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How to extract the n-th elements from a list of tuples

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How do you access each element in a list of tuples?

In the majority of programming languages when you need to access a nested data type (such as arrays, lists, or tuples), you append the brackets to get to the innermost item. The first bracket gives you the location of the tuple in your list. The second bracket gives you the location of the item in the tuple.

How do you find the nth element of a list in Python?

To get every nth element in a list, a solution is to do mylist[::n].

How do I get the second item in my tuple?

If you need to get the second element from a list of tuples, use a list comprehension. Copied! We used a list comprehension to get a new list that contains the second element of each tuple. List comprehensions are used to perform some operation for every element, or select a subset of elements that meet a condition.


n = 1 # N. . .
[x[n] for x in elements]

This also works:

zip(*elements)[1]

(I am mainly posting this, to prove to myself that I have groked zip...)

See it in action:

>>> help(zip)

Help on built-in function zip in module builtin:

zip(...)

zip(seq1 [, seq2 [...]]) -> [(seq1[0], seq2[0] ...), (...)]

Return a list of tuples, where each tuple contains the i-th element from each of the argument sequences. The returned list is truncated in length to the length of the shortest argument sequence.

>>> elements = [(1,1,1),(2,3,7),(3,5,10)]
>>> zip(*elements)
[(1, 2, 3), (1, 3, 5), (1, 7, 10)]
>>> zip(*elements)[1]
(1, 3, 5)
>>>

Neat thing I learned today: Use *list in arguments to create a parameter list for a function...

Note: In Python3, zip returns an iterator, so instead use list(zip(*elements)) to return a list of tuples.


I know that it could be done with a FOR but I wanted to know if there's another way

There is another way. You can also do it with map and itemgetter:

>>> from operator import itemgetter
>>> map(itemgetter(1), elements)

This still performs a loop internally though and it is slightly slower than the list comprehension:

setup = 'elements = [(1,1,1) for _ in range(100000)];from operator import itemgetter'
method1 = '[x[1] for x in elements]'
method2 = 'map(itemgetter(1), elements)'

import timeit
t = timeit.Timer(method1, setup)
print('Method 1: ' + str(t.timeit(100)))
t = timeit.Timer(method2, setup)
print('Method 2: ' + str(t.timeit(100)))

Results:

Method 1: 1.25699996948
Method 2: 1.46600008011

If you need to iterate over a list then using a for is fine.


Found this as I was searching for which way is fastest to pull the second element of a 2-tuple list. Not what I wanted but ran same test as shown with a 3rd method plus test the zip method

setup = 'elements = [(1,1) for _ in range(100000)];from operator import itemgetter'
method1 = '[x[1] for x in elements]'
method2 = 'map(itemgetter(1), elements)'
method3 = 'dict(elements).values()'
method4 = 'zip(*elements)[1]'

import timeit
t = timeit.Timer(method1, setup)
print('Method 1: ' + str(t.timeit(100)))
t = timeit.Timer(method2, setup)
print('Method 2: ' + str(t.timeit(100)))
t = timeit.Timer(method3, setup)
print('Method 3: ' + str(t.timeit(100)))
t = timeit.Timer(method4, setup)
print('Method 4: ' + str(t.timeit(100)))

Method 1: 0.618785858154
Method 2: 0.711684942245
Method 3: 0.298138141632
Method 4: 1.32586884499

So over twice as fast if you have a 2 tuple pair to just convert to a dict and take the values.


Timings for Python 3.6 for extracting the second element from a 2-tuple list.

Also, added numpy array method, which is simpler to read (but arguably simpler than the list comprehension).

from operator import itemgetter
elements = [(1,1) for _ in range(100000)]

%timeit second = [x[1] for x in elements]
%timeit second = list(map(itemgetter(1), elements))
%timeit second = dict(elements).values()
%timeit second = list(zip(*elements))[1]
%timeit second = np.array(elements)[:,1]

and the timings:

list comprehension:  4.73 ms ± 206 µs per loop
list(map):           5.3 ms ± 167 µs per loop
dict:                2.25 ms ± 103 µs per loop
list(zip)            5.2 ms ± 252 µs per loop
numpy array:        28.7 ms ± 1.88 ms per loop

Note that map() and zip() do not return a list anymore, hence the explicit conversion.


map (lambda x:(x[1]),elements)

Using islice and chain.from_iterable:

>>> from itertools import chain, islice
>>> elements = [(1,1,1),(2,3,7),(3,5,10)]
>>> list(chain.from_iterable(islice(item, 1, 2) for item in elements))
[1, 3, 5]

This can be useful when you need more than one element:

>>> elements = [(0, 1, 2, 3, 4, 5), 
                (10, 11, 12, 13, 14, 15), 
                (20, 21, 22, 23, 24, 25)]
>>> list(chain.from_iterable(islice(tuple_, 2, 5) for tuple_ in elements))
[2, 3, 4, 12, 13, 14, 22, 23, 24]