Plt.subplots with rows and columns in Matplotlib - Mini Project: Build & Apply

Create a Grid of Plots Using plt.subplots with Rows and Columns

📖 Scenario: You are a data analyst who needs to visualize multiple sets of data side by side. To do this neatly, you want to create a grid of plots using matplotlib.

🎯 Goal: Build a 2 by 2 grid of plots using plt.subplots with rows and columns, then plot simple line charts on each subplot.

📋 What You'll Learn

Use plt.subplots to create a figure with 2 rows and 2 columns of subplots

Plot a simple line on each subplot using the provided data

Use the variables fig and axes exactly as shown

Print the figure and axes objects to confirm creation

💡 Why This Matters

🌍 Real World

Creating multiple plots in a grid helps compare different data sets side by side, like sales over months for different products.

💼 Career

Data scientists and analysts often use subplot grids to present multiple visual insights clearly in reports and presentations.

1

Create a 2x2 grid of subplots

Write code to create a figure and a 2 by 2 grid of subplots using plt.subplots. Assign the outputs to variables fig and axes.

Matplotlib

import matplotlib.pyplot as plt
# Create a 2 by 2 grid of subplots using plt.subplots
# Your code here

Hint

Use plt.subplots(nrows=2, ncols=2) and assign the result to fig, axes.

2

Prepare data for plotting

Create a list called data containing four lists of numbers: [1, 2, 3], [3, 2, 1], [1, 3, 2], and [2, 1, 3].

Matplotlib

import matplotlib.pyplot as plt
fig, axes = plt.subplots(nrows=2, ncols=2)
# Create a list called data with four lists of numbers
# Your code here

Hint

Make a list named data with exactly these four lists inside.

3

Plot each data list on the subplots

Use a for loop with variables ax and d to iterate over axes.flat and data simultaneously. Inside the loop, call ax.plot(d) to plot the data on each subplot.

Matplotlib

import matplotlib.pyplot as plt
fig, axes = plt.subplots(nrows=2, ncols=2)
data = [[1, 2, 3], [3, 2, 1], [1, 3, 2], [2, 1, 3]]
# Use a for loop to plot each list in data on each subplot in axes.flat
# Your code here

Hint

Use zip(axes.flat, data) to loop over both together and plot each data list on its subplot.

4

Display the figure and print objects

Print the variables fig and axes on separate lines. Then call plt.show() to display the plots.

Matplotlib

import matplotlib.pyplot as plt
fig, axes = plt.subplots(nrows=2, ncols=2)
data = [[1, 2, 3], [3, 2, 1], [1, 3, 2], [2, 1, 3]]
for ax, d in zip(axes.flat, data):
    ax.plot(d)
# Print fig and axes, then show the plot
# Your code here

Hint

Use print(fig) and print(axes) to show the objects, then plt.show() to display the figure.

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]