Find indices of rows of numpy 2d array in another 2D array

Question

I am a newbie in numpy. I have 2 2d arrays. I would like to find indices of arr2 in arr1. Please advice me.

    arr1 = [[1, 2, 3],
            [4, 5, 6],
            [7, 8, 9],
            [4, 5, 6],
            [1, 2, 3]]

    arr2 = [[1, 2, 3],
            [4, 5, 6],
            [7, 8, 9]]
    
    desired_output = [0, 1, 2, 1, 0]

Answer 1

One way to achieve this.

If any row of arr1 were not found in arr2, then at that location in pos will have value -1 for simplicity.

This heavily uses numpy broadcasting and indexing. Feel free to ask for further clarifications.

Original example:

import numpy as np
arr1 = np.array([[1, 2, 3],
                 [4, 5, 6],
                 [7, 8, 9],
                 [4, 5, 6],
                 [1, 2, 3]])
arr2 = np.array([[1, 2, 3],
                 [4, 5, 6],
                 [7, 8, 9]])

inds = arr1 == arr2[:, None]
row_sums = inds.sum(axis = 2)
i, j = np.where(row_sums == 3) # Check which rows match in all 3 columns

pos = np.ones(arr1.shape[0], dtype = 'int64') * -1
pos[j] = i
pos

array([0, 1, 2, 1, 0])

Example 2:

import numpy as np
arr1 = np.array([[1, 2, 4],
                 [4, 5, 6],
                 [7, 8, 9],
                 [4, 1, 6],
                 [1, 2, 3]])
arr2 = np.array([[1, 2, 3],
                 [4, 5, 6],
                 [7, 8, 9]])

inds = arr1 == arr2[:, None]
row_sums = inds.sum(axis = 2)
i, j = np.where(row_sums == 3)

pos = np.ones(arr1.shape[0], dtype = 'int64') * -1
pos[j] = i
pos

array([-1,  1,  2, -1,  0])

If you have more number of columns just change the line i, j = np.where(row_sums == 3) to i, j = np.where(row_sums == arr1.shape[1]).