Why broadcasting matters in NumPy - Test Your Understanding

Practice - 5 Tasks

1fill in blank

easy

Complete the code to create a numpy array of shape (3, 1).

NumPy

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

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

A.dtype

B.size

C.shape

D.ndim

Attempts:

3 left

💡 Hint

Common Mistakes

Using .size instead of .shape

Trying to call .shape() as a function

The .shape attribute shows the dimensions of the array, which is (3, 1) here.

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
A = np.array([[1, 2, 3], [4, 5, 6]])
B = np.array([10, 20, 30])
result = A [1] B
print(result)

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A+

B-

C/

D*

Attempts:

3 left

💡 Hint

Common Mistakes

Using subtraction or multiplication instead of addition

Trying to add arrays with incompatible shapes without broadcasting

Adding arrays with compatible shapes uses broadcasting to add B to each row of A.

3fill in blank

hard

Fix the error in the code to multiply a (3,1) array by a (3,) array using broadcasting.

NumPy

import numpy as np
x = np.array([[1], [2], [3]])
y = np.array([4, 5, 6])
result = x [1] y
print(result)

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

A+

B*

C-

D/

Attempts:

3 left

💡 Hint

Common Mistakes

Using addition or subtraction instead of multiplication

Not understanding how broadcasting aligns dimensions

Multiplying arrays with shapes (3,1) and (3,) uses broadcasting to multiply each element correctly.

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 = ['apple', 'bat', 'carrot', 'dog']
lengths = {word: [1] for word in words if [2]

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Alen(word)

Blen(word) > 3

Cword

Dlen(words)

Attempts:

3 left

💡 Hint

Common Mistakes

Using the word itself as value

Using wrong condition like len(words) instead of len(word) > 3

The dictionary comprehension maps each word to its length using len(word). The condition len(word) > 3 filters words longer than 3 letters.

5fill in blank

hard

Fill all three blanks to create a dictionary comprehension that maps uppercase words to their lengths if length is greater than 4.

NumPy

words = ['apple', 'bat', 'carrot', 'dog']
[1] = { [2]: [3] for w in words if len(w) > 4 }

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Aresult

Bw.upper()

Clen(w)

Dword

Attempts:

3 left

💡 Hint

Common Mistakes

Using 'word' instead of 'w.upper()' for keys

Not assigning the comprehension to a variable

The dictionary comprehension creates result mapping each uppercase word w.upper() to its length len(w) for words longer than 4 letters.