Create Table of all Sums from two Arrays in Pandas-CodePudding

I got two arrays:

arr1 = [1,2,3]
arr2 = [5,10]

Now i want to create a Dataframe from the arrays which hold the sum of all combinations:

pd.DataFrame([[6,7,8], [11,12,13]],
                        columns=['1', '2', '3'],
                        index=['5', '10'])

	1	2	3
5	6	7	8
10	11	12	13

I know this can be easily done by iterating over the arrays, but I guess there is a built-in function to accomplish the same but way faster.
I've already looked in the documentation of different functions like the merge function but without success.

CodePudding user response：

We can use numpy broadcasting with addition then build the resulting DataFrame by assigning the index and column names from the lists:

import numpy as np
import pandas as pd

arr1 = [1, 2, 3]
arr2 = [5, 10]

df = pd.DataFrame(
    np.array(arr1)   np.array(arr2)[:, None], index=arr2, columns=arr1
)

Or with add outer (which works if arr1 and arr2 are lists or arrays):

df = pd.DataFrame(np.add.outer(arr2, arr1), index=arr2, columns=arr1)

*Note if arr1 and arr2 are already arrays (instead of list) it can just look like:

import numpy as np
import pandas as pd

arr1 = np.array([1, 2, 3])
arr2 = np.array([5, 10])

df = pd.DataFrame(arr1   arr2[:, None], index=arr2, columns=arr1)

All ways produce df:

     1   2   3
5    6   7   8
10  11  12  13