reshape() for changing dimensions in NumPy - Interactive Code Practice

Practice - 5 Tasks

1fill in blank

easy

Complete the code to reshape the 1D array into a 2D array with 3 rows.

NumPy

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

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

Areshape

Bflatten

Cravel

Dresize

Attempts:

3 left

💡 Hint

Common Mistakes

Using resize instead of reshape.

Using flatten which converts to 1D instead of reshaping.

The reshape() method changes the shape of the array without changing its data. Here, it changes a 1D array into a 2D array with 3 rows and 2 columns.

2fill in blank

medium

Complete the code to reshape the array into 3 rows and 2 columns.

NumPy

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

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

Aflatten

Bresize

Creshape

Dravel

Attempts:

3 left

💡 Hint

Common Mistakes

Using resize which modifies the original array.

Using flatten which makes the array 1D.

reshape() changes the shape of the array to the given dimensions (3 rows, 2 columns).

3fill in blank

hard

Fix the error in reshaping the array to 2 rows and 4 columns.

NumPy

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

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

Areshape

Bresize

Cflatten

Dravel

Attempts:

3 left

💡 Hint

Common Mistakes

Using reshape with incompatible shape causes an error.

Using flatten or ravel does not change shape as needed.

The error is because the total size (6) does not match the new shape (2*4=8). Using resize() changes the array size and fills with zeros if needed.

4fill in blank

hard

Fill both blanks to create a 3D array with shape (2, 3, 1).

NumPy

import numpy as np
arr = np.arange(6)
reshaped = arr.[1]((2, [2], 1))
print(reshaped.shape)

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

Areshape

B3

C4

Dresize

Attempts:

3 left

💡 Hint

Common Mistakes

Using resize which changes array size.

Choosing wrong middle dimension that does not match total elements.

Use reshape to change the array shape to (2, 3, 1). The middle dimension is 3 to match total elements (2*3*1=6).

5fill in blank

hard

Fill both blanks to create a dictionary with word lengths for words longer than 3 letters.

NumPy

words = ['data', 'science', 'is', 'fun']
lengths = {word: [1] for word in words if len(word) [2] 3}
print(lengths)

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A:

Blen(word)

C>

D=

Attempts:

3 left

💡 Hint

Common Mistakes

Using '=' instead of ':' in dictionary comprehension.

Using wrong comparison operator like '=' instead of '>'.

This dictionary comprehension creates a dictionary where keys are words and values are their lengths, but only for words longer than 3 letters.