Constrained layout vs tight layout in Matplotlib - Practice Questions

Challenge - 5 Problems

❓ Predict Output

intermediate

Output difference between constrained_layout and tight_layout

What will be the main visual difference when running this code?

import matplotlib.pyplot as plt
fig, axs = plt.subplots(2, 2, constrained_layout=True)
for ax in axs.flat:
    ax.plot([1, 2, 3], [1, 4, 9])
plt.show()

compared to the same code but using plt.tight_layout() instead of constrained_layout=True?

Matplotlib

import matplotlib.pyplot as plt
fig, axs = plt.subplots(2, 2, constrained_layout=True)
for ax in axs.flat:
    ax.plot([1, 2, 3], [1, 4, 9])
plt.show()

A The plots will be arranged vertically with large gaps between subplots.

B The plots will overlap and axes labels will be cut off because no layout adjustment is applied.

C The plots will have fixed spacing and tight_layout will add padding around the figure edges.

D The plots will have automatically adjusted spacing with no overlaps, and axes labels will not be cut off.

💡 Hint

Think about how constrained_layout automatically adjusts subplot parameters to fit labels and titles.

constrained_layout=True automatically adjusts subplot parameters to prevent overlaps and clipping of labels. It is more advanced than tight_layout() and handles complex layouts better.

❓ data_output

intermediate

Number of subplots visible with tight_layout and constrained_layout

Consider this code snippet:

import matplotlib.pyplot as plt
fig, axs = plt.subplots(3, 3)
for ax in axs.flat:
    ax.set_title('Title')
plt.tight_layout()
plt.show()

How many subplot titles will be fully visible without overlap?

Matplotlib

import matplotlib.pyplot as plt
fig, axs = plt.subplots(3, 3)
for ax in axs.flat:
    ax.set_title('Title')
plt.tight_layout()
plt.show()

A Some subplot titles will be cut off or overlap due to limited spacing.

B Only the first row of subplot titles will be fully visible; others will overlap.

C All 9 subplot titles will be fully visible without overlap.

D No subplot titles will be visible because tight_layout does not adjust titles.

💡 Hint

Think about how tight_layout() handles many subplots with titles.

tight_layout() tries to adjust spacing but may not fully prevent overlaps or clipping when many subplots have titles. Some titles may be cut off or overlap.

🔧 Debug

advanced

Why does tight_layout fail with colorbars?

Given this code:

import matplotlib.pyplot as plt
fig, ax = plt.subplots()
cbar = fig.colorbar(plt.cm.ScalarMappable(), ax=ax)
plt.tight_layout()
plt.show()

Why does plt.tight_layout() not adjust the layout properly to avoid overlap with the colorbar?

Matplotlib

import matplotlib.pyplot as plt
fig, ax = plt.subplots()
cbar = fig.colorbar(plt.cm.ScalarMappable(), ax=ax)
plt.tight_layout()
plt.show()

A Because tight_layout does not consider colorbars when adjusting subplot parameters.

B Because colorbars are automatically handled by tight_layout and no adjustment is needed.

C Because the colorbar is outside the figure and tight_layout only adjusts inside axes.

D Because tight_layout requires constrained_layout to be enabled to work with colorbars.

💡 Hint

Think about what elements tight_layout adjusts and what it ignores.

tight_layout() adjusts subplot parameters but does not account for colorbars, so overlaps can occur. constrained_layout handles colorbars better.

🚀 Application

advanced

Choosing layout method for complex figure with multiple axes and colorbars

You want to create a figure with 4 subplots and 2 colorbars. Which layout method should you use to ensure no overlaps and proper spacing?

A Manually adjust subplot positions with <code>fig.subplots_adjust()</code>.

B Use <code>constrained_layout=True</code> when creating the figure and axes.

C Use <code>plt.tight_layout()</code> after creating all subplots and colorbars.

D Use no layout adjustment and rely on default spacing.

💡 Hint

Consider which method handles colorbars and complex layouts automatically.

constrained_layout=True automatically adjusts spacing including colorbars and multiple axes, making it best for complex figures.

🧠 Conceptual

expert

Key difference between constrained_layout and tight_layout

Which statement best describes the key difference between constrained_layout and tight_layout in matplotlib?

A <code>tight_layout</code> supports colorbars and legends automatically, but <code>constrained_layout</code> does not.

B <code>tight_layout</code> is the default layout engine in matplotlib, while <code>constrained_layout</code> is deprecated.

C <code>constrained_layout</code> uses a layout engine considering all figure elements simultaneously, while <code>tight_layout</code> uses a simpler algorithm based on subplot bounding boxes.

D <code>constrained_layout</code> adjusts subplot parameters after drawing, while <code>tight_layout</code> adjusts before drawing.

💡 Hint

Think about how each method calculates spacing and what elements they consider.

constrained_layout uses a more advanced layout engine that considers all figure elements (axes, colorbars, legends) simultaneously for spacing. tight_layout uses a simpler approach based on bounding boxes of subplots.