Figure-level methods vs axes-level in Matplotlib - Quick Revision & Key Differences

Recall & Review

beginner

What is a figure-level method in matplotlib?

A figure-level method controls the entire figure, including all its axes and elements. It manages the overall layout and appearance of the whole plot.

beginner

What is an axes-level method in matplotlib?

An axes-level method controls a single plot area (axes) within a figure. It manages details like plotting data, labels, and titles inside that specific axes.

beginner

Give an example of a figure-level method in matplotlib.

The method plt.figure() is a figure-level method. It creates or modifies the whole figure container that can hold multiple axes.

beginner

Give an example of an axes-level method in matplotlib.

The method ax.plot() is an axes-level method. It draws data lines inside a specific axes object within the figure.

intermediate

Why is it important to understand the difference between figure-level and axes-level methods?

Understanding the difference helps you control your plots better. Use figure-level methods to manage the whole plot layout and axes-level methods to customize individual plots inside the figure.

Which method controls the entire figure in matplotlib?

A ax.set_title()

B ax.plot()

C plt.plot()

D plt.figure()

plt.figure() creates or modifies the whole figure container, controlling the entire figure.

Which method is used to plot data inside a specific axes?

A plt.figure()

B ax.plot()

C plt.show()

D plt.title()

ax.plot() draws data lines inside a specific axes object.

If you want to add a title to a single plot area, which method should you use?

A ax.set_title()

B plt.title()

C plt.figure()

D plt.suptitle()

ax.set_title() adds a title to a specific axes (plot area).

Which method manages the layout of multiple plots inside one figure?

A plt.subplots()

B plt.figure()

C ax.set_xlabel()

D ax.plot()

plt.subplots() creates a figure and multiple axes, managing layout of multiple plots.

What is the main difference between figure-level and axes-level methods?

A Both control the same parts of the plot.

B Figure-level methods control individual plots; axes-level methods control the whole figure.

C Axes-level methods control individual plots; figure-level methods control the whole figure.

D Axes-level methods are only for 3D plots.

Axes-level methods control individual plots inside the figure; figure-level methods control the entire figure.

Explain the difference between figure-level and axes-level methods in matplotlib with examples.

Think about controlling the whole plot versus controlling one plot area.

Describe a situation where you would use a figure-level method instead of an axes-level method.

Consider when you want to affect the entire drawing area, not just one plot.

Practice

1. Which method would you use to set the main title for the entire figure in matplotlib?

easy

A. plt.title()

B. ax.set_title()

C. ax.set_xlabel()

D. fig.suptitle()

Solution

1. Step 1: Understand figure-level vs axes-level

   Figure-level methods control the whole figure, axes-level methods control individual plots.

2. Step 2: Identify method for main figure title

   The method fig.suptitle() sets the main title for the entire figure, while ax.set_title() sets title for one subplot.

3. Final Answer:

   fig.suptitle() -> Option D

4. Quick Check:

   Figure main title = fig.suptitle() [OK]

Hint: Main figure title uses fig.suptitle(), not ax.set_title() [OK]

Common Mistakes:

• Using ax.set_title() for main figure title
• Using plt.title() which affects current axes
• Confusing xlabel with title

2. Which of the following is the correct syntax to set the x-axis label for a single plot (axes) in matplotlib?

easy

A. plt.set_xlabel('X Label')

B. fig.set_xlabel('X Label')

C. ax.set_xlabel('X Label')

D. fig.xlabel('X Label')

Solution

1. Step 1: Identify the object controlling axis labels

   Axis labels belong to individual plots, so axes-level methods are used.

2. Step 2: Choose correct method and object

   The method set_xlabel() is called on an axes object, so ax.set_xlabel('X Label') is correct.

