How to find the index of an element in an numpy array?

Question

I have an array df in which each element is a list of 2 numbers. Given an element p = [18, 169] . I would like to find the indices of such elements p in df . Given df

[[[13, 169],    [18, 169],  [183, 169]],
 [[-183, 169],  [18, 169],  [183, 169]],
 [[18, 169],    [-18, 169], [183, 169]]]

With (df == p).all(-1) , I get

array([[False,  True, False],
       [False,  True, False],
       [ True, False, False]])

What I want is

[[0, 1],
 [1, 1],
 [2, 0]]

Could you please elaborate on how to do so?

import numpy as np
df = np.array([[[13, 169],   [18, 169], [183, 169]],
               [[-183, 169], [18, 169], [183, 169]],
               [[18, 169],   [-18, 169], [183, 169]]])
p = [18, 169]
ind = (df == p).all(-1)
ind

Answer 1

What you've computed with (df==p).all(-1) is a mask . They have lots of uses, but you can use that directly to compute the value you want.

# True or false at each coordinate
mask = (df==p).all(-1)

# Extract the coordinates where the mask is True
result = np.argwhere(mask)