np.broadcast_to() for explicit broadcasting in NumPy - Interactive Code Practice

Practice - 5 Tasks

1fill in blank

easy

Complete the code to broadcast array a to shape (3, 3).

NumPy

import numpy as np

a = np.array([1, 2, 3])
b = np.broadcast_to(a, [1])
print(b)

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A(3, 1)

B(3,)

C(1, 3)

D(3, 3)

Attempts:

3 left

💡 Hint

Common Mistakes

Using the original shape (3,) which does not broadcast.

Using (1, 3) which only adds a new axis but does not repeat rows.

We use np.broadcast_to to expand a to shape (3, 3) by repeating its values along the new axis.

2fill in blank

medium

Complete the code to broadcast a 1D array arr to a 2D array with 4 rows and 5 columns.

NumPy

import numpy as np

arr = np.array([10, 20, 30, 40, 50])
broadcasted = np.broadcast_to(arr, [1])
print(broadcasted)

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A(4, 5)

B(5, 4)

C(1, 5)

D(5, 1)

Attempts:

3 left

💡 Hint

Common Mistakes

Swapping the dimensions and using (5, 4) which is incorrect.

Using (1, 5) which does not add the required rows.

The array arr has 5 elements. Broadcasting to (4, 5) repeats arr across 4 rows.

3fill in blank

hard

Fix the error in broadcasting a 1D array data to shape (2, 3).

NumPy

import numpy as np

data = np.array([1, 2, 3])
result = np.broadcast_to(data, [1])
print(result)

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A(3, 2)

B(2, 2)

C(2, 3)

D(3, 3)

Attempts:

3 left

💡 Hint

Common Mistakes

Using (3, 2) which swaps dimensions and causes an error.

Using (2, 2) which does not match the original array length.

The original array has shape (3,), so broadcasting to (2, 3) repeats the array over 2 rows correctly.

4fill in blank

hard

Fill both blanks to create a dictionary with words as keys and their lengths broadcasted only if length is greater than 3.

NumPy

words = ['apple', 'bat', 'carrot', 'dog']
lengths = {word: len(word) for word in words if len(word) [1] 3}
broadcasted = np.broadcast_to(np.array(list(lengths.values())), [2])
print(broadcasted)

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A>

B(2, 2)

C(4, 1)

D<

Attempts:

3 left

💡 Hint

Common Mistakes

Using '<' instead of '>' in the filter condition.

Broadcasting to a shape that does not match the number of filtered lengths.

We filter words with length greater than 3, then broadcast the lengths array to shape (2, 2).

5fill in blank

hard

Fill all three blanks to create a dictionary with uppercase words as keys, their lengths as values, and broadcast lengths greater than 4 to shape (3, 2).

NumPy

words = ['tree', 'house', 'car', 'elephant']
lengths = {word[1]: [2] for word in words if len(word) [3] 4}
broadcasted = np.broadcast_to(np.array(list(lengths.values())), (3, 2))
print(broadcasted)

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A.upper()

Blen(word)

C>

Dword

Attempts:

3 left

💡 Hint

Common Mistakes

Not converting words to uppercase keys.

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

Using '<' instead of '>' in the filter condition.

We convert words to uppercase keys, use their lengths as values, and filter lengths greater than 4 before broadcasting.