Shared axes between subplots in Matplotlib - Practice Problems & Coding Challenges

Challenge - 5 Problems

❓ Predict Output

intermediate

Output of shared x-axis subplots

What will be the output of this code that creates two subplots sharing the x-axis?

Matplotlib

import matplotlib.pyplot as plt
fig, (ax1, ax2) = plt.subplots(2, sharex=True)
ax1.plot([1, 2, 3], [1, 4, 9])
ax2.plot([1, 2, 3], [2, 3, 4])
plt.show()

A A single plot with two lines overlapping sharing both axes.

B Two plots stacked vertically with independent x-axis labels on both plots.

C Two plots stacked vertically with the same x-axis labels visible only on the bottom plot.

D Two plots side by side sharing the y-axis with independent x-axis labels.

💡 Hint

Think about what sharex=True does when creating subplots stacked vertically.

Using sharex=True makes the subplots share the same x-axis. When stacked vertically, only the bottom plot shows the x-axis labels to avoid repetition.

❓ data_output

intermediate

Number of tick labels shown with shared y-axis

Given this code, how many y-axis tick labels will be visible in total?

Matplotlib

import matplotlib.pyplot as plt
fig, (ax1, ax2) = plt.subplots(2, sharey=True)
ax1.plot([1, 2, 3], [1, 4, 9])
ax2.plot([1, 2, 3], [2, 3, 4])
plt.show()

A No y-axis tick labels are shown on either subplot.

B Both subplots show independent y-axis tick labels on their left side.

C Only the left y-axis of the first subplot shows tick labels; the second subplot hides them.

D Both subplots show y-axis tick labels on the right side.

💡 Hint

When subplots are stacked vertically with sharey=True, both show y-axis tick labels on the left side, as hiding applies to horizontal sharing.

With sharey=True in a vertical stack (2 rows, 1 column), both subplots display y-axis tick labels on their left side because automatic hiding of y-labels occurs only for horizontally adjacent subplots.

❓ visualization

advanced

Effect of sharex and sharey on subplot grid

Which option correctly describes the layout and axis sharing of this code?

Matplotlib

import matplotlib.pyplot as plt
fig, axs = plt.subplots(2, 2, sharex='col', sharey='row')
for i in range(2):
    for j in range(2):
        axs[i, j].plot([1, 2, 3], [1, 2, 3])
plt.show()

A Subplots in each row share the x-axis; subplots in each column share the y-axis.

B All subplots share both x and y axes globally.

C No axes are shared; each subplot has independent axes.

D Subplots in each column share the x-axis; subplots in each row share the y-axis.

💡 Hint

Check the parameters sharex='col' and sharey='row' carefully.

sharex='col' means subplots in the same column share x-axis; sharey='row' means subplots in the same row share y-axis.

🔧 Debug

advanced

Identify the error in shared axes subplot code

What error will this code raise when run?

Matplotlib

import matplotlib.pyplot as plt
fig, axs = plt.subplots(2, 2, sharex=True, sharey=True)
axs[0].plot([1, 2, 3], [1, 4, 9])
plt.show()

A AttributeError: 'numpy.ndarray' object has no attribute 'plot'

B IndexError: list index out of range

C AttributeError: 'Figure' object has no attribute 'plot'

D No error; the code runs and shows plots.

💡 Hint

Check how axs is indexed when subplots creates a 2x2 array.

plt.subplots(2, 2) returns a 2D array of axes. axs[0] is a 1D array (the first row), not a single AxesSubplot, so axs[0].plot(...) causes AttributeError: 'numpy.ndarray' object has no attribute 'plot'.

🚀 Application

expert

Creating a complex shared axes layout

You want to create a 3x1 subplot layout where all subplots share the x-axis but have independent y-axes. Which code snippet achieves this correctly?

A

fig, axs = plt.subplots(3, 1, sharex=True)
for ax in axs:
    ax.plot([1, 2, 3], [1, 2, 3])
plt.show()

B

fig, axs = plt.subplots(3, 1, sharey=True)
for ax in axs:
    ax.plot([1, 2, 3], [1, 2, 3])
plt.show()

C

fig, axs = plt.subplots(3, 1, sharex=False)
for ax in axs:
    ax.plot([1, 2, 3], [1, 2, 3])
plt.show()

D

fig, axs = plt.subplots(3, 1)
for ax in axs:
    ax.plot([1, 2, 3], [1, 2, 3])
plt.show()

💡 Hint

Sharing x-axis means sharex=True; independent y-axes means no sharey.

Setting sharex=True shares the x-axis among subplots. Not setting sharey means y-axes are independent.