Matplotlib backend selection - Cheat Sheet & Quick Revision

Recall & Review

beginner

What is a Matplotlib backend?

A Matplotlib backend is the part of Matplotlib that handles how and where plots are displayed or saved. It can show plots on the screen or save them to files.

beginner

Name two types of Matplotlib backends.

There are two main types: interactive backends that show plots in windows you can interact with, and non-interactive backends that only save plots to files without showing them.

beginner

How can you check which backend Matplotlib is currently using?

You can check the current backend by running <code>import matplotlib; print(matplotlib.get_backend())</code> in your Python code.

intermediate

How do you set a Matplotlib backend before importing pyplot?

Use matplotlib.use('backend_name') before importing matplotlib.pyplot. For example, matplotlib.use('Agg') sets a non-interactive backend for saving files.

beginner

Why might you choose the 'Agg' backend in Matplotlib?

The 'Agg' backend is good for creating image files like PNGs without opening any windows. It's useful when running code on servers or scripts without a display.

Which Matplotlib backend type allows you to interact with plots on your screen?

A Non-interactive backend

B Interactive backend

C File backend

D Static backend

Interactive backends open windows where you can zoom, pan, and update plots.

What does the 'Agg' backend in Matplotlib do?

A Displays plots in a window

B Runs plots in a web browser

C Saves plots to image files without showing them

D Creates 3D plots

The 'Agg' backend is non-interactive and saves plots as image files like PNG.

How do you find out which backend Matplotlib is currently using?

A matplotlib.get_backend()

B matplotlib.show_backend()

C matplotlib.backend()

D matplotlib.check_backend()

The function matplotlib.get_backend() returns the current backend name.

When should you set the backend using matplotlib.use()?

A It does not matter when

B After importing matplotlib.pyplot

C After plotting

D Before importing matplotlib.pyplot

You must set the backend before importing pyplot to avoid errors.

Which backend is best for running Matplotlib on a server without a display?

A Agg

B Qt5Agg

C TkAgg

D MacOSX

The 'Agg' backend works without a display, perfect for servers.

Explain what a Matplotlib backend is and why it matters when creating plots.

Think about how plots appear or get saved.

Describe how to change the Matplotlib backend in your code and when you should do it.

Order of imports is important.

Practice

1. What is the main purpose of selecting a Matplotlib backend?

easy

A. To control how plots are displayed or saved

B. To change the color of the plot lines

C. To speed up data processing

D. To import data from files

Solution

1. Step 1: Understand what a backend does

   A backend in Matplotlib decides how the plot appears, either on screen or in files.

2. Step 2: Match backend role to options

   Only To control how plots are displayed or saved correctly describes controlling plot display or saving.

3. Final Answer:

   To control how plots are displayed or saved -> Option A

4. Quick Check:

   Backend controls plot display/save = A [OK]

Hint: Backend controls plot display or saving method [OK]

Common Mistakes:

• Confusing backend with plot styling
• Thinking backend speeds up calculations
• Mixing backend with data import

2. Which of the following is the correct way to set the Matplotlib backend to 'Agg' before importing pyplot?

easy

A. import matplotlib.pyplot as plt
matplotlib.use('Agg')

B. import matplotlib.pyplot as plt
plt.use('Agg')

C. import matplotlib
matplotlib.use('Agg')
import matplotlib.pyplot as plt

D. matplotlib.use('Agg')
import matplotlib.pyplot as plt

Solution

1. Step 1: Understand backend setting order

   The backend must be set before importing pyplot to take effect.

2. Step 2: Check each option's order

   import matplotlib matplotlib.use('Agg') import matplotlib.pyplot as plt sets backend after importing matplotlib but before pyplot, which is correct.

3. Final Answer:

   import matplotlib matplotlib.use('Agg') import matplotlib.pyplot as plt -> Option C

4. Quick Check:

   Set backend before pyplot import = D [OK]

Hint: Set backend before importing pyplot module [OK]

Common Mistakes:

• Setting backend after importing pyplot
• Calling use() on pyplot instead of matplotlib
• Importing pyplot before setting backend

3. What will happen if you run this code snippet?

import matplotlib
matplotlib.use('Agg')
import matplotlib.pyplot as plt
plt.plot([1, 2, 3], [4, 5, 6])
plt.savefig('plot.png')

medium

A. A plot window will open showing the graph

B. The plot will be saved to 'plot.png' without opening a window

C. An error will occur because 'Agg' backend does not support plotting

D. Nothing will happen because plt.show() is missing

Solution

1. Step 1: Identify the 'Agg' backend behavior

   'Agg' is a non-interactive backend that saves plots to files but does not open windows.

2. Step 2: Analyze the code actions

   The code plots data and saves it to 'plot.png' without calling plt.show(), so no window opens.

3. Final Answer:

   The plot will be saved to 'plot.png' without opening a window -> Option B

4. Quick Check:

   'Agg' saves files, no window = B [OK]

Hint: Agg backend saves files, no GUI window opens [OK]

Common Mistakes:

• Expecting a plot window to open
• Thinking plt.show() is needed to save files
• Assuming 'Agg' backend causes errors

4. You wrote this code but get an error:

import matplotlib.pyplot as plt
matplotlib.use('TkAgg')
plt.plot([1, 2], [3, 4])
plt.show()

What is the likely cause?

medium

A. Backend must be set before importing pyplot

B. The 'TkAgg' backend is not installed

C. plt.plot() syntax is incorrect

D. plt.show() cannot be used with 'TkAgg'

Solution

1. Step 1: Check backend setting order

   The backend must be set before importing pyplot to avoid errors.

2. Step 2: Analyze the code order

   Here, pyplot is imported before setting backend, causing the error.

3. Final Answer:

   Backend must be set before importing pyplot -> Option A

4. Quick Check:

   Set backend before pyplot import = A [OK]

Hint: Set backend before importing pyplot to avoid errors [OK]

Common Mistakes:

• Setting backend after importing pyplot
• Assuming backend installation error
• Blaming plot syntax or plt.show()

5. You want to create plots in a Jupyter notebook that update interactively without opening new windows. Which backend should you select and how?

hard

A. Use 'TkAgg' backend by calling matplotlib.use('TkAgg') after importing pyplot

B. Use 'Agg' backend and call plt.show() to open interactive windows

C. Use 'Qt5Agg' backend by setting matplotlib.use('Qt5Agg') before importing pyplot

D. Use 'inline' backend by running '%matplotlib inline' magic command in the notebook

Solution

1. Step 1: Understand Jupyter notebook backend needs

   Jupyter notebooks use special magic commands to enable inline interactive plots.

2. Step 2: Identify correct backend and usage

   '%matplotlib inline' enables plots inside the notebook without new windows.

3. Final Answer:

   Use 'inline' backend by running '%matplotlib inline' magic command in the notebook -> Option D

4. Quick Check:

   Jupyter inline plots = '%matplotlib inline' = C [OK]

Hint: Use '%matplotlib inline' in Jupyter for interactive plots [OK]

Common Mistakes:

• Setting backend after importing pyplot
• Using GUI backends that open new windows
• Calling plt.show() expecting inline plots