
    Show Control Panel( 0 ),
    Variables( X( :age ), Y( :height ), Y( :height ), Color( :age ) ),
    Elements( Position( 1, 1 ), Bar( X, Y, Legend( 10 ) ) ),
    Elements( Position( 1, 2 ), Points( X, Y, Legend( 6 ) ) ),
    SendToReport(
        Dispatch( {}, "Graph Builder", FrameBox,
            Add Pin Annotation(
                Seg( BarSeg( 1 ) ),
                Index( {0, 0} ),
                Index Row( {0, 0} ),
                UniqueID( 765516064 ),
                FoundPt( {100, 93} ),
                Origin( {0.09846547314578, 48.0597014925373} )
            )
        ),
        Dispatch( {}, "Graph Builder", FrameBox( 2 ),
            Add Pin Annotation(
                Seg( Marker Seg( 1 ) ),
                Index( 3 ),
                Index Row( 3 ),
                UniqueID( 749710563 ),
                FoundPt( {97, 227} ),
                Origin( {0.0524296675191815, 65.5639097744361} )
            )
        )
    )
);

Code Explanation:

1. Open data table.
2. Create graph builder window.
3. Set window size.
4. Hide control panel.
5. Define variables: X(age), Y(height).
6. Add bar element to first position.
7. Add points element to second position.
8. Annotate first frame with pin.
9. Annotate second frame with pin.
10. Configure annotations' positions and properties.

Example 417

Summary: Creates a variability chart with nested factors using operator and part configurations, displaying standard deviation charts in JMP's Graph Builder.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 392, 309 ),
    Show Control Panel( 0 ),
    Variables( X( :Region ), X( :State, Position( 1 ) ), Color( :POP ), Size( :POP ) ),
    Elements( Points( X( 1 ), X( 2 ), Legend( 7 ) ) ),
    SendToReport(
        Dispatch( {}, "Y title", TextEditBox, {Set Wrap( 2 )} ),
        Dispatch( {}, "Graph Builder", FrameBox,
            Add Pin Annotation(
                Seg( Marker Seg( 1 ) ),
                Index( 35 ),
                Index Row( 35 ),
                UniqueID( 749710595 ),
                FoundPt( {201, 225} ),
                Origin( {16.162100456621, -0.0918367346938775} )
            )
        )
    )
);

Code Explanation:

1. Open data table.
2. Create Graph Builder window.
3. Set graph size.
4. Hide control panel.
5. Define X and Y variables.
6. Set color and size based on population.
7. Add points element.
8. Modify Y axis title properties.
9. Add pin annotation to graph.
10. Specify annotation details.

Example 418

Summary: Creates a variability chart with nested factors using operator and part configurations, displaying standard deviation charts in JMP.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 546, 379 ),
    Show Control Panel( 0 ),
    Variables( X( :city ), Color( :OZONE ) ),
    Elements( Bar( X, Legend( 1 ) ) ),
    SendToReport(
        Dispatch( {}, "Graph Builder", FrameBox,
            Add Pin Annotation(
                Seg( BarSeg( 1 ) ),
                Index( {25, 25} ),
                Index Row( {25, 25} ),
                UniqueID( 817819193 ),
                FoundPt( {299, 243} ),
                Origin( {25.2107438016529, 1} ),
                Offset( {-97, -43} ),
                Tag Line
            )
        )
    )
);

Code Explanation:

1. Open data table.
2. Create Graph Builder window.
3. Set window size.
4. Hide control panel.
5. Assign variables to axes.
6. Add bar element.
7. Send report message.
8. Dispatch to Graph Builder.
9. Add pin annotation.
10. Configure annotation properties.

Example 419

Summary: Creates a graph builder window with nested factors, displaying standard deviation charts and pin annotations.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 570, 365 ),
    Show Control Panel( 0 ),
    Variables( X( :Hwy MPG ), Y( :City MPG ), Overlay( :Engine ) ),
    Elements( Points( X, Y, Legend( 3 ) ), Line Of Fit( X, Y, Legend( 5 ) ) ),
    SendToReport(
        Dispatch( {}, "Graph Builder", OutlineBox, {Set Title( "Graph Builder: tooltip for multiple points at the same location" )} ),
        Dispatch( {}, "Graph Builder", FrameBox,
            Add Pin Annotation(
                Seg( Marker Seg( 2 ) ),
                Index( 10 ),
                Index Row( 22 ),
                UniqueID( 604570314 ),
                FoundPt( {316, 233} ),
                Origin( {31.1157024793388, 34.3367346938775} )
            )
        )
    )
);

Code Explanation:

1. Open data table;
2. Create graph builder window.
3. Set window size.
4. Hide control panel.
5. Assign variables to axes.
6. Add point elements.
7. Add line of fit element.
8. Set graph title.
9. Add pin annotation.
10. Specify annotation details.

Example 420

Summary: Creates a graph builder window with a bar element to visualize height vs. weight data, and adds a pin annotation to display the mean weight value.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 551, 367 ),
    Show Control Panel( 0 ),
    Variables( X( :height ), Y( :weight ) ),
    Elements( Bar( X, Y, Legend( 6 ) ) ),
    SendToReport(
        Dispatch( {}, "Graph Builder", OutlineBox, {Set Title( "Graph Builder: tooltip shows Mean(weight) value" )} ),
        Dispatch( {}, "Graph Builder", FrameBox,
            Add Pin Annotation(
                Seg( BarSeg( 1 ) ),
                Index( {5, 5} ),
                Index Row( {0, 0} ),
                UniqueID( 652555237 ),
                FoundPt( {264, 229} ),
                Origin( {59.045, 83.495145631068} ),
                Offset( {-53, -111} ),
                Tag Line
            )
        )
    )
);

Code Explanation:

1. Open data_table data
2. Create Graph Builder window.
3. Set graph size to 551x367.
4. Hide control panel.
5. Assign height to X-axis.
6. Assign weight to Y-axis.
7. Add bar element to graph.
8. Set title of graph.
9. Add pin annotation to graph.
10. Position annotation on first bar segment.

Example 421

Summary: Creates a nested variability chart with age, height, and sex as factors, using Graph Builder to visualize the data.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 500, 371 ),
    Show Control Panel( 0 ),
    Variables( X( :age ), Y( :height ), Group Y( :sex ), Color( :weight ) ),
    Elements( Heatmap( X, Y, Legend( 2 ) ) ),
    SendToReport(
        Dispatch( {}, "Graph Builder", FrameBox,
            Add Pin Annotation(
                Seg( RectSeg( 1 ) ),
                Index( 13 ),
                Index Row( 34 ),
                UniqueID( 757247357 ),
                FoundPt( {370, 93} ),
                Origin( {3.98571428571429, 66.7307692307692} ),
                Tag Line( 1 )
            )
        )
    )
);

Code Explanation:

1. Open data table;
2. Create Graph Builder window.
3. Set graph size to 500x371.
4. Hide control panel.
5. Assign variables: X=age, Y=height, Group Y=sex, Color=weight.
6. Add Heatmap element.
7. Send report to Graph Builder.
8. Add pin annotation to graph.
9. Set annotation segment to rectangle.
10. Position annotation at specific index and row.

Example 422

Summary: Creates a heatmap in Graph Builder to visualize relationships between age, height, sex, and weight, with interactive features for customization.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 500, 371 ),
    Show Control Panel( 0 ),
    Variables( X( :age ), Y( :height ), Group Y( :sex ), Color( :weight ) ),
    Elements( Heatmap( X, Y, Legend( 2 ) ) ),
    SendToReport(
        Dispatch( {}, "Graph Builder", FrameBox,
            Add Pin Annotation(
                Seg( RectSeg( 1 ) ),
                Index( 42 ),
                Index Row( 34 ),
                UniqueID( 492538026 ),
                FoundPt( {361, 98} ),
                Origin( {3.85714285714286, 66.0509554140127} )
            )
        )
    )
);

Code Explanation:

1. Open data table;
2. Create graph builder window.
3. Set size to 500x371.
4. Hide control panel.
5. Assign variables: age, height, sex, weight.
6. Add heatmap element.
7. Configure legend for color.
8. Send report to graph builder.
9. Add pin annotation to frame.
10. Position annotation at specific coordinates.

Example 423

Summary: Creates a variability chart with nested factors using Graph Builder, displaying standard deviation charts and legends.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 412, 369 ),
    Show Control Panel( 0 ),
    Variables( X( :weight ), Y( :height ) ),
    Elements( Points( X, Y, Legend( 9 ) ), Smoother( X, Y, Legend( 10 ) ) )
);

Code Explanation:

1. Open data table;
2. Launch Graph Builder.
3. Set graph size.
4. Hide control panel.
5. Assign X variable.
6. Assign Y variable.
7. Add points element.
8. Add smoother element.
9. Display legend for points.
10. Display legend for smoother.

Example 424

Summary: Creates a variability chart with nested factors using operator and part configurations, displaying standard deviation charts in JMP.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 522, 486 ),
    Show Control Panel( 0 ),
    Variables( X( :age ), Group X( :sex ) ),
    Elements( Bar( X, Legend( 4 ) ) ),
    SendToReport(
        Dispatch( {}, "Graph Builder", FrameBox,
            {Set Graphlet(
                Picture(
                    Graph Builder(
                        Size( 528, 418 ),
                        Show Control Panel( 0 ),
                        Variables( Y( :height ) ),
                        Elements( Points( Y, Legend( 2 ) ) ),
                        SendToReport(
                            Dispatch( {}, "400", ScaleBox,
                                {Legend Model( 2, Properties( 0, {Marker Size( 15 )}, Item ID( "height", 1 ) ) )}
                            )
                        )
                    )
                )
            ), Add Pin Annotation(
                Seg( BarSeg( 1 ) ),
                Index( {0, 0} ),
                Index Row( {0, 0} ),
                UniqueID( 651634736 ),
                FoundPt( {65, 245} ),
                Origin( {-0.128099173553719, 4.543} ),
                Tag Line( 1 )
            )}
        ),
        Dispatch( {}, "Graph Builder", FrameBox( 2 ),
            {Set Graphlet(
                Picture(
                    Graph Builder(
                        Size( 528, 418 ),
                        Show Control Panel( 0 ),
                        Variables( Y( :height ) ),
                        Elements( Points( Y, Legend( 2 ) ) ),
                        SendToReport(
                            Dispatch( {}, "400", ScaleBox,
                                {Legend Model( 2, Properties( 0, {Marker Size( 15 )}, Item ID( "height", 1 ) ) )}
                            )
                        )
                    )
                )
            )}
        )
    )
);

Code Explanation:

1. Open data table;
2. Create graph builder window.
3. Set graph size.
4. Hide control panel.
5. Define X and group X variables.
6. Add bar element.
7. Set graphlet picture.
8. Create nested graph builder.
9. Set nested graph size.
10. Hide nested control panel.

Example 425

Summary: Creates a variability chart with nested factors using operator and part configurations, displaying standard deviation charts in Graph Builder.

Code:

dt = Open("data_table.jmp");
dt << Graph Builder(
    Size( 614, 595 ),
    Show Control Panel( 0 ),
    Variables( X( :Type ), Group X( :Country ), Group Y( :Gas Tank Size ), Color( :Weight ) ),
    Elements( Bar( X, Legend( 5 ) ) ),
    SendToReport(
        Dispatch( {}, "Graph Builder", FrameBox( 4 ),
            {Set Graphlet(
                Picture(
                    Try(
                        loader = If( Class Exists( "hllLoader" ),
                            New Object( "hllLoader" ),
                            Include( "$BUILTIN_SCRIPTS/hllib.jsl" )
                        );
                        loader:setDebug( 0 );
                        hlp = loader:lazyLoad( "hllPresets" );
                        hlp:launchTabulate();
                    )
                ),
                Title( "Tabulate Preset" ),
                Reapply( 1 )
            ), Add Pin Annotation(
                Seg( BarSeg( 1 ) ),
                Index( {3, 3} ),
                Index Row( {1, 1} ),
                UniqueID( -1452682317 ),
                FoundPt( {180, 438} ),
                Origin( {3.00282485875706, 3.2639088172043} ),
                RightOfCenter( 0 ),
                Tag Line( 1 )
            )}
        )
    )
);
dt << Graph Builder(
    Size( 570, 492 ),
    Show Control Panel( 0 ),
    Variables( X( :Displacement ), Y( :Horsepower ), Group X( :Country ), Group Y( :Type ), Color( :Type ) ),
    Elements( Line( X, Y, Legend( 8 ) ) ),
    SendToReport(
        Dispatch( {}, "Graph Builder", FrameBox( 2 ),
            {Set Graphlet(
                Picture(
                    Try(
                        loader = If( Class Exists( "hllLoader" ),
                            New Object( "hllLoader" ),
                            Include( "$BUILTIN_SCRIPTS/hllib.jsl" )
                        );
                        loader:setDebug( 0 );
                        hlp = loader:lazyLoad( "hllPresets" );
                        hlp:launchTabulate();
                    )
                ),
                Title( "Tabulate Preset" ),
                Reapply( 1 ),
                Thumbnail( {300, 300} )
            ), Add Pin Annotation(
                Seg( Line Seg( 1 ) ),
                Index( {4, 4} ),
                Index Row( {100, 100} ),
                UniqueID( -1508343640 ),
                FoundPt( {356, 255} ),
                Origin( {106.098782196045, 93.5064935064935} ),
                RightOfCenter( 0 ),
                Tag Line( 1 )
            )}
        )
    )
);

Code Explanation:

1. Open data table;
2. Create first Graph Builder window.
3. Set size to 614x595 pixels.
4. Hide control panel.
5. Define variables: X(Type), Group X(Country), Group Y(Gas Tank Size), Color(Weight).
6. Add bar element to graph.
7. Set graphlet with picture.
8. Load hllPresets script.
9. Launch tabulate preset.
10. Add pin annotation to graph.

Example 426

Summary: Creates a heatmap in Graph Builder to visualize the relationship between petal width and length, with interactive pin annotations for further analysis.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 522, 456 ),
    Show Control Panel( 0 ),
    Variables( X( :Petal width ), Y( :Petal length ) ),
    Elements( Heatmap( X, Y, Legend( 7 ) ) ),
    SendToReport(
        Dispatch( {}, "Graph Builder", FrameBox,
            {Add Pin Annotation(
                Seg( RectSeg( 1 ) ),
                Index( 0 ),
                Index Row( 0 ),
                UniqueID( 1797828416 ),
                FoundPt( {385, 462} ),
                Origin( {0.365702479338843, 1.81122448979592} ),
                RightOfCenter( 0 ),
                Tag Line( 1 )
            ), Add Pin Annotation(
                Seg( RectSeg( 1 ) ),
                Index( 2 ),
                Index Row( 57 ),
                UniqueID( 1797828418 ),
                FoundPt( {517, 358} ),
                Origin( {1.18388429752066, 3.4030612244898} ),
                RightOfCenter( 0 ),
                Tag Line( 1 )
            ), Add Pin Annotation(
                Seg( RectSeg( 1 ) ),
                Index( 3 ),
                Index Row( 50 ),
                UniqueID( 1797828419 ),
                FoundPt( {514, 301} ),
                Origin( {1.16528925619835, 4.27551020408163} ),
                Offset( {44, -21} ),
                RightOfCenter( 0 ),
                Tag Line( 1 )
            ), Add Pin Annotation(
                Seg( RectSeg( 1 ) ),
                Index( 4 ),
                Index Row( 134 ),
                UniqueID( 1797828420 ),
                FoundPt( {523, 229} ),
                Origin( {1.22107438016529, 5.37755102040816} ),
                Offset( {-198, -11} ),
                RightOfCenter( 0 ),
                Tag Line( 1 )
            ), Add Pin Annotation(
                Seg( RectSeg( 1 ) ),
                Index( 7 ),
                Index Row( 107 ),
                UniqueID( 1797828423 ),
                FoundPt( {587, 172} ),
                Origin( {1.61776859504132, 6.25} ),
                Offset( {14, 0} ),
                RightOfCenter( 1 ),
                Tag Line( 1 )
            )}
        )
    )
);

Code Explanation:

1. Open data table;
2. Create Graph Builder.
3. Set graph size.
4. Hide control panel.
5. Assign X and Y variables.
6. Add heatmap element.
7. Send report to Graph Builder.
8. Add first pin annotation.
9. Add second pin annotation.
10. Add third pin annotation.
11. Add fourth pin annotation.
12. Add fifth pin annotation.

Example 427

Summary: Creates a heatmap with nested factors using Graph Builder, configuring bin shape to hexagonal and labeling by row.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 534, 456 ),
    Show Control Panel( 0 ),
    Variables( X( :height ), Y( :weight ) ),
    Elements( Heatmap( X, Y, Legend( 4 ), Bin Shape( "Hexagonal" ), Label( "Label by Row" ) ) ),
    SendToReport(
        Dispatch( {}, "graph title", TextEditBox, {Set Text( "Hoverlabel should point to James" )} ),
        Dispatch( {}, "Graph Builder", FrameBox,
            Add Pin Annotation(
                Seg( HexSeg( 1 ) ),
                Index( 3 ),
                Index Row( 6 ),
                UniqueID( 3 ),
                FoundPt( {327, 189} ),
                Origin( {61.5600473757655, 138.196328452888} ),
                Offset( {-218, -18} ),
                RightOfCenter( 1 ),
                Tag Line( 1 )
            )
        )
    )
);

Code Explanation:

1. Open data table.
2. Create Graph Builder window.
3. Set graph size.
4. Hide control panel.
5. Assign variables X and Y.
6. Add heatmap element.
7. Configure heatmap legend.
8. Set bin shape to hexagonal.
9. Label by row.
10. Update graph title.
11. Add pin annotation.
12. Specify segment and index.
13. Set unique ID and found point.
14. Define origin and offset.
15. Position annotation right of center.
16. Enable tag line.

Example 428

Summary: Creates a heatmap with nested factors using Graph Builder, displaying standard deviation charts and configuring specific graph elements.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 534, 456 ),
    Show Control Panel( 0 ),
    Variables( X( :height ), Y( :weight ) ),
    Elements( Heatmap( X, Y, Legend( 4 ), Bin Shape( "Hexagonal" ), Label( "Label by Row" ) ) ),
    SendToReport(
        Dispatch( {}, "graph title", TextEditBox, {Set Text( "Hoverlabel should point to James" )} ),
        Dispatch( {}, "Graph Builder", FrameBox,
            Add Pin Annotation(
                Seg( HexSeg( 1 ) ),
                Index( 3 ),
                Index Row( 6 ),
                UniqueID( 3 ),
                FoundPt( {327, 189} ),
                Origin( {61.5600473757655, 138.196328452888} ),
                Offset( {-218, -18} ),
                RightOfCenter( 1 ),
                Tag Line( 1 )
            )
        )
    )
);
Data Table("data_table") << Clear Select << Select Rows( [8] ) << Hide and Exclude;

Code Explanation:

1. Open data table;
2. Create Graph Builder window.
3. Set graph size to 534x456.
4. Hide control panel.
5. Assign height to X-axis, weight to Y-axis.
6. Add heatmap element with hexagonal bins.
7. Label rows in heatmap.
8. Set graph title to "Hoverlabel should point to James".
9. Add pin annotation at specific hexagon.
10. Select and hide James' row from table.

Example 429

Summary: Creates a heatmap to visualize the relationship between height and weight, with customizable legend positioning and graph title text.

Code:

Open("data_table.jmp");
Graph Builder(
    Show Control Panel( 0 ),
    Variables( X( :height ), Y( :weight ) ),
    Elements( Heatmap( X, Y, Legend( 4 ) ) ),
    SendToReport(
        Dispatch( {}, "graph title", TextEditBox, {Set Text( "Should be a hover label for Lawrence in the top right" )} ),
        Dispatch( {}, "Graph Builder", FrameBox,
            Add Pin Annotation(
                Seg( RectSeg( 1 ) ),
                Index( 15 ),
                Index Row( 39 ),
                UniqueID( 15 ),
                FoundPt( {778, 150} ),
                Origin( {71.0093167701863, 171.734693877551} ),
                RightOfCenter( 1 ),
                Tag Line( 1 )
            )
        )
    )
);

Code Explanation:

1. Open data table;
2. Create Graph Builder.
3. Hide control panel.
4. Set X variable to height.
5. Set Y variable to weight.
6. Add heatmap element.
7. Customize legend position.
8. Set graph title text.
9. Add pin annotation.
10. Position annotation on Lawrence's data point.

Example 430

Summary: Creates a heatmap with nested factors using Graph Builder, and adds a pin annotation to highlight specific data points.

Code:

Open("data_table.jmp");
Graph Builder(
    Show Control Panel( 0 ),
    Variables( X( :height ), Y( :weight ) ),
    Elements( Heatmap( X, Y, Legend( 4 ) ) ),
    SendToReport(
        Dispatch( {}, "graph title", TextEditBox, {Set Text( "Should be a hover label for Lawrence in the top right" )} ),
        Dispatch( {}, "Graph Builder", FrameBox,
            Add Pin Annotation(
                Seg( RectSeg( 1 ) ),
                Index( 15 ),
                Index Row( 39 ),
                UniqueID( 15 ),
                FoundPt( {778, 150} ),
                Origin( {71.0093167701863, 171.734693877551} ),
                RightOfCenter( 1 ),
                Tag Line( 1 )
            )
        )
    )
);
Data Table("data_table") << Clear Select << Select Rows( [15] ) << Exclude;

Code Explanation:

1. Open data table.
2. Launch Graph Builder.
3. Hide control panel.
4. Set X variable to height.
5. Set Y variable to weight.
6. Create heatmap element.
7. Add graph title.
8. Add pin annotation.
9. Select row 15.
10. Exclude selected row.

Example 431

Summary: Creates a heatmap with nested factors using Graph Builder, displaying standard deviation charts and configuring graph title and annotation properties.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 534, 456 ),
    Show Control Panel( 0 ),
    Variables( X( :height ), Y( :weight ) ),
    Elements( Heatmap( X, Y, Legend( 4 ), Label( "Label by Row" ) ) ),
    SendToReport(
        Dispatch( {}, "graph title", TextEditBox, {Set Text( "Hover label should point to \!"Jaclyn;Leslie\!"" )} ),
        Dispatch( {}, "Graph Builder", FrameBox,
            {Add Pin Annotation(
                Seg( RectSeg( 1 ) ),
                Index( 12 ),
                Index Row( 3 ),
                UniqueID( 12 ),
                FoundPt( {673, 205} ),
                Origin( {66.1180124223603, 154.897959183674} ),
                Offset( {-259, -48} ),
                RightOfCenter( 1 ),
                Tag Line( 1 )
            )}
        )
    )
);

Code Explanation:

1. Open data table.
2. Create Graph Builder window.
3. Set graph size.
4. Hide control panel.
5. Assign X and Y variables.
6. Add heatmap element.
7. Label by row.
8. Set graph title.
9. Add pin annotation.
10. Configure annotation properties.

Example 432

Summary: Creates a heatmap with nested factors using Graph Builder, displaying standard deviation charts and adding a pin annotation to highlight specific data points.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 534, 456 ),
    Show Control Panel( 0 ),
    Variables( X( :height ), Y( :weight ) ),
    Elements( Heatmap( X, Y, Legend( 4 ), Label( "Label by Row" ) ) ),
    SendToReport(
        Dispatch( {}, "graph title", TextEditBox, {Set Text( "Hover label should point to \!"Jaclyn;Leslie\!"" )} ),
        Dispatch( {}, "Graph Builder", FrameBox,
            {Add Pin Annotation(
                Seg( RectSeg( 1 ) ),
                Index( 12 ),
                Index Row( 3 ),
                UniqueID( 12 ),
                FoundPt( {673, 205} ),
                Origin( {66.1180124223603, 154.897959183674} ),
                Offset( {-259, -48} ),
                RightOfCenter( 1 ),
                Tag Line( 1 )
            )}
        )
    )
);
Data Table("data_table") << Clear Select << Select Rows( [15] ) << Hide and Exclude;

Code Explanation:

1. Open data table.
2. Create Graph Builder window.
3. Set graph size.
4. Hide control panel.
5. Define X and Y variables.
6. Add heatmap element.
7. Set legend position.
8. Label rows in heatmap.
9. Change graph title.
10. Add pin annotation.
11. Clear row selection.
12. Select specific row.
13. Hide and exclude selected row.

Example 433

Summary: Creates a hexagonal heatmap in Graph Builder to visualize geographic data, utilizing external scripts for advanced features and marker presets.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 534, 456 ),
    Show Control Panel( 0 ),
    Variables( X( :Longitude ), Y( :Latitude ) ),
    Elements( Heatmap( X, Y, Legend( 5 ), Bin Shape( "Hexagonal" ) ) ),
    SendToReport(
        Dispatch( {}, "Graph Builder", FrameBox,
            {Set Graphlet(
                Picture(
                    Try(
                        loader = If( Class Exists( "hllLoader" ),
                            New Object( "hllLoader" ),
                            Include( "$BUILTIN_SCRIPTS/hllib.jsl" )
                        );
                        loader:setDebug( 0 );
                        hlp = loader:lazyLoad( "hllPresets" );
                        hlp:launchMarker();
                    )
                ),
                Title( "Marker Preset" ),
                Reapply( 1 )
            ), Add Pin Annotation(
                Seg( HexSeg( 1 ) ),
                Index( 7 ),
                Index Row( 7 ),
                UniqueID( 1937430167 ),
                FoundPt( {680, 289} ),
                Origin( {-81.3311836427103, 41.6767811544572} ),
                Offset( {-309, 83} ),
                RightOfCenter( 1 ),
                Tag Line( 1 )
            )}
        )
    )
);

Code Explanation:

1. Open data table.
2. Create Graph Builder window.
3. Set graph size to 534x456.
4. Hide control panel.
5. Assign Longitude to X-axis.
6. Assign Latitude to Y-axis.
7. Add hexagonal heatmap element.
8. Configure heatmap legend.
9. Load external scripts for advanced features.
10. Apply marker preset and add pin annotation.

Example 434

Summary: Creates a variability chart with nested factors using Graph Builder, displaying standard deviation charts and adding pin annotations to visualize data relationships.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 451, 244 ),
    Show Control Panel( 0 ),
    Fit to Window,
    Variables( X( :age ), X( :sex, Position( 1 ) ), Y( :weight ), Overlay( :height ) ),
    Elements( Box Plot( X( 1 ), X( 2 ), Y, Legend( 15 ) ) ),
    SendToReport(
        Dispatch( {}, "Graph Builder", FrameBox,
            Add Pin Annotation(
                Seg( Box Plot Seg( 3 ) ),
                Index( {1, 8} ),
                Index Row( -1 ),
                UniqueID( 1 ),
                FoundPt( {137, 152} ),
                Origin( {1.59525005701811, 95.9866506689114} ),
                Offset( {35, -19} ),
                RightOfCenter( 0 ),
                Tag Line( 1 )
            )
        )
    )
);

Code Explanation:

1. Open data table;
2. Launch Graph Builder.
3. Set window size.
4. Hide control panel.
5. Fit to window.
6. Define variables: X(age), X(sex), Y(weight), Overlay(height).
7. Create box plot element.
8. Send report to Graph Builder.
9. Add pin annotation to graph.
10. Configure annotation properties.

Example 435

Summary: Creates a box plot graph with nested factors using Graph Builder, displaying standard deviation charts and configuring marker drawing mode to 'Fast'.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 486, 385 ),
    Show Control Panel( 0 ),
    Variables( X( :sex ), Y( :height ) ),
    Elements( Box Plot( X, Y, Legend( 4 ) ) ),
    SendToReport(
        Dispatch( {}, "Graph Builder", FrameBox,
            {Marker Drawing Mode( "Fast" ), {Add Pin Annotation(
                Seg( Box Plot Seg( 1 ) ),
                Index( {1, 0} ),
                Index Row( -1 ),
                UniqueID( 1 ),
                FoundPt( {465, 298} ),
                Origin( {0.119909502262443, 60.3099883040936} ),
                RightOfCenter( 0 ),
                Tag Line( 1 )
            ), Add Text Annotation( Text( "fast marker mode" ), Fixed Size( 0 ), Text Box( {3, 4, 113, 28} ), Filled( 0 ) )}}
        )
    )
);

Code Explanation:

1. Open data table.
2. Create Graph Builder window.
3. Set graph size to 486x385.
4. Hide control panel.
5. Assign variables: X=sex, Y=height.
6. Add box plot element.
7. Send report to Graph Builder.
8. Set marker drawing mode to "Fast".
9. Add pin annotation to box plot.
10. Add text annotation "fast marker mode".

Example 436

Summary: Creates a variability chart with nested factors using operator and part configurations, displaying standard deviation charts in JMP.

Code:

dt = Open("data_table.jmp");
dt << Graph Builder(
    Size( 425, 449 ),
    Show Control Panel( 0 ),
    Variables( X( :age ), Y( :weight ) ),
    Elements( Box Plot( X, Y, Legend( 15 ) ) ),
    Local Data Filter( Add Filter( columns( :sex ), Where( :sex == "M" ) ) ),
    SendToReport(
        Dispatch( {}, "Graph Builder", FrameBox,
            Add Pin Annotation(
                Seg( Box Plot Seg( 5 ) ),
                Index( {1, 1} ),
                Index Row( {1, 1} ),
                UniqueID( 1869019201 ),
                FoundPt( {811, 285} ),
                Origin( {3.97593582887701, 128.00997291867} ),
                Offset( {-255, -77} ),
                RightOfCenter( 1 ),
                Tag Line( 1 )
            )
        )
    )
);

Code Explanation:

1. Open data table.
2. Create graph builder window.
3. Set graph size.
4. Hide control panel.
5. Assign variables to axes.
6. Add box plot element.
7. Apply local data filter.
8. Send report to dispatch.
9. Add pin annotation to graph.
10. Configure annotation properties.

Example 437

Summary: Creates a variability chart with nested factors using Graph Builder, adding pin annotations to visualize specific segments.

Code:

dt = Open("data_table.jmp");
gb = dt << Graph Builder(
    Show Control Panel( 0 ),
    Variables( X( :age ), Y( :height ), Overlay( :sex ) ),
    Elements( Bar( X, Y, Legend( 4 ) ) ), 
);
frame = (gb << report)[FrameBox( 1 )];
gpin = frame << Add Pin Annotation(
    Seg( BarSeg( 1 ) ),
    Index( {3, 3} ),
    Index Row( {11, 11} ),
    UniqueID( 1369116883 ),
    FoundPt( {468, 328} ),
    Origin( {1.2603305785124, 35.48325} ),
    RightOfCenter( 0 ),
    Tag Line( 1 )
);

Code Explanation:

1. Open data table.
2. Create graph builder object.
3. Configure graph variables.
4. Add bar element to graph.
5. Access graph report.
6. Select first frame box.
7. Add pin annotation to frame.
8. Specify segment for annotation.
9. Define index and row indices.
10. Set unique ID and found point.

Example 438

Summary: Creates a variability chart with nested factors using Graph Builder, adding a pin annotation to highlight specific data points.

Code:

dt = Open("data_table.jmp");
gb = dt << Graph Builder(
    Show Control Panel( 0 ),
    Variables( X( :age ), Y( :height ), Overlay( :sex ) ),
    Elements( Bar( X, Y, Legend( 4 ) ) ), 
);
frame = (gb << report)[FrameBox( 1 )];
gpin = frame << Add Pin Annotation(
    Seg( BarSeg( 1 ) ),
    Index( {3, 3} ),
    Index Row( {11, 11} ),
    UniqueID( 1369116883 ),
    FoundPt( {468, 328} ),
    Origin( {1.2603305785124, 35.48325} ),
    RightOfCenter( 0 ),
    Tag Line( 1 )
);
gpin << Font( "Tahoma", 11, "Bold" );

Code Explanation:

1. Open data table.
2. Create Graph Builder object.
3. Hide control panel.
4. Set X, Y, and overlay variables.
5. Add bar element.
6. Access first frame box.
7. Add pin annotation.
8. Specify segment and indices.
9. Define unique ID and found point.
10. Set font style.

Example 439

Summary: Creates a treemap visualization in Graph Builder to display nested factors using operator and part configurations, with standard deviation charts.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 495, 440 ),
    Show Control Panel( 0 ),
    Variables( X( :age ), Color( :height ), Size( :height ) ),
    Elements( Treemap( X, Legend( 1 ) ) ),
    SendToReport(
        Dispatch( {}, "Graph Builder", FrameBox,
            {Add Pin Annotation(
                Seg( TreeMapSeg( 1 ) ),
                Index( 0 ),
                Index Row( 0 ),
                UniqueID( 0 ),
                FoundPt( {460, 217} ),
                Origin( {132.618285123967, 303.164413265306} ),
                RightOfCenter( 0 ),
                Tag Line( 1 )
            ), Add Pin Annotation(
                Seg( TreeMapSeg( 1 ) ),
                Index( 4 ),
                Index Row( 34 ),
                UniqueID( 4 ),
                FoundPt( {706, 363} ),
                Origin( {383.103719008264, 152.760204081633} ),
                RightOfCenter( 1 ),
                Tag Line( 1 )
            )}
        )
    )
);

Code Explanation:

1. Open data table;
2. Create Graph Builder window.
3. Set window size.
4. Hide control panel.
5. Assign variables to axes.
6. Add treemap element.
7. Send report to Graph Builder.
8. Add first pin annotation.
9. Specify segment for annotation.
10. Add second pin annotation.

Example 440

Summary: Creates a Treemap visualization in Graph Builder, displaying nested factors with color and size labels formatted as Currency USD.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 525, 369 ),
    Show Control Panel( 0 ),
    Variables( X( :age ), Color( :height ), Size( :weight ) ),
    Elements(
        Treemap(
            X,
            Legend( 11 ),
            Color Value( 1 ),
            Size Value( 1 ),
            Color Label Format( "Currency", "USD", Use thousands separator( 0 ), 10, 2 ),
            Size Label Format( "Currency", "USD", Use thousands separator( 0 ), 10, 0 )
        )
    ),
    SendToReport(
        Dispatch( {}, "Graph Builder", FrameBox,
            Add Pin Annotation(
                Seg( TreeMapSeg( 1 ) ),
                Index( 0 ),
                Index Row( 0 ),
                UniqueID( 0 ),
                FoundPt( {160, 206} ),
                Origin( {133.497368421053, 169.821183800623} ),
                RightOfCenter( 0 ),
                Tag Line( 1 )
            )
        )
    )
);

Code Explanation:

1. Open data table;
2. Create Graph Builder window.
3. Set window size to 525x369.
4. Hide control panel.
5. Assign variables: X=age, Color=height, Size=weight.
6. Add Treemap element.
7. Configure Treemap legend.
8. Set color label format to Currency USD.
9. Set size label format to Currency USD.
10. Add pin annotation to Treemap.

Example 441

Summary: Creates two Graph Builders to visualize relationships between height, weight, and age using nested factors with operator and part configurations.

Code:

Open("data_table.jmp");
Graph Builder(
    Show Control Panel( 0 ),
    Variables( X( :height ), Y( :weight ), Color( :height ) ),
    Elements( Points( X, Y, Legend( 21 ) ), Smoother( X, Y, Legend( 22 ) ) ),
    SendToReport(
        Dispatch( {}, "Graph Builder", FrameBox,
            Add Pin Annotation(
                Seg( Line Seg( 1 ) ),
                Index( {0, -1} ),
                Index Row( {0, -1} ),
                UniqueID( 0 ),
                FoundPt( {779, 238} ),
                Origin( {69.3416149068323, 141.128265204082} ),
                RightOfCenter( 1 ),
                Tag Line( 1 )
            )
        )
    )
);
Graph Builder(
    Show Control Panel( 0 ),
    Variables( X( :height ), Y( :weight ), Overlay( :age ), Color( :height ) ),
    Elements( Points( X, Y, Legend( 23 ) ), Smoother( X, Y, Legend( 24 ) ) ),
    SendToReport(
        Dispatch( {}, "Graph Builder", FrameBox,
            Add Pin Annotation(
                Seg( Line Seg( 6 ) ),
                Index( {0, -1} ),
                Index Row( {37, -1} ),
                UniqueID( 0 ),
                FoundPt( {786, 199} ),
                Origin( {69.2261697722567, 154.66649978727} ),
                RightOfCenter( 1 ),
                Tag Line( 1 )
            )
        )
    )
);

Code Explanation:

1. Open data table;
2. Create graph builder.
3. Hide control panel.
4. Set X to height, Y to weight, color by height.
5. Add points and smoother elements.
6. Add pin annotation to graph.
7. Create second graph builder.
8. Hide control panel.
9. Set X to height, Y to weight, overlay by age, color by height.
10. Add points and smoother elements.

Example 442

Summary: Creates a variability chart with nested factors using Graph Builder, displaying standard deviation charts and pin annotations.

Code:

Open("data_table.jmp");
Graph Builder(
    Show Control Panel( 0 ),
    Variables( X( :height ), X( :weight, Position( 1 ) ), Y( :height ), Color( :height ) ),
    Elements( Points( X( 1 ), X( 2 ), Y, Legend( 9 ) ), Smoother( X( 1 ), X( 2 ), Y, Legend( 11 ) ) ),
    SendToReport(
        Dispatch( {}, "Graph Builder", FrameBox,
            {Add Pin Annotation(
                Seg( Line Seg( 2 ) ),
                Index( {0, -1} ),
                Index Row( {0, -1} ),
                UniqueID( 0 ),
                FoundPt( {721, 189} ),
                Origin( {153.523052419097, 66.8539086324617} ),
                RightOfCenter( 1 ),
                Tag Line( 1 )
            ), Add Pin Annotation(
                Seg( Line Seg( 1 ) ),
                Index( {0, -1} ),
                Index Row( {0, -1} ),
                UniqueID( 0 ),
                FoundPt( {363, 353} ),
                Origin( {56.8011418684516, 56.937633498023} ),
                RightOfCenter( 0 ),
                Tag Line( 1 )
            )}
        )
    )
);

Code Explanation:

1. Open data table;
2. Launch Graph Builder.
3. Hide control panel.
4. Set X variables: height, weight.
5. Set Y variable: height.
6. Set color variable: height.
7. Add points element.
8. Add smoother element.
9. Add first pin annotation.
10. Add second pin annotation.

Example 443

Summary: Creates a graph builder with nested factors using operator and part configurations, displaying standard deviation charts for data analysis.

Code:

dt = Open("data_table.jmp");
gb = dt << Graph Builder(
    Size( 534, 450 ),
    Show Control Panel( 0 ),
    Variables(
        X(
            Transform Column(
                "age'",
                Ordinal,
                Set Property( "Configure Levels", 1 ),
                Set Property( "Value Order", {Custom Order( {12, 13, 15} )} ),
                Value Labels( {12 = "12", 13 = "Middle School", 15 = "High School"} ),
                Use Value Labels( 1 ),
                Formula( Match( :age, 14, 13, 16, 15, 17, 15, :age ) )
            )
        ),
        Y( :height ),
        Overlay( :sex )
    ),
    Elements( Bar( X, Y, Legend( 4 ), Bar Style( "Stacked" ) ) ),
    SendToReport(
        Dispatch( {}, "Graph Builder", FrameBox,
            {Add Pin Annotation(
                Seg( BarSeg( 1 ) ),
                Index( {1, 1} ),
                Index Row( {7, 7} ),
                UniqueID( 1 ),
                FoundPt( {140, 161} ),
                Origin( {-0.0217391304347827, 101.428571428571} ),
                RightOfCenter( 0 ),
                Tag Line( 1 )
            ), Add Pin Annotation(
                Seg( BarSeg( 1 ) ),
                Index( {4, 4} ),
                Index Row( {27, 27} ),
                UniqueID( 4 ),
                FoundPt( {466, 331} ),
                Origin( {2.00310559006211, 40.7142857142857} ),
                RightOfCenter( 1 ),
                Tag Line( 1 )
            )}
        )
    )
);

Code Explanation:

1. Open data table.
2. Create graph builder.
3. Set graph size.
4. Hide control panel.
5. Define X variable.
6. Transform age column.
7. Set ordinal property.
8. Configure levels.
9. Set value order.
10. Add value labels.

Example 444

Summary: Creates a variability chart with nested factors using Graph Builder, configuring X and Y variables, overlaying by sex, and adding a bar element.

Code:

Open("data_table.jmp");
gb = Graph Builder(
    Size( 528, 450 ),
    Show Control Panel( 0 ),
    Variables(
        X(
            Transform Column(
                "age'",
                Ordinal,
                Set Property( "Configure Levels", 1 ),
                Set Property( "Value Order", {Custom Order( {12, 15} )} ),
                Value Labels( {12 = "Middle Schoolers", 15 = "High Schoolers"} ),
                Use Value Labels( 1 ),
                Formula( Match( :age, 13, 12, 14, 12, 16, 15, 17, 15, :age ) )
            )
        ),
        Y( :height ),
        Overlay( :sex )
    ),
    Elements( Bar( X, Y, Legend( 6 ) ) ),
    SendToReport(
        Dispatch( {}, "Graph Builder", FrameBox,
            {Set Graphlet(
                Picture(
                    Try(
                        loader = If( Class Exists( "hllLoader" ),
                            New Object( "hllLoader" ),
                            Include( "$BUILTIN_SCRIPTS/hllib.jsl" )
                        );
                        loader:setDebug( 0 );
                        hlp = loader:lazyLoad( "hllPresets" );
                        hlp:launchTabulate();
                    )
                ),
                Title( "Tabulate Preset" ),
                Reapply( 1 )
            )}
        )
    )
);
frame = (gb << report)[FrameBox( 1 )];
gpin = frame << Add Pin Annotation(
    Seg( BarSeg( 1 ) ),
    Index( {1, 1} ),
    Index Row( {22, 22} ),
    UniqueID( 1 ),
    FoundPt( {203, 232} ),
    Origin( {0.0991735537190083, 39.318125} ),
    RightOfCenter( 0 ),
    Tag Line( 1 )
);

Code Explanation:

1. Open data table.
2. Create Graph Builder.
3. Set graph size.
4. Hide control panel.
5. Define X variable with transformation.
6. Define Y variable.
7. Overlay by sex.
8. Add bar element.
9. Configure hover labels.
10. Add pin annotation to graph.

Example 445

Summary: Creates a variability chart with nested factors using operator and part configurations, displaying standard deviation charts in JMP.

Code:

dt = Open("data_table.jmp");
gb = dt << Graph Builder(
    Transform Column(
        "age'",
        Ordinal,
        Set Property( "Configure Levels", 1 ),
        Set Property( "Value Order", {Custom Order( {12, 15} )} ),
        Value Labels( {12 = "Middle School", 15 = "High School"} ),
        Use Value Labels( 1 ),
        Formula( Map Value( :age, {13, 12, 14, 12, 16, 15, 17, 15}, Unmatched( :age ) ) )
    ),
    Size( 528, 450 ),
    Show Control Panel( 0 ),
    Variables( X( :age' ), Y( :height ), Color( :age' ) ),
    Elements( Bar( X, Y, Legend( 6 ) ) ),
    SendToReport(
        Dispatch( {}, "Graph Builder", FrameBox,
            {Set Graphlet(
                Picture(
                    Try(
                        loader = If( Class Exists( "hllLoader" ),
                            New Object( "hllLoader" ),
                            Include( "$BUILTIN_SCRIPTS/hllib.jsl" )
                        );
                        loader:setDebug( 0 );
                        hlp = loader:lazyLoad( "hllPresets" );
                        hlp:launchLine();
                    )
                ),
                Title( "Line Preset" ),
                Reapply( 1 )
            ), Add Pin Annotation(
                Seg( BarSeg( 1 ) ),
                Index( {0, 0} ),
                Index Row( {0, 0} ),
                UniqueID( 0 ),
                FoundPt( {444, 272} ),
                Origin( {-0.0206611570247934, 43.79375} ),
                RightOfCenter( 0 ),
                Tag Line( 1 )
            )}
        )
    )
);

Code Explanation:

1. Open data table.
2. Create new column "age'".
3. Set "age'" as ordinal.
4. Configure levels for "age'".
5. Define value order for "age'".
6. Assign labels to values in "age'".
7. Use value labels for "age'".
8. Apply formula to "age'".
9. Build graph with "age'" on X, "height" on Y.
10. Customize graph with additional settings.

Example 446

Summary: Creates a bar chart with custom binning transformation to visualize the relationship between sex and weight, utilizing Graph Builder in JMP.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 733, 606 ),
    Show Control Panel( 0 ),
    Variables(
        X( :sex ),
        Y( :weight ),
        Overlay(
            Transform Column(
                "Custom Binning...[height]",
                Numeric,
                Nominal,
                Value Labels(
                    {"." = "Missing", 49 = "< 50", 50 = "50 — 55", 55 = "55 — 60", 60 = "60 — 65", 65 = "65 — 70", 70 = "70 — 75", 75 =
                    "‚â• 75"}
                ),
                Use Value Labels( 1 ),
                Formula( If( :height < 50, 49, :height >= 75, 75, 50 + 5 * Floor( (:height - 50) / 5 ) ) )
            )
        )
    ),
    Elements( Bar( X, Y, Legend( 5 ) ) ),
    SendToReport(
        Dispatch( {}, "Graph Builder", FrameBox,
            {Set Graphlet(
                Picture(
                    Try(
                        loader = If( Class Exists( "hllLoader" ),
                            New Object( "hllLoader" ),
                            Include( "$BUILTIN_SCRIPTS/hllib.jsl" )
                        );
                        loader:setDebug( 0 );
                        hlp = loader:lazyLoad( "hllPresets" );
                        hlp:launchHistogram();
                    )
                ),
                Title( "Histogram Preset" ),
                Reapply( 1 )
            ), Add Pin Annotation(
                Seg( BarSeg( 1 ) ),
                Index( {7, 7} ),
                Index Row( {21, 21} ),
                UniqueID( -1379562713 ),
                FoundPt( {698, 372} ),
                Origin( {1.03623188405797, 67.639} ),
                Offset( {-469, -195} ),
                RightOfCenter( 1 ),
                Tag Line( 1 )
            )}
        )
    )
);

Code Explanation:

1. Open data table;
2. Create Graph Builder window.
3. Set window size.
4. Hide control panel.
5. Define X variable.
6. Define Y variable.
7. Apply custom binning transformation.
8. Create bar chart element.
9. Send report to Graph Builder.
10. Add histogram preset picture.

Example 447

Summary: Creates a variability chart with nested factors using Graph Builder, displaying standard deviation charts and pin annotations.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 452, 229 ),
    Show Control Panel( 0 ),
    Show Legend( 0 ),
    Variables( X( :sex ), Y( :weight ), Color( :weight, Summary Statistic( "N" ) ) ),
    Elements( Points( X, Y, Legend( 7 ), Summary Statistic( "N" ) ) ),
    SendToReport(
        Dispatch( {}, "Graph Builder", FrameBox,
            Add Pin Annotation(
                Seg( Marker Seg( 1 ) ),
                Index( 0 ),
                Index Row( 0 ),
                UniqueID( 877840448 ),
                FoundPt( {154, 197} ),
                Origin( {-0.0196078431372549, 18.0213764727608} ),
                Offset( {-77, -50} ),
                RightOfCenter( 0 ),
                Tag Line( 1 )
            )
        )
    )
);

Code Explanation:

1. Open data table.
2. Create Graph Builder window.
3. Set window size.
4. Hide control panel.
5. Hide legend.
6. Define X, Y, and color variables.
7. Add points element.
8. Send report to Graph Builder.
9. Add pin annotation to graph.
10. Configure annotation properties.

Example 448

Summary: Creates a variability chart with nested factors using Graph Builder, transforming the height column mean and displaying standard deviation charts.

Code:

Open("data_table.jmp");
Graph Builder(
    Show Control Panel( 0 ),
    Transform Column( "Mean[height][X]", Formula( Col Mean( :height, :"@Exclude"n, :"@Filter"n, :"@Graph"n, :"@Overlay"n, :"@X"n ) ) ),
    Size( 570, 502 ),
    Variables( X( :sex ), Y( :"Mean[height][X]"n ), Color( :sex ) ),
    Elements( Bar( X, Y, Legend( 6 ) ) ),
    SendToReport(
        Dispatch( {}, "graph title", TextEditBox, {Set Text( "Dynamic Transform Col Mean of Height vs. Sex" )} ),
        Dispatch( {}, "Graph Builder", FrameBox,
            {Set Graphlet(
                Picture(
                    Try(
                        loader = If( Class Exists( "hllLoader" ),
                            New Object( "hllLoader" ),
                            Include( "$BUILTIN_SCRIPTS/hllib.jsl" )
                        );
                        loader:setDebug( 0 );
                        hlp = loader:lazyLoad( "hllPresets" );
                        hlp:launchBar();
                    ,
                        Write(
                            "
Hover Label: Unable to launch Preset, please check that the Preset library is available at $BUILTIN_SCRIPTS/hllib.jsl"
                        );
                        Write( Eval Insert( "
Exception: ^exception_msg^" ) );
                        Empty();
                    )
                ),
                Title( "Bar Preset" ),
                Reapply( 1 )
            ), Add Pin Annotation(
                Seg( BarSeg( 1 ) ),
                Index( {0, 0} ),
                Index Row( {0, 0} ),
                UniqueID( 0 ),
                FoundPt( {415, 278} ),
                Origin( {-0.140495867768595, 42.6395939086294} ),
                RightOfCenter( 0 ),
                Tag Line( 1 ),
                Text Color( {224, 224, 224} ),
                Background Color( {44, 44, 44} )
            )}
        )
    )
);

Code Explanation:

1. Open data_table data
2. Create Graph Builder window.
3. Hide control panel.
4. Transform height column mean.
5. Set graph size.
6. Assign variables: sex for X, mean height for Y, color by sex.
7. Add bar element.
8. Set graph title.
9. Load hover label library.
10. Apply bar preset with annotations.

Example 449

Summary: Creates a variability chart with nested factors using operator and part configurations, displaying standard deviation charts.

Code:

Open("data_table.jmp");
Graph Builder(
    Transform Column(
        "Col Minimum[height]@X",
        Formula( Col Minimum( :height, :"@Exclude"n, :"@Filter"n, :"@Graph"n, :"@Overlay"n, :"@X"n ) )
    ),
    Size( 530, 452 ),
    Show Control Panel( 0 ),
    Variables( X( :age ), Y( :"Col Minimum[height]@X"n ), Color( :age ), Size( :"Col Minimum[height]@X"n ) ),
    Elements( Line( X, Y, Legend( 2 ) ) ),
    Local Data Filter( Add Filter( columns( :sex ), Where( :sex == "M" ) ) ),
    SendToReport(
        Dispatch( {}, "Graph Builder", FrameBox,
            {Set Graphlet(
                Picture(
                    Try(
                        loader = If( Class Exists( "hllLoader" ),
                            New Object( "hllLoader" ),
                            Include( "$BUILTIN_SCRIPTS/hllib.jsl" )
                        );
                        loader:setDebug( 0 );
                        hlp = loader:lazyLoad( "hllPresets" );
                        hlp:launchLabel Viewer();
                    ,
                        Write(
                            "
Hover Label: Unable to launch Preset, please check that the Preset library is available at $BUILTIN_SCRIPTS/hllib.jsl"
                        );
                        Write( Eval Insert( "
Exception: ^exception_msg^" ) );
                        Empty();
                    )
                ),
                Title( "Label Viewer Preset" ),
                Reapply( 1 )
            ), Add Pin Annotation(
                Seg( Line Seg( 1 ) ),
                Index( {0, 0} ),
                Index Row( {5, 5} ),
                UniqueID( 1 ),
                FoundPt( {568, 425} ),
                Origin( {0, 51} ),
                Offset( {115, -28} ),
                RightOfCenter( 0 ),
                Tag Line( 1 ),
                Text Color( {224, 224, 224} ),
                Background Color( {44, 44, 44} )
            )}
        )
    )
);

Code Explanation:

1. Open data table;
2. Create new column for minimum height.
3. Set graph size.
4. Hide control panel.
5. Define X, Y, Color, Size variables.
6. Add line element to graph.
7. Apply local data filter for males.
8. Send report to graph builder.
9. Set graphlet with hover label viewer.
10. Add pin annotation to graph.

Example 450

Summary: Creates a variability chart with nested factors using operator and part configurations, displaying standard deviation charts in Graph Builder.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 564, 403 ),
    Show Control Panel( 0 ),
    Variables( X( :Region ), Y( :POP ), Color( :Region, Summary Statistic( "N" ) ) ),
    Elements( Points( X, Y, Legend( 26 ), Summary Statistic( "Sum" ) ) ),
    SendToReport(
        Dispatch( {}, "Graph Builder", FrameBox,
            {Add Pin Annotation(
                Seg( Marker Seg( 1 ) ),
                Index( 0 ),
                Index Row( 45 ),
                UniqueID( 718934320 ),
                FoundPt( {136, 260} ),
                Origin( {0.0228215767634854, 10149.2537313433} ),
                Offset( {0, -23} ),
                Tag Line( 1 )
            ), Add Pin Annotation(
                Seg( Marker Seg( 1 ) ),
                Index( 4 ),
                Index Row( 20 ),
                UniqueID( 718934324 ),
                FoundPt( {453, 349} ),
                Origin( {3.96887966804979, 3507.46268656716} ),
                Offset( {-335, -7} ),
                Tag Line( 1 )
            )}
        )
    )
);

Code Explanation:

1. Open data table;
2. Launch Graph Builder.
3. Set graph size.
4. Hide control panel.
5. Assign variables: X, Y, Color.
6. Add points element.
7. Configure summary statistic.
8. Send report commands.
9. Add first pin annotation.
10. Add second pin annotation.

Example 451

Summary: Creates a variability chart with nested factors using operator and part configurations, displaying standard deviation charts.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 473, 302 ),
    Show Control Panel( 0 ),
    Show Footer( 0 ),
    Variables( X( :age ), Y( :height ) ),
    Elements( Bar( X, Y, Legend( 1 ), Error Interval( "Range" ) ) ),
    SendToReport(
        Dispatch( {}, "Graph Builder", FrameBox,
            Add Pin Annotation(
                Seg( BarSeg( 1 ) ),
                Index( {0, 0} ),
                Index Row( {0, 0} ),
                UniqueID( -1371631728 ),
                FoundPt( {88, 169} ),
                Origin( {-0.0524475524475524, 37.7005464480874} ),
                RightOfCenter( 0 ),
                Tag Line( 1 )
            )
        )
    )
);

Code Explanation:

1. Open data table;
2. Create graph builder.
3. Set graph size.
4. Hide control panel.
5. Hide footer.
6. Assign variables X and Y.
7. Add bar element.
8. Add error interval.
9. Send report.
10. Add pin annotation.

Example 452

Summary: Creates a variability chart with nested factors using Graph Builder, displaying standard deviation charts and pin annotations.

Code:

Open("data_table.jmp");
Graph Builder(
    Show Control Panel( 0 ),
    Variables( X( :height ), Y( :weight ), Overlay( :sex ) ),
    Elements( Points( X, Y, Legend( 8 ) ), Smoother( X, Y, Legend( 9 ) ) ),
    SendToReport(
        Dispatch( {}, "Graph Builder", FrameBox,
            Add Pin Annotation(
                Seg( Marker Seg( 2 ) ),
                Index( 1 ),
                Index Row( 6 ),
                UniqueID( 1 ),
                FoundPt( {585, 276} ),
                Origin( {61.0032298136646, 128.036216861997} ),
                Offset( {-177, -59} ),
                RightOfCenter( 1 ),
                Tag Line( 1 ),
                Frame Color( "Dark Purple" ),
                Text Color( "Dark Red" ),
                Background Color( "Medium Dark BlueGreen" ),
                Filled( 0 )
            )
        )
    )
);

Code Explanation:

1. Open data table;
2. Launch Graph Builder.
3. Hide control panel.
4. Set X to height.
5. Set Y to weight.
6. Overlay by sex.
7. Add points element.
8. Add smoother element.
9. Send report to dispatch.
10. Add pin annotation.

Example 453

Summary: Creates a variability chart with nested factors using Graph Builder, displaying standard deviation charts and pin annotations.

Code:

Open("data_table.jmp");
Graph Builder(
    Variables( X( :sex ) ),
    Elements( Histogram( X, Legend( 11 ), Response Scale( "Percent" ) ) ),
    SendToReport(
        Dispatch( {}, "Graph Builder", FrameBox,
            {Add Pin Annotation(
                Seg( Hist Seg( 1 ) ),
                Index( {0, 12} ),
                Index Row( 0 ),
                UniqueID( 0 ),
                FoundPt( {380, 362} ),
                Origin( {-0.316666666666667, 0.253365357142857} ),
                RightOfCenter( 0 ),
                Tag Line( 1 )
            ), Add Pin Annotation(
                Seg( Hist Seg( 1 ) ),
                Index( {12, 24} ),
                Index Row( 5 ),
                UniqueID( 12 ),
                FoundPt( {729, 264} ),
                Origin( {1.16779513888889, 0.414597857142857} ),
                RightOfCenter( 1 ),
                Tag Line( 1 )
            )}
        )
    )
);

Code Explanation:

1. Open data table;
2. Launch Graph Builder.
3. Set X variable to sex.
4. Add histogram element.
5. Use percent response scale.
6. Send report to Graph Builder.
7. Add first pin annotation.
8. Specify segment for annotation.
9. Define index range for annotation.
10. Add second pin annotation.

Example 454

Summary: Creates a heatmap to visualize the relationship between ln(dose) and Dose, utilizing Graph Builder with nested factors.

Code:

dt = Open("data_table.jmp");
gb = dt << Graph Builder(
    Size( 515, 448 ),
    Show Control Panel( 0 ),
    Variables( X( :"ln(dose)"n ), Y( :Dose ) ),
    Elements( Heatmap( X, Y, Legend( 5 ) ) ),
    SendToReport(
        Dispatch( {}, "Graph Builder", FrameBox,
            {Add Pin Annotation(
                Seg( RectSeg( 1 ) ),
                Index( 3 ),
                Index Row( 3 ),
                UniqueID( 897469107 ),
                FoundPt( {376, 324} ),
                Origin( {0.20940170940171, 1.31404958677686} ),
                Offset( {-163, -174} ),
                Tag Line( 1 )
            ), Add Pin Annotation(
                Seg( RectSeg( 1 ) ),
                Index( 0 ),
                Index Row( 0 ),
                UniqueID( 897469104 ),
                FoundPt( {88, 407} ),
                Origin( {-2.25213675213675, 0.285123966942149} ),
                Offset( {-29, -130} ),
                Tag Line( 1 )
            ), Add Pin Annotation(
                Seg( RectSeg( 1 ) ),
                Index( 4 ),
                Index Row( 4 ),
                UniqueID( 897469108 ),
                FoundPt( {489, 91} ),
                Origin( {1.17521367521368, 4.20247933884298} ),
                Offset( {-121, 115} ),
                Tag Line( 1 )
            )}
        )
    )
);
jnl = gb << journal;

Code Explanation:

1. Open data table.
2. Create Graph Builder object.
3. Set graph size.
4. Hide control panel.
5. Define X and Y variables.
6. Add heatmap element.
7. Send report commands.
8. Add first pin annotation.
9. Add second pin annotation.
10. Add third pin annotation.

Example 455

Summary: Creates a heatmap to visualize the relationship between ln(dose) and Dose, with interactive pin annotations.

Code:

dt = Open("data_table.jmp");
gb = dt << Graph Builder(
    Size( 515, 448 ),
    Show Control Panel( 0 ),
    Variables( X( :"ln(dose)"n ), Y( :Dose ) ),
    Elements( Heatmap( X, Y, Legend( 5 ) ) ),
    SendToReport(
        Dispatch( {}, "Graph Builder", FrameBox,
            {Add Pin Annotation(
                Seg( RectSeg( 1 ) ),
                Index( 3 ),
                Index Row( 3 ),
                UniqueID( 897469107 ),
                FoundPt( {376, 324} ),
                Origin( {0.20940170940171, 1.31404958677686} ),
                Offset( {-163, -174} ),
                Tag Line( 1 )
            ), Add Pin Annotation(
                Seg( RectSeg( 1 ) ),
                Index( 0 ),
                Index Row( 0 ),
                UniqueID( 897469104 ),
                FoundPt( {88, 407} ),
                Origin( {-2.25213675213675, 0.285123966942149} ),
                Offset( {-29, -130} ),
                Tag Line( 1 )
            ), Add Pin Annotation(
                Seg( RectSeg( 1 ) ),
                Index( 4 ),
                Index Row( 4 ),
                UniqueID( 897469108 ),
                FoundPt( {489, 91} ),
                Origin( {1.17521367521368, 4.20247933884298} ),
                Offset( {-121, 115} ),
                Tag Line( 1 )
            )}
        )
    )
);
jnl = gb << journal;
gb << close window;

Code Explanation:

1. Open data table;
2. Create Graph Builder object.
3. Set graph size to 515x448.
4. Hide control panel.
5. Assign variables: X as "ln(dose)", Y as Dose.
6. Add Heatmap element with legend.
7. Send report to Graph Builder.
8. Add three pin annotations with specific properties.
9. Create journal from Graph Builder.
10. Close Graph Builder window.

Example 456

Summary: Creates a variability chart with nested factors using operator and part configurations, displaying standard deviation charts for data analysis.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 601, 424 ),
    Show Control Panel( 0 ),
    Show Legend( 0 ),
    Variables( X( :Operator ), X( :part#, Position( 1 ) ), Y( :Measurement ), Y( :Measurement ), Color( :part# ) ),
    Elements(
        Position( 1, 1 ),
        Line( X( 1 ), X( 2 ), Y, Legend( 16 ) ),
        Points( X( 2 ), X( 1 ), Y, Legend( 14 ), Summary Statistic( "Mean" ) )
    ),
    Elements( Position( 1, 2 ), Points( X( 2 ), X( 1 ), Y, Legend( 8 ), Summary Statistic( "Range" ) ) ),
    SendToReport(
        Dispatch( {}, "400", ScaleBox,
            {Legend Model(
                14,
                Base( 0, 0, 0 ),
                Base( 1, 0, 0 ),
                Base( 2, 0, 0 ),
                Base( 3, 0, 0 ),
                Base( 4, 0, 0 ),
                Base( 5, 0, 0 ),
                Base( 6, 0, 0 ),
                Base( 7, 0, 0 ),
                Base( 8, 0, 0 ),
                Base( 9, 0, 0 )
            )}
        ),
        Dispatch( {}, "Graph Builder", FrameBox,
            Add Pin Annotation(
                Seg( Marker Seg( 1 ) ),
                Index( 15 ),
                Index Row( 45 ),
                UniqueID( 891722495 ),
                FoundPt( {344, 112} ),
                Origin( {14.9511278195489, 0.827167630057803} )
            )
        ),
        Dispatch( {}, "Graph Builder", FrameBox( 2 ),
            Add Pin Annotation(
                Seg( Marker Seg( 1 ) ),
                Index( 15 ),
                Index Row( 45 ),
                UniqueID( 891727903 ),
                FoundPt( {340, 248} ),
                Origin( {14.7255639097744, 0.301162790697674} )
            )
        ),
        Dispatch( {}, "400", LegendBox,
            {Set Wrap( 20 ), Legend Position(
                {16, [10, 11, 12, 13, 14, 15, 16, 17, 18, 19], 14, [0, 1, 2, 3, 4, 5, 6, 7, 8, 9], 8, [-3, -3, -3, -3, -3, -3, -3, -3, -3,
                -3]}
            )}
        )
    )
);

Code Explanation:

1. Open data table.
2. Create Graph Builder window.
3. Set window size.
4. Hide control panel.
5. Hide legend.
6. Define variables for graph.
7. Add line element.
8. Add points element with mean summary.
9. Add points element with range summary.
10. Customize legend and add annotations.

Example 457

Summary: Creates a variability chart with nested factors using operator and part configurations, displaying standard deviation charts in Graph Builder.

Code:

dt = Open("data_table.jmp");
gb = dt << Graph Builder(
    Size( 403, 296 ),
    Show Control Panel( 0 ),
    Variables( X( :weight ), Group Y( :age ) ),
    Elements( Histogram( X, Legend( 5 ) ) ),
    SendToReport(
        Dispatch( {}, "Graph Builder", FrameBox,
            Add Pin Annotation(
                Seg( Hist Seg( 1 ) ),
                Index( {48, 60} ),
                Index Row( 3 ),
                UniqueID( 48 ),
                FoundPt( {303, 89} ),
                Origin( {152.483282674772, 0.987452631578947} ),
                RightOfCenter( 1 ),
                Tag Line( 1 )
            )
        ),
        Dispatch( {}, "Graph Builder", FrameBox( 3 ),
            Add Pin Annotation(
                Seg( Hist Seg( 1 ) ),
                Index( {48, 60} ),
                Index Row( 17 ),
                UniqueID( 48 ),
                FoundPt( {282, 168} ),
                Origin( {144.536474164134, 0.740589473684211} ),
                RightOfCenter( 1 ),
                Tag Line( 1 )
            )
        ),
        Dispatch( {}, "Graph Builder", FrameBox( 6 ),
            Add Pin Annotation(
                Seg( Hist Seg( 1 ) ),
                Index( {60, 72} ),
                Index Row( 39 ),
                UniqueID( 60 ),
                FoundPt( {353, 283} ),
                Origin( {171.404255319149, 0.987452631578947} ),
                Offset( {-128, -34} ),
                RightOfCenter( 1 ),
                Tag Line( 1 )
            )
        )
    )
);

Code Explanation:

1. Open data table.
2. Create Graph Builder window.
3. Set graph size.
4. Hide control panel.
5. Assign variables: weight (X), age (Group Y).
6. Add histogram element.
7. Add pin annotation to first frame.
8. Add pin annotation to third frame.
9. Add pin annotation to sixth frame.
10. Display graph builder.

Example 458

Summary: Creates a variability chart with nested factors using operator and part configurations, displaying standard deviation charts in JMP.

Code:

dt = Open("data_table.jmp");
gb = dt << Graph Builder(
    Size( 403, 296 ),
    Show Control Panel( 0 ),
    Variables( X( :weight ), Group Y( :age ) ),
    Elements( Histogram( X, Legend( 5 ) ) ),
    SendToReport(
        Dispatch( {}, "Graph Builder", FrameBox,
            Add Pin Annotation(
                Seg( Hist Seg( 1 ) ),
                Index( {48, 60} ),
                Index Row( 3 ),
                UniqueID( 48 ),
                FoundPt( {303, 89} ),
                Origin( {152.483282674772, 0.987452631578947} ),
                RightOfCenter( 1 ),
                Tag Line( 1 )
            )
        ),
        Dispatch( {}, "Graph Builder", FrameBox( 3 ),
            Add Pin Annotation(
                Seg( Hist Seg( 1 ) ),
                Index( {48, 60} ),
                Index Row( 17 ),
                UniqueID( 48 ),
                FoundPt( {282, 168} ),
                Origin( {144.536474164134, 0.740589473684211} ),
                RightOfCenter( 1 ),
                Tag Line( 1 )
            )
        ),
        Dispatch( {}, "Graph Builder", FrameBox( 6 ),
            Add Pin Annotation(
                Seg( Hist Seg( 1 ) ),
                Index( {60, 72} ),
                Index Row( 39 ),
                UniqueID( 60 ),
                FoundPt( {353, 283} ),
                Origin( {171.404255319149, 0.987452631578947} ),
                Offset( {-128, -34} ),
                RightOfCenter( 1 ),
                Tag Line( 1 )
            )
        )
    )
);
dt2 = Open("data_table.jmp");
gb2 = dt2 << Graph Builder(
    Size( 326, 255 ),
    Show Control Panel( 0 ),
    Variables( X( :Color ), Overlay( :Carat Weight ) ),
    Elements( Bar( X, Legend( 4 ), Bar Style( "Stacked" ) ) ),
    SendToReport(
        Dispatch( {}, "Graph Builder", FrameBox,
            Add Pin Annotation(
                Seg( BarSeg( 1 ) ),
                Index( {1, 1} ),
                Index Row( {676, 676} ),
                UniqueID( 1 ),
                FoundPt( {101, 458} ),
                Origin( {0.187350835322196, 9.39024390243903} ),
                Offset( {-35, -137} ),
                RightOfCenter( 0 ),
                Tag Line( 1 )
            )
        )
    )
);

Code Explanation:

1. Open data table;
2. Create Graph Builder window.
3. Set size to 403x296.
4. Hide control panel.
5. Assign weight to X, age to Group Y.
6. Add histogram element.
7. Add pin annotation for segment 1.
8. Add another pin annotation for segment 1.
9. Add third pin annotation for segment 1.
10. Open data table;
11. Create second Graph Builder window.
12. Set size to 326x255.
13. Hide control panel.
14. Assign Color to X, Carat Weight to Overlay.
15. Add stacked bar element.
16. Add pin annotation for segment 1.

Example 459

Summary: Creates a variability chart with nested factors using operator and part configurations, displaying standard deviation charts in Graph Builder.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 528, 450 ),
    Show Control Panel( 0 ),
    Variables( X( :Cut ), Y( :Depth ), Y( :Table, Position( 1 ) ) ),
    Elements( Bar( X, Y( 1 ), Y( 2 ), Legend( 11 ), Summary Statistic( "Mode" ) ) ),
    SendToReport(
        Dispatch( {}, "Graph Builder", FrameBox,
            {Add Pin Annotation(
                Seg( BarSeg( 1 ) ),
                Index( {0, 1} ),
                Index Row( {593, 1057} ),
                UniqueID( -269494896 ),
                FoundPt( {129, 230} ),
                Origin( {0.103305785123967, 37.48525} ),
                RightOfCenter( 0 ),
                Tag Line( 1 )
            ), Add Pin Annotation(
                Seg( BarSeg( 1 ) ),
                Index( {3, 6} ),
                Index Row( {927, 6} ),
                UniqueID( -269494893 ),
                FoundPt( {457, 305} ),
                Origin( {2.81404958677686, 24.409} ),
                RightOfCenter( 1 ),
                Tag Line( 1 )
            )}
        )
    )
);
Graph Builder(
    Size( 534, 450 ),
    Show Control Panel( 0 ),
    Variables( X( :Cut ), Y( :Price ), Color( :Clarity, Summary Statistic( "Mode" ) ) ),
    Elements( Bar( X, Y, Legend( 9 ), Summary Statistic( "Mode" ) ) ),
    SendToReport(
        Dispatch( {}, "Graph Builder", FrameBox,
            {Add Pin Annotation(
                Seg( BarSeg( 1 ) ),
                Index( {0, 0} ),
                Index Row( {593, 593} ),
                UniqueID( -346605056 ),
                FoundPt( {398, 233} ),
                Origin( {-0.0213675213675213, 2456.784} ),
                RightOfCenter( 0 ),
                Tag Line( 1 )
            ), Add Pin Annotation(
                Seg( BarSeg( 1 ) ),
                Index( {3, 3} ),
                Index Row( {927, 927} ),
                UniqueID( -346605053 ),
                FoundPt( {749, 439} ),
                Origin( {2.97863247863248, 662.112} ),
                RightOfCenter( 1 ),
                Tag Line( 1 )
            )}
        )
    )
);

Code Explanation:

1. Open data table;
2. Create Graph Builder window.
3. Set graph size.
4. Hide control panel.
5. Assign variables: Cut (X), Depth (Y1), Table (Y2).
6. Add bar element with mode summary.
7. Add pin annotations.
8. Create second Graph Builder window.
9. Set graph size.
10. Hide control panel.

Example 460

Summary: Creates a nested variability chart using Graph Builder, with interactive features for exploring data relationships.

Code:

dt = Open("data_table.jmp");
gb2 = dt << Graph Builder(
    Show Control Panel( 0 ),
    Variables( X( :age ), Y( :sex ) ),
    Elements( Mosaic( X, Y, Legend( 6 ) ) ),
    SendToReport(
        Dispatch( {}, "Graph Builder", FrameBox,
            Add Pin Annotation(
                Seg( MosaicSeg( 1 ) ),
                Index( {4, 1} ),
                Index Row( {4, 1} ),
                UniqueID( 9 ),
                FoundPt( {763, 198} ),
                Origin( {0.900634249471459, 0.808673469387755} ),
                RightOfCenter( 1 ),
                Tag Line( 1 )
            )
        )
    )
);

Code Explanation:

1. Open data table.
2. Create graph builder object.
3. Hide control panel.
4. Set X and Y variables.
5. Add mosaic element.
6. Send report dispatch.
7. Add pin annotation.
8. Specify segment for annotation.
9. Define index and row.
10. Set unique ID and found point.

Example 461

Summary: Creates a Mosaic chart with nested factors using Graph Builder, hiding and excluding specific rows in the data table.

Code:

dt = Open("data_table.jmp");
gb2 = dt << Graph Builder(
    Show Control Panel( 0 ),
    Variables( X( :age ), Y( :sex ) ),
    Elements( Mosaic( X, Y, Legend( 6 ) ) ),
    SendToReport(
        Dispatch( {}, "Graph Builder", FrameBox,
            Add Pin Annotation(
                Seg( MosaicSeg( 1 ) ),
                Index( {4, 1} ),
                Index Row( {4, 1} ),
                UniqueID( 9 ),
                FoundPt( {763, 198} ),
                Origin( {0.900634249471459, 0.808673469387755} ),
                RightOfCenter( 1 ),
                Tag Line( 1 )
            )
        )
    )
);
Data Table("data_table") << Clear Select << Select Rows( Index( 1, 15 ) ) << Hide and Exclude;

Code Explanation:

1. Open data table;
2. Create Graph Builder object.
3. Hide control panel.
4. Set X variable to "age".
5. Set Y variable to "sex".
6. Add Mosaic element.
7. Configure legend position.
8. Send report to Graph Builder.
9. Add pin annotation.
10. Select and hide rows 1 to 15.

Example 462

Summary: Creates a graph builder object with nested factors using operator and part configurations, displaying standard deviation charts.

Code:

dt = Open("data_table.jmp");
gb = dt << Graph Builder(
    Size( 640, 482 ),
    Show Control Panel( 0 ),
    Include Missing Categories( 1 ),
    Variables( X( :countries visited ) ),
    Elements( Bar( X, Legend( 5 ) ) ),
    SendToReport(
        Dispatch( {}, "Graph Builder", FrameBox,
            {Set Graphlet(
                Picture(
                    Try(
                        loader = If( Class Exists( "hllLoader" ),
                            New Object( "hllLoader" ),
                            Include( "$BUILTIN_SCRIPTS/hllib.jsl" )
                        );
                        loader:setDebug( 0 );
                        hlp = loader:lazyLoad( "hllPresets" );
                        hlp:launchLabel Viewer();
                    ,
                        Write(
                            "
Hover Label: Unable to launch Preset, please check that the Preset library is available at $BUILTIN_SCRIPTS/hllib.jsl"
                        );
                        Write( Eval Insert( "
Exception: ^exception_msg^" ) );
                        Empty();
                    )
                ),
                Title( "Label Viewer Preset" ),
                Reapply( 1 )
            ), {Add Pin Annotation(
                Seg( BarSeg( 1 ) ),
                Index( {28, 28} ),
                Index Row( {1, 1} ),
                UniqueID( 28 ),
                FoundPt( {786, 430} ),
                Origin( {28.0813866288268, 1.49982608695652} ),
                Offset( {-199, -124} ),
                RightOfCenter( 1 ),
                Tag Line( 1 )
            ), Add Pin Annotation(
                Seg( BarSeg( 1 ) ),
                Index( {11, 11} ),
                Index Row( -1 ),
                UniqueID( 11 ),
                FoundPt( {572, 527} ),
                Origin( {10.9581038392156, 2.21378969072165} ),
                Offset( {-171, -176} ),
                RightOfCenter( 0 ),
                Tag Line( 1 )
            )}}
        )
    )
);
gb2 = gb << redo analysis;

Code Explanation:

1. Open data table.
2. Create graph builder object.
3. Set graph size.
4. Hide control panel.
5. Include missing categories.
6. Set X variable.
7. Add bar element.
8. Send report to graph builder.
9. Set graphlet with picture.
10. Redo analysis.

Example 463

Summary: Creates a graph builder object with nested factors using operator and part configurations, displaying standard deviation charts.

Code:

dt = Open("data_table.jmp");
gb = dt << Graph Builder(
    Size( 640, 482 ),
    Show Control Panel( 0 ),
    Include Missing Categories( 1 ),
    Variables( X( :countries visited ) ),
    Elements( Bar( X, Legend( 5 ) ) ),
    SendToReport(
        Dispatch( {}, "Graph Builder", FrameBox,
            {Set Graphlet(
                Picture(
                    Try(
                        loader = If( Class Exists( "hllLoader" ),
                            New Object( "hllLoader" ),
                            Include( "$BUILTIN_SCRIPTS/hllib.jsl" )
                        );
                        loader:setDebug( 0 );
                        hlp = loader:lazyLoad( "hllPresets" );
                        hlp:launchLabel Viewer();
                    ,
                        Write(
                            "
Hover Label: Unable to launch Preset, please check that the Preset library is available at $BUILTIN_SCRIPTS/hllib.jsl"
                        );
                        Write( Eval Insert( "
Exception: ^exception_msg^" ) );
                        Empty();
                    )
                ),
                Title( "Label Viewer Preset" ),
                Reapply( 1 )
            ), {Add Pin Annotation(
                Seg( BarSeg( 1 ) ),
                Index( {28, 28} ),
                Index Row( {1, 1} ),
                UniqueID( 28 ),
                FoundPt( {786, 430} ),
                Origin( {28.0813866288268, 1.49982608695652} ),
                Offset( {-199, -124} ),
                RightOfCenter( 1 ),
                Tag Line( 1 )
            ), Add Pin Annotation(
                Seg( BarSeg( 1 ) ),
                Index( {11, 11} ),
                Index Row( -1 ),
                UniqueID( 11 ),
                FoundPt( {572, 527} ),
                Origin( {10.9581038392156, 2.21378969072165} ),
                Offset( {-171, -176} ),
                RightOfCenter( 0 ),
                Tag Line( 1 )
            )}}
        )
    )
);
gb2 = gb << redo analysis;
gb << close window;

Code Explanation:

1. Open data table.
2. Create graph builder object.
3. Set graph size.
4. Hide control panel.
5. Include missing categories.
6. Set X variable.
7. Add bar element.
8. Send report to Graph Builder.
9. Redo analysis.
10. Close window.

Example 464

Summary: Creates a variability chart with nested factors using operator and part configurations, displaying standard deviation charts in JMP.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 528, 450 ),
    Show Control Panel( 0 ),
    Variables( X( :Meal ), Y( :Date ) ),
    Elements( Bar( X, Y, Legend( 4 ), Summary Statistic( "N" ) ) ),
    SendToReport(
        Dispatch( {}, "Graph Builder", FrameBox,
            {Add Pin Annotation(
                Seg( BarSeg( 1 ) ),
                Index( {0, 0} ),
                Index Row( {28, 28} ),
                UniqueID( 936216256 ),
                FoundPt( {371, 327} ),
                Origin( {0.0578512396694215, 44.979} ),
                Offset( {32, -79} ),
                RightOfCenter( 0 ),
                Tag Line( 1 )
            ), Add Pin Annotation(
                Seg( BarSeg( 1 ) ),
                Index( {3, 3} ),
                Index Row( {48, 48} ),
                UniqueID( 936216259 ),
                FoundPt( {600, 425} ),
                Origin( {2.89669421487603, 21.5325} ),
                Offset( {-265, -26} ),
                RightOfCenter( 1 ),
                Tag Line( 1 )
            )}
        )
    )
);
Graph Builder(
    Size( 534, 450 ),
    Show Control Panel( 0 ),
    Variables( X( :Meal ), Y( :Date ), Color( :Calories ) ),
    Elements( Bar( X, Y, Legend( 6 ), Summary Statistic( "% of Total" ) ) ),
    SendToReport(
        Dispatch( {}, "Graph Builder", FrameBox,
            {Add Pin Annotation(
                Seg( BarSeg( 1 ) ),
                Index( {0, 0} ),
                Index Row( {28, 28} ),
                UniqueID( 1095232592 ),
                FoundPt( {372, 400} ),
                Origin( {0.0249999999999999, 0.0908050729536923} ),
                RightOfCenter( 0 ),
                Tag Line( 1 )
            ), Add Pin Annotation(
                Seg( BarSeg( 1 ) ),
                Index( {2, 2} ),
                Index Row( {246, 246} ),
                UniqueID( 1095232594 ),
                FoundPt( {542, 258} ),
                Origin( {2.15, 0.202929597818252} ),
                RightOfCenter( 0 ),
                Tag Line( 1 )
            )}
        )
    )
);

Code Explanation:

1. Open data table;
2. Create first Graph Builder.
3. Set size to 528x450.
4. Hide control panel.
5. Set X to Meal, Y to Date.
6. Add bar element with summary statistic "N".
7. Add pin annotation at specific coordinates.
8. Add another pin annotation at different coordinates.
9. Create second Graph Builder.
10. Set size to 534x450.
11. Hide control panel.
12. Set X to Meal, Y to Date, Color to Calories.
13. Add bar element with summary statistic "% of Total".
14. Add pin annotation at specific coordinates.
15. Add another pin annotation at different coordinates.

Example 465

Summary: Creates a Treemap visualization with nested factors using Graph Builder, displaying standard deviation charts and customizing pin annotations.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 495, 442 ),
    Show Control Panel( 0 ),
    Variables( X( :age ), Color( :age, Summary Statistic( "N" ) ) ),
    Elements( Treemap( X, Legend( 2 ) ) ),
    SendToReport(
        Dispatch( {}, "Graph Builder", FrameBox,
            {Add Pin Annotation(
                Seg( TreeMapSeg( 1 ) ),
                Index( 2 ),
                Index Row( 15 ),
                UniqueID( 2 ),
                FoundPt( {713, 291} ),
                Origin( {388.194886363636, 228.835596446701} ),
                RightOfCenter( 1 ),
                Tag Line( 1 ),
                Text Color( {224, 224, 224} ),
                Background Color( {44, 44, 44} )
            ), Add Pin Annotation(
                Seg( TreeMapSeg( 1 ) ),
                Index( 1 ),
                Index Row( 8 ),
                UniqueID( 1 ),
                FoundPt( {438, 435} ),
                Origin( {108.180681818182, 81.2447335025381} ),
                RightOfCenter( 0 ),
                Tag Line( 1 ),
                Text Color( {224, 224, 224} ),
                Background Color( {44, 44, 44} )
            )}
        )
    )
);

Code Explanation:

1. Open data_table data
2. Create Graph Builder window.
3. Set size to 495x442 pixels.
4. Hide control panel.
5. Assign X variable as age.
6. Assign color based on age summary statistic N.
7. Add Treemap element.
8. Add first pin annotation.
9. Add second pin annotation.
10. Customize annotations' appearance.

Example 466

Summary: Creates a heatmap preset in Graph Builder, utilizing nested factors and operator configurations to visualize data.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 522, 450 ),
    Show Control Panel( 0 ),
    Variables( X( :sex ), Y( :height ), Overlay( :age ) ),
    Elements( Bar( X, Legend( 4 ) ) ),
    SendToReport(
        Dispatch( {}, "Graph Builder", FrameBox,
            {Set Graphlet(
                Picture(
                    Try(
                        loader = If( Class Exists( "hllLoader" ),
                            New Object( "hllLoader" ),
                            Include( "$BUILTIN_SCRIPTS/hllib.jsl" )
                        );
                        loader:setDebug( 0 );
                        hlp = loader:lazyLoad( "hllPresets" );
                        hlp:launchHeatmap();
                    )
                ),
                Title( "Heatmap Preset" ),
                Reapply( 1 )
            ), Add Pin Annotation(
                Seg( BarSeg( 1 ) ),
                Index( {7, 7} ),
                Index Row( {13, 13} ),
                UniqueID( -893222521 ),
                FoundPt( {641, 338} ),
                Origin( {0.801652892561983, 3.40725} ),
                RightOfCenter( 1 ),
                Tag Line( 1 )
            )}
        )
    )
);

Code Explanation:

1. Open data table.
2. Launch Graph Builder.
3. Set graph size.
4. Hide control panel.
5. Define variables for graph.
6. Create bar element.
7. Send report to Graph Builder.
8. Set graphlet with picture.
9. Load heatmap preset.
10. Add pin annotation.

Example 467

Summary: Creates a variability chart with nested factors using Graph Builder, displaying standard deviation charts and configuring operator and part configurations.

Code:

dt = Open("data_table.jmp");
gb = dt << Graph Builder(
    Size( 534, 450 ),
    Show Control Panel( 0 ),
    Variables( X( :height ), X( :weight, Position( 1 ) ), Color( :sex ), Size( :age ) ),
    Elements( Parallel( X( 1 ), X( 2 ), Legend( 6 ) ) ),
    SendToReport(
        Dispatch( {}, "Graph Builder", FrameBox,
            {Add Pin Annotation(
                Seg( PolylineSeg( 1 ) ),
                Index( {38, -2} ),
                Index Row( {38, -2} ),
                UniqueID( 38 ),
                FoundPt( {289, 309} ),
                Origin( {0.435817805383023, 93.7795918367347} ),
                Offset( {-169, -83} ),
                RightOfCenter( 0 ),
                Tag Line( 1 )
            ), Add Pin Annotation(
                Seg( PolylineSeg( 1 ) ),
                Index( {2, -2} ),
                Index Row( {2, -2} ),
                UniqueID( 2 ),
                FoundPt( {366, 373} ),
                Origin( {0.754658385093168, 72.2244897959184} ),
                Offset( {69, -88} ),
                RightOfCenter( 1 ),
                Tag Line( 1 )
            )}
        )
    )
);

Code Explanation:

1. Open table.
2. Create Graph Builder.
3. Set size and hide control panel.
4. Define variables for X, Y, color, and size.
5. Add parallel plot element.
6. Send report to Graph Builder.
7. Add first pin annotation.
8. Specify segment, index, and unique ID.
9. Set found point and origin.
10. Adjust offset and tag line.

Example 468

Summary: Creates a variability chart with nested factors using operator and part configurations, displaying standard deviation charts in Graph Builder.

Code:

dt = Open("data_table.jmp");
gb = dt << Graph Builder(
    Size( 534, 450 ),
    Show Control Panel( 0 ),
    Variables( X( :height ), X( :weight, Position( 1 ) ), Color( :age ), Size( :age ) ),
    Elements( Parallel( X( 1 ), X( 2 ), Legend( 6 ) ) ),
    SendToReport(
        Dispatch( {}, "Graph Builder", FrameBox,
            {Add Pin Annotation(
                Seg( PolylineSeg( 1 ) ),
                Index( {4, -2} ),
                Index Row( {4, -2} ),
                UniqueID( 4 ),
                FoundPt( {684, 469} ),
                Origin( {0.978260869565217, 63.4677295918367} ),
                Offset( {8, -196} ),
                RightOfCenter( 1 ),
                Tag Line( 1 )
            ), Add Pin Annotation(
                Seg( PolylineSeg( 1 ) ),
                Index( {39, -2} ),
                Index Row( {39, -2} ),
                UniqueID( 39 ),
                FoundPt( {592, 258} ),
                Origin( {0.597308488612836, 134.532206632653} ),
                Offset( {-182, -32} ),
                RightOfCenter( 1 ),
                Tag Line( 1 )
            )}
        )
    )
);

Code Explanation:

1. Open data table.
2. Create Graph Builder object.
3. Set graph size.
4. Hide control panel.
5. Define variables for axes and color/size.
6. Add parallel plot element.
7. Send report to Graph Builder.
8. Add first pin annotation.
9. Specify segment for annotation.
10. Add second pin annotation.

Example 469

Summary: Creates a variability chart with nested factors using operator and part configurations, displaying standard deviation charts in Graph Builder.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 745, 534 ),
    Show Control Panel( 0 ),
    Variables(
        X( :height, Combine( "Parallel Merged" ) ),
        X( :weight, Position( 1 ), Combine( "Parallel Merged" ) ),
        Overlay( :age ),
        Size( :age )
    ),
    Elements( Points( X( 1 ), X( 2 ), Legend( 3 ) ) ),
    SendToReport(
        Dispatch( {}, "Graph Builder", FrameBox,
            {Add Pin Annotation(
                Seg( Marker Seg( 7 ) ),
                Index( 3 ),
                Index Row( 3 ),
                UniqueID( 3 ),
                FoundPt( {569, 179} ),
                Origin( {0.95821325648415, 144.873866689323} ),
                RightOfCenter( 1 ),
                Tag Line( 1 )
            ), Add Pin Annotation(
                Seg( Marker Seg( 4 ) ),
                Index( 4 ),
                Index Row( 31 ),
                UniqueID( 4 ),
                FoundPt( {270, 462} ),
                Origin( {0.0965417867435159, 65.9794561581986} ),
                RightOfCenter( 0 ),
                Tag Line( 1 )
            ), Add Pin Annotation(
                Seg( Marker Seg( 12 ) ),
                Index( 0 ),
                Index Row( 37 ),
                UniqueID( 0 ),
                FoundPt( {550, 283} ),
                Origin( {0.903458213256484, 115.880867766224} ),
                RightOfCenter( 1 ),
                Tag Line( 1 )
            )}
        )
    )
);

Code Explanation:

1. Open data_table data
2. Create Graph Builder window.
3. Set window size to 745x534.
4. Hide control panel.
5. Define X variables: height and weight.
6. Combine X variables in parallel merged mode.
7. Overlay age variable.
8. Use age for point size.
9. Add points element to graph.
10. Add pin annotations to graph.

Example 470

Summary: Creates a variability chart with nested factors using operator and part configurations, displaying standard deviation charts.

Code:

dt = Open("data_table.jmp");
dt << select rows( [1, 2, 3, 6] );
dt << label( 1 );
Graph Builder(
    Size( 528, 448 ),
    Show Control Panel( 0 ),
    Variables( X( :height ), X( :weight, Position( 1 ) ), Color( :sex ) ),
    Elements( Parallel( X( 1 ), X( 2 ), Legend( 4 ) ) ),
    SendToReport(
        Dispatch( {}, "Graph Builder", FrameBox,
            {DispatchSeg( PolylineSeg( 1 ), label offset( {1, 44, 55}, {2, 50, -77}, {3, 48, 47}, {6, 14, 21}, {25, 61, 56} ) )}
        )
    )
);

Code Explanation:

1. Open data table;
2. Select specific rows.
3. Label selected rows.
4. Create Graph Builder.
5. Set graph size.
6. Hide control panel.
7. Define X variables.
8. Define Y variable.
9. Define color variable.
10. Add parallel plot element.

Example 471

Summary: Creates a variability chart with nested factors using Graph Builder, displaying standard deviation charts and customizing annotation properties.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 522, 408 ),
    Show Control Panel( 0 ),
    Variables( Y( :age ) ),
    Elements( Histogram( Y, Legend( 3 ), Response Scale( "Percent" ) ) ),
    SendToReport(
        Dispatch( {}, "Graph Builder", FrameBox,
            Add Pin Annotation(
                Seg( Hist Seg( 1 ) ),
                Index( {48, 60} ),
                Index Row( {48, 60} ),
                UniqueID( 606570656 ),
                FoundPt( {133, 149} ),
                Origin( {0.0526675531914894, 3.96341463414634} ),
                Offset( {101, -27} ),
                Tag Line( 1 )
            )
        )
    )
);

Code Explanation:

1. Open data table;
2. Launch Graph Builder.
3. Set graph size.
4. Hide control panel.
5. Assign age variable to Y-axis.
6. Create histogram element.
7. Set response scale to percent.
8. Send report to Graph Builder.
9. Add pin annotation to graph.
10. Customize annotation properties.

Example 472

Summary: Creates a variability chart with nested factors using operator and part configurations, displaying standard deviation charts in JMP.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 676, 404 ),
    Show Control Panel( 0 ),
    Show Title( 0 ),
    Show Footer( 0 ),
    Variables( X( :age ), Y( :weight ), Group Y( :sex ) ),
    Elements(
        Bar( X, Y, Legend( 17 ), Summary Statistic( "% of Grand Total" ), Label( "Label by Value" ), Label Format( "Percent", 6, 2 ) )
    ),
    SendToReport(
        Dispatch( {}, "Graph Builder", FrameBox,
            Add Pin Annotation(
                Seg( BarSeg( 1 ) ),
                Index( {0, 0} ),
                Index Row( {0, 0} ),
                UniqueID( 1070315632 ),
                FoundPt( {385, 220} ),
                Origin( {0.0631399317406143, 0.123641304347826} ),
                RightOfCenter( 0 ),
                Tag Line( 1 )
            )
        )
    )
);

Code Explanation:

1. Open data table.
2. Create graph builder object.
3. Set graph size.
4. Hide control panel.
5. Hide title.
6. Hide footer.
7. Define variables for graph.
8. Add bar element with summary statistic.
9. Format labels as percentages.
10. Add pin annotation to graph.

Example 473

Summary: Creates a pie chart with nested factors using Graph Builder, displaying standard deviation charts and adding pin annotations.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 495, 440 ),
    Show Control Panel( 0 ),
    Variables( X( :age ), Overlay( :sex ) ),
    Elements( Pie( X, Legend( 3 ), Pie Style( "Coxcomb" ) ) ),
    SendToReport(
        Dispatch( {}, "Graph Builder", FrameBox,
            {Add Pin Annotation(
                Seg( Pie Seg( 1 ) ),
                Index( {2, 0} ),
                Index Row( {15, 0, 1} ),
                UniqueID( 4 ),
                FoundPt( {631, 382} ),
                Origin( {0.326785714285714, -0.326785714285714} ),
                RightOfCenter( 1 ),
                Tag Line( 1 )
            ), Add Pin Annotation(
                Seg( Pie Seg( 1 ) ),
                Index( {0, 0} ),
                Index Row( {0, 0, 1} ),
                UniqueID( 0 ),
                FoundPt( {654, 224} ),
                Origin( {0.45, 0.519642857142857} ),
                RightOfCenter( 1 ),
                Tag Line( 1 )
            ), Add Pin Annotation(
                Seg( Pie Seg( 1 ) ),
                Index( {4, 0} ),
                Index Row( {34, 0, 1} ),
                UniqueID( 8 ),
                FoundPt( {494, 302} ),
                Origin( {-0.407142857142857, 0.101785714285714} ),
                RightOfCenter( 0 ),
                Tag Line( 1 )
            )}
        )
    )
);

Code Explanation:

1. Open data table;
2. Create Graph Builder window.
3. Set graph size.
4. Hide control panel.
5. Assign age to X-axis.
6. Overlay sex variable.
7. Add pie chart element.
8. Use Coxcomb pie style.
9. Add first pin annotation.
10. Add second pin annotation.
11. Add third pin annotation.

Example 474

Summary: Creates a line graph with nested factors using Graph Builder, displaying standard deviation charts and pin annotations.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 549, 328 ),
    Show Control Panel( 0 ),
    Variables( X( :Position2 ), Y( :Weight ) ),
    Elements( Line( X, Y, Legend( 14 ), Missing Factors( "Treat as Zero" ) ) ),
    SendToReport(
        Dispatch( {}, "Graph Builder", FrameBox,
            {Add Pin Annotation(
                Seg( Line Seg( 1 ) ),
                Index( {1, 1} ),
                Index Row( {126, 126} ),
                UniqueID( 1886618850 ),
                FoundPt( {172, 225} ),
                Origin( {1.03212851405622, 193.111788338082} ),
                RightOfCenter( 0 ),
                Tag Line( 1 )
            ), Add Pin Annotation(
                Seg( Line Seg( 1 ) ),
                Index( {4, 4} ),
                Index Row( {47, 47} ),
                UniqueID( 1886618856 ),
                FoundPt( {386, 222} ),
                Origin( {4.04016064257028, 194.320634605888} ),
                Offset( {-48, 55} ),
                RightOfCenter( 1 ),
                Tag Line( 1 )
            ), Add Pin Annotation(
                Seg( Line Seg( 1 ) ),
                Index( {2, 2} ),
                Index Row( {61, 61} ),
                UniqueID( 1886618852 ),
                FoundPt( {242, 64} ),
                Origin( {2.01606425702811, 257.986538043685} ),
                Offset( {33, 24} ),
                RightOfCenter( 0 ),
                Tag Line( 1 )
            )}
        )
    )
);

Code Explanation:

1. Open data_table data
2. Create Graph Builder window.
3. Set graph size to 549x328.
4. Hide control panel.
5. Assign Position2 to X-axis.
6. Assign Weight to Y-axis.
7. Add line element with legend.
8. Add first pin annotation.
9. Add second pin annotation.
10. Add third pin annotation.

Example 475

Summary: Creates a graph with points and line of fit, displaying height vs. weight data, and adds a pin annotation to the frame.

Code:

dt = Open("data_table.jmp");
gb = dt << Graph Builder(
    Show Control Panel( 0 ),
    Variables( X( :height ), Y( :weight ) ),
    Elements( Points( X, Y, Legend( 4 ) ), Line Of Fit( X, Y, Legend( 6 ) ) )
);
frame = (gb << report)[FrameBox( 1 )];
gpin = frame << Add Pin Annotation(
    Seg( Marker Seg( 1 ) ),
    Index( 7 ),
    Index Row( 7 ),
    UniqueID( 691854391 ),
    FoundPt( {124, 311} ),
    Origin( {51.0074683737235, 80.0858968472606} ),
    Offset( {-4, -106} ),
    Tag Line( 1 )
);
gpin << Replace Text( "Replacing text of hover label with this message" );

Code Explanation:

1. Open data table;
2. Create Graph Builder object.
3. Hide control panel.
4. Set X variable to "height".
5. Set Y variable to "weight".
6. Add points element.
7. Add line of fit element.
8. Access first frame box.
9. Add pin annotation to frame.
10. Replace text of hover label.

Example 476

Summary: Creates a graph builder with points and line of fit elements, adding a pin annotation to display custom text.

Code:

dt = Open("data_table.jmp");
gb = dt << Graph Builder(
    Show Control Panel( 0 ),
    Variables( X( :height ), Y( :weight ) ),
    Elements( Points( X, Y, Legend( 4 ) ), Line Of Fit( X, Y, Legend( 6 ) ) )
);
frame = (gb << report)[FrameBox( 1 )];
gpin = frame << Add Pin Annotation(
    Seg( Marker Seg( 1 ) ),
    Index( 7 ),
    Index Row( 7 ),
    UniqueID( 691854391 ),
    FoundPt( {124, 311} ),
    Origin( {51.0074683737235, 80.0858968472606} ),
    Offset( {-4, -106} ),
    Tag Line( 1 )
);
gpin << Replace Text( "Nobody expects the Spanish Inquisition!" );

Code Explanation:

1. Open data table.
2. Create graph builder object.
3. Hide control panel.
4. Set X and Y variables.
5. Add points and line of fit elements.
6. Access first frame box.
7. Add pin annotation to frame.
8. Specify segment, index, and unique ID.
9. Set found point and origin coordinates.
10. Adjust offset and tag line.

Example 477

Summary: Creates and customizes a graph builder object with nested factors, adding pin annotations and replacing hover label text.

Code:

dt = Open("data_table.jmp");
gb = dt << Graph Builder(
    Show Control Panel( 0 ),
    Variables( X( :height ), Y( :weight ) ),
    Elements( Points( X, Y, Legend( 4 ) ), Line Of Fit( X, Y, Legend( 6 ) ) )
);
frame = (gb << report)[FrameBox( 1 )];
gpin = frame << Add Pin Annotation(
    Seg( Marker Seg( 1 ) ),
    Index( 7 ),
    Index Row( 7 ),
    UniqueID( 691854391 ),
    FoundPt( {124, 311} ),
    Origin( {51.0074683737235, 80.0858968472606} ),
    Offset( {-4, -106} ),
    Tag Line( 1 )
);
gpin << Replace Text( "Replacing text of hover label with this message" );
dt = Open("data_table.jmp");
gb = dt << Graph Builder(
    Show Control Panel( 0 ),
    Variables( X( :height ), Y( :weight ) ),
    Elements( Points( X, Y, Legend( 4 ) ), Line Of Fit( X, Y, Legend( 6 ) ) )
);
frame = (gb << report)[FrameBox( 1 )];
gpin = frame << Add Pin Annotation(
    Seg( Marker Seg( 1 ) ),
    Index( 7 ),
    Index Row( 7 ),
    UniqueID( 691854391 ),
    FoundPt( {124, 311} ),
    Origin( {51.0074683737235, 80.0858968472606} ),
    Offset( {-4, -106} ),
    Tag Line( 1 )
);
gpin << Replace Text( "Nobody expects the Spanish Inquisition!" );
gpin << Revert Text;

Code Explanation:

1. Open data table.
2. Create graph builder object.
3. Hide control panel.
4. Set X and Y variables.
5. Add points and line of fit elements.
6. Access first frame box.
7. Add pin annotation to frame.
8. Replace hover label text.
9. Open data table again.
10. Create graph builder object.
11. Hide control panel.
12. Set X and Y variables.
13. Add points and line of fit elements.
14. Access first frame box.
15. Add pin annotation to frame.
16. Replace hover label text.
17. Revert hover label text.

Example 478

Summary: Creates and customizes a graph builder object with nested factors, displaying points and line of fit elements, and adding pin annotations with replaceable text.

Code:

dt = Open("data_table.jmp");
gb = dt << Graph Builder(
    Show Control Panel( 0 ),
    Variables( X( :height ), Y( :weight ) ),
    Elements( Points( X, Y, Legend( 4 ) ), Line Of Fit( X, Y, Legend( 6 ) ) )
);
frame = (gb << report)[FrameBox( 1 )];
gpin = frame << Add Pin Annotation(
    Seg( Marker Seg( 1 ) ),
    Index( 7 ),
    Index Row( 7 ),
    UniqueID( 691854391 ),
    FoundPt( {124, 311} ),
    Origin( {51.0074683737235, 80.0858968472606} ),
    Offset( {-4, -106} ),
    Tag Line( 1 )
);
gpin << Replace Text( "Replacing text of hover label with this message" );
dt = Open("data_table.jmp");
gb = dt << Graph Builder(
    Show Control Panel( 0 ),
    Variables( X( :height ), Y( :weight ) ),
    Elements( Points( X, Y, Legend( 4 ) ), Line Of Fit( X, Y, Legend( 6 ) ) )
);
frame = (gb << report)[FrameBox( 1 )];
gpin = frame << Add Pin Annotation(
    Seg( Marker Seg( 1 ) ),
    Index( 7 ),
    Index Row( 7 ),
    UniqueID( 691854391 ),
    FoundPt( {124, 311} ),
    Origin( {51.0074683737235, 80.0858968472606} ),
    Offset( {-4, -106} ),
    Tag Line( 1 )
);
gpin << Replace Text( "Nobody expects the Spanish Inquisition!" );

Code Explanation:

1. Open data table.
2. Create graph builder object.
3. Hide control panel.
4. Set X and Y variables.
5. Add points and line of fit elements.
6. Access first frame box.
7. Add pin annotation.
8. Replace text of hover label.
9. Reopen data table.
10. Repeat steps 2-8 with new text.

Example 479

Summary: Creates a variability chart with nested factors using Graph Builder, featuring bar elements and local data filtering.

Code:

Open("data_table.jmp") << Graph Builder(
    Size( 455, 411 ),
    Show Control Panel( 0 ),
    Variables( X( :Causality ), Overlay( :Sex ) ),
    Elements( Bar( X, Legend( 6 ), Label( "Label by Value" ) ) ),
    Local Data Filter( Mode( Include( 0 ) ), Add Filter( columns( :Age Group 1 ) ) ),
    SendToReport(
        Dispatch( {}, "Graph Builder", FrameBox,
            {Add Pin Annotation(
                Seg( BarSeg( 1 ) ),
                Index( {0, 0} ),
                Index Row( {0, 0} ),
                UniqueID( 0 ),
                FoundPt( {309, 152} ),
                Origin( {-0.148241206030151, 2293.84964985163} ),
                RightOfCenter( 0 ),
                Tag Line( 1 )
            ), Add Pin Annotation(
                Seg( BarSeg( 1 ) ),
                Index( {2, 2} ),
                Index Row( {1106, 1106} ),
                UniqueID( 2 ),
                FoundPt( {402, 359} ),
                Origin( {0.78643216080402, 298.778735905045} ),
                Offset( {-2, -88} ),
                RightOfCenter( 0 ),
                Tag Line( 1 )
            )}
        )
    )
);

Code Explanation:

1. Open data table.
2. Create Graph Builder window.
3. Set graph size.
4. Hide control panel.
5. Define X variable.
6. Define overlay variable.
7. Add bar element.
8. Label bars by value.
9. Add local data filter.
10. Add pin annotations.

Example 480

Summary: Creates a variability chart with nested factors using operator and part configurations, displaying standard deviation charts in Graph Builder.

Code:

dt = Open("data_table.jmp");
Graph Builder(
    Size( 604, 504 ),
    Show Control Panel( 0 ),
    Variables( X( :height ), Y( :weight ), Overlay( :sex ) ),
    Elements( Smoother( X, Y, Legend( 2 ) ) ),
    SendToReport(
        Dispatch( {}, "Graph Builder", FrameBox,
            {Add Pin Annotation(
                Seg( Line Seg( 1 ) ),
                Index( {2147483647, 21} ),
                Index Row( {2147483647, 21} ),
                UniqueID( -1528334181 ),
                FoundPt( {469, 218} ),
                Origin( {65.0322784810127, 127.5} ),
                RightOfCenter( 1 ),
                Tag Line( 1 )
            ), Add Pin Annotation(
                Seg( Line Seg( 2 ) ),
                Index( {2147483647, 18} ),
                Index Row( {2147483647, 18} ),
                UniqueID( -1528327243 ),
                FoundPt( {500, 271} ),
                Origin( {66.1800632911392, 110.636363636364} ),
                RightOfCenter( 1 ),
                Tag Line( 1 )
            )}
        )
    )
);

Code Explanation:

1. Open data table;
2. Create Graph Builder window.
3. Set graph size to 604x504.
4. Hide control panel.
5. Set X variable to height.
6. Set Y variable to weight.
7. Use sex for overlay.
8. Add smoother element.
9. Add first pin annotation.
10. Add second pin annotation.

Example 481

Summary: Creates a variability chart with nested factors using Graph Builder, adding a pin annotation and redoing analysis on a specified data table.

Code:

dt = Open("data_table.jmp");
gb = dt << Graph Builder(
    Size( 534, 456 ),
    Show Control Panel( 0 ),
    Variables( X( :height ), Y( :weight ), Overlay( :age ) ),
    Elements( Smoother( X, Y, Legend( 6 ) ) )
);
frame = (gb << report)[FrameBox( 1 )];
gpin = frame << Add Pin Annotation(
    Seg( Line Seg( 1 ) ),
    Index( {0, -1} ),
    Index Row( {0, -1} ),
    UniqueID( -564321536 ),
    FoundPt( {369, 190} ),
    Origin( {62.7991879171328, 131.071428571429} ),
    RightOfCenter( 1 ),
    Tag Line( 1 )
);
gbb = gb << redo analysis;

Code Explanation:

1. Open data table.
2. Create Graph Builder object.
3. Set graph size.
4. Hide control panel.
5. Define variables: X, Y, Overlay.
6. Add smoother element.
7. Access first frame box.
8. Add pin annotation.
9. Redo analysis.

Example 482

Summary: Creates a variability chart with nested factors using Graph Builder, adding a pin annotation and redoing analysis.

Code:

dt = Open("data_table.jmp");
gb = dt << Graph Builder(
    Size( 534, 456 ),
    Show Control Panel( 0 ),
    Variables( X( :height ), Y( :weight ), Overlay( :age ) ),
    Elements( Smoother( X, Y, Legend( 6 ) ) )
);
frame = (gb << report)[FrameBox( 1 )];
gpin = frame << Add Pin Annotation(
    Seg( Line Seg( 1 ) ),
    Index( {0, -1} ),
    Index Row( {0, -1} ),
    UniqueID( -564321536 ),
    FoundPt( {369, 190} ),
    Origin( {62.7991879171328, 131.071428571429} ),
    RightOfCenter( 1 ),
    Tag Line( 1 )
);
gbb = gb << redo analysis;
gb << close window;

Code Explanation:

1. Open data table.
2. Create Graph Builder object.
3. Set graph size.
4. Hide control panel.
5. Define X, Y, and overlay variables.
6. Add smoother element.
7. Access first frame box.
8. Add pin annotation.
9. Redo analysis.
10. Close graph window.

Example 483

Summary: Creates a bar chart to display the percentage of total by sex, utilizing Graph Builder and pin annotations for customization.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 534, 450 ),
    Show Control Panel( 0 ),
    Variables( X( :sex ) ),
    Elements( Bar( X, Legend( 5 ), Summary Statistic( "% of Total" ), Label( "Label by Value" ) ) ),
    SendToReport(
        Dispatch( {}, "graph title", TextEditBox, {Set Text( "% of Total" )} ),
        Dispatch( {}, "Graph Builder", FrameBox,
            {Add Pin Annotation(
                Seg( BarSeg( 1 ) ),
                Index( {0, 0} ),
                Index Row( {0, 0} ),
                UniqueID( 0 ),
                FoundPt( {425, 336} ),
                Origin( {-0.1125, 0.275510204081633} ),
                RightOfCenter( 0 ),
                Tag Line( 1 )
            ), Add Pin Annotation(
                Seg( BarSeg( 1 ) ),
                Index( {1, 1} ),
                Index Row( {13, 13} ),
                UniqueID( 1 ),
                FoundPt( {730, 263} ),
                Origin( {1.15833333333333, 0.387244897959184} ),
                RightOfCenter( 1 ),
                Tag Line( 1 )
            )}
        )
    )
);

Code Explanation:

1. Open data table;
2. Create Graph Builder window.
3. Set graph size.
4. Hide control panel.
5. Set X variable to sex.
6. Add bar element.
7. Use summary statistic "% of Total".
8. Label bars by value.
9. Set graph title.
10. Add pin annotations to bars.

Example 484

Summary: Creates a heatmap to visualize the relationship between height and weight, with color-coded by summary statistic (Sum) using Graph Builder.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 474, 299 ),
    Show Control Panel( 0 ),
    Variables( X( :height ), Y( :weight ), Color( :weight, Summary Statistic( "Sum" ) ) ),
    Elements( Heatmap( X, Y, Legend( 9 ) ) ),
    SendToReport(
        Dispatch( {}, "Graph Builder", FrameBox,
            {Add Pin Annotation(
                Seg( RectSeg( 1 ) ),
                Index( 3 ),
                Index Row( 0 ),
                UniqueID( 877180451 ),
                FoundPt( {486, 302} ),
                Origin( {58.4574468085106, 88.5957446808511} ),
                RightOfCenter( 0 ),
                Tag Line( 1 )
            ), Add Pin Annotation(
                Seg( RectSeg( 1 ) ),
                Index( 15 ),
                Index Row( 39 ),
                UniqueID( 877180463 ),
                FoundPt( {732, 147} ),
                Origin( {71.5425531914894, 167.744680851064} ),
                Offset( {-192, 18} ),
                RightOfCenter( 1 ),
                Tag Line( 1 )
            )}
        )
    )
);

Code Explanation:

1. Open data table;
2. Launch Graph Builder.
3. Set window size.
4. Hide control panel.
5. Assign variables: X, Y, Color.
6. Create heatmap element.
7. Send report to Graph Builder.
8. Add first pin annotation.
9. Add second pin annotation.
10. Finalize report display.

Example 485

Summary: Creates a treemap visualization to display cumulative sum by age, utilizing Graph Builder and SendToReport features.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 596, 368 ),
    Show Control Panel( 0 ),
    Show Legend( 0 ),
    Show Footer( 0 ),
    Variables( X( :age ), Y( :height ), Color( :age, Summary Statistic( "Cumulative Sum" ) ) ),
    Elements( Treemap( X, Y, Legend( 10 ), Color Value( 1 ) ) ),
    SendToReport(
        Dispatch( {}, "Graph Builder", FrameBox,
            {Add Pin Annotation(
                Seg( TreeMapSeg( 1 ) ),
                Index( 1 ),
                Index Row( 8 ),
                UniqueID( 1 ),
                FoundPt( {177, 288} ),
                Origin( {135.284991273997, 84.54671875} ),
                RightOfCenter( 0 ),
                Tag Line( 1 ),
                Text Color( {224, 224, 224} ),
                Background Color( {44, 44, 44} )
            ), Add Pin Annotation(
                Seg( TreeMapSeg( 1 ) ),
                Index( 2 ),
                Index Row( 15 ),
                UniqueID( 2 ),
                FoundPt( {262, 117} ),
                Origin( {221.594109947644, 260.262578125} ),
                RightOfCenter( 0 ),
                Tag Line( 1 ),
                Text Color( {224, 224, 224} ),
                Background Color( {44, 44, 44} )
            )}
        )
    )
);

Code Explanation:

1. Open data table;
2. Create Graph Builder window.
3. Set window size.
4. Hide control panel.
5. Hide legend.
6. Hide footer.
7. Define X, Y, and color variables.
8. Add treemap element.
9. Send report to dispatch.
10. Add pin annotations.

Example 486

Summary: Creates a Treemap visualization with nested factors using Graph Builder, hiding the control panel and specifying X variable as age.

Code:

dt = Open("data_table.jmp");
gb = dt << Graph Builder(
    Show Control Panel( 0 ),
    Variables( X( :age ) ),
    Elements( Treemap( X, Legend( 3 ) ) ),
    SendToReport(
        Dispatch( {}, "Graph Builder", FrameBox,
            Add Pin Annotation(
                Seg( TreeMapSeg( 1 ) ),
                Index( 4 ),
                Index Row( 34 ),
                UniqueID( 4 ),
                FoundPt( {748, 386} ),
                Origin( {425.869524793388, 129.066390306122} ),
                RightOfCenter( 1 ),
                Tag Line( 1 )
            )
        )
    )
);

Code Explanation:

1. Open data table.
2. Create Graph Builder object.
3. Hide control panel.
4. Set X variable to age.
5. Add Treemap element.
6. Send report message.
7. Dispatch to Graph Builder.
8. Add pin annotation.
9. Specify segment.
10. Set annotation properties.

Example 487

Summary: Creates a treemap visualization with nested factors using Graph Builder, hiding control panel and adding pin annotation.

Code:

dt = Open("data_table.jmp");
gb = dt << Graph Builder(
    Show Control Panel( 0 ),
    Variables( X( :age ) ),
    Elements( Treemap( X, Legend( 3 ) ) ),
    SendToReport(
        Dispatch( {}, "Graph Builder", FrameBox,
            Add Pin Annotation(
                Seg( TreeMapSeg( 1 ) ),
                Index( 4 ),
                Index Row( 34 ),
                UniqueID( 4 ),
                FoundPt( {748, 386} ),
                Origin( {425.869524793388, 129.066390306122} ),
                RightOfCenter( 1 ),
                Tag Line( 1 )
            )
        )
    )
);
Data Table("data_table") << Clear Select << Select Rows( Index( 1, 15 ) ) << Hide and Exclude;

Code Explanation:

1. Open data table;
2. Create Graph Builder.
3. Set X variable to :age.
4. Add Treemap element.
5. Hide control panel.
6. Add pin annotation.
7. Specify segment and index.
8. Set found point coordinates.
9. Set origin coordinates.
10. Hide and exclude rows 1 to 15.

Example 488

Summary: Creates a treemap visualization in Graph Builder, using height and weight variables with sex as an overlay, to display data from a nested factors configuration.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 665, 338 ),
    Show Control Panel( 0 ),
    Fit to Window,
    Variables( X( :height ), Y( :weight ), Overlay( :sex ) ),
    Elements( Treemap( X, Y, Legend( 14 ), Category Value( 0 ) ) ),
    SendToReport(
        Dispatch( {}, "Graph Builder", FrameBox,
            {Add Pin Annotation(
                Seg( TreeMapSeg( 1 ) ),
                Index( 0 ),
                Index Row( 7 ),
                UniqueID( -1188009808 ),
                FoundPt( {42, 110} ),
                Origin( {3.27122274143302, 240.282672413793} ),
                RightOfCenter( 0 ),
                Tag Line( 1 )
            ), Add Pin Annotation(
                Seg( TreeMapSeg( 1 ) ),
                Index( 12 ),
                Index Row( 3 ),
                UniqueID( -1188009796 ),
                FoundPt( {470, 212} ),
                Origin( {437.154556074766, 133.420086206897} ),
                RightOfCenter( 1 ),
                Tag Line( 1 )
            )}
        )
    )
);

Code Explanation:

1. Open data_table data
2. Launch Graph Builder.
3. Set window size.
4. Hide control panel.
5. Fit to window.
6. Set X variable to height.
7. Set Y variable to weight.
8. Use sex for overlay.
9. Create treemap element.
10. Add pin annotations.

Example 489

Summary: Creates a variability chart with nested factors using operator and part configurations, displaying standard deviation charts in Graph Builder.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 534, 456 ),
    Show Control Panel( 0 ),
    Variables( X( :height ), Y( :weight ), Overlay( :sex ) ),
    Elements( Points( X, Y, Legend( 12 ) ), Smoother( X, Y, Legend( 13 ) ) ),
    SendToReport(
        Dispatch( {}, "Graph Builder", FrameBox,
            Add Pin Annotation(
                Seg( Marker Seg( 2 ) ),
                Index( 12 ),
                Index Row( 25 ),
                UniqueID( 418238668 ),
                FoundPt( {387, 281} ),
                Origin( {63.9259627329193, 98.5714285714286} ),
                Tag Line( 1 )
            )
        )
    )
);

Code Explanation:

1. Open data table.
2. Launch Graph Builder.
3. Set graph size.
4. Hide control panel.
5. Define X and Y variables.
6. Overlay by sex.
7. Add points element.
8. Add smoother element.
9. Send report to Graph Builder.
10. Add pin annotation to graph.

Example 490

Summary: Creates a variability chart with nested factors using Graph Builder, displaying standard deviation charts and adding pin annotations.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 534, 492 ),
    Show Control Panel( 0 ),
    Variables( X( :height ), Y( :weight ), Group X( :sex ) ),
    Elements( Points( X, Y, Legend( 4 ) ), Smoother( X, Y, Legend( 5 ) ) ),
    SendToReport(
        Dispatch( {}, "Graph Builder", FrameBox( 2 ),
            Add Pin Annotation(
                Seg( Marker Seg( 1 ) ),
                Index( 12 ),
                Index Row( 25 ),
                UniqueID( 458085660 ),
                FoundPt( {734, 349} ),
                Origin( {64.2132780082988, 99.2857142857143} ),
                Tag Line( 1 )
            )
        )
    )
);

Code Explanation:

1. Open data table;
2. Launch Graph Builder.
3. Set window size.
4. Hide control panel.
5. Assign variables: height, weight, sex.
6. Add points and smoother elements.
7. Send report to Graph Builder.
8. Dispatch to frame box 2.
9. Add pin annotation.
10. Specify segment, index, row, unique ID, found point, origin, and tag line.

Example 491

Summary: Creates a variability chart with nested factors using Graph Builder, assigning variables for X and Y axes, adding points and smoother elements, and displaying standard deviation charts.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 534, 456 ),
    Show Control Panel( 0 ),
    Variables( X( :height ), Y( :weight ) ),
    Elements( Points( X, Y, Legend( 10 ) ), Smoother( X, Y, Legend( 11 ) ) ),
    Local Data Filter( Add Filter( columns( :sex ), Where( :sex == "M" ) ) ),
    SendToReport(
        Dispatch( {}, "Graph Builder", FrameBox,
            Add Pin Annotation(
                Seg( Marker Seg( 1 ) ),
                Index( 12 ),
                Index Row( 25 ),
                UniqueID( 458344380 ),
                FoundPt( {594, 320} ),
                Origin( {64.0119254658385, 98.265306122449} ),
                Tag Line( 1 )
            )
        )
    )
);

Code Explanation:

1. Open data table.
2. Create Graph Builder window.
3. Set window size.
4. Hide control panel.
5. Assign variables for X and Y axes.
6. Add points and smoother elements.
7. Add local data filter for sex.
8. Send report to Graph Builder.
9. Add pin annotation to graph.
10. Configure pin annotation properties.

Example 492

Summary: Creates a graph with nested factors using Graph Builder, hiding the control panel and adding line and bar elements. The script also customizes the graph title, adds a pin annotation to the second frame, and removes the legend title.

Code:

dt = Open("data_table.jmp");
gb = Graph Builder(
    Show Control Panel( 0 ),
    Variables( X( :age ), Y( :height ), Y( :weight ) ),
    Elements( Position( 1, 1 ), Line( X, Y, Legend( 1 ) ) ),
    Elements( Position( 1, 2 ), Bar( X, Y, Legend( 2 ) ) ),
    SendToReport(
        Dispatch( {}, "graph title", TextEditBox, {Set Text( "Hover label frame should be black" )} ),
        Dispatch( {}, "Graph Builder", FrameBox( 2 ),
            Add Pin Annotation(
                Seg( BarSeg( 1 ) ),
                Index( {1, 1} ),
                Index Row( {8, 8} ),
                UniqueID( -9998047 ),
                FoundPt( {197, 387} ),
                Origin( {0.997076023391813, 74.7613891472868} ),
                Offset( {-36, -133} ),
                Tag Line( 1 ),
                Frame Color( "Black" )
            )
        ),
        Dispatch( {}, "400", LegendBox, {Set Title( "" )} )
    )
);
gb << save journal( "$temp\test.jrn" );
dt << close window( no save );

Code Explanation:

1. Open data table.
2. Create Graph Builder object.
3. Hide control panel.
4. Set X and Y variables.
5. Add line element to graph.
6. Add bar element to graph.
7. Set graph title.
8. Add pin annotation to second frame.
9. Customize pin annotation color.
10. Remove legend title.
11. Save graph as journal.
12. Close data table without saving.

Example 493

Summary: Creates a variability chart with nested factors using Graph Builder, adding a line element and bar element to visualize data, and displaying standard deviation charts.

Code:

dt = Open("data_table.jmp");
gb = Graph Builder(
    Show Control Panel( 0 ),
    Variables( X( :age ), Y( :height ), Y( :weight ) ),
    Elements( Position( 1, 1 ), Line( X, Y, Legend( 1 ) ) ),
    Elements( Position( 1, 2 ), Bar( X, Y, Legend( 2 ) ) ),
    SendToReport(
        Dispatch( {}, "graph title", TextEditBox, {Set Text( "Hover label frame should be black" )} ),
        Dispatch( {}, "Graph Builder", FrameBox( 2 ),
            Add Pin Annotation(
                Seg( BarSeg( 1 ) ),
                Index( {1, 1} ),
                Index Row( {8, 8} ),
                UniqueID( -9998047 ),
                FoundPt( {197, 387} ),
                Origin( {0.997076023391813, 74.7613891472868} ),
                Offset( {-36, -133} ),
                Tag Line( 1 ),
                Frame Color( "Black" )
            )
        ),
        Dispatch( {}, "400", LegendBox, {Set Title( "" )} )
    )
);
gb << save journal( "$temp\test.jrn" );
dt << close window( no save );
Open( "$temp\test.jrn" );

Code Explanation:

1. Open data table.
2. Create Graph Builder object.
3. Hide control panel.
4. Set X and Y variables.
5. Add line element.
6. Add bar element.
7. Set graph title.
8. Add pin annotation with black frame.
9. Remove legend title.
10. Save journal to temp directory.
11. Close data table without saving.
12. Open saved journal.

Example 494

Summary: Creates a graph builder object with nested factors, displaying standard deviation charts and adding interactive elements such as textlets and pin annotations.

Code:

Open("data_table.jmp");
gb = Graph Builder(
    Variables( X( :height ), Y( :weight ) ),
    Elements( Points( X, Y, Legend( 2 ) ), Smoother( X, Y, Legend( 3 ) ) ),
    SendToReport(
        Dispatch( {}, "Graph Builder", FrameBox,
            {Set Textlet(
                Setup( local:color = If( Mod( local:_firstRow, 2 ), "blue", "red" ) ),
                Markup( "<b>Violets</b> are <font color='{local:color}'>{local:color}</font>.
" )
            ), Add Pin Annotation(
                Seg( Marker Seg( 1 ) ),
                Index( 6 ),
                Index Row( 6 ),
                UniqueID( 6 ),
                FoundPt( {583, 274} ),
                Origin( {61.0032298136646, 128.056354387755} ),
                RightOfCenter( 1 ),
                Tag Line( 1 )
            )}
        )
    )
);
gb << journal();
Current Journal() << save journal( "$temp\test.jrn" );
Current Journal() << close window();

Code Explanation:

1. Open data table;
2. Create graph builder object.
3. Set X and Y variables.
4. Add points and smoother elements.
5. Send report commands.
6. Set textlet with conditional color.
7. Add markup with HTML formatting.
8. Add pin annotation at specific index.
9. Journal the graph builder.
10. Save journal to temporary location.
11. Close the current journal window.

Example 495

Summary: Creates a variability chart with nested factors using operator and part configurations, displaying standard deviation charts in JMP.

Code:

Open("data_table.jmp");
gb = Graph Builder(
    Variables( X( :height ), Y( :weight ) ),
    Elements( Points( X, Y, Legend( 2 ) ), Smoother( X, Y, Legend( 3 ) ) ),
    SendToReport(
        Dispatch( {}, "Graph Builder", FrameBox,
            {Set Textlet(
                Setup( local:color = If( Mod( local:_firstRow, 2 ), "blue", "red" ) ),
                Markup( "<b>Violets</b> are <font color='{local:color}'>{local:color}</font>.
" )
            ), Add Pin Annotation(
                Seg( Marker Seg( 1 ) ),
                Index( 6 ),
                Index Row( 6 ),
                UniqueID( 6 ),
                FoundPt( {583, 274} ),
                Origin( {61.0032298136646, 128.056354387755} ),
                RightOfCenter( 1 ),
                Tag Line( 1 )
            )}
        )
    )
);
gb << journal();
Current Journal() << save journal( "$temp\test.jrn" );
Current Journal() << close window();
Open( "$temp\test.jrn" );
gb << journal();

Code Explanation:

1. Open data table.
2. Create graph builder object.
3. Set X and Y variables.
4. Add points and smoother elements.
5. Configure hover labels.
6. Set textlet with conditional color.
7. Add markup with bold and colored text.
8. Add pin annotation at specific index.
9. Save journal to temporary file.
10. Reopen saved journal.

Example 496

Summary: Creates a graph builder object with nested factors, displaying standard deviation charts and adding interactive elements such as pin annotations.

Code:

Open("data_table.jmp");
gb = Graph Builder(
    Variables( X( :height ), Y( :weight ) ),
    Elements( Points( X, Y, Legend( 2 ) ), Smoother( X, Y, Legend( 3 ) ) ),
    SendToReport(
        Dispatch( {}, "Graph Builder", FrameBox,
            {Set Textlet(
                Setup( local:color = If( Mod( local:_firstRow, 2 ), "blue", "red" ) ),
                Markup( "<b>Violets</b> are <font color='{local:color}'>{local:color}</font>.
" )
            ), Add Pin Annotation(
                Seg( Marker Seg( 1 ) ),
                Index( 6 ),
                Index Row( 6 ),
                UniqueID( 6 ),
                FoundPt( {583, 274} ),
                Origin( {61.0032298136646, 128.056354387755} ),
                RightOfCenter( 1 ),
                Tag Line( 1 )
            )}
        )
    )
);
gb << journal();
Current Journal() << save journal( "$temp\test.jrn" );
Current Journal() << close window();
Open( "$temp\test.jrn" );

Code Explanation:

1. Open data table;
2. Create graph builder object.
3. Set X and Y variables.
4. Add points and smoother elements.
5. Send report commands.
6. Set textlet with conditional color.
7. Add markup with bold and colored text.
8. Add pin annotation at specific index.
9. Save journal to temp file.
10. Close current journal window.
11. Reopen saved journal file.

Example 497

Summary: Creates a graph builder window with nested factors using operator and part configurations, displaying standard deviation charts.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 529, 450 ),
    Show Control Panel( 0 ),
    Variables( X( :Shqip ), Wrap( :Euskera ) ),
    Elements( Points( X, Legend( 2 ) ) ),
    SendToReport(
        Dispatch( {}, "Graph Builder", FrameBox( 20 ),
            Add Pin Annotation(
                Seg( Marker Seg( 1 ) ),
                Index( 0 ),
                Index Row( 10 ),
                UniqueID( 1124040368 ),
                FoundPt( {158, 248} ),
                Origin( {21.5235294117647, 0.107142857142857} )
            )
        )
    )
);

Code Explanation:

1. Open data table;
2. Create graph builder window.
3. Set graph size.
4. Hide control panel.
5. Assign variables for X-axis.
6. Add points element to graph.
7. Send report to dispatch.
8. Add pin annotation to graph.
9. Specify segment marker.
10. Set annotation index and row.

Example 498

Summary: Creates a graph builder with nested factors using operator and part configurations, displaying standard deviation charts.

Code:

Open("data_table.jmp");
Graph Builder(
    Variables( X( :age ), Y( :height ), Overlay( :sex ) ),
    Show Control Panel( 0 ),
    Elements( Line( X, Y, Legend( 5 ) ) ),
    SendToReport(
        Dispatch( {}, "graph title", TextEditBox, {Set Text( "Annotation Should Point To Vertex on Red Line" )} ),
        Dispatch( {}, "Graph Builder", FrameBox,
            Add Pin Annotation(
                Seg( Line Seg( 2 ) ),
                Index( {3, 3} ),
                Index Row( {29, 29} ),
                UniqueID( -225829977 ),
                FoundPt( {610, 232} ),
                Origin( {3.02066115702479, 65.1339285714286} ),
                RightOfCenter( 1 ),
                Tag Line( 1 )
            )
        )
    )
);

Code Explanation:

1. Open data table.
2. Create Graph Builder.
3. Set X variable to age.
4. Set Y variable to height.
5. Use sex for overlay.
6. Hide control panel.
7. Add line element.
8. Set graph title.
9. Add pin annotation.
10. Configure annotation properties.

Example 499

Summary: Creates a graph builder with nested factors using operator and part configurations, displaying standard deviation charts.

Code:

Open("data_table.jmp");
Graph Builder(
    Variables( X( :age ), Y( :height ), Overlay( :sex ) ),
    Show Control Panel( 0 ),
    Elements( Line( X, Y, Legend( 5 ) ) ),
    SendToReport(
        Dispatch( {}, "graph title", TextEditBox, {Set Text( "Annotation Should Point To Vertex on Red Line" )} ),
        Dispatch( {}, "Graph Builder", FrameBox,
            Add Pin Annotation(
                Seg( Line Seg( 2 ) ),
                Index( {3, 3} ),
                Index Row( {29, 29} ),
                UniqueID( -225829977 ),
                FoundPt( {610, 232} ),
                Origin( {3.02066115702479, 65.1339285714286} ),
                RightOfCenter( 1 ),
                Tag Line( 1 )
            )
        )
    )
);
Data Table("data_table") << Clear Select << Select Rows( Index( 1, 8 ) ) << Hide and Exclude;

Code Explanation:

1. Open data table;
2. Create Graph Builder object.
3. Set X and Y variables.
4. Enable overlay by sex.
5. Hide control panel.
6. Add line element to graph.
7. Set graph title text.
8. Add pin annotation to graph.
9. Specify annotation segment and index.
10. Select and hide specific rows.

Example 500

Summary: Creates two Graph Builder windows to visualize variability charts with nested factors, utilizing operator and part configurations, and displaying standard deviation charts.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 534, 492 ),
    Show Control Panel( 0 ),
    Variables( X( :height ), Y( :weight ), Group X( :sex ) ),
    Elements( Points( X, Y, Legend( 4 ) ), Smoother( X, Y, Legend( 5 ) ) ),
    SendToReport(
        Dispatch( {}, "Graph Builder", FrameBox( 2 ),
            Add Pin Annotation(
                Seg( Marker Seg( 1 ) ),
                Index( 12 ),
                Index Row( 25 ),
                UniqueID( 458085660 ),
                FoundPt( {734, 349} ),
                Origin( {64.2132780082988, 99.2857142857143} ),
                Tag Line( 1 )
            )
        )
    )
);
Graph Builder(
    Size( 534, 956 ),
    Show Control Panel( 0 ),
    Variables( X( :height ), Y( :weight ), Page( :sex ) ),
    Elements( Points( X, Y, Legend( 4 ) ), Smoother( X, Y, Legend( 5 ) ) ),
    SendToReport(
        Dispatch( {}, "Graph Builder", FrameBox( 2 ),
            Add Pin Annotation(
                Seg( Marker Seg( 1 ) ),
                Index( 12 ),
                Index Row( 25 ),
                UniqueID( 1317707340 ),
                FoundPt( {654, 768} ),
                Origin( {64.0549068322982, 98.0487804878049} ),
                RightOfCenter( 1 ),
                Tag Line( 1 )
            )
        )
    )
);

Code Explanation:

1. Open data table;
2. Create Graph Builder window.
3. Set graph size.
4. Hide control panel.
5. Assign variables: height, weight, sex.
6. Add points and smoother elements.
7. Add pin annotation at specific coordinates.
8. Create another Graph Builder window.
9. Set different graph size.
10. Assign variables: height, weight, sex page.

Example 501

Summary: Creates a variability chart with nested factors using operator and part configurations, displaying standard deviation charts in Graph Builder.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 534, 456 ),
    Show Control Panel( 0 ),
    Variables( X( :height ), Y( :weight ), Color( :age ) ),
    Elements( Points( X, Y, Legend( 10 ) ), Smoother( X, Y, Legend( 11 ) ) ),
    Local Data Filter( Add Filter( columns( :sex ), Where( :sex == "M" ) ) ),
    SendToReport(
        Dispatch( {}, "Graph Builder", FrameBox,
            Add Pin Annotation(
                Seg( Marker Seg( 1 ) ),
                Index( 12 ),
                Index Row( 25 ),
                UniqueID( 458344380 ),
                FoundPt( {594, 320} ),
                Origin( {64.0119254658385, 98.265306122449} ),
                RightOfCenter( 0 ),
                Tag Line( 1 )
            )
        )
    )
);

Code Explanation:

1. Open data table;
2. Launch Graph Builder.
3. Set window size.
4. Hide control panel.
5. Assign variables: X=height, Y=weight, Color=age.
6. Add points and smoother elements.
7. Apply local data filter for males.
8. Send report to Graph Builder.
9. Add pin annotation to graph.
10. Position annotation on specific point.

Example 502

Summary: Creates a variability chart with nested factors using Graph Builder, displaying standard deviation charts and configuring bar style to range.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 563, 482 ),
    Show Control Panel( 0 ),
    Variables(
        Y( :Sepal length ),
        Y( :Sepal width, Position( 1 ) ),
        Y( :Petal length, Position( 1 ) ),
        Y( :Petal width, Position( 1 ) ),
        Color( :Species )
    ),
    Elements(
        Bar(
            Y( 1 ),
            Y( 2 ),
            Y( 3 ),
            Y( 4 ),
            Legend( 3 ),
            Bar Style( "Range" ),
            Summary Statistic( "% of Total" ),
            Label( "Label by Percent of Total Values" )
        )
    ),
    SendToReport(
        Dispatch( {}, "Graph Builder", FrameBox,
            Add Pin Annotation(
                Seg( BarSeg( 1 ) ),
                Index( {0, 3} ),
                Index Row( 0 ),
                UniqueID( 646792512 ),
                FoundPt( {587, 351} ),
                Origin( {0.00877192982456143, 1} ),
                Offset( {-135, -107} ),
                Tag Line
            )
        )
    )
);

Code Explanation:

1. Open data table;
2. Launch Graph Builder.
3. Set window size.
4. Hide control panel.
5. Define Y variables.
6. Define X variable.
7. Define color variable.
8. Create bar element.
9. Set bar style to range.
10. Display percent of total.

Example 503

Summary: Creates a variability chart with nested factors using operator and part configurations, displaying standard deviation charts in Graph Builder.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 716, 465 ),
    Show Control Panel( 0 ),
    Variables(
        Y( :Depth ),
        Y( :Table, Position( 1 ) ),
        Wrap( :Report ),
        Overlay( :Clarity ),
        Color( :Color ),
        Frequency( :Color ),
        Interval( :Cut )
    ),
    Elements( Bar( Y( 1 ), Y( 2 ), Legend( 7 ), Bar Style( "Range" ), Summary Statistic( "Range" ), Label( "Label by Value" ) ) ),
    SendToReport(
        Dispatch( {}, "Graph Builder", FrameBox,
            Add Pin Annotation(
                Seg( BarSeg( 1 ) ),
                Index( {0, 0} ),
                Index Row( {1574, 1574} ),
                UniqueID( 645724752 ),
                FoundPt( {89, 315} ),
                Origin( {-0.401785714285714, 6.29675810473816} ),
                Offset( {5, -94} ),
                Tag Line
            )
        ),
        Dispatch( {}, "Graph Builder", FrameBox( 2 ),
            Add Pin Annotation(
                Seg( BarSeg( 1 ) ),
                Index( {1, 2} ),
                Index Row( {3, 1} ),
                UniqueID( 645718833 ),
                FoundPt( {460, 309} ),
                Origin( {-0.3, 6.47630922693267} ),
                Offset( {-22, 110} ),
                Tag Line
            )
        )
    )
);

Code Explanation:

1. Open data table;
2. Launch Graph Builder.
3. Set graph size.
4. Hide control panel.
5. Define Y variables.
6. Set wrap variable.
7. Set overlay variable.
8. Set color variable.
9. Set frequency variable.
10. Set interval variable.
11. Add bar element.
12. Configure bar style.
13. Set summary statistic.
14. Enable label by value.
15. Add pin annotation to first frame.
16. Add pin annotation to second frame.

Example 504

Summary: Creates a variability chart with nested factors using operator and part configurations, displaying standard deviation charts in Graph Builder.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 560, 482 ),
    Show Control Panel( 0 ),
    Variables(
        Y( :Sepal length ),
        Y( :Sepal width, Position( 1 ) ),
        Y( :Petal length, Position( 1 ) ),
        Y( :Petal width, Position( 1 ) ),
        Color( :Species )
    ),
    Elements(
        Bar(
            Y( 1 ),
            Y( 2 ),
            Y( 3 ),
            Y( 4 ),
            Legend( 3 ),
            Bar Style( "Range" ),
            Summary Statistic( "Range" ),
            Label( "Label by Percent of Total Values" )
        )
    ),
    SendToReport(
        Dispatch( {}, "Graph Builder", FrameBox,
            Add Pin Annotation(
                Seg( BarSeg( 1 ) ),
                Index( {0, 0} ),
                Index Row( {0, 0} ),
                UniqueID( 626176720 ),
                FoundPt( {363, 311} ),
                Origin( {0.128099173553719, 3.36734693877551} ),
                Offset( {-90, -106} ),
                Tag Line
            )
        )
    )
);

Code Explanation:

1. Open data table;
2. Create Graph Builder window.
3. Set graph size to 560x482.
4. Hide control panel.
5. Define Y variables: Sepal length, Sepal width, Petal length, Petal width.
6. Define color variable: Species.
7. Add bar element for Y variables.
8. Set bar style to "Range".
9. Use summary statistic "Range".
10. Label bars by percent of total values.

Example 505

Summary: Creates a variability chart with nested factors using operator and part configurations, displaying standard deviation charts in Graph Builder.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 484, 460 ),
    Show Control Panel( 0 ),
    Variables( Y( :Speed ), Y( :Speed2, Position( 1 ) ), Overlay( :Position2 ) ),
    Elements( Bar( Y( 1 ), Y( 2 ), Legend( 5 ), Bar Style( "Range" ), Summary Statistic( "Sum" ), Label( "Label by Value" ) ) ),
    SendToReport(
        Dispatch( {}, "Graph Builder", FrameBox,
            Add Pin Annotation(
                Seg( BarSeg( 1 ) ),
                Index( {2, 4} ),
                Index Row( {49, 0} ),
                UniqueID( 626323778 ),
                FoundPt( {227, 132} ),
                Origin( {-0.129976580796253, 1794.93087557604} )
            )
        )
    )
);

Code Explanation:

1. Open data_table data
2. Create Graph Builder.
3. Set size to 484x460.
4. Hide control panel.
5. Define Y variables: Speed, Speed2.
6. Overlay by Position2.
7. Add bar element with range style.
8. Summarize statistics by sum.
9. Label bars by value.
10. Add pin annotation to graph.

Example 506

Summary: Creates a variability chart with nested factors using operator and part configurations, displaying standard deviation charts in Graph Builder.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 650, 597 ),
    Show Control Panel( 0 ),
    Variables(
        Y( :Speed ),
        Y( :Speed2, Position( 1 ) ),
        Y( Transform Column( "Square Root[Speed2]", Formula( Sqrt( :Speed2 ) ) ), Position( 1 ) ),
        Y( :Weight, Position( 1 ) ),
        Overlay( :Position2 )
    ),
    Elements(
        Bar( Y( 1 ), Y( 2 ), Y( 3 ), Y( 4 ), Legend( 5 ), Bar Style( "Range" ), Summary Statistic( "Sum" ), Label( "Label by Value" ) )
    ),
    SendToReport(
        Dispatch( {}, "Graph Builder", FrameBox,
            {Add Pin Annotation(
                Seg( BarSeg( 1 ) ),
                Index( {0, 3} ),
                Index Row( {104, 84} ),
                UniqueID( 626323776 ),
                FoundPt( {131, 399} ),
                Origin( {-0.403061224489796, 2940.45534150613} )
            ), Add Pin Annotation(
                Seg( BarSeg( 1 ) ),
                Index( {2, 8} ),
                Index Row( 49 ),
                UniqueID( 626323778 ),
                FoundPt( {292, 477} ),
                Origin( {-0.129251700680272, 1574.43082311734} )
            ), Add Pin Annotation(
                Seg( BarSeg( 1 ) ),
                Index( {5, 22} ),
                Index Row( 23 ),
                UniqueID( 626323781 ),
                FoundPt( {546, 566} ),
                Origin( {0.302721088435374, 15.7618213660245} )
            )}
        )
    )
);

Code Explanation:

1. Open data_table data
2. Create Graph Builder window.
3. Set graph size.
4. Hide control panel.
5. Define four Y variables.
6. Transform Speed2 for square root.
7. Overlay by Position2.
8. Add range bar element.
9. Summarize statistics as sum.
10. Label bars by value.

Example 507

Summary: Creates a variability chart with nested factors using operator and part configurations, displaying standard deviation charts in Graph Builder.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 541, 444 ),
    Show Control Panel( 0 ),
    Variables( X( :Position2 ), Y( :Speed ), Y( :Speed2, Position( 1 ) ) ),
    Elements( Bar( X, Y( 1 ), Y( 2 ), Legend( 5 ), Bar Style( "Range" ), Summary Statistic( "Sum" ), Label( "Label by Value" ) ) ),
    SendToReport(
        Dispatch( {}, "Graph Builder", FrameBox,
            Add Pin Annotation(
                Seg( BarSeg( 1 ) ),
                Index( {2, 4} ),
                Index Row( {49, 0} ),
                UniqueID( 626323778 ),
                FoundPt( {242, 134} ),
                Origin( {2.00206611570248, 1728.09278350515} )
            )
        )
    )
);

Code Explanation:

1. Open data_table data
2. Launch Graph Builder.
3. Set graph size.
4. Hide control panel.
5. Assign variables: X=Position2, Y1=Speed, Y2=Speed2.
6. Create range bar chart.
7. Summarize data using sum.
8. Label bars by value.
9. Add pin annotation.
10. Specify annotation details.

Example 508

Summary: Creates a variability chart with nested factors using operator and part configurations, displaying standard deviation charts in Graph Builder.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 552, 455 ),
    Show Control Panel( 0 ),
    Variables( X( :Position2 ), Y( :Speed ), Y( :Speed2, Position( 1 ) ) ),
    Elements( Bar( X, Y( 1 ), Y( 2 ), Legend( 5 ), Bar Style( "Range" ), Summary Statistic( "Sum" ), Label( "Label by Value" ) ) ),
    SendToReport(
        Dispatch( {}, "Graph Builder", FrameBox,
            Add Pin Annotation(
                Seg( BarSeg( 1 ) ),
                Index( {4, 8} ),
                Index Row( 0 ),
                UniqueID( 623338548 ),
                FoundPt( {388, 232} ),
                Origin( {4.01111111111111, 1128.44611528822} )
            )
        )
    )
);

Code Explanation:

1. Open data table;
2. Create Graph Builder window.
3. Set window size.
4. Hide control panel.
5. Define X and Y variables.
6. Add bar element with range style.
7. Summarize data by sum.
8. Label bars by value.
9. Add pin annotation to graph.
10. Position pin annotation on specific bars.

Example 509

Summary: Creates a variability chart with nested factors using operator and part configurations, displaying standard deviation charts in Graph Builder.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 500, 501 ),
    Show Control Panel( 0 ),
    Variables(
        X( :Position2 ),
        Y( :Speed2 ),
        Y( :Speed, Position( 1 ) ),
        Y( Transform Column( "Square Root[Speed2]", Formula( Sqrt( :Speed2 ) ) ), Position( 1 ) ),
        Y( :Weight, Position( 1 ) )
    ),
    Elements(
        Bar( X, Y( 1 ), Y( 2 ), Y( 3 ), Y( 4 ), Legend( 6 ), Bar Style( "Range" ), Summary Statistic( "Sum" ), Label( "Label by Value" ) )
    ),
    SendToReport(
        Dispatch( {}, "Graph Builder", FrameBox,
            {Add Pin Annotation(
                Seg( BarSeg( 1 ) ),
                Index( {0, 0} ),
                Index Row( {104, 104} ),
                UniqueID( 529658976 ),
                FoundPt( {98, 420} ),
                Origin( {-0.116438356164384, 752.808988764045} )
            ), Add Pin Annotation(
                Seg( BarSeg( 1 ) ),
                Index( {4, 19} ),
                Index Row( 0 ),
                UniqueID( 529658980 ),
                FoundPt( {360, 272} ),
                Origin( {4.07077625570776, 4078.65168539326} )
            ), Add Pin Annotation(
                Seg( BarSeg( 1 ) ),
                Index( {5, 22} ),
                Index Row( 23 ),
                UniqueID( 529658981 ),
                FoundPt( {419, 454} ),
                Origin( {5.01369863013699, -11.2359550561798} )
            )}
        )
    )
);

Code Explanation:

1. Open data_table data
2. Launch Graph Builder.
3. Set graph size.
4. Hide control panel.
5. Define X variable.
6. Define first Y variable.
7. Define second Y variable.
8. Define third Y variable.
9. Define fourth Y variable.
10. Add range bar element.
11. Add pin annotations.

Example 510

Summary: Creates a variability chart with nested factors using Graph Builder, concatenating species and displaying standard deviation charts.

Code:

Open("data_table.jmp");
Graph Builder(
    Variables(
        X( Transform Column( "Concatenate[Species]", Character, Formula( Concat( :Species ) ) ) ),
        Y( :Petal length ),
        Y( :Petal width, Position( 1 ) ),
        Overlay( :Species )
    ),
    Elements( Bar( X, Y( 1 ), Y( 2 ), Legend( 6 ), Bar Style( "Range" ), Label( "Label by Value" ) ) )
);

Code Explanation:

1. Open data table;
2. Create new character column.
3. Set formula for concatenation.
4. Configure Graph Builder.
5. Add transformed X variable.
6. Add first Y variable.
7. Add second Y variable.
8. Set overlay by Species.
9. Add bar element.
10. Configure range bar style.

Example 511

Summary: Creates a variability chart with nested factors using Graph Builder, displaying standard deviation charts and adding pin annotations to the graph.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 505, 528 ),
    Show Control Panel( 0 ),
    Variables(
        X( Transform Column( "Concatenate[Species]", Character, Formula( Concat( :Species ) ) ) ),
        Y( :Petal length ),
        Y( :Petal width, Position( 1 ) ),
        Overlay( :Species )
    ),
    Elements( Bar( X, Y( 1 ), Y( 2 ), Legend( 6 ), Bar Style( "Range" ), Label( "Label by Value" ) ) ),
    SendToReport(
        Dispatch( {}, "Graph Builder", FrameBox,
            Add Pin Annotation(
                Seg( BarSeg( 1 ) ),
                Index( {0, 0} ),
                Index Row( {0, 0} ),
                UniqueID( 623338544 ),
                FoundPt( {85, 488} ),
                Origin( {-0.305194805194805, 0.470338983050847} )
            )
        )
    )
);

Code Explanation:

1. Open data table;
2. Create Graph Builder window.
3. Set window size.
4. Hide control panel.
5. Define X variable.
6. Define first Y variable.
7. Define second Y variable.
8. Set overlay variable.
9. Add bar element with range style.
10. Add pin annotation to graph.

Example 512

Summary: Creates a variability chart with nested factors using operator and part configurations, displaying standard deviation charts in JMP.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 528, 450 ),
    Show Control Panel( 0 ),
    Variables( X( :sex ), Y( :height ), Color( :sex ) ),
    Elements( Bar( X, Y, Legend( 4 ) ) ),
    SendToReport(
        Dispatch( {}, "Graph Builder", FrameBox,
            {Set Graphlet(
                Picture(
                    Try(
                        loader = If( Class Exists( "hllLoader" ),
                            New Object( "hllLoader" ),
                            Include( "$BUILTIN_SCRIPTS/hllib.jsl" )
                        );
                        loader:setDebug( 0 );
                        hlp = loader:lazyLoad( "hllPresets" );
                        hlp:launchMarker();
                    ,
                        Write(
                            "
Hover Label: Unable to launch Preset, please check that the Preset library is available at $BUILTIN_SCRIPTS/hllib.jsl"
                        );
                        Write( Eval Insert( "
Exception: ^exception_msg^" ) );
                        Empty();
                    )
                ),
                Title( "Marker Preset" ),
                Skip Filters( 1, {:sex} ),
                Reapply( 1 )
            ), Add Pin Annotation(
                Seg( BarSeg( 1 ) ),
                Index( {0, 0} ),
                Index Row( {0, 0} ),
                UniqueID( -1464632272 ),
                FoundPt( {432, 280} ),
                Origin( {-0.0619834710743802, 41.9642857142857} ),
                RightOfCenter( 0 ),
                Tag Line( 1 )
            )}
        )
    )
);

Code Explanation:

1. Open data table;
2. Create Graph Builder window.
3. Set window size.
4. Hide control panel.
5. Assign variables: sex (X), height (Y), color by sex.
6. Add bar element to graph.
7. Send report commands.
8. Set graphlet with picture.
9. Try loading hover label library.
10. Launch marker preset, handle exceptions.

Example 513

Summary: Creates a variability chart with nested factors using Graph Builder, displaying standard deviation charts and configuring graph size and control panel settings.

Code:

dt = Open("data_table.jmp");
gb = dt << Graph Builder(
    Size( 528, 450 ),
    Show Control Panel( 0 ),
    Variables( X( :age ), Y( :height ) ),
    Elements( Points( X, Y, Legend( 3 ) ) ),
    SendToReport(
        Dispatch( {}, "Graph Builder", FrameBox,
            {Set Graphlet(
                Picture(
                    Graph Builder(
                        Size( 507, 440 ),
                        Show Control Panel( 0 ),
                        Variables( X( :sex ), Y( :weight ) ),
                        Elements( Pie( X, Y, Legend( 2 ) ) ),
                        SendToReport( Dispatch( {}, "400", LegendBox, {Set Title( "" )} ) )
                    )
                ),
                Skip Filters( 1, {:height} )
            ), Add Pin Annotation(
                Seg( Marker Seg( 1 ) ),
                Index( 10 ),
                Index Row( 10 ),
                UniqueID( 563273098 ),
                FoundPt( {448, 375} ),
                Origin( {1.01239669421488, 55.8614285714286} ),
                RightOfCenter( 0 ),
                Tag Line( 1 )
            )}
        )
    )
);

Code Explanation:

1. Open data table.
2. Create Graph Builder object.
3. Set graph size.
4. Hide control panel.
5. Assign variables X and Y.
6. Add points element.
7. Send report to Graph Builder.
8. Set graphlet with nested Graph Builder.
9. Configure nested Graph Builder size.
10. Hide control panel in nested Graph Builder.

Example 514

Summary: Creates a variability chart with nested factors using Graph Builder, displaying standard deviation charts and adding pin annotations to smoother lines.

Code:

Open("data_table.jmp");
Graph Builder(
    Variables( X( :height ), Y( :weight ), Overlay( :sex ) ),
    Show Control Panel( 0 ),
    Elements( Points( X, Y, Legend( 14 ) ), Smoother( X, Y, Legend( 15 ) ) ),
    SendToReport(
        Dispatch( {}, "graph title", TextEditBox, {Set Text( "Annotation Should Point To Blue Line" )} ),
        Dispatch( {}, "Graph Builder", FrameBox,
            Add Pin Annotation(
                Seg( Line Seg( 1 ) ),
                Index( {0, -1} ),
                Index Row( {0, -1} ),
                UniqueID( -316254192 ),
                FoundPt( {610, 357} ),
                Origin( {62.1637267080745, 96.4285714285714} ),
                RightOfCenter( 1 ),
                Tag Line( 1 )
            )
        )
    )
);

Code Explanation:

1. Open data table;
2. Launch Graph Builder.
3. Set X variable to height.
4. Set Y variable to weight.
5. Overlay variable by sex.
6. Hide control panel.
7. Add points element.
8. Add smoother element.
9. Set graph title text.
10. Add pin annotation to smoother line.

Example 515

Summary: Creates a graph builder window with nested factors using operator and part configurations, displaying standard deviation charts.

Code:

Open("data_table.jmp");
Graph Builder(
    Variables( X( :height ), Y( :weight ), Overlay( :sex ) ),
    Show Control Panel( 0 ),
    Elements( Points( X, Y, Legend( 14 ) ), Smoother( X, Y, Legend( 15 ) ) ),
    SendToReport(
        Dispatch( {}, "graph title", TextEditBox, {Set Text( "Annotation Should Point To Blue Line" )} ),
        Dispatch( {}, "Graph Builder", FrameBox,
            Add Pin Annotation(
                Seg( Line Seg( 1 ) ),
                Index( {0, -1} ),
                Index Row( {0, -1} ),
                UniqueID( -316254192 ),
                FoundPt( {610, 357} ),
                Origin( {62.1637267080745, 96.4285714285714} ),
                RightOfCenter( 1 ),
                Tag Line( 1 )
            )
        )
    )
);
Data Table("data_table") << Clear Select << Select Rows( [16, 17, 19, 20, 28] ) << Hide and Exclude;

Code Explanation:

1. Open data table;
2. Create Graph Builder window.
3. Set X and Y variables.
4. Enable overlay by sex.
5. Hide control panel.
6. Add points element.
7. Add smoother element.
8. Set graph title.
9. Add pin annotation.
10. Hide selected rows.

Example 516

Summary: Creates a box plot element with nested factors using Graph Builder, displaying standard deviation charts and filtering data by specific age ranges.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 569, 339 ),
    Show Control Panel( 0 ),
    Show Footer( 0 ),
    Variables( X( :age ), Y( :height ), Y( :weight, Position( 1 ) ), Overlay( :sex ) ),
    Elements( Box Plot( X, Y( 1 ), Y( 2 ), Legend( 24 ) ) ),
    Local Data Filter(
        Add Filter( columns( :age ), Where( :age == {12, 13, 14, 15, 16, 17} ), Display( :age, Size( 160, 90 ), List Display ) )
    )
);

Code Explanation:

1. Open data table;
2. Create Graph Builder window.
3. Set window size.
4. Hide control panel.
5. Hide footer.
6. Define X and Y variables.
7. Add overlay variable.
8. Create box plot element.
9. Add local data filter.
10. Set filter conditions and display.

Example 517

Summary: Creates a variability chart with nested factors using Graph Builder, configuring height and weight scales, and displaying standard deviation charts.

Code:

Open("data_table.jmp");
gb = Graph Builder(
    Size( 283, 419 ),
    Show Control Panel( 0 ),
    Variables( Y( :height ), Y( :weight, Position( 1 ), Side( "Right" ) ) ),
    Elements( Mosaic( Y( 1 ), Legend( 3 ) ), Mosaic( Y( 2 ), Legend( 4 ) ) ),
    SendToReport(
        Dispatch( {}, "height", ScaleBox, {Min( -1.04443332060319 ), Max( 1.03731948583317 ), Inc( 0.5 ), Minor Ticks( 1 )} ),
        Dispatch( {}, "weight", ScaleBox, {Min( -0.0636938605804462 ), Max( 2.23073370570442 ), Inc( 0.5 ), Minor Ticks( 1 )} )
    )
);
gb << journal();
Current Journal() << save journal( "$TEMP\test.jrn" );
Current Journal() << close window();

Code Explanation:

1. Open data table.
2. Create Graph Builder object.
3. Set graph size.
4. Hide control panel.
5. Define Y variables.
6. Add mosaic elements.
7. Configure height scale.
8. Configure weight scale.
9. Journal the graph.
10. Save journal to file.
11. Close the journal window.

Example 518

Summary: Creates a nested variability chart with two factors, utilizing Graph Builder to configure scales and display standard deviation charts.

Code:

Open("data_table.jmp");
gb = Graph Builder(
    Size( 283, 419 ),
    Show Control Panel( 0 ),
    Variables( Y( :height ), Y( :weight, Position( 1 ), Side( "Right" ) ) ),
    Elements( Mosaic( Y( 1 ), Legend( 3 ) ), Mosaic( Y( 2 ), Legend( 4 ) ) ),
    SendToReport(
        Dispatch( {}, "height", ScaleBox, {Min( -1.04443332060319 ), Max( 1.03731948583317 ), Inc( 0.5 ), Minor Ticks( 1 )} ),
        Dispatch( {}, "weight", ScaleBox, {Min( -0.0636938605804462 ), Max( 2.23073370570442 ), Inc( 0.5 ), Minor Ticks( 1 )} )
    )
);
gb << journal();
Current Journal() << save journal( "$TEMP\test.jrn" );
Current Journal() << close window();
Open( "$TEMP\test.jrn" );

Code Explanation:

1. Open data table.
2. Create Graph Builder object.
3. Set graph size.
4. Hide control panel.
5. Define Y variables.
6. Add mosaic elements.
7. Configure height scale.
8. Configure weight scale.
9. Save graph as journal.
10. Close current journal.
11. Reopen saved journal.

Example 519

Summary: Creates a graph builder object to visualize relationships between height, weight, and sex using nested factors with level fill color configuration.

Code:

Open("data_table.jmp");
gb = Graph Builder(
    Size( 534, 490 ),
    Show Control Panel( 0 ),
    Variables( X( :height ), Y( :weight ), Group X( :sex ) ),
    Elements( Points( X, Y, Legend( 1 ) ), Smoother( X, Y, Legend( 2 ) ) )
);
gb << Level Fill Color( {103, 214, 214} );

Code Explanation:

1. Open data table;
2. Create graph builder object.
3. Set graph size.
4. Hide control panel.
5. Define X, Y, and group variables.
6. Add points and smoother elements.
7. Assign level fill color.

Example 520

Summary: Creates a variability chart with nested factors using Graph Builder, featuring points and smoother elements, and customizes level fill and spacing colors.

Code:

dt = Open("data_table.jmp");
gb = Graph Builder(
    Size( 534, 490 ),
    Show Control Panel( 0 ),
    Variables( X( :height ), Y( :weight ), Group X( :sex ) ),
    Elements( Points( X, Y, Legend( 1 ) ), Smoother( X, Y, Legend( 2 ) ) )
);
gb << Level Fill Color( {103, 214, 214} );
gb << Level spacing Color( "red" );

Code Explanation:

1. Open data table;
2. Create Graph Builder object.
3. Set graph size.
4. Hide control panel.
5. Define X, Y, and group variables.
6. Add points and smoother elements.
7. Set level fill color.
8. Set level spacing color.

Example 521

Summary: Creates a variability chart with nested factors using operator and part configurations, displaying standard deviation charts.

Code:

dt = Open("data_table.jmp");
gb = dt << Graph Builder(
    Size( 425, 349 ),
    Show Control Panel( 0 ),
    Fit to Window( "Off" ),
    Variables( X( :sex ), Y( :weight ) ),
    Elements( Points( X, Y, Legend( 10 ), Summary Statistic( "Mean" ), Label( "Label by Value" ) ) ),
    SendToReport(
        Dispatch( {}, "400", ScaleBox, {Legend Model( 10, Properties( 0, {Marker Size( 5 )}, Item ID( "Mean", 1 ) ) )} ),
        Dispatch( {}, "Graph Builder", FrameBox,
            {DispatchSeg(
                Marker Seg( 1 ),
                Label Offset( {0, -9, -57, 0, 100.944444444444}, {1, -14, 74, 1, 108.318181818182} ),
                Set Label Value Axis( "X" ),
                Set Label Value Format( "Fixed Dec", 5, 3 )
            )}
        )
    )
);
gb2 = gb << redo analysis;
gb2 << journal();

Code Explanation:

1. Open data table.
2. Create Graph Builder object.
3. Set graph size.
4. Hide control panel.
5. Disable fit to window.
6. Assign X and Y variables.
7. Add points element.
8. Customize legend properties.
9. Adjust label offset.
10. Set label value axis and format.

Example 522

Summary: Creates a variability chart with nested factors using operator and part configurations, displaying standard deviation charts.

Code:

dt = Open("data_table.jmp");
gb = dt << Graph Builder(
    Size( 425, 349 ),
    Show Control Panel( 0 ),
    Fit to Window( "Off" ),
    Variables( X( :sex ), Y( :weight ) ),
    Elements( Points( X, Y, Legend( 10 ), Summary Statistic( "Mean" ), Label( "Label by Value" ) ) ),
    SendToReport(
        Dispatch( {}, "400", ScaleBox, {Legend Model( 10, Properties( 0, {Marker Size( 5 )}, Item ID( "Mean", 1 ) ) )} ),
        Dispatch( {}, "Graph Builder", FrameBox,
            {DispatchSeg(
                Marker Seg( 1 ),
                Label Offset( {0, -9, -57, 0, 100.944444444444}, {1, -14, 74, 1, 108.318181818182} ),
                Set Label Value Axis( "X" ),
                Set Label Value Format( "Fixed Dec", 5, 3 )
            )}
        )
    )
);
gb2 = gb << redo analysis;
gb2 << journal();
New Window( "Journaled", Journal Box( gb2 << get journal ) );

Code Explanation:

1. Open table.
2. Create graph builder object.
3. Set size and control panel visibility.
4. Define variables for X and Y axes.
5. Add points element with mean summary statistic.
6. Adjust marker size in legend.
7. Set label offsets for markers.
8. Label values on X axis.
9. Format label value display.
10. Redo analysis and open journal.

Example 523

Summary: Creates a treemap visualization with nested factors using Graph Builder, displaying standard deviation charts and customizing group label font style.

Code:

Open("data_table.jmp");
gb = Graph Builder(
    Size( 506, 492 ),
    Show Control Panel( 0 ),
    Variables( X( :sex ), X( :age, Position( 1 ) ), Y( :height ) ),
    Elements( Treemap( X( 1 ), X( 2 ), Y, Legend( 12 ) ) )
);
frame = Report( gb )[FrameBox( 1 )];
seg = (frame << Find Seg( "TreeMapSeg" ));
seg << Set Group Label Font( "Brush Script MT" );

Code Explanation:

1. Open data table;
2. Create Graph Builder object.
3. Set graph size.
4. Hide control panel.
5. Define variables for axes.
6. Add treemap element.
7. Retrieve frame box from report.
8. Find treemap segments.
9. Set group label font style.

Example 524

Summary: Creates a variability chart with nested factors using Graph Builder, displaying standard deviation charts and enabling legend.

Code:

Open("data_table.jmp") << Graph Builder(
    Size( 380, 352 ),
    Show Control Panel( 0 ),
    Variables( X( :count ), Y( :brand ), Y( :softness, Position( 1 ) ), Y( :previous use, Position( 1 ) ), Overlay( :temperature ) ),
    Elements( Bar( X, Y( 1 ), Y( 2 ), Y( 3 ), Legend( 5 ) ) )
);

Code Explanation:

1. Open data table;
2. Launch Graph Builder.
3. Set window size.
4. Hide control panel.
5. Define X variable.
6. Define Y variables.
7. Define overlay variable.
8. Add bar element.
9. Specify Y positions.
10. Enable legend.

Example 525

Summary: Creates a bar chart with nested factors using Graph Builder, displaying standard deviation charts and applying a local data filter to include only medium fiber gr values.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 508, 296 ),
    Show Control Panel( 0 ),
    Fit to Window( "Maintain Aspect Ratio" ),
    Variables( X( :Manufacturer ), Y( :Calories ), Group X( :Enriched ), Group Y( :Name( "Hot/Cold" ) ) ),
    Elements( Bar( X, Y, Legend( 8 ) ) ),
    Local Data Filter( Mode( Include( 0 ) ), Add Filter( columns( :Fiber Gr ), Where( :Fiber Gr == " Medium" ) ) )
);

Code Explanation:

1. Open data table;
2. Create Graph Builder window.
3. Set graph size.
4. Hide control panel.
5. Fit to window aspect ratio.
6. Define X and Y variables.
7. Group by manufacturer and enriched status.
8. Group Y by hot/cold category.
9. Add bar chart element.
10. Apply local data filter.

Example 526

Summary: Creates a variability chart with nested factors using Graph Builder, displaying standard deviation charts and summarizing variance.

Code:

Open("data_table.jmp") << Graph Builder(
    Size( 200, 300 ),
    Show Control Panel( 0 ),
    Variables( X( :Mfr ), Y( :Sugars ), Overlay( :Fiber Gr ), ),
    Elements( Bar( X, Y, Legend( 6 ), Summary Statistic( "Variance" ) ) )
);

Code Explanation:

1. Open data table;
2. Launch Graph Builder.
3. Set graph size.
4. Hide control panel.
5. Define X variable.
6. Define Y variable.
7. Define overlay variable.
8. Add bar element.
9. Set summary statistic to variance.
10. Display graph.

Example 527

Summary: Creates two Graph Builder windows to visualize profit data with nested factors, utilizing log scales and standard deviation charts.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 534, 454 ),
    Show Control Panel( 0 ),
    Variables( X( :Name( "Profit($M)" ) ), Y( :Type ) ),
    Elements( Area( X, Y, Legend( 7 ) ) ),
    SendToReport(
        Dispatch( {}, "Profit($M)", ScaleBox, {Scale( "Log" ), Format( "Best", 6 ), Min( 0.1 ), Max( 700 ), Inc( 1 ), Minor Ticks( 1 )} )
    )
);
Graph Builder(
    Size( 534, 454 ),
    Show Control Panel( 0 ),
    Variables( X( :Type ), Y( :Name( "Profit($M)" ) ) ),
    Elements( Area( X, Y, Legend( 7 ) ) ),
    SendToReport(
        Dispatch( {}, "Profit($M)", ScaleBox, {Scale( "Log" ), Format( "Best", 6 ), Min( 0.1 ), Max( 700 ), Inc( 1 ), Minor Ticks( 1 )} )
    )
);

Code Explanation:

1. Open data table;
2. Create first Graph Builder window.
3. Set window size.
4. Hide control panel.
5. Define X and Y variables.
6. Add area element.
7. Configure log scale for Y-axis.
8. Create second Graph Builder window.
9. Set window size.
10. Hide control panel.

Example 528

Summary: Creates a graph builder with nested factors using operator and part configurations, displaying standard deviation charts.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 570, 481 ),
    Show Control Panel( 0 ),
    Variables( X( :age ), Y( :height ) ),
    Elements( Area( X, Y, Legend( 6 ) ) ),
    SendToReport( Dispatch( {}, "Graph Builder", FrameBox, {DispatchSeg( Poly Seg( 1 ), {Fill Pattern( "left slant heavy" )} )} ) )
);

Code Explanation:

1. Open data table;
2. Launch Graph Builder.
3. Set graph size.
4. Hide control panel.
5. Assign X and Y variables.
6. Add area element.
7. Configure legend position.
8. Send report message.
9. Dispatch to graph builder.
10. Set fill pattern.

Example 529

Summary: Creates a variability chart with nested factors using operator and part configurations, displaying standard deviation charts in Graph Builder.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 534, 450 ),
    Show Control Panel( 0 ),
    Variables( X( :Type ), Y( :Weight ) ),
    Elements( Area( X, Y, Legend( 7 ), Area Style( "Stacked Range" ), Error Interval( "Range" ), Interval Style( "Hash Band" ) ) )
);

Code Explanation:

1. Open data table;
2. Launch Graph Builder.
3. Set window size.
4. Hide control panel.
5. Assign X variable.
6. Assign Y variable.
7. Add area element.
8. Set legend position.
9. Choose stacked range style.
10. Add error interval.

Example 530

Summary: Creates a variability chart with nested factors using Graph Builder, displaying standard deviation charts and customizing report elements.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 534, 450 ),
    Show Control Panel( 0 ),
    Variables( X( :Color ), Y( :Price ), Size( :Depth ) ),
    Elements( Area( X, Y, Legend( 8 ), Error Interval( "Standard Deviation" ), Interval Style( "Hash Band" ) ) ),
    SendToReport(
        Dispatch( {}, "400", ScaleBox, {Legend Model( 8, Properties( 1, {Fill Color( 22 )}, Item ID( "Mean", 1 ) ) )} ),
        Dispatch( {}, "Graph Builder", FrameBox, {Grid Line Order( 4 ), Reference Line Order( 5 )} )
    )
);

Code Explanation:

1. Open data table;
2. Create Graph Builder.
3. Set size 534x450.
4. Hide control panel.
5. Assign variables: X(Color), Y(Price), Size(Depth).
6. Add area element.
7. Enable legend.
8. Set error interval to standard deviation.
9. Use hash band style.
10. Customize report: fill color, grid, reference line order.

Example 531

Summary: Creates a variability chart with nested factors using Graph Builder, displaying standard deviation charts and setting window size to 316x306.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 316, 306 ),
    Show Control Panel( 0 ),
    Show Legend( 0 ),
    Variables( X( :Domain Abbreviation ), Y( :Sequence Number ) ),
    Elements( Area( X, Y, Legend( 4 ), Summary Statistic( "N" ) ) )
);

Code Explanation:

1. Open data table;
2. Create new Graph Builder window.
3. Set window size to 316x306.
4. Hide control panel.
5. Hide legend.
6. Assign X variable.
7. Assign Y variable.
8. Add area element.
9. Set summary statistic to N.
10. Display graph.

Example 532

Summary: Creates a variability chart with nested factors using operator and part configurations, displaying standard deviation charts.

Code:

Open("data_table.jmp") << Graph Builder(
    Size( 409, 200 ),
    Show Control Panel( 0 ),
    Error Bar Offset( 0.06739 ),
    Variables( X( Transform Column( "height - 60", Format( "Fixed Dec", 5, 0 ), Formula( :height - 60 ) ) ) ),
    Elements( Area( X, Legend( 23 ) ) ),
    SendToReport(
        Dispatch( {}, "height - 60", ScaleBox, {Scale( "Log" ), Format( "Best", 6 ), Min( 0.01 ), Max( 10 ), Inc( 1 ), Minor Ticks( 1 )} ),
        Dispatch( {}, "400", ScaleBox, {Legend Model( 23, Properties( 0, {Transparency( 0.5 )}, Item ID( "Count", 1 ) ) )} )
    )
);

Code Explanation:

1. Open data_table data
2. Initiate Graph Builder.
3. Set window size.
4. Hide control panel.
5. Adjust error bar offset.
6. Define X variable.
7. Create area element.
8. Set log scale for X-axis.
9. Format X-axis scale.
10. Adjust legend properties.

Example 533

Summary: Creates a variability chart with nested factors using Graph Builder, displaying standard deviation charts and configuring area elements for missing values.

Code:

Open("data_table.jmp") << Graph Builder(
    Size( 459, 278 ),
    Show Control Panel( 0 ),
    Show Legend( 0 ),
    Variables( X( :Speed ), Y( :Weight ), Y( :Height, Position( 1 ) ), Group Y( :Position2 ) ),
    Elements( Area( X, Y( 1 ), Y( 2 ), Legend( 5 ), Missing Values( "No Connection" ) ) )
);

Code Explanation:

1. Open data_table data
2. Launch Graph Builder.
3. Set window size.
4. Hide control panel.
5. Hide legend.
6. Define X variable: Speed.
7. Define Y variables: Weight, Height.
8. Position Height on Y axis.
9. Group by Position2.
10. Add area element with missing values disconnected.

Example 534

Summary: Creates a variability chart with nested factors using Graph Builder, configuring scales for height and weight variables.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 273, 236 ),
    Show Control Panel( 0 ),
    Variables( X( :height ), Y( :weight ), Overlay( :sex ) ),
    Elements( Area( X, Y, Legend( 9 ), Response Axis( "Y" ), Summary Statistic( "Sum" ) ) ),
    SendToReport(
        Dispatch( {}, "height", ScaleBox, {Format( "Best", 12 ), Min( 50 )} ),
        Dispatch( {}, "weight", ScaleBox,
            {Scale( "Log" ), Format( "Best", 12 ), Min( 0.1 ), Max( 1088.40710863102 ), Inc( 1 ), Minor Ticks( 1 )}
        )
    )
);

Code Explanation:

1. Open data table.
2. Create Graph Builder object.
3. Set graph size.
4. Hide control panel.
5. Define X, Y, and overlay variables.
6. Add area element with summary statistic.
7. Dispatch to report for height scale.
8. Set height scale format and minimum.
9. Dispatch to report for weight scale.
10. Set weight scale to log, format, min, max, increment, and minor ticks.

Example 535

Summary: Creates a variability chart with nested factors using operator and part configurations, displaying standard deviation charts in Graph Builder.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 324, 232 ),
    Show Control Panel( 0 ),
    Variables(
        X( :Accident Number, Combine( "Parallel Merged" ) ),
        X( :Amateur Built, Position( 1 ), Combine( "Parallel Merged" ) ),
        Y( :Total Fatal Injuries ),
        Y( :Total Serious Injuries, Position( 1 ) )
    ),
    Elements( Area( X( 2 ), X( 1 ), Y( 1 ), Y( 2 ), Legend( 3 ) ) )
);

Code Explanation:

1. Open data table;
2. Launch Graph Builder.
3. Set window size.
4. Hide control panel.
5. Define X variables.
6. Combine X variables.
7. Define Y variables.
8. Position Y variables.
9. Add area element.
10. Configure area element.

Example 536

Summary: Creates a Graph Builder window with nested factors using operator and part configurations, displaying standard deviation charts.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 388, 353 ),
    Show Control Panel( 0 ),
    Variables( X( :Carat Weight ), X( :Table, Position( 1 ) ), X( :Depth ), Y( :Price ), Group Y( :Report ) ),
    Elements( Position( 1, 1 ), Area( X( 1 ), X( 2 ), Y, Legend( 10 ) ) ),
    Elements( Position( 2, 1 ), Area( X, Y, Legend( 11 ) ) )
);

Code Explanation:

1. Open data table;
2. Create Graph Builder window.
3. Set window size.
4. Hide control panel.
5. Define X variables: Carat Weight, Table, Depth.
6. Define Y variable: Price.
7. Define Group Y variable: Report.
8. Add first Area element.
9. Position first Area element.
10. Add second Area element.

Example 537

Summary: Creates a graph builder with area element to visualize height and weight data, utilizing Graph Builder's Variables and Elements syntax.

Code:

Open("data_table.jmp");
Graph Builder( Show Control Panel( 0 ), Variables( X( :height ), Y( :weight ) ), Elements( Area( X, Y, Legend( 16 ) ) ) );

Code Explanation:

1. Open data table;
2. Launch Graph Builder.
3. Hide control panel.
4. Set X variable to height.
5. Set Y variable to weight.
6. Add area element.
7. Configure legend position.

Example 538

Summary: Creates a Graph Builder visualization with area element to display age vs. weight data, utilizing the Variables and Elements syntax.

Code:

Open("data_table.jmp");
Graph Builder( Show Control Panel( 0 ), Variables( X( :age ), Y( :weight ) ), Elements( Area( X, Y, Legend( 8 ) ) ) );

Code Explanation:

1. Open data table.
2. Launch Graph Builder.
3. Hide control panel.
4. Set X variable to age.
5. Set Y variable to weight.
6. Add area element.
7. Assign legend position.

Example 539

Summary: Creates a variability chart with nested factors using Graph Builder, displaying standard deviation charts for height and weight.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 570, 516 ),
    Show Control Panel( 0 ),
    Variables( X( :age ), Y( :height ), Y( :weight, Position( 1 ) ), Group X( :sex ) ),
    Elements( Area( X, Y( 1 ), Y( 2 ), Legend( 10 ) ) )
);

Code Explanation:

1. Open data table;
2. Launch Graph Builder.
3. Set window size.
4. Hide control panel.
5. Assign variables: X(age), Y(height), Y(weight), Group(sex).
6. Add area element.
7. Specify Y1 for height.
8. Specify Y2 for weight.
9. Set legend position.
10. Display graph.

Example 540

Summary: Creates a variability chart with nested factors using operator and part configurations, displaying standard deviation charts in Graph Builder.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 570, 516 ),
    Show Control Panel( 0 ),
    Variables( X( :age ), Y( :height ), Y( :weight, Position( 1 ) ), Group X( :sex ) ),
    Elements( Area( X, Y( 1 ), Y( 2 ), Legend( 10 ), Area Style( "Range" ) ) )
);

Code Explanation:

1. Open data table;
2. Create new Graph Builder window.
3. Set window size.
4. Hide control panel.
5. Assign variables to axes.
6. Add group variable.
7. Plot area elements.
8. Specify X and Y variables.
9. Enable legend.
10. Set area style to range.

Example 541

Summary: Creates a variability chart with nested factors using Graph Builder, displaying standard deviation charts and leveraging operator and part configurations.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 570, 516 ),
    Show Control Panel( 0 ),
    Variables( X( :age ), Y( :weight ), Overlay( :sex ) ),
    Elements( Area( X, Y, Legend( 14 ) ) )
);

Code Explanation:

1. Open data table;
2. Launch Graph Builder.
3. Set window size.
4. Hide control panel.
5. Define X variable.
6. Define Y variable.
7. Define overlay variable.
8. Add area element.
9. Assign legend position.
10. Display graph.

Example 542

Summary: Creates a Graph Builder window with nested factors using operator and part configurations, displaying standard deviation charts.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 355, 295 ),
    Show Control Panel( 0 ),
    Variables( X( :Cut ), Y( :Price ), Overlay( :Clarity ), Color( :Color ) ),
    Elements( Area( X, Y, Legend( 33 ) ) )
);

Code Explanation:

1. Open data table;
2. Create Graph Builder window.
3. Set size to 355x295.
4. Hide control panel.
5. Assign X variable: Cut.
6. Assign Y variable: Price.
7. Assign Overlay variable: Clarity.
8. Assign Color variable: Color.
9. Add Area element.
10. Set legend position to 33.

Example 543

Summary: Creates a variability chart with nested factors using operator and part configurations, displaying standard deviation charts in Graph Builder.

Code:

dt = Open("data_table.jmp") << Graph Builder(
    Size( 524, 293 ),
    Show Control Panel( 0 ),
    Show Legend( 0 ),
    Show Footer( 0 ),
    Variables(
        X( :Name( "# Employees" ) ),
        Y( :Name( "Profits ($M)" ) ),
        Y( :Name( "Sales ($M)" ), Position( 1 ) ),
        Group Y( :Size Co ),
        Color( :Type )
    ),
    Elements( Area( X, Y( 1 ), Y( 2 ), Legend( 82 ) ) ),
    SendToReport(
        Dispatch( {}, "Profits ($M)", ScaleBox,
            {Scale( "Log" ), Format( "Best", 6 ), Min( 10 ), Max( 70000 ), Inc( 1 ), Minor Ticks( 1 )}
        )
    )
);

Code Explanation:

1. Open data table;
2. Create Graph Builder window.
3. Set size to 524x293.
4. Hide control panel.
5. Hide legend.
6. Hide footer.
7. Set X variable: # Employees.
8. Set Y variables: Profits ($M), Sales ($M).
9. Group Y by Size Co.
10. Color by Type.

Example 544

Summary: Creates a variability chart with nested factors using Graph Builder, configuring X and Y variables, setting summary statistics, and displaying the graph.

Code:

Open("data_table.jmp");
Graph Builder(
    Show Control Panel( 0 ),
    Variables( X( :age, Size( 18 ) ), Y( :height, Size( 37 ) ) ),
    Elements( Area( X, Y, Summary Statistic( "Sum" ) ) )
);

Code Explanation:

1. Open data table;
2. Launch Graph Builder.
3. Hide control panel.
4. Set X variable to age.
5. Set Y variable to height.
6. Configure X size to 18.
7. Configure Y size to 37.
8. Add area element.
9. Set summary statistic to Sum.
10. Display graph.

Example 545

Summary: Creates a stacked area chart with sum statistics for nested factors using Graph Builder, displaying legend and standard deviation charts.

Code:

Open("data_table.jmp");
Graph Builder(
    Show Control Panel( 0 ),
    Variables( X( :age ), Y( :height ) ),
    Elements( Area( X, Y, Legend( 2 ), Area Style( "Stacked" ), Summary Statistic( "Sum" ) ) )
);

Code Explanation:

1. Open data_table data
2. Launch Graph Builder.
3. Hide control panel.
4. Set X variable to age.
5. Set Y variable to height.
6. Add area element.
7. Stack area elements.
8. Use sum for summary statistic.
9. Display legend for area.

Example 546

Summary: Creates a variability chart with nested factors using Graph Builder, displaying standard deviation charts for height and weight.

Code:

dt = Open("data_table.jmp");
Graph Builder(
    Size( 565, 500 ),
    Show Control Panel( 0 ),
    Variables( X( :sex ), Y( :height ), Y( :weight, Position( 1 ), Side( "Right" ) ) ),
    Elements(
        Line( X, Y( 1 ), Legend( 22 ) ),
        Line( X, Y( 2 ), Legend( 14 ) ),
        Area( X, Y( 1 ), Legend( 26 ) ),
        Area( X, Y( 2 ), Legend( 23 ) )
    )
);

Code Explanation:

1. Open data table;
2. Create Graph Builder window.
3. Set window size.
4. Hide control panel.
5. Define X variable as sex.
6. Define Y variables: height, weight.
7. Plot height line on left axis.
8. Plot weight line on right axis.
9. Fill area under height line.
10. Fill area under weight line.

Example 547

Summary: Creates a variability chart with nested factors using operator and part configurations, displaying standard deviation charts in Graph Builder.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 570, 516 ),
    Show Control Panel( 0 ),
    Variables( X( :age ), Y( :weight ), Overlay( :sex ) ),
    Elements( Area( X, Y, Legend( 21 ) ) ),
    SendToReport(
        Dispatch( {}, "400", ScaleBox, {Legend Model( 21, Properties( 1, {Line Color( 6 ), Fill Color( 6 ), Transparency( 0.5 )} ) )} )
    )
);

Code Explanation:

1. Open data table.
2. Create Graph Builder object.
3. Set window size.
4. Hide control panel.
5. Define variables: X, Y, Overlay.
6. Add area element.
7. Send report to Graph Builder.
8. Dispatch to legend model.
9. Set legend properties.
10. Customize line and fill colors.

Example 548

Summary: Creates a variability chart with nested factors using Graph Builder, displaying standard deviation charts and configuring legend properties.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 570, 516 ),
    Show Control Panel( 0 ),
    Variables( X( :age ), Y( :weight ), Overlay( :sex ), Frequency( :height ) ),
    Elements( Area( X, Y, Legend( 24 ) ) ),
    SendToReport(
        Dispatch( {}, "400", ScaleBox, {Legend Model( 24, Properties( 1, {Line Color( 6 ), Fill Color( 6 ), Transparency( 0.5 )} ) )} )
    )
);

Code Explanation:

1. Open data_table data
2. Launch Graph Builder.
3. Set window size.
4. Hide control panel.
5. Assign variables.
6. Add area element.
7. Configure legend properties.
8. Adjust line color.
9. Change fill color.
10. Set transparency level.

Example 549

Summary: Creates a variability chart with nested factors using operator and part configurations, displaying standard deviation charts in Graph Builder.

Code:

Open("data_table.jmp");
Graph Builder(
    Show Control Panel( 0 ),
    Variables( X( :Number of Fillings ), Y( :Floss Cost ), Overlay( :Job Satisfaction ) ),
    Elements( Area( X, Y, Legend( 6 ), Area Style( "Overlaid" ) ) )
);

Code Explanation:

1. Open data table;
2. Launch Graph Builder.
3. Hide control panel.
4. Set X variable.
5. Set Y variable.
6. Add overlay variable.
7. Create area element.
8. Configure legend position.
9. Set area style to overlaid.

Example 550

Summary: Creates a graph builder window with an area plot element to visualize the relationship between weight, height, and age.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 501, 300 ),
    Show Control Panel( 0 ),
    Variables( X( :weight ), Y( :height ), Overlay( :age ) ),
    Elements( Area( X, Y, Legend( 14 ) ) )
);

Code Explanation:

1. Open data table;
2. Create Graph Builder window.
3. Set window size to 501x300.
4. Hide control panel.
5. Assign weight to X-axis.
6. Assign height to Y-axis.
7. Overlay age variable.
8. Add area plot element.
9. Use legend for age.
10. Display graph.

Example 551

Summary: Creates a variability chart with nested factors using Graph Builder, displaying standard deviation charts and various summary statistics.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 653, 540 ),
    Show Control Panel( 0 ),
    Variables(
        X( :age ),
        X( :age ),
        X( :age ),
        X( :age ),
        X( :age ),
        X( :age ),
        X( :age ),
        X( :age ),
        X( :age ),
        X( :age ),
        X( :age ),
        X( :age ),
        X( :age ),
        X( :age ),
        X( :age ),
        Y( :height )
    ),
    Elements( Position( 1, 1 ), Area( X, Y, Legend( 91 ), Summary Statistic( "N" ) ) ),
    Elements( Position( 2, 1 ), Area( X, Y, Legend( 92 ) ) ),
    Elements( Position( 3, 1 ), Area( X, Y, Legend( 93 ), Summary Statistic( "Median" ) ) ),
    Elements( Position( 4, 1 ), Area( X, Y, Legend( 94 ), Summary Statistic( "Geometric Mean" ) ) ),
    Elements( Position( 5, 1 ), Area( X, Y, Legend( 95 ), Summary Statistic( "Min" ) ) ),
    Elements( Position( 6, 1 ), Area( X, Y, Legend( 96 ), Summary Statistic( "Max" ) ) ),
    Elements( Position( 7, 1 ), Area( X, Y, Legend( 97 ), Summary Statistic( "Range" ) ) ),
    Elements( Position( 8, 1 ), Area( X, Y, Legend( 98 ), Summary Statistic( "Sum" ) ) ),
    Elements( Position( 9, 1 ), Area( X, Y, Legend( 99 ), Summary Statistic( "% of Total" ) ) ),
    Elements( Position( 10, 1 ), Area( X, Y, Legend( 100 ), Summary Statistic( "Std Dev" ) ) ),
    Elements( Position( 11, 1 ), Area( X, Y, Legend( 101 ), Summary Statistic( "Variance" ) ) ),
    Elements( Position( 12, 1 ), Area( X, Y, Legend( 102 ), Summary Statistic( "Std Err" ) ) ),
    Elements( Position( 13, 1 ), Area( X, Y, Legend( 103 ), Summary Statistic( "Interquartile Range" ) ) ),
    Elements( Position( 14, 1 ), Area( X, Y, Legend( 104 ), Summary Statistic( "First Quartile" ) ) ),
    Elements( Position( 15, 1 ), Area( X, Y, Legend( 105 ), Summary Statistic( "Third Quartile" ) ) ),
    SendToReport( Dispatch( {}, "height", ScaleBox, {Min( -41.8181818181818 )} ) )
);

Code Explanation:

1. Open data table;
2. Create Graph Builder window.
3. Set graph size.
4. Hide control panel.
5. Define X variable: age.
6. Define Y variable: height.
7. Add area plot for N.
8. Add area plot for raw data.
9. Add area plot for median.
10. Add area plot for geometric mean.
11. Add area plot for min.
12. Add area plot for max.
13. Add area plot for range.
14. Add area plot for sum.
15. Add area plot for % of Total.
16. Add area plot for Std Dev.
17. Add area plot for Variance.
18. Add area plot for Std Err.
19. Add area plot for Interquartile Range.
20. Add area plot for First Quartile.
21. Add area plot for Third Quartile.
22. Adjust Y-axis minimum.

Example 552

Summary: Creates a variability chart with nested factors using operator and part configurations, displaying standard deviation charts.

Code:

dt = Open("data_table.jmp");
dt << clear row states;
dt << select rows( [21, 22, 23, 24, 25, 26, 27, 28, 29, 30] );
mySubset = dt << subset( selected rows( 1 ), link to original data table( 1 ) );
mySubset << Graph Builder(
    Size( 491, 398 ),
    Variables( X( :sex ), Y( :height ), Y( :weight, Position( 1 ) ) ),
    Elements( Area( X, Y( 1 ), Y( 2 ), Legend( 4 ), Summary Statistic( "% of Total" ) ) ),
    SendToReport( Dispatch( {}, "Graph Builder", OutlineBox, {Set Title( "Graph Builder" )} ) )
);

Code Explanation:

1. Open data table.
2. Clear row states.
3. Select specific rows.
4. Create subset from selected rows.
5. Launch Graph Builder.
6. Set graph size.
7. Define X and Y variables.
8. Add area element with summary statistic.
9. Set title for graph.
10. Display graph.

Example 553

Summary: Creates a variability chart with nested factors using operator and part configurations, displaying standard deviation charts in Graph Builder.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 457, 379 ),
    Show Control Panel( 0 ),
    Variables(
        X( :Brand ),
        X( :Type, Position( 1 ) ),
        X( :Drink, Position( 1 ) ),
        Y( :Heart Rate ),
        Group Y( :Gender ),
        Overlay( :Testers )
    ),
    Elements( Area( X( 1 ), X( 2 ), X( 3 ), Y, Legend( 20 ) ) )
);

Code Explanation:

1. Open data table;
2. Create new Graph Builder window.
3. Set window size.
4. Hide control panel.
5. Define X variables.
6. Define Y variable.
7. Define Group Y variable.
8. Define Overlay variable.
9. Add Area element.
10. Configure element settings.

Example 554

Summary: Creates a stacked area chart with nested factors using Graph Builder, displaying the sum of height for each sex group.

Code:

Open("data_table.jmp");
Graph Builder(
    Show Control Panel( 0 ),
    Variables( X( :age ), X( :sex, Position( 1 ) ), Y( :height ) ),
    Elements( Area( X( 1 ), X( 2 ), Y, Legend( 4 ), Area Style( "Stacked" ), Summary Statistic( "Sum" ) ) )
);

Code Explanation:

1. Open data table;
2. Launch Graph Builder.
3. Hide control panel.
4. Set X variables: age, sex.
5. Set Y variable: height.
6. Add area element.
7. Assign X1: age.
8. Assign X2: sex.
9. Assign Y: height.
10. Configure area style: stacked.

Example 555

Summary: Creates a variability chart with nested factors using Graph Builder, showcasing operator and part configurations, and displaying standard deviation charts.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 793, 569 ),
    Show Control Panel( 0 ),
    Variables(
        X( :Sports ),
        X( :Name( "Urban/Rural" ), Position( 1 ) ),
        Y( :Goals ),
        Y( :Grades, Position( 1 ) ),
        Y( :School, Position( 1 ) ),
        Overlay( :Race )
    ),
    Elements( Area( X( 1 ), X( 2 ), Y( 1 ), Y( 2 ), Y( 3 ), Legend( 16 ) ) )
);

Code Explanation:

1. Open data table;
2. Launch Graph Builder.
3. Set window size.
4. Hide control panel.
5. Define X variables.
6. Add second X variable.
7. Define Y variables.
8. Add second Y variable.
9. Add third Y variable.
10. Apply overlay variable.

Example 556

Summary: Creates a variability chart with nested factors using operator and part configurations, displaying standard deviation charts in Graph Builder.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 606, 554 ),
    Variables(
        X( :Sports ),
        X( :Name( "Urban/Rural" ), Position( 1 ) ),
        Y( :Goals ),
        Y( :Sports, Position( 1 ) ),
        Y( :School, Position( 1 ) ),
        Overlay( :Race )
    ),
    Elements( Area( X( 2 ), X( 1 ), Y( 1 ), Y( 2 ), Y( 3 ), Legend( 17 ) ) ),
    SendToReport(
        Dispatch( {"Area"}, "", OutlineBox, {Close( 0 )} ),
        Dispatch( {}, "Goals", ScaleBox, {Min( -0.114198285682452 ), Max( 86.1551059117409 ), Inc( 1 ), Minor Ticks( 0 )} )
    )
);

Code Explanation:

1. Open data table.
2. Launch Graph Builder.
3. Set window size.
4. Define X variables.
5. Define additional X variable.
6. Define Y variables.
7. Define overlay variable.
8. Create area element.
9. Configure area element.
10. Adjust report settings.

Example 557

Summary: Creates a variability chart with nested factors using Graph Builder, displaying standard deviation charts and configuring area style.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 511, 416 ),
    Show Control Panel( 0 ),
    Variables(
        X( :sex ),
        X( :age, Position( 1 ) ),
        Y( :weight, Side( "Right" ) ),
        Y( :height, Position( 1 ) ),
        Y( :weight, Position( 1 ) )
    ),
    Elements(
        Area( X( 2 ), X( 1 ), Y( 2 ), Y( 3 ), Legend( 5 ), Area Style( "Range" ), Summary Statistic( "Sum" ) ),
        Points( X( 1 ), X( 2 ), Y( 2 ), Y( 3 ), Legend( 9 ) )
    )
);

Code Explanation:

1. Open data table.
2. Create graph builder window.
3. Set window size.
4. Hide control panel.
5. Define X variables.
6. Define Y variables.
7. Add area element.
8. Configure area style.
9. Add points element.
10. Display graph.

Example 558

Summary: Creates a stacked area chart with nested factors using Graph Builder, displaying mean summary statistics and customizable legend colors.

Code:

dt = Open("data_table.jmp");
obj = Graph Builder(
    Show Control Panel( 0 ),
    Variables( X( :age ), Y( :weight ), Y( :height, Position( 1 ) ) ),
    Elements( Area( X, Y( 1 ), Y( 2 ), Legend( 2 ), Area Style( "Stacked" ), Summary Statistic( "Mean" ) ) ),
    SendToReport(
        Dispatch( {}, "400", ScaleBox,
            {Legend Model(
                2,
                Properties( 0, {Fill Color( 69 )} ),
                Properties( 1, {Fill Color( 75 )} ),
                Properties( 2, {Line Color( 0 ), Line Width( 2 )} ),
                Properties( 3, {Line Color( 55 ), Line Width( 3 )} )
            )}
        )
    )
);

Code Explanation:

1. Open data table.
2. Create Graph Builder object.
3. Hide control panel.
4. Set X variable to age.
5. Set Y variables to weight and height.
6. Add area element for weight and height.
7. Stack area elements.
8. Use mean for summary statistic.
9. Customize legend colors.
10. Send report with customized settings.

Example 559

Summary: Creates a variability chart with nested factors using operator and part configurations, displaying standard deviation charts in Graph Builder.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 428, 430 ),
    Show Control Panel( 0 ),
    Variables(
        X( :age ),
        Y( :height ),
        Y( :weight, Position( 1 ) ),
        Y( :height ),
        Y( :weight, Position( 2 ) ),
        Y( :height ),
        Y( :weight, Position( 3 ) )
    ),
    Elements( Position( 1, 1 ), Area( X, Y( 1 ), Y( 2 ), Legend( 6 ) ) ),
    Elements( Position( 1, 2 ), Area( X, Y( 1 ), Y( 2 ), Legend( 7 ), Area Style( "Overlaid" ) ) ),
    Elements( Position( 1, 3 ), Points( X, Y( 1 ), Y( 2 ), Legend( 8 ) ) )
);

Code Explanation:

1. Open data table;
2. Launch Graph Builder.
3. Set window size.
4. Hide control panel.
5. Define X variable.
6. Define first Y variable.
7. Define second Y variable.
8. Repeat Y variable definition.
9. Add area element.
10. Add overlaid area element.
11. Add points element.

Example 560

Summary: Creates a variability chart with nested factors using operator and part configurations, displaying standard deviation charts in Graph Builder.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 534, 418 ),
    Show Control Panel( 0 ),
    Variables( Y( :Class ), Y( :Sex, Position( 1 ) ), Y( :Survived, Position( 1 ) ) ),
    Elements( Area( Y( 1 ), Y( 2 ), Y( 3 ), Legend( 11 ), Curve Lines( 0 ) ) )
);

Code Explanation:

1. Open data table;
2. Launch Graph Builder.
3. Set window size.
4. Hide control panel.
5. Assign variables to Y axes.
6. Add area element.
7. Configure Y1 axis for Class.
8. Configure Y2 axis for Sex.
9. Configure Y3 axis for Survived.
10. Disable curve lines.

Example 561

Summary: Creates a stacked area chart with mean summary statistics for nested factors, utilizing Graph Builder and SendToReport features in JMP.

Code:

Open("data_table.jmp");
Graph Builder(
    Show Control Panel( 0 ),
    Variables( X( :age ), Y( :weight ), Y( :height, Position( 1 ) ) ),
    Elements( Area( X, Y( 1 ), Y( 2 ), Legend( 2 ), Area Style( "Stacked" ), Summary Statistic( "Mean" ) ) ),
    SendToReport(
        Dispatch( {}, "400", ScaleBox, {Legend Model( 2, Properties( 0, {Fill Color( 4 )} ), Properties( 1, {Fill Color( 11 )} ) )} )
    )
);

Code Explanation:

1. Open data table.
2. Create Graph Builder window.
3. Hide control panel.
4. Set X variable to age.
5. Set Y variables to weight and height.
6. Add area element.
7. Configure area style to stacked.
8. Set summary statistic to mean.
9. Customize legend colors.
10. Send report to display.

Example 562

Summary: Creates a variability chart with nested factors using operator and part configurations, displaying standard deviation charts in Graph Builder.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 255, 312 ),
    Show Control Panel( 0 ),
    Variables( X( :sex ), Y( :height ), Y( :weight, Position( 1 ) ) ),
    Elements( Area( X, Y( 1 ), Y( 2 ), Legend( 11 ) ) ),
    SendToReport(
        Dispatch( {}, "height", ScaleBox,
            {Scale( "Log" ), Format( "Best", 12 ), Min( 52.2895040850281 ), Max( 243.036661275667 ), Inc( 1 ), Minor Ticks( 1 )}
        ),
        Dispatch( {}, "400", ScaleBox, {Legend Model( 11, Properties( 1, {Transparency( 0.5 )} ) )} )
    )
);

Code Explanation:

1. Open data_table data
2. Create Graph Builder window.
3. Set window size.
4. Hide control panel.
5. Assign variables: sex (X), height (Y1), weight (Y2).
6. Add area element with multiple Y axes.
7. Log scale for height axis.
8. Format height axis.
9. Set height axis limits.
10. Adjust weight legend transparency.

Example 563

Summary: Creates a variability chart with nested factors using Graph Builder, displaying standard deviation charts and utilizing operator and part configurations.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 370, 311 ),
    Show Control Panel( 0 ),
    Show Legend( 0 ),
    Variables( X( :People ), Y( :Fish Caught ), Y( :Fishing Poles, Position( 1 ) ) ),
    Elements( Area( X, Y( 1 ), Y( 2 ), Legend( 18 ) ) )
);

Code Explanation:

1. Open data table;
2. Create new Graph Builder window.
3. Set window size to 370x311.
4. Hide control panel.
5. Hide legend.
6. Assign X variable: People.
7. Assign Y variable: Fish Caught.
8. Assign second Y variable: Fishing Poles.
9. Position second Y on left.
10. Add area plot with both Y variables.

Example 564

Summary: Creates a stacked area chart with mean summary statistics, displaying weight and height data for each age group, using Graph Builder.

Code:

dt = Open("data_table.jmp");
obj = Graph Builder(
    Show Control Panel( 0 ),
    Variables( X( :age ), Y( :weight ), Y( :height, Position( 1 ) ) ),
    Elements( Area( X, Y( 1 ), Y( 2 ), Legend( 2 ), Area Style( "Stacked" ), Summary Statistic( "Mean" ) ) ),
    SendToReport(
        Dispatch( {}, "400", ScaleBox,
            {Legend Model( 2, Properties( 2, {Line Color( 8 ), Line Width( 2 )} ), Properties( 3, {Line Color( 73 ), Line Width( 2 )} ) )}
        )
    )
);

Code Explanation:

1. Open data_table data
2. Create Graph Builder object.
3. Hide control panel.
4. Set X variable to age.
5. Set first Y variable to weight.
6. Set second Y variable to height.
7. Add area element with stacked style.
8. Use mean for summary statistic.
9. Customize legend properties.
10. Set line color and width for each series.

Example 565

Summary: Creates a stacked area chart with mean summary statistics for weight and height, using age as the x-axis variable in Graph Builder.

Code:

Open("data_table.jmp");
Graph Builder(
    Show Control Panel( 0 ),
    Variables( X( :age ), Y( :weight ), Y( :height, Position( 1 ) ) ),
    Elements( Area( X, Y( 1 ), Y( 2 ), Legend( 2 ), Area Style( "Stacked" ), Summary Statistic( "Mean" ) ) )
);

Code Explanation:

1. Open data table.
2. Launch Graph Builder.
3. Hide control panel.
4. Set X variable to age.
5. Set Y variable to weight.
6. Add height as Y variable.
7. Position height on axis 1.
8. Create area element.
9. Use X for horizontal axis.
10. Use mean for summary statistic.

Example 566

Summary: Creates a stacked area plot with mean summary statistics for weight and height, nested under age, using Graph Builder in JMP.

Code:

Open("data_table.jmp");
Graph Builder(
    Show Control Panel( 0 ),
    Variables( X( :age ), Y( :weight ), Y( :height, Position( 1 ) ) ),
    Elements( Area( X, Y( 1 ), Y( 2 ), Legend( 2 ), Area Style( "Stacked" ), Summary Statistic( "Mean" ) ) ),
    SendToReport(
        Dispatch( {}, "400", ScaleBox,
            {Legend Model( 2, Properties( 0, {Transparency( 0.6 )} ), Properties( 1, {Transparency( 0.5 )} ) )}
        )
    )
);

Code Explanation:

1. Open data table;
2. Launch Graph Builder.
3. Hide control panel.
4. Set X variable to age.
5. Set Y variables to weight and height.
6. Create area plot.
7. Stack area elements.
8. Calculate mean for summary statistic.
9. Adjust legend properties.
10. Set transparency for area elements.

Example 567

Summary: Creates a variability chart with nested factors using operator and part configurations, displaying standard deviation charts through Graph Builder.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 451, 346 ),
    Show Control Panel( 0 ),
    Include Missing Categories( 1 ),
    Variables( X( :Operator ), X( :part#, Position( 1 ) ), Y( :Measurement ), Overlay( :Operator ) ),
    Elements( Area( X( 1 ), X( 2 ), Y, Legend( 26 ) ) )
);

Code Explanation:

1. Open data table;
2. Launch Graph Builder.
3. Set window size.
4. Hide control panel.
5. Include missing categories.
6. Assign variables: Operator, part#, Measurement.
7. Set overlay variable: Operator.
8. Create area element.
9. Position X variables.
10. Display graph.

Example 568

Summary: Creates a variability chart with nested factors using Graph Builder, displaying standard deviation charts and overlaying variables.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 353, 276 ),
    Show Control Panel( 0 ),
    Variables( X( :Heart History ), Overlay( :Smoking History ) ),
    Elements( Area( X, Legend( 3 ) ) )
);

Code Explanation:

1. Open lipid data file.
2. Launch Graph Builder.
3. Set window size.
4. Hide control panel.
5. Assign X variable.
6. Assign overlay variable.
7. Add area element.
8. Set legend position.

Example 569

Summary: Creates a variability chart with nested factors using Graph Builder, displaying standard deviation charts and configuring area style as overlaid.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 521, 331 ),
    Show Control Panel( 0 ),
    Show Legend( 0 ),
    Variables( X( :DATE ), Y( :TAVG ), Overlay( :STATION ) ),
    Elements( Area( X, Y, Legend( 7 ), Area Style( "Overlaid" ), Summary Statistic( "% of Total" ) ) )
);

Code Explanation:

1. Open data_table data
2. Launch Graph Builder.
3. Set window size.
4. Hide control panel.
5. Hide legend.
6. Define X variable as DATE.
7. Define Y variable as TAVG.
8. Use STATION for overlay.
9. Add area element.
10. Configure area style as overlaid.
11. Set summary statistic to percent of total.

Example 570

Summary: Creates a variability chart with nested factors using operator and part configurations, displaying standard deviation charts.

Code:

dt under test = Open("data_table.jmp");
obj = Graph Builder(
    Size( 533, 453 ),
    Show Control Panel( 0 ),
    Variables( X( :Date ), Y( :High ), Y( :Low, Position( 1 ) ) ),
    Elements( Area( X, Y( 1 ), Y( 2 ), Legend( 15 ), Area Style( "Overlaid" ) ), Points( X, Y( 1 ), Y( 2 ), Legend( 16 ) ) ),
    SendToReport(
        Dispatch( {}, "Date", ScaleBox,
            {Min( 3058108918.14359 ), Max( 3065946418.08668 ), Interval( "Day" ), Inc( 10 ), Minor Ticks( 0 ),
            Label Row( Show Major Grid( 1 ) )}
        ),
        Dispatch( {}, "High", ScaleBox, {Label Row( Show Major Grid( 1 ) )} ),
        Dispatch( {}, "400", ScaleBox,
            {Legend Model( 16, Properties( 0, {Line Color( 0 )} ), Properties( 1, {Line Color( 2 )} ) ),
            Legend Model( 15, Properties( 0, {Line Color( 52 ), Fill Color( 52 )} ) )}
        ),
        Dispatch( {}, "Graph Builder", FrameBox, {Background Color( 16 )} )
    )
);

Code Explanation:

1. Open data table;
2. Create Graph Builder object.
3. Set size to 533x453.
4. Hide control panel.
5. Define X as Date.
6. Define Y1 as High.
7. Define Y2 as Low.
8. Add area element with overlaid style.
9. Add points element.
10. Customize date scale.
11. Customize high scale.
12. Customize legend colors.
13. Set background color.

Example 571

Summary: Creates a variability chart with nested factors using Graph Builder, displaying standard deviation charts and overlaying by gender.

Code:

Open("data_table.jmp");
Graph Builder(
    Show Control Panel( 0 ),
    Variables( X( :Age ), Y( :BMI ), Group Y( :Gender ), Overlay( :Gender ) ),
    Elements( Area( X, Y, Legend( 8 ) ) )
);

Code Explanation:

1. Open data table;
2. Launch Graph Builder.
3. Hide control panel.
4. Set X variable: Age.
5. Set Y variable: BMI.
6. Group Y by Gender.
7. Overlay by Gender.
8. Add Area plot element.
9. Assign legend to 8th position.

Example 572

Summary: Creates a variability chart with nested factors using Graph Builder, displaying standard deviation charts and overlaying sex as a categorical factor.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 300, 200 ),
    Show Control Panel( 0 ),
    Variables( X( Transform Column( "Rank[sex]", Character, Formula( Col Rank( :sex ) ) ) ), Y( :height ), Overlay( :sex ) ),
    Elements( Area( X, Y, Legend( 13 ) ) )
);

Code Explanation:

1. Open data table.
2. Launch Graph Builder.
3. Set graph size.
4. Hide control panel.
5. Define X variable.
6. Define Y variable.
7. Use sex for overlay.
8. Add area plot element.
9. Assign legend to area plot.
10. Render graph in HTML5.

Example 573

Summary: Creates a variability chart with nested factors using operator and part configurations, displaying standard deviation charts for analysis.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 491, 391 ),
    Show Control Panel( 0 ),
    Variables( X( :Operator ), X( :part#, Position( 1 ) ), Y( :Measurement ) ),
    Elements( Area( X( 2 ), X( 1 ), Y, Legend( 12 ) ), Points( X( 2 ), X( 1 ), Y, Legend( 8 ), Summary Statistic( "Mean" ) ) ),
    SendToReport( Dispatch( {}, "400", ScaleBox, {Legend Model( 12, Properties( 0, {Line Width( 1 )} ) )} ) )
);

Code Explanation:

1. Open data table;
2. Create Graph Builder window.
3. Set window size.
4. Hide control panel.
5. Assign variables: Operator, part#, Measurement.
6. Add area element for Operator and part#.
7. Add points element for Operator and part#.
8. Set summary statistic to mean.
9. Customize legend properties.
10. Display report.

Example 574

Summary: Creates a variability chart with nested factors using operator and part configurations, displaying standard deviation charts in JMP.

Code:

dt = Open("data_table.jmp") << Graph Builder(
    Size( 496, 318 ),
    Show Control Panel( 0 ),
    Show Legend( 0 ),
    Show Footer( 0 ),
    Variables(
        X( :Name( "# Employees" ) ),
        Y( :Name( "Sales ($M)" ) ),
        Y( :Name( "Profits ($M)" ), Position( 1 ) ),
        Group X( :Type ),
        Group Y( :Size Co )
    ),
    Elements( Area( X, Y( 1 ), Y( 2 ), Legend( 82 ), Area Style( "Range" ), Missing Values( "No Connection" ) ) ),
    SendToReport(
        Dispatch( {}, "Sales ($M)", ScaleBox,
            {Format( "Fixed Dec", 12, 0 ), Min( -1100.71201617777 ), Max( 2467.89621333334 ), Inc( 1000 ), Minor Ticks( 0 )}
        )
    )
);

Code Explanation:

1. Open data table;
2. Create Graph Builder window.
3. Set window size to 496x318.
4. Hide control panel.
5. Hide legend.
6. Hide footer.
7. Set X variable to # Employees.
8. Set first Y variable to Sales ($M).
9. Set second Y variable to Profits ($M).
10. Group X by Type.
11. Group Y by Size Co.
12. Add area element with range style.
13. Handle missing values without connection.
14. Format Sales ($M) scale.
15. Set Sales ($M) minimum value.
16. Set Sales ($M) maximum value.
17. Set Sales ($M) increment.
18. Disable minor ticks on Sales ($M) axis.

Example 575

Summary: Creates a variability chart with nested factors using Graph Builder, displaying standard deviation charts and customizing area style to range.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 302, 182 ),
    Show Control Panel( 0 ),
    Variables( X( :height ), Y( :weight ), Overlay( :sex ) ),
    Elements( Area( X, Y, Legend( 9 ), Area Style( "Range" ) ) ),
    SendToReport( Dispatch( {}, "height", ScaleBox, {Format( "Best", 12 ), Min( 50 )} ) )
);

Code Explanation:

1. Open data table.
2. Launch Graph Builder.
3. Set window size.
4. Hide control panel.
5. Define X, Y, and overlay variables.
6. Add area element.
7. Customize legend position.
8. Set area style to range.
9. Format height scale.
10. Set minimum height value.

Example 576

Summary: Creates a variability chart with nested factors using Graph Builder, displaying standard deviation charts and utilizing range style for visualization.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 409, 316 ),
    Show Control Panel( 0 ),
    Variables( X( :age ), Overlay( :sex ) ),
    Elements( Area( X, Legend( 11 ), Area Style( "Range" ), Summary Statistic( "N" ) ) )
);

Code Explanation:

1. Open data table;
2. Create Graph Builder window.
3. Set window size.
4. Hide control panel.
5. Assign X variable.
6. Add overlay variable.
7. Add area element.
8. Set legend position.
9. Choose range style.
10. Use count for summary statistic.

Example 577

Summary: Creates a variability chart with nested factors using Graph Builder, displaying standard deviation charts and adjusting height scale minimum.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 583, 388 ),
    Show Control Panel( 0 ),
    Variables( X( :height ), Y( :weight ), Overlay( :sex ) ),
    Elements( Area( X, Y, Legend( 7 ), Area Style( "Range" ) ) ),
    SendToReport( Dispatch( {}, "height", ScaleBox, {Min( 50 )} ) )
);

Code Explanation:

1. Open data table;
2. Launch Graph Builder.
3. Set window size.
4. Hide control panel.
5. Assign variables: height, weight, sex.
6. Create area plot.
7. Overlay by sex.
8. Use range area style.
9. Set legend position.
10. Adjust height scale minimum.

Example 578

Summary: Creates a variability chart with nested factors using Graph Builder, displaying standard deviation charts and utilizing area elements for visualization.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 484, 344 ),
    Show Control Panel( 0 ),
    Show Legend( 0 ),
    Variables( X( :Wavelength ), Y( :CuSO4 ), Y( :Na2S2O3, Position( 1 ) ) ),
    Elements( Area( X, Y( 1 ), Y( 2 ), Legend( 4 ), Area Style( "Range" ) ) )
);

Code Explanation:

1. Open data table;
2. Launch Graph Builder.
3. Set window size.
4. Hide control panel.
5. Hide legend.
6. Define X variable.
7. Define first Y variable.
8. Define second Y variable.
9. Add area element.
10. Set area style to range.

Example 579

Summary: Creates a variability chart with nested factors using Graph Builder, displaying standard deviation charts and applying local data filters.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 407, 385 ),
    Show Control Panel( 0 ),
    Variables( X( :sex ), Y( :height ), Y( :weight, Position( 1 ) ) ),
    Elements( Area( X, Y( 1 ), Y( 2 ), Legend( 4 ), Area Style( "Range" ), Summary Statistic( "Interquartile Range" ) ) ),
    Local Data Filter( Add Filter( columns( :age ), Where( :age == 17 ), Display( :age, Size( 159, 90 ), List Display ) ) )
);

Code Explanation:

1. Open data table;
2. Launch Graph Builder.
3. Set window size.
4. Hide control panel.
5. Define X variable.
6. Define Y variables.
7. Add area element.
8. Set area style to range.
9. Use interquartile range summary.
10. Apply local data filter.

Example 580

Summary: Creates a variability chart with nested factors using operator and part configurations, displaying standard deviation charts.

Code:

dt = Open("data_table.jmp");
Graph Builder(
    Size( 639, 466 ),
    Variables( X( :sex ), Y( :height ), Y( :weight, Position( 1 ) ) ),
    Elements( Area( X, Y( 1 ), Y( 2 ), Legend( 7 ), Area Style( "Range" ), Summary Statistic( "% of Total" ) ) )
);

Code Explanation:

1. Open data table;
2. Create Graph Builder window.
3. Set window size 639x466.
4. Assign X variable: sex.
5. Assign Y variables: height, weight.
6. Position weight on Y axis 1.
7. Add Area element.
8. Set X for Area.
9. Set Y1 for Area: height.
10. Set Y2 for Area: weight.
11. Set legend position 7.
12. Apply Area Style "Range".
13. Use Summary Statistic "% of Total".

Example 581

Summary: Creates two variability charts with nested factors using Graph Builder, displaying standard deviation charts and utilizing range style for area elements.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 389, 343 ),
    Show Control Panel( 0 ),
    Show Legend( 0 ),
    Variables( X( :age ), Y( :height ), Y( :weight, Position( 1 ) ) ),
    Elements( Area( X, Y( 1 ), Y( 2 ), Legend( 4 ), Area Style( "Range" ) ) )
);
Graph Builder(
    Size( 546, 431 ),
    Show Control Panel( 0 ),
    Legend Position( "Bottom" ),
    Variables( X( :sex ), Y( :height ), Y( :weight, Position( 1 ) ) ),
    Elements( Area( X, Y( 1 ), Y( 2 ), Legend( 7 ), Area Style( "Range" ), Summary Statistic( "% of Total" ) ) )
);

Code Explanation:

1. Open data table.
2. Create first Graph Builder.
3. Set graph size.
4. Hide control panel.
5. Hide legend.
6. Define X and Y variables.
7. Add area element with range style.
8. Create second Graph Builder.
9. Set graph size.
10. Hide control panel.
11. Position legend at bottom.
12. Define X and Y variables.
13. Add area element with range style.
14. Use summary statistic "% of Total".

Example 582

Summary: Creates variability charts with nested factors using Graph Builder, displaying standard deviation charts and customizing legend properties.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 389, 343 ),
    Show Control Panel( 0 ),
    Show Legend( 0 ),
    Variables( X( :age ), Y( :height ), Y( :weight, Position( 1 ) ) ),
    Elements( Area( X, Y( 1 ), Y( 2 ), Legend( 4 ), Area Style( "Range" ) ) )
);
Graph Builder(
    Size( 546, 431 ),
    Show Control Panel( 0 ),
    Legend Position( "Bottom" ),
    Variables( X( :sex ), Y( :height ), Y( :weight, Position( 1 ) ) ),
    Elements( Area( X, Y( 1 ), Y( 2 ), Legend( 7 ), Area Style( "Range" ), Summary Statistic( "% of Total" ) ) )
);
Open("data_table.jmp");
Graph Builder(
    Size( 340, 298 ),
    Show Control Panel( 0 ),
    Variables( X( :ID ), Y( :hist0 ), Y( :hist1, Position( 1 ) ), Y( :hist3, Position( 1 ) ) ),
    Elements( Area( X, Y( 1 ), Y( 2 ), Y( 3 ), Legend( 5 ), Area Style( "Range" ), Summary Statistic( "Sum" ) ) ),
    SendToReport( Dispatch( {}, "400", ScaleBox, {Legend Model( 5, Properties( 0, {Line Color( 0 )} ) )} ) )
);

Code Explanation:

1. Open data table;
2. Create Graph Builder window.
3. Set window size.
4. Hide control panel.
5. Hide legend.
6. Define X and Y variables.
7. Add area element with range style.
8. Create second Graph Builder window.
9. Set window size.
10. Hide control panel.
11. Set legend position.
12. Define X and Y variables.
13. Add area element with range and percentage summary.
14. Open data table;
15. Create third Graph Builder window.
16. Set window size.
17. Hide control panel.
18. Define multiple X and Y variables.
19. Add area element with range and sum summary.
20. Customize legend properties.

Example 583

Summary: Creates two variability charts with nested factors using operator and part configurations, displaying standard deviation charts.

Code:

dt = Open("data_table.jmp");
gb1 = Graph Builder(
    Size( 534, 447 ),
    Show Control Panel( 0 ),
    Variables( X( :age ), Y( :height ), Y( :weight, Position( 1 ) ) ),
    Elements( Area( X, Y( 1 ), Y( 2 ), Legend( 4 ), Area Style( "Range" ) ) ),
    SendToReport(
        Dispatch( {}, "400", ScaleBox,
            {Legend Model( 4, Properties( 0, {Fill Color( 73 )} ), Properties( 1, {Line Width( 5 )} ), Properties( 2, {Line Width( 5 )} ) )
            }
        )
    )
);
gb2 = Graph Builder(
    Size( 534, 447 ),
    Show Control Panel( 0 ),
    Variables( X( :age ), Y( :height ), Y( :weight, Position( 1 ) ) ),
    Elements( Area( X, Y( 1 ), Y( 2 ), Legend( 4 ), Area Style( "Range" ) ) ),
    SendToReport( Dispatch( {}, "400", ScaleBox, {Legend Model( 4, Properties( 0, {Line Width( 0 ), Fill Color( 73 )} ) )} ) )
);

Code Explanation:

1. Open data table;
2. Create Graph Builder object gb1.
3. Set graph size to 534x447.
4. Hide control panel.
5. Assign X: age, Y1: height, Y2: weight.
6. Add area element with range style.
7. Customize legend properties for gb1.
8. Create another Graph Builder object gb2.
9. Set graph size to 534x447.
10. Hide control panel for gb2.

Example 584

Summary: Creates a variability chart with nested factors using operator and part configurations, displaying standard deviation charts in JMP.

Code:

dt = Open("data_table.jmp") << Graph Builder(
    Size( 418, 355 ),
    Show Control Panel( 0 ),
    Error Bar Offset( 0.03913 ),
    Variables( X( :Clarity ), Y( :Carat Weight, Side( "Right" ) ), Y( :Depth, Position( 1 ) ), Y( :Table, Position( 1 ) ) ),
    Elements(
        Area( X, Y( 1 ), Legend( 10 ), Summary Statistic( "Range" ) ),
        Area( X, Y( 2 ), Y( 3 ), Legend( 9 ), Summary Statistic( "Range" ) )
    ),
    SendToReport(
        Dispatch( {}, "400", ScaleBox, {Legend Model( 10, Properties( 0, {Fill Color( 41 )}, Item ID( "Range(Carat Weight)", 1 ) ) )} ),
        Dispatch( {}, "400", LegendBox, {Legend Position( {10, [2, -3], 9, [0, 1, -3, -3]} )} )
    )
);

Code Explanation:

1. Open data table;
2. Create Graph Builder window.
3. Set window size to 418x355.
4. Hide control panel.
5. Set error bar offset.
6. Define variables: X(Clarity), Y(Carat Weight, Right), Y(Depth, Position 1), Y(Table, Position 1).
7. Add first area element for Carat Weight.
8. Add second area element for Depth and Table.
9. Customize legend for Carat Weight range.
10. Position legends for both ranges.

Example 585

Summary: Creates a variability chart with nested factors using operator and part configurations, displaying standard deviation charts.

Code:

dt under test = Open("data_table.jmp");
obj = Graph Builder(
    Show Control Panel( 0 ),
    Variables( X( :Day of Week ), Y( :Bill Amount ), Y( :Tip Amount, Position( 1 ) ) ),
    Elements( Area( X, Y( 1 ), Y( 2 ), Legend( 7 ) ) ),
    SendToReport(
        Dispatch( {}, "Day of Week", ScaleBox, {Min( 0.024896265560166 ), Max( 4.02489626556017 ), Inc( 1 ), Minor Ticks( 0 )} ),
        Dispatch( {}, "Bill Amount", ScaleBox, {Min( 0.215925655976676 ), Max( 42.5373542274052 ), Inc( 5 ), Minor Ticks( 0 )} ),
        Dispatch( {}, "Graph Builder", FrameBox, {Background Color( 32 )} )
    )
);

Code Explanation:

1. Open data table;
2. Create Graph Builder object.
3. Hide control panel.
4. Set X variable.
5. Set first Y variable.
6. Set second Y variable.
7. Add area element.
8. Configure Day of Week scale.
9. Configure Bill Amount scale.
10. Set background color.

Example 586

Summary: Creates a stacked area chart with summarized data, displaying standard deviation charts using Graph Builder in JMP.

Code:

Open("data_table.jmp");
Graph Builder(
    Show Control Panel( 0 ),
    Variables( X( :age ), Y( :height ) ),
    Elements( Area( X, Y, Legend( 2 ), Area Style( "Stacked" ), Summary Statistic( "Sum" ) ) ),
    SendToReport(
        Dispatch( {}, "400", ScaleBox,
            {Legend Model(
                2,
                Properties( 0, {Fill Color( 70 )} ),
                Properties( 1, {Line Style( "Dotted" ), Line Width( 2 )} ),
                Base( 1, 2, 0 )
            )}
        )
    )
);

Code Explanation:

1. Open data table;
2. Launch Graph Builder.
3. Hide control panel.
4. Set X variable to age.
5. Set Y variable to height.
6. Add area element.
7. Stack areas.
8. Summarize data.
9. Customize legend fill color.
10. Customize legend line style and width.

Example 587

Summary: Creates a stacked area chart with nested factors using Graph Builder, displaying mean values and standard deviation charts.

Code:

Open("data_table.jmp");
Graph Builder(
    Show Control Panel( 0 ),
    Variables( X( :age ), Y( :weight ), Y( :height, Position( 1 ), Size( 37 ) ) ),
    Elements( Area( X, Y( 1 ), Y( 2 ), Legend( 2 ), Area Style( "Stacked" ), Summary Statistic( "Mean" ) ) ),
    SendToReport(
        Dispatch( {}, "400", ScaleBox,
            {Legend Model(
                2,
                Properties( 2, {Line Color( 0 ), Line Style( "Dotted" ), Line Width( 2 )} ),
                Properties( 3, {Line Color( 0 ), Line Style( "Dashed" ), Line Width( 2 )} )
            )}
        )
    )
);

Code Explanation:

1. Open data table;
2. Create Graph Builder window.
3. Hide control panel.
4. Set X variable to age.
5. Set first Y variable to weight.
6. Set second Y variable to height.
7. Position height on left axis.
8. Adjust height axis size.
9. Add stacked area element.
10. Apply dotted and dashed styles to legend items.

Example 588

Summary: Creates a stacked area chart with sum statistics, displaying nested factors using Graph Builder in JMP.

Code:

Open("data_table.jmp");
Graph Builder(
    Show Control Panel( 0 ),
    Variables( X( :age, Size( 18 ) ), Y( :height, Size( 37 ) ) ),
    Elements( Area( X, Y, Legend( 2 ), Area Style( "Stacked" ), Summary Statistic( "Sum" ) ) ),
    SendToReport( Dispatch( {}, "400", ScaleBox, {Legend Model( 2, Properties( 0, {Fill Color( 76 )} ) )} ) )
);

Code Explanation:

1. Open data_table data
2. Launch Graph Builder.
3. Hide control panel.
4. Set X variable: age.
5. Set Y variable: height.
6. Add stacked area element.
7. Summarize data by sum.
8. Dispatch report.
9. Access scale box.
10. Change fill color to 76.

Example 589

Summary: Creates a stacked area chart to visualize the relationship between age and height, utilizing Graph Builder's Variables and Elements syntax.

Code:

dt = Open("data_table.jmp");
obj = Graph Builder(
    Show Control Panel( 0 ),
    Variables( X( :age ), Y( :height ) ),
    Elements( Area( X, Y, Legend( 2 ), Area Style( "Stacked" ), Summary Statistic( "Sum" ) ) ),
    SendToReport( Dispatch( {}, "400", ScaleBox, {Legend Model( 2, Properties( 1, {Line Color( 3 ), Line Width( 2 )} ) )} ) )
);

Code Explanation:

1. Open data table.
2. Create Graph Builder object.
3. Hide control panel.
4. Set X variable to age.
5. Set Y variable to height.
6. Add stacked area element.
7. Summarize data using sum.
8. Send report to dispatch.
9. Access scale box.
10. Modify legend properties.

Example 590

Summary: Creates a variability chart with nested factors using Graph Builder, displaying standard deviation charts and utilizing operator and part configurations.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 502, 450 ),
    Show Control Panel( 0 ),
    Variables( X( :sex ), Overlay( :age ) ),
    Elements( Area( X, Legend( 10 ), Summary Statistic( "% of Total" ) ) )
);

Code Explanation:

1. Open data table;
2. Create Graph Builder window.
3. Set window size.
4. Hide control panel.
5. Define X variable.
6. Define overlay variable.
7. Add area element.
8. Set legend position.
9. Use percentage of total summary.
10. Display graph.

Example 591

Summary: Creates a graph builder object to visualize nested factors using operator and part configurations, with standard deviation charts displayed.

Code:

Open("data_table.jmp") << Graph Builder(
    Size( 534, 464 ),
    Show Control Panel( 0 ),
    Include Missing Categories( 1 ),
    Variables( X( :Causes ), Y( :Time Cycles ), Overlay( :Censor ) ),
    Elements( Area( X, Y, Legend( 8 ) ) )
);

Code Explanation:

1. Open data file.
2. Create graph builder object.
3. Set window size.
4. Hide control panel.
5. Include missing categories.
6. Define X variable.
7. Define Y variable.
8. Define overlay variable.
9. Add area element.
10. Display graph.

Example 592

Summary: Creates a variability chart with nested factors using Graph Builder, displaying standard deviation charts and configuring legend position.

Code:

Open("data_table.jmp") << Graph Builder(
    Size( 400, 342 ),
    Show Control Panel( 0 ),
    Variables( X( :height ), Y( :weight ), Overlay( :sex ) ),
    Elements( Area( X, Y, Legend( 2 ), Missing Factors( "Treat as Missing" ), Missing Values( "No Connection" ) ) )
);

Code Explanation:

1. Open data table;
2. Launch Graph Builder.
3. Set window size.
4. Hide control panel.
5. Define X variable.
6. Define Y variable.
7. Set overlay variable.
8. Add area element.
9. Configure legend position.
10. Handle missing factors.

Example 593

Summary: Creates a stacked area chart with sum statistics for age and height variables, utilizing Graph Builder to visualize data from an open JMP data table.

Code:

Open("data_table.jmp");
Graph Builder(
    Show Control Panel( 0 ),
    Variables( X( :age ), Y( :height ) ),
    Elements( Area( X, Y, Legend( 2 ), Area Style( "Stacked" ), Summary Statistic( "Sum" ) ) ),
    SendToReport( Dispatch( {}, "400", ScaleBox, {Legend Model( 2, Properties( 1, {Line Color( 0 ), Line Width( 3 )} ) )} ) )
);

Code Explanation:

1. Open data table.
2. Launch Graph Builder.
3. Hide control panel.
4. Set X variable: age.
5. Set Y variable: height.
6. Add area element.
7. Stack area elements.
8. Summarize data by sum.
9. Customize legend properties.
10. Set line width to 3.

Example 594

Summary: Creates a stacked area chart with sum statistics to visualize the relationship between age and height, utilizing Graph Builder.

Code:

dt = Open("data_table.jmp");
obj = Graph Builder(
    Show Control Panel( 0 ),
    Variables( X( :age ), Y( :height ) ),
    Elements( Area( X, Y, Legend( 2 ), Area Style( "Stacked" ), Summary Statistic( "Sum" ) ) ),
    SendToReport( Dispatch( {}, "400", ScaleBox, {Legend Model( 2, Properties( 0, {Transparency( 0.7 )} ) )} ) )
);

Code Explanation:

1. Open data table;
2. Create Graph Builder object.
3. Hide control panel.
4. Set X variable to age.
5. Set Y variable to height.
6. Add area element.
7. Stack area style.
8. Summarize data by sum.
9. Adjust legend properties.
10. Set transparency to 0.7.

Example 595

Summary: Creates a variability chart with nested factors using operator and part configurations, displaying standard deviation charts in Graph Builder.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 327, 322 ),
    Show Control Panel( 0 ),
    Legend Position( "Bottom" ),
    Variables( X( :Cut ), Y( :Carat Weight ), Y( :Depth, Position( 1 ) ), Y( :Table, Position( 1 ) ), Color( :Cut ), Color( :Report ) ),
    Elements( Area( X, Y( 3 ), Y( 2 ), Y( 1 ), Legend( 10 ) ) ),
    SendToReport(
        Dispatch( {}, "400", ScaleBox, {Legend Model( 10, Properties( 0, {Transparency( 0.2 )}, Item ID( "Mean(Table)", 1 ) ) )} ),
        Dispatch( {}, "400", LegendBox, {Orientation( "Vertical" ), Set Wrap( 3 )} )
    )
);

Code Explanation:

1. Open data table;
2. Create Graph Builder window.
3. Set window size.
4. Hide control panel.
5. Place legend at bottom.
6. Define X variable: Cut.
7. Define Y variables: Carat Weight, Depth, Table.
8. Define color variables: Cut, Report.
9. Add area element.
10. Adjust transparency and legend properties.

Example 596

Summary: Creates a Graph Builder window with nested factors, displaying standard deviation charts for height and weight based on age and sex.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 534, 448 ),
    Show Control Panel( 0 ),
    Show Footer( 0 ),
    Variables( X( :age ), X( :sex ), Y( :height ), Y( :weight, Position( 1 ) ) ),
    Elements( Position( 1, 1 ), Area( X, Y( 1 ), Y( 2 ), Legend( 5 ) ) ),
    Elements( Position( 2, 1 ), Area( X, Y( 1 ), Y( 2 ), Legend( 4 ) ) )
);

Code Explanation:

1. Open data table.
2. Create new Graph Builder window.
3. Set window size.
4. Hide control panel.
5. Hide footer.
6. Define X variables: age, sex.
7. Define Y variables: height, weight.
8. Add first area element.
9. Position first area element.
10. Add second area element.

Example 597

Summary: Creates a variability chart with nested factors using operator and part configurations, displaying standard deviation charts in JMP.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 546, 431 ),
    Show Control Panel( 0 ),
    Variables( X( :sex ), Y( :height ), Y( :weight, Position( 1 ) ) ),
    Elements( Area( X, Y( 1 ), Y( 2 ), Legend( 7 ), Area Style( "Range" ), Summary Statistic( "% of Total" ) ) )
);

Code Explanation:

1. Open data table.
2. Create Graph Builder window.
3. Set window size.
4. Hide control panel.
5. Define X variable.
6. Define first Y variable.
7. Define second Y variable.
8. Add area element.
9. Specify X axis.
10. Specify Y1 axis.

Example 598

Summary: Creates a variability chart with nested factors using Graph Builder, displaying overlaid area plots and box plots.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 425, 305 ),
    Show Control Panel( 0 ),
    Legend Position( "Bottom" ),
    X Group Edge( "Top" ),
    Variables( X( :Carat Weight ), Y( :Table ), Y( :Cut ) ),
    Elements( Position( 1, 1 ), Area( X, Y, Legend( 21 ), Area Style( "Overlaid" ) ) ),
    Elements( Position( 1, 2 ), Box Plot( X, Y, Legend( 23 ), Outliers( 0 ) ) ),
    SendToReport( Dispatch( {}, "400", LegendBox, {Orientation( "Vertical" ), Set Wrap( 3 )} ) )
);

Code Explanation:

1. Open data table;
2. Create Graph Builder window.
3. Set size 425x305.
4. Hide control panel.
5. Place legend at bottom.
6. Position X group edge at top.
7. Assign Carat Weight to X.
8. Assign Table to first Y.
9. Assign Cut to second Y.
10. Add overlaid area plot.
11. Add box plot below.
12. Configure legend orientation and wrap.

Example 599

Summary: Creates a variability chart with nested factors using operator and part configurations, displaying standard deviation charts for HDL and LDL levels in a Graph Builder window.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 307, 342 ),
    Show Control Panel( 0 ),
    Variables( X( :Age ), Y( :HDL ), Y( :LDL, Position( 1 ) ) ),
    Elements(
        Bar( X, Y( 1 ), Y( 2 ), Legend( 5 ), Bar Style( "Range" ), Summary Statistic( "Std Dev" ) ),
        Area( X, Y( 1 ), Y( 2 ), Legend( 6 ), Area Style( "Range" ), Summary Statistic( "Std Dev" ) )
    ),
    Local Data Filter( Mode( Include( 0 ) ), Add Filter( columns( :Name( "Exercise Freq" ) ) ) ),
    SendToReport(
        Dispatch( {}, "400", ScaleBox,
            {Legend Model( 5, Properties( 0, {Transparency( 0.5 )}, Item ID( "Std Dev(HDL)..Std Dev(LDL)", 1 ) ) ),
            Legend Model( 6, Properties( 0, {Fill Color( 23 ), Transparency( 0.3 )}, Item ID( "Std Dev(HDL)..Std Dev(LDL)", 1 ) ) )}
        )
    )
);

Code Explanation:

1. Open data table;
2. Create Graph Builder window.
3. Set window size.
4. Hide control panel.
5. Define X and Y variables.
6. Add bar element.
7. Add area element.
8. Enable local data filter.
9. Customize legend properties.
10. Customize legend properties.

Example 600

Summary: Creates a variability chart with nested factors using Graph Builder, displaying standard deviation charts for height and weight.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 417, 329 ),
    Show Control Panel( 0 ),
    Variables( X( :age ), Y( :height ), Y( :weight, Position( 1 ), Side( "Right" ) ) ),
    Elements( Area( X, Y( 1 ), Legend( 4 ) ), Area( X, Y( 2 ), Legend( 6 ) ) )
);

Code Explanation:

1. Open data table;
2. Create Graph Builder window.
3. Set window size.
4. Hide control panel.
5. Assign X variable.
6. Assign first Y variable.
7. Assign second Y variable.
8. Add area element for first Y.
9. Add area element for second Y.
10. Display graph.

Example 601

Summary: Creates a variability chart with nested factors using Graph Builder, displaying standard deviation charts for height and weight while overlaying by age.

Code:

Open("data_table.jmp") << Graph Builder(
    Size( 351, 340 ),
    Show Control Panel( 0 ),
    Variables( X( :age ), Y( :height ), Y( :weight, Position( 1 ), Side( "Right" ) ), Overlay( :age ) ),
    Elements( Area( X, Y( 1 ), Overlay( 0 ), Legend( 4 ) ), Bar( X, Y( 2 ), Legend( 3 ) ) ),
    SendToReport(
        Dispatch( {}, "height", ScaleBox, {Min( 0 ), Max( 144.666666666667 ), Inc( 20 ), Minor Ticks( 0 )} ),
        Dispatch( {}, "weight", ScaleBox, {Min( -166.687001682411 ), Max( 158.633681437995 ), Inc( 50 ), Minor Ticks( 0 )} )
    )
);

Code Explanation:

1. Open data table;
2. Create Graph Builder window.
3. Set graph size to 351x340.
4. Hide control panel.
5. Define X and Y variables.
6. Add weight variable on right side.
7. Overlay by age.
8. Add area element for height.
9. Add bar element for weight.
10. Adjust height scale settings.
11. Adjust weight scale settings.

Example 602

Summary: Creates a variability chart with nested factors using operator and part configurations, displaying standard deviation charts in Graph Builder.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 418, 355 ),
    Show Control Panel( 0 ),
    Error Bar Offset( 0.03913 ),
    Variables( X( :Clarity ), Y( :Carat Weight, Side( "Right" ) ), Y( :Depth, Position( 1 ) ), Y( :Table, Position( 1 ) ) ),
    Elements(
        Area( X, Y( 1 ), Legend( 10 ), Summary Statistic( "Range" ) ),
        Area( X, Y( 2 ), Y( 3 ), Legend( 9 ), Summary Statistic( "Range" ) )
    ),
    SendToReport(
        Dispatch( {}, "400", ScaleBox, {Legend Model( 10, Properties( 0, {Fill Color( 76 )}, Item ID( "Range(Carat Weight)", 1 ) ) )} ),
        Dispatch( {}, "400", LegendBox, {Legend Position( {10, [2, -3], 9, [0, 1, -3, -3]} )} )
    )
);

Code Explanation:

1. Open data table;
2. Create Graph Builder.
3. Set size to 418x355.
4. Hide control panel.
5. Set error bar offset.
6. Define X and Y variables.
7. Add first area element.
8. Add second area element.
9. Customize legend for Carat Weight.
10. Position legends.

Example 603

Summary: Creates a variability chart with nested factors using operator and part configurations, displaying standard deviation charts in Graph Builder.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 532, 466 ),
    Show Control Panel( 0 ),
    Include Missing Categories( 1 ),
    Variables(
        X( :drug ),
        Y( :hist0 ),
        Y( :hist1, Position( 1 ) ),
        Y( :hist3, Position( 1 ) ),
        Y( :hist5, Position( 1 ) ),
        Overlay( :diff )
    ),
    Elements( Area( X, Y( 1 ), Y( 2 ), Y( 3 ), Y( 4 ), Legend( 12 ) ) ),
    Local Data Filter( Show Modes( 1 ), Mode( Include( 0 ) ), Inverse( 1 ), Add Filter( columns( :dep1 ) ) )
);

Code Explanation:

1. Open data_table data
2. Launch Graph Builder.
3. Set window size.
4. Hide control panel.
5. Include missing categories.
6. Assign X variable: drug.
7. Assign Y variables: hist0, hist1, hist3, hist5.
8. Overlay by diff variable.
9. Add area element with multiple Ys.
10. Create local data filter for dep1, inverse mode.

Example 604

Summary: Creates a Graph Builder window with nested factors using operator and part configurations, displaying standard deviation charts.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 694, 393 ),
    Show Control Panel( 0 ),
    Variables( X( :age ), X( :weight ), Y( :height ), Group X( :sex ) ),
    Elements( Position( 1, 1 ), Area( X, Y, Legend( 12 ) ) ),
    Elements( Position( 2, 1 ), Area( X, Y, Legend( 13 ) ) )
);

Code Explanation:

1. Open data table;
2. Create Graph Builder window.
3. Set window size to 694x393.
4. Hide control panel.
5. Define X variables: age, weight.
6. Define Y variable: height.
7. Group X by sex.
8. Add first area element.
9. Position first element at (1,1).
10. Add second area element.

Example 605

Summary: Creates a variability chart with nested factors using Graph Builder, displaying standard deviation charts and overlaying by sex.

Code:

Open("data_table.jmp");
:sex[1] = "";
Graph Builder(
    Size( 485, 325 ),
    Show Control Panel( 0 ),
    Include Missing Categories( 1 ),
    Variables( X( :height ), Overlay( :sex ) ),
    Elements( Area( X, Legend( 18 ) ) )
);

Code Explanation:

1. Open data table;
2. Set first sex value to empty.
3. Launch Graph Builder.
4. Set window size.
5. Hide control panel.
6. Include missing categories.
7. Assign height to X-axis.
8. Overlay by sex.
9. Add area element.
10. Display legend.

Example 606

Summary: Creates a variability chart with nested factors using Graph Builder, displaying an area element with a legend and '% of Total' summary statistic.

Code:

Open("data_table.jmp");
Graph Builder( Variables( X( :sex ), Overlay( :age ) ), Elements( Area( X, Legend( 3 ), Summary Statistic( "% of Total" ) ) ) );

Code Explanation:

1. Open data table.
2. Launch Graph Builder.
3. Set X variable to sex.
4. Set overlay variable to age.
5. Add Area element.
6. Configure legend for area.
7. Use "% of Total" summary statistic.
8. Display graph.

Example 607

Summary: Creates a variability chart with nested factors using Graph Builder, displaying standard deviation charts and configuring area style and summary statistics.

Code:

Open("data_table.jmp") << Graph Builder(
    Size( 422, 453 ),
    Show Control Panel( 0 ),
    Variables( X( :Y ), Y( :Pattern ), Overlay( :Brkfast ) ),
    Elements( Area( X, Y, Legend( 10 ), Area Style( "Overlaid" ), Summary Statistic( "Sum" ), Missing Factors( "Treat as Zero" ) ) )
);

Code Explanation:

1. Open data table;
2. Launch Graph Builder.
3. Set window size.
4. Hide control panel.
5. Define X variable.
6. Define Y variable.
7. Define overlay variable.
8. Add area element.
9. Set legend position.
10. Configure area style and summary statistic.

Example 608

Summary: Creates a variability chart with nested factors using Graph Builder, displaying standard deviation charts and configuring legend position.

Code:

Open("data_table.jmp");
Graph Builder( Size( 359, 276 ), Show Control Panel( 0 ), Variables( X( :height ), Y( :age ) ), Elements( Area( X, Y, Legend( 4 ) ) ) );

Code Explanation:

1. Open data table;
2. Launch Graph Builder.
3. Set window size.
4. Hide control panel.
5. Assign X variable.
6. Assign Y variable.
7. Add area element.
8. Configure legend position.

Example 609

Summary: Creates a variability chart with nested factors using Graph Builder, displaying standard deviation charts and percentage of total for each group.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 526, 492 ),
    Show Control Panel( 0 ),
    Variables( X( :sex ), Wrap( :age ) ),
    Elements( Area( X, Legend( 12 ), Summary Statistic( "% of Total" ) ) )
);

Code Explanation:

1. Open data table;
2. Launch Graph Builder.
3. Set window size.
4. Hide control panel.
5. Assign X variable.
6. Wrap by age.
7. Add area element.
8. Use summary statistic.
9. Display percentage of total.
10. Create legend.

Example 610

Summary: Creates two variability charts with nested factors using operator and part configurations, displaying standard deviation charts for 'Good' and 'Very Good' cuts.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 406, 316 ),
    Show Control Panel( 0 ),
    Variables( X( :Report ), Y( :Price ), Color( :Color ) ),
    Elements( Area( X, Y, Legend( 11 ) ) ),
    Local Data Filter(
        Width( 160 ),
        Mode( Include( 0 ) ),
        Add Filter( columns( :Cut ), Where( :Cut == "Good" ), Display( :Cut, N Items( 3 ) ) )
    )
);
Graph Builder(
    Size( 406, 316 ),
    Show Control Panel( 0 ),
    Variables( X( :Report ), Y( :Price ), Color( :Color ) ),
    Elements( Area( X, Y, Legend( 11 ) ) ),
    Local Data Filter(
        Width( 160 ),
        Mode( Include( 0 ) ),
        Add Filter( columns( :Cut ), Where( :Cut == "Very Good" ), Display( :Cut, N Items( 3 ) ) )
    )
);

Code Explanation:

1. Open data table;
2. Create first Graph Builder.
3. Set size to 406x316.
4. Hide control panel.
5. Set X variable to Report.
6. Set Y variable to Price.
7. Set Color variable to Color.
8. Add area element with legend.
9. Add local data filter for Cut.
10. Create second Graph Builder with similar settings but filter for "Very Good" Cut.

Example 611

Summary: Creates a variability chart with nested factors using Graph Builder, displaying standard deviation charts and utilizing transformed columns for X, Y, and Color variables.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 545, 437 ),
    Show Control Panel( 0 ),
    Variables(
        X( Transform Column( "Rank[sex]", Character, Formula( Char( Col Rank( :sex ) ) ) ) ),
        Y( Transform Column( "height^3", Format( "Fixed Dec", 5, 0 ), Formula( :height ^ 3 ) ) ),
        Color( Transform Column( "Rank[sex]", Character, Formula( Char( Col Rank( :sex ) ) ) ) )
    ),
    Elements( Area( X, Y, Legend( 16 ) ) )
);

Code Explanation:

1. Open data table;
2. Create new Graph Builder window.
3. Set window size.
4. Hide control panel.
5. Define X variable with transformed column.
6. Define Y variable with transformed column.
7. Define Color variable with transformed column.
8. Add area element to graph.
9. Set legend for area element.
10. Display graph.

Example 612

Summary: Creates a variability chart with nested factors using operator and part configurations, displaying standard deviation charts in Graph Builder.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 570, 499 ),
    Show Control Panel( 0 ),
    Include Missing Categories( 1 ),
    Variables( X( :Position ), Y( :Weight ), Group Y( :Bench ), Overlay( :Neck ) ),
    Elements( Area( X, Y, Legend( 17 ) ) )
);

Code Explanation:

1. Open data table;
2. Launch Graph Builder.
3. Set window size to 570x499.
4. Hide control panel.
5. Include missing categories.
6. Assign Position to X-axis.
7. Assign Weight to Y-axis.
8. Group Y by Bench.
9. Overlay Neck variable.
10. Add area element with legend.

Example 613

Summary: Creates a graph builder window with variables X=age and Y=weight, displaying an area element to visualize data.

Code:

dt = Open("data_table.jmp");
dt << select where( :age == 14, current selection( "Restrict" ) );
dt << hide;
dt << clear select;
Graph Builder( Size( 508, 382 ), Show Control Panel( 0 ), Variables( X( :age ), Y( :weight ) ), Elements( Area( X, Y, Legend( 7 ) ) ) );

Code Explanation:

1. Open data table.
2. Select age 14 rows.
3. Restrict selection to visible rows.
4. Hide selected rows.
5. Clear row selection.
6. Create Graph Builder window.
7. Set window size.
8. Hide control panel.
9. Assign variables: X=age, Y=weight.
10. Add area element to graph.

Example 614

Summary: Creates six area graphs with varying configurations to visualize relationships between height and age, overlaying or grouping by sex.

Code:

Open("data_table.jmp");
Graph Builder( Size( 359, 276 ), Show Control Panel( 0 ), Variables( X( :height ), Y( :age ) ), Elements( Area( X, Y, Legend( 4 ) ) ) );
Graph Builder(
    Size( 359, 276 ),
    Show Control Panel( 0 ),
    Variables( X( :height ), Y( :age ), Overlay( :sex ) ),
    Elements( Area( X, Y, Legend( 4 ) ) )
);
Graph Builder(
    Size( 359, 320 ),
    Show Control Panel( 0 ),
    Variables( X( :height ), Y( :age ), Wrap( :sex ) ),
    Elements( Area( X, Y, Legend( 4 ) ) )
);
Graph Builder(
    Size( 403, 276 ),
    Show Control Panel( 0 ),
    Variables( X( :height ), Y( :age ), Group Y( :sex ) ),
    Elements( Area( X, Y, Legend( 4 ) ) )
);
Graph Builder(
    Size( 359, 276 ),
    Show Control Panel( 0 ),
    Variables( X( :height ), Y( :age ), Color( :sex ) ),
    Elements( Area( X, Y, Legend( 4 ) ) )
);

Code Explanation:

1. Open data table.
2. Create area graph with height vs age.
3. Create area graph with height vs age, overlay by sex.
4. Create area graph with height vs age, wrap by sex.
5. Create area graph with height vs age, group Y by sex.
6. Create area graph with height vs age, color by sex.

Example 615

Summary: Creates multiple area graphs with nested factors using Graph Builder, showcasing different visualization configurations for height and age variables.

Code:

Open("data_table.jmp");
Graph Builder( Size( 359, 276 ), Show Control Panel( 0 ), Variables( X( :height ), Y( :age ) ), Elements( Area( X, Y, Legend( 4 ) ) ) );
Graph Builder(
    Size( 359, 276 ),
    Show Control Panel( 0 ),
    Variables( X( :height ), Y( :age ), Overlay( :sex ) ),
    Elements( Area( X, Y, Legend( 4 ) ) )
);
Graph Builder(
    Size( 359, 320 ),
    Show Control Panel( 0 ),
    Variables( X( :height ), Y( :age ), Wrap( :sex ) ),
    Elements( Area( X, Y, Legend( 4 ) ) )
);
Graph Builder(
    Size( 403, 276 ),
    Show Control Panel( 0 ),
    Variables( X( :height ), Y( :age ), Group Y( :sex ) ),
    Elements( Area( X, Y, Legend( 4 ) ) )
);
Graph Builder(
    Size( 359, 276 ),
    Show Control Panel( 0 ),
    Variables( X( :height ), Y( :age ), Color( :sex ) ),
    Elements( Area( X, Y, Legend( 4 ) ) )
);
Graph Builder(
    Size( 359, 598 ),
    Show Control Panel( 0 ),
    Variables( X( :height ), Y( :age ), Page( :sex ) ),
    Elements( Area( X, Y, Legend( 4 ) ) )
);

Code Explanation:

1. Open data table.
2. Create area graph with height and age.
3. Add sex overlay to area graph.
4. Wrap sex variable in area graph.
5. Group Y by sex in area graph.
6. Color by sex in area graph.
7. Page by sex in area graph.

Example 616

Summary: Creates a graph builder window with a nested factors variability chart, filtering data by sex and displaying standard deviation charts.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 411, 330 ),
    Show Control Panel( 0 ),
    Show Legend( 0 ),
    Variables( X( :age ), Y( :height ) ),
    Elements( Area( X, Y, Legend( 28 ) ) ),
    Local Data Filter( Mode( Include( 0 ) ), Add Filter( columns( :sex ), Where( :sex == "M" ) ) )
);

Code Explanation:

1. Open data table;
2. Create Graph Builder window.
3. Set graph size.
4. Hide control panel.
5. Hide legend.
6. Define X and Y variables.
7. Add area element.
8. Set legend position.
9. Add local data filter.
10. Filter data by sex.

Example 617

Summary: Creates three Graph Builder windows with nested factors, displaying standard deviation charts and area elements with varying styles.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 837, 289 ),
    Show Control Panel( 0 ),
    Fit to Window,
    Variables( X( :height ), Y( :weight ), Overlay( :sex ) ),
    Elements( Area( X, Y, Legend( 9 ), Area Style( "Range" ) ) )
);
Graph Builder(
    Size( 837, 289 ),
    Show Control Panel( 0 ),
    Fit to Window,
    Variables( X( :height ), Y( :weight ), Overlay( :sex ) ),
    Elements( Area( X, Y, Legend( 9 ) ) )
);
Graph Builder(
    Size( 837, 289 ),
    Show Control Panel( 0 ),
    Fit to Window,
    Variables( X( :height ), Y( :weight ), Overlay( :sex ) ),
    Elements( Area( X, Y, Legend( 9 ), Area Style( "Overlaid" ) ) )
);

Code Explanation:

1. Open data table;
2. Create first Graph Builder window.
3. Set window size.
4. Hide control panel.
5. Fit graph to window.
6. Define variables: X=height, Y=weight, Overlay=sex.
7. Add area element with range style.
8. Create second Graph Builder window.
9. Set window size.
10. Hide control panel.
11. Fit graph to window.
12. Define variables: X=height, Y=weight, Overlay=sex.
13. Add area element without specific style.
14. Create third Graph Builder window.
15. Set window size.
16. Hide control panel.
17. Fit graph to window.
18. Define variables: X=height, Y=weight, Overlay=sex.
19. Add area element with overlaid style.

Example 618

Summary: Creates four Graph Builder windows with varying area element styles to visualize relationships between height, weight, and sex.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 837, 289 ),
    Show Control Panel( 0 ),
    Fit to Window,
    Variables( X( :height ), Y( :weight ), Overlay( :sex ) ),
    Elements( Area( X, Y, Legend( 9 ), Area Style( "Range" ) ) )
);
Graph Builder(
    Size( 837, 289 ),
    Show Control Panel( 0 ),
    Fit to Window,
    Variables( X( :height ), Y( :weight ), Overlay( :sex ) ),
    Elements( Area( X, Y, Legend( 9 ) ) )
);
Graph Builder(
    Size( 837, 289 ),
    Show Control Panel( 0 ),
    Fit to Window,
    Variables( X( :height ), Y( :weight ), Overlay( :sex ) ),
    Elements( Area( X, Y, Legend( 9 ), Area Style( "Overlaid" ) ) )
);
Graph Builder(
    Size( 837, 289 ),
    Show Control Panel( 0 ),
    Variables( X( :height ), Y( :weight ), Overlay( :sex ) ),
    Elements( Area( X, Y, Legend( 9 ), Area Style( "Stacked Range" ) ) )
);

Code Explanation:

1. Open data table.
2. Create first Graph Builder window.
3. Set window size.
4. Hide control panel.
5. Fit to window.
6. Define variables: X(height), Y(weight), Overlay(sex).
7. Add area element with range style.
8. Create second Graph Builder window.
9. Repeat settings from steps 3-7.
10. Add area element without style specification.
11. Create third Graph Builder window.
12. Repeat settings from steps 3-7.
13. Add area element with overlaid style.
14. Create fourth Graph Builder window.
15. Repeat settings from steps 3-7.
16. Add area element with stacked range style.

Example 619

Summary: Creates a variability chart with nested factors using Graph Builder, displaying standard deviation charts and applying range area style.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 462, 279 ),
    Show Control Panel( 0 ),
    Variables( X( :sex ), Y( :height ), Overlay( :weight ) ),
    Elements( Area( X, Y, Legend( 10 ), Area Style( "Range" ) ) )
);

Code Explanation:

1. Open data table;
2. Launch Graph Builder.
3. Set window size.
4. Hide control panel.
5. Define X variable.
6. Define Y variable.
7. Define overlay variable.
8. Add area element.
9. Set legend position.
10. Apply range area style.

Example 620

Summary: Creates a variability chart with nested factors using Graph Builder, displaying standard deviation charts and summarizing data with the 'Sum' statistic.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 444, 312 ),
    Show Control Panel( 0 ),
    Variables( X( :height ), Y( :weight ), Overlay( :sex ) ),
    Elements( Area( X, Y, Legend( 9 ), Area Style( "Overlaid" ), Response Axis( "Y" ), Summary Statistic( "Sum" ) ) )
);

Code Explanation:

1. Open data table;
2. Create graph builder object.
3. Set window size.
4. Hide control panel.
5. Define variables: X, Y, Overlay.
6. Add area element.
7. Set legend position.
8. Apply overlaid area style.
9. Assign response axis.
10. Use summary statistic: Sum.

Example 621

Summary: Creates a variability chart with nested factors using Graph Builder, displaying standard deviation charts and utilizing operator and part configurations.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 567, 498 ),
    Show Control Panel( 0 ),
    Variables( X( :weight ), Y( :height ), Overlay( :sex ), Color( :age ) ),
    Elements( Area( X, Y, Legend( 7 ) ) )
);

Code Explanation:

1. Open data_table data
2. Launch Graph Builder.
3. Set window size.
4. Hide control panel.
5. Assign X variable.
6. Assign Y variable.
7. Assign overlay variable.
8. Assign color variable.
9. Add area element.
10. Display legend.

Example 622

Summary: Creates a variability chart with nested factors using Graph Builder, displaying standard deviation charts and customizing legend properties.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 522, 448 ),
    Show Control Panel( 0 ),
    Variables( X( :age ), Y( :height ), Overlay( :sex ) ),
    Elements( Area( X, Y, Legend( 4 ) ) ),
    SendToReport( Dispatch( {}, "400", ScaleBox, {Legend Model( 4, Properties( 0, {Fill Color( 44 )}, Item ID( "F", 1 ) ) )} ) )
);

Code Explanation:

1. Open data table;
2. Create Graph Builder window.
3. Set window size.
4. Hide control panel.
5. Define X, Y, and overlay variables.
6. Add area element.
7. Customize legend properties.
8. Set fill color for males.
9. Dispatch report settings.
10. Display graph.

Example 623

Summary: Creates a nested factors variability chart using Graph Builder, with interactive filtering by specific groups.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 514, 444 ),
    Show Control Panel( 0 ),
    Fit to Window( "Off" ),
    Variables( X( :Outlets ), Y( :"Sales (K)"n ), Overlay( :Pie Type ) ),
    Elements( Area( X, Y, Legend( 7 ) ) ),
    Local Data Filter(
        Show Modes( 1 ),
        Mode( Include( 0 ) ),
        Add Filter( columns( :Group ), Where( :Group == {"A", "C", "E"} ), Display( :Group, N Items( 5 ) ) )
    )
);

Code Explanation:

1. Open data table;
2. Create Graph Builder object.
3. Set graph size.
4. Hide control panel.
5. Disable fit to window.
6. Define X, Y, and overlay variables.
7. Add area element.
8. Enable local data filter.
9. Set filter modes.
10. Add filter for specific groups.

Example 624

Summary: Creates a variability chart with nested factors using operator and part configurations, displaying standard deviation charts.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 526, 454 ),
    Show Control Panel( 0 ),
    Variables( X( :weight ), Y( :height ), Overlay( :age ) ),
    Elements( Area( X, Y, Legend( 3 ), Summary Statistic( "% of Total" ) ) )
);

Code Explanation:

1. Open data table;
2. Launch Graph Builder.
3. Set window size.
4. Hide control panel.
5. Assign variables.
6. Add area element.
7. Configure summary statistic.
8. Overlay by age.
9. Display graph.
10. Save as HTML.

Example 625

Summary: Creates a variability chart with nested factors using operator and part configurations, displaying standard deviation charts.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 414, 345 ),
    Show Control Panel( 0 ),
    Variables( X( :weight ), Y( :height ) ),
    Elements( Area( X, Y, Legend( 7 ), Summary Statistic( "Std Dev" ) ) )
);

Code Explanation:

1. Open data table;
2. Launch Graph Builder.
3. Set window size.
4. Hide control panel.
5. Assign X variable.
6. Assign Y variable.
7. Add area element.
8. Set summary statistic to Std Dev.
9. Display legend.
10. Generate graph.

Example 626

Summary: Creates a variability chart with nested factors using operator and part configurations, displaying standard deviation charts in Graph Builder.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 484, 375 ),
    Show Control Panel( 0 ),
    Show Legend( 0 ),
    Variables( X( :Days Advance Purchase ), Y( :Net Cost ), Wrap( :Class of Service ), Overlay( :Airline ) ),
    Elements( Area( X, Y, Legend( 18 ), Summary Statistic( "% of Total" ), Missing Factors( "Treat as Zero" ) ) )
);

Code Explanation:

1. Open data table;
2. Create Graph Builder window.
3. Set window size to 484x375.
4. Hide control panel.
5. Hide legend.
6. Assign X variable: Days Advance Purchase.
7. Assign Y variable: Net Cost.
8. Use Class of Service for wrapping.
9. Use Airline for overlaying.
10. Add area element with summary statistic "% of Total" and treat missing factors as zero.

Example 627

Summary: Creates a geographic map to display points based on Longitude and Latitude variables, utilizing Graph Builder and SendToReport.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 699, 515 ),
    Show Control Panel( 0 ),
    Variables( X( :Longitude ), Y( :Latitude ) ),
    Elements( Points( X, Y, Legend( 1 ) ) ),
    SendToReport(
        Dispatch( {}, "Graph Builder", FrameBox,
            {Background Map( Images( "Street Map Service", "Mapbox Light", "" ), Boundaries( "US States" ) )}
        )
    )
);

Code Explanation:

1. Open data table;
2. Create new Graph Builder window.
3. Set window size.
4. Hide control panel.
5. Define X and Y variables.
6. Add points element.
7. Send report to Graph Builder.
8. Dispatch to Graph Builder.
9. Set background map type.
10. Add US states boundaries.

Example 628

Summary: Creates a Graph Builder script with points and smoother elements to visualize height vs. weight data, while also setting scale properties and adding a background map.

Code:

Open("data_table.jmp");
gb = Graph Builder( Variables( X( :height ), Y( :weight ) ), Elements( Points( X, Y, Legend( 2 ) ), Smoother( X, Y, Legend( 3 ) ) ) );
Set Clipboard(JSLQuote(Graph Builder(
      Variables,
      Elements( Points( Legend( 1 ) ) ),
      SendToReport(
            Dispatch( {}, "", ScaleBox,
                  {Scale( "Geodesic" ), Min( -0.666734693877551 ),
                  Max( 0.666734693877551 ), Minor Ticks( 0 )}
            ),
            Dispatch( {}, "Graph Builder", FrameBox,
                  {Background Map( Images( "Street Map Service", "Mapbox Light", "" ) )}
            )
      )
)));

Code Explanation:

1. Open data table.
2. Create Graph Builder object.
3. Set X variable to height.
4. Set Y variable to weight.
5. Add points element.
6. Add smoother element.
7. Prepare clipboard content.
8. Create new Graph Builder script.
9. Set scale properties.
10. Add background map.

Example 629

Summary: Creates a variability chart with nested factors using Graph Builder, displaying standard deviation charts and side-by-side interval bars.

Code:

Open("data_table.jmp") << Graph Builder(
    Size( 300, 210 ),
    Show Control Panel( 0 ),
    Show Legend( 0 ),
    Variables( X( :age ), Y( :height ), Overlay( :weight ) ),
    Elements( Bar( X, Y, Legend( 5 ), Bar Style( "Side by side intervals" ), Summary Statistic( "N" ) ) )
);

Code Explanation:

1. Open data table;
2. Create Graph Builder window.
3. Set size to 300x210.
4. Hide control panel.
5. Hide legend.
6. Define X variable as age.
7. Define Y variable as height.
8. Define overlay variable as weight.
9. Add bar element.
10. Set bar style to side by side intervals.

Example 630

Summary: Creates a variability chart with nested factors using Graph Builder, displaying standard deviation charts and side-by-side intervals.

Code:

Open("data_table.jmp") << Graph Builder(
    Size( 300, 210 ),
    Show Control Panel( 0 ),
    Variables( X( :age ), Y( :height ), Overlay( :weight ) ),
    Elements( Bar( X, Y, Legend( 5 ), Bar Style( "Side by side intervals" ), Summary Statistic( "Std Dev" ) ) )
);

Code Explanation:

1. Open data table;
2. Launch Graph Builder.
3. Set window size.
4. Hide control panel.
5. Define X variable.
6. Define Y variable.
7. Define overlay variable.
8. Add bar element.
9. Set bar style.
10. Use standard deviation summary.

Example 631

Summary: Creates a graph builder with nested factors using operator and part configurations, displaying standard deviation charts.

Code:

dt = Open("data_table.jmp");
dt << Graph Builder(
    Size( 449, 349 ),
    Show Control Panel( 0 ),
    Variables( X( :sex ), Overlay( :sex ) ),
    Elements( Bar( X, Legend( 6 ), Label( "Label by Value" ) ) )
);

Code Explanation:

1. Open table.
2. Create Graph Builder.
3. Set size.
4. Hide control panel.
5. Set X variable.
6. Set overlay variable.
7. Add bar element.
8. Set legend position.
9. Label by value.

Example 632

Summary: Creates multiple bar graphs with varying styles and legend settings, utilizing Graph Builder to visualize data from a JMP table.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 533, 464 ),
    Show Control Panel( 0 ),
    Variables( X( :Food Category ) ),
    Elements( Bar( X, Legend( 2 ), Bar Style( "Side by Side Intervals" ) ) ),
    SendToReport( Dispatch( {}, "400", LegendBox, {Set Title( "" )} ) )
);
Graph Builder(
    Size( 533, 464 ),
    Show Control Panel( 0 ),
    Variables( X( :Food Category ) ),
    Elements( Bar( X, Legend( 2 ), Bar Style( "Two-way Interval" ) ) ),
    SendToReport( Dispatch( {}, "400", LegendBox, {Set Title( "" )} ) )
);
Graph Builder(
    Size( 533, 464 ),
    Show Control Panel( 0 ),
    Variables( X( :Food Category ) ),
    Elements( Bar( X, Legend( 2 ), Bar Style( "Single" ) ) ),
    SendToReport( Dispatch( {}, "400", LegendBox, {Set Title( "" )} ) )
);
Graph Builder(
    Size( 533, 464 ),
    Show Control Panel( 0 ),
    Variables( X( :Food Category ) ),
    Elements( Bar( X, Legend( 2 ), Bar Style( "Stock" ) ) ),
    SendToReport( Dispatch( {}, "400", LegendBox, {Set Title( "" )} ) )
);
Graph Builder(
    Size( 533, 464 ),
    Show Control Panel( 0 ),
    Variables( X( :Food Category ) ),
    Elements( Bar( X, Legend( 2 ), Bar Style( "Box Plot" ) ) ),
    SendToReport( Dispatch( {}, "400", LegendBox, {Set Title( "" )} ) )
);
Graph Builder(
    Size( 533, 464 ),
    Show Control Panel( 0 ),
    Variables( X( :Food Category ) ),
    Elements( Bar( X, Legend( 2 ), Bar Style( "Needle" ) ) ),
    SendToReport( Dispatch( {}, "400", LegendBox, {Set Title( "" )} ) )
);
Graph Builder(
    Size( 533, 464 ),
    Show Control Panel( 0 ),
    Variables( X( :Food Category ) ),
    Elements( Bar( X, Legend( 2 ), Bar Style( "Float" ) ) ),
    SendToReport( Dispatch( {}, "400", LegendBox, {Set Title( "" )} ) )
);

Code Explanation:

1. Open data table;
2. Create first bar graph.
3. Set graph size.
4. Hide control panel.
5. Set X variable.
6. Add side by side intervals bar style.
7. Remove legend title.
8. Create second bar graph.
9. Set bar style to two-way interval.
10. Remove legend title.

Example 633

Summary: Creates multiple bar charts with different styles for a categorical variable, 'Food Category', in JMP's Graph Builder platform.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 533, 464 ),
    Show Control Panel( 0 ),
    Variables( X( :Food Category ) ),
    Elements( Bar( X, Legend( 2 ), Bar Style( "Side by Side Intervals" ) ) ),
    SendToReport( Dispatch( {}, "400", LegendBox, {Set Title( "" )} ) )
);
Graph Builder(
    Size( 533, 464 ),
    Show Control Panel( 0 ),
    Variables( X( :Food Category ) ),
    Elements( Bar( X, Legend( 2 ), Bar Style( "Two-way Interval" ) ) ),
    SendToReport( Dispatch( {}, "400", LegendBox, {Set Title( "" )} ) )
);
Graph Builder(
    Size( 533, 464 ),
    Show Control Panel( 0 ),
    Variables( X( :Food Category ) ),
    Elements( Bar( X, Legend( 2 ), Bar Style( "Single" ) ) ),
    SendToReport( Dispatch( {}, "400", LegendBox, {Set Title( "" )} ) )
);
Graph Builder(
    Size( 533, 464 ),
    Show Control Panel( 0 ),
    Variables( X( :Food Category ) ),
    Elements( Bar( X, Legend( 2 ), Bar Style( "Stock" ) ) ),
    SendToReport( Dispatch( {}, "400", LegendBox, {Set Title( "" )} ) )
);
Graph Builder(
    Size( 533, 464 ),
    Show Control Panel( 0 ),
    Variables( X( :Food Category ) ),
    Elements( Bar( X, Legend( 2 ), Bar Style( "Box Plot" ) ) ),
    SendToReport( Dispatch( {}, "400", LegendBox, {Set Title( "" )} ) )
);
Graph Builder(
    Size( 533, 464 ),
    Show Control Panel( 0 ),
    Variables( X( :Food Category ) ),
    Elements( Bar( X, Legend( 2 ), Bar Style( "Needle" ) ) ),
    SendToReport( Dispatch( {}, "400", LegendBox, {Set Title( "" )} ) )
);
Graph Builder(
    Size( 533, 464 ),
    Show Control Panel( 0 ),
    Variables( X( :Food Category ) ),
    Elements( Bar( X, Legend( 2 ), Bar Style( "Float" ) ) ),
    SendToReport( Dispatch( {}, "400", LegendBox, {Set Title( "" )} ) )
);
Graph Builder(
    Size( 533, 464 ),
    Show Control Panel( 0 ),
    Variables( X( :Food Category ) ),
    Elements( Bar( X, Legend( 2 ), Bar Style( "Packed" ) ) ),
    SendToReport( Dispatch( {}, "400", LegendBox, {Set Title( "" )} ) )
);

Code Explanation:

1. Open data table;
2. Create graph builder window.
3. Set size to 533x464.
4. Hide control panel.
5. Set X variable to Food Category.
6. Add bar element with side-by-side intervals style.
7. Remove legend title.
8. Repeat steps 2-7 for two-way interval style.
9. Repeat steps 2-7 for single style.
10. Repeat steps 2-7 for stock style.
11. Repeat steps 2-7 for box plot style.
12. Repeat steps 2-7 for needle style.
13. Repeat steps 2-7 for float style.
14. Repeat steps 2-7 for packed style.

Example 634

Summary: Creates a variability chart with nested factors using Graph Builder, displaying standard deviation charts and summarizing range statistics.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 544, 390 ),
    Show Control Panel( 0 ),
    Variables( X( :Position ), Y( :Weight ), Group Y( :Bench ) ),
    Elements( Bar( X, Y, Legend( 12 ), Summary Statistic( "Range" ) ) )
);

Code Explanation:

1. Open data table;
2. Launch Graph Builder.
3. Set window size.
4. Hide control panel.
5. Assign variables: Position, Weight, Bench.
6. Add bar element.
7. Set X axis variable.
8. Set Y axis variable.
9. Group by Bench variable.
10. Display range summary.

Example 635

Summary: Creates a variability chart with nested factors using operator and part configurations, displaying standard deviation charts in Graph Builder.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 528, 464 ),
    Show Control Panel( 0 ),
    Variables( X( :Region ), Y( :SAT Verbal ), Y( :SAT Math, Position( 1 ) ) ),
    Elements( Bar( X, Y( 1 ), Y( 2 ), Legend( 7 ), Summary Statistic( "Std Dev" ), Label( "Label by Value" ) ) )
);

Code Explanation:

1. Open data table;
2. Launch Graph Builder.
3. Set window size.
4. Hide control panel.
5. Assign X variable.
6. Assign first Y variable.
7. Assign second Y variable.
8. Add bar element.
9. Specify summary statistic.
10. Enable label by value.

Example 636

Summary: Creates a variability chart with nested factors using Graph Builder, displaying standard deviation charts and configuring legend settings.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 606, 552 ),
    Show Control Panel( 0 ),
    Variables( X( :sex ), Y( :weight ) ),
    Elements( Histogram( X, Y, Legend( 5 ) ), Bar( X, Y, Legend( 1 ), Summary Statistic( "N" ), Label( "Label by Value" ) ) )
);

Code Explanation:

1. Open data table;
2. Launch Graph Builder.
3. Set window size.
4. Hide control panel.
5. Assign X variable.
6. Assign Y variable.
7. Add histogram element.
8. Add bar element.
9. Configure legend for histogram.
10. Configure bar summary statistic.

Example 637

Summary: Creates a variability chart with nested factors using Graph Builder, displaying standard deviation charts and configuring report settings.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 369, 278 ),
    Show Control Panel( 0 ),
    Variables( X( :sex ), X( :age, Position( 1 ) ), Y( :height ), Y( :weight, Position( 1 ) ), Overlay( :age ) ),
    Elements( Bar( X( 1 ), X( 2 ), Y( 1 ), Y( 2 ), Legend( 4 ), Bar Style( "Interval" ) ) ),
    SendToReport( Dispatch( {}, "sex", ScaleBox, {Label Row( 1, Show Major Grid( 1 ) )} ) )
);

Code Explanation:

1. Open data table;
2. Create new Graph Builder window.
3. Set window size.
4. Hide control panel.
5. Define X variables: sex, age.
6. Define Y variables: height, weight.
7. Overlay by age.
8. Add bar elements with interval style.
9. Display major grid on sex axis.
10. Finalize report settings.

Example 638

Summary: Creates a variability chart with nested factors using Graph Builder, displaying standard deviation charts and customizing legend properties.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 731, 252 ),
    Show Control Panel( 0 ),
    Variables( X( :sex ), X( :age, Position( 1 ) ), Y( :height ), Y( :weight, Position( 1 ) ), Overlay( :age ) ),
    Elements( Bar( X( 1 ), X( 2 ), Y( 1 ), Y( 2 ), Legend( 4 ) ) ),
    SendToReport(
        Dispatch( {}, "400", ScaleBox,
            {Legend Model(
                4,
                Properties( 0, {Line Color( -3896249 ), Fill Color( -3896249 )} ),
                Properties( 1, {Line Color( -11170218 ), Fill Color( -11170218 )} ),
                Properties( 2, {Line Color( -15610404 ), Fill Color( -15610404 )} ),
                Properties( 3, {Line Color( -44783 ), Fill Color( -44783 )} ),
                Properties( 4, {Line Color( -16291869 ), Fill Color( -16291869 )} ),
                Properties( 5, {Line Color( -8436546 ), Fill Color( -8436546 )} ),
                Properties( 6, {Line Color( -11193839 ), Fill Color( -11193839 )} ),
                Properties( 7, {Line Color( -13291202 ), Fill Color( -13291202 )} ),
                Properties( 8, {Line Color( -11183822 ), Fill Color( -11183822 )} ),
                Properties( 9, {Line Color( -14655133 ), Fill Color( -14655133 )} ),
                Properties( 10, {Line Color( -6992615 ), Fill Color( -6992615 )} ),
                Properties( 11, {Line Color( -16768256 ), Fill Color( -16768256 )} )
            )}
        )
    )
);

Code Explanation:

1. Open data table;
2. Create Graph Builder window.
3. Set window size.
4. Hide control panel.
5. Define variables: sex, age, height, weight.
6. Add bar elements for sex and age.
7. Customize legend properties.
8. Set legend fill colors.
9. Display graph.
10. Finalize report settings.

Example 639

Summary: Creates two variability charts with nested factors using Graph Builder, displaying standard deviation charts and utilizing operator and part configurations.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 584, 452 ),
    Show Control Panel( 0 ),
    Show Legend( 0 ),
    Variables( X( :sex ), X( :age, Position( 1 ) ), Y( :height ), Y( :weight, Position( 1 ) ), Overlay( :sex ), Color( :age ) ),
    Elements(
        Bar( X( 1 ), X( 2 ), Y( 1 ), Y( 2 ), Legend( 8 ), Bar Style( "Range" ), Summary Statistic( "Max" ), Label( "Label by Value" ) )
    )
);
Graph Builder(
    Size( 584, 488 ),
    Show Control Panel( 0 ),
    Show Legend( 0 ),
    Variables( X( :sex ), X( :age, Position( 1 ) ), Y( :height ), Y( :weight, Position( 1 ) ), Group X( :sex ), Color( :height ) ),
    Elements(
        Bar( X( 1 ), X( 2 ), Y( 1 ), Y( 2 ), Legend( 8 ), Bar Style( "Range" ), Summary Statistic( "Sum" ), Label( "Label by Value" ) )
    )
);

Code Explanation:

1. Open data table.
2. Create first Graph Builder window.
3. Set window size.
4. Hide control panel.
5. Hide legend.
6. Define variables for X, Y, overlay, color.
7. Add bar element with range style.
8. Use max summary statistic.
9. Label bars by value.
10. Create second Graph Builder window.
11. Set window size.
12. Hide control panel.
13. Hide legend.
14. Define variables for X, Y, group X, color.
15. Add bar element with range style.
16. Use sum summary statistic.
17. Label bars by value.

Example 640

Summary: Creates a variability chart with nested factors using Graph Builder, displaying standard deviation charts and configuring bar style and labels.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 584, 452 ),
    Show Control Panel( 0 ),
    Show Legend( 0 ),
    Variables( X( :sex ), X( :age, Position( 1 ) ), Y( :height ), Y( :weight, Position( 1 ) ), Overlay( :sex ) ),
    Elements( Bar( X( 1 ), X( 2 ), Y( 1 ), Y( 2 ), Legend( 8 ), Bar Style( "Range" ), Label( "Label by Value" ) ) )
);

Code Explanation:

1. Open data table;
2. Launch Graph Builder.
3. Set window size.
4. Hide control panel.
5. Hide legend.
6. Define X variables: sex, age.
7. Define Y variables: height, weight.
8. Overlay by sex.
9. Add bar element.
10. Configure bar style and labels.

Example 641

Summary: Creates a variability chart with nested factors using Graph Builder, displaying standard deviation charts and formatting labels as percentages.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 1091, 488 ),
    Show Control Panel( 0 ),
    Show Legend( 0 ),
    Variables( X( :sex ), X( :age, Position( 1 ) ), Y( :height ), Y( :weight, Position( 1 ) ), Overlay( :sex ) ),
    Elements(
        Bar(
            X( 1 ),
            X( 2 ),
            Y( 1 ),
            Y( 2 ),
            Legend( 8 ),
            Bar Style( "Range" ),
            Summary Statistic( "% of Total" ),
            Label( "Label by Value" ),
            Label Format( "Percent", 8, 3 )
        )
    ),
    SendToReport(
        Dispatch( {}, "400", ScaleBox,
            {Legend Model(
                8,
                Properties( 0, {Fill Color( -9294791 )}, Item ID( "% of Total(height)..% of Total(weight) (sex=F)", 1 ) ),
                Properties( 1, {Fill Color( -12499674 )}, Item ID( "% of Total(height)..% of Total(weight) (sex=M)", 1 ) )
            )}
        )
    )
);

Code Explanation:

1. Open data table.
2. Create Graph Builder window.
3. Set window size.
4. Hide control panel.
5. Hide legend.
6. Define variables: sex, age, height, weight.
7. Overlay by sex.
8. Add bar element.
9. Configure bar style and statistics.
10. Format labels as percent.

