transpose() for swapping axes in NumPy - Practice Problems & Coding Challenges

Challenge - 5 Problems

❓ Predict Output

intermediate

Output of 2D array transpose

What is the output of this code snippet using numpy.transpose() on a 2D array?

NumPy

import numpy as np
arr = np.array([[1, 2, 3], [4, 5, 6]])
result = np.transpose(arr)
print(result)

A

[[1 4]
 [2 5]
 [3 6]]

B

[[1 2 3]
 [4 5 6]]

C

[[1 2]
 [3 4]
 [5 6]]

D

[[6 5 4]
 [3 2 1]]

💡 Hint

Transpose swaps rows and columns.

The transpose of a 2x3 array becomes a 3x2 array where rows become columns and columns become rows.

❓ data_output

intermediate

Shape after transpose on 3D array

Given a 3D numpy array with shape (2, 3, 4), what is the shape after applying np.transpose(arr, (1, 0, 2))?

NumPy

import numpy as np
arr = np.zeros((2, 3, 4))
result = np.transpose(arr, (1, 0, 2))
print(result.shape)

A (2, 3, 4)

B (3, 2, 4)

C (4, 3, 2)

D (3, 4, 2)

💡 Hint

The tuple (1, 0, 2) reorders axes by their indices.

The axes are reordered: axis 1 becomes axis 0, axis 0 becomes axis 1, axis 2 stays the same.

🔧 Debug

advanced

Identify the error in transpose usage

What error does this code raise when trying to transpose a 2D numpy array with an invalid axes tuple?

NumPy

import numpy as np
arr = np.array([[1, 2], [3, 4]])
result = np.transpose(arr, (0, 2))

A ValueError: axes don't match array

B TypeError: transpose() takes 1 positional argument but 2 were given

C IndexError: axis 2 is out of bounds for array of dimension 2

D No error, returns transposed array

💡 Hint

Check the axes indices against array dimensions.

The array has only 2 dimensions (axes 0 and 1). Axis 2 does not exist, causing ValueError.

🧠 Conceptual

advanced

Effect of transpose on array memory layout

Which statement best describes the effect of numpy.transpose() on the memory layout of an array?

A Transpose flattens the array into 1D

B Transpose always copies data to a new memory location

C Transpose modifies the original array in-place

D Transpose returns a view with changed strides, no data is copied

💡 Hint

Think about whether transpose copies data or not.

Transpose returns a view with modified strides, so no data copying happens unless explicitly requested.

🚀 Application

expert

Using transpose to swap axes in image data

You have a color image stored as a numpy array with shape (height, width, channels). Which np.transpose() call correctly swaps the height and width axes without changing the color channels?

A np.transpose(image, (0, 2, 1))

B np.transpose(image, (2, 0, 1))

C np.transpose(image, (1, 0, 2))

D np.transpose(image, (2, 1, 0))

💡 Hint

Height is axis 0, width is axis 1, channels is axis 2.

Swapping height and width means swapping axes 0 and 1, keeping axis 2 (channels) the same.