Tight layout for spacing in Matplotlib - Practice Problems & Coding Challenges

Challenge - 5 Problems

❓ Predict Output

intermediate

What is the output of this matplotlib layout code?

Consider the following Python code using matplotlib to create a plot with tight layout:

import matplotlib.pyplot as plt
fig, ax = plt.subplots()
ax.plot([1, 2, 3], [1, 4, 9])
fig.tight_layout()
print(fig.subplotpars.left, fig.subplotpars.right)

What will be printed?

Matplotlib

import matplotlib.pyplot as plt
fig, ax = plt.subplots()
ax.plot([1, 2, 3], [1, 4, 9])
fig.tight_layout()
print(round(fig.subplotpars.left, 2), round(fig.subplotpars.right, 2))

A 0.1 0.95

B 0.125 0.9

C 0.15 0.85

D 0.2 0.8

💡 Hint

tight_layout adjusts subplot parameters to give specified padding.

After calling fig.tight_layout(), the subplot parameters adjust to fit the plot tightly. The left and right margins typically become around 0.1 and 0.95 respectively.

❓ data_output

intermediate

How many subplots fit without overlap using tight_layout?

Given this code creating multiple subplots:

import matplotlib.pyplot as plt
fig, axs = plt.subplots(3, 3)
fig.tight_layout()
print(len(axs.flatten()))

What is the output?

Matplotlib

import matplotlib.pyplot as plt
fig, axs = plt.subplots(3, 3)
fig.tight_layout()
print(len(axs.flatten()))

A 9

B 6

C 12

D 3

💡 Hint

Count total subplots created in a 3x3 grid.

3 rows and 3 columns create 9 subplots total. tight_layout does not change the number of subplots.

❓ visualization

advanced

Which option shows correct tight layout spacing for overlapping labels?

Which code snippet will produce a plot where x-axis labels do not overlap, using tight layout?

A

fig, ax = plt.subplots()
ax.plot(range(10))
plt.xticks(rotation=45)
fig.subplots_adjust(left=0.2)
plt.show()

B

fig, ax = plt.subplots()
ax.plot(range(10))
plt.xticks(rotation=45)
plt.show()

C

fig, ax = plt.subplots()
ax.plot(range(10))
fig.subplots_adjust(bottom=0.1)
plt.show()

D

fig, ax = plt.subplots()
ax.plot(range(10))
plt.xticks(rotation=45)
fig.tight_layout()
plt.show()

💡 Hint

tight_layout helps adjust spacing automatically for rotated labels.

Option D uses fig.tight_layout() after rotating x-axis labels, which prevents overlap by adjusting margins automatically.

🔧 Debug

advanced

Why does tight_layout not fix overlapping titles?

Given this code:

import matplotlib.pyplot as plt
fig, axs = plt.subplots(2, 1)
axs[0].set_title('Title 1')
axs[1].set_title('Title 2')
fig.tight_layout()
plt.show()

Why might the titles still overlap?

A The figure size is too large for tight_layout to work

B tight_layout only works for legends, not titles

C tight_layout does not adjust space for suptitle or axes titles by default

D tight_layout requires plt.tight_layout() instead of fig.tight_layout()

💡 Hint

Consider what tight_layout adjusts automatically.

tight_layout adjusts subplot parameters but does not reserve space for axes titles or suptitles automatically, so titles can overlap.

🚀 Application

expert

How to combine tight_layout with constrained_layout for best spacing?

You want to create a figure with multiple subplots and avoid label and title overlaps. Which approach is best?

A Call fig.tight_layout() and then set constrained_layout=True

B Use constrained_layout=True when creating figure and avoid calling tight_layout()

C Call fig.tight_layout() twice after plotting

D Use plt.subplots_adjust() only without tight_layout or constrained_layout

💡 Hint

constrained_layout is a newer layout manager than tight_layout.

Using constrained_layout=True when creating the figure automatically manages spacing better than tight_layout, so calling both is not recommended.