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Small multiples (facet grid) in Matplotlib - Interactive Code Practice

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Practice - 5 Tasks
Answer the questions below
1fill in blank
easy

Complete the code to create a 2x2 grid of plots using matplotlib subplots.

Matplotlib
fig, axes = plt.subplots([1], 2)
plt.show()
Drag options to blanks, or click blank then click option'
A1
B3
C4
D2
Attempts:
3 left
💡 Hint
Common Mistakes
Using 3 rows instead of 2.
Confusing rows and columns.
2fill in blank
medium

Complete the code to plot data on the first subplot in a 2x2 grid.

Matplotlib
fig, axes = plt.subplots(2, 2)
axes[[1], 0].plot([1, 2, 3], [4, 5, 6])
plt.show()
Drag options to blanks, or click blank then click option'
A2
B0
C3
D1
Attempts:
3 left
💡 Hint
Common Mistakes
Using 1 instead of 0 for the first subplot.
Using an index out of range.
3fill in blank
hard

Fix the error in the code to create a facet grid with 3 rows and 1 column.

Matplotlib
fig, axes = plt.subplots([1], 1)
axes[0].plot([1, 2, 3], [3, 2, 1])
plt.show()
Drag options to blanks, or click blank then click option'
A3
B1
C2
D4
Attempts:
3 left
💡 Hint
Common Mistakes
Setting rows to 1 instead of 3.
Confusing rows and columns.
4fill in blank
hard

Fill both blanks to create a dictionary comprehension that maps words to their lengths only if length is greater than 3.

Matplotlib
lengths = {word: [1] for word in words if [2]
Drag options to blanks, or click blank then click option'
Alen(word)
Blen(word) > 3
Cword
Dword > 3
Attempts:
3 left
💡 Hint
Common Mistakes
Using the word itself instead of its length.
Using the word in the condition instead of its length.
5fill in blank
hard

Fill all three blanks to create a dictionary comprehension that maps uppercase words to their counts if count is greater than 0.

Matplotlib
result = { [1]: [2] for [3], [2] in data.items() if [2] > 0}
Drag options to blanks, or click blank then click option'
Ak.upper()
Bv
Ck
Ditem
Attempts:
3 left
💡 Hint
Common Mistakes
Using 'item' instead of 'k' and 'v'.
Not converting keys to uppercase.
Using the wrong variable names.

Practice

(1/5)
1. What is the main purpose of using small multiples (facet grid) in matplotlib?
easy
A. To display multiple related charts side by side for easy comparison
B. To create a single large plot with multiple lines
C. To animate a plot over time
D. To change the color scheme of a plot

Solution

  1. Step 1: Understand the concept of small multiples

    Small multiples are multiple small charts arranged in a grid to compare different groups or categories easily.
  2. Step 2: Identify the purpose in matplotlib

    Matplotlib uses small multiples to show many charts side by side, making it easier to compare data visually.
  3. Final Answer:

    To display multiple related charts side by side for easy comparison -> Option A
  4. Quick Check:

    Small multiples = multiple charts side by side [OK]
Hint: Small multiples = many small charts for comparison [OK]
Common Mistakes:
  • Confusing small multiples with animations
  • Thinking it changes colors only
  • Assuming it creates one big plot
2. Which of the following is the correct way to create a 2x2 grid of subplots in matplotlib?
easy
A. fig, axes = plt.subplots(4)
B. fig, axes = plt.subplots(1, 4)
C. fig, axes = plt.subplots(2, 2)
D. fig, axes = plt.subplots(2)

Solution

  1. Step 1: Recall plt.subplots() syntax

    plt.subplots(rows, columns) creates a grid of subplots with given rows and columns.
  2. Step 2: Match the grid size

    To create a 2x2 grid, use plt.subplots(2, 2).
  3. Final Answer:

    fig, axes = plt.subplots(2, 2) -> Option C
  4. Quick Check:

    plt.subplots(2, 2) = 2 rows and 2 columns [OK]
Hint: Use plt.subplots(rows, columns) for grid size [OK]
Common Mistakes:
  • Using single number for grid shape
  • Confusing rows and columns
  • Missing one dimension in arguments
3. What will be the output of this code snippet?
import matplotlib.pyplot as plt
fig, axes = plt.subplots(1, 3)
data = [1, 2, 3]
for i, ax in enumerate(axes):
    ax.plot([data[i]] * 3)
plt.show()
medium
A. Three line plots each with three points of the same value 1, 2, and 3 respectively
B. A single plot with three lines of values 1, 2, and 3
C. Error because axes is not iterable
D. Three scatter plots with points 1, 2, and 3

Solution

  1. Step 1: Understand plt.subplots(1, 3)

    This creates 1 row and 3 columns of subplots, so axes is an array of 3 axes objects.
  2. Step 2: Loop plots each subplot

    For each axis, it plots a line with three points all equal to data[i] (1, then 2, then 3).
  3. Final Answer:

    Three line plots each with three points of the same value 1, 2, and 3 respectively -> Option A
  4. Quick Check:

    Loop over axes plots lines with repeated values [OK]
Hint: Loop over axes to plot each subplot separately [OK]
Common Mistakes:
  • Thinking axes is a single plot
  • Assuming error due to axes type
  • Confusing line plot with scatter plot
4. Identify the error in this code for creating a 2x2 grid of plots:
fig, axes = plt.subplots(2, 2)
for i in range(4):
    axes[i].plot([1, 2, 3])
plt.show()
medium
A. The plot data list is invalid
B. plt.subplots(2, 2) creates only 2 plots, not 4
C. plt.show() is missing
D. axes is a 2D array, so axes[i] indexing causes an error

Solution

  1. Step 1: Understand axes shape from plt.subplots(2, 2)

    axes is a 2x2 numpy array of Axes objects, not a flat list.
  2. Step 2: Identify indexing error

    axes[i] tries to index a 2D array with one index, causing an error. Correct is axes[row, col] or flatten axes first.
  3. Final Answer:

    axes is a 2D array, so axes[i] indexing causes an error -> Option D
  4. Quick Check:

    2D axes need two indices or flatten before looping [OK]
Hint: 2D axes need two indices or flatten before indexing [OK]
Common Mistakes:
  • Assuming axes is 1D array
  • Ignoring error from wrong indexing
  • Thinking plt.show() is missing
5. You have a dataset with sales data for 3 regions. How would you create a 1-row, 3-column grid of plots showing sales trends for each region separately using matplotlib?
hard
A. Use plt.plot() three times without subplots
B. Use plt.subplots(1, 3), loop over axes, and plot each region's data on each subplot
C. Use plt.subplots(3, 1) and plot all regions on each subplot
D. Use plt.subplots(1, 1) and plot all regions on the same plot

Solution

  1. Step 1: Create a 1x3 grid for three regions

    Use plt.subplots(1, 3) to create one row and three columns of plots.
  2. Step 2: Loop over axes and plot each region's data

    Loop through each axis and plot the sales data for each region separately to compare trends side by side.
  3. Final Answer:

    Use plt.subplots(1, 3), loop over axes, and plot each region's data on each subplot -> Option B
  4. Quick Check:

    One row, three columns, loop to plot each region [OK]
Hint: Create grid then loop axes to plot groups separately [OK]
Common Mistakes:
  • Plotting all data on one plot
  • Using wrong grid shape
  • Not looping over axes