Avoiding broadcasting mistakes in NumPy - Interactive Code Practice

Practice - 5 Tasks

1fill in blank

easy

Complete the code to create a NumPy array of zeros with shape (3, 4).

NumPy

import numpy as np
arr = np.[1]((3, 4))

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Azeros

Bfull

Cempty

Dones

Attempts:

3 left

💡 Hint

Common Mistakes

Using np.ones instead of np.zeros creates an array of ones.

Using np.empty creates an uninitialized array with random values.

The np.zeros function creates an array filled with zeros of the specified shape.

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
arr = np.array([[1, 2, 3], [4, 5, 6]])
add = np.array([10, 20, 30])
result = arr + [1]

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Aadd.reshape(3, 1)

Badd

Cadd.T

Dadd.reshape(1, 3)

Attempts:

3 left

💡 Hint

Common Mistakes

Reshaping to (3, 1) tries to add column-wise, causing shape mismatch.

Using add.T does not change shape correctly for broadcasting.

Reshaping add to (1, 3) allows it to broadcast correctly across each row of arr.

3fill in blank

hard

Fix the error in the code to multiply a 2D array by a 1D array along columns using broadcasting.

NumPy

import numpy as np
arr = np.array([[1, 2, 3], [4, 5, 6]])
multiplier = np.array([2, 3])
result = arr * [1]

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Amultiplier.reshape(2, 1)

Bmultiplier

Cmultiplier.reshape(1, 2)

Dmultiplier.T

Attempts:

3 left

💡 Hint

Common Mistakes

Using multiplier without reshape causes shape mismatch error.

Reshaping to (1, 2) aligns with columns, not rows.

Reshaping multiplier to (2, 1) aligns it with the rows of arr for correct broadcasting.

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.startswith('a')

Dword != 'dog'

Attempts:

3 left

💡 Hint

Common Mistakes

Using word.startswith('a') filters words starting with 'a' instead of length.

Using word != 'dog' excludes 'dog' but does not check length.

The dictionary maps each word to its length, but only includes words with length greater than 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 4.

NumPy

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

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Aw.upper()

Blen(w)

Clen(w) > 4

Dw.lower()

Attempts:

3 left

💡 Hint

Common Mistakes

Using w.lower() instead of w.upper() changes the case incorrectly.

Filtering with len(w) > 3 includes shorter words than required.

The dictionary comprehension converts each word to uppercase as the key, maps it to its length, and includes only words longer than 4 characters.