Figure and Axes mental model in Matplotlib - Interactive Code Practice

Practice - 5 Tasks

1fill in blank

easy

Complete the code to create a figure and a single axes using matplotlib.

Matplotlib

import matplotlib.pyplot as plt
fig, ax = plt.[1]()

Drag options to blanks, or click blank then click option'

Aplot

Bfigure

Cshow

Dsubplots

Attempts:

3 left

💡 Hint

Common Mistakes

Using plt.figure() which only creates a figure without axes.

Using plt.plot() which is for plotting data, not creating figure or axes.

The plt.subplots() function creates a figure and axes together.

2fill in blank

medium

Complete the code to set the title of the axes to 'My Plot'.

Matplotlib

import matplotlib.pyplot as plt
fig, ax = plt.subplots()
ax.[1]('My Plot')

Drag options to blanks, or click blank then click option'

Aset_title

Bset_xlabel

Ctitle

Dshow

Attempts:

3 left

💡 Hint

Common Mistakes

Using title() which is a pyplot function, not an axes method.

Using show() which displays the plot.

The set_title() method sets the title of the axes.

3fill in blank

hard

Fix the error in the code to plot a line on the axes.

Matplotlib

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

Drag options to blanks, or click blank then click option'

Ashow

Bscatter

Cplot

Dfigure

Attempts:

3 left

💡 Hint

Common Mistakes

Using show() as a method on axes which causes error.

Using figure() which creates a new figure, not plotting.

The plot() method draws a line plot on the axes.

4fill in blank

hard

Fill both blanks to create a figure with 2 rows and 1 column of axes.

Matplotlib

import matplotlib.pyplot as plt
fig, ax = plt.subplots([1], [2])

Drag options to blanks, or click blank then click option'

A2

B1

C3

D4

Attempts:

3 left

💡 Hint

Common Mistakes

Swapping rows and columns.

Using more than 2 rows or columns when only 2x1 is needed.

The arguments to plt.subplots() specify rows and columns of axes.

5fill in blank

hard

Fill both blanks to create a dictionary comprehension that maps each axes to its index if the index is greater than 0.

Matplotlib

axes_dict = {ax:: i[1] i in range(3) if i [2] 0}

Drag options to blanks, or click blank then click option'

As

Bfor

C>

D:

Attempts:

3 left

💡 Hint

Common Mistakes

Using 's' instead of colon for key-value separator.

Using '<' instead of '>' in the condition.

This dictionary comprehension uses ax: i for i in range(3) if i > 0 syntax.

Practice

1. What does the Figure represent in matplotlib's Figure and Axes model?

easy

A. A single data point on the plot

B. The area where data points are drawn

C. The entire image or window that contains all plots

D. The color scheme of the plot

Solution

1. Step 1: Understand the role of Figure

   The Figure is the whole container or window that holds one or more plots.

2. Step 2: Differentiate Figure from Axes

   Axes is the part inside the Figure where data is drawn, not the entire window.

3. Final Answer:

   The entire image or window that contains all plots -> Option C

4. Quick Check:

   Figure = whole window [OK]

Hint: Figure is the whole plot window, not just the data area [OK]

Common Mistakes:

• Confusing Figure with Axes
• Thinking Figure is a single plot line
• Mixing Figure with plot colors

2. Which of the following is the correct way to create a Figure and Axes in matplotlib?

easy

A. fig, ax = plt.subplots()

B. fig = plt.figure(), ax = plt.plot()

C. ax = plt.figure(), fig = plt.axes()

D. plt.create_figure(), plt.create_axes()

Solution

1. Step 1: Recall matplotlib syntax

   The standard way to create Figure and Axes together is using plt.subplots().

2. Step 2: Check each option

   fig, ax = plt.subplots() correctly assigns Figure and Axes from plt.subplots(). Others misuse functions or assign incorrectly.

3. Final Answer:

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

4. Quick Check:

   Use plt.subplots() to get Figure and Axes [OK]

Hint: Use plt.subplots() to get both Figure and Axes [OK]

Common Mistakes:

• Using plt.plot() to create Axes
• Confusing plt.figure() with plt.subplots()
• Trying non-existent functions like plt.create_figure()

3. What will be the output type of the variable ax after running this code?

import matplotlib.pyplot as plt
fig, ax = plt.subplots()

medium

A. A matplotlib Figure object

B. A matplotlib Axes object

C. A list of Axes objects

D. A NumPy array

Solution

1. Step 1: Understand plt.subplots() return values

   It returns a tuple: (Figure object, Axes object or array of Axes).

