np.where() for conditional selection in NumPy - Interactive Code Practice

Practice - 5 Tasks

1fill in blank

easy

Complete the code to select elements greater than 5 using np.where().

NumPy

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

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

A!=

B<

C==

D>

Attempts:

3 left

💡 Hint

Common Mistakes

Using < instead of > will select wrong elements.

Using == will only select elements exactly equal to 5.

The np.where() function returns indices where the condition is true. Here, we want indices where elements are greater than 5.

2fill in blank

medium

Complete the code to replace values less than 4 with 0 using np.where().

NumPy

import numpy as np
arr = np.array([2, 5, 3, 7, 1])
new_arr = np.where(arr [1] 4, 0, arr)
print(new_arr)

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

A>

B<

C==

D!=

Attempts:

3 left

💡 Hint

Common Mistakes

Using > will replace wrong elements.

Forgetting to provide the else part keeps all elements unchanged.

The condition arr < 4 selects elements less than 4. np.where() replaces those with 0, else keeps original.

3fill in blank

hard

Fix the error in the code to select elements equal to 10 using np.where().

NumPy

import numpy as np
arr = np.array([10, 5, 10, 3, 10])
indices = np.where(arr [1] 10)
print(indices)

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

A===

B=

C==

D!=

Attempts:

3 left

💡 Hint

Common Mistakes

Using single = causes syntax error.

Using === is invalid in Python.

In Python, == is used to check equality. = is assignment and causes error here.

4fill in blank

hard

Fill both blanks to create a new array where values greater than 3 are replaced by 1, else 0.

NumPy

import numpy as np
arr = np.array([2, 4, 1, 5, 3])
new_arr = np.where(arr [1] 3, [2], 0)
print(new_arr)

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

A>

B1

C<

D3

Attempts:

3 left

💡 Hint

Common Mistakes

Using < instead of > selects wrong elements.

Replacing with 0 instead of 1 changes the output.

The condition arr > 3 selects elements greater than 3. These are replaced by 1, else 0.

5fill in blank

hard

Fill all three blanks to create a new array where values less than 5 are replaced by 0, values equal to 5 by 5, else by 10.

NumPy

import numpy as np
arr = np.array([3, 5, 7, 2, 5])
new_arr = np.where(arr [1] 5, 0, np.where(arr [2] 5, [3], 10))
print(new_arr)

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

A<

B==

C5

D0

Attempts:

3 left

💡 Hint

Common Mistakes

Mixing up < and == operators.

Using wrong replacement values changes the output.

The first condition checks for values less than 5 to replace with 0. The nested np.where() checks for values equal to 5 to replace with 5, else 10.