Defending Pie Charts

Bobby Johnson makes a valiant effort at defending the indefensible:

In the world of data analysis, there are few things more reviled than the pie chart. Among “serious” data people, it is at best trivial and naive, and at worst downright evil.

I do not agree with this. The pie chart is simple, but that is its beauty. It does exactly one thing and it does it well: it shows you how much different parts contribute to a whole. This isn’t the only question you ever have about your data, but when it’s the question you do have, the pie chart is perfect. That is not evil and it is not naive. It is data visualization doing what it should: taking something large and abstract and saying something simple about it that your brain can easily internalize.

I strongly disagree with arguments in the article, but do respect the attempt.  In each of the cases, at least one of a bar chart, stacked 100% bar chart, or dot plot could give at least the same amount of information with less lower mental overhead.

Related Posts

Combining Plots In R With cowplot

Abdul Majed Raja shows how to use the cowplot library in R to merge together independent plots into a single image: The way it works in cowplot is that, we have assign our individual ggplot-plots as an R object (which is by default of type ggplot). These objects are finally used by cowplot to produce […]

Read More

R htmlTable Updates

Max Gordon has some updates to the htmlTable package: Even more common than grouping columns is probably grouping data by rows. The htmlTable allows you to do this by rgroup and tspanner. The most common approach is by using rgroupas the first row-grouping element but with larger tables you frequently want to separate concepts into separate sections. Here’s a […]

Read More


March 2018
« Feb Apr »