Matrix transpose operations in NumPy - Interactive Code Practice

Practice - 5 Tasks

1fill in blank

easy

Complete the code to transpose the matrix using NumPy.

NumPy

import numpy as np
matrix = np.array([[1, 2], [3, 4]])
transposed = matrix[1]

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A.transpose()

B.T

C.reshape(2,2)

D.flatten()

Attempts:

3 left

💡 Hint

Common Mistakes

Using .reshape() changes the shape but does not transpose.

Using .flatten() converts the matrix to a 1D array.

The .T attribute transposes the matrix by swapping rows and columns.

2fill in blank

medium

Complete the code to transpose the matrix using the transpose() function.

NumPy

import numpy as np
matrix = np.array([[5, 6, 7], [8, 9, 10]])
transposed = np.[1](matrix)

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Aflatten

Breshape

Ctranspose

Dravel

Attempts:

3 left

💡 Hint

Common Mistakes

Using flatten() or ravel() which flatten the array instead of transposing.

Using reshape() which changes shape but does not transpose.

The np.transpose() function returns the transpose of the input matrix.

3fill in blank

hard

Fix the error in the code to correctly transpose the matrix.

NumPy

import numpy as np
matrix = np.array([[1, 2], [3, 4]])
transposed = matrix.transpose[1]

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A{}

B[]

C.T

D()

Attempts:

3 left

💡 Hint

Common Mistakes

Forgetting parentheses causes the method object to be returned, not the transposed matrix.

Using square brackets or curly braces causes syntax errors.

The transpose method requires parentheses () to be called as a function.

4fill in blank

hard

Fill both blanks to create a dictionary with words as keys and their lengths as values, only for words longer than 3 characters.

NumPy

words = ['data', 'is', 'fun', 'and', 'cool']
lengths = {word: [1] for word in words if [2]

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Alen(word)

Blen(word) > 3

Cword > 3

Dword.length > 3

Attempts:

3 left

💡 Hint

Common Mistakes

Using word > 3 compares string to number, which is invalid.

Using word.length is not valid in Python.

Use len(word) to get the length and filter words with length greater than 3.

5fill in blank

hard

Fill all three blanks to create a dictionary with uppercase words as keys and their lengths as values, only for words longer than 3 characters.

NumPy

words = ['apple', 'bat', 'carrot', 'dog']
result = { [1]: [2] for w in words if [3] }

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Aw.upper()

Blen(w)

Clen(w) > 3

Dw.lower()

Attempts:

3 left

💡 Hint

Common Mistakes

Using w.lower() instead of uppercase keys.

Not filtering words by length > 3.

Use w.upper() for keys, len(w) for values, and filter words with length greater than 3.