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.

Practice

1. What is the main advantage of using unequal subplot sizes in matplotlib?

easy

A. To automatically adjust colors of the plots

B. To make all charts the same size for uniformity

C. To highlight important charts by giving them more space

D. To reduce the total number of charts displayed

Solution

1. Step 1: Understand subplot size purpose

   Unequal subplot sizes allow some plots to be larger, drawing more attention.

2. Step 2: Compare options

   Only To highlight important charts by giving them more space mentions highlighting important charts by size, which is the main advantage.

3. Final Answer:

   To highlight important charts by giving them more space -> Option C

4. Quick Check:

   Unequal sizes highlight key charts [OK]

Hint: Unequal sizes = emphasize important plots [OK]

Common Mistakes:

• Thinking all subplots must be equal size
• Confusing size with color or number of plots
• Assuming unequal sizes reduce charts

2. Which of the following is the correct way to create subplots with unequal sizes using gridspec_kw in plt.subplots()?

easy

A. plt.subplots(1, 2, gridspec_kw={'width_ratios': [2, 1]})

B. plt.subplots(2, 1, gridspec_kw={'height_ratios': [1, 2]})

C. plt.subplots(1, 2, gridspec_kw={'height_ratios': [2, 1]})

D. plt.subplots(2, 1, gridspec_kw={'width_ratios': [1, 2]})

Solution

1. Step 1: Identify correct parameter for horizontal subplots

   For 1 row and 2 columns, use 'width_ratios' to set horizontal size ratios.

2. Step 2: Match ratios to subplot layout

   plt.subplots(1, 2, gridspec_kw={'width_ratios': [2, 1]}) uses 1 row, 2 columns with width_ratios, which is correct syntax.

3. Final Answer:

   plt.subplots(1, 2, gridspec_kw={'width_ratios': [2, 1]}) -> Option A

4. Quick Check:

   Width ratios for columns = plt.subplots(1, 2, gridspec_kw={'width_ratios': [2, 1]}) [OK]

Hint: Use width_ratios for columns, height_ratios for rows [OK]

Common Mistakes:

• Mixing width_ratios with rows instead of columns
• Using height_ratios for horizontal layout
• Wrong number of rows and columns in function

3. What will be the width ratio of the two subplots created by this code?

fig, axs = plt.subplots(1, 2, gridspec_kw={'width_ratios': [3, 1]})

medium

A. Both subplots have equal width

B. The subplots have random widths

C. The second subplot is 3 times wider than the first

D. The first subplot is 3 times wider than the second

Solution

1. Step 1: Understand width_ratios parameter

   The list [3, 1] means the first subplot width is 3 units, second is 1 unit.

2. Step 2: Interpret ratio meaning

   This means the first subplot is 3 times wider than the second subplot.

3. Final Answer:

   The first subplot is 3 times wider than the second -> Option D

4. Quick Check:

   Width ratio 3:1 means first is 3x wider [OK]

Hint: Ratio list directly shows relative sizes [OK]

Common Mistakes:

• Assuming equal widths despite ratios
• Reversing which subplot is wider
• Ignoring the ratio values

4. Identify the error in this code that tries to create unequal subplot sizes:

fig, axs = plt.subplots(2, 1, gridspec_kw={'width_ratios': [1, 2]})

medium

A. Incorrect number of subplots specified

B. Using width_ratios for vertical subplots instead of height_ratios

C. Missing plt.show() to display plots

D. width_ratios list length does not match subplot count

Solution

1. Step 1: Check subplot layout

   2 rows and 1 column means vertical stacking of subplots.

2. Step 2: Verify correct ratio parameter

   For vertical layout, use 'height_ratios', not 'width_ratios'.

3. Final Answer:

   Using width_ratios for vertical subplots instead of height_ratios -> Option B

4. Quick Check:

   Vertical layout needs height_ratios [OK]

Hint: Use height_ratios for rows, width_ratios for columns [OK]

Common Mistakes:

• Confusing width_ratios and height_ratios
• Ignoring subplot grid shape
• Assuming plt.show() affects subplot sizes

5. You want to create a figure with 3 subplots in one row where the middle subplot is twice as wide as the others. Which code correctly achieves this?

hard

A. plt.subplots(1, 3, gridspec_kw={'width_ratios': [1, 2, 1]})

B. plt.subplots(3, 1, gridspec_kw={'height_ratios': [1, 2, 1]})

C. plt.subplots(1, 3, gridspec_kw={'height_ratios': [1, 2, 1]})

D. plt.subplots(3, 1, gridspec_kw={'width_ratios': [1, 2, 1]})

Solution

1. Step 1: Determine subplot layout

   One row and three columns means horizontal layout.

2. Step 2: Choose correct ratio parameter

   For horizontal layout, use 'width_ratios' to set widths.

3. Step 3: Set ratios to make middle subplot twice as wide

   Use [1, 2, 1] so middle subplot is twice the width of others.

4. Final Answer:

   plt.subplots(1, 3, gridspec_kw={'width_ratios': [1, 2, 1]}) -> Option A

5. Quick Check:

   Horizontal layout with width_ratios = plt.subplots(1, 3, gridspec_kw={'width_ratios': [1, 2, 1]}) [OK]

Hint: Middle subplot twice wide = width_ratios [1, 2, 1] [OK]

Common Mistakes:

• Using height_ratios for horizontal layout
• Setting wrong number of rows and columns
• Reversing ratio order