How to make a list of integers that is the sum of all the integers from a set of lists in a dict?

Question

Let\'s assume I have a created a dict that is made up of n keys. Each key is mapped to a list of integers of a consistent length. What I want to make now is a new list that

Answer 1

Depending on your use-case you might want to consider using an adequate library for more general/complex functionality.

numpy: general scientific computing

import numpy as np

my_dict = {'a': [1, 2, 3, 4], 'b': [2, 3, 4, 5], 'c': [3, 4, 5, 6]}

arr = np.array(list(d.values()))
# [[1 2 3 4]
#  [2 3 4 5]
#  [3 4 5 6]]

arr.sum(axis=0)
# [ 6  9 12 15]

---

pandas: data-analysis toolkit

import pandas as pd

my_dict = {'a': [1, 2, 3, 4], 'b': [2, 3, 4, 5], 'c': [3, 4, 5, 6]}

df = pd.DataFrame(my_dict)
#    a  b  c
# 0  1  2  3
# 1  2  3  4
# 2  3  4  5
# 3  4  5  6

df.sum(axis=1)
# 0     6
# 1     9
# 2    12
# 3    15

Answer 2

What you need is to transpose the lists so you can sum the columns. So use zip on the dictionary values (keys can be ignored) and sum in list comprehension:

in one line:

total_sum_list = [sum(x) for x in zip(*my_dict.values())]

result:

[6, 9, 12, 15]

How it works:

zip interleaves the values. I'm using argument unpacking to pass the dict values are arguments to zip (like zip(a,b,c)). So when you do:

for x in zip(*my_dict.values()):
    print(x)

you get (as tuple):

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

data are ready to be summed (even in different order, but we don't care since addition is commutative :))