Question

One can use numpy‘s extract function to match an element in an array. The following code matches an element 'a.' exactly in an array. Suppose I want
to match all elements containing '.', how would I do that? Note that in this case, there would be two matches. I’d also like to get the row and column number of the matches. The method doesn’t have to use extract; any method will do. Thanks.

In [110]: x = np.array([['a.','cd'],['ef','g.']])

In [111]: 'a.' == x
Out[111]: 
array([[ True, False],
       [False, False]], dtype=bool)

In [112]: np.extract('a.' == x, x)
Out[112]: 
array(['a.'], 
      dtype='|S2')

Answer 1

You can use the string operations:

>>> import numpy as np
>>> x = np.array([['a.','cd'],['ef','g.']])
>>> x[np.char.find(x, '.') > -1]
array(['a.', 'g.'], 
      dtype='|S2')

EDIT: As per request in the comments… If you want to find out the indexes of where the target condition is true, use numpy.where:

>>> np.where(np.char.find(x, '.') > -1)
(array([0, 1]), array([0, 1]))

or

>>> zip(*np.where(np.char.find(x, '.') > -1))
[(0, 0), (1, 1)]