Unequal subplot sizes in Matplotlib

Introduction

Sometimes you want to show multiple charts in one figure but with different sizes. This helps highlight important data or save space.

You want a big main chart and smaller side charts.

You need to compare one detailed plot with simpler summary plots.

You want to save space by making less important plots smaller.

You want to create a dashboard with charts of different sizes.

You want to control layout precisely for presentations or reports.

Syntax

Matplotlib

fig = plt.figure()
ax1 = fig.add_axes([left, bottom, width1, height1])
ax2 = fig.add_axes([left2, bottom2, width2, height2])

The add_axes method takes a list of 4 numbers: [left, bottom, width, height].

All values are between 0 and 1 and represent the fraction of the figure size.

Examples

This creates one large plot on the left and a narrow plot on the right.

Matplotlib

fig = plt.figure()
ax1 = fig.add_axes([0.1, 0.1, 0.7, 0.8])  # big plot
ax2 = fig.add_axes([0.85, 0.1, 0.1, 0.8])  # narrow side plot

This creates one big plot on top and two smaller plots side by side below.

Matplotlib

fig = plt.figure()
ax1 = fig.add_axes([0.1, 0.5, 0.8, 0.4])  # top plot
ax2 = fig.add_axes([0.1, 0.1, 0.35, 0.3])  # bottom left
ax3 = fig.add_axes([0.55, 0.1, 0.35, 0.3])  # bottom right

Sample Program

This code creates a figure with one large plot on the left and two smaller plots stacked on the right side. Each plot shows a different function.

Matplotlib

import matplotlib.pyplot as plt
import numpy as np

x = np.linspace(0, 10, 100)
y1 = np.sin(x)
y2 = np.cos(x)
y3 = np.tan(x) / 10  # scaled down for visibility

fig = plt.figure(figsize=(8, 5))

# Big main plot
ax1 = fig.add_axes([0.1, 0.3, 0.6, 0.6])
ax1.plot(x, y1, label='sin(x)')
ax1.set_title('Main Plot: sin(x)')
ax1.legend()

# Smaller side plot
ax2 = fig.add_axes([0.75, 0.6, 0.2, 0.3])
ax2.plot(x, y2, 'r', label='cos(x)')
ax2.set_title('Side Plot: cos(x)')
ax2.legend()

# Smaller bottom plot
ax3 = fig.add_axes([0.75, 0.3, 0.2, 0.2])
ax3.plot(x, y3, 'g', label='tan(x)/10')
ax3.set_title('Bottom Plot: tan(x)/10')
ax3.legend()

plt.show()

Important Notes

Use add_axes for precise control of subplot size and position.

Coordinates are fractions of the figure size, so 0.1 means 10% from the left or bottom.

Remember to adjust figsize for overall figure size to keep plots clear.

Summary

You can create subplots of different sizes using fig.add_axes().

Specify position and size as fractions of the figure with [left, bottom, width, height].

This helps highlight important plots or save space in your figure.