Don’t let Excel’s default settings ruin your data analysis!
I gathered together some insights from research into visual perception and interpretation (borrowed from the likes of Edward Tufte, Leland Wilkinson, and Stephen Few) and presented these in a talk which I hope will mean you never look at a pie chart quite the same way again!
The title - Stop Making Pie Charts - is polemic, but I think the idea is quite reasonable - pie charts are, generally speaking, not a good choice of visualisation for communicating quantitative information.
The central argument is that the most effective way to encode data in a graphic is with the position of the elements and their distance from a common baseline (like in a scatter plot or bar chart). By contrast, angle and areas (as in a pie chart) are harder to decode accurately.
In defence of Pie Charts
I’ve given the talk a couple of times now and I’ve been fascinated to hear people’s defense of pie charts. Clearly there’s no single form of visualisation that is the best in every context (although I feel like, given suitably transformed data, the scatter plot comes close) and there are circumstances in which the much-maligned pie is appropriate.
Here are some of the counter-arguments - reasons why you shouldn’t stop using pie charts:
- Pie charts are easy to understand - people are used to seeing them, what they lack in decoding accuracy, they make up for in decoding simplicity and familiarity
- Some values are easy to read on a pie chart - it’s easy to compare against the quartiles (i.e. 25%, 50%, 75%, and 0/100%) even without guidelines
- The circular shape is aesthetically pleasing and can provide variety to decorate dry reports otherwise filled with dots and rectangles
- Sometimes people want give a subjective representation of the facts - a one-sided perspective (and 3d distortions) can help support a narrative
Indeed if you’re just looking to tell a story - particular one like “only a very small proportion of people do x” - and you don’t need your audience to decode quantitative data, then pie charts aren’t so bad after all.
Still, if you have an inquisitive audience, complex quantitative data, and find raw objective data points aesthetically pleasing, then perhaps you have no excuse but to stop making pie charts?!