With this chapter, we will move into the topics that focus on the computationally intensive matplotlib tasks. This is not something that is usually associated with matplotlib directly, but rather with libraries like NumPy, Pandas, or scikit-learn, which are often brought to bear on large number-crunching jobs. However, there are a number of situations in which organizations or individual researchers need to generate a large number of plots. In the remainder of the book, our exploration of matplotlib in advanced usage scenarios will rely on the free or low-cost modern techniques that are available to the public. In the early 1960s, the famous computer scientist John McCarthy predicted a day when computational resources would be available like the public utilities of electricity and water. This has indeed come to pass, and we will now turn our focus to these types of environments.

We will cover the following topics in this chapter...