We just talked about the advantages of displaying multiple plots next to each other. One common challenge with subplots–as we saw in the last exercise– is getting the graphs and their axes, labels, titles, and legends to display nicely. Luckily, the function plt.figure() can help us out.

We can adjust any single graph in a subplot using its respective code – adding xlabel or title as usual, for example. We can make changes to the whole grid by defining the space around the subplots as a “figure” using matplotlib’s general function plt.figure(), like so:

fig = plt.figure()

plt.figure can take parameters, including:

• figsize: adjusts the dimensions of the figure
• tight_layout: adjusts the spacing of plots for an automated “best fit” with a Boolean
• facecolor: sets the background color

fig = plt.figure(figsize = (10, 4), tight_layout = True, facecolor=’lightgray’)

fig, the instance we’ve defined of plt.figure, also has its own methods, including:

• suptitle(): adds a centered title at the top of all subplots, with font size and spacing parameters
• supxlabel(): adds an xlabel to all plots
• supylabel(): adds a ylabel to all plots
• subplots_adjust(hspace, wspace): manually adjusts spacing around plots

fig.suptitle(‘Six line graphs’, fontsize=24, x=0.45, y=0.95)
fig.supxlabel(‘Time’)
fig.subplots_adjust(hspace = 0.5, wspace = 0.25)

These functions are helpful for uncluttering the figure when a single title or label applies to multiple subplots, or when graphs need more padding to prevent crowded labeling.

Let’s return to the subplots we made in the last exercise and see if we can make them visually cleaner.