Search for duplicated rows in two numpy arrays with different length (Python)
Question:
I have two numpy arrays with different length.
array([['A', 'B'],
['C', 'D'],
['E', 'F']])
array([['B', 'A'],
['C', 'E']])
What I want is to see is if they have common rows, BUT not consider the order. So in the above two arrays, ‘A’ ‘B’ and ‘B’ ‘A’ are duplicates.
Answers:
A possible solution, where a1 and a2 are the first and second arrays, respectively:
a1[np.isin(a1, a2).all(axis=1)]
Output:
array([['A', 'B']], dtype='<U1')
I have two numpy arrays with different length.
array([['A', 'B'],
['C', 'D'],
['E', 'F']])
array([['B', 'A'],
['C', 'E']])
What I want is to see is if they have common rows, BUT not consider the order. So in the above two arrays, ‘A’ ‘B’ and ‘B’ ‘A’ are duplicates.
A possible solution, where a1 and a2 are the first and second arrays, respectively:
a1[np.isin(a1, a2).all(axis=1)]
Output:
array([['A', 'B']], dtype='<U1')