Shuffling arrays in NumPy - Interactive Code Practice

Practice - 5 Tasks

1fill in blank

easy

Complete the code to shuffle the array in-place using NumPy.

NumPy

import numpy as np
arr = np.array([1, 2, 3, 4, 5])
np.random.[1](arr)
print(arr)

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Ashuffle

Brandomize

Cpermutation

Dsort

Attempts:

3 left

💡 Hint

Common Mistakes

Using np.random.permutation() which returns a new shuffled array instead of shuffling in-place.

Using np.random.sort() which sorts the array instead of shuffling.

The np.random.shuffle() function shuffles the array in-place, changing the order of elements randomly.

2fill in blank

medium

Complete the code to create a shuffled copy of the array without changing the original.

NumPy

import numpy as np
arr = np.array([10, 20, 30, 40, 50])
shuffled_arr = np.random.[1](arr)
print(shuffled_arr)
print(arr)

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Apermutation

Bshuffle

Crandom

Dchoice

Attempts:

3 left

💡 Hint

Common Mistakes

Using np.random.shuffle() which shuffles the array in-place and changes the original.

Using np.random.choice() which samples elements but may repeat or reduce size.

The np.random.permutation() function returns a new shuffled array, leaving the original unchanged.

3fill in blank

hard

Fix the error in the code to shuffle the array in-place.

NumPy

import numpy as np
arr = np.array([5, 6, 7, 8])
np.random.[1](arr)
print(arr)

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Achoice

Bpermutation

Cshuffle

Dsample

Attempts:

3 left

💡 Hint

Common Mistakes

Using np.random.permutation() with a size argument which is invalid.

Using np.random.choice() or np.random.sample() which do not shuffle in-place.

np.random.shuffle() shuffles the array in-place and does not take a size argument. The other functions either return new arrays or do not exist.

4fill in blank

hard

Fill both blanks to create a dictionary with words as keys and their lengths as values, but only for words longer than 3 letters.

NumPy

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

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Alen(word)

Bword > 3

Clen(word) > 3

Dword

Attempts:

3 left

💡 Hint

Common Mistakes

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

Checking if the word string is greater than 3 instead of its length.

The dictionary comprehension uses len(word) to get the length and filters words with length greater than 3 using len(word) > 3.

5fill in blank

hard

Fill all three blanks to create a dictionary with uppercase words as keys and their lengths as values, only for words longer than 3 letters.

NumPy

words = ['pear', 'fig', 'grape', 'kiwi']
result = { [1]: [2] for w in words if [3] }
print(result)

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Aw.upper()

Blen(w)

Clen(w) > 3

Dw

Attempts:

3 left

💡 Hint

Common Mistakes

Using the original word as key instead of uppercase.

Using the word itself as value instead of length.

Not filtering words by length.

The dictionary comprehension uses w.upper() as keys, len(w) as values, and filters words with length greater than 3.