Fig, ax = plt.subplots pattern in Matplotlib - Mini Project: Build & Apply

Using the Fig, ax = plt.subplots Pattern in Matplotlib

📖 Scenario: You are a data analyst who wants to create a simple line chart to show sales over a week. You will use the fig, ax = plt.subplots() pattern to create the plot.

🎯 Goal: Build a line plot using fig, ax = plt.subplots() to display sales data for 7 days.

📋 What You'll Learn

Create a list called days with the values: 'Mon', 'Tue', 'Wed', 'Thu', 'Fri', 'Sat', 'Sun'.

Create a list called sales with the values: 150, 200, 170, 220, 180, 190, 210.

Use fig, ax = plt.subplots() to create the figure and axes.

Plot the sales data on the axes with days on the x-axis and sales on the y-axis.

Set the title of the plot to 'Weekly Sales'.

Display the plot using plt.show().

💡 Why This Matters

🌍 Real World

Creating clear and simple charts is important for sharing data insights with others in business, science, and everyday life.

💼 Career

Data analysts and scientists use matplotlib and the fig, ax = plt.subplots() pattern to build flexible and professional plots for reports and presentations.

1

Create the sales data lists

Create a list called days with the values 'Mon', 'Tue', 'Wed', 'Thu', 'Fri', 'Sat', 'Sun'. Also create a list called sales with the values 150, 200, 170, 220, 180, 190, 210.

Matplotlib

# Create the days and sales lists
# Your code here

Hint

Use square brackets to create lists. Separate each day and sales number with commas.

2

Create the figure and axes using plt.subplots()

Import matplotlib.pyplot as plt. Then create the figure and axes by writing fig, ax = plt.subplots().

Matplotlib

days = ['Mon', 'Tue', 'Wed', 'Thu', 'Fri', 'Sat', 'Sun']
sales = [150, 200, 170, 220, 180, 190, 210]

# Import matplotlib.pyplot as plt
# Create fig and ax using plt.subplots()
# Your code here

Hint

Use import matplotlib.pyplot as plt to import. Then call plt.subplots() to get fig and ax.

3

Plot the sales data on the axes

Use the ax.plot() method to plot days on the x-axis and sales on the y-axis. Then set the plot title to 'Weekly Sales' using ax.set_title().

Matplotlib

import matplotlib.pyplot as plt

days = ['Mon', 'Tue', 'Wed', 'Thu', 'Fri', 'Sat', 'Sun']
sales = [150, 200, 170, 220, 180, 190, 210]

fig, ax = plt.subplots()

# Plot sales vs days using ax.plot()
# Set the title to 'Weekly Sales' using ax.set_title()
# Your code here

Hint

Use ax.plot(x, y) to draw the line. Use ax.set_title('Weekly Sales') to add the title.

4

Display the plot

Use plt.show() to display the plot on the screen.

Matplotlib

import matplotlib.pyplot as plt

days = ['Mon', 'Tue', 'Wed', 'Thu', 'Fri', 'Sat', 'Sun']
sales = [150, 200, 170, 220, 180, 190, 210]

fig, ax = plt.subplots()
ax.plot(days, sales)
ax.set_title('Weekly Sales')

# Display the plot using plt.show()
# Your code here

Hint

Call plt.show() to open the plot window.

Practice

1. What does the variable fig represent when you write fig, ax = plt.subplots() in matplotlib?

easy

A. The specific plot area where data is drawn

B. The whole figure container that holds all plot elements

C. A list of all plots in the figure

D. The title of the plot

Solution

1. Step 1: Understand the role of fig in plt.subplots()

   The fig variable holds the entire figure container, which can include multiple plots, titles, legends, and other elements.

2. Step 2: Differentiate fig from ax

   The ax variable is the specific plot area inside the figure where data is drawn, not the whole container.