2. Step 2: Check variable assignment

   Here, ax is assigned the second element, which is a single Axes object.

3. Final Answer:

   A matplotlib Axes object -> Option B

4. Quick Check:

   ax = Axes object from plt.subplots() [OK]

Hint: plt.subplots() returns (Figure, Axes) tuple [OK]

Common Mistakes:

• Thinking ax is a Figure
• Assuming ax is a list without multiple plots
• Confusing Axes with NumPy arrays

4. Identify the error in this code snippet:

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

medium

A. plt.axes() should be called on the Figure object

B. plt.axes() creates a new Figure, not Axes

C. plt.figure() must be called after plt.axes()

D. No error, code runs fine

Solution

1. Step 1: Understand plt.figure() and plt.axes()

   plt.figure() creates a Figure and sets it as current. plt.axes() creates Axes in the current Figure using default positioning.

2. Step 2: Verify code execution

   The plot is correctly added to ax and plt.show() displays the figure. The code runs without errors.

3. Final Answer:

   No error, code runs fine -> Option D

4. Quick Check:

   plt.axes() adds to current Figure [OK]

Hint: plt.figure() sets current figure for plt.axes() [OK]

Common Mistakes:

• Calling plt.axes() without linking to Figure
• Assuming plt.axes() auto-links to last Figure
• Calling plt.figure() after plt.axes()

5. You want to create a figure with two side-by-side plots sharing the same y-axis. Which code correctly uses the Figure and Axes model to achieve this?

hard

A. fig, (ax1, ax2) = plt.subplots(1, 2, sharey=True)
ax1.plot([1,2,3], [4,5,6])
ax2.plot([1,2,3], [6,5,4])

B. fig = plt.figure()
ax1 = fig.add_subplot(1, 2, 1)
ax2 = fig.add_subplot(1, 2, 2)
ax1.sharey(ax2)

C. fig, ax = plt.subplots(2, 1)
ax[0].plot([1,2,3], [4,5,6])
ax[1].plot([1,2,3], [6,5,4])

D. fig, ax = plt.subplots(1, 2)
ax[0].plot([1,2,3], [4,5,6])
ax[1].plot([1,2,3], [6,5,4])

Solution

1. Step 1: Understand subplots with shared axes

   Using plt.subplots(1, 2, sharey=True) creates one row, two columns of Axes sharing the y-axis.

2. Step 2: Check code correctness

   fig, (ax1, ax2) = plt.subplots(1, 2, sharey=True) ax1.plot([1,2,3], [4,5,6]) ax2.plot([1,2,3], [6,5,4]): fig, (ax1, ax2) = plt.subplots(1, 2, sharey=True) ax1.plot([1,2,3], [4,5,6]) ax2.plot([1,2,3], [6,5,4]) correctly unpacks two Axes and plots data with shared y-axis. fig, ax = plt.subplots(1, 2) ax[0].plot([1,2,3], [4,5,6]) ax[1].plot([1,2,3], [6,5,4]) omits sharey=True. fig = plt.figure() ax1 = fig.add_subplot(1, 2, 1) ax2 = fig.add_subplot(1, 2, 2) ax1.sharey(ax2) calls non-existent sharey() method. fig, ax = plt.subplots(2, 1) ax[0].plot([1,2,3], [4,5,6]) ax[1].plot([1,2,3], [6,5,4]) creates vertical subplots.

3. Final Answer:

   fig, (ax1, ax2) = plt.subplots(1, 2, sharey=True) ax1.plot([1,2,3], [4,5,6]) ax2.plot([1,2,3], [6,5,4]) -> Option A

4. Quick Check:

   Use sharey=True in plt.subplots() for shared y-axis [OK]

Hint: Use sharey=True in plt.subplots() for shared y-axis [OK]

Common Mistakes:

• Trying to call sharey() on Axes objects
• Creating vertical subplots instead of horizontal
• Not unpacking multiple Axes correctly