Element-wise addition of 2 lists

Question

I have now   list1    1  2  3  list2    4  5  6    I wish to have    1  2  3            4  5  6            5  7  9    Simply an element-wise addition of two lists   I can surely iterate the two lists  but I don t want do that   What is the most Pythonic way of doing so

User · Answer

Perhaps this is pythonic and slightly useful if you have an unknown number of lists, and without importing anything.

As long as the lists are of the same length, you can use the below function.

Here the *args accepts a variable number of list arguments (but only sums the same number of elements in each).

The * is used again in the returned list to unpack the elements in each of the lists.

def sum_lists(*args):
    return list(map(sum, zip(*args)))

a = [1,2,3]
b = [1,2,3]  

sum_lists(a,b)

Output:

[2, 4, 6]

Or with 3 lists

sum_lists([5,5,5,5,5], [10,10,10,10,10], [4,4,4,4,4])

Output:

[19, 19, 19, 19, 19]

User · Answer

Use map with lambda function    gt  gt  gt  map lambda x  y  x   y  list1  list2   5  7  9

User · Answer

list1 i    list2 i  for i in range len list1

User · Answer

The others gave examples how to do this in pure python  If you want to do this with arrays with 100 000 elements  you should use numpy   In  1   import numpy as np In  2   vector1   np array  1  2  3   In  3   vector2   np array  4  5  6     Doing the element-wise addition is now as trivial as  In  4   sum vector   vector1   vector2 In  5   print sum vector  5 7 9    just like in Matlab   Timing to compare with Ashwini s fastest version   In  16   from operator import add In  17   n   10  5 In  18   vector2   np tile  4 5 6   n  In  19   vector1   np tile  1 2 3   n  In  20   list1    1 2 3  n In  21   list2    4 5 6  n In  22   timeit map add  list1  list2  10 loops  best of 3  26 9 ms per loop  In  23   timeit vector1   vector2 1000 loops  best of 3  1 06 ms per loop   So this is a factor 25 faster  But use what suits your situation  For a simple program  you probably don t want to install numpy  so use standard python  and I find Henry s version the most Pythonic one   If you are into serious number crunching  let numpy do the heavy lifting  For the speed freaks  it seems that the numpy solution is faster starting around n   8

User · Answer

The zip function is useful here  used with a list comprehension v1  v2  If you have a list of lists  instead of just two lists  you can use v3  For lists with different length  for example  By adding 1 to the end of the first secound list   then you can try something like this  using zip longest  - v4  first    1  2  3  1  second    4  5  6   output   5  7  9  1    If you have an unknown number of lists of the same length  you can use the function v5   v6 - The operator module exports a set of efficient functions corresponding to the intrinsic operators of Python  For example  operator add x  y  is equivalent to the expression x y   v7 - Assuming both lists first and second have same length  you do not need zip or anything else                     first    1  2  3  second    4  5  6           v1          third1    sum i  for i in zip first second            v2          third2    x   y for x  y in zip first  second            v3          lists of lists     1  2  3    4  5  6   third3    sum x  for x in zip  lists of lists            v4          from itertools import zip longest third4   list map sum  zip longest first  second  fillvalue 0             v5          def sum lists  args       return list map sum  zip  args     third5   sum lists first  second           v6          import operator third6   list map operator add  first second            v7          third7   first i  second i  for i in range len first             v i            print third1     5  7  9  print third2     5  7  9  print third3     5  7  9  print third4     5  7  9  print third5     5  7  9  print third6     5  7  9  print third7     5  7  9

User · Answer

Perhaps  the most pythonic way  should include handling the case where list1 and list2 are not the same size  Applying some of these methods will quietly give you an answer  The numpy approach will let you know  most likely with a ValueError   Example   import numpy as np  gt  gt  gt  list1     1  2    gt  gt  gt  list2     1  2  3   gt  gt  gt  list3     1    gt  gt  gt   a   b for a  b in zip list1  list2    2  4   gt  gt  gt   a   b for a  b in zip list1  list3    2   gt  gt  gt  a   np array  list1   gt  gt  gt  b   np array  list2   gt  gt  gt  a b Traceback  most recent call last     File   lt stdin gt    line 1  in  lt module gt  ValueError  operands could not be broadcast together with shapes  2   3    Which result might you want if this were in a function in your problem

