Slicing with start:stop:step in NumPy - Interactive Code Practice

Practice - 5 Tasks

1fill in blank

easy

Complete the code to slice the array from index 1 to 5 (exclusive).

NumPy

import numpy as np
arr = np.array([10, 20, 30, 40, 50])
sliced = arr[[1]:5]
print(sliced)

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

A4

B0

C2

D1

Attempts:

3 left

💡 Hint

Common Mistakes

Using 0 as start index which includes the first element.

Using 5 as start index which is out of range.

The slice 1:5 selects elements starting at index 1 up to but not including index 5.

2fill in blank

medium

Complete the code to slice the array to get every second element from the start to the end.

NumPy

import numpy as np
arr = np.array([5, 10, 15, 20, 25, 30])
sliced = arr[[1]]
print(sliced)

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

A0:5:2

B1:6:2

C0:6:2

D1:5:2

Attempts:

3 left

💡 Hint

Common Mistakes

Starting at 1 which skips the first element.

Using stop index less than array length causing missing last elements.

The slice 0:6:2 starts at index 0, goes up to index 6 (exclusive), stepping by 2, selecting every second element.

3fill in blank

hard

Fix the error in the code to correctly slice the array backwards with step -1.

NumPy

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

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A1::-1

B::-1

C5::-1

D-1::-1

Attempts:

3 left

💡 Hint

Common Mistakes

Using invalid start or stop indices that cause empty slices.

Using positive step with negative indices.

The slice ::-1 reverses the array by stepping backwards through all elements.

4fill in blank

hard

Fill both blanks to slice the array from index 2 to 8 (exclusive) with step 3.

NumPy

import numpy as np
arr = np.arange(10)
sliced = arr[[1]:[2]:3]
print(sliced)

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A2

B7

C8

D9

Attempts:

3 left

💡 Hint

Common Mistakes

Using stop index 7 which excludes index 7 element.

Using step other than 3.

The slice 2:8:3 starts at index 2, stops before index 8, stepping by 3.

5fill in blank

hard

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

NumPy

words = ['apple', 'bat', 'carrot', 'dog', 'elephant']
lengths = { [1]: [2] for word in words if len(word) [3] 3 }
print(lengths)

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Aword

Blen(word)

C>

D{word

Attempts:

3 left

💡 Hint

Common Mistakes

Using square brackets instead of curly braces.

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

Not including the condition to filter words.

The dictionary comprehension syntax is {key: value for item in iterable if condition}. Here, keys are words, values are their lengths, and condition filters words longer than 3 letters.