Nested subplots with subfigures in Matplotlib

Introduction

Nested subplots with subfigures help you organize multiple plots clearly in one figure. This makes it easier to compare related charts side by side.

You want to show different groups of charts in one figure, each group having its own layout.

You need to compare multiple sets of data with separate titles and labels.

You want to save space by combining many plots in a neat, structured way.

You are preparing a report or presentation and want clear visual sections.

You want to control spacing and arrangement of plots inside bigger plot areas.

Syntax

Matplotlib

fig = plt.figure()
subfigs = fig.subfigures(nrows, ncols)
ax = subfigs[row, col].subplots(nrows, ncols)

fig.subfigures() creates big sections inside the main figure.

Each subfigure can have its own subplots() grid inside it.

Examples

Creates one figure with two side-by-side subfigures, each with one plot.

Matplotlib

fig = plt.figure()
subfigs = fig.subfigures(1, 2)
ax1 = subfigs[0].subplots()
ax2 = subfigs[1].subplots()

Creates two stacked subfigures. The first has two rows of plots, the second has two columns.

Matplotlib

fig = plt.figure()
subfigs = fig.subfigures(2, 1)
ax1 = subfigs[0].subplots(2, 1)
ax2 = subfigs[1].subplots(1, 2)

Sample Program

This code creates a figure with two subfigures side by side. The left subfigure has two line plots stacked vertically. The right subfigure has two scatter plots arranged horizontally. Each subfigure has its own title.

Matplotlib

import matplotlib.pyplot as plt
import numpy as np

# Create main figure
fig = plt.figure(constrained_layout=True, figsize=(8, 6))

# Create 2 subfigures side by side
subfigs = fig.subfigures(1, 2, wspace=0.07)

# Left subfigure with 2 rows of plots
x = np.linspace(0, 10, 100)
ax_left = subfigs[0].subplots(2, 1)
ax_left[0].plot(x, np.sin(x))
ax_left[0].set_title('Sine Wave')
ax_left[1].plot(x, np.cos(x), 'r')
ax_left[1].set_title('Cosine Wave')

# Right subfigure with 2 columns of plots
ax_right = subfigs[1].subplots(1, 2)
ax_right[0].scatter(x, np.sin(x))
ax_right[0].set_title('Sine Scatter')
ax_right[1].scatter(x, np.cos(x), color='orange')
ax_right[1].set_title('Cosine Scatter')

# Set main titles for subfigures
subfigs[0].suptitle('Trigonometric Line Plots')
subfigs[1].suptitle('Trigonometric Scatter Plots')

plt.show()

Important Notes

Use constrained_layout=True in plt.figure() to avoid overlapping labels.

Subfigures help keep related plots grouped and easier to read.

You can customize spacing between subfigures with wspace and hspace.

Summary

Nested subplots with subfigures organize multiple plots clearly inside one figure.

Use fig.subfigures() to create big sections, then add subplots inside each.

This method improves readability and layout control for complex visualizations.

Practice

1. What is the main purpose of using fig.subfigures() in matplotlib?

easy

A. To add a single plot to a figure

B. To create large groups inside a figure that can hold their own smaller plots

C. To change the color of a plot

D. To save a figure as an image file

Solution

1. Step 1: Understand the role of fig.subfigures()

   This method creates subfigures, which are large groups inside a main figure.

2. Step 2: Recognize the use of subfigures

   Each subfigure can contain its own grid of smaller plots, helping organize complex layouts.

3. Final Answer:

   To create large groups inside a figure that can hold their own smaller plots -> Option B

4. Quick Check:

   Subfigures = large groups inside figure [OK]

Hint: Subfigures group plots inside a figure [OK]

Common Mistakes:

• Thinking subfigures add only one plot
• Confusing subfigures with saving figures
• Assuming subfigures change plot colors

2. Which of the following is the correct way to create two subfigures side by side in matplotlib?

easy

A. fig.subplots(1, 2)

B. fig.subfigures(2, 1)

C. fig.subfigures(1, 2)

D. fig.subfigures(2, 2)

Solution

1. Step 1: Understand subfigures layout parameters

   The parameters (rows, columns) define the grid of subfigures. For side by side, use 1 row and 2 columns.

2. Step 2: Match parameters to options

   fig.subfigures(1, 2) uses fig.subfigures(1, 2), which creates 1 row and 2 columns, placing subfigures side by side.

