find index based on data from two numpy arrays

Question

I have huge numpy matrix. Let us say

A['a1'] = [1,2,3,6]
A['a3']= [3,4,3,7]
A['a4']= [4,6,8,7]
B['b2'] = [2,2,2,4]

A['a1']     A['a3']  A['a4']  B['b2']
1              3         4     2
2              4         6     2
3              3         8     2  
6              7         7     4

I want to select the index where B['b2'] has value 2 and A['a3'] has value 3. So that means I need the index 0 and 2.

For single array I can use np.where, but how can I correlate between that between different arrays. I have been using Pandas before and it was quite easy, but unable to find something to achieve it using numpy.

Laurent B. · Accepted Answer · 2021-05-01 06:56:35Z

1

You could use a set object {...} combined with its method intersection

import numpy as np

A, B = {}, {} # Optional : to avoid bug in this chunk of code

A['a1'] = [1,2,3,6]
A['a3']= [3,4,3,7]
A['a4']= [4,6,8,7]
B['b2'] = [2,2,2,4]

n1 = np.where(np.array(A['a3'])==3) # {0, 2}
n2 = np.where(np.array(B['b2'])==2) # {0, 1, 2}

print(set(n1[0]).intersection(n2[0]))
# {0, 2}

edited May 1, 2021 at 6:56

answered Apr 30, 2021 at 22:17

Laurent B.

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1 Comment

saras Over a year ago

Thanks. thats nice. why didn't I think of it before. Thanks once again

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