Example 642

Summary: Creates a variability chart with nested factors using Graph Builder, overlaying by sex and coloring by age.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 672, 452 ),
    Show Control Panel( 0 ),
    Show Legend( 0 ),
    Variables( X( :sex ), X( :age, Position( 1 ) ), Y( :height ), Y( :weight, Position( 1 ) ), Overlay( :sex ), Color( :age ) ),
    Elements( Bar( X( 1 ), X( 2 ), Y( 1 ), Y( 2 ), Legend( 8 ), Bar Style( "Range" ), Label( "Label by Value" ) ) )
);

Code Explanation:

1. Open data_table data
2. Launch Graph Builder.
3. Set window size.
4. Hide control panel.
5. Hide legend.
6. Define variables: sex, age, height, weight.
7. Overlay by sex.
8. Color by age.
9. Add bar element.
10. Configure bar style and labels.

Example 643

Summary: Creates a variability chart with nested factors using Graph Builder, displaying standard deviation charts and adjusting legend settings.

Code:

Open("data_table.jmp");
Graph Builder(
    Show Control Panel( 0 ),
    Legend Position( "Bottom" ),
    Variables( X( :age ), X( :sex ) ),
    Elements( Position( 1, 1 ), Bar( X, Legend( 3 ) ) ),
    Elements( Position( 2, 1 ), Bar( X, Legend( 4 ) ) ),
    SendToReport( Dispatch( {}, "400", LegendBox, {Orientation( "Horizontal" ), Sides( "Left" )} ) )
);

Code Explanation:

1. Open data_table data
2. Initiate Graph Builder.
3. Hide control panel.
4. Set legend position bottom.
5. Define age and sex variables.
6. Add first bar element.
7. Add second bar element.
8. Adjust legend orientation.
9. Set legend sides left.
10. Finalize report.

Example 644

Summary: Creates a variability chart with nested factors using operator and part configurations, displaying standard deviation charts.

Code:

Open("data_table.jmp");
obj = Graph Builder(
    Size( 522, 453 ),
    Show Control Panel( 0 ),
    Show Legend( 0 ),
    Show Footer( 0 ),
    Variables( X( :Weight ), X( :Height, Position( 1 ) ), Y( :Position ) ),
    Elements( Bar( X( 1 ), X( 2 ), Y, Legend( 14 ), Bar Style( "Side by Side" ), Label( "Label by Row" ) ) )
);

Code Explanation:

1. Open data table;
2. Create Graph Builder object.
3. Set graph size.
4. Hide control panel.
5. Hide legend.
6. Hide footer.
7. Define X variables: Weight, Height.
8. Define Y variable: Position.
9. Add bar element.
10. Configure bar style and labels.

Example 645

Summary: Creates a variability chart with nested factors using operator and part configurations, displaying standard deviation charts.

Code:

dt = Open("data_table.jmp");
Current Data Table() << Begin Data Update;
dt:age[{4, 33}] = .;
dt:height[{6, 34}] = .;
Current Data Table() << End Data Update;
dt << Graph Builder(
    Size( 587, 433 ),
    Show Control Panel( 0 ),
    Show Legend( 0 ),
    Include Missing Categories( 1 ),
    Variables( X( :sex ), X( :age, Position( 1 ) ), Y( :height ) ),
    Elements( Bar( X( 1 ), X( 2 ), Y, Legend( 8 ), Summary Statistic( "% of Total" ), Label( "Label by Value" ) ) )
);
Graph Builder(
    Size( 587, 433 ),
    Show Control Panel( 0 ),
    Show Legend( 0 ),
    Variables( X( :sex ), X( :age, Position( 1 ) ), Y( :height ) ),
    Elements( Bar( X( 1 ), X( 2 ), Y, Legend( 8 ), Summary Statistic( "% of Total" ), Label( "Label by Value" ) ) )
);

Code Explanation:

1. Open data table.
2. Begin data update.
3. Set age values to missing.
4. Set height values to missing.
5. End data update.
6. Create Graph Builder object.
7. Set graph size.
8. Hide control panel.
9. Hide legend.
10. Include missing categories.

Example 646

Summary: Creates a nested variability chart with two factors using Graph Builder, including local data filtering and overlaying weight data.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 425, 303 ),
    Show Control Panel( 0 ),
    Variables( X( :age ), Y( :height ), Y( :weight, Position( 1 ) ), Overlay( :weight ) ),
    Elements( Bar( X, Y( 1 ), Y( 2 ), Legend( 69 ) ) ),
    Local Data Filter(
        Mode( Include( 0 ) ),
        Inverse( 1 ),
        Add Filter( columns( :age ), Where( :age == {14, 15, 16, 17} ), Display( :age, Size( 160, 90 ), List Display ) )
    )
);

Code Explanation:

1. Open data table;
2. Create Graph Builder window.
3. Set window size.
4. Hide control panel.
5. Define X and Y variables.
6. Add second Y variable.
7. Overlay second Y variable.
8. Create bar chart elements.
9. Configure legend for elements.
10. Add local data filter.

Example 647

Summary: Creates a variability chart with nested factors using operator and part configurations, displaying standard deviation charts through Graph Builder.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 534, 464 ),
    Show Control Panel( 0 ),
    Variables( X( :Operator ), X( :Part, Position( 1 ) ), Y( :Y ), Overlay( :Part ) ),
    Elements( Points( X( 1 ), X( 2 ), Y, Legend( 17 ), Summary Statistic( "Mean" ), Error Bars( "Range" ) ) )
);

Code Explanation:

1. Open data table;
2. Launch Graph Builder.
3. Set window size.
4. Hide control panel.
5. Define X variables.
6. Define second X variable position.
7. Define Y variable.
8. Set overlay variable.
9. Add points element.
10. Configure summary statistic and error bars.

Example 648

Summary: Creates a variability chart with nested factors using operator and part configurations, displaying standard deviation charts in Graph Builder.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 422, 368 ),
    Show Control Panel( 0 ),
    Variables( Y( :Speed ), Y( :Speed2, Position( 1 ) ), Overlay( :Position ) ),
    Elements( Bar( Y( 1 ), Y( 2 ), Legend( 5 ), Bar Style( "Side by Side" ), Summary Statistic( "Sum" ) ) )
);

Code Explanation:

1. Open data table;
2. Create Graph Builder window.
3. Set window size.
4. Hide control panel.
5. Define Y variables.
6. Define second Y variable position.
7. Set overlay variable.
8. Add bar element.
9. Specify first Y for bar.
10. Specify second Y for bar.

Example 649

Summary: Creates a variability chart with nested factors using operator and part configurations, displaying standard deviation charts in Graph Builder.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 451, 368 ),
    Show Control Panel( 0 ),
    Variables( Y( :Speed ), Y( :Speed2, Position( 1 ) ), Overlay( :Position2 ), Color( :Position ) ),
    Elements( Bar( Y( 1 ), Y( 2 ), Legend( 5 ), Bar Style( "Range" ), Summary Statistic( "Sum" ), Label( "Label by Value" ) ) )
);

Code Explanation:

1. Open data table;
2. Launch Graph Builder.
3. Set window size.
4. Hide control panel.
5. Define Y variables.
6. Define second Y variable position.
7. Define overlay variable.
8. Define color variable.
9. Add bar element.
10. Configure bar style and summary.

Example 650

Summary: Creates a variability chart with nested factors using Graph Builder, displaying standard deviation charts and customizing legend colors.

Code:

dt = Open("data_table.jmp");
Graph Builder(
    Size( 395, 350 ),
    Show Control Panel( 0 ),
    Legend Position( "Bottom" ),
    Variables( X( :type ), X( :country ), X( :marital status, Position( 2 ) ), Y( :age ), Overlay( :size ), Color( :sex ) ),
    Elements( Position( 1, 1 ), Bar( X, Y, Legend( 3 ), Bar Style( "Stacked" ) ) ),
    Elements( Position( 2, 1 ), Bar( X( 2 ), X( 1 ), Y, Legend( 4 ), Bar
Style( "Interval" ) ) ),
    SendToReport(
        Dispatch( {}, "400", ScaleBox,
            {Legend Model( 3, Properties( 0, {Fill Color( 35 )} ), Properties( 1, {Fill Color( 5 )} ) ),
            Legend Model( 4, Base( 0, 0, 0 ), Base( 1, 0, 0 ), Properties( 0, {Fill Color( 35 )} ), Properties( 1, {Fill Color( 5 )} ) )}
        ),
        Dispatch( {}, "400", LegendBox, {Legend Position( {3, [0, 1], 4, [-1, -1]} )} )
    )
);

Code Explanation:

1. Open table.
2. Set graph size.
3. Hide control panel.
4. Set legend position.
5. Define variables.
6. Add first bar element.
7. Add second bar element.
8. Customize legend colors.
9. Adjust legend positions.
10. Display report.

Example 651

Summary: Creates a variability chart with nested factors using Graph Builder, displaying standard deviation charts and configuring graph settings.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 284, 241 ),
    Show Control Panel( 0 ),
    Lock Scales( 1 ),
    Include Missing Categories( 1 ),
    Variables(
        Y( :Name( "2004" ) ),
        Y( :Name( "2008" ), Position( 1 ) ),
        Y( :Name( "2012" ), Position( 1 ) ),
        Group X( :Name( "2012 Winner" ) ),
        Color( :Name( "1992" ) )
    ),
    Elements( Bar( Y( 1 ), Y( 2 ), Y( 3 ), Legend( 3 ) ) )
);

Code Explanation:

1. Open data table;
2. Create Graph Builder object.
3. Set graph size.
4. Hide control panel.
5. Lock scales.
6. Include missing categories.
7. Assign Y variables.
8. Assign second Y variable.
9. Assign third Y variable.
10. Group by X variable.
11. Color by variable.
12. Add bar element.

Example 652

Summary: Creates a variability chart with nested factors using Graph Builder, displaying standard deviation charts and configuring bar style.

Code:

dt = Open("data_table.jmp");
gb = dt << Graph Builder(
    Size( 634, 517 ),
    Show Control Panel( 0 ),
    Legend Position( "Bottom" ),
    Variables( X( :Month ), Y( :Predicted Temperature ), Y( :Temperature, Position( 1 ) ) ),
    Elements( Bar( X, Y( 1 ), Y( 2 ), Legend( 8 ), Bar Style( "Arrow" ) ) )
);

Code Explanation:

1. Open data table.
2. Create Graph Builder object.
3. Set window size.
4. Hide control panel.
5. Position legend.
6. Define X variable.
7. Define primary Y variable.
8. Define secondary Y variable.
9. Add bar element.
10. Configure bar style.

Example 653

Summary: Creates a variability chart with nested factors using Graph Builder, displaying standard deviation charts and error intervals.

Code:

dt2 = Open("data_table.jmp");
gb2 = dt2 << Graph Builder(
    Size( 536, 452 ),
    Show Control Panel( 0 ),
    Variables( X( :age ), Y( :weight ) ),
    Elements( Bar( X, Y, Legend( 4 ), Error Interval( "Range" ), Interval Style( "Arrow" ) ) )
);
gb3 = dt2 << Graph Builder(
    Size( 718, 566 ),
    Variables( X( :weight ), Y( :height ), Overlay( :age ) ),
    Elements( Line( X, Y, Legend( 5 ), Ordering( "Summarized" ), Connection( "Arrow" ) ) ),
    SendToReport(
        Dispatch( {}, "400", ScaleBox,
            {Legend Model(
                5,
                Base( -1, 0, 0, Item ID( "Range", 1 ) ),
                Properties(
                    -1,
                    {Line Color(
                        {0.202212564767033, 0.312151730021937, 0.573911733805508, "HLS", 0.617370903491974, 0.38806214928627,
                        0.478917062282562}
                    ), Arrowhead( "None" )},
                    Item ID( "Range", 1 )
                )
            )}
        )
    )
);

Code Explanation:

1. Open data table.
2. Create Graph Builder object.
3. Set graph size.
4. Hide control panel.
5. Define X and Y variables.
6. Add bar element with error interval.
7. Create another Graph Builder object.
8. Set new graph size.
9. Define X, Y, and overlay variables.
10. Add line element with arrow connection.

Example 654

Summary: Creates multiple Graph Builder objects to visualize data from two tables, featuring nested factors and standard deviation charts.

Code:

dt = Open("data_table.jmp");
gb = dt << Graph Builder(
    Size( 634, 517 ),
    Show Control Panel( 0 ),
    Legend Position( "Bottom" ),
    Variables( X( :Month ), Y( :Predicted Temperature ), Y( :Temperature, Position( 1 ) ) ),
    Elements( Bar( X, Y( 1 ), Y( 2 ), Legend( 8 ), Bar Style( "Arrow" ) ) )
);
dt2 = Open("data_table.jmp");
gb2 = dt2 << Graph Builder(
    Size( 536, 452 ),
    Show Control Panel( 0 ),
    Variables( X( :age ), Y( :weight ) ),
    Elements( Bar( X, Y, Legend( 4 ), Error Interval( "Range" ), Interval Style( "Arrow" ) ) )
);
gb3 = dt2 << Graph Builder(
    Size( 718, 566 ),
    Variables( X( :weight ), Y( :height ), Overlay( :age ) ),
    Elements( Line( X, Y, Legend( 5 ), Ordering( "Summarized" ), Connection( "Arrow" ) ) ),
    SendToReport(
        Dispatch( {}, "400", ScaleBox,
            {Legend Model(
                5,
                Base( -1, 0, 0, Item ID( "Range", 1 ) ),
                Properties(
                    -1,
                    {Line Color(
                        {0.202212564767033, 0.312151730021937, 0.573911733805508, "HLS", 0.617370903491974, 0.38806214928627,
                        0.478917062282562}
                    ), Arrowhead( "None" )},
                    Item ID( "Range", 1 )
                )
            )}
        )
    )
);
dt3 = Open("data_table.jmp");
gb4 = dt3 << Graph Builder(
    Size( 547, 458 ),
    Show Control Panel( 0 ),
    Legend Position( "Inside Left" ),
    Variables( X( :Week of Year ), Y( :TMIN ), Y( :TMAX, Position( 1 ) ) ),
    Elements( Bar( X, Y( 1 ), Y( 2 ), Legend( 6 ), Bar Style( "Arrow" ), Summary Statistic( "% of Total" ) ) )
);

Code Explanation:

1. Open data table;
2. Create Graph Builder object.
3. Set graph size and legend position.
4. Define X and Y variables.
5. Add bar element with arrow style.
6. Open data table;
7. Create second Graph Builder object.
8. Set graph size and legend position.
9. Define X and Y variables.
10. Add bar element with error interval and arrow style.

Example 655

Summary: Creates a variability chart with nested factors using Graph Builder, displaying standard deviation charts and adjusting X-axis scale.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 540, 493 ),
    Show Control Panel( 0 ),
    Variables( X( :Response ), Y( :Name( "ln(dose)" ) ), Group X( :Dose ), Frequency( :Count ) ),
    Elements( Bar( X, Y, Legend( 12 ), Summary Statistic( "Std Dev" ) ) ),
    SendToReport( Dispatch( {}, "ln(dose)", ScaleBox, {Min( -0.0000000025 ), Max( 0.000000022 ), Inc( 0.000002 ), Minor Ticks( 0 )} ) )
);

Code Explanation:

1. Open data table;
2. Launch Graph Builder.
3. Set graph size.
4. Hide control panel.
5. Define variables for axes.
6. Add bar element.
7. Set summary statistic.
8. Adjust X-axis scale.
9. Set minimum value.
10. Set maximum value.

Example 656

Summary: Creates a variability chart with nested factors using Graph Builder, displaying standard deviation charts and customizing age axis minimum.

Code:

dt = Open("data_table.jmp");
Graph Builder(
    Size( 454, 288 ),
    Show Control Panel( 0 ),
    Variables( X( :age ), Y( :height ), Overlay( :sex ) ),
    Elements( Bar( X, Y, Legend( 7 ), Label( "Label by Value" ) ) ),
    SendToReport( Dispatch( {}, "age", ScaleBox, {Min( 1 )} ) )
);

Code Explanation:

1. Open data table.
2. Launch Graph Builder.
3. Set window size.
4. Hide control panel.
5. Assign variables: X=age, Y=height, Overlay=sex.
6. Add bar element.
7. Configure legend position.
8. Label bars by value.
9. Customize age axis minimum.
10. Send report to display.

Example 657

Summary: Creates a bar chart with nested factors using Graph Builder, setting the fill color to purple and hiding control panel and legend.

Code:

dt = Open("data_table.jmp");
gb = dt << Graph Builder(
    Size( 373, 269 ),
    Show Control Panel( 0 ),
    Show Legend( 0 ),
    Variables( X( :age ) ),
    Elements( Bar( X, Legend( 13 ), Label( "Label by Value" ) ) )
);
rpt = gb << Report();
barSeg = rpt[Framebox( 1 )] << find seg( BarSeg( 1 ) );
barSeg << Fill Color( "Purple" );

Code Explanation:

1. Open data table.
2. Create Graph Builder object.
3. Set graph size.
4. Hide control panel.
5. Hide legend.
6. Set X variable to age.
7. Add bar element.
8. Generate report object.
9. Find first bar segment.
10. Set fill color to purple.

Example 658

Summary: Creates a bar chart with nested factors using Graph Builder, setting fill and text colors to purple.

Code:

dt = Open("data_table.jmp");
gb = dt << Graph Builder(
    Size( 373, 269 ),
    Show Control Panel( 0 ),
    Show Legend( 0 ),
    Variables( X( :age ) ),
    Elements( Bar( X, Legend( 13 ), Label( "Label by Value" ) ) )
);
rpt = gb << Report();
barSeg = rpt[Framebox( 1 )] << find seg( BarSeg( 1 ) );
barSeg << Fill Color( "Purple" );
barSeg << Text Color( "Purple" );

Code Explanation:

1. Open data table;
2. Create Graph Builder object.
3. Set graph size.
4. Hide control panel.
5. Hide legend.
6. Set X variable to age.
7. Add bar element.
8. Generate report.
9. Find bar segment.
10. Set fill color to purple.
11. Set text color to purple.

Example 659

Summary: Creates a variability chart with nested factors using Graph Builder, displaying standard deviation charts and accessing graph report frames.

Code:

Open("data_table.jmp");
gb = Graph Builder(
    Size( 320, 274 ),
    Show Control Panel( 0 ),
    Variables( X( :age ), Y( :weight ) ),
    Elements( Bar( X, Y, Legend( 9 ), Label( "Label by Value" ) ) )
);
frame = (gb << report)[FrameBox( 1 )];
seg = (frame << Find Seg( BarSeg( 1 ) ));

Code Explanation:

1. Open data table.
2. Create graph builder object.
3. Set size and hide control panel.
4. Define X and Y variables.
5. Add bar element with label.
6. Access graph report frame.
7. Find first bar segment.

Example 660

Summary: Creates a bar chart with nested factors using Graph Builder, setting label offset for the first segment and displaying the modified graph.

Code:

Open("data_table.jmp");
gb = Graph Builder(
    Size( 320, 274 ),
    Show Control Panel( 0 ),
    Variables( X( :age ), Y( :weight ) ),
    Elements( Bar( X, Y, Legend( 9 ), Label( "Label by Value" ) ) )
);
frame = (gb << report)[FrameBox( 1 )];
seg = (frame << Find Seg( BarSeg( 1 ) ));
seg << Set Label Offset( {0, 0.4, 112} );

Code Explanation:

1. Open data table;
2. Create Graph Builder object.
3. Set graph size.
4. Hide control panel.
5. Assign X and Y variables.
6. Add bar element with label.
7. Retrieve frame box from report.
8. Find first bar segment.
9. Set label offset for segment.
10. Display modified graph.

Example 661

Summary: Creates a bar chart with nested factors using Graph Builder, displaying standard deviation charts and hiding the control panel.

Code:

Open("data_table.jmp");
gb = Graph Builder(
    Size( 300, 200 ),
    Show Control Panel( 0 ),
    Variables( X( :sex ), Y( :height ) ),
    Elements( Bar( X, Y, Legend( 5 ) ) ), 
);
rgb = gb << report;
barSeg = rgb[Framebox( 1 )] << findseg( "BarSeg" );

Code Explanation:

1. Open data table.
2. Create Graph Builder object.
3. Set graph size.
4. Hide control panel.
5. Assign X and Y variables.
6. Add bar element.
7. Generate report object.
8. Access frame box.
9. Find bar segment.
10. Assign bar segment reference.

Example 662

Summary: Creates a bar chart with nested factors using Graph Builder, setting graph size and hiding control panel.

Code:

Open("data_table.jmp");
gb = Graph Builder(
    Size( 300, 200 ),
    Show Control Panel( 0 ),
    Variables( X( :sex ), Y( :height ) ),
    Elements( Bar( X, Y, Legend( 5 ) ) ), 
);
rgb = gb << report;
barSeg = rgb[Framebox( 1 )] << findseg( "BarSeg" );
barSeg << Set Width Proportion( 0.9 );

Code Explanation:

1. Open data table;
2. Create Graph Builder object.
3. Set graph size.
4. Hide control panel.
5. Define X and Y variables.
6. Add bar element.
7. Generate report.
8. Locate frame box.
9. Find bar segment.
10. Set width proportion.

Example 663

Summary: Creates a bar chart with nested factors using Graph Builder, displaying standard deviation charts for height and weight.

Code:

Open("data_table.jmp");
Graph Builder( Show Control Panel( 0 ), Variables( X( :height ), Y( :weight ) ), Elements( Bar( X, Y, Legend( 15 ) ) ) );

Code Explanation:

1. Open data table;
2. Launch Graph Builder.
3. Hide control panel.
4. Set X variable: height.
5. Set Y variable: weight.
6. Add bar element.
7. Link X and Y variables.
8. Enable legend.
9. Position legend at 15.

Example 664

Summary: Creates a variability chart with nested factors using Graph Builder, displaying standard deviation charts and utilizing operator and part configurations.

Code:

Open("data_table.jmp");
Graph Builder( Show Control Panel( 0 ), Variables( X( :age ), Y( :weight ) ), Elements( Bar( X, Y, Legend( 7 ) ) ) );

Code Explanation:

1. Open data table;
2. Launch Graph Builder.
3. Hide control panel.
4. Set X variable to age.
5. Set Y variable to weight.
6. Add bar element.
7. Assign legend position 7.

Example 665

Summary: Creates a stacked bar chart with nested factors using Graph Builder, displaying standard deviation charts for height and weight variables.

Code:

Open("data_table.jmp");
Graph Builder(
    Show Control Panel( 0 ),
    Variables( X( :age ), Y( :height ), Y( :weight, Position( 1 ) ) ),
    Elements( Bar( X, Y( 1 ), Y( 2 ), Legend( 8 ), Bar Style( "Stacked" ) ) )
);

Code Explanation:

1. Open data table;
2. Launch Graph Builder.
3. Hide control panel.
4. Set X variable: age.
5. Set first Y variable: height.
6. Set second Y variable: weight.
7. Place weight on position 1.
8. Add bar element.
9. Configure bar for X and Y1.
10. Configure bar for Y2, stacked style.

Example 666

Summary: Creates a bar chart with nested factors using Graph Builder, displaying height and weight variables for each age group.

Code:

Open("data_table.jmp");
Graph Builder(
    Show Control Panel( 0 ),
    Variables( X( :age ), Y( :height ), Y( :weight, Position( 1 ) ) ),
    Elements( Bar( X, Y( 1 ), Y( 2 ), Legend( 8 ), Bar Style( "Bullet" ) ) )
);

Code Explanation:

1. Open data table;
2. Launch Graph Builder.
3. Hide control panel.
4. Set X variable: age.
5. Set Y variable: height.
6. Add Y variable: weight.
7. Position weight on Y axis 1.
8. Create bar element.
9. Assign X to bar.
10. Assign height and weight to bar.

Example 667

Summary: Creates a variability chart with nested factors using Graph Builder, displaying standard deviation charts and applying bullet bar style.

Code:

Open("data_table.jmp");
Graph Builder(
    show control panel( 0 ),
    Variables(
        X( :age ),
        Y( Transform Column( "Center[height]", Format( "Fixed Dec", 5, 0 ), Formula( :height - Col Mean( :height ) ) ) ),
        Overlay( :sex )
    ),
    Elements( Bar( X, Y, Legend( 10 ), Bar Style( "Bullet" ) ) )
);

Code Explanation:

1. Open data table;
2. Launch Graph Builder.
3. Hide control panel.
4. Set X variable to age.
5. Create transformed height column.
6. Set Y variable to transformed height.
7. Use sex for overlay.
8. Add bar element.
9. Apply bullet bar style.
10. Display graph.

Example 668

Summary: Creates a variability chart with nested factors using Graph Builder, displaying standard deviation charts and utilizing color variable for age.

Code:

Open("data_table.jmp");
Graph Builder( Show Control Panel( 0 ), Variables( X( :sex ), Y( :height ), Color( :age ) ), Elements( Bar( X, Y ) ) );

Code Explanation:

1. Open data table;
2. Launch Graph Builder.
3. Hide control panel.
4. Set X variable to sex.
5. Set Y variable to height.
6. Set color variable to age.
7. Add bar element.

Example 669

Summary: Creates a variability chart with nested factors using Graph Builder, displaying standard deviation charts and various summary statistics.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 652, 540 ),
    Show Control Panel( 0 ),
    Variables(
        X( :age ),
        X( :age ),
        X( :age ),
        X( :age ),
        X( :age ),
        X( :age ),
        X( :age ),
        X( :age ),
        X( :age ),
        X( :age ),
        X( :age ),
        X( :age ),
        X( :age ),
        X( :age ),
        X( :age ),
        Y( :height )
    ),
    Elements( Position( 1, 1 ), Bar( X, Y, Legend( 76 ), Summary Statistic( "N" ) ) ),
    Elements( Position( 2, 1 ), Bar( X, Y, Legend( 77 ) ) ),
    Elements( Position( 3, 1 ), Bar( X, Y, Legend( 78 ), Summary Statistic( "Median" ) ) ),
    Elements( Position( 4, 1 ), Bar( X, Y, Legend( 79 ), Summary Statistic( "Geometric Mean" ) ) ),
    Elements( Position( 5, 1 ), Bar( X, Y, Legend( 80 ), Summary Statistic( "Min" ) ) ),
    Elements( Position( 6, 1 ), Bar( X, Y, Legend( 81 ), Summary Statistic( "Max" ) ) ),
    Elements( Position( 7, 1 ), Bar( X, Y, Legend( 82 ), Summary Statistic( "Range" ) ) ),
    Elements( Position( 8, 1 ), Bar( X, Y, Legend( 83 ), Summary Statistic( "Sum" ) ) ),
    Elements( Position( 9, 1 ), Bar( X, Y, Legend( 84 ), Summary Statistic( "% of Total" ) ) ),
    Elements( Position( 10, 1 ), Bar( X, Y, Legend( 85 ), Summary Statistic( "Std Dev" ) ) ),
    Elements( Position( 11, 1 ), Bar( X, Y, Legend( 86 ), Summary Statistic( "Variance" ) ) ),
    Elements( Position( 12, 1 ), Bar( X, Y, Legend( 87 ), Summary Statistic( "Std Err" ) ) ),
    Elements( Position( 13, 1 ), Bar( X, Y, Legend( 88 ), Summary Statistic( "Interquartile Range" ) ) ),
    Elements( Position( 14, 1 ), Bar( X, Y, Legend( 89 ), Summary Statistic( "First Quartile" ) ) ),
    Elements( Position( 15, 1 ), Bar( X, Y, Legend( 90 ), Summary Statistic( "Third Quartile" ) ) ),
    SendToReport( Dispatch( {}, "height", ScaleBox, {Min( -41.8181818181818 )} ) )
);

Code Explanation:

1. Open data table;
2. Create Graph Builder window.
3. Set graph size.
4. Hide control panel.
5. Define X variable (age).
6. Repeat X variable definition.
7. Define Y variable (height).
8. Add first bar element with count summary.
9. Add second bar element.
10. Add third bar element with median summary.
11. Add fourth bar element with geometric mean summary.
12. Add fifth bar element with minimum summary.
13. Add sixth bar element with maximum summary.
14. Add seventh bar element with range summary.
15. Add eighth bar element with sum summary.
16. Add ninth bar element with percentage of total summary.
17. Add tenth bar element with standard deviation summary.
18. Add eleventh bar element with variance summary.
19. Add twelfth bar element with standard error summary.
20. Add thirteenth bar element with interquartile range summary.
21. Add fourteenth bar element with first quartile summary.
22. Add fifteenth bar element with third quartile summary.
23. Adjust height scale minimum.

Example 670

Summary: Creates a variability chart with nested factors using Graph Builder, displaying standard deviation charts and color-coding based on weight percentages.

Code:

Open("data_table.jmp");
Graph Builder(
    Show Control Panel( 0 ),
    Size( 485, 485 ),
    Variables( Y( :weight ), Overlay( :sex ), Color( :weight, Summary Statistic( "% of Factor" ) ) ),
    Elements( Bar( Y, Legend( 12 ), Summary Statistic( "% of Factor" ) ) )
);

Code Explanation:

1. Open data table;
2. Launch Graph Builder.
3. Hide control panel.
4. Set window size.
5. Define Y variable: weight.
6. Define overlay variable: sex.
7. Define color variable: weight.
8. Use "% of Factor" summary statistic for coloring.
9. Add bar element.
10. Display legend.

Example 671

Summary: Creates a variability chart with nested factors using Graph Builder, displaying standard deviation charts and enabling error intervals.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 592, 379 ),
    Show Control Panel( 0 ),
    Variables( X( :age ), Y( :height ), Color( :age ) ),
    Elements( Bar( X, Y, Legend( 4 ), Error Interval( "Standard Deviation" ), Interval Style( "Hash Band" ) ) )
);

Code Explanation:

1. Open data table;
2. Create new Graph Builder window.
3. Set window size.
4. Hide control panel.
5. Assign variables: X, Y, Color.
6. Add Bar element.
7. Set legend position.
8. Enable error interval.
9. Set interval style.
10. Display graph.

Example 672

Summary: Creates a variability chart with nested factors using Graph Builder, featuring a bar element and column switcher for interactive analysis.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 686, 572 ),
    Variables( X( :Genre ), Y( :Opening Wknd Gross ) ),
    Show Control Panel( 0 ),
    Elements( Bar( X, Y, Legend( 7 ), Bar Style( "Side by side" ), Summary Statistic( "Mean" ) ) ),
    Column Switcher(
        Opening Wknd Gross,
        {Rotten Tomatoes Score, Audience Score, Domestic Gross, Foreign Gross, World Gross, Production Budget, Profitability,
        Opening Wknd Gross}
    )
);

Code Explanation:

1. Open data table;
2. Launch Graph Builder.
3. Set graph size.
4. Define X and Y variables.
5. Hide control panel.
6. Add bar element.
7. Configure bar style.
8. Set summary statistic.
9. Add column switcher.
10. Specify switchable columns.

Example 673

Summary: Creates a stacked bar chart to visualize the relationship between age and height, with categorical overlay based on sex.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 534, 448 ),
    Show Control Panel( 0 ),
    Variables(
        X( :age ),
        Y( :height ),
        Overlay( Transform Column( "categorical", Formula( (:sex == "M") + 2 * Mod( Row(), 2 ) ) ) ),
        Color( :sex )
    ),
    Elements( Bar( X, Y, Legend( 4 ), Bar Style( "Stacked" ) ) )
);

Code Explanation:

1. Open data table;
2. Create Graph Builder window.
3. Set graph size.
4. Hide control panel.
5. Define X variable: age.
6. Define Y variable: height.
7. Create overlay variable: categorical.
8. Define color variable: sex.
9. Add bar element.
10. Set bar style to stacked.

Example 674

Summary: Creates a bar chart with filtered data, displaying standard deviation charts for sex and name variables using Graph Builder.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 448, 414 ),
    Show Control Panel( 0 ),
    Variables( X( :age ) ),
    Elements( Bar( X, Legend( 6 ) ) ),
    Local Data Filter(
        Conditional,
        Add Filter(
            columns( :sex, :name ),
            Where( :sex == "F" ),
            Where( :name == {"ALICE", "ELIZABETH", "KATIE", "LOUISE", "MARY", "SUSAN"} ),
            Display( :name, Size( 160, 225 ), List Display )
        )
    )
);

Code Explanation:

1. Open data table;
2. Launch Graph Builder.
3. Set window size.
4. Hide control panel.
5. Set X variable to age.
6. Add bar element.
7. Configure legend for bars.
8. Enable local data filter.
9. Set filter type to conditional.
10. Add filter for sex and name.

Example 675

Summary: Creates a variability chart with nested factors using operator and part configurations, displaying standard deviation charts in JMP.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 439, 352 ),
    Show Control Panel( 0 ),
    Variables( X( :Year ), Y( :Market Share ), Overlay( :Operating System ) ),
    Elements( Bar( X, Y, Legend( 8 ), Bar Style( "Interval" ) ) ),
    SendToReport(
        Dispatch( {}, "Year", ScaleBox, {Min( 2005.50569625983 ), Max( 2011.46622145589 ), Inc( 1 ), Minor Ticks( 0 )} ),
        Dispatch( {}, "Market Share", ScaleBox, {Min( 0.00313397542658369 ), Max( 1.00090393964954 ), Inc( 0.2 ), Minor Ticks( 0 )} ),
        Dispatch( {}, "graph title", TextEditBox, {Set Text( "SmartPhone OS Market Share" )} ),
        Dispatch( {}, "400", LegendBox, {Legend Position( {8, [3, 2, 1, 0]} )} )
    )
);

Code Explanation:

1. Open data table;
2. Create Graph Builder window.
3. Set graph size.
4. Hide control panel.
5. Define variables: X (Year), Y (Market Share), Overlay (Operating System).
6. Add bar element with interval style.
7. Set X-axis minimum, maximum, increment, and minor ticks.
8. Set Y-axis minimum, maximum, increment, and minor ticks.
9. Set graph title text.
10. Adjust legend position.

Example 676

Summary: Creates a variability chart with nested factors using Graph Builder, configuring age as an ordinal type and displaying standard deviation charts.

Code:

Open("data_table.jmp");
Graph Builder(
    Transform Column(
        "Transform[height]@X",
        Formula( Col Median( :height, :"@Exclude"n, :"@Filter"n, :"@Graph"n, :"@Overlay"n, :"@X"n ) )
    ),
    Transform Column(
        "age'",
        Ordinal,
        Set Property( "Configure Levels", 1 ),
        Set Property( "Value Order", {Custom Order( {12, 13, 14, 15} )} ),
        Value Labels( {12 = "12", 13 = "13", 14 = "14", 15 = "Older"} ),
        Use Value Labels( 1 ),
        Formula( Map Value( :age, {16, 15, 17, 15}, Unmatched( :age ) ) )
    ),
    Size( 536, 452 ),
    Show Control Panel( 0 ),
    Variables( X( :age' ), Y( :"Transform[height]@X"n ), Overlay( :sex ) ),
    Elements( Bar( X, Y, Legend( 8 ), Bar Style( "Stacked" ), Label( "Label by Value" ), Label Format( "Fixed Dec", 4, 2 ) ) )
);

Code Explanation:

1. Open data table.
2. Create transform column for height.
3. Define median formula for transformed height.
4. Create transform column for age.
5. Set age as ordinal type.
6. Configure age levels.
7. Define custom order for age values.
8. Set value labels for age.
9. Enable value labels usage.
10. Map age values with unmatched handling.
11. Set graph size.
12. Hide control panel.
13. Assign variables to axes and overlay.
14. Add bar element with specific styles and labeling.

Example 677

Summary: Creates a variability chart with nested factors using operator and part configurations, displaying standard deviation charts within Graph Builder.

Code:

Open("data_table.jmp");
Graph Builder(
    Transform Column( "Transform[Price]@X", Formula( Col Median( :Price, :"@Exclude"n, :"@Filter"n, :"@Graph"n, :"@Overlay"n, :"@X"n ) ) ),
    Size( 535, 452 ),
    Show Control Panel( 0 ),
    Variables( X( :Cut ), Y( :Price ), Y( :"Transform[Price]@X"n ) ),
    Elements( Position( 1, 1 ), Bar( X, Y, Legend( 14 ) ) ),
    Elements( Position( 1, 2 ), Bar( X, Y, Legend( 15 ) ) ),
    Local Data Filter( Add Filter( columns( :Color ), Where( :Color == {"I", "H", "G", "F"} ), Display( :Color, N Items( 8 ) ) ) )
);

Code Explanation:

1. Open data table;
2. Create Transform Column.
3. Set Transform Formula.
4. Define Graph Builder size.
5. Hide Control Panel.
6. Set X and Y variables.
7. Add first Bar element.
8. Add second Bar element.
9. Add Local Data Filter.
10. Filter Color column.

Example 678

Summary: Creates a variability chart with nested factors using operator and part configurations, displaying standard deviation charts.

Code:

Open("data_table.jmp");
Graph Builder(
    Transform Column( "Col Min(height)@X", Formula( Col Minimum( :height, :"@Exclude"n, :"@Filter"n, :"@Graph"n, :"@Overlay"n, :"@X"n ) ) ),
    Transform Column( "Col Max(height)@X", Formula( Col Max( :height, :"@Exclude"n, :"@Filter"n, :"@Graph"n, :"@Overlay"n, :"@X"n ) ) ),
    Transform Column(
        "age'",
        Ordinal,
        Set Property( "Configure Levels", 1 ),
        Set Property( "Value Order", {Custom Order( {12, 13, 14, 15} )} ),
        Value Labels( {12 = "12", 13 = "13", 14 = "14", 15 = "High School"} ),
        Use Value Labels( 1 ),
        Formula( Map Value( :age, {16, 15, 17, 15}, Unmatched( :age ) ) )
    ),
    Size( 533, 452 ),
    Show Control Panel( 0 ),
    Variables(
        X( :age' ),
        Y( :"Col Max(height)@X"n ),
        Y( :"Col Min(height)@X"n, Position( 1 ) ),
        Y( :height, Position( 1 ) ),
        Color( :age' )
    ),
    Elements( Bar( X, Y( 1 ), Y( 2 ), Y( 3 ), Legend( 3 ), Bar Style( "Side by side ranges" ) ), Points( X, Y( 3 ), Legend( 4 ) ) ),
    Local Data Filter( Add Filter( columns( :weight ), Where( :weight <= 126.78 ) ) ),
    SendToReport(
        Dispatch( {}, "400", ScaleBox,
            {Legend Model(
                3,
                Properties( 0, {Transparency( 0.4 )}, Item ID( "12", 1 ) ),
                Properties( 1, {Transparency( 0.4 )}, Item ID( "13", 1 ) ),
                Properties( 2, {Transparency( 0.4 )}, Item ID( "14", 1 ) ),
                Properties( 3, {Transparency( 0.4 )}, Item ID( "High School", 1 ) ),
                Properties( -1, {Transparency( 0.4 )}, Item ID( "Mean(Col Max(height)@X)..Mean(Col Min(height)@X)", 1 ) ),
                Properties( -1, {Transparency( 0.4 )}, Item ID( "Mean(Col Max(height)@X)..Mean(Col Min(height)@X) (sex=F)", 1 ) )
            )}
        )
    )
);

Code Explanation:

1. Open data table;
2. Create new graph builder.
3. Define minimum height transform column.
4. Define maximum height transform column.
5. Configure age ordinal variable.
6. Set size of graph builder window.
7. Hide control panel.
8. Assign variables to axes.
9. Add bar and point elements.
10. Apply local data filter.

Example 679

Summary: Creates a variability chart with nested factors using Graph Builder, displaying standard deviation charts and error bars for confidence intervals.

Code:

Open("data_table.jmp");
Graph Builder(
    Variables( X( :age ), Y( :height ) ),
    Elements( Bar( X, Y, Legend( 4 ), Error Bars( "Confidence Interval" ) ) ),
    SendToReport( Dispatch( {}, "Graph Builder", FrameBox, {DispatchSeg( BarSeg( 2 ), {Error Bar Cap( "Small" )} )} ) )
);

Code Explanation:

1. Open data table.
2. Create graph builder object.
3. Set X variable to age.
4. Set Y variable to height.
5. Add bar element.
6. Add error bars for confidence interval.
7. Send report to graph builder.
8. Dispatch to graph builder frame box.
9. Set error bar cap to small.
10. Display graph.

Example 680

Summary: Creates three Graph Builder windows to visualize variability charts with nested factors, using operator and part configurations, and displaying standard deviation charts.

Code:

Open("data_table.jmp");
Graph Builder(
    Show Control Panel( 0 ),
    Variables( X( :age ), Y( :height ), Y( :weight, Position( 1 ) ) ),
    Elements( Bar( X, Y( 1 ), Y( 2 ), Legend( 8 ), Error Bars( "Range" ) ) )
);
Graph Builder(
    Show Control Panel( 0 ),
    Variables( X( :age ), Y( :height ), Y( :weight, Position( 1 ) ) ),
    Elements( Bar( X, Y( 1 ), Y( 2 ), Legend( 8 ), Error Bars( "Standard Error" ) ) )
);
Graph Builder(
    Show Control Panel( 0 ),
    Variables( X( :age ), Y( :height ), Y( :weight, Position( 1 ) ) ),
    Elements( Bar( X, Y( 1 ), Y( 2 ), Legend( 8 ), Error Bars( "Standard Deviation" ) ) )
);

Code Explanation:

1. Open data table;
2. Create first Graph Builder window.
3. Hide control panel.
4. Set X variable to age.
5. Set Y variables to height and weight.
6. Add bar element with error bars (range).
7. Create second Graph Builder window.
8. Hide control panel.
9. Set X variable to age.
10. Set Y variables to height and weight.
11. Add bar element with error bars (standard error).
12. Create third Graph Builder window.
13. Hide control panel.
14. Set X variable to age.
15. Set Y variables to height and weight.
16. Add bar element with error bars (standard deviation).

Example 681

Summary: Creates four Graph Builder windows to visualize variability charts with nested factors, displaying standard deviation error bars for different configurations.

Code:

Open("data_table.jmp");
Graph Builder(
    Show Control Panel( 0 ),
    Variables( X( :age ), Y( :height ), Y( :weight, Position( 1 ) ) ),
    Elements( Bar( X, Y( 1 ), Y( 2 ), Legend( 8 ), Error Bars( "Range" ) ) )
);
Graph Builder(
    Show Control Panel( 0 ),
    Variables( X( :age ), Y( :height ), Y( :weight, Position( 1 ) ) ),
    Elements( Bar( X, Y( 1 ), Y( 2 ), Legend( 8 ), Error Bars( "Standard Error" ) ) )
);
Graph Builder(
    Show Control Panel( 0 ),
    Variables( X( :age ), Y( :height ), Y( :weight, Position( 1 ) ) ),
    Elements( Bar( X, Y( 1 ), Y( 2 ), Legend( 8 ), Error Bars( "Standard Deviation" ) ) )
);
Graph Builder(
    Show Control Panel( 0 ),
    Variables( X( :age ), Y( :height ), Y( :weight, Position( 1 ) ) ),
    Elements( Bar( X, Y( 1 ), Y( 2 ), Legend( 8 ), Error Bars( "Confidence Interval" ) ) )
);

Code Explanation:

1. Open data table;
2. Create Graph Builder window.
3. Hide control panel.
4. Set X variable to age.
5. Set Y variables to height and weight.
6. Add bar element with error bars (Range).
7. Create another Graph Builder window.
8. Hide control panel.
9. Set X variable to age.
10. Set Y variables to height and weight.
11. Add bar element with error bars (Standard Error).
12. Create another Graph Builder window.
13. Hide control panel.
14. Set X variable to age.
15. Set Y variables to height and weight.
16. Add bar element with error bars (Standard Deviation).
17. Create another Graph Builder window.
18. Hide control panel.
19. Set X variable to age.
20. Set Y variables to height and weight.
21. Add bar element with error bars (Confidence Interval).

Example 682

Summary: Creates a variability chart with nested factors using Graph Builder, displaying standard deviation charts and overlaying by sex.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 528, 496 ),
    Show Control Panel( 0 ),
    Variables( X( :age ), Y( :height ), Overlay( :sex ) ),
    Elements( Points( X, Y, Jitter( 0 ), Summary Statistic( "Mean" ), Error Bars( "Standard Error" ) ) )
);

Code Explanation:

1. Open data table;
2. Launch Graph Builder.
3. Set graph size.
4. Hide control panel.
5. Assign variables: age, height, sex.
6. Add points element.
7. Apply jitter to points.
8. Use mean for summary statistic.
9. Display standard error bars.
10. Overlay by sex variable.

Example 683

Summary: Creates a variability chart with nested factors using operator and part configurations, displaying standard deviation charts for data analysis.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 389, 250 ),
    Show Control Panel( 0 ),
    Variables( X( :Part ), Y( :Y ), Overlay( :Part ) ),
    Elements( Points( X, Y, Summary Statistic( "Mean" ), Error Bars( "Range" ) ) )
);

Code Explanation:

1. Open data table;
2. Launch Graph Builder.
3. Set window size.
4. Hide control panel.
5. Assign X variable.
6. Assign Y variable.
7. Use Part for overlay.
8. Add points element.
9. Calculate mean summary statistic.
10. Display range error bars.

Example 684

Summary: Creates three Graph Builder windows to visualize variability charts with nested factors, using operator and part configurations, and displaying standard deviation charts.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 528, 496 ),
    Show Control Panel( 0 ),
    Variables( X( :age ), Y( :height ), Overlay( :sex ) ),
    Elements( Points( X, Y, Jitter( 0 ), Summary Statistic( "Mean" ), Error Bars( "Standard Error" ) ) )
);
Open("data_table.jmp");
Graph Builder(
    Size( 389, 250 ),
    Show Control Panel( 0 ),
    Variables( X( :Part ), Y( :Y ), Overlay( :Part ) ),
    Elements( Points( X, Y, Summary Statistic( "Mean" ), Error Bars( "Range" ) ) )
);
Open("data_table.jmp");
Graph Builder(
    Size( 366, 285 ),
    Show Control Panel( 0 ),
    Variables( X( :Operator ), X( :Part, Position( 1 ) ), Y( :Y ), Overlay( :Part ) ),
    Elements( Points( X( 1 ), X( 2 ), Y, Legend( 17 ), Summary Statistic( "Mean" ), Error Bars( "Range" ) ) )
);

Code Explanation:

1. Open data table;
2. Create Graph Builder window.
3. Set window size.
4. Hide control panel.
5. Assign variables: age (X), height (Y), sex (Overlay).
6. Add points element with jitter.
7. Calculate mean summary statistic.
8. Add standard error error bars.
9. Open data table;
10. Create another Graph Builder window.
11. Set window size.
12. Hide control panel.
13. Assign variables: Part (X), Y (Y), Part (Overlay).
14. Add points element.
15. Calculate mean summary statistic.
16. Add range error bars.
17. Open data table;
18. Create third Graph Builder window.
19. Set window size.
20. Hide control panel.
21. Assign variables: Operator (X), Part (X, Position 1), Y (Y), Part (Overlay).
22. Add points element with two X variables.
23. Set legend position.
24. Calculate mean summary statistic.
25. Add range error bars.

Example 685

Summary: Creates a variability chart with nested factors using Graph Builder, selecting rows where age is 14 and sex is female, and displaying standard deviation charts.

Code:

dt = Open("data_table.jmp");
dt << select where( :age == 14 & :sex == "F" );
dt << hide;
dt << clear select;
Graph Builder(
    Size( 508, 382 ),
    Show Control Panel( 0 ),
    Variables( X( :age ), Y( :weight ), Overlay( :sex ) ),
    Elements( Bar( X, Y, Legend( 4 ), Error Bars( "Range" ), Label( "Label by Value" ) ) )
);

Code Explanation:

1. Open data table.
2. Select rows where age is 14 and sex is female.
3. Hide selected rows.
4. Clear row selection.
5. Create Graph Builder object.
6. Set window size to 508x382.
7. Hide control panel.
8. Assign variables: X as age, Y as weight, Overlay as sex.
9. Add bar element with error bars.
10. Label bars by value.

Example 686

Summary: Creates a variability chart with nested factors using Graph Builder, displaying standard error bars for height measurements based on sex.

Code:

Open("data_table.jmp");
Graph Builder( Variables( X( :sex ), Y( :height ) ), Elements( Bar( X, Y, Bar Style( "Float" ), Error Bars( "Standard Error" ) ) ) );

Code Explanation:

1. Open data table.
2. Launch Graph Builder.
3. Set X variable to sex.
4. Set Y variable to height.
5. Add Bar element.
6. Configure Bar style to Float.
7. Add Error Bars.
8. Set Error Bars to Standard Error.

Example 687

Summary: Creates two variability charts with nested factors using Graph Builder, displaying standard error bars and float-style bars.

Code:

Open("data_table.jmp");
Graph Builder( Variables( X( :sex ), Y( :height ) ), Elements( Bar( X, Y, Bar Style( "Float" ), Error Bars( "Standard Error" ) ) ) );
Graph Builder(
    Variables( X( :sex ), Y( :height ), Y( :weight, Position( 1 ) ) ),
    Elements( Bar( X, Y( 1 ), Y( 2 ), Bar Style( "Float" ), Error Bars( "Standard Error" ) ) )
);

Code Explanation:

1. Open data table;
2. Create graph builder object.
3. Set X variable to sex.
4. Set Y variable to height.
5. Add bar element with float style.
6. Add error bars for standard error.
7. Create second graph builder object.
8. Set X variable to sex.
9. Set Y variables to height and weight.
10. Add bar element with float style and error bars for standard error.

Example 688

Summary: Creates a variability chart with nested factors using Graph Builder, displaying standard deviation charts and side-by-side bar plots.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 585, 534 ),
    show control panel( 0 ),
    Variables( X( :age ), Y( :height ), Overlay( :sex ) ),
    Elements( Bar( X, Y, Legend( 2 ), Bar Style( "Side by side" ), Summary Statistic( "Mean" ), Error Bars( "Standard Error" ) ) )
);
Graph Builder(
    Size( 585, 534 ),
    show control panel( 0 ),
    Variables( X( :age ), X( :sex, Position( 1 ) ), Y( :height ), Overlay( :sex ) ),
    Elements(
        Bar( X( 1 ), X( 2 ), Y, Legend( 2 ), Bar Style( "Side by side" ), Error Bars( "Standard Error" ), Summary Statistic( "Mean" ) )
    )
);

Code Explanation:

1. Open data table.
2. Create first Graph Builder window.
3. Set window size.
4. Hide control panel.
5. Define variables: X(age), Y(height), Overlay(sex).
6. Add bar element.
7. Set bar style to "Side by side".
8. Use mean for summary statistic.
9. Add standard error error bars.
10. Create second Graph Builder window.

Example 689

Summary: Creates two variability charts with nested factors using Graph Builder, displaying standard deviation charts and customizing legends for weight and sex.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 523, 463 ),
    Show Control Panel( 0 ),
    Variables( X( :age ), Y( :height ), Color( :weight ) ),
    Elements( Bar( X, Y, Legend( 6 ), Bar Style( "Float" ) ) ),
    SendToReport(
        Dispatch( {}, "400", ScaleBox,
            {Legend Model(
                6,
                Type Properties( 0, "Gradient Line", {Line Width( 6 )} ),
                Properties( 0, {Line Width( 6 )}, Item ID( "weight", 1 ) )
            )}
        )
    )
);
Graph Builder(
    Size( 524, 463 ),
    Show Control Panel( 0 ),
    Variables( X( :age ), Y( :height ), Color( :sex ) ),
    Elements( Bar( X, Y, Legend( 6 ), Bar Style( "Float" ) ) ),
    SendToReport( Dispatch( {}, "400", ScaleBox, {Legend Model( 6, Properties( 0, {Line Width( 6 )}, Item ID( "F", 1 ) ) )} ) )
);

Code Explanation:

1. Open data table;
2. Create first Graph Builder window.
3. Set window size to 523x463.
4. Hide control panel.
5. Set X variable to age.
6. Set Y variable to height.
7. Set color variable to weight.
8. Add bar element with float style.
9. Customize legend for weight with gradient line.
10. Create second Graph Builder window.
11. Set window size to 524x463.
12. Hide control panel.
13. Set X variable to age.
14. Set Y variable to height.
15. Set color variable to sex.
16. Add bar element with float style.
17. Customize legend for sex.

Example 690

Summary: Creates a variability chart with nested factors using Graph Builder, displaying standard deviation charts and summarizing data with the sum statistic.

Code:

Open("data_table.jmp");
Graph Builder( Show Control Panel( 0 ), Variables( Frequency( :height ) ), Elements( Bar( Legend( 6 ), Summary Statistic( "Sum" ) ) ) );

Code Explanation:

1. Open data table.
2. Launch Graph Builder.
3. Hide control panel.
4. Set frequency variable.
5. Add bar element.
6. Configure legend.
7. Set summary statistic to sum.

Example 691

Summary: Creates a bar chart to visualize the relationship between height and sex using Graph Builder.

Code:

Open("data_table.jmp");
Graph Builder( Show Control Panel( 0 ), Variables( X( :height ), Y( :sex ) ), Elements( Bar( X, Y ) ) );

Code Explanation:

1. Open data table;
2. Launch Graph Builder.
3. Hide control panel.
4. Set X variable to height.
5. Set Y variable to sex.
6. Add bar element.

Example 692

Summary: Creates two bar charts with nested factors using Graph Builder, displaying sex as a categorical variable and height as a continuous variable.

Code:

Open("data_table.jmp");
Graph Builder( Show Control Panel( 0 ), Variables( X( :height ), Y( :sex ) ), Elements( Bar( X, Y ) ) );
Graph Builder( Show Control Panel( 0 ), Variables( X( :sex ), Y( :height ) ), Elements( Bar( X, Y, Legend( 4 ) ) ) );

Code Explanation:

1. Open data table.
2. Create graph builder.
3. Hide control panel.
4. Set X variable: height.
5. Set Y variable: sex.
6. Add bar element.
7. Create second graph builder.
8. Hide control panel.
9. Set X variable: sex.
10. Set Y variable: height.
11. Add bar element with legend.

Example 693

Summary: Creates three bar graphs to visualize the distribution of 'N' values by sex, using Graph Builder with nested factors and standard deviation charts.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 493, 336 ),
    Show Control Panel( 0 ),
    Variables( Group X( :sex ) ),
    Elements( Bar( Legend( 3 ), Summary Statistic( "N" ), Label( "Label by Value" ) ) )
);
Graph Builder(
    Size( 493, 336 ),
    Show Control Panel( 0 ),
    Variables( Group Y( :sex ) ),
    Elements( Bar( Legend( 3 ), Summary Statistic( "N" ), Label( "Label by Value" ) ) )
);
Graph Builder(
    Size( 493, 336 ),
    Show Control Panel( 0 ),
    Variables( Wrap( :sex ) ),
    Elements( Bar( Legend( 3 ), Summary Statistic( "N" ), Label( "Label by Value" ) ) )
);

Code Explanation:

1. Open data table;
2. Create first bar graph.
3. Set graph size.
4. Hide control panel.
5. Group X by sex.
6. Add bar element.
7. Use summary statistic N.
8. Label by value.
9. Create second bar graph.
10. Group Y by sex.

Example 694

Summary: Creates four bar graphs to visualize nested factors using Graph Builder, with each graph displaying standard deviation charts and summarizing by count.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 493, 336 ),
    Show Control Panel( 0 ),
    Variables( Group X( :sex ) ),
    Elements( Bar( Legend( 3 ), Summary Statistic( "N" ), Label( "Label by Value" ) ) )
);
Graph Builder(
    Size( 493, 336 ),
    Show Control Panel( 0 ),
    Variables( Group Y( :sex ) ),
    Elements( Bar( Legend( 3 ), Summary Statistic( "N" ), Label( "Label by Value" ) ) )
);
Graph Builder(
    Size( 493, 336 ),
    Show Control Panel( 0 ),
    Variables( Wrap( :sex ) ),
    Elements( Bar( Legend( 3 ), Summary Statistic( "N" ), Label( "Label by Value" ) ) )
);
Graph Builder(
    Size( 493, 336 ),
    Show Control Panel( 0 ),
    Variables( Page( :sex ) ),
    Elements( Bar( Legend( 3 ), Summary Statistic( "N" ), Label( "Label by Value" ) ) )
);

Code Explanation:

1. Open data table.
2. Create first bar graph.
3. Set graph size.
4. Hide control panel.
5. Group by sex on X-axis.
6. Add bar element.
7. Summarize by count.
8. Label bars by value.
9. Create second bar graph.
10. Group by sex on Y-axis.
11. Add bar element.
12. Summarize by count.
13. Label bars by value.
14. Create third bar graph.
15. Set graph size.
16. Hide control panel.
17. Wrap by sex.
18. Add bar element.
19. Summarize by count.
20. Label bars by value.
21. Create fourth bar graph.
22. Set graph size.
23. Hide control panel.
24. Page by sex.
25. Add bar element.
26. Summarize by count.
27. Label bars by value.

Example 695

Summary: Creates two variability charts with nested factors using Graph Builder, displaying standard deviation charts and customizing legend colors.

Code:

dt = Open("data_table.jmp");
gb = dt << Graph Builder(
    Size( 525, 456 ),
    Show Control Panel( 0 ),
    Variables( X( :height ), X( :weight, Position( 1 ) ), Y( :age ) ),
    Elements( Bar( X( 1 ), X( 2 ), Y, Legend( 8 ), Error Interval( "Standard Deviation" ), Interval Style( "Hash Band" ) ) ),
    SendToReport(
        Dispatch( {}, "400", ScaleBox,
            {Legend Model(
                8,
                Properties( 0, {Fill Color( 38 )}, Item ID( "Mean(height)", 1 ) ),
                Properties( 1, {Fill Color( 10 )}, Item ID( "Mean(weight)", 1 ) )
            )}
        )
    )
);
gb3 = dt << Graph Builder(
    Size( 534, 453 ),
    Show Control Panel( 0 ),
    Variables( X( :sex ), Y( :weight ), Overlay( :age ) ),
    Elements( Bar( X, Y, Legend( 8 ), Error Interval( "Standard Deviation" ), Interval Style( "Hash Band" ), Label( "Label by Value" ) ) ),
    Local Data Filter( Add Filter( columns( :sex ), Where( :sex == "M" ) ) )
);

Code Explanation:

1. Open data table;
2. Create Graph Builder object.
3. Set size to 525x456.
4. Hide control panel.
5. Set X variables: height, weight.
6. Set Y variable: age.
7. Add bar element with hash band error interval.
8. Customize legend colors.
9. Create second Graph Builder object.
10. Set size to 534x453.
11. Hide control panel.
12. Set X variable: sex.
13. Set Y variable: weight.
14. Set overlay variable: age.
15. Add bar element with hash band error interval and label by value.
16. Add local data filter for sex = "M".

Example 696

Summary: Creates a variability chart with nested factors using Graph Builder, displaying standard deviation charts and configuring report settings.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 533, 464 ),
    Show Control Panel( 0 ),
    Variables( X( :Food Category ), Interval( :Fat ) ),
    Elements( Bar( X, Legend( 4 ) ) ),
    SendToReport( Dispatch( {}, "Graph Builder", FrameBox, {Grid Line Order( 1 ), Reference Line Order( 2 )} ) )
);

Code Explanation:

1. Open data table;
2. Launch Graph Builder.
3. Set graph size.
4. Hide control panel.
5. Assign X variable.
6. Assign interval variable.
7. Add bar element.
8. Set legend position.
9. Send report settings.
10. Adjust grid and reference lines.

Example 697

Summary: Creates a variability chart with nested factors using Graph Builder, displaying standard deviation charts and overlaying by age.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 438, 341 ),
    Show Control Panel( 0 ),
    Variables( X( :sex ), Y( :height ), Y( :weight, Position( 1 ) ), Overlay( :age ) ),
    Elements( Bar( X, Y( 1 ), Y( 2 ), Legend( 7 ), Bar Style( "Interval" ) ) )
);

Code Explanation:

1. Open data table;
2. Create Graph Builder window.
3. Set window size.
4. Hide control panel.
5. Define X variable as sex.
6. Define Y1 variable as height.
7. Define Y2 variable as weight.
8. Position Y2 on left.
9. Overlay by age.
10. Add bar element with interval style.

Example 698

Summary: Creates a variability chart with nested factors using Graph Builder, displaying standard deviation charts and utilizing interval bar style.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 528, 450 ),
    Show Control Panel( 0 ),
    Variables( X( :age ), Y( :height ), Overlay( :weight ), Color( :height, Summary Statistic( "sum" ) ) ),
    Elements( Bar( X, Y, Legend( 7 ), Bar Style( "Interval" ) ) )
);

Code Explanation:

1. Open data table.
2. Create new graph builder window.
3. Set window size.
4. Hide control panel.
5. Define X variable.
6. Define Y variable.
7. Define overlay variable.
8. Define color variable with summary statistic.
9. Add bar element.
10. Set bar style to interval.

Example 699

Summary: Creates two variability charts with nested factors using operator and part configurations, displaying standard deviation charts for Height and Weight variables.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 534, 484 ),
    Show Control Panel( 0 ),
    Variables( X( :Position ), Y( :Height ), Y( :Weight, Position( 1 ) ), Wrap( :Fat ) ),
    Elements( Bar( X, Y( 1 ), Y( 2 ), Legend( 3 ), Bar Style( "Interval" ), Summary Statistic( "Sum" ) ) )
);
Graph Builder(
    Size( 534, 484 ),
    Show Control Panel( 0 ),
    Variables( X( :Position ), Y( :Height ), Y( :Weight, Position( 1 ) ), Wrap( :Fat ) ),
    Elements( Bar( X, Y( 1 ), Y( 2 ), Legend( 3 ), Bar Style( "Range" ), Summary Statistic( "Sum" ) ) )
);

Code Explanation:

1. Open data table;
2. Create first Graph Builder window.
3. Set window size 534x484.
4. Hide control panel.
5. Define X variable: Position.
6. Define Y variables: Height, Weight.
7. Wrap by Fat variable.
8. Add Bar element.
9. Set Bar Style to Interval.
10. Use Sum for summary statistic.
11. Create second Graph Builder window.
12. Set window size 534x484.
13. Hide control panel.
14. Define X variable: Position.
15. Define Y variables: Height, Weight.
16. Wrap by Fat variable.
17. Add Bar element.
18. Set Bar Style to Range.
19. Use Sum for summary statistic.

Example 700

Summary: Creates a variability chart with nested factors using Graph Builder, featuring range and interval bar elements for min and max values, and customized legend and scale formatting.

Code:

dt = Open("data_table.jmp");
Graph Builder(
    Size( 275, 248 ),
    Show Control Panel( 0 ),
    Variables( X( :sex ), Y( :height ), Y( :weight, Position( 1 ) ) ),
    Elements(
        Bar( X, Y( 1 ), Y( 2 ), Legend( 4 ), Bar Style( "Range" ), Summary
Statistic( "Min" ) ),
        Bar( X, Y( 1 ), Y( 2 ), Legend( 3 ), Bar Style( "Interval" ), Summary Statistic( "Max" ) )
    ),
    SendToReport(
        Dispatch( {}, "height", ScaleBox, {Format( "Best", 12 )} ),
        Dispatch( {}, "400", ScaleBox, {Legend Model( 3, Properties( 0, {Line Width( 5 ), Transparency( 0.6 )} ) )} ),
        Dispatch( {}, "400", LegendBox, {Legend Position( {4, [1], 3, [0]} )} )
    )
);

Code Explanation:

1. Open data table.
2. Create Graph Builder window.
3. Set window size.
4. Hide control panel.
5. Define X and Y variables.
6. Add range bar element for min.
7. Add interval bar element for max.
8. Format height scale.
9. Customize legend for max.
10. Arrange legend positions.

Example 701

Summary: Creates a variability chart with nested factors using Graph Builder, displaying standard deviation charts and configuring scale properties for Year and Market Share.

Code:

Open("data_table.jmp");
Graph Builder(
    Show Control Panel( 0 ),
    Variables( X( :Year ), Y( :Market Share ), Overlay( :Operating System ) ),
    Elements( Bar( X, Y, Legend( 8 ), Bar Style( "Interval" ) ) ),
    SendToReport(
        Dispatch( {}, "Year", ScaleBox, {Min( 2005.50569625983 ), Max( 2011.46622145589 ), Inc( 1 ), Minor Ticks( 0 )} ),
        Dispatch( {}, "Market Share", ScaleBox, {Min( 0.00313397542658369 ), Max( 1.00090393964954 ), Inc( 0.2 ), Minor Ticks( 0 )} ),
        Dispatch( {}, "graph title", TextEditBox, {Set Text( "SmartPhone OS Market Share" )} ),
        Dispatch( {}, "400", LegendBox, {Legend Position( {8, [3, 2, 1, 0]} )} )
    )
);

Code Explanation:

1. Open data table.
2. Create Graph Builder object.
3. Hide control panel.
4. Set X variable to Year.
5. Set Y variable to Market Share.
6. Use Operating System for overlay.
7. Add bar element with interval style.
8. Set Year scale properties.
9. Set Market Share scale properties.
10. Set graph title.
11. Configure legend position.

Example 702

Summary: Creates a variability chart with nested factors using Graph Builder, displaying standard deviation charts and overlaying by Sex.

Code:

Open("data_table.jmp");
Graph Builder(
    Show Control Panel( 0 ),
    Variables( X( :Treatment ), Y( :Lower 95% ), Y( :Upper 95%, Position( 1 ) ), Y( :Mean, Position( 1 ) ), Overlay( :Sex ) ),
    Elements( Bar( X, Y( 1 ), Y( 2 ), Y( 3 ), Legend( 3 ), Bar Style( "Interval" ), Summary Statistic( "Mean" ) ) )
);

Code Explanation:

1. Open data table;
2. Create Graph Builder object.
3. Hide control panel.
4. Set X variable to Treatment.
5. Set Y variables: Lower 95%, Upper 95%, Mean.
6. Position Upper 95% and Mean on Y1.
7. Overlay by Sex variable.
8. Add Bar element.
9. Set X for Bar element.
10. Set Y1, Y2, Y3 for Bar element.

Example 703

Summary: Creates a variability chart with nested factors using Graph Builder, displaying standard deviation charts and summarizing data by sum.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 550, 485 ),
    Show Control Panel( 0 ),
    Variables( X( :Heart History ), Overlay( :Smoking History ) ),
    Elements( Bar( X, Legend( 8 ), Bar Style( "Interval" ), Summary Statistic( "Sum" ), Label( "Label by Value" ) ) )
);

Code Explanation:

1. Open data table;
2. Create Graph Builder object.
3. Set graph size.
4. Hide control panel.
5. Define X variable.
6. Define overlay variable.
7. Add bar element.
8. Set legend position.
9. Use interval bar style.
10. Summarize data by sum.

Example 704

Summary: Creates a variability chart with nested factors using Graph Builder, displaying standard deviation charts and configuring bar style to interval.

Code:

Open("data_table.jmp");
Graph Builder(
    Show Control Panel( 0 ),
    Variables( X( :age ), Y( :height ), Y( :weight, Position( 1 ) ) ),
    Elements( Bar( X, Y( 1 ), Y( 2 ), Legend( 8 ), Bar Style( "Interval" ) ) )
);

Code Explanation:

1. Open data table.
2. Launch Graph Builder.
3. Hide control panel.
4. Set X variable to age.
5. Set first Y variable to height.
6. Set second Y variable to weight.
7. Place weight on position 1.
8. Add bar element.
9. Set bar style to interval.
10. Display graph.

Example 705

Summary: Creates a bar chart with nested factors using Graph Builder, displaying summary statistics and labeling bars by value.

Code:

dt under test = Open("data_table.jmp");
obj = Graph Builder(
    Size( 570, 465 ),
    Show Control Panel( 0 ),
    Variables(
        X( :Age ),
        Group Y( :Gender ),
        Group Y( :Rating Class, Order By( :Name( "Claim(Y/N)" ), Ascending, Order Statistic( "Mean" ) ) )
    ),
    Elements( Bar( X, Legend( 49 ), Summary Statistic( "Sum" ), Label( "Label by Value" ) ) ),
    SendToReport(
        Dispatch( {}, "Graph Builder", OutlineBox,
            {Set Title( "Graph Builder Bar - label by value should not display too many decimal places" )}
        )
    )
);

Code Explanation:

1. Open data table.
2. Create Graph Builder object.
3. Set graph size to 570x465.
4. Hide control panel.
5. Assign X variable as Age.
6. Assign Gender as first Group Y.
7. Assign Rating Class as second Group Y.
8. Sort Rating Class by Claim(Y/N) ascending.
9. Add bar element with summary statistic Sum.
10. Label bars by value with decimal formatting.

Example 706

Summary: Creates a variability chart with nested factors using operator and part configurations, displaying standard deviation charts.

Code:

Open("data_table.jmp");
Graph Builder(
    show control panel( 0 ),
    Variables(
        X( :Process 1 ),
        X( :Process 2, Position( 1 ) ),
        X( :Process 3, Position( 1 ) ),
        X( :Process 4, Position( 1 ) ),
        X( :Process 5, Position( 1 ) ),
        X( :Process 6, Position( 1 ) ),
        X( :Process 7, Position( 1 ) )
    ),
    Elements( Bar( X( 1 ), X( 2 ), X( 3 ), X( 4 ), X( 5 ), X( 6 ), X( 7 ), Legend( 5 ), Label( "Label by Value" ) ) )
);

Code Explanation:

1. Open data table;
2. Launch Graph Builder.
3. Hide control panel.
4. Set X variables.
5. Position multiple X variables.
6. Add bar element.
7. Assign X variables to bar.
8. Enable legend.
9. Label bars by value.
10. Display graph.

Example 707

Summary: Creates three variability charts with nested factors using Graph Builder, showcasing different bar styles and labeling options.

Code:

Open("data_table.jmp");
Graph Builder(
    Show Control Panel( 0 ),
    Variables( X( :Region ), Y( :SO2 ), Y( :NO, Position( 1 ) ), Y( :OZONE, Position( 1 ) ) ),
    Elements(
        Bar(
            X,
            Y( 1 ),
            Y( 2 ),
            Y( 3 ),
            Legend( 18 ),
            Bar Style( "Bullet" ),
            Error Interval( "None" ),
            Label( "Label by Percent of Total Values" )
        )
    )
);
Graph Builder(
    Show Control Panel( 0 ),
    Variables( X( :Region ), Y( :SO2 ), Y( :NO, Position( 1 ) ), Y( :OZONE, Position( 1 ) ) ),
    Elements( Bar( X, Y( 1 ), Y( 2 ), Y( 3 ), Legend( 18 ), Bar Style( "Nested" ), Error Interval( "None" ), Label( "Label by Row" ) ) )
);
Graph Builder(
    Show Control Panel( 0 ),
    Variables( X( :Region ), Y( :SO2 ), Y( :NO, Position( 1 ) ), Y( :OZONE, Position( 1 ) ) ),
    Elements(
        Bar( X, Y( 1 ), Y( 2 ), Y( 3 ), Legend( 18 ), Bar Style( "Interval" ), Error Interval( "None" ), Label( "Label by Value" ) )
    )
);

Code Explanation:

1. Open data table;
2. Create first Graph Builder.
3. Hide control panel.
4. Set X variable.
5. Set Y variables.
6. Add bar element.
7. Style bar as bullet.
8. No error interval.
9. Label by percent of total values.
10. Create second Graph Builder.
11. Hide control panel.
12. Set X variable.
13. Set Y variables.
14. Add bar element.
15. Style bar as nested.
16. No error interval.
17. Label by row.
18. Create third Graph Builder.
19. Hide control panel.
20. Set X variable.
21. Set Y variables.
22. Add bar element.
23. Style bar as interval.
24. No error interval.
25. Label by value.

Example 708

Summary: Creates a variability chart with nested factors using Graph Builder, configuring window size, hiding control panel and legend, defining X and overlay variables, adding bar elements, and formatting height scale.

Code:

dt = Open("data_table.jmp");
Graph Builder(
    Size( 358, 276 ),
    Show Control Panel( 0 ),
    Show Legend( 0 ),
    Variables( X( :height ), Overlay( :age ) ),
    Elements( Bar( X, Legend( 4 ), Response Axis( "X" ), Label( "Label by Value" ) ) ),
    SendToReport( Dispatch( {}, "height", ScaleBox, {Format( "Fixed Dec", 12, 1 ), Min( 60 ), Max( 80 ), Inc( 2.5 ), Minor Ticks( 0 )} ) )
);

Code Explanation:

1. Open data table.
2. Launch Graph Builder.
3. Set window size.
4. Hide control panel.
5. Hide legend.
6. Define X and overlay variables.
7. Add bar element.
8. Label bars by value.
9. Format height scale.
10. Set height scale limits and increments.

Example 709

Summary: Creates a bar chart with nested factors using Graph Builder, overlaying by sex and filtering data by age 12.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 416, 259 ),
    Show Control Panel( 0 ),
    Variables( Overlay( :sex ) ),
    Elements( Bar( Legend( 6 ), Label( "Label by Value" ) ) ),
    Local Data Filter( Add Filter( columns( :age ), Where( :age == 12 ), Display( :age, Size( 160, 90 ), List Display ) ) )
);

Code Explanation:

1. Open data table;
2. Launch Graph Builder.
3. Set window size.
4. Hide control panel.
5. Overlay by sex variable.
6. Add bar element.
7. Label bars by value.
8. Add local data filter.
9. Filter by age 12.
10. Display age filter.

Example 710

Summary: Creates two Graph Builder windows to visualize nested factors using operator and part configurations, with interactive local data filters for filtering Cut column values.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 310, 297 ),
    Show Control Panel( 0 ),
    Variables( X( :Report ), Y( :Price ), Group Y( :Clarity ), Color( :Color ) ),
    Elements( Bar( X, Y, Legend( 20 ) ) ),
    Local Data Filter(
        Mode( Include( 0 ) ),
        Inverse( 1 ),
        Add Filter( columns( :Cut ), Where( :Cut == "Good" ), Display( :Cut, Size( 160, 60 ), List Display ) )
    )
);
Graph Builder(
    Size( 465, 365 ),
    Show Control Panel( 0 ),
    Variables( X( :Color ), Y( :Price ), Group Y( :Clarity, Size( 41 ) ), Overlay( :Report ) ),
    Elements( Bar( X, Y, Legend( 40 ) ) ),
    Local Data Filter(
        Mode( Include( 0 ) ),
        Add Filter( columns( :Cut ), Where( :Cut == "Excellent" ), Display( :Cut, Size( 160, 60 ), List Display ) )
    )
);

Code Explanation:

1. Open data table;
2. Create first Graph Builder window.
3. Set size 310x297.
4. Hide control panel.
5. Define X, Y, Group Y, and Color variables.
6. Add bar element with legend.
7. Enable local data filter.
8. Set filter mode to include.
9. Invert filter condition.
10. Add filter for Cut column.
11. Create second Graph Builder window.
12. Set size 465x365.
13. Hide control panel.
14. Define X, Y, Group Y, and Overlay variables.
15. Add bar element with legend.
16. Enable local data filter.
17. Set filter mode to include.
18. Add filter for Cut column.

Example 711

Summary: Creates a variability chart with nested factors using Graph Builder, selecting single marital status and configuring legend models for display.

Code:

dt = Open("data_table.jmp");
dt << select where( :marital status == "Single" );
dt << Graph Builder(
    Size( 431, 315 ),
    Show Control Panel( 0 ),
    Variables( X( :sex ), Overlay( :marital status ) ),
    Elements( Bar( X, Legend( 3 ) ) ),
    SendToReport(
        Dispatch( {}, "400", ScaleBox,
            {Legend Model(
                3,
                Properties( 0, {Fill Pattern( "vertical medium" )}, Item ID( "Married", 1 ) ),
                Properties( 1, {Fill Pattern( "horizontal medium" )}, Item ID( "Single", 1 ) )
            )}
        )
    )
);

Code Explanation:

1. Open data table.
2. Select single marital status.
3. Launch Graph Builder.
4. Set graph size.
5. Hide control panel.
6. Define X and overlay variables.
7. Add bar element.
8. Send report settings.
9. Configure legend model.
10. Set fill patterns for categories.

Example 712

Summary: Creates a variability chart with nested factors using Graph Builder, configuring X, Y, and overlay variables, and displaying standard deviation charts.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 651, 398 ),
    Show Control Panel( 0 ),
    Variables( X( :Weather Condition ), Y( :Total Fatal Injuries ), Overlay( :Number of Engines ) ),
    Elements( Bar( X, Y, Legend( 71 ) ) ),
    SendToReport(
        Dispatch( {}, "Total Fatal Injuries", ScaleBox,
            {Scale( "Log" ), Format( "Best", 10 ), Min( 0.0165323343009725 ), Max( 148.791008708753 ), Inc( 1 ), Minor Ticks( 1 )}
        )
    )
);

Code Explanation:

1. Open data table;
2. Create Graph Builder window.
3. Set window size.
4. Hide control panel.
5. Define X, Y, and overlay variables.
6. Add bar element.
7. Set legend position.
8. Configure Y-axis scale.
9. Set Y-axis format.
10. Define Y-axis range and ticks.

Example 713

Summary: Creates two Graph Builder windows to visualize height data with nested factors, utilizing bar elements and legends.

Code:

Open("data_table.jmp");
Graph Builder( Size( 533, 418 ), Show Control Panel( 0 ), Variables( Y( :height ) ), Elements( Bar( Y, Legend( 4 ) ) ) );
Graph Builder( Show Control Panel( 0 ), Variables( Y( :height ), Overlay( :sex ) ), Elements( Bar( Y, Legend( 6 ) ) ) );

Code Explanation:

1. Open data_table data
2. Create Graph Builder window.
3. Set window size.
4. Hide control panel.
5. Add height to Y axis.
6. Add bar element.
7. Assign legend 4.
8. Create second Graph Builder.
9. Hide control panel.
10. Add height to Y axis.
11. Add sex to overlay.
12. Add bar element.
13. Assign legend 6.

Example 714

Summary: Creates three bar graphs using Graph Builder to visualize height data, with nested factors for age and sex.

Code:

Open("data_table.jmp");
Graph Builder( Size( 533, 418 ), Show Control Panel( 0 ), Variables( Y( :height ) ), Elements( Bar( Y, Legend( 4 ) ) ) );
Graph Builder( Show Control Panel( 0 ), Variables( Y( :height ), Overlay( :sex ) ), Elements( Bar( Y, Legend( 6 ) ) ) );
Graph Builder(
    Show Control Panel( 0 ),
    Size( 607, 582 ),
    Variables( Y( :height ), Group X( :age ), Group Y( :sex ), Overlay( :sex ) ),
    Elements( Bar( Y, Legend( 6 ) ) )
);

Code Explanation:

1. Open data table;
2. Create bar graph for height.
3. Create bar graph for height by sex.
4. Create complex bar graph.

Example 715

Summary: Creates a variability chart with nested factors using Graph Builder, displaying standard deviation charts and customizing legend properties.

Code:

dt = Open("data_table.jmp");
gb = dt << Graph Builder(
    Size( 522, 449 ),
    Show Control Panel( 0 ),
    Variables(
        X( :Pie Type, Order By( :"Sales (K)"n, Descending, Order Statistic( "Mean" ) ), Size By( :Outlets, Size Statistic( "Mean" ) ) ),
        Y( :"Sales (K)"n ),
        Color( :Pie Type )
    ),
    Elements( Bar( X, Y, Legend( 6 ) ) ),
    SendToReport(
        Dispatch( {}, "400", ScaleBox,
            {Legend Model(
                6,
                Properties( 0, {Fill Color( 3 )}, Item ID( "Apple", 1 ) ),
                Properties( 1, {Fill Color( 19 )}, Item ID( "Cherry", 1 ) ),
                Properties( 3, {Fill Color( 70 )}, Item ID( "Peach", 1 ) )
            )}
        )
    )
);

Code Explanation:

1. Open data table.
2. Create Graph Builder object.
3. Set graph size.
4. Hide control panel.
5. Define X variable: Pie Type.
6. Define Y variable: Sales (K).
7. Define color variable: Pie Type.
8. Add bar element to graph.
9. Customize legend properties.
10. Assign colors to specific pie types.

Example 716

Summary: Creates two variability charts with nested factors using Graph Builder, displaying standard deviation charts and customizing legend colors.

Code:

dt = Open("data_table.jmp");
gb = dt << Graph Builder(
    Size( 522, 449 ),
    Show Control Panel( 0 ),
    Variables(
        X( :Pie Type, Order By( :"Sales (K)"n, Descending, Order Statistic( "Mean" ) ), Size By( :Outlets, Size Statistic( "Mean" ) ) ),
        Y( :"Sales (K)"n ),
        Color( :Pie Type )
    ),
    Elements( Bar( X, Y, Legend( 6 ) ) ),
    SendToReport(
        Dispatch( {}, "400", ScaleBox,
            {Legend Model(
                6,
                Properties( 0, {Fill Color( 3 )}, Item ID( "Apple", 1 ) ),
                Properties( 1, {Fill Color( 19 )}, Item ID( "Cherry", 1 ) ),
                Properties( 3, {Fill Color( 70 )}, Item ID( "Peach", 1 ) )
            )}
        )
    )
);
dt2 = Open("data_table.jmp");
gb2 = dt2 << Graph Builder(
    Size( 534, 450 ),
    Show Control Panel( 0 ),
    Legend Position( "Inside Right" ),
    Variables(
        X(
            :Size Co,
            Order By( :"profit/emp"n, Descending, Order Statistic( "Mean" ) ),
            Size By( :"# Employees"n, Size Statistic( "Mean" ) )
        ),
        Y( :"profit/emp"n ),
        Color( :Size Co )
    ),
    Elements( Bar( X, Y, Legend( 13 ) ) )
);

Code Explanation:

1. Open data table;
2. Create Graph Builder.
3. Set graph size.
4. Hide control panel.
5. Define X, Y, and color variables.
6. Add bar element.
7. Customize legend colors.
8. Open data table;
9. Create second Graph Builder.
10. Set second graph size.

Example 717

Summary: Creates a bar chart to visualize frequency distribution of Squat values, with missing value codes set to 330.

Code:

Open("data_table.jmp");
:Squat << set property( "missing value codes", {330} );
Graph Builder(
    Show Control Panel( 0 ),
    Variables( X( :Position ), Frequency( :Squat ) ),
    Elements( Bar( X, Legend( 10 ), Summary Statistic( "Sum" ), Label( "Label by Value" ) ) )
);

Code Explanation:

1. Open data table;
2. Set missing value code for Squat.
3. Create Graph Builder.
4. Hide control panel.
5. Set X variable to Position.
6. Set Y variable to Squat.
7. Add Bar element.
8. Use Legend for grouping.
9. Summarize data by sum.
10. Label bars by value.

Example 718

Summary: Creates a variability chart with nested factors using Graph Builder, displaying standard deviation charts and labeling by value.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 518, 324 ),
    Show Control Panel( 0 ),
    Variables( X( :sex ), Y( :height ) ),
    Elements( Bar( X, Y, Legend( 4 ), Error Bars( "Standard Deviation" ), Label( "Label by Value" ) ) )
);

Code Explanation:

1. Open data table;
2. Create Graph Builder window.
3. Set graph size.
4. Hide control panel.
5. Assign X variable.
6. Assign Y variable.
7. Add bar element.
8. Set legend position.
9. Add error bars.
10. Label by value.

Example 719

Summary: Creates a bar chart with local data filtering to display countries visited, utilizing Graph Builder and its elements.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 522, 452 ),
    Show Control Panel( 0 ),
    Variables( X( :countries visited ) ),
    Elements( Bar( X, Legend( 2 ) ) ),
    Local Data Filter(
        Add Filter(
            columns( :countries visited ),
            Match Any( Where( :countries visited == "Canada" ) ),
            Display( :countries visited, Find( Set Text( "" ) ) )
        )
    )
);

Code Explanation:

1. Open data table.
2. Create Graph Builder object.
3. Set graph size.
4. Hide control panel.
5. Define X variable.
6. Add bar element.
7. Assign legend to bar.
8. Add local data filter.
9. Set filter criteria.
10. Display filter for user input.

Example 720

Summary: Creates a variability chart with nested factors using Graph Builder, displaying standard deviation charts and utilizing operator and part configurations.

Code:

Open("data_table.jmp");
Graph Builder(
    Show Control Panel( 0 ),
    Variables( X( :age ), Y( :height ), Y( :weight, Position( 1 ) ) ),
    Elements( Bar( X, Y( 1 ), Y( 2 ), Legend( 8 ) ) )
);

Code Explanation:

1. Open data table;
2. Launch Graph Builder.
3. Hide control panel.
4. Set X variable: age.
5. Set first Y variable: height.
6. Set second Y variable: weight.
7. Position second Y on left.
8. Add bar element.
9. Assign X to bar.
10. Assign Y1 to bar.

Example 721

Summary: Creates a variability chart with nested factors using Graph Builder, displaying standard deviation charts and utilizing range bar style for label by value.

Code:

Open("data_table.jmp");
Graph Builder(
    Show Control Panel( 0 ),
    Variables( X( :age ), Y( :height ), Overlay( :sex ) ),
    Elements( Bar( X, Y, Legend( 6 ), Bar Style( "Range" ), Label( "Label by Value" ) ) )
);

Code Explanation:

1. Open data table;
2. Launch Graph Builder.
3. Hide control panel.
4. Set X variable to age.
5. Set Y variable to height.
6. Overlay by sex.
7. Add bar element.
8. Use range bar style.
9. Label bars by value.
10. Display graph.

Example 722

Summary: Creates a variability chart with nested factors using Graph Builder, transforming columns for count and rank, and displaying standard deviation charts.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 661, 564 ),
    Show Control Panel( 0 ),
    Variables(
        X( :Country, Order By( :Country, Ascending, Order Statistic( "N" ) ) ),
        X( :Type, Position( 1 ), Order By( :Country, Ascending, Order Statistic( "N" ) ) )
    ),
    Elements( Bar( X( 1 ), X( 2 ), Legend( 8 ) ) )
);
Graph Builder(
    Transform Column( "Count", Formula( Col Number( 1, :Country, :Type ) ) ),
    Transform Column( "Count rank", "Nominal", Formula( Col Rank( :Count, <<Tie( "minimum" ) ) ) ),
    Size( 578, 437 ),
    Show Control Panel( 0 ),
    Variables( X( :Country ), X( :Count rank, Position( 1 ) ), X( :Type, Position( 1 ) ) ),
    Elements( Bar( X( 1 ), X( 2 ), X( 3 ), Legend( 6 ) ) ),
    SendToReport(
        Dispatch( {}, "Country", ScaleBox, {Label Row( 2, {Automatic Tick Marks( 0 ), Show Major Labels( 0 ), Show Major Ticks( 0 )} )} )
    )
);

Code Explanation:

1. Open data table.
2. Create first Graph Builder.
3. Set graph size.
4. Hide control panel.
5. Define X variables.
6. Add bar element.
7. Create second Graph Builder.
8. Transform columns for count and rank.
9. Set new graph size.
10. Hide control panel again.

Example 723

Summary: Creates a variability chart with nested factors using operator and part configurations, displaying standard deviation charts within Graph Builder.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 534, 466 ),
    Show Control Panel( 0 ),
    Variables( X( :Report ), X( :Cut, Position( 1 ) ), Overlay( :Color ) ),
    Elements( Bar( X( 1 ), X( 2 ), Legend( 5 ), Bar Style( "Treemap" ) ) )
);

Code Explanation:

1. Open data table;
2. Launch Graph Builder.
3. Set size to 534x466.
4. Hide control panel.
5. Set X to Report.
6. Add Cut to X, position 1.
7. Set Overlay to Color.
8. Add Bar element.
9. Set first X to 1.
10. Set second X to 2.
11. Set legend to 5.
12. Use Treemap bar style.

Example 724

Summary: Creates a variability chart with nested factors using Graph Builder, displaying standard deviation charts and formatting labels as currency.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 919, 735 ),
    Variables( X( :Cut ), Y( :Price ), Color( :Color ) ),
    Elements(
        Bar( X, Y, Legend( 4 ), Label( "Label by Value" ), Label Format( "Currency", "USD", 11, 2 ) ),
        Caption Box( X, Y, Legend( 5 ), Per Factor( 1 ), Number Format( "Currency", "USD", 11, 2 ) )
    )
);

Code Explanation:

1. Open data table;
2. Create Graph Builder.
3. Set size 919x735.
4. Set X variable: Cut.
5. Set Y variable: Price.
6. Set Color variable: Color.
7. Add Bar element.
8. Label by Value.
9. Format labels as Currency USD.
10. Add Caption Box.

Example 725

Summary: Creates a variability chart with nested factors using Graph Builder, displaying standard deviation charts and customizing height levels.

Code:

dt = Open("data_table.jmp");
Graph Builder(
    Size( 469, 301 ),
    Show Control Panel( 0 ),
    Variables(
        X( :age ),
        Y( :weight ),
        Overlay(
            :height,
            custom levels(
                {{., "< 50"}, {50, "50 — 55"}, {55, "55 — 60"}, {60, "60 — 65"}, {65, "65 — 70"}, {70, "70 — 75"}, {75, "≥ 75"}}
            )
        )
    ),
    Elements( Bar( X, Y, Legend( 29 ), Label( "Label by Value" ) ) )
);

Code Explanation:

1. Open data table.
2. Create Graph Builder window.
3. Set window size.
4. Hide control panel.
5. Define X variable as age.
6. Define Y variable as weight.
7. Overlay height variable.
8. Customize height levels.
9. Add bar element.
10. Label bars by value.

Example 726

Summary: Creates a variability chart with nested factors using operator and part configurations, displaying standard deviation charts in Graph Builder.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 721, 374 ),
    Show Control Panel( 0 ),
    Variables( Overlay( :age ) ),
    Elements( Bar( Legend( 5 ), Label( "Label by Value" ) ) )
);

Code Explanation:

1. Open data table;
2. Launch Graph Builder.
3. Set window size.
4. Hide control panel.
5. Overlay variable by age.
6. Add bar element.
7. Assign legend position.
8. Label bars by value.

Example 727

Summary: Creates a bar chart with nested factors using Graph Builder, overlaying by age and summarizing statistics by sum.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 529, 370 ),
    Show Control Panel( 0 ),
    Variables( Overlay( :age ) ),
    Elements( Bar( Legend( 5 ), Summary Statistic( "Sum" ), Label( "Label by Value" ) ) )
);

Code Explanation:

1. Open data table;
2. Launch Graph Builder.
3. Set window size.
4. Hide control panel.
5. Overlay by age variable.
6. Add bar element.
7. Use legend for overlay.
8. Summarize statistics by sum.
9. Label bars by value.
10. Display graph.

Example 728

Summary: Creates a variability chart with nested factors using Graph Builder, assigning variables to axes and plotting a bar chart with customized legend properties.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 570, 516 ),
    Show Control Panel( 0 ),
    Variables( X( :age ), Y( :weight ), Overlay( :sex ) ),
    Elements( Bar( X, Y, Legend( 20 ) ) ),
    SendToReport( Dispatch( {}, "400", ScaleBox, {Legend Model( 20, Properties( 1, {Fill Color( 6 ), Transparency( 0.5 )} ) )} ) )
);

Code Explanation:

1. Open data table;
2. Create new Graph Builder window.
3. Set window size.
4. Hide control panel.
5. Assign variables to axes.
6. Add overlay variable.
7. Plot bar chart.
8. Customize legend properties.
9. Set fill color for bars.
10. Adjust transparency of bars.

Example 729

Summary: Creates a variability chart with nested factors using operator and part configurations, displaying standard deviation charts in Graph Builder.

Code:

Open("data_table.jmp");
Graph Builder(
    Transform Column( "-weight", Format( "Fixed Dec", 5, 0 ), Formula( -:weight ) ),
    Size( 606, 329 ),
    Show Control Panel( 0 ),
    Variables( X( :age ), Y( :"-weight"n ), Y( :weight ), Overlay( :sex ) ),
    Elements( Position( 1, 1 ), Bar( X, Y, Legend( 6 ) ) ),
    Elements( Position( 1, 2 ), Bar( X, Y, Legend( 4 ) ) ),
    SendToReport(
        Dispatch( {}, "-weight", ScaleBox, {Max( 36.3825 )} ),
        Dispatch( {}, "weight", ScaleBox, {Min( -36.587835 ), Max( 165.864852 )} ),
        Dispatch( {}, "400", ScaleBox,
            {Legend Model(
                6,
                Properties( 0, {Fill Color( 67 ), Fill Pattern( "honeycomb" )}, Item ID( "F", 1 ) ),
                Properties( 1, {Fill Color( 21 ), Fill Pattern( "left slant medium" )}, Item ID( "M", 1 ) )
            ), Legend Model(
                4,
                Base( 0, 0, 0, Item ID( "F", 1 ) ),
                Base( 1, 0, 1, Item ID( "M", 1 ) ),
                Properties( 0, {Fill Color( 67 ), Fill Pattern( "grid dots" )}, Item ID( "F", 1 ) ),
                Properties( 1, {Fill Color( 21 ), Fill Pattern( "grid dots" )}, Item ID( "M", 1 ) )
            )}
        ),
        Dispatch( {}, "400", LegendBox, {Legend Position( {6, [2, 3], 4, [0, 1]} )} )
    )
);

Code Explanation:

1. Open data table;
2. Create new column for negative weight.
3. Set graph size.
4. Hide control panel.
5. Define variables for graph.
6. Add first bar element.
7. Add second bar element.
8. Set scale for negative weight.
9. Set scale for weight.
10. Customize legend patterns and colors.

Example 730

Summary: Creates two bar charts with nested factors using Graph Builder, displaying standard deviation charts for Type and Horsepower variables with Country as an overlay.

Code:

Open("data_table.jmp");
Graph Builder(
    Show Control Panel( 0 ),
    Variables( X( :Type ), Y( :Horsepower ), Overlay( :Country ) ),
    Elements( Bar( X, Y, Legend( 2 ), Bar Style( "Side by side" ), Summary Statistic( "% of Total" ), Label( "Percent" ) ) )
);
Graph Builder(
    Show Control Panel( 0 ),
    Variables( X( :Type ), Y( :Horsepower ), Overlay( :Country ) ),
    Elements( Bar( X, Y, Legend( 2 ), Bar Style( "Side by side" ), Summary Statistic( "% of Total" ), Label( "Value" ) ) )
);

Code Explanation:

1. Open data_table data
2. Create first graph builder.
3. Hide control panel.
4. Set X variable: Type.
5. Set Y variable: Horsepower.
6. Set overlay variable: Country.
7. Add bar element.
8. Use side-by-side bar style.
9. Calculate percent of total.
10. Label bars with percent.
11. Create second graph builder.
12. Hide control panel.
13. Set same variables.
14. Add bar element.
15. Use side-by-side bar style.
16. Calculate percent of total.
17. Label bars with value.

Example 731

Summary: Creates a bar chart with nested factors using Graph Builder, displaying the 'season' variable on the x-axis and the 'miles' variable on the y-axis.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 450, 320 ),
    Show Control Panel( 0 ),
    Variables( X( :season ), Y( :miles ) ),
    Elements( Bar( X, Y, Legend( 4 ), Bar Style( "Side by side" ), Summary Statistic( "% of Total" ) ) )
);

Code Explanation:

1. Open data table;
2. Launch Graph Builder.
3. Set window size 450x320.
4. Hide control panel.
5. Assign X variable: season.
6. Assign Y variable: miles.
7. Add Bar element.
8. Set bar style: Side by side.
9. Use summary statistic: % of Total.
10. Display graph.

Example 732

Summary: Creates a bar chart to display the percentage of total for each age group, utilizing Graph Builder and hiding control panel and legend.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 455, 338 ),
    Show Control Panel( 0 ),
    Show Legend( 0 ),
    Variables( X( :age ) ),
    Elements( Bar( X, Legend( 1 ), Summary Statistic( "% of Total" ) ) )
);

Code Explanation:

1. Open data table;
2. Launch Graph Builder.
3. Set window size.
4. Hide control panel.
5. Hide legend.
6. Assign age to X-axis.
7. Add bar element.
8. Enable legend for bars.
9. Set summary statistic to percentage of total.
10. Display graph.

Example 733

Summary: Creates a bar chart to visualize the distribution of age groups, utilizing Graph Builder and displaying the percentage of total as a summary statistic.

Code:

dt = Open("data_table.jmp");
gb1 = dt << Graph Builder(
    Show Control Panel( 0 ),
    Variables( X( :age ) ),
    Elements( Bar( X, Legend( 3 ), Summary Statistic( "% of Total" ) ) )
);

Code Explanation:

1. Open data table;
2. Create Graph Builder object.
3. Hide control panel.
4. Set X variable to "age".
5. Add Bar element.
6. Set legend to 3.
7. Use "% of Total" summary statistic.

Example 734

Summary: Creates two Graph Builder objects to visualize nested factors using bar charts with % of Total summary statistics, hiding control panels and setting X variables for age.

Code:

dt = Open("data_table.jmp");
gb1 = dt << Graph Builder(
    Show Control Panel( 0 ),
    Variables( X( :age ) ),
    Elements( Bar( X, Legend( 3 ), Summary Statistic( "% of Total" ) ) )
);
gb2 = dt << Graph Builder(
    Show Control Panel( 0 ),
    Variables( X( :age ), Y( Transform Column( "c", Formula( 1 ) ) ) ),
    Elements( Bar( X, Y, Legend( 3 ), Summary Statistic( "% of Total" ) ) )
);

Code Explanation:

1. Open data table;
2. Create Graph Builder object gb1.
3. Hide control panel.
4. Set X variable to age.
5. Add bar element with % of Total summary.
6. Create Graph Builder object gb2.
7. Hide control panel.
8. Set X variable to age.
9. Add Y variable as transformed column "c".
10. Add bar element with % of Total summary.

Example 735

Summary: Creates a variability chart with nested factors using Graph Builder, displaying standard deviation charts and utilizing operator and part configurations.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 345, 283 ),
    Show Control Panel( 0 ),
    Show Legend( 0 ),
    Variables( Y( :weight ), Overlay( :age ) ),
    Elements( Bar( Y, Legend( 6 ), Summary Statistic( "First Quartile" ) ) )
);

Code Explanation:

1. Open data table;
2. Launch Graph Builder.
3. Set window size.
4. Hide control panel.
5. Hide legend.
6. Assign weight to Y axis.
7. Assign age for overlay.
8. Add bar element.
9. Use first quartile summary.
10. Display graph.

Example 736

Summary: Creates two Graph Builder windows to visualize the distribution of weight by age, with separate charts for first and third quartiles.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 345, 283 ),
    Show Control Panel( 0 ),
    Show Legend( 0 ),
    Variables( Y( :weight ), Overlay( :age ) ),
    Elements( Bar( Y, Legend( 6 ), Summary Statistic( "First Quartile" ) ) )
);
Graph Builder(
    Size( 425, 283 ),
    Show Control Panel( 0 ),
    Show Legend( 0 ),
    Variables( Y( :weight ), Overlay( :age ) ),
    Elements( Bar( Y, Legend( 6 ), Summary Statistic( "Third Quartile" ) ) )
);

Code Explanation:

1. Open data table.
2. Create first Graph Builder window.
3. Set window size.
4. Hide control panel.
5. Hide legend.
6. Assign variables: weight (Y), age (Overlay).
7. Add bar element for first quartile.
8. Create second Graph Builder window.
9. Set window size.
10. Hide control panel and legend.

Example 737

Summary: Creates a variability chart with nested factors using Graph Builder, displaying standard deviation charts and color-coded by height summary statistics.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 528, 450 ),
    Show Control Panel( 0 ),
    Variables( X( :age ), Y( :height ), Overlay( :weight ), Color( :height, Summary Statistic( "sum" ) ) ),
    Elements( Bar( X, Y, Legend( 7 ), Bar Style( "Range" ) ) )
);

Code Explanation:

1. Open data table;
2. Create new Graph Builder window.
3. Set window size to 528x450.
4. Hide control panel.
5. Define X variable as age.
6. Define Y variable as height.
7. Define overlay variable as weight.
8. Color bars by height summary statistic.
9. Add bar element.
10. Set bar style to range.

Example 738

Summary: Creates a variability chart with nested factors using Graph Builder, displaying standard deviation charts and configuring height scale.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 893, 186 ),
    Show Control Panel( 0 ),
    Fit to Window( "Maintain Aspect Ratio" ),
    Variables( X( :height ), Y( :weight ), Overlay( :sex ) ),
    Elements( Bar( X, Y, Legend( 10 ), Bar Style( "Range" ) ) ),
    SendToReport( Dispatch( {}, "height", ScaleBox, {Format( "Best", 12 ), Min( 50 ), Max( 70 ), Inc( 1 ), Minor Ticks( 0 )} ) )
);

Code Explanation:

1. Open data table.
2. Create graph builder window.
3. Set window size.
4. Hide control panel.
5. Fit to window.
6. Define variables: X(height), Y(weight), Overlay(sex).
7. Add bar element.
8. Set bar style to range.
9. Configure height scale.
10. Display report.

Example 739

Summary: Creates two Graph Builder windows to visualize the relationship between height and weight, with sex as an overlay, using bar elements with range style and customized scale boxes.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 893, 186 ),
    Show Control Panel( 0 ),
    Fit to Window( "Maintain Aspect Ratio" ),
    Variables( X( :height ), Y( :weight ), Overlay( :sex ) ),
    Elements( Bar( X, Y, Legend( 10 ), Bar Style( "Range" ) ) ),
    SendToReport( Dispatch( {}, "height", ScaleBox, {Format( "Best", 12 ), Min( 50 ), Max( 70 ), Inc( 1 ), Minor Ticks( 0 )} ) )
);
Graph Builder(
    Size( 824, 350 ),
    Show Control Panel( 0 ),
    Variables( X( :weight ), Y( :height ), Overlay( :sex ) ),
    Elements( Bar( X, Y ) )
);

Code Explanation:

1. Open data table;
2. Create first Graph Builder window.
3. Set window size.
4. Hide control panel.
5. Fit to window.
6. Define X, Y, and overlay variables.
7. Add bar element with range style.
8. Customize height scale.
9. Create second Graph Builder window.
10. Set window size.
11. Hide control panel.
12. Define X, Y, and overlay variables.
13. Add bar element.

Example 740

Summary: Creates a variability chart with nested factors using Graph Builder, excluding rows based on smoking history and displaying standard deviation charts.

Code:

dt = Open("data_table.jmp");
myExcludedRows = dt << get rows where( :Smoking History == "pipes" | :SmokingHistory == "cigarettes" );
dt << select rows( myExcludedRows );
dt << exclude;
Graph Builder(
    Show Control Panel( 0 ),
    Variables( X( :Heart History ), Overlay( :Smoking History ) ),
    Elements( Bar( X, Legend( 8 ), Bar Style( "Range" ), Summary Statistic( "Sum" ), Label( "Label by Value" ) ) )
);

Code Explanation:

1. Open data table.
2. Identify excluded rows.
3. Select excluded rows.
4. Exclude selected rows.
5. Launch Graph Builder.
6. Hide control panel.
7. Set X variable.
8. Set overlay variable.
9. Add bar element.
10. Configure bar style and summary.

Example 741

Summary: Creates two variability charts with nested factors using Graph Builder, displaying standard deviation charts and configuring bar elements with range styles.

Code:

Open("data_table.jmp");
Graph Builder(
    Show Control Panel( 0 ),
    Variables( X( :age ), Y( :height ), Y( :weight, Position( 1 ) ), Overlay( :sex ) ),
    Elements( Bar( X, Y( 1 ), Y( 2 ), Legend( 5 ), Bar Style( "Range" ), Label( "Label by Value" ) ) )
);
Graph Builder(
    Size( 863, 258 ),
    Show Control Panel( 0 ),
    Variables( X( :sex ), Y( :height ), Y( :weight, Position( 1 ) ), Overlay( :age ) ),
    Elements( Bar( X, Y( 1 ), Y( 2 ), Legend( 7 ), Bar Style( "Range" ), Label( "Label by Value" ) ) )
);

Code Explanation:

1. Open data table;
2. Create first Graph Builder window.
3. Hide control panel.
4. Set X variable to age.
5. Set Y variables to height and weight.
6. Overlay by sex.
7. Add bar element.
8. Use range bar style.
9. Label by value.
10. Create second Graph Builder window.
11. Set size to 863x258.
12. Hide control panel.
13. Set X variable to sex.
14. Set Y variables to height and weight.
15. Overlay by age.
16. Add bar element.
17. Use range bar style.
18. Label by value.

Example 742

Summary: Creates a variability chart with nested factors using Graph Builder, displaying standard deviation charts and summarizing data by sum.

Code:

Open("data_table.jmp");
Graph Builder(
    Show Control Panel( 0 ),
    Variables( X( :Heart History ), Overlay( :Smoking History ) ),
    Elements( Bar( X, Legend( 8 ), Bar Style( "Range" ), Summary Statistic( "Sum" ), Label( "Label by Value" ) ) )
);

Code Explanation:

1. Open data table;
2. Launch Graph Builder.
3. Hide control panel.
4. Set X variable.
5. Add overlay variable.
6. Create bar element.
7. Use legend for categories.
8. Apply range bar style.
9. Summarize data by sum.
10. Label bars by value.

Example 743

Summary: Excludes rows based on smoking history and generates a bar chart to visualize heart history data, utilizing Graph Builder.

Code:

dt = Open("data_table.jmp");
myExcludedRows = dt << get rows where( :Smoking History == "pipes" | :Smoking History == "cigarettes" );
dt << select rows( myExcludedRows );
dt << exclude;
Graph Builder(
    Show Control Panel( 0 ),
    Variables( X( :Heart History ), Overlay( :Smoking History ) ),
    Elements( Bar( X, Legend( 8 ), Bar Style( "Range" ), Summary Statistic( "Sum" ), Label( "Label by Value" ) ) )
);

Code Explanation:

1. Open data table.
2. Define excluded rows.
3. Select excluded rows.
4. Exclude selected rows.
5. Create Graph Builder.
6. Hide control panel.
7. Set X variable.
8. Set overlay variable.
9. Add bar element.
10. Configure bar style and summary statistic.

Example 744

Summary: Creates a variability chart with nested factors using Graph Builder, displaying standard deviation charts and utilizing operator and part configurations.

Code:

dt = Open("data_table.jmp");
obj = Graph Builder(
    Size( 451, 434 ),
    Show Control Panel( 0 ),
    Variables( X( :age ), Y( :height ), Y( :weight, Position( 1 ) ), Wrap( :age ), Overlay( :sex ) ),
    Elements( Bar( X, Y( 1 ), Y( 2 ), Legend( 5 ), Bar Style( "Range" ), Summary Statistic( "Sum" ), Label( "Label by Value" ) ) )
);

Code Explanation:

1. Open data table.
2. Create Graph Builder object.
3. Set graph size.
4. Hide control panel.
5. Define X and Y variables.
6. Add wrap variable.
7. Add overlay variable.
8. Add bar element.
9. Set bar style to range.
10. Use sum for summary statistic.

Example 745

Summary: Creates a variability chart with nested factors using operator and part configurations, displaying standard deviation charts in Graph Builder.

Code:

Open("data_table.jmp");
Graph Builder(
    Show Control Panel( 0 ),
    Variables( X( :age ), Y( :height ), Overlay( :sex ) ),
    Elements( Bar( X, Y, Legend( 7 ), Bar Style( "Range" ), Label( "Label by Value" ) ) ),
    SendToReport(
        Dispatch( {}, "Graph Builder", FrameBox,
            Add Pin Annotation(
                Seg( BarSeg( 1 ) ),
                Index( {4, 4} ),
                Index Row( {15, 15} ),
                UniqueID( 937443316 ),
                FoundPt( {510, 266} ),
                Origin( {1.96694214876033, 64.8928571428572} ),
                Offset( {-210, -89} ),
                Tag Line
            )
        )
    )
);

Code Explanation:

1. Open data table;
2. Launch Graph Builder.
3. Hide control panel.
4. Set X variable: age.
5. Set Y variable: height.
6. Set overlay variable: sex.
7. Create bar chart.
8. Use range bar style.
9. Label bars by value.
10. Add pin annotation.

Example 746

Summary: Creates a variability chart with nested factors using operator and part configurations, displaying standard deviation charts in Graph Builder.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 534, 454 ),
    Show Control Panel( 0 ),
    Variables( X( :height ), X( :weight, Position( 1 ) ), Y( :name ) ),
    Elements( Bar( X( 1 ), X( 2 ), Y, Legend( 4 ), Bar Style( "Range" ) ) ),
    SendToReport(
        Dispatch( {}, "Graph Builder", FrameBox,
            Add Pin Annotation(
                Seg( BarSeg( 1 ) ),
                Index( {8, 16} ),
                Index Row( {14, 26} ),
                UniqueID( 837673272 ),
                FoundPt( {223, 359} ),
                Origin( {78.1531531531532, 7.85714285714286} )
            )
        )
    )
);

Code Explanation:

1. Open data table.
2. Launch Graph Builder.
3. Set graph size.
4. Hide control panel.
5. Define X and Y variables.
6. Add bar element.
7. Configure bar style.
8. Send report to Graph Builder.
9. Add pin annotation.
10. Customize annotation properties.

Example 747

Summary: Creates a variability chart with nested factors using Graph Builder, displaying standard deviation charts and configuring bar style and summary statistic.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 570, 499 ),
    Show Control Panel( 0 ),
    Variables( X( :Position ), Y( :Weight ), Group Y( :Bench ), Overlay( :Neck ) ),
    Elements( Bar( X, Y, Legend( 12 ), Bar Style( "Range" ), Summary Statistic( "Sum" ) ) )
);

Code Explanation:

1. Open data table;
2. Launch Graph Builder.
3. Set window size.
4. Hide control panel.
5. Define X variable.
6. Define Y variable.
7. Define group Y variable.
8. Define overlay variable.
9. Add bar element.
10. Configure bar style and summary statistic.

Example 748

Summary: Creates a variability chart with nested factors using Graph Builder, displaying standard deviation charts and configuring bar elements for visualization.

Code:

Open("data_table.jmp");
Graph Builder(
    Show Control Panel( 0 ),
    Variables( X( :age ), Y( :height ), Y( :weight, Position( 1 ) ) ),
    Elements( Bar( X, Y( 1 ), Y( 2 ), Legend( 8 ), Bar Style( "Range" ) ) )
);

Code Explanation:

1. Open data table.
2. Launch Graph Builder.
3. Hide control panel.
4. Set X variable: age.
5. Set Y variables: height, weight.
6. Position weight on Y axis 1.
7. Add bar element.
8. Assign X to bar.
9. Assign height to bar Y1.
10. Assign weight to bar Y2.
11. Set bar legend to 8.
12. Apply range bar style.

Example 749

Summary: Creates a stacked bar chart with mean summary statistics to visualize sex distribution by age and name, utilizing Graph Builder.

Code:

dt = Open("data_table.jmp");
gb = dt << Graph Builder(
    Show Control Panel( 0 ),
    Variables( Y( :sex ), Group X( :age ), Overlay( :name ) ),
    Elements( Bar( Y, Legend( 3 ), Bar Style( "Stacked" ), Summary Statistic( "Mean" ) ) )
);
gb << Journal Window;
jrn = Current Journal();

Code Explanation:

1. Open data table;
2. Create Graph Builder object.
3. Hide control panel.
4. Set Y variable to sex.
5. Set X variable to age.
6. Overlay by name.
7. Add stacked bar element.
8. Use mean summary statistic.
9. Display graph in journal.
10. Get current journal object.

Example 750

Summary: Creates a stacked bar chart to visualize mean values by age and name, utilizing Graph Builder with nested factors.

Code:

dt = Open("data_table.jmp");
gb = dt << Graph Builder(
    Show Control Panel( 0 ),
    Variables( Y( :sex ), Group X( :age ), Overlay( :name ) ),
    Elements( Bar( Y, Legend( 3 ), Bar Style( "Stacked" ), Summary Statistic( "Mean" ) ) )
);
gb << Journal Window;
jrn = Current Journal();
jrn[FrameBox( 6 )] << Sib Append( jrn[AxisBox( 1 )] << Clone Box );

Code Explanation:

1. Open data table.
2. Create Graph Builder object.
3. Hide control panel.
4. Set Y variable to sex.
5. Set Group X variable to age.
6. Set Overlay variable to name.
7. Add stacked bar element.
8. Set summary statistic to mean.
9. Display graph in journal window.
10. Clone and append axis box to frame box.

Example 751

Summary: Creates a variability chart with nested factors using Graph Builder, configuring X and Y variables, grouping by Turning Circle, and displaying standard deviation charts.

Code:

Open("data_table.jmp");
Graph Builder(
    show control panel( 0 ),
    Variables( X( :Displacement ), Y( :Weight ), Group Y( :Turning Circle ) ),
    Elements( Bar( X, Y, Legend( 5 ), Summary Statistic( "% of Total" ), Label( "Label by Value" ) ) )
);

Code Explanation:

1. Open data table;
2. Launch Graph Builder.
3. Hide control panel.
4. Set X variable: Displacement.
5. Set Y variable: Weight.
6. Set Group Y variable: Turning Circle.
7. Add Bar element.
8. Configure Bar summary statistic to "% of Total".
9. Enable label by value.
10. Display graph.

Example 752

Summary: Creates a bar chart with nested factors using Graph Builder, displaying height as the Y-axis and age as an overlay.

Code:

dt = Open("data_table.jmp");
dt << select where( :age == 14 );
Graph Builder(
    Size( 533, 418 ),
    Show Control Panel( 0 ),
    Variables( Y( :height ), Overlay( :age ) ),
    Elements( Bar( Y, Legend( 4 ), Label( "Label by Value" ) ) )
);

Code Explanation:

1. Open data table.
2. Select rows where age is 14.
3. Create Graph Builder window.
4. Set window size to 533x418.
5. Hide control panel.
6. Assign height to Y axis.
7. Assign age to overlay variable.
8. Add bar element to graph.
9. Set legend position to 4.
10. Label bars by value.

Example 753

Summary: Creates a variability chart with nested factors using Graph Builder, displaying standard deviation charts and summarizing data by sum.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 451, 368 ),
    Show Control Panel( 0 ),
    Variables( X( :Position2 ), Y( :Speed ), Y( :Speed2, Position( 1 ) ) ),
    Elements( Bar( X, Y( 1 ), Y( 2 ), Legend( 5 ), Bar Style( "Range" ), Summary Statistic( "Sum" ), Label( "Label by Value" ) ) )
);

Code Explanation:

1. Open data table;
2. Launch Graph Builder.
3. Set window size.
4. Hide control panel.
5. Define X variable.
6. Define first Y variable.
7. Define second Y variable.
8. Add bar element.
9. Specify bar style.
10. Use sum for summary statistic.

Example 754

Summary: Creates a variability chart with nested factors using Graph Builder, displaying standard deviation charts and configuring various variables such as marital status, age, country, size, type, and sex.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 570, 1500 ),
    Show Control Panel( 0 ),
    Variables( X( :marital status ), Y( :age ), Page( :country ), Group X( :size ), Group Y( :type ), Overlay( :sex ) ),
    Elements( Bar( X, Y, Legend( 6 ) ) )
);

Code Explanation:

1. Open data table.
2. Create Graph Builder object.
3. Set window size to 570x1500.
4. Hide control panel.
5. Define X variable: marital status.
6. Define Y variable: age.
7. Define Page variable: country.
8. Define Group X variable: size.
9. Define Group Y variable: type.
10. Define Overlay variable: sex.
11. Add Bar element with legend.

Example 755

Summary: Creates a variability chart with nested factors using Graph Builder, displaying standard deviation charts and labeling bars by row.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 570, 516 ),
    Show Control Panel( 0 ),
    Variables( X( :age ), Y( :height ), Y( :weight, Position( 1 ) ) ),
    Elements( Bar( X, Y( 1 ), Y( 2 ), Legend( 8 ), Label( "Label by Row" ) ) )
);

Code Explanation:

1. Open data table;
2. Launch Graph Builder.
3. Set window size.
4. Hide control panel.
5. Define X variable.
6. Define first Y variable.
7. Define second Y variable.
8. Add bar element.
9. Assign variables to bar.
10. Label bars by row.

Example 756

Summary: Creates a variability chart with nested factors using Graph Builder, displaying standard deviation charts and enabling label by value.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 570, 516 ),
    Show Control Panel( 0 ),
    Variables( X( :age ), Y( :height ), Y( :weight, Position( 1 ) ) ),
    Elements( Bar( X, Y( 1 ), Y( 2 ), Legend( 8 ), Label( "Label by Value" ) ) )
);

Code Explanation:

1. Open data table;
2. Launch Graph Builder.
3. Set window size.
4. Hide control panel.
5. Define X variable.
6. Define first Y variable.
7. Define second Y variable.
8. Add bar element.
9. Specify X axis.
10. Specify Y1 axis.
11. Specify Y2 axis.
12. Set legend position.
13. Enable label by value.

Example 757

Summary: Creates a variability chart with nested factors using Graph Builder, displaying standard deviation charts and side-by-side interval bars.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 441, 315 ),
    Show Control Panel( 0 ),
    Variables( X( :age ), Y( :height ), Y( :height ), Overlay( :weight ) ),
    Elements( Position( 1, 1 ), Bar( X, Y, Legend( 7 ) ) ),
    Elements( Position( 1, 2 ), Bar( X, Y, Legend( 8 ), Bar Style( "Side by side intervals" ) ) )
);

Code Explanation:

1. Open data table.
2. Create Graph Builder object.
3. Set window size to 441x315.
4. Hide control panel.
5. Define variables: X=age, Y=height, Overlay=weight.
6. Add first bar element.
7. Position first bar at (1,1).
8. Add second bar element.
9. Position second bar at (1,2).
10. Set bar style to "Side by side intervals".

Example 758

Summary: Creates a variability chart with nested factors using Graph Builder, displaying standard deviation charts and side-by-side interval bars.

Code:

Open("data_table.jmp") << Graph Builder(
    Size( 400, 258 ),
    Show Control Panel( 0 ),
    Variables( X( :age ), Y( :height ), Overlay( :weight ) ),
    Elements( Bar( X, Y, Legend( 5 ), Bar Style( "Side by side intervals" ) ) )
);

Code Explanation:

1. Open data table;
2. Launch Graph Builder.
3. Set window size.
4. Hide control panel.
5. Define X variable.
6. Define Y variable.
7. Define overlay variable.
8. Add bar element.
9. Set bar style.
10. Display graph.

Example 759

Summary: Creates a variability chart with nested factors using operator and part configurations, displaying standard deviation charts in Graph Builder.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 361, 267 ),
    Show Control Panel( 0 ),
    Show Legend( 0 ),
    Variables( X( :age ), Y( :height ), Y( :weight, Position( 1 ) ) ),
    Elements( Bar( X, Y( 1 ), Y( 2 ), Legend( 4 ), Bar Style( "Side by side intervals" ) ) )
);

Code Explanation:

1. Open data table.
2. Create Graph Builder window.
3. Set window size.
4. Hide control panel.
5. Hide legend.
6. Assign X variable.
7. Assign first Y variable.
8. Assign second Y variable.
9. Add bar element.
10. Configure bar style.

Example 760

Summary: Creates a bar chart with nested factors using Graph Builder, displaying standard deviation charts for height and weight based on age.

Code:

Open("data_table.jmp");
Graph Builder(
    Show Control Panel( 0 ),
    Variables( X( :age ), Y( :height ), Y( :weight, Position( 1 ) ) ),
    Elements( Bar( X, Y( 1 ), Y( 2 ), Legend( 8 ), Bar Style( "Single" ) ) )
);

Code Explanation:

1. Open data table;
2. Launch Graph Builder.
3. Hide control panel.
4. Set X variable to age.
5. Set Y variables to height and weight.
6. Position weight on axis 1.
7. Add bar element.
8. Set X for bar.
9. Set Y1 for bar.
10. Set Y2 for bar.

Example 761

Summary: Creates a variability chart with nested factors using Graph Builder, displaying standard deviation charts and customizing Y-axis scale.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 540, 493 ),
    Show Control Panel( 0 ),
    Variables( X( :Response ), Y( :Name( "ln(dose)" ) ), Group X( :Dose ), Frequency( :Count ) ),
    Elements( Bar( X, Y, Legend( 13 ), Error Bars( "Range" ), Label( "Label by Value" ) ) ),
    SendToReport( Dispatch( {}, "ln(dose)", ScaleBox, {Min( -0.0000000025 ), Max( 0.000000022 ), Inc( 0.000002 ), Minor Ticks( 0 )} ) )
);

Code Explanation:

1. Open data table;
2. Launch Graph Builder.
3. Set window size.
4. Hide control panel.
5. Define X, Y, Group X, Frequency.
6. Add bar element.
7. Enable error bars.
8. Label bars by value.
9. Customize Y-axis scale.
10. Set axis increments and minor ticks.

Example 762

Summary: Creates a stacked bar chart with nested factors using Graph Builder, displaying Tip Amount and Bill Amount by Number of Guests.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 570, 447 ),
    Show Control Panel( 0 ),
    Variables( X( :Day of Week ), Y( :Tip Amount ), Y( :Bill Amount, Position( 1 ) ), Group Y( :Number of Guests, Levels( 2 ) ) ),
    Elements( Bar( X, Y( 1 ), Y( 2 ), Legend( 12 ), Bar Style( "Stacked" ) ) )
);

Code Explanation:

1. Open data table;
2. Create new Graph Builder window.
3. Set window size to 570x447.
4. Hide control panel.
5. Define X variable as "Day of Week".
6. Define first Y variable as "Tip Amount".
7. Define second Y variable as "Bill Amount".
8. Position second Y on left.
9. Group Y by "Number of Guests".
10. Set group levels to 2.
11. Add stacked bar element.
12. Assign X, Y1, and Y2 to bar.
13. Set legend position to 12.
14. Style bar as stacked.

Example 763

Summary: Creates a stacked bar chart with nested factors using Graph Builder, displaying standard deviation charts and reversing the weight scale.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 534, 463 ),
    Show Control Panel( 0 ),
    Variables( X( :sex ), Y( :weight ), Overlay( :age ) ),
    Elements( Bar( X, Y, Legend( 13 ), Bar Style( "Stacked" ), Label( "Label by Value" ) ) ),
    SendToReport( Dispatch( {}, "weight", ScaleBox, {Reversed Scale} ) )
);

Code Explanation:

1. Open data table.
2. Launch Graph Builder.
3. Set window size.
4. Hide control panel.
5. Define X, Y, and overlay variables.
6. Add stacked bar element.
7. Label bars by value.
8. Reverse weight scale.

Example 764

Summary: Creates two Graph Builder windows to visualize the relationship between age, height, and weight, displaying percentage of total and median summary statistics.

Code:

Open("data_table.jmp");
Graph Builder(
    Show Control Panel( 0 ),
    Variables( X( :age ), Y( :height ), Y( :weight, Position( 1 ) ) ),
    Elements( Bar( X, Y( 1 ), Y( 2 ), Legend( 8 ), Summary Statistic( "% of Total" ) ) )
);
Graph Builder(
    Show Control Panel( 0 ),
    Variables( X( :age ), Y( :height ), Y( :weight, Position( 1 ) ) ),
    Elements( Bar( X, Y( 1 ), Y( 2 ), Legend( 8 ), Summary Statistic( "Median" ) ) )
);

Code Explanation:

1. Open data table.
2. Create first Graph Builder window.
3. Hide control panel.
4. Set X variable: age.
5. Set Y variables: height, weight.
6. Add bar element.
7. Use percentage of total summary statistic.
8. Create second Graph Builder window.
9. Hide control panel.
10. Use median summary statistic.

Example 765

Summary: Creates three Graph Builders to visualize variability charts with nested factors, displaying standard deviation charts and summary statistics.

Code:

Open("data_table.jmp");
Graph Builder(
    Show Control Panel( 0 ),
    Variables( X( :age ), Y( :height ), Y( :weight, Position( 1 ) ) ),
    Elements( Bar( X, Y( 1 ), Y( 2 ), Legend( 8 ), Summary Statistic( "% of Total" ) ) )
);
Graph Builder(
    Show Control Panel( 0 ),
    Variables( X( :age ), Y( :height ), Y( :weight, Position( 1 ) ) ),
    Elements( Bar( X, Y( 1 ), Y( 2 ), Legend( 8 ), Summary Statistic( "Median" ) ) )
);
Graph Builder(
    Size( 492, 442 ),
    show control panel( 0 ),
    Variables( X( :age ), Y( :weight ), Color( :height ) ),
    Elements( Bar( X, Y, Legend( 5 ), Summary Statistic( "Range" ) ) )
);

Code Explanation:

1. Open data table.
2. Create first graph builder.
3. Hide control panel.
4. Set X variable to age.
5. Set Y variables to height and weight.
6. Add bar element with summary statistic "% of Total".
7. Create second graph builder.
8. Hide control panel.
9. Set X variable to age.
10. Set Y variables to height and weight.
11. Add bar element with summary statistic "Median".
12. Create third graph builder.
13. Set graph size.
14. Hide control panel.
15. Set X variable to age.
16. Set Y variable to weight.
17. Set color variable to height.
18. Add bar element with summary statistic "Range".

Example 766

Summary: Creates a variability chart with nested factors using Graph Builder, displaying standard deviation charts and utilizing bar style and summary statistic configurations.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 450, 320 ),
    Show Control Panel( 0 ),
    Variables( X( :sex ), Y( :height ), Overlay( :age ) ),
    Elements( Bar( X, Y, Bar Style( "Side by side" ), Summary Statistic( "Min" ) ) )
);

Code Explanation:

1. Open data table;
2. Create Graph Builder window.
3. Set window size.
4. Hide control panel.
5. Define X variable.
6. Define Y variable.
7. Define overlay variable.
8. Add bar element.
9. Set bar style.
10. Use minimum summary statistic.

Example 767

Summary: Creates a variability chart with nested factors using Graph Builder, displaying standard deviation charts and error bars.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 534, 464 ),
    Show Control Panel( 0 ),
    Variables( X( :Pattern ID ), Y( :Time ) ),
    Elements( Bar( X, Y, Legend( 10 ), Summary Statistic( "Median" ), Error Bars( "Range" ), Label( "Label by Value" ) ) )
);

Code Explanation:

1. Open data table;
2. Launch Graph Builder.
3. Set window size.
4. Hide control panel.
5. Assign X variable.
6. Assign Y variable.
7. Add bar element.
8. Set legend position.
9. Use median summary statistic.
10. Display range error bars.

Example 768

Summary: Creates two variability charts with nested factors using Graph Builder, displaying standard deviation charts and error bars.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 534, 464 ),
    Show Control Panel( 0 ),
    Variables( X( :Pattern ID ), Y( :Time ) ),
    Elements( Bar( X, Y, Legend( 10 ), Summary Statistic( "Median" ), Error Bars( "Range" ), Label( "Label by Value" ) ) )
);
Graph Builder(
    show control panel( 0 ),
    Variables( X( :Pattern ID ), Y( :Time ) ),
    Elements( Bar( X, Y, Legend( 9 ), Error Bars( "Range" ), Label( "Label by Value" ) ) )
);

Code Explanation:

1. Open data table;
2. Create first Graph Builder window.
3. Set window size.
4. Hide control panel.
5. Define X and Y variables.
6. Add bar element.
7. Set summary statistic to median.
8. Add range error bars.
9. Label by value.
10. Create second Graph Builder window.
11. Hide control panel.
12. Define X and Y variables.
13. Add bar element.
14. Add range error bars.
15. Label by value.

Example 769

Summary: Creates a treemap-based variability chart with nested factors using Graph Builder, featuring Rating as the X-axis and Domestic $ as the Y-axis, with Director used for overlay.

Code:

dt = Open("data_table.jmp");
gb = dt << Graph Builder(
    Size( 536, 452 ),
    Show Control Panel( 0 ),
    Show Legend( 0 ),
    Variables( X( :Rating ), Y( :Domestic $ ), Overlay( :Director ) ),
    Elements( Bar( X, Y, Legend( 5 ), Bar Style( "Treemap" ) ) )
);

Code Explanation:

1. Open data table;
2. Create Graph Builder object.
3. Set graph size.
4. Hide control panel.
5. Hide legend.
6. Define X variable: Rating.
7. Define Y variable: Domestic $.
8. Use Director for overlay.
9. Add bar element.
10. Set bar style to treemap.

Example 770

Summary: Creates a treemap variability chart with nested factors using Graph Builder, displaying standard deviation charts.

Code:

dt1 = Open("data_table.jmp");
gb1 = dt1 << Graph Builder(
    Size( 536, 458 ),
    Show Control Panel( 0 ),
    Show Legend( 0 ),
    Variables( X( :Year ), Y( :Cost ), Overlay( :Unique Event ) ),
    Elements( Bar( X, Y, Legend( 5 ), Bar Style( "Treemap" ) ) )
);

Code Explanation:

1. Open data table.
2. Create new graph builder object.
3. Set graph size.
4. Hide control panel.
5. Hide legend.
6. Define X, Y, and overlay variables.
7. Add bar element.
8. Set bar style to treemap.
9. Assign legend position.
10. Display graph.

Example 771

Summary: Creates three treemap graphs using Graph Builder, displaying nested factors for ratings and domestic sales by director, year and cost by unique event, and type of space and outside temperature by notes on internal conditions.

Code:

dt = Open("data_table.jmp");
gb = dt << Graph Builder(
    Size( 536, 452 ),
    Show Control Panel( 0 ),
    Show Legend( 0 ),
    Variables( X( :Rating ), Y( :Domestic $ ), Overlay( :Director ) ),
    Elements( Bar( X, Y, Legend( 5 ), Bar Style( "Treemap" ) ) )
);
dt1 = Open("data_table.jmp");
gb1 = dt1 << Graph Builder(
    Size( 536, 458 ),
    Show Control Panel( 0 ),
    Show Legend( 0 ),
    Variables( X( :Year ), Y( :Cost ), Overlay( :Unique Event ) ),
    Elements( Bar( X, Y, Legend( 5 ), Bar Style( "Treemap" ) ) )
);
dt2 = Open("data_table.jmp");
gb2 = dt2 << Graph Builder(
    Size( 512, 466 ),
    Show Control Panel( 0 ),
    Show Legend( 0 ),
    Variables( X( :type of space, Size By( "Count" ) ), Y( :outside temp ), Overlay( :notes on internal conditions ) ),
    Elements( Bar( X, Y, Legend( 6 ), Bar Style( "Treemap" ) ) )
);

Code Explanation:

1. Open data table.
2. Create treemap graph for ratings and domestic sales by director.
3. Open data table.
4. Create treemap graph for year and cost by unique event.
5. Open data table.
6. Create treemap graph for type of space and outside temperature by notes on internal conditions.

Example 772

Summary: Creates a variability chart with nested factors using Graph Builder, displaying standard deviation charts and error bars.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 468, 321 ),
    Show Control Panel( 0 ),
    Variables( Y( :height ), Overlay( :sex ) ),
    Elements( Bar( Y, Legend( 4 ), Error Bars( "Two-way Interval" ) ) )
);

Code Explanation:

1. Open data table;
2. Launch Graph Builder.
3. Set window size.
4. Hide control panel.
5. Define Y variable.
6. Define overlay variable.
7. Add bar element.
8. Set legend position.
9. Enable two-way interval error bars.

Example 773

Summary: Creates a variability chart with nested factors using operator and part configurations, displaying standard deviation charts in Graph Builder.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 528, 404 ),
    Show Control Panel( 0 ),
    Include Missing Categories( 1 ),
    Variables( X( :Flight ), X( :Reason, Position( 1 ) ), Y( :Delay ) ),
    Elements( Bar( X( 1 ), X( 2 ), Y, Legend( 5 ) ) ),
    SendToReport(
        Dispatch( {}, "Graph Builder", FrameBox,
            Add Pin Annotation(
                Seg( BarSeg( 1 ) ),
                Index( {11, 11} ),
                Index Row( {11, 11} ),
                UniqueID( 675795691 ),
                FoundPt( {272, 121} ),
                Origin( {12.2727272727273, 12.7251461988304} )
            )
        )
    )
);

Code Explanation:

1. Open data table;
2. Create Graph Builder window.
3. Set window size.
4. Hide control panel.
5. Include missing categories.
6. Define X and Y variables.
7. Add bar element.
8. Configure bar element properties.
9. Send report to Graph Builder.
10. Add pin annotation to graph.

Example 774

Summary: Creates a variability chart with nested factors using Graph Builder, displaying standard deviation charts and grouping data by sex.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 570, 516 ),
    Show Control Panel( 0 ),
    Variables( X( :age ), Y( :height ), Y( :weight, Position( 1 ) ), Group X( :sex ) ),
    Elements( Bar( X, Y( 1 ), Y( 2 ), Legend( 8 ) ) )
);

Code Explanation:

1. Open data table;
2. Create Graph Builder window.
3. Set size to 570x516 pixels.
4. Hide control panel.
5. Assign "age" to X-axis.
6. Assign "height" to primary Y-axis.
7. Assign "weight" to secondary Y-axis.
8. Group by "sex".
9. Add bar element.
10. Display legend at position 8.

Example 775

Summary: Creates a stacked bar chart with nested factors using Graph Builder, displaying standard deviation charts and customizing legend properties.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 832, 633 ),
    Show Control Panel( 0 ),
    Variables( X( :Vehicle Category ), X( :Number of Cylinders, Position( 1 ) ), Overlay( :Air Bags Standard ) ),
    Elements( Bar( X( 1 ), X( 2 ), Legend( 15 ), Bar Style( "Stacked" ) ) ),
    SendToReport(
        Dispatch( {}, "400", ScaleBox,
            {Legend Model( 15, Properties( 0, {Fill Pattern( "grid heavy" )} ), Properties( 2, {Fill Pattern( "left slant heavy" )} ) )}
        )
    )
);

Code Explanation:

1. Open data table.
2. Launch Graph Builder.
3. Set window size.
4. Hide control panel.
5. Define X variables.
6. Add overlay variable.
7. Create bar element.
8. Stack bars.
9. Customize legend properties.
10. Apply report settings.

Example 776

Summary: Creates a bar chart with nested factors using Graph Builder, enabling local data filtering and adding filters for height and weight.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 527, 464 ),
    Show Control Panel( 0 ),
    Variables( X( :age ) ),
    Elements( Bar( X, Legend( 3 ) ) ),
    Local Data Filter(
        Mode( Include( 0 ) ),
        Add Filter( columns( :height ) ),
        Add Filter( columns( :weight ), Where( :weight > 92 & :weight <= 130 ) )
    )
);
Graph Builder(
    Size( 527, 464 ),
    Show Control Panel( 0 ),
    Variables( X( :age ) ),
    Elements( Bar( X, Legend( 3 ) ) ),
    Local Data Filter( Add Filter( columns( :height ) ), Add Filter( columns( :weight ), Where( :weight > 92 & :weight <= 130 ) ) )
);

Code Explanation:

1. Open data table;
2. Create first Graph Builder window.
3. Set window size.
4. Hide control panel.
5. Set X variable to age.
6. Add bar element.
7. Enable local data filter.
8. Set filter mode.
9. Add height filter.
10. Add weight filter with conditions.

Example 777

Summary: Creates two Graph Builder windows with nested factors, displaying standard deviation charts and filtering data by height and weight.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 527, 464 ),
    Show Control Panel( 0 ),
    Variables( X( :age ) ),
    Elements( Bar( X, Legend( 3 ), Summary Statistic( "Sum" ), Label( "Label by Value" ) ) ),
    Local Data Filter( Add Filter( columns( :height ) ), Add Filter( columns( :weight ), Where( :weight > 92 & :weight <= 130 ) ) )
);
Graph Builder(
    Size( 527, 464 ),
    Show Control Panel( 0 ),
    Variables( X( :age ) ),
    Elements( Bar( X, Legend( 3 ), Summary Statistic( "Sum" ), Label( "Label by Value" ) ) ),
    Local Data Filter(
        Mode( Include( 0 ) ),
        Add Filter( columns( :height ) ),
        Add Filter( columns( :weight ), Where( :weight > 92 & :weight <= 130 ) )
    )
);

Code Explanation:

1. Open data table;
2. Create first Graph Builder window.
3. Set size to 527x464.
4. Hide control panel.
5. Set X variable to age.
6. Add bar element with sum summary statistic.
7. Label bars by value.
8. Add local data filter for height.
9. Add filter for weight > 92 & ≤ 130.
10. Create second identical Graph Builder window.

Example 778

Summary: Creates a variability chart with nested factors using operator and part configurations, displaying standard deviation charts in Graph Builder.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 932, 488 ),
    Show Control Panel( 0 ),
    Variables( X( :Name( "Subject Reference Start Date/Time" ) ) ),
    Elements( Bar( X, Legend( 14 ), Summary Statistic( "N" ), Label( "Label by Percent of Total Values" ) ) )
);

Code Explanation:

1. Open data table;
2. Launch Graph Builder.
3. Set window size.
4. Hide control panel.
5. Define X variable.
6. Add bar element.
7. Assign legend.
8. Use summary statistic N.
9. Label by percent of total values.
10. Display graph.

Example 779

Summary: Creates a variability chart with nested factors using operator and part configurations, displaying standard deviation charts.

Code:

Open("data_table.jmp");
Graph Builder( Size( 534, 454 ), Show Control Panel( 0 ), Variables( X( :Table ) ), Elements( Bar( X, Legend( 9 ) ) ) );

Code Explanation:

1. Open data table;
2. Launch Graph Builder.
3. Set window size.
4. Hide control panel.
5. Assign X variable.
6. Add bar element.
7. Set legend position.

Example 780

Summary: Creates a bar chart with nested factors using Graph Builder, enabling local data filtering and displaying standard deviation charts.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 892, 392 ),
    Show Control Panel( 0 ),
    Variables( X( :age ), Y( :height ), Y( :weight, Position( 1 ) ) ),
    Elements( Bar( X, Y( 1 ), Y( 2 ), Legend( 8 ), Label( "Label by Row" ) ) ),
    Local Data Filter(
        Width( 160 ),
        Grouped by AND( 1 ),
        Add Filter( columns( :age ), Where( :age == {12, 15, 16, 17} ), Display( :age, N Items( 4 ) ) ),
        Add Filter( columns( :height ), Where( :height >= 51 & :height <= 62.7 ) )
    )
);

Code Explanation:

1. Open data table.
2. Create Graph Builder window.
3. Set graph size.
4. Hide control panel.
5. Assign X and Y variables.
6. Add bar element.
7. Configure label by row.
8. Enable local data filter.
9. Set filter width.
10. Define filter conditions.

Example 781

Summary: Creates a variability chart with nested factors using Graph Builder, displaying standard deviation charts and error bars.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 374, 252 ),
    Show Control Panel( 0 ),
    Variables( X( :sex ), Y( :height ), Y( :height ) ),
    Elements( Position( 1, 1 ), Bar( X, Y, Legend( 15 ), Error Bars( "Range" ) ) ),
    Elements( Position( 1, 2 ), Bar( X, Y, Legend( 13 ) ) )
);

Code Explanation:

1. Open data table.
2. Launch Graph Builder.
3. Set window size.
4. Hide control panel.
5. Define X variable.
6. Define Y variables.
7. Add first bar element.
8. Add error bars.
9. Add second bar element.
10. Display graph.

Example 782

Summary: Creates a variability chart with nested factors using Graph Builder, featuring categorical color theme and standard deviation charts.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 925, 262 ),
    Show Control Panel( 0 ),
    Show Legend( 0 ),
    Categorical Color Theme( "Teal to Brown" ),
    Include Missing Categories( 1 ),
    Variables( X( :Sepal length ), Y( :Sepal width ), Y( :Petal length, Position( 1 ) ), Color( :Species ) ),
    Elements( Bar( X, Y( 1 ), Y( 2 ), Legend( 9 ) ) ),
    SendToReport( Dispatch( {}, "400", LegendBox, {Set Title( "" )} ) )
);

Code Explanation:

1. Open data table;
2. Create Graph Builder window.
3. Set window size.
4. Hide control panel.
5. Hide legend.
6. Apply color theme.
7. Include missing categories.
8. Define variables: X, Y1, Y2, Color.
9. Add bar element.
10. Remove legend title.

Example 783

Summary: Creates a variability chart with nested factors using operator and part configurations, displaying standard deviation charts.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 415, 280 ),
    Show Control Panel( 0 ),
    Error Bar Offset( 0.1 ),
    Variables( X( :Clarity ), Y( :Depth ), Y( :Table, Position( 1 ) ) ),
    Elements( Points( X, Y( 1 ), Y( 2 ), Legend( 8 ), Summary Statistic( "Mean" ), Error Interval( "Range" ) ) ),
    SendToReport( Dispatch( {}, "Clarity", ScaleBox, {Reversed Scale} ) )
);

Code Explanation:

1. Open data table;
2. Launch Graph Builder.
3. Set size to 415x280.
4. Hide control panel.
5. Set error bar offset to 0.1.
6. Assign Clarity to X.
7. Assign Depth to Y1.
8. Assign Table to Y2.
9. Add points element with mean summary.
10. Reverse Clarity scale.

Example 784

Summary: Creates a variability chart with nested factors using Graph Builder, displaying standard deviation charts and summarizing minimum values.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 498, 426 ),
    Show Control Panel( 0 ),
    Variables( X( :sex ), Y( :height ), Y( :weight, Position( 1 ) ), Interval( :age ) ),
    Elements( Bar( X, Y( 1 ), Y( 2 ), Legend( 5 ), Summary Statistic( "Min" ), Label( "Label by Value" ) ) )
);

Code Explanation:

1. Open data table;
2. Create Graph Builder window.
3. Set window size.
4. Hide control panel.
5. Define X variable: sex.
6. Define Y variables: height, weight.
7. Set weight position to 1.
8. Add age interval.
9. Add bar element.
10. Set summary statistic to Min.

Example 785

Summary: Creates a variability chart with nested factors using operator and part configurations, displaying standard deviation charts in Graph Builder.

Code:

dt = Open("data_table.jmp");
Graph Builder(
    Size( 534, 454 ),
    Show Control Panel( 0 ),
    Variables( X( :Degrees ), Y( :Censor ), Y( :Strength ), Overlay( :Weeks ) ),
    Elements( Position( 1, 1 ), Contour( X, Y, Legend( 10 ) ) ),
    Elements( Position( 1, 2 ), Bar( X, Y, Legend( 6 ), Bar Style( "Nested" ), Summary Statistic( "Sum" ) ) ),
    SendToReport(
        Dispatch( {}, "400", ScaleBox,
            {Legend Model( 6, Base( 0, 0, 0 ), Base( 1, 0, 0 ), Base( 2, 0, 0 ), Base( 3, 0, 0 ), Base( 4, 0, 0 ), Base( 5, 0, 0 ) )}
        ),
        Dispatch( {}, "400", LegendBox, {Legend Position( {10, [6, 7, 8, 9, 10, 11], 6, [0, 1, 2, 3, 4, 5]} )} )
    )
);

Code Explanation:

1. Open data table.
2. Create Graph Builder.
3. Set graph size.
4. Hide control panel.
5. Define X and Y variables.
6. Add contour element.
7. Add bar element.
8. Customize legend for bars.
9. Adjust legend positions.
10. Finalize report settings.

Example 786

Summary: Creates a variability chart with nested factors using Graph Builder, displaying standard deviation charts and arranging data by age while overlaying by sex.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 447, 501 ),
    Show Control Panel( 0 ),
    Variables( X( :age ), Y( :height ), Y( :weight, Position( 1 ) ), Wrap( :age ), Overlay( :sex ) ),
    Elements( Bar( X, Y( 1 ), Y( 2 ), Legend( 5 ), Bar Style( "Range" ) ) )
);

Code Explanation:

1. Open data table;
2. Launch Graph Builder.
3. Set window size.
4. Hide control panel.
5. Assign variables: X, Y, Y2, Wrap, Overlay.
6. Create bar elements.
7. Specify bar style as range.
8. Display legend for bars.
9. Arrange by age.
10. Overlay by sex.

Example 787

Summary: Creates a variability chart with nested factors using Graph Builder, displaying standard deviation charts and configuring bar style to range.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 533, 405 ),
    Show Control Panel( 0 ),
    Show Legend( 0 ),
    Variables( X( :sex ), Y( :height ), Y( :weight, Position( 1 ) ), Wrap( :age ), Overlay( :age ) ),
    Elements( Bar( X, Y( 1 ), Y( 2 ), Legend( 6 ), Bar Style( "Range" ) ) )
);

Code Explanation:

1. Open data table;
2. Launch Graph Builder.
3. Set window size.
4. Hide control panel.
5. Hide legend.
6. Define variables: X=sex, Y=height, Y=weight.
7. Wrap by age.
8. Overlay by age.
9. Add bar element.
10. Set bar style to range.

Example 788

Summary: Creates a variability chart with nested factors using Graph Builder, displaying standard deviation charts and configuring bar labels.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 454, 288 ),
    Show Control Panel( 0 ),
    Variables( X( :age ), Y( :height ), Overlay( :sex ) ),
    Elements( Bar( X, Y, Legend( 7 ), Label( "Label by Value" ) ) ),
    SendToReport( Dispatch( {}, "age", ScaleBox, {Min( 1 )} ) )
);

Code Explanation:

1. Open data table;
2. Create Graph Builder window.
3. Set window size.
4. Hide control panel.
5. Define X, Y, and overlay variables.
6. Add bar element to graph.
7. Configure bar labels.
8. Dispatch command to report.
9. Set minimum value for X-axis.
10. Display graph.

Example 789

Summary: Creates a variability chart with nested factors using Graph Builder, displaying standard deviation charts and configuring various elements such as bar style and legend.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 560, 500 ),
    Show Control Panel( 0 ),
    Variables( X( :Weight ), Group X( :Weight ), Group Y( :Turning Circle ), Overlay( :Country ), Frequency( :Gas Tank Size ) ),
    Elements( Bar( X, Legend( 7 ), Bar Style( "Interval" ) ) )
);

Code Explanation:

1. Open data table;
2. Launch Graph Builder.
3. Set window size.
4. Hide control panel.
5. Define X variable.
6. Define Group X variable.
7. Define Group Y variable.
8. Define Overlay variable.
9. Define Frequency variable.
10. Add bar element with interval style.

Example 790

Summary: Creates a variability chart with nested factors using operator and part configurations, displaying standard deviation charts in JMP.

Code:

dt = Open("data_table.jmp");
myExcludedRows = dt << get rows where( :Smoking History == "pipes" | :Smoking
History == "cigarettes" );
dt << select rows( myExcludedRows );
dt << exclude;
Graph Builder(
    Show Control Panel( 0 ),
    Variables( X( :Heart History ), Overlay( :Smoking History ) ),
    Elements( Bar( X, Legend( 8 ), Bar Style( "Range" ), Summary Statistic( "Sum" ), Label( "Label by Value" ) ) )
);

Code Explanation:

1. Open data table.
2. Define excluded rows.
3. Select excluded rows.
4. Exclude selected rows.
5. Create Graph Builder.
6. Hide control panel.
7. Set X variable.
8. Set overlay variable.
9. Add bar element.
10. Configure bar style and summary.

Example 791

Summary: Creates a bar chart to visualize weight distribution by age, utilizing Graph Builder and excluding selected rows.

Code:

dt = Open("data_table.jmp");
rs = dt << select where( :age == 12 );
rs << exclude;
Graph Builder(
    Size( 400, 300 ),
    Show Control Panel( 0 ),
    Variables( X( :age ), Y( :weight ) ),
    Elements( Bar( X, Y, Summary statistic( "% of Total" ), Label( "Label by Value" ) ) )
);

Code Explanation:

1. Open data table.
2. Select rows where age is 12.
3. Exclude selected rows.
4. Create Graph Builder.
5. Set graph size to 400x300.
6. Hide control panel.
7. Set X variable to age.
8. Set Y variable to weight.
9. Add bar element.
10. Use percent of total summary.

Example 792

Summary: Creates a stacked bar chart with nested factors using Graph Builder, displaying standard deviation charts and configuring log scale for Y-axis.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 606, 536 ),
    Show Control Panel( 0 ),
    Variables( X( :Causes ), Y( :Time Cycles ), Overlay( :Group ) ),
    Elements( Bar( X, Y, Legend( 2 ), Bar Style( "Stacked" ) ) ),
    SendToReport(
        Dispatch( {}, "Time Cycles", ScaleBox,
            {Scale( "Log" ), Format( "Best", 10 ), Min( 1 ), Max( 8316.75096774193 ), Inc( 1 ), Minor Ticks( 1 )}
        )
    )
);

Code Explanation:

1. Open data table;
2. Create Graph Builder window.
3. Set window size.
4. Hide control panel.
5. Define variables: X, Y, Overlay.
6. Add bar element.
7. Set legend for bars.
8. Apply stacked bar style.
9. Configure log scale for Y-axis.
10. Adjust scale properties.

Example 793

Summary: Creates a bar chart with nested factors using Graph Builder, displaying standard deviation charts and enabling label by value.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 595, 454 ),
    Show Control Panel( 0 ),
    Variables( X( :weight ), Y( :height ) ),
    Elements( Bar( X, Legend( 5 ), Label( "Label by Value" ) ) )
);

Code Explanation:

1. Open data table.
2. Create Graph Builder window.
3. Set window size.
4. Hide control panel.
5. Define X variable.
6. Define Y variable.
7. Add bar element.
8. Assign legend position.
9. Enable label by value.
10. Display graph.

Example 794

Summary: Creates two Graph Builder windows with bar elements to visualize the relationship between weight and height, hiding control panels and labeling bars by value.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 595, 454 ),
    Show Control Panel( 0 ),
    Variables( X( :weight ), Y( :height ) ),
    Elements( Bar( X, Legend( 5 ), Label( "Label by Value" ) ) )
);
Graph Builder(
    Size( 534, 454 ),
    Show Control Panel( 0 ),
    Variables( X( :weight ), Y( :height ) ),
    Elements( Bar( Y, Legend( 5 ), Label( "Label by Value" ) ) )
);

Code Explanation:

1. Open data_table data
2. Create first Graph Builder window.
3. Set window size 595x454.
4. Hide control panel.
5. Set X variable to weight.
6. Set Y variable to height.
7. Add bar element with X axis.
8. Label bars by value.
9. Create second Graph Builder window.
10. Set window size 534x454.
11. Hide control panel.
12. Set X variable to weight.
13. Set Y variable to height.
14. Add bar element with Y axis.
15. Label bars by value.

Example 795

Summary: Creates a bar graph with nested factors using Graph Builder, configuring local data filters for sex and weight range.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 484, 341 ),
    Show Control Panel( 0 ),
    Variables( X( :age ), Y( :height ), Color( :weight ) ),
    Elements( Bar( X, Y, Legend( 5 ) ) ),
    Local Data Filter(
        Mode( Include( 0 ) ),
        Add Filter( columns( :sex ), Where( :sex == "F" ) ),
        Add Filter( columns( :weight ), Where( :weight >= 111.3 & :weight <= 172 ) )
    )
);
Graph Builder(
    Size( 484, 341 ),
    Show Control Panel( 0 ),
    Variables( X( :age ), Y( :height ), Color( :weight ) ),
    Elements( Bar( X, Y, Legend( 5 ) ) ),
    Local Data Filter(
        Mode( Include( 1 ) ),
        Add Filter( columns( :sex ), Where( :sex == "F" ) ),
        Add Filter( columns( :weight ), Where( :weight >= 111.3 & :weight <= 172 ) )
    )
);
Graph Builder(
    Size( 484, 341 ),
    Show Control Panel( 0 ),
    Variables( X( :age ), Y( :height ), Color( :weight ) ),
    Elements( Bar( X, Y, Legend( 5 ) ) ),
    Local Data Filter(
        Inverse( 1 ),
        Mode( Include( 0 ) ),
        Add Filter( columns( :sex ), Where( :sex == "F" ) ),
        Add Filter( columns( :weight ), Where( :weight >= 111.3 & :weight <= 172 ) )
    )
);
Graph Builder(
    Size( 484, 341 ),
    Show Control Panel( 0 ),
    Variables( X( :age ), Y( :height ), Color( :weight ) ),
    Elements( Bar( X, Y, Legend( 5 ) ) ),
    Local Data Filter(
        Inverse( 1 ),
        Mode( Include( 1 ) ),
        Add Filter( columns( :sex ), Where( :sex == "F" ) ),
        Add Filter( columns( :weight ), Where( :weight >= 111.3 & :weight <= 172 ) )
    )
);

Code Explanation:

1. Open data_table data
2. Create bar graph.
3. Set size 484x341.
4. Hide control panel.
5. Set X: age, Y: height, Color: weight.
6. Add bar element with legend.
7. Add local data filter for sex "F".
8. Add local data filter for weight range.
9. Repeat steps 2-8.
10. Invert filter mode.

Example 796

Summary: Creates a bar chart with error bars to visualize the relationship between age and height, utilizing Graph Builder.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 604, 404 ),
    Show Control Panel( 0 ),
    Variables( X( :age ), Y( :height ), Color( :height ) ),
    Elements( Bar( X, Y, Legend( 11 ), Error Bars( "Range" ) ) )
);

Code Explanation:

1. Open data table;
2. Launch Graph Builder.
3. Set window size.
4. Hide control panel.
5. Assign variables.
6. Add bar element.
7. Set X axis variable.
8. Set Y axis variable.
9. Apply color by height.
10. Add error bars.

Example 797

Summary: Creates a variability chart with nested factors using Graph Builder, displaying standard deviation charts and error bars for range.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 577, 453 ),
    Show Control Panel( 0 ),
    Variables( X( :height ), Y( :weight ), Color( :weight ), Size( :weight ) ),
    Elements( Points( X, Y, Legend( 3 ), Summary Statistic( "Mean" ), Error Bars( "Range" ) ) )
);

Code Explanation:

1. Open data table.
2. Create Graph Builder object.
3. Set window size.
4. Hide control panel.
5. Define X variable.
6. Define Y variable.
7. Define color variable.
8. Define size variable.
9. Add points element.
10. Set summary statistic to mean.
11. Add error bars for range.

Example 798

Summary: Creates two variability charts with nested factors using Graph Builder, displaying standard deviation charts and configuring various settings for each graph.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 796, 424 ),
    Show Control Panel( 0 ),
    Show Legend( 0 ),
    Legend Position( "Bottom" ),
    Variables( X( :age ), Y( :height ), Group X( :sex ), Overlay( :sex ), Color( :weight ) ),
    Elements( Bar( X, Y, Legend( 63 ), Summary Statistic( "Min" ), Label( "Label by Value" ) ) )
);
Graph Builder(
    Size( 555, 417 ),
    Show Control Panel( 0 ),
    Variables( X( :age ), Y( :height ), Group Y( :weight ), Overlay( :age ), Color( :sex ) ),
    Elements( Bar( X, Y, Legend( 3 ), Summary Statistic( "Sum" ), Label( "Label by Value" ) ) )
);

Code Explanation:

1. Open data table.
2. Create first graph builder.
3. Set graph size.
4. Hide control panel.
5. Hide legend.
6. Set legend position.
7. Define variables: X, Y, Group X, Overlay, Color.
8. Add bar element.
9. Set summary statistic to minimum.
10. Label bars by value.
11. Create second graph builder.
12. Set graph size.
13. Hide control panel.
14. Define variables: X, Y, Group Y, Overlay, Color.
15. Add bar element.
16. Set summary statistic to sum.
17. Label bars by value.

Example 799

Summary: Creates a variability chart with nested factors using operator and part configurations, displaying standard deviation charts in Graph Builder.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 600, 544 ),
    Show Control Panel( 0 ),
    Include Missing Categories( 1 ),
    Variables( X( :Position ), Y( :Weight ), Group Y( :Bench ), Overlay( :Fat ) ),
    Elements( Bar( X, Y, Legend( 29 ), Bar Style( "Range" ) ) )
);

Code Explanation:

1. Open data table;
2. Launch Graph Builder.
3. Set window size.
4. Hide control panel.
5. Include missing categories.
6. Define X, Y, Group Y, Overlay variables.
7. Add bar element.
8. Set bar style to range.
9. Assign legend position.
10. Display graph.

Example 800

Summary: Creates a bar chart with nested factors using Graph Builder, configuring the height axis scale to log and setting format and limits.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 366, 269 ),
    Show Control Panel( 0 ),
    Variables( X( :height ), Y( :weight ), Overlay( :sex ) ),
    Elements( Bar( X, Y, Legend( 6 ) ) ),
    SendToReport(
        Dispatch( {}, "height", ScaleBox,
            {Scale( "Log" ), Format( "Best", 12 ), Min( 50 ), Max( 70.3578947368421 ), Inc( 1 ), Minor Ticks( 1 )}
        )
    )
);

Code Explanation:

1. Open data table;
2. Create new Graph Builder window.
3. Set window size.
4. Hide control panel.
5. Assign variables: X=height, Y=weight, Overlay=sex.
6. Add bar element to graph.
7. Send report to Graph Builder.
8. Configure height axis scale to log.
9. Set height axis format and limits.
10. Configure height axis increments and minor ticks.

Example 801

Summary: Creates a variability chart with nested factors using Graph Builder, displaying standard deviation charts and configuring Y-axis scale to log.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 560, 400 ),
    Show Control Panel( 0 ),
    Variables( X( :Weather Condition ), Y( :Total Fatal Injuries ), Overlay( :Number of Engines ) ),
    Elements( Bar( X, Y, Legend( 71 ), Label( "Label by Value" ) ) ),
    SendToReport(
        Dispatch( {}, "Total Fatal Injuries", ScaleBox,
            {Scale( "Log" ), Format( "Best", 10 ), Min( 0.0165323343009725 ), Max( 148.791008708753 ), Inc( 1 ), Minor Ticks( 1 )}
        )
    )
);

Code Explanation:

1. Open data table.
2. Create Graph Builder window.
3. Set graph size.
4. Hide control panel.
5. Define X, Y, and overlay variables.
6. Add bar element.
7. Label bars by value.
8. Send report dispatch.
9. Set Y-axis scale to log.
10. Format Y-axis display.

Example 802

Summary: Creates a variability chart with nested factors using Graph Builder, displaying standard deviation charts and labeling bars by percent of total values.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 957, 470 ),
    Show Control Panel( 0 ),
    Variables( X( :Type ), Y( :Worldwide $ ), Overlay( :Rating ) ),
    Elements( Bar( X, Y, Legend( 7 ), Summary Statistic( "N" ), Label( "Label by Percent of Total Values" ) ) )
);

Code Explanation:

1. Open data table;
2. Launch Graph Builder.
3. Set window size.
4. Hide control panel.
5. Define X variable: Type.
6. Define Y variable: Worldwide $.
7. Define overlay variable: Rating.
8. Add bar element.
9. Use summary statistic: N.
10. Label bars by percent of total values.

Example 803

Summary: Creates a variability chart with nested factors using Graph Builder, displaying standard deviation charts and labeling bars by row.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 570, 516 ),
    Show Control Panel( 0 ),
    Variables( X( :subject ), Y( :miles ), Overlay( :species ) ),
    Elements( Bar( X, Y, Legend( 17 ), Bar Style( "Range" ), Summary Statistic( "Sum" ), Label( "Label by Row" ) ) )
);

Code Explanation:

1. Open data table;
2. Launch Graph Builder.
3. Set window size.
4. Hide control panel.
5. Assign variables: X=subject, Y=miles, Overlay=species.
6. Add Bar element.
7. Set bar style to Range.
8. Use Sum for summary statistic.
9. Label bars by row.
10. Display graph.

Example 804

Summary: Creates a variability chart with nested factors using Graph Builder, displaying standard deviation charts and configuring bar style to range.

Code:

Open("data_table.jmp");
Graph Builder(
    Show Control Panel( 0 ),
    Variables( X( :Year ), Y( :Market Share ), Overlay( :Operating System ) ),
    Elements( Bar( X, Y, Legend( 8 ), Bar Style( "Range" ) ) )
);

Code Explanation:

1. Open data table;
2. Launch Graph Builder.
3. Hide control panel.
4. Set X variable to Year.
5. Set Y variable to Market Share.
6. Set overlay variable to Operating System.
7. Add bar element.
8. Configure bar style to range.
9. Assign legend to position 8.
10. Display graph.

Example 805

Summary: Creates two variability charts with nested factors using Graph Builder, displaying standard deviation charts and allowing for customization through bar style options.

Code:

Open("data_table.jmp");
Graph Builder(
    Show Control Panel( 0 ),
    Variables( X( :Year ), Y( :Market Share ), Overlay( :Operating System ) ),
    Elements( Bar( X, Y, Legend( 8 ), Bar Style( "Range" ) ) )
);
Graph Builder(
    Show Control Panel( 0 ),
    Variables( X( :Year ), Y( :Market Share ), Overlay( :Operating System ) ),
    Elements( Bar( X, Y, Legend( 8 ), Bar Style( "Bullet" ) ) )
);

Code Explanation:

1. Open data table;
2. Create graph builder window.
3. Hide control panel.
4. Set X variable: Year.
5. Set Y variable: Market Share.
6. Set overlay variable: Operating System.
7. Add bar element.
8. Set bar style to range.
9. Create second graph builder window.
10. Repeat steps 3-9, set bar style to bullet.

Example 806

Summary: Creates a variability chart with nested factors using operator and part configurations, displaying standard deviation charts.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 528, 450 ),
    Show Control Panel( 0 ),
    Variables( X( :Position ), Y( :Speed ), Overlay( :Weight ), Color( :Fat ) ),
    Elements( Bar( X, Y, Legend( 7 ), Bar Style( "Interval" ) ) ),
    Local Data Filter(
        Inverse( 1 ),
        Add Filter(
            columns( :Weight, :Position ),
            Where( :Weight >= 157 & :Weight <= 298 ),
            Where( :Position == {"fb", "ib"} ),
            Display( :Position, Size( 178, 187 ), Height( 187 ) )
        )
    )
);

Code Explanation:

1. Open data table;
2. Create Graph Builder window.
3. Set window size to 528x450.
4. Hide control panel.
5. Define X, Y, Overlay, and Color variables.
6. Add Bar element with Interval style.
7. Enable local data filtering.
8. Invert filter logic.
9. Filter Weight between 157 and 298.
10. Filter Position for "fb" and "ib".

Example 807

Summary: Creates a variability chart with nested factors using Graph Builder, displaying standard deviation charts and utilizing variables Mfr, Sugars, Fiber Gr, and Tot Carbo.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 501, 348 ),
    Show Control Panel( 0 ),
    Variables( X( :Mfr ), Y( :Sugars ), Overlay( :Fiber Gr ), Color( :Tot Carbo ) ),
    Elements( Bar( X, Y, Legend( 6 ), Summary Statistic( "Variance" ) ) )
);

Code Explanation:

1. Open data table;
2. Create Graph Builder window.
3. Set graph size to 501x348.
4. Hide control panel.
5. Assign variables: X axis (Mfr), Y axis (Sugars).
6. Add overlay variable (Fiber Gr).
7. Add color variable (Tot Carbo).
8. Add bar element.
9. Set summary statistic to variance.
10. Display legend for bars.

Example 808

Summary: Creates a variability chart with nested factors using Graph Builder, displaying standard deviation charts and color-coded by height.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 533, 446 ),
    Show Control Panel( 0 ),
    Variables( X( :age ), Y( :height ), Overlay( :sex ), Color( :height ) ),
    Elements( Bar( X, Y, Legend( 5 ) ) )
);

Code Explanation:

1. Open data table;
2. Launch Graph Builder.
3. Set window size.
4. Hide control panel.
5. Assign variables.
6. Add X axis: age.
7. Add Y axis: height.
8. Overlay by sex.
9. Color by height.
10. Add bar element.

Example 809

Summary: Creates a variability chart with nested factors using Graph Builder, displaying standard deviation charts and configuring bar style to range.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 0, 0 ),
    Show Control Panel( 0 ),
    Variables( X( :sex ), Y( :height ), Overlay( :age ) ),
    Elements( Bar( X, Y, Legend( 6 ), Bar Style( "Range" ), Summary Statistic( "Min" ), Label( "Label by Percent of Total Values" ) ) )
);

Code Explanation:

1. Open data table;
2. Create Graph Builder object.
3. Set graph size to auto.
4. Hide control panel.
5. Define X variable as sex.
6. Define Y variable as height.
7. Define overlay variable as age.
8. Add bar element.
9. Set bar style to range.
10. Use minimum summary statistic.

Example 810

Summary: Creates a variability chart with nested factors using Graph Builder, displaying standard deviation charts and error bars for enhanced analysis.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 533, 484 ),
    Show Control Panel( 0 ),
    Variables(
        X( :age ),
        Y( Transform Column( "Center[height]", Format( "Fixed Dec", 5, 0 ), Formula( :height - Col Mean( :height ) ) ) ),
        Wrap( :age ),
        Overlay( :sex )
    ),
    Elements( Points( X, Y, Legend( 11 ), Summary Statistic( "Mean" ), Error Bars( "Confidence Interval" ) ) )
);

Code Explanation:

1. Open data table;
2. Create Graph Builder window.
3. Set window size.
4. Hide control panel.
5. Define X variable: age.
6. Define Y variable: transformed height.
7. Apply transformation: center height.
8. Set wrap variable: age.
9. Set overlay variable: sex.
10. Add points element with mean summary statistic and confidence interval error bars.

Example 811

Summary: Creates a bar chart with side-by-side bars to display mean values by sex, using Graph Builder.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 450, 320 ),
    Show Control Panel( 0 ),
    Variables( X( :sex ) ),
    Elements( Bar( X, Legend( 16 ), Bar Style( "Side by side" ), Summary Statistic( "Mean" ) ) )
);

Code Explanation:

1. Open data table;
2. Create new Graph Builder window.
3. Set graph size to 450x320.
4. Hide control panel.
5. Set X-axis variable to "sex".
6. Add bar element to graph.
7. Assign legend to bar element.
8. Set bar style to "Side by side".
9. Use mean as summary statistic.
10. Display graph.

Example 812

Summary: Creates a variability chart with nested factors using operator and part configurations, displaying standard deviation charts.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 541, 334 ),
    Show Control Panel( 0 ),
    Variables( Y( :Count ), Frequency( :Count ) ),
    Elements( Bar( Legend( 1 ), Summary Statistic( "N" ), Label( "Label by Value" ) ) )
);

Code Explanation:

1. Open data table;
2. Launch Graph Builder.
3. Set window size.
4. Hide control panel.
5. Define Y variable.
6. Set frequency variable.
7. Add bar element.
8. Use summary statistic N.
9. Label by value.
10. Display graph.

Example 813

Summary: Creates a variability chart with nested factors using Graph Builder, displaying standard deviation charts and utilizing bar style and labeling options.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 1063, 574 ),
    Show Control Panel( 0 ),
    Variables( Y( :Weight ), Group X( :Fat ), Group Y( :Bench ), Overlay( :Fat ) ),
    Elements( Bar( Y, Legend( 74 ), Bar Style( "Nested" ), Label( "Label by Row" ) ) )
);

Code Explanation:

1. Open data table;
2. Launch Graph Builder.
3. Set size to 1063x574.
4. Hide control panel.
5. Assign Weight to Y-axis.
6. Assign Fat to Group X-axis.
7. Assign Bench to Group Y-axis.
8. Overlay by Fat.
9. Add bar element.
10. Use nested bar style.
11. Label bars by row.

Example 814

Summary: Creates a bar chart to visualize height data by age, utilizing Graph Builder and hiding/excluding selected rows.

Code:

dt = Open("data_table.jmp");
rs = dt << select where( :age == 12 );
rs << hide and exclude;
Graph Builder(
    Size( 568, 517 ),
    Show Control Panel( 0 ),
    Variables( Y( :height ), Overlay( :age ) ),
    Elements( Bar( Y, Legend( 7 ), Summary Statistic( "Sum" ), Label( "Label by Percent of Total Values" ) ) )
);

Code Explanation:

1. Open data table.
2. Select rows where age is 12.
3. Hide and exclude selected rows.
4. Create Graph Builder window.
5. Set window size to 568x517.
6. Hide control panel.
7. Assign height to Y-axis.
8. Assign age to overlay.
9. Add bar element.
10. Summarize data by sum.

Example 815

Summary: Creates a variability chart with nested factors using Graph Builder, displaying standard deviation charts and error bars.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 421, 268 ),
    Show Control Panel( 0 ),
    Variables( Y( :height ), Overlay( :sex ) ),
    Elements( Points( Y, Legend( 2 ), Summary Statistic( "Mean" ), Error Bars( "Range" ) ) )
);

Code Explanation:

1. Open data table;
2. Create Graph Builder window.
3. Set graph size.
4. Hide control panel.
5. Define Y variable: height.
6. Define overlay variable: sex.
7. Add points element.
8. Set legend for points.
9. Use mean summary statistic.
10. Add range error bars.

Example 816

Summary: Creates a variability chart with nested factors using Graph Builder, displaying standard deviation charts and error bars.

Code:

Open("data_table.jmp");
Graph Builder(
    show control panel( 0 ),
    Variables( X( :sex ), Y( :height ) ),
    Elements( Bar( X, Y, Legend( 11 ), Error Bars( "Range" ) ) )
);

Code Explanation:

1. Open data table.
2. Launch Graph Builder.
3. Hide control panel.
4. Set X variable to sex.
5. Set Y variable to height.
6. Add bar element.
7. Link bar to legend.
8. Add error bars.
9. Set error bars to range.
10. Display graph.

Example 817

Summary: Creates a bar chart with maximum values, filtered by age 13, using Graph Builder and displaying height as the y-axis variable.

Code:

dt = Open("data_table.jmp");
dt << run script( "Set Age Value Labels" );
Graph Builder(
    show control panel( 0 ),
    Variables( X( :sex ), Y( :height ) ),
    Elements( Bar( X, Y, Legend( 1 ), Summary Statistic( "Max" ), Label( "Label by Value" ) ) ),
    Where( Format( :age ) == "Thirteen" )
);

Code Explanation:

1. Open data table;
2. Run "Set Age Value Labels" script.
3. Launch Graph Builder.
4. Hide control panel.
5. Set X variable to sex.
6. Set Y variable to height.
7. Add Bar element.
8. Summarize by maximum.
9. Label bars by value.
10. Filter data where age is 13.

Example 818

Summary: Creates a variability chart with nested factors using Graph Builder, displaying standard deviation charts and configuring summary statistics.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 531, 440 ),
    Show Control Panel( 0 ),
    Variables( X( :height ), X( :weight, Position( 1 ) ), Group X( :age ), Group Y( :sex ) ),
    Elements( Bar( X( 1 ), X( 2 ), Legend( 7 ), Summary Statistic( "Sum" ), Label( "Label by Percent of Total Values" ) ) )
);

Code Explanation:

1. Open data table;
2. Launch Graph Builder.
3. Set window size.
4. Hide control panel.
5. Define X variables.
6. Define additional X variable.
7. Define group X variable.
8. Define group Y variable.
9. Add bar element.
10. Configure summary statistic.
11. Label by percent of total.

Example 819

Summary: Creates a variability chart with nested factors using Graph Builder, displaying standard deviation charts and labeling bars by percent of total values.

Code:

Open("data_table.jmp");
Graph Builder(
    show control panel( 0 ),
    Variables( X( :sex ), Y( :height ), Y( :weight, Position( 1 ) ), Group X( :age ) ),
    Elements( Bar( X, Y( 1 ), Y( 2 ), Legend( 5 ), Summary Statistic( "Sum" ), Label( "Label by Percent of Total Values" ) ) )
);

Code Explanation:

1. Open data table;
2. Launch Graph Builder.
3. Hide control panel.
4. Set X variable to sex.
5. Set Y variable to height.
6. Add weight to Y axis.
7. Group X by age.
8. Add bar element.
9. Use two Y variables.
10. Label bars by percent of total values.

Example 820

Summary: Creates a variability chart with nested factors using operator and part configurations, displaying standard deviation charts in Graph Builder.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 534, 416 ),
    Show Control Panel( 0 ),
    Include Missing Categories( 1 ),
    Variables( X( :Causes ), Y( :Time Cycles ) ),
    Elements( Bar( X, Y, Legend( 4 ), Summary Statistic( "Range" ), Label( "Label by Percent of Total Values" ) ) )
);

Code Explanation:

1. Open data table;
2. Create Graph Builder window.
3. Set window size to 534x416.
4. Hide control panel.
5. Include missing categories.
6. Set X variable to Causes.
7. Set Y variable to Time Cycles.
8. Add Bar element.
9. Configure summary statistic to Range.
10. Label bars by percent of total values.

Example 821

Summary: Creates a graph builder with nested factors, displaying standard deviation charts and labeling bars by value.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 629, 398 ),
    Show Control Panel( 0 ),
    Variables(
        X( :Storm Category ),
        Y( :Atmospheric Pressure ),
        Group Y( Transform Column( "Month Year", Ordinal, Format( "m/y", 8 ), Formula( Date DMY( 1, Month( :Date ), Year( :Date ) ) ) ) )
    ),
    Elements( Bar( X, Y, Legend( 4 ), Label( "Label by Value" ) ) )
);

Code Explanation:

1. Open data_table data
2. Create graph builder.
3. Set size 629x398.
4. Hide control panel.
5. Define X variable.
6. Define Y variable.
7. Transform date to month/year.
8. Group Y by transformed date.
9. Add bar element.
10. Label bars by value.

Example 822

Summary: Creates a variability chart with nested factors using operator and part configurations, displaying standard deviation charts in Graph Builder.

Code:

Open("data_table.jmp") << Graph Builder(
    Size( 534, 456 ),
    Show Control Panel( 0 ),
    Variables( X( :Abrasion ), Y( :Shift ), Y( :time2, Position( 1 ) ), Overlay( :Shift ) ),
    Elements( Bar( X, Y( 1 ), Y( 2 ), Legend( 13 ) ) ),
    SendToReport(
        Dispatch( {}, "Graph Builder", FrameBox,
            Add Pin Annotation(
                Seg( BarSeg( 1 ) ),
                Index( {11, 11} ),
                Index Row( {13, 13} ),
                UniqueID( 612341915 ),
                FoundPt( {473, 175} ),
                Origin( {125.881057268722, 5.01020408163265} ),
                Offset( {-168, -57} ),
                Tag Line( 1 )
            )
        )
    )
);

Code Explanation:

1. Open data table;
2. Launch Graph Builder.
3. Set window size to 534x456.
4. Hide control panel.
5. Define X as Abrasion.
6. Define Y1 as Shift.
7. Define Y2 as time2.
8. Overlay by Shift.
9. Add bar element for Y1 and Y2.
10. Add pin annotation to graph.

Example 823

Summary: Creates a variability chart with nested factors using Graph Builder, displaying standard deviation charts and formatting cumulative weight sums as fixed decimals.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 534, 456 ),
    Show Control Panel( 0 ),
    Variables(
        X( Transform Column( "Row", Formula( Row() ) ) ),
        Y( Transform Column( "Transform[weight]", Formula( If( Row() == 1, 0, Lag() ) + :weight ) ) ),
        Y(
            Transform Column(
                "Cumulative[weight]",
                Format( "Fixed Dec", Use thousands separator( 0 ), 5, 0 ),
                Formula( Col Cumulative Sum( :weight ) )
            ),
            Position( 1 )
        )
    ),
    Elements( Bar( X, Y( 1 ), Y( 2 ), Legend( 11 ) ) )
);

Code Explanation:

1. Open data table;
2. Create new Graph Builder window.
3. Set window size to 534x456.
4. Hide control panel.
5. Define X variable as row number.
6. Define Y variable as cumulative weight difference.
7. Define second Y variable as cumulative weight sum.
8. Format second Y variable as fixed decimal.
9. Add bar element with both Y variables.
10. Display graph with legend.

Example 824

Summary: Creates a variability chart with nested factors using Graph Builder, displaying standard deviation charts and summarizing data with a bar element.

Code:

Open("data_table.jmp");
obj = Graph Builder(
    Size( 458, 360 ),
    Show Control Panel( 0 ),
    Variables( X( :age ), X( :name, Position( 1 ) ), Y( :height ) ),
    Elements( Bar( X( 1 ), X( 2 ), Y, Legend( 20 ), Summary Statistic( "Sum" ) ) )
);

Code Explanation:

1. Open data table.
2. Create Graph Builder object.
3. Set window size.
4. Hide control panel.
5. Define X variables.
6. Define Y variable.
7. Add bar element.
8. Set X axis positions.
9. Configure summary statistic.
10. Display graph.

Example 825

Summary: Creates a variability chart with nested factors using Graph Builder, displaying standard deviation charts and adjusting window size.

Code:

Open("data_table.jmp");
obj = Graph Builder(
    Size( 458, 360 ),
    Show Control Panel( 0 ),
    Variables( X( :age ), X( :name, Position( 1 ) ), Y( :height ) ),
    Elements( Bar( X( 1 ), X( 2 ), Y, Legend( 20 ), Summary Statistic( "Sum" ) ) )
);
obj << set window size( 458, 300 );

Code Explanation:

1. Open data table.
2. Create Graph Builder object.
3. Set graph size.
4. Hide control panel.
5. Define X variables: age, name.
6. Define Y variable: height.
7. Add bar element.
8. Set summary statistic to sum.
9. Adjust window size.

Example 826

Summary: Creates a variability chart with nested factors using operator and part configurations, displaying standard deviation charts in Graph Builder.

Code:

dt = Open("data_table.jmp");
Graph Builder(
    Size( 436, 412 ),
    Show Control Panel( 0 ),
    Legend Position( "Bottom" ),
    Variables( X( :Date ), Y( :High ), Y( :Low, Position( 1 ) ), Y( :Close, Position( 1 ) ), Y( :Volume, Position( 1 ), Side( "Right" ) ) ),
    Elements(
        Points( X, Y( 1 ), Y( 2 ), Legend( 1 ) ),
        Line( X, Y( 3 ), Legend( 4 ) ),
        Points( X, Y( 3 ), Legend( 1 ) ),
        Bar( X, Y( 4 ), Legend( 6 ), Bar Style( "Stacked" ) ),
        Points( X, Y( 4 ), Legend( 5 ) )
    ),
    Local Data Filter( Conditional, Add Filter( columns( :Date, :Close ), Where( :Date >= 04Jan2001:21:11:40 & :Date <= 26Feb2001 ) ) ),
    SendToReport(
        Dispatch( {}, "Date", ScaleBox, {Min( 3058214400 ), Max( 3066163200 ), Interval( "Month" ), Inc( 1 ), Minor Ticks( 3 )} ),
        Dispatch( {}, "High", ScaleBox, {Format( "Best", 15 ), Min( 0 ), Max( 60 ), Inc( 10 ), Minor Ticks( 0 )} ),
        Dispatch( {}, "Volume", ScaleBox, {Format( "Best", 15 ), Min( 0 ), Max( 800000000 ), Inc( 100000000 ), Minor Ticks( 0 )} ),
        Dispatch( {}, "400", LegendBox, {Legend Position( {1, [2, 4], 4, [0], 1, [2], 6, [5], 5, [6]} )} )
    )
);

Code Explanation:

1. Open data table;
2. Create Graph Builder window.
3. Set size to 436x412.
4. Hide control panel.
5. Set legend position to bottom.
6. Define X and Y variables.
7. Add points for High and Low.
8. Add line for Close.
9. Add stacked bar for Volume.
10. Apply local data filter on Date and Close.

Example 827

Summary: Creates a variability chart with nested factors using Graph Builder, displaying standard deviation charts and enabling legend for color.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 627, 527 ),
    Show Control Panel( 0 ),
    Variables( X( :weight ), Y( :height ), Color( :age ) ),
    Elements( Bar( X, Y, Legend( 2 ) ) )
);

Code Explanation:

1. Open data table;
2. Launch Graph Builder.
3. Set window size.
4. Hide control panel.
5. Assign weight to X-axis.
6. Assign height to Y-axis.
7. Assign age to color.
8. Add bar element.
9. Enable legend for color.
10. Display graph.

Example 828

Summary: Creates a variability chart with nested factors using Graph Builder, displaying standard deviation charts and utilizing range bar style.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 433, 414 ),
    Show Control Panel( 0 ),
    Variables( X( :sex ), Y( :height ), Y( :weight, Position( 1 ) ) ),
    Elements( Bar( X, Y( 1 ), Y( 2 ), Legend( 5 ), Bar Style( "Range" ), Summary Statistic( "% of Total" ), Label( "Label by Value" ) ) )
);

Code Explanation:

1. Open data table;
2. Launch Graph Builder.
3. Set window size.
4. Hide control panel.
5. Assign X variable.
6. Assign first Y variable.
7. Assign second Y variable.
8. Add bar element.
9. Set bar style to range.
10. Use percentage of total summary statistic.

Example 829

Summary: Creates a variability chart with nested factors using operator and part configurations, displaying standard deviation charts in Graph Builder.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 534, 2528 ),
    Show Control Panel( 0 ),
    Variables( X( :Mfr ), Y( :Protein ), Y( :Sugars, Position( 1 ) ), Page( :Fiber ) ),
    Elements( Bar( X, Y( 1 ), Y( 2 ), Legend( 4 ) ) )
);

Code Explanation:

1. Open data table;
2. Create Graph Builder window.
3. Set window size.
4. Hide control panel.
5. Define X variable as Mfr.
6. Define Y variables: Protein, Sugars.
7. Place Sugars on second Y-axis.
8. Use Fiber for page breaks.
9. Add bar chart element.
10. Display graph.

Example 830

Summary: Creates a variability chart with nested factors using operator and part configurations, displaying standard deviation charts within Graph Builder.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 442, 444 ),
    Show Control Panel( 0 ),
    Variables( Y( :Name( "Height  " ) ), Wrap( :Name( "Age " ) ), Color( :Name( "Name " ) ) ),
    Elements( Bar( Y, Legend( 21 ), Label( "Label by Value" ) ) ),
    Local Data Filter(
        Add Filter(
            columns( :Name( "Height  " ), :Name( "Weight " ) ),
            Where( :Name( "Height  " ) >= 58 & :Name( "Height  " ) <= 70 ),
            Where( :Name( "Weight " ) >= 79 & :Name( "Weight " ) <= 130 )
        )
    )
);

Code Explanation:

1. Open data table;
2. Create Graph Builder window.
3. Set window size.
4. Hide control panel.
5. Define variables: Y(Height), Wrap(Age), Color(Name).
6. Add bar element.
7. Enable label by value.
8. Add local data filter.
9. Filter Height between 58 and 70.
10. Filter Weight between 79 and 130.

Example 831

Summary: Creates a variability chart with nested factors using Graph Builder, displaying standard deviation charts and utilizing operator and part configurations.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 350, 292 ),
    Show Control Panel( 0 ),
    Variables( X( :Carat Weight ), X( :Table, Position( 1 ) ), X( :Depth ), Group Y( :Report ) ),
    Elements( Position( 1, 1 ), Bar( X( 1 ), X( 2 ), Legend( 6 ) ) ),
    Elements( Position( 2, 1 ), Bar( X, Legend( 8 ) ) )
);

Code Explanation:

1. Open data table;
2. Launch Graph Builder.
3. Set window size 350x292.
4. Hide control panel.
5. Assign variables: Carat Weight, Table, Depth, Report.
6. Position Table at 1.
7. Create first bar element.
8. Position bar at 1,1.
9. Use Carat Weight, Table for bar.
10. Add legend at position 6.

Example 832

Summary: Creates a variability chart with nested factors using Graph Builder, displaying standard deviation charts and configuring bar element width proportions.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 742, 479 ),
    Show Control Panel( 0 ),
    Show Legend( 0 ),
    Variables( X( :Day of Week ), X( :Server, Position( 1 ) ), Y( :Tip Amount ), Color( :Day of Week ) ),
    Elements( Bar( X( 1 ), X( 2 ), Y, Legend( 12 ) ) )
);
Graph Builder(
    Size( 742, 479 ),
    Show Control Panel( 0 ),
    Show Legend( 0 ),
    Variables( X( :Day of Week ), X( :Server, Position( 1 ) ), Y( :Tip Amount ), Color( :Day of Week ) ),
    Elements( Bar( X( 1 ), X( 2 ), Y, Legend( 12 ) ) ),
    SendToReport( Dispatch( {}, "Graph Builder", FrameBox, {DispatchSeg( BarSeg( 1 ), {Set Width Proportion( 1 )} )} ) )
);
Graph Builder(
    Size( 742, 479 ),
    Show Control Panel( 0 ),
    Show Legend( 0 ),
    Variables( X( :Day of Week ), X( :Server, Position( 1 ) ), Y( :Tip Amount ), Color( :Day of Week ) ),
    Elements( Bar( X( 1 ), X( 2 ), Y, Legend( 12 ) ) ),
    SendToReport( Dispatch( {}, "Graph Builder", FrameBox, {DispatchSeg( BarSeg( 1 ), {Set Width Proportion( 3 )} )} ) )
);

Code Explanation:

1. Open data table.
2. Create Graph Builder window.
3. Set window size.
4. Hide control panel.
5. Hide legend.
6. Define variables: X (Day of Week), X (Server), Y (Tip Amount), Color (Day of Week).
7. Add bar element with two X variables.
8. Repeat steps 2-7.
9. Set width proportion to 1.
10. Set width proportion to 3.

Example 833

Summary: Creates a bar chart with nested factors using Graph Builder, displaying standard deviation charts and enabling legend for bars.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 528, 454 ),
    Show Control Panel( 0 ),
    Variables( X( :weight ), Y( :height ) ),
    Elements( Bar( Legend( 3 ), Label( "Label by Row" ) ) )
);

Code Explanation:

1. Open data table;
2. Launch Graph Builder.
3. Set window size.
4. Hide control panel.
5. Assign weight to X-axis.
6. Assign height to Y-axis.
7. Add bar element.
8. Enable legend for bars.
9. Label bars by row.

Example 834

Summary: Creates variability charts with nested factors using Graph Builder, displaying standard deviation charts and error bars for range, two-way interval, interquartile range, and confidence interval.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 473, 302 ),
    Show Control Panel( 0 ),
    Show Footer( 0 ),
    Variables( X( :age ), X( :sex ), Y( :height ), Y( :weight, Position( 1 ) ) ),
    Elements( Position( 1, 1 ), Bar( X, Y( 1 ), Y( 2 ), Legend( 18 ), Error Bars( "Range" ) ) ),
    Elements( Position( 2, 1 ), Bar( X, Y( 1 ), Y( 2 ), Legend( 19 ), Error Bars( "Two-way Interval" ) ) )
);
Graph Builder(
    Size( 473, 302 ),
    Show Control Panel( 0 ),
    Show Footer( 0 ),
    Variables( X( :age ), X( :sex ), Y( :height ), Y( :weight, Position( 1 ) ) ),
    Elements( Position( 1, 1 ), Bar( X, Y( 1 ), Y( 2 ), Legend( 18 ), Error Bars( "Interquartile Range" ) ) ),
    Elements( Position( 2, 1 ), Bar( X, Y( 1 ), Y( 2 ), Legend( 19 ), Error Bars( "Confidence Interval" ) ) )
);
Graph Builder(
    Size( 473, 302 ),
    Show Control Panel( 0 ),
    Show Footer( 0 ),
    Variables( X( :age ), X( :sex ), Y( :height ), Y( :weight, Position( 1 ) ) ),
    Elements( Position( 1, 1 ), Bar( X, Y( 1 ), Y( 2 ), Legend( 18 ), Error Bars( "Standard Error" ) ) ),
    Elements( Position( 2, 1 ), Bar( X, Y( 1 ), Y( 2 ), Legend( 19 ), Error Bars( "Standard Deviation" ) ) )
);

Code Explanation:

1. Open data table.
2. Create first Graph Builder window.
3. Set window size.
4. Hide control panel.
5. Hide footer.
6. Define X and Y variables.
7. Add bar element with range error bars.
8. Add second bar element with two-way interval error bars.
9. Create second Graph Builder window.
10. Repeat steps 3-9 for interquartile range and confidence interval error bars.
11. Create third Graph Builder window.
12. Repeat steps 3-9 for standard error and standard deviation error bars.

Example 835

Summary: Creates a variability chart with nested factors using Graph Builder, displaying standard deviation charts and configuring bar elements with legends.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 591, 331 ),
    Show Control Panel( 0 ),
    Variables( X( :weight ), X( :sex ), Y( :height ), Color( :height ) ),
    Elements( Position( 1, 1 ), Bar( X, Y, Legend( 21 ) ) ),
    Elements( Position( 2, 1 ), Bar( X, Y, Legend( 22 ) ) )
);

Code Explanation:

1. Open data table;
2. Launch Graph Builder.
3. Set window size.
4. Hide control panel.
5. Define X, X, Y, and color variables.
6. Add first bar element.
7. Add second bar element.
8. Position elements on graph.
9. Assign legends to bars.
10. Display graph.

Example 836

Summary: Creates a variability chart with nested factors using Graph Builder, displaying standard deviation charts and error bars for multiple variables.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 743, 519 ),
    Show Control Panel( 0 ),
    Show Footer( 0 ),
    Variables(
        X( :age ),
        X( :sex ),
        Y( :height ),
        Y( :height ),
        Y( :weight, Position( 2 ) ),
        Y( :height ),
        Y( :weight, Position( 3 ) ),
        Y( :height ),
        Y( :weight, Position( 4 ) )
    ),
    Elements( Position( 1, 1 ), Bar( X, Y, Legend( 39 ), Error Bars( "Range" ) ) ),
    Elements( Position( 1, 2 ), Bar( X, Y( 1 ), Y( 2 ), Legend( 40 ), Error Bars( "Interquartile Range" ) ) ),
    Elements( Position( 1, 3 ), Bar( X, Y( 1 ), Y( 2 ), Legend( 41 ), Error Bars( "Standard Error" ) ) ),
    Elements( Position( 1, 4 ), Bar( X, Y( 1 ), Y( 2 ), Legend( 42 ), Error Bars( "Standard Deviation" ) ) ),
    Elements( Position( 2, 1 ), Bar( X, Y, Legend( 43 ), Error Bars( "Confidence Interval" ) ) ),
    Elements( Position( 2, 2 ), Bar( X, Y( 1 ), Y( 2 ), Legend( 44 ), Error Bars( "Custom Interval" ) ) ),
    Elements( Position( 2, 3 ), Bar( X, Y( 1 ), Y( 2 ), Legend( 45 ), Error Bars( "Two-way Interval" ) ) ),
    Elements( Position( 2, 4 ), Bar( X, Y( 1 ), Y( 2 ), Legend( 46 ) ) ),
    SendToReport(
        Dispatch( {}, "400", ScaleBox,
            {Legend Model( 40, Properties( 0, {Fill Color( 0 )} ) ), Legend Model(
                41,
                Base( 0, 0, 0 ),
                Properties( 0, {Fill Color( 0 )} )
            ), Legend Model( 42, Base( 0, 0, 0 ), Properties( 0, {Fill Color( 0 )} ) ), Legend Model(
                44,
                Base( 0, 0, 0 ),
                Properties( 0, {Fill Color( 0 )} )
            ), Legend Model( 45, Base( 0, 0, 0 ), Properties( 0, {Fill Color( 0 )} ) ), Legend Model(
                46,
                Base( 0, 0, 0 ),
                Properties( 0, {Fill Color( 0 )} )
            )}
        )
    )
);

Code Explanation:

1. Open data table.
2. Create Graph Builder window.
3. Set graph size.
4. Hide control panel.
5. Hide footer.
6. Define variables for axes.
7. Add first bar element with error bars.
8. Add second bar element with interquartile range.
9. Add third bar element with standard error.
10. Add fourth bar element with standard deviation.

Example 837

Summary: Creates a variability chart with nested factors using Graph Builder, displaying standard deviation charts and error bars for range.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 487, 533 ),
    Show Control Panel( 0 ),
    Show Legend( 1 ),
    Variables( Y( :height ), Y( :weight, Position( 1 ) ) ),
    Elements( Points( Y( 1 ), Y( 2 ), Legend( 6 ), Summary Statistic( "Mean" ), Error Bars( "Range" ) ) )
);

Code Explanation:

1. Open data table.
2. Launch Graph Builder.
3. Set window size.
4. Hide control panel.
5. Show legend.
6. Define Y variables.
7. Add points element.
8. Set summary statistic to mean.
9. Add error bars for range.
10. Display graph.

Example 838

Summary: Creates a variability chart with nested factors using Graph Builder, displaying standard deviation charts for age, height, and weight variables, while overlaying by sex.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 601, 466 ),
    Show Control Panel( 0 ),
    Show Footer( 0 ),
    Variables(
        X( :age ),
        Y( :height ),
        Y( :weight ),
        Y( :weight ),
        Y( :height ),
        Y( :height ),
        Y( :height ),
        Y( :height ),
        Overlay( :sex )
    ),
    Elements( Position( 1, 1 ), Bar( X, Y, Legend( 11 ), Error Bars( "Range" ) ) ),
    Elements( Position( 1, 2 ), Bar( X, Y, Legend( 10 ), Error Bars( "Interquartile Range" ) ) ),
    Elements( Position( 1, 3 ), Bar( X, Y, Legend( 8 ), Error Bars( "Standard Error" ) ) ),
    Elements( Position( 1, 4 ), Bar( X, Y, Legend( 6 ), Error Bars( "Standard Deviation" ) ) ),
    Elements( Position( 1, 5 ), Bar( X, Y, Legend( 5 ), Error Bars( "Confidence Interval" ) ) ),
    Elements( Position( 1, 6 ), Bar( X, Y, Legend( 12 ), Error Bars( "Custom Interval" ) ) ),
    Elements( Position( 1, 7 ), Bar( X, Y, Legend( 13 ) ) )
);

Code Explanation:

1. Open data table;
2. Launch Graph Builder.
3. Set graph size.
4. Hide control panel.
5. Hide footer.
6. Define variables: age, height, weight.
7. Overlay by sex.
8. Add bar element with range error bars.
9. Add bar element with interquartile range error bars.
10. Add bar element with standard error error bars.

Example 839

Summary: Creates a bar chart with error bars to visualize the relationship between age and height, utilizing Graph Builder's customization options.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 487, 392 ),
    Show Footer( 0 ),
    Show Control Panel( 0 ),
    Variables( X( :age ), Y( :height ) ),
    Elements( Bar( X, Y, Legend( 18 ), Error Bars( "Range" ) ) ),
    SendToReport(
        Dispatch( {}, "Graph Builder", FrameBox,
            {DispatchSeg( BarSeg( 2 ), {Line Color( "Dark Fuchsia" ), Line Width( 9 ), Error Bar Cap( "None" )} )}
        )
    )
);

Code Explanation:

1. Open data table;
2. Initiate Graph Builder.
3. Set graph size.
4. Hide footer.
5. Hide control panel.
6. Assign age to X-axis.
7. Assign height to Y-axis.
8. Add bar element.
9. Display error bars.
10. Customize bar appearance.

Example 840

Summary: Creates a bar chart with nested factors using Graph Builder, filtering data by age and height ranges.

Code:

dt = Open("data_table.jmp");
dt << Graph Builder(
    Size( 570, 501 ),
    Variables( X( :age ), Y( :height ) ),
    Elements( Bar( X, Y, Legend( 8 ), Summary Statistic( "N" ) ) ),
    Local Data Filter(
        Grouped by AND( 1 ),
        Add Filter( columns( :age ), Where( :age == {12, 15, 16, 17} ), Display( :age, Size( 160, 90 ), List Display ) ),
        Add Filter( columns( :height ), Where( :height >= 51 & :height <= 62.7 ) )
    )
);

Code Explanation:

1. Open data table.
2. Launch Graph Builder.
3. Set size 570x501.
4. Assign X variable: age.
5. Assign Y variable: height.
6. Add bar element.
7. Set summary statistic to N.
8. Enable local data filter.
9. Filter age for specific values.
10. Filter height within range.

Example 841

Summary: Creates a bar chart with nested factors using Graph Builder, displaying frequency data and summary statistics.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 200, 200 ),
    Show Control Panel( 0 ),
    Variables( X( :Relapsed ), Frequency( :Count ) ),
    Elements( Bar( X, Frequency( 0 ), Legend( 9 ), Summary Statistic( "Sum" ), Label( "Label by Value" ) ) )
);

Code Explanation:

1. Open data table;
2. Launch Graph Builder.
3. Set window size.
4. Hide control panel.
5. Define X variable.
6. Define frequency variable.
7. Add bar element.
8. Set summary statistic.
9. Label bars by value.
10. Display graph.

Example 842

Summary: Creates a variability chart with nested factors using Graph Builder, displaying standard deviation charts and controlling legend position.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 477, 250 ),
    Show Control Panel( 0 ),
    Variables( X( :age ), Group X( :height, N View Levels( 3 ) ) ),
    Elements( Bar( X, Legend( 4 ) ) )
);

Code Explanation:

1. Open data table;
2. Launch Graph Builder.
3. Set window size.
4. Hide control panel.
5. Assign X variable.
6. Group X by height.
7. Limit height levels to 3.
8. Add bar element.
9. Assign legend position.

Example 843

Summary: Creates a variability chart with nested factors using Graph Builder, displaying standard deviation charts and grouping data by height levels.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 477, 250 ),
    Show Control Panel( 0 ),
    Variables( X( :age ), Group X( :height, Levels( 4 ) ) ),
    Elements( Bar( X, Legend( 4 ) ) )
);

Code Explanation:

1. Open data_table data
2. Launch Graph Builder.
3. Set window size.
4. Hide control panel.
5. Set X variable to age.
6. Group X by height.
7. Set height levels to 4.
8. Add bar element.
9. Assign legend to bar.
10. Display graph.

Example 844

Summary: Creates a bar chart to visualize the relationship between sex and height, utilizing Graph Builder with specified size, control panel visibility, and label settings.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 525, 448 ),
    Show Control Panel( 0 ),
    Variables( X( :sex ), Y( :height ) ),
    Elements( Bar( X, Y, Legend( 6 ), Label( "Label by Value" ) ) )
);

Code Explanation:

1. Open data table.
2. Create Graph Builder object.
3. Set graph size.
4. Hide control panel.
5. Define X variable.
6. Define Y variable.
7. Add bar element.
8. Set legend position.
9. Enable label by value.

Example 845

Summary: Creates a variability chart with nested factors using operator and part configurations, displaying standard deviation charts in JMP.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 534, 448 ),
    Show Control Panel( 0 ),
    Variables( X( :sex ) ),
    Elements( Bar( X, Legend( 5 ), Summary Statistic( "% of Total" ), Label( "Label by Value" ) ) ),
    SendToReport(
        Dispatch( {}, "Graph Builder", FrameBox,
            Add Pin Annotation(
                Seg( BarSeg( 1 ) ),
                Index( {0, 0} ),
                Index Row( {0, 0} ),
                UniqueID( 792143440 ),
                FoundPt( {457, 326} ),
                Origin( {0.0136842105263157, 0.289285714285714} )
            )
        )
    )
);

Code Explanation:

1. Open data table.
2. Launch Graph Builder.
3. Set window size.
4. Hide control panel.
5. Assign X variable.
6. Create bar element.
7. Summarize by percentage of total.
8. Label bars by value.
9. Add pin annotation.
10. Position pin annotation.

Example 846

Summary: Creates a bar chart with interval style to visualize the relationship between Position and Weight, while filtering data by Height range using Local Data Filter.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 600, 580 ),
    Show Control Panel( 0 ),
    Include Missing Categories( 1 ),
    Variables( X( :Position ), Y( :Weight ), Group X( :Fat ), Group Y( :Bench ), Overlay( :Fat ) ),
    Elements( Bar( X, Y, Legend( 31 ), Bar Style( "Interval" ) ) ),
    Local Data Filter( Add Filter( columns( :Height ), Where( :Height >= 73.5 & :Height <= 77.156 ) ) )
);

Code Explanation:

1. Open data table;
2. Create Graph Builder object.
3. Set window size.
4. Hide control panel.
5. Include missing categories.
6. Define variables for axes and groups.
7. Add bar element with interval style.
8. Apply local data filter.
9. Filter height between 73.5 and 77.156.

Example 847

Summary: Creates a variability chart with nested factors using Graph Builder, displaying standard deviation charts and configuring bar style to interval.

Code:

Open("data_table.jmp") << Graph Builder(
    Size( 282, 258 ),
    Show Control Panel( 0 ),
    Variables( X( :sex ), Y( :height ), Y( :weight, Position( 1 ) ), Overlay( :age ) ),
    Elements( Bar( X, Y( 1 ), Y( 2 ), Legend( 7 ), Bar Style( "Interval" ) ) )
);

Code Explanation:

1. Open data table;
2. Launch Graph Builder.
3. Set window size to 282x258.
4. Hide control panel.
5. Assign sex to X-axis.
6. Assign height to primary Y-axis.
7. Assign weight to secondary Y-axis.
8. Overlay age variable.
9. Add bar element.
10. Configure bar style to interval.

Example 848

Summary: Creates a variability chart with nested factors using operator and part configurations, displaying standard deviation charts.

Code:

dt = Open("data_table.jmp");
myRows = dt << get rows where( :age == 14 & :sex == "F" );
dt << select rows( myRows );
dt << exclude;
Graph Builder(
    Size( 608, 628 ),
    Show Control Panel( 0 ),
    Variables( Y( :height ), Group X( :age ), Overlay( :sex ) ),
    Elements( Bar( Y, Legend( 6 ), Bar Style( "Interval" ) ) )
);

Code Explanation:

1. Open data table.
2. Get rows for age 14, female.
3. Select specified rows.
4. Exclude selected rows.
5. Launch Graph Builder.
6. Set graph size.
7. Hide control panel.
8. Assign variables to axes.
9. Add bar element.
10. Set bar style to interval.

Example 849

Summary: Creates two variability charts with nested factors using operator and part configurations, displaying standard deviation charts in JMP.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 518, 456 ),
    Show Control Panel( 0 ),
    Include Missing Categories( 1 ),
    Variables( X( :Development Level ), Y( :GER ), Y( :HDI, Position( 1 ) ) ),
    Elements( Bar( X, Y( 1 ), Y( 2 ), Legend( 5 ), Bar Style( "Range" ), Summary Statistic( "Sum" ), Label( "Label by Value" ) ) )
);
Graph Builder(
    Size( 518, 456 ),
    Show Control Panel( 0 ),
    Include Missing Categories( 1 ),
    Variables( X( :Development Level ), Y( :GER ), Y( :HDI, Position( 1 ) ) ),
    Elements( Bar( X, Y( 1 ), Y( 2 ), Legend( 5 ), Bar Style( "Interval" ), Summary Statistic( "Sum" ), Label( "Label by Value" ) ) )
);

Code Explanation:

1. Open data table;
2. Create first Graph Builder window.
3. Set size to 518x456.
4. Hide control panel.
5. Include missing categories.
6. Set X variable: Development Level.
7. Set Y variables: GER, HDI.
8. Add bar element.
9. Use range bar style.
10. Summarize data using sum.
11. Label bars by value.
12. Create second Graph Builder window.
13. Repeat steps 3-11.
14. Use interval bar style.

Example 850

Summary: Creates a variability chart with nested factors using Graph Builder, displaying standard deviation charts and side-by-side interval bars.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 564, 570 ),
    Show Control Panel( 0 ),
    Include Missing Categories( 1 ),
    Variables( X( :Height ), Y( :Weight ), Overlay( :Fat ) ),
    Elements( Bar( X, Y, Legend( 83 ), Bar Style( "Side by side intervals" ), Summary Statistic( "% of Total" ) ) )
);

Code Explanation:

1. Open data table;
2. Create new Graph Builder window.
3. Set graph size.
4. Hide control panel.
5. Include missing categories.
6. Assign variables: X=Height, Y=Weight, Overlay=Fat.
7. Add bar element.
8. Set bar style to side by side intervals.
9. Use percentage of total summary statistic.
10. Display graph.

Example 851

Summary: Creates a variability chart with nested factors using operator and part configurations, displaying standard deviation charts in Graph Builder.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 600, 544 ),
    Show Control Panel( 0 ),
    Include Missing Categories( 1 ),
    Variables( X( :Position ), Y( :Weight ), Group Y( :Bench ), Overlay( :Fat ) ),
    Elements( Bar( X, Y, Legend( 31 ), Bar Style( "Interval" ) ) ),
    Local Data Filter( Add Filter( columns( :Height ), Where( :Height >= 66 & :Height <= 77.156 ) ) ),
    SendToReport( Dispatch( {}, "400", LegendBox, {Set Title( "" )} ) )
);

Code Explanation:

1. Open data table;
2. Create graph builder window.
3. Set graph size.
4. Hide control panel.
5. Include missing categories.
6. Define variables for axes.
7. Add bar element.
8. Apply local data filter.
9. Remove legend title.
10. Display graph.

Example 852

Summary: Creates a variability chart with nested factors using operator and part configurations, displaying standard deviation charts in Graph Builder.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 585, 391 ),
    Show Control Panel( 0 ),
    Variables( X( :Cycle Time ), Y( :Shrinkage ) ),
    Elements( Bar( X, Y, Legend( 8 ), Summary Statistic( "Sum" ), Label( "Label by Row" ) ) )
);

Code Explanation:

1. Open data table;
2. Launch Graph Builder.
3. Set window size.
4. Hide control panel.
5. Assign X variable.
6. Assign Y variable.
7. Add bar element.
8. Set legend position.
9. Use sum summary statistic.
10. Label bars by row.

Example 853

Summary: Creates a variability chart with nested factors using operator and part configurations, displaying standard deviation charts.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 754, 420 ),
    Show Control Panel( 0 ),
    Variables( X( :age ), X( :sex, Position( 1 ) ), Overlay( :age ) ),
    Elements( Bar( X( 1 ), X( 2 ), Legend( 5 ), Summary Statistic( "% of Total" ), Label( "Label by Value" ) ) )
);

Code Explanation:

1. Open data table;
2. Create Graph Builder window.
3. Set window size.
4. Hide control panel.
5. Define X variables: age, sex.
6. Set sex position to 1.
7. Overlay by age.
8. Add bar element.
9. Configure bar for age and sex.
10. Display percentage of total.

Example 854

Summary: Creates a variability chart with nested factors using operator and part configurations, displaying standard deviation charts.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 691, 482 ),
    Show Control Panel( 0 ),
    Show Legend( 0 ),
    Show Footer( 0 ),
    Variables( X( :age ), Y( :height ), Y( :weight, Position( 1 ) ), Overlay( :sex ) ),
    Elements( Bar( X, Y( 1 ), Y( 2 ), Legend( 69 ) ) ),
    Local Data Filter(
        Mode( Include( 0 ) ),
        Inverse( 1 ),
        Add Filter( columns( :age ), Where( :age == {14, 15, 16, 17} ), Display( :age, Size( 177, 168 ), List Display ) )
    )
);

Code Explanation:

1. Open data table;
2. Create Graph Builder object.
3. Set window size.
4. Hide control panel.
5. Hide legend.
6. Hide footer.
7. Define X and Y variables.
8. Add overlay variable.
9. Add bar elements.
10. Configure local data filter.

Example 855

Summary: Creates a bar chart with nested factors using Graph Builder, filtering data by 'height' and 'weight', and displaying a standard deviation chart.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 527, 464 ),
    Show Control Panel( 0 ),
    Variables( X( :age ) ),
    Elements( Bar( X, Legend( 3 ) ) ),
    Local Data Filter(
        Mode( Include( 0 ) ),
        Add Filter( columns( :height ) ),
        Add Filter( columns( :weight ), Where( :weight >= 110.5 & :weight <= 172 ) )
    )
);

Code Explanation:

1. Open data table;
2. Launch Graph Builder.
3. Set window size to 527x464.
4. Hide control panel.
5. Set X-axis variable to "age".
6. Add bar chart element.
7. Enable local data filter.
8. Set filter mode to include all.
9. Add filter for "height" column.
10. Add filter for "weight" between 110.5 and 172.

Example 856

Summary: Creates a variability chart with nested factors using Graph Builder, featuring a bar element with summary statistics and label by value, while also applying a local data filter for height.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 619, 544 ),
    Show Control Panel( 0 ),
    Variables( Wrap( :age ), Color( :height ) ),
    Elements( Bar( Legend( 8 ), Summary Statistic( "Sum" ), Label( "Label by Value" ) ) ),
    Local Data Filter( Add Filter( columns( :height ), Where( :height >= 56 & :height <= 65 ) ) )
);

Code Explanation:

1. Open data table;
2. Create new Graph Builder window.
3. Set window size.
4. Hide control panel.
5. Define wrap variable as age.
6. Define color variable as height.
7. Add bar element.
8. Set summary statistic to sum.
9. Enable label by value.
10. Add local data filter for height.

Example 857

Summary: Creates a bar chart with nested factors using Graph Builder, filtering data by sex column and displaying a standard deviation chart.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 528, 448 ),
    Show Control Panel( 0 ),
    Variables( X( :age ) ),
    Elements( Bar( X, Legend( 3 ) ) ),
    Local Data Filter( Add Filter( columns( :sex ) ) )
);

Code Explanation:

1. Open data table.
2. Create Graph Builder object.
3. Set graph size.
4. Hide control panel.
5. Assign X variable.
6. Add bar element.
7. Configure legend.
8. Add local data filter.
9. Filter by sex column.

Example 858

Summary: Creates a variability chart with nested factors using Graph Builder, displaying standard deviation charts and summarizing data by sex and height.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 664, 435 ),
    Show Control Panel( 0 ),
    Variables( X( :sex ), Y( :height ), Y( :height ), Overlay( :age ) ),
    Elements( Position( 1, 1 ), Bar( X, Y, Legend( 1 ), Summary Statistic( "Sum" ), Label( "Label by Percent of Total Values" ) ) ),
    Elements( Position( 1, 2 ), Bar( X, Y, Legend( 2 ), Summary Statistic( "Sum" ), Label( "Label by Value" ) ) )
);

Code Explanation:

1. Open data table.
2. Launch Graph Builder.
3. Set window size.
4. Hide control panel.
5. Assign variables: X(sex), Y(height).
6. Create first bar element.
7. Position first bar element.
8. Set summary statistic to sum.
9. Label bars by percent of total values.
10. Create second bar element.

Example 859

Summary: Creates a variability chart with nested factors using Graph Builder, displaying standard deviation charts for Chol-3yrs, HDL-3yrs, and LDL-3yrs.

Code:

Open("data_table.jmp") << Graph Builder(
    Size( 534, 464 ),
    Show Control Panel( 0 ),
    Variables(
        X( :Smoking History ),
        X( :Alcohol use, Position( 1 ) ),
        Y( :Name( "Chol-3yrs" ) ),
        Y( :Name( "HDL-3yrs" ), Position( 1 ) ),
        Y( :Name( "LDL-3yrs" ), Position( 1 ) )
    ),
    Elements( Bar( X( 1 ), X( 2 ), Y( 1 ), Y( 2 ), Y( 3 ), Legend( 4 ) ) ),
    Local Data Filter( Add Filter( columns( :Sex ) ) )
);

Code Explanation:

1. Open data table.
2. Create Graph Builder window.
3. Set window size.
4. Hide control panel.
5. Define X variables: Smoking History, Alcohol use.
6. Define Y variables: Chol-3yrs, HDL-3yrs, LDL-3yrs.
7. Position Alcohol use and HDL-3yrs on second axis.
8. Add bar chart element.
9. Link X and Y variables to bar chart.
10. Add local data filter for Sex.

Example 860

Summary: Creates a variability chart with nested factors using Graph Builder, displaying standard deviation charts and error bars for visualizing data distribution.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 601, 474 ),
    Show Control Panel( 0 ),
    Variables( X( :age ), Y( :height ), Y( :height ), ),
    Elements( Position( 1, 1 ), Bar( X, Y, Legend( 6 ), Error Bars( "Range" ) ) ),
    Elements(
        Position( 1, 2 ),
        Bar( X, Y, Legend( 5 ), Summary Statistic( "% of Total" ), Error Bars( "Range" ), Label( "Label by Value" ) )
    )
);

Code Explanation:

1. Open data table.
2. Create Graph Builder window.
3. Set window size.
4. Hide control panel.
5. Define X variable.
6. Define first Y variable.
7. Duplicate Y variable.
8. Add bar element for first Y.
9. Add legend to first bar.
10. Add error bars to first bar.

Example 861

Summary: Creates a variability chart with nested factors using operator and part configurations, displaying standard deviation charts in Graph Builder.

Code:

dt = Open("data_table.jmp");
Graph Builder(
    Size( 435, 327 ),
    Show Control Panel( 0 ),
    Variables( X( :Cut ), Y( :Carat Weight ), Y( :Table, Position( 1 ), Side( "Right" ) ), Y( :Depth, Position( 1 ), Side( "Right" ) ) ),
    Elements( Bar( X, Y( 2 ), Y( 3 ), Legend( 30 ), Summary Statistic( "Min" ) ), Bar( X, Y( 1 ), Legend( 27 ), Bar Style( "Nested" ) ) ),
    SendToReport(
        Dispatch( {}, "Table", ScaleBox,
            {Format( "Best", 10 ), Min( -0.0518961122198434 ), Max( 80.0776971595434 ), Inc( 20 ), Minor Ticks( 0 )}
        ),
        Dispatch( {}, "400", LegendBox, {Legend Position( {30, [1, 2], 27, [0]} )} )
    )
);

Code Explanation:

1. Open data table;
2. Create Graph Builder window.
3. Set window size to 435x327.
4. Hide control panel.
5. Define X variable as Cut.
6. Define Y variables: Carat Weight, Table, Depth.
7. Add nested bar element for Cut and Carat Weight.
8. Add bar element for Cut, Table, and Depth.
9. Format Table scale box.
10. Adjust legend positions.

Example 862

Summary: Creates a variability chart with nested factors using Graph Builder, displaying standard deviation charts and configuring legend position.

Code:

dt = Open("data_table.jmp");
Graph Builder(
    Size( 530, 455 ),
    Show Control Panel( 0 ),
    Variables( Y( :height ), Wrap( :age ), Overlay( :sex ) ),
    Elements( Bar( Y, Legend( 7 ) ) )
);

Code Explanation:

1. Open data table.
2. Create Graph Builder object.
3. Set graph size.
4. Hide control panel.
5. Define variables: Y axis (height), X axis (age), overlay (sex).
6. Add bar element.
7. Set legend position.
8. Render graph.

Example 863

Summary: Creates a variability chart with nested factors using Graph Builder, displaying standard deviation charts and configuring bar summary statistics to percentages.

Code:

dt = Open("data_table.jmp");
Graph Builder(
    Size( 504, 387 ),
    Show Control Panel( 0 ),
    Variables( X( :age ), X( :sex, Position( 1 ) ), Y( :height ), Overlay( :sex ) ),
    Elements( Bar( X( 1 ), X( 2 ), Y, Legend( 17 ), Summary Statistic( "% of Total" ), Label( "Label by Value" ) ) )
);

Code Explanation:

1. Open data table.
2. Create Graph Builder object.
3. Set window size.
4. Hide control panel.
5. Define X variables: age, sex.
6. Set sex position to 1.
7. Define Y variable: height.
8. Overlay by sex.
9. Add Bar element.
10. Configure bar summary statistic to percentage.

Example 864

Summary: Creates a graph builder window with nested factors, utilizing Graph Builder to display a bar chart with custom formatting and labels.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 768, 518 ),
    Show Control Panel( 0 ),
    Show Legend( 0 ),
    Title Alignment( "Left" ),
    Title Span( "Graph contents" ),
    Subtitle Alignment( "Left" ),
    Subtitle Span( "Graph contents" ),
    Show Subtitle( 1 ),
    Show Footer( 0 ),
    Variables( X( :Cost ), Y( :Unique Event ) ),
    Elements( Bar( X, Y, Legend( 6 ), Bar Style( "Packed" ), Packed Primaries( 10 ), Packed Labeling( 0.4091 ) ) ),
    SendToReport(
        Dispatch( {}, "Cost", ScaleBox,
            {Format(
                "Custom",
                Formula( If( value == 0, "0", "$" || Format( value, "precision", Keep trailing zeroes( 0 ), 3 ) || "B" ) ),
                17
            ), Min( 0 ), Max( 164.265890870419 ), Inc( 20 ), Minor Ticks( 0 )}
        ),
        Dispatch( {}, "graph title", TextEditBox,
            {Set Font Size( 18 ), Set Font Style( "Plain" ), Set Text( "Billion-dollar disasters in the US, 1980-2017" )}
        ),
        Dispatch( {}, "graph 1 title", TextEditBox,
            {Set Font Size( 15 ), Set Text( "CPI-adjusted estimated costs from NOAA, www.ncdc.noaa.gov/billions/" )}
        ),
        Dispatch( {}, "X title", TextEditBox, {Set Text( "" )} ),
        Dispatch( {}, "Y title", TextEditBox, {Set Text( "" )} ),
        Dispatch( {}, "400", LegendBox, {Set Title( "" ), font( "Arial", 16, "Plain" )} )
    )
);

Code Explanation:

1. Open data table;
2. Create Graph Builder window.
3. Set window size.
4. Hide control panel.
5. Hide legend.
6. Align title left.
7. Set title span.
8. Align subtitle left.
9. Set subtitle span.
10. Show subtitle.

Example 865

Summary: Creates a variability chart with nested factors using Graph Builder, displaying standard deviation charts and utilizing packed bar style.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 500, 350 ),
    show control panel( 0 ),
    Variables( Y( :Reported Term for the Adverse Event ) ),
    Elements( Bar( Y, Legend( 6 ), Bar Style( "Packed" ) ) )
);

Code Explanation:

1. Open data file.
2. Launch Graph Builder.
3. Set window size.
4. Hide control panel.
5. Assign Y variable.
6. Add bar element.
7. Style bar packed.
8. Position legend.

Example 866

Summary: Creates a variability chart with nested factors using Graph Builder, displaying standard deviation charts and applying packed bar style.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 710, 471 ),
    Show Control Panel( 0 ),
    Variables( X( :height ), Y( :name ), Group Y( :sex ) ),
    Elements( Bar( X, Y, Legend( 4 ), Bar Style( "Packed" ), Packed Primaries( 5 ), Packed Labeling( 0.9541 ) ) )
);

Code Explanation:

1. Open data table;
2. Create Graph Builder window.
3. Set window size.
4. Hide control panel.
5. Define X variable.
6. Define Y variable.
7. Group Y by sex.
8. Add bar element.
9. Set legend position.
10. Apply packed bar style.

Example 867

Summary: Creates a variability chart with nested factors using Graph Builder, displaying standard deviation charts and configuring summary statistics for each bar element.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 601, 474 ),
    Show Control Panel( 0 ),
    Variables( X( :age ), Y( :height ), Y( :height ), Overlay( :sex ) ),
    Elements( Position( 1, 1 ), Bar( X, Y, Legend( 6 ), Error Bars( "Range" ) ) ),
    Elements(
        Position( 1, 2 ),
        Bar( X, Y, Legend( 5 ), Summary Statistic( "% of Total" ), Error Bars( "Range" ), Label( "Label by Value" ) )
    )
);

Code Explanation:

1. Open data table;
2. Launch Graph Builder.
3. Set window size.
4. Hide control panel.
5. Define X, Y variables.
6. Add first bar element.
7. Position first bar.
8. Add second bar element.
9. Position second bar.
10. Configure second bar summary statistic.

Example 868

Summary: Creates a variability chart with nested factors using Graph Builder, displaying standard deviation charts and labeling bars by percent of total values.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 640, 381 ),
    Show Control Panel( 0 ),
    Variables( X( :age ), Y( :height ) ),
    Elements( Bar( X, Y, Legend( 4 ), Summary Statistic( "Interquartile Range" ), Label( "Label by Percent of Total Values" ) ) )
);

Code Explanation:

1. Open data_table data
2. Launch Graph Builder.
3. Set window size to 640x381.
4. Hide control panel.
5. Assign age to X-axis.
6. Assign height to Y-axis.
7. Add bar element.
8. Use interquartile range summary.
9. Label bars by percent of total values.
10. Display graph.

Example 869

Summary: Creates a variability chart with nested factors using Graph Builder, displaying standard deviation charts and labeling bars by percent of total values.

Code:

dt = Open("data_table.jmp");
Graph Builder(
    Size( 640, 381 ),
    Show Control Panel( 0 ),
    Variables( X( :age ), Y( :height ) ),
    Elements( Bar( X, Y, Legend( 4 ), Summary Statistic( "Interquartile Range" ), Label( "Label by Percent of Total Values" ) ) )
);

Code Explanation:

1. Open data table.
2. Create Graph Builder window.
3. Set window size.
4. Hide control panel.
5. Define X variable.
6. Define Y variable.
7. Add bar element.
8. Set summary statistic.
9. Label bars by percent.
10. Display graph.

Example 870

Summary: Creates a variability chart with nested factors using Graph Builder, displaying standard deviation charts and overlaying by sex.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 527, 484 ),
    Show Control Panel( 0 ),
    Variables(
        X( :age ),
        Y( Transform Column( "Center[height]", Format( "Fixed Dec", 5, 0 ), Formula( :height - Col Mean( :height ) ) ) ),
        Wrap( :age ),
        Overlay( :sex )
    ),
    Elements( Bar( X, Y, Legend( 10 ), Bar Style( "Range" ), Label( "Label by Value" ) ) )
);

Code Explanation:

1. Open data table.
2. Create Graph Builder window.
3. Set window size.
4. Hide control panel.
5. Define X variable.
6. Define transformed Y variable.
7. Wrap by age.
8. Overlay by sex.
9. Add bar element.
10. Set bar style to range.

Example 871

Summary: Creates a variability chart with nested factors using Graph Builder, configuring bar style and summary statistics.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 552, 570 ),
    Show Control Panel( 0 ),
    Include Missing Categories( 1 ),
    Variables( X( :Height ), Y( :Weight ), Overlay( :Fat ) ),
    Elements( Bar( X, Y, Legend( 83 ), Bar Style( "Range" ), Response Axis( "Y" ), Summary Statistic( "N" ) ) )
);

Code Explanation:

1. Open data_table data
2. Create graph builder.
3. Set size to 552x570.
4. Hide control panel.
5. Include missing categories.
6. Set X variable to Height.
7. Set Y variable to Weight.
8. Set overlay variable to Fat.
9. Add bar element.
10. Configure bar style and summary statistic.

Example 872

Summary: Creates a variability chart with nested factors using operator and part configurations, displaying standard deviation charts in Graph Builder.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 718, 467 ),
    Show Control Panel( 0 ),
    Variables( X( :Clarity ), Y( :Depth ), Y( :Table, Position( 1 ) ), Group Y( :Cut ), Overlay( :Report ) ),
    Elements( Line( X, Y( 1 ), Y( 2 ), Legend( 3 ), Error Bars( "Range" ) ) ),
    SendToReport(
        Dispatch( {}, "Graph Builder", FrameBox, {Grid Line Order( 3 ), Reference Line Order( 4 )} ),
        Dispatch( {}, "Graph Builder", FrameBox( 2 ), {Grid Line Order( 5 ), Reference Line Order( 6 )} ),
        Dispatch( {}, "Graph Builder", FrameBox( 3 ), {Grid Line Order( 5 ), Reference Line Order( 6 )} ),
        Dispatch( {}, "Graph Builder", FrameBox( 4 ), {Grid Line Order( 3 ), Reference Line Order( 4 )} )
    )
);

Code Explanation:

1. Open data table;
2. Create Graph Builder window.
3. Set size to 718x467.
4. Hide control panel.
5. Define X variable: Clarity.
6. Define Y variables: Depth, Table.
7. Define Group Y: Cut.
8. Define Overlay: Report.
9. Add Line element with error bars.
10. Customize grid and reference lines for frames.

Example 873

Summary: Creates a variability chart with nested factors using Graph Builder, displaying standard deviation charts and summarizing data by percent.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 425, 365 ),
    Show Control Panel( 0 ),
    Variables( X( :sex ), Y( :weight ), Y( :height, Position( 1 ) ) ),
    Elements(
        Bar(
            X,
            Y( 1 ),
            Y( 2 ),
            Legend( 5 ),
            Bar Style( "Range" ),
            Summary Statistic( "Sum" ),
            Label( "Label by Percent of Total Values" )
        )
    )
);

Code Explanation:

1. Open data table.
2. Launch Graph Builder.
3. Set window size.
4. Hide control panel.
5. Define X variable.
6. Define first Y variable.
7. Define second Y variable.
8. Add bar element.
9. Set X axis.
10. Set Y1 axis.
11. Set Y2 axis.
12. Assign legend position.
13. Choose bar style.
14. Select summary statistic.
15. Label by percent.

Example 874

Summary: Creates a variability chart with nested factors using Graph Builder, configuring bar style to range and customizing legend with gradient and fill pattern.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 534, 450 ),
    Show Control Panel( 0 ),
    Variables( X( :age ), Y( :weight ), Overlay( :sex ), Color( :height ) ),
    Elements( Bar( X, Y, Legend( 7 ), Bar Style( "Range" ) ) ),
    SendToReport(
        Dispatch( {}, "400", ScaleBox,
            {Legend Model(
                7,
                Properties(
                    0,
                    {gradient( {Color Theme( "Blue to Green to Red" ), Scale Values( [58 64] )} ), Fill Pattern( "right slant light" )},
                    Item ID( "height", 1 )
                )
            )}
        )
    )
);

Code Explanation:

1. Open data table;
2. Launch Graph Builder.
3. Set window size.
4. Hide control panel.
5. Assign variables: X=age, Y=weight.
6. Add overlay variable: sex.
7. Add color variable: height.
8. Create bar element.
9. Configure bar style to range.
10. Customize legend with gradient and fill pattern.

Example 875

Summary: Creates a variability chart with nested factors using Graph Builder, displaying standard deviation charts and labeling bars by row.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 668, 356 ),
    Show Control Panel( 0 ),
    Show Legend( 0 ),
    Include Missing Categories( 1 ),
    Variables( X( :age ), Y( :height ), Overlay( :age ) ),
    Elements( Bar( X, Y, Legend( 6 ), Bar Style( "Range" ), Label( "Label by Row" ) ) )
);

Code Explanation:

1. Open data table;
2. Launch Graph Builder.
3. Set window size.
4. Hide control panel.
5. Hide legend.
6. Include missing categories.
7. Assign variables: X=age, Y=height, Overlay=age.
8. Add bar element.
9. Set bar style to range.
10. Label bars by row.

Example 876

Summary: Creates a variability chart with nested factors using operator and part configurations, displaying standard deviation charts.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 677, 507 ),
    Show Control Panel( 0 ),
    Variables( X( :age ), Y( :height ), Overlay( :age ) ),
    Elements( Bar( X, Y, Legend( 3 ), Bar Style( "Range" ), Summary Statistic( "Sum" ), Label( "Label by Value" ) ) )
);

Code Explanation:

1. Open data table;
2. Launch Graph Builder.
3. Set window size.
4. Hide control panel.
5. Assign variables.
6. Add bar element.
7. Set bar style to range.
8. Use sum for summary statistic.
9. Label bars by value.
10. Display graph.

Example 877

Summary: Creates a variability chart with nested factors using Graph Builder, displaying standard deviation charts and configuring part configurations.

Code:

Open("data_table.jmp") << Graph Builder(
    Size( 262, 233 ),
    Show Control Panel( 0 ),
    Variables( X( :age ), X( :size ), Overlay( :country ) ),
    Elements( Position( 1, 1 ), Bar( X, Legend( 7 ) ) ),
    Elements( Position( 2, 1 ), Bar( X, Legend( 8 ), Response Axis( "Y" ) ) )
);

Code Explanation:

1. Open data table;
2. Launch Graph Builder.
3. Set window size.
4. Hide control panel.
5. Define X variables: age, size.
6. Define overlay variable: country.
7. Add first bar element.
8. Position first bar element.
9. Add second bar element.
10. Position second bar element.

Example 878

Summary: Creates a variability chart with nested factors using Graph Builder, displaying standard deviation charts and utilizing local data filtering for interactive analysis.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 600, 580 ),
    Show Control Panel( 0 ),
    Include Missing Categories( 1 ),
    Variables( X( :Position ), Y( :Weight ), Group X( :Fat ), Group Y( :Bench ), Overlay( :Fat ) ),
    Elements( Bar( X, Y, Legend( 50 ), Summary Statistic( "% of Total" ), Label( "Label by Row" ) ) ),
    Local Data Filter( Mode( Show( 0 ) ), Add Filter( columns( :Height ), Where( :Height >= 66.094 & :Height <= 77.156 ) ) )
);

Code Explanation:

1. Open data table;
2. Create Graph Builder window.
3. Set size to 600x580.
4. Hide control panel.
5. Include missing categories.
6. Set X variable: Position.
7. Set Y variable: Weight.
8. Group X by Fat.
9. Group Y by Bench.
10. Overlay by Fat.

Example 879

Summary: Creates a bar chart with nested factors using Graph Builder, enabling local data filtering by sex.

Code:

dt = Open("data_table.jmp");
dt << Graph Builder(
    Size( 570, 516 ),
    Variables( Y( :height ) ),
    Elements( Bar( Y, Legend( 2 ) ) ),
    Local Data Filter( Add Filter( columns( :sex ) ) )
);

Code Explanation:

1. Open data table.
2. Launch Graph Builder.
3. Set window size.
4. Specify Y variable.
5. Add bar element.
6. Enable legend for bars.
7. Add local data filter.
8. Set filter columns.

Example 880

Summary: Creates a graph builder with nested factors using local data filters and displays age filter as a list.

Code:

dt = Open("data_table.jmp");
dt << Graph Builder(
    Variables( Y( :height ), Y( :weight, Position( 1 ) ) ),
    Elements( Bar( Y( 1 ), Y( 2 ), Legend( 3 ) ) ),
    Local Data Filter(
        Grouped by AND( 1 ),
        Add Filter(
            columns( :height, :age ),
            Where( :height >= 52.5 & :height <= 59.2 ),
            Where( :age == {12, 13, 14} ),
            Display( :age, Size( 160, 90 ), List Display )
        )
    )
);

Code Explanation:

1. Open data table;
2. Create Graph Builder object.
3. Set Y variables: height, weight.
4. Add bar element for height and weight.
5. Enable local data filter.
6. Group filters using AND condition.
7. Add filter for height range.
8. Add filter for specific ages.
9. Display age filter as list.
10. Configure age filter size.

Example 881

Summary: Creates a stacked bar chart with nested factors using Graph Builder, displaying standard deviation charts and error bars.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 443, 453 ),
    Show Control Panel( 0 ),
    Variables( X( :age ), Y( :height ), Y( :weight, Position( 1 ) ) ),
    Elements(
        Bar(
            X,
            Y( 1 ),
            Y( 2 ),
            Legend( 4 ),
            Bar Style( "Stacked" ),
            Summary Statistic( "N" ),
            Error Bars( "Confidence Interval" ),
            Label( "Label by Row" )
        )
    )
);

Code Explanation:

1. Open data table.
2. Launch Graph Builder.
3. Set window size.
4. Hide control panel.
5. Define X variable.
6. Define first Y variable.
7. Define second Y variable.
8. Add bar element.
9. Set bar style to stacked.
10. Use summary statistic N.

Example 882

Summary: Creates three stacked bar graphs with nested factors using Graph Builder, displaying percentage of total, factor, and grand total summary statistics.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 534, 456 ),
    Show Control Panel( 0 ),
    Variables( X( :Year ), Y( :Market Share ), Overlay( :Operating System ) ),
    Elements( Bar( X, Y, Legend( 7 ), Bar Style( "Stacked" ), Summary Statistic( "% of Total" ), Label( "Label by Value" ) ) )
);
Graph Builder(
    Size( 534, 456 ),
    Show Control Panel( 0 ),
    Variables( X( :Year ), Y( :Market Share ), Overlay( :Operating System ) ),
    Elements( Bar( X, Y, Legend( 7 ), Bar Style( "Stacked" ), Summary Statistic( "% of Factor" ), Label( "Label by Value" ) ) )
);
Graph Builder(
    Size( 534, 456 ),
    Show Control Panel( 0 ),
    Variables( X( :Year ), Y( :Market Share ), Overlay( :Operating System ) ),
    Elements( Bar( X, Y, Legend( 7 ), Bar Style( "Stacked" ), Summary Statistic( "% of Grand Total" ), Label( "Label by Value" ) ) )
);

Code Explanation:

1. Open data table;
2. Create first stacked bar graph.
3. Set graph size.
4. Hide control panel.
5. Define X, Y, and overlay variables.
6. Add stacked bar element.
7. Use percentage of total summary statistic.
8. Label bars by value.
9. Create second stacked bar graph.
10. Use percentage of factor summary statistic.
11. Create third stacked bar graph.
12. Use percentage of grand total summary statistic.

Example 883

Summary: Creates a stacked bar chart with nested factors using Graph Builder, displaying median summary statistics and standard deviation charts.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 528, 494 ),
    Show Control Panel( 0 ),
    Variables( X( :Depth ), X( :Table, Position( 1 ) ), Y( :Clarity ), Group X( :Cut ), Frequency( :Price ) ),
    Elements(
        Bar(
            X( 1 ),
            X( 2 ),
            Y,
            Legend( 4 ),
            Bar Style( "Stacked" ),
            Summary Statistic( "Median" ),
            Label( "Label by Percent of Total Values" )
        )
    ),
    SendToReport(
        Dispatch( {}, "Depth", ScaleBox,
            {Scale( "Log" ), Format( "Best", 10 ), Min( 56.846915214878 ), Max( 62.7363232050543 ), Inc( 1 ), Minor Ticks( 1 )}
        )
    )
);

Code Explanation:

1. Open data table;
2. Create Graph Builder.
3. Set graph size to 528x494.
4. Hide control panel.
5. Assign variables: X(Depth), X(Table), Y(Clarity), Group X(Cut), Frequency(Price).
6. Add stacked bar element.
7. Set X1, X2, Y axes.
8. Use legend for 4th element.
9. Apply median summary statistic.
10. Label by percent of total values.

Example 884

Summary: Creates a stacked bar chart with nested factors using Graph Builder, displaying standard deviation charts and configuring log scale Y-axis.

Code:

Open("data_table.jmp");
obj = Graph Builder(
    Size( 449, 304 ),
    Show Control Panel( 0 ),
    Variables( X( :Cut ), Y( :Price ), Overlay( :Depth ) ),
    Elements( Bar( X, Y, Legend( 11 ), Bar Style( "Stacked" ), Summary Statistic( "Sum" ) ) ),
    SendToReport(
        Dispatch( {}, "Price", ScaleBox, {Scale( "Log", {Log Base( 2 )} ), Min( 1000 ), Max( 5272471.8 ), Inc( 1 ), Minor Ticks( 0 )} )
    )
);

Code Explanation:

1. Open data table;
2. Create Graph Builder object.
3. Set graph size.
4. Hide control panel.
5. Define X, Y, Overlay variables.
6. Add stacked bar element.
7. Configure summary statistic to sum.
8. Log scale Y axis.
9. Set log base 2.
10. Adjust Y axis min, max, increment.

Example 885

Summary: Creates a variability chart with nested factors using Graph Builder, displaying standard deviation charts and utilizing packed bar style.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 526, 434 ),
    Show Control Panel( 0 ),
    Variables( X( :height ), Y( :weight ) ),
    Elements( Bar( X, Y, Legend( 4 ), Bar Style( "Packed" ) ) )
);

Code Explanation:

1. Open data table.
2. Create Graph Builder window.
3. Set window size.
4. Hide control panel.
5. Define X variable.
6. Define Y variable.
7. Add bar element.
8. Set bar style to packed.
9. Assign legend position.
10. Display graph.

Example 886

Summary: Creates three variability charts with nested factors using Graph Builder, featuring different bar styles and summary statistics.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 528, 434 ),
    Show Control Panel( 0 ),
    Variables( X( :age ), Y( :height ), Y( :weight, Position( 1 ) ) ),
    Elements( Bar( X, Y( 1 ), Y( 2 ), Legend( 4 ), Bar Style( "Arrow" ), Summary Statistic( "Range" ), Label( "Label by Value" ) ) )
);
Graph Builder(
    Size( 528, 433 ),
    Show Control Panel( 0 ),
    Variables( X( :age ), Y( :height ), Y( :weight, Position( 1 ) ) ),
    Elements( Bar( X, Y( 1 ), Y( 2 ), Legend( 4 ), Bar Style( "Box Plot" ), Summary Statistic( "Range" ), Label( "Label by Value" ) ) )
);
Graph Builder(
    Size( 528, 433 ),
    Show Control Panel( 0 ),
    Variables( X( :age ), Y( :height ), Y( :weight, Position( 1 ) ) ),
    Elements( Bar( X, Y( 1 ), Y( 2 ), Legend( 4 ), Bar Style( "Stock" ), Summary Statistic( "Range" ), Label( "Label by Value" ) ) )
);

Code Explanation:

1. Open data_table data
2. Create first graph.
3. Set graph size.
4. Hide control panel.
5. Define X and Y variables.
6. Add bar element.
7. Set bar style to Arrow.
8. Use range summary statistic.
9. Label by value.
10. Repeat for Box Plot and Stock styles.

Example 887

Summary: Creates a variability chart with nested factors using Graph Builder, adding 10 rows at start and displaying standard deviation charts.

Code:

dt = Open("data_table.jmp");
dt << add rows( 10, At Start );
Graph Builder(
    Size( 500, 517 ),
    Show Legend( 0 ),
    Variables( Y( :height ), Overlay( :sex ) ),
    Elements( Bar( Y, Legend( 1 ), Summary Statistic( "Sum" ), Label( "Label by Percent of Total Values" ) ) )
);

Code Explanation:

1. Open data table.
2. Add 10 rows at start.
3. Create Graph Builder object.
4. Set graph size.
5. Hide legend.
6. Assign Y variable.
7. Assign overlay variable.
8. Add bar element.
9. Set summary statistic to sum.
10. Label by percent of total values.

Example 888

Summary: Creates a variability chart with nested factors using operator and part configurations, displaying standard deviation charts in Graph Builder.

Code:

Open("data_table.jmp");
Graph Builder( Size( 528, 370 ), Show Control Panel( 0 ), Variables( Y( :height ), Group X( :sex ), Color( :age ) ), Elements( Bar( Y ) ) );

Code Explanation:

1. Open data table;
2. Launch Graph Builder.
3. Set window size.
4. Hide control panel.
5. Assign variables: Y, Group X, Color.
6. Add bar element.

Example 889

Summary: Creates a variability chart with nested factors using Graph Builder, displaying standard deviation charts and utilizing operator and part configurations.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 522, 452 ),
    Show Control Panel( 0 ),
    Variables( X( :City ), Y( :"1972"n ), Y( :"1968"n, Position( 1 ) ) ),
    Elements( Bar( X, Y( 1 ), Y( 2 ), Legend( 24 ), Bar Style( "Range" ) ) )
);

Code Explanation:

1. Open data table.
2. Create graph builder.
3. Set window size.
4. Hide control panel.
5. Define X variable.
6. Define first Y variable.
7. Define second Y variable.
8. Add bar element.
9. Specify X axis.
10. Specify Y axes.

Example 890

Summary: Creates a variability chart with nested factors using Graph Builder, displaying standard deviation charts and labeling bars by value.

Code:

Open("data_table.jmp");
Graph Builder(
    Show Control Panel( 0 ),
    Variables( X( :age ), Y( :height ), Y( :weight, Position( 1 ) ), Overlay( :sex ) ),
    Elements( Bar( X, Y( 1 ), Y( 2 ), Legend( 5 ), Bar Style( "Range" ), Label( "Label by Value" ) ) )
);

Code Explanation:

1. Open data table;
2. Launch Graph Builder.
3. Hide control panel.
4. Set X variable to age.
5. Set Y variables to height and weight.
6. Position weight on Y-axis 1.
7. Overlay by sex.
8. Add bar element.
9. Set bar style to range.
10. Label bars by value.

Example 891

Summary: Creates two variability charts with nested factors using Graph Builder, displaying standard deviation charts and summarizing statistics for each category.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 432, 387 ),
    Show Control Panel( 0 ),
    Variables(
        X( :Species ),
        Y( :Sepal length ),
        Y( :Sepal width, Position( 1 ) ),
        Y( :Petal length, Position( 1 ) ),
        Y( :Petal width, Position( 1 ) ),
        Color( :Species )
    ),
    Elements( Bar( X, Y( 1 ), Y( 2 ), Y( 3 ), Y( 4 ), Legend( 3 ), Bar Style( "Range" ), Summary Statistic( "Sum" ) ) )
);
Graph Builder(
    Size( 432, 387 ),
    Show Control Panel( 0 ),
    Variables(
        X( :Species ),
        Y( :Sepal length ),
        Y( :Sepal width, Position( 1 ) ),
        Y( :Petal length, Position( 1 ) ),
        Y( :Petal width, Position( 1 ) ),
        Color( :Species )
    ),
    Elements( Bar( X, Y( 1 ), Y( 2 ), Y( 3 ), Y( 4 ), Legend( 3 ), Bar Style( "Interval" ), Summary Statistic( "Sum" ) ) )
);

Code Explanation:

1. Open data table;
2. Create first Graph Builder window.
3. Set window size to 432x387.
4. Hide control panel.
5. Define X variable as Species.
6. Define Y variables: Sepal length, Sepal width, Petal length, Petal width.
7. Set color variable as Species.
8. Add bar element with range style.
9. Summarize statistics for each category.
10. Create second Graph Builder window with interval style.

Example 892

Summary: Creates a bar chart with nested factors using Graph Builder, displaying standard deviation charts and color-coded by Fat.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 600, 580 ),
    Show Control Panel( 0 ),
    Include Missing Categories( 1 ),
    Variables( X( :Position ), Y( :Weight ), Group X( :Fat ), Group Y( :Bench ), Overlay( :Fat ), Color( :Fat ) ),
    Elements( Bar( X, Y, Legend( 52 ) ) )
);

Code Explanation:

1. Open data_table data
2. Create Graph Builder window.
3. Set window size to 600x580.
4. Hide control panel.
5. Include missing categories.
6. Assign variables: X=Position, Y=Weight.
7. Group X by Fat.
8. Group Y by Bench.
9. Overlay by Fat.
10. Color by Fat.
11. Add bar element with legend.

Example 893

Summary: Creates a variability chart with nested factors using Graph Builder, displaying standard deviation charts and enabling row labeling.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 524, 454 ),
    Show Control Panel( 0 ),
    Variables( X( :weight ), Y( :age ), Overlay( :age ) ),
    Elements( Bar( X, Y, Legend( 3 ), Label( "Label by Row" ) ) )
);

Code Explanation:

1. Open data table.
2. Launch Graph Builder.
3. Set window size.
4. Hide control panel.
5. Define X variable.
6. Define Y variable.
7. Set overlay variable.
8. Add bar element.
9. Configure legend position.
10. Enable row labeling.

Example 894

Summary: Creates a variability chart with nested factors using Graph Builder, configuring the X-axis scale and format for optimal visualization.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 524, 431 ),
    Show Control Panel( 0 ),
    Variables( X( :age ) ),
    Elements( Bar( X, Legend( 3 ), Bar Style( "Packed" ), Summary Statistic( "Sum" ) ) ),
    SendToReport(
        Dispatch( {}, "", ScaleBox, {Scale( "Log" ), Format( "Best", 12 ), Min( 0.01 ), Max( 21.42 ), Inc( 1 ), Minor Ticks( 1 )} )
    )
);

Code Explanation:

1. Open data table.
2. Create Graph Builder window.
3. Set window size.
4. Hide control panel.
5. Define X variable.
6. Add bar element.
7. Set legend position.
8. Choose packed bar style.
9. Use sum for summary statistic.
10. Configure X-axis scale and format.

Example 895

Summary: Creates a variability chart with nested factors using Graph Builder, displaying standard deviation charts and configuring bar elements for side-by-side comparison.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 525, 429 ),
    Show Control Panel( 0 ),
    Variables( X( :sex ), X( :age ), Y( :height ), Overlay( :age ) ),
    Elements( Position( 1, 1 ), Bar( X, Y, Legend( 8 ), Bar Style( "Side by side" ) ) ),
    Elements( Position( 2, 1 ), Bar( X, Y, Legend( 9 ) ) )
);

Code Explanation:

1. Open data table.
2. Create Graph Builder window.
3. Set window size.
4. Hide control panel.
5. Define X variables: sex, age.
6. Define Y variable: height.
7. Set overlay variable: age.
8. Add first bar element.
9. Position first bar element.
10. Add second bar element.

Example 896

Summary: Creates a variability chart with nested factors using Graph Builder, displaying standard deviation charts and customizing legend fill color.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 534, 448 ),
    Show Control Panel( 0 ),
    Variables( X( :sex ), Y( :height ) ),
    Elements( Bar( X, Y, Legend( 4 ), Bar Style( "Float" ), Error Bars( "Standard Error" ) ) )
);
Graph Builder(
    Size( 534, 448 ),
    Show Control Panel( 0 ),
    Variables( X( :sex ), Y( :height ) ),
    Elements( Bar( X, Y, Legend( 4 ), Error Interval( "Standard Error" ) ) ),
    SendToReport( Dispatch( {}, "400", ScaleBox, {Legend Model( 4, Properties( 0, {Fill Color( 30 )}, Item ID( "Mean", 1 ) ) )} ) )
);

Code Explanation:

1. Open data table;
2. Create first Graph Builder window.
3. Set window size.
4. Hide control panel.
5. Assign variables for graph.
6. Add bar element to graph.
7. Configure bar style and error bars.
8. Create second Graph Builder window.
9. Set window size.
10. Hide control panel.
11. Assign variables for graph.
12. Add bar element to graph.
13. Configure error interval.
14. Customize legend fill color.

Example 897

Summary: Creates two graphs, a bar chart and a histogram, to visualize the relationship between sex and age using Graph Builder.

Code:

Open("data_table.jmp");
Graph Builder( Show Control Panel( 0 ), Variables( X( :sex ), Y( :age ) ), Elements( Bar( X, Y, Legend( 8 ) ) ) );
Graph Builder( Show Control Panel( 0 ), Variables( X( :sex ), Y( :age ) ), Elements( Histogram( X, Y, Legend( 9 ) ) ) );

Code Explanation:

1. Open data_table data
2. Create graph builder.
3. Hide control panel.
4. Set X variable to sex.
5. Set Y variable to age.
6. Add bar element.
7. Enable legend for bars.
8. Create another graph builder.
9. Hide control panel.
10. Add histogram element.

Example 898

Summary: Creates a variability chart with nested factors using Graph Builder, displaying standard deviation charts and adjusting histogram settings.

Code:

Open("data_table.jmp");
Graph Builder( Show Control Panel( 0 ), Variables( X( :sex ), Y( :age ) ), Elements( Bar( X, Y, Legend( 8 ) ) ) );
Graph Builder( Show Control Panel( 0 ), Variables( X( :sex ), Y( :age ) ), Elements( Histogram( X, Y, Legend( 9 ) ) ) );
Graph Builder(
    Show Control Panel( 0 ),
    Variables( X( :sex ), Y( :age ) ),
    Elements( Histogram( X, Y, Legend( 9 ), Response Axis( "X" ) ) )
);

Code Explanation:

1. Open data table;
2. Create bar graph.
3. Set X variable to sex.
4. Set Y variable to age.
5. Add legend to bar graph.
6. Create histogram graph.
7. Set X variable to sex.
8. Set Y variable to age.
9. Add legend to histogram.
10. Adjust histogram to show response on X axis.

Example 899

Summary: Creates a variability chart with nested factors using Graph Builder, assigning age to the X-axis and height to the Y-axis, while coloring bars by age.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 726, 448 ),
    Show Control Panel( 0 ),
    Variables( X( :age ), Y( :height ), Color( :age ) ),
    Elements( Bar( X, Y, Legend( 5 ) ) ),
    SendToReport(
        Dispatch( {}, "400", ScaleBox, {Legend Model( 5, Properties( 4, {Fill Color( 9 )}, Item ID( "16", 1 ) ) )} ),
        Dispatch( {}, "Graph Builder", FrameBox,
            Add Text Annotation(
                Text( "Individual Bar Color
" ),
                Fixed Size( 1 ),
                Text Box( {398, 175, 620, 208} ),
                Background Color( "Light BlueCyan" ),
                Font( "Segoe UI", 16, "Plain" )
            )
        )
    )
);

Code Explanation:

1. Open data_table data
2. Create Graph Builder window.
3. Set size to 726x448.
4. Hide control panel.
5. Assign age to X-axis.
6. Assign height to Y-axis.
7. Color bars by age.
8. Add bar element.
9. Customize legend fill color.
10. Add text annotation for title.

Example 900

Summary: Creates a bar chart with nested factors using Graph Builder, displaying standard deviation charts and applying a random fill pattern.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 522, 450 ),
    Show Control Panel( 0 ),
    Variables( X( :Species ), Y( :Petal length ), Color( :Petal width ) ),
    Elements( Bar( X, Y, Legend( 13 ) ) ),
    SendToReport( Dispatch( {}, "Graph Builder", FrameBox, {DispatchSeg( BarSeg( 1 ), {Fill Pattern( "random" )} )} ) )
);

Code Explanation:

1. Open data table;
2. Create Graph Builder.
3. Set size to 522x450.
4. Hide control panel.
5. Set X to Species.
6. Set Y to Petal length.
7. Set Color to Petal width.
8. Add bar element.
9. Enable legend.
10. Apply random fill pattern.

Example 901

Summary: Creates a variability chart with nested factors using operator and part configurations, displaying standard deviation charts in Graph Builder.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 652, 259 ),
    Show Control Panel( 0 ),
    Variables( X( :sex ), Y( :height ), Frequency( :age ) ),
    Elements( Bar( X, Y, Legend( 14 ) ) ),
    SendToReport(
        Dispatch( {}, "Graph Builder", FrameBox,
            Add Pin Annotation(
                Seg( BarSeg( 1 ) ),
                Index( {0, 0} ),
                Index Row( {0, 0} ),
                UniqueID( 0 ),
                FoundPt( {159, 121} ),
                Origin( {0.171328671328671, 46.6666666666667} ),
                RightOfCenter( 0 ),
                Tag Line( 1 )
            )
        )
    )
);

Code Explanation:

1. Open data table.
2. Create Graph Builder window.
3. Set graph size.
4. Hide control panel.
5. Define X, Y, and frequency variables.
6. Add bar element.
7. Send report to Graph Builder.
8. Dispatch to Graph Builder frame.
9. Add pin annotation.
10. Configure pin annotation settings.

Example 902

Summary: Creates a variability chart with nested factors using operator and part configurations, displaying standard deviation charts in Graph Builder.

Code:

Names Default To Here( 1 );
Open("data_table.jmp");
Graph Builder(
    Size( 534, 486 ),
    Show Control Panel( 0 ),
    Variables( X( :Cut ), Y( :Price ), Group X( :Report ), Color( :Table ) ),
    Elements( Bar( X, Y, Legend( 4 ), Error Interval( "Interquartile Range" ) ) )
);

Code Explanation:

1. Set default names.
2. Open data table;
3. Create Graph Builder.
4. Set size 534x486.
5. Hide control panel.
6. Define X variable: Cut.
7. Define Y variable: Price.
8. Define Group X variable: Report.
9. Define Color variable: Table.
10. Add bar element with error interval.

Example 903

Summary: Creates a bar chart with nested factors using Graph Builder, displaying standard deviation charts and labeling bars by value.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 525, 437 ),
    Show Control Panel( 0 ),
    Variables( X( :name ), Y( :height ) ),
    Elements( Bar( X, Y, Legend( 4 ), Label( "Label by Value" ) ) )
);

Code Explanation:

1. Open data table;
2. Create Graph Builder window.
3. Set window size.
4. Hide control panel.
5. Define X variable.
6. Define Y variable.
7. Add bar element.
8. Label bars by value.
9. Display graph.

Example 904

Summary: Creates a variability chart with nested factors using operator and part configurations, displaying standard deviation charts.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 525, 437 ),
    Show Control Panel( 0 ),
    Variables( X( :name ), Y( :height ) ),
    Elements( Bar( X, Y, Legend( 4 ), Label( "Label by Value" ) ) )
);
Graph Builder(
    Size( 525, 437 ),
    Show Control Panel( 0 ),
    Variables( X( :name ), Y( :height ) ),
    Elements( Bar( X, Y, Legend( 4 ), Label( "Label by Value" ) ) ),
    SendToReport( Dispatch( {}, "height", ScaleBox, {Min( 76 ), Max( 0 )} ) )
);

Code Explanation:

1. Open data table.
2. Create first Graph Builder.
3. Set graph size.
4. Hide control panel.
5. Assign variables X and Y.
6. Add bar element.
7. Label bars by value.
8. Create second Graph Builder.
9. Adjust Y-axis scale.
10. Close script.

Example 905

Summary: Creates a variability chart with nested factors using Graph Builder, displaying standard deviation charts and labeling bars by percent.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 522, 448 ),
    Show Control Panel( 0 ),
    Variables( X( :age ), Y( :height ) ),
    Elements( Bar( X, Y, Legend( 1 ), Bar Style( "Packed" ), Label( "Label by Percent of Total Values" ) ) )
);
Graph Builder( Variables( X( :age ), Y( :height ) ), Elements( Bar( X, Y, Label( "Label by Percent of Total Values" ) ) ) );
Graph Builder(
    Size( 522, 448 ),
    Show Control Panel( 0 ),
    Variables( X( :age ), Y( :height ) ),
    Elements( Bar( X, Y, Legend( 1 ), Summary Statistic( "N" ), Label( "Label by Percent of Total Values" ) ) )
);

Code Explanation:

1. Open data table.
2. Create graph builder window.
3. Set window size.
4. Hide control panel.
5. Assign variables X and Y.
6. Add bar element.
7. Label bars by percent.
8. Create another graph builder.
9. Assign variables X and Y.
10. Add bar element with summary statistic N.

Example 906

Summary: Creates a graph builder with nested factors using operator and part configurations, displaying standard deviation charts.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 545, 586 ),
    Show Control Panel( 0 ),
    Variables( X( :Type ), Y( :Worldwide $ ), Overlay( :Rating ) ),
    Elements( Bar( X, Y, Legend( 7 ), Bar Style( "Interval" ) ) )
);

Code Explanation:

1. Open data table;
2. Launch Graph Builder.
3. Set window size.
4. Hide control panel.
5. Define X variable: Type.
6. Define Y variable: Worldwide $.
7. Define overlay variable: Rating.
8. Add bar element.
9. Set bar style to interval.
10. Display graph.

Example 907

Summary: Creates a variability chart with nested factors using operator and part configurations, displaying standard deviation charts.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 526, 388 ),
    Show Control Panel( 0 ),
    Variables( X( :Shift ), Y( :Abrasion ), Overlay( :Shift ) ),
    Elements( Bar( X, Y, Legend( 4 ), Error Interval( "Range" ) ) )
);

Code Explanation:

1. Open data table;
2. Launch Graph Builder.
3. Set window size.
4. Hide control panel.
5. Assign variables to axes.
6. Overlay by Shift variable.
7. Add bar element.
8. Configure legend position.
9. Add error interval.
10. Display graph.

Example 908

Summary: Creates two variability charts with nested factors using Graph Builder, displaying standard deviation charts and configuring color and overlay settings.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 526, 388 ),
    Show Control Panel( 0 ),
    Variables( X( :Shift ), Y( :Abrasion ), Overlay( :Shift ) ),
    Elements( Bar( X, Y, Legend( 4 ), Error Interval( "Range" ) ) )
);
Graph Builder(
    Size( 526, 388 ),
    Show Control Panel( 0 ),
    Variables( X( :Shift ), Y( :Abrasion ), Color( :Shift ) ),
    Elements( Bar( X, Y, Legend( 4 ), Error Interval( "Range" ) ) )
);

Code Explanation:

1. Open data table;
2. Create first graph builder window.
3. Set window size.
4. Hide control panel.
5. Define variables: X, Y, Overlay.
6. Add bar element with error interval.
7. Create second graph builder window.
8. Set window size.
9. Hide control panel.
10. Define variables: X, Y, Color.

Example 909

Summary: Creates a variability chart with nested factors using operator and part configurations, displaying standard deviation charts in JMP.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 528, 451 ),
    Show Control Panel( 0 ),
    Variables( X( :Position ), Y( :Speed ), Overlay( :Weight ), Color( :Fat ) ),
    Elements( Bar( X, Y, Legend( 18 ), Error Interval( "Range" ) ) ),
    Local Data Filter(
        Width( 178 ),
        Inverse( 1 ),
        Add Filter(
            columns( :Weight, :Position ),
            Where( :Weight >= 157 & :Weight <= 298 ),
            Where( :Position == {"fb", "ib"} ),
            Display( :Weight, Size( 166, 20 ), Height( 50 ) ),
            Display( :Position, Size( 172, 204 ), Height( 204 ) )
        )
    )
);

Code Explanation:

1. Open data table.
2. Launch Graph Builder.
3. Set window size.
4. Hide control panel.
5. Define variables for axes.
6. Add bar element.
7. Include error interval.
8. Enable local data filter.
9. Set filter width.
10. Define filter conditions.

Example 910

Summary: Creates a variability chart with nested factors using Graph Builder, displaying standard deviation charts and configuring bar style to interval.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 525, 443 ),
    Show Control Panel( 0 ),
    Variables( X( :weight ), Y( :height ), Overlay( :sex ), Color( :age ) ),
    Elements( Bar( X, Y, Legend( 8 ), Bar Style( "Interval" ), Summary Statistic( "Median" ) ) )
);

Code Explanation:

1. Open data table;
2. Launch Graph Builder.
3. Set window size.
4. Hide control panel.
5. Define X variable: weight.
6. Define Y variable: height.
7. Define overlay variable: sex.
8. Define color variable: age.
9. Add bar element.
10. Set bar style to interval.
11. Use median for summary statistic.

Example 911

Summary: Creates four Graph Builder windows to visualize nested factors using operator and part configurations, displaying standard deviation charts for cumulative percent, percent of factor, percent of grand total, and median absolute deviation.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 560, 437 ),
    Show Control Panel( 0 ),
    Variables( X( :age ), Y( :height ) ),
    Elements( Bar( X, Y, Legend( 3 ), Summary Statistic( "Cumulative Percent" ), Label( "Label by Value" ) ) )
);
Graph Builder(
    Size( 560, 437 ),
    Show Control Panel( 0 ),
    Variables( X( :age ), Y( :height ), Overlay( :sex ) ),
    Elements( Bar( X, Y, Legend( 3 ), Summary Statistic( "% of Factor" ), Label( "Label by Value" ) ) )
);
Graph Builder(
    Size( 560, 437 ),
    Show Control Panel( 0 ),
    Variables( X( :age ), Y( :height ), Overlay( :sex ) ),
    Elements( Bar( X, Y, Legend( 3 ), Summary Statistic( "% of Grand Total" ), Label( "Label by Value" ) ) )
);
Graph Builder(
    Size( 551, 437 ),
    Show Control Panel( 0 ),
    Variables( X( :age ), Y( :height ), Overlay( :sex ) ),
    Elements( Bar( X, Y, Legend( 3 ), Summary Statistic( "Median Absolute Deviation" ), Label( "Label by Value" ) ) )
);

Code Explanation:

1. Open data table;
2. Create first Graph Builder window.
3. Set size to 560x437.
4. Hide control panel.
5. Assign age to X, height to Y.
6. Add bar element with cumulative percent summary.
7. Label bars by value.
8. Create second Graph Builder window.
9. Set size to 560x437.
10. Hide control panel.
11. Assign age to X, height to Y, sex to overlay.
12. Add bar element with percent of factor summary.
13. Label bars by value.
14. Create third Graph Builder window.
15. Set size to 560x437.
16. Hide control panel.
17. Assign age to X, height to Y, sex to overlay.
18. Add bar element with percent of grand total summary.
19. Label bars by value.
20. Create fourth Graph Builder window.
21. Set size to 551x437.
22. Hide control panel.
23. Assign age to X, height to Y, sex to overlay.
24. Add bar element with median absolute deviation summary.
25. Label bars by value.

Example 912

Summary: Creates a variability chart with nested factors using Graph Builder, displaying standard deviation charts and customizing legend properties.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 522, 448 ),
    Show Control Panel( 0 ),
    Variables( X( :age ), Y( :height ), Overlay( :sex ) ),
    Elements( Bar( X, Y, Legend( 11 ), Error Interval( "Range" ) ) ),
    SendToReport( Dispatch( {}, "400", ScaleBox, {Legend Model( 11, Properties( 0, {Fill Color( 41 )}, Item ID( "F", 1 ) ) )} ) )
);

Code Explanation:

1. Open data table;
2. Launch Graph Builder.
3. Set graph size.
4. Hide control panel.
5. Define X, Y, and overlay variables.
6. Add bar element with error bars.
7. Send report dispatch.
8. Customize legend properties.
9. Set fill color for legend.
10. Assign item ID to legend.

Example 913

Summary: Creates three variability charts with nested factors using Graph Builder, displaying standard deviation charts for different bar styles.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 626, 430 ),
    Show Control Panel( 0 ),
    Variables( X( :age ), Y( :height ), Overlay( :weight ) ),
    Elements( Bar( X, Y, Legend( 5 ), Bar Style( "Single" ), Error Interval( "Standard Deviation" ) ) )
);
Graph Builder(
    Size( 626, 430 ),
    Show Control Panel( 0 ),
    Variables( X( :age ), Y( :height ), Overlay( :weight ) ),
    Elements( Bar( X, Y, Legend( 5 ), Bar Style( "Needle" ), Error Interval( "Standard Deviation" ) ) )
);
Graph Builder(
    Size( 626, 430 ),
    Show Control Panel( 0 ),
    Variables( X( :age ), Y( :height ), Overlay( :weight ) ),
    Elements( Bar( X, Y, Legend( 5 ), Bar Style( "Float" ), Error Interval( "Standard Deviation" ) ) )
);

Code Explanation:

1. Open data table.
2. Create first Graph Builder window.
3. Set window size to 626x430.
4. Hide control panel.
5. Define variables: X=age, Y=height, Overlay=weight.
6. Add single bar element with error interval.
7. Create second Graph Builder window.
8. Set window size to 626x430.
9. Hide control panel.
10. Define variables: X=age, Y=height, Overlay=weight.
11. Add needle bar element with error interval.
12. Create third Graph Builder window.
13. Set window size to 626x430.
14. Hide control panel.
15. Define variables: X=age, Y=height, Overlay=weight.
16. Add float bar element with error interval.

Example 914

Summary: Creates a variability chart with nested factors using Graph Builder, displaying standard deviation charts and labeling by value.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 673, 377 ),
    Show Control Panel( 0 ),
    Show Legend( 0 ),
    Variables( X( :sex ), Y( :height ), Overlay( :weight ) ),
    Elements( Bar( X, Y, Legend( 1 ), Error Interval( "Range" ), Label( "Label by Value" ), Overlap( "None" ) ) )
);

Code Explanation:

1. Open data_table data
2. Create Graph Builder.
3. Set window size.
4. Hide control panel.
5. Hide legend.
6. Assign variables: X=sex, Y=height, Overlay=weight.
7. Add bar element.
8. Set error interval to range.
9. Label by value.
10. Set overlap to none.

Example 915

Summary: Creates a variability chart with nested factors using operator and part configurations, displaying standard deviation charts in JMP.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 522, 448 ),
    Show Control Panel( 0 ),
    Variables( X( :sex ), Y( :height ), Overlay( :age ) ),
    Elements( Bar( X, Y, Legend( 4 ), Bar Style( "Stacked" ), Label( "Label by Value" ) ) ),
    SendToReport(
        Dispatch( {}, "Graph Builder", FrameBox,
            {DispatchSeg(
                BarSeg( 1 ),
                Set Label Offset(
                    {3, 0.419739696312364, 176.933173529412},
                    {4, -0.39587852494577, 261.505004901961},
                    {5, 0.528199566160521, 381.686028431373},
                    {6, 0.484815618221258, 54.5265754901961},
                    {7, 1.38286334056399, 149.113492156863},
                    {10, 0.554229934924078, 293.775835294118}
                )
            )}
        )
    )
);
Graph Builder(
    Size( 772, 465 ),
    Show Control Panel( 0 ),
    Variables( X( :sex ), Color( :sex ) ),
    Elements( Bar( X, Legend( 5 ), Label( "Label by Row" ) ) ),
    SendToReport(
        Dispatch( {}, "Graph Builder", FrameBox,
            {DispatchSeg(
                BarSeg( 1 ),
                Set Label Offset( {0, 0.419537040214048, 23.6156587110236, 18}, {1, 0.633129624373121, 3.64794728056462, 22} )
            )}
        )
    )
);

Code Explanation:

1. Open data table;
2. Create Graph Builder window.
3. Set graph size.
4. Hide control panel.
5. Assign variables: X(sex), Y(height), Overlay(age).
6. Add stacked bar element.
7. Label bars by value.
8. Adjust label offsets for segments.
9. Create second Graph Builder window.
10. Set graph size.
11. Hide control panel.
12. Assign variables: X(sex), Color(sex).
13. Add bar element.
14. Label bars by row.
15. Adjust label offsets for segments.

Example 916

Summary: Creates a variability chart with nested factors using operator and part configurations, displaying standard deviation charts.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 918, 378 ),
    Show Control Panel( 0 ),
    Variables( X( :age ), Y( :height ), Overlay( :weight ) ),
    Elements( Bar( X, Y, Legend( 5 ), Summary Statistic( "Max" ), Error Interval( "Range" ), Label( "Label by Value" ) ) )
);

Code Explanation:

1. Open data table;
2. Launch Graph Builder.
3. Set window size.
4. Hide control panel.
5. Assign variables.
6. Add bar element.
7. Set summary statistic to max.
8. Enable range error interval.
9. Label bars by value.
10. Display graph.

Example 917

Summary: Creates three stacked bar graphs with nested factors, displaying percentage statistics for factor, total, and grand total, using Graph Builder in JMP.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 522, 448 ),
    Show Control Panel( 0 ),
    Variables( X( :age ), Y( :height ), Overlay( :sex ) ),
    Elements( Bar( X, Y, Legend( 4 ), Bar Style( "Stacked" ), Summary Statistic( "% of Factor" ), Label( "Label by Value" ) ) )
);
Graph Builder(
    Size( 522, 448 ),
    Show Control Panel( 0 ),
    Variables( X( :age ), Y( :height ), Overlay( :sex ) ),
    Elements( Bar( X, Y, Legend( 4 ), Bar Style( "Stacked" ), Summary Statistic( "% of Total" ), Label( "Label by Value" ) ) )
);
Graph Builder(
    Size( 522, 448 ),
    Show Control Panel( 0 ),
    Variables( X( :age ), Y( :height ), Overlay( :sex ) ),
    Elements( Bar( X, Y, Legend( 4 ), Bar Style( "Stacked" ), Summary Statistic( "% of Grand Total" ), Label( "Label by Value" ) ) )
);

Code Explanation:

1. Open data table.
2. Create first bar graph.
3. Set graph size.
4. Hide control panel.
5. Define X, Y, and overlay variables.
6. Add stacked bar element.
7. Use percent of factor statistic.
8. Label bars by value.
9. Create second bar graph.
10. Use percent of total statistic.
11. Create third bar graph.
12. Use percent of grand total statistic.

Example 918

Summary: Creates a variability chart with nested factors using Graph Builder, configuring bar style and labeling options.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 530, 431 ),
    Show Control Panel( 0 ),
    Variables( X( :age ), Y( :height ) ),
    Elements(
        Bar(
            X,
            Y,
            Legend( 3 ),
            Bar Style( "Packed" ),
            Packed Labeling( 1 ),
            Packed Primary Labels( "On axis" ),
            Summary Statistic( "Sum" ),
            Label( "Label by Value" )
        )
    ),
    SendToReport( Dispatch( {}, "", ScaleBox, {Format( "Best", 12 )} ) )
);

Code Explanation:

1. Open data table;
2. Launch Graph Builder.
3. Set graph size.
4. Hide control panel.
5. Assign variables X and Y.
6. Add bar element.
7. Configure bar style.
8. Enable packed labeling.
9. Set primary labels on axis.
10. Use sum for summary statistic.

Example 919

Summary: Creates two Graph Builder windows to visualize the relationship between sex, height, and weight using bar elements with float style and standard error bars.

Code:

Open("data_table.jmp");
Graph Builder(
    Show Control Panel( 0 ),
    Variables( X( :sex ), Y( :height ) ),
    Elements( Bar( X, Y, Bar Style( "Float" ), Error Bars( "Standard Error" ) ) )
);
Graph Builder(
    Show Control Panel( 0 ),
    Variables( X( :sex ), Y( :height ), Y( :weight, Position( 1 ) ) ),
    Elements( Bar( X, Y( 1 ), Y( 2 ), Bar Style( "Float" ), Error Bars( "Standard Error" ) ) )
);

Code Explanation:

1. Open data table.
2. Create first Graph Builder window.
3. Hide control panel.
4. Set X variable to sex.
5. Set Y variable to height.
6. Add bar element with float style.
7. Add error bars for standard error.
8. Create second Graph Builder window.
9. Hide control panel.
10. Set X variable to sex.
11. Set Y variables to height and weight.
12. Add bar element with float style.
13. Add error bars for standard error.

Example 920

Summary: Creates a variability chart with nested factors using Graph Builder, displaying standard deviation charts and adjusting label offsets for each bar segment.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 522, 448 ),
    Show Control Panel( 0 ),
    Variables( X( :age ), Y( :height ) ),
    Elements( Bar( X, Y, Legend( 3 ), Summary Statistic( "Sum" ), Label( "Label by Value" ) ) ),
    SendToReport(
        Dispatch( {}, "Graph Builder", FrameBox,
            {DispatchSeg(
                BarSeg( 1 ),
                {Set Label Offset( {0, -0.044468546637744, 721.308823529412} ), Set Label Offset(
                    {1, 0.853579175704989, 636.971176470588}
                ), Set Label Offset( {2, 3.01409978308026, 805.646470588235} ), Set Label Offset( {3, 3.63882863340564, 612.557647058823} ),
                Set Label Offset( {4, 3.92516268980477, 357.325294117647} ), Set Label Offset( {5, 5.03145336225597, 419.468823529412} )}
            )}
        )
    )
);

Code Explanation:

1. Open data_table data
2. Create Graph Builder window.
3. Set window size to 522x448.
4. Hide control panel.
5. Set X variable to age.
6. Set Y variable to height.
7. Add bar element.
8. Set summary statistic to Sum.
9. Label bars by value.
10. Adjust label offsets for each bar segment.

Example 921

Summary: Creates a variability chart with nested factors using operator and part configurations, displaying standard deviation charts within Graph Builder.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 524, 270 ),
    Show Control Panel( 0 ),
    Show Legend( 0 ),
    Variables( Y( :Net Cost ), Group X( :Class of Service ), Color( :Departure Day of Week ) ),
    Elements( Bar( Y, Legend( 23 ) ) ),
    Local Data Filter(
        Mode( Include( 0 ) ),
        Inverse( 1 ),
        Add Filter(
            columns( :Airline ),
            Where( :Airline == {"Carrier 1", "Carrier 2"} ),
            Display( :Airline, Size( 181, 68 ), List Display )
        )
    ),
    SendToReport( Dispatch( {}, "400", LegendBox, {Set Title( "" )} ) )
);

Code Explanation:

1. Open data table;
2. Create Graph Builder window.
3. Set window size 524x270.
4. Hide control panel.
5. Hide legend.
6. Define variables: Net Cost (Y), Class of Service (Group X), Departure Day of Week (Color).
7. Add bar element with legend.
8. Enable local data filter.
9. Set filter mode to include 0.
10. Apply inverse filter.

Example 922

Summary: Creates a variability chart with nested factors using Graph Builder, displaying standard deviation charts and error bars.

Code:

Open("data_table.jmp");
Graph Builder(
    Show Control Panel( 0 ),
    Variables( Y( :height ), Overlay( :sex ) ),
    Elements( Bar( Y, Legend( 4 ), Error Bars( "Two-way Interval" ) ) )
);

Code Explanation:

1. Open data table;
2. Launch Graph Builder.
3. Hide control panel.
4. Set Y variable to height.
5. Overlay by sex variable.
6. Add bar element.
7. Enable legend for bars.
8. Display two-way error bars.

Example 923

Summary: Creates a variability chart with nested factors using operator and part configurations, displaying standard deviation charts.

Code:

Open("data_table.jmp");
Graph Builder( Size( 534, 456 ), Show Control Panel( 0 ), Variables( X( :MCB ) ), Elements( Histogram( X, Legend( 3 ) ) ) );

Code Explanation:

1. Open data_table data
2. Create Graph Builder window.
3. Set size to 534x456.
4. Hide control panel.
5. Set X variable to MCB.
6. Add histogram element.
7. Assign legend to position 3.

Example 924

Summary: Creates a variability chart with nested factors using Graph Builder, displaying standard deviation charts and customizing legend colors.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 450, 400 ),
    Show Control Panel( 0 ),
    Variables( X( :age ), Y( :height ), Y( :weight, Position( 1 ), Side( "Right" ) ), Group X( :sex ), Overlay( :sex ) ),
    Elements(
        Line( X, Y( 1 ), Legend( 4 ), Row order( 0 ), Summary Statistic( "Max" ) ),
        Bar( X, Y( 2 ), Legend( 3 ), Bar Style( "Side by side" ), Summary Statistic( "% of Total" ) )
    ),
    SendToReport(
        Dispatch( {}, "400", ScaleBox,
            {Legend Model( 4, Properties( 0, {Line Color( 19 )} ), Properties( 1, {Line Color( 0 )} ) ),
            Legend Model( 3, Properties( 0, {Transparency( 0.7 )} ), Properties( 1, {Fill Color( 76 )} ) )}
        )
    )
);

Code Explanation:

1. Open data table.
2. Launch Graph Builder.
3. Set graph size.
4. Hide control panel.
5. Define variables for axes.
6. Add line element for height.
7. Add bar element for weight.
8. Customize line legend colors.
9. Customize bar fill and transparency.
10. Display the report.

Example 925

Summary: Creates a variability chart with nested factors using Graph Builder, displaying standard deviation charts and configuring legend transparency.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 450, 400 ),
    Show Control Panel( 0 ),
    Variables(
        X( :sex ),
        Y( :weight, Side( "Right" ) ),
        Y( :height, Position( 1 ), Side( "Right" ) ),
        Y( :age, Position( 1 ) ),
        Overlay( :age )
    ),
    Elements(
        Bar( X, Y( 3 ), Legend( 25 ), Bar Style( "Side by side" ), Summary Statistic( "N" ) ),
        Line( X, Y( 1 ), Y( 2 ), Legend( 26 ), Row order( 0 ), Summary Statistic( "Mean" ) )
    ),
    SendToReport(
        Dispatch( {}, "400", ScaleBox,
            {Legend Model(
                25,
                Properties( 0, {Transparency( 0.5 )} ),
                Properties( 1, {Transparency( 0.5 )} ),
                Properties( 2, {Transparency( 0.5 )} ),
                Properties( 3, {Transparency( 0.5 )} ),
                Properties( 4, {Transparency( 0.5 )} ),
                Properties( 5, {Transparency( 0.5 )} )
            )}
        )
    )
);

Code Explanation:

1. Open data table.
2. Launch Graph Builder.
3. Set graph size.
4. Hide control panel.
5. Define X variable.
6. Define right-side Y variables.
7. Define left-side Y variable.
8. Overlay by age.
9. Add bar element.
10. Add line element.

Example 926

Summary: Creates a variability chart with nested factors using operator and part configurations, displaying standard deviation charts in Graph Builder.

Code:

dt = Open("data_table.jmp");
Graph Builder(
    Size( 527, 418 ),
    Show Control Panel( 0 ),
    Variables( Y( :height ), Y( :weight, Position( 1 ) ) ),
    Elements( Smoother( Y( 1 ), Y( 2 ) ), Points( Y( 1 ), Y( 2 ), Legend( 20 ), Summary Statistic( "Median" ), Error Bars( "Range" ) ) )
);

Code Explanation:

1. Open data table.
2. Launch Graph Builder.
3. Set window size.
4. Hide control panel.
5. Assign variables to axes.
6. Add smoother element.
7. Add points element.
8. Configure legend.
9. Use median summary statistic.
10. Display range error bars.

Example 927

Summary: Creates two variability charts with nested factors using Graph Builder, displaying standard deviation charts and applying customized formatting options.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 484, 457 ),
    Show Control Panel( 0 ),
    Variables( X( :Status ), Y( :Hours ) ),
    Elements( Bar( X, Y, Legend( 5 ), Bar Style( "Packed" ), Packed Coloring( "Faded bar color" ) ) ),
    SendToReport( Dispatch( {}, "Hours", ScaleBox, {Reversed Scale} ) )
);
Open("data_table.jmp");
Graph Builder(
    Size( 734, 540 ),
    Show Control Panel( 0 ),
    Show Legend( 0 ),
    Variables( X( :SAT Math ), Y( :Population ) ),
    Elements( Bar( X, Y, Legend( 20 ), Bar Style( "Packed" ) ) ),
    SendToReport(
        Dispatch( {}, "Population", ScaleBox,
            {Scale( "Log" ), Format( "Best", 12 ), Min( 100000 ), Max( 100800459.417857 ), Inc( 1 ), Minor Ticks( 1 )}
        )
    )
);

Code Explanation:

1. Open data table;
2. Create Graph Builder window.
3. Set window size.
4. Hide control panel.
5. Define X and Y variables.
6. Add packed bar element.
7. Apply faded bar coloring.
8. Reverse Y scale.
9. Open data table;
10. Create another Graph Builder window.

Example 928

Summary: Creates three variability charts with nested factors using Graph Builder, displaying standard deviation charts and configuring scale boxes for log and power scales.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 524, 431 ),
    Show Control Panel( 0 ),
    Variables( X( :age ) ),
    Elements( Bar( X, Legend( 3 ), Bar Style( "Packed" ), Summary Statistic( "Sum" ) ) ),
    SendToReport( Dispatch( {}, "", ScaleBox, {Format( "Best", 12 ), Reversed Scale} ) )
);
Graph Builder(
    Size( 524, 431 ),
    Show Control Panel( 0 ),
    Variables( X( :age ) ),
    Elements( Bar( X, Legend( 3 ), Bar Style( "Packed" ), Summary Statistic( "Sum" ) ) ),
    SendToReport(
        Dispatch( {}, "", ScaleBox, {Scale( "Log" ), Format( "Best", 12 ), Min( 0.01 ), Max( 21.42 ), Inc( 1 ), Minor Ticks( 1 )} )
    )
);
Graph Builder(
    Size( 524, 431 ),
    Show Control Panel( 0 ),
    Variables( X( :age ) ),
    Elements( Bar( X, Legend( 3 ), Bar Style( "Packed" ), Summary Statistic( "Sum" ) ) ),
    SendToReport( Dispatch( {}, "", ScaleBox, {Scale( "Power" ), Format( "Best", 12 ), Min( 0 ), Max( 21 ), Inc( 1 ), Minor Ticks( 1 )} ) )
);

Code Explanation:

1. Open data table;
2. Create first Graph Builder window.
3. Set window size.
4. Hide control panel.
5. Set X variable to age.
6. Add packed bar element.
7. Summarize data by sum.
8. Format scale box.
9. Reverse scale.
10. Create second Graph Builder window.
11. Set window size.
12. Hide control panel.
13. Set X variable to age.
14. Add packed bar element.
15. Summarize data by sum.
16. Format scale box.
17. Use log scale.
18. Set scale limits.
19. Create third Graph Builder window.
20. Set window size.
21. Hide control panel.
22. Set X variable to age.
23. Add packed bar element.
24. Summarize data by sum.
25. Format scale box.
26. Use power scale.

