np.random.default_rng() modern approach in NumPy - Interactive Code Practice

Practice - 5 Tasks

1fill in blank

easy

Complete the code to create a new random number generator using the modern numpy approach.

NumPy

rng = np.random.[1]()

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

Adefault_rng

Brandint

Crandom

Dseed

Attempts:

3 left

💡 Hint

Common Mistakes

Using older functions like np.random.seed() instead of default_rng()

Trying to call np.random.random() to create a generator

The default_rng() function creates a new random number generator instance in numpy's modern API.

2fill in blank

medium

Complete the code to generate 5 random integers between 1 and 10 using the modern numpy random generator.

NumPy

rng = np.random.default_rng()
random_numbers = rng.integers([1], 11, size=5)

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

A5

B1

C0

D10

Attempts:

3 left

💡 Hint

Common Mistakes

Setting low to 0 which includes 0 in output

Setting high to 10 which excludes 10

The integers(low, high) method generates random integers from low (inclusive) to high (exclusive). To get numbers from 1 to 10, low must be 1 and high 11.

3fill in blank

hard

Fix the error in the code to generate 3 random floats between 0 and 1 using the modern numpy random generator.

NumPy

rng = np.random.default_rng()
random_floats = rng.[1](3)

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Arandom

Brandint

Cintegers

Dchoice

Attempts:

3 left

💡 Hint

Common Mistakes

Using integers() which returns integers

Using randint() which is not a method of the generator instance

The random() method generates random floats in [0, 1). The integers() method generates integers, so it is incorrect here.

4fill in blank

hard

Fill both blanks to create a random number generator with a fixed seed and generate 4 random integers from 0 to 9.

NumPy

rng = np.random.[1](12345)
numbers = rng.[2](0, 10, size=4)

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Adefault_rng

Bintegers

Crandom

Dseed

Attempts:

3 left

💡 Hint

Common Mistakes

Using np.random.seed() which does not return a generator

Using random() instead of integers() for integers

Use default_rng(seed) to create a reproducible generator. Then use integers() to generate random integers.

5fill in blank

hard

Fill all three blanks to create a dictionary of word lengths for words longer than 3 letters using a comprehension and the modern numpy random generator to shuffle the list.

NumPy

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

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

Adefault_rng

Blen(word)

C>

Drandom

Attempts:

3 left

💡 Hint

Common Mistakes

Using random() instead of default_rng()

Using < instead of > in the condition

Using word instead of len(word) for the dictionary values

Create the generator with default_rng(). Use len(word) to get word length. Filter words with length greater than 3 using >.