np.take() and np.put() for advanced selection in NumPy - Interactive Code Practice

Practice - 5 Tasks

1fill in blank

easy

Complete the code to select elements from array 'a' at indices 1 and 3 using np.take().

NumPy

import numpy as np

a = np.array([10, 20, 30, 40, 50])
indices = [1, 3]
selected = np.[1](a, indices)
print(selected)

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

Atake

Bput

Cselect

Dchoose

Attempts:

3 left

💡 Hint

Common Mistakes

Using np.put() instead of np.take() for selection.

Trying to use np.select() which is for conditions.

np.take() selects elements from an array at specified indices.

2fill in blank

medium

Complete the code to replace elements at indices 0 and 2 in array 'a' with values 100 and 200 using np.put().

NumPy

import numpy as np

a = np.array([1, 2, 3, 4, 5])
indices = [0, 2]
values = [100, 200]
np.[1](a, indices, values)
print(a)

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Aput

Btake

Cinsert

Dreplace

Attempts:

3 left

💡 Hint

Common Mistakes

Using np.take() which only selects elements.

Trying to use np.insert() which inserts elements shifting others.

np.put() replaces elements at given indices with new values.

3fill in blank

hard

Fix the error in the code to correctly select elements at indices 2 and 4 from array 'a' using np.take().

NumPy

import numpy as np

a = np.array([5, 10, 15, 20, 25])
indices = (2, 4)
selected = np.[1](a, indices)
print(selected)

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Aput

Btake

Cget

Dfetch

Attempts:

3 left

💡 Hint

Common Mistakes

Using np.put() which is for assignment, not selection.

Using non-existent functions like np.get() or np.fetch().

np.take() accepts tuples or lists for indices to select elements.

4fill in blank

hard

Fill both blanks to create a dictionary comprehension that maps each word to its length only if the length is greater than 3.

NumPy

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

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Alen(word)

Bword

Clen(word) > 3

Dword > 3

Attempts:

3 left

💡 Hint

Common Mistakes

Using word instead of len(word) for the value.

Using word > 3 which compares string to number.

We map each word to its length (len(word)) only if length is greater than 3 (len(word) > 3).

5fill in blank

hard

Fill all three blanks to create a dictionary comprehension that maps uppercase words to their values only if the value is positive.

NumPy

data = {'a': 1, 'b': -2, 'c': 3}
result = { [1]: [2] for k, v in data.items() if v [3] 0 }

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Ak.upper()

Bv

C>

Dk.lower()

Attempts:

3 left

💡 Hint

Common Mistakes

Using k.lower() instead of k.upper().

Using v < 0 which filters negative values.

We map uppercase keys (k.upper()) to their values (v) only if value is greater than zero (v > 0).