Plt.subplots with rows and columns in Matplotlib - Practice Problems & Coding Challenges

Challenge - 5 Problems

❓ Predict Output

intermediate

What is the shape of the axes array?

Consider this code snippet using plt.subplots with 3 rows and 2 columns. What is the shape of the axes object?

Matplotlib

import matplotlib.pyplot as plt
fig, axes = plt.subplots(3, 2)
print(axes.shape)

A (2, 3)

B ()

C (6,)

D (3, 2)

💡 Hint

The axes is a 2D array matching rows and columns.

When you create subplots with 3 rows and 2 columns, axes is a 2D numpy array with shape (3, 2).

❓ data_output

intermediate

How many axes objects are created?

What is the total number of axes objects created by plt.subplots(4, 1)?

Matplotlib

import matplotlib.pyplot as plt
fig, axes = plt.subplots(4, 1)
print(len(axes))

A 4

B 1

C 5

D 0

💡 Hint

Number of axes equals rows times columns.

With 4 rows and 1 column, axes is a 1D array of length 4.

❓ visualization

advanced

Identify the subplot layout from the plot

You run this code to create subplots and plot data. Which layout matches the figure shown?

Matplotlib

import matplotlib.pyplot as plt
import numpy as np
x = np.linspace(0, 10, 100)
fig, axes = plt.subplots(2, 3)
for i, ax in enumerate(axes.flat):
    ax.plot(x, np.sin(x + i))
plt.show()

A 2 rows and 3 columns

B 3 rows and 2 columns

C 1 row and 6 columns

D 6 rows and 1 column

💡 Hint

Check how many rows and columns are passed to plt.subplots.

The code creates 2 rows and 3 columns of subplots, so the figure shows 6 plots arranged in 2 rows and 3 columns.

🔧 Debug

advanced

Why does this code raise an error?

This code tries to plot on subplots but raises an error. What is the cause?

Matplotlib

import matplotlib.pyplot as plt
fig, axes = plt.subplots(2, 2)
axes[2].plot([1, 2, 3])
plt.show()

A ValueError because plot data is invalid

B TypeError because axes is not subscriptable

C IndexError because axes is a 2D array and index 2 is invalid

D No error, code runs fine

💡 Hint

Check the shape of axes and how indexing works.

The axes is a 2x2 array, so axes[2] is out of bounds. You must use two indices like axes[0, 1].

🚀 Application

expert

How to flatten axes for iteration?

You create subplots with 3 rows and 3 columns. You want to loop over all axes in one loop. Which code correctly flattens the axes array?

Matplotlib

import matplotlib.pyplot as plt
fig, axes = plt.subplots(3, 3)
# Which line below correctly flattens axes for iteration?

A

for ax in axes.flat:
    ax.plot([1, 2, 3])

B

for ax in axes.flatten():
    ax.plot([1, 2, 3])

C

for ax in axes.ravel():
    ax.plot([1, 2, 3])

D

for ax in axes:
    ax.plot([1, 2, 3])

💡 Hint

Check the methods available on numpy arrays for flattening.

The flatten() method returns a 1D copy of the array, allowing iteration over all axes.

Practice

1. What does plt.subplots(2, 3) create in matplotlib?

easy

A. A figure with 2 rows and 3 columns of subplots

B. A figure with 3 rows and 2 columns of subplots

C. A single plot with size 2x3 inches

D. A figure with 6 rows and 1 column of subplots

Solution

1. Step 1: Understand plt.subplots parameters

   The first parameter is the number of rows, the second is columns.

2. Step 2: Apply to given code

   plt.subplots(2, 3) means 2 rows and 3 columns of subplots.

