ndarray as the core data structure in NumPy - Interactive Code Practice

Practice - 5 Tasks

1fill in blank

easy

Complete the code to create a NumPy array from a Python list.

NumPy

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

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

Aarray

Blist

Cndarray

Dmatrix

Attempts:

3 left

💡 Hint

Common Mistakes

Using np.list instead of np.array

Using np.matrix which creates a different object

Trying to use np.ndarray directly without arguments

The np.array function converts a Python list into a NumPy ndarray.

2fill in blank

medium

Complete the code to find the shape of the NumPy array.

NumPy

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

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

Asize

Bdim

Clength

Dshape

Attempts:

3 left

💡 Hint

Common Mistakes

Using size which returns total elements, not shape

Using length which is not an ndarray attribute

Using dim which is not a valid attribute

The shape attribute shows the dimensions of the array as a tuple.

3fill in blank

hard

Fix the error in the code to correctly create a 2D NumPy array.

NumPy

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

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

A[1, [2, 3, 4]]

B[1, 2, 3, 4]

C[[1, 2], [3, 4]]

D[[1, 2, 3], 4]

Attempts:

3 left

💡 Hint

Common Mistakes

Using uneven nested lists causing ragged arrays

Using a flat list when a 2D array is needed

Mixing data types inside the list

A 2D array requires a list of lists with equal lengths. Option C is correct.

4fill in blank

hard

Fill both blanks to create a 3x3 array of zeros and print its data type.

NumPy

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

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

Azeros

Bones

Cint

Dfloat

Attempts:

3 left

💡 Hint

Common Mistakes

Using np.ones instead of zeros

Using int dtype when float is expected

Forgetting to specify shape as a tuple

np.zeros creates an array of zeros. Setting dtype=float makes elements floats.

5fill in blank

hard

Fill all three blanks to create a dictionary comprehension that maps each word to its length if length is greater than 3.

NumPy

words = ['data', 'science', 'ai', 'ml']
lengths = { [1]: [2] for word in words if [3] }

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

Aword

Blen(word)

Clen(word) > 3

Dword > 3

Attempts:

3 left

💡 Hint

Common Mistakes

Using word > 3 which compares string to number

Using len(word) without comparison in if condition

Swapping key and value positions

The dictionary comprehension uses the word as key, its length as value, and filters words longer than 3 characters.