User · Answer

This is simple with numpy add    import numpy  list1   numpy array  1  2  3   list2   numpy array  4  5  6   result   numpy add list1  list2    result receive element-wise addition of list1 and list2 print result  array  5  7  9     See doc here  If you want to receiver a python list   result tolist

User · Answer

Use map with operator add    gt  gt  gt  from operator import add  gt  gt  gt  list  map add  list1  list2     5  7  9    or zip with a list comprehension    gt  gt  gt   sum x  for x in zip list1  list2    5  7  9    Timing comparisons    gt  gt  gt  list2    4  5  6  10  5  gt  gt  gt  list1    1  2  3  10  5  gt  gt  gt   timeit from operator import add map add  list1  list2  10 loops  best of 3  44 6 ms per loop  gt  gt  gt   timeit from itertools import izip   a   b for a  b in izip list1  list2   10 loops  best of 3  71 ms per loop  gt  gt  gt   timeit  a   b for a  b in zip list1  list2   10 loops  best of 3  112 ms per loop  gt  gt  gt   timeit from itertools import izip  sum x  for x in izip list1  list2   1 loops  best of 3  139 ms per loop  gt  gt  gt   timeit  sum x  for x in zip list1  list2   1 loops  best of 3  177 ms per loop

User · Answer

It s simpler to use numpy from my opinion   import numpy as np list1  1 2 3  list2  4 5 6  np add list1 list2    Results     For detailed parameter information  check here  numpy add

User · Answer

I haven t timed it but I suspect this would be pretty quick     import numpy as np list1  1  2  3  list2  4  5  6   list sum    np add list1  list2   tolist     5  7  9

User · Answer

If you need to handle lists of different sizes  worry not  The wonderful itertools module has you covered    gt  gt  gt  from itertools import zip longest  gt  gt  gt  list1    1 2 1   gt  gt  gt  list2    2 1 2 3   gt  gt  gt   sum x  for x in zip longest list1  list2  fillvalue 0    3  3  3  3   gt  gt  gt    In Python 2  zip longest is called izip longest   See also this relevant answer and comment on another question

User · Answer

This will work for 2 or more lists  iterating through the list of lists  but using numpy addition to deal with elements of each list  import numpy as np list1  1  2  3  list2  4  5  6   lists    list1  list2  list sum   np zeros len list1   for i in lists     list sum    i list sum   list sum tolist         5 0  7 0  9 0

User · Answer

a list      b list      for i in range 1 100       a list append random randint 1 100    for i in range 1 100       a list append random randint 101 200    sum x  for x in zip a list   b list

User · Answer

Although  the actual question does not want to iterate over the list to generate the result  but all the solutions that has been proposed does exactly that under-neath the hood    To refresh  You cannot add two vectors without looking into all the vector elements  So  the algorithmic complexity of most of these solutions are Big-O n   Where n is the dimension of the vector   So  from an algorithmic point of view  using a for loop to iteratively generate the resulting list is logical and pythonic too  However  in addition  this method does not have the overhead of calling or importing any additional library     Assumption  The lists are of equal length  resultList    list1 i    list2 i  for i in range len list1      The timings that are being showed discussed here are system and implementation dependent  and cannot be reliable measure to measure the efficiency of the operation  In any case  the big O complexity of the vector addition operation is linear  meaning O n

User · Answer

a   b for a  b in zip list1  list2

User · Answer

As described by others  a fast and also space efficient solution is using numpy  np  with it s built-in vector manipulation capability   1  With Numpy  x   np array  1 2 3   y   np array  2 3 4   print x y   2  With built-ins  2 1 Lambda  list1  1  2  3  list2  4  5  6  print map lambda x y x y  list1  list2    Notice that map   supports multiple arguments   2 2 zip and list comprehension  list1  1  2  3  list2  4  5  6  print  x   y for x  y in zip list1  list2

[python] Element-wise addition of 2 lists?

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