3. Final Answer:

   The whole figure container that holds all plot elements -> Option B

4. Quick Check:

   fig = whole figure container [OK]

Hint: Remember: fig = full figure, ax = plot area [OK]

Common Mistakes:

• Confusing fig with ax as the plot area
• Thinking fig is just the plot title
• Assuming fig is a list of plots

2. Which of the following is the correct syntax to create a figure and axes using matplotlib's plt.subplots()?

easy

A. plt.subplots = fig, ax

B. fig = plt.subplots(ax)

C. ax, fig = plt.subplots()

D. fig, ax = plt.subplots()

Solution

1. Step 1: Recall the correct unpacking syntax

   The function plt.subplots() returns two objects: the figure and the axes. The correct way to capture them is fig, ax = plt.subplots().

2. Step 2: Check each option for syntax correctness

   fig = plt.subplots(ax) tries to pass ax as an argument incorrectly. ax, fig = plt.subplots() reverses the order, which is wrong. plt.subplots = fig, ax tries to assign incorrectly.

3. Final Answer:

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

4. Quick Check:

   Correct unpacking = fig, ax = plt.subplots() [OK]

Hint: Remember: fig first, then ax from plt.subplots() [OK]

Common Mistakes:

• Swapping fig and ax order
• Passing ax as argument to plt.subplots()
• Incorrect assignment syntax

3. What will be the output type of ax after running this code?

import matplotlib.pyplot as plt
fig, ax = plt.subplots()

medium

A.

B.

C.

D.

Solution

1. Step 1: Understand what plt.subplots() returns

   The function returns a figure object and an axes object. The axes object is usually an instance of AxesSubplot class.

2. Step 2: Identify the type of ax

   After unpacking, ax is the axes object, which is of type matplotlib.axes._subplots.AxesSubplot.

3. Final Answer:

   <class 'matplotlib.axes._subplots.AxesSubplot'> -> Option A

4. Quick Check:

   ax type = AxesSubplot [OK]

Hint: ax is the plot area object, not the figure [OK]

Common Mistakes:

• Confusing ax type with fig type
• Thinking ax is a list or tuple
• Assuming ax is a string or number

4. Identify the error in this code snippet:

import matplotlib.pyplot as plt
fig, ax = plt.subplots
ax.plot([1, 2, 3], [4, 5, 6])
plt.show()

medium

A. fig and ax are reversed in assignment

B. ax.plot() arguments are incorrect

C. Missing parentheses after plt.subplots

D. plt.show() is called before plotting

Solution

1. Step 1: Check the call to plt.subplots

   The code uses plt.subplots without parentheses, so it assigns the function itself, not its result.

2. Step 2: Understand the impact on ax.plot

   Since fig, ax are assigned incorrectly, ax is a function, not an axes object, so ax.plot() will cause an error.

3. Final Answer:

   Missing parentheses after plt.subplots -> Option C

4. Quick Check:

   Call plt.subplots() with () [OK]

Hint: Always add () to call plt.subplots function [OK]

Common Mistakes:

• Forgetting parentheses on plt.subplots
• Mixing up fig and ax variables
• Calling plt.show() too early

5. You want to create a figure with 2 rows and 1 column of plots using plt.subplots(). Which code correctly creates the figure and axes, and plots a line on the second subplot?

hard

A. fig, ax = plt.subplots(2, 1)
ax[1].plot([1, 2, 3], [3, 2, 1])

B. fig, ax = plt.subplots(1, 2)
ax[2].plot([1, 2, 3], [3, 2, 1])

C. fig, ax = plt.subplots(2, 1)
ax.plot([1, 2, 3], [3, 2, 1])

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

Solution

1. Step 1: Create figure with 2 rows and 1 column

   Use plt.subplots(2, 1) to create 2 vertical subplots. This returns ax as an array of axes.

2. Step 2: Plot on the second subplot

   Access the second subplot with ax[1] (indexing starts at 0) and call plot() on it.

3. Final Answer:

   fig, ax = plt.subplots(2, 1) ax[1].plot([1, 2, 3], [3, 2, 1]) -> Option A

4. Quick Check:

   2 rows, 1 col = plt.subplots(2,1), plot on ax[1] [OK]

Hint: Use ax[index] for multiple subplots, index starts at 0 [OK]

Common Mistakes:

• Using wrong subplot shape (1,2) instead of (2,1)
• Trying to plot on ax without indexing when multiple axes exist
• Using invalid index like ax[2] when only 2 subplots exist