Python Data Science Handbook, 2nd Edition

Chapter 31. Multiple Subplots

Sometimes it is helpful to compare different views of data side by side. To this end, Matplotlib has the concept of subplots: groups of smaller axes that can exist together within a single figure. These subplots might be insets, grids of plots, or other more complicated layouts. In this chapter we’ll explore four routines for creating subplots in Matplotlib. We’ll start by importing the packages we will use:

In [1]: %matplotlib inline
        import matplotlib.pyplot as plt
        plt.style.use('seaborn-white')
        import numpy as np

plt.axes: Subplots by Hand

The most basic method of creating an axes is to use the plt.axes function. As we’ve seen previously, by default this creates a standard axes object that fills the entire figure. plt.axes also takes an optional argument that is a list of four numbers in the figure coordinate system ([left, bottom, width, height]), which ranges from 0 at the bottom left of the figure to 1 at the top right of the figure.

For example, we might create an inset axes at the top-right corner of another axes by setting the x and y position to 0.65 (that is, starting at 65% of the width and 65% of the height of the figure) and the x and y extents to 0.2 (that is, the size of the axes is 20% of the width and 20% of the height of the figure). Figure 31-1 shows the result:

In [2]: ax1 = plt.axes()  # standard axes
        ax2 = plt.axes([0.65, 0.65, 0.2, 0.2])

Figure 31-1. Example of an inset axes

The equivalent of this command within the object-oriented ...