Why the OO interface matters in Matplotlib - Challenge Your Understanding

Challenge - 5 Problems

❓ Predict Output

intermediate

Output of plot commands using OO interface

What will be the output of this code snippet using matplotlib's OO interface?

Matplotlib

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

A An empty plot with no lines and no title

B A line plot with points (1,4), (2,5), (3,6) and title 'Test Plot' displayed

C A scatter plot with points (1,4), (2,5), (3,6) but no title

D A bar chart with bars at x=1,2,3 with heights 4,5,6 and title 'Test Plot'

💡 Hint

Remember that ax.plot creates a line plot and ax.set_title sets the title for that axes.

Using the OO interface, ax.plot draws a line plot on the axes, and ax.set_title sets the title. So the plot shows a line connecting points (1,4), (2,5), (3,6) with the given title.

🧠 Conceptual

intermediate

Why prefer OO interface over pyplot state-machine?

Which reason best explains why the OO interface is preferred over the pyplot state-machine interface in matplotlib?

A It allows explicit control over multiple figures and axes, avoiding confusion in complex plots

B It automatically chooses the best colors for plots without user input

C It requires less code to create simple plots

D It disables interactive plotting features

💡 Hint

Think about managing multiple plots at once.

The OO interface lets you create and control multiple figures and axes explicitly, which is important for complex plots. The pyplot interface relies on a global state which can cause confusion.

🔧 Debug

advanced

Identify the error in this OO interface code

What error will this code raise when run?

Matplotlib

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

A ValueError: x and y must have same first dimension

B TypeError: 'AxesSubplot' object is not callable

C No error, plot displays correctly

D AttributeError: 'AxesSubplot' object has no attribute 'set_title'

💡 Hint

Check the lengths of x and y data passed to plot.

The x data has length 3 but y data has length 2, so matplotlib raises a ValueError because the dimensions do not match.

❓ data_output

advanced

Number of axes created with subplots

What is the shape and number of axes objects created by this code?

Matplotlib

import matplotlib.pyplot as plt
fig, axes = plt.subplots(2, 3)
print(type(axes), axes.shape)

A <class 'tuple'> (2, 3)

B <class 'matplotlib.axes._subplots.AxesSubplot'> (6,)

C <class 'list'> (2, 3)

D <class 'numpy.ndarray'> (2, 3)

💡 Hint

plt.subplots returns a numpy array of axes when rows and columns are more than 1.

When creating multiple subplots with plt.subplots(2,3), axes is a 2x3 numpy array of AxesSubplot objects.

🚀 Application

expert

Correctly update title for specific subplot

Given a 2x2 grid of subplots, which code correctly sets the title of the bottom-right subplot only?

Matplotlib

import matplotlib.pyplot as plt
fig, axes = plt.subplots(2, 2)
# Set title for bottom-right subplot here

A fig.axes[3].set_title('Bottom Right')

B axes[2, 2].set_title('Bottom Right')

C axes[1, 1].set_title('Bottom Right')

D axes[1].set_title('Bottom Right')

💡 Hint

Remember Python uses zero-based indexing for arrays.

axes is a 2x2 numpy array indexed by [row, column]. The bottom-right subplot is at row 1, column 1 (zero-based).