numpy convert categorical string arrays to an integer array

Question

I'm trying to convert a string array of categorical variables to an integer array of categorical variables.

Ex.

import numpy as np a = np.array( ['a', 'b', 'c', 'a', 'b', 'c']) print a.dtype >>> |S1  b = np.unique(a) print b >>>  ['a' 'b' 'c']  c = a.desired_function(b) print c, c.dtype >>> [1,2,3,1,2,3] int32 

I realize this can be done with a loop but I imagine there is an easier way. Thanks.

Answer 1

np.unique has some optional returns

return_inverse gives the integer encoding, which I use very often

>>> b, c = np.unique(a, return_inverse=True) >>> b array(['a', 'b', 'c'],        dtype='|S1') >>> c array([0, 1, 2, 0, 1, 2]) >>> c+1 array([1, 2, 3, 1, 2, 3]) 

it can be used to recreate the original array from uniques

>>> b[c] array(['a', 'b', 'c', 'a', 'b', 'c'],        dtype='|S1') >>> (b[c] == a).all() True