How to convert list of tuples to multiple lists?

Suppose I have a list of tuples and I want to convert to multiple lists.

For example, the list of tuples is

[(1,2),(3,4),(5,6),]

Is there any built-in function in Python that convert it to:

[1,3,5],[2,4,6]

This can be a simple program. But I am just curious about the existence of such built-in function in Python.

Answers:

Thank you for visiting the Q&A section on Magenaut. Please note that all the answers may not help you solve the issue immediately. So please treat them as advisements. If you found the post helpful (or not), leave a comment & I’ll get back to you as soon as possible.

Method 1

The built-in function zip() will almost do what you want:

>>> list(zip(*[(1, 2), (3, 4), (5, 6)]))
[(1, 3, 5), (2, 4, 6)]

The only difference is that you get tuples instead of lists. You can convert them to lists using

list(map(list, zip(*[(1, 2), (3, 4), (5, 6)])))

Method 2

From the python docs:

zip() in conjunction with the * operator can be used to unzip a list:

Specific example:

>>> zip((1,3,5),(2,4,6))
[(1, 2), (3, 4), (5, 6)]
>>> zip(*[(1, 2), (3, 4), (5, 6)])
[(1, 3, 5), (2, 4, 6)]

Or, if you really want lists:

>>> map(list, zip(*[(1, 2), (3, 4), (5, 6)]))
[[1, 3, 5], [2, 4, 6]]

Method 3

Use:

a = [(1,2),(3,4),(5,6),]    
b = zip(*a)
>>> [(1, 3, 5), (2, 4, 6)]

Method 4

Despite *zip being more Pythonic, the following code has much better performance:

xs, ys = [], []
for x, y in zs:
    xs.append(x)
    ys.append(y)

Also, when the original list zs is empty, *zip will raise, but this code can properly handle.

I just ran a quick experiment, and here is the result:

Using *zip:     1.54701614s
Using append:   0.52687597s

Running it multiple times, append is 3x – 4x faster than zip! The test script is here:

#!/usr/bin/env python3
import time

N = 2000000
xs = list(range(1, N))
ys = list(range(N+1, N*2))
zs = list(zip(xs, ys))

t1 = time.time()

xs_, ys_ = zip(*zs)
print(len(xs_), len(ys_))

t2 = time.time()

xs_, ys_ = [], []
for x, y in zs:
    xs_.append(x)
    ys_.append(y)
print(len(xs_), len(ys_))

t3 = time.time()

print('Using *zip:t{:.8f}s'.format(t2 - t1))
print('Using append:t{:.8f}s'.format(t3 - t2))

My Python Version:

Python 3.6.3 (default, Oct 24 2017, 12:18:40)
[GCC 4.2.1 Compatible Apple LLVM 8.1.0 (clang-802.0.42)] on darwin
Type "help", "copyright", "credits" or "license" for more information.

Method 5

franklsf95 goes for performance in his answer and opts for list.append(), but they are not optimal.

Adding list comprehensions, I ended up with the following:

def t1(zs):
    xs, ys = zip(*zs)
    return xs, ys

def t2(zs):
    xs, ys = [], []
    for x, y in zs:
        xs.append(x)
        ys.append(y)
    return xs, ys

def t3(zs):
    xs, ys = [x for x, y in zs], [y for x, y in zs]
    return xs, ys

if __name__ == '__main__':
    from timeit import timeit
    setup_string='''
N = 2000000
xs = list(range(1, N))
ys = list(range(N+1, N*2))
zs = list(zip(xs, ys))
from __main__ import t1, t2, t3
'''
    print(f'zip:tt{timeit('t1(zs)', setup=setup_string, number=1000)}')
    print(f'append:tt{timeit('t2(zs)', setup=setup_string, number=1000)}')
    print(f'list comp:t{timeit('t3(zs)', setup=setup_string, number=1000)}')

This gave the result:

zip:            122.11585397789766
append:         356.44876132614047
list comp:      144.637765085659

So if you are after performance, you should probably use zip() although list comprehensions are not too far behind. The performance of append is actually pretty poor in comparison.

Method 6

In addition to Claudiu’s answer, you can use:

>>>a, b = map(list, zip(*[(1, 2), (3, 4), (5, 6)]))
>>>a
[1,3,5]
>>>b
[2,4,6]

Edited according to @Peyman mohseni kiasari

Method 7

Adding to Claudiu’s and Claudiu’s answer and since map needs to be imported from itertools in python 3, you also use a list comprehension like:

[[*x] for x in zip(*[(1,2),(3,4),(5,6)])]
>>> [[1, 3, 5], [2, 4, 6]]


All methods was sourced from stackoverflow.com or stackexchange.com, is licensed under cc by-sa 2.5, cc by-sa 3.0 and cc by-sa 4.0

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