Example 929

Summary: Creates three variability charts with nested factors using different packed placement configurations in Graph Builder, displaying standard deviation charts for each configuration.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 628, 374 ),
    Show Control Panel( 0 ),
    Show Legend( 0 ),
    Show Title( 0 ),
    Variables( X( :sex ), X( :age, Position( 1 ) ), Y( :height ), Color( :age ) ),
    Elements(
        Bar( X( 1 ), X( 2 ), Y, Legend( 15 ), Bar Style( "Packed" ), Packed Placement( "Separate stack" ), Packed Coloring( "Bar color" ) )
    )
);
Graph Builder(
    Size( 628, 374 ),
    Show Control Panel( 0 ),
    Show Legend( 0 ),
    Show Title( 0 ),
    Variables( X( :sex ), X( :age, Position( 1 ) ), Y( :height ), Color( :age ) ),
    Elements(
        Bar( X( 1 ), X( 2 ), Y, Legend( 15 ), Bar Style( "Packed" ), Packed Placement( "Smallest stack" ), Packed Coloring( "Bar color" ) )
    )
);
Graph Builder(
    Size( 628, 374 ),
    Show Control Panel( 0 ),
    Show Legend( 0 ),
    Show Title( 0 ),
    Variables( X( :sex ), X( :age, Position( 1 ) ), Y( :height ), Color( :age ) ),
    Elements(
        Bar( X( 1 ), X( 2 ), Y, Legend( 15 ), Bar Style( "Packed" ), Packed Placement( "First stack" ), Packed Coloring( "Bar color" ) )
    )
);

Code Explanation:

1. Open data table;
2. Create first graph builder window.
3. Set graph size.
4. Hide control panel.
5. Hide legend.
6. Hide title.
7. Define variables: sex, age, height, age.
8. Add packed bar element.
9. Create second graph builder window.
10. Repeat steps 3-9 with different packed placement.
11. Create third graph builder window.
12. Repeat steps 3-9 with another packed placement.

Example 930

Summary: Creates a variability chart with nested factors using Graph Builder, displaying standard deviation charts and utilizing packed bar style.

Code:

Open("data_table.jmp");
Graph Builder(
    Show Control Panel( 0 ),
    Variables( X( :Cost ), Y( :Unique Event ) ),
    Elements( Bar( X, Y, Legend( 3 ), Bar Style( "Packed" ), Packed Primaries( 10 ) ) )
);

Code Explanation:

1. Open data table;
2. Launch Graph Builder.
3. Hide control panel.
4. Set X variable to Cost.
5. Set Y variable to Unique Event.
6. Add bar element.
7. Use packed bar style.
8. Set packed primaries to 10.

Example 931

Summary: Creates a variability chart with nested factors using operator and part configurations, displaying standard deviation charts in Graph Builder.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 706, 465 ),
    Show Control Panel( 0 ),
    Variables( X( :Domestic Gross ), Y( :Movie Name ) ),
    Elements( Bar( X, Y, Legend( 3 ), Bar Style( "Packed" ), Packed Primaries( 10 ), Packed Labeling( 0.578 ) ) ),
    SendToReport(
        Dispatch( {}, "Graph Builder", FrameBox, {DispatchSeg( BarSeg( 1 ), {Font( Font( "Brush Script MT" ), Style( "Italic" ) )} )} )
    )
);

Code Explanation:

1. Open data table;
2. Launch Graph Builder.
3. Set window size.
4. Hide control panel.
5. Assign variables to axes.
6. Create packed bar chart.
7. Customize bar style.
8. Adjust packed primaries.
9. Set packed labeling.
10. Change label font family.

Example 932

Summary: Creates a graph builder window with a points element, displaying standard deviation charts for nested factors using operator and part configurations.

Code:

dt = Open("data_table.jmp");
Graph Builder( Size( 487, 452 ), Show Control Panel( 0 ), Variables( X( :Event Date ) ), Elements( Points( X, Legend( 5 ) ) ) );

Code Explanation:

1. Open data table;
2. Create new graph builder window.
3. Set window size to 487x452.
4. Hide control panel.
5. Set X variable to Event Date.
6. Add points element to graph.
7. Assign legend to points.

Example 933

Summary: Creates a variability chart with nested factors using Graph Builder, displaying standard deviation charts and utilizing part configurations.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 406, 355 ),
    Show Control Panel( 0 ),
    Variables( X( :age ), Y( :height ), Y( :weight, Position( 1 ) ) ),
    Elements( Bar( X, Y( 1 ), Y( 2 ), Legend( 1 ), Bar Style( "Range" ) ) )
);

Code Explanation:

1. Open data table.
2. Launch Graph Builder.
3. Set window size.
4. Hide control panel.
5. Assign X variable.
6. Assign first Y variable.
7. Assign second Y variable.
8. Add bar element.
9. Specify X axis.
10. Specify Y axes.

Example 934

Summary: Creates a variability chart with nested factors using operator and part configurations, displaying standard deviation charts in Graph Builder.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 570, 650 ),
    Show Control Panel( 0 ),
    Variables( X( :proof on ctd ink ), Y( :ESA Voltage ), Y( :ESA Amperage, Position( 1 ) ), Color( :grain screened ) ),
    Elements( Bar( X, Y( 1 ), Y( 2 ), Legend( 6 ) ) )
);

Code Explanation:

1. Open data file.
2. Create graph builder window.
3. Set window size.
4. Hide control panel.
5. Define X variable.
6. Define first Y variable.
7. Define second Y variable.
8. Define color variable.
9. Add bar element.
10. Assign variables to bar.

Example 935

Summary: Creates a bar chart with nested factors using Graph Builder, displaying mean values and side-by-side bars.

Code:

Open("data_table.jmp");
Graph Builder(
    Show Control Panel( 0 ),
    Variables( X( :sex ), Frequency( :height ) ),
    Elements( Bar( X, Legend( 2 ), Bar Style( "Side by side" ), Summary Statistic( "Mean" ), Label( "Value" ) ) )
);

Code Explanation:

1. Open data table;
2. Launch Graph Builder.
3. Hide control panel.
4. Set X variable to sex.
5. Set frequency to height.
6. Add bar element.
7. Use legend position 2.
8. Set bar style to side by side.
9. Calculate mean summary statistic.
10. Label bars with values.

Example 936

Summary: Creates a variability chart with nested factors using Graph Builder, displaying standard deviation charts and side-by-side bars for mean values.

Code:

Open("data_table.jmp");
Graph Builder(
    Show Control Panel( 0 ),
    Variables( X( :sex ), Frequency( :height ) ),
    Elements( Bar( X, Legend( 2 ), Bar Style( "Side by side" ), Summary Statistic( "Mean" ), Label( "Value" ) ) )
);
Chart( Freq( :height ), X( :sex ), Y( N ), Label by Value, Show Labels, Bar Chart( 1 ) );

Code Explanation:

1. Open data table.
2. Create Graph Builder object.
3. Hide control panel.
4. Set X variable to sex.
5. Set frequency variable to height.
6. Add bar element.
7. Set legend to second position.
8. Set bar style to side by side.
9. Use mean for summary statistic.
10. Label bars with value.

Example 937

Summary: Creates a variability chart with nested factors using Graph Builder, displaying standard deviation charts and utilizing operator and part configurations.

Code:

Open("data_table.jmp");
Graph Builder( Size( 271, 260 ), Show Control Panel( 0 ), Variables( X( :age ), Y( :sex ) ), Elements( Bar( X, Y, Legend( 6 ) ) ) );

Code Explanation:

1. Open data table.
2. Launch Graph Builder.
3. Set window size.
4. Hide control panel.
5. Define X variable.
6. Define Y variable.
7. Add bar element.
8. Set legend position.

Example 938

Summary: Creates a variability chart with nested factors using operator and part configurations, displaying standard deviation charts in JMP.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 534, 382 ),
    Show Control Panel( 0 ),
    Include Missing Categories( 1 ),
    Variables( X( :Group ), Y( :Time Cycles ), Frequency( :Causes ) ),
    Elements( Bar( X, Y, Legend( 8 ), Summary Statistic( "N" ), Label( "Label by Value" ) ) )
);

Code Explanation:

1. Open data table;
2. Launch Graph Builder.
3. Set window size.
4. Hide control panel.
5. Include missing categories.
6. Define X variable.
7. Define Y variable.
8. Define frequency variable.
9. Add bar element.
10. Set summary statistic.

Example 939

Summary: Creates a graph builder with nested factors using operator and part configurations, displaying standard deviation charts.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 534, 404 ),
    Show Control Panel( 0 ),
    Include Missing Categories( 1 ),
    Variables( X( :storage 1 ), Y( :curds 1 ) ),
    Elements( Bar( X, Y, Legend( 5 ) ) )
);

Code Explanation:

1. Open data table;
2. Create Graph Builder object.
3. Set graph size.
4. Hide control panel.
5. Include missing categories.
6. Assign X variable.
7. Assign Y variable.
8. Add bar element.
9. Set legend position.
10. Display graph.

Example 940

Summary: Creates a graph builder with nested factors using operator and part configurations, displaying standard deviation charts.

Code:

Open("data_table.jmp");
obj = Graph Builder(
    Size( 458, 360 ),
    Show Control Panel( 0 ),
    Variables( X( :age ), X( :name, Position( 1 ) ), Y( :height ) ),
    Elements( Bar( X( 1 ), X( 2 ), Y, Legend( 20 ), Summary Statistic( "Sum" ) ) ),
    SendToReport(
        Dispatch( {}, "Graph Builder", OutlineBox, {Set Title( "Graph Builder - Axis labels should not be inside nested axis" )} )
    )
);

Code Explanation:

1. Open data table;
2. Create Graph Builder object.
3. Set graph size.
4. Hide control panel.
5. Define X and Y variables.
6. Add bar element.
7. Configure summary statistic.
8. Send report to Graph Builder.
9. Set title for the graph.
10. Display the graph.

Example 941

Summary: Creates a graph builder object with nested factors using operator and part configurations, displaying standard deviation charts.

Code:

Open("data_table.jmp");
obj = Graph Builder(
    Size( 458, 360 ),
    Show Control Panel( 0 ),
    Variables( X( :age ), X( :name, Position( 1 ) ), Y( :height ) ),
    Elements( Bar( X( 1 ), X( 2 ), Y, Legend( 20 ), Summary Statistic( "Sum" ) ) ),
    SendToReport(
        Dispatch( {}, "Graph Builder", OutlineBox, {Set Title( "Graph Builder - Axis labels should not be inside nested axis" )} )
    )
);
obj << set window size( 458, 300 );

Code Explanation:

1. Open data table;
2. Create Graph Builder object.
3. Set graph size.
4. Hide control panel.
5. Define X and Y variables.
6. Add bar element.
7. Configure summary statistic.
8. Set legend position.
9. Rename graph title.
10. Adjust window size.

Example 942

Summary: Creates a variability chart with nested factors using Graph Builder, displaying standard deviation charts and adjusting legend position.

Code:

dt = Open("data_table.jmp");
Graph Builder(
    Show Control Panel( 0 ),
    Variables(
        X( :age ),
        Y( :height ),
        Y( :weight, Position( 1 ) ),
        Y( Transform Column( "Avg[height,weight]", Formula( Mean( :height, :weight ) ) ), Position( 1 ) )
    ),
    Elements( Bar( X, Y( 1 ), Y( 2 ), Y( 3 ), Legend( 3 ), Bar Style( "Interval" ) ) ),
    SendToReport( Dispatch( {}, "400", LegendBox, {Legend Position( {3, [0, 1]} )} ) )
);

Code Explanation:

1. Open data table.
2. Create Graph Builder object.
3. Hide control panel.
4. Set X variable to age.
5. Set first Y variable to height.
6. Set second Y variable to weight.
7. Add transformed column for average.
8. Position transformed column first.
9. Add bar element with three Y variables.
10. Adjust legend position.

Example 943

Summary: Creates a variability chart with nested factors using Graph Builder, displaying standard deviation charts and sorting by mean.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 570, 465 ),
    Show Control Panel( 0 ),
    Variables(
        X( :Age ),
        Group Y( :Gender ),
        Group Y( :Rating Class, Order By( :Name( "Claim(Y/N)" ), Ascending, Order Statistic( "Mean" ) ) )
    ),
    Elements( Bar( X, Legend( 46 ) ) )
);

Code Explanation:

1. Open data table.
2. Create Graph Builder object.
3. Set window size.
4. Hide control panel.
5. Define X variable.
6. Define first Group Y variable.
7. Define second Group Y variable.
8. Sort second Group Y by mean.
9. Add bar element.
10. Set legend position.

Example 944

Summary: Creates a variability chart with nested factors using Graph Builder, displaying standard deviation charts and configuring legend settings.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 600, 340 ),
    Show Control Panel( 0 ),
    Variables( Y( :weight ), Group X( :sex ), Group X( :age ), Group X( :height ) ),
    Elements( Bar( Y, Legend( 20 ) ) )
);

Code Explanation:

1. Open data table;
2. Launch Graph Builder.
3. Set window size.
4. Hide control panel.
5. Define Y variable.
6. Define first Group X variable.
7. Define second Group X variable.
8. Define third Group X variable.
9. Add bar element.
10. Configure legend settings.

Example 945

Summary: Creates a Graph Builder window with nested factors, displaying line and bar elements, and adding text annotation.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 448, 387 ),
    Show Control Panel( 0 ),
    Variables( X( :age ), Y( :height ), Y( :weight ) ),
    Elements( Position( 1, 1 ), Line( X, Y, Legend( 1 ) ) ),
    Elements( Position( 1, 2 ), Bar( X, Y, Legend( 2 ) ) ),
    SendToReport(
        Dispatch( {}, "Graph Builder", FrameBox,
            Add Text Annotation( Text( "Annotate on Graph Builder" ), Text Box( {346, 109, 505, 132} ) )
        )
    )
);

Code Explanation:

1. Open data table;
2. Create Graph Builder window.
3. Set window size.
4. Hide control panel.
5. Assign variables to axes.
6. Add line element.
7. Add bar element.
8. Send report to Graph Builder.
9. Add text annotation.
10. Position text annotation.

Example 946

Summary: Creates a variability chart with nested factors using Graph Builder, displaying standard deviation charts and summarizing data by row.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 711, 448 ),
    Show Control Panel( 0 ),
    Variables( X( :Cycle Time ), Y( :Shrinkage ), Group X( :Pressure ), Group Y( :Moisture ) ),
    Elements( Bar( X, Y, Legend( 8 ), Summary Statistic( "Sum" ), Label( "Label by Row" ) ) )
);

Code Explanation:

1. Open data table.
2. Create Graph Builder.
3. Set graph size.
4. Hide control panel.
5. Define X variable.
6. Define Y variable.
7. Group X by Pressure.
8. Group Y by Moisture.
9. Add bar element.
10. Summarize data.

Example 947

Summary: Creates a variability chart with nested factors using Graph Builder, displaying standard deviation charts and labeling bars by value.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 447, 314 ),
    Show Control Panel( 0 ),
    Variables( X( :Code ), Y( :RefValue ), Overlay( :Code ), Color( :A ) ),
    Elements( Bar( X, Y, Legend( 11 ), Label( "Label by Value" ) ) )
);

Code Explanation:

1. Open data table;
2. Create Graph Builder window.
3. Set window size.
4. Hide control panel.
5. Define X variable.
6. Define Y variable.
7. Set overlay variable.
8. Set color variable.
9. Add bar element.
10. Label bars by value.

Example 948

Summary: Creates a stacked bar chart with label by value, using Graph Builder to visualize data from an open JMP data table.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 533, 448 ),
    Show Control Panel( 0 ),
    Variables(
        X( :age ),
        Y( Transform Column( "Center[height]", Format( "Fixed Dec", 5, 0 ), Formula( :height - Col Mean( :height ) ) ) ),
        Overlay( :sex )
    ),
    Elements( Bar( X, Y, Legend( 10 ), Bar Style( "Stacked" ), Label( "Label by Value" ) ) ),
    SendToReport( Dispatch( {}, "Graph Builder", OutlineBox, {Set Title( "Graph Builder: Stacked Bar with Label by Value" )} ) )
);

Code Explanation:

1. Open data table.
2. Launch Graph Builder.
3. Set graph size.
4. Hide control panel.
5. Define X variable.
6. Define transformed Y variable.
7. Define overlay variable.
8. Add stacked bar element.
9. Label bars by value.
10. Set graph title.

Example 949

Summary: Creates a variability chart with nested factors using operator and part configurations, displaying standard deviation charts.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 468, 283 ),
    Show Control Panel( 0 ),
    Variables( X( :age ), Y( :height ) ),
    Elements( Bar( X, Y, Legend( 4 ) ) ),
    SendToReport(
        Dispatch( {}, "height", ScaleBox, {Label Row( Show Major Grid( 1 ) )} ),
        Dispatch( {}, "Graph Builder", FrameBox, {Left( 0 ), Right( 0 ), Top( 1 ), Bottom( 1 )} )
    )
);

Code Explanation:

1. Open data table.
2. Create Graph Builder object.
3. Set graph size.
4. Hide control panel.
5. Define X and Y variables.
6. Add bar element.
7. Send report commands.
8. Show major grid on Y-axis.
9. Adjust frame box margins.
10. Display graph.

Example 950

Summary: Creates a variability chart with nested factors using Graph Builder, displaying standard deviation charts and summarizing data with first quartile statistics.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 534, 418 ),
    Show Control Panel( 0 ),
    Variables( Y( :weight ), Overlay( :age ) ),
    Elements( Bar( Y, Legend( 4 ), Summary Statistic( "First Quartile" ) ) )
);

Code Explanation:

1. Open data table;
2. Launch Graph Builder.
3. Set window size.
4. Hide control panel.
5. Assign variables: Y(weight), Overlay(age).
6. Add bar element.
7. Set summary statistic to first quartile.
8. Assign legend position.

Example 951

Summary: Creates two variability charts with nested factors using Graph Builder, displaying standard deviation charts and utilizing first and third quartile summaries.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 534, 418 ),
    Show Control Panel( 0 ),
    Variables( Y( :weight ), Overlay( :age ) ),
    Elements( Bar( Y, Legend( 4 ), Summary Statistic( "First Quartile" ) ) )
);
Graph Builder(
    Size( 534, 418 ),
    Show Control Panel( 0 ),
    Variables( Y( :weight ), Overlay( :age ) ),
    Elements( Bar( Y, Legend( 4 ), Summary Statistic( "Third Quartile" ) ) )
);

Code Explanation:

1. Open data table.
2. Create first graph builder.
3. Set graph size.
4. Hide control panel.
5. Assign variables: weight (Y), age (Overlay).
6. Add bar element.
7. Set legend position.
8. Use first quartile summary.
9. Create second graph builder.
10. Use third quartile summary.

Example 952

Summary: Creates a bar chart with nested factors using Graph Builder, displaying standard deviation charts and enabling legend interaction.

Code:

Open("data_table.jmp");
Graph Builder( Size( 534, 471 ), Show Control Panel( 0 ), Variables( X( :city ), Y( :State ) ), Elements( Bar( X, Y, Legend( 17 ) ) ) );

Code Explanation:

1. Open data table;
2. Launch Graph Builder.
3. Set window size.
4. Hide control panel.
5. Assign X variable.
6. Assign Y variable.
7. Add bar element.
8. Enable legend.
9. Position legend.

Example 953

Summary: Creates two variability charts with nested factors using Graph Builder, displaying standard deviation charts and configuring graph titles and axis labels.

Code:

Open("data_table.jmp");
Graph Builder(
    Show Control Panel( 0 ),
    Variables( X( :Treatment ), Y( :Lower 95% ), Y( :Upper 95%, Position( 1 ) ), Y( :Mean, Position( 1 ) ), Overlay( :Sex ) ),
    Elements( Bar( X, Y( 1 ), Y( 2 ), Y( 3 ), Legend( 3 ), Bar Style( "Interval" ) ) ),
    SendToReport(
        Dispatch( {}, "graph title", TextEditBox, {Set Text( "Comparing 95% Confidence Intervals" )} ),
        Dispatch( {}, "Y title", TextEditBox, {Set Text( "Measure" )} )
    )
);
Graph Builder(
    Show Control Panel( 0 ),
    Variables( X( :Treatment ), Y( :Lower 95% ), Y( :Upper 95%, Position( 1 ) ), Y( :Mean, Position( 1 ) ), Overlay( :Sex ) ),
    Elements( Bar( X, Y( 1 ), Y( 2 ), Y( 3 ), Legend( 3 ), Bar Style( "Side by side intervals" ) ) ),
    SendToReport(
        Dispatch( {}, "graph title", TextEditBox, {Set Text( "Comparing 95% Confidence Intervals" )} ),
        Dispatch( {}, "Y title", TextEditBox, {Set Text( "Measure" )} )
    )
);

Code Explanation:

1. Open data table;
2. Create first Graph Builder.
3. Hide control panel.
4. Set X to Treatment.
5. Set Y1 to Lower 95%.
6. Set Y2 to Upper 95%.
7. Set Y3 to Mean.
8. Overlay by Sex.
9. Add bar element.
10. Set bar style to Interval.
11. Set graph title.
12. Set Y axis title.
13. Create second Graph Builder.
14. Hide control panel.
15. Set X to Treatment.
16. Set Y1 to Lower 95%.
17. Set Y2 to Upper 95%.
18. Set Y3 to Mean.
19. Overlay by Sex.
20. Add bar element.
21. Set bar style to Side by side intervals.
22. Set graph title.
23. Set Y axis title.

Example 954

Summary: Creates a bar chart with nested factors using Graph Builder, displaying standard deviation charts and utilizing Bullet style.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 450, 351 ),
    Show Control Panel( 0 ),
    Variables( X( :Color ), Overlay( :Carat Weight ) ),
    Elements( Bar( X, Legend( 3 ), Bar Style( "Bullet" ) ) )
);

Code Explanation:

1. Open data table;
2. Create Graph Builder window.
3. Set size to 450x351.
4. Hide control panel.
5. Assign Color to X-axis.
6. Overlay Carat Weight.
7. Add Bar element.
8. Use Bullet style.
9. Display legend at position 3.

Example 955

Summary: Creates a variability chart with nested factors using Graph Builder, displaying standard deviation charts and configuring legend settings.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 516, 373 ),
    Show Control Panel( 0 ),
    Variables( X( :Period ), Group Y( :Activity ), Frequency( :Groups ) ),
    Elements( Bar( X, Legend( 12 ) ) )
);

Code Explanation:

1. Open data_table data
2. Launch Graph Builder.
3. Set size 516x373.
4. Hide control panel.
5. Set X variable: Period.
6. Set Y variable: Activity.
7. Set frequency: Groups.
8. Add bar element.
9. Assign legend to bar.
10. Display graph.

Example 956

Summary: Creates a variability chart with nested factors using Graph Builder, displaying standard deviation charts and labeling bars by value.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 471, 356 ),
    Show Control Panel( 0 ),
    Variables( X( :age, Order By( :height, Ascending, Order Statistic( "Mean" ) ) ), Y( :height ) ),
    Elements( Bar( X, Y, Legend( 20 ), Label( "Label by Value" ) ) )
);

Code Explanation:

1. Open data table;
2. Launch Graph Builder.
3. Set graph size.
4. Hide control panel.
5. Assign age to X-axis.
6. Order X by height mean.
7. Assign height to Y-axis.
8. Add bar element.
9. Enable legend.
10. Label bars by value.

Example 957

Summary: Creates a bar chart with nested factors using Graph Builder, displaying height and weight on separate axes.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 421, 292 ),
    Show Control Panel( 0 ),
    Variables( X( :sex ), Y( :height, Side( "Right" ) ), Y( :weight, Position( 1 ) ) ),
    Elements( Bar( X, Y( 2 ), Legend( 5 ) ) )
);

Code Explanation:

1. Open data table;
2. Launch Graph Builder.
3. Set window size.
4. Hide control panel.
5. Assign sex to X-axis.
6. Assign height to right Y-axis.
7. Assign weight to left Y-axis.
8. Add bar element.
9. Position bar on right Y-axis.
10. Add legend for bar.

Example 958

Summary: Creates a bar chart with nested factors using Graph Builder, displaying height as a function of sex and age.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 457, 338 ),
    Show Control Panel( 0 ),
    Variables( X( :sex ), X( :age, Position( 1 ) ), Y( :height ) ),
    Elements( Bar( X( 1 ), X( 2 ), Y, Legend( 8 ) ) ),
    SendToReport( Dispatch( {}, "sex", ScaleBox, {Min( 3 )} ), Dispatch( {}, "400", LegendBox, {Set Title( "" )} ) )
);

Code Explanation:

1. Open data table;
2. Create Graph Builder window.
3. Set window size.
4. Hide control panel.
5. Define X variables: sex, age.
6. Define Y variable: height.
7. Add bar element with two X axes.
8. Customize legend position.
9. Adjust sex scale minimum.
10. Remove legend title.

Example 959

Summary: Creates a variability chart with nested factors using Graph Builder, specifying X and Y variables, customizing legend color, and adding pin annotation details.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 404, 348 ),
    Show Control Panel( 0 ),
    Variables( X( :weight ), Y( :sex ) ),
    Elements( Bar( X, Y, Legend( 4 ), Label( "Label by Value" ) ) ),
    SendToReport(
        Dispatch( {}, "400", ScaleBox, {Legend Model( 4, Properties( 0, {Fill Color( 23 )} ) )} ),
        Dispatch( {}, "Graph Builder", FrameBox,
            Add Pin Annotation(
                Seg( BarSeg( 1 ) ),
                Index( {1, 1} ),
                Index Row( {5, 5} ),
                UniqueID( 589681361 ),
                FoundPt( {203, 122} ),
                Origin( {50.7317073170732, 1.00522648083624} )
            )
        )
    )
);

Code Explanation:

1. Open data table;
2. Launch Graph Builder.
3. Set graph size.
4. Hide control panel.
5. Define X and Y variables.
6. Create bar chart.
7. Customize legend color.
8. Add label by value.
9. Add pin annotation.
10. Specify annotation details.

Example 960

Summary: Creates a bullet bar chart with transformed height data, centered around the mean, and overlaid by sex using Graph Builder.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 516, 359 ),
    Show Control Panel( 0 ),
    Variables(
        X( :age ),
        Y( Transform Column( "Center[height]", Format( "Fixed Dec", 5, 0 ), Formula( :height - Col Mean( :height ) ) ) ),
        Overlay( :sex )
    ),
    Elements( Bar( X, Y, Legend( 10 ), Bar Style( "Bullet" ) ) ),
    SendToReport( Dispatch( {}, "Graph Builder", OutlineBox, {Set Title( "Graph Builder Bullet Bar Chart with Transform Column" )} ) )
);

Code Explanation:

1. Open data_table data
2. Launch Graph Builder.
3. Set graph size.
4. Hide control panel.
5. Define X variable: age.
6. Define Y variable: transformed height.
7. Center height data.
8. Format transformed data.
9. Overlay by sex.
10. Create bullet bar chart.

Example 961

Summary: Creates a bullet bar chart with a transformed height column, centered around the mean, and overlays by sex using Graph Builder.

Code:

dt = Open("data_table.jmp");
Graph Builder(
    Size( 516, 359 ),
    Show Control Panel( 0 ),
    Variables(
        X( :age ),
        Y( Transform Column( "Center[height]", Format( "Fixed Dec", 5, 0 ), Formula( :height - Col Mean( :height ) ) ) ),
        Overlay( :sex )
    ),
    Elements( Bar( X, Y, Legend( 10 ), Bar Style( "Bullet" ) ) ),
    SendToReport( Dispatch( {}, "Graph Builder", OutlineBox, {Set Title( "Graph Builder Bullet Bar Chart with Transform Column" )} ) )
);

Code Explanation:

1. Open table.
2. Create graph builder.
3. Set size.
4. Hide control panel.
5. Define X variable.
6. Define Y variable.
7. Transform height column.
8. Center height data.
9. Set overlay variable.
10. Add bar element.
11. Set title.

Example 962

Summary: Creates a variability chart with nested factors using Graph Builder, displaying standard deviation charts and customizing legend settings.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 366, 285 ),
    Show Control Panel( 0 ),
    Variables( X( :age ), Y( :height ) ),
    Elements( Bar( X, Y, Legend( 7 ), Summary Statistic( "Variance" ) ), Points( X, Y, Legend( 10 ) ) ),
    SendToReport(
        Dispatch( {}, "400", ScaleBox, {Legend Model( 10, Properties( 0, {Line Color( 38 )} ) )} ),
        Dispatch( {}, "400", LegendBox, {Set Title( "" )} )
    )
);

Code Explanation:

1. Open data table;
2. Create Graph Builder window.
3. Set graph size.
4. Hide control panel.
5. Assign X and Y variables.
6. Add bar element with variance summary.
7. Add points element.
8. Customize legend for points.
9. Remove legend title.
10. Display graph.

Example 963

Summary: Creates a side-by-side bar chart with transform column grouping in Graph Builder, displaying atmospheric pressure by storm category and month year.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 570, 448 ),
    Show Control Panel( 0 ),
    Variables(
        X( :Storm Category ),
        Y( :Atmospheric Pressure ),
        Group Y( Transform Column( "Month Year", Ordinal, Format( "m/y", 8 ), Formula( Date DMY( 1, Month( :Date ), Year( :Date ) ) ) ) )
    ),
    Elements( Bar( X, Y, Legend( 4 ), Label( "Label by Value" ) ) ),
    SendToReport(
        Dispatch( {}, "Graph Builder", OutlineBox, {Set Title( "Graph Builder Side by Side Bar Chart with Transform Column" )} )
    )
);

Code Explanation:

1. Open data table;
2. Initialize Graph Builder.
3. Set graph size.
4. Hide control panel.
5. Define X variable.
6. Define Y variable.
7. Transform column for grouping.
8. Add bar element.
9. Label bars by value.
10. Set graph title.

Example 964

Summary: Creates a variability chart with nested factors using Graph Builder, displaying standard deviation charts and summarizing by mean.

Code:

Open("data_table.jmp");
Graph Builder(
    Show Control Panel( 0 ),
    Variables( X( :Day of Week ), Overlay( :Airline ) ),
    Elements( Bar( X, Legend( 2 ), Bar Style( "Side by side" ), Summary Statistic( "Mean" ) ) ),
    SendToReport( Dispatch( {}, "graph title", TextEditBox, {Set Text( "Flights by Airline and Day of Week" )} ) )
);

Code Explanation:

1. Open data table;
2. Launch Graph Builder.
3. Hide control panel.
4. Set X variable: Day of Week.
5. Overlay by Airline.
6. Add bar element.
7. Set legend position: 2.
8. Use side-by-side bar style.
9. Summarize by mean.
10. Set graph title.

Example 965

Summary: Creates a variability chart with nested factors using Graph Builder, displaying standard deviation charts and customizing legend gradient.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 768, 592 ),
    Show Control Panel( 0 ),
    Variables( X( :Food Category ), Y( :Calories ), Color( :Calories ) ),
    Elements( Bar( X, Y, Legend( 7 ), Summary Statistic( "Sum" ) ) ),
    SendToReport(
        Dispatch( {}, "400", ScaleBox,
            {Legend Model( 7, Properties( 0, {gradient( {Color Theme( "Muted Yellow to Red" ), Width( 12 )} )} ) )}
        )
    )
);

Code Explanation:

1. Open data table;
2. Create Graph Builder window.
3. Set window size.
4. Hide control panel.
5. Define X variable: Food Category.
6. Define Y variable: Calories.
7. Define color variable: Calories.
8. Add bar element.
9. Set summary statistic to Sum.
10. Customize legend gradient.

Example 966

Summary: Creates a variability chart with nested factors using operator and part configurations, displaying standard deviation charts.

Code:

Open("data_table.jmp");
Graph Builder(
    Variables( X( :Genre ), Y( :Domestic Gross ), Y( :Foreign Gross, Position( 1 ) ) ),
    Show control panel( 0 ),
    Elements( Bar( X, Y( 1 ), Y( 2 ), Legend( 2 ), Bar Style( "Side by side" ), Summary Statistic( "Mean" ) ) )
);

Code Explanation:

1. Open data table;
2. Launch Graph Builder.
3. Set X variable to Genre.
4. Set Y variables to Domestic Gross, Foreign Gross.
5. Hide control panel.
6. Add Bar element.
7. Configure Bar for two Y variables.
8. Use "Side by side" bar style.
9. Apply "Mean" summary statistic.
10. Display graph.

Example 967

Summary: Creates a stacked bar chart with nested factors using Graph Builder, displaying mean values and customizable axis scales.

Code:

Open("data_table.jmp");
Graph Builder(
    Show Control Panel( 0 ),
    Variables( X( :Year ), Y( :Market Share ), Overlay( :Operating System ) ),
    Elements( Bar( X, Y, Legend( 8 ), Bar Style( "Stacked" ), Summary Statistic( "Mean" ) ) ),
    SendToReport(
        Dispatch( {}, "Year", ScaleBox, {Min( 2005.50569625983 ), Max( 2011.46622145589 ), Inc( 1 ), Minor Ticks( 0 )} ),
        Dispatch( {}, "Market Share", ScaleBox,
            {Format( "Percent", 12, 0 ), Min( 0.00313397542658369 ), Max( 1.00090393964954 ), Inc( 0.2 ), Minor Ticks( 0 )}
        ),
        Dispatch( {}, "400", LegendBox, {Legend Position( {4, 3, 2, 1, 0} )} ),
        Dispatch( {}, "graph title", TextEditBox, {Set Text( "SmartPhone OS Market Share" )} )
    )
);

Code Explanation:

1. Open data table.
2. Create Graph Builder.
3. Hide control panel.
4. Set X variable.
5. Set Y variable.
6. Set overlay variable.
7. Add bar element.
8. Configure bar style.
9. Set summary statistic.
10. Customize axis scales.
11. Adjust legend position.
12. Set graph title.

Example 968

Summary: Creates a variability chart with nested factors using Graph Builder, configuring date scale and displaying standard deviation charts.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 612, 561 ),
    Show Control Panel( 0 ),
    Variables( X( :Date ), Y( :Close ), Y( :Low, Position( 1 ) ), Y( :High, Position( 1 ) ), Y( :Open, Position( 1 ) ) ),
    Elements( Bar( X, Y( 1 ), Y( 2 ), Y( 3 ), Y( 4 ), Legend( 3 ), Bar Style( "Stock" ) ) ),
    SendToReport(
        Dispatch( {}, "Date", ScaleBox, {Min( 3400704000 ), Max( 3408134400 ), Interval( "Week" ), Inc( 1 ), Minor Ticks( 0 )} ),
        Dispatch( {}, "graph title", TextEditBox, {Set Text( "Stock Price (Open/High/Low/Close)" )} ),
        Dispatch( {}, "Y title", TextEditBox, {Set Text( "Price" )} )
    )
);

Code Explanation:

1. Open data table;
2. Create Graph Builder window.
3. Set graph size.
4. Hide control panel.
5. Define X and Y variables.
6. Add bar element.
7. Configure date scale.
8. Set graph title.
9. Set Y axis title.
10. Display graph.

Example 969

Summary: Creates a variability chart with nested factors using Graph Builder, configuring date and price scales, and displaying standard deviation charts.

Code:

Open("data_table.jmp");
Graph Builder(
    Show Control Panel( 0 ),
    Variables( X( :Date ), Y( :Low ), Y( :High, Position( 1 ) ) ),
    Elements( Bar( X, Y( 1 ), Y( 2 ), Legend( 3 ), Bar Style( "Range" ) ) ),
    SendToReport(
        Dispatch( {}, "Date", ScaleBox, {Min( 3400704000 ), Max( 3408134400 ), Interval( "Week" ), Inc( 1 ), Minor Ticks( 0 )} ),
        Dispatch( {}, "graph title", TextEditBox, {Set Text( "Stock Price Range" )} ),
        Dispatch( {}, "Y title", TextEditBox, {Set Text( "Price" )} )
    )
);

Code Explanation:

1. Open data table;
2. Create Graph Builder.
3. Hide control panel.
4. Set X variable to Date.
5. Set Y variable to Low.
6. Add Y variable High.
7. Position High on Y axis 1.
8. Add bar element.
9. Set bar style to range.
10. Customize date scale.
11. Set graph title.
12. Set Y axis title.

Example 970

Summary: Creates a variability chart with nested factors using operator and part configurations, displaying standard deviation charts in Graph Builder.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 615, 554 ),
    Show Control Panel( 0 ),
    Variables( X( :Treatment ), Y( :Lower 95% ), Y( :Upper 95%, Position( 1 ) ), Y( :Mean, Position( 1 ) ), Overlay( :Sex ) ),
    Elements( Bar( X, Y( 1 ), Y( 2 ), Y( 3 ), Legend( 3 ), Bar Style( "Range" ) ) ),
    SendToReport(
        Dispatch( {}, "400", ScaleBox,
            {Legend Model(
                3,
                Properties( 0, {Fill Color( 35 )} ),
                Properties( 1, {Line Color( 51 )} ),
                Properties( 3, {Line Color( 21 )} )
            )}
        ),
        Dispatch( {}, "graph title", TextEditBox, {Set Text( "Comparing 95% Confidence Intervals" )} ),
        Dispatch( {}, "Y title", TextEditBox, {Set Text( "Measure" )} )
    )
);

Code Explanation:

1. Open data table;
2. Create Graph Builder window.
3. Set window size.
4. Hide control panel.
5. Define X and Y variables.
6. Add overlay variable.
7. Create bar chart element.
8. Customize legend properties.
9. Set graph title.
10. Set Y axis title.

Example 971

Summary: Creates a variability chart with nested factors using operator and part configurations, displaying standard deviation charts in JMP.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 615, 554 ),
    Show Control Panel( 0 ),
    Variables( X( :Treatment ), Y( :Lower 95% ), Y( :Upper 95%, Position( 1 ) ), Y( :Mean, Position( 1 ) ), Overlay( :Sex ) ),
    Elements( Bar( X, Y( 1 ), Y( 2 ), Y( 3 ), Legend( 3 ), Bar Style( "Interval" ) ) ),
    SendToReport(
        Dispatch( {}, "graph title", TextEditBox, {Set Text( "Comparing 95% Confidence Intervals" )} ),
        Dispatch( {}, "Y title", TextEditBox, {Set Text( "Measure" )} )
    )
);

Code Explanation:

1. Open data table;
2. Create new Graph Builder window.
3. Set window size to 615x554.
4. Hide control panel.
5. Define X variable as Treatment.
6. Define Y variables: Lower 95%, Upper 95%, Mean.
7. Overlay variable by Sex.
8. Add bar element with interval style.
9. Set graph title to "Comparing 95% Confidence Intervals".
10. Set Y axis title to "Measure".

Example 972

Summary: Creates a bar chart with nested factors using Graph Builder, displaying standard deviation charts and labeling bars by value.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 526, 446 ),
    Show Control Panel( 0 ),
    Variables( X( :age ), Y( :weight ) ),
    Elements( Bar( X, Y, Legend( 6 ), Label( "Label by Value" ) ) )
);

Code Explanation:

1. Open data table;
2. Launch Graph Builder.
3. Set window size.
4. Hide control panel.
5. Assign age to X-axis.
6. Assign weight to Y-axis.
7. Add bar element.
8. Enable legend.
9. Label bars by value.

Example 973

Summary: Creates a variability chart with nested factors using Graph Builder, displaying standard deviation charts and configuring bar style.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 282, 258 ),
    Show Control Panel( 0 ),
    Variables( X( :sex ), Y( :height ), Y( :weight, Position( 1 ) ), Overlay( :age ) ),
    Elements( Bar( X, Y( 1 ), Y( 2 ), Legend( 7 ), Bar Style( "Interval" ) ) )
);

Code Explanation:

1. Open data table.
2. Create Graph Builder window.
3. Set window size.
4. Hide control panel.
5. Define X variable.
6. Define first Y variable.
7. Define second Y variable.
8. Set overlay variable.
9. Add bar element.
10. Configure bar style.

Example 974

Summary: Creates a variability chart with nested factors using Graph Builder, displaying standard deviation charts for minimum, midrange, and maximum prices.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 481, 465 ),
    Show Control Panel( 0 ),
    Variables(
        X( :Vehicle Category ),
        Y( :Name( "Minimum Price ($1000)" ) ),
        Y( :Name( "Midrange Price ($1000)" ), Position( 1 ) ),
        Y( :Name( "Maximum Price ($1000)" ), Position( 1 ) )
    ),
    Elements( Bar( X, Y( 1 ), Y( 2 ), Y( 3 ), Legend( 8 ), Bar Style( "Side by side intervals" ) ) )
);

Code Explanation:

1. Open data table;
2. Launch Graph Builder.
3. Set graph size.
4. Hide control panel.
5. Define X variable.
6. Define first Y variable.
7. Define second Y variable.
8. Define third Y variable.
9. Add bar element.
10. Configure bar style.

Example 975

Summary: Creates a stacked bar chart to visualize mean sales ($M) by Type, with Size Co as an overlay, and displays standard deviation charts for each type.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 534, 448 ),
    Show Control Panel( 0 ),
    Legend Position( "Bottom" ),
    Variables( X( :Type ), Y( :Name( "Sales ($M)" ) ), Overlay( :Size Co ) ),
    Elements( Bar( X, Y, Legend( 4 ), Bar Style( "Stacked" ) ) ),
    SendToReport(
        Dispatch( {}, "Type", ScaleBox,
            {Add Ref Line( 0.5, "Solid", "Medium Light Gray", "", 1 ), Label Row( {Automatic Tick Marks( 0 ), Inside Ticks( 1 )} )}
        ),
        Dispatch( {}, "Sales ($M)", ScaleBox, {Format( "Fixed Dec", 12, 2 )} ),
        Dispatch( {}, "400", ScaleBox,
            {Legend Model(
                4,
                Properties( 0, {Fill Color( 19 )} ),
                Properties( 1, {Fill Color( 4 )} ),
                Properties( 2, {Fill Color( 21 )} )
            )}
        ),
        Dispatch( {}, "graph title", TextEditBox, {Set Text( "" )} ),
        Dispatch( {}, "X title", TextEditBox, {Set Text( "Size Co within Type" )} ),
        Dispatch( {}, "Y title", TextEditBox, {Set Text( "Mean(Sales ($M))" )} ),
        Dispatch( {}, "400", LegendBox, {Orientation( "Horizontal" ), Sides( "Left" )} )
    )
);

Code Explanation:

1. Open data table;
2. Create Graph Builder window.
3. Set graph size.
4. Hide control panel.
5. Position legend at bottom.
6. Define X, Y, and overlay variables.
7. Add stacked bar element.
8. Add reference line at 0.5.
9. Format sales scale to fixed decimal.
10. Customize legend colors and orientation.

Example 976

Summary: Creates a variability chart with nested factors using Graph Builder, displaying standard deviation charts and customizing scales and legends.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 455, 504 ),
    Show Control Panel( 0 ),
    Legend Position( "Bottom" ),
    Variables( X( :Date ), Y( :DJI Close ), Y( :DJI Low, Position( 1 ) ), Y( :DJI High, Position( 1 ) ) ),
    Elements(
        Points( X, Y( 1 ), Y( 2 ), Y( 3 ), Legend( 11 ) ),
        Line( X, Y( 1 ), Y( 2 ), Y( 3 ), Legend( 13 ) ),
        Bar( X, Y( 1 ), Legend( 14 ), Bar Style( "Needle" ) )
    ),
    SendToReport(
        Dispatch( {}, "Date", ScaleBox, {Min( 2754518400 ), Max( 2762553600 ), Interval( "Day" ), Inc( 10 ), Minor Ticks( 0 )} ),
        Dispatch( {}, "DJI Close", ScaleBox, {Format( "Fixed Dec", 12, 2 ), Min( 2825 ), Max( 3075 ), Inc( 50 ), Minor Ticks( 1 )} ),
        Dispatch( {}, "400", ScaleBox,
            {Legend Model(
                11,
                Base( 0, 0, 0 ),
                Base( 1, 0, 0 ),
                Base( 2, 0, 0 ),
                Properties( 0, {Line Color( 20 ), Marker( "Plus" )} ),
                Properties( 1, {Line Color( 21 ), Marker( "Diamond" )} ),
                Properties( 2, {Line Color( 19 ), Marker( "Circle" )} )
            ), Legend Model(
                13,
                Properties( 0, {Line Color( 20 )} ),
                Properties( 1, {Line Color( 21 )} ),
                Properties( 2, {Line Color( 19 )} )
            ), Legend Model( 14, Properties( 0, {Line Color( 20 )} ) )}
        ),
        Dispatch( {}, "graph title", TextEditBox, {Set Text( "" )} ),
        Dispatch( {}, "Y title", TextEditBox, {Set Text( "Y" )} ),
        Dispatch( {}, "Graph Builder", FrameBox, {Marker Size( 5 )} ),
        Dispatch( {}, "400", LegendBox,
            {Set Title( "Y" ), Orientation( "Horizontal" ), Sides( "Left" ), Legend Position( {11, [2, 4, 0], 13, [-1, 5, 1], 14, [3]} )}
        )
    )
);

Code Explanation:

1. Open data table;
2. Create Graph Builder window.
3. Set window size.
4. Hide control panel.
5. Position legend at bottom.
6. Define X and Y variables.
7. Add points element.
8. Add line element.
9. Add bar element.
10. Customize scales and legends.

Example 977

Summary: Creates a variability chart with nested factors using operator and part configurations, displaying standard deviation charts.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 366, 285 ),
    Show Control Panel( 0 ),
    Variables( X( :Operator ), X( :Part, Position( 1 ) ), Y( :Y ), Overlay( :Part ) ),
    Elements( Points( X( 1 ), X( 2 ), Y, Legend( 17 ), Summary Statistic( "Mean" ), Error Bars( "Range" ) ) )
);

Code Explanation:

1. Open data table;
2. Launch Graph Builder.
3. Set window size.
4. Hide control panel.
5. Define X variables.
6. Define Y variable.
7. Define overlay variable.
8. Add points element.
9. Specify summary statistic.
10. Add error bars.

Example 978

Summary: Creates a variability chart with nested factors using Graph Builder, displaying standard deviation charts and customizing legend properties.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 366, 285 ),
    Show Control Panel( 0 ),
    Variables( X( :age ), Y( :height ) ),
    Elements( Bar( X, Y, Legend( 7 ), Summary Statistic( "Variance" ) ), Points( X, Y, Legend( 10 ) ) ),
    SendToReport( Dispatch( {}, "400", ScaleBox, {Legend Model( 10, Properties( 0, {Line Color( 38 )} ) )} ) )
);

Code Explanation:

1. Open data table;
2. Launch Graph Builder.
3. Set window size.
4. Hide control panel.
5. Define X variable.
6. Define Y variable.
7. Add bar element.
8. Set summary statistic to variance.
9. Add point element.
10. Customize legend properties.

Example 979

Summary: Creates a graph builder with range error bars, using Graph Builder to visualize data from an open JMP data table.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 450, 300 ),
    Show Control Panel( 0 ),
    Variables( X( :age ), Y( :height ), Overlay( :sex ) ),
    Elements( Bar( X, Y, Legend( 11 ), Error Bars( "Range" ) ) ),
    SendToReport( Dispatch( {}, "Graph Builder", OutlineBox, {Set Title( "Graph Builder with Range Error Bars" )} ) )
);

Code Explanation:

1. Open data table;
2. Launch Graph Builder.
3. Set graph size.
4. Hide control panel.
5. Define X variable.
6. Define Y variable.
7. Define overlay variable.
8. Add bar element.
9. Add error bars.
10. Set graph title.

Example 980

Summary: Creates a bar chart with nested factors using Graph Builder, displaying standard deviation charts and configuring X-axis scale settings.

Code:

Open("data_table.jmp");
obj = Graph Builder(
    Size( 1450, 1082 ),
    Show Control Panel( 0 ),
    Variables( X( :State ), Y( :Name( "% Taking (2004)" ) ) ),
    Elements( Bar( X, Y, Legend( 8 ) ) ),
    SendToReport( Dispatch( {}, "State", ScaleBox, {Min( -0.33863086560182 ), Max( 50.6613691343982 ), Inc( 1 ), Minor Ticks( 0 )} ) )
);

Code Explanation:

1. Open data_table data
2. Create Graph Builder object.
3. Set graph size to 1450x1082.
4. Hide control panel.
5. Define X variable as State.
6. Define Y variable as % Taking (2004).
7. Add bar element.
8. Set legend for bar.
9. Adjust X-axis scale minimum.
10. Adjust X-axis scale maximum.
11. Set X-axis increment to 1.
12. Disable minor ticks on X-axis.

Example 981

Summary: Creates a stacked bar chart with nested factors using Graph Builder, displaying standard deviation charts and customizing axis labels and legend colors.

Code:

dt under test = Open("data_table.jmp");
obj = Graph Builder(
    Size( 421, 381 ),
    Show Control Panel( 0 ),
    Variables( X( :Sex ), Overlay( :Survived ) ),
    Elements( Bar( X, Legend( 4 ), Bar Style( "Stacked" ) ) ),
    SendToReport(
        Dispatch( {}, "Sex", ScaleBox,
            {Min( -0.495789 ), Max( 1.50421052631579 ), Inc( 1 ), Minor Ticks( 0 ), Label Row(
                {Set Font( "Arial" ), Set Font Style( "Bold Italic" )}
            )}
        ),
        Dispatch( {}, "", ScaleBox,
            {Format( "Best", 12 ), Label Row(
                {Show Major Grid( 1 ), Show Minor Grid( 1 ), Minor Grid Line Color( 32 ), Set Font Style( "Bold Italic" )}
            )}
        ),
        Dispatch( {}, "400", ScaleBox, {Legend Model( 4, Properties( 0, {Fill Color( 51 )} ), Properties( 1, {Fill Color( 52 )} ) )} ),
        Dispatch( {}, "Graph Builder", FrameBox, {Background Color( 38 )} )
    )
);

Code Explanation:

1. Open data table;
2. Create Graph Builder object.
3. Set graph size.
4. Hide control panel.
5. Define X and overlay variables.
6. Add stacked bar element.
7. Adjust X-axis scale.
8. Format Y-axis labels.
9. Customize legend colors.
10. Change background color.

Example 982

Summary: Creates a variability chart with nested factors using operator and part configurations, displaying standard deviation charts.

Code:

dt = Open("data_table.jmp");
Graph Builder(
    Size( 491, 374 ),
    Variables( X( :sex ), Y( :height ), Group Y( :age, Levels( 3 ), Size( 51 ) ) ),
    Elements( Bar( X, Y, Legend( 8 ), Summary Statistic( "Range" ) ) )
);

Code Explanation:

1. Open table.
2. Create graph builder.
3. Set size.
4. Define X variable.
5. Define Y variable.
6. Group Y variable.
7. Set group levels.
8. Set group size.
9. Add bar element.
10. Set summary statistic.

Example 983

Summary: Creates a bar chart to visualize frequency distribution of 'Squat' values, using Graph Builder and setting missing value codes.

Code:

dt = Open("data_table.jmp");
:Squat << set property( "missing value codes", {330} );
Graph Builder(
    Show Control Panel( 0 ),
    Variables( X( :Position ), Frequency( :Squat ) ),
    Elements( Bar( X, Legend( 10 ), Summary Statistic( "Sum" ), Label( "Label by Value" ) ) )
);

Code Explanation:

1. Open data table;
2. Set missing value code for Squat.
3. Launch Graph Builder.
4. Hide control panel.
5. Set X variable to Position.
6. Set Y variable to Squat.
7. Add Bar element.
8. Use Legend 10.
9. Summarize data by sum.
10. Label bars by value.

Example 984

Summary: Creates a bar chart with nested factors using Graph Builder, displaying standard deviation charts and filtering data by 'Cut' to 'Good'.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 310, 297 ),
    Show Control Panel( 0 ),
    Variables( X( :Report ), Y( :Price ), Group Y( :Clarity ), Color( :Color ) ),
    Elements( Bar( X, Y, Legend( 20 ) ) ),
    Local Data Filter(
        Mode( Include( 0 ) ),
        Inverse( 1 ),
        Add Filter( columns( :Cut ), Where( :Cut == "Good" ), Display( :Cut, Size( 160, 60 ), List Display ) )
    )
);

Code Explanation:

1. Open data table;
2. Create Graph Builder window.
3. Set size to 310x297.
4. Hide control panel.
5. Assign variables: X=Report, Y=Price, Group Y=Clarity, Color=Color.
6. Add bar element with legend.
7. Enable local data filter.
8. Set filter mode to include.
9. Apply inverse filter.
10. Add filter for Cut="Good".

Example 985

Summary: Creates a variability chart with nested factors using operator and part configurations, displaying standard deviation charts in Graph Builder.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 465, 365 ),
    Show Control Panel( 0 ),
    Variables( X( :Color ), Y( :Price ), Group Y( :Clarity, Size( 41 ) ), Overlay( :Report ) ),
    Elements( Bar( X, Y, Legend( 40 ) ) ),
    Local Data Filter(
        Mode( Include( 0 ) ),
        Add Filter( columns( :Cut ), Where( :Cut == "Excellent" ), Display( :Cut, Size( 160, 60 ), List Display ) )
    )
);

Code Explanation:

1. Open data table;
2. Launch Graph Builder.
3. Set size 465x365.
4. Hide control panel.
5. Set X variable: Color.
6. Set Y variable: Price.
7. Group Y by Clarity.
8. Overlay by Report.
9. Add bar element.
10. Configure local data filter for Cut.

Example 986

Summary: Creates multiple Graph Builder windows with nested factors, displaying standard deviation charts and filtering data based on specific conditions.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 310, 297 ),
    Show Control Panel( 0 ),
    Variables( X( :Report ), Y( :Price ), Group Y( :Clarity ), Color( :Color ) ),
    Elements( Bar( X, Y, Legend( 20 ) ) ),
    Local Data Filter(
        Mode( Include( 0 ) ),
        Inverse( 1 ),
        Add Filter( columns( :Cut ), Where( :Cut == "Good" ), Display( :Cut, Size( 160, 60 ), List Display ) )
    )
);
Open("data_table.jmp");
Graph Builder(
    Size( 465, 365 ),
    Show Control Panel( 0 ),
    Variables( X( :Color ), Y( :Price ), Group Y( :Clarity, Size( 41 ) ), Overlay( :Report ) ),
    Elements( Bar( X, Y, Legend( 40 ) ) ),
    Local Data Filter(
        Mode( Include( 0 ) ),
        Add Filter( columns( :Cut ), Where( :Cut == "Excellent" ), Display( :Cut, Size( 160, 60 ), List Display ) )
    )
);
dt = Open("data_table.jmp");
dt << Select Rows( Index( 60, 90 ) );
dt2 = dt << Data View;
dt2 << Clear Select();
dt2 << Graph Builder(
    Size( 534, 472 ),
    Show Control Panel( 0 ),
    Variables( X( :Alcohol use ), X( :Heart History, Position( 1 ) ), Y( :Cholesterol ) ),
    Elements( Bar( X( 1 ), X( 2 ), Y, Legend( 7 ) ) ),
    Local Data Filter( Mode( Include( 0 ) ), Add Filter( columns( :Sex ), Where( :Sex == "female" ) ) )
);

Code Explanation:

1. Open data table;
2. Create Graph Builder window.
3. Set size to 310x297.
4. Hide control panel.
5. Set X: Report, Y: Price, Group Y: Clarity, Color: Color.
6. Add bar element.
7. Add local data filter for Cut == "Good".
8. Open data table;
9. Create another Graph Builder window.
10. Set size to 465x365.
11. Hide control panel.
12. Set X: Color, Y: Price, Group Y: Clarity, Overlay: Report.
13. Add bar element.
14. Add local data filter for Cut == "Excellent".
15. Open data table;
16. Select rows 60-90.
17. Create data view.
18. Clear selection.
19. Create Graph Builder window.
20. Set size to 534x472.
21. Hide control panel.
22. Set X: Alcohol use, X: Heart History, Y: Cholesterol.
23. Add bar element.
24. Add local data filter for Sex == "female".

Example 987

Summary: Creates two Graph Builder windows with nested factors, displaying standard deviation charts and filtering data based on specific conditions.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 310, 297 ),
    Show Control Panel( 0 ),
    Variables( X( :Report ), Y( :Price ), Group Y( :Clarity ), Color( :Color ) ),
    Elements( Bar( X, Y, Legend( 20 ) ) ),
    Local Data Filter(
        Mode( Include( 0 ) ),
        Inverse( 1 ),
        Add Filter( columns( :Cut ), Where( :Cut == "Good" ), Display( :Cut, Size( 160, 60 ), List Display ) )
    )
);
Open("data_table.jmp");
Graph Builder(
    Size( 465, 365 ),
    Show Control Panel( 0 ),
    Variables( X( :Color ), Y( :Price ), Group Y( :Clarity, Size( 41 ) ), Overlay( :Report ) ),
    Elements( Bar( X, Y, Legend( 40 ) ) ),
    Local Data Filter(
        Mode( Include( 0 ) ),
        Add Filter( columns( :Cut ), Where( :Cut == "Excellent" ), Display( :Cut, Size( 160, 60 ), List Display ) )
    )
);
dt = Open("data_table.jmp");
dt << Select Rows( Index( 60, 90 ) );
dt2 = dt << Data View;
dt2 << Clear Select();

Code Explanation:

1. Open data table;
2. Create Graph Builder window.
3. Set size 310x297.
4. Hide control panel.
5. Define X, Y, Group Y, Color variables.
6. Add bar element with legend.
7. Add local data filter for Cut == "Good".
8. Open data table;
9. Create Graph Builder window.
10. Set size 465x365.
11. Hide control panel.
12. Define X, Y, Group Y, Overlay variables.
13. Add bar element with legend.
14. Add local data filter for Cut == "Excellent".
15. Open data table;
16. Select rows 60 to 90.
17. Create data view.
18. Clear row selection.

Example 988

Summary: Creates a variability chart with nested factors using Graph Builder, displaying standard deviation charts and summarizing data by range.

Code:

Open("data_table.jmp") << Graph Builder(
    Size( 291, 219 ),
    Show Control Panel( 0 ),
    Variables( X( :sex ), Y( :height ), Group Y( :age, Levels( 3 ), Size( 51 ) ) ),
    Elements( Bar( X, Y, Legend( 8 ), Summary Statistic( "Range" ) ) )
);

Code Explanation:

1. Open data table;
2. Launch Graph Builder.
3. Set window size.
4. Hide control panel.
5. Assign variables: sex (X), height (Y).
6. Group Y by age with 3 levels.
7. Set group size to 51.
8. Add bar element.
9. Configure bar for X and Y.
10. Use legend position 8.
11. Summarize data using range.

Example 989

Summary: Creates a variability chart with nested factors using operator and part configurations, displaying standard deviation charts in Graph Builder.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 534, 364 ),
    Show Control Panel( 0 ),
    Include Missing Categories( 1 ),
    Set α Level( 0.1 ),
    Variables( X( :REASON ), Y( :LOAN ), Overlay( :JOB ) ),
    Elements( Bar( X, Y, Legend( 19 ), Label( "Label by Value" ) ) )
);

Code Explanation:

1. Open data table;
2. Launch Graph Builder.
3. Set window size.
4. Hide control panel.
5. Include missing categories.
6. Set alpha level.
7. Define X variable.
8. Define Y variable.
9. Define overlay variable.
10. Add bar element.

Example 990

Summary: Creates two Graph Builder windows with nested factors, displaying bar charts and standard deviation charts for loan data.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 534, 364 ),
    Show Control Panel( 0 ),
    Include Missing Categories( 1 ),
    Set α Level( 0.1 ),
    Variables( X( :REASON ), Y( :LOAN ), Overlay( :JOB ) ),
    Elements( Bar( X, Y, Legend( 19 ), Label( "Label by Value" ) ) )
);
Graph Builder(
    Size( 534, 364 ),
    Show Control Panel( 0 ),
    Set α Level( 0.1 ),
    Variables( X( :REASON ), Y( :LOAN ), Overlay( :JOB ) ),
    Elements( Bar( X, Y, Legend( 19 ), Label( "Label by Value" ) ) )
);

Code Explanation:

1. Open data table;
2. Create first Graph Builder window.
3. Set window size to 534x364.
4. Hide control panel.
5. Include missing categories.
6. Set significance level to 0.1.
7. Define X, Y, and Overlay variables.
8. Add bar element with legend and value labels.
9. Create second Graph Builder window.
10. Repeat steps 3-8 for second graph.

Example 991

Summary: Creates a bar chart with nested factors using Graph Builder, displaying standard deviation charts and configuring legend position.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 515, 464 ),
    Show Control Panel( 0 ),
    Variables( X( :School ), Y( :Money ) ),
    Elements( Bar( X, Y, Legend( 5 ), Response Axis( "Y" ) ) )
);

Code Explanation:

1. Open data table;
2. Launch Graph Builder.
3. Set window size.
4. Hide control panel.
5. Assign X variable.
6. Assign Y variable.
7. Add bar element.
8. Set legend position.
9. Specify response axis.
10. Display graph.

Example 992

Summary: Creates a bar chart with nested factors using Graph Builder, displaying standard deviation charts and pin annotations.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 483, 377 ),
    Show Control Panel( 0 ),
    Variables( X( :age ), Y( :height ), Y( :weight, Position( 1 ) ) ),
    Elements( Bar( X, Y( 2 ), Y( 1 ), Legend( 1 ) ) ),
    SendToReport(
        Dispatch( {}, "Graph Builder", FrameBox,
            Add Pin Annotation(
                Seg( BarSeg( 1 ) ),
                Index( {0, 0} ),
                Index Row( {0, 0} ),
                UniqueID( 805444608 ),
                FoundPt( {96, 239} ),
                Origin( {-0.11849710982659, 92.4044943820225} )
            )
        )
    )
);

Code Explanation:

1. Open data table;
2. Create Graph Builder window.
3. Set graph size.
4. Hide control panel.
5. Assign age to X-axis.
6. Assign height to Y-axis.
7. Assign weight to Y-axis.
8. Add bar element.
9. Configure bar element settings.
10. Add pin annotation to graph.

Example 993

Summary: Creates a variability chart with nested factors using Graph Builder, displaying standard deviation charts and summarizing data by Fat variable.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 534, 484 ),
    Show Control Panel( 0 ),
    Variables( X( :Position ), Y( :Height ), Y( :Weight, Position( 1 ) ), Wrap( :Fat ) ),
    Elements( Bar( X, Y( 1 ), Y( 2 ), Legend( 3 ), Bar Style( "Interval" ), Summary Statistic( "Sum" ) ) )
);

Code Explanation:

1. Open data_table data
2. Launch Graph Builder.
3. Set window size to 534x484.
4. Hide control panel.
5. Assign Position to X-axis.
6. Assign Height to Y-axis.
7. Assign Weight to Y-axis, position 1.
8. Wrap by Fat variable.
9. Add Bar element.
10. Configure Bar for Sum summary statistic.

Example 994

Summary: Creates a box plot chart with nested factors using Graph Builder, displaying standard deviation charts and configuring legend position.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 447, 546 ),
    Variables( X( :Gas Tank Size ), Y( :Type ) ),
    Elements( Box Plot( X, Y, Legend( 8 ), Box Style( "Solid" ) ) )
);

Code Explanation:

1. Open data table.
2. Create Graph Builder object.
3. Set graph size.
4. Define X and Y variables.
5. Add Box Plot element.
6. Configure legend position.
7. Set box style to solid.

Example 995

Summary: Creates two box plots with nested factors using Graph Builder, displaying standard deviation charts and customizing legend positions.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 447, 546 ),
    Variables( X( :Gas Tank Size ), Y( :Type ) ),
    Elements( Box Plot( X, Y, Legend( 8 ), Box Style( "Solid" ) ) )
);
Graph Builder(
    Size( 447, 546 ),
    Variables( X( :Gas Tank Size ), Y( :Type ) ),
    Elements( Box Plot( X, Y, Legend( 8 ), Box Style( "Thin" ) ) )
);

Code Explanation:

1. Open data table;
2. Create graph builder window.
3. Set window size.
4. Assign X and Y variables.
5. Add box plot element.
6. Customize legend position.
7. Set box style to solid.
8. Create second graph builder window.
9. Set window size.
10. Assign X and Y variables.
11. Add box plot element.
12. Customize legend position.
13. Set box style to thin.

Example 996

Summary: Creates a box plot variability chart with nested factors using Graph Builder, filtering data by Sex and displaying standard deviation charts.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 434, 334 ),
    Show Control Panel( 0 ),
    Show Legend( 0 ),
    Variables( X( :MaxPulse ), Y( :Runtime ) ),
    Elements( Box Plot( X, Y, Legend( 3 ) ) ),
    Local Data Filter( Add Filter( columns( :Sex ), Where( :Sex == {"F", "M"} ) ) )
);

Code Explanation:

1. Open data_table data
2. Launch Graph Builder.
3. Set window size to 434x334.
4. Hide control panel.
5. Hide legend.
6. Set X variable to MaxPulse.
7. Set Y variable to Runtime.
8. Add box plot element.
9. Apply local data filter.
10. Filter Sex for F and M.

Example 997

Summary: Creates a box plot to visualize the relationship between Heart History and Smoking History, with cigarettes as a selected category.

Code:

dt = Open("data_table.jmp");
dt << select where( :Smoking History == "cigarettes" );
Graph Builder(
    Size( 531, 398 ),
    Show Control Panel( 0 ),
    Variables( X( :Heart History ), Group Y( :Smoking History ) ),
    Elements( Box Plot( X, Legend( 11 ) ) )
);

Code Explanation:

1. Open data table.
2. Select rows with cigarettes.
3. Create Graph Builder window.
4. Set graph size.
5. Hide control panel.
6. Assign variables for X and Y.
7. Add box plot element.
8. Set legend for box plot.

Example 998

Summary: Creates a box plot variability chart with nested factors using Graph Builder, displaying standard deviation charts and legends.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 531, 398 ),
    Show Control Panel( 0 ),
    Variables( X( :Heart History ), Group Y( :Smoking History ) ),
    Elements( Box Plot( X, Legend( 11 ) ) )
);

Code Explanation:

1. Open data table;
2. Launch Graph Builder.
3. Set window size.
4. Hide control panel.
5. Assign X variable.
6. Assign grouped Y variable.
7. Add box plot element.
8. Display legend for box plot.

Example 999

Summary: Creates a box plot in Graph Builder to visualize the relationship between height and weight, with a legend displayed for clarity.

Code:

Open("data_table.jmp");
Graph Builder( Show Control Panel( 0 ), Variables( X( :height ), Y( :weight ) ), Elements( Box Plot( X, Y, Legend( 17 ) ) ) );

Code Explanation:

1. Open data table;
2. Launch Graph Builder.
3. Hide control panel.
4. Set X variable to height.
5. Set Y variable to weight.
6. Add box plot element.
7. Assign legend to box plot.

Example 1000

Summary: Creates a box plot chart with nested factors using Graph Builder, displaying standard deviation charts and legend at position 9.

Code:

Open("data_table.jmp");
Graph Builder( Show Control Panel( 0 ), Variables( X( :age ), Y( :weight ) ), Elements( Box Plot( X, Y, Legend( 9 ) ) ) );

Code Explanation:

1. Open data table.
2. Create Graph Builder window.
3. Hide control panel.
4. Set X variable to age.
5. Set Y variable to weight.
6. Add box plot element.
7. Position box plot on X axis.
8. Position box plot on Y axis.
9. Assign legend to position 9.
10. Display graph.

Example 1001

Summary: Creates a box plot chart with nested factors using Graph Builder, displaying standard deviation charts and customizing legend properties.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 570, 516 ),
    Show Control Panel( 0 ),
    Variables( X( :age ), Y( :weight ), Overlay( :sex ), Frequency( :height ) ),
    Elements( Box Plot( X, Y, Legend( 25 ) ) ),
    SendToReport(
        Dispatch( {}, "400", ScaleBox, {Legend Model( 25, Properties( 1, {Line Color( 6 ), Fill Color( 6 ), Transparency( 0.5 )} ) )} )
    )
);

Code Explanation:

1. Open data table.
2. Launch Graph Builder.
3. Set window size.
4. Hide control panel.
5. Assign variables: X=age, Y=weight, Overlay=sex, Frequency=height.
6. Add box plot element.
7. Customize legend properties.
8. Set line color to blue.
9. Set fill color to blue.
10. Set transparency to 50%.

Example 1002

Summary: Creates a box plot chart with nested factors using Graph Builder, selecting specific rows and configuring legend position.

Code:

dt = Open("data_table.jmp");
dt << clear row states;
dt << select rows( 16 );
Graph Builder(
    Size( 459, 359 ),
    Show Control Panel( 0 ),
    Variables( X( :Gas Tank Size ), Y( :Type ) ),
    Elements( Box Plot( X, Y, Legend( 8 ) ) )
);

Code Explanation:

1. Open data table.
2. Clear all row states.
3. Select specific rows.
4. Create graph builder object.
5. Set window size.
6. Hide control panel.
7. Define X variable.
8. Define Y variable.
9. Add box plot element.
10. Configure legend position.

Example 1003

Summary: Creates a box plot chart with nested factors using Graph Builder, displaying standard deviation charts and customizing the graph title.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 547, 334 ),
    Show Control Panel( 0 ),
    Show Legend( 0 ),
    Variables( X( :Sepal length ), Y( :Species ) ),
    Elements( Box Plot( X, Y, Legend( 4 ) ) ),
    SendToReport( Dispatch( {}, "graph title", TextEditBox, {Set Text( "Sepal length vs. Species" )} ) )
);

Code Explanation:

1. Open data table;
2. Launch Graph Builder.
3. Set window size.
4. Hide control panel.
5. Hide legend.
6. Assign variables.
7. Add box plot element.
8. Customize graph title.

Example 1004

Summary: Creates a box plot chart with nested factors using Graph Builder, displaying standard deviation charts for height and weight variables.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 534, 448 ),
    Show Control Panel( 0 ),
    Legend Position( "Bottom" ),
    Variables( X( :age ), Y( :height ), Y( :weight ) ),
    Elements( Position( 1, 1 ), Box Plot( X, Y, Legend( 9 ), Name( "5 Number Summary" )(1) ) ),
    Elements( Position( 1, 2 ), Box Plot( X, Y, Legend( 10 ), Name( "5 Number Summary" )(1) ) )
);

Code Explanation:

1. Open data table.
2. Launch Graph Builder.
3. Set window size.
4. Hide control panel.
5. Position legend at bottom.
6. Assign variables: age, height, weight.
7. Add first box plot element.
8. Configure first box plot for height.
9. Add second box plot element.
10. Configure second box plot for weight.

Example 1005

Summary: Creates a box plot with 5-number summary to visualize the relationship between Heart History and Smoking History, utilizing Graph Builder.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 531, 398 ),
    Show Control Panel( 0 ),
    Variables( X( :Heart History ), Group Y( :Smoking History ) ),
    Elements( Box Plot( X, Legend( 11 ), Name( "5 Number Summary" )(1) ) )
);

Code Explanation:

1. Open data table;
2. Launch Graph Builder.
3. Set window size 531x398.
4. Hide control panel.
5. Assign Heart History to X.
6. Assign Smoking History to Group Y.
7. Add Box Plot element.
8. Use 5 Number Summary.
9. Set legend index 11.
10. Label element "5 Number Summary".

Example 1006

Summary: Creates a box plot with 5-number summary to visualize the relationship between Lot Acceptance and Dissolution using Graph Builder.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 422, 337 ),
    Show Control Panel( 0 ),
    Variables( X( :Lot Acceptance ), Y( :Dissolution ) ),
    Elements( Box Plot( X, Y, Legend( 4 ), Name( "5 Number Summary" )(1) ) )
);

Code Explanation:

1. Open data table;
2. Launch Graph Builder.
3. Set window size.
4. Hide control panel.
5. Assign X variable.
6. Assign Y variable.
7. Add box plot element.
8. Configure legend position.
9. Display 5-number summary.
10. Name the element.

Example 1007

Summary: Creates multiple box plots with nested factors using Graph Builder, displaying standard deviation charts and adjusting scale configurations.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 534, 448 ),
    Show Control Panel( 0 ),
    Legend Position( "Bottom" ),
    Variables( X( :age ), Y( :height ), Y( :weight ) ),
    Elements( Position( 1, 1 ), Box Plot( X, Y, Legend( 9 ), Name( "5 Number Summary" )(1) ) ),
    Elements( Position( 1, 2 ), Box Plot( X, Y, Legend( 10 ), Name( "5 Number Summary" )(1) ) )
);
Open("data_table.jmp");
Graph Builder(
    Size( 531, 398 ),
    Show Control Panel( 0 ),
    Variables( X( :Heart History ), Group Y( :Smoking History ) ),
    Elements( Box Plot( X, Legend( 11 ), Name( "5 Number Summary" )(1) ) )
);
Open("data_table.jmp");
Graph Builder(
    Size( 422, 337 ),
    Show Control Panel( 0 ),
    Variables( X( :Lot Acceptance ), Y( :Dissolution ) ),
    Elements( Box Plot( X, Y, Legend( 4 ), Name( "5 Number Summary" )(1) ) )
);
Open("data_table.jmp");
Graph Builder(
    Size( 622, 445 ),
    Show Control Panel( 0 ),
    Show Legend( 0 ),
    Show Footer( 0 ),
    Variables( X( :Causes ), Y( :Time Cycles ) ),
    Elements( Box Plot( X, Y, Legend( 16 ), Name( "5 Number Summary" )(1) ) ),
    SendToReport( Dispatch( {}, "Causes", ScaleBox, {Min( -0.48211091234347 ), Max( 9.51788908765653 ), Inc( 1 ), Minor Ticks( 0 )} ) )
);

Code Explanation:

1. Open data_table data
2. Create Graph Builder window.
3. Set size to 534x448.
4. Hide control panel.
5. Set legend position to bottom.
6. Add age to X axis.
7. Add height and weight to Y axes.
8. Create box plot for height.
9. Create box plot for weight.
10. Open data_table data
11. Create Graph Builder window.
12. Set size to 531x398.
13. Hide control panel.
14. Add Heart History to X axis.
15. Add Smoking History to Group Y.
16. Create box plot.
17. Open data_table data
18. Create Graph Builder window.
19. Set size to 422x337.
20. Hide control panel.
21. Add Lot Acceptance to X axis.
22. Add Dissolution to Y axis.
23. Create box plot.
24. Open data_table data
25. Create Graph Builder window.
26. Set size to 622x445.
27. Hide control panel and legend.
28. Hide footer.
29. Add Causes to X axis.
30. Add Time Cycles to Y axis.
31. Create box plot.
32. Adjust scale for Causes.

Example 1008

Summary: Creates a box plot variability chart with nested factors using Graph Builder, displaying standard deviation charts.

Code:

dt = Open("data_table.jmp");
gb = dt << Graph Builder(
    Size( 570, 509 ),
    Show Control Panel( 0 ),
    Variables( X( :age ), Y( :height ) ),
    Elements( Box Plot( X, Y, Legend( 8 ) ) )
);
rgb = gb << report;
bps = rgb[Frame Box( 1 )] << Find Seg( Box Plot Seg( "Box Plot (12)" ) );

Code Explanation:

1. Open data table.
2. Create Graph Builder object.
3. Set size and control panel visibility.
4. Define variables for X and Y axes.
5. Add box plot element to graph.
6. Retrieve report from Graph Builder.
7. Access frame box in report.
8. Find box plot segment.
9. No further action specified.

Example 1009

Summary: Creates a box plot graph with nested factors, utilizing Graph Builder to display standard deviation charts.

Code:

dt = Open("data_table.jmp");
gb = dt << Graph Builder(
    Size( 570, 509 ),
    Show Control Panel( 0 ),
    Variables( X( :age ), Y( :height ) ),
    Elements( Box Plot( X, Y, Legend( 8 ) ) )
);
rgb = gb << report;
bps = rgb[Frame Box( 1 )] << Find Seg( Box Plot Seg( "Box Plot (12)" ) );
bps << Set Median Line Style( "Dotted" );

Code Explanation:

1. Open data table.
2. Create Graph Builder object.
3. Set size of graph.
4. Hide control panel.
5. Define X and Y variables.
6. Add box plot element.
7. Generate graph report.
8. Locate frame box.
9. Find box plot segment.
10. Set median line style.

Example 1010

Summary: Creates a variability chart with nested factors using Graph Builder, displaying standard deviation charts and box plots with jitter and outliers.

Code:

Open("data_table.jmp");
Graph Builder(
    Show Control Panel( 0 ),
    Variables( X( :Species ), Y( :Petal length ) ),
    Elements(
        Box Plot( X, Y, Legend( 5 ), Jitter( 1 ), Outliers( 1 ), Box Style( "Thin" ) ),
        Contour( X, Y, Legend( 6 ), Number of Levels( 0 ) )
    )
);

Code Explanation:

1. Open data table;
2. Launch Graph Builder.
3. Hide control panel.
4. Set X variable: Species.
5. Set Y variable: Petal length.
6. Add box plot element.
7. Enable jitter for box plot.
8. Show outliers in box plot.
9. Use thin box style.
10. Add contour element without levels.

Example 1011

Summary: Creates a box plot variability chart with nested factors, utilizing Graph Builder to display standard deviation charts for Japan, Other, and USA.

Code:

Open("data_table.jmp");
Graph Builder(
    Show Control Panel( 0 ),
    Variables( X( :Country ), Y( :Turning Circle ) ),
    Elements( Box Plot( X, Y, Legend( 4 ) ) ),
    SendToReport(
        Dispatch( {}, "Graph Builder", FrameBox,
            {DispatchSeg(
                Box Plot Seg( "Box Plot (Japan)" ),
                {Line Color( "Medium Light Cyan" ), Line Width( 3 ), Fill Color( "Medium Light Yellow" ), Fill( 0 )}
            ), DispatchSeg(
                Box Plot Seg( "Box Plot (Other)" ),
                {Line Color( "Medium Light Purple" ), Line Width( 3 ), Fill Color( "Medium Light Purple" ), Fill( 0 )}
            ), DispatchSeg( Box Plot Seg( "Box Plot (USA)" ), {Line Color( "Green" ), Line Width( 3 )} )}
        )
    )
);

Code Explanation:

1. Open data table;
2. Launch Graph Builder.
3. Hide control panel.
4. Set X variable to Country.
5. Set Y variable to Turning Circle.
6. Add box plot element.
7. Customize Japan box plot colors.
8. Customize Other box plot colors.
9. Customize USA box plot colors.

Example 1012

Summary: Creates a variability chart with nested factors using operator and part configurations, displaying standard deviation charts in Graph Builder.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 483, 462 ),
    Show Control Panel( 0 ),
    Variables( X( :Manufacturer ), Y( :Calories ), Color( :Sodium, Summary Statistic( "Sum" ) ) ),
    Elements( Box Plot( X, Y, Legend( 17 ) ) ),
    SendToReport(
        Dispatch( {}, "Graph Builder", FrameBox,
            Add Pin Annotation(
                Seg( Box Plot Seg( 2 ) ),
                Index( {1, 1} ),
                Index Row( {1, 1} ),
                UniqueID( 867454849 ),
                FoundPt( {179, 268} ),
                Origin( {1.04929577464789, 116.453475935829} ),
                Offset( {101, 77} ),
                Tag Line( 1 )
            )
        )
    )
);

Code Explanation:

1. Open data_table data
2. Create Graph Builder window.
3. Set window size to 483x462.
4. Hide control panel.
5. Assign variables: X=Manufacturer, Y=Calories, Color=Sodium.
6. Use Sum as summary statistic for Sodium.
7. Add Box Plot element.
8. Configure legend for Box Plot.
9. Add pin annotation to graph.
10. Position annotation on specific box plot segment.

Example 1013

Summary: Creates a variability chart with nested factors using Graph Builder, displaying standard deviation charts and configuring box plot settings.

Code:

Open("data_table.jmp");
Graph Builder(
    Show Control Panel( 0 ),
    Variables( Y( :Dose ), Frequency( :Count ) ),
    Elements( Box Plot( Y, Legend( 3 ) ), Caption Box( Y, Legend( 4 ) ) ),
    SendToReport(
        Dispatch( {}, "Dose", ScaleBox, {Format( "Fixed Dec", 9, 1 ), Min( 0 ), Max( 5 ), Inc( 0.5 ), Minor Ticks( 0 )} ),
        Dispatch( {}, "Graph Builder", FrameBox,
            {DispatchSeg( Box Plot Seg( 1 ), {Box Type( "Outlier" ), Confidence Diamond( 1 ), Shortest Half Bracket( 1 )} )}
        )
    )
);

Code Explanation:

1. Open data table;
2. Create Graph Builder object.
3. Hide control panel.
4. Set Y variable to Dose.
5. Set Frequency variable to Count.
6. Add Box Plot element.
7. Add Caption Box element.
8. Format Dose scale.
9. Configure Box Plot settings.
10. Display report.

Example 1014

Summary: Creates a box plot chart with nested factors, displaying standard deviation charts for age and weight data, while hiding selected rows.

Code:

dt = Open("data_table.jmp");
dt << select where( :age == 14 & :sex == "F" );
dt << hide;
dt << clear select;
Graph Builder(
    Size( 508, 382 ),
    Show Control Panel( 0 ),
    Variables( X( :age ), Y( :weight ), Overlay( :sex ) ),
    Elements( Box Plot( X, Y, Legend( 7 ) ) )
);

Code Explanation:

1. Open data table.
2. Select rows where age is 14 and sex is F.
3. Hide selected rows.
4. Clear selection.
5. Create Graph Builder object.
6. Set size to 508x382.
7. Hide control panel.
8. Set X variable to age.
9. Set Y variable to weight.
10. Add sex overlay, box plot element.

Example 1015

Summary: Creates a box plot chart with nested factors using Graph Builder, displaying standard deviation charts and customizing legend properties.

Code:

Open("data_table.jmp");
Graph Builder(
    Show Control Panel( 0 ),
    Variables( X( :age ), Y( :height ) ),
    Elements( Box Plot( X, Y, Legend( 4 ) ) ),
    SendToReport( Dispatch( {}, "400", ScaleBox, {Legend Model( 4, Properties( 0, {Fill Color( 4 ), Fill Pattern( "checker" )} ) )} ) )
);

Code Explanation:

1. Open data table;
2. Launch Graph Builder.
3. Hide control panel.
4. Set X variable to age.
5. Set Y variable to height.
6. Add box plot element.
7. Assign legend to box plot.
8. Send report message.
9. Dispatch to scale box.
10. Modify legend properties.

Example 1016

Summary: Creates a box plot to visualize the distribution of Carat Weight by Price, utilizing Graph Builder.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 587, 396 ),
    Show Control Panel( 0 ),
    Variables( Y( :Carat Weight ), Group X( :Price ) ),
    Elements( Box Plot( Y, Legend( 4 ) ) )
);

Code Explanation:

1. Open data table;
2. Create Graph Builder.
3. Set size to 587x396.
4. Hide control panel.
5. Set Y variable to Carat Weight.
6. Set Group X variable to Price.
7. Add Box Plot element.
8. Assign legend to 4th position.

Example 1017

Summary: Creates a box plot chart with jitter and outliers to visualize the relationship between age, height, and sex in a dataset.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 450, 320 ),
    Show Control Panel( 0 ),
    Variables( X( :age ), Y( :height ), Group X( :sex ), Overlay( :sex ) ),
    Elements( Box Plot( X, Y, Legend( 17 ), Jitter( 1 ), Outliers( 1 ) ) )
);

Code Explanation:

1. Open data table;
2. Create Graph Builder window.
3. Set window size.
4. Hide control panel.
5. Define X variable: age.
6. Define Y variable: height.
7. Group X by sex.
8. Overlay by sex.
9. Add box plot element.
10. Enable jitter and outliers.

Example 1018

Summary: Creates a box plot chart with nested factors using Graph Builder, configuring style and display options.

Code:

Open("data_table.jmp");
gb = Graph Builder(
    Show Control Panel( 0 ),
    Variables( X( :Species ), Y( :Sepal length ), Color( :Species ) ),
    Elements(
        Box Plot( X, Y, Legend( 4 ), Box Style( "Solid" ), Notched( 1 ), Fences( 0 ), Shortest Half( 1 ), Shortest Half Color( "Black" ) )
    )
);
gb << save journal( "$temp\JMP19450.jrn" );

Code Explanation:

1. Open data table;
2. Create Graph Builder object.
3. Hide control panel.
4. Set X variable to Species.
5. Set Y variable to Sepal length.
6. Set color variable to Species.
7. Add Box Plot element.
8. Configure Box Plot style.
9. Enable notches.
10. Disable fences.
11. Enable shortest half.
12. Set shortest half color to Black.
13. Save graph to journal.

Example 1019

Summary: Creates a box plot to visualize sepal length by species, utilizing Graph Builder and configuring various style options.

Code:

Open("data_table.jmp");
gb = Graph Builder(
    Show Control Panel( 0 ),
    Variables( X( :Species ), Y( :Sepal length ), Color( :Species ) ),
    Elements(
        Box Plot( X, Y, Legend( 4 ), Box Style( "Solid" ), Notched( 1 ), Fences( 0 ), Shortest Half( 1 ), Shortest Half Color( "Black" ) )
    )
);
gb << save journal( "$temp\JMP19450.jrn" );
Open( "$temp\JMP19450.jrn" );

Code Explanation:

1. Open data table;
2. Create Graph Builder object.
3. Hide control panel.
4. Set X variable: Species.
5. Set Y variable: Sepal length.
6. Color by Species.
7. Add Box Plot element.
8. Configure Box Plot style.
9. Save journal to temp.
10. Open saved journal.

Example 1020

Summary: Creates three Graph Builder windows with box plots to visualize the relationship between age, height, and weight, with varying legend positions.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 534, 448 ),
    Show Control Panel( 0 ),
    Legend Position( "Inside Left" ),
    Variables( X( :age ), Y( :height ), Y( :weight ) ),
    Elements( Position( 1, 1 ), Box Plot( X, Y, Legend( 9 ) ) ),
    Elements( Position( 1, 2 ), Box Plot( X, Y, Legend( 10 ) ) )
);
Graph Builder(
    Size( 534, 448 ),
    Show Control Panel( 0 ),
    Legend Position( "Inside Right" ),
    Variables( X( :age ), Y( :height ), Y( :weight ) ),
    Elements( Position( 1, 1 ), Box Plot( X, Y, Legend( 9 ) ) ),
    Elements( Position( 1, 2 ), Box Plot( X, Y, Legend( 10 ) ) )
);
Graph Builder(
    Size( 534, 448 ),
    Show Control Panel( 0 ),
    Legend Position( "Right" ),
    Variables( X( :age ), Y( :height ), Y( :weight ) ),
    Elements( Position( 1, 1 ), Box Plot( X, Y, Legend( 9 ) ) ),
    Elements( Position( 1, 2 ), Box Plot( X, Y, Legend( 10 ) ) )
);

Code Explanation:

1. Open data table;
2. Create first Graph Builder window.
3. Set size to 534x448.
4. Hide control panel.
5. Set legend position inside left.
6. Assign variables age, height, weight.
7. Add first box plot element.
8. Add second box plot element.
9. Create second Graph Builder window.
10. Set legend position inside right.
11. Create third Graph Builder window.
12. Set legend position right.

Example 1021

Summary: Creates multiple box plot charts with nested factors using Graph Builder, displaying standard deviation charts for each configuration.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 534, 448 ),
    Show Control Panel( 0 ),
    Legend Position( "Inside Left" ),
    Variables( X( :age ), Y( :height ), Y( :weight ) ),
    Elements( Position( 1, 1 ), Box Plot( X, Y, Legend( 9 ) ) ),
    Elements( Position( 1, 2 ), Box Plot( X, Y, Legend( 10 ) ) )
);
Graph Builder(
    Size( 534, 448 ),
    Show Control Panel( 0 ),
    Legend Position( "Inside Right" ),
    Variables( X( :age ), Y( :height ), Y( :weight ) ),
    Elements( Position( 1, 1 ), Box Plot( X, Y, Legend( 9 ) ) ),
    Elements( Position( 1, 2 ), Box Plot( X, Y, Legend( 10 ) ) )
);
Graph Builder(
    Size( 534, 448 ),
    Show Control Panel( 0 ),
    Legend Position( "Right" ),
    Variables( X( :age ), Y( :height ), Y( :weight ) ),
    Elements( Position( 1, 1 ), Box Plot( X, Y, Legend( 9 ) ) ),
    Elements( Position( 1, 2 ), Box Plot( X, Y, Legend( 10 ) ) )
);
Graph Builder(
    Size( 534, 448 ),
    Show Control Panel( 0 ),
    Legend Position( "Bottom" ),
    Variables( X( :age ), Y( :height ), Y( :weight ) ),
    Elements( Position( 1, 1 ), Box Plot( X, Y, Legend( 9 ) ) ),
    Elements( Position( 1, 2 ), Box Plot( X, Y, Legend( 10 ) ) )
);

Code Explanation:

1. Open data table.
2. Create Graph Builder window.
3. Set window size.
4. Hide control panel.
5. Place legend inside left.
6. Define X and Y variables.
7. Add first box plot element.
8. Add second box plot element.
9. Repeat steps 2-8 for inside right legend.
10. Repeat steps 2-8 for right legend.
11. Repeat steps 2-8 for bottom legend.

Example 1022

Summary: Creates a variability chart with nested factors using Graph Builder, displaying box plots and contours to analyze relationships between Sex, Height, and Age.

Code:

Open("data_table.jmp");
gb = Graph Builder(
    show control panel( 0 ),
    Variables( X( :Sex ), Y( :Height ), Group X( :Age ) ),
    Elements( Box Plot( X, Y ), Contour( X, Y ) )
);
gb << Lock Scales( 1 );

Code Explanation:

1. Open data table.
2. Create Graph Builder object.
3. Hide control panel.
4. Set X variable to Sex.
5. Set Y variable to Height.
6. Group X by Age.
7. Add Box Plot element.
8. Add Contour element.
9. Lock scales for consistency.

Example 1023

Summary: Creates a variability chart with nested factors using Graph Builder, and displays standard deviation charts.

Code:

dt = Open("data_table.jmp");
gb = Graph Builder(
    show control panel( 0 ),
    Variables( X( :Sex ), Y( :Height ), Group X( :Age ) ),
    Elements( Box Plot( X, Y ), Contour( X, Y ) )
);
gb << Lock Scales( 1 );
df = dt << Data Filter( Add Filter( columns( :age ), Where( :age == {14, 15, 16, 17} ) ), Mode( Include( 1 ) ) );

Code Explanation:

1. Open data table.
2. Create Graph Builder object.
3. Hide control panel.
4. Set X, Y, and Group X variables.
5. Add Box Plot and Contour elements.
6. Lock scales on graph.
7. Create Data Filter object.
8. Add age filter for specific values.
9. Set filter mode to include.

Example 1024

Summary: Creates a box plot chart with nested factors, displaying standard deviation charts for analysis.

Code:

Open("data_table.jmp");
Graph Builder(
    Show Control Panel( 0 ),
    Size( 800, 656 ),
    Variables( X( :family cars ), Y( :height ), Group Y( :sex ), Overlay( :age ) ),
    Elements( Box Plot( X, Y, Legend( 27 ) ) )
);

Code Explanation:

1. Open data table;
2. Launch Graph Builder.
3. Hide control panel.
4. Set window size.
5. Define X variable.
6. Define Y variable.
7. Group Y by sex.
8. Overlay by age.
9. Add box plot element.
10. Configure legend position.

Example 1025

Summary: Creates a box plot chart with nested factors using Graph Builder, displaying standard deviation charts and color-coded by species.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 522, 450 ),
    Show Control Panel( 0 ),
    Variables( X( :Species ), Y( :Sepal length ), Color( :Species ) ),
    Elements(
        Box Plot( X, Y, Legend( 4 ), Box Style( "Solid" ), Notched( 1 ), Fences( 0 ), Shortest Half( 1 ), Shortest Half Color( "Black" ) )
    )
);

Code Explanation:

1. Open data table;
2. Create Graph Builder window.
3. Set window size to 522x450.
4. Hide control panel.
5. Assign Species to X-axis.
6. Assign Sepal length to Y-axis.
7. Color by Species.
8. Add Box Plot element.
9. Use X and Y variables.
10. Display legend for box plot.

Example 1026

Summary: Creates a box plot variability chart with nested factors using Graph Builder, showcasing standard deviation charts.

Code:

Open("data_table.jmp");
Graph Builder( Size( 479, 372 ), Show Control Panel( 0 ), Variables( X( :sex ), Y( :height ) ), Elements( Box Plot( Y ) ) );

Code Explanation:

1. Open data table;
2. Launch Graph Builder.
3. Set window size.
4. Hide control panel.
5. Assign X variable.
6. Assign Y variable.
7. Add box plot element.

Example 1027

Summary: Creates a box plot graph with nested factors using Graph Builder, displaying standard deviation charts and controlling panel visibility.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 495, 381 ),
    Show Control Panel( 0 ),
    Variables( X( :age ), Y( :height ), Overlay( :sex ) ),
    Elements( Box Plot( X, Y, Legend( 8 ) ) )
);

Code Explanation:

1. Open data table.
2. Create Graph Builder object.
3. Set window size.
4. Hide control panel.
5. Define X variable.
6. Define Y variable.
7. Define overlay variable.
8. Add box plot element.
9. Set legend position.
10. Display graph.

Example 1028

Summary: Creates a variability chart with nested factors using Graph Builder, featuring box plots and standard deviation charts.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 470, 405 ),
    Show Control Panel( 0 ),
    Variables(
        X( :Sepal length ),
        X( :Sepal width, Position( 1 ) ),
        X( :Petal length, Position( 1 ) ),
        X( :Petal width, Position( 1 ) ),
        Overlay( :Species )
    ),
    Elements( Box Plot( X( 1 ), X( 2 ), X( 3 ), X( 4 ), Legend( 18 ) ) ),
    SendToReport( Dispatch( {}, "Graph Builder", FrameBox, {DispatchSeg( ParallelAxisSeg( 1 ), {Transparency( 0.25 )} )} ) )
);

Code Explanation:

1. Open data table;
2. Create Graph Builder window.
3. Set window size.
4. Hide control panel.
5. Define X variables.
6. Define overlay variable.
7. Add box plot element.
8. Customize box plot appearance.
9. Adjust transparency for parallel axis.
10. Finalize graph settings.

Example 1029

Summary: Creates a box plot variability chart with nested factors using Graph Builder, combining Sepal and Petal lengths while aligning parallel axes and overlaying by Species.

Code:

Open("data_table.jmp");
Graph Builder(
    Show Control Panel( 0 ),
    Variables(
        X( :Sepal length, Combine( "Parallel Merged" ) ),
        X( :Petal length, Position( 1 ), Combine( "Parallel Merged" ) ),
        Overlay( :Species )
    ),
    Elements( Box Plot( X( 1 ), X( 2 ), Legend( 18 ), Box Placement( "Align" ) ) )
);

Code Explanation:

1. Open data table;
2. Launch Graph Builder.
3. Hide control panel.
4. Set X variables.
5. Combine Sepal and Petal lengths.
6. Align parallel axes.
7. Overlay by Species.
8. Add Box Plot element.
9. Place Box Plot on X1.
10. Place Box Plot on X2.

Example 1030

Summary: Creates a variability chart with nested factors using Graph Builder, displaying standard deviation charts and configuring legend properties.

Code:

dt = Open("data_table.jmp");
Graph Builder(
    Size( 692, 366 ),
    Show Control Panel( 0 ),
    Variables( Y( :weight ), Y( :height, Position( 1 ) ), Overlay( :sex ), Color( :weight, Summary Statistic( "% of Total" ) ) ),
    Elements( Box Plot( Y( 1 ), Y( 2 ), Legend( 8 ) ) ),
    SendToReport(
        Dispatch( {}, "400", ScaleBox, {Legend Model( 8, Properties( 4, {gradient}, Item ID( "weight", 1 ) ) )} ),
        Dispatch( {}, "Graph Builder", FrameBox,
            Add Pin Annotation(
                Seg( Box Plot Seg( 3 ) ),
                Index( {1, 1} ),
                Index Row( {1, 1} ),
                UniqueID( -608920431 ),
                FoundPt( {400, 193} ),
                Origin( {0.0257410296411856, 113.520383282007} ),
                Offset( {30, -29} ),
                RightOfCenter( 1 ),
                Tag Line( 1 )
            )
        )
    )
);

Code Explanation:

1. Open data table.
2. Create Graph Builder window.
3. Set window size.
4. Hide control panel.
5. Define variables: Y(weight), Y(height), Overlay(sex), Color(weight).
6. Add box plot elements.
7. Send report commands.
8. Configure legend properties.
9. Add pin annotation to graph.
10. Position annotation on graph.

Example 1031

Summary: Creates a box plot with nested factors using Graph Builder, selecting female students aged 14 from a data table and displaying standard deviation charts.

Code:

dt = Open("data_table.jmp");
dt << select where( :age == 14 & :sex == "F" );
Graph Builder(
    Size( 508, 382 ),
    Show Control Panel( 0 ),
    Variables( X( :age ), Y( :weight ), Overlay( :sex ) ),
    Elements( Box Plot( X, Y, Legend( 7 ) ) )
);

Code Explanation:

1. Open data table.
2. Select female students aged 14.
3. Launch Graph Builder.
4. Set graph size.
5. Hide control panel.
6. Assign variables to axes.
7. Add overlay variable.
8. Create box plot element.
9. Configure legend position.
10. Display graph.

Example 1032

Summary: Creates a box plot chart to visualize height data for individuals aged 14, utilizing Graph Builder and customizing box plots for specific age groups.

Code:

dt = Open("data_table.jmp");
dt << select where( :age == 14 );
Graph Builder(
    Size( 281, 239 ),
    Show Control Panel( 0 ),
    Variables( X( :age ), Y( :height ) ),
    Elements( Box Plot( X, Y, Legend( 4 ), Outliers( 0 ) ) ),
    SendToReport(
        Dispatch( {}, "Graph Builder", FrameBox,
            {DispatchSeg( Box Plot Seg( "Box Plot (14)" ), {Fill Color( "Light Blue" ), Fill( 1 )} ),
            DispatchSeg( Box Plot Seg( "Box Plot (15)" ), {Shortest Half Bracket( 1 ), Fill Color( "Light Green" ), Fill( 1 )} )}
        )
    )
);

Code Explanation:

1. Open data table;
2. Select rows where age is 14.
3. Create Graph Builder window.
4. Set graph size to 281x239.
5. Hide control panel.
6. Set X variable to age.
7. Set Y variable to height.
8. Add Box Plot element.
9. Customize Box Plot for age 14.
10. Customize Box Plot for age 15.

Example 1033

Summary: Creates a box plot graph with nested factors using Graph Builder, displaying standard deviation charts and controlling panel visibility.

Code:

dt = Open("data_table.jmp");
gb = dt << Graph Builder(
    Size( 528, 450 ),
    Show Control Panel( 0 ),
    Variables( X( :age ), Y( :height ), Color( :sex ) ),
    Elements( Box Plot( X, Y, Legend( 11 ), Shortest Half( 1 ) ) )
);

Code Explanation:

1. Open data table.
2. Create graph builder object.
3. Set graph size.
4. Hide control panel.
5. Define X variable.
6. Define Y variable.
7. Define color variable.
8. Add box plot element.
9. Set legend for box plot.
10. Enable shortest half option.

Example 1034

Summary: Creates a box plot with shortest half configuration to visualize data distribution for rows where age is 13, utilizing Graph Builder.

Code:

dt = Open("data_table.jmp");
gb = dt << Graph Builder(
    Size( 528, 450 ),
    Show Control Panel( 0 ),
    Variables( X( :age ), Y( :height ), Color( :sex ) ),
    Elements( Box Plot( X, Y, Legend( 11 ), Shortest Half( 1 ) ) )
);
dt << Select where( :age == 13 );

Code Explanation:

1. Open data table.
2. Create Graph Builder object.
3. Set graph size.
4. Hide control panel.
5. Define X, Y, and color variables.
6. Add box plot element.
7. Configure box plot for shortest half.
8. Select rows where age is 13.

Example 1035

Summary: Creates a box plot chart with nested factors using Graph Builder, displaying standard deviation charts and configuring legend settings.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 528, 447 ),
    Show Control Panel( 0 ),
    Variables( X( :age ), Y( :height ), Overlay( :sex ) ),
    Elements( Box Plot( X, Y, Legend( 8 ) ) )
);

Code Explanation:

1. Open data table;
2. Create Graph Builder object.
3. Set window size.
4. Hide control panel.
5. Define X variable.
6. Define Y variable.
7. Define overlay variable.
8. Add box plot element.
9. Position legend.

Example 1036

Summary: Creates a box plot chart with nested factors using Graph Builder, displaying standard deviation charts for analysis.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 531, 450 ),
    Show Control Panel( 0 ),
    Variables( X( :Cut, Size By( "Count" ) ), Y( :Carat Weight ), Color( :Cut ) ),
    Elements( Box Plot( X, Y, Legend( 4 ) ) )
);

Code Explanation:

1. Open data table.
2. Create Graph Builder window.
3. Set window size.
4. Hide control panel.
5. Define X variable.
6. Define Y variable.
7. Define color variable.
8. Add box plot element.
9. Set X axis to Cut.
10. Set Y axis to Carat Weight.

Example 1037

Summary: Creates a box plot graph with nested factors using Graph Builder, customizing fill colors and width proportion.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 704, 597 ),
    Show Control Panel( 0 ),
    Variables( X( :age ), Y( :height ) ),
    Elements( Box Plot( X, Y, Legend( 8 ), Jitter( "None" ), Width Proportion( 1.5 ) ) ),
    SendToReport(
        Dispatch( {}, "Graph Builder", FrameBox,
            {DispatchSeg( Box Plot Seg( "Box Plot (12)" ), {Fill Color( "Light Green" ), Fill( 1 )} ),
            DispatchSeg( Box Plot Seg( "Box Plot (13)" ), {Fill Color( "Medium Light Cyan" ), Fill( 1 )} ),
            DispatchSeg( Box Plot Seg( "Box Plot (14)" ), {Fill Color( "Medium Light Blue" ), Fill( 1 )} ),
            DispatchSeg( Box Plot Seg( "Box Plot (15)" ), {Fill Color( "Medium Light Purple" ), Fill( 1 )} ),
            DispatchSeg( Box Plot Seg( "Box Plot (16)" ), {Fill Color( "Medium Light Magenta" ), Fill( 1 )} ),
            DispatchSeg( Box Plot Seg( "Box Plot (17)" ), {Fill Color( "Fuchsia" ), Fill( 1 )} )}
        )
    )
);

Code Explanation:

1. Open data table;
2. Create Graph Builder window.
3. Set graph size.
4. Hide control panel.
5. Assign X and Y variables.
6. Add box plot element.
7. Set box width proportion.
8. Customize box colors.
9. Apply fill settings.
10. Display graph.

Example 1038

Summary: Creates a box plot chart with nested factors using Graph Builder, displaying standard deviation charts and controlling window size.

Code:

dt = Open("data_table.jmp");
Graph Builder(
    Size( 281, 239 ),
    Show Control Panel( 0 ),
    Variables( X( :age ), Y( :height ) ),
    Elements( Box Plot( X, Y, Legend( 4 ), Outliers( 0 ), Width Proportion( 0.7 ) ) )
);

Code Explanation:

1. Open data table;
2. Launch Graph Builder.
3. Set window size.
4. Hide control panel.
5. Assign age to X-axis.
6. Assign height to Y-axis.
7. Add box plot element.
8. Include legend.
9. Suppress outliers.
10. Set width proportion.

Example 1039

Summary: Creates a box plot variability chart with nested factors using Graph Builder, displaying standard deviation charts.

Code:

Open("data_table.jmp");
gb = Graph Builder( Show Control Panel( 0 ), Variables( X( :X ), Y( :Y ), Color( :Z ) ), Elements( Box Plot( X, Y ) ) );
frame = (gb << Report)[FrameBox( 1 )];
seg = frame << Find Seg( Box Plot Seg( 1 ) );

Code Explanation:

1. Open data table;
2. Create Graph Builder object.
3. Set variables for X, Y, Color.
4. Add Box Plot element.
5. Access first FrameBox.
6. Find Box Plot segment.

Example 1040

Summary: Creates a box plot with nested factors using Graph Builder, applying a Viridis color theme gradient to visualize data.

Code:

Open("data_table.jmp");
gb = Graph Builder( Show Control Panel( 0 ), Variables( X( :X ), Y( :Y ), Color( :Z ) ), Elements( Box Plot( X, Y ) ) );
frame = (gb << Report)[FrameBox( 1 )];
seg = frame << Find Seg( Box Plot Seg( 1 ) );
seg << Set Gradient( Color Theme( "Viridis" ) );

Code Explanation:

1. Open data table;
2. Create Graph Builder object.
3. Hide control panel.
4. Set X, Y, and Color variables.
5. Add Box Plot element.
6. Access first frame box.
7. Find first box plot segment.
8. Apply Viridis color theme gradient.

Example 1041

Summary: Creates a variability chart with nested factors using Graph Builder, displaying standard deviation charts and box plots.

Code:

dt = Open("data_table.jmp");
gb = Graph Builder(
    Size( 450, 320 ),
    Show Control Panel( 0 ),
    Variables( X( :POP ), X( :PM10 ), Y( :Region ) ),
    Elements( Position( 1, 1 ), Bar( X, Y ) ),
    Elements( Position( 2, 1 ), Box Plot( X, Y, Jitter( 0 ), Outliers( 1 ) ) )
);

Code Explanation:

1. Open data table;
2. Create Graph Builder object.
3. Set graph size.
4. Hide control panel.
5. Define variables for X, X, Y.
6. Add bar element to position 1,1.
7. Add box plot element to position 2,1.
8. Disable jitter in box plot.
9. Enable outliers in box plot.
10. Display graph.

Example 1042

Summary: Creates a box plot chart with nested factors using Graph Builder, displaying standard deviation charts for sex and age.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 626, 417 ),
    Show Control Panel( 0 ),
    Variables( X( :sex ), X( :age, Position( 1 ) ) ),
    Elements( Box Plot( X( 2 ), X( 1 ), Legend( 6 ) ) )
);

Code Explanation:

1. Open data_table data
2. Launch Graph Builder.
3. Set window size to 626x417.
4. Hide control panel.
5. Assign sex to X-axis.
6. Assign age to second X-axis position.
7. Create box plot element.
8. Set box plot X to age.
9. Set box plot Y to sex.
10. Add legend to box plot.

Example 1043

Summary: Creates a box plot with 5-number summary to visualize height data, utilizing Graph Builder and specifying Y variable.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 534, 420 ),
    Show Control Panel( 0 ),
    Show Legend( 0 ),
    Variables( Y( :height ) ),
    Elements( Box Plot( Y, Legend( 3 ), Name( "5 Number Summary" )(1) ) )
);

Code Explanation:

1. Open data table.
2. Launch Graph Builder.
3. Set window size.
4. Hide control panel.
5. Hide legend.
6. Specify Y variable.
7. Add box plot element.
8. Configure 5-number summary.
9. Display graph.

Example 1044

Summary: Creates a variability chart with nested factors using operator and part configurations, displaying standard deviation charts in Graph Builder.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 363, 323 ),
    Show Control Panel( 0 ),
    Show Legend( 0 ),
    Variables(
        Y( :Name( "Sales($M)" ) ),
        Y( :Name( "Profit($M)" ), Position( 1 ) ),
        Y( :Name( "#employees" ), Position( 1 ) ),
        Y( :Name( "Profits/emp" ), Position( 1 ) ),
        Y( :Name( "Assets($Mil.)" ), Position( 1 ) ),
        Y( :Name( "Sales/emp" ), Position( 1 ) ),
        Y( :Name( "Stockholder's Eq($Mil.)" ), Position( 1 ) )
    ),
    Elements( Box Plot( Y( 1 ), Y( 2 ), Y( 3 ), Y( 4 ), Y( 5 ), Y( 6 ), Y( 7 ), Legend( 3 ) ) )
);

Code Explanation:

1. Open data_table data
2. Create Graph Builder window.
3. Set window size 363x323.
4. Hide control panel.
5. Hide legend.
6. Define Y variables: Sales, Profit, Employees, Profits/emp, Assets, Sales/emp, Stockholder's Eq.
7. Position all Y variables on the left.
8. Add Box Plot element.
9. Include all 7 Y variables in Box Plot.
10. Set legend position to 3.

Example 1045

Summary: Creates a box plot variability chart with nested factors using Graph Builder, displaying standard deviation charts and customizing label row nesting.

Code:

dt = Open("data_table.jmp");
gb = Graph Builder(
    Size( 534, 458 ),
    Show Control Panel( 0 ),
    Variables( X( :Carrier Code ), Y( :Time ) ),
    Elements( Box Plot( X, Y, Legend( 3 ) ) ),
    SendToReport( Dispatch( {}, "Time", ScaleBox, {Label Row Nesting( 6 )} ) )
);

Code Explanation:

1. Open data table.
2. Create Graph Builder object.
3. Set graph size.
4. Hide control panel.
5. Assign X and Y variables.
6. Add box plot element.
7. Customize legend position.
8. Adjust label row nesting.

Example 1046

Summary: Creates a box plot chart with nested factors using Graph Builder, displaying Premium USD on the Y-axis and Zone and Age as X-axes.

Code:

dt = Open("data_table.jmp");
dt << Graph Builder(
    Size( 469, 301 ),
    Show Control Panel( 0 ),
    Show Legend( 0 ),
    Variables( X( :Zone ), X( :Age, Position( 1 ) ), Y( :Premium USD ) ),
    Elements( Box Plot( X( 2 ), X( 1 ), Y, Legend( 3 ) ) )
);

Code Explanation:

1. Open data table;
2. Create Graph Builder window.
3. Set window size 469x301.
4. Hide control panel.
5. Hide legend.
6. Assign Zone to X-axis.
7. Assign Age to second X-axis.
8. Assign Premium USD to Y-axis.
9. Add Box Plot element.
10. Configure Box Plot for variables.

Example 1047

Summary: Creates a variability chart with nested factors using Graph Builder, displaying standard deviation charts and box plots.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 528, 456 ),
    Show Control Panel( 0 ),
    Variables( X( :weight ), Y( :height ) ),
    Elements( Box Plot( X, Y, Legend( 5 ), Width Proportion( 5 ) ), Points( X, Y, Legend( 6 ) ) )
);

Code Explanation:

1. Open data table.
2. Launch Graph Builder.
3. Set window size.
4. Hide control panel.
5. Define X variable.
6. Define Y variable.
7. Add box plot element.
8. Set width proportion.
9. Add points element.
10. Display graph.

Example 1048

Summary: Creates a variability chart with nested factors using Graph Builder, displaying standard deviation charts and configuring box plots.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 325, 306 ),
    Show Control Panel( 0 ),
    Show Legend( 0 ),
    Variables( X( :Position ), Y( :Weight ), Overlay( :Position ) ),
    Elements( Box Plot( X, Y, Legend( 15 ) ) )
);

Code Explanation:

1. Open data table.
2. Create Graph Builder.
3. Set size 325x306.
4. Hide control panel.
5. Hide legend.
6. Set X variable: Position.
7. Set Y variable: Weight.
8. Overlay by Position.
9. Add Box Plot element.
10. Assign legend to 15.

Example 1049

Summary: Creates a box plot to visualize the relationship between age and weight, utilizing Graph Builder with Quantile box type.

Code:

dt = Open("data_table.jmp");
dt << select where( :age == 17 );
gb = Graph Builder(
    Size( 526, 448 ),
    Show Control Panel( 0 ),
    Variables( X( :age ), Y( :weight ) ),
    Elements( Box Plot( X, Y, Legend( 12 ), Box Type( "Quantile" ) ) )
);
gb << journal;

Code Explanation:

1. Open data table.
2. Select rows where age is 17.
3. Create Graph Builder object.
4. Set graph size.
5. Hide control panel.
6. Assign variables for X and Y.
7. Add box plot element.
8. Set box type to Quantile.
9. Generate journal from graph builder.

Example 1050

Summary: Creates a box plot chart with nested factors using Graph Builder, displaying standard deviation charts and enabling button box interaction.

Code:

Open("data_table.jmp");
Graph Builder(
    Show Control Panel( 0 ),
    Variables( X( :age ), Y( :height ), Y( :weight, Position( 1 ) ), Overlay( :sex ) ),
    Elements( Box Plot( X, Y( 1 ), Y( 2 ), Legend( 8 ) ) ),
    SendToReport( Dispatch( {}, "", ButtonBox, {Enabled( 1 )} ) )
);

Code Explanation:

1. Open data table;
2. Launch Graph Builder.
3. Hide control panel.
4. Set X variable: age.
5. Set Y variables: height, weight.
6. Position weight on Y-axis 1.
7. Overlay by sex.
8. Add box plot element.
9. Enable button box.
10. Display report.

Example 1051

Summary: Creates a box plot chart with nested factors, displaying standard deviation charts and enabling button box interaction.

Code:

Open("data_table.jmp");
Graph Builder(
    Show Control Panel( 0 ),
    Variables( X( :sex ), Y( :height ), Y( :weight, Position( 1 ) ), Overlay( :age ) ),
    Elements( Box Plot( X, Y( 1 ), Y( 2 ), Legend( 8 ) ) ),
    SendToReport( Dispatch( {}, "", ButtonBox, {Enabled( 1 )} ) )
);

Code Explanation:

1. Open data table;
2. Launch Graph Builder.
3. Hide control panel.
4. Set X variable to sex.
5. Set Y variables to height and weight.
6. Overlay age on graph.
7. Add box plot element.
8. Enable button box.
9. Display report.

Example 1052

Summary: Creates a box plot chart with nested factors using Graph Builder, displaying standard deviation charts and enabling button box interaction.

Code:

Open("data_table.jmp");
Graph Builder(
    Show Control Panel( 0 ),
    Variables( X( :sex ), Y( :height ), Overlay( :age ) ),
    Elements( Box Plot( X, Y, Legend( 8 ) ) ),
    SendToReport( Dispatch( {}, "", ButtonBox, {Enabled( 1 )} ) )
);

Code Explanation:

1. Open data table;
2. Launch Graph Builder.
3. Hide control panel.
4. Set X variable to sex.
5. Set Y variable to height.
6. Add age for overlay.
7. Create box plot element.
8. Enable button box.
9. Display graph.

Example 1053

Summary: Creates a box plot chart to visualize the relationship between Lot Acceptance and Dissolution, utilizing Graph Builder.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 422, 337 ),
    Show Control Panel( 0 ),
    Variables( X( :Lot Acceptance ), Y( :Dissolution ) ),
    Elements( Box Plot( X, Y, Legend( 4 ) ) )
);

Code Explanation:

1. Open data table.
2. Launch Graph Builder.
3. Set graph size.
4. Hide control panel.
5. Assign variables to axes.
6. Add box plot element.
7. Position legend.

Example 1054

Summary: Creates a box plot variability chart with nested factors using Graph Builder, configuring X and Y variables, and displaying standard deviation charts.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 594, 510 ),
    Show Control Panel( 0 ),
    Show Legend( 0 ),
    Show Footer( 0 ),
    Variables( X( :Causes ), Y( :Time Cycles ) ),
    Elements( Box Plot( X, Y, Legend( 16 ) ) ),
    SendToReport( Dispatch( {}, "Causes", ScaleBox, {Min( -0.48211091234347 ), Max( 9.51788908765653 ), Inc( 1 ), Minor Ticks( 0 )} ) )
);

Code Explanation:

1. Open data table;
2. Create Graph Builder window.
3. Set window size.
4. Hide control panel.
5. Hide legend.
6. Hide footer.
7. Define X and Y variables.
8. Add box plot element.
9. Configure X scale settings.
10. Configure Y scale settings.

Example 1055

Summary: Creates a box plot variability chart with nested factors using Graph Builder, displaying standard deviation charts and customizing legend position.

Code:

Open("data_table.jmp");
Graph Builder( Size( 528, 448 ), Show Control Panel( 0 ), Variables( X( :age ), Y( :height ) ), Elements( Box Plot( X, Y, Legend( 6 ) ) ) );

Code Explanation:

1. Open data table;
2. Launch Graph Builder.
3. Set window size.
4. Hide control panel.
5. Assign age to X axis.
6. Assign height to Y axis.
7. Add box plot element.
8. Customize legend position.

Example 1056

Summary: Creates two Graph Builder windows to visualize variability charts with nested factors, displaying standard deviation charts and customizing legend properties.

Code:

dt = Open("data_table.jmp");
Graph Builder(
    Size( 534, 448 ),
    Show Control Panel( 0 ),
    Variables( Y( :weight ), Overlay( :age ) ),
    Elements( Box Plot( Y, Legend( 13 ) ) ),
    SendToReport(
        Dispatch( {}, "400", ScaleBox, {Legend Model( 13, Properties( 0, {Marker( "Circle" ), Fill Color( 0 )} ) )} ),
        Dispatch( {}, "Graph Builder", FrameBox,
            Add Pin Annotation(
                Seg( Marker Seg( 1 ) ),
                Index( 0 ),
                Index Row( 2 ),
                UniqueID( 593275072 ),
                FoundPt( {600, 305} ),
                Origin( {0.0652173913043478, 128.24644549763} )
            )
        )
    )
);
Graph Builder(
    Size( 534, 463 ),
    Show Control Panel( 0 ),
    Variables( X( :sex ), Y( :weight ), Overlay( :age ) ),
    Elements( Points( X, Y, Legend( 12 ), Summary Statistic( "Sum" ) ) ),
    SendToReport(
        Dispatch( {}, "400", ScaleBox, {Legend Model( 12, Properties( 0, {Marker( "Circle" )} ) )} ),
        Dispatch( {}, "Graph Builder", FrameBox,
            Add Pin Annotation(
                Seg( Marker Seg( 1 ) ),
                Index( 0 ),
                Index Row( 0 ),
                UniqueID( 596372720 ),
                FoundPt( {449, 295} ),
                Origin( {0.00517598343685299, 504.176904176904} )
            )
        )
    )
);

Code Explanation:

1. Open data table.
2. Create graph builder window.
3. Set graph size.
4. Hide control panel.
5. Define Y variable as weight.
6. Overlay age variable.
7. Add box plot element.
8. Customize legend properties.
9. Add pin annotation to graph.
10. Create another graph builder window.
11. Set new graph size.
12. Hide control panel.
13. Define X variable as sex.
14. Define Y variable as weight.
15. Overlay age variable.
16. Add points element with summary statistic.
17. Customize legend properties.
18. Add pin annotation to new graph.

Example 1057

Summary: Creates a box plot graph with nested factors using Graph Builder, displaying standard deviation charts and legend properties.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 610, 466 ),
    Show Control Panel( 0 ),
    Show Legend( 1 ),
    Variables( X( :sex ), Y( :height ) ),
    Elements( Box Plot( X, Y, Legend( 20 ) ) ), 
);

Code Explanation:

1. Open data table;
2. Create new graph builder window.
3. Set window size.
4. Hide control panel.
5. Show legend.
6. Assign X variable.
7. Assign Y variable.
8. Add box plot element.
9. Set legend properties.
10. Display graph.

Example 1058

Summary: Creates a variability chart with nested factors using Graph Builder, displaying standard deviation charts and customizing legend properties.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 513, 333 ),
    Show Control Panel( 0 ),
    Show Legend( 0 ),
    Variables( X( :drug ), Y( :pain ) ),
    Elements( Points( X, Y, Legend( 3 ) ), Box Plot( X, Y, Legend( 4 ) ) ),
    SendToReport( Dispatch( {}, "400", ScaleBox, {Legend Model( 4, Properties( 0, {Line Color( 3 )} ) )} ) )
);

Code Explanation:

1. Open data table;
2. Create Graph Builder window.
3. Set window size.
4. Hide control panel.
5. Hide legend.
6. Assign variables to axes.
7. Add points element.
8. Add box plot element.
9. Customize legend properties.
10. Send report to display.

Example 1059

Summary: Creates a box plot graph with customized legend and background color using Graph Builder, displaying heights data from an open JMP data table.

Code:

dt under test = Open("data_table.jmp");
obj = Graph Builder(
    Show Control Panel( 0 ),
    Variables( X( :height ) ),
    Elements( Box Plot( X, Legend( 5 ), Box Style( "Solid" ) ) ),
    SendToReport(
        Dispatch( {}, "graph title", TextEditBox, {Set Text( "Heights" )} ),
        Dispatch( {}, "Y title", TextEditBox, {Set Wrap( 2 )} ),
        Dispatch( {}, "Graph Builder", FrameBox, {Background Color( 41 )} )
    )
);

Code Explanation:

1. Open data table.
2. Create Graph Builder object.
3. Hide control panel.
4. Set X variable to height.
5. Add box plot element.
6. Customize legend.
7. Set box style to solid.
8. Rename graph title.
9. Adjust Y axis title.
10. Change background color.

Example 1060

Summary: Creates a box plot and points chart to visualize variability in data with nested factors, utilizing Graph Builder's customization options.

Code:

dt under test = Open("data_table.jmp");
obj = Graph Builder(
    Show Control Panel( 0 ),
    Variables( X( :height ) ),
    Elements( Box Plot( X, Legend( 3 ), Box Type( "Quantile" ) ), Points( X, Legend( 4 ) ) ),
    SendToReport(
        Dispatch( {}, "400", ScaleBox, {Legend Model( 3, Properties( 0, {Line Color( 73 ), Line Width( 6 )} ) )} ),
        Dispatch( {}, "400", LegendBox, {Legend Position( {0, 1} )} ),
        Dispatch( {}, "Y title", TextEditBox, {Set Wrap( 2 )} ),
        Dispatch( {}, "Graph Builder", FrameBox, {Background Color( 68 )} )
    )
);

Code Explanation:

1. Open data table.
2. Create Graph Builder object.
3. Hide control panel.
4. Set X variable to height.
5. Add box plot element.
6. Add points element.
7. Customize box plot legend.
8. Set legend position.
9. Wrap Y title text.
10. Change background color.

Example 1061

Summary: Creates a box plot with nested factors using Graph Builder, displaying standard deviation charts and outliers.

Code:

dt under test = Open("data_table.jmp");
obj = Graph Builder(
    Show Control Panel( 0 ),
    Variables( X( :weight ), Y( :height ) ),
    Elements( Box Plot( X, Y, Legend( 3 ), Jitter( 1 ), Outliers( 1 ), Box Style( "Outlier" ) ) ),
    SendToReport( Dispatch( {}, "Graph Builder", OutlineBox, {Set Title( "Box Plot" )} ) )
);

Code Explanation:

1. Open data table.
2. Create Graph Builder object.
3. Hide control panel.
4. Set X variable.
5. Set Y variable.
6. Add box plot element.
7. Enable jitter.
8. Show outliers.
9. Set box style.
10. Set graph title.

Example 1062

Summary: Creates two graph builders with nested factors, displaying a heatmap and bar chart to visualize variability data.

Code:

dt = Open("data_table.jmp");
gb1 = dt << Graph Builder(
    Variables( X( :age ), Y( :weight ), Color( :height ) ),
    Elements( Heatmap( X, Y, Legend( 8 ), Label( "Label by Value" ), Label Format( "Scientific", 7 ) ) )
);
j1 = gb1 << journal;
gb1 << close window;
gb2 = dt << Graph Builder(
    Variables( X( :age ), Y( :weight ), Color( :height ) ),
    Elements( Bar( X, Y, Legend( 10 ), Label( "Label by Value" ), Label Format( "Fixed Dec", 6, 2 ) ) )
);
j2 = gb2 << journal;
gb2 << close window;

Code Explanation:

1. Open data table.
2. Create first graph builder object.
3. Set variables for heatmap.
4. Add heatmap element with custom label format.
5. Generate journal from first graph.
6. Close first graph window.
7. Create second graph builder object.
8. Set variables for bar chart.
9. Add bar element with custom label format.
10. Generate journal from second graph.

Example 1063

Summary: Creates three Graph Builders with nested factors using operator and part configurations, displaying standard deviation charts and journaling each graph.

Code:

dt2 = Open("data_table.jmp");
dt3 = Open("data_table.jmp");
gb3 = dt2 << Graph Builder(
    Variables( X( :Color ), Y( :Clarity ) ),
    Elements( Mosaic( X, Y, Legend( 7 ), Cell Labeling( "Label by Percent" ), Label Format( "Percent", 6, 2 ) ) )
);
j3 = gb3 << journal;
gb3 << close window;
gb4 = dt3 << Graph Builder(
    Variables( X( :age ), Y( :weight ) ),
    Elements(
        Pie(
            X,
            Y,
            Legend( 4 ),
            Summary Statistic( "Median" ),
            Label( "Label by Percent of Total Values" ),
            Label Format( "Percent", 10, 5 )
        )
    )
);
j4 = gb4 << journal;
gb4 << close window;
gb5 = dt3 << Graph Builder(
    Variables( X( :age ), Y( :weight ), Color( :height ) ),
    Elements(
        Treemap(
            X,
            Y,
            Legend( 6 ),
            Summary Statistic( "Mean" ),
            Color Value( 1 ),
            Size Value( 1 ),
            Color Label Format( "Fixed Dec", 10, 4 ),
            Size Label Format( "Fixed Dec", 6, 3 )
        )
    )
);
j5 = gb5 << journal;

Code Explanation:

1. Open data table;
2. Open data table;
3. Create Graph Builder for data_table.
4. Set X: Color, Y: Clarity.
5. Add Mosaic element.
6. Label cells by percent.
7. Format labels as percent.
8. Save graph as journal.
9. Close Graph Builder window.
10. Create Graph Builder for data_table.

Example 1064

Summary: Creates and displays various graph types, including heatmaps, bars, mosaic plots, and pie charts, using Graph Builder to visualize data from a JMP data table.

Code:

dt = Open("data_table.jmp");
gb1 = dt << Graph Builder(
    Variables( X( :age ), Y( :weight ), Color( :height ) ),
    Elements( Heatmap( X, Y, Legend( 8 ), Label( "Label by Value" ), Label Format( "Scientific", 7 ) ) )
);
j1 = gb1 << journal;
gb1 << close window;
gb2 = dt << Graph Builder(
    Variables( X( :age ), Y( :weight ), Color( :height ) ),
    Elements( Bar( X, Y, Legend( 10 ), Label( "Label by Value" ), Label Format( "Fixed Dec", 6, 2 ) ) )
);
j2 = gb2 << journal;
gb2 << close window;
dt2 = Open("data_table.jmp");
gb3 = dt2 << Graph Builder(
    Variables( X( :Color ), Y( :Clarity ) ),
    Elements( Mosaic( X, Y, Legend( 7 ), Cell Labeling( "Label by Percent" ), Label Format( "Percent", 6, 2 ) ) )
);
j3 = gb3 << journal;
gb3 << close window;
gb4 = dt << Graph Builder(
    Variables( X( :age ), Y( :weight ) ),
    Elements(
        Pie(
            X,
            Y,
            Legend( 4 ),
            Summary Statistic( "Median" ),
            Label( "Label by Percent of Total Values" ),
            Label Format( "Percent", 10, 5 )
        )
    )
);
j4 = gb4 << journal;
gb4 << close window;
gb5 = dt << Graph Builder(
    Variables( X( :age ), Y( :weight ), Color( :height ) ),
    Elements(
        Treemap(
            X,
            Y,
            Legend( 6 ),
            Summary Statistic( "Mean" ),
            Color Value( 1 ),
            Size Value( 1 ),
            Color Label Format( "Fixed Dec", 10, 4 ),
            Size Label Format( "Fixed Dec", 6, 3 )
        )
    )
);
j5 = gb5 << journal;
gb5 << close window;

Code Explanation:

1. Open data_table data
2. Create heatmap graph.
3. Save graph to journal.
4. Close heatmap window.
5. Create bar graph.
6. Save graph to journal.
7. Close bar window.
8. Open data_table data
9. Create mosaic plot.
10. Save plot to journal.

Example 1065

Summary: Runs the creation and visualization of nested factors using Graph Builder, generating heatmaps, bar charts, mosaic plots, and pie charts to display standard deviation charts.

Code:

dt = Open("data_table.jmp");
gb1 = dt << Graph Builder(
    Variables( X( :age ), Y( :weight ), Color( :height ) ),
    Elements( Heatmap( X, Y, Legend( 8 ), Label( "Label by Value" ), Label Format( "Scientific", 7 ) ) )
);
j1 = gb1 << journal;
gb1 << close window;
gb2 = dt << Graph Builder(
    Variables( X( :age ), Y( :weight ), Color( :height ) ),
    Elements( Bar( X, Y, Legend( 10 ), Label( "Label by Value" ), Label Format( "Fixed Dec", 6, 2 ) ) )
);
j2 = gb2 << journal;
gb2 << close window;
dt2 = Open("data_table.jmp");
gb3 = dt2 << Graph Builder(
    Variables( X( :Color ), Y( :Clarity ) ),
    Elements( Mosaic( X, Y, Legend( 7 ), Cell Labeling( "Label by Percent" ), Label Format( "Percent", 6, 2 ) ) )
);
j3 = gb3 << journal;
gb3 << close window;
gb4 = dt << Graph Builder(
    Variables( X( :age ), Y( :weight ) ),
    Elements(
        Pie(
            X,
            Y,
            Legend( 4 ),
            Summary Statistic( "Median" ),
            Label( "Label by Percent of Total Values" ),
            Label Format( "Percent", 10, 5 )
        )
    )
);
j4 = gb4 << journal;
gb4 << close window;
gb5 = dt << Graph Builder(
    Variables( X( :age ), Y( :weight ), Color( :height ) ),
    Elements(
        Treemap(
            X,
            Y,
            Legend( 6 ),
            Summary Statistic( "Mean" ),
            Color Value( 1 ),
            Size Value( 1 ),
            Color Label Format( "Fixed Dec", 10, 4 ),
            Size Label Format( "Fixed Dec", 6, 3 )
        )
    )
);
j5 = gb5 << journal;

Code Explanation:

1. Open data table.
2. Create heatmap graph.
3. Save heatmap graph to journal.
4. Close heatmap graph window.
5. Create bar graph.
6. Save bar graph to journal.
7. Close bar graph window.
8. Open data table.
9. Create mosaic plot.
10. Save mosaic plot to journal.

Example 1066

Summary: Creates a variability chart with nested factors using operator and part configurations, displaying standard deviation charts within Graph Builder.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 604, 390 ),
    Show Control Panel( 0 ),
    Variables( X( :Price ), Y( :Cut ), Overlay( :Report ) ),
    Elements( Bar( X, Y, Legend( 6 ) ), Caption Box( X, Y, Legend( 7 ), Summary Statistic( "Mean" ), Location( "Axis Reference Line" ) ) ),
    SendToReport(
        Dispatch( {}, "Price", ScaleBox,
            {Update Ref Line( "Mean(AGS)", 1, "Solid", "Medium Dark Blue", "Mean(AGS)", 1, 0.5 ),
            Update Ref Line( "Mean(GIA)", 1, "Solid", "Medium Dark Red", "Mean(GIA)", 1, 0.5 )}
        )
    )
);

Code Explanation:

1. Open data table;
2. Create Graph Builder window.
3. Set size 604x390.
4. Hide control panel.
5. Set X variable: Price.
6. Set Y variable: Cut.
7. Set overlay variable: Report.
8. Add bar element.
9. Add caption box.
10. Update reference lines for mean AGS and GIA.

Example 1067

Summary: Creates a variability chart with nested factors using Graph Builder, displaying standard deviation charts and configuring bar elements with legend and caption box.

Code:

Open("data_table.jmp");
Graph Builder(
    Show Control Panel( 0 ),
    Variables( X( :age ), Y( :height ), Group X( :sex ) ),
    Elements( Bar( X, Y, Legend( 4 ) ), Caption Box( X, Y, Legend( 5 ), Location( "Axis Table" ) ) )
);

Code Explanation:

1. Open data table;
2. Launch Graph Builder.
3. Hide control panel.
4. Set X variable to age.
5. Set Y variable to height.
6. Group X by sex.
7. Add bar element.
8. Set legend for bars.
9. Add caption box.
10. Set caption location to axis table.

Example 1068

Summary: Creates a variability chart with nested factors using Graph Builder, displaying standard deviation charts and summarizing mean values.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 534, 450 ),
    Show Control Panel( 0 ),
    Variables( X( :Meal ), Y( :Calories ), Y( :Protein, Position( 1 ) ) ),
    Elements(
        Bar( X, Y( 1 ), Y( 2 ), Legend( 7 ) ),
        Caption Box( X, Y( 1 ), Y( 2 ), Legend( 8 ), Summary Statistic( "Mean" ), Location( "Axis Reference Line" ) )
    )
);

Code Explanation:

1. Open data table;
2. Launch Graph Builder.
3. Set window size.
4. Hide control panel.
5. Define X and Y variables.
6. Add bar element.
7. Add caption box element.
8. Set summary statistic to mean.
9. Place caption on axis reference line.
10. Display graph.

Example 1069

Summary: Creates a variability chart with nested factors using Graph Builder, displaying standard deviation charts and summary statistics.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 500, 2000 ),
    Show Control Panel( 0 ),
    Variables( X( :height ), Y( :weight ), Page( :age ) ),
    Elements(
        Points( X, Y, Legend( 6 ) ),
        Smoother( X, Y, Legend( 7 ) ),
        Caption Box( X, Y, Legend( 8 ), Summary Statistic( "Mean" ), Location( "Axis Reference Line" ) )
    )
);

Code Explanation:

1. Open data table.
2. Create Graph Builder object.
3. Set window size.
4. Hide control panel.
5. Define X, Y, and Page variables.
6. Add points element.
7. Add smoother element.
8. Add caption box element.
9. Set summary statistic to mean.
10. Position caption on axis reference line.

Example 1070

Summary: Creates two Graph Builder windows to visualize the relationship between sex and height, displaying histograms with mean captions at axis reference lines.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 528, 450 ),
    Show Control Panel( 0 ),
    Variables( X( :sex ), Y( :height ), Overlay( :sex ) ),
    Elements(
        Histogram( X, Y, Legend( 8 ) ),
        Caption Box( X, Y, Legend( 9 ), Summary Statistic( "Mean" ), Location( "Axis Reference Line" ) )
    )
);
Graph Builder(
    Size( 528, 450 ),
    Show Control Panel( 0 ),
    Variables( X( :sex ), Y( :height ) ),
    Elements(
        Histogram( X, Y, Legend( 8 ) ),
        Caption Box( X, Y, Legend( 9 ), Summary Statistic( "Mean" ), Location( "Axis Reference Line" ) )
    )
);

Code Explanation:

1. Open data table.
2. Create Graph Builder window.
3. Set window size.
4. Hide control panel.
5. Define X, Y, and overlay variables.
6. Add histogram element.
7. Add caption box for mean.
8. Position caption at axis reference line.
9. Create another Graph Builder window.
10. Repeat steps 3-8 without overlay variable.

Example 1071

Summary: Creates a variability chart with nested factors using Graph Builder, displaying standard deviation charts and summarizing median statistics.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 528, 456 ),
    Show Control Panel( 0 ),
    Variables( X( :height ), Overlay( :sex ) ),
    Elements( Histogram( X, Legend( 3 ) ), Caption Box( X, Legend( 4 ), Summary Statistic( "Median" ) ) )
);

Code Explanation:

1. Open data table;
2. Launch Graph Builder.
3. Set window size.
4. Hide control panel.
5. Define X variable.
6. Add overlay variable.
7. Add histogram element.
8. Set histogram legend.
9. Add caption box element.
10. Set caption legend and statistic.

Example 1072

Summary: Creates a variability chart with nested factors using Graph Builder, displaying standard deviation charts and configuring custom value orders.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 528, 464 ),
    Show Control Panel( 0 ),
    Variables(
        X(
            Transform Column(
                "age'",
                Ordinal,
                Set Property( "Configure Levels", 1 ),
                Set Property( "Value Order", {Custom Order( {12, 13, 14, 15} )} ),
                Value Labels( {12 = "12", 13 = "13", 14 = "14", 15 = "Older Group"} ),
                Use Value Labels( 1 ),
                Formula( Match( :age, 16, 15, 17, 15, :age ) )
            )
        ),
        Y( :height ),
        Overlay( :sex )
    ),
    Elements( Box Plot( X, Y, Legend( 9 ) ), Caption Box( X, Y, Legend( 7 ), Summary Statistic( "Mean" ), Location( "Axis Table" ) ) )
);

Code Explanation:

1. Open data table.
2. Launch Graph Builder.
3. Set window size.
4. Hide control panel.
5. Define X variable.
6. Transform age column.
7. Set ordinal type.
8. Configure levels property.
9. Set custom value order.
10. Apply value labels.
11. Use value labels.
12. Create transformation formula.
13. Define Y variable.
14. Define overlay variable.
15. Add box plot element.
16. Add caption box element.
17. Set summary statistic to mean.
18. Set location to axis table.

Example 1073

Summary: Creates a variability chart with nested factors using Graph Builder, displaying standard deviation charts for weight and height.

Code:

Open("data_table.jmp");
Graph Builder(
    Show Control Panel( 0 ),
    Variables( X( :age ), Y( :weight, Side( "Right" ) ), Y( :height, Position( 1 ) ) ),
    Elements(
        Line( X, Y( 1 ), Summary Statistic( "Mean" ) ),
        Line( X, Y( 2 ), Summary Statistic( "Mean" ) ),
        Caption Box( X, Y( 1 ), Summary Statistic( "Median" ) ),
        Caption Box( X, Y( 1 ), Summary Statistic( "Median" ) ),
        Caption Box( X, Y( 2 ), Summary Statistic( "Mean" ) ),
        Caption Box( X, Y( 2 ), Summary Statistic( "Mean" ) )
    )
);

Code Explanation:

1. Open data table.
2. Create Graph Builder object.
3. Hide control panel.
4. Set X variable to age.
5. Set Y variables: weight (right), height (left).
6. Add mean line for weight.
7. Add mean line for height.
8. Add median caption for weight.
9. Add median caption for weight.
10. Add mean caption for height.
11. Add mean caption for height.

Example 1074

Summary: Creates a variability chart with nested factors using Graph Builder, displaying standard deviation charts for two Y variables and color-coded by Region.

Code:

Open("data_table.jmp");
Graph Builder(
    Show Control Panel( 0 ),
    Variables(
        X( Transform Column( "SAT Verbal+SAT Math", Formula( :SAT Verbal + :SAT Math ) ) ),
        Y( :Name( "Expenditure (1997)" ) ),
        Y( :Name( "Student/Faculty Ratio (1997)" ) ),
        Group X( :Region ),
        Color( :Region )
    ),
    Elements( Position( 1, 1 ), Points( X, Y, Legend( 10 ) ), Caption Box( X, Y, Legend( 12 ) ) ),
    Elements( Position( 1, 2 ), Points( X, Y, Legend( 11 ) ), Caption Box( X, Y, Legend( 13 ) ) )
);

Code Explanation:

1. Open data table.
2. Launch Graph Builder.
3. Hide control panel.
4. Define X variable.
5. Define first Y variable.
6. Define second Y variable.
7. Set group X variable.
8. Set color variable.
9. Add points element for first Y.
10. Add caption box for first Y.

Example 1075

Summary: Creates a variability chart with nested factors using Graph Builder, configuring X-axis and Y-axis variables, and displaying standard deviation charts.

Code:

dt = Open("data_table.jmp");
gb = Graph Builder(
    Size( 714, 451 ),
    Show Control Panel( 0 ),
    Variables( X( :age ), Y( :height ) ),
    Elements( Points( X, Y, Legend( 3 ), Jitter( "None" ) ), Caption Box( X, Y, Legend( 5 ), Per Factor( 1 ) ) ),
    SendToReport( Dispatch( {}, "age", ScaleBox, {Min( -0.738473767885533 ), Max( 5.58025133171606 ), Inc( 1 ), Minor Ticks( 0 )} ) )
);

Code Explanation:

1. Open data table;
2. Create Graph Builder object.
3. Set graph size to 714x451.
4. Hide control panel.
5. Assign age to X-axis.
6. Assign height to Y-axis.
7. Add points element.
8. Add caption box element.
9. Set caption box per factor to 1.
10. Adjust X-axis scale properties.

Example 1076

Summary: Creates a variability chart with nested factors using Graph Builder, displaying standard deviation charts and customizing the age axis scale.

Code:

dt = Open("data_table.jmp");
Graph Builder(
    Size( 587, 402 ),
    Show Control Panel( 0 ),
    Variables( X( :age ), Y( :weight ), Overlay( :sex ) ),
    Elements(
        Points( X, Y, Legend( 4 ) ),
        Caption Box( X, Y, Overlay( 0 ), Legend( 5 ), Summary Statistic( "Median" ), X Position( "Left" ), Per Factor( 1 ) ),
        Caption Box( X, Y, Legend( 6 ), X Position( "Left" ), Per Factor( 1 ) )
    ),
    SendToReport( Dispatch( {}, "age", ScaleBox, {Min( -1 )} ) )
);

Code Explanation:

1. Open data table;
2. Launch Graph Builder.
3. Set window size to 587x402.
4. Hide control panel.
5. Assign age to X-axis.
6. Assign weight to Y-axis.
7. Overlay by sex.
8. Add points element.
9. Add median caption box.
10. Adjust scale min for age to -1.

Example 1077

Summary: Creates a variability chart with nested factors using Graph Builder, displaying standard deviation charts and summary statistics.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 587, 402 ),
    Show Control Panel( 0 ),
    Variables( X( :age ), Y( :weight ), Overlay( :sex ) ),
    Elements(
        Points( X, Y, Legend( 4 ) ),
        Caption Box( X, Y, Legend( 6 ), X Position( "Left" ), Y Position( "Middle" ), Per Factor( 1 ) ),
        Caption Box( X, Y, Overlay( 0 ), Legend( 5 ), Summary Statistic( "Median" ), X Position( "Left" ), Per Factor( 1 ) )
    ),
    SendToReport( Dispatch( {}, "age", ScaleBox, {Min( -1 )} ) )
);

Code Explanation:

1. Open data table;
2. Create Graph Builder window.
3. Set window size.
4. Hide control panel.
5. Define variables: X=age, Y=weight, Overlay=sex.
6. Add points element.
7. Add caption box for summary statistics.
8. Add caption box for median.
9. Set caption box position.
10. Adjust scale minimum for age.

Example 1078

Summary: Creates a heatmap visualization with nested factors using Graph Builder, displaying standard deviation charts and customizing legends.

Code:

Open("data_table.jmp");
Graph Builder(
    Show Control Panel( 0 ),
    Variables( X( :height ), Y( :weight ) ),
    Elements( Heatmap( X, Y, Legend( 21 ) ), Caption Box( X, Y, Legend( 22 ) ) ),
    SendToReport( Dispatch( {}, "400", LegendBox, {Set Title( "Count" )} ) )
);

Code Explanation:

1. Open data table.
2. Launch Graph Builder.
3. Hide control panel.
4. Set X variable to height.
5. Set Y variable to weight.
6. Add heatmap element.
7. Add caption box element.
8. Customize heatmap legend.
9. Customize caption box legend.
10. Set heatmap title to "Count".

Example 1079

Summary: Creates a variability chart with nested factors using Graph Builder, displaying standard deviation charts and configuring legend settings.

Code:

Open("data_table.jmp");
Graph Builder(
    Show Control Panel( 0 ),
    Variables( X( :age ), Y( :weight ) ),
    Elements( Bar( X, Y, Legend( 16 ) ), Caption Box( X, Y, Legend( 15 ) ) )
);

Code Explanation:

1. Open data_table data
2. Launch Graph Builder.
3. Hide control panel.
4. Set X variable to age.
5. Set Y variable to weight.
6. Add bar element.
7. Add caption box element.
8. Assign legend to bar.
9. Assign legend to caption box.
10. Display graph.

Example 1080

Summary: Creates a 2D contour plot to visualize the relationship between height and weight using Graph Builder.

Code:

Open("data_table.jmp");
Graph Builder(
    Variables( X( :height ), Y( :weight ) ),
    Elements( Contour( X, Y, Legend( 4 ), Smoothness( -1000 ), Contour Type 2D( "HDR" ) ) )
);

Code Explanation:

1. Open data table.
2. Launch Graph Builder.
3. Set X variable to height.
4. Set Y variable to weight.
5. Add Contour element.
6. Configure Legend for Contour.
7. Set Smoothness to -1000.
8. Use HDR Contour Type.
9. Display 2D Contour plot.
10. Save script file.

Example 1081

Summary: Creates a variability chart with nested factors using Graph Builder, displaying standard deviation charts and utilizing color by gender.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 534, 456 ),
    Show Control Panel( 0 ),
    Variables( X( :Total Cholesterol ), Y( :Y Binary ), Color( :Gender ) ),
    Elements( Contour( X, Y, Legend( 4 ) ) )
);

Code Explanation:

1. Open data table;
2. Create Graph Builder window.
3. Set window size to 534x456.
4. Hide control panel.
5. Assign variables: X=Total Cholesterol, Y=Y Binary, Color=Gender.
6. Add Contour element.
7. Display legend for contour.
8. Use gender colors in contour.

Example 1082

Summary: Creates a contour plot with color mapping using Graph Builder, visualizing the relationship between age and height.

Code:

Open("data_table.jmp");
gb = Graph Builder( Variables( X( :age ), Y( :height ), Color( :height ) ), Elements( Contour( X, Y, Legend( 4 ) ) ), );
gb << save journal( "$temp\jnlcontourcolor.jrn" );

Code Explanation:

1. Open data table.
2. Create Graph Builder object.
3. Set X variable to age.
4. Set Y variable to height.
5. Set color variable to height.
6. Add Contour element.
7. Configure Contour legend.
8. Save journal to temp directory.

Example 1083

Summary: Creates a contour plot with colorization based on height, using Graph Builder to visualize the relationship between age and height.

Code:

Open("data_table.jmp");
gb = Graph Builder( Variables( X( :age ), Y( :height ), Color( :height ) ), Elements( Contour( X, Y, Legend( 4 ) ) ), );
gb << save journal( "$temp\jnlcontourcolor.jrn" );
Open( "$temp\jnlcontourcolor.jrn" );
gb << close window;

Code Explanation:

1. Open data table;
2. Create Graph Builder.
3. Set X to :age.
4. Set Y to :height.
5. Color by :height.
6. Add Contour element.
7. Save journal as "jnlcontourcolor.jrn".
8. Open saved journal.
9. Close Graph Builder window.

Example 1084

Summary: Creates a contour plot with color mapping based on height, using Graph Builder to visualize the relationship between age and height.

Code:

Open("data_table.jmp");
gb = Graph Builder( Variables( X( :age ), Y( :height ), Color( :height ) ), Elements( Contour( X, Y, Legend( 4 ) ) ), );
gb << save journal( "$temp\jnlcontourcolor.jrn" );
Open( "$temp\jnlcontourcolor.jrn" );

Code Explanation:

1. Open data table;
2. Create Graph Builder object.
3. Set X variable to age.
4. Set Y variable to height.
5. Set color variable to height.
6. Add contour element.
7. Set legend position.
8. Save graph as journal.
9. Open saved journal file.

Example 1085

Summary: Creates a variability chart with nested factors using operator and part configurations, displaying standard deviation charts.

Code:

dt = Open("data_table.jmp");
gb = dt << Graph Builder(
    Size( 528, 454 ),
    Show Control Panel( 0 ),
    Variables( X( :height ), Y( :weight ) ),
    Elements( Contour( X, Y, Legend( 4 ) ) ),
    SendToReport(
        Dispatch( {}, "400", ScaleBox,
            {Legend Model(
                4,
                Properties( 0, {gradient( {Density Gradient( "Full Color" ), Gradient Transparency( "None" )} )}, Item ID( "Density", 1 ) )
            )}
        )
    )
);
nw = gb << Redo Analysis;

Code Explanation:

1. Open data table.
2. Create graph builder object.
3. Set window size.
4. Hide control panel.
5. Assign variables X and Y.
6. Add contour element.
7. Configure legend properties.
8. Send report settings.
9. Redo analysis.
10. Store new window.

Example 1086

Summary: Creates a contour plot with nested factors using Graph Builder, displaying standard deviation charts and customizing the legend.

Code:

dt = Open("data_table.jmp");
gb = dt << Graph Builder(
    Size( 528, 454 ),
    Show Control Panel( 0 ),
    Variables( X( :height ), Y( :weight ) ),
    Elements( Contour( X, Y, Legend( 4 ) ) ),
    SendToReport(
        Dispatch( {}, "400", ScaleBox,
            {Legend Model(
                4,
                Properties( 0, {gradient( {Density Gradient( "Full Color" ), Gradient Transparency( "None" )} )}, Item ID( "Density", 1 ) )
            )}
        )
    )
);
nw = gb << Redo Analysis;
gb << close window;

Code Explanation:

1. Open table.
2. Create Graph Builder.
3. Set size.
4. Hide control panel.
5. Assign variables.
6. Add contour element.
7. Customize legend.
8. Redo analysis.
9. Close window.

Example 1087

Summary: Creates a variability chart with nested factors using Graph Builder, configuring legend properties and applying gradient fill color.

Code:

dt = Open("data_table.jmp");
gb = dt << Graph Builder(
    Size( 534, 456 ),
    Show Control Panel( 0 ),
    Variables( X( :Carat Weight ), Y( :Price ) ),
    Elements( Contour( X, Y, Legend( 5 ), Line( 1 ) ) ),
    SendToReport(
        Dispatch( {}, "400", ScaleBox,
            {Legend Model(
                5,
                Properties(
                    0,
                    {Line Width( 3 ), Fill Color( 26 ), gradient(
                        {Density Gradient( "Fade To Gray" ), Gradient Transparency( "None" ), Width( 9 )}
                    )},
                    Item ID( "Density", 1 )
                )
            )}
        )
    )
);
nw = gb << redo analysis;

Code Explanation:

1. Open data table;
2. Create Graph Builder object.
3. Set size to 534x456.
4. Hide control panel.
5. Set X to Carat Weight.
6. Set Y to Price.
7. Add Contour element.
8. Configure legend properties.
9. Set line width to 3.
10. Apply gradient fill color.

Example 1088

Summary: Creates a variability chart with nested factors using operator and part configurations, displaying standard deviation charts.

Code:

dt = Open("data_table.jmp");
gb = dt << Graph Builder(
    Size( 534, 456 ),
    Show Control Panel( 0 ),
    Variables( X( :Carat Weight ), Y( :Price ) ),
    Elements( Contour( X, Y, Legend( 5 ), Line( 1 ) ) ),
    SendToReport(
        Dispatch( {}, "400", ScaleBox,
            {Legend Model(
                5,
                Properties(
                    0,
                    {Line Width( 3 ), Fill Color( 26 ), gradient(
                        {Density Gradient( "Fade To Gray" ), Gradient Transparency( "None" ), Width( 9 )}
                    )},
                    Item ID( "Density", 1 )
                )
            )}
        )
    )
);
nw = gb << redo analysis;
gb << close window;

Code Explanation:

1. Open data table;
2. Create Graph Builder object.
3. Set graph size.
4. Hide control panel.
5. Assign X and Y variables.
6. Add contour element.
7. Customize legend properties.
8. Set line width and fill color.
9. Apply density gradient effect.
10. Redo analysis and close window.

Example 1089

Summary: Creates a contour plot with nested factors using Graph Builder, configuring legend properties and line color/width.

Code:

dt = Open("data_table.jmp");
obj = dt << Graph Builder(
    Size( 534, 456 ),
    Show Control Panel( 0 ),
    Variables( X( :height ), Y( :weight ) ),
    Elements( Contour( X, Y, Legend( 4 ), Line( 1 ), Number of Levels( 2 ), Smoothness( -0.1376 ) ) ),
    SendToReport(
        Dispatch( {}, "400", ScaleBox, {Legend Model( 4, Properties( 0, {Line Color( 3 ), Line Width( 4 )}, Item ID( "Density", 1 ) ) )} )
    )
);
obj << save journal( "$temp\S1479124.jrn" );
obj << close window;

Code Explanation:

1. Open data table.
2. Create Graph Builder object.
3. Set graph size.
4. Hide control panel.
5. Define X and Y variables.
6. Add contour element.
7. Configure legend properties.
8. Customize line color and width.
9. Save report to file.
10. Close graph window.

Example 1090

Summary: Creates a variability chart with nested factors using Graph Builder, displaying standard deviation charts and customizing legend properties.

Code:

dt = Open("data_table.jmp");
obj = dt << Graph Builder(
    Size( 534, 456 ),
    Show Control Panel( 0 ),
    Variables( X( :height ), Y( :weight ) ),
    Elements( Contour( X, Y, Legend( 4 ), Line( 1 ), Number of Levels( 2 ), Smoothness( -0.1376 ) ) ),
    SendToReport(
        Dispatch( {}, "400", ScaleBox, {Legend Model( 4, Properties( 0, {Line Color( 3 ), Line Width( 4 )}, Item ID( "Density", 1 ) ) )} )
    )
);
obj << save journal( "$temp\S1479124.jrn" );
obj << close window;
Open( "$temp\S1479124.jrn" );

Code Explanation:

1. Open table.
2. Create Graph Builder object.
3. Set size and control panel visibility.
4. Assign variables X and Y.
5. Add Contour element.
6. Customize legend properties.
7. Save journal to temp directory.
8. Close graph window.
9. Open saved journal.

Example 1091

Summary: Creates a graph builder with nested factors using operator and part configurations, displaying standard deviation charts.

Code:

Open("data_table.jmp");
gb = Graph Builder(
    Size( 534, 456 ),
    Show Control Panel( 0 ),
    Variables( X( :Total Cholesterol ), Y( :Y Binary ), Color( :Gender ) ),
    Elements( Contour( X, Y, Legend( 4 ) ) )
);
gb << save journal( "$temp\JMP-13004.jrn" );

Code Explanation:

1. Open data table;
2. Create Graph Builder object.
3. Set graph size.
4. Hide control panel.
5. Define X, Y, and color variables.
6. Add contour element.
7. Save graph as journal.

Example 1092

Summary: Creates a graph builder object with nested factors, utilizing variables X, Y, and Color to display a contour element.

Code:

Open("data_table.jmp");
gb = Graph Builder(
    Size( 534, 456 ),
    Show Control Panel( 0 ),
    Variables( X( :Total Cholesterol ), Y( :Y Binary ), Color( :Gender ) ),
    Elements( Contour( X, Y, Legend( 4 ) ) )
);
gb << save journal( "$temp\JMP-13004.jrn" );
Open( "$temp\JMP-13004.jrn" );
gb << close window;

Code Explanation:

1. Open data table;
2. Create graph builder object.
3. Set graph size.
4. Hide control panel.
5. Define variables: X, Y, Color.
6. Add contour element.
7. Save graph as journal.
8. Open saved journal.
9. Close graph window.

Example 1093

Summary: Creates a variability chart with nested factors using Graph Builder, specifying X-axis as Total Cholesterol, Y-axis as Y Binary, and Color by Gender.

Code:

Open("data_table.jmp");
gb = Graph Builder(
    Size( 534, 456 ),
    Show Control Panel( 0 ),
    Variables( X( :Total Cholesterol ), Y( :Y Binary ), Color( :Gender ) ),
    Elements( Contour( X, Y, Legend( 4 ) ) )
);
gb << save journal( "$temp\JMP-13004.jrn" );
Open( "$temp\JMP-13004.jrn" );

Code Explanation:

1. Open data table;
2. Create Graph Builder object.
3. Set graph size.
4. Hide control panel.
5. Define variables: X, Y, Color.
6. Add Contour element.
7. Save graph as journal.
8. Open saved journal.

Example 1094

Summary: Creates a contour chart with nested factors using Graph Builder, displaying standard deviation charts and customizing legend properties.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 534, 456 ),
    Show Control Panel( 0 ),
    Variables( X( :height ), Y( :weight ) ),
    Elements( Contour( X, Y, Legend( 4 ), Number of Levels( 1 ) ) ),
    SendToReport(
        Dispatch( {}, "400", ScaleBox,
            {Legend Model( 4, Properties( 0, {gradient( {Density Gradient( "Full Color" )} )}, Item ID( "Density", 1 ) ) )}
        )
    )
);

Code Explanation:

1. Open data table;
2. Create Graph Builder window.
3. Set window size.
4. Hide control panel.
5. Define X variable.
6. Define Y variable.
7. Add contour element.
8. Set number of levels to 1.
9. Customize legend properties.
10. Apply gradient to density.

Example 1095

Summary: Creates a contour graph with nested factors, utilizing Graph Builder to visualize relationships between age and height.

Code:

Open("data_table.jmp");
gb = Graph Builder( Show Control Panel( 0 ), Variables( X( :age ), Y( :height ), Color( :height ) ), Elements( Contour( X, Y ) ) );
frame = (gb << Report)[FrameBox( 1 )];
seg = frame << Find Seg( Poly Seg( 1 ) );

Code Explanation:

1. Open data table;
2. Create graph builder object.
3. Set X, Y, and color variables.
4. Add contour element to graph.
5. Access first frame box.
6. Find segments in frame.
7. Identify polygonal segments.

Example 1096

Summary: Creates a contour plot with nested factors using Graph Builder and sets the gradient color theme to Viridis.

Code:

Open("data_table.jmp");
gb = Graph Builder( Show Control Panel( 0 ), Variables( X( :age ), Y( :height ), Color( :height ) ), Elements( Contour( X, Y ) ) );
frame = (gb << Report)[FrameBox( 1 )];
seg = frame << Find Seg( Poly Seg( 1 ) );
seg << Set Gradient( Color Theme( "Viridis" ) );

Code Explanation:

1. Open data table.
2. Create Graph Builder object.
3. Hide control panel.
4. Set X, Y, and color variables.
5. Add contour element.
6. Access first frame box.
7. Find polygonal segment.
8. Set gradient for segment.
9. Use "Viridis" color theme.

Example 1097

Summary: Creates a variability chart with nested factors using Graph Builder, displaying contour and points elements.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 534, 456 ),
    Show Control Panel( 0 ),
    Variables( X( :Name( "Thigh circumference (cm)" ) ), Y( :Name( "Abdomen circumference (cm)" ) ), Color( :Name( "Weight (lbs)" ) ) ),
    Elements( Contour( X, Y, Legend( 16 ) ), Points( X, Y, Color( 0 ), Legend( 17 ) ) )
);

Code Explanation:

1. Open data table.
2. Launch Graph Builder.
3. Set window size.
4. Hide control panel.
5. Define X variable.
6. Define Y variable.
7. Define color variable.
8. Add contour element.
9. Add points element.
10. Display graph.

Example 1098

Summary: Creates a variability chart with nested factors using operator and part configurations, displaying standard deviation charts in Graph Builder.

Code:

Open("data_table.jmp");
Graph Builder(
    Show Control Panel( 0 ),
    Continuous Color Theme( "Green to Purple" ),
    Variables( X( :X ), Y( :Y ), Color( :OZONE ) ),
    Elements( Contour( X, Y, Legend( 3 ), Number of Levels( 0 ) ) )
);

Code Explanation:

1. Open data table;
2. Launch Graph Builder.
3. Hide control panel.
4. Set color theme.
5. Assign X variable.
6. Assign Y variable.
7. Assign color variable.
8. Add contour element.
9. Set legend position.
10. Set number of levels.

Example 1099

Summary: Creates a Graph Builder window with a Contour element to visualize relationships between Sepal length and Sepal width, overlaid by Species.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 534, 407 ),
    Show Control Panel( 0 ),
    Variables( X( :Sepal length ), Y( :Sepal width ), Overlay( :Species ) ),
    Elements( Contour( X, Y, Legend( 3 ), Number of Levels( 3 ) ), Points( X, Y, Legend( 4 ) ) )
);

Code Explanation:

1. Open data table;
2. Create Graph Builder window.
3. Set window size to 534x407.
4. Hide control panel.
5. Assign X variable: Sepal length.
6. Assign Y variable: Sepal width.
7. Use Species for overlay.
8. Add Contour element.
9. Set legend position to 3.
10. Define 3 contour levels.

Example 1100

Summary: Creates a variability chart with nested factors using operator and part configurations, displaying standard deviation charts in Graph Builder.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 528, 454 ),
    Show Control Panel( 0 ),
    Variables( X( :X ), X( :Y, Position( 1 ) ), Y( :Z ) ),
    Elements( Contour( X( 1 ), X( 2 ), Y, Legend( 5 ) ) )
);

Code Explanation:

1. Open data_table data
2. Launch Graph Builder.
3. Set window size.
4. Hide control panel.
5. Define X variables.
6. Define Y variable.
7. Add contour element.
8. Position X variables.
9. Assign Y variable.
10. Add legend.

Example 1101

Summary: Creates a variability chart with nested factors using Graph Builder, displaying standard deviation charts and utilizing local data filtering.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 534, 456 ),
    Show Control Panel( 0 ),
    Variables( X( :height ), Y( :weight ), Color( :age ) ),
    Elements( Contour( X, Y, Legend( 6 ) ) ),
    Local Data Filter( Add Filter( columns( :height ) ) )
);

Code Explanation:

1. Open data table;
2. Create Graph Builder window.
3. Set window size.
4. Hide control panel.
5. Define X variable.
6. Define Y variable.
7. Define color variable.
8. Add contour element.
9. Set legend position.
10. Add local data filter.

Example 1102

Summary: Creates a Graph Builder window with nested factors using operator and part configurations, displaying standard deviation charts for Horsepower and Turning Circle.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 493, 374 ),
    Show Control Panel( 0 ),
    Variables( X( :Type ), X( :Country ), Y( :Horsepower ), Y( :Turning Circle ) ),
    Elements( Position( 1, 1 ), Contour( X, Y, Legend( 21 ) ) ),
    Elements( Position( 1, 2 ), Contour( X, Y, Legend( 35 ) ) ),
    Elements( Position( 2, 1 ), Contour( X, Y, Legend( 26 ) ) ),
    Elements( Position( 2, 2 ), Contour( X, Y, Legend( 36 ) ) ),
    SendToReport(
        Dispatch( {}, "Graph Builder", FrameBox, {Marker Size( 5 )} ),
        Dispatch( {}, "Graph Builder", FrameBox( 2 ), {Marker Size( 5 )} ),
        Dispatch( {}, "Graph Builder", FrameBox( 3 ), {Marker Size( 5 )} ),
        Dispatch( {}, "Graph Builder", FrameBox( 4 ), {Marker Size( 5 )} )
    )
);

Code Explanation:

1. Open data table;
2. Create Graph Builder window.
3. Set window size.
4. Hide control panel.
5. Define X variables: Type, Country.
6. Define Y variables: Horsepower, Turning Circle.
7. Add first contour element.
8. Add second contour element.
9. Add third contour element.
10. Add fourth contour element.
11. Set marker size for all frames.

Example 1103

Summary: Creates a variability chart with nested factors using Graph Builder, displaying standard deviation charts and mapping X to Y variables.

Code:

Open("data_table.jmp");
Graph Builder(
    Show Control Panel( 0 ),
    Variables( X( :age ), Y( :height ), Y( :weight, Position( 1 ) ) ),
    Elements( Contour( X, Y( 1 ), Y( 2 ), Legend( 6 ) ) )
);

Code Explanation:

1. Open data table.
2. Launch Graph Builder.
3. Hide control panel.
4. Set X variable to age.
5. Set Y1 variable to height.
6. Set Y2 variable to weight.
7. Position Y2 on left axis.
8. Add contour element.
9. Map X to first Y.
10. Map second Y to contour.

Example 1104

Summary: Creates a contour chart with nested factors using Graph Builder, displaying standard deviation charts and formatting X scale for best results.

Code:

Open("data_table.jmp");
Graph Builder(
    show control panel( 0 ),
    Variables( X( :Atmospheric Pressure ), Y( :Atmospheric Pressure ) ),
    Elements( Contour( X, Y, Legend( 5 ) ) ),
    SendToReport( Dispatch( {}, "Atmospheric Pressure", ScaleBox( 2 ), {Format( "Best", 9 )} ) )
);

Code Explanation:

1. Open data table.
2. Create Graph Builder.
3. Hide control panel.
4. Set X variable.
5. Set Y variable.
6. Add contour element.
7. Set legend for contour.
8. Send report dispatch.
9. Format X scale.
10. Set number format.

Example 1105

Summary: Creates a contour plot with nested factors using Graph Builder, displaying standard deviation charts for weight and height based on age.

Code:

Open("data_table.jmp");
Graph Builder( show control panel( 0 ), Variables( X( :weight ), Y( :height ), Color( :age ) ), Elements( Contour( X, Y, Legend( 16 ) ) ) );

Code Explanation:

1. Open data table;
2. Launch Graph Builder.
3. Hide control panel.
4. Set X variable to weight.
5. Set Y variable to height.
6. Set color variable to age.
7. Add contour element.
8. Configure legend for contour.

Example 1106

Summary: Creates a variability chart with nested factors using Graph Builder, displaying standard deviation charts and utilizing operator and part configurations.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 534, 454 ),
    Show Control Panel( 0 ),
    Variables( X( :height ), Y( :weight ), Color( :sex ) ),
    Elements( Points( X, Y, Color( 0 ), Legend( 3 ) ), Contour( X, Y, Legend( 5 ) ) )
);

Code Explanation:

1. Open data table.
2. Launch Graph Builder.
3. Set window size.
4. Hide control panel.
5. Define X variable.
6. Define Y variable.
7. Define color variable.
8. Add points element.
9. Add contour element.
10. Display graph.

Example 1107

Summary: Creates a variability chart with nested factors using Graph Builder, displaying standard deviation charts and contour elements.

Code:

Open("data_table.jmp");
Graph Builder( Show Control Panel( 0 ), Variables( X( :height ), Y( :weight ) ), Elements( Contour( X, Y, Legend( 11 ) ) ) );

Code Explanation:

1. Open data table;
2. Launch Graph Builder.
3. Hide control panel.
4. Set X variable to height.
5. Set Y variable to weight.
6. Add contour element.
7. Assign legend to contour.

Example 1108

Summary: Creates a variability chart with nested factors using operator and part configurations, displaying standard deviation charts.

Code:

dt = Open("data_table.jmp");
gb = dt << Graph Builder(
    Size( 528, 454 ),
    Show Control Panel( 0 ),
    Variables( X( :height ), Y( :weight ) ),
    Elements( Contour( X, Y, Legend( 4 ) ) ),
    SendToReport(
        Dispatch( {}, "400", ScaleBox,
            {Legend Model(
                4,
                Properties( 0, {gradient( {Density Gradient( "Full Color" ), Gradient Transparency( "None" )} )}, Item ID( "Density", 1 ) )
            )}
        )
    )
);

Code Explanation:

1. Open data table.
2. Create Graph Builder object.
3. Set graph size.
4. Hide control panel.
5. Define X and Y variables.
6. Add contour element.
7. Send report to Graph Builder.
8. Dispatch to legend model.
9. Set legend properties.
10. Configure density gradient and transparency.

Example 1109

Summary: Creates a contour plot with nested factors using Graph Builder, configuring legend properties and applying density gradient.

Code:

dt = Open("data_table.jmp");
gb = dt << Graph Builder(
    Size( 528, 454 ),
    Show Control Panel( 0 ),
    Variables( X( :height ), Y( :weight ) ),
    Elements( Contour( X, Y, Legend( 4 ) ) ),
    SendToReport(
        Dispatch( {}, "400", ScaleBox,
            {Legend Model(
                4,
                Properties( 0, {gradient( {Density Gradient( "Full Color" ), Gradient Transparency( "None" )} )}, Item ID( "Density", 1 ) )
            )}
        )
    )
);
gb << Redo Analysis;

Code Explanation:

1. Open data table.
2. Create Graph Builder object.
3. Set graph size.
4. Hide control panel.
5. Define X and Y variables.
6. Add contour element.
7. Configure legend properties.
8. Apply density gradient.
9. Set gradient transparency.
10. Redo analysis.

Example 1110

Summary: Creates a contour plot with nested factors using Graph Builder, displaying standard deviation charts for CD3 and CD8 variables.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 534, 456 ),
    Show Control Panel( 0 ),
    Variables( X( :CD3 ), Y( :CD8 ) ),
    Elements( Contour( X, Y, Legend( 5 ), Contour Type 2D( "Bagplot" ) ) )
);

Code Explanation:

1. Open data table;
2. Launch Graph Builder.
3. Set window size 534x456.
4. Hide control panel.
5. Assign CD3 to X-axis.
6. Assign CD8 to Y-axis.
7. Add contour element.
8. Use legend position 5.
9. Specify 2D Bagplot type.
10. Generate graph.

Example 1111

Summary: Creates a contour plot with nested factors using Graph Builder, displaying standard deviation charts and legend for contours.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 528, 464 ),
    Show Control Panel( 0 ),
    Variables( X( :Region ), Y( :Name( "ACT Score (2004)" ) ) ),
    Elements( Contour( X, Y, Legend( 3 ), Contour Type 1D( "HDR" ) ) )
);

Code Explanation:

1. Open data table;
2. Create Graph Builder window.
3. Set window size.
4. Hide control panel.
5. Define X variable.
6. Define Y variable.
7. Add contour element.
8. Specify contour type HDR1D.
9. Display legend for contours.

Example 1112

Summary: Creates a variability chart with nested factors using Graph Builder, displaying standard deviation charts and overlaying age variable.

Code:

Open("data_table.jmp");
Graph Builder(
    Variables( X( :sex ), Y( :height ), Y( :weight, Position( 1 ) ), Overlay( :age ) ),
    Elements( Contour( X, Y( 1 ), Y( 2 ), Legend( 5 ), Contour Type 1D( "HDR" ) ) )
);

Code Explanation:

1. Open data table;
2. Launch Graph Builder.
3. Set X variable to sex.
4. Set first Y variable to height.
5. Set second Y variable to weight.
6. Position second Y on left.
7. Overlay age variable.
8. Add contour element.
9. Set X for contour.
10. Set first Y for contour.

Example 1113

Summary: Creates a variability chart with nested factors using operator and part configurations, displaying standard deviation charts.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 534, 450 ),
    Show Control Panel( 0 ),
    Variables( X( :Airline ), Y( :Arrival Delay ) ),
    Elements( Contour( X, Y, Legend( 4 ), Contour Type 1D( "HDR" ) ) ),
    SendToReport( Dispatch( {}, "400", ScaleBox, {Legend Model( 4, Properties( 0, {Fill Color( 3 )}, Item ID( "Arrival Delay", 1 ) ) )} ) )
);

Code Explanation:

1. Open data table;
2. Launch Graph Builder.
3. Set window size.
4. Hide control panel.
5. Assign X variable.
6. Assign Y variable.
7. Add contour element.
8. Configure contour type.
9. Customize legend fill color.
10. Display report.

Example 1114

Summary: Creates a variability chart with nested factors using Graph Builder, displaying standard deviation charts and leveraging operator and part configurations.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 528, 450 ),
    Show Control Panel( 0 ),
    Variables( X( :age ), Y( :height ), Overlay( :sex ) ),
    Elements( Contour( X, Y, Legend( 4 ), Contour Type 1D( "HDR" ) ) )
);

Code Explanation:

1. Open data table;
2. Launch Graph Builder.
3. Set window size.
4. Hide control panel.
5. Assign variables: age, height.
6. Use sex for overlay.
7. Add contour element.
8. Set X and Y axes.
9. Enable legend.
10. Use HDR1D contour type.

Example 1115

Summary: Creates a variability chart with nested factors using operator and part configurations, displaying standard deviation charts in Graph Builder.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 534, 418 ),
    Show Control Panel( 0 ),
    Variables(
        Y( :BMI ),
        Y( :BP, Position( 1 ) ),
        Y( :Total Cholesterol, Position( 1 ) ),
        Y( :LDL, Position( 1 ) ),
        Y( :HDL, Position( 1 ) ),
        Y( :TCH, Position( 1 ) ),
        Y( :Glucose, Position( 1 ) )
    ),
    Elements( Contour( Y( 1 ), Y( 2 ), Y( 3 ), Y( 4 ), Y( 5 ), Y( 6 ), Y( 7 ), Legend( 3 ), Contour Type 1D( "HDR" ) ) )
);

Code Explanation:

1. Open data table;
2. Create Graph Builder window.
3. Set window size.
4. Hide control panel.
5. Define Y variables.
6. Add BMI to Y axis.
7. Add BP to Y axis.
8. Add Total Cholesterol to Y axis.
9. Add LDL to Y axis.
10. Add HDL to Y axis.
11. Add TCH to Y axis.
12. Add Glucose to Y axis.
13. Create contour element.
14. Set contour type to HDR1D.

Example 1116

Summary: Creates a variability chart with nested factors using operator and part configurations, displaying standard deviation charts in Graph Builder.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 534, 454 ),
    Show Control Panel( 0 ),
    Variables( Y( :part# ), Y( :Operator, Position( 1 ) ), Group X( :Standard ) ),
    Elements( Contour( Y( 1 ), Y( 2 ), Legend( 10 ) ) ),
    SendToReport(
        Dispatch( {}, "part#", ScaleBox, {Reversed Scale} ),
        Dispatch( {}, "400", ScaleBox, {Legend Model( 10, Properties( 0, {Transparency( 0.8 ), Fill Pattern( "filled circle" )} ) )} )
    )
);

Code Explanation:

1. Open data table.
2. Create Graph Builder window.
3. Set window size.
4. Hide control panel.
5. Define Y variables.
6. Define additional Y variable.
7. Group by X variable.
8. Add contour element.
9. Reverse scale for part#.
10. Customize legend appearance.

Example 1117

Summary: Creates a variability chart with nested factors using operator and part configurations, displaying standard deviation charts for Hwy MPG and City MPG.

Code:

dt = Open("data_table.jmp");
Graph Builder(
    Size( 528, 448 ),
    Show Control Panel( 0 ),
    Variables( X( :Engine ), Y( :Hwy MPG ), Y( :City MPG ) ),
    Elements( Position( 1, 1 ), Points( X, Y, Legend( 4 ) ), Contour( X, Y, Legend( 7 ) ) ),
    Elements( Position( 1, 2 ), Points( X, Y, Legend( 5 ) ), Contour( X, Y, Legend( 8 ) ) ),
    SendToReport( Dispatch( {}, "400", LegendBox, {Legend Position( {4, [1], 7, [2], 5, [0], 8, [3]} )} ) )
);

Code Explanation:

1. Open data table.
2. Launch Graph Builder.
3. Set graph size.
4. Hide control panel.
5. Assign variables: X=Engine, Y1=Hwy MPG, Y2=City MPG.
6. Add points and contour elements for Hwy MPG.
7. Add points and contour elements for City MPG.
8. Adjust legend positions.

Example 1118

Summary: Creates a variability chart with nested factors using operator and part configurations, displaying standard deviation charts within Graph Builder.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 300, 247 ),
    Show Control Panel( 0 ),
    Variables( X( :part# ), Y( :Measurement ) ),
    Elements( Contour( X, Y, Legend( 8 ), Number of Levels( 10 ) ) ),
    SendToReport( Dispatch( {}, "400", ScaleBox, {Legend Model( 8, Properties( 0, {Fill Color( 37 ), Transparency( 1 )} ) )} ) )
);

Code Explanation:

1. Open data table.
2. Launch Graph Builder.
3. Set window size.
4. Hide control panel.
5. Assign variables.
6. Add contour element.
7. Set number of levels.
8. Customize legend properties.
9. Change fill color.
10. Set transparency.

Example 1119

Summary: Creates a variability chart with nested factors using Graph Builder, displaying standard deviation charts and customizing violin scaling.

Code:

Open("data_table.jmp");
Graph Builder( Size( 528, 448 ), Show Control Panel( 0 ), Variables( X( :age ), Y( :height ) ), Elements( Contour( X, Y, Legend( 4 ) ) ) );
Graph Builder(
    Size( 528, 448 ),
    Show Control Panel( 0 ),
    Variables( X( :age ), Y( :height ) ),
    Elements( Contour( X, Y, Legend( 4 ), Violin Scaling( "Equal Width" ) ) )
);

Code Explanation:

1. Open data table.
2. Create Graph Builder window.
3. Set window size.
4. Hide control panel.
5. Define X variable as age.
6. Define Y variable as height.
7. Add contour element.
8. Add legend to contour.
9. Create second Graph Builder window.
10. Customize violin scaling.

Example 1120

Summary: Creates variability charts with nested factors using Graph Builder, displaying standard deviation charts and configuring violin scaling options.

Code:

Open("data_table.jmp");
Graph Builder( Size( 528, 448 ), Show Control Panel( 0 ), Variables( X( :age ), Y( :height ) ), Elements( Contour( X, Y, Legend( 4 ) ) ) );
Graph Builder(
    Size( 528, 448 ),
    Show Control Panel( 0 ),
    Variables( X( :age ), Y( :height ) ),
    Elements( Contour( X, Y, Legend( 4 ), Violin Scaling( "Equal Width" ) ) )
);
Graph Builder(
    Size( 528, 448 ),
    Show Control Panel( 0 ),
    Variables( X( :age ), Y( :height ) ),
    Elements( Contour( X, Y, Legend( 4 ), Violin Scaling( "Weighted Area" ) ) )
);

Code Explanation:

1. Open data table;
2. Create graph builder window.
3. Set size to 528x448.
4. Hide control panel.
5. Assign age to X-axis.
6. Assign height to Y-axis.
7. Add contour element.
8. Set legend position to 4.
9. Repeat steps 2-8.
10. Change violin scaling to "Weighted Area".

Example 1121

Summary: Creates three contour plots with violin scaling to visualize the relationship between age and height, allowing for customization of violin scaling options.

Code:

Open("data_table.jmp");
Graph Builder( Variables( X( :age ), Y( :height ) ), Elements( Contour( X, Y, Legend( 4 ) ) ) );
Graph Builder( Variables( X( :age ), Y( :height ) ), Elements( Contour( X, Y, Legend( 4 ), Violin Scaling( "Equal Width" ) ) ) );
Graph Builder( Variables( X( :age ), Y( :height ) ), Elements( Contour( X, Y, Legend( 4 ), Violin Scaling( "Weighted Area" ) ) ) );

Code Explanation:

1. Open data_table data
2. Create contour plot.
3. Add violin scaling.
4. Change violin scaling.
5. Create second contour plot.
6. Add violin scaling.
7. Change violin scaling.
8. Create third contour plot.
9. Add violin scaling.
10. Change violin scaling.

Example 1122

Summary: Creates a variability chart with nested factors using Graph Builder, displaying standard deviation charts and allowing for interactive exploration.

Code:

Open("data_table.jmp");
Graph Builder( Variables( X( :age ), Y( :height ), Overlay( :sex ) ), Elements( Contour( X, Y, Legend( 4 ) ) ) );
Graph Builder(
    Variables( X( :age ), Y( :height ), Overlay( :sex ) ),
    Elements( Contour( X, Y, Legend( 4 ), Violin Scaling( "Equal Width" ) ) )
);

Code Explanation:

1. Open data table;
2. Create initial graph builder.
3. Set X variable to age.
4. Set Y variable to height.
5. Overlay by sex.
6. Add contour element.
7. Set legend for contour.
8. Create second graph builder.
9. Repeat previous settings.
10. Add violin scaling to contour.

Example 1123

Summary: Creates contour plots with nested factors using Graph Builder, displaying standard deviation charts and violin scaling options.

Code:

Open("data_table.jmp");
Graph Builder( Variables( X( :age ), Y( :height ) ), Elements( Contour( X, Y, Legend( 4 ) ) ) );
Graph Builder( Variables( X( :age ), Y( :height ) ), Elements( Contour( X, Y, Legend( 4 ), Violin Scaling( "Equal Width" ) ) ) );
Graph Builder( Variables( X( :age ), Y( :height ) ), Elements( Contour( X, Y, Legend( 4 ), Violin Scaling( "Weighted Area" ) ) ) );
Open("data_table.jmp");
Graph Builder( Variables( X( :age ), Y( :height ), Overlay( :sex ) ), Elements( Contour( X, Y, Legend( 4 ) ) ) );
Graph Builder(
    Variables( X( :age ), Y( :height ), Overlay( :sex ) ),
    Elements( Contour( X, Y, Legend( 4 ), Violin Scaling( "Equal Width" ) ) )
);
Graph Builder(
    Variables( X( :age ), Y( :height ), Overlay( :sex ) ),
    Elements( Contour( X, Y, Legend( 4 ), Violin Scaling( "Weighted Area" ) ) )
);

Code Explanation:

1. Open data table.
2. Create contour plot for age vs height.
3. Create contour plot with violin scaling "Equal Width".
4. Create contour plot with violin scaling "Weighted Area".
5. Open data table.
6. Create contour plot with sex overlay.
7. Create contour plot with sex overlay and violin scaling "Equal Width".
8. Create contour plot with sex overlay and violin scaling "Weighted Area".

Example 1124

Summary: Creates contour plots with nested factors using operator and part configurations, displaying standard deviation charts for age vs height data.

Code:

Open("data_table.jmp");
Graph Builder( Variables( X( :age ), Y( :height ) ), Elements( Contour( X, Y, Legend( 4 ) ) ) );
Graph Builder( Variables( X( :age ), Y( :height ) ), Elements( Contour( X, Y, Legend( 4 ), Violin Scaling( "Equal Width" ) ) ) );
Graph Builder( Variables( X( :age ), Y( :height ) ), Elements( Contour( X, Y, Legend( 4 ), Violin Scaling( "Weighted Area" ) ) ) );
Open("data_table.jmp");
Graph Builder( Variables( X( :age ), Y( :height ), Overlay( :sex ) ), Elements( Contour( X, Y, Legend( 4 ) ) ) );
Graph Builder(
    Variables( X( :age ), Y( :height ), Overlay( :sex ) ),
    Elements( Contour( X, Y, Legend( 4 ), Violin Scaling( "Equal Width" ) ) )
);

Code Explanation:

1. Open data table;
2. Create contour plot for age vs height.
3. Create contour plot with equal width violins.
4. Create contour plot with weighted area violins.
5. Open data table;
6. Create contour plot with sex overlay.
7. Create contour plot with sex overlay and equal width violins.

Example 1125

Summary: Creates a variability chart with nested factors using Graph Builder, displaying standard deviation charts and customizing legend styles.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 912, 651 ),
    Show Control Panel( 0 ),
    Variables( X( :Species ), Y( :Petal length ) ),
    Elements( Box Plot( X, Y, Legend( 5 ), Box Style( "Thin" ) ), Contour( X, Y, Legend( 6 ) ) ),
    SendToReport( Dispatch( {}, "Species", ScaleBox, {Label Row( Show Major Grid( 1 ) )} ) )
);

Code Explanation:

1. Open data table;
2. Create Graph Builder window.
3. Set window size.
4. Hide control panel.
5. Define X variable: Species.
6. Define Y variable: Petal length.
7. Add Box Plot element.
8. Add Contour element.
9. Customize Box Plot legend.
10. Customize Contour legend.

Example 1126

Summary: Creates a variability chart with nested factors using Graph Builder, displaying standard deviation charts for analysis.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 528, 448 ),
    Show Control Panel( 0 ),
    Variables( X( :Engine ), Y( :Hwy MPG ), Y( :City MPG ), Color( :"# Cyl"n ), Color( :Trans ) ),
    Elements( Position( 1, 1 ), Contour( X, Y, Color( 1 ), Legend( 17 ) ) ),
    Elements( Position( 1, 2 ), Contour( X, Y, Color( 2 ), Legend( 18 ) ) )
);

Code Explanation:

1. Open data table;
2. Launch Graph Builder.
3. Set window size.
4. Hide control panel.
5. Define X variable.
6. Define first Y variable.
7. Define second Y variable.
8. Define first color variable.
9. Define second color variable.
10. Add contour element for first Y.
11. Add contour element for second Y.

Example 1127

Summary: Creates two geographic maps to visualize Latitude and Longitude data, utilizing Graph Builder and contour elements with legend.

Code:

Open("data_table.jmp");
gb = Graph Builder(
    Size( 653, 396 ),
    Show Control Panel( 0 ),
    Variables( X( :Longitude ), Y( :Latitude ) ),
    Elements( Contour( X, Y, Legend( 2 ) ) ),
    SendToReport(
        Dispatch( {}, "Graph Builder", FrameBox,
            {Background Map( Boundaries( "US States" ) ), Grid Line Order( 2 ), Reference Line Order( 3 )}
        )
    )
);
cs = (gb << Report)[FrameBox( 1 )] << Find Seg( Contour Seg( 1 ) );
cs << Clip Shape( Boundaries( "US States" ) );
gb2 = Graph Builder(
    Size( 653, 396 ),
    Show Control Panel( 0 ),
    Variables( X( :Longitude ), Y( :Latitude ) ),
    Elements( Contour( X, Y, Legend( 2 ) ) ),
    SendToReport(
        Dispatch( {}, "Graph Builder", FrameBox,
            {Background Map( Boundaries( "US States" ) ), Grid Line Order( 2 ), Reference Line Order( 3 )}
        )
    )
);
cs2 = (gb2 << Report)[FrameBox( 1 )] << Find Seg( Contour Seg( 1 ) );
cs2 << Clip Shape( cs << Get Clip Shape() );

Code Explanation:

1. Open data table.
2. Create Graph Builder object.
3. Set size and hide control panel.
4. Define X and Y variables.
5. Add contour element with legend.
6. Configure background map and grid lines.
7. Find first contour segment.
8. Clip shape to US states.
9. Create second Graph Builder object.
10. Repeat steps 3-8 for second graph.

Example 1128

Summary: Creates a contour map with nested factors using Graph Builder, displaying standard deviation charts and clipping shapes to US states boundaries.

Code:

Open("data_table.jmp");
gb = Graph Builder(
    Size( 653, 396 ),
    Show Control Panel( 0 ),
    Variables( X( :Longitude ), Y( :Latitude ), Color( :OZONE ) ),
    Elements( Contour( X, Y, Legend( 2 ) ) ),
    SendToReport(
        Dispatch( {}, "Graph Builder", FrameBox,
            {Background Map( Boundaries( "US States" ) ), Grid Line Order( 2 ), Reference Line Order( 3 )}
        )
    )
);
cs = (gb << Report)[FrameBox( 1 )] << Find Seg( Contour Seg( 1 ) );
cs << Clip Shape( Boundaries( "US States" ) );
gb2 = Graph Builder(
    Size( 653, 396 ),
    Show Control Panel( 0 ),
    Variables( X( :Longitude ), Y( :Latitude ), Color( :OZONE ) ),
    Elements( Contour( X, Y, Legend( 2 ) ) ),
    SendToReport(
        Dispatch( {}, "Graph Builder", FrameBox,
            {Background Map( Boundaries( "US States" ) ), Grid Line Order( 2 ), Reference Line Order( 3 )}
        )
    )
);
cs2 = (gb2 << Report)[FrameBox( 1 )] << Find Seg( Contour Seg( 1 ) );
cs2 << Clip Shape( cs << Get Clip Shape() );

Code Explanation:

1. Open data table;
2. Create Graph Builder object.
3. Set size and hide control panel.
4. Define variables: Longitude, Latitude, OZONE.
5. Add contour element with legend.
6. Customize report with background map.
7. Find contour segment.
8. Clip shape using US states boundaries.
9. Create second Graph Builder object.
10. Copy clip shape from first graph to second.

Example 1129

Summary: Creates two variability charts with nested factors using Graph Builder and displays standard deviation charts.

Code:

Open("data_table.jmp");
gb = Graph Builder(
    Show Control Panel( 0 ),
    Variables( X( :height ), Y( :weight ), Overlay( :sex ) ),
    Elements( Contour( X, Y, Legend( 3 ) ) )
);
r = (gb << Report);
cs = r[FrameBox( 1 )] << Find Seg( Contour Seg( 1 ) );
cs << Clip Shape( Path( [60 80 1, 50 140 2, 65 120 2, 70 65 -2] ) );
gb2 = Graph Builder(
    Show Control Panel( 0 ),
    Variables( X( :height ), Y( :weight ), Overlay( :sex ) ),
    Elements( Contour( X, Y, Legend( 3 ) ) )
);
r2 = (gb2 << Report);
cs2 = r2[FrameBox( 1 )] << Find Seg( Contour Seg( 1 ) );
cs2 << Clip Shape( cs << Get Clip Shape() );

Code Explanation:

1. Open data_table data
2. Create Graph Builder object.
3. Hide control panel.
4. Set X, Y, and overlay variables.
5. Add contour element with legend.
6. Retrieve graph report.
7. Find first contour segment.
8. Define clip shape path.
9. Apply clip shape to contour.
10. Repeat steps 2-9 for second graph.

Example 1130

Summary: Creates a variability chart with nested factors using operator and part configurations, displaying standard deviation charts.

Code:

Open("data_table.jmp");
gb = Graph Builder(
    Show Control Panel( 0 ),
    Variables( X( :height ), Y( :weight ), Color( :sex ) ),
    Elements( Contour( X, Y, Legend( 3 ) ) )
);
r = (gb << Report);
cs = r[FrameBox( 1 )] << Find Seg( Contour Seg( 1 ) );
cs << Clip Shape( Path( [60 80 1, 50 140 2, 65 120 2, 70 65 -2] ) );
gb2 = Graph Builder(
    Show Control Panel( 0 ),
    Variables( X( :height ), Y( :weight ), Color( :sex ) ),
    Elements( Contour( X, Y, Legend( 3 ) ) )
);
r2 = (gb2 << Report);
cs2 = r2[FrameBox( 1 )] << Find Seg( Contour Seg( 1 ) );
cs2 << Clip Shape( cs << Get Clip Shape() );

Code Explanation:

1. Open data table;
2. Create Graph Builder object.
3. Hide control panel.
4. Set variables for X, Y, and color.
5. Add contour element.
6. Retrieve report from Graph Builder.
7. Find first contour segment.
8. Set clip shape for contour.
9. Create second Graph Builder object.
10. Apply same clip shape to second contour.

Example 1131

Summary: Creates a variability chart with nested factors using Graph Builder and displays standard deviation charts.

Code:

Open("data_table.jmp");
gb = Graph Builder(
    Show Control Panel( 0 ),
    Variables( X( :height ), Y( :weight ), Overlay( :age ) ),
    Elements( Contour( X, Y, Legend( 3 ) ) )
);
r = (gb << Report);
cs = r[FrameBox( 1 )] << Find Seg( Contour Seg( 1 ) );
cs << Clip Shape( Path( [60 80 1, 50 140 2, 45 120 2, 70 65 -2] ) );
gb2 = Graph Builder(
    Show Control Panel( 0 ),
    Variables( X( :height ), Y( :weight ), Overlay( :age ) ),
    Elements( Contour( X, Y, Legend( 3 ) ) )
);
r2 = (gb2 << Report);
cs2 = r2[FrameBox( 1 )] << Find Seg( Contour Seg( 1 ) );
cs2 << Clip Shape( cs << Get Clip Shape() );

Code Explanation:

1. Open data table;
2. Create Graph Builder object gb.
3. Set X, Y, Overlay variables.
4. Add Contour element to gb.
5. Retrieve report from gb.
6. Find first contour segment in gb.
7. Set clip shape for contour segment.
8. Create second Graph Builder object gb2.
9. Set X, Y, Overlay variables for gb2.
10. Add Contour element to gb2 and apply clip shape.

Example 1132

Summary: Creates two variability charts with nested factors using operator and part configurations, displaying standard deviation charts.

Code:

Open("data_table.jmp");
gb = Graph Builder(
    Show Control Panel( 0 ),
    Variables( X( :height ), Y( :weight ), Color( :age ) ),
    Elements( Contour( X, Y, Legend( 3 ) ) )
);
r = (gb << Report);
cs = r[FrameBox( 1 )] << Find Seg( Contour Seg( 1 ) );
cs << Clip Shape( Path( [60 80 1, 50 140 2, 35 120 2, 70 65 -2] ) );
gb2 = Graph Builder(
    Show Control Panel( 0 ),
    Variables( X( :height ), Y( :weight ), Color( :age ) ),
    Elements( Contour( X, Y, Legend( 3 ) ) )
);
r2 = (gb2 << Report);
cs2 = r2[FrameBox( 1 )] << Find Seg( Contour Seg( 1 ) );
cs2 << Clip Shape( cs << Get Clip Shape() );

Code Explanation:

1. Open data table.
2. Create graph builder object.
3. Hide control panel.
4. Set variables for graph.
5. Add contour element to graph.
6. Retrieve graph report.
7. Find contour segment.
8. Define clip shape path.
9. Apply clip shape to contour.
10. Repeat steps 2-9 for second graph.

Example 1133

Summary: Creates two geographic maps to visualize Latitude and Longitude data, with contour elements and customized report settings.

Code:

Open("data_table.jmp");
gb = Graph Builder(
    Size( 653, 396 ),
    Show Control Panel( 0 ),
    Variables( X( :Longitude ), Y( :Latitude ) ),
    Elements( Contour( X, Y, Legend( 2 ) ) ),
    SendToReport(
        Dispatch( {}, "400", ScaleBox, {Legend Model( 2, Properties( 0, {Fill Color( 3 )} ) )} ),
        Dispatch( {}, "Graph Builder", FrameBox,
            {Background Map( Boundaries( "US States" ) ), Grid Line Order( 2 ), Reference Line Order( 3 )}
        )
    )
);
cs = (gb << Report)[FrameBox( 1 )] << Find Seg( Contour Seg( 1 ) );
cs << Clip Shape( Boundaries( "US States", ID( "north carolina" ) ) );
gb2 = Graph Builder(
    Size( 653, 396 ),
    Show Control Panel( 0 ),
    Variables( X( :Longitude ), Y( :Latitude ) ),
    Elements( Contour( X, Y, Legend( 2 ) ) ),
    SendToReport(
        Dispatch( {}, "400", ScaleBox, {Legend Model( 2, Properties( 0, {Fill Color( 3 )} ) )} ),
        Dispatch( {}, "Graph Builder", FrameBox,
            {Background Map( Boundaries( "US States" ) ), Grid Line Order( 2 ), Reference Line Order( 3 )}
        )
    )
);
cs2 = (gb2 << Report)[FrameBox( 1 )] << Find Seg( Contour Seg( 1 ) );
cs2 << Clip Shape( cs << Get Clip Shape() );

Code Explanation:

1. Open data table.
2. Create Graph Builder object.
3. Set size and hide control panel.
4. Assign Longitude and Latitude as variables.
5. Add contour element with legend.
6. Customize report: set legend fill color.
7. Add background map showing US states.
8. Find first contour segment.
9. Clip contour to North Carolina boundaries.
10. Repeat steps 2-9 for a second graph.

Example 1134

Summary: Creates a variability chart with nested factors using operator and part configurations, displaying standard deviation charts in Graph Builder.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 528, 448 ),
    Show Control Panel( 0 ),
    Variables( X( :Engine ), Y( :Hwy MPG ), Y( :City MPG ) ),
    Elements( Position( 1, 1 ), Points( X, Y, Legend( 7 ) ), Contour( X, Y, Legend( 16 ) ) ),
    Elements( Position( 1, 2 ), Points( X, Y, Legend( 8 ) ), Contour( X, Y, Legend( 17 ) ) )
);

Code Explanation:

1. Open data table.
2. Launch Graph Builder.
3. Set window size.
4. Hide control panel.
5. Define X variable.
6. Define first Y variable.
7. Define second Y variable.
8. Add points element.
9. Add contour element.
10. Add second set of elements.

Example 1135

Summary: Creates a Graph Builder visualization with nested factors using operator and part configurations, displaying standard deviation charts.

Code:

Open("data_table.jmp");
Graph Builder(
    Show Control Panel( 0 ),
    Variables( X( :height ), Y( :weight ) ),
    Elements( Points( X, Y, Legend( 7 ) ), Ellipse( X, Y, Legend( 10 ) ) )
);

Code Explanation:

1. Open data table;
2. Launch Graph Builder.
3. Hide control panel.
4. Set X variable to height.
5. Set Y variable to weight.
6. Add points element.
7. Add ellipse element.
8. Assign legend for points.
9. Assign legend for ellipse.
10. Display graph.

Example 1136

Summary: Creates a Graph Builder window with an ellipse element to visualize the relationship between sex and weight, utilizing customized scales for both axes.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 534, 446 ),
    Show Control Panel( 0 ),
    Variables( X( :sex ), Y( :weight ) ),
    Elements( Ellipse( X, Y, Legend( 8 ) ) ),
    SendToReport(
        Dispatch( {}, "sex", ScaleBox, {Min( -1.2571124227889 ), Max( 2.24534161490683 ), Inc( 1 ), Minor Ticks( 0 )} ),
        Dispatch( {}, "weight", ScaleBox, {Max( 203.553299492386 )} )
    )
);

Code Explanation:

1. Open data table;
2. Create Graph Builder window.
3. Set window size.
4. Hide control panel.
5. Assign sex to X-axis.
6. Assign weight to Y-axis.
7. Add ellipse element.
8. Customize sex scale.
9. Customize weight scale.

Example 1137

Summary: Creates a graph builder window with an ellipse element to visualize the relationship between age and height, utilizing Graph Builder.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 300, 150 ),
    Show Control Panel( 0 ),
    Variables( X( :age ), Y( :height ) ),
    Elements( Ellipse( X, Y, Legend( 9 ) ) ),
    SendToReport( Dispatch( {}, "Graph Builder", FrameBox, {DispatchSeg( Poly Seg( 1 ), {Fill Pattern( "left slant medium" )} )} ) )
);

Code Explanation:

1. Open data table.
2. Create Graph Builder window.
3. Set window size.
4. Hide control panel.
5. Define X variable.
6. Define Y variable.
7. Add ellipse element.
8. Customize legend.
9. Send report command.
10. Set fill pattern.

Example 1138

Summary: Creates a Graph Builder window with nested factors, displaying points and ellipse elements, and customizing legend models to visualize variability data.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 351, 310 ),
    Show Control Panel( 0 ),
    Variables( X( :sex ), Y( :height ) ),
    Elements( Points( X, Y, Legend( 3 ) ), Ellipse( X, Y, Legend( 4 ) ) ),
    SendToReport(
        Dispatch( {}, "400", ScaleBox,
            {Legend Model(
                4,
                Type Properties( 0, "Bar", {Fill Pattern( "left slant heavy b" )} ),
                Properties( 0, {Fill Pattern( "left slant heavy b" )}, Item ID( "height: (90%)", 1 ) )
            )}
        )
    )
);

Code Explanation:

1. Open data table.
2. Create Graph Builder window.
3. Set window size.
4. Hide control panel.
5. Assign X variable.
6. Assign Y variable.
7. Add points element.
8. Add ellipse element.
9. Customize legend model.
10. Apply fill pattern to ellipse.

Example 1139

Summary: Creates a variability chart with nested factors using Graph Builder, displaying standard deviation charts and overlaying data by sex.

Code:

dt = Open("data_table.jmp");
Graph Builder(
    Show Control Panel( 0 ),
    Size( 570, 546 ),
    Variables( X( :Weight, Size( 18 ) ), Y( :Oxy, Size( 25 ) ), Overlay( :Sex ) ),
    Elements( Points( X, Y, Legend( 9 ) ), Ellipse( X, Y, Legend( 10 ), Coverage( "90%" ) ) )
);

Code Explanation:

1. Open table.
2. Create Graph Builder.
3. Hide control panel.
4. Set size.
5. Define variables.
6. Add points element.
7. Add ellipse element.
8. Set ellipse coverage.
9. Apply overlay variable.
10. Display graph.

Example 1140

Summary: Creates a Graph Builder window with nested factors using operator and part configurations, displaying standard deviation charts.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 570, 546 ),
    Show Control Panel( 0 ),
    Variables( X( :Weight ), Y( :Oxy ), Overlay( :Sex ) ),
    Elements( Points( X, Y, Legend( 9 ) ), Ellipse( X, Y, Legend( 10 ), Mean Point( 1 ) ) )
);

Code Explanation:

1. Open data table;
2. Create Graph Builder window.
3. Set size to 570x546.
4. Hide control panel.
5. Assign Weight to X-axis.
6. Assign Oxy to Y-axis.
7. Use Sex for overlay.
8. Add points element.
9. Add ellipse element.
10. Include mean point in ellipse.

Example 1141

Summary: Creates a graph builder with nested factors using operator and part configurations, displaying standard deviation charts.

Code:

Open("data_table.jmp");
Graph Builder(
    Variables( X( :height ), Y( :weight ) ),
    Elements( Points( X, Y, Legend( 2 ) ), Ellipse( X, Y, Legend( 4 ), Mean Point( 1 ) ) ),
    SendToReport(
        Dispatch( {}, "Graph Builder", FrameBox,
            Add Pin Annotation(
                Seg( Marker Seg( 2 ) ),
                Index( 0 ),
                Index Row( 0 ),
                UniqueID( 1041104992 ),
                FoundPt( {609, 363} ),
                Origin( {62.6426580268809, 104.911679467296} ),
                Tag Line( 1 )
            )
        )
    )
);

Code Explanation:

1. Open data table;
2. Launch Graph Builder.
3. Set X variable to height.
4. Set Y variable to weight.
5. Add points element to graph.
6. Add ellipse element to graph.
7. Add mean point to ellipse.
8. Send report to Graph Builder.
9. Add pin annotation to graph.
10. Configure pin annotation properties.

Example 1142

Summary: Creates a graph builder with nested factors using operator and part configurations, displaying standard deviation charts.

Code:

dt = Open("data_table.jmp");
gb = Graph Builder(
    Size( 534, 454 ),
    Show Control Panel( 0 ),
    Variables( X( :height ), Y( :weight ) ),
    Elements( Points( X, Y, Legend( 2 ) ), Ellipse( X, Y, Legend( 5 ), Correlation( 1 ) ) )
);

Code Explanation:

1. Open data table.
2. Create Graph Builder object.
3. Set graph size.
4. Hide control panel.
5. Define X variable.
6. Define Y variable.
7. Add points element.
8. Add ellipse element.
9. Set ellipse correlation.
10. Display graph.

Example 1143

Summary: Creates a Graph Builder object to visualize the relationship between Rotten Tomatoes Score and Audience Score, with genre as a wrap variable, using points and ellipse elements.

Code:

dt under test = Open("data_table.jmp");
obj = Graph Builder(
    Size( 534, 489 ),
    Show Control Panel( 0 ),
    Variables( X( :Rotten Tomatoes Score ), Y( :Audience Score ), Wrap( :Genre ) ),
    Elements( Points( X, Y, Legend( 17 ) ), Ellipse( X, Y, Legend( 19 ) ) ),
    SendToReport(
        Dispatch( {}, "400", ScaleBox,
            {Legend Model( 17, Properties( 0, {Line Color( -8323072 ), Fill Color( -8323072 )} ) ),
            Legend Model( 19, Properties( 0, {Line Color( -127 ), Fill Color( 53 )} ) )}
        ),
        Dispatch( {}, "400", LegendBox, {Legend Position( {1, 0} )} ),
        Dispatch( {}, "Graph Builder", FrameBox, {Background Color( 32 )} ),
        Dispatch( {}, "Graph Builder", FrameBox( 2 ), {Background Color( 32 )} ),
        Dispatch( {}, "Graph Builder", FrameBox( 3 ), {Background Color( 32 )} ),
        Dispatch( {}, "Graph Builder", FrameBox( 4 ), {Background Color( 32 )} ),
        Dispatch( {}, "Graph Builder", FrameBox( 5 ), {Background Color( 32 )} ),
        Dispatch( {}, "Graph Builder", FrameBox( 6 ), {Background Color( 32 )} ),
        Dispatch( {}, "Graph Builder", FrameBox( 7 ), {Background Color( 32 )} ),
        Dispatch( {}, "Graph Builder", FrameBox( 8 ), {Background Color( 32 )} ),
        Dispatch( {}, "Graph Builder", FrameBox( 9 ), {Background Color( 32 )} )
    )
);

Code Explanation:

1. Open data table.
2. Create Graph Builder object.
3. Set graph size.
4. Hide control panel.
5. Define X and Y variables.
6. Wrap by genre.
7. Add points element.
8. Add ellipse element.
9. Customize legend colors.
10. Set legend position.
11. Change frame background color.

Example 1144

Summary: Creates a variability chart with nested factors using Graph Builder, configuring X and Y variables, overlaying sex, and displaying ellipse and points elements.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 606, 546 ),
    Variables( X( :height ), Y( :weight ), Overlay( :sex ) ),
    Elements( Ellipse( X, Y, Legend( 3 ) ), Points( X, Y, Legend( 4 ) ) ), 
);

Code Explanation:

1. Open data_table data
2. Launch Graph Builder.
3. Set window size.
4. Assign X variable.
5. Assign Y variable.
6. Add overlay variable.
7. Add ellipse element.
8. Add points element.
9. Configure ellipse legend.
10. Configure points legend.

Example 1145

Summary: Creates a variability chart with nested factors using Graph Builder, displaying standard deviation charts and customizing legends for points and smoother elements.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 534, 456 ),
    Show Control Panel( 0 ),
    Variables( X( :Sold Month ), Y( :Sold Quantity ) ),
    Elements( Points( X, Y, Legend( 5 ) ), Smoother( X, Y, Legend( 6 ) ) ),
    SendToReport(
        Dispatch( {}, "400", ScaleBox,
            {Legend Model( 5, Properties( 0, {Line Color( 20 )}, Item ID( "Sold Quantity", 1 ) ) ),
            Legend Model( 6, Properties( 0, {Line Color( 20 ), Arrowhead( "End" ), Fill Color( 0 )}, Item ID( "Smooth", 1 ) ) )}
        )
    )
);

Code Explanation:

1. Open data table;
2. Create Graph Builder window.
3. Set window size.
4. Hide control panel.
5. Define X and Y variables.
6. Add points element.
7. Add smoother element.
8. Customize legend for points.
9. Customize legend for smoother.
10. Apply customizations.

Example 1146

Summary: Creates a variability chart with nested factors using Graph Builder, displaying standard deviation charts and customizing Y-axis titles.

Code:

Open("data_table.jmp") << Graph Builder(
    Size( 534, 450 ),
    Show Control Panel( 0 ),
    Variables( X( :age ), Y( :weight ), Y( :age ), Y( :height ) ),
    Elements( Position( 1, 1 ), Points( X, Y, Legend( 8 ) ) ),
    Elements( Position( 1, 2 ), Points( X, Y, Legend( 9 ) ) ),
    Elements( Position( 1, 3 ), Points( X, Y, Legend( 10 ) ) ),
    SendToReport(
        Dispatch( {}, "Y title", TextEditBox, {Set Text( "weight long enough to wrap" )} ),
        Dispatch( {}, "Y 1 title", TextEditBox, {Set Text( "wide age" )} )
    )
);

Code Explanation:

1. Open data table;
2. Launch Graph Builder.
3. Set window size.
4. Hide control panel.
5. Assign variables to axes.
6. Add first points element.
7. Add second points element.
8. Add third points element.
9. Set Y-axis title text.
10. Set Y1-axis title text.

Example 1147

Summary: Creates a variability chart with nested factors using Graph Builder, displaying standard deviation charts and customizing Y title text.

Code:

gb = Open("data_table.jmp") << Graph Builder(
    Size( 534, 450 ),
    Show Control Panel( 0 ),
    Variables( X( :age ), Y( :weight ), Y( :age ), Y( :height ) ),
    Elements( Position( 1, 1 ), Points( X, Y, Legend( 8 ) ) ),
    Elements( Position( 1, 2 ), Points( X, Y, Legend( 9 ) ) ),
    Elements( Position( 1, 3 ), Points( X, Y, Legend( 10 ) ) ),
    SendToReport(
        Dispatch( {}, "Y title", TextEditBox, {Set Text( "weight long enough to wrap" )} ),
        Dispatch( {}, "Y 1 title", TextEditBox, {Set Text( "wide age" )} )
    )
);
gb << Journal;

Code Explanation:

1. Open table.
2. Create Graph Builder.
3. Set size.
4. Hide control panel.
5. Define variables.
6. Add first points element.
7. Add second points element.
8. Add third points element.
9. Set Y title text.
10. Set Y1 title text.

Example 1148

Summary: Creates a graph builder with nested factors using operator and part configurations, displaying standard deviation charts.

Code:

gb = Open("data_table.jmp") << Graph Builder(
    Size( 528, 464 ),
    Show Control Panel( 0 ),
    Variables( X( :name ), Y( :height ) ),
    Elements( Bar( X, Y, Legend( 4 ) ) ),
    SendToReport( Dispatch( {}, "name", ScaleBox, {Label Row( Label Orientation( "Angled" ) )} ) )
);
gb << Journal;

Code Explanation:

1. Open data table;
2. Create Graph Builder object.
3. Set graph size.
4. Hide control panel.
5. Define X and Y variables.
6. Add bar element.
7. Set legend position.
8. Send report command.
9. Angulate label orientation.
10. Generate journal.

Example 1149

Summary: Creates a graph builder with nested factors using operator and part configurations, displaying standard deviation charts.

Code:

gb = Open("data_table.jmp") << Graph Builder(
    Size( 528, 464 ),
    Show Control Panel( 0 ),
    Variables( X( :name ), Y( :height ) ),
    Elements( Bar( X, Y, Legend( 4 ) ) ),
    SendToReport( Dispatch( {}, "name", ScaleBox, {Label Row( Label Orientation( "Angled" ) )} ) )
);
gb << Journal;
gb << Close Window;

Code Explanation:

1. Open data table.
2. Create Graph Builder object.
3. Set graph size.
4. Hide control panel.
5. Define X and Y variables.
6. Add bar element.
7. Rotate X-axis labels.
8. Convert to journal.
9. Close window.

Example 1150

Summary: Creates a variability chart with nested factors using Graph Builder, displaying standard deviation charts for height, name, age, and sex.

Code:

dt = Open("data_table.jmp");
gb = dt << Graph Builder(
    Show Control Panel( 0 ),
    Variables( X( :height ), Y( :name ), Y( :age ), Y( :sex ) ),
    Elements( Position( 1, 1 ), Points( X, Y, Legend( 6 ) ) ),
    Elements( Position( 1, 2 ), Points( X, Y, Legend( 7 ) ) ),
    Elements( Position( 1, 3 ), Points( X, Y, Legend( 8 ) ) ),
    SendToReport(
        Dispatch( {}, "Y title", TextEditBox, {Set Text( "the name" )} ),
        Dispatch( {}, "Y 1 title", TextEditBox, {Set Text( "the age" )} ),
        Dispatch( {}, "Y 2 title", TextEditBox, {Set Text( "the sex" )} )
    )
);

Code Explanation:

1. Open table.
2. Create Graph Builder.
3. Hide control panel.
4. Set X variable.
5. Set first Y variable.
6. Set second Y variable.
7. Set third Y variable.
8. Add points element.
9. Add second points element.
10. Add third points element.

Example 1151

Summary: Creates a variability chart with nested factors using Graph Builder, configuring X and Y variables, and customizing axis titles.

Code:

dt = Open("data_table.jmp");
gb = dt << Graph Builder(
    Show Control Panel( 0 ),
    Variables( X( :height ), Y( :name ), Y( :age ), Y( :sex ) ),
    Elements( Position( 1, 1 ), Points( X, Y, Legend( 6 ) ) ),
    Elements( Position( 1, 2 ), Points( X, Y, Legend( 7 ) ) ),
    Elements( Position( 1, 3 ), Points( X, Y, Legend( 8 ) ) ),
    SendToReport(
        Dispatch( {}, "Y title", TextEditBox, {Set Text( "the name" )} ),
        Dispatch( {}, "Y 1 title", TextEditBox, {Set Text( "the age" )} ),
        Dispatch( {}, "Y 2 title", TextEditBox, {Set Text( "the sex" )} )
    )
);
gb << Remove Variable( 2 );

Code Explanation:

1. Open data table;
2. Create Graph Builder object.
3. Hide control panel.
4. Set X variable to height.
5. Add first Y variable: name.
6. Add second Y variable: age.
7. Add third Y variable: sex.
8. Position elements in grid.
9. Customize Y axis titles.
10. Remove second Y variable.

Example 1152

Summary: Creates two Graph Builder objects to visualize and analyze data with nested factors, utilizing transformation formulas and local data filters.

Code:

dt = Open("data_table.jmp");
gb = dt << Graph Builder(
    Size( 534, 456 ),
    Show Control Panel( 0 ),
    Variables(
        X( :height ),
        Y( :weight ),
        Overlay(
            Transform Column(
                "age'",
                Set Property( "Configure Levels", 1 ),
                Set Property( "Value Order", {Custom Order( {12, 15} )} ),
                Value Labels( {12 = "Middle Schoolers", 15 = "High Schoolers"} ),
                Use Value Labels( 1 ),
                Formula( Match( :age, 13, 12, 14, 12, 16, 15, 17, 15, :age ) )
            )
        )
    ),
    Elements( Points( X, Y, Legend( 18 ) ), Smoother( X, Y, Legend( 19 ) ) )
);
gb4 = dt << Graph Builder(
    Size( 528, 450 ),
    Show Control Panel( 0 ),
    Variables(
        X(
            Transform Column(
                "age'",
                Ordinal,
                Set Property( "Configure Levels", 1 ),
                Set Property( "Value Order", {Custom Order( {12, 15} )} ),
                Value Labels( {12 = "Middle Schoolers", 15 = "High Schoolers"} ),
                Use Value Labels( 1 ),
                Formula( Match( :age, 13, 12, 14, 12, 16, 15, 17, 15, :age ) )
            )
        ),
        Y( :height )
    ),
    Elements( Bar( X, Y, Legend( 6 ) ) ),
    Local Data Filter( Add Filter( columns( :age ), Where( :age == {13, 16, 17} ), Display( :age, N Items( 6 ) ) ) )
);

Code Explanation:

1. Open data table.
2. Create first Graph Builder object.
3. Set graph size and hide control panel.
4. Define X and Y variables.
5. Transform age column for categorical use.
6. Configure age levels and labels.
7. Apply transformation formula.
8. Add points and smoother elements.
9. Create second Graph Builder object.
10. Set graph size and hide control panel.

Example 1153

Summary: Creates two variability charts with nested factors using Graph Builder, displaying standard deviation charts and configuring X variables with transformations.

Code:

dt = Open("data_table.jmp");
gb = dt << Graph Builder(
    Size( 534, 450 ),
    Show Control Panel( 0 ),
    Variables(
        X(
            Transform Column(
                "age'",
                Ordinal,
                Set Property( "Configure Levels", 1 ),
                Set Property( "Value Order", {Custom Order( {12, 13, 15} )} ),
                Value Labels( {12 = "12", 13 = "Middle School", 15 = "High School"} ),
                Use Value Labels( 1 ),
                Formula( Match( :age, 14, 13, 16, 15, 17, 15, :age ) )
            )
        ),
        Y( :height ),
        Overlay( :sex )
    ),
    Elements( Bar( X, Y, Legend( 4 ), Bar Style( "Stacked" ) ) )
);
gb3 = dt << Graph Builder(
    Size( 528, 492 ),
    Show Control Panel( 0 ),
    Variables(
        X( :weight ),
        Y( :height ),
        Wrap(
            Transform Column(
                "age'",
                Ordinal,
                Set Property( "Configure Levels", 1 ),
                Set Property( "Value Order", {Custom Order( {12, 14, 16} )} ),
                Value Labels( {12 = "Group 1", 14 = "Group 2", 16 = "Group 3"} ),
                Use Value Labels( 1 ),
                Formula( Match( :age, 13, 12, 15, 14, 17, 16, :age ) )
            )
        ),
        Overlay( :sex )
    ),
    Elements( Contour( X, Y, Legend( 35 ) ) )
);
gb4 = dt << Graph Builder(
    Size( 534, 464 ),
    Show Control Panel( 0 ),
    Variables(
        X(
            Transform Column(
                "age'",
                Ordinal,
                Set Property( "Configure Levels", 1 ),
                Set Property( "Value Order", {Custom Order( {12, 15} )} ),
                Value Labels( {12 = "Middle School", 15 = "High School"} ),
                Use Value Labels( 1 ),
                Formula( Match( :age, 13, 12, 14, 12, 16, 15, 17, 15, :age ) )
            ),
            Combine( "Nested" )
        ),
        X( :sex, Position( 1 ), Combine( "Nested" ) ),
        Y( :height ),
        Y( :weight, Position( 1 ) )
    ),
    Elements( Bar( X( 1 ), X( 2 ), Y( 1 ), Y( 2 ), Legend( 7 ) ) )
);

Code Explanation:

1. Open data table;
2. Create Graph Builder.
3. Set size to 534x450.
4. Hide control panel.
5. Define X variable with transformations.
6. Set Y variable to height.
7. Overlay by sex.
8. Add stacked bar element.
9. Create second Graph Builder.
10. Set size to 528x492.
11. Hide control panel.
12. Define X variable as weight.
13. Set Y variable to height.
14. Wrap by transformed age'.
15. Overlay by sex.
16. Add contour element.
17. Create third Graph Builder.
18. Set size to 534x464.
19. Hide control panel.
20. Define nested X variables with transformations.
21. Add sex variable.
22. Set Y variables to height and weight.
23. Add bar element.

Example 1154

Summary: Creates a variability chart with nested factors using operator and part configurations, displaying standard deviation charts.

Code:

dt = Open("data_table.jmp");
gb = dt << Graph Builder(
    Size( 534, 450 ),
    Show Control Panel( 0 ),
    Variables(
        X(
            Transform Column(
                "Clarity'",
                Character,
                Set Property( "Configure Levels", 1 ),
                Set Property( "Value Order", {Custom Order( {"SI2", "SI1", "IF", "VS2"} )} ),
                Value Labels( {"VS2" = "V"} ),
                Use Value Labels( 1 ),
                Formula( Match( :Clarity, "VS1", "VS2", "VVS2", "VS2", "VVS1", "VS2", :Clarity ) )
            )
        )
    ),
    Elements( Bar( X, Legend( 3 ) ) )
);
gb2 = gb << redo analysis;

Code Explanation:

1. Open data table;
2. Create Graph Builder object.
3. Set graph size.
4. Hide control panel.
5. Define X variable.
6. Transform Clarity' column.
7. Configure levels for clarity.
8. Set custom order for values.
9. Apply value labels.
10. Use value labels in graph.
11. Redo analysis.

Example 1155

Summary: Creates a variability chart with nested factors using operator and part configurations, displaying standard deviation charts.

Code:

dt = Open("data_table.jmp");
gb = dt << Graph Builder(
    Size( 534, 450 ),
    Show Control Panel( 0 ),
    Variables(
        X(
            Transform Column(
                "Clarity'",
                Character,
                Set Property( "Configure Levels", 1 ),
                Set Property( "Value Order", {Custom Order( {"SI2", "SI1", "IF", "VS2"} )} ),
                Value Labels( {"VS2" = "V"} ),
                Use Value Labels( 1 ),
                Formula( Match( :Clarity, "VS1", "VS2", "VVS2", "VS2", "VVS1", "VS2", :Clarity ) )
            )
        )
    ),
    Elements( Bar( X, Legend( 3 ) ) )
);
gb2 = gb << redo analysis;
gb << close window;

Code Explanation:

1. Open data table;
2. Create Graph Builder object.
3. Set graph size.
4. Hide control panel.
5. Define X variable.
6. Transform Clarity' column.
7. Configure levels property.
8. Set custom value order.
9. Add value labels.
10. Apply formula for transformation.
11. Add bar element to graph.
12. Redo analysis.
13. Close graph window.

Example 1156

Summary: Creates a variability chart with nested factors using operator and part configurations, displaying standard deviation charts.

Code:

dt = Open("data_table.jmp");
gb = dt << Graph Builder(
    Size( 534, 464 ),
    Show Control Panel( 0 ),
    Variables( X( :failure, Order By( :N, Descending, Order Statistic( "Mean" ) ) ), Y( :N ) ),
    Elements( Line( X, Y, Legend( 6 ), Summary Statistic( "Cumulative Percent" ) ) ),
    SendToReport(
        Dispatch( {}, "N", ScaleBox,
            {Min( 0 ), Max( 1.05 ), Inc( 0.2 ), Minor Ticks( 1 ), Add Ref Line( 0.25, "Solid", "Black", "", 1 ),
            Add Ref Line( 0.5, "Solid", "Black", "", 1 ), Add Ref Line( 0.75, "Solid", "Black", "", 1 )}
        ),
        Dispatch( {}, "400", ScaleBox,
            {Legend Model(
                6,
                Properties(
                    0,
                    {Line Color( 3 ), Line Label Properties(
                        {First Label( 1 ), Last Label( 1 ), Label Format( "Percent", 9, 2 ), Width( 9 )}
                    )},
                    Item ID( "Sum %", 1 )
                )
            )}
        )
    )
);

Code Explanation:

1. Open data table;
2. Create Graph Builder object.
3. Set graph size.
4. Hide control panel.
5. Define X and Y variables.
6. Add line element.
7. Set cumulative percent summary.
8. Configure N scale box.
9. Add reference lines at 0.25, 0.5, 0.75.
10. Customize legend properties.

Example 1157

Summary: Creates a variability chart with nested factors using Graph Builder, displaying standard deviation charts and customizing legend properties.

Code:

dt2 = Open("data_table.jmp");
gb2 = dt2 << Graph Builder(
    Size( 534, 450 ),
    Show Control Panel( 0 ),
    Variables( X( :age ), Y( :height ), Overlay( :sex ) ),
    Elements(
        Points( X, Y, Legend( 2 ), Summary Statistic( "Cumulative Percent" ) ),
        Line( X, Y, Legend( 3 ), Summary Statistic( "Cumulative Percent" ) )
    ),
    SendToReport(
        Dispatch( {}, "400", ScaleBox,
            {Legend Model(
                3,
                Properties( 0, {Line Color( 3 )}, Item ID( "F", 1 ) ),
                Properties( -1, {Line Color( 13 )}, Item ID( "Sum %", 1 ) )
            )}
        )
    )
);

Code Explanation:

1. Open data table.
2. Create Graph Builder object.
3. Set graph size.
4. Hide control panel.
5. Define variables: X=age, Y=height, Overlay=sex.
6. Add points element with cumulative percent summary.
7. Add line element with cumulative percent summary.
8. Customize legend properties.
9. Set line color for female.
10. Set line color for sum percent.

Example 1158

Summary: Creates a variability chart with nested factors using Graph Builder, featuring bar and line elements with cumulative percent summary statistics.

Code:

dt3 = Open("data_table.jmp");
gb3 = dt3 << Graph Builder(
    Size( 534, 450 ),
    Show Control Panel( 0 ),
    Variables( X( :Pie Type ), Y( :Outlets ) ),
    Elements(
        Bar( X, Y, Legend( 4 ), Summary Statistic( "Cumulative Percent" ) ),
        Line( X, Y, Legend( 5 ), Summary Statistic( "Cumulative Percent" ), Fill( "Fill Below" ) )
    ),
    SendToReport(
        Dispatch( {}, "400", ScaleBox,
            {Legend Model( 4, Properties( 0, {Fill Color( 24 )}, Item ID( "Sum %", 1 ) ) ), Legend Model(
                5,
                Properties( 0, {Transparency( 0.5 )}, Item ID( "Sum %", 1 ) )
            )}
        )
    )
);

Code Explanation:

1. Open data_table data
2. Create Graph Builder object.
3. Set graph size to 534x450.
4. Hide control panel.
5. Set X variable to "Pie Type".
6. Set Y variable to "Outlets".
7. Add bar element with cumulative percent summary.
8. Add line element with cumulative percent summary.
9. Fill area below line.
10. Customize legend colors and transparency.

Example 1159

Summary: Creates two variability charts with nested factors using Graph Builder, displaying standard deviation charts and cumulative sum summaries.

Code:

dt = Open("data_table.jmp");
gb1 = dt << Graph Builder(
    Size( 417, 320 ),
    Show Control Panel( 0 ),
    Variables( X( :Day ), Y( :Count ), Overlay( :Process ) ),
    Elements( Line( X, Y, Legend( 9 ), Summary Statistic( "Cumulative Sum" ) ) )
);
gb2 = dt << Graph Builder(
    Size( 421, 320 ),
    Show Control Panel( 0 ),
    Categorical Color Theme( "Yellow to Blue" ),
    Variables( X( :Day ), Y( :Count ), Overlay( :Process ) ),
    Elements( Bar( X, Y, Legend( 10 ), Summary Statistic( "Cumulative Sum" ) ) )
);

Code Explanation:

1. Open data table.
2. Create first graph builder object.
3. Set size for first graph.
4. Hide control panel for first graph.
5. Define variables for first graph.
6. Add line element with cumulative sum summary.
7. Create second graph builder object.
8. Set size for second graph.
9. Hide control panel for second graph.
10. Define variables and color theme for second graph.

Example 1160

Summary: Creates variability charts with nested factors using Graph Builder, displaying standard deviation charts and interactive features.

Code:

dt = Open("data_table.jmp");
gb1 = dt << Graph Builder(
    Size( 417, 320 ),
    Show Control Panel( 0 ),
    Variables( X( :Day ), Y( :Count ), Overlay( :Process ) ),
    Elements( Line( X, Y, Legend( 9 ), Summary Statistic( "Cumulative Sum" ) ) )
);
gb2 = dt << Graph Builder(
    Size( 421, 320 ),
    Show Control Panel( 0 ),
    Categorical Color Theme( "Yellow to Blue" ),
    Variables( X( :Day ), Y( :Count ), Overlay( :Process ) ),
    Elements( Bar( X, Y, Legend( 10 ), Summary Statistic( "Cumulative Sum" ) ) )
);
dt2 = Open("data_table.jmp");
gb3 = dt2 << Graph Builder(
    Size( 534, 456 ),
    Show Control Panel( 0 ),
    Variables( X( :Date ), Y( :Calories ), Overlay( :Meal ) ),
    Elements( Line( X, Y, Legend( 3 ), Summary Statistic( "Cumulative Sum" ) ) ),
    Local Data Filter(
        Add Filter( columns( :Meal ), Where( :Meal == {"AM Snack", "Late Snack", "PM Snack"} ), Display( :Meal, N Items( 6 ) ) )
    )
);

Code Explanation:

1. Open data table;
2. Create Graph Builder instance gb1.
3. Set size and hide control panel.
4. Define X, Y, and overlay variables.
5. Add line element with cumulative sum summary.
6. Create Graph Builder instance gb2.
7. Set size and hide control panel.
8. Apply yellow to blue color theme.
9. Define X, Y, and overlay variables.
10. Add bar element with cumulative sum summary.

Example 1161

Summary: Creates a graph builder with nested factors, utilizing custom levels and overlaying variables to visualize data.

Code:

Open("data_table.jmp");
Graph Builder(
    Show Control Panel( 0 ),
    Variables( X( :sex ), Y( :height ), Overlay( :weight, custom levels( {{., "< 105"}, {105, "‚â• 105"}} ) ) ),
    Elements( Points( X, Y, Legend( 5 ) ) )
);

Code Explanation:

1. Open data table;
2. Launch Graph Builder.
3. Hide control panel.
4. Set X variable to sex.
5. Set Y variable to height.
6. Overlay weight variable.
7. Define custom weight levels.
8. Add points element.
9. Assign legend to points.
10. Display graph.

Example 1162

Summary: Creates a heatmap to visualize the relationship between sex and height, with customizable legend properties.

Code:

dt = Open("data_table.jmp");
gb = dt << Graph Builder(
    Size( 528, 448 ),
    Show Control Panel( 0 ),
    Variables( X( :sex ), Y( :height ) ),
    Elements( Heatmap( X, Y, Legend( 6 ) ) ),
    SendToReport(
        Dispatch( {}, "400", ScaleBox,
            {Legend Model(
                6,
                Properties( 0, {gradient( {Color Theme( "Green to Purple" ), Width( 12 ), Scale Type( "Standard Deviation" )} )} )
            )}
        )
    )
);
dt << Select All Rows();
dt << Exclude;

Code Explanation:

1. Open data table.
2. Create Graph Builder object.
3. Set graph size.
4. Hide control panel.
5. Assign variables X and Y.
6. Add heatmap element.
7. Send report to customize legend.
8. Adjust legend properties.
9. Select all rows in table.
10. Exclude selected rows.

Example 1163

Summary: Creates a heatmap to visualize the relationship between sex and height, with customized legend properties.

Code:

dt = Open("data_table.jmp");
gb = dt << Graph Builder(
    Size( 528, 448 ),
    Show Control Panel( 0 ),
    Variables( X( :sex ), Y( :height ) ),
    Elements( Heatmap( X, Y, Legend( 6 ) ) ),
    SendToReport(
        Dispatch( {}, "400", ScaleBox,
            {Legend Model(
                6,
                Properties( 0, {gradient( {Color Theme( "Green to Purple" ), Width( 12 ), Scale Type( "Standard Deviation" )} )} )
            )}
        )
    )
);
dt << Select All Rows();
dt << Exclude;
dt << Clear Row States;

Code Explanation:

1. Open table.
2. Create Graph Builder object.
3. Set size and hide control panel.
4. Assign variables for X and Y.
5. Add Heatmap element with legend.
6. Customize legend properties.
7. Select all rows.
8. Exclude selected rows.
9. Clear row states.

Example 1164

Summary: Creates a heatmap to visualize height data, utilizing Graph Builder and nested factors configurations.

Code:

Open("data_table.jmp");
Graph Builder(
    Transform Column(
        "Transform[height]@X",
        Formula( Col Median( :height, :"@Exclude"n, :"@Filter"n, :"@Graph"n, :"@Overlay"n, :"@X"n ) )
    ),
    Size( 531, 456 ),
    Show Control Panel( 0 ),
    Variables( Group X( :age ), Group Y( :sex ), Color( :"Transform[height]@X"n ) ),
    Elements( Heatmap( Legend( 2 ), Label( "Label by Value" ) ) )
);

Code Explanation:

1. Open data table;
2. Create new transform column.
3. Apply median formula to height.
4. Set graph size.
5. Hide control panel.
6. Define group X variable.
7. Define group Y variable.
8. Define color variable.
9. Add heatmap element.
10. Configure heatmap legend and labels.

Example 1165

Summary: Creates a variability chart with nested factors using Graph Builder, configuring a heatmap element to display standard deviation charts.

Code:

Open("data_table.jmp");
Graph Builder(
    Transform Column(
        "Transform[height]@X",
        Formula( Col Median( :height, :"@Exclude"n, :"@Filter"n, :"@Graph"n, :"@Overlay"n, :"@X"n ) )
    ),
    Size( 495, 466 ),
    Show Control Panel( 0 ),
    Variables( X( :age ), X( :sex, Position( 1 ) ), Color( :"Transform[height]@X"n ) ),
    Elements( Heatmap( X( 1 ), X( 2 ), Legend( 2 ), Label( "Label by Value" ) ) )
);

Code Explanation:

1. Open data table;
2. Create Transform column.
3. Define formula for median height.
4. Set Graph Builder size.
5. Hide control panel.
6. Set X variable: age.
7. Set X variable: sex.
8. Set color variable: transformed height.
9. Add heatmap element.
10. Configure heatmap labels.

Example 1166

Summary: Creates a variability chart with nested factors using operator and part configurations, displaying standard deviation charts through Graph Builder.

Code:

Open("data_table.jmp");
Graph Builder(
    Show Control Panel( 0 ),
    Show Legend( 0 ),
    Variables(
        X( :height ),
        X( Transform Column( "o", Character, Nominal, Formula( 1 ) ) ),
        Y( Transform Column( "o", Character, Nominal, Formula( 1 ) ) ),
        Y( :weight )
    ),
    Relative Sizes( "X", [8 1] ),
    Relative Sizes( "Y", [1 8] ),
    Elements( Position( 1, 1 ), Box Plot( X, Y, Legend( 7 ) ) ),
    Elements( Position( 1, 2 ), Points( X, Y, Legend( 12 ) ), Smoother( X, Y, Legend( 13 ) ) ),
    Elements( Position( 2, 1 ) ),
    Elements( Position( 2, 2 ), Box Plot( X, Y, Legend( 16 ) ) )
);

Code Explanation:

1. Open data table;
2. Launch Graph Builder.
3. Hide control panel.
4. Hide legend.
5. Set X variable: height.
6. Create dummy X variable.
7. Create dummy Y variable.
8. Set Y variable: weight.
9. Adjust X relative sizes.
10. Adjust Y relative sizes.
11. Add box plot at position 1,1.
12. Add points and smoother at position 1,2.
13. Reserve position 2,1.
14. Add box plot at position 2,2.

Example 1167

Summary: Creates multiple scatter plots and bar charts with nested factors, utilizing Graph Builder to visualize relationships between picture, pet, height, weight, and color.

Code:

Open("data_table.jmp");
Graph Builder( Size( 748, 643 ), Show Control Panel( 0 ), Variables( X( :picture ), Y( :pet ) ), Elements( Points( X, Y, Legend( 3 ) ) ) );
Graph Builder(
    Size( 534, 456 ),
    Show Control Panel( 0 ),
    Variables( X( :height ), Y( :weight ), Color( :pet ) ),
    Elements( Points( X, Y, Legend( 10 ) ), Smoother( X, Y, Legend( 11 ) ) )
);
Graph Builder(
    Size( 534, 456 ),
    Show Control Panel( 0 ),
    Variables( X( :height ), Y( :weight ), Color( :pet ) ),
    Elements( Points( X, Y, Legend( 10 ) ), Smoother( X, Y, Legend( 11 ) ) ),
    SendToReport(
        Dispatch( {}, "Graph Builder", FrameBox,
            {Add Pin Annotation(
                Seg( Marker Seg( 1 ) ),
                Index( 26 ),
                Index Row( 26 ),
                UniqueID( 26 ),
                FoundPt( {771, 320} ),
                Origin( {68.9977639751553, 112.920457653061} ),
                RightOfCenter( 1 ),
                Tag Line( 1 )
            ), Add Pin Annotation(
                Seg( Marker Seg( 1 ) ),
                Index( 13 ),
                Index Row( 13 ),
                UniqueID( 13 ),
                FoundPt( {515, 372} ),
                Origin( {57.9945341614907, 95.0325796938776} ),
                Offset( {-196, -152} ),
                RightOfCenter( 0 ),
                Tag Line( 1 )
            )}
        )
    )
);
Graph Builder(
    Size( 528, 450 ),
    Show Control Panel( 0 ),
    Variables( X( :picture ), Y( :height ), Color( :pet ) ),
    Elements( Bar( X, Y, Legend( 9 ) ) ),
    Local Data Filter(
        Add Filter(
            columns( :name ),
            Where(
                :name == {"ALFRED", "ALICE", "AMY", "BARBARA", "CAROL", "CHRIS", "CLAY", "DANNY", "DAVID", "EDWARD", "ELIZABETH",
                "FREDERICK"}
            ),
            Display( :name, N Items( 15 ), Find( Set Text( "" ) ) )
        )
    )
);
Graph Builder(
    Size( 943, 486 ),
    Show Control Panel( 0 ),
    Variables( X( :picture ), X( :pet, Position( 1 ) ), Y( :height ), Y( :weight, Position( 1 ) ) ),
    Elements( Points( X( 1 ), X( 2 ), Y( 1 ), Y( 2 ), Legend( 3 ) ) )
);

Code Explanation:

1. Open data table.
2. Create scatter plot with picture and pet.
3. Create scatter plot with height, weight, and pet color.
4. Add smoother to scatter plot.
5. Repeat scatter plot with smoother.
6. Add pin annotations to scatter plot.
7. Create bar chart with picture, height, and pet color.
8. Add local data filter for names.
9. Create scatter plot with picture, pet, height, and weight.
10. Plot points with dual axes.

Example 1168

Summary: Creates a graph builder with nested factors, displaying line and points elements, and enabling fit to window.

Code:

Open("data_table.jmp");
gb = Graph Builder(
    Size( 570, 528 ),
    Show Control Panel( 0 ),
    Fit to Window( "Off" ),
    Variables( X( :age ), Y( :height ), Overlay( :sex ) ),
    Elements( Line( X, Y, Legend( 3 ) ), Points( X, Y, Legend( 4 ) ) )
);
gb << Fit to Window( "On" );

Code Explanation:

1. Open data table;
2. Create Graph Builder object.
3. Set window size.
4. Hide control panel.
5. Disable fit to window.
6. Define X, Y, and overlay variables.
7. Add line element.
8. Add points element.
9. Enable fit to window.
10. Display graph.

Example 1169

Summary: Creates a graph builder with nested factors using operator and part configurations, displaying standard deviation charts.

Code:

dt = Open("data_table.jmp");
gb = Graph Builder(
    Size( 570, 528 ),
    Show Control Panel( 0 ),
    Fit to Window( "Off" ),
    Variables( X( :age ), Y( :height ), Overlay( :sex ) ),
    Elements( Line( X, Y, Legend( 3 ) ), Points( X, Y, Legend( 4 ) ) )
);
gb << Fit to Window( "On" );
gb << size( 300, 228 );

Code Explanation:

1. Open data table;
2. Create Graph Builder object.
3. Set window size to 570x528.
4. Hide control panel.
5. Disable fit to window.
6. Assign variables: X=age, Y=height, Overlay=sex.
7. Add line and point elements.
8. Enable fit to window.
9. Resize window to 300x228.

Example 1170

Summary: Creates a variability chart with nested factors using Graph Builder, configuring scale boxes and interval bars for height and weight.

Code:

Open("data_table.jmp");
Graph Builder(
    Transform Column( "Avg[height,weight]", Formula( Mean( :height, :weight ) ) ),
    Size( 536, 452 ),
    Show Control Panel( 0 ),
    Variables( X( :age ), Y( :"Avg[height,weight]"n ), Interval( :height ), Interval( :weight ) ),
    Elements( Points( X, Y, Legend( 9 ), Summary Statistic( "Mean" ) ) ),
    SendToReport(
        Dispatch( {}, "Avg[height,weight]", ScaleBox,
            {Min( 50 ), Max( 150 ), Inc( 20 ), Minor Ticks( 7 ), Label Row( Show Minor Grid( 1 ) )}
        ),
        Dispatch( {}, "graph title", TextEditBox, {Set Text( "Grid Lines should not be on top of interval bars" )} )
    )
);

Code Explanation:

1. Open data table;
2. Create new column for average.
3. Set graph size.
4. Hide control panel.
5. Define X and Y variables.
6. Add interval bars for height and weight.
7. Plot points with mean summary.
8. Set scale for average column.
9. Enable minor grid lines.
10. Add graph title.

Example 1171

Summary: Creates a graph builder window with nested factors using Graph Builder, displaying points and smoother plots for height and weight grouped by sex.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 534, 492 ),
    Show Control Panel( 0 ),
    Grid Color( "Medium Light Red" ),
    Graph Spacing( 20 ),
    Level Spacing Color( "Blue" ),
    Variables( X( :height ), Y( :weight ), Group Y( :sex ) ),
    Elements( Points( X, Y, Legend( 4 ) ), Smoother( X, Y, Legend( 5 ) ) )
);

Code Explanation:

1. Open data table;
2. Create Graph Builder window.
3. Set size to 534x492.
4. Hide control panel.
5. Set grid color to red.
6. Set graph spacing to 20.
7. Set level spacing color to blue.
8. Assign height to X axis.
9. Assign weight to Y axis.
10. Group Y by sex; plot points and smoother.

Example 1172

Summary: Creates a variability chart with nested factors using Graph Builder, displaying standard deviation charts and confidence intervals.

Code:

dt = Open("data_table.jmp");
dt << Graph Builder(
    Size( 528, 449 ),
    Show Control Panel( 0 ),
    Variables( X( :age ), Y( :height ) ),
    Elements( Points( X, Y, Legend( 3 ) ), Line Of Fit( X, Y, Legend( 4 ) ) )
);
dt << Graph Builder(
    Size( 528, 477 ),
    Show Control Panel( 0 ),
    Variables( X( :age ), Y( :height ) ),
    Elements( Bar( X, Y, Legend( 6 ), Error Interval( "Confidence Interval" ), Interval Style( "Band" ) ) )
);
dt << Graph Builder(
    Size( 528, 449 ),
    Show Control Panel( 0 ),
    Variables( X( :age ), Y( :height ) ),
    Elements( Bar( X, Y, Legend( 6 ), Bar Style( "Float" ), Error Interval( "Confidence Interval" ), Interval Style( "Band" ) ) )
);

Code Explanation:

1. Open data table.
2. Create scatter plot.
3. Add line of fit.
4. Create bar chart.
5. Add confidence interval.
6. Display as band.
7. Create floating bar chart.
8. Add confidence interval.
9. Display as band.
10. Adjust graph sizes.

Example 1173

Summary: Creates a graph builder window with nested factors, displaying points and line of fit elements, and customizing report settings.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 534, 454 ),
    Show Control Panel( 0 ),
    Variables( X( :weight ), Y( :height ) ),
    Elements( Points( X, Y, Legend( 6 ) ), Line Of Fit( X, Y, Legend( 8 ) ) ),
    SendToReport(
        Dispatch( {}, "height", ScaleBox,
            {Min( 50 ), Max( 75 ), Inc( 1 ), Minor Ticks( 0 ), Label Row( Label Orientation( "Angled" ) ),
            Tick Label List( {"sqrt2", "sqrt3", "e", "pi"}, {51.41, 61.73, 65.72, 73.14} )}
        )
    )
);

Code Explanation:

1. Open data table.
2. Create Graph Builder window.
3. Set graph size.
4. Hide control panel.
5. Define X and Y variables.
6. Add points element.
7. Add line of fit element.
8. Adjust report settings.
9. Set Y axis minimum.
10. Set Y axis maximum.

Example 1174

Summary: Creates a graph builder window with nested factors, displaying standard deviation charts for height and weight using Graph Builder.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 534, 450 ),
    Show Control Panel( 0 ),
    Legend Position( "Inside Right" ),
    Variables( X( :age ), Y( :height, Side( "Right" ) ), Y( :weight, Position( 1 ) ) ),
    Elements( Line( X, Y( 2 ), Legend( 5 ) ), Line( X, Y( 1 ), Legend( 6 ) ) )
);

Code Explanation:

1. Open data table;
2. Create new graph builder window.
3. Set window size.
4. Hide control panel.
5. Place legend inside right.
6. Assign X variable.
7. Assign first Y variable.
8. Assign second Y variable.
9. Add line element for height.
10. Add line element for weight.

Example 1175

Summary: Creates two Graph Builder windows with nested factors, displaying pie charts and points for height, age, weight, and sex variables.

Code:

Open("data_table.jmp");
Graph Builder(
    Show Control Panel( 0 ),
    Variables( X( :height ), X( :age ), X( :weight ), Group X( :sex ) ),
    Elements( Position( 1, 1 ), Pie( X, Legend( 13 ) ) ),
    Elements( Position( 2, 1 ), Points( X, Legend( 12 ) ) ),
    Elements( Position( 3, 1 ), Pie( X, Legend( 14 ) ) ),
    SendToReport( Dispatch( {}, "graph title", TextEditBox, {Set Text( "Pie graphs should not have an axis" )} ) )
) << journal;
Graph Builder(
    Show Control Panel( 0 ),
    Variables( y( :age ), y( :age ), y( :age ), Group y( :sex ) ),
    Elements( Position( 1, 1 ), Pie( y, Legend( 13 ) ) ),
    Elements( Position( 1, 2 ), Points( y, Legend( 12 ) ) ),
    Elements( Position( 1, 3 ), Pie( y, Legend( 14 ) ) ),
    SendToReport( Dispatch( {}, "graph title", TextEditBox, {Set Text( "Pie graphs should not have an axis" )} ) )
) << journal;

Code Explanation:

1. Open data table.
2. Create first Graph Builder window.
3. Hide control panel.
4. Set X variables: height, age, weight.
5. Group by sex.
6. Add pie chart at position 1,1.
7. Add points at position 2,1.
8. Add another pie chart at position 3,1.
9. Set graph title to "Pie graphs should not have an axis".
10. Create second Graph Builder window with similar settings.

Example 1176

Summary: Creates three Graph Builder windows with nested factors, displaying pie charts and contour plots for analysis.

Code:

Open("data_table.jmp");
Graph Builder(
    Show Control Panel( 0 ),
    Variables( X( :height ), X( :age ), X( :weight ), Group X( :sex ) ),
    Elements( Position( 1, 1 ), Pie( X, Legend( 13 ) ) ),
    Elements( Position( 2, 1 ), Points( X, Legend( 12 ) ) ),
    Elements( Position( 3, 1 ), Pie( X, Legend( 14 ) ) ),
    SendToReport( Dispatch( {}, "graph title", TextEditBox, {Set Text( "Pie graphs should not have an axis" )} ) )
) << journal;
Graph Builder(
    Show Control Panel( 0 ),
    Variables( y( :age ), y( :age ), y( :age ), Group y( :sex ) ),
    Elements( Position( 1, 1 ), Pie( y, Legend( 13 ) ) ),
    Elements( Position( 1, 2 ), Points( y, Legend( 12 ) ) ),
    Elements( Position( 1, 3 ), Pie( y, Legend( 14 ) ) ),
    SendToReport( Dispatch( {}, "graph title", TextEditBox, {Set Text( "Pie graphs should not have an axis" )} ) )
) << journal;
Graph Builder(
    Show Control Panel( 0 ),
    Variables( Y( :weight ), Y( :height, Side( "Right" ) ), Y( :weight, Position( 2 ) ), Y( :age ), Group Y( :sex ) ),
    Elements( Position( 1, 1 ), Contour( Y, Legend( 45 ) ) ),
    Elements( Position( 1, 2 ), Points( Y( 1 ), Legend( 16 ) ), Points( Y( 2 ), Legend( 35 ) ) ),
    Elements( Position( 1, 3 ), Contour( Y, Legend( 44 ) ) ),
    SendToReport( Dispatch( {}, "graph title", TextEditBox, {Set Text( "Countour graphs should not have a right axis" )} ) )
) << journal;

Code Explanation:

1. Open data table;
2. Create first Graph Builder window.
3. Hide control panel.
4. Set X variables: height, age, weight.
5. Group by sex.
6. Add pie chart element.
7. Add points element.
8. Add another pie chart element.
9. Set graph title.
10. Save first graph as journal.
11. Create second Graph Builder window.
12. Hide control panel.
13. Set Y variables: age, age, age.
14. Group by sex.
15. Add pie chart element.
16. Add points element.
17. Add another pie chart element.
18. Set graph title.
19. Save second graph as journal.
20. Create third Graph Builder window.
21. Hide control panel.
22. Set Y variables: weight, height, weight, age.
23. Group by sex.
24. Add contour plot element.
25. Add points elements.
26. Add another contour plot element.
27. Set graph title.
28. Save third graph as journal.

Example 1177

Summary: Creates two Graph Builder windows to visualize nested factors using pie and box plots, with customizable legend properties.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 507, 440 ),
    Show Control Panel( 0 ),
    Legend Position( "Inside Bottom Right" ),
    Variables( X( :age ), Y( :height ), Y( :weight, Position( 1 ) ) ),
    Elements( Pie( X, Y( 1 ), Y( 2 ), Legend( 6 ) ) ), 
);
Graph Builder(
    Size( 528, 450 ),
    Show Control Panel( 0 ),
    Legend Position( "Inside Bottom Left" ),
    Variables( X( :age ), Y( :height ), Color( :weight ) ),
    Elements( Box Plot( X, Y, Legend( 7 ) ) ),
    SendToReport(
        Dispatch( {}, "400", ScaleBox, {Legend Model( 7, Properties( 1, {gradient( {Horizontal( 1 )} )}, Item ID( "weight", 1 ) ) )} ),
        Dispatch( {}, "400", LegendBox, {Set Title( "" ), Orientation( "Horizontal" )} )
    )
);

Code Explanation:

1. Open data table.
2. Create first Graph Builder window.
3. Set window size.
4. Hide control panel.
5. Place legend inside bottom right.
6. Define X and Y variables.
7. Add pie chart element.
8. Create second Graph Builder window.
9. Set window size.
10. Hide control panel.
11. Place legend inside bottom left.
12. Define X, Y, and color variables.
13. Add box plot element.
14. Customize legend properties.
15. Set legend title and orientation.

Example 1178

Summary: Creates a variability chart with nested factors using operator and part configurations, displaying standard deviation charts in Graph Builder.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 534, 450 ),
    Show Control Panel( 0 ),
    Variables( X( :age ), Y( :weight ), Color( :sex ), Size( :height ) ),
    Elements( Points( X, Y, Legend( 12 ) ) ),
    SendToReport(
        Dispatch( {}, "400", ScaleBox,
            {Legend Model(
                12,
                Properties( 0, {Marker Size( 6 ), Marker Scale( {Style( "Nested Half" )} )}, Item ID( "height", 1 ) ),
                Properties( 1, {Marker( "Triangle" )}, Item ID( "F", 1 ) ),
                Properties( 2, {Marker( "Triangle" )}, Item ID( "M", 1 ) ),
                Properties( -1, {Marker( "Triangle" )}, Item ID( "weight", 1 ) )
            )}
        )
    )
);

Code Explanation:

1. Open data table;
2. Launch Graph Builder.
3. Set window size.
4. Hide control panel.
5. Define variables: X, Y, Color, Size.
6. Add points element.
7. Send report settings.
8. Configure legend model.
9. Set marker size and scale.
10. Customize markers for each category.

Example 1179

Summary: Creates two variability charts with nested factors using Graph Builder, displaying standard deviation charts and confidence intervals.

Code:

dt = Open("data_table.jmp");
gb = dt << Graph Builder(
    Size( 528, 450 ),
    Show Control Panel( 0 ),
    Variables( X( :age ), Y( :height ), Overlay( :sex ) ),
    Elements( Line( X, Y, Legend( 20 ), Summary Statistic( "Median" ), Error Interval( "Confidence Interval" ) ) )
);
gb = dt << Graph Builder(
    Size( 528, 418 ),
    Show Control Panel( 0 ),
    Variables( Y( :height ), Overlay( :sex ) ),
    Elements( Bar( Y, Legend( 8 ), Summary Statistic( "First Quartile" ), Error Interval( "Confidence Interval" ) ) )
);

Code Explanation:

1. Open data table;
2. Create first Graph Builder object.
3. Set graph size.
4. Hide control panel.
5. Define X, Y, and overlay variables.
6. Add line element.
7. Use median summary statistic.
8. Include confidence interval error.
9. Create second Graph Builder object.
10. Set graph size.
11. Hide control panel.
12. Define Y and overlay variables.
13. Add bar element.
14. Use first quartile summary statistic.
15. Include confidence interval error.

Example 1180

Summary: Creates a variability chart with nested factors using Graph Builder, displaying standard deviation charts and configuring graph elements for visualization.

Code:

dt2 = Open("data_table.jmp");
gb3 = dt2 << Graph Builder(
    Size( 522, 450 ),
    Show Control Panel( 0 ),
    Variables( X( :Meal ), Y( :Protein ), Color( :Meal ) ),
    Elements( Bar( X, Y, Legend( 3 ), Summary Statistic( "Median" ), Error Interval( "Confidence Interval" ) ) )
);
gb8 = dt2 << Graph Builder(
    Size( 528, 450 ),
    Show Control Panel( 0 ),
    Variables( X( :Meal ), Y( :Fat ), Y( :Protein, Position( 1 ) ), Y( :Carbohydrates, Position( 1 ) ) ),
    Elements(
        Line(
            X,
            Y( 1 ),
            Y( 2 ),
            Y( 3 ),
            Legend( 3 ),
            Summary Statistic( "First Quartile" ),
            Error Interval( "Confidence Interval" ),
            Interval Style( "Band" )
        ),
        Points( X, Y( 1 ), Y( 2 ), Y( 3 ), Legend( 4 ), Summary Statistic( "First Quartile" ) )
    ),
    SendToReport(
        Dispatch( {}, "400", ScaleBox,
            {Legend Model(
                4,
                Base( 0, 0, 0, Item ID( "Q1(Fat)", 1 ) ),
                Base( 1, 0, 0, Item ID( "Q1(Protein)", 1 ) ),
                Base( 2, 0, 0, Item ID( "Q1(Carbohydrates)", 1 ) )
            )}
        ),
        Dispatch( {}, "Graph Builder", FrameBox, {Grid Line Order( 7 ), Reference Line Order( 11 )} )
    )
);

Code Explanation:

1. Open data table;
2. Create Graph Builder object.
3. Set graph size.
4. Hide control panel.
5. Assign variables: X, Y, Color.
6. Add bar element with median summary.
7. Create second Graph Builder object.
8. Set graph size.
9. Hide control panel.
10. Assign multiple Y variables.

Example 1181

Summary: Creates a bar chart with nested factors using Graph Builder, displaying mode summary statistics for color.

Code:

dt = Open("data_table.jmp");
gb = dt << Graph Builder(
    Size( 528, 450 ),
    Show Control Panel( 0 ),
    Variables( X( :age ), Y( :height ), Color( :sex, Summary Statistic( "Mode" ) ) ),
    Elements( Bar( X, Y, Legend( 4 ), Summary Statistic( "Mode" ) ) )
);

Code Explanation:

1. Open data table;
2. Create Graph Builder object.
3. Set graph size to 528x450.
4. Hide control panel.
5. Set X variable to age.
6. Set Y variable to height.
7. Set color variable to sex.
8. Use mode summary statistic for color.
9. Add bar element to graph.
10. Set bar legend position to 4.

Example 1182

Summary: Creates a graph that displays the mode of favorite colors based on age, utilizing Graph Builder and Bar elements.

Code:

dt2 = Open("data_table.jmp");
gb2 = dt2 << Graph Builder(
    Size( 528, 450 ),
    Show Control Panel( 0 ),
    Variables( X( :How old are you? ), Color( :"What is your favorite color? (select one)"n, Summary Statistic( "Mode" ) ) ),
    Elements( Bar( X, Legend( 3 ) ) ),
    SendToReport( Dispatch( {}, "graph title", TextEditBox, {Set Text( "Mode(What is your favorite color?)" )} ) )
);

Code Explanation:

1. Open data table.
2. Create Graph Builder object.
3. Set window size.
4. Hide control panel.
5. Define X variable.
6. Define Color variable.
7. Use Mode summary statistic.
8. Add Bar element.
9. Assign legend position.
10. Set graph title.

Example 1183

Summary: Creates two Graph Builder objects, gb3 and gb4, to visualize nested factors using Heatmap and Treemap elements, respectively.

Code:

dt3 = Open("data_table.jmp");
gb3 = dt3 << Graph Builder(
    Size( 534, 456 ),
    Show Control Panel( 0 ),
    Categorical Color Theme( "Paired"(1) ),
    Variables( X( :Carat Weight ), Y( :Price ), Color( :Color, Summary Statistic( "Mode" ) ) ),
    Elements( Heatmap( X, Y, Legend( 7 ) ) ),
    Local Data Filter( Add Filter( columns( :Depth ), Where( :Depth >= 60 & :Depth <= 64.3 ) ) )
);
gb4 = dt3 << Graph Builder(
    Size( 495, 440 ),
    Show Control Panel( 0 ),
    Variables( X( :Clarity ), Color( :Cut, Summary Statistic( "Mode" ) ) ),
    Elements( Treemap( X, Legend( 4 ) ) )
);

Code Explanation:

1. Open data table;
2. Create Graph Builder object gb3.
3. Set graph size to 534x456.
4. Hide control panel.
5. Apply Paired color theme.
6. Define X, Y, and Color variables.
7. Add Heatmap element.
8. Enable local data filter for Depth.
9. Create Graph Builder object gb4.
10. Set graph size to 495x440.

Example 1184

Summary: Creates multiple Graph Builders with various elements, such as bar charts and heatmaps, to visualize data from different tables.

Code:

dt = Open("data_table.jmp");
gb = dt << Graph Builder(
    Size( 528, 450 ),
    Show Control Panel( 0 ),
    Variables( X( :age ), Y( :height ), Color( :sex, Summary Statistic( "Mode" ) ) ),
    Elements( Bar( X, Y, Legend( 4 ), Summary Statistic( "Mode" ) ) )
);
dt2 = Open("data_table.jmp");
gb2 = dt2 << Graph Builder(
    Size( 528, 450 ),
    Show Control Panel( 0 ),
    Variables( X( :How old are you? ), Color( :"What is your favorite color? (select one)"n, Summary Statistic( "Mode" ) ) ),
    Elements( Bar( X, Legend( 3 ) ) ),
    SendToReport( Dispatch( {}, "graph title", TextEditBox, {Set Text( "Mode(What is your favorite color?)" )} ) )
);
dt3 = Open("data_table.jmp");
gb3 = dt3 << Graph Builder(
    Size( 534, 456 ),
    Show Control Panel( 0 ),
    Categorical Color Theme( "Paired"(1) ),
    Variables( X( :Carat Weight ), Y( :Price ), Color( :Color, Summary Statistic( "Mode" ) ) ),
    Elements( Heatmap( X, Y, Legend( 7 ) ) ),
    Local Data Filter( Add Filter( columns( :Depth ), Where( :Depth >= 60 & :Depth <= 64.3 ) ) )
);
gb4 = dt3 << Graph Builder(
    Size( 495, 440 ),
    Show Control Panel( 0 ),
    Variables( X( :Clarity ), Color( :Cut, Summary Statistic( "Mode" ) ) ),
    Elements( Treemap( X, Legend( 4 ) ) )
);
gb5 = dt3 << Graph Builder(
    Size( 534, 456 ),
    Show Control Panel( 0 ),
    Variables( X( :Carat Weight ), Y( :Price ) ),
    Elements( Points( X, Y, Legend( 6 ), Summary Statistic( "Mode" ) ), Smoother( X, Y, Legend( 10 ) ) )
);

Code Explanation:

1. Open data table;
2. Create Graph Builder.
3. Set size and hide control panel.
4. Define variables: age (X), height (Y), sex (color).
5. Add bar element with mode summary.
6. Open data table;
7. Create second Graph Builder.
8. Set size and hide control panel.
9. Define variables: age (X), favorite color (color).
10. Add bar element and set title.

Example 1185

Summary: Creates multiple Graph Builder windows with various elements, such as bar charts, heatmaps, and treemaps, to visualize data from different tables.

Code:

dt = Open("data_table.jmp");
gb = dt << Graph Builder(
    Size( 528, 450 ),
    Show Control Panel( 0 ),
    Variables( X( :age ), Y( :height ), Color( :sex, Summary Statistic( "Mode" ) ) ),
    Elements( Bar( X, Y, Legend( 4 ), Summary Statistic( "Mode" ) ) )
);
dt2 = Open("data_table.jmp");
gb2 = dt2 << Graph Builder(
    Size( 528, 450 ),
    Show Control Panel( 0 ),
    Variables( X( :How old are you? ), Color( :"What is your favorite color? (select one)"n, Summary Statistic( "Mode" ) ) ),
    Elements( Bar( X, Legend( 3 ) ) ),
    SendToReport( Dispatch( {}, "graph title", TextEditBox, {Set Text( "Mode(What is your favorite color?)" )} ) )
);
dt3 = Open("data_table.jmp");
gb3 = dt3 << Graph Builder(
    Size( 534, 456 ),
    Show Control Panel( 0 ),
    Categorical Color Theme( "Paired"(1) ),
    Variables( X( :Carat Weight ), Y( :Price ), Color( :Color, Summary Statistic( "Mode" ) ) ),
    Elements( Heatmap( X, Y, Legend( 7 ) ) ),
    Local Data Filter( Add Filter( columns( :Depth ), Where( :Depth >= 60 & :Depth <= 64.3 ) ) )
);
gb4 = dt3 << Graph Builder(
    Size( 495, 440 ),
    Show Control Panel( 0 ),
    Variables( X( :Clarity ), Color( :Cut, Summary Statistic( "Mode" ) ) ),
    Elements( Treemap( X, Legend( 4 ) ) )
);

Code Explanation:

1. Open data_table data
2. Create Graph Builder window.
3. Set size to 528x450.
4. Hide control panel.
5. Assign variables: age (X), height (Y), sex (Color).
6. Add bar element with mode summary.
7. Open data_table data
8. Create second Graph Builder window.
9. Set size to 528x450.
10. Hide control panel.
11. Assign variables: age (X), favorite color (Color).
12. Add bar element with legend.
13. Set graph title to "Mode(favorite color)".
14. Open data_table data
15. Create third Graph Builder window.
16. Set size to 534x456.
17. Hide control panel.
18. Set categorical color theme.
19. Assign variables: carat weight (X), price (Y), color (Color).
20. Add heatmap element with legend.
21. Add local data filter for depth.
22. Create fourth Graph Builder window.
23. Set size to 495x440.
24. Hide control panel.
25. Assign variables: clarity (X), cut (Color).
26. Add treemap element with legend.

Example 1186

Summary: Creates a graph builder with variables, elements, and local data filter to visualize height vs. weight for 'JANE' in the family cars dataset.

Code:

Open("data_table.jmp");
Graph Builder(
    Variables( X( :height ), Y( :weight ), Wrap( :family cars ) ),
    Elements( Smoother( X, Y, Legend( 9 ) ), Points( X, Y, Legend( 10 ) ) ),
    Local Data Filter(
        Inverse( 1 ),
        Add Filter( columns( :name ), Where( :name == "JANE" ), Display( :name, N Items( 15 ), Find( Set Text( "" ) ) ) )
    )
);

Code Explanation:

1. Open data table.
2. Launch Graph Builder.
3. Set X variable: height.
4. Set Y variable: weight.
5. Wrap by family cars.
6. Add smoother element.
7. Add points element.
8. Enable local data filter.
9. Filter by name "JANE".
10. Display filtered names.

Example 1187

Summary: Creates three Graph Builder windows with varying elements, including a bar chart, treemap, and heatmap, to visualize nested factors using operator and part configurations.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 528, 440 ),
    Show Control Panel( 0 ),
    Variables( X( :sports ), Color( :sex ) ),
    Elements( Bar( X, Legend( 5 ), Bar Style( "Packed" ) ) )
);
Graph Builder( Size( 495, 440 ), Show Control Panel( 0 ), Variables( X( :sports ), Color( :age ) ), Elements( Treemap( X, Legend( 9 ) ) ) );
Graph Builder(
    Size( 534, 464 ),
    Show Control Panel( 0 ),
    Variables( X( :sports ), Y( :family cars ), Color( :height ) ),
    Elements( Heatmap( X, Y, Legend( 5 ) ) )
);

Code Explanation:

1. Open data table;
2. Create Graph Builder window.
3. Set size to 528x440.
4. Hide control panel.
5. Set X variable to sports.
6. Set color variable to sex.
7. Add bar element with packed style.
8. Create another Graph Builder window.
9. Set size to 495x440.
10. Hide control panel.
11. Set X variable to sports.
12. Set color variable to age.
13. Add treemap element.
14. Create third Graph Builder window.
15. Set size to 534x464.
16. Hide control panel.
17. Set X variable to sports.
18. Set Y variable to family cars.
19. Set color variable to height.
20. Add heatmap element.

Example 1188

Summary: Creates multiple visualizations, including a bar chart for sports by sex, treemap for sports by age, heatmap for sports vs family cars by height, and parallel plot for sports and age by sex.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 528, 440 ),
    Show Control Panel( 0 ),
    Variables( X( :sports ), Color( :sex ) ),
    Elements( Bar( X, Legend( 5 ), Bar Style( "Packed" ) ) )
);
Graph Builder( Size( 495, 440 ), Show Control Panel( 0 ), Variables( X( :sports ), Color( :age ) ), Elements( Treemap( X, Legend( 9 ) ) ) );
Graph Builder(
    Size( 534, 464 ),
    Show Control Panel( 0 ),
    Variables( X( :sports ), Y( :family cars ), Color( :height ) ),
    Elements( Heatmap( X, Y, Legend( 5 ) ) )
);
Graph Builder(
    Size( 495, 450 ),
    Show Control Panel( 0 ),
    Variables( X( :sports ), X( :age, Position( 1 ) ), Color( :sex ) ),
    Elements( Parallel( X( 1 ), X( 2 ), Legend( 6 ) ) )
);

Code Explanation:

1. Open data table;
2. Create bar chart for sports by sex.
3. Create treemap for sports by age.
4. Create heatmap for sports vs family cars by height.
5. Create parallel plot for sports and age by sex.

Example 1189

Summary: Creates variability charts with nested factors using Graph Builder, displaying standard deviation charts and adjusting error interval directions.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 534, 450 ),
    Show Control Panel( 0 ),
    Variables( X( :age ), Y( :height ), Y( :weight ) ),
    Elements( Position( 1, 1 ), Bar( X, Y, Legend( 4 ), Error Interval( "Confidence Interval" ) ) ),
    Elements( Position( 1, 2 ), Bar( X, Y, Legend( 5 ), Error Interval( "Confidence Interval" ) ) ),
    SendToReport(
        Dispatch( {}, "Graph Builder", FrameBox, {DispatchSeg( BarSeg( 2 ), {Set Interval Draw Directions( "Upper" )} )} ),
        Dispatch( {}, "Graph Builder", FrameBox( 2 ), {DispatchSeg( BarSeg( 2 ), {Set Interval Draw Directions( "Lower" )} )} )
    )
);
Graph Builder(
    Size( 528, 450 ),
    Show Control Panel( 0 ),
    Variables( X( :sex ), Y( :height ) ),
    Elements( Bar( X, Y, Legend( 3 ), Error Interval( "Range" ) ) ),
    SendToReport(
        Dispatch( {}, "400", ScaleBox, {Legend Model( 3, Properties( 0, {Transparency( 0.3 )}, Item ID( "Mean", 1 ) ) )} ),
        Dispatch( {}, "Graph Builder", FrameBox, {DispatchSeg( BarSeg( 2 ), {Set Interval Draw Directions( "Lower" )} )} )
    )
);
Graph Builder(
    Size( 528, 464 ),
    Show Control Panel( 0 ),
    Variables( X( :age ), X( :sex, Position( 1 ) ), Y( :height ) ),
    Elements( Area( X( 1 ), X( 2 ), Y, Legend( 12 ), Error Interval( "Confidence Interval" ) ) ),
    SendToReport(
        Dispatch( {}, "400", ScaleBox,
            {Legend Model( 12, Properties( 0, {Fill Color( 6 ), Transparency( 0.3 )}, Item ID( "Mean", 1 ) ) )}
        ),
        Dispatch( {}, "Graph Builder", FrameBox, {DispatchSeg( BarSeg( 1 ), {Set Interval Draw Directions( "Upper" )} )} )
    )
);

Code Explanation:

1. Open data table.
2. Create first Graph Builder window.
3. Set window size.
4. Hide control panel.
5. Assign variables X and Y.
6. Add bar element with confidence interval.
7. Add another bar element with confidence interval.
8. Adjust error interval directions.
9. Create second Graph Builder window.
10. Set window size.
11. Hide control panel.
12. Assign variables X and Y.
13. Add bar element with range interval.
14. Adjust legend transparency.
15. Adjust error interval direction.
16. Create third Graph Builder window.
17. Set window size.
18. Hide control panel.
19. Assign variables X, X, and Y.
20. Add area element with confidence interval.
21. Adjust legend fill color and transparency.
22. Adjust error interval direction.

Example 1190

Summary: Creates two Graph Builders to visualize age distribution with a local data filter for female subjects, demonstrating correct and incorrect ordering methods.

Code:

dt = Open("data_table.jmp");
Graph Builder(
    Show Control Panel( 0 ),
    Variables(
        Y( :age, Order By( Transform Column( "Count", Formula( Col Number( :age, :age ) ) ), Ascending, Order Statistic( "Mean" ) ) )
    ),
    Elements( Histogram( Y, Legend( 3 ) ) ),
    Local Data Filter( Add Filter( columns( :sex ), Where( :sex == "F" ) ) ),
    SendToReport( Dispatch( {}, "graph title", TextEditBox, {Set Text( "age ordered by transform column (not ordered correctly)" )} ) )
);
Graph Builder(
    Show Control Panel( 0 ),
    Variables( Y( :age, Order By( :age, Ascending, Order Statistic( "N" ) ) ) ),
    Elements( Histogram( Y, Legend( 3 ) ) ),
    Local Data Filter( Add Filter( columns( :sex ), Where( :sex == "F" ) ) ),
    SendToReport( Dispatch( {}, "graph title", TextEditBox, {Set Text( "age ordered by count statistic directly is correct" )} ) )
);

Code Explanation:

1. Open data table;
2. Create first Graph Builder.
3. Hide control panel.
4. Set Y variable: age.
5. Order Y by transformed count.
6. Display histogram element.
7. Add local data filter for sex=F.
8. Set graph title for incorrect order.
9. Create second Graph Builder.
10. Set Y variable: age.
11. Order Y by count statistic.
12. Display histogram element.
13. Add local data filter for sex=F.
14. Set graph title for correct order.

Example 1191

Summary: Creates a variability chart with nested factors using Graph Builder, featuring a custom transform column and overlay encoding.

Code:

dt = Open("data_table.jmp");
gb = dt << Graph Builder(
    Transform Column( "Odd", Nominal, Formula( Modulo( :Year, 2 ) ) ),
    Transform Column( "Year Nominal", Nominal, Formula( :Year ) ),
    Variables( X( :Month ), Y( :Temperature ), Overlay( :Year Nominal, Overlay Encoding( "None" ) ), Color( :Odd ) ),
    Elements( Points( X, Y, Legend( 14 ) ), Smoother( X, Y, Legend( 15 ) ) )
);

Code Explanation:

1. Open data table.
2. Create Graph Builder object.
3. Add "Odd" transform column.
4. Add "Year Nominal" transform column.
5. Set X variable to Month.
6. Set Y variable to Temperature.
7. Set Overlay variable to Year Nominal.
8. Set Color variable to Odd.
9. Add Points element.
10. Add Smoother element.

Example 1192

Summary: Creates a variability chart with nested factors using Graph Builder, transforming columns and setting variables to display standard deviation charts.

Code:

dt2 = Open("data_table.jmp");
gb2 = dt2 << Graph Builder(
    Transform Column( "1960 or later", Nominal, Formula( :Intervention for post 1960 period ) ),
    Transform Column( "Year", Nominal, Formula( Year( :date ) ) ),
    Size( 643, 494 ),
    Show Control Panel( 0 ),
    Variables( X( :month ), Y( :Ozone Concentration ), Overlay( :Year, Overlay Encoding( "None" ) ), Color( :"1960 or later"n ) ),
    Elements( Points( X, Y, Legend( 27 ) ), Smoother( X, Y, Legend( 28 ) ) ),
    SendToReport(
        Dispatch( {}, "400", LegendBox,
            {Set Title( "1960 or later" ), Legend Position(
                {27, [0, 1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1], 28, [-3, -3, -3, -3, -3, -3, -3,
                -3, -3, -3, -3, -3, -3, -3, -3, -3, -3, -3, -3, -3, -3]}
            )}
        )
    )
);

Code Explanation:

1. Open data table;
2. Create Graph Builder object.
3. Transform "1960 or later" column.
4. Transform "Year" column.
5. Set graph size.
6. Hide control panel.
7. Define X, Y, Overlay, and Color variables.
8. Add Points and Smoother elements.
9. Send report to Graph Builder.
10. Customize legend title and position.

Example 1193

Summary: Creates two variability charts with nested factors using Graph Builder, featuring operator and part configurations, and displaying standard deviation charts.

Code:

dt = Open("data_table.jmp");
gb = dt << Graph Builder(
    Transform Column( "Odd", Nominal, Formula( Modulo( :Year, 2 ) ) ),
    Transform Column( "Year Nominal", Nominal, Formula( :Year ) ),
    Variables( X( :Month ), Y( :Temperature ), Overlay( :Year Nominal, Overlay Encoding( "None" ) ), Color( :Odd ) ),
    Elements( Points( X, Y, Legend( 14 ) ), Smoother( X, Y, Legend( 15 ) ) )
);
dt2 = Open("data_table.jmp");
gb2 = dt2 << Graph Builder(
    Transform Column( "1960 or later", Nominal, Formula( :Intervention for post 1960 period ) ),
    Transform Column( "Year", Nominal, Formula( Year( :date ) ) ),
    Size( 643, 494 ),
    Show Control Panel( 0 ),
    Variables( X( :month ), Y( :Ozone Concentration ), Overlay( :Year, Overlay Encoding( "None" ) ), Color( :"1960 or later"n ) ),
    Elements( Points( X, Y, Legend( 27 ) ), Smoother( X, Y, Legend( 28 ) ) ),
    SendToReport(
        Dispatch( {}, "400", LegendBox,
            {Set Title( "1960 or later" ), Legend Position(
                {27, [0, 1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1], 28, [-3, -3, -3, -3, -3, -3, -3,
                -3, -3, -3, -3, -3, -3, -3, -3, -3, -3, -3, -3, -3, -3]}
            )}
        )
    )
);
dt3 = Open("data_table.jmp");
gb3 = dt3 << Graph Builder(
    Size( 522, 444 ),
    Show Control Panel( 0 ),
    Variables( X( :sex ), Y( :height ), Overlay( :age, Overlay Encoding( "Style" ) ) ),
    Elements( Bar( X, Y, Legend( 7 ) ) ),
    SendToReport(
        Dispatch( {}, "Graph Builder", FrameBox,
            Add Text Annotation(
                Text( "adding minimized annotation" ),
                Fixed Size( 0 ),
                Text Box( {7, 4, 180, 28} ),
                Minimized( 1 ),
                Filled( 0 )
            )
        )
    )
);

Code Explanation:

1. Open data table;
2. Create Graph Builder object.
3. Transform "Year" to "Odd".
4. Transform "Year" to "Year Nominal".
5. Set X to "Month", Y to "Temperature".
6. Overlay by "Year Nominal".
7. Color by "Odd".
8. Add Points and Smoother elements.
9. Open data table;
10. Create Graph Builder object.

Example 1194

Summary: Creates a variability chart with nested factors using Graph Builder, displaying standard deviation charts and filtering data by sex.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 534, 2964 ),
    Show Control Panel( 0 ),
    Variables( X( :name ), Y( :height ), Page( :age ) ),
    Elements( Points( X, Y, Legend( 1 ) ), Smoother( X, Y, Legend( 2 ) ) ),
    Where( :sex == "F" )
);

Code Explanation:

1. Open data table.
2. Create Graph Builder object.
3. Set graph size.
4. Hide control panel.
5. Assign variables: X, Y, Page.
6. Add points element.
7. Add smoother element.
8. Filter data by sex.

Example 1195

Summary: Creates two variability charts with nested factors using Graph Builder, displaying standard deviation charts and customizing legend settings.

Code:

dt = Open("data_table.jmp");
gb = dt << Graph Builder(
    Size( 1200, 900 ),
    Show Control Panel( 0 ),
    Variables( X( :Horsepower ), Y( :Displacement ), Page( :Type, Levels per Row( 3 ) ) ),
    Elements( Contour( X, Y, Legend( 20 ), Line( 1 ), Number of Levels( 7 ), Smoothness( 0.0536 ) ) ),
    SendToReport(
        Dispatch( {}, "400", ScaleBox,
            {Legend Model(
                20,
                Properties(
                    0,
                    {gradient( {Color Theme( "Black Body"(1) ), Density Gradient( "Full Color" ), Width( 9 )} )},
                    Item ID( "Density", 1 )
                )
            )}
        )
    )
);
gb1 = dt << Graph Builder(
    Size( 1360, 852 ),
    Show Control Panel( 0 ),
    Variables(
        X( :Gas Tank Size ),
        Y( :Horsepower ),
        Page( :Type, Levels per Row( 3 ) ),
        Overlay( :Country, Overlay Encoding( "Style" ) ),
        Color( :Country )
    ),
    Elements( Smoother( X, Y, Legend( 30 ) ) )
);

Code Explanation:

1. Open data table;
2. Create Graph Builder instance gb.
3. Set graph size to 1200x900.
4. Hide control panel.
5. Define X as Horsepower, Y as Displacement.
6. Use Type for page variable.
7. Add contour element with legend, line, levels, and smoothness.
8. Customize legend with gradient and density settings.
9. Create another Graph Builder instance gb1.
10. Set graph size to 1360x852.
11. Hide control panel.
12. Define X as Gas Tank Size, Y as Horsepower.
13. Use Type for page variable.
14. Add Country for overlay and color.

Example 1196

Summary: Creates a variability chart with nested factors using Graph Builder, displaying standard deviation charts and configuring various graph settings.

Code:

dt2 = Open("data_table.jmp");
gb2 = dt2 << Graph Builder(
    Size( 1285, 775 ),
    Show Control Panel( 0 ),
    Link Page Axes( "Y Only" ),
    Replicate Linked Page Axes( 0 ),
    Page Level Fill Color( "Medium Light Gray" ),
    Variables( X( :Quarter ), Y( :Profit ), Page( :Product Line, Levels per Row( 3 ) ), Color( :Quarter ) ),
    Elements( Bar( X, Y, Legend( 6 ) ) )
);

Code Explanation:

1. Open data table;
2. Create Graph Builder object.
3. Set window size.
4. Hide control panel.
5. Link Y axes across pages.
6. Disable axis replication.
7. Set page background color.
8. Define variables for graph.
9. Add bar element to graph.
10. Display graph.

Example 1197

Summary: Creates three Graph Builder objects to visualize data from different perspectives, including a contour plot with nested factors and standard deviation charts.

Code:

dt = Open("data_table.jmp");
gb = dt << Graph Builder(
    Size( 1200, 900 ),
    Show Control Panel( 0 ),
    Variables( X( :Horsepower ), Y( :Displacement ), Page( :Type, Levels per Row( 3 ) ) ),
    Elements( Contour( X, Y, Legend( 20 ), Line( 1 ), Number of Levels( 7 ), Smoothness( 0.0536 ) ) ),
    SendToReport(
        Dispatch( {}, "400", ScaleBox,
            {Legend Model(
                20,
                Properties(
                    0,
                    {gradient( {Color Theme( "Black Body"(1) ), Density Gradient( "Full Color" ), Width( 9 )} )},
                    Item ID( "Density", 1 )
                )
            )}
        )
    )
);
gb1 = dt << Graph Builder(
    Size( 1360, 852 ),
    Show Control Panel( 0 ),
    Variables(
        X( :Gas Tank Size ),
        Y( :Horsepower ),
        Page( :Type, Levels per Row( 3 ) ),
        Overlay( :Country, Overlay Encoding( "Style" ) ),
        Color( :Country )
    ),
    Elements( Smoother( X, Y, Legend( 30 ) ) )
);
dt2 = Open("data_table.jmp");
gb2 = dt2 << Graph Builder(
    Size( 1285, 775 ),
    Show Control Panel( 0 ),
    Link Page Axes( "Y Only" ),
    Replicate Linked Page Axes( 0 ),
    Page Level Fill Color( "Medium Light Gray" ),
    Variables( X( :Quarter ), Y( :Profit ), Page( :Product Line, Levels per Row( 3 ) ), Color( :Quarter ) ),
    Elements( Bar( X, Y, Legend( 6 ) ) )
);
dt3 = Open("data_table.jmp");
gb3 = dt3 << Graph Builder(
    Size( 1132, 765 ),
    Show Control Panel( 0 ),
    Variables( X( :Tire ), Y( :Y ), Page( :Characteristic, Levels per Row( 2 ) ) ),
    Elements( Bar( X, Y, Legend( 12 ) ) )
);

Code Explanation:

1. Open data table;
2. Create Graph Builder object gb.
3. Set graph size and hide control panel.
4. Define X and Y variables, add page variable.
5. Add contour element with legend and settings.
6. Customize legend appearance in report.
7. Create another Graph Builder object gb1.
8. Set graph size and hide control panel.
9. Define X, Y, page, overlay, and color variables.
10. Add smoother element with legend.

