Why array processing matters in NumPy - 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

numbers = [1, 2, 3, 4, 5]
array = np.[1](numbers)
print(array)

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

Aarray

Blist

Carrayify

Dtoarray

Attempts:

3 left

💡 Hint

Common Mistakes

Using np.list() instead of np.array()

Trying to use np.arrayify() which does not exist

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 add 5 to every element in the NumPy array.

NumPy

import numpy as np

arr = np.array([10, 20, 30])
result = arr [1] 5
print(result)

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A-

B/

C+

D*

Attempts:

3 left

💡 Hint

Common Mistakes

Using * which multiplies instead of adds

Using / which divides instead of adds

Adding 5 to a NumPy array adds 5 to each element because NumPy supports element-wise operations.

3fill in blank

hard

Fix the error in the code to compute the mean of the array elements.

NumPy

import numpy as np

arr = np.array([2, 4, 6, 8])
mean_value = arr.[1]()
print(mean_value)

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Amean

Bavg

Cmedian

Daverage

Attempts:

3 left

💡 Hint

Common Mistakes

Using arr.average() which is not a NumPy method

Using arr.avg() which does not exist

The correct NumPy method to compute the average value is mean().

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 = ['cat', 'elephant', 'dog', 'giraffe']
lengths = {word: [1] for word in words if [2]
print(lengths)

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Alen(word)

Bword > 3

Clen(word) > 3

Dword

Attempts:

3 left

💡 Hint

Common Mistakes

Using 'word > 3' which compares string to number

Using 'word' instead of length in the dictionary values

Use len(word) to get the length and filter words with length greater than 3 using len(word) > 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 4 letters.

NumPy

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

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Aw.upper()

Blen(w)

Clen(w) > 4

Dw.lower()

Attempts:

3 left

💡 Hint

Common Mistakes

Using w.lower() instead of w.upper() for keys

Not filtering words by length

Using w instead of len(w) for values

The keys are uppercase words using w.upper(), values are lengths with len(w), and filter words longer than 4 with len(w) > 4.