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.

Practice

1. What does the numpy.transpose() function do to an array?

easy

A. It removes duplicate elements from the array.

B. It adds new elements to the array.

C. It sorts the array elements in ascending order.

D. It swaps or flips the axes of the array.

Solution

1. Step 1: Understand the purpose of transpose()

   The transpose() function changes the order of axes in an array, effectively flipping or swapping them.

2. Step 2: Compare with other options

   Adding elements, sorting, or removing duplicates are unrelated to axis swapping.

3. Final Answer:

   It swaps or flips the axes of the array. -> Option D

4. Quick Check:

   transpose() = swaps axes [OK]

Hint: Remember: transpose flips axes, not values or elements [OK]

Common Mistakes:

• Thinking transpose sorts or changes values
• Confusing transpose with adding or removing elements
• Assuming transpose only works on 2D arrays

2. Which of the following is the correct syntax to transpose a 2D NumPy array named arr?

easy

A. transpose(arr)

B. arr.transpose

C. arr.transpose()

D. arr.transpose[]

Solution

1. Step 1: Recall method call syntax in Python

   To call a method, parentheses are required: arr.transpose().

2. Step 2: Check other options

   transpose(arr) is incorrect because transpose is a method, not a standalone function here; arr.transpose misses parentheses; arr.transpose[] is invalid syntax.

3. Final Answer:

   arr.transpose() -> Option C

4. Quick Check:

   Method call needs parentheses [OK]

Hint: Use parentheses to call transpose method: arr.transpose() [OK]

Common Mistakes:

• Omitting parentheses when calling transpose
• Using transpose as a standalone function without import
• Using invalid syntax like brackets after method

3. What is the output of the following code?

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

medium

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

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

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

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

Solution

1. Step 1: Understand the original array shape

   The array has shape (2, 3): 2 rows and 3 columns.

2. Step 2: Apply transpose()

   Transpose swaps axes, so shape becomes (3, 2). Rows become columns and vice versa. The first column becomes the first row: [1,4], second: [2,5], third: [3,6].

3. Final Answer:

   [[1 4] [2 5] [3 6]] -> Option A

4. Quick Check:

   Transpose swaps rows and columns [OK]

Hint: Transpose flips rows and columns in 2D arrays [OK]

Common Mistakes:

• Confusing transpose with reversing elements
• Expecting original shape after transpose
• Mixing up rows and columns in output

4. The following code throws an error. What is the mistake?

import numpy as np
arr = np.array([[[1,2],[3,4]], [[5,6],[7,8]]])
print(arr.transpose(1, 0))

medium

A. transpose() requires all axes to be specified for 3D arrays.

B. The array is not a NumPy array.

C. transpose() cannot be used on 3D arrays.

D. The axes argument must be a list, not a tuple.

Solution

1. Step 1: Check array dimensions

   The array has 3 dimensions (shape (2, 2, 2)).

2. Step 2: Understand transpose axes argument

   For 3D arrays, transpose requires all three axes to be specified. Passing only two axes (1, 0) causes an error.

3. Final Answer:

   transpose() requires all axes to be specified for 3D arrays. -> Option A

4. Quick Check:

   All axes must be given for 3D transpose [OK]

Hint: Specify all axes when transposing multi-dimensional arrays [OK]

Common Mistakes:

• Passing fewer axes than array dimensions
• Thinking transpose can't handle 3D arrays
• Confusing tuple and list for axes argument

5. Given a 3D NumPy array arr with shape (2, 3, 4), which transpose() call will swap the first and last axes, resulting in shape (4, 3, 2)?

hard

A. arr.transpose(2, 0, 1)

B. arr.transpose(2, 1, 0)

C. arr.transpose(0, 2, 1)

D. arr.transpose(1, 0, 2)

Solution

1. Step 1: Identify original axes order

   Original shape (2, 3, 4) corresponds to axes (0, 1, 2).

2. Step 2: Determine desired axes order

   Swapping first and last axes means new order is (2, 1, 0), resulting in shape (4, 3, 2).

3. Final Answer:

   arr.transpose(2, 1, 0) -> Option B

4. Quick Check:

   Swap axes 0 and 2: (2,1,0) [OK]

Hint: List axes in desired order to swap them correctly [OK]

Common Mistakes:

• Mixing up axes order in transpose
• Not specifying all axes for 3D arrays
• Assuming transpose swaps only two axes automatically