Why advanced broadcasting matters in NumPy - Test Your Understanding

Practice - 5 Tasks

1fill in blank

easy

Complete the code to create a 2D array of shape (3, 3) filled with ones.

NumPy

import numpy as np
array = np.[1]((3, 3))

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Aempty

Bzeros

Cones

Dfull

Attempts:

3 left

💡 Hint

Common Mistakes

Using np.zeros instead of np.ones

Using np.empty which creates uninitialized values

The np.ones function creates an array filled with ones.

2fill in blank

medium

Complete the code to add a 1D array to each row of a 2D array using broadcasting.

NumPy

import numpy as np
arr2d = np.array([[1, 2, 3], [4, 5, 6]])
arr1d = np.array([10, 20, 30])
result = arr2d + [1]

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Aarr1d.reshape(3, 1)

Barr1d.T

Carr1d.reshape(1, 3)

Darr1d

Attempts:

3 left

💡 Hint

Common Mistakes

Using reshape(3, 1) which is incompatible

Using transpose which does not change shape as needed

Adding arr1d directly works because its shape (3,) broadcasts correctly across the columns of arr2d.

3fill in blank

hard

Fix the error in the code that tries to add arrays with incompatible shapes.

NumPy

import numpy as np
arr1 = np.array([[1, 2, 3], [4, 5, 6]])
arr2 = np.array([10, 20, 30])
result = arr1 + [1]

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

Aarr2.reshape(3, 1)

Barr2

Carr2.reshape(2, 3)

Darr2.reshape(1, 3)

Attempts:

3 left

💡 Hint

Common Mistakes

Using reshape(3, 1) which mismatches dimensions

Not reshaping at all causing shape error

Adding arr2 directly works because its shape (3,) broadcasts correctly across the columns of arr1.

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.

NumPy

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

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Alen(word)

Bword

Clen(word) > 3

Dword > 3

Attempts:

3 left

💡 Hint

Common Mistakes

Using word instead of length

Using word > 3 which compares strings incorrectly

Use len(word) to get length and filter with len(word) > 3.

5fill in blank

hard

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

NumPy

words = ['data', 'ai', 'science', 'ml']
result = { [1]: [2] for word in words if [3] }

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Aword.upper()

Blen(word)

Clen(word) > 3

Dword.lower()

Attempts:

3 left

💡 Hint

Common Mistakes

Using lowercase instead of uppercase

Using word instead of length for values

Map uppercase words (word.upper()) to their lengths (len(word)) only if length is greater than 3 (len(word) > 3).