Why You Should Avoid Using Pie Charts
Pie charts are the simplest way to show a part-to-whole analysis. It is also a chart type which beginner loves to create. A-ha, students frequently use them in their presentations or meeting. Yes, pie charts are very popular in our data analysis!
I remember my professor in my college once taught me that: The golden rule of using pie charts is not more than 5 categories. He is right~ But actually, there is a very tricky problem behind the scene.
For a better data visualization, you should avoid using a pie chart. This is a very common consensus among high-skilled data analysts or data scientists when they are preparing the dashboard. Don’t get me wrong, I do not persuade you to permanently stop using the pie charts.
Indeed, I admit that the pie chart has its own advantages for some rare situations. However, overall, the pie chart is sucked at presenting the comparison. Sounds unbelievable huh, let’s look at the following diagram.
The source of this example is from Tableau’s guidebook. I bet you will come with an idea that: It is hard to make these comparisons with pie charts! I hope you did so. If not, let me convince you with explanations.
Our humans are just naturally not good at estimating and distinguishing the area. When the slices of a circle are ambiguous, it’s difficult for our visual to notice differences. Also, it’s almost impossible to compare similar slices from two different pie charts!
Tableau’s guidebook later gives us a solution to cope with this problem. Let’s see what happens on the same data if we use a percent-total bar chart.
Now, we have a clear insight about differences across all age groups much more easily while these minor differences can’t be view simply through the pie chart.
The most important thing about visualizing data is to make it clear to your audience. Hence, your dashboard should look pretty friendly and enable the audience to catch the critical point from just a glance.
Therefore, we suggest avoiding using pie charts in the dashboard to make your data visualization better.
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