np.intersect1d() for intersection in NumPy - Interactive Code Practice

Practice - 5 Tasks

1fill in blank

easy

Complete the code to find the common elements between two arrays using numpy.

NumPy

import numpy as np
arr1 = np.array([1, 2, 3, 4])
arr2 = np.array([3, 4, 5, 6])
common = np.[1](arr1, arr2)
print(common)

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Aintersect1d

Bunion1d

Csetdiff1d

Dunique

Attempts:

3 left

💡 Hint

Common Mistakes

Using np.union1d() which returns all unique elements from both arrays.

Using np.setdiff1d() which returns elements in one array but not the other.

The np.intersect1d() function returns the sorted, unique values that are in both input arrays.

2fill in blank

medium

Complete the code to find the intersection of two lists converted to numpy arrays.

NumPy

import numpy as np
list1 = [10, 20, 30, 40]
list2 = [30, 40, 50, 60]
arr1 = np.array(list1)
arr2 = np.array(list2)
result = np.intersect1d(arr1, [1])
print(result)

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Alist2

Barr2

Cnp.array(list2)

Dnp.array(list1)

Attempts:

3 left

💡 Hint

Common Mistakes

Passing a list instead of a numpy array as the second argument.

Passing the first array again instead of the second.

The intersection function requires two numpy arrays as input. Here, arr2 is the second numpy array.

3fill in blank

hard

Fix the error in the code to correctly find the intersection of two arrays.

NumPy

import numpy as np
arr1 = np.array([7, 8, 9])
arr2 = np.array([8, 9, 10])
common = np.intersect1d(arr1, arr2[1])
print(common)

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A, assume_unique=True

B, axis=0

C)

D, return_indices=True

Attempts:

3 left

💡 Hint

Common Mistakes

Adding unnecessary parameters that cause errors.

Forgetting to close the function call with a parenthesis.

The function call was missing the closing parenthesis. Adding ) fixes the syntax error.

4fill in blank

hard

Fill both blanks to create a dictionary with words as keys and their lengths only if length is greater than 3.

NumPy

words = ['data', 'science', 'ai', 'ml']
lengths = {word: [1] for word in words if [2]
print(lengths)

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Alen(word)

Bword

Clen(word) > 3

Dword > 3

Attempts:

3 left

💡 Hint

Common Mistakes

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

Checking if the word string is greater than 3 instead of its length.

The dictionary comprehension uses len(word) as the value and filters words where length is greater than 3.

5fill in blank

hard

Fill all three blanks to create a dictionary with uppercase keys and values only for items with values greater than 0.

NumPy

data = {'a': 1, 'b': -1, 'c': 3}
result = { [1]: [2] for k, v in data.items() if v [3] 0 }
print(result)

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Ak.upper()

Bv

C>

Dk

Attempts:

3 left

💡 Hint

Common Mistakes

Using original keys without uppercase.

Using keys as values or vice versa.

Using wrong comparison operators.

The dictionary comprehension uses uppercase keys with k.upper(), values v, and filters items where value is greater than 0.