Much data isn't purely numerical; it often involves categories like types of products, regions, or experimental groups. Visualizing relationships and distributions within such categorical data requires specific approaches. This chapter focuses on using Seaborn's specialized functions designed for effectively plotting categorical information.

You will learn to create and interpret several plot types suitable for categorical analysis, including:

• barplot to show aggregate statistics (like mean or median) per category.
• countplot to display the frequency of observations in each category.
• boxplot, stripplot, and swarmplot to compare distributions across different categories, showing individual data points or summary statistics.
• pointplot to highlight trends or differences in point estimates between categories.

By the end of this chapter, you will be equipped to choose and generate appropriate visualizations for exploring and presenting categorical data using Seaborn.