具有变量组合（或排列）并分配给数据框的函数值

Question

I have n variables. Suppose n equals 3 in this case. I want to apply one function to all of the combinations(or permutations, depending on how you want to solve this) of variables and store the result in the same row and column in dataframe.

a = 1
b = 2
c = 3
indexes = ['a', 'b', 'c']
df = pd.DataFrame({x:np.nan for x in indexes}, index=indexes)

If I apply sum(the function can be anything), then the result that I want to get is like this:

    a   b   c
a   2   3   4
b   3   4   5
c   4   5   6

I can only think of iterating all the variables, apply the function one by one, and use the index of the iterators to set the value in the dataframe. Is there any better solution?

Answer 1

You can use apply and return a pd.Series for that effect. In such cases, pandas uses the series indices as columns in the resulting dataframe.

s = pd.Series({"a": 1, "b": 2, "c": 3})
s.apply(lambda x: x+s) 

Just note that the operation you do is between an element and a series.

Answer 2

I believe you need broadcast sum of array created from variables if performance is important:

a = 1
b = 2
c = 3
indexes = ['a', 'b', 'c']

arr = np.array([a,b,c])
df =  pd.DataFrame(arr + arr[:, None], index=indexes, columns=indexes)
print (df)
   a  b  c
a  2  3  4
b  3  4  5
c  4  5  6