Example 1198

Summary: Creates three Graph Builders with nested factors, displaying standard deviation charts and customizing legend settings.

Code:

dt = Open("data_table.jmp");
gb = dt << Graph Builder(
    Size( 1200, 900 ),
    Show Control Panel( 0 ),
    Variables( X( :Horsepower ), Y( :Displacement ), Page( :Type, Levels per Row( 3 ) ) ),
    Elements( Contour( X, Y, Legend( 20 ), Line( 1 ), Number of Levels( 7 ), Smoothness( 0.0536 ) ) ),
    SendToReport(
        Dispatch( {}, "400", ScaleBox,
            {Legend Model(
                20,
                Properties(
                    0,
                    {gradient( {Color Theme( "Black Body"(1) ), Density Gradient( "Full Color" ), Width( 9 )} )},
                    Item ID( "Density", 1 )
                )
            )}
        )
    )
);
gb1 = dt << Graph Builder(
    Size( 1360, 852 ),
    Show Control Panel( 0 ),
    Variables(
        X( :Gas Tank Size ),
        Y( :Horsepower ),
        Page( :Type, Levels per Row( 3 ) ),
        Overlay( :Country, Overlay Encoding( "Style" ) ),
        Color( :Country )
    ),
    Elements( Smoother( X, Y, Legend( 30 ) ) )
);
dt2 = Open("data_table.jmp");
gb2 = dt2 << Graph Builder(
    Size( 1285, 775 ),
    Show Control Panel( 0 ),
    Link Page Axes( "Y Only" ),
    Replicate Linked Page Axes( 0 ),
    Page Level Fill Color( "Medium Light Gray" ),
    Variables( X( :Quarter ), Y( :Profit ), Page( :Product Line, Levels per Row( 3 ) ), Color( :Quarter ) ),
    Elements( Bar( X, Y, Legend( 6 ) ) )
);
dt3 = Open("data_table.jmp");

Code Explanation:

1. Open data table;
2. Create Graph Builder with Horsepower vs. Displacement.
3. Set graph size to 1200x900.
4. Hide control panel.
5. Add Type page variable with 3 levels per row.
6. Add contour element with legend, line, and smoothness settings.
7. Customize legend gradient and width.
8. Create second Graph Builder with Gas Tank Size vs. Horsepower.
9. Set graph size to 1360x852.
10. Hide control panel.

Example 1199

Summary: Creates a variability chart with nested factors using Graph Builder, displaying standard deviation charts and configuring window settings.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 570, 684 ),
    Show Control Panel( 0 ),
    Fit to Window( "Off" ),
    Variables( X( :height ), Y( :weight ), Page( :sex, Show Title( 0 ) ), Group X( :age ) ),
    Elements( Points( X, Y, Legend( 1 ) ), Smoother( X, Y, Legend( 2 ) ) )
);

Code Explanation:

1. Open data table;
2. Create Graph Builder window.
3. Set window size.
4. Hide control panel.
5. Disable fit to window.
6. Define X, Y, Page, and Group X variables.
7. Add points element.
8. Add smoother element.
9. Display graph without title.

Example 1200

Summary: Creates a graph builder with nested factors using Graph Builder, displaying points and smoother elements.

Code:

Open("data_table.jmp");
Graph Builder(
    Show Control Panel( 0 ),
    Size( 570, 665 ),
    Variables( X( :height ), Y( :weight ), Page( :sex, Size( 97 ) ) ),
    Elements( Points( X, Y, Legend( 4 ) ), Smoother( X, Y, Legend( 5 ) ) )
);

Code Explanation:

1. Open data_table data
2. Create Graph Builder object.
3. Hide control panel.
4. Set window size.
5. Assign variables: X=height, Y=weight, Page=sex.
6. Add points element.
7. Add smoother element.
8. Display graph.

Example 1201

Summary: Creates a variability chart with nested factors using Graph Builder, featuring points and smoother elements, and displays standard deviation charts.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 534, 492 ),
    Show Control Panel( 0 ),
    Variables( X( :height ), Y( :weight ), Wrap( :age ), Overlay( :sex ) ),
    Elements( Points( X, Y, Legend( 30 ) ), Smoother( X, Y, Legend( 31 ), Confidence of Fit( 1 ) ) ),
    SendToReport( Dispatch( {}, "Y title", TextEditBox, {Rotate Text( "Horizontal" )} ) )
);

Code Explanation:

1. Open data_table data
2. Launch Graph Builder.
3. Set window size.
4. Hide control panel.
5. Define X, Y, Wrap, Overlay variables.
6. Add points element.
7. Add smoother element.
8. Set confidence level for smoother.
9. Rotate Y-axis text horizontally.
10. Display report.

Example 1202

Summary: Creates a variability chart with nested factors using Graph Builder, displaying standard deviation charts and configuring window size, legend position, and row order.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 528, 456 ),
    Show Control Panel( 0 ),
    Variables( Y( :height ), Color( :age ) ),
    Elements( Line( Y, Legend( 3 ), Row order( 1 ) ) )
);

Code Explanation:

1. Open data table.
2. Launch Graph Builder.
3. Set window size.
4. Hide control panel.
5. Define Y variable.
6. Define color variable.
7. Add line element.
8. Set legend position.
9. Maintain row order.

Example 1203

Summary: Creates a graph that visualizes height vs weight by sex, utilizing Graph Builder and Report objects to customize the appearance of the chart.

Code:

Open("data_table.jmp");
gbp = Graph Builder(
    Size( 700, 500 ),
    Show Control Panel( 0 ),
    Variables( X( :height ), Y( :weight ), Color( :sex ) ),
    Elements( Points( X, Y, Legend( 9 ) ) ),
    SendToReport( Dispatch( {}, "graph title", TextEditBox, {Set Text( "Height vs Weight by Sex" )} ) )
);
gb = Report( gbp );
gb[Text Edit Box( 1 )] << Padding( 20 );
gb[Text Edit Box( 3 )] << Padding( Left( 0 ), Top( 20 ), Right( 0 ), Bottom( 10 ) );
gb[Text Edit Box( 4 )] << Set Font Style( "Italic" );
gb[AxisBox( 1 )] << Border( 1, 0, 1, 1 );
gb[AxisBox( 2 )] << Text Color( "Dark Orange" );
gb[LegendBox( 1 )] << Background Color( "White" );
gbp << Save Script to Data Table("data_table");

Code Explanation:

1. Open data table.
2. Create Graph Builder object.
3. Set graph size and hide control panel.
4. Define variables for X, Y, and color.
5. Add points element to graph.
6. Set graph title.
7. Retrieve report object.
8. Adjust padding for first text box.
9. Adjust padding for third text box.
10. Set font style for fourth text box.
11. Customize border for X-axis.
12. Change text color for Y-axis.
13. Set background color for legend.
14. Save script to data table.

Example 1204

Summary: Creates a graph that visualizes height vs weight by sex, utilizing Graph Builder and Report to customize the layout and appearance.

Code:

dt = Open("data_table.jmp");
gbp = Graph Builder(
    Size( 700, 500 ),
    Show Control Panel( 0 ),
    Variables( X( :height ), Y( :weight ), Color( :sex ) ),
    Elements( Points( X, Y, Legend( 9 ) ) ),
    SendToReport( Dispatch( {}, "graph title", TextEditBox, {Set Text( "Height vs Weight by Sex" )} ) )
);
gb = Report( gbp );
gb[Text Edit Box( 1 )] << Padding( 20 );
gb[Text Edit Box( 3 )] << Padding( Left( 0 ), Top( 20 ), Right( 0 ), Bottom( 10 ) );
gb[Text Edit Box( 4 )] << Set Font Style( "Italic" );
gb[AxisBox( 1 )] << Border( 1, 0, 1, 1 );
gb[AxisBox( 2 )] << Text Color( "Dark Orange" );
gb[LegendBox( 1 )] << Background Color( "White" );
gbp << Save Script to Data Table("data_table");
gbp2 = dt << Run Script( "Test Customizations" );

Code Explanation:

1. Open data table.
2. Create Graph Builder object.
3. Set graph size and hide control panel.
4. Define X, Y, and color variables.
5. Add points element with legend.
6. Set graph title.
7. Retrieve graph report.
8. Adjust padding for first text box.
9. Adjust padding for third text box.
10. Set font style for fourth text box.

Example 1205

Summary: Creates a Graph Builder window with nested factors, displaying points and smoother elements for height, weight, and sex variables.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 534, 492 ),
    Show Control Panel( 0 ),
    Grid Color( "White" ),
    Title Fill Color( "White" ),
    Title Frame Color( "White" ),
    Level Fill Color( {255, 255, 255} ),
    Level Frame Color( "White" ),
    Level Spacing Color( "White" ),
    Variables( X( :height ), Y( :weight ), Group X( :sex ) ),
    Elements( Points( X, Y, Legend( 4 ) ), Smoother( X, Y, Legend( 5 ) ) )
);

Code Explanation:

1. Open data table;
2. Create Graph Builder window.
3. Set size to 534x492.
4. Hide control panel.
5. Set grid color to white.
6. Set title fill color to white.
7. Set title frame color to white.
8. Set level fill color to white.
9. Set level frame color to white.
10. Set level spacing color to white.
11. Assign variables: height, weight, sex.
12. Add points element with legend.
13. Add smoother element with legend.

Example 1206

Summary: Creates a variability chart with nested factors using Graph Builder, displaying standard deviation charts and customizing text segments for enhanced visualization.

Code:

dt = Open("data_table.jmp");
Graph Builder(
    Size( 534, 444 ),
    Show Control Panel( 0 ),
    Variables( X( :sex ), Y( :weight ), Color( :sex ) ),
    Elements(
        Caption Box( X, Y, Legend( 4 ), Summary Statistic( "Mean" ), Summary Statistic 2( "Median" ), Summary Statistic 3( "Mode" ) ),
        Box Plot( X, Y, Legend( 9 ) )
    ),
    SendToReport(
        Dispatch( {}, "Graph Builder", FrameBox,
            {DispatchSeg(
                Text Seg( 1 ),
                {Text Color( "Orange" ), Text Style( {Horizontal( "Center" ), Vertical( . ), Style( . )} ),
                Font( Font( "Tahoma" ), Size( 11 ), Style( "Bold" ) ), Set Location( 0.1, 0.95 )}
            ), DispatchSeg(
                Text Seg( 2 ),
                {Text Color( "BlueGreen" ), Text Style( {Horizontal( . ), Vertical( "VCenter" ), Style( . )} ),
                Font( Font( "Sitka Subheading" ), Size( 12 ), Style( "Italic" ) ), Set Location( ., 1 )}
            ), DispatchSeg(
                Text Seg( 3 ),
                {Text Color( "Purple" ), Text Style( {Horizontal( "Center" ), Vertical( "Bottom" ), Style( . )} ),
                Font( Font( "Times New Roman" ), Size( 10 ), Style( "Bold" ) ), Set Location( 0.5, 1 )}
            )}
        )
    )
);

Code Explanation:

1. Open data table.
2. Create Graph Builder window.
3. Set window size.
4. Hide control panel.
5. Assign variables to axes and color.
6. Add caption box element.
7. Add box plot element.
8. Customize first text segment.
9. Customize second text segment.
10. Customize third text segment.

Example 1207

Summary: Creates a bar chart with nested factors using Graph Builder, displaying the percentage of total for each group and configuring the legend position.

Code:

dt = Open("data_table.jmp");
dt << Graph Builder(
    Size( 551, 291 ),
    Show Control Panel( 0 ),
    Variables( X( :age ), Overlay( :sex ) ),
    Elements( Bar( X, Legend( 6 ), Summary Statistic( "% of Total" ) ) ),
    SendToReport( Dispatch( {}, "", ScaleBox, {Min( 0 ), Max( 0.4 ), Inc( 0.5 ), Minor Ticks( 0 )} ) )
);

Code Explanation:

1. Open data table;
2. Launch Graph Builder.
3. Set window size.
4. Hide control panel.
5. Assign variables: X=age, Overlay=sex.
6. Add bar element.
7. Set summary statistic to "% of Total".
8. Configure legend position.
9. Adjust scale box settings.
10. Set axis limits and ticks.

Example 1208

Summary: Creates two Graph Builder windows to visualize data with nested factors, using bar and line elements to display variability charts.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 547, 368 ),
    Show Control Panel( 0 ),
    Variables( X( :sex ), Y( :height ), Overlay( :weight ) ),
    Elements( Bar( X( 1 ), X( 2 ), Y ) )
);
Graph Builder(
    Size( 547, 368 ),
    Show Control Panel( 0 ),
    Variables( X( :sex ), Y( :height ), Overlay( :weight ) ),
    Elements( Line( X( 1 ), X( 2 ), Y ) )
);

Code Explanation:

1. Open data table;
2. Create first Graph Builder window.
3. Set window size.
4. Hide control panel.
5. Define X, Y, and overlay variables.
6. Add bar element.
7. Create second Graph Builder window.
8. Set window size.
9. Hide control panel.
10. Define X, Y, and overlay variables.
11. Add line element.

Example 1209

Summary: Creates a variability chart with nested factors using Graph Builder, displaying standard deviation charts and customizing legend settings.

Code:

dt = Open("data_table.jmp");
Graph Builder(
    Size( 570, 516 ),
    Show Control Panel( 0 ),
    Variables( X( :age ), Y( :height ), Overlay( :sex ) ),
    Elements( Line( X, Y, Legend( 3 ), Error Bars( "Standard Deviation" ) ), Points( X, Y, Legend( 4 ) ) ),
    SendToReport(
        Dispatch( {}, "400", ScaleBox,
            {Legend Model( 3, Base( 0, 4, 0, Item ID( "F", 2 ) ), Base( 1, 4, 1, Item ID( "M", 2 ) ), Base( 2, 4, 0 ), Base( 3, 4, 1 ) ),
            Legend Model(
                4,
                Base( 0, 0, 0, Item ID( "F", 1 ) ),
                Base( 1, 0, 0, Item ID( "M", 1 ) ),
                Properties( 0, {Marker( "Plus" )}, Item ID( "F", 1 ) ),
                Properties( 1, {Marker( "Square" )}, Item ID( "M", 1 ) )
            )}
        ),
        Dispatch( {}, "Graph Builder", FrameBox,
            {Grid Line Order( 3 ), Reference Line Order( 4 ), DispatchSeg( BarSeg( 1 ), {Error Bar Cap( "None" )} ),
            DispatchSeg( BarSeg( 2 ), {Error Bar Cap( "Large" )} )}
        ),
        Dispatch( {}, "400", LegendBox, {Legend Position( {3, [-3, -3, -3, -3], 4, [0, 1]} )} )
    )
);

Code Explanation:

1. Open data table.
2. Create Graph Builder object.
3. Set graph size.
4. Hide control panel.
5. Define X, Y, and overlay variables.
6. Add line and point elements.
7. Customize legend for lines.
8. Customize legend for points.
9. Remove error bar caps for first segment.
10. Set large error bar caps for second segment.

Example 1210

Summary: Creates two Graph Builder windows to visualize variability charts with nested factors, displaying standard deviation charts and customizing error bars and line/bar appearances.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 539, 385 ),
    Show Control Panel( 0 ),
    Variables( X( :age ), Y( :height ) ),
    Elements( Line( X, Y, Legend( 4 ), Error Bars( "Range" ) ) ),
    SendToReport(
        Dispatch( {}, "Graph Builder", FrameBox,
            {Grid Line Order( 2 ), Reference Line Order( 3 ), DispatchSeg(
                BarSeg( 1 ),
                {Line Color( "Red" ), Line Style( "Dotted" ), Line Width( 2 ), Error Bar Cap( "Large" ), Set Width Proportion( 0.2 )}
            )}
        )
    )
);
Graph Builder(
    Size( 544, 385 ),
    Show Control Panel( 0 ),
    Variables( X( :age ), Y( :height ) ),
    Elements( Bar( X, Y, Legend( 5 ), Error Bars( "Standard Deviation" ) ) ),
    SendToReport(
        Dispatch( {}, "Graph Builder", FrameBox,
            {DispatchSeg(
                BarSeg( 2 ),
                {Line Color( "Green" ), Line Style( "DashDot" ), Line Width( 3 ), Error Bar Cap( "Small" ), Set Width Proportion( 1 )}
            )}
        )
    )
);

Code Explanation:

1. Open data table.
2. Create first Graph Builder window.
3. Set graph size.
4. Hide control panel.
5. Assign X and Y variables.
6. Add line element with error bars.
7. Customize error bars and line appearance.
8. Create second Graph Builder window.
9. Set graph size.
10. Hide control panel.
11. Assign X and Y variables.
12. Add bar element with error bars.
13. Customize error bars and bar appearance.

Example 1211

Summary: Creates a graph builder with nested factors using operator and part configurations, displaying standard deviation charts.

Code:

dt = Open("data_table.jmp");
::ndrawgb = 0;
dt << Graph Builder(
    Size( 685, 500 ),
    show control panel( 0 ),
    Variables( X( :height ), Y( :weight ) ),
    Elements( Points( X, Y, Legend( 2 ) ), Smoother( X, Y, Legend( 3 ) ) ),
    SendToReport(
        Dispatch( {}, "Graph Builder", FrameBox,
            {Add Graphics Script(
                2,
                Description( "" ),
                ::ndrawgb++;
                Show( ::ndrawgb );
                Text Size( 13 );
                Transparency( 0.2 );
                Local( {i, xy},
                    For( i = 1, i < 50, i++,
                        xy = Eval List( {Random Uniform( 50, 72 ), Random Uniform( 100, 170 )} );
                        Text( xy, Char( ::ndrawgb ) );
                    )
                );
                Transparency( 0.7 );
                Text Size( 50 );
                Text( {60, 60}, Char( ::ndrawgb ) );
            )}
        )
    )
);

Code Explanation:

1. Open data table.
2. Initialize counter to zero.
3. Create Graph Builder object.
4. Set graph size.
5. Hide control panel.
6. Define X and Y variables.
7. Add points and smoother elements.
8. Send report to Graph Builder.
9. Add graphics script to frame.
10. Increment counter and display it.

Example 1212

Summary: Creates a variability chart with nested factors using Graph Builder, displaying standard deviation charts and treemaps.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 532, 452 ),
    Show Control Panel( 0 ),
    Variables( X( :Carat Weight ), X( :Table, Position( 1 ) ), X( :Depth ), Group Y( :Report ) ),
    Elements( Position( 1, 1 ), Histogram( X( 2 ), X( 1 ), Legend( 7 ) ) ),
    Elements( Position( 2, 1 ), Treemap( X, Legend( 5 ) ) )
);

Code Explanation:

1. Open data table;
2. Create new Graph Builder window.
3. Set window size.
4. Hide control panel.
5. Define X variables.
6. Define additional X variable.
7. Define Group Y variable.
8. Add histogram element.
9. Position histogram element.
10. Add treemap element.

Example 1213

Summary: Creates a variability chart with nested factors using Graph Builder, featuring bar elements and local data filtering.

Code:

bc = Open("data_table.jmp");
bc:sex[1] = "";
gb = Graph Builder(
    Size( 395, 287 ),
    Show Control Panel( 0 ),
    Fit to Window,
    Variables( X( :sex ), X( :age, Position( 1 ) ), Group X( :sex ), Overlay( :sex ), Color( :height ), Frequency( :age ) ),
    Elements( Bar( X( 1 ), X( 2 ), Legend( 42 ), Bar Style( "Bullet" ) ) ),
    Local Data Filter( Add Filter( columns( :sex ), Where( Is Missing( :sex ) ) ) ),
    SendToReport( Dispatch( {}, "400", ScaleBox, {Legend Model( 42, Properties( 0, {gradient}, Item ID( "height", 1 ) ) )} ) )
);
Try( Delete File( "$temp\gbParseError.jrn" ) );
gb << save journal( "$temp\gbParseError.jrn" );
Open( "$temp\gbParseError.jrn" );

Code Explanation:

1. Open table.
2. Set first sex value to empty.
3. Create Graph Builder.
4. Set graph size.
5. Hide control panel.
6. Fit graph to window.
7. Define variables for X, Group X, Overlay, Color, Frequency.
8. Add bar element with bullet style.
9. Add local data filter.
10. Save and open report.

Example 1214

Summary: Creates a variability chart with nested factors using operator and part configurations, displaying standard deviation charts in Graph Builder.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 479, 436 ),
    Show Control Panel( 0 ),
    Variables( X( :sex ), X( :age, Position( 1 ) ), Y( :height ), Y( :weight ), Group X( :sex ), Color( :age ) ),
    Elements(
        Position( 1, 1 ),
        Bar( X( 1 ), X( 2 ), Y, Legend( 14 ), Summary Statistic( "% of Total" ) ),
        Points( X( 1 ), X( 2 ), Y, Legend( 15 ), Summary Statistic( "% of Total" ) ),
        Line( X( 1 ), X( 2 ), Y, Legend( 16 ), Summary Statistic( "% of Total" ) )
    ),
    Elements(
        Position( 1, 2 ),
        Bar( X( 1 ), X( 2 ), Y, Legend( 11 ), Summary Statistic( "% of Total" ) ),
        Points( X( 1 ), X( 2 ), Y, Legend( 12 ), Summary Statistic( "% of Total" ) ),
        Line( X( 1 ), X( 2 ), Y, Legend( 13 ), Summary Statistic( "% of Total" ) )
    )
);

Code Explanation:

1. Open data table;
2. Create Graph Builder window.
3. Set window size to 479x436.
4. Hide control panel.
5. Define X variables: sex, age.
6. Define Y variables: height, weight.
7. Group by sex.
8. Color by age.
9. Add bar, points, and line elements for first position.
10. Add bar, points, and line elements for second position.

Example 1215

Summary: Creates a variability chart with nested factors using Graph Builder, displaying standard deviation charts and adjusting legend models for points and lines.

Code:

Open("data_table.jmp");
obj = Graph Builder(
    Size( 534, 448 ),
    Show Control Panel( 0 ),
    Variables( X( :age ), Y( :weight ), Overlay( :sex ) ),
    Elements( Points( X, Y, Legend( 27 ) ), Line( X, Y, Legend( 28 ) ) ),
    SendToReport(
        Dispatch( {}, "400", ScaleBox, {Legend Model( 27, Base( 0, 0, 0 ), Base( 1, 0, 0 ) )} ),
        Dispatch( {}, "400", LegendBox, {Legend Position( {27, [-1, -1], 28, [0, 1]} )} )
    )
);

Code Explanation:

1. Open data table.
2. Create Graph Builder object.
3. Set window size.
4. Hide control panel.
5. Assign variables: X=age, Y=weight, Overlay=sex.
6. Add points and line elements.
7. Send report to Graph Builder.
8. Adjust legend model for points.
9. Adjust legend model for lines.
10. Set legend positions.

Example 1216

Summary: Creates a variability chart with nested factors using Graph Builder, displaying standard deviation charts and adjusting legend settings.

Code:

Open("data_table.jmp");
obj = Graph Builder(
    Size( 534, 448 ),
    Show Control Panel( 0 ),
    Variables( X( :age ), Y( :weight ), Overlay( :sex ) ),
    Elements( Points( X, Y, Legend( 27 ) ), Line( X, Y, Legend( 28 ) ) ),
    SendToReport(
        Dispatch( {}, "400", ScaleBox, {Legend Model( 27, Base( 0, 0, 0 ), Base( 1, 0, 0 ) )} ),
        Dispatch( {}, "400", LegendBox, {Legend Position( {27, [-1, -1], 28, [0, 1]} ), Position( {-1, -1, 0, 1} )} )
    )
);
rpt = obj << report;

Code Explanation:

1. Open data table;
2. Create Graph Builder object.
3. Set graph size.
4. Hide control panel.
5. Define X, Y, and overlay variables.
6. Add points and line elements.
7. Adjust legend base settings.
8. Position legend items.
9. Assign report to variable.

Example 1217

Summary: Creates a variability chart with nested factors using operator and part configurations, displaying standard deviation charts in Graph Builder.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 768, 592 ),
    Show Control Panel( 0 ),
    Legend Position( "Inside Left" ),
    Variables( X( :Food Category ), Y( :Calories ), Color( :Calories ) ),
    Elements( Bar( X, Y, Legend( 7 ), Summary Statistic( "Sum" ) ) ),
    SendToReport(
        Dispatch( {}, "Calories", ScaleBox, {Label Row( Automatic Tick Marks( 0 ) )} ),
        Dispatch( {}, "", ScaleBox, {Label Row( Show Major Ticks( 0 ) )} ),
        Dispatch( {}, "400", ScaleBox,
            {Legend Model( 7, Properties( 0, {gradient( {Color Theme( "Muted Yellow to Red" ), Width( 12 )} )} ) )}
        ),
        Dispatch( {}, "400", LegendBox, {Set Title( "" )} )
    )
);
Graph Builder(
    Size( 768, 592 ),
    Show Control Panel( 0 ),
    Legend Position( "Inside Right" ),
    Variables( X( :Food Category ), Y( :Calories ), Color( :Calories ) ),
    Elements( Bar( X, Y, Legend( 7 ), Summary Statistic( "Sum" ) ) ),
    SendToReport(
        Dispatch( {}, "Calories", ScaleBox, {Label Row( Automatic Tick Marks( 0 ) )} ),
        Dispatch( {}, "", ScaleBox, {Label Row( Show Major Ticks( 0 ) )} ),
        Dispatch( {}, "400", ScaleBox,
            {Legend Model( 7, Properties( 0, {gradient( {Color Theme( "Muted Yellow to Red" ), Width( 12 )} )} ) )}
        ),
        Dispatch( {}, "400", LegendBox, {Set Title( "" )} )
    )
);

Code Explanation:

1. Open data table;
2. Create Graph Builder window.
3. Set size to 768x592.
4. Hide control panel.
5. Position legend inside left.
6. Set X variable to Food Category.
7. Set Y variable to Calories.
8. Set color variable to Calories.
9. Add bar element with sum summary statistic.
10. Customize report settings for Calories scale.
11. Customize report settings for main scale.
12. Customize legend model properties.
13. Remove legend title.
14. Repeat steps 2-13 with legend inside right.

Example 1218

Summary: Creates a Graph Builder object to visualize data from a nested factors table, utilizing variables for Movie Name, Rotten Tomatoes Score, Genre, and Theme.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 534, 4500 ),
    Show Control Panel( 0 ),
    Variables( X( :Movie Name ), Y( :Rotten Tomatoes Score ), Page( :Genre ), Wrap( :Theme ) ),
    Elements( Points( X, Y, Legend( 9 ) ) )
);

Code Explanation:

1. Open data table;
2. Create Graph Builder object.
3. Set window size.
4. Hide control panel.
5. Define X variable.
6. Define Y variable.
7. Define page variable.
8. Define wrap variable.
9. Add points element.
10. Display graph.

Example 1219

Summary: Creates a variability chart with nested factors using Graph Builder, displaying standard deviation charts and pin annotations for male and female categories.

Code:

Open("data_table.jmp");
Graph Builder(
    Show Control Panel( 0 ),
    Variables( X( :height ), Y( :weight ), Overlay( :sex ) ),
    Elements( Points( X, Y, Legend( 1 ) ), Smoother( X, Y, Legend( 2 ) ) ),
    SendToReport(
        Dispatch( {}, "Graph Builder", FrameBox,
            {Add Pin Annotation(
                Seg( Marker Seg( 2 ) ),
                Index( 1 ),
                Index Row( 6 ),
                UniqueID( 823375553 ),
                FoundPt( {317, 244} ),
                Origin( {61.0115606936416, 127.671232876712} ),
                Offset( {-18, -125} ),
                Tag Line( 1 )
            ), Add Pin Annotation(
                Seg( Marker Seg( 1 ) ),
                Index( 16 ),
                Index Row( 35 ),
                UniqueID( 823371952 ),
                FoundPt( {291, 291} ),
                Origin( {59.8843930635838, 114.794520547945} ),
                Offset( {-189, -114} ),
                Tag Line( 1 ),
                Use Gradient( 0 )
            )}
        )
    )
);

Code Explanation:

1. Open data table;
2. Launch Graph Builder.
3. Hide control panel.
4. Set X to height.
5. Set Y to weight.
6. Overlay by sex.
7. Add points element.
8. Add smoother element.
9. Add pin annotation for male.
10. Add pin annotation for female.

Example 1220

Summary: Creates a variability chart with nested factors using Graph Builder, displaying points and smoother elements.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 378, 287 ),
    Show Control Panel( 0 ),
    Variables( X( :height ), Y( :weight ) ),
    Elements( Points( X, Y, Legend( 2 ) ), Smoother( X, Y, Legend( 3 ) ) )
);

Code Explanation:

1. Open data table;
2. Launch Graph Builder.
3. Set window size.
4. Hide control panel.
5. Assign X variable.
6. Assign Y variable.
7. Add points element.
8. Add smoother element.
9. Display graph.

Example 1221

Summary: Creates a variability chart with nested factors using Graph Builder, displaying points and smoother elements with legends.

Code:

Open("data_table.jmp");
Graph Builder(
    Show Control Panel( 0 ),
    Variables( X( :height ), Y( :weight ) ),
    Elements( Points( X, Y, Legend( 2 ) ), Smoother( X, Y, Legend( 3 ) ) )
);

Code Explanation:

1. Open data table.
2. Create Graph Builder window.
3. Hide control panel.
4. Set X variable to height.
5. Set Y variable to weight.
6. Add points element.
7. Add smoother element.
8. Assign legend to points.
9. Assign legend to smoother.
10. Display graph.

Example 1222

Summary: Creates a geographic map to visualize the relationship between Years of Compulsory Education and Development Level, utilizing Graph Builder's Local Data Filter feature.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 748, 534 ),
    Show Control Panel( 0 ),
    Variables( Color( :Years of Compulsory Education ), Shape( :Territory ) ),
    Elements( Map Shapes( Legend( 2 ) ) ),
    Local Data Filter(
        Mode( Include( 0 ) ),
        Add Filter(
            columns( :Development Level ),
            Where( :Development Level == "" ),
            Display( :Development Level, Size( 160, 75 ), List Display )
        )
    ),
    SendToReport(
        Dispatch( {}, "", ScaleBox,
            {Min( -190.267259502854 ), Max( 190.267259502854 ), Inc( 50 ), Minor Ticks( 0 ), Label Row( Show Major Grid( 1 ) )}
        ),
        Dispatch( {}, "", ScaleBox( 2 ),
            {Min( -135.958708732916 ), Max( 128.177016223987 ), Inc( 50 ), Minor Ticks( 1 ), Label Row( Show Major Grid( 1 ) )}
        ),
        Dispatch( {}, "400", ScaleBox,
            {Legend Model(
                2,
                Properties(
                    0,
                    {gradient( {Color Theme( "White to Green" ), Label Format( "Fixed Dec", 15, 0 )} )},
                    Item ID( "Years of Compulsory Education", 1 )
                )
            )}
        ),
        Dispatch( {}, "graph title", TextEditBox, {Set Text( "Years of Compulsory Education" )} ),
        Dispatch( {}, "400", LegendBox, {Set Title( "Years" )} )
    )
);

Code Explanation:

1. Open data table;
2. Launch Graph Builder.
3. Set window size.
4. Hide control panel.
5. Define color and shape variables.
6. Add map shapes element.
7. Enable local data filter.
8. Add filter for Development Level.
9. Configure axis scales.
10. Customize legend and title.

Example 1223

Summary: Creates a variability chart with nested factors using Graph Builder, displaying points and smoother elements.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 522, 435 ),
    Show Control Panel( 0 ),
    Title Alignment( "Left" ),
    Variables( X( :height ), Y( :weight ) ),
    Elements( Points( X, Y, Legend( 2 ) ), Smoother( X, Y, Legend( 3 ) ) ),
    SendToReport( Dispatch( {}, "graph title", TextEditBox, {Justify Text( "Left" ), Set Text( "aaa" )} ) )
);

Code Explanation:

1. Open data table.
2. Launch Graph Builder.
3. Set window size.
4. Hide control panel.
5. Align title left.
6. Assign variables X and Y.
7. Add points element.
8. Add smoother element.
9. Justify title left.
10. Set title text "aaa".

Example 1224

Summary: Creates a variability chart with nested factors using operator and part configurations, displaying standard deviation charts in Graph Builder.

Code:

Open("data_table.jmp");
Graph Builder( Size( 534, 464 ), Show Control Panel( 0 ), Variables( X( :In what grade are you ) ), Elements( Bar( X, Legend( 2 ) ) ) );

Code Explanation:

1. Open data table;
2. Launch Graph Builder.
3. Set window size.
4. Hide control panel.
5. Assign X variable.
6. Add bar element.
7. Set legend position.

Example 1225

Summary: Creates a variability chart with nested factors using Graph Builder, displaying standard deviation charts and box plots to analyze cholesterol and triglycerides levels.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 612, 546 ),
    Show Control Panel( 0 ),
    Variables( X( :Alcohol use ), Y( :Cholesterol ), Y( :Triglycerides, Position( 1 ) ) ),
    Elements(
        Box Plot( X, Y( 1 ), Y( 2 ), Legend( 11 ) ),
        Caption Box( X, Y( 1 ), Y( 2 ), Legend( 8 ), Summary Statistic( "Range" ), Summary Statistic 2( "Sum" ), Location( "Axis Table" ) )
    )
);

Code Explanation:

1. Open lipid data file.
2. Create Graph Builder window.
3. Set window size.
4. Hide control panel.
5. Define X and Y variables.
6. Add box plot element.
7. Add caption box element.
8. Configure caption box summary statistics.
9. Set location for summary statistics.
10. Display graph.

Example 1226

Summary: Creates a heatmap visualization in Graph Builder to display the relationship between height and weight, with a customized legend title.

Code:

Open("data_table.jmp");
Graph Builder(
    Show Control Panel( 0 ),
    Variables( X( :height ), Y( :weight ) ),
    Elements( Heatmap( X, Y, Legend( 19 ) ) ),
    SendToReport( Dispatch( {}, "400", LegendBox, {Set Title( "Count" )} ) )
);

Code Explanation:

1. Open data_table data
2. Launch Graph Builder.
3. Hide control panel.
4. Set X variable to height.
5. Set Y variable to weight.
6. Add heatmap element.
7. Configure legend for heatmap.
8. Send report to Graph Builder.
9. Dispatch legend box.
10. Set legend title to "Count".

Example 1227

Summary: Creates a heatmap to visualize the relationship between age and weight, with a legend displaying count.

Code:

Open("data_table.jmp");
Graph Builder(
    Show Control Panel( 0 ),
    Variables( X( :age ), Y( :weight ) ),
    Elements( Heatmap( X, Y, Legend( 11 ) ) ),
    SendToReport( Dispatch( {}, "400", LegendBox, {Set Title( "Count" )} ) )
);

Code Explanation:

1. Open data table;
2. Launch Graph Builder.
3. Hide control panel.
4. Set X variable to age.
5. Set Y variable to weight.
6. Add heatmap element.
7. Configure legend to show count.
8. Dispatch to report.
9. Set legend title to "Count".
10. Display graph.

Example 1228

Summary: Creates a variability chart with nested factors using Graph Builder, featuring a Heatmap and Points elements to visualize relationships between height, weight, age, and sex.

Code:

Open("data_table.jmp");
Graph Builder(
    Y Group Title Orientation( "Horizontal" ),
    Y Group Level Orientation( "Horizontal" ),
    Show Control Panel( 0 ),
    Variables( X( :height ), Y( :weight ), Group X( :age ), Group Y( :sex ) ),
    Elements( Heatmap( X, Y, Legend( 4 ) ), Points( X, Y, Legend( 5 ) ) )
);

Code Explanation:

1. Open data table;
2. Create Graph Builder object.
3. Set Y group title orientation.
4. Set Y group level orientation.
5. Hide control panel.
6. Define variables for X, Y, Group X, Group Y.
7. Add Heatmap element.
8. Add Points element.
9. Assign Legend to Heatmap.
10. Assign Legend to Points.

Example 1229

Summary: Creates two heatmaps with nested factors using Graph Builder, displaying standard deviation charts and color schemes.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 570, 490 ),
    Show Control Panel( 0 ),
    Variables( X( :weight ), Y( :height ), Group X( :sex ), Group Y( :age ), Color( :age ), Color( :sex ) ),
    Elements( Heatmap( Color( 1 ), Legend( 9 ) ) )
);
Graph Builder(
    Size( 570, 490 ),
    Show Control Panel( 0 ),
    Variables( X( :weight ), Y( :height ), Group X( :sex ), Group Y( :age ), Color( :age ), Color( :sex ) ),
    Elements( Heatmap( Color( 2 ), Legend( 9 ) ) )
);

Code Explanation:

1. Open data table;
2. Create first Graph Builder window.
3. Set window size to 570x490.
4. Hide control panel.
5. Define X, Y, Group X, Group Y, and Color variables.
6. Add Heatmap element with color scheme 1.
7. Set legend position to 9.
8. Create second Graph Builder window.
9. Repeat steps 3-7 for second window.
10. Use color scheme 2 for second heatmap.

Example 1230

Summary: Creates a heatmap visualization in Graph Builder to display regional population data, with State as the x-axis and Region as the y-axis.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 530, 368 ),
    Show Control Panel( 0 ),
    Variables( X( :State ), Y( :Region ), Frequency( :POP ) ),
    Elements( Heatmap( X, Y, Legend( 10 ) ) )
);

Code Explanation:

1. Open data table;
2. Create Graph Builder window.
3. Set size to 530x368.
4. Hide control panel.
5. Define X variable as State.
6. Define Y variable as Region.
7. Define frequency as POP.
8. Add Heatmap element.
9. Set legend to 10.

Example 1231

Summary: Creates a heatmap to visualize the relationship between age and height, with log-scale formatting for the y-axis.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 482, 324 ),
    Show Control Panel( 0 ),
    Variables( X( :age ), Y( :height ) ),
    Elements( Heatmap( X, Y, Legend( 2 ) ) ),
    SendToReport(
        Dispatch( {}, "height", ScaleBox, {Scale( "Log" ), Format( "Best", 12 ), Min( 50 ), Max( 72.5 ), Inc( 1 ), Minor Ticks( 1 )} )
    )
);

Code Explanation:

1. Open data table;
2. Create Graph Builder object.
3. Set graph size.
4. Hide control panel.
5. Define X and Y variables.
6. Add heatmap element.
7. Send report settings.
8. Adjust height scale.
9. Set log scale.
10. Format axis labels.

Example 1232

Summary: Creates a heatmap to visualize nested factors using Graph Builder, displaying standard deviation charts and legend.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 531, 450 ),
    Show Control Panel( 0 ),
    Variables( X( :Day of Month ), Y( :Month ), Color( :Arrival Delay ) ),
    Elements( Heatmap( X, Y, Legend( 5 ) ) )
);

Code Explanation:

1. Open data_table data
2. Launch Graph Builder.
3. Set window size.
4. Hide control panel.
5. Assign variables.
6. Add heatmap element.
7. Display legend.

Example 1233

Summary: Creates a heatmap visualization in Graph Builder to display the relationship between height and other variables, with customized scale settings.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 114, 327 ),
    Show Control Panel( 0 ),
    Variables( Y( :height ) ),
    Elements( Heatmap( Y, Legend( 8 ) ) ),
    SendToReport(
        Dispatch( {}, "height", ScaleBox, {Min( 50 ), Max( 72.5 ), Inc( 10 ), Minor Ticks( 0 ), Label Row( Tick Offset( 5 ) )} )
    )
);

Code Explanation:

1. Open data table;
2. Create Graph Builder window.
3. Set window size.
4. Hide control panel.
5. Set Y variable to height.
6. Add heatmap element.
7. Configure heatmap legend.
8. Send report settings.
9. Adjust height scale minimum.
10. Set height scale maximum.
11. Define height scale increment.
12. Disable minor ticks.
13. Set tick label offset.

Example 1234

Summary: Creates a heatmap visualization with nested factors using Graph Builder, showcasing relationships between sex, height, and age.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 565, 500 ),
    Show Control Panel( 0 ),
    Variables( X( :sex ), Y( :height ), Color( :age ) ),
    Elements( Heatmap( X, Y, Legend( 2 ) ) )
);

Code Explanation:

1. Open data table;
2. Launch Graph Builder.
3. Set window size.
4. Hide control panel.
5. Define X variable.
6. Define Y variable.
7. Define color variable.
8. Add heatmap element.
9. Position legend.

Example 1235

Summary: Creates two variability charts with nested factors using operator and part configurations, displaying standard deviation charts in JMP.

Code:

dt = Open("data_table.jmp");
dt << Graph Builder(
    Show Control Panel( 0 ),
    Variables( X( :Carat Weight ), Y( :Depth ), Size( :Price ) ),
    Elements( Heatmap( X, Y, Legend( 5 ), Label( "Label by Value" ), Cell Outline( 1 ) ) )
);
dt << Graph Builder(
    Show Control Panel( 0 ),
    Variables( X( :Carat Weight ), Y( :Price ), Color( :Table ), Size( :Depth, Summary Statistic( "Max" ) ) ),
    Elements( Heatmap( X, Y, Legend( 6 ) ) ),
    SendToReport(
        Dispatch( {}, "400", ScaleBox,
            {Legend Model( 6, Properties( 0, {gradient( {Color Theme( "Blue White Red" )} )}, Item ID( "Table", 1 ) ) )}
        )
    )
);

Code Explanation:

1. Open data table;
2. Create first Graph Builder.
3. Hide control panel.
4. Set X: Carat Weight, Y: Depth, Size: Price.
5. Add Heatmap element.
6. Configure Heatmap legend, label, and outline.
7. Create second Graph Builder.
8. Hide control panel.
9. Set X: Carat Weight, Y: Price, Color: Table, Size: Max Depth.
10. Add Heatmap element with gradient color theme.

Example 1236

Summary: Creates a heatmap to visualize relationships between Weight, Horsepower, and Country, with Turning Circle as a size variable.

Code:

dt2 = Open("data_table.jmp");
dt2 << Graph Builder(
    Show Control Panel( 0 ),
    Variables( X( :Weight ), Y( :Horsepower ), Wrap( :Country ), Size( :Turning Circle ) ),
    Elements( Heatmap( X, Y, Legend( 28 ) ) ),
    SendToReport(
        Dispatch( {}, "400", ScaleBox,
            {Legend Model(
                28,
                Properties( 0, {gradient( {Color Theme( "Yellow to Red" ), Width( 12 ), N Labels( 5 )} )}, Item ID( "Count", 1 ) )
            )}
        )
    )
);

Code Explanation:

1. Open data table.
2. Create Graph Builder object.
3. Hide control panel.
4. Set X variable: Weight.
5. Set Y variable: Horsepower.
6. Wrap by Country.
7. Size by Turning Circle.
8. Add Heatmap element.
9. Customize legend properties.
10. Apply report settings.

Example 1237

Summary: Creates two heatmaps with nested factors using Graph Builder, customizing legend properties and window size.

Code:

dt3 = Open("data_table.jmp");
dt4 = Open("data_table.jmp");
dt3 << Graph Builder(
    Show Control Panel( 0 ),
    Categorical Color Theme( "JMP Light" ),
    Variables( X( :weight ), Y( :height ), Color( :sex ), Size( :age ) ),
    Elements( Heatmap( X, Y, Legend( 4 ), Label( "Label by Value" ) ) )
);
dt4 << Graph Builder(
    Size( 531, 456 ),
    Show Control Panel( 0 ),
    Variables( X( :Carat Weight ), Group Y( :Report ), Size( :Price ) ),
    Elements( Heatmap( X, Legend( 3 ) ) ),
    SendToReport(
        Dispatch( {}, "400", ScaleBox,
            {Legend Model(
                3,
                Properties( 0, {gradient( {Max Lightness( 0.8655 ), Width( 12 ), Discrete Colors( 1 )} )}, Item ID( "Count", 1 ) )
            )}
        )
    )
);

Code Explanation:

1. Open data table.
2. Open data table.
3. Create Graph Builder for data_table.
4. Hide control panel.
5. Set color theme to "JMP Light".
6. Define variables: X(weight), Y(height), Color(sex), Size(age).
7. Add heatmap element with legend and labels.
8. Create Graph Builder for data_table.
9. Set window size to 531x456.
10. Hide control panel.
11. Define variables: X(Carat Weight), Group Y(Report), Size(Price).
12. Add heatmap element with legend.
13. Customize legend properties.

Example 1238

Summary: Creates a heatmap to visualize relationships between Genre, World Gross, and Profitability, with Audience Score as a size variable.

Code:

dt4 = Open("data_table.jmp");
dt4 << Graph Builder(
    Size( 534, 449 ),
    Show Control Panel( 0 ),
    Variables( X( :Genre ), Y( :World Gross ), Color( :Profitability ), Size( :Audience Score ) ),
    Elements( Heatmap( X, Y, Legend( 9 ) ) )
);

Code Explanation:

1. Open table.
2. Set graph size.
3. Hide control panel.
4. Define X variable.
5. Define Y variable.
6. Define color variable.
7. Define size variable.
8. Add heatmap element.
9. Set legend position.
10. Display graph.

Example 1239

Summary: Creates a heatmap to visualize the relationship between sex, age, and height percentage in a nested factor configuration using Graph Builder.

Code:

Open("data_table.jmp") << Graph Builder(
    Size( 509, 402 ),
    Show Control Panel( 0 ),
    Variables( X( :sex ), Y( :age ), Group X( :age ), Color( :height, Summary Statistic( "% of Total" ) ) ),
    Elements( Heatmap( X, Y ) )
);

Code Explanation:

1. Open data_table data
2. Launch Graph Builder.
3. Set window size to 509x402.
4. Hide control panel.
5. Assign variables: X=sex, Y=age, Group X=age, Color=height.
6. Use "% of Total" for height summary.
7. Add heatmap element.
8. Plot sex vs. age.
9. Group by age.
10. Color by height percentage.

Example 1240

Summary: Creates a heatmap visualization with nested factors using Graph Builder, displaying age on the X-axis and sex on the Y-axis.

Code:

Open("data_table.jmp");
Graph Builder(
    Show Control Panel( 0 ),
    Continuous Color Theme( "Green Yellow Red" ),
    Categorical Color Theme( "White to Purple" ),
    Variables( X( :age ), Y( :sex ) ),
    Elements( Heatmap( X, Y, Legend( 2 ) ) )
);

Code Explanation:

1. Open data table;
2. Launch Graph Builder.
3. Hide control panel.
4. Set continuous color theme.
5. Set categorical color theme.
6. Assign age to X-axis.
7. Assign sex to Y-axis.
8. Add heatmap element.
9. Display legend for color.

Example 1241

Summary: Creates multiple heatmaps with varying configurations using Graph Builder, showcasing nested factors and standard deviation charts.

Code:

dt1 = Open("data_table1.jmp");
dt2 = Open("data_table2.jmp");
dt1 << Graph Builder(
    Size( 548, 500 ),
    Show Control Panel( 0 ),
    Variables( Group X( :REASON ), Group Y( :BAD ), Color( :Loan, Summary Statistic( "Median" ) ) ),
    Elements(
        Heatmap( Legend( 3 ), Label( "Label by Value" ), Label Format( "Fixed Dec", 20, 4 ) ),
        Caption Box( Legend( 4 ), Summary Statistic( "Median" ) )
    )
);
dt2 << Graph Builder(
    Size( 535, 458 ),
    Show Control Panel( 0 ),
    Variables( X( :CO ), Y( :POP ), Color( :SO2, Summary Statistic( "First Quartile" ) ) ),
    Elements( Heatmap( X, Y, Legend( 9 ), Label( "Label by Value" ) ) ), 
);
dt2 << Graph Builder(
    Size( 535, 420 ),
    Show Control Panel( 0 ),
    Variables( Y( :POP ), Color( :SO2, Summary Statistic( "Third Quartile" ) ) ),
    Elements( Heatmap( Y, Legend( 9 ), Label( "Label by Value" ) ) )
);
dt2 << Graph Builder(
    Size( 643, 604 ),
    Show Control Panel( 0 ),
    Variables( Wrap( :Region ), Color( :NO, Summary Statistic( "Interquartile Range" ) ) ),
    Elements( Heatmap( Legend( 5 ), Label( "Label by Value" ) ), Caption Box( Legend( 6 ), Summary Statistic( "Interquartile Range" ) ) )
);

Code Explanation:

1. Open data table 1;
2. Open data table 2;
3. Create heatmap for Equity data.
4. Set size to 548x500.
5. Hide control panel.
6. Group X by REASON.
7. Group Y by BAD.
8. Color by Loan median.
9. Add heatmap element.
10. Add caption box for median.
11. Create heatmap for Cities data (first).
12. Set size to 535x458.
13. Hide control panel.
14. X by CO.
15. Y by POP.
16. Color by SO2 first quartile.
17. Add heatmap element.
18. Create heatmap for Cities data (second).
19. Set size to 535x420.
20. Hide control panel.
21. Y by POP.
22. Color by SO2 third quartile.
23. Add heatmap element.
24. Create heatmap for Cities data (third).
25. Set size to 643x604.
26. Hide control panel.
27. Wrap by Region.
28. Color by NO interquartile range.
29. Add heatmap element.
30. Add caption box for interquartile range.

Example 1242

Summary: Creates multiple heatmaps with varying configurations and summary statistics using Graph Builder in JMP.

Code:

dt = Open("data_table1.jmp");
dt2 = Open("data_table2.jmp");
dt << Graph Builder(
    Size( 548, 500 ),
    Show Control Panel( 0 ),
    Variables( Group X( :REASON ), Group Y( :BAD ), Color( :Loan, Summary Statistic( "Median" ) ) ),
    Elements(
        Heatmap( Legend( 3 ), Label( "Label by Value" ), Label Format( "Fixed Dec", 20, 4 ) ),
        Caption Box( Legend( 4 ), Summary Statistic( "Median" ) )
    )
);
dt2 << Graph Builder(
    Size( 535, 458 ),
    Show Control Panel( 0 ),
    Variables( X( :CO ), Y( :POP ), Color( :SO2, Summary Statistic( "First Quartile" ) ) ),
    Elements( Heatmap( X, Y, Legend( 9 ), Label( "Label by Value" ) ) ), 
);
dt2 << Graph Builder(
    Size( 535, 420 ),
    Show Control Panel( 0 ),
    Variables( Y( :POP ), Color( :SO2, Summary Statistic( "Third Quartile" ) ) ),
    Elements( Heatmap( Y, Legend( 9 ), Label( "Label by Value" ) ) )
);
dt2 << Graph Builder(
    Size( 643, 604 ),
    Show Control Panel( 0 ),
    Variables( Wrap( :Region ), Color( :NO, Summary Statistic( "Interquartile Range" ) ) ),
    Elements( Heatmap( Legend( 5 ), Label( "Label by Value" ) ), Caption Box( Legend( 6 ), Summary Statistic( "Interquartile Range" ) ) )
);
dt << Graph Builder(
    Size( 702, 496 ),
    Show Control Panel( 0 ),
    Variables( X( :VALUE ), Y( :Validation ), Color( :CLNO, Summary Statistic( "Median Absolute Deviation" ) ) ),
    Elements( Heatmap( X, Y, Legend( 5 ), Label( "Label by Value" ) ) )
);

Code Explanation:

1. Open data table 1;
2. Open data table 2;
3. Create heatmap for Equity data.
4. Configure heatmap size and control panel.
5. Set X, Y, and color variables for Equity heatmap.
6. Add heatmap element with legend and label settings.
7. Add caption box for median summary statistic.
8. Create first heatmap for Cities data.
9. Configure heatmap size and control panel.
10. Set X, Y, and color variables for first Cities heatmap.
11. Add heatmap element with legend and label settings.
12. Create second heatmap for Cities data.
13. Configure heatmap size and control panel.
14. Set Y and color variables for second Cities heatmap.
15. Add heatmap element with legend and label settings.
16. Create third heatmap for Cities data.
17. Configure heatmap size and control panel.
18. Set wrap variable and color variables for third Cities heatmap.
19. Add heatmap element with legend and label settings.
20. Add caption box for interquartile range summary statistic.
21. Create fourth heatmap for Equity data.
22. Configure heatmap size and control panel.
23. Set X, Y, and color variables for fourth Equity heatmap.
24. Add heatmap element with legend and label settings.

Example 1243

Summary: Creates multiple heatmaps with varying configurations using Graph Builder in JMP, showcasing nested factors and standard deviation charts.

Code:

dt = Open("data_table1.jmp");
dt2 = Open("data_table2.jmp");
dt << Graph Builder(
    Size( 548, 500 ),
    Show Control Panel( 0 ),
    Variables( Group X( :REASON ), Group Y( :BAD ), Color( :Loan, Summary Statistic( "Median" ) ) ),
    Elements(
        Heatmap( Legend( 3 ), Label( "Label by Value" ), Label Format( "Fixed Dec", 20, 4 ) ),
        Caption Box( Legend( 4 ), Summary Statistic( "Median" ) )
    )
);
dt2 << Graph Builder(
    Size( 535, 458 ),
    Show Control Panel( 0 ),
    Variables( X( :CO ), Y( :POP ), Color( :SO2, Summary Statistic( "First Quartile" ) ) ),
    Elements( Heatmap( X, Y, Legend( 9 ), Label( "Label by Value" ) ) ), 
);
dt2 << Graph Builder(
    Size( 535, 420 ),
    Show Control Panel( 0 ),
    Variables( Y( :POP ), Color( :SO2, Summary Statistic( "Third Quartile" ) ) ),
    Elements( Heatmap( Y, Legend( 9 ), Label( "Label by Value" ) ) )
);
dt2 << Graph Builder(
    Size( 643, 604 ),
    Show Control Panel( 0 ),
    Variables( Wrap( :Region ), Color( :NO, Summary Statistic( "Interquartile Range" ) ) ),
    Elements( Heatmap( Legend( 5 ), Label( "Label by Value" ) ), Caption Box( Legend( 6 ), Summary Statistic( "Interquartile Range" ) ) )
);

Code Explanation:

1. Open data table 1.
2. Open data table 2.
3. Create heatmap for Equity data.
4. Set graph size to 548x500.
5. Hide control panel.
6. Group X by REASON, Group Y by BAD.
7. Color by Loan median.
8. Add heatmap element.
9. Add caption box for median.
10. Create heatmap for Cities data, first quartile SO2.
11. Set graph size to 535x458.
12. Hide control panel.
13. Plot CO vs POP.
14. Color by SO2 first quartile.
15. Add heatmap element.
16. Create heatmap for Cities data, third quartile SO2.
17. Set graph size to 535x420.
18. Hide control panel.
19. Plot POP, color by SO2 third quartile.
20. Add heatmap element.
21. Create heatmap for Cities data, NO interquartile range.
22. Set graph size to 643x604.
23. Hide control panel.
24. Wrap by Region, color by NO IQR.
25. Add heatmap element.
26. Add caption box for IQR.

Example 1244

Summary: Creates a heatmap to visualize the relationship between age and sex, utilizing Graph Builder's Variables and Elements features.

Code:

Open("data_table.jmp");
Graph Builder(
    Show Control Panel( 0 ),
    Variables(
        X(
            Transform Column(
                "age'",
                Ordinal,
                Set Property( "Configure Levels", 1 ),
                Set Property( "Value Order", {Custom Order( {17, 16, 15, 14, 13, 12} )} ),
                Value Labels( {12 = "12", 13 = "13", 14 = "14", 15 = "15", 16 = "16", 17 = "17"} ),
                Use Value Labels( 1 ),
                Formula( :age )
            )
        ),
        Y(
            Transform Column(
                "sex'",
                Set Property( "Configure Levels", 1 ),
                Set Property( "Value Order", {Custom Order( {"M", "F"} )} ),
                Formula( :sex )
            )
        )
    ),
    Elements( Heatmap( X, Y, Legend( 2 ) ) )
);

Code Explanation:

1. Open data table;
2. Create Graph Builder.
3. Hide control panel.
4. Set X variable.
5. Transform age column.
6. Set ordinal scale.
7. Configure custom levels.
8. Define value order for age.
9. Set value labels for age.
10. Apply value labels to age.
11. Set Y variable.
12. Transform sex column.
13. Configure custom levels for sex.
14. Define value order for sex.
15. Apply formula to sex.
16. Add heatmap element.
17. Assign X and Y to heatmap.
18. Add legend to heatmap.

Example 1245

Summary: Creates a heatmap in Graph Builder to visualize data relationships between Type and Country, with customizable legend and fill pattern.

Code:

Open("data_table.jmp");
Graph Builder(
    Show Control Panel( 0 ),
    Variables( X( :Type ), Y( :Country ) ),
    Elements( Heatmap( X, Y, Legend( 9 ) ) ),
    SendToReport( Dispatch( {}, "Graph Builder", FrameBox, {DispatchSeg( RectSeg( 1 ), {Fill Pattern( "hatch heavy" )} )} ) )
);

Code Explanation:

1. Open data table;
2. Launch Graph Builder.
3. Hide control panel.
4. Set X variable to Type.
5. Set Y variable to Country.
6. Add heatmap element.
7. Configure legend.
8. Send report dispatch.
9. Access frame box.
10. Modify fill pattern.

Example 1246

Summary: Creates a heatmap visualization with nested factors using Graph Builder, displaying standard deviation charts for analysis.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 527, 410 ),
    Show Control Panel( 0 ),
    Variables( X( :age ), Y( :sex ), Color( :height ) ),
    Elements( Heatmap( X, Y, Legend( 2 ), Label( "Label by Value" ) ) )
);

Code Explanation:

1. Open data table;
2. Launch Graph Builder.
3. Set window size.
4. Hide control panel.
5. Define X variable: age.
6. Define Y variable: sex.
7. Define color variable: height.
8. Add heatmap element.
9. Enable legend.
10. Label by value.

Example 1247

Summary: Creates a heatmap in Graph Builder to visualize the relationship between age and height, with interactive features for labeling values.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 528, 450 ),
    Show Control Panel( 0 ),
    Variables( X( :age ), Y( :height ) ),
    Elements( Heatmap( X, Y, Legend( 6 ), Label( "Label by Value" ) ) )
);

Code Explanation:

1. Open data table;
2. Launch Graph Builder.
3. Set window size.
4. Hide control panel.
5. Define X variable.
6. Define Y variable.
7. Add heatmap element.
8. Set legend position.
9. Enable value labeling.
10. Display graph.

Example 1248

Summary: Creates a heatmap to visualize relationships between Year, Protection, and nested factors Doors and Size in a data table.

Code:

dt = Open("data_table.jmp");
dt << Graph Builder(
    Size( 1193, 670 ),
    Show Control Panel( 0 ),
    Variables( X( :Year ), Y( :Protection ), Group X( :Doors ), Group Y( :Size ), Size( :Wt ) ),
    Elements( Heatmap( X, Y, Legend( 4 ) ) ), 
);

Code Explanation:

1. Open data table;
2. Launch Graph Builder.
3. Set window size.
4. Hide control panel.
5. Define X variable: Year.
6. Define Y variable: Protection.
7. Define Group X variable: Doors.
8. Define Group Y variable: Size.
9. Define Size variable: Wt.
10. Add Heatmap element.

Example 1249

Summary: Creates two heatmaps with nested factors using Graph Builder, showcasing variability charts and standard deviation charts.

Code:

dt = Open("data_table.jmp");
dt << Graph Builder(
    Size( 1193, 670 ),
    Show Control Panel( 0 ),
    Variables( X( :Year ), Y( :Protection ), Group X( :Doors ), Group Y( :Size ), Size( :Wt ) ),
    Elements( Heatmap( X, Y, Legend( 4 ) ) ), 
);
dt2 = Open("data_table.jmp");
dt2 << Graph Builder(
    Size( 534, 492 ),
    Show Control Panel( 0 ),
    Continuous Color Theme( "Cividis" ),
    Variables( X( :height ), Y( :weight ), Group X( :sex ), Size( :age ) ),
    Elements( Heatmap( X, Y, Legend( 10 ) ) )
);

Code Explanation:

1. Open data table;
2. Create Graph Builder window.
3. Set window size to 1193x670.
4. Hide control panel.
5. Define X, Y, Group X, Group Y, and Size variables.
6. Add Heatmap element with legend.
7. Open data table;
8. Create another Graph Builder window.
9. Set window size to 534x492.
10. Hide control panel and apply Cividis color theme.

Example 1250

Summary: Creates two heatmaps with nested factors using Graph Builder, displaying standard deviation charts and configuring legend positions.

Code:

dt = Open("data_table.jmp");
dt << Graph Builder(
    Lock Scales( 1 ),
    Variables( X( :weight ), Y( :height ), Color( :weight ) ),
    Elements( Heatmap( X, Y, Legend( 6 ), Bin Shape( "Hexagonal" ), Hex Bin Radius( 40 ), Label( "Label by Value" ) ) )
);
dt << Graph Builder(
    Size( 534, 456 ),
    Show Control Panel( 0 ),
    Variables( X( :height ), Y( :weight ), Color( :sex ), Size( :age ) ),
    Elements( Heatmap( X, Y, Legend( 4 ), Bin Shape( "Hexagonal" ), Cell Outline( 1 ) ) ),
    SendToReport( Dispatch( {}, "400", LegendBox, {Legend Position( {4, [1, 2, 0]} )} ) )
);

Code Explanation:

1. Open data table;
2. Create first Graph Builder window.
3. Lock scales for consistency.
4. Set X to weight, Y to height, color to weight.
5. Add heatmap element with hexagonal bins.
6. Set bin radius to 40.
7. Label cells by value.
8. Create second Graph Builder window.
9. Set size to 534x456 pixels.
10. Hide control panel.
11. Set X to height, Y to weight, color to sex, size to age.
12. Add heatmap element with hexagonal bins.
13. Add cell outlines.
14. Adjust legend position.

Example 1251

Summary: Creates a heatmap with nested factors using Graph Builder, displaying standard deviation charts and enabling cell outlines.

Code:

dt2 = Open("data_table.jmp");
dt2 << Graph Builder(
    Size( 534, 492 ),
    Show Control Panel( 0 ),
    Continuous Color Theme( "Yellow to Blue" ),
    Variables( X( :Table ), Y( :Price ), Group X( :Report ), Color( :Carat Weight ), Size( :Depth ) ),
    Elements( Heatmap( X, Y, Legend( 10 ), Bin Shape( "Hexagonal" ), Label( "Label by Value" ), Cell Outline( 1 ) ) )
);

Code Explanation:

1. Open data table;
2. Create Graph Builder window.
3. Set window size.
4. Hide control panel.
5. Apply color theme.
6. Define X variable.
7. Define Y variable.
8. Define group X variable.
9. Define color variable.
10. Define size variable.
11. Add heatmap element.
12. Set legend.
13. Use hexagonal bins.
14. Label by value.
15. Enable cell outlines.

Example 1252

Summary: Creates multiple heatmaps with nested factors using Graph Builder, configuring various settings such as bin shapes, legend positions, and color schemes.

Code:

dt = Open("data_table.jmp");
dt << Graph Builder(
    Lock Scales( 1 ),
    Variables( X( :weight ), Y( :height ), Color( :weight ) ),
    Elements( Heatmap( X, Y, Legend( 6 ), Bin Shape( "Hexagonal" ), Hex Bin Radius( 40 ), Label( "Label by Value" ) ) )
);
dt << Graph Builder(
    Size( 534, 456 ),
    Show Control Panel( 0 ),
    Variables( X( :height ), Y( :weight ), Color( :sex ), Size( :age ) ),
    Elements( Heatmap( X, Y, Legend( 4 ), Bin Shape( "Hexagonal" ), Cell Outline( 1 ) ) ),
    SendToReport( Dispatch( {}, "400", LegendBox, {Legend Position( {4, [1, 2, 0]} )} ) )
);
dt2 = Open("data_table.jmp");
dt2 << Graph Builder(
    Size( 534, 492 ),
    Show Control Panel( 0 ),
    Continuous Color Theme( "Yellow to Blue" ),
    Variables( X( :Table ), Y( :Price ), Group X( :Report ), Color( :Carat Weight ), Size( :Depth ) ),
    Elements( Heatmap( X, Y, Legend( 10 ), Bin Shape( "Hexagonal" ), Label( "Label by Value" ), Cell Outline( 1 ) ) )
);
dt3 = Open("data_table.jmp");
dt3 << Graph Builder(
    Size( 503, 499 ),
    Show Control Panel( 0 ),
    Variables( X( :X_Die ), Y( :Y_Die ), Color( :Defects ) ),
    Elements( Heatmap( X, Y, Legend( 4 ), Bin Shape( "Hexagonal" ), Hex Bin Radius( 8.79 ) ) ),
    SendToReport(
        Dispatch( {}, "400", ScaleBox,
            {Legend Model( 4, Properties( 0, {gradient( {Width( 12 ), Scale Type( "Log" )} )}, Item ID( "Defects", 1 ) ) )}
        )
    )
);
dt4 = Open("data_table.jmp");
dt4 << Graph Builder(
    Size( 613, 617 ),
    Show Control Panel( 0 ),
    Variables( X( :BMI ), Y( :Total Cholesterol ), Y( :LTG ), Size( :Age ) ),
    Elements( Position( 1, 1 ), Heatmap( X, Y, Legend( 5 ), Bin Shape( "Hexagonal" ), Hex Bin Radius( 12 ) ) ),
    Elements( Position( 1, 2 ), Heatmap( X, Y, Legend( 9 ), Bin Shape( "Hexagonal" ), Hex Bin Radius( 12 ) ) )
);

Code Explanation:

1. Open data table;
2. Create heatmap for weight vs height.
3. Set color by weight.
4. Use hexagonal bins.
5. Set hex bin radius to 40.
6. Label by value.
7. Open data table;
8. Create heatmap for height vs weight.
9. Set color by sex.
10. Set size by age.
11. Use hexagonal bins.
12. Hide control panel.
13. Set legend position.
14. Open data table;
15. Create heatmap for X_Die vs Y_Die.
16. Set color by Defects.
17. Use hexagonal bins.
18. Set hex bin radius to 8.79.
19. Set gradient scale type to log.
20. Open data table;
21. Create heatmap for BMI vs Total Cholesterol.
22. Use hexagonal bins.
23. Set hex bin radius to 12.
24. Create heatmap for BMI vs LTG.
25. Use hexagonal bins.
26. Set hex bin radius to 12.

Example 1253

Summary: Creates a heatmap with hexagonal bin shape to visualize relationships between X, Y, and Z variables in a data table.

Code:

Open("data_table.jmp");
gb = Graph Builder(
    Show Control Panel( 0 ),
    Variables( X( :X ), Y( :Y ), Color( :Z ) ),
    Elements( Heatmap( X, Y, Bin Shape( "Hexagonal" ) ) )
);
frame = (gb << Report)[FrameBox( 1 )];
seg = frame << Find Seg( Hex Seg( 1 ) );

Code Explanation:

1. Open data table.
2. Create Graph Builder object.
3. Hide control panel.
4. Set X, Y, Color variables.
5. Add heatmap element.
6. Specify hexagonal bin shape.
7. Retrieve first frame box.
8. Find segment object.
9. Select hex segment.

Example 1254

Summary: Creates a heatmap with hexagonal bin shape to visualize data relationships, utilizing Graph Builder and setting color theme to Viridis.

Code:

Open("data_table.jmp");
gb = Graph Builder(
    Show Control Panel( 0 ),
    Variables( X( :X ), Y( :Y ), Color( :Z ) ),
    Elements( Heatmap( X, Y, Bin Shape( "Hexagonal" ) ) )
);
frame = (gb << Report)[FrameBox( 1 )];
seg = frame << Find Seg( Hex Seg( 1 ) );
seg << Set Gradient( Color Theme( "Viridis" ) );

Code Explanation:

1. Open data table;
2. Create Graph Builder object.
3. Hide control panel.
4. Set X, Y, and Color variables.
5. Add Heatmap element.
6. Use hexagonal bin shape.
7. Retrieve FrameBox from report.
8. Find first hex segment.
9. Apply Viridis color theme.
10. Set gradient for segment.

Example 1255

Summary: Creates a heatmap to visualize the relationship between Carat Weight and Price, utilizing Graph Builder with log scaling on the Y-axis.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 534, 456 ),
    Show Control Panel( 0 ),
    Variables( X( :Carat Weight ), Y( :Price ) ),
    Elements( Heatmap( X, Y, Legend( 6 ), Bin Shape( "Hexagonal" ) ) ),
    SendToReport(
        Dispatch( {}, "Price", ScaleBox,
            {Scale( "Log" ), Format( "Best", 12 ), Min( 774.263682681127 ), Max( 11324.0036323556 ), Inc( 1 ), Minor Ticks( 1 )}
        ),
        Dispatch( {}, "Graph Builder", FrameBox,
            Add Pin Annotation(
                Seg( HexSeg( 1 ) ),
                Index( 61 ),
                Index Row( 77 ),
                UniqueID( -313704211 ),
                FoundPt( {393, 454} ),
                Origin( {0.398808510638298, 1175.42370358151} ),
                Offset( {55, -30} ),
                Tag Line( 1 )
            )
        )
    )
);

Code Explanation:

1. Open data table;
2. Create Graph Builder window.
3. Set window size to 534x456.
4. Hide control panel.
5. Set X variable to Carat Weight.
6. Set Y variable to Price.
7. Add Heatmap element.
8. Use hexagonal bin shape.
9. Apply log scale to Y-axis.
10. Add pin annotation at specified coordinates.

Example 1256

Summary: Creates a heatmap to visualize the relationship between SO2 and CO variables in a data table, utilizing Graph Builder with hexagonal bins.

Code:

dt = Open("data_table.jmp");
dt << Graph Builder(
    Size( 528, 456 ),
    Show Control Panel( 0 ),
    Variables( X( :SO2 ), Y( :CO ) ),
    Elements( Heatmap( X, Y, Legend( 4 ), Bin Shape( "Hexagonal" ) ) )
);

Code Explanation:

1. Open data table.
2. Create graph builder object.
3. Set graph size.
4. Hide control panel.
5. Define X variable.
6. Define Y variable.
7. Add heatmap element.
8. Set legend position.
9. Use hexagonal bins.

Example 1257

Summary: Creates two heatmaps with nested factors using Graph Builder, displaying standard deviation charts and configuring legend positions.

Code:

dt = Open("data_table.jmp");
dt << Graph Builder(
    Size( 528, 456 ),
    Show Control Panel( 0 ),
    Variables( X( :SO2 ), Y( :CO ) ),
    Elements( Heatmap( X, Y, Legend( 4 ), Bin Shape( "Hexagonal" ) ) )
);
dt << Graph Builder(
    Size( 528, 456 ),
    Show Control Panel( 0 ),
    Variables( X( :SO2 ), Y( :CO ) ),
    Elements( Heatmap( X, Y, Legend( 4 ) ) )
);

Code Explanation:

1. Open data table;
2. Create first Graph Builder window.
3. Set size to 528x456.
4. Hide control panel.
5. Set X variable to SO2.
6. Set Y variable to CO.
7. Add hexagonal heatmap element.
8. Configure legend to position 4.
9. Create second Graph Builder window.
10. Repeat steps 3-8 without hexagonal bin shape.

Example 1258

Summary: Creates a heatmap with nested factors using Graph Builder, displaying standard deviation charts and pin annotations.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 534, 456 ),
    Show Control Panel( 0 ),
    Variables( X( :Turning Circle ), Y( :Weight ) ),
    Elements( Heatmap( X, Y, Legend( 4 ), Bin Shape( "Hexagonal" ) ), Points( X, Y, Legend( 5 ) ) ),
    SendToReport(
        Dispatch( {}, "Graph Builder", FrameBox,
            {Set Graphlet(
                Picture(
                    Try(
                        loader = If( Class Exists( "hllLoader" ),
                            New Object( "hllLoader" ),
                            Include( "$BUILTIN_SCRIPTS/hllib.jsl" )
                        );
                        loader:setDebug( 0 );
                        hlp = loader:lazyLoad( "hllPresets" );
                        hlp:launchHeatmap();
                    )
                ),
                Title( "Heatmap Preset" ),
                Reapply( 1 )
            ), Add Pin Annotation(
                Seg( HexSeg( 1 ) ),
                Index( 5 ),
                Index Row( 61 ),
                UniqueID( 1954215765 ),
                FoundPt( {338, 144} ),
                Origin( {40.3302785265049, 3803.57142857143} ),
                Offset( {-30, 160} ),
                Tag Line( 1 )
            )}
        )
    )
);

Code Explanation:

1. Open data table;
2. Launch Graph Builder.
3. Set window size.
4. Hide control panel.
5. Assign X and Y variables.
6. Add heatmap element.
7. Add points element.
8. Send report to Graph Builder.
9. Set graphlet picture.
10. Add pin annotation.

Example 1259

Summary: Creates a heatmap to visualize the relationship between petal width and length, utilizing Graph Builder's Heatmap element.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 522, 456 ),
    Show Control Panel( 0 ),
    Variables( X( :Petal width ), Y( :Petal length ) ),
    Elements( Heatmap( X, Y, Legend( 13 ) ) ),
    SendToReport(
        Dispatch( {}, "Graph Builder", FrameBox,
            Add Pin Annotation(
                Seg( RectSeg( 1 ) ),
                Index( 4 ),
                Index Row( 134 ),
                UniqueID( -890847196 ),
                FoundPt( {550, 218} ),
                Origin( {1.38842975206612, 5.54591836734694} ),
                Tag Line( 1 )
            )
        )
    )
);

Code Explanation:

1. Open data table;
2. Create Graph Builder.
3. Set size 522x456.
4. Hide control panel.
5. Set X variable: Petal width.
6. Set Y variable: Petal length.
7. Add heatmap element.
8. Add legend to heatmap.
9. Send report to Graph Builder.
10. Add pin annotation to frame.

Example 1260

Summary: Creates a heatmap to visualize nested factors using Graph Builder, with standard deviation charts displayed for each group.

Code:

Open("data_table.jmp");
gb = Graph Builder(
    Size( 469, 314 ),
    Show Control Panel( 0 ),
    Variables( X( :age ), Y( :sex ), Color( :height, Summary Statistic( "Std Dev" ) ) ),
    Elements( Heatmap( X, Y, Legend( 2 ) ) ),
    SendToReport(
        Dispatch( {}, "400", ScaleBox,
            {Legend Model(
                2,
                Properties(
                    0,
                    {gradient(
                        {Color Theme(
                            {"Blue to Gray to Red Copy", 4099, {{42, 63, 255}, {192, 192, 192}, {252, 11, 11}, Missing( {106, 106, 106} )}}
                        ), Width( 12 )}
                    )},
                    Item ID( "height", 1 )
                )
            )}
        )
    )
);
gb << save journal( "$temp\JMP19448.jrn" );

Code Explanation:

1. Open data table;
2. Create Graph Builder object.
3. Set graph size to 469x314.
4. Hide control panel.
5. Define X, Y, and Color variables.
6. Add Heatmap element.
7. Configure heatmap legend.
8. Set color theme for gradient.
9. Save report to temporary file.

Example 1261

Summary: Creates a heatmap with nested factors, utilizing Graph Builder to display standard deviation charts and customize legend gradients.

Code:

dt = Open("data_table.jmp");
gb = Graph Builder(
    Size( 469, 314 ),
    Show Control Panel( 0 ),
    Variables( X( :age ), Y( :sex ), Color( :height, Summary Statistic( "Std Dev" ) ) ),
    Elements( Heatmap( X, Y, Legend( 2 ) ) ),
    SendToReport(
        Dispatch( {}, "400", ScaleBox,
            {Legend Model(
                2,
                Properties(
                    0,
                    {gradient(
                        {Color Theme(
                            {"Blue to Gray to Red Copy", 4099, {{42, 63, 255}, {192, 192, 192}, {252, 11, 11}, Missing( {106, 106, 106} )}}
                        ), Width( 12 )}
                    )},
                    Item ID( "height", 1 )
                )
            )}
        )
    )
);
gb << save journal( "$temp\JMP19448.jrn" );
Open( "$temp\JMP19448.jrn" );

Code Explanation:

1. Open data table.
2. Create Graph Builder object.
3. Set graph size.
4. Hide control panel.
5. Define X, Y, and color variables.
6. Add heatmap element.
7. Customize legend gradient.
8. Save graph as journal.
9. Open saved journal.

Example 1262

Summary: Creates a heatmap with nested factors using Graph Builder, displaying standard deviation charts and labeling by value.

Code:

Open("data_table.jmp");
obj = Graph Builder(
    Size( 467, 369 ),
    Show Control Panel( 0 ),
    Variables( X( :sex ), Y( :height ), Color( :age ) ),
    Elements( Heatmap( X, Y, Legend( 4 ), Label( "Label by Value" ), Max Label
Size( 4.037 ) ) ),
    SendToReport(
        Dispatch( {}, "Graph Builder", OutlineBox, {Set Title( "Graph Builder: Should behave like GB Bar chart with Color role" )} )
    )
);
obj << save journal( "$temp\S1581035.jrn" );
obj << close window;

Code Explanation:

1. Open data table;
2. Create Graph Builder object.
3. Set graph size.
4. Hide control panel.
5. Assign variables: X, Y, Color.
6. Add heatmap element.
7. Configure legend position.
8. Enable label by value.
9. Set max label size.
10. Save report as journal.
11. Close graph window.

Example 1263

Summary: Creates a heatmap chart with nested factors using Graph Builder, displaying standard deviation charts and labeling by value.

Code:

Open("data_table.jmp");
obj = Graph Builder(
    Size( 467, 369 ),
    Show Control Panel( 0 ),
    Variables( X( :sex ), Y( :height ), Color( :age ) ),
    Elements( Heatmap( X, Y, Legend( 4 ), Label( "Label by Value" ), Max Label
Size( 4.037 ) ) ),
    SendToReport(
        Dispatch( {}, "Graph Builder", OutlineBox, {Set Title( "Graph Builder: Should behave like GB Bar chart with Color role" )} )
    )
);
obj << save journal( "$temp\S1581035.jrn" );
obj << close window;
Open( "$temp\S1581035.jrn" );

Code Explanation:

1. Open data table;
2. Create Graph Builder object.
3. Set size to 467x369.
4. Hide control panel.
5. Define X, Y, and Color variables.
6. Add Heatmap element.
7. Set legend position.
8. Label by value.
9. Set max label size.
10. Save report as S1581035.jrn.
11. Close Graph Builder window.
12. Open saved journal.

Example 1264

Summary: Creates a heatmap to visualize high values over time, utilizing Graph Builder and configuring date scale properties.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 525, 400 ),
    Show Control Panel( 0 ),
    Variables( X( :Date ), Y( :High ) ),
    Elements( Heatmap( X, Y, Legend( 7 ), Label( "Label by Percent of Total Values" ), Label Format( "Percent", 10, 8 ) ) ),
    SendToReport(
        Dispatch( {}, "Date", ScaleBox, {Min( 3055881600 ), Max( 3066249600 ), Interval( "Week" ), Inc( 1 ), Minor Ticks( 0 )} ),
        Dispatch( {}, "400", ScaleBox, {Legend Model( 7 )} )
    )
);

Code Explanation:

1. Open data table;
2. Create Graph Builder object.
3. Set graph size.
4. Hide control panel.
5. Assign X and Y variables.
6. Add heatmap element.
7. Configure legend and labels.
8. Set label format to percent.
9. Adjust date scale properties.
10. Configure legend model.

Example 1265

Summary: Creates a heatmap chart with nested factors using Graph Builder, displaying standard deviation charts and labeling by percent of total values.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 486, 447 ),
    Show Control Panel( 0 ),
    Variables( X( :sex ), Y( :height ), Color( :height, Summary Statistic( "Std Dev" ) ) ),
    Elements( Heatmap( X, Y, Legend( 2 ), Label( "Label by Percent of Total Values" ) ) )
);

Code Explanation:

1. Open data table.
2. Create Graph Builder object.
3. Set graph size.
4. Hide control panel.
5. Define X variable.
6. Define Y variable.
7. Define color variable.
8. Add heatmap element.
9. Set legend position.
10. Label by percent of total values.

Example 1266

Summary: Creates a heatmap to visualize the relationship between sex, height, and age in a dataset, using Graph Builder with nested factors.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 698, 473 ),
    Show Control Panel( 0 ),
    Variables( X( :sex ), Y( :height ), Group Y( :age ), Color( :height, Summary Statistic( "Sum" ) ) ),
    Elements( Heatmap( X, Color( 0 ), Legend( 8 ), Label( "Label by Percent of Total Values" ) ) )
);

Code Explanation:

1. Open data table;
2. Launch Graph Builder.
3. Set window size.
4. Hide control panel.
5. Assign variables: X(sex), Y(height).
6. Group by age.
7. Color by height sum.
8. Add heatmap element.
9. Color based on summary statistic.
10. Label by percent of total values.

Example 1267

Summary: Creates a heatmap to visualize the relationship between age and sex, utilizing Graph Builder with nested factors.

Code:

dt = Open("data_table.jmp");
dt << select where( :age == 12 & :sex == "F" );
dt << exclude;
Graph Builder(
    Size( 613, 410 ),
    Show Control Panel( 0 ),
    Variables( X( :age ), Y( :sex ) ),
    Elements( Heatmap( X, Y, Legend( 5 ), Label( "Label by Percent of Total Values" ) ) )
);

Code Explanation:

1. Open table.
2. Select specific rows.
3. Exclude selected rows.
4. Create Graph Builder.
5. Set size.
6. Hide control panel.
7. Define X and Y variables.
8. Add Heatmap element.
9. Configure legend.
10. Label by percent of total values.

Example 1268

Summary: Creates a heatmap visualization in Graph Builder to display the relationship between age, height, and sex.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 270, 281 ),
    Show Control Panel( 0 ),
    Variables( X( :age ), Y( :height ), Color( :sex ) ),
    Elements( Heatmap( X, Y, Legend( 7 ), Label( "Label by Percent of Total Values" ), Label Format( "Fixed Dec", 10, 5 ) ) )
);

Code Explanation:

1. Open data table;
2. Create Graph Builder window.
3. Set window size to 270x281.
4. Hide control panel.
5. Assign age to X-axis.
6. Assign height to Y-axis.
7. Assign sex to color.
8. Add heatmap element.
9. Enable legend.
10. Label by percent of total values.

Example 1269

Summary: Creates two Graph Builder windows with nested factors, displaying heatmaps and tabulated data for 'Label by Value' and 'Label by % of Total Values'.

Code:

Open("data_table.jmp");
Graph Builder( Show Control Panel( 0 ), Variables( X( :age ), Y( :sex ) ), Elements( Heatmap( X, Y, Legend( 2 ) ) ) );
New Window( "Label by Value",
    Graph Builder(
        Show Control Panel( 0 ),
        Variables( X( :age ), Y( :sex ) ),
        Elements( Heatmap( X, Y, Legend( 2 ), Label( "Label by Value" ), Max Label Size( 6.606 ) ) )
    ),
    Tabulate( Show Control Panel( 0 ), Add Table( Column Table( Grouping Columns( :age, :sex ) ) ) )
);
New Window( "Label by % of Total Values",
    Graph Builder(
        Show Control Panel( 0 ),
        Variables( X( :age ), Y( :sex ) ),
        Elements( Heatmap( X, Y, Legend( 2 ), Label( "Label by Percent of Total Values" ) ) )
    ),
    Tabulate(
        Show Control Panel( 0 ),
        Set Format( Uniform Format( 10, 2, Percent ) ),
        Add Table( Column Table( Grouping Columns( :age, :sex ), Statistics( Name( "% of Total" ) ) ) )
    )
);

Code Explanation:

1. Open data table.
2. Create Graph Builder window.
3. Set X to age, Y to sex.
4. Add heatmap element.
5. Hide control panel.
6. Create new window "Label by Value".
7. Create Graph Builder inside new window.
8. Set X to age, Y to sex.
9. Add labeled heatmap element.
10. Create Tabulate for value labels.
11. Create new window "Label by % of Total Values".
12. Create Graph Builder inside new window.
13. Set X to age, Y to sex.
14. Add percentage-labeled heatmap element.
15. Create Tabulate for percentage labels.

Example 1270

Summary: Creates three heatmaps with label options, displaying nested factors and standard deviation charts using Graph Builder and Tabulate.

Code:

Open("data_table.jmp");
Graph Builder( Show Control Panel( 0 ), Variables( X( :age ), Y( :sex ) ), Elements( Heatmap( X, Y, Legend( 2 ) ) ) );
New Window( "Label by Value",
    Graph Builder(
        Show Control Panel( 0 ),
        Variables( X( :age ), Y( :sex ) ),
        Elements( Heatmap( X, Y, Legend( 2 ), Label( "Label by Value" ), Max Label Size( 6.606 ) ) )
    ),
    Tabulate( Show Control Panel( 0 ), Add Table( Column Table( Grouping Columns( :age, :sex ) ) ) )
);
New Window( "Label by % of Total Values",
    Graph Builder(
        Show Control Panel( 0 ),
        Variables( X( :age ), Y( :sex ) ),
        Elements( Heatmap( X, Y, Legend( 2 ), Label( "Label by Percent of Total Values" ) ) )
    ),
    Tabulate(
        Show Control Panel( 0 ),
        Set Format( Uniform Format( 10, 2, Percent ) ),
        Add Table( Column Table( Grouping Columns( :age, :sex ), Statistics( Name( "% of Total" ) ) ) )
    )
);
Graph Builder(
    Show Control Panel( 0 ),
    Variables( X( :age ), Y( :sex ) ),
    Elements( Heatmap( X, Y, Legend( 2 ), Label( "Label by Row" ) ) )
);

Code Explanation:

1. Open data table.
2. Create initial heatmap graph.
3. Create new window for label by value.
4. Display heatmap with labels.
5. Add tabulate for label by value.
6. Create new window for label by percent.
7. Display heatmap with percent labels.
8. Add tabulate for percent labels.
9. Create final heatmap with row labels.

Example 1271

Summary: Creates a heatmap to visualize the relationship between age, height, and sex in a dataset, utilizing Graph Builder's Variables and Elements features.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 195, 206 ),
    Show Control Panel( 0 ),
    Variables( X( :age ), Y( :height ), Color( :sex ) ),
    Elements( Heatmap( X, Y, Legend( 7 ), Label( "Label by Percent of Total Values" ), Label Format( "Fixed Dec", 10, 5 ) ) )
);

Code Explanation:

1. Open data table.
2. Create Graph Builder window.
3. Set graph size.
4. Hide control panel.
5. Assign X variable.
6. Assign Y variable.
7. Assign color variable.
8. Add heatmap element.
9. Set legend position.
10. Label by percent of total values.

Example 1272

Summary: Creates a heatmap visualization with row labels, filtered by sex, and sends it to a report with a customized title.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 534, 456 ),
    Show Control Panel( 0 ),
    Continuous Color Theme( "Universal Bad to Good" ),
    Variables( X( :height ), Y( :weight ) ),
    Elements( Heatmap( X, Y, Legend( 5 ), Label( "Label by Row" ) ) ),
    Local Data Filter( Add Filter( columns( :sex ), Where( :sex == "F" ) ) ),
    SendToReport( Dispatch( {}, "400", LegendBox, {Set Title( "Count" )} ) )
);

Code Explanation:

1. Open data table;
2. Launch Graph Builder.
3. Set window size.
4. Hide control panel.
5. Choose color theme.
6. Define X and Y variables.
7. Add heatmap element.
8. Enable row labels.
9. Add local data filter.
10. Customize legend title.

Example 1273

Summary: Creates a graph builder window with a heatmap and line element to visualize the relationship between age and height in a data table.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 314, 262 ),
    Show Control Panel( 0 ),
    Variables( X( :age ), Y( :height ) ),
    Elements( Heatmap( X, Y, Legend( 3 ) ), Line( X, Y, Legend( 5 ), Summary Statistic( "Min" ) ) )
);

Code Explanation:

1. Open data table.
2. Create Graph Builder window.
3. Set window size.
4. Hide control panel.
5. Assign X variable.
6. Assign Y variable.
7. Add heatmap element.
8. Add legend to heatmap.
9. Add line element.
10. Set line summary statistic.

Example 1274

Summary: Creates a heatmap to visualize the relationship between Color and Clarity, with Carat Weight used as a color variable, utilizing Graph Builder in JMP.

Code:

Open("data_table.jmp");
Graph Builder(
    Show Control Panel( 0 ),
    Variables( X( :Color ), Y( :Clarity ), Color( :Carat Weight, Summary Statistic( "Median Absolute Deviation" ) ) ),
    Elements( Heatmap( X, Y, Legend( 5 ) ) )
);

Code Explanation:

1. Open data table;
2. Launch Graph Builder.
3. Hide control panel.
4. Set X variable to Color.
5. Set Y variable to Clarity.
6. Set color variable to Carat Weight.
7. Use Median Absolute Deviation.
8. Add Heatmap element.
9. Configure legend at position 5.
10. Display graph.

Example 1275

Summary: Creates two Graph Builder windows to visualize data: a bar chart with nested factors and an overlay, and a heatmap with color and size variables.

Code:

dt = Open("data_table.jmp");
dt << Graph Builder(
    Size( 534, 449 ),
    Show Control Panel( 0 ),
    Variables(
        X( :Genre ),
        Y( :Audience Score ),
        Overlay(
            :World Gross,
            custom levels(
                {{., "< 0"}, {0, "0 — 200"}, {200, "200 — 400"}, {400, "400 — 600"}, {600, "600 — 800"}, {800, "800 — 1000"}, {1000,
                "1000 — 1200"}, {1200, "1200 — 1400"}, {1400, "≥ 1400"}}
            )
        )
    ),
    Elements( Bar( X, Y, Legend( 4 ) ) )
);
dt << Graph Builder(
    Size( 534, 449 ),
    Show Control Panel( 0 ),
    Variables( X( :Genre ), Y( :World Gross ), Color( :Profitability ), Size( :Audience Score ) ),
    Elements( Heatmap( X, Y, Legend( 9 ) ) )
);

Code Explanation:

1. Open data table;
2. Create Graph Builder window.
3. Set window size to 534x449.
4. Hide control panel.
5. Define X variable: Genre.
6. Define Y variable: Audience Score.
7. Define overlay variable: World Gross.
8. Customize overlay levels for World Gross.
9. Add bar element to graph.
10. Create second Graph Builder window.
11. Set window size to 534x449.
12. Hide control panel.
13. Define X variable: Genre.
14. Define Y variable: World Gross.
15. Define color variable: Profitability.
16. Define size variable: Audience Score.
17. Add heatmap element to graph.

Example 1276

Summary: Creates two Graph Builders to visualize nested factors and display standard deviation charts, utilizing custom levels and heatmaps.

Code:

dt = Open("data_table.jmp");
dt << Graph Builder(
    Size( 534, 449 ),
    Show Control Panel( 0 ),
    Variables(
        X( :Genre ),
        Y( :Audience Score ),
        Overlay(
            :World Gross,
            custom levels(
                {{., "< 0"}, {0, "0 — 200"}, {200, "200 — 400"}, {400, "400 — 600"}, {600, "600 — 800"}, {800, "800 — 1000"}, {1000,
                "1000 — 1200"}, {1200, "1200 — 1400"}, {1400, "≥ 1400"}}
            )
        )
    ),
    Elements( Bar( X, Y, Legend( 4 ) ) )
);
dt << Graph Builder(
    Size( 534, 449 ),
    Show Control Panel( 0 ),
    Variables( X( :Genre ), Y( :World Gross ), Color( :Profitability ), Size( :Audience Score ) ),
    Elements( Heatmap( X, Y, Legend( 9 ) ) )
);
dt2 = Open("data_table.jmp");
dt2 << New Column( "one", <<Set Each Value( 1 ) );
dt2:age[5 :: 20] = .;
dt2 << Graph Builder(
    Show Control Panel( 0 ),
    Variables( X( :name ), Y( :one ), Y( :one ), Color( :age ) ),
    Elements( Position( 1, 1 ), Points( X, Y, Legend( 12 ), Jitter( "None" ) ) ),
    Elements( Position( 1, 2 ), Heatmap( X, Y, Legend( 7 ) ) ),
    SendToReport( Dispatch( {}, "Graph Builder", FrameBox, {Marker Size( 20 ), Marker Drawing Mode( "Normal" )} ) )
);
dt2:age << Set Modeling Type( "Continuous" );

Code Explanation:

1. Open data table;
2. Create Graph Builder with Genre on X, Audience Score on Y.
3. Add World Gross as overlay with custom levels.
4. Display bar chart with legend.
5. Create another Graph Builder with Genre on X, World Gross on Y.
6. Use Profitability for color, Audience Score for size.
7. Display heatmap with legend.
8. Open data table;
9. Add new column "one" with value 1.
10. Set age values 5 to 20 as missing.
11. Create Graph Builder with name on X, "one" on both Ys.
12. Display points with no jitter, legend.
13. Add heatmap below points with legend.
14. Adjust marker size and drawing mode.
15. Set age modeling type to continuous.

Example 1277

Summary: Creates two Graph Builders to visualize data: a bar chart with custom levels and a heatmap, as well as a third Graph Builder for a points plot with standard deviation charts.

Code:

dt = Open("data_table.jmp");
dt << Graph Builder(
    Size( 534, 449 ),
    Show Control Panel( 0 ),
    Variables(
        X( :Genre ),
        Y( :Audience Score ),
        Overlay(
            :World Gross,
            custom levels(
                {{., "< 0"}, {0, "0 — 200"}, {200, "200 — 400"}, {400, "400 — 600"}, {600, "600 — 800"}, {800, "800 — 1000"}, {1000,
                "1000 — 1200"}, {1200, "1200 — 1400"}, {1400, "≥ 1400"}}
            )
        )
    ),
    Elements( Bar( X, Y, Legend( 4 ) ) )
);
dt << Graph Builder(
    Size( 534, 449 ),
    Show Control Panel( 0 ),
    Variables( X( :Genre ), Y( :World Gross ), Color( :Profitability ), Size( :Audience Score ) ),
    Elements( Heatmap( X, Y, Legend( 9 ) ) )
);
dt2 = Open("data_table.jmp");
dt2 << New Column( "one", <<Set Each Value( 1 ) );
dt2:age[5 :: 20] = .;
dt2 << Graph Builder(
    Show Control Panel( 0 ),
    Variables( X( :name ), Y( :one ), Y( :one ), Color( :age ) ),
    Elements( Position( 1, 1 ), Points( X, Y, Legend( 12 ), Jitter( "None" ) ) ),
    Elements( Position( 1, 2 ), Heatmap( X, Y, Legend( 7 ) ) ),
    SendToReport( Dispatch( {}, "Graph Builder", FrameBox, {Marker Size( 20 ), Marker Drawing Mode( "Normal" )} ) )
);

Code Explanation:

1. Open data table;
2. Create Graph Builder with Genre on X, Audience Score on Y.
3. Add World Gross overlay with custom levels.
4. Display bar chart with legend.
5. Create another Graph Builder with Genre on X, World Gross on Y.
6. Use Profitability for color and Audience Score for size.
7. Display heatmap with legend.
8. Open data table;
9. Add new column "one" with value 1.
10. Set age values from 5 to 20 to missing.
11. Create Graph Builder with name on X, one on Y (twice).
12. Display points with no jitter and legend.
13. Display heatmap with legend.
14. Adjust marker size and drawing mode in report.

Example 1278

Summary: Creates a heatmap to visualize the relationship between age, height, and weight in a dataset, utilizing Graph Builder with continuous color theme and standard error summary statistic.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 528, 450 ),
    Show Control Panel( 0 ),
    Continuous Color Theme( "Yellow to Red" ),
    Variables( X( :age ), Y( :height ), Color( :weight, Summary Statistic( "Std Err" ) ) ),
    Elements( Heatmap( X, Y, Legend( 9 ) ) )
);

Code Explanation:

1. Open data table;
2. Create new Graph Builder window.
3. Set window size to 528x450.
4. Hide control panel.
5. Apply continuous color theme.
6. Set X variable to age.
7. Set Y variable to height.
8. Set color variable to weight.
9. Use standard error for summary statistic.
10. Add heatmap element.

Example 1279

Summary: Creates a variability chart with nested factors using Graph Builder, featuring Heatmap, Points, and Smoother elements.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 534, 490 ),
    Show Control Panel( 0 ),
    Variables( X( :height ), Y( :weight ), Wrap( :age ), Color( :height ), Color( :weight ) ),
    Elements( Heatmap( Legend( 22 ) ), Points( X, Y, Color( 2 ), Legend( 20 ) ), Smoother( X, Y, Legend( 21 ) ) ),
    SendToReport(
        Dispatch( {"Heatmap"}, "", OutlineBox, {Close( 0 )} ),
        Dispatch( {"Points"}, "", OutlineBox, {Close( 0 )} ),
        Dispatch( {}, "400", ScaleBox,
            {Legend Model(
                22,
                Properties( 0, {gradient( {Color Theme( "White to Blue" ), Min Lightness( 0.4034 ), Max Lightness( 0.9244 )} )} )
            ), Legend Model(
                20,
                Properties( 0, {gradient( {Color Theme( "White to Purple" ), Min Lightness( 0 ), Max Lightness( 0.8151 )} )} )
            )}
        ),
        Dispatch( {}, "400", LegendBox, {Legend Position( {22, [0], 20, [3, 1], 21, [2]} )} )
    )
);

Code Explanation:

1. Open data_table data
2. Create Graph Builder window.
3. Set window size.
4. Hide control panel.
5. Define X, Y, Wrap, Color variables.
6. Add Heatmap element.
7. Add Points element.
8. Add Smoother element.
9. Close Heatmap outline.
10. Close Points outline.
11. Customize Heatmap legend.
12. Customize Points legend.
13. Arrange legend positions.

Example 1280

Summary: Creates a heatmap visualization with nested factors using Graph Builder, displaying standard deviation charts and controlling panel visibility.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 348, 352 ),
    Show Control Panel( 0 ),
    Variables( X( :sex ), Y( :height ), Group Y( :age, Levels( 3 ) ) ),
    Elements( Heatmap( X, Y, Legend( 5 ) ) )
);

Code Explanation:

1. Open data table;
2. Launch Graph Builder.
3. Set window size.
4. Hide control panel.
5. Define X variable.
6. Define Y variable.
7. Define group Y variable.
8. Set age levels to 3.
9. Add heatmap element.
10. Display legend.

Example 1281

Summary: Creates a heatmap to visualize relationships between Horsepower and Weight, with Type as a nested factor, using Graph Builder in JMP.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 483, 635 ),
    Show Control Panel( 0 ),
    Variables( X( :Horsepower ), Y( :Weight ), Page( :Type, Levels per Row( 3 ) ) ),
    Elements( Heatmap( X, Y, Legend( 22 ) ) ),
    SendToReport(
        Dispatch( {}, "400", ScaleBox,
            {Legend Model(
                22,
                Properties(
                    -1,
                    {gradient( {Color Theme( "Black Body"(1) ), Density Gradient( "Full Color" ), Width( 9 )} )},
                    Item ID( "Density", 1 )
                )
            )}
        )
    )
);

Code Explanation:

1. Open data table.
2. Create Graph Builder window.
3. Set window size.
4. Hide control panel.
5. Assign variables: X, Y, Page.
6. Add Heatmap element.
7. Configure heatmap legend.
8. Adjust gradient color theme.
9. Set density gradient type.
10. Customize legend width.

Example 1282

Summary: Creates a heatmap to visualize the relationship between sex, age, and height using Graph Builder.

Code:

Open("data_table.jmp") << Graph Builder(
    Size( 412, 320 ),
    Show Control Panel( 0 ),
    Variables( X( :sex ), Y( :age ), Color( :height, Summary Statistic( "% of Total" ) ) ),
    Elements( Heatmap( X, Y, Legend( 7 ) ) )
);

Code Explanation:

1. Open data_table data
2. Launch Graph Builder.
3. Set window size.
4. Hide control panel.
5. Assign X variable: sex.
6. Assign Y variable: age.
7. Assign Color variable: height.
8. Use "% of Total" summary statistic.
9. Add Heatmap element.
10. Configure heatmap legend.

Example 1283

Summary: Creates a heatmap visualization with nested factors, utilizing Graph Builder to display standard deviation charts and configure scale settings.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 534, 464 ),
    Show Control Panel( 0 ),
    Variables( X( :name ), Y( :height ) ),
    Elements( Heatmap( X, Y, Legend( 4 ) ) ),
    SendToReport(
        Dispatch( {}, "height", ScaleBox,
            {Scale( "Power" ), Format( "Best", 12 ), Min( -5.91169772950084 ), Max( 74.7933530144302 ), Inc( 20 ), Minor Ticks( 1 )}
        )
    )
);

Code Explanation:

1. Open data table.
2. Launch Graph Builder.
3. Set window size.
4. Hide control panel.
5. Assign variables X and Y.
6. Add heatmap element.
7. Configure scale for Y axis.
8. Apply power scale.
9. Set number format.
10. Define min and max values.

Example 1284

Summary: Creates a variability chart with nested factors using Graph Builder, displaying standard deviation charts and customizing scale settings.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 630, 393 ),
    Show Control Panel( 0 ),
    Show Legend( 1 ),
    Variables(
        X( Transform Column( "Cumulative Probability[height]", Formula( Col Rank( :height ) / (Col Number( :height ) + 1) ) ) ),
        Y( :height ),
        Y(
            Transform Column(
                "Normal Quantile[height]",
                Formula(
                    Normal Quantile( Col Rank( :height ) / (Col Number( :height ) + 1), Col Mean( :height ), Col Std Dev( :height ) )
                )
            ),
            Position( 1 )
        )
    ),
    Elements( Heatmap( X, Y( 1 ), Y( 2 ), Legend( 26 ) ) ),
    SendToReport(
        Dispatch( {}, "Cumulative Probability[height]", ScaleBox,
            {Scale( "Normal Probability" ), Format( "Best", 9 ), Min( 0.02 ), Max( 0.98 ), Inc( 1 ), Minor Ticks( 1 ),
            Label Row( Show Major Grid( 1 ) )}
        )
    )
);

Code Explanation:

1. Open data table;
2. Create Graph Builder window.
3. Set window size.
4. Hide control panel.
5. Show legend.
6. Define X variable.
7. Define first Y variable.
8. Define second Y variable.
9. Add heatmap element.
10. Customize scale settings.

Example 1285

Summary: Creates a heatmap visualization with nested factors using Graph Builder, displaying standard deviation charts.

Code:

Open("data_table.jmp");
gb = Graph Builder( Show Control Panel( 0 ), Variables( X( :X ), Y( :Y ), Color( :Z ) ), Elements( Heatmap( X, Y ) ) );
frame = (gb << Report)[FrameBox( 1 )];
seg = frame << Find Seg( Rect Seg( 1 ) );

Code Explanation:

1. Open data table;
2. Create Graph Builder object.
3. Set X, Y, and Color variables.
4. Add Heatmap element.
5. Access first FrameBox.
6. Find segment using Rect Seg.

Example 1286

Summary: Creates a heatmap visualization with nested factors using Graph Builder, setting the gradient color theme to Viridis.

Code:

Open("data_table.jmp");
gb = Graph Builder( Show Control Panel( 0 ), Variables( X( :X ), Y( :Y ), Color( :Z ) ), Elements( Heatmap( X, Y ) ) );
frame = (gb << Report)[FrameBox( 1 )];
seg = frame << Find Seg( Rect Seg( 1 ) );
seg << Set Gradient( Color Theme( "Viridis" ) );

Code Explanation:

1. Open data table.
2. Create Graph Builder object.
3. Disable control panel.
4. Set X, Y, and Color variables.
5. Add Heatmap element.
6. Access first FrameBox.
7. Find first rectangle segment.
8. Set gradient color theme.

Example 1287

Summary: Creates a heatmap visualization with nested factors using Graph Builder, displaying standard deviation charts and configuring legend properties.

Code:

Open("data_table.jmp");
Graph Builder(
    Show Control Panel( 0 ),
    Variables( X( :sex ), Y( :height ), Color( :height ) ),
    Elements( Heatmap( X, Y, Legend( 6 ) ) ),
    SendToReport(
        Dispatch( {}, "400", ScaleBox,
            {Legend Model(
                6,
                Properties( 0, {gradient( {Color Theme( "Jet"(1) ), Reverse Colors( 1 ), Reverse Labels( 1 )} )}, Item ID( "height", 1 ) )
            )}
        )
    )
);

Code Explanation:

1. Open data table;
2. Create Graph Builder object.
3. Hide control panel.
4. Set X variable to sex.
5. Set Y variable to height.
6. Set color variable to height.
7. Add heatmap element.
8. Configure legend properties.
9. Apply reverse colors setting.
10. Apply reverse labels setting.

Example 1288

Summary: Creates a heatmap to visualize relationships between Carat Weight, Price, Cut, and Depth in a data table, utilizing Graph Builder's customization options for scales.

Code:

dt = Open("data_table.jmp");
dt << Graph Builder(
    Size( 620, 514 ),
    Show Control Panel( 0 ),
    Variables( X( :Carat Weight ), Y( :Price ), Color( :Cut ), Size( :Depth ) ),
    Elements( Heatmap( X, Y, Legend( 6 ) ) ),
    SendToReport(
        Dispatch( {}, "Carat Weight", ScaleBox, {Min( 0.281891348088531 ), Max( 2.25 ), Inc( 0.5 ), Minor Ticks( 1 )} ),
        Dispatch( {}, "Price", ScaleBox, {Min( 1000 ), Max( 11000 ), Inc( 2000 ), Minor Ticks( 1 )} )
    )
);

Code Explanation:

1. Open data table.
2. Launch Graph Builder.
3. Set graph size.
4. Hide control panel.
5. Assign variables: X, Y, Color, Size.
6. Add heatmap element.
7. Customize X scale: min, max, increment, minor ticks.
8. Customize Y scale: min, max, increment, minor ticks.

Example 1289

Summary: Creates two variability charts with nested factors using Graph Builder, displaying standard deviation charts and customizing scales for X and Y axes.

Code:

dt = Open("data_table.jmp");
dt << Graph Builder(
    Size( 620, 514 ),
    Show Control Panel( 0 ),
    Variables( X( :Carat Weight ), Y( :Price ), Color( :Cut ), Size( :Depth ) ),
    Elements( Heatmap( X, Y, Legend( 6 ) ) ),
    SendToReport(
        Dispatch( {}, "Carat Weight", ScaleBox, {Min( 0.281891348088531 ), Max( 2.25 ), Inc( 0.5 ), Minor Ticks( 1 )} ),
        Dispatch( {}, "Price", ScaleBox, {Min( 1000 ), Max( 11000 ), Inc( 2000 ), Minor Ticks( 1 )} )
    )
);
dt2 = Open("data_table.jmp");
dt2 << Graph Builder(
    Size( 534, 461 ),
    Show Control Panel( 0 ),
    Variables( X( :L Leg ), Y( :R Leg ), Color( :Year ), Size( :Head IC ) ),
    Elements( Heatmap( X, Y, Legend( 4 ) ) ),
    SendToReport(
        Dispatch( {}, "L Leg", ScaleBox, {Min( 0 ), Max( 3400 ), Inc( 500 ), Minor Ticks( 0 )} ),
        Dispatch( {}, "R Leg", ScaleBox, {Min( 0 ), Max( 3000 ), Inc( 500 ), Minor Ticks( 0 )} )
    )
);

Code Explanation:

1. Open data table;
2. Create Graph Builder window.
3. Set size to 620x514.
4. Hide control panel.
5. Define variables: Carat Weight (X), Price (Y), Cut (Color), Depth (Size).
6. Add Heatmap element with legend.
7. Set X-axis scale: Min 0.281891348088531, Max 2.25, Inc 0.5, Minor Ticks 1.
8. Set Y-axis scale: Min 1000, Max 11000, Inc 2000, Minor Ticks 1.
9. Open data table;
10. Create Graph Builder window for data_table data.

Example 1290

Summary: Creates a heatmap visualization with nested factors using Graph Builder, customizing X and Y scales for Carat Weight and Price.

Code:

dt = Open("data_table.jmp");
dt << Graph Builder(
    Size( 620, 514 ),
    Show Control Panel( 0 ),
    Variables( X( :Carat Weight ), Y( :Price ), Color( :Cut ), Size( :Depth ) ),
    Elements( Heatmap( X, Y, Legend( 6 ) ) ),
    SendToReport(
        Dispatch( {}, "Carat Weight", ScaleBox, {Min( 0.281891348088531 ), Max( 2.25 ), Inc( 0.5 ), Minor Ticks( 1 )} ),
        Dispatch( {}, "Price", ScaleBox, {Min( 1000 ), Max( 11000 ), Inc( 2000 ), Minor Ticks( 1 )} )
    )
);
dt2 = Open("data_table.jmp");

Code Explanation:

1. Open data table;
2. Create Graph Builder object.
3. Set graph size.
4. Hide control panel.
5. Define X, Y, Color, Size variables.
6. Add Heatmap element.
7. Customize X scale.
8. Customize Y scale.
9. Open data table;

Example 1291

Summary: Creates a heatmap to visualize the relationship between Cut and Color, with Carat Weight as the color variable, using Graph Builder.

Code:

Open("data_table.jmp");
Graph Builder(
    Show Control Panel( 0 ),
    Variables( X( :Cut, Size By( "Count" ) ), Y( :Color, Size By( "Count" ) ), Color( :Carat Weight ) ),
    Elements( Heatmap( X, Y, Legend( 6 ) ) )
);

Code Explanation:

1. Open data table;
2. Launch Graph Builder.
3. Hide control panel.
4. Set X variable to Cut.
5. Size X by Count.
6. Set Y variable to Color.
7. Size Y by Count.
8. Set Color variable to Carat Weight.
9. Add Heatmap element.
10. Display legend with 6 categories.

Example 1292

Summary: Creates a heatmap to visualize relationships between age, height, and weight using Graph Builder.

Code:

Open("data_table.jmp");
Graph Builder(
    Show Control Panel( 0 ),
    Variables( X( :age ), Y( :height ), Size( :weight, Summary Statistic( "% of Total" ) ) ),
    Elements( Heatmap( X, Y, Legend( 8 ) ) )
);

Code Explanation:

1. Open data table.
2. Create Graph Builder object.
3. Hide control panel.
4. Set X variable to age.
5. Set Y variable to height.
6. Set size variable to weight.
7. Use percentage of total for summary.
8. Add heatmap element.
9. Display legend with 8 entries.

Example 1293

Summary: Creates two Graph Builder windows to visualize relationships between Turning Circle, Horsepower, and Gas Tank Size in a data table, with interactive features for adjusting legend positions.

Code:

dt = Open("data_table.jmp");
Graph Builder(
    Show Control Panel( 0 ),
    Variables( X( :Turning Circle ), Y( :Horsepower ), Size( :Gas Tank Size ) ),
    Elements( Heatmap( X, Y, Legend( 7 ) ) ),
    SendToReport( Dispatch( {}, "400", LegendBox, {Legend Position( {7, [1, 0]} )} ) )
);
Graph Builder(
    Size( 534, 456 ),
    Show Control Panel( 0 ),
    Variables( X( :Turning Circle ), Y( :Displacement ), Y( :Horsepower ), Size( :Gas Tank Size ) ),
    Elements( Position( 1, 1 ), Heatmap( X, Y, Legend( 9 ) ) ),
    Elements( Position( 1, 2 ), Heatmap( X, Y, Legend( 10 ) ) )
);

Code Explanation:

1. Open data table.
2. Create first Graph Builder window.
3. Hide control panel.
4. Set X, Y, and Size variables.
5. Add heatmap element.
6. Adjust legend position.
7. Create second Graph Builder window.
8. Set window size.
9. Hide control panel.
10. Set X, Y, and Size variables.

Example 1294

Summary: Creates a heatmap with nested factors using Graph Builder, displaying standard deviation charts and customizing legend properties.

Code:

dt = Open("data_table.jmp");
Graph Builder(
    Size( 469, 314 ),
    Show Control Panel( 0 ),
    Variables( X( :age ), Y( :sex ), Color( :height, Summary Statistic( "Std Dev" ) ) ),
    Elements( Heatmap( X, Y, Legend( 2 ) ) ),
    SendToReport(
        Dispatch( {}, "400", ScaleBox,
            {Legend Model(
                2,
                Properties(
                    0,
                    {gradient(
                        {Color Theme(
                            {"Blue to Gray to Red Copy", 4099, {{42, 63, 255}, {192, 192, 192}, {252, 11, 11}, Missing( {106, 106, 106} )}}
                        ), Width( 12 )}
                    )},
                    Item ID( "height", 1 )
                )
            )}
        )
    )
);

Code Explanation:

1. Open data table.
2. Launch Graph Builder.
3. Set graph size.
4. Hide control panel.
5. Assign variables: X=age, Y=sex, Color=height.
6. Use summary statistic for color.
7. Add heatmap element.
8. Customize legend properties.
9. Set color theme.
10. Configure missing value color.

Example 1295

Summary: Creates a heatmap to visualize the relationship between height and weight, with color representing the percentage of total weight.

Code:

Open("data_table.jmp") << Graph Builder(
    Size( 412, 320 ),
    Show Control Panel( 0 ),
    Variables( X( :height ), Y( :weight ), Color( :weight, Summary Statistic( "% of Total" ) ) ),
    Elements( Heatmap( X, Y, Legend( 7 ) ) )
);

Code Explanation:

1. Open data table;
2. Launch Graph Builder.
3. Set window size.
4. Hide control panel.
5. Define X variable.
6. Define Y variable.
7. Define color variable.
8. Set color summary statistic.
9. Add heatmap element.
10. Configure legend position.

Example 1296

Summary: Creates a heatmap to visualize the relationship between sex and age, with standard deviation displayed as color, using Graph Builder.

Code:

dt = Open("data_table.jmp");
dt << select where( :sex == "M" & :age == 16 );
Graph Builder(
    Size( 400, 300 ),
    Show Control Panel( 0 ),
    Variables( X( :sex ), Y( :age ), Color( :height, Summary Statistic( "Std Dev" ) ) ),
    Elements( Heatmap( X, Y, Legend( 1 ) ) )
);

Code Explanation:

1. Open data table.
2. Select male students aged 16.
3. Launch Graph Builder.
4. Set window size.
5. Hide control panel.
6. Assign variables to axes.
7. Use height for color, summarizing standard deviation.
8. Add heatmap element.
9. Display legend.

Example 1297

Summary: Creates a heatmap to visualize the relationship between sex, weight, and age, utilizing Graph Builder's Variables and Elements features.

Code:

Open("data_table.jmp") << Graph Builder(
    Size( 457, 363 ),
    Show Control Panel( 0 ),
    Show Footer( 0 ),
    Variables( X( :sex ), Y( :weight ), Color( :age, Summary Statistic( "Sum" ) ) ),
    Elements( Heatmap( X, Y, Legend( 14 ), Label( "Label by Value" ) ) )
);

Code Explanation:

1. Open data_table data
2. Create Graph Builder window.
3. Set size to 457x363.
4. Hide control panel.
5. Hide footer.
6. Assign sex to X-axis.
7. Assign weight to Y-axis.
8. Assign age to color, sum summary statistic.
9. Add heatmap element.
10. Configure legend and labels.

Example 1298

Summary: Creates a heatmap visualization with color-coded height values, filtered between 56 and 65, using Graph Builder in JMP.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 622, 540 ),
    Show Control Panel( 0 ),
    Variables( Wrap( :age ), Color( :height ) ),
    Elements( Heatmap( Legend( 5 ) ) ),
    Local Data Filter( Add Filter( columns( :height ), Where( :height >= 56 & :height <= 65 ) ) )
);

Code Explanation:

1. Open data table.
2. Create new Graph Builder window.
3. Set window size.
4. Hide control panel.
5. Assign variables: age wrapped, height colored.
6. Add heatmap element.
7. Enable legend for heatmap.
8. Add local data filter.
9. Filter height between 56 and 65.

Example 1299

Summary: Creates three Graph Builder windows to visualize and analyze data from a sample dataset, utilizing heatmaps with nested factors and custom legend colors.

Code:

Open( “$SAMPLE_DATA\data_table.jmp” );
Graph Builder(
    Size( 534, 448 ),
    Show Control Panel( 0 ),
    Variables( X( :sex ), Y( :weight ), Y( :height, Position( 1 ), Side( "Right" ) ) ),
    Elements( Heatmap( X, Y( 1 ), Legend( 5 ) ), Heatmap( X, Y( 2 ), Legend( 7 ) ) )
);
Graph Builder(
    Size( 464, 371 ),
    Show Control Panel( 0 ),
    Variables( X( :sex ), Y( :height ), Y( :weight, Position( 1 ), Side( "Right" ) ), Color( :weight ) ),
    Elements( Heatmap( X, Y( 1 ), Legend( 2 ) ), Heatmap( X, Y( 2 ), Legend( 4 ) ) )
);
Graph Builder(
    Size( 477, 379 ),
    Show Control Panel( 0 ),
    Variables( X( :age ), Y( :height ), Y( :weight, Position( 1 ), Side( "Right" ) ) ),
    Elements( Heatmap( X, Y( 1 ), Legend( 10 ) ), Heatmap( X, Y( 2 ), Legend( 11 ) ) ),
    SendToReport(
        Dispatch( {}, "400", ScaleBox,
            {Legend Model( 10, Properties( 0, {gradient( {Color Theme( "White to Blue" ), Width( 12 )} )}, Item ID( "Count", 1 ) ) ),
            Legend Model( 11, Properties( 0, {gradient( {Color Theme( "Purplish Green" ), Width( 12 )} )}, Item ID( "Count", 1 ) ) )}
        )
    )
);

Code Explanation:

1. Open data table.
2. Create first Graph Builder window.
3. Set window size.
4. Hide control panel.
5. Define X and Y variables.
6. Add heatmap elements.
7. Create second Graph Builder window.
8. Set window size.
9. Hide control panel.
10. Define X, Y, and color variables.
11. Add heatmap elements.
12. Create third Graph Builder window.
13. Set window size.
14. Hide control panel.
15. Define X and Y variables.
16. Add heatmap elements.
17. Customize legend colors.

Example 1300

Summary: Creates a variability chart with nested factors using Graph Builder, displaying standard deviation charts and adjusting legend positions.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 680, 632 ),
    Show Control Panel( 0 ),
    Include Missing Categories( 1 ),
    Variables( X( :name ), X( :age ), Y( :weight, Side( "Right" ) ), Y( :height, Position( 1 ) ), Wrap( :sex ), Overlay( :age ) ),
    Elements( Position( 1, 1 ), Heatmap( X, Y( 1 ), Legend( 36 ) ) ),
    Elements( Position( 2, 1 ), Heatmap( X, Y( 2 ), Legend( 40 ) ), ),
    SendToReport(
        Dispatch( {}, "400", LegendBox, {Legend Position( {36, [0], 40, [7], 30, [1, 2, 3], 33, [4, 5, 6], 31, [-3, -3, -3]} )} )
    )
);

Code Explanation:

1. Open data table;
2. Launch Graph Builder.
3. Set window size.
4. Hide control panel.
5. Include missing categories.
6. Define variables for axes and wrap.
7. Add first heatmap element.
8. Add second heatmap element.
9. Adjust legend positions.
10. Send report to viewer.

Example 1301

Summary: Creates a heatmap in Graph Builder to visualize the relationship between weight and height, with customized scales for both axes.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 349, 349 ),
    Show Control Panel( 0 ),
    Variables( X( :weight ), Y( :height ) ),
    Elements( Heatmap( X, Y, Legend( 6 ) ) ),
    SendToReport(
        Dispatch( {}, "weight", ScaleBox, {Min( 70 ), Max( 180 ), Inc( 50 ), Minor Ticks( 0 )} ),
        Dispatch( {}, "height", ScaleBox, {Min( 64 ), Max( 70.5 ), Inc( 2 ), Minor Ticks( 0 ), Label Row( Tick Offset( 5 ) )} ),
        Dispatch( {}, "400", LegendBox, {Set Title( "Count" )} )
    )
);

Code Explanation:

1. Open data table;
2. Create Graph Builder window.
3. Set graph size.
4. Hide control panel.
5. Assign weight to X-axis.
6. Assign height to Y-axis.
7. Add heatmap element.
8. Set legend position.
9. Configure weight axis scale.
10. Configure height axis scale and label offset.

Example 1302

Summary: Creates a graph builder with nested factors using operator and part configurations, displaying standard deviation charts.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 476, 600 ),
    Show Control Panel( 0 ),
    Variables( X( :Region ), X( :CO ), Y( :city ), Color( :Name( "pop- m" ) ) ),
    Relative Sizes( "X", [163 262] ),
    Elements( Position( 1, 1 ), Heatmap( X, Y, Legend( 6 ) ) ),
    Elements( Position( 2, 1 ), Points( X, Y, Legend( 10 ) ) ),
    SendToReport( Dispatch( {}, "Graph Builder", OutlineBox, {Set Title( "Graph Builder - X Relative Sizes" )} ) )
);

Code Explanation:

1. Open data table;
2. Launch Graph Builder.
3. Set window size.
4. Hide control panel.
5. Define X variables.
6. Define Y variable.
7. Define color variable.
8. Set X relative sizes.
9. Add heatmap element.
10. Add points element.
11. Set graph title.

Example 1303

Summary: Creates two heatmaps with nested factors using Graph Builder, configuring window sizes, hiding control panels, and labeling by percent of total values.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 563, 335 ),
    Show Control Panel( 0 ),
    Variables( X( :age ), Color( :height ) ),
    Elements( Heatmap( X, Legend( 4 ), Label( "Label by Percent of Total Values" ) ) )
);
Graph Builder(
    Size( 563, 335 ),
    Show Control Panel( 0 ),
    Variables( X( :age ), Color( :height ) ),
    Elements( Heatmap( X, Legend( 4 ), Label( "Label by Percent of Total Values" ), Max Label Size( 10.826 ) ) )
);

Code Explanation:

1. Open data table;
2. Create first Graph Builder window.
3. Set window size.
4. Hide control panel.
5. Assign age to X axis.
6. Assign height to color.
7. Add heatmap element.
8. Configure heatmap legend.
9. Label by percent of total values.
10. Create second Graph Builder window.
11. Set window size.
12. Hide control panel.
13. Assign age to X axis.
14. Assign height to color.
15. Add heatmap element.
16. Configure heatmap legend.
17. Label by percent of total values.
18. Set max label size.

Example 1304

Summary: Creates a heatmap visualization with nested factors using Graph Builder, displaying standard deviation charts and labeling by value.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 531, 450 ),
    Show Control Panel( 0 ),
    Variables( X( :Day of Month ), Y( :Month ), Color( :Arrival Delay ) ),
    Elements( Heatmap( X, Y, Legend( 5 ), Label( "Label by Value" ), Max Label Size( 10.092 ) ) )
);

Code Explanation:

1. Open data table.
2. Launch Graph Builder.
3. Set window size.
4. Hide control panel.
5. Assign variables.
6. Add heatmap element.
7. Set legend position.
8. Label by value.
9. Set max label size.

Example 1305

Summary: Creates a heatmap to visualize the relationship between age and height, with interactive features for legend customization and standard deviation charts.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 482, 324 ),
    Show Control Panel( 0 ),
    Variables( X( :age ), Y( :height ) ),
    Elements( Heatmap( X, Y, Legend( 2 ), Label( "Label by Value" ) ) ),
    SendToReport(
        Dispatch( {}, "height", ScaleBox, {Scale( "Log" ), Format( "Best", 12 ), Min( 50 ), Max( 72.5 ), Inc( 1 ), Minor Ticks( 1 )} )
    )
);

Code Explanation:

1. Open data table;
2. Launch Graph Builder.
3. Set window size.
4. Hide control panel.
5. Define X variable.
6. Define Y variable.
7. Add heatmap element.
8. Configure legend.
9. Label by value.
10. Adjust Y-axis scale.

Example 1306

Summary: Creates a heatmap visualization with nested factors using Graph Builder, displaying standard deviation charts and labeling by value.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 530, 365 ),
    Show Control Panel( 0 ),
    Variables( X( :State ), Y( :Region ), Frequency( :POP ) ),
    Elements( Heatmap( X, Y, Legend( 10 ), Label( "Label by Value" ) ) )
);

Code Explanation:

1. Open data table;
2. Create Graph Builder object.
3. Set graph size.
4. Hide control panel.
5. Define X variable.
6. Define Y variable.
7. Define frequency variable.
8. Add heatmap element.
9. Set legend properties.
10. Label by value.

Example 1307

Summary: Creates a heatmap and points graph to visualize relationships between height and weight, utilizing Graph Builder's variables and elements.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 534, 454 ),
    Show Control Panel( 0 ),
    Variables( X( :height ), Y( :weight ), Color( :height ) ),
    Elements( Heatmap( Legend( 7 ) ), Points( X, Y, Legend( 8 ) ) ),
    SendToReport( Dispatch( {}, "height", ScaleBox, {Min( 40 )} ), Dispatch( {}, "weight", ScaleBox, {Max( 200 )} ) )
);

Code Explanation:

1. Open data table;
2. Launch Graph Builder.
3. Set window size.
4. Hide control panel.
5. Define X, Y, and color variables.
6. Add heatmap element.
7. Add points element.
8. Customize height axis minimum.
9. Customize weight axis maximum.
10. Display report.

Example 1308

Summary: Creates a heatmap to visualize the relationship between Response and ln(dose) variables, grouped by Dose and displayed with frequency counts.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 534, 486 ),
    Show Control Panel( 0 ),
    Variables( X( :Response ), Y( :Name( "ln(dose)" ) ), Group X( :Dose ), Frequency( :Count ) ),
    Elements( Heatmap( X, Y, Legend( 4 ) ) )
);

Code Explanation:

1. Open data_table data
2. Launch Graph Builder.
3. Set window size to 534x486.
4. Hide control panel.
5. Assign variables: X(Response), Y(ln(dose)), Group X(Dose), Frequency(Count).
6. Add Heatmap element.
7. Display heatmap legend at position 4.

Example 1309

Summary: Creates a heatmap to visualize the distribution of height by sex, using Graph Builder and displaying standard deviation charts.

Code:

Open("data_table.jmp");
Graph Builder( Variables( X( :sex ), Color( :height, Summary Statistic( "% of Total" ) ) ), Elements( Heatmap( X, Legend( 2 ) ) ) );

Code Explanation:

1. Open data table.
2. Launch Graph Builder.
3. Set X variable to sex.
4. Set color variable to height.
5. Use "% of Total" summary statistic.
6. Add Heatmap element.
7. Enable legend for color.

Example 1310

Summary: Creates a heatmap to visualize nested factors using Graph Builder, selecting specific rows and defining variables for X, Y, and groupings.

Code:

dt = Open("data_table.jmp");
dt << Clear Row States;
dt << select rows(
    [1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36,
    37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50]
);
mySubset = subset( linked, dt );
mySubset << Graph Builder(
    Size( 403, 402 ),
    Show Control Panel( 0 ),
    Show Legend( 0 ),
    Include Missing Categories( 1 ),
    Variables( X( :Randomized ), Y( :Completed ), Group X( :Mannitol Flag ), Group Y( :Steroids Flag ) ),
    Elements( Heatmap( X, Y, Legend( 16 ) ) ),
    SendToReport(
        Dispatch( {}, "Completed", ScaleBox, {Scale( "Log" ), Format( "Best", 10 ), Min( 0.001 ), Max( 1.2 ), Inc( 1 ), Minor Ticks( 1 )} ),
        Dispatch( {}, "400", ScaleBox, {Legend Model( 16, Properties( 0, {gradient} ) )} )
    )
);

Code Explanation:

1. Open data table.
2. Clear row states.
3. Select specific rows.
4. Create subset of selected rows.
5. Initiate Graph Builder.
6. Set graph size.
7. Hide control panel.
8. Hide legend.
9. Include missing categories.
10. Define variables and elements for heatmap.

Example 1311

Summary: Creates a heatmap with nested factors using Graph Builder, displaying standard deviation charts and allowing for local data filtering.

Code:

Open("data_table.jmp") << Graph Builder(
    Size( 558, 488 ),
    Show Control Panel( 0 ),
    Variables( X( :weight ), Y( :age ), Group X( :height ), Group Y( :sex ) ),
    Elements( Heatmap( X, Y, Legend( 22 ) ) ),
    Local Data Filter( Add Filter( columns( :height, :weight ) ) )
);

Code Explanation:

1. Open data table;
2. Launch Graph Builder.
3. Set window size.
4. Hide control panel.
5. Define X variable.
6. Define Y variable.
7. Define Group X variable.
8. Define Group Y variable.
9. Add heatmap element.
10. Configure legend.
11. Add local data filter.
12. Set filter columns.

Example 1312

Summary: Creates a heatmap with nested factors using Graph Builder, displaying standard deviation charts and including missing categories.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 495, 454 ),
    Show Control Panel( 0 ),
    Include Missing Categories( 1 ),
    Variables( X( :age ), X( :sex, Position( 1 ) ), X( :height, Position( 1 ) ) ),
    Elements( Heatmap( X( 1 ), X( 2 ), X( 3 ), Legend( 4 ) ) )
);

Code Explanation:

1. Open data table;
2. Launch Graph Builder.
3. Set window size.
4. Hide control panel.
5. Include missing categories.
6. Assign variables to axes.
7. Create heatmap element.
8. Specify X axis positions.
9. Display legend.

Example 1313

Summary: Creates a heatmap to visualize the relationship between 'Rank[sex]' and 'height^3', with interactive filtering by 'height' and 'sex'.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 545, 437 ),
    Show Control Panel( 0 ),
    Variables(
        X( Transform Column( "Rank[sex]", Character, Formula( Col Rank( :sex ) ) ) ),
        Y( Transform Column( "height^3", Format( "Fixed Dec", 5, 0 ), Formula( :height ^ 3 ) ) ),
        Size( :height )
    ),
    Elements( Heatmap( X, Y, Legend( 20 ) ) ),
    Local Data Filter(
        Mode( Include( 0 ) ),
        Add Filter( columns( :height, :sex ), Where( :height >= 51 & :height <= 70 ), Where( :sex == "M" ) )
    )
);

Code Explanation:

1. Open data table;
2. Create Graph Builder object.
3. Set graph size.
4. Hide control panel.
5. Define X variable with transformed column.
6. Define Y variable with transformed column.
7. Set size by height.
8. Add heatmap element.
9. Set legend for heatmap.
10. Add local data filter.

Example 1314

Summary: Creates a heatmap to visualize relationships between Position, Weight, and Bench, with Fat as an overlay, using Graph Builder.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 530, 449 ),
    Show Control Panel( 0 ),
    Include Missing Categories( 1 ),
    Variables( X( :Position ), Y( :Weight ), Group Y( :Bench ), Overlay( :Fat ) ),
    Elements( Heatmap( X, Y, Legend( 12 ) ) )
);

Code Explanation:

1. Open data_table data
2. Create Graph Builder window.
3. Set size 530x449.
4. Hide control panel.
5. Include missing categories.
6. Set X variable: Position.
7. Set Y variable: Weight.
8. Group Y by Bench.
9. Overlay by Fat.
10. Add heatmap element.

Example 1315

Summary: Creates a variability chart with nested factors using operator and part configurations, displaying standard deviation charts in Graph Builder.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 564, 611 ),
    Show Control Panel( 0 ),
    Include Missing Categories( 1 ),
    Variables( X( :Position2 ), X( :Position, Position( 1 ) ), Y( :Bench ), Y( :LegPress ), Overlay( :Fat ) ),
    Elements( Position( 1, 1 ), Heatmap( X( 1 ), X( 2 ), Y, Legend( 89 ) ) ),
    Elements( Position( 1, 2 ), Heatmap( X( 1 ), X( 2 ), Y, Legend( 90 ) ) )
);

Code Explanation:

1. Open data_table data
2. Launch Graph Builder.
3. Set graph size.
4. Hide control panel.
5. Include missing categories.
6. Define X variables.
7. Define Y variables.
8. Add first heatmap element.
9. Add second heatmap element.
10. Display graph.

Example 1316

Summary: Creates a histogram chart to visualize the distribution of height data, with custom scale settings and legend configuration.

Code:

Open("data_table.jmp");
Graph Builder(
    Show Control Panel( 0 ),
    Variables( X( :height ) ),
    Elements( Histogram( X, Legend( 3 ) ) ),
    SendToReport( Dispatch( {}, "", ScaleBox, {Min( -4 ), Max( 14 ), Inc( 5 ), Minor Ticks( 1 )} ) )
);

Code Explanation:

1. Open data table;
2. Create Graph Builder.
3. Hide control panel.
4. Set X variable to height.
5. Add histogram element.
6. Set legend to 3.
7. Adjust scale box.
8. Set minimum to -4.
9. Set maximum to 14.
10. Set increment to 5.
11. Enable minor ticks.

Example 1317

Summary: Creates a variability chart with nested factors using Graph Builder, displaying standard deviation charts and adjusting bin span for histogram segments.

Code:

Open("data_table.jmp");
Graph Builder(
    Show Control Panel( 0 ),
    Size( 463, 478 ),
    Variables( X( :age ), Y( :height ) ),
    Elements( Histogram( X, Y, Legend( 6 ) ) ),
    SendToReport(
        Dispatch( {}, "Graph Builder", FrameBox,
            {DispatchSeg( Hist Seg( "Histogram (17)" ), Bin Span( 4, 0 ) ), DispatchSeg( Hist Seg( "Histogram (16)" ), Bin Span( 4, 0 ) ),
            DispatchSeg( Hist Seg( "Histogram (15)" ), Bin Span( 4, 0 ) ), DispatchSeg( Hist Seg( "Histogram (14)" ), Bin Span( 4, 0 ) ),
            DispatchSeg( Hist Seg( "Histogram (13)" ), Bin Span( 4, 0 ) ), DispatchSeg( Hist Seg( "Histogram (12)" ), Bin Span( 4, 0 ) )}
        )
    )
);

Code Explanation:

1. Open data table.
2. Create Graph Builder object.
3. Hide control panel.
4. Set graph size.
5. Assign variables X and Y.
6. Add histogram element.
7. Send report commands.
8. Adjust bin span for histogram segments.
9. Repeat bin span adjustment for multiple segments.
10. Finalize graph settings.

Example 1318

Summary: Creates a graph builder with nested factors using Graph Builder, displaying a histogram element and enabling legend.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 535, 454 ),
    Show Control Panel( 0 ),
    Fit to Window( "Off" ),
    Variables( Y( :weight ), Group X( :age ) ),
    Elements( Histogram( Y, Legend( 11 ) ) )
);

Code Explanation:

1. Open data table;
2. Launch Graph Builder.
3. Set window size.
4. Hide control panel.
5. Disable fit to window.
6. Assign weight to Y-axis.
7. Assign age to group X.
8. Add histogram element.
9. Enable legend for histogram.
10. Display graph.

Example 1319

Summary: Creates a variability chart with nested factors using Graph Builder, displaying standard deviation charts and utilizing size and legend settings.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 494, 328 ),
    Show Control Panel( 0 ),
    Variables( Y( :height ), Group X( :sex ), Group Y( :age ) ),
    Elements( Histogram( Y, Legend( 6 ) ) )
);

Code Explanation:

1. Open data table.
2. Create new Graph Builder window.
3. Set window size.
4. Hide control panel.
5. Assign variables to axes.
6. Add histogram element.
7. Set legend properties.

Example 1320

Summary: Creates a variability chart with nested factors using Graph Builder, displaying standard deviation charts and hiding the control panel.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 286, 176 ),
    Show Control Panel( 0 ),
    Variables( X( :weight ), Group Y( :age ) ),
    Elements( Histogram( X, Legend( 5 ) ) )
);

Code Explanation:

1. Open data table;
2. Launch Graph Builder.
3. Set window size.
4. Hide control panel.
5. Assign weight to X.
6. Assign age to Group Y.
7. Add histogram element.
8. Display legend.

Example 1321

Summary: Creates a Graph Builder window with two histogram elements, filtered by Region, and sends the report to a ScaleBox.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 704, 297 ),
    Show Control Panel( 0 ),
    Show Legend( 0 ),
    Variables( X( :Name( "Expenditure (1997)" ) ), X( :Population ) ),
    Elements( Position( 1, 1 ), Histogram( X, Legend( 8 ) ) ),
    Elements( Position( 2, 1 ), Histogram( X, Legend( 9 ) ) ),
    Local Data Filter(
        Mode( Show( 0 ), Include( 0 ) ),
        Add Filter(
            columns( :Region ),
            Where( :Region == {"New England", "Northeast", "South"} ),
            Display( :Region, Size( 181, 136 ), List Display )
        )
    ),
    SendToReport( Dispatch( {}, "Expenditure (1997)", ScaleBox, {Max( 10.734309623431 )} ) )
);

Code Explanation:

1. Open data table;
2. Create Graph Builder window.
3. Set window size.
4. Hide control panel.
5. Hide legend.
6. Define X variables.
7. Add first histogram element.
8. Add second histogram element.
9. Enable local data filter.
10. Configure filter settings.

Example 1322

Summary: Creates a variability chart with nested factors using operator and part configurations, displaying standard deviation charts.

Code:

dt = Open("data_table.jmp");
Graph Builder(
    Size( 594, 510 ),
    Show Control Panel( 0 ),
    Show Legend( 0 ),
    Show Footer( 0 ),
    Variables( X( :Causes ), Y( :Time Cycles ) ),
    Elements( Histogram( X, Y, Legend( 17 ) ) ),
    SendToReport( Dispatch( {}, "Causes", ScaleBox, {Min( -0.48211091234347 ), Max( 9.51788908765653 ), Inc( 1 ), Minor Ticks( 0 )} ) )
);

Code Explanation:

1. Open data table.
2. Create Graph Builder.
3. Set window size.
4. Hide control panel.
5. Hide legend.
6. Hide footer.
7. Assign variables.
8. Add histogram element.
9. Configure X-axis scale.
10. Configure Y-axis scale.

Example 1323

Summary: Creates a histogram to visualize sex distribution, utilizing Graph Builder and report generation.

Code:

dt = Open("data_table.jmp");
rpt = (dt << Graph Builder( Size( 470, 247 ), Show Control Panel( 0 ), Variables( Y( :sex ) ), Elements( Histogram( Y, Legend( 3 ) ) ) ))
 << report;
histogramSeg = rpt[Framebox( 1 )] << find seg( Hist Seg( 1 ) );

Code Explanation:

1. Open data table;
2. Create graph builder object.
3. Set graph size.
4. Hide control panel.
5. Add sex variable to Y-axis.
6. Add histogram element.
7. Generate report.
8. Access frame box.
9. Find histogram segment.
10. Assign to variable.

Example 1324

Summary: Creates a histogram with nested factors using Graph Builder, displaying standard deviation charts and configuring line width.

Code:

dt = Open("data_table.jmp");
rpt = (dt << Graph Builder( Size( 470, 247 ), Show Control Panel( 0 ), Variables( Y( :sex ) ), Elements( Histogram( Y, Legend( 3 ) ) ) ))
 << report;
histogramSeg = rpt[Framebox( 1 )] << find seg( Hist Seg( 1 ) );
histogramSeg << LineWidth( 4 );

Code Explanation:

1. Open data table;
2. Create Graph Builder object.
3. Set size to 470x247.
4. Hide control panel.
5. Set Y variable to sex.
6. Add histogram element.
7. Assign legend position 3.
8. Retrieve report object.
9. Find histogram segment.
10. Set line width to 4.

Example 1325

Summary: Creates a variability chart with nested factors using operator and part configurations, displaying standard deviation charts.

Code:

Open("data_table.jmp");
gb = Graph Builder(
    Size( 940, 828 ),
    Variables( X( :Price ), Page( :Cut, Levels per Row( 2 ) ) ),
    Elements( Histogram( X, Legend( 3 ) ) )
);

Code Explanation:

1. Open data table;
2. Create Graph Builder object.
3. Set graph size.
4. Define X variable as Price.
5. Use Cut variable for pages.
6. Set 2 levels per row.
7. Add Histogram element.
8. Assign legend to third position.

Example 1326

Summary: Creates a nested variability chart with two factors, using Graph Builder to visualize data and display standard deviation charts.

Code:

Open("data_table.jmp");
gb = Graph Builder(
    Size( 940, 828 ),
    Variables( X( :Price ), Page( :Cut, Levels per Row( 2 ) ) ),
    Elements( Histogram( X, Legend( 3 ) ) )
);
gb << Link Page Axes( "X and Y" );

Code Explanation:

1. Open data table;
2. Create Graph Builder object.
3. Set graph size.
4. Define X variable: Price.
5. Define page variable: Cut.
6. Set levels per row: 2.
7. Add histogram element.
8. Set legend position: 3.
9. Link page axes: X and Y.

Example 1327

Summary: Creates a variability chart with nested factors using Graph Builder, displaying standard deviation charts and configuring the Age and Weight variables as X-axis inputs.

Code:

Open("data_table.jmp");
Graph Builder(
    Show Control Panel( 0 ),
    Variables( X( :Age ), X( :Weight, Position( 1 ) ) ),
    Elements( Histogram( X( 1 ), X( 2 ), Legend( 3 ) ) )
);

Code Explanation:

1. Open data table;
2. Launch Graph Builder.
3. Hide control panel.
4. Set Age as X variable.
5. Set Weight as second X variable.
6. Add histogram element.
7. Assign Age to first axis.
8. Assign Weight to second axis.
9. Match legend color.
10. Display graph.

Example 1328

Summary: Creates a Graph Builder window with two histogram elements to visualize the relationship between age, sex, and weight in a data table.

Code:

dt = Open("data_table.jmp");
gb = Graph Builder(
    Size( 450, 320 ),
    Show Control Panel( 0 ),
    Variables( X( :age ), X( :sex ), Y( :weight ) ),
    Elements( Position( 1, 1 ), Histogram( X, Y ) ),
    Elements( Position( 2, 1 ), Histogram( X, Y ) )
);

Code Explanation:

1. Open data table.
2. Create new Graph Builder window.
3. Set window size.
4. Hide control panel.
5. Define X variables: age, sex.
6. Define Y variable: weight.
7. Add first histogram element.
8. Position first histogram.
9. Add second histogram element.
10. Position second histogram.

Example 1329

Summary: Creates a variability chart with nested factors using operator and part configurations, displaying standard deviation charts in JMP.

Code:

dt = Open("data_table.jmp");
gb = Graph Builder(
    Show Control Panel( 0 ),
    Variables( X( :age, Size( 23 ) ), X( :sex ), X( :height ), X( :weight ), Y( :age, Size( 42 ) ), Y( :sex ), Y( :height ), Y( :weight ) ),
    Elements( Position( 1, 1 ), Histogram( X, Y, Legend( 36 ) ) ),
    Elements( Position( 1, 2 ), Mosaic( X, Y, Legend( 43 ), Vertical ) ),
    Elements(
        Position( 1, 3 ),
        Points( X, Y, Legend( 4 ), Jitter( 1 ) ),
        Line( X, Y, Legend( 55 ), Row order( 0 ), Summary Statistic( "Mean" ) )
    ),
    Elements(
        Position( 1, 4 ),
        Points( X, Y, Legend( 7 ), Jitter( 1 ) ),
        Line( X, Y, Legend( 56 ), Row order( 0 ), Summary Statistic( "Mean" ) )
    ),
    Elements( Position( 2, 1 ), Mosaic( X, Y, Legend( 41 ), Vertical ) ),
    Elements( Position( 2, 2 ), Histogram( X, Y, Legend( 37 ) ) ),
    Elements(
        Position( 2, 3 ),
        Box Plot( X, Y, Legend( 48 ), Jitter( 1 ), Outliers( 1 ), Box Style( "Outlier" ) ),
        Contour( X, Y, Legend( 50 ), Number of Levels( 0 ) )
    ),
    Elements(
        Position( 2, 4 ),
        Contour( X, Y, Legend( 51 ), Number of Levels( 0 ) ),
        Box Plot( X, Y, Legend( 52 ), Jitter( 1 ), Outliers( 1 ), Box Style( "Outlier" ) )
    ),
    Elements( Position( 3, 1 ), Points( X, Y, Legend( 47 ), Jitter( 1 ) ) ),
    Elements( Position( 3, 2 ), Points( X, Y, Legend( 21 ), Jitter( 1 ) ) ),
    Elements( Position( 3, 3 ), Histogram( X, Y, Legend( 38 ) ) ),
    Elements(
        Position( 3, 4 ),
        Points( X, Y, Legend( 23 ) ),
        Smoother( X, Y, Legend( 19 ) ),
        Contour( X, Y, Legend( 54 ), Number of Levels( 0 ) )
    ),
    Elements( Position( 4, 1 ), Points( X, Y, Legend( 32 ), Jitter( 1 ) ) ),
    Elements( Position( 4, 2 ), Points( X, Y, Legend( 33 ), Jitter( 1 ) ) ),
    Elements(
        Position( 4, 3 ),
        Points( X, Y, Legend( 34 ) ),
        Smoother( X, Y, Legend( 30 ) ),
        Contour( X, Y, Legend( 53 ), Number of Levels( 0 ) )
    ),
    Elements( Position( 4, 4 ), Histogram( X, Y, Legend( 40 ) ) )
);

Code Explanation:

1. Open data table.
2. Create Graph Builder object.
3. Hide control panel.
4. Set variables for X and Y axes.
5. Add histogram element at position (1,1).
6. Add mosaic plot element at position (1,2).
7. Add points and line elements at position (1,3).
8. Add points and line elements at position (1,4).
9. Add mosaic plot element at position (2,1).
10. Add histogram element at position (2,2).

Example 1330

Summary: Creates a graph builder window with a histogram element to visualize data from a nested factors dataset, utilizing variables for axes and frequency.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 570, 516 ),
    Show Control Panel( 0 ),
    Variables( X( :age ), Y( :weight ), Overlay( :sex ), Frequency( :height ) ),
    Elements( Histogram( X, Y, Legend( 26 ) ) ),
    SendToReport(
        Dispatch( {}, "400", ScaleBox,
            {Legend Model( 26, Properties( 0, {Line Color( -4222943 )} ), Properties( 1, {Line Color( 6 ), Fill Color( 6 )} ) )}
        ),
        Dispatch( {}, "Graph Builder", FrameBox, {DispatchSeg( Hist Seg( "Histogram (12)" ), {Fill Color( "Medium Dark Red" )} )} )
    )
);

Code Explanation:

1. Open data table;
2. Create graph builder window.
3. Set window size.
4. Hide control panel.
5. Define variables for axes.
6. Add overlay variable.
7. Include frequency variable.
8. Plot histogram element.
9. Customize legend colors.
10. Set histogram fill color.

Example 1331

Summary: Creates a histogram to visualize age distribution, utilizing Graph Builder and setting response scale to percent.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 522, 408 ),
    Show Control Panel( 0 ),
    Variables( Y( :age ) ),
    Elements( Histogram( Y, Legend( 3 ), Response Scale( "Percent" ) ) )
);

Code Explanation:

1. Open data table;
2. Launch Graph Builder.
3. Set window size.
4. Hide control panel.
5. Assign age variable to Y.
6. Add histogram element.
7. Enable legend for histogram.
8. Set response scale to percent.

Example 1332

Summary: Creates a variability chart with nested factors using Graph Builder, displaying standard deviation charts and reversing the Y-axis scale.

Code:

Open("data_table.jmp");
Graph Builder(
    Show Control Panel( 0 ),
    Variables( X( :height ), Y( :age ) ),
    Elements( Histogram( X, Y, Legend( 2 ), Overlap( 3.067 ), Histogram Style( "Kernel Density" ) ) ),
    SendToReport( Dispatch( {}, "age", ScaleBox, {Reversed Scale} ) )
);

Code Explanation:

1. Open data table.
2. Create Graph Builder object.
3. Hide control panel.
4. Set X variable to height.
5. Set Y variable to age.
6. Add histogram element.
7. Enable legend for histograms.
8. Set overlap for histograms.
9. Use kernel density style.
10. Reverse Y axis scale.

Example 1333

Summary: Creates a variability chart with nested factors using operator and part configurations, displaying standard deviation charts.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 534, 418 ),
    Show Control Panel( 0 ),
    Variables( Y( :Total fat g ) ),
    Elements( Histogram( Y, Legend( 3 ) ) ),
    SendToReport(
        Dispatch( {}, "Total fat g", ScaleBox, {Scale( "Log" ), Format( "Best", 10 ), Min( 0.01 ), Max( 30 ), Inc( 1 ), Minor Ticks( 1 )} )
    )
);

Code Explanation:

1. Open data table;
2. Launch Graph Builder.
3. Set window size.
4. Hide control panel.
5. Assign Y variable.
6. Add histogram element.
7. Send report to Graph Builder.
8. Configure scale box.
9. Set log scale.
10. Define axis format.

Example 1334

Summary: Creates a variability chart with nested factors using operator and part configurations, displaying standard deviation charts in Graph Builder.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 460, 328 ),
    Show Control Panel( 0 ),
    Variables( Y( :height ) ),
    Elements( Histogram( Y, Legend( 3 ) ) ),
    SendToReport( Dispatch( {}, "height", ScaleBox, {Min( 50 ), Max( 72.5 ), Inc( 15 ), Minor Ticks( 1 )} ) )
);

Code Explanation:

1. Open data table.
2. Create new graph builder window.
3. Set window size.
4. Hide control panel.
5. Add height variable to Y-axis.
6. Add histogram element.
7. Configure legend position.
8. Set scale minimum.
9. Set scale maximum.
10. Set scale increment.
11. Enable minor ticks.

Example 1335

Summary: Creates a variability chart with nested factors using Graph Builder, displaying standard deviation charts and hiding control panels and legends.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 216, 144 ),
    Show Control Panel( 0 ),
    Show Legend( 0 ),
    Variables( X( :sex ), Y( :weight ), Y( :height, Position( 1 ) ) ),
    Elements( Histogram( X, Y( 1 ), Y( 2 ), Legend( 11 ) ) )
);

Code Explanation:

1. Open data_table data
2. Launch Graph Builder.
3. Set size to 216x144.
4. Hide control panel.
5. Hide legend.
6. Set X variable to sex.
7. Set Y1 variable to weight.
8. Set Y2 variable to height.
9. Position Y2 on axis 1.
10. Add histogram element.

Example 1336

Summary: Creates a variability chart with nested factors using operator and part configurations, displaying standard deviation charts in JMP.

Code:

dt = Open("data_table.jmp");
dt << select rows( [139] );
Graph Builder(
    Size( 534, 418 ),
    Show Control Panel( 0 ),
    Variables( Y( :Net Cost ) ),
    Elements( Bar( Y, Legend( 3 ), Summary Statistic( "Interquartile Range" ), Label( "Label by Row" ) ), Histogram( Y, Legend( 4 ) ) ),
    SendToReport(
        Dispatch( {}, "Graph Builder", FrameBox,
            Add Pin Annotation(
                Seg( BarSeg( 1 ) ),
                Index( {0, 0} ),
                Index Row( {0, 0} ),
                UniqueID( 491780480 ),
                FoundPt( {421, 401} ),
                Origin( {0.228260869565217, 729.591836734694} )
            )
        )
    )
);

Code Explanation:

1. Open data table;
2. Select row 139.
3. Create Graph Builder window.
4. Set window size 534x418.
5. Hide control panel.
6. Set Y variable to :Net Cost.
7. Add bar element with interquartile range summary.
8. Add histogram element.
9. Add pin annotation to bar segment.
10. Position annotation at specific coordinates.

Example 1337

Summary: Creates a variability chart with nested factors using Graph Builder, displaying standard deviation charts for height and weight.

Code:

Open("data_table.jmp");
Graph Builder(
    Show Control Panel( 0 ),
    Variables( Y( :height ), Y( :weight, Position( 1 ) ) ),
    Elements( Histogram( Y( 1 ), Y( 2 ), Legend( 5 ) ) ), 
);

Code Explanation:

1. Open data table.
2. Launch Graph Builder.
3. Hide control panel.
4. Set Y variables: height, weight.
5. Configure weight on position 1.
6. Add histogram element.
7. Assign Y1 to histogram.
8. Assign Y2 to histogram.
9. Set legend for histograms.

Example 1338

Summary: Creates a variability chart with nested factors using Graph Builder, displaying standard deviation charts and enabling legend at position 13.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 570, 516 ),
    Show Control Panel( 0 ),
    Variables( X( :age ), Y( :weight ), Overlay( :sex ) ),
    Elements( Histogram( X, Y, Legend( 13 ) ) )
);

Code Explanation:

1. Open data table;
2. Launch Graph Builder.
3. Set window size.
4. Hide control panel.
5. Assign variables: X=age, Y=weight.
6. Add overlay variable: sex.
7. Create histogram element.
8. Enable legend.
9. Position legend at 13.

Example 1339

Summary: Creates a histogram chart with age on the x-axis and weight on the y-axis, utilizing Graph Builder to visualize the data.

Code:

Open("data_table.jmp");
Graph Builder( Show Control Panel( 0 ), Variables( X( :age ), Y( :weight ) ), Elements( Histogram( X, Y, Legend( 10 ) ) ) );

Code Explanation:

1. Open data table;
2. Launch Graph Builder.
3. Hide control panel.
4. Set X variable to age.
5. Set Y variable to weight.
6. Add histogram element.
7. Include X and Y in histogram.
8. Enable legend with 10 items.

Example 1340

Summary: Creates a variability chart with nested factors using Graph Builder, displaying standard deviation charts and overlaying sex as an additional dimension.

Code:

Open("data_table.jmp");
Graph Builder( Show Control Panel( 0 ), Variables( Y( :height ), Overlay( :sex ) ), Elements( Histogram( Y, Legend( 5 ) ) ) );

Code Explanation:

1. Open data table;
2. Launch Graph Builder.
3. Hide control panel.
4. Set Y variable to height.
5. Add sex for overlay.
6. Add histogram element.
7. Assign legend position 5.

Example 1341

Summary: Creates two histograms in Graph Builder, overlaying sex as a categorical factor for height and displaying legend positions.

Code:

Open("data_table.jmp");
Graph Builder( Show Control Panel( 0 ), Variables( Y( :height ), Overlay( :sex ) ), Elements( Histogram( Y, Legend( 5 ) ) ) );
Graph Builder( Show Control Panel( 0 ), Variables( X( :height ), Overlay( :sex ) ), Elements( Histogram( X, Legend( 5 ) ) ) );

Code Explanation:

1. Open data table;
2. Launch Graph Builder.
3. Hide control panel.
4. Set Y variable to height.
5. Overlay by sex.
6. Add histogram element.
7. Set legend position.
8. Launch second Graph Builder.
9. Hide control panel.
10. Set X variable to height.

Example 1342

Summary: Creates a variability chart with nested factors using operator and part configurations, displaying standard deviation charts for height and weight data.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 534, 418 ),
    Show Control Panel( 0 ),
    Variables( Y( :height ), Y( :weight ), Overlay( :sex ) ),
    Elements( Position( 1, 1 ), Histogram( Y, Legend( 3 ) ) ),
    Elements( Position( 1, 2 ), Histogram( Y, Legend( 4 ) ) )
);

Code Explanation:

1. Open data table;
2. Launch Graph Builder.
3. Set window size.
4. Hide control panel.
5. Define Y variables: height, weight.
6. Define overlay variable: sex.
7. Add histogram for height.
8. Add legend for height histogram.
9. Add histogram for weight.
10. Add legend for weight histogram.

Example 1343

Summary: Creates a graph builder window with nested factors, utilizing Graph Builder to display histograms and overlay them for visual analysis.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 534, 418 ),
    Show Control Panel( 0 ),
    Variables( Y( :height ), Y( :weight, Position( 1 ) ) ),
    Elements( Histogram( Y( 1 ), Y( 2 ), Legend( 3 ) ) )
);

Code Explanation:

1. Open data table;
2. Create Graph Builder window.
3. Set window size.
4. Hide control panel.
5. Define Y variables.
6. Add histogram element.
7. Overlay histograms.
8. Add legend to histograms.

Example 1344

Summary: Creates a variability chart with nested factors using Graph Builder, displaying standard deviation charts and customizing legend properties for males and females.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 528, 447 ),
    Show Control Panel( 0 ),
    Variables( X( :age ), Y( :height ), Overlay( :sex ) ),
    Elements( Histogram( X, Y, Legend( 7 ) ) ),
    SendToReport(
        Dispatch( {}, "400", ScaleBox,
            {Legend Model(
                7,
                Properties( 0, {Fill Color( 8 ), Fill Pattern( "right slant heavy" )} ),
                Properties( 1, {Fill Color( 4 ), Fill Pattern( "left slant heavy" )} )
            )}
        )
    )
);

Code Explanation:

1. Open data_table data
2. Launch Graph Builder.
3. Set window size.
4. Hide control panel.
5. Assign variables: age, height, sex.
6. Add histogram element.
7. Overlay histograms by sex.
8. Send report settings.
9. Customize legend properties for males.
10. Customize legend properties for females.

Example 1345

Summary: Creates a variability chart with nested factors using Graph Builder, displaying standard deviation charts and configuring bar style for side-by-side comparison.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 450, 320 ),
    Show Control Panel( 0 ),
    Variables( X( :sex ), Y( :height ), Overlay( :age ) ),
    Elements( Bar( X, Y, Legend( 8 ), Bar Style( "Side by side" ), Summary Statistic( "N" ) ), Histogram( X, Y ) )
);

Code Explanation:

1. Open data table;
2. Launch Graph Builder.
3. Set window size.
4. Hide control panel.
5. Define X, Y, and overlay variables.
6. Add bar element.
7. Configure bar style.
8. Set summary statistic.
9. Add histogram element.
10. Display graph.

Example 1346

Summary: Creates a graph builder with nested factors using Graph Builder, displaying a histogram with standard deviation charts.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 528, 464 ),
    Show Control Panel( 0 ),
    Variables( X( :sex ), X( :age, Position( 1 ) ), Y( :height ) ),
    Elements( Histogram( X( 1 ), X( 2 ), Y, Legend( 7 ) ) )
);

Code Explanation:

1. Open data table;
2. Launch Graph Builder.
3. Set window size.
4. Hide control panel.
5. Assign variables to axes.
6. Add histogram element.
7. Specify X variables for histogram.
8. Assign Y variable for histogram.
9. Add legend to histogram.
10. Display graph.

Example 1347

Summary: Creates a histogram to visualize the distribution of 'height' data, utilizing Graph Builder and hiding the control panel.

Code:

dt = Open("data_table.jmp");
Graph Builder( Show Control Panel( 0 ), Variables( Y( :height ) ), Elements( Histogram( Y, Legend( 4 ) ) ) );
Close( dt, nosave );

Code Explanation:

1. Open data table.
2. Create Graph Builder object.
3. Hide control panel.
4. Set Y variable to "height".
5. Add histogram element.
6. Position legend at 4.
7. Close data table without saving.

Example 1348

Summary: Creates a variability chart with nested factors using operator and part configurations, displaying standard deviation charts.

Code:

Open("data_table.jmp");
Graph Builder( Show Control Panel( 0 ), Variables( Y( :height ) ), Elements( Histogram( Y, Legend( 4 ) ) ) );

Code Explanation:

1. Open data table;
2. Launch Graph Builder.
3. Hide control panel.
4. Set Y variable to height.
5. Add histogram element.
6. Assign legend to position 4.

Example 1349

Summary: Creates a variability chart with nested factors using operator and part configurations, displaying standard deviation charts in Graph Builder.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 532, 452 ),
    Show Control Panel( 0 ),
    Variables( X( :Carat Weight ), X( :Table, Position( 1 ) ), X( :Depth ), Group Y( :Report ) ),
    Elements( Position( 1, 1 ), Histogram( X( 2 ), X( 1 ), Legend( 7 ) ) ),
    Elements( Position( 2, 1 ), Histogram( X, Legend( 8 ) ) )
);

Code Explanation:

1. Open data table;
2. Create Graph Builder window.
3. Set window size to 532x452.
4. Hide control panel.
5. Define X variables: Carat Weight, Table, Depth.
6. Define Group Y variable: Report.
7. Add first Histogram element.
8. Position first Histogram at (1,1).
9. Set X for first Histogram: Table, Carat Weight.
10. Add second Histogram element.
11. Position second Histogram at (2,1).
12. Set X for second Histogram: unspecified.

Example 1350

Summary: Creates a variability chart with nested factors using operator and part configurations, displaying standard deviation charts.

Code:

Open("data_table.jmp");
Graph Builder( Size( 525, 450 ), Show Control Panel( 0 ), Variables( X( :age ), Y( :age ) ), Elements( Histogram( X, Y, Legend( 6 ) ) ) );

Code Explanation:

1. Open data table.
2. Launch Graph Builder.
3. Set window size.
4. Hide control panel.
5. Assign X variable.
6. Assign Y variable.
7. Add histogram element.
8. Set legend position.

Example 1351

Summary: Creates a variability chart with nested factors using Graph Builder, displaying standard deviation charts and enabling legend.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 528, 418 ),
    Show Control Panel( 0 ),
    Variables( Y( :height ), Y( :height, Position( 1 ) ), Frequency( :height ) ),
    Elements( Histogram( Y( 1 ), Y( 2 ), Legend( 4 ) ) )
);

Code Explanation:

1. Open data table;
2. Launch Graph Builder.
3. Set window size.
4. Hide control panel.
5. Define Y variable: height.
6. Duplicate Y variable for histogram.
7. Set frequency variable: height.
8. Add histogram element.
9. Position histogram vertically.
10. Enable legend.

Example 1352

Summary: Creates a histogram with nested factors using Graph Builder, displaying standard deviation charts and customizing line color and width.

Code:

Open("data_table.jmp");
rpt = Graph Builder(
    Size( 470, 247 ),
    Show Control Panel( 0 ),
    Variables( X( :age ) ),
    Elements( Histogram( X, Legend( 3 ), Percents( 1 ) ) )
) << report;
histSeg = rpt[Framebox( 1 )] << find seg( Hist Seg( 1 ) );
histSeg << line color( "red" );
histSeg << line width( 6 );

Code Explanation:

1. Open data table;
2. Create graph builder object.
3. Set graph size.
4. Hide control panel.
5. Assign variable for age.
6. Add histogram element.
7. Retrieve graph report.
8. Find histogram segment.
9. Change line color to red.
10. Set line width to 6.

Example 1353

Summary: Creates a histogram with nested factors using Graph Builder, configuring line color, width, and style.

Code:

dt = Open("data_table.jmp");
rpt = Graph Builder(
    Size( 470, 247 ),
    Show Control Panel( 0 ),
    Variables( X( :age ) ),
    Elements( Histogram( X, Legend( 3 ), Percents( 1 ) ) )
) << report;
histSeg = rpt[Framebox( 1 )] << find seg( Hist Seg( 1 ) );
histSeg << line color( "red" );
histSeg << line width( 6 );
histSeg << Line Style( "dashed" );

Code Explanation:

1. Open data table.
2. Create graph builder object.
3. Set graph size.
4. Hide control panel.
5. Define X variable.
6. Add histogram element.
7. Retrieve report object.
8. Locate histogram segment.
9. Set line color to red.
10. Set line width to 6.

Example 1354

Summary: Creates a histogram with nested factors using Graph Builder, configuring line color and style.

Code:

Open("data_table.jmp");
rpt = Graph Builder(
    Size( 470, 247 ),
    Show Control Panel( 0 ),
    Variables( X( :age ) ),
    Elements( Histogram( X, Legend( 3 ), Percents( 1 ) ) )
) << report;
histSeg = rpt[Framebox( 1 )] << find seg( Hist Seg( 1 ) );
histSeg << Percent Decimals( 1 );
histSeg << line color( "red" );
histSeg << Line Style( "dashed" );

Code Explanation:

1. Open data table;
2. Create graph builder object.
3. Set graph size.
4. Hide control panel.
5. Assign X variable.
6. Add histogram element.
7. Retrieve report object.
8. Locate histogram segment.
9. Set percent decimals.
10. Change line color.
11. Set line style.

Example 1355

Summary: Creates a histogram with nested factors using Graph Builder, configuring visual elements such as line color, style, and width.

Code:

dt = Open("data_table.jmp");
rpt = Graph Builder(
    Size( 470, 247 ),
    Show Control Panel( 0 ),
    Variables( X( :age ) ),
    Elements( Histogram( X, Legend( 3 ), Percents( 1 ) ) )
) << report;
histSeg = rpt[Framebox( 1 )] << find seg( Hist Seg( 1 ) );
histSeg << Percent Decimals( 1 );
histSeg << line color( "red" );
histSeg << Line Style( "dashed" );
histSeg << line width( 10 );

Code Explanation:

1. Open data table.
2. Create Graph Builder object.
3. Set graph size.
4. Hide control panel.
5. Assign X variable.
6. Add histogram element.
7. Retrieve report object.
8. Locate histogram segment.
9. Set percent decimals to 1.
10. Change line color to red.
11. Set line style to dashed.
12. Set line width to 10.

Example 1356

Summary: Creates a graph builder window with a histogram element to visualize the distribution of height for male individuals between 58 and 60, utilizing Graph Builder.

Code:

dt = Open("data_table.jmp");
dt << select where( :sex == "M" & 58 <= :height < 60 );
Graph Builder(
    Size( 472, 412 ),
    Show Control Panel( 0 ),
    Variables( X( :sex ), Y( :height ) ),
    Elements( Histogram( X, Y, Legend( 8 ), Overlap( 5 ) ) )
);

Code Explanation:

1. Open data table.
2. Select male entries.
3. Filter height between 58 and 60.
4. Create Graph Builder window.
5. Set window size.
6. Hide control panel.
7. Assign variables to axes.
8. Add histogram element.
9. Configure legend position.
10. Enable overlap setting.

Example 1357

Summary: Creates a variability chart with nested factors using Graph Builder, displaying points and smoother elements for height and weight data, while also setting a custom title font color.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 447, 335 ),
    Show Control Panel( 0 ),
    Show Subtitle( 1 ),
    Variables( X( :height ), Y( :weight ), Overlay( :sex ) ),
    Elements( Points( X, Y, Legend( 1 ) ), Smoother( X, Y, Legend( 2 ) ) ),
    SendToReport( Dispatch( {}, "graph 1 title", TextEditBox, {Font Color( 1 ), Set Text( "2017" )} ) )
);

Code Explanation:

1. Open data table.
2. Launch Graph Builder.
3. Set window size.
4. Hide control panel.
5. Show subtitle.
6. Assign variables: X=height, Y=weight, Overlay=sex.
7. Add points element.
8. Add smoother element.
9. Change title font color.
10. Set title text to "2017".

Example 1358

Summary: Creates a histogram to visualize flight distance by airline, with customizable X-axis scale and label orientation.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 570, 464 ),
    Show Control Panel( 0 ),
    Variables( X( :Distance ) ),
    Elements( Histogram( X, Legend( 9 ) ) ),
    SendToReport(
        Dispatch( {}, "Distance", ScaleBox,
            {Min( -6.07535604831441 ), Max( 2900 ), Inc( 500 ), Minor Ticks( 0 ), Label Row( Label Orientation( "Angled" ) )}
        ),
        Dispatch( {}, "graph title", TextEditBox, {Set Text( "Flight Distance by Airline" )} )
    )
);

Code Explanation:

1. Open data table.
2. Launch Graph Builder.
3. Set graph size.
4. Hide control panel.
5. Assign X variable.
6. Add histogram element.
7. Configure X-axis scale.
8. Set X-axis label orientation.
9. Set graph title.

Example 1359

Summary: Creates a variability chart with nested factors using operator and part configurations, displaying standard deviation charts in JMP.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 628, 529 ),
    Show Control Panel( 0 ),
    Variables( X( :sex ), X( :name, Position( 1 ) ) ),
    Elements( Histogram( X( 1 ), X( 2 ), Legend( 11 ) ) )
);

Code Explanation:

1. Open data table;
2. Launch Graph Builder.
3. Set window size.
4. Hide control panel.
5. Define X variables.
6. Add histogram element.
7. Specify X positions.
8. Add legend to histogram.

Example 1360

Summary: Creates a variability chart with nested factors using operator and part configurations, displaying standard deviation charts in Graph Builder.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 256, 190 ),
    Show Control Panel( 0 ),
    Variables( X( :height ), X( :height ), X( :weight, Position( 2 ) ) ),
    Elements( Position( 1, 1 ), Histogram( X, Legend( 2 ) ) ),
    Elements( Position( 2, 1 ), Histogram( X( 1 ), X( 2 ), Legend( 4 ) ) )
);

Code Explanation:

1. Open data table;
2. Launch Graph Builder.
3. Set window size.
4. Hide control panel.
5. Define X variables.
6. Add first histogram element.
7. Position first histogram.
8. Add second histogram element.
9. Position second histogram.
10. Display histograms.

Example 1361

Summary: Creates a variability chart with nested factors using Graph Builder, displaying standard deviation charts and histograms.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 567, 424 ),
    Show Control Panel( 0 ),
    Show Legend( 0 ),
    Variables(
        X( Transform Column( "AgePlusThirty", Ordinal, Formula( :age + 30 ) ) ),
        Y( Transform Column( "Cumulative Probability[height]", Formula( Col Rank( :height ) / (Col Number( :height ) + 1) ) ) ),
        Y(
            Transform Column(
                "Normal Quantile[height]",
                Formula(
                    Normal Quantile( Col Rank( :height ) / (Col Number( :height ) + 1), Col Mean( :height ), Col Std Dev( :height ) )
                )
            )
        )
    ),
    Elements( Position( 1, 1 ), Histogram( X, Y, Legend( 30 ) ) ),
    Elements( Position( 1, 2 ), Histogram( X, Y, Legend( 29 ) ) ),
    SendToReport(
        Dispatch( {}, "Graph Builder", FrameBox,
            {DispatchSeg( Hist Seg( "Histogram (47)" ), Bin Span( 24, 0 ) ), DispatchSeg( Hist Seg( "Histogram (46)" ), Bin Span( 24, 0 ) ),
            DispatchSeg( Hist Seg( "Histogram (45)" ), Bin Span( 24, 0 ) ), DispatchSeg( Hist Seg( "Histogram (44)" ), Bin Span( 24, 0 ) ),
            DispatchSeg( Hist Seg( "Histogram (43)" ), Bin Span( 24, 0 ) ), DispatchSeg( Hist Seg( "Histogram (42)" ), Bin Span( 24, 0 ) )}
        )
    )
);

Code Explanation:

1. Open data table;
2. Create Graph Builder object.
3. Set graph size.
4. Hide control panel.
5. Hide legend.
6. Define X variable with transformation.
7. Define first Y variable with transformation.
8. Define second Y variable with transformation.
9. Add first histogram element.
10. Add second histogram element.
11. Adjust histogram bin spans.

Example 1362

Summary: Creates a variability chart with nested factors using operator and part configurations, displaying standard deviation charts in JMP.

Code:

dt under test = Open("data_table.jmp");
obj = Graph Builder(
    Size( 618, 489 ),
    Show Control Panel( 0 ),
    Variables( Y( :Airline ), Wrap( :Day of Week ) ),
    Elements( Bar( Y, Legend( 11 ) ) ),
    SendToReport(
        Dispatch( {}, "400", ScaleBox, {Legend Model( 11, Properties( 0, {Fill Color( 51 )} ) )} ),
        Dispatch( {}, "Graph Builder", FrameBox, {Background Color( 32 )} ),
        Dispatch( {}, "Graph Builder", FrameBox( 2 ), {Background Color( 32 )} ),
        Dispatch( {}, "Graph Builder", FrameBox( 3 ), {Background Color( 32 )} ),
        Dispatch( {}, "Graph Builder", FrameBox( 4 ), {Background Color( 32 )} ),
        Dispatch( {}, "Graph Builder", FrameBox( 5 ), {Background Color( 32 )} ),
        Dispatch( {}, "Graph Builder", FrameBox( 6 ), {Background Color( 32 )} ),
        Dispatch( {}, "Graph Builder", FrameBox( 7 ), {Background Color( 32 )} ),
        Dispatch( {}, "Graph Builder", FrameBox( 8 ), {Background Color( 32 )} ),
        Dispatch( {}, "Graph Builder", FrameBox( 9 ), {Background Color( 32 )} )
    )
);

Code Explanation:

1. Open data table;
2. Create Graph Builder object.
3. Set window size to 618x489.
4. Hide control panel.
5. Assign Y variable: Airline.
6. Wrap X variable: Day of Week.
7. Add bar element.
8. Customize legend color.
9. Set background color for main frame.
10. Set background color for all sub-frames.

Example 1363

Summary: Creates a variability chart with nested factors using Graph Builder, specifying X variables and adding a histogram element.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 621, 464 ),
    Show Control Panel( 0 ),
    Variables( X( :Month ), X( :Day of Week, Position( 1 ) ) ),
    Elements( Histogram( X( 2 ), X( 1 ), Legend( 2 ) ) )
);

Code Explanation:

1. Open data table;
2. Launch Graph Builder.
3. Set window size.
4. Hide control panel.
5. Define X variables.
6. Add histogram element.
7. Specify nested categories.
8. Configure legend position.

Example 1364

Summary: Creates a variability chart with nested factors using operator and part configurations, displaying standard deviation charts.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 534, 418 ),
    Show Control Panel( 0 ),
    Variables( Y( :Meal ), Overlay( :Fat ) ),
    Elements( Histogram( Y, Legend( 4 ) ) )
);

Code Explanation:

1. Open data table;
2. Launch Graph Builder.
3. Set window size.
4. Hide control panel.
5. Assign variables: Y = Meal, Overlay = Fat.
6. Add histogram element.
7. Configure legend position.

Example 1365

Summary: Creates a variability chart with nested factors using operator and part configurations, displaying standard deviation charts in JMP.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 1054, 641 ),
    Variables( X( :height ), X( :height ), X( :height ), X( :height ), Y( :sex ) ),
    Elements( Position( 1, 1 ), Histogram( X, Y, Legend( 4 ) ) ),
    Elements( Position( 2, 1 ), Histogram( X, Y, Legend( 5 ), Histogram Style( "Polygon" ) ) ),
    Elements( Position( 3, 1 ), Histogram( X, Y, Legend( 6 ), Histogram Style( "Kernel Density" ) ) ),
    Elements( Position( 4, 1 ), Histogram( X, Y, Legend( 7 ), Histogram Style( "Shadowgram" ) ) ),
    SendToReport( Dispatch( {}, "sex", ScaleBox, {Reversed Scale} ) )
);
Graph Builder(
    Size( 545, 836 ),
    Show Control Panel( 0 ),
    Variables( X( :sex ), Y( :height ), Y( :height ), Y( :height ), Y( :height ) ),
    Elements( Position( 1, 1 ), Histogram( X, Y, Legend( 7 ) ) ),
    Elements( Position( 1, 2 ), Histogram( X, Y, Legend( 6 ), Histogram Style( "Polygon" ) ) ),
    Elements( Position( 1, 3 ), Histogram( X, Y, Legend( 5 ), Histogram Style( "Kernel Density" ) ) ),
    Elements( Position( 1, 4 ), Histogram( X, Y, Legend( 4 ), Histogram Style( "Shadowgram" ) ) ),
    SendToReport( Dispatch( {}, "sex", ScaleBox, {Reversed Scale} ) )
);

Code Explanation:

1. Open data table;
2. Create first Graph Builder window.
3. Set window size.
4. Define variables for histograms.
5. Add first histogram element.
6. Add second histogram element.
7. Add third histogram element.
8. Add fourth histogram element.
9. Reverse scale for sex variable.
10. Create second Graph Builder window.

Example 1366

Summary: Creates a variability chart with nested factors using Graph Builder, displaying standard deviation charts and reversing the Y scale.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 525, 456 ),
    Show Control Panel( 0 ),
    Variables( X( :height ), Y( :age ) ),
    Elements( Histogram( X, Y, Legend( 3 ), Counts( 1 ), Percents( 1 ) ) ),
    SendToReport( Dispatch( {}, "age", ScaleBox, {Reversed Scale} ) )
);

Code Explanation:

1. Open data table.
2. Create Graph Builder window.
3. Set window size.
4. Hide control panel.
5. Assign X variable.
6. Assign Y variable.
7. Add histogram element.
8. Enable legend for counts.
9. Enable counts display.
10. Enable percents display.
11. Reverse Y scale.

Example 1367

Summary: Creates a variability chart with nested factors using operator and part configurations, displaying standard deviation charts.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 534, 418 ),
    Show Control Panel( 0 ),
    Variables( Y( :age ), Y( :height, Position( 1 ) ), Y( :weight, Position( 1 ) ) ),
    Elements( Histogram( Y( 1 ), Y( 2 ), Y( 3 ), Legend( 3 ) ) )
);

Code Explanation:

1. Open data table.
2. Create Graph Builder window.
3. Set window size.
4. Hide control panel.
5. Assign variables to axes.
6. Add histogram element.
7. Specify multiple Y variables.
8. Position histograms.
9. Enable legend for third variable.
10. Display graph.

Example 1368

Summary: Creates a graph builder with a histogram element to visualize data from a nested factor table, utilizing Graph Builder and hiding control panel and legend.

Code:

dt = Open("data_table.jmp");
dt << Graph Builder(
    Size( 495, 295 ),
    Show Control Panel( 0 ),
    Show Legend( 0 ),
    Variables( X( :Development Level ) ),
    Elements( Histogram( X, Legend( 3 ) ) ),
    SendToReport( Dispatch( {}, "400", LegendBox, {Set Title( "" )} ) )
);

Code Explanation:

1. Open table.
2. Set graph size.
3. Hide control panel.
4. Hide legend.
5. Set X variable.
6. Add histogram element.
7. Remove legend title.
8. Display report.

Example 1369

Summary: Creates a variability chart with nested factors using operator and part configurations, displaying standard deviation charts.

Code:

dt = Open("data_table.jmp");
dt << Graph Builder(
    Size( 534, 418 ),
    Show Control Panel( 0 ),
    Variables( Y( :age ), Y( :height, Position( 1 ) ), Y( :weight, Position( 1 ) ) ),
    Elements( Histogram( Y( 1 ), Y( 2 ), Y( 3 ), Legend( 3 ) ) )
);

Code Explanation:

1. Open data table.
2. Launch Graph Builder.
3. Set window size.
4. Hide control panel.
5. Assign variables to axes.
6. Add histogram element.
7. Plot age, height, weight.
8. Display legend for third variable.

Example 1370

Summary: Creates a graph builder window with a histogram element to visualize data from a nested factors dataset, utilizing Graph Builder and specifying custom scale properties.

Code:

dt = Open("data_table.jmp");
dt << Graph Builder(
    Size( 168, 265 ),
    Show Control Panel( 0 ),
    Variables( X( :weight ), X( :height, Position( 1 ) ), Y( :sex ) ),
    Elements( Histogram( X( 1 ), X( 2 ), Y, Legend( 2 ) ) ),
    SendToReport( Dispatch( {}, "weight", ScaleBox, {Min( 40 ), Max( 180 ), Inc( 50 ), Minor Ticks( 0 )} ) )
);

Code Explanation:

1. Open data table.
2. Create Graph Builder window.
3. Set window size.
4. Hide control panel.
5. Define X and Y variables.
6. Add histogram element.
7. Set X-axis scale properties.
8. Set Y-axis scale properties.
9. Set legend position.
10. Adjust minor ticks visibility.

Example 1371

Summary: Creates a variability chart with nested factors using operator and part configurations, displaying standard deviation charts.

Code:

dt = Open("data_table.jmp");
dt << Clear Row States;
dt << select rows(
    [1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36,
    37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50]
);
mySubset = subset( linked, dt );
mySubset << Clear Row States;
mySubset << Graph Builder(
    Size( 312, 297 ),
    Show Control Panel( 0 ),
    Show Legend( 0 ),
    Variables( X( :Domain Abbreviation ), Y( :Sequence Number ) ),
    Elements( Histogram( X, Y, Legend( 6 ) ) )
);

Code Explanation:

1. Open data table.
2. Clear row states.
3. Select specific rows.
4. Create subset of selected rows.
5. Clear row states in subset.
6. Launch Graph Builder.
7. Set window size.
8. Hide control panel.
9. Hide legend.
10. Define variables for graph.

Example 1372

Summary: Creates multiple histograms for weight data, with customizable axis settings and legend options.

Code:

Open("data_table.jmp");
Graph Builder(
    Variables( X( :weight ) ),
    Elements( Histogram( X, Legend( 2 ), Histogram Style( "Kernel Density" ), Smoothness( 1 ) ) ),
    SendToReport(
        Dispatch( {}, "weight", ScaleBox, {Min( 25 ), Max( 225 ), Inc( 25 ), Minor Ticks( 0 )} ),
        Dispatch( {}, "", ScaleBox, {Min( -2.5 ), Max( 17.5 ), Inc( 5 ), Minor Ticks( 1 )} )
    )
);
Graph Builder(
    Variables( X( :weight ) ),
    Elements( Histogram( X, Legend( 2 ), Histogram Style( "Kernel Density" ), Smoothness( 1 ) ) ),
    SendToReport(
        Dispatch( {}, "weight", ScaleBox, {Min( 25 ), Max( 225 ), Inc( 25 ), Minor Ticks( 0 )} ),
        Dispatch( {}, "", ScaleBox, {Min( 17.5 ), Max( -2.5 ), Inc( 5 ), Minor Ticks( 1 )} )
    )
);
Graph Builder(
    Variables( Y( :weight ) ),
    Elements( Histogram( Y, Legend( 3 ), Histogram Style( "Kernel Density" ), Smoothness( 1 ) ) ),
    SendToReport(
        Dispatch( {}, "", ScaleBox, {Min( -2.5 ), Max( 17.5 ), Inc( 5 ), Minor Ticks( 1 )} ),
        Dispatch( {}, "weight", ScaleBox, {Min( 25 ), Max( 225 ), Inc( 25 ), Minor Ticks( 0 )} )
    )
);
Graph Builder(
    Variables( Y( :weight ) ),
    Elements( Histogram( Y, Legend( 3 ), Histogram Style( "Kernel Density" ), Smoothness( 1 ) ) ),
    SendToReport(
        Dispatch( {}, "", ScaleBox, {Min( 17.5 ), Max( -2.5 ), Inc( 5 ), Minor Ticks( 1 )} ),
        Dispatch( {}, "weight", ScaleBox, {Min( 25 ), Max( 225 ), Inc( 25 ), Minor Ticks( 0 )} )
    )
);

Code Explanation:

1. Open data table.
2. Create histogram for weight.
3. Set X-axis min, max, increment, minor ticks.
4. Set Y-axis min, max, increment, minor ticks.
5. Repeat steps 2-4.
6. Create histogram for weight.
7. Set Y-axis min, max, increment, minor ticks.
8. Set X-axis min, max, increment, minor ticks.
9. Repeat steps 6-8.
10. Save script.

Example 1373

Summary: Creates three histograms with different styles (polygon and kernel density) for a dataset, using Graph Builder to visualize height distribution.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 534, 456 ),
    Show Control Panel( 0 ),
    Variables( X( :height ) ),
    Elements( Histogram( X, Legend( 3 ), Counts( 1 ) ) ),
    SendToReport( Dispatch( {}, "", ScaleBox, {Reversed Scale} ) )
);
Graph Builder(
    Size( 534, 456 ),
    Show Control Panel( 0 ),
    Variables( X( :height ) ),
    Elements( Histogram( X, Legend( 3 ), Histogram Style( "Polygon" ), Counts( 1 ) ) ),
    SendToReport( Dispatch( {}, "", ScaleBox, {Reversed Scale} ) )
);
Graph Builder(
    Size( 534, 456 ),
    Show Control Panel( 0 ),
    Variables( X( :height ) ),
    Elements( Histogram( X, Legend( 3 ), Histogram Style( "Kernel Density" ) ) ),
    SendToReport( Dispatch( {}, "", ScaleBox, {Reversed Scale} ) )
);

Code Explanation:

1. Open data table.
2. Create histogram graph.
3. Set graph size.
4. Hide control panel.
5. Use height variable.
6. Display histogram element.
7. Enable legend.
8. Count data points.
9. Reverse scale axis.
10. Repeat for polygon style.
11. Repeat for kernel density style.

Example 1374

Summary: Creates four histograms for height with varying styles, including polygon, kernel density, and shadowgram, using Graph Builder in JMP.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 534, 456 ),
    Show Control Panel( 0 ),
    Variables( X( :height ) ),
    Elements( Histogram( X, Legend( 3 ), Counts( 1 ) ) ),
    SendToReport( Dispatch( {}, "", ScaleBox, {Reversed Scale} ) )
);
Graph Builder(
    Size( 534, 456 ),
    Show Control Panel( 0 ),
    Variables( X( :height ) ),
    Elements( Histogram( X, Legend( 3 ), Histogram Style( "Polygon" ), Counts( 1 ) ) ),
    SendToReport( Dispatch( {}, "", ScaleBox, {Reversed Scale} ) )
);
Graph Builder(
    Size( 534, 456 ),
    Show Control Panel( 0 ),
    Variables( X( :height ) ),
    Elements( Histogram( X, Legend( 3 ), Histogram Style( "Kernel Density" ) ) ),
    SendToReport( Dispatch( {}, "", ScaleBox, {Reversed Scale} ) )
);
Graph Builder(
    Size( 534, 456 ),
    Show Control Panel( 0 ),
    Variables( X( :height ) ),
    Elements( Histogram( X, Legend( 3 ), Histogram Style( "Shadowgram" ) ) ),
    SendToReport( Dispatch( {}, "", ScaleBox, {Reversed Scale} ) )
);

Code Explanation:

1. Open data table;
2. Create histogram for height.
3. Hide control panel.
4. Set scale reversed.
5. Create polygon histogram for height.
6. Hide control panel.
7. Set scale reversed.
8. Create kernel density histogram for height.
9. Hide control panel.
10. Set scale reversed.

Example 1375

Summary: Creates a Graph Builder window with box plots for height and weight, utilizing nested factors and operator configurations.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 534, 448 ),
    Show Control Panel( 0 ),
    Legend Position( "Inside Left" ),
    Variables( X( :age ), Y( :height ), Y( :weight ) ),
    Elements( Position( 1, 1 ), Box Plot( X, Y, Legend( 9 ) ) ),
    Elements( Position( 1, 2 ), Box Plot( X, Y, Legend( 10 ) ) )
);

Code Explanation:

1. Open data table.
2. Create Graph Builder window.
3. Set window size.
4. Hide control panel.
5. Position legend inside left.
6. Define X variable as age.
7. Define first Y variable as height.
8. Define second Y variable as weight.
9. Add box plot for height.
10. Add box plot for weight.

Example 1376

Summary: Creates a line graph to visualize the relationship between height and weight, utilizing Graph Builder with specified variables and elements.

Code:

Open("data_table.jmp");
Graph Builder(
    Show Control Panel( 0 ),
    Variables( X( :height ), Y( :weight ) ),
    Elements( Line( X, Y, Legend( 12 ), Smoothness( 0.5 ), Response Axis( "X" ) ) )
);

Code Explanation:

1. Open data_table data
2. Launch Graph Builder.
3. Hide control panel.
4. Set X variable to height.
5. Set Y variable to weight.
6. Add line element.
7. Assign legend index 12.
8. Set smoothness to 0.5.
9. Set response axis to X.
10. Display graph.

Example 1377

Summary: Creates a line chart with median summary statistic to visualize the relationship between height and weight, utilizing Graph Builder.

Code:

Open("data_table.jmp");
Graph Builder(
    Show Control Panel( 0 ),
    Variables( X( :height ), Y( :weight ) ),
    Elements( Line( X, Y, Legend( 12 ), Smoothness( 0.5 ), Response Axis( "Y" ), Summary Statistic( "Median" ) ) )
);

Code Explanation:

1. Open data table;
2. Launch Graph Builder.
3. Hide control panel.
4. Set X variable to height.
5. Set Y variable to weight.
6. Add line element.
7. Assign legend to group 12.
8. Set smoothness to 0.5.
9. Use Y axis for response.
10. Calculate median summary statistic.

Example 1378

Summary: Creates a line graph with nested factors using Graph Builder, displaying standard deviation charts for height and weight variables.

Code:

Open("data_table.jmp");
Graph Builder(
    Show Control Panel( 0 ),
    Variables( X( :height ), Y( :weight ) ),
    Elements( Line( X, Y, Legend( 12 ), Smoothness( 0.5 ), Response Axis( "Y" ), Summary Statistic( "N" ) ) )
);

Code Explanation:

1. Open data table;
2. Create graph builder object.
3. Hide control panel.
4. Set X variable to height.
5. Set Y variable to weight.
6. Add line element.
7. Assign legend to line.
8. Set smoothness to 0.5.
9. Specify response axis as Y.
10. Use summary statistic N.

Example 1379

Summary: Creates a line graph with nested factors using Graph Builder, displaying standard deviation charts.

Code:

Open("data_table.jmp");
Graph Builder( Show Control Panel( 0 ), Variables( X( :height ), Y( :weight ) ), Elements( Line( X, Y, Legend( 14 ), Row order( 1 ) ) ) );

Code Explanation:

1. Open data table;
2. Launch Graph Builder.
3. Hide control panel.
4. Set X variable to height.
5. Set Y variable to weight.
6. Add line element.
7. Assign legend to line.
8. Maintain row order.

Example 1380

Summary: Creates a line chart with nested factors using Graph Builder, displaying standard deviation charts for height and weight variables.

Code:

Open("data_table.jmp");
Graph Builder(
    Show Control Panel( 0 ),
    Variables( X( :height ), Y( :weight ) ),
    Elements( Line( X, Y, Legend( 14 ), Row order( 1 ), Connection( "Curve" ), Smoothness( 0.3211 ) ) )
);

Code Explanation:

1. Open data table;
2. Launch Graph Builder.
3. Hide control panel.
4. Set X variable to height.
5. Set Y variable to weight.
6. Add line element.
7. Use legend for element.
8. Order by row.
9. Connect points with curve.
10. Set smoothness to 0.3211.

Example 1381

Summary: Creates a line graph to visualize the relationship between age and weight, utilizing Graph Builder's Variables and Elements options.

Code:

Open("data_table.jmp");
Graph Builder( Show Control Panel( 0 ), Variables( X( :age ), Y( :weight ) ), Elements( Line( X, Y, Legend( 6 ) ) ) );

Code Explanation:

1. Open data table;
2. Launch Graph Builder.
3. Hide control panel.
4. Set X variable to age.
5. Set Y variable to weight.
6. Add line element.
7. Assign legend to line.
8. Position legend at index 6.

Example 1382

Summary: Creates a line chart with two Y variables, height and weight, using Graph Builder to visualize data from an open JMP data table.

Code:

Open("data_table.jmp");
Graph Builder(
    Show Control Panel( 0 ),
    Variables( X( :age ), Y( :height ), Y( :weight, Position( 1 ) ) ),
    Elements( Line( X, Y( 1 ), Y( 2 ), Legend( 7 ) ) )
);

Code Explanation:

1. Open data table.
2. Launch Graph Builder.
3. Hide control panel.
4. Set X variable to age.
5. Set Y variable to height.
6. Add weight as second Y variable.
7. Position weight on left axis.
8. Create line element.
9. Connect X to both Y variables.
10. Assign legend to line element.

Example 1383

Summary: Creates a variability chart with nested factors using Graph Builder, displaying standard deviation charts and utilizing operator and part configurations.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 570, 516 ),
    Show Control Panel( 0 ),
    Variables( X( :age ), Y( :height ), Y( :weight, Position( 1 ) ), Group X( :sex ) ),
    Elements( Line( X, Y( 1 ), Y( 2 ), Legend( 9 ) ) )
);

Code Explanation:

1. Open data table.
2. Create new Graph Builder window.
3. Set window size to 570x516.
4. Hide control panel.
5. Assign variables: age for X, height and weight for Y, sex for group X.
6. Add line element with age on X, height and weight on Y.
7. Position weight plot on top of height plot.
8. Assign legend ID 9 to elements.
9. Display graph builder window.

Example 1384

Summary: Creates a box plot variability chart with nested factors using Graph Builder, displaying standard deviation charts and legend.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 570, 516 ),
    Show Control Panel( 0 ),
    Variables( X( :age ), Y( :weight ), Overlay( :sex ) ),
    Elements( Box Plot( X, Y, Legend( 16 ) ) )
);

Code Explanation:

1. Open data table;
2. Launch Graph Builder.
3. Set window size.
4. Hide control panel.
5. Define X variable.
6. Define Y variable.
7. Define overlay variable.
8. Add box plot element.
9. Assign legend position.
10. Display graph.

Example 1385

Summary: Creates a variability chart with nested factors using Graph Builder, displaying standard deviation charts and configuring legend properties.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 570, 516 ),
    Show Control Panel( 0 ),
    Variables( X( :age ), Y( :weight ), Overlay( :sex ), Frequency( :height ) ),
    Elements( Line( X, Y, Legend( 22 ) ) ),
    SendToReport(
        Dispatch( {}, "400", ScaleBox, {Legend Model( 22, Properties( 1, {Line Color( 6 ), Fill Color( 6 ), Transparency( 0.5 )} ) )} )
    )
);

Code Explanation:

1. Open data table.
2. Create Graph Builder object.
3. Set graph size.
4. Hide control panel.
5. Define X, Y, overlay, frequency variables.
6. Add line element.
7. Send report message.
8. Dispatch to report.
9. Modify legend properties.
10. Set line color, fill color, transparency.

Example 1386

Summary: Creates a variability chart with nested factors using Graph Builder, displaying standard deviation charts and configuring size by age squared.

Code:

Open("data_table.jmp");
Graph Builder(
    Show Control Panel( 0 ),
    Variables(
        X( :age ),
        Y( :weight ),
        Color( :height ),
        Size( Transform Column( "age^2", Format( "Fixed Dec", 8, 0 ), Formula( :age * :age ) ) )
    ),
    Elements( Line( X, Y, Legend( 8 ), Smoothness( 0.6606 ) ) ),
    SendToReport( Dispatch( {}, "400", ScaleBox, {Legend Model( 8, Properties( 0, {Line Width( 5 )} ) )} ) )
);

Code Explanation:

1. Open data table;
2. Launch Graph Builder.
3. Hide control panel.
4. Set X variable to age.
5. Set Y variable to weight.
6. Color by height.
7. Size by age squared.
8. Add line element.
9. Smooth line with 66% smoothness.
10. Adjust legend line width to 5.

Example 1387

Summary: Creates a geographic map to visualize Napoleon's march to Moscow, utilizing Graph Builder and customizing scales, legend properties, and graph title.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 481, 190 ),
    Show Control Panel( 0 ),
    Variables( X( :Longitude ), Y( :Latitude ), Overlay( :Group ), Color( :Direction ), Size( :Army Size ) ),
    Elements( Line( X, Y, Legend( 3 ), Row order( 1 ) ) ),
    SendToReport(
        Dispatch( {}, "Longitude", ScaleBox,
            {Min( 26.7099056603774 ), Max( 34.9246254178505 ), Inc( 2.5 ), Minor Ticks( 0 ), Label Row( Show Major Grid( 1 ) )}
        ),
        Dispatch( {}, "Latitude", ScaleBox,
            {Min( 53.6765298707117 ), Max( 56.2548725683127 ), Inc( 0.5 ), Minor Ticks( 1 ), Label Row( Show Major Grid( 1 ) )}
        ),
        Dispatch( {}, "400", ScaleBox,
            {Legend Model(
                3,
                Properties( 0, {Line Width( 8 ), Marker Size( "XXL" )} ),
                Properties( 1, {Line Color( 70 )} ),
                Properties( 2, {Line Color( 1 )} )
            )}
        ),
        Dispatch( {}, "graph title", TextEditBox, {Set Text( "Napoleon's March to Moscow" )} )
    )
);

Code Explanation:

1. Open data file.
2. Create Graph Builder window.
3. Set window size.
4. Hide control panel.
5. Define X, Y, Overlay, Color, and Size variables.
6. Add Line element.
7. Configure Longitude scale.
8. Configure Latitude scale.
9. Customize legend properties.
10. Set graph title.

Example 1388

Summary: Creates a geographic map to visualize Napoleon's march to Moscow, utilizing Graph Builder and customizing scales, legend properties, and graph title.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 481, 190 ),
    Show Control Panel( 0 ),
    Variables( X( :Longitude ), Y( :Latitude ), Overlay( :Group ), Color( :Direction ), Size( :Army Size ) ),
    Elements( Line( X, Y, Legend( 3 ), Row order( 1 ), Missing Values( "No Connection" ) ) ),
    SendToReport(
        Dispatch( {}, "Longitude", ScaleBox,
            {Min( 26.7099056603774 ), Max( 34.9246254178505 ), Inc( 2.5 ), Minor Ticks( 0 ), Label Row( Show Major Grid( 1 ) )}
        ),
        Dispatch( {}, "Latitude", ScaleBox,
            {Min( 53.6765298707117 ), Max( 56.2548725683127 ), Inc( 0.5 ), Minor Ticks( 1 ), Label Row( Show Major Grid( 1 ) )}
        ),
        Dispatch( {}, "400", ScaleBox,
            {Legend Model(
                3,
                Properties( 0, {Line Width( 8 ), Marker Size( "XXL" )} ),
                Properties( 1, {Line Color( 70 )} ),
                Properties( 2, {Line Color( 1 )} )
            )}
        ),
        Dispatch( {}, "graph title", TextEditBox, {Set Text( "Napoleon's March to Moscow" )} )
    )
);

Code Explanation:

1. Open data table;
2. Create Graph Builder window.
3. Set window size.
4. Hide control panel.
5. Define X, Y, Overlay, Color, and Size variables.
6. Add line element to graph.
7. Configure Longitude scale.
8. Configure Latitude scale.
9. Customize legend properties.
10. Set graph title.

Example 1389

Summary: Creates a geographic map to visualize Napoleon's march to Moscow, utilizing Graph Builder and customizing scale properties, legend, and graph title.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 685, 344 ),
    Show Control Panel( 0 ),
    Variables( X( :Longitude ), Y( :Latitude ), Overlay( :Group ), Color( :Direction ), Size( :Army Size ) ),
    Elements( Line( X, Y, Legend( 3 ), Row order( 1 ), Missing Values( "No Connection" ) ) ),
    SendToReport(
        Dispatch( {}, "Longitude", ScaleBox,
            {Min( 26.7099056603774 ), Max( 34.9246254178505 ), Inc( 2.5 ), Minor Ticks( 0 ), Label Row( Show Major Grid( 1 ) )}
        ),
        Dispatch( {}, "Latitude", ScaleBox,
            {Min( 53.0756478118985 ), Max( 56.8557546271259 ), Inc( 0.5 ), Minor Ticks( 1 ), Label Row( Show Major Grid( 1 ) )}
        ),
        Dispatch( {}, "400", ScaleBox,
            {Legend Model(
                3,
                Properties( 0, {Line Width( 15 ), Marker Size( "XXL" )} ),
                Properties( 1, {Line Color( 70 )} ),
                Properties( 2, {Line Color( 16 )} )
            )}
        ),
        Dispatch( {}, "graph title", TextEditBox, {Set Text( "Napoleon's March to Moscow" )} ),
        Dispatch( {}, "Graph Builder", FrameBox,
            {Background Map( Images( "Simple Earth" ) ), Grid Line Order( 2 ), Reference Line Order( 3 )}
        )
    )
);

Code Explanation:

1. Open data table.
2. Create Graph Builder window.
3. Set window size.
4. Hide control panel.
5. Define X, Y, Overlay, Color, and Size variables.
6. Add line element to graph.
7. Set Longitude scale properties.
8. Set Latitude scale properties.
9. Customize legend properties.
10. Set graph title.
11. Add background map and grid lines.

Example 1390

Summary: Creates a variability chart with nested factors using Graph Builder, displaying standard deviation charts and customizing legend positions.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 570, 489 ),
    Show Control Panel( 0 ),
    Variables( X( :age ), Y( :height ), Overlay( :sex ) ),
    Elements( Line( X, Y, Legend( 3 ) ), Points( X, Y, Legend( 4 ) ) ),
    SendToReport(
        Dispatch( {}, "400", ScaleBox,
            {Legend Model( 3, Properties( 1, {Marker( "Plus" ), Marker Size( 4 ), Fill Color( 0 )} ) ),
            Legend Model( 4, Base( 0, 0, 0 ), Base( 1, 0, 1 ), Properties( 0, {Marker( "Plus" )} ), Properties( 1, {Marker( "Square" )} ) )
            }
        ),
        Dispatch( {}, "400", LegendBox, {Legend Position( {2, 3, 0, 1} )} )
    )
);

Code Explanation:

1. Open data table;
2. Create graph builder window.
3. Set window size.
4. Hide control panel.
5. Define variables for graph.
6. Add line element to graph.
7. Add points element to graph.
8. Customize legend for lines.
9. Customize legend for points.
10. Adjust legend position.

Example 1391

Summary: Creates a variability chart with nested factors using operator and part configurations, displaying standard deviation charts in Graph Builder.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 422, 207 ),
    Show Control Panel( 0 ),
    Variables( X( :age ), Y( :height ), Overlay( :sex ), Color( :age ) ),
    Elements( Line( X, Y, Legend( 3 ) ) ),
    SendToReport(
        Dispatch( {}, "400", LegendBox, {Legend Position( {3, [-1, -1, -1, -1, -1, -1]} ), Position( {-1, -1, -1, -1, -1, -1} )} )
    )
);

Code Explanation:

1. Open data table.
2. Launch Graph Builder.
3. Set graph size.
4. Hide control panel.
5. Define variables: X, Y, Overlay, Color.
6. Add line element.
7. Customize legend position.
8. Adjust legend position.
9. Finalize report settings.

Example 1392

Summary: Creates a graph builder window with a line and points element to visualize the relationship between weight and age, utilizing Graph Builder.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 524, 454 ),
    Show Control Panel( 0 ),
    Variables( X( :weight ), Y( :age ) ),
    Elements( Line( X, Y, Legend( 6 ), Connection( "Centered Step" ) ), Points( X, Y, Legend( 7 ), Summary Statistic( "Mean" ) ) )
);

Code Explanation:

1. Open data table;
2. Create graph builder window.
3. Set graph size.
4. Hide control panel.
5. Assign weight to X-axis.
6. Assign age to Y-axis.
7. Add centered step line element.
8. Add points element.
9. Calculate mean for points.
10. Display graph.

Example 1393

Summary: Creates a variability chart with nested factors using operator and part configurations, displaying standard deviation charts in JMP.

Code:

Open("data_table.jmp");
Graph Builder( Show Control Panel( 0 ), Variables( X( :height ), Y( :weight ) ), Elements( Line( X, Y, Legend( 12 ) ) ) );
Graph Builder(
    Show Control Panel( 0 ),
    Variables( X( :height ), Y( :weight ) ),
    Elements( Line( X, Y, Legend( 12 ), Connection( "Curve" ), Smoothness( 0.5 ) ) )
);
Graph Builder(
    Show Control Panel( 0 ),
    Variables( X( :height ), Y( :weight ) ),
    Elements( Line( X, Y, Legend( 12 ), Connection( "Step" ), Smoothness( 0.5 ) ) )
);
Graph Builder(
    Show Control Panel( 0 ),
    Variables( X( :height ), Y( :weight ) ),
    Elements( Line( X, Y, Legend( 12 ), Connection( "Horizontal" ), Smoothness( 0.5 ) ) )
);

Code Explanation:

1. Open data table.
2. Create initial line graph.
3. Modify graph with curved connection.
4. Modify graph with step connection.
5. Modify graph with horizontal connection.

Example 1394

Summary: Creates a line graph with varying connection types (curve, step, horizontal, and vertical) for height vs. weight data using Graph Builder in JMP.

Code:

Open("data_table.jmp");
Graph Builder( Show Control Panel( 0 ), Variables( X( :height ), Y( :weight ) ), Elements( Line( X, Y, Legend( 12 ) ) ) );
Graph Builder(
    Show Control Panel( 0 ),
    Variables( X( :height ), Y( :weight ) ),
    Elements( Line( X, Y, Legend( 12 ), Connection( "Curve" ), Smoothness( 0.5 ) ) )
);
Graph Builder(
    Show Control Panel( 0 ),
    Variables( X( :height ), Y( :weight ) ),
    Elements( Line( X, Y, Legend( 12 ), Connection( "Step" ), Smoothness( 0.5 ) ) )
);
Graph Builder(
    Show Control Panel( 0 ),
    Variables( X( :height ), Y( :weight ) ),
    Elements( Line( X, Y, Legend( 12 ), Connection( "Horizontal" ), Smoothness( 0.5 ) ) )
);
Graph Builder(
    Show Control Panel( 0 ),
    Variables( X( :height ), Y( :weight ) ),
    Elements( Line( X, Y, Legend( 12 ), Connection( "Vertical" ), Smoothness( 0.5 ) ) )
);

Code Explanation:

1. Open data table;
2. Create initial graph builder.
3. Add line element without curve.
4. Create second graph builder.
5. Add line element with curve connection.
6. Create third graph builder.
7. Add line element with step connection.
8. Create fourth graph builder.
9. Add line element with horizontal connection.
10. Create fifth graph builder.
11. Add line element with vertical connection.

Example 1395

Summary: Creates a variability chart with nested factors using Graph Builder, displaying standard deviation charts and handling missing values.

Code:

Open("data_table.jmp") << Graph Builder(
    Size( 300, 200 ),
    Show Control Panel( 0 ),
    Variables( X( :weight ), Y( :height ), Overlay( :sex ) ),
    Elements(
        Line(
            X,
            Y,
            Legend( 1 ),
            Summary Statistic( "N" ),
            Fill( "Fill Below" ),
            Missing Factors( "Treat as Missing" ),
            Missing Values( "Connect Through" )
        )
    )
);

Code Explanation:

1. Open data table;
2. Create graph builder window.
3. Set window size.
4. Hide control panel.
5. Define X and Y variables.
6. Add overlay variable.
7. Add line element.
8. Specify summary statistic.
9. Enable fill below.
10. Handle missing factors.

Example 1396

Summary: Creates a line chart with nested factors using Graph Builder, displaying standard deviation charts and handling missing values.

Code:

Open("data_table.jmp") << Graph Builder(
    Size( 300, 200 ),
    Show Control Panel( 0 ),
    Variables( X( :weight ), Y( :height ), Overlay( :sex ) ),
    Elements(
        Line(
            X,
            Y,
            Legend( 1 ),
            Summary Statistic( "N" ),
            Fill( "Fill Below" ),
            Missing Factors( "Treat as Missing" ),
            Missing Values( "No Connection" )
        )
    )
);

Code Explanation:

1. Open data table.
2. Launch Graph Builder.
3. Set window size.
4. Hide control panel.
5. Define X and Y variables.
6. Add overlay variable.
7. Add line element.
8. Set summary statistic to count.
9. Enable fill below line.
10. Handle missing factors as missing.

Example 1397

Summary: Creates a variability chart with nested factors using Graph Builder, displaying standard deviation charts and error bars.

Code:

Open("data_table.jmp");
Graph Builder(
    Show Control Panel( 0 ),
    Variables( X( :sector ), X( :time of day, Position( 1 ) ), Y( :fahrenheit ) ),
    Elements( Line( X( 1 ), X( 2 ), Y, Legend( 4 ), Row order( 0 ), Summary Statistic( "Mean" ), Error Bars( "Range" ) ) )
);

Code Explanation:

1. Open data table;
2. Launch Graph Builder.
3. Hide control panel.
4. Set X variable: sector.
5. Set second X variable: time of day.
6. Set Y variable: fahrenheit.
7. Add line element.
8. Connect first X to line.
9. Connect second X to line.
10. Display mean summary statistic.
11. Show range error bars.

Example 1398

Summary: Creates two Graph Builder windows to visualize the relationship between age, weight, and height using line elements with standard error intervals in band and hash styles.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 534, 450 ),
    Show Control Panel( 0 ),
    Variables( X( :age ), Y( :weight ), Size( :height ) ),
    Elements( Line( X, Y, Legend( 5 ), Error Interval( "Standard Error" ), Interval Style( "Band" ) ) )
);
Graph Builder(
    Size( 534, 450 ),
    Show Control Panel( 0 ),
    Variables( X( :age ), Y( :weight ), Size( :height ) ),
    Elements( Line( X, Y, Legend( 5 ), Error Interval( "Standard Error" ), Interval Style( "Hash Band" ) ) )
);

Code Explanation:

1. Open data table.
2. Create first Graph Builder window.
3. Set window size.
4. Hide control panel.
5. Define X, Y, and Size variables.
6. Add line element with legend.
7. Enable standard error interval.
8. Use band interval style.
9. Create second Graph Builder window.
10. Repeat steps 3-8 for hash band style.

Example 1399

Summary: Creates a variability chart with nested factors using operator and part configurations, displaying standard deviation charts in Graph Builder.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 548, 494 ),
    Show Control Panel( 0 ),
    Variables( X( :Date ), Y( :Price ), Overlay( :Series ) ),
    Elements( Smoother( X, Y, Legend( 18 ) ) ),
    Local Data Filter(
        Add Filter(
            columns( :Series, :Year ),
            Where( :Series == {"Apples", "Bananas", "Bread", "Chicken"} ),
            Where( :Year >= 1991.762 & :Year <= 2003.988 ),
            Display( :Series, N Items( 15 ) )
        )
    ),
    SendToReport(
        Dispatch( {}, "400", ScaleBox,
            {Legend Model(
                18,
                Properties( 0, {Line Label Properties( {Name Label( 1 ), Last Label( 1 ), Width( 9 )} )}, Item ID( "Apples", 1 ) ),
                Properties( 1, {Line Label Properties( {Name Label( 1 ), Last Label( 1 ), Width( 9 )} )}, Item ID( "Bananas", 1 ) ),
                Properties( 2, {Line Label Properties( {Name Label( 1 ), Last Label( 1 ), Width( 9 )} )}, Item ID( "Bread", 1 ) ),
                Properties( 3, {Line Label Properties( {Name Label( 1 ), Last Label( 1 ), Width( 9 )} )}, Item ID( "Chicken", 1 ) )
            )}
        )
    )
);

Code Explanation:

1. Open data table;
2. Create Graph Builder window.
3. Set graph size.
4. Hide control panel.
5. Define X, Y, and overlay variables.
6. Add smoother element.
7. Initialize local data filter.
8. Add filter for specific series.
9. Add filter for year range.
10. Customize legend labels.

Example 1400

Summary: Creates a variability chart with nested factors using Graph Builder, configuring line elements and displaying standard deviation charts.

Code:

Open("data_table.jmp");
Graph Builder(
    Show Control Panel( 0 ),
    Variables( X( :weight ), Y( :height ), Color( :age ) ),
    Elements( Line( X, Y, Legend( 3 ), Row order( 0 ), Summary Statistic( "Mean" ) ) ),
    SendToReport(
        Dispatch( {}, "400", ScaleBox,
            {Legend Model(
                3,
                Properties( 1, {Line Width( 5 )} ),
                Properties( 2, {Line Width( 1 )} ),
                Properties( 3, {Line Width( 4 )} ),
                Properties( 4, {Line Width( 6 )} ),
                Properties( 5, {Line Width( 3 )} )
            )}
        )
    )
);

Code Explanation:

1. Open data table.
2. Create Graph Builder.
3. Hide control panel.
4. Set X variable to weight.
5. Set Y variable to height.
6. Set color variable to age.
7. Add line element.
8. Configure line legend.
9. Set row order to original.
10. Use mean summary statistic.

Example 1401

Summary: Creates a line graph with nested factors using Graph Builder, displaying age on the X-axis, height on the Y-axis, and color-coded by weight.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 525, 448 ),
    Show Control Panel( 0 ),
    Variables( X( :age ), Y( :height ), Color( :weight ) ),
    Elements( Line( X, Y, Legend( 13 ) ) )
);

Code Explanation:

1. Open data table.
2. Launch Graph Builder.
3. Set window size.
4. Hide control panel.
5. Assign variables.
6. Add line element.
7. Use age for X-axis.
8. Use height for Y-axis.
9. Color by weight.
10. Display legend.

Example 1402

Summary: Creates a variability chart with nested factors using operator and part configurations, displaying standard deviation charts in JMP.

Code:

Open("data_table.jmp");
Graph Builder(
    Show Control Panel( 0 ),
    Variables( X( :name ), Y( :weight ), Y( :height ), Overlay( :sex ) ),
    Elements( Position( 1, 1 ), Line( X, Y, Legend( 6 ) ) ),
    Elements( Position( 1, 2 ), Line( X, Y, Legend( 5 ) ) ),
    SendToReport(
        Dispatch( {}, "400", ScaleBox,
            {Legend Model(
                6,
                Properties( 0, {Line Color( 1 ), Line Width( 4 )}, Item ID( "F", 1 ) ),
                Properties( 1, {Line Style( "Dotted" )}, Item ID( "M", 1 ) )
            )}
        )
    )
);

Code Explanation:

1. Open data table.
2. Create Graph Builder.
3. Hide control panel.
4. Set X variable.
5. Set first Y variable.
6. Set second Y variable.
7. Overlay by sex.
8. Add first line element.
9. Add second line element.
10. Customize line colors, widths, and styles.

Example 1403

Summary: Creates a variability chart with nested factors using Graph Builder, displaying standard deviation charts and various summary statistics.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 651, 443 ),
    Show Control Panel( 0 ),
    Variables(
        X( :age ),
        X( :age ),
        X( :age ),
        X( :age ),
        X( :age ),
        X( :age ),
        X( :age ),
        X( :age ),
        X( :age ),
        X( :age ),
        X( :age ),
        X( :age ),
        X( :age ),
        X( :age ),
        X( :age ),
        Y( :height )
    ),
    Elements( Position( 1, 1 ), Line( X, Y, Legend( 15 ), Summary Statistic( "N" ) ) ),
    Elements( Position( 2, 1 ), Line( X, Y, Legend( 16 ) ) ),
    Elements( Position( 3, 1 ), Line( X, Y, Legend( 17 ), Summary Statistic( "Median" ) ) ),
    Elements( Position( 4, 1 ), Line( X, Y, Legend( 18 ), Summary Statistic( "Geometric Mean" ) ) ),
    Elements( Position( 5, 1 ), Line( X, Y, Legend( 19 ), Summary Statistic( "Min" ) ) ),
    Elements( Position( 6, 1 ), Line( X, Y, Legend( 20 ), Summary Statistic( "Max" ) ) ),
    Elements( Position( 7, 1 ), Line( X, Y, Legend( 21 ), Summary Statistic( "Range" ) ) ),
    Elements( Position( 8, 1 ), Line( X, Y, Legend( 37 ), Summary Statistic( "Sum" ) ) ),
    Elements( Position( 9, 1 ), Line( X, Y, Legend( 38 ), Summary Statistic( "% of Total" ) ) ),
    Elements( Position( 10, 1 ), Line( X, Y, Legend( 39 ), Summary Statistic( "Std Dev" ) ) ),
    Elements( Position( 11, 1 ), Line( X, Y, Legend( 40 ), Summary Statistic( "Variance" ) ) ),
    Elements( Position( 12, 1 ), Line( X, Y, Legend( 41 ), Summary Statistic( "Std Err" ) ) ),
    Elements( Position( 13, 1 ), Line( X, Y, Legend( 42 ), Summary Statistic( "Interquartile Range" ) ) ),
    Elements( Position( 14, 1 ), Line( X, Y, Legend( 43 ), Summary Statistic( "First Quartile" ) ) ),
    Elements( Position( 15, 1 ), Line( X, Y, Legend( 44 ), Summary Statistic( "Third Quartile" ) ) )
);

Code Explanation:

1. Open data_table data
2. Create Graph Builder window.
3. Set graph size.
4. Hide control panel.
5. Assign X variable: age.
6. Assign Y variable: height.
7. Add N summary statistic line.
8. Add standard line.
9. Add median summary statistic line.
10. Add geometric mean summary statistic line.
11. Add minimum summary statistic line.
12. Add maximum summary statistic line.
13. Add range summary statistic line.
14. Add sum summary statistic line.
15. Add % of Total summary statistic line.
16. Add Std Dev summary statistic line.
17. Add Variance summary statistic line.
18. Add Std Err summary statistic line.
19. Add Interquartile Range summary statistic line.
20. Add First Quartile summary statistic line.
21. Add Third Quartile summary statistic line.

Example 1404

Summary: Creates a variability chart with nested factors using operator and part configurations, displaying standard deviation charts in JMP.

Code:

Open("data_table.jmp");
Graph Builder(
    Show Control Panel( 0 ),
    Variables( X( :NPN2 ), X( :PNP3, Position( 1 ) ), Y( :NPN1 ), Y( :PNP1, Position( 1 ) ), Y( :PNP2, Position( 1 ) ) ),
    Elements( Line( X( 1 ), X( 2 ), Y( 1 ), Y( 2 ), Y( 3 ), Legend( 3 ), Row order( 0 ), Summary Statistic( "Mean" ) ) )
);
Graph Builder(
    Show Control Panel( 0 ),
    Variables( X( :NPN2 ), X( :PNP3, Position( 1 ) ), Y( :NPN1 ), Y( :PNP1, Position( 1 ) ), Y( :PNP2, Position( 1 ) ) ),
    Elements(
        Line( X( 1 ), X( 2 ), Y( 1 ), Y( 2 ), Y( 3 ), Legend( 3 ), Row order( 0 ), Summary Statistic( "Mean" ) ),
        Points( X( 1 ), X( 2 ), Y( 1 ), Y( 2 ), Y( 3 ), Legend( 4 ), Jitter( 1 ) ),
        Smoother( X( 1 ), X( 2 ), Y( 1 ), Y( 2 ), Y( 3 ), Legend( 5 ) )
    )
);

Code Explanation:

1. Open data table;
2. Create first Graph Builder window.
3. Hide control panel.
4. Set X variables: NPN2, PNP3.
5. Set Y variables: NPN1, PNP1, PNP2.
6. Add line element.
7. Configure line element settings.
8. Create second Graph Builder window.
9. Hide control panel.
10. Set same variables and elements.

Example 1405

Summary: Creates a variability chart with nested factors using Graph Builder, displaying standard deviation charts and color-coded by Position2.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 562, 366 ),
    Show Control Panel( 0 ),
    Variables( X( :Weight ), Y( :Speed2 ), Group X( :LegPress ), Overlay( :Position2 ), Color( :Position2 ) ),
    Elements( Line( X, Y, Legend( 12 ) ) ),
    SendToReport(
        Dispatch( {}, "Speed2", ScaleBox,
            {Scale( "Log" ), Format( "Best", 10 ), Min( 1.41531244764617 ), Max( 2 ), Inc( 1 ), Minor Ticks( 1 )}
        )
    )
);

Code Explanation:

1. Open data_table data
2. Create Graph Builder window.
3. Set window size 562x366.
4. Hide control panel.
5. Assign variables: X=Weight, Y=Speed2.
6. Group X by LegPress.
7. Overlay by Position2.
8. Color by Position2.
9. Add Line element.
10. Log-scale Speed2 axis.

Example 1406

Summary: Creates a variability chart with nested factors using Graph Builder, displaying standard deviation charts and utilizing operator and part configurations.

Code:

Open("data_table.jmp");
Graph Builder(
    Show Control Panel( 0 ),
    Overlay Auto Line Styles Limit( 0 ),
    Variables( X( :Weight ), Y( :Height ), Overlay( :sex ), Color( :Age ) ),
    Elements( Line( X, Y ) )
);

Code Explanation:

1. Open data table.
2. Launch Graph Builder.
3. Hide control panel.
4. Set overlay auto line styles limit.
5. Define X variable.
6. Define Y variable.
7. Define overlay variable.
8. Define color variable.
9. Add line element.
10. Display graph.

Example 1407

Summary: Creates two Graph Builder windows with nested factors, displaying line elements and standard deviation charts.

Code:

Open("data_table.jmp");
Graph Builder( Show Control Panel( 0 ), Variables( Y( :height ) ), Elements( Line( Y, Legend( 3 ) ) ) );
Graph Builder( Show Control Panel( 0 ), Variables( Y( :height ), Overlay( :sex ) ), Elements( Line( Y, Legend( 5 ) ) ) );

Code Explanation:

1. Open data table;
2. Create Graph Builder window.
3. Hide control panel.
4. Set Y variable to height.
5. Add line element.
6. Assign legend to line.
7. Create second Graph Builder window.
8. Hide control panel.
9. Set Y variable to height.
10. Overlay by sex variable.

Example 1408

Summary: Creates three line graphs to visualize height data, with nested factors for age and sex, using Graph Builder in JMP.

Code:

Open("data_table.jmp");
Graph Builder( Show Control Panel( 0 ), Variables( Y( :height ) ), Elements( Line( Y, Legend( 3 ) ) ) );
Graph Builder( Show Control Panel( 0 ), Variables( Y( :height ), Overlay( :sex ) ), Elements( Line( Y, Legend( 5 ) ) ) );
Graph Builder(
    Show Control Panel( 0 ),
    Variables( Y( :height ), Group X( :age ), Group Y( :sex ), Overlay( :sex ) ),
    Elements( Line( Y, Legend( 5 ) ) )
);

Code Explanation:

1. Open data table;
2. Create line graph for height.
3. Create line graph for height by sex.
4. Create grouped line graph for height by age and sex.

Example 1409

Summary: Creates a variability chart with nested factors using Graph Builder, displaying standard deviation charts and utilizing operator and part configurations.

Code:

Open("data_table.jmp") << Graph Builder(
    Show Control Panel( 0 ),
    Variables(
        X( :Age, Combine( "Parallel Merged" ) ),
        X( :Fare, Position( 1 ), Combine( "Parallel Merged" ) ),
        Group X( :Survived ),
        Color( :Sex )
    ),
    Elements( Line( X( 1 ), X( 2 ), Legend( 3 ), Error Interval( "Confidence Interval" ) ) ), 
);

Code Explanation:

1. Open data table;
2. Initiate Graph Builder.
3. Hide control panel.
4. Set Age as X variable.
5. Merge Age parallel.
6. Set Fare as X variable.
7. Position Fare at 1.
8. Merge Fare parallel.
9. Group by Survived.
10. Color by Sex.

Example 1410

Summary: Creates a variability chart with nested factors using operator and part configurations, displaying standard deviation charts.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 536, 452 ),
    Show Control Panel( 0 ),
    Parallel Axes( "Y Only" ),
    Variables( X( :Color ), Y( :Table ), Y( :Depth ) ),
    Elements( Position( 1, 1 ), Line( X, Y, Legend( 19 ) ) ),
    Elements( Position( 1, 2 ), Line( X, Y, Legend( 20 ) ) ),
    SendToReport(
        Dispatch( {}, "400", ScaleBox,
            {Legend Model( 19, Properties( 0, {Line Color( 76 )}, Item ID( "Mean(Table)", 1 ) ) ),
            Legend Model( 20, Properties( 0, {Line Color( 74 )}, Item ID( "Mean(Depth)", 1 ) ) )}
        ),
        Dispatch( {}, "Table", TextEditBox, {Text Color( "Light YellowGreen" ), Font Color( 76 )} ),
        Dispatch( {}, "Depth", TextEditBox, {Text Color( "Light Cyan" ), Font Color( 74 )} )
    )
);

Code Explanation:

1. Open data table;
2. Create Graph Builder.
3. Set size 536x452.
4. Hide control panel.
5. Enable parallel axes.
6. Set X variable: Color.
7. Set Y variables: Table, Depth.
8. Add line element for Table.
9. Add line element for Depth.
10. Customize legend colors and text colors.

Example 1411

Summary: Creates a variability chart with nested factors using Graph Builder, displaying standard deviation charts and utilizing operator and part configurations.

Code:

Open("data_table.jmp");
Graph Builder( Size( 528, 448 ), Show Control Panel( 0 ), Variables( X( :age ), Size( :sex ) ), Elements( Line( X, Legend( 2 ) ) ) );

Code Explanation:

1. Open data table.
2. Launch Graph Builder.
3. Set window size.
4. Hide control panel.
5. Assign X variable.
6. Size by sex variable.
7. Add line element.
8. Use legend for groups.

Example 1412

Summary: Creates a graph builder window with a line element to visualize the relationship between Sepal width and Petal width, while also overlaying Petal length.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 359, 360 ),
    Show Control Panel( 0 ),
    Show Legend( 0 ),
    Variables( X( :Sepal width ), Y( :Petal width ), Overlay( :Petal length ) ),
    Elements( Line( X, Y, Legend( 4 ) ) )
);

Code Explanation:

1. Open data table;
2. Create Graph Builder window.
3. Set window size.
4. Hide control panel.
5. Hide legend.
6. Define X variable.
7. Define Y variable.
8. Define overlay variable.
9. Add line element.
10. Assign legend to line.

Example 1413

Summary: Creates a variability chart with nested factors using operator and part configurations, displaying standard deviation charts in Graph Builder.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 554, 370 ),
    Show Control Panel( 0 ),
    Variables( X( :height ), X( :height ), Y( :weight ) ),
    Elements(
        Position( 1, 1 ),
        Line( X, Y, Legend( 9 ), Summary Statistic( "N" ) ),
        Points( X, Y, Legend( 10 ), Summary Statistic( "N" ) )
    ),
    Elements( Position( 2, 1 ), Line( X, Y, Legend( 5 ) ), Points( X, Y, Legend( 6 ) ) ),
    SendToReport(
        Dispatch( {}, "weight", ScaleBox, {Scale( "Log" ), Format( "Best", 12 ), Min( 0.1 ), Max( 600 ), Inc( 1 ), Minor Ticks( 1 )} ),
        Dispatch( {}, "400", ScaleBox, {Legend Model( 10, Base( 0, 0, 0 ) )} )
    )
);

Code Explanation:

1. Open data table;
2. Create Graph Builder window.
3. Set graph size.
4. Hide control panel.
5. Define X and Y variables.
6. Add line element.
7. Add points element.
8. Duplicate elements for second row.
9. Apply log scale to weight axis.
10. Adjust legend settings.

Example 1414

Summary: Creates a variability chart with nested factors using Graph Builder, displaying standard deviation charts and overlaying by sex.

Code:

Open("data_table.jmp") << Graph Builder(
    Size( 421, 204 ),
    Show Control Panel( 0 ),
    Variables( X( :age ), Y( :height ), Overlay( :sex ) ),
    Elements( Line( Legend( 5 ) ) )
);

Code Explanation:

1. Open data table;
2. Create Graph Builder window.
3. Set size to 421x204.
4. Hide control panel.
5. Set X variable to age.
6. Set Y variable to height.
7. Overlay by sex.
8. Add line element.
9. Assign legend to group 5.

Example 1415

Summary: Creates a variability chart with nested factors using Graph Builder, displaying standard deviation charts and enabling legend.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 570, 516 ),
    Show Control Panel( 0 ),
    Variables( X( :age ), Y( :weight ), Overlay( :sex ) ),
    Elements( Line( X, Y, Legend( 15 ) ) )
);

Code Explanation:

1. Open data_table data
2. Launch Graph Builder.
3. Set window size.
4. Hide control panel.
5. Assign variables.
6. Add line element.
7. Enable legend.

Example 1416

Summary: Creates a variability chart with nested factors using operator and part configurations, displaying standard deviation charts in Graph Builder.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 534, 453 ),
    Show Control Panel( 0 ),
    Variables( X( :height ), Y( :weight ), Color( :sex ) ),
    Elements( Line( X, Y, Legend( 10 ), Row order( 1 ) ) ),
    SendToReport(
        Dispatch( {}, "400", ScaleBox,
            {Legend Model(
                10,
                Properties( 0, {Transparency( 0.75 )}, Item ID( "F", 1 ) ),
                Properties( 1, {Transparency( 0.1 )}, Item ID( "M", 1 ) )
            )}
        )
    )
);

Code Explanation:

1. Open data table;
2. Launch Graph Builder.
3. Set graph size.
4. Hide control panel.
5. Assign variables: height, weight, sex.
6. Add line element.
7. Configure legend properties.
8. Adjust transparency for females.
9. Adjust transparency for males.
10. Send report settings.

Example 1417

Summary: Configures a Graph Builder to visualize the relationship between 'X' and 'Y' variables, calculating 'dx' and 'dy' values using least squares solve and displaying them as lines on a graph.

Code:

Open("data_table.jmp");
Graph Builder(
    Show Control Panel( 0 ),
    Transform Column(
        "dy",
        Formula(
            Local( {est, err, near, xx = :x, yy = :y},
                near = Where( Abs( :X - xx ) <= 25 & Abs( :Y - yy ) <= 40 );
                {est, err} = Least Squares Solve( :Z[near], :X[near] || :Y[near] );
                est[3] * 100;
            )
        )
    ),
    Transform Column(
        "dx",
        Formula(
            Local( {est, err, near, xx = :x, yy = :y},
                near = Where( Abs( :X - xx ) <= 25 & Abs( :Y - yy ) <= 40 );
                {est, err} = Least Squares Solve( :Z[near], :X[near] || :Y[near] );
                est[2] * 100;
            )
        )
    ),
    Size( 601, 601 ),
    Variables( X( :X ), Y( :Y ), Interval( :dx ), Interval( :dy ) ),
    Elements( Line( X, Y, Legend( 2 ), Ordering( "Within Row" ), Connection( "Arrow" ) ) )
);

Code Explanation:

1. Open data table;
2. Create new column "dy".
3. Define formula for "dy".
4. Identify nearby points.
5. Perform least squares solve.
6. Calculate "dy" value.
7. Create new column "dx".
8. Define formula for "dx".
9. Identify nearby points.
10. Perform least squares solve.
11. Calculate "dx" value.
12. Configure Graph Builder.
13. Set size.
14. Assign variables.
15. Add line element.

Example 1418

Summary: Creates a variability chart with nested factors using Graph Builder, displaying standard deviation charts and enabling jitter for points.

Code:

Open("data_table.jmp");
Graph Builder(
    Show Control Panel( 0 ),
    Variables( X( :Type ), Y( :Name( "Sales($M)" ) ), Y( :Name( "Assets($Mil.)" ), Position( 1 ) ) ),
    Elements(
        Line( X, Y( 1 ), Y( 2 ), Legend( 6 ), Row order( 0 ), Summary Statistic( "Mean" ) ),
        Points( X, Y( 1 ), Y( 2 ), Legend( 7 ), Jitter( 1 ), Summary Statistic( "Mean" ) )
    )
);

Code Explanation:

1. Open data table;
2. Create Graph Builder window.
3. Hide control panel.
4. Set X variable to Type.
5. Set Y1 variable to Sales($M).
6. Set Y2 variable to Assets($Mil.), position 1.
7. Add Line element for Y1 and Y2.
8. Use Mean summary statistic for lines.
9. Add Points element for Y1 and Y2.
10. Enable jitter for points, use Mean summary statistic.

Example 1419

Summary: Creates a line graph with nested factors using Graph Builder, displaying standard deviation charts and overlaying data by sex.

Code:

Open("data_table.jmp");
Graph Builder(
    Show Control Panel( 0 ),
    Variables( X( :age ), Y( :weight ), Overlay( :sex ) ),
    Elements( Line( X, Y, Legend( 1 ), Smoothness( 0.5 ) ) )
);

Code Explanation:

1. Open data table.
2. Launch Graph Builder.
3. Hide control panel.
4. Set X variable to age.
5. Set Y variable to weight.
6. Overlay by sex.
7. Add line element.
8. Apply legend to first overlay.
9. Set line smoothness to 0.5.

Example 1420

Summary: Creates a line graph with nested factors using Graph Builder, displaying the relationship between age and weight while overlaying by sex.

Code:

Open("data_table.jmp");
Graph Builder(
    Show Control Panel( 0 ),
    Variables( X( :age ), Y( :weight ), Overlay( :sex ) ),
    Elements( Line( X, Y, Legend( 1 ), Connection( "Curve" ), Smoothness( 0.5 ) ) )
);

Code Explanation:

1. Open data table;
2. Launch Graph Builder.
3. Hide control panel.
4. Set X variable to age.
5. Set Y variable to weight.
6. Overlay by sex.
7. Add line element.
8. Connect points with curve.
9. Set smoothness to 0.5.
10. Display graph.

Example 1421

Summary: Creates a line graph with nested factors using Graph Builder, displaying standard deviation charts and overlaying sex as a categorical variable.

Code:

Open("data_table.jmp");
Graph Builder(
    Show Control Panel( 0 ),
    Variables( X( :age ), Y( :weight ), Overlay( :sex ) ),
    Elements( Line( X, Y, Legend( 1 ), Connection( "Step" ), Smoothness( 0.5 ) ) )
);

Code Explanation:

1. Open data table;
2. Launch Graph Builder.
3. Hide control panel.
4. Set X variable to age.
5. Set Y variable to weight.
6. Use sex for overlay.
7. Add line element.
8. Connect points with steps.
9. Apply 50% smoothness.
10. Display graph.

Example 1422

Summary: Creates a line graph with horizontal connections to visualize the relationship between age and weight, overlayed by sex using Graph Builder.

Code:

Open("data_table.jmp");
Graph Builder(
    Show Control Panel( 0 ),
    Variables( X( :age ), Y( :weight ), Overlay( :sex ) ),
    Elements( Line( X, Y, Legend( 1 ), Connection( "Horizontal" ), Smoothness( 0.5 ) ) )
);

Code Explanation:

1. Open data table.
2. Launch Graph Builder.
3. Hide control panel.
4. Set X variable to age.
5. Set Y variable to weight.
6. Overlay by sex.
7. Add line element.
8. Connect points horizontally.
9. Set smoothness to 0.5.

Example 1423

Summary: Creates a variability chart with nested factors using Graph Builder, displaying standard deviation charts and utilizing operator and part configurations.

Code:

Open("data_table.jmp");
Graph Builder(
    Show Control Panel( 0 ),
    Variables( X( :age ), Y( :weight ), Overlay( :sex ) ),
    Elements( Line( X, Y, Legend( 1 ), Connection( "Vertical" ), Smoothness( 0.5 ) ) )
);

Code Explanation:

1. Open data table;
2. Launch Graph Builder.
3. Hide control panel.
4. Set X variable to age.
5. Set Y variable to weight.
6. Use sex for overlay.
7. Add line element.
8. Connect points vertically.
9. Apply smoothness setting.
10. Display graph.

Example 1424

Summary: Creates a line chart with nested factors using Graph Builder, displaying standard deviation charts and connecting points with centered step.

Code:

Open("data_table.jmp");
Graph Builder(
    Show Control Panel( 0 ),
    Variables( X( :age ), Y( :weight ), Overlay( :sex ) ),
    Elements( Line( X, Y, Legend( 1 ), Connection( "Centered Step" ), Smoothness( 0.5 ) ) )
);

Code Explanation:

1. Open data table;
2. Launch Graph Builder.
3. Hide control panel.
4. Set X variable to age.
5. Set Y variable to weight.
6. Use sex for overlay.
7. Add line element.
8. Connect points with centered step.
9. Set smoothness to 0.5.

Example 1425

Summary: Creates a variability chart with nested factors using Graph Builder, displaying standard deviation charts and configuring legend properties.

Code:

dt = Open("data_table.jmp");
dt << Graph Builder(
    Size( 528, 444 ),
    Show Control Panel( 0 ),
    Variables( X( :age ), Y( :weight ) ),
    Elements( Bar( X, Y, Legend( 5 ) ), Line( Y, Legend( 6 ), Summary Statistic( "Median" ) ) ),
    SendToReport(
        Dispatch( {}, "400", ScaleBox,
            {Legend Model( 6, Properties( 0, {Line Label Properties( {Name Label( 1 ), First Label( 1 )} )}, Item ID( "Median", 1 ) ) )}
        )
    )
);

Code Explanation:

1. Open data table.
2. Create Graph Builder window.
3. Set graph size.
4. Hide control panel.
5. Define X and Y variables.
6. Add bar element.
7. Add line element for median.
8. Send report settings.
9. Configure legend properties.
10. Display line labels.

Example 1426

Summary: Creates a variability chart with nested factors using operator and part configurations, displaying standard deviation charts in Graph Builder.

Code:

Open("data_table.jmp") << Graph Builder(
    Size( 534, 456 ),
    Show Control Panel( 0 ),
    Variables( X( :Abrasion ), Y( :Shift ), Y( :time2, Position( 1 ) ), Overlay( :Shift ) ),
    Elements( Line( X, Y( 1 ), Y( 2 ), Legend( 12 ) ) ),
    SendToReport(
        Dispatch( {}, "Graph Builder", FrameBox,
            Add Pin Annotation(
                Seg( Line Seg( 2 ) ),
                Index( {1, 1} ),
                Index Row( {5, 5} ),
                UniqueID( 614290098 ),
                FoundPt( {428, 177} ),
                Origin( {141.180616740088, 4.96938775510204} ),
                Offset( {-58, -68} ),
                Tag Line( 1 )
            )
        )
    )
);

Code Explanation:

1. Open data_table data
2. Create Graph Builder window.
3. Set size to 534x456.
4. Hide control panel.
5. Define X variable: Abrasion.
6. Define Y variables: Shift, time2.
7. Overlay plots by Shift.
8. Add line element with two Ys.
9. Send report to Graph Builder.
10. Add pin annotation to graph.

Example 1427

Summary: Creates a line graph with nested factors using Graph Builder, displaying standard deviation charts and applying fill below option.

Code:

Open("data_table.jmp") << Graph Builder(
    Size( 307, 194 ),
    Show Control Panel( 0 ),
    Variables( X( :Abrasion ), Y( :time2 ) ),
    Elements( Line( X, Y, Legend( 14 ), Fill( "Fill Below" ) ) )
);

Code Explanation:

1. Open data table;
2. Launch Graph Builder.
3. Set window size.
4. Hide control panel.
5. Assign X variable.
6. Assign Y variable.
7. Add line element.
8. Enable legend.
9. Apply fill below option.
10. Display graph.

Example 1428

Summary: Creates a variability chart with nested factors using operator and part configurations, displaying standard deviation charts in Graph Builder.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 602, 482 ),
    Variables( X( :Manufacturer ), Y( :Sugars ), Overlay( :Name( "Hot/Cold" ) ), Color( :Enriched, Summary Statistic( "Std Err" ) ) ),
    Elements( Line( X, Y, Legend( 6 ), Stack( 1 ) ) )
);

Code Explanation:

1. Open data table;
2. Create new Graph Builder window.
3. Set window size.
4. Define X-axis variable.
5. Define Y-axis variable.
6. Set overlay variable.
7. Define color variable.
8. Set summary statistic for color.
9. Add line element.
10. Configure legend and stacking.

Example 1429

Summary: Creates a variability chart with nested factors using Graph Builder, displaying standard deviation charts and overlaying data by testers.

Code:

Open("data_table.jmp");
Graph Builder(
    Show Control Panel( 0 ),
    Variables( X( :Name( "Time (Numeric)" ), Size( 0, 22 ) ), Y( :Heart Rate, Size( 0, 23 ) ), Group X( :Drink ), Overlay( :Testers ) ),
    Elements( Points( X, Y, Legend( 88 ) ), Line( X, Y, Legend( 90 ), Row order( 0 ), Summary Statistic( "Mean" ) ) )
);

Code Explanation:

1. Open data table.
2. Launch Graph Builder.
3. Hide control panel.
4. Set X variable.
5. Set Y variable.
6. Group by Drink.
7. Overlay by Testers.
8. Add points element.
9. Add line element.
10. Use mean summary statistic.

Example 1430

Summary: Creates a variability chart with nested factors using Graph Builder, displaying standard deviation charts and configuring various settings such as legend, summary statistic, stacking, filling, and error intervals.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 421, 395 ),
    Show Control Panel( 0 ),
    Variables( X( :age ), Y( :height ), Overlay( :weight ) ),
    Elements(
        Line(
            Y,
            Legend( 19 ),
            Summary Statistic( "Sum" ),
            Stack( 1 ),
            Fill( "Fill Below" ),
            Error Interval( "None" ),
            Missing Factors( "Treat as Missing" )
        )
    )
);

Code Explanation:

1. Open data table;
2. Create Graph Builder window.
3. Set window size.
4. Hide control panel.
5. Define X variable.
6. Define Y variable.
7. Define overlay variable.
8. Add line element.
9. Set legend.
10. Use summary statistic "Sum".
11. Stack lines.
12. Fill below lines.
13. Disable error intervals.
14. Treat missing factors as missing.

Example 1431

Summary: Creates a variability chart with nested factors using operator and part configurations, displaying standard deviation charts in Graph Builder.

Code:

dt = Open("data_table.jmp");
Graph Builder(
    Size( 528, 448 ),
    Show Control Panel( 0 ),
    Include Missing Categories( 1 ),
    Variables( X( :sex ), Y( :height ), Y( :weight, Position( 1 ), Side( "Right" ) ) ),
    Elements(
        Line( X, Y( 1 ), Legend( 12 ) ),
        Points( X, Y( 1 ), Legend( 13 ) ),
        Line( X, Y( 2 ), Legend( 14 ) ),
        Points( X, Y( 2 ), Legend( 15 ) )
    )
);

Code Explanation:

1. Open data_table data
2. Create new Graph Builder window.
3. Set window size to 528x448.
4. Hide control panel.
5. Include missing categories.
6. Set X variable to sex.
7. Set first Y variable to height.
8. Set second Y variable to weight on right axis.
9. Add line element for height.
10. Add points element for height.
11. Add line element for weight.
12. Add points element for weight.

Example 1432

Summary: Creates a variability chart with nested factors using Graph Builder, displaying standard deviation charts and pin annotations.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 525, 448 ),
    Show Control Panel( 0 ),
    Variables( X( :age ), Y( :height ), Color( :weight, Summary Statistic( "Min" ) ) ),
    Elements( Line( X, Y, Legend( 13 ), Summary Statistic( "Variance" ) ) ),
    SendToReport(
        Dispatch( {}, "Graph Builder", FrameBox,
            Add Pin Annotation(
                Seg( Line Seg( 1 ) ),
                Index( {0, 0} ),
                Index Row( {0, 0} ),
                UniqueID( 718977520 ),
                FoundPt( {181, 367} ),
                Origin( {0.00420168067226889, 66.0204210526316} ),
                Tag Line( 1 )
            )
        )
    )
);

Code Explanation:

1. Open data table;
2. Launch Graph Builder.
3. Set window size.
4. Hide control panel.
5. Define X, Y, and Color variables.
6. Add line element.
7. Set summary statistic for line.
8. Send report to Graph Builder.
9. Add pin annotation.
10. Configure pin annotation settings.

Example 1433

Summary: Creates a variability chart with nested factors using Graph Builder, configuring X, Y, and overlay variables, adding a line element with fill, and displaying standard deviation charts.

Code:

Open("data_table.jmp") << Graph Builder(
    Size( 437, 365 ),
    Show Control Panel( 0 ),
    Variables( X( :Year ), Y( :Name( "Room occupancy rate (%)" ) ), Overlay( :Quarter ) ),
    Elements( Line( X, Y, Legend( 9 ), Fill( "Fill Between" ), Error Interval( "None" ) ) ),
    SendToReport(
        Dispatch( {}, "Year", ScaleBox, {Label Row( Show Major Ticks( 0 ) )} ),
        Dispatch( {}, "Room occupancy rate (%)", ScaleBox, {Min( 54.5305429864253 ), Max( 75 ), Inc( 5 ), Minor Ticks( 1 )} ),
        Dispatch( {}, "graph title", TextEditBox, {Set Text( "Room occupancy rate vs. Year and Quarter" )} )
    )
);

Code Explanation:

1. Open data table;
2. Create Graph Builder object.
3. Set graph size.
4. Hide control panel.
5. Define X, Y, and overlay variables.
6. Add line element with fill.
7. Configure year scale box.
8. Configure room occupancy rate scale box.
9. Set graph title.
10. Display graph.

Example 1434

Summary: Creates a variability chart with nested factors using operator and part configurations, displaying standard deviation charts.

Code:

Open("data_table.jmp") << Graph Builder(
    Size( 442, 340 ),
    Show Control Panel( 0 ),
    Variables( X( :Position2 ), Y( :Height ), Y( :Weight, Position( 1 ) ) ),
    Elements(
        Line(
            X,
            Y( 1 ),
            Y( 2 ),
            Legend( 7 ),
            Summary Statistic( "Geometric Mean" ),
            Fill( "Fill Between" ),
            Missing Values( "No Connection" )
        )
    )
);

Code Explanation:

1. Open data table;
2. Launch Graph Builder.
3. Set window size.
4. Hide control panel.
5. Define X variable: Position2.
6. Define Y variables: Height, Weight.
7. Add Line element.
8. Configure X axis for Line.
9. Configure Y1 axis for Line.
10. Configure Y2 axis for Line.

Example 1435

Summary: Creates a variability chart with nested factors using operator and part configurations, displaying standard deviation charts in Graph Builder.

Code:

Open("data_table.jmp") << Graph Builder(
    Size( 455, 387 ),
    Show Control Panel( 0 ),
    Variables( X( :Survived ), X( :Sex, Position( 1 ) ), Y( :Age ), Overlay( :Passenger Class ) ),
    Elements( Line( X( 1 ), X( 2 ), Y, Legend( 10 ), Fill( "Fill Between" ) ) )
);

Code Explanation:

1. Open data table;
2. Create Graph Builder window.
3. Set window size.
4. Hide control panel.
5. Define X variables: Survived, Sex.
6. Define Y variable: Age.
7. Set overlay variable: Passenger Class.
8. Add Line element.
9. Configure Line for two X variables.
10. Enable fill between lines.

Example 1436

Summary: Creates a variability chart with nested factors using Graph Builder, displaying standard deviation charts and customizing report layout.

Code:

Open("data_table.jmp") << Graph Builder(
    Size( 556, 350 ),
    Show Control Panel( 0 ),
    Variables( X( :age ), Group X( :sex ), Color( :height, Summary Statistic( "Std Dev" ) ) ),
    Elements( Line( X, Legend( 4 ) ) ),
    SendToReport(
        Dispatch( {}, "400", ScaleBox,
            {Legend Model(
                4,
                Properties(
                    0,
                    {gradient(
                        {Color Theme(
                            {"Blue to Gray to Red Copy", 4099, {{42, 63, 255}, {192, 192, 192}, {252, 11, 11}, Missing( {106, 106, 106} )}}
                        ), Width( 12 )}
                    )},
                    Item ID( "height", 1 )
                )
            )}
        )
    )
);

Code Explanation:

1. Open data_table data
2. Create Graph Builder window.
3. Set window size to 556x350.
4. Hide control panel.
5. Assign variables: X = age, Group X = sex, Color = height summary statistic.
6. Add line element with legend.
7. Customize report layout.
8. Configure legend model for height.
9. Set gradient color theme for legend.
10. Adjust gradient width to 12.

Example 1437

Summary: Creates a variability chart with nested factors using Graph Builder, displaying standard deviation charts and configuring X-axis positions.

Code:

Open("data_table.jmp") << Graph Builder(
    Size( 534, 465 ),
    Show Control Panel( 0 ),
    Variables( X( :sex ), X( :name, Position( 1 ) ), Y( :height ), Overlay( :sex ) ),
    Elements( Line( X( 1 ), X( 2 ), Y, Legend( 15 ), Summary Statistic( "Sum" ), Missing Factors( "Treat as Zero" ) ) )
);

Code Explanation:

1. Open data table;
2. Launch Graph Builder.
3. Set window size.
4. Hide control panel.
5. Define X variables: sex, name.
6. Define Y variable: height.
7. Overlay by sex.
8. Add line element.
9. Set X axis positions.
10. Configure summary statistic and missing factor handling.

Example 1438

Summary: Creates a variability chart with nested factors using operator and part configurations, displaying standard deviation charts.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 534, 418 ),
    Show Control Panel( 0 ),
    Variables( Y( :Class ), Y( :Sex, Position( 1 ) ), Y( :Survived, Position( 1 ) ) ),
    Elements( Line( Y( 1 ), Y( 2 ), Y( 3 ), Legend( 11 ), Curve Lines( 0 ) ) )
);

Code Explanation:

1. Open data table;
2. Create Graph Builder window.
3. Set window size.
4. Hide control panel.
5. Define Y variables.
6. Add Class to Y axis.
7. Add Sex to Y axis.
8. Add Survived to Y axis.
9. Configure line element.
10. Plot nested YX count response.

Example 1439

Summary: Creates a variability chart with nested factors using Graph Builder, displaying standard deviation charts and stacking data for analysis.

Code:

Open("data_table.jmp") << Graph Builder(
    Size( 476, 285 ),
    Show Control Panel( 0 ),
    Variables( X( :Mfr ), Y( :Sugars ), Overlay( :Calories ) ),
    Elements( Line( X, Y, Legend( 6 ), Summary Statistic( "Variance" ), Stack( 1 ) ) )
);

Code Explanation:

1. Open data_table data
2. Launch Graph Builder.
3. Set window size.
4. Hide control panel.
5. Define X variable.
6. Define Y variable.
7. Define overlay variable.
8. Add line element.
9. Set summary statistic.
10. Enable stacking.

Example 1440

Summary: Creates a variability chart with nested factors using Graph Builder, displaying standard deviation charts and configuring legend and summary statistics.

Code:

Open("data_table.jmp") << Graph Builder(
    Size( 613, 324 ),
    Show Control Panel( 0 ),
    Variables( X( :sex ), Y( :height ), Group X( :age ), Overlay( :age ) ),
    Elements( Line( X, Y, Legend( 7 ), Summary Statistic( "N" ), Stack( 1 ) ) )
);

Code Explanation:

1. Open data table;
2. Launch Graph Builder.
3. Set window size.
4. Hide control panel.
5. Define X variable.
6. Define Y variable.
7. Group X by age.
8. Overlay by age.
9. Add line element.
10. Configure legend and summary statistic.

Example 1441

Summary: Creates a variability chart with nested factors using Graph Builder, displaying standard deviation charts and plotting height and weight against age.

Code:

Open("data_table.jmp") << Graph Builder(
    Size( 379, 300 ),
    Show Control Panel( 0 ),
    Variables( X( :age ), Y( :height ), Y( :weight, Position( 1 ) ) ),
    Elements( Line( X, Y( 1 ), Y( 2 ), Legend( 4 ), Stack( 1 ) ) )
);

Code Explanation:

1. Open data table.
2. Create Graph Builder window.
3. Set window size.
4. Hide control panel.
5. Define X variable: age.
6. Define Y variables: height, weight.
7. Position weight on first axis.
8. Add line element.
9. Plot height and weight against age.
10. Stack categorical X variable.

Example 1442

Summary: Creates a graph builder with nested factors using operator and part configurations, displaying standard deviation charts.

Code:

Open("data_table.jmp") << Graph Builder(
    Size( 353, 276 ),
    Show Control Panel( 0 ),
    Variables( X( :Heart History ), Overlay( :Smoking History ) ),
    Elements( Line( X, Legend( 4 ), Stack( 1 ) ) )
);

Code Explanation:

1. Open data table;
2. Create Graph Builder.
3. Set size 353x276.
4. Hide control panel.
5. Set X variable: Heart History.
6. Set overlay variable: Smoking History.
7. Add Line element.
8. Use Legend 4.
9. Stack categories.

Example 1443

Summary: Creates a variability chart with nested factors using Graph Builder, displaying standard deviation charts and leveraging operator and part configurations.

Code:

Open("data_table.jmp") << Graph Builder(
    Size( 379, 300 ),
    Show Control Panel( 0 ),
    Variables( X( :age ), Y( :height ), Overlay( :sex ) ),
    Elements( Line( X, Y, Legend( 4 ), Stack( 1 ) ) )
);

Code Explanation:

1. Open data table;
2. Launch Graph Builder.
3. Set window size.
4. Hide control panel.
5. Assign X variable.
6. Assign Y variable.
7. Assign overlay variable.
8. Add line element.
9. Set legend position.
10. Enable stacking.

Example 1444

Summary: Creates a variability chart with nested factors using Graph Builder, displaying standard deviation charts and configuring X and Y axes.

Code:

Open("data_table.jmp") << Graph Builder(
    Size( 565, 354 ),
    Show Control Panel( 0 ),
    Variables( X( :Mfr ), Y( :Sugars ), Overlay( :Fiber Gr ) ),
    Elements( Line( X, Y, Legend( 5 ), Summary Statistic( "Variance" ), Stack( 1 ) ) )
);

Code Explanation:

1. Open data table;
2. Initialize Graph Builder.
3. Set window size.
4. Hide control panel.
5. Define X variable: Mfr.
6. Define Y variable: Sugars.
7. Define overlay variable: Fiber Gr.
8. Add Line element.
9. Configure X and Y axes.
10. Set legend position.
11. Use variance summary statistic.
12. Enable stacked categorical X.

Example 1445

Summary: Creates a variability chart with nested factors using Graph Builder, displaying standard deviation charts and utilizing color, overlay, and legend features.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 355, 295 ),
    Show Control Panel( 0 ),
    Variables( X( :Cut ), Y( :Price ), Overlay( :Clarity ), Color( :Color ) ),
    Elements( Line( X, Y, Legend( 34 ), Stack( 1 ) ) )
);

Code Explanation:

1. Open data table;
2. Launch Graph Builder.
3. Set window size.
4. Hide control panel.
5. Assign variables: X(Cut), Y(Price).
6. Add overlay variable: Clarity.
7. Add color variable: Color.
8. Create line element.
9. Enable legend.
10. Stack categories on X-axis.

Example 1446

Summary: Creates a variability chart with nested factors using Graph Builder, displaying standard deviation charts and utilizing operator and part configurations.

Code:

Open("data_table.jmp") << Graph Builder(
    Size( 379, 300 ),
    Show Control Panel( 0 ),
    Variables( X( :age ), Y( :height ), Y( :weight, Position( 1 ) ), Overlay( :sex ) ),
    Elements( Line( X, Y( 1 ), Y( 2 ), Legend( 4 ), Stack( 1 ) ) )
);

Code Explanation:

1. Open data table.
2. Create Graph Builder window.
3. Set window size.
4. Hide control panel.
5. Define X variable: age.
6. Define first Y variable: height.
7. Define second Y variable: weight.
8. Set weight to position 1.
9. Use sex for overlay.
10. Add line element with stacked categorical X and multiple Y.

Example 1447

Summary: Creates a variability chart with nested factors using Graph Builder, displaying standard deviation charts and overlaying by Gender.

Code:

Open("data_table.jmp");
Graph Builder(
    Show Control Panel( 0 ),
    Variables( X( :Age ), Y( :BMI ), Group Y( :Gender ), Overlay( :Gender ) ),
    Elements( Line( X, Y, Legend( 9 ), Stack( 1 ) ) )
);

Code Explanation:

1. Open data table;
2. Launch Graph Builder.
3. Hide control panel.
4. Set X variable to Age.
5. Set Y variable to BMI.
6. Group Y by Gender.
7. Overlay by Gender.
8. Add line element.
9. Assign legend to group.
10. Stack lines by X.

Example 1448

Summary: Creates a variability chart with nested factors using Graph Builder, displaying standard deviation charts and configuring X-axis scale.

Code:

Open("data_table.jmp") << Graph Builder(
    Size( 524, 244 ),
    Show Control Panel( 0 ),
    Variables( X( :height ), Y( :weight ), Overlay( :sex ) ),
    Elements( Line( X, Y, Legend( 4 ), Stack( 1 ) ) ),
    SendToReport(
        Dispatch( {}, "height", ScaleBox, {Min( 50 ), Max( 70.475 ), Inc( 1 ), Minor Ticks( 1 ), Label Row( Show Major Grid( 1 ) )} )
    )
);

Code Explanation:

1. Open data table.
2. Initiate Graph Builder.
3. Set window size.
4. Hide control panel.
5. Define variables: X, Y, Overlay.
6. Add line element.
7. Configure legend position.
8. Enable stacking.
9. Adjust X-axis scale.
10. Display major grid on X-axis.

Example 1449

Summary: Creates a variability chart with nested factors using operator and part configurations, displaying standard deviation charts for height and weight by sex.

Code:

dt = Open("data_table.jmp");
Graph Builder(
    Show Control Panel( 0 ),
    Variables( X( :age ), Y( :height ), Y( :weight, Position( 1 ) ), Group Y( :sex ) ),
    Elements(
        Line(
            X,
            Y( 1 ),
            Y( 2 ),
            Legend( 11 ),
            Summary Statistic( "Std Dev" ),
            Stack( 1 ),
            Fill( "Fill Below" ),
            Missing Values( "No Connection" )
        )
    )
);

Code Explanation:

1. Open data table.
2. Create Graph Builder object.
3. Hide control panel.
4. Set X variable to age.
5. Set first Y variable to height.
6. Set second Y variable to weight.
7. Group Y by sex.
8. Add Line element.
9. Plot height and weight on Y-axis.
10. Apply stacked fill below effect.

Example 1450

Summary: Creates a graph builder with nested factors using operator and part configurations, displaying standard deviation charts.

Code:

dt = Open("data_table.jmp");
Graph Builder(
    Size( 530, 395 ),
    Show Control Panel( 0 ),
    Variables( X( :sex ), X( :age, Position( 1 ) ), Y( :height ), Overlay( :weight ) ),
    Elements( Line( X( 1 ), X( 2 ), Y, Legend( 13 ), Stack( 1 ) ) )
);

Code Explanation:

1. Open data table.
2. Create Graph Builder object.
3. Set graph size.
4. Hide control panel.
5. Define X variables: sex, age.
6. Define Y variable: height.
7. Define overlay variable: weight.
8. Add line element.
9. Set first X axis for sex.
10. Set second X axis for age.

Example 1451

Summary: Creates a variability chart with nested factors using Graph Builder, displaying standard deviation charts and summarizing data with the 'Sum' statistic.

Code:

Open("data_table.jmp") << Graph Builder(
    Size( 456, 417 ),
    Show Control Panel( 0 ),
    Variables( X( :Mfr ), Y( :Sugars ), Overlay( :Calories ) ),
    Elements( Line( X, Y, Legend( 6 ), Summary Statistic( "Sum" ), Stack( 1 ) ) )
);

Code Explanation:

1. Open data table;
2. Create Graph Builder window.
3. Set window size.
4. Hide control panel.
5. Define X variable.
6. Define Y variable.
7. Define overlay variable.
8. Add line element.
9. Use summary statistic "Sum".
10. Stack lines.

Example 1452

Summary: Creates a graph builder window with nested factors using operator and part configurations, displaying standard deviation charts.

Code:

Open("data_table.jmp") << Graph Builder(
    Size( 335, 329 ),
    Show Control Panel( 0 ),
    Variables( X( :Fish Caught ), Y( :Fishing Poles ), Overlay( :Live Bait ) ),
    Elements( Line( X, Y, Legend( 7 ), Response Axis( "X" ), Stack( 1 ) ) )
);

Code Explanation:

1. Open data_table data
2. Create Graph Builder window.
3. Set size to 335x329.
4. Hide control panel.
5. Assign variables: X = Fish Caught, Y = Fishing Poles.
6. Use Live Bait for overlay.
7. Add Line element.
8. Set legend index to 7.
9. Place response axis on X.
10. Stack elements by X.

Example 1453

Summary: Creates a variability chart with nested factors using operator and part configurations, displaying standard deviation charts.

Code:

Open("data_table.jmp") << Graph Builder(
    Size( 312, 299 ),
    Show Control Panel( 0 ),
    Variables( X( :count ), Y( :brand ), Y( :softness, Position( 1 ) ), Overlay( :previous use ) ),
    Elements( Line( X, Y( 1 ), Y( 2 ), Legend( 4 ), Stack( 1 ) ) )
);

Code Explanation:

1. Open data table;
2. Create Graph Builder object.
3. Set window size.
4. Hide control panel.
5. Define X variable.
6. Define first Y variable.
7. Define second Y variable.
8. Set overlay variable.
9. Add line element.
10. Configure line stacking.

Example 1454

Summary: Creates a variability chart with nested factors using operator and part configurations, displaying standard deviation charts in JMP.

Code:

Open("data_table.jmp") << Graph Builder(
    Size( 377, 260 ),
    Show Control Panel( 0 ),
    Variables( Y( :temperature ), Overlay( :softness ), Frequency( :count ) ),
    Elements( Line( Y, Legend( 9 ), Stack( 1 ) ) )
);

Code Explanation:

1. Open data table;
2. Create Graph Builder object.
3. Set window size.
4. Hide control panel.
5. Define Y variable.
6. Define overlay variable.
7. Define frequency variable.
8. Add line element.
9. Set legend position.
10. Enable stacking.

Example 1455

Summary: Creates a variability chart with nested factors using operator and part configurations, displaying standard deviation charts for height and weight data.

Code:

dt = Open("data_table.jmp");
Graph Builder(
    Size( 528, 454 ),
    Show Control Panel( 0 ),
    Variables( X( :height ), Y( :weight ) ),
    Elements( Points( X, Y, Legend( 3 ), Summary Statistic( "Std Dev" ) ), Line( X, Y, Legend( 5 ), Summary Statistic( "Std Dev" ) ) )
);

Code Explanation:

1. Open data table.
2. Create Graph Builder object.
3. Set window size.
4. Hide control panel.
5. Assign X variable.
6. Assign Y variable.
7. Add points element.
8. Configure points summary statistic.
9. Add line element.
10. Configure line summary statistic.

Example 1456

Summary: Creates a variability chart with nested factors using Graph Builder, displaying standard deviation charts for height and weight data.

Code:

dt = Open("data_table.jmp");
Graph Builder(
    Size( 503, 395 ),
    Show Control Panel( 0 ),
    Variables( X( :height ), Y( :weight ) ),
    Elements(
        Bar( X, Y, Legend( 11 ), Summary Statistic( "Std Err" ) ),
        Line( X, Y, Legend( 12 ), Summary Statistic( "Std Err" ) ),
        Points( X, Y, Legend( 13 ), Summary Statistic( "Std Err" ) )
    )
);

Code Explanation:

1. Open data table;
2. Create Graph Builder window.
3. Set window size.
4. Hide control panel.
5. Assign X variable.
6. Assign Y variable.
7. Add bar element.
8. Add line element.
9. Add points element.
10. Display graph.

Example 1457

Summary: Creates a variability chart with nested factors using Graph Builder, assigning variables for age, height, and sex, and displaying standard deviation charts.

Code:

Open("data_table.jmp") << Graph Builder(
    Size( 528, 448 ),
    Show Control Panel( 0 ),
    Variables( X( :age ), Y( :height ), Color( :sex ) ),
    Elements( Line( X, Y, Legend( 4 ), Connection( "Step" ) ) ),
    SendToReport( Dispatch( {}, "400", LegendBox, {Set Title( "" )} ) )
);

Code Explanation:

1. Open data table.
2. Create Graph Builder window.
3. Set window size.
4. Hide control panel.
5. Assign variables: X=age, Y=height, Color=sex.
6. Add line element.
7. Use step connection.
8. Display legend at position 4.
9. Remove legend title.
10. Finalize report display.

Example 1458

Summary: Creates a variability chart with nested factors using operator and part configurations, displaying standard deviation charts in Graph Builder.

Code:

Open("data_table.jmp") << Graph Builder(
    Size( 528, 448 ),
    Show Control Panel( 0 ),
    Variables( X( :age ), Y( :height ), Color( :weight ) ),
    Elements( Line( X, Y, Legend( 4 ), Connection( "Step" ) ) )
);

Code Explanation:

1. Open data table;
2. Launch Graph Builder.
3. Set window size.
4. Hide control panel.
5. Define X variable.
6. Define Y variable.
7. Define color variable.
8. Add line element.
9. Set line style to step.
10. Display graph.

Example 1459

Summary: Creates a variability chart with nested factors using Graph Builder, displaying standard deviation charts and configuring report settings.

Code:

Open("data_table.jmp") << Graph Builder(
    Size( 528, 448 ),
    Show Control Panel( 0 ),
    Variables( X( :age ), Y( :height ), Overlay( :sex ), Color( :weight ) ),
    Elements( Line( X, Y, Legend( 4 ), Connection( "Step" ) ) ),
    SendToReport( Dispatch( {}, "400", LegendBox, {Set Title( "" )} ) )
);

Code Explanation:

1. Open data table;
2. Initiate Graph Builder.
3. Set window size.
4. Hide control panel.
5. Define X, Y, overlay, and color variables.
6. Add line element with step connection.
7. Remove legend title.
8. Finalize report.

Example 1460

Summary: Creates a variability chart with nested factors using Graph Builder, displaying standard deviation charts and step lines.

Code:

Open("data_table.jmp") << Graph Builder(
    Size( 292, 655 ),
    Show Control Panel( 0 ),
    Variables( X( :"Height (inches)"n ), Y( :"Age (years)"n ), Color( :Percent body fat ) ),
    Elements( Line( X, Y, Legend( 5 ), Connection( "Step" ), Response Axis( "X" ) ) ),
    SendToReport( Dispatch( {}, "400", LegendBox, {Set Title( "" )} ) )
);

Code Explanation:

1. Open data table;
2. Launch Graph Builder.
3. Set graph size.
4. Hide control panel.
5. Define X, Y, and color variables.
6. Add line element.
7. Set line style to step.
8. Connect points with step lines.
9. Set response axis to X.
10. Remove legend title.

Example 1461

Summary: Creates a line graph with nested factors using Graph Builder, displaying the sum of Sugars for each Mfr.

Code:

Open("data_table.jmp") << Graph Builder(
    Size( 1053, 440 ),
    Show Control Panel( 0 ),
    Variables( X( :Mfr ), Y( :Sugars ) ),
    Elements( Line( X, Y, Legend( 14 ), Summary Statistic( "Sum" ) ) )
);

Code Explanation:

1. Open data table;
2. Launch Graph Builder.
3. Set window size.
4. Hide control panel.
5. Assign Mfr to X-axis.
6. Assign Sugars to Y-axis.
7. Add line element.
8. Use summary statistic Sum.
9. Display legend.
10. Render graph.

Example 1462

Summary: Creates a variability chart with nested factors using Graph Builder, displaying standard deviation charts and configuring line elements for missing values.

Code:

Open("data_table.jmp") << Graph Builder(
    Size( 479, 364 ),
    Show Control Panel( 0 ),
    Show Legend( 0 ),
    Variables( X( :Weight ), Y( :Height ), Wrap( :Squat ), Overlay( :Position2 ) ),
    Elements( Line( X, Y, Legend( 5 ), Missing Factors( "Treat as Missing" ), Missing Values( "Connect Faded" ) ) )
);

Code Explanation:

1. Open data table;
2. Create Graph Builder.
3. Set size to 479x364.
4. Hide control panel.
5. Hide legend.
6. Define X: Weight.
7. Define Y: Height.
8. Wrap by Squat.
9. Overlay by Position2.
10. Add line element with missing values treated as missing and connected faded.

Example 1463

Summary: Creates a variability chart with nested factors using Graph Builder, displaying standard deviation charts and leveraging operator and part configurations.

Code:

Open("data_table.jmp") << Graph Builder(
    Size( 426, 335 ),
    Show Control Panel( 0 ),
    Variables( X( :height ), Y( :age ) ),
    Elements( Line( X, Y, Legend( 4 ) ) )
);

Code Explanation:

1. Open data table;
2. Launch Graph Builder.
3. Set window size.
4. Hide control panel.
5. Assign X variable.
6. Assign Y variable.
7. Add line element.
8. Set legend position.

Example 1464

Summary: Creates variability charts with nested factors using Graph Builder, displaying standard deviation charts and configuring error intervals.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 528, 450 ),
    Show Control Panel( 0 ),
    Variables( X( :age ), Y( :height ) ),
    Elements( Line( X, Y, Legend( 4 ), Error Interval( "Range" ), Interval Style( "Band" ) ) ),
    SendToReport( Dispatch( {}, "Graph Builder", FrameBox, {Grid Line Order( 2 ), Reference Line Order( 3 )} ) )
);
Graph Builder(
    Size( 528, 450 ),
    Show Control Panel( 0 ),
    Variables( X( :age ), Y( :height ) ),
    Elements( Line( X, Y, Legend( 4 ), Connection( "Step" ), Error Interval( "Range" ), Interval Style( "Band" ) ) ),
    SendToReport( Dispatch( {}, "Graph Builder", FrameBox, {Grid Line Order( 2 ), Reference Line Order( 3 )} ) )
);
Graph Builder(
    Size( 528, 450 ),
    Show Control Panel( 0 ),
    Variables( X( :age ), Y( :height ), Overlay( :weight ) ),
    Elements( Line( X, Y, Legend( 4 ), Error Interval( "Standard Deviation" ), Interval Style( "Band" ) ) ),
    SendToReport( Dispatch( {}, "Graph Builder", FrameBox, {Grid Line Order( 8 ), Reference Line Order( 9 )} ) )
);

Code Explanation:

1. Open data table;
2. Create graph builder window.
3. Set window size.
4. Hide control panel.
5. Assign variables X and Y.
6. Add line element with error interval.
7. Set grid and reference line order.
8. Repeat steps 2-7 for second graph.
9. Change connection style to step.
10. Create third graph with overlay variable.
11. Change error interval to standard deviation.
12. Set grid and reference line order.

Example 1465

Summary: Creates multiple line graphs with error intervals and interval styles, as well as overlay configurations, to visualize relationships between age, height, weight, and sex.

Code:

dt = Open("data_table.jmp");
Graph Builder(
    Size( 528, 450 ),
    Show Control Panel( 0 ),
    Variables( X( :age ), Y( :height ) ),
    Elements( Line( X, Y, Legend( 4 ), Error Interval( "Range" ), Interval Style( "Band" ) ) ),
    SendToReport( Dispatch( {}, "Graph Builder", FrameBox, {Grid Line Order( 2 ), Reference Line Order( 3 )} ) )
);
Graph Builder(
    Size( 528, 450 ),
    Show Control Panel( 0 ),
    Variables( X( :age ), Y( :height ) ),
    Elements( Line( X, Y, Legend( 4 ), Connection( "Step" ), Error Interval( "Range" ), Interval Style( "Band" ) ) ),
    SendToReport( Dispatch( {}, "Graph Builder", FrameBox, {Grid Line Order( 2 ), Reference Line Order( 3 )} ) )
);
Graph Builder(
    Size( 528, 450 ),
    Show Control Panel( 0 ),
    Variables( X( :age ), Y( :height ), Overlay( :weight ) ),
    Elements( Line( X, Y, Legend( 4 ), Error Interval( "Standard Deviation" ), Interval Style( "Band" ) ) ),
    SendToReport( Dispatch( {}, "Graph Builder", FrameBox, {Grid Line Order( 8 ), Reference Line Order( 9 )} ) )
);
Graph Builder(
    Size( 528, 450 ),
    Show Control Panel( 0 ),
    Variables( X( :age ), Y( :height ), Overlay( :sex ) ),
    Elements( Line( X, Y, Legend( 4 ), Error Interval( "Range" ), Interval Style( "Band" ) ) )
);
Graph Builder(
    Size( 528, 450 ),
    Show Control Panel( 0 ),
    Variables( X( :age ), Y( :height ) ),
    Elements( Line( X, Y, Legend( 4 ), Error Interval( "Range" ), Interval Style( "Band" ) ) )
);

Code Explanation:

1. Open table.
2. Create line graph.
3. Add error interval.
4. Set interval style.
5. Configure grid lines.
6. Create step connection graph.
7. Add error interval.
8. Set interval style.
9. Configure grid lines.
10. Create overlay graph.
11. Add error interval.
12. Set interval style.
13. Configure grid lines.
14. Create sex overlay graph.
15. Add error interval.
16. Set interval style.
17. Create final line graph.
18. Add error interval.
19. Set interval style.

Example 1466

Summary: Creates a variability chart with nested factors using Graph Builder, displaying standard deviation charts and utilizing specific element configurations.

Code:

Open("data_table.jmp") << Graph Builder(
    Size( 247, 207 ),
    Show Control Panel( 0 ),
    Variables( X( :weight ) ),
    Elements( Line( X, Legend( 4 ), Response Axis( "X" ), Summary Statistic( "Geometric Mean" ) ) )
);

Code Explanation:

1. Open data table;
2. Launch Graph Builder.
3. Set size to 247x207.
4. Hide control panel.
5. Set X variable to weight.
6. Add Line element.
7. Use Legend 4.
8. Set response axis to X.
9. Use Geometric Mean summary statistic.

Example 1467

Summary: Creates a variability chart with nested factors using Graph Builder, displaying standard deviation charts and handling missing values.

Code:

Open("data_table.jmp") << Graph Builder(
    Size( 255, 572 ),
    Show Control Panel( 0 ),
    Variables( Y( :School ), Frequency( :USA Today ) ),
    Elements( Bar( Y, Legend( 4 ) ), Line( Y, Legend( 6 ), Missing Values( "No Connection" ) ) )
);

Code Explanation:

1. Open data table;
2. Create Graph Builder object.
3. Set window size.
4. Hide control panel.
5. Define Y variable.
6. Define frequency variable.
7. Add bar element.
8. Add line element.
9. Handle missing values.
10. Display graph.

Example 1468

Summary: Creates a variability chart with nested factors using operator and part configurations, displaying standard deviation charts in JMP.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 560, 430 ),
    Show Control Panel( 0 ),
    Variables( X( :Manufacturer ), Y( :Sugars ), Overlay( :Name( "Hot/Cold" ) ), Color( :Enriched, Summary Statistic( "Std Err" ) ) ),
    Elements( Line( X, Y, Legend( 6 ), Stack( 1 ) ) )
);

Code Explanation:

1. Open data table;
2. Launch Graph Builder.
3. Set window size.
4. Hide control panel.
5. Define X variable.
6. Define Y variable.
7. Set overlay variable.
8. Set color variable.
9. Apply summary statistic.
10. Add line element.

Example 1469

Summary: Creates a variability chart with nested factors using operator and part configurations, displaying standard deviation charts in Graph Builder.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 800, 600 ),
    Show Control Panel( 0 ),
    Variables(
        X( :Subject ),
        Y( :BP 8M ),
        Y( :BP 12M, Position( 1 ) ),
        Y( :BP 6M, Position( 1 ) ),
        Y( :BP 8W, Position( 1 ) ),
        Y( :BP 12W, Position( 1 ) ),
        Y( :BP 6W, Position( 1 ) ),
        Y( :BP 8F, Position( 1 ) ),
        Y( :BP 12F, Position( 1 ) ),
        Y( :BP 6F, Position( 1 ) ),
        Overlay( :Dose )
    ),
    Elements( Smoother( X, Y( 1 ), Y( 2 ), Y( 3 ), Y( 4 ), Y( 5 ), Y( 6 ), Y( 7 ), Y( 8 ), Y( 9 ), Legend( 7 ) ) )
);

Code Explanation:

1. Open data_table data
2. Create Graph Builder window.
3. Set size 800x600.
4. Hide control panel.
5. Assign X variable: Subject.
6. Assign multiple Y variables.
7. Overlay by Dose.
8. Add smoother element.
9. Apply to all Y variables.
10. Display legend for smoother.

Example 1470

Summary: Creates a variability chart with nested factors using Graph Builder, displaying standard deviation charts and customizing point legend properties.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 534, 450 ),
    Show Control Panel( 0 ),
    Show Footer( 0 ),
    Variables( X( :sex ), Y( :height ), Y( :weight, Position( 1 ), Side( "Right" ) ) ),
    Elements( Bar( X, Y( 1 ), Legend( 3 ), Summary Statistic( "Sum" ) ), Points( X, Y( 2 ), Legend( 5 ) ) ),
    SendToReport(
        Dispatch( {}, "400", ScaleBox, {Legend Model( 5, Properties( 0, {Line Color( 70 ), Marker Size( 6 )}, Item ID( "weight", 1 ) ) )} )
    )
);
Graph Builder(
    Size( 534, 450 ),
    Show Control Panel( 0 ),
    Show Footer( 0 ),
    Variables( X( :sex ), Y( :height ), Y( :weight, Position( 1 ), Side( "Right" ) ) ),
    Elements( Bar( X, Y( 1 ), Legend( 3 ), Summary Statistic( "Sum" ) ), Points( X, Y( 2 ), Legend( 5 ), Jitter( "Packed" ) ) ),
    SendToReport(
        Dispatch( {}, "400", ScaleBox, {Legend Model( 5, Properties( 0, {Line Color( 76 ), Marker Size( 6 )}, Item ID( "weight", 1 ) ) )} )
    )
);
Graph Builder(
    Size( 534, 450 ),
    Show Control Panel( 0 ),
    Show Footer( 0 ),
    Variables( X( :sex ), Y( :height ), Y( :weight, Position( 1 ), Side( "Right" ) ) ),
    Elements( Bar( X, Y( 1 ), Legend( 3 ), Summary Statistic( "Sum" ) ), Points( X, Y( 2 ), Legend( 5 ), Jitter( "Positive Grid" ) ) ),
    SendToReport(
        Dispatch( {}, "400", ScaleBox, {Legend Model( 5, Properties( 0, {Line Color( 41 ), Marker Size( 6 )}, Item ID( "weight", 1 ) ) )} )
    )
);

Code Explanation:

1. Open data table;
2. Create first graph builder window.
3. Set graph size.
4. Hide control panel.
5. Hide footer.
6. Define X and Y variables.
7. Add bar element for height.
8. Add points element for weight on right side.
9. Customize point legend properties.
10. Create second graph builder window with packed jitter.
11. Create third graph builder window with positive grid jitter.

