Random choice from array in NumPy - Interactive Code Practice

Practice - 5 Tasks

1fill in blank

easy

Complete the code to select a random element from the array using NumPy.

NumPy

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

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

Ashuffle

Bchoice

Crandint

Drandom

Attempts:

3 left

💡 Hint

Common Mistakes

Using np.random.randint which returns a random integer, not an element from the array.

Using np.random.shuffle which shuffles the array instead of selecting one element.

The np.random.choice() function picks a random element from the array.

2fill in blank

medium

Complete the code to select 3 random elements from the array with replacement.

NumPy

import numpy as np
arr = np.array([5, 10, 15, 20, 25])
sample = np.random.choice(arr, size=[1], replace=True)
print(sample)

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A1

B5

C3

D10

Attempts:

3 left

💡 Hint

Common Mistakes

Setting size to 1 or 5 which does not match the requirement.

Forgetting to set replace=True when sampling with replacement.

The size parameter controls how many elements to pick. Here, 3 elements are selected.

3fill in blank

hard

Fix the error in the code to select 2 unique random elements from the array.

NumPy

import numpy as np
arr = np.array([1, 2, 3, 4, 5])
sample = np.random.choice(arr, size=[1], replace=False)
print(sample)

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A2

B3

C4

D1

Attempts:

3 left

💡 Hint

Common Mistakes

Using replace=True which allows duplicates.

Setting size to 1 or more than 2 which does not match the requirement.

To select 2 unique elements, replace must be False. The size is 2.

4fill in blank

hard

Fill both blanks to create a dictionary with elements as keys and their squares as values for elements greater than 3.

NumPy

import numpy as np
arr = np.array([1, 2, 3, 4, 5])
squares = {x: x[1]2 for x in arr if x [2] 3}
print(squares)

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A**

B%

C>

D<

Attempts:

3 left

💡 Hint

Common Mistakes

Using % instead of ** for power.

Using < instead of > for filtering.

The operator ** is used for power, and > filters elements greater than 3.

5fill in blank

hard

Fill all three blanks to create a dictionary with uppercase keys and values greater than 10.

NumPy

data = {'a': 5, 'b': 15, 'c': 20}
result = [1]: [2] for [3], [2] in data.items() if [2] > 10
print(result)

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Ak.upper()

Bv

Ck

Ditem

Attempts:

3 left

💡 Hint

Common Mistakes

Using item as loop variable instead of k.

Not converting keys to uppercase.

Using wrong variable names for keys or values.

Keys are converted to uppercase with k.upper(). Values are v. Loop variable is k.