In an analysis, marking items in one visualization spreads to other visualizations based on the same data table. This way you can explore the same data in different contexts.

When you mark items in a visualization, you in fact mark the underlying data, that is, the data rows on which the marked items are based. The marked rows are associated with a specific marking, defined by a name and a color.

Other visualizations that include any of these marked rows are also affected. If any marked data row is part of an item in another visualization, this item also becomes marked. There is one condition though: to interplay, the visualizations must have the same marking applied.

This interplay between visualizations can be used to follow up your marked data in another context.

Example

The visualizations below show the sum of toys purchases from two perspectives. The bar chart presents the sum of purchases made at different store locations during a week, and the line chart presents these purchases per day.

If you mark any of the bars in the bar chart, corresponding line in the line chart becomes marked simultaneously.

Moreover, you can easily switch between the store locations. Mark another bar, and corresponding line gets marked, alternatively mark another line, and corresponding bar gets marked.

The interplay is possible, because the visualizations are based on the same data table, and the same marking is applied. The table with the marked rows is shown below.

Note: In case you do not want the marking of items in a visualization to affect another visualization, select the (None) option in the Marking drop-down list in the legend.