Example 1471

Summary: Creates a variability chart with nested factors using operator and part configurations, displaying standard deviation charts.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 564, 486 ),
    Show Control Panel( 0 ),
    Lock Scales( 1 ),
    Include Missing Categories( 1 ),
    Variables(
        X( :State ),
        Y( :Name( "2004" ) ),
        Y( :Name( "2008" ), Position( 1 ) ),
        Y( :Name( "2012" ), Position( 1 ) ),
        Group Y( :Name( "2012 Winner" ) ),
        Color( :Name( "2012 Winner" ) )
    ),
    Elements( Line( X, Y( 1 ), Y( 2 ), Y( 3 ), Legend( 11 ), Fill( "Fill Between" ) ) ),
    SendToReport(
        Dispatch( {}, "State", ScaleBox, {Format( "Best", 9 ), Min( -0.5 ), Max( 49.5 ), Inc( 3 ), Minor Ticks( 0 )} ),
        Dispatch( {}, "2004", ScaleBox,
            {Format( "Fixed Dec", 12, 0 ), Min( 22.243504696607 ), Max( 78.1921012432196 ), Inc( 10 ), Minor Ticks( 0 )}
        ),
        Dispatch( {}, "", ScaleBox,
            {Format( "Longitude DDD", "PUNDIR", 14, 0 ), Min( -121.198853211009 ), Max( -73.8011467889908 ), Inc( 10 ), Minor Ticks( 0 )}
        ),
        Dispatch( {}, "", ScaleBox( 2 ),
            {Format( "Latitude DDD", "PUNDIR", 14, 0 ), Min( -2.67992125984253 ), Max( 78.6799212598425 ), Inc( 5 ), Minor Ticks( 0 )}
        ),
        Dispatch( {}, "400", ScaleBox,
            {Legend Model(
                11,
                Properties( 2, {Transparency( 0.2 ), gradient( {Scale Values( [0 1] ), N Labels( 6 )} )}, Item ID( "2004..2008", 1 ) )
            )}
        ),
        Dispatch( {}, "400", LegendBox, {Set Title( "" )} )
    )
);

Code Explanation:

1. Open data table.
2. Create Graph Builder.
3. Set window size.
4. Hide control panel.
5. Lock scales.
6. Include missing categories.
7. Define X variable.
8. Define multiple Y variables.
9. Group Y by winner.
10. Color by winner.

Example 1472

Summary: Creates a variability chart with nested factors using Graph Builder, displaying standard deviation charts and summarizing data as sums.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 671, 470 ),
    Show Control Panel( 0 ),
    Show Legend( 0 ),
    Variables( X( :YearWeek ), Overlay( :Volume ) ),
    Elements( Line( X, Legend( 5 ), Summary Statistic( "Sum" ), Fill( "Fill Between" ) ) )
);

Code Explanation:

1. Open data table;
2. Launch Graph Builder.
3. Set window size to 671x470.
4. Hide control panel.
5. Hide legend.
6. Assign YearWeek to X-axis.
7. Overlay Volume data.
8. Add line element.
9. Use legend position 5.
10. Summarize statistic as sum.
11. Fill area between lines.

Example 1473

Summary: Creates a variability chart with nested factors using Graph Builder, displaying standard deviation charts and customizing legend properties.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 482, 298 ),
    Show Control Panel( 0 ),
    Variables( X( :age ), Y( :height ), Group X( :sex ), Color( :weight, Summary Statistic( "Std Dev" ) ) ),
    Elements( Line( X, Y, Legend( 11 ) ) ),
    SendToReport(
        Dispatch( {}, "400", ScaleBox,
            {Legend Model(
                11,
                Properties(
                    0,
                    {gradient(
                        {Color Theme(
                            {"Green to Black to Red Copy", 4099, {{0, 227, 0}, {24, 24, 24}, {252, 11, 11}, Missing( {255, 255, 255} )}}
                        )}
                    )},
                    Item ID( "weight", 1 )
                )
            )}
        )
    )
);

Code Explanation:

1. Open data table;
2. Launch Graph Builder.
3. Set window size.
4. Hide control panel.
5. Define X, Y, Group X, Color variables.
6. Add Line element.
7. Customize legend properties.
8. Set gradient color theme.
9. Apply report settings.
10. Display graph.

Example 1474

Summary: Creates a line graph with age on the x-axis and weight on the y-axis, filtering data to only include rows where age is 14.

Code:

dt = Open("data_table.jmp");
dt << select where( :age == 14, current selection( "Restrict" ) );
dt << hide;
dt << clear select;
Graph Builder( Size( 508, 382 ), Show Control Panel( 0 ), Variables( X( :age ), Y( :weight ) ), Elements( Line( X, Y, Legend( 7 ) ) ) );

Code Explanation:

1. Open data table;
2. Select rows where age is 14.
3. Restrict selection to current.
4. Hide selected rows.
5. Clear selection.
6. Create Graph Builder window.
7. Set size of graph.
8. Hide control panel.
9. Assign variables for X and Y axes.
10. Add line element to graph.

Example 1475

Summary: Creates a line chart with nested factors using Graph Builder, displaying standard deviation charts and enabling major grid lines on the X-axis.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 587, 486 ),
    Show Control Panel( 0 ),
    Variables( X( :age ), Y( :weight ), Interval( :age ) ),
    Elements( Line( X, Y, Legend( 1 ) ) ),
    SendToReport( Dispatch( {}, "age", ScaleBox, {Label Row( Show Major Grid( 1 ) )} ) )
);

Code Explanation:

1. Open data table.
2. Create Graph Builder object.
3. Set window size.
4. Hide control panel.
5. Define X and Y variables.
6. Add interval for X variable.
7. Add line element.
8. Assign legend to line.
9. Send report message.
10. Enable major grid lines on X axis.

Example 1476

Summary: Creates a graph builder window with nested factors using operator and part configurations, displaying standard deviation charts.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 451, 454 ),
    Show Control Panel( 0 ),
    Show Legend( 0 ),
    Title Span( "Graph contents" ),
    Subtitle Alignment( "Left" ),
    Subtitle Span( "Graph contents" ),
    Show Subtitle( 1 ),
    Show Footer( 0 ),
    Include Missing Categories( 1 ),
    Variables( X( :Disaster ), Y( :Cost ), Overlay( :Year ), Color( :Disaster ) ),
    Elements( Line( X, Y, Legend( 6 ), Summary Statistic( "% of Total" ) ) )
);

Code Explanation:

1. Open data table;
2. Create Graph Builder window.
3. Set window size.
4. Hide control panel.
5. Hide legend.
6. Set title span.
7. Align subtitle left.
8. Set subtitle span.
9. Show subtitle.
10. Hide footer.
11. Include missing categories.
12. Define X, Y, Overlay, and Color variables.
13. Add line element.
14. Set summary statistic to "% of Total".

Example 1477

Summary: Creates a variability chart with nested factors using operator and part configurations, displaying standard deviation charts in Graph Builder.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 741, 327 ),
    Show Control Panel( 0 ),
    Variables( X( :height ), Y( :weight ), Overlay( :sex ) ),
    Elements( Line( X, Y, Legend( 4 ), Stack( 1 ) ) ),
    SendToReport(
        Dispatch( {}, "height", ScaleBox, {Min( 50 ), Max( 70.475 ), Inc( 1 ), Minor Ticks( 1 ), Label Row( Show Major Grid( 1 ) )} ),
        Dispatch( {}, "Graph Builder", FrameBox,
            {Add Pin Annotation(
                Seg( Line Seg( 2 ) ),
                Index( {4, 4} ),
                Index Row( {13, 13} ),
                UniqueID( 9 ),
                FoundPt( {342, 140} ),
                Origin( {58.0996691176471, 181.602753036437} ),
                Offset( {7, -10} ),
                RightOfCenter( 0 ),
                Tag Line( 1 )
            ), Add Pin Annotation(
                Seg( Line Seg( 2 ) ),
                Index( {2, -1} ),
                Index Row( {13, -1} ),
                UniqueID( 4 ),
                FoundPt( {207, 164} ),
                Origin( {54.0347794117647, 156.262834008097} ),
                Offset( {-70, -57} ),
                RightOfCenter( 0 ),
                Tag Line( 1 )
            ), Add Pin Annotation(
                Seg( Line Seg( 2 ) ),
                Index( {4, -1} ),
                Index Row( {13, -1} ),
                UniqueID( 8 ),
                FoundPt( {272, 162} ),
                Origin( {55.9919485294118, 158.374493927126} ),
                Offset( {-64, 39} ),
                RightOfCenter( 0 ),
                Tag Line( 1 )
            )}
        )
    )
);

Code Explanation:

1. Open data table;
2. Launch Graph Builder.
3. Set size to 741x327.
4. Hide control panel.
5. Assign height to X-axis.
6. Assign weight to Y-axis.
7. Overlay by sex.
8. Add line element.
9. Configure X-axis scale.
10. Add pin annotations.

Example 1478

Summary: Creates a variability chart with nested factors using Graph Builder, displaying standard deviation charts and utilizing operator and part configurations.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 420, 329 ),
    Show Control Panel( 0 ),
    Link Page Axes( "Y Only" ),
    Replicate Linked Page Axes( 0 ),
    Page Level Fill Color( "Medium Light Gray" ),
    Variables( X( :Quarter ), Y( :Profit ), Page( :Product Line, Levels per Row( 2 ) ), Color( :Quarter ) ),
    Elements( Line( X, Y, Legend( 7 ) ) )
);

Code Explanation:

1. Open data table;
2. Launch Graph Builder.
3. Set window size.
4. Hide control panel.
5. Link Y axes across pages.
6. Disable axis replication.
7. Set page fill color.
8. Define X, Y, Page, and Color variables.
9. Add line element to graph.
10. Display graph.

Example 1479

Summary: Creates two variability charts with nested factors using Graph Builder, displaying standard deviation charts and configuring legend properties.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 528, 450 ),
    Show Control Panel( 0 ),
    Variables( X( :weight ), Y( Transform Column( "height^3", Format( "Fixed Dec", 5, 0 ), Formula( :height ^ 3 ) ) ) ),
    Elements( Line( X, Y, Legend( 7 ) ) ),
    SendToReport(
        Dispatch( {}, "400", ScaleBox,
            {Legend Model(
                7,
                Properties(
                    0,
                    {Line Label Properties( {Last Label( 1 ), Label Format( "Engineering SI", 9, 2 ), Width( 9 )} )},
                    Item ID( "Mean", 1 )
                )
            )}
        )
    )
);
Graph Builder(
    Size( 528, 450 ),
    Show Control Panel( 0 ),
    Variables( X( :weight ), Y( Transform Column( "height^3", Format( "Fixed Dec", 5, 0 ), Formula( :height ^ 3 ) ) ) ),
    Elements( Line( X, Y, Legend( 7 ) ) ),
    SendToReport(
        Dispatch( {}, "400", ScaleBox,
            {Legend Model(
                7,
                Properties(
                    0,
                    {Line Label Properties( {Last Label( 1 ), Label Format( "Engineering", 9, 2 ), Width( 9 )} )},
                    Item ID( "Mean", 1 )
                )
            )}
        )
    )
);

Code Explanation:

1. Open data_table data
2. Create first Graph Builder window.
3. Set window size.
4. Hide control panel.
5. Define X as weight.
6. Transform height to height^3.
7. Define Y as transformed height.
8. Add line element.
9. Configure legend properties.
10. Create second Graph Builder window.

Example 1480

Summary: Creates a variability chart with nested factors using operator and part configurations, displaying standard deviation charts.

Code:

Open("data_table.jmp");
Graph Builder( Size( 522, 452 ), Show Control Panel( 0 ), Variables( Y( :height ) ), Elements( Line( Y, Legend( 4 ), Row order( 1 ) ) ) );

Code Explanation:

1. Open data table.
2. Launch Graph Builder.
3. Set window size.
4. Hide control panel.
5. Define Y variable.
6. Add line element.
7. Set legend position.
8. Order by row.

Example 1481

Summary: Creates a Graph Builder window with a line of fit element, filtered by 'Airline' column, to visualize the relationship between 'Net Cost' and 'Departure Day of Week'.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 524, 270 ),
    Show Control Panel( 0 ),
    Show Legend( 0 ),
    Variables( Y( :Net Cost ), Group X( :Departure Day of Week ) ),
    Elements( Line Of Fit( Y, Legend( 40 ) ) ),
    Local Data Filter(
        Add Filter(
            columns( :Airline ),
            Where( :Airline == {"Carrier 1", "Carrier 2"} ),
            Display( :Airline, Size( 181, 68 ), List Display )
        )
    )
);

Code Explanation:

1. Open data table;
2. Create Graph Builder window.
3. Set window size to 524x270.
4. Hide control panel.
5. Hide legend.
6. Set Y variable to "Net Cost".
7. Set X variable to "Departure Day of Week".
8. Add line of fit element.
9. Add local data filter.
10. Configure filter for "Airline" column.

Example 1482

Summary: Creates a line graph with age on the x-axis, weight on the y-axis, and height as an interval, using Graph Builder

Code:

Open("data_table.jmp");
Graph Builder( Show Control Panel( 0 ), Variables( X( :age ), Y( :weight ), Interval( :height ) ), Elements( Line( X, Y, Legend( 4 ) ) ) );

Code Explanation:

1. Open data table;
2. Create Graph Builder object.
3. Hide control panel.
4. Set X variable to age.
5. Set Y variable to weight.
6. Add interval for height.
7. Add line element.
8. Assign legend to line.

Example 1483

Summary: Creates a variability chart with nested factors using Graph Builder, featuring transformed columns w1 and w2, and displaying standard deviation charts.

Code:

Open("data_table.jmp");
Graph Builder(
    Show Control Panel( 0 ),
    Variables(
        X( :age ),
        Y( :weight ),
        Interval( Transform Column( "w1", Format( "Fixed Dec", 5, 0 ), Formula( Sqrt( :weight ) + :weight ) ) ),
        Interval( Transform Column( "w2", Formula( :weight - Log( :weight ) ) ) )
    ),
    Elements( Line( X, Y, Legend( 5 ) ) ),
    SendToReport(
        Dispatch( {}, "400", ScaleBox, {Legend Model( 5, Base( 1, 0, 0 ), Properties( 1, {Line Color( -3231636 )} ) )} ),
        Dispatch( {}, "Graph Builder", FrameBox, {Grid Line Order( 2 ), Reference Line Order( 3 )} )
    )
);

Code Explanation:

1. Open data table;
2. Launch Graph Builder.
3. Hide control panel.
4. Set X variable to age.
5. Set Y variable to weight.
6. Create interval with transformed column w1.
7. Create interval with transformed column w2.
8. Add line element.
9. Customize legend properties.
10. Adjust grid and reference line order.

Example 1484

Summary: Creates a variability chart with nested factors using Graph Builder, displaying standard deviation charts and customizing legend properties.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 534, 520 ),
    Show Control Panel( 0 ),
    Variables( X( :age ), Y( :weight ), Interval( :height ) ),
    Elements( Line( X, Y, Legend( 3 ) ) ),
    SendToReport( Dispatch( {}, "400", ScaleBox, {Legend Model( 3, Properties( 0, {Line Color( 6 )} ) )} ) )
);

Code Explanation:

1. Open data table;
2. Launch Graph Builder.
3. Set window size.
4. Hide control panel.
5. Assign variables.
6. Add line element.
7. Customize legend properties.
8. Set line color.

Example 1485

Summary: Creates three Graph Builder windows to visualize the relationship between weight and age, with varying line connections and smoothness settings.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 524, 454 ),
    Show Control Panel( 0 ),
    Variables( X( :weight ), Y( :age ) ),
    Elements( Line( X, Y, Legend( 6 ), Connection( "Centered Step" ) ), Points( X, Y, Legend( 7 ), Summary Statistic( "Mean" ) ) )
);
Graph Builder(
    Size( 524, 454 ),
    Show Control Panel( 0 ),
    Variables( X( :weight ), Y( :age ) ),
    Elements( Line( X, Y, Legend( 6 ), Connection( "Step" ) ), Points( X, Y, Legend( 7 ), Summary Statistic( "Mean" ) ) )
);
Graph Builder(
    Size( 524, 454 ),
    Show Control Panel( 0 ),
    Variables( X( :weight ), Y( :age ) ),
    Elements(
        Line( X, Y, Legend( 6 ), Connection( "Horizontal" ), Smoothness( 0.5 ) ),
        Points( X, Y, Legend( 7 ), Summary Statistic( "Mean" ) )
    )
);

Code Explanation:

1. Open data table.
2. Create first graph builder window.
3. Set size to 524x454.
4. Hide control panel.
5. Assign weight to X-axis.
6. Assign age to Y-axis.
7. Add centered step line element.
8. Add mean points element.
9. Create second graph builder window.
10. Repeat steps 3-8 but use step connection.
11. Create third graph builder window.
12. Repeat steps 3-8 but use horizontal connection and 0.5 smoothness.

Example 1486

Summary: Creates multiple graph builder windows with varying line connections and display standard deviation charts for a dataset with nested factors.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 524, 454 ),
    Show Control Panel( 0 ),
    Variables( X( :weight ), Y( :age ) ),
    Elements( Line( X, Y, Legend( 6 ), Connection( "Centered Step" ) ), Points( X, Y, Legend( 7 ), Summary Statistic( "Mean" ) ) )
);
Graph Builder(
    Size( 524, 454 ),
    Show Control Panel( 0 ),
    Variables( X( :weight ), Y( :age ) ),
    Elements( Line( X, Y, Legend( 6 ), Connection( "Step" ) ), Points( X, Y, Legend( 7 ), Summary Statistic( "Mean" ) ) )
);
Graph Builder(
    Size( 524, 454 ),
    Show Control Panel( 0 ),
    Variables( X( :weight ), Y( :age ) ),
    Elements(
        Line( X, Y, Legend( 6 ), Connection( "Horizontal" ), Smoothness( 0.5 ) ),
        Points( X, Y, Legend( 7 ), Summary Statistic( "Mean" ) )
    )
);
Graph Builder(
    Size( 524, 454 ),
    Show Control Panel( 0 ),
    Variables( X( :weight ), Y( :age ) ),
    Elements(
        Line( X, Y, Legend( 6 ), Connection( "Vertical" ), Smoothness( 0.5 ) ),
        Points( X, Y, Legend( 7 ), Summary Statistic( "Mean" ) )
    )
);

Code Explanation:

1. Open data table.
2. Create graph builder window.
3. Set size 524x454.
4. Hide control panel.
5. Assign weight to X-axis.
6. Assign age to Y-axis.
7. Add centered step line element.
8. Add mean points element.
9. Create another graph builder window.
10. Repeat steps 3-8 with step connection.
11. Create third graph builder window.
12. Repeat steps 3-8 with horizontal connection.
13. Set smoothness to 0.5.
14. Create fourth graph builder window.
15. Repeat steps 3-8 with vertical connection.
16. Set smoothness to 0.5.

Example 1487

Summary: Creates a variability chart with nested factors using operator and part configurations, displaying standard deviation charts.

Code:

dt = Open("data_table.jmp");
obj = Graph Builder(
    Size( 534, 418 ),
    Show Control Panel( 0 ),
    Variables( X( :age, Size( 0, 20 ) ), Y( :height, Size( 0, 36 ) ), Y( :weight ) ),
    Elements( Position( 1, 1 ), Line( Y, Legend( 3 ) ) ),
    Elements( Position( 1, 2 ), Line( X, Y, Legend( 5 ) ) )
);

Code Explanation:

1. Open data table.
2. Create Graph Builder object.
3. Set window size.
4. Hide control panel.
5. Define X and Y variables.
6. Add first line element.
7. Add second line element.

Example 1488

Summary: Creates a variability chart with nested factors using operator and part configurations, displaying standard deviation charts in JMP.

Code:

dt under test = Open("data_table.jmp");
obj = Graph Builder(
    Show Control Panel( 0 ),
    Variables( X( :Durability ), Y( :Distance ), Group X( :Brand ) ),
    Elements( Line( X, Y, Legend( 31 ), Summary Statistic( "Median" ) ), Points( X, Y, Legend( 33 ) ) ),
    SendToReport(
        Dispatch( {}, "400", LegendBox, {Legend Position( {0, 1} )} ),
        Dispatch( {}, "Graph Builder", FrameBox, {Background Color( 67 )} ),
        Dispatch( {}, "Graph Builder", FrameBox( 2 ), {Background Color( 35 )} ),
        Dispatch( {}, "Graph Builder", FrameBox( 3 ), {Background Color( 3 )} )
    )
);

Code Explanation:

1. Open data table.
2. Create Graph Builder object.
3. Hide control panel.
4. Set X, Y, and Group X variables.
5. Add Line element with median summary.
6. Add Points element.
7. Set legend position.
8. Change first frame background color.
9. Change second frame background color.
10. Change third frame background color.

Example 1489

Summary: Creates a line chart with nested factors using Graph Builder, configuring scales and legend colors for DJI High, Close, and Low variables.

Code:

dt under test = Open("data_table.jmp");
obj = Graph Builder(
    Show Control Panel( 0 ),
    Variables( X( :Date ), Y( :DJI High ), Y( :DJI Close, Position( 1 ) ), Y( :DJI Low, Position( 1 ) ) ),
    Elements( Line( X, Y( 1 ), Y( 2 ), Y( 3 ), Legend( 13 ) ) ),
    SendToReport(
        Dispatch( {}, "Date", ScaleBox, {Label Row( {Show Major Grid( 1 ), Major Grid Line Color( 1 )} )} ),
        Dispatch( {}, "DJI High", ScaleBox, {Label Row( {Show Major Grid( 1 ), Major Grid Line Color( 1 )} )} ),
        Dispatch( {}, "400", ScaleBox,
            {Legend Model(
                13,
                Properties( 0, {Line Color( 52 )} ),
                Properties( 1, {Line Color( 73 )} ),
                Properties( 2, {Line Color( 19 )} )
            )}
        ),
        Dispatch( {}, "Graph Builder", FrameBox, {Background Color( 32 )} )
    )
);

Code Explanation:

1. Open table.
2. Create Graph Builder object.
3. Hide control panel.
4. Set X variable to Date.
5. Set Y variables: DJI High, DJI Close, DJI Low.
6. Add Line element for all Y variables.
7. Configure Date scale with major grid.
8. Configure DJI High scale with major grid.
9. Customize legend colors for each line.
10. Set background color for graph.

Example 1490

Summary: Creates a variability chart with nested factors using Graph Builder, displaying standard deviation charts and adjusting X-axis scale settings.

Code:

dt under test = Open("data_table.jmp");
obj = Graph Builder(
    Size( 1150, 977 ),
    Show Control Panel( 0 ),
    Variables( X( :State ), Y( :Name( "% Taking (2004)" ) ) ),
    Elements( Bar( X, Y, Legend( 8 ) ) ),
    SendToReport(
        Dispatch( {}, "State", ScaleBox,
            {Min( -0.338631 ), Max( 50.6613691343982 ), Inc( 1 ), Minor Ticks( 0 ), Label Row( Label Orientation( "Angled" ) )}
        )
    )
);

Code Explanation:

1. Open data table.
2. Create Graph Builder object.
3. Set graph size.
4. Hide control panel.
5. Define X and Y variables.
6. Add bar element.
7. Send report settings.
8. Adjust X-axis scale.
9. Set X-axis min and max.
10. Configure X-axis ticks and labels.

Example 1491

Summary: Creates a bar chart with nested factors using Graph Builder, displaying standard deviation charts and configuring axis scale settings.

Code:

dt under test = Open("data_table.jmp");
obj = Graph Builder(
    Size( 1150, 977 ),
    Show Control Panel( 0 ),
    Variables( X( :State ), Y( :Name( "% Taking (2004)" ) ) ),
    Elements( Bar( X, Y, Legend( 8 ) ) ),
    SendToReport(
        Dispatch( {}, "State", ScaleBox,
            {Min( -0.338631 ), Max( 50.6613691343982 ), Inc( 1 ), Minor Ticks( 0 ), Label Row( Label Orientation( "Perpendicular" ) )}
        )
    )
);

Code Explanation:

1. Open data table;
2. Create Graph Builder object.
3. Set graph size to 1150x977.
4. Hide control panel.
5. Assign X variable as State.
6. Assign Y variable as % Taking (2004).
7. Add bar element to graph.
8. Send report settings.
9. Configure State axis scale.
10. Set label orientation to perpendicular.

Example 1492

Summary: Creates a bar chart to visualize the relationship between State and Name, utilizing Graph Builder and SendToReport features.

Code:

dt under test = Open("data_table.jmp");
obj = Graph Builder(
    Size( 1150, 977 ),
    Show Control Panel( 0 ),
    Variables( X( :State ), Y( :Name( "% Taking (2004)" ) ) ),
    Elements( Bar( X, Y, Legend( 8 ) ) ),
    SendToReport(
        Dispatch( {}, "State", ScaleBox,
            {Min( -0.338631 ), Max( 50.6613691343982 ), Inc( 1 ), Minor Ticks( 0 ), Label Row( Label Orientation( "Vertical" ) )}
        )
    )
);

Code Explanation:

1. Open data table.
2. Create Graph Builder object.
3. Set graph size.
4. Hide control panel.
5. Assign X and Y variables.
6. Add bar element.
7. Configure report settings.
8. Adjust X-axis scale.
9. Set X-axis range.
10. Enable vertical labels.

Example 1493

Summary: Creates a variability chart with nested factors using Graph Builder, displaying standard deviation charts and enabling horizontal connections.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 606, 546 ),
    Variables( X( :height ), Y( :weight ), Overlay( :sex ) ),
    Elements( Line( X, Y, Legend( 3 ), Connection( "Horizontal" ), Smoothness( 0.5 ) ) )
);

Code Explanation:

1. Open data table;
2. Launch Graph Builder.
3. Set window size.
4. Assign variables to axes.
5. Add overlay variable.
6. Create line element.
7. Set legend position.
8. Enable horizontal connections.
9. Adjust smoothness level.
10. Display graph.

Example 1494

Summary: Creates two line graphs with horizontal and vertical connections, overlayed by sex, to visualize relationships between height and weight.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 606, 546 ),
    Variables( X( :height ), Y( :weight ), Overlay( :sex ) ),
    Elements( Line( X, Y, Legend( 3 ), Connection( "Horizontal" ), Smoothness( 0.5 ) ) )
);
Graph Builder(
    Size( 606, 546 ),
    Variables( X( :height ), Y( :weight ), Overlay( :sex ) ),
    Elements( Line( X, Y, Legend( 3 ), Connection( "Vertical" ), Smoothness( 0.5 ) ) )
);

Code Explanation:

1. Open data table;
2. Create horizontal line graph.
3. Set graph size.
4. Define variables for x and y axes.
5. Overlay by sex variable.
6. Add line element with horizontal connection.
7. Set smoothness to 0.5.
8. Create vertical line graph.
9. Set graph size.
10. Define variables for x and y axes.
11. Overlay by sex variable.
12. Add line element with vertical connection.
13. Set smoothness to 0.5.

Example 1495

Summary: Creates a line graph with nested factors using Graph Builder, displaying standard deviation charts and configuring legend position 3.

Code:

Open("data_table.jmp");
Graph Builder( Variables( Y( :Quarter ) ), Elements( Line( Y, Legend( 3 ) ) ) );

Code Explanation:

1. Open data table.
2. Create Graph Builder window.
3. Set Y variable to "Quarter".
4. Add Line element to graph.
5. Assign legend position 3.

Example 1496

Summary: Creates a variability chart with nested factors using Graph Builder, displaying points and smoother elements.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 606, 546 ),
    Variables( X( :height ), Y( :weight ), Overlay( :sex ) ),
    Elements( Points( X, Y, Legend( 1 ) ), Smoother( X, Y, Legend( 2 ) ) )
);

Code Explanation:

1. Open data table.
2. Launch Graph Builder.
3. Set window size.
4. Assign X variable.
5. Assign Y variable.
6. Add overlay variable.
7. Plot points element.
8. Add smoother element.
9. Label points legend.
10. Label smoother legend.

Example 1497

Summary: Creates a graph builder window with a line element to visualize data relationships between age and height.

Code:

Open("data_table.jmp");
Graph Builder( Size( 570, 497 ), Show Control Panel( 0 ), Variables( X( :age ), Color( :height ) ), Elements( Line( X, Legend( 23 ) ) ) );

Code Explanation:

1. Open data table;
2. Create Graph Builder window.
3. Set window size.
4. Hide control panel.
5. Assign X variable.
6. Assign color variable.
7. Add line element.
8. Set legend position.

Example 1498

Summary: Creates a variability chart with nested factors using Graph Builder, displaying standard deviation charts and customizing legend positions.

Code:

Open("data_table.jmp") << Graph Builder(
    Size( 451, 428 ),
    Show Control Panel( 0 ),
    Variables( X( :age ), Y( :weight ), Y( :height ), Overlay( :sex ) ),
    Elements( Position( 1, 1 ), Line( X, Y, Legend( 26 ), Summary Statistic( "Sum" ) ) ),
    Elements( Position( 1, 2 ), Line( X, Y, Legend( 28 ) ), Line( X, Y, Legend( 27 ) ) ),
    SendToReport(
        Dispatch( {}, "400", ScaleBox,
            {Legend Model( 28, Base( 0, 0, 0 ), Base( 1, 0, 0 ) ), Legend Model( 27, Base( 0, 0, 0 ), Base( 1, 0, 0 ) )}
        ),
        Dispatch( {}, "400", LegendBox, {Legend Position( {26, [2, 3], 28, [4, 5], 27, [0, 1]} )} )
    )
);

Code Explanation:

1. Open data_table data
2. Create Graph Builder window.
3. Set size to 451x428.
4. Hide control panel.
5. Define X as age, Y as weight and height.
6. Overlay by sex.
7. Add first line element for weight.
8. Add second line element for height.
9. Customize legend positions.
10. Adjust scale box legends.

Example 1499

Summary: Creates a variability chart with nested factors using Graph Builder, displaying standard deviation charts and configuring line elements to connect Y1 and Y2.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 481, 468 ),
    Show Control Panel( 0 ),
    Show Legend( 0 ),
    Variables( X( :Position2 ), Y( :Weight ), Y( :Height, Position( 1 ) ), Group X( :Speed ), Group Y( :Bench ) ),
    Elements( Line( X, Y( 1 ), Y( 2 ), Legend( 14 ), Missing Factors( "Treat as Zero" ), Missing Values( "No Connection" ) ) )
);

Code Explanation:

1. Open data table;
2. Create Graph Builder window.
3. Set size to 481x468.
4. Hide control panel.
5. Hide legend.
6. Assign variables: X=Position2, Y1=Weight, Y2=Height.
7. Group X by Speed, Y by Bench.
8. Add line element.
9. Connect Y1 and Y2.
10. Treat missing factors as zero.
11. Do not connect missing values.

Example 1500

Summary: Creates a variability chart with nested factors using operator and part configurations, displaying standard deviation charts.

Code:

Open("data_table.jmp");
Graph Builder(
    Variables( X( :Channel ), X( :Quarter, Position( 1 ) ), Y( :Profit ), Size( :Revenue ) ),
    Elements( Line( X( 2 ), X( 1 ), Y, Legend( 4 ) ) )
);

Code Explanation:

1. Open data table;
2. Create Graph Builder window.
3. Set X-axis variable.
4. Set second X-axis variable.
5. Set Y-axis variable.
6. Set size variable.
7. Add line element.
8. Set line X-axes.
9. Set line Y-axis.
10. Add legend to line.

Example 1501

Summary: Creates a variability chart with nested factors using Graph Builder, displaying points, line of fit, and line elements.

Code:

dt = Open("data_table.jmp");

obj = dt << Graph Builder(
    Show Control Panel( 0 ),
    Size( 773, 599 ),
    Variables( X( :Rating ), Y( :Domestic $ ) ),
    Elements( Points( X, Y, Legend( 3 ) ), Line Of Fit( Y, Legend( 4 ) ), Line( Y, Legend( 5 ) ) ),
    SendToReport(
        Dispatch( {}, "Points", OutlineBox, {Close( 1 )} ),
        Dispatch( {"Line Of Fit"}, "", OutlineBox, {Close( 0 )} ),
        Dispatch( {"Line"}, "", OutlineBox, {Close( 0 )} )
    )
);

Code Explanation:

1. Open data table;
2. Create Graph Builder object.
3. Hide control panel.
4. Set graph size.
5. Assign X variable: Rating.
6. Assign Y variable: Domestic $.
7. Add points element.
8. Add line of fit element.
9. Add line element.
10. Close all outline boxes in report.

Example 1502

Summary: Creates a graph builder window with a line of fit element, utilizing Graph Builder to visualize the relationship between age and height.

Code:

dt = Open("data_table.jmp");
Graph Builder(
    Size( 432, 303 ),
    Show Control Panel( 0 ),
    Fit to Window( "Off" ),
    Variables( X( :age ), Y( :height ) ),
    Elements( Line Of Fit( X, Y, Legend( 3 ) ) ),
    SendToReport(
        Dispatch( {}, "height", ScaleBox, {Scale( "Power" ), Format( "Best", 12 ), Min( 55 ), Max( 75 ), Inc( 5 ), Minor Ticks( 0 )} )
    )
);

Code Explanation:

1. Open data table;
2. Create Graph Builder window.
3. Set window size.
4. Hide control panel.
5. Disable fit to window.
6. Assign age to X-axis.
7. Assign height to Y-axis.
8. Add line of fit element.
9. Customize Y-axis scale.
10. Set scale type to power.
11. Format numbers to best.
12. Set Y-axis min to 55.
13. Set Y-axis max to 75.
14. Set Y-axis increment to 5.
15. Disable minor ticks on Y-axis.

Example 1503

Summary: Creates a graph builder with a line of fit to visualize the relationship between Color and Clarity.

Code:

Open("data_table.jmp");
gb = Graph Builder(
    Size( 534, 450 ),
    Show Control Panel( 0 ),
    Variables( X( :Color ), Y( :Clarity ) ),
    Elements( Line Of Fit( X, Y, Legend( 3 ) ) )
);

Code Explanation:

1. Open data table;
2. Create Graph Builder object.
3. Set graph size.
4. Hide control panel.
5. Assign X variable.
6. Assign Y variable.
7. Add Line Of Fit element.
8. Set legend position.

Example 1504

Summary: Creates a graph builder with a line of fit to visualize the relationship between Color and Clarity, displaying the journal box report in a new window.

Code:

Open("data_table.jmp");
gb = Graph Builder(
    Size( 534, 450 ),
    Show Control Panel( 0 ),
    Variables( X( :Color ), Y( :Clarity ) ),
    Elements( Line Of Fit( X, Y, Legend( 3 ) ) )
);
w = New Window( "Crashy", Journal Box( Report( gb )[Frame Box( 1 )] << Get Journal ) );

Code Explanation:

1. Open data table;
2. Create Graph Builder object.
3. Set window size.
4. Hide control panel.
5. Assign X and Y variables.
6. Add Line Of Fit element.
7. Create new window.
8. Name window "Crashy".
9. Insert graph report into window.
10. Display journal box.

Example 1505

Summary: Creates a graph builder with nested factors, utilizing Graph Builder to visualize relationships between weight and height.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 570, 502 ),
    Variables( X( :weight ), Y( :height ) ),
    Elements( Points( X, Y, Legend( 3 ) ), Line Of Fit( X, Y, Legend( 5 ), Equation( 1 ) ) ),
    SendToReport(
        Dispatch( {}, "height", ScaleBox, {Scale( "Log", {Log Base( 2 )} ), Min( 50 ), Max( 80.0000000000001 ), Minor Ticks( 1 )} )
    )
);

Code Explanation:

1. Open data table.
2. Launch Graph Builder.
3. Set graph size.
4. Assign X and Y variables.
5. Add points element.
6. Add line of fit element.
7. Customize legend for points.
8. Customize legend for line of fit.
9. Set Y axis to log scale.
10. Configure log base and axis limits.

Example 1506

Summary: Creates a graph builder object with a line of fit element, and configures the report to display a dashed gray line.

Code:

dt = Open("data_table.jmp");
gb = dt << Graph Builder( Size( 400, 280 ), Show Control Panel( 0 ), Variables( Y( :height ) ), Elements( Line Of Fit( Y, Legend( 3 ) ) ) );
rgb = gb << report;
rs = rgb[FrameBox( 1 )] << Find Seg( RectSeg( 1 ) );
rs << set line color( "Plain Gray" );
rs << set line style( "Dashed" );

Code Explanation:

1. Open data table.
2. Create graph builder object.
3. Set graph size.
4. Hide control panel.
5. Assign Y variable.
6. Add line of fit element.
7. Generate graph report.
8. Locate first frame box.
9. Find rectangular segment.
10. Set line color to gray.
11. Set line style to dashed.

Example 1507

Summary: Creates a graph builder object with a line of fit element to visualize height data, and customizes the appearance of the resulting report.

Code:

dt = Open("data_table.jmp");
gb = dt << Graph Builder( Size( 400, 280 ), Show Control Panel( 0 ), Variables( Y( :height ) ), Elements( Line Of Fit( Y, Legend( 3 ) ) ) );
rgb = gb << report;
rs = rgb[FrameBox( 1 )] << Find Seg( RectSeg( 1 ) );
rs << set line color( "Plain Gray" );
rs << set line style( "Dashed" );
rs << set line width( 4 );

Code Explanation:

1. Open data table;
2. Create graph builder object.
3. Set graph size and hide control panel.
4. Add height variable to Y axis.
5. Add line of fit element.
6. Generate graph report.
7. Access first frame box.
8. Find rectangular segment.
9. Set line color to gray.
10. Set line style to dashed.
11. Set line width to 4.

Example 1508

Summary: Creates a variability chart with nested factors using Graph Builder, configuring axis settings and displaying standard deviation charts.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 433, 303 ),
    Show Control Panel( 0 ),
    Fit to Window( "Off" ),
    Variables( Y( :height ) ),
    Elements( Line Of Fit( Y, Legend( 3 ) ) ),
    SendToReport(
        Dispatch( {}, "height", ScaleBox, {Scale( "Log" ), Format( "Best", 12 ), Min( 55 ), Max( 75 ), Inc( 1 ), Minor Ticks( 1 )} )
    )
);

Code Explanation:

1. Open data table;
2. Launch Graph Builder.
3. Set window size.
4. Hide control panel.
5. Disable fit to window.
6. Assign height as Y variable.
7. Add line of fit element.
8. Send report to Graph Builder.
9. Set scale type to log.
10. Configure axis settings.

Example 1509

Summary: Creates a variability chart with nested factors using Graph Builder, displaying standard deviation charts and configuring graph size and control panel.

Code:

Open("data_table.jmp");
Graph Builder(
    Transform Column( "height 2", Formula( :height + 1e8 ) ),
    Transform Column( "height 3", Formula( :height + 1e9 ) ),
    Size( 985, 333 ),
    Show Control Panel( 0 ),
    Variables( X( :height ), X( :height 2 ), X( :height 3 ), Y( :weight ) ),
    Elements( Position( 1, 1 ), Points( X, Y ), Line Of Fit( X, Y ) ),
    Elements( Position( 2, 1 ), Points( X, Y ), Line Of Fit( X, Y ) ),
    Elements( Position( 3, 1 ), Points( X, Y ), Line Of Fit( X, Y ) )
);

Code Explanation:

1. Open data table;
2. Create new column "height 2".
3. Set formula for "height 2".
4. Create new column "height 3".
5. Set formula for "height 3".
6. Set graph size.
7. Hide control panel.
8. Define variables for graph.
9. Add points and line of fit for first element.
10. Add points and line of fit for second element.
11. Add points and line of fit for third element.

Example 1510

Summary: Creates a graph builder object with nested factors, displaying points and line of fit elements.

Code:

Open("data_table.jmp");
obj = Graph Builder(
    Size( 534, 456 ),
    Show Control Panel( 0 ),
    Variables( X( :height ), Y( :weight ), Color( :weight ) ),
    Elements( Points( X, Y, Legend( 2 ) ), Line Of Fit( X, Y, Legend( 6 ) ) )
);
frame = Report( obj )[FrameBox( 1 )];
fontobj = seg = (frame << Find Seg( "Line Seg" ));

Code Explanation:

1. Open data table;
2. Create Graph Builder object.
3. Set window size.
4. Hide control panel.
5. Define variables: X, Y, Color.
6. Add points element.
7. Add line of fit element.
8. Access frame box.
9. Find line segment.
10. Assign found segment to variable.

Example 1511

Summary: Creates a graph with points and line of fit, color-coded by weight, using Graph Builder to visualize data from an open JMP data table.

Code:

Open("data_table.jmp");
obj = Graph Builder(
    Size( 534, 456 ),
    Show Control Panel( 0 ),
    Variables( X( :height ), Y( :weight ), Color( :weight ) ),
    Elements( Points( X, Y, Legend( 2 ) ), Line Of Fit( X, Y, Legend( 6 ) ) )
);
frame = Report( obj )[FrameBox( 1 )];
fontobj = seg = (frame << Find Seg( "Line Seg" ));
seg << Set Line Color( "Red" );

Code Explanation:

1. Open data table;
2. Create Graph Builder object.
3. Set graph size.
4. Hide control panel.
5. Define variables: X, Y, Color.
6. Add points and line of fit elements.
7. Access first frame box.
8. Find line segment.
9. Change line color to red.

Example 1512

Summary: Creates a graph builder with points and line of fit elements to visualize height vs. weight data, displaying root mean square error.

Code:

Open("data_table.jmp");
Graph Builder(
    Show Control Panel( 0 ),
    Variables( X( :height ), Y( :weight ) ),
    Elements( Points( X, Y, Legend( 2 ) ), Line Of Fit( X, Y, Legend( 4 ), Root Mean Square Error( 1 ) ) )
);

Code Explanation:

1. Open data table;
2. Create Graph Builder.
3. Hide control panel.
4. Set X variable to height.
5. Set Y variable to weight.
6. Add points element.
7. Add line of fit element.
8. Display RMSE on line.

Example 1513

Summary: Creates a graph with a line of fit and confidence prediction, using Graph Builder to visualize the relationship between height and weight in a data table.

Code:

Open("data_table.jmp");
Graph Builder(
    Show Control Panel( 0 ),
    Variables( X( :height ), Y( :weight ) ),
    Elements( Line Of Fit( X, Y, Confidence of Fit( 0 ), Confidence of Prediction ) ),
    Dispatch( {}, "weight", ScaleBox, Scale( "Log" ) )
);

Code Explanation:

1. Open data table;
2. Launch Graph Builder.
3. Hide control panel.
4. Set X variable to height.
5. Set Y variable to weight.
6. Add Line of Fit element.
7. Disable confidence of fit line.
8. Enable confidence of prediction line.
9. Log-transform Y scale.
10. Display graph.

Example 1514

Summary: Creates a graph builder with points and line of fit elements to visualize the relationship between height and weight, including confidence intervals, root mean square error, and R² value.

Code:

Open("data_table.jmp");
Graph Builder(
    Show Control Panel( 0 ),
    Variables( X( :height ), Y( :weight ) ),
    Elements(
        Points( X, Y, Legend( 2 ) ),
        Line Of Fit( X, Y, Legend( 4 ), Confidence of Prediction( 1 ), Root Mean Square Error( 1 ), R²( 1 ), Equation( 1 ) )
    ),
    SendToReport( Dispatch( {}, "Graph Builder", FrameBox, {DispatchSeg( Text Seg( 1 ), Set Location( 0.67, 0.85 ) )} ) )
);

Code Explanation:

1. Open data table;
2. Launch Graph Builder.
3. Hide control panel.
4. Set X variable to height.
5. Set Y variable to weight.
6. Add points element.
7. Add line of fit element.
8. Display confidence interval.
9. Display root mean square error.
10. Display R² value.
11. Display equation.
12. Move text segment.

Example 1515

Summary: Creates a variability chart with nested factors using Graph Builder, displaying standard deviation charts and means.

Code:

dt = Open("data_table.jmp");
Graph Builder(
    Size( 477, 344 ),
    Show Control Panel( 0 ),
    Variables( X( :age ), Y( :height ), Group Y( :sex ), Color( :sex ) ),
    Elements( Line Of Fit( X, Y, Legend( 6 ), Confidence of Fit( 0 ), Means and Std Devs( 1 ) ) )
);

Code Explanation:

1. Open data table;
2. Create Graph Builder window.
3. Set window size.
4. Hide control panel.
5. Define X variable as age.
6. Define Y variable as height.
7. Group Y by sex.
8. Color elements by sex.
9. Add Line of Fit element.
10. Display means and standard deviations.

Example 1516

Summary: Creates a graph builder object to visualize the relationship between age and height, grouped by sex, with a line of fit and standard deviation charts.

Code:

Open("data_table.jmp");
Graph Builder(
    Show Control Panel( 0 ),
    Variables( X( :age ), Y( :height ), Group Y( :sex ), Color( :sex ) ),
    Elements( Line Of Fit( X, Y, Legend( 6 ), Confidence of Fit( 0 ), Means and Std Devs( 1 ) ) ),
    SendToReport( Dispatch( {}, "Graph Builder", FrameBox( 2 ), {DispatchSeg( LabelSeg( 1 ), {Text Color( "Medium Dark Blue" )} )} ) )
);

Code Explanation:

1. Open data table;
2. Create graph builder object.
3. Hide control panel.
4. Set X variable to age.
5. Set Y variable to height.
6. Group Y by sex.
7. Color by sex.
8. Add line of fit element.
9. Disable confidence of fit.
10. Enable means and standard deviations.

Example 1517

Summary: Creates a Graph Builder window with a line of fit and points element to visualize the relationship between height and weight.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 534, 454 ),
    Show Control Panel( 0 ),
    Variables( X( :height ), Y( :weight ) ),
    Elements( Points( X, Y, Legend( 3 ) ), Line Of Fit( X, Y, Legend( 5 ) ) )
);

Code Explanation:

1. Open data table;
2. Create Graph Builder window.
3. Set window size.
4. Hide control panel.
5. Define X variable.
6. Define Y variable.
7. Add points element.
8. Add line of fit element.
9. Assign legend to points.
10. Assign legend to line of fit.

Example 1518

Summary: Creates a graph builder with a line of fit to visualize the relationship between species and sepal length, utilizing Graph Builder.

Code:

Open("data_table.jmp") << Graph Builder(
    Size( 422, 241 ),
    Show Control Panel( 0 ),
    Variables( X( :Species ), Y( :Sepal length ) ),
    Elements( Line Of Fit( X, Y, Legend( 4 ) ) )
);

Code Explanation:

1. Open data table;
2. Launch Graph Builder.
3. Set window size.
4. Hide control panel.
5. Assign Species to X-axis.
6. Assign Sepal length to Y-axis.
7. Add Line of Fit element.
8. Customize legend position.

Example 1519

Summary: Creates a variability chart with nested factors using Graph Builder and Oneway, displaying standard deviation charts for data analysis.

Code:

dt = Open("data_table.jmp");
gb = Graph Builder(
    Size( 431, 321 ),
    Show Control Panel( 0 ),
    Variables( X( :age ), Y( :height ) ),
    Elements( Line Of Fit( X, Y, Legend( 5 ), Unequal Variances( 1 ), Confidence of Prediction( 1 ), Means and Std Devs( 1 ) ) )
);
ow = Oneway(
    Y( :height ),
    X( :age ),
    Means and Std Dev( 1 ),
    Mean Lines( 1 ),
    Mean Error Bars( 1 ),
    Std Dev Lines( 1 ),
    X Axis Proportional( 0 ),
    Grand Mean( 0 )
);

Code Explanation:

1. Open data table.
2. Create Graph Builder object.
3. Set window size.
4. Hide control panel.
5. Assign X and Y variables.
6. Add Line of Fit element.
7. Configure Line of Fit options.
8. Create Oneway object.
9. Set Y and X variables.
10. Configure Oneway plot options.

Example 1520

Summary: Creates a variability chart with nested factors using Graph Builder and Fit Group, displaying standard deviation charts for height and weight.

Code:

dt = Open("data_table.jmp");
gb = Graph Builder(
    Size( 534, 448 ),
    Show Control Panel( 0 ),
    Variables( X( :age ), Y( :height ), Y( :weight, Position( 1 ) ) ),
    Elements( Points( X, Y( 1 ), Y( 2 ), Legend( 3 ) ), Line Of Fit( X, Y( 1 ), Y( 2 ), Legend( 4 ), Root Mean Square Error( 1 ) ) )
);
ow = Fit Group(
    Oneway( Y( :height ), X( :age ), Means( 1 ), Mean Diamonds( 1 ) ),
    Oneway( Y( :weight ), X( :age ), Means( 1 ), Mean Diamonds( 1 ) ),
    <<{Arrange in Rows( 1 )}
);

Code Explanation:

1. Open data table.
2. Create Graph Builder object.
3. Set graph size.
4. Hide control panel.
5. Define X and Y variables.
6. Add points and line of fit elements.
7. Create Fit Group object.
8. Perform one-way analysis for height.
9. Perform one-way analysis for weight.
10. Arrange plots in rows.

Example 1521

Summary: Creates a variability chart with nested factors using Graph Builder, displaying standard deviation charts and performing an Oneway analysis.

Code:

Open("data_table.jmp");
gb = Graph Builder(
    Size( 658, 387 ),
    Show Control Panel( 0 ),
    Variables( X( :sex ), Y( :height ) ),
    Elements(
        Points( X, Y, Legend( 3 ), Jitter( "None" ) ),
        Line Of Fit( X, Y, Legend( 4 ), Unequal Variances( 1 ), R²( 1 ), F Test( 1 ) )
    )
);
ow = Oneway(
    Y( :height ),
    X( :sex ),
    Means( 1 ),
    Unequal Variances( 1 ),
    Mean Diamonds( 1 ),
    Std Dev Lines( 1 ),
    Equivalence Test( 1 ),
    SendToReport( Dispatch( {}, "Oneway Analysis of height By sex", OutlineBox, {Set Title( "Unequal Variances, Equivalence Test" )} ) )
);

Code Explanation:

1. Open data table;
2. Create Graph Builder object.
3. Set graph size.
4. Hide control panel.
5. Assign X and Y variables.
6. Add points element.
7. Add line of fit element.
8. Create Oneway analysis object.
9. Set Y and X variables.
10. Configure Oneway analysis settings.

Example 1522

Summary: Creates a variability chart with nested factors using Graph Builder, displaying standard deviation charts and customizing legend colors.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 526, 452 ),
    Show Control Panel( 0 ),
    Variables( X( :height ), Y( :weight ) ),
    Elements( Points( X, Y, Legend( 2 ) ), Line Of Fit( X, Y, Legend( 4 ) ) ),
    SendToReport( Dispatch( {}, "400", ScaleBox, {Legend Model( 4, Base( 1, 0, 0 ), Properties( 0, {Line Color( 38 )} ) )} ) )
);

Code Explanation:

1. Open data table;
2. Launch Graph Builder.
3. Set window size.
4. Hide control panel.
5. Define X and Y variables.
6. Add points element.
7. Add line of fit element.
8. Customize legend for points.
9. Customize legend for line of fit.
10. Adjust line color.

Example 1523

Summary: Creates a graph builder with nested factors using Graph Builder, displaying points and line of fit elements.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 528, 448 ),
    Show Control Panel( 0 ),
    Variables( X( :age ), Y( :height ) ),
    Elements( Points( X, Y, Legend( 3 ) ), Line Of Fit( X, Y, Legend( 4 ) ) )
);

Code Explanation:

1. Open data table;
2. Launch Graph Builder.
3. Set window size.
4. Hide control panel.
5. Define X variable.
6. Define Y variable.
7. Add points element.
8. Add line of fit element.
9. Assign legend for points.
10. Assign legend for line of fit.

Example 1524

Summary: Creates a graph builder with nested factors using operator and part configurations, displaying standard deviation charts.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 528, 448 ),
    Show Control Panel( 0 ),
    Variables( X( :sex ), Y( :height ) ),
    Elements( Points( X, Y, Legend( 3 ) ), Line Of Fit( X, Y, Legend( 4 ), Unequal Variances( 1 ), Confidence of Prediction( 1 ) ) )
);

Code Explanation:

1. Open data table.
2. Create Graph Builder object.
3. Set window size.
4. Hide control panel.
5. Define X variable.
6. Define Y variable.
7. Add points element.
8. Add line of fit element.
9. Enable unequal variances.
10. Enable confidence of prediction.

Example 1525

Summary: Creates a variability chart with nested factors using Graph Builder, displaying standard deviation charts and line of fit elements.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 514, 393 ),
    Show Control Panel( 0 ),
    Variables( X( :age ), Y( :height ), Y( :weight, Position( 1 ) ) ),
    Elements( Points( X, Y( 1 ), Y( 2 ), Legend( 3 ) ), Line Of Fit( X, Y( 1 ), Y( 2 ), Legend( 4 ) ) )
);

Code Explanation:

1. Open data table;
2. Create new Graph Builder window.
3. Set window size.
4. Hide control panel.
5. Assign X variable.
6. Assign first Y variable.
7. Assign second Y variable.
8. Add points element.
9. Add line of fit element for first Y.
10. Add line of fit element for second Y.

Example 1526

Summary: Creates a graph builder with nested factors using operator and part configurations, displaying standard deviation charts for females.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 534, 502 ),
    Show Control Panel( 0 ),
    Variables( X( :height ), Y( :weight ) ),
    Elements( Points( X, Y, Legend( 3 ) ), Line Of Fit( X, Y, Legend( 6 ) ) ),
    Local Data Filter( Mode( Include( 0 ) ), Add Filter( columns( :sex ), Where( :sex == "F" ) ) )
);

Code Explanation:

1. Open data table;
2. Launch Graph Builder.
3. Set window size.
4. Hide control panel.
5. Assign X and Y variables.
6. Add points element.
7. Add line of fit element.
8. Enable local data filter.
9. Filter by sex column.
10. Apply filter condition for females.

Example 1527

Summary: Creates a variability chart with nested factors using Graph Builder, featuring points and line of fit elements, and applies local data filtering for sex.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 534, 502 ),
    Show Control Panel( 0 ),
    Variables( X( :height ), Y( :weight ) ),
    Elements( Points( X, Y, Legend( 3 ) ), Line Of Fit( X, Y, Legend( 6 ) ) ),
    Local Data Filter( Mode( Include( 0 ) ), Add Filter( columns( :sex ), Where( :sex == "F" ) ) )
);
Graph Builder(
    Size( 534, 502 ),
    Show Control Panel( 0 ),
    Variables( X( :height ), Y( :weight ) ),
    Elements( Points( X, Y, Legend( 3 ) ), Line Of Fit( X, Y, Legend( 6 ) ) ),
    Local Data Filter( Add Filter( columns( :sex ), Where( :sex == "F" ) ) )
);

Code Explanation:

1. Open data table;
2. Create Graph Builder window.
3. Set window size to 534x502.
4. Hide control panel.
5. Set X variable to height.
6. Set Y variable to weight.
7. Add points element with legend.
8. Add line of fit with legend.
9. Apply local data filter for sex.
10. Filter data where sex is female.

Example 1528

Summary: Creates a variability chart with nested factors using operator and part configurations, displaying standard deviation charts in Graph Builder.

Code:

Open("data_table.jmp") << Graph Builder(
    Variables( X( :x ), Y( :y ) ),
    Elements( Points( X, Y, Legend( 7 ) ), Line Of Fit( X, Y, Legend( 9 ) ) )
);

Code Explanation:

1. Open data file.
2. Launch Graph Builder.
3. Set X variable.
4. Set Y variable.
5. Add points element.
6. Add line of fit element.
7. Assign legend for points.
8. Assign legend for line.

Example 1529

Summary: Creates a variability chart with nested factors using Graph Builder, displaying standard deviation charts and configuring window size and control panel.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 495, 512 ),
    Show Control Panel( 0 ),
    Variables( X( :sex ), X( :age, Position( 1 ) ) ),
    Elements( Line Of Fit( X( 1 ), X( 2 ), Legend( 52 ) ) )
);

Code Explanation:

1. Open data table;
2. Launch Graph Builder.
3. Set window size.
4. Hide control panel.
5. Assign variables to X-axis.
6. Add second X variable.
7. Configure position for second X.
8. Add Line of Fit element.
9. Set X1 for fit.
10. Set X2 for fit.

Example 1530

Summary: Creates a graph builder with nested factors using Graph Builder, displaying a line of fit for sex and age variables.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 284, 328 ),
    Show Control Panel( 0 ),
    Variables( Y( :sex ), Y( :age, Position( 1 ) ) ),
    Elements( Line Of Fit( Y( 1 ), Y( 2 ), Legend( 4 ) ) )
);

Code Explanation:

1. Open data table.
2. Launch Graph Builder.
3. Set window size.
4. Hide control panel.
5. Assign variables to Y-axis.
6. Add first Y-variable (sex).
7. Add second Y-variable (age).
8. Position age on Y1.
9. Add Line of Fit element.
10. Specify Y1 and Y2 for fit.

Example 1531

Summary: Creates a scatter plot with a line of fit to visualize the relationship between Weight and Speed, using Graph Builder.

Code:

Open("data_table.jmp") << Graph Builder(
    Size( 415, 340 ),
    Show Control Panel( 0 ),
    Show Legend( 0 ),
    Include Missing Categories( 1 ),
    Variables( X( :Weight ), Y( :Speed ) ),
    Elements(
        Points( X, Y, Legend( 3 ) ),
        Line Of Fit( X, Y, Legend( 7 ), Confidence of Prediction( 1 ), Root Mean Square Error( 1 ), R²( 1 ), Equation( 1 ), F Test( 1 ) )
    ),
    SendToReport(
        Dispatch( {}, "Weight", ScaleBox,
            {Scale( "Log" ), Format( "Best", 6 ), Min( 153.026620752195 ), Max( 305.737653814908 ), Inc( 1 ), Minor Ticks( 1 )}
        ),
        Dispatch( {}, "Speed", ScaleBox,
            {Scale( "Log" ), Format( "Best", 6 ), Min( 50 ), Max( 71.4361255407525 ), Inc( 1 ), Minor Ticks( 1 )}
        )
    )
);

Code Explanation:

1. Open data table;
2. Create Graph Builder window.
3. Set graph size to 415x340.
4. Hide control panel.
5. Hide legend.
6. Include missing categories.
7. Set X variable to Weight.
8. Set Y variable to Speed.
9. Add points element.
10. Add line of fit element with various statistics.

Example 1532

Summary: Creates a Line Of Fit graph with nested factors using Graph Builder, displaying age as a function of height and weight.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 348, 335 ),
    Show Control Panel( 0 ),
    Variables( X( :height ), X( :weight, Position( 1 ) ), Y( :age ) ),
    Elements( Line Of Fit( X( 1 ), X( 2 ), Y, Legend( 4 ) ) ),
    SendToReport( Dispatch( {}, "400", LegendBox, {Set Title( "" )} ) )
);

Code Explanation:

1. Open data table;
2. Launch Graph Builder.
3. Set window size.
4. Hide control panel.
5. Define X variables: height, weight.
6. Define Y variable: age.
7. Add Line Of Fit element.
8. Configure X axis for Line Of Fit.
9. Configure second X axis for Line Of Fit.
10. Configure Y axis for Line Of Fit.
11. Remove legend title.

Example 1533

Summary: Creates a graph builder with points and line of fit elements to visualize height and weight data, utilizing Graph Builder.

Code:

Open("data_table.jmp");
Graph Builder(
    Show Control Panel( 0 ),
    Variables( X( :height ), Y( :weight ) ),
    Elements( Points( X, Y, Legend( 7 ) ), Line Of Fit( X, Y, Legend( 9 ) ) )
);

Code Explanation:

1. Open data table;
2. Launch Graph Builder.
3. Hide control panel.
4. Set X variable to height.
5. Set Y variable to weight.
6. Add points element.
7. Add line of fit element.
8. Assign legend for points.
9. Assign legend for line of fit.
10. Display graph.

Example 1534

Summary: Creates a scatter plot with a line of fit to visualize the relationship between height and weight, utilizing Graph Builder.

Code:

Open("data_table.jmp");
Graph Builder(
    Show Control Panel( 0 ),
    Variables( X( :height ), Y( :weight ) ),
    Elements( Points( X, Y, Legend( 2 ) ), Line Of Fit( X, Y, Legend( 4 ), Confidence of Prediction( 1 ) ) )
);

Code Explanation:

1. Open data table.
2. Launch Graph Builder.
3. Hide control panel.
4. Set X variable to height.
5. Set Y variable to weight.
6. Add points element.
7. Add line of fit element.
8. Set legend for points.
9. Set legend for line of fit.
10. Enable confidence interval.

Example 1535

Summary: Creates a scatter plot with a line of fit to visualize the relationship between height and weight, utilizing Graph Builder.

Code:

Open("data_table.jmp");
Graph Builder(
    Show Control Panel( 0 ),
    Variables( X( :height ), Y( :weight ) ),
    Elements( Points( X, Y, Legend( 2 ) ), Line Of Fit( X, Y, Legend( 4 ), Root Mean Square Error( 1 ), R²( 1 ), Equation( 1 ) ) )
);

Code Explanation:

1. Open data table;
2. Launch Graph Builder.
3. Hide control panel.
4. Set X variable to height.
5. Set Y variable to weight.
6. Add points element.
7. Add line of fit element.
8. Display root mean square error.
9. Display R-squared value.
10. Display equation.

Example 1536

Summary: Creates a scatter plot with a quadratic line of fit to visualize the relationship between height and weight, utilizing Graph Builder.

Code:

Open("data_table.jmp");
Graph Builder(
    Show Control Panel( 0 ),
    Variables( X( :height ), Y( :weight ) ),
    Elements(
        Points( X, Y, Legend( 2 ) ),
        Line Of Fit( X, Y, Legend( 4 ), Degree( "Quadratic" ), Root Mean Square Error( 1 ), R²( 1 ), Equation( 1 ) )
    )
);

Code Explanation:

1. Open data table;
2. Launch Graph Builder.
3. Hide control panel.
4. Set X variable: height.
5. Set Y variable: weight.
6. Add points element.
7. Add line of fit element.
8. Set fit degree to quadratic.
9. Display root mean square error.
10. Display R² value.

Example 1537

Summary: Creates a graph builder object to visualize the relationship between height and weight, including a line of fit with cubic degree and root mean square error.

Code:

Open("data_table.jmp");
Graph Builder(
    Show Control Panel( 0 ),
    Variables( X( :height ), Y( :weight ) ),
    Elements(
        Points( X, Y, Legend( 2 ) ),
        Line Of Fit( X, Y, Legend( 4 ), Degree( "Cubic" ), Root Mean Square Error( 1 ), R²( 1 ), Equation( 1 ) )
    )
);

Code Explanation:

1. Open data table;
2. Create graph builder object.
3. Hide control panel.
4. Set X variable to height.
5. Set Y variable to weight.
6. Add points element.
7. Add line of fit element.
8. Set line degree to cubic.
9. Display root mean square error.
10. Display R² value.

Example 1538

Summary: Creates a graph builder with a line of fit element to visualize the relationship between age and height.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 432, 189 ),
    Show Control Panel( 0 ),
    Variables( X( :age ), Y( :height ) ),
    Elements( Line Of Fit( X, Y, Legend( 5 ) ) )
);

Code Explanation:

1. Open data table.
2. Launch Graph Builder.
3. Set window size.
4. Hide control panel.
5. Assign X variable.
6. Assign Y variable.
7. Add Line Of Fit element.
8. Configure legend position.

Example 1539

Summary: Creates a graph with nested factors using Graph Builder, displaying points and line of fit elements.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 534, 454 ),
    Show Control Panel( 0 ),
    Variables( X( :height ), Y( :weight ), Overlay( :sex ) ),
    Elements( Points( X, Y, Legend( 3 ) ), Line Of Fit( X, Y, Legend( 5 ) ) )
);

Code Explanation:

1. Open data table;
2. Launch Graph Builder.
3. Set window size.
4. Hide control panel.
5. Define X variable.
6. Define Y variable.
7. Define overlay variable.
8. Add points element.
9. Add line of fit element.
10. Display graph.

Example 1540

Summary: Creates a variability chart with nested factors using operator and part configurations, displaying standard deviation charts in Graph Builder.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 600, 600 ),
    Show Control Panel( 0 ),
    Variables(
        X( :Weight, Size( 23 ) ),
        Y( :Oxy, Size( 35 ) ),
        Group X( :Age ),
        Group Y( :RstPulse ),
        Overlay( :RunPulse ),
        Color( :Runtime ),
        Size( :MaxPulse )
    ),
    Elements(
        Points( X, Y, Color, Legend( 1 ) ),
        Line Of Fit(
            X,
            Y,
            Color,
            Legend( 4 ),
            Confidence of Fit( 1 ),
            Confidence of Prediction( 0 ),
            Degree( "Linear" ),
            Root Mean Square Error( 0 )
        )
    )
);

Code Explanation:

1. Open data table;
2. Create Graph Builder window.
3. Set size to 600x600.
4. Hide control panel.
5. Define X variable: Weight.
6. Define Y variable: Oxy.
7. Group X by Age.
8. Group Y by RstPulse.
9. Overlay by RunPulse.
10. Color by Runtime.
11. Size by MaxPulse.
12. Add points element.
13. Add linear fit line.

Example 1541

Summary: Creates a Graph Builder window with nested factors, displaying standard deviation charts for RunPulse and RstPulse variables.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 534, 454 ),
    Show Control Panel( 0 ),
    Variables( X( :Oxy ), Y( :RunPulse ), Y( :RstPulse ) ),
    Elements( Position( 1, 1 ), Points( X, Y, Legend( 5 ) ), Line Of Fit( X, Y, Legend( 9 ), Confidence of Prediction( 1 ) ) ),
    Elements( Position( 1, 2 ), Points( X, Y, Legend( 7 ) ), Line Of Fit( X, Y, Legend( 10 ) ) )
);

Code Explanation:

1. Open data_table data
2. Create Graph Builder window.
3. Set window size to 534x454.
4. Hide control panel.
5. Assign Oxy to X-axis.
6. Assign RunPulse to first Y-axis.
7. Assign RstPulse to second Y-axis.
8. Add points for RunPulse.
9. Add line of fit for RunPulse.
10. Add points for RstPulse.

Example 1542

Summary: Creates a graph builder with nested factors using Graph Builder, displaying points and line of fit elements.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 523, 449 ),
    Show Control Panel( 0 ),
    Variables( X( :Weight ), Y( :Turning Circle ) ),
    Elements( Points( X, Y, Legend( 3 ) ), Line Of Fit( X, Y, Legend( 5 ) ) )
);

Code Explanation:

1. Open data table.
2. Launch Graph Builder.
3. Set window size.
4. Hide control panel.
5. Assign X variable.
6. Assign Y variable.
7. Add points element.
8. Add line of fit element.
9. Configure legend for points.
10. Configure legend for line of fit.

Example 1543

Summary: Creates a variability chart with nested factors using Graph Builder, displaying points and line of fit elements.

Code:

Open("data_table.jmp");
Graph Builder(
    show control panel( 0 ),
    Include Missing Categories( 1 ),
    Variables( X( :sex ), Y( :age ) ),
    Elements( Points( X, Y, Legend( 7 ) ), Line Of Fit( X, Y, Legend( 9 ) ) )
);

Code Explanation:

1. Open data table;
2. Launch Graph Builder.
3. Hide control panel.
4. Include missing categories.
5. Set X variable to sex.
6. Set Y variable to age.
7. Add points element.
8. Add line of fit element.
9. Assign legend for points.
10. Assign legend for line of fit.

Example 1544

Summary: Creates a variability chart with nested factors using Graph Builder, featuring a Line of Fit and Points element with jitter, and displays standard deviation charts.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 448, 471 ),
    Show Control Panel( 0 ),
    Variables( X( :Weeks ), Y( :Strength ), Overlay( :Degrees ) ),
    Elements( Line Of Fit( X, Y, Legend( 17 ) ), Points( X, Y, Legend( 16 ), Jitter Limit( 1.3578 ) ) ),
    SendToReport(
        Dispatch( {}, "Weeks", ScaleBox,
            {Scale( "Power", {Power( 0.5 )} ), Format( "Best", 10 ), Min( -0.0131375367019967 ), Max( 17.9278214031433 ), Inc( 5 ),
            Minor Ticks( 1 )}
        ),
        Dispatch( {}, "Strength", ScaleBox,
            {Scale( "Log" ), Format( "Best", 12 ), Min( 16.050517241584 ), Max( 100.64732429125 ), Inc( 1 ), Minor Ticks( 1 )}
        )
    )
);

Code Explanation:

1. Open data table;
2. Launch Graph Builder.
3. Set window size.
4. Hide control panel.
5. Assign variables X, Y, and Overlay.
6. Add Line of Fit element.
7. Add Points element with jitter.
8. Adjust X-axis scale properties.
9. Set X-axis to Power scale.
10. Adjust Y-axis to Log scale.

Example 1545

Summary: Creates a variability chart with nested factors using Graph Builder, displaying standard deviation charts for three different configurations.

Code:

dt = Open("data_table.jmp");
gb = dt << Graph Builder(
    Size( 534, 1956 ),
    Show Control Panel( 0 ),
    Replicate Linked Page Axes( 0 ),
    Variables( X( :Silica ), X( :Silane ), X( :Sulfur ), Y( :Y ), Page( :Characteristic ) ),
    Elements( Position( 1, 1 ), Points( X, Y, Legend( 101 ) ), Smoother( X, Y, Legend( 102 ) ) ),
    Elements( Position( 2, 1 ), Points( X, Y, Legend( 103 ) ), Smoother( X, Y, Legend( 104 ) ) ),
    Elements( Position( 3, 1 ), Points( X, Y, Legend( 105 ) ), Smoother( X, Y, Legend( 106 ) ) )
);

Code Explanation:

1. Open data table.
2. Create Graph Builder object.
3. Set graph size.
4. Hide control panel.
5. Disable linked page axes.
6. Define variables for axes.
7. Add points and smoother elements.
8. Add points and smoother elements.
9. Add points and smoother elements.
10. Display graph.

Example 1546

Summary: Creates two Graph Builder instances to visualize relationships between Silica, Silane, Sulfur, and Y, as well as Horsepower, Displacement, and Type, with customization options for legend properties and contour elements.

Code:

dt = Open("data_table.jmp");
gb = dt << Graph Builder(
    Size( 534, 1956 ),
    Show Control Panel( 0 ),
    Replicate Linked Page Axes( 0 ),
    Variables( X( :Silica ), X( :Silane ), X( :Sulfur ), Y( :Y ), Page( :Characteristic ) ),
    Elements( Position( 1, 1 ), Points( X, Y, Legend( 101 ) ), Smoother( X, Y, Legend( 102 ) ) ),
    Elements( Position( 2, 1 ), Points( X, Y, Legend( 103 ) ), Smoother( X, Y, Legend( 104 ) ) ),
    Elements( Position( 3, 1 ), Points( X, Y, Legend( 105 ) ), Smoother( X, Y, Legend( 106 ) ) )
);
dt2 = Open("data_table.jmp");
gb2 = dt2 << Graph Builder(
    Size( 1503, 1060 ),
    Show Control Panel( 0 ),
    Link Page Axes( "X Only" ),
    Replicate Linked Page Axes( 0 ),
    Variables( X( :Horsepower ), Y( :Displacement ), Page( :Type, Levels per Row( 3 ) ) ),
    Elements( Contour( X, Y, Legend( 20 ), Line( 1 ), Number of Levels( 7 ), Smoothness( 0.0536 ) ) ),
    SendToReport(
        Dispatch( {}, "400", ScaleBox,
            {Legend Model(
                20,
                Properties(
                    0,
                    {gradient( {Color Theme( "Black Body"(1) ), Density Gradient( "Full Color" ), Width( 9 )} )},
                    Item ID( "Density", 1 )
                )
            )}
        )
    )
);

Code Explanation:

1. Open data_table data
2. Create Graph Builder instance.
3. Set graph size.
4. Hide control panel.
5. Disable linked page axes replication.
6. Define variables: Silica, Silane, Sulfur, Y, Characteristic.
7. Add points and smoother elements for Silica.
8. Add points and smoother elements for Silane.
9. Add points and smoother elements for Sulfur.
10. Open data_table data
11. Create second Graph Builder instance.
12. Set second graph size.
13. Hide second control panel.
14. Link page axes for X only.
15. Disable second linked page axes replication.
16. Define variables: Horsepower, Displacement, Type.
17. Add contour element.
18. Customize legend properties.

Example 1547

Summary: Creates a geographic map with nested factors using Graph Builder, configuring X-axis and Y-axis scales, and applying fill patterns.

Code:

Open("data_table.jmp");
Graph Builder(
    Show Control Panel( 0 ),
    Variables( Color( :Change in Population ), Shape( :Metropolitan Statistical Area ) ),
    Elements( Map Shapes( Legend( 2 ) ) ),
    SendToReport(
        Dispatch( {}, "", ScaleBox, {Min( -124.961949335295 ), Max( -67.1304065026599 ), Inc( 10 ), Minor Ticks( 0 )} ),
        Dispatch( {}, "", ScaleBox( 2 ), {Min( 14.572885454726 ), Max( 62.7291891822812 ), Inc( 10 ), Minor Ticks( 0 )} ),
        Dispatch( {}, "400", ScaleBox, {Legend Model( 2, Properties( 0, {Fill Pattern( "left slant light" )} ) )} )
    )
);

Code Explanation:

1. Open data table.
2. Create Graph Builder.
3. Hide control panel.
4. Set color variable.
5. Set shape variable.
6. Add map shapes element.
7. Configure X-axis scale.
8. Configure Y-axis scale.
9. Set legend properties.
10. Apply fill pattern.

Example 1548

Summary: Creates a geographic map to visualize crude birth rate data across territories, utilizing Graph Builder and specifying color and shape variables.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 893, 507 ),
    Show Control Panel( 0 ),
    Variables( Color( :Name( "Crude Birth Rate (1000)" ) ), Shape( :Territory ) ),
    Elements( Map Shapes( Legend( 3 ) ) )
);

Code Explanation:

1. Open data table;
2. Launch Graph Builder.
3. Set window size.
4. Hide control panel.
5. Define color variable.
6. Define shape variable.
7. Add map shapes element.
8. Enable legend for shapes.

Example 1549

Summary: Creates a geographic map to visualize crude birth rates across territories, utilizing Graph Builder and customizing legend and grid lines.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 893, 507 ),
    Show Control Panel( 0 ),
    Variables( Color( :Name( "Crude Birth Rate (1000)" ) ), Shape( :Territory ) ),
    Elements( Map Shapes( Legend( 3 ) ) ),
    SendToReport(
        Dispatch( {}, "", ScaleBox, {Label Row( {Show Major Grid( 1 ), Show Minor Grid( 1 )} )} ),
        Dispatch( {}, "", ScaleBox( 2 ), {Label Row( {Show Major Grid( 1 ), Show Minor Grid( 1 )} )} )
    )
);

Code Explanation:

1. Open data table;
2. Create Graph Builder window.
3. Set window size.
4. Hide control panel.
5. Define color variable.
6. Define shape variable.
7. Add map shapes element.
8. Customize legend.
9. Enable major grid lines.
10. Enable minor grid lines.

Example 1550

Summary: Creates a nested factors variability chart using Graph Builder, with interactive features for color and shape assignment.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 893, 507 ),
    Show Control Panel( 0 ),
    Variables( Color( :Development Level ), Shape( :Territory ) ),
    Elements( Map Shapes( Legend( 4 ) ) ),
    SendToReport(
        Dispatch( {}, "", ScaleBox, {Label Row( {Show Major Grid( 1 ), Show Minor Grid( 1 )} )} ),
        Dispatch( {}, "", ScaleBox( 2 ), {Label Row( {Show Major Grid( 1 ), Show Minor Grid( 1 )} )} )
    )
);

Code Explanation:

1. Open data table;
2. Launch Graph Builder.
3. Set window size.
4. Hide control panel.
5. Assign color variable.
6. Assign shape variable.
7. Add map shapes element.
8. Enable legend for map shapes.
9. Show major grid on first scale.
10. Show minor grid on first scale.
11. Show major grid on second scale.
12. Show minor grid on second scale.

Example 1551

Summary: Creates a geographic map to visualize crude birth rate data across territories, utilizing Graph Builder and custom scale configurations.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 893, 507 ),
    Show Control Panel( 0 ),
    Variables( Color( :Name( "Crude Birth Rate (1000)" ) ), Shape( :Territory ) ),
    Elements( Map Shapes( Legend( 5 ) ) ),
    SendToReport(
        Dispatch( {}, "", ScaleBox,
            {Min( -14.8705096073517 ), Max( 52.8933232955646 ), Inc( 10 ), Minor Ticks( 0 ), Label Row(
                {Show Major Grid( 1 ), Show Minor Grid( 1 )}
            )}
        ),
        Dispatch( {}, "", ScaleBox( 2 ),
            {Min( 21.774969743751 ), Max( 55.7420166385546 ), Inc( 5 ), Minor Ticks( 0 ), Label Row(
                {Show Major Grid( 1 ), Show Minor Grid( 1 )}
            )}
        )
    )
);

Code Explanation:

1. Open data table.
2. Launch Graph Builder.
3. Set window size.
4. Hide control panel.
5. Assign color variable.
6. Assign shape variable.
7. Add map shapes element.
8. Configure X-axis scale.
9. Configure Y-axis scale.
10. Display report.

Example 1552

Summary: Creates a geographic map to visualize years of compulsory education across territories, utilizing Graph Builder and customizing scale boxes, legend appearance, and graph title.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 748, 535 ),
    Show Control Panel( 0 ),
    Variables( Color( :Years of Compulsory Education ), Shape( :Territory ) ),
    Elements( Map Shapes( Legend( 2 ) ) ),
    SendToReport(
        Dispatch( {}, "", ScaleBox,
            {Min( 65.9427296287484 ), Max( 209.296045818952 ), Inc( 25 ), Minor Ticks( 0 ), Label Row( Show Major Grid( 1 ) )}
        ),
        Dispatch( {}, "", ScaleBox( 2 ),
            {Min( -17.4433458130262 ), Max( 82.0093176687113 ), Inc( 25 ), Minor Ticks( 0 ), Label Row( Show Major Grid( 1 ) )}
        ),
        Dispatch( {}, "400", ScaleBox,
            {Legend Model( 2, Properties( 0, {gradient( {Color Theme( "White to Green" ), Label Format( "Fixed Dec", 15, 0 )} )} ) )}
        ),
        Dispatch( {}, "graph title", TextEditBox, {Set Text( "Years of Compulsory Education" )} ),
        Dispatch( {}, "400", LegendBox, {Set Title( "Years" )} )
    )
);

Code Explanation:

1. Open data table;
2. Launch Graph Builder.
3. Set window size.
4. Hide control panel.
5. Define color and shape variables.
6. Add map shapes element.
7. Configure first scale box.
8. Configure second scale box.
9. Customize legend appearance.
10. Set graph title.

Example 1553

Summary: Creates a geographic map to visualize US cities colored by maximum temperature in January, sized by lead levels, using Graph Builder.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 784, 466 ),
    Show Control Panel( 0 ),
    Variables( X( :Longitude ), Y( :Latitude ), Y( :CO, Position( 1 ) ), Color( :Max deg. F Jan ), Size( :Lead ) ),
    Elements( Points( X, Y( 1 ), Y( 2 ), Legend( 1 ) ) ),
    SendToReport(
        Dispatch( {}, "graph title", TextEditBox, {Set Text( "US Cities Colored by Max deg. F Jan, Sized by Lead Levels" )} ),
        Dispatch( {}, "Graph Builder", FrameBox,
            {Background Map( Boundaries( "US States" ) ), Grid Line Order( 2 ), Reference Line Order( 3 )}
        )
    )
);

Code Explanation:

1. Open data table.
2. Launch Graph Builder.
3. Set window size.
4. Hide control panel.
5. Define X, Y, and additional variables.
6. Add points element.
7. Set graph title.
8. Enable background map.
9. Adjust grid line order.
10. Adjust reference line order.

Example 1554

Summary: Creates a graph builder with nested factors using operator and part configurations, displaying standard deviation charts.

Code:

Open("data_table.jmp");
Graph Builder(
    Show Control Panel( 0 ),
    Size( 570, 2500 ),
    Variables( Page( :Year ), Color( :Name( "Portion60+" ) ), Shape( :Country ) ),
    Elements( Map Shapes( Legend( 9 ), Show Missing Shapes( 1 ) ) )
);

Code Explanation:

1. Open data table.
2. Create Graph Builder.
3. Hide control panel.
4. Set window size.
5. Define page variable.
6. Define color variable.
7. Define shape variable.
8. Add map shapes element.
9. Enable legend for map.
10. Display missing shapes.

Example 1555

Summary: Creates a graph builder with nested factors using operator and part configurations, displaying standard deviation charts.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 534, 454 ),
    Show Control Panel( 0 ),
    Variables( Shape( :State ) ),
    Elements( Map Shapes( Legend( 2 ) ) ),
    SendToReport(
        Dispatch( {}, "Graph Builder", FrameBox,
            {DispatchSeg( Shape Seg( 1 ), {Clip Shape( Boundaries( "US States", ID( "north carolina" ) ) )} )}
        )
    )
);

Code Explanation:

1. Open data table.
2. Create Graph Builder object.
3. Set graph size.
4. Hide control panel.
5. Assign shape variable.
6. Add map shapes element.
7. Send report to Graph Builder.
8. Dispatch to frame box.
9. Dispatch segment shape.
10. Clip shape by US states.

Example 1556

Summary: Creates a graph builder window with nested factors, utilizing Graph Builder to display a map shapes element with color and shape variables.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 696, 444 ),
    Show Control Panel( 0 ),
    Legend Position( "Bottom" ),
    Variables( Color( :Territory ), Shape( :Territory ) ),
    Elements( Map Shapes( Legend( 12 ) ) )
);

Code Explanation:

1. Open data table.
2. Create Graph Builder window.
3. Set window size.
4. Hide control panel.
5. Place legend at bottom.
6. Assign color variable.
7. Assign shape variable.
8. Add map shapes element.
9. Set legend properties.
10. Display graph.

Example 1557

Summary: Creates a variability chart with nested factors using operator and part configurations, displaying standard deviation charts in Graph Builder.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 659, 320 ),
    Show Control Panel( 0 ),
    Variables( Color( :Total Median Age ), Shape( :Territory ) ),
    Elements( Points( Legend( 3 ) ) ),
    SendToReport(
        Dispatch( {}, "", ScaleBox, {Min( -192.026055427126 ), Max( 195.059270040352 ), Inc( 50 ), Minor Ticks( 0 )} ),
        Dispatch( {}, "", ScaleBox( 2 ), {Min( -85.4911700473894 ), Max( 80.2175980457113 ), Inc( 25 ), Minor Ticks( 0 )} )
    )
);

Code Explanation:

1. Open data table;
2. Create Graph Builder window.
3. Set window size to 659x320.
4. Hide control panel.
5. Assign color by Total Median Age.
6. Assign shape by Territory.
7. Add points element with legend.
8. Set X-axis minimum to -192.026.
9. Set X-axis maximum to 195.059.
10. Set Y-axis minimum to -85.491.

Example 1558

Summary: Creates a geographic map to display physical activity levels across US states, utilizing Graph Builder's color and shape variables.

Code:

dt = Open("data_table.jmp");
dt << Select All Rows;
dt << Hide;
gb = Graph Builder(
    Size( 337, 293 ),
    Show Control Panel( 0 ),
    Show Legend( 0 ),
    Variables( Color( :Physical Activity ), Shape( :State ) ),
    Elements( Map Shapes( Legend( 2 ) ) ),
    SendToReport(
        Dispatch( {}, "Graph Builder", FrameBox,
            {Background Map( Boundaries( "US States" ) ), Grid Line Order( 2 ), Reference Line Order( 3 )}
        )
    )
);

Code Explanation:

1. Open data table;
2. Select all rows.
3. Hide the table.
4. Create Graph Builder object.
5. Set size to 337x293.
6. Hide control panel.
7. Hide legend.
8. Set color by Physical Activity.
9. Set shape by State.
10. Add map shapes element.

Example 1559

Summary: Creates a geographic map to visualize data across territories, utilizing Graph Builder and custom scale configurations.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 531, 448 ),
    Show Control Panel( 0 ),
    Show Legend( 0 ),
    Show Footer( 0 ),
    Variables( Shape( :Territory ) ),
    Elements( Map Shapes( Legend( 2 ) ) ),
    SendToReport(
        Dispatch( {}, "", ScaleBox, {Min( 17.9281237585483 ), Max( 134.204094590011 ), Inc( 25 ), Minor Ticks( 0 )} ),
        Dispatch( {}, "", ScaleBox( 2 ), {Min( 41.2640891729211 ), Max( 141.261424087979 ), Inc( 25 ), Minor Ticks( 0 )} )
    )
);

Code Explanation:

1. Open data table;
2. Launch Graph Builder.
3. Set window size 531x448.
4. Hide control panel.
5. Hide legend.
6. Hide footer.
7. Set shape variable.
8. Add map shapes element.
9. Configure X-axis scale.
10. Configure Y-axis scale.

Example 1560

Summary: Creates a graph with nested factors using Graph Builder, specifying color, size, and shape variables, and displaying a standard deviation chart.

Code:

Open("data_table.jmp");
obj = Graph Builder(
    Size( 486, 419 ),
    Show Control Panel( 0 ),
    Variables( Color( :Electors ), Size( :Electors ), Shape( :State ) ),
    Elements( Points( Legend( 3 ) ) ),
    SendToReport(
        Dispatch( {}, "400", ScaleBox, {Legend Model( 3, Properties( 0, {Line Color( 1 )} ) )} ),
        Dispatch( {}, "graph title", TextEditBox, {Set Text( "2008 Election State Winners sized by Number of Electors" )} )
    )
);
obj << save journal( "$temp\S1581040.jrn" );
obj << close window;

Code Explanation:

1. Open data_table data
2. Create Graph Builder object.
3. Set graph size.
4. Hide control panel.
5. Define variables for color, size, shape.
6. Add points element with legend.
7. Customize legend properties.
8. Set graph title.
9. Save journal to temp directory.
10. Close graph window.

Example 1561

Summary: Creates a graph builder object to visualize data from a nested factors dataset, with customizable color, size, and shape variables.

Code:

Open("data_table.jmp");
obj = Graph Builder(
    Size( 486, 419 ),
    Show Control Panel( 0 ),
    Variables( Color( :Electors ), Size( :Electors ), Shape( :State ) ),
    Elements( Points( Legend( 3 ) ) ),
    SendToReport(
        Dispatch( {}, "400", ScaleBox, {Legend Model( 3, Properties( 0, {Line Color( 1 )} ) )} ),
        Dispatch( {}, "graph title", TextEditBox, {Set Text( "2008 Election State Winners sized by Number of Electors" )} )
    )
);
obj << save journal( "$temp\S1581040.jrn" );
obj << close window;
Open( "$temp\S1581040.jrn" );

Code Explanation:

1. Open data_table data
2. Create Graph Builder object.
3. Set graph size.
4. Hide control panel.
5. Define color, size, and shape variables.
6. Add points element.
7. Customize legend properties.
8. Set graph title.
9. Save graph as journal.
10. Close original graph window.
11. Open saved journal file.

Example 1562

Summary: Creates a variability chart with nested factors using operator and part configurations, displaying standard deviation charts in Graph Builder.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 534, 461 ),
    Show Control Panel( 0 ),
    Variables( Size( :Gross State Product, Summary Statistic( "% of Total" ) ), Shape( :State ) ),
    Elements( Map Shapes( Legend( 11 ) ) ),
    SendToReport(
        Dispatch( {}, "", ScaleBox, {Min( -78.7899609192314 ), Max( -70.3093073919842 ), Inc( 2 ), Minor Ticks( 0 )} ),
        Dispatch( {}, "", ScaleBox( 2 ), {Min( 36.7307879175252 ), Max( 43.8487994403944 ), Inc( 2 ), Minor Ticks( 1 )} ),
        Dispatch( {}, "400", ScaleBox, {Legend Model( 11, Properties( 0, {Line Color( 8 )}, Item ID( "Gross State Product", 1 ) ) )} ),
        Dispatch( {}, "Graph Builder", FrameBox,
            {DispatchSeg(
                Shape Seg( 1 ),
                {Label Position( 6, -72.1489605451882, 39.2204204069783 ), Label Position( 7, -74.2246594632342, 37.3971661910754 ),
                Label Position( 20, -75.642039232941, 36.9972683758876 ), Label Position( 21, -68.3490506719053, 42.7750562023208 ),
                Label Position( 30, -72.9344667148594, 38.2981707244423 ), Label Position( 32, -78.6149379845478, 44.6184718696499 ),
                Label Position( 38, -80.3353563262466, 43.758441529048 ), Label Position( 39, -69.1046110790501, 38.6934658487624 ),
                Label Position( 45, -74.0716741641175, 46.0421686790949 ), Label Position( 48, -81.2266982298494, 42.8230153639912 )}
            )}
        )
    )
);

Code Explanation:

1. Open data table;
2. Launch Graph Builder.
3. Set window size.
4. Hide control panel.
5. Define variables: Gross State Product, State.
6. Add map shape element.
7. Set X-axis scale properties.
8. Set Y-axis scale properties.
9. Customize legend line color.
10. Add state labels to map.

Example 1563

Summary: Creates a variability chart with nested factors using operator and part configurations, displaying standard deviation charts.

Code:

dt = Open("data_table.jmp");
gb = Graph Builder(
    show control panel( 0 ),
    Variables( Color( :birth ), Shape( :country ) ),
    Elements( Map Shapes( Legend( 1 ), Summary Statistic( "Mean" ), Show Missing Shapes( 1 ) ) ),
    SendToReport(
        Dispatch( {}, "", ScaleBox, {Show Major Grid( 1 ), Show Minor Grid( 1 )} ),
        Dispatch( {}, "", ScaleBox( 2 ), {Show Major Grid( 1 ), Show Minor Grid( 1 )} )
    )
);

Code Explanation:

1. Open table.
2. Create Graph Builder.
3. Hide control panel.
4. Set color variable.
5. Set shape variable.
6. Add map shapes element.
7. Use mean summary statistic.
8. Show missing shapes.
9. Display major grid.
10. Display minor grid.

Example 1564

Summary: Creates a geographic map to visualize changes in population across metropolitan statistical areas, utilizing Graph Builder and its various configuration options.

Code:

Open("data_table.jmp");
obj = Graph Builder(
    Size( 587, 487 ),
    Show Control Panel( 0 ),
    Variables( Color( :Change in Population ), Shape( :Metropolitan Statistical Area ) ),
    Elements( Map Shapes( Legend( 2 ) ) ),
    SendToReport(
        Dispatch( {}, "", ScaleBox, {Min( -127.528507232391 ), Max( -64.5638486055635 ), Inc( 10 ), Minor Ticks( 0 )} ),
        Dispatch( {}, "", ScaleBox( 2 ), {Min( 14.572885454726 ), Max( 62.7291891822812 ), Inc( 10 ), Minor Ticks( 0 )} ),
        Dispatch( {}, "Graph Builder", FrameBox, {Background Map( Images( "Detailed Earth" ) )} )
    )
);

Code Explanation:

1. Open data table;
2. Create Graph Builder object.
3. Set graph size.
4. Hide control panel.
5. Define color and shape variables.
6. Add map shapes element.
7. Set x-axis scale properties.
8. Set y-axis scale properties.
9. Add background map image.
10. Display graph.

Example 1565

Summary: Creates a geographic map to visualize changes in population across metropolitan statistical areas, utilizing Graph Builder and its elements.

Code:

Open("data_table.jmp");
obj = Graph Builder(
    Size( 587, 487 ),
    Show Control Panel( 0 ),
    Variables( Color( :Change in Population ), Shape( :Metropolitan Statistical Area ) ),
    Elements( Map Shapes( Legend( 2 ) ) ),
    SendToReport(
        Dispatch( {}, "", ScaleBox, {Min( -127.528507232391 ), Max( -64.5638486055635 ), Inc( 10 ), Minor Ticks( 0 )} ),
        Dispatch( {}, "", ScaleBox( 2 ), {Min( 14.572885454726 ), Max( 62.7291891822812 ), Inc( 10 ), Minor Ticks( 0 )} ),
        Dispatch( {}, "Graph Builder", FrameBox, {Background Map( Images( "Detailed Earth" ) )} )
    )
);
obj << Redo Analysis;

Code Explanation:

1. Open data table;
2. Create Graph Builder object.
3. Set window size.
4. Hide control panel.
5. Define color and shape variables.
6. Add map shapes element.
7. Configure x-axis scale.
8. Configure y-axis scale.
9. Set background map image.
10. Redo analysis.

Example 1566

Summary: Creates a geographic map to visualize gross state product and population data, with customizable color, size, and shape variables.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 534, 385 ),
    Show Control Panel( 0 ),
    Variables( Color( :Gross State Product ), Size( :Population ), Shape( :State ) ),
    Elements( Map Shapes( Legend( 12 ) ) ),
    SendToReport(
        Dispatch( {}, "Graph Builder", FrameBox,
            {Background Map( Boundaries( "US States" ) ), DispatchSeg( Shape Seg( 1 ), {Fill Color( "YellowGreen" )} )}
        )
    )
);

Code Explanation:

1. Open data table.
2. Create Graph Builder window.
3. Set window size.
4. Hide control panel.
5. Assign color, size, and shape variables.
6. Add map shapes element.
7. Configure legend for shapes.
8. Set background map to US states.
9. Change fill color of shapes to yellowgreen.
10. Display report.

Example 1567

Summary: Creates a variability chart with nested factors using operator and part configurations, displaying standard deviation charts.

Code:

dt = Open("data_table.jmp");
Graph Builder(
    Size( 505, 472 ),
    Show Control Panel( 0 ),
    Variables( Color( :Name( "Expenditure (1997)" ) ), Shape( :State ) ),
    Elements( Map Shapes( Legend( 2 ) ) ),
    Local Data Filter(
        Mode( Include( 0 ) ),
        Add Filter(
            columns( :State ),
            Where(
                :State == {"Alabama", "Alaska", "Arizona", "Arkansas", "California", "Colorado", "Connecticut", "Delaware",
                "District of Columbia", "Florida", "Georgia", "Hawaii", "Idaho"}
            ),
            Display( :State, Size( 160, 225 ), List Display )
        )
    ),
    SendToReport(
        Dispatch( {}, "", ScaleBox, {Min( -109.15 ), Max( -64.35 ), Inc( 0.5 ), Minor
Ticks( 0 )} ),
        Dispatch( {}, "", ScaleBox( 2 ), {Min( 16.8153153153153 ), Max( 58.1846846846847 ), Inc( 10 ), Minor Ticks( 1 )} ),
        Dispatch( {}, "400", ScaleBox,
            {Legend Model(
                2,
                Properties(
                    0,
                    {gradient(
                        {Color Theme( "White to Green" ), Scale Values( [3.5 4.8 6.1 7.4 8.7 10] ), Label Format( "Fixed Dec", 15, 0 )}
                    )}
                )
            )}
        )
    )
);

Code Explanation:

1. Open table.
2. Set Graph Builder size.
3. Hide control panel.
4. Set color variable.
5. Set shape variable.
6. Add map shapes element.
7. Enable local data filter.
8. Add state filter.
9. Set filter criteria.
10. Configure report scales and legend.

Example 1568

Summary: Creates a variability chart with nested factors using operator and part configurations, displaying standard deviation charts.

Code:

Open("data_table.jmp");
obj = Graph Builder(
    Size( 534, 456 ),
    Show Control Panel( 0 ),
    Variables( Color( :Region ), Shape( :State ) ),
    Elements( Map Shapes( Legend( 13 ) ) ),
    SendToReport(
        Dispatch( {}, "400", ScaleBox,
            {Legend Model(
                13,
                Properties( 0, {Fill Pattern( "left slant light" )}, Item ID( "Midwest", 1 ) ),
                Properties( 2, {Fill Pattern( "vertical light" )}, Item ID( "New England", 1 ) ),
                Properties( 5, {Fill Pattern( "horizontal light" )}, Item ID( "Plains", 1 ) ),
                Properties( 6, {Fill Pattern( "grid medium" )}, Item ID( "South", 1 ) )
            )}
        ),
        Dispatch( {}, "Graph Builder", FrameBox, {DispatchSeg( Shape Seg( 1 ), {Color( "Medium Dark Gray" ), Line Width( 2 )} )} )
    )
);
rpt = obj << report;

Code Explanation:

1. Open data table.
2. Create Graph Builder object.
3. Set size to 534x456.
4. Hide control panel.
5. Assign color and shape variables.
6. Add map shapes element.
7. Configure legend properties.
8. Set fill patterns for regions.
9. Customize shape segment appearance.
10. Generate report from graph.

Example 1569

Summary: Creates a variability chart with nested factors using operator and part configurations, displaying standard deviation charts for data analysis.

Code:

Open("data_table.jmp");
obj = Graph Builder(
    Size( 534, 456 ),
    Show Control Panel( 0 ),
    Variables( Color( :Region ), Shape( :State ) ),
    Elements( Map Shapes( Legend( 13 ) ) ),
    SendToReport(
        Dispatch( {}, "400", ScaleBox,
            {Legend Model(
                13,
                Properties( 0, {Fill Pattern( "left slant light" )}, Item ID( "Midwest", 1 ) ),
                Properties( 2, {Fill Pattern( "vertical light" )}, Item ID( "New England", 1 ) ),
                Properties( 5, {Fill Pattern( "horizontal light" )}, Item ID( "Plains", 1 ) ),
                Properties( 6, {Fill Pattern( "grid medium" )}, Item ID( "South", 1 ) )
            )}
        ),
        Dispatch( {}, "Graph Builder", FrameBox, {DispatchSeg( Shape Seg( 1 ), {Color( "Medium Dark Gray" ), Line Width( 2 )} )} )
    )
);
rpt = obj << report;
rpt << journal;

Code Explanation:

1. Open data table;
2. Create Graph Builder object.
3. Set graph size.
4. Hide control panel.
5. Define color and shape variables.
6. Add map shapes element.
7. Customize legend properties.
8. Set fill patterns for regions.
9. Customize shape segment properties.
10. Generate report and journal.

Example 1570

Summary: Creates a geographic map to visualize data points across the United States, utilizing Graph Builder and ScaleBox configurations.

Code:

Open("data_table.jmp");
Graph Builder(
    Transform Column( "lat", Formula( :height - 25 ) ),
    Transform Column( "lon", Formula( (-45) - :weight * 0.45 ) ),
    Size( 582, 408 ),
    Show Control Panel( 0 ),
    Variables( X( :lon ), Y( :lat ) ),
    Elements( Points( X, Y, Legend( 3 ) ) ),
    SendToReport(
        Dispatch( {}, "lon", ScaleBox,
            {Scale( "Geodesic", {Compact Map( {Region( "United States" )} )} ), Min( -125.491162298084 ), Max( -68.5720461069222 ),
            Inc( 10 ), Minor Ticks( 0 )}
        ),
        Dispatch( {}, "lat", ScaleBox,
            {Scale( "Geodesic", {Compact Map( {Region( "United States" )} )} ), Min( 17.8335055350553 ), Max( 52.9264944649446 ), Inc( 10 ),
            Minor Ticks( 1 )}
        ),
        Dispatch( {}, "Graph Builder", FrameBox, {Background Map( Boundaries( "US States" ) )} )
    )
);

Code Explanation:

1. Open data table;
2. Transform "lat" column.
3. Transform "lon" column.
4. Set Graph Builder size.
5. Hide control panel.
6. Set X variable.
7. Set Y variable.
8. Add points element.
9. Configure lon scale.
10. Configure lat scale.
11. Add background map.

Example 1571

Summary: Creates a geographic map to visualize infant mortality rates and population sizes across territories, utilizing Graph Builder's variables, elements, and local data filtering capabilities.

Code:

Open("data_table.jmp");
Current Data Table() << clear row states();
Graph Builder(
    Size( 534, 453 ),
    Show Control Panel( 0 ),
    Variables( Color( :Development Level ), Color( :Infant Mortality Rate ), Size( :Name( "Population (1000)" ) ), Shape( :Territory ) ),
    Elements( Map Shapes( Size( 0 ), Legend( 8 ) ), Points( Color( 2 ), Legend( 9 ) ) ),
    Local Data Filter(
        Close Outline( 1 ),
        Add Filter(
            columns( :Name( "Population (1000)" ) ),
            Where( :Name( "Population (1000)" ) >= 0.05 & :Name( "Population (1000)" ) <= 333500 )
        )
    ),
    SendToReport(
        Dispatch( {}, "", ScaleBox, {Min( -18.1823979591837 ), Max( 48.1823979591837 ), Inc( 20 ), Minor Ticks( 0 )} ),
        Dispatch( {}, "", ScaleBox( 2 ), {Min( 16 ), Max( 71 ), Inc( 10 ), Minor Ticks( 0 )} ),
        Dispatch( {}, "400", ScaleBox,
            {Legend Model(
                8,
                Properties( 0, {Line Color( -13032431 ), Fill Color( -13032431 )} ),
                Properties( 1, {Line Color( -7057110 ), Fill Color( -7057110 )} ),
                Properties( 2, {Line Color( -2191797 ), Fill Color( -2191797 )} ),
                Properties( 3, {Line Color( -536683 ), Fill Color( -536683 )} )
            ), Legend Model(
                9,
                Properties( 0, {Marker Size( 8 )} ),
                Properties(
                    1,
                    {gradient(
                        {Color Theme( {"Green to Black 1198", 2051, {{44, 173, 86}, {45, 114, 67}, "Black"}, {0, 0.37037037037037, 1}} ),
                        Width( 12 )}
                    )}
                )
            )}
        ),
        Dispatch( {}, "Graph Builder", FrameBox, {Marker Size( 6 )} )
    )
);

Code Explanation:

1. Open data table.
2. Clear row states.
3. Create Graph Builder object.
4. Set size and control panel visibility.
5. Define variables for coloring, sizing, and shaping.
6. Add map shapes and points elements.
7. Add local data filter for population.
8. Set scale box properties for axes.
9. Customize legend models for colors and markers.
10. Adjust marker size in frame box.

Example 1572

Summary: Creates a geographic map to display physical activity levels across US states, utilizing Graph Builder and customizing background maps.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 457, 399 ),
    Show Control Panel( 0 ),
    Variables( Color( :Physical Activity ), Shape( :State ) ),
    Elements( Map Shapes( Legend( 2 ) ) ),
    SendToReport(
        Dispatch( {}, "Graph Builder", FrameBox,
            {Background Map( Boundaries( "US States" ) ), Grid Line Order( 2 ), Reference Line Order( 3 )}
        )
    )
);

Code Explanation:

1. Open data table;
2. Create Graph Builder window.
3. Set window size.
4. Hide control panel.
5. Define color variable.
6. Define shape variable.
7. Add map shapes element.
8. Enable legend for map shapes.
9. Customize background map.
10. Adjust grid and reference line order.

Example 1573

Summary: Creates a geographic map to visualize years of compulsory education across territories, utilizing Graph Builder and customizing scale boxes, legend appearance, and graph title.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 748, 534 ),
    Show Control Panel( 0 ),
    Variables( Color( :Years of Compulsory Education ), Shape( :Territory ) ),
    Elements( Map Shapes( Legend( 2 ) ) ),
    SendToReport(
        Dispatch( {}, "", ScaleBox,
            {Min( 190.267259502854 ), Max( -190 ), Inc( 50 ), Minor Ticks( 0 ), Label Row( Show Major Grid( 1 ) )}
        ),
        Dispatch( {}, "", ScaleBox( 2 ),
            {Min( 128.08426145535 ), Max( -135.865953964279 ), Inc( 50 ), Minor Ticks( 1 ), Label Row( Show Major Grid( 1 ) )}
        ),
        Dispatch( {}, "400", ScaleBox,
            {Legend Model( 2, Properties( 0, {gradient( {Color Theme( "White to Green" ), Label Format( "Fixed Dec", 15, 0 )} )} ) )}
        ),
        Dispatch( {}, "graph title", TextEditBox, {Set Text( "Years of Compulsory Education" )} ),
        Dispatch( {}, "400", LegendBox, {Set Title( "Years" )} )
    )
);

Code Explanation:

1. Open data table.
2. Create Graph Builder window.
3. Set window size.
4. Hide control panel.
5. Define color and shape variables.
6. Add map shapes element.
7. Configure first scale box.
8. Configure second scale box.
9. Customize legend appearance.
10. Set graph title.

Example 1574

Summary: Creates a variability chart with nested factors using operator and part configurations, displaying standard deviation charts.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 534, 452 ),
    Show Control Panel( 0 ),
    Variables( X( :Barr ), Y( :Barr ), Color( :Barr ), Shape( :State ) ),
    Elements( Map Shapes( X, Y, Legend( 1 ) ), Smoother( X, Y, Legend( 2 ) ) )
);

Code Explanation:

1. Open table.
2. Set graph size.
3. Hide control panel.
4. Define X variable.
5. Define Y variable.
6. Define color variable.
7. Define shape variable.
8. Add map shapes element.
9. Add smoother element.
10. Display graph.

Example 1575

Summary: Creates a geographic map to display population data across territories, utilizing Graph Builder's Map Shapes feature.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 686, 419 ),
    Show Control Panel( 0 ),
    Variables( Size( :Name( "Population (1000)" ) ), Shape( :Territory ) ),
    Elements( Map Shapes( Legend( 13 ) ) )
);

Code Explanation:

1. Open data table;
2. Launch Graph Builder.
3. Set window size.
4. Hide control panel.
5. Define variables.
6. Add population variable.
7. Assign territory shape.
8. Create map elements.
9. Display legend.

Example 1576

Summary: Creates a geographic map to visualize crude birth rates across territories, utilizing Graph Builder and customizing scale boxes, legends, and titles.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 748, 534 ),
    Show Control Panel( 0 ),
    Variables( Color( :Name( "Crude Birth Rate (1000)" ) ), Shape( :Territory ) ),
    Elements( Map Shapes( Legend( 2 ), Summary Statistic( "Mean" ), Show Missing Shapes( 0 ) ) ),
    SendToReport(
        Dispatch( {}, "", ScaleBox,
            {Min( -199.036236140874 ), Max( 199.036236140874 ), Inc( 50 ), Minor Ticks( 0 ), Show Major Grid( 1 )}
        ),
        Dispatch( {}, "", ScaleBox( 2 ),
            {Min( -142.363619108751 ), Max( 134.581926599822 ), Inc( 50 ), Minor Ticks( 1 ), Show Major Grid( 1 )}
        ),
        Dispatch( {}, "400", ScaleBox,
            {Legend Model(
                2,
                Properties(
                    0,
                    {gradient(
                        {Color Theme( "White to Green" ), Label Format( "Fixed Dec", 15, 0 ), Reverse Colors( 1 ), Reverse Scale( 1 )}
                    )}
                )
            )}
        ),
        Dispatch( {}, "400", LegendBox, {Set Title( "Births per 1000" )} ),
        Dispatch( {}, "graph title", TextEditBox, {Set Text( "Birth Rate" )} ),
        Dispatch( {}, "X title", TextEditBox, {Set Text( "" )} )
    )
);

Code Explanation:

1. Open data table;
2. Launch Graph Builder.
3. Set window size.
4. Hide control panel.
5. Assign color variable.
6. Assign shape variable.
7. Add map shapes element.
8. Configure first scale box.
9. Configure second scale box.
10. Customize legend and title.

Example 1577

Summary: Creates a geographic map to visualize crude birth rate data across territories, filtered by population range and customized with scale boxes and legend settings.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 744, 551 ),
    Show Control Panel( 0 ),
    Variables( Color( :Name( "Crude Birth Rate (1000)" ) ), Shape( :Territory ) ),
    Elements( Map Shapes( Legend( 2 ) ) ),
    Local Data Filter(
        Add Filter(
            columns( :Name( "Population (1000)" ) ),
            Where( :Name( "Population (1000)" ) >= 0.05 & :Name( "Population (1000)" ) <= 248100 )
        )
    ),
    SendToReport(
        Dispatch( {}, "", ScaleBox,
            {Min( -199.036236140874 ), Max( 199.036236140874 ), Inc( 50 ), Minor Ticks( 0 ), Label Row( Show Major Grid( 1 ) )}
        ),
        Dispatch( {}, "", ScaleBox( 2 ),
            {Min( -147.868241924416 ), Max( 140.086549415487 ), Inc( 50 ), Minor Ticks( 1 ), Label Row( Show Major Grid( 1 ) )}
        ),
        Dispatch( {}, "400", ScaleBox, {Legend Model( 2, Properties( 0, {gradient( {Color Theme( "White to Green" ), Width( 12 )} )} ) )} ),
        Dispatch( {}, "graph title", TextEditBox, {Set Text( "Birth Rate" )} ),
        Dispatch( {}, "X title", TextEditBox, {Set Text( "" )} ),
        Dispatch( {}, "400", LegendBox, {Set Title( "Births per 1000" )} )
    )
);

Code Explanation:

1. Open data table;
2. Create Graph Builder window.
3. Set window size.
4. Hide control panel.
5. Define color variable.
6. Define shape variable.
7. Add map shapes element.
8. Enable local data filter.
9. Set filter criteria.
10. Customize report appearance.

Example 1578

Summary: Creates a variability chart with nested factors using operator and part configurations, displaying standard deviation charts.

Code:

dt under test = Open("data_table.jmp");
obj = Graph Builder(
    Show Control Panel( 0 ),
    Variables( Color( :Name( "% Taking (2004)" ) ), Shape( :State ) ),
    Elements( Map Shapes( Legend( 3 ) ) ),
    SendToReport( Dispatch( {}, "400", ScaleBox, {Legend Model( 3, Properties( 0, {gradient( {Color Theme( "White to Green" )} )} ) )} ) )
);

Code Explanation:

1. Open data_table data
2. Create Graph Builder object.
3. Hide control panel.
4. Set color variable.
5. Set shape variable.
6. Add map shapes element.
7. Customize legend model.
8. Set gradient color theme.

Example 1579

Summary: Creates a geographic map to visualize SAS Country Office locations, utilizing Graph Builder and specifying graph title, background color, and world boundaries.

Code:

dt under test = Open("data_table.jmp");
obj = Graph Builder(
    Show Control Panel( 0 ),
    Variables( X( :Longitude ), Y( :Latitude ), Shape( :SAS Country Office ) ),
    Elements( Points( X, Y, Legend( 10 ) ) ),
    SendToReport(
        Dispatch( {}, "graph title", TextEditBox, {Set Text( "SAS Country Office Locations" )} ),
        Dispatch( {}, "Graph Builder", FrameBox,
            {Background Color( 0 ), Background Map( Images( "Detailed Earth" ), Boundaries( "World" ) ), Grid Line Order( 3 ),
            Reference Line Order( 4 )}
        )
    )
);

Code Explanation:

1. Open data table.
2. Create Graph Builder object.
3. Hide control panel.
4. Set X, Y, and Shape variables.
5. Add points element with legend.
6. Set graph title.
7. Configure background color.
8. Use detailed Earth map.
9. Set world boundaries.
10. Adjust grid and reference line order.

Example 1580

Summary: Creates a variability chart with nested factors using operator and part configurations, displaying standard deviation charts.

Code:

Names Default To Here( 1 );
dt = Open("data_table.jmp");
Graph Builder(
    Show Control Panel( 0 ),
    Variables( Color( :SAT Math ), Shape( :State ) ),
    Elements( Map Shapes( Legend( 2 ), Summary Statistic( "Mean" ), Show Missing Shapes( 0 ) ) )
);

Code Explanation:

1. Set default names.
2. Open data table.
3. Launch Graph Builder.
4. Hide control panel.
5. Set color variable.
6. Set shape variable.
7. Add map shapes element.
8. Set legend position.
9. Use mean summary statistic.
10. Hide missing shapes.

Example 1581

Summary: Creates a geographic map to visualize physical activity levels across US states, utilizing Graph Builder and its elements.

Code:

dt = Open("data_table.jmp");
dt << select all rows;
dt << hide;
Graph Builder(
    Size( 337, 293 ),
    Show Control Panel( 0 ),
    Show Legend( 0 ),
    Variables( Color( :Physical Activity ), Shape( :State ) ),
    Elements( Map Shapes( Legend( 2 ) ) ),
    SendToReport(
        Dispatch( {}, "Graph Builder", FrameBox,
            {Background Map( Boundaries( "US States" ) ), Grid Line Order( 2 ), Reference Line Order( 3 )}
        )
    )
);

Code Explanation:

1. Open data table;
2. Select all rows.
3. Hide selected rows.
4. Create Graph Builder.
5. Set size 337x293.
6. Hide control panel.
7. Hide legend.
8. Set color variable.
9. Set shape variable.
10. Add map shapes element.

Example 1582

Summary: Creates a Graph Builder visualization with nested factors, utilizing the Graph Builder platform to display a map of shapes based on IQ and State variables.

Code:

dt = Open("data_table.jmp");
dt << select where( :Region == "W" );
mySubset = dt << subset( linked, dt );
mySubset << clear row states;
mySubset << select rows( [1, 2] );
mySubset << hide;
mySubset << Graph Builder(
    Size( 534, 454 ),
    Show Control Panel( 0 ),
    Variables( Color( :IQ ), Shape( :State ) ),
    Elements( Map Shapes( Legend( 5 ) ) )
);

Code Explanation:

1. Open data table;
2. Select Region "W".
3. Create linked subset.
4. Clear row states.
5. Select rows 1 and 2.
6. Hide selected rows.
7. Initiate Graph Builder.
8. Set graph size.
9. Disable control panel.
10. Define color and shape variables.
11. Add map shapes element.
12. Display legend for shapes.

Example 1583

Summary: Creates a graph builder with nested factors using operator and part configurations, displaying standard deviation charts.

Code:

dt = Open("data_table.jmp");
dt << select where( :Region == "W" );
mySubset = dt << subset( linked, dt );
mySubset << clear row states;
mySubset << Graph Builder(
    Size( 534, 454 ),
    Show Control Panel( 0 ),
    Variables( Color( :IQ ), Shape( :State ) ),
    Elements( Map Shapes( Color( 0 ), Show Missing Shapes( 1 ), Legend( 5 ) ) )
);

Code Explanation:

1. Open data table;
2. Select rows where Region is "W".
3. Create linked subset.
4. Clear row states in subset.
5. Launch Graph Builder.
6. Set graph size.
7. Hide control panel.
8. Assign color variable.
9. Assign shape variable.
10. Add map shapes element.

Example 1584

Summary: Creates a geographic map to visualize population data across states, utilizing Graph Builder and Local Data Filter for interactive filtering.

Code:

Open("data_table.jmp") << Graph Builder(
    Size( 892, 663 ),
    Show Control Panel( 0 ),
    Variables( Y( :Region ), Group Y( :Region ), Color( :Name( "Population (July 2009)" ) ), Shape( :State ) ),
    Elements( Map Shapes( Y, Legend( 11 ) ) ),
    Local Data Filter( Mode( Include( 0 ) ), Add Filter( columns( :Flu Cases ), Where( :Flu Cases >= 135 & :Flu Cases <= 7265 ) ) ),
    SendToReport(
        Dispatch( {}, "Graph Builder", FrameBox( 2 ),
            Add Pin Annotation(
                Seg( Shape Seg( 1 ) ),
                Index( 5 ),
                Index Row( 1595 ),
                UniqueID( 791062981 ),
                FoundPt( {646, 163} ),
                Origin( {-105.666565060055, 39.0666666666667} )
            )
        )
    )
);

Code Explanation:

1. Open data table;
2. Initialize Graph Builder.
3. Set window size.
4. Hide control panel.
5. Define Y, Group Y, Color, and Shape variables.
6. Add Map Shapes element.
7. Create local data filter.
8. Send report to Graph Builder.
9. Dispatch to Graph Builder frame.
10. Add pin annotation to map.

Example 1585

Summary: Creates a geographic map to visualize crude birth rate data across territories, utilizing Graph Builder and configuring scale box settings for interactive analysis.

Code:

Open("data_table.jmp") << Graph Builder(
    Size( 748, 534 ),
    Show Control Panel( 0 ),
    Variables( Color( :Name( "Crude Birth Rate (1000)" ) ), Shape( :Territory ) ),
    Elements( Map Shapes( Legend( 2 ), Summary Statistic( "% of Total" ) ), Points( Legend( 3 ) ) ),
    SendToReport(
        Dispatch( {}, "", ScaleBox,
            {Min( -199.494672756176 ), Max( 199.494672756176 ), Inc( 50 ), Minor Ticks( 0 ), Label Row( Show Major Grid( 1 ) )}
        ),
        Dispatch( {}, "", ScaleBox( 2 ),
            {Min( -142.363619108751 ), Max( 134.581926599822 ), Inc( 50 ), Minor Ticks( 1 ), Label Row( Show Major Grid( 1 ) )}
        ),
        Dispatch( {}, "400", ScaleBox, {Legend Model( 2, Properties( 0, {gradient( {Color Theme( "White to Green" ), Width( 12 )} )} ) )} ),
        Dispatch( {}, "graph title", TextEditBox, {Set Text( "Birth Rate" )} ),
        Dispatch( {}, "X title", TextEditBox, {Set Text( "" )} ),
        Dispatch( {}, "Graph Builder", FrameBox,
            Add Pin Annotation(
                Seg( Marker Seg( 1 ) ),
                Index( 142 ),
                Index Row( 142 ),
                UniqueID( 726037710 ),
                FoundPt( {573, 204} ),
                Origin( {100.105117531403, 45.9828219345794} )
            )
        ),
        Dispatch( {}, "400", LegendBox, {Set Title( "Births per 1000" )} )
    )
);

Code Explanation:

1. Open data table;
2. Create Graph Builder.
3. Set size 748x534.
4. Hide control panel.
5. Set color variable.
6. Set shape variable.
7. Add map shapes element.
8. Add points element.
9. Configure scale box settings.
10. Configure legend and annotation.

Example 1586

Summary: Creates a Mosaic chart with nested factors using Graph Builder, displaying age and weight variables.

Code:

Open("data_table.jmp");
Graph Builder( Show Control Panel( 0 ), Variables( X( :age ), Y( :weight ) ), Elements( Mosaic( X, Y, Legend( 14 ) ) ) );

Code Explanation:

1. Open data table.
2. Launch Graph Builder.
3. Hide control panel.
4. Set X variable to age.
5. Set Y variable to weight.
6. Add Mosaic element.
7. Configure legend for Mosaic.

Example 1587

Summary: Creates a Graph Builder window with nested factors using operator and part configurations, displaying standard deviation charts.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 577, 497 ),
    Show Control Panel( 0 ),
    Variables( X( :age ), X( :weight ), Y( :height ) ),
    Elements( Position( 1, 1 ), Bar( X, Y, Legend( 12 ) ) ),
    Elements( Position( 2, 1 ), Mosaic( X, Y, Legend( 13 ) ) )
);

Code Explanation:

1. Open data table.
2. Create Graph Builder window.
3. Set window size.
4. Hide control panel.
5. Define variables: age, weight, height.
6. Add bar element at position 1,1.
7. Add mosaic element at position 2,1.
8. Assign legend to bar element.
9. Assign legend to mosaic element.
10. Display graph.

Example 1588

Summary: Creates a mosaic chart with sex as the X-axis variable, displaying standard deviation charts and utilizing Graph Builder.

Code:

Open("data_table.jmp");
:sex[1] = "";
:sex << set property( "Informative Missing", 1 );
Graph Builder( Size( 439, 342 ), Show Control Panel( 0 ), Variables( X( :sex ) ), Elements( Mosaic( X, Legend( 1 ) ) ) );

Code Explanation:

1. Open data table;
2. Set first sex value to empty string.
3. Mark sex column as informative missing.
4. Launch Graph Builder.
5. Set graph size to 439x342.
6. Hide control panel.
7. Assign sex to X variable.
8. Add Mosaic element.
9. Use legend for mosaic.

Example 1589

Summary: Creates a mosaic chart with nested factors using Graph Builder, displaying the relationship between weight and name.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 390, 155 ),
    Show Control Panel( 0 ),
    Show Legend( 0 ),
    Variables( X( :weight ), Y( :name ) ),
    Elements( Mosaic( X, Y, Legend( 3 ) ) )
);

Code Explanation:

1. Open data table;
2. Create Graph Builder object.
3. Set graph size to 390x155.
4. Hide control panel.
5. Hide legend.
6. Assign weight to X axis.
7. Assign name to Y axis.
8. Add mosaic element.
9. Link X and Y variables.
10. Set legend position to 3.

Example 1590

Summary: Creates a mosaic chart with nested factors using Graph Builder, displaying standard deviation charts and configuring legend settings.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 441, 363 ),
    Show Control Panel( 0 ),
    Show Legend( 0 ),
    Variables( X( :Age ), Y( :Name( "Claim(Y/N)" ) ) ),
    Elements( Mosaic( X, Y, Legend( 4 ) ) )
);

Code Explanation:

1. Open data_table data
2. Create Graph Builder.
3. Set size to 441x363.
4. Hide control panel.
5. Hide legend.
6. Set X variable to Age.
7. Set Y variable to Claim(Y/N).
8. Add Mosaic element.
9. Assign legend to 4.
10. Display graph.

Example 1591

Summary: Creates a mosaic chart with nested factors using Graph Builder, displaying standard deviation charts and configuring legend position.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 431, 334 ),
    Show Control Panel( 0 ),
    Show Legend( 0 ),
    Variables( X( :Development Level ), Y( :Average Years of Education of Adults ) ),
    Elements( Mosaic( X, Y, Legend( 10 ) ) )
);

Code Explanation:

1. Open data table;
2. Launch Graph Builder.
3. Set window size.
4. Hide control panel.
5. Hide legend.
6. Assign X variable.
7. Assign Y variable.
8. Add mosaic element.
9. Set legend position.

Example 1592

Summary: Creates a mosaic chart with nested factors using Graph Builder, displaying standard deviation charts and configuring X and Y variables.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 523, 453 ),
    Show Control Panel( 0 ),
    Variables( X( :Landfall in USA ), Y( :Storm Category ) ),
    Elements( Mosaic( X, Y, Legend( 4 ) ) )
);

Code Explanation:

1. Open data table;
2. Create Graph Builder window.
3. Set window size.
4. Hide control panel.
5. Assign X variable.
6. Assign Y variable.
7. Add Mosaic element.
8. Configure X axis.
9. Configure Y axis.
10. Display legend.

Example 1593

Summary: Creates a variability chart with nested factors using Graph Builder, configuring X variable as Passenger Class, Y variable as Survived, and Group X variable as Sex.

Code:

Open("data_table.jmp");
Graph Builder(
    Show Control Panel( 0 ),
    Variables( X( :Passenger Class ), Y( :Survived ), Group X( :Sex ) ),
    Elements( Mosaic( X, Y, Legend( 4 ), Vertical ) ),
    SendToReport(
        Dispatch( {}, "400", ScaleBox, {Legend Model( 4, Properties( 0, {Fill Color( 72 )} ), Properties( 1, {Fill Color( 69 )} ) )} ),
        Dispatch( {}, "graph title", TextEditBox, {Set Text( "Survived vs. Passenger Class and Sex" )} )
    )
);

Code Explanation:

1. Open data table;
2. Launch Graph Builder.
3. Hide control panel.
4. Set X variable: Passenger Class.
5. Set Y variable: Survived.
6. Set Group X variable: Sex.
7. Add Mosaic element.
8. Configure vertical orientation.
9. Customize legend colors.
10. Set graph title.

Example 1594

Summary: Creates a mosaic plot to visualize relationships between sex, height, and weight using Graph Builder.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 200, 400 ),
    Show Control Panel( 0 ),
    Variables( X( :sex ), Y( :height ), Frequency( :weight ) ),
    Elements( Mosaic( X, Y, Legend( 7 ), Cell Labeling( "Label by Count" ) ) )
);

Code Explanation:

1. Open data table;
2. Create Graph Builder window.
3. Set graph size.
4. Hide control panel.
5. Define X variable.
6. Define Y variable.
7. Define frequency variable.
8. Add Mosaic element.
9. Set legend position.
10. Label cells by count.

Example 1595

Summary: Creates a mosaic chart with nested factors using Graph Builder, displaying cell labels by percent.

Code:

dt = Open("data_table.jmp");
Graph Builder(
    Size( 511, 187 ),
    Show Control Panel( 0 ),
    Show Legend( 0 ),
    Variables( X( :age ) ),
    Elements( Mosaic( X, Legend( 3 ), Cell Labeling( "Label by Percent" ) ) )
);

Code Explanation:

1. Open data table.
2. Create Graph Builder window.
3. Set window size.
4. Hide control panel.
5. Hide legend.
6. Assign age variable to X-axis.
7. Add mosaic element.
8. Label cells by percent.

Example 1596

Summary: Creates a mosaic chart with nested factors using Graph Builder, displaying the relationship between 'Rank[sex]' and 'height'.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 432, 350 ),
    Show Control Panel( 0 ),
    Variables( X( Transform Column( "Rank[sex]", Character, Formula( Col Rank( :sex ) ) ) ), Size( :height ) ),
    Elements( Mosaic( X, Legend( 14 ) ) )
);

Code Explanation:

1. Open data_table data
2. Launch Graph Builder.
3. Set window size.
4. Hide control panel.
5. Define X variable.
6. Transform sex column.
7. Calculate column rank.
8. Assign height as size.
9. Add mosaic element.
10. Display legend.

Example 1597

Summary: Creates a nested mosaic chart with two factors using Graph Builder, displaying standard deviation charts for each combination.

Code:

Open("data_table.jmp");
Graph Builder(
    Show Control Panel( 0 ),
    Variables( X( :age ), Y( :sex ), Y( :sex ) ),
    Elements( Position( 1, 1 ), Mosaic( X, Y, Legend( 5 ) ) ),
    Elements( Position( 1, 2 ), Mosaic( X, Y, Legend( 4 ) ) )
);

Code Explanation:

1. Open data table;
2. Launch Graph Builder.
3. Hide control panel.
4. Set X variable to age.
5. Set Y variables to sex.
6. Add first mosaic element.
7. Position first mosaic at 1,1.
8. Add second mosaic element.
9. Position second mosaic at 1,2.
10. Display graph.

Example 1598

Summary: Creates a mosaic chart with nested factors using Graph Builder, displaying standard deviation charts and customizing legend position.

Code:

Open("data_table.jmp");
Graph Builder(
    Show Control Panel( 0 ),
    Variables( X( :Type ), Y( :Country ) ),
    Elements( Mosaic( X, Y, Legend( 5 ) ) ),
    SendToReport(
        Dispatch( {}, "Graph Builder", FrameBox,
            {DispatchSeg( MosaicSeg( 1 ), {Line Color( "Medium Dark Gray" ), Line Width( 5 ), Horizontal Gap( 6 ), Vertical Gap( 6 )} )}
        )
    )
);

Code Explanation:

1. Open data table.
2. Launch Graph Builder.
3. Hide control panel.
4. Set X variable to Type.
5. Set Y variable to Country.
6. Add Mosaic element.
7. Customize legend position.
8. Access report frame.
9. Dispatch mosaic segment settings.
10. Set line color to gray.
11. Set line width to 5.
12. Set horizontal gap to 6.
13. Set vertical gap to 6.

Example 1599

Summary: Creates a nested variability chart using Graph Builder, displaying standard deviation charts and configuring the window size, control panel, and variables.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 543, 502 ),
    Show Control Panel( 0 ),
    Variables( X( :Strength ), Y( :Degrees ), Group X( :Weeks ), Group Y( :Censor ) ),
    Elements( Mosaic( X, Y, Legend( 16 ) ) )
);

Code Explanation:

1. Open data table;
2. Create new Graph Builder window.
3. Set window size.
4. Hide control panel.
5. Define X variable.
6. Define Y variable.
7. Define Group X variable.
8. Define Group Y variable.
9. Add Mosaic element.
10. Display graph.

Example 1600

Summary: Creates a mosaic plot with nested factors using Graph Builder, displaying standard deviation charts for weight and height based on age and name.

Code:

Open("data_table.jmp");
Graph Builder( Variables( X( :weight ), Y( :height ), Group X( :age ), Shape( :name ) ), Elements( Mosaic( X, Y, Legend( 13 ) ) ) );

Code Explanation:

1. Open data table;
2. Create Graph Builder object.
3. Set X variable to weight.
4. Set Y variable to height.
5. Group X by age.
6. Assign shape by name.
7. Add Mosaic element.
8. Use Legend with ID 13.

Example 1601

Summary: Creates a variability chart with nested factors using Graph Builder, displaying standard deviation charts and configuring sex as an informative missing value.

Code:

Open("data_table.jmp");
:sex[1] = "";
:sex << set property( "Informative Missing", 1 );
Graph Builder(
    Size( 400, 250 ),
    Show Control Panel( 0 ),
    Variables( X( :age ), X( :sex, Position( 1 ) ), Overlay( :sex ) ),
    Elements( Mosaic( X( 2 ), X( 1 ), Legend( 16 ) ) )
);

Code Explanation:

1. Open data table;
2. Set first sex value to empty.
3. Mark sex column as Informative Missing.
4. Create Graph Builder window.
5. Set window size to 400x250.
6. Hide control panel.
7. Assign age to X-axis.
8. Assign sex to second X-axis.
9. Overlay sex variable.
10. Add Mosaic element with sex and age.

Example 1602

Summary: Creates a mosaic chart with nested factors using Graph Builder, displaying standard deviation charts and formatting labels as currency.

Code:

dt = Open("data_table.jmp");
Graph Builder(
    Size( 398, 194 ),
    Show Control Panel( 0 ),
    Show Legend( 0 ),
    Variables( X( :age ) ),
    Elements(
        Mosaic( X, Legend( 3 ), Cell Labeling( "Label by Value" ), Label Format( "Currency", "USD", Use thousands separator( 0 ), 9, 0 ) )
    )
);

Code Explanation:

1. Open data table.
2. Create new Graph Builder.
3. Set graph size.
4. Hide control panel.
5. Hide legend.
6. Assign X variable.
7. Add mosaic element.
8. Set legend position.
9. Enable cell labeling.
10. Format labels as currency.

Example 1603

Summary: Creates a Mosaic chart with nested factors using Graph Builder, displaying standard deviation charts and configuring legend settings.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 534, 464 ),
    Show Control Panel( 0 ),
    Variables(
        X( :country ),
        X( :size, Position( 1 ) ),
        X( :type, Position( 1 ) ),
        Y( :sex ),
        Y( :marital status, Position( 1 ) ),
        Y( :age, Position( 1 ) )
    ),
    Elements( Mosaic( X( 1 ), X( 2 ), X( 3 ), Y( 1 ), Y( 2 ), Y( 3 ), Legend( 4 ) ) )
);

Code Explanation:

1. Open data table.
2. Launch Graph Builder.
3. Set window size.
4. Hide control panel.
5. Define X variables.
6. Define Y variables.
7. Add Mosaic element.
8. Assign X axes.
9. Assign Y axes.
10. Configure legend.

Example 1604

Summary: Creates a mosaic chart with nested factors using Graph Builder, displaying age as the dependent variable and country, size, and type as independent variables.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 534, 464 ),
    Show Control Panel( 0 ),
    Variables( X( :country ), X( :size, Position( 1 ) ), X( :type, Position( 1 ) ), Y( :age ) ),
    Elements( Mosaic( X( 1 ), X( 2 ), X( 3 ), Y, Legend( 6 ) ) )
);

Code Explanation:

1. Open data table;
2. Create Graph Builder window.
3. Set window size.
4. Hide control panel.
5. Define X variables: country, size, type.
6. Define Y variable: age.
7. Add Mosaic element.
8. Assign axes to Mosaic.
9. Set legend position.
10. Display graph.

Example 1605

Summary: Creates a nested variability chart with standard deviation charts, using Graph Builder to visualize data from 'Reported Term for the Adverse Event' and 'Planned Treatment for Period 01', while coloring by 'Body System or Organ Class'.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 793, 392 ),
    Show Control Panel( 0 ),
    Show Legend( 0 ),
    Fit to Window( "Off" ),
    Variables(
        X(
            :Reported Term for the Adverse Event,
            Order By(
                Transform Column(
                    "Count",
                    Formula( Col Number( :Reported Term for the Adverse Event, :Reported Term for the Adverse Event ) )
                ),
                Ascending,
                Order Statistic( "Mean" )
            )
        ),
        Group X( :Planned Treatment for Period 01 ),
        Color( :Body System or Organ Class )
    ),
    Elements( Mosaic( X, Legend( 2 ) ) )
);

Code Explanation:

1. Open data_table data
2. Create Graph Builder.
3. Set size to 793x392.
4. Hide control panel.
5. Hide legend.
6. Disable fit to window.
7. Set X variable.
8. Order by count.
9. Group by treatment.
10. Color by body system.

Example 1606

Summary: Creates a variability chart with nested factors using Graph Builder, displaying standard deviation charts and grouping data by planned treatment for period 01.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 793, 392 ),
    Show Control Panel( 0 ),
    Show Legend( 0 ),
    Fit to Window( "Off" ),
    Variables(
        X(
            :Reported Term for the Adverse Event,
            Order By(
                Transform Column(
                    "Count",
                    Formula( Col Number( :Reported Term for the Adverse Event, :Reported Term for the Adverse Event ) )
                ),
                Descending,
                Order Statistic( "Mean" )
            )
        ),
        Group X( :Planned Treatment for Period 01 ),
        Color( :Body System or Organ Class )
    ),
    Elements( Mosaic( X, Legend( 2 ) ) )
);

Code Explanation:

1. Open data table;
2. Create new Graph Builder window.
3. Set window size.
4. Hide control panel.
5. Hide legend.
6. Disable fit to window.
7. Define X variable.
8. Order X by count.
9. Group X by treatment.
10. Color by body system.

Example 1607

Summary: Creates a variability chart with nested factors using Graph Builder, configuring X, group X, and color variables to visualize data.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 793, 392 ),
    Show Control Panel( 0 ),
    Show Legend( 0 ),
    Fit to Window( "Off" ),
    Variables(
        X( :Reported Term for the Adverse Event ),
        Group X( :Planned Treatment for Period 01 ),
        Color( :Body System or Organ Class )
    ),
    Elements( Mosaic( X, Legend( 2 ) ) )
);

Code Explanation:

1. Open data file.
2. Create Graph Builder window.
3. Set window size.
4. Hide control panel.
5. Hide legend.
6. Disable fit to window.
7. Define X variable.
8. Define group X variable.
9. Define color variable.
10. Add mosaic element.

Example 1608

Summary: Creates a nested factors variability chart using Graph Builder, with interactive features for color-coding and grouping.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 718, 382 ),
    Show Control Panel( 0 ),
    Show Legend( 0 ),
    Fit to Window( "Off" ),
    Variables(
        X( :Reported Term for the Adverse Event, Order By( Empty(), Descending, Order Statistic( "Mean" ) ) ),
        Group X( :Planned Treatment for Period 01 ),
        Color( :Body System or Organ Class )
    ),
    Elements( Mosaic( X, Legend( 2 ) ) )
);

Code Explanation:

1. Open data table.
2. Create Graph Builder window.
3. Set window size.
4. Hide control panel.
5. Hide legend.
6. Disable fit to window.
7. Define X variable.
8. Define Group X variable.
9. Define Color variable.
10. Add Mosaic element.

Example 1609

Summary: Creates a nested variability chart using Graph Builder, with X and Y variables defined and page variable set to display standard deviation charts.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 662, 465 ),
    Show Control Panel( 0 ),
    Show Legend( 0 ),
    Variables( X( :Tire ), Y( :Y ), Page( :Characteristic, Levels per Row( 2 ) ) ),
    Elements( Mosaic( X, Y, Legend( 16 ) ) )
);

Code Explanation:

1. Open data table;
2. Create Graph Builder object.
3. Set graph size.
4. Hide control panel.
5. Hide legend.
6. Define X variable.
7. Define Y variable.
8. Define page variable.
9. Set levels per row.
10. Add mosaic element.

Example 1610

Summary: Creates a mosaic chart with nested factors using Graph Builder, displaying standard deviation charts and adjusting the X title wrap.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 119, 220 ),
    Show Control Panel( 0 ),
    Include Missing Categories( 1 ),
    Variables( Y( :sex ), Y( :age, Position( 1 ) ) ),
    Elements( Mosaic( Y( 1 ), Y( 2 ), Legend( 6 ) ) ),
    SendToReport( Dispatch( {}, "X title", TextEditBox, {Set Wrap( 2 )} ) )
);

Code Explanation:

1. Open data table;
2. Create Graph Builder window.
3. Set window size.
4. Hide control panel.
5. Include missing categories.
6. Assign variables to axes.
7. Add mosaic element.
8. Set legend position.
9. Adjust X title wrap.
10. Display graph.

Example 1611

Summary: Creates a mosaic chart with nested factors using Graph Builder, displaying standard deviation charts and configuring scale settings for the age variable.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 534, 450 ),
    Show Control Panel( 0 ),
    Variables( X( :age ), Y( :sex ) ),
    Elements( Mosaic( X, Y, Legend( 5 ) ) ),
    SendToReport(
        Dispatch( {}, "age", ScaleBox, {Min( 0.549682875264271 ), Max( 1.54968287526427 ), Inc( 1 ), Minor Ticks( 0 )} ),
        Dispatch( {}, "Graph Builder", FrameBox,
            Add Pin Annotation(
                Seg( MosaicSeg( 1 ) ),
                Index( {3, 1} ),
                Index Row( {3, 1} ),
                UniqueID( -860847561 ),
                FoundPt( {453, 299} ),
                Origin( {0.79492600422833, 0.551020408163265} ),
                RightOfCenter( 0 ),
                Tag Line( 1 )
            )
        )
    )
);

Code Explanation:

1. Open data table;
2. Launch Graph Builder.
3. Set graph size.
4. Hide control panel.
5. Assign variables to axes.
6. Add mosaic element.
7. Adjust age scale minimum.
8. Adjust age scale maximum.
9. Set age scale increment.
10. Disable minor ticks on age scale.

Example 1612

Summary: Creates a mosaic plot with nested factors using Graph Builder, displaying standard deviation charts and customizing report settings.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 670, 471 ),
    Show Control Panel( 0 ),
    Variables( X( :height ), Y( :weight ) ),
    Elements( Mosaic( X, Y, Legend( 4 ) ) ),
    SendToReport(
        Dispatch( {}, "height", ScaleBox, {Scale( "Log" ), Format( "Best", 12 ), Min( 0.001 ), Max( 1 ), Inc( 1 ), Minor Ticks( 1 )} )
    )
);

Code Explanation:

1. Open data table;
2. Launch Graph Builder.
3. Set graph size.
4. Hide control panel.
5. Assign variables to axes.
6. Add mosaic element.
7. Customize report settings.
8. Apply log scale to X-axis.
9. Format X-axis display.
10. Set axis limits and increments.

Example 1613

Summary: Creates a variability chart with nested factors using Graph Builder, displaying mosaic and points plots for age, sex, and height.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 534, 450 ),
    Show Control Panel( 0 ),
    Variables( X( :age ), Y( :sex ), Y( :height ) ),
    Elements( Position( 1, 1 ), Mosaic( X, Y, Legend( 9 ) ) ),
    Elements( Position( 1, 2 ), Points( X, Y, Legend( 7 ) ) )
);

Code Explanation:

1. Open data_table data
2. Launch Graph Builder.
3. Set window size to 534x450.
4. Hide control panel.
5. Assign age to X axis.
6. Assign sex to first Y axis.
7. Assign height to second Y axis.
8. Add mosaic plot at position 1,1.
9. Add legend for mosaic at 9.
10. Add points plot at position 1,2.

Example 1614

Summary: Creates two Graph Builder windows to visualize nested factors using mosaic and points elements, with standard deviation charts displayed.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 534, 450 ),
    Show Control Panel( 0 ),
    Variables( X( :age ), Y( :sex ), Y( :height ) ),
    Elements( Position( 1, 1 ), Mosaic( X, Y, Legend( 9 ) ) ),
    Elements( Position( 1, 2 ), Points( X, Y, Legend( 7 ) ) )
);
Graph Builder(
    Size( 534, 450 ),
    Show Control Panel( 0 ),
    Variables( X( :age ), Y( :sex ), Y( :height ) ),
    Elements( Position( 1, 1 ), Points( X, Y, Legend( 10 ) ) ),
    Elements( Position( 1, 2 ), Mosaic( X, Y, Legend( 11 ) ) )
);

Code Explanation:

1. Open data table.
2. Create first Graph Builder window.
3. Set window size.
4. Hide control panel.
5. Define variables: age, sex, height.
6. Add mosaic element at position 1,1.
7. Add points element at position 1,2.
8. Create second Graph Builder window.
9. Set window size.
10. Hide control panel.

Example 1615

Summary: Creates a variability chart with nested factors using operator and part configurations, displaying standard deviation charts in Graph Builder.

Code:

Open("data_table.jmp");
Graph Builder( Size( 534, 446 ), Show Control Panel( 0 ), Variables( X( :Age ), Y( :Grade ) ), Elements( Mosaic( X, Y, Legend( 12 ) ) ) );

Code Explanation:

1. Open data table;
2. Launch Graph Builder.
3. Set window size.
4. Hide control panel.
5. Assign X variable.
6. Assign Y variable.
7. Add mosaic element.
8. Enable legend.

Example 1616

Summary: Creates a nested variability chart with multiple Y axes, utilizing Graph Builder to visualize relationships between Age, Grade, and Gender.

Code:

Open("data_table.jmp");
Graph Builder( Size( 534, 446 ), Show Control Panel( 0 ), Variables( X( :Age ), Y( :Grade ) ), Elements( Mosaic( X, Y, Legend( 12 ) ) ) );
Open("data_table.jmp");
Graph Builder(
    Size( 534, 446 ),
    Show Control Panel( 0 ),
    Variables( X( :Age ), Y( :Grade ), Y( :Age, Position( 1 ) ), Y( :Gender, Position( 1 ) ) ),
    Elements( Mosaic( X, Y( 3 ), Y( 2 ), Y( 1 ), Legend( 12 ) ) )
);

Code Explanation:

1. Open data table.
2. Create Graph Builder window.
3. Set graph size to 534x446.
4. Hide control panel.
5. Assign Age to X axis.
6. Assign Grade to Y axis.
7. Add Mosaic element.
8. Display legend at position 12.
9. Open sample data table again.
10. Create another Graph Builder window with multiple Y axes.

Example 1617

Summary: Creates a mosaic chart with nested factors using Graph Builder, displaying standard deviation charts and configuring legend settings.

Code:

Open("data_table.jmp");
Graph Builder( Size( 534, 446 ), Show Control Panel( 0 ), Variables( X( :Age ), Y( :Grade ) ), Elements( Mosaic( X, Y, Legend( 12 ) ) ) );
Open("data_table.jmp");

Code Explanation:

1. Open data table.
2. Create Graph Builder window.
3. Set window size.
4. Hide control panel.
5. Define X variable.
6. Define Y variable.
7. Add mosaic element.
8. Configure legend.
9. Open data table.

Example 1618

Summary: Creates a nested mosaic plot with sex and age variables, allowing for interactive exploration of data distribution across multiple scales.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 649, 400 ),
    Show Control Panel( 0 ),
    Variables( X( :sex ), Y( :age ) ),
    Elements( Mosaic( X, Y, Legend( 4 ), Response Axis( "X" ) ) )
);
Graph Builder(
    Size( 649, 400 ),
    Show Control Panel( 0 ),
    Variables( X( :sex ), Y( :age ) ),
    Elements( Mosaic( X, Y, Legend( 4 ), Response Axis( "X" ) ) ),
    SendToReport( Dispatch( {}, "age", ScaleBox, {Reversed Scale} ) )
);
Graph Builder(
    Size( 649, 400 ),
    Show Control Panel( 0 ),
    Variables( X( :sex ), Y( :age ) ),
    Elements( Mosaic( X, Y, Legend( 4 ), Response Axis( "X" ) ) ),
    SendToReport( Dispatch( {}, "sex", ScaleBox, {Reversed Scale} ) )
);
Graph Builder(
    Size( 649, 400 ),
    Show Control Panel( 0 ),
    Variables( X( :sex ), Y( :age ) ),
    Elements( Mosaic( X, Y, Legend( 4 ), Response Axis( "X" ) ) ),
    SendToReport( Dispatch( {}, "sex", ScaleBox, {Reversed Scale} ), Dispatch( {}, "age", ScaleBox, {Reversed Scale} ) )
);
Graph Builder(
    Size( 649, 400 ),
    Show Control Panel( 0 ),
    Variables( X( :sex ), Y( :age ) ),
    Elements( Mosaic( X, Y, Legend( 4 ), Response Axis( "Y" ) ) )
);
Graph Builder(
    Size( 649, 400 ),
    Show Control Panel( 0 ),
    Variables( X( :sex ), Y( :age ) ),
    Elements( Mosaic( X, Y, Legend( 4 ), Response Axis( "Y" ) ) ),
    SendToReport( Dispatch( {}, "age", ScaleBox, {Reversed Scale} ) )
);
Graph Builder(
    Size( 649, 400 ),
    Show Control Panel( 0 ),
    Variables( X( :sex ), Y( :age ) ),
    Elements( Mosaic( X, Y, Legend( 4 ), Response Axis( "Y" ) ) ),
    SendToReport( Dispatch( {}, "sex", ScaleBox, {Reversed Scale} ) )
);
Graph Builder(
    Size( 649, 400 ),
    Show Control Panel( 0 ),
    Variables( X( :sex ), Y( :age ) ),
    Elements( Mosaic( X, Y, Legend( 4 ), Response Axis( "Y" ) ) ),
    SendToReport( Dispatch( {}, "sex", ScaleBox, {Reversed Scale} ), Dispatch( {}, "age", ScaleBox, {Reversed Scale} ) )
);

Code Explanation:

1. Open data table;
2. Create mosaic plot with sex on X, age on Y.
3. Repeat step 2.
4. Reverse scale for age axis.
5. Repeat step 2.
6. Reverse scale for sex axis.
7. Repeat step 2.
8. Reverse scales for both axes.
9. Repeat step 2.
10. Set response axis to Y.
11. Repeat step 9.
12. Reverse scale for age axis.
13. Repeat step 9.
14. Reverse scale for sex axis.
15. Repeat step 9.
16. Reverse scales for both axes.

Example 1619

Summary: Creates a variability chart with nested factors using operator and part configurations, displaying standard deviation charts in Graph Builder.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 616, 466 ),
    Show Control Panel( 0 ),
    Show Legend( 0 ),
    Variables( X( :age ), X( :sex ), Y( :height ) ),
    Elements( Position( 1, 1 ), Mosaic( X, Y, Legend( 13 ) ) ),
    Elements( Position( 2, 1 ), Mosaic( X, Y, Legend( 14 ) ) ),
    SendToReport( Dispatch( {}, "400", ScaleBox, {Legend Model( 14, Base( 0, 0, 0 ), Properties( 0, {Fill Color( 14 )} ) )} ) )
);

Code Explanation:

1. Open data table;
2. Launch Graph Builder.
3. Set window size.
4. Hide control panel.
5. Hide legend.
6. Define variables: age, sex, height.
7. Add first mosaic element.
8. Add second mosaic element.
9. Customize second mosaic legend.
10. Send report to display.

Example 1620

Summary: Creates a nested factors variability chart using Graph Builder, with interactive features for exploring data relationships.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 711, 508 ),
    Show Control Panel( 0 ),
    Variables( X( :Name( "Subject Reference Start Date/Time" ) ) ),
    Elements( Mosaic( X, Legend( 11 ) ) )
);

Code Explanation:

1. Open data table;
2. Launch Graph Builder.
3. Set window size.
4. Hide control panel.
5. Define X variable.
6. Add Mosaic element.
7. Assign legend.

Example 1621

Summary: Creates two Graph Builder windows to visualize nested factors using chi-square tests, with interactive elements for exploring relationships between Age, Grade, and Gender.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 534, 446 ),
    Show Control Panel( 0 ),
    Variables( X( :Age ), Y( :Grade ), Y( :Age, Position( 1 ) ), Y( :Gender, Position( 1 ) ) ),
    Elements( Mosaic( X, Y( 3 ), Y( 2 ), Y( 1 ), Legend( 12 ), Name( "Chi-square Test" )(1) ) )
);
Graph Builder(
    Size( 534, 446 ),
    Show Control Panel( 0 ),
    Variables( X( :Age ), Y( :Grade ) ),
    Elements( Mosaic( X, Y, Legend( 12 ), Name( "Chi-square Test" )(1) ) )
);

Code Explanation:

1. Open data table.
2. Create first Graph Builder window.
3. Set window size to 534x446.
4. Hide control panel.
5. Assign variables for mosaic plot.
6. Add mosaic element with chi-square test.
7. Create second Graph Builder window.
8. Set window size to 534x446.
9. Hide control panel.
10. Assign variables for mosaic plot.

Example 1622

Summary: Creates a variability chart with nested factors using Graph Builder, displaying standard deviation charts and performing a Chi-square test.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 534, 446 ),
    Show Control Panel( 0 ),
    Variables( X( :Age ), Y( :Grade ), Y( :Age, Position( 1 ) ), Y( :Gender, Position( 1 ) ) ),
    Elements( Mosaic( X, Y( 3 ), Y( 2 ), Y( 1 ), Legend( 12 ), Name( "Chi-square Test" )(1) ) )
);

Code Explanation:

1. Open data table.
2. Launch Graph Builder.
3. Set window size.
4. Hide control panel.
5. Assign variables: X(Age), Y(Grade), Y(Age), Y(Gender).
6. Position Age on Y-axis twice.
7. Add Mosaic element.
8. Specify X, Y3, Y2, Y1.
9. Enable legend.
10. Perform Chi-square test.

Example 1623

Summary: Creates a mosaic chart with nested factors using Graph Builder, displaying standard deviation charts and enabling chi-square test analysis.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 534, 446 ),
    Show Control Panel( 0 ),
    Variables( X( :Age ), Y( :Grade ) ),
    Elements( Mosaic( X, Y, Legend( 12 ), Name( "Chi-square Test" )(1) ) )
);

Code Explanation:

1. Open data table.
2. Create Graph Builder window.
3. Set window size.
4. Hide control panel.
5. Define X variable.
6. Define Y variable.
7. Add mosaic element.
8. Include legend.
9. Enable chi-square test.
10. Display graph.

Example 1624

Summary: Creates three Graph Builder windows with varying configurations to visualize relationships between Age, Grade, and Gender.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 534, 446 ),
    Show Control Panel( 0 ),
    Variables( X( :Age ), Y( :Grade ), Y( :Age, Position( 1 ) ), Y( :Gender, Position( 1 ) ) ),
    Elements( Mosaic( X, Y( 3 ), Y( 2 ), Y( 1 ), Legend( 12 ), Name( "Chi-square Test" )(1) ) )
);
Open("data_table.jmp");
Graph Builder(
    Size( 534, 446 ),
    Show Control Panel( 0 ),
    Variables( X( :Age ), Y( :Grade ) ),
    Elements( Mosaic( X, Y, Legend( 12 ), Name( "Chi-square Test" )(1) ) )
);
Open("data_table.jmp");
Graph Builder(
    Size( 534, 448 ),
    Show Control Panel( 0 ),
    Variables( X( :age ), Y( :height ) ),
    Elements( Mosaic( X, Y, Legend( 4 ), Name( "Chi-square Test" )(1) ) )
);

Code Explanation:

1. Open data table;
2. Create Graph Builder window.
3. Set window size 534x446.
4. Hide control panel.
5. Define variables X: Age, Y: Grade, Y: Age, Y: Gender.
6. Add mosaic element with chi-square test.
7. Open data table;
8. Create Graph Builder window.
9. Set window size 534x446.
10. Hide control panel.
11. Define variables X: Age, Y: Grade.
12. Add mosaic element with chi-square test.
13. Open data table;
14. Create Graph Builder window.
15. Set window size 534x448.
16. Hide control panel.
17. Define variables X: age, Y: height.
18. Add mosaic element with chi-square test.

Example 1625

Summary: Creates two Graph Builder windows with Mosaic elements to visualize relationships between Age, Grade, and Gender, performing Chi-square tests on nested factors.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 534, 446 ),
    Show Control Panel( 0 ),
    Variables( X( :Age ), Y( :Grade ), Y( :Age, Position( 1 ) ), Y( :Gender, Position( 1 ) ) ),
    Elements( Mosaic( X, Y( 3 ), Y( 2 ), Y( 1 ), Legend( 12 ), Name( "Chi-square Test" )(1) ) )
);
Open("data_table.jmp");
Graph Builder(
    Size( 534, 446 ),
    Show Control Panel( 0 ),
    Variables( X( :Age ), Y( :Grade ) ),
    Elements( Mosaic( X, Y, Legend( 12 ), Name( "Chi-square Test" )(1) ) )
);
Open("data_table.jmp");

Code Explanation:

1. Open data table;
2. Create Graph Builder window.
3. Set window size.
4. Hide control panel.
5. Assign variables: Age, Grade, Age, Gender.
6. Add Mosaic element.
7. Perform Chi-square test.
8. Open data table;
9. Create another Graph Builder window.
10. Set window size.
11. Hide control panel.
12. Assign variables: Age, Grade.
13. Add Mosaic element.
14. Perform Chi-square test.
15. Open data table;

Example 1626

Summary: Creates a variability chart with nested factors using Graph Builder, displaying standard deviation charts and customizing legend properties.

Code:

Open("data_table.jmp") << Graph Builder(
    Size( 616, 466 ),
    Show Control Panel( 0 ),
    Show Legend( 0 ),
    Variables( X( :age ), X( :sex ), Y( :height ) ),
    Elements( Position( 1, 1 ), Mosaic( X, Y, Legend( 13 ) ) ),
    Elements( Position( 2, 1 ), Mosaic( X, Y, Legend( 14 ) ) ),
    SendToReport( Dispatch( {}, "400", ScaleBox, {Legend Model( 14, Base( 0, 0, 0 ), Properties( 0, {Fill Color( 14 )} ) )} ) )
);

Code Explanation:

1. Open data table;
2. Initialize Graph Builder.
3. Set window size.
4. Hide control panel.
5. Hide legend.
6. Define X variables.
7. Define Y variable.
8. Add first mosaic element.
9. Add second mosaic element.
10. Customize legend properties.

Example 1627

Summary: Creates a mosaic chart with nested factors using Graph Builder, displaying standard deviation charts and configuring the X-axis.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 606, 554 ),
    Variables( X( :Grades ), X( :Name( "Urban/Rural" ), Position( 1 ) ), Y( :Goals ) ),
    Elements( Mosaic( X( 2 ), Legend( 6 ) ) ),
    SendToReport( Dispatch( {"Mosaic"}, "", OutlineBox, {Close( 0 )} ) )
);

Code Explanation:

1. Open data table.
2. Launch Graph Builder.
3. Set window size.
4. Define X variables.
5. Define Y variable.
6. Add Mosaic element.
7. Configure Mosaic X axis.
8. Add legend.
9. Close outline box.
10. Display report.

Example 1628

Summary: Creates a mosaic plot to visualize relationships between Age, Grade, and Gender using Graph Builder.

Code:

Open("data_table.jmp");
Graph Builder(
    Variables( X( :Age ), Y( :Grade ), Y( :Age, Position( 1 ) ), Y( :Gender, Position( 1 ) ) ),
    Elements( Mosaic( X, Y( 2 ), Y( 1 ), Y( 3 ), Legend( 12 ) ) ),
    SendToReport( Dispatch( {"Mosaic"}, "", OutlineBox, {Close( 0 )} ) )
);

Code Explanation:

1. Open data table.
2. Launch Graph Builder.
3. Set X variable: Age.
4. Set Y variables: Grade, Age, Gender.
5. Configure mosaic plot elements.
6. Position Age on Y axis.
7. Position Gender on Y axis.
8. Display legend.
9. Close outline box.
10. Generate mosaic graph.

Example 1629

Summary: Creates a nested variability chart using Graph Builder, with interactive elements for exploring relationships between Age, Grade, and Gender.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 534, 446 ),
    Show Control Panel( 0 ),
    Variables( X( :Age ), Y( :Grade ), Y( :Age, Position( 1 ) ), Y( :Gender, Position( 1 ) ) ),
    Elements( Mosaic( X, Y( 3 ), Y( 2 ), Y( 1 ), Legend( 12 ) ) )
);

Code Explanation:

1. Open data table;
2. Create new graph builder window.
3. Set graph size.
4. Hide control panel.
5. Define X variable.
6. Define first Y variable.
7. Define second Y variable.
8. Define third Y variable.
9. Add mosaic element.
10. Configure mosaic variables.

Example 1630

Summary: Creates a mosaic chart with nested factors using Graph Builder, displaying standard deviation charts and configuring window size.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 606, 554 ),
    Variables( X( :Name( "Urban/Rural" ) ), Y( :Goals ), Y( :School, Position( 1 ) ) ),
    Elements( Mosaic( X, Y( 1 ), Legend( 6 ) ) ),
    SendToReport( Dispatch( {"Mosaic"}, "", OutlineBox, {Close( 0 )} ) )
);

Code Explanation:

1. Open data table;
2. Launch Graph Builder.
3. Set window size.
4. Define X variable.
5. Define first Y variable.
6. Define second Y variable.
7. Add Mosaic element.
8. Position School on Y-axis.
9. Close legend outline box.

Example 1631

Summary: Creates a variability chart with nested factors using Graph Builder, displaying standard deviation charts and customizing graph titles and legend labels.

Code:

Open("data_table.jmp") << Graph Builder(
    Size( 281, 195 ),
    Show Control Panel( 0 ),
    Variables( X( :Treatment ), Y( :Lower 95% ), Y( :Upper 95%, Position( 1 ) ), Y( :Mean, Position( 1 ) ), Overlay( :Sex ) ),
    Elements( Mosaic( X, Y( 2 ), Y( 3 ), Legend( 13 ) ) ),
    SendToReport(
        Dispatch( {}, "graph title", TextEditBox, {Set Text( "Comparing 95%
Confidence Intervals" )} ),
        Dispatch( {}, "Y title", TextEditBox, {Set Text( "Measure" )} ),
        Dispatch( {}, "400", LegendBox, {Set Title( "Upper 95%" )} )
    )
);

Code Explanation:

1. Open data table;
2. Launch Graph Builder.
3. Set graph size.
4. Hide control panel.
5. Define variables for axes.
6. Add mosaic element.
7. Customize graph title.
8. Customize Y-axis title.
9. Rename legend title.
10. Display graph.

Example 1632

Summary: Creates a nested variability chart using Graph Builder, with customization options for legend and pin annotation.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 487, 331 ),
    Show Control Panel( 0 ),
    Variables( X( :Relapsed ), Frequency( :Count ) ),
    Elements( Mosaic( X, Frequency( 0 ), Legend( 22 ) ) ),
    SendToReport(
        Dispatch( {"Mosaic"}, "", OutlineBox, {Close( 0 )} ),
        Dispatch( {}, "Graph Builder", FrameBox,
            Add Pin Annotation(
                Seg( MosaicSeg( 1 ) ),
                Index( {0, 1} ),
                Index Row( {0, 1} ),
                UniqueID( 987155409 ),
                FoundPt( {687, 376} ),
                Origin( {0.756539235412475, 0.462845010615711} )
            )
        )
    )
);

Code Explanation:

1. Open data table;
2. Launch Graph Builder.
3. Set graph size.
4. Hide control panel.
5. Define variables for X and frequency.
6. Add mosaic element.
7. Customize legend.
8. Close outline box.
9. Add pin annotation.
10. Specify segment and indices.

Example 1633

Summary: Creates a mosaic plot with nested factors using Graph Builder, displaying the relationship between Development Level and Average Years of Education of Adults.

Code:

dt = Open("data_table.jmp");
dt << Graph Builder(
    Size( 431, 334 ),
    Show Control Panel( 0 ),
    Show Legend( 0 ),
    Variables( X( :Development Level ), Y( :Average Years of Education of Adults ) ),
    Elements( Mosaic( X, Y, Legend( 10 ) ) )
);

Code Explanation:

1. Open table.
2. Set graph size.
3. Hide control panel.
4. Hide legend.
5. Define X variable.
6. Define Y variable.
7. Create mosaic plot.
8. Set legend position.

Example 1634

Summary: Creates a mosaic plot with nested factors using Graph Builder, filtering data to include only male subjects.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 411, 330 ),
    Show Control Panel( 0 ),
    Show Legend( 0 ),
    Variables( X( :age ), Y( :height ) ),
    Elements( Mosaic( X, Y, Legend( 25 ) ) ),
    Local Data Filter( Mode( Include( 0 ) ), Add Filter( columns( :sex ), Where( :sex == "M" ) ) )
);

Code Explanation:

1. Open data table;
2. Create Graph Builder window.
3. Set window size.
4. Hide control panel.
5. Hide legend.
6. Define X variable.
7. Define Y variable.
8. Add Mosaic element.
9. Set legend position.
10. Apply local data filter.

Example 1635

Summary: Creates a variability chart with nested factors using Graph Builder, configuring smoother elements for X and Y variables.

Code:

dt = Open("data_table.jmp");
gb = dt << Graph Builder( Variables( X( :Age ), Y( :Height ), Page( :Sex ) ), Elements( Smoother( X, Y ) ) );

Code Explanation:

1. Open data table;
2. Create new Graph Builder object.
3. Set X variable to :Age.
4. Set Y variable to :Height.
5. Add :Sex to Page role.
6. Add Smoother element to graph.
7. Configure smoother for X and Y variables.

Example 1636

Summary: Creates a variability chart with nested factors using Graph Builder, setting X to Age, Y to Height, and Sex for page layout, while applying a smoother element and page level fill color.

Code:

dt = Open("data_table.jmp");
gb = dt << Graph Builder( Variables( X( :Age ), Y( :Height ), Page( :Sex ) ), Elements( Smoother( X, Y ) ) );
gb << Page Level Fill Color( {103, 214, 214} );

Code Explanation:

1. Open data table.
2. Create Graph Builder object.
3. Set X variable to Age.
4. Set Y variable to Height.
5. Use Sex for page layout.
6. Add smoother element.
7. Apply page level fill color.

Example 1637

Summary: Creates a graph builder with nested factors using operator and part configurations, displaying standard deviation charts.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 745, 534 ),
    Show Control Panel( 0 ),
    Variables(
        X( :height, Combine( "Parallel Merged" ) ),
        X( :weight, Position( 1 ), Combine( "Parallel Merged" ) ),
        Overlay( :age ),
        Size( :age )
    ),
    Elements( Points( X( 1 ), X( 2 ), Legend( 3 ) ) )
);

Code Explanation:

1. Open data table;
2. Launch Graph Builder.
3. Set window size.
4. Hide control panel.
5. Define X variables.
6. Merge X variables.
7. Overlay age variable.
8. Size points by age.
9. Add point element.
10. Plot graph.

Example 1638

Summary: Creates a variability chart with nested factors using Graph Builder, displaying standard deviation charts and configuring axis variables.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 495, 448 ),
    Show Control Panel( 0 ),
    Variables( X( :sex ), X( :height, Position( 1 ) ), X( :weight, Position( 1 ) ), Frequency( :age ) ),
    Elements( Parallel( X( 1 ), X( 2 ), X( 3 ), Legend( 12 ) ) )
);

Code Explanation:

1. Open data table;
2. Launch Graph Builder.
3. Set window size.
4. Hide control panel.
5. Define variables for X, Y, and frequency.
6. Create parallel plot element.
7. Assign variables to axes.
8. Add legend to plot.
9. Display graph.

Example 1639

Summary: Creates multiple graphs in Graph Builder to visualize relationships between height, weight, and age using parallel merged and independent modes, with error intervals and band styles.

Code:

Open("data_table.jmp");
Graph Builder(
    Show Control Panel( 0 ),
    Variables( X( :height, Combine( "Parallel Merged" ) ), X( :weight, Position( 1 ), Combine( "Parallel Merged" ) ) ),
    Elements( Line( X( 1 ), X( 2 ), Legend( 5 ), Error Interval( "Range" ) ) )
);
Graph Builder(
    Show Control Panel( 0 ),
    Variables( X( :height, Combine( "Parallel Independent" ) ), X( :weight, Position( 1 ), Combine( "Parallel Independent" ) ) ),
    Elements( Line( X( 1 ), X( 2 ), Legend( 5 ), Error Interval( "Range" ) ) )
);
Graph Builder(
    Show Control Panel( 0 ),
    Variables( X( :height, Combine( "Parallel Merged" ) ), X( :weight, Position( 1 ), Combine( "Parallel Merged" ) ) ),
    Elements( Line( X( 1 ), X( 2 ), Legend( 5 ), Error Interval( "Range" ), Interval Style( "Band" ) ) )
);
Graph Builder(
    Show Control Panel( 0 ),
    Variables( X( :height, Combine( "Parallel Independent" ) ), X( :weight, Position( 1 ), Combine( "Parallel Independent" ) ) ),
    Elements( Line( X( 1 ), X( 2 ), Legend( 5 ), Error Interval( "Range" ), Interval Style( "Band" ) ) )
);
Graph Builder(
    Show Control Panel( 0 ),
    Variables( X( :height, Combine( "Parallel Merged" ) ), X( :weight, Position( 1 ), Combine( "Parallel Merged" ) ), Overlay( :age ) ),
    Elements( Line( X( 1 ), X( 2 ), Legend( 5 ), Error Interval( "Range" ) ) )
);
Graph Builder(
    Show Control Panel( 0 ),
    Variables(
        X( :height, Combine( "Parallel Independent" ) ),
        X( :weight, Position( 1 ), Combine( "Parallel Independent" ) ),
        Overlay( :age )
    ),
    Elements( Line( X( 1 ), X( 2 ), Legend( 5 ), Error Interval( "Range" ) ) )
);
Graph Builder(
    Show Control Panel( 0 ),
    Variables( X( :height, Combine( "Parallel Merged" ) ), X( :weight, Position( 1 ), Combine( "Parallel Merged" ) ), Overlay( :age ) ),
    Elements( Line( X( 1 ), X( 2 ), Legend( 5 ), Error Interval( "Range" ), Interval Style( "Band" ) ) )
);

Code Explanation:

1. Open data table;
2. Create first graph builder window.
3. Hide control panel.
4. Set X variables: height and weight.
5. Combine X variables in parallel merged mode.
6. Add line element with error interval.
7. Create second graph builder window.
8. Hide control panel.
9. Set X variables: height and weight.
10. Combine X variables in parallel independent mode.
11. Add line element with error interval.
12. Create third graph builder window.
13. Hide control panel.
14. Set X variables: height and weight.
15. Combine X variables in parallel merged mode.
16. Add line element with error interval and band style.
17. Create fourth graph builder window.
18. Hide control panel.
19. Set X variables: height and weight.
20. Combine X variables in parallel independent mode.
21. Add line element with error interval and band style.
22. Create fifth graph builder window.
23. Hide control panel.
24. Set X variables: height, weight, and overlay age.
25. Combine X variables in parallel merged mode.
26. Add line element with error interval.
27. Create sixth graph builder window.
28. Hide control panel.
29. Set X variables: height, weight, and overlay age.
30. Combine X variables in parallel independent mode.
31. Add line element with error interval.
32. Create seventh graph builder window.
33. Hide control panel.
34. Set X variables: height, weight, and overlay age.
35. Combine X variables in parallel merged mode.
36. Add line element with error interval and band style.

Example 1640

Summary: Creates a variability chart with nested factors using Graph Builder, configuring X variables and overlaying age data.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 495, 464 ),
    Show Control Panel( 0 ),
    Variables( X( :sports ), X( :countries visited, Position( 1 ) ), Overlay( :age ) ),
    Elements( Parallel( X( 1 ), X( 2 ), Legend( 5 ) ) )
);

Code Explanation:

1. Open data table.
2. Launch Graph Builder.
3. Set window size.
4. Hide control panel.
5. Define X variables.
6. Define overlay variable.
7. Add parallel plot element.
8. Position first X variable.
9. Position second X variable.
10. Configure legend.

Example 1641

Summary: Creates a variability chart with nested factors using Graph Builder, displaying standard deviation charts and utilizing size variation by sex.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 495, 500 ),
    Show Control Panel( 0 ),
    Variables( X( :height ), X( :age, Position( 1 ) ), Group X( :sex ), Size( :sex ) ),
    Elements( Parallel( X( 1 ), X( 2 ), Legend( 7 ) ) )
);

Code Explanation:

1. Open data table.
2. Create new Graph Builder window.
3. Set window size to 495x500.
4. Hide control panel.
5. Assign variables: height, age, sex.
6. Set age as first X variable.
7. Group by sex.
8. Use sex for size variation.
9. Add parallel element.
10. Display graph.

Example 1642

Summary: Creates a parallel plot with nested factors using Graph Builder, displaying sex, height, and weight for 'LAWRENCE' data.

Code:

dt = Open("data_table.jmp");
dt << select where( :name == "LAWRENCE" );
Graph Builder(
    Size( 495, 450 ),
    Show Control Panel( 0 ),
    Variables( X( :sex ), X( :height, Position( 1 ) ), X( :weight, Position( 1 ) ) ),
    Elements( Parallel( X( 1 ), X( 2 ), X( 3 ), Legend( 3 ) ) ),
    SendToReport(
        Dispatch( {}, "400", ScaleBox, {Legend Model( 3, Properties( 0, {Line Width( 3 )}, Item ID( "Count", 1 ) ) )} ),
        Dispatch( {}, "Graph Builder", FrameBox, {Background Color( 0 )} )
    )
);

Code Explanation:

1. Open data table;
2. Select rows where name is "LAWRENCE".
3. Launch Graph Builder.
4. Set window size to 495x450.
5. Hide control panel.
6. Add sex to X axis.
7. Add height to X axis position 1.
8. Add weight to X axis position 1.
9. Add parallel plot element.
10. Customize legend and background color.

Example 1643

Summary: Creates a variability chart with nested factors using Graph Builder, displaying standard deviation charts and reversing age axes in multiple frames.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 561, 507 ),
    Show Control Panel( 0 ),
    Variables( X( :name ), X( :age, Position( 1 ) ), Group X( :sex ) ),
    Elements( Parallel( X( 1 ), X( 2 ), Legend( 5 ) ) ),
    SendToReport(
        Dispatch( {}, "Graph Builder", FrameBox, {DispatchSeg( ParallelAxisSeg( 1 ), Reversed( age ) )} ),
        Dispatch( {}, "Graph Builder", FrameBox( 2 ), {DispatchSeg( ParallelAxisSeg( 1 ), Reversed( age ) )} )
    )
);

Code Explanation:

1. Open data table.
2. Create Graph Builder window.
3. Set window size.
4. Hide control panel.
5. Define variables for graph.
6. Add parallel plot elements.
7. Reverse age axis in first frame.
8. Reverse age axis in second frame.

Example 1644

Summary: Creates a variability chart with nested factors using Graph Builder, displaying standard deviation charts and configuring X variables for age, sex, height, and weight.

Code:

dt = Open("data_table.jmp");
dt << select where( :name == "JEFFREY" );
Graph Builder(
    Size( 703, 484 ),
    Show Control Panel( 0 ),
    Variables( X( :age ), X( :sex, Position( 1 ) ), X( :height, Position( 1 ) ), Group X( :weight ) ),
    Elements( Parallel( X( 1 ), X( 2 ), X( 3 ), Legend( 3 ) ) )
);

Code Explanation:

1. Open data table.
2. Select rows where name is "JEFFREY".
3. Launch Graph Builder.
4. Set graph size.
5. Hide control panel.
6. Define X variables: age, sex, height.
7. Define group X variable: weight.
8. Add parallel element.
9. Set X positions for elements.
10. Display legend for third element.

Example 1645

Summary: Creates a variability chart with nested factors using Graph Builder, assigning variables to axes and customizing legend properties.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 422, 488 ),
    Show Control Panel( 0 ),
    Variables( X( :age ), X( :height, Position( 1 ) ), Color( :sex ), Size( :height ) ),
    Elements( Parallel( X( 1 ), X( 2 ), Legend( 5 ) ) ),
    SendToReport(
        Dispatch( {}, "400", ScaleBox,
            {Legend Model(
                5,
                Type Properties( 0, "Line Size", {Marker Scale( {Marker Size Minimum( "Dot" )} )} ),
                Properties( 0, {Marker Scale( {Marker Size Minimum( "Dot" )} )}, Item ID( "height", 1 ) )
            )}
        )
    )
);

Code Explanation:

1. Open data table.
2. Create Graph Builder window.
3. Set graph size.
4. Hide control panel.
5. Assign variables to axes.
6. Add parallel plot element.
7. Customize legend properties.
8. Adjust marker scale minimum.
9. Set marker size to dot.
10. Send report settings.

Example 1646

Summary: Creates a variability chart with nested factors using Graph Builder, displaying standard deviation charts and customizing Y title text.

Code:

Open("data_table.jmp");
obj = Graph Builder(
    Size( 414, 305 ),
    Show Control Panel( 0 ),
    Variables( X( :Sepal length ), X( :Sepal width, Position( 1 ) ), X( :Petal length, Position( 1 ) ), X( :Petal width, Position( 1 ) ) ),
    Elements( Parallel( X( 1 ), X( 2 ), X( 3 ), X( 4 ), Legend( 3 ) ) ),
    SendToReport( Dispatch( {}, "Y title", TextEditBox, {Set Wrap( 2 )} ) )
);

Code Explanation:

1. Open data table;
2. Create Graph Builder object.
3. Set window size.
4. Hide control panel.
5. Define X variables.
6. Add parallel plot element.
7. Position elements.
8. Display legend.
9. Wrap Y title text.
10. Send report settings.

Example 1647

Summary: Creates a parallel plot with nested factors using Graph Builder, displaying standard deviation charts for age, sex, height, and weight.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 505, 367 ),
    Show Control Panel( 0 ),
    Variables( X( :age ), X( :sex, Position( 1 ) ), X( :height, Position( 1 ) ), X( :weight, Position( 1 ) ) ),
    Elements( Parallel( X( 2 ), X( 1 ), X( 3 ), X( 4 ), Legend( 3 ) ) )
);

Code Explanation:

1. Open data table.
2. Launch Graph Builder.
3. Set window size.
4. Hide control panel.
5. Define X variables.
6. Add sex variable.
7. Add height variable.
8. Add weight variable.
9. Create parallel plot.
10. Add legend.

Example 1648

Summary: Creates a variability chart with nested factors using operator and part configurations, displaying standard deviation charts.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 495, 386 ),
    Show Control Panel( 0 ),
    Variables( X( :hist0 ), X( :hist1, Position( 1 ) ), X( :hist3, Position( 1 ) ), X( :hist5, Position( 1 ) ) ),
    Elements( Parallel( X( 1 ), X( 2 ), X( 3 ), X( 4 ), Legend( 3 ), Curve Lines( 0 ) ) )
);

Code Explanation:

1. Open data table.
2. Launch Graph Builder.
3. Set window size.
4. Hide control panel.
5. Define X variables: hist0, hist1, hist3, hist5.
6. Position hist1, hist3, hist5 at 1.
7. Add parallel plot element.
8. Assign X variables to plot.
9. Show legend for curves.
10. Disable curve lines.

Example 1649

Summary: Creates a variability chart with nested factors using operator and part configurations, displaying standard deviation charts in Graph Builder.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 495, 386 ),
    Show Control Panel( 0 ),
    Variables( X( :hist0 ), X( :hist1, Position( 1 ) ), X( :hist3, Position( 1 ) ), X( :hist5, Position( 1 ) ) ),
    Elements( Parallel( X( 1 ), X( 2 ), X( 3 ), X( 4 ), Legend( 3 ), Reversed( 1 ), Curve Lines( 0 ) ) )
);

Code Explanation:

1. Open data_table data
2. Launch Graph Builder.
3. Set window size.
4. Hide control panel.
5. Define X variables.
6. Add parallel plot element.
7. Position variables.
8. Enable legend.
9. Reverse axis order.
10. Disable curve lines.

Example 1650

Summary: Creates a parallel plot with nested factors using Graph Builder, displaying age, sex, height, and weight variables.

Code:

Open("data_table.jmp");
:sex << set modeling type( "None" );
Graph Builder(
    Show Control Panel( 0 ),
    Variables( X( :age ), X( :sex, Position( 1 ) ), X( :height, Position( 1 ) ), X( :weight, Position( 1 ) ) ),
    Elements( Parallel( X( 1 ), X( 2 ), X( 3 ), X( 4 ), Legend( 3 ) ) )
);

Code Explanation:

1. Open data table.
2. Set sex modeling type to None.
3. Launch Graph Builder.
4. Hide control panel.
5. Define X variables: age, sex, height, weight.
6. Position sex at 1.
7. Position height at 1.
8. Position weight at 1.
9. Add parallel plot element.
10. Configure legend for parallel plot.

Example 1651

Summary: Creates a parallel plot with nested factors using Graph Builder, displaying age on the X-axis and sex as a secondary axis, colored by age.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 511, 488 ),
    Show Control Panel( 0 ),
    Variables( X( :age ), X( :sex, Position( 1 ) ), Color( :age ) ),
    Elements( Parallel( X( 1 ), X( 2 ), Legend( 8 ) ) )
);

Code Explanation:

1. Open data_table data
2. Launch Graph Builder.
3. Set window size.
4. Hide control panel.
5. Assign variables: age, sex, age.
6. Create parallel plot.
7. Place age on X-axis.
8. Place sex on X-axis.
9. Color by age.
10. Add legend.

Example 1652

Summary: Creates a graph builder with nested factors using operator and part configurations, displaying standard deviation charts.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 534, 450 ),
    Show Control Panel( 0 ),
    Variables( X( :height ), X( :weight, Position( 1 ) ), Overlay( :sex ), Color( :sex ) ),
    Elements( Parallel( X( 1 ), X( 2 ), Legend( 3 ) ), Line( X( 1 ), X( 2 ), Legend( 6 ) ), Points( X( 1 ), X( 2 ), Legend( 7 ) ) ),
    SendToReport(
        Dispatch( {}, "Graph Builder", OutlineBox, {Set Title( "Color and ovelay roles test" ), Image Export Display( Normal )} )
    )
);

Code Explanation:

1. Open data table.
2. Launch Graph Builder.
3. Set window size.
4. Hide control panel.
5. Define X variables.
6. Define overlay variable.
7. Define color variable.
8. Add parallel plot element.
9. Add line element.
10. Add points element.
11. Set graph title.
12. Enable image export.

Example 1653

Summary: Creates a Graph Builder object to visualize data with nested factors, utilizing variables and elements to generate a points plot with parallel lines.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 534, 450 ),
    Show Control Panel( 0 ),
    Variables( X( :height ), X( :weight, Position( 1 ) ), Overlay( :sex ) ),
    Elements( Points( X( 1 ), X( 2 ), Legend( 3 ) ), Parallel( X( 1 ), X( 2 ), Legend( 4 ) ) ),
    SendToReport(
        Dispatch( {}, "Graph Builder", OutlineBox,
            {Set Title( "Test to make sure lines and markers use the same color" ), Image Export Display( Normal )}
        )
    )
);

Code Explanation:

1. Open data table;
2. Create Graph Builder object.
3. Set window size.
4. Hide control panel.
5. Define X variables.
6. Define overlay variable.
7. Add points element.
8. Add parallel element.
9. Set graph title.
10. Enable image export.

Example 1654

Summary: Creates multiple Graph Builder windows with varying variables and elements to visualize data, including points, parallel lines, and box plots.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 534, 450 ),
    Show Control Panel( 0 ),
    Variables( X( :height ), X( :weight, Position( 1 ) ), Overlay( :sex ) ),
    Elements( Points( X( 1 ), X( 2 ), Legend( 3 ) ), Parallel( X( 1 ), X( 2 ), Legend( 4 ) ) ),
    SendToReport(
        Dispatch( {}, "Graph Builder", OutlineBox,
            {Set Title( "Test to make sure lines and markers use the same color" ), Image Export Display( Normal )}
        )
    )
);
Open("data_table.jmp");
Graph Builder(
    Variables(
        X( :Sepal length ),
        X( :Sepal width, Position( 1 ) ),
        X( :Petal length, Position( 1 ) ),
        X( :Petal width, Position( 1 ) ),
        Overlay( :Species )
    ),
    Elements( Points( X( 1 ), X( 2 ), X( 3 ), X( 4 ), Legend( 3 ) ), Parallel( X( 1 ), X( 2 ), X( 3 ), X( 4 ), Legend( 4 ) ) ),
    SendToReport(
        Dispatch( {}, "Graph Builder", OutlineBox,
            {Set Title( "Test to make sure lines and markers use the same color" ), Image Export Display( Normal )}
        )
    )
);
Graph Builder(
    Variables(
        X( :Sepal length ),
        X( :Sepal width, Position( 1 ) ),
        X( :Petal length, Position( 1 ) ),
        X( :Petal width, Position( 1 ) ),
        Overlay( :Species )
    ),
    Elements( Points( X( 1 ), X( 2 ), X( 3 ), X( 4 ), Legend( 6 ) ), Box Plot( X( 1 ), X( 2 ), X( 3 ), X( 4 ), Legend( 7 ) ) ),
    SendToReport(
        Dispatch( {}, "Graph Builder", OutlineBox,
            {Set Title( "Test to make sure lines and markers use the same color" ), Image Export Display( Normal )}
        )
    )
);

Code Explanation:

1. Open data_table data
2. Create Graph Builder window.
3. Set size to 534x450.
4. Hide control panel.
5. Add height and weight variables.
6. Overlay by sex.
7. Add points and parallel elements.
8. Set title for report.
9. Export image normally.
10. Open data_table data
11. Create Graph Builder window.
12. Add sepal and petal variables.
13. Overlay by species.
14. Add points and parallel elements.
15. Set title for report.
16. Export image normally.
17. Create another Graph Builder window.
18. Add sepal and petal variables.
19. Overlay by species.
20. Add points and box plot elements.
21. Set title for report.
22. Export image normally.

Example 1655

Summary: Creates a variability chart with nested factors using Graph Builder, configuring X variables and parallel elements to display standard deviation charts.

Code:

Open("data_table.jmp");
Graph Builder(
    Variables( X( :age ), X( :sex, Position( 1 ) ), X( :height, Position( 1 ) ), X( :weight, Position( 1 ) ) ),
    Elements( Parallel( X( 1 ), X( 2 ), X( 3 ), X( 4 ), Legend( 7 ) ) ),
    SendToReport( Dispatch( {}, "Graph Builder", FrameBox, {DispatchSeg( ParallelAxisSeg( 1 ), Reversed( age, height ) )} ) )
);

Code Explanation:

1. Open data table;
2. Create Graph Builder object.
3. Set X variables: age, sex, height, weight.
4. Position sex, height, weight on axis 1.
5. Add Parallel element with all X variables.
6. Set legend position to 7.
7. Send report to dispatch.
8. Access Graph Builder frame box.
9. Reverse axes for age and height.
10. Finalize graph configuration.

Example 1656

Summary: Creates two Graph Builders to visualize relationships between sepal length, width, petal length, and width, with species as an overlay, using fill between and below options.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 522, 450 ),
    Show Control Panel( 0 ),
    Variables(
        X( :Sepal length ),
        X( :Sepal width, Position( 1 ) ),
        X( :Petal length, Position( 1 ) ),
        X( :Petal width, Position( 1 ) ),
        Overlay( :Species )
    ),
    Elements( Line( X( 1 ), X( 2 ), X( 3 ), X( 4 ), Legend( 4 ), Fill( "Fill Between" ) ) ),
    SendToReport(
        Dispatch( {}, "Graph Builder", OutlineBox, {Set Title( "Graph Builder Fill Between" ), Image Export Display( Normal )} ),
        Dispatch( {}, "Graph Builder", FrameBox, {DispatchSeg( ParallelAxisSeg( 1 ), {Transparency( 0.25 )} )} )
    )
);
Graph Builder(
    Size( 522, 450 ),
    Show Control Panel( 0 ),
    Variables(
        X( :Sepal length ),
        X( :Sepal width, Position( 1 ) ),
        X( :Petal length, Position( 1 ) ),
        X( :Petal width, Position( 1 ) ),
        Overlay( :Species )
    ),
    Elements( Line( X( 1 ), X( 2 ), X( 3 ), X( 4 ), Legend( 4 ), Fill( "Fill Below" ) ) ),
    SendToReport(
        Dispatch( {}, "Graph Builder", OutlineBox, {Set Title( "Graph Builder Fill Below" ), Image Export Display( Normal )} ),
        Dispatch( {}, "Graph Builder", FrameBox, {DispatchSeg( ParallelAxisSeg( 1 ), {Transparency( 0.25 )} )} )
    )
);

Code Explanation:

1. Open data table;
2. Create first Graph Builder.
3. Set size to 522x450.
4. Hide control panel.
5. Define X variables.
6. Add overlay for species.
7. Plot lines with fill between.
8. Set title and export settings.
9. Adjust axis transparency.
10. Create second Graph Builder.
11. Repeat steps 3-9 with fill below option.

Example 1657

Summary: Creates two variability charts with nested factors using operator and part configurations, displaying standard deviation charts for audience score, domestic gross, foreign gross, world gross, and profitability.

Code:

Open("data_table.jmp");
Graph Builder(
    Variables(
        X( :Audience Score, Combine( "Parallel Independent" ) ),
        X( :Domestic Gross, Position( 1 ), Combine( "Parallel Independent" ) ),
        X( :Foreign Gross, Position( 1 ), Combine( "Parallel Independent" ) ),
        X( :World Gross, Position( 1 ), Combine( "Parallel Independent" ) ),
        X( :Profitability, Position( 1 ), Combine( "Parallel Independent" ) ),
        Overlay( :Genre )
    ),
    Elements(
        Parallel( X( 1 ), X( 2 ), X( 3 ), X( 4 ), X( 5 ), Legend( 15 ) ),
        Line( X( 1 ), X( 2 ), X( 3 ), X( 4 ), X( 5 ), Legend( 16 ) )
    )
);
Graph Builder(
    Variables(
        X( :Domestic Gross ),
        X( :Foreign Gross, Position( 1 ) ),
        X( :World Gross, Position( 1 ) ),
        X( :Production Budget, Position( 1 ) ),
        Overlay( :Genre )
    ),
    Elements( Parallel( X( 1 ), X( 2 ), X( 3 ), X( 4 ), Legend( 4 ) ), Line( X( 1 ), X( 2 ), X( 3 ), X( 4 ), Legend( 5 ) ) )
);

Code Explanation:

1. Open data table.
2. Create first Graph Builder window.
3. Set X variables for audience score.
4. Set X variables for domestic gross.
5. Set X variables for foreign gross.
6. Set X variables for world gross.
7. Set X variables for profitability.
8. Overlay by genre.
9. Add parallel plot element.
10. Add summary line element.

Example 1658

Summary: Creates a graph builder with parallel elements to visualize relationships between height, weight, and age, utilizing Graph Builder and Report features.

Code:

Open("data_table.jmp");
gb = Graph Builder(
    Show Control Panel( 0 ),
    Variables( X( :height ), X( :weight, Position( 1 ) ), X( :age, Position( 1 ) ), Color( :height ) ),
    Elements( Parallel( X( 1 ), X( 2 ), X( 3 ) ) )
);
frame = (gb << Report)[FrameBox( 1 )];
seg = frame << Find Seg( Polyline Seg( 1 ) );

Code Explanation:

1. Open data table.
2. Create Graph Builder object.
3. Hide control panel.
4. Set variables: height, weight, age, color.
5. Add parallel element.
6. Access first frame box.
7. Find polyline segment.

Example 1659

Summary: Creates a graph builder object with nested factors, utilizing Graph Builder and Parallel elements to visualize data.

Code:

Open("data_table.jmp");
gb = Graph Builder(
    Show Control Panel( 0 ),
    Variables( X( :height ), X( :weight, Position( 1 ) ), X( :age, Position( 1 ) ), Color( :height ) ),
    Elements( Parallel( X( 1 ), X( 2 ), X( 3 ) ) )
);
frame = (gb << Report)[FrameBox( 1 )];
seg = frame << Find Seg( Polyline Seg( 1 ) );
seg << Set Gradient( Color Theme( "Viridis" ) );

Code Explanation:

1. Open data table;
2. Create graph builder object.
3. Hide control panel.
4. Set variables for graph.
5. Add parallel element.
6. Access first frame box.
7. Find first polyline segment.
8. Set gradient color theme.

Example 1660

Summary: Creates a variability chart with nested factors using Graph Builder, specifying X variables and customizing legend properties.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 495, 450 ),
    Show Control Panel( 0 ),
    Variables( X( :sex ), X( :height, Position( 1 ) ), X( :weight, Position( 1 ) ) ),
    Elements( Parallel( X( 1 ), X( 2 ), X( 3 ), Legend( 3 ) ) ),
    SendToReport(
        Dispatch( {}, "400", ScaleBox, {Legend Model( 3, Properties( 0, {Line Width( 3 )}, Item ID( "Count", 1 ) ) )} ),
        Dispatch( {}, "Graph Builder", FrameBox, {Background Color( 0 )} )
    )
);

Code Explanation:

1. Open data_table data
2. Create Graph Builder window.
3. Set window size.
4. Hide control panel.
5. Define X variables: sex, height, weight.
6. Add parallel plot element.
7. Customize legend properties.
8. Set line width for legend item.
9. Change background color to black.
10. Send report to display graph.

Example 1661

Summary: Creates a Graph Builder window with variables and elements to visualize data, utilizing the Graph Builder platform.

Code:

dt = Open("data_table.jmp");
dt << clear row states;
rs = dt << select where( :age == 12 );
rs << hide and exclude;
rs = dt << select where( :name == "LESLIE" );
dt << label();
Graph Builder(
    Size( 654, 587 ),
    Show Control Panel( 0 ),
    Variables( X( :name ), X( :age, Position( 1 ) ) ),
    Elements( Parallel( X( 1 ), X( 2 ), Legend( 5 ) ) )
);

Code Explanation:

1. Open data table.
2. Clear all row states.
3. Select rows where age is 12.
4. Hide and exclude selected rows.
5. Select row where name is "LESLIE".
6. Label selected row.
7. Create Graph Builder window.
8. Set window size.
9. Hide control panel.
10. Define variables for graph.

Example 1662

Summary: Creates a variability chart with nested factors using Graph Builder, displaying standard deviation charts and customizing legend colors.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 534, 463 ),
    Show Control Panel( 0 ),
    Variables( X( :height ), X( :weight, Position( 1 ) ), Color( :sex ) ),
    Elements( Parallel( X( 1 ), X( 2 ), Legend( 3 ) ) ),
    SendToReport(
        Dispatch( {}, "400", ScaleBox, {Legend Model( 3, Properties( 0, {Line Style( "Dotted" ), Line Width( 2 )}, Item ID( "F", 1 ) ) )} )
    )
);

Code Explanation:

1. Open data table;
2. Create Graph Builder window.
3. Set window size.
4. Hide control panel.
5. Define X variables: height, weight.
6. Define color variable: sex.
7. Add parallel element.
8. Customize legend for sex.
9. Set line style to dotted.
10. Set line width to 2.

Example 1663

Summary: Creates a variability chart with nested factors using operator and part configurations, displaying standard deviation charts in Graph Builder.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 620, 422 ),
    Show Control Panel( 0 ),
    Variables(
        X( :Anticonvulsants Flag ),
        X( :Antiemetics or Phenothiazines Flag, Position( 1 ) ),
        X( :Antifibrinolytics Flag, Position( 1 ) ),
        X( :Antihypertensives Flag, Position( 1 ) ),
        X( :Blood Transfusion Flag, Position( 1 ) ),
        X( :Central Venous Pressure Monitoring Flag, Position( 1 ) ),
        X( :Induced Hypertension Flag, Position( 1 ) ),
        X( :Intentional Hypervolemia Flag, Position( 1 ) ),
        X( :Intentional Hemodilution Flag, Position( 1 ) ),
        X( :Low Molecular Weight Dextran Flag, Position( 1 ) ),
        X( :Mannitol Flag, Position( 1 ) ),
        X( :Steroids Flag, Position( 1 ) ),
        X( :Swan Ganz Monitoring Flag, Position( 1 ) ),
        X( :Vasopressors Flag, Position( 1 ) ),
        X( :Patient Died Flag, Position( 1 ) )
    ),
    Elements(
        Parallel(
            X( 1 ),
            X( 2 ),
            X( 3 ),
            X( 4 ),
            X( 5 ),
            X( 6 ),
            X( 7 ),
            X( 8 ),
            X( 9 ),
            X( 10 ),
            X( 11 ),
            X( 12 ),
            X( 13 ),
            X( 14 ),
            X( 15 ),
            Legend( 3 )
        )
    )
);

Code Explanation:

1. Open data_table data
2. Launch Graph Builder.
3. Set window size.
4. Hide control panel.
5. Define variables.
6. Add multiple X variables.
7. Configure variable positions.
8. Create parallel plot.
9. Plot all X variables.
10. Add legend.

Example 1664

Summary: Creates a variability chart with nested factors using Graph Builder, displaying standard deviation charts and configuring operator and part configurations.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 495, 2983 ),
    Show Control Panel( 0 ),
    Variables( X( :height ), X( :age, Position( 1 ) ), Page( :age ), Group X( :sex ), Size( :sex ) ),
    Elements( Parallel( X( 1 ), X( 2 ), Legend( 7 ) ) )
);

Code Explanation:

1. Open data table.
2. Create Graph Builder window.
3. Set window size.
4. Hide control panel.
5. Define X variables: height, age.
6. Set age as first position.
7. Use age for pages.
8. Group by sex.
9. Set sex size.
10. Add parallel element.

Example 1665

Summary: Creates a variability chart with nested factors using Graph Builder, displaying standard deviation charts and utilizing operator and part configurations.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 534, 418 ),
    Show Control Panel( 0 ),
    Variables( Y( :Sepal length ), Y( :Sepal width, Position( 1 ) ), Y( :Petal length, Position( 1 ) ), Y( :Petal width, Position( 1 ) ) ),
    Elements( Line( Y( 1 ), Y( 2 ), Y( 3 ), Y( 4 ), Legend( 3 ) ), Parallel( Y( 1 ), Y( 2 ), Y( 3 ), Y( 4 ), Legend( 4 ) ) )
);

Code Explanation:

1. Open data_table data
2. Launch Graph Builder.
3. Set window size.
4. Hide control panel.
5. Define Y variables.
6. Add line element.
7. Add parallel element.
8. Assign legend positions.
9. Display graph.
10. End script.

Example 1666

Summary: Creates two parallel plots with color roles and customized legend properties using Graph Builder in JMP.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 495, 450 ),
    Show Control Panel( 0 ),
    Variables(
        X( :name ),
        X( :age, Position( 1 ) ),
        X( :sex, Position( 1 ) ),
        X( :height, Position( 1 ) ),
        X( :weight, Position( 1 ) ),
        Color( :age )
    ),
    Elements( Points( X( 1 ), X( 2 ), X( 3 ), X( 4 ), X( 5 ), Legend( 3 ) ) ),
    SendToReport(
        Dispatch( {}, "400", ScaleBox,
            {Legend Model(
                3,
                Properties( 3, {Marker Size( 6 )}, Item ID( "15", 1 ) ),
                Properties( 4, {Marker( "X" )}, Item ID( "16", 1 ) ),
                Properties( 5, {Line Color( 0 )}, Item ID( "17", 1 ) )
            )}
        ),
        Dispatch( {}, "graph title", TextEditBox,
            {Set Text( "Marker parallel plot with color role and 15 set to xxxl, 16 set to x marker 17 set to black marker" )}
        )
    )
);
Graph Builder(
    Size( 495, 450 ),
    Show Control Panel( 0 ),
    Variables( X( :name ), X( :age, Position( 1 ) ), X( :sex, Position( 1 ) ), X( :height, Position( 1 ) ), X( :weight, Position( 1 ) ) ),
    Elements( Points( X( 1 ), X( 2 ), X( 3 ), X( 4 ), X( 5 ), Legend( 3 ) ) ),
    SendToReport(
        Dispatch( {}, "400", ScaleBox,
            {Legend Model( 3, Properties( 0, {Line Color( 3 ), Marker( "X" ), Marker Size( 4 )}, Item ID( "Marker", 1 ) ) )}
        ),
        Dispatch( {}, "graph title", TextEditBox, {Set Text( "large red x marker" )} )
    )
);

Code Explanation:

1. Open data table;
2. Create Graph Builder window.
3. Set graph size.
4. Hide control panel.
5. Define X variables.
6. Add color variable.
7. Plot points for all X variables.
8. Customize legend properties.
9. Set graph title.
10. Repeat steps 2-9 for another graph.

Example 1667

Summary: Creates a pie chart with nested factors using Graph Builder, displaying standard deviation charts and enabling button box interactions.

Code:

Open("data_table.jmp");
Graph Builder(
    Variables( X( :age ), Color( :age ) ),
    Elements( Pie( X, Legend( 4 ), Pie Style( "Coxcomb" ) ) ),
    SendToReport( Dispatch( {}, "", Button Box( 3 ), {Enabled( 1 )} ), Dispatch( {}, "Y title", TextEditBox, {Set Wrap( 2 )} ) )
);

Code Explanation:

1. Open data table;
2. Create Graph Builder window.
3. Set X variable to age.
4. Set color variable to age.
5. Add pie chart element.
6. Use Coxcomb pie style.
7. Enable third button box.
8. Set Y title wrap to 2.

Example 1668

Summary: Creates a nested variability chart with pie elements and caption boxes, utilizing Graph Builder to visualize data from a JMP data table.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 507, 440 ),
    Show Control Panel( 0 ),
    Variables( X( :age ), Y( :height ) ),
    Elements(
        Pie( X, Y, Legend( 8 ), Pie Style( "Ring" ) ),
        Caption Box( X, Y, Legend( 9 ), X Position( "Middle" ), Y Position( "Middle" ), Number Format( "Best", 7 ) )
    ),
    SendToReport(
        Dispatch( {}, "Graph Builder", FrameBox,
            {Add Pin Annotation(
                Seg( Pie Seg( 1 ) ),
                Index( {5, 0} ),
                Index Row( {37, 0, 1} ),
                UniqueID( 5 ),
                FoundPt( {443, 216} ),
                Origin( {-0.669642857142857, 0.551785714285714} ),
                Offset( {-123, -46} ),
                RightOfCenter( 0 ),
                Tag Line( 1 )
            ), Add Pin Annotation(
                Seg( Pie Seg( 1 ) ),
                Index( {2, 0} ),
                Index Row( {15, 0, 1} ),
                UniqueID( 2 ),
                FoundPt( {669, 402} ),
                Origin( {0.541071428571429, -0.444642857142857} ),
                RightOfCenter( 1 ),
                Tag Line( 1 )
            )}
        )
    )
);

Code Explanation:

1. Open data table;
2. Launch Graph Builder.
3. Set window size.
4. Hide control panel.
5. Assign variables X and Y.
6. Add pie element.
7. Add caption box.
8. Customize pie style.
9. Add pin annotation.
10. Add second pin annotation.

Example 1669

Summary: Creates a pie chart to visualize the count of values in the 'age' variable, using Graph Builder and sending the report to dispatch with a black background.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 400, 300 ),
    Show Control Panel( 0 ),
    Variables( X( :age ) ),
    Elements( Pie( X, Summary Statistic( "N" ), Label( "Label by Value" ) ) ),
    SendToReport( Dispatch( {}, "Graph Builder", FrameBox, {Background Color( 0 )} ) )
);

Code Explanation:

1. Open data table;
2. Create Graph Builder.
3. Set size to 400x300.
4. Hide control panel.
5. Set X variable to age.
6. Add pie chart element.
7. Summarize by count.
8. Label by value.
9. Send report to dispatch.
10. Set background color to black.

Example 1670

Summary: Creates a pie chart to display data by percent of total values, utilizing Graph Builder and specifying X variable.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 495, 440 ),
    Show Control Panel( 0 ),
    Variables( X( :Type ) ),
    Elements( Pie( X, Legend( 3 ), Label( "Label by Percent of Total Values" ) ) )
);

Code Explanation:

1. Open data table;
2. Launch Graph Builder.
3. Set window size.
4. Hide control panel.
5. Assign X variable.
6. Add pie chart element.
7. Configure legend position.
8. Label by percent.

Example 1671

Summary: Creates a pie chart with nested factors using Graph Builder, displaying standard deviation charts and adjusting legend transparency.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 466, 341 ),
    Show Control Panel( 0 ),
    Variables( X( :age ) ),
    Elements( Pie( X, Legend( 7 ), Summary Statistic( "N" ) ) ),
    SendToReport( Dispatch( {}, "400", ScaleBox, {Legend Model( 7, Properties( 1, {Transparency( 0.5 )}, Item ID( "13", 1 ) ) )} ) )
);

Code Explanation:

1. Open data table;
2. Create Graph Builder object.
3. Set graph size.
4. Hide control panel.
5. Assign age variable to X-axis.
6. Add pie chart element.
7. Configure pie legend.
8. Set summary statistic to count.
9. Adjust legend transparency.
10. Apply changes to report.

Example 1672

Summary: Creates a pie chart to visualize countries visited, with a local data filter applied to display only Canada.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 495, 440 ),
    Show Control Panel( 0 ),
    Variables( X( :countries visited ) ),
    Elements( Pie( X, Legend( 3 ) ) ),
    Local Data Filter(
        Add Filter(
            columns( :countries visited ),
            Match Any( Where( :countries visited == "Canada" ) ),
            Display( :countries visited, Find( Set Text( "" ) ) )
        )
    )
);

Code Explanation:

1. Open data table.
2. Launch Graph Builder.
3. Set window size.
4. Hide control panel.
5. Define X variable.
6. Add pie chart element.
7. Enable legend.
8. Create local data filter.
9. Add filter for countries visited.
10. Set filter criteria to Canada.

Example 1673

Summary: Creates a pie chart with nested factors using Graph Builder, displaying standard deviation charts for Clarity and Report variables.

Code:

Open("data_table.jmp");
Graph Builder(
    Show Control Panel( 0 ),
    Variables( X( :Clarity ), X( :Report, Position( 1 ) ), X( :Cut, Position( 1 ) ) ),
    Elements( Pie( X( 2 ), X( 3 ), X( 1 ), Legend( 6 ) ) ),
    SendToReport(
        Dispatch( {}, "Clarity", ScaleBox, {Min( -6.77401967975207 ), Max( 6.77401967975207 ), Inc( 1 ), Minor Ticks( 0 )} ),
        Dispatch( {}, "", ScaleBox, {Min( -5.486396104262 ), Max( 5.486396104262 ), Inc( 0.25 ), Minor Ticks( 0 )} )
    )
);

Code Explanation:

1. Open data table.
2. Create Graph Builder.
3. Hide control panel.
4. Set X variables: Clarity, Report, Cut.
5. Add Pie element.
6. Configure Pie element axes.
7. Dispatch settings for Clarity axis.
8. Dispatch settings for Report axis.

Example 1674

Summary: Creates a nested pie chart with two variables, sex and age, using Graph Builder to visualize data from an open JMP data table.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 400, 300 ),
    Show Control Panel( 0 ),
    Variables( X( :sex ), X( :age ) ),
    Elements( Position( 1, 1 ), Pie( X, Legend( 4 ) ) ),
    Elements( Position( 2, 1 ), Pie( X, Legend( 6 ) ) )
);

Code Explanation:

1. Open data table;
2. Launch Graph Builder.
3. Set window size.
4. Hide control panel.
5. Define X variables.
6. Add first pie chart.
7. Position first pie chart.
8. Assign legend for first pie.
9. Add second pie chart.
10. Position second pie chart.

Example 1675

Summary: Creates a pie chart with nested factors using Graph Builder, displaying standard deviation charts and hiding the control panel.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 400, 300 ),
    Show Control Panel( 0 ),
    Variables( X( :sex ), X( :age, Position( 1 ) ) ),
    Elements( Pie( X( 1 ), X( 2 ), Legend( 6 ), Summary Statistic( "N" ), Label( "Label by Value" ) ) )
);

Code Explanation:

1. Open data table;
2. Create new Graph Builder window.
3. Set graph size.
4. Hide control panel.
5. Assign sex variable to X-axis.
6. Assign age variable to X-axis.
7. Position age variable first.
8. Add pie chart element.
9. Set first X-axis for pie.
10. Set second X-axis for pie.

Example 1676

Summary: Creates a pie chart to visualize data with nested factors, using Graph Builder and specifying order statistics for the x-axis.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 566, 346 ),
    Show Control Panel( 0 ),
    Variables( X( :age, Order By( :height, Ascending, Order Statistic( "N" ) ) ) ),
    Elements( Pie( X, Legend( 14 ), Summary Statistic( "Sum" ), Label( "Label by Value" ) ) )
);

Code Explanation:

1. Open data table;
2. Create new Graph Builder window.
3. Set window size.
4. Hide control panel.
5. Define X variable.
6. Order by height ascending.
7. Use N for order statistic.
8. Add Pie element.
9. Enable legend.
10. Summarize by sum.

Example 1677

Summary: Creates a pie chart with nested factors using Graph Builder, displaying height and weight as y-axes and sex as an overlay.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 507, 440 ),
    Show Control Panel( 0 ),
    Variables( X( :age ), Y( :height ), Y( :weight, Position( 1 ) ), Overlay( :sex ) ),
    Elements( Pie( X, Y( 1 ), Y( 2 ), Legend( 5 ) ) ),
    SendToReport( Dispatch( {}, "graph title", TextEditBox, {Set Text( "Only the outer two blue slices should be selected" )} ) )
);

Code Explanation:

1. Open data table;
2. Create Graph Builder object.
3. Set graph size.
4. Hide control panel.
5. Define variables: X(age), Y(height), Y(weight), Overlay(sex).
6. Add Pie element with X, Y1(height), Y2(weight).
7. Set legend position.
8. Send report to Graph Builder.
9. Dispatch to graph title.
10. Set text for graph title.

Example 1678

Summary: Creates a pie chart with multiple Ys and an overlay, using Graph Builder to visualize data from a JMP data table.

Code:

dt = Open("data_table.jmp");
Graph Builder(
    Size( 507, 440 ),
    Show Control Panel( 0 ),
    Variables( X( :age ), Y( :height ), Y( :weight, Position( 1 ) ), Overlay( :sex ) ),
    Elements( Pie( X, Y( 1 ), Y( 2 ), Legend( 5 ) ) ),
    SendToReport( Dispatch( {}, "graph title", TextEditBox, {Set Text( "Only the outer two blue slices should be selected" )} ) )
);
dt << select rows( 1 );

Code Explanation:

1. Open data table.
2. Create Graph Builder object.
3. Set graph size.
4. Hide control panel.
5. Define variables: X(age), Y(height), Y(weight), Overlay(sex).
6. Add Pie element with multiple Ys.
7. Set legend position.
8. Update graph title text.
9. Select first row in data table.

Example 1679

Summary: Creates a pie chart with nested factors using Graph Builder, displaying standard deviation charts and adjusting transparency.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 466, 341 ),
    Show Control Panel( 0 ),
    Variables( X( :age ) ),
    Elements( Pie( X, Legend( 7 ), Summary Statistic( "N" ) ) ),
    SendToReport( Dispatch( {}, "Graph Builder", FrameBox, {DispatchSeg( Pie Seg( 1 ), {Transparency( 0.5 )} )} ) )
);

Code Explanation:

1. Open data table;
2. Launch Graph Builder.
3. Set graph size.
4. Hide control panel.
5. Assign age variable to X-axis.
6. Add pie chart element.
7. Enable legend.
8. Use count for summary statistic.
9. Adjust pie segment transparency.
10. Send report settings.

Example 1680

Summary: Creates a pie chart with nested factors using Graph Builder, displaying standard deviation charts and customizing line color and width.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 442, 398 ),
    Show Control Panel( 0 ),
    Variables( X( :age ) ),
    Elements( Pie( X, Legend( 83 ) ) ),
    SendToReport( Dispatch( {}, "Graph Builder", FrameBox, {DispatchSeg( Pie Seg( 1 ), {Line Color( "Red" ), Line Width( 6 )} )} ) )
);

Code Explanation:

1. Open data table.
2. Launch Graph Builder.
3. Set graph size.
4. Hide control panel.
5. Assign age variable to X-axis.
6. Add pie chart element.
7. Enable legend.
8. Customize pie segment line color.
9. Customize pie segment line width.
10. Display report.

Example 1681

Summary: Creates a pie chart with nested factors using Graph Builder, displaying standard deviation charts and color-coded by age.

Code:

Open("data_table.jmp");
Graph Builder( Size( 517, 390 ), Show Control Panel( 0 ), Variables( X( :age ), Color( :age ) ), Elements( Pie( X, Legend( 4 ) ) ) );

Code Explanation:

1. Open data table;
2. Launch Graph Builder.
3. Set window size.
4. Hide control panel.
5. Assign age to X.
6. Color by age.
7. Add pie chart element.
8. Place legend at position 4.

Example 1682

Summary: Creates a pie chart with nested factors using Graph Builder, displaying standard deviation charts and configuring graph size, control panel visibility, and legend display.

Code:

Open("data_table.jmp");
Graph Builder( Size( 517, 390 ), Show Control Panel( 0 ), Variables( X( :age ), Color( :age ) ), Elements( Pie( X, Legend( 4 ) ) ) );
Graph Builder(
    Size( 517, 390 ),
    Show Control Panel( 0 ),
    Variables( X( :age ), Color( :age ) ),
    Elements( Pie( X, Legend( 4 ), Pie Style( "Ring" ) ) )
);

Code Explanation:

1. Open data table.
2. Create pie chart.
3. Set graph size.
4. Hide control panel.
5. Assign age to X-axis.
6. Color by age.
7. Add pie element.
8. Display legend.
9. Create second pie chart.
10. Apply ring style.

Example 1683

Summary: Creates two pie charts with nested factors using Graph Builder, displaying summary statistics and labels.

Code:

dt = Open("data_table.jmp");
Graph Builder( Size( 466, 369 ), Show Control Panel( 0 ), Variables( X( :age ) ), Elements( Pie( X, Legend( 7 ) ) ) );
Graph Builder(
    Size( 466, 341 ),
    Show Control Panel( 0 ),
    Variables( X( :age ) ),
    Elements( Pie( X, Legend( 7 ), Summary Statistic( "Sum" ), Label( "Label by Value" ) ) )
);

Code Explanation:

1. Open data table.
2. Create first pie chart.
3. Hide control panel.
4. Set X variable to age.
5. Display pie elements.
6. Create second pie chart.
7. Set size to 466x341.
8. Hide control panel.
9. Set X variable to age.
10. Display pie elements with sum summary statistic.

Example 1684

Summary: Creates three pie charts with varying summary statistics, utilizing Graph Builder to visualize data from a specified data table.

Code:

lstSummaryStat = {"N", "Mean", "Sum"};
dt = Open("data_table.jmp");
Graph Builder( Size( 466, 369 ), Show Control Panel( 0 ), Variables( X( :age ) ), Elements( Pie( X, Legend( 7 ) ) ) );
Graph Builder(
    Size( 466, 341 ),
    Show Control Panel( 0 ),
    Variables( X( :age ) ),
    Elements( Pie( X, Legend( 7 ), Summary Statistic( "Sum" ), Label( "Label by Value" ) ) )
);
Graph Builder(
    Size( 466, 397 ),
    Show Control Panel( 0 ),
    Variables( X( :age ) ),
    Elements( Pie( X, Legend( 7 ), Summary Statistic( "N" ) ) )
);

Code Explanation:

1. Define summary statistics list.
2. Open data table.
3. Create initial pie graph.
4. Modify graph size.
5. Disable control panel.
6. Set X variable to age.
7. Add pie element with legend.
8. Change summary statistic to sum.
9. Label by value.
10. Change summary statistic to N.

Example 1685

Summary: Creates a pie chart to visualize the relationship between age and weight, utilizing Graph Builder's Variables and Elements features.

Code:

Open("data_table.jmp");
Graph Builder( Show Control Panel( 0 ), Variables( X( :age ), Y( :weight ) ), Elements( Pie( X, Y, Legend( 12 ) ) ) );

Code Explanation:

1. Open data table;
2. Launch Graph Builder.
3. Hide control panel.
4. Set X variable to age.
5. Set Y variable to weight.
6. Add pie chart element.
7. Display legend outside.

Example 1686

Summary: Creates a pie chart with nested factors using Graph Builder, displaying standard deviation charts and labeling by value.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 487, 419 ),
    Show Control Panel( 0 ),
    Variables( X( :age ) ),
    Elements( Pie( X, Legend( 3 ), Label( "Label by Value" ) ) )
);

Code Explanation:

1. Open data table;
2. Launch Graph Builder.
3. Set window size.
4. Hide control panel.
5. Assign X variable.
6. Add pie chart element.
7. Enable legend.
8. Label by value.

Example 1687

Summary: Creates a graph builder with nested factors using operator and part configurations, displaying standard deviation charts.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 534, 464 ),
    Show Control Panel( 0 ),
    Variables( X( :Theme ), Y( :Rotten Tomatoes Score ), Frequency( :Genre ) ),
    Elements( Points( X, Y, Legend( 4 ) ) )
);

Code Explanation:

1. Open data table;
2. Launch Graph Builder.
3. Set window size.
4. Hide control panel.
5. Assign Theme to X-axis.
6. Assign Rotten Tomatoes Score to Y-axis.
7. Use Genre for frequency.
8. Add points element.
9. Enable legend for points.
10. Display graph.

Example 1688

Summary: Creates a variability chart with nested factors using Graph Builder, displaying standard deviation charts and utilizing operator and part configurations.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 534, 454 ),
    Show Control Panel( 0 ),
    Variables( X( :height ), Y( :weight ), Frequency( :sex ) ),
    Elements( Points( X, Y, Legend( 7 ) ), Smoother( X, Y, Legend( 8 ) ) )
);

Code Explanation:

1. Open data table;
2. Launch Graph Builder.
3. Set window size.
4. Hide control panel.
5. Assign X variable.
6. Assign Y variable.
7. Assign frequency variable.
8. Add points element.
9. Add smoother element.
10. Display graph.

Example 1689

Summary: Creates a scatter plot with jittering disabled, displaying age on the x-axis and weight on the y-axis using Graph Builder.

Code:

Open("data_table.jmp");
Graph Builder( Show Control Panel( 0 ), Variables( X( :age ), Y( :weight ) ), Elements( Points( X, Y, Legend( 2 ), Jitter( 0 ) ) ) );

Code Explanation:

1. Open data table;
2. Launch Graph Builder.
3. Hide control panel.
4. Set X variable to age.
5. Set Y variable to weight.
6. Add points element.
7. Assign legend to point 2.
8. Disable jittering.

Example 1690

Summary: Creates a variability chart with nested factors using Graph Builder, displaying points and smoother elements with assigned legends.

Code:

Open("data_table.jmp");
Graph Builder(
    Show Control Panel( 0 ),
    Variables( X( :age ), Y( :weight ) ),
    Elements( Points( X, Y, Legend( 2 ), Jitter( 0 ) ), Smoother( X, Y, Legend( 5 ) ) )
);

Code Explanation:

1. Open data table;
2. Launch Graph Builder.
3. Hide control panel.
4. Set X variable to age.
5. Set Y variable to weight.
6. Add points element.
7. Assign legend to points.
8. Disable jitter for points.
9. Add smoother element.
10. Assign legend to smoother.

Example 1691

Summary: Creates a variability chart with nested factors using Graph Builder, displaying standard deviation charts and jitter effect.

Code:

Open("data_table.jmp");
Graph Builder(
    Show Control Panel( 0 ),
    Variables( X( :age ), Y( :height ), Y( :weight, Position( 1 ) ) ),
    Elements( Points( X, Y( 1 ), Y( 2 ), Legend( 3 ), Jitter( 0 ) ) )
);

Code Explanation:

1. Open data table;
2. Launch Graph Builder.
3. Hide control panel.
4. Set X variable to age.
5. Set first Y variable to height.
6. Set second Y variable to weight.
7. Position weight on axis 1.
8. Add points element.
9. Assign X and Y variables.
10. Add jitter effect.

Example 1692

Summary: Creates a variability chart with nested factors using Graph Builder, displaying standard deviation charts and customizing legend settings.

Code:

Open("data_table.jmp");
Graph Builder(
    Show Control Panel( 0 ),
    Variables( X( :age ), Y( :height ), Y( :weight, Position( 1 ) ) ),
    Elements( Points( X, Y( 1 ), Y( 2 ), Legend( 3 ), Jitter( 0 ) ), Smoother( X, Y( 1 ), Y( 2 ), Legend( 4 ) ) ),
    SendToReport( Dispatch( {}, "400", ScaleBox, {Legend Model( 3 )} ) )
);

Code Explanation:

1. Open data table.
2. Launch Graph Builder.
3. Hide control panel.
4. Set X variable: age.
5. Set Y variables: height, weight.
6. Add points element.
7. Add smoother element.
8. Customize legend for points.
9. Customize legend for smoother.
10. Adjust report settings.

Example 1693

Summary: Creates a variability chart with nested factors using Graph Builder, displaying standard deviation charts and controlling visibility settings.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 664, 550 ),
    Show Control Panel( 0 ),
    Variables( X( :age ), Y( :weight ) ),
    Elements( Points( X, Y, Legend( 5 ) ) ),
    SendToReport( Dispatch( {}, "", AxisBox( 2 ), {Visibility( "Collapse" )} ) )
);

Code Explanation:

1. Open data table;
2. Create Graph Builder window.
3. Set window size.
4. Hide control panel.
5. Assign X and Y variables.
6. Add points element.
7. Configure legend for points.
8. Send report to Graph Builder.
9. Collapse Y-axis visibility.

Example 1694

Summary: Creates two Graph Builder windows with nested factors, displaying points and controlling visibility for Y-axis.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 664, 550 ),
    Show Control Panel( 0 ),
    Variables( X( :age ), Y( :weight ) ),
    Elements( Points( X, Y, Legend( 5 ) ) ),
    SendToReport( Dispatch( {}, "", AxisBox( 2 ), {Visibility( "Collapse" )} ) )
);
Graph Builder(
    Size( 664, 550 ),
    Show Control Panel( 0 ),
    Variables( X( :age ), Y( :weight ) ),
    Elements( Points( X, Y, Legend( 5 ) ) ),
    SendToReport( Dispatch( {}, "", AxisBox( 2 ), {Visibility( "Hidden" )} ) )
);

Code Explanation:

1. Open data table.
2. Create first Graph Builder window.
3. Set window size.
4. Hide control panel.
5. Assign variables X and Y.
6. Add points element.
7. Collapse Y-axis visibility.
8. Create second Graph Builder window.
9. Set window size.
10. Hide control panel.
11. Assign variables X and Y.
12. Add points element.
13. Hide Y-axis visibility.

Example 1695

Summary: Creates a graph builder window with nested factors, utilizing Graph Builder to display points with varying marker sizes based on sex.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 452, 413 ),
    Show Control Panel( 0 ),
    Variables( X( :height ), Color( :sex ) ),
    Elements( Points( X, Legend( 3 ) ) ),
    SendToReport(
        Dispatch( {}, "400", ScaleBox,
            {Legend Model(
                3,
                Properties( 0, {Marker Size( 10 )}, Item ID( "F", 1 ) ),
                Properties( 1, {Marker Size( 10 )}, Item ID( "M", 1 ) )
            )}
        )
    )
);

Code Explanation:

1. Open data table;
2. Create Graph Builder window.
3. Set window size.
4. Hide control panel.
5. Assign height to X-axis.
6. Assign sex to color.
7. Add points element.
8. Adjust legend properties.
9. Set marker size for females.
10. Set marker size for males.

Example 1696

Summary: Creates a variability chart with nested factors using Graph Builder, displaying standard deviation charts and labeling points by value.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 400, 300 ),
    Show Control Panel( 0 ),
    Variables( X( :height ), Y( :weight ) ),
    Elements( Points( X, Y, Legend( 2 ), Label( "Label by Value" ) ) )
);

Code Explanation:

1. Open data table;
2. Launch Graph Builder.
3. Set window size.
4. Hide control panel.
5. Assign X variable.
6. Assign Y variable.
7. Add points element.
8. Enable legend.
9. Label points by value.

Example 1697

Summary: Creates a variability chart with nested factors using Graph Builder, displaying standard deviation charts and customizing legend settings.

Code:

Open("data_table.jmp");
gbp = Graph Builder(
    Size( 752, 578 ),
    Show Control Panel( 0 ),
    Variables( X( :height ), Y( :weight ) ),
    Elements( Points( X, Y, Legend( 2 ) ), Smoother( X, Y, Legend( 3 ) ) ),
    SendToReport(
        Dispatch( {}, "400", ScaleBox,
            {Legend Model( 2, Properties( 0, {Marker Size( 6 ), Transparency( 0.4 )}, Item ID( "weight", 1 ) ) )}
        )
    )
);
gb = Report( gbp );

Code Explanation:

1. Open data table.
2. Create Graph Builder object.
3. Set graph size.
4. Hide control panel.
5. Define X and Y variables.
6. Add points and smoother elements.
7. Customize legend for points.
8. Adjust marker size and transparency.
9. Send report settings.
10. Generate final report.

Example 1698

Summary: Creates a variability chart with nested factors using operator and part configurations, displaying standard deviation charts.

Code:

dt = Open("data_table.jmp");
gbp = Graph Builder(
    Size( 752, 578 ),
    Show Control Panel( 0 ),
    Variables( X( :height ), Y( :weight ) ),
    Elements( Points( X, Y, Legend( 2 ) ), Smoother( X, Y, Legend( 3 ) ) ),
    SendToReport(
        Dispatch( {}, "400", ScaleBox,
            {Legend Model( 2, Properties( 0, {Marker Size( 6 ), Transparency( 0.4 )}, Item ID( "weight", 1 ) ) )}
        )
    )
);
gb = Report( gbp );
gb << Add Variable( {:sex, role( "overlay" )} );

Code Explanation:

1. Open data table.
2. Create Graph Builder object.
3. Set graph size.
4. Hide control panel.
5. Define X and Y variables.
6. Add points and smoother elements.
7. Customize legend properties.
8. Retrieve report object.
9. Add sex variable for overlay.
10. Finalize graph settings.

Example 1699

Summary: Creates a variability chart with nested factors using operator and part configurations, displaying standard deviation charts.

Code:

dt = Open("data_table.jmp");
dt << run script( "Set Sex Value Labels" );
myGB = dt << Graph Builder(
    Size( 534, 454 ),
    Show Control Panel( 0 ),
    Variables( X( :height ), Y( :weight ) ),
    Elements( Points( X, Y, Legend( 2 ) ) )
);
rpt = myGB << Report();
myMarkerSeg = rpt[framebox( 1 )] << find seg( Marker Seg( 1 ) );

Code Explanation:

1. Open data table.
2. Run script to set value labels.
3. Create Graph Builder object.
4. Set graph size and hide control panel.
5. Define X and Y variables.
6. Add points element to graph.
7. Generate report from graph.
8. Find first frame box in report.
9. Locate marker segment in frame box.
10. Assign marker segment to variable.

Example 1700

Summary: Creates a graph builder with nested factors, setting sex value labels and displaying standard deviation charts.

Code:

dt = Open("data_table.jmp");
dt << run script( "Set Sex Value Labels" );
myGB = dt << Graph Builder(
    Size( 534, 454 ),
    Show Control Panel( 0 ),
    Variables( X( :height ), Y( :weight ) ),
    Elements( Points( X, Y, Legend( 2 ) ) )
);
rpt = myGB << Report();
myMarkerSeg = rpt[framebox( 1 )] << find seg( Marker Seg( 1 ) );
myMarkerSeg << Set Marker Draw Column( :sex );

Code Explanation:

1. Open data table.
2. Run script to set value labels.
3. Create Graph Builder object.
4. Configure Graph Builder size and options.
5. Set X and Y variables.
6. Add points element to graph.
7. Generate report from graph.
8. Locate first frame box in report.
9. Find first marker segment.
10. Set marker draw column to sex.

Example 1701

Summary: Creates a Graph Builder object with a points element to visualize failure data, utilizing a size of 200x140 and hiding the control panel.

Code:

dt = Open("data_table.jmp");
Graph Builder(
    Size( 200, 140 ),
    Show Control Panel( 0 ),
    Variables( X( :failure ) ),
    Elements( Points( X, Legend( 4 ), Summary Statistic( "N" ) ) )
);

Code Explanation:

1. Open data table.
2. Create Graph Builder object.
3. Set graph size to 200x140.
4. Hide control panel.
5. Assign X variable as :failure.
6. Add points element.
7. Set legend index to 4.
8. Use summary statistic "N".
9. Generate graph.

Example 1702

Summary: Creates a variability chart with nested factors using operator and part configurations, displaying standard deviation charts.

Code:

Open("data_table.jmp");
gb = Graph Builder(
    Set α Level( 0.01 ),
    Summary Statistic( "Median" ),
    Variables( X( :sex ), X( :age, Position( 1 ) ), Y( :weight ), Overlay( :sex ) ),
    Elements( Points( X( 1 ), X( 2 ), Y, Legend( 13 ) ) )
);
rpt = gb << Report();
sb1 = rpt[ScaleBox( 1 )];
sb1 << label row( 1, row title side( "Start" ) );

Code Explanation:

1. Open data table;
2. Create graph builder object.
3. Set alpha level to 0.01.
4. Use median summary statistic.
5. Define X and Y variables.
6. Add overlay variable.
7. Plot points element.
8. Generate report from graph.
9. Access first scale box.
10. Label row with title side "Start".

Example 1703

Summary: Creates a variability chart with nested factors using operator and part configurations, displaying standard deviation charts.

Code:

dt = Open("data_table.jmp");
gb = Graph Builder(
    Set α Level( 0.01 ),
    Summary Statistic( "Median" ),
    Variables( X( :sex ), X( :age, Position( 1 ) ), Y( :weight ), Overlay( :sex ) ),
    Elements( Points( X( 1 ), X( 2 ), Y, Legend( 13 ) ) )
);
rpt = gb << Report();
sb1 = rpt[ScaleBox( 1 )];
sb1 << label row( 1, row title side( "Start" ) );
sb1 << label row( 2, row title side( "Both" ) );

Code Explanation:

1. Open data table.
2. Create Graph Builder object.
3. Set alpha level to 0.01.
4. Use median summary statistic.
5. Define variables for X, Y, and overlay.
6. Add points element to graph.
7. Generate report from graph builder.
8. Access first scale box.
9. Label first row title side as "Start".
10. Label second row title side as "Both".

Example 1704

Summary: Creates a variability chart with nested factors using Graph Builder, displaying standard deviation charts and customizing legend properties.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 525, 452 ),
    Show Control Panel( 0 ),
    Variables( X( :weight ), Y( :height ), Overlay( :sex ), Color( :age ) ),
    Elements( Points( X, Y, Legend( 3 ) ) ),
    SendToReport(
        Dispatch( {}, "400", ScaleBox,
            {Legend Model( 3, Properties( 5, {Line Color( 41 )} ), Properties( 6, {Line Color( 29 ), Fill Color( 0 )} ) )}
        )
    )
);

Code Explanation:

1. Open data table;
2. Create graph builder window.
3. Set window size.
4. Hide control panel.
5. Define X, Y, overlay, and color variables.
6. Add points element.
7. Send report to dispatch.
8. Modify legend properties for overlay.
9. Set line color for first property.
10. Set line and fill colors for second property.

Example 1705

Summary: Creates a graph builder object with nested factors, displaying points and standard deviation charts.

Code:

Open("data_table.jmp");
gb = Graph Builder( Show Control Panel( 0 ), Variables( X( :X ), Y( :Y ), Color( :Z ) ), Elements( Points( X, Y ) ) );
frame = (gb << Report)[FrameBox( 1 )];
seg = frame << Find Seg( Marker Seg( 1 ) );

Code Explanation:

1. Open data table;
2. Create graph builder object.
3. Set X, Y, and color variables.
4. Add points element to graph.
5. Access first frame box.
6. Find marker segment.
7. Store found segment.

Example 1706

Summary: Creates a graph with nested factors using Graph Builder, hiding the control panel and defining X, Y, and Color variables.

Code:

Open("data_table.jmp");
gb = Graph Builder( Show Control Panel( 0 ), Variables( X( :X ), Y( :Y ), Color( :Z ) ), Elements( Points( X, Y ) ) );
frame = (gb << Report)[FrameBox( 1 )];
seg = frame << Find Seg( Marker Seg( 1 ) );
seg << Set Gradient( Color Theme( "Viridis" ) );

Code Explanation:

1. Open data table;
2. Create Graph Builder object.
3. Hide control panel.
4. Define X, Y, and Color variables.
5. Add points element to graph.
6. Access first frame box.
7. Find marker segment.
8. Set gradient color theme.

Example 1707

Summary: Creates a variability chart with nested factors using Graph Builder, defining X variable as height, color variable as sex, and size variable as height, while displaying standard deviation charts.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 427, 494 ),
    Show Control Panel( 0 ),
    Variables( X( :height ), Color( :sex ), Size( :height ) ),
    Elements( Points( X, Legend( 6 ) ) ),
    SendToReport(
        Dispatch( {}, "400", ScaleBox,
            {Legend Model(
                6,
                Type Properties( 0, "Marker Size", {Marker Scale( {Marker Size Minimum( "Dot" )} )} ),
                Properties( 0, {Marker Scale( {Marker Size Minimum( "Dot" )} )}, Item ID( "height", 1 ) )
            )}
        )
    )
);

Code Explanation:

1. Open data table;
2. Create Graph Builder window.
3. Set window size.
4. Hide control panel.
5. Define X variable as height.
6. Define color variable as sex.
7. Define size variable as height.
8. Add points element.
9. Adjust legend properties.
10. Set marker size minimum to dot.

Example 1708

Summary: Creates a graph builder with nested factors using operator and part configurations, displaying standard deviation charts.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 534, 454 ),
    Show Control Panel( 0 ),
    Variables( X( :height ), Y( :weight ) ),
    Elements( Points( X, Y, Legend( 3 ) ) ),
    SendToReport( Dispatch( {}, "weight", ScaleBox, {Label Row( Tick Offset( 5 ) )} ) )
);

Code Explanation:

1. Open data table;
2. Create new Graph Builder.
3. Set graph size.
4. Hide control panel.
5. Assign X and Y variables.
6. Add points element.
7. Set legend position.
8. Adjust weight axis.
9. Set tick offset to 5.

Example 1709

Summary: Creates a variability chart with nested factors using operator and part configurations, displaying standard deviation charts in Graph Builder.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 531, 448 ),
    Show Control Panel( 0 ),
    Variables( X( :Operator ), Y( :Measurement ), Color( :part# ) ),
    Elements( Points( X, Y, Legend( 1 ) ) )
);

Code Explanation:

1. Open data table;
2. Create new Graph Builder window.
3. Set window size.
4. Hide control panel.
5. Define X variable.
6. Define Y variable.
7. Define color variable.
8. Add points element.
9. Enable legend for points.
10. Display graph.

Example 1710

Summary: Creates a variability chart with nested factors using operator and part configurations, displaying standard deviation charts in Graph Builder.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 534, 448 ),
    Show Control Panel( 0 ),
    Variables( X( :Operator ), Y( :Measurement ), Color( :part# ) ),
    Elements( Points( X, Y, Legend( 1 ), Summary Statistic( "Mean" ) ) )
);

Code Explanation:

1. Open data table;
2. Launch Graph Builder.
3. Set window size.
4. Hide control panel.
5. Define X variable.
6. Define Y variable.
7. Define color variable.
8. Add points element.
9. Set summary statistic to mean.
10. Display graph.

Example 1711

Summary: Creates a geographic map to visualize data across regions, utilizing Graph Builder's variables and elements configuration.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 780, 649 ),
    Show Control Panel( 0 ),
    Variables(
        X( :Longitude ),
        Y( :Latitude ),
        Overlay( :Region ),
        Color( :Population ),
        Size( :Name( "% Taking (1997)" ) ),
        Shape( :State )
    ),
    Elements( Points( X, Y, Legend( 39 ) ) )
);

Code Explanation:

1. Open data table;
2. Launch Graph Builder.
3. Set window size.
4. Hide control panel.
5. Define X variable.
6. Define Y variable.
7. Define overlay variable.
8. Define color variable.
9. Define size variable.
10. Define shape variable.

Example 1712

Summary: Creates a variability chart with nested factors using Graph Builder, displaying points and smoother elements, and customizing the legend title.

Code:

Open("data_table.jmp");
Graph Builder(
    Show Control Panel( 0 ),
    Variables( X( :Total fat g ), Y( :Calories ), Overlay( :Carbohydrate g ) ),
    Elements( Points( X, Y, Legend( 1 ) ), Smoother( X, Y, Legend( 2 ) ) ),
    SendToReport( Dispatch( {}, "400", LegendBox, {Set Title( "Carbohydrate grams" )} ) )
);

Code Explanation:

1. Open data table;
2. Launch Graph Builder.
3. Hide control panel.
4. Set X variable.
5. Set Y variable.
6. Set overlay variable.
7. Add points element.
8. Add smoother element.
9. Customize legend title.
10. Display graph.

Example 1713

Summary: Creates a variability chart with nested factors using Graph Builder, displaying standard deviation charts and customizing legend properties.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 495, 247 ),
    Show Control Panel( 0 ),
    Variables( X( :Y ), Y( :Y ), Color( :X ) ),
    Elements( Points( X, Y, Legend( 10 ) ) ),
    SendToReport(
        Dispatch( {}, "400", ScaleBox, {Legend Model( 10, Properties( 0, {gradient( {Scale Type( "Log" )} )} ) )} ),
        Dispatch( {}, "Graph Builder", FrameBox, {Marker Size( 6 )} )
    )
);

Code Explanation:

1. Open data table.
2. Launch Graph Builder.
3. Set window size.
4. Hide control panel.
5. Assign variables to axes.
6. Add points element.
7. Customize legend properties.
8. Set scale type to log.
9. Adjust marker size.
10. Send report settings.

Example 1714

Summary: Configures a geographic map to visualize the relationship between Longitude and Latitude using Graph Builder, with customized scale settings for both axes.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 342, 304 ),
    Show Control Panel( 0 ),
    Variables( X( :Longitude ), Y( :Latitude ) ),
    Elements( Points( X, Y, Legend( 8 ) ) ),
    SendToReport(
        Dispatch( {}, "Longitude", ScaleBox,
            {Scale( "Geodesic US" ), Format( "Best", 10 ), Min( -130.465133704084 ), Max( -65.2794320942478 ), Inc( 5 ), Minor Ticks( 1 )}
        ),
        Dispatch( {}, "Latitude", ScaleBox,
            {Scale( "Geodesic US" ), Format( "Best", 10 ), Min( 15.8741127240009 ), Max( 68.8101522863511 ), Inc( 5 ), Minor Ticks( 1 )}
        ),
        Dispatch( {}, "Graph Builder", FrameBox,
            {Background Map( Images( "Simple Earth" ) ), Grid Line Order( 2 ), Reference Line Order( 3 )}
        )
    )
);

Code Explanation:

1. Open data table;
2. Create Graph Builder window.
3. Set graph size.
4. Hide control panel.
5. Assign variables to axes.
6. Add points element.
7. Configure Longitude scale.
8. Configure Latitude scale.
9. Add background map.
10. Set grid and reference line order.

Example 1715

Summary: Creates a graph builder with nested factors using operator and part configurations, displaying standard deviation charts.

Code:

Open("data_table.jmp");
Graph Builder(
    Show Control Panel( 0 ),
    Variables( X( :age ), Y( :height ), Color( :sex ) ),
    Elements( Points( X, Y, Legend( 1 ) ) ),
    SendToReport(
        Dispatch( {}, "400", ScaleBox, {Legend Model( 1, Properties( 0, {Marker( "Star" )} ), Properties( 1, {Marker( "Z" )} ) )} )
    )
);

Code Explanation:

1. Open data table.
2. Launch Graph Builder.
3. Hide control panel.
4. Set X variable: age.
5. Set Y variable: height.
6. Set color variable: sex.
7. Add points element.
8. Customize legend properties.
9. Set marker for males: Star.
10. Set marker for females: Z.

Example 1716

Summary: Creates a variability chart with nested factors using Graph Builder, displaying standard deviation charts and configuring points alignment and error bars.

Code:

dt = Open("data_table.jmp");
Graph Builder(
    Size( 563, 463 ),
    Show Control Panel( 0 ),
    Variables( X( :sex ), X( :age, Position( 1 ) ), Y( :height ), Group Y( :weight ) ),
    Elements( Points( X( 1 ), X( 2 ), Y, Legend( 5 ), Summary Statistic( "Mean" ), Error Bars( "Range" ) ) )
);

Code Explanation:

1. Open data table;
2. Launch Graph Builder.
3. Set window size.
4. Hide control panel.
5. Define X variables.
6. Define second X variable position.
7. Define Y variable.
8. Define group Y variable.
9. Add points element.
10. Configure points alignment and error bars.

Example 1717

Summary: Creates a variability chart with nested factors using Graph Builder, displaying standard deviation charts and configuring reference lines.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 573, 333 ),
    Show Control Panel( 0 ),
    Variables( X( :age ), X( :sex, Position( 1 ) ), Y( :weight ) ),
    Elements( Points( X( 1 ), X( 2 ), Y, Legend( 5 ) ) ),
    SendToReport(
        Dispatch( {}, "age", ScaleBox,
            {Add Ref Line( {5.5, 8}, "Solid", "Medium Light Orange", "range", 1, 0.35 ), Label Row( 1, Show Major Labels( 0 ) )}
        )
    )
);

Code Explanation:

1. Open data table;
2. Launch Graph Builder.
3. Set window size.
4. Hide control panel.
5. Define X variables: age, sex.
6. Define Y variable: weight.
7. Add points element.
8. Configure points element.
9. Send report to Graph Builder.
10. Add reference line to age axis.

Example 1718

Summary: Creates a variability chart with nested factors using Graph Builder, assigning variables to axes and displaying standard deviation charts.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 564, 490 ),
    Show Control Panel( 0 ),
    Variables( X( :weight ), Y( :height ), Group X( :sex ), Group Y( :age ) ),
    Elements( Points( X, Y, Legend( 7 ) ) ),
    SendToReport(
        Dispatch( {}, "Graph Builder", FrameBox, {Background Color( 41 )} ),
        Dispatch( {}, "Graph Builder", FrameBox( 9 ), {Background Color( 38 )} )
    )
);

Code Explanation:

1. Open data table;
2. Launch Graph Builder.
3. Set graph size.
4. Hide control panel.
5. Assign variables to axes.
6. Add points element.
7. Send report to dispatch.
8. Set background color for first frame.
9. Set background color for second frame.

Example 1719

Summary: Creates a variability chart with nested factors using Graph Builder, displaying standard deviation charts and utilizing size and color variables.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 223, 228 ),
    Show Control Panel( 0 ),
    Variables( X( :weight ), Y( :height ), Size( :sex ), Color( :age ) ),
    Elements( Points( X, Y, Legend( 15 ), Summary Statistic( "Mean" ) ) )
);

Code Explanation:

1. Open data table;
2. Launch Graph Builder.
3. Set window size.
4. Hide control panel.
5. Assign variables to axes.
6. Set size variable.
7. Set color variable.
8. Add points element.
9. Enable legend.
10. Use mean summary statistic.

Example 1720

Summary: Creates a variability chart with nested factors using Graph Builder, displaying standard deviation charts and overlaying by sex.

Code:

Open("data_table.jmp");
Graph Builder(
    Show Control Panel( 0 ),
    Variables( X( :height ), Y( :weight ), Overlay( :sex ), Size( :sex ) ),
    Elements( Points( X, Y, Legend( 118 ), Summary Statistic( "Mean" ) ), Smoother( X, Y, Legend( 119 ) ) )
);

Code Explanation:

1. Open data table;
2. Launch Graph Builder.
3. Hide control panel.
4. Set X variable: height.
5. Set Y variable: weight.
6. Overlay by sex.
7. Size by sex.
8. Add points element.
9. Use mean summary statistic.
10. Add smoother element.

Example 1721

Summary: Creates a variability chart with nested factors using Graph Builder, applying square root transformation and displaying standard deviation charts.

Code:

Open("data_table.jmp");
Graph Builder(
    Show Control Panel( 0 ),
    Transform Column( "Square Root[height]", Formula( Sqrt( :height - 62 ) ) ),
    Variables( X( :sex ), Y( :"Square Root[height]"n ) ),
    Elements( Points( X, Y, Summary Statistic( "Median" ), Error Interval( "Confidence Interval" ) ) )
);

Code Explanation:

1. Open data table;
2. Create new column.
3. Apply square root transformation.
4. Adjust column name.
5. Launch Graph Builder.
6. Hide control panel.
7. Set X variable.
8. Set Y variable.
9. Add points element.
10. Use median summary statistic.
11. Enable confidence interval.

Example 1722

Summary: Creates a variability chart with nested factors using Graph Builder, displaying standard deviation charts and error intervals.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 528, 450 ),
    Show Control Panel( 0 ),
    Variables( X( :age ), Y( :height ) ),
    Elements( Points( X, Y, Legend( 4 ), Summary Statistic( "Mean" ), Error Interval( "Range" ), Interval Style( "Band" ) ) )
);

Code Explanation:

1. Open data table.
2. Create new Graph Builder window.
3. Set window size to 528x450.
4. Hide control panel.
5. Assign X variable as age.
6. Assign Y variable as height.
7. Add points element.
8. Use mean summary statistic.
9. Display range error interval.
10. Style interval as band.

Example 1723

Summary: Creates a variability chart with nested factors using operator and part configurations, displaying standard deviation charts.

Code:

Open("data_table.jmp");
Graph Builder(
    Show Control Panel( 0 ),
    Variables( X( :Cut, Size By( "Count" ) ), Y( :Carat Weight ) ),
    Elements( Points( X, Y, Legend( 3 ), Summary Statistic( "Mean" ), Error Interval( "Range" ), Interval Style( "Band" ) ) )
);

Code Explanation:

1. Open data table;
2. Launch Graph Builder.
3. Hide Control Panel.
4. Set X variable: Cut.
5. Size by Count.
6. Set Y variable: Carat Weight.
7. Add Points element.
8. Use Mean for summary statistic.
9. Enable Range error interval.
10. Display interval as Band.

Example 1724

Summary: Creates a graph builder with nested factors using operator and part configurations, displaying standard deviation charts.

Code:

Open("data_table.jmp");
Graph Builder(
    Show Control Panel( 0 ),
    Variables( X( :age ), Y( :height ), Overlay( :sex ), Interval( :weight ) ),
    Elements( Points( X, Y ) ), 
);

Code Explanation:

1. Open data table;
2. Launch Graph Builder.
3. Hide control panel.
4. Set X variable to age.
5. Set Y variable to height.
6. Use sex for overlay.
7. Use weight for interval.
8. Add points element.
9. Display graph.
10. Save script.

Example 1725

Summary: Creates a variability chart with nested factors using Graph Builder, displaying standard deviation charts and error bars.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 487, 533 ),
    Show Control Panel( 0 ),
    Variables( Y( :height ), Y( :weight, Position( 1 ) ) ),
    Elements( Points( Y( 1 ), Y( 2 ), Legend( 6 ), Summary Statistic( "Mean" ), Error Bars( "Range" ) ) )
);

Code Explanation:

1. Open data table;
2. Launch Graph Builder.
3. Set window size.
4. Hide control panel.
5. Define Y variables: height, weight.
6. Add points element.
7. Set Y positions for points.
8. Assign legend to points.
9. Use mean for summary statistic.
10. Display range error bars.

Example 1726

Summary: Creates a variability chart with nested factors using Graph Builder, displaying standard deviation charts and error bars.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 321, 344 ),
    Show Control Panel( 0 ),
    Variables( Y( :height ), Y( :weight, Position( 1 ) ) ),
    Elements( Points( Y( 1 ), Y( 2 ), Legend( 6 ), Summary Statistic( "Mean" ), Error Bars( "Standard Error" ) ) )
);

Code Explanation:

1. Open data table.
2. Launch Graph Builder.
3. Set window size.
4. Hide control panel.
5. Assign height to Y-axis.
6. Assign weight to Y-axis.
7. Add points element.
8. Set summary statistic to mean.
9. Add error bars.
10. Set error bar type to standard error.

Example 1727

Summary: Creates a variability chart with nested factors using Graph Builder, displaying standard deviation charts and mean statistics.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 367, 261 ),
    Show Control Panel( 0 ),
    Variables( X( :age ), Group Y( :sex ) ),
    Elements( Points( X, Legend( 3 ), Summary Statistic( "Mean" ) ) )
);

Code Explanation:

1. Open data table;
2. Launch Graph Builder.
3. Set window size.
4. Hide control panel.
5. Assign X variable.
6. Assign Group Y variable.
7. Add points element.
8. Use legend.
9. Set summary statistic to mean.

Example 1728

Summary: Creates a geographic map to visualize total serious injuries across the United States, utilizing Graph Builder and configuring scales for Longitude and Latitude.

Code:

dt = Open("data_table.jmp");
gb = dt << Graph Builder(
    Size( 528, 453 ),
    Show Control Panel( 0 ),
    Variables( X( :Longitude ), Y( :Latitude ), Color( :Total Serious Injuries ), Size( :Total Serious Injuries ) ),
    Elements( Points( X, Y, Legend( 8 ) ) ),
    SendToReport(
        Dispatch( {}, "Longitude", ScaleBox,
            {Scale( "Geodesic", {Compact Map( {Region( "United States" ), Alaska( 1 ), Hawaii( 1 )} )} ), Format( "Best", 10 ),
            Min( -130.716492450652 ), Max( -65.0280733476802 ), Inc( 5 ), Minor Ticks( 1 )}
        ),
        Dispatch( {}, "Latitude", ScaleBox,
            {Scale( "Geodesic", {Compact Map( {Region( "United States" ), Alaska( 1 ), Hawaii( 1 )} )} ), Format( "Best", 10 ),
            Min( 15.9446169772257 ), Max( 68.7396480331263 ), Inc( 5 ), Minor Ticks( 1 )}
        ),
        Dispatch( {}, "Graph Builder", FrameBox,
            {Background Map( Images( "Simple Earth" ) ), DispatchSeg(
                Marker Seg( 1 ),
                {Set Hide Missing Size( 1 ), Set Hide Missing Color( 1 )}
            )}
        )
    )
);

Code Explanation:

1. Open table.
2. Create Graph Builder.
3. Set size.
4. Hide control panel.
5. Define variables.
6. Add points element.
7. Configure Longitude scale.
8. Configure Latitude scale.
9. Set background map.
10. Hide missing color and size.

Example 1729

Summary: Creates a graph builder with nested factors using operator and part configurations, displaying standard deviation charts.

Code:

dt2 = Open("data_table.jmp");
gb2 = dt2 << Graph Builder(
    Size( 495, 461 ),
    Show Control Panel( 0 ),
    Variables( X( :School Department Type Code ), Color( :Class Rank Number ) ),
    Elements( Points( X, Legend( 6 ) ) ),
    SendToReport( Dispatch( {}, "Graph Builder", FrameBox, {DispatchSeg( Marker Seg( 1 ), Set Hide Missing Color( 1 ) )} ) )
);

Code Explanation:

1. Open table.
2. Create Graph Builder object.
3. Set size to 495x461.
4. Hide control panel.
5. Define X variable.
6. Define Color variable.
7. Add points element.
8. Set legend position.
9. Send report dispatch.
10. Hide missing color.

Example 1730

Summary: Creates a Graph Builder object with nested factors, utilizing operator and part configurations to display standard deviation charts.

Code:

dt3 = Open("data_table.jmp");
dt3:Position2 << set property( "missing value codes", {"o"} );
gb3 = dt3 << Graph Builder(
    Size( 562, 406 ),
    Show Control Panel( 0 ),
    Variables( X( :Weight ), Y( :Height ), Color( :Position2 ), Size( :LegPress ) ),
    Elements( Points( X, Y, Legend( 6 ) ) ),
    SendToReport(
        Dispatch( {}, "Graph Builder", FrameBox,
            {DispatchSeg( Marker Seg( 1 ), {Set Hide Missing Size( 1 ), Set Hide Missing Color( 1 )} )}
        )
    )
);

Code Explanation:

1. Open data table;
2. Set missing value code for Position2.
3. Create Graph Builder object.
4. Set graph size.
5. Hide control panel.
6. Define X, Y, Color, Size variables.
7. Add Points element.
8. Send report to Graph Builder.
9. Dispatch to Marker Seg.
10. Hide missing size and color.

Example 1731

Summary: Creates three Graph Builders to visualize data with nested factors, utilizing variables such as longitude, latitude, weight, height, and leg press, while configuring scales and hiding missing values.

Code:

dt = Open("data_table.jmp");
gb = dt << Graph Builder(
    Size( 528, 453 ),
    Show Control Panel( 0 ),
    Variables( X( :Longitude ), Y( :Latitude ), Color( :Total Serious Injuries ), Size( :Total Serious Injuries ) ),
    Elements( Points( X, Y, Legend( 8 ) ) ),
    SendToReport(
        Dispatch( {}, "Longitude", ScaleBox,
            {Scale( "Geodesic", {Compact Map( {Region( "United States" ), Alaska( 1 ), Hawaii( 1 )} )} ), Format( "Best", 10 ),
            Min( -130.716492450652 ), Max( -65.0280733476802 ), Inc( 5 ), Minor Ticks( 1 )}
        ),
        Dispatch( {}, "Latitude", ScaleBox,
            {Scale( "Geodesic", {Compact Map( {Region( "United States" ), Alaska( 1 ), Hawaii( 1 )} )} ), Format( "Best", 10 ),
            Min( 15.9446169772257 ), Max( 68.7396480331263 ), Inc( 5 ), Minor Ticks( 1 )}
        ),
        Dispatch( {}, "Graph Builder", FrameBox,
            {Background Map( Images( "Simple Earth" ) ), DispatchSeg(
                Marker Seg( 1 ),
                {Set Hide Missing Size( 1 ), Set Hide Missing Color( 1 )}
            )}
        )
    )
);
dt2 = Open("data_table.jmp");
gb2 = dt2 << Graph Builder(
    Size( 495, 461 ),
    Show Control Panel( 0 ),
    Variables( X( :School Department Type Code ), Color( :Class Rank Number ) ),
    Elements( Points( X, Legend( 6 ) ) ),
    SendToReport( Dispatch( {}, "Graph Builder", FrameBox, {DispatchSeg( Marker Seg( 1 ), Set Hide Missing Color( 1 ) )} ) )
);
dt3 = Open("data_table.jmp");
dt3:Position2 << set property( "missing value codes", {"o"} );
gb3 = dt3 << Graph Builder(
    Size( 562, 406 ),
    Show Control Panel( 0 ),
    Variables( X( :Weight ), Y( :Height ), Color( :Position2 ), Size( :LegPress ) ),
    Elements( Points( X, Y, Legend( 6 ) ) ),
    SendToReport(
        Dispatch( {}, "Graph Builder", FrameBox,
            {DispatchSeg( Marker Seg( 1 ), {Set Hide Missing Size( 1 ), Set Hide Missing Color( 1 )} )}
        )
    )
);

Code Explanation:

1. Open data_table data
2. Create Graph Builder for data_table.
3. Set size and hide control panel.
4. Define variables: longitude, latitude, injuries, size.
5. Add points element with legend.
6. Configure longitude scale: geodesic, compact map, region settings.
7. Configure latitude scale: geodesic, compact map, region settings.
8. Set background map to "Simple Earth".
9. Hide missing color and size.
10. Open data_table data
11. Create Graph Builder for data_table.
12. Set size and hide control panel.
13. Define variables: school type, class rank.
14. Add points element with legend.
15. Hide missing color.
16. Open data_table data
17. Set missing value codes for position.
18. Create Graph Builder for data_table.
19. Set size and hide control panel.
20. Define variables: weight, height, position, leg press.
21. Add points element with legend.
22. Hide missing color and size.

Example 1732

Summary: Creates two variability charts with nested factors using Graph Builder, displaying standard deviation charts and mean summary statistics.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 528, 496 ),
    Show Control Panel( 0 ),
    Variables( X( :age ), Y( :height ), Overlay( :sex ) ),
    Elements( Points( X, Y, Legend( 4 ), Summary Statistic( "Mean" ) ) )
);
Graph Builder(
    Size( 528, 496 ),
    Show Control Panel( 0 ),
    Variables( X( :age ), Y( :height ), Overlay( :sex ) ),
    Elements( Points( X, Y, Legend( 4 ), Jitter( 0 ), Summary Statistic( "Mean" ), Error Bars( "Standard Error" ) ) )
);

Code Explanation:

1. Open data table;
2. Create Graph Builder window.
3. Set graph size.
4. Hide control panel.
5. Assign variables: X=age, Y=height, Overlay=sex.
6. Add points element.
7. Set legend for points.
8. Calculate mean summary statistic.
9. Create second Graph Builder window.
10. Add jitter to points.

Example 1733

Summary: Creates two Graph Builder objects to visualize nested factors using operator and part configurations, with standard deviation charts displayed for each factor.

Code:

dt = Open("data_table.jmp");
gb = Graph Builder(
    Show Control Panel( 0 ),
    Variables( X( :Age ), Y( :Weight ), Y( :Oxy ), Y( :Runtime ), Color( :Sex ) ),
    Elements( Position( 1, 1 ), Points( X, Y, Color, Legend( 7 ) ) ),
    Elements( Position( 1, 2 ), Points( X, Y, Color, Legend( 8 ) ) ),
    Elements( Position( 1, 3 ), Points( X, Y, Color, Legend( 9 ) ) )
);
gb2 = Graph Builder(
    Show Control Panel( 0 ),
    Variables( X( :Age ), Y( :Weight ), Y( :Oxy ), Y( :Runtime ), Color( :Sex ) ),
    Elements( Position( 1, 1 ), Points( X, Y, Legend( 7 ), Jitter( 1 ) ) ),
    Elements( Position( 1, 2 ), Points( X, Y, Legend( 8 ), Jitter( 1 ) ) ),
    Elements( Position( 1, 3 ), Points( X, Y, Legend( 9 ), Jitter( 1 ) ) ),
    SendToReport( Dispatch( {}, "400", ScaleBox, {Legend Model( 7, Properties( 0, {Line Color( 74 )} ) )} ) )
);

Code Explanation:

1. Open data table;
2. Create first Graph Builder object.
3. Hide control panel.
4. Set X variable: Age.
5. Set Y variables: Weight, Oxy, Runtime.
6. Set color variable: Sex.
7. Add points element for Weight.
8. Add points element for Oxy.
9. Add points element for Runtime.
10. Create second Graph Builder object with jitter.

Example 1734

Summary: Creates a graph builder object to visualize temperature data over time, with nested factors represented by color and overlay encoding.

Code:

Open("data_table.jmp");
gb = Graph Builder(
    Transform Column( "Odd", Nominal, Formula( Modulo( :Year, 2 ) ) ),
    Transform Column( "Year Nominal", Nominal, Formula( :Year ) ),
    Variables( X( :Month ), Y( :Temperature ), Overlay( :Year Nominal, Overlay Encoding( "None" ) ), Color( :Odd ) ),
    Elements( Points( X, Y, Legend( 14 ) ), Smoother( X, Y, Legend( 15 ) ) )
);
gb << journal;

Code Explanation:

1. Open data table;
2. Create graph builder object.
3. Transform "Odd" column.
4. Transform "Year Nominal" column.
5. Set X, Y variables.
6. Overlay by "Year Nominal".
7. Color by "Odd".
8. Add points element.
9. Add smoother element.
10. Show graph in journal.

Example 1735

Summary: Creates a variability chart with nested factors using Graph Builder, transforming 'Year' into 'Odd' and 'Year Nominal', and displaying standard deviation charts.

Code:

Open("data_table.jmp");
gb = Graph Builder(
    Transform Column( "Odd", Nominal, Formula( Modulo( :Year, 2 ) ) ),
    Transform Column( "Year Nominal", Nominal, Formula( :Year ) ),
    Variables( X( :Month ), Y( :Temperature ), Overlay( :Year Nominal, Overlay Encoding( "None" ) ), Color( :Odd ) ),
    Elements( Points( X, Y, Legend( 14 ) ), Smoother( X, Y, Legend( 15 ) ) )
);
gb << journal;
gb << close window;

Code Explanation:

1. Open data table;
2. Create Graph Builder object.
3. Transform "Year" to "Odd".
4. Transform "Year" to "Year Nominal".
5. Set X axis to "Month".
6. Set Y axis to "Temperature".
7. Overlay by "Year Nominal".
8. Color points by "Odd".
9. Add Points element.
10. Add Smoother element.
11. Show journal.
12. Close graph window.

Example 1736

Summary: Creates a variability chart with nested factors using Graph Builder, displaying standard deviation charts and configuring legend orientation.

Code:

Open("data_table.jmp");
Graph Builder(
    Show Control Panel( 0 ),
    Variables( X( :height ), Y( :weight ), Overlay( :sex ) ),
    Elements( Points( X, Y, Legend( 1 ) ), Smoother( X, Y, Legend( 1 ) ) ),
    SendToReport( Dispatch( {}, "400", LegendBox, {Orientation( "Horizontal" ), Sides( "Left" )} ) )
);

Code Explanation:

1. Open data table.
2. Launch Graph Builder.
3. Hide control panel.
4. Set X variable to height.
5. Set Y variable to weight.
6. Overlay by sex.
7. Add points element.
8. Add smoother element.
9. Send report to Graph Builder.
10. Configure legend orientation and sides.

Example 1737

Summary: Creates two Graph Builders to visualize relationships between height, weight, and sex in a dataset, with customizable legend orientation and sides.

Code:

Open("data_table.jmp");
Graph Builder(
    Show Control Panel( 0 ),
    Variables( X( :height ), Y( :weight ), Overlay( :sex ) ),
    Elements( Points( X, Y, Legend( 1 ) ), Smoother( X, Y, Legend( 1 ) ) ),
    SendToReport( Dispatch( {}, "400", LegendBox, {Orientation( "Horizontal" ), Sides( "Left" )} ) )
);
Graph Builder(
    Show Control Panel( 0 ),
    Variables( X( :height ), Y( :weight ), Overlay( :sex ) ),
    Elements( Points( X, Y, Legend( 1 ) ), Smoother( X, Y, Legend( 1 ) ) )
);

Code Explanation:

1. Open data table.
2. Create first Graph Builder.
3. Hide control panel.
4. Set X, Y, and overlay variables.
5. Add points and smoother elements.
6. Customize legend orientation and sides.
7. Create second Graph Builder.
8. Hide control panel.
9. Set X, Y, and overlay variables.
10. Add points and smoother elements.

Example 1738

Summary: Creates a variability chart with nested factors using Graph Builder, displaying standard deviation charts for height and weight data.

Code:

Open("data_table.jmp");
Graph Builder(
    Show Control Panel( 0 ),
    Variables( X( :age ), Y( :height ), Y( :weight ), Overlay( :name ), Color( :age ) ),
    Elements( Position( 1, 1 ), Points( X, Y, Legend( 14 ) ) ),
    Elements( Position( 1, 2 ), Points( X, Y, Legend( 15 ) ) )
);

Code Explanation:

1. Open data table;
2. Launch Graph Builder.
3. Hide control panel.
4. Set X variable: age.
5. Set Y variables: height, weight.
6. Overlay by name.
7. Color by age.
8. Add points element for height.
9. Add points element for weight.
10. Configure legends.

Example 1739

Summary: Creates two variability charts with nested factors using Graph Builder, configuring marker size and legend properties.

Code:

Open("data_table.jmp");
Graph Builder(
    Variables( X( :LDL ), Y( :Total Cholesterol ), Size( :HDL ) ),
    Elements( Points( X, Y, Legend( 9 ) ), Smoother( X, Y, Legend( 10 ) ) ),
    SendToReport(
        Dispatch( {}, "400", ScaleBox,
            {Legend Model(
                9,
                Properties( 0, {Marker Scale( {Marker Size Minimum( "Dot" ), Label Format( "Fixed Dec", 15, 0 )} )}, Item ID( "HDL", 1 ) )
            )}
        )
    )
);
Graph Builder(
    Variables( X( :LDL ), Y( :Total Cholesterol ), Size( :HDL ) ),
    Elements( Points( X, Y, Legend( 9 ) ), Smoother( X, Y, Legend( 10 ) ) ),
    SendToReport(
        Dispatch( {}, "400", ScaleBox,
            {Legend Model(
                9,
                Properties(
                    0,
                    {Marker Scale( {Marker Size Minimum( "Relative To", 50 ), Label Format( "Fixed Dec", 15, 0 )} )},
                    Item ID( "HDL", 1 )
                )
            )}
        )
    )
);

Code Explanation:

1. Open data table;
2. Create Graph Builder.
3. Set X to LDL.
4. Set Y to Total Cholesterol.
5. Set Size to HDL.
6. Add Points element.
7. Add Smoother element.
8. Adjust marker size minimum to Dot.
9. Create second Graph Builder.
10. Adjust marker size minimum to Relative To 50.

Example 1740

Summary: Creates a variability chart with nested factors using Graph Builder, displaying standard deviation charts and applying mean summary statistics.

Code:

Open("data_table.jmp");
Graph Builder(
    Show Control Panel( 0 ),
    Variables( X( :height ), Y( :weight ) ),
    Elements( Points( X, Y, Legend( 2 ), Summary Statistic( "Mean" ) ) )
);

Code Explanation:

1. Open data table;
2. Launch Graph Builder.
3. Hide control panel.
4. Set X variable to height.
5. Set Y variable to weight.
6. Add points element.
7. Assign legend to second position.
8. Apply mean summary statistic.
9. Display graph.

Example 1741

Summary: Creates two Graph Builder windows to visualize relationships between height and weight, as well as age and weight, using the Graph Builder platform in JMP.

Code:

Open("data_table.jmp");
Graph Builder(
    Show Control Panel( 0 ),
    Variables( X( :height ), Y( :weight ) ),
    Elements( Points( X, Y, Legend( 2 ), Summary Statistic( "Mean" ) ) )
);
Graph Builder(
    Show Control Panel( 0 ),
    Variables( X( :age ), Y( :weight ) ),
    Elements( Points( X, Y, Legend( 2 ), Summary Statistic( "Mean" ) ) )
);

Code Explanation:

1. Open data table;
2. Create first graph builder window.
3. Hide control panel.
4. Set X variable to height.
5. Set Y variable to weight.
6. Add points element.
7. Set summary statistic to mean.
8. Create second graph builder window.
9. Hide control panel.
10. Set X variable to age.

Example 1742

Summary: Creates a graph builder with nested factors using operator and part configurations, displaying standard deviation charts.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 495, 461 ),
    Show Control Panel( 0 ),
    Variables( X( :School Department Type Code ), Color( :Class Rank Number ) ),
    Elements( Points( X, Legend( 6 ) ) ),
    SendToReport( Dispatch( {}, "Graph Builder", FrameBox, {DispatchSeg( Marker Seg( 1 ), Set Hide Missing Color( 1 ) )} ) )
);

Code Explanation:

1. Open data table.
2. Launch Graph Builder.
3. Set window size.
4. Hide control panel.
5. Assign X variable.
6. Assign Color variable.
7. Add points element.
8. Set legend position.
9. Send report command.
10. Hide missing color in legend.

Example 1743

Summary: Creates a graph builder window with a points element, utilizing variables Weight and Height for X and Y axes, and Position2 as the color variable.

Code:

Open("data_table.jmp");
:Position2 << set property( "missing value codes", {"o"} );
Graph Builder(
    Size( 562, 406 ),
    Show Control Panel( 0 ),
    Variables( X( :Weight ), Y( :Height ), Color( :Position2 ) ),
    Elements( Points( X, Y, Legend( 6 ) ) )
);

Code Explanation:

1. Open data table;
2. Set missing value code for Position2.
3. Create Graph Builder window.
4. Disable control panel.
5. Set X variable to Weight.
6. Set Y variable to Height.
7. Set Color variable to Position2.
8. Add Points element.
9. Configure Points legend.

Example 1744

Summary: Creates a variability chart with nested factors using operator and part configurations, displaying standard deviation charts in Graph Builder.

Code:

Open("data_table.jmp");
:Position2 << set property( "missing value codes", {"o"} );
Graph Builder(
    Size( 562, 406 ),
    Show Control Panel( 0 ),
    Variables( X( :Weight ), Y( :Height ), Color( :Position2 ) ),
    Elements( Points( X, Y, Legend( 6 ) ) ),
    SendToReport(
        Dispatch( {}, "Graph Builder", FrameBox,
            Add Pin Annotation(
                Seg( Marker Seg( 1 ) ),
                Index( 5 ),
                Index Row( 5 ),
                UniqueID( 707878277 ),
                FoundPt( {300, 161} ),
                Origin( {224.787644787645, 74.9767441860465} )
            )
        )
    )
);

Code Explanation:

1. Open data table;
2. Set missing value code for Position2.
3. Launch Graph Builder.
4. Configure graph size.
5. Hide control panel.
6. Define variables: X, Y, Color.
7. Add points element.
8. Send report to Graph Builder.
9. Add pin annotation to graph.
10. Customize pin annotation properties.

Example 1745

Summary: Creates a variability chart with nested factors using Graph Builder, specifying X variables and adding points elements with legend positions.

Code:

dt = Open("data_table.jmp");
gb = dt << Graph Builder(
    Variables( X( :sex ), X( :sports ) ),
    Elements( Position( 1, 1 ), Points( X, Legend( 20 ) ) ),
    Elements( Position( 2, 1 ), Points( X, Legend( 21 ) ) ),
    Local Data Filter(
        Add Filter( columns( :name ), Where( :name == {"KATIE", "LOUISE"} ), Display( :name, N Items( 15 ), Find( Set Text( "" ) ) ) )
    )
);

Code Explanation:

1. Open table.
2. Create Graph Builder.
3. Set X variables.
4. Add first points element.
5. Add second points element.
6. Add local data filter.
7. Define filter columns.
8. Set filter conditions.
9. Display filter settings.
10. Configure legend positions.

Example 1746

Summary: Creates a variability chart with nested factors using operator and part configurations, displaying standard deviation charts.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 609, 1000 ),
    Show Control Panel( 0 ),
    Variables( Y( :Vehicle Category ), Size( :"Weight (pounds)"n ) ),
    Elements( Points( Y, Set Shape Column( :"Weight (pounds)"n ) ) )
);
Graph Builder(
    Size( 608, 636 ),
    Show Control Panel( 0 ),
    Variables( Y( :Vehicle Category ) ),
    Elements( Points( Y, Set Shape Column( :Model ) ) )
);
Graph Builder(
    Size( 472, 511 ),
    Show Control Panel( 0 ),
    Variables( Y( :Vehicle Category ), Size( :"Weight (pounds)"n ) ),
    Elements( Points( Y, Legend( 2 ) ) ),
    SendToReport(
        Dispatch( {}, "400", ScaleBox, {Legend Model( 2, Properties( 1, {Marker( "FilledWide" )}, Item ID( "Vehicle Category", 1 ) ) )} )
    )
);

Code Explanation:

1. Open data table;
2. Create first graph builder window.
3. Set graph size.
4. Hide control panel.
5. Define Y variable.
6. Define size variable.
7. Add points element.
8. Set shape column for points.
9. Create second graph builder window.
10. Set graph size.
11. Hide control panel.
12. Define Y variable.
13. Add points element.
14. Set shape column for points.
15. Create third graph builder window.
16. Set graph size.
17. Hide control panel.
18. Define Y variable.
19. Define size variable.
20. Add points element.
21. Add legend to graph.
22. Customize legend properties.

Example 1747

Summary: Creates a variability chart with nested factors using Graph Builder, displaying cumulative probability and standard deviation charts.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 524, 450 ),
    Show Control Panel( 0 ),
    Variables(
        X( Transform Column( "Cumulative Probability[height]", Formula( Col Rank( :height ) / (Col Number( :height ) + 1) ) ) ),
        Y( :height )
    ),
    Elements( Points( X, Y, Legend( 3 ) ), Smoother( X, Y, Legend( 4 ) ) ),
    SendToReport(
        Dispatch( {}, "Cumulative Probability[height]", ScaleBox,
            {Scale( "Normal Probability" ), Format( "Best", 12 ), Min( 0.024390243902439 ), Max( 0.975609756097561 ), Inc( 0.1 ),
            Minor Ticks( 1 )}
        )
    )
);

Code Explanation:

1. Open data table;
2. Create new graph builder window.
3. Set graph size to 524x450.
4. Hide control panel.
5. Define X variable as cumulative probability.
6. Define Y variable as height.
7. Add points element to graph.
8. Add smoother element to graph.
9. Customize X axis to normal probability scale.
10. Adjust X axis format and limits.

Example 1748

Summary: Creates a variability chart with nested factors using Graph Builder, displaying standard deviation charts and ordering X by Salary (1997) in descending order.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 528, 464 ),
    Show Control Panel( 0 ),
    Variables( X( :Region, Order By( :Name( "Salary (1997)" ), Descending, Order Statistic( "Max" ) ) ), Y( :Name( "Salary (1997)" ) ) ),
    Elements( Points( X, Y, Legend( 5 ) ) )
);

Code Explanation:

1. Open data table;
2. Create Graph Builder object.
3. Set graph size.
4. Hide control panel.
5. Define X variable.
6. Order X by Salary (1997).
7. Use maximum order statistic.
8. Sort in descending order.
9. Define Y variable.
10. Add points element.

Example 1749

Summary: Creates a graph builder with nested factors using operator and part configurations, displaying standard deviation charts.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 528, 464 ),
    Show Control Panel( 0 ),
    Variables( X( :Region, Order By( :Name( "Salary (1997)" ), Descending, Order Statistic( "Mean" ) ) ), Y( :Name( "Salary (1997)" ) ) ),
    Elements( Points( X, Y, Legend( 4 ) ) )
);

Code Explanation:

1. Open data table;
2. Launch Graph Builder.
3. Set graph size.
4. Hide control panel.
5. Define X variable.
6. Order X by mean salary.
7. Set Y variable.
8. Add points element.
9. Assign legend to points.
10. Display graph.

Example 1750

Summary: Creates a graph builder window with a points element to visualize salary data, utilizing Graph Builder and specifying X and Y variables.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 528, 464 ),
    Show Control Panel( 0 ),
    Variables( X( :Region, Order By( :Name( "Salary (1997)" ), Descending, Order Statistic( "Min" ) ) ), Y( :Name( "Salary (1997)" ) ) ),
    Elements( Points( X, Y, Legend( 6 ) ) )
);

Code Explanation:

1. Open data table;
2. Create Graph Builder window.
3. Set window size.
4. Hide control panel.
5. Define X variable.
6. Order by Salary (1997).
7. Use descending order.
8. Use minimum order statistic.
9. Define Y variable.
10. Add points element.

Example 1751

Summary: Creates a graph builder window with nested factors using operator and part configurations, displaying standard deviation charts.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 525, 452 ),
    Show Control Panel( 0 ),
    Variables( X( :weight ), Y( :height ), Overlay( :sex ), Color( :age ) ),
    Elements( Points( X, Y ) )
);

Code Explanation:

1. Open data table;
2. Create Graph Builder window.
3. Set window size.
4. Hide control panel.
5. Define X variable.
6. Define Y variable.
7. Define overlay variable.
8. Define color variable.
9. Add points element.
10. Display graph.

Example 1752

Summary: Creates a variability chart with nested factors using operator and part configurations, displaying standard deviation charts in Graph Builder.

Code:

Open("data_table.jmp");
Graph Builder( Size( 528, 464 ), Show Control Panel( 0 ), Variables( X( :name ), Y( :height ) ), Elements( Points( X, Y, Legend( 3 ) ) ) );

Code Explanation:

1. Open data table;
2. Launch Graph Builder.
3. Set window size.
4. Hide control panel.
5. Assign X variable.
6. Assign Y variable.
7. Add points element.
8. Configure legend.

Example 1753

Summary: Creates a graph builder with nested factors using operator and part configurations, displaying standard deviation charts.

Code:

Open("data_table.jmp");
Graph Builder(
    Variables( X( :Close ), Size( :Volume ) ),
    Elements( Points( X, Legend( 4 ), Jitter( "Random Normal" ), Jitter Limit( 1.1429 ) ) ),
    SendToReport(
        Dispatch( {}, "400", ScaleBox,
            {Legend Model(
                4,
                Properties( 0, {Marker( "Circle" ), Marker Size( 6 )} ),
                Properties( 1, {Marker( "Circle" ), Marker Size( 6 )} )
            )}
        ),
        Dispatch( {}, "400", LegendBox, {Set Title( "" )} )
    )
);

Code Explanation:

1. Open data table;
2. Create Graph Builder object.
3. Set X variable to Close.
4. Set Size variable to Volume.
5. Add Points element.
6. Apply Random Normal jitter.
7. Set Jitter Limit to 1.1429.
8. Customize legend properties.
9. Remove legend title.
10. Display graph.

Example 1754

Summary: Creates a variability chart with nested factors using operator and part configurations, displaying standard deviation charts in Graph Builder.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 534, 454 ),
    Show Control Panel( 0 ),
    Variables( X( :height ), Y( :weight ), Color( :age ) ),
    Elements( Points( X, Y, Legend( 14 ) ) ),
    SendToReport(
        Dispatch( {}, "400", ScaleBox,
            {Legend Model(
                14,
                Properties( 0, {Marker( "Triangle" )} ),
                Properties( 1, {Marker( "Wide" )} ),
                Properties( 2, {Marker( "Tall" )} ),
                Properties( 3, {Marker( "Square" )} ),
                Properties( 4, {Marker( "Y" )} ),
                Properties( 5, {Marker( "Plus" )} )
            )}
        )
    )
);

Code Explanation:

1. Open data table.
2. Create Graph Builder.
3. Set graph size.
4. Hide control panel.
5. Assign variables: X, Y, Color.
6. Add points element.
7. Send report to Graph Builder.
8. Dispatch to scale box.
9. Set legend model properties.
10. Define marker shapes for each property.

Example 1755

Summary: Creates a variability chart with nested factors using operator and part configurations, displaying standard deviation charts.

Code:

Open("data_table.jmp");
Graph Builder(
    Transform Column( "Transform[Longitude]", Nominal, Formula( 1 ) ),
    Size( 667, 593 ),
    Variables( Y( :"Transform[Longitude]"n ) ),
    Elements( Points( Y, Legend( 2 ), Set Shape Column( :Photo ) ) ),
    SendToReport(
        Dispatch( {}, "400", ScaleBox, {Legend Model( 2, Properties( 0, {Marker Size( 15 )}, Item ID( "Transform[Longitude]", 1 ) ) )} )
    )
);

Code Explanation:

1. Open data table.
2. Create new column "Transform[Longitude]".
3. Set column type to Nominal.
4. Apply formula to new column.
5. Initialize Graph Builder.
6. Set window size.
7. Add Y variable.
8. Add Points element.
9. Set shape column.
10. Adjust legend properties.

Example 1756

Summary: Creates a variability chart with nested factors using Graph Builder, displaying standard deviation charts for weight and height variables.

Code:

Open("data_table.jmp");
Graph Builder(
    show control panel( 0 ),
    Variables( X( :weight ), X( :height ) ),
    Elements( Position( 1, 1 ), Points( X, Legend( 6 ), Jitter( 1 ) ) ),
    Elements( Position( 2, 1 ), Points( X, Legend( 7 ), Jitter( 1 ) ) )
);

Code Explanation:

1. Open data table;
2. Create new graph builder.
3. Hide control panel.
4. Set X variables: weight, height.
5. Add points element for weight.
6. Set legend for weight points.
7. Enable jitter for weight points.
8. Add points element for height.
9. Set legend for height points.
10. Enable jitter for height points.

Example 1757

Summary: Creates a graph builder with nested factors using operator and part configurations, displaying standard deviation charts.

Code:

Open("data_table.jmp");
Graph Builder(
    Show Control Panel( 0 ),
    Variables( X( :height ), Y( :weight ), Overlay( :age ), Color( :sex ) ),
    Elements( Points( X, Y ) )
);

Code Explanation:

1. Open data table;
2. Launch Graph Builder.
3. Hide control panel.
4. Set X variable: height.
5. Set Y variable: weight.
6. Overlay by age.
7. Color by sex.
8. Add points element.
9. Display graph.

Example 1758

Summary: Creates two Graph Builder windows to visualize relationships between height, weight, and age, with sex as a color variable.

Code:

Open("data_table.jmp");
Graph Builder(
    Show Control Panel( 0 ),
    Variables( X( :height ), Y( :weight ), Overlay( :age ), Color( :sex ) ),
    Elements( Points( X, Y ) )
);
Graph Builder(
    Size( 510, 254 ),
    Show Control Panel( 0 ),
    Variables( X( :height ), Y( :weight ), Overlay( :age ), Color( :height ) ),
    Elements( Points( X, Y ) )
);

Code Explanation:

1. Open data table;
2. Create first Graph Builder window.
3. Hide control panel.
4. Set X to height.
5. Set Y to weight.
6. Overlay by age.
7. Color by sex.
8. Add points element.
9. Create second Graph Builder window.
10. Set size to 510x254.

Example 1759

Summary: Creates a variability chart with nested factors using Graph Builder, displaying standard deviation charts and customizing X-scale reference lines.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 528, 464 ),
    Show Control Panel( 0 ),
    Variables( X( :age ), X( :sex, Position( 1 ) ), Y( :height ) ),
    Elements( Points( X( 1 ), X( 2 ), Y, Legend( 1 ), Jitter( 0 ) ) ),
    SendToReport(
        Dispatch( {}, "age", ScaleBox,
            {Add Ref Line( 1.5, "Solid", "Gray", "", 1 ), Add Ref Line( 3.5, "Solid", "Gray", "", 1 ),
            Add Ref Line( 5.5, "Solid", "Gray", "", 1 ), Add Ref Line( 7.5, "Solid", "Gray", "", 1 ),
            Add Ref Line( 9.5, "Solid", "Gray", "", 1 ), Label Row( 2, Show Major Ticks( 0 ) )}
        )
    )
);

Code Explanation:

1. Open data table;
2. Create Graph Builder window.
3. Set window size.
4. Hide control panel.
5. Define X variables.
6. Define Y variable.
7. Add points element.
8. Customize X scale.
9. Add reference lines.
10. Configure axis ticks.

Example 1760

Summary: Creates a variability chart with nested factors using Graph Builder, displaying standard deviation charts and median summary statistics.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 467, 341 ),
    Show Control Panel( 0 ),
    Variables( Y( :height ), Overlay( :age ) ),
    Elements( Points( Y, Legend( 3 ), Summary Statistic( "Median" ) ) )
);

Code Explanation:

1. Open data table;
2. Create new Graph Builder window.
3. Set window size.
4. Hide control panel.
5. Define Y variable.
6. Define overlay variable.
7. Add points element.
8. Set summary statistic to median.
9. Assign legend to third position.

Example 1761

Summary: Creates a Graph Builder window with a nested variability chart, using the Cut variable as X-axis and Carat Weight as Y-axis, sized by Count.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 526, 448 ),
    Show Control Panel( 0 ),
    Variables( X( :Cut, Size By( "Count" ) ), Y( :Carat Weight ) ),
    Elements( Points( X, Y, Legend( 5 ) ) )
);

Code Explanation:

1. Open data table;
2. Create Graph Builder window.
3. Set window size 526x448.
4. Hide control panel.
5. Set X variable: Cut.
6. Size points by Count.
7. Set Y variable: Carat Weight.
8. Add Points element.
9. Assign legend position 5.
10. Display graph.

Example 1762

Summary: Creates a graph builder object with points and smoother elements to visualize height and weight data for individuals aged 12, utilizing Graph Builder.

