Constrained layout vs tight layout in Matplotlib - Hands-On Comparison

Constrained layout vs tight layout in Matplotlib

📖 Scenario: You are creating a simple report with two plots side by side. You want to make sure the plots and their labels do not overlap and look neat.

🎯 Goal: Learn how to use constrained_layout and tight_layout in Matplotlib to improve plot spacing and appearance.

📋 What You'll Learn

Create a figure with two subplots side by side

Use constrained_layout=True in the figure creation

Create a variable use_tight_layout to switch layout methods

Apply tight_layout() if use_tight_layout is True

Print which layout method is used

💡 Why This Matters

🌍 Real World

When creating reports or presentations with multiple plots, good layout ensures the visuals are clear and labels are readable.

💼 Career

Data scientists and analysts often need to present data clearly. Knowing how to control plot layouts helps make professional and understandable charts.

1

Create a figure with two subplots using constrained_layout

Create a Matplotlib figure called fig with constrained_layout=True and two subplots side by side stored in ax1 and ax2. Plot a simple line on each subplot: ax1.plot([1, 2, 3], [1, 4, 9]) and ax2.plot([1, 2, 3], [2, 3, 5]).

Matplotlib

# Create figure with constrained_layout=True and two subplots ax1, ax2
# Plot lines on ax1 and ax2

Need a hint?

Use plt.subplots(1, 2, constrained_layout=True) to create the figure and axes.

2

Add a variable to choose layout method

Create a variable called use_tight_layout and set it to False. This will control if we use tight_layout() later.

Matplotlib

import matplotlib.pyplot as plt

fig, (ax1, ax2) = plt.subplots(1, 2, constrained_layout=True)
ax1.plot([1, 2, 3], [1, 4, 9])
ax2.plot([1, 2, 3], [2, 3, 5])

# Create variable use_tight_layout and set to False

Need a hint?

Just create a variable use_tight_layout and assign False.

3

Apply tight_layout if use_tight_layout is True

Write an if statement that checks if use_tight_layout is True. If yes, call fig.tight_layout() to adjust the layout.

Matplotlib

import matplotlib.pyplot as plt

fig, (ax1, ax2) = plt.subplots(1, 2, constrained_layout=True)
ax1.plot([1, 2, 3], [1, 4, 9])
ax2.plot([1, 2, 3], [2, 3, 5])

use_tight_layout = False

# If use_tight_layout is True, call fig.tight_layout()

Need a hint?

Use an if statement to check use_tight_layout and call fig.tight_layout() inside it.

4

Print which layout method is used and show the plot

Print 'Using tight_layout' if use_tight_layout is True, otherwise print 'Using constrained_layout'. Then call plt.show() to display the figure.

Matplotlib

import matplotlib.pyplot as plt

fig, (ax1, ax2) = plt.subplots(1, 2, constrained_layout=True)
ax1.plot([1, 2, 3], [1, 4, 9])
ax2.plot([1, 2, 3], [2, 3, 5])

use_tight_layout = False

if use_tight_layout:
    fig.tight_layout()

# Print which layout is used
# Show the plot

Need a hint?

Use print() to show which layout is used based on use_tight_layout. Then call plt.show().