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I have two lists with the same number of elements, all of them strings. These strings are the same set but in a different order in each list with no duplicates.

list_a = ['s1', 's2', 's3', 's4', 's5', ...] list_b = ['s8', 's5', 's1', 's9', 's3', ...]

I need to go through each element in list_a and find the index in list_b that contains that same element. I can do this with two nested for loops but there has to be a better/more efficient way:

b_indexes = [] for elem_a in list_a: for indx_b, elem_b in enumerate(list_b): if elem_b == elem_a: b_indexes.append(indx_b) break
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  • Are there duplicates? Commented Oct 7, 2013 at 11:38
  • No duplicates, sorry. Commented Oct 7, 2013 at 11:39

4 Answers 4

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If there are no duplicates, you can just use list.index():

list_a = ['s1', 's2', 's3', 's4', 's5'] list_b = ['s8', 's5', 's1', 's9', 's3'] print [list_b.index(i) for i in list_a]

You only need to use one for loop, because you've said that the strings in list_a also appear in list_b, so there's no need to go if elem_b == elem_a: and iterate through the second list.

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3

In functional style:

map(list_b.index, list_a)

A list will be produced containing the index in list_b of each element in list_a.

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Now I don't know which one to choose. Is this way recommended over Haidro's way?
@Gabriel Either is fine. It's the exact same thing. map() is probably a little bit faster, but a list comprehension is more readable and you can use conditionals and stuff (well, you can with map() by adding a custom function, but then it just goes a bit untidy)
@Gabriel Oh, and if you're using Python 3, map() will return a generator, while a list comprehension will return a list (although changing the [] to a () will make it a generator expression :)
@Haidro: I thought it was too controversial to say it in my answer, but I personally find map more readable than the list comprehension--mostly because each person thinks of their own special name for the value in the LC, and because the LC might have the extra conditionals you speak of--with map, you can see in the first three characters that there is no funny business going on. :)
@Haidro Actually, list comprehensions are a bit faster than maps.
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This should give you a list of the indexes.

[list_b.index(elem) for elem in list_a]
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An alternative approach to the index method is to build a dictionary of the locations in one pass instead of searching through the list each time. If the list is long enough, this should be faster, because it makes the process linear in the number of elements (on average) instead of quadratic. To be specific, instead of

def index_method(la, lb): return [lb.index(i) for i in la]

you could use

def dict_method(la, lb): where = {v: i for i,v in enumerate(lb)} return [where[i] for i in la]

This should be roughly comparable on small lists, albeit maybe a little slower:

>>> list_a = ['s{}'.format(i) for i in range(5)] >>> list_b = list_a[:] >>> random.shuffle(list_b) >>> %timeit index_method(list_a, list_b) 1000000 loops, best of 3: 1.86 µs per loop >>> %timeit dict_method(list_a, list_b) 1000000 loops, best of 3: 1.93 µs per loop

But it should be much faster on longer ones, and the difference will only grow:

>>> list_a = ['s{}'.format(i) for i in range(100)] >>> list_b = list_a[:] >>> random.shuffle(list_b) >>> %timeit index_method(list_a, list_b) 10000 loops, best of 3: 140 µs per loop >>> %timeit dict_method(list_a, list_b) 10000 loops, best of 3: 20.9 µs per loop
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