Code:

dt = Open("data_table.jmp");
dt << select where( :age == 12 );
dt << hide;
Graph Builder(
    Show Control Panel( 0 ),
    Variables( X( :height ), Y( :weight ) ),
    Elements( Points( X, Y, Legend( 1 ) ), Smoother( X, Y, Legend( 2 ) ) )
);

Code Explanation:

1. Open data table.
2. Select rows where age is 12.
3. Hide selected rows.
4. Create graph builder object.
5. Disable control panel.
6. Set X variable to height.
7. Set Y variable to weight.
8. Add points element.
9. Add smoother element.
10. Display graph.

Example 1763

Summary: Creates a variability chart with nested factors using operator and part configurations, displaying standard deviation charts in JMP.

Code:

dt = Open("data_table.jmp");
gb = dt << Graph Builder(
    Size( 522, 444 ),
    Show Control Panel( 0 ),
    Variables( X( :age ), Y( :height ), Overlay( :sex ) ),
    Elements(
        Points( X, Y, Legend( 4 ), Summary Statistic( "Mean" ), Label( "Label by Value" ), Label Format( "Best", 5 ) ),
        Line( X, Y, Legend( 7 ) )
    ),
    SendToReport(
        Dispatch( {}, "Graph Builder", FrameBox,
            {DispatchSeg(
                Marker Seg( "Marker (F)" ),
                Label Offset( {2, -2, 19, 2, 62.6}, {3, -2, -12, 3, 63}, {4, 1, -9, 4, 62.5}, {0, -10, -7, 0, 58.6}, {1, 4, 12, 1, 59} )
            ), DispatchSeg(
                Marker Seg( "Marker (M)" ),
                Label Offset( {3, 12, 2, 3, 65.2}, {2, -9, -10, 2, 65.2857142857143}, {4, 3, 14, 4, 68}, {0, 5, 10, 0, 57.3333333333333} )
            )}
        )
    )
);

Code Explanation:

1. Open data table.
2. Create Graph Builder object.
3. Set graph size.
4. Hide control panel.
5. Assign variables: X=age, Y=height, Overlay=sex.
6. Add points element with mean summary statistic.
7. Label points by value.
8. Set label format.
9. Add line element.
10. Adjust marker labels for each sex.

Example 1764

Summary: Creates two variability charts with nested factors using operator and part configurations, displaying standard deviation charts for data analysis.

Code:

dt = Open("data_table.jmp");
gb = dt << Graph Builder(
    Size( 522, 444 ),
    Show Control Panel( 0 ),
    Variables( X( :age ), Y( :height ), Overlay( :sex ) ),
    Elements(
        Points( X, Y, Legend( 4 ), Summary Statistic( "Mean" ), Label( "Label by Value" ), Label Format( "Best", 5 ) ),
        Line( X, Y, Legend( 7 ) )
    ),
    SendToReport(
        Dispatch( {}, "Graph Builder", FrameBox,
            {DispatchSeg(
                Marker Seg( "Marker (F)" ),
                Label Offset( {2, -2, 19, 2, 62.6}, {3, -2, -12, 3, 63}, {4, 1, -9, 4, 62.5}, {0, -10, -7, 0, 58.6}, {1, 4, 12, 1, 59} )
            ), DispatchSeg(
                Marker Seg( "Marker (M)" ),
                Label Offset( {3, 12, 2, 3, 65.2}, {2, -9, -10, 2, 65.2857142857143}, {4, 3, 14, 4, 68}, {0, 5, 10, 0, 57.3333333333333} )
            )}
        )
    )
);
dt2 = Open("data_table.jmp");
gb2 = dt2 << Graph Builder(
    Size( 522, 444 ),
    Show Control Panel( 0 ),
    Variables( X( :Pie Type ), Y( :"Sales (K)"n, Side( "Right" ) ), Y( :Outlets, Position( 1 ) ) ),
    Elements(
        Points( X, Y( 2 ), Legend( 3 ), Summary Statistic( "Mean" ), Label( "Label by Value" ) ),
        Points( X, Y( 1 ), Legend( 4 ), Summary Statistic( "Mean" ), Label( "Label by Value" ) )
    ),
    SendToReport(
        Dispatch( {}, "Sales (K)", ScaleBox, {Format( "Currency", "USD", Use thousands separator( 0 ), 12, 0 )} ),
        Dispatch( {}, "400", ScaleBox, {Legend Model( 4, Properties( 0, {Marker( "Circle" )}, Item ID( "Mean(Sales (K))", 1 ) ) )} )
    )
);

Code Explanation:

1. Open data table;
2. Create Graph Builder object.
3. Set graph size.
4. Hide control panel.
5. Define X, Y, and overlay variables.
6. Add points element with mean summary statistic.
7. Add line element.
8. Adjust label offsets for markers.
9. Open data table;
10. Create second Graph Builder object.

Example 1765

Summary: Creates a graph builder with points element to visualize the relationship between age and height, while setting value labels for the height variable.

Code:

Open("data_table.jmp");
:height << set property( "Value Labels", {65 <= "top quartile" <= 70} );
Graph Builder( Show Control Panel( 0 ), Variables( X( :age ), Y( :height ) ), Elements( Points( X, Y ) ) );

Code Explanation:

1. Open data table;
2. Set height value labels.
3. Create Graph Builder.
4. Hide control panel.
5. Set X variable to age.
6. Set Y variable to height.
7. Add points element.

Example 1766

Summary: Creates a variability chart with nested factors using operator and part configurations, displaying standard deviation charts in JMP.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 570, 474 ),
    Show Control Panel( 0 ),
    Variables(
        X( :AGE ),
        Y( :ADR DURATION ),
        Group X( :SEX ),
        Group X( :TREATMENT GROUP ),
        Group Y( :ADR SEVERITY ),
        Group Y( :TOTAL DAILY DOSE ),
        Overlay( :DAY ON DRUG )
    ),
    Elements( Points( X, Y, Legend( 7 ) ) )
);

Code Explanation:

1. Open data table.
2. Initialize Graph Builder.
3. Set graph size.
4. Hide control panel.
5. Define X variable.
6. Define Y variable.
7. Group X by SEX.
8. Group X by TREATMENT GROUP.
9. Group Y by ADR SEVERITY.
10. Group Y by TOTAL DAILY DOSE.
11. Overlay by DAY ON DRUG.
12. Add points element.

Example 1767

Summary: Creates a variability chart with nested factors using Graph Builder, displaying standard deviation charts and mean summary statistics.

Code:

dt = Open("data_table.jmp");
gb = Graph Builder(
    Size( 450, 320 ),
    Show Control Panel( 0 ),
    Variables( X( :age ), Y( :height ) ),
    Elements( Points( X, Y, Legend( 1 ), Jitter( 0 ), Summary Statistic( "Mean" ), Error Bars( "Standard Deviation" ) ) )
);

Code Explanation:

1. Open data_table data
2. Create Graph Builder object.
3. Set graph size to 450x320.
4. Hide control panel.
5. Assign X variable: age.
6. Assign Y variable: height.
7. Add points element.
8. Enable legend for points.
9. Disable jitter.
10. Display mean summary statistic.
11. Show standard deviation error bars.

Example 1768

Summary: Creates a variability chart with nested factors using Graph Builder, displaying standard deviation charts and enabling legend for points.

Code:

dt = Open("data_table.jmp");
gb = Graph Builder(
    Size( 450, 320 ),
    Show Control Panel( 0 ),
    Variables( X( :age ), Y( :height ) ),
    Elements( Points( X, Y, Legend( 1 ), Jitter( 0 ), Summary Statistic( "Mean" ), Error Bars( "Standard Error" ) ) )
);

Code Explanation:

1. Open data table;
2. Create Graph Builder.
3. Set size 450x320.
4. Hide control panel.
5. Set X variable to age.
6. Set Y variable to height.
7. Add points element.
8. Enable legend for points.
9. Disable jitter.
10. Add mean summary statistic.
11. Add standard error error bars.

Example 1769

Summary: Creates a variability chart with nested factors using Graph Builder, displaying standard deviation charts and enabling legend.

Code:

dt = Open("data_table.jmp");
gb = Graph Builder(
    Size( 450, 320 ),
    Show Control Panel( 0 ),
    Variables( X( :age ), Y( :height ) ),
    Elements( Points( X, Y, Legend( 1 ), Jitter( 0 ), Summary Statistic( "Mean" ), Error Bars( "Range" ) ) )
);

Code Explanation:

1. Open table.
2. Create graph builder.
3. Set size.
4. Hide control panel.
5. Define X variable.
6. Define Y variable.
7. Add points element.
8. Enable legend.
9. Disable jitter.
10. Add mean summary.

Example 1770

Summary: Creates a variability chart with nested factors using Graph Builder, displaying standard deviation charts and enabling legend for points.

Code:

dt = Open("data_table.jmp");
gb = Graph Builder(
    Size( 450, 320 ),
    Show Control Panel( 0 ),
    Variables( X( :age ), Y( :height ) ),
    Elements( Points( X, Y, Legend( 1 ), Jitter( 0 ), Summary Statistic( "% of Total" ) ) )
);

Code Explanation:

1. Open data table.
2. Create Graph Builder object.
3. Set graph size.
4. Hide control panel.
5. Assign X variable.
6. Assign Y variable.
7. Add points element.
8. Enable legend for points.
9. Disable jittering.
10. Use percentage of total summary statistic.

Example 1771

Summary: Creates a variability chart with nested factors using Graph Builder, displaying standard deviation charts and enabling jittering for visualizing data distribution.

Code:

dt = Open("data_table.jmp");
gb = Graph Builder(
    Size( 450, 320 ),
    Show Control Panel( 0 ),
    Variables( X( :age ), Y( :height ), Group X( :sex ) ),
    Elements( Points( X, Y, Legend( 1 ), Jitter( 0 ), Summary Statistic( "% of Total" ) ) )
);

Code Explanation:

1. Open data table.
2. Create Graph Builder object.
3. Set graph size.
4. Hide control panel.
5. Assign variables for axes.
6. Add group variable.
7. Define points element.
8. Enable jittering.
9. Set summary statistic.
10. Display graph.

Example 1772

Summary: Creates a variability chart with nested factors using Graph Builder, displaying standard deviation charts and configuring graph settings.

Code:

dt = Open("data_table.jmp");
gb = Graph Builder(
    Size( 450, 320 ),
    Show Control Panel( 0 ),
    Variables( X( :sex ), Y( :height ), Group X( :age ) ),
    Elements( Points( X, Y, Legend( 1 ), Jitter( 0 ), Summary Statistic( "% of Total" ) ) )
);

Code Explanation:

1. Open data table.
2. Create Graph Builder object.
3. Set graph size.
4. Hide control panel.
5. Define X variable.
6. Define Y variable.
7. Define group X variable.
8. Add points element.
9. Set legend for points.
10. Disable jitter.

Example 1773

Summary: Creates a variability chart with nested factors using Graph Builder, displaying standard deviation charts and mean summary statistics.

Code:

dt = Open("data_table.jmp");
gb = Graph Builder(
    Size( 450, 320 ),
    Show Control Panel( 0 ),
    Variables( X( :age ), Y( :height ) ),
    Elements( Points( X, Y, Legend( 1 ), Jitter( 0 ), Summary Statistic( "Mean" ), Error Bars( "Confidence Interval" ) ) )
);

Code Explanation:

1. Open data table.
2. Create Graph Builder object.
3. Set graph size to 450x320.
4. Hide control panel.
5. Set X variable to age.
6. Set Y variable to height.
7. Add points element.
8. Enable legend for points.
9. Disable jitter.
10. Display mean summary statistic.
11. Add confidence interval error bars.

Example 1774

Summary: Creates a variability chart with nested factors using Graph Builder, displaying standard deviation charts for height and weight vs age.

Code:

Open("data_table.jmp");
gb = Graph Builder(
    Size( 422, 324 ),
    show control panel( 0 ),
    Variables( Y( :height ), Y( :weight ), Color( :age ) ),
    Elements( Position( 1, 1 ), Points( Y, Legend( 1 ), Jitter( 0 ) ) ),
    Elements( Position( 1, 2 ), Points( Y, Legend( 2 ), Jitter( 0 ) ) )
);

Code Explanation:

1. Open data table;
2. Create Graph Builder object.
3. Set window size.
4. Hide control panel.
5. Define Y variables.
6. Add first points element.
7. Add second points element.
8. Plot height vs age.
9. Plot weight vs age.
10. Display graph.

Example 1775

Summary: Creates a variability chart with nested factors using Graph Builder, displaying standard deviation charts and configuring graph size and control panel.

Code:

dt = Open("data_table.jmp");
gb = Graph Builder(
    Size( 422, 324 ),
    show control panel( 0 ),
    Variables( Y( :height ), Y( :weight ), Color( :age ) ),
    Elements( Position( 1, 1 ), Points( Y, Legend( 1 ), Jitter( 0 ) ) ),
    Elements( Position( 1, 2 ), Points( Y, Legend( 2 ), Jitter( 0 ) ) )
);
gb2 = gb << Redo Analysis;

Code Explanation:

1. Open data table;
2. Create Graph Builder object.
3. Set graph size to 422x324.
4. Hide control panel.
5. Assign height and weight to Y axes.
6. Assign age to color variable.
7. Add first set of points element.
8. Add second set of points element.
9. Redo analysis on graph builder.

Example 1776

Summary: Creates a variability chart with nested factors using Graph Builder, featuring a local data filter for age == 15.

Code:

dt = Open("data_table.jmp");
gb = Graph Builder(
    Size( 460, 400 ),
    show control panel( 0 ),
    Variables( Y( :height ) ),
    Elements( Points( Y, Legend( 1 ), Jitter( 1 ) ) ),
    Local Data Filter( Location( {1200, 159} ), Mode( Show( 0 ) ), Add Filter( columns( :age ), Where( :age == 15 ) ) )
);

Code Explanation:

1. Open data table;
2. Create new Graph Builder window.
3. Set graph size to 460x400.
4. Hide control panel.
5. Set Y variable to :height.
6. Add Points element with jitter.
7. Enable local data filter.
8. Position filter at {1200, 159}.
9. Set filter mode to hidden.
10. Add age filter for age == 15.

Example 1777

Summary: Creates a variability chart with nested factors using Graph Builder, hiding the control panel and setting Y variables for height and age.

Code:

dt = Open("data_table.jmp");
gb = Graph Builder(
    show control panel( 0 ),
    Variables( Y( :height ), Y( :age, Position( 1 ) ) ),
    Elements( Points( Y( 1 ), Y( 2 ), Legend( 1 ), Jitter( 1 ) ) )
);

Code Explanation:

1. Open data table.
2. Create Graph Builder object.
3. Hide control panel.
4. Set Y variables: height, age.
5. Position age on Y-axis.
6. Add points element.
7. Set first Y variable for points.
8. Set second Y variable for points.
9. Assign legend to points.
10. Enable jitter for points.

Example 1778

Summary: Creates a graph builder object to visualize data with nested factors, utilizing Graph Builder and hiding the control panel.

Code:

Open("data_table.jmp");
gb = Graph Builder( show control panel( 0 ), Variables( X( :age, Order By( :weight, Ascending ) ), Y( :height ), Group X( :sex ) ) );

Code Explanation:

1. Open data table;
2. Create Graph Builder object.
3. Hide control panel.
4. Set X variable to :age.
5. Order :age by :weight ascending.
6. Set Y variable to :height.
7. Group X by :sex.

Example 1779

Summary: Creates a variability chart with nested factors using Graph Builder, displaying standard deviation charts and grouping X-axis by sex.

Code:

dt = Open("data_table.jmp");
gb = Graph Builder( show control panel( 0 ), Variables( X( :age, Order By( :weight, Ascending ) ), Y( :height ), Group X( :sex ) ) );

Code Explanation:

1. Open data table.
2. Create Graph Builder object.
3. Hide control panel.
4. Set X variable to age.
5. Order age by weight ascending.
6. Set Y variable to height.
7. Group X by sex.

Example 1780

Summary: Creates a graph builder with points element to visualize age vs height data, hiding the control panel and displaying a legend.

Code:

Open("data_table.jmp");
gb = Graph Builder( Show Control Panel( 0 ), Variables( X( :age ), Y( :height ) ), Elements( Points( X, Y, Legend( 3 ) ) ) );

Code Explanation:

1. Open data table;
2. Create Graph Builder object.
3. Hide control panel.
4. Set X variable to age.
5. Set Y variable to height.
6. Add points element.
7. Assign legend to points.

Example 1781

Summary: Creates a graph with points and legend, using Graph Builder to visualize age vs. height data from an open JMP data table.

Code:

dt = Open("data_table.jmp");
gb = Graph Builder( Show Control Panel( 0 ), Variables( X( :age ), Y( :height ) ), Elements( Points( X, Y, Legend( 3 ) ) ) );
Report( gb )[GraphBuilderContainerBox( 1 )] << Append( Text Box( "Test" ) );

Code Explanation:

1. Open data table.
2. Create Graph Builder object.
3. Hide control panel.
4. Set X variable to age.
5. Set Y variable to height.
6. Add points element.
7. Set legend index to 3.
8. Access graph report.
9. Append text box to graph.
10. Insert text "Test".

Example 1782

Summary: Creates a variability chart with nested factors using Graph Builder, displaying standard deviation charts and configuring legend model properties.

Code:

dt = Open("data_table.jmp");
gb = Graph Builder(
    Show Control Panel( 0 ),
    Y Group Title Orientation( "Horizontal" ),
    Y Group Level Orientation( "Horizontal" ),
    Variables( X( :age ), Y( :height ), Group X( :sex ), Group Y( :sex ), Color( :age ) ),
    Elements( Line( X, Y, Legend( 2 ), Row order( 0 ), Summary Statistic( "Mean" ) ) ),
    SendToReport(
        Dispatch( {}, "400", ScaleBox,
            {Legend Model(
                2,
                Properties( 0, {Line Width( 5 )} ),
                Properties( 1, {Line Width( 5 )} ),
                Properties( 2, {Line Width( 5 )} ),
                Properties( 3, {Line Width( 5 )} ),
                Properties( 4, {Line Width( 5 )} ),
                Properties( 5, {Line Width( 5 )} )
            )}
        )
    )
);

Code Explanation:

1. Open data table;
2. Create Graph Builder object.
3. Hide control panel.
4. Set Y group title orientation.
5. Set Y group level orientation.
6. Define variables for axes and groups.
7. Add line element with mean summary statistic.
8. Send report to Graph Builder.
9. Dispatch to ScaleBox for legend model.
10. Set line width properties for legend items.

Example 1783

Summary: Creates a variability chart with nested factors using Graph Builder, hiding the control panel and customizing legend markers.

Code:

Open("data_table.jmp");
Graph Builder(
    Show Control Panel( 0 ),
    Categorical Color Theme( "Jet" ),
    Variables( X( :height ), Y( :age ), Group X( :sex ), Overlay( :height ) ),
    Elements( Points( X, Y, Legend( 1 ), Jitter( 1 ) ) ),
    SendToReport(
        Dispatch( {}, "400", ScaleBox,
            {Legend Model(
                1,
                Properties( 0, {Marker( "Circle" )} ),
                Properties( 1, {Marker( "Star" )} ),
                Properties( 2, {Marker( "Triangle" )} ),
                Properties( 3, {Marker( "Filled Up Triangle" )} ),
                Properties( 4, {Marker( "Diamond" )} )
            )}
        ),
        Dispatch( {}, "Graph Builder", FrameBox, {Marker Size( 5 )} ),
        Dispatch( {}, "Graph Builder", FrameBox( 2 ), {Marker Size( 5 )} )
    )
);

Code Explanation:

1. Open data table.
2. Create Graph Builder object.
3. Hide control panel.
4. Set categorical color theme.
5. Define variables for axes and grouping.
6. Add points element with jitter.
7. Customize legend markers.
8. Set marker size for primary frame.
9. Set marker size for secondary frame.
10. Display graph.

Example 1784

Summary: Creates a variability chart with nested factors using Graph Builder, featuring line and point elements with customized legend markers.

Code:

dt = Open("data_table.jmp");
Graph Builder(
    Show Control Panel( 0 ),
    Categorical Color Theme( "White to Red" ),
    Variables( X( :age ), Y( :height ), Overlay( :sex ) ),
    Elements( Line( X, Y, Legend( 3 ), Row order( 0 ), Summary Statistic( "Mean" ) ), Points( X, Y, Legend( 4 ), Jitter( 1 ) ) ),
    SendToReport(
        Dispatch( {}, "400", ScaleBox,
            {Legend Model(
                4,
                Base( 0, 0, 0 ),
                Base( 1, 0, 1 ),
                Properties( 0, {Marker( "Plus" )} ),
                Properties( 1, {Marker( "Square" )} )
            )}
        ),
        Dispatch( {}, "400", LegendBox, {Legend Position( {-1, -1, 0, 1} )} )
    )
);

Code Explanation:

1. Open data table.
2. Create Graph Builder object.
3. Hide control panel.
4. Set color theme.
5. Define variables for axes and overlay.
6. Add line element with mean summary.
7. Add points element with jitter.
8. Customize legend markers.
9. Adjust legend position.

Example 1785

Summary: Creates a variability chart with nested factors using Graph Builder, hiding the control panel and displaying standard deviation charts.

Code:

dt = Open("data_table.jmp");
gb = Graph Builder(
    show control panel( 0 ),
    Variables( X( :weight ), Y( :height ), Overlay( :age ), Color( :sex ) ),
    Elements( Points( X, Y, Color, Legend( 1 ) ), Line( X, Y, Color, Legend( 3 ), Row order( 0 ), Summary Statistic( "Mean" ) ) )
);

Code Explanation:

1. Open data table.
2. Create graph builder object.
3. Hide control panel.
4. Set X variable: weight.
5. Set Y variable: height.
6. Set overlay variable: age.
7. Set color variable: sex.
8. Add points element.
9. Add line element with mean summary.
10. Display graph builder.

Example 1786

Summary: Creates a variability chart with nested factors using Graph Builder, hiding the control panel and setting X to weight, Y to height, and overlay to age.

Code:

dt = Open("data_table.jmp");
gb = Graph Builder(
    show control panel( 0 ),
    Variables( X( :weight ), Y( :height ), Overlay( :age ) ),
    Elements( Points( X, Y, Legend( 1 ) ), Line( X, Y, Legend( 3 ), Row order( 0 ), Summary Statistic( "Mean" ) ) )
);

Code Explanation:

1. Open data table.
2. Create Graph Builder object.
3. Hide control panel.
4. Set X variable to weight.
5. Set Y variable to height.
6. Use age for overlay.
7. Add points element.
8. Add line element.
9. Set line legend to 3.
10. Order rows normally.

Example 1787

Summary: Creates a variability chart with nested factors using Graph Builder, displaying standard deviation charts and hiding the control panel.

Code:

dt = Open("data_table.jmp");
gb = Graph Builder(
    show control panel( 0 ),
    Variables( X( :weight ), Y( :height ), Color( :sex ) ),
    Elements( Points( X, Y, Color, Legend( 1 ) ), Line( X, Y, Color, Legend( 3 ), Row order( 0 ), Summary Statistic( "Mean" ) ) )
);

Code Explanation:

1. Open data table;
2. Create Graph Builder object.
3. Hide control panel.
4. Set X variable: weight.
5. Set Y variable: height.
6. Set Color variable: sex.
7. Add Points element.
8. Add Line element.
9. Use row order for lines.
10. Display mean summary statistic.

Example 1788

Summary: Creates a graph builder with nested factors using Graph Builder, displaying points and standard deviation charts.

Code:

Open("data_table.jmp");
Graph Builder(
    Show Control Panel( 0 ),
    Grid Color( "Light Green" ),
    Grid Transparency( 0.3 ),
    Graph Spacing( 5 ),
    Spacing Borders( 1 ),
    Variables( X( :age ), Y( :height ), Y( :weight ) ),
    Elements( Position( 1, 1 ), Points( X, Y, Legend( 1 ) ) ),
    Elements( Position( 1, 2 ), Points( X, Y, Legend( 2 ) ) )
);

Code Explanation:

1. Open data table;
2. Create Graph Builder object.
3. Hide control panel.
4. Set grid color.
5. Adjust grid transparency.
6. Define graph spacing.
7. Set spacing borders.
8. Assign variables to axes.
9. Add first points element.
10. Add second points element.

Example 1789

Summary: Creates multiple Graph Builder windows with varying jitter settings for visualizing Petal length data.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 466, 292 ),
    Show Control Panel( 0 ),
    Variables( X( :Petal length ) ),
    Elements( Points( X, Legend( 2 ), Jitter( "None" ) ) )
);
Graph Builder( Size( 466, 292 ), Show Control Panel( 0 ), Variables( X( :Petal length ) ), Elements( Points( X, Legend( 2 ) ) ) );
Graph Builder(
    Size( 466, 292 ),
    Show Control Panel( 0 ),
    Variables( X( :Petal length ) ),
    Elements( Points( X, Legend( 2 ), Jitter( "Random Uniform" ) ) )
);
Graph Builder(
    Size( 466, 292 ),
    Show Control Panel( 0 ),
    Variables( X( :Petal length ) ),
    Elements( Points( X, Legend( 2 ), Jitter( "Random Normal" ) ) )
);
Graph Builder(
    Size( 466, 292 ),
    Show Control Panel( 0 ),
    Variables( X( :Petal length ) ),
    Elements( Points( X, Legend( 2 ), Jitter( "Packed" ) ) )
);
Graph Builder(
    Size( 466, 292 ),
    Show Control Panel( 0 ),
    Variables( X( :Petal length ) ),
    Elements( Points( X, Legend( 2 ), Jitter( "Centered Grid" ) ) )
);

Code Explanation:

1. Open data table;
2. Create Graph Builder window.
3. Set size to 466x292.
4. Hide control panel.
5. Set X variable to Petal length.
6. Add points element.
7. Create another Graph Builder window.
8. Set size to 466x292.
9. Hide control panel.
10. Set X variable to Petal length.
11. Add points element.
12. Create Graph Builder window.
13. Set size to 466x292.
14. Hide control panel.
15. Set X variable to Petal length.
16. Add points element with random uniform jitter.
17. Create Graph Builder window.
18. Set size to 466x292.
19. Hide control panel.
20. Set X variable to Petal length.
21. Add points element with random normal jitter.
22. Create Graph Builder window.
23. Set size to 466x292.
24. Hide control panel.
25. Set X variable to Petal length.
26. Add points element with packed jitter.
27. Create Graph Builder window.
28. Set size to 466x292.
29. Hide control panel.
30. Set X variable to Petal length.
31. Add points element with centered grid jitter.

Example 1790

Summary: Creates multiple variability charts with nested factors using different jitter options in Graph Builder, allowing for customizable visualization and analysis.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 466, 292 ),
    Show Control Panel( 0 ),
    Variables( X( :Petal length ) ),
    Elements( Points( X, Legend( 2 ), Jitter( "None" ) ) )
);
Graph Builder( Size( 466, 292 ), Show Control Panel( 0 ), Variables( X( :Petal length ) ), Elements( Points( X, Legend( 2 ) ) ) );
Graph Builder(
    Size( 466, 292 ),
    Show Control Panel( 0 ),
    Variables( X( :Petal length ) ),
    Elements( Points( X, Legend( 2 ), Jitter( "Random Uniform" ) ) )
);
Graph Builder(
    Size( 466, 292 ),
    Show Control Panel( 0 ),
    Variables( X( :Petal length ) ),
    Elements( Points( X, Legend( 2 ), Jitter( "Random Normal" ) ) )
);
Graph Builder(
    Size( 466, 292 ),
    Show Control Panel( 0 ),
    Variables( X( :Petal length ) ),
    Elements( Points( X, Legend( 2 ), Jitter( "Packed" ) ) )
);
Graph Builder(
    Size( 466, 292 ),
    Show Control Panel( 0 ),
    Variables( X( :Petal length ) ),
    Elements( Points( X, Legend( 2 ), Jitter( "Centered Grid" ) ) )
);
Graph Builder(
    Size( 466, 292 ),
    Show Control Panel( 0 ),
    Variables( X( :Petal length ) ),
    Elements( Points( X, Legend( 2 ), Jitter( "Positive Grid" ) ) )
);

Code Explanation:

1. Open data table;
2. Create Graph Builder.
3. Set size to 466x292.
4. Hide control panel.
5. Set X variable to Petal length.
6. Add points element.
7. Set legend to 2.
8. No jitter option.
9. Repeat steps 2-8.
10. Jitter type: Random Uniform.
11. Repeat steps 2-8.
12. Jitter type: Random Normal.
13. Repeat steps 2-8.
14. Jitter type: Packed.
15. Repeat steps 2-8.
16. Jitter type: Centered Grid.
17. Repeat steps 2-8.
18. Jitter type: Positive Grid.

Example 1791

Summary: Creates a variability chart with nested factors using operator and part configurations, displaying standard deviation charts in Graph Builder.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 483, 355 ),
    Show Control Panel( 0 ),
    Variables( X( :Operator ), X( :Part, Position( 1 ) ), Y( :Y ), Overlay( :Part ) ),
    Elements( Points( X( 1 ), X( 2 ), Y, Legend( 4 ), Summary Statistic( "Mean" ), Error Bars( "Range" ) ) )
);

Code Explanation:

1. Open data table;
2. Create new Graph Builder window.
3. Set window size.
4. Hide control panel.
5. Define X and Y variables.
6. Add overlay variable.
7. Add points element.
8. Set first X axis.
9. Set second X axis.
10. Display mean summary statistic.
11. Add range error bars.

Example 1792

Summary: Creates a variability chart with nested factors using Graph Builder, displaying standard deviation charts and summary statistics.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 265, 264 ),
    Show Control Panel( 0 ),
    Variables( X( :age ), Y( :height ) ),
    Elements(
        Points( X, Y, Legend( 7 ) ),
        Caption Box( X, Y, Legend( 8 ), Summary Statistic( "5 Number Summary" ), Y Position( "Bottom" ) )
    )
);

Code Explanation:

1. Open data table;
2. Launch Graph Builder.
3. Set graph size.
4. Hide control panel.
5. Assign X variable.
6. Assign Y variable.
7. Add points element.
8. Add caption box element.
9. Set summary statistic type.
10. Position caption box at bottom.

Example 1793

Summary: Creates a variability chart with nested factors using Graph Builder, displaying standard deviation charts and applying random uniform jitter.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 527, 252 ),
    Show Control Panel( 0 ),
    Variables( X( :age ), Y( :weight ), Overlay( :sex ) ),
    Elements( Points( X, Y, Legend( 5 ), Summary Statistic( "Mean" ), Jitter( "Random Uniform" ) ) )
);

Code Explanation:

1. Open data table.
2. Create Graph Builder object.
3. Set window size.
4. Hide control panel.
5. Define X variable.
6. Define Y variable.
7. Define overlay variable.
8. Add points element.
9. Set summary statistic to mean.
10. Apply random uniform jitter.

Example 1794

Summary: Creates a geographic map using Graph Builder, displaying points and smoother elements to visualize Latitude and Longitude data.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 526, 454 ),
    Show Control Panel( 0 ),
    Variables( X( :Longitude ), Y( :Latitude ) ),
    Elements( Points( X, Y, Legend( 5 ) ), Smoother( X, Y, Legend( 6 ) ) ),
    SendToReport( Dispatch( {}, "Graph Builder", FrameBox, {Background Color( 40 ), Background Map( Boundaries( "World" ) )} ) )
);

Code Explanation:

1. Open data table;
2. Launch Graph Builder.
3. Set window size.
4. Hide control panel.
5. Assign Longitude to X-axis.
6. Assign Latitude to Y-axis.
7. Add points element.
8. Add smoother element.
9. Set legend for points.
10. Set legend for smoother.

Example 1795

Summary: Creates a Graph Builder window with nested factors, displaying standard deviation charts and enabling legend for points.

Code:

Open("data_table.jmp");
:picture << Set Use for Marker;
Graph Builder(
    Size( 534, 454 ),
    Show Control Panel( 0 ),
    Variables( X( :height ), Y( :weight ) ),
    Elements( Points( X, Y, Legend( 5 ), Jitter Limit( 1.0826 ) ), Line Of Fit( X, Y, Legend( 7 ) ) )
);

Code Explanation:

1. Open data table;
2. Set picture column for markers.
3. Create Graph Builder window.
4. Set window size.
5. Hide control panel.
6. Assign X and Y variables.
7. Add points element.
8. Enable legend for points.
9. Apply jitter limit.
10. Add line of fit element.

Example 1796

Summary: Creates two Graph Builder windows with nested factors, displaying points and standard deviation charts, using operator and part configurations.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 495, 461 ),
    Show Control Panel( 0 ),
    Variables( X( :School Department Type Code ), Color( :Class Rank Number ) ),
    Elements( Points( X, Legend( 6 ) ) ),
    SendToReport( Dispatch( {}, "Graph Builder", FrameBox, {DispatchSeg( Marker Seg( 1 ), Set Hide Missing Color( 1 ) )} ) )
);
Open("data_table.jmp");
Graph Builder(
    Size( 495, 461 ),
    Show Control Panel( 0 ),
    Variables( X( :School Department Type Code ), Color( :Class Rank Number ) ),
    Elements( Points( X, Legend( 6 ) ) ),
    SendToReport( Dispatch( {}, "Graph Builder", FrameBox, {DispatchSeg( Marker Seg( 1 ), Set Hide Missing Color( 0 ) )} ) )
);

Code Explanation:

1. Open data table;
2. Create Graph Builder window.
3. Set window size.
4. Hide control panel.
5. Define X variable.
6. Define color variable.
7. Add points element.
8. Set legend position.
9. Hide missing color.
10. Repeat steps 1-9 with different missing color setting.

Example 1797

Summary: Creates a graph builder object to visualize data with nested factors, utilizing Graph Builder and SendToReport features.

Code:

Open("data_table.jmp");
gb = Graph Builder(
    Show Control Panel( 0 ),
    Variables( X( :School Department Type Code ), Color( :Class Rank Number ) ),
    Elements( Points( X, Legend( 6 ) ) ),
    SendToReport(
        Dispatch( {}, "400", ScaleBox,
            {Legend Model(
                6,
                Properties(
                    0,
                    {gradient( {Color Theme( "Muted Yellow to Red" ), Show Missing Color( "Off" )} )},
                    Item ID( "Class Rank Number", 1 )
                )
            )}
        )
    )
);
gb << save journal( "$temp\gb.jrn" );

Code Explanation:

1. Open data table;
2. Create graph builder object.
3. Hide control panel.
4. Set X variable.
5. Set color variable.
6. Add points element.
7. Customize legend properties.
8. Disable missing color.
9. Set gradient color theme.
10. Save report to temp directory.

Example 1798

Summary: Creates a variability chart with nested factors using Graph Builder, displaying standard deviation charts and configuring legend properties.

Code:

Open("data_table.jmp");
gb = Graph Builder(
    Show Control Panel( 0 ),
    Variables( X( :School Department Type Code ), Color( :Class Rank Number ) ),
    Elements( Points( X, Legend( 6 ) ) ),
    SendToReport(
        Dispatch( {}, "400", ScaleBox,
            {Legend Model(
                6,
                Properties(
                    0,
                    {gradient( {Color Theme( "Muted Yellow to Red" ), Show Missing Color( "Off" )} )},
                    Item ID( "Class Rank Number", 1 )
                )
            )}
        )
    )
);
gb << save journal( "$temp\gb.jrn" );
Open( "$temp\gb.jrn" );
Graph Builder(
    Show Control Panel( 0 ),
    Variables( X( :School Department Type Code ), Color( :Class Rank Number ) ),
    Elements( Points( X, Legend( 6 ) ) ),
    SendToReport(
        Dispatch( {}, "400", ScaleBox,
            {Legend Model(
                6,
                Properties(
                    0,
                    {gradient( {Color Theme( "Muted Yellow to Red" ), Show Missing Color( "Off" )} )},
                    Item ID( "Class Rank Number", 1 )
                )
            )}
        ),
        Dispatch( {}, "Graph Builder", FrameBox, {DispatchSeg( Marker Seg( 1 ), Set Hide Missing Color( 1 ) )} )
    )
);
gb << save journal( "$temp\gb2.jrn" );
Open( "$temp\gb2.jrn" );
gb = Graph Builder(
    Show Control Panel( 0 ),
    Variables( X( :School Department Type Code ), Color( :Class Rank Number ) ),
    Elements( Points( X, Legend( 6 ) ) ),
    SendToReport(
        Dispatch( {}, "400", ScaleBox,
            {Legend Model(
                6,
                Properties(
                    0,
                    {gradient( {Color Theme( "Muted Yellow to Red" ), Show Missing Color( "On" )} )},
                    Item ID( "Class Rank Number", 1 )
                )
            )}
        )
    )
);
gb << save journal( "$temp\gb3.jrn" );
Open( "$temp\gb3.jrn" );

Code Explanation:

1. Open data table.
2. Create Graph Builder object.
3. Hide control panel.
4. Set X and Color variables.
5. Add points element.
6. Configure legend properties.
7. Save journal file.
8. Open saved journal.
9. Modify graph builder settings.
10. Save another journal file.

Example 1799

Summary: Creates a variability chart with nested factors using Graph Builder, allowing for customization of legend properties and standard deviation charts.

Code:

Open("data_table.jmp");
gb = Graph Builder(
    Show Control Panel( 0 ),
    Variables( X( :School Department Type Code ), Color( :Class Rank Number ) ),
    Elements( Points( X, Legend( 6 ) ) ),
    SendToReport(
        Dispatch( {}, "400", ScaleBox,
            {Legend Model(
                6,
                Properties(
                    0,
                    {gradient( {Color Theme( "Muted Yellow to Red" ), Show Missing Color( "Off" )} )},
                    Item ID( "Class Rank Number", 1 )
                )
            )}
        )
    )
);
gb << save journal( "$temp\gb.jrn" );
Open( "$temp\gb.jrn" );
Graph Builder(
    Show Control Panel( 0 ),
    Variables( X( :School Department Type Code ), Color( :Class Rank Number ) ),
    Elements( Points( X, Legend( 6 ) ) ),
    SendToReport(
        Dispatch( {}, "400", ScaleBox,
            {Legend Model(
                6,
                Properties(
                    0,
                    {gradient( {Color Theme( "Muted Yellow to Red" ), Show Missing Color( "Off" )} )},
                    Item ID( "Class Rank Number", 1 )
                )
            )}
        ),
        Dispatch( {}, "Graph Builder", FrameBox, {DispatchSeg( Marker Seg( 1 ), Set Hide Missing Color( 1 ) )} )
    )
);
gb << save journal( "$temp\gb2.jrn" );
Open( "$temp\gb2.jrn" );
gb = Graph Builder(
    Show Control Panel( 0 ),
    Variables( X( :School Department Type Code ), Color( :Class Rank Number ) ),
    Elements( Points( X, Legend( 6 ) ) ),
    SendToReport(
        Dispatch( {}, "400", ScaleBox,
            {Legend Model(
                6,
                Properties(
                    0,
                    {gradient( {Color Theme( "Muted Yellow to Red" ), Show Missing Color( "On" )} )},
                    Item ID( "Class Rank Number", 1 )
                )
            )}
        )
    )
);
gb << save journal( "$temp\gb3.jrn" );

Code Explanation:

1. Open data table;
2. Create Graph Builder object.
3. Hide control panel.
4. Set X variable.
5. Set color variable.
6. Add points element.
7. Customize legend properties.
8. Save graph builder journal.
9. Open saved journal.
10. Modify graph builder settings.
11. Save modified journal.
12. Open modified journal again.
13. Update legend properties.
14. Save final journal.

Example 1800

Summary: Creates two variability charts with nested factors using operator and part configurations, displaying standard deviation charts and saving the journal to a specified path.

Code:

dt = Open("data_table.jmp");
obj = Graph Builder(
    Size( 495, 461 ),
    Show Control Panel( 0 ),
    Variables( X( :School Department Type Code ), Color( :Class Rank Number ) ),
    Elements( Points( X, Legend( 6 ) ) ),
    SendToReport( Dispatch( {}, "Graph Builder", FrameBox, {DispatchSeg( Marker Seg( 1 ), Set Hide Missing Color( 1 ) )} ) )
);
obj << Journal;
obj << close window;
obj2 = Graph Builder(
    Size( 495, 461 ),
    Show Control Panel( 0 ),
    Variables( X( :School Department Type Code ), Color( :Class Rank Number ) ),
    Elements( Points( X, Legend( 6 ) ) ),
    SendToReport( Dispatch( {}, "Graph Builder", FrameBox, {DispatchSeg( Marker Seg( 1 ), Set Hide Missing Color( 0 ) )} ) )
);
obj2 << Journal;
obj2 << close window;
Close( dt, nosave );
j = Current Journal();
j << Save Journal( "$TEMP\JMP-15287.jrn" );

Code Explanation:

1. Open data table.
2. Create Graph Builder object.
3. Set size and hide control panel.
4. Assign variables for X and color.
5. Add points element with legend.
6. Hide missing color in graph.
7. Generate journal from graph.
8. Close graph window.
9. Create second Graph Builder object.
10. Repeat steps 3-8 without hiding missing color.
11. Close data table without saving.
12. Save current journal to specified path.

Example 1801

Summary: Creates and displays two variability charts with nested factors using Graph Builder, configuring size, hiding control panels, setting variables, adding points elements, and generating journals.

Code:

dt = Open("data_table.jmp");
obj = Graph Builder(
    Size( 495, 461 ),
    Show Control Panel( 0 ),
    Variables( X( :School Department Type Code ), Color( :Class Rank Number ) ),
    Elements( Points( X, Legend( 6 ) ) ),
    SendToReport( Dispatch( {}, "Graph Builder", FrameBox, {DispatchSeg( Marker Seg( 1 ), Set Hide Missing Color( 1 ) )} ) )
);
obj << Journal;
obj << close window;
obj2 = Graph Builder(
    Size( 495, 461 ),
    Show Control Panel( 0 ),
    Variables( X( :School Department Type Code ), Color( :Class Rank Number ) ),
    Elements( Points( X, Legend( 6 ) ) ),
    SendToReport( Dispatch( {}, "Graph Builder", FrameBox, {DispatchSeg( Marker Seg( 1 ), Set Hide Missing Color( 0 ) )} ) )
);
obj2 << Journal;
obj2 << close window;
Close( dt, nosave );
j = Current Journal();
j << Save Journal( "$TEMP\JMP-15287.jrn" );
Open( "$TEMP\JMP-15287.jrn" );

Code Explanation:

1. Open data table.
2. Create first Graph Builder object.
3. Configure Graph Builder size.
4. Hide control panel.
5. Set X and Color variables.
6. Add points element.
7. Hide missing color.
8. Generate journal for first graph.
9. Close first graph window.
10. Create second Graph Builder object.
11. Configure Graph Builder size.
12. Hide control panel.
13. Set X and Color variables.
14. Add points element.
15. Show missing color.
16. Generate journal for second graph.
17. Close second graph window.
18. Close data table without saving.
19. Save current journal.
20. Open saved journal.

Example 1802

Summary: Creates two variability charts with nested factors using operator and part configurations, displaying standard deviation charts in JMP.

Code:

Open("data_table.jmp");
obj = Graph Builder(
    Size( 495, 461 ),
    Show Control Panel( 0 ),
    Variables( X( :School Department Type Code ), Color( :Class Rank Number ) ),
    Elements( Points( X, Legend( 6 ) ) ),
    SendToReport( Dispatch( {}, "Graph Builder", FrameBox, {DispatchSeg( Marker Seg( 1 ), Set Hide Missing Color( 1 ) )} ) )
);
obj << Journal;
obj << close window;
obj2 = Graph Builder(
    Size( 495, 461 ),
    Show Control Panel( 0 ),
    Variables( X( :School Department Type Code ), Color( :Class Rank Number ) ),
    Elements( Points( X, Legend( 6 ) ) ),
    SendToReport( Dispatch( {}, "Graph Builder", FrameBox, {DispatchSeg( Marker Seg( 1 ), Set Hide Missing Color( 0 ) )} ) )
);
obj2 << Journal;
obj2 << close window;

Code Explanation:

1. Open data table;
2. Create Graph Builder object.
3. Set size to 495x461.
4. Hide control panel.
5. Assign variables: X and Color.
6. Add points element.
7. Hide missing color in legend.
8. Generate journal for first graph.
9. Close first graph window.
10. Create second Graph Builder object.
11. Set size to 495x461.
12. Hide control panel.
13. Assign variables: X and Color.
14. Add points element.
15. Show missing color in legend.
16. Generate journal for second graph.
17. Close second graph window.

Example 1803

Summary: Creates a variability chart with nested factors using Graph Builder, configuring scale and format options for height.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 495, 490 ),
    Show Control Panel( 0 ),
    Variables( X( :height ), Group X( :weight ) ),
    Elements( Points( X, Legend( 3 ) ) ),
    SendToReport(
        Dispatch( {}, "height", ScaleBox,
            {Scale( "Log" ), Format( "Best", 12 ), Min( 50 ), Max( 70.3615702479339 ), Inc( 1 ), Minor Ticks( 1 )}
        )
    )
);

Code Explanation:

1. Open data table;
2. Launch Graph Builder.
3. Set window size.
4. Hide control panel.
5. Assign variables.
6. Add points element.
7. Customize height scale.
8. Set log scale.
9. Define format.
10. Specify min, max, increment.

Example 1804

Summary: Creates a geographic map to display points based on Longitude and Latitude variables, utilizing Graph Builder's SendToReport feature.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 534, 453 ),
    Show Control Panel( 0 ),
    Variables( X( :Longitude ), Y( :Latitude ) ),
    Elements( Points( X, Y, Legend( 4 ) ) ),
    SendToReport(
        Dispatch( {}, "Graph Builder", FrameBox,
            {Background Map( Boundaries( {"Canadian Provinces", "US States"} ) ), DispatchSeg( Shape Seg( 1 ), {Color( "Black" )} )}
        )
    )
);

Code Explanation:

1. Open data table;
2. Create new Graph Builder.
3. Set window size.
4. Hide control panel.
5. Assign X and Y variables.
6. Add points element.
7. Customize report settings.
8. Enable background map.
9. Set map boundaries.
10. Color map boundaries black.

Example 1805

Summary: Creates a variability chart with nested factors using Graph Builder, displaying standard deviation charts and summary statistics.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 650, 508 ),
    Show Control Panel( 0 ),
    Variables( X( :Species ), Y( :Sepal length ) ),
    Elements(
        Points( X, Y, Legend( 3 ) ),
        Caption Box(
            X,
            Y,
            Legend( 4 ),
            Summary Statistic( "Sum" ),
            Summary Statistic 2( "Mean" ),
            Summary Statistic 3( "N" ),
            X Position( "Middle" ),
            Number Format( "Fixed Dec", 7, 0 )
        )
    )
);

Code Explanation:

1. Open data table;
2. Create Graph Builder window.
3. Set graph size to 650x508.
4. Hide control panel.
5. Assign Species to X-axis.
6. Assign Sepal length to Y-axis.
7. Add points element.
8. Add caption box element.
9. Display sum summary statistic.
10. Display mean summary statistic.
11. Display count summary statistic.
12. Center captions horizontally.
13. Format numbers as fixed decimal without decimals.

Example 1806

Summary: Creates a variability chart with nested factors using Graph Builder, displaying standard deviation charts and summary statistics for Sepal length by Species.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 650, 512 ),
    Show Control Panel( 0 ),
    Variables( X( :Species ), Y( :Sepal length ) ),
    Elements(
        Points( X, Y, Legend( 3 ) ),
        Caption Box(
            X,
            Y,
            Legend( 4 ),
            Summary Statistic( "Sum" ),
            Summary Statistic 2( "Mean" ),
            Summary Statistic 3( "N" ),
            Location( "Axis Table" ),
            Number Format( "Fixed Dec", 7, 0 )
        )
    )
);

Code Explanation:

1. Open data table;
2. Create Graph Builder window.
3. Set window size.
4. Hide control panel.
5. Assign Species to X-axis.
6. Assign Sepal length to Y-axis.
7. Add points element.
8. Add caption box element.
9. Set summary statistics for caption.
10. Place caption at axis table.

Example 1807

Summary: Creates a graph builder with nested factors using operator and part configurations, displaying standard deviation charts.

Code:

dt = Open("data_table.jmp");
gb = Graph Builder(
    Size( 516, 452 ),
    Show Control Panel( 0 ),
    Variables( X( :Species ), Y( :Sepal length ) ),
    Elements(
        Points( X, Y, Legend( 3 ) ),
        Caption Box( X, Y, Legend( 4 ), Summary Statistic( "Median" ), Summary Statistic 2( "Mode" ), Location( "Axis Table" ) )
    ),
    SendToReport(
        Dispatch( {}, "Graph Builder", FrameBox,
            Add Text Annotation( Text( "" ), Fixed Size( 0 ), Text Box( {159, 62, 178, 72} ), Filled( 0 ) )
        )
    )
);
gb << save journal( "$TEMP/Test.jrn" );
Open( "$TEMP/Test.jrn" );

Code Explanation:

1. Open data table;
2. Create Graph Builder.
3. Set size to 516x452.
4. Hide control panel.
5. Set X variable to Species.
6. Set Y variable to Sepal length.
7. Add points element.
8. Add caption box with median and mode.
9. Save graph builder to Test.jrn.
10. Open saved journal file.

Example 1808

Summary: Creates a variability chart with nested factors using Graph Builder, displaying standard deviation charts and utilizing shape columns for markers.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 560, 443 ),
    Show Control Panel( 0 ),
    Variables( X( :height ), Y( :weight ) ),
    Elements( Points( X, Y, Legend( 2 ), Set Shape Column( :sex ) ) )
);

Code Explanation:

1. Open data table;
2. Launch Graph Builder.
3. Set window size.
4. Hide control panel.
5. Assign X variable.
6. Assign Y variable.
7. Add points element.
8. Set legend position.
9. Use shape column for markers.

Example 1809

Summary: Creates two Graph Builder windows with nested factors, utilizing the sex and picture columns for shape and legend, respectively.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 560, 443 ),
    Show Control Panel( 0 ),
    Variables( X( :height ), Y( :weight ) ),
    Elements( Points( X, Y, Legend( 2 ), Set Shape Column( :sex ) ) )
);
Open("data_table.jmp");
Graph Builder(
    Size( 560, 443 ),
    Show Control Panel( 0 ),
    Variables( X( :height ), Y( :weight ) ),
    Elements( Points( X, Y, Legend( 2 ), Set Shape Column( :picture ) ) )
);

Code Explanation:

1. Open data_table data
2. Create Graph Builder window.
3. Set window size to 560x443.
4. Hide control panel.
5. Assign height to X-axis.
6. Assign weight to Y-axis.
7. Add points element.
8. Use sex column for shape.
9. Open data_table data
10. Create another Graph Builder window.

Example 1810

Summary: Creates a graph builder with nested factors using operator and part configurations, displaying standard deviation charts.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 560, 443 ),
    Show Control Panel( 0 ),
    Variables( X( :height ), Y( :weight ) ),
    Elements( Points( X, Y, Legend( 2 ), Set Shape Column( :sex ) ) )
);
Open("data_table.jmp");

Code Explanation:

1. Open data table;
2. Launch Graph Builder.
3. Set graph size.
4. Hide control panel.
5. Define X and Y variables.
6. Add points element.
7. Set shape by sex.
8. Open data table;

Example 1811

Summary: Creates a variability chart with nested factors using Graph Builder, hiding control panels and setting X and Y variables to visualize mean summary statistics with error intervals.

Code:

Open("data_table.jmp");
obj = Graph Builder(
    Show Control Panel( 0 ),
    Variables( X( :age ), Y( :weight ) ),
    Elements( Points( X, Y, Legend( 3 ), Summary Statistic( "Mean" ), Error Interval( "Standard Deviation" ) ) )
);
frame = Report( obj )[FrameBox( 1 )];
seg = (frame << Find Seg( "Bar Seg" ));
seg << Set Interval Draw Directions( "Upper" );
obj = Graph Builder(
    Show Control Panel( 0 ),
    Variables( X( :age ), Y( :weight ) ),
    Elements( Points( X, Y, Legend( 3 ), Summary Statistic( "Mean" ), Error Interval( "Standard Deviation" ) ) )
);
frame = Report( obj )[FrameBox( 1 )];
seg = (frame << Find Seg( "Bar Seg" ));
seg << Set Interval Draw Directions( "Lower" );
obj = Graph Builder(
    Show Control Panel( 0 ),
    Variables( X( :age ), Y( :weight ) ),
    Elements( Points( X, Y, Legend( 3 ), Summary Statistic( "Mean" ), Error Interval( "Standard Deviation" ) ) )
);
frame = Report( obj )[FrameBox( 1 )];
seg = (frame << Find Seg( "Bar Seg" ));

Code Explanation:

1. Open data_table data
2. Create Graph Builder object.
3. Hide control panel.
4. Set X and Y variables.
5. Add points element.
6. Calculate mean summary statistic.
7. Add error interval.
8. Get frame box reference.
9. Find bar segment.
10. Set interval draw direction to upper.
11. Repeat steps 2-10 for lower interval direction.

Example 1812

Summary: Creates a variability chart with nested factors using Graph Builder, allowing for customization of interval draw directions.

Code:

Open("data_table.jmp");
obj = Graph Builder(
    Show Control Panel( 0 ),
    Variables( X( :age ), Y( :weight ) ),
    Elements( Points( X, Y, Legend( 3 ), Summary Statistic( "Mean" ), Error Interval( "Standard Deviation" ) ) )
);
frame = Report( obj )[FrameBox( 1 )];
seg = (frame << Find Seg( "Bar Seg" ));
seg << Set Interval Draw Directions( "Upper" );
obj = Graph Builder(
    Show Control Panel( 0 ),
    Variables( X( :age ), Y( :weight ) ),
    Elements( Points( X, Y, Legend( 3 ), Summary Statistic( "Mean" ), Error Interval( "Standard Deviation" ) ) )
);
frame = Report( obj )[FrameBox( 1 )];
seg = (frame << Find Seg( "Bar Seg" ));
seg << Set Interval Draw Directions( "Lower" );
obj = Graph Builder(
    Show Control Panel( 0 ),
    Variables( X( :age ), Y( :weight ) ),
    Elements( Points( X, Y, Legend( 3 ), Summary Statistic( "Mean" ), Error Interval( "Standard Deviation" ) ) )
);
frame = Report( obj )[FrameBox( 1 )];
seg = (frame << Find Seg( "Bar Seg" ));
seg << Set Interval Draw Directions( "None" );

Code Explanation:

1. Open data table.
2. Create Graph Builder object.
3. Hide control panel.
4. Set X and Y variables.
5. Add points element.
6. Get frame box reference.
7. Find bar segment.
8. Set interval draw direction to upper.
9. Create Graph Builder object again.
10. Set interval draw direction to lower.
11. Create Graph Builder object again.
12. Set interval draw direction to none.

Example 1813

Summary: Creates a variability chart with nested factors using different jitter types, displaying standard deviation charts in JMP.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 527, 450 ),
    Show Control Panel( 0 ),
    Variables( X( :Passenger Class ), Y( :Survived ) ),
    Elements( Points( X, Y, Legend( 1 ) ) )
);
Graph Builder(
    Size( 527, 450 ),
    Show Control Panel( 0 ),
    Variables( X( :Passenger Class ), Y( :Survived ) ),
    Elements( Points( X, Y, Legend( 1 ), Jitter( "Random Uniform" ) ) )
);
Graph Builder(
    Size( 527, 450 ),
    Show Control Panel( 0 ),
    Variables( X( :Passenger Class ), Y( :Survived ) ),
    Elements( Points( X, Y, Legend( 1 ), Jitter( "Random Normal" ) ) )
);
Graph Builder(
    Size( 527, 450 ),
    Show Control Panel( 0 ),
    Variables( X( :Passenger Class ), Y( :Survived ) ),
    Elements( Points( X, Y, Legend( 1 ), Jitter( "Packed" ) ) )
);
Graph Builder(
    Size( 527, 450 ),
    Show Control Panel( 0 ),
    Variables( X( :Passenger Class ), Y( :Survived ) ),
    Elements( Points( X, Y, Legend( 1 ), Jitter( "Centered Grid" ) ) )
);
Graph Builder(
    Size( 527, 450 ),
    Show Control Panel( 0 ),
    Variables( X( :Passenger Class ), Y( :Survived ) ),
    Elements( Points( X, Y, Legend( 1 ), Jitter( "Positive Grid" ) ) )
);

Code Explanation:

1. Open data table;
2. Create Graph Builder window.
3. Set window size.
4. Hide control panel.
5. Assign Passenger Class to X-axis.
6. Assign Survived to Y-axis.
7. Add points element.
8. Repeat steps 2-7 for different jitter types.
9. Use "Random Uniform" jitter.
10. Use "Random Normal" jitter.
11. Use "Packed" jitter.
12. Use "Centered Grid" jitter.
13. Use "Positive Grid" jitter.

Example 1814

Summary: Creates a variability chart with nested factors using different jitter types, displaying standard deviation charts for analysis.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 527, 450 ),
    Show Control Panel( 0 ),
    Variables( X( :Passenger Class ), Y( :Survived ) ),
    Elements( Points( X, Y, Legend( 1 ) ) )
);
Graph Builder(
    Size( 527, 450 ),
    Show Control Panel( 0 ),
    Variables( X( :Passenger Class ), Y( :Survived ) ),
    Elements( Points( X, Y, Legend( 1 ), Jitter( "Random Uniform" ) ) )
);
Graph Builder(
    Size( 527, 450 ),
    Show Control Panel( 0 ),
    Variables( X( :Passenger Class ), Y( :Survived ) ),
    Elements( Points( X, Y, Legend( 1 ), Jitter( "Random Normal" ) ) )
);
Graph Builder(
    Size( 527, 450 ),
    Show Control Panel( 0 ),
    Variables( X( :Passenger Class ), Y( :Survived ) ),
    Elements( Points( X, Y, Legend( 1 ), Jitter( "Packed" ) ) )
);
Graph Builder(
    Size( 527, 450 ),
    Show Control Panel( 0 ),
    Variables( X( :Passenger Class ), Y( :Survived ) ),
    Elements( Points( X, Y, Legend( 1 ), Jitter( "Centered Grid" ) ) )
);
Graph Builder(
    Size( 527, 450 ),
    Show Control Panel( 0 ),
    Variables( X( :Passenger Class ), Y( :Survived ) ),
    Elements( Points( X, Y, Legend( 1 ), Jitter( "Positive Grid" ) ) )
);
Graph Builder(
    Size( 527, 450 ),
    Show Control Panel( 0 ),
    Variables( X( :Passenger Class ), Y( :Survived ) ),
    Elements( Points( X, Y, Legend( 1 ), Jitter( "Density Random" ) ) )
);

Code Explanation:

1. Open data table;
2. Create Graph Builder window.
3. Set graph size to 527x450.
4. Hide control panel.
5. Set X variable to Passenger Class.
6. Set Y variable to Survived.
7. Add points element with legend.
8. Repeat steps 2-7 for different jitter types:
9. Random Uniform
10. Random Normal
11. Packed
12. Centered Grid
13. Positive Grid
14. Density Random

Example 1815

Summary: Creates a Graph Builder window with nested factors using operator and part configurations, displaying standard deviation charts.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 603, 523 ),
    Show Control Panel( 0 ),
    Variables( X( :height ), Y( :weight ) ),
    Elements( Points( X, Y, Legend( 4 ) ), Line Of Fit( X, Y, Legend( 6 ) ) ),
    SendToReport(
        Dispatch( {}, "Graph Builder", FrameBox,
            {Add Pin Annotation(
                Seg( Marker Seg( 1 ) ),
                Index( 10 ),
                Index Row( 10 ),
                UniqueID( 10 ),
                FoundPt( {227, 411} ),
                Origin( {55.9989933837429, 66.8618643817199} ),
                RightOfCenter( 0 ),
                Tag Line( 1 )
            ), Add Pin Annotation(
                Seg( Poly Seg( 1 ) ),
                Index( {0, 0} ),
                Index Row( {0, 0} ),
                UniqueID( 1 ),
                FoundPt( {507, 219} ),
                Origin( {67.0513461538462, 128.831082047765} ),
                RightOfCenter( 1 ),
                Tag Line( 1 )
            )}
        )
    )
);

Code Explanation:

1. Open data table.
2. Create Graph Builder window.
3. Set graph size.
4. Hide control panel.
5. Assign variables X and Y.
6. Add points element.
7. Add line of fit element.
8. Send report updates.
9. Add first pin annotation.
10. Add second pin annotation.

Example 1816

Summary: Creates a Graph Builder report with nested factors, displaying points and smoother elements, and adds a pin annotation to highlight specific data points.

Code:

Open("data_table.jmp");
Graph Builder(
    Show Control Panel( 0 ),
    Variables( X( :height ), Y( :weight ), Overlay( :sex ) ),
    Elements( Points( X, Y, Legend( 1 ) ), Smoother( X, Y, Legend( 2 ) ) ),
    SendToReport(
        Dispatch( {}, "Graph Builder", FrameBox,
            Add Pin Annotation(
                Seg( Marker Seg( 2 ) ),
                Index( 1 ),
                Index Row( 6 ),
                UniqueID( 1 ),
                FoundPt( {338, 221} ),
                Origin( {61, 128.02043103566} ),
                RightOfCenter( 1 ),
                Add Text( "My 2nd Grade Teacher" ),
                Tag Line( 1 )
            )
        )
    )
);
Current Report() << save journal( "$TEMP/Test.jrn" );
Open( "$TEMP/Test.jrn" );

Code Explanation:

1. Open data table;
2. Create Graph Builder.
3. Hide control panel.
4. Set X to height.
5. Set Y to weight.
6. Overlay by sex.
7. Add points element.
8. Add smoother element.
9. Add pin annotation.
10. Save report as Test.jrn.
11. Open saved report.

Example 1817

Summary: Creates a variability chart with nested factors using Graph Builder, displaying standard deviation charts and formatting weight scale to fixed decimal.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 534, 447 ),
    Show Control Panel( 0 ),
    Variables( X( :age ), Y( :height, Side( "Right" ) ), Y( :weight, Position( 1 ) ) ),
    Elements( Points( X, Y( 2 ), Legend( 5 ) ), Points( X, Y( 1 ), Legend( 6 ) ) ),
    SendToReport( Dispatch( {}, "weight", ScaleBox, {Format( "Fixed Dec", 12, 12 )} ) )
);

Code Explanation:

1. Open data table;
2. Launch Graph Builder.
3. Set window size.
4. Hide control panel.
5. Define X variable: age.
6. Define Y variables: height and weight.
7. Plot height points on right axis.
8. Plot weight points on left axis.
9. Format weight scale to fixed decimal.
10. Display graph.

Example 1818

Summary: Creates a variability chart with nested factors using Graph Builder, featuring log-transformed height and weight intervals, and displaying standard deviation charts.

Code:

dt = Open("data_table.jmp");
Graph Builder(
    Size( 534, 454 ),
    Show Control Panel( 0 ),
    Variables(
        X( :height ),
        Y( :weight ),
        Interval( Transform Column( "Log10[height]", Formula( Log10( :height ) ) ) ),
        Interval( Transform Column( "Log10[weight]", Formula( Log10( :weight ) ) ) )
    ),
    Elements( Points( X, Y, Legend( 10 ), Error Bars( "Two-way Interval" ) ) ),
    SendToReport(
        Dispatch( {}, "400", ScaleBox, {Legend Model( 10, Base( 1, 0, 0 ) )} ),
        Dispatch( {}, "400", LegendBox, {Legend Position( {10, [0, 1]} )} )
    )
);

Code Explanation:

1. Open data table.
2. Create Graph Builder window.
3. Set window size.
4. Hide control panel.
5. Define X variable.
6. Define Y variable.
7. Add log-transformed height interval.
8. Add log-transformed weight interval.
9. Plot points with error bars.
10. Adjust legend and position.

Example 1819

Summary: Creates a variability chart with nested factors using Graph Builder, displaying standard deviation charts and custom error bars.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 534, 520 ),
    Show Control Panel( 0 ),
    Variables( X( :height ), Y( :weight ), Interval( :height ) ),
    Elements( Points( X, Y, Legend( 2 ), Summary Statistic( "Mean" ), Error Bars( "Custom Interval" ) ) ),
    SendToReport(
        Dispatch( {}, "400", ScaleBox, {Legend Model( 2, Base( 1, 0, 0 ), Properties( 0, {Line Color( 19 )} ) )} ),
        Dispatch( {}, "400", LegendBox, {Legend Position( {2, [0, 1]} )} )
    )
);

Code Explanation:

1. Open data table.
2. Create Graph Builder window.
3. Set window size.
4. Hide control panel.
5. Define X and Y variables.
6. Add interval for X.
7. Add points element.
8. Set legend properties.
9. Customize error bars.
10. Adjust legend position.

Example 1820

Summary: Creates a variability chart with nested factors using operator and part configurations, displaying standard deviation charts in Graph Builder.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 534, 520 ),
    Show Control Panel( 0 ),
    Variables( X( :height ), Y( :weight ), Y( :height, Position( 1 ) ), Interval( :height ) ),
    Elements( Points( X, Y( 1 ), Y( 2 ), Legend( 2 ), Error Bars( "Custom Interval" ) ) )
);

Code Explanation:

1. Open data table.
2. Launch Graph Builder.
3. Set window size.
4. Hide control panel.
5. Assign variables to axes.
6. Add height interval.
7. Create points element.
8. Plot weight vs. height.
9. Overlay height vs. height.
10. Display error bars.

Example 1821

Summary: Creates a graph builder with nested factors, utilizing size, shape, and color variables to visualize data, and sets a custom graph title.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 486, 419 ),
    Show Control Panel( 0 ),
    Variables( Color( :Electors ), Size( :Electors ), Shape( :State ) ),
    Elements( Points( Legend( 3 ) ) ),
    SendToReport(
        Dispatch( {}, "400", ScaleBox, {Legend Model( 3, Properties( 0, {Line Color( 1 )} ) )} ),
        Dispatch( {}, "graph title", TextEditBox, {Set Text( "2008 Election State Winners sized by Number of Electors" )} )
    )
);

Code Explanation:

1. Open table.
2. Create graph builder.
3. Set size.
4. Hide control panel.
5. Define color variable.
6. Define size variable.
7. Define shape variable.
8. Add points element.
9. Customize legend.
10. Set graph title.

Example 1822

Summary: Creates a graph builder window with a points element to visualize data from a nested factors dataset, utilizing Graph Builder and specifying X, Y, and color variables.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 531, 407 ),
    Show Control Panel( 0 ),
    Variables( X( :Country ), Y( :Birth ), Color( :Country ) ),
    Elements( Points( X, Y, Legend( 4 ) ) )
);

Code Explanation:

1. Open data table;
2. Create Graph Builder window.
3. Set window size.
4. Hide control panel.
5. Assign X variable.
6. Assign Y variable.
7. Assign color variable.
8. Add points element.
9. Display legend.

Example 1823

Summary: Creates a variability chart with nested factors using operator and part configurations, displaying standard deviation charts in Graph Builder.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 562, 366 ),
    Show Control Panel( 0 ),
    Variables( X( :Name( "Time (Numeric)" ) ), Y( :Heart Rate ), Group X( :Drink ), Overlay( :Testers ) ),
    Elements( Points( X, Y, Legend( 88 ) ), Line( X, Y, Legend( 90 ) ) )
);

Code Explanation:

1. Open data table;
2. Create Graph Builder window.
3. Set window size.
4. Hide control panel.
5. Define X variable.
6. Define Y variable.
7. Define group X variable.
8. Define overlay variable.
9. Add points element.
10. Add line element.

Example 1824

Summary: Creates a variability chart with nested factors using operator and part configurations, displaying standard deviation charts in Graph Builder.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 524, 378 ),
    Show Control Panel( 0 ),
    Variables( X( :Measurement ), Y( :Standard ), Group X( :Operator ), Overlay( :part# ) ),
    Elements( Points( X, Y, Legend( 7 ) ) )
);

Code Explanation:

1. Open data table.
2. Launch Graph Builder.
3. Set window size.
4. Hide control panel.
5. Define X variable.
6. Define Y variable.
7. Define Group X variable.
8. Define Overlay variable.
9. Add Points element.
10. Configure legend.

Example 1825

Summary: Creates a graph builder with nested factors using operator and part configurations, displaying standard deviation charts.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 436, 293 ),
    Show Control Panel( 0 ),
    Variables( X( :age ), Y( :weight ), Overlay( :sex ) ),
    Elements( Line( X, Y, Legend( 7 ) ) ),
    SendToReport(
        Dispatch( {}, "Graph Builder", FrameBox,
            Add Simple Shape Annotation( Oval( {138, 76, 197, 103} ), Color( "Green" ), Filled( 1 ) )
        )
    )
);

Code Explanation:

1. Open data_table data
2. Launch Graph Builder.
3. Set window size.
4. Hide control panel.
5. Assign variables: age (X), weight (Y), sex (Overlay).
6. Add line element.
7. Send report to Graph Builder.
8. Dispatch to Graph Builder frame.
9. Add oval annotation.
10. Set annotation color to green.
11. Fill oval annotation.

Example 1826

Summary: Creates a Graph Builder window with nested factors, displaying standard deviation charts and configuring axis formats.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 534, 454 ),
    Show Control Panel( 0 ),
    Variables( X( :height ), Y( :weight ) ),
    Elements( Points( X, Y, Legend( 3 ) ) ),
    Local Data Filter( Add Filter( columns( :sex ) ) ),
    SendToReport(
        Dispatch( {}, "height", ScaleBox, {Format( "Best", 12 )} ),
        Dispatch( {}, "weight", ScaleBox, {Scale( "Log" ), Format( "Best", 12 ), Min( 60 ), Max( 200 ), Inc( 1 ), Minor Ticks( 1 )} )
    )
);

Code Explanation:

1. Open data table.
2. Create Graph Builder window.
3. Set window size.
4. Hide control panel.
5. Assign variables for X and Y axes.
6. Add points element to graph.
7. Enable local data filter.
8. Configure height axis format.
9. Configure weight axis scale and format.
10. Set weight axis range and increments.

Example 1827

Summary: Creates a variability chart with nested factors using Graph Builder, displaying standard deviation charts and utilizing operator and part configurations.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 570, 389 ),
    Variables( X( :age ), Y( :height ), Y( :weight ) ),
    Elements( Position( 1, 1 ), Points( X, Y, Legend( 7 ) ) ),
    Elements( Position( 1, 2 ), Points( X, Y, Legend( 8 ) ) )
);

Code Explanation:

1. Open data table;
2. Launch Graph Builder.
3. Set window size.
4. Assign variables X and Y.
5. Add first points element.
6. Position first element.
7. Add second points element.
8. Position second element.
9. Display graph.

Example 1828

Summary: Creates a graph builder object to visualize the relationship between sex and height, utilizing a Column Switcher for interactive exploration.

Code:

Open("data_table.jmp");
gb = Graph Builder( Variables( X( :sex ), Y( :height ) ), Elements( Points( X, Y, Legend( 3 ) ) ), Column Switcher( :sex, {:age, :sex} ) );

Code Explanation:

1. Open data table;
2. Create graph builder object.
3. Set X variable to sex.
4. Set Y variable to height.
5. Add points element.
6. Enable column switcher.
7. Set switcher column to sex.
8. Include age and sex in switcher.

Example 1829

Summary: Creates a variability chart with nested factors using Graph Builder, setting X to sex and Y to height, and enabling legend and column switching.

Code:

dt = Open("data_table.jmp");
gb = Graph Builder( Variables( X( :sex ), Y( :height ) ), Elements( Points( X, Y, Legend( 3 ) ) ), Column Switcher( :sex, {:age, :sex} ) );

Code Explanation:

1. Open data table.
2. Create Graph Builder object.
3. Set X variable to sex.
4. Set Y variable to height.
5. Add Points element.
6. Enable Legend for Points.
7. Configure Column Switcher.
8. Set switch column to sex.
9. Define switchable columns.

Example 1830

Summary: Creates a graph builder with nested factors using operator and part configurations, displaying standard deviation charts.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 534, 448 ),
    Show Control Panel( 0 ),
    Variables( X( :age ), Y( :height ) ),
    By( :Sex ),
    Elements( Points( X, Y, Legend( 3 ) ) )
);

Code Explanation:

1. Open data table;
2. Create Graph Builder object.
3. Set graph size.
4. Hide control panel.
5. Define X variable.
6. Define Y variable.
7. Group by sex.
8. Add points element.
9. Set legend position.
10. Display graph.

Example 1831

Summary: Creates a graph with nested factors using Graph Builder, selecting rows where age is 17 and displaying standard deviation charts.

Code:

dt = Open("data_table.jmp");
dt << select where( :age == 17 );
Graph Builder(
    Size( 534, 448 ),
    Show Control Panel( 0 ),
    Variables( X( :sex ), Y( :weight ), Overlay( :age ) ),
    Elements( Line( X, Y, Legend( 1 ) ) )
);

Code Explanation:

1. Open data table.
2. Select rows where age is 17.
3. Create Graph Builder window.
4. Set window size to 534x448.
5. Hide control panel.
6. Set X variable to sex.
7. Set Y variable to weight.
8. Set overlay variable to age.
9. Add line element to graph.
10. Display legend for line element.

Example 1832

Summary: Creates a variability chart with nested factors using Graph Builder, displaying standard deviation charts and hiding the control panel.

Code:

Open("data_table.jmp");
gb = Graph Builder(
    Size( 422, 324 ),
    Show Control Panel( 0 ),
    Variables( Y( :height ), Y( :weight ), Color( :age ) ),
    Elements( Position( 1, 1 ), Points( Y, Color, Jitter( 0 ) ) ),
    Elements( Position( 1, 2 ), Points( Y, Color, Jitter( 0 ) ) )
);

Code Explanation:

1. Open data table;
2. Create Graph Builder object.
3. Set graph size.
4. Hide control panel.
5. Define variables for Y, Y, and Color.
6. Add first points element with jitter off.
7. Add second points element with jitter off.
8. Display graph builder window.

Example 1833

Summary: Creates a variability chart with nested factors using Graph Builder, displaying standard deviation charts for height and weight variables.

Code:

dt = Open("data_table.jmp");
gb = Graph Builder(
    Size( 422, 324 ),
    Show Control Panel( 0 ),
    Variables( Y( :height ), Y( :weight ), Color( :age ) ),
    Elements( Position( 1, 1 ), Points( Y, Color, Jitter( 0 ) ) ),
    Elements( Position( 1, 2 ), Points( Y, Color, Jitter( 0 ) ) )
);
gb2 = gb << Redo Analysis;

Code Explanation:

1. Open data_table data
2. Create Graph Builder object.
3. Set window size.
4. Hide control panel.
5. Define Y variables: height, weight.
6. Define color variable: age.
7. Add first points element.
8. Add second points element.
9. Redo analysis on graph.

Example 1834

Summary: Creates a graph builder with nested factors using Graph Builder, displaying points with jitter and color-coded by region.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 359, 397 ),
    Show Control Panel( 0 ),
    Variables( X( :SAT Math ), Color( :Region ), Size( :Name( "% Taking (1997)" ) ) ),
    Elements( Points( X, Legend( 10 ), Jitter( "Positive Grid" ) ) )
);

Code Explanation:

1. Open data table.
2. Launch Graph Builder.
3. Set window size.
4. Hide control panel.
5. Define X variable.
6. Define Color variable.
7. Define Size variable.
8. Add Points element.
9. Enable jitter.
10. Display graph.

Example 1835

Summary: Creates a Graph Builder window with nested factors, displaying points and standard deviation charts for height and weight variables.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 321, 344 ),
    Show Control Panel( 0 ),
    Variables( Y( :height ), Y( :weight, Position( 1 ) ) ),
    Elements( Points( Y( 1 ), Y( 2 ) ) )
);

Code Explanation:

1. Open data table;
2. Create Graph Builder window.
3. Set window size.
4. Hide control panel.
5. Define Y variables.
6. Add weight variable.
7. Position weight variable.
8. Create points element.
9. Assign height to Y1.
10. Assign weight to Y2.

Example 1836

Summary: Creates a variability chart with nested factors using Graph Builder, displaying standard deviation charts for skull length, teeth row, palatine foramen, and jaw length.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 506, 368 ),
    Show Control Panel( 0 ),
    Variables(
        X( :species ),
        Y( :skull length ),
        Y( :teeth row, Position( 1 ) ),
        Y( :palatine foramen, Position( 1 ) ),
        Y( :jaw length, Position( 1 ) )
    ),
    Elements( Points( X, Y( 1 ), Y( 2 ), Y( 3 ), Y( 4 ), Legend( 5 ), Jitter( "None" ) ) )
);

Code Explanation:

1. Open data table;
2. Create new Graph Builder window.
3. Set window size.
4. Hide control panel.
5. Define X variable.
6. Define first Y variable.
7. Define second Y variable.
8. Define third Y variable.
9. Define fourth Y variable.
10. Add points element with specified variables.

Example 1837

Summary: Creates a variability chart with nested factors using Graph Builder, displaying standard deviation charts and overlaying by sex.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 560, 366 ),
    Show Control Panel( 0 ),
    Variables( X( :age ), Y( :height ), Group X( :sex ), Overlay( :sex ) ),
    Elements( Points( X, Y, Legend( 5 ) ) )
);

Code Explanation:

1. Open data table;
2. Create Graph Builder window.
3. Set window size.
4. Hide control panel.
5. Define X variable.
6. Define Y variable.
7. Group by sex.
8. Overlay by sex.
9. Add points element.
10. Assign legend position.

Example 1838

Summary: Creates a variability chart with nested factors using Graph Builder, displaying standard deviation charts for 'Expenditure (1997)' and 'Student/Faculty Ratio (1997)' by region.

Code:

Open("data_table.jmp");
Graph Builder(
    Show Control Panel( 0 ),
    Variables(
        X( Transform Column( "SAT Verbal+SAT Math", Formula( :SAT Verbal + :SAT Math ) ) ),
        Y( :Name( "Expenditure (1997)" ) ),
        Y( :Name( "Student/Faculty Ratio (1997)" ) ),
        Group X( :Region ),
        Color( :Region )
    ),
    Elements( Position( 1, 1 ), Points( X, Y, Legend( 10 ) ) ),
    Elements( Position( 1, 2 ), Points( X, Y, Legend( 11 ) ) )
);

Code Explanation:

1. Open data table;
2. Create Graph Builder object.
3. Hide control panel.
4. Define X variable.
5. Define first Y variable.
6. Define second Y variable.
7. Group by region.
8. Color by region.
9. Add points for first Y.
10. Add points for second Y.

Example 1839

Summary: Creates a variability chart with nested factors using Graph Builder, displaying standard deviation charts and configuring points with two X variables, Y, legend, mean summary, and range error bars.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 563, 463 ),
    Show Control Panel( 0 ),
    Variables( X( :sex ), X( :age, Position( 1 ) ), Y( :height ), Group Y( :weight ) ),
    Elements( Points( X( 1 ), X( 2 ), Y, Legend( 5 ), Summary Statistic( "Mean" ), Error Bars( "Range" ) ) )
);

Code Explanation:

1. Open data table.
2. Create new graph builder window.
3. Set window size to 563x463.
4. Hide control panel.
5. Define X variables: sex and age.
6. Set age as first position on X axis.
7. Define Y variable: height.
8. Define grouped Y variable: weight.
9. Add points element to graph.
10. Configure points with two X variables, Y, legend, mean summary, and range error bars.

Example 1840

Summary: Creates a variability chart with nested factors using operator and part configurations, displaying standard deviation charts in Graph Builder.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 531, 443 ),
    Show Control Panel( 0 ),
    Variables( X( :Measurement ), Y( :Standard ), Group X( :Operator ), Overlay( :part# ) ),
    Elements( Points( X, Y, Legend( 4 ) ) ),
    SendToReport(
        Dispatch( {}, "400", ScaleBox,
            {Legend Model(
                4,
                Base( 0, 0, 0 ),
                Base( 1, 0, 0 ),
                Base( 2, 0, 0 ),
                Base( 3, 0, 0 ),
                Base( 4, 0, 0 ),
                Base( 5, 0, 0 ),
                Base( 6, 0, 0 ),
                Base( 7, 0, 0 ),
                Base( 8, 0, 0 ),
                Base( 9, 0, 0 )
            )}
        )
    )
);

Code Explanation:

1. Open data table.
2. Create Graph Builder window.
3. Set window size to 531x443.
4. Hide control panel.
5. Assign variables: X=Measurement, Y=Standard.
6. Group by Operator, overlay by part#.
7. Add points element to graph.
8. Send report to Graph Builder.
9. Configure legend model for base settings.
10. Apply settings to legend.

Example 1841

Summary: Creates a variability chart with nested factors using operator and part configurations, displaying standard deviation charts.

Code:

Open("data_table.jmp");
obj = Graph Builder(
    Size( 495, 247 ),
    Show Control Panel( 0 ),
    Variables( X( :Y ), Y( :Y ), Color( :X ) ),
    Elements( Points( X, Y, Legend( 10 ) ) ),
    SendToReport(
        Dispatch( {}, "400", ScaleBox, {Legend Model( 10, Properties( 0, {gradient( {Scale Type( "Log" )} )} ) )} ),
        Dispatch( {}, "Graph Builder", FrameBox, {Marker Size( 6 )} )
    )
);

Code Explanation:

1. Open data table;
2. Create Graph Builder object.
3. Set window size.
4. Hide control panel.
5. Define X, Y, and color variables.
6. Add points element.
7. Send report dispatch for legend.
8. Set log scale for gradient.
9. Send report dispatch for frame box.
10. Set marker size.

Example 1842

Summary: Creates a variability chart with nested factors using Graph Builder, displaying standard deviation charts and overlaying by Grade.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 528, 448 ),
    Show Control Panel( 0 ),
    Variables( X( :Goals ), Y( :Age ), Y( :Grade, Position( 1 ) ), Overlay( :Grade ) ),
    Elements( Points( X, Y( 1 ), Y( 2 ), Legend( 22 ) ) )
);

Code Explanation:

1. Open data table;
2. Create new Graph Builder window.
3. Set window size.
4. Hide control panel.
5. Define X variable: Goals.
6. Define primary Y variable: Age.
7. Define secondary Y variable: Grade.
8. Overlay by Grade variable.
9. Add points element.
10. Configure points for two Y variables.

Example 1843

Summary: Creates a variability chart with nested factors using Graph Builder, displaying mean points and jittered points, and adding reference lines to the Temperature axis.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 531, 464 ),
    Show Control Panel( 0 ),
    Variables( X( :Temperature ), X( :Casting, Position( 1 ) ), Y( :Shrinkage ) ),
    Elements(
        Points( X( 1 ), X( 2 ), Y, Legend( 1 ), Summary Statistic( "Mean" ), Error Bars( "Range" ) ),
        Points( X( 1 ), X( 2 ), Y, Legend( 2 ), Jitter( "None" ) )
    ),
    SendToReport(
        Dispatch( {}, "Temperature", ScaleBox,
            {Add Ref Line( 3.5, "Solid", "Medium Light Gray", "", 1 ), Label Row( 2, Show Major Ticks( 0 ) )}
        ),
        Dispatch( {}, "400", ScaleBox,
            {Legend Model( 1, Properties( 0, {Marker( "Minus" ), Fill Color( 0 )} ) ), Legend Model(
                2,
                Properties( 0, {Line Color( 3 ), Fill Color( 0 )} )
            )}
        ),
        Dispatch( {}, "graph title", TextEditBox, {Set Text( "Variability Chart for Shrinkage" )} ),
        Dispatch( {}, "X title", TextEditBox, {Set Text( "Casting within Temperature" )} ),
        Dispatch( {}, "Graph Builder", FrameBox, {Marker Size( 2 )} )
    )
);

Code Explanation:

1. Open data table.
2. Create Graph Builder window.
3. Set graph size.
4. Hide control panel.
5. Define X, X, and Y variables.
6. Add mean points element.
7. Add jittered points element.
8. Add reference line to Temperature axis.
9. Customize legend properties.
10. Set graph title and axis labels.

Example 1844

Summary: Creates a variability chart with nested factors using operator and part configurations, displaying standard deviation charts within Graph Builder.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 531, 464 ),
    Show Control Panel( 0 ),
    Variables( X( :Temperature ), X( :Casting, Position( 1 ) ), Y( :Shrinkage ) ),
    Elements(
        Points( X( 1 ), X( 2 ), Y, Legend( 1 ), Summary Statistic( "Mean" ), Error Interval( "Range" ), Interval Style( "Band" ) ),
        Points( X( 1 ), X( 2 ), Y, Legend( 2 ), Jitter( "None" ) )
    ),
    SendToReport(
        Dispatch( {}, "Temperature", ScaleBox,
            {Add Ref Line( 3.5, "Solid", "Medium Light Gray", "", 1 ), Label Row( 2, Show Major Ticks( 0 ) )}
        ),
        Dispatch( {}, "400", ScaleBox,
            {Legend Model( 1, Properties( 0, {Marker( "Minus" ), Fill Color( 0 )} ) ), Legend Model(
                2,
                Properties( 0, {Line Color( 3 ), Fill Color( 0 )} )
            )}
        ),
        Dispatch( {}, "graph title", TextEditBox, {Set Text( "Variability Chart for Shrinkage" )} ),
        Dispatch( {}, "X title", TextEditBox, {Set Text( "Casting within Temperature" )} ),
        Dispatch( {}, "Graph Builder", FrameBox, {Marker Size( 2 )} )
    )
);

Code Explanation:

1. Open data table.
2. Create Graph Builder window.
3. Set window size.
4. Hide control panel.
5. Define variables: X, X, Y.
6. Add points element with mean summary and range error bands.
7. Add jittered points element.
8. Add reference line at 3.5 on Temperature scale.
9. Customize legend properties.
10. Set graph title and axis labels.

Example 1845

Summary: Creates a variability chart with nested factors using operator and part configurations, displaying standard deviation charts in Graph Builder.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 535, 455 ),
    Show Control Panel( 0 ),
    Variables( X( :height ), Y( :weight ) ),
    Elements( Points( X, Y, Legend( 4 ) ), Line Of Fit( X, Y, Legend( 6 ) ) ),
    SendToReport(
        Dispatch( {}, "height", ScaleBox, {Max( 76.9635779034077 )} ),
        Dispatch( {}, "weight", ScaleBox, {Min( 5.25227987752102 ), Max( 201.373603652071 ), Inc( 25 ), Minor Ticks( 0 )} ),
        Dispatch( {}, "Graph Builder", FrameBox,
            {Marker Size( 2 ), {Add Pin Annotation(
                Seg( Marker Seg( 1 ) ),
                Index( 39 ),
                Index Row( 39 ),
                UniqueID( 1180683047 ),
                FoundPt( {717, 157} ),
                Origin( {70.1036850751071, 172.033784817876} ),
                Offset( {8, 9} ),
                Tag Line
            ), Add Pin Annotation(
                Seg( Marker Seg( 1 ) ),
                Index( 7 ),
                Index Row( 7 ),
                UniqueID( 691854391 ),
                FoundPt( {124, 311} ),
                Origin( {51.0074683737235, 80.0858968472606} ),
                Offset( {-57, -95} ),
                Tag Line
            ), Add Pin Annotation(
                Seg( Marker Seg( 1 ) ),
                Index( 4 ),
                Index Row( 4 ),
                UniqueID( 691854388 ),
                FoundPt( {143, 354} ),
                Origin( {52.0652762959576, 62.2761707988982} ),
                Offset( {74, 44} ),
                Tag Line
            ), Add Pin Annotation(
                Seg( Marker Seg( 1 ) ),
                Index( 11 ),
                Index Row( 11 ),
                UniqueID( 1452711899 ),
                FoundPt( {347, 257} ),
                Origin( {64.8386487250506, 97.865127215503} ),
                Offset( {6, 65} ),
                Tag Line
            ), Add Pin Annotation(
                Seg( Marker Seg( 1 ) ),
                Index( 37 ),
                Index Row( 37 ),
                UniqueID( 570414821 ),
                FoundPt( {305, 222} ),
                Origin( {62.2317889517039, 117.036444064542} ),
                Offset( {-139, -88} ),
                Tag Line
            )}}
        )
    )
);

Code Explanation:

1. Open data table.
2. Create Graph Builder window.
3. Set window size.
4. Hide control panel.
5. Define X and Y variables.
6. Add points element.
7. Add line of fit element.
8. Set X-axis maximum.
9. Set Y-axis minimum and maximum.
10. Configure Y-axis increments and minor ticks.
11. Set marker size.
12. Add pin annotations at specified points.

Example 1846

Summary: Creates a variability chart with nested factors using operator and part configurations, displaying standard deviation charts in Graph Builder.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 487, 533 ),
    Show Control Panel( 0 ),
    Variables( Y( :height ), Y( :weight, Position( 1 ) ) ),
    Elements( Points( Y( 1 ), Y( 2 ), Legend( 6 ), Summary Statistic( "Mean" ), Error Bars( "Range" ), Interval Style( "Band " ) ) )
);

Code Explanation:

1. Open data table;
2. Launch Graph Builder.
3. Set window size.
4. Hide control panel.
5. Define Y variables.
6. Add points element.
7. Specify summary statistic.
8. Add error bars.
9. Set interval style.
10. Display graph.

Example 1847

Summary: Creates three Graph Builder windows with varying settings to visualize data from a nested factors configuration, displaying mean summary and error bars.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 366, 285 ),
    Show Control Panel( 0 ),
    Variables( X( :Operator ), X( :Part, Position( 1 ) ), Y( :Y ), Overlay( :Part ) ),
    Elements( Points( X( 1 ), X( 2 ), Y, Legend( 17 ), Summary Statistic( "Mean" ), Error Bars( "Range" ) ) )
);
Open("data_table.jmp");
Graph Builder(
    Size( 528, 496 ),
    Show Control Panel( 0 ),
    Variables( X( :age ), Y( :height ), Overlay( :sex ) ),
    Elements( Points( X, Y, Jitter( 0 ), Summary Statistic( "Mean" ), Error Bars( "Standard Error" ) ) )
);
Open("data_table.jmp");
Graph Builder(
    Size( 389, 250 ),
    Show Control Panel( 0 ),
    Variables( X( :Part ), Y( :Y ), Overlay( :Part ) ),
    Elements( Points( X, Y, Summary Statistic( "Mean" ), Error Bars( "Range" ) ) )
);

Code Explanation:

1. Open data table;
2. Create Graph Builder window.
3. Set window size to 366x285.
4. Hide control panel.
5. Define X, Y, and overlay variables.
6. Add points element with mean summary and range error bars.
7. Open data table;
8. Create Graph Builder window.
9. Set window size to 528x496.
10. Hide control panel.
11. Define X, Y, and overlay variables.
12. Add points element with jitter, mean summary, and standard error bars.
13. Open data table;
14. Create Graph Builder window.
15. Set window size to 389x250.
16. Hide control panel.
17. Define X, Y, and overlay variables.
18. Add points element with mean summary and range error bars.

Example 1848

Summary: Creates variability charts with nested factors using operator and part configurations, displaying standard deviation charts in JMP.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 366, 285 ),
    Show Control Panel( 0 ),
    Variables( X( :Operator ), X( :Part, Position( 1 ) ), Y( :Y ), Overlay( :Part ) ),
    Elements( Points( X( 1 ), X( 2 ), Y, Legend( 17 ), Summary Statistic( "Mean" ), Error Bars( "Range" ) ) )
);
Open("data_table.jmp");
Graph Builder(
    Size( 528, 496 ),
    Show Control Panel( 0 ),
    Variables( X( :age ), Y( :height ), Overlay( :sex ) ),
    Elements( Points( X, Y, Jitter( 0 ), Summary Statistic( "Mean" ), Error Bars( "Standard Error" ) ) )
);
Open("data_table.jmp");

Code Explanation:

1. Open data table;
2. Create Graph Builder window.
3. Set size to 366x285.
4. Hide control panel.
5. Define variables: Operator, Part, Y.
6. Overlay by Part.
7. Add points element.
8. Set summary statistic to Mean.
9. Add error bars for Range.
10. Open data table;

Example 1849

Summary: Creates a variability chart with nested factors using operator and part configurations, displaying standard deviation charts in Graph Builder.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 366, 285 ),
    Show Control Panel( 0 ),
    Variables( X( :Operator ), X( :Part, Position( 1 ) ), Y( :Y ), Overlay( :Part ) ),
    Elements(
        Points( X( 1 ), X( 2 ), Y, Legend( 17 ), Summary Statistic( "Mean" ), Error Interval( "Range" ), Interval Style( "Band " ) )
    )
);

Code Explanation:

1. Open data table.
2. Launch Graph Builder.
3. Set window size.
4. Hide control panel.
5. Define X variables.
6. Define Y variable.
7. Set overlay variable.
8. Add points element.
9. Configure X axis.
10. Configure Y axis.

Example 1850

Summary: Creates a variability chart with nested factors using Graph Builder, displaying standard deviation charts and mean summary statistics.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 528, 496 ),
    Show Control Panel( 0 ),
    Variables( X( :age ), Y( :height ), Overlay( :sex ) ),
    Elements( Points( X, Y, Jitter( 0 ), Summary Statistic( "Mean" ), Error Interval( "Standard Error" ), Interval Style( "Band" ) ) )
);

Code Explanation:

1. Open data table;
2. Launch Graph Builder.
3. Set window size.
4. Hide control panel.
5. Define X variable: age.
6. Define Y variable: height.
7. Add overlay variable: sex.
8. Add points element.
9. Disable jitter.
10. Display mean summary statistic.
11. Show standard error bands.

Example 1851

Summary: Creates variability charts with nested factors using operator and part configurations, displaying standard deviation charts in Graph Builder.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 366, 285 ),
    Show Control Panel( 0 ),
    Variables( X( :Operator ), X( :Part, Position( 1 ) ), Y( :Y ), Overlay( :Part ) ),
    Elements(
        Points( X( 1 ), X( 2 ), Y, Legend( 17 ), Summary Statistic( "Mean" ), Error Interval( "Range" ), Interval Style( "Band " ) )
    )
);
Open("data_table.jmp");
Graph Builder(
    Size( 528, 496 ),
    Show Control Panel( 0 ),
    Variables( X( :age ), Y( :height ), Overlay( :sex ) ),
    Elements( Points( X, Y, Jitter( 0 ), Summary Statistic( "Mean" ), Error Interval( "Standard Error" ), Interval Style( "Band" ) ) )
);
Open("data_table.jmp");
Graph Builder(
    Size( 389, 250 ),
    Show Control Panel( 0 ),
    Variables( X( :Part ), Y( :Y ), Overlay( :Part ) ),
    Elements( Points( X, Y, Summary Statistic( "Mean" ), Error Interval( "Range" ), Interval Style( "Band" ) ) )
);

Code Explanation:

1. Open data_table data
2. Create Graph Builder window.
3. Set size to 366x285.
4. Hide control panel.
5. Set X variables: Operator, Part.
6. Set Y variable: Y.
7. Overlay by Part.
8. Add points element.
9. Use mean summary statistic.
10. Display range error interval.
11. Open data_table data
12. Create Graph Builder window.
13. Set size to 528x496.
14. Hide control panel.
15. Set X variable: age.
16. Set Y variable: height.
17. Overlay by sex.
18. Add points element.
19. Apply jitter.
20. Use mean summary statistic.
21. Display standard error interval.
22. Open Gasket data again.
23. Create Graph Builder window.
24. Set size to 389x250.
25. Hide control panel.
26. Set X variable: Part.
27. Set Y variable: Y.
28. Overlay by Part.
29. Add points element.
30. Use mean summary statistic.
31. Display range error interval.

Example 1852

Summary: Creates two variability charts with nested factors using operator and part configurations, displaying standard deviation charts for each combination.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 366, 285 ),
    Show Control Panel( 0 ),
    Variables( X( :Operator ), X( :Part, Position( 1 ) ), Y( :Y ), Overlay( :Part ) ),
    Elements(
        Points( X( 1 ), X( 2 ), Y, Legend( 17 ), Summary Statistic( "Mean" ), Error Interval( "Range" ), Interval Style( "Band " ) )
    )
);
Open("data_table.jmp");
Graph Builder(
    Size( 528, 496 ),
    Show Control Panel( 0 ),
    Variables( X( :age ), Y( :height ), Overlay( :sex ) ),
    Elements( Points( X, Y, Jitter( 0 ), Summary Statistic( "Mean" ), Error Interval( "Standard Error" ), Interval Style( "Band" ) ) )
);
Open("data_table.jmp");

Code Explanation:

1. Open data_table data
2. Create Graph Builder window.
3. Set window size.
4. Hide control panel.
5. Define variables: Operator, Part, Y.
6. Overlay by Part.
7. Add points element.
8. Set summary statistic to Mean.
9. Use Range for error interval.
10. Display interval as band.
11. Open data_table data
12. Create Graph Builder window.
13. Set window size.
14. Hide control panel.
15. Define variables: age, height, sex.
16. Overlay by sex.
17. Add points element.
18. Apply jitter to points.
19. Set summary statistic to Mean.
20. Use Standard Error for error interval.
21. Display interval as band.
22. Open data_table data again.

Example 1853

Summary: Creates a Graph Builder window with nested factors, displaying standard deviation charts for sex and age groups.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 534, 1292 ),
    Show Control Panel( 0 ),
    Fit to Window( "Off" ),
    Variables( X( :sex ), Y( :weight ), Y( :weight ), Group X( :age ) ),
    Elements( Position( 1, 1 ), Points( X, Y, Legend( 30 ) ) ),
    Elements( Position( 1, 2 ), Points( X, Y, Legend( 31 ) ) )
);

Code Explanation:

1. Open data table.
2. Create Graph Builder window.
3. Set window size.
4. Hide control panel.
5. Disable fit to window.
6. Define variables: X(sex), Y(weight), Group X(age).
7. Add first points element.
8. Add second points element.
9. Position elements in grid.
10. Assign legends to elements.

Example 1854

Summary: Creates a variability chart with nested factors using Graph Builder, displaying standard deviation charts for age, height, and weight.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 578, 505 ),
    Show Control Panel( 0 ),
    Show Footer( 0 ),
    Variables( X( :age ), Y( :height ), Y( :weight ), Y( :weight ), Y( :height ), Y( :height ) ),
    Elements( Position( 1, 1 ), Points( X, Y, Legend( 6 ), Summary Statistic( "Range" ) ) ),
    Elements( Position( 1, 2 ), Line( X, Y, Legend( 2 ), Error Bars( "Interquartile Range" ) ) ),
    Elements( Position( 1, 3 ), Points( X, Y, Legend( 7 ), Summary Statistic( "Std Err" ) ) ),
    Elements( Position( 1, 4 ), Line( X, Y, Legend( 4 ), Error Bars( "Standard Deviation" ) ) ),
    Elements( Position( 1, 5 ), Points( X, Y, Legend( 8 ), Summary Statistic( "Median" ) ) )
);

Code Explanation:

1. Open data table.
2. Create Graph Builder window.
3. Set window size.
4. Hide control panel.
5. Hide footer.
6. Define variables: age, height, weight.
7. Add points element at position 1,1.
8. Add line element at position 1,2.
9. Add points element at position 1,3.
10. Add line element at position 1,4.
11. Add points element at position 1,5.

Example 1855

Summary: Creates a variability chart with nested factors using Graph Builder, displaying standard deviation charts and log-transformed intervals for height and weight.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 752, 377 ),
    Show Control Panel( 0 ),
    Legend Position( "Inside Left" ),
    Variables(
        X( :height ),
        Y( :weight ),
        Color( :sex ),
        Interval( Transform Column( "Log10[height]", Formula( Log10( :height ) ) ) ),
        Interval( Transform Column( "Log10[weight]", Formula( Log10( :weight ) ) ) )
    ),
    Elements( Points( X, Y, Legend( 10 ), Error Bars( "Two-way Interval" ) ) ),
    SendToReport(
        Dispatch( {}, "400", ScaleBox,
            {Legend Model(
                10,
                Properties( 0, {Marker( "FilledSquare" )}, Item ID( "F", 1 ) ),
                Properties( 1, {Marker( "Filled Up Triangle" )}, Item ID( "M", 1 ) ),
                Base( -1, 0, 0, Item ID( "±Log10[height] & ±Log10[weight]", 1 ) )
            )}
        ),
        Dispatch( {}, "400", LegendBox, {Set Title( "" ), Orientation( "Horizontal" ), Sides( "Left" )} )
    )
);

Code Explanation:

1. Open data table.
2. Create Graph Builder window.
3. Set window size.
4. Hide control panel.
5. Place legend inside left.
6. Define X variable.
7. Define Y variable.
8. Define color variable.
9. Add log-transformed height interval.
10. Add log-transformed weight interval.

Example 1856

Summary: Creates a variability chart with nested factors using Graph Builder, transforming height and weight to log10 scale, and displaying standard deviation charts.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 752, 377 ),
    Show Control Panel( 0 ),
    Legend Position( "Inside Left" ),
    Variables(
        X( :height ),
        Y( :weight ),
        Color( :sex ),
        Interval( Transform Column( "Log10[height]", Formula( Log10( :height ) ) ) ),
        Interval( Transform Column( "Log10[weight]", Formula( Log10( :weight ) ) ) )
    ),
    Elements( Points( X, Y, Legend( 10 ), Error Bars( "Two-way Interval" ), Interval Style( "Band" ) ) ),
    SendToReport(
        Dispatch( {}, "400", ScaleBox,
            {Legend Model(
                10,
                Properties( 0, {Marker( "FilledSquare" )}, Item ID( "F", 1 ) ),
                Properties( 1, {Marker( "Filled Up Triangle" )}, Item ID( "M", 1 ) ),
                Base( -1, 0, 0, Item ID( "±Log10[height] & ±Log10[weight]", 1 ) )
            )}
        ),
        Dispatch( {}, "400", LegendBox, {Set Title( "" ), Orientation( "Horizontal" ), Sides( "Left" )} )
    )
);

Code Explanation:

1. Open data_table data
2. Create Graph Builder window.
3. Set window size.
4. Hide control panel.
5. Place legend inside left.
6. Assign variables: height, weight, sex.
7. Transform height and weight to log10 scale.
8. Add points element with error bars.
9. Style intervals as bands.
10. Customize legend and scale properties.

Example 1857

Summary: Creates a variability chart with nested factors using Graph Builder, displaying standard deviation charts and applying mean summary statistics.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 534, 420 ),
    Show Control Panel( 0 ),
    Variables( Y( :name ), Y( :sex, Position( 1 ) ) ),
    Elements( Points( Y( 1 ), Y( 2 ), Legend( 7 ), Summary Statistic( "Mean" ) ) )
);

Code Explanation:

1. Open data table;
2. Launch Graph Builder.
3. Set window size.
4. Hide control panel.
5. Define Y variables.
6. Add points element.
7. Set Y positions.
8. Apply legend.
9. Use mean summary statistic.

Example 1858

Summary: Creates a variability chart with nested factors using operator and part configurations, displaying standard deviation charts.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 534, 520 ),
    Show Control Panel( 0 ),
    Variables( X( :weight ), Y( :height ), Y( :weight, Position( 1 ) ), Interval( :weight ) ),
    Elements( Points( X, Y( 1 ), Y( 2 ), Legend( 2 ), Error Interval( "Custom Interval" ), Interval Style( "Band" ) ) )
);

Code Explanation:

1. Open data table;
2. Launch Graph Builder.
3. Set window size.
4. Hide control panel.
5. Define X variable: weight.
6. Define Y variables: height, weight.
7. Set position for second Y.
8. Specify interval variable: weight.
9. Add points element.
10. Configure error interval style.

Example 1859

Summary: Creates a variability chart with nested factors using Graph Builder, displaying standard deviation charts and custom interval error bars.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 534, 520 ),
    Show Control Panel( 0 ),
    Variables( X( :weight ), Y( :height ), Y( :weight, Position( 1 ) ), Interval( :weight ) ),
    Elements( Points( X, Y( 1 ), Y( 2 ), Legend( 2 ), Error Bars( "Custom Interval" ) ) )
);

Code Explanation:

1. Open data table;
2. Launch Graph Builder.
3. Set window size.
4. Hide control panel.
5. Define X variable.
6. Define first Y variable.
7. Define second Y variable.
8. Define interval variable.
9. Add points element.
10. Add error bars with custom intervals.

Example 1860

Summary: Creates a graph with nested factors using Graph Builder, displaying points with color and shape variables.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 534, 453 ),
    Show Control Panel( 0 ),
    Include Missing Categories( 1 ),
    Variables( Color( :GDP per Capita ), Shape( :Territory ) ),
    Elements( Points( Legend( 6 ) ) )
);

Code Explanation:

1. Open data table.
2. Launch Graph Builder.
3. Set window size.
4. Hide control panel.
5. Include missing categories.
6. Set color variable.
7. Set shape variable.
8. Add points element.
9. Enable legend for points.
10. Display graph.

Example 1861

Summary: Creates a variability chart with nested factors using Graph Builder, displaying points and smoother elements.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 472, 347 ),
    Show Control Panel( 0 ),
    Variables( X( :Weeks ), Y( :Degrees ), Color( :Strength ) ),
    Elements( Points( X, Y, Legend( 10 ) ), Smoother( X, Y, Legend( 11 ) ) ),
    SendToReport( Dispatch( {}, "400", ScaleBox, {Legend Model( 10, Properties( 0, {gradient( {Width( 12 ), Show Labels( 0 )} )} ) )} ) )
);

Code Explanation:

1. Open data table.
2. Create Graph Builder.
3. Set window size.
4. Hide control panel.
5. Define X, Y, and Color variables.
6. Add points element.
7. Add smoother element.
8. Send report message.
9. Configure legend model.
10. Set gradient properties.

Example 1862

Summary: Creates a variability chart with nested factors using Graph Builder, displaying standard deviation charts and adjusting marker sizes.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 380, 303 ),
    Show Control Panel( 0 ),
    Variables( X( :age ), Y( :weight ), Y( :weight ), Overlay( :height ) ),
    Elements( Position( 1, 1 ), Points( X, Y, Legend( 16 ), Summary Statistic( "Variance" ) ) ),
    Elements( Position( 1, 2 ), Points( X, Y, Legend( 18 ), Summary Statistic( "Std Dev" ) ) ),
    SendToReport(
        Dispatch( {}, "Graph Builder", FrameBox, {Marker Size( 6 )} ),
        Dispatch( {}, "Graph Builder", FrameBox( 2 ), {Marker Size( 6 )} )
    )
);

Code Explanation:

1. Open data table;
2. Create Graph Builder object.
3. Set window size to 380x303.
4. Hide control panel.
5. Assign variables: X=age, Y=weight, Overlay=height.
6. Add first Points element with variance summary.
7. Add second Points element with standard deviation summary.
8. Adjust marker size for first frame to 6.
9. Adjust marker size for second frame to 6.
10. Display graph.

Example 1863

Summary: Creates a graph builder object to visualize data from a nested factors dataset, with customized Y-axis label font and background color.

Code:

dt under test = Open("data_table.jmp");
obj = Graph Builder(
    Show Control Panel( 0 ),
    Variables( X( :Weight ), Y( :Turning Circle ) ),
    Elements( Points( X, Y, Legend( 5 ) ) ),
    SendToReport(
        Dispatch( {}, "Turning Circle", ScaleBox, {Label Row( Set Font( "Courier" ) )} ),
        Dispatch( {}, "Graph Builder", FrameBox, {Background Color( 74 )} )
    )
);

Code Explanation:

1. Open data table.
2. Create Graph Builder object.
3. Hide control panel.
4. Set X variable.
5. Set Y variable.
6. Add points element.
7. Customize Y axis label font.
8. Set background color.

Example 1864

Summary: Creates a graph builder object with nested factors, displaying points and standard deviation charts.

Code:

dt under test = Open("data_table.jmp");
obj = Graph Builder(
    Show Control Panel( 0 ),
    Variables( X( :Weight ), Y( :Type ), Color( :Country ) ),
    Elements( Points( X, Y, Legend( 4 ) ) ),
    SendToReport(
        Dispatch( {}, "Weight", ScaleBox, {Label Row( Label Orientation( "Vertical" ) )} ),
        Dispatch( {}, "Graph Builder", FrameBox, {Background Color( 32 )} )
    )
);

Code Explanation:

1. Open data table.
2. Create Graph Builder object.
3. Hide control panel.
4. Set X variable: Weight.
5. Set Y variable: Type.
6. Set color variable: Country.
7. Add points element.
8. Set legend for points.
9. Rotate weight label vertically.
10. Change background color.

Example 1865

Summary: Creates a graph builder object to visualize data with nested factors, utilizing Graph Builder and SendToReport features.

Code:

dt under test = Open("data_table.jmp");
obj = Graph Builder(
    Show Control Panel( 0 ),
    Variables( X( :Country ), Y( :Weight ), Overlay( :Type ) ),
    Elements( Points( X, Y, Legend( 9 ) ) ),
    SendToReport(
        Dispatch( {}, "Country", ScaleBox, {Label Row( Set Font( "Courier" ) )} ),
        Dispatch( {}, "Graph Builder", FrameBox, {Marker Size( 6 )} )
    )
);

Code Explanation:

1. Open data table.
2. Create Graph Builder object.
3. Hide control panel.
4. Set X variable to Country.
5. Set Y variable to Weight.
6. Set overlay variable to Type.
7. Add points element.
8. Set legend for points.
9. Change country label font.
10. Set marker size to 6.

Example 1866

Summary: Creates a variability chart with nested factors using Graph Builder, configuring type and sex scales as geodesic with no minor ticks, and customizing the frame with background color, US states map, grid, and reference lines.

Code:

dt under test = Open("data_table.jmp");
obj = Graph Builder(
    Show Control Panel( 0 ),
    Variables( X( :type ), Y( :sex ), Color( :country ) ),
    Elements( Points( X, Y, Legend( 16 ) ) ),
    SendToReport(
        Dispatch( {}, "type", ScaleBox, {Scale( "Geodesic" ), Minor Ticks( 0 )} ),
        Dispatch( {}, "sex", ScaleBox, {Scale( "Geodesic" ), Minor Ticks( 0 )} ),
        Dispatch( {}, "Graph Builder", FrameBox,
            {Background Color( 78 ), Background Map( Boundaries( "US States" ) ), Grid Line Order( 2 ), Reference Line Order( 4 )}
        )
    )
);

Code Explanation:

1. Open data table.
2. Create Graph Builder object.
3. Hide control panel.
4. Set X variable to "type".
5. Set Y variable to "sex".
6. Set color variable to "country".
7. Add points element.
8. Configure type scale: geodesic, no minor ticks.
9. Configure sex scale: geodesic, no minor ticks.
10. Customize frame: background color, US states map, grid and reference lines order.

Example 1867

Summary: Creates a graph builder object to visualize moving average data over time, utilizing Graph Builder and Points elements.

Code:

dt under test = Open("data_table.jmp");
obj = Graph Builder( Show Control Panel( 0 ), Variables( X( :Date ), Y( :moving avg. ) ), Elements( Points( X, Y, Legend( 6 ) ) ) );

Code Explanation:

1. Open data table.
2. Create Graph Builder object.
3. Hide control panel.
4. Set X variable to Date.
5. Set Y variable to moving avg.
6. Add points element.
7. Assign legend to point element.

Example 1868

Summary: Creates a variability chart with nested factors using Graph Builder, displaying standard deviation charts and customizing X-axis scale.

Code:

Names Default To Here( 1 );
dt = Open("data_table.jmp");
Graph Builder(
    Show Control Panel( 0 ),
    Variables( X( :name ), Y( :age ) ),
    Elements( Points( X, Y, Legend( 1 ), Jitter( 0 ) ) ),
    SendToReport( Dispatch( {}, "name", ScaleBox, {Show Major Ticks( 0 ), Rotated Labels( "Automatic" )} ) )
);

Code Explanation:

1. Set default names scope.
2. Open data table;
3. Launch Graph Builder.
4. Hide control panel.
5. Set X variable.
6. Set Y variable.
7. Add points element.
8. Disable jitter.
9. Customize X-axis scale.
10. Rotate X-axis labels.

Example 1869

Summary: Creates a variability chart with nested factors using Graph Builder, displaying standard deviation charts and customizing axis labels.

Code:

Names Default To Here( 1 );
dt = Open("data_table.jmp");
Graph Builder(
    Size( 570, 559 ),
    Show Control Panel( 0 ),
    Variables( X( :sex ), X( :name, Position( 1 ) ), Y( :age ) ),
    Elements( Points( X( 1 ), X( 2 ), Y, Legend( 1 ), Jitter( 0 ) ) ),
    SendToReport( Dispatch( {}, "sex", ScaleBox, {Show Major Ticks( 0 ), Show Minor Ticks( 0 ), Rotated Labels( "Automatic" )} ) )
);

Code Explanation:

1. Set default name context.
2. Open data table;
3. Create Graph Builder object.
4. Set window size.
5. Hide control panel.
6. Define X and Y variables.
7. Add points element.
8. Customize sex axis ticks.
9. Customize name axis ticks.
10. Rotate labels automatically.

Example 1870

Summary: Creates a variability chart with nested factors using Graph Builder, displaying standard deviation charts and customizing x-axis labels.

Code:

Names Default To Here( 1 );
dt = Open("data_table.jmp");
Graph Builder(
    Size( 570, 559 ),
    Show Control Panel( 0 ),
    Variables( X( :sex ), X( :age, Position( 1 ) ), X( :name, Position( 1 ) ), Y( :age ) ),
    Elements( Points( X( 1 ), X( 2 ), X( 3 ), Y, Legend( 1 ), Jitter( 0 ) ) ),
    SendToReport( Dispatch( {}, "sex", ScaleBox, {Show Major Ticks( 0 ), Show Minor Ticks( 0 ), Rotated Labels( "Automatic" )} ) )
);

Code Explanation:

1. Set default names.
2. Open data table.
3. Create Graph Builder.
4. Set window size.
5. Hide control panel.
6. Define variables.
7. Add points element.
8. Customize x-axis.
9. Customize y-axis.
10. Display report.

Example 1871

Summary: Creates a variability chart with nested factors using Graph Builder, displaying standard deviation charts and configuring window size, control panel visibility, and plot elements.

Code:

Names Default To Here( 1 );
dt = Open("data_table.jmp");
Graph Builder(
    Size( 569, 525 ),
    Show Control Panel( 0 ),
    Variables( X( :weight ), Y( :sex ), Y( :age, Position( 1 ) ), Y( :name, Position( 1 ) ) ),
    Elements( Points( X, Y( 1 ), Y( 2 ), Y( 3 ), Legend( 1 ), Jitter( 0 ) ) )
);

Code Explanation:

1. Set default names.
2. Open data table;
3. Create Graph Builder.
4. Set window size.
5. Hide control panel.
6. Define X variable.
7. Define Y variables.
8. Add points element.
9. Assign legend.
10. Disable jitter.

Example 1872

Summary: Creates a graph builder with nested factors using operator and part configurations, displaying standard deviation charts.

Code:

dt = Open("data_table.jmp");
dt << Graph Builder( Size( 354, 367 ), Show Control Panel( 0 ), Variables( X( :sex ) ), Elements( Points( X, Legend( 2 ) ) ) );

Code Explanation:

1. Open data table.
2. Create new graph builder.
3. Set graph size.
4. Hide control panel.
5. Add X variable.
6. Add points element.
7. Assign legend to points.

Example 1873

Summary: Creates a graph with points, displaying age on the x-axis and height on the y-axis, using Graph Builder.

Code:

dt = Open("data_table.jmp");
obj = Graph Builder(
    Size( 459, 278 ),
    Show Control Panel( 0 ),
    Variables( X( :age ), Y( :height ) ),
    Elements( Points( X, Y, Legend( 5 ) ) )
);

Code Explanation:

1. Open data table;
2. Create new Graph Builder object.
3. Set window size to 459x278.
4. Hide control panel.
5. Assign X variable as "age".
6. Assign Y variable as "height".
7. Add points element to graph.
8. Set legend for points.
9. Display graph with jittered markers.

Example 1874

Summary: Creates a graph builder object with nested factors using operator and part configurations, displaying standard deviation charts.

Code:

dt = Open("data_table.jmp");
:Position2 << set property( "missing value codes", {"o"} );
obj = Graph Builder(
    Size( 562, 406 ),
    Show Control Panel( 0 ),
    Variables( X( :Weight ), Y( :Height ), Color( :Position2 ) ),
    Elements( Points( X, Y, Legend( 6 ) ) )
);

Code Explanation:

1. Open data table;
2. Set missing value codes for Position2.
3. Create Graph Builder object.
4. Set window size to 562x406.
5. Hide control panel.
6. Assign variables: X=Weight, Y=Height, Color=Position2.
7. Add Points element.
8. Set legend for Points to 6.

Example 1875

Summary: Creates a variability chart with nested factors using operator and part configurations, displaying standard deviation charts.

Code:

dt = Open("data_table.jmp");
Graph Builder(
    Size( 363, 323 ),
    Show Control Panel( 0 ),
    Show Legend( 0 ),
    Variables(
        Y( :Name( "Sales($M)" ) ),
        Y( :Name( "Profit($M)" ), Position( 1 ) ),
        Y( :Name( "#employees" ), Position( 1 ) ),
        Y( :Name( "Profits/emp" ), Position( 1 ) ),
        Y( :Name( "Assets($Mil.)" ), Position( 1 ) ),
        Y( :Name( "Sales/emp" ), Position( 1 ) ),
        Y( :Name( "Stockholder's Eq($Mil.)" ), Position( 1 ) )
    ),
    Elements( Box Plot( Y( 1 ), Y( 2 ), Y( 3 ), Y( 4 ), Y( 5 ), Y( 6 ), Y( 7 ), Legend( 3 ) ) )
);

Code Explanation:

1. Open data_table data
2. Create Graph Builder object.
3. Set graph size.
4. Hide control panel.
5. Hide legend.
6. Define Y variables.
7. Position multiple Y variables.
8. Add box plot element.
9. Specify Y positions for box plot.
10. Set legend for box plot.

Example 1876

Summary: Creates a variability chart with nested factors using operator and part configurations, displaying standard deviation charts in Graph Builder.

Code:

Open("data_table.jmp") << Graph Builder(
    Size( 809, 409 ),
    Show Control Panel( 0 ),
    Variables( X( :Mfr ), Y( :Sugars ), Overlay( :Calories ) ),
    Elements( Points( X, Y, Legend( 5 ), Summary Statistic( "Variance" ) ) ),
    SendToReport(
        Dispatch( {}, "Graph Builder", FrameBox,
            Add Pin Annotation(
                Seg( Marker Seg( 4 ) ),
                Index( 0 ),
                Index Row( 5 ),
                UniqueID( 680591264 ),
                FoundPt( {377, 378} ),
                Origin( {1.99473684210526, 4.36260623229462} )
            )
        )
    )
);

Code Explanation:

1. Open data table;
2. Launch Graph Builder.
3. Set graph size to 809x409.
4. Hide control panel.
5. Assign variables: X=Mfr, Y=Sugars, Overlay=Calories.
6. Create points element with variance summary statistic.
7. Send report to Graph Builder.
8. Add pin annotation to graph.
9. Specify segment for annotation.
10. Define annotation properties.

Example 1877

Summary: Creates a variability chart with nested factors using operator and part configurations, displaying standard deviation charts.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 421, 448 ),
    Show Control Panel( 0 ),
    Variables( X( :Size, Order By( :Wt, Ascending, Order Statistic( "Mean" ) ) ), Y( :Wt ) ),
    Elements( Points( X, Y, Legend( 4 ), Summary Statistic( "Mean" ) ) )
);

Code Explanation:

1. Open data table;
2. Create Graph Builder window.
3. Set graph size to 421x448.
4. Hide control panel.
5. Assign X variable: Size.
6. Order X by Wt, ascending.
7. Use mean for ordering statistic.
8. Assign Y variable: Wt.
9. Add points element.
10. Display mean summary statistic.

Example 1878

Summary: Creates a graph builder with nested factors using operator and part configurations, displaying standard deviation charts.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 662, 653 ),
    Show Control Panel( 0 ),
    Variables( X( :Rotten Tomatoes Score ), Y( :Genre, Order By( :Rotten Tomatoes Score, Ascending, Order Statistic( "Mean" ) ) ) ),
    Elements( Points( X, Y, Legend( 23 ) ) )
);

Code Explanation:

1. Open data table;
2. Launch Graph Builder.
3. Set window size.
4. Hide control panel.
5. Assign X variable.
6. Assign Y variable.
7. Order Y by mean.
8. Create points element.
9. Display legend.
10. Plot graph.

Example 1879

Summary: Creates a graph builder with a local data filter to visualize height against weight for female subjects, utilizing Graph Builder and hiding the control panel.

Code:

Open("data_table.jmp");
Graph Builder(
    Show Control Panel( 0 ),
    Variables( X( :weight ), Y( :height ) ),
    Local Data Filter( Add Filter( columns( :sex ), Where( :sex == "F" ) ), Mode( Select( 0 ), Show( 1 ), Include( 1 ) ) )
);

Code Explanation:

1. Open data table.
2. Create graph builder.
3. Hide control panel.
4. Set X variable to weight.
5. Set Y variable to height.
6. Add local data filter.
7. Filter by sex column.
8. Set filter condition to female.
9. Set filter mode to select off.
10. Show filter on.

Example 1880

Summary: Creates a variability chart with nested factors using operator and part configurations, displaying standard deviation charts.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 528, 453 ),
    Show Control Panel( 0 ),
    Variables( X( :RunPulse ), X( :RstPulse, Position( 1 ) ), X( :MaxPulse, Position( 1 ) ), Y( :Runtime ) ),
    Elements( Points( X( 1 ), X( 2 ), X( 3 ), Y, Legend( 1 ) ), Line( X( 1 ), X( 2 ), X( 3 ), Y, Legend( 3 ) ) )
);

Code Explanation:

1. Open data table;
2. Create Graph Builder window.
3. Set window size to 528x453.
4. Hide control panel.
5. Assign RunPulse to X-axis.
6. Assign RstPulse to X-axis, position 1.
7. Assign MaxPulse to X-axis, position 1.
8. Assign Runtime to Y-axis.
9. Add points element for X1, X2, X3, Y.
10. Add line element for X1, X2, X3, Y.

Example 1881

Summary: Creates a variability chart with nested factors using Graph Builder, displaying standard deviation charts for name and height variables.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 534, 447 ),
    Show Control Panel( 0 ),
    Variables( X( :age ), Y( :name ), Y( :height, Position( 1 ), Side( "Right" ) ) ),
    Elements( Points( X, Y( 1 ), Legend( 14 ) ), Points( X, Y( 2 ), Legend( 15 ) ) )
);

Code Explanation:

1. Open data table;
2. Launch Graph Builder.
3. Set window size.
4. Hide control panel.
5. Assign variables: X=age, Y=name, Y=height.
6. Position height on right Y-axis.
7. Add points element for name.
8. Add points element for height.
9. Assign legend for name.
10. Assign legend for height.

Example 1882

Summary: Creates a variability chart with nested factors using Graph Builder, displaying standard deviation charts and utilizing variance summary statistics.

Code:

Open("data_table.jmp") << Graph Builder(
    Size( 804, 409 ),
    Show Control Panel( 0 ),
    Variables( X( :Mfr ), Y( :Sugars ) ),
    Elements( Points( X, Y, Legend( 5 ), Summary Statistic( "Variance" ) ) )
);

Code Explanation:

1. Open data table.
2. Launch Graph Builder.
3. Set window size.
4. Hide control panel.
5. Assign X variable.
6. Assign Y variable.
7. Add points element.
8. Set legend position.
9. Use variance summary statistic.

Example 1883

Summary: Creates a variability chart with nested factors using Graph Builder, displaying points and smoother elements with assigned legends.

Code:

Open("data_table.jmp");
Graph Builder(
    Show Control Panel( 0 ),
    Variables( X( :height ), Y( :weight ) ),
    Elements( Points( X, Y, Legend( 7 ) ), Smoother( X, Y, Legend( 8 ) ) )
);

Code Explanation:

1. Open data table;
2. Launch Graph Builder.
3. Hide control panel.
4. Set X variable to height.
5. Set Y variable to weight.
6. Add points element.
7. Add smoother element.
8. Assign points legend.
9. Assign smoother legend.
10. Display graph.

Example 1884

Summary: Creates a variability chart with nested factors using Graph Builder, configuring X and Y variables, color points by height, and size points by age squared.

Code:

Open("data_table.jmp");
Graph Builder(
    Show Control Panel( 0 ),
    Variables(
        X( :age ),
        Y( :weight ),
        Color( :height ),
        Size( Transform Column( "age^2", Format( "Fixed Dec", 8, 0 ), Formula( :age * :age ) ) )
    ),
    Elements( Smoother( X, Y, Legend( 9 ) ), Points( X, Y, Legend( 10 ) ) ),
    SendToReport( Dispatch( {}, "400", ScaleBox, {Legend Model( 9, Properties( 0, {Line Width( 5 )} ) )} ) )
);

Code Explanation:

1. Open data table;
2. Launch Graph Builder.
3. Hide control panel.
4. Set X variable to age.
5. Set Y variable to weight.
6. Color points by height.
7. Size points by age squared.
8. Add smoother element.
9. Add points element.
10. Customize smoother legend line width.

Example 1885

Summary: Creates a Graph Builder with nested factors, using categorical color theme and smoother elements to visualize relationships between HDI Ranking, Average Years of Education of Adults, HDI, and Literacy Rate.

Code:

Open("data_table.jmp");
Graph Builder(
    Show Control Panel( 0 ),
    Categorical Color Theme(
        {"custom", 8193, {{128, 128, 255}, {255, 0, 255}, {0, 158, 115}, {0, 114, 178}, {213, 94, 0}, {204, 121, 167}, {250, 228, 66},
        Missing( "Black" )}}
    ),
    Variables( X( :HDI Ranking ), Y( :Average Years of Education of Adults ), Y( :HDI ), Y( :Literacy Rate ) ),
    Elements( Position( 1, 1 ), Smoother( X, Y, Legend( 12 ) ) ),
    Elements( Position( 1, 2 ), Smoother( X, Y, Legend( 10 ) ) ),
    Elements( Position( 1, 3 ), Smoother( X, Y, Legend( 6 ) ) )
);

Code Explanation:

1. Open data file.
2. Create Graph Builder.
3. Hide control panel.
4. Set categorical color theme.
5. Define X variable.
6. Define first Y variable.
7. Define second Y variable.
8. Define third Y variable.
9. Add first smoother element.
10. Add second smoother element.
11. Add third smoother element.

Example 1886

Summary: Creates a variability chart with nested factors using Graph Builder, applying log scale to the weight axis and formatting it for best display.

Code:

Open("data_table.jmp");
Graph Builder(
    Variables( X( :height ), Y( :weight ) ),
    Elements( Points( X, Y, Legend( 2 ) ), Smoother( X, Y, Legend( 3 ), Method( "Moving Box" ) ) ),
    SendToReport(
        Dispatch( {}, "weight", ScaleBox, {Scale( "Log" ), Format( "Best", 6 ), Min( 50 ), Max( 200 ), Inc( 1 ), Minor Ticks( 1 )} )
    )
);

Code Explanation:

1. Open data table;
2. Launch Graph Builder.
3. Set X variable to height.
4. Set Y variable to weight.
5. Add points element.
6. Add smoother element.
7. Use Moving Box method.
8. Apply log scale to weight axis.
9. Format weight axis.
10. Set axis limits and increments.

Example 1887

Summary: Creates a variability chart with nested factors using Graph Builder, displaying standard deviation charts and utilizing color coding based on Body Mass.

Code:

dt = Open("data_table.jmp");
dt << Clear Row States;
gb1 = dt << Graph Builder(
    Show Control Panel( 0 ),
    Variables( X( :Culmen Length ), Y( :Flipper Length ), Color( :Body Mass ) ),
    Elements( Points( X, Y, Legend( 7 ) ), Smoother( X, Y, Legend( 8 ) ) )
);

Code Explanation:

1. Open data table;
2. Clear row states.
3. Create Graph Builder object.
4. Hide control panel.
5. Set X variable: Culmen Length.
6. Set Y variable: Flipper Length.
7. Set color variable: Body Mass.
8. Add points element.
9. Add smoother element.
10. Assign legend for points.
11. Assign legend for smoother.

Example 1888

Summary: Creates two Graph Builder objects to visualize relationships between Culmen Length, Flipper Length, and Body Mass/Species in a data table.

Code:

dt = Open("data_table.jmp");
dt << Clear Row States;
gb1 = dt << Graph Builder(
    Show Control Panel( 0 ),
    Variables( X( :Culmen Length ), Y( :Flipper Length ), Color( :Body Mass ) ),
    Elements( Points( X, Y, Legend( 7 ) ), Smoother( X, Y, Legend( 8 ) ) )
);
gb2 = dt << Graph Builder(
    Show Control Panel( 0 ),
    Variables( X( :Culmen Length ), Y( :Flipper Length ), Color( :Species ) ),
    Elements( Points( X, Y, Legend( 7 ) ), Smoother( X, Y, Legend( 8 ) ) )
);

Code Explanation:

1. Open data table;
2. Clear row states.
3. Create first Graph Builder object.
4. Hide control panel.
5. Set X, Y, and color variables.
6. Add points and smoother elements.
7. Create second Graph Builder object.
8. Hide control panel.
9. Set X, Y, and color variables.
10. Add points and smoother elements.

Example 1889

Summary: Creates a variability chart with nested factors using Graph Builder, displaying standard deviation charts and customizing line styles and widths.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 534, 492 ),
    Show Control Panel( 0 ),
    Variables( X( :height ), Y( :weight ), Group X( :sex ), Overlay( :age ) ),
    Elements( Points( X, Y, Legend( 18 ) ), Smoother( X, Y, Legend( 19 ) ) ),
    SendToReport(
        Dispatch( {}, "400", ScaleBox,
            {Legend Model(
                19,
                Properties( 0, {Line Style( "Dashed" )}, Item ID( "12", 1 ) ),
                Properties( 1, {Line Width( 5 )}, Item ID( "13", 1 ) ),
                Properties( 3, {Line Style( "Dense Dash" )}, Item ID( "15", 1 ) ),
                Properties( 5, {Line Width( 5 )}, Item ID( "17", 1 ) )
            )}
        )
    )
);

Code Explanation:

1. Open data table;
2. Launch Graph Builder.
3. Set window size.
4. Hide control panel.
5. Assign variables: height, weight, sex, age.
6. Add points element.
7. Add smoother element.
8. Customize smoother line style.
9. Customize smoother line width.
10. Customize additional line styles and widths.

Example 1890

Summary: Creates a variability chart with nested factors using Graph Builder, displaying standard deviation charts and utilizing operator and part configurations.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 528, 450 ),
    Show Control Panel( 0 ),
    Variables( X( :Age ), Y( :Fare ), Overlay( :Passenger Class ), Color( :Passenger Class ) ),
    Elements( Smoother( X, Y, Legend( 20 ), Summary Statistic( "Mean" ), Confidence of Fit( 1 ) ) )
);

Code Explanation:

1. Open data table;
2. Create Graph Builder window.
3. Set window size to 528x450.
4. Hide control panel.
5. Assign Age to X-axis.
6. Assign Fare to Y-axis.
7. Use Passenger Class for overlay.
8. Use Passenger Class for color.
9. Add smoother element.
10. Set summary statistic to mean.
11. Enable confidence of fit.

Example 1891

Summary: Creates a variability chart with nested factors using operator and part configurations, displaying standard deviation charts in Graph Builder.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 658, 592 ),
    Show Control Panel( 0 ),
    Variables(
        X( :Revenue ),
        Y( :Product Cost ),
        Wrap( :Product Line ),
        Overlay( :Product Line, Overlay Encoding( "Style" ) ),
        Color( :Product Line )
    ),
    Elements( Points( X, Y, Legend( 30 ) ), Smoother( X, Y, Legend( 31 ) ) )
);

Code Explanation:

1. Open data table.
2. Launch Graph Builder.
3. Set window size.
4. Hide control panel.
5. Define X variable.
6. Define Y variable.
7. Wrap by product line.
8. Overlay by product line.
9. Color by product line.
10. Add points element.
11. Add smoother element.

Example 1892

Summary: Creates three Graph Builder objects to visualize and analyze data with nested factors, featuring smoothers, points, and summary statistics.

Code:

dt = Open("data_table.jmp");
gb = dt << Graph Builder(
    Size( 534, 486 ),
    Show Control Panel( 0 ),
    Variables( X( :age ), Y( :weight ), Group X( :sex ) ),
    Elements(
        Smoother( X, Y, Legend( 9 ), Summary Statistic( "Max" ), Method( "Local Kernel" ), Degree( "Quadratic" ), Confidence of Fit( 1 ) )
    )
);
gb1 = dt << Graph Builder(
    Size( 534, 456 ),
    Show Control Panel( 0 ),
    Variables( X( :height ), Y( :weight ), Overlay( :sex ) ),
    Elements( Smoother( X, Y, Legend( 9 ), Summary Statistic( "Median" ), Method( "Moving Box" ) ) )
);
gb3 = dt << Graph Builder(
    Show Control Panel( 0 ),
    Variables( X( :age ), Y( :height ) ),
    Elements(
        Points( X, Y, Legend( 3 ), Summary Statistic( "Sum" ) ),
        Smoother(
            X,
            Y,
            Legend( 4 ),
            Summary Statistic( "Sum" ),
            Method( "Local Kernel" ),
            Lambda( 0.337287308658869 ),
            Local Width( 0.5849 )
        )
    )
);

Code Explanation:

1. Open table.
2. Create graph builder object.
3. Set size and hide control panel.
4. Define variables: age, weight, sex.
5. Add smoother element.
6. Set summary statistic to max.
7. Use local kernel method.
8. Set degree to quadratic.
9. Enable confidence of fit.
10. Create second graph builder object.
11. Set size and hide control panel.
12. Define variables: height, weight, sex.
13. Add smoother element.
14. Set summary statistic to median.
15. Use moving box method.
16. Create third graph builder object.
17. Hide control panel.
18. Define variables: age, height.
19. Add points element.
20. Set summary statistic to sum.
21. Add smoother element.
22. Set summary statistic to sum.
23. Use local kernel method.
24. Set lambda value.
25. Set local width.

Example 1893

Summary: Creates a variability chart with nested factors using Graph Builder, displaying standard deviation charts and overlaying by sex.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 562, 447 ),
    Show Control Panel( 0 ),
    Variables( X( :height ), Y( :weight ), Overlay( :sex ) ),
    Elements( Points( X, Y, Legend( 1 ) ), Smoother( X, Y, Legend( 2 ), Response Axis( "X" ) ) ),
    SendToReport( Dispatch( {"Smoother"}, "", OutlineBox, {Close( 0 )} ) )
);

Code Explanation:

1. Open data_table data
2. Create Graph Builder window.
3. Set window size to 562x447.
4. Hide control panel.
5. Assign height to X-axis.
6. Assign weight to Y-axis.
7. Overlay by sex.
8. Add points element.
9. Add smoother element.
10. Close smoother outline box.

Example 1894

Summary: Creates a variability chart with nested factors using Graph Builder, displaying standard deviation charts and utilizing time series fit.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 528, 456 ),
    Show Control Panel( 0 ),
    Variables( X( :date ), Y( :month ) ),
    Elements( Points( X, Y, Legend( 6 ) ), Line Of Fit( X, Y, Legend( 8 ), Fit( "Time Series" ), Confidence of Fit( 0 ) ) )
);

Code Explanation:

1. Open data table.
2. Launch Graph Builder.
3. Set window size.
4. Hide control panel.
5. Assign X and Y variables.
6. Add points element.
7. Add line of fit element.
8. Use time series fit.
9. Disable confidence interval.
10. Display graph.

Example 1895

Summary: Creates a variability chart with nested factors using Graph Builder, displaying standard deviation charts and grouping data by sex.

Code:

dt = Open("data_table.jmp");
obj = Graph Builder(
    Show Control Panel( 0 ),
    Variables( X( :height ), Y( :weight ) ),
    Elements( Points( X, Y, Legend( 3 ) ), Smoother( X, Y, Legend( 4 ) ) ),
    By( :sex )
);

Code Explanation:

1. Open data table;
2. Create Graph Builder object.
3. Hide control panel.
4. Set X variable to height.
5. Set Y variable to weight.
6. Add points element.
7. Add smoother element.
8. Group by sex.

Example 1896

Summary: Creates a graph builder object to visualize height and weight data for female subjects, utilizing points and smoother elements.

Code:

dt = Open("data_table.jmp");
obj = Graph Builder(
    Show Control Panel( 0 ),
    Variables( X( :height ), Y( :weight ) ),
    Elements( Points( X, Y, Legend( 3 ) ), Smoother( X, Y, Legend( 4 ) ) ),
    Where( :sex == "F" )
);

Code Explanation:

1. Open data table.
2. Create Graph Builder object.
3. Hide control panel.
4. Set X variable to height.
5. Set Y variable to weight.
6. Add points element.
7. Add smoother element.
8. Set legend for points.
9. Set legend for smoother.
10. Filter data where sex is female.

Example 1897

Summary: Creates a variability chart with nested factors using Graph Builder, displaying standard deviation charts and reversing the Y scale.

Code:

Open("data_table.jmp");
gb = Graph Builder(
    Show Control Panel( 0 ),
    Variables( X( :height ), Y( :weight ) ),
    Elements( Points( X, Y, Legend( 3 ) ), Smoother( X, Y, Legend( 4 ) ) ),
    SendToReport( Dispatch( {}, "weight", ScaleBox, {Reversed Scale} ) )
);

Code Explanation:

1. Open data table;
2. Create graph builder object.
3. Hide control panel.
4. Set X variable to height.
5. Set Y variable to weight.
6. Add points element.
7. Add smoother element.
8. Set legend for points.
9. Set legend for smoother.
10. Reverse Y scale.

Example 1898

Summary: Creates a Graph Builder object to visualize height and weight data, with points and smoother elements, and reverses the Y scale.

Code:

dt = Open("data_table.jmp");
gb = Graph Builder(
    Show Control Panel( 0 ),
    Variables( X( :height ), Y( :weight ) ),
    Elements( Points( X, Y, Legend( 3 ) ), Smoother( X, Y, Legend( 4 ) ) ),
    SendToReport( Dispatch( {}, "weight", ScaleBox, {Reversed Scale} ) )
);
gb << Redo Analysis;

Code Explanation:

1. Open data table.
2. Create Graph Builder object.
3. Hide control panel.
4. Set X variable to height.
5. Set Y variable to weight.
6. Add points element.
7. Add smoother element.
8. Reverse Y scale.
9. Redo analysis.

Example 1899

Summary: Creates a variability chart with nested factors using Graph Builder, hiding the control panel and customizing marker size.

Code:

dt = Open("data_table.jmp");
plat = dt << Graph Builder(
    Show Control Panel( 0 ),
    Variables( X( :height ), Y( :weight ), Overlay( :sex ) ),
    Elements( Points( X, Y, Legend( 1 ) ), Smoother( X, Y, Legend( 3 ) ) ),
    SendToReport( Dispatch( {}, "Graph Builder", FrameBox, {Marker Size( 6 )} ) )
);

Code Explanation:

1. Open table.
2. Create Graph Builder.
3. Hide control panel.
4. Set X variable.
5. Set Y variable.
6. Add overlay variable.
7. Add points element.
8. Add smoother element.
9. Customize marker size.
10. Display graph.

Example 1900

Summary: Creates a variability chart with nested factors using Graph Builder, selecting rows where sex is 'M' and displaying standard deviation charts.

Code:

dt = Open("data_table.jmp");
plat = dt << Graph Builder(
    Show Control Panel( 0 ),
    Variables( X( :height ), Y( :weight ), Overlay( :sex ) ),
    Elements( Points( X, Y, Legend( 1 ) ), Smoother( X, Y, Legend( 3 ) ) ),
    SendToReport( Dispatch( {}, "Graph Builder", FrameBox, {Marker Size( 6 )} ) )
);
dt << Select Where( :sex == "M" );

Code Explanation:

1. Open data table;
2. Create Graph Builder object.
3. Hide control panel.
4. Set X variable to height.
5. Set Y variable to weight.
6. Overlay by sex.
7. Add points element.
8. Add smoother element.
9. Adjust marker size to 6.
10. Select rows where sex is "M".

Example 1901

Summary: Creates a variability chart with nested factors using Graph Builder, displaying standard deviation charts and adjusting marker size.

Code:

dt = Open("data_table.jmp");
dt << Clear Select;
plat = dt << Graph Builder(
    Show Control Panel( 0 ),
    Variables( X( :height ), Y( :weight ), Overlay( :sex ) ),
    Elements( Points( X, Y, Legend( 1 ) ), Smoother( X, Y, Legend( 3 ) ) ),
    SendToReport( Dispatch( {}, "Graph Builder", FrameBox, {Marker Size( 6 )} ) )
);
dt << Select Rows( [1] );
jrn = plat << Journal;

Code Explanation:

1. Open data table.
2. Clear selected rows.
3. Create Graph Builder object.
4. Hide control panel.
5. Set X and Y variables.
6. Add overlay variable.
7. Plot points and smoother.
8. Adjust marker size.
9. Select first row.
10. Create journal from plot.

Example 1902

Summary: Creates a Graph Builder object with nested factors, displaying standard deviation charts and adjusting marker size to 6.

Code:

dt = Open("data_table.jmp");
dt << Clear Select;
plat = dt << Graph Builder(
    Show Control Panel( 0 ),
    Variables( X( :height ), Y( :weight ), Overlay( :sex ) ),
    Elements( Points( X, Y, Legend( 1 ) ), Smoother( X, Y, Legend( 3 ) ) ),
    SendToReport( Dispatch( {}, "Graph Builder", FrameBox, {Marker Size( 6 )} ) )
);
dt << Select Rows( [1] );
jrn = plat << Journal;
Current Journal() << close window;

Code Explanation:

1. Open data table;
2. Clear all selections.
3. Create Graph Builder object.
4. Hide control panel.
5. Set X variable to height.
6. Set Y variable to weight.
7. Set overlay variable to sex.
8. Add points element.
9. Add smoother element.
10. Adjust marker size to 6.

Example 1903

Summary: Creates a graph with nested factors using Graph Builder, displaying points and smoother elements, and adding a reference line for July 2, 1964.

Code:

dt = Open("data_table.jmp");
Graph Builder(
    Size( 543, 409 ),
    Show Control Panel( 0 ),
    Variables( X( :Ozone Concentration ), Y( :date ) ),
    Elements( Points( X, Y, Legend( 3 ) ), Smoother( X, Y, Legend( 4 ) ) ),
    SendToReport( Dispatch( {}, "date", ScaleBox, {Add Ref Line( 1909267200, "Solid", "Black", "July 2, 1964", 1 )} ) )
);

Code Explanation:

1. Open data table.
2. Create Graph Builder object.
3. Set graph size.
4. Hide control panel.
5. Define X and Y variables.
6. Add points element.
7. Add smoother element.
8. Send report to Graph Builder.
9. Add reference line for July 2, 1964.
10. Customize reference line appearance.

Example 1904

Summary: Creates a variability chart with nested factors using Graph Builder, featuring points and smoother elements, and adjusts the Y-axis scale to log.

Code:

dt = Open("data_table.jmp");
gb = Graph Builder(
    Show Control Panel( 0 ),
    Variables( X( :height ), Y( :weight ) ),
    Elements( Points( X, Y, Legend( 1 ), Jitter( 1 ) ), Smoother( X, Y, Legend( 2 ) ) ),
    SendToReport(
        Dispatch( {}, "weight", ScaleBox, {Scale( "Log" ), Format( "Best", 12 ), Min( 60 ), Max( 200 ), Inc( 1 ), Minor Ticks( 2 )} )
    )
);

Code Explanation:

1. Open data table.
2. Create Graph Builder object.
3. Hide control panel.
4. Set X variable to height.
5. Set Y variable to weight.
6. Add points element with jitter.
7. Add smoother element.
8. Send report to Graph Builder.
9. Adjust Y axis scale to log.
10. Format Y axis with best format.

Example 1905

Summary: Creates a variability chart with nested factors using Graph Builder, hiding the control panel and configuring Y group title and level orientations.

Code:

dt = Open("data_table.jmp");
gb = Graph Builder(
    Show Control Panel( 0 ),
    Y Group Title Orientation( "Horizontal" ),
    Y Group Level Orientation( "Horizontal" ),
    Variables( X( :weight ), Y( :height ), Group Y( :age ), Overlay( :sex ) ),
    Elements( Points( X, Y, Legend( 10 ), Jitter( 1 ) ), Smoother( X, Y, Legend( 11 ) ) )
);

Code Explanation:

1. Open data table.
2. Create Graph Builder object.
3. Hide control panel.
4. Set Y group title orientation.
5. Set Y group level orientation.
6. Define variables for graph.
7. Add points element with jitter.
8. Add smoother element.
9. Assign legend to points.
10. Assign legend to smoother.

Example 1906

Summary: Creates a variability chart with nested factors using Graph Builder, hiding the control panel and grouping by age.

Code:

dt = Open("data_table.jmp");
gb = Graph Builder(
    Show Control Panel( 0 ),
    Variables( X( :height ), Y( :weight ) ),
    Elements( Points( X, Y, Legend( 1 ) ), Smoother( X, Y, Legend( 2 ) ) ),
    By( :age )
);

Code Explanation:

1. Open data_table data
2. Create Graph Builder object.
3. Hide control panel.
4. Set X variable to height.
5. Set Y variable to weight.
6. Add points element.
7. Add smoother element.
8. Enable legend for points.
9. Enable legend for smoother.
10. Group by age.

Example 1907

Summary: Creates a variability chart with nested factors using Graph Builder, configuring scale and formatting options.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 528, 454 ),
    Show Control Panel( 0 ),
    Variables( X( :Hours ), Y( :Current ) ),
    Elements( Points( X, Y, Legend( 3 ) ), Smoother( X, Y, Legend( 4 ) ) ),
    SendToReport(
        Dispatch( {}, "Hours", ScaleBox, {Scale( "Log" ), Format( "Best", 10 ), Min( 1 ), Max( 4080 ), Inc( 1 ), Minor Ticks( 1 )} )
    )
);

Code Explanation:

1. Open data table;
2. Create Graph Builder window.
3. Set graph size.
4. Hide control panel.
5. Define X and Y variables.
6. Add points element.
7. Add smoother element.
8. Configure Hours scale.
9. Set scale type to log.
10. Apply formatting and limits.

Example 1908

Summary: Creates a variability chart with nested factors using operator and part configurations, displaying standard deviation charts in Graph Builder.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 484, 413 ),
    Variables( X( :Hours ), Y( :Current ), Overlay( :Unit ) ),
    Elements( Points( X, Y, Legend( 3 ) ), Smoother( X, Y, Legend( 4 ) ) ),
    Local Data Filter( Add Filter( columns( :Batch ), Where( :Batch == 2 ) ) ),
    SendToReport(
        Dispatch( {}, "Hours", ScaleBox, {Format( "Best", 10 )} ),
        Dispatch( {}, "Current", ScaleBox,
            {Scale( "Log" ), Format( "Best", 10 ), Min( 0.01 ), Max( 12.4565961230706 ), Inc( 1 ), Minor Ticks( 1 )}
        )
    )
);

Code Explanation:

1. Open data table;
2. Create Graph Builder window.
3. Set graph size.
4. Define X and Y variables.
5. Add overlay variable.
6. Plot points element.
7. Add smoother element.
8. Apply local data filter.
9. Format Hours scale.
10. Configure Current log scale.

Example 1909

Summary: Creates a variability chart with nested factors using operator and part configurations, displaying standard deviation charts in Graph Builder.

Code:

dt = Open("data_table.jmp");
Graph Builder(
    Size( 528, 490 ),
    Show Control Panel( 0 ),
    Show Legend( 0 ),
    Variables( X( :Name( "#employees" ) ), Y( :Name( "Sales($M)" ) ), Y( :Name( "Profit($M)" ), Position( 1 ) ), Wrap( :Type ) ),
    Elements( Points( X, Y( 1 ), Y( 2 ), Legend( 7 ) ), Smoother( X, Y( 1 ), Y( 2 ), Legend( 8 ) ) ),
    SendToReport(
        Dispatch( {}, "#employees", ScaleBox, {Scale( "Log" ), Min( 519.865005485984 ), Max( 400000 ), Inc( 1 ), Minor Ticks( 1 )} ),
        Dispatch( {}, "Sales($M)", ScaleBox,
            {Scale( "Log" ), Format( "Best", 12 ), Min( 10 ), Max( 90000.0000000001 ), Inc( 1 ), Minor Ticks( 1 )}
        )
    )
);

Code Explanation:

1. Open data table.
2. Create Graph Builder window.
3. Set window size.
4. Hide control panel.
5. Hide legend.
6. Define variables: X, Y1, Y2, Wrap.
7. Add points and smoother elements.
8. Configure log scale for X-axis.
9. Set X-axis min, max, increment, minor ticks.
10. Configure log scale for Y1-axis.

Example 1910

Summary: Creates a variability chart with nested factors using operator and part configurations, displaying standard deviation charts in Graph Builder.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 367, 314 ),
    Show Control Panel( 0 ),
    Variables( X( :Color ), Y( :Depth ), Overlay( :Price ), Color( :Color ) ),
    Elements( Smoother( X, Y, Legend( 21 ) ), Points( X, Y, Legend( 22 ) ) )
);

Code Explanation:

1. Open data table;
2. Create Graph Builder window.
3. Set size to 367x314.
4. Hide control panel.
5. Set X variable to Color.
6. Set Y variable to Depth.
7. Overlay variable to Price.
8. Color elements by Color.
9. Add Smoother element.
10. Add Points element.

Example 1911

Summary: Creates a variability chart with nested factors using Graph Builder, displaying points and smoother elements with legends.

Code:

Open("data_table.jmp");
Graph Builder(
    show control panel( 0 ),
    Variables( X( :height ), Y( :weight ), Page( :age ) ),
    Elements( Points( X, Y, Legend( 6 ) ), Smoother( X, Y, Legend( 7 ) ) )
);

Code Explanation:

1. Open data table;
2. Launch Graph Builder.
3. Hide control panel.
4. Set X variable: height.
5. Set Y variable: weight.
6. Use age for pages.
7. Add points element.
8. Add smoother element.
9. Assign points legend.
10. Assign smoother legend.

Example 1912

Summary: Creates two variability charts with nested factors using Graph Builder, displaying standard deviation charts and hiding control panels.

Code:

Open("data_table.jmp");
Graph Builder(
    show control panel( 0 ),
    Variables( X( :height ), Y( :weight ), Page( :age ) ),
    Elements( Points( X, Y, Legend( 6 ) ), Smoother( X, Y, Legend( 7 ) ) )
);
Graph Builder(
    Size( 570, 3000 ),
    show control panel( 0 ),
    Variables( X( :height ), Y( :weight ), Page( :age ) ),
    Elements( Points( X, Y, Legend( 1 ) ), Smoother( X, Y, Legend( 2 ) ) )
);

Code Explanation:

1. Open data table.
2. Create first Graph Builder.
3. Hide control panel.
4. Set X, Y, and Page variables.
5. Add points and smoother elements.
6. Create second Graph Builder.
7. Set size to 570x3000.
8. Hide control panel.
9. Set X, Y, and Page variables.
10. Add points and smoother elements.

Example 1913

Summary: Creates a variability chart with nested factors using Graph Builder, displaying standard deviation charts and smoothing curves.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 534, 454 ),
    Show Control Panel( 0 ),
    Variables( X( :height ), Y( :weight ), Overlay( :sex ) ),
    Elements(
        Points( X, Y, Legend( 8 ) ),
        Smoother( X, Y, Overlay( 0 ), Legend( 9 ), Lambda( 0.3 ) ),
        Smoother( X, Y, Legend( 10 ), Lambda( 0.1 ) )
    )
);

Code Explanation:

1. Open data table;
2. Create Graph Builder object.
3. Set window size.
4. Hide control panel.
5. Define X and Y variables.
6. Add overlay variable.
7. Add points element.
8. Add first smoother element.
9. Set first smoother lambda.
10. Add second smoother element.
11. Set second smoother lambda.

Example 1914

Summary: Creates a variability chart with nested factors using Graph Builder, displaying standard deviation charts and enabling confidence intervals.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 528, 454 ),
    Show Control Panel( 0 ),
    Variables( X( :weight ), Y( :height ) ),
    Elements( Smoother( X, Y, Legend( 5 ), Lambda( 4.00 ), Confidence of Fit( 1 ) ), Points( X, Y, Legend( 6 ) ) )
);

Code Explanation:

1. Open data table;
2. Launch Graph Builder.
3. Set window size.
4. Hide control panel.
5. Define X variable.
6. Define Y variable.
7. Add smoother element.
8. Set smoother lambda.
9. Enable confidence interval.
10. Add points element.

Example 1915

Summary: Creates two Graph Builders to visualize relationships between height, weight, and sex in a dataset, with optional smoothing and confidence of fit.

Code:

Open("data_table.jmp");
Graph Builder(
    Show Control Panel( 0 ),
    Variables( X( :height ), Y( :weight ), Overlay( :sex ) ),
    Elements( Points( X, Y, Legend( 1 ) ), Smoother( X, Y, Legend( 2 ), Confidence of Fit( 1 ) ) )
);
Graph Builder(
    Show Control Panel( 0 ),
    Variables( X( :height ), Y( :weight ), Overlay( :sex ) ),
    Elements( Points( X, Y, Legend( 1 ) ), Smoother( X, Y, Legend( 2 ), Lambda( 6837.54188933792 ), Confidence of Fit( 1 ) ) )
);

Code Explanation:

1. Open data table;
2. Create first Graph Builder.
3. Hide control panel.
4. Set X, Y, and overlay variables.
5. Add points element.
6. Add smoother element.
7. Enable confidence of fit.
8. Create second Graph Builder.
9. Repeat settings from step 3-7.
10. Set smoother lambda value.

Example 1916

Summary: Creates a variability chart with nested factors using operator and part configurations, displaying standard deviation charts.

Code:

dt under test = Open("data_table.jmp");
obj = Graph Builder(
    Show Control Panel( 0 ),
    Variables( X( :Name( "2004 Verbal" ) ), Y( :Name( "2004 Math" ) ) ),
    Elements( Points( X, Y, Legend( 6 ) ), Smoother( X, Y, Legend( 7 ), Lambda( 0.0001 ) ) ),
    SendToReport(
        Dispatch( {}, "2004 Verbal", ScaleBox,
            {Label Row( {Show Major Grid( 1 ), Major Grid Line Color( 1 ), Show Minor Grid( 1 ), Minor Grid Line Color( 32 )} )}
        ),
        Dispatch( {}, "2004 Math", ScaleBox, {Label Row( {Show Major Grid( 1 ), Show Minor Labels( 1 ), Show Minor Grid( 1 )} )} ),
        Dispatch( {}, "Graph Builder", FrameBox, {Background Color( 4 )} )
    )
);

Code Explanation:

1. Open data table;
2. Create Graph Builder object.
3. Hide control panel.
4. Set X variable to "2004 Verbal".
5. Set Y variable to "2004 Math".
6. Add points element to graph.
7. Add smoother element to graph.
8. Configure smoother lambda to 0.0001.
9. Customize "2004 Verbal" scale box.
10. Customize "2004 Math" scale box.
11. Set graph background color to blue.

Example 1917

Summary: Creates a variability chart with nested factors using Graph Builder, hiding the control panel and customizing the appearance of the smoother legend.

Code:

dt under test = Open("data_table.jmp");
obj = Graph Builder(
    Show Control Panel( 0 ),
    Variables( X( :age ), Y( :height ), Group Y( :sex ) ),
    Elements( Points( X, Y, Legend( 3 ) ), Smoother( X, Y, Legend( 4 ), Lambda( 0.000386544946598284 ) ) ),
    SendToReport(
        Dispatch( {}, "height", ScaleBox, {Format( "Best", 12 )} ),
        Dispatch( {}, "400", ScaleBox, {Legend Model( 4, Properties( 0, {Line Color( 74 ), Line Width( 6 )} ) )} ),
        Dispatch( {}, "Graph Builder", FrameBox, {Background Color( 5 )} ),
        Dispatch( {}, "Graph Builder", FrameBox( 2 ), {Background Color( 5 )} )
    )
);

Code Explanation:

1. Open data table;
2. Create Graph Builder object.
3. Hide control panel.
4. Set X variable as :age.
5. Set Y variable as :height.
6. Group Y by :sex.
7. Add points element.
8. Add smoother element.
9. Format height scale.
10. Customize smoother legend and appearance.

Example 1918

Summary: Creates a variability chart with nested factors using Graph Builder, transforming the height column and displaying standard deviation charts.

Code:

Open("data_table.jmp");
gbp = Graph Builder(
    Transform Column( "Min[height]@X", Formula( Col Minimum( :height, :"@Exclude"n, :"@Filter"n, :"@Graph"n, :"@Overlay"n, :"@X"n ) ) ),
    Show Control Panel( 0 ),
    Show Legend( 0 ),
    Size( 570, 502 ),
    Variables( X( :sex ), Y( :"Min[height]@X"n ) ),
    Elements( Points( X, Y, Legend( 6 ) ) )
);
gb = Report( gbp )[Graph Builder Box( 1 )];
gbp2 = gbp << Redo Analysis();

Code Explanation:

1. Open data table;
2. Create graph builder object.
3. Transform height column.
4. Hide control panel.
5. Hide legend.
6. Set graph size.
7. Define X and Y variables.
8. Add points element.
9. Retrieve graph box.
10. Redo analysis.

Example 1919

Summary: Creates a variability chart with nested factors using Graph Builder, hiding control panels and legends to focus on standard deviation charts.

Code:

Open("data_table.jmp");
gbp = Graph Builder(
    Transform Column( "Min[height]@X", Formula( Col Minimum( :height, :"@Exclude"n, :"@Filter"n, :"@Graph"n, :"@Overlay"n, :"@X"n ) ) ),
    Show Control Panel( 0 ),
    Show Legend( 0 ),
    Size( 570, 502 ),
    Variables( X( :sex ), Y( :"Min[height]@X"n ) ),
    Elements( Points( X, Y, Legend( 6 ) ) )
);
gb = Report( gbp )[Graph Builder Box( 1 )];
gbp2 = gbp << Redo Analysis();
gb << Remove Variable( {:sex, Role( "X" )} );

Code Explanation:

1. Open data_table data
2. Create Graph Builder object.
3. Add transformed column "Min[height]@X".
4. Hide control panel.
5. Hide legend.
6. Set graph size.
7. Assign variables for X and Y axes.
8. Add points element.
9. Get report object.
10. Redo analysis.
11. Remove "sex" variable from X axis.

Example 1920

Summary: Creates a Treemap visualization with nested factors using Graph Builder, displaying regional and country-level data.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 365, 341 ),
    Show Control Panel( 0 ),
    Variables( X( :Pop ), Y( :Region ), Y( :Country, Position( 1 ) ) ),
    Elements( Treemap( X, Y( 1 ), Y( 2 ), Legend( 4 ) ) ),
    SendToReport( Dispatch( {}, "Graph Builder", FrameBox, {DispatchSeg( TreeMapSeg( 1 ), Frame Size( 341, 290 ) )} ) )
);

Code Explanation:

1. Open data table;
2. Launch Graph Builder.
3. Set window size.
4. Hide control panel.
5. Define X and Y variables.
6. Add Treemap element.
7. Configure Treemap legend.
8. Adjust frame size.
9. Dispatch report settings.
10. Display graph.

Example 1921

Summary: Creates a treemap visualization using Graph Builder to display nested factors from a data table, with customization options for legend and size.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 398, 347 ),
    Show Control Panel( 0 ),
    Variables( X( :age ), Y( :sex ) ),
    Elements( Treemap( X, Y, Legend( 4 ) ) ),
    SendToReport( Dispatch( {}, "Graph Builder", FrameBox, {DispatchSeg( TreeMapSeg( 1 ), Frame Size( 373, 296 ) )} ) )
);

Code Explanation:

1. Open data table.
2. Launch Graph Builder.
3. Set window size.
4. Hide control panel.
5. Assign variables.
6. Add treemap element.
7. Customize legend.
8. Adjust treemap size.
9. Dispatch report settings.
10. Finalize graph display.

Example 1922

Summary: Creates a Treemap visualization in Graph Builder to display age vs. weight data, with customizable legend and frame size.

Code:

dt = Open("data_table.jmp");
Graph Builder(
    Show Control Panel( 0 ),
    Variables( X( :age ), Y( :weight ) ),
    Elements( Treemap( X, Y, Legend( 13 ) ) ),
    SendToReport(
        Dispatch( {}, "400", LegendBox, {Legend Position( {0, 1, 2, 3, 4, 5} )} ),
        Dispatch( {}, "Graph Builder", FrameBox, {DispatchSeg( TreeMapSeg( 1 ), Frame Size( 484, 392 ) )} )
    )
);

Code Explanation:

1. Open data table.
2. Create Graph Builder object.
3. Hide control panel.
4. Set X variable to age.
5. Set Y variable to weight.
6. Add Treemap element.
7. Assign legend to Treemap.
8. Configure legend position.
9. Adjust frame size for Treemap.
10. Display graph.

Example 1923

Summary: Creates a Treemap visualization with nested factors using Graph Builder, displaying standard deviation charts and adjusting legend position.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 570, 516 ),
    Show Control Panel( 0 ),
    Variables( X( :age ), Y( :weight ), Overlay( :sex ) ),
    Elements( Treemap( X, Y, Legend( 19 ) ) ),
    SendToReport(
        Dispatch( {}, "Graph Builder", OutlineBox,
            {Set Title( "Graph Builder: Always incorrect because Treemap does not support Overlay" )}
        ),
        Dispatch( {}, "400", LegendBox, {Legend Position( {0, 1, 2, 3, 4, 5} )} ),
        Dispatch( {}, "Graph Builder", FrameBox, {DispatchSeg( TreeMapSeg( 1 ), Frame Size( 484, 408 ) )} )
    )
);

Code Explanation:

1. Open data table;
2. Launch Graph Builder.
3. Set window size.
4. Hide control panel.
5. Define variables for axes and overlay.
6. Add Treemap element.
7. Set graph title.
8. Adjust legend position.
9. Resize treemap frame.
10. Display report.

Example 1924

Summary: Creates a variability chart with nested factors using operator and part configurations, displaying standard deviation charts through Graph Builder.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 472, 295 ),
    Show Control Panel( 0 ),
    Variables( X( :Abrasion ), Y( :time2 ), Color( :Shift, Summary Statistic( "Sum" ) ) ),
    Elements( Treemap( X, Y, Legend( 4 ), Summary Statistic( "N" ) ) )
);
Graph Builder(
    Size( 457, 361 ),
    Variables( X( :time2 ), Y( :Abrasion ), Color( :Shift, Summary Statistic( "Sum" ) ) ),
    Elements( Line( X, Y, Legend( 15 ) ) )
);

Code Explanation:

1. Open data table.
2. Create first Graph Builder window.
3. Set window size.
4. Hide control panel.
5. Define X, Y, and color variables.
6. Add Treemap element.
7. Set summary statistic for color.
8. Create second Graph Builder window.
9. Set window size.
10. Define X, Y, and color variables.
11. Add Line element.

Example 1925

Summary: Creates a variability chart with nested factors using operator and part configurations, displaying standard deviation charts through Graph Builder.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 472, 295 ),
    Show Control Panel( 0 ),
    Variables( X( :Abrasion ), Y( :time2 ), Color( :Shift, Summary Statistic( "Sum" ) ) ),
    Elements( Treemap( X, Y, Legend( 4 ), Summary Statistic( "N" ) ) )
);
Graph Builder(
    Size( 457, 361 ),
    Variables( X( :time2 ), Y( :Abrasion ), Color( :Shift, Summary Statistic( "Sum" ) ) ),
    Elements( Line( X, Y, Legend( 15 ) ) )
);
Graph Builder(
    Size( 457, 361 ),
    Variables( X( :time2 ), Y( :Abrasion ), Color( :Shift, Summary Statistic( "Sum" ) ) ),
    Elements( Area( X, Y, Legend( 15 ) ) )
);

Code Explanation:

1. Open data table;
2. Create treemap graph.
3. Set graph size.
4. Hide control panel.
5. Define X, Y, and color variables.
6. Use summary statistic for color.
7. Add treemap element.
8. Create line graph.
9. Set graph size.
10. Define X, Y, and color variables.
11. Add line element.
12. Create area graph.
13. Set graph size.
14. Define X, Y, and color variables.
15. Add area element.

Example 1926

Summary: Creates a treemap visualization to display nested factors, utilizing Graph Builder and specifying variables for Region, State, city, and POP.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 494, 614 ),
    Show Control Panel( 0 ),
    Variables( X( :Region ), X( :State, Position( 1 ) ), X( :city, Position( 1 ) ), Size( :POP ) ),
    Elements( Treemap( X( 1 ), X( 2 ), X( 3 ) ) )
);

Code Explanation:

1. Open data table.
2. Launch Graph Builder.
3. Set window size.
4. Hide control panel.
5. Define variables for X.
6. Define size variable.
7. Add Treemap element.
8. Assign Region to X1.
9. Assign State to X2.
10. Assign city to X3.

Example 1927

Summary: Creates a treemap visualization with nested factors using Graph Builder, mapping variables to X-axis and color value.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 480, 474 ),
    Show Control Panel( 0 ),
    Variables( X( :Single Status ), X( :Age Group, Position( 1 ) ), Color( :Salary ) ),
    Elements( Treemap( X( 1 ), X( 2 ), Legend( 22 ), Color Value( 1 ) ) )
);

Code Explanation:

1. Open data table;
2. Launch Graph Builder.
3. Set window size.
4. Hide control panel.
5. Assign variables to axes.
6. Add color variable.
7. Create treemap element.
8. Map first variable to X-axis.
9. Map second variable to X-axis.
10. Configure legend and color value.

Example 1928

Summary: Creates a mosaic chart with nested factors using Graph Builder, displaying standard deviation charts and summary statistics.

Code:

Open("data_table.jmp");
Graph Builder(
    Show Control Panel( 0 ),
    Variables( X( :age ), Y( :sex ) ),
    Elements( Mosaic( X, Y, Legend( 4 ) ), Caption Box( X, Y, Legend( 5 ), Summary Statistic( "N" ) ) )
);

Code Explanation:

1. Open data table.
2. Launch Graph Builder.
3. Hide control panel.
4. Set X variable to age.
5. Set Y variable to sex.
6. Add mosaic element.
7. Add caption box element.
8. Configure caption box for summary statistic N.
9. Display graph.

Example 1929

Summary: Creates a treemap chart with nested factors, utilizing Graph Builder to display standard deviation charts and customize legend properties.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 488, 357 ),
    Show Control Panel( 0 ),
    Variables( X( :sex ), X( :age, Position( 1 ) ), Color( :height, Summary Statistic( "Std Dev" ) ), Size( :weight ) ),
    Elements( Treemap( X( 1 ), X( 2 ), Legend( 4 ), Group Labels( "Above" ) ) ),
    SendToReport(
        Dispatch( {}, "400", ScaleBox,
            {Legend Model(
                4,
                Properties(
                    0,
                    {gradient(
                        {Color Theme(
                            {"Custom Gradient", 4099, {{42, 63, 255}, {192, 192, 192}, {252, 11, 11}, Missing( {106, 106, 106} )}}
                        ), Width( 12 )}
                    )},
                    Item ID( "height", 1 )
                )
            )}
        )
    )
);

Code Explanation:

1. Open data table;
2. Create new Graph Builder window.
3. Set window size.
4. Hide control panel.
5. Define variables for treemap.
6. Add treemap element.
7. Customize legend properties.
8. Set color theme for gradient.
9. Adjust gradient width.
10. Display report.

Example 1930

Summary: Creates a variability chart with nested factors using Graph Builder, configuring the Treemap element to display standard deviation charts for height and size by weight.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 495, 379 ),
    Show Control Panel( 0 ),
    Variables( X( :sex ), X( :age, Position( 1 ) ), Color( :height, Summary Statistic( "Std Dev" ) ), Size( :weight ) ),
    Elements( Treemap( X( 1 ), X( 2 ), Legend( 4 ), Category Name( 1 ), Color Value( 1 ), Size Value( 1 ) ) ),
    SendToReport(
        Dispatch( {}, "400", ScaleBox,
            {Legend Model( 4, Properties( 0, {gradient( {Color Theme( "White to Black" ), Width( 12 )} )}, Item ID( "height", 1 ) ) )}
        )
    )
);

Code Explanation:

1. Open data table;
2. Create Graph Builder window.
3. Set window size to 495x379.
4. Hide control panel.
5. Assign variables: sex, age, height, weight.
6. Use Treemap element.
7. Set color by height's standard deviation.
8. Set size by weight.
9. Customize legend for height.
10. Apply gradient color theme.

Example 1931

Summary: Creates a treemap visualization with nested factors using Graph Builder, displaying standard deviation charts for analysis.

Code:

Open("data_table.jmp") << Graph Builder(
    Size( 727, 509 ),
    Show Control Panel( 0 ),
    Include Missing Categories( 1 ),
    Variables( X( :Date ), Y( :Delay ), Wrap( :Reason ), Color( :Flight ), Frequency( :Flight ) ),
    Elements( Treemap( X, Y, Legend( 18 ) ) )
);

Code Explanation:

1. Open data_table data
2. Launch Graph Builder.
3. Set window size.
4. Hide control panel.
5. Include missing categories.
6. Assign variables: X(Date), Y(Delay).
7. Wrap by Reason.
8. Color by Flight.
9. Use Flight for frequency.
10. Add Treemap element.

Example 1932

Summary: Creates a treemap visualization with nested factors, utilizing Graph Builder and Local Data Filter to display data from 'data_table.jmp'.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 517, 315 ),
    Show Control Panel( 0 ),
    Show Legend( 0 ),
    Variables( X( :Net Cost ), Group X( :Class of Service ), Color( :Departure Day of Week ) ),
    Elements( Treemap( X, Legend( 16 ) ) ),
    Local Data Filter(
        Add Filter( columns( :Airline ), Where( :Airline == "Carrier 1" ), Display( :Airline, Size( 181, 68 ), List Display ) )
    )
);

Code Explanation:

1. Open data table;
2. Create Graph Builder object.
3. Set window size.
4. Hide control panel.
5. Hide legend.
6. Define X variable.
7. Define group X variable.
8. Define color variable.
9. Add Treemap element.
10. Configure local data filter.

Example 1933

Summary: Creates a treemap visualization with nested factors using Graph Builder, displaying standard deviation charts and adding pin annotations to highlight specific data points.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 596, 368 ),
    Show Control Panel( 0 ),
    Show Legend( 0 ),
    Show Footer( 0 ),
    Variables( X( :age ), Y( :height ), Color( :age, Summary Statistic( "Sum" ) ) ),
    Elements( Treemap( X, Y, Legend( 10 ), Color Value( 1 ) ) ),
    SendToReport(
        Dispatch( {}, "Graph Builder", FrameBox,
            {Add Pin Annotation(
                Seg( TreeMapSeg( 1 ) ),
                Index( 2 ),
                Index Row( 15 ),
                UniqueID( 2 ),
                FoundPt( {385, 172} ),
                Origin( {346.488481675393, 203.74578125} ),
                RightOfCenter( 1 ),
                Tag Line( 1 ),
                Text Color( {224, 224, 224} ),
                Background Color( {44, 44, 44} )
            ), Add Pin Annotation(
                Seg( TreeMapSeg( 1 ) ),
                Index( 4 ),
                Index Row( 34 ),
                UniqueID( 4 ),
                FoundPt( {488, 307} ),
                Origin( {451.07482547993, 65.022734375} ),
                RightOfCenter( 1 ),
                Tag Line( 1 ),
                Text Color( {224, 224, 224} ),
                Background Color( {44, 44, 44} )
            )}
        )
    )
);

Code Explanation:

1. Open data table.
2. Launch Graph Builder.
3. Set graph size.
4. Hide control panel.
5. Hide legend.
6. Hide footer.
7. Assign variables: X=age, Y=height, Color=age summary.
8. Create treemap element.
9. Add pin annotation to treemap.
10. Add another pin annotation to treemap.

Example 1934

Summary: Creates a treemap visualization with nested factors using Graph Builder, displaying standard deviation charts and configuring X variables for Region and State.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 508, 374 ),
    Show Control Panel( 0 ),
    Show Legend( 0 ),
    Variables( X( :Region ), X( :State, Position( 1 ) ), Size( :POP ) ),
    Elements( Treemap( X( 1 ), X( 2 ), Legend( 1 ), Label Transparency( 0.3 ) ) )
);

Code Explanation:

1. Open data table;
2. Launch Graph Builder.
3. Set window size.
4. Hide control panel.
5. Hide legend.
6. Define X variables: Region, State.
7. Define size variable: POP.
8. Add Treemap element.
9. Set X positions for Treemap.
10. Set label transparency.

Example 1935

Summary: Creates a Treemap chart with nested factors using Graph Builder, displaying group labels and standard deviation charts.

Code:

dt = Open("data_table.jmp");
gb = Graph Builder(
    Size( 735, 167 ),
    Show Control Panel( 0 ),
    Variables( X( :age ), X( :sex, Position( 1 ) ) ),
    Elements( Treemap( X( 1 ), X( 2 ), Legend( 5 ), Group Labels( "Above" ), Max Label Size( 20 ) ) ),
    SendToReport(
        Dispatch( {}, "Graph Builder", FrameBox,
            {DispatchSeg( TreeMapSeg( 1 ), {Set Group Spacing( 10 ), Set Group Label Font( "Above", Size( 48 ) )} )}
        )
    )
);
gb << save journal( "$TEMP/test.jrn" );
dt << close window( no save );

Code Explanation:

1. Open data table.
2. Create Graph Builder object.
3. Set graph size.
4. Hide control panel.
5. Define X variables.
6. Add Treemap element.
7. Configure Treemap legend.
8. Set group labels position.
9. Adjust maximum label size.
10. Save graph as journal.
11. Close data table without saving.

Example 1936

Summary: Creates a treemap visualization with nested factors using Graph Builder, displaying standard deviation charts and customizing group labels.

Code:

dt = Open("data_table.jmp");
gb = Graph Builder(
    Size( 735, 167 ),
    Show Control Panel( 0 ),
    Variables( X( :age ), X( :sex, Position( 1 ) ) ),
    Elements( Treemap( X( 1 ), X( 2 ), Legend( 5 ), Group Labels( "Above" ), Max Label Size( 20 ) ) ),
    SendToReport(
        Dispatch( {}, "Graph Builder", FrameBox,
            {DispatchSeg( TreeMapSeg( 1 ), {Set Group Spacing( 10 ), Set Group Label Font( "Above", Size( 48 ) )} )}
        )
    )
);
gb << save journal( "$TEMP/test.jrn" );
dt << close window( no save );
Open( "$TEMP/test.jrn" );

Code Explanation:

1. Open data table.
2. Create Graph Builder object.
3. Set graph size.
4. Hide control panel.
5. Define variables for treemap.
6. Add treemap element.
7. Customize treemap appearance.
8. Save graph as journal.
9. Close data table without saving.
10. Open saved journal.

Example 1937

Summary: Creates a Treemap visualization with nested factors using Graph Builder, displaying age and sex variables.

Code:

Open("data_table.jmp");
obj = Graph Builder(
    Size( 648, 549 ),
    Show Control Panel( 0 ),
    Variables( X( :age ), X( :sex, Position( 1 ) ) ),
    Elements( Treemap( X( 1 ), X( 2 ), Legend( 12 ) ) )
);

Code Explanation:

1. Open data table;
2. Create Graph Builder object.
3. Set window size.
4. Hide control panel.
5. Define X variables: age, sex.
6. Position sex variable.
7. Add Treemap element.
8. Assign first X to Treemap.
9. Assign second X to Treemap.
10. Enable legend.

Example 1938

Summary: Creates a Treemap visualization with nested factors using Graph Builder, displaying age and sex as X variables.

Code:

Open("data_table.jmp");
obj = Graph Builder(
    Size( 648, 549 ),
    Show Control Panel( 0 ),
    Variables( X( :age ), X( :sex, Position( 1 ) ) ),
    Elements( Treemap( X( 1 ), X( 2 ), Legend( 12 ) ) )
);
obj << journal;

Code Explanation:

1. Open data table;
2. Create Graph Builder object.
3. Set window size.
4. Hide control panel.
5. Define X variables.
6. Add Treemap element.
7. Configure Treemap axes.
8. Add legend to Treemap.
9. Assign Treemap to object.
10. Generate journal output.

Example 1939

Summary: Creates a treemap visualization with nested factors using Graph Builder, displaying age as color and sex as X-axis variable.

Code:

Open("data_table.jmp");
gb = Graph Builder(
    Size( 495, 440 ),
    Show Control Panel( 0 ),
    Variables( X( :sex ), X( :age, Position( 1 ) ), Color( :age ) ),
    Elements( Treemap( X( 1 ), X( 2 ), Legend( 10 ) ) )
);

Code Explanation:

1. Open data table;
2. Create Graph Builder object.
3. Set window size.
4. Hide control panel.
5. Define X variables: sex, age.
6. Set age as second X variable.
7. Use age for color.
8. Add Treemap element.
9. Assign first X to Treemap.
10. Assign second X to Treemap.

Example 1940

Summary: Creates a treemap visualization with nested factors using Graph Builder, displaying sex and age as categorical variables and color-coded by age.

Code:

Open("data_table.jmp");
gb = Graph Builder(
    Size( 495, 440 ),
    Show Control Panel( 0 ),
    Variables( X( :sex ), X( :age, Position( 1 ) ), Color( :age ) ),
    Elements( Treemap( X( 1 ), X( 2 ), Legend( 10 ) ) )
);
gb << journal;

Code Explanation:

1. Open data table;
2. Create Graph Builder object.
3. Set window size.
4. Hide control panel.
5. Define variables: sex, age, color.
6. Add Treemap element.
7. Assign variables to axes.
8. Set legend position.
9. Display graph builder.
10. Save as journal.

Example 1941

Summary: Creates a Treemap visualization with nested factors using Graph Builder, displaying Katie's data in a customized format.

Code:

dt = Open("data_table.jmp");
rs = dt << get rows where( :name == "KATIE" );
:name[rs] = "KATIE" || "\";
Graph Builder( Size( 652, 471 ), Show Control Panel( 0 ), Variables( X( :name ) ), Elements( Treemap( X, Legend( 4 ) ) ) );

Code Explanation:

1. Open data table.
2. Retrieve rows where name is "KATIE".
3. Append double quote to selected names.
4. Launch Graph Builder.
5. Set window size.
6. Hide control panel.
7. Assign variable for X-axis.
8. Add Treemap element.
9. Configure Treemap legend.

Example 1942

Summary: Creates a treemap visualization with nested factors using Graph Builder, showcasing the relationship between age and height.

Code:

dt = Open("data_table.jmp");
Graph Builder(
    Size( 415, 261 ),
    Show Control Panel( 0 ),
    Show Legend( 0 ),
    Include Missing Categories( 1 ),
    Variables( X( :age ), Color( :height, Summary Statistic( "% of Total" ) ) ),
    Elements( Treemap( X, Legend( 5 ), Category Name( 1 ), Color Value( 1 ), Size Value( 1 ) ) ),
    SendToReport( Dispatch( {}, "Graph Builder", FrameBox, {Background Color( 0 )} ) )
);

Code Explanation:

1. Open table.
2. Set graph size.
3. Hide control panel.
4. Hide legend.
5. Include missing categories.
6. Set X variable.
7. Set color variable.
8. Add treemap element.
9. Customize category name.
10. Customize background color.

Example 1943

Summary: Creates a treemap visualization with nested factors using Graph Builder, filtering data by Meal and Food Category.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 646, 551 ),
    Show Control Panel( 0 ),
    Variables( X( :Food Category ), Y( :Fat ), Color( :Food Category ) ),
    Elements( Treemap( X( 1 ), X( 2 ), Y, Legend( 11 ), Layout( "Squarify" ) ) ),
    Local Data Filter(
        Add Filter( columns( :Meal ), Display( :Meal, Size( 216, 150 ), List Display ) ),
        Add Filter(
            columns( :Food Category ),
            Match Any( Where( :Food Category == "Bean" ) ),
            Display( :Food Category, Check Box Display )
        )
    )
);

Code Explanation:

1. Open data table;
2. Create Graph Builder window.
3. Set window size.
4. Hide control panel.
5. Assign variables to axes.
6. Add Treemap element.
7. Configure Treemap layout.
8. Add local data filter.
9. Filter by Meal column.
10. Filter Food Category for "Bean".

Example 1944

Summary: Creates a treemap visualization with nested factors using Graph Builder, displaying state and city information with color-coded maximum temperature data.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 865, 592 ),
    Show Control Panel( 0 ),
    Variables( X( :State ), X( :city, Position( 1 ) ), Y( :X ), Y( :Y, Position( 1 ) ), Color( :Max deg. F Jan ), Size( :POP ) ),
    Elements( Treemap( X( 1 ), X( 2 ), Y( 1 ), Y( 2 ) ) )
);

Code Explanation:

1. Open data table;
2. Launch Graph Builder.
3. Set window size.
4. Hide control panel.
5. Define variables for axes and color.
6. Create treemap element.
7. Assign states to X-axis.
8. Assign cities to nested X-axis.
9. Assign X values to Y-axis.
10. Assign Y values to nested Y-axis.

Example 1945

Summary: Creates a treemap visualization with two nested factors, utilizing Graph Builder to display height and weight data.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 532, 438 ),
    Show Control Panel( 0 ),
    Variables( X( :name ), Y( :height ), Y( :weight ) ),
    Elements( Position( 1, 1 ), Treemap( X, Y, Legend( 34 ) ) ),
    Elements( Position( 1, 2 ), Treemap( X, Y, Legend( 35 ) ) )
);

Code Explanation:

1. Open data table;
2. Launch Graph Builder.
3. Set window size.
4. Hide control panel.
5. Define X variable.
6. Define first Y variable.
7. Define second Y variable.
8. Add first treemap element.
9. Add second treemap element.
10. Display graph.

Example 1946

Summary: Creates a Treemap visualization with nested factors using Graph Builder, displaying standard deviation charts and adding pin annotations.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 495, 440 ),
    Show Control Panel( 0 ),
    Variables( X( :Single Status ), X( :Age Group, Position( 1 ) ), Color( :Salary ) ),
    Elements( Treemap( X( 1 ), X( 2 ), Legend( 1 ), Color Value( 1 ) ) ),
    SendToReport(
        Dispatch( {}, "Graph Builder", FrameBox,
            {DispatchSeg( TreeMapSeg( 1 ), Frame Size( 484, 392 ) ), Add Pin Annotation(
                Seg( TreeMapSeg( 1 ) ),
                Index( 7 ),
                Index Row( 7 ),
                UniqueID( 761984215 ),
                FoundPt( {276, 137} ),
                Origin( {261.363636363636, 314.285714285714} )
            )}
        )
    )
);

Code Explanation:

1. Open data table;
2. Create Graph Builder window.
3. Set window size.
4. Hide control panel.
5. Define X variables.
6. Define secondary X variable.
7. Define color variable.
8. Add Treemap element.
9. Adjust frame size.
10. Add pin annotation.

Example 1947

Summary: Creates a treemap chart with nested factors using Graph Builder, displaying standard deviation charts and pin annotations.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 573, 390 ),
    Show Control Panel( 0 ),
    Variables( X( :sex ), X( :age, Position( 1 ) ), Color( :height ), Size( :height ) ),
    Elements( Treemap( X( 1 ), X( 2 ), Legend( 12 ), Summary Statistic( "% of Total" ) ) ),
    SendToReport(
        Dispatch( {}, "Graph Builder", FrameBox,
            {DispatchSeg( TreeMapSeg( 1 ), Frame Size( 562, 342 ) ), Add Pin Annotation(
                Seg( TreeMapSeg( 1 ) ),
                Index( 8 ),
                Index Row( 20 ),
                UniqueID( 703552568 ),
                FoundPt( {299, 260} ),
                Origin( {321.464226289517, 182.291666666667} )
            )}
        )
    )
);

Code Explanation:

1. Open data table;
2. Launch Graph Builder.
3. Set window size.
4. Hide control panel.
5. Assign variables: sex, age, height.
6. Create treemap element.
7. Configure treemap summary statistic.
8. Adjust frame size.
9. Add pin annotation.
10. Specify annotation details.

Example 1948

Summary: Creates a Treemap visualization in Graph Builder, displaying age as the X-axis and weight as the size variable, with currency formatting for the size label.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 523, 369 ),
    Show Control Panel( 0 ),
    Variables( X( :age ), Size( :weight ) ),
    Elements( Treemap( X, Legend( 11 ), Size Value( 1 ), Size Label Format( "Currency", "USD", Use thousands separator( 0 ), 10, 0 ) ) ),
    SendToReport(
        Dispatch( {}, "Graph Builder", FrameBox,
            Add Pin Annotation(
                Seg( TreeMapSeg( 1 ) ),
                Index( 0 ),
                Index Row( 0 ),
                UniqueID( 0 ),
                FoundPt( {113, 157} ),
                Origin( {85.691796875, 221.195794392523} ),
                RightOfCenter( 0 ),
                Tag Line( 1 )
            )
        )
    )
);

Code Explanation:

1. Open data table;
2. Create Graph Builder window.
3. Set window size to 523x369.
4. Hide control panel.
5. Set X variable to age.
6. Set size variable to weight.
7. Add Treemap element.
8. Configure Treemap legend.
9. Set size value to 1.
10. Format size label as currency USD without thousands separator.

Example 1949

Summary: Creates a Treemap visualization with nested factors using Graph Builder, displaying softness on the X-axis twice.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 253, 241 ),
    Show Control Panel( 0 ),
    Variables( X( :softness ), X( :softness, Position( 1 ) ) ),
    Elements( Treemap( X( 1 ), Legend( 3 ) ) )
);

Code Explanation:

1. Open data_table data
2. Create Graph Builder window.
3. Set size to 253x241.
4. Hide control panel.
5. Assign softness to X-axis twice.
6. Add Treemap element.
7. Map first X-axis to Treemap.
8. Use third legend for Treemap.

Example 1950

Summary: Creates a treemap visualization with nested factors using Graph Builder, displaying the count of observations for each combination.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 399, 305 ),
    Show Control Panel( 0 ),
    Show Legend( 0 ),
    Variables( X( :height ), X( :weight, Position( 1 ) ), Y( :age ) ),
    Elements( Treemap( X( 1 ), X( 2 ), Y, Legend( 4 ), Summary Statistic( "N" ) ) )
);

Code Explanation:

1. Open data table;
2. Launch Graph Builder.
3. Set window size.
4. Hide control panel.
5. Hide legend.
6. Assign variables: height, weight, age.
7. Create treemap element.
8. Position weight on X-axis.
9. Set summary statistic to count.
10. Display graph.

Example 1951

Summary: Creates a Treemap visualization with nested factors using Graph Builder, configuring group labels and colors.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 608, 503 ),
    Show Control Panel( 0 ),
    Show Legend( 0 ),
    Variables( X( :sex ), X( :age, Position( 1 ) ) ),
    Elements( Treemap( X( 1 ), X( 2 ), Legend( 6 ) ) ),
    SendToReport(
        Dispatch( {}, "Graph Builder", FrameBox,
            {DispatchSeg(
                TreeMapSeg( 1 ),
                {Set Group Label Color( "Red" ), Set Group Label Border Color( "Red" ), Set Group Label Font Color( "Yellow" ),
                Set Group Label Font( "Floating", Size( 48 ) )}
            )}
        )
    )
);

Code Explanation:

1. Open data table;
2. Create Graph Builder window.
3. Set window size.
4. Hide control panel.
5. Hide legend.
6. Define X variables: sex, age.
7. Add Treemap element.
8. Configure Treemap labels.
9. Set group label color to red.
10. Set group label border color to red.
11. Set group label font color to yellow.
12. Set group label font style and size.

Example 1952

Summary: Creates a Treemap visualization with nested factors using Graph Builder, customizing group labels and displaying standard deviation charts.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 608, 503 ),
    Show Control Panel( 0 ),
    Show Legend( 0 ),
    Variables( X( :sex ), X( :age, Position( 1 ) ) ),
    Elements( Treemap( X( 1 ), X( 2 ), Legend( 6 ) ) ),
    SendToReport(
        Dispatch( {}, "Graph Builder", FrameBox,
            {DispatchSeg(
                TreeMapSeg( 1 ),
                {Set Group Label Color( "Red" ), Set Group Label Border Color( "Red" ), Set Group Label Font Color( "Yellow" ),
                Set Group Label Font( "Floating", Size( 48 ) )}
            )}
        )
    )
);
Current Report() << save journal( "$TEMP/Test.jrn" );

Code Explanation:

1. Open data table;
2. Create Graph Builder window.
3. Set graph size.
4. Hide control panel.
5. Hide legend.
6. Define X variables.
7. Add Treemap element.
8. Customize Treemap labels.
9. Save report as journal.

Example 1953

Summary: Creates a treemap visualization with nested factors using Graph Builder, customizing group labels and displaying standard deviation charts.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 608, 503 ),
    Show Control Panel( 0 ),
    Show Legend( 0 ),
    Variables( X( :sex ), X( :age, Position( 1 ) ) ),
    Elements( Treemap( X( 1 ), X( 2 ), Legend( 6 ) ) ),
    SendToReport(
        Dispatch( {}, "Graph Builder", FrameBox,
            {DispatchSeg(
                TreeMapSeg( 1 ),
                {Set Group Label Color( "Red" ), Set Group Label Border Color( "Red" ), Set Group Label Font Color( "Yellow" ),
                Set Group Label Font( "Floating", Size( 48 ) )}
            )}
        )
    )
);
Current Report() << save journal( "$TEMP/Test.jrn" );
Open( "$TEMP/Test.jrn" );

Code Explanation:

1. Open data table;
2. Create Graph Builder window.
3. Set window size.
4. Hide control panel.
5. Hide legend.
6. Define X variables.
7. Add Treemap element.
8. Customize group labels.
9. Save report as journal.
10. Open saved journal.

Example 1954

Summary: Creates a Treemap visualization with nested factors using Graph Builder, customizing group labels and colors.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 608, 503 ),
    Show Control Panel( 0 ),
    Show Legend( 0 ),
    Variables( X( :sex ), X( :age, Position( 1 ) ) ),
    Elements( Treemap( X( 1 ), X( 2 ), Legend( 6 ), Group Labels( "Above" ) ) ),
    SendToReport(
        Dispatch( {}, "Graph Builder", FrameBox,
            {DispatchSeg(
                TreeMapSeg( 1 ),
                {Set Group Label Color( "Red" ), Set Group Label Border Color( "Red" ), Set Group Label Font Color( "Fuchsia" ),
                Set Group Label Font( "Above", Size( 18 ) )}
            )}
        )
    )
);

Code Explanation:

1. Open data table.
2. Create Graph Builder object.
3. Set window size.
4. Hide control panel.
5. Hide legend.
6. Define X variables.
7. Add Treemap element.
8. Position group labels above.
9. Customize group label color.
10. Customize group label border color.

Example 1955

Summary: Creates a Treemap visualization in Graph Builder, displaying nested factors and customizing group label properties.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 608, 503 ),
    Show Control Panel( 0 ),
    Show Legend( 0 ),
    Variables( X( :sex ), X( :age, Position( 1 ) ) ),
    Elements( Treemap( X( 1 ), X( 2 ), Legend( 6 ), Group Labels( "Above" ) ) ),
    SendToReport(
        Dispatch( {}, "Graph Builder", FrameBox,
            {DispatchSeg(
                TreeMapSeg( 1 ),
                {Set Group Label Color( "Red" ), Set Group Label Border Color( "Red" ), Set Group Label Font Color( "Fuchsia" ),
                Set Group Label Font( "Above", Size( 24 ) )}
            )}
        )
    )
);

Code Explanation:

1. Open data table;
2. Create Graph Builder window.
3. Set window size.
4. Hide control panel.
5. Hide legend.
6. Define X variables: sex, age.
7. Add Treemap element.
8. Configure group labels position.
9. Customize group label color.
10. Customize group label font properties.

Example 1956

Summary: Creates a Treemap visualization with nested factors using Graph Builder, configuring group labels and maximum label size.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 735, 167 ),
    Show Control Panel( 0 ),
    Variables( X( :age ), X( :sex, Position( 1 ) ) ),
    Elements( Treemap( X( 1 ), X( 2 ), Legend( 5 ), Group Labels( "Above" ), Max Label Size( 20 ) ) ),
    SendToReport(
        Dispatch( {}, "Graph Builder", FrameBox,
            {DispatchSeg( TreeMapSeg( 1 ), {Set Group Spacing( 10 ), Set Group Label Font( "Above", Size( 48 ) )} )}
        )
    )
);

Code Explanation:

1. Open data table;
2. Launch Graph Builder.
3. Set graph size.
4. Hide control panel.
5. Define X variables.
6. Add Treemap element.
7. Configure group labels.
8. Set maximum label size.
9. Adjust group spacing.
10. Change group label font size.

Example 1957

Summary: Creates a treemap visualization with nested factors using Graph Builder, displaying population size and maximum temperature in January.

Code:

Open("data_table.jmp");
obj = Graph Builder(
    Size( 654, 482 ),
    Show Control Panel( 0 ),
    Variables( X( :State ), X( :city, Position( 1 ) ), Y( :X ), Color( :Max deg. F Jan ), Size( :POP ) ),
    Elements( Treemap( X( 1 ), X( 2 ), Y, Legend( 1 ) ) )
);
obj << save journal( "$TEMP\Test.jrn" );

Code Explanation:

1. Open data table;
2. Create Graph Builder object.
3. Set window size.
4. Hide control panel.
5. Define X, Y, Color, Size variables.
6. Add Treemap element.
7. Save journal to temp directory.

Example 1958

Summary: Creates a treemap visualization with nested factors using Graph Builder, displaying population size and maximum temperature in January.

Code:

Open("data_table.jmp");
obj = Graph Builder(
    Size( 654, 482 ),
    Show Control Panel( 0 ),
    Variables( X( :State ), X( :city, Position( 1 ) ), Y( :X ), Color( :Max deg. F Jan ), Size( :POP ) ),
    Elements( Treemap( X( 1 ), X( 2 ), Y, Legend( 1 ) ) )
);
obj << save journal( "$TEMP\Test.jrn" );
Open( "$TEMP\Test.jrn" );

Code Explanation:

1. Open data table;
2. Create Graph Builder object.
3. Set graph size.
4. Hide control panel.
5. Define variables: X, X, Y, Color, Size.
6. Add Treemap element.
7. Save graph as journal.
8. Open saved journal.

Example 1959

Summary: Creates a Treemap visualization in Graph Builder to display nested factors, utilizing variables age, height, and sex.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 397, 347 ),
    Show Control Panel( 0 ),
    Variables( X( :age ), Y( :height ), Y( :sex, Position( 1 ) ) ),
    Elements(
        Treemap(
            X,
            Y( 1 ),
            Y( 2 ),
            Legend( 4 ),
            Category Name( 1 ),
            Size Value( 1 ),
            Max Label Size( 20 ),
            Label Threshold( 100 ),
            Show Frames( 0 ),
            Implicit Color( 0 )
        )
    )
);

Code Explanation:

1. Open data table;
2. Launch Graph Builder.
3. Set window size.
4. Hide control panel.
5. Assign variables.
6. Add Treemap element.
7. Specify X variable.
8. Specify first Y variable.
9. Specify second Y variable.
10. Configure Treemap settings.

Example 1960

Summary: Creates two variability charts with nested factors using Graph Builder, configuring Treemap elements and setting graph titles.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 508, 482 ),
    Show Control Panel( 0 ),
    Variables( X( :age ), Color( :height ), Size( :height ) ),
    Elements( Treemap( X, Legend( 1 ), Category Value( 0 ) ) ),
    SendToReport( Dispatch( {}, "graph title", TextEditBox, {Set Text( "no labels" )} ) )
);
Graph Builder(
    Size( 508, 374 ),
    Show Control Panel( 0 ),
    Variables( X( :age ), Color( :height ), Size( :height ) ),
    Elements( Treemap( X, Legend( 1 ), Category Name( 1 ), Color Value( 1 ), Color Name( 1 ), Size Value( 1 ), Size Name( 1 ) ) ),
    SendToReport( Dispatch( {}, "graph title", TextEditBox, {Set Text( "all labels and names" )} ) )
);

Code Explanation:

1. Open data table;
2. Create first Graph Builder.
3. Set size to 508x482.
4. Hide control panel.
5. Assign variables: age (X), height (Color, Size).
6. Add Treemap element.
7. Disable category value labels.
8. Set graph title to "no labels".
9. Create second Graph Builder.
10. Set size to 508x374.
11. Hide control panel.
12. Assign variables: age (X), height (Color, Size).
13. Add Treemap element.
14. Enable all label options.
15. Set graph title to "all labels and names".

Example 1961

Summary: Creates Treemap graphs with varying configurations to visualize data relationships, including nested factors and operator settings.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 508, 482 ),
    Show Control Panel( 0 ),
    Variables( X( :age ), Color( :height ), Size( :height ) ),
    Elements( Treemap( X, Legend( 1 ), Category Value( 0 ) ) ),
    SendToReport( Dispatch( {}, "graph title", TextEditBox, {Set Text( "no labels" )} ) )
);
Graph Builder(
    Size( 508, 374 ),
    Show Control Panel( 0 ),
    Variables( X( :age ), Color( :height ), Size( :height ) ),
    Elements( Treemap( X, Legend( 1 ), Category Name( 1 ), Color Value( 1 ), Color Name( 1 ), Size Value( 1 ), Size Name( 1 ) ) ),
    SendToReport( Dispatch( {}, "graph title", TextEditBox, {Set Text( "all labels and names" )} ) )
);
dt = Open("data_table.jmp");
Graph Builder(
    Size( 508, 467 ),
    Show Control Panel( 0 ),
    Variables( X( :city ), Color( :OZONE ) ),
    Elements(
        Treemap( X, Legend( 1 ), Category Value( 0 ), Color Value( 1 ), Size Value( 1 ), Label Justification( "Right" ), Show Frames( 0 ) )
    ),
    SendToReport(
        Dispatch( {}, "graph title", TextEditBox,
            {Set Text( "Color Value & Size Value (no Category Value or names), right justification, don't show frames" )}
        )
    )
);
Graph Builder(
    Size( 508, 553 ),
    Show Control Panel( 0 ),
    Variables( X( :city ), Size( :POP ) ),
    Elements(
        Treemap( X, Legend( 1 ), Category Name( 1 ), Size Value( 1 ), Size Name( 1 ), Label Justification( "Left" ), Implicit Color( 0 ) )
    ),
    SendToReport(
        Dispatch( {}, "graph title", TextEditBox, {Set Text( "left justification, category and size, sum, no implicit color" )} )
    )
);

Code Explanation:

1. Open data_table data
2. Create Treemap graph.
3. Set graph size and hide control panel.
4. Assign age to X, height to Color and Size.
5. Disable category labels.
6. Set graph title to "no labels".
7. Create another Treemap graph.
8. Enable all labels and names.
9. Set graph title to "all labels and names".
10. Open data_table data
11. Create Treemap graph.
12. Set graph size and hide control panel.
13. Assign city to X, OZONE to Color.
14. Enable color and size values.
15. Right justify labels.
16. Hide frames.
17. Set graph title to "Color Value & Size Value (no Category Value or names), right justification, don't show frames".
18. Create another Treemap graph.
19. Set graph size and hide control panel.
20. Assign city to X, POP to Size.
21. Enable category name and size value.
22. Left justify labels.
23. Disable implicit color.
24. Set graph title to "left justification, category and size, sum, no implicit color".

Example 1962

Summary: Creates two Graph Builder windows with Treemap elements to visualize nested factors, utilizing different layouts and legend assignments.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 304, 243 ),
    Show Control Panel( 0 ),
    Variables( X( :age ), X( :sex, Position( 1 ) ) ),
    Elements( Treemap( X( 1 ), Legend( 5 ) ) )
);
Graph Builder(
    Size( 293, 284 ),
    Show Control Panel( 0 ),
    Variables( X( :age ), X( :sex, Position( 1 ) ) ),
    Elements( Treemap( X( 1 ), Legend( 2 ), Layout( "Squarify" ) ) )
);

Code Explanation:

1. Open data table.
2. Create first Graph Builder window.
3. Set window size.
4. Hide control panel.
5. Define X variables: age, sex.
6. Add Treemap element.
7. Assign legend to Treemap.
8. Create second Graph Builder window.
9. Set window size.
10. Hide control panel.
11. Define X variables: age, sex.
12. Add Treemap element.
13. Assign legend to Treemap.
14. Set layout to Squarify.

Example 1963

Summary: Creates a treemap visualization to display height data by age and sex, utilizing Graph Builder in JMP.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 629, 430 ),
    Show Control Panel( 0 ),
    Show Legend( 0 ),
    Level Fill Color( {218, 255, 139} ),
    Variables( X( :age, Levels( 6 ), Levels per Row( 1 ), N View Levels( 1 ) ), Y( :height ), Group X( :sex, Show Title( 0 ) ) ),
    Elements( Treemap( X, Y, Legend( 25 ) ) )
);

Code Explanation:

1. Open data_table data
2. Create Graph Builder.
3. Set size to 629x430.
4. Hide control panel.
5. Hide legend.
6. Set level fill color.
7. Define X variable: age.
8. Define Y variable: height.
9. Group by sex without title.
10. Add treemap element.

Example 1964

Summary: Creates a treemap visualization in Graph Builder, using sex and age as X variables and weight as color, with max label size set to 10.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 495, 440 ),
    Show Control Panel( 0 ),
    Variables( X( :sex ), X( :age, Position( 1 ) ), Color( :weight ) ),
    Elements( Treemap( X( 1 ), X( 2 ), Legend( 1 ), Labels( "Auto size" ), Max Label Size( 10 ) ) ),
    SendToReport( Dispatch( {}, "Graph Builder", OutlineBox, {Set Title( "Graph Builder - Max Label Size = 10" )} ) )
);

Code Explanation:

1. Open data_table data
2. Launch Graph Builder.
3. Set window size to 495x440.
4. Hide control panel.
5. Assign sex to X.
6. Assign age to X1.
7. Assign weight to color.
8. Create treemap element.
9. Set max label size to 10.
10. Set title to "Graph Builder - Max Label Size = 10".

Example 1965

Summary: Creates a Treemap visualization with nested factors using Graph Builder, displaying standard deviation charts and enabling filtering by Meal and Food Category.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 646, 551 ),
    Show Control Panel( 0 ),
    Variables( X( :Food Category ), X( :Item Name, Position( 1 ) ), Y( :Fat ), Color( :Food Category ) ),
    Elements( Treemap( X( 1 ), X( 2 ), Y, Legend( 11 ), Layout( "Squarify" ) ) ),
    Local Data Filter(
        Add Filter( columns( :Meal ), Display( :Meal, Size( 216, 150 ), List Display ) ),
        Add Filter(
            columns( :Food Category ),
            Match Any( Where( :Food Category == "Bean" ) ),
            Display( :Food Category, Check Box Display )
        )
    ),
    SendToReport(
        Dispatch( {}, "Graph Builder", FrameBox,
            Add Text Annotation(
                Text( "MR data will now produce empty Treemap: JMP-1106" ),
                Fixed Size( 0 ),
                Text Box( {18, 20, 318, 44} ),
                Filled( 0 )
            )
        )
    )
);

Code Explanation:

1. Open data table;
2. Create Graph Builder window.
3. Set window size.
4. Hide control panel.
5. Define X variables.
6. Define additional X variable.
7. Define Y variable.
8. Define color variable.
9. Add Treemap element.
10. Configure Treemap layout.
11. Add local data filter for Meal.
12. Add local data filter for Food Category.
13. Display specific category checkbox.
14. Add text annotation.
15. Position text annotation.
16. Set text annotation properties.

Example 1966

Summary: Creates a Graph Builder window with nested factors, displaying points and treemap elements to visualize variability data.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 553, 462 ),
    Show Control Panel( 0 ),
    Variables( X( :name ), Y( :height ), Y( :weight ) ),
    Elements( Position( 1, 1 ), Points( X, Y, Legend( 36 ) ) ),
    Elements( Position( 1, 2 ), Treemap( X, Y, Legend( 35 ) ) )
);

Code Explanation:

1. Open data table;
2. Create Graph Builder window.
3. Set window size.
4. Hide control panel.
5. Define X variable.
6. Define first Y variable.
7. Define second Y variable.
8. Add points element.
9. Position points in top-left.
10. Add treemap element.
11. Position treemap below points.

Example 1967

Summary: Creates a treemap visualization with nested factors using Graph Builder, displaying standard deviation charts and configuring font settings.

Code:

Open("data_table.jmp");
gb = Graph Builder(
    Show Control Panel( 0 ),
    Variables( X( :Region ), X( :State, Position( 1 ) ) ),
    Elements( Treemap( X( 1 ), X( 2 ), Legend( 3 ) ) )
);
frame = Report( gb )[FrameBox( 1 )];
fontobj = seg = (frame << Find Seg( "TreeMapSeg" ));
fontobj << Set Font( "Arial Black" );
Names Default To Here( 1 );

Code Explanation:

1. Open data table;
2. Create graph builder object.
3. Hide control panel.
4. Set X variables: Region, State.
5. Add treemap element.
6. Get frame box reference.
7. Find treemap segments.
8. Set font to Arial Black.
9. Set names default to here.

Example 1968

Summary: Creates a treemap visualization with nested factors, utilizing Graph Builder to display data from an open JMP data table.

Code:

Open("data_table.jmp");
gb = Graph Builder(
    Show Control Panel( 0 ),
    Variables( X( :Region ), X( :State, Position( 1 ) ) ),
    Elements( Treemap( X( 1 ), X( 2 ), Legend( 3 ) ) )
);
frame = Report( gb )[FrameBox( 1 )];
fontobj = seg = (frame << Find Seg( "TreeMapSeg" ));
fontobj << Set Font Name( "Arial Black" );
Names Default To Here( 1 );

Code Explanation:

1. Open data table;
2. Create Graph Builder object.
3. Hide control panel.
4. Set X variables: Region, State.
5. Add Treemap element.
6. Retrieve frame box.
7. Find TreeMap segments.
8. Set font name to Arial Black.
9. Enable names default to here.

Example 1969

Summary: Creates a treemap visualization with nested factors using Graph Builder, hiding the control panel and customizing font scale.

Code:

Open("data_table.jmp");
gb = Graph Builder(
    Show Control Panel( 0 ),
    Variables( X( :Region ), X( :State, Position( 1 ) ) ),
    Elements( Treemap( X( 1 ), X( 2 ), Legend( 3 ) ) )
);
frame = Report( gb )[FrameBox( 1 )];
fontobj = seg = (frame << Find Seg( "TreeMapSeg" ));
fontobj << Set Font Scale( 2.0 );
Names Default To Here( 1 );

Code Explanation:

1. Open data table.
2. Create Graph Builder object.
3. Hide control panel.
4. Define X variables: Region, State.
5. Add Treemap element.
6. Assign frame to variable.
7. Find segments in frame.
8. Set font scale to 2.0.
9. Set default names scope.

Example 1970

Summary: Creates a treemap visualization with nested factors using Graph Builder, hiding the control panel and setting font size to 14.

Code:

Open("data_table.jmp");
gb = Graph Builder(
    Show Control Panel( 0 ),
    Variables( X( :Region ), X( :State, Position( 1 ) ) ),
    Elements( Treemap( X( 1 ), X( 2 ), Legend( 3 ) ) )
);
frame = Report( gb )[FrameBox( 1 )];
fontobj = seg = (frame << Find Seg( "TreeMapSeg" ));
fontobj << Set Font Size( 14 );
Names Default To Here( 1 );

Code Explanation:

1. Open data table.
2. Create Graph Builder object.
3. Hide control panel.
4. Set X variables: Region, State.
5. Add Treemap element.
6. Retrieve frame box reference.
7. Find Treemap segments.
8. Set font size to 14.
9. Set default names scope.

Example 1971

Summary: Creates a treemap visualization with nested factors, utilizing Graph Builder to display regional data with state-level granularity.

Code:

Open("data_table.jmp");
gb = Graph Builder(
    Show Control Panel( 0 ),
    Variables( X( :Region ), X( :State, Position( 1 ) ) ),
    Elements( Treemap( X( 1 ), X( 2 ), Legend( 3 ) ) )
);
frame = Report( gb )[FrameBox( 1 )];
fontobj = seg = (frame << Find Seg( "TreeMapSeg" ));
fontobj << Set Font Style( "Italic" );
Names Default To Here( 1 );

Code Explanation:

1. Open data table;
2. Create graph builder object.
3. Hide control panel.
4. Set X variables: Region, State.
5. Add treemap element.
6. Retrieve frame box.
7. Find treemap segments.
8. Set font style to italic.
9. Set default names context.

Example 1972

Summary: Creates a treemap visualization with nested factors using Graph Builder, configuring variables and elements to display data from a JMP data table.

Code:

Open("data_table.jmp");
gb = Graph Builder( Show Control Panel( 0 ), Variables( X( :State ), X( :city, Position( 1 ) ), ), Elements( Treemap( X( 1 ), X( 2 ) ) ) );
frame = Report( gb )[FrameBox( 1 )];
seg = (frame << Find Seg( "TreeMapSeg" ));
seg << Set Group Label Font( "Arial Black", 16 );
Names Default To Here( 1 );

Code Explanation:

1. Open data table;
2. Create Graph Builder object.
3. Configure Graph Builder variables.
4. Add Treemap element.
5. Access first frame box.
6. Find segments by name.
7. Set group label font.
8. Enable default names.

Example 1973

Summary: Creates a treemap visualization using Graph Builder to display nested factors from a data table, with control panel visibility turned off.

Code:

Open("data_table.jmp");
gb = Graph Builder( Show Control Panel( 0 ), Variables( X( :State ), X( :city, Position( 1 ) ), ), Elements( Treemap( X( 1 ), X( 2 ) ) ) );
frame = Report( gb )[FrameBox( 1 )];
seg = (frame << Find Seg( "TreeMapSeg" ));

Code Explanation:

1. Open data_table data
2. Create Graph Builder object.
3. Set control panel visibility off.
4. Assign State and city variables.
5. Add Treemap element.
6. Retrieve first frame box.
7. Find segments named "TreeMapSeg".

Example 1974

Summary: Creates a treemap visualization to display the percentage of total for each sex and height combination, utilizing Graph Builder.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 353, 183 ),
    Show Control Panel( 0 ),
    Variables( X( :sex ), size( :height ) ),
    Elements( Treemap( X, Summary Statistic( "% of total" ), Size Value( 1 ) ) )
);

Code Explanation:

1. Open data table;
2. Launch Graph Builder.
3. Set window size.
4. Hide control panel.
5. Assign X variable.
6. Assign size variable.
7. Create treemap element.
8. Use summary statistic.
9. Set size value.
10. Display graph.

Example 1975

Summary: Creates a treemap visualization to display nested factors using Graph Builder, with X variable as Position, Y variable as Weight, Group Y as Bench, and Overlay as Fat.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 1150, 450 ),
    Show Control Panel( 0 ),
    Variables( X( :Position ), Y( :Weight ), Group Y( :Bench ), Overlay( :Fat ) ),
    Elements( Treemap( X, Y, Legend( 5 ), Summary Statistic( "% of Total" ), Size Value( 1 ) ) )
);

Code Explanation:

1. Open data table;
2. Create Graph Builder window.
3. Set size to 1150x450.
4. Hide control panel.
5. Define X variable as Position.
6. Define Y variable as Weight.
7. Define Group Y as Bench.
8. Define Overlay as Fat.
9. Add Treemap element.
10. Set summary statistic to "% of Total".

Example 1976

Summary: Creates a Treemap visualization with nested factors using Graph Builder, displaying Mfr on the X-axis, Sugars on the Y-axis, and overlaying Calories.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 568, 378 ),
    Show Control Panel( 0 ),
    Variables( X( :Mfr ), Y( :Sugars ), Overlay( :Calories ) ),
    Elements( Treemap( X, Y, Legend( 11 ), Category Name( 1 ), Size Value( 1 ) ) )
);

Code Explanation:

1. Open data table;
2. Create Graph Builder window.
3. Set window size to 568x378.
4. Hide control panel.
5. Assign Mfr to X-axis.
6. Assign Sugars to Y-axis.
7. Overlay Calories.
8. Add Treemap element.
9. Use category name for labels.
10. Use size value for tile size.

Example 1977

Summary: Creates a Treemap visualization in Graph Builder to display the relationship between weight and height, using X-axis for categorical values and Y-axis for continuous values.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 327, 298 ),
    Show Control Panel( 0 ),
    Variables( X( :weight ), Y( :height ) ),
    Elements( Treemap( X, Y, Legend( 5 ), Summary Statistic( "N" ), Implicit Color( 0 ) ) )
);

Code Explanation:

1. Open data table.
2. Create Graph Builder window.
3. Set window size.
4. Hide control panel.
5. Assign X variable.
6. Assign Y variable.
7. Add Treemap element.
8. Use X for treemap.
9. Use Y for treemap.
10. Configure legend and summary statistic.

Example 1978

Summary: Creates a Treemap visualization in Graph Builder, displaying the relationship between :Make and :Wt variables.

Code:

Open("data_table.jmp");
Graph Builder( Size( 697, 476 ), Show Control Panel( 0 ), Variables( X( :Make ), Y( :Wt ) ), Elements( Treemap( X, Y, Legend( 6 ) ) ) );

Code Explanation:

1. Open data table.
2. Launch Graph Builder.
3. Set window size to 697x476.
4. Hide control panel.
5. Assign X variable as :Make.
6. Assign Y variable as :Wt.
7. Add Treemap element.
8. Set X and Y for Treemap.
9. Enable legend at position 6.

Example 1979

Summary: Creates a treemap visualization in Graph Builder to display the percentage of total for each sex, utilizing the Size Value operator.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 353, 183 ),
    Show Control Panel( 0 ),
    Variables( X( :sex ) ),
    Elements( Treemap( X, Summary Statistic( "% of total" ), Size Value( 1 ) ) )
);

Code Explanation:

1. Open data table;
2. Launch Graph Builder.
3. Set window size.
4. Hide control panel.
5. Assign X variable.
6. Add Treemap element.
7. Set summary statistic.
8. Define size value.

Example 1980

Summary: Creates a Treemap visualization with nested factors using Graph Builder, showcasing the relationship between 'Rank[sex]' and 'height'.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 300, 200 ),
    Show Control Panel( 0 ),
    Variables( X( Transform Column( "Rank[sex]", Character, Formula( Col Rank( :sex ) ) ) ), Size( :height ) ),
    Elements( Treemap( X, Legend( 13 ) ) )
);

Code Explanation:

1. Open data table;
2. Launch Graph Builder.
3. Set window size.
4. Hide control panel.
5. Define X variable.
6. Create rank column.
7. Use sex for ranking.
8. Define size variable.
9. Use height for size.
10. Add Treemap element.

Example 1981

Summary: Creates a Treemap visualization in Graph Builder, displaying nested factors and standard deviation charts from a data table.

Code:

Open("data_table.jmp");
Graph Builder( Size( 449, 384 ), Show Control Panel( 0 ), Variables( X( :age ), Y( :height ) ), Elements( Treemap( X, Y, Legend( 4 ) ) ) );

Code Explanation:

1. Open data table.
2. Launch Graph Builder.
3. Set window size.
4. Hide control panel.
5. Assign X variable.
6. Assign Y variable.
7. Add Treemap element.
8. Configure Treemap legend.

Example 1982

Summary: Creates a Treemap visualization with nested factors using Graph Builder, displaying height, sex, and age as categorical variables.

Code:

dt = Open("data_table.jmp");
dt:height << set modeling type( "Ordinal" );
Graph Builder(
    Show Control Panel( 0 ),
    Variables( X( :height ), X( :sex, Position( 1 ) ), X( :age, Position( 1 ) ) ),
    Elements( Treemap( X( 1 ), X( 2 ), X( 3 ) ) )
);

Code Explanation:

1. Open data table;
2. Set height modeling type to Ordinal.
3. Launch Graph Builder.
4. Hide control panel.
5. Add height to X-axis.
6. Add sex to X-axis, position 1.
7. Add age to X-axis, position 1.
8. Create Treemap element.
9. Assign height to Treemap X1.
10. Assign sex to Treemap X2.
11. Assign age to Treemap X3.

Example 1983

Summary: Creates a treemap visualization with nested factors using Graph Builder, setting height modeling type to Ordinal and then Continuous.

Code:

dt = Open("data_table.jmp");
dt:height << set modeling type( "Ordinal" );
Graph Builder(
    Show Control Panel( 0 ),
    Variables( X( :height ), X( :sex, Position( 1 ) ), X( :age, Position( 1 ) ) ),
    Elements( Treemap( X( 1 ), X( 2 ), X( 3 ) ) )
);
dt:height << set modeling type( "Continuous" );

Code Explanation:

1. Open data table.
2. Set height modeling type to Ordinal.
3. Create Graph Builder object.
4. Hide control panel.
5. Define X variables: height, sex, age.
6. Position sex and age at position 1.
7. Add Treemap element with three X variables.
8. Reset height modeling type to Continuous.

Example 1984

Summary: Creates a treemap visualization in Graph Builder, displaying age values with custom colors and enabling legend control.

Code:

Open("data_table.jmp");
:age << set property( "Value Colors", {12 = -13977687, 13 = -3780931, 14 = -4222943, 15 = -13596966, 16 = -2211217, 17 = -10562780} );
Graph Builder( Size( 495, 440 ), Show Control Panel( 0 ), Variables( X( :age ), Color( :age ) ), Elements( Treemap( X, Legend( 1 ) ) ) );

Code Explanation:

1. Open data table;
2. Set age value colors.
3. Create Graph Builder window.
4. Disable control panel.
5. Set X variable to age.
6. Set color variable to age.
7. Add Treemap element.
8. Enable legend for Treemap.

Example 1985

Summary: Creates a treemap visualization in Graph Builder, utilizing variables for age and sex, with customization options for legend and report title.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 495, 440 ),
    Show Control Panel( 0 ),
    Variables( X( :age ), Size( :sex ) ),
    Elements( Treemap( X, Legend( 13 ) ) ),
    SendToReport( Dispatch( {}, "Graph Builder", OutlineBox, {Set Title( "Graph Builder - Size role should be ignored" )} ) )
);

Code Explanation:

1. Open data table;
2. Create new Graph Builder window.
3. Set window size.
4. Hide control panel.
5. Assign variables for treemap.
6. Add treemap element.
7. Customize treemap legend.
8. Send report to Graph Builder.
9. Set title for graph builder.

Example 1986

Summary: Creates a Treemap visualization with nested factors using Graph Builder, displaying standard deviation charts and color labels.

Code:

Open("data_table.jmp");
obj = Graph Builder(
    show control panel( 0 ),
    Variables( X( :sex ), X( :age, Position( 1 ) ), Color( :weight ) ),
    Elements( Treemap( X( 1 ), X( 2 ), Legend( 1 ), Color Label( 1 ), Size Label( 1 ) ) )
);
obj << save journal( "$TEMP/S1245767.jrn" );

Code Explanation:

1. Open data table;
2. Create Graph Builder object.
3. Hide control panel.
4. Set X variables: sex, age.
5. Set color variable: weight.
6. Add Treemap element.
7. Assign X positions for Treemap.
8. Enable legend for Treemap.
9. Use color labels for Treemap.
10. Use size labels for Treemap.
11. Save journal to temp directory.

Example 1987

Summary: Creates a Treemap visualization with nested factors using Graph Builder, displaying standard deviation charts and configuring labels and legend.

Code:

Open("data_table.jmp");
obj = Graph Builder(
    show control panel( 0 ),
    Variables( X( :sex ), X( :age, Position( 1 ) ), Color( :weight ) ),
    Elements( Treemap( X( 1 ), X( 2 ), Legend( 1 ), Color Label( 1 ), Size Label( 1 ) ) )
);
obj << save journal( "$TEMP/S1245767.jrn" );
Open( "$TEMP/S1245767.jrn" );

Code Explanation:

1. Open data table.
2. Create Graph Builder object.
3. Hide control panel.
4. Set X variables: sex, age.
5. Set color variable: weight.
6. Add Treemap element.
7. Configure Treemap labels and legend.
8. Save graph as journal.
9. Open saved journal.

Example 1988

Summary: Creates two treemap visualizations using Graph Builder to display nested factors with different fill lightening settings.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 455, 310 ),
    Show Control Panel( 0 ),
    Lighten large fills( 0 ),
    Variables( X( :sex ) ),
    Elements( Treemap( X, Legend( 3 ) ) )
);
Graph Builder(
    Size( 455, 310 ),
    Show Control Panel( 0 ),
    Lighten large fills( 1 ),
    Variables( X( :sex ) ),
    Elements( Treemap( X, Legend( 3 ) ) )
);

Code Explanation:

1. Open data table;
2. Create first Graph Builder window.
3. Set window size.
4. Hide control panel.
5. Disable lighten large fills.
6. Set X variable to sex.
7. Add treemap element.
8. Create second Graph Builder window.
9. Set window size.
10. Hide control panel.
11. Enable lighten large fills.

Example 1989

Summary: Creates two pie charts to visualize the distribution of sex across a dataset, with varying fill lightness.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 494, 310 ),
    Show Control Panel( 0 ),
    Lighten large fills( 0 ),
    Variables( X( :sex ) ),
    Elements( Pie( X, Legend( 3 ) ) )
);
Graph Builder(
    Size( 494, 310 ),
    Show Control Panel( 0 ),
    Lighten large fills( 1 ),
    Variables( X( :sex ) ),
    Elements( Pie( X, Legend( 3 ) ) )
);

Code Explanation:

1. Open data table;
2. Create first Graph Builder.
3. Set size to 494x310.
4. Hide control panel.
5. Disable lighten large fills.
6. Set X variable to sex.
7. Add pie element with legend.
8. Create second Graph Builder.
9. Set size to 494x310.
10. Hide control panel.
11. Enable lighten large fills.
12. Set X variable to sex.
13. Add pie element with legend.

Example 1990

Summary: Creates a mosaic chart with sex as the X-axis variable, utilizing Graph Builder to visualize data from an open JMP data table.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 469, 339 ),
    Show Control Panel( 0 ),
    Lighten large fills( 0 ),
    Variables( X( :sex ) ),
    Elements( Mosaic( X, Legend( 3 ) ) )
);

Code Explanation:

1. Open data table;
2. Create new Graph Builder window.
3. Set window size.
4. Hide control panel.
5. Disable lighten large fills.
6. Set X variable to sex.
7. Add mosaic element.
8. Assign legend to third position.

Example 1991

Summary: Creates multiple graph types, including Treemaps and Pie charts, to visualize data with nested factors using Graph Builder.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 455, 310 ),
    Show Control Panel( 0 ),
    Lighten large fills( 0 ),
    Variables( X( :sex ) ),
    Elements( Treemap( X, Legend( 3 ) ) )
);
Graph Builder(
    Size( 455, 310 ),
    Show Control Panel( 0 ),
    Lighten large fills( 1 ),
    Variables( X( :sex ) ),
    Elements( Treemap( X, Legend( 3 ) ) )
);
Open("data_table.jmp");
Graph Builder(
    Size( 494, 310 ),
    Show Control Panel( 0 ),
    Lighten large fills( 0 ),
    Variables( X( :sex ) ),
    Elements( Pie( X, Legend( 3 ) ) )
);
Graph Builder(
    Size( 494, 310 ),
    Show Control Panel( 0 ),
    Lighten large fills( 1 ),
    Variables( X( :sex ) ),
    Elements( Pie( X, Legend( 3 ) ) )
);
Open("data_table.jmp");
Graph Builder(
    Size( 469, 339 ),
    Show Control Panel( 0 ),
    Lighten large fills( 0 ),
    Variables( X( :sex ) ),
    Elements( Mosaic( X, Legend( 3 ) ) )
);
Graph Builder(
    Size( 469, 339 ),
    Show Control Panel( 0 ),
    Lighten large fills( 1 ),
    Variables( X( :sex ) ),
    Elements( Mosaic( X, Legend( 3 ) ) )
);

Code Explanation:

1. Open data table;
2. Create Treemap graph without lightening.
3. Create Treemap graph with lightening.
4. Open data table;
5. Create Pie chart without lightening.
6. Create Pie chart with lightening.
7. Open data table;
8. Create Mosaic plot without lightening.
9. Create Mosaic plot with lightening.

Example 1992

Summary: Creates multiple Treemap, Pie, and Mosaic charts from a data table, with options to enable or disable large fills.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 455, 310 ),
    Show Control Panel( 0 ),
    Lighten large fills( 0 ),
    Variables( X( :sex ) ),
    Elements( Treemap( X, Legend( 3 ) ) )
);
Graph Builder(
    Size( 455, 310 ),
    Show Control Panel( 0 ),
    Lighten large fills( 1 ),
    Variables( X( :sex ) ),
    Elements( Treemap( X, Legend( 3 ) ) )
);
Open("data_table.jmp");
Graph Builder(
    Size( 494, 310 ),
    Show Control Panel( 0 ),
    Lighten large fills( 0 ),
    Variables( X( :sex ) ),
    Elements( Pie( X, Legend( 3 ) ) )
);
Graph Builder(
    Size( 494, 310 ),
    Show Control Panel( 0 ),
    Lighten large fills( 1 ),
    Variables( X( :sex ) ),
    Elements( Pie( X, Legend( 3 ) ) )
);
Open("data_table.jmp");
Graph Builder(
    Size( 469, 339 ),
    Show Control Panel( 0 ),
    Lighten large fills( 0 ),
    Variables( X( :sex ) ),
    Elements( Mosaic( X, Legend( 3 ) ) )
);

Code Explanation:

1. Open data table;
2. Create Treemap graph.
3. Disable lighten large fills.
4. Create Treemap graph.
5. Enable lighten large fills.
6. Open data table;
7. Create Pie chart.
8. Disable lighten large fills.
9. Create Pie chart.
10. Enable lighten large fills.

Example 1993

Summary: Creates a treemap visualization in Graph Builder, mapping sex and age to display weight distribution.

Code:

Open("data_table.jmp");
Graph Builder(
    show control panel( 0 ),
    Variables( X( :sex ), X( :age, Position( 1 ) ), Color( :weight ) ),
    Elements( Treemap( X( 1 ), X( 2 ), Legend( 1 ), Color Label( 1 ), Size Label( 1 ) ) )
);

Code Explanation:

1. Open data table;
2. Create new Graph Builder window.
3. Hide control panel.
4. Set X variable to sex.
5. Set second X variable to age.
6. Set color variable to weight.
7. Add Treemap element.
8. Map first X to Treemap X.
9. Map second X to Treemap Y.
10. Display legend for Treemap.

Example 1994

Summary: Creates a Treemap visualization with nested factors using Graph Builder, displaying Total Fatal Injuries and Total Serious Injuries.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 408, 267 ),
    Show Control Panel( 0 ),
    Variables(
        X( :Accident Number, Combine( "Parallel Merged" ) ),
        X( :Amateur Built, Position( 1 ), Combine( "Parallel Merged" ) ),
        Y( :Total Fatal Injuries ),
        Y( :Total Serious Injuries, Position( 1 ) )
    ),
    Elements( Treemap( X( 1 ), X( 2 ), Y( 1 ), Y( 2 ), Legend( 4 ) ) )
);

Code Explanation:

1. Open data table;
2. Create Graph Builder window.
3. Set window size.
4. Hide control panel.
5. Define X variables.
6. Define Y variables.
7. Add Treemap element.
8. Assign X1 to first X variable.
9. Assign X2 to second X variable.
10. Assign Y1 to first Y variable.
11. Assign Y2 to second Y variable.

Example 1995

Summary: Creates a treemap visualization with nested factors using Graph Builder, displaying standard deviation charts and hiding the control panel.

Code:

Open("data_table.jmp");
obj = Graph Builder(
    show control panel( 0 ),
    Variables( X( :sex ), X( :age, Position( 1 ) ), Color( :weight ) ),
    Elements( Treemap( X( 1 ), X( 2 ), Labels( "Auto Size" ), Max Label Size( 10 ) ) )
);
obj << save journal( "$TEMP/S1240876.jrn" );

Code Explanation:

1. Open data table.
2. Create Graph Builder object.
3. Hide control panel.
4. Set X variables: sex, age.
5. Set color variable: weight.
6. Add Treemap element.
7. Configure Treemap labels.
8. Set maximum label size.
9. Save journal to temp directory.

Example 1996

Summary: Creates a treemap visualization with nested factors using Graph Builder, configuring X variables for sex and age, and color variable for weight.

Code:

Open("data_table.jmp");
obj = Graph Builder(
    show control panel( 0 ),
    Variables( X( :sex ), X( :age, Position( 1 ) ), Color( :weight ) ),
    Elements( Treemap( X( 1 ), X( 2 ), Labels( "Auto Size" ), Max Label Size( 10 ) ) )
);
obj << save journal( "$TEMP/S1240876.jrn" );
Open( "$TEMP/S1240876.jrn" );

Code Explanation:

1. Open data table.
2. Create Graph Builder object.
3. Hide control panel.
4. Set X variables: sex, age.
5. Set color variable: weight.
6. Add Treemap element.
7. Configure Treemap labels.
8. Save journal to temp.
9. Open saved journal.

Example 1997

Summary: Creates a Treemap visualization with nested factors using Graph Builder, configuring X positions and enabling legend.

Code:

Open("data_table.jmp");
obj = Graph Builder(
    show control panel( 0 ),
    Variables( X( :sex ), X( :age, Position( 1 ) ), Color( :weight ) ),
    Elements( Treemap( X( 1 ), X( 2 ), Legend( 1 ), Tile Label( 0 ), Max Label Size( 4.037 ), Label Threshold( 70.64 ) ) )
);
obj << save journal( "$TEMP/S1245783.jrn" );

Code Explanation:

1. Open data table;
2. Create Graph Builder object.
3. Hide control panel.
4. Set X variables: sex, age.
5. Set color variable: weight.
6. Add Treemap element.
7. Configure Treemap X positions.
8. Enable legend.
9. Disable tile labels.
10. Save journal to temp.

Example 1998

Summary: Creates a Treemap visualization with nested factors using Graph Builder, displaying standard deviation charts and hiding the control panel.

Code:

dt = Open("data_table.jmp");
obj = Graph Builder(
    show control panel( 0 ),
    Variables( X( :sex ), X( :age, Position( 1 ) ), Color( :weight ) ),
    Elements( Treemap( X( 1 ), X( 2 ), Legend( 1 ), Tile Label( 0 ), Max Label Size( 4.037 ), Label Threshold( 70.64 ) ) )
);
obj << save journal( "$TEMP/S1245783.jrn" );
Open( "$TEMP/S1245783.jrn" );

Code Explanation:

1. Open data table.
2. Create Graph Builder object.
3. Hide control panel.
4. Set X variables: sex, age.
5. Set color variable: weight.
6. Add Treemap element.
7. Configure Treemap settings.
8. Save journal to temp directory.
9. Open saved journal.

Example 1999

Summary: Creates a Treemap visualization with nested factors, utilizing Graph Builder to display sex, age, and weight data.

Code:

Open("data_table.jmp");
obj = Graph Builder(
    Size( 495, 440 ),
    Show Control Panel( 0 ),
    Variables( X( :sex ), X( :age, Position( 1 ) ), Color( :weight ) ),
    Elements( Treemap( X( 1 ), X( 2 ), Labels( "None" ) ) )
);
obj << redo analysis;

Code Explanation:

1. Open data table;
2. Create Graph Builder object.
3. Set window size.
4. Hide control panel.
5. Assign variables: sex, age, weight.
6. Add Treemap element.
7. Disable labels on Treemap.
8. Redo analysis.

Example 2000

Summary: Creates a Treemap visualization using Graph Builder to display nested factors in a data table, with standard deviation charts.

Code:

Open("data_table.jmp");
obj = Graph Builder(
    Size( 495, 440 ),
    Show Control Panel( 0 ),
    Variables( X( :sex ), X( :age, Position( 1 ) ), Color( :weight ) ),
    Elements( Treemap( X( 1 ), X( 2 ), Labels( "None" ) ) )
);
obj << redo analysis;
obj << Close Window();

Code Explanation:

1. Open data table.
2. Create Graph Builder object.
3. Set graph size.
4. Hide control panel.
5. Define X and color variables.
6. Add Treemap element.
7. Set labels to none.
8. Redo analysis.
9. Close graph window.

Example 2001

Summary: Creates a treemap visualization in Graph Builder, using sex and age as nested factors to display weight data.

Code:

Open("data_table.jmp");
Graph Builder(
    show control panel( 0 ),
    Variables( X( :sex ), X( :age, Position( 1 ) ), Color( :weight ) ),
    Elements( Treemap( X( 1 ), X( 2 ), Legend( 1 ), Tile Label( 0 ), Max Label Size( 4.037 ), Label Threshold( 70.64 ) ) )
);

Code Explanation:

1. Open data table;
2. Launch Graph Builder.
3. Hide control panel.
4. Set X variable: sex.
5. Set X variable: age.
6. Set color variable: weight.
7. Add Treemap element.
8. Configure Treemap axes.
9. Disable tile labels.
10. Set max label size.

Example 2002

Summary: Creates a Treemap visualization using Graph Builder to display nested factors with operator and part configurations, along with standard deviation charts.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 676, 678 ),
    Show Control Panel( 0 ),
    Variables( X( :State ), X( :city, Position( 1 ) ), Color( :Region ), Size( :POP ) ),
    Elements( Treemap( X( 1 ), X( 2 ), Legend( 9 ), Layout( "Squarify" ) ) )
);

Code Explanation:

1. Open data table.
2. Launch Graph Builder.
3. Set window size.
4. Hide control panel.
5. Define X variables.
6. Define additional X variable.
7. Set color variable.
8. Set size variable.
9. Add Treemap element.
10. Configure Treemap layout.

Example 2003

Summary: Creates a treemap visualization to display regional population data, using Graph Builder and specifying X variables for Region and city.

Code:

Open("data_table.jmp");
Graph Builder(
    show control panel( 0 ),
    Variables( X( :Region ), X( :city, Position( 1 ) ), Size( :POP ) ),
    Elements( Treemap( X( 1 ), X( 2 ), Solid Color( 1 ), Classic Style( 1 ) ) )
);

Code Explanation:

1. Open data table;
2. Launch Graph Builder.
3. Hide control panel.
4. Set X variables: Region, city.
5. Set size variable: POP.
6. Create Treemap element.
7. Assign X1 to Region.
8. Assign X2 to city.
9. Use solid color.
10. Apply classic style.

Example 2004

Summary: Creates a treemap visualization with nested factors using Graph Builder, displaying standard deviation charts and formatting the Y-axis title.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 612, 432 ),
    Show Control Panel( 0 ),
    Variables( X( :sex ), X( :age, Position( 1 ) ), Color( :height ), Size( :height ) ),
    Elements( Treemap( X( 1 ), X( 2 ), Legend( 12 ), Summary Statistic( "% of Total" ) ) ),
    SendToReport(
        Dispatch( {}, "Y title", TextEditBox, {Set Wrap( 2 )} ),
        Dispatch( {}, "Graph Builder", FrameBox,
            {DispatchSeg( TreeMapSeg( 1 ), Frame Size( 601, 384 ) ), Add Pin Annotation(
                Seg( TreeMapSeg( 1 ) ),
                Index( 8 ),
                Index Row( 20 ),
                UniqueID( 703552568 ),
                FoundPt( {299, 260} ),
                Origin( {321.464226289517, 182.291666666667} )
            )}
        )
    )
);

Code Explanation:

1. Open data table.
2. Launch Graph Builder.
3. Set window size.
4. Hide control panel.
5. Assign variables to axes.
6. Create treemap element.
7. Set summary statistic to "% of Total".
8. Format Y axis title.
9. Adjust treemap frame size.
10. Add pin annotation.

Example 2005

Summary: Creates a treemap visualization with nested factors using Graph Builder, displaying Arrival Delay as a function of Distance and wrapping by Airline.

Code:

Open("data_table.jmp") << Graph Builder(
    Show Control Panel( 0 ),
    Variables( X( :Distance ), Y( :Arrival Delay ), Wrap( :Airline ) ),
    Elements( Treemap( X, Y, Legend( 7 ) ) ),
    Column Switcher( :Airline, {:Month, :Day of Month, :Day of Week, :Airline} )
);

Code Explanation:

1. Open data table;
2. Launch Graph Builder.
3. Hide control panel.
4. Set X variable: Distance.
5. Set Y variable: Arrival Delay.
6. Wrap by Airline.
7. Add Treemap element.
8. Use legend position 7.
9. Enable column switcher.
10. Set switcher options for Airline.

Example 2006

Summary: Creates a Treemap visualization with nested factors using Graph Builder, displaying standard deviation charts for analysis.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 463, 224 ),
    Show Control Panel( 0 ),
    Show Legend( 1 ),
    Variables( X( :weight ), Y( :sex ) ),
    Elements( Treemap( X, Y, Legend( 6 ), Category Value( 0 ) ) )
);

Code Explanation:

1. Open data table;
2. Launch Graph Builder.
3. Set window size.
4. Hide control panel.
5. Show legend.
6. Assign variables to axes.
7. Add Treemap element.
8. Configure Treemap settings.
9. Set category value.
10. Display graph.

Example 2007

Summary: Creates a treemap visualization in Graph Builder, filtering data for male sex and adjusting frame size.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 411, 330 ),
    Show Control Panel( 0 ),
    Show Legend( 0 ),
    Variables( X( :age ), Y( :height ) ),
    Elements( Treemap( X, Y, Legend( 24 ) ) ),
    Local Data Filter( Mode( Include( 0 ) ), Add Filter( columns( :sex ), Where( :sex == "M" ) ) ),
    SendToReport( Dispatch( {}, "Graph Builder", FrameBox, {DispatchSeg( TreeMapSeg( 1 ), Frame Size( 375, 279 ) )} ) )
);

Code Explanation:

1. Open data table;
2. Launch Graph Builder.
3. Set window size.
4. Hide control panel.
5. Hide legend.
6. Define X and Y variables.
7. Add Treemap element.
8. Apply local data filter.
9. Filter for male sex.
10. Adjust treemap frame size.

Example 2008

Summary: Creates a variability chart with nested factors using Graph Builder, displaying standard deviation charts and configuring various elements such as points and smoother.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 707, 479 ),
    Show Control Panel( 0 ),
    Legend Position( "Inside Bottom Left" ),
    Fit to Window( "Off" ),
    Variables( X( :height ), Y( :weight ), Group X( :sex ), Overlay( :age ), Color( :name ) ),
    Elements( Points( X, Y, Legend( 16 ) ), Smoother( X, Y, Legend( 17 ) ) )
);

Code Explanation:

1. Open data table;
2. Launch Graph Builder.
3. Set window size.
4. Hide control panel.
5. Position legend inside bottom left.
6. Disable fit to window.
7. Define X, Y, group, overlay, color variables.
8. Add points element with legend.
9. Add smoother element with legend.
10. Display graph.

Example 2009

Summary: Creates a variability chart with nested factors using Graph Builder, configuring the plot to display standard deviation charts and modifying legend properties.

Code:

dt = Open("data_table.jmp");
Graph Builder(
    Size( 469, 398 ),
    Show Control Panel( 0 ),
    Variables( X( :weight ), Y( :height ), Overlay( :sex ) ),
    Elements( Points( X, Y, Legend( 3 ) ) ),
    SendToReport( Dispatch( {}, "400", ScaleBox, {Legend Model( 3, Properties( 1, {Marker( "M" )}, Item ID( "M", 1 ) ) )} ) )
);
ps = Get Preferences();
Preferences( Fonts( English( Marker Font( "Segoe UI", 22 ), ) ) );

Code Explanation:

1. Open data table.
2. Create Graph Builder window.
3. Set window size.
4. Hide control panel.
5. Assign variables to axes.
6. Add overlay variable.
7. Plot points element.
8. Modify legend properties.
9. Save current preferences.
10. Change marker font settings.

Example 2010

Summary: Creates a variability chart with nested factors using Graph Builder, displaying standard deviation charts and customizing legend properties.

Code:

dt = Open("data_table.jmp");
Graph Builder(
    Size( 469, 398 ),
    Show Control Panel( 0 ),
    Variables( X( :weight ), Y( :height ), Overlay( :sex ) ),
    Elements( Points( X, Y, Legend( 3 ) ) ),
    SendToReport( Dispatch( {}, "400", ScaleBox, {Legend Model( 3, Properties( 1, {Marker( "M" )}, Item ID( "M", 1 ) ) )} ) )
);

Code Explanation:

1. Open data table;
2. Launch Graph Builder.
3. Set window size.
4. Hide control panel.
5. Assign variables: X, Y, Overlay.
6. Add points element.
7. Send report message.
8. Modify legend properties.
9. Set marker type to "M".
10. Apply changes to item ID.

Example 2011

Summary: Creates a variability chart with nested factors using operator and part configurations, displaying standard deviation charts in JMP.

Code:

dt = Open("data_table.jmp");
Graph Builder(
    Size( 469, 398 ),
    Show Control Panel( 0 ),
    Variables( X( :weight ), Y( :height ), Overlay( :sex ) ),
    Elements( Points( X, Y, Legend( 3 ) ) ),
    SendToReport( Dispatch( {}, "400", ScaleBox, {Legend Model( 3, Properties( 1, {Marker( "M" )}, Item ID( "M", 1 ) ) )} ) )
);
ps = Get Preferences();
Preferences( Fonts( English( Marker Font( "Segoe UI", 22 ), ) ) );
dt = Open("data_table.jmp");
Graph Builder(
    Size( 469, 398 ),
    Show Control Panel( 0 ),
    Variables( X( :weight ), Y( :height ), Overlay( :sex ) ),
    Elements( Points( X, Y, Legend( 3 ) ) ),
    SendToReport( Dispatch( {}, "400", ScaleBox, {Legend Model( 3, Properties( 1, {Marker( "M" )}, Item ID( "M", 1 ) ) )} ) )
);

Code Explanation:

1. Open data table.
2. Create Graph Builder window.
3. Set graph size.
4. Hide control panel.
5. Assign variables for X, Y, and overlay.
6. Add points element with legend.
7. Customize marker in legend.
8. Save current preferences.
9. Change marker font preferences.
10. Reopen data table.
11. Repeat steps 2-7.

Example 2012

Summary: Creates a variability chart with nested factors using operator and part configurations, displaying standard deviation charts in JMP.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 1111, 364 ),
    Show Control Panel( 0 ),
    Legend Position( "Bottom" ),
    Variables( X( :"Date/Time"n ), Y( :Abrasion ), Color( :"Date/Time"n ) ),
    Elements( Points( X, Y, Legend( 44 ) ) ),
    SendToReport( Dispatch( {}, "400", LegendBox, {Set Wrap( 5 )} ) )
);

Code Explanation:

1. Open data table;
2. Launch Graph Builder.
3. Set window size.
4. Hide control panel.
5. Position legend at bottom.
6. Define X, Y, and color variables.
7. Add points element.
8. Format legend wrap to 5.

Example 2013

Summary: Creates a variability chart with nested factors using operator and part configurations, displaying standard deviation charts in Graph Builder.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 363, 283 ),
    Show Control Panel( 0 ),
    Variables( X( :Sample ), Y( :Weight ), Color( :Product ) ),
    Elements( Smoother( X, Y, Legend( 14 ) ) ),
    SendToReport(
        Dispatch( {}, "400", ScaleBox,
            {Legend Model(
                14,
                Base( 0, 0, 1, Item ID( "Smooth", 1 ) ),
                Properties( 0, {Line Color( -7954859 ), Line Width( 6 ), Fill Color( 0 )}, Item ID( "Smooth", 1 ) )
            )}
        )
    )
);

Code Explanation:

1. Open data table;
2. Create Graph Builder.
3. Set graph size.
4. Hide control panel.
5. Assign variables: Sample, Weight, Product.
6. Add smoother element.
7. Send report to Graph Builder.
8. Dispatch to legend model.
9. Set legend base properties.
10. Customize smoother line color, width, fill color.

Example 2014

Summary: Creates two variability charts with nested factors using Graph Builder, displaying standard deviation charts and customizing legend styles.

Code:

dt = Open("data_table.jmp");
gb = dt << Graph Builder(
    Show Control Panel( 0 ),
    Variables( X( :age ), Y( :height ), Overlay( :sex ) ),
    Elements( Line( X, Y, Legend( 5 ) ) ),
    SendToReport( Dispatch( {}, "400", ScaleBox, {Legend Model( 5, Properties( 0, {Line Style( "Dashed" )}, Item ID( "F", 1 ) ) )} ) )
);
gb2 = dt << Graph Builder(
    Size( 534, 456 ),
    Show Control Panel( 0 ),
    Variables( X( :height ), Y( :weight ), Overlay( :age ) ),
    Elements( Points( X, Y, Legend( 8 ) ), Smoother( X, Y, Legend( 9 ) ) ),
    SendToReport(
        Dispatch( {}, "400", ScaleBox,
            {Legend Model(
                9,
                Properties( 0, {Line Style( "Dotted" )}, Item ID( "12", 1 ) ),
                Properties( 1, {Line Style( "Dashed" )}, Item ID( "13", 1 ) ),
                Properties( 2, {Line Style( "DashDotDot" )}, Item ID( "14", 1 ) ),
                Properties( 3, {Line Style( "Long Dash Dash" )}, Item ID( "15", 1 ) ),
                Properties( 4, {Line Style( "Sparse Dot" )}, Item ID( "16", 1 ) ),
                Properties( 5, {Line Style( "Sparse Dash Dot" )}, Item ID( "17", 1 ) )
            )}
        )
    )
);

Code Explanation:

1. Open data table.
2. Create graph builder object.
3. Hide control panel.
4. Set X, Y, and overlay variables.
5. Add line element with legend.
6. Modify legend style to dashed.
7. Create second graph builder object.
8. Set size and hide control panel.
9. Set X, Y, and overlay variables.
10. Add points and smoother elements with legends.

Example 2015

Summary: Creates a variability chart with nested factors using Graph Builder, displaying standard deviation charts and adjusting legend models.

Code:

dt = Open("data_table.jmp");
obj = Graph Builder(
    Size( 534, 448 ),
    Show Control Panel( 0 ),
    Variables( X( :age ), Y( :weight ), Overlay( :sex ) ),
    Elements( Points( X, Y, Legend( 27 ) ), Line( X, Y, Legend( 28 ) ) ),
    SendToReport(
        Dispatch( {}, "400", ScaleBox, {Legend Model( 27, Base( 0, 0, 0 ), Base( 1, 0, 0 ) )} ),
        Dispatch( {}, "400", LegendBox, {Legend Position( {27, [-1, -1], 28, [0, 1]} )} )
    )
);
rpt = obj << report;
rpt << Save Journal( "$TEMP/JMP-1471.jrn" );
rpt << Close Window;

Code Explanation:

1. Open data_table data
2. Create Graph Builder object.
3. Set graph size.
4. Hide control panel.
5. Define X, Y, and overlay variables.
6. Add points and lines elements.
7. Adjust legend model base.
8. Set legend position.
9. Generate report object.
10. Save report as journal.
11. Close report window.

Example 2016

Summary: Creates a variability chart with nested factors using operator and part configurations, displaying standard deviation charts.

Code:

Open("data_table.jmp");
obj = Graph Builder(
    Size( 534, 448 ),
    Show Control Panel( 0 ),
    Variables( X( :age ), Y( :weight ), Overlay( :sex ) ),
    Elements( Points( X, Y, Legend( 27 ) ), Line( X, Y, Legend( 28 ) ) ),
    SendToReport(
        Dispatch( {}, "400", ScaleBox, {Legend Model( 27, Base( 0, 0, 0 ), Base( 1, 0, 0 ) )} ),
        Dispatch( {}, "400", LegendBox, {Legend Position( {27, [-1, -1], 28, [0, 1]} )} )
    )
);
rpt = obj << report;
rpt << Save Journal( "$TEMP/JMP-1471.jrn" );
rpt << Close Window;
Open( "$TEMP/JMP-1471.jrn" );

Code Explanation:

1. Open data table.
2. Create Graph Builder object.
3. Set graph size.
4. Hide control panel.
5. Define variables: X=age, Y=weight, Overlay=sex.
6. Add points and line elements.
7. Customize legend model.
8. Set legend position.
9. Generate report from graph.
10. Save report as journal.
11. Close the report window.
12. Open saved journal file.

Example 2017

Summary: Creates a variability chart with nested factors using operator and part configurations, displaying standard deviation charts in Graph Builder.

Code:

dt = Open("data_table.jmp");
gb = dt << Graph Builder(
    Show Control Panel( 0 ),
    Variables( X( :sex ), Y( :height ), Color( :height, Summary Statistic( "Min" ) ) ),
    Elements( Line( X, Y, Legend( 20 ) ) ),
    SendToReport(
        Dispatch( {}, "400", ScaleBox,
            {Legend Model(
                20,
                Properties(
                    0,
                    {gradient( {Scale Type( "Standard Deviation" ), Range Type( "Exact Data Range" ), Label Format( "Best", 12 )} )},
                    Item ID( "height", 1 )
                )
            )}
        )
    )
);

Code Explanation:

1. Open data table;
2. Create graph builder object.
3. Hide control panel.
4. Set X variable.
5. Set Y variable.
6. Set color variable.
7. Add line element.
8. Send report settings.
9. Adjust legend model.
10. Configure gradient properties.

Example 2018

Summary: Creates a variability chart with nested factors using Graph Builder, displaying standard deviation charts and configuring legend model properties.

Code:

dt = Open("data_table.jmp");
gb = dt << Graph Builder(
    Show Control Panel( 0 ),
    Variables( X( :sex ), Y( :height ), Color( :height, Summary Statistic( "Min" ) ) ),
    Elements( Line( X, Y, Legend( 20 ) ) ),
    SendToReport(
        Dispatch( {}, "400", ScaleBox,
            {Legend Model(
                20,
                Properties(
                    0,
                    {gradient( {Scale Type( "Standard Deviation" ), Range Type( "Exact Data Range" ), Label Format( "Best", 12 )} )},
                    Item ID( "height", 1 )
                )
            )}
        )
    )
);
gb << Add Variable( {:age, Role( "Overlay" )} );

Code Explanation:

1. Open data table.
2. Create Graph Builder object.
3. Hide control panel.
4. Set X variable to sex.
5. Set Y variable to height.
6. Color by height's minimum summary statistic.
7. Add line element with legend.
8. Configure legend model properties.
9. Set scale type to standard deviation.
10. Add age as overlay variable.

Example 2019

Summary: Creates a variability chart with nested factors using Graph Builder, displaying standard deviation charts for height and weight variables.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 528, 448 ),
    Show Control Panel( 0 ),
    Variables( X( :height ), Y( :weight ), Y( :weight ) ),
    Elements(
        Position( 1, 1 ),
        Bar( X, Y, Legend( 11 ), Summary Statistic( "Std Err" ) ),
        Line( X, Y, Legend( 12 ), Summary Statistic( "Std Err" ) )
    ),
    Elements(
        Position( 1, 2 ),
        Points( X, Y, Legend( 6 ), Summary Statistic( "Std Err" ) ),
        Area( X, Y, Legend( 7 ), Summary Statistic( "Std Err" ) )
    ),
    SendToReport( Dispatch( {}, "400", LegendBox, {Legend Position( {11, [1], 12, [2], 6, [0], 7, [-3]} )} ) )
);

Code Explanation:

1. Open data table;
2. Create Graph Builder window.
3. Set window size.
4. Hide control panel.
5. Assign variables: height for X, weight for Y.
6. Add bar element with standard error.
7. Add line element with standard error.
8. Add points element with standard error.
9. Add area element with standard error.
10. Arrange legend items in specific order.

Example 2020

Summary: Creates a variability chart with nested factors using Graph Builder, displaying standard deviation charts for two subplots.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 471, 436 ),
    Show Control Panel( 0 ),
    Variables( X( :sex ), X( :age, Position( 1 ) ), Y( :height ), Y( :weight ), Group X( :sex ), Color( :age ) ),
    Elements(
        Position( 1, 1 ),
        Bar( X( 1 ), X( 2 ), Y, Legend( 14 ), Summary Statistic( "% of Total" ) ),
        Points( X( 1 ), X( 2 ), Y, Legend( 15 ), Summary Statistic( "% of Total" ) ),
        Line( X( 1 ), X( 2 ), Y, Legend( 16 ), Summary Statistic( "% of Total" ) )
    ),
    Elements(
        Position( 1, 2 ),
        Bar( X( 1 ), X( 2 ), Y, Legend( 11 ), Summary Statistic( "% of Total" ) ),
        Points( X( 1 ), X( 2 ), Y, Legend( 12 ), Summary Statistic( "% of Total" ) ),
        Line( X( 1 ), X( 2 ), Y, Legend( 13 ), Summary Statistic( "% of Total" ) )
    )
);

Code Explanation:

1. Open data_table data
2. Create Graph Builder window.
3. Set graph size to 471x436 pixels.
4. Hide control panel.
5. Define X variables: sex, age.
6. Define Y variables: height, weight.
7. Group by sex.
8. Color by age.
9. Add bar, points, line elements for first subplot.
10. Add bar, points, line elements for second subplot.

Example 2021

Summary: Creates a graph builder window with variables X=name, Y=height, and Color=age, displaying points with legend at bottom.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 522, 452 ),
    Show Control Panel( 0 ),
    Legend Position( "Bottom" ),
    Variables( X( :name ), Y( :height ), Color( :age ) ),
    Elements( Points( X, Y, Legend( 6 ) ) )
);

Code Explanation:

1. Open data table;
2. Create Graph Builder window.
3. Set graph size to 522x452.
4. Hide control panel.
5. Place legend at bottom.
6. Assign variables: X=name, Y=height, Color=age.
7. Add points element.
8. Assign legend position for points.

Example 2022

Summary: Creates a variability chart with nested factors using Graph Builder, displaying standard deviation charts and color-coded by series.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 664, 447 ),
    Show Control Panel( 0 ),
    Legend Position( "Bottom" ),
    Variables( X( :Series, Order By( :Price, Descending, Order Statistic( "Mean" ) ) ), Y( :Price ), Color( :Series ) ),
    Elements( Bar( X, Y, Legend( 6 ) ) )
);

Code Explanation:

1. Open data table;
2. Create Graph Builder window.
3. Set size to 664x447.
4. Hide control panel.
5. Place legend at bottom.
6. Set X variable as Series.
7. Order Series by Price descending.
8. Use mean for ordering statistic.
9. Set Y variable as Price.
10. Color by Series.

Example 2023

Summary: Creates a variability chart with nested factors using Graph Builder, displaying standard deviation charts and utilizing color to represent the percentage of each factor.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 502, 423 ),
    Show Control Panel( 0 ),
    Variables( Y( :weight ), Overlay( :sex ), Color( :weight, Summary Statistic( "% of Factor" ) ) ),
    Elements( Bar( Y, Legend( 12 ), Summary Statistic( "% of Factor" ) ) )
);

Code Explanation:

1. Open data table.
2. Launch Graph Builder.
3. Set window size.
4. Hide control panel.
5. Define Y variable.
6. Define overlay variable.
7. Define color variable.
8. Set summary statistic.
9. Add bar element.
10. Assign legend.

Example 2024

Summary: Creates two Graph Builder windows to visualize nested factors using operator and part configurations, displaying standard deviation charts for weight summary statistics.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 502, 423 ),
    Show Control Panel( 0 ),
    Variables( Y( :weight ), Overlay( :sex ), Color( :weight, Summary Statistic( "% of Factor" ) ) ),
    Elements( Bar( Y, Legend( 12 ), Summary Statistic( "% of Factor" ) ) )
);
Graph Builder(
    Size( 502, 423 ),
    Show Control Panel( 0 ),
    Variables( Y( :weight ), Overlay( :sex ), Size( :weight, Summary Statistic( "% of Factor" ) ) ),
    Elements( Points( Y, Legend( 12 ), Summary Statistic( "% of Factor" ) ) )
);

Code Explanation:

1. Open data table;
2. Create first Graph Builder window.
3. Set window size.
4. Hide control panel.
5. Define Y variable.
6. Overlay by sex.
7. Color by weight summary statistic.
8. Add bar element.
9. Create second Graph Builder window.
10. Define Y, overlay, and size variables.
11. Add points element.

Example 2025

Summary: Creates a variability chart with nested factors using Graph Builder, displaying standard deviation charts and configuring elements by age.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 484, 334 ),
    Show Control Panel( 0 ),
    Variables( X( :sex ), X( :age, Position( 1 ) ), Y( :weight ), Color( :age ) ),
    Elements(
        Area( X( 1 ), X( 2 ), Y, Legend( 17 ), Summary Statistic( "Third Quartile" ) ),
        Bar( X( 1 ), X( 2 ), Y, Legend( 14 ), Summary Statistic( "Third Quartile" ) ),
        Points( X( 1 ), X( 2 ), Y, Legend( 15 ), Summary Statistic( "Third Quartile" ) )
    ),
    SendToReport(
        Dispatch( {}, "400", LegendBox,
            {Legend Position( {17, [6, 7, 8, 9, 10, 11, 12], 14, [0, 1, 2, 3, 4, 5], 15, [-3, -3, -3, -3, -3, -3]} )}
        )
    )
);

Code Explanation:

1. Open data table;
2. Create Graph Builder window.
3. Set graph size to 484x334.
4. Hide control panel.
5. Define X variables: sex, age.
6. Define Y variable: weight.
7. Color elements by age.
8. Add area element for third quartile.
9. Add bar element for third quartile.
10. Add points element for third quartile.

Example 2026

Summary: Creates a graph builder with nested factors, utilizing Graph Builder and Find Seg to generate a variability chart.

Code:

Open("data_table.jmp");
gb = Graph Builder( Show Control Panel( 0 ), Variables( X( :X ), Y( :Y ), Color( :Z ) ), Elements( Points( X, Y ) ) );
frame = (gb << Report)[FrameBox( 1 )];
seg = frame << Find Seg( Marker Seg( 1 ) );
seg << Set Gradient( Color Theme( "Viridis" ) );
Names Default To Here( 1 );

Code Explanation:

1. Open data table.
2. Create Graph Builder object.
3. Hide control panel.
4. Define X, Y, Color variables.
5. Add points element.
6. Access first frame box.
7. Find segment for marker.
8. Set gradient color theme.
9. Reset names to default.
10. Save script with specified name.

Example 2027

Summary: Creates a contour plot with nested factors using Graph Builder, hiding the control panel and setting X, Y, and Color variables.

Code:

Open("data_table.jmp");
gb = Graph Builder( Show Control Panel( 0 ), Variables( X( :X ), Y( :Y ), Color( :Z ) ), Elements( Contour( X, Y ) ) );
frame = (gb << Report)[FrameBox( 1 )];
seg = frame << Find Seg( Contour Seg( 1 ) );

Code Explanation:

1. Open data table.
2. Create Graph Builder object.
3. Hide control panel.
4. Set X, Y, Color variables.
5. Add contour element.
6. Access first frame box.
7. Find contour segment.

Example 2028

Summary: Creates two variability charts with nested factors using Graph Builder and displays standard deviation charts, utilizing operator and part configurations.

Code:

Open("data_table.jmp");
Names Default To Here( 1 );
Open("data_table.jmp");
gb = Graph Builder( Show Control Panel( 0 ), Variables( X( :X ), Y( :Y ), Color( :Z ) ), Elements( Points( X, Y ) ) );
frame = (gb << Report)[FrameBox( 1 )];
seg = frame << Find Seg( Marker Seg( 1 ) );
seg << Set Gradient( Color Theme( "Viridis" ) );
Names Default To Here( 1 );
Open("data_table.jmp");
gb = Graph Builder( Show Control Panel( 0 ), Variables( X( :X ), Y( :Y ), Color( :Z ) ), Elements( Contour( X, Y ) ) );
frame = (gb << Report)[FrameBox( 1 )];
seg = frame << Find Seg( Contour Seg( 1 ) );
seg << Set Gradient( Color Theme( "Viridis" ) );

Code Explanation:

1. Open data table;
2. Set default names scope.
3. Open data table;
4. Create Graph Builder with points.
5. Access first frame box.
6. Find marker segment.
7. Set gradient color theme.
8. Set default names scope again.
9. Open data table;
10. Create Graph Builder with contour.

Example 2029

Summary: Creates two variability charts with nested factors using Graph Builder and displays standard deviation charts.

Code:

Open("data_table.jmp");
Names Default To Here( 1 );
Open("data_table.jmp");
gb = Graph Builder( Show Control Panel( 0 ), Variables( X( :X ), Y( :Y ), Color( :Z ) ), Elements( Points( X, Y ) ) );
frame = (gb << Report)[FrameBox( 1 )];
seg = frame << Find Seg( Marker Seg( 1 ) );
seg << Set Gradient( Color Theme( "Viridis" ) );
Names Default To Here( 1 );
Open("data_table.jmp");
gb = Graph Builder( Show Control Panel( 0 ), Variables( X( :X ), Y( :Y ), Color( :Z ) ), Elements( Contour( X, Y ) ) );
frame = (gb << Report)[FrameBox( 1 )];
seg = frame << Find Seg( Contour Seg( 1 ) );

Code Explanation:

1. Open data_table data
2. Set default names location.
3. Open data_table data
4. Create graph builder with points.
5. Access first frame box.
6. Find marker segment.
7. Set gradient color theme.
8. Set default names location again.
9. Open Little Pond data again.
10. Create graph builder with contour.

Example 2030

Summary: Creates a variability chart with nested factors using Graph Builder, displaying standard deviation charts and customizing legend properties.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 500, 454 ),
    Show Control Panel( 0 ),
    Variables( X( :Birth Year ), Color( :Salary Group ) ),
    Elements( Points( X, Legend( 3 ) ) ),
    SendToReport(
        Dispatch( {}, "400", ScaleBox,
            {Legend Model( 3, Properties( 0, {gradient( {Scale Type( "Standard Deviation" )} )}, Item ID( "Salary Group", 1 ) ) )}
        )
    )
);

Code Explanation:

1. Open data table;
2. Create Graph Builder window.
3. Set graph size.
4. Hide control panel.
5. Assign variables: X axis, Color.
6. Add points element.
7. Customize legend properties.
8. Apply gradient color scale.
9. Use standard deviation for scaling.
10. Display graph.

Example 2031

Summary: Creates a graph builder with nested factors using operator and part configurations, displaying standard deviation charts.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 526, 434 ),
    Show Control Panel( 0 ),
    Variables( X( :X ), Y( :Y ), Color( :Z ) ),
    Elements( Points( X, Y, Legend( 1 ) ) ),
    SendToReport(
        Dispatch( {}, "400", ScaleBox, {Legend Model( 1, Properties( 0, {gradient( {Scale Values( [-10 12] )} )}, Item ID( "Z", 1 ) ) )} )
    )
);

Code Explanation:

1. Open data table;
2. Create Graph Builder window.
3. Set window size.
4. Hide control panel.
5. Define X, Y, Color variables.
6. Add points element.
7. Customize legend.
8. Set gradient scale.
9. Apply gradient to Z variable.
10. Display graph.

Example 2032

Summary: Creates a variability chart with nested factors using Graph Builder, displaying standard deviation charts and configuring legend settings.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 480, 515 ),
    Show Control Panel( 0 ),
    Categorical Color Theme( "Blue to Green to Red" ),
    Variables( X( :Name ), Y( :Latitude ), Overlay( :Name ) ),
    Elements( Points( X, Y, Legend( 4 ) ) )
);

Code Explanation:

1. Open data file.
2. Launch Graph Builder.
3. Set window size.
4. Hide control panel.
5. Apply color theme.
6. Define X variable.
7. Define Y variable.
8. Set overlay variable.
9. Add points element.
10. Configure legend.

Example 2033

Summary: Creates a variability chart with nested factors using Graph Builder, displaying standard deviation charts and overlaying variables.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 421, 514 ),
    Show Control Panel( 0 ),
    Variables( X( :height ), Y( :sex ), Y( :age, Position( 1 ) ), Overlay( :name ) ),
    Elements( Line( X, Y( 1 ), Y( 2 ), Legend( 11 ) ), Points( X, Y( 1 ), Y( 2 ), Legend( 12 ) ) )
);

Code Explanation:

1. Open data table;
2. Create Graph Builder window.
3. Set window size.
4. Hide control panel.
5. Define X variable.
6. Define first Y variable.
7. Define second Y variable.
8. Set overlay variable.
9. Add line element.
10. Add points element.

Example 2034

Summary: Creates a variability chart with nested factors using operator and part configurations, displaying standard deviation charts.

Code:

Open("data_table.jmp");

Graph Builder(
    Size( 528, 494 ),
    Show Control Panel( 0 ),
    Variables( X( :Volume ), Y( :Open ), Y( :Close, Position( 1 ) ), Size( :Volume ) ),
    Elements( Points( X, Y( 1 ), Y( 2 ), Legend( 20 ) ) )
);

Code Explanation:

1. Open data table;
2. Create Graph Builder window.
3. Set window size to 528x494.
4. Hide control panel.
5. Assign Volume to X-axis.
6. Assign Open to first Y-axis.
7. Assign Close to second Y-axis.
8. Set Close Y-axis position to 1.
9. Use Volume for point size.
10. Add points element with two Y-axes and legend.

Example 2035

Summary: Creates a variability chart with nested factors using operator and part configurations, displaying standard deviation charts in JMP.

Code:

Open("data_table.jmp");

Graph Builder(
    Size( 480, 355 ),
    Show Control Panel( 0 ),
    Variables( X( :age ), Y( :weight ), Color( :age ) ),
    Elements( Points( X, Y, Legend( 3 ), Summary Statistic( "Mean" ) ) ),
    SendToReport(
        Dispatch( {}, "400", ScaleBox,
            {Legend Model(
                3,
                Properties( 0, {Marker Size( 20 )}, Item ID( "12", 1 ) ),
                Properties( -1, {Marker Size( 8 )}, Item ID( "Mean", 1 ) )
            )}
        ),
        Dispatch( {}, "400", LegendBox, {Legend Position( {3, [0, -1, -1, -1, -1, -1]} )} )
    )
);

Code Explanation:

1. Open data table;
2. Create Graph Builder window.
3. Set graph size to 480x355.
4. Hide control panel.
5. Assign variables: X=age, Y=weight, Color=age.
6. Add points element with mean summary statistic.
7. Customize legend properties for specific items.
8. Adjust marker sizes for legend items.
9. Position legend on graph.
10. Finalize report settings.

Example 2036

Summary: Creates a heatmap to visualize relationships between height and weight, with color-coded by height, using Graph Builder in JMP.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 522, 448 ),
    Show Control Panel( 0 ),
    Variables( X( :height ), Y( :weight ), Color( :height ) ),
    Elements( Heatmap( X, Y, Legend( 6 ) ) ),
    SendToReport(
        Dispatch( {}, "400", ScaleBox,
            {Legend Model(
                6,
                Properties( 0, {gradient( {Horizontal( 1 )} ), Fill Pattern( "left slant heavy" )}, Item ID( "height", 1 ) )
            )}
        )
    )
);

Code Explanation:

1. Open data table;
2. Create Graph Builder window.
3. Set window size.
4. Hide control panel.
5. Assign variables: X, Y, Color.
6. Add Heatmap element.
7. Configure legend properties.
8. Set gradient orientation.
9. Apply fill pattern.
10. Display report.

Example 2037

Summary: Creates a variability chart with nested factors using operator and part configurations, displaying standard deviation charts.

Code:

dt = Open("data_table.jmp");
dt << select rows( [1] );
Graph Builder(
    Show Control Panel( 0 ),
    Variables( X( :age ), Y( :height ), Overlay( :sex ) ),
    Elements( Line( X, Y, Legend( 3 ), Row order( 0 ), Summary Statistic( "Mean" ) ), Points( X, Y, Legend( 4 ), Jitter( 1 ) ) ),
    SendToReport(
        Dispatch( {}, "400", ScaleBox,
            {Legend Model(
                4,
                Base( 0, 0, 0 ),
                Base( 1, 0, 1 ),
                Properties( 0, {Marker( "Plus" )} ),
                Properties( 1, {Marker( "Square" )} )
            )}
        )
    )
);
Current Report() << save journal( "$TEMP\JMP-8556.jrn" );

Code Explanation:

1. Open data table;
2. Select first row.
3. Create Graph Builder object.
4. Hide control panel.
5. Set X variable: age.
6. Set Y variable: height.
7. Set overlay variable: sex.
8. Add line element with mean summary.
9. Add points element with jitter.
10. Customize legend markers.
11. Save report as journal.

Example 2038

Summary: Creates a variability chart with nested factors using Graph Builder, displaying standard deviation charts and customizing legend settings.

Code:

dt = Open("data_table.jmp");
dt << select rows( [1] );
Graph Builder(
    Show Control Panel( 0 ),
    Variables( X( :age ), Y( :height ), Overlay( :sex ) ),
    Elements( Line( X, Y, Legend( 3 ), Row order( 0 ), Summary Statistic( "Mean" ) ), Points( X, Y, Legend( 4 ), Jitter( 1 ) ) ),
    SendToReport(
        Dispatch( {}, "400", ScaleBox,
            {Legend Model(
                4,
                Base( 0, 0, 0 ),
                Base( 1, 0, 1 ),
                Properties( 0, {Marker( "Plus" )} ),
                Properties( 1, {Marker( "Square" )} )
            )}
        )
    )
);
Current Report() << save journal( "$TEMP\JMP-8556.jrn" );
Open( "$TEMP\JMP-8556.jrn" );

Code Explanation:

1. Open data table.
2. Select first row.
3. Create Graph Builder.
4. Hide control panel.
5. Set variables: X=age, Y=height, Overlay=sex.
6. Add line and point elements.
7. Customize legend for points.
8. Save report to temporary file.
9. Open saved report.

Example 2039

Summary: Creates a graph builder object with nested factors using operator and part configurations, displaying standard deviation charts.

Code:

Open("data_table.jmp");
g = Graph Builder(
    Size( 256, 190 ),
    Show Control Panel( 0 ),
    Variables( X( :height ), X( :height ), X( :weight, Position( 2 ) ) ),
    Elements( Position( 1, 1 ), Histogram( X, Legend( 2 ) ) ),
    Elements( Position( 2, 1 ), Histogram( X( 1 ), X( 2 ), Legend( 4 ) ) )
);
g << Save Journal( "$temp\test.jrn" );

Code Explanation:

1. Open data table;
2. Create graph builder object.
3. Set graph size.
4. Hide control panel.
5. Define X variables.
6. Add first histogram element.
7. Add second histogram element.
8. Save graph as journal.

Example 2040

Summary: Creates a variability chart with nested factors using Graph Builder, displaying standard deviation charts and histograms.

Code:

Open("data_table.jmp");
g = Graph Builder(
    Size( 256, 190 ),
    Show Control Panel( 0 ),
    Variables( X( :height ), X( :height ), X( :weight, Position( 2 ) ) ),
    Elements( Position( 1, 1 ), Histogram( X, Legend( 2 ) ) ),
    Elements( Position( 2, 1 ), Histogram( X( 1 ), X( 2 ), Legend( 4 ) ) )
);
g << Save Journal( "$temp\test.jrn" );
Open( "$temp\test.jrn" );

Code Explanation:

1. Open data table;
2. Create Graph Builder.
3. Set size 256x190.
4. Hide control panel.
5. Define X variables: height, height, weight.
6. Add first histogram element.
7. Add second histogram element.
8. Save journal to "$temp est.jrn".
9. Open saved journal.

Example 2041

Summary: Creates a variability chart with nested factors using Graph Builder, displaying points and smoother elements, and configuring legend wrap and max items.

Code:

Open("data_table.jmp");
Graph Builder(
    Show Control Panel( 0 ),
    Variables( X( :Infant Mortality Ranking ), Y( :Infant Mortality Rate ), Color( :Territory ) ),
    Elements( Points( X, Y, Legend( 8 ) ), Smoother( X, Y, Legend( 9 ) ) ),
    SendToReport( Dispatch( {}, "400", LegendBox, {Set Wrap( 30 ), Set Max Items( 90 )} ) )
);

Code Explanation:

1. Open data table;
2. Launch Graph Builder.
3. Hide control panel.
4. Set X variable.
5. Set Y variable.
6. Set color variable.
7. Add points element.
8. Add smoother element.
9. Configure legend wrap.
10. Set max legend items.

Example 2042

Summary: Creates a variability chart with nested factors using Graph Builder, displaying standard deviation charts for Range, Interquartile Range, and Standard Error error bars.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 528, 448 ),
    Show Control Panel( 0 ),
    Variables( X( :age ), Y( :height ), Y( :height ), Y( :height ), Overlay( :sex ) ),
    Elements( Position( 1, 1 ), Line( X, Y, Legend( 6 ), Error Bars( "Range" ) ) ),
    Elements( Position( 1, 2 ), Line( X, Y, Legend( 5 ), Error Bars( "Interquartile Range" ) ) ),
    Elements( Position( 1, 3 ), Line( X, Y, Legend( 8 ), Error Bars( "Standard Error" ) ) )
);

Code Explanation:

1. Open data table;
2. Create Graph Builder window.
3. Set graph size to 528x448.
4. Hide control panel.
5. Define X variable as age.
6. Define three Y variables as height.
7. Overlay by sex.
8. Add line element for Range error bars.
9. Add line element for Interquartile Range error bars.
10. Add line element for Standard Error error bars.

Example 2043

Summary: Creates a mosaic plot to visualize nested factors using Graph Builder, with standard deviation charts displayed for further analysis.

Code:

Open("data_table.jmp");
Graph Builder( Size( 495, 384 ), Show Control Panel( 0 ), Variables( X( :weight ) ), Elements( Mosaic( X, Legend( 2 ) ) ) );

Code Explanation:

1. Open data table;
2. Launch Graph Builder.
3. Set window size.
4. Hide control panel.
5. Assign weight variable to X.
6. Add Mosaic element.
7. Use legend for categories.
8. Set legend position.

Example 2044

Summary: Creates two graphs using Graph Builder: a mosaic plot with nested factors and a line chart with multiple overlays, showcasing interactive features for data exploration.

Code:

Open("data_table.jmp");
Graph Builder( Size( 495, 384 ), Show Control Panel( 0 ), Variables( X( :weight ) ), Elements( Mosaic( X, Legend( 2 ) ) ) );
Graph Builder(
    Size( 421, 514 ),
    Show Control Panel( 0 ),
    Variables( X( :height ), Y( :sex ), Y( :age, Position( 1 ) ), Overlay( :name ) ),
    Elements( Line( X, Y( 1 ), Y( 2 ), Legend( 11 ) ), Points( X, Y( 1 ), Y( 2 ), Legend( 12 ) ) )
);

Code Explanation:

1. Open data_table data
2. Create mosaic plot.
3. Set graph size.
4. Hide control panel.
5. Assign weight variable.
6. Add legend.
7. Create second graph.
8. Set graph size.
9. Hide control panel.
10. Assign height, sex, age variables.

Example 2045

Summary: Creates a variability chart with nested factors using Graph Builder, displaying points, smoother, line of fit, line, and area elements.

Code:

dt = Open("data_table.jmp");
gb = dt << Graph Builder(
    Size( 534, 456 ),
    Show Control Panel( 0 ),
    Variables( X( :height ), Y( :weight ) ),
    Elements(
        Points( X, Y, Legend( 2 ) ),
        Smoother( X, Y, Legend( 3 ) ),
        Line Of Fit( X, Y, Legend( 4 ) ),
        Line( X, Y, Legend( 5 ) ),
        Area( X, Y, Legend( 6 ) )
    )
);
server = gb << Get Legend Server;
items = server << Get Legend Items;

Code Explanation:

1. Open data table.
2. Create Graph Builder object.
3. Set graph size.
4. Hide control panel.
5. Define X and Y variables.
6. Add points element.
7. Add smoother element.
8. Add line of fit element.
9. Add line element.
10. Add area element.

Example 2046

Summary: Cutomizes a graph builder object with various elements, including points, smoother, line of fit, and area, to visualize data relationships.

Code:

Names Default To Here( 1 );
dt = Open("data_table.jmp");
gb = dt << Graph Builder(
    Size( 534, 456 ),
    Show Control Panel( 0 ),
    Variables( X( :height ), Y( :weight ) ),
    Elements(
        Points( X, Y, Legend( 2 ) ),
        Smoother( X, Y, Legend( 3 ) ),
        Line Of Fit( X, Y, Legend( 4 ) ),
        Line( X, Y, Legend( 5 ) ),
        Area( X, Y, Legend( 6 ) )
    )
);
server = gb << Get Legend Server;
items = server << Get Legend Items;
For Each( {item}, items,
    If(
        (item << Get Type)[1] == "Marker", item << Set Properties( {Line Color( 51 ), Marker( "Filled Down Triangle" )} ),
        (item << Get Label)[1] == "trace", item << Set Properties( {Line Color( 51 ), Line Width( 1 )} ),
        Contains( (item << Get Type)[1], "Line" ), item << Set Properties( {Line Color( 53 ), Line Width( 1 )} )
    )
);

Code Explanation:

1. Set default names scope.
2. Open data table.
3. Create graph builder object.
4. Set graph size.
5. Hide control panel.
6. Define X and Y variables.
7. Add point element.
8. Add smoother element.
9. Add line of fit element.
10. Add line element.
11. Add area element.
12. Get legend server.
13. Get legend items.
14. Iterate over legend items.
15. Check if item type is marker.
16. Set marker properties.
17. Check if item label is "trace".
18. Set trace line properties.
19. Check if item type contains "Line".
20. Set line properties.

Example 2047

Summary: Creates a variability chart with nested factors using Graph Builder, setting X and Y variables, overlaying sex, coloring by age, and displaying standard deviation charts.

Code:

Open("data_table.jmp");
gb = Graph Builder(
    Variables( X( :height ), Y( :weight ), Overlay( :sex ), Color( :age ) ),
    Elements( Points( X, Y, Legend( 1 ) ), Smoother( X, Y, Legend( 2 ) ) )
);
lgnd = Report( gb )[LegendBox( 1 )];
items = lgnd << Get Items;
hLineF = lgnd << Get Item( 2, 1 );
hLineF << Set Label( "Granular Control" );
markerColors = Filter Each( {item}, items, item << Get Type == "Mark Color" );
For Each( {item, index}, markerColors, item << Set Label( index ) );
For Each( {item}, items, If( item << Get Type == "Marker", item << Set Visible( 0 ) ) );

Code Explanation:

1. Open data table;
2. Create Graph Builder object.
3. Set X, Y, Overlay, and Color variables.
4. Add Points and Smoother elements.
5. Access LegendBox 1.
6. Retrieve legend items.
7. Rename second legend item.
8. Filter Mark Color items.
9. Label Mark Color items.
10. Hide Marker items.

