The Right Way to Make a Pie Chart
These are the do’s and don’ts for designing the familiar data visualization.
The pie chart is so popular that it’s the default data visualization in Microsoft Excel and PowerPoint. It’s certainly charming how it calls to mind a dessert being served. Yet despite its wide recognition and adoption, it’s not always an appropriate design. Misconceptions about pie charts abound and even analysts can share bad examples.
At best, a poorly made pie chart underwhelms viewers. At worst, it confuses them and sabotages their decision-making. Every successful pie chart plays into human instincts. Once you understand some basics about visual perception, you’ll master this data visualization and reserve it for the perfect situations.
WHAT IS A PIE CHART?
In 1801, the Scottish engineer and political economist William Playfair introduced the world to pie charts. He invented the data visualization to demonstrate parts of a whole; each part has its own color and all of their values total 100 percent.
Pie charts use angles to represent quantity, but humans struggle with measuring them at a glance. Research has found that we generally underestimate the size of acute angles (<90°) and overestimate the size of obtuse ones (>90°). Therefore, it’s good practice to mark the values in your pie charts — particularly if they have segments with similar amounts.
The more angles a pie chart contains, the more challenging it is for viewers to interpret. Multiple segments also lead to longer legends, which force people to constantly look up labels. As a result, the ideal pie chart should not exceed five slices.
DON’T ASSUME IT’S EASY AS PIE
Pie charts are a well-known data visualization, however they’re rarely implemented properly. This diagram features some typical mistakes in designing pie charts and outlines the rules for formatting them correctly.
Aside from observing these principles, you should take further steps to ensure that your pie charts are readable.
For starters, you should never create a 3D data visualization. This effect produces extra angles and colors that will only make your information harder to analyze. When it comes to pie charts, 3D inevitably misleads viewers about the size of each part.
Moreover, you should consider your color choices when you design a pie chart. Almost every sighted individual can discern red from green, except for 4.5 percent of the population with red-green color blindness. This group sees these colors as brownish-green hues that could be hard to tell apart.
If you’re concerned about accessibility, you can upload your pie chart to an online simulator like Coblis and check how it appears to color blind viewers. Alternatively, you can apply a single color to your pie chart and adjust its saturation. Just note that humans naturally equate greater saturation with greater volume, hence your biggest slices should have the richest hues.
Grading the saturation in your segments is a simple approach that can work for all sighted individuals.
KEEP YOUR OPTIONS OPEN
A pie chart isn’t the only data visualization that can break down parts of a whole. You can also try a bar chart, especially if you have to split a measure into more than five segments.
Both of the above data visualizations classify new opportunities by lead quality. The pie chart isn’t a suitable choice since it has too many slices. Plus, the angles have subtle variations and they’re indistinguishable without marked values. Nonetheless, the bar chart effectively displays this data. Whereas a pie chart uses angles to represent quantity, a bar chart uses length — which humans can easily interpret. It’s much better at showing small increments, like the minor gap between “Very High” and “High”. The 0.10 percent for “Field Sales: Very High” is detectable as well.
On the other hand, your data may meet all of the pie chart criteria but you may want to emphasize its differences. In this case, you should create a donut chart.
A donut chart adds another dimension, allowing viewers to scan the length of each part for comparison. It marries the circular shape of a pie chart with the linear quality of a bar chart.
PIE CHARTS ARE IN OUR DNA
The pie chart isn’t an optimal data visualization unless it falls under a specific set of circumstances. For this reason, eminent statisticians have dismissed pie charts and encouraged the use of bar charts instead. Edward Tufte, a modern thought leader in data visualization, is definitely in this camp. He has argued, “the only worse design than a pie chart is several of them.”
Regardless, pie charts are classic components of BI dashboards, presentations, and reports. While statisticians seem to avoid them, business managers seem to love them. One explanation for the pie chart’s appeal may have to do with its contours; evolution has conditioned people to associate sharp edges with danger and round curves with wellness. From Africa to the Americas, some of the earliest figures that ancient humans ever drew were concentric spirals and sectioned circles.
Although a chart’s primary purpose is to communicate data effectively, aesthetics are still hugely important. You need compelling graphics to draw an audience and engage viewers. Pie charts can be impactful data visualizations, as long as you design them according to the right standards.
