Axes vs pyplot interface comparison in Matplotlib - Practice Questions

Challenge - 5 Problems

❓ Predict Output

intermediate

Output of plotting with Axes vs pyplot

What will be the output of the following code snippet comparing Axes and pyplot interfaces?

Matplotlib

import matplotlib.pyplot as plt
fig, ax = plt.subplots()
ax.plot([1, 2, 3], [4, 5, 6])
plt.plot([1, 2, 3], [6, 5, 4])
print(len(fig.axes))

A 2

B 3

C 0

D 1

💡 Hint

Think about how many axes objects are created and used in the figure.

The code creates one figure and one Axes object with plt.subplots(). The ax.plot() adds a line to that Axes. The plt.plot() call without specifying axes adds a new line to the current axes, which is the same Axes. So only one Axes exists in the figure, but two lines are plotted on it. The length of fig.axes is 1, but the question asks for output of print(len(fig.axes)) which is 1. However, plt.plot() outside of ax adds to the current axes, so no new axes are created. So the output is 1.

❓ Predict Output

intermediate

Number of lines plotted on Axes

After running this code, how many lines are plotted on the Axes object ax?

Matplotlib

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

A 1

B 3

C 2

D 0

💡 Hint

Consider which axes the pyplot plot adds lines to.

Both ax.plot() and plt.plot() add lines to the same Axes object ax because plt.plot() uses the current axes, which is ax here. So ax has two lines plotted.

🔧 Debug

advanced

Identify the error in Axes vs pyplot plotting

What error will this code produce?

Matplotlib

import matplotlib.pyplot as plt
fig, ax = plt.subplots()
plt.plot([1, 2, 3], [4, 5, 6])
ax.plot([1, 2, 3], [6, 5, 4])
plt.show()
print(len(fig.axes))

A No error, output is 1

B No error, output is 2

C AttributeError: 'NoneType' object has no attribute 'axes'

D TypeError: 'int' object is not callable

💡 Hint

Check if plt.plot() creates new axes or uses existing ones.

plt.plot() uses the current axes, which is ax created by plt.subplots(). So no new axes are created. fig.axes contains one Axes object, so len(fig.axes) is 1. No error occurs.

❓ data_output

advanced

Axes object properties after plotting

After running this code, what is the value of ax.get_lines()[1].get_ydata()?

Matplotlib

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

A [6 5 4]

B [4 5 6]

C [1 2 3]

D IndexError: list index out of range

💡 Hint

Remember plt.plot() adds to the current Axes lines list.

ax.get_lines() returns a list of Line2D objects. The first line plotted is with y data [4,5,6], the second line is from plt.plot() with y data [6,5,4]. So ax.get_lines()[1].get_ydata() returns [6 5 4].

❓ visualization

expert

Visual difference between Axes and pyplot interface

Which option best describes the visual output difference when plotting with Axes.plot() vs pyplot.plot() in this code?

Matplotlib

import matplotlib.pyplot as plt
fig, ax = plt.subplots()
ax.plot([1, 2, 3], [4, 5, 6], label='Axes plot')
plt.plot([1, 2, 3], [6, 5, 4], label='Pyplot plot')
ax.legend()
plt.show()

A One plot with only the 'Axes plot' line visible

B One plot with two lines and a legend showing both labels

C Two separate plots appear in different windows

D One plot with only the 'Pyplot plot' line visible

💡 Hint

Consider how legend and lines are managed on the same Axes.

Both lines are plotted on the same Axes object ax. The legend shows both labels because both lines belong to ax. So the plot shows two lines with a legend listing 'Axes plot' and 'Pyplot plot'.

Practice

1. Which statement best describes the difference between the pyplot interface and the Axes interface in matplotlib?

easy

A. Axes is simpler and good for quick plots, while pyplot offers more control for complex figures.

B. pyplot is simpler and good for quick plots, while Axes offers more control for complex figures.

C. Both pyplot and Axes interfaces are equally simple and offer the same control.

D. pyplot is only used for 3D plots, while Axes is for 2D plots.

Solution

1. Step 1: Understand pyplot interface

   The pyplot interface is designed for quick and easy plotting with simple commands.

2. Step 2: Understand Axes interface

   The Axes interface provides detailed control over plot elements, useful for complex figures.

