Detailed Tab

Use the Detailed tab when you know what type of visualization you want to create or when you want to add optional aesthetics, panels, and/or animation to a visualization. For examples, see Examples .

  1. If you selected a visualization type on the Basic tab, it will be displayed. Otherwise, choose one from the drop-down list. For information about the visualization types, see Available Built-in Visualization Types .
  2. To the immediate right of the visualization's thumbnail image are controls for specifying the fields (variables) required for the visualization type. You must specify all of these fields.
  3. For certain visualizations, you can select a summary statistic. In some cases (such as with bar charts), you can use one of these summary options for the transparency aesthetic. For descriptions of the summary statistics, see Basic Tab .
  4. You can select one or more of the optional aesthetics. These can add dimensionality by allowing you to include other fields in the visualization. For example, you may use a field to vary the size of points in a scatterplot.
  5. If you are creating a map visualization, the Map Files group shows the map file or files that will be used. If there is a default map file, this file is displayed. To change the map file, click Select a Map File to display the Select Maps dialog box. You can also specify the default map file in this dialog box. See the topic Selecting map files for map visualizations for more information.
  6. You can select one or more of the paneling or animation options.

Understanding Optional Aesthetics

Aesthetics (and overlays) add dimensionality to a visualization. The effect of an aesthetic (grouping, clustering, or stacking) depends on the visualization type, the type of field (variable), and the graphic element type and statistic. For example, a categorical field for color may be used to group points in a scatterplot or to create the stacks in a stacked bar chart. A continuous numeric range for color may also be used to indicate the range's values for each point in a scatterplot.

You should experiment with the aesthetics and overlays to find one that fulfills your needs. The following descriptions may help you pick the right one.

Note: Not all aesthetics or overlays are available for all visualization types.

  • Color. When color is defined by a categorical field, it splits the visualization based on the individual categories, one color for each category. When color is a continuous numeric range, it varies the color based on the value of the range field. If the graphic element (for example, a bar or box) represents more than one record/case and a range field is used for color, the color varies based on the mean of the range field.
  • Shape. Shape is defined by a categorical field that splits the visualization into elements of different shapes, one for each category.
  • Transparency. When transparency is defined by a categorical field, it splits the visualization based on the individual categories, one transparency level for each category. When transparency is a continuous numeric range, it varies the transparency based on the value of the range field. If the graphic element (for example, a bar or box) represents more than one record/case and a range field is used for transparency, the color varies based on the mean of the range field. At the largest value, the graphic elements are fully transparent. At the smallest value, they are fully opaque.
  • Data Label. Data labels are defined by any type of field whose values are used to create labels that are attached to the graphic elements.
  • Size. When size is defined by a categorical field, it splits the visualization based on the individual categories, one size for each category. When size is a continuous numeric range, it varies the size based on the value of the range field. If the graphic element (for example, a bar or box) represents more than one record/case and a range field is used for size, the size varies based on the mean of the range field.

Graph with color overlay aesthetic

Figure 1. Graph with a color overlay aesthetic
Graph with a color overlay aesthetic

Graph with size overlay aesthetic

Figure 2. Graph with a size overlay aesthetic
Graph with a size overlay aesthetic

Understanding Paneling and Animation

Paneling. Paneling, also known as faceting, creates a table of graphs. One graph is generated for each category in the paneling fields, but all panels appear simultaneously. Paneling is useful for checking whether the visualization is subject to the conditions of the paneling fields. For example, you may panel a histogram by gender to determine whether the frequency distributions are equal across males and females. That is, you can check whether salary is subject to gender differences. Select a categorical field for paneling.

Graph with panels

Figure 3. Graph with panels by married status (YES/NO)
Graph with panels by married status (YES/NO)

Animation. Animation resembles paneling in that multiple graphs are created from the values of the animation field, but these graphs are not shown together. Rather, you use the controls in Explore mode to animate the output and flip through a sequence of individual graphs. Furthermore, unlike paneling, animation does not require a categorical field. You can specify a continuous field whose values are split up into ranges automatically. You can vary the size of the range with the animation controls in explore mode. Not all visualizations offer animation.