Python Data Science Handbook, 2nd Edition

Chapter 25. General Matplotlib Tips

Before we dive into the details of creating visualizations with Matplotlib, there are a few useful things you should know about using the package.

Importing Matplotlib

Just as we use the np shorthand for NumPy and the pd shorthand for Pandas, we will use some standard shorthands for Matplotlib imports:

In [1]: import matplotlib as mpl
        import matplotlib.pyplot as plt

The plt interface is what we will use most often, as you shall see throughout this part of the book.

Setting Styles

We will use the plt.style directive to choose appropriate aesthetic styles for our figures. Here we will set the classic style, which ensures that the plots we create use the classic Matplotlib style:

In [2]: plt.style.use('classic')

Throughout this chapter, we will adjust this style as needed. For more information on stylesheets, see Chapter 34.

show or No show? How to Display Your Plots

A visualization you can’t see won’t be of much use, but just how you view your Matplotlib plots depends on the context. The best use of Matplotlib differs depending on how you are using it; roughly, the three applicable contexts are using Matplotlib in a script, in an IPython terminal, or in a Jupyter notebook.

Plotting from a Script

If you are using Matplotlib from within a script, the function plt.show is your friend. plt.show starts an event loop, looks for all currently active Figure objects, and opens one or more interactive windows that display your figure or figures.