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Here are a couple of ways of sorting one list by another list in Python. The first uses plain ol’ Python, and the others use NumPy.

In each case imagine we want to sort a list of peoples names by their ages.

Method 1

Zip the lists together, making sure that the one to sort by is passed first to zip(). The result is a list of tuples. When you sort a list of tuples, it sorts using the first item in each tuple. Then use the zip* trick to unzip the now sorted tuples into separate variables.

people = ['Jim', 'Pam', 'Micheal', 'Dwight']
ages = [27, 25, 4, 9]

agesAndPeople = zip(ages, people)
agesAndPeople.sort()
sortedAges, sortedPeople = zip(*agesAndPeople)

Note that if you want to sort in reverse, you can use agesAndPeople.sort(reverse=True).

Method 2

This method uses NumPy, and you don’t have to convert the lists into arrays. The argsort() function doesn’t return the sorted ages . . . instead, it returns the indices that each item would if it were in an already sorted array (try it to see what I mean). take() is a way of using useful NumPy indexing on a list. See the next example for something that might be more straigtforward for Matlab users.

people = ['Jim', 'Pam', 'Micheal', 'Dwight']
ages = [27, 25, 4, 9]

import numpy
inds = numpy.argsort(ages)
sortedPeople = numpy.take(people, inds)

Method 3

This method also uses NumPy, but first it converts the lists into arrays. Then it uses the argsort() of one to index into the other.

people = ['Jim', 'Pam', 'Micheal', 'Dwight']
ages = [27, 25, 4, 9]

import numpy
people = numpy.array(people)
ages = numpy.array(ages)
inds = ages.argsort()
sortedPeople = people[inds]

Tags: argsort, NumPy, sort, sorting

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