Individual subplot customization in Matplotlib - Mini Project: Build & Apply

Individual subplot customization

📖 Scenario: You are analyzing sales data for two different products over four quarters. You want to visualize the sales trends side by side using two subplots. Each subplot should have its own title and y-axis label to clearly show which product's sales are being displayed.

🎯 Goal: Create a figure with two subplots side by side. Plot the sales data for Product A in the first subplot and Product B in the second subplot. Customize each subplot with its own title and y-axis label.

📋 What You'll Learn

Create a list called quarters with values [1, 2, 3, 4].

Create two lists called sales_a and sales_b with sales data for Product A and Product B respectively.

Create a figure with two subplots side by side using plt.subplots() with 1 row and 2 columns.

Plot sales_a against quarters in the first subplot.

Plot sales_b against quarters in the second subplot.

Set the title of the first subplot to 'Product A Sales' and the y-axis label to 'Sales (units)'.

Set the title of the second subplot to 'Product B Sales' and the y-axis label to 'Sales (units)'.

Display the plot using plt.show().

💡 Why This Matters

🌍 Real World

Visualizing multiple related datasets side by side helps compare trends easily, such as sales of different products over time.

💼 Career

Data scientists and analysts often create customized subplots to present clear and informative visual reports to stakeholders.

1

Create sales data lists

Create a list called quarters with values [1, 2, 3, 4]. Create a list called sales_a with values [150, 200, 250, 300] for Product A sales. Create a list called sales_b with values [180, 210, 260, 310] for Product B sales.

Matplotlib

# Create the lists quarters, sales_a, and sales_b
# Your code here

Hint

Use square brackets to create lists with the exact values given.

2

Create subplots figure

Import matplotlib.pyplot as plt. Create a figure and two subplots side by side using plt.subplots() with 1 row and 2 columns. Store the axes in a variable called axes.

Matplotlib

import matplotlib.pyplot as plt
# Create a figure and two subplots side by side
# Your code here

Hint

Use plt.subplots(1, 2) to create 1 row and 2 columns of subplots.

3

Plot sales data and customize subplots

Plot sales_a against quarters on the first subplot using axes[0].plot(). Plot sales_b against quarters on the second subplot using axes[1].plot(). Set the title of the first subplot to 'Product A Sales' using axes[0].set_title(). Set the y-axis label of the first subplot to 'Sales (units)' using axes[0].set_ylabel(). Set the title of the second subplot to 'Product B Sales' using axes[1].set_title(). Set the y-axis label of the second subplot to 'Sales (units)' using axes[1].set_ylabel().

Matplotlib

# Plot sales_a on the first subplot
# Plot sales_b on the second subplot
# Set titles and y-axis labels for both subplots
# Your code here

Hint

Use axes[index].plot() to plot on each subplot. Use set_title() and set_ylabel() to customize each subplot.

4

Display the plot

Use plt.show() to display the figure with the two customized subplots.

Matplotlib

# Display the plot
# Your code here

Hint

Call plt.show() to display the figure window with your plots.

Practice

1. What is the correct way to change the title of the second subplot when using fig, axs = plt.subplots(2, 2)?

easy

A. Use plt.title('New Title')

B. Use axs[1].set_title('New Title')

C. Use fig.set_title('New Title')

D. Use axs[0, 1].set_title('New Title')

Solution

1. Step 1: Understand subplot indexing

   With plt.subplots(2, 2), axs is a 2x2 array. The second subplot in the first row is at position [0, 1].

2. Step 2: Set title for specific subplot

   Use axs[0, 1].set_title('New Title') to change only that subplot's title.

3. Final Answer:

   Use axs[0, 1].set_title('New Title') -> Option D

4. Quick Check:

   Indexing subplots by row and column = A [OK]

Hint: Use axs[row, col] to target specific subplot [OK]

Common Mistakes:

• Using axs[1] instead of axs[0, 1]
• Setting title on fig instead of axs
• Using plt.title affects whole figure, not subplot

2. Which of the following is the correct syntax to change the x-axis label of the first subplot in a 1D array of subplots fig, axs = plt.subplots(3)?

easy

A. axs[1].set_xlabel('X Label')

B. axs[0].set_xlabel('X Label')

C. axs.set_xlabel('X Label')

D. fig.set_xlabel('X Label')

Solution

1. Step 1: Identify subplot indexing in 1D array

   With plt.subplots(3), axs is a 1D array with indices 0, 1, 2. The first subplot is at index 0.

