Matplotlib Subplot

Understand the idea

subplots can return several Axes objects, which you then configure individually. Shared axes are useful for comparable quantities but inappropriate when units differ. layout='constrained' helps allocate space for labels. The example deliberately compares counts rather than mixing an amount and a count on an unlabeled shared scale.

Where to try it

Run this complete script in a local virtual environment with Matplotlib installed (py -m pip install matplotlib). It uses a non-interactive backend and saves workshop.png in the current folder. The site shows a rendered example below; its text-only online runner does not display plot windows.

A worked example

import matplotlib
matplotlib.use("Agg")
import matplotlib.pyplot as plt
fig, ax = plt.subplots(figsize=(7, 4), layout="constrained")
plt.close(fig)
fig, axes = plt.subplots(1, 2, figsize=(8, 3), sharey=True, layout="constrained")
axes[0].bar(["Morning", "Evening"], [8, 12])
axes[1].bar(["Morning", "Evening"], [10, 14])
axes[0].set(title="Week 1", ylabel="Attendees")
axes[1].set_title("Week 2")
fig.savefig("workshop.png", dpi=140)
plt.close(fig)
print("Saved workshop.png")

Read the result

Two panels share the attendee scale, so the taller bars reflect a real cross-panel difference.

Try one change

Remove sharey and inspect the new limits, then decide which version matches the report's purpose.