Introduction

In the previous chapter, we took an in-depth look at Matplotlib, one of the most popular plotting libraries for Python. Various plot types were covered, and we looked into customizing plots to create aesthetic plots.

Unlike Matplotlib, Seaborn is not a standalone Python library. It is built on top of Matplotlib and provides a higher-level abstraction to make visually appealing statistical visualizations. A neat feature of Seaborn is the ability to integrate with DataFrames from the pandas library.

With Seaborn, we attempt to make visualization a central part of data exploration and understanding. Internally, Seaborn operates on DataFrames and arrays that contain the complete dataset. This enables it to perform semantic mappings and statistical aggregations that are essential for displaying informative visualizations. Seaborn can also be used to simply change the style and appearance of Matplotlib visualizations.

The most prominent features of Seaborn are as follows...