[FIXED] Numpy use one array as mask for another array

Issue

I am trying to do these steps in NumPy. It was easy to do this with python list sort(), and argsort().

How do I do this in Numpy?

a = np.array([10,30,20,40,50])

a_sorted = np.array([10,20,30,40,50])

Get mask of a_sorted

b = np.array(['one','three','two','four','five'])

Apply the mask to b

Expected array sorted according to a_sorted:

b_sorted = np.array(['one','two','three','four','five'])

Solution

Try like this

import numpy as np

a = np.array([10, 30, 20, 40, 50])
a_sorted_indices = np.argsort(a)
a_sorted = a[a_sorted_indices]

b = np.array(['one', 'three', 'two', 'four', 'five'])

b_sorted = b[a_sorted_indices]

print("Sorted array 'a':", a_sorted)
print("Sorted array 'b':", b_sorted)

Output:

Sorted array 'a': [10 20 30 40 50]
Sorted array 'b': ['one' 'two' 'three' 'four' 'five']

Answered By - Mahboob Nur