Why boolean masking matters in NumPy - Test Your Understanding

Practice - 5 Tasks

1fill in blank

easy

Complete the code to create a boolean mask that selects values greater than 5.

NumPy

import numpy as np
arr = np.array([3, 7, 2, 9, 5])
mask = arr [1] 5
print(mask)

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

A<

B==

C>

D!=

Attempts:

3 left

💡 Hint

Common Mistakes

Using '==' instead of '>' results in a mask selecting only values equal to 5.

Using '<' selects values less than 5, which is the opposite of what we want.

The operator > creates a boolean mask selecting values greater than 5.

2fill in blank

medium

Complete the code to use the boolean mask to select values greater than 5 from the array.

NumPy

import numpy as np
arr = np.array([3, 7, 2, 9, 5])
mask = arr > 5
selected = arr[1]mask]
print(selected)

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

A[

B+

C*

D-

Attempts:

3 left

💡 Hint

Common Mistakes

Using '+' or '*' tries to add or multiply, which is incorrect for masking.

Forgetting brackets causes a syntax error.

Using square brackets [] applies the boolean mask to select elements.

3fill in blank

hard

Fix the error in the code to correctly create a mask for values less than or equal to 4.

NumPy

import numpy as np
arr = np.array([1, 4, 6, 3, 8])
mask = arr [1] 4
print(mask)

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

A<

B<=

C==

D>=

Attempts:

3 left

💡 Hint

Common Mistakes

Using '<' excludes values equal to 4.

Using '>=' selects values greater than or equal to 4, which is wrong.

The operator <= selects values less than or equal to 4, matching the requirement.

4fill in blank

hard

Complete the code to create a dictionary of words and their lengths, but only for words longer than 3 letters.

NumPy

words = ['cat', 'elephant', 'dog', 'lion']
lengths = {word: len(word) for word in words if len(word) [1] 3}
print(lengths)

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

A:

B>

C<

D=

Attempts:

3 left

💡 Hint

Common Mistakes

Using '=' instead of ':' causes syntax errors in dictionary comprehension.

Using '<' filters words shorter than 3, opposite of requirement.

Use : to map word to its length, and > to filter words longer than 3 letters.

5fill in blank

hard

Fill all three blanks to create a dictionary with uppercase words as keys and their lengths as values, only for words with length greater than 3.

NumPy

words = ['apple', 'bat', 'carrot', 'dog']
result = [1]: [2] for w in words if len(w) [3] 3
print(result)

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

Aw.upper()

Blen(w)

C>

Dw.lower()

Attempts:

3 left

💡 Hint

Common Mistakes

Using w.lower() instead of uppercase keys.

Using '<' instead of '>' filters wrong words.

Use w.upper() for keys, len(w) for values, and filter with > for length greater than 3.