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binning and grouping

Contributor(s): Corinne Bernstein

Binning and grouping is form of data visualization in which individual data values are sorted into classes or categories and depicted graphically to help explain the significance of the data. Binning and grouping is useful when there are so many individual graphic elements in a chart, that distinguishing them is difficult. 

Statistical data binning offers a way to group continuous values into a smaller number of bins. For example, data about a group of people could be arranged into a smaller number of age intervals (e.g., grouping every five years together). Ideally, bins should contain the same number of items and when possible, the data set should be evenly divisible by the number of bins. Bins should include all data under study, including outliers, and boundaries for bins should be whole numbers to make the data easier to visualize.

Large data sets typically require a large number of bins. Deciding on the exact number is often a judgment call. Choosing the right number of bins with the right number of items to provide the information needed is important but can be challenging. 

This was last updated in August 2018

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