A pie chart is a type of data visualization used to represent data in a circular graph. It is helpful for showing the proportional distribution of data points. In a pie chart, the entire “pie” represents 100% of the data, and each “slice” represents a portion of that whole. Each slice’s size is proportional to the value it represents in relation to the total.
Some common types of pie charts are:
- Exploded Pie Chart: In an exploded pie chart, one or more slices are separated or “exploded” from the rest of the chart to emphasize those particular categories.
- 3D Pie Chart: A 3D pie chart adds depth to the chart, making it appear three-dimensional. It is essentially a standard pie chart with a 3D effect for visual appeal.
- Doughnut Chart: A doughnut chart is similar to a pie chart but has a hole or empty center. This type is useful when you want to display multiple data series, and it can help save space in a crowded chart.
- Nightingale Rose Chart: Also known as a polar area chart, the Nightingale Rose Chart is a variation of the pie chart designed for displaying data related to time or angles. It divides the chart into varying-sized segments to represent data points over a specific time period, such as months or hours.
Pie charts can be created using various software tools, including spreadsheet programs like Microsoft Excel, data visualization libraries in programming languages like Python, and specialized charting software. When designing a pie chart, choosing appropriate colors, labels, and formatting is essential to make the chart easily understandable to the audience.
List of recommended resources #
For a broad overview #
Resource: Customize a pie chart
This Microsoft Support tutorial provides an easy-to-access video on how to customize a pie chart according to the user’s needs.
This blog post by Jorge Camoes for ExcelCharts presents arguments for and against using pie charts for data visualization as well as provides advice regarding the dos and don’t of using pie charts.
How to choose the best chart or graph for your data
This data analytics blog on Google Cloud by Jill Hardy gives a broad overview of the different types of charts and graphs to show comparison, distribution, composition and relationship between data values. Hardy mentions donut and pie charts as the best choices to show composition especially when simple proportions are to be presented.
For in depth understanding #
Better Data Visualizations: A Guide for Scholars, Researchers, and Wonks
This book by Jonathan Schwabish details essential strategies to create more effective data visualizations. Schwabish examines more than eighty visualization types, from horizon charts to histograms, choropleth maps to ridgeline plots, and explains how each has its place in the visual toolkit.
Effective Data Visualization: The Right Chart for the Right Data
Written by Stephanie D. H. Evergreen, this comprehensive how-to guide shows readers how to create Excel charts and graphs that best communicate their data findings.
Case study #
Digital Data Sources and Their Impact on People’s Health: A Systematic Review of Systematic Reviews
This study uses pie charts to show the impact of digital data sources on health emergencies.
Humidity driven nanoscale chemical separation in complex organic matter
This paper makes use of pie charts to illustrate the chemical composition with their typical mass proportion in a) urban and b) high alpine air.
References #
A Complete Guide to Pie Charts
