In this Python visualization tutorial you’ll learn how to create and save as a file multiple bar charts in Python using Matplotlib and Pandas. We’ll easily read in a .csv file to a Pandas dataframe and then let Matplotlib perform the visualization. As a bonus you’ll also learn how to save the plot as a file.

The key to making two plots work is the creation of two axes that will hold the respective bar chart subplots.

# define the figure container and the two plot axes
fig = plt.figure(figsize=(20,5))

# add subplots to the figure (build a 1x2 grid and place chart in the first or second section)
ax1 = fig.add_subplot(1,2,1)
ax2 = fig.add_subplot(1,2,2)

Understanding the subplot nomenclature is essential. Adding axes to the figure as part of a subplot arrangement is simple with the fig.add_subplot() call. In this arrangement the first digit is the number of rows, the second represents the number of columns, and the third is the index of the subplot (where we want to place our visualization).

Of course you need to watch the video to see how all of the code comes together.

Also, keep this Matplotlib style sheet reference handy for changing up the style on your visual.

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See the following links for additional background:

https://matplotlib.org/3.1.0/gallery/subplots_axes_and_figures/subplots_demo.html

https://matplotlib.org/3.1.1/api/_as_gen/matplotlib.figure.Figure.html#matplotlib.figure.Figure.add_subplot