NumPy and scientific computing ecosystem - 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)

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Aarray

Blist

Cseries

Dmatrix

Attempts:

3 left

💡 Hint

Common Mistakes

Using 'list' instead of 'array' causes an AttributeError.

Using 'matrix' creates a different NumPy object, not a simple array.

The np.array() function converts a Python list into a NumPy array.

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])
mean_value = arr.[1]()
print(mean_value)

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Amode

Baverage

Cmean

Dmedian

Attempts:

3 left

💡 Hint

Common Mistakes

Using 'average' is not a NumPy array method, it causes an AttributeError.

Using 'median' calculates the middle value, not the average.

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

3fill in blank

hard

Fix the error in the code to create a 2D NumPy array with shape (2, 3).

NumPy

import numpy as np
arr = np.array([[1, 2, 3], [4, 5, [1]]])
print(arr.shape)
# Fix the inner list to have equal length by adding [1]

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A0

B6

C3

D7

Attempts:

3 left

💡 Hint

Common Mistakes

Adding a number larger than 3 changes the data meaning.

Leaving the lists uneven causes an array of lists, not a 2D array.

All inner lists must have the same length to form a proper 2D array. Adding 0 to the second list makes it length 3.

4fill in blank

hard

Fill both blanks to create a dictionary comprehension that maps words to their lengths only if length is greater than 3.

NumPy

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

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Alen(word)

Blen(word) > 3

Cword

Dlen(words)

Attempts:

3 left

💡 Hint

Common Mistakes

Using len(words) instead of len(word) causes wrong lengths.

Using word instead of len(word) as the value.

The dictionary comprehension maps each word to its length using len(word). The condition len(word) > 3 filters words longer than 3 characters.

5fill in blank

hard

Fill all three blanks to create a dictionary comprehension that maps uppercase words to their lengths only if length is greater than 2.

NumPy

words = ['cat', 'dog', 'a', 'bird']
result = { [1]: [2] for w in words if [3] }

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Aw.upper()

Blen(w)

Clen(w) > 2

Dw.lower()

Attempts:

3 left

💡 Hint

Common Mistakes

Using w.lower() instead of w.upper() changes the key format.

Using len(w) > 3 excludes words of length 3.

The dictionary comprehension uses w.upper() as keys, len(w) as values, and filters words with length greater than 2.