Partial sorting with np.partition() in NumPy - Interactive Code Practice

Practice - 5 Tasks

1fill in blank

easy

Complete the code to partially sort the array so the smallest 3 elements are in the first 3 positions.

NumPy

import numpy as np
arr = np.array([7, 2, 5, 3, 9, 1])
result = np.partition(arr, [1])
print(result)

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A3

B2

C4

D1

Attempts:

3 left

💡 Hint

Common Mistakes

Using an index larger than the array length causes an error.

Confusing the partition index with sorting the whole array.

The second argument to np.partition is the index where the array is partitioned. Using 3 puts the smallest 3 elements in the first 3 positions.

2fill in blank

medium

Complete the code to get the 2 smallest elements using np.partition.

NumPy

import numpy as np
arr = np.array([10, 4, 6, 2, 8])
partitioned = np.partition(arr, [1])
smallest_two = partitioned[:2]
print(smallest_two)

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A2

B1

C3

D0

Attempts:

3 left

💡 Hint

Common Mistakes

Using 2 as partition index returns 3 smallest elements, not 2.

Using 0 returns only the smallest element.

Using np.partition(arr, 1) places the smallest 2 elements in the first two positions (indices 0 and 1).

3fill in blank

hard

Fix the error in the code to correctly partition the array to get the 4 smallest elements.

NumPy

import numpy as np
arr = np.array([9, 1, 7, 3, 5])
result = np.partition(arr, [1])
print(result[:4])

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A3

B4

C2

D5

Attempts:

3 left

💡 Hint

Common Mistakes

Using 4 as partition index causes an error because index is out of bounds.

Using 5 is invalid since array length is 5 and max index is 4.

The partition index should be 3 to place the 4 smallest elements in the first 4 positions (indices 0 to 3).

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 4 characters.

NumPy

words = ['apple', 'bat', 'carrot', 'dog', 'elephant']
lengths = { [1] : [2] for word in words if len(word) > 4 }
print(lengths)

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Aword

Blen(word)

Cword.upper()

Dlen

Attempts:

3 left

💡 Hint

Common Mistakes

Using len as a value instead of len(word).

Using word.upper() as key changes the original word.

The dictionary comprehension uses the word as key and its length as value for words longer than 4 characters.

5fill in blank

hard

Fill all three blanks to create a dictionary with uppercase words as keys and their lengths as values, but only for words shorter than 6 characters.

NumPy

words = ['apple', 'bat', 'carrot', 'dog', 'elephant']
result = { [1] : [2] for word in words if len(word) [3] 5 }
print(result)

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Aword.upper()

Blen(word)

C<=

D>

Attempts:

3 left

💡 Hint

Common Mistakes

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

Using 'word' instead of 'word.upper()' as keys.

The dictionary comprehension uses uppercase words as keys and their lengths as values for words with length less than or equal to 5.