Pie Charts

by Nicole Cardillo

Pie charts are one of the most common visualizations that we see when analyzing data. The circle or the "pie" is made up of slices which each represent a certain percentages. The total amount of slices should have a sum of 100%. It is key to not have too many slices in a pie chart to avoid a busy visualization. Pie charts with too much information may distract the viewers and take away from the main point of the graphic. Instead, pie charts should be made of about five categories that are relevant to the topic and story that is being told through the graph. 

I created the pie chart below to reflect popular music genres among college students. The categories for genres consist of Pop, Hip-Hop, Rock, and Country, along with a slice for other miscellaneous genres. 

This pie chart is a valid visualization for this type of data because it clearly displays a small amount of categories, along with the value for each slice of the pie chart. Additionally, it is easy to tell the differences in slices as each percent is significantly smaller/larger than the surrounding slices. Often, a common misconception when analyzing a pie chart is accurately deciphering between different sized slices.  Storytelling With Data explains, "This example demonstrates one limitation of data encoded as pie slices: humans’ eyes aren’t well-equipped to compare areas" (Storytelling With Data). For instance, if we are given two slices that are 19% and 20%, respectively, it will be extremely difficult for the human eye to see which slice is which. In this case, labels or a completely different visualization would be more beneficial to the data set.

A bar graph would also be suitable for my data. These values are comparable to one another; turning the data into a bar graph would give me a clear visualization of which values are largest/smallest. Despite this, I still believe a pie chart is the best visualization for this data because it is so simple. The total of each percentage for music genre sums to 100%, making this data appropriate for a pie chart. Furthermore, humans are more drawn to circles. While a bar graph has the ability to reflect this data just as effectively as a pie chart, humans will desire to analyzing the pie chart. Author Manuel Lima explains, "Today, when someone looks at a pie chart they are recognizing a visual pattern they see everywhere, everyday, in both the natural world and our man-made culture. They are recognizing a graphical arrangement that our ancestors have been exposed to for countless generations" (Medium). Overall, circles are historically the most appealing geometric shape to the human eye. It is all around us in nature and thus maintains our attention as we are more prone to analyze data visualizations like pie charts.

I think one of the best practices when creating pie charts like the one I made is to keep it short and simple. My pie chart reflects five percentages that add to 100%. This short amount of categories provide me with the space to label inside the slices. I think labeling inside the slices is more beneficial than a legend because it keeps our focus on the pie itself, rather than having to look back and forth to match a color to a slice. 

Ultimately, pie charts are one of the most common data visualizations in our world. While they are not ideal for a large amount of raw data, they are great for simple datasets! 

References:

Ricks, E. (2020, May 14). What is a pie chart and when to use it. Storytelling with Data. https://www.storytellingwithdata.com/blog/2020/5/14/what-is-a-pie-chart

Lima, M. (2018, July 26). Why humans love pie charts. Medium. https://medium.com/@mslima/why-humans-love-pie-charts-9cd346000bdc

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