Find matching rows in 2 dimensional numpy array

Question

I would like to get the index of a 2 dimensional Numpy array that matches a row. For example, my array is this:

vals = np.array([[0, 0],
                 [1         


        

Answer 1

In [5]: np.where((vals[:,0] == 0) & (vals[:,1]==1))[0]
Out[5]: array([ 3, 15])

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I'm not sure why, but this is significantly faster than
np.where((vals == (0, 1)).all(axis=1)):

In [34]: vals2 = np.tile(vals, (1000,1))

In [35]: %timeit np.where((vals2 == (0, 1)).all(axis=1))[0]
1000 loops, best of 3: 808 µs per loop

In [36]: %timeit np.where((vals2[:,0] == 0) & (vals2[:,1]==1))[0]
10000 loops, best of 3: 152 µs per loop