Broadcasting with higher dimensions in NumPy - Interactive Code Practice

Practice - 5 Tasks

1fill in blank

easy

Complete the code to create a 3D array of zeros with shape (2, 3, 4).

NumPy

import numpy as np
arr = np.zeros([1])
print(arr.shape)

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

A(2, 3, 4)

B2, 3, 4

C[2, 3, 4]

D3, 4, 2

Attempts:

3 left

💡 Hint

Common Mistakes

Using a list instead of a tuple for the shape.

Passing separate numbers without parentheses.

The np.zeros function requires a tuple to specify the shape. So (2, 3, 4) is correct.

2fill in blank

medium

Complete the code to add a 1D array to a 3D array using broadcasting.

NumPy

import numpy as np
arr3d = np.ones((2, 3, 4))
arr1d = np.array([1, 2, 3, 4])
result = arr3d + [1]
print(result.shape)

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Aarr1d.reshape(1, 4)

Barr1d.reshape(4, 1)

Carr1d.reshape(1, 1, 4)

Darr1d

Attempts:

3 left

💡 Hint

Common Mistakes

Using the original 1D array without reshaping.

Reshaping to incompatible shapes like (4, 1) or (1, 4).

To broadcast a 1D array over the last dimension of a 3D array, reshape it to (1, 1, 4).

3fill in blank

hard

Fix the error in the code to multiply a (3, 1) array with a (1, 4) array using broadcasting.

NumPy

import numpy as np
arr1 = np.array([[1], [2], [3]])
arr2 = np.array([[4, 5, 6, 7]])
result = arr1 [1] arr2
print(result.shape)

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

A/

B+

C-

D*

Attempts:

3 left

💡 Hint

Common Mistakes

Using addition or subtraction instead of multiplication.

Using division which would also broadcast but is not the intended operation.

Multiplying arrays with shapes (3,1) and (1,4) broadcasts to (3,4). The operator * is correct.

4fill in blank

hard

Fill both blanks to create a 3D array by broadcasting a (3, 1) array and a (1, 4) array.

NumPy

import numpy as np
arr1 = np.array([[1], [2], [3]])
arr2 = np.array([[4, 5, 6, 7]])
result = arr1 [1] arr2
print(result.shape == ([2]))

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A*

B+

C(3, 4)

D(4, 3)

Attempts:

3 left

💡 Hint

Common Mistakes

Using addition instead of multiplication.

Confusing the shape order as (4, 3) instead of (3, 4).

Multiplying arr1 and arr2 broadcasts to shape (3, 4).

5fill in blank

hard

Fill all three blanks to multiply two arrays using broadcasting and verify the resulting shape.

NumPy

import numpy as np
a = np.ones((3,1))
b = np.arange(4).reshape(1,4)
result = a [1] b
print(result.shape == ([2], [3]))

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

A*

B3

C4

D1

Attempts:

3 left

💡 Hint

Common Mistakes

Using matrix multiplication @ instead of element-wise *.

Reversing the shape dimensions to (4,3).

The arrays with shapes (3,1) and (1,4) broadcast to (3,4) when using the element-wise multiplication operator *.