如何基于索引添加子列表的元素-Python

Question

How do you add the elements in sub-lists according to the index of the values? For example, how do you turn this:

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

into this? :

sublist_sums = [9,12] # [1 + 3 + 5, 2 + 4 + 6]

Sorry if the title wasn't very clear, I wasn't really sure how to put it.

Answer 1

If using NumPy is allowed, then you can use numpy.sum() along axis=0 :

In [11]: np.sum(nested_list, axis=0)
Out[11]: array([ 9, 12])

On the other hand, if you want a plain Python solution, then using zip ed result in a list comprehension would suffice:

In [32]: [sum(l) for l in zip(*nested_list)]
Out[32]: [9, 12]

Answer 2

Already an answer is accepted , but the following can also be used for your requirement.Let me know does this answer your question.

import pandas as pd
import numpy as np

c = ['Val1','Val2'] 
v = [
        [1,1.0],
        [2,1.0],
        [1,1.0],
        [2,0.98],
        [3,0.78],
        [4,0.70],
        [9,0.97],
        [6,0.67],
        [12,0.75],

    ]



n = len(v)

df = pd.DataFrame(v,columns=c)


#Take top N ie all elements in this case and sum it.
print(list(df.groupby('Val1').head(n).sum()))  

#### Output ####
[40.0, 7.85]




#Alternatively you can create a column where the value is same for all
#In my case column is 'id' and value is 1
#Then apply group-by-sum on 'id'
df['id'] = [1]*n   
print(df.groupby('id').sum())

#### Output ####
    Val1  Val2
id            
1     40  7.85