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Pie charts are an efficient and easy to read way to represent data in percentages or portions. However, it is sometimes difficult to include absolute numbers on a pie chart instead of percentages, particularly if there are many categories shown in the chart.

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Pie charts are built in to many mathematical and statistical software packages, including Microsoft Excel, Minitab, SPSS and R. They are generally simple to create and do not require a lot of explanation when used in a report or a presentation.

While the reader of a pie chart can clearly see which categories dominate, it can be difficult to see categories that occupy only a small percentage of the chart. This problem becomes worse if there are many small categories in the chart. Labeling the categories can also be difficult, leading to either excessively long legends or multiple labels on the chart itself. Both of these options detract from the visual appeal and make it difficult to extract useful conclusions.

Pie charts are recommended for data sets with relatively few (five to 10) categories. To represent data in more than 10 categories, a bar chart of percentages with category labels on the horizontal axis is easier to read and interpret.

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The percentages of people with various eye colors are unknown for many countries. However, according to the American Academy of Ophthalmology, 32 percent of Americans have blue or grey eyes; 15 percent have blue, grey or green eyes with brown or yellow flecks; 12 percent have green or light brown eyes with minimal flecks; 16 percent have brown eyes with dark specks; and 25 percent have uniformly brown eyes.

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A pie graph is an effective visual tool used for showing how something breaks into parts. A pie graph is essentially a circle sliced into 100 pieces. Each category or part represented in the pie graph is given a piece of the pie to represent the percentage that it comprises of the whole.

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