How can I “zip sort” parallel numpy arrays?

Question

If I have two parallel lists and want to sort them by the order of the elements in the first, it\'s very easy:

>>> a = [2, 3, 1]
>>> b = [4         


        

Answer 1

This might the simplest and most general way to do what you want. (I used three arrays here, but this will work on arrays of any shape, whether two columns or two hundred).

import numpy as NP
fnx = lambda : NP.random.randint(0, 10, 6)
a, b, c = fnx(), fnx(), fnx()
abc = NP.column_stack((a, b, c))
keys = (abc[:,0], abc[:,1])          # sort on 2nd column, resolve ties using 1st col
indices = NP.lexsort(keys)        # create index array
ab_sorted = NP.take(abc, indices, axis=0)

One quirk w/ lexsort is that you have to specify the keys in reverse order, i.e., put your primary key second and your secondary key first. In my example, i want to sort using the 2nd column as the primary key so i list it second; the 1st column resolves ties only, but it is listed first).