3. Final Answer:

   pyplot is simpler and good for quick plots, while Axes offers more control for complex figures. -> Option B

4. Quick Check:

   Interface complexity = pyplot simple, Axes detailed [OK]

Hint: Remember: pyplot = quick, Axes = control [OK]

Common Mistakes:

• Confusing which interface is simpler
• Thinking both interfaces have same control level
• Assuming pyplot is only for 3D plots

2. Which of the following is the correct way to create a figure and axes using the Axes interface?

easy

A. fig, ax = plt.subplots()

B. ax = plt.figure()

C. fig = plt.axes()

D. plt.plot(), ax = plt.figure()

Solution

1. Step 1: Recall syntax for creating figure and axes

   The correct syntax to create a figure and axes object is fig, ax = plt.subplots().

2. Step 2: Check other options

   plt.figure() creates only a figure, plt.axes() creates axes but not figure, and plt.plot() is for plotting, not creating axes.

3. Final Answer:

   fig, ax = plt.subplots() -> Option A

4. Quick Check:

   Correct Axes creation = plt.subplots() [OK]

Hint: Use plt.subplots() to get figure and axes together [OK]

Common Mistakes:

• Using plt.figure() expecting axes returned
• Confusing plt.axes() with plt.figure()
• Trying to assign plt.plot() to axes

3. What will be the output of this code snippet?

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

medium

A. A plot without title because plt.title() affects only pyplot interface.

B. An error because plt.title() cannot be used with Axes interface.

C. A blank figure with no plot or title.

D. A plot with line connecting points (1,4), (2,5), (3,6) and title 'My Plot'.

Solution

1. Step 1: Understand plotting with Axes

   The ax.plot() draws the line on the axes object.

2. Step 2: Understand plt.title() effect

   plt.title() sets the title on the current axes, so it works here.

3. Final Answer:

   A plot with line connecting points (1,4), (2,5), (3,6) and title 'My Plot'. -> Option D

4. Quick Check:

   Axes plot + plt.title() = plot with title [OK]

Hint: plt.title() sets title on current axes even with Axes interface [OK]

Common Mistakes:

• Thinking plt.title() won't work with Axes interface
• Expecting error due to mixing interfaces
• Assuming no plot will show

4. Identify the error in this code using the Axes interface:

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

medium

A. fig, ax = plt.subplots() is incorrect syntax.

B. ax.set_title() is invalid; should use plt.title() instead.

C. Using plt.plot() instead of ax.plot() causes the plot to appear on a different axes.

D. plt.show() is missing and causes no output.

Solution

1. Step 1: Check plotting method

   plt.plot() plots on the current pyplot axes, not the ax created by plt.subplots().

2. Step 2: Check title setting

   ax.set_title() correctly sets the title on the ax axes.

3. Final Answer:

   Using plt.plot() instead of ax.plot() causes the plot to appear on a different axes. -> Option C

4. Quick Check:

   Plotting on wrong axes = plt.plot() vs ax.plot() [OK]

Hint: Use ax.plot() to plot on specific axes, not plt.plot() [OK]

Common Mistakes:

• Confusing plt.plot() and ax.plot()
• Thinking ax.set_title() is invalid
• Missing plt.show() causing no output

5. You want to create a figure with two side-by-side plots sharing the same y-axis. Which approach using the Axes interface is best?

hard

A. Use fig, (ax1, ax2) = plt.subplots(1, 2, sharey=True) and plot on ax1 and ax2.

B. Call plt.plot() twice and then set plt.sharey(True).

C. Create two separate figures with plt.figure() and plot independently.

D. Use fig, ax = plt.subplots() and plot both lines on the same axes.

Solution

1. Step 1: Understand subplot creation with shared axis

   plt.subplots(1, 2, sharey=True) creates two axes side-by-side sharing the y-axis.

2. Step 2: Plot on each axes separately

   Plotting on ax1 and ax2 allows independent x-data but shared y-axis.

3. Final Answer:

   Use fig, (ax1, ax2) = plt.subplots(1, 2, sharey=True) and plot on ax1 and ax2. -> Option A

4. Quick Check:

   Shared y-axis subplots = plt.subplots with sharey=True [OK]

Hint: Use plt.subplots with sharey=True for shared y-axis plots [OK]

Common Mistakes:

• Trying to share axis with plt.plot() only
• Creating separate figures instead of subplots
• Plotting both lines on one axes when separate plots needed