Why indexing matters in NumPy - Test Your Understanding

Practice - 5 Tasks

1fill in blank

easy

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

NumPy

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

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A[1, 2, 3, 4]

B(1, 2, 3, 4)

C1, 2, 3, 4

D{1, 2, 3, 4}

Attempts:

3 left

💡 Hint

Common Mistakes

Using a tuple or set instead of a list inside np.array()

Forgetting the brackets around the numbers

NumPy arrays are created from lists using np.array(). Lists are enclosed in square brackets.

2fill in blank

medium

Complete the code to access the third element of the NumPy array.

NumPy

import numpy as np
arr = np.array([10, 20, 30, 40, 50])
third_element = arr[[1]]
print(third_element)

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A1

B0

C3

D2

Attempts:

3 left

💡 Hint

Common Mistakes

Using 3 instead of 2 for the third element

Confusing 1-based indexing with 0-based indexing

Indexing in Python starts at 0, so the third element is at index 2.

3fill in blank

hard

Fix the error in the code to correctly slice the first three elements of the array.

NumPy

import numpy as np
arr = np.array([5, 10, 15, 20, 25])
slice_arr = arr[[1]]
print(slice_arr)

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A[0:3]

B0,3

C0:3

D(0:3)

Attempts:

3 left

💡 Hint

Common Mistakes

Using commas instead of colon for slicing

Adding extra brackets around the slice

Slicing uses the colon : inside square brackets without extra brackets or commas.

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 = ['cat', 'elephant', 'dog', 'horse']
lengths = { [1] : [2] for word in words if len(word) > 3 }
print(lengths)

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Aword

Blen(word)

Cword.upper()

Dword.lower()

Attempts:

3 left

💡 Hint

Common Mistakes

Using the length as the key and the word as the value

Using transformations like upper or lower instead of the original word

The dictionary comprehension uses the word as the key and its length as the value.

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

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Aword.upper()

Blen(word)

C>

D<

Attempts:

3 left

💡 Hint

Common Mistakes

Using lowercase or original words as keys

Using wrong comparison operators in the condition

The dictionary keys are uppercase words, values are their lengths, and the condition filters words longer than 3 characters.