np.setdiff1d() for difference in NumPy - Interactive Code Practice

Practice - 5 Tasks

1fill in blank

easy

Complete the code to find elements in array1 that are not in array2 using np.setdiff1d().

NumPy

import numpy as np
array1 = np.array([1, 2, 3, 4, 5])
array2 = np.array([3, 4, 6])
difference = np.[1](array1, array2)
print(difference)

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

Aunique

Bunion1d

Cintersect1d

Dsetdiff1d

Attempts:

3 left

💡 Hint

Common Mistakes

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

Using np.intersect1d() which returns common elements.

Using np.unique() which just returns unique elements of one array.

The np.setdiff1d() function returns the sorted, unique values in the first array that are not in the second array.

2fill in blank

medium

Complete the code to find the difference between two arrays and store it in 'diff'.

NumPy

import numpy as np
arr1 = np.array([10, 20, 30, 40])
arr2 = np.array([20, 50])
diff = np.[1](arr1, arr2)
print(diff)

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

Aintersect1d

Bsetdiff1d

Cunion1d

Dsort

Attempts:

3 left

💡 Hint

Common Mistakes

Using np.intersect1d() which returns common elements.

Using np.union1d() which returns all unique elements combined.

np.setdiff1d(arr1, arr2) returns elements in arr1 that are not in arr2.

3fill in blank

hard

Fix the error in the code to correctly find the difference between arrays using np.setdiff1d().

NumPy

import numpy as np
x = np.array([5, 6, 7, 8])
y = np.array([7, 9])
diff = np.setdiff1d(x, [1])
print(diff)

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

Anp.array([7, 9])

B[7, 9]

Cy

Dx

Attempts:

3 left

💡 Hint

Common Mistakes

Passing the first array again as the second argument.

Passing a list literal instead of the array variable.

The second argument to np.setdiff1d() should be the array to compare against, which is y here.

4fill in blank

hard

Fill both blanks to create a dictionary with words as keys and their lengths as values, but only for words longer than 3 characters.

NumPy

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

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

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.

Using the word variable in the condition instead of its length.

The dictionary comprehension uses len(word) for values and filters words with length greater than 3.

5fill in blank

hard

Fill all three blanks to create a dictionary of words and their lengths, but only include words with length greater than 3.

NumPy

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

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

Aw.upper()

Blen(w)

C>

Dw

Attempts:

3 left

💡 Hint

Common Mistakes

Using uppercase words as keys instead of original words.

Using the word variable as value instead of length.

Using wrong comparison operators.

The dictionary keys are the words themselves (w), values are their lengths (len(w)), and the condition filters words longer than 3 characters (> 3).