Boolean indexing for filtering in NumPy - Interactive Code Practice

Practice - 5 Tasks

1fill in blank

easy

Complete the code to filter the array and keep only values greater than 5.

NumPy

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

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A>

B<

C==

D<=

Attempts:

3 left

💡 Hint

Common Mistakes

Using == instead of > which selects only values equal to 5.

Using < which selects values less than 5.

We use > to select values greater than 5.

2fill in blank

medium

Complete the code to filter the array and keep only even numbers.

NumPy

import numpy as np
arr = np.array([1, 4, 7, 8, 10])
even = arr[arr [1] 2 == 0]
print(even)

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A+

B//

C**

D%

Attempts:

3 left

💡 Hint

Common Mistakes

Using floor division // which does not check for evenness.

Using exponentiation ** which is unrelated.

The modulo operator % gives the remainder. Even numbers have remainder 0 when divided by 2.

3fill in blank

hard

Fix the error in the code to filter values less than 10.

NumPy

import numpy as np
arr = np.array([12, 5, 8, 15, 3])
filtered = arr[arr [1] 10]
print(filtered)

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

A=>

B<

C==

D!=

Attempts:

3 left

💡 Hint

Common Mistakes

Using invalid operator => which causes syntax error.

Using == which selects only values equal to 10.

The operator < selects values less than 10.

4fill in blank

hard

Fill both blanks to create a dictionary of words and their lengths for words longer than 3 characters.

NumPy

words = ['cat', 'elephant', 'dog', 'lion']
lengths = {word: [1] for word in words if [2]
print(lengths)

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Alen(word)

Bword

Clen(word) > 3

Dword > 3

Attempts:

3 left

💡 Hint

Common Mistakes

Using word > 3 which compares string to number and causes error.

Using word instead of length in the dictionary values.

We use len(word) to get the length and filter words with length greater than 3.

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 longer than 4 characters.

NumPy

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

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Aw.upper()

Blen(w)

Clen(w) > 4

Dw.lower()

Attempts:

3 left

💡 Hint

Common Mistakes

Using w.lower() instead of uppercase for keys.

Filtering with len(w) >= 4 which includes words of length 4.

Keys are uppercase words using w.upper(), values are lengths with len(w), filtered by length > 4.