Indexing with ellipsis in NumPy - Interactive Code Practice

Practice - 5 Tasks

1fill in blank

easy

Complete the code to select all elements in the last dimension of a 3D NumPy array using ellipsis.

NumPy

import numpy as np
arr = np.arange(27).reshape(3, 3, 3)
result = arr[1]

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

A[..., :]

B[..., 1]

C[:, :, :]

D[0, ...]

Attempts:

3 left

💡 Hint

Common Mistakes

Using explicit slicing for all dimensions instead of ellipsis.

Using an index instead of a slice after ellipsis.

The ellipsis ... represents all preceding dimensions, so arr[..., :] selects all elements in the last dimension.

2fill in blank

medium

Complete the code to select the first element in the last dimension for all other dimensions using ellipsis.

NumPy

import numpy as np
arr = np.arange(24).reshape(2, 3, 4)
result = arr[1]

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

A[..., 0]

B[0, ..., 0]

C[..., 1]

D[:, :, 0]

Attempts:

3 left

💡 Hint

Common Mistakes

Using explicit indices for all dimensions instead of ellipsis.

Selecting the wrong index in the last dimension.

arr[..., 0] selects the first element in the last dimension for all other dimensions.

3fill in blank

hard

Fix the error in the code to correctly select all elements in the last two dimensions using ellipsis.

NumPy

import numpy as np
arr = np.arange(60).reshape(3, 4, 5)
result = arr[1]

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

A[..., ::]

B[..., 0]

C[..., :, :]

D[..., 1:]

Attempts:

3 left

💡 Hint

Common Mistakes

Using invalid slice syntax after ellipsis.

Selecting only one dimension instead of two.

The correct syntax to select all elements in the last two dimensions is arr[..., :, :].

4fill in blank

hard

Fill both blanks to create a dictionary comprehension that maps each word to its length only if the length is greater than 3.

NumPy

words = ['data', 'science', 'ai', 'ml']
lengths = {word: [1] for word in words if [2]

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Alen(word)

Blen(word) > 3

Cword.startswith('a')

Dword

Attempts:

3 left

💡 Hint

Common Mistakes

Using the word itself as the value instead of its length.

Filtering with incorrect conditions.

The dictionary comprehension maps each word to its length using len(word) and 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 each word in uppercase to its length only if the length is greater than 2.

NumPy

words = ['cat', 'dog', 'a', 'elephant']
result = [1]: [2] for word in words if [3]

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

Aword.upper()

Blen(word)

Clen(word) > 2

Dword.lower()

Attempts:

3 left

💡 Hint

Common Mistakes

Using lowercase instead of uppercase for keys.

Not filtering words by length correctly.

The comprehension maps each word in uppercase (word.upper()) to its length (len(word)) only if the length is greater than 2 (len(word) > 2).