Normal distribution with normal() in NumPy - Interactive Code Practice

Practice - 5 Tasks

1fill in blank

easy

Complete the code to generate 5 random numbers from a normal distribution with mean 0 and standard deviation 1.

NumPy

import numpy as np
samples = np.random.normal(loc=0, scale=[1], size=5)
print(samples)

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

A10

B0

C1

D5

Attempts:

3 left

💡 Hint

Common Mistakes

Using 0 for scale which results in all zeros.

Confusing mean (loc) with standard deviation (scale).

The scale parameter sets the standard deviation. For a standard normal distribution, it is 1.

2fill in blank

medium

Complete the code to generate 10 random numbers from a normal distribution with mean 5 and standard deviation 2.

NumPy

import numpy as np
samples = np.random.normal(loc=[1], scale=2, size=10)
print(samples)

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A5

B0

C2

D10

Attempts:

3 left

💡 Hint

Common Mistakes

Using scale instead of loc for the mean.

Setting mean to 0 instead of 5.

The loc parameter sets the mean. Here, the mean is 5.

3fill in blank

hard

Fix the error in the code to generate 3 random numbers from a normal distribution with mean 0 and standard deviation 1.

NumPy

import numpy as np
samples = np.random.normal(loc=0, scale=1, size=[1])
print(samples)

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

A3

B1

C0

D5

Attempts:

3 left

💡 Hint

Common Mistakes

Passing size as a string instead of an integer.

Using scale 0 which results in no variation.

The size parameter must be an integer, not a string. Use 3.

4fill in blank

hard

Fill both blanks to create a dictionary with words as keys and their lengths as values, but only include words longer than 4 characters.

NumPy

words = ['apple', 'bat', 'carrot', 'dog', 'elephant']
lengths = {word: [1] for word in words if len(word) [2] 4}
print(lengths)

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Alen(word)

Bword

C>

D<

Attempts:

3 left

💡 Hint

Common Mistakes

Using the word itself as the value instead of its length.

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

We want the length of each word as the value, so use len(word). To include words longer than 4 characters, use the condition len(word) > 4.

5fill in blank

hard

Fill all three blanks to create a dictionary with uppercase words as keys and their lengths as values, including only words longer than 3 characters.

NumPy

words = ['sun', 'moon', 'star', 'sky', 'planet']
result = { [1]: [2] for word in words if len(word) [3] 3 }
print(result)

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Aword.upper()

Blen(word)

C>

Dword

Attempts:

3 left

💡 Hint

Common Mistakes

Using the original word as key instead of uppercase.

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

Using word instead of length for values.

The keys should be uppercase words using word.upper(). The values are the lengths using len(word). The condition includes words longer than 3 characters using >.