Find indices of elements equal to zero in a NumPy array

numpy.where() is my favorite.

>>> x = numpy.array([1,0,2,0,3,0,4,5,6,7,8])
>>> numpy.where(x == 0)[0]
array([1, 3, 5])

The method where returns a tuple of ndarrays, each corresponding to a different dimension of the input. Since the input is one-dimensional, the [0] unboxes the tuple's only element.

You can search for any scalar condition with:

>>> a = np.asarray([0,1,2,3,4])
>>> a == 0 # or whatver
array([ True, False, False, False, False], dtype=bool)

Which will give back the array as an boolean mask of the condition.

There is np.argwhere,

import numpy as np
arr = np.array([[1,2,3], [0, 1, 0], [7, 0, 2]])
np.argwhere(arr == 0)

which returns all found indices as rows:

array([[1, 0],    # Indices of the first zero
       [1, 2],    # Indices of the second zero
       [2, 1]],   # Indices of the third zero
      dtype=int64)