3. Final Answer:

   ax.set_xlabel('X Label') -> Option C

4. Quick Check:

   Axis label = ax.set_xlabel() [OK]

Hint: Use ax.set_xlabel() for x-axis label, not fig or plt [OK]

Common Mistakes:

• Calling set_xlabel() on figure object
• Using plt.set_xlabel() which does not exist
• Confusing axis label with figure title

3. What will the following code display?

import matplotlib.pyplot as plt
fig, ax = plt.subplots()
fig.suptitle('Main Title')
ax.set_title('Plot Title')
ax.set_xlabel('X Axis')
ax.set_ylabel('Y Axis')
plt.show()

medium

A. A figure with main title 'Main Title' and one plot titled 'Plot Title' with labeled axes

B. Only a plot titled 'Main Title' with axes labeled 'X Axis' and 'Y Axis'

C. A figure with no titles but axes labeled 'X Axis' and 'Y Axis'

D. Error because fig.suptitle() cannot be used with ax.set_title()

Solution

1. Step 1: Understand figure and axes titles

   fig.suptitle() sets the main figure title; ax.set_title() sets the subplot title.

2. Step 2: Analyze axis labels and display

   ax.set_xlabel() and ax.set_ylabel() label the x and y axes of the plot. The code will show all these correctly.

3. Final Answer:

   A figure with main title 'Main Title' and one plot titled 'Plot Title' with labeled axes -> Option A

4. Quick Check:

   fig.suptitle + ax.set_title + ax labels = A figure with main title 'Main Title' and one plot titled 'Plot Title' with labeled axes [OK]

Hint: fig.suptitle is main title; ax.set_title is subplot title [OK]

Common Mistakes:

• Thinking fig.suptitle replaces ax.set_title
• Expecting error when using both titles
• Ignoring axis labels

4. Identify the error in this code snippet:

import matplotlib.pyplot as plt
fig, ax = plt.subplots()
fig.set_title('Main Title')
ax.set_xlabel('X Label')
plt.show()

medium

A. fig.set_title() is not a valid method for figure objects

B. ax.set_xlabel() should be called on fig, not ax

C. plt.show() must be called before setting titles

D. fig, ax = plt.subplots() returns only one object

Solution

1. Step 1: Check figure method usage

   The figure object does not have a method called set_title(). The correct method for figure title is suptitle().

2. Step 2: Verify other method calls

   ax.set_xlabel() is correct for labeling x-axis. plt.show() is correctly placed at the end.

3. Final Answer:

   fig.set_title() is not a valid method for figure objects -> Option A

4. Quick Check:

   Figure title method = fig.suptitle() not fig.set_title() [OK]

Hint: Figure title uses suptitle(), not set_title() [OK]

Common Mistakes:

• Using fig.set_title() instead of fig.suptitle()
• Confusing axes methods with figure methods
• Calling plt.show() too early

5. You want to create a figure with 2 subplots side by side. You want a main title for the figure and individual titles for each subplot. Which code correctly achieves this?

hard

A. fig, axs = plt.subplots(1, 2)
fig.title('Main Title')
axs[0].title('Left Plot')
axs[1].title('Right Plot')
plt.show()

B. fig, axs = plt.subplots(1, 2)
fig.suptitle('Main Title')
axs[0].set_title('Left Plot')
axs[1].set_title('Right Plot')
plt.show()

C. fig, axs = plt.subplots(2, 1)
fig.set_title('Main Title')
axs[0].set_xlabel('Left Plot')
axs[1].set_xlabel('Right Plot')
plt.show()

D. fig, axs = plt.subplots(1, 2)
axs.set_title('Main Title')
fig.set_title('Left Plot')
fig.set_title('Right Plot')
plt.show()

Solution

1. Step 1: Create subplots and set main figure title

   plt.subplots(1, 2) creates two side-by-side plots. fig.suptitle() sets the main figure title.

2. Step 2: Set individual subplot titles correctly

   Each subplot is accessed by axs[0] and axs[1]. Use set_title() to set their titles.

3. Step 3: Verify other options are incorrect

   The other options misuse methods like fig.set_title() or fig.title() which do not exist or use wrong subplot layout.

4. Final Answer:

   fig, axs = plt.subplots(1, 2) fig.suptitle('Main Title') axs[0].set_title('Left Plot') axs[1].set_title('Right Plot') plt.show() -> Option B

5. Quick Check:

   Figure main title = fig.suptitle(), subplot titles = axs[i].set_title() [OK]

Hint: Use fig.suptitle() for main title, axs[i].set_title() for subplots [OK]

Common Mistakes:

• Using fig.set_title() instead of fig.suptitle()
• Calling title() instead of set_title()
• Wrong subplot layout dimensions