Pie charts are a bit of a paradox. They’re both easy to understand and difficult to understand. A pie is a helpful visual aid when describing proportions, but just a little too much detail can make things confusing. Many analytics and statistics experts avoid using pie charts altogether. At the same time, many business audiences prefer them. Every form of data visualization has its strengths and weaknesses, but pie charts come with more pitfalls than most. In their simplest form, pie charts offer a quick, visual representation of proportions, but if you’re not careful, they can get out of hand. Here are some of the most common problems with pie charts, along with tips for how to avoid them.

1. Too Many Items

When it comes to pie charts, less is more. Ideally, pie charts should have no more than 15 slices. After that, things get complicated pretty fast. A pie chart with 2 or 3 slices can give the viewer a sense of the data in a single glance. However, a pie chart with 20 slices on it requires careful examination, and it can be hard to draw any sort of conclusion by staring at 20 little slivers. If you need to show more than 15 items, consider a different type of chart, like a bar chart or a histogram.

2. Too Much Detail

Pie charts aren’t good for showing granular detail. The problem is that the human eye isn’t good at telling the difference between 18% of a circle and 16% of a circle. While we may be able to tell they’re different, the average person would be hard pressed to say by how much. Things also get complicated when pie charts include tiny slivers of percentages. It’s not uncommon to see pie charts with a few large chunks, and then a clump of tiny slivers that each represent 1%. This is fine if you’re trying to communicate in broad strokes, but when tiny differences matter, pie charts aren’t the best choice. Bar charts are much more effective for showing subtle differences. With bar charts or histograms, even a difference of 1% is fairly clear.

3. Confusing Colors

Most pie charts require the use of a legend to identify what each slice represents, but this can lead to confusion, especially when colors are similar. The problem is at its worst when there’s too many items, but even pie charts with less than 12 items can get confusing if the colors aren’t thought out. Reading a chart isn’t the time to try to decipher the differences between purple and violet. If you find your eyes darting back and forth between the pie chart and the legend, it’s a good sign you need to rethink your chart. Try to use colors that are easy to differentiate. If you have to use two shades of the same color, try to make them as different as possible, and don’t put them close together.

4. Data is too consistent

It’s hard to illustrate the differences in your data when every item looks the same. For example, let’s say you have a pie chart with four items, and each slice is roughly the same size (22%, 28%, 24%, and 26%). If you were to look at this as a pie chart, you wouldn’t be able to draw many conclusions from it. Visually, they’d all look fairly equal. Unless there are pronounced differences in your data, pie charts are a bad choice. To illustrate these subtleties, your best option is a bar chart.

Pie charts are a simple way to show percentages of a whole, but their strength is also their weakness. That same simplicity makes it difficult to illustrate complex, or nuanced data. Pie charts aren’t all bad, but they’re probably not as effective as you think. Just about every analytics tool includes pie charts as a data visualization, but if you look around, there’s probably a better way to visualize your data.

stacked-chart

For example, if you wanted to show how much each of your sales reps contribute to your overall sales, you could use a pie chart. However, a bar chart would be more effective. With iCharts, you can even create a stacked bar chart, so you can get a breakdown of where each person’s sales come from. It’s sort of like having a pie chart and a bar chart in one.

For more information on how to choose the right chart for your data, head to our resources page.