The Box Plot is a useful visualization when analyzing Data Tables that do not lend themselves easily to Bar Charts or Histograms. Because of the small size of a Box Plot, it is easy to display and compare several in a small space. A Box Plot is a good alternative or complement to a Histogram when showing several simultaneous comparisons.
For example, assume we have a Data Table that analyzes information about various cars. The data contains many numeric columns for which we may want to look at the distribution on. If we use a Bar Chart, we can analyze each variable separately (for example MSRP, the Wheel Base, or the Engine Size of the car).
If we want to plot all our variables side by side and analyze them simultaneously, a Box Plot would be a better visualization. See the image below where we plot MSRP, Wheel Base, Engine Size, and five other variables).
In addition to displaying multiple variables at the same time, Box Plots are also good for detecting and visualizing outliers. You can see outliers in a Box Plot as circles above or below the main part of the visualization.
For more information on Box Plots and other built-in visualization types, please take our Introduction to Data Analysis and Visual Analytics course, or Spotfire Essentials I and II. These courses are well suited to be delivered via our blended training. To see a sample module from one of our blended learning courses, click here (you will have to click on 'Guest Access' before viewing the content). This sample module is all about Box Plots.
