Memory management with large figures in Matplotlib - Mini Project: Build & Apply

Memory management with large figures

📖 Scenario: You are working on a data science project that requires creating multiple large plots using matplotlib. You notice your computer slows down and uses a lot of memory after generating many figures.To keep your computer fast and avoid crashes, you need to learn how to manage memory properly when working with large figures.

🎯 Goal: Learn how to create large figures with matplotlib and properly release memory by closing figures after saving or displaying them.

📋 What You'll Learn

Create a large figure with matplotlib

Add a plot with sample data

Close the figure after saving it to free memory

Print confirmation that the figure was saved and closed

💡 Why This Matters

🌍 Real World

Data scientists often create many large plots for reports or presentations. Managing memory prevents slowdowns and crashes.

💼 Career

Knowing how to save and close figures properly is essential for efficient data visualization workflows in data science and analytics jobs.

1

Create a large figure with matplotlib

Import matplotlib.pyplot as plt. Create a figure called fig with size 12 by 8 inches using plt.figure(figsize=(12, 8)).

Matplotlib

# Your code here

Need a hint?

Use import matplotlib.pyplot as plt to import the plotting library.

Use plt.figure(figsize=(12, 8)) to create a large figure.

2

Add a plot with sample data

Create a list called data with values [1, 3, 2, 5, 7, 4]. Add a plot of data to the figure fig using fig.add_subplot(1, 1, 1).plot(data).

Matplotlib

import matplotlib.pyplot as plt
fig = plt.figure(figsize=(12, 8))
# Your code here

Need a hint?

Create a list data with the given numbers.

Add a subplot to fig and plot data on it.

3

Close the figure after saving it to free memory

Save the figure fig to a file named 'large_plot.png' using fig.savefig('large_plot.png'). Then close the figure using plt.close(fig) to free memory.

Matplotlib

import matplotlib.pyplot as plt
fig = plt.figure(figsize=(12, 8))
data = [1, 3, 2, 5, 7, 4]
fig.add_subplot(1, 1, 1).plot(data)
# Your code here

Need a hint?

Use fig.savefig('large_plot.png') to save the figure.

Use plt.close(fig) to close and free memory.

4

Print confirmation that the figure was saved and closed

Print the exact text 'Figure saved and memory freed.' to confirm the process is done.

Matplotlib

import matplotlib.pyplot as plt
fig = plt.figure(figsize=(12, 8))
data = [1, 3, 2, 5, 7, 4]
fig.add_subplot(1, 1, 1).plot(data)
fig.savefig('large_plot.png')
plt.close(fig)
# Your code here

Need a hint?

Use print('Figure saved and memory freed.') to show confirmation.