Subplots for multiple charts in Data Analysis Python - Practice Problems & Coding Challenges

Challenge - 5 Problems

❓ Predict Output

intermediate

Output of a 2x2 subplot grid with line plots

What is the output of this code that creates a 2x2 grid of line plots with matplotlib?

Data Analysis Python

import matplotlib.pyplot as plt
import numpy as np
x = np.arange(5)
fig, axs = plt.subplots(2, 2)
for i, ax in enumerate(axs.flat):
    ax.plot(x, x*(i+1))
plt.tight_layout()
plt.show()

A A single plot with four lines overlapping, slopes 1 to 4.

B Four line plots arranged in 2 rows and 2 columns, each plot showing lines with slopes 1, 2, 3, and 4 respectively.

C An error because axs.flat is not iterable.

D Four scatter plots arranged in 2 rows and 2 columns.

💡 Hint

Remember that axs.flat lets you iterate over all subplot axes in a grid.

The code creates a 2x2 grid of subplots. The loop uses axs.flat to access each subplot axis and plots a line with slope increasing from 1 to 4. The result is four separate line plots arranged in a 2x2 grid.

❓ data_output

intermediate

Number of subplots created by plt.subplots(3,1)

How many subplot axes are created by the command plt.subplots(3, 1)?

A An error because 3 and 1 are invalid arguments

B 1 subplot axis spanning 3 rows

C 6 subplot axes arranged in 3 rows and 2 columns

D 3 subplot axes arranged vertically

💡 Hint

The first argument is rows, the second is columns.

plt.subplots(3, 1) creates 3 subplot axes arranged vertically in a single column.

❓ visualization

advanced

Identify the subplot layout from the code

Given this code, what is the layout of the subplots shown?

Data Analysis Python

import matplotlib.pyplot as plt
fig, axs = plt.subplots(1, 3, figsize=(9, 3))
for i, ax in enumerate(axs):
    ax.bar([1, 2, 3], [i+1, i+2, i+3])
plt.show()

A Three bar charts side by side in one row

B Three bar charts stacked vertically in one column

C A single bar chart with three bars

D An error because axs is not iterable

💡 Hint

plt.subplots(1, 3) means 1 row and 3 columns.

The code creates a figure with 1 row and 3 columns of subplots. Each subplot shows a bar chart. So the layout is three bar charts side by side.

🔧 Debug

advanced

Why does this subplot code raise an error?

What error does this code raise and why? import matplotlib.pyplot as plt fig, axs = plt.subplots(2, 2) axs[2].plot([1, 2, 3], [4, 5, 6]) plt.show()

A IndexError because axs has shape (2, 2) and index 2 is out of range

B TypeError because axs is not subscriptable

C ValueError because plot data lengths differ

D No error, the plot shows correctly

💡 Hint

axs is a 2D array of axes, not a flat list.

axs is a 2x2 numpy array of axes. Indexing axs[2] tries to access the third row which does not exist, causing IndexError.

🚀 Application

expert

Create a 2x3 grid of scatter plots with different colors

You want to create a 2 rows by 3 columns grid of scatter plots using matplotlib. Each subplot should plot points (x, y) where x = [1,2,3] and y = [3,2,1] multiplied by the subplot index (starting at 1). Each subplot should have a unique color from ['red', 'green', 'blue', 'orange', 'purple', 'brown']. Which code snippet correctly creates this figure?

A

import matplotlib.pyplot as plt
x = [1,2,3]
y = [3,2,1]
colors = ['red', 'green', 'blue', 'orange', 'purple', 'brown']
fig, axs = plt.subplots(2, 3)
for i in range(6):
    axs[i].scatter(x, [v*i for v in y], color=colors[i])
plt.show()

B

import matplotlib.pyplot as plt
x = [1,2,3]
y = [3,2,1]
colors = ['red', 'green', 'blue', 'orange', 'purple', 'brown']
fig, axs = plt.subplots(3, 2)
for i, ax in enumerate(axs.flat):
    ax.scatter(x, [v*i for v in y], color=colors[i])
plt.show()

C

import matplotlib.pyplot as plt
x = [1,2,3]
y = [3,2,1]
colors = ['red', 'green', 'blue', 'orange', 'purple', 'brown']
fig, axs = plt.subplots(2, 3)
for i, ax in enumerate(axs.flat, 1):
    ax.scatter(x, [v*i for v in y], color=colors[i-1])
plt.tight_layout()
plt.show()

D

import matplotlib.pyplot as plt
x = [1,2,3]
y = [3,2,1]
colors = ['red', 'green', 'blue', 'orange', 'purple', 'brown']
fig, axs = plt.subplots(2, 3)
for i, ax in enumerate(axs):
    ax.scatter(x, [v*(i+1) for v in y], color=colors[i])
plt.show()

💡 Hint

Use axs.flat to iterate over all axes in a 2D grid and start index at 1 for multiplication.

Option C correctly creates a 2x3 grid, iterates over all 6 axes with index starting at 1, multiplies y by i, and assigns colors correctly. Other options have wrong shape, indexing, or iteration errors.

