Visualizing the distribution of data is essential for understanding its characteristics, such as central tendency, spread, and shape. Having established Seaborn's advantages for creating informative plots, this chapter concentrates on functions designed specifically for visualizing distributions.

You will learn how to use:

• histplot and kdeplot to view frequency distributions and smoothed density estimates.
• boxplot and violinplot to compare distributions across categories using summary statistics and density shapes.
• jointplot to examine the relationship between two variables while simultaneously viewing their individual distributions.

By the end of this chapter, you will be able to select and create appropriate Seaborn plots to effectively represent the distributions within your data.