Find the row indexes of several values in a numpy array

Question

I have an array X:

X = np.array([[4,  2],
              [9,  3],
              [8,  5],
              [3,  3],
              [5,  6]])

And

Answer 1

The numpy_indexed package (disclaimer: I am its author) contains functionality for performing such operations efficiently (also uses searchsorted under the hood). In terms of functionality, it acts as a vectorized equivalent of list.index:

import numpy_indexed as npi
result = npi.indices(X, searched_values)

Note that using the 'missing' kwarg, you have full control over behavior of missing items, and it works for nd-arrays (fi; stacks of images) as well.

Update: using the same shapes as @Rik X=[520000,28,28] and searched_values=[20000,28,28], it runs in 0.8064 secs, using missing=-1 to detect and denote entries not present in X.