Layouts

There are multiple ways to define a visualization layout in Matplotlib. By layout, we mean the arrangement of multiple Axes within a Figure. We will start with subplots and how to use the tight layout to create visually appealing plots and then cover GridSpec, which offers a more flexible way to create multi-plots.

Subplots

It is often useful to display several plots next to one another. Matplotlib offers the concept of subplots, which are multiple Axes within a Figure. These plots can be grids of plots, nested plots, and so on.

Explore the following options to create subplots:

• The plt.subplots(, ncols) function creates a Figure and a set of subplots. nrows, ncols define the number of rows and columns of the subplots, respectively.
• The plt.subplot(nrows, ncols, index) function or, equivalently, plt.subplot(pos) adds a subplot to the current Figure. The index starts at 1. The plt.subplot(2, 2, 1) function is equivalent to plt.subplot(221).
• The Figure...