np.std() and np.var() for spread in NumPy - Interactive Code Practice

Practice - 5 Tasks

1fill in blank

easy

Complete the code to calculate the standard deviation of the array.

NumPy

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

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

Amean

Bstd

Cvar

Dsum

Attempts:

3 left

💡 Hint

Common Mistakes

Using np.mean() instead of np.std()

Using np.var() which calculates variance, not standard deviation

The np.std() function calculates the standard deviation, which measures how spread out the numbers are.

2fill in blank

medium

Complete the code to calculate the variance of the array.

NumPy

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

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

Avar

Bstd

Cmean

Dmedian

Attempts:

3 left

💡 Hint

Common Mistakes

Using np.std() instead of np.var()

Using np.mean() which calculates the average, not variance

The np.var() function calculates the variance, which is the average of the squared differences from the mean.

3fill in blank

hard

Fix the error in the code to correctly calculate the standard deviation.

NumPy

import numpy as np
values = [2, 4, 6, 8]
result = np.std([1])
print(result)

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Avalues.tolist()

Bvalues

Clist(values)

Dnp.array(values)

Attempts:

3 left

💡 Hint

Common Mistakes

Passing a plain Python list directly without conversion

Using list() or tolist() which do not convert to NumPy array

NumPy functions work best with NumPy arrays. Converting the list to an array ensures correct calculation.

4fill in blank

hard

Fill both blanks to create a dictionary of word lengths for words longer than 3 characters.

NumPy

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

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Alen(word)

B>

C<

Dword

Attempts:

3 left

💡 Hint

Common Mistakes

Using the word itself instead of its length

Using less than < instead of greater than > for filtering

The dictionary comprehension uses len(word) to get the length and filters words with length greater than 3 using >.

5fill in blank

hard

Fill all three blanks to create a dictionary of uppercase words and their lengths for words longer than 4 characters.

NumPy

words = ['tree', 'house', 'river', 'sky', 'mountain']
result = { [1]: [2] for word in words if len(word) [3] 4 }
print(result)

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Aword.upper()

Blen(word)

C>

Dword

Attempts:

3 left

💡 Hint

Common Mistakes

Using the original word instead of uppercase

Using less than < instead of greater than > for filtering

Using the word itself as value instead of length

The dictionary comprehension uses the uppercase word as the key (word.upper()), the length as the value (len(word)), and filters words longer than 4 characters (>).