Figure-level methods vs axes-level in Matplotlib - When to Use Which

The Big Idea

Discover how to make your charts smarter and your work easier by mastering figure-level and axes-level methods!

The Scenario

Imagine you have many charts to make, each with different parts like titles, labels, and legends. You try to draw each chart by hand, adding every detail one by one for each small plot.

The Problem

This manual way is slow and confusing. You might forget to add a label or place a legend wrongly. Managing many small plots separately can cause mistakes and wastes time.

The Solution

Figure-level and axes-level methods help you organize your charts smartly. Figure-level methods handle the whole picture, while axes-level methods focus on each small plot. This way, you control details easily and avoid errors.

Before vs After

✗ Before

plt.subplot(1,2,1)
plt.plot(data1)
plt.title('Plot 1')
plt.subplot(1,2,2)
plt.plot(data2)
plt.title('Plot 2')

✓ After

fig, axs = plt.subplots(1, 2)
axs[0].plot(data1)
axs[0].set_title('Plot 1')
axs[1].plot(data2)
axs[1].set_title('Plot 2')

What It Enables

You can create complex, multi-part charts clearly and quickly, making your data stories easier to understand.

Real Life Example

A scientist comparing two experiments side by side can use figure-level methods to arrange plots and axes-level methods to label each graph perfectly.

Key Takeaways

Manual plotting of multiple charts is slow and error-prone.

Figure-level methods manage the whole chart layout.

Axes-level methods control details inside each 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