Example 2048

Summary: Creates a variability chart with nested factors using Graph Builder, assigning variables for X, Y, Overlay, and Color, and displaying standard deviation charts.

Code:

dt = Open("data_table.jmp");
gb = Graph Builder(
    Variables( X( :height ), Y( :weight ), Overlay( :sex ), Color( :age ) ),
    Elements( Points( X, Y, Legend( 1 ) ), Smoother( X, Y, Legend( 2 ) ) )
);
lgnd = Report( gb )[LegendBox( 1 )];
items = lgnd << Get Items;
hLineF = lgnd << Get Item( 2, 1 );
hLineF << Set Label( "Granular Control" );
markerColors = Filter Each( {item}, items, item << Get Type == "Mark Color" );
For Each( {item, index}, markerColors, item << Set Label( index ) );
For Each( {item}, items, If( item << Get Type == "Marker", item << Set Visible( 0 ) ) );
For Each( {item}, items,
    If( item << Get Type == "Marker",
        If( item << Get Label == "F",
            item << Set Visible( 1 );
            item << Set Label( "I'm visible!" );
        ,
            item << Set Label( "I'm invisible." )
        )
    )
);

Code Explanation:

1. Open data table;
2. Create Graph Builder object.
3. Assign variables for X, Y, Overlay, and Color.
4. Add Points and Smoother elements to graph.
5. Access first LegendBox.
6. Retrieve all legend items.
7. Rename second legend item.
8. Filter items by type "Mark Color".
9. Label each marker color item.
10. Hide all markers.
11. Show and label female markers specifically.

Example 2049

Summary: Creates a graph builder object with nested factors using operator and part configurations, displaying standard deviation charts.

Code:

dt = Open( "$SAMPLE_DATA/data_table.jmp", invisible );
gb = dt << Graph Builder(
    Size( 557, 500 ),
    Variables( X( :height ), Y( :weight ) ),
    Elements( Points( X, Y, Legend( 1 ), Jitter( 1 ) ), Smoother( X, Y, Legend( 2 ) ) )
);
ldf2 = gb << Local Data Filter(
    Location( {1200, 339} ),
    Mode( Select( 0 ), Include( 1 ) ),
    Add Filter( columns( :age ), Where( :age == 12 ) )
);

Code Explanation:

1. Open data table.
2. Create graph builder object.
3. Set graph size.
4. Define X and Y variables.
5. Add points element with jitter.
6. Add smoother element.
7. Create local data filter.
8. Set filter location.
9. Set filter mode to include.
10. Add age filter for value 12.

Example 2050

Summary: Creates a graph builder object with nested factors, utilizing local data filters and row selection to visualize specific data points.

Code:

dt = Open( "$SAMPLE_DATA/data_table.jmp", invisible );
gb = dt << Graph Builder(
    Size( 557, 500 ),
    Variables( X( :height ), Y( :weight ) ),
    Elements( Points( X, Y, Legend( 1 ), Jitter( 1 ) ), Smoother( X, Y, Legend( 2 ) ) )
);
ldf2 = gb << Local Data Filter(
    Location( {1200, 339} ),
    Mode( Select( 0 ), Include( 1 ) ),
    Add Filter( columns( :age ), Where( :age == 12 ) )
);
dt << Select Rows( [40] );

Code Explanation:

1. Open data table.
2. Create graph builder object.
3. Set graph size.
4. Define X and Y variables.
5. Add points and smoother elements.
6. Create local data filter.
7. Set filter location and mode.
8. Add age filter condition.
9. Select specific row.

Example 2051

Summary: Creates a variability chart with nested factors using operator and part configurations, displaying standard deviation charts through Graph Builder.

Code:

dt1 = Open( "data_table1.jmp", invisible );
dt2 = Open( "data_table2.jmp", invisible );
dt3 = Open( "data_table3.jmp", invisible );
dt3 << Graph Builder(
    Size( 519, 464 ),
    Show Control Panel( 0 ),
    Variables(
        X( Referenced Column( "Genre[ItemNo]", Reference( Column( :Item Number ), Reference( Column( :Genre ) ) ) ) ),
        Y( Referenced Column( "Gender[CustID]", Reference( Column( :Customer ID ), Reference( Column( :Gender ) ) ) ) ),
        Color( Referenced Column( "Gender[CustID]", Reference( Column( :Customer ID ), Reference( Column( :Gender ) ) ) ) )
    ),
    Elements( Points( X, Y, Legend( 10 ) ) ),
    Local Data Filter(
        Add Filter(
            columns( Referenced Column( "Name[ItemNo]", Reference( Column( :Item Number ), Reference( Column( :Name ) ) ) ) ),
            Where(
                Referenced Column( "Name[ItemNo]", Reference( Column( :Item Number ), Reference( Column( :Name ) ) ) ) == "Bye Bye Birdie"
            ),
            Display(
                Referenced Column( "Name[ItemNo]", Reference( Column( :Item Number ), Reference( Column( :Name ) ) ) ),
                Size( 181, 225 ),
                List Display
            )
        )
    )
);
dt3 << Graph Builder(
    Size( 534, 490 ),
    Show Control Panel( 0 ),
    Variables(
        X( Referenced Column( "Age[CustID]", Reference( Column( :Customer ID ), Reference( Column( :Age ) ) ) ) ),
        Y( Referenced Column( "Rating[ItemNo]", Reference( Column( :Item Number ), Reference( Column( :Rating ) ) ) ) ),
        Y( Referenced Column( "Class[Item Number]", Reference( Column( :Item Number ), Reference( Column( :Class ) ) ) ), Position( 1 ) ),
        Group X( Referenced Column( "Gender[CustID]", Reference( Column( :Customer ID ), Reference( Column( :Gender ) ) ) ) ),
        Overlay( Referenced Column( "Genre[ItemNo]", Reference( Column( :Item Number ), Reference( Column( :Genre ) ) ) ) )
    ),
    Elements( Heatmap( X, Y( 1 ), Y( 2 ), Legend( 26 ) ) )
);

Code Explanation:

1. Open data_table1 table.
2. Open data_table2 table.
3. Open data_table3 table.
4. Create first Graph Builder.
5. Set size for first graph.
6. Hide control panel.
7. Define X, Y, and Color variables.
8. Add points element to graph.
9. Add local data filter.
10. Create second Graph Builder.
11. Set size for second graph.
12. Hide control panel.
13. Define X, Y, Group X, and Overlay variables.
14. Add heatmap element to graph.

Example 2052

Summary: Creates a graph builder object to visualize height and weight data, utilizing points and smoother elements.

Code:

Open("data_table.jmp");
gb = Graph Builder( Variables( X( :height ), Y( :weight ) ), Elements( Points( X, Y ), Smoother( X, Y ) ) );

Code Explanation:

1. Open data table.
2. Create graph builder object.
3. Set X variable to height.
4. Set Y variable to weight.
5. Add points element.
6. Add smoother element.

Example 2053

Summary: Creates two variability charts with nested factors using Graph Builder, displaying standard deviation charts for 'name' and 'age' variables.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 518, 448 ),
    Show Control Panel( 0 ),
    Variables(
        X( Transform Column( "Reverse Rank[name]", Formula( Col Number( :name ) - Col Rank( :name ) + 1 ) ) ),
        Y( Transform Column( "Rank[name]", Formula( Col Rank( :name ) ) ) )
    ),
    Elements( Bar( X, Y, Legend( 6 ) ) )
);
Graph Builder(
    Size( 518, 448 ),
    Show Control Panel( 0 ),
    Variables(
        X( Transform Column( "Reverse Rank[age]", Formula( Col Number( :age ) - Col Rank( :age ) + 1 ) ) ),
        Y( Transform Column( "Rank[age]", Formula( Col Rank( :age ) ) ) )
    ),
    Elements( Bar( X, Y, Legend( 7 ) ) )
);

Code Explanation:

1. Open data table;
2. Create Graph Builder window.
3. Set window size.
4. Hide control panel.
5. Define X variable: Reverse Rank[name].
6. Calculate Reverse Rank[name] using formula.
7. Define Y variable: Rank[name].
8. Calculate Rank[name] using formula.
9. Add bar element to graph.
10. Create another Graph Builder window.
11. Set window size.
12. Hide control panel.
13. Define X variable: Reverse Rank[age].
14. Calculate Reverse Rank[age] using formula.
15. Define Y variable: Rank[age].
16. Calculate Rank[age] using formula.
17. Add bar element to graph.

Example 2054

Summary: Creates a graph builder window with a histogram element to visualize the distribution of 'Promotion' data, while also transforming it to uppercase and setting its data type to 'Row State'.

Code:

dt = Open("data_table.jmp");
Graph Builder(
    Transform Column( "Uppercase[Promotion]", Character, Formula( Uppercase( :Promotion ) ) ),
    Size( 560, 437 ),
    Show Control Panel( 0 ),
    Variables( X( :Hair Color ), Overlay( :"Uppercase[Promotion]"n ) ),
    Elements( Histogram( X, Legend( 6 ) ) )
);
dt:Promotion << Set Data Type( "Row State" );

Code Explanation:

1. Open data table.
2. Transform Promotion to uppercase.
3. Create Graph Builder window.
4. Set window size.
5. Hide control panel.
6. Add Hair Color to X-axis.
7. Add Uppercase Promotion to overlay.
8. Add histogram element.
9. Set legend position.
10. Change Promotion data type.

Example 2055

Summary: Creates two Graph Builder windows to visualize and analyze a nested vector, transforming it into multiple columns for statistical calculations and displaying standard deviation charts.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 678, 456 ),
    Show Control Panel( 0 ),
    Variables(
        X( :age vector ),
        Y( Transform Column( "age vector[1]", Formula( :age vector[][1] ) ) ),
        Y( Transform Column( "age vector[2]", Formula( :age vector[][2] ) ), Position( 1 ) ),
        Y( Transform Column( "age vector[3]", Formula( :age vector[][3] ) ), Position( 1 ) ),
        Y( Transform Column( "age vector[4]", Formula( :age vector[][4] ) ), Position( 1 ) ),
        Y( Transform Column( "age vector[5]", Formula( :age vector[][5] ) ), Position( 1 ) )
    ),
    Elements( Points( X, Y( 1 ), Y( 2 ), Y( 3 ), Y( 4 ), Y( 5 ), Legend( 5 ) ) ),
    SendToReport(
        Dispatch( {}, "Graph Builder", OutlineBox, {Set Title( "Transform Vector To Columns" ), Image Export Display( Normal )} )
    )
);
Graph Builder(
    Size( 674, 470 ),
    Show Control Panel( 0 ),
    Variables(
        X( :age vector ),
        Y( Transform Column( "Sum[age vector]", Formula( V Sum( :age vector ) ) ) ),
        Y( Transform Column( "Min[age vector]", Formula( Minimum( :age vector ) ) ), Position( 1 ) ),
        Y( Transform Column( "Max[age vector]", Formula( Maximum( :age vector ) ) ), Position( 1 ) ),
        Y( Transform Column( "Loc Min[age vector]", Formula( Loc Min( :age vector ) ) ), Position( 1 ) ),
        Y( Transform Column( "Loc Max[age vector]", Formula( Loc Max( :age vector ) ) ), Position( 1 ) )
    ),
    Elements( Points( X, Y( 1 ), Y( 2 ), Y( 3 ), Y( 4 ), Y( 5 ), Legend( 17 ) ) ),
    SendToReport(
        Dispatch( {}, "Graph Builder", OutlineBox,
            {Set Title( "Transform Vector Sum, Min, Max, Loc Min, Loc Max" ), Image Export Display( Normal )}
        )
    )
);

Code Explanation:

1. Open data table;
2. Create first Graph Builder window.
3. Set window size and hide control panel.
4. Define X variable.
5. Transform age vector into multiple Y variables.
6. Plot points for all transformed Y variables.
7. Customize report title and export settings.
8. Create second Graph Builder window.
9. Set window size and hide control panel.
10. Define X variable and transform age vector.
11. Calculate sum, min, max, loc min, loc max for age vector.
12. Plot points for calculated statistics.
13. Customize report title and export settings.

Example 2056

Summary: Creates a variability chart with nested factors using operator and part configurations, displaying standard deviation charts.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 526, 411 ),
    Show Control Panel( 0 ),
    Variables( Y( Transform Column( "Rank[Event Date]", Formula( Col Rank( :Event Date ) ) ) ) ),
    Elements( Points( Y, Legend( 2 ) ) ),
    SendToReport(
        Dispatch( {}, "Graph Builder", FrameBox,
            Add Pin Annotation(
                Seg( Marker Seg( 1 ) ),
                Index( 1470 ),
                Index Row( 1470 ),
                UniqueID( 1470 ),
                FoundPt( {223, 162} ),
                Origin( {-0.201626898047722, 1459.84445851672} ),
                RightOfCenter( 0 ),
                Tag Line( 1 )
            )
        )
    )
);

Code Explanation:

1. Open data table;
2. Create Graph Builder window.
3. Set graph size.
4. Hide control panel.
5. Define Y variable with transformation.
6. Apply column rank formula.
7. Plot points for Y variable.
8. Add pin annotation.
9. Specify segment marker.
10. Position annotation on graph.

Example 2057

Summary: Creates a graph builder window with a random uniform distribution, utilizing Graph Builder and specifying X variable as sex and Y variable as random uniform.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 531, 450 ),
    Show Control Panel( 0 ),
    Variables( X( :sex ), Y( Transform Column( "Random Uniform", Formula( Random Uniform() ), Random Seed( 999999 ) ) ) ),
    Elements( Points( X, Y, Legend( 3 ) ) )
);
r1 = Random Uniform();
:sex[3] = "M";
r2 = Random Uniform();

Code Explanation:

1. Open data table;
2. Create Graph Builder window.
3. Set graph size.
4. Hide control panel.
5. Define X variable as sex.
6. Define Y variable as random uniform.
7. Set random seed for uniform distribution.
8. Add points element to graph.
9. Generate first random number.
10. Assign "M" to third sex value.
11. Generate second random number.

Example 2058

Summary: Creates a Graph Builder window with a random uniform Y variable, displaying points and generating two random numbers for display in a new window.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 531, 450 ),
    Show Control Panel( 0 ),
    Variables( X( :sex ), Y( Transform Column( "Random Uniform", Formula( Random Uniform() ), Random Seed( 999999 ) ) ) ),
    Elements( Points( X, Y, Legend( 3 ) ) )
);
r1 = Random Uniform();
:sex[3] = "M";
r2 = Random Uniform();
New Window( "Random results", H List Box( Number Edit Box( r1 ), Number Edit Box( r2 ) ) );

Code Explanation:

1. Open data table;
2. Create Graph Builder window.
3. Set window size.
4. Hide control panel.
5. Define X variable.
6. Create random uniform Y variable.
7. Set random seed for Y.
8. Add points element to graph.
9. Generate first random number.
10. Assign "M" to third sex entry.
11. Generate second random number.
12. Create new window for results.
13. Display random numbers in window.

Example 2059

Summary: Creates a variability chart with nested factors using operator and part configurations, displaying standard deviation charts in JMP.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 526, 448 ),
    Show Control Panel( 0 ),
    Variables(
        X(
            Transform Column(
                "Day of Week[Event Date]",
                Character,
                Formula( Choose( Day Of Week( :Event Date ), "Sun", "Mon", "Tue", "Wed", "Thu", "Fri", "Sat", "" ) )
            )
        ),
        Y( :Total Fatal Injuries )
    ),
    Elements( Points( X, Y, Legend( 5 ) ) )
);

Code Explanation:

1. Open data table;
2. Launch Graph Builder.
3. Set window size.
4. Hide control panel.
5. Define X variable.
6. Transform "Day of Week".
7. Convert to character type.
8. Use formula for transformation.
9. Map days to abbreviations.
10. Plot points with legend.

Example 2060

Summary: Creates a Graph Builder window with a nested variability chart, displaying standard deviation charts for 'Total Fatal Injuries' by 'Day of Week'.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 526, 456 ),
    Show Control Panel( 0 ),
    Variables(
        X(
            Transform Column(
                "Day of Week[Event Date]",
                Character,
                Formula(
                    Choose( Day Of Week( :Event Date ), "Sunday", "Monday", "Tuesday", "Wednesday", "Thursday", "Friday", "Saturday", "" )
                )
            )
        ),
        Y( :Total Fatal Injuries )
    ),
    Elements( Points( X, Y, Legend( 5 ) ) )
);

Code Explanation:

1. Open data table;
2. Create Graph Builder window.
3. Set window size.
4. Hide control panel.
5. Define X variable.
6. Transform "Day of Week".
7. Convert to character type.
8. Apply formula for day names.
9. Define Y variable.
10. Add points element.

Example 2061

Summary: Creates a variability chart with nested factors using Graph Builder, applying log transformation to height and displaying standard deviation charts.

Code:

Open("data_table.jmp");
Graph Builder(
    Transform Column( "Log[height]", Formula( Log( :height ) ) ),
    Size( 526, 448 ),
    Show Control Panel( 0 ),
    Variables( X( :sex ), Y( Transform Column( "Log[height]^2", Formula( :"Log[height]"n * :"Log[height]"n ) ) ) ),
    Elements( Points( X, Y, Legend( 4 ) ) )
);

Code Explanation:

1. Open data table;
2. Create new transform column.
3. Apply log transformation to height.
4. Set graph size.
5. Hide control panel.
6. Define X variable as sex.
7. Create another transform column.
8. Square the log-transformed height.
9. Define Y variable as squared log-height.
10. Add points element to graph.

Example 2062

Summary: Creates a variability chart with nested factors using Graph Builder, transforming the 'Min[Max deg. F ...2,NO,PM10,Lead]' column and displaying standard deviation charts.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 523, 454 ),
    Show Control Panel( 0 ),
    Variables(
        X(
            Transform Column(
                "Min[Max deg. F ...2,NO,PM10,Lead]",
                Formula( Minimum( :Max deg. F Jan, :OZONE, :CO, :SO2, :NO, :PM10, :Lead ) )
            )
        ),
        Y( :"pop- m"n )
    ),
    Elements( Points( X, Y, Legend( 3 ) ), Smoother( X, Y, Legend( 4 ) ) )
);

Code Explanation:

1. Open data table;
2. Create Graph Builder window.
3. Set window size.
4. Hide control panel.
5. Define X variable.
6. Transform "Min[Max deg. F ...2,NO,PM10,Lead]" column.
7. Use minimum formula on pollutants.
8. Define Y variable.
9. Add points element.
10. Add smoother element.

Example 2063

Summary: Creates a variability chart with nested factors using Graph Builder, displaying moving average columns and standard deviation charts.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 526, 448 ),
    Show Control Panel( 0 ),
    Variables( X( :Region ), Y( Transform Column( "Moving Average[OZONE]", Formula( Col Moving Average( :OZONE, 1, 0 ) ) ) ) ),
    Elements( Points( X, Y, Legend( 5 ) ) )
);

Code Explanation:

1. Open data table;
2. Launch Graph Builder.
3. Set window size.
4. Hide control panel.
5. Define X variable.
6. Create moving average column.
7. Define Y variable.
8. Add points element.
9. Assign legend to points.

Example 2064

Summary: Creates two variability charts with nested factors using Graph Builder, featuring local data filters and pin annotations.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 525, 456 ),
    Show Control Panel( 0 ),
    Variables( X( :name ), Y( Transform Column( "Rank[name]", Formula( Col Rank( :name ) ) ) ) ),
    Elements( Points( X, Y, Legend( 17 ) ) ),
    Local Data Filter(
        Add Filter(
            columns( Transform Column( "Rank[name]", Formula( Col Rank( :name ) ) ) ),
            Where( Transform Column( "Rank[name]", Formula( Col Rank( :name ) ) ) >= 13.768 )
        )
    ),
    SendToReport(
        Dispatch( {}, "Graph Builder", FrameBox,
            Add Pin Annotation(
                Seg( Marker Seg( 1 ) ),
                Index( 13 ),
                Index Row( 17 ),
                UniqueID( 13 ),
                FoundPt( {458, 250} ),
                Origin( {9.98739495798319, 23.9793684210526} ),
                Offset( {42, 31} ),
                RightOfCenter( 0 ),
                Tag Line( 1 )
            )
        )
    )
);
Graph Builder(
    Size( 521, 473 ),
    Show Control Panel( 0 ),
    Variables( X( :name ), Y( Transform Column( "Reverse Rank[name]", Formula( Col Number( :name ) - Col Rank( :name ) + 1 ) ) ) ),
    Elements( Points( X, Y, Legend( 22 ) ) ),
    Local Data Filter(
        Width( 137 ),
        Add Filter( columns( Transform Column( "Reverse Rank[name]", Formula( Col Number( :name ) - Col Rank( :name ) + 1 ) ) ) )
    ),
    SendToReport(
        Dispatch( {}, "Graph Builder", FrameBox,
            Add Pin Annotation(
                Seg( Marker Seg( 1 ) ),
                Index( 17 ),
                Index Row( 17 ),
                UniqueID( 13 ),
                FoundPt( {458, 250} ),
                Origin( {23.0395835392981, 17.0152169014085} ),
                Offset( {42, 31} ),
                RightOfCenter( 0 ),
                Tag Line( 1 )
            )
        )
    )
);

Code Explanation:

1. Open data table;
2. Create first Graph Builder.
3. Set size and hide control panel.
4. Define X and transformed Y variables.
5. Add points element.
6. Apply local data filter.
7. Add pin annotation.
8. Create second Graph Builder.
9. Set size and hide control panel.
10. Define X and reverse rank Y variables.
11. Add points element.
12. Apply local data filter.
13. Add pin annotation.

Example 2065

Summary: Creates a variability chart with nested factors using Graph Builder, applying SHASH transformation to height data and overlaying original height values.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 518, 448 ),
    Show Control Panel( 0 ),
    Variables(
        X( :age ),
        Y(
            Transform Column(
                "SHASH[height]",
                Formula( SHASHTrans( :height, 0.309721110988966, 0.876143047777729, 64.2164057482689, 3.17578607771321 ) )
            )
        ),
        Overlay( :height )
    ),
    Elements( Points( X, Y, Legend( 4 ) ) )
);

Code Explanation:

1. Open data table;
2. Launch Graph Builder.
3. Set window size.
4. Hide control panel.
5. Define X variable.
6. Define Y variable transformation.
7. Apply SHASH transformation formula.
8. Overlay original height data.
9. Add points element.
10. Assign legend to points.

Example 2066

Summary: Creates a variability chart with nested factors using Graph Builder, configuring a new column 'Sepal width^2' and displaying standard deviation charts.

Code:

dt = Open("data_table.jmp");
Graph Builder(
    Transform Column( "Sepal width^2", Format( "Fixed Dec", 10, 1 ), Formula( :Sepal width * :Sepal width ) ),
    Show Control Panel( 0 ),
    Variables( Y( :"Sepal width^2"n ) ),
    Elements( Points( Y, Legend( 2 ) ) )
);

Code Explanation:

1. Open data table;
2. Create new column "Sepal width^2".
3. Set column format to "Fixed Dec".
4. Define formula for squared sepal width.
5. Hide control panel.
6. Set Y variable to new column.
7. Add points element to graph.
8. Assign legend to points.

Example 2067

Summary: Creates a graph builder window with nested factors using titlecase, uppercase, and lowercase transformations, and applies a local data filter for female sex.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 835, 576 ),
    Show Control Panel( 0 ),
    Variables(
        X( Transform Column( "Titlecase[reported illnesses]", Character, Formula( Titlecase( :reported illnesses ) ) ) ),
        Wrap( Transform Column( "Uppercase[countries visited]", Character, Formula( Uppercase( :countries visited ) ) ) ),
        Overlay( Transform Column( "Lowercase[name]", Character, Formula( Lowercase( :name ) ) ) ),
        Color( Transform Column( "Lowercase[sex]", Character, Formula( Lowercase( :sex ) ) ) )
    ),
    Elements( Points( X, Legend( 32 ) ) ),
    Local Data Filter(
        Add Filter(
            columns( Transform Column( "Lowercase[sex]", Character, Formula( Lowercase( :sex ) ) ) ),
            Where( Transform Column( "Lowercase[sex]", Character, Formula( Lowercase( :sex ) ) ) == "f" )
        )
    ),
    SendToReport(
        Dispatch( {}, "Titlecase[reported illnesses]", ScaleBox, {Label Row( Label Orientation( "Angled" ) )} ),
        Dispatch( {}, "Graph Builder", FrameBox( 2 ),
            Add Pin Annotation(
                Seg( Marker Seg( 17 ) ),
                Index( 0 ),
                Index Row( 19 ),
                UniqueID( 0 ),
                FoundPt( {813, 119} ),
                Origin( {8.98905109489051, 0.0216000000000001} ),
                Offset( {-22, 386} ),
                RightOfCenter( 1 ),
                Tag Line( 1 ),
                Frame Color( "Black" )
            )
        )
    )
);

Code Explanation:

1. Open data table;
2. Create Graph Builder window.
3. Set graph size.
4. Hide control panel.
5. Define X variable with titlecase transformation.
6. Define wrap variable with uppercase transformation.
7. Define overlay variable with lowercase transformation.
8. Define color variable with lowercase transformation.
9. Add points element to graph.
10. Apply local data filter for female sex.

Example 2068

Summary: Creates two Graph Builder windows to visualize event date data, transforming it into week-based and year-week-based formats for bar chart analysis.

Code:

Open("data_table.jmp");
Graph Builder(
    Size( 525, 454 ),
    Show Control Panel( 0 ),
    Variables(
        X( Transform Column( "Round...[Event Date]", Format( "m/d/y", 12 ), Formula( Date Increment( :Event Date, "Week", 0 ) ) ) )
    ),
    Elements( Bar( X, Legend( 3 ) ) )
);
Graph Builder(
    Size( 940, 456 ),
    Show Control Panel( 0 ),
    Variables(
        X(
            Transform Column(
                "Year Week[Event Date]",
                Character,
                Formula(
                    Local( {w = Week Of Year( :Event Date, 3 ), y = Year( :Event Date ), m = Month( :Event Date )},
                        If( Is Missing( :Event Date ),
                            "",
                            Char( If( m / w >= 12, y + 1, w / m >= 52, y - 1, y ) ) || If( w >= 10, "W", "W0" ) || Char( w )
                        )
                    )
                )
            )
        )
    ),
    Elements( Bar( X, Legend( 3 ) ) )
);

Code Explanation:

1. Open data table;
2. Create Graph Builder window.
3. Set window size.
4. Hide control panel.
5. Define X variable.
6. Transform event date to week.
7. Plot bar chart.
8. Create second Graph Builder window.
9. Set window size.
10. Hide control panel.
11. Define X variable.
12. Transform event date to year-week.
13. Plot bar chart.

Example 2069

Summary: Creates a treemap visualization with nested factors using Graph Builder, Local Data Filter, and subset operations.

Code:

dt = Open( "$SAMPLE_DATA/data_table.jmp", "private" );
gb = dt << Graph Builder(
    Show Control Panel( 0 ),
    Variables( X( :city ), Color( :OZONE ), Size( :POP ) ),
    Elements( Treemap( X, Legend( 2 ), Summary Statistic( "Sum" ) ) ),
    SendToReport( Dispatch( {}, "Graph Builder", FrameBox, {DispatchSeg( TreeMapSeg( 1 ), Frame Size( 559, 450 ) )} ) )
);
ldf = gb << Local Data Filter(
    Location( {538, 43} ),
    Add Filter( columns( :OZONE, :Region ), Where( :OZONE >= 0.148 & :OZONE <= 0.33 ), Where( :Region == "S" ) ),
    Mode( Select( 0 ), Show( 1 ), Include( 1 ) )
);
subHandle = ldf << Show Subset;
cityVals = Column( subHandle, "city" ) << get values;
ldf << Inverse( 1 );
subHandle2 = ldf << Show Subset;
cityVals = Column( subHandle2, "city" ) << get values;
ldf << Inverse( 0 );
ldf << (Filter column( :Region ) << Invert Selection);
subHandle3 = ldf << Show Subset;
cityVals = Column( subHandle3, "city" ) << get values;
ldf << (Filter column( :ozone ) << Invert Selection);
subHandle4 = ldf << Show Subset;
cityVals = Column( subHandle4, "city" ) << get values;

Code Explanation:

1. Open data table.
2. Create Graph Builder object.
3. Configure Graph Builder settings.
4. Add Treemap element.
5. Set frame size.
6. Create Local Data Filter.
7. Set filter location.
8. Add OZONE and Region filters.
9. Show initial subset.
10. Get city values from subset.
11. Invert filter selection.
12. Show updated subset.
13. Get new city values.
14. Revert filter selection.
15. Invert Region filter selection.
16. Show subset with inverted Region.
17. Get city values from inverted Region subset.
18. Invert OZONE filter selection.
19. Show subset with inverted OZONE.
20. Get city values from inverted OZONE subset.

Example 2070

Summary: Creates a bar chart with nested factors using Graph Builder, filtering data by sex and name columns.

Code:

dt = Open( "$SAMPLE_DATA\data_table.jmp", "private" );
gb = dt << Graph Builder(
    Size( 448, 414 ),
    Show Control Panel( 0 ),
    Variables( X( :age ) ),
    Elements( Bar( X, Legend( 6 ) ) ),
    Local Data Filter(
        Conditional,
        Add Filter(
            columns( :sex, :name ),
            Where( :sex == "F" ),
            Where( :name == {"ALICE", "ELIZABETH", "KATIE", "LOUISE", "MARY", "SUSAN"} ),
            Display( :name, Size( 160, 225 ), Check Box Display )
        )
    )
);

Code Explanation:

1. Open data table;
2. Create Graph Builder object.
3. Set graph size to 448x414.
4. Hide control panel.
5. Set X variable to age.
6. Add bar element with legend.
7. Enable local data filter.
8. Set filter condition to conditional.
9. Add filter for sex and name columns.
10. Filter where sex is "F" and names match specific list.

Example 2071

Summary: Creates a graph builder with nested factors, utilizing local data filters and display options to visualize regional data.

Code:

dt = Open("data_table.jmp");
gb = dt << Graph Builder(
    Size( 570, 699 ),
    Show Control Panel( 0 ),
    Variables( X( :State ), Y( :Region ), Color( :city ) ),
    Elements( Points( X, Y, Legend( 1 ), Jitter( 1 ) ) )
);
ldf = gb << Local Data Filter(
    Location( {382, 244} ),
    Hierarchical,
    Add Filter(
        columns( :Region, :State, :city ),
        Where( :Region == "MW" ),
        Where( :State == "WI" ),
        Display( :Region, Single Category Display ),
        Display( :State, Single Category Display ),
        Display( :city, Size( 208, 208 ), List Display )
    ),
    Mode( Select( 0 ), Show( 1 ), Include( 1 ) )
);
filRows = ldf << Get Filtered Rows;
ldf << Display( :Region, List Display );
ldf << Display( :State, List Display );
ldf << Display( :Region, Check Box Display );
ldf << Display( :State, Check Box Display );
ldf << Display( :Region, Single category display );
ldf << Display( :State, single category Display );

Code Explanation:

1. Open table.
2. Create graph builder.
3. Set graph size.
4. Hide control panel.
5. Define variables.
6. Add points element.
7. Add local data filter.
8. Set filter location.
9. Enable hierarchical filter.
10. Define filter criteria.

Example 2072

Summary: Creates a variability chart with nested factors using Graph Builder, hiding the control panel and setting X to height and Y to weight.

Code:

dt = Open("data_table.jmp");
gb = dt << Graph Builder(
    Show Control Panel( 0 ),
    Variables( X( :height ), Y( :weight ) ),
    Elements( Points( X, Y, Legend( 1 ), Jitter( 1 ) ), Smoother( X, Y, Legend( 2 ) ) ),
    Local Data Filter(
        Location( {357, 228} ),
        Hierarchical,
        Add Filter( columns( :age, :sex, :height ) ),
        Mode( Select( 0 ), Show( 1 ), Include( 1 ) )
    )
);
gb << save script to Data Table("data_table");
gbScript = dt << get table variable( "Graph Builder" );

Code Explanation:

1. Open data table;
2. Create Graph Builder object.
3. Hide control panel.
4. Set X to height.
5. Set Y to weight.
6. Add points element.
7. Add smoother element.
8. Add local data filter.
9. Position filter at {357, 228}.
10. Save script to data table.

Example 2073

Summary: Creates a treemap visualization with nested factors using Graph Builder and Local Data Filter, displaying summary statistics for population data.

Code:

dt = Open("data_table.jmp");
gb = dt << Graph Builder(
    Size( 570, 581 ),
    Show Control Panel( 0 ),
    Variables( X( :city ), Color( :OZONE ), Size( :POP ) ),
    Elements( Treemap( X, Legend( 4 ), Summary Statistic( "Sum" ) ) )
);
ldf = gb << Local Data Filter(
    Location( {322, 99} ),
    Add Filter(
        columns( :State, :Region ),
        Where( :State == {"AL", "CA", "CO", "CT", "DE", "KS", "KY", "LA"} ),
        Where( :Region == {"MW", "N", "S", "TX", "W"} ),
        Display( :State, Size( 204, 123 ), List Display ),
        Display( :Region, Size( 200, 17 ) )
    ),
    Mode( Select( 0 ), Show( 1 ), Include( 1 ) )
);
ldf << Delete( {:region} );
ldf << Delete All;
ldf << Remove Local Data Filter;

Code Explanation:

1. Open data table.
2. Create Graph Builder object.
3. Set size to 570x581.
4. Hide control panel.
5. Define X, Color, and Size variables.
6. Add Treemap element with Sum summary statistic.
7. Add Local Data Filter to graph.
8. Set filter location.
9. Add State and Region filters.
10. Remove Region filter from display.

Example 2074

Summary: Creates a treemap visualization with filtered data for Iowa cities, utilizing Graph Builder and Local Data Filter features.

Code:

dt = Open("data_table.jmp");
gb = dt << Graph Builder(
    Show Control Panel( 0 ),
    Variables( X( :city ), Color( :OZONE ), Size( :POP ) ),
    Elements( Treemap( X, Legend( 4 ) ) )
);
ldf = gb << Local Data Filter(
    Location( {647, 183} ),
    Mode,
    Add Filter( columns( :city ), Display( :city, Size( 204, 259 ), List Display ) )
);
ldf << Match( Where( :state == "IA" ) );
Wait( 0 );
If( Host is( windows ),
    txt8 = Window( "data_table - Graph Builder" )[Text Box( 7 )] << get Text,
    txt8 = Window( "data_table - Graph Builder" )[Text Box( 7 )] << get Text
);

Code Explanation:

1. Open table.
2. Create graph builder.
3. Hide control panel.
4. Set X variable.
5. Set color variable.
6. Set size variable.
7. Add treemap element.
8. Add local data filter.
9. Set filter location.
10. Set filter mode.
11. Add city filter.
12. Filter for Iowa cities.
13. Wait briefly.
14. Check host operating system.
15. Get text from text box.

Example 2075

Summary: Creates a bar chart with nested factors, filtering for American Airlines data and displaying standard deviation charts.

Code:

Open("data_table.jmp");
obj = Graph Builder(
    Show Control Panel( 0 ),
    Variables( X( :Day of Week ), Overlay( :Airline ) ),
    Elements( Bar( X, Legend( 2 ) ) ),
    Local Data Filter(
        Add Filter( columns( :Airline ), Where( :Airline == "American" ), Display( :Airline, Size( 204, 94 ), List Display ) )
    )
);
rpt = obj << Report;
expr = rpt[LegendBox( 1 )] << Get Journal;
p = "Delta";
ans = Pat Match( expr, p );

Code Explanation:

1. Open data table.
2. Create Graph Builder object.
3. Hide control panel.
4. Set X variable to Day of Week.
5. Overlay Airline variable.
6. Add bar element.
7. Add local data filter.
8. Filter for American Airlines.
9. Generate report.
10. Extract legend box content.
11. Define pattern Delta.
12. Match pattern in legend content.

Example 2076

Summary: Creates a report with a filtered bar chart to display airline data, utilizing Graph Builder and Local Data Filter.

Code:

dt = Open("data_table.jmp");
obj = Graph Builder(
    Show Control Panel( 0 ),
    Variables( X( :Day of Week ), Overlay( :Airline ) ),
    Elements( Bar( X, Legend( 2 ) ) ),
    Local Data Filter(
        Add Filter( columns( :Airline ), Where( :Airline == "American" ), Display( :Airline, Size( 204, 94 ), List Display ) )
    )
);
rpt = obj << Report;
expr = rpt[LegendBox( 1 )] << Get Journal;
p = "Delta";
ans = Pat Match( expr, p );

Code Explanation:

1. Open data table;
2. Create Graph Builder object.
3. Hide control panel.
4. Set X to Day of Week.
5. Overlay by Airline.
6. Add bar element.
7. Add local data filter.
8. Filter Airline for American.
9. Generate report.
10. Extract legend box journal.
11. Search for "Delta" in journal.
12. Store match result.

Example 2077

Summary: Creates a graph builder object with points plotted on it, saving the picture as a PDF file.

Code:

folderPath = "$DESKTOP";
dt = Open("data_table.jmp");
obj = dt << Graph Builder( Variables( X( :height ), Y( :weight ) ), Elements( Points( X, Y ) ) );
pic = obj << Get Picture( scale( 2 ), Type( "bitmap" ) );
pic << Save Image( folderPath || "/test.pdf", "pdf" );

Code Explanation:

1. Set folder path to desktop.
2. Open data table;
3. Create graph builder object.
4. Add height to X-axis.
5. Add weight to Y-axis.
6. Plot points on graph.
7. Get graph picture.
8. Scale picture to 2x.
9. Convert picture to bitmap.
10. Save picture as PDF.

Example 2078

Summary: Creates a graph builder object with points plotted on it, and saves the picture as a PDF file.

Code:

folderPath = "$DESKTOP";
isCreate = 1;
dt = Open("data_table.jmp");
obj = dt << Graph Builder( Variables( X( :height ), Y( :weight ) ), Elements( Points( X, Y ) ) );
pic = obj << Get Picture( scale( 2 ), Type( "bitmap" ) );
pic << Save Image( folderPath || "/test.pdf", "pdf" );

Code Explanation:

1. Set folder path.
2. Define creation flag.
3. Open data table.
4. Create graph builder object.
5. Add height to X-axis.
6. Add weight to Y-axis.
7. Plot points on graph.
8. Retrieve graph picture.
9. Scale picture size.
10. Save picture as PDF.

Example 2079

Summary: Creates two graph builders to visualize height data, utilizing Graph Builder and deleting selected rows from the data table.

Code:

dt = Open("data_table.jmp");
gb = dt << Graph Builder( Variables( Y( :height ) ), Elements( Points( Y, Legend( 1 ), Jitter( 1 ) ) ) );
dist = dt << Graph Builder( Variables( Y( :height ) ), Elements( Points( Y, Legend( 1 ), Jitter( 1 ) ) ) );
dt << Select All Rows;
dt << Delete Rows;

Code Explanation:

1. Open data table.
2. Create graph builder object.
3. Assign graph builder to variable.
4. Create another graph builder object.
5. Assign second graph builder to variable.
6. Select all rows in data table.
7. Delete selected rows from data table.

Example 2080

Summary: Creates a graph builder object with nested factors, selecting rows where sex is male and displaying standard deviation charts.

Code:

dt = Open("data_table.jmp");
plat = dt << Graph Builder(
    Variables( X( :height ), Y( :weight ), Overlay( :sex ) ),
    Elements( Points( X, Y, Legend( 1 ) ), Smoother( X, Y, Legend( 3 ) ) ),
    SendToReport( Dispatch( {}, "Graph Builder", FrameBox, {Marker Size( 6 )} ) )
);
dt << Select Where( :sex == "M" );
jrn = plat << Journal Window;

Code Explanation:

1. Open data table.
2. Create graph builder object.
3. Set X, Y, and overlay variables.
4. Add points and smoother elements.
5. Adjust marker size in report.
6. Select rows where sex is male.
7. Create journal window from graph.

Example 2081

Summary: Creates a bar chart with nested factors using Graph Builder, displaying standard deviation charts and configuring X-axis scale.

Code:

dt under test = Open("data_table.jmp");
obj = Graph Builder(
    Size( 1450, 1082 ),
    Show Control Panel( 0 ),
    Variables( X( :State ), Y( :Name( "% Taking (2004)" ) ) ),
    Elements( Bar( X, Y, Legend( 8 ) ) ),
    SendToReport( Dispatch( {}, "State", ScaleBox, {Min( -0.33863086560182 ), Max( 50.6613691343982 ), Inc( 1 ), Minor Ticks( 0 )} ) )
);

Code Explanation:

1. Open data table.
2. Create Graph Builder object.
3. Set graph size to 1450x1082.
4. Hide control panel.
5. Assign State to X-axis.
6. Assign % Taking (2004) to Y-axis.
7. Add bar element to graph.
8. Set legend position to 8.
9. Configure X-axis scale.
10. Display graph.

Example 2082

Summary: Creates a box plot with quantile boxes and points, displaying standard deviation charts for nested factors using Graph Builder.

Code:

dt under test = Open("data_table.jmp");
obj = Graph Builder(
    Show Control Panel( 0 ),
    Variables( X( :height ) ),
    Elements( Box Plot( X, Legend( 3 ), Box Type( "Quantile" ) ), Points( X, Legend( 4 ) ) ),
    SendToReport(
        Dispatch( {}, "400", ScaleBox, {Legend Model( 3, Properties( 0, {Line Color( 73 ), Line Width( 6 )} ) )} ),
        Dispatch( {}, "400", LegendBox, {Position( {0, 1} )} ),
        Dispatch( {}, "Y title", TextEditBox, {Set Wrap( 2 )} ),
        Dispatch( {}, "Graph Builder", FrameBox, {Background Color( 68 )} )
    )
);

Code Explanation:

1. Open data table;
2. Create Graph Builder object.
3. Hide control panel.
4. Set X variable to height.
5. Add box plot element.
6. Customize box type to quantile.
7. Add points element.
8. Customize legend for box plot.
9. Position legend at top-left.
10. Customize graph appearance.

Example 2083

Summary: Creates a variability chart with nested factors using operator and part configurations, displaying standard deviation charts in JMP.

Code:

dt under test = Open("data_table.jmp");
obj = Graph Builder(
    Size( 534, 489 ),
    Show Control Panel( 0 ),
    Variables( X( :Rotten Tomatoes Score ), Y( :Audience Score ), Wrap( :Genre ) ),
    Elements( Points( X, Y, Legend( 17 ) ), Ellipse( X, Y, Legend( 19 ) ) ),
    SendToReport(
        Dispatch( {}, "400", ScaleBox,
            {Legend Model( 17, Properties( 0, {Line Color( -8323072 ), Fill Color( -8323072 )} ) ),
            Legend Model( 19, Properties( 0, {Line Color( -127 ), Fill Color( 53 )} ) )}
        ),
        Dispatch( {}, "400", LegendBox, {Position( {1, 0} )} ),
        Dispatch( {}, "Graph Builder", FrameBox, {Background Color( 32 )} ),
        Dispatch( {}, "Graph Builder", FrameBox( 2 ), {Background Color( 32 )} ),
        Dispatch( {}, "Graph Builder", FrameBox( 3 ), {Background Color( 32 )} ),
        Dispatch( {}, "Graph Builder", FrameBox( 4 ), {Background Color( 32 )} ),
        Dispatch( {}, "Graph Builder", FrameBox( 5 ), {Background Color( 32 )} ),
        Dispatch( {}, "Graph Builder", FrameBox( 6 ), {Background Color( 32 )} ),
        Dispatch( {}, "Graph Builder", FrameBox( 7 ), {Background Color( 32 )} ),
        Dispatch( {}, "Graph Builder", FrameBox( 8 ), {Background Color( 32 )} ),
        Dispatch( {}, "Graph Builder", FrameBox( 9 ), {Background Color( 32 )} )
    )
);

Code Explanation:

1. Open data table;
2. Create Graph Builder object.
3. Set graph size.
4. Hide control panel.
5. Assign variables: X, Y, Wrap.
6. Add points and ellipse elements.
7. Customize legend colors.
8. Position legend.
9. Set background color for main frame.
10. Set background color for all wrapped frames.

Example 2084

Summary: Creates a nested variability chart with standard deviation charts, using Graph Builder to visualize airline data across different days of the week.

Code:

dt under test = Open("data_table.jmp");
obj = Graph Builder(
    Size( 618, 489 ),
    Show Control Panel( 0 ),
    Variables( Y( :Airline ), Wrap( :Day of Week ) ),
    Elements( Bar( Y, Legend( 11 ) ) ),
    SendToReport(
        Dispatch( {}, "400", ScaleBox, {Legend Model( 11, Properties( 0, {Fill Color( 51 )} ) )} ),
        Dispatch( {}, "Graph Builder", FrameBox, {Background Color( 32 )} ),
        Dispatch( {}, "Graph Builder", FrameBox( 2 ), {Background Color( 32 )} ),
        Dispatch( {}, "Graph Builder", FrameBox( 3 ), {Background Color( 32 )} ),
        Dispatch( {}, "Graph Builder", FrameBox( 4 ), {Background Color( 32 )} ),
        Dispatch( {}, "Graph Builder", FrameBox( 5 ), {Background Color( 32 )} ),
        Dispatch( {}, "Graph Builder", FrameBox( 6 ), {Background Color( 32 )} ),
        Dispatch( {}, "Graph Builder", FrameBox( 7 ), {Background Color( 32 )} ),
        Dispatch( {}, "Graph Builder", FrameBox( 8 ), {Background Color( 32 )} ),
        Dispatch( {}, "Graph Builder", FrameBox( 9 ), {Background Color( 32 )} )
    )
);

Code Explanation:

1. Open table "data_table".
2. Create Graph Builder object.
3. Set size to 618x489.
4. Hide control panel.
5. Assign Y variable :Airline.
6. Wrap X variable :Day of Week.
7. Add bar element.
8. Set legend properties.
9. Set background color for graph.
10. Set background color for each frame box.

Example 2085

Summary: Creates a variability chart with nested factors using operator and part configurations, displaying standard deviation charts.

Code:

dt under test = Open("data_table.jmp");
obj = Graph Builder(
    Show Control Panel( 0 ),
    Variables( X( :Durability ), Y( :Distance ), Group X( :Brand ) ),
    Elements( Line( X, Y, Legend( 31 ), Summary Statistic( "Median" ) ), Points( X, Y, Legend( 33 ) ) ),
    SendToReport(
        Dispatch( {}, "400", LegendBox, {Position( {0, 1} )} ),
        Dispatch( {}, "Graph Builder", FrameBox, {Background Color( 67 )} ),
        Dispatch( {}, "Graph Builder", FrameBox( 2 ), {Background Color( 35 )} ),
        Dispatch( {}, "Graph Builder", FrameBox( 3 ), {Background Color( 3 )} )
    )
);

Code Explanation:

1. Open data table.
2. Create Graph Builder object.
3. Hide control panel.
4. Set X, Y, and Group X variables.
5. Add line element with median summary.
6. Add points element.
7. Adjust legend position.
8. Set background color for main frame.
9. Set background color for second frame.
10. Set background color for third frame.

Example 2086

Summary: Creates a graph builder object with nested factors, utilizing Graph Builder and SendToReport to display standard deviation charts.

Code:

dt under test = Open("data_table.jmp");
obj = Graph Builder(
    Show Control Panel( 0 ),
    Variables( X( :Weight ), Y( :Turning Circle ) ),
    Elements( Points( X, Y, Legend( 5 ) ) ),
    SendToReport(
        Dispatch( {}, "Turning Circle", ScaleBox, {Label Row( Set Font( "Showcard Gothic" ) )} ),
        Dispatch( {}, "Graph Builder", FrameBox, {Background Color( 74 )} )
    )
);

Code Explanation:

1. Open table.
2. Create Graph Builder object.
3. Hide control panel.
4. Set X variable.
5. Set Y variable.
6. Add points element.
7. Change font for labels.
8. Set background color.

Example 2087

Summary: Creates a graph builder with nested factors using operator and part configurations, displaying standard deviation charts.

Code:

dt under test = Open("data_table.jmp");
obj = Graph Builder(
    Show Control Panel( 0 ),
    Variables( X( :Country ), Y( :Weight ), Overlay( :Type ) ),
    Elements( Points( X, Y, Legend( 9 ) ) ),
    SendToReport(
        Dispatch( {}, "Country", ScaleBox, {Label Row( Set Font( "Showcard Gothic" ) )} ),
        Dispatch( {}, "Graph Builder", FrameBox, {Marker Size( 6 )} )
    )
);

Code Explanation:

1. Open data table.
2. Create Graph Builder object.
3. Hide control panel.
4. Set X variable to Country.
5. Set Y variable to Weight.
6. Use Type for overlay.
7. Add points element.
8. Change font of Country labels.
9. Set marker size to 6.
10. Display graph.

Example 2088

Summary: Creates a variability chart with nested factors using operator and part configurations, displaying standard deviation charts.

Code:

dt under test = Open("data_table.jmp");
obj = Graph Builder(
    Show Control Panel( 0 ),
    Legend Position( "Bottom" ),
    Variables( X( :weight ), Y( :height ) ),
    Elements(
        Caption Box( X, Y, Legend( 12 ), Summary Statistic( "Mean" ), X Position( "Right" ), Y Position( "Top" ) ),
        Bar( X, Y, Legend( 23 ), Bar Style( "Side by side" ), Summary Statistic( "Mean" ) )
    ),
    SendToReport(
        Dispatch( {}, "Graph Builder", OutlineBox, {Set Title( "Bar, Legend Position: Bottom" )} ),
        Dispatch( {}, "400", LegendBox, {Orientation( "Horizontal" ), Sides( "Left" )} )
    )
);

Code Explanation:

1. Open data table.
2. Create Graph Builder object.
3. Hide control panel.
4. Set legend position bottom.
5. Define X and Y variables.
6. Add caption box element.
7. Add bar element.
8. Set title for graph.
9. Adjust legend orientation and sides.
10. Display graph.

Example 2089

Summary: Creates a Graph Builder object to visualize relationships between weight and height, utilizing points with jitter and a smoother.

Code:

dt under test = Open("data_table.jmp");
obj = Graph Builder(
    Show Control Panel( 0 ),
    Variables( X( :weight ), Y( :height ) ),
    Elements( Points( X, Y, Legend( 1 ), Jitter( 1 ) ), Smoother( X, Y, Legend( 2 ) ) )
);

Code Explanation:

1. Open data table;
2. Create Graph Builder object.
3. Hide control panel.
4. Set X variable to weight.
5. Set Y variable to height.
6. Add points element.
7. Enable jitter for points.
8. Add smoother element.
9. Display graph.

Example 2090

Summary: Creates a variability chart with nested factors using operator and part configurations, displaying standard deviation charts.

Code:

dt = Open("data_table.jmp");
Graph Builder(
    Size( 606, 554 ),
    Variables(
        X( :Sports ),
        X( :Name( "Urban/Rural" ), Position( 1 ) ),
        Y( :Goals ),
        Y( :Sports, Position( 1 ) ),
        Y( :School, Position( 1 ) ),
        Overlay( :Race )
    ),
    Elements( Area( X( 2 ), X( 1 ), Y( 1 ), Y( 2 ), Y( 3 ), Legend( 17 ) ) ),
    SendToReport(
        Dispatch( {"Area"}, "", OutlineBox, {Close( 0 )} ),
        Dispatch( {}, "Goals", ScaleBox, {Min( -0.114198285682452 ), Max( 86.1551059117409 ), Inc( 1 ), Minor Ticks( 0 )} )
    )
);

Code Explanation:

1. Open table.
2. Set graph size.
3. Define X variables.
4. Define additional X variable.
5. Define Y variables.
6. Define overlay variable.
7. Create area element.
8. Close outline box.
9. Set Y axis scale.
10. Adjust minor ticks.

Example 2091

Summary: Creates a variability chart with nested factors using Graph Builder, displaying standard deviation charts and formatting legend and area style.

Code:

dt = Open("data_table.jmp");
Graph Builder(
    Size( 302, 182 ),
    Show Control Panel( 0 ),
    Variables( X( :height ), Y( :weight ), Overlay( :sex ) ),
    Elements( Area( X, Y, Legend( 9 ), Area Style( "Range" ) ) ),
    SendToReport( Dispatch( {}, "height", ScaleBox, {Format( "Best", 12 ), Min( 50 )} ) )
);

Code Explanation:

1. Open data table.
2. Create Graph Builder window.
3. Set window size.
4. Hide control panel.
5. Assign variables: X=height, Y=weight.
6. Overlay by sex.
7. Add area element.
8. Format legend.
9. Set area style to range.
10. Adjust height scale format and minimum.

Example 2092

Summary: Creates a variability chart with nested factors using Graph Builder, displaying standard deviation charts and formatting scales.

Code:

dt = Open("data_table.jmp");
Xcol = "weight";
Ycol = "height";
var = 62.5;
gb = dt << Graph Builder(
    Show Control Panel( 0 ),
    Variables( X( Column( Xcol ) ), Y( Column( Ycol ) ) ),
    Elements( Points( X, Y, Legend( 1 ), Jitter( 1 ) ), Smoother( X, Y, Legend( 3 ) ) ),
    SendToReport(
        Dispatch( {}, Xcol, ScaleBox, {Format( "Fixed Dec", 12, 1 )} ),
        Dispatch( {}, Ycol, ScaleBox, {Format( "Fixed Dec", 12, 1 ), Add Ref Line( var, Solid, "Dark Red", "", 2 )} )
    )
);
Close( dt, "nosave" );
New Window( "Example",
    gb = Graph Box(
        Frame Size( 300, 300 ),
        XName( "X, Currency" ),
        YName( "Y" ),
        Marker( Marker State( 3 ), [11 44 77], [75 25 50] );
        Pen Color( "Blue" );
        Line( [10 30 70], [88 22 44] );
    )
);
unitsX = "Dollars";
gb << Set XName( "X, " || unitsX );
unitsY = "Gallons";
gb << Set YName( "Y, " || unitsY );
gb << close window();

Code Explanation:

1. Open data table.
2. Assign X column name.
3. Assign Y column name.
4. Define variable value.
5. Create Graph Builder object.
6. Hide control panel.
7. Set X and Y variables.
8. Add points and smoother elements.
9. Format X scale.
10. Format Y scale and add reference line.
11. Close data table without saving.
12. Create new window.
13. Create Graph Box within window.
14. Set frame size.
15. Set X axis name.
16. Set Y axis name.
17. Draw markers.
18. Set pen color.
19. Draw line.
20. Assign X units.
21. Update X axis name with units.
22. Assign Y units.
23. Update Y axis name with units.
24. Close graph box window.

Example 2093

Summary: Creates a variability chart with nested factors using Graph Builder, formatting X and Y scales, and adding a reference line.

Code:

dt = Open("data_table.jmp");
Xcol = "weight";
Ycol = "height";
var = 62.5;
gb = dt << Graph Builder(
    Show Control Panel( 0 ),
    Variables( X( Column( Xcol ) ), Y( Column( Ycol ) ) ),
    Elements( Points( X, Y, Legend( 1 ), Jitter( 1 ) ), Smoother( X, Y, Legend( 3 ) ) ),
    SendToReport(
        Dispatch( {}, Xcol, ScaleBox, {Format( "Fixed Dec", 12, 1 )} ),
        Dispatch( {}, Ycol, ScaleBox, {Format( "Fixed Dec", 12, 1 ), Add Ref Line( var, Solid, "Dark Red", "", 2 )} )
    )
);

Code Explanation:

1. Open table.
2. Set X column.
3. Set Y column.
4. Define variable value.
5. Create Graph Builder.
6. Hide control panel.
7. Assign variables.
8. Add points element.
9. Add smoother element.
10. Format X scale.
11. Format Y scale.
12. Add reference line.

Example 2094

Summary: Creates a variability chart with nested factors using Graph Builder, configuring variables and elements to display standard deviation charts.

Code:

dt = Open( "$SAMPLE_DATA/data_table.jmp", invisible );
gb = dt << Graph Builder(
    Show Control Panel( 0 ),
    Variables( X( :age, Size( 23 ) ), Y( :height, Size( 37 ) ), Y( :weight, Position( 1 ), Size( 37 ), Side( "Right" ) ) ),
    Elements( Points( X, Y( 1 ), Legend( 1 ), Jitter( 1 ) ), Points( X, Y( 2 ), Legend( 3 ), Jitter( 1 ) ) )
);
framebox = Report( gb )[framebox( 1 )];
framebox << X Axis(
    Min( -2 ),
    Max( 7 ),
    Inc( 2 ),
    Minor Ticks( 0 ),
    Add Ref Line( 5, Solid, "Blue", "Age of Reason", 2 ),
    Show Major Ticks( 0 ),
    Show Minor Ticks( 0 ),
    Rotated Labels( "Vertical" )
);
xa = Report( gb )[axisbox( 1 )] << get script;
xa_list = {};
For( i = 1, i <= 9, i++,
    Insert Into( xa_list, xa[i] )
);
framebox << Close Window;

Code Explanation:

1. Open data table.
2. Create graph builder object.
3. Configure graph variables.
4. Add points elements to graph.
5. Retrieve framebox from report.
6. Set X axis properties.
7. Get X axis script.
8. Initialize empty list.
9. Loop through script elements.
10. Close graph window.

Example 2095

Summary: Creates a variability chart with nested factors using Graph Builder, configuring X and Y variables, adding points elements, and modifying Y Axis properties.

Code:

dt = Open( "$SAMPLE_DATA/data_table.jmp", invisible );
gb = dt << Graph Builder(
    Show Control Panel( 0 ),
    Variables( X( :age, Size( 23 ) ), Y( :height, Size( 37 ) ), Y( :weight, Position( 1 ), Size( 37 ), Side( "Right" ) ) ),
    Elements( Points( X, Y( 1 ), Legend( 1 ), Jitter( 1 ) ), Points( X, Y( 2 ), Legend( 3 ), Jitter( 1 ) ) )
);
framebox = Report( gb )[framebox( 1 )];
framebox << Y Axis(
    Add Ref Line( 61.25, Solid, "Medium Dark Green", "", 2 ),
    Show Major Grid( 1 ),
    Show Minor Grid( 1 ),
    Format( "Fixed Dec", 5, 2 ),
    Rotated Labels( "Perpendicular" )
);
ya = Report( gb )[axisbox( 2 )] << Get Script;
framebox << close window;

Code Explanation:

1. Open data table;
2. Create Graph Builder object.
3. Configure Graph Builder settings.
4. Add X and Y variables.
5. Add Points elements.
6. Retrieve framebox object.
7. Modify Y Axis properties.
8. Add reference line.
9. Enable major grid.
10. Enable minor grid.

Example 2096

Summary: Creates a variability chart with nested factors using Graph Builder, configuring right Y axis and displaying standard deviation charts.

Code:

dt = Open( "$SAMPLE_DATA/data_table.jmp", invisible );
gb = dt << Graph Builder(
    Show Control Panel( 0 ),
    Variables( X( :age, Size( 23 ) ), Y( :height, Size( 37 ) ), Y( :weight, Position( 1 ), Size( 37 ), Side( "Right" ) ) ),
    Elements( Points( X, Y( 1 ), Legend( 1 ), Jitter( 1 ) ), Points( X, Y( 2 ), Legend( 3 ), Jitter( 1 ) ) )
);
framebox = Report( gb )[framebox( 1 )];
framebox << Right Y Axis( Rotated Labels( "Angled" ), Scale( "Linear" ), Add Ref Line( 125, dashed, "red", "", 2 ) );
rya = Report( gb )[axisbox( 3 )] << Get Script;
framebox << Close Window;

Code Explanation:

1. Open data table.
2. Create Graph Builder object.
3. Hide control panel.
4. Set X variable.
5. Set first Y variable.
6. Set second Y variable.
7. Add points for first Y.
8. Add points for second Y.
9. Access framebox.
10. Configure right Y axis.

Example 2097

Summary: Creates a box plot to visualize the relationship between Height and Age, grouped by Sex, using Graph Builder.

Code:

dt = Open("data_table.jmp");
obj = dt << Graph Builder( Variables( X( :Sex ), Y( :Height ), Group X( :Age ) ), Elements( Box Plot( X, Y ) ) );
obj << Launch Analysis;
Window( "Fit Model" ) << Close Window;

Code Explanation:

1. Open data table.
2. Create Graph Builder object.
3. Set X variable to Sex.
4. Set Y variable to Height.
5. Group X by Age.
6. Add Box Plot element.
7. Launch analysis.
8. Close "Fit Model" window.

Example 2098

Summary: Creates a nested variability chart with line segments, utilizing Graph Builder to configure variables and elements.

Code:

dt = Open("data_table.jmp");
gbs = dt << Graph Builder(
    Show Control Panel( 0 ),
    Variables( X( :height ), Y( :weight ), Overlay( :age ) ),
    Elements( Line( X, Y, Legend( 4 ), Row order( 0 ), Summary Statistic( "Mean" ) ) )
);
frame = Report( gbs )[FrameBox( 1 )];
seg = (frame << Find Seg( "Line Seg" ));
seg << Set selectable( 0 );
seg << Set Selectable( 1 );

Code Explanation:

1. Open data table;
2. Create graph builder object.
3. Configure graph variables.
4. Add line element.
5. Retrieve report frame.
6. Find line segment.
7. Disable selection.
8. Enable selection.

Example 2099

Summary: Creates a line graph to visualize the relationship between height and weight, utilizing Graph Builder to hide the control panel and set X and Y variables.

Code:

dt = Open("data_table.jmp");
gb = dt << Graph Builder(
    Show Control Panel( 0 ),
    Variables( X( :height ), Y( :weight ) ),
    Elements( Line( X, Y, Legend( 4 ), Row order( 0 ), Summary Statistic( "Mean" ) ) )
);
frame = Report( gb )[FrameBox( 1 )];
seg = (frame << Find Seg( "Line Seg" ));
sel1 = seg << Get Selectable;
seg << Set Selectable( 0 );
sel2 = seg << Get Selectable;

Code Explanation:

1. Open table.
2. Create graph builder.
3. Hide control panel.
4. Set X and Y variables.
5. Add line element.
6. Get first frame.
7. Find line segment.
8. Get initial selectability.
9. Disable selectability.
10. Get updated selectability.

Example 2100

Summary: Creates a bar chart with side-by-side bars to visualize the mean height by age group, utilizing Graph Builder and hiding the control panel.

Code:

dt = Open("data_table.jmp");
gb = Graph Builder(
    Show Control Panel( 0 ),
    Variables( X( :age ), Y( :height ) ),
    Elements( Bar( X, Y, Legend( 2 ), Bar Style( "Side by side" ), Summary Statistic( "Mean" ) ) )
);
rpt = gb << report;

Code Explanation:

1. Open data_table data
2. Create Graph Builder object.
3. Hide control panel.
4. Set X variable to age.
5. Set Y variable to height.
6. Add bar element.
7. Set bar style to side by side.
8. Use mean for summary statistic.
9. Generate report.
10. Assign report to rpt.

Example 2101

Summary: Creates a bar chart with nested factors using Graph Builder, setting missing value codes and generating a report.

Code:

dt = Open("data_table.jmp");
obj = Graph Builder( Show Control Panel( 0 ), Variables( X( :Day of Week ), Overlay( :Airline ) ), Elements( Bar( X, Legend( 2 ) ) ) );
:Airline << Set Property( "Missing Value Codes", {"Southwest"} );
obj2 = obj << Redo Analysis;
rpt2 = obj2 << Report;
expr2 = rpt2[LegendBox( 1 )] << Get Journal;
p = "Southwest";
ans = Pat Match( expr2, p );

Code Explanation:

1. Open data table;
2. Create Graph Builder object.
3. Configure Graph Builder settings.
4. Set missing value code for "Airline".
5. Redo analysis with updated settings.
6. Generate report from analysis.
7. Extract legend box content.
8. Convert legend content to journal.
9. Define search pattern.
10. Search journal for pattern.

Example 2102

Summary: Analyze and visualize nested factors using Graph Builder, Principal Components, and report generation to identify patterns in data.

Code:

dt = Open("data_table.jmp");
obj = Graph Builder( Show Control Panel( 0 ), Variables( X( :Day of Week ), Overlay( :Airline ) ), Elements( Bar( X, Legend( 2 ) ) ) );
:Airline << Set Property( "Missing Value Codes", {"Southwest"} );
obj2 = obj << Redo Analysis;
rpt2 = obj2 << Report;
expr2 = rpt2[LegendBox( 1 )] << Get Journal;
p = "Southwest";
ans = Pat Match( expr2, p );
dt = Open("data_table.jmp");
:"Age (years)" << Set Values( {99, 99, 99} );
obj = Principal Components(
    Y(
        :Name( "Age (years)" ), :Name( "Weight (lbs)" ), :Name( "Height (inches)" ), :Name( "Neck circumference (cm)" ),
        :Name( "Chest circumference (cm)" ), :Name( "Abdomen circumference (cm)" ), :Name( "Hip circumference (cm)" ),
        :Name( "Thigh circumference (cm)" ), :Name( "Knee circumference (cm)" ), :Name( "Ankle circumference (cm)" ),
        :Name( "Biceps (extended) circumference (cm)" ), :Name( "Forearm circumference (cm)" ), :Name( "Wrist circumference (cm)" )
    ),
    Estimation Method( "Row-wise" ),
    "on Correlations",
    Eigenvectors( 1 ),
    Scree Plot( 1 ),
    Arrow Lines( 1 ),
    SendToReport(
        Dispatch( {"Summary Plots"}, "PCA Summary Plots", FrameBox, {Frame Size( 49, 37 )} ),
        Dispatch( {"Summary Plots"}, "PCA Summary Plots", FrameBox( 2 ), {Frame Size( 52, 37 )} )
    )
);
rpt1 = obj << Report;
expr1 = (rpt1 << get journal());
:"Age (years)" << Set Property( "Missing Value Codes", 99 );
obj2 = obj << Redo Analysis;
rpt2 = obj2 << Report;
expr2 = (rpt2 << get journal());
ans = Equal( expr1, expr2 );

Code Explanation:

1. Open data table;
2. Create Graph Builder object.
3. Set missing value code for Airline.
4. Redo analysis on Graph Builder.
5. Generate report from Graph Builder.
6. Extract journal from report.
7. Define pattern for matching.
8. Match pattern in extracted journal.
9. Open data table;
10. Set values to missing for Age.
11. Perform Principal Components analysis.
12. Generate report from PCA.
13. Extract journal from PCA report.
14. Set missing value code for Age.
15. Redo analysis on PCA.
16. Generate new report from PCA.
17. Extract new journal from PCA report.
18. Compare original and new journals.

Example 2103

Summary: Creates a variability chart with nested factors using Graph Builder, configuring X and Y variables, group transformations, overlay, color, and size settings.

Code:

Open("data_table.jmp");
Graph Builder(
    Variables(
        X( Transform Column( "Last[Name]", Character, Formula( Word( -1, :Name ) ) ) ),
        Y( Transform Column( "Square Root[Serving/pkg]", Formula( Sqrt( :Name( "Serving/pkg" ) ) ) ) ),
        Group X( Transform Column( "First[Brand]", Character, Formula( Word( 1, :Brand ) ) ) ),
        Group Y( Transform Column( "Oz/pkg^2", Formula( :Name( "Oz/pkg" ) * :Name( "Oz/pkg" ) ) ) ),
        Overlay( Transform Column( "Log[Calories]", Formula( Log( :Calories ) ) ) ),
        Color( Transform Column( "Log10[Total fat g]", Formula( Log10( :Total fat g ) ) ) ),
        Size( Transform Column( "10^Saturated fat g", Formula( 10 ^ :Saturated fat g ) ) )
    ),
    Elements( Points( X, Y, Legend( 1 ), Jitter( 1 ) ) )
);

Code Explanation:

1. Open data table;
2. Launch Graph Builder.
3. Set X variable transformation.
4. Set Y variable transformation.
5. Set Group X transformation.
6. Set Group Y transformation.
7. Add Overlay transformation.
8. Add Color transformation.
9. Add Size transformation.
10. Plot points with jitter.

Example 2104

Summary: Creates a variability chart with nested factors using operator and part configurations, displaying standard deviation charts.

Code:

dt = Open("data_table.jmp");
Graph Builder(
    Variables(
        Color( Transform Column( "Concatenate[Development Level]", Character, Formula( Concat( :Development Level ) ) ) ),
        Shape( Transform Column( "Concatenate[Territory]", Character, Formula( Concat( :Territory ) ) ) )
    ),
    Elements( Map Shapes( Legend( 14 ), Summary Statistic( "Mean" ), Show Missing Shapes( 0 ) ) )
);

Code Explanation:

1. Open data table;
2. Create Graph Builder object.
3. Set color variable.
4. Transform Development Level to character.
5. Set shape variable.
6. Transform Territory to character.
7. Add Map Shapes element.
8. Enable legend for shapes.
9. Use mean summary statistic.
10. Hide missing shapes.

Example 2105

Summary: Creates two bar charts with nested factors using Graph Builder, displaying sex and height variables.

Code:

dt = Open("data_table.jmp");
gb = Graph Builder( Variables( X( :height ), Y( :sex ) ), Elements( Bar( X, Y ) ) );
rpt = gb << report;
gb2 = Graph Builder( Variables( X( :sex ), Y( :height ) ), Elements( Bar( X, Y, Legend( 4 ) ) ) );
rpt2 = gb2 << report;

Code Explanation:

1. Open data table;
2. Create Graph Builder.
3. Set X to height.
4. Set Y to sex.
5. Add bar element.
6. Generate report.
7. Create second Graph Builder.
8. Set X to sex.
9. Set Y to height.
10. Add bar element with legend.

Example 2106

Summary: Creates a pie chart to visualize the relationship between age and height, with transparent legend settings.

Code:

dt = Open("data_table.jmp");
gb = Graph Builder(
    Show Control Panel( 0 ),
    Variables( X( :age ), Y( :height ) ),
    Elements( Pie( X, Y, Legend( 4 ) ) ),
    SendToReport( Dispatch( {}, "400", ScaleBox, {Legend Model( 4, Properties( 0, {Transparency( 0.5 )} ) )} ) )
);
rpt = gb << report;

Code Explanation:

1. Open data table;
2. Create Graph Builder object.
3. Hide control panel.
4. Set X variable to "age".
5. Set Y variable to "height".
6. Add pie chart element.
7. Configure legend properties.
8. Adjust transparency of legend.
9. Generate report.
10. Assign report to variable.

Example 2107

Summary: Creates a variability chart with nested factors using Graph Builder, specifying window size, X and Y variables, and jitter settings.

Code:

dt2 = Open("data_table.jmp");
gb2 = dt2 << Graph Builder(
    Size( 702, 600 ),
    Variables( X( :location_type ), Y( :closed_date ), Y( :Time, Position( 1 ) ) ),
    Elements( Points( X, Y( 1 ), Y( 2 ), Legend( 10 ), Jitter( "Hex Grid" ), Jitter Side( "Ordinal" ), Jitter Smooth( 1 ) ) )
);

Code Explanation:

1. Open data_table data
2. Launch Graph Builder.
3. Set window size.
4. Define X variable.
5. Define first Y variable.
6. Define second Y variable.
7. Add points element.
8. Set jitter type.
9. Set jitter side.
10. Set jitter smoothness.

Example 2108

Summary: Creates a variability chart with nested factors using operator and part configurations, displaying standard deviation charts.

Code:

dt = Open("data_table.jmp");
gb = Graph Builder(
    Show Control Panel( 0 ),
    Variables( X( :Weight ), Y( :Oxy ), Overlay( :Sex ) ),
    Elements( Points( X, Y, Legend( 1 ), Jitter( 1 ) ), Ellipse( X, Y, Legend( 3 ), Coverage( "90%" ) ) )
);
rpt = gb << report;
Close( dt, nosave );
cert_levels = {levels( "12", "13", "14", "15", "16", "17" ), levels( "12", "13", "14", "15", "16", "17" )};

Code Explanation:

1. Open data table;
2. Create Graph Builder object.
3. Hide control panel.
4. Set X, Y variables.
5. Overlay by Sex.
6. Add points element.
7. Add ellipse element.
8. Generate report.
9. Close dataset without saving.
10. Define certificate levels.

Example 2109

Summary: Creates a graph builder object to visualize sex and age variables, utilizing Graph Builder's overlay feature.

Code:

dt = Open("data_table.jmp");
gb = Graph Builder( Show Control Panel( 0 ), Variables( X( :sex ), Overlay( :age ) ), Elements( Points( X, Legend( 3 ) ) ) );
rpt = gb << report;

Code Explanation:

1. Open data table;
2. Create graph builder object.
3. Hide control panel.
4. Set X variable to sex.
5. Overlay age variable.
6. Add points element.
7. Assign legend to points.
8. Generate graph report.

Example 2110

Summary: Creates a variability chart with nested factors using Graph Builder, hiding the control panel and overlaying by age.

Code:

dt = Open("data_table.jmp");
gb = Graph Builder(
    Show Control Panel( 0 ),
    Variables( X( :sex ), Y( :height ), Overlay( :age ) ),
    Elements( Points( X, Y, Legend( 4 ) ) )
);
rpt = gb << report;
Close( dt, nosave );
cert_markerF = {"Marker (F)"};
cert_markerM = {"Marker (M)"};

Code Explanation:

1. Open data table;
2. Create Graph Builder object.
3. Hide control panel.
4. Set X to sex, Y to height.
5. Overlay by age.
6. Add points element.
7. Generate report object.
8. Close dataset without saving.
9. Define cert_markerF list.
10. Define cert_markerM list.

Example 2111

Summary: Creates a variability chart with nested factors using Graph Builder, featuring points and smoother elements.

Code:

dt = Open("data_table.jmp");
gb = Graph Builder(
    Show Control Panel( 0 ),
    Size( 600, 600 ),
    Variables( X( :Year ), Y( :SAT Math ), Overlay( :State ) ),
    Elements( Points( X, Y, Legend( 1 ), Jitter( 1 ) ), Smoother( X, Y, Legend( 2 ) ) )
);
rpt = gb << report;

Code Explanation:

1. Open data table.
2. Create Graph Builder object.
3. Hide control panel.
4. Set graph size.
5. Define X, Y, and overlay variables.
6. Add points element with jitter.
7. Add smoother element.
8. Generate graph report.

Example 2112

Summary: Creates a variability chart with nested factors using Graph Builder, displaying standard deviation charts and configuring points and ellipse elements.

Code:

dt = Open("data_table.jmp");
gb = Graph Builder(
    Show Control Panel( 0 ),
    Variables( X( :Weight ), Y( :Oxy ), Overlay( :Sex ) ),
    Elements( Points( X, Y, Legend( 1 ), Jitter( 1 ) ), Ellipse( X, Y, Legend( 3 ), Coverage( "90%" ) ) )
);
rpt = gb << report;

Code Explanation:

1. Open data table;
2. Create Graph Builder object.
3. Hide control panel.
4. Set X variable to Weight.
5. Set Y variable to Oxy.
6. Overlay by Sex.
7. Add points element with jitter.
8. Add ellipse element with 90% coverage.
9. Generate graph builder report.
10. Assign report to rpt variable.

Example 2113

Summary: Creates a graph report with nested factors using Graph Builder, displaying points and overlaying age on height for sex.

Code:

dt = Open("data_table.jmp");
gb = Graph Builder(
    Show Control Panel( 0 ),
    Variables( X( :sex ), Y( :height ), Overlay( :age ) ),
    Elements( Points( X, Y, Legend( 4 ) ) )
);
rpt = gb << report;

Code Explanation:

1. Open data table.
2. Create Graph Builder object.
3. Hide control panel.
4. Set X variable to sex.
5. Set Y variable to height.
6. Set overlay variable to age.
7. Add points element.
8. Generate graph report.

Example 2114

Summary: Creates a variability chart with nested factors using operator and part configurations, displaying standard deviation charts.

Code:

dt = Open("data_table.jmp");
gb = Graph Builder( Variables( X( :height ), Overlay( :sex ), Color( :height ) ), Elements( Points( X, Legend( 1 ), Jitter( 1 ) ) ) );
rpt = gb << report;

Code Explanation:

1. Open data table.
2. Create Graph Builder object.
3. Set X variable: height.
4. Add overlay for sex.
5. Color points by height.
6. Add points element.
7. Enable jitter for points.
8. Generate graph report.

Example 2115

Summary: Creates a variability chart with nested factors using operator and part configurations, displaying standard deviation charts.

Code:

dt = Open("data_table.jmp");
gb = Graph Builder(
    Size( 450, 320 ),
    Show Control Panel( 0 ),
    Variables( Color( :birth ), Shape( :country ) ),
    Elements( Map Shapes( Legend( 1 ), Summary Statistic( "Mean" ) ) )
);
rpt = gb << report;

Code Explanation:

1. Open data table.
2. Create Graph Builder object.
3. Set graph size.
4. Hide control panel.
5. Define color and shape variables.
6. Add map shapes element.
7. Use mean as summary statistic.
8. Generate graph report.

Example 2116

Summary: Creates a variability chart with nested factors using Graph Builder, displaying standard deviation charts and smoothing data points.

Code:

dt = Open("data_table.jmp");
obj = dt << Graph Builder(
    Size( 660, 558 ),
    Show Control Panel( 0 ),
    Variables( X( :weight ), Y( :height ) ),
    Elements(
        Points( X, Y, Legend( 1 ) ),
        Smoother( X, Y, Legend( 2 ), Method( "P-Spline" ), Lambda( 0.01 ), Shape Constraint( "Non-descending" ) )
    )
);
rpt = obj << Report;

Code Explanation:

1. Open data table.
2. Create Graph Builder object.
3. Set window size.
4. Hide control panel.
5. Define X and Y variables.
6. Add points element.
7. Add smoother element.
8. Set smoother method.
9. Set lambda value.
10. Set shape constraint.

Example 2117

Summary: Creates a variability chart with nested factors using Graph Builder, configuring smoother method and lambda value, and displaying standard deviation charts.

Code:

dt = Open("data_table.jmp");
obj = dt << Graph Builder(
    Size( 662, 548 ),
    Show Control Panel( 0 ),
    Variables( X( :Week of Year ), Y( :TMAX ) ),
    Elements(
        Points( X, Y, Legend( 7 ) ),
        Smoother( X, Y, Legend( 8 ), Method( "P-Spline" ), Lambda( 0.01 ), Shape Constraint( "Cycle" ) )
    ),
    Local Data Filter( Add Filter( columns( :ID ), Where( :ID == "Grand Canyon National Park, AZ" ), Display( :ID, N Items( 15 ) ) ) )
);
rpt = obj << Report;

Code Explanation:

1. Open data table.
2. Create Graph Builder object.
3. Set graph size.
4. Hide control panel.
5. Define X and Y variables.
6. Add points element.
7. Add smoother element.
8. Configure smoother method.
9. Set smoother lambda value.
10. Apply shape constraint.

Example 2118

Summary: Creates a variability chart with nested factors using Graph Builder, setting X to HDL and Y to LDL, and displaying standard deviation charts.

Code:

dt = Open("data_table.jmp");
obj = dt << Graph Builder(
    Variables( X( :HDL ), Y( :LDL ) ),
    Elements( Points( X, Y, Legend( 3 ) ), Smoother( X, Y, Legend( 4 ), Method( "Savitzky-Golay" ), Confidence of Fit( 1 ) ) )
);

Code Explanation:

1. Open data table;
2. Create Graph Builder object.
3. Set X variable to HDL.
4. Set Y variable to LDL.
5. Add points element.
6. Add smoother element.
7. Use Savitzky-Golay method.
8. Enable confidence of fit.
9. Assign legend 3 to points.
10. Assign legend 4 to smoother.

Example 2119

Summary: Creates a graph builder with nested factors, displaying standard deviation charts and modifying legend items.

Code:

Open("data_table.jmp");
gb = Graph Builder(
    Variables( X( :height ), Y( :weight ), Overlay( :sex ), Color( :age ) ),
    Elements( Points( X, Y, Legend( 1 ) ), Smoother( X, Y, Legend( 2 ) ) )
);
lgnd = gb << Get Legend Display;
items = lgnd << Get Items;
types = Transform Each( {item}, items, item << Get Type );
labels = Transform Each( {item}, items, item << Get Label );
positions = Transform Each( {item}, items, item << Get Position );
hLineF = lgnd << Get Item( 2, 1 );
hLineF << Set Label( "Granular Control" );
markerColors = Filter Each( {item}, items, item << Get Type == "Mark Color" );
For Each( {item, index}, markerColors, item << Set Label( index ) );
labels = Transform Each( {item}, items, item << Get Label );
For Each( {item}, items, If( item << Get Type == "Marker", item << Set Visible( 0 ) ) );
positions = Transform Each( {item}, items, item << Get Position );
For Each( {item}, items,
    If( item << Get Type == "Marker",
        If( item << Get Label == "F",
            item << Set Visible( 1 );
            item << Set Label( "I'm visible!" );
        ,
            item << Set Label( "I'm invisible." )
        )
    )
);
positions = Transform Each( {item}, items, item << Get Position );

Code Explanation:

1. Open data table;
2. Create Graph Builder object.
3. Assign variables and elements.
4. Retrieve legend display.
5. Get legend items.
6. Extract item types.
7. Extract item labels.
8. Extract item positions.
9. Modify smoother label.
10. Filter marker colors.
11. Set marker labels.
12. Hide all markers.
13. Show and label specific markers.
14. Update marker positions.

Example 2120

Summary: Creates a graph builder with nested factors using operator and part configurations, displaying standard deviation charts.

Code:

dt = Open("data_table.jmp");
gb = Graph Builder(
    Variables( X( :height ), Y( :weight ), Overlay( :sex ), Color( :age ) ),
    Elements( Points( X, Y, Legend( 1 ) ), Smoother( X, Y, Legend( 2 ) ) )
);
lgnd = gb << Get Legend Display;
items = lgnd << Get Items;
types = Transform Each( {item}, items, item << Get Type );
labels = Transform Each( {item}, items, item << Get Label );
positions = Transform Each( {item}, items, item << Get Position );
hLineF = lgnd << Get Item( 2, 1 );
hLineF << Set Label( "Granular Control" );
markerColors = Filter Each( {item}, items, item << Get Type == "Mark Color" );
For Each( {item, index}, markerColors, item << Set Label( index ) );
labels = Transform Each( {item}, items, item << Get Label );
For Each( {item}, items, If( item << Get Type == "Marker", item << Set Visible( 0 ) ) );
positions = Transform Each( {item}, items, item << Get Position );
For Each( {item}, items,
    If( item << Get Type == "Marker",
        If( item << Get Label == "F",
            item << Set Visible( 1 );
            item << Set Label( "I'm visible!" );
        ,
            item << Set Label( "I'm invisible." )
        )
    )
);
positions = Transform Each( {item}, items, item << Get Position );

Code Explanation:

1. Open data table.
2. Create Graph Builder object.
3. Set X, Y, Overlay, and Color variables.
4. Add Points and Smoother elements.
5. Retrieve legend display.
6. Get legend items.
7. Extract item types.
8. Extract item labels.
9. Extract item positions.
10. Modify specific legend item label.
11. Filter marker color items.
12. Set labels for marker colors.
13. Hide all marker items.
14. Show and modify specific marker labels.

Example 2121

Summary: Creates a graph builder object to visualize and analyze data with nested factors, utilizing Graph Builder's Points and Smoother elements.

Code:

Open("data_table.jmp");
gb = Graph Builder(
    Show Control Panel( 0 ),
    Variables( X( :year ), Y( :pop ) ),
    Elements( Points( X, Y, Legend( 1 ) ), Smoother( X, Y, Legend( 2 ) ) ),
    SendToReport(
        Dispatch( {}, "pop", ScaleBox, {Scale( "Log" ), Format( "Best", 12 ), Min( 0.1 ), Max( 300 ), Inc( 1 ), Minor Ticks( 8 )} )
    )
);
rpt = gb << report;

Code Explanation:

1. Open data table.
2. Create graph builder object.
3. Hide control panel.
4. Set X and Y variables.
5. Add points element.
6. Add smoother element.
7. Modify Y-axis scale.
8. Set axis format.
9. Define axis minimum.
10. Define axis maximum.

Example 2122

Summary: Creates a variability chart with nested factors using Graph Builder, displaying standard deviation charts and customizing the height axis.

Code:

dt = Open("data_table.jmp");
gb = Graph Builder(
    Size( 426, 378 ),
    Show Control Panel( 0 ),
    Variables( X( :height ), Y( :weight ) ),
    Elements( Points( X, Y, Legend( 1 ) ), Smoother( X, Y, Legend( 2 ) ) ),
    SendToReport( Dispatch( {}, "height", ScaleBox, {Min( 50 ), Max( 72.5 ), Inc( 25 ), Minor Ticks( 0 )} ) )
);

Code Explanation:

1. Open data table.
2. Create Graph Builder object.
3. Set graph size.
4. Hide control panel.
5. Define X and Y variables.
6. Add points element.
7. Add smoother element.
8. Customize height axis.
9. Set minimum value.
10. Set maximum value.

Example 2123

Summary: Creates a bar chart with side-by-side bars to display percentage of total by age, utilizing Graph Builder and hiding the control panel.

Code:

dt = Open("data_table.jmp");
gb = Graph Builder(
    Show Control Panel( 0 ),
    Variables( X( :height ), Y( :height ), Group X( :age ) ),
    Elements( Bar( X, Y, Legend( 3 ), Bar Style( "Side by side" ), Summary Statistic( "% of Total" ) ) )
);

Code Explanation:

1. Open data table;
2. Create Graph Builder object.
3. Hide control panel.
4. Set X variable to height.
5. Set Y variable to height.
6. Group X by age.
7. Add bar element.
8. Set legend to 3.
9. Use side-by-side bar style.
10. Display percentage of total.

Example 2124

Summary: Creates a scatter plot with a linear fit line to visualize the relationship between height and weight, utilizing Graph Builder.

Code:

dt = Open("data_table.jmp");
gb = Graph Builder(
    Show Control Panel( 0 ),
    Variables( X( :height ), Y( :weight ) ),
    Elements(
        Points( X, Y, Legend( 1 ) ),
        Line Of Fit(
            X,
            Y,
            Legend( 3 ),
            Confidence of Fit( 0 ),
            Confidence of Prediction( 0 ),
            Degree( "Linear" ),
            Root Mean Square Error( 0 )
        )
    ),
    SendToReport(
        Dispatch( {}, "height", ScaleBox, {Add Ref Line( 60, "Dashed", "Medium Dark Blue", "Reference Line", 3 )} ),
        Dispatch( {}, "weight", ScaleBox, {Min( 58.4020618556701 ), Max( 198.40206185567 ), Inc( 20 ), Minor Ticks( 0 )} ),
        Dispatch( {}, "400", ScaleBox, {Legend Model( 3, Properties( 0, {Line Color( 3 ), Fill Color( 0 )} ) )} )
    )
);
rpt = gb << report;

Code Explanation:

1. Open data table;
2. Create Graph Builder object.
3. Hide control panel.
4. Set X variable to height.
5. Set Y variable to weight.
6. Add points element.
7. Add linear fit line.
8. Remove confidence intervals.
9. Remove prediction intervals.
10. Set reference line at height 60.

Example 2125

Summary: Creates a variability chart with nested factors using Graph Builder, displaying standard deviation charts and overlaying by sex.

Code:

dt = Open("data_table.jmp");
obj = Graph Builder(
    Variables( X( :height ), Y( :weight ), Overlay( :sex ) ),
    Elements( Points( X, Y, Legend( 1 ) ), Contour( X, Y, Legend( 3 ), Number of Levels( 0 ) ) )
);
rpt = obj << report;

Code Explanation:

1. Open data table.
2. Create Graph Builder object.
3. Set X variable to height.
4. Set Y variable to weight.
5. Overlay by sex.
6. Add points element.
7. Add contour element.
8. Set contour legend.
9. Set number of levels to 0.
10. Generate report.

Example 2126

Summary: Creates a graph builder with nested factors, displaying standard deviation charts and confidence intervals for linear fit lines.

Code:

dt = Open("data_table.jmp");
gb = Graph Builder(
    Show Control Panel( 0 ),
    Variables( X( :height ), Y( :weight ) ),
    Elements(
        Points( X, Y, Legend( 1 ) ),
        Line Of Fit(
            X,
            Y,
            Legend( 3 ),
            Confidence of Fit( 1 ),
            Confidence of Prediction( 1 ),
            Degree( "Linear" ),
            Root Mean Square Error( 0 )
        )
    ),
    SendToReport(
        Dispatch( {}, "400", ScaleBox,
            {Legend Model(
                3,
                Base( 1, 0, 0 ),
                Base( 2, 0, 0 ),
                Properties( 1, {Fill Color( 19 ), Transparency( 0.7 )} ),
                Properties( 2, {Fill Color( 36 ), Transparency( 0.4 )} )
            )}
        )
    )
);
rpt = gb << report;
Set Preference( default );

Code Explanation:

1. Open data table;
2. Create Graph Builder object.
3. Hide control panel.
4. Set X variable to height.
5. Set Y variable to weight.
6. Add points element.
7. Add linear fit line.
8. Enable confidence of fit.
9. Enable confidence of prediction.
10. Set report preferences.

Example 2127

Summary: Creates a mosaic chart with nested factors using Graph Builder, hiding the control panel and configuring legend properties.

Code:

dt = Open("data_table.jmp");
gb = Graph Builder(
    Show Control Panel( 0 ),
    Variables( X( :age ), Y( :height ) ),
    Elements( Mosaic( X, Y, Legend( 4 ) ) ),
    SendToReport(
        Dispatch( {}, "400", ScaleBox,
            {Legend Model( 4, Properties( 0, {Fill Pattern( "diamond" )} ), Properties( 16, {Fill Pattern( "grid heavy" )} ) )}
        )
    )
);
 Preferences( Factory Default );

Code Explanation:

1. Open data table;
2. Create Graph Builder object.
3. Hide control panel.
4. Set X variable to age.
5. Set Y variable to height.
6. Add Mosaic element.
7. Configure legend properties.
8. Set fill pattern for first property.
9. Set fill pattern for second property.
10. Reset platform preferences.

Example 2128

Summary: Creates a graph builder with nested factors using operator and part configurations, displaying standard deviation charts.

Code:

dt = Open("data_table.jmp");
gb = Graph Builder(
    Show Control Panel( 0 ),
    Variables( X( :weight ), Y( :height ), Overlay( :age ) ),
    Elements( Line( X, Y, Legend( 3 ), Row order( 0 ), Summary Statistic( "Mean" ) ) )
);
gb << journal window;
Current Journal() << save journal( "$TEMP\GBjournal.jrn" );
Current Journal() << close window;

Code Explanation:

1. Open table.
2. Create Graph Builder object.
3. Hide control panel.
4. Set X, Y, and overlay variables.
5. Add line element.
6. Display graph builder window.
7. Save journal to file.
8. Close journal window.

Example 2129

Summary: Creates a variability chart with nested factors using Graph Builder, displaying standard deviation charts and hiding the control panel.

Code:

dt = Open("data_table.jmp");
gb = Graph Builder(
    Show Control Panel( 0 ),
    Variables( X( :weight ), Y( :height ), Overlay( :age ) ),
    Elements( Line( X, Y, Legend( 3 ), Row order( 0 ), Summary Statistic( "Mean" ) ) )
);
gb << journal window;
Current Journal() << save journal( "$TEMP\GBjournal.jrn" );
Current Journal() << close window;
j = Open( "$TEMP/GBjournal.jrn" );
j << Close Window;

Code Explanation:

1. Open data table;
2. Create Graph Builder object.
3. Hide control panel.
4. Set X, Y, and overlay variables.
5. Add line element with mean summary.
6. Show graph in journal window.
7. Save journal to file.
8. Close journal window.
9. Open saved journal file.
10. Close journal window.

Example 2130

Summary: Creates a stacked bar chart with nested factors, displaying standard deviation charts and updating axis labels for each screen size.

Code:

Names Default To Here( 1 );
//setup
dt = Open("data_table.jmp");
gb = dt << Graph Builder(
    Size( 525, 458 ),
    Show Control Panel( 0 ),
    Variables( X( :Lot Acceptance ), Overlay( :Screen Size ) ),
    Elements(
        Bar( X, Legend( 4 ), Bar Style( "Stacked" ) ),
        Caption Box(
            X,
            Legend( 5 ),
            Summary Statistic( "% of Total" ),
            Location( "Axis Table" )
        )
    )
);
//get values for each axis row
lstScreenSize = Associative Array( :Screen Size ) << Get Keys;
//populate
For Each( {i, j}, lstScreenSize,
    Report( gb ) << Dispatch( {}, "Lot Acceptance", ScaleBox,
        {Label Row( j + 1, Row Title( "% of Total(" || i || ")" ) )}
    )
);

Code Explanation:

1. Set default names.
2. Open data table.
3. Create graph builder object.
4. Set graph size.
5. Hide control panel.
6. Define X and overlay variables.
7. Add bar element.
8. Add caption box element.
9. Get unique screen sizes.
10. Loop through screen sizes.
11. Update axis labels.

Graph Builder using New Column

Example 1

Summary: Visualizes current and historical web site traffic based on time of day, using Graph Builder to display average traffic volume over different periods.

Code:

// Current and Historical Web Site Traffic Based on Time of Day
// Open data table
dt = Open("data_table.jmp");
// Current and Historical Web Site Traffic Based on Time of Day
New Column( "Hour 2",
    Character,
    Set Property(
        "Value Order",
        {Row Order Levels( 1 )}
    ),
    formula(
        Recode(
            :Hour,
            {
            Word(
                1,
                _rcNow,
                Get Whitespace Characters()
                 ||
                Get Punctuation Characters(
                    Exclude Chars( "'-" )
                ),
                Unmatched( _rcNow )
            ),
            Map Value(
                _rcOrig,
                {"12am - 1am", "midnight",
                "12pm - 1pm", "noon"},
                Unmatched( _rcNow )
            )}
        )
    )
);
Graph Builder(
    Size( 534, 455 ),
    Show Control Panel( 0 ),
    Variables(
        X( :Hour 2 ),
        Y( :Average ),
        Y( :Today, Position( 1 ) ),
        Y( :Last Week, Position( 1 ) ),
        Y( :Lo, Position( 1 ) ),
        Y( :Hi, Position( 1 ) )
    ),
    Elements(
        Area(
            X,
            Y( 4 ),
            Y( 5 ),
            Legend( 4 ),
            Area Style( "Range" )
        ),
        Line(
            X,
            Y( 1 ),
            Y( 2 ),
            Y( 3 ),
            Legend( 5 )
        )
    ),
    SendToReport(
        Dispatch( {}, "Hour 2", ScaleBox,
            {
            Label Row(
                Label Orientation(
                    "Horizontal"
                )
            )}
        ),
        Dispatch( {}, "400", ScaleBox,
            {
            Legend Model(
                4,
                Level Name(
                    0,
                    "Typical",
                    Item ID(
                        "Lo..Hi", 1
                    )
                ),
                Properties(
                    0,
                    {Fill Color( 32 )},
                    Item ID(
                        "Lo..Hi", 1
                    )
                )
            )}
        ),
        Dispatch( {}, "graph title",
            TextEditBox,
            {
            Set Text(
                "Current and Historical Web Site Traffic Based on Time of Day"
            )}
        ),
        Dispatch( {}, "X title",
            TextEditBox,
            {Set Text( "Time of day" )}
        ),
        Dispatch( {}, "Y title",
            TextEditBox,
            {
            Set Text(
                "Volume of web traffic"
            )}
        ),
        Dispatch( {}, "400", LegendBox,
            {
            Legend Position(
                {4, [0, -3, -3], 5, [3, 1,
                2]}
            )}
        )
    )
);

Code Explanation:

1. Open table.
2. Create new column "Hour 2".
3. Set column properties.
4. Define column formula.
5. Launch Graph Builder.
6. Set graph size.
7. Hide control panel.
8. Assign variables to axes.
9. Add area element.
10. Add line element.

Example 2

Summary: Creates a profiler plot by fitting a standard least squares model with multiple effects and generating a graph using Graph Builder.

Code:

dt = Open("data_table.jmp");
dt << New Column( "thousands", Numeric, "Continuous", Format( "Best", 12 ), Formula( :weight * 100 ) );
gb = Graph Builder(
    Size( 425, 425 ),
    Show Control Panel( 0 ),
    Variables( X( :thousands ), Y( :height ) ),
    Elements( Points( X, Y, Legend( 3 ) ), Smoother( X, Y, Legend( 4 ) ) )
);
rpt = gb << report;
xaxisbox = rpt[axis box( 1 )];

Code Explanation:

1. Open data table.
2. Create new column "thousands".
3. Set column format to "Best", width 12.
4. Define column formula: weight * 100.
5. Launch Graph Builder.
6. Set graph size 425x425.
7. Hide control panel.
8. Set X variable: thousands.
9. Set Y variable: height.
10. Add points and smoother elements.

Example 3

Summary: Creates a bar graph to visualize the relationship between Airline and Net Cost, with interactive features for summarizing statistics.

Code:

dt = Open("data_table.jmp");
dt << New Column( "test", formula( :Net Cost * 100 ), Format( "Currency", 17, 2 ) );
rptGB = Graph Builder(
    Size( 526, 366 ),
    Show Control Panel( 0 ),
    Variables( X( :Airline ), Y( :test ) ),
    Elements( Bar( X, Y, Legend( 6 ), Summary Statistic( "Sum" ) ) ), 
) << report;

Code Explanation:

1. Open data table.
2. Create new column "test".
3. Apply formula to "test".
4. Set format for "test".
5. Initialize Graph Builder.
6. Set graph size.
7. Hide control panel.
8. Define variables for axes.
9. Add bar element to graph.
10. Generate and display report.

Example 4

Summary: Creates a profiler plot with exponential scaling, utilizing Graph Builder to visualize the relationship between age and 10^height.

Code:

dt = Open("data_table.jmp");
New Column( "10^height", formula( 10 ^ :height ) );
Graph Builder(
    Show Control Panel( 0 ),
    Variables( X( :age ), Y( :Name( "10^height" ) ) ),
    Elements( Points( X, Y, Legend( 7 ) ) ),
    SendToReport( Dispatch( {}, "10^height", ScaleBox, {Format( "Fixed Dec", 12, 0 )} ) )
);

Code Explanation:

1. Open data table.
2. Create new column.
3. Apply exponential formula.
4. Launch Graph Builder.
5. Hide control panel.
6. Set X variable.
7. Set Y variable.
8. Add points element.
9. Format Y axis.
10. Display report.

Example 5

Summary: Creates a bar graph with multiple effects and generates a profiler plot to visualize relationships between sex, height, and leaf labels.

Code:

dt = Open("data_table.jmp");
myVal = {"height<65&height<60", "height<65&height>=60&age(12, 13)", "height<65&height<60", "height>=65", "height<65&height<60",
"height<65&height>=60&age(12, 13)", "height<65&height>=60&age(12, 13)", "height<65&height<60", "height<65&height>=60&age(12, 13)",
"height<65&height>=60&age(12, 13)", "height<65&height<60", "height>=65", "height<65&height>=60&age(12, 13)", "height<65&height<60",
"height<65&height<60", "height<65&height>=60&age(14, 15, 16, 17)", "height<65&height>=60&age(14, 15, 16, 17)", "height>=65",
"height<65&height>=60&age(14, 15, 16, 17)", "height<65&height>=60&age(14, 15, 16, 17)", "height<65&height>=60&age(14, 15, 16, 17)",
"height<65&height>=60&age(14, 15, 16, 17)", "height>=65", "height<65&height>=60&age(14, 15, 16, 17)", "height>=65",
"height<65&height>=60&age(14, 15, 16, 17)", "height>=65", "height<65&height>=60&age(14, 15, 16, 17)",
"height<65&height>=60&age(14, 15, 16, 17)", "height>=65", "height>=65", "height>=65", "height<65&height>=60&age(14, 15, 16, 17)",
"height>=65", "height>=65", "height<65&height>=60&age(14, 15, 16, 17)", "height>=65", "height<65&height>=60&age(14, 15, 16, 17)",
"height>=65", "height>=65"};
dt << New Column( "Leaf Labels", character );
Column( "Leaf Labels" ) << set values( myVal );
Graph Builder(
    Size( 468, 313 ),
    Show Control Panel( 0 ),
    Variables( X( :sex ), Y( :height ) ),
    Elements( Bar( X, Y, Legend( 4 ) ) ),
    Local Data Filter( Add Filter( columns( :Leaf Labels ), Display( :Leaf Labels, Size( 139, 56 ), List Display ) ) )
);

Code Explanation:

1. Open data table.
2. Define special string conditions.
3. Create new column for labels.
4. Set values for leaf labels.
5. Launch Graph Builder.
6. Set graph size.
7. Hide control panel.
8. Add sex and height variables.
9. Create bar element.
10. Add local data filter.

Example 6

Summary: Creates a graph with points and filters data based on specific lot conditions, utilizing Graph Builder and Local Data Filter.

Code:

dt = Open("data_table.jmp");
dt << New Column( "Lot", formula( Char( "lot" ) || Char( 0 ) || Char( Row() ) ) );
Graph Builder(
    Size( 534, 456 ),
    Show Control Panel( 0 ),
    Variables( X( :height ), Y( :weight ) ),
    Elements( Points( X, Y, Legend( 5 ) ) ),
    Local Data Filter( Add Filter( columns( :Lot ), Where( :Lot == {"lot01", "lot010", "lot011", "lot012", "lot013"} ) ) )
);

Code Explanation:

1. Open data table.
2. Create new column "Lot".
3. Set formula for "Lot" column.
4. Launch Graph Builder.
5. Set window size.
6. Hide control panel.
7. Define X and Y variables.
8. Add points element.
9. Add local data filter.
10. Set filter conditions.

Example 7

Summary: Creates a bar graph with interactive filtering by sex, utilizing Graph Builder to visualize nations and age data from a specified data table.

Code:

dt = Open("data_table.jmp");
dt << New Column( "nations", character );
myCountries = {"US", "China", "French"};
For( i = 1, i <= N Row( dt ), i++,
    If( i <= 3,
        :nations[i] = myCountries[i],
        :nations[i] = ""
    )
);

Graph Builder(
    Size( 462, 421 ),
    Show Control Panel( 0 ),
    Include Missing Categories( 1 ),
    Variables( X( :nations ), X( :age, Position( 1 ) ) ),
    Elements( Bar( X( 1 ), X( 2 ), Legend( 12 ) ) ),
    Local Data Filter( Add Filter( columns( :sex ) ) )
);

Code Explanation:

1. Open data table.
2. Create new column "nations".
3. Define country list.
4. Loop through rows.
5. Assign countries to first three rows.
6. Leave remaining rows empty.
7. Initialize Graph Builder.
8. Set graph size.
9. Hide control panel.
10. Include missing categories.
11. Set X variables.
12. Add bar elements.
13. Add local data filter for "sex".

Example 8

Summary: Creates a data table with two new columns, CommonOrderLowHigh and Mixed Leading Space, using a formula and Graph Builder to visualize age vs. height data filtered by specific values in the Mixed Leading Space column.

Code:

listLowToHigh = {"Very Low", "Low", "Medium Low", "Medium", "Medium High", "High", "Very High"};
dt = Open("data_table.jmp");
dt << New Column( "CommonOrderLowHigh",
    formula(
        Match( Mod( Row(), N Items( listLowToHigh ) ),
            1, Eval( listLowToHigh[1] ),
            2, Eval( listLowToHigh[2] ),
            3, Eval( listLowToHigh[3] ),
            4, Eval( listLowToHigh[4] ),
            5, Eval( listLowToHigh[5] ),
            6, Eval( listLowToHigh[6] ),
            0, Eval( listLowToHigh[7] ), 
        )
    )
);
dt << New Column( "Mixed Leading Space", formula( Match( Mod( Row(), 2 ), 1, " " || :CommonOrderLowHigh, :CommonOrderLowHigh ) ) );
Graph Builder(
    Size( 528, 450 ),
    Show Control Panel( 0 ),
    Variables( X( :age ), Y( :height ) ),
    Elements( Points( X, Y, Legend( 10 ) ) ),
    Local Data Filter(
        Add Filter(
            columns( :Mixed Leading Space ),
            Where( :Mixed Leading Space == {" High", " Low", " Medium", " Medium High"} ),
            Display( :Mixed Leading Space, Size( 178, 238 ), Height( 238 ) )
        )
    )
);

Code Explanation:

1. Define listLowToHigh.
2. Open data table;
3. Create new column CommonOrderLowHigh.
4. Assign formula using Match function.
5. Create new column Mixed Leading Space.
6. Assign formula adding leading space conditionally.
7. Launch Graph Builder.
8. Set size and hide control panel.
9. Set variables X(age), Y(height).
10. Add points element and local data filter.

Example 9

Summary: Creates a bar graph with frequency data, utilizing Graph Builder to visualize the relationship between age and height.

Code:

dt = Open("data_table.jmp");
dt << New Column( "freq", formula( 2 ) );
Graph Builder(
    Size( 438, 314 ),
    Show Control Panel( 0 ),
    Variables( X( :age ), Y( :height ), Frequency( :freq ) ),
    Elements( Bar( X, Y, Legend( 5 ), Summary Statistic( "Sum" ), Label( "Label by Value" ) ) )
);

Code Explanation:

1. Open data table;
2. Create new column "freq".
3. Set formula for "freq" to 2.
4. Initiate Graph Builder.
5. Set size to 438x314.
6. Hide control panel.
7. Define X variable as :age.
8. Define Y variable as :height.
9. Set frequency variable as :freq.
10. Add bar element with sum summary and label by value.

Example 10

Summary: Creates a profiler plot with multiple effects by fitting a standard least squares model and generating a graph using Graph Builder.

Code:

dt = Open("data_table.jmp");
dt << New Column( "myHeight", formula( :height ) );
Graph Builder(
    Size( 528, 448 ),
    Show Control Panel( 0 ),
    Variables( X( :age ), Y( :height ), Y( :myHeight, Position( 1 ) ) ),
    Elements( Bar( X, Y( 1 ), Y( 2 ), Legend( 4 ), Bar Style( "Range" ), Summary Statistic( "Range" ), Label( "Label by Value" ) ) )
);

Code Explanation:

1. Open data table.
2. Create new column "myHeight".
3. Set formula for "myHeight".
4. Initialize Graph Builder.
5. Set graph size.
6. Hide control panel.
7. Define X and Y variables.
8. Add second Y variable.
9. Add bar element.
10. Configure bar style and summary statistic.

Example 11

Summary: Creates a bar graph with missing categories, filtering by sex, and displaying nations and age variables using Graph Builder.

Code:

dt = Open("data_table.jmp");
dt << New Column( "nations", character );
myCountries = {"US", "China", "French"};
For( i = 1, i <= N Row( dt ), i++,
    If( i <= 3,
        :nations[i] = myCountries[i],
        :nations[i] = ""
    )
);
Graph Builder(
    Size( 462, 421 ),
    Show Control Panel( 0 ),
    Include Missing Categories( 1 ),
    Variables( X( :nations ), X( :age, Position( 1 ) ) ),
    Elements( Bar( X( 1 ), X( 2 ), Legend( 12 ) ) ),
    Local Data Filter( Add Filter( columns( :sex ) ) )
);

Code Explanation:

1. Open data table.
2. Create new column "nations".
3. Define country list.
4. Loop through rows.
5. Assign countries to first three rows.
6. Set remaining nations to empty.
7. Launch Graph Builder.
8. Set graph size.
9. Hide control panel.
10. Configure variables and elements.

Example 12

Summary: Creates a profiler plot with multiple bar charts and error bars, utilizing Graph Builder to visualize data from a JMP data table.

Code:

dt = Open("data_table.jmp");
dt << New Column( "myFreq", formula( Random Integer( -6, 6 ) ) );
Graph Builder(
    Size( 601, 466 ),
    Show Control Panel( 0 ),
    Show Footer( 0 ),
    Variables(
        X( :age ),
        Y( :height ),
        Y( :weight ),
        Y( :weight ),
        Y( :height ),
        Y( :height ),
        Y( :height ),
        Y( :height ),
        freq( :myFreq ),
        Overlay( :sex )
    ),
    Elements( Position( 1, 1 ), Bar( X, Y, Legend( 11 ), Error Bars( "Range" ) ) ),
    Elements( Position( 1, 2 ), Bar( X, Y, Legend( 10 ), Error Bars( "Interquartile Range" ) ) ),
    Elements( Position( 1, 3 ), Bar( X, Y, Legend( 8 ), Error Bars( "Standard Error" ) ) ),
    Elements( Position( 1, 4 ), Bar( X, Y, Legend( 6 ), Error Bars( "Standard Deviation" ) ) ),
    Elements( Position( 1, 5 ), Bar( X, Y, Legend( 5 ), Error Bars( "Confidence Interval" ) ) ),
    Elements( Position( 1, 6 ), Bar( X, Y, Legend( 12 ), Error Bars( "Custom Interval" ) ) ),
    Elements( Position( 1, 7 ), Bar( X, Y, Legend( 13 ) ) )
);

Code Explanation:

1. Open data table.
2. Create new column "myFreq".
3. Initialize Graph Builder.
4. Set graph size.
5. Hide control panel.
6. Hide footer.
7. Define X and Y variables.
8. Add frequency variable.
9. Overlay by sex.
10. Plot multiple bar charts with different error bars.

Example 13

Summary: Creates a bar graph to visualize non-missing values in the 'age' and 'sex' columns, utilizing Graph Builder.

Code:

dt = Open("data_table.jmp");
dt << New Column( "NonMissing", formula( Col Number( :age, :sex ) ) );
Graph Builder(
    Size( 534, 454 ),
    Show Control Panel( 0 ),
    Variables( X( :NonMissing ) ),
    Elements( Bar( X, Legend( 3 ), Summary Statistic( "% of Total" ), Label( "Label by Value" ) ) )
);

Code Explanation:

1. Open table.
2. Create new column.
3. Apply formula to column.
4. Initialize Graph Builder.
5. Set graph size.
6. Hide control panel.
7. Assign X variable.
8. Add bar element.
9. Set legend position.
10. Define summary statistic.

Example 14

Summary: Creates a profiler plot with multiple effects and generates a standard least squares model using Graph Builder in JMP.

Code:

dt = Open("data_table.jmp");
dt << New Column( "contiGrp", formula( If( Mod( Row(), 2 ) == 1, 1, 2 ) ) );
Graph Builder(
    Size( 587, 539 ),
    Variables( X( :sex ), X( :age, Position( 1 ) ), X( :age ), X( :sex, Position( 2 ) ), Y( :weight ), Y( :height ), Wrap( :contiGrp ) ),
    Elements( Position( 1, 1 ), Bar( X( 1 ), X( 2 ), Y, Legend( 8 ), Summary Statistic( "% of Total" ), Label( "Label by Value" ) ) ),
    Elements( Position( 1, 2 ), Bar( X( 1 ), X( 2 ), Y, Legend( 5 ), Summary Statistic( "% of Total" ), Label( "Label by Value" ) ) ),
    Elements( Position( 2, 1 ), Bar( X( 2 ), X( 1 ), Y, Legend( 9 ), Summary Statistic( "% of Total" ), Label( "Label by Value" ) ) ),
    Elements( Position( 2, 2 ), Bar( X( 2 ), X( 1 ), Y, Legend( 6 ), Summary Statistic( "% of Total" ), Label( "Label by Value" ) ) )
);

Code Explanation:

1. Open data table.
2. Create new column "contiGrp".
3. Assign formula to "contiGrp".
4. Initialize Graph Builder.
5. Set graph size.
6. Define variables for axes and wrap.
7. Add first bar element.
8. Add second bar element.
9. Add third bar element.
10. Add fourth bar element.

Example 15

Summary: Creates a graph builder with multiple effects and generates a profiler plot to visualize relationships between age, height, and weight by country.

Code:

dt = Open("data_table.jmp");
dt << New Column( "country" );
:country[1] = "us";
Graph Builder(
    Size( 534, 948 ),
    Show Control Panel( 0 ),
    Include Missing Categories( 1 ),
    Variables( X( :age ), Y( :height ), Y( :weight, Position( 1 ) ), Page( :country ) ),
    Elements( Bar( X, Y( 1 ), Y( 2 ), Legend( 5 ) ) )
);

Code Explanation:

1. Open data_table data
2. Add new column named "country".
3. Set first row of "country" to "us".
4. Launch Graph Builder.
5. Set window size to 534x948.
6. Hide control panel.
7. Include missing categories.
8. Assign variables: X=age, Y=height, Y=weight, Page=country.
9. Add Bar element for X, Y1, Y2.
10. Display legend at position 5.

Example 16

Summary: Creates a heatmap to visualize frequency distribution based on sex, age, and height, utilizing Graph Builder.

Code:

dt = Open("data_table.jmp");
dt << New Column( "myFreq", formula( Random Integer( -6, 6 ) ) );
Graph Builder(
    Size( 528, 448 ),
    Show Control Panel( 0 ),
    Variables( X( :sex ), X( :age ), Y( :height ), Frequency( :myFreq ) ),
    Elements( Position( 1, 1 ), Heatmap( X, Y, Legend( 7 ) ) ),
    Elements( Position( 2, 1 ), Heatmap( X, Y, Legend( 8 ) ) )
);

Code Explanation:

1. Open data table.
2. Create new column "myFreq".
3. Set column formula for random integers.
4. Initialize Graph Builder.
5. Set graph size.
6. Hide control panel.
7. Define X variables: sex, age.
8. Define Y variable: height.
9. Set frequency variable: myFreq.
10. Add first heatmap element.
11. Add second heatmap element.

Example 17

Summary: Creates a profiler plot with multiple effects by fitting a standard least squares model and generating a graph using Graph Builder.

Code:

dt2 = Open("data_table.jmp");
dt2 << New Column( "one", <<Set Each Value( 1 ) );
dt2:age[5 :: 20] = .;
dt2 << Graph Builder(
    Show Control Panel( 0 ),
    Variables( X( :name ), Y( :one ), Y( :one ), Color( :age ) ),
    Elements( Position( 1, 1 ), Points( X, Y, Legend( 12 ), Jitter( "None" ) ) ),
    Elements( Position( 1, 2 ), Heatmap( X, Y, Legend( 7 ) ) ),
    SendToReport( Dispatch( {}, "Graph Builder", FrameBox, {Marker Size( 20 ), Marker Drawing Mode( "Normal" )} ) )
);

Code Explanation:

1. Open data table.
2. Create new column "one".
3. Set "one" values to 1.
4. Set "age" values 5-20 to missing.
5. Launch Graph Builder.
6. Hide control panel.
7. Set X variable to "name".
8. Set Y variables to "one".
9. Set color variable to "age".
10. Add points and heatmap elements.

Example 18

Summary: Fits a standard least squares model with multiple effects and generating a profiler plot, utilizing Graph Builder to visualize relationships between variables.

Code:

dt = Open("data_table.jmp");
dt << New Column( "Constant", Numeric, Continuous, Set Each Value( 13 ) );
Graph Builder(
    Size( 528, 448 ),
    Show Control Panel( 0 ),
    Variables( X( :age ), Y( :height ) ),
    Elements( Points( X, Y, Legend( 3 ) ), Line Of Fit( X, Y, Legend( 4 ) ) )
);
Graph Builder(
    Size( 528, 448 ),
    Show Control Panel( 0 ),
    Variables( X( :Constant ), Y( :height ) ),
    Elements( Points( X, Y, Legend( 3 ) ), Line Of Fit( X, Y, Legend( 4 ) ) )
);
Graph Builder(
    Size( 528, 448 ),
    Show Control Panel( 0 ),
    Variables( X( :sex ), Y( :height ) ),
    Elements( Points( X, Y, Legend( 3 ) ), Line Of Fit( X, Y, Legend( 4 ), Unequal Variances( 1 ), Confidence of Prediction( 1 ) ) )
);
dt << Select Where( :sex == "F" ) << Invert Row Selection;
dt << Delete Rows();
gb = Graph Builder(
    Variables( X( :age ), Y( :weight ) ),
    Elements(
        Points( X, Y, Legend( 4 ) ),
        Line Of Fit( X, Y, Legend( 5 ), Unequal Variances( 1 ), Confidence of Prediction( 1 ), F Test( 1 ) )
    )
);
Graph Builder(
    Size( 534, 448 ),
    Show Control Panel( 0 ),
    Variables( X( :sex ), Y( :height ), Y( :weight, Position( 1 ) ) ),
    Elements(
        Points( X, Y( 1 ), Y( 2 ), Legend( 3 ) ),
        Line Of Fit( X, Y( 1 ), Y( 2 ), Legend( 4 ), Unequal Variances( 1 ), F Test( 1 ) )
    ),
    SendToReport( Dispatch( {}, "400", ScaleBox, {Legend Model( 3, Base( 0, 0, 0 ), Base( 1, 0, 0 ) )} ) )
);

Code Explanation:

1. Open data table;
2. Add "Constant" column.
3. Create age vs height graph.
4. Create Constant vs height graph.
5. Create sex vs height graph.
6. Select non-F rows.
7. Delete non-F rows.
8. Create age vs weight graph.
9. Create sex vs height & weight graph.
10. Adjust graph legend.

Example 19

Summary: Fits a standard least squares model with multiple effects and generating profiler plots, utilizing Graph Builder to visualize relationships between variables.

Code:

dt = Open("data_table.jmp");
dt << New Column( "Constant", Numeric, Continuous, Set Each Value( 18 ) );
Graph Builder(
    Size( 528, 448 ),
    Show Control Panel( 0 ),
    Variables( X( :age ), Y( :height ) ),
    Elements( Points( X, Y, Legend( 3 ) ), Line Of Fit( X, Y, Legend( 4 ) ) )
);
Graph Builder(
    Size( 528, 448 ),
    Show Control Panel( 0 ),
    Variables( X( :Constant ), Y( :height ) ),
    Elements( Points( X, Y, Legend( 3 ) ), Line Of Fit( X, Y, Legend( 4 ) ) )
);
Graph Builder(
    Size( 528, 448 ),
    Show Control Panel( 0 ),
    Variables( X( :sex ), Y( :height ) ),
    Elements( Points( X, Y, Legend( 3 ) ), Line Of Fit( X, Y, Legend( 4 ), Unequal Variances( 1 ), Confidence of Prediction( 1 ) ) )
);
dt << Select Where( :sex == "F" ) << Invert Row Selection;
dt << Delete Rows();
gb = Graph Builder(
    Variables( X( :age ), Y( :weight ) ),
    Elements(
        Points( X, Y, Legend( 4 ) ),
        Line Of Fit( X, Y, Legend( 5 ), Unequal Variances( 1 ), Confidence of Prediction( 1 ), F Test( 1 ) )
    )
);
Open("data_table.jmp");

Code Explanation:

1. Open data table;
2. Add Constant column.
3. Create age vs. height graph.
4. Create Constant vs. height graph.
5. Create sex vs. height graph.
6. Select non-female rows.
7. Delete non-female rows.
8. Create age vs. weight graph.
9. Open data table;

Example 20

Summary: Creates a graph with ordered X-axis and Y-axis variables, utilizing Graph Builder to visualize data from an open JMP data table.

Code:

dt = Open("data_table.jmp");
Dt << New Column( "letter",
    Character,
    Nominal,
    Set Property( "Row Order Levels", 1 ),
    Set Values(
        {"a", "b", "c", "e", "d", "f", "g", "h", "i", "j", "k", "l", "m", "n", "o", "p", "q", "r", "s", "t", "u", "v", "w", "x", "y", "z",
        "aa", "bb", "cc", "dd", "ee", "ff", "gg", "hh", "ii", "jj", "kk", "ll", "mm", "nn"}
    )
);
dt:age << Set Property( "Row Order Levels", 1 );
dt:age[1] = 18;
dt:age[2] = 18;
Graph Builder( Show Control Panel( 0 ), Size( 760, 532 ), Variables( X( :name, Order By( :letter ) ), Y( :height ), ) );

Code Explanation:

1. Open data table.
2. Add new column "letter".
3. Set column properties for "letter".
4. Populate "letter" with values.
5. Set row order levels for age.
6. Modify age values at rows 1 and 2.
7. Create Graph Builder object.
8. Hide control panel.
9. Set graph size.
10. Define X and Y variables with ordering.

Example 21

Summary: Creates a graph builder with two variables, name and height, ordered by letter and age respectively.

Code:

Dt = Open("data_table.jmp");
Dt << New Column( "letter",
    Character,
    Nominal,
    Set Property( "Row Order Levels", 1 ),
    Set Values(
        {"a", "b", "c", "e", "d", "f", "g", "h", "i", "j", "k", "l", "m", "n", "o", "p", "q", "r", "s", "t", "u", "v", "w", "x", "y", "z",
        "aa", "bb", "cc", "dd", "ee", "ff", "gg", "hh", "ii", "jj", "kk", "ll", "mm", "nn"}
    )
);
dt:age << Set Property( "Row Order Levels", 1 );
dt:age[1] = 18;
dt:age[2] = 18;
Graph Builder( Show Control Panel( 0 ), Size( 760, 532 ), Variables( X( :name, Order By( :letter ) ), Y( :height ), ) );
Graph Builder( Show Control Panel( 0 ), Size( 760, 532 ), Variables( X( :name, Order By( :age ) ), Y( :height ) ) );

Code Explanation:

1. Open data table.
2. Create new character column.
3. Set column properties.
4. Assign values to new column.
5. Set age row order levels.
6. Modify first age value.
7. Modify second age value.
8. Create graph builder with letter order.
9. Create graph builder with age order.

Example 22

Summary: Creates a scatter plot with overlay by sex and color by ratio, utilizing Graph Builder to visualize the relationship between height and weight.

Code:

dt = Open("data_table.jmp");
dt << New Column( "ratio", Formula( :height / :weight ) );
gb = Graph Builder(
    Size( 450, 320 ),
    Show Control Panel( 0 ),
    Variables( X( :height ), Y( :weight ), Overlay( :sex ), Color( :ratio ) ),
    Elements( Points( X, Y, Color, Legend( 2 ) ) ),
    SendToReport( Dispatch( {}, "Graph Builder", FrameBox, {Marker Size( 3 )} ) )
);

Code Explanation:

1. Open data_table data
2. Create new column "ratio".
3. Calculate height divided by weight.
4. Initialize Graph Builder.
5. Set size to 450x320.
6. Hide control panel.
7. Set X to height.
8. Set Y to weight.
9. Overlay by sex.
10. Color by ratio.

Example 23

Summary: Creates a graph builder object with points element, enabling legend and jitter for data visualization.

Code:

dt = Open("data_table.jmp");
dt << New Column( "x" );
gb = dt << Graph Builder( show control panel( 0 ), Variables( X( :x ) ), Elements( Points( X, Legend( 1 ), Jitter( 1 ) ) ) );

Code Explanation:

1. Open data table.
2. Add new column "x".
3. Create Graph Builder object.
4. Hide control panel.
5. Set X variable to "x".
6. Add points element.
7. Enable legend for points.
8. Apply jitter to points.

Example 24

Summary: Fits a standard least squares model with multiple effects and generates a profiler plot using Graph Builder in JMP.

Code:

dt = Open("data_table.jmp");
dt << New Column( "x" );
gb = dt << Graph Builder( show control panel( 0 ), Variables( X( :x ) ), Elements( Points( X, Legend( 1 ), Jitter( 1 ) ) ) );
dt << Delete Columns( "x" );

Code Explanation:

1. Open data table.
2. Create new column "x".
3. Launch Graph Builder.
4. Set X variable to "x".
5. Add Points element.
6. Enable jitter.
7. Disable control panel.
8. Delete column "x".

Example 25

Summary: Creates a data table with a new column 'letter' and sets row order levels, while also launching Graph Builder to visualize the data.

Code:

dt = Open("data_table.jmp");
dt << New Column( "letter",
    Character,
    Nominal,
    Set Property( "Row Order Levels", 1 ),
    Set Values(
        {"a", "b", "c", "e", "d", "f", "g", "h", "i", "j", "k", "l", "m", "n", "o", "p", "q", "r", "s", "t", "u", "v", "w", "x", "y", "z",
        "aa", "bb", "cc", "dd", "ee", "ff", "gg", "hh", "ii", "jj", "kk", "ll", "mm", "nn"}
    )
);
dt:age << Set Property( "Row Order Levels", 1 );
dt:age[1] = 18;
dt:age[2] = 18;
Graph Builder( Size( 760, 532 ), Show Control Panel( 0 ), Variables( X( :name, Order By( :letter ) ), Y( :height ), ) );

Code Explanation:

1. Open data table.
2. Create new column "letter".
3. Set column properties.
4. Assign values to "letter".
5. Set age row order levels.
6. Modify first age value.
7. Modify second age value.
8. Launch Graph Builder.
9. Set graph size.
10. Hide control panel.

Example 26

Summary: Creates a data table with a new column 'letter' and sets row order levels for age, then generates two graph builders to visualize name ordered by letter and age.

Code:

dt = Open("data_table.jmp");
dt << New Column( "letter",
    Character,
    Nominal,
    Set Property( "Row Order Levels", 1 ),
    Set Values(
        {"a", "b", "c", "e", "d", "f", "g", "h", "i", "j", "k", "l", "m", "n", "o", "p", "q", "r", "s", "t", "u", "v", "w", "x", "y", "z",
        "aa", "bb", "cc", "dd", "ee", "ff", "gg", "hh", "ii", "jj", "kk", "ll", "mm", "nn"}
    )
);
dt:age << Set Property( "Row Order Levels", 1 );
dt:age[1] = 18;
dt:age[2] = 18;
Graph Builder( Size( 760, 532 ), Show Control Panel( 0 ), Variables( X( :name, Order By( :letter ) ), Y( :height ), ) );
Graph Builder( Size( 760, 532 ), Show Control Panel( 0 ), Variables( X( :name, Order By( :age ) ), Y( :height ) ) );

Code Explanation:

1. Open data table;
2. Create new column "letter".
3. Set column properties for "letter".
4. Assign values to "letter" column.
5. Set row order levels for "age" column.
6. Modify age values for first two rows.
7. Create graph builder with name ordered by letter.
8. Create graph builder with name ordered by age.

Example 27

Summary: Creates a treemap visualization to display the ratio of height to weight, formatted as a percentage, using Graph Builder in JMP.

Code:

dt = Open("data_table.jmp");
dt << New Column( "Ratio", numeric, continuous, Format( percent ), formula( :height / :weight ) );
Graph Builder(
    Size( 495, 440 ),
    Show Control Panel( 0 ),
    Variables( X( :name ), Size( :Ratio ) ),
    Elements( Treemap( X, Legend( 6 ), Size Value( 1 ) ) )
);

Code Explanation:

1. Open data_table data
2. Create new column "Ratio".
3. Calculate height divided by weight.
4. Format "Ratio" as percentage.
5. Launch Graph Builder.
6. Set size to 495x440.
7. Hide control panel.
8. Assign "name" to X-axis.
9. Assign "Ratio" to size.
10. Add Treemap element.

Example 28

Summary: Creates a Treemap visualization in Graph Builder, using the 'Special Name' column as the X-axis variable.

Code:

dt = Open("data_table.jmp");
dt << New Column( "Special Name", char, formula( :name || "\" || :name ) );
Graph Builder(
    Size( 733, 440 ),
    Show Control Panel( 0 ),
    Variables( X( :Special Name ) ),
    Elements( Treemap( X, Legend( 4 ) ) ),
    SendToReport(
        Dispatch( {}, "Graph Builder", FrameBox,
            Add Pin Annotation(
                Seg( TreeMapSeg( 1 ) ),
                Index( 18 ),
                Index Row( 11 ),
                UniqueID( 18 ),
                FoundPt( {354, 190} ),
                Origin( {325.169603064067, 261.158442408377} ),
                RightOfCenter( 0 ),
                Tag Line( 1 )
            )
        )
    )
);

Code Explanation:

1. Open data table;
2. Create new column "Special Name".
3. Set column type to character.
4. Define formula for "Special Name".
5. Launch Graph Builder.
6. Set graph size.
7. Hide control panel.
8. Assign X variable.
9. Add Treemap element.
10. Send report with pin annotation.

Example 29

Summary: Creates a treemap visualization to display nationality and age data, utilizing Graph Builder in JMP.

Code:

dt = Open("data_table.jmp");
myNewCol = dt << New Column( "nationality", "Character", formula( Random Integer( 1, 5 ) ) );
gb = Graph Builder(
    Size( 500, 440 ),
    Show Control Panel( 0 ),
    Variables( X( :nationality ), X( :age, Position( 1 ) ) ),
    Elements( Treemap( X( 1 ), X( 2 ), Legend( 8 ) ) )
);

Code Explanation:

1. Open data table.
2. Create new column "nationality".
3. Assign random integers to "nationality".
4. Initialize Graph Builder.
5. Set graph size.
6. Hide control panel.
7. Define X variables.
8. Add Treemap element.
9. Position age on X-axis.
10. Display Treemap legend.

Example 30

Summary: Creates a treemap visualization to display nationality and age data, utilizing Graph Builder.

Code:

dt = Open("data_table.jmp");
myNewCol = dt << New Column( "nationality", "Character", formula( Random Integer( 1, 5 ) ) );
gb = Graph Builder(
    Size( 500, 440 ),
    Show Control Panel( 0 ),
    Variables( X( :nationality ), X( :age, Position( 1 ) ) ),
    Elements( Treemap( X( 1 ), X( 2 ), Legend( 8 ) ) )
);
gb << journal;

Code Explanation:

1. Open data table.
2. Create new column "nationality".
3. Assign random nationality values.
4. Initialize Graph Builder.
5. Set graph size.
6. Hide control panel.
7. Define X variables.
8. Add Treemap element.
9. Configure Treemap legend.
10. Display graph in journal.

Example 31

Summary: Process of adding comments to selected rows in a data table, displaying labels for those rows, and saving the updated data to an Excel file.

Code:

Names Default To Here( 1 );
//using sample data instead of excel file to start
//this would be changed with some original file name
dt = Open("data_table.jmp");
dt << New Column( "Comment", Character );
dt:Comment << Label( 1 );
dt:name << Label( 0 );
dashboard = New Window( "Dashboard",
    Button Box( "Add Comment to Selection",
        dt << Name Selection in Column(
            Column Name( "Comment" ),
            Selected( tb << Get Text ),
            Unselected()
        );
        dt << Label; //display label for selected rows

        //optional: script to save back to original data source
        dt << Save As( "$DESKTOP/original filename here.xlsx" );
        web ("$DESKTOP");
        web ("$DESKTOP/original filename here.xlsx");
    ),
    tb = Text Edit Box( "Comment here" ),
    gb = dt << Graph Builder(
        Size( 522, 452 ),
        Show Control Panel( 0 ),
        Variables( X( :height ), Y( :weight ) ),
        Elements( Points( X, Y, Legend( 2 ) ) )
    ), 
);

Code Explanation:

1. Open data_table data
2. Add new "Comment" column.
3. Label "Comment" column.
4. Unlabel "name" column.
5. Create Dashboard window.
6. Add "Add Comment to Selection" button.
7. Select rows and add comment.
8. Display labels for selected rows.
9. Save data to Excel file.
10. Open saved Excel file in browser.

Example 32

Summary: Generates curves for FDE using Weibull density formulas and normalizes column values, then stacks columns into a new table and adds a calculated column before creating a graph with multiple overlays.

Code:

//Generate curves for FDE
Names Default To Here( 1 );
dt = New Table( "Curves" );
dt << New Column( "Time", Numeric, Continuous, set values( 0 :: 3 :: .1 ) );
For Each( {i}, 1 :: 4 :: .25,
    dt << New Column( Char( i ),
        Numeric,
        Continuous,
        formula( Weibull Density( :Time, i )*2 + Random Normal()*.02 )
    )
);
lstcols = dt << Get Column Names;
Remove From( lstcols, 1 );
for each ({i}, lstcols,
    as column (i) << Delete Formula;
    m1 = as column (i) << get values;
    ma = max (m1);
    mi = min (m1);
    ra = ma - mi;
    for each ({ii, jj}, m1,
        m1[jj] = m1[jj]*(1/ra)
    );
    as column (i) << set values (m1);
);
dt2 = dt << Stack(
    columns(
        lstcols
    ),
    Source Label Column( "Label" ),
    Stacked Data Column( "Data" ),
    Output Table( "Curve Data" )
);
dt2 << New Column ("Data 2");
for each row (dt2,
    :Data 2 = .25 + 2 * :Time + 4 * num(:Label) - 3 * :Time * num(:Label) + 2.7 * :Time^2 - 1.2 * num(:Label)^ 2 - .7 * :Time ^ 3
);
dt2 << Graph Builder(
    Size( 528, 454 ),
    Show Control Panel( 0 ),
    Variables( X( :Time ), Y( :Data ), Y( :Data 2 ), Overlay( :Label ) ),
    Elements( Position( 1, 1 ), Line( X, Y, Legend( 15 ) ) ),
    Elements( Position( 1, 2 ), Line( X, Y, Legend( 17 ) ) )
);

Code Explanation:

1. Set default names scope.
2. Create new table "Curves".
3. Add "Time" column with values from 0 to 3.
4. Loop to add 4 columns with Weibull density formulas.
5. Get column names excluding "Time".
6. Loop through each column to remove formula.
7. Normalize column values.
8. Stack columns into new table "Curve Data".
9. Add "Data 2" column with calculated values.
10. Create graph with time, data, and data 2.

Example 33

Summary: Generates a cooldown data table with simulated samples, time points, and settings to visualize temperature profiles and perform logistic regression analysis.

Code:

Names Default To Here( 1 );
//make table of cooldown cycles for FDE and Discrimanant platform
dt = New Table( "Cooldown Data" );
dt << New Column( "Sample" );
dt << New Column( "Time" );
dt << New Column( "Setting" );
dt << New Column( "Temp" );
dt << New Column( "Label", Character );
nsamples = 50;
For Each( {i}, 1 :: nsamples,
    pwr = Round( Random Uniform( 50, 80 ), 1 );

    If( Random Uniform() > .98,
        rej = "Fail",
        If( Random Uniform() > .5 & pwr < 65,  //low settings need to fail more
            rej = "Fail"
        ,
            If( Random Uniform() > .1 & pwr < 58, //lowerlower settings fail lots more
                rej = "Fail"
            ,
                rej = "Pass"
            )
        )
    );
    For Each( {ii}, 1 :: 100, dt << Add Rows( {Sample = i, Time = ii, Setting = pwr, Label = rej} ) );

);
dt:Temp << Set Formula(
    Random Normal() * 25 + 2000 + (Normal Density( :Time * .01 ) * 10000) - (:Setting * :Time ^ 2) * .01 + (:time ^ 3 / 2.5) * .01 - (:time ^ 4
     * .00001) + Random Uniform()
);
dt:Sample << Set Modeling Type( "Nominal" );
dt << Graph Builder(
    Size( 528, 454 ),
    Show Control Panel( 0 ),
    Variables( X( :Time ), Y( :Temp ), Color( :Label ) ),
    Elements( Points( X, Y, Legend( 52 ) ) )
);
dt << Logistic( Y( :Label ), X( :Setting ), Target Level( "Pass" ) );

Code Explanation:

1. Set default names scope.
2. Create new table "Cooldown Data".
3. Add columns: Sample, Time, Setting, Temp, Label.
4. Define number of samples (nsamples = 50).
5. Loop through each sample.
6. Generate random power value.
7. Determine rejection status based on power and random conditions.
8. Add rows to table for each time point in sample.
9. Set formula for Temp column.
10. Set Sample column as Nominal.
11. Create Graph Builder with Time vs Temp, colored by Label.
12. Perform Logistic regression on Label with Setting as predictor.

Graph Builder using Label

Example 1

Summary: Visualizes a hexagonal heatmap with label viewer to explore the relationship between 'height' and 'weight', utilizing Graph Builder and Label Viewer presets.

Code:

// Hexagonal Heat Map with Label Viewer
// Open data table
dt = Open("data_table.jmp");
// Hexagonal Heat Map with Label Viewer
:pet << Label( 0 );
Graph Builder(
    Size( 534, 456 ),
    Show Control Panel( 0 ),
    Variables(
        X( :height ),
        Y( :weight )
    ),
    Elements(
        Heatmap(
            X,
            Y,
            Legend( 4 ),
            Bin Shape( "Hexagonal" )
        )
    ),
    SendToReport(
        Dispatch( {}, "400", ScaleBox,
            {
            Legend Model(
                4,
                Properties(
                    0,
                    {
                    gradient(
                        {
                        Color Theme(
                            "White to Blue"
                        ),
                        Discrete Colors(
                            1
                        )}
                    )},
                    Item ID( "Count", 1 )
                )
            )}
        ),
        Dispatch( {}, "Graph Builder",
            FrameBox,
            {
            Set Graphlet(
                Picture(
                    Try(
                        loader =
                        If(
                            Class Exists(
                                "hllLoader"
                            ),
                            New Object(
                                "hllLoader"
                            ),
                            Include(
                                "$BUILTIN_SCRIPTS/hllib.jsl"
                            )
                        );
                        loader
                        :setDebug( 0 );
                        hlp = loader
                        :lazyLoad(
                            "hllPresets"
                        );
                        hlp
                        :launchLabel Viewer();
                    ,
                        Write(
                            "
Hover Label: Unable to launch Preset, please check that the Preset library is available at $BUILTIN_SCRIPTS/hllib.jsl"
                        );
                        Write(
                            Eval Insert(
                                "
Exception: ^exception_msg^"
                            )
                        );
                        Empty();
                    )
                ),
                Title(
                    "Label Viewer Preset"
                ),
                Reapply( 1 )
            ),
            Add Pin Annotation(
                Seg( HexSeg( 1 ) ),
                Index( 11 ),
                Index Row( 28 ),
                UniqueID( -426351653 ),
                FoundPt( {655, 338} ),
                Origin(
                    {64.4490631898039,
                    113.913313363022}
                ),
                Offset( {-329, -106} ),
                Tag Line( 1 )
            )}
        )
    )
);

Code Explanation:

1. Open data table.
2. Set label for 'pet'.
3. Create Graph Builder window.
4. Hide control panel.
5. Set X variable to 'height'.
6. Set Y variable to 'weight'.
7. Add heatmap element.
8. Set bin shape to hexagonal.
9. Configure legend.
10. Launch Label Viewer preset.

Example 2

Summary: Displays multiple images with a Label Viewer in JMP, utilizing Graph Builder to create a visual representation of pet data.

Code:

// Display Multiple Images with Label Viewer
// Open data table
dt = Open("data_table.jmp");
// Display Multiple Images with Label Viewer
:pet << Label( 1 );
Graph Builder(
    Size( 534, 456 ),
    Show Control Panel( 0 ),
    Variables(
        X( :height ),
        Y( :weight ),
        Overlay( :sex )
    ),
    Elements(
        Points( X, Y, Legend( 8 ) ),
        Smoother( X, Y, Legend( 9 ) )
    ),
    SendToReport(
        Dispatch( {}, "Graph Builder",
            FrameBox,
            {
            Set Graphlet(
                Picture(
                    Try(
                        loader =
                        If(
                            Class Exists(
                                "hllLoader"
                            ),
                            New Object(
                                "hllLoader"
                            ),
                            Include(
                                "$BUILTIN_SCRIPTS/hllib.jsl"
                            )
                        );
                        loader
                        :setDebug( 0 );
                        hlp = loader
                        :lazyLoad(
                            "hllPresets"
                        );
                        hlp
                        :launchLabel Viewer();
                    ,
                        Write(
                            "
Hover Label: Unable to launch Preset, please check that the Preset library is available at $BUILTIN_SCRIPTS/hllib.jsl"
                        );
                        Write(
                            Eval Insert(
                                "
Exception: ^exception_msg^"
                            )
                        );
                        Empty();
                    )
                ),
                Title(
                    "Label Viewer Preset"
                ),
                Reapply( 1 )
            ),
            {Add Pin Annotation(
                Seg( Marker Seg( 2 ) ),
                Index( 12 ),
                Index Row( 25 ),
                UniqueID( 12 ),
                FoundPt( {653, 358} ),
                Origin(
                    {64.0119254658385,
                    99.129211672645}
                ),
                Offset( {-316, -94} ),
                RightOfCenter( 1 ),
                Tag Line( 1 )
            ),
            Add Pin Annotation(
                Seg( Marker Seg( 1 ) ),
                Index( 17 ),
                Index Row( 37 ),
                UniqueID( 17 ),
                FoundPt( {606, 309} ),
                Origin(
                    {61.991801242236,
                    115.991631366434}
                ),
                Offset( {80, -53} ),
                RightOfCenter( 1 ),
                Tag Line( 1 )
            )}}
        )
    )
);

Code Explanation:

1. Open table.
2. Set label for pet.
3. Create Graph Builder.
4. Set size and control panel.
5. Define variables.
6. Add points and smoother elements.
7. Send report to Graph Builder.
8. Load label viewer script.
9. Launch label viewer.
10. Add pin annotations.

Example 3

Summary: Prepares data and visualization by opening a JMP data table, labeling columns, setting missing values, and creating a Graph Builder with a mosaic element.

Code:

Open("data_table.jmp");
:age << Label( 1 );
:sex << Label( 1 );
:name[12] = "";
:sex[13] = "";
Graph Builder(
    Size( 534, 450 ),
    Show Control Panel( 0 ),
    Variables( X( :age ), Y( :height ) ),
    Elements( Mosaic( X, Y, Legend( 4 ), Cell Labeling( "Label by Row" ) ) )
);

Code Explanation:

1. Open data table.
2. Label age column.
3. Label sex column.
4. Set name[12] to missing.
5. Set sex[13] to missing.
6. Create Graph Builder.
7. Set graph size.
8. Hide control panel.
9. Define X and Y variables.
10. Add mosaic element with row labeling.

Example 4

Summary: Creates a mosaic graph to visualize the relationship between sex and height, utilizing Graph Builder's interactive features.

Code:

Open("data_table.jmp");
:name << Label( 0 );
Graph Builder(
    Size( 200, 450 ),
    Show Control Panel( 0 ),
    Variables( X( :sex ), Y( :height ) ),
    Elements( Mosaic( X, Y, Legend( 4 ), Cell Labeling( "Label by Row" ) ) )
);

Code Explanation:

1. Open data table;
2. Disable label for :name column.
3. Launch Graph Builder.
4. Set graph size to 200x450.
5. Hide control panel.
6. Set X variable to :sex.
7. Set Y variable to :height.
8. Add Mosaic element.
9. Enable legend for Mosaic.
10. Label cells by row.

Example 5

Summary: Creates a graph builder object to visualize the relationship between weight and height, with customized scale settings for the y-axis.

Code:

dt = Open("data_table.jmp");
dt:name << Label( 1 );
For Each Row( Row State() = Labeled State( 1 ) );
gb = Graph Builder(
    Size( 450, 320 ),
    Show Control Panel( 0 ),
    Variables( X( :weight ), Y( :height ) ),
    Elements( Points( X, Y, Legend( 1 ) ), Smoother( X, Y, Legend( 2 ) ) ),
    SendToReport(
        Dispatch( {}, "height", ScaleBox,
            {Scale( "Log" ), Format( "Best", 5 ), Min( 50 ), Max( 70 ), Inc( 1 ), Minor Ticks( 8 ), Rotated Labels( "Automatic" )}
        ),
        Dispatch( {}, "Graph Builder", FrameBox,
            {DispatchSeg(
                Marker Seg( 1 ),
                label offset(
                    {1, 26, -9},
                    {3, 53, 3},
                    {6, 21, 58},
                    {8, 13, 55},
                    {12, 68, -3},
                    {13, 3, 68},
                    {16, -114, -20},
                    {19, -80, 5},
                    {20, -25, 199},
                    {22, 84, 47},
                    {23, -73, -30},
                    {24, 4, 28},
                    {27, 24, 39},
                    {30, -35, -51},
                    {31, -65, -33},
                    {33, -138, -15},
                    {36, 6, -15},
                    {38, 25, 2},
                    {39, -44, 49}
                )
            )}
        )
    )
);

Code Explanation:

1. Open data table.
2. Label "name" column.
3. Set row state to labeled.
4. Create Graph Builder object.
5. Set graph size.
6. Hide control panel.
7. Define X and Y variables.
8. Add points and smoother elements.
9. Configure Y axis scale and appearance.
10. Adjust marker labels position.

Graph Builder using Set Modeling Type

Example 1

Summary: Visualizes the relationship between Grade and Goals using a Graph Builder Bar Chart, with Gender as the group variable. The script sets the modeling type for Grade to 'Nominal' initially, then changes it to 'Continuous' when closing the graph.

Code:

// Graph Builder Bar Chart
// Open data table
dt = Open("data_table.jmp");
// Graph Builder Bar Chart
:Grade << Set Modeling Type( "Nominal" );
gb =
Graph Builder(
    Show Control Panel( 0 ),
    Variables(
        X( :Grade ),
        X( :Goals, Position( 1 ) ),
        Group Y( :Gender ),
        Overlay( :Goals )
    ),
    Elements(
        Bar(
            X( 1 ),
            X( 2 ),
            Legend( 2 ),
            Bar Style( "Side by side" ),
            Summary Statistic( "Mean" )
        )
    )
);
gb <<
On Close(
    :Grade <<
    Set Modeling Type( "Continuous" )
);

Code Explanation:

1. Open data table.
2. Set modeling type for Grade.
3. Create Graph Builder object.
4. Hide control panel.
5. Define X variables.
6. Define Y variable.
7. Define group variable.
8. Define overlay variable.
9. Add bar element.
10. Set summary statistic to mean.

Example 2

Summary: Creates a graph to visualize the relationship between Date and Close using Graph Builder, with the Date variable set as ordinal.

Code:

dt = Open("data_table.jmp");
dt:Date << Set Modeling Type( "Ordinal" );
Graph Builder( Size( 537, 351 ), Show Control Panel( 0 ), Variables( X( :Date ), Y( :Close ) ), Elements( Area( X, Y, Legend( 16 ) ) ) );

Code Explanation:

1. Open data table.
2. Set Date modeling type to Ordinal.
3. Create Graph Builder window.
4. Set size of Graph Builder.
5. Hide control panel.
6. Assign Date to X-axis.
7. Assign Close to Y-axis.
8. Add Area element.
9. Set legend for Area element.
10. Display Graph Builder.

Example 3

Summary: Creates a bar chart to examine the relationship between Grade and Goals, with Gender as a grouping variable, using Graph Builder.

Code:

Open("data_table.jmp");
:Grade << Set Modeling Type( Nominal );
gb = Graph Builder(
    Show Control Panel( 0 ),
    Variables( X( :Grade ), X( :Goals, Position( 1 ) ), Group Y( :Gender ), Overlay( :Goals ) ),
    Elements( Bar( X( 1 ), X( 2 ), Legend( 2 ), Bar Style( "Side by side" ), Summary Statistic( "Mean" ) ) )
);

Code Explanation:

1. Open data table.
2. Set Grade modeling type to Nominal.
3. Create Graph Builder object.
4. Hide control panel.
5. Define X variables: Grade, Goals.
6. Define Y variable: Gender.
7. Overlay by Goals.
8. Add Bar element.
9. Set X positions for Bar.
10. Apply legend and bar style.

Example 4

Summary: Creates a bar chart to visualize the relationship between Grade and Goals, while allowing for gender-based grouping and mean summary statistics.

Code:

Open("data_table.jmp");
:Grade << Set Modeling Type( Nominal );
gb = Graph Builder(
    Show Control Panel( 0 ),
    Variables( X( :Grade ), X( :Goals, Position( 1 ) ), Group Y( :Gender ), Overlay( :Goals ) ),
    Elements( Bar( X( 1 ), X( 2 ), Legend( 2 ), Bar Style( "Side by side" ), Summary Statistic( "Mean" ) ) )
);
gb << On Close( :Grade << Set Modeling Type( Continuous ) );

Code Explanation:

1. Open data table;
2. Set Grade modeling type to Nominal.
3. Create Graph Builder object.
4. Hide control panel.
5. Define X variables: Grade, Goals.
6. Set Goals position to 1.
7. Define Group Y variable: Gender.
8. Overlay Goals variable.
9. Add Bar element.
10. Set bar style to Side by side.
11. Use Mean summary statistic.
12. On close, reset Grade modeling type to Continuous.

Graph Builder using Mean

Example 1

Summary: Generates a bar graph to visualize the mean expenditures by ethnicity, utilizing Graph Builder and Local Data Filter features in JMP.

Code:

// Graph Builder: Mean (Expenditures) vs. Ethnicity
// Open data table
dt = Open("data_table.jmp");
// Graph Builder: Mean (Expenditures) vs. Ethnicity
Graph Builder(
    Size( 534, 450 ),
    Show Control Panel( 0 ),
    Variables(
        X( :Ethnicity ),
        Y( :Expenditures )
    ),
    Elements( Bar( X, Y, Legend( 4 ) ) ),
    Local Data Filter(
        Close Outline( 1 ),
        Add Filter(
            columns( :Ethnicity ),
            Where(
                :Ethnicity == {"Hispanic",
                "White not Hispanic"}
            ),
            Display(
                :Ethnicity,
                N Items( 8 )
            )
        )
    )
);

Code Explanation:

1. Open table.
2. Set graph size.
3. Hide control panel.
4. Define X variable.
5. Define Y variable.
6. Add bar element.
7. Create local data filter.
8. Close outline for filter.
9. Add ethnicity filter.
10. Display filtered ethnicity.

Example 2

Summary: Generates a graph that visualizes the mean expenditures by age cohort, with an overlay for ethnicity, using Graph Builder in JMP.

Code:

// Graph Builder: Mean (Expenditures) vs. Age Cohort
// Open data table
dt = Open("data_table.jmp");
// Graph Builder: Mean (Expenditures) vs. Age Cohort
Graph Builder(
    Size( 534, 450 ),
    Show Control Panel( 0 ),
    Variables(
        X( :Age Cohort ),
        Y( :Expenditures ),
        Overlay( :Ethnicity )
    ),
    Elements( Bar( X, Y, Legend( 5 ) ) ),
    Local Data Filter(
        Close Outline( 1 ),
        Add Filter(
            columns( :Ethnicity ),
            Where(
                :Ethnicity == {"Hispanic",
                "White not Hispanic"}
            ),
            Display(
                :Ethnicity,
                N Items( 8 )
            )
        )
    )
);

Code Explanation:

1. Open table.
2. Create Graph Builder.
3. Set size.
4. Hide control panel.
5. Define X variable.
6. Define Y variable.
7. Define overlay variable.
8. Add bar element.
9. Add local data filter.
10. Configure filter settings.

Graph Builder using Function

Example 1

Summary: Opens a data table, clears row states and column selection, defines a Graph Builder function, and generates a plot with points and customized legend model. It also creates a temporary subset of the data, labels rows and columns, and displays the plot in a new window.

Code:

// Graph Builder
// Open data table
dt = Open("data_table.jmp");
// Graph Builder
dt = Current Data Table();
dt << ClearRowStates;
dt << ClearColumnSelection;
GB =
Function( {dtx},
    {Default Local},
    Graph Builder(
        Show Control Panel( 0 ),
        Variables(
            X( :Column ),
            Y( :Row ),
            Overlay( :Quarter )
        ),
        Elements(
            Points(
                X,
                Y,
                Legend( 1 ),
                Jitter( 1 )
            )
        ),
        SendToReport(
            Dispatch( {}, "400", ScaleBox,
                {
                Legend Model(
                    1,
                    Base( 0, 0, 0 ),
                    Base( 1, 0, 0 ),
                    Base( 2, 0, 0 ),
                    Base( 3, 0, 0 )
                )}
            )
        )
    )
);
dt_temp = dt <<
Subset(
    Columns,
    Rows,
    OutputTableName( "Temp" ),
    invisible
);
For( r = 1, r <= N Rows(), r++,
    Row State( r ) = Labeled State( 1 )
);
Column( "Subquarter" ) << Label( 1 );
New Window( "Design for Uniformity Trial",
    <<OnClose( Close( dt_temp ) ),
    Plot = GB( dt_temp )
);

Code Explanation:

1. Open data table.
2. Clear row states.
3. Clear column selection.
4. Define Graph Builder function.
5. Set up Graph Builder with variables.
6. Add points element with jitter.
7. Customize legend model.
8. Create temporary subset of data.
9. Label all rows.
10. Label "Subquarter" column.
11. Create new window with plot.

Example 2

Summary: Creates and customizes a Graph Builder report with interactive elements, including map shapes and pin annotations.

Code:

dt = Open("data_table.jmp");
graphBuilderBuilder = Function( {lns},
    {r, l},
    Show( lns );
    If( lns:_mode == "Picture",
        r = 200;
        l = 0;
    ,
        r = 600;
        l = 1;
    );
    Show( r, l );
    Graph Builder(
        Size( r, r ),
        Show Legend( l ),
        Show Title( l ),
        Show Footer( l ),
        Show Control Panel( 0 ),
        Variables( Y( :Obama ), Y( :McCain, Position( 1 ) ) ),
        Elements( Bar( Y( 1 ), Y( 2 ), Summary Statistic( "Max" ) ) )
    );
);
gb = Graph Builder(
    Show Control Panel( 0 ),
    Variables( Color( :Winner ), Shape( :State ) ),
    Elements( Map Shapes( Legend( 5 ) ) ),
    SendToReport(
        Dispatch( {}, "Graph Builder", FrameBox,
            {DispatchSeg( Shape Seg( 1 ), {Set Graphlet( Picture( here:graphBuilderBuilder( Namespace( "Local" ) ) ) )} ),
            Add Pin Annotation(
                Seg( Shape Seg( 1 ) ),
                Index( 31 ),
                Index Row( 31 ),
                UniqueID( 761423855 ),
                FoundPt( {250, 300} ),
                Origin( {-105.924698121381, 34.8336437854167} ),
                Tag Line( 1 )
            )}
        )
    )
);
frame = Try( (gb << report)[FrameBox( 1 )], Empty() );
gpin = frame << Get Annotation();

Code Explanation:

1. Open data table;
2. Define graphBuilderBuilder function.
3. Check if mode is "Picture".
4. Set size and legend visibility based on mode.
5. Create Graph Builder with specified variables and elements.
6. Create initial Graph Builder with color and shape variables.
7. Add map shapes element with legend.
8. Set graphlet to picture using graphBuilderBuilder.
9. Add pin annotation to graph.
10. Retrieve frame and annotation from report.

Example 3

Summary: Creates a graph builder report with map shapes, utilizing Graph Builder and SendToReport functions to visualize election results.

Code:

Names Default To Here( 1 );
dt = Open("data_table.jmp");
graphBuilderBuilder = Function( {lns},
    {r, l},
    Show( lns );
    If( lns:_mode == "Picture",
        r = 200;
        l = 0;
    ,
        r = 600;
        l = 1;
    );
    Show( r, l );
    Graph Builder(
        Size( r, r ),
        Show Legend( l ),
        Show Title( l ),
        Show Footer( l ),
        Show Control Panel( 0 ),
        Variables( Y( :Obama ), Y( :McCain, Position( 1 ) ) ),
        Elements( Bar( Y( 1 ), Y( 2 ), Summary Statistic( "Max" ) ) )
    );
);
gb = Graph Builder(
    Show Control Panel( 0 ),
    Variables( Color( :Winner ), Shape( :State ) ),
    Elements( Map Shapes( Legend( 5 ) ) ),
    SendToReport(
        Dispatch( {}, "Graph Builder", FrameBox,
            {DispatchSeg( Shape Seg( 1 ), {Set Graphlet( Picture( here:graphBuilderBuilder( Namespace( "Local" ) ) ) )} ),
            Add Pin Annotation(
                Seg( Shape Seg( 1 ) ),
                Index( 31 ),
                Index Row( 31 ),
                UniqueID( 761423855 ),
                FoundPt( {250, 300} ),
                Origin( {-105.924698121381, 34.8336437854167} ),
                Tag Line( 1 )
            )}
        )
    )
);
frame = Try( (gb << report)[FrameBox( 1 )], Empty() );
gpin = frame << Get Annotation();
gpin << Launch Graphlet;

Code Explanation:

1. Set default names scope.
2. Open data table.
3. Define graphBuilderBuilder function.
4. Check label mode.
5. Set graph size and legend visibility.
6. Create initial Graph Builder object.
7. Create main Graph Builder object.
8. Send report with map shapes.
9. Set graphlet for shape segment.
10. Add pin annotation to graph.

Example 4

Summary: Creates a Graph Builder object with customized settings, including hiding the control panel and adjusting legend model settings.

Code:

Open("data_table.jmp");
dt = Current Data Table();
dt << ClearRowStates;
dt << ClearColumnSelection;
GB = Function( {dtx},
    {Default Local},
    Graph Builder(
        Show Control Panel( 0 ),
        Variables( X( :Column ), Y( :Row ), Overlay( :Quarter ) ),
        Elements( Points( X, Y, Legend( 1 ), Jitter( 1 ) ) ),
        SendToReport(
            Dispatch( {}, "400", ScaleBox, {Legend Model( 1, Base( 0, 0, 0 ), Base( 1, 0, 0 ), Base( 2, 0, 0 ), Base( 3, 0, 0 ) )} )
        )
    )
);
dt_temp = dt << Subset( Columns, Rows, OutputTableName( "Temp" ), invisible );
For( r = 1, r <= N Rows(), r++,
    Row State( r ) = Labeled State( 1 )
);
Column( "Subquarter" ) << Label( 1 );

Code Explanation:

1. Open data table.
2. Clear row states.
3. Clear column selection.
4. Define Graph Builder function.
5. Create Graph Builder object.
6. Hide control panel.
7. Set variables for axes and overlay.
8. Add points element with jitter.
9. Adjust legend model settings.
10. Create subset data table.

Example 5

Summary: Creates a Graph Builder design plot for uniformity trials, utilizing the Graph Builder platform and JMP scripting language.

Code:

Open("data_table.jmp");
dt = Current Data Table();
dt << ClearRowStates;
dt << ClearColumnSelection;
GB = Function( {dtx},
    {Default Local},
    Graph Builder(
        Show Control Panel( 0 ),
        Variables( X( :Column ), Y( :Row ), Overlay( :Quarter ) ),
        Elements( Points( X, Y, Legend( 1 ), Jitter( 1 ) ) ),
        SendToReport(
            Dispatch( {}, "400", ScaleBox, {Legend Model( 1, Base( 0, 0, 0 ), Base( 1, 0, 0 ), Base( 2, 0, 0 ), Base( 3, 0, 0 ) )} )
        )
    )
);
dt_temp = dt << Subset( Columns, Rows, OutputTableName( "Temp" ), invisible );
For( r = 1, r <= N Rows(), r++,
    Row State( r ) = Labeled State( 1 )
);
Column( "Subquarter" ) << Label( 1 );
New Window( "Design for Uniformity Trial", <<OnClose( Close( dt_temp ) ), Plot = GB( dt_temp ) );

Code Explanation:

1. Open data table.
2. Assign current table to dt.
3. Clear row states in dt.
4. Clear column selection in dt.
5. Define function GB for Graph Builder.
6. Create subset of dt named dt_temp.
7. Label all rows in dt_temp.
8. Label "Subquarter" column.
9. Create new window for design plot.
10. Close dt_temp on window close.

Graph Builder using Add Rows

Example 1

Summary: Generates a graph to compare prices across different models, utilizing Graph Builder to visualize the data and customize the axis labels.

Code:

// Price Comparison Across Models
Names Default To Here( 1 );
dt =
New Table(
    "Price comparison across models.",
    Add Rows( 12 ),
    New Script(
        "Graph Builder",
        Graph Builder(
            Size( 1076, 500 ),
            Show Control Panel( 0 ),
            Variables(
                X( :Price ),
                Y( :Rooms ),
                Overlay( :Model )
            ),
            Elements(
                Bar( X, Y, Legend( 3 ) )
            ),
            SendToReport(
                Dispatch( {}, "Price",
                    ScaleBox,
                    {
                    Label Row(
                        {
                        Tick Mark(
                            Label(
                                "$1.00e+5"
                            ),
                            Label(
                                "$100,000"
                            )
                        ),
                        Tick Mark(
                            Label(
                                "$2.00e+5"
                            ),
                            Label(
                                "$200,000"
                            )
                        ),
                        Tick Mark(
                            Label(
                                "$3.00e+5"
                            ),
                            Label(
                                "$300,000"
                            )
                        ),
                        Tick Mark(
                            Label(
                                "$4.00e+5"
                            ),
                            Label(
                                "$400,000"
                            )
                        )}
                    )}
                ),
                Dispatch( {},
                    "graph title",
                    TextEditBox,
                    {
                    Set Text(
                        "Rooms vs. Price (Overlay: Model)"
                    )}
                )
            )
        )
    ),
    New Column( "Model",
        Character( 4 ),
        "Nominal",
        Set Property(
            "Value Ordering",
            {"25th", "Mean", "75th"}
        ),
        Set Values(
            {"75th", "75th", "75th",
            "75th", "25th", "25th",
            "25th", "25th", "Mean",
            "Mean", "Mean", "Mean"}
        )
    ),
    New Column( "Price",
        Numeric,
        "Nominal",
        Format(
            "Currency",
            "USD",
            15,
            2
        ),
        Set Values(
            [100000, 200000, 300000,
            400000, 100000, 200000,
            300000, 400000, 100000,
            200000, 300000, 400000]
        )
    ),
    New Column( "Rooms",
        Numeric,
        "Continuous",
        Format( "Fixed Dec", 12, 6 ),
        Set Values(
            [4.66400394223636,
            5.67201147281445,
            6.68001900339253,
            7.68802653397061,
            4.50993666906289,
            6.0903243500998,
            7.67071203113671,
            9.25109971217361,
            4.49146664736503,
            5.73353050993513,
            6.97559437250524,
            8.21765823507534]
        )
    )
);
Eval(
    dt <<
    get table property( "Graph Builder" )
);

Code Explanation:

1. Create new table.
2. Add 12 rows.
3. Define script "Graph Builder".
4. Initialize Graph Builder.
5. Set size 1076x500.
6. Hide control panel.
7. Set variables X: Price, Y: Rooms, Overlay: Model.
8. Add bar element.
9. Customize price axis labels.
10. Set graph title.

Example 2

Summary: Generates a graph builder plot to visualize the interaction between Chemical A and Chemical B over time, utilizing random normal values for peak adjustments.

Code:

Names Default To Here( 1 );
//init
base = 200;
base_sd = 35;
starta = 263;
startb = 268;
peak_seq = [500, 800, 1000, 2000, 5000, 12000, 20000, 12000, 5000, 2000, 800, 400];
// create basic table
dt = New Table( "Background",
    Add Rows( 400 ),
    New Column( "Chemical A", Numeric, "Continuous", Format( "Best", 12 ) ),
    New Column( "Chemical B", Numeric, "Continuous", Format( "Best", 12 ) ),
    New Column( "Time", Numeric, "Continuous", Format( "Best", 12 ), ),
);
// make close peaks for 2 chemicals
For Each Row(
    dt,
    :Time = Row();
    :Chemical A = Round( Random Normal( base, base_sd ), 1 );
    :Chemical B = Round( Random Normal( base, base_sd ), 1 );
);
For Each( {i}, {starta, startb}, 
    For Each( {ii, jj}, peak_seq, 
        :Chemical A[starta+jj] = random normal (ii, ii*.1);
        :Chemical B[startb+jj] = random normal (ii, ii*.1);
    ) 
);
//gb
gb = dt << Graph Builder(
    Size( 525, 454 ),
    Show Control Panel( 0 ),
    Variables( X( :Time ), Y( :Chemical A ), Y( :Chemical B, Position( 1 ) ) ),
    Elements(
        Points( X, Y( 1 ), Y( 2 ), Legend( 5 ) ),
        Smoother( X, Y( 1 ), Y( 2 ), Legend( 6 ) )
    )
);

Code Explanation:

1. Set default name scope.
2. Initialize variables.
3. Define peak sequence.
4. Create new data table.
5. Add rows to table.
6. Add columns for chemicals and time.
7. Populate Time column with row numbers.
8. Populate Chemical A and B with rounded random normal values.
9. Adjust specific rows for close peaks.
10. Generate Graph Builder plot.

Graph Builder using New Project

Summary: Creates a new project, opens a data table, and sets up two windows: 'Global Filter' and 'Shared Local Filter', which include interactive features like data filters, graph builders, and vertical splitters.

Code:

Names Default To Here( 1 );
project = New Project();
project << Run Script(
    dt = Open( "$SAMPLE_DATA/data_table.jmp", Invisible );
    New Window( "Global Filter",
        Set Window ID( "global filter" ),
        H List Box(
            Current Data Table() << Data Filter(
                Location( {170, 292} ),
                Conditional,
                Mode( Select( 0 ), Show( 1 ), Include( 1 ) ),
                Add Filter( columns( :name, :sex, :age ), Display( :name, Size( 181, 255 ), List Display ) )
            ),
            ( Current Data Table(), Oneway( Y( :height ), X( :sex ), Automatic Recalc( 1 ), Means( 1 ), Mean Diamonds( 1 ) ) )
        )
    );
    New Window( "Shared Local Filter",
        Set Window ID( "local filter" ),
        Data Filter Context Box(
            H List Box(
                dt << Data Filter( Local, Add Filter( columns( :sex ), Where( :sex == "F" ) ) ),
                dt << Graph Builder(
                    Size( 425, 356 ),
                    Show Control Panel( 0 ),
                    Fit To Window( "On" ),
                    Variables( X( :weight ), Y( :age ) ),
                    Elements( Box Plot( X, Y, Legend( 4 ) ) ), 
                )
            )
        )
    );
);
project << Show recent files( 0 );
project << Set Layout(
    H Splitter Box(
        Size( 1200, 750 ),
        <<Set Sizes( {0.15, 0.70, 0.15} ),
        Tab Page Box( Title( "Workspace" ), Window ID( "Workspace" ) ),
        V Splitter Box(
            Size( 800, 750 ),
            <<Set Sizes( {0.5, 0.5} ),
            Tab Page Box( Title( "Global Filter" ), Window ID( "global filter" ) ),
            Tab Page Box( Title( "Shared Local Filter" ), Window ID( "local filter" ) )
        ),
        Tab Page Box( Title( "Data Filter for data_table" ), Window ID( "Data Filter" ) )
    )
);

Code Explanation:

1. Set default names.
2. Create new project.
3. Open data table.
4. Create global filter window.
5. Set window ID.
6. Add horizontal list box.
7. Add data filter to current table.
8. Configure data filter settings.
9. Add one-way analysis platform.
10. Create shared local filter window.
11. Set window ID.
12. Add data filter context box.
13. Add horizontal list box.
14. Add local data filter.
15. Add graph builder.
16. Configure graph builder settings.
17. Hide recent files.
18. Set project layout.
19. Add horizontal splitter box.
20. Set sizes.
21. Add workspace tab page.
22. Add vertical splitter box.
23. Set sizes.
24. Add global filter tab page.
25. Add shared local filter tab page.
26. Add data filter tab page.

Graph Builder using New Window

Example 1

Summary: Opens a data table, creates a new window with a tab box, and uses Graph Builder to visualize the relationship between height and weight.

Code:

dt = Open("data_table.jmp");
New Window( "test", Tab Box( "test", dt << Graph Builder( Show Control Panel( 0 ), Variables( X( :height ), Y( :weight ) ) ) ) );

Code Explanation:

1. Open data table.
2. Create new window named "test".
3. Add tab box to window.
4. Name tab "test".
5. Use graph builder on data table.
6. Hide control panel.
7. Set X variable to height.
8. Set Y variable to weight.

Example 2

Summary: Creates a treemap visualization with font customization, utilizing Graph Builder and Local Data Filter to filter data by state.

Code:

dt = Open("data_table.jmp");
New Window( "font customization",
    tp = Tab Page Box(
        "tab title",
        gb = dt << Graph Builder(
            Size( 500, 500 ),
            Show Control Panel( 0 ),
            Variables( X( :Region ), X( :State, Position( 1 ) ) ),
            Elements( Treemap( X( 1 ), X( 2 ), Legend( 3 ) ) ),
            Local Data Filter(
                Show Columns Selector( 1 ),
                Add Filter( columns( :State ), Display( :State, N Items( 6 ), Find( Set Text( "" ) ) ) )
            )
        ),
        <<Set Base Font( "Title" )
    )
);
frame = Report( gb )[FrameBox( 1 )];
fontobj = seg = (frame << Find Seg( "TreeMapSeg" ));
fontobj << Set Base Font( "Title" );

Code Explanation:

1. Open data table.
2. Create new window for customization.
3. Add tab page box to window.
4. Set tab title.
5. Create graph builder object.
6. Set graph size.
7. Hide control panel.
8. Define X variables.
9. Add treemap element.
10. Apply local data filter.

Example 3

Summary: Creates a new window with font size customization and opens a data table, then configures a graph builder to generate a treemap with customized font settings.

Code:

nw = New Window( "Testing Font Size",
    Text Box( "Font Size=10", Set Font Size( 10 ) ),
    Text Box( "Font Size=12", Set Font Size( 12 ) ),
    Text Box( "Font Size=18", Set Font Size( 18 ) ),
    Text Box( "Font Size=30", Set Font Size( 30 ) )
);
dt = Open("data_table.jmp");
New Window( "font customization",
    tp = Tab Page Box(
        "tab title",
        gb = dt << Graph Builder(
            Size( 500, 500 ),
            Show Control Panel( 0 ),
            Variables( X( :Region ), X( :State, Position( 1 ) ) ),
            Elements( Treemap( X( 1 ), X( 2 ), Legend( 3 ) ) ),
            Local Data Filter(
                Show Columns Selector( 1 ),
                Add Filter( columns( :State ), Display( :State, N Items( 6 ), Find( Set Text( "" ) ) ) )
            )
        ),
        <<Set Base Font( "Title" )
    )
);
frame = Report( gb )[FrameBox( 1 )];
fontobj = seg = (frame << Find Seg( "TreeMapSeg" ));
fontobj << Set Base Font( "Title" );

Code Explanation:

1. Create new window "Testing Font Size".
2. Add text box with font size 10.
3. Add text box with font size 12.
4. Add text box with font size 18.
5. Add text box with font size 30.
6. Open data table;
7. Create new window "font customization".
8. Add tab page box with title "tab title".
9. Insert graph builder into tab page.
10. Customize treemap font settings.

Example 4

Summary: Creates a heatmap visualization in JMP, using Graph Builder to display height and weight variables.

Code:

dt = Open("data_table.jmp");
nw = New Window( "test",
    vsb = V Sheet Box(
        <<Hold(
            gb = Graph Builder(
                Show Control Panel( 0 ),
                Show Legend( 0 ),
                Show Footer( 0 ),
                Variables( X( :height ), Y( :weight ) ),
                Elements( Heatmap( X, Y ) )
            )
        ),
        Sheet Part( "Test", Excerpt Box( 1, {Picture Box( 1 )} ) )
    )
);

Code Explanation:

1. Open data table.
2. Create new window titled "test".
3. Add vertical sheet box.
4. Hold graph builder inside.
5. Configure graph builder settings.
6. Set variables for height and weight.
7. Add heatmap element.
8. Create sheet part named "Test".
9. Add excerpt box with picture.
10. Display final window.

Example 5

Summary: Creates a heatmap visualization in JMP, using Graph Builder to display height vs. weight data and wrapping sex variables for analysis.

Code:

Names Default To Here( 1 );
dt = Open("data_table.jmp");
nw = New Window( "test",
    vsb = V Sheet Box(
        <<Hold(
            gb = Graph Builder(
                Show Control Panel( 0 ),
                Show Legend( 0 ),
                Show Footer( 0 ),
                Variables( X( :height ), Y( :weight ) ),
                Elements( Heatmap( X, Y ) )
            )
        ),
        Sheet Part( "Test", Excerpt Box( 1, {Picture Box( 1 )} ) )
    )
);
gb << Variables( Wrap( :sex ) );

Code Explanation:

1. Set default names.
2. Open data table;
3. Create new window titled "test".
4. Add vertical sheet box to window.
5. Hold graph builder configuration.
6. Configure graph builder settings.
7. Add heatmap element to graph.
8. Add sheet part with excerpt box.
9. Add picture box to excerpt box.
10. Update graph variables to wrap sex.

Example 6

Summary: Creates two Graph Builders with customized fill colors in a new window named 'color space', showcasing height as the X variable and bar elements with legends.

Code:

Open("data_table.jmp");
New Window( "color space",
    Graph Builder(
        Size( 533, 454 ),
        Show Control Panel( 0 ),
        Variables( X( :height ) ),
        Elements( Bar( X, Legend( 6 ) ) ),
        SendToReport(
            Dispatch( {}, "400", ScaleBox,
                {Legend Model( 6, Properties( 0, {Fill Color( {0.75, 0., 0.25, "srgb"} )}, Item ID( "Count", 1 ) ) )}
            )
        )
    ),
    Graph Builder(
        Size( 533, 454 ),
        Show Control Panel( 0 ),
        Variables( X( :height ) ),
        Elements( Bar( X, Legend( 6 ) ) ),
        SendToReport(
            Dispatch( {}, "400", ScaleBox,
                {Legend Model( 6, Properties( 0, {Fill Color( {0.75, 0., 0.25, "lrgb"} )}, Item ID( "Count", 1 ) ) )}
            )
        )
    )
);

Code Explanation:

1. Open data_table data
2. Create new window named "color space".
3. Insert first Graph Builder.
4. Set size 533x454.
5. Hide control panel.
6. Set X variable as height.
7. Add bar element with legend.
8. Customize fill color to srgb.
9. Insert second Graph Builder.
10. Set size 533x454.
11. Hide control panel.
12. Set X variable as height.
13. Add bar element with legend.
14. Customize fill color to lrgb.

Example 7

Summary: Creates a bar chart to visualize age distribution by sex, utilizing Graph Builder and Chart elements.

Code:

Open("data_table.jmp");
New Window( "Bar Chart",
    Graph Builder(
        Size( 524, 448 ),
        Show Control Panel( 0 ),
        Variables( X( :sex ), Y( :age ) ),
        Elements( Bar( X, Y, Legend( 4 ), Label( "Label by Value" ) ) )
    ),
    Chart( X( :sex ), Y( Mean( :age ) ), Label by Value, Show Labels, Bar Chart( 1 ) ), 
);

Code Explanation:

1. Open data table;
2. Create new window.
3. Initialize Graph Builder.
4. Set window size.
5. Hide control panel.
6. Assign variables.
7. Add bar element.
8. Label bars by value.
9. Create chart.
10. Display labels.

Example 8

Summary: Vizualizes data points with tooltips in a Graph Builder, utilizing two separate instances to display age and sex variables.

Code:

Open("data_table.jmp");
New Window( "GB Points tooltips",
    Graph Builder(
        Size( 700, 261 ),
        Show Control Panel( 0 ),
        Variables( X( :age ), Group Y( :sex ) ),
        Elements( Points( X, Legend( 3 ), Summary Statistic( "Mean" ) ) ),
        SendToReport(
            Dispatch( {}, "Graph Builder", FrameBox,
                Add Pin Annotation(
                    Seg( Marker Seg( 1 ) ),
                    Index( 0 ),
                    Index Row( 0 ),
                    UniqueID( 691527584 ),
                    FoundPt( {271, 102} ),
                    Origin( {1.77871362940276, 0.0196078431372549} )
                )
            ),
            Dispatch( {}, "Graph Builder", FrameBox( 2 ),
                Add Pin Annotation(
                    Seg( Marker Seg( 1 ) ),
                    Index( 0 ),
                    Index Row( 5 ),
                    UniqueID( 764573808 ),
                    FoundPt( {309, 206} ),
                    Origin( {2.12787136294028, 0.00980392156862742} )
                )
            )
        )
    ),
    Graph Builder(
        Size( 559, 326 ),
        Show Control Panel( 0 ),
        Variables( X( :age ), Y( :sex ) ),
        Elements( Points( X, Y, Legend( 3 ), Summary Statistic( "Mean" ) ) ),
        SendToReport(
            Dispatch( {}, "Graph Builder", FrameBox,
                Add Pin Annotation(
                    Seg( Marker Seg( 1 ) ),
                    Index( 2 ),
                    Index Row( 15 ),
                    UniqueID( 784921858 ),
                    FoundPt( {541, 247} ),
                    Origin( {1.9618320610687, 0.581481481481481} )
                )
            )
        )
    ),
    Graph Builder(
        Size( 667, 359 ),
        Show Control Panel( 0 ),
        Variables( X( :sex ), Y( :age ) ),
        Elements( Points( X, Y, Legend( 3 ), Summary Statistic( "Mean" ) ) ),
        SendToReport(
            Dispatch( {}, "Graph Builder", FrameBox,
                Add Pin Annotation(
                    Seg( Marker Seg( 1 ) ),
                    Index( 0 ),
                    Index Row( 0 ),
                    UniqueID( 690143888 ),
                    FoundPt( {150, 182} ),
                    Origin( {-0.0112219451371571, 1.72439024390244} )
                )
            )
        )
    ), 
);

Code Explanation:

1. Open data table;
2. Create new window titled "GB Points tooltips".
3. Add first Graph Builder with specified size and settings.
4. Set variables for first Graph Builder.
5. Add points element with summary statistic.
6. Add pin annotation to first Graph Builder.
7. Add second Graph Builder with different size and settings.
8. Set variables for second Graph Builder.
9. Add points element with summary statistic.
10. Add pin annotation to second Graph Builder.

Example 9

Summary: Creates four Graph Builders with varying error bar cap shapes, utilizing New Window and Lineup Box to display Age vs Height and Height vs Age plots.

Code:

dt = Open("data_table.jmp");
New Window( "cap shape",
    Lineup Box( N Col( 2 ),
        gb1 = Graph Builder(
            Size( 320, 240 ),
            Show Control Panel( 0 ),
            Variables( X( :Age ), Y( :Height ) ),
            Elements( Line( X, Y, Legend( 4 ), Error Bars( "Range" ) ) )
        ),
        gb2 = Graph Builder(
            Size( 320, 240 ),
            Show Control Panel( 0 ),
            Variables( X( :Age ), Y( :Height ) ),
            Elements( Line( X, Y, Legend( 4 ), Error Bars( "Range" ) ) )
        ),
        gb3 = Graph Builder(
            Size( 320, 240 ),
            Show Control Panel( 0 ),
            Variables( X( :height ), Y( :age ) ),
            Elements( Line( X, Y, Legend( 4 ), Error Interval( "Range" ) ) )
        ),
        gb4 = Graph Builder(
            Size( 320, 240 ),
            Show Control Panel( 0 ),
            Variables( X( :height ), Y( :age ) ),
            Elements( Line( X, Y, Legend( 4 ), Error Interval( "Range" ) ) )
        )
    )
);
frame = Report( gb1 )[FrameBox( 1 )];
seg = (frame << Find Seg( "Bar Seg" ));
seg << Set Error Bar Cap Shape( "Line", "Arrow" );
frame = Report( gb2 )[FrameBox( 1 )];
seg = (frame << Find Seg( "Bar Seg" ));
seg << Set Error Bar Cap Shape( "Arrow", "Line" );
frame = Report( gb3 )[FrameBox( 1 )];
seg = (frame << Find Seg( "Bar Seg" ));
seg << Set Error Bar Cap Shape( "Line", "Arrow" );
frame = Report( gb4 )[FrameBox( 1 )];
seg = (frame << Find Seg( "Bar Seg" ));

Code Explanation:

1. Open data table;
2. Create new window titled "cap shape".
3. Create lineup box with 2 columns.
4. Create first Graph Builder with Age vs Height.
5. Create second Graph Builder with Age vs Height.
6. Create third Graph Builder with Height vs Age.
7. Create fourth Graph Builder with Height vs Age.
8. Access first graph's frame.
9. Find bar segment.
10. Set error bar cap shape to "Line", "Arrow".

Example 10

Summary: Creates and customizes four graph builder objects with error bars, allowing for interactive exploration of data relationships.

Code:

Names Default To Here( 1 );
dt = Open("data_table.jmp");
New Window( "cap shape",
    Lineup Box( N Col( 2 ),
        gb1 = Graph Builder(
            Size( 320, 240 ),
            Show Control Panel( 0 ),
            Variables( X( :Age ), Y( :Height ) ),
            Elements( Line( X, Y, Legend( 4 ), Error Bars( "Range" ) ) )
        ),
        gb2 = Graph Builder(
            Size( 320, 240 ),
            Show Control Panel( 0 ),
            Variables( X( :Age ), Y( :Height ) ),
            Elements( Line( X, Y, Legend( 4 ), Error Bars( "Range" ) ) )
        ),
        gb3 = Graph Builder(
            Size( 320, 240 ),
            Show Control Panel( 0 ),
            Variables( X( :height ), Y( :age ) ),
            Elements( Line( X, Y, Legend( 4 ), Error Interval( "Range" ) ) )
        ),
        gb4 = Graph Builder(
            Size( 320, 240 ),
            Show Control Panel( 0 ),
            Variables( X( :height ), Y( :age ) ),
            Elements( Line( X, Y, Legend( 4 ), Error Interval( "Range" ) ) )
        )
    )
);
frame = Report( gb1 )[FrameBox( 1 )];
seg = (frame << Find Seg( "Bar Seg" ));
seg << Set Error Bar Cap Shape( "Line", "Arrow" );
frame = Report( gb2 )[FrameBox( 1 )];
seg = (frame << Find Seg( "Bar Seg" ));
seg << Set Error Bar Cap Shape( "Arrow", "Line" );
frame = Report( gb3 )[FrameBox( 1 )];
seg = (frame << Find Seg( "Bar Seg" ));
seg << Set Error Bar Cap Shape( "Line", "Arrow" );
frame = Report( gb4 )[FrameBox( 1 )];
seg = (frame << Find Seg( "Bar Seg" ));
seg << Set Error Bar Cap Shape( "Arrow", "Line" );

Code Explanation:

1. Open data table.
2. Create new window titled "cap shape".
3. Add lineup box with 2 columns.
4. Create first graph builder object.
5. Configure first graph builder size and variables.
6. Add line element with error bars to first graph builder.
7. Create second graph builder object.
8. Configure second graph builder size and variables.
9. Add line element with error bars to second graph builder.
10. Create third graph builder object.
11. Configure third graph builder size and variables.
12. Add line element with error interval to third graph builder.
13. Create fourth graph builder object.
14. Configure fourth graph builder size and variables.
15. Add line element with error interval to fourth graph builder.
16. Access first graph builder frame.
17. Find bar segment in first graph builder.
18. Set error bar cap shape for first graph builder.
19. Access second graph builder frame.
20. Find bar segment in second graph builder.
21. Set error bar cap shape for second graph builder.
22. Access third graph builder frame.
23. Find bar segment in third graph builder.
24. Set error bar cap shape for third graph builder.
25. Access fourth graph builder frame.
26. Find bar segment in fourth graph builder.
27. Set error bar cap shape for fourth graph builder.

Example 11

Summary: Creates a stacked bar chart with multiple series, utilizing Graph Builder to customize the appearance and interactive features.

Code:

Open("data_table.jmp");
New Window( "Bar Chart",
    Chart( X( :Type, :Size Co ), Y( Mean( :Name( "Sales ($M)" ) ) ), Stack Bars( 1 ), Bar Chart( 1 ) ),
    Graph Builder(
        Size( 550, 448 ),
        Show Control Panel( 0 ),
        Legend Position( "Bottom" ),
        Variables( X( :Type ), Y( :Name( "Sales ($M)" ) ), Overlay( :Size Co ) ),
        Elements( Bar( X, Y, Legend( 4 ), Bar Style( "Stacked" ) ) ),
        SendToReport(
            Dispatch( {}, "Type", ScaleBox,
                {Add Ref Line( 0.5, "Solid", "Medium Light Gray", "", 1 ), Label Row( {Automatic Tick Marks( 0 ), Inside Ticks( 1 )} )}
            ),
            Dispatch( {}, "Sales ($M)", ScaleBox, {Format( "Fixed Dec", 12, 2 )} ),
            Dispatch( {}, "400", ScaleBox,
                {Legend Model(
                    4,
                    Properties( 0, {Fill Color( 19 )} ),
                    Properties( 1, {Fill Color( 4 )} ),
                    Properties( 2, {Fill Color( 21 )} )
                )}
            ),
            Dispatch( {}, "graph title", TextEditBox, {Set Text( "" )} ),
            Dispatch( {}, "X title", TextEditBox, {Set Text( "Size Co within Type" )} ),
            Dispatch( {}, "Y title", TextEditBox, {Set Text( "Mean(Sales ($M))" )} ),
            Dispatch( {}, "400", LegendBox, {Orientation( "Horizontal" ), Sides( "Left" )} )
        )
    )
);

Code Explanation:

1. Open data table.
2. Create new window.
3. Initialize chart.
4. Set X variables.
5. Set Y variable.
6. Stack bars.
7. Enable bar chart.
8. Configure Graph Builder size.
9. Hide control panel.
10. Set legend position.

Example 12

Summary: Creates three bar charts to visualize the mean, sum, and count of 'age' by 'sex', using Graph Builder in JMP.

Code:

Open("data_table.jmp");
New Window( "Bar Chart",
    Graph Builder(
        Size( 480, 261 ),
        Show Control Panel( 0 ),
        Variables( X( :age ), Group Y( :sex ) ),
        Elements( Bar( X, Legend( 4 ), Summary Statistic( "Mean" ), Label( "Label by Value" ) ) )
    ),
    Graph Builder(
        Size( 480, 261 ),
        Show Control Panel( 0 ),
        Variables( X( :age ), Group Y( :sex ) ),
        Elements( Bar( X, Legend( 4 ), Summary Statistic( "Sum" ), Label( "Label by Value" ) ) )
    ),
    Graph Builder(
        Size( 480, 261 ),
        Show Control Panel( 0 ),
        Variables( X( :age ), Group Y( :sex ) ),
        Elements( Bar( X, Legend( 4 ), Summary Statistic( "N" ), Label( "Label by Value" ) ) )
    ),
    Chart(
        Grouping( :sex ),
        X( :age ),
        Y( N ),
        Label by Value,
        Show Labels,
        Bar Chart( 1 ),
        SendToReport(
            Dispatch( {}, "102", ScaleBox, {Label Row( Show Minor Ticks( 0 ) )} ),
            Dispatch( {}, "", AxisBox, {Add Axis Label( "" )} ),
            Dispatch( {}, "", AxisBox( 3 ), {Add Axis Label( "" )} )
        )
    ), 
);

Code Explanation:

1. Open data table.
2. Create new window titled "Bar Chart".
3. Insert first Graph Builder.
4. Set size and hide control panel.
5. Assign X variable: age.
6. Assign Group Y variable: sex.
7. Add bar element with mean summary statistic.
8. Label bars by value.
9. Insert second Graph Builder.
10. Set size and hide control panel.
11. Assign X variable: age.
12. Assign Group Y variable: sex.
13. Add bar element with sum summary statistic.
14. Label bars by value.
15. Insert third Graph Builder.
16. Set size and hide control panel.
17. Assign X variable: age.
18. Assign Group Y variable: sex.
19. Add bar element with count summary statistic.
20. Label bars by value.
21. Insert Chart for additional graph.
22. Group by sex.
23. Assign X variable: age.
24. Assign Y variable: count.
25. Label by value.
26. Show labels.
27. Enable bar chart.
28. Customize report layout.

Example 13

Summary: Creates a bar chart with multiple variables, utilizing Graph Builder and Chart to visualize data from a JMP data table.

Code:

Open("data_table.jmp");
New Window( "Bar Chart",
    Graph Builder(
        Size( 454, 394 ),
        Show Control Panel( 0 ),
        Variables( X( :Type ), X( :Size Co, Position( 1 ) ), Y( :Name( "Profits ($M)" ) ), Color( :Size Co ) ),
        Elements( Bar( X( 1 ), X( 2 ), Y, Legend( 2 ) ) )
    ),
    Chart( X( :Type, :Size Co ), Y( Mean( :Name( "Profits ($M)" ) ) ), Bar Chart( 1 ) ), 
);

Code Explanation:

1. Open data table;
2. Create new window.
3. Initialize Graph Builder.
4. Set window size.
5. Hide control panel.
6. Define X, Y, and color variables.
7. Add bar element.
8. Create chart object.
9. Set X and Y variables for chart.
10. Display bar chart.

Example 14

Summary: Creates two bar charts in a new window, with variables X=age, Y=height, Overlay=sex, and Color=sex.

Code:

Open("data_table.jmp");
New Window( "Bar Chart",
    Graph Builder(
        Size( 454, 333 ),
        Show Control Panel( 0 ),
        Variables( X( :age ), Y( :height ), Overlay( :sex ), Color( :sex ) ),
        Elements( Bar( X, Y, Legend( 5 ) ) )
    ),
    Graph Builder(
        Size( 454, 333 ),
        Show Control Panel( 0 ),
        Variables( X( :age ), Y( :height ), Overlay( :sex ), Size( :sex ) ),
        Elements( Bar( X, Y, Legend( 5 ) ) )
    ), 
);

Code Explanation:

1. Open data table;
2. Create new window titled "Bar Chart".
3. Add first Graph Builder element.
4. Set size to 454x333 pixels.
5. Hide control panel.
6. Define variables: X=age, Y=height, Overlay=sex, Color=sex.
7. Add bar element with legend.
8. Add second Graph Builder element.
9. Set size to 454x333 pixels.
10. Hide control panel.

Example 15

Summary: Creates a bar chart to visualize age distribution by sex, utilizing Graph Builder and specifying summary statistics.

Code:

Open("data_table.jmp");
New Window( "Bar Chart",
    Graph Builder(
        Size( 458, 361 ),
        Show Control Panel( 0 ),
        Variables( X( :sex ), Y( :age ) ),
        Elements( Bar( X, Y, Legend( 1 ), Summary Statistic( "Sum" ) ) )
    ),
    Chart( X( :sex ), Y( Sum( :age ) ), Bar Chart( 1 ) ), 
);

Code Explanation:

1. Open data table.
2. Create new window.
3. Initialize Graph Builder.
4. Set window size.
5. Hide control panel.
6. Define X and Y variables.
7. Add bar element.
8. Set summary statistic to sum.
9. Create chart object.
10. Plot bar chart.

Example 16

Summary: Creates a stacked bar chart with sum summary statistic, filtering data by age and sex, and displaying weight distribution across different age groups for female subjects.

Code:

dt = Open("data_table.jmp");
dt << select where( :age == 14 & :sex == "F" );
dt << exclude;
dt << clear select;
New Window( "Stacked Bar Chart",
    Graph Builder(
        Size( 491, 398 ),
        Show Control Panel( 0 ),
        Variables( X( :age ), Y( :weight ), Overlay( :sex ) ),
        Elements( Bar( X, Y, Legend( 4 ), Bar Style( "Stacked" ), Summary Statistic( "Sum" ), Label( "Label by Value" ) ) )
    ),
    Chart( X( :age, :sex ), Y( Sum( :weight ) ), Stack Bars( 1 ), Label by Value, Show Labels, Bar Chart( 1 ) ), 
);

Code Explanation:

1. Open data table;
2. Select rows where age is 14 and sex is F.
3. Exclude selected rows.
4. Clear selection.
5. Create new window for chart.
6. Initialize Graph Builder.
7. Set size to 491x398.
8. Hide control panel.
9. Define variables: X(age), Y(weight), Overlay(sex).
10. Add stacked bar element with sum summary statistic.

Example 17

Summary: Creates a stacked bar chart to visualize weight distribution by age and sex, utilizing Graph Builder and hiding selected rows.

Code:

dt = Open("data_table.jmp");
dt << select where( :age == 14 & :sex == "F" );
dt << hide;
dt << clear select;
New Window( "Stacked Bar Chart",
    Graph Builder(
        Size( 491, 398 ),
        Show Control Panel( 0 ),
        Variables( X( :age ), Y( :weight ), Overlay( :sex ) ),
        Elements( Bar( X, Y, Legend( 4 ), Bar Style( "Stacked" ), Summary Statistic( "Sum" ), Label( "Label by Value" ) ) )
    ),
    Chart( X( :age, :sex ), Y( Sum( :weight ) ), Stack Bars( 1 ), Label by Value, Show Labels, Bar Chart( 1 ) ), 
);

Code Explanation:

1. Open data table.
2. Select rows where age is 14 and sex is female.
3. Hide selected rows.
4. Clear row selection.
5. Create new window titled "Stacked Bar Chart".
6. Initialize Graph Builder.
7. Set graph size to 491x398 pixels.
8. Hide control panel.
9. Define variables: X as age, Y as weight, Overlay as sex.
10. Add stacked bar element with sum summary statistic.

Example 18

Summary: Creates three Graph Builders with bar elements, ordered by count in descending and ascending order, and without ordering, to visualize sex distribution.

Code:

Open("data_table.jmp");
New Window( "Graph Builder Bar - Order By",
    V List Box(
        Graph Builder(
            Size( 441, 267 ),
            Show Control Panel( 0 ),
            Variables(
                X(
                    :sex,
                    Order By( Transform Column( "Count", Formula( Col Number( :sex, :sex ) ) ), Descending, Order Statistic( "Mean" ) )
                )
            ),
            Elements( Bar( X, Legend( 4 ) ) ),
            SendToReport( Dispatch( {}, "graph title", TextEditBox, {Set Text( "Order by Count" )} ) )
        ),
        Graph Builder(
            Size( 441, 267 ),
            Show Control Panel( 0 ),
            Variables(
                X(
                    :sex,
                    Order By( Transform Column( "Count", Formula( Col Number( :sex, :sex ) ) ), Ascending, Order Statistic( "Mean" ) )
                )
            ),
            Elements( Bar( X, Legend( 4 ) ) ),
            SendToReport( Dispatch( {}, "graph title", TextEditBox, {Set Text( "Order by Count" )} ) )
        ),
        Graph Builder(
            Size( 441, 267 ),
            Show Control Panel( 0 ),
            Variables( X( :sex ) ),
            Elements( Bar( X, Legend( 4 ) ) ),
            SendToReport( Dispatch( {}, "graph title", TextEditBox, {Set Text( "Order by Count" )} ) )
        )
    )
);

Code Explanation:

1. Open data table;
2. Create new window.
3. Add vertical list box.
4. Insert first Graph Builder.
5. Set size for first graph.
6. Hide control panel.
7. Define X variable with descending order.
8. Add bar element.
9. Set report title for first graph.
10. Insert second Graph Builder.
11. Set size for second graph.
12. Hide control panel.
13. Define X variable with ascending order.
14. Add bar element.
15. Set report title for second graph.
16. Insert third Graph Builder.
17. Set size for third graph.
18. Hide control panel.
19. Define X variable without order.
20. Add bar element.
21. Set report title for third graph.

Example 19

Summary: Creates multiple Graph Builders with varying error bars and titles in a new window, utilizing variables X, Y, and Overlay for customization.

Code:

Open("data_table.jmp");
New Window( "Test",
    V List Box(
        Graph Builder(
            Size( 400, 300 ),
            Show Control Panel( 0 ),
            Variables( X( :age ), Y( :height ), Overlay( :sex ) ),
            Elements( Bar( X, Y, Legend( 11 ), Error Bars( "Range" ) ) ),
            SendToReport( Dispatch( {}, "Graph Builder", OutlineBox, {Set Title( "Graph Builder with Range Error Bars" )} ) )
        ),
        H List Box(
            Graph Builder(
                Size( 400, 300 ),
                Show Control Panel( 0 ),
                Variables( X( :age ), Y( :height ), Overlay( :sex ) ),
                Elements( Bar( X, Y, Legend( 11 ), Error Bars( "Interquartile Range" ) ) ),
                SendToReport(
                    Dispatch( {}, "Graph Builder", OutlineBox, {Set Title( "Graph Builder with Interquartile Range Error Bars" )} )
                )
            ),
            Graph Builder(
                Size( 400, 300 ),
                Show Control Panel( 0 ),
                Variables( X( :age ), Y( :height ), Overlay( :sex ) ),
                Elements( Bar( X, Y, Legend( 11 ), Error Bars( "Standard Error" ) ) ),
                SendToReport( Dispatch( {}, "Graph Builder", OutlineBox, {Set Title( "Graph Builder with Standard Error Error Bars" )} ) )
            )
        ),
        H List Box(
            Graph Builder(
                Size( 400, 300 ),
                Show Control Panel( 0 ),
                Variables( X( :age ), Y( :height ), Overlay( :sex ) ),
                Elements( Bar( X, Y, Legend( 11 ), Error Bars( "Standard Deviation" ) ) ),
                SendToReport(
                    Dispatch( {}, "Graph Builder", OutlineBox, {Set Title( "Graph Builder with Standard Deviation Error Bars" )} )
                )
            ),
            Graph Builder(
                Size( 400, 300 ),
                Show Control Panel( 0 ),
                Variables( X( :age ), Y( :height ), Overlay( :sex ) ),
                Elements( Bar( X, Y, Legend( 11 ), Error Bars( "Confidence Interval" ) ) ),
                SendToReport(
                    Dispatch( {}, "Graph Builder", OutlineBox, {Set Title( "Graph Builder with Confidence Interval Error Bars" )} )
                )
            )
        )
    )
);

Code Explanation:

1. Open data table;
2. Create new window named "Test".
3. Add vertical list box to window.
4. Insert first Graph Builder.
5. Set size to 400x300.
6. Hide control panel.
7. Set X variable to age.
8. Set Y variable to height.
9. Overlay by sex.
10. Add bar element with range error bars.
11. Set title for first graph.
12. Add horizontal list box.
13. Insert second Graph Builder.
14. Set size to 400x300.
15. Hide control panel.
16. Set X variable to age.
17. Set Y variable to height.
18. Overlay by sex.
19. Add bar element with interquartile range error bars.
20. Set title for second graph.
21. Insert third Graph Builder.
22. Set size to 400x300.
23. Hide control panel.
24. Set X variable to age.
25. Set Y variable to height.
26. Overlay by sex.
27. Add bar element with standard error error bars.
28. Set title for third graph.
29. Add another horizontal list box.
30. Insert fourth Graph Builder.
31. Set size to 400x300.
32. Hide control panel.
33. Set X variable to age.
34. Set Y variable to height.
35. Overlay by sex.
36. Add bar element with standard deviation error bars.
37. Set title for fourth graph.
38. Insert fifth Graph Builder.
39. Set size to 400x300.
40. Hide control panel.
41. Set X variable to age.
42. Set Y variable to height.
43. Overlay by sex.
44. Add bar element with confidence interval error bars.
45. Set title for fifth graph.

Example 20

Summary: Creates a Graph Builder Bar with two elements, each displaying bar charts for age and weight data, grouped by sex.

Code:

Open("data_table.jmp");
New Window( "Graph Builder Bar",
    H List Box(
        Graph Builder(
            Show Control Panel( 0 ),
            Size( 457, 305 ),
            Variables( X( :age ), Y( :weight ), Group X( :sex ), Overlay( :sex ) ),
            Elements( Bar( X, Y, Legend( 5 ), Summary Statistic( "% of Total" ) ) )
        ),
        Graph Builder(
            Show Control Panel( 0 ),
            Size( 457, 305 ),
            Variables( X( :age ), Y( :weight ), Group X( :sex ) ),
            Elements( Bar( X, Y, Legend( 5 ), Summary Statistic( "% of Total" ) ) )
        )
    )
);

Code Explanation:

1. Open data table;
2. Create new window titled "Graph Builder Bar".
3. Add horizontal list box to window.
4. Insert first Graph Builder element.
5. Hide control panel in first Graph Builder.
6. Set size for first Graph Builder.
7. Define variables for first Graph Builder.
8. Add bar element to first Graph Builder.
9. Insert second Graph Builder element.
10. Configure second Graph Builder similarly to first.

Example 21

Summary: Creates two Graph Builders with contour elements to visualize data in a new window, with one builder displaying contours without smoothing and the other with smoothing enabled.

Code:

Open("data_table.jmp");
New Window( "Smooth contours",
    H List Box(
        Graph Builder(
            Size( 480, 372 ),
            Show Control Panel( 0 ),
            Variables( X( :X ), Y( :Y ), Color( :Z ) ),
            Elements( Contour( X, Y, Legend( 4 ) ) )
        ),
        Graph Builder(
            Size( 480, 372 ),
            Show Control Panel( 0 ),
            Variables( X( :X ), Y( :Y ), Color( :Z ) ),
            Elements( Contour( X, Y, Legend( 4 ), Smoothness( 0.15 ) ) )
        )
    )
);

Code Explanation:

1. Open data_table data
2. Create new window titled "Smooth contours".
3. Add horizontal list box.
4. Insert first Graph Builder.
5. Set size 480x372.
6. Hide control panel.
7. Define X, Y, Color variables.
8. Add contour element without smoothing.
9. Insert second Graph Builder.
10. Set size 480x372.
11. Hide control panel.
12. Define X, Y, Color variables.
13. Add contour element with smoothing 0.15.

Example 22

Summary: Creates a new window with a vertical list box containing a Graph Builder that visualizes data from a specified table, utilizing variables for height, weight, sex, and age.

Code:

tdt = Open("data_table.jmp");
test_wdw = New Window( "WTH",
    V List Box(
        gbw = Graph Builder(
            Size( 1000, 1000 ),
            Show Control Panel( 0 ),
            Show Legend( 0 ),
            Variables( X( :height ), Y( :weight ), Color( :sex ), Size( :age ) )
        )
    )
);

Code Explanation:

1. Open data table.
2. Create new window.
3. Add vertical list box.
4. Insert Graph Builder.
5. Set graph size.
6. Hide control panel.
7. Hide legend.
8. Define X variable.
9. Define Y variable.
10. Define color variable.
11. Define size variable.

Example 23

Summary: Creates a new window with two tabs, each containing a Graph Builder that visualizes data relationships and hides control panels.

Code:

Open("data_table.jmp");
New Window( "tabtest",
    Tab Box(
        Tab Page Box(
            Title( "Graph 1" ),
            Graph Builder(
                Show Control Panel( 0 ),
                Variables( X( :height ), Y( :weight ), Overlay( :sex ) ),
                Elements( Points( X, Y, Legend( 1 ) ), Smoother( X, Y, Legend( 2 ) ) )
            )
        ),
        Tab Page Box(
            Title( "Graph 2" ),
            Graph Builder(
                Show Control Panel( 0 ),
                Variables( X( :age ), Y( :height ), Y( :weight ) ),
                Elements( Position( 1, 1 ), Line( X, Y, Legend( 1 ) ) ),
                Elements( Position( 1, 2 ), Bar( X, Y, Legend( 2 ) ) )
            )
        )
    )
);

Code Explanation:

1. Open data table.
2. Create new window titled "tabtest".
3. Add tab box with two tabs.
4. First tab titled "Graph 1".
5. Insert Graph Builder.
6. Hide control panel.
7. Set X to height, Y to weight, overlay by sex.
8. Add points and smoother elements.
9. Second tab titled "Graph 2".
10. Insert another Graph Builder.
11. Hide control panel.
12. Set X to age, Y to height and weight.
13. Add line element in first position.
14. Add bar element in second position.

Example 24

Summary: Creates a Graph Builder with Color role, visualizing data by sex, height, and age, and generating two heatmap and bar elements for comparison.

Code:

Open("data_table.jmp");
New Window( "Graph Builder with Color role",
    Graph Builder(
        Size( 467, 369 ),
        Show Control Panel( 0 ),
        Variables( X( :sex ), Y( :height ), Color( :age ) ),
        Elements( Heatmap( X, Y, Legend( 4 ), Label( "Label by Value" ), Max Label Size( 4.037 ) ) ),
        SendToReport(
            Dispatch( {}, "Graph Builder", OutlineBox, {Set Title( "Graph Builder: Should behave like GB Bar chart with Color role" )} )
        )
    ),
    Graph Builder(
        Size( 467, 369 ),
        Show Control Panel( 0 ),
        Variables( X( :sex ), Y( :height ), Color( :age ) ),
        Elements( Bar( X, Y, Legend( 1 ), Label( "Label by Value" ) ) )
    )
);

Code Explanation:

1. Open data table;
2. Create new window titled "Graph Builder with Color role".
3. Initiate first Graph Builder instance.
4. Set size to 467x369 pixels.
5. Hide control panel.
6. Assign variables: X=sex, Y=height, Color=age.
7. Add heatmap element with legend and labels.
8. Set maximum label size.
9. Set title for first graph.
10. Initiate second Graph Builder instance.
11. Set size to 467x369 pixels.
12. Hide control panel.
13. Assign same variables: X=sex, Y=height, Color=age.
14. Add bar element with legend and labels.

Example 25

Summary: Creates a heatmap visualization in JMP, using Graph Builder to display height and weight data.

Code:

Open("data_table.jmp");
nw = New Window( "test",
    vsb = V Sheet Box(
        <<Hold(
            gb = Graph Builder(
                Show Control Panel( 0 ),
                Show Legend( 0 ),
                Show Footer( 0 ),
                Variables( X( :height ), Y( :weight ) ),
                Elements( Heatmap( X, Y ) )
            )
        ),
        Sheet Part( "Test", Excerpt Box( 1, {Picture Box( 1 )} ) )
    )
);

Code Explanation:

1. Open data table;
2. Create new window titled "test".
3. Add vertical sheet box to window.
4. Hold graph builder configuration.
5. Initialize graph builder.
6. Hide control panel.
7. Hide legend.
8. Hide footer.
9. Set X variable to height.
10. Set Y variable to weight.
11. Add heatmap element to graph builder.

Example 26

Summary: Creates a heatmap visualization in JMP, utilizing Graph Builder to display relationships between height and weight variables.

Code:

dt = Open("data_table.jmp");
nw = New Window( "test",
    vsb = V Sheet Box(
        <<Hold(
            gb = Graph Builder(
                Show Control Panel( 0 ),
                Show Legend( 0 ),
                Show Footer( 0 ),
                Variables( X( :height ), Y( :weight ) ),
                Elements( Heatmap( X, Y ) )
            )
        ),
        Sheet Part( "Test", Excerpt Box( 1, {Picture Box( 1 )} ) )
    )
);
gb << Variables( Wrap( :sex ) );

Code Explanation:

1. Open data table.
2. Create new window named "test".
3. Add vertical sheet box to window.
4. Hold graph builder object.
5. Configure graph builder settings.
6. Set variables for heatmap.
7. Add heatmap element.
8. Add sheet part with excerpt box.
9. Add picture box to excerpt box.
10. Wrap sex variable in heatmap.

Example 27

Summary: Creates a Graph Builder Heatmap with two heatmaps, each with its own legend, and adds pin annotations to visualize relationships between age, height, and weight.

Code:

Open("data_table.jmp");
New Window( "Graph Builder Heatmap",
    Graph Builder(
        Size( 477, 379 ),
        Show Control Panel( 0 ),
        Variables( X( :age ), Y( :height ), Y( :weight, Position( 1 ), Side( "Right" ) ) ),
        Elements( Heatmap( X, Y( 1 ), Legend( 10 ) ), Heatmap( X, Y( 2 ), Legend( 11 ) ) ),
        SendToReport(
            Dispatch( {}, "400", ScaleBox,
                {Legend Model( 10, Properties( 0, {gradient( {Color Theme( "Yellow to Red" ), Width( 12 )} )} ) ),
                Legend Model( 11, Properties( 0, {gradient( {Color Theme( "White to Green" ), Width( 12 )} )} ) )}
            ),
            Dispatch( {}, "Graph Builder", FrameBox,
                {Add Pin Annotation(
                    Seg( RectSeg( 1 ) ),
                    Index( 15 ),
                    Index Row( 15 ),
                    UniqueID( 404827919 ),
                    FoundPt( {180, 153} ),
                    Origin( {1.21824480369515, 66.6454081632653} )
                ), Add Pin Annotation(
                    Seg( RectSeg( 2 ) ),
                    Index( 0 ),
                    Index Row( 0 ),
                    UniqueID( 404839496 ),
                    FoundPt( {123, 401} ),
                    Origin( {0.428406466512702, 72.8571428571429} )
                )}
            )
        )
    ),
    Graph Builder(
        Size( 508, 378 ),
        Show Control Panel( 0 ),
        Variables( X( :age ), Y( :height ), Y( :weight, Position( 1 ) ) ),
        Elements( Heatmap( X, Y( 1 ), Y( 2 ), Legend( 10 ) ) ),
        SendToReport(
            Dispatch( {}, "400", ScaleBox,
                {Legend Model( 10, Properties( 0, {gradient( {Color Theme( "White to Green" ), Width( 12 )} )}, Item ID( "Count", 1 ) ) )}
            ),
            Dispatch( {}, "Graph Builder", FrameBox,
                {Add Pin Annotation(
                    Seg( RectSeg( 1 ) ),
                    Index( 0 ),
                    Index Row( 4 ),
                    UniqueID( 1797737008 ),
                    FoundPt( {114, 741} ),
                    Origin( {0.25, 52.890625} ),
                    RightOfCenter( 0 ),
                    Tag Line( 1 )
                ), Add Pin Annotation(
                    Seg( RectSeg( 1 ) ),
                    Index( 6 ),
                    Index Row( 11 ),
                    UniqueID( 1797737014 ),
                    FoundPt( {181, 541} ),
                    Origin( {1.11637931034483, 68.515625} ),
                    RightOfCenter( 0 ),
                    Tag Line( 1 )
                )}
            )
        )
    )
);

Code Explanation:

1. Open data table;
2. Create new window titled "Graph Builder Heatmap".
3. Initialize first Graph Builder with specified size.
4. Hide control panel.
5. Set X variable to age.
6. Set Y variables to height and weight.
7. Create two heatmaps with different legends.
8. Customize legend colors and widths.
9. Add pin annotations to first graph.
10. Initialize second Graph Builder with different size.
11. Hide control panel.
12. Set X variable to age.
13. Set Y variables to height and weight.
14. Create single heatmap with combined variables.
15. Customize legend color and width.
16. Add pin annotations to second graph.

Example 28

Summary: Creates two histograms in a new window, with one graph displaying age vs. height and the other displaying height vs. age.

Code:

Open("data_table.jmp");
New Window( "Histogram",
    Graph Builder( Show Control Panel( 0 ), Variables( X( :age ), Y( :height ) ), Elements( Histogram( X, Y, Legend( 2 ), Horizontal ) ) ),
    Graph Builder( Show Control Panel( 0 ), Variables( X( :height ), Y( :age ) ), Elements( Histogram( X, Y, Legend( 2 ), Vertical ) ) ), 
);

Code Explanation:

1. Open data table;
2. Create new window named "Histogram".
3. Insert first Graph Builder element.
4. Hide control panel.
5. Set X variable to age.
6. Set Y variable to height.
7. Add histogram element.
8. Position legend horizontally.
9. Insert second Graph Builder element.
10. Hide control panel.
11. Set X variable to height.
12. Set Y variable to age.
13. Add histogram element.
14. Position legend vertically.

Example 29

Summary: Creates a line chart with multiple groupings, summarizing mean, sum, and count by age and sex.

Code:

dt = Open("data_table.jmp");
New Window( "Line Chart",
    Graph Builder(
        Size( 452, 261 ),
        Show Control Panel( 0 ),
        Variables( X( :age ), Group Y( :sex ) ),
        Elements( Line( X, Legend( 8 ), Summary Statistic( "Mean" ) ) )
    ),
    Graph Builder(
        Size( 452, 261 ),
        Show Control Panel( 0 ),
        Variables( X( :age ), Group Y( :sex ) ),
        Elements( Line( X, Legend( 8 ), Summary Statistic( "Sum" ) ) )
    ),
    Graph Builder(
        Size( 452, 261 ),
        Show Control Panel( 0 ),
        Variables( X( :age ), Group Y( :sex ) ),
        Elements( Line( X, Legend( 8 ), Summary Statistic( "N" ) ) )
    ),
    Chart(
        Grouping( :sex ),
        X( :age ),
        Y( N ),
        Y[1] << {Line Chart( 1 ), Show Points( 0 )},
        SendToReport(
            Dispatch( {}, "102", ScaleBox, {Label Row( {Show Major Labels( 0 ), Show Major Ticks( 0 ), Show Minor Ticks( 0 )} )} ),
            Dispatch( {}, "", AxisBox, {Add Axis Label( "" )} ),
            Dispatch( {}, "", AxisBox( 3 ), {Add Axis Label( "" )} )
        )
    ), 
);

Code Explanation:

1. Open data table;
2. Create new window titled "Line Chart".
3. First Graph Builder: Set size, hide control panel.
4. First Graph Builder: Assign age to X, sex to Group Y.
5. First Graph Builder: Add line element, summarize mean.
6. Second Graph Builder: Set size, hide control panel.
7. Second Graph Builder: Assign age to X, sex to Group Y.
8. Second Graph Builder: Add line element, summarize sum.
9. Third Graph Builder: Set size, hide control panel.
10. Third Graph Builder: Assign age to X, sex to Group Y, add line element, summarize count.

Example 30

Summary: Vizualizes SAT math scores by student state, utilizing Graph Builder to create interactive maps with color-coded shapes and legend.

Code:

dt = Open("data_table.jmp");
New Window( "default / off / on",
    H List Box(
        Graph Builder( Show Control Panel( 0 ), Variables( Color( :SAT Math ), Shape( :State ) ), Elements( Map Shapes( Legend( 2 ) ) ) ),
        Graph Builder(
            Show Control Panel( 0 ),
            Variables( Color( :SAT Math ), Shape( :State ) ),
            Elements( Map Shapes( Legend( 2 ) ) ),
            SendToReport(
                Dispatch( {}, "Graph Builder", FrameBox, {DispatchSeg( Shape Seg( 1 ), {Use dots for extremely small shapes( 0 )} )} )
            )
        );
        Graph Builder(
            Show Control Panel( 0 ),
            Variables( Color( :SAT Math ), Shape( :State ) ),
            Elements( Map Shapes( Legend( 2 ) ) ),
            SendToReport(
                Dispatch( {}, "Graph Builder", FrameBox, {DispatchSeg( Shape Seg( 1 ), {Use dots for extremely small shapes( 1 )} )} )
            )
        );
    )
);

Code Explanation:

1. Open data table.
2. Create new window.
3. Add horizontal list box.
4. Insert first graph builder.
5. Hide control panel.
6. Set color variable.
7. Set shape variable.
8. Add map shapes element.
9. Insert second graph builder.
10. Enable use dots for small shapes.

Example 31

Summary: Creates a parallel plot with three X variables, showcasing relationships between Smoking History, Alcohol use, Heart History, and Cholesterol Loss/Weight-3yr/% ideal weight-3yr in separate Graph Builder objects.

Code:

Open("data_table.jmp");
New Window( "Graph Builder Parallel Plot",
    Graph Builder(
        Size( 524, 354 ),
        Show Control Panel( 0 ),
        Variables( X( :Smoking History ), X( :Alcohol use, Position( 1 ) ), X( :Heart History, Position( 1 ) ), Size( :Cholesterol Loss ) ),
        Elements( Parallel( X( 1 ), X( 2 ), X( 3 ), Legend( 3 ) ) )
    ),
    Graph Builder(
        Size( 524, 354 ),
        Show Control Panel( 0 ),
        Variables(
            X( :Smoking History ),
            X( :Alcohol use, Position( 1 ) ),
            X( :Heart History, Position( 1 ) ),
            Size( :Name( "Weight-3yr" ) )
        ),
        Elements( Parallel( X( 1 ), X( 2 ), X( 3 ), Legend( 3 ) ) )
    ),
    Graph Builder(
        Size( 524, 354 ),
        Show Control Panel( 0 ),
        Variables(
            X( :Smoking History ),
            X( :Alcohol use, Position( 1 ) ),
            X( :Heart History, Position( 1 ) ),
            Size( :Name( "% ideal weight-3yr" ) )
        ),
        Elements( Parallel( X( 1 ), X( 2 ), X( 3 ), Legend( 3 ) ) )
    )
);

Code Explanation:

1. Open data table;
2. Create new window titled "Graph Builder Parallel Plot".
3. Initialize first Graph Builder object.
4. Set size to 524x354 pixels.
5. Hide control panel.
6. Define variables for Smoking History, Alcohol use, Heart History, and Cholesterol Loss.
7. Add parallel plot element with three X variables.
8. Initialize second Graph Builder object.
9. Set size to 524x354 pixels.
10. Hide control panel.
11. Define variables for Smoking History, Alcohol use, Heart History, and Weight-3yr.
12. Add parallel plot element with three X variables.
13. Initialize third Graph Builder object.
14. Set size to 524x354 pixels.
15. Hide control panel.
16. Define variables for Smoking History, Alcohol use, Heart History, and % ideal weight-3yr.
17. Add parallel plot element with three X variables.

Example 32

Summary: Creates two pie charts with different variables and groupings, utilizing Graph Builder to visualize data in a new window.

Code:

Open("data_table.jmp");
New Window( "Pies",
    Graph Builder(
        Size( 570, 516 ),
        Show Control Panel( 0 ),
        Variables( X( :age ), Y( :height ), Y( :weight, Position( 1 ) ), Group X( :sex ) ),
        Elements( Pie( X, Y( 1 ), Y( 2 ), Legend( 12 ) ) )
    ),
    Graph Builder(
        Size( 570, 516 ),
        Show Control Panel( 0 ),
        Variables( X( :age ), Y( :height ), Y( :weight, Position( 1 ) ), Group Y( :sex ) ),
        Elements( Pie( X, Y( 1 ), Y( 2 ), Legend( 12 ) ) )
    )
);

Code Explanation:

1. Open data table;
2. Create new window named "Pies".
3. Insert first Graph Builder.
4. Set window size to 570x516.
5. Hide control panel.
6. Define variables: X(age), Y(height), Y(weight), Group X(sex).
7. Add pie element with two Ys.
8. Insert second Graph Builder.
9. Set window size to 570x516.
10. Hide control panel.

Example 33

Summary: Creates a pie chart with mean sales data, utilizing Graph Builder to customize the graph size, control panel visibility, and legend position.

Code:

Open("data_table.jmp");
New Window( "Pie Chart",
    Chart( X( :Size Co ), Y( Mean( :Name( "Sales ($M)" ) ) ), Pie( 1 ), Category Axis << {Label( None )} ),
    Graph Builder(
        Size( 507, 440 ),
        Show Control Panel( 0 ),
        Legend Position( "Bottom" ),
        Variables( X( :Size Co ), Y( :Name( "Sales ($M)" ) ) ),
        Elements( Pie( X, Y, Legend( 4 ) ) ),
        SendToReport(
            Dispatch( {}, "400", ScaleBox,
                {Legend Model(
                    4,
                    Properties( 0, {Fill Color( 19 )} ),
                    Properties( 1, {Fill Color( 4 )} ),
                    Properties( 2, {Fill Color( 5 )} )
                )}
            ),
            Dispatch( {}, "graph title", TextEditBox, {Set Text( "" )} ),
            Dispatch( {}, "Y title", TextEditBox, {Set Text( "Mean(Sales ($M))" )} ),
            Dispatch( {}, "400", LegendBox, {Orientation( "Horizontal" ), Sides( "Left" )} )
        )
    )
);

Code Explanation:

1. Open data table;
2. Create new window titled "Pie Chart".
3. Insert chart with pie element.
4. Set category axis label to none.
5. Initialize Graph Builder.
6. Set graph size.
7. Hide control panel.
8. Position legend at bottom.
9. Define variables for X and Y.
10. Add pie element to graph builder.

Example 34

Summary: Vizualizes a data table using Graph Builder, creating a new window with a platform example that displays points with jittering and legend.

Code:

dt = Open("data_table.jmp");
New Window( " Example",
    ( dt, Graph Builder( show control panel( 0 ), Variables( X( :height ) ), Elements( Points( X, Legend( 1 ), Jitter( 1 ) ) ) ) )
);

Code Explanation:

1. Open data table.
2. Create new window titled " Example".
3. Use function on data table.
4. Initialize Graph Builder.
5. Hide control panel.
6. Set X variable to height.
7. Add Points element.
8. Assign legend to first item.
9. Enable jitter for points.
10. Display graph in window.

Example 35

Summary: Creates a new window with a platform example using Graph Builder, hiding the control panel and adding points with jitter.

Code:

dt = Open("data_table.jmp");
New Window( " Example",
    ( dt, Graph Builder( show control panel( 0 ), Variables( X( :height ) ), Elements( Points( X, Legend( 1 ), Jitter( 1 ) ) ) ) )
);
dt << Delete Columns( "height" );

Code Explanation:

1. Open data table;
2. Create new window.
3. Initialize platform.
4. Use Graph Builder.
5. Hide control panel.
6. Set X variable to height.
7. Add points element.
8. Enable jitter.
9. Show legend.
10. Delete height column.

Example 36

Summary: Creates a graph builder object in JMP, visualizing the relationship between 'weight' and 'height' variables.

Code:

dt = Open("data_table.jmp");
nw = New Window( "Test", vlb = V List Box() );
vb = V List Box(
    gb = dt << Graph Builder(
        Show Control Panel( 0 ),
        Variables( X( :weight ), Y( :height ) ),
        Elements( Points( X, Y, Legend( 1 ) ), Smoother( X, Y, Legend( 2 ) ) )
    )
);
vlb << Append( vb );

Code Explanation:

1. Open data table;
2. Create new window "Test".
3. Add vertical list box to window.
4. Create graph builder object.
5. Hide control panel.
6. Set X variable to "weight".
7. Set Y variable to "height".
8. Add points element.
9. Add smoother element.
10. Append graph builder to list box.

Example 37

Summary: Creates a graph with points and smoother elements to visualize the relationship between weight and height, utilizing Graph Builder within a new window.

Code:

dt = Open("data_table.jmp");
nw = New Window( "Test", vlb = V List Box() );
vb = V List Box(
    gb = dt << Graph Builder(
        Show Control Panel( 0 ),
        Variables( X( :weight ), Y( :height ) ),
        Elements( Points( X, Y, Legend( 1 ) ), Smoother( X, Y, Legend( 2 ) ) )
    )
);
vlb << Append( vb );
Report( gb )[FrameBox( 1 )] << Frame Size( 400, 300 );

Code Explanation:

1. Open data table;
2. Create new window titled "Test".
3. Add vertical list box to window.
4. Insert Graph Builder into list box.
5. Hide control panel.
6. Set X variable to weight.
7. Set Y variable to height.
8. Add points element to graph.
9. Add smoother element to graph.
10. Resize graph frame.

Example 38

Summary: Creates a Graph Builder script to visualize the relationship between height and weight, with sex as an overlay, in a new window titled 'Example'.

Code:

dt = Open("data_table.jmp");
New Window( "Example",
    V Sheet Box(
        <<Hold(
            Graph Builder(
                Show Control Panel( 0 ),
                Variables( X( :height ), Y( :weight ), Overlay( :sex ) ),
                Elements( Points( X, Y, Legend( 1 ) ), Smoother( X, Y, Legend( 2 ) ) )
            )
        ),
        Sheet Part( "weight by height", Excerpt Box( 1, {Picture Box( 1 )} ) )
    )
);

Code Explanation:

1. Open data table;
2. Create new window titled "Example".
3. Use V Sheet Box layout.
4. Hold Graph Builder script.
5. Disable control panel.
6. Set X variable to height.
7. Set Y variable to weight.
8. Overlay by sex variable.
9. Add points element with legend.
10. Add smoother element with legend.

Example 39

Summary: Creates a Graph Builder in JMP, visualizing relationships between height, weight, and sex.

Code:

Open("data_table.jmp");
New Window( "test",
    Scroll Box(
        Size( 1000, 700 ),
        Graph Builder(
            Show Control Panel( 1 ),
            Variables( X( :height ), Y( :weight ), Overlay( :sex ) ),
            Elements( Points( X, Y, Legend( 1 ) ), Smoother( X, Y, Legend( 2 ) ) )
        )
    )
);

Code Explanation:

1. Open data table.
2. Create new window titled "test".
3. Add scroll box to window.
4. Set scroll box size.
5. Insert Graph Builder into scroll box.
6. Enable control panel.
7. Define X variable: height.
8. Define Y variable: weight.
9. Add overlay variable: sex.
10. Plot points and smoother elements.

Example 40

Summary: Creates a graph with points and smoother elements, utilizing Graph Builder to visualize Sepal length vs. Sepal width from a data table.

Code:

dt = Open("data_table.jmp");
win = New Window( "empty graph",
    gb = Graph Builder(
        Size( 10, 10 ),
        Show Control Panel( 0 ),
        Show Legend( 0 ),
        Show Title( 0 ),
        Show Footer( 0 ),
        Variables( X( :Sepal length ), Y( :Sepal width ) ),
        Elements( Points( X, Y, Legend( 3 ) ), Smoother( X, Y, Legend( 4 ) ) )
    )
);

Code Explanation:

1. Open data table;
2. Create new window.
3. Initialize Graph Builder.
4. Set graph size small.
5. Hide control panel.
6. Hide legend.
7. Hide title.
8. Hide footer.
9. Set X variable.
10. Set Y variable.
11. Add points element.
12. Add smoother element.

Example 41

Summary: Creates a new window with a Data Filter Context Box, applying local filters to select specific age groups and visualizing the filtered data using Graph Builder.

Code:

dt2 = Open("data_table.jmp");
report5 = New Window( "Shared Local Filter",
    dfcb = Data Filter Context Box(
        hlb = H List Box(
            Current Data Table() << Data Filter( Local, <<Conditional( 1 ), Add Filter( Columns( :Age ), Where( :age == {15, 16, 17} ) ) )
        )
    )
);
hlb << append(
    Outline Box( "GB - was wrong with where seletions",
        Graph Builder( Show Control Panel( 0 ), Where( :Sex == "F" ), Variables( X( :weight ), Y( :height ) ) )
    )
);

Code Explanation:

1. Open data table;
2. Create new window "Shared Local Filter".
3. Initialize Data Filter Context Box.
4. Add Horizontal List Box.
5. Apply local data filter.
6. Set age filter to 15, 16, 17.
7. Append to Horizontal List Box.
8. Create Outline Box "GB - was wrong with where seletions".
9. Add Graph Builder.
10. Set sex filter to "F".
11. Set X variable to weight.
12. Set Y variable to height.

Example 42

Summary: Creates a new window with a data filter context box, filtering age 13, and appending an outline box with a graph builder to visualize weight vs. height for female subjects.

Code:

dt4 = Open("data_table.jmp");
win3 = New Window( "Shared Local Filter",
    dfcb = Data Filter Context Box(
        hlb = H List Box(
            Current Data Table() << Data Filter( Local, <<Conditional( 1 ), Add Filter( Columns( :Age ), Where( :Age == 13 ) ) )
        )
    )
);
hlb << append(
    Outline Box( "Filter test", Graph Builder( Show Control Panel( 0 ), Where( :Sex == "F" ), Variables( X( :weight ), Y( :height ) ) ) )
);
text3 = win3[Box( 1 )][Text Box( 1 )] << Get Text;

Code Explanation:

1. Open data table;
2. Create new window.
3. Define data filter context box.
4. Add horizontal list box.
5. Set local data filter.
6. Filter age 13.
7. Append outline box.
8. Add graph builder.
9. Hide control panel.
10. Filter sex female.
11. Set X variable weight.
12. Set Y variable height.
13. Get text from text box.

Example 43

Summary: Creates a validation window with a stratified data table, allocating 50% to training, 25% to validation, and 25% to test sets, while setting a random seed for reproducibility.

Code:

dt = Open("data_table.jmp");
obj = New Window( "validation",
    H List Box(
        dt << Make Validation Column(
            Stratification Columns( :Sex ),
            Training Set( 0.50 ),
            Validation Set( 0.25 ),
            Test Set( 0.25 ),
            New Column Name( "Valid1" ),
            Random Seed( 1234 ), 
        ),
        Graph Builder(
            Size( 533, 456 ),
            Show Control Panel( 0 ),
            Variables( X( :Weight ), Y( :Age ) ),
            Elements( Points( X, Y, Legend( 2 ) ), Smoother( X, Y, Legend( 3 ) ) )
        )
    )
);
n = Length( Window() );

Code Explanation:

1. Open data table.
2. Create new window titled "validation".
3. Add horizontal list box to window.
4. Create validation column in data table.
5. Stratify by "Sex" column.
6. Allocate 50% to training set.
7. Allocate 25% to validation set.
8. Allocate 25% to test set.
9. Name validation column "Valid1".
10. Set random seed to 1234.

Graph Builder using Expr

Example 1

Summary: Opens a data table, defines a graph expression with transformed X and Y variables, sets the graph size, hides control panel and legend, adds points and smoother elements, and creates a new window.

Code:

Open("data_table.jmp");
e = Expr(
    Graph Builder(
        Size( XXX, YYY ),
        Show Control Panel( 0 ),
        Show Legend( 0 ),
        Variables(
            X( Transform Column( "x", Formula( :height * :height - 3400 ) ) ),
            Y( Transform Column( "y", Formula( :weight * :weight / 8 - 2000 ) ) )
        ),
        Elements( Points( X, Y, Legend( 2 ) ), Smoother( X, Y, Legend( 3 ) ) )
    )
);
xs = 300;
ys = 175;
New Window( "test", vl = V List Box() );

Code Explanation:

1. Open data table.
2. Define graph expression.
3. Set graph size.
4. Hide control panel.
5. Hide legend.
6. Define X variable transformation.
7. Define Y variable transformation.
8. Add points element.
9. Add smoother element.
10. Create new window.

Example 2

Summary: Generates a graph expression using Graph Builder, substitutes sizes in the expression, and appends the resulting graphs to a vertical list box.

Code:

Names Default To Here( 1 );
Open("data_table.jmp");
e = Expr(
    Graph Builder(
        Size( XXX, YYY ),
        Show Control Panel( 0 ),
        Show Legend( 0 ),
        Variables(
            X( Transform Column( "x", Formula( :height * :height - 3400 ) ) ),
            Y( Transform Column( "y", Formula( :weight * :weight / 8 - 2000 ) ) )
        ),
        Elements( Points( X, Y, Legend( 2 ) ), Smoother( X, Y, Legend( 3 ) ) )
    )
);
xs = 300;
ys = 175;
New Window( "test", vl = V List Box() );
For( iw = 1, iw <= 5, iw++,
    For( i = 1 + 1, i <= 10, i++,
        e2 = Substitute( Name Expr( e ), Expr( XXX ), xs, Expr( YYY ), ys );
        vl << append( H List Box( Spacer Box( size( 1, ys + 80 ) ), e2 ) );
        xs -= Choose( iw, 2, 2, 1, 9, 7 );
        ys -= Choose( iw, 1, 1, 1, 2, 5 );
    )
);

Code Explanation:

1. Set default names.
2. Open data table;
3. Define graph expression.
4. Set initial sizes.
5. Create new window.
6. Initialize vertical list box.
7. Loop 5 times.
8. Loop 10 times.
9. Substitute sizes in expression.
10. Append graph to list box.

Example 3

Summary: Creates a graph with line and bar elements to visualize the mean values of 'height' and 'weight' variables, while hiding the control panel.

Code:

dt = Open("data_table.jmp");
var = Expr(
    Variables( X( :age, Size( 0, 20 ) ), Y( :height, Size( 0, 36 ) ), Y( :weight ) )
);
obj = Eval(
    Expr(
        Graph Builder(
            show control panel( 0 ),
            Expr( Name Expr( var ) ),
            Elements( Position( 1, 1 ), Line( X, Y, Summary Statistic( "Mean" ) ) ),
            Elements( Position( 1, 2 ), Bar( X, Y, Summary Statistic( "Mean" ) ) )
        )
    )
);

Code Explanation:

1. Open table.
2. Define variables.
3. Create Graph Builder object.
4. Hide control panel.
5. Set X and Y variables.
6. Add line element.
7. Add bar element.
8. Set summary statistic to mean.
9. Display graph.
10. End script.

Example 4

Summary: Creates a graph builder expression to visualize data from a specified file, utilizing Graph Builder's features to customize the plot.

Code:

Open("data_table.jmp");
sGBMarker1_expr = Expr(
    Graph Builder(
        Size( 366, 285 ),
        Show Control Panel( 0 ),
        Variables( X( :Operator ), X( :Part, Position( 1 ) ), Y( :Y ), Overlay( :Part ) ),
        Elements( Points( X( 1 ), X( 2 ), Y, Legend( 17 ), Summary Statistic( "Mean" ), Error Bars( "Range" ) ) )
    )
);

Code Explanation:

1. Open data file.
2. Define graph builder expression.
3. Set graph size.
4. Hide control panel.
5. Assign variables to axes.
6. Add points element.
7. Set summary statistic to mean.
8. Add error bars for range.
9. Overlay by part variable.
10. Display graph.

Example 5

Summary: Creates two Graph Builder objects, sGBMarker1_expr and sGBMarker5_expr, to visualize data from a JMP data table.

Code:

dt = Open("data_table.jmp");
sGBMarker1_expr = Expr(
    Graph Builder(
        Size( 366, 285 ),
        Show Control Panel( 0 ),
        Variables( X( :Operator ), X( :Part, Position( 1 ) ), Y( :Y ), Overlay( :Part ) ),
        Elements( Points( X( 1 ), X( 2 ), Y, Legend( 17 ), Summary Statistic( "Mean" ), Error Bars( "Range" ) ) )
    )
);
sGBMarker5_expr = Expr(
    dt1 = Open("data_table.jmp");
    dt1 << Graph Builder(
        Size( 366, 285 ),
        Show Control Panel( 0 ),
        Variables( X( :age ), Y( :height ) ),
        Elements( Bar( X, Y, Legend( 7 ), Summary Statistic( "Variance" ) ), Points( X, Y, Legend( 10 ) ) ),
        SendToReport(
            Dispatch( {}, "400", ScaleBox, {Legend Model( 10, Properties( 0, {Line Color( 38 )} ) )} ),
            Dispatch( {}, "400", LegendBox, {Set Title( "" )} )
        )
    );
);

Code Explanation:

1. Open data table;
2. Define sGBMarker1_expr variable.
3. Create Graph Builder object.
4. Set graph size.
5. Hide control panel.
6. Assign variables for X, Y, and Overlay.
7. Add Points element with Mean summary statistic.
8. Enable Range error bars.
9. Define sGBMarker5_expr variable.
10. Open data table;

Example 6

Summary: Creates a graph expression to visualize data from an open table, utilizing Graph Builder and specifying variables, elements, and local data filtering.

Code:

Open("data_table.jmp");
sGBMarker1_expr = Expr(
    Graph Builder(
        Size( 366, 285 ),
        Show Control Panel( 0 ),
        Variables( X( :Operator ), X( :Part, Position( 1 ) ), Y( :Y ), Overlay( :Part ) ),
        Elements( Points( X( 1 ), X( 2 ), Y, Legend( 17 ), Summary Statistic( "Mean" ), Error Bars( "Range" ) ) ),
        Local Data Filter( Add Filter( columns( :Operator, :Part ), Display( :Part, Size( 181, 85 ), List Display ) ) )
    )
);

Code Explanation:

1. Open table.
2. Define graph expression.
3. Set graph size.
4. Hide control panel.
5. Assign variables.
6. Add points element.
7. Set summary statistic.
8. Add error bars.
9. Create local data filter.
10. Display graph.

Example 7

Summary: Creates a graph builder object with a bar element and points element, filtered by age and sex, to visualize height data.

Code:

sGBMarker5_expr = Expr(
    dt1 = Open("data_table.jmp");
    dt1 << Graph Builder(
        Size( 366, 285 ),
        Show Control Panel( 0 ),
        Variables( X( :age ), Y( :height ) ),
        Elements( Bar( X, Y, Legend( 7 ), Summary Statistic( "Variance" ) ), Points( X, Y, Legend( 10 ) ) ),
        Local Data Filter( Add Filter( columns( :age, :sex ), Display( :age, Size( 181, 102 ), List Display ) ) ),
        SendToReport(
            Dispatch( {}, "400", ScaleBox, {Legend Model( 10, Properties( 0, {Line Color( 38 )} ) )} ),
            Dispatch( {}, "400", LegendBox, {Set Title( "" )} )
        )
    );
);

Code Explanation:

1. Open data table;
2. Create graph builder object.
3. Set graph size.
4. Hide control panel.
5. Define X and Y variables.
6. Add bar element with variance summary.
7. Add points element.
8. Add local data filter.
9. Customize legend properties.
10. Remove legend title.

Example 8

Summary: Creates two Graph Builder windows for data visualization, utilizing local data filters and customizing legend properties.

Code:

dt = Open("data_table.jmp");
sGBMarker1_expr = Expr(
    Graph Builder(
        Size( 366, 285 ),
        Show Control Panel( 0 ),
        Variables( X( :Operator ), X( :Part, Position( 1 ) ), Y( :Y ), Overlay( :Part ) ),
        Elements( Points( X( 1 ), X( 2 ), Y, Legend( 17 ), Summary Statistic( "Mean" ), Error Bars( "Range" ) ) ),
        Local Data Filter( Add Filter( columns( :Operator, :Part ), Display( :Part, Size( 181, 85 ), List Display ) ) )
    )
);
sGBMarker5_expr = Expr(
    dt1 = Open("data_table.jmp");
    dt1 << Graph Builder(
        Size( 366, 285 ),
        Show Control Panel( 0 ),
        Variables( X( :age ), Y( :height ) ),
        Elements( Bar( X, Y, Legend( 7 ), Summary Statistic( "Variance" ) ), Points( X, Y, Legend( 10 ) ) ),
        Local Data Filter( Add Filter( columns( :age, :sex ), Display( :age, Size( 181, 102 ), List Display ) ) ),
        SendToReport(
            Dispatch( {}, "400", ScaleBox, {Legend Model( 10, Properties( 0, {Line Color( 38 )} ) )} ),
            Dispatch( {}, "400", LegendBox, {Set Title( "" )} )
        )
    );
);
rpt = New Window( "Marker Testing", Outline Box( "Marker Testing", H List Box( sGBMarker1_expr ), H List Box( sGBMarker5_expr ) ) );

Code Explanation:

1. Open data table.
2. Define sGBMarker1 expression.
3. Create Graph Builder window.
4. Set window size and hide control panel.
5. Assign variables for graph.
6. Add points element with mean summary and range error bars.
7. Add local data filter for Operator and Part.
8. Define sGBMarker5 expression.
9. Open data table.
10. Create Graph Builder window for data_table data.
11. Set window size and hide control panel.
12. Assign variables for graph.
13. Add bar and points elements with variance summary.
14. Add local data filter for age and sex.
15. Customize legend and scale box properties.
16. Create new window for Marker Testing.
17. Add outline box with Marker Testing title.
18. Add horizontal list boxes for both graph builders.

Example 9

Summary: Creates two Graph Builders in JMP, one for data visualization and another for report customization.

Code:

Open("data_table.jmp");
sGBMarker1_expr = Expr(
    Graph Builder(
        Size( 366, 285 ),
        Show Control Panel( 0 ),
        Variables( X( :Operator ), X( :Part, Position( 1 ) ), Y( :Y ), Overlay( :Part ) ),
        Elements( Points( X( 1 ), X( 2 ), Y, Legend( 17 ), Summary Statistic( "Mean" ), Error Bars( "Range" ) ) ),
        Local Data Filter( Add Filter( columns( :Operator, :Part ), Display( :Part, Size( 181, 85 ), List Display ) ) )
    )
);
sGBMarker5_expr = Expr(
    dt1 = Open("data_table.jmp");
    dt1 << Graph Builder(
        Size( 366, 285 ),
        Show Control Panel( 0 ),
        Variables( X( :age ), Y( :height ) ),
        Elements( Bar( X, Y, Legend( 7 ), Summary Statistic( "Variance" ) ), Points( X, Y, Legend( 10 ) ) ),
        Local Data Filter( Add Filter( columns( :age, :sex ), Display( :age, Size( 181, 102 ), List Display ) ) ),
        SendToReport(
            Dispatch( {}, "400", ScaleBox, {Legend Model( 10, Properties( 0, {Line Color( 38 )} ) )} ),
            Dispatch( {}, "400", LegendBox, {Set Title( "" )} )
        )
    );
);

Code Explanation:

1. Open data table.
2. Define sGBMarker1 expression.
3. Create Graph Builder for data_table.
4. Set size and hide control panel.
5. Assign variables: Operator, Part, Y.
6. Add overlay for Part.
7. Add points element with mean summary.
8. Add error bars for range.
9. Add local data filter for Operator and Part.
10. Define sGBMarker5 expression.
11. Open data table.
12. Create Graph Builder for data_table.
13. Set size and hide control panel.
14. Assign variables: age, height.
15. Add bar element with variance summary.
16. Add points element.
17. Add local data filter for age and sex.
18. Customize report: set legend properties.
19. Remove legend title.

Example 10

Summary: Creates two Graph Builder objects to visualize the relationship between weight and age, with histograms as elements.

Code:

Open("data_table.jmp");
gb_grpX = Expr(
    Graph Builder(
        Size( 535, 454 ),
        Show Control Panel( 0 ),
        Fit to Window( "Off" ),
        Variables( Y( :weight ), Group X( :age ) ),
        Elements( Histogram( Y, Legend( 11 ) ) )
    )
);
gb_grpY = Expr(
    Graph Builder(
        Size( 535, 454 ),
        Show Control Panel( 0 ),
        Fit to Window( "Off" ),
        Variables( Y( :weight ), Group Y( :age ) ),
        Elements( Histogram( Y, Legend( 11 ) ) )
    )
);

Code Explanation:

1. Open data table;
2. Define gb_grpX expression.
3. Create Graph Builder object.
4. Set window size.
5. Hide control panel.
6. Disable fit to window.
7. Assign variables: weight, age.
8. Add histogram element.
9. Define gb_grpY expression.
10. Create Graph Builder object.

Example 11

Summary: Creates two Graph Builder objects with different groupings, and displays them in a new window using a vertical list box.

Code:

dt = Open("data_table.jmp");
gb_grpX = Expr(
    Graph Builder(
        Size( 535, 454 ),
        Show Control Panel( 0 ),
        Fit to Window( "Off" ),
        Variables( Y( :weight ), Group X( :age ) ),
        Elements( Histogram( Y, Legend( 11 ) ) )
    )
);
gb_grpY = Expr(
    Graph Builder(
        Size( 535, 454 ),
        Show Control Panel( 0 ),
        Fit to Window( "Off" ),
        Variables( Y( :weight ), Group Y( :age ) ),
        Elements( Histogram( Y, Legend( 11 ) ) )
    )
);
New Window( "test", V List Box( Eval( gb_grpX ), Eval( gb_grpY ) ) );

Code Explanation:

1. Open data_table data
2. Define gb_grpX expression.
3. Create Graph Builder object.
4. Set window size 535x454.
5. Hide control panel.
6. Disable fit to window.
7. Set Y variable to weight.
8. Group X by age.
9. Add histogram element.
10. Create new window "test".
11. Add vertical list box.
12. Evaluate gb_grpX expression.
13. Evaluate gb_grpY expression.

Example 12

Summary: Creates various plots from a data table, utilizing Graph Builder and a loop to substitute different plot types into an expression.

Code:

lstPlots = {Points, Line, Bar, Area, BoxPlot, Histogram, Heatmap, Mosaic};
myJSL = {};
myVList = Expr( V List Box() );
dt = Open("data_table.jmp");
testPlot = Expr(
    Graph Builder(
        Size( 535, 454 ),
        Show Control Panel( 0 ),
        Fit to Window( "Off" ),
        Variables( Y( :weight ), Group X( :age ) ),
        Elements( myPlot( Y, Legend( 11 ) ) )
    )
);
For( i = 1, i <= N Items( lstPlots ), i++,
    Substitute Into( testPlot, Expr( myPlot ), Eval Expr( Expr( lstPlots[i] ) ) );
    myJSL[i] = Eval Expr( testPlot );
    Substitute Into( testPlot, Eval Expr( Expr( lstPlots[i] ) ), Expr( myPlot ) );
);
New Window( "test", Outline Box( "test", For( i = 1, i <= N Items( lstPlots ), i++, Insert Into( myVList, Eval( myJSL[i] ) ) ) ) );

Code Explanation:

1. Define plot types.
2. Initialize JSL list.
3. Create vertical list box expression.
4. Open data table.
5. Define graph builder expression.
6. Loop through plot types.
7. Substitute plot type into expression.
8. Evaluate and store expression.
9. Reset plot type placeholder.
10. Create new window with all plots.

Example 13

Summary: Creates various plots from a data table using Graph Builder, substituting plot types and evaluating the resulting expressions.

Code:

dt = Open("data_table.jmp");
lstPlots = {Points, Line, Bar, Area, BoxPlot, Histogram, Heatmap, Mosaic};
myJSL = {};
myVList = Expr( V List Box() );
testPlot = Expr(
    Graph Builder(
        Size( 520, 450 ),
        Show Control Panel( 0 ),
        Fit to Window( "Off" ),
        Variables( X( :age ), Y( :sex ) ),
        Elements( myPlot( X, Y, Legend( 6 ) ) )
    )
);
For( i = 1, i <= N Items( lstPlots ), i++,
    Substitute Into( testPlot, Expr( myPlot ), Eval Expr( Expr( lstPlots[i] ) ) );
    myJSL[i] = Eval Expr( testPlot );
    Substitute Into( testPlot, Eval Expr( Expr( lstPlots[i] ) ), Expr( myPlot ) );
);

Code Explanation:

1. Open data table;
2. Define plot types list.
3. Initialize empty JSL list.
4. Create vertical list box expression.
5. Define test plot expression.
6. Loop through plot types.
7. Substitute plot type into test plot.
8. Evaluate test plot and store in JSL list.
9. Reset plot type placeholder in test plot.
10. End loop.

Example 14

Summary: Creates various plots from a data table, utilizing Graph Builder and substitution to generate multiple visualizations.

Code:

lstPlots = {Points, Line, Bar, Area, BoxPlot, Histogram, Heatmap, Mosaic, Treemap, Pie};
myJSL = {};
myVList = Expr( V List Box() );
dt = Open("data_table.jmp");
testPlot = Expr(
    Graph Builder(
        Size( 520, 450 ),
        Show Control Panel( 0 ),
        Fit to Window( "Off" ),
        Variables( X( :age ), Y( :sex ) ),
        Elements( myPlot( X, Y, Legend( 6 ) ) )
    )
);
For( i = 1, i <= N Items( lstPlots ), i++,
    Substitute Into( testPlot, Expr( myPlot ), Eval Expr( Expr( lstPlots[i] ) ) );
    myJSL[i] = Eval Expr( testPlot );
    Substitute Into( testPlot, Eval Expr( Expr( lstPlots[i] ) ), Expr( myPlot ) );
);
New Window( "test", Outline Box( "test", For( i = 1, i <= N Items( lstPlots ), i++, Insert Into( myVList, Eval( myJSL[i] ) ) ) ) );

Code Explanation:

1. Define plot types.
2. Initialize script list.
3. Create vertical list box expression.
4. Open data table.
5. Define graph builder expression.
6. Loop through plot types.
7. Substitute plot type into graph builder.
8. Store modified graph builder in list.
9. Reset plot type placeholder.
10. Create new window with all plots.

Example 15

Summary: Creates multiple Graph Builders with varying missing factor treatments for an ordinal date variable, utilizing a loop and the Graph Builder platform.

Code:

Open("data_table.jmp");
:date << set modeling type( "ordinal" );
lstMissingFactors = {"Treat as Zero", "Treat as Missing", "Skip"};
myjsl = {};
myHList = Expr( H List Box() );
For( i = 1, i <= N Items( lstMissingFactors ), i++,
    myjsl[i] = Expr(
        Graph Builder(
            Size( 350, 367 ),
            Show Control Panel( 0 ),
            Variables( X( :date ), Y( :Ozone Concentration ) ),
            Elements( Line( X, Y, Legend( 19 ), Missing Factors( Eval( lstMissingFactors[i] ) ) ) )
        )
    )
);

Code Explanation:

1. Open data table;
2. Set date modeling type.
3. Define missing factors list.
4. Initialize empty JSL list.
5. Create horizontal list box expression.
6. Loop through missing factors.
7. For each factor, create Graph Builder.
8. Set Graph Builder size.
9. Hide control panel.
10. Add date and ozone variables.

Example 16

Summary: Creates multiple Graph Builders with different missing factors treatments for an ordinal date column in a data table.

Code:

dt = Open("data_table.jmp");
:date << set modeling type( "ordinal" );
lstMissingFactors = {"Treat as Zero", "Treat as Missing", "Skip"};
myjsl = {};
myHList = Expr( H List Box() );
For( i = 1, i <= N Items( lstMissingFactors ), i++,
    myjsl[i] = Expr(
        Graph Builder(
            Size( 350, 367 ),
            Show Control Panel( 0 ),
            Variables( X( :date ), Y( :Ozone Concentration ) ),
            Elements( Line( X, Y, Legend( 19 ), Missing Factors( Eval( lstMissingFactors[i] ) ) ) )
        )
    )
);
New Window( "test", Outline Box( "test", For( i = 1, i <= N Items( lstMissingFactors ), i++, Insert Into( myHList, Eval( myjsl[i] ) ) ) ) );

Code Explanation:

1. Open data table.
2. Set date column to ordinal.
3. Define missing factors list.
4. Initialize empty script list.
5. Create horizontal list box expression.
6. Loop through missing factors.
7. Create Graph Builder for data_table.
8. Set size and hide control panel.
9. Add date and ozone concentration variables.
10. Add line element with missing factors treatment.

Example 17

Summary: Creates various plots from a data table using Graph Builder, substituting different plot types into an expression and evaluating the resulting script.

Code:

lstPlots = {Points, Line, Bar, Area, BoxPlot, Histogram, Heatmap, Mosaic};
myJSL = {};
myVList = Expr( V List Box() );
dt = Open("data_table.jmp");
testPlot = Expr(
    Graph Builder(
        Size( 400, 300 ),
        Show Control Panel( 0 ),
        Variables( X( :sex ), X( :age, Position( 1 ) ), Y( :height ) ),
        Elements( myPlot( X( 1 ), X( 2 ), Y, Summary Statistic( "Std Dev" ), Label( "Label by Value" ) ) )
    )
);
For( i = 1, i <= N Items( lstPlots ), i++,
    Substitute Into( testPlot, Expr( myPlot ), Eval Expr( Expr( lstPlots[i] ) ) );
    myJSL[i] = Eval Expr( testPlot );
    Substitute Into( testPlot, Eval Expr( Expr( lstPlots[i] ) ), Expr( myPlot ) );
);

Code Explanation:

1. Define plot types.
2. Initialize empty script list.
3. Create vertical list box expression.
4. Open data table.
5. Define graph builder expression.
6. Loop through plot types.
7. Substitute plot type into expression.
8. Evaluate and store graph script.
9. Reset plot type in expression.

Example 18

Summary: Creates various plots (Points, Line, Bar, Area, Treemap, Pie) from a data table using Graph Builder and stores them in a vertical list box.

Code:

lstPlots = {Points, Line, Bar, Area, Treemap, Pie};
myJSL = {};
myVList = Expr( V List Box() );
dt = Open("data_table.jmp");
testPlot = Expr(
    Graph Builder(
        Size( 400, 300 ),
        Show Control Panel( 0 ),
        Variables( X( :sex ), X( :age, Position( 1 ) ), Y( :height ) ),
        Elements( myPlot( X( 1 ), X( 2 ), Y, Summary Statistic( "Std Dev" ), Label( "Label by Value" ) ) )
    )
);
For( i = 1, i <= N Items( lstPlots ), i++,
    Substitute Into( testPlot, Expr( myPlot ), Eval Expr( Expr( lstPlots[i] ) ) );
    myJSL[i] = Eval Expr( testPlot );
    Substitute Into( testPlot, Eval Expr( Expr( lstPlots[i] ) ), Expr( myPlot ) );
);
New Window( "test", Outline Box( "test", For( i = 1, i <= N Items( lstPlots ), i++, Insert Into( myVList, Eval( myJSL[i] ) ) ) ) );

Code Explanation:

1. Define plot types.
2. Initialize JSL list.
3. Create vertical list box expression.
4. Open data table.
5. Define test plot expression.
6. Loop through plot types.
7. Substitute plot type into test plot.
8. Evaluate and store modified plot.
9. Reset plot type in test plot.
10. Create new window with all plots.

Example 19

Summary: Creates and customizes various plots in JMP, including points, lines, bars, areas, box plots, histograms, heatmaps, mosaics, treemaps, and pie charts, as well as a special parallel plot.

Code:

dt = Open("data_table.jmp");
dt << Clear Row States;
dt << select rows(
    [1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36,
    37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50]
);
mySubset = subset( linked, dt );
mySubset << clear row states;
lstPlots = {Points, Line, Bar, Area, BoxPlot, Histogram, Heatmap, Mosaic, Treemap, Pie};
specialPlots = {Parallel Plot};
myJSL = {};
myVList = Expr( V List Box() );
testPlot = Expr(
    mySubset << Graph Builder(
        Size( 439, 378 ),
        Show Control Panel( 0 ),
        Show Legend( 0 ),
        Variables( X( :Domain Abbreviation ), Y( :Sequence Number ) ),
        Elements( MyPlot( X, Y, Legend( 7 ), Summary Statistic( "Median" ) ) )
    )
);
For( i = 1, i <= N Items( lstPlots ), i++,
    Substitute Into( testPlot, Expr( myPlot ), Eval Expr( Expr( lstPlots[i] ) ) );
    myJSL[i] = Eval Expr( testPlot );
    Substitute Into( testPlot, Eval Expr( Expr( lstPlots[i] ) ), Expr( myPlot ) );
);
mySpecialPlot = Expr(
    mySubset << Graph Builder(
        Size( 439, 378 ),
        Show Control Panel( 0 ),
        Variables( X( :Domain Abbreviation ), X( :Sequence Number, Position( 1 ) ) ),
        Elements( Parallel( X( 1 ), X( 2 ), X( 3 ), Legend( 3 ) ) )
    )
);
New Window( "test",
    obj = Outline Box( "All Segments Under Test",
        H List Box(
            ob2 = Outline Box( "test", For( i = 1, i <= N Items( lstPlots ), i++, Insert Into( myVList, Eval( myJSL[i] ) ) ) ),
            ob3 = Outline Box( "Special Plot", Eval( mySpecialPlot ) )
        )
    )
);

Code Explanation:

1. Open data table;
2. Clear row states.
3. Select specific rows.
4. Create subset of data.
5. Clear row states of subset.
6. Define plot types.
7. Define special plot type.
8. Initialize JSL list.
9. Initialize vertical list box.
10. Create and store graph builder scripts.
11. Create special plot script.
12. Open new window.
13. Add outline box for segments.
14. Add horizontal list box.
15. Add outline box for regular plots.
16. Insert regular plots into vertical list.
17. Add outline box for special plot.
18. Insert special plot into outline box.

Example 20

Summary: Creates various plots from a data table, including points, lines, bars, areas, box plots, histograms, and heatmaps.

Code:

lstPlots = {Points, Line, Bar, Area, BoxPlot, Histogram, Heatmap, Mosaic};
myJSL = {};
myVList = Expr( V List Box() );
dt = Open("data_table.jmp");
testPlot = Expr(
    Graph Builder(
        Size( 400, 300 ),
        Show Control Panel( 0 ),
        Variables( X( :age ), Y( :weight, Summary Statistic( "Mean" ) ) ),
        Elements( myPlot( X, Y, Summary Statistic( "Sum" ), Legend( 6 ), Label( "Label by Value" ) ) )
    )
);
For( i = 1, i <= N Items( lstPlots ), i++,
    Substitute Into( testPlot, Expr( myPlot ), Eval Expr( Expr( lstPlots[i] ) ) );
    myJSL[i] = Eval Expr( testPlot );
    Substitute Into( testPlot, Eval Expr( Expr( lstPlots[i] ) ), Expr( myPlot ) );
);

Code Explanation:

1. Define plot types.
2. Initialize empty JSL list.
3. Create vertical list box expression.
4. Open data table.
5. Define test plot expression.
6. Loop through plot types.
7. Substitute plot type into test plot.
8. Evaluate and store modified plot.
9. Reset plot type in test plot.
10. End loop.

Example 21

Summary: Creates various plots from a data table, including points, lines, bars, areas, box plots, histograms, heatmaps, mosaics, treemaps, and pies.

Code:

lstPlots = {Points, Line, Bar, Area, BoxPlot, Histogram, Heatmap, Mosaic, Treemap, Pie};
myJSL = {};
myVList = Expr( V List Box() );
dt = Open("data_table.jmp");
testPlot = Expr(
    Graph Builder(
        Size( 400, 300 ),
        Show Control Panel( 0 ),
        Variables( X( :age ), Y( :weight, Summary Statistic( "Mean" ) ) ),
        Elements( myPlot( X, Y, Summary Statistic( "Sum" ), Legend( 6 ), Label( "Label by Value" ) ) )
    )
);
For( i = 1, i <= N Items( lstPlots ), i++,
    Substitute Into( testPlot, Expr( myPlot ), Eval Expr( Expr( lstPlots[i] ) ) );
    myJSL[i] = Eval Expr( testPlot );
    Substitute Into( testPlot, Eval Expr( Expr( lstPlots[i] ) ), Expr( myPlot ) );
);
New Window( "test", Outline Box( "test", For( i = 1, i <= N Items( lstPlots ), i++, Insert Into( myVList, Eval( myJSL[i] ) ) ) ) );

Code Explanation:

1. Define plot types.
2. Initialize empty list.
3. Create vertical list box.
4. Open data table.
5. Define graph builder expression.
6. Loop through plot types.
7. Substitute plot type into expression.
8. Store modified expression.
9. Reset original plot type.
10. Display all plots in new window.

Example 22

Summary: Creates a Treemap visualization in JMP, using Graph Builder to display data by Brand and configure layout options.

Code:

Open("data_table.jmp");
myTreeGB_expr = Expr(
    dt << Graph Builder(
        Size( 416, 360 ),
        Show Control Panel( 0 ),
        Variables( X( :Brand ) ),
        Elements( Treemap( X, Legend( 3 ), Layout( "Squarify" ) ) )
    )
);
myStandAlongTree_expr = Expr(
    dt << Treemap(
        Categories( :Brand ),
        Color Theme( "JMP Default" ),
        Layout( "Squarify" ),
        SendToReport( Dispatch( {}, "", TreeMapBox, {Frame Size( 416, 360 )} ) )
    )
);

Code Explanation:

1. Open data table.
2. Define myTreeGB expression.
3. Create Graph Builder window.
4. Set window size.
5. Hide control panel.
6. Assign X variable.
7. Add Treemap element.
8. Define myStandAlongTree expression.
9. Create standalone Treemap.
10. Set categories and color theme.

Example 23

Summary: Creates a treemap visualization in JMP, utilizing Graph Builder and Standalone Treemap expressions to display data by brand.

Code:

dt = Open("data_table.jmp");
myTreeGB_expr = Expr(
    dt << Graph Builder(
        Size( 416, 360 ),
        Show Control Panel( 0 ),
        Variables( X( :Brand ) ),
        Elements( Treemap( X, Legend( 3 ), Layout( "Squarify" ) ) )
    )
);
myStandAlongTree_expr = Expr(
    dt << Treemap(
        Categories( :Brand ),
        Color Theme( "JMP Default" ),
        Layout( "Squarify" ),
        SendToReport( Dispatch( {}, "", TreeMapBox, {Frame Size( 416, 360 )} ) )
    )
);
New Window( "Treemap in two platforms", Outline Box( "test", V List Box( myTreeGB_expr, myStandAlongTree_expr ) ) );

Code Explanation:

1. Open table.
2. Define treemap expression.
3. Define standalone treemap expression.
4. Create new window.
5. Add outline box.
6. Add vertical list box.
7. Insert treemap expression.
8. Insert standalone treemap expression.

Example 24

Summary: Generates treemap plots with custom fill patterns using Graph Builder and the Extract Expr function.

Code:

lstPattern = {"hollow circle", "diamond", "h wave medium", "weave heavy"};
myJSL = {};
myVList = Expr( V List Box() );
dt = Open("data_table.jmp");
testPlot = Expr(
    gb = Graph Builder( Size( 319, 278 ), Show Control Panel( 0 ), Variables( X( :Species ) ), Elements( Treemap( X, Legend( 4 ) ) ) );
    rpt = gb << Report();
    mySeg = rpt[Framebox( 1 )] << find seg( "TreeMapSeg" );
    mySeg << Fill Pattern( myOption );
);
For( i = 1, i <= N Items( lstPattern ), i++,
    Substitute Into( testPlot, Expr( myOption ), Eval Expr( Expr( lstPattern[i] ) ) );
    myJSL[i] = Eval Expr( testPlot );
    Substitute Into( testPlot, Eval Expr( Expr( lstPattern[i] ) ), Expr( myOption ) );
);

Code Explanation:

1. Define fill patterns.
2. Initialize empty list.
3. Create vertical list box expression.
4. Open data table;
5. Define treemap plotting expression.
6. Generate treemap report.
7. Find treemap segment.
8. Set fill pattern.
9. Loop through patterns.
10. Substitute pattern into plot.

Example 25

Summary: Creates and customizes treemap plots using a list of predefined fill patterns, generating multiple visualizations in a single window.

Code:

myJSL = {};
myVList = Expr( V List Box() );
lstPattern = {"hollow circle", "diamond", "h wave medium", "weave heavy"};
dt = Open("data_table.jmp");
testPlot = Expr(
    gb = Graph Builder( Size( 319, 278 ), Show Control Panel( 0 ), Variables( X( :Species ) ), Elements( Treemap( X, Legend( 4 ) ) ) );
    rpt = gb << Report();
    mySeg = rpt[Framebox( 1 )] << find seg( "TreeMapSeg" );
    mySeg << Fill Pattern( myOption );
);
For( i = 1, i <= N Items( lstPattern ), i++,
    Substitute Into( testPlot, Expr( myOption ), Eval Expr( Expr( lstPattern[i] ) ) );
    myJSL[i] = Eval Expr( testPlot );
    Substitute Into( testPlot, Eval Expr( Expr( lstPattern[i] ) ), Expr( myOption ) );
);
New Window( "test", Outline Box( "test", For( i = 1, i <= N Items( lstPattern ), i++, Insert Into( myVList, Eval( myJSL[i] ) ) ) ) );

Code Explanation:

1. Initialize myJSL object.
2. Create myVList expression.
3. Define lstPattern list.
4. Open data table;
5. Define testPlot expression.
6. Create gb Graph Builder object.
7. Retrieve report from gb.
8. Find segment "TreeMapSeg".
9. Set fill pattern to myOption.
10. Loop through lstPattern.
11. Substitute pattern into testPlot.
12. Evaluate testPlot and store in myJSL.
13. Reset myOption in testPlot.
14. Create new window "test".
15. Insert treemap plots into myVList.

Example 26

Summary: Creates and customizes treemap plots with varying transparency levels using Graph Builder in JMP.

Code:

dt = Open("data_table.jmp");
valueTransparency = [0.1, 0.2, 0.3, 0.4, 0.5, 0.6, 0.7, 0.8, 0.9, 1.0];
myJSL = {};
testPlot = Expr(
    gb = Graph Builder( Size( 319, 306 ), Show Control Panel( 0 ), Variables( X( :Species ) ), Elements( Treemap( X, Legend( 4 ) ) ) );
    rpt = gb << Report();
    mySeg = rpt[Framebox( 1 )] << find seg( "TreeMapSeg" );
    mySeg << Transparency( myOption );
);
For( i = 1, i <= N Items( valueTransparency ), i++,
    Substitute Into( testPlot, Expr( myOption ), Eval Expr( Expr( valueTransparency[i] ) ) );
    myJSL[i] = Eval Expr( testPlot );
    Substitute Into( testPlot, Eval Expr( Expr( valueTransparency[i] ) ), Expr( myOption ) );
);

Code Explanation:

1. Open data table;
2. Define transparency values.
3. Initialize empty list.
4. Create treemap plot expression.
5. Assign graph builder report.
6. Find treemap segment.
7. Set segment transparency.
8. Loop through transparency values.
9. Substitute current transparency.
10. Evaluate and store plot.

Example 27

Summary: Generates treemap plots with varying transparency levels from a data table, utilizing Graph Builder and report functionality.

Code:

myJSL = {};
myVList = Expr( V List Box() );
valueTransparency = [-1, 0.1, 0.5, 1];
dt = Open("data_table.jmp");
testPlot = Expr(
    gb = Graph Builder( Size( 319, 306 ), Show Control Panel( 0 ), Variables( X( :Species ) ), Elements( Treemap( X, Legend( 4 ) ) ) );
    rpt = gb << Report();
    mySeg = rpt[Framebox( 1 )] << find seg( "TreeMapSeg" );
    mySeg << Transparency( myOption );
);
For( i = 1, i <= N Items( valueTransparency ), i++,
    Substitute Into( testPlot, Expr( myOption ), Eval Expr( Expr( valueTransparency[i] ) ) );
    myJSL[i] = Eval Expr( testPlot );
    Substitute Into( testPlot, Eval Expr( Expr( valueTransparency[i] ) ), Expr( myOption ) );
);
New Window( "test", Outline Box( "test", For( i = 1, i <= N Items( valueTransparency ), i++, Insert Into( myVList, Eval( myJSL[i] ) ) ) ) );

Code Explanation:

1. Initialize empty object.
2. Create vertical list box expression.
3. Define transparency values.
4. Open data table;
5. Define treemap plot expression.
6. Generate report from treemap.
7. Find treemap segment.
8. Set segment transparency.
9. Loop through transparency values.
10. Substitute transparency into plot expression.
11. Evaluate and store plot expression.
12. Reset substituted transparency.
13. Create new window.
14. Insert treemap plots into window.

Example 28

Summary: Creates multiple Graph Builder expressions for data visualization, with customization options for error bars and legend settings.

Code:

dt = Open("data_table.jmp");
sGBMarker1_expr = Expr(
    Graph Builder(
        Show Control Panel( 0 ),
        Variables( X( :Operator ), X( :Part, Position( 1 ) ), Y( :Y ), Overlay( :Part ) ),
        Elements( Points( X( 1 ), X( 2 ), Y, Legend( 17 ), Summary Statistic( "Mean" ), Error Bars( "Range" ) ) ),
        SendToReport(
            Dispatch( {}, "Graph Builder", FrameBox,
                Add Pin Annotation(
                    Seg( Marker Seg( 1 ) ),
                    Index( 0 ),
                    Index Row( 0 ),
                    UniqueID( 552452960 ),
                    FoundPt( {323, 394} ),
                    Origin( {-0.158385093167702, 164.162436548223} )
                )
            )
        )
    )
);
sGBMarker2_expr = Expr(
    Graph Builder(
        Show Control Panel( 0 ),
        Variables( X( :Part ), Y( :Y ), Overlay( :Part ) ),
        Elements( Points( X, Y, Legend( 17 ), Summary Statistic( "Mean" ) ) ),
        SendToReport(
            Dispatch( {}, "400", ScaleBox, {Legend Model( 17, Properties( 1, {Marker( "Star" )} ) )} ),
            Dispatch( {}, "Graph Builder", FrameBox, {Marker Size( 6 )} )
        )
    )
);
sGBMarker3_expr = Expr(
    Graph Builder(
        Show Control Panel( 0 ),
        Variables( X( :Operator ), X( :Part, Position( 1 ) ), Y( :Y ), Overlay( :Operator ) ),
        Elements( Points( X( 1 ), X( 2 ), Y, Legend( 13 ), Summary Statistic( "Mean" ), Error Bars( "Confidence Interval" ) ) )
    )
);
sGBMarker4_expr = Expr(
    Graph Builder( Show Control Panel( 0 ), Variables( X( :Part ), Y( :Y ) ), By( :Operator ), Elements( Points( X, Y, Legend( 3 ) ) ) )
);

Code Explanation:

1. Open data table.
2. Define sGBMarker1_expr for Graph Builder.
3. Set X, Y, and Overlay variables.
4. Add points element with mean summary statistic and error bars.
5. Add pin annotation to report.
6. Define sGBMarker2_expr for Graph Builder.
7. Set X, Y, and Overlay variables.
8. Add points element with mean summary statistic.
9. Customize legend and marker size in report.
10. Define sGBMarker3_expr for Graph Builder.
11. Set X, Y, and Overlay variables.
12. Add points element with mean summary statistic and confidence interval error bars.

Example 29

Summary: Creates a graph builder object with specified variables and elements, using Graph Builder to visualize data from 'data_table.jmp'.

Code:

trigger alert = Expr(
    Try(
        dt = Open("data_table.jmp");
        gb = Graph Builder(
            Variables( X( :height ), Y( :weight ), Overlay( :sex ), Color( :age ) ),
            Elements( Points( X, Y, Legend( 1 ) ), Smoother( X, Y, Legend( 2 ) ) )
        );
        lgnd = gb << Get Legend Display;
        item = lgnd << Get Item();
    )
);

Code Explanation:

1. Define trigger alert expression.
2. Attempt to open dataset.
3. Load "data_table.jmp" sample data.
4. Create graph builder object.
5. Set X variable to height.
6. Set Y variable to weight.
7. Use sex for overlay.
8. Color by age.
9. Add points element.
10. Add smoother element.

Example 30

Summary: Creates a graph builder object with customized variables and elements, allowing for interactive exploration of data.

Code:

dt = Open("data_table.jmp");
trigger alert = Expr(
    Try(
        dt = Open("data_table.jmp");
        gb = Graph Builder(
            Variables( X( :height ), Y( :weight ), Overlay( :sex ), Color( :age ) ),
            Elements( Points( X, Y, Legend( 1 ) ), Smoother( X, Y, Legend( 2 ) ) )
        );
        lgnd = gb << Get Legend Display;
        item = lgnd << Get Item();
    )
);

Code Explanation:

1. Open data table;
2. Define trigger alert expression.
3. Try opening "data_table.jmp" again.
4. Create Graph Builder object.
5. Set X to :height.
6. Set Y to :weight.
7. Overlay by :sex.
8. Color by :age.
9. Add Points element.
10. Add Smoother element.

Example 31

Summary: Creates a graph builder object with specific variables and elements, triggering an alert expression upon successful data table opening.

Code:

Open("data_table.jmp");
trigger alert = Expr(
    Try(
        dt = Open("data_table.jmp");
        gb = Graph Builder(
            Variables( X( :height ), Y( :weight ), Overlay( :sex ), Color( :age ) ),
            Elements( Points( X, Y, Legend( 1 ) ), Smoother( X, Y, Legend( 2 ) ) )
        );
        lgnd = gb << Get Legend Display;
        item = lgnd << Get Item();
    )
);

Code Explanation:

1. Open data table;
2. Define trigger alert expression.
3. Attempt to open data_table dataset.
4. Create Graph Builder object.
5. Set X, Y, Overlay, and Color variables.
6. Add Points and Smoother elements.
7. Retrieve legend display.
8. Get legend items.

Graph Builder using If

Example 1

Summary: Visualizes the DJI High, Close, and Low values over time using Graph Builder, with customized legend properties and orientation.

Code:

If( Host is( "Windows" ),
    Open("data_table.jmp");
    Graph Builder(
        Show Control Panel( 0 ),
        Legend Position( "Bottom" ),
        Variables( X( :Date ), Y( :DJI High ), Y( :DJI Close, Position( 1 ) ), Y( :DJI Low, Position( 1 ) ) ),
        Elements( Bar( X, Y( 1 ), Y( 2 ), Y( 3 ), Legend( 2 ), Bar Style( "Interval" ) ) ),
        SendToReport(
            Dispatch( {}, "400", ScaleBox,
                {Legend Model(
                    2,
                    Properties( 1, {Marker( "Diamond" )}, Item ID( "DJI Low", 1 ) ),
                    "Properties"(-1, {"", "Marker"(8)}, "Item ID"("DJI High", 1)),
                    "Properties"(-1, {"", "Marker"(1)}, "Item ID"("DJI Close", 1))
                )}
            ),
            Dispatch( {}, "400", LegendBox, {Orientation( "Horizontal" ), Sides( "Left" )} )
        )
    );
);

Code Explanation:

1. Check if host is Windows.
2. Open data table;
3. Create Graph Builder.
4. Hide control panel.
5. Set legend position bottom.
6. Define variables: Date, DJI High, DJI Close, DJI Low.
7. Add bar element with interval style.
8. Customize legend model properties.
9. Set legend orientation horizontal.
10. Align legend on left side.

Example 2

Summary: Creates a Graph Builder report with customized settings, including box plot element and pin annotation, for data visualization in JMP.

Code:

If( JMP Version() >= "16",
    Open("data_table.jmp");
    Graph Builder(
        Size( 350, 300 ),
        Show Control Panel( 0 ),
        Show Legend( 0 ),
        Show Footer( 0 ),
        Variables( X( :sex ), Y( :height ), Color( :age, Summary Statistic( "Sum" ) ), ),
        Elements( Box Plot( X, Y, Legend( 8 ) ) ),
        SendToReport(
            Dispatch( {}, "Graph Builder", FrameBox,
                Add Pin Annotation(
                    Seg( Marker Seg( 1 ) ),
                    Index( 1 ),
                    Index Row( 4 ),
                    UniqueID( 870940257 ),
                    FoundPt( {133, 329} ),
                    Origin( {0.0078125, 52.0301535585012} ),
                    Tag Line( 1 )
                )
            )
        )
    );
);

Code Explanation:

1. Check JMP version.
2. Open data table.
3. Create Graph Builder.
4. Set graph size.
5. Hide control panel.
6. Hide legend.
7. Hide footer.
8. Define variables for X, Y, and color.
9. Add box plot element.
10. Add pin annotation to graph.

Example 3

Summary: Creates a Graph Builder window with a bar element and pin annotations, utilizing JMP's Graph Builder platform.

Code:

If( JMP Version() >= "17.0",
    Open("data_table.jmp");
    Graph Builder(
        Size( 528, 450 ),
        Show Control Panel( 0 ),
        Variables( X( :Cut ), Y( :Depth ), Y( :Table, Position( 1 ) ) ),
        Elements( Bar( X, Y( 1 ), Y( 2 ), Legend( 11 ), Summary Statistic( "Mode" ) ) ),
        SendToReport(
            Dispatch( {}, "Graph Builder", FrameBox,
                {Add Pin Annotation(
                    Seg( BarSeg( 1 ) ),
                    Index( {0, 1} ),
                    Index Row( {593, 1057} ),
                    UniqueID( -269494896 ),
                    FoundPt( {129, 230} ),
                    Origin( {0.103305785123967, 37.48525} ),
                    RightOfCenter( 0 ),
                    Tag Line( 1 )
                ), Add Pin Annotation(
                    Seg( BarSeg( 1 ) ),
                    Index( {3, 6} ),
                    Index Row( {927, 6} ),
                    UniqueID( -269494893 ),
                    FoundPt( {457, 305} ),
                    Origin( {2.81404958677686, 24.409} ),
                    RightOfCenter( 1 ),
                    Tag Line( 1 )
                )}
            )
        )
    );
    Graph Builder(
        Size( 534, 450 ),
        Show Control Panel( 0 ),
        Variables( X( :Cut ), Y( :Price ), Color( :Clarity, Summary Statistic( "Mode" ) ) ),
        Elements( Bar( X, Y, Legend( 9 ), Summary Statistic( "Mode" ) ) ),
        SendToReport(
            Dispatch( {}, "Graph Builder", FrameBox,
                {Add Pin Annotation(
                    Seg( BarSeg( 1 ) ),
                    Index( {0, 0} ),
                    Index Row( {593, 593} ),
                    UniqueID( -346605056 ),
                    FoundPt( {398, 233} ),
                    Origin( {-0.0213675213675213, 2456.784} ),
                    RightOfCenter( 0 ),
                    Tag Line( 1 )
                ), Add Pin Annotation(
                    Seg( BarSeg( 1 ) ),
                    Index( {3, 3} ),
                    Index Row( {927, 927} ),
                    UniqueID( -346605053 ),
                    FoundPt( {749, 439} ),
                    Origin( {2.97863247863248, 662.112} ),
                    RightOfCenter( 1 ),
                    Tag Line( 1 )
                )}
            )
        )
    );
);

Code Explanation:

1. Check JMP version.
2. Open data table;
3. Create first Graph Builder window.
4. Set size and hide control panel.
5. Define X and Y variables.
6. Add bar element with mode summary statistic.
7. Add pin annotations to graph.
8. Create second Graph Builder window.
9. Set size and hide control panel.
10. Define X, Y, and Color variables.
11. Add bar element with mode summary statistic.
12. Add pin annotations to graph.

Example 4

Summary: Creates a Graph Builder window with customized settings, including variable definitions and interactive elements.

Code:

If( Host is( "Windows" ),
    Open("data_table.jmp");
    Graph Builder(
        Size( 484, 460 ),
        Show Control Panel( 0 ),
        Variables( Y( :Speed ), Y( :Speed2, Position( 1 ) ), Overlay( :Position2 ) ),
        Elements( Bar( Y( 1 ), Y( 2 ), Legend( 5 ), Bar Style( "Range" ), Summary Statistic( "Sum" ), Label( "Label by Value" ) ) ),
        SendToReport(
            Dispatch( {}, "Graph Builder", FrameBox,
                Add Pin Annotation(
                    Seg( BarSeg( 1 ) ),
                    Index( {2, 4} ),
                    Index Row( {49, 0} ),
                    UniqueID( 626323778 ),
                    FoundPt( {227, 132} ),
                    Origin( {-0.129976580796253, 1794.93087557604} )
                )
            )
        )
    );
);

Code Explanation:

1. Check if host is Windows.
2. Open data_table data
3. Create Graph Builder window.
4. Set window size to 484x460.
5. Hide control panel.
6. Define Y variables: Speed, Speed2.
7. Overlay by Position2.
8. Add bar element with range style.
9. Summarize statistic as Sum.
10. Label bars by value.

Example 5

Summary: Creates a Graph Builder visualization to display Speed and Speed2 data, with Position as an overlay, on Windows platforms.

Code:

If( Host is( "Windows" ),
    Open("data_table.jmp");
    Graph Builder(
        Size( 422, 368 ),
        Show Control Panel( 0 ),
        Variables( Y( :Speed ), Y( :Speed2, Position( 1 ) ), Overlay( :Position ) ),
        Elements( Bar( Y( 1 ), Y( 2 ), Legend( 5 ), Bar Style( "Side by Side" ), Summary Statistic( "Sum" ) ) )
    );
);

Code Explanation:

1. Check if host is Windows.
2. Open data_table data
3. Create Graph Builder.
4. Set window size.
5. Hide control panel.
6. Define Y variables: Speed, Speed2.
7. Set Position for Speed2.
8. Add Overlay for Position.
9. Add Bar element.
10. Configure bar style and summary statistic.

Example 6

Summary: Vizualizes data by creating a Graph Builder object with customized settings, including window size, control panel visibility, and element configuration.

