How can I find identical rows in different arrays regardless of element order using Numpy?

Question

I was working on a project and stumbled upon this problem. I have two arrays A and B of shape (8,3) and (2,2). How can I find all the rows of A that contain elements of each row of B regardless of the order of the elements in B?

A = np.random.randint(0,5,(8,3))
B = np.random.randint(0,5,(2,2))

Thanks!

You mean the set of rows in A that contain all elements in B? — anon01, Aug 19 '20 at 06:09

score 2 · Accepted Answer · answered Aug 19 '20 at 06:05

2

Here is a one way to do it:

Import numpy as np

A = np.random.randint(0,5,(8,3))
B = np.random.randint(0,5,(2,2))

C = (A[..., np.newaxis, np.newaxis] == B)
rows = np.where(C.any((3,1)).all(1))[0]
print(rows)

Output:

[0 2 3 4]

answered Aug 19 '20 at 06:05

Geom

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Can you please explain a little bit? – Jack.C Aug 19 '20 at 06:11

score 2 · Answer 2 · answered Aug 19 '20 at 06:14

import numpy as np

A = np.random.randint(0, 5, (8, 3))
B = np.random.randint(0, 5, (2, 2))

for BRow in B:
    for ARow in A:
        if all(item in ARow for item in BRow):
            print(f'{BRow} in {ARow}')

This doesn't check for duplicates though, eg it accepts [3, 3] in [1, 2, 3]

How can I find identical rows in different arrays regardless of element order using Numpy?

2 Answers2