Multiple Subplots and Figures

Up to now, you’ve worked with one chart per figure. But what if you want to compare several plots side by side?

Matplotlib lets you organize multiple plots within a single figure using subplots, or create entirely separate figures for different visualizations.

Use plt.subplot(rows, cols, index) to divide the figure into a grid.

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import matplotlib.pyplot as plt

x = [1, 2, 3, 4]
y1 = [2, 4, 1, 3]
y2 = [3, 1, 5, 2]

plt.subplot(1, 2, 1)  # 1 row, 2 columns, 1st plot
plt.plot(x, y1)
plt.title("Plot A")

plt.subplot(1, 2, 2)  # 1 row, 2 columns, 2nd plot
plt.plot(x, y2)
plt.title("Plot B")

plt.tight_layout()
plt.show()

You control the layout by setting the number of rows and columns, while the index determines each subplot’s position in the grid.

Use plt.figure() to start a new figure. Each figure is independent.

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plt.figure(1)
plt.plot([1, 2, 3], [4, 5, 6])
plt.title("Figure 1")

plt.figure(2)
plt.plot([1, 2, 3], [6, 5, 4])
plt.title("Figure 2")

plt.show()

This is useful when generating different types of charts within the same script.

• Use subplots when you want to compare related datasets in a single visual space.
• Use multiple figures when creating distinct visualizations for separate analyses or outputs.