Aggregation along specific axes in NumPy - Interactive Code Practice

Practice - 5 Tasks

1fill in blank

easy

Complete the code to calculate the sum of all elements in the array.

NumPy

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

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

Amax

Bmean

Csum

Dmin

Attempts:

3 left

💡 Hint

Common Mistakes

Using mean() instead of sum()

Using max() or min() which find extremes, not totals

The sum() function adds all elements in the array.

2fill in blank

medium

Complete the code to calculate the mean of the array elements along axis 0 (columns).

NumPy

import numpy as np
arr = np.array([[1, 2], [3, 4]])
col_mean = arr.[1](axis=0)

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

Asum

Bmean

Cmax

Dmin

Attempts:

3 left

💡 Hint

Common Mistakes

Using axis=1 which averages rows instead of columns

Using sum() instead of mean()

The mean(axis=0) calculates the average of each column.

3fill in blank

hard

Fix the error in the code to find the maximum value along axis 1 (rows).

NumPy

import numpy as np
arr = np.array([[5, 7, 2], [3, 8, 1]])
max_per_row = arr.[1](axis=1)

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

Amax

Bmin

Cmean

Dsum

Attempts:

3 left

💡 Hint

Common Mistakes

Using min() which finds smallest values

Using mean() or sum() which calculate averages or totals

The max(axis=1) function finds the largest value in each row.

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 characters.

NumPy

words = ['cat', 'elephant', 'dog', 'giraffe']
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 > in the condition

Using word instead of len(word) for the value

We use len(word) to get the length and filter words with length greater than 3 using >.

5fill in blank

hard

Fill all three blanks to create a dictionary with uppercase words as keys and their lengths as values, but only for words longer than 4 characters.

NumPy

words = ['apple', 'bat', 'carrot', 'dog']
result = { [1]: [2] for w in words if len(w) [3] 4 }

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Aw.upper()

Blen(w)

C>

Dw

Attempts:

3 left

💡 Hint

Common Mistakes

Using w instead of w.upper() for keys

Using < instead of > in the condition

Using w instead of len(w) for values

We convert words to uppercase for keys using w.upper(), get lengths with len(w), and filter words longer than 4 with >.