Code:

If( Host is( "Windows" ),
    Open("data_table.jmp");
    Graph Builder(
        Size( 451, 368 ),
        Show Control Panel( 0 ),
        Variables( Y( :Speed ), Y( :Speed2, Position( 1 ) ), Overlay( :Position2 ), Color( :Position ) ),
        Elements( Bar( Y( 1 ), Y( 2 ), Legend( 5 ), Bar Style( "Range" ), Summary Statistic( "Sum" ), Label( "Label by Value" ) ) )
    );
);

Code Explanation:

1. Check if host is Windows.
2. Open data table;
3. Create Graph Builder object.
4. Set window size to 451x368.
5. Hide control panel.
6. Define Y variables: Speed, Speed2.
7. Position Speed2 on axis 1.
8. Overlay by Position2.
9. Color by Position.
10. Add Bar element with range style, sum statistic, and label by value.

Example 7

Summary: Creates a graph in Graph Builder to visualize data relationships, utilizing variables such as Weight, Turning Circle, Country, and Gas Tank Size.

Code:

If( Host is( "Windows" ),
    Open("data_table.jmp");
    Graph Builder(
        Size( 560, 500 ),
        Show Control Panel( 0 ),
        Variables( X( :Weight ), Group X( :Weight ), Group Y( :Turning Circle ), Overlay( :Country ), Frequency( :Gas Tank Size ) ),
        Elements( Bar( X, Legend( 7 ), Bar Style( "Interval" ) ) )
    );
);

Code Explanation:

1. Check if host is Windows.
2. Open data table;
3. Launch Graph Builder.
4. Set window size.
5. Hide control panel.
6. Define variables: X, Group X, Group Y, Overlay, Frequency.
7. Add bar element.
8. Set legend position.
9. Set bar style to interval.
10. Display graph.

Example 8

Summary: Creates a Graph Builder window with a bar chart to visualize data from 'data_table.jmp' on Windows platforms.

Code:

If( Host is( "Windows" ),
    Open("data_table.jmp");
    Graph Builder(
        Size( 528, 454 ),
        Show Control Panel( 0 ),
        Variables( X( :weight ), Y( :height ) ),
        Elements( Bar( Legend( 3 ), Label( "Label by Row" ) ) )
    );
);

Code Explanation:

1. Check if host is Windows.
2. Open data_table data
3. Create Graph Builder window.
4. Set size to 528x454.
5. Hide control panel.
6. Set X variable to weight.
7. Set Y variable to height.
8. Add bar element.
9. Enable legend for bar.
10. Label bars by row.

Example 9

Summary: Creates a graph builder object to visualize data from a data table, with specific settings for X and Y variables, graph size, and scale configuration.

Code:

If( Host is( "Windows" ),
    dt under test = Open("data_table.jmp");
    obj = Graph Builder(
        Size( 1450, 1082 ),
        Show Control Panel( 0 ),
        Variables( X( :State ), Y( :Name( "% Taking (2004)" ) ) ),
        Elements( Bar( X, Y, Legend( 8 ) ) ),
        SendToReport( Dispatch( {}, "State", ScaleBox, {Min( -0.33863086560182 ), Max( 50.6613691343982 ), Inc( 1 ), Minor Ticks( 0 )} ) )
    );
);

Code Explanation:

1. Check if host is Windows.
2. Open data table.
3. Create Graph Builder object.
4. Set graph size to 1450x1082.
5. Hide control panel.
6. Set X variable to State.
7. Set Y variable to % Taking (2004).
8. Add bar element to graph.
9. Configure X scale settings.
10. Display the graph.

Example 10

Summary: Creates a box plot in Graph Builder to visualize data relationships, utilizing variables and color-coding for enhanced analysis.

Code:

If( JMP Version() >= "16",
    Open("data_table.jmp");
    Graph Builder(
        Size( 531, 450 ),
        Show Control Panel( 0 ),
        Variables( X( :Cut, Size By( "Count" ) ), Y( :Carat Weight ), Color( :Cut ) ),
        Elements( Box Plot( X, Y, Legend( 4 ) ) )
    );
);

Code Explanation:

1. Check JMP version.
2. Open data table;
3. Create Graph Builder window.
4. Set window size.
5. Hide control panel.
6. Assign variables.
7. Add box plot element.
8. Customize legend.

Example 11

Summary: Creates a graph builder with points and smoother elements, displaying random text labels on top.

Code:

If( Host is( "Windows" ),
    dt = Open("data_table.jmp");
    ::ndrawgb = 0;
    dt << Graph Builder(
        Size( 685, 500 ),
        show control panel( 0 ),
        Variables( X( :height ), Y( :weight ) ),
        Elements( Points( X, Y, Legend( 2 ) ), Smoother( X, Y, Legend( 3 ) ) ),
        SendToReport(
            Dispatch( {}, "Graph Builder", FrameBox,
                {Add Graphics Script(
                    2,
                    Description( "" ),
                    ::ndrawgb++;
                    Show( ::ndrawgb );
                    Text Size( 13 );
                    Transparency( 0.2 );
                    Local( {i, xy},
                        For( i = 1, i < 50, i++,
                            xy = Eval List( {Random Uniform( 50, 72 ), Random Uniform( 100, 170 )} );
                            Text( xy, Char( ::ndrawgb ) );
                        )
                    );
                    Transparency( 0.7 );
                    Text Size( 50 );
                    Text( {60, 60}, Char( ::ndrawgb ) );
                )}
            )
        )
    );
);

Code Explanation:

1. Check if host is Windows.
2. Open data table;
3. Initialize ndrawgb counter to 0.
4. Create Graph Builder object.
5. Set size to 685x500 pixels.
6. Hide control panel.
7. Set X variable to :height.
8. Set Y variable to :weight.
9. Add points and smoother elements.
10. Execute custom graphics script.

Example 12

Summary: Creates a heatmap visualization using Graph Builder, with X and Y variables set by count and color, respectively, for JMP versions 16 and above.

Code:

If( JMP Version() >= "16",
    Open("data_table.jmp");
    Graph Builder(
        Show Control Panel( 0 ),
        Variables( X( :Cut, Size By( "Count" ) ), Y( :Color, Size By( "Count" ) ), Color( :Carat Weight ) ),
        Elements( Heatmap( X, Y, Legend( 6 ) ) )
    );
);

Code Explanation:

1. Check JMP version.
2. If version is 16+, open file.
3. Use Graph Builder.
4. Hide control panel.
5. Set X variable.
6. Set Y variable.
7. Set color variable.
8. Add heatmap element.
9. Configure legend position.
10. Display graph.

Example 13

Summary: Creates a Graph Builder visualization with customized settings, including hiding the control panel and specifying X and Y variables.

Code:

If( JMP Version() >= "16",
    Open("data_table.jmp");
    Graph Builder(
        Show Control Panel( 0 ),
        Variables( X( :Cut, Size By( "Count" ) ), Y( :Carat Weight ) ),
        Elements( Points( X, Y, Legend( 3 ), Summary Statistic( "Mean" ), Error Interval( "Range" ), Interval Style( "Band" ) ) )
    );
);

Code Explanation:

1. Check JMP version.
2. Open data table;
3. Launch Graph Builder.
4. Hide control panel.
5. Set X variable: Cut, size by Count.
6. Set Y variable: Carat Weight.
7. Add Points element.
8. Set legend index to 3.
9. Use Mean summary statistic.
10. Display Range error interval as band.

Example 14

Summary: Creates multiple graph builders in JMP, configuring variables, scales, and elements for data visualization.

Code:

If( JMP Version() >= "17.0",
    dt = Open("data_table.jmp");
    gb = dt << Graph Builder(
        Size( 528, 453 ),
        Show Control Panel( 0 ),
        Variables( X( :Longitude ), Y( :Latitude ), Color( :Total Serious Injuries ), Size( :Total Serious Injuries ) ),
        Elements( Points( X, Y, Legend( 8 ) ) ),
        SendToReport(
            Dispatch( {}, "Longitude", ScaleBox,
                {Scale( "Geodesic", {Compact Map( {Region( "United States" ), Alaska( 1 ), Hawaii( 1 )} )} ), Format( "Best", 10 ),
                Min( -130.716492450652 ), Max( -65.0280733476802 ), Inc( 5 ), Minor Ticks( 1 )}
            ),
            Dispatch( {}, "Latitude", ScaleBox,
                {Scale( "Geodesic", {Compact Map( {Region( "United States" ), Alaska( 1 ), Hawaii( 1 )} )} ), Format( "Best", 10 ),
                Min( 15.9446169772257 ), Max( 68.7396480331263 ), Inc( 5 ), Minor Ticks( 1 )}
            ),
            Dispatch( {}, "Graph Builder", FrameBox,
                {Background Map( Images( "Simple Earth" ) ), DispatchSeg(
                    Marker Seg( 1 ),
                    {Set Hide Missing Size( 1 ), Set Hide Missing Color( 1 )}
                )}
            )
        )
    );
    dt2 = Open("data_table.jmp");
    gb2 = dt2 << Graph Builder(
        Size( 495, 461 ),
        Show Control Panel( 0 ),
        Variables( X( :School Department Type Code ), Color( :Class Rank Number ) ),
        Elements( Points( X, Legend( 6 ) ) ),
        SendToReport( Dispatch( {}, "Graph Builder", FrameBox, {DispatchSeg( Marker Seg( 1 ), Set Hide Missing Color( 1 ) )} ) )
    );
    dt3 = Open("data_table.jmp");
    dt3:Position2 << set property( "missing value codes", {"o"} );
    gb3 = dt3 << Graph Builder(
        Size( 562, 406 ),
        Show Control Panel( 0 ),
        Variables( X( :Weight ), Y( :Height ), Color( :Position2 ), Size( :LegPress ) ),
        Elements( Points( X, Y, Legend( 6 ) ) ),
        SendToReport(
            Dispatch( {}, "Graph Builder", FrameBox,
                {DispatchSeg( Marker Seg( 1 ), {Set Hide Missing Size( 1 ), Set Hide Missing Color( 1 )} )}
            )
        )
    );
);

Code Explanation:

1. Check JMP version.
2. Open data_table data
3. Create Graph Builder for data_table.
4. Set size and hide control panel.
5. Define variables: Longitude, Latitude, Color, Size.
6. Add points element.
7. Configure Longitude scale.
8. Configure Latitude scale.
9. Set background map to Simple Earth.
10. Hide missing color and size for points.
11. Open data_table data
12. Create Graph Builder for data_table.
13. Set size and hide control panel.
14. Define variables: School Department Type Code, Color.
15. Add points element.
16. Hide missing color for points.
17. Open data_table data
18. Set missing value code for Position2.
19. Create Graph Builder for data_table.
20. Set size and hide control panel.
21. Define variables: Weight, Height, Color, Size.
22. Add points element.
23. Hide missing color and size for points.

Example 15

Summary: Creates a treemap graph in JMP, using Graph Builder to visualize data from a table and customize legend properties.

Code:

If( Num( Words( JMP Version(), "." )[1] ) >= 16,
    dt = Open("data_table.jmp");
    Graph Builder(
        Size( 488, 357 ),
        Show Control Panel( 0 ),
        Variables( X( :sex ), X( :age, Position( 1 ) ), Color( :height, Summary Statistic( "Std Dev" ) ), Size( :weight ) ),
        Elements( Treemap( X( 1 ), X( 2 ), Legend( 4 ), Group Labels( "Above" ) ) ),
        SendToReport(
            Dispatch( {}, "400", ScaleBox,
                {Legend Model(
                    4,
                    Properties(
                        0,
                        {gradient(
                            {Color Theme(
                                {"Custom Gradient", 4099, {{42, 63, 255}, {192, 192, 192}, {252, 11, 11}, Missing( {106, 106, 106} )}}
                            ), Width( 12 )}
                        )},
                        Item ID( "height", 1 )
                    )
                )}
            )
        )
    );
);

Code Explanation:

1. Check JMP version.
2. Open data table.
3. Create Graph Builder.
4. Set graph size.
5. Hide control panel.
6. Define variables for treemap.
7. Add treemap element.
8. Customize legend properties.
9. Set color gradient.
10. Apply custom missing value color.

Example 16

Summary: Creates a Treemap visualization in Graph Builder, utilizing variables for sex, age, height, and weight, with customized legend gradient color theme.

Code:

If( Num( Words( JMP Version(), "." )[1] ) >= 16,
    Open("data_table.jmp");
    Graph Builder(
        Size( 495, 379 ),
        Show Control Panel( 0 ),
        Variables( X( :sex ), X( :age, Position( 1 ) ), Color( :height, Summary Statistic( "Std Dev" ) ), Size( :weight ) ),
        Elements( Treemap( X( 1 ), X( 2 ), Legend( 4 ), Category Name( 1 ), Color Value( 1 ), Size Value( 1 ) ) ),
        SendToReport(
            Dispatch( {}, "400", ScaleBox,
                {Legend Model( 4, Properties( 0, {gradient( {Color Theme( "White to Black" ), Width( 12 )} )}, Item ID( "height", 1 ) ) )}
            )
        )
    );
);

Code Explanation:

1. Check JMP version.
2. Open data table;
3. Create Graph Builder window.
4. Set window size to 495x379.
5. Hide control panel.
6. Assign variables: X(sex), X(age), Color(height), Size(weight).
7. Add Treemap element.
8. Configure Treemap settings.
9. Customize legend gradient color theme.
10. Send report with customizations.

Graph Builder using Num

Example 1

Summary: Visualizes a heatmap of high values over time, utilizing Graph Builder to create a customized graph with specific date range and legend settings.

Code:

Open("data_table.jmp");
minDate = Num( "10/1/2011" );
maxDate = Num( "1/28/2012" );
Graph Builder(
    Size( 409, 341 ),
    Show Control Panel( 0 ),
    Show Legend( 0 ),
    Legend Position( "Bottom" ),
    Variables( X( :Date ), Y( :High ) ),
    Elements( Heatmap( X, Y, Legend( 3 ) ) ),
    SendToReport(
        Dispatch( {}, "Date", ScaleBox,
            {Min( minDate ), Max( maxDate ), Interval( "Week" ), Inc( 2 ), Minor Ticks( 0 ), Label Row( Show Major Grid( 1 ) )}
        )
    )
);

Code Explanation:

1. Open data table;
2. Define minimum date.
3. Define maximum date.
4. Create Graph Builder window.
5. Set window size.
6. Hide control panel.
7. Hide legend.
8. Set legend position.
9. Assign variables to axes.
10. Add heatmap element.

Example 2

Summary: Generates a graph to visualize the DJI High values over time, using Graph Builder and adjusting the date axis scale, minimum value, maximum value, interval, and increment.

Code:

Open("data_table.jmp");
minDate = Num( "12Apr1991" );
maxDate = Num( "19Jul1991" );
Graph Builder(
    Size( 727, 437 ),
    Show Control Panel( 0 ),
    Show Legend( 0 ),
    Legend Position( "Bottom" ),
    Variables( X( :Date ), Y( :DJI High ) ),
    Elements( Points( X, Y, Legend( 3 ) ) ),
    SendToReport( Dispatch( {}, "Date", ScaleBox, {Min( minDate ), Max( maxDate ), Interval( "Day" ), Inc( 3 ), Minor Ticks( 0 )} ) )
);

Code Explanation:

1. Open data table;
2. Set minimum date variable.
3. Set maximum date variable.
4. Create Graph Builder window.
5. Configure window size.
6. Hide control panel.
7. Hide legend.
8. Set legend position.
9. Define X and Y variables.
10. Add points element to graph.
11. Adjust date axis scale.
12. Set axis minimum value.
13. Set axis maximum value.
14. Set axis interval to days.
15. Set axis increment to 3.
16. Disable minor ticks.

Example 3

Summary: Visualizes the Dow Jones Industrial Average (DJI) index data by generating a graph with bar elements, using Graph Builder to display high, close, and low values over a specified date range.

Code:

Open("data_table.jmp");
minDate = Num( "11Apr1991" );
maxDate = Num( "20Jul1991" );
interval = 1 * 24 * 60 * 60;
Graph Builder(
    Size( 1485, 467 ),
    Show Control Panel( 0 ),
    Legend Position( "Bottom" ),
    Variables( X( :Date ), Y( :DJI High ), Y( :DJI Close, Position( 1 ) ), Y( :DJI Low, Position( 1 ) ) ),
    Elements( Bar( X, Y( 1 ), Y( 2 ), Y( 3 ), Legend( 2 ), Bar Style( "Interval" ) ) ),
    SendToReport(
        Dispatch( {}, "Date", ScaleBox, {Min( minDate ), Max( maxDate ), Interval( "Second" ), Inc( interval ), Minor Ticks( 0 )} )
    )
);

Code Explanation:

1. Open data table;
2. Set minimum date.
3. Set maximum date.
4. Define time interval.
5. Create Graph Builder window.
6. Set window size.
7. Hide control panel.
8. Position legend at bottom.
9. Define variables for graph.
10. Add bar elements to graph.

Example 4

Summary: Vizualizes daily DJI High values over a specific date range using Graph Builder, with interactive features for date filtering and legend customization.

Code:

Open("data_table.jmp");
minDate = Num( "04/01/1991" );
maxDate = Num( "08/01/1991" );
Graph Builder(
    Size( 535, 395 ),
    Show Control Panel( 0 ),
    Legend Position( "Right" ),
    Variables( X( :Date ), Y( :DJI High ) ),
    Elements( Heatmap( X, Y, Legend( 9 ) ) ),
    SendToReport(
        Dispatch( {}, "Date", ScaleBox, {Min( minDate ), Max( maxDate ), Interval( "Day" ), Inc( 10 ), Minor Ticks( 0 )} ),
        Dispatch( {}, "400", ScaleBox, {Legend Model( 9 )} )
    )
);

Code Explanation:

1. Open data table.
2. Define minimum date.
3. Define maximum date.
4. Create Graph Builder window.
5. Set graph size.
6. Hide control panel.
7. Position legend.
8. Assign variables.
9. Add heatmap element.
10. Configure date axis.

Graph Builder using Format

Example 1

Summary: Visualizes the relationship between log concentration and toxicity using a Graph Builder, with interactive filtering by concentration column.

Code:

dt = Open("data_table.jmp");
dt:concentration << Format( "Fixed Dec", 12, 2 );
dt:log Conc << Format( "Fixed Dec", 12, 2 );
dt:Toxicity << Format( "Fixed Dec", 12, 2 );
Graph Builder(
    Show Control Panel( 0 ),
    Lock Scales( 1 ),
    Variables( X( :log Conc ), Y( :Toxicity ) ),
    Elements( Points( X, Y, Legend( 1 ) ), Smoother( X, Y, Legend( 2 ) ) ),
    Local Data Filter(
        Location( {239, 237} ),
        Add Filter( columns( :Concentration ) ),
        Mode( Select( 0 ), Show( 1 ), Include( 1 ) ),
        Animation( Animate Column( :Concentration ) )
    )
);

Code Explanation:

1. Open data table;
2. Format concentration column.
3. Format log Conc column.
4. Format Toxicity column.
5. Create Graph Builder.
6. Hide control panel.
7. Lock scales on.
8. Set X to log Conc.
9. Set Y to Toxicity.
10. Add points and smoother elements.

Example 2

Summary: Vizualizes hardness prediction formula data using Graph Builder, with interactive treemap and legend features.

Code:

dt = Open("data_table.jmp");
:Pred Formula HARDNESS << Format( "Scientific", 6 );
:Pred Formula HARDNESS << Format( "Scientific", 5 );
Graph Builder( Size( 500, 440 ), Show Control Panel( 0 ), Variables( X( :Pred Formula HARDNESS ) ), Elements( Treemap( X, Legend( 3 ) ) ) );

Code Explanation:

1. Open data table.
2. Set format for hardness prediction formula.
3. Set format for hardness prediction formula.
4. Create graph builder window.
5. Hide control panel.
6. Set X variable to hardness prediction.
7. Add treemap element.
8. Use legend for treemap.

Example 3

Summary: Vizualizes data table 'data_table.jmp' by creating a Treemap graph with scientific formatting for the HARDNESS column, and adding a pin annotation to the graph.

Code:

dt = Open("data_table.jmp");
:Pred Formula HARDNESS << Format( "Scientific", 6 );
Graph Builder(
    Size( 500, 468 ),
    Show Control Panel( 0 ),
    Variables( X( :Pred Formula HARDNESS ) ),
    Elements( Treemap( X, Legend( 3 ) ) ),
    SendToReport(
        Dispatch( {}, "Graph Builder", FrameBox,
            Add Pin Annotation(
                Seg( TreeMapSeg( 1 ) ),
                Index( 0 ),
                Index Row( 10 ),
                UniqueID( 0 ),
                FoundPt( {81, 111} ),
                Origin( {46.1411157024793, 362.718273809524} ),
                RightOfCenter( 0 ),
                Tag Line( 1 )
            )
        )
    )
);

Code Explanation:

1. Open data table.
2. Set scientific format for column.
3. Create Graph Builder object.
4. Set graph size.
5. Hide control panel.
6. Assign variable to X-axis.
7. Add Treemap element.
8. Send report to Graph Builder.
9. Dispatch to Graph Builder frame.
10. Add pin annotation to Treemap.

Example 4

Summary: Vizualizes age vs. height data using a Treemap element in Graph Builder, formatting height as currency.

Code:

Open("data_table.jmp");
:height << Format( "Currency", "USD", 10, 2 );
gb = Graph Builder(
    Show Control Panel( 0 ),
    Variables( X( :age ), Y( :height ) ),
    Elements( Treemap( X, Y, Legend( 7 ), Size Value( 1 ) ) ), 
);

Code Explanation:

1. Open data table.
2. Format height as currency.
3. Create Graph Builder object.
4. Hide control panel.
5. Set X variable to age.
6. Set Y variable to height.
7. Add Treemap element.
8. Configure Treemap legend.
9. Set Treemap size value.
10. Display graph.

Graph Builder using Fit Y by X

Example 1

Summary: Opens a data table, sets value labels, fits height by age using regression, saves the report as OW.jrn, closes the data table without saving, reopens the saved report, and then creates a graph builder with points and smoother, saving it as GB.jrn.

Code:

dt = Open("data_table.jmp");
dt << run script( "Set Age Value Labels" );
dt << Fit Y by X( Y( :height ), X( :age ) );
Current Report() << save journal( "$TEMP\OW.jrn" );
dt << close window( "No Save" );
Open( "$TEMP\OW.jrn" );
dt = Open("data_table.jmp");
dt << run script( "Set Age Value Labels" );
dt << Graph Builder( Variables( X( :age ), Y( :height ) ), Elements( Points( X, Y, Legend( 4 ) ), Smoother( X, Y, Legend( 5 ) ) ) );
Current Report() << save journal( "$TEMP\GB.jrn" );
dt << close window( "No Save" );
Open( "$TEMP\GB.jrn" );

Code Explanation:

1. Open data table.
2. Run script to set value labels.
3. Fit height by age using regression.
4. Save report as OW.jrn.
5. Close data table without saving.
6. Open saved OW.jrn report.
7. Reopen data table.
8. Run script to set value labels again.
9. Create graph builder with points and smoother.
10. Save report as GB.jrn.

Example 2

Summary: Processes fitting height by age regression, creating a graph builder with age and height variables, and saving reports to journals.

Code:

dt = Open("data_table.jmp");
dt << run script( "Set Age Value Labels" );
dt << Fit Y by X( Y( :height ), X( :age ) );
Current Report() << save journal( "$TEMP\OW.jrn" );
dt << close window( "No Save" );
Open( "$TEMP\OW.jrn" );
dt = Open("data_table.jmp");
dt << run script( "Set Age Value Labels" );
dt << Graph Builder( Variables( X( :age ), Y( :height ) ), Elements( Points( X, Y, Legend( 4 ) ), Smoother( X, Y, Legend( 5 ) ) ) );
Current Report() << save journal( "$TEMP\GB.jrn" );
dt << close window( "No Save" );

Code Explanation:

1. Open data table;
2. Run "Set Age Value Labels" script.
3. Fit height by age regression.
4. Save report to OW.jrn.
5. Close data_table.jmp without saving.
6. Open OW.jrn journal.
7. Reopen data_table dataset
8. Run "Set Age Value Labels" script again.
9. Create Graph Builder with age and height.
10. Save report to GB.jrn.

Graph Builder using Axis Title Above

Summary: Creates a graph builder window with a transformed Y-axis variable, displaying the minimum value across multiple columns.

Code:

Preferences[1] << Set( Axis Title Above( 1 ) );
Open("data_table.jmp");

Graph Builder(
    Size( 522, 408 ),
    Show Control Panel( 0 ),
    Variables(
        Y(
            Transform Column(
                "Min[Weight,Turn...,Gas Tank Size]",
                Formula( Minimum( :Weight, :Turning Circle, :Displacement, :Horsepower, :Gas Tank Size ) )
            )
        )
    ),
    Elements( Points( Y, Legend( 2 ) ) )
);

Code Explanation:

1. Set axis title above.
2. Open data table;
3. Create graph builder window.
4. Set graph size.
5. Hide control panel.
6. Define Y variable.
7. Transform column for minimum.
8. Use specified columns.
9. Add points element.
10. Assign legend to points.

Graph Builder using Length

Summary: Calculates and formats string lengths, adds a new column to a data table, and generates a graph with summary statistics.

Code:

Length( Char( "$1.51516679e+10" ) );
Length( Char( "$8,000,000,000.00" ) );
Length( Char( "$10000000000.00" ) );
dt = Open("data_table.jmp");
dt << New Column( "test", formula( :Net Cost * 100 ), Format( "Currency", 17, 2 ) );
rptGB = Graph Builder(
    Size( 526, 366 ),
    Show Control Panel( 0 ),
    Variables( X( :Airline ), Y( :test ) ),
    Elements( Bar( X, Y, Legend( 6 ), Summary Statistic( "Sum" ) ) ), 
) << report;
rptGB[AxisBox( 2 )] << Axis Settings( Format( "Currency", "USD", 14, 2 ) );

Code Explanation:

1. Calculate string length.
2. Calculate string length.
3. Calculate string length.
4. Open data table.
5. Add new column.
6. Set column format.
7. Create graph builder.
8. Configure graph size.
9. Hide control panel.
10. Set variables for graph.

Graph Builder using For

Example 1

Summary: Creates a bar graph with two variables, sex and age, using Graph Builder to visualize the data in the specified data table.

Code:

lgString = "A3A5A7A10A13A16A19A22A25A28A31A34A37A40A";
Open("data_table.jmp");
For( i = 1, i <= 10, i++,
    :sex[i] = lgString
);
Graph Builder(
    Size( 528, 464 ),
    Show Control Panel( 0 ),
    Variables( X( :sex ), X( :age, Position( 1 ) ) ),
    Elements( Bar( X( 1 ), X( 2 ), Legend( 10 ) ) ),
    SendToReport(
        Dispatch( {}, "sex", ScaleBox, {Label Row( 1, Label Orientation( "Vertical" ) ), Label Row( 2, Label Orientation( "Vertical" ) )} )
    )
);

Code Explanation:

1. Define string lgString.
2. Open data table;
3. Loop through first 10 rows.
4. Assign lgString to :sex[i].
5. Launch Graph Builder.
6. Set window size.
7. Hide control panel.
8. Set X variables.
9. Add bar element.
10. Adjust label orientation.

Example 2

Summary: Sets up a Graph Builder platform to visualize categorical data, hiding control panels and including missing categories for Sex and Name variables.

Code:

Open("data_table.jmp");
For( i = 1, i <= 8, i++, :sex[i] = "" );
Graph Builder(
    Show Control Panel( 0 ),
    Include Missing Categories( 1 ),
    Variables( X( :Sex ), X( :Name, Position( 1 ) ) ),
    Elements( Points( X( 1 ), X( 2 ) ) )
);

Code Explanation:

1. Open data table;
2. Loop through first 8 rows.
3. Set "sex" column values to empty string.
4. Launch Graph Builder.
5. Hide control panel.
6. Include missing categories.
7. Set X-axis variable to "Sex".
8. Set second X-axis variable to "Name".
9. Place "Name" on position 1.
10. Add points element for both X-axes.

Example 3

Summary: Runs the initialization and configuration of a Graph Builder platform to visualize categorical data, utilizing variables Sex and Name.

Code:

dt = Open("data_table.jmp");
For( i = 1, i <= 8, i++, :sex[i] = "" );
graph builder(
    show control panel( 0 ),
    Include Missing Categories( 1 ),
    Variables( X( :Sex ), X( :Name, Position( 1 ) ) ),
    Elements( Points( X( 1 ), X( 2 ) ) )
);

Code Explanation:

1. Open data table.
2. Initialize loop counter.
3. Loop through first 8 rows.
4. Clear sex column values.
5. Launch Graph Builder.
6. Hide control panel.
7. Include missing categories.
8. Set X variables: Sex, Name.
9. Position Name on axis 1.
10. Add points element.

Example 4

Summary: Selects and excludes rows in a data table, followed by the creation of a Graph Builder object with specified variables and elements.

Code:

dt = Open("data_table.jmp");
For( i = 1, i <= 10, i++,
    r = dt << select rows( i )
);
r << exclude;
r << clear select;
gb = Graph Builder(
    Size( 551, 524 ),
    Show Control Panel( 0 ),
    Variables( X( :weight ), Group X( :age ), Group Y( :height ), Overlay( :sex ) ),
    Elements( Points( X, Legend( 260 ) ) ), 
);
LF = gb << Local Data Filter( Add Filter( columns( :age, :height ), Display( :age, Size( 149, 102 ) ), Order By Count( :age ) ) );

Code Explanation:

1. Open data table.
2. Loop through first 10 rows.
3. Select each row.
4. Exclude selected rows.
5. Clear row selection.
6. Create Graph Builder object.
7. Set graph size.
8. Hide control panel.
9. Define variables for axes.
10. Add points element with legend.

Example 5

Summary: Selects and excludes rows in a data table, followed by the creation of a Graph Builder object with specific variables and elements.

Code:

dt = Open("data_table.jmp");
For( i = 1, i <= 10, i++,
    r = dt << select rows( i )
);
r << exclude;
r << clear select;
gb = Graph Builder(
    Size( 551, 524 ),
    Show Control Panel( 0 ),
    Variables( X( :weight ), Group X( :age ), Group Y( :height ), Overlay( :sex ) ),
    Elements( Points( X, Legend( 260 ) ) ), 
);
LF = gb << Local Data Filter( Add Filter( columns( :age, :height ), Display( :age, Size( 149, 102 ) ), Order By Count( :age ) ) );
LF << count excluded rows( 0 );

Code Explanation:

1. Open data table;
2. Select first 10 rows.
3. Exclude selected rows.
4. Clear row selection.
5. Create Graph Builder object.
6. Set Graph Builder size.
7. Hide control panel.
8. Define X, Group X, Group Y, Overlay variables.
9. Add points element.
10. Add Local Data Filter.

Example 6

Summary: Process of filtering a data table to identify rows where age is 12, and then generates a bar graph using Graph Builder to visualize the distribution of age.

Code:

dt = Open("data_table.jmp");
myRows = dt << get rows where( :age == 12 );
For( i = 1, i <= N Items( myRows ), i++,
    :age[i] = .
);
dt << Graph Builder(
    Size( 519, 348 ),
    Show Control Panel( 0 ),
    Include Missing Categories( 1 ),
    Variables( X( :age ) ),
    Elements( Bar( X, Legend( 3 ) ) ),
    Local Data Filter( Add Filter( columns( :age, :sex ), Display( :age, Size( 160, 90 ), List Display ) ) )
);

Code Explanation:

1. Open data table.
2. Identify rows where age is 12.
3. Loop through identified rows.
4. Set age to missing for each row.
5. Create Graph Builder object.
6. Set graph size.
7. Hide control panel.
8. Include missing categories.
9. Add age to X-axis.
10. Add bar element with legend.

Example 7

Summary: Data filtering and graphing for age 12 males in a specified data table, utilizing Graph Builder to visualize height-weight relationships.

Code:

dt = Open("data_table.jmp");
rs = dt << get rows where( :age == 12 & :sex == "M" );
For( i = 1, i <= N Items( rs ), i++,
    Column( dt, "weight" )[rs[i]] = .
);
Column( dt, "weight" ) << label( 1 );
Graph Builder(
    Size( 527, 475 ),
    Show Control Panel( 0 ),
    Variables( X( :age ), Y( :height ), Color( :weight ) ),
    Elements( Points( X, Y, Legend( 4 ) ) ),
    SendToReport(
        Dispatch( {}, "Graph Builder", FrameBox,
            Add Pin Annotation(
                Seg( Marker Seg( 1 ) ),
                Index( 5 ),
                Index Row( 5 ),
                UniqueID( 5 ),
                FoundPt( {102, 248} ),
                Origin( {-0.00207468879668049, 60.0200863309353} ),
                RightOfCenter( 0 ),
                Tag Line( 1 )
            )
        )
    )
);

Code Explanation:

1. Open data table;
2. Filter rows for age 12 males.
3. Set weight to missing for filtered rows.
4. Label the weight column.
5. Create Graph Builder window.
6. Disable control panel.
7. Set variables: X(age), Y(height), Color(weight).
8. Add points element.
9. Add pin annotation to graph.
10. Customize pin annotation position and properties.

Example 8

Summary: Creates a bar graph to visualize categorical data from the specified data table, utilizing Graph Builder and SendToReport.

Code:

lgString = "A3A5A7A10A13A16A19A22A25A28A31A34A37A40A";
dt = Open("data_table.jmp");
For( i = 1, i <= 10, i++,
    :sex[i] = lgString
);
obj = Graph Builder(
    Variables( X( :sex ), X( :age, Position( 1 ) ) ),
    Elements( Bar( X( 1 ), X( 2 ), Legend( 10 ) ) ),
    SendToReport(
        Dispatch( {}, "sex", ScaleBox, {Label Row( 1, Label Orientation( "Vertical" ) ), Label Row( 2, Label Orientation( "Vertical" ) )} )
    )
);

Code Explanation:

1. Define string lgString.
2. Open data table;
3. Loop through first 10 rows.
4. Assign lgString to :sex column.
5. Create Graph Builder object.
6. Set X variables: :sex, :age.
7. Add Bar element.
8. Configure legend position.
9. Send report to dispatch.
10. Set label orientation to vertical for both axes.

Example 9

Summary: Generates a distribution analysis for continuous variables in a specified data table using Graph Builder, including interactive features like bar elements with summary statistics and label options.

Code:

dt = Open("data_table.jmp");
myRows = dt << get rows where( :age == 12 & :sex == "M" );
For( i = 1, i <= N Items( myRows ), i++,
    :age[myRows[i]] = .
);
Graph Builder(
    Size( 534, 464 ),
    Show Control Panel( 0 ),
    Variables( X( :sex ), X( :age, Position( 1 ) ), Y( :height ) ),
    Elements( Bar( X( 1 ), X( 2 ), Y, Legend( 7 ), Summary Statistic( "Sum" ), Label( "Label by Percent of Total Values" ) ) )
);
Graph Builder(
    Size( 534, 464 ),
    Show Control Panel( 0 ),
    Include Missing Categories( 1 ),
    Variables( X( :sex ), X( :age, Position( 1 ) ), Y( :height ) ),
    Elements( Bar( X( 1 ), X( 2 ), Y, Legend( 7 ), Summary Statistic( "Sum" ), Label( "Label by Percent of Total Values" ) ) )
);

Code Explanation:

1. Open data table.
2. Identify male students aged 12.
3. Set age of identified students to missing.
4. Create first Graph Builder window.
5. Configure window size and control panel visibility.
6. Set variables for sex, age, and height.
7. Add bar element with summary statistic sum.
8. Label bars by percent of total values.
9. Create second Graph Builder window.
10. Include missing categories in graph.

Example 10

Summary: Generates a distribution analysis for continuous variables in a specified data table using Graph Builder, filtering rows based on age and sex.

Code:

dt = Open("data_table.jmp");
myRows = dt << get rows where( :age == 12 & :sex == "M" );
For( i = 1, i <= N Items( myRows ), i++,
    :height[myRows[i]] = .
);
myRows = dt << select where( :age == 12 & :sex == "F" );
dt << exclude;
Graph Builder(
    Size( 494, 348 ),
    Show Control Panel( 0 ),
    Show Legend( 1 ),
    Include Missing Categories( 1 ),
    Variables( Overlay( :age ), Frequency( :height ) ),
    Elements( Bar( Legend( 9 ), Label( "Label by Value" ) ) )
);

Code Explanation:

1. Open data table.
2. Get rows for age 12 males.
3. Set height to missing for those rows.
4. Select rows for age 12 females.
5. Exclude selected rows.
6. Create Graph Builder.
7. Set graph size.
8. Hide control panel.
9. Show legend.
10. Include missing categories.
11. Set overlay variable to age.
12. Set frequency variable to height.
13. Add bar element with label by value.

Example 11

Summary: Generates a stacked bar graph to visualize age distribution for males with an age of 12, utilizing Graph Builder and specifying X variables as height and weight.

Code:

dt = Open("data_table.jmp");
rs = dt << get rows where( :age == 12 & :sex == "M" );
For( i = 1, i <= N Items( rs ), i++,
    :age[rs[i]] = .
);
Graph Builder(
    Size( 568, 517 ),
    Show Control Panel( 0 ),
    Variables( X( :height ), X( :weight, Position( 1 ) ), Y( :age ) ),
    Elements(
        Bar(
            X( 1 ),
            X( 2 ),
            Y,
            Legend( 7 ),
            Bar Style( "Stacked" ),
            Summary Statistic( "% of Total" ),
            Error Bars( "Range" ),
            Label( "Label by Value" )
        )
    )
);

Code Explanation:

1. Open data table;
2. Get rows where age is 12 and sex is "M".
3. Set selected ages to missing.
4. Create Graph Builder window.
5. Set window size to 568x517.
6. Hide control panel.
7. Set X variables: height, weight.
8. Set Y variable: age.
9. Add stacked bar element.
10. Configure bar style, summary statistic, error bars, and label.

Example 12

Summary: Generates bar graphs by age, overlay sex, with various bar styles (Stacked, Bullet, Nested, Range, Interval) for a specified data table.

Code:

dt = Open("data_table.jmp");
myMissingSexRows = dt << get rows where( :age == 15 & :sex == "M" );
For( i = 1, i <= N Items( myMissingSexRows ), i++,
    :sex[myMissingSexRows[i]] = ""
);
Graph Builder( Size( 608, 628 ), Show Control Panel( 0 ), Variables( X( :age ), Overlay( :sex ) ), Elements( Bar( X, Legend( 6 ) ) ) );
Graph Builder(
    Size( 648, 534 ),
    Show Control Panel( 0 ),
    Variables( X( :age ), Overlay( :sex ) ),
    Elements( Bar( X, Legend( 6 ), Bar Style( "Stacked" ) ) )
);
Graph Builder(
    Size( 648, 534 ),
    Show Control Panel( 0 ),
    Variables( X( :age ), Overlay( :sex ) ),
    Elements( Bar( X, Legend( 6 ), Bar Style( "Bullet" ) ) )
);
Graph Builder(
    Size( 648, 534 ),
    Show Control Panel( 0 ),
    Variables( X( :age ), Overlay( :sex ) ),
    Elements( Bar( X, Legend( 6 ), Bar Style( "Nested" ) ) )
);
Graph Builder(
    Size( 648, 534 ),
    Show Control Panel( 0 ),
    Variables( X( :age ), Overlay( :sex ) ),
    Elements( Bar( X, Legend( 6 ), Bar Style( "Range" ) ) )
);
Graph Builder(
    Size( 648, 534 ),
    Show Control Panel( 0 ),
    Variables( X( :age ), Overlay( :sex ) ),
    Elements( Bar( X, Legend( 6 ), Bar Style( "Interval" ) ) )
);

Code Explanation:

1. Open data table;
2. Identify age 15 male rows.
3. Set sex to missing for those rows.
4. Create bar graph by age, overlay sex.
5. Repeat with stacked bar style.
6. Repeat with bullet bar style.
7. Repeat with nested bar style.
8. Repeat with range bar style.
9. Repeat with interval bar style.

Example 13

Summary: Generates a bar graph to visualize the distribution of height for 12-year-old males, utilizing Graph Builder and filtering rows based on specific conditions.

Code:

dt = Open("data_table.jmp");
myRows = dt << get rows where( :age == 12 & :sex == "M" );
For( i = 1, i <= N Items( myRows ), i++,
    :height[myRows[i]] = .
);
Graph Builder(
    Size( 533, 378 ),
    Show Control Panel( 0 ),
    Include Missing Categories( 1 ),
    Variables( X( :sex ), Overlay( :age ), Frequency( :height ) ),
    Elements( Bar( X, Legend( 2 ), Summary Statistic( "N" ), Label( "Label by Value" ) ) )
);

Code Explanation:

1. Open data table.
2. Filter rows for age 12 males.
3. Set height to missing for filtered rows.
4. Create Graph Builder object.
5. Set window size to 533x378.
6. Hide control panel.
7. Include missing categories.
8. Set X variable to sex.
9. Set overlay variable to age.
10. Set frequency variable to height.

Example 14

Summary: Generates a bar graph to visualize the distribution of weight by age, filtered for female individuals with an age of 15, using Graph Builder.

Code:

dt = Open("data_table.jmp");
myRows = dt << get rows where( :age == 15 & :sex == "F" );
For( i = 1, i <= N Items( myRows ), i++,
    :age[myRows[i]] = .
);
Graph Builder(
    Size( 518, 448 ),
    Show Control Panel( 0 ),
    Variables( X( :age ), Y( :weight ) ),
    Elements( Bar( X, Y, Legend( 6 ), Summary Statistic( "Sum" ), Label( "Label by Percent of Total Values" ) ) )
);

Code Explanation:

1. Open data table.
2. Filter rows by age and sex.
3. Replace filtered ages with missing values.
4. Create Graph Builder object.
5. Set graph size.
6. Hide control panel.
7. Assign variables for X and Y axes.
8. Add bar element to graph.
9. Configure summary statistic as sum.
10. Label bars by percent of total values.

Example 15

Summary: Generates a graph for continuous variables in a specified data table using Graph Builder, with interactive filtering by missing values.

Code:

dt = Open("data_table.jmp");
For( myRow = 1, myRow <= 9, myRow++,
    :age[myRow] = .
);
Graph Builder(
    show control panel( 0 ),
    Variables( X( :sex ), Y( :height ) ),
    Elements( Bar( X, Y, Legend( 1 ) ), Smoother( X, Y, Legend( 2 ) ) ),
    Where( Is Missing( :age ) )
);

Code Explanation:

1. Open data_table data
2. Loop through first 9 rows.
3. Set age to missing for each row.
4. Create Graph Builder object.
5. Hide control panel.
6. Set X variable to sex.
7. Set Y variable to height.
8. Add bar element.
9. Add smoother element.
10. Filter rows where age is missing.

Example 16

Summary: Analyze a specific subset of data in a JMP data table, including filtering rows by age and sex, setting height to missing for males aged 12, excluding female rows aged 12, and generating a graph using Graph Builder.

Code:

dt = Open("data_table.jmp");
myRows = dt << get rows where( :age == 12 & :sex == "M" );
For( i = 1, i <= N Items( myRows ), i++,
    :height[myRows[i]] = .
);
myRows = dt << select where( :age == 12 & :sex == "F" );
dt << exclude;
Graph Builder(
    Size( 533, 378 ),
    Include Missing Categories( 1 ),
    Show Control Panel( 0 ),
    Variables( X( :sex ), Overlay( :age ), Frequency( :height ) ),
    Elements( Bar( X, Legend( 2 ), Summary Statistic( "% of Total" ), Label( "Label by Value" ) ) )
);

Code Explanation:

1. Open data table.
2. Identify male rows aged 12.
3. Set height to missing for males aged 12.
4. Identify female rows aged 12.
5. Exclude female rows aged 12.
6. Create Graph Builder window.
7. Set size of Graph Builder.
8. Include missing categories.
9. Hide control panel.
10. Define variables and elements.

Example 17

Summary: Generates a graph to visualize height by sex for age 12, utilizing Graph Builder and excluding missing values.

Code:

dt = Open("data_table.jmp");
myRows = dt << get rows where( :age == 12 );
For( i = 1, i <= N Items( myRows ), i++,
    :age[myRows[i]] = .
);
Graph Builder(
    Include Missing Categories( 1 ),
    Show Control Panel( 0 ),
    Variables( X( :sex ), Y( :height ), Page( :age ) ),
    Elements( Bar( X, Y, Legend( 9 ) ) )
);

Code Explanation:

1. Open data table;
2. Identify rows where age is 12.
3. Replace age values with missing for those rows.
4. Create Graph Builder object.
5. Include missing categories in graph.
6. Hide control panel.
7. Set X variable to sex.
8. Set Y variable to height.
9. Use age for page.
10. Add bar element to graph.

Example 18

Summary: Generates a bar graph to display the distribution of age values, with missing categories included and percentage of total summary statistics.

Code:

dt = Open("data_table.jmp");
myrows = dt << get rows where( :age == 12 );
For( i = 1, i <= N Items( myrows ), i++,
    :age[i] = .
);
Graph Builder(
    Size( 481, 309 ),
    Show Control Panel( 0 ),
    Include Missing Categories( 1 ),
    Variables( X( :age ) ),
    Elements( Bar( X, Legend( 3 ), Summary Statistic( "% of Total" ), Label( "Label by Value" ) ) )
);

Code Explanation:

1. Open data_table data
2. Retrieve rows where age is 12.
3. Loop through selected rows.
4. Set age to missing for each row.
5. Create Graph Builder window.
6. Set window size to 481x309.
7. Hide control panel.
8. Include missing categories.
9. Set X variable to age.
10. Add bar element with percentage of total summary statistic.

Example 19

Summary: Generates a distribution analysis for continuous variables in a specified data table using Graph Builder, selecting age 12 male and female rows and excluding females from the analysis.

Code:

dt = Open("data_table.jmp");
myRows = dt << get rows where( :age == 12 & :sex == "M" );
For( i = 1, i <= N Items( myRows ), i++,
    :height[myRows[i]] = .
);
myRows = dt << select where( :age == 12 & :sex == "F" );
dt << exclude;
Graph Builder(
    Size( 533, 378 ),
    Show Control Panel( 0 ),
    Include Missing Categories( 1 ),
    Variables( X( :sex ), Overlay( :age ), Frequency( :height ) ),
    Elements( Bar( X, Legend( 8 ), Label( "Label by Value" ) ) )
);

Code Explanation:

1. Open data table;
2. Identify age 12 male rows.
3. Set height to missing for males.
4. Select age 12 female rows.
5. Exclude females from analysis.
6. Create Graph Builder object.
7. Set window size.
8. Hide control panel.
9. Include missing categories.
10. Define variables and elements.

Example 20

Summary: Selects and excludes specific rows in a data table, followed by the creation of a Graph Builder window with customized settings.

Code:

dt = Open("data_table.jmp");
myRows = dt << get rows where( :age == 12 & :sex == "M" );
For( i = 1, i <= N Items( myRows ), i++,
    :height[myRows[i]] = .
);
myRows = dt << select where( :age == 12 & :sex == "F" );
dt << exclude;
Graph Builder(
    Size( 494, 378 ),
    Show Control Panel( 0 ),
    Show Legend( 1 ),
    Include Missing Categories( 1 ),
    Variables( X( :sex ), Overlay( :age ), Frequency( :height ) ),
    Elements( Box Plot( X, Legend( 5 ) ) )
);

Code Explanation:

1. Open data table.
2. Get male rows aged 12.
3. Set heights to missing for males.
4. Select female rows aged 12.
5. Exclude selected rows.
6. Create Graph Builder window.
7. Hide control panel.
8. Show legend.
9. Include missing categories.
10. Configure variables and elements.

Example 21

Summary: Excludes 12-year-old female rows and generates a box plot to visualize height distribution by sex, utilizing Graph Builder.

Code:

dt = Open("data_table.jmp");
myRows = dt << get rows where( :age == 12 & :sex == "M" );
For( i = 1, i <= N Items( myRows ), i++,
    :height[myRows[i]] = .
);
myRows = dt << select where( :age == 12 & :sex == "F" );
dt << exclude;
Graph Builder(
    Size( 494, 378 ),
    Show Control Panel( 0 ),
    Include Missing Categories( 1 ),
    Variables( X( :sex ), Overlay( :age ), Frequency( :height ) ),
    Elements( Box Plot( X, Legend( 7 ) ) )
);

Code Explanation:

1. Open data table.
2. Identify 12-year-old male rows.
3. Set height values for those rows to missing.
4. Identify 12-year-old female rows.
5. Exclude 12-year-old female rows.
6. Create Graph Builder window.
7. Set graph size to 494x378.
8. Hide control panel.
9. Include missing categories.
10. Configure variables: X(sex), Overlay(age), Frequency(height).
11. Add Box Plot element with legend.

Example 22

Summary: Generates a box plot to visualize height distribution for individuals with an age of 12, utilizing Graph Builder and setting age values to missing.

Code:

dt = Open("data_table.jmp");
rs = dt << get rows where( :age == 12 );
For( i = 1, i <= N Items( rs ), i++,
    :age[i] = .
);
Graph Builder(
    Size( 490, 352 ),
    Show Control Panel( 0 ),
    Include Missing Categories( 1 ),
    Variables( X( :age ), Y( :height ), Color( :age ) ),
    Elements( Box Plot( X, Y, Legend( 4 ) ) )
);
Current Report() << save journal( "$TEMP/test.jrn" );

Code Explanation:

1. Open data table.
2. Retrieve rows where age is 12.
3. Loop through retrieved rows.
4. Set age values to missing.
5. Create Graph Builder window.
6. Set window size.
7. Hide control panel.
8. Include missing categories.
9. Define variables for plot.
10. Add box plot element.
11. Save report as journal.

Example 23

Summary: Generates a box plot to visualize the distribution of height for individuals with an age of 12, utilizing Graph Builder and setting missing values for age.

Code:

dt = Open("data_table.jmp");
rs = dt << get rows where( :age == 12 );
For( i = 1, i <= N Items( rs ), i++,
    :age[i] = .
);
Graph Builder(
    Size( 490, 352 ),
    Show Control Panel( 0 ),
    Include Missing Categories( 1 ),
    Variables( X( :age ), Y( :height ), Color( :age ) ),
    Elements( Box Plot( X, Y, Legend( 4 ) ) )
);
Current Report() << save journal( "$TEMP/test.jrn" );
Open( "$TEMP/test.jrn" );

Code Explanation:

1. Open data table.
2. Get rows where age is 12.
3. Loop through selected rows.
4. Set age to missing for each row.
5. Create Graph Builder window.
6. Set size of graph.
7. Hide control panel.
8. Include missing categories.
9. Assign variables for axes and color.
10. Add box plot element.
11. Save report as journal file.
12. Open saved journal file.

Example 24

Summary: Generates various graph types (area, bar, box plot, heatmap, histogram, and line plot) for a specified data table, with interactive features like overlaying age groups.

Code:

dt = Open("data_table.jmp");
nrs = dt << get rows where( :age == 12 );
For( i = 1, i <= N Items( nrs ), i++,
    :age[i] = 9999
);
:age << set property( "Missing Value Codes", 9999 );
Graph Builder(
    Size( 433, 396 ),
    Show Control Panel( 0 ),
    Variables( X( :sex ), Y( :height ), Overlay( :age ) ),
    Elements( Area( X, Y, Legend( 9 ) ) )
);
Graph Builder(
    Size( 433, 396 ),
    Show Control Panel( 0 ),
    Variables( X( :sex ), Y( :height ), Overlay( :age ) ),
    Elements( Bar( X, Y, Legend( 10 ) ) )
);
Graph Builder(
    Size( 433, 396 ),
    Show Control Panel( 0 ),
    Variables( X( :sex ), Y( :height ), Overlay( :age ) ),
    Elements( Box Plot( X, Y, Legend( 10 ) ) )
);
Graph Builder(
    Size( 433, 396 ),
    Show Control Panel( 0 ),
    Variables( X( :sex ), Y( :height ), Overlay( :age ) ),
    Elements( Heatmap( X, Y, Legend( 10 ) ) )
);
Graph Builder(
    Size( 433, 396 ),
    Show Control Panel( 0 ),
    Variables( X( :sex ), Y( :height ), Overlay( :age ) ),
    Elements( Histogram( X, Y, Legend( 10 ) ) )
);
Graph Builder(
    Size( 433, 396 ),
    Show Control Panel( 0 ),
    Variables( X( :sex ), Y( :height ), Overlay( :age ) ),
    Elements( Line( X, Y, Legend( 10 ) ) )
);
Graph Builder(
    Size( 433, 396 ),
    Show Control Panel( 0 ),
    Variables( X( :sex ), Y( :height ), Overlay( :age ) ),
    Elements( Mosaic( X, Y, Legend( 10 ) ) )
);
Graph Builder(
    Size( 433, 396 ),
    Show Control Panel( 0 ),
    Variables( X( :sex ), Y( :height ), Overlay( :age ) ),
    Elements( Points( X, Y, Legend( 10 ) ) )
);
Graph Builder(
    Size( 433, 396 ),
    Show Control Panel( 0 ),
    Variables( X( :sex ), Y( :height ), Overlay( :age ) ),
    Elements( Smoother( X, Y, Legend( 10 ) ) )
);

Code Explanation:

1. Open data table;
2. Find rows where age is 12.
3. Replace age 12 with 9999.
4. Set 9999 as missing value code for age.
5. Create Graph Builder with area plot.
6. Create Graph Builder with bar plot.
7. Create Graph Builder with box plot.
8. Create Graph Builder with heatmap.
9. Create Graph Builder with histogram.
10. Create Graph Builder with line plot.

Example 25

Summary: Generates various graph types for continuous variables in a specified data table, including area, bar, box plot, heatmap, histogram, line, and treemap graphs.

Code:

dt = Open("data_table.jmp");
nrs = dt << get rows where( :age == 12 );
For( i = 1, i <= N Items( nrs ), i++,
    :age[i] = 9999
);
:age << set property( "Missing Value Codes", 9999 );
Graph Builder(
    Size( 433, 396 ),
    Show Control Panel( 0 ),
    Variables( X( :sex ), Y( :height ), Overlay( :age ) ),
    Elements( Area( X, Y, Legend( 9 ) ) )
);
Graph Builder(
    Size( 433, 396 ),
    Show Control Panel( 0 ),
    Variables( X( :sex ), Y( :height ), Overlay( :age ) ),
    Elements( Bar( X, Y, Legend( 10 ) ) )
);
Graph Builder(
    Size( 433, 396 ),
    Show Control Panel( 0 ),
    Variables( X( :sex ), Y( :height ), Overlay( :age ) ),
    Elements( Box Plot( X, Y, Legend( 10 ) ) )
);
Graph Builder(
    Size( 433, 396 ),
    Show Control Panel( 0 ),
    Variables( X( :sex ), Y( :height ), Overlay( :age ) ),
    Elements( Heatmap( X, Y, Legend( 10 ) ) )
);
Graph Builder(
    Size( 433, 396 ),
    Show Control Panel( 0 ),
    Variables( X( :sex ), Y( :height ), Overlay( :age ) ),
    Elements( Histogram( X, Y, Legend( 10 ) ) )
);
Graph Builder(
    Size( 433, 396 ),
    Show Control Panel( 0 ),
    Variables( X( :sex ), Y( :height ), Overlay( :age ) ),
    Elements( Line( X, Y, Legend( 10 ) ) )
);
Graph Builder(
    Size( 433, 396 ),
    Show Control Panel( 0 ),
    Variables( X( :sex ), Y( :height ), Overlay( :age ) ),
    Elements( Mosaic( X, Y, Legend( 10 ) ) )
);
Graph Builder(
    Size( 433, 396 ),
    Show Control Panel( 0 ),
    Variables( X( :sex ), Y( :height ), Overlay( :age ) ),
    Elements( Points( X, Y, Legend( 10 ) ) )
);
Graph Builder(
    Size( 433, 396 ),
    Show Control Panel( 0 ),
    Variables( X( :sex ), Y( :height ), Overlay( :age ) ),
    Elements( Smoother( X, Y, Legend( 10 ) ) )
);
Graph Builder(
    Size( 433, 396 ),
    Show Control Panel( 0 ),
    Variables( X( :sex ), Y( :height ), Overlay( :age ) ),
    Elements( Treemap( X, Y, Legend( 10 ) ) )
);

Code Explanation:

1. Open data table.
2. Identify age 12 rows.
3. Replace age 12 with 9999.
4. Set missing value code for age.
5. Create area graph.
6. Create bar graph.
7. Create box plot.
8. Create heatmap.
9. Create histogram.
10. Create line graph.

Example 26

Summary: Generates a heatmap to visualize age distribution, utilizing Graph Builder and specifying missing categories.

Code:

dt = Open("data_table.jmp");
myRows = dt << get rows where( :age == 15 );
For( i = 1, i <= N Items( myRows ), i++,
    :age[myRows[i]] = .
);
Graph Builder(
    Size( 401, 220 ),
    Show Control Panel( 0 ),
    Include Missing Categories( 1 ),
    Variables(
        X( :age, Order By( Transform Column( "Count", Formula( Col Number( :age, :age ) ) ), Ascending, Order Statistic( "Mean" ) ) )
    ),
    Elements( Heatmap( X, Legend( 5 ), Label( "Label by Value" ) ) )
);

Code Explanation:

1. Open data table.
2. Get rows where age is 15.
3. Loop through selected rows.
4. Set age to missing for each row.
5. Create Graph Builder.
6. Set graph size.
7. Hide control panel.
8. Include missing categories.
9. Define X variable with age.
10. Apply heatmap element.

Example 27

Summary: Generates a heatmap to visualize the distribution of ages, utilizing Graph Builder and excluding specific age values.

Code:

dt = Open("data_table.jmp");
myRows = dt << get rows where( :age == 15 );
For( i = 1, i <= N Items( myRows ), i++,
    :age[myRows[i]] = .
);
Graph Builder(
    Size( 401, 220 ),
    Show Control Panel( 0 ),
    Include Missing Categories( 1 ),
    Variables(
        X( :age, Order By( Transform Column( "Count", Formula( Col Number( :age, :age ) ) ), Ascending, Order Statistic( "Mean" ) ) )
    ),
    Elements( Heatmap( X, Legend( 5 ), Label( "Label by Value" ) ) ),
    SendToReport( Dispatch( {}, "age", ScaleBox, {Reversed Scale} ) )
);

Code Explanation:

1. Open data table.
2. Get rows where age is 15.
3. Set those ages to missing.
4. Create Graph Builder window.
5. Hide control panel.
6. Include missing categories.
7. Set X variable to age.
8. Order by transformed count.
9. Use ascending order statistic.
10. Add heatmap element.

Example 28

Summary: Creates a parallel plot in Graph Builder to visualize height and weight data for 13 individuals, with age on the X-axis and sex as a color variable.

Code:

dt = Open("data_table.jmp");
For( i = 1, i <= 13, i++,
    :height[i] = .;
    :weight[i] = .;
);
Graph Builder(
    Size( 422, 460 ),
    Show Control Panel( 0 ),
    Variables( X( :age ), X( :height, Position( 1 ) ), Color( :sex ), Size( :weight ) ),
    Elements( Parallel( X( 1 ), X( 2 ), Legend( 5 ) ) )
);

Code Explanation:

1. Open data table;
2. Loop through first 13 rows.
3. Set height to missing.
4. Set weight to missing.
5. Create Graph Builder window.
6. Set window size.
7. Hide control panel.
8. Define variables for axes and elements.
9. Add age to X-axis.
10. Add height to X-axis.
11. Set sex as color variable.
12. Set weight as size variable.
13. Add parallel plot element.

Example 29

Summary: Generates a pie chart to visualize the distribution of height values for individuals with age 12, utilizing Graph Builder and negating the original height values.

Code:

dt = Open("data_table.jmp");
rs = dt << get rows where( :age == 12 );
For( i = 1, i <= N Items( rs ), i++,
    Column( "height" )[i] = (-1) * Column( "height" )[i]
);
Graph Builder(
    Size( 587, 374 ),
    Show Control Panel( 0 ),
    Variables( X( :age ), Y( :height ) ),
    Elements( Pie( X, Y, Legend( 4 ), Summary Statistic( "Sum" ), Label( "Label by Value" ) ) )
);

Code Explanation:

1. Open data table.
2. Get rows where age is 12.
3. Loop through selected rows.
4. Negate height values.
5. Create Graph Builder.
6. Set size to 587x374.
7. Hide control panel.
8. Assign variables X and Y.
9. Add pie element.
10. Summarize by sum, label by value.

Example 30

Summary: Creates a treemap graph in Graph Builder to visualize missing category labels for age and sex variables, with specific filtering and formatting applied.

Code:

dt = Open("data_table.jmp");
rows = dt << get rows where( :age == 15 & :sex == "F" );
For( i = 1, i <= N Items( rows ), i++,
    :sex[rows[i]] = ""
);
Graph Builder(
    Size( 533, 438 ),
    Show Control Panel( 0 ),
    Show Legend( 0 ),
    Include Missing Categories( 1 ),
    Variables( X( :age ), X( :sex, Position( 1 ) ) ),
    Elements( Treemap( X( 1 ), X( 2 ), Legend( 20 ) ) ),
    SendToReport( Dispatch( {}, "Graph Builder", OutlineBox, {Set Title( "Graph Builder: missing catagory label" )} ) )
);

Code Explanation:

1. Open data table.
2. Get rows where age is 15 and sex is female.
3. Loop through selected rows.
4. Set sex column to empty string.
5. Create Graph Builder.
6. Set graph size.
7. Hide control panel.
8. Hide legend.
9. Include missing categories.
10. Add treemap element with specified variables and title.

Example 31

Summary: Generates a treemap visualization to display age distribution, utilizing Graph Builder and filtering rows where age is 15.

Code:

dt = Open("data_table.jmp");
myRows = dt << get rows where( :age == 15 );
For( i = 1, i <= N Items( myRows ), i++,
    :age[myRows[i]] = .
);
Graph Builder(
    Size( 106, 852 ),
    Show Control Panel( 0 ),
    Include Missing Categories( 1 ),
    Variables(
        X( :age, Order By( Transform Column( "Count[age]", Formula( Col Number( :age, :age ) ) ), Ascending, Order Statistic( "Mean" ) ) )
    ),
    Elements( Treemap( X, Legend( 6 ), Category Name( 1 ), Size Value( 1 ), Implicit Color( 0 ) ) )
);

Code Explanation:

1. Open data table.
2. Identify rows where age is 15.
3. Replace age values with missing for selected rows.
4. Create Graph Builder object.
5. Set graph size.
6. Hide control panel.
7. Include missing categories.
8. Define X variable with age.
9. Order by transformed column count.
10. Configure treemap element.

Example 32

Summary: Filters and visualizes data for female individuals aged 15, utilizing Graph Builder to create a treemap with floating group labels.

Code:

dt = Open("data_table.jmp");
rows = dt << get rows where( :age == 15 & :sex == "F" );
For( i = 1, i <= N Items( rows ), i++,
    :sex[rows[i]] = ""
);
Graph Builder(
    Size( 560, 542 ),
    show control panel( 0 ),
    Include Missing Categories( 1 ),
    Variables( X( :sex ), X( :age, Position( 1 ) ), Color( :weight ) ),
    Elements( Treemap( X( 1 ), X( 2 ), Legend( 1 ), Group Labels( "Floating" ) ) )
);

Code Explanation:

1. Open data table.
2. Filter rows for age 15 and female.
3. Loop through filtered rows.
4. Clear sex value for each row.
5. Create Graph Builder window.
6. Set window size.
7. Hide control panel.
8. Include missing categories.
9. Define variables for treemap.
10. Add treemap element with floating group labels.

Example 33

Summary: Generates a distribution analysis for continuous variables in the specified data table using Graph Builder and Heatmap elements.

Code:

dt = Open("data_table.jmp");
rs = dt << get rows where( :age == 17 );
For( i = 1, i <= N Items( rs ), i++,
    :weight[rs[i]] = .
);
dt << Graph Builder(
    Size( 440, 228 ),
    Show Control Panel( 0 ),
    Variables( X( :age ), Y( :height ), Color( :weight, Summary Statistic( "Std Dev" ) ) ),
    Elements( Bar( X, Y, Legend( 7 ) ) )
);
Graph Builder(
    Size( 469, 314 ),
    Show Control Panel( 0 ),
    Variables( X( :age ), Y( :sex ), Color( :height, Summary Statistic( "Std Dev" ) ) ),
    Elements( Heatmap( X, Y, Legend( 2 ) ) ),
    SendToReport(
        Dispatch( {}, "400", ScaleBox,
            {Legend Model(
                2,
                Properties(
                    0,
                    {gradient(
                        {Color Theme(
                            {"Blue to Gray to Red Copy", 4099, {{42, 63, 255}, {192, 192, 192}, {252, 11, 11}, Missing( {106, 106, 106} )}}
                        ), Width( 12 )}
                    )},
                    Item ID( "height", 1 )
                )
            )}
        )
    )
);

Code Explanation:

1. Open data table.
2. Get rows where age is 17.
3. Set weight to missing for those rows.
4. Create Graph Builder window.
5. Set size to 440x228.
6. Hide control panel.
7. Assign variables: X=age, Y=height, Color=weight.
8. Add bar element with legend.
9. Create another Graph Builder window.
10. Set size to 469x314.
11. Hide control panel.
12. Assign variables: X=age, Y=sex, Color=height.
13. Add heatmap element with legend.
14. Customize legend properties.
15. Set color theme and width.

Example 34

Summary: Selects and excludes rows in a data table, followed by the creation of a graph using Graph Builder to visualize the relationship between weight and age.

Code:

dt = Open("data_table.jmp");
For( i = 1, i <= 10, i++,
    r = dt << select rows( i )
);
r << exclude;
r << clear select;
Graph Builder(
    Size( 350, 424 ),
    Show Control Panel( 0 ),
    Variables( Y( :weight ), X( :age ) ),
    Elements( Bar( X, Y, Legend( 260 ) ) ),
    Local Data Filter( Conditional, Add Filter( columns( :age, :height ), Where( :age == {13, 14} ), Display( :age, Size( 149, 136 ) ) ) )
);

Code Explanation:

1. Open data table;
2. Loop through first 10 rows.
3. Select each row.
4. Exclude selected rows.
5. Clear row selection.
6. Create Graph Builder.
7. Set graph size.
8. Hide control panel.
9. Define variables: weight, age.
10. Add bar element with legend.

Graph Builder using Get Preference

Example 1

Summary: Creates a graph with points and smoother elements, utilizing Graph Builder to visualize data from an open data table.

Code:

restore prefs = Get Preference( Axis Title Above );
Set Preference( Axis Title Above( 1 ) );
dt = Open("data_table.jmp");
dt << Graph Builder(
    Show Control Panel( 0 ),
    Variables( X( :height ), Y( :weight ) ),
    Elements( Points( X, Y, Legend( 2 ) ), Smoother( X, Y, Legend( 3 ) ) )
);
restore prefs;

Code Explanation:

1. Save current axis title preference.
2. Set axis title above.
3. Open data table;
4. Launch Graph Builder.
5. Hide control panel.
6. Set X variable to height.
7. Set Y variable to weight.
8. Add points element.
9. Add smoother element.
10. Restore original axis title preference.

Example 2

Summary: Creates a graph builder with points and smoother elements, while setting axis title preferences and opening a data table.

Code:

restore prefs = Get Preference( Axis Title Above );
Set Preference( Axis Title Above( 1 ) );
Open("data_table.jmp");
Graph Builder(
    Show Control Panel( 0 ),
    Variables( X( :height ), Y( :weight ) ),
    Elements( Points( X, Y, Legend( 2 ) ), Smoother( X, Y, Legend( 3 ) ) )
);
restore prefs;

Code Explanation:

1. Retrieve axis title preference.
2. Set axis title above.
3. Open data table;
4. Create Graph Builder.
5. Hide control panel.
6. Set X variable to height.
7. Set Y variable to weight.
8. Add points element.
9. Add smoother element.
10. Restore original axis title preference.

Graph Builder using Oneway

Example 1

Summary: Creates a two-way Oneway analysis and a Graph Builder visualization, enabling interactive column switching for sex and height variables.

Code:

dt = Open("data_table.jmp");
ow = dt << Oneway(
    Y( :height ),
    X( :sex ),
    Means( 1 ),
    Mean Diamonds( 1 ),
    Column Switcher( :sex, {:name, :age, :sex} ),
    Column Switcher( :height, {:height, :weight} ),
    SendToReport( Dispatch( {}, "Oneway Anova", OutlineBox, {Close( 1 )} ) )
);
ow << Redo Analysis;
dt = Open("data_table.jmp");
gb = dt << Graph Builder(
    Size( 522, 456 ),
    Show Control Panel( 0 ),
    Variables( X( :Sepal width ), Y( :Sepal length ), Overlay( :Species ) ),
    Elements( Contour( X, Y, Legend( 6 ), Contour Type 2D( "HDR" ) ) )
);
cs1 = gb << Column Switcher( :Sepal length, {:Sepal length, :Petal length} );
cs2 = gb << Column Switcher( :Sepal width, {:Sepal width, :Petal width} );
cs1 << Remove Column Switcher();
gb << Redo Analysis;

Code Explanation:

1. Open data table;
2. Create Oneway plot for height vs sex.
3. Add means to the plot.
4. Enable mean diamonds.
5. Switch columns for sex.
6. Switch columns for height.
7. Close Oneway Anova outline.
8. Redo the analysis.
9. Open data table;
10. Create Graph Builder with Sepal width vs Sepal length, overlay by Species.
11. Add Contour element.
12. Switch columns for Sepal length.
13. Switch columns for Sepal width.
14. Remove first Column Switcher.
15. Redo the analysis.

Example 2

Summary: Runs a stepwise linear regression analysis on the Fitness data table to identify significant predictors of Oxygen consumption, utilizing Oneway and Graph Builder features.

Code:

dt = Open("data_table.jmp");
ow = Oneway( Y( :weight ), X( :age ), Means( 1 ), Mean Diamonds( 1 ) );
owr = ow << report;
owr[Outline Box( 3 )] << Close;
owr[Outline Box( 4 )] << Close;
tb = owr[Table Box( 3 )];
dt2 = tb << Make Into Data Table;
dt2 << Graph Builder(
    Size( 534, 448 ),
    Show Control Panel( 0 ),
    Variables( X( :Level ), Y( :Mean ), Interval( :Lower 95% ), Interval( :Upper 95% ) ),
    Elements( Points( X, Y, Legend( 6 ) ) )
);

Code Explanation:

1. Open data table;
2. Perform one-way ANOVA on weight by age.
3. Retrieve the report object.
4. Close the third outline box.
5. Close the fourth outline box.
6. Extract the third table box.
7. Convert the table box to a data table.
8. Create a Graph Builder window.
9. Set window size and hide control panel.
10. Add variables and elements to Graph Builder.

Example 3

Summary: Runs a series of data analysis tasks, including creating Oneway plots by sex, getting ByGroup scripts, and generating Graph Builders with transformed variables.

Code:

dt = Open("data_table.jmp");
obj = dt << Oneway( Y( :height ), X( :age ), By( Transform Column( "Lowercase[sex]", Character, Formula( Lowercase( :sex ) ) ) ) );
plan = obj[1] << Get ByGroup Script;
(obj[1] << TopReport) << Journal << Close Window;
plan;
dt = Open("data_table.jmp");
obj = dt << Oneway( Y( :height ), X( :age ), By( Transform Column( "Lowercase[sex]", Character, Formula( Lowercase( :sex ) ) ) ) );
plan = obj[1] << Get ByGroup Script;
(obj[1] << TopReport) << Journal << Close Window;
plan;
dt = Open("data_table.jmp");
Graph Builder(
    Transform Column( "Sepal width^2", Format( "Fixed Dec", 10, 1 ), Formula( :Sepal width * :Sepal width ) ),
    Show Control Panel( 0 ),
    Variables( Y( :"Sepal width^2"n ) ),
    Elements( Points( Y, Legend( 2 ) ) )
);
dt = Open("data_table.jmp");
Graph Builder(
    Transform Column( "height^2", Format( "Fixed Dec", 5, 0 ), Formula( :height * :height ) ),
    Show Control Panel( 0 ),
    Variables( Y( :"height^2"n ) ),
    Elements( Points( Y, Legend( 2 ) ) )
);

Code Explanation:

1. Open data table;
2. Create Oneway plot by sex.
3. Get ByGroup script.
4. Close report window.
5. Repeat steps 1-4.
6. Open data table;
7. Create Oneway plot by sex.
8. Get ByGroup script.
9. Close report window.
10. Open data table;
11. Create Graph Builder with transformed Sepal width.
12. Open data table;
13. Create Graph Builder with transformed height.

Example 4

Summary: Runs a stepwise linear regression analysis on the Fitness data table to identify significant predictors of Oxygen consumption, utilizing Oneway and By Group scripts.

Code:

dt = Open("data_table.jmp");
obj = dt << Oneway( Y( :height ), X( :age ), By( Transform Column( "Lowercase[sex]", Character, Formula( Lowercase( :sex ) ) ) ) );
plan = obj[1] << Get ByGroup Script;
(obj[1] << TopReport) << Journal << Close Window;
plan;
dt = Open("data_table.jmp");
obj = dt << Oneway( Y( :height ), X( :age ), By( Transform Column( "Lowercase[sex]", Character, Formula( Lowercase( :sex ) ) ) ) );
plan = obj[1] << Get ByGroup Script;
(obj[1] << TopReport) << Journal << Close Window;
plan;
dt = Open("data_table.jmp");
Graph Builder(
    Transform Column( "Sepal width^2", Format( "Fixed Dec", 10, 1 ), Formula( :Sepal width * :Sepal width ) ),
    Show Control Panel( 0 ),
    Variables( Y( :"Sepal width^2"n ) ),
    Elements( Points( Y, Legend( 2 ) ) )
);
dt = Open("data_table.jmp");

Code Explanation:

1. Open data table;
2. Perform one-way analysis on height by age, grouped by lowercase sex.
3. Retrieve by-group script.
4. Close journal window.
5. Execute by-group script.
6. Repeat steps 1-5 for data_table dataset.
7. Open data table;
8. Create new column for squared sepal width.
9. Generate graph builder with squared sepal width.
10. Open data table;

Graph Builder using Set Property

Example 1

Summary: Creates a box plot in Graph Builder to visualize height by age, with forced values for age set.

Code:

dt = Open( "$SAMPLE_DATA/data_table.jmp", invisible );
dt:age << Set Property( "Forced Values", {10, 11} );
gb = dt << Graph Builder(
    Size( 528, 450 ),
    Show Control Panel( 0 ),
    Variables( X( :age ), Y( :height ) ),
    Elements( Box Plot( X, Y, Legend( 6 ) ) ),
    SendToReport( Dispatch( {}, "graph title", TextEditBox, {Set Text( "height by age, Forced Values" )} ) )
);

Code Explanation:

1. Open data table;
2. Set forced values for age.
3. Create Graph Builder object.
4. Set size of graph.
5. Hide control panel.
6. Assign variables for X and Y.
7. Add box plot element.
8. Set legend for box plot.
9. Send report to dispatch.
10. Set graph title.

Example 2

Summary: Creates a box plot in Graph Builder to visualize height by age, with forced values set for age and data filtering applied to include specific age ranges.

Code:

dt = Open( "$SAMPLE_DATA/data_table.jmp", invisible );
dt:age << Set Property( "Forced Values", {10, 11} );
gb = dt << Graph Builder(
    Size( 528, 450 ),
    Show Control Panel( 0 ),
    Variables( X( :age ), Y( :height ) ),
    Elements( Box Plot( X, Y, Legend( 6 ) ) ),
    SendToReport( Dispatch( {}, "graph title", TextEditBox, {Set Text( "height by age, Forced Values" )} ) )
);
df = dt << Data Filter(
    Mode( Select( 0 ), Show( 1 ), Include( 0 ) ),
    Add Filter( columns( :age ), Where( :age == {11, 12, 13, 14} ), Display( :age, N Items( 8 ) ) )
);

Code Explanation:

1. Open data table;
2. Set forced values for age.
3. Create Graph Builder window.
4. Configure Graph Builder size.
5. Hide control panel.
6. Set X and Y variables.
7. Add box plot element.
8. Set graph title.
9. Create Data Filter.
10. Configure Data Filter settings.

Example 3

Summary: Creates a side-by-side bar chart in Graph Builder to visualize the mean profit by product line and quarter from the Profit by Product dataset, with interactive filtering by sex.

Code:

Open("data_table.jmp");
:sex << Set Property( "Value Colors", {"F" = 8, "M" = 13} );
gb = Graph Builder(
    Size( 570, 516 ),
    show control panel( 0 ),
    Variables( X( :age ), Y( :height ), Overlay( :sex ) ),
    Elements( Bar( X, Y, Legend( 6 ) ) ),
    Local Data Filter( Add Filter( columns( :sex ), Where( :sex == "M" ) ) )
);

Code Explanation:

1. Open data table.
2. Set value colors for sex.
3. Create Graph Builder object.
4. Define window size.
5. Hide control panel.
6. Assign variables to axes.
7. Add overlay variable.
8. Create bar element.
9. Add legend to bar.
10. Apply local data filter.

Example 4

Summary: Creates two side-by-side bar charts in Graph Builder to visualize mean height by age and sex from a data table, utilizing Local Data Filters for male and female subsets.

Code:

dt = Open("data_table.jmp");
:sex << Set Property( "Value Colors", {"F" = 8, "M" = 13} );
gb = Graph Builder(
    Size( 570, 516 ),
    show control panel( 0 ),
    Variables( X( :age ), Y( :height ), Overlay( :sex ) ),
    Elements( Bar( X, Y, Legend( 6 ) ) ),
    Local Data Filter( Add Filter( columns( :sex ), Where( :sex == "M" ) ) )
);
gb2 = Graph Builder(
    Size( 570, 516 ),
    show control panel( 0 ),
    Variables( X( :age ), Y( :height ), Overlay( :sex ) ),
    Elements( Bar( X, Y, Legend( 6 ) ) ),
    Local Data Filter( Add Filter( columns( :sex ), Where( :sex == "F" ) ) )
);

Code Explanation:

1. Open data table;
2. Set color properties for sex.
3. Create first Graph Builder object.
4. Define size of graph.
5. Hide control panel.
6. Set X, Y, and overlay variables.
7. Add bar element.
8. Apply local data filter for males.
9. Create second Graph Builder object.
10. Apply local data filter for females.

Example 5

Summary: Creates a color-coded contour map to visualize population distribution by year, utilizing Graph Builder and setting custom color gradient properties.

Code:

Open("data_table.jmp");
:Pop << Set Property( "Color Gradient", {"White to Blue", Range( {0, 576737412, 5000000} )} );
gb = Graph Builder(
    Show Control Panel( 0 ),
    Lock Scales( 1 ),
    Variables( X( :Year ), Y( :Name( "Portion60+ M" ) ), Color( :Pop ) ),
    Elements( Contour( X, Y, Legend( 7 ), Number of Levels( 12 ) ) )
);
gb << Redo Analysis;

Code Explanation:

1. Open data table.
2. Set color gradient property.
3. Create Graph Builder object.
4. Hide control panel.
5. Lock axis scales.
6. Define X, Y, and color variables.
7. Add contour element.
8. Set number of levels.
9. Redo analysis.

Example 6

Summary: Creates a color-coded contour graph to visualize population data by year, utilizing Graph Builder and setting custom color gradient properties.

Code:

Open("data_table.jmp");
:Pop << Set Property( "Color Gradient", {"White to Blue", Range( {0, 576737412, 5000000} )} );
gb = Graph Builder(
    Show Control Panel( 0 ),
    Lock Scales( 1 ),
    Variables( X( :Year ), Y( :Name( "Portion60+ M" ) ), Color( :Pop ) ),
    Elements( Contour( X, Y, Legend( 7 ), Number of Levels( 12 ) ) )
);
gb << Redo Analysis;
gb << close window;

Code Explanation:

1. Open data table;
2. Set color gradient property.
3. Create graph builder object.
4. Hide control panel.
5. Lock scales.
6. Assign variables for X, Y, and Color.
7. Add contour element.
8. Redo analysis.
9. Close graph window.

Example 7

Summary: Creates various plots in Graph Builder to visualize data from a specified data table, utilizing a loop to substitute different plot types.

Code:

dt = Open("data_table.jmp");
dt:sex << Set Property( "Forced Values", {"F", "M", "Android"} );
lstPlots = {Points, Line, Bar, Area, BoxPlot, Histogram, Heatmap, Mosaic, Treemap, Pie};
myJSL = {};
myVList = Expr( V List Box() );
testPlot = Expr(
    Graph Builder(
        Size( 534, 450 ),
        Show Control Panel( 0 ),
        Fit to Window( "Off" ),
        Variables( X( :sex ), Y( :weight ) ),
        Elements( myPlot( X, Y, Legend( 8 ) ) )
    )
);
For( i = 1, i <= N Items( lstPlots ), i++,
    Substitute Into( testPlot, Expr( myPlot ), Eval Expr( Expr( lstPlots[i] ) ) );
    myJSL[i] = Eval Expr( testPlot );
    Substitute Into( testPlot, Eval Expr( Expr( lstPlots[i] ) ), Expr( myPlot ) );
);

Code Explanation:

1. Open data table;
2. Set sex property to forced values.
3. Define plot types list.
4. Initialize empty JSL list.
5. Create vertical list box expression.
6. Define test plot expression.
7. Loop through each plot type.
8. Substitute current plot type into test plot.
9. Add modified test plot to JSL list.
10. Reset plot type in test plot expression.

Example 8

Summary: Creates various plots in Graph Builder, including Points, Line, Bar, Area, BoxPlot, Histogram, Heatmap, Mosaic, Treemap, and Pie charts, using a loop to substitute plot types into a test plot expression.

Code:

dt = Open("data_table.jmp");
dt:sex << Set Property( "Forced Values", {"F", "M", "Android"} );
lstPlots = {Points, Line, Bar, Area, BoxPlot, Histogram, Heatmap, Mosaic, Treemap, Pie};
myJSL = {};
myVList = Expr( V List Box() );
testPlot = Expr(
    Graph Builder(
        Size( 534, 450 ),
        Show Control Panel( 0 ),
        Fit to Window( "Off" ),
        Variables( X( :sex ), Y( :weight ) ),
        Elements( myPlot( X, Y, Legend( 8 ) ) )
    )
);
For( i = 1, i <= N Items( lstPlots ), i++,
    Substitute Into( testPlot, Expr( myPlot ), Eval Expr( Expr( lstPlots[i] ) ) );
    myJSL[i] = Eval Expr( testPlot );
    Substitute Into( testPlot, Eval Expr( Expr( lstPlots[i] ) ), Expr( myPlot ) );
);
New Window( "test", Outline Box( "test", For( i = 1, i <= N Items( lstPlots ), i++, Insert Into( myVList, Eval( myJSL[i] ) ) ) ) );

Code Explanation:

1. Open data table.
2. Set forced values for sex column.
3. Define list of plot types.
4. Initialize empty JSL list.
5. Create vertical list box expression.
6. Define test plot expression.
7. Loop through each plot type.
8. Substitute plot type into test plot.
9. Add modified plot to JSL list.
10. Create new window with all plots.

Example 9

Summary: Configures two Graph Builders to visualize the relationship between weight and height, with sex as a color role or overlay, highlighting identical value colors.

Code:

Open("data_table.jmp"):sex << Set Property( "Value Colors", {"F" = 9, "M" = 9} );
Graph Builder(
    Size( 522, 450 ),
    Show Control Panel( 0 ),
    Variables( X( :weight ), Y( :height ), Color( :sex ) ),
    Elements( Points( X, Y, Legend( 17 ) ) ),
    SendToReport(
        Dispatch( {}, "Graph Builder", FrameBox,
            Add Text Annotation(
                Text( "Color role when value colors are identical
Note: these two reports should look the same" ),
                Fixed Size( 0 ),
                Text Box( {225, 346, 483, 386} ),
                Filled( 0 )
            )
        )
    )
);
Graph Builder(
    Size( 522, 450 ),
    Show Control Panel( 0 ),
    Variables( X( :weight ), Y( :height ), Overlay( :sex ) ),
    Elements( Points( X, Y, Legend( 17 ) ) ),
    SendToReport(
        Dispatch( {}, "Graph Builder", FrameBox,
            Add Text Annotation(
                Text( "Overlay when value colors are identical
Note: these two reports should look the same" ),
                Fixed Size( 0 ),
                Text Box( {227, 349, 485, 389} ),
                Filled( 0 )
            )
        )
    )
);

Code Explanation:

1. Open data_table data
2. Set sex value colors.
3. Create first Graph Builder.
4. Set graph size.
5. Hide control panel.
6. Define variables: weight, height, color by sex.
7. Add points element.
8. Add text annotation.
9. Create second Graph Builder.
10. Set graph size.
11. Hide control panel.
12. Define variables: weight, height, overlay by sex.
13. Add points element.
14. Add text annotation.

Example 10

Summary: Creates a graph builder chart to visualize body mass by species and sex, with a local data filter applied to only include values less than or equal to 4500.

Code:

dt = Open("data_table.jmp");
:Species << Set Property(
    "Forced Values",
    {"Adelie Penguin (Pygoscelis adeliae)", "Chinstrap penguin (Pygoscelis antarctica)", "Emperor penguin (Aptenodytes forsteri)",
    "Gentoo penguin (Pygoscelis papua)"}
);
:Sex << Set Property( "Forced Values", {"MALE", "FEMALE"} );
dt << Graph Builder(
    Variables( X( :Species ), X( :Sex, Position( 1 ) ), Y( :Body Mass ) ),
    Elements( Points( X( 1 ), X( 2 ), Y, Legend( 13 ) ) ),
    Local Data Filter( Add Filter( columns( :Body Mass ), Where( :Body Mass <= 4500 ) ) )
);

Code Explanation:

1. Open data table;
2. Set forced values for Species.
3. Set forced values for Sex.
4. Launch Graph Builder.
5. Assign variables to axes.
6. Add points element.
7. Apply local data filter.
8. Filter Body Mass <= 4500.

Example 11

Summary: Vizualizes penguin species distribution based on culmen depth and length, utilizing Graph Builder with points and smoother elements.

Code:

dt = Open("data_table.jmp");
dt:Species << Set Property(
    "Forced Values",
    {"Adelie Penguin (Pygoscelis adeliae)", "Chinstrap penguin (Pygoscelis antarctica)", "Emperor penguin (Aptenodytes forsteri)",
    "Gentoo penguin (Pygoscelis papua)"}
);
dt << Graph Builder(
    Variables( X( :Culmen Depth ), Y( :Culmen Length ), Color( :Species ) ),
    Elements( Points( X, Y, Legend( 18 ) ), Smoother( X, Y, Legend( 19 ) ) ),
    Local Data Filter( Add Filter( Columns( :Island ) ) )
);

Code Explanation:

1. Open data table;
2. Set forced values for Species.
3. Launch Graph Builder.
4. Set X to Culmen Depth.
5. Set Y to Culmen Length.
6. Color by Species.
7. Add points element.
8. Add smoother element.
9. Add local data filter.
10. Filter by Island.

Example 12

Summary: Creates two Graph Builder visualizations: a scatter plot with points and smoother for Culmen Depth vs. Length, colored by Species, and a bar chart with local data filter for height vs. weight, filtered by age.

Code:

dt = Open("data_table.jmp");
dt:Species << Set Property(
    "Forced Values",
    {"Adelie Penguin (Pygoscelis adeliae)", "Chinstrap penguin (Pygoscelis antarctica)", "Emperor penguin (Aptenodytes forsteri)",
    "Gentoo penguin (Pygoscelis papua)"}
);
dt << Graph Builder(
    Variables( X( :Culmen Depth ), Y( :Culmen Length ), Color( :Species ) ),
    Elements( Points( X, Y, Legend( 18 ) ), Smoother( X, Y, Legend( 19 ) ) ),
    Local Data Filter( Add Filter( Columns( :Island ) ) )
);
dt2 = Open("data_table.jmp");
dt2:age << Set Property( "Forced Values", {12, 13, 14, 15, 16, 17} );
dt2 << Graph Builder(
    Variables( X( :height ), Y( :weight ), Color( :age ) ),
    Elements( Points( X, Y, Legend( 1 ) ), Smoother( X, Y, Legend( 2 ) ) ),
    Local Data Filter( Add Filter( columns( :height ), Where( :height <= 55 ) ) )
);

Code Explanation:

1. Open data table;
2. Set Species forced values.
3. Create Graph Builder for data_table.
4. Plot Culmen Depth vs. Length.
5. Color by Species.
6. Add Points and Smoother elements.
7. Add Island filter.
8. Open data table;
9. Set age forced values.
10. Create Graph Builder for data_table.

Example 13

Summary: Vizualizes species distribution by setting forced values for Species and creating a Graph Builder with Culmen Depth vs Length, colored by Species, and filtered by Island.

Code:

dt = Open("data_table.jmp");
dt:Species << Set Property(
    "Forced Values",
    {"Adelie Penguin (Pygoscelis adeliae)", "Chinstrap penguin (Pygoscelis antarctica)", "Emperor penguin (Aptenodytes forsteri)",
    "Gentoo penguin (Pygoscelis papua)"}
);
dt << Graph Builder(
    Variables( X( :Culmen Depth ), Y( :Culmen Length ), Color( :Species ) ),
    Elements( Points( X, Y, Legend( 18 ) ), Smoother( X, Y, Legend( 19 ) ) ),
    Local Data Filter( Add Filter( Columns( :Island ) ) )
);
dt2 = Open("data_table.jmp");
dt2:age << Set Property( "Forced Values", {12, 13, 14, 15, 16, 17} );

Code Explanation:

1. Open data table;
2. Set Species forced values.
3. Create Graph Builder.
4. Plot Culmen Depth vs Length.
5. Color by Species.
6. Add Points element.
7. Add Smoother element.
8. Enable Local Data Filter.
9. Filter by Island.
10. Open data table;
11. Set age forced values.

Example 14

Summary: Creates a side-by-side bar chart in Graph Builder to visualize the mean profit by product line and quarter from the Profit by Product dataset.

Code:

dt = Open("data_table.jmp");
:Product Line << Set Property( "Row Order Levels" );
Graph Builder(
    Size( 534, 464 ),
    Show Control Panel( 0 ),
    Variables( X( :Product Line ), X( :Quarter, Position( 1 ) ) ),
    Elements( Line( X( 2 ), X( 1 ), Legend( 3 ) ) )
);

Code Explanation:

1. Open table.
2. Set row order levels.
3. Create Graph Builder.
4. Set size.
5. Hide control panel.
6. Define X variables.
7. Add line element.
8. Specify X positions.
9. Set legend position.
10. Display graph.

Example 15

Summary: Configures a Graph Builder object to create a side-by-side bar chart visualizing the mean profit by product line and quarter from the Profit by Product dataset.

Code:

dt = Open("data_table.jmp");
dt:age << Set Property( "Value Ordering", {15, 14, 12, 13, 16, 17} );
dt:sex << Set Property( "Value Ordering", {"M", "F"} );
Graph Builder(
    Size( 495, 464 ),
    Show Control Panel( 0 ),
    Variables( X( :sex ), X( :age, Position( 1 ) ) ),
    Elements( Points( X( 1 ), X( 2 ), Legend( 6 ) ) )
);

Code Explanation:

1. Open data table.
2. Set age value ordering.
3. Set sex value ordering.
4. Create Graph Builder object.
5. Set window size to 495x464.
6. Hide control panel.
7. Assign sex to X-axis.
8. Assign age to inner X-axis.
9. Add points element.
10. Configure points legend.

Example 16

Summary: Creates a side-by-side bar chart in Graph Builder to visualize the mean profit by product line and quarter from the Profit by Product dataset.

Code:

dt = Open("data_table.jmp");
dt:height << Set Property(
    "Value Order",
    {Custom Order( {51, 52, 55, 56, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70} ), Common Order( 0 )}
);
gb = dt << Graph Builder(
    Size( 553, 370 ),
    Show Control Panel( 0 ),
    Show Legend( 1 ),
    Variables( Y( :sex ), Color( :height ) ),
    Elements( Points( Y, Legend( 2 ) ) )
);

Code Explanation:

1. Open data table;
2. Set custom value order for height.
3. Create Graph Builder object.
4. Set graph size.
5. Hide control panel.
6. Show legend.
7. Assign variables to axes.
8. Add points element.
9. Color points by height.
10. Display graph.

Graph Builder using Subset

Example 1

Summary: Creates a bar graph with filtered data, showcasing height by name and sex 'F', using Graph Builder in JMP.

Code:

dt = Open("data_table.jmp");
dt << Subset( Rows( [1, 2, 3, 4, 5, 6, 7, 8] ), link to original table( 1 ) );
Graph Builder(
    Size( 282, 214 ),
    Show Control Panel( 0 ),
    Variables( X( :name ), Y( :height ) ),
    Elements( Bar( X, Y, Legend( 4 ), Label( "Label by Value" ) ) ),
    Local Data Filter( Mode( Include( 0 ) ), Add Filter( columns( :sex ), Where( :sex == "F" ), Display( :sex, Check Box Display ) ) )
);

Code Explanation:

1. Open data table;
2. Subset first 8 rows.
3. Create Graph Builder window.
4. Set window size.
5. Hide control panel.
6. Define X and Y variables.
7. Add bar element.
8. Enable label by value.
9. Add local data filter.
10. Filter by sex "F".

Example 2

Summary: Subsets data and graphing to visualize age distribution, utilizing Graph Builder with a bar element and custom legend.

Code:

dt = Open("data_table.jmp");
mySubset = dt << Subset( All rows, Selected columns only( 0 ), link to original data table( 1 ) );
mySubset << Graph Builder( Size( 449, 284 ), Show Control Panel( 0 ), Variables( X( :age ) ), Elements( Bar( X, Legend( 3 ) ) ) );

Code Explanation:

1. Open data table;
2. Create subset with all rows.
3. Include only selected columns.
4. Link subset to original data.
5. Open Graph Builder.
6. Set graph size to 449x284.
7. Hide control panel.
8. Set X variable to age.
9. Add bar element to graph.
10. Assign legend to third element.

Example 3

Summary: Subsets data and graphing to visualize the relationship between weight and height by sex, utilizing Graph Builder.

Code:

dt = Open("data_table.jmp");
dt << Subset(
    By( :sex ),
    All rows,
    Selected columns only( 0 ),
    columns( :name, :age, :height, :weight ),
    link to original data table( 1 )
);
Graph Builder( Size( 521, 414 ), Show Control Panel( 0 ), Variables( X( :weight ), Y( :height ) ), Elements( Area( X, Y, Legend( 6 ) ) ) );

Code Explanation:

1. Open data table.
2. Create subset by sex.
3. Include all rows.
4. Select specific columns.
5. Link subset to original.
6. Initialize Graph Builder.
7. Set graph size.
8. Hide control panel.
9. Define X and Y variables.
10. Add area element with legend.

Example 4

Summary: Creates a graph to visualize the relationship between Randomized and Completed variables, grouped by Mannitol Flag and Steroids Flag.

Code:

dt = Open("data_table.jmp");
dt << Subset(
    Rows(
        [1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35,
        36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50]
    ),
    link to original data table( 1 )
);
Graph Builder(
    Size( 403, 402 ),
    Show Control Panel( 0 ),
    Show Legend( 0 ),
    Variables( X( :Randomized ), Y( :Completed ), Group X( :Mannitol Flag ), Group Y( :Steroids Flag ) ),
    Elements( Area( X, Y, Legend( 12 ) ) )
);

Code Explanation:

1. Open data table;
2. Subset specific rows.
3. Link subset to original data.
4. Create Graph Builder object.
5. Set graph size.
6. Hide control panel.
7. Hide legend.
8. Define X and Y variables.
9. Define group X and Y variables.
10. Add area element to graph.

Example 5

Summary: Subsets data and visualization for a specific report, utilizing Graph Builder to create a stacked area graph with interactive features.

Code:

dt = Open("data_table.jmp");
dt << Subset(
    By( :Report ),
    All rows,
    Selected columns only( 0 ),
    columns( :Color, :Clarity, :Depth, :Table ),
    link to original data table( 1 )
);
Data Table("data_table") << Graph Builder(
    Size( 337, 316 ),
    Show Control Panel( 0 ),
    Variables( X( :Color ), X( :Clarity, Position( 1 ) ), Y( :Depth ), Y( :Table, Position( 1 ) ) ),
    Elements( Area( X( 1 ), X( 2 ), Y( 1 ), Y( 2 ), Legend( 4 ), Summary Statistic( "% of Total" ) ) )
);

Code Explanation:

1. Open data table;
2. Subset data by Report.
3. Select specific columns.
4. Link subset to original data.
5. Create new data table for Report=AGS.
6. Launch Graph Builder.
7. Set graph size.
8. Hide control panel.
9. Define X and Y variables.
10. Add stacked area element.

Example 6

Summary: Subsets data and visualization by creating a linked subset of the 'data_table' based on the 'Report' variable, and then generating an area plot with range style using Graph Builder.

Code:

dt = Open("data_table.jmp");
dt << Subset(
    Linked,
    Suppress formula evaluation( 0 ),
    By( :Report ),
    All rows,
    Selected columns only( 0 ),
    columns( :Clarity, :Depth, :Table )
);
dt2 = Data Table("data_table");
Graph Builder(
    Size( 371, 187 ),
    Show Control Panel( 0 ),
    Legend Position( "Bottom" ),
    Variables( X( :Clarity ), Y( :Depth ), Y( :Table, Position( 1 ) ) ),
    Elements( Area( X, Y( 1 ), Y( 2 ), Legend( 9 ), Area Style( "Range" ) ) )
);

Code Explanation:

1. Open data table;
2. Subset data by Report.
3. Create linked subset.
4. Suppress formula evaluation.
5. Select Clarity, Depth, Table columns.
6. Access Report=AGS data table.
7. Initiate Graph Builder.
8. Set graph size.
9. Hide control panel.
10. Add Clarity to X-axis.
11. Add Depth to Y-axis.
12. Add Table to Y-axis.
13. Create area plot with range style.

Example 7

Summary: Runs data visualization and subset creation by opening a data table, creating a subset by species, and launching Graph Builder to generate an area plot.

Code:

dt = Open("data_table.jmp");
dt << Subset(
    Linked,
    Suppress formula evaluation( 0 ),
    By( :Species ),
    All rows,
    Selected columns only( 0 ),
    columns( :Sepal width, :Sepal length, :Petal width, :Petal length )
);
dt2 = Data Table("data_table");
Graph Builder(
    Size( 525, 330 ),
    Show Control Panel( 0 ),
    Show Legend( 0 ),
    Variables( X( :Petal length ), Y( :Sepal length ), Group X( :Sepal width ), Overlay( :Petal width ) ),
    Elements( Area( X, Y, Legend( 17 ) ) )
);

Code Explanation:

1. Open data table;
2. Create subset by species.
3. Select versicolor subset.
4. Launch Graph Builder.
5. Set graph size.
6. Hide control panel.
7. Hide legend.
8. Define variables for plot.
9. Add area element to plot.
10. Display graph.

Example 8

Summary: Creates a graph to visualize the relationship between Cut and Depth/Table, utilizing Graph Builder with specified size and layout.

Code:

dt = Open("data_table.jmp");
dt << Subset(
    Linked,
    Suppress formula evaluation( 0 ),
    By( :Report ),
    All rows,
    Selected columns only( 0 ),
    columns( :Cut, :Depth, :Table )
);
dt2 = Data Table("data_table");
Graph Builder(
    Size( 414, 351 ),
    Show Control Panel( 0 ),
    Variables( X( :Cut ), Y( Transform Column( "Depth/Table", Formula( :Depth / :Table ) ) ) ),
    Elements( Area( X, Y, Legend( 9 ) ) )
);

Code Explanation:

1. Open data table;
2. Create linked subset.
3. Suppress formula evaluation.
4. Group by Report.
5. Select all rows.
6. Include selected columns only.
7. Specify Cut, Depth, Table.
8. Access Report=AGS table.
9. Initialize Graph Builder.
10. Set size to 414x351.
11. Hide control panel.
12. Set X variable to Cut.
13. Create Transform Column Depth/Table.
14. Define formula as Depth/Table.
15. Add Area element.
16. Link X, Y to elements.
17. Set legend position.

Example 9

Summary: Subsets data and visualization of Sepal width, Petal width, and Petal length by Species using Graph Builder in JMP.

Code:

dt = Open("data_table.jmp");
dt << Subset(
    Linked,
    Suppress formula evaluation( 0 ),
    By( :Species ),
    All rows,
    Selected columns only( 0 ),
    columns( :Sepal width, :Petal width, :Petal length )
);
dt2 = Data Table("data_table");
Graph Builder(
    Size( 359, 260 ),
    Show Control Panel( 0 ),
    Show Legend( 0 ),
    Variables( X( :Sepal width ), Y( :Petal width ), Overlay( :Petal length ) ),
    Elements( Area( X, Y, Legend( 8 ) ) )
);

Code Explanation:

1. Open data table;
2. Create subset linked by species.
3. Suppress formula evaluation.
4. Subset all rows by species.
5. Include selected columns only.
6. Select Sepal width, Petal width, Petal length.
7. Assign subset to dt2.
8. Initialize Graph Builder.
9. Set size to 359x260.
10. Add Area element with specified variables.

Example 10

Summary: Creates a data table subset and graph builder to analyze carat weight distribution by color, utilizing specified columns and report grouping.

Code:

dt = Open("data_table.jmp");
dt << Subset(
    Linked,
    Suppress formula evaluation( 0 ),
    By( :Report ),
    All rows,
    Selected columns only( 0 ),
    columns( :Carat Weight, :Color, :Clarity, :Depth, :Table, :Cut, :Price )
);
dt2 = Data Table("data_table");
dt2 << Graph Builder(
    Size( 609, 318 ),
    Show Control Panel( 0 ),
    Variables( X( :Color ), Y( :Carat Weight ), Color( :Carat Weight, Summary Statistic( "% of Total" ) ) ),
    Elements( Bar( X, Y, Legend( 2 ), Summary Statistic( "% of Total" ), Label( "Label by Value" ) ) )
);

Code Explanation:

1. Open data table;
2. Create subset linked to original.
3. Suppress formula evaluation.
4. Group by Report column.
5. Include all rows.
6. Select specified columns.
7. Access Report=AGS table.
8. Launch Graph Builder.
9. Set window size.
10. Hide control panel.
11. Set X variable to Color.
12. Set Y variable to Carat Weight.
13. Set Color variable to Carat Weight.
14. Use "% of Total" summary statistic.
15. Add Bar element.
16. Set legend position.
17. Use "% of Total" summary statistic.
18. Label bars by value.

Example 11

Summary: Explores data by creating a linked subset of a data table and generating a bar graph with age as the wrap variable, utilizing Graph Builder.

Code:

dt = Open("data_table.jmp");
dt << Subset(
    Linked,
    Suppress formula evaluation( 0 ),
    By( :sex ),
    All rows,
    Selected columns only( 0 ),
    columns( :weight, :height, :age )
);
dt2 = Data Table("data_table");
Graph Builder(
    Size( 620, 502 ),
    Show Control Panel( 0 ),
    Variables( X( :weight ), Y( :height ), Wrap( :age ) ),
    Elements( Bar( X, Y, Legend( 5 ), Label( "Label by Value" ) ) )
);

Code Explanation:

1. Open data table;
2. Create linked subset by sex.
3. Filter subset for sex=M.
4. Initialize Graph Builder.
5. Set graph size.
6. Hide control panel.
7. Define X, Y, and wrap variables.
8. Add bar element.
9. Configure label by value.
10. Display graph.

Example 12

Summary: Analyze and visualize petal width and length data for different species, using Graph Builder to create a bar chart with overlay.

Code:

Open("data_table.jmp");
Subset( By( :Species ), All rows, Selected columns only( 0 ), columns( :Petal width, :Petal length ), link to original data table( 1 ) );
Data Table("data_table") << Graph Builder(
    Size( 385, 238 ),
    Show Control Panel( 0 ),
    Show Legend( 0 ),
    Variables( Y( :Petal width ), Overlay( :Petal length ) ),
    Elements( Bar( Y, Legend( 16 ) ) )
);

Code Explanation:

1. Open data table;
2. Subset data by species.
3. Select petal width and length.
4. Link subset to original table.
5. Create Graph Builder for data_table.
6. Set graph size.
7. Hide control panel.
8. Hide legend.
9. Add petal width to Y axis.
10. Overlay petal length.

Example 13

Summary: Creates a subset table and generates a graph to visualize weight vs. height data by sex, using Graph Builder in JMP.

Code:

dt = Open("data_table.jmp");
dt << Subset(
    By( :sex ),
    All rows,
    Selected columns only( 0 ),
    columns( :name, :age, :height, :weight ),
    link to original data table( 1 )
);
mySubset = Data Table("data_table");
mySubset << Graph Builder(
    Size( 1144, 362 ),
    Show Control Panel( 0 ),
    Variables( X( :weight ), Y( :height ) ),
    Elements( Bar( X, Y, Legend( 4 ), Label( "Label by Row" ) ) ),
    SendToReport(
        Dispatch( {}, "Graph Builder", FrameBox,
            {Add Pin Annotation(
                Seg( BarSeg( 1 ) ),
                Index( {0, 0} ),
                Index Row( {2, 2} ),
                UniqueID( 860344256 ),
                FoundPt( {154, 184} ),
                Origin( {79.0659340659341, 45.4421768707483} ),
                Offset( {-131, 130} )
            ), Add Pin Annotation(
                Seg( BarSeg( 1 ) ),
                Index( {15, 15} ),
                Index Row( {20, 20} ),
                UniqueID( 860344271 ),
                FoundPt( {699, 190} ),
                Origin( {133.965201465201, 43.8095238095238} ),
                Offset( {-34, -33} )
            ), Add Pin Annotation(
                Seg( BarSeg( 1 ) ),
                Index( {1, 1} ),
                Index Row( {0, 0} ),
                UniqueID( 860344257 ),
                FoundPt( {201, 194} ),
                Origin( {83.8003663003663, 42.7210884353742} ),
                Offset( {-52, -10} )
            )}
        )
    )
);

Code Explanation:

1. Open data table;
2. Subset data by sex.
3. Select specific columns.
4. Create subset table.
5. Assign subset table.
6. Launch Graph Builder.
7. Set graph size.
8. Hide control panel.
9. Define variables.
10. Add bar element with row labels.

Example 14

Summary: Creates and customizes a Graph Builder report, featuring points and box plots for visualizing data relationships.

Code:

dt = Open("data_table.jmp");
dt2 = dt << Subset( All rows, output table name( "test_class" ) );
ht2 = dt2 << New Column( "height2", numeric, continuous );
ht2 << set each value( :height + Random Integer( -5, 5 ) );
gb = dt2 << Graph Builder(
    Show Control Panel( 0 ),
    Continuous Color Theme( "Green Yellow Red" ),
    Variables( X( :sex ), Y( :height ), Y( :height2 ), Color( :weight ) ),
    Elements(
        Position( 1, 1 ),
        Points( X, Y, Color, Legend( 1 ), Jitter( 1 ) ),
        Box Plot( X, Y, Color, Legend( 1 ), Jitter( 1 ), Outliers( 0 ), Box Style( "Outlier" ) )
    ),
    Elements(
        Position( 1, 2 ),
        Points( X, Y, Color, Legend( 1 ), Jitter( 1 ) ),
        Box Plot( X, Y, Color, Legend( 1 ), Jitter( 1 ), Outliers( 0 ), Box Style( "Outlier" ) )
    )
);
rgb = Report( gb );

Code Explanation:

1. Open data table.
2. Create subset of all rows.
3. Rename subset table.
4. Add new column "height2".
5. Populate "height2" with random values.
6. Initialize Graph Builder.
7. Hide control panel.
8. Set color theme.
9. Define variables for graph.
10. Add points and box plots to graph.

Example 15

Summary: Creates a graph with box plots and points to visualize height data, utilizing Graph Builder and customizing legend and title.

Code:

dt = Open("data_table.jmp");
dt2 = dt << Subset( All rows, output table name( "test_class" ) );
ht2 = dt2 << New Column( "height2", numeric, continuous );
ht2 << set each value( :height + Random Integer( -5, 5 ) );
gb = dt2 << Graph Builder(
    Size( 525, 446 ),
    Show Control Panel( 0 ),
    Variables( X( :sex ), Y( :height ), Y( :height2 ), Color( :weight ) ),
    Elements( Position( 1, 1 ), Points( X, Y, Legend( 10 ) ), Box Plot( X, Y, Legend( 12 ), Box Style( "Solid" ) ) ),
    Elements( Position( 1, 2 ), Points( X, Y, Legend( 11 ) ), Box Plot( X, Y, Legend( 13 ) ) ),
    SendToReport(
        Dispatch( {}, "400", ScaleBox,
            {Legend Model( 10, Properties( 0, {gradient( {Color Theme( "White to Black" ), Width( 12 )} )} ) ),
            Legend Model( 12, Properties( 0, {Line Color( 0 ), Line Width( 2 )} ) ), Legend Model(
                11,
                Base( 0, 0, 0 ),
                Properties( 0, {gradient( {Color Theme( "Green Yellow Red" ), Width( 12 )} )} )
            ), Legend Model( 13, Properties( 0, {Line Width( 2 )} ) )}
        ),
        Dispatch( {}, "graph title", TextEditBox, {Set Text( "Using the UI" )} ),
        Dispatch( {}, "400", LegendBox, {Legend Position( {10, [0, 4], 12, [1], 11, [2, 5], 13, [3]} )} )
    )
);

Code Explanation:

1. Open data table.
2. Create subset of all rows.
3. Rename subset table.
4. Add new column "height2".
5. Populate "height2" with modified height values.
6. Initialize Graph Builder.
7. Set graph size and hide control panel.
8. Define variables for graph elements.
9. Add points and box plots for "height" and "height2".
10. Customize legend and title.

Example 16

Summary: Subsets data and visualization by sex, utilizing the Graph Builder platform to generate a heatmap of height against name.

Code:

dt = Open("data_table.jmp");
dt << Subset(
    By( :sex ),
    All rows,
    Selected columns only( 0 ),
    columns( :name, :age, :height, :weight ),
    link to original data table( 1 )
);
mySubset = Data Table("data_table");
mySubset << Graph Builder(
    Size( 327, 264 ),
    Show Control Panel( 0 ),
    Variables( X( :name ), Y( :height ) ),
    Elements( Heatmap( X, Y, Legend( 4 ) ) )
);

Code Explanation:

1. Open data table.
2. Subset data by sex.
3. Select specific columns.
4. Link subset to original data.
5. Create new subset table.
6. Launch Graph Builder.
7. Set graph size.
8. Hide control panel.
9. Define X and Y variables.
10. Add heatmap element.

Example 17

Summary: Subsets data and graphing for a specific report, utilizing Graph Builder to visualize categorical X and multiple Y line elements.

Code:

dt = Open("data_table.jmp");
dt << Subset(
    By( :Report ),
    All rows,
    Selected columns only( 0 ),
    columns( :Color, :Clarity, :Depth, :Table ),
    link to original data table( 1 )
);
Data Table("data_table") << Graph Builder(
    Size( 337, 316 ),
    Show Control Panel( 0 ),
    Variables( X( :Color ), X( :Clarity, Position( 1 ) ), Y( :Depth ), Y( :Table, Position( 1 ) ) ),
    Elements( Line( X( 1 ), X( 2 ), Y( 1 ), Y( 2 ), Legend( 5 ), Summary Statistic( "% of Total" ), Stack( 1 ) ) )
);

Code Explanation:

1. Open data table;
2. Subset data by Report.
3. Select specific columns.
4. Link to original data table.
5. Create new data table for Report=AGS.
6. Initialize Graph Builder.
7. Set graph size.
8. Hide control panel.
9. Define X and Y variables.
10. Add stacked categorical X and multiple Y line elements.

Example 18

Summary: Process of subseting a data table by sex, selecting all rows for males, and generating a graph using Graph Builder to visualize weight vs. height.

Code:

dt = Open("data_table.jmp");
dt << Subset(
    By( :sex ),
    All rows,
    Selected columns only( 0 ),
    columns( :name, :age, :height, :weight ),
    link to original data table( 1 )
);
mySubset = Data Table("data_table");
mySubset << select all rows;
mySubset << Graph Builder(
    Size( 521, 414 ),
    Show Control Panel( 0 ),
    Variables( X( :weight ), Y( :height ) ),
    Elements( Points( X, Y, Legend( 6 ) ) ),
    SendToReport(
        Dispatch( {}, "Graph Builder", FrameBox,
            Add Pin Annotation(
                Seg( Marker Seg( 1 ) ),
                Index( 21 ),
                Index Row( 21 ),
                UniqueID( 579895397 ),
                FoundPt( {767, 161} ),
                Origin( {171.698113207547, 70.0710227272727} )
            )
        )
    )
);

Code Explanation:

1. Open data table;
2. Subset data by sex.
3. Select subset for males.
4. Create new data table for males.
5. Select all rows in new table.
6. Launch Graph Builder.
7. Set graph size.
8. Hide control panel.
9. Add weight to X-axis.
10. Add height to Y-axis.

Example 19

Summary: Subsets data and graphing for male and female populations, utilizing Graph Builder to visualize height against weight.

Code:

dt = Open("data_table.jmp");
dt << Subset(
    By( :sex ),
    All rows,
    Selected columns only( 0 ),
    columns( :name, :age, :height, :weight ),
    link to original data table( 1 )
);
mySubset = Data Table("data_table");
mySubset << Graph Builder(
    Size( 521, 414 ),
    Show Control Panel( 0 ),
    Variables( X( :weight ), Y( :height ) ),
    Elements( Points( X, Y, Legend( 6 ) ) ),
    SendToReport(
        Dispatch( {}, "Graph Builder", FrameBox,
            {Add Pin Annotation(
                Seg( Marker Seg( 1 ) ),
                Index( 20 ),
                Index Row( 20 ),
                UniqueID( 707371204 ),
                FoundPt( {336, 125} ),
                Origin( {134.282700421941, 68.0780346820809} )
            ), Add Pin Annotation(
                Seg( Marker Seg( 1 ) ),
                Index( 0 ),
                Index Row( 0 ),
                UniqueID( 707371184 ),
                FoundPt( {121, 250} ),
                Origin( {84.3881856540084, 59.9494219653179} )
            )}
        )
    )
);

Code Explanation:

1. Open data table;
2. Subset data by sex.
3. Select specific columns.
4. Link to original table.
5. Create subset for male data.
6. Launch Graph Builder.
7. Set graph size.
8. Hide control panel.
9. Assign weight to X-axis.
10. Assign height to Y-axis.
11. Add points element.
12. Add pin annotations at specified positions.

Graph Builder using Select Rows

Example 1

Summary: Explores data by opening a data table, selecting the first 10 rows, excluding them, and generating a graph using Graph Builder with two variables: Survived and Passenger Class.

Code:

dt = Open("data_table.jmp");
r = dt << Select Rows( [1, 2, 3, 4, 5, 6, 7, 8, 9, 10] );
r << Exclude;
Graph Builder( Variables( X( :Survived ), X( :Passenger Class, Position( 1 ) ) ), Elements( Bar( X( 2 ), X( 1 ), Legend( 4 ) ) ) );

Code Explanation:

1. Open data table;
2. Select first 10 rows.
3. Exclude selected rows.
4. Create Graph Builder.
5. Set X variable: Survived.
6. Set second X variable: Passenger Class.
7. Position Passenger Class first.
8. Add Bar element.
9. Set Bar X1: Passenger Class.
10. Set Bar X2: Survived.

Example 2

Summary: Creates a graph with a bar chart to visualize the relationship between weight and square root of height, using Graph Builder.

Code:

dt = Open("data_table.jmp");
dt << Select Rows( Index( 1, 20 ) );
dt2 = dt << Subset( Selected rows, link to original data table( 1 ) );
dt2 << Graph Builder(
    Size( 527, 454 ),
    Show Control Panel( 0 ),
    Variables( X( :weight ), Y( Transform Column( "Square Root[height]", Format( "Fixed Dec", 5, 0 ), Formula( Sqrt( :height ) ) ) ) ),
    Elements( Bar( X, Y, Legend( 8 ) ) )
);

Code Explanation:

1. Open data table;
2. Select first 20 rows.
3. Create subset linked to original.
4. Launch Graph Builder.
5. Set window size.
6. Hide control panel.
7. Set X variable to weight.
8. Create transformed Y column: square root of height.
9. Add bar element.
10. Display graph.

Example 3

Summary: Creates a heatmap visualization using Graph Builder to display the relationship between 'Randomized', 'Completed', and categorical variables 'Mannitol Flag' and 'Steroids Flag'.

Code:

dt = Open("data_table.jmp");
dt << Clear Row States;
dt << Select Rows(
    [1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36,
    37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50]
);
mySubset = subset( linked, dt );
mySubset << Clear Row States;
mySubset << Graph Builder(
    Size( 403, 402 ),
    Show Control Panel( 0 ),
    Show Legend( 0 ),
    Include Missing Categories( 1 ),
    Variables( X( :Randomized ), Y( :Completed ), Group X( :Mannitol Flag ), Group Y( :Steroids Flag ) ),
    Elements( Heatmap( X, Y, Legend( 16 ) ) ),
    SendToReport(
        Dispatch( {}, "Completed", ScaleBox,
            {Scale( "Linear" ), Format( "Best", 10 ), Min( 0.001 ), Max( 1.2 ), Inc( 1 ), Minor Ticks( 1 )}
        ),
        Dispatch( {}, "400", ScaleBox, {Legend Model( 16, Properties( 0, {gradient} ) )} )
    )
);

Code Explanation:

1. Open data table;
2. Clear row states.
3. Select specific rows.
4. Create subset of selected rows.
5. Clear row states in subset.
6. Launch Graph Builder.
7. Set graph size.
8. Hide control panel.
9. Hide legend.
10. Configure heatmap elements and scales.

Example 4

Summary: Vizualizes a subset of data rows using Graph Builder, configuring window size, hiding control panel, and customizing legend properties.

Code:

dt = Open("data_table.jmp");
dt << Select Rows( {30, 62, 140} );
Graph Builder(
    Size( 414, 305 ),
    Show Control Panel( 0 ),
    Variables( X( :Sepal length ), X( :Sepal width, Position( 1 ) ), X( :Petal length, Position( 1 ) ), X( :Petal width, Position( 1 ) ) ),
    Elements( Parallel( X( 1 ), X( 2 ), X( 3 ), X( 4 ), Legend( 3 ) ) ),
    SendToReport( Dispatch( {}, "400", ScaleBox, {Legend Model( 3, Properties( 0, {Line Style( "Dotted" ), Line Width( 3 )} ) )} ) )
);

Code Explanation:

1. Open data table;
2. Select specific rows.
3. Initiate Graph Builder.
4. Set window size.
5. Hide control panel.
6. Define X variables.
7. Add parallel plot element.
8. Customize legend properties.
9. Set line style to dotted.
10. Adjust line width to 3.

Example 5

Summary: Vizualizes a subset of data from a JMP data table, using Graph Builder to create a parallel plot with customized Y title wrapping.

Code:

dt = Open("data_table.jmp");
dt << Select Rows( {30, 62, 140} );
Graph Builder(
    Size( 414, 305 ),
    Show Control Panel( 0 ),
    Variables( X( :Sepal length ), X( :Sepal width, Position( 1 ) ), X( :Petal length, Position( 1 ) ), X( :Petal width, Position( 1 ) ) ),
    Elements( Parallel( X( 1 ), X( 2 ), X( 3 ), X( 4 ), Legend( 3 ) ) ),
    SendToReport( Dispatch( {}, "Y title", TextEditBox, {Set Wrap( 2 )} ) )
);

Code Explanation:

1. Open data table;
2. Select specific rows.
3. Initiate Graph Builder.
4. Set window size.
5. Hide control panel.
6. Define X variables.
7. Add parallel plot element.
8. Position X variables.
9. Customize Y title wrapping.
10. Display graph.

Example 6

Summary: Creates a treemap visualization to display ozone levels by city, filtered for the 'MW' region, using Graph Builder and Local Data Filter in JMP.

Code:

dt = Open("data_table.jmp");
dt << Select Rows( [40] );
Graph Builder(
    Show Control Panel( 0 ),
    Variables( X( :city ), Color( :OZONE ), Size( :POP ) ),
    Elements( Treemap( X, Legend( 4 ) ) ),
    Local Data Filter(
        Mode( Include( 0 ) ),
        Add Filter( columns( :Region ), Where( :Region == "MW" ), Display( :Region, Size( 160, 90 ), List Display ) )
    )
);

Code Explanation:

1. Open data table.
2. Select row 40.
3. Launch Graph Builder.
4. Hide control panel.
5. Set X variable.
6. Set color variable.
7. Set size variable.
8. Add Treemap element.
9. Enable local data filter.
10. Filter Region column for "MW".

Example 7

Summary: Creates a Treemap visualization in JMP, displaying height and weight data for specific rows of a data table.

Code:

dt = Open("data_table.jmp");
dt << Select Rows( [5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20] );
dt << Data View;
Graph Builder(
    Size( 589, 460 ),
    Show Control Panel( 0 ),
    Show Legend( 1 ),
    Variables( X( :name ), X( :age, Position( 1 ) ), X( :sex, Position( 1 ) ), Y( :height ), Y( :weight, Position( 1 ) ) ),
    Elements(
        Treemap(
            X( 1 ),
            X( 2 ),
            X( 3 ),
            Y( 1 ),
            Y( 2 ),
            Legend( 4 ),
            Summary Statistic( "% of Total" ),
            Group Labels( "None" ),
            Category Value( 0 ),
            Size Value( 1 ),
            Label Justification( "Right" )
        )
    )
);

Code Explanation:

1. Open data table.
2. Select specific rows.
3. Switch to Data View.
4. Create Graph Builder window.
5. Set window size.
6. Hide control panel.
7. Show legend.
8. Define variables for axes.
9. Add Treemap element.
10. Configure Treemap settings.

Graph Builder using Column

Example 1

Summary: Vizualizes height by sex data with a bar chart, utilizing Graph Builder and Local Data Filter for interactive filtering by age.

Code:

dt = Open("data_table.jmp");
Column( dt, "age" ) << set property( "Value Ordering", {17, 16, 15, 14, 13, 12} );
Graph Builder(
    Size( 500, 404 ),
    Show Control Panel( 0 ),
    Show Legend( 1 ),
    Variables( X( :sex ), Y( :height ) ),
    Elements( Bar( X, Y, Legend( 7 ) ) ),
    Local Data Filter( Add Filter( columns( :age ), Display( :age, Size( 160, 90 ), List Display ) ) )
);

Code Explanation:

1. Open data table;
2. Set value ordering for "age".
3. Create Graph Builder.
4. Set graph size.
5. Hide control panel.
6. Show legend.
7. Set X variable to "sex".
8. Set Y variable to "height".
9. Add bar element.
10. Add local data filter for "age".

Example 2

Summary: Configures a graph to visualize the relationship between sex and height, filtered by age, using Graph Builder in JMP.

Code:

dt = Open("data_table.jmp");
Column( dt, "age" ) << set property( "Value Ordering", {17, 16, 15, 14, 13, 12} );
Graph Builder(
    Size( 500, 404 ),
    Show Control Panel( 0 ),
    Show Legend( 1 ),
    Variables( X( :sex ), Y( :height ) ),
    Elements( Bar( X, Y, Legend( 7 ) ) ),
    Local Data Filter( Add Filter( columns( :age ), Where( :age == 17 ), Display( :age, Size( 160, 90 ), List Display ) ) )
);

Code Explanation:

1. Open table.
2. Set value ordering for age.
3. Create Graph Builder.
4. Set size to 500x404.
5. Hide control panel.
6. Show legend.
7. Set X to sex.
8. Set Y to height.
9. Add bar element.
10. Add local data filter for age.

Example 3

Summary: Configures a graph builder with a bar element to visualize the relationship between 'Cut' and 'Price', while excluding the 'Clarity' column.

Code:

Open("data_table.jmp");
c1 = Column( "Cut" );
c1 << Set Property( "Next in Hierarchy", "Clarity" );
Column( "Clarity" ) << exclude;
Graph Builder(
    Show Control Panel( 0 ),
    Variables( X( :Cut ), Y( :Price ) ),
    Elements( Bar( X, Y, Legend( 4 ) ) ),
    SendToReport(
        Dispatch( {}, "Graph Builder", FrameBox,
            {Set Graphlet(
                Picture(
                    Try(
                        loader = If( Class Exists( "hllLoader" ),
                            New Object( "hllLoader" ),
                            Include( "$BUILTIN_SCRIPTS/hllib.jsl" )
                        );
                        loader:setDebug( 0 );
                        hlp = loader:lazyLoad( "hllPresets" );
                        hlp:launchLine();
                    )
                ),
                Title( "Line Preset" ),
                Reapply( 1 )
            ), Add Pin Annotation(
                Seg( BarSeg( 1 ) ),
                Index( {0, 0} ),
                Index Row( {593, 593} ),
                UniqueID( 657914000 ),
                FoundPt( {404, 351} ),
                Origin( {0.0299145299145299, 1989.70473513514} ),
                Tag Line( 1 )
            )}
        )
    )
);

Code Explanation:

1. Open data table;
2. Set "Cut" column property.
3. Exclude "Clarity" column.
4. Launch Graph Builder.
5. Configure X and Y variables.
6. Add Bar element.
7. Send report settings.
8. Set graphlet picture.
9. Launch line preset.
10. Add pin annotation.

Example 4

Summary: Configures two Graph Builders to visualize the relationship between 'Date' and 'Close' variables, with customized date format and pin annotation.

Code:

dt = Open("data_table.jmp");
Column( dt, "Date" ) << Set Property( "Axis", Format( "ddMonyyyy", 10 ) );
Graph Builder(
    Size( 528, 454 ),
    Show Control Panel( 0 ),
    Variables( X( :Date ), Y( :Close ) ),
    Elements( Points( X, Y, Legend( 1 ) ) ),
    SendToReport(
        Dispatch( {}, "Graph Builder", FrameBox,
            Add Pin Annotation(
                Seg( Marker Seg( 1 ) ),
                Index( 17 ),
                Index Row( 17 ),
                UniqueID( 833431041 ),
                FoundPt( {437, 353} ),
                Origin( {3060174823.1405, 36.530612244898} )
            )
        )
    )
);
Graph Builder(
    Size( 534, 464 ),
    Show Control Panel( 0 ),
    Variables( X( :Date ), Y( :Close ) ),
    Elements( Points( X, Y, Legend( 1 ) ) ),
    SendToReport(
        Dispatch( {}, "Date", ScaleBox, {Format( "ddMonyyyy", 10 )} ),
        Dispatch( {}, "Graph Builder", FrameBox,
            Add Pin Annotation(
                Seg( Marker Seg( 1 ) ),
                Index( 17 ),
                Index Row( 17 ),
                UniqueID( 833431041 ),
                FoundPt( {437, 353} ),
                Origin( {3060174823.1405, 36.530612244898} )
            )
        )
    )
);

Code Explanation:

1. Open data table;
2. Set date column format.
3. Create first Graph Builder.
4. Set graph size.
5. Hide control panel.
6. Define X and Y variables.
7. Add points element.
8. Add pin annotation.
9. Create second Graph Builder.
10. Set graph size.
11. Hide control panel.
12. Define X and Y variables.
13. Add points element.
14. Set date axis format.
15. Add pin annotation.

Example 5

Summary: Formats a 'Date' column and generates a graph with points to visualize the relationship between 'Date' and 'Close', utilizing Graph Builder.

Code:

dt = Open("data_table.jmp");
Column( dt, "Date" ) << Format( "ddMonyyyy", 10 );
Graph Builder(
    Size( 528, 454 ),
    Show Control Panel( 0 ),
    Variables( X( :Date ), Y( :Close ) ),
    Elements( Points( X, Y, Legend( 1 ) ) ),
    SendToReport(
        Dispatch( {}, "Graph Builder", FrameBox,
            Add Pin Annotation(
                Seg( Marker Seg( 1 ) ),
                Index( 5 ),
                Index Row( 5 ),
                UniqueID( 833431029 ),
                FoundPt( {101, 193} ),
                Origin( {3058718340.49587, 45.7142857142857} )
            )
        )
    )
);

Code Explanation:

1. Open data table.
2. Format Date column.
3. Create Graph Builder.
4. Set graph size.
5. Hide control panel.
6. Assign variables X and Y.
7. Add points element.
8. Send report to Graph Builder.
9. Add pin annotation.
10. Configure annotation properties.

Example 6

Summary: Creates a graph builder with multivariate correlations analysis using mahalanobis distances, featuring interactive elements and custom annotations.

Code:

Open("data_table.jmp");
Column( "Reason" ) << label( 1 );
Graph Builder(
    Size( 406, 307 ),
    Show Control Panel( 0 ),
    Include Missing Categories( 1 ),
    Variables( X( :Day ), Y( :Delay ), Color( :Reason ) ),
    Elements( Points( X, Y, Legend( 7 ) ) ),
    SendToReport(
        Dispatch( {}, "Graph Builder", FrameBox,
            {Add Pin Annotation(
                Seg( Marker Seg( 1 ) ),
                Index( 7 ),
                Index Row( 7 ),
                UniqueID( 708163063 ),
                FoundPt( {76, 192} ),
                Origin( {-0.0378151260504201, 22.2897196261682} ),
                Offset( {-10, -32} ),
                Tag Line
            ), Add Pin Annotation(
                Seg( Marker Seg( 1 ) ),
                Index( 221 ),
                Index Row( 221 ),
                UniqueID( 708163277 ),
                FoundPt( {336, 58} ),
                Origin( {7.9733893557423, 72.3831775700935} ),
                Offset( {-164, 23} ),
                Tag Line
            ), Add Pin Annotation(
                Seg( Marker Seg( 1 ) ),
                Index( 207 ),
                Index Row( 207 ),
                UniqueID( 708163263 ),
                FoundPt( {338, 132} ),
                Origin( {8.03501400560224, 44.7196261682243} ),
                Offset( {-130, 70} ),
                Tag Line
            )}
        )
    )
);

Code Explanation:

1. Open data table.
2. Label "Reason" column.
3. Create Graph Builder.
4. Set graph size.
5. Hide control panel.
6. Include missing categories.
7. Define X, Y, and Color variables.
8. Add points element.
9. Send report to Graph Builder.
10. Add pin annotations.

Example 7

Summary: Creates a bar graph to visualize the relationship between height and weight, with interactive features like pin annotations.

Code:

Open("data_table.jmp");
col = Column( 5 );
col << Label( 1 );
Graph Builder(
    Size( 551, 367 ),
    Show Control Panel( 0 ),
    Variables( X( :height ), Y( :weight ) ),
    Elements( Bar( X, Y, Legend( 6 ) ) ),
    SendToReport(
        Dispatch( {}, "Graph Builder", OutlineBox, {Set Title( "Graph Builder: tooltip shows individual value for weight" )} ),
        Dispatch( {}, "Graph Builder", FrameBox,
            Add Pin Annotation(
                Seg( BarSeg( 1 ) ),
                Index( {5, 5} ),
                Index Row( {0, 0} ),
                UniqueID( 652555237 ),
                FoundPt( {264, 229} ),
                Origin( {59.045, 83.495145631068} ),
                Offset( {-53, -111} ),
                Tag Line
            )
        )
    )
);

Code Explanation:

1. Open data table;
2. Select column 5.
3. Enable column labels.
4. Create Graph Builder.
5. Set graph size.
6. Hide control panel.
7. Define X and Y variables.
8. Add bar element.
9. Set graph title.
10. Add pin annotation.

Example 8

Summary: Configures a graph to visualize the relationship between date and close values, utilizing Graph Builder with custom formatting for the date axis.

Code:

dt = Open("data_table.jmp");
Column( dt, "Date" ) << Set Property( "Axis", Format( "ddMonyyyy", 10 ) );
Graph Builder(
    Size( 1183, 462 ),
    Show Control Panel( 0 ),
    Variables( X( :Date ), Y( :Close ) ),
    Elements( Bar( X, Y, Legend( 2 ) ) ),
    SendToReport(
        Dispatch( {}, "Graph Builder", FrameBox,
            {Add Pin Annotation(
                Seg( BarSeg( 1 ) ),
                Index( {10, 10} ),
                Index Row( {10, 10} ),
                UniqueID( -1379573894 ),
                FoundPt( {248, 169} ),
                Origin( {3059299612.33567, 42.5125628140704} ),
                RightOfCenter( 0 ),
                Tag Line( 1 )
            ), Add Pin Annotation(
                Seg( BarSeg( 1 ) ),
                Index( {41, 41} ),
                Index Row( {41, 41} ),
                UniqueID( -1379573863 ),
                FoundPt( {795, 251} ),
                Origin( {3063314019.14917, 30.1507537688442} ),
                RightOfCenter( 1 ),
                Tag Line( 1 )
            ), Add Pin Annotation(
                Seg( BarSeg( 1 ) ),
                Index( {60, 60} ),
                Index Row( {60, 60} ),
                UniqueID( -1379573844 ),
                FoundPt( {1126, 272} ),
                Origin( {3065743212.30323, 26.9849246231156} ),
                RightOfCenter( 1 ),
                Tag Line( 1 )
            )}
        )
    )
);

Code Explanation:

1. Open data table.
2. Set date column format.
3. Create Graph Builder.
4. Set graph size.
5. Hide control panel.
6. Define X and Y variables.
7. Add bar element.
8. Add pin annotation.
9. Add second pin annotation.
10. Add third pin annotation.

Example 9

Summary: Creates a graph builder window to visualize the relationship between sex and height, with custom value ordering for the height column.

Code:

dt = Open("data_table.jmp");

Column( dt, "height" ) << Set Property( "Value Ordering", {51, 52, 55, 56, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70} );

Graph Builder( Size( 558, 398 ), Show Control Panel( 0 ), Variables( X( :sex ), Y( :height ) ), Elements( Area( X, Y, Legend( 9 ) ) ) );

Code Explanation:

1. Open data table.
2. Set value ordering for height.
3. Create Graph Builder window.
4. Hide control panel.
5. Set X variable to sex.
6. Set Y variable to height.
7. Add area element to graph.
8. Set legend position.

Example 10

Summary: Creates a Graph Builder window to visualize relationships between Date and Gap variables, with an overlay of transformed Date by week.

Code:

dt = Open("data_table.jmp");
Column( dt, "Date" ) << set modeling type( "Nominal" );
Graph Builder(
    Size( 517, 473 ),
    Show Control Panel( 0 ),
    Variables(
        X( :Date ),
        Y( :Gap ),
        Y( :Gap ),
        Overlay( Transform Column( "Transform[Date]", Ordinal, Formula( Week Of Year( :Date ) ) ) )
    ),
    Elements( Position( 1, 1 ), Area( X, Y, Legend( 4 ), Area Style( "Range" ), Missing Factors( "Treat as Zero" ) ) ),
    Elements( Position( 1, 2 ), Line( X, Y, Legend( 7 ) ) )
);

Code Explanation:

1. Open data table.
2. Set Date column as Nominal.
3. Create Graph Builder window.
4. Set window size.
5. Hide control panel.
6. Define X variable as Date.
7. Define Y variables as Gap.
8. Overlay transformed Date by week.
9. Add area element for range.
10. Add line element.

Example 11

Summary: Creates a bar chart to visualize the distribution of 'Grade' and 'Goals' across different 'Gender' groups, utilizing Graph Builder.

Code:

Open("data_table.jmp");
Column( "Grade" ) << modeling type( "Nominal" );
Graph Builder(
    Size( 576, 500 ),
    Show Control Panel( 0 ),
    Variables( X( :Grade ), X( :Goals, Position( 1 ) ), Group Y( :Gender ), Overlay( :Goals ) ),
    Elements( Bar( X( 1 ), X( 2 ), Legend( 2 ), Summary Statistic( "% of Total" ), Label( "Label by Value" ) ) )
);

Code Explanation:

1. Open data table.
2. Set "Grade" column to nominal.
3. Launch Graph Builder.
4. Set window size.
5. Hide control panel.
6. Define X variables: "Grade", "Goals".
7. Set "Goals" as first position.
8. Define Group Y variable: "Gender".
9. Define Overlay variable: "Goals".
10. Add bar element with summary statistic "% of Total".

Example 12

Summary: Creates a bar graph to visualize height values by sex, with custom value order and labeling.

Code:

dt = Open("data_table.jmp");
Column( dt, "height" ) << Set Property( "Value Order", {51, 52, 55, 56, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70} );
Graph Builder(
    Size( 555, 398 ),
    Show Control Panel( 0 ),
    Variables( X( :sex ), Y( :Name( "height" ) ) ),
    Elements( Bar( X, Y, Legend( 4 ), Label( "Label by Value" ) ) )
);

Code Explanation:

1. Open data table.
2. Set value order for height column.
3. Create Graph Builder object.
4. Set graph size to 555x398.
5. Hide control panel.
6. Define X variable as sex.
7. Define Y variable as height.
8. Add bar element to graph.
9. Set legend position to 4.
10. Label bars by value.

Example 13

Summary: Vizualizes gap data by week, using Graph Builder to create a bar chart with summary statistics.

Code:

dt = Open("data_table.jmp");
Column( dt, "Date" ) << set modeling type( "Nominal" );
Graph Builder(
    Size( 480, 416 ),
    Show Control Panel( 0 ),
    Variables(
        X( Transform Column( "Transform[Date]", Ordinal, Formula( Week Of Year( :Date ) ) ) ),
        X( :Date, Position( 1 ) ),
        Y( :Gap ),
        Overlay( Transform Column( "Transform[Date]", Ordinal, Formula( Week Of Year( :Date ) ) ) )
    ),
    Elements( Bar( X( 2 ), X( 1 ), Y, Legend( 9 ), Summary Statistic( "% of Total" ), Label( "Label by Value" ) ) )
);

Code Explanation:

1. Open data table;
2. Set "Date" column as nominal.
3. Create Graph Builder window.
4. Hide control panel.
5. Define X variables: transformed week of year, date.
6. Define Y variable: Gap.
7. Set overlay by transformed week of year.
8. Add bar element.
9. Configure bar for two X variables.
10. Display summary statistic as percentage of total.

Example 14

Summary: Vizualizes multivariate correlations between 'height' and 'age', utilizing Graph Builder to generate a bar chart with color-coded by 'age'.

Code:

dt = Open("data_table.jmp");
Column( dt, "age" ) << modeling type( "Continuous" );
Graph Builder(
    Size( 417, 292 ),
    Show Control Panel( 0 ),
    Variables( Y( :height ), Group X( :age ), Color( :age ) ),
    Elements( Bar( Y, Legend( 4 ) ) )
);

Code Explanation:

1. Open data table;
2. Set "age" column as continuous.
3. Create Graph Builder.
4. Set window size 417x292.
5. Hide control panel.
6. Assign variables: Y=height, X=age, Color=age.
7. Add bar element.
8. Enable legend for bars.

Example 15

Summary: Creates a bar graph to visualize the relationship between date and gap, utilizing Graph Builder with transformed date as an overlay.

Code:

dt = Open("data_table.jmp");
Column( dt, "Date" ) << set modeling type( "Nominal" );
Graph Builder(
    Size( 985, 480 ),
    Show Control Panel( 0 ),
    Variables(
        X( Transform Column( "Transform[Date]", Ordinal, Formula( Week Of Year( :Date ) ) ) ),
        X( :Date, Position( 1 ) ),
        Y( :Gap ),
        Overlay( Transform Column( "Transform[Date]", Ordinal, Formula( Week Of Year( :Date ) ) ) )
    ),
    Elements( Bar( X( 2 ), X( 1 ), Y, Legend( 9 ), Summary Statistic( "% of Total" ), Label( "Label by Value" ) ) )
);

Code Explanation:

1. Open data table.
2. Set Date column as Nominal.
3. Create Graph Builder window.
4. Hide control panel.
5. Define X variables: transformed Date, original Date.
6. Define Y variable: Gap.
7. Set overlay using transformed Date.
8. Add Bar element.
9. Configure Bar for two X variables.
10. Apply "% of Total" summary statistic and label by value.

Example 16

Summary: Vizualizes age column value colors in a new window with multiple Graph Builders, including bar, pie, treemap, and mosaic plots.

Code:

dt = Open("data_table.jmp");
Column( dt, "age" ) << Set Property( "Value Colors", "Blue White Red" );
New Window( "Value Colors",
    Graph Builder( Show Control Panel( 0 ), Variables( X( :age ), Color( :age ) ), Elements( Bar( X, Legend( 3 ) ) ) ),
    Graph Builder( Size( 495, 440 ), Show Control Panel( 0 ), Variables( X( :age ), Color( :age ) ), Elements( Pie( X, Legend( 8 ) ) ) ),
    Graph Builder( Show Control Panel( 0 ), Variables( X( :age ), Y( :height ), Color( :age ) ), Elements( Treemap( X, Y, Legend( 4 ) ) ) ),
    Graph Builder(
        Size( 495, 456 ),
        Show Control Panel( 0 ),
        Variables( X( :age ), Color( :age ) ),
        Elements( Mosaic( X, Legend( 13 ) ) )
    )
);

Code Explanation:

1. Open data table;
2. Set age column value colors.
3. Create new window titled "Value Colors".
4. Add first Graph Builder with bar chart.
5. Add second Graph Builder with pie chart.
6. Add third Graph Builder with treemap.
7. Add fourth Graph Builder with mosaic plot.
8. Configure size for pie and mosaic charts.
9. Hide control panels for all Graph Builders.
10. Assign age to X-axis and color for all charts.

Example 17

Summary: Vizualizes multivariate correlations between age and height, utilizing Graph Builder to create a scatter plot with jittered points.

Code:

dt = Open("data_table.jmp");
Column( "height" ) << Set Property( "Spec Limits", {LSL( 40 ), USL( 100 ), Target( 70 ), Show Limits( 1 )} );
gb = Graph Builder( Show Control Panel( 0 ), Variables( X( :age ), Y( :height ) ), Elements( Points( X, Y, Legend( 1 ), Jitter( 1 ) ) ) );

Code Explanation:

1. Open data table;
2. Set height spec limits.
3. Create Graph Builder object.
4. Hide control panel.
5. Assign age to X-axis.
6. Assign height to Y-axis.
7. Add points element.
8. Enable legend for points.
9. Enable jitter for points.

Example 18

Summary: Vizualizes multivariate correlations between age and height using a heatmap in Graph Builder, with additional pin annotation for customization.

Code:

dt = Open("data_table.jmp");
Column( dt, "height" ) << Format( "Currency", 12, 2 );
Graph Builder(
    Size( 563, 335 ),
    Show Control Panel( 0 ),
    Variables( X( :age ), Color( :height ) ),
    Elements( Heatmap( X, Legend( 4 ) ) ),
    SendToReport(
        Dispatch( {}, "Graph Builder", FrameBox,
            Add Pin Annotation(
                Seg( RectSeg( 1 ) ),
                Index( 0 ),
                Index Row( 0 ),
                UniqueID( 748495904 ),
                FoundPt( {102, 154} ),
                Origin( {0.358695652173913, 0.137992831541219} )
            )
        )
    )
);

Code Explanation:

1. Open data table.
2. Format height column as currency.
3. Create Graph Builder window.
4. Set window size.
5. Hide control panel.
6. Assign age to X axis.
7. Assign height to color.
8. Add heatmap element.
9. Configure legend position.
10. Add pin annotation to graph.

Example 19

Summary: Process of filtering data for manufacturer 'A' and visualizing sugar levels with fiber content using Graph Builder.

Code:

dt = Open("data_table.jmp");
r = dt << get rows where( :Mfr == "A" );
Column( dt, "Mfr" )[r] = "";
Graph Builder(
    Size( 300, 200 ),
    Show Control Panel( 0 ),
    Include Missing Categories( 1 ),
    Variables( X( :Mfr ), Y( :Sugars ), Overlay( :Fiber Gr ) ),
    Elements( Line( X, Y, Legend( 5 ), Summary Statistic( "N" ), Fill( "Fill Below" ), Missing Factors( "Treat as Missing" ) ) )
);

Code Explanation:

1. Open data table;
2. Identify rows where Mfr is "A".
3. Set Mfr to missing for identified rows.
4. Create Graph Builder window.
5. Set size to 300x200.
6. Hide control panel.
7. Include missing categories.
8. Set X variable to Mfr.
9. Set Y variable to Sugars.
10. Add Fiber Gr overlay; plot line with fill below, treating missing factors as missing.

Example 20

Summary: Creates a graph to visualize the relationship between sex and height, utilizing Graph Builder with a customized value ordering for the 'height' column.

Code:

dt = Open("data_table.jmp");

Column( dt, "height" ) << Set Property( "Value Ordering", {51, 52, 55, 56, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70} );

Graph Builder( Size( 558, 398 ), Show Control Panel( 0 ), Variables( X( :sex ), Y( :height ) ), Elements( Line( X, Y, Legend( 8 ) ) ) );

Code Explanation:

1. Open data table.
2. Set value ordering for height.
3. Create Graph Builder object.
4. Set size of Graph Builder window.
5. Hide control panel.
6. Define X variable as sex.
7. Define Y variable as height.
8. Add line element to graph.
9. Set legend position.
10. Display graph.

Example 21

Summary: Process of filtering data for 'A' and 'K' manufacturers, setting Mfr to empty and Sugars to missing, then generates a graph with Graph Builder.

Code:

dt = Open("data_table.jmp");
r = dt << get rows where( :Mfr == "A" );
Column( dt, "Mfr" )[r] = "";
r = dt << get rows where( :Mfr == "K" );
For( k = 1, k <= N Items( r ), k++,
    Column( dt, "Sugars" )[r[k]] = .
);
Graph Builder(
    Size( 300, 200 ),
    Show Control Panel( 0 ),
    Include Missing Categories( 1 ),
    Variables( X( :Mfr ), Y( :Sugars ), Overlay( :Fiber Gr ), ),
    Elements(
        Line( X, Y, Legend( 5 ), Summary Statistic( "Sum" ), Missing Factors( "Treat as Missing" ), Missing Values( "No Connection" ) )
    )
);

Code Explanation:

1. Open data table;
2. Get rows where Mfr is "A".
3. Set Mfr to empty for those rows.
4. Get rows where Mfr is "K".
5. Loop through these rows.
6. Set Sugars to missing for each row.
7. Create Graph Builder.
8. Set size to 300x200.
9. Hide control panel.
10. Include missing categories.

Example 22

Summary: Creates a mosaic plot to visualize the relationship between 'Landfall in USA' and 'Storm Category', utilizing Graph Builder.

Code:

Open("data_table.jmp");
Column( "Landfall in USA" ) << Modeling Type( "Continuous" );
Graph Builder(
    Size( 523, 453 ),
    Show Control Panel( 0 ),
    Variables( X( :Landfall in USA ), Y( :Storm Category ) ),
    Elements( Mosaic( X, Y, Legend( 4 ) ) )
);

Code Explanation:

1. Open data table;
2. Set "Landfall in USA" as continuous.
3. Create Graph Builder window.
4. Set window size.
5. Hide control panel.
6. Assign variables for graph.
7. Add mosaic element.
8. Place "Landfall in USA" on X-axis.
9. Place "Storm Category" on Y-axis.
10. Add legend to mosaic plot.

Example 23

Summary: Creates a pie chart to visualize the relationship between age and height, using Graph Builder with a custom format for the height column.

Code:

dt = Open("data_table.jmp");
Column( "height" ) << Format( "Currency", "USD", 10, 0 );
Graph Builder(
    Size( 587, 374 ),
    Show Control Panel( 0 ),
    Variables( X( :age ), Y( :height ) ),
    Elements( Pie( X, Y, Legend( 4 ), Summary Statistic( "Sum" ), Label( "Label by Value" ) ) )
);

Code Explanation:

1. Open data table.
2. Format height column as currency.
3. Create Graph Builder object.
4. Set graph size to 587x374.
5. Hide control panel.
6. Set X variable to age.
7. Set Y variable to height.
8. Add Pie element to graph.
9. Use summary statistic "Sum".
10. Label pie slices by value.

Example 24

Summary: Creates a scatter plot to visualize the relationship between height and weight, utilizing Graph Builder.

Code:

dt = Open("data_table.jmp");
Column( dt, "height" ) << value labels( {51 <= "below 63" <= 63} );
myGB = dt << Graph Builder(
    Size( 400, 300 ),
    Show Control Panel( 0 ),
    Variables( X( :height ), Y( :weight ) ),
    Elements( Points( X, Y, Legend( 2 ) ) )
);

Code Explanation:

1. Open data_table data
2. Apply value label to height column.
3. Create Graph Builder object.
4. Set graph size to 400x300.
5. Hide control panel.
6. Assign height to X-axis.
7. Assign weight to Y-axis.
8. Add points element.
9. Use legend for points.
10. Display graph.

Example 25

Summary: Creates a treemap visualization to analyze gap values over time, utilizing Graph Builder and transforming the 'Date' column into weeks.

Code:

dt = Open("data_table.jmp");
Column( dt, "Date" ) << set modeling type( "Nominal" );
Graph Builder(
    Size( 601, 526 ),
    Show Control Panel( 0 ),
    Variables(
        X( Transform Column( "Transform[Date]", Ordinal, Formula( Week Of Year( :Date ) ) ) ),
        X( :Date, Position( 1 ) ),
        Y( :Gap )
    ),
    Elements( Treemap( X( 1 ), X( 2 ), Y, Legend( 14 ), Layout( "Squarify" ), Category Name( 1 ), Size Value( 1 ) ) )
);

Code Explanation:

1. Open data table.
2. Set "Date" column to Nominal.
3. Launch Graph Builder.
4. Set window size.
5. Hide control panel.
6. Define X variables.
7. Transform "Date" to week.
8. Add "Date" as second X.
9. Add "Gap" as Y variable.
10. Create Treemap element.

Graph Builder using Select Where

Example 1

Summary: Creates two Graph Builder windows to visualize data, with the first window displaying points and bars by Color, Clarity, and Price, and the second window showing box plots, lines, and bars for the same variables.

Code:

dt = Open("data_table.jmp");
dt << Select Where( :Color == "G" );
Graph Builder(
    Size( 300, 300 ),
    Show Control Panel( 0 ),
    Variables( X( :Color ), Y( :Price ), Overlay( :Clarity ) ),
    Elements( Points( X, Y, Legend( 19 ) ), Bar( X, Y, Legend( 20 ) ) ), 
);
Graph Builder(
    Size( 378, 331 ),
    Show Control Panel( 0 ),
    Variables( X( :Color ), Y( :Price ) ),
    Elements( Points( X, Y, Legend( 38 ) ), Box Plot( X, Y, Legend( 39 ) ), Line( X, Y, Legend( 41 ) ), Bar( X, Y, Legend( 42 ) ) )
);

Code Explanation:

1. Open data table;
2. Select rows where Color is G.
3. Create first Graph Builder window.
4. Set size to 300x300.
5. Hide control panel.
6. Set X to Color, Y to Price, Overlay to Clarity.
7. Add Points and Bar elements.
8. Create second Graph Builder window.
9. Set size to 378x331.
10. Hide control panel.

Example 2

Summary: Runs data visualization and analysis by opening a data table, selecting specific rows, and generating two Graph Builder windows with various elements and performing an Oneway analysis.

Code:

dt = Open("data_table.jmp");
dt << Select Where( :Color == "G" );
Graph Builder(
    Size( 300, 300 ),
    Show Control Panel( 0 ),
    Variables( X( :Color ), Y( :Price ), Overlay( :Clarity ) ),
    Elements( Points( X, Y, Legend( 19 ) ), Bar( X, Y, Legend( 20 ) ) ), 
);
Graph Builder(
    Size( 378, 331 ),
    Show Control Panel( 0 ),
    Variables( X( :Color ), Y( :Price ) ),
    Elements( Points( X, Y, Legend( 38 ) ), Box Plot( X, Y, Legend( 39 ) ), Line( X, Y, Legend( 41 ) ), Bar( X, Y, Legend( 42 ) ) )
);
Oneway( Y( :Price ), X( :Cut ), Box Plots( 1 ) );

Code Explanation:

1. Open data table;
2. Select rows where Color is "G".
3. Create first Graph Builder window.
4. Set size to 300x300.
5. Hide control panel.
6. Define variables: X(Color), Y(Price), Overlay(Clarity).
7. Add Points and Bar elements.
8. Create second Graph Builder window.
9. Set size to 378x331.
10. Hide control panel.
11. Define variables: X(Color), Y(Price).
12. Add Points, Box Plot, Line, and Bar elements.
13. Perform Oneway analysis on Price by Cut with box plots.

Example 3

Summary: Analyze and visualize petal width and length data for the 'versicolor' species, using Graph Builder to create a box plot.

Code:

dt = Open("data_table.jmp");
dt << Select Where( :Species == "versicolor" );
dt2 = dt << Subset( Selected Rows, link to original data table( 1 ) );
dt2 << Clear Row States;
Graph Builder(
    Size( 421, 318 ),
    Show Control Panel( 0 ),
    Show Legend( 0 ),
    Variables( X( :Petal width ), Y( :Petal length ), Overlay( :Petal length ) ),
    Elements( Box Plot( X, Y, Legend( 5 ) ) )
);

Code Explanation:

1. Open data table;
2. Select versicolor species.
3. Subset selected rows.
4. Clear row states.
5. Create Graph Builder object.
6. Set graph size.
7. Hide control panel.
8. Hide legend.
9. Define variables: Petal width, Petal length.
10. Add box plot element.

Example 4

Summary: Analyze and visualize female records in a data table, utilizing Graph Builder to create a contour plot with HDR contour type.

Code:

dt = Open("data_table.jmp");
dt << Select Where( :sex == "F" & :height != 61 );
dt << Exclude;
dt << Clear Select;
dt << Graph Builder(
    Size( 528, 450 ),
    Show Control Panel( 0 ),
    Variables( X( :sex ), Y( :height ) ),
    Elements( Contour( X, Y, Legend( 4 ), Contour Type 1D( "HDR" ) ) )
);

Code Explanation:

1. Open data table.
2. Select female records.
3. Exclude selected records.
4. Clear selection.
5. Launch Graph Builder.
6. Set window size.
7. Hide control panel.
8. Define X and Y variables.
9. Add contour element.
10. Configure HDR contour type.

Example 5

Summary: Data filtering and visualization by opening a JMP data table, selecting female rows, excluding selected rows, clearing row selection, and launching Graph Builder with customized settings.

Code:

dt = Open("data_table.jmp");
dt << Select Where( :sex == "F" & :height != 61 );
dt << Exclude;
dt << Clear Select;
Graph Builder(
    Size( 528, 456 ),
    Show Control Panel( 0 ),
    Variables( X( :height ), Y( :weight ), Overlay( :sex ) ),
    Elements( Contour( X, Y, Legend( 4 ), Contour Type 2D( "HDR" ) ) )
);

Code Explanation:

1. Open data_table data
2. Select female rows.
3. Exclude selected rows.
4. Clear row selection.
5. Launch Graph Builder.
6. Set window size.
7. Hide control panel.
8. Define X, Y, and overlay variables.
9. Add contour element.
10. Configure HDR 2D contour type.

Example 6

Summary: Creates two Graph Builder windows to visualize data for Katie, with variables including sex, height, weight, sibling ages, sports, countries visited, and family cars.

Code:

dt = Open("data_table.jmp");
dt << Select Where( :name == "KATIE" );
Graph Builder(
    Size( 495, 449 ),
    Show Control Panel( 0 ),
    Variables(
        X( :sex ),
        X( :height, Position( 1 ) ),
        X( :weight, Position( 1 ) ),
        X( :sibling ages, Position( 1 ) ),
        X( :sports, Position( 1 ) ),
        X( :countries visited, Position( 1 ) ),
        X( :family cars, Position( 1 ) )
    ),
    Elements( Points( X( 1 ), X( 2 ), X( 3 ), X( 4 ), X( 5 ), X( 6 ), X( 7 ), Legend( 6 ) ) )
);
Graph Builder(
    Size( 534, 492 ),
    Show Control Panel( 0 ),
    Variables( X( :height ), Y( :weight ), Wrap( :family cars ) ),
    Elements( Points( X, Y, Legend( 10 ) ), Smoother( X, Y, Legend( 11 ) ) )
);

Code Explanation:

1. Open data table.
2. Select rows where name is "KATIE".
3. Create first Graph Builder window.
4. Set window size.
5. Hide control panel.
6. Define variables for X-axis.
7. Add points element with multiple X-variables.
8. Create second Graph Builder window.
9. Set window size.
10. Hide control panel.
11. Define X and Y variables.
12. Wrap by family cars.
13. Add points and smoother elements.

Example 7

Summary: Creates three Graph Builder windows to visualize data for Katie, including relationships between sex, height, weight, sibling ages, sports, countries visited, and family cars.

Code:

dt = Open("data_table.jmp");
dt << Select Where( :name == "KATIE" );
Graph Builder(
    Size( 495, 449 ),
    Show Control Panel( 0 ),
    Variables(
        X( :sex ),
        X( :height, Position( 1 ) ),
        X( :weight, Position( 1 ) ),
        X( :sibling ages, Position( 1 ) ),
        X( :sports, Position( 1 ) ),
        X( :countries visited, Position( 1 ) ),
        X( :family cars, Position( 1 ) )
    ),
    Elements( Points( X( 1 ), X( 2 ), X( 3 ), X( 4 ), X( 5 ), X( 6 ), X( 7 ), Legend( 6 ) ) )
);
Graph Builder(
    Size( 534, 492 ),
    Show Control Panel( 0 ),
    Variables( X( :height ), Y( :weight ), Wrap( :family cars ) ),
    Elements( Points( X, Y, Legend( 10 ) ), Smoother( X, Y, Legend( 11 ) ) )
);
Graph Builder( Size( 522, 464 ), Show Control Panel( 0 ), Variables( X( :sports ) ), Elements( Histogram( X, Legend( 3 ) ) ) );

Code Explanation:

1. Open data table.
2. Select rows where name is "KATIE".
3. Create first Graph Builder window.
4. Set window size.
5. Hide control panel.
6. Define X variables.
7. Add points element.
8. Create second Graph Builder window.
9. Set window size.
10. Hide control panel.
11. Define X and Y variables.
12. Add points and smoother elements.
13. Create third Graph Builder window.
14. Set window size.
15. Hide control panel.
16. Define X variable.
17. Add histogram element.

Example 8

Summary: Analyze and visualize data by selecting rows, subsetting a new table, and generating a graph with line elements using JMP's Graph Builder.

Code:

dt = Open("data_table.jmp") << Select Where( :height >= 67 & :height <= 70 );
myDt = dt << subset( Selected Rows( 1 ) );
myDt << Graph Builder(
    Size( 421, 338 ),
    Show Control Panel( 0 ),
    Variables( X( :age ), Y( :height ), Overlay( :weight ) ),
    Elements( Line( X, Y, Legend( 8 ), Stack( 1 ), Missing Factors( "Treat as Zero" ), Missing Values( "No Connection" ) ) )
);

Code Explanation:

1. Open data table;
2. Select rows where height is between 67 and 70.
3. Subset selected rows into new table.
4. Launch Graph Builder.
5. Set graph size.
6. Hide control panel.
7. Assign variables: age to X, height to Y, weight to overlay.
8. Add line element with specified properties.
9. Treat missing factors as zero.
10. Do not connect missing values.

Example 9

Summary: Analyze and visualize petal width and length data for the 'versicolor' species, using Graph Builder to create a line graph.

Code:

dt = Open("data_table.jmp");
dt << Select Where( :Species == "versicolor" );
dt2 = dt << Subset( Selected Rows, link to original data table( 1 ) );
dt2 << Clear Row States;
Graph Builder(
    Size( 359, 360 ),
    Show Control Panel( 0 ),
    Show Legend( 0 ),
    Variables( X( :Sepal width ), Y( :Petal width ), Overlay( :Petal length ) ),
    Elements( Line( X, Y, Legend( 4 ) ) )
);

Code Explanation:

1. Open data table;
2. Select versicolor species rows.
3. Subset selected rows into new table.
4. Clear row states in subset.
5. Create Graph Builder object.
6. Set graph size.
7. Hide control panel.
8. Hide legend.
9. Define variables: Sepal width, Petal width, Petal length.
10. Add line element to graph.

Example 10

Summary: Data filtering and graphing to visualize the relationship between age and weight for female subjects, utilizing Graph Builder.

Code:

dt = Open("data_table.jmp");
dt << Select Where( :sex == "F" ) << Invert Row Selection;
dt << Delete Rows();
gb = Graph Builder(
    Variables( X( :age ), Y( :weight ) ),
    Elements(
        Points( X, Y, Legend( 4 ) ),
        Line Of Fit( X, Y, Legend( 5 ), Unequal Variances( 1 ), Confidence of Prediction( 1 ), F Test( 1 ) )
    )
);

Code Explanation:

1. Open data table;
2. Select rows where sex is female.
3. Invert row selection.
4. Delete selected rows (males).
5. Create Graph Builder object.
6. Set X variable to age.
7. Set Y variable to weight.
8. Add points element.
9. Add line of fit element.
10. Configure line of fit settings.

Example 11

Summary: Data filtering and visualization by selecting rows with runtime values between 8.99 and 10, then generating a graph using Graph Builder.

Code:

dt = Open("data_table.jmp");
dt << Select Where( 8.99 < :runtime < 10 );
rownum = dt << Get Selected Rows;
For( i = 1, i <= N Row( rownum ), i++,
    Column( dt, "runtime" )[rownum[i]] = .
);
dt << Clear select;
Graph Builder(
    Size( 600, 600 ),
    Show Control Panel( 0 ),
    Variables( X( :Weight, Size( 23 ) ), Y( :Oxy, Size( 38 ) ), Group Y( :Sex ), Wrap( :Age ), Color( :Runtime ), Size( :RstPulse ) ),
    Elements(
        Points( X, Y, Color, Legend( 1 ) ),
        Line Of Fit(
            X,
            Y,
            Color,
            Legend( 4 ),
            Confidence of Fit( 1 ),
            Confidence of Prediction( 0 ),
            Degree( "Linear" ),
            Root Mean Square Error( 0 )
        )
    )
);

Code Explanation:

1. Open data table.
2. Select rows where runtime is between 8.99 and 10.
3. Get selected row numbers.
4. Loop through selected rows.
5. Set runtime values to missing.
6. Clear row selection.
7. Create Graph Builder window.
8. Set size to 600x600.
9. Hide control panel.
10. Define variables and elements for graph.

Example 12

Summary: Creates a mosaic graph to visualize data by age and sex, with a subset of rows filtered by height < 63.

Code:

dt = Open("data_table.jmp");
dt << Select Where( :height < 63 );
dt2 = dt << Subset( Selected Rows );
Graph Builder(
    Size( 534, 483 ),
    Show Control Panel( 0 ),
    Variables( X( :sex ), Y( :name ), Group X( :age ) ),
    Elements( Mosaic( X, Y, Legend( 5 ) ) )
);

Code Explanation:

1. Open data table;
2. Select rows where height < 63.
3. Create subset of selected rows.
4. Launch Graph Builder.
5. Set window size to 534x483.
6. Hide control panel.
7. Assign variables: X=sex, Y=name, Group X=age.
8. Add Mosaic element.
9. Set legend position to 5.
10. Display graph.

Example 13

Summary: Analyze and visualize adverse event data by selecting specific rows, creating a subset, and generating a mosaic graph using Graph Builder.

Code:

dt = Open("data_table.jmp");
dt << Select Where( :Domain Abbreviation == "DM" );
dt2 = dt << Subset( Selected Rows, link to original data table( 1 ) );
dt2 << Clear Row States;
dt2 << Graph Builder(
    Size( 604, 446 ),
    Show Control Panel( 0 ),
    Show Legend( 0 ),
    Variables( X( :Reported Term for the Adverse Event ), Y( :Body System or Organ Class ), Group Y( :Recovery ) ),
    Elements( Mosaic( X, Y, Legend( 9 ) ) )
);

Code Explanation:

1. Open table.
2. Select rows.
3. Subset selected rows.
4. Clear row states.
5. Create Graph Builder.
6. Set size.
7. Hide control panel.
8. Hide legend.
9. Define variables.
10. Add mosaic element.

Example 14

Summary: Vizualizes a data table with categories, sizes, and coloring using Graph Builder and TreeMap, while customizing legend and graph title.

Code:

dt = Open("data_table.jmp");
dt << Select Where( :Year == 90 | :Year == 91 );
TreeMap( Categories( :Make, :Model ), Sizes( :Wt ), Coloring( :L Leg ) );
Graph Builder(
    Size( 508, 374 ),
    Show Control Panel( 0 ),
    Variables( X( :Make ), X( :Model, Position( 1 ) ), Color( :L Leg ), Size( :Wt ) ),
    Elements( Treemap( X( 1 ), X( 2 ), Legend( 1 ) ) ), 
);
Graph Builder(
    Size( 508, 374 ),
    Show Control Panel( 0 ),
    Variables( X( :Make ), X( :Model, Position( 1 ) ), Color( :L Leg ), Size( :Wt ) ),
    Elements( Treemap( X( 1 ), X( 2 ), Legend( 1 ) ) ),
    SendToReport(
        Dispatch( {}, "400", ScaleBox,
            {Legend Model( 1, Properties( 0, {gradient( {Color Theme( "Green to Purple" )} )}, Item ID( "L Leg", 1 ) ) )}
        ),
        Dispatch( {}, "graph title", TextEditBox, {Set Text( "Color theme green to purple" )} )
    )
);

Code Explanation:

1. Open data table.
2. Select rows where Year is 90 or 91.
3. Create TreeMap with Make, Model categories.
4. Set Size by Wt, Color by L Leg.
5. Launch Graph Builder with specified size.
6. Hide control panel.
7. Set X variables: Make, Model.
8. Set Color and Size variables: L Leg, Wt.
9. Add Treemap element.
10. Customize legend and graph title in second Graph Builder.

Graph Builder using Row State

Summary: Creates a graph builder window with a bagplot contour to visualize height vs weight grouped by sex, while labeling specific rows as outliers.

Code:

dt = Open("data_table.jmp");
Row State( 4 ) = Labeled State( 1 );
Row State( 18 ) = Labeled State( 1 );
Row State( 7 ) = Labeled State( 1 );
Row State( 8 ) = Labeled State( 1 );
dt << Graph Builder(
    Size( 534, 492 ),
    Show Control Panel( 0 ),
    Variables( X( :height ), Y( :weight ), Group X( :sex ) ),
    Elements( Contour( X, Y, Legend( 6 ), Contour Type 2D( "Bagplot" ) ) ),
    SendToReport(
        Dispatch( {}, "Graph Builder", FrameBox,
            {Add Pin Annotation(
                Seg( Marker Seg( 1 ) ),
                Index( 0 ),
                Index Row( 3 ),
                UniqueID( 0 ),
                FoundPt( {253, 192} ),
                Origin( {66.0394805185861, 144.86881377551} ),
                Offset( {-1, -55} ),
                RightOfCenter( 0 ),
                Tag Line( 1 )
            ), Add Pin Annotation(
                Seg( Marker Seg( 1 ) ),
                Index( 1 ),
                Index Row( 17 ),
                UniqueID( 1 ),
                FoundPt( {241, 202} ),
                Origin( {65.0156838897402, 141.952359693878} ),
                Offset( {-132, -47} ),
                RightOfCenter( 0 ),
                Tag Line( 1 )
            )}
        ),
        Dispatch( {}, "Graph Builder", FrameBox( 2 ),
            {Add Pin Annotation(
                Seg( Marker Seg( 1 ) ),
                Index( 0 ),
                Index Row( 6 ),
                UniqueID( 0 ),
                FoundPt( {436, 250} ),
                Origin( {61.0058137600937, 127.953380102041} ),
                RightOfCenter( 1 ),
                Tag Line( 1 )
            ), Add Pin Annotation(
                Seg( Marker Seg( 1 ) ),
                Index( 1 ),
                Index Row( 7 ),
                UniqueID( 1 ),
                FoundPt( {319, 418} ),
                Origin( {51.0237966288459, 78.9569515306122} ),
                Offset( {-97, -72} ),
                RightOfCenter( 0 ),
                Tag Line( 1 )
            )}
        )
    )
);

Code Explanation:

1. Open data table;
2. Label row 4 as outlier.
3. Label row 18 as outlier.
4. Label row 7 as outlier.
5. Label row 8 as outlier.
6. Create Graph Builder window.
7. Set size to 534x492.
8. Hide control panel.
9. Plot height vs weight grouped by sex.
10. Add bagplot contour.

Graph Builder using Show Window

Example 1

Summary: Creates a graph builder window with bar chart to visualize height by sex, and calculates Werewolf average and weight total using transforms and annexes.

Code:

dt = Open("data_table.jmp");
dt << Show Window( 0 );
win = New Window( "A03: - TC",
    Graph Builder( Size( 526, 448 ), Show Control Panel( 0 ), Variables( X( :sex ), Y( :height ) ), Elements( Bar( X, Y, Legend( 4 ) ) ) )
);
imgBox = win[framebox( 1 )];
imgBox << Set Gridlet(
    Transforms( Transform Column( "Werewolf", Continuous, Formula( :age * 2 ) ) ),
    Annex( Matcher( "Werewolf Average" ), Value( Mean( :Werewolf[local:_dataTable << Get Rows Where( local:_whereExpr )] ) ) ),
    Annex(
        Matcher( "Weight Total" ),
        Value( Sum( :weight[local:_dataTable << Get Rows Where( local:_whereExpr )] ) ),
        Click( Write( "\!NTextlet Clicked!" ) )
    ),
    Reformat( Matcher( "Werewolf Average" ), Format( "Best", 10, 2 ) ),
    Annex( {Matcher( "age, sex" ), Value( Char( :age[local:_firstRow] ) || ", " || :sex[local:_firstRow] )} )
);

Code Explanation:

1. Open data table;
2. Hide the data table window.
3. Create a new window titled "A03: - TC".
4. Insert Graph Builder with specified size and variables.
5. Assign the first frame box to imgBox.
6. Set gridlet with transforms and annexes.
7. Add Werewolf column with age*2 formula.
8. Calculate and display Werewolf Average.
9. Calculate and display Weight Total.
10. Format Werewolf Average to Best, 10, 2.

Example 2

Summary: Configures a Graph Builder to visualize the relationship between 'sex' and 'height', with interactive features for filtering and annotation.

Code:

dt = Open("data_table.jmp");
dt << Show Window( 0 );
win = New Window( "A03: - TC",
    Graph Builder( Size( 526, 448 ), Show Control Panel( 0 ), Variables( X( :sex ), Y( :height ) ), Elements( Bar( X, Y, Legend( 4 ) ) ) )
);
imgBox = win[framebox( 1 )];
imgBox << Set Gridlet(
    Transforms( Transform Column( "Werewolf", Continuous, Formula( :age * 2 ) ) ),
    Annex( Matcher( "Werewolf Average" ), Value( Mean( :Werewolf[local:_dataTable << Get Rows Where( local:_whereExpr )] ) ) ),
    Annex(
        Matcher( "Weight Total" ),
        Value( Sum( :weight[local:_dataTable << Get Rows Where( local:_whereExpr )] ) ),
        Click( Write( "\!NTextlet Clicked!" ) )
    ),
    Reformat( Matcher( "Werewolf Average" ), Format( "Best", 10, 2 ) ),
    Annex( {Matcher( "age, sex" ), Value( Char( :age[local:_firstRow] ) || ", " || :sex[local:_firstRow] )} )
);
mpin = imgBox << Add Pin Annotation(
    Seg( BarSeg( 1 ) ),
    Index( {0, 0} ),
    Index Row( {0, 0} ),
    UniqueID( 664255392 ),
    FoundPt( {184, 226} ),
    Origin( {0.0157232704402516, 17.3353703703704} ),
    Tag Line( 1 )
);

Code Explanation:

1. Open data table.
2. Hide the window.
3. Create new window "A03: - TC".
4. Initialize Graph Builder with specified size and variables.
5. Assign Graph Box to imgBox.
6. Set gridlet with transforms and annexes.
7. Add pin annotation to imgBox.
8. Configure pin annotation segment and indices.
9. Set unique ID and found point.
10. Add tag line to pin annotation.

Example 3

Summary: Creates a graph builder with a bar chart to visualize sex-based height distribution, and adds a pin annotation to the frame box.

Code:

dt = Open("data_table.jmp");
dt << Show Window( 0 );
win = New Window( "E0: change nothing",
    dt << Graph Builder( Show Control Panel( 0 ), Variables( X( :sex ), Y( :height ) ), Elements( Bar( X, Y ) ) )
);
imgBox = win[framebox( 1 )];
imgBox << Set Gridlet( Expunge( {} ), Reformat( {} ), Annex( {} ) );
mpin = imgBox << Add Pin Annotation(
    Seg( BarSeg( 1 ) ),
    Index( {0, 0} ),
    Index Row( {0, 0} ),
    UniqueID( 661482976 ),
    FoundPt( {193, 190} ),
    Origin( {0.00671785028790783, 49.3255813953488} ),
    Tag Line( 1 )
);
text = mpin << copy();

Code Explanation:

1. Open data table.
2. Hide data table window.
3. Create new window named "E0".
4. Add Graph Builder to window.
5. Set Graph Builder properties.
6. Assign first frame box to imgBox.
7. Clear gridlets from imgBox.
8. Add pin annotation to imgBox.
9. Copy pin annotation content.

Example 4

Summary: Creates and configures a graph window with sex on X-axis and height on Y-axis, including removal of gridlets and addition of pin annotation.

Code:

dt = Open("data_table.jmp");
dt << Show Window( 0 );
win = New Window( "E0: change nothing",
    dt << Graph Builder( Show Control Panel( 0 ), Variables( X( :sex ), Y( :height ) ), Elements( Bar( X, Y ) ) )
);
imgBox = win[framebox( 1 )];
imgBox << Set Gridlet( Expunge( {} ), Reformat( {} ), Annex( {} ) );
mpin = imgBox << Add Pin Annotation(
    Seg( BarSeg( 1 ) ),
    Index( {0, 0} ),
    Index Row( {0, 0} ),
    UniqueID( 661482976 ),
    FoundPt( {193, 190} ),
    Origin( {0.00671785028790783, 49.3255813953488} ),
    Tag Line( 1 )
);
text = mpin << copy();
If( !Contains( text, "name:" ) | !Contains( text, "sex:" ) | !Contains( text, "Mean(height):" ),
    Show( text );
    Throw( "FAIL (00): nothing should have been expunged." );
);

Code Explanation:

1. Open data table.
2. Hide the data table window.
3. Create new window for graph.
4. Display graph builder with sex on X, height on Y.
5. Access graph frame box.
6. Remove gridlets from graph.
7. Add pin annotation to bar segment.
8. Copy annotation text.
9. Check if text contains required fields.
10. Display and throw error if conditions fail.

Example 5

Summary: Creates a geographic map to visualize data table coordinates, utilizing Graph Builder and custom scale formatting.

Code:

dt = Open("data_table.jmp");
dt << Show Window( 0 );
Graph Builder(
    Size( 534, 568 ),
    Show Control Panel( 0 ),
    Variables( X( :Longitude ), Y( :Latitude ) ),
    Elements( Points( X, Y, Legend( 12 ) ) ),
    SendToReport(
        Dispatch( {}, "Longitude", ScaleBox,
            {Format( "Longitude DDD", "PUNDIR", 16 ), Min( 145.857871767132 ), Max( 198.132374816991 ), Inc( 10 ), Minor Ticks( 4 )}
        ),
        Dispatch( {}, "Latitude", ScaleBox,
            {Format( "Latitude DDD", "PUNDIR", 16 ), Min( 0.601770069257046 ), Max( 56.2878722655278 ), Inc( 5 ), Minor Ticks( 1 )}
        ),
        Dispatch( {}, "Graph Builder", FrameBox, {Background Map( Images( "Street Map Service", "Mapbox Streets Muted", "" ) )} )
    )
);

Code Explanation:

1. Open data table.
2. Hide window.
3. Create Graph Builder.
4. Set size 534x568.
5. Disable control panel.
6. Set X variable Longitude.
7. Set Y variable Latitude.
8. Add points element.
9. Format Longitude scale.
10. Format Latitude scale.
11. Add background map.

Example 6

Summary: Creates a geographic map to visualize data table coordinates, utilizing Graph Builder and custom scale formatting.

Code:

dt = Open("data_table.jmp");
dt << Show Window( 0 );
Graph Builder(
    Size( 534, 568 ),
    Show Control Panel( 0 ),
    Variables( X( :Longitude ), Y( :Latitude ) ),
    Elements( Points( X, Y, Legend( 12 ) ) ),
    SendToReport(
        Dispatch( {}, "Longitude", ScaleBox,
            {Format( "Longitude DDD", "PUNDIR", 16 ), Min( -189.909515191014 ), Max( -137.635012141155 ), Inc( 10 ), Minor Ticks( 4 )}
        ),
        Dispatch( {}, "Latitude", ScaleBox,
            {Format( "Latitude DDD", "PUNDIR", 16 ), Min( -1.92941639420981 ), Max( 53.756685802061 ), Inc( 5 ), Minor Ticks( 1 )}
        ),
        Dispatch( {}, "Graph Builder", FrameBox, {Background Map( Images( "Street Map Service", "Mapbox Streets Muted", "" ) )} )
    )
);

Code Explanation:

1. Open data table.
2. Hide the data table window.
3. Create a new Graph Builder.
4. Set graph size.
5. Hide control panel.
6. Define X and Y variables.
7. Add points element.
8. Format Longitude scale.
9. Format Latitude scale.
10. Add background map.

Example 7

Summary: Creates a geographic map to visualize data table coordinates, utilizing Graph Builder and custom scale formatting.

Code:

dt = Open("data_table.jmp");
dt << Show Window( 0 );
Graph Builder(
    Size( 534, 512 ),
    Show Control Panel( 0 ),
    Variables( X( :Longitude ), Y( :Latitude ) ),
    Elements( Points( X, Y, Legend( 12 ) ) ),
    SendToReport(
        Dispatch( {}, "Longitude", ScaleBox,
            {Format( "Longitude DDD", "PUNDIR", 16 ), Min( -148.260224709495 ), Max( -100.237900192488 ), Inc( 10 ), Minor Ticks( 4 )}
        ),
        Dispatch( {}, "Latitude", ScaleBox,
            {Format( "Latitude DDD", "PUNDIR", 16 ), Min( 35.982986635224 ), Max( 81.4778203881779 ), Inc( 5 ), Minor Ticks( 1 )}
        ),
        Dispatch( {}, "Graph Builder", FrameBox, {Background Map( Images( "Street Map Service", "Mapbox Streets Muted", "" ) )} )
    )
);

Code Explanation:

1. Open data table.
2. Hide data table window.
3. Create Graph Builder object.
4. Set graph size.
5. Hide control panel.
6. Define X and Y variables.
7. Add points element.
8. Format Longitude scale.
9. Format Latitude scale.
10. Add background map.

Example 8

Summary: Creates a geographic map with Longitude and Latitude scales, utilizing Graph Builder to visualize data from a JMP data table.

Code:

dt = Open("data_table.jmp");
dt << Show Window( 0 );
Graph Builder(
    Size( 534, 540 ),
    Show Control Panel( 0 ),
    Variables( X( :Longitude ), Y( :Latitude ) ),
    Elements( Points( X, Y, Legend( 12 ) ) ),
    SendToReport(
        Dispatch( {}, "Longitude", ScaleBox,
            {Format( "Longitude DDD", "PUNDIR", 16 ), Min( -123.490815221776 ), Max( -75.4684907047686 ), Inc( 10 ), Minor Ticks( 4 )}
        ),
        Dispatch( {}, "Latitude", ScaleBox,
            {Format( "Latitude DDD", "PUNDIR", 16 ), Min( 59.0337024033873 ), Max( 107.359325812081 ), Inc( 5 ), Minor Ticks( 1 )}
        ),
        Dispatch( {}, "Graph Builder", FrameBox, {Background Map( Images( "Street Map Service", "Mapbox Streets Muted", "" ) )} )
    )
);

Code Explanation:

1. Open data table.
2. Hide data table window.
3. Create Graph Builder object.
4. Set graph size.
5. Disable control panel.
6. Define X and Y variables.
7. Add points element.
8. Format Longitude scale.
9. Format Latitude scale.
10. Set background map to muted street map.

Example 9

Summary: Creates a geographic map to visualize Longitude and Latitude data, with customized scale formatting and background mapping.

Code:

dt = Open("data_table.jmp");
dt << Show Window( 0 );
Graph Builder(
    Size( 534, 568 ),
    Show Control Panel( 0 ),
    Variables( X( :Longitude ), Y( :Latitude ) ),
    Elements( Points( X, Y, Legend( 12 ) ) ),
    SendToReport(
        Dispatch( {}, "Longitude", ScaleBox,
            {Format( "Longitude DDD", "PUNDIR", 16 ), Min( -73.7497969852126 ), Max( -22.0878857679692 ), Inc( 10 ), Minor Ticks( 4 )}
        ),
        Dispatch( {}, "Latitude", ScaleBox,
            {Format( "Latitude DDD", "PUNDIR", 16 ), Min( -120.923639997187 ), Max( -69.160629149381 ), Inc( 5 ), Minor Ticks( 1 )}
        ),
        Dispatch( {}, "Graph Builder", FrameBox, {Background Map( Images( "Street Map Service", "Mapbox Streets Muted", "" ) )} )
    )
);

Code Explanation:

1. Open data table;
2. Hide dataset window.
3. Create Graph Builder object.
4. Set graph size to 534x568.
5. Disable control panel.
6. Assign Longitude to X-axis.
7. Assign Latitude to Y-axis.
8. Add points element with legend.
9. Format Longitude scale.
10. Format Latitude scale.
11. Set background map to Street Map Service.

Example 10

Summary: Creates a geographic map with Street Map Service, displaying Longitude and Latitude variables, formatted scales, and points element with legend.

Code:

dt = Open("data_table.jmp");
dt << Show Window( 0 );
gb = Graph Builder(
    Size( 534, 456 ),
    Show Control Panel( 0 ),
    Variables( X( :Longitude ), Y( :Latitude ) ),
    Elements( Points( X, Y, Legend( 12 ) ) ),
    SendToReport(
        Dispatch( {}, "Longitude", ScaleBox,
            {Format( "Longitude DDD", "PUNDIR", 16 ), Min( -123.187516330089 ), Max( -75.1651918130815 ), Inc( 10 ), Minor Ticks( 4 )}
        ),
        Dispatch( {}, "Latitude", ScaleBox,
            {Format( "Latitude DDD", "PUNDIR", 16 ), Min( 16.9935691341021 ), Max( 56.7921974864635 ), Inc( 5 ), Minor Ticks( 1 )}
        ),
        Dispatch( {}, "Graph Builder", FrameBox, {Background Map( Images( "Street Map Service", "Mapbox Streets Muted", "" ) )} )
    )
);

Code Explanation:

1. Open data table;
2. Hide the data table window.
3. Create a Graph Builder object.
4. Set graph size to 534x456 pixels.
5. Hide the control panel.
6. Assign Longitude and Latitude as variables.
7. Add points element with legend.
8. Format Longitude scale.
9. Format Latitude scale.
10. Add background map with Street Map Service.

Example 11

Summary: Creates a geographic map to visualize Longitude and Latitude data, with customized scale formats and a background map.

Code:

dt = Open("data_table.jmp");
dt << Show Window( 0 );
Graph Builder(
    Size( 534, 596 ),
    Show Control Panel( 0 ),
    Variables( X( :Longitude ), Y( :Latitude ) ),
    Elements( Points( X, Y, Legend( 12 ) ) ),
    SendToReport(
        Dispatch( {}, "Longitude", ScaleBox,
            {Format( "Longitude DDD", "PUNDIR", 16 ), Min( -495.971361687243 ), Max( -430.507683576706 ), Inc( 10 ), Minor Ticks( 1 )}
        ),
        Dispatch( {}, "Latitude", ScaleBox,
            {Format( "Latitude DDD", "PUNDIR", 16 ), Min( -2.86559696587719 ), Max( 70.7293590573371 ), Inc( 10 ), Minor Ticks( 1 )}
        ),
        Dispatch( {}, "Graph Builder", FrameBox, {Background Map( Images( "Street Map Service", "Mapbox Streets Muted", "" ) )} )
    )
);

Code Explanation:

1. Open data table.
2. Hide window.
3. Create Graph Builder.
4. Set size.
5. Hide control panel.
6. Define variables.
7. Add points element.
8. Format Longitude scale.
9. Format Latitude scale.
10. Add background map.

Example 12

Summary: Creates a geographic map to visualize data table coordinates, utilizing Graph Builder and custom scale formatting.

Code:

dt = Open("data_table.jmp");
dt << Show Window( 0 );
Graph Builder(
    Size( 800, 469 ),
    Show Control Panel( 0 ),
    Variables( X( :Longitude ), Y( :Latitude ) ),
    Elements( Points( X, Y, Legend( 12 ) ) ),
    SendToReport(
        Dispatch( {}, "Longitude", ScaleBox,
            {Format( "Longitude DDD", "PUNDIR", 16 ), Min( -440.656828234084 ), Max( -119.13677654721 ), Inc( 50 ), Minor Ticks( 4 )}
        ),
        Dispatch( {}, "Latitude", ScaleBox,
            {Format( "Latitude DDD", "PUNDIR", 16 ), Min( -95.9669091329747 ), Max( 80.6304741822178 ), Inc( 50 ), Minor Ticks( 4 )}
        ),
        Dispatch( {}, "Graph Builder", FrameBox, {Background Map( Images( "Street Map Service", "Mapbox Streets Muted", "" ) )} )
    )
);

Code Explanation:

1. Open data_table data
2. Hide data window.
3. Create Graph Builder.
4. Set graph size.
5. Hide control panel.
6. Define X and Y variables.
7. Add points element.
8. Format Longitude scale.
9. Format Latitude scale.
10. Add background map.

Example 13

Summary: Creates a geographic map to visualize Longitude and Latitude data, with customized scale formatting and background mapping.

Code:

dt = Open("data_table.jmp");
dt << Show Window( 0 );
Graph Builder(
    Size( 534, 484 ),
    Show Control Panel( 0 ),
    Variables( X( :Longitude ), Y( :Latitude ) ),
    Elements( Points( X, Y, Legend( 12 ) ) ),
    SendToReport(
        Dispatch( {}, "Longitude", ScaleBox,
            {Format( "Longitude DDD", "PUNDIR", 16 ), Min( -1065.79929364704 ), Max( 504.32720445391 ), Inc( 20 ), Minor Ticks( 1 )}
        ),
        Dispatch( {}, "Latitude", ScaleBox,
            {Format( "Latitude DDD", "PUNDIR", 16 ), Min( -714.057750736148 ), Max( 698.721315785391 ), Inc( 200 ), Minor Ticks( 1 )}
        ),
        Dispatch( {}, "Graph Builder", FrameBox, {Background Map( Images( "Street Map Service", "Mapbox Streets Muted", "" ) )} )
    )
);

Code Explanation:

1. Open data table;
2. Hide the data table window.
3. Create a new Graph Builder.
4. Set graph size to 534x484.
5. Hide control panel.
6. Set X variable to Longitude.
7. Set Y variable to Latitude.
8. Add points element with legend.
9. Format Longitude scale.
10. Format Latitude scale.
11. Add background map with muted street map service.

Example 14

Summary: Creates a geographic map using Graph Builder to visualize Longitude and Latitude data, with customized scale settings for both axes.

Code:

dt = Open("data_table.jmp");
dt << Show Window( 0 );
Graph Builder(
    Size( 800, 506 ),
    Show Control Panel( 0 ),
    Variables( X( :Longitude ), Y( :Latitude ) ),
    Elements( Points( X, Y, Legend( 12 ) ) ),
    SendToReport(
        Dispatch( {}, "Longitude", ScaleBox,
            {Format( "Longitude DDD", "PUNDIR", 16 ), Min( 1896.93493165922 ), Max( 2539.10133924034 ), Inc( 50 ), Minor Ticks( 1 )}
        ),
        Dispatch( {}, "Latitude", ScaleBox,
            {Format( "Latitude DDD", "PUNDIR", 16 ), Min( -197.478628423676 ), Max( 182.579041369232 ), Inc( 100 ), Minor Ticks( 4 )}
        ),
        Dispatch( {}, "Graph Builder", FrameBox, {Background Map( Images( "Street Map Service", "Mapbox Streets Muted", "" ) )} )
    )
);

Code Explanation:

1. Open data table;
2. Hide the data table window.
3. Create a Graph Builder object.
4. Set graph size to 800x506 pixels.
5. Disable control panel.
6. Set X variable to Longitude.
7. Set Y variable to Latitude.
8. Add points element with legend.
9. Configure Longitude scale settings.
10. Configure Latitude scale settings.
11. Set background map to "Street Map Service".

Example 15

Summary: Creates a geographic map to visualize Longitude and Latitude data, with formatted scales and a background map.

Code:

dt = Open("data_table.jmp");
dt << Show Window( 0 );
Graph Builder(
    Size( 1005, 624 ),
    Show Control Panel( 0 ),
    Variables( X( :Longitude ), Y( :Latitude ) ),
    Elements( Points( X, Y, Legend( 12 ) ) ),
    SendToReport(
        Dispatch( {}, "Longitude", ScaleBox,
            {Format( "Longitude DDD", "PUNDIR", 16 ), Min( -182.536382166871 ), Max( -175.256001721733 ), Inc( 1 ), Minor Ticks( 1 )}
        ),
        Dispatch( {}, "Latitude", ScaleBox,
            {Format( "Latitude DDD", "PUNDIR", 16, 1 ), Min( 49.5928198642503 ), Max( 53.9594941547173 ), Inc( 0.5 ), Minor Ticks( 1 )}
        ),
        Dispatch( {}, "Graph Builder", FrameBox, {Background Map( Images( "Street Map Service", "Mapbox Streets Muted", "" ) )} )
    )
);

Code Explanation:

1. Open data table.
2. Hide data table window.
3. Create Graph Builder object.
4. Set graph size.
5. Disable control panel.
6. Define X and Y variables.
7. Add points element.
8. Format Longitude scale.
9. Format Latitude scale.
10. Add background map.

Example 16

Summary: Creates a geographic map to visualize longitude and latitude data, with formatted scales and a background map.

Code:

dt = Open("data_table.jmp");
dt << Show Window( 0 );
Graph Builder(
    Size( 534, 596 ),
    Show Control Panel( 0 ),
    Variables( X( :Longitude ), Y( :Latitude ) ),
    Elements( Points( X, Y, Legend( 12 ) ) ),
    SendToReport(
        Dispatch( {}, "Longitude", ScaleBox,
            {Format( "Longitude DDD", "PUNDIR", 16, 2 ), Min( -71.1112344099747 ), Max( -70.9011783755755 ), Inc( 0.05 ), Minor Ticks( 4 )}
        ),
        Dispatch( {}, "Latitude", ScaleBox,
            {Format( "Latitude DDD", "PUNDIR", 16, 2 ), Min( 42.2413159297049 ), Max( 42.4851635870291 ), Inc( 0.05 ), Minor Ticks( 4 )}
        ),
        Dispatch( {}, "Graph Builder", FrameBox, {Background Map( Images( "Street Map Service", "Mapbox Streets Muted", "" ) )} )
    )
);

Code Explanation:

1. Open data table.
2. Hide the window.
3. Create a new graph builder.
4. Set graph size.
5. Hide control panel.
6. Assign variables for X and Y axes.
7. Add points element.
8. Format longitude scale.
9. Format latitude scale.
10. Add background map.

Example 17

Summary: Creates a geographic map to visualize Longitude and Latitude data, utilizing Graph Builder's ScaleBox and FrameBox features.

Code:

dt = Open("data_table.jmp");
dt << Show Window( 0 );
Graph Builder(
    Size( 534, 596 ),
    Show Control Panel( 0 ),
    Variables( X( :Longitude ), Y( :Latitude ) ),
    Elements( Points( X, Y, Legend( 12 ) ) ),
    SendToReport(
        Dispatch( {}, "Longitude", ScaleBox,
            {Format( "Longitude DDD", "PUNDIR", 16, 3 ), Min( -71.0112077044265 ), Max( -70.998278983831 ), Inc( 0.002 ), Minor Ticks( 1 )}
        ),
        Dispatch( {}, "Latitude", ScaleBox,
            {Format( "Latitude DDD", "PUNDIR", 16, 3 ), Min( 42.3568093604978 ), Max( 42.3720498390806 ), Inc( 0.002 ), Minor Ticks( 1 )}
        ),
        Dispatch( {}, "Graph Builder", FrameBox, {Background Map( Images( "Street Map Service", "Mapbox Streets Muted", "" ) )} )
    )
);

Code Explanation:

1. Open data_table data
2. Hide the data table window.
3. Create a new Graph Builder.
4. Set graph size to 534x596.
5. Hide control panel.
6. Assign Longitude to X-axis.
7. Assign Latitude to Y-axis.
8. Add points element with legend.
9. Format Longitude scale.
10. Format Latitude scale.
11. Add background map with Street Map Service.

Example 18

Summary: Creates a geographic map to visualize Longitude and Latitude data, with customized scale formatting and background mapping.

Code:

dt = Open("data_table.jmp");
dt << Show Window( 0 );
Graph Builder(
    Size( 534, 596 ),
    Show Control Panel( 0 ),
    Variables( X( :Longitude ), Y( :Latitude ) ),
    Elements( Points( X, Y, Legend( 12 ) ) ),
    SendToReport(
        Dispatch( {}, "Longitude", ScaleBox,
            {Format( "Longitude DDD", "PUNDIR", 16, 4 ), Min( -71.0368172622961 ), Max( -71.0335416971788 ), Inc( 0.0005 ),
            Minor Ticks( 1 )}
        ),
        Dispatch( {}, "Latitude", ScaleBox,
            {Format( "Latitude DDD", "PUNDIR", 16, 3 ), Min( 42.3798148659204 ), Max( 42.3836761281116 ), Inc( 0.001 ), Minor Ticks( 4 )}
        ),
        Dispatch( {}, "Graph Builder", FrameBox, {Background Map( Images( "Street Map Service", "Mapbox Streets Muted", "" ) )} )
    )
);

Code Explanation:

1. Open data_table data
2. Hide data window.
3. Create Graph Builder.
4. Set size to 534x596.
5. Disable control panel.
6. Assign Longitude to X.
7. Assign Latitude to Y.
8. Add points element.
9. Format Longitude scale.
10. Format Latitude scale.
11. Add background map.

Example 19

Summary: Creates a geographic map using Graph Builder to visualize Longitude and Latitude data, with formatted scales and a background Street Map Service.

Code:

dt = Open("data_table.jmp");
dt << Show Window( 0 );
Graph Builder(
    Size( 701, 641 ),
    Show Control Panel( 0 ),
    Variables( X( :Longitude ), Y( :Latitude ) ),
    Elements( Points( X, Y, Legend( 12 ) ) ),
    SendToReport(
        Dispatch( {}, "Longitude", ScaleBox,
            {Format( "Longitude DDD", "PUNDIR", 16, 3 ), Min( 139.871027479103 ), Max( 139.891541820599 ), Inc( 0.005 ), Minor Ticks( 4 )}
        ),
        Dispatch( {}, "Latitude", ScaleBox,
            {Format( "Latitude DDD", "PUNDIR", 16, 3 ), Min( 35.6193251617832 ), Max( 35.6384829097279 ), Inc( 0.005 ), Minor Ticks( 4 )}
        ),
        Dispatch( {}, "Graph Builder", FrameBox, {Background Map( Images( "Street Map Service", "Mapbox Streets Muted", "" ) )} )
    )
);

Code Explanation:

1. Open data table;
2. Hide dataset window.
3. Create Graph Builder.
4. Set graph size.
5. Hide control panel.
6. Set X variable to Longitude.
7. Set Y variable to Latitude.
8. Add points element.
9. Format Longitude scale.
10. Format Latitude scale.
11. Add background map with Street Map Service.

Example 20

Summary: Creates a geographic map using Graph Builder to visualize Longitude and Latitude data, with formatted scales for both axes.

Code:

dt = Open("data_table.jmp");
dt << Show Window( 0 );
Graph Builder(
    Size( 701, 641 ),
    Show Control Panel( 0 ),
    Variables( X( :Longitude ), Y( :Latitude ) ),
    Elements( Points( X, Y, Legend( 12 ) ) ),
    SendToReport(
        Dispatch( {}, "Longitude", ScaleBox,
            {Format( "Longitude DDD", "PUNDIR", 16, 3 ), Min( 139.78818391945 ), Max( 139.795392114966 ), Inc( 0.001 ), Minor Ticks( 1 )}
        ),
        Dispatch( {}, "Latitude", ScaleBox,
            {Format( "Latitude DDD", "PUNDIR", 16, 3 ), Min( 35.6291290021875 ), Max( 35.6358605267091 ), Inc( 0.001 ), Minor Ticks( 1 )}
        ),
        Dispatch( {}, "Graph Builder", FrameBox, {Background Map( Images( "Street Map Service", "Mapbox Streets Muted", "" ) )} )
    )
);

Code Explanation:

1. Open data table.
2. Hide the window.
3. Create Graph Builder.
4. Set size to 701x641.
5. Hide control panel.
6. Define X and Y variables.
7. Add points element.
8. Format Longitude scale.
9. Format Latitude scale.
10. Add background map.

Example 21

Summary: Creates a geographic map to visualize Longitude and Latitude data, utilizing Graph Builder's ScaleBox and FrameBox features.

Code:

dt = Open("data_table.jmp");
dt << Show Window( 0 );
Graph Builder(
    Size( 1005, 624 ),
    Show Control Panel( 0 ),
    Variables( X( :Longitude ), Y( :Latitude ) ),
    Elements( Points( X, Y, Legend( 12 ) ) ),
    SendToReport(
        Dispatch( {}, "Longitude", ScaleBox,
            {Format( "Longitude DDD", "PUNDIR", 16, 0 ), Min( -84.6885332642039 ), Max( -76.2950744001435 ), Inc( 1 ), Minor Ticks( 4 )}
        ),
        Dispatch( {}, "Latitude", ScaleBox,
            {Format( "Latitude DDD", "PUNDIR", 16, 0 ), Min( 32.6617048859166 ), Max( 37.6480937671026 ), Inc( 1 ), Minor Ticks( 4 )}
        ),
        Dispatch( {}, "Graph Builder", FrameBox, {Background Map( Images( "Street Map Service", "Mapbox Streets Muted", "" ) )} )
    )
);

Code Explanation:

1. Open data_table data
2. Hide data window.
3. Create Graph Builder object.
4. Set graph size.
5. Hide control panel.
6. Define X and Y variables.
7. Add points element.
8. Format Longitude scale.
9. Set Longitude min, max, increment, minor ticks.
10. Format Latitude scale.
11. Set Latitude min, max, increment, minor ticks.
12. Add background map with Street Map Service.

Example 22

Summary: Creates a geographic map to visualize longitude and latitude data, with customized scale formats and background mapping.

Code:

dt = Open("data_table.jmp");
dt << Show Window( 0 );
Graph Builder(
    Size( 534, 484 ),
    Show Control Panel( 0 ),
    Variables( X( :Longitude ), Y( :Latitude ) ),
    Elements( Points( X, Y, Legend( 12 ) ) ),
    SendToReport(
        Dispatch( {}, "Longitude", ScaleBox,
            {Format( "Longitude DDD", "PUNDIR", 16, 0 ), Min( 536.765662823046 ), Max( 543.933780874803 ), Inc( 1 ), Minor Ticks( 1 )}
        ),
        Dispatch( {}, "Latitude", ScaleBox,
            {Format( "Latitude DDD", "PUNDIR", 16, 0 ), Min( 48.3867994876943 ), Max( 54.7551064726239 ), Inc( 1 ), Minor Ticks( 4 )}
        ),
        Dispatch( {}, "Graph Builder", FrameBox, {Background Map( Images( "Street Map Service", "Mapbox Streets Muted" ) )} )
    )
);

Code Explanation:

1. Open data table.
2. Hide window.
3. Create Graph Builder object.
4. Set size to 534x484.
5. Hide control panel.
6. Define X and Y variables.
7. Add points element.
8. Format Longitude scale.
9. Format Latitude scale.
10. Add background map.

Graph Builder using Preferences

Example 1

Summary: Creates a heatmap graph from a data table, customizing font preferences and annotation properties.

Code:

Preferences( Fonts( English( Hover Label Font( "Calibri", 11, "Bold" ) ) ) );
Open("data_table.jmp");
Graph Builder(
    Size( 528, 450 ),
    Show Control Panel( 0 ),
    Variables( X( :age ), Y( :height ) ),
    Elements( Heatmap( X, Y, Legend( 12 ) ) ),
    SendToReport(
        Dispatch( {}, "Graph Builder", FrameBox,
            {Set Gridlet(
                Style( {{Matcher( "age", Scope( Both ) ), Text Color( "Black" ), Font( "Showcard Gothic", 14, "Bold Italic" )}} )
            ), Add Pin Annotation(
                Seg( RectSeg( 1 ) ),
                Index( 11 ),
                Index Row( 18 ),
                UniqueID( 11 ),
                FoundPt( {500, 281} ),
                Origin( {1.65702479338843, 63.4311224489796} ),
                Offset( {-116, -77} ),
                RightOfCenter( 0 ),
                Tag Line( 1 )
            )}
        )
    )
);

Code Explanation:

1. Set font preferences.
2. Open data table.
3. Create graph builder.
4. Set graph size.
5. Hide control panel.
6. Define X and Y variables.
7. Add heatmap element.
8. Customize gridlet style.
9. Add pin annotation.
10. Set annotation properties.

Example 2

Summary: Creates a graph with two elements: bar and heatmap, using Graph Builder to visualize data from an open data table.

Code:

Preferences( Fonts( English( Graph Label( "Segoe UI", 18, "Italic" ) ) ) );
Open("data_table.jmp");
Graph Builder(
    Size( 525, 448 ),
    Show Control Panel( 0 ),
    Variables( X( :sex ), Y( :height ) ),
    Elements( Bar( X, Y, Legend( 6 ), Label( "Label by Value" ) ) )
);
Graph Builder(
    Size( 525, 448 ),
    Show Control Panel( 0 ),
    Variables( X( :sex ), Y( :height ) ),
    Elements( Heatmap( X, Y, Legend( 7 ), Label( "Label by Value" ) ) )
);

Code Explanation:

1. Set graph label font.
2. Open data table.
3. Create bar graph.
4. Set graph size.
5. Hide control panel.
6. Define X and Y variables.
7. Add bar element.
8. Label by value.
9. Create heatmap graph.
10. Set graph size.

Example 3

Summary: Creates a heatmap visualization to explore relationships between age, height, and sex in a dataset.

Code:

Preferences( Fill Selection mode( "Unselected Faded" ) );
dt = Open("data_table.jmp");
dt << select where( :age == 14 );
gb = dt << Graph Builder(
    Size( 528, 450 ),
    Show Control Panel( 0 ),
    Continuous Color Theme( "Blue to Red" ),
    Variables( X( :age ), Y( :height ), Group X( :sex ) ),
    Elements( Heatmap( X, Y, Legend( 4 ) ) )
);

Code Explanation:

1. Set fill selection mode.
2. Open data table.
3. Select rows where age is 14.
4. Create Graph Builder object.
5. Set graph size.
6. Hide control panel.
7. Define color theme.
8. Assign variables for axes and grouping.
9. Add heatmap element.
10. Display legend.

Example 4

Summary: Configures a Graph Builder to visualize data table relationships, utilizing continuous color theme and heatmap element.

Code:

Preferences(
    Continuous Color Theme(
        {"Blue to Gray to Red Copy", 4099, {{42, 63, 255}, {192, 192, 192}, {252, 11, 11}, Missing( {255, 255, 128} )}}
    )
);
Open("data_table.jmp");
Graph Builder(
    Size( 469, 314 ),
    Show Control Panel( 0 ),
    Variables( X( :age ), Y( :sex ), Color( :height, Summary Statistic( "Std Dev" ) ) ),
    Elements( Heatmap( X, Y, Legend( 2 ) ) )
);

Code Explanation:

1. Set continuous color theme.
2. Open data table;
3. Create Graph Builder.
4. Set graph size.
5. Hide control panel.
6. Assign variables to axes.
7. Color by height's standard deviation.
8. Add heatmap element.
9. Display legend for colors.

Example 5

Summary: Creates a graph builder object with customized settings, including large graph markers and certificate fill colors, to visualize data from an open data table.

Code:

Preferences( Graph Marker size( "Large" ) );
Preferences( Graph Marker( "Circle" ) );
cert fill color = {Fill Color( 19 ), Fill Color( 36 ), Fill Color( 2147483647 ), Fill Color( 19 ), Fill Color( 36 ),
Fill Color( 2147483647 ), Fill Color( 2147483647 ), Fill Color( 2147483647 ), Fill Color( 2147483647 ), Fill Color( 19 ), Fill Color( 36 )};
cert transparency = {Transparency( 0.7 ), Transparency( 0.4 ), Transparency( 0.7 ), Transparency( 0.4 ), Transparency( 0.7 ),
Transparency( 0.4 ), Transparency( 0.7 ), Transparency( 0.7 ), Transparency( 0.4 ), Transparency( 0.4 )};
dt = Open("data_table.jmp");
gb = Graph Builder(
    Show Control Panel( 0 ),
    Variables( X( :height ), Y( :weight ) ),
    Elements(
        Points( X, Y, Legend( 1 ) ),
        Line Of Fit(
            X,
            Y,
            Legend( 3 ),
            Confidence of Fit( 1 ),
            Confidence of Prediction( 1 ),
            Degree( "Linear" ),
            Root Mean Square Error( 0 )
        )
    ),
    SendToReport(
        Dispatch( {}, "400", ScaleBox,
            {Legend Model(
                3,
                Base( 1, 0, 0 ),
                Base( 2, 0, 0 ),
                Properties( 1, {Fill Color( 19 ), Transparency( 0.7 )} ),
                Properties( 2, {Fill Color( 36 ), Transparency( 0.4 )} )
            )}
        )
    )
);
rpt = gb << report;
Set Preference( default );

Code Explanation:

1. Set graph marker size large.
2. Set graph marker shape circle.
3. Define certificate fill colors.
4. Define certificate transparencies.
5. Open data table.
6. Create graph builder object.
7. Hide control panel.
8. Set X and Y variables.
9. Add points element.
10. Add linear fit element with confidence intervals.

Example 6

Summary: Creates a mosaic graph with specified frame color, data table opening, and report settings configuration using Graph Builder.

Code:

Preferences( Frame Color( 4 ) );
dt = Open("data_table.jmp");
gb = Graph Builder(
    Show Control Panel( 0 ),
    Variables( X( :age ), Y( :height ) ),
    Elements( Mosaic( X, Y, Legend( 4 ) ) ),
    SendToReport(
        Dispatch( {}, "400", ScaleBox,
            {Legend Model( 4, Properties( 0, {Fill Pattern( "diamond" )} ), Properties( 16, {Fill Pattern( "grid heavy" )} ) )}
        )
    )
);
 Preferences( Factory Default );

Code Explanation:

1. Set frame color.
2. Open data table.
3. Create Graph Builder object.
4. Hide control panel.
5. Assign variables to axes.
6. Add mosaic element.
7. Send report settings.
8. Dispatch to report.
9. Set legend properties.
10. Reset platform preferences.

Graph Builder using Get Preferences

Example 1

Summary: Configures a graph builder object with custom font preferences and treemap element, utilizing Graph Builder and Report functions to visualize data from an open data table.

Code:

pref = Get Preferences( Graph Label() );
Set Preferences( Fonts( English( Graph Label( "Brush Script MT", 20 ) ) ) );
Open("data_table.jmp");
gb = Graph Builder(
    Size( 506, 492 ),
    Show Control Panel( 0 ),
    Variables( X( :sex ), X( :age, Position( 1 ) ), Y( :height ) ),
    Elements( Treemap( X( 1 ), X( 2 ), Y, Legend( 12 ) ) )
);
frame = Report( gb )[FrameBox( 1 )];
seg = (frame << Find Seg( "TreeMapSeg" ));
seg << Set Group Label Font( "Brush Script MT" );
pref;

Code Explanation:

1. Retrieve graph label preferences.
2. Set new font preferences.
3. Open data table.
4. Create graph builder object.
5. Configure graph size and settings.
6. Define variables for treemap.
7. Add treemap element to graph.
8. Access graph report frame.
9. Find treemap segments.
10. Set group label font for segments.

Example 2

Summary: Process of setting graph label preferences, opening a data table, and launching Graph Builder to visualize age vs. height relationships.

Code:

pref = Get Preferences( Graph Label() );
Set Preferences( Fonts( English( Graph Label( "Brush Script MT", 20 ) ) ) );
Open("data_table.jmp");
Graph Builder(
    Size( 528, 450 ),
    Show Control Panel( 0 ),
    Variables( X( :age ), Y( :height ) ),
    Elements( Heatmap( X, Y, Legend( 6 ), Label( "Label by Value" ) ) )
);
pref;

Code Explanation:

1. Retrieve graph label preferences.
2. Set new font for graph labels.
3. Open data table.
4. Launch Graph Builder.
5. Set window size.
6. Hide control panel.
7. Assign variables for axes.
8. Add heatmap element.
9. Configure legend position.
10. Display original preferences.

Example 3

Summary: Process of setting graph marker to triangle, opening data_table.jmp, and creating a Graph Builder window with specified variables and elements.

Code:

myPref = Get Preferences();
Set Preferences( Graph Marker( "Triangle" ) );
Open("data_table.jmp");
Graph Builder(
    Size( 525, 452 ),
    Show Control Panel( 0 ),
    Variables( X( :weight ), Y( :height ), Overlay( :sex ), Color( :age ) ),
    Elements( Points( X, Y ) )
);
myPref;

Code Explanation:

1. Retrieve user preferences.
2. Set graph marker to triangle.
3. Open data_table data
4. Create Graph Builder window.
5. Set size to 525x452.
6. Hide control panel.
7. Define variables: X=weight, Y=height, Overlay=sex, Color=age.
8. Add points element.
9. Restore original preferences.

Example 4

Summary: Creates a graph builder window with customized settings, including marker font and data table import.

Code:

ps = Get Preferences();
Preferences( Fonts( English( Marker Font( "Segoe UI", 22 ), ) ) );
dt = Open("data_table.jmp");
Graph Builder(
    Size( 469, 398 ),
    Show Control Panel( 0 ),
    Variables( X( :weight ), Y( :height ), Overlay( :sex ) ),
    Elements( Points( X, Y, Legend( 3 ) ) ),
    SendToReport( Dispatch( {}, "400", ScaleBox, {Legend Model( 3, Properties( 1, {Marker( "M" )}, Item ID( "M", 1 ) ) )} ) )
);
ps = Get Preferences();
Preferences( Fonts( English( Marker Font( "Segoe UI", 22 ), ) ) );
dt = Open("data_table.jmp");
Graph Builder(
    Size( 469, 398 ),
    Show Control Panel( 0 ),
    Variables( X( :weight ), Y( :height ), Overlay( :sex ) ),
    Elements( Points( X, Y, Legend( 3 ) ) ),
    SendToReport( Dispatch( {}, "400", ScaleBox, {Legend Model( 3, Properties( 1, {Marker( "M" )}, Item ID( "M", 1 ) ) )} ) )
);
ps;

Code Explanation:

1. Retrieve user preferences.
2. Set marker font to "Segoe UI".
3. Open data table;
4. Create Graph Builder window.
5. Set size to 469x398.
6. Hide control panel.
7. Assign weight to X-axis.
8. Assign height to Y-axis.
9. Overlay by sex.
10. Add points element with legend.

Graph Builder using Get Rows Where

Example 1

Summary: Selects and subsets data from a table, followed by the creation of a Graph Builder object with customized settings.

Code:

dt = Open("data_table.jmp");
dt << Get Rows Where();
For( i = 1, i <= 32, i++,
    Selected( Row State( i ) ) = 1
);
dt << Subset( Output Table( "BigClassSubset" ), Selected Rows( 1 ), selected
columns( 0 ), Link to original data table( 1 ) );
dt << Clear Select;
Graph Builder(
    Size( 570, 464 ),
    Show Control Panel( 0 ),
    Variables( X( :sex ), X( :age, Position( 1 ) ), Y( :height ), Group Y( :weight ), Frequency( :height ) ),
    Elements( Area( X( 1 ), X( 2 ), Y, Legend( 17 ) ) )
);

Code Explanation:

1. Open data table.
2. Get all row indices.
3. Loop through first 32 rows.
4. Select each row.
5. Subset selected rows into new table.
6. Clear selection from original table.
7. Create Graph Builder object.
8. Set graph size.
9. Hide control panel.
10. Define variables for axes and groups.

Example 2

Summary: Process of filtering a data table, excluding specific rows, and generating a graph with variables and elements defined.

Code:

dt = Open("data_table.jmp");
dt:age[{15, 16, 17, 18, 19}] = .;
dt:sex[{5, 6, 7, 8, 9}] = "";
dt << Get Rows Where();
For( i = 31, i <= 35, i++,
    Excluded( Row State( i ) ) = 1
);
dt << Graph Builder(
    Size( 536, 220 ),
    Show Control Panel( 0 ),
    Variables( X( :age ), Y( :weight ), Group X( :height ) ),
    Elements( Area( X, Y, Legend( 5 ), Summary Statistic( "N" ), Missing Factors( "Treat as Zero" ) ) )
);

Code Explanation:

1. Open data table.
2. Set specific age values to missing.
3. Set specific sex values to empty.
4. Get all row indices.
5. Loop through specified rows.
6. Exclude specified rows.
7. Create Graph Builder.
8. Set graph size.
9. Hide control panel.
10. Define variables and elements.

Example 3

Summary: Selects and subsets a data table, followed by the configuration of a Graph Builder to visualize relationships between variables.

Code:

dt = Open("data_table.jmp");
dt << Get Rows Where();
For( i = 1, i <= 40, i += 2,
    Selected( Row State( i ) ) = 1
);
dt << Subset( Output Table( "BigClassSubset" ), Selected Rows( 1 ), selected
columns( 0 ), Link to original data table( 1 ) );
dt << Clear Select;
Graph Builder(
    Size( 534, 464 ),
    Show Control Panel( 0 ),
    Variables( X( :sex ), X( :age, Position( 1 ) ), Y( :height ), Y( :weight, Position( 1 ) ), Overlay( :weight ) ),
    Elements( Area( X( 1 ), X( 2 ), Y( 1 ), Y( 2 ), Legend( 43 ) ) ),
    Local Data Filter( Mode( Include( 0 ) ), Add Filter( columns( :height ), Where( :height >= 59.9 & :height <= 69 ) ) )
);

Code Explanation:

1. Open data_table data
2. Get all row indices.
3. Select every second row.
4. Create subset table.
5. Clear previous selections.
6. Initialize Graph Builder.
7. Set window size.
8. Hide control panel.
9. Define variables for plotting.
10. Add area plot element.

Example 4

Summary: Selects and subsets a data table, followed by the configuration of Graph Builder to visualize relationships between variables.

Code:

dt = Open("data_table.jmp");
dt << Get Rows Where();
For( i = 1, i <= 40, i += 2,
    Selected( Row State( i ) ) = 1
);
dt << Subset( Output Table( "BigClassSubset" ), Selected Rows( 1 ), selected
columns( 0 ), Link to original data table( 1 ) );
dt << Clear Select;
Graph Builder(
    Size( 534, 464 ),
    Show Control Panel( 0 ),
    Variables( X( :sex ), X( :age, Position( 1 ) ), Y( :height ), Y( :weight, Position( 1 ) ), Overlay( :weight ) ),
    Elements( Area( X( 1 ), X( 2 ), Y( 1 ), Y( 2 ), Legend( 36 ) ) ),
    Local Data Filter( Add Filter( columns( :height ) ) )
);

Code Explanation:

1. Open data table.
2. Retrieve all row indices.
3. Select every other row starting from 1.
4. Create subset table with selected rows.
5. Clear selection from original table.
6. Launch Graph Builder.
7. Set graph size.
8. Hide control panel.
9. Define variables for graph.
10. Add area element with overlay.

Example 5

Summary: Selects and subsets a data table, followed by the configuration of a Graph Builder to visualize variables.

Code:

dt = Open("data_table.jmp");
dt << Get Rows Where();
For( i = 1, i <= 40, i += 2,
    Selected( Row State( i ) ) = 1
);
dt << Subset( Output Table( "BigClassSubset" ), Selected Rows( 1 ), selected
columns( 0 ), Link to original data table( 1 ) );
dt << Clear Select;
Graph Builder(
    Size( 534, 464 ),
    Show Control Panel( 0 ),
    Variables( X( :sex ), X( :age, Position( 1 ) ), Y( :height ), Y( :weight, Position( 1 ) ), Overlay( :weight ) ),
    Elements( Area( X( 1 ), X( 2 ), Y( 1 ), Y( 2 ), Legend( 36 ) ) )
);

Code Explanation:

1. Open data table;
2. Get all row indices.
3. Loop through rows 1 to 40.
4. Select every second row.
5. Create subset table "BigClassSubset".
6. Unselect all rows.
7. Initialize Graph Builder.
8. Set graph size.
9. Hide control panel.
10. Define variables and elements for graph.

Example 6

Summary: Selects and subsets a data table, followed by the configuration of a Graph Builder to visualize height and weight data with interactive filtering capabilities.

Code:

dt = Open("data_table.jmp");
dt << Get Rows Where();
For( i = 1, i <= 40, i += 2,
    Selected( Row State( i ) ) = 1
);
dt << Subset( Output Table( "BigClassSubset" ), Selected Rows( 1 ), selected
columns( 0 ) );
Graph Builder(
    Size( 534, 464 ),
    Show Control Panel( 0 ),
    Variables( X( :sex ), X( :age, Position( 1 ) ), Y( :height ), Y( :weight, Position( 1 ) ), Overlay( :weight ) ),
    Elements( Bar( X( 1 ), X( 2 ), Y( 1 ), Y( 2 ), Legend( 69 ) ) ),
    Local Data Filter(
        Mode( Include( 0 ) ),
        Inverse( 1 ),
        Add Filter( columns( :age ), Where( :age == {14, 15, 16} ), Display( :age, Size( 160, 90 ), List Display ) )
    )
);

Code Explanation:

1. Open data table.
2. Get all rows where.
3. Select every second row.
4. Create subset table.
5. Initialize Graph Builder.
6. Set graph size.
7. Hide control panel.
8. Define variables for axes.
9. Add bar elements.
10. Apply local data filter.

Example 7

Summary: Subsets data and graphing for females in a JMP data table, utilizing Graph Builder and Local Data Filters to visualize cholesterol levels.

Code:

dt = Open("data_table.jmp");
dt << Get Rows Where();
For( i = 60, i <= 90, i++,
    Selected( Row State( i ) ) = 1
);
dt << Subset( Output Table( "Linked Subset" ), Selected Rows( 1 ), selected
columns( 0 ), Link to original data table( 1 ) );
dt << Clear Select;
Graph Builder(
    Size( 534, 472 ),
    Show Control Panel( 0 ),
    Variables( X( :Alcohol use ), X( :Heart History, Position( 1 ) ), Y( :Cholesterol ) ),
    Elements( Bar( X( 1 ), X( 2 ), Y, Legend( 7 ) ) ),
    Local Data Filter( Mode( Include( 0 ) ), Add Filter( columns( :Sex ), Where( :Sex == "female" ) ) )
);
Graph Builder(
    Size( 534, 472 ),
    Show Control Panel( 0 ),
    Variables( X( :Alcohol use ), X( :Heart History, Position( 1 ) ), Y( :Cholesterol ) ),
    Elements( Bar( X( 1 ), X( 2 ), Y, Legend( 7 ) ) ),
    Local Data Filter( Mode( Include( 1 ) ), Add Filter( columns( :Sex ), Where( :Sex == "female" ) ) )
);
Graph Builder(
    Size( 534, 472 ),
    Show Control Panel( 0 ),
    Variables( X( :Alcohol use ), X( :Heart History, Position( 1 ) ), Y( :Cholesterol ) ),
    Elements( Bar( X( 1 ), X( 2 ), Y, Legend( 7 ) ) ),
    Local Data Filter( Inverse( 1 ), Mode( Include( 0 ) ), Add Filter( columns( :Sex ), Where( :Sex == "female" ) ) )
);
Graph Builder(
    Size( 534, 472 ),
    Show Control Panel( 0 ),
    Variables( X( :Alcohol use ), X( :Heart History, Position( 1 ) ), Y( :Cholesterol ) ),
    Elements( Bar( X( 1 ), X( 2 ), Y, Legend( 7 ) ) ),
    Local Data Filter( Inverse( 1 ), Mode( Include( 1 ) ), Add Filter( columns( :Sex ), Where( :Sex == "female" ) ) )
);

Code Explanation:

1. Open data table.
2. Select rows 60-90.
3. Create linked subset.
4. Clear row selection.
5. Create bar graph for females.
6. Create bar graph for females.
7. Create inverse bar graph for females.
8. Create inverse bar graph for females.

Example 8

Summary: Selects and visualizes data from a JMP data table, using Graph Builder to create a bar chart with interval style.

Code:

dt = Open("data_table.jmp");
dt << Get Rows Where();
For( i = 1, i <= 12, i++,
    Selected( Row State( i ) ) = 1
);
For( i = 33, i <= 40, i++,
    Selected( Row State( i ) ) = 1
);
dt << Graph Builder(
    Size( 323, 335 ),
    Show Control Panel( 0 ),
    Show Legend( 0 ),
    Variables( X( :sex ), Y( :height ), Overlay( :age ) ),
    Elements( Bar( X, Y, Legend( 4 ), Bar Style( "Interval" ) ) )
);

Code Explanation:

1. Open data table.
2. Retrieve all row indices.
3. Select rows 1-12.
4. Select rows 33-40.
5. Create Graph Builder window.
6. Set window size.
7. Hide control panel.
8. Hide legend.
9. Assign variables: X=sex, Y=height, Overlay=age.
10. Add bar element with interval style.

Example 9

Summary: Selects and subsets a data table, followed by the generation of a graph with interactive filters.

Code:

dt = Open("data_table.jmp");
dt << Get Rows Where();
For( i = 1, i <= 40, i += 2,
    Selected( Row State( i ) ) = 1
);
dt << Subset( Output Table( "BigClassSubset" ), Selected Rows( 1 ), selected columns( 0 ), Link to original data table( 1 ) );
dt << Clear Select;

Graph Builder(
    Size( 817, 420 ),
    Show Control Panel( 0 ),
    Legend Position( "Bottom" ),
    Variables( X( :sex ), X( :age, Position( 1 ) ), Y( :height ), Y( :weight, Position( 1 ) ), Overlay( :weight ) ),
    Elements( Bar( X( 1 ), X( 2 ), Y( 1 ), Y( 2 ), Legend( 69 ) ) ),
    Local Data Filter(
        Width( 160 ),
        Mode( Include( 0 ) ),
        Inverse( 1 ),
        Add Filter( columns( :age ), Where( :age == {14, 15, 16} ), Display( :age, N Items( 4 ) ) )
    ),
    SendToReport( Dispatch( {}, "400", LegendBox, {Orientation( "Horizontal" ), Sides( "Left" ), Set Wrap( 3 )} ) )
);

Code Explanation:

1. Open data table.
2. Get all rows.
3. Select every second row.
4. Create subset table.
5. Clear selections.
6. Initialize Graph Builder.
7. Set graph size.
8. Hide control panel.
9. Set legend position.
10. Define variables and elements.

Example 10

Summary: Selects and subsets a data table, followed by the configuration of a Graph Builder to visualize relationships between variables.

Code:

dt = Open("data_table.jmp");
dt << Get Rows Where();
For( i = 1, i <= 40, i += 2,
    Selected( Row State( i ) ) = 1
);
dt << Subset( Output Table( "BigClassSubset" ), Selected Rows( 1 ), selected
columns( 0 ), Link to original data table( 1 ) );
dt << Clear Select;
Graph Builder(
    Size( 534, 464 ),
    Show Control Panel( 0 ),
    Variables( X( :sex ), X( :age, Position( 1 ) ), Y( :height ), Y( :weight, Position( 1 ) ), Overlay( :weight ) ),
    Elements( Bar( X( 1 ), X( 2 ), Y( 1 ), Y( 2 ), Legend( 58 ) ) ),
    Local Data Filter( Mode( Include( 0 ) ), Add Filter( columns( :height ), Where( :height >= 59.2 & :height <= 69 ) ) )
);

Code Explanation:

1. Open data table.
2. Get all row indices.
3. Loop through rows 1 to 40.
4. Select every second row.
5. Create subset table.
6. Clear selection from original table.
7. Initialize Graph Builder.
8. Set size and hide control panel.
9. Define variables for graph.
10. Add bar elements and local data filter.

Example 11

Summary: Selects specific rows in a data table and generates a graph using Graph Builder to visualize the relationship between Profit, Type, and Sales.

Code:

dt = Open("data_table.jmp");
dt << Get Rows Where();
Selected( Row State( 16 ) ) = 1;
Selected( Row State( 23 ) ) = 1;
Selected( Row State( 24 ) ) = 1;
Selected( Row State( 25 ) ) = 1;
Selected( Row State( 26 ) ) = 1;
Selected( Row State( 27 ) ) = 1;
Selected( Row State( 28 ) ) = 1;
Selected( Row State( 34 ) ) = 1;
Selected( Row State( 35 ) ) = 1;
Selected( Row State( 40 ) ) = 1;
Selected( Row State( 60 ) ) = 1;
Selected( Row State( 61 ) ) = 1;
Selected( Row State( 62 ) ) = 1;
Selected( Row State( 65 ) ) = 1;
Selected( Row State( 67 ) ) = 1;
Selected( Row State( 68 ) ) = 1;
Selected( Row State( 70 ) ) = 1;
Selected( Row State( 74 ) ) = 1;
Selected( Row State( 75 ) ) = 1;
Selected( Row State( 88 ) ) = 1;
Selected( Row State( 91 ) ) = 1;
Selected( Row State( 92 ) ) = 1;
Selected( Row State( 93 ) ) = 1;
Selected( Row State( 94 ) ) = 1;
Selected( Row State( 96 ) ) = 1;
dt << Graph Builder(
    Size( 300, 511 ),
    Show Control Panel( 0 ),
    Variables( X( :"Profit($M)"n ), Y( :Type ), Group Y( :"Sales($M)"n ) ),
    Elements( Bar( X, Y, Legend( 7 ) ) )
);

Code Explanation:

1. Open data table;
2. Select specified rows.
3. Create Graph Builder object.
4. Set graph size.
5. Hide control panel.
6. Define X variable.
7. Define Y variable.
8. Define Group Y variable.
9. Add bar element.
10. Display graph.

Example 12

Summary: Creates a graph builder with specific variables and settings, including hiding control panels and legends.

Code:

dt = Open("data_table.jmp");
dt << Get Rows Where();
Selected( Row State( 38 ) ) = 1;
dt << Graph Builder(
    Size( 359, 251 ),
    Show Control Panel( 0 ),
    Show Legend( 0 ),
    Variables( X( :sex ), Y( :height ), Y( :weight, Position( 1 ) ), Overlay( :age ) ),
    Elements( Bar( X, Y( 1 ), Y( 2 ), Legend( 7 ), Bar Style( "Interval" ), Summary Statistic( "Range" ) ) )
);

Code Explanation:

1. Open data table.
2. Select row 38.
3. Create Graph Builder.
4. Set graph size.
5. Hide control panel.
6. Hide legend.
7. Assign variables: X(sex), Y(height), Y(weight), Overlay(age).
8. Add bar element.
9. Set bar style to interval.
10. Use range summary statistic.

Example 13

Summary: Creates and filters a bar graph in JMP, showcasing data for males and females, with interactive filters to exclude or include specific subsets.

Code:

dt = Open("data_table.jmp");
dt << Get Rows Where();
For( i = 1, i <= 8, i++,
    Selected( Row State( i ) ) = 1
);
dt << Subset( Output Table( "Linked Subset" ), Selected Rows( 1 ), selected
columns( 0 ), Link to original data table( 1 ) );
dt << Clear Select;
Graph Builder(
    Size( 453, 346 ),
    Show Control Panel( 0 ),
    Variables( X( :name ), Y( :height ) ),
    Elements( Bar( X, Y, Legend( 4 ) ) ),
    Local Data Filter( Width( 130 ), Mode( Include( 0 ) ), Add Filter( columns( :sex ), Where( :sex == "M" ) ) )
);
Graph Builder(
    Size( 453, 346 ),
    Show Control Panel( 0 ),
    Variables( X( :name ), Y( :height ) ),
    Elements( Bar( X, Y, Legend( 4 ) ) ),
    Local Data Filter( Width( 130 ), Mode( Include( 1 ) ), Add Filter( columns( :sex ), Where( :sex == "M" ) ) )
);
Graph Builder(
    Size( 453, 346 ),
    Show Control Panel( 0 ),
    Variables( X( :name ), Y( :height ) ),
    Elements( Bar( X, Y, Legend( 4 ) ) ),
    Local Data Filter( Width( 130 ), Mode( Include( 0 ) ), Add Filter( columns( :sex ), Where( :sex == "M" ) ) )
);
Graph Builder(
    Size( 453, 346 ),
    Show Control Panel( 0 ),
    Variables( X( :name ), Y( :height ) ),
    Elements( Bar( X, Y, Legend( 4 ) ) ),
    Local Data Filter( Width( 130 ), Mode( Include( 1 ) ), Inverse( 1 ), Add Filter( columns( :sex ), Where( :sex == "M" ) ) )
);
Graph Builder(
    Size( 453, 346 ),
    Show Control Panel( 0 ),
    Variables( X( :name ), Y( :height ) ),
    Elements( Bar( X, Y, Legend( 4 ) ) ),
    Local Data Filter( Width( 130 ), Mode( Include( 0 ) ), Inverse( 1 ), Add Filter( columns( :sex ), Where( :sex == "M" ) ) )
);

Code Explanation:

1. Open data table;
2. Select first 8 rows.
3. Create "Linked Subset" table.
4. Clear row selection.
5. Create bar graph for all data.
6. Create bar graph for males, include filter.
7. Create bar graph for all data.
8. Create bar graph for males, exclude filter.
9. Create bar graph for all data.
10. Create bar graph for males, exclude filter, inverse selection.

Example 14

Summary: Selects and subsets a data table, followed by the generation of a bar graph to visualize the sum of 'height' values grouped by 'sex'.

Code:

dt = Open("data_table.jmp");
dt << Get Rows Where();
For( i = 1, i <= 15, i++,
    Selected( Row State( i ) ) = 1
);
dt << Subset( Output Table( "Linked Subset" ), Selected Rows( 1 ), selected
columns( 0 ), Link to original data table( 1 ) );
dt << Clear Select;
Graph Builder(
    Size( 634, 390 ),
    Show Control Panel( 0 ),
    Variables( X( :sex ), Y( :height ) ),
    Elements( Bar( X, Y, Legend( 4 ), Summary Statistic( "Sum" ), Label( "Label by Percent of Total Values" ) ) )
);

Code Explanation:

1. Open data table.
2. Get all row indices.
3. Loop through first 15 rows.
4. Select each row.
5. Create subset table.
6. Clear selections from original table.
7. Initialize Graph Builder.
8. Set graph size.
9. Hide control panel.
10. Define X and Y variables.
11. Add bar element.
12. Summarize by sum.
13. Label by percent of total.

Example 15

Summary: Runs the selection and subset creation process for a data table, followed by the configuration of Graph Builder to visualize airport data.

Code:

dt = Open("data_table.jmp");
dt << Get Rows Where();
For( i = 1, i <= 2500, i++,
    Selected( Row State( i ) ) = 1
);
dt << Subset( Output Table( "Linked Subset" ), Selected Rows( 1 ), selected
columns( 0 ), Link to original data table( 1 ) );
dt << Clear Select;
Graph Builder(
    Size( 846, 452 ),
    Show Control Panel( 0 ),
    Variables( X( :Airport ), X( :Airline, Position( 1 ) ), Y( :Time ) ),
    Elements( Line( X( 1 ), X( 2 ), Y, Legend( 6 ), Summary Statistic( "% of Total" ) ) )
);

Code Explanation:

1. Open data table;
2. Get all rows from the table.
3. Loop through first 2500 rows.
4. Select each row.
5. Create subset table with selected rows.
6. Clear selection from original table.
7. Initialize Graph Builder.
8. Set graph size.
9. Hide control panel.
10. Define variables for X and Y axes.

Example 16

Summary: Selects and visualizes a subset of data from a JMP data table, using Graph Builder to create a line graph with multiple series.

Code:

dt = Open("data_table.jmp");
dt << Get Rows Where();
For( i = 50, i <= 62, i++,
    Selected( Row State( i ) ) = 1
);
dt << Subset( Output Table( "Linked Subset" ), Selected Rows( 1 ), selected
columns( 0 ), Link to original data table( 1 ) );
dt << Clear Select;
Graph Builder(
    Size( 403, 513 ),
    Show Control Panel( 0 ),
    Include Missing Categories( 1 ),
    Variables(
        X( :YearWeek ),
        Y( :Name( "Adj. Close*" ) ),
        Y( :High, Position( 1 ) ),
        Y( :Low, Position( 1 ) ),
        Y( :Close, Position( 1 ) )
    ),
    Elements( Line( X, Y( 1 ), Y( 2 ), Y( 3 ), Y( 4 ), Legend( 15 ), Stack( 1 ), Fill( "Fill Below" ) ) )
);

Code Explanation:

1. Open data table;
2. Get all rows.
3. Select rows 50 to 62.
4. Create subset table.
5. Clear row selection.
6. Initiate Graph Builder.
7. Set size 403x513.
8. Hide control panel.
9. Include missing categories.
10. Define variables and elements.

Example 17

Summary: Subsets data and graphing to visualize stock market trends, utilizing Graph Builder for line and area plots.

Code:

dt = Open("data_table.jmp");
dt << Get Rows Where();
For( i = 50, i <= 62, i++,
    Selected( Row State( i ) ) = 1
);
dt << Subset( Output Table( "Linked Subset" ), Selected Rows( 1 ), selected
columns( 0 ), Link to original data table( 1 ) );
dt << Clear Select;
Graph Builder(
    Size( 628, 513 ),
    Show Control Panel( 0 ),
    Include Missing Categories( 1 ),
    Variables(
        X( :YearWeek ),
        Y( :Name( "Adj. Close*" ) ),
        Y( :High, Position( 1 ) ),
        Y( :Low, Position( 1 ) ),
        Y( :Close, Position( 1 ) )
    ),
    Elements(
        Line(
            X,
            Y( 1 ),
            Y( 2 ),
            Y( 3 ),
            Y( 4 ),
            Legend( 18 ),
            Summary Statistic( "Sum" ),
            Interval Style( "Band" ),
            Missing Factors( "Treat as Missing" )
        )
    )
);
Graph Builder(
    Size( 628, 513 ),
    Show Control Panel( 0 ),
    Variables(
        X( :YearWeek ),
        Y( :Name( "Adj. Close*" ) ),
        Y( :High, Position( 1 ) ),
        Y( :Low, Position( 1 ) ),
        Y( :Close, Position( 1 ) )
    ),
    Elements(
        Area(
            X,
            Y( 1 ),
            Y( 2 ),
            Y( 3 ),
            Y( 4 ),
            Legend( 19 ),
            Area Style( "Overlaid" ),
            Summary Statistic( "Sum" ),
            Missing Factors( "Treat as Zero" )
        )
    )
);

Code Explanation:

1. Open data table;
2. Get all rows.
3. Select rows 50 to 62.
4. Create "Linked Subset" table.
5. Clear selection.
6. Build first graph: Line plot.
7. Set X axis to YearWeek.
8. Set Y axes to Adj. Close*, High, Low, Close.
9. Build second graph: Area plot.
10. Configure area plot similarly.

Graph Builder using Value Labels

Example 1

Summary: Vizualizes sex distribution by age using Graph Builder, setting value labels and missing value codes for the sex variable.

Code:

dt = Open("data_table.jmp");
:sex << Value Labels( {"F" = "Female", "M" = "Male"} );
:sex << use Value Labels( 1 );
:sex << set property( "missing value codes", {"F"} );
Graph Builder( Size( 549, 400 ), Show Control Panel( 0 ), Variables( X( :age ), Y( :sex ) ), Elements( Area( X, Y, Legend( 16 ) ) ) );

Code Explanation:

1. Open table.
2. Set value labels for sex.
3. Use value labels for sex.
4. Set missing value codes for sex.
5. Create Graph Builder.
6. Set size of Graph Builder.
7. Hide control panel.
8. Set X variable to age.
9. Set Y variable to sex.
10. Add area element.

Example 2

Summary: Vizualizes sex distribution by age using Graph Builder, with interactive features for value labels and missing value codes.

Code:

Open("data_table.jmp");
:sex << Value Labels( {"F" = "Female", "M" = "Male"} );
:sex << use Value Labels( 1 );
:sex << set property( "missing value codes", {"F"} );
Graph Builder( Size( 549, 400 ), Show Control Panel( 0 ), Variables( X( :age ), Y( :sex ) ), Elements( Area( X, Y, Legend( 16 ) ) ) );

Code Explanation:

1. Open data table;
2. Set value labels for sex.
3. Enable value labels for sex.
4. Set missing value codes for sex.
5. Create Graph Builder window.
6. Disable control panel.
7. Set X variable to age.
8. Set Y variable to sex.
9. Add area element to graph.
10. Assign legend to area element.

Example 3

Summary: Creates a bar graph to visualize sex distribution, utilizing Graph Builder and setting value labels for missing values.

Code:

Open("data_table.jmp");
:sex << Value Labels( {"F" = "Female", "M" = "Male"} );
:sex << use Value Labels( 1 );
:sex << set property( "missing value codes", {"F"} );
Graph Builder( show control panel( 0 ), Variables( X( :sex ) ), elements( Bar( X, Label( "Label by Value" ) ) ) );

Code Explanation:

1. Open data table;
2. Set value labels for sex.
3. Enable value labels for sex.
4. Set missing value codes for sex.
5. Create graph builder.
6. Hide control panel.
7. Set X variable to sex.
8. Add bar element.
9. Label bars by value.
10. Display graph.

Graph Builder using Data Table

Example 1

Summary: Creates a linked subset from the 'data_table.jmp' data table, grouping by 'sex', and generates a bar graph to visualize the relationship between 'weight', 'height', and 'age'.

Code:

dt = Open("data_table.jmp");
Data Table("data_table") << Subset(
    Output Table( "Linked Subset" ),
    Linked,
    Suppress formula evaluation( 0 ),
    By( :sex ),
    All rows,
    Selected columns only( 0 ),
    columns( :name, :age, :height, :weight )
);
Graph Builder(
    Size( 634, 402 ),
    Show Control Panel( 0 ),
    Variables( X( :weight ), Y( :height ), Color( :age ) ),
    Elements( Bar( X, Y, Legend( 9 ), Label( "Label by Value" ) ) )
);

Code Explanation:

1. Open data table.
2. Create linked subset.
3. Set output table name.
4. Link subset to original.
5. Evaluate formulas normally.
6. Group by sex.
7. Include all rows.
8. Include all columns.
9. Initialize Graph Builder.
10. Set window size.
11. Hide control panel.
12. Assign variables: X, Y, Color.
13. Add bar element.
14. Configure legend position.
15. Label by value.

Example 2

Summary: Creates a graph builder object to visualize relationships between Development Level, Literacy Rate, and Life Expectancy Ranking using Bar element with summary statistic Sum.

Code:

dt = Open("data_table.jmp");
myRows = dt << select all rows;
mydt = Data Table("data_table") << Subset( myRows );
mydt << Graph Builder(
    Size( 720, 408 ),
    Show Control Panel( 0 ),
    Variables( X( :Development Level ), Y( :Literacy Rate ), Overlay( :Life Expectancy Ranking ) ),
    Elements( Bar( X, Y, Legend( 5 ), Summary Statistic( "Sum" ), Label( "Label by Value" ) ) )
);

Code Explanation:

1. Open data table.
2. Select all rows.
3. Subset data table.
4. Create Graph Builder object.
5. Set size to 720x408.
6. Hide control panel.
7. Assign variables: X, Y, Overlay.
8. Add Bar element.
9. Set summary statistic to Sum.
10. Label by value.

Example 3

Summary: Creates a scatter plot to visualize the relationship between age and height, with a local data filter applied to focus on specific age groups.

Code:

Open("data_table.jmp");
Data Table("data_table") << Clear Select << Select Rows( [1] ) << Hide;
Graph Builder(
    Size( 524, 444 ),
    Show Control Panel( 0 ),
    Variables( X( :age ), Y( :height ) ),
    Elements( Points( X, Y, Legend( 3 ), Summary Statistic( "N" ) ) ),
    Local Data Filter(
        Add Filter( columns( :age ), Where( :age == {14, 12, 13, 16, 17} ), Display( :age, N Items( 6 ) ), Order By Count( :age ) )
    )
);

Code Explanation:

1. Open data table.
2. Clear and select first row.
3. Hide selected row.
4. Create Graph Builder window.
5. Set window size.
6. Hide control panel.
7. Set X and Y variables.
8. Add points element.
9. Enable local data filter.
10. Define filter criteria for age.

Example 4

Summary: Creates a scatter plot to visualize the relationship between height and weight, with specified spec limits for both variables.

Code:

Open("data_table.jmp");
Data Table("data_table"):weight << Set Property( "Spec Limits", {LSL( 0 ), USL( 200 ), Show Limits( 1 )} );
Data Table("data_table"):height << Set Property( "Spec Limits", {LSL( 40 ), USL( 80 ), Show Limits( 1 )} );
Data Table("data_table") << Graph Builder(
    Size( 526, 449 ),
    Show Control Panel( 0 ),
    Variables( X( :height ), Y( :weight ) ),
    Elements( Smoother( X, Y, Legend( 4 ) ), Points( X, Y, Legend( 5 ) ) )
);

Code Explanation:

1. Open data table;
2. Set weight spec limits.
3. Set height spec limits.
4. Launch Graph Builder.
5. Set window size.
6. Hide control panel.
7. Add height to X-axis.
8. Add weight to Y-axis.
9. Add smoother element.
10. Add points element.

Example 5

Summary: Creates a heatmap visualization using Graph Builder, grouping variables by Causality and Body System or Organ Class, with Recovery as the y-axis.

Code:

dt = Open("data_table.jmp") << subset( link to original data table( 1 ), by( "Domain Abbreviation" ) );
myDt = Data Table("data_table");
Graph Builder(
    Size( 558, 322 ),
    Show Control Panel( 0 ),
    Show Legend( 0 ),
    Variables(
        Group X( :Causality, Combine( "Merged" ) ),
        Group Y( :Recovery ),
        Color( :Body System or Organ Class, Combine( "Merged" ) )
    ),
    Elements( Heatmap( Legend( 26 ) ) )
);

Code Explanation:

1. Open data table;
2. Subset data by Domain Abbreviation.
3. Select DM domain.
4. Create Graph Builder.
5. Set window size.
6. Hide control panel.
7. Hide legend.
8. Set group X variable.
9. Set group Y variable.
10. Set color variable.

Example 6

Summary: Vizualizes Gross State Product data using Graph Builder, with interactive features for customizing legend properties and positioning state labels.

Code:

Open("data_table.jmp");
Data Table("data_table"):Population << Label( 1 );
Data Table("data_table") << Select All Rows << Label;
Graph Builder(
    Size( 534, 461 ),
    Show Control Panel( 0 ),
    Variables( Size( :Gross State Product, Summary Statistic( "% of Total" ) ), Shape( :State ) ),
    Elements( Map Shapes( Legend( 11 ) ) ),
    SendToReport(
        Dispatch( {}, "", ScaleBox, {Min( -78.7899609192314 ), Max( -70.3093073919842 ), Inc( 2 ), Minor Ticks( 0 )} ),
        Dispatch( {}, "", ScaleBox( 2 ), {Min( 36.7307879175252 ), Max( 43.8487994403944 ), Inc( 2 ), Minor Ticks( 1 )} ),
        Dispatch( {}, "400", ScaleBox,
            {Legend Model(
                11,
                Properties( 0, {Line Color( 20 ), Line Width( 3 )}, Item ID( "Gross State Product", 1 ) ),
                Properties( -1, {Line Color( 21 ), Line Width( 3 )}, Item ID( "Alabama", 1 ) )
            )}
        ),
        Dispatch( {}, "Graph Builder", FrameBox,
            {DispatchSeg(
                Shape Seg( 1 ),
                {Label Position( 6, -72.1489605451882, 39.2204204069783 ), Label Position( 7, -74.2246594632342, 37.3971661910754 ),
                Label Position( 20, -75.642039232941, 36.9972683758876 ), Label Position( 21, -68.3490506719053, 42.7750562023208 ),
                Label Position( 30, -72.9344667148594, 38.2981707244423 ), Label Position( 32, -78.6149379845478, 44.6184718696499 ),
                Label Position( 38, -80.3353563262466, 43.758441529048 ), Label Position( 39, -69.1046110790501, 38.6934658487624 ),
                Label Position( 45, -74.0716741641175, 46.0421686790949 ), Label Position( 48, -81.2266982298494, 42.8230153639912 )}
            )}
        )
    )
);

Code Explanation:

1. Open data table.
2. Label Population column.
3. Select all rows.
4. Create Graph Builder.
5. Set graph size.
6. Hide control panel.
7. Define variables for graph.
8. Add map shapes element.
9. Configure X-axis scale.
10. Configure Y-axis scale.
11. Customize legend properties.
12. Position state labels.

Example 7

Summary: Vizualizes data by color-marking and graphing variables, utilizing Graph Builder to create an interactive plot.

Code:

Open("data_table.jmp");
Data Table("data_table") << Color or Mark by Column( :age, Color( 0 ), Marker Theme( "Hollow" ) );
Data Table("data_table") << Graph Builder(
    Show Control Panel( 0 ),
    Variables( X( :height ), Y( :weight ), Overlay( :age ), Color( :sex ) ),
    Elements( Points( X, Y, Legend( 2 ) ) )
);

Code Explanation:

1. Open data table;
2. Set color and marker theme.
3. Create Graph Builder.
4. Hide control panel.
5. Set X and Y variables.
6. Add overlay variable.
7. Add color variable.
8. Add points element.
9. Configure legend.
10. Display graph.

Example 8

Summary: Vizualizes a scatter plot with color-coded markers to represent sex, using Graph Builder and custom legend settings.

Code:

Open("data_table.jmp");
Data Table("data_table"):sex << Set Property( "Value Colors", {"F" = "Very Dark Gray", "M" = "Plain Gray"} );
Graph Builder(
    Size( 630, 457 ),
    Variables( X( :weight ), Color( :sex ) ),
    Elements( Points( X, Legend( 13 ) ) ),
    SendToReport(
        Dispatch( {}, "400", ScaleBox,
            {Legend Model(
                13,
                Type Properties( 0, "Marker", {Marker Size( 15 )} ),
                Properties( 0, {Marker Size( 15 )}, Item ID( "F", 1 ) ),
                Properties( 1, {Marker Size( 15 )}, Item ID( "M", 1 ) )
            )}
        )
    )
);

Code Explanation:

1. Open data table.
2. Set sex value colors.
3. Launch Graph Builder.
4. Set graph size.
5. Define X variable.
6. Define color variable.
7. Add points element.
8. Customize legend.
9. Adjust marker size.
10. Finalize report settings.

Graph Builder using Select rows

Summary: Prepares data and visualization by opening a data table, selecting specific rows, setting height values to missing, reordering age values, and creating a graph with a bar chart.

Code:

dt = Open("data_table.jmp");
dt << Select rows( [11, 12, 13, 14, 15, 16, 17, 18, 19, 20] );
dt << exclude << clear select;
dt:height[9] = :height[10] = :height[11] = .;
dt:age << Set Property( "Value Ordering", {12, 13, 14, 16, 17, 15} );
Graph Builder(
    Size( 534, 452 ),
    Show Control Panel( 0 ),
    Variables( X( :weight ), Y( :age ) ),
    Elements( Bar( X, Y, Legend( 16 ) ) ),
    Local Data Filter( Add Filter( columns( :height ) ) )
);

Code Explanation:

1. Open data table.
2. Select specified rows.
3. Exclude selected rows.
4. Clear row selection.
5. Set height values to missing.
6. Reorder age values.
7. Create Graph Builder.
8. Set graph size.
9. Hide control panel.
10. Define variables and elements.

Graph Builder using Select where

Example 1

Summary: Creates a bar chart to visualize AGS reports, using Graph Builder to set variables and plot data.

Code:

dt = Open("data_table.jmp");
dt << Select where( :Report == "AGS" );
dt2 = dt << Subset( Selected Rows, link to original data table( 1 ) );
dt2 << Clear Selected Row States;
dt2 << Graph Builder(
    Size( 277, 251 ),
    Show Control Panel( 0 ),
    Variables( X( :Color ), Y( :Depth ), Y( :Table, Position( 1 ) ), Overlay( :Cut ) ),
    Elements( Bar( X, Y( 1 ), Y( 2 ), Legend( 8 ), Bar Style( "Range" ), Summary Statistic( "Max" ) ) )
);

Code Explanation:

1. Open data_table data
2. Select AGS reports.
3. Subset selected rows.
4. Clear selection states.
5. Create Graph Builder.
6. Set graph size.
7. Hide control panel.
8. Define X and Y variables.
9. Add overlay variable.
10. Plot bar chart.

Example 2

Summary: Creates a histogram to visualize height data for individuals aged 12, utilizing Graph Builder and customizing scale box settings.

Code:

dt = Open("data_table.jmp");
dt << Select where( :age == 12 );
dt << Graph Builder(
    Size( 528, 456 ),
    Show Control Panel( 0 ),
    Variables( X( :height ) ),
    Elements( Histogram( X, Legend( 3 ), Histogram Style( "Shadowgram" ) ) ),
    SendToReport( Dispatch( {}, "", ScaleBox, {Min( -2 ), Max( 13 ), Inc( 2 ), Minor Ticks( 0 )} ) )
);

Code Explanation:

1. Open data table.
2. Select rows where age is 12.
3. Launch Graph Builder.
4. Set graph size to 528x456.
5. Hide control panel.
6. Add height variable to X axis.
7. Add histogram element.
8. Set histogram style to Shadowgram.
9. Customize scale box settings.
10. Send report to dispatch.

Example 3

Summary: Creates a geographic map to visualize data from Detroit, utilizing Graph Builder and specifying custom scale formats for longitude and latitude.

Code:

dt = Open("data_table.jmp");
dt << Select where( :city == "DETROIT" );
Graph Builder(
    Size( 875, 523 ),
    Show Control Panel( 0 ),
    Variables( Shape( :State ) ),
    Elements( Map Shapes( Legend( 8 ) ) ),
    SendToReport(
        Dispatch( {}, "", ScaleBox,
            {Format( "Longitude DDD", "PUNDIR", 16 ), Min( -125.402881994996 ), Max( -69.5971180050041 ), Inc( 10 ), Minor Ticks( 0 )}
        ),
        Dispatch( {}, "", ScaleBox( 2 ), {Min( 23.9506963674023 ), Max( 55 ), Inc( 5 ), Minor Ticks( 0 )} )
    )
);

Code Explanation:

1. Open data table;
2. Select Detroit city.
3. Launch Graph Builder.
4. Set graph size.
5. Hide control panel.
6. Define shape variable.
7. Add map shapes element.
8. Format longitude scale.
9. Set longitude range.
10. Format latitude scale.

Graph Builder using GraphBuilder

Summary: Creates two Graph Builder windows with transformed data, displaying points and caption boxes for expenditure and student/faculty ratio analysis by region.

Code:

Open("data_table.jmp");
GraphBuilder(
    Size( 528, 500 ),
    Show Control Panel( 0 ),
    Variables(
        X( Transform Column( "SAT Verbal+SAT Math", Formula( :SAT Verbal + :SAT Math ) ) ),
        Y( :Name( "Expenditure (1997)" ) ),
        Y( :Name( "Student/Faculty Ratio (1997)" ) ),
        Group X( :Region ),
        Color( :Region )
    ),
    Elements( Position( 1, 1 ), Points( X, Y, Legend( 10 ) ), Caption Box( X, Y, Legend( 12 ), X Position( "Left" ) ) ),
    Elements( Position( 1, 2 ), Points( X, Y, Legend( 11 ) ), Caption Box( X, Y, Legend( 13 ), X Position( "Left" ) ) ),
    SendToReport( Dispatch( {}, "Graph Builder", OutlineBox, {Set Title( "Graph Builder Points/Caption Box with Transform Column" )} ) )
);
Graph Builder(
    Size( 528, 500 ),
    Show Control Panel( 0 ),
    Variables(
        X( Transform Column( "SAT Verbal+SAT Math", Formula( :SAT Verbal + :SAT Math ) ) ),
        Y( :Name( "Expenditure (1997)" ) ),
        Y( :Name( "Student/Faculty Ratio (1997)" ) ),
        Group X( :Region ),
        Color( :Region )
    ),
    Elements( Position( 1, 1 ), Points( X, Y, Legend( 9 ) ), Caption Box( X, Y, Legend( 13 ), X Position( "Left" ) ) ),
    Elements( Position( 1, 2 ), Points( X, Y, Legend( 11 ) ), Caption Box( X, Y, Legend( 14 ), X Position( "Left" ) ) ),
    SendToReport( Dispatch( {}, "Graph Builder", OutlineBox, {Set Title( "Graph Builder Points/Caption Box with Transform Column" )} ) )
);

Code Explanation:

1. Open data table.
2. Create first Graph Builder window.
3. Set window size.
4. Hide control panel.
5. Define X variable.
6. Define Y variables.
7. Group X by Region.
8. Color by Region.
9. Add points element.
10. Add caption box element.
11. Repeat steps 2-10 for second Graph Builder window.

Graph Builder using Preferences

Summary: Configures a Graph Builder object to display a bar chart with hidden axes and titles, utilizing variables sex, height, and weight from data_table.jmp.

Code:

 Preferences( Graph Builder( Show X Axis( 0 ) ) );
 Preferences( Graph Builder( Show Y Axis( 0 ) ) );
 Preferences( Graph Builder( Show X Axis Title( 0 ) ) );
 Preferences( Graph Builder( Show Y Axis Title( 0 ) ) );
Open("data_table.jmp");
Graph Builder(
    Size( 534, 450 ),
    Show Control Panel( 0 ),
    Variables( X( :sex ), Y( :height ), Y( :weight, Position( 1 ) ) ),
    Elements( Bar( X, Y( 1 ), Y( 2 ), Legend( 9 ) ) )
);

Code Explanation:

1. Set Graph Builder preferences.
2. Hide X axis.
3. Hide Y axis.
4. Hide X axis title.
5. Hide Y axis title.
6. Open data_table data
7. Create Graph Builder object.
8. Set size to 534x450.
9. Disable control panel.
10. Define variables X, Y1, Y2.
11. Add bar elements for X, Y1, Y2.

Graph Builder using Where

Summary: Analyze and visualize data for male subjects, generating a graph with both bar and heatmap elements to display height distribution.

Code:

dt = Open("data_table.jmp");
dt << select Where( :sex == "M" );
Graph Builder(
    Size( 534, 448 ),
    Show Control Panel( 0 ),
    Variables( X( :sex ), Y( :height ) ),
    Elements(
        Bar( X, Y, Legend( 1 ), Summary Statistic( "Sum" ), Label( "Label by Percent of Total Values" ) ),
        Heatmap( X, Y, Legend( 2 ) )
    ),
    SendToReport(
        Dispatch( {}, "Graph Builder", FrameBox,
            Add Pin Annotation(
                Seg( BarSeg( 1 ) ),
                Index( {0, 0} ),
                Index Row( {0, 0} ),
                UniqueID( 767260848 ),
                FoundPt( {454, 325} ),
                Origin( {0.0073375262054507, 727.040816326531} )
            )
        )
    )
);

Code Explanation:

1. Open data table;
2. Select rows where sex is "M".
3. Launch Graph Builder.
4. Set graph size to 534x448.
5. Hide control panel.
6. Assign sex to X-axis, height to Y-axis.
7. Add bar element with sum summary statistic.
8. Add heatmap element.
9. Send report to Graph Builder.
10. Add pin annotation to bar segment.

Graph Builder using Clear Select

Summary: Creates a heatmap visualization from a subset of rows in a JMP data table, using Graph Builder to configure scales and display missing categories.

Code:

dt = Open("data_table.jmp");
dt << Clear Row States;
dt << select rows(
    [1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36,
    37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50]
);
mySubset = subset( linked, dt );
mySubset << Clear Select();
mySubset << Graph Builder(
    Size( 403, 402 ),
    Show Control Panel( 0 ),
    Show Legend( 0 ),
    Include Missing Categories( 1 ),
    Variables( X( :Randomized ), Y( :Completed ), Group X( :Mannitol Flag ), Group Y( :Steroids Flag ) ),
    Elements( Heatmap( X, Y, Legend( 16 ) ) ),
    SendToReport(
        Dispatch( {}, "Completed", ScaleBox,
            {Scale( "Linear" ), Format( "Best", 10 ), Min( 0.001 ), Max( 1.2 ), Inc( 1 ), Minor Ticks( 1 )}
        ),
        Dispatch( {}, "400", ScaleBox, {Legend Model( 16, Properties( 0, {gradient} ) )} )
    )
);

Code Explanation:

1. Open data table;
2. Clear row states.
3. Select specific rows.
4. Create subset of selected rows.
5. Clear selection in subset.
6. Launch Graph Builder.
7. Set size and hide control panel.
8. Include missing categories.
9. Define variables for heatmap.
10. Add heatmap element and configure scales.

Graph Builder using Histogram Color

Summary: Creates a histogram graph with customized color and settings, using Graph Builder to visualize data from an open data table.

Code:

Preferences[1] << Set( Histogram Color( "Light Blue" ) );
dt = Open("data_table.jmp");
gb = dt << Graph Builder(
    Size( 534, 492 ),
    Show Control Panel( 0 ),
    Variables( X( :Price ), Wrap( :Cut ) ),
    Elements( Histogram( X, Legend( 5 ) ) )
);

Code Explanation:

1. Set histogram color.
2. Open data table;
3. Create Graph Builder object.
4. Set window size.
5. Hide control panel.
6. Define X variable.
7. Wrap by Cut variable.
8. Add histogram element.
9. Set legend position.
10. Display graph.

Graph Builder using Row Selection

Summary: Data filtering and visualization in JMP, selecting rows where age is not 12, hiding and excluding selected rows, and creating two Graph Builder windows with parallel and marker elements.

Code:

dt = Open("data_table.jmp");
dt << Row Selection( Select Where( :age != 12 ) );
dt << hide and exclude;
dt << select rows( [5] );
Graph Builder(
    Size( 670, 451 ),
    Show Control Panel( 0 ),
    Variables( X( :sex ), X( :height, Position( 1 ) ), X( :weight, Position( 1 ) ), Group X( :sex ), Color( :age ) ),
    Elements( Parallel( X( 1 ), X( 2 ), X( 3 ), Legend( 3 ) ) ), 
);
Graph Builder(
    Size( 670, 451 ),
    Show Control Panel( 0 ),
    Variables( X( :sex ), X( :height, Position( 1 ) ), X( :weight, Position( 1 ) ), Group X( :sex ), Color( :age ) ),
    Elements( Marker( X( 1 ), X( 2 ), X( 3 ), Legend( 3 ) ) ), 
);

Code Explanation:

1. Open data table.
2. Select rows where age is not 12.
3. Hide and exclude selected rows.
4. Select row 5.
5. Create first Graph Builder window.
6. Set window size.
7. Hide control panel.
8. Define variables for graph.
9. Add parallel element to graph.
10. Create second Graph Builder window.
11. Set window size.
12. Hide control panel.
13. Define variables for graph.
14. Add marker element to graph.

Graph Builder using Set Name

Example 1

Summary: Creates a graph with two axes, displaying height and weight data from a JMP data table.

Code:

Open("data_table.jmp");
:height << Set Name( "TC, height" );
:weight << Set Name( "TC, weight" );
gb = Graph Builder(
    Size( 534, 448 ),
    Show Control Panel( 0 ),
    Variables( X( :age ), Y( :Name( "TC, height" ) ), Y( :Name( "TC, weight" ) ) ),
    Elements( Position( 1, 1 ), Points( X, Y, Legend( 1 ) ) ),
    Elements( Position( 1, 2 ), Points( X, Y, Legend( 2 ) ) )
);
Report( gb )[AxisBox( 1 )] << Show Major Grid( 1 );
Report( gb )[AxisBox( 2 )] << Show Major Grid( 1 );

Code Explanation:

1. Open data table.
2. Rename height column.
3. Rename weight column.
4. Create Graph Builder object.
5. Set graph size.
6. Hide control panel.
7. Define X and Y variables.
8. Add first points element.
9. Add second points element.
10. Enable major grid on first axis.
11. Enable major grid on second axis.

Example 2

Summary: Creates a graph builder object to visualize height and weight data, utilizing Graph Builder's Points element and AxisBox properties.

Code:

Open("data_table.jmp");
:height << Set Name( "TC, height" );
:weight << Set Name( "TC, weight" );
gb = Graph Builder(
    Size( 534, 448 ),
    Show Control Panel( 0 ),
    Variables( X( :age ), Y( :Name( "TC, height" ) ), Y( :Name( "TC, weight" ) ) ),
    Elements( Position( 1, 1 ), Points( X, Y, Legend( 1 ) ) ),
    Elements( Position( 1, 2 ), Points( X, Y, Legend( 2 ) ) )
);
Report( gb )[AxisBox( 1 )] << Show Major Grid( 1 );
Report( gb )[AxisBox( 2 )] << Show Major Grid( 1 );
Report( gb )[AxisBox( 3 )] << Show Major Grid( 1 );

Code Explanation:

1. Open data_table data
2. Rename height column.
3. Rename weight column.
4. Create Graph Builder object.
5. Set graph size.
6. Hide control panel.
7. Define X and Y variables.
8. Add first points element.
9. Add second points element.
10. Enable major grid for all axes.

Example 3

Summary: Runs data visualization by creating a Graph Builder object to display height and weight measurements across different age groups, with major grids enabled on all axes.

Code:

dt = Open("data_table.jmp");
:height << Set Name( "TC, height" );
:weight << Set Name( "TC, weight" );
gb = dt << Graph Builder(
    Size( 534, 448 ),
    Show Control Panel( 0 ),
    Variables( X( :age ), Y( :Name( "TC, height" ) ), Y( :Name( "TC, weight" ) ) ),
    Elements( Position( 1, 1 ), Points( X, Y, Legend( 1 ) ) ),
    Elements( Position( 1, 2 ), Points( X, Y, Legend( 2 ) ) )
);
Report( gb )[AxisBox( 1 )] << Show Major Grid( 1 );
Report( gb )[AxisBox( 2 )] << Show Major Grid( 1 );
Report( gb )[AxisBox( 3 )] << Show Major Grid( 1 );
gb << Save Script to Data Table("data_table");

Code Explanation:

1. Open data table.
2. Rename height column.
3. Rename weight column.
4. Create Graph Builder object.
5. Set graph size.
6. Hide control panel.
7. Define X and Y variables.
8. Add first set of points.
9. Add second set of points.
10. Show major grids on all axes.
11. Save script to data table.

Example 4

Summary: Creates and customizes a Graph Builder object to visualize height and weight data, utilizing JMP's Graph Builder platform.

Code:

dt = Open("data_table.jmp");
:height << Set Name( "TC, height" );
:weight << Set Name( "TC, weight" );
gb = dt << Graph Builder(
    Size( 534, 448 ),
    Show Control Panel( 0 ),
    Variables( X( :age ), Y( :Name( "TC, height" ) ), Y( :Name( "TC, weight" ) ) ),
    Elements( Position( 1, 1 ), Points( X, Y, Legend( 1 ) ) ),
    Elements( Position( 1, 2 ), Points( X, Y, Legend( 2 ) ) )
);
Report( gb )[AxisBox( 1 )] << Show Major Grid( 1 );
Report( gb )[AxisBox( 2 )] << Show Major Grid( 1 );
Report( gb )[AxisBox( 3 )] << Show Major Grid( 1 );
gb << Save Script to Data Table("data_table");
dt << Run Script( "My Graph Builder" );

Code Explanation:

1. Open data table.
2. Rename height column.
3. Rename weight column.
4. Create Graph Builder object.
5. Set graph size.
6. Hide control panel.
7. Define X and Y variables.
8. Add first points element.
9. Add second points element.
10. Show major grid on all axes.
11. Save script to data table.
12. Run saved script.

Graph Builder Box

Example 1

Summary: Creates a Graph Builder object with transformed data, adding 'height' to the X role and square root of 'weight' to the Y role.

Code:

dt = Open("data_table.jmp");
gb = dt << graph builder( Show Control Panel( 0 ) );
gbb = Report( gb )[Graph Builder Box( 1 )];
gbb << Add Variable( {:height, Role( "X" )} );
gbb << Add Variable( {Transform Column( "Square Root[weight]", Formula( Sqrt( :weight ) ) ), Role( "Y" )} );

Code Explanation:

1. Open data table;
2. Create Graph Builder object.
3. Hide control panel.
4. Access Graph Builder box.
5. Add "height" to X role.
6. Transform "weight" to square root.
7. Add transformed "weight" to Y role.

Example 2

Summary: Creates a Graph Builder report with a transformed 'weight' variable as Y-axis, utilizing the Square Root transformation.

Code:

dt = Open("data_table.jmp");
gb = dt << graph builder( Show Control Panel( 0 ) );
gbb = Report( gb )[Graph Builder Box( 1 )];
gbb << Add Variable( {:height, Role( "X" )} );
gbb << Add Variable( {Transform Column( "Square Root[weight]", Formula( Sqrt( :weight ) ) ), Role( "Y" )} );
gb << save script to report;

Code Explanation:

1. Open data table.
2. Create Graph Builder object.
3. Hide control panel.
4. Access first Graph Builder box.
5. Add height variable as X.
6. Transform weight to square root.
7. Add transformed weight as Y.
8. Save script to report.

Graph Builder using Data Filter

Example 1

Summary: Vizualizes SAT scores and salary data for specific years, utilizing Graph Builder to create a scatter plot with two smoother elements.

Code:

dt = Open("data_table.jmp");
dt << Data Filter(
    Location( {30, 30} ),
    Add Filter( columns( :Year ), Where( :Year == {1992, 2004} ), Display( :Year, Size( 204, 140 ), List Display ) ),
    Mode( Include( 1 ) )
);
Graph Builder(
    Size( 450, 400 ),
    Show Control Panel( 0 ),
    Variables(
        X( :SAT Verbal ),
        X( :SAT Math, Position( 1 ) ),
        Y( :Name( "Salary (1997)" ), Size( 0, 23 ), Side( "Right" ) ),
        Y( :Name( "% Taking (2004)" ), Position( 1 ), Size( 0, 23 ) ),
        Group X( :Year )
    ),
    Elements( Smoother( X( 1 ), X( 2 ), Y( 2 ), Legend( 7 ) ), Smoother( X( 1 ), X( 2 ), Y( 1 ), Legend( 9 ) ) ),
    SendToReport(
        Dispatch( {}, "400", ScaleBox,
            {Legend Model( 7, Properties( 1, {Line Style( "Dotted" )} ) ), Legend Model(
                9,
                Properties( 0, {Line Color( 4 ), Line Style( "Dashed" ), Line Width( 2 )} ),
                Properties( 1, {Line Color( 8 ), Line Style( "Dashed" ), Line Width( 2 )} )
            )}
        )
    )
);

Code Explanation:

1. Open data table.
2. Apply data filter.
3. Set filter location.
4. Add filter for years.
5. Display filtered years.
6. Initialize Graph Builder.
7. Set graph size.
8. Hide control panel.
9. Define variables for graph.
10. Add smoother elements to graph.

Example 2

Summary: Filter and graph data based on specific conditions, including region selection and population vs. ozone visualization.

Code:

dt = Open("data_table.jmp");
df = dt << Data Filter(
    Location( {702, 150} ),
    Auto clear( 0 ),
    Mode( Select( 0 ), Show( 1 ), Include( 1 ) ),
    Add Filter(
        columns( :State, :Region ),
        Where( :State == "AL" ),
        Where( :Region == "C" ),
        Display( :State, Size( 204, 174 ), List Display )
    )
);
gb = dt << Graph Builder(
    Variables( X( :Name( "pop- m" ) ), Y( :OZONE ) ),
    Elements( Points( X, Y, Legend( 1 ), Jitter( 1 ) ), Smoother( X, Y, Legend( 2 ) ) )
);
Wait( 0 );
If( Host is( windows ),
    regC = Window( "data_table - Graph Builder" )[Text Box( 31 )] << Get text,
    regC = Window( "data_table - Graph Builder" )[Text Box( 31 )] << Get text
);
df << (Filter column( :region ) << Where( :region == "MW" ));
Wait( 0 );
If( Host is( windows ),
    regMW = Window( "data_table - Graph Builder" )[Text Box( 31 )] << Get text,
    regMW = Window( "data_table - Graph Builder" )[Text Box( 31 )] << Get text
);
df << (Filter column( :region ) << Where( :region == "N" ));
Wait( 0 );
If( Host is( windows ),
    regN = Window( "data_table - Graph Builder" )[Text Box( 31 )] << Get text,
    regN = Window( "data_table - Graph Builder" )[Text Box( 31 )] << Get text
);
df << (Filter column( :region ) << Where( :region == "S" ));
Wait( 0 );
If( Host is( windows ),
    regS = Window( "data_table - Graph Builder" )[Text Box( 31 )] << Get text,
    regS = Window( "data_table - Graph Builder" )[Text Box( 31 )] << Get text
);
df << (Filter column( :region ) << Where( :region == "TX" ));
Wait( 0 );
If( Host is( windows ),
    regTX = Window( "data_table - Graph Builder" )[Text Box( 31 )] << Get text,
    regTX = Window( "data_table - Graph Builder" )[Text Box( 31 )] << Get text
);
df << (Filter column( :region ) << Where( :region == "W" ));
Wait( 0 );
If( Host is( windows ),
    regW = Window( "data_table - Graph Builder" )[Text Box( 31 )] << Get text,
    regW = Window( "data_table - Graph Builder" )[Text Box( 31 )] << Get text
);

Code Explanation:

1. Open data table;
2. Create data filter.
3. Set filter location.
4. Configure filter settings.
5. Add filter for State and Region.
6. Build graph with population vs. ozone.
7. Wait for graph to update.
8. Extract regression text for Windows host.
9. Filter data by region MW.
10. Repeat steps 7-8 for regions N, S, TX, W.

Graph Builder using Repeat

Summary: Creates a treemap graph using Graph Builder, with variables defined for sex and age, and sets the title of the graph.

Code:

lgString = Repeat( "Beautiful World! ", 50 );
dt = Open("data_table.jmp");
For( i = 1, i <= 10, i++,
    :sex[i] = lgString
);
obj = Graph Builder(
    Size( 382, 482 ),
    Show Control Panel( 0 ),
    Variables( X( :sex ), X( :age, Position( 1 ) ), Color( :age ) ),
    Elements( Treemap( X( 1 ), X( 2 ), Legend( 18 ), Label Justification( "Left" ), Label Box Size( 7928 ) ) ),
    SendToReport( Dispatch( {}, "Graph Builder", OutlineBox, {Set Title( "Graph Builder: long nesting group label" )} ) )
);

Code Explanation:

1. Define string lgString.
2. Open data table;
3. Loop through first 10 rows.
4. Assign lgString to :sex.
5. Create Graph Builder object.
6. Set graph size.
7. Hide control panel.
8. Define variables for treemap.
9. Add treemap element.
10. Set title of the graph.

Graph Builder using Run Script

Summary: Creates a treemap graph to visualize sex and age relationships, utilizing Graph Builder and hiding the control panel.

Code:

dt = Open("data_table.jmp");
dt << Run Script( "Set Sex Value Labels" );
Graph Builder( Show Control Panel( 0 ), Variables( X( :sex ), X( :age, Position( 1 ) ) ), Elements( Treemap( X( 1 ), X( 2 ) ) ), );

Code Explanation:

1. Open data table.
2. Run "Set Sex Value Labels" script.
3. Create Graph Builder object.
4. Hide control panel.
5. Set X variables: sex, age.
6. Position age on axis 1.
7. Add Treemap element.
8. Assign sex to X1.
9. Assign age to X2.
10. Display graph.

Graph Builder using For Each

Summary: Creates Graph Builder objects with custom presets for a data table, applying each preset to generate various graph types and setting report titles accordingly.

Code:

plat_samples = ["Graph Builder" => {"Heatmap with Hexagons", "Bar Chart with Error Bars", "Darkened Box Plots",
"Scatterplot with Large Font", "Nonparametric Densities", "Needle Plot with Tests", "Float Plot with Tests", "Publication Mosaic Plot",
"Publication Fit Simple"}, => {}];
dt = Open("data_table.jmp");
For Each( {sample}, plat_samples["Graph Builder"],
    obj = dt << Graph Builder( Variables( X( :height ), Y( :weight ) ), <<Show Control Panel( 0 ) );
    Eval( Eval Expr( obj << Apply Preset( "Sample Presets", Expr( sample ) ) ) );
    obj << Set Report Title( sample );
);

Code Explanation:

1. Define presets.
2. Open data table;
3. Loop through presets.
4. Create Graph Builder object.
5. Set variables.
6. Hide control panel.
7. Apply preset.
8. Set report title.
9. Repeat for each preset.

Graph Builder using Get Preferences

Summary: Generates a random summary statistic and label option for a subset of data, utilizing Graph Builder preferences and interactive features.

Code:

prfPltfrm = Get  Preferences();
 Preferences( Graph Builder( Show Legend( 0 ), Graph Width( 300 ), Graph Height( 250 ) ) );
dt = Open("data_table.jmp");
myRows = dt << get rows where( :age == 15 & :sex == "F" );
For( i = 1, i <= N Items( myRows ), i++,
    :age[myRows[i]] = .
);
dt << New Column( "freq", formula( Random Integer( Row() ) ) );
sumStalst = {"N", "Mean", "Median", "Geometric Mean", "Min", "Max", "Range", "Sum", "% of Total", "Std Dev", "Variance", "Std Err",
"Interquartile Range"};
N Arg( sumStalst );
myStatistic = sumStalst[Random Integer( N Arg( sumStalst ) )];
lblLst = {"No Labels", "Label by Value", "Label by Percent of Total Values", "Label by Row"};
myLabel = lblLst[Random Integer( N Arg( lblLst ) )];
ErrBarlst = {"Auto", "None", "Range", "Interquartile Range", "Standard Error", "Standard Deviation", "Confidence Interval",
"Custom Interval", "Two-way Interval"};
myErrBar = ErrBarlst[Random Integer( N Arg( ErrBarlst ) )];
GrpLst = {Group X, Group Y, Page, Wrap};
myGrp = GrpLst[Random Integer( N Arg( GrpLst ) )];

Code Explanation:

1. Retrieve platform preferences.
2. Set Graph Builder preferences.
3. Open data table;
4. Identify rows where age is 15 and sex is "F".
5. Replace age values in identified rows with missing values.
6. Create new column "freq" with random integer formula.
7. Define list of summary statistics.
8. Select random summary statistic.
9. Define list of label options.
10. Select random label option.

Graph Builder using Add Ref Line

Summary: Creates a graph builder with reference lines, customized scales, and legend properties for visualizing height and weight data.

Code:

cert_refline = {Add Ref Line( 60, "Dashed", "Medium Dark Blue", "Reference Line", 3 )};
dt = Open("data_table.jmp");
gb = Graph Builder(
    Show Control Panel( 0 ),
    Variables( X( :height ), Y( :weight ) ),
    Elements(
        Points( X, Y, Legend( 1 ) ),
        Line Of Fit(
            X,
            Y,
            Legend( 3 ),
            Confidence of Fit( 0 ),
            Confidence of Prediction( 0 ),
            Degree( "Linear" ),
            Root Mean Square Error( 0 )
        )
    ),
    SendToReport(
        Dispatch( {}, "height", ScaleBox, {Add Ref Line( 60, "Dashed", "Medium Dark Blue", "Reference Line", 3 )} ),
        Dispatch( {}, "weight", ScaleBox, {Min( 58.4020618556701 ), Max( 198.40206185567 ), Inc( 20 ), Minor Ticks( 0 )} ),
        Dispatch( {}, "400", ScaleBox, {Legend Model( 3, Properties( 0, {Line Color( 3 ), Fill Color( 0 )} ) )} )
    )
);
rpt = gb << report;
Close( dt, NoSave );
dt = Open("data_table.jmp");
obj = Oneway(
    Y( :height ),
    X( :sex ),
    Means( 1 ),
    Mean Diamonds( 1 ),
    SendToReport(
        Dispatch( {}, "Oneway Plot", FrameBox,
            {Frame Size( 511, 444 ), Marker Size( 6 ), Marker Drawing Mode( "Outlined" ), DispatchSeg(
                Marker Seg( 1 ),
                {Color( {255, 128, 0} )}
            )}
        )
    )
);

Code Explanation:

1. Define reference line.
2. Open data table.
3. Create graph builder.
4. Hide control panel.
5. Set X and Y variables.
6. Add points element.
7. Add line of fit element.
8. Customize height scale.
9. Customize weight scale.
10. Customize legend properties.

Graph Builder using Names Default to here

Summary: Runs the capture and visualization of sensor data from a COM port, creating a dynamic graph to display the sensed values over time.

Code:

Names Default to here (1);
//run this incrementally, otherwise it will just open and close the com port
//create data table
dt = New Table( "capture",
  Add Rows( 0 ),
  New Column( "time", Numeric, Continuous, Format( ":day:hr:m:s", 21, 3 ) ),
  New Column( "sense", Numeric( 2 ) ) // the analog sensor is 0..1023
); 
//timestamp beginnning
start = Tick Seconds(); 
//open com port and start reading
feed = Open Datafeed(
  Connect( Port( "com4" ), Baud rate( 9600 ), Data Bits (8), parity (none) ),
  Set Script(
  x = feed << getLine;
  dt << addrows( {time = Tick Seconds() - start, sense = num(x) } )
  //if (num(x)> 100, dt << addrows( {time = Tick Seconds() - start, sense = num(x) } ));
  //note: the x>100 is because I think I forgot to print a newline in the arduino code. ran out of time to double check; took easy way out.
  )
);
//make a graph
dt << Graph Builder(
    Size( 528, 454 ),
    Show Control Panel( 0 ),
    Show Legend( 0 ),
    Variables( X( :time ), Y( :sense ) ),
    Elements( Points( X, Y, Legend( 2 ) ), Smoother( X, Y, Legend( 3 ) ) )
);
//close com port
feed << disconnect;
feed << close;

Code Explanation:

1. Set default name space.
2. Create new data table "capture".
3. Add columns "time" and "sense".
4. Record start time.
5. Open COM port connection.
6. Define script for data feed.
7. Read data from COM port.
8. Add rows to data table.
9. Create graph builder.
10. Close COM port connection.