Shared axes between subplots in Matplotlib - Interactive Code Practice

Practice - 5 Tasks

1fill in blank

easy

Complete the code to create two subplots sharing the x-axis.

Matplotlib

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

Drag options to blanks, or click blank then click option'

ATrue

BFalse

CNone

D0

Attempts:

3 left

💡 Hint

Common Mistakes

Using 'False' instead of 'True' disables sharing.

Using 'None' does not enable sharing.

Using '0' is not a valid boolean.

Setting sharex=True makes the subplots share the x-axis.

2fill in blank

medium

Complete the code to create subplots sharing both x and y axes.

Matplotlib

fig, axs = plt.subplots(2, 2, sharex=[1], sharey=[2])
axs[0, 0].plot([1, 2, 3], [1, 2, 3])
axs[1, 1].plot([1, 2, 3], [3, 2, 1])
plt.show()

Drag options to blanks, or click blank then click option'

AFalse

BTrue

CNone

D0

Attempts:

3 left

💡 Hint

Common Mistakes

Setting only one axis to share.

Using 'False' disables sharing.

Using 'None' does not enable sharing.

Setting both sharex and sharey to True shares both axes.

3fill in blank

hard

Fix the error in the code to share the y-axis between subplots.

Matplotlib

fig, (ax1, ax2) = plt.subplots(1, 2, sharey=[1])
ax1.plot([1, 2, 3], [3, 2, 1])
ax2.plot([1, 2, 3], [1, 2, 3])
plt.show()

Drag options to blanks, or click blank then click option'

ATrue

BNone

CFalse

D1

Attempts:

3 left

💡 Hint

Common Mistakes

Using '1' instead of 'True'.

Using 'None' disables sharing.

Using 'False' disables sharing.

To share the y-axis, sharey must be set to True.

4fill in blank

hard

Fill both blanks to create subplots sharing the x-axis and set figure size.

Matplotlib

fig, axs = plt.subplots(2, 1, sharex=[1], figsize=([2], 6))
axs[0].plot([1, 2, 3], [1, 4, 9])
axs[1].plot([1, 2, 3], [9, 4, 1])
plt.show()

Drag options to blanks, or click blank then click option'

ATrue

BFalse

C8

D10

Attempts:

3 left

💡 Hint

Common Mistakes

Using 'False' disables sharing.

Setting figure width too small or too large.

Confusing height and width values.

Setting sharex=True shares the x-axis. The figure width is set to 8 inches.

5fill in blank

hard

Fill all three blanks to create a 2x2 grid of subplots sharing y-axis and set figure size.

Matplotlib

fig, axs = plt.subplots(2, 2, sharey=[1], figsize=([2], [3]))
axs[0, 0].plot([1, 2, 3], [3, 2, 1])
axs[1, 1].plot([1, 2, 3], [1, 2, 3])
plt.show()

Drag options to blanks, or click blank then click option'

ATrue

BFalse

C6

D8

Attempts:

3 left

💡 Hint

Common Mistakes

Using 'False' disables sharing.

Swapping width and height values.

Using too small figure size causing cramped plots.

Sharing the y-axis is enabled with True. The figure size is set to 8 inches wide and 6 inches tall.

Practice

1. What is the main benefit of using sharex or sharey when creating subplots in matplotlib?

easy

A. It changes the color of the axes to match across subplots.

B. It makes the x or y axes use the same scale across subplots for easier comparison.

C. It automatically adds titles to each subplot.

D. It increases the size of the figure window.

Solution

1. Step 1: Understand the purpose of shared axes

   Shared axes mean multiple plots use the same scale on x or y axis, making it easier to compare data visually.

2. Step 2: Identify what sharex and sharey do

   These parameters in plt.subplots() link the axes scales so they stay consistent across subplots.

3. Final Answer:

   It makes the x or y axes use the same scale across subplots for easier comparison. -> Option B

4. Quick Check:

   Shared axes = same scale for easy comparison [OK]

Hint: Shared axes keep scales same for easy visual comparison [OK]

Common Mistakes:

• Thinking shared axes change colors
• Assuming shared axes add titles automatically
• Believing shared axes affect figure size

2. Which of the following is the correct way to create two subplots sharing the y-axis using matplotlib?

easy

A. plt.subplots(1, 2, sharex=false)

B. plt.subplots(2, 1, sharex=true)

C. plt.subplots(1, 2, sharey=false)

D. plt.subplots(2, 1, sharey=true)

Solution

1. Step 1: Identify the parameter for sharing y-axis

   The parameter sharey=true shares the y-axis between subplots.

