Sum all possible combinations of an array with python

# Look at all subsets from size 2 up to the whole thing
for size in range(2, len(records) + 1):
   # Iterate through all subsets of size "size"
   for subset in itertools.combinations(records, size):
       # subset will be a subset of the records. Feel free
       # to grab their sum and print them out however you want

Edited: Accidentally mistyped combinations as combination. Sorry.

You can try the following:

import pandas as pd
from itertools import product

a = [2, 6, 7]
df = pd.DataFrame(product([0, 1], repeat=len(a)), columns=a)
df['sum'] = df[a] @ a
print(df)

This gives:

   2  6  7  sum
0  0  0  0    0
1  0  0  1    7
2  0  1  0    6
3  0  1  1   13
4  1  0  0    2
5  1  0  1    9
6  1  1  0    8
7  1  1  1   15

The first three columns of the dataframe are labeled with elements of the list a. The value of 0 in a column indicates that the corresponding element of a is used in a sum, and 0 that it is not used. The last column gives sums of the elements of a selected in this way.

If you are interested only in sums that involve at least two elements of a, then you can select the relevant rows of the dataframe using df[df[a].sum(axis=1) >= 2].

Edit. The code above produces a dataframe consisting of 2**len(a) rows. For larger values of len(a) this will use a lot of memory. In such cases, it may be better to produce sums one by one in a loop instead of computing a dataframe with all of them. This can be done, for example, as follows:

from itertools import product
import numpy as np

a = [2, 6, 7]
arr = np.array(a)
for p in product([0, 1], repeat=len(a)):
    print(p, p @ arr)