3. Final Answer:

   fig.subfigures(1, 2) -> Option C

4. Quick Check:

   Side by side = 1 row, 2 columns [OK]

Hint: Rows first, columns second in subfigures() [OK]

Common Mistakes:

• Swapping rows and columns
• Using subplots() instead of subfigures()
• Choosing more rows than needed

3. What will be the output shape of the axes array when running this code?

fig = plt.figure()
subfigs = fig.subfigures(2, 1)
ax1 = subfigs[0].subplots(1, 3)
ax2 = subfigs[1].subplots(2, 2)
print(ax1.shape, ax2.shape)

medium

A. (1, 3) (4,)

B. (3,) (4,)

C. (3,) (2, 2)

D. (1, 3) (2, 2)

Solution

1. Step 1: Analyze subfigures and their subplot grids

   First subfigure has 1 row and 3 columns, so ax1 shape is (1, 3). Second subfigure has 2 rows and 2 columns, so ax2 shape is (2, 2).

2. Step 2: Confirm shapes printed

   Printing ax1.shape and ax2.shape outputs (1, 3) and (2, 2) respectively.

3. Final Answer:

   (1, 3) (2, 2) -> Option D

4. Quick Check:

   Subplots shape = (rows, columns) [OK]

Hint: Shape matches (rows, columns) in subplots() [OK]

Common Mistakes:

• Confusing flat arrays with 2D arrays
• Mixing up rows and columns
• Assuming subfigures affect shape differently

4. Identify the error in this code snippet for creating nested subplots with subfigures:

fig = plt.figure()
subfigs = fig.subfigures(1, 2)
ax = subfigs.subplots(2, 2)

medium

A. subfigs.subplots() should be called on each subfigure, not on the list

B. fig.subfigures() requires 3 arguments, missing one

C. subfigs is a list, so subfigs.subplots() is invalid

D. subfigures cannot have nested subplots

Solution

1. Step 1: Understand the type of subfigs

   fig.subfigures(1, 2) returns a list or array of subfigure objects, not a single subfigure.

2. Step 2: Correct method call for subplots

   We must call subplots() on each individual subfigure, not on the entire list subfigs.

3. Final Answer:

   subfigs.subplots() should be called on each subfigure, not on the list -> Option A

4. Quick Check:

   Call subplots() on single subfigure [OK]

Hint: Call subplots() on one subfigure, not list [OK]

Common Mistakes:

• Calling subplots() on the list of subfigures
• Assuming subfigures() needs 3 args
• Thinking subfigures can't have subplots

5. You want to create a figure with 2 subfigures stacked vertically. The top subfigure should have a 2x2 grid of plots, and the bottom subfigure a single plot. Which code correctly achieves this?

hard

A. fig = plt.figure()
subfigs = fig.subfigures(2, 1)
axs_top = subfigs[0].subplots(2, 2)
axs_bottom = subfigs[1].subplots(1, 1)

B. fig = plt.figure()
subfigs = fig.subfigures(1, 2)
axs_top = subfigs[0].subplots(2, 2)
axs_bottom = subfigs[1].subplots(1, 1)

C. fig = plt.figure()
subfigs = fig.subfigures(2, 1)
axs_top = subfigs.subplots(2, 2)
axs_bottom = subfigs.subplots(1, 1)

D. fig = plt.figure()
subfigs = fig.subfigures(1, 2)
axs_top = subfigs.subplots(2, 2)
axs_bottom = subfigs.subplots(1, 1)

Solution

1. Step 1: Set subfigures layout vertically

   Two subfigures stacked vertically means 2 rows and 1 column, so fig.subfigures(2, 1).

2. Step 2: Create subplots inside each subfigure

   Top subfigure gets a 2x2 grid, bottom subfigure gets a single plot (1x1). Call subplots() on each subfigure individually.

3. Final Answer:

   fig = plt.figure() subfigs = fig.subfigures(2, 1) axs_top = subfigs[0].subplots(2, 2) axs_bottom = subfigs[1].subplots(1, 1) -> Option A

4. Quick Check:

   Vertical stack = (2,1), call subplots() on each subfigure [OK]

Hint: Vertical stack = (2,1), subplots() on each subfigure [OK]

Common Mistakes:

• Using (1,2) for vertical stacking
• Calling subplots() on the list of subfigures
• Not matching subplot grids to subfigures