By default, the key to sort by is the first letter of each string. Or the first item in a sequence if it’s list of sequences. But Python allows you to specify any key that you want, using the key parameter for the sort() function. The key is the name of a function.

The way it works is this: sort runs every item in the list through the function. Whatever the function returns is used to sort, overriding the default of using the first thing.

Example 1

So to sort a list of strings by the second letter instead of the first letter then we simply need a function that returns the second letter of a string. Here’s such a function, and how to use it as a key to sort. Note that key=secondletter, NOT key=secondletter(). We’re specifying the reference to secondletter, not trying to call it.

def secondletter(x):
    return x[1]

mylist = ['orange', 'banana', 'apple']

mylist.sort(key=secondletter)

# ['banana', 'apple', 'orange']

By the way, for simple one-liner functions like this, we could have used the lambda syntax instead of defining the secondletter function:

mylist = ['orange', 'banana', 'apple']
mylist.sort(key=lambda x: x[1])

Example 2

OK, while it’s a good first example, sorting on the second letter isn’t terribly useful. How about sorting a list of people’s names by their last name? We simply need a function to return the last name, and use the name of that function as the sort key.

def lastname(x):
    firstname, lastname = x.split()
    return lastname

presidents = ['Abraham Lincoln', 'George Washington',
              'Benjamin Harrison', 'Millard Fillmore']

presidents.sort(key=lastname)

#['Millard Fillmore',
# 'Benjamin Harrison',
# 'Abraham Lincoln',
# 'George Washington']

Of course, in practice you would have to be careful with this . . . if there’s a middle name in there, then it would break the lastname function. This one works better:

def lastname2(x):
        return x.split()[-1]

not_all_presidents = ['Abraham Lincoln', 'George Washington', 'Benjamin Harrison',
                     'Millard Fillmore', 'Prince', 'Madonna', 'Arthur C. Clarke']

not_all_presidents.sort(key=lastname2)

#['Arthur C. Clarke',
# 'Millard Fillmore',
# 'Benjamin Harrison',
# 'Abraham Lincoln',
# 'Madonna',
# 'Prince',
# 'George Washington']

…but if you have names like ‘King George III’, you’ll have to fix the function to deal with them.

Example 3

How about sorting a list of stocks by their maximum closing price for this week? (Use reverse=True so that highest are listed first)

stocks = [ [56, 94, 13, 90, 91], [33, 76, 22, 34, 105], [25, 28, 29, 30, 35] ]
stocks.sort(key=max, reverse=True)

# [[33, 76, 22, 34, 105], [56, 94, 13, 90, 91], [25, 28, 29, 30, 35]]

Example 4

You can get tricky…knowing that sort() changes the list in-place, sort individual items by stock price, then sort each stock by its max.

def mymax(x):
    x.sort(reverse=True)
    return x[0]

stocks = [ [56, 94, 13, 90, 91], [33, 76, 22, 34, 105], [25, 28, 29, 30, 35] ]
stocks2 = stocks[:] # make a copy, cause we're about to change it

stocks2.sort(key=mymax, reverse=True)

#[[105, 76, 34, 33, 22], [94, 91, 90, 56, 13], [35, 30, 29, 28, 25]]

Example 5

Or the sort a list by absolute value instead of paying attention to negative signs:

deviations = [10, -34, -5, 90, -87]
deviations.sort(key=abs)
# [-5, 10, -34, -87, 90]

As you can see, specifying the sort key can be pretty useful if you know it’s there. Coming up with these examples really helped me see where this technique would be useful. You can find more info on sorting on the Python wiki, and comparisons between Python and Perl sorting.

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]