The Python Oracle

Sorting a Python list by two fields

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Chapters
00:00 Question
00:29 Accepted answer (Score 181)
00:42 Answer 2 (Score 444)
01:05 Answer 3 (Score 28)
04:34 Answer 4 (Score 19)
04:44 Thank you

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Full question
https://stackoverflow.com/questions/5212...

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https://meta.stackexchange.com/help/lice...

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Tags
#python #sorting

#avk47



ANSWER 1

Score 470


No need to import anything when using lambda functions.
The following sorts list by the first element, then by the second element. You can also sort by one field ascending and another descending for example:

sorted_list = sorted(list, key=lambda x: (x[0], -x[1]))



ACCEPTED ANSWER

Score 183


like this:

import operator
list1 = sorted(csv1, key=operator.itemgetter(1, 2))



ANSWER 3

Score 31


Python has a stable sort, so provided that performance isn't an issue the simplest way is to sort it by field 2 and then sort it again by field 1.

That will give you the result you want, the only catch is that if it is a big list (or you want to sort it often) calling sort twice might be an unacceptable overhead.

list1 = sorted(csv1, key=operator.itemgetter(2))
list1 = sorted(list1, key=operator.itemgetter(1))

Doing it this way also makes it easy to handle the situation where you want some of the columns reverse sorted, just include the 'reverse=True' parameter when necessary.

Otherwise you can pass multiple parameters to itemgetter or manually build a tuple. That is probably going to be faster, but has the problem that it doesn't generalise well if some of the columns want to be reverse sorted (numeric columns can still be reversed by negating them but that stops the sort being stable).

So if you don't need any columns reverse sorted, go for multiple arguments to itemgetter, if you might, and the columns aren't numeric or you want to keep the sort stable go for multiple consecutive sorts.

Edit: For the commenters who have problems understanding how this answers the original question, here is an example that shows exactly how the stable nature of the sorting ensures we can do separate sorts on each key and end up with data sorted on multiple criteria:

DATA = [
    ('Jones', 'Jane', 58),
    ('Smith', 'Anne', 30),
    ('Jones', 'Fred', 30),
    ('Smith', 'John', 60),
    ('Smith', 'Fred', 30),
    ('Jones', 'Anne', 30),
    ('Smith', 'Jane', 58),
    ('Smith', 'Twin2', 3),
    ('Jones', 'John', 60),
    ('Smith', 'Twin1', 3),
    ('Jones', 'Twin1', 3),
    ('Jones', 'Twin2', 3)
]

# Sort by Surname, Age DESCENDING, Firstname
print("Initial data in random order")
for d in DATA:
    print("{:10s} {:10s} {}".format(*d))

print('''
First we sort by first name, after this pass all
Twin1 come before Twin2 and Anne comes before Fred''')
DATA.sort(key=lambda row: row[1])

for d in DATA:
    print("{:10s} {:10s} {}".format(*d))

print('''
Second pass: sort by age in descending order.
Note that after this pass rows are sorted by age but
Twin1/Twin2 and Anne/Fred pairs are still in correct
firstname order.''')
DATA.sort(key=lambda row: row[2], reverse=True)
for d in DATA:
    print("{:10s} {:10s} {}".format(*d))

print('''
Final pass sorts the Jones from the Smiths.
Within each family members are sorted by age but equal
age members are sorted by first name.
''')
DATA.sort(key=lambda row: row[0])
for d in DATA:
    print("{:10s} {:10s} {}".format(*d))

This is a runnable example, but to save people running it the output is:

Initial data in random order
Jones      Jane       58
Smith      Anne       30
Jones      Fred       30
Smith      John       60
Smith      Fred       30
Jones      Anne       30
Smith      Jane       58
Smith      Twin2      3
Jones      John       60
Smith      Twin1      3
Jones      Twin1      3
Jones      Twin2      3

First we sort by first name, after this pass all
Twin1 come before Twin2 and Anne comes before Fred
Smith      Anne       30
Jones      Anne       30
Jones      Fred       30
Smith      Fred       30
Jones      Jane       58
Smith      Jane       58
Smith      John       60
Jones      John       60
Smith      Twin1      3
Jones      Twin1      3
Smith      Twin2      3
Jones      Twin2      3

Second pass: sort by age in descending order.
Note that after this pass rows are sorted by age but
Twin1/Twin2 and Anne/Fred pairs are still in correct
firstname order.
Smith      John       60
Jones      John       60
Jones      Jane       58
Smith      Jane       58
Smith      Anne       30
Jones      Anne       30
Jones      Fred       30
Smith      Fred       30
Smith      Twin1      3
Jones      Twin1      3
Smith      Twin2      3
Jones      Twin2      3

Final pass sorts the Jones from the Smiths.
Within each family members are sorted by age but equal
age members are sorted by first name.

Jones      John       60
Jones      Jane       58
Jones      Anne       30
Jones      Fred       30
Jones      Twin1      3
Jones      Twin2      3
Smith      John       60
Smith      Jane       58
Smith      Anne       30
Smith      Fred       30
Smith      Twin1      3
Smith      Twin2      3

Note in particular how in the second step the reverse=True parameter keeps the firstnames in order whereas simply sorting then reversing the list would lose the desired order for the third sort key.




ANSWER 4

Score 22


list1 = sorted(csv1, key=lambda x: (x[1], x[2]) )