2. Step 2: Check the subplot layout

   2, 1 means 2 rows and 1 column, which is valid for vertical stacking with shared y-axis.

3. Final Answer:

   plt.subplots(2, 1, sharey=true) -> Option D

4. Quick Check:

   sharey=true shares y-axis [OK]

Hint: Use sharey=true for vertical subplots sharing y-axis [OK]

Common Mistakes:

• Using sharex instead of sharey
• Mixing rows and columns incorrectly
• Setting sharey=false when sharing is needed

3. What will be the output of the following code snippet?

import matplotlib.pyplot as plt
fig, axs = plt.subplots(1, 2, sharex=True)
axs[0].plot([1, 2, 3], [10, 20, 30])
axs[1].plot([1, 2, 3], [15, 25, 35])
print(axs[1].get_xlim())

medium

A. (0.9, 3.1)

B. (10.0, 35.0)

C. (1.0, 3.0)

D. (15.0, 35.0)

Solution

1. Step 1: Understand sharex=true effect

   With sharex=True, both subplots share the same x-axis limits.

2. Step 2: Check data x-values and default limits

   The x data is [1, 2, 3]. Matplotlib adds a small margin, so limits are slightly beyond 1 and 3, e.g., (0.9, 3.1).

3. Final Answer:

   (0.9, 3.1) -> Option A

4. Quick Check:

   Shared x-axis limits include margin around data [OK]

Hint: Shared axes use same limits with small margin [OK]

Common Mistakes:

• Confusing x and y limits
• Expecting exact data min/max as limits
• Ignoring margin matplotlib adds

4. Consider this code:

fig, axs = plt.subplots(2, 2, sharex=True, sharey=True)
axs[0, 0].plot([1, 2], [3, 4])
axs[1, 1].plot([1, 2], [5, 6])
axs[1, 0].set_xlim(0, 3)
print(axs[0, 1].get_xlim())

What is the likely output and why might it cause confusion?

medium

A. Error because set_xlim cannot be used with shared axes.

B. (1.0, 2.0) because each subplot keeps its own limits despite sharing.

C. (0.0, 3.0) because all x-axes are shared and limits set on one affect all.

D. (3.0, 0.0) because limits are reversed causing an error.

Solution

1. Step 1: Understand sharex and sharey effect on limits

   Sharing axes means setting limits on one subplot updates all linked subplots.

2. Step 2: Analyze set_xlim call and its effect

   Setting set_xlim(0, 3) on axs[1, 0] changes x-axis limits for all subplots sharing x-axis.

3. Final Answer:

   (0.0, 3.0) because all x-axes are shared and limits set on one affect all. -> Option C

4. Quick Check:

   Shared axes share limits changes [OK]

Hint: Changing limits on one shared axis updates all linked subplots [OK]

Common Mistakes:

• Thinking each subplot keeps independent limits
• Expecting error from set_xlim with shared axes
• Confusing reversed limits as error

5. You want to create a 2x2 grid of subplots where the top row shares the x-axis, the left column shares the y-axis, but the bottom row and right column do not share axes. Which code snippet correctly achieves this?

hard

A. Use plt.subplots(2, 2, sharex='row', sharey='col') to share x in rows and y in columns.

B. Create subplots with sharex='col' and sharey='row' then manually adjust axes sharing.

C. Use plt.subplots(2, 2, sharex='col', sharey='row') to share x in columns and y in rows.

D. Create subplots without sharing and link axes manually with ax.sharex() and ax.sharey().

Solution

1. Step 1: Understand sharex and sharey options

   In plt.subplots(), sharex='col' shares x-axis within each column, and sharey='row' shares y-axis within each row.

2. Step 2: Match requirement to parameters

   We want top row to share x-axis (same x in row), so sharex='row' is needed. Left column shares y-axis (same y in column), so sharey='col' is needed.

3. Step 3: Identify correct code

   Use plt.subplots(2, 2, sharex='col', sharey='row') to share x in columns and y in rows. uses sharex='col' and sharey='row', which is reversed. Use plt.subplots(2, 2, sharex='row', sharey='col') to share x in rows and y in columns. uses sharex='row' and sharey='col', which matches the requirement.

4. Final Answer:

   Use plt.subplots(2, 2, sharex='row', sharey='col') to share x in rows and y in columns. -> Option A

5. Quick Check:

   sharex='row' and sharey='col' matches sharing needs [OK]

Hint: sharex='row' shares x in rows; sharey='col' shares y in columns [OK]

Common Mistakes:

• Confusing 'row' and 'col' values for sharex/sharey
• Assuming sharex='col' shares x in rows
• Trying to manually link axes unnecessarily