# Summary

In this chapter, we provided a detailed introduction to Matplotlib, one of the most popular visualization libraries for Python. We started off with the basics of pyplot and its operations, and then followed up with a deep insight into the numerous possibilities that help to enrich visualizations with text. Using practical examples, this chapter covered the most popular plotting functions that Matplotlib offers, including comparison charts, and composition and distribution plots. It concluded with how to visualize images and write mathematical expressions.

In the next chapter, we will learn about the Seaborn library. Seaborn is built on top of Matplotlib and provides a higher-level abstraction to create visualizations in an easier way. One neat feature of Seaborn is the easy integration of DataFrames from the pandas library. Furthermore, Seaborn offers a few more plots out of the box, including more advanced visualizations, such as violin plots.