In-place operations for memory efficiency in NumPy - Interactive Code Practice

Practice - 5 Tasks

1fill in blank

easy

Complete the code to add 5 to each element of the numpy array in-place.

NumPy

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

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

A*

B-

C+

D/

Attempts:

3 left

💡 Hint

Common Mistakes

Using = instead of += which creates a new array.

Using * or / which multiply or divide instead of adding.

The += operator adds the value to each element of the array in-place, saving memory.

2fill in blank

medium

Complete the code to multiply each element of the numpy array by 3 in-place.

NumPy

import numpy as np
arr = np.array([2, 4, 6])
arr [1]= 3
print(arr)

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

A+

B/

C-

D*

Attempts:

3 left

💡 Hint

Common Mistakes

Using = instead of *= which creates a new array.

Using + or - which add or subtract instead of multiplying.

The *= operator multiplies each element by the given value in-place, saving memory.

3fill in blank

hard

Fix the error in the code to subtract 2 from each element of the numpy array in-place.

NumPy

import numpy as np
arr = np.array([10, 20, 30])
arr [1]= 2
print(arr)

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

A-=

B+=

C*=

D/=

Attempts:

3 left

💡 Hint

Common Mistakes

Using = instead of -= which creates a new array.

Using += which adds instead of subtracting.

The -= operator subtracts the value from each element in-place, which is the correct way to modify the array without creating a new one.

4fill in blank

hard

Fill both blanks to divide each element of the numpy array by 4 in-place and then print the array.

NumPy

import numpy as np
arr = np.array([8, 16, 24])
arr [1]= [2]
print(arr)

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

A/

B*

C4

D2

Attempts:

3 left

💡 Hint

Common Mistakes

Using * instead of / which multiplies instead of dividing.

Using 2 instead of 4 which changes the division factor.

The /= operator divides each element by the given value in-place. Here, dividing by 4 modifies the array without extra memory.

5fill in blank

hard

Fill all three blanks to create a numpy array, add 10 in-place, and then multiply by 2 in-place.

NumPy

import numpy as np
arr = np.array([1])
arr [2]= 10
arr [3]= 2
print(arr)

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

A[5, 10, 15]

B+=

C*=

D[1, 2, 3]

Attempts:

3 left

💡 Hint

Common Mistakes

Using the wrong list for the array creation.

Using = instead of += or *= which creates new arrays.

Mixing up the order of operations.

First, we create an array with values 5, 10, 15. Then we add 10 to each element in-place using +=. Finally, we multiply each element by 2 in-place using *=.