Using categorical data with Matplotlib

By Martin McBride, 2022-06-13
Tags: bar chart pie chart scatter plot
Categories: matplotlib

Categorical data is data where at least one of the variables is a category rather than a numerical value. For example:

  • The average UK temperature for each month of the year 2009. Temperature is a numerical value, but the values are grouped and averaged by month - the temperatures measured in January are one category, the temperatures measured in February are another category, and so on.
  • The most popular names of given to girls born in the UK in 2021 is also categorical data. "Oliuia", "Amelia", "Isla", etc are categories, the number of girls with each name are numerical values.

These types of plot are useful is the case where one variable is categorical and the other is numerical:

Sometimes, both variables can be categorical. For example, if we looked at the single most popular girl's name each year for the last 50 years, then the names are categorical and the year are also categorical.

Years are numbers, but those number are effectively the names of the years. If we named our years differently, it would make no differnce to the meaning of the data.

Bar charts and pie charts are not very useful for displaying data where both variables are categorical. A scatter plot is better.

See also

If you found this article useful, you might be interested in the book NumPy Recipes or other books by the same author.

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