3. Final Answer:

   A figure with 2 rows and 3 columns of subplots -> Option A

4. Quick Check:

   rows=2, columns=3 = B [OK]

Hint: First number = rows, second = columns in plt.subplots [OK]

Common Mistakes:

• Confusing rows and columns order
• Thinking parameters set figure size
• Assuming single plot created

2. Which of the following is the correct syntax to create a 3x1 subplot grid using plt.subplots?

easy

A. fig, axes = plt.subplots(1, 3)

B. fig, axes = plt.subplots(3)

C. fig, axes = plt.subplots(3, 1)

D. fig, axes = plt.subplots(rows=3, cols=1)

Solution

1. Step 1: Recall plt.subplots parameter order

   The first argument is rows, second is columns.

2. Step 2: Match to 3 rows and 1 column

   plt.subplots(3, 1) creates 3 rows and 1 column.

3. Final Answer:

   fig, axes = plt.subplots(3, 1) -> Option C

4. Quick Check:

   3 rows, 1 column = C [OK]

Hint: Remember: plt.subplots(rows, columns) order matters [OK]

Common Mistakes:

• Swapping rows and columns
• Using single number for both dimensions
• Using keyword arguments incorrectly

3. What is the shape of axes returned by fig, axes = plt.subplots(2, 2)?

medium

A. A 1D array with 4 axes objects

B. A 2D array with shape (2, 2) of axes objects

C. A list of 2 axes objects

D. A single axes object

Solution

1. Step 1: Understand axes shape for multiple rows and columns

   When rows and columns are more than 1, axes is a 2D array matching shape.

2. Step 2: Apply to plt.subplots(2, 2)

   axes will be a 2x2 array of axes objects.

3. Final Answer:

   A 2D array with shape (2, 2) of axes objects -> Option B

4. Quick Check:

   Multiple rows and columns = 2D axes array [OK]

Hint: Multiple rows & columns -> axes is 2D array [OK]

Common Mistakes:

• Assuming axes is always 1D
• Confusing number of axes with shape
• Expecting a single axes object

4. Given the code:

fig, axes = plt.subplots(2, 2)
axes[2, 0].plot([1, 2, 3])

What error will occur?

medium

A. No error, plot will display

B. TypeError: axes object is not subscriptable

C. AttributeError: 'AxesSubplot' object has no attribute 'plot'

D. IndexError: index 2 is out of bounds for axis 0 with size 2

Solution

1. Step 1: Check axes shape from plt.subplots(2, 2)

   axes is a 2x2 array with indices 0 and 1 for rows and columns.

2. Step 2: Analyze axes[2, 0] access

   Index 2 for rows is out of bounds since max index is 1.

3. Final Answer:

   IndexError: index 2 is out of bounds for axis 0 with size 2 -> Option D

4. Quick Check:

   axes shape (2,2), index 2 invalid [OK]

Hint: Check axes array shape before indexing [OK]

Common Mistakes:

• Using invalid indices beyond shape
• Confusing axes as list instead of array
• Expecting no error on wrong index

5. You want to create a 2x3 grid of subplots and plot a line on each subplot with data from a list of 6 arrays. Which code correctly accesses each subplot to plot inside a nested loop?

hard

A. for i in range(2):
for j in range(3):
axes[i][j].plot(data[i*3 + j])

B. for i in range(2):
for j in range(3):
axes[i, j].plot(data[i + j])

C. for i in range(3):
for j in range(2):
axes[i][j].plot(data[i*2 + j])

D. for i in range(2):
for j in range(3):
axes[j][i].plot(data[i*3 + j])

Solution

1. Step 1: Understand axes shape and indexing

   plt.subplots(2, 3) creates axes as a 2x3 array, indexed as axes[row][col].

2. Step 2: Correctly map data list to subplot indices

   Data index = row * number_of_columns + column = i*3 + j matches subplot position.

3. Final Answer:

   for i in range(2): for j in range(3): axes[i][j].plot(data[i*3 + j]) -> Option A

4. Quick Check:

   axes[row][col], data index = row*cols + col [OK]

Hint: Use axes[row][col] and data index = row*cols + col [OK]

Common Mistakes:

• Swapping row and column loops
• Incorrect data indexing
• Using axes[j][i] instead of axes[i][j]