2. Step 2: Use set_xlabel on the correct subplot

   Use axs[0].set_xlabel('X Label') to set the x-axis label of the first subplot.

3. Final Answer:

   axs[0].set_xlabel('X Label') -> Option B

4. Quick Check:

   Index 0 for first subplot in 1D axs = D [OK]

Hint: Remember 1D axs uses zero-based indexing [OK]

Common Mistakes:

• Using axs[1] for first subplot
• Calling set_xlabel on fig or axs directly
• Confusing 1D and 2D axs indexing

3. What will be the color of the line in the third subplot after running this code?

import matplotlib.pyplot as plt
fig, axs = plt.subplots(2, 2)
axs[1, 0].plot([1, 2, 3], [4, 5, 6], color='green')
plt.show()

medium

A. Blue

B. Red

C. Green

D. Black

Solution

1. Step 1: Identify subplot position

   With plt.subplots(2, 2), subplots are indexed as [0,0], [0,1], [1,0], [1,1]. The third subplot is at [1,0].

2. Step 2: Check plot color argument

   The code sets color='green' for the line in subplot [1,0].

3. Final Answer:

   Green -> Option C

4. Quick Check:

   Color set explicitly to green = B [OK]

Hint: Check subplot index and color argument carefully [OK]

Common Mistakes:

• Assuming default blue color
• Confusing subplot index order
• Ignoring color parameter in plot

4. Identify the error in this code that tries to set the y-axis label of the last subplot:

fig, axs = plt.subplots(2, 2)
axs[2, 1].set_ylabel('Y Label')

medium

A. IndexError because axs has shape (2,2) and index (2,1) is out of range

B. AttributeError because set_ylabel is not a valid method

C. SyntaxError due to wrong indexing syntax

D. No error, code runs fine

Solution

1. Step 1: Check axs shape and indexing

   With plt.subplots(2, 2), axs shape is (2, 2), valid indices are 0 or 1 for each dimension.

2. Step 2: Identify invalid index

   Indexing axs[2, 1] tries to access third row (index 2), which does not exist, causing IndexError.

3. Final Answer:

   IndexError because axs has shape (2,2) and index (2,1) is out of range -> Option A

4. Quick Check:

   Index out of range error = C [OK]

Hint: Check subplot array shape before indexing [OK]

Common Mistakes:

• Assuming axs has more rows than created
• Confusing AttributeError with IndexError
• Using wrong indexing syntax

5. You want to create a 2x2 grid of subplots and set a different background color for each subplot: red, blue, green, and yellow respectively. Which code snippet correctly applies these colors?

hard

A. colors = ['red', 'blue', 'green', 'yellow']
fig, axs = plt.subplots(2, 2)
for ax, color in zip(axs.flat, colors):
ax.set_facecolor(color)

B. colors = ['red', 'blue', 'green', 'yellow']
fig, axs = plt.subplots(2, 2)
for i in range(4):
axs[i].set_facecolor(colors[i])

C. colors = ['red', 'blue', 'green', 'yellow']
fig, axs = plt.subplots(2, 2)
for i, j in range(2):
axs[i, j].set_facecolor(colors[i+j])

D. colors = ['red', 'blue', 'green', 'yellow']
fig, axs = plt.subplots(2, 2)
for ax in axs:
ax.set_facecolor(colors)

Solution

1. Step 1: Understand axs structure and iteration

   With plt.subplots(2, 2), axs is a 2D array. Using axs.flat flattens it to 1D for easy iteration.

2. Step 2: Apply colors correctly

   Using zip(axs.flat, colors) pairs each subplot with a color. Calling ax.set_facecolor(color) sets background color individually.

3. Final Answer:

   Use axs.flat with zip and set_facecolor for each subplot -> Option A

4. Quick Check:

   Flatten axs and zip with colors = A [OK]

Hint: Use axs.flat to loop all subplots in order [OK]

Common Mistakes:

• Trying to index axs as 1D without flattening
• Using axs as 2D but wrong color indexing
• Passing full color list to set_facecolor