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Posted by on Mar 13, 2017

Put Your Data Visuals on a Diet: No More Pie Charts!

Put Your Data Visuals on a Diet: No More Pie Charts!

International Pi Day, March 14

 

Happy Pi Day! To celebrate, I will be discussing one of the most widely-used (but not widely useful!) data visualizations: the Pie Chart.

Data-driven, strategic decisions are only as good as the information behind them—and to decision-makers presented with data, the information’s only as good as the chart or graph that represents it.

As data analysis is used more and more, the communication of actionable information becomes just as important as the information itself. While charts and graphs are invaluable tools for easily and quickly communicating a complex message to an audience, if they aren’t wisely designed, they can also be misinterpreted, misleading, or even deterrents to action. And pie charts—despite their deceptively simple style and popularity—often lead viewers astray, or lead nowhere at all.

So, here are 3.14 Reasons to Never Use Pie Charts!

1. Distortion of the Information

3D and ‘explosion’ effects are very common pie chart features. But look at the following example of regional sales data—can you tell which region had the most first-quarter sales?

3d explosion effect pie chart

I can’t tell either, and I built the chart! The explosion makes it difficult to gauge the slices’ sizes in relation to each other. And when using the 3D effect, slices that are closer to the reader appear larger than the others.

Let’s remove the 3D and explosion effects and see if that helps.

3d and explosion style of pie chart removed

Still stuck? Me too. Dark colors naturally look larger than light colors, making it difficult to compare. Instead of a pie chart, use a bar chart that you can sort and label efficiently. Bar charts can often display the same exact data without distorting the information—and audiences are always relieved by easy-to-read charts.

2. Difficulty Communicating the Information

How many times have you seen a pie chart with too many slices and a crowded legend?

Pie chart with way too many slices

If your eyes need to move back and forth between the chart and the legend (and who can squint hard enough to read that legend, right?), you’re not focusing on the information or what it means. Instead, your brainpower is spent remembering which color matches each legend entry.

Let’s try to fix it by limiting the number of pie flavors.

Pie chart with distracting or confusing slices

This shows the top pie preferences, and buckets everything else into ‘Other’. But we’re now inviting questions about what falls into the mysterious ‘Other’ category rather than effectively communicating the pie preferences. (And if you hadn’t noticed, we’re experiencing distortion of information with the colors—e.g. is the dark blue slice twice the size of the orange slice? Hard to say!)

A bar chart allows you to communicate the important information without inviting tangential (or completely unrelated!) questions.

3. Difficult to Draw Meaningful Conclusions

This is the result of reasons #1 and #2.

When a data visualization does not accurately represent or effectively communicate the data, one of two things is most likely to happen. One – you’re going to make a decision that you shouldn’t. Or two – you’re not going to make any decision at all.

In today’s environment it is increasingly important to be able to make data-driven, strategic decisions. That’s so much easier when you use a chart style that fits your data and your message. Most often, a pie chart is not the right choice.

3.14. Pie is for eating, not for data.

Don’t get me wrong—pie is supremely delicious. But save it for your team’s next big win, not its next big data-based presentation.

Bar charts are almost always easier to read—they make comparisons much clearer, and take the human brain way less time to process visually. For more tips on effective data visualization, subscribe to this blog for monthly data analytics posts, check out our Data Visualization training course, and download our complimentary job aid: The Language of Data Visualization.

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