The box-and-whisker plot, or box plot, is another effective visualization choice for illustrating distributions. Along with histograms and stacked area charts, box-and-whisker plots are among my favorite chart types used for this purpose. They work particularly well when you want to compare the distributions across two different dimension members side-by-side, where one set of dimension members makes up the x-axis, and the other dimension member is used as the visualization’s level of detail. To help illustrate, here’s the box-and-whisker plot we will create with the Sample – Superstore dataset during this tutorial:
As you can see, each set of circles corresponds to the dimension members on the x-axis for the Sub-Category dimension. The level of detail, or most granular level of the analysis, is Month of Order Date. Since the level of detail is Month of Order Date, each Sub-Category column has 12 circles, one for each month of the year.
In short, this visualization is showing how the distributions of monthly sales vary between product sub-categories. While I can easily find several insights in this visualization and believe box-and-whisker plots to be among the most effective ways to communicate distributions, I find them to be one of the most misunderstood chart types when I attempt to share them with an external audience.
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