Why 3D visualization matters in Matplotlib - Test Your Understanding

Practice - 5 Tasks

1fill in blank

easy

Complete the code to import the 3D plotting toolkit from matplotlib.

Matplotlib

from mpl_toolkits.mplot3d import [1]

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AAxes3D

Bplot3d

Cplot2d

DAxes2D

Attempts:

3 left

💡 Hint

Common Mistakes

Using 2D plotting modules instead of 3D.

Misspelling the module name.

The Axes3D module is needed to create 3D plots in matplotlib.

2fill in blank

medium

Complete the code to create a 3D subplot in matplotlib.

Matplotlib

fig = plt.figure()
ax = fig.add_subplot(111, projection=[1])

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A'2d'

B'3D'

C'3d'

D'xyz'

Attempts:

3 left

💡 Hint

Common Mistakes

Using uppercase '3D' which causes errors.

Using '2d' projection for 3D plots.

The projection argument must be set to '3d' (all lowercase) to create a 3D plot.

3fill in blank

hard

Fix the error in the code to plot 3D scatter points.

Matplotlib

ax.scatter([1], y, z)

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Ax

Bz

Cy

Dscatter

Attempts:

3 left

💡 Hint

Common Mistakes

Using y or z twice instead of x.

Passing the function name instead of data.

The scatter function requires x, y, and z coordinates. The missing variable is x.

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

{word: [1] for word in words if [2]

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Alen(word)

Blen(word) > 3

Cword > 3

Dlen(words)

Attempts:

3 left

💡 Hint

Common Mistakes

Comparing word string directly to number.

Using len(words) instead of len(word).

The dictionary maps each word to its length using len(word). The condition filters words with length greater than 3 using len(word) > 3.

5fill in blank

hard

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

Matplotlib

result = [1]: [2] for [3] in data.items() if [2] > 0}

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Ak.upper()

Bv

Ck

Ddata

Attempts:

3 left

💡 Hint

Common Mistakes

Using data instead of k or v.

Not converting keys to uppercase.

The dictionary comprehension maps the uppercase key k.upper() to its value v for each key k in the data items, filtering values greater than zero.