Why NumPy performance matters - Test Your Understanding

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, 5])

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

Amatrix

Bseries

Clist

Darray

Attempts:

3 left

💡 Hint

Common Mistakes

Using 'list' instead of 'array' which is not a NumPy function.

Using 'matrix' which is a different NumPy type.

Using 'series' which belongs to pandas, not NumPy.

The np.array function converts a Python list into a NumPy array, which allows fast numerical operations.

2fill in blank

medium

Complete the code to calculate the mean of a NumPy array.

NumPy

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

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Amean

Bsum

Cmedian

Dmax

Attempts:

3 left

💡 Hint

Common Mistakes

Using 'sum' which adds all elements but does not average.

Using 'median' which finds the middle value, not the average.

Using 'max' which finds the largest value.

The mean() method calculates the average value of the elements in the array.

3fill in blank

hard

Fix the error in the code to multiply two NumPy arrays element-wise.

NumPy

import numpy as np
arr1 = np.array([1, 2, 3])
arr2 = np.array([4, 5, 6])
result = arr1 [1] arr2

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A-

B+

C*

D/

Attempts:

3 left

💡 Hint

Common Mistakes

Using '+' which adds elements instead of multiplying.

Using '-' which subtracts elements.

Using '/' which divides elements.

The * operator performs element-wise multiplication between two NumPy arrays.

4fill in blank

hard

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

NumPy

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

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Alen(word)

B>

C<

Dword

Attempts:

3 left

💡 Hint

Common Mistakes

Using '<' instead of '>' which selects shorter words.

Using 'word' as value instead of length.

Not filtering words by length.

The dictionary comprehension uses len(word) to get the length and filters 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 letters.

NumPy

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

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Aword.upper()

Blen(word)

C>

Dword

Attempts:

3 left

💡 Hint

Common Mistakes

Using 'word' instead of 'word.upper()' for keys.

Using '<' instead of '>' in the condition.

Using 'word' instead of 'len(word)' for values.

The dictionary comprehension uses word.upper() as keys, len(word) as values, and filters words with length greater than (>) 3.