Chapter 35. How to Make Marginal Histograms
As I often discuss, one of my main objectives as a data visualization practitioner is to avoid causing my audience to ask the question, “So what?” I never want to have an analytics partner put their trust in me and spend my time building out a dashboard, only to have them not know why my findings are important or what to do about them. Three of the best ways to make your data visualization deliverables useful are to build in comparisons, add context, and visualize the same fields in different ways.
In the case of scatter plots, adding marginal histograms accomplishes all three of these techniques. Marginal histograms are histograms that are incorporated into the margin of each axis of a scatter plot for analyzing the distribution of each measure. And as my friend Steve Wexler of Data Revelations points out, “They’re not just for scatter plots”.
This chapter shows you how to make marginal histograms for scatter plots, marginal bar charts for highlight tables, and explains the difference between the two.
How to Add Histograms to the Margins of Scatter Plots
The traditional use of marginal histograms involves adding a histogram of each measure used in a scatter plot to the top and right margin.
To begin, consider the following scatter plot looking at the Profit and Age of Customer (in days they’ve been a customer) measures by the Customer Name dimension:
If you want to follow along using the Sample – Superstore dataset, Age of Customer ...
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