Matplotlib Subplot — Data Visualization Tutorial

For the ultimate matplotlib data visualization tutorial, read our full matplotlib for machine learning, data science tutorial. This tutorial focuses specifically on creating subplots.

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Subplots are useful for displaying dense information in data visualization. Subplots fit multiple plots on the same matplotlib figure. They are good for comparison: aligning comparable attributes, columns side by side for convenient visualization. It gives us a sense how comparable data attributes vary, sometimes with the same horizontal axis and scale. But the subplots don’t have to be related. Subplots can also be used to lay out unrelated plots in a tight format of columns and rows. It can be used for laying out complex charts and advanced charts such as longitudinal studies.

matplotlib.pyplot.subplots “Create a figure and a set of subplots. This utility wrapper makes it convenient to create common layouts of subplots, including the enclosing figure object, in a single call.” The functionality sure works, however, there’s surely a long learning curve. Source official documentation .Documentation matplotlib subplot matplotlib.pyplot.subplots .

import matplotlib.pyplot as plt
fig, axes = plt.subplots(nrows=1, ncols=2)