Practice

1. What is the main purpose of using plt.subplots() in data visualization?

easy

A. To create multiple charts in one figure for easy comparison

B. To save a plot as an image file

C. To change the color of a single plot

D. To add a title to a chart

Solution

1. Step 1: Understand the function of plt.subplots()

   This function creates a figure and a grid of subplots (axes) to hold multiple charts.

2. Step 2: Recognize the benefit of multiple charts in one figure

   Having multiple charts in one figure helps compare data visually side-by-side.

3. Final Answer:

   To create multiple charts in one figure for easy comparison -> Option A

4. Quick Check:

   Subplots = multiple charts in one figure [OK]

Hint: Subplots = multiple charts in one figure [OK]

Common Mistakes:

• Thinking it saves images
• Confusing with styling functions
• Assuming it adds titles

2. Which of the following is the correct way to create a 2x2 grid of subplots using Matplotlib?

easy

A. fig, axs = plt.subplots(2)

B. fig, axs = plt.subplots(4)

C. fig, axs = plt.subplots(1, 4)

D. fig, axs = plt.subplots(2, 2)

Solution

1. Step 1: Recall the syntax of plt.subplots()

   The function takes rows and columns as arguments to create a grid.

2. Step 2: Identify the 2x2 grid syntax

   Using plt.subplots(2, 2) creates 2 rows and 2 columns, making 4 subplots.

3. Final Answer:

   fig, axs = plt.subplots(2, 2) -> Option D

4. Quick Check:

   Rows and columns = plt.subplots(2, 2) [OK]

Hint: Rows and columns go as two numbers in plt.subplots() [OK]

Common Mistakes:

• Passing only one number for grid
• Confusing total plots with grid shape
• Using wrong argument order

3. What will be the output shape of axs when you run fig, axs = plt.subplots(3, 1)?

medium

A. A list of 3 Axes objects

B. A single Axes object

C. A 3x1 numpy array of Axes objects

D. A 1x3 numpy array of Axes objects

Solution

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

   This means 3 subplots stacked vertically.

2. Step 2: Check the type of axs for single column

   When columns = 1, axs is a 2D numpy array of shape (3,1) of Axes objects, not a list.

3. Final Answer:

   A 3x1 numpy array of Axes objects -> Option C

4. Quick Check:

   Single column = 2D numpy array of shape (3,1) [OK]

Hint: Single column subplots return 2D numpy array of shape (n,1) [OK]

Common Mistakes:

• Assuming always 1D list
• Confusing rows and columns order
• Expecting single Axes object

4. Identify the error in this code snippet for plotting on subplots:

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

medium

A. TypeError because axs is not subscriptable

B. IndexError because axs[2, 0] is out of range

C. No error, code runs fine

D. SyntaxError due to wrong indexing

Solution

1. Step 1: Check the shape of axs from plt.subplots(2, 2)

   It creates a 2x2 grid, so valid indices are 0 or 1 for rows and columns.

2. Step 2: Analyze the index axs[2, 0]

   Index 2 for rows is out of range (only 0 and 1 allowed), causing IndexError.

3. Final Answer:

   IndexError because axs[2, 0] is out of range -> Option B

4. Quick Check:

   Index out of range = IndexError [OK]

Hint: Check subplot indices start at 0 and max is rows-1 [OK]

Common Mistakes:

• Using indices beyond grid size
• Confusing syntax error with index error
• Assuming axs is a flat list

5. You want to plot 5 different line charts in a single figure using subplots arranged in 2 rows and 3 columns. Which code correctly handles the extra subplot that will remain empty?

hard

A. fig, axs = plt.subplots(2, 3)
for i in range(5):
axs.flat[i].plot([i, i+1, i+2])
axs.flat[5].axis('off')

B. fig, axs = plt.subplots(2, 3)
for i in range(6):
axs[i].plot([i, i+1, i+2])

C. fig, axs = plt.subplots(5, 1)
for i in range(5):
axs[i].plot([i, i+1, i+2])

D. fig, axs = plt.subplots(1, 5)
for i in range(5):
axs[i].plot([i, i+1, i+2])

Solution

1. Step 1: Understand subplot grid and number of plots

   A 2x3 grid has 6 subplots but only 5 are needed, so one remains empty.

2. Step 2: Use axs.flat to iterate all subplots in 1D

   This allows easy indexing over the 2D array of axes.

3. Step 3: Turn off the extra subplot axis

   Calling axs.flat[5].axis('off') hides the unused subplot.

4. Final Answer:

   fig, axs = plt.subplots(2, 3) for i in range(5): axs.flat[i].plot([i, i+1, i+2]) axs.flat[5].axis('off') -> Option A

5. Quick Check:

   Use axs.flat and turn off extra subplot [OK]

Hint: Use axs.flat to index subplots and turn off unused ones [OK]

Common Mistakes:

• Ignoring extra subplot and leaving it blank
• Indexing axs as 1D when it's 2D without flat
• Creating wrong grid shape for number of plots