Loop sum excluding one column of pandas dataframe

Question

I have a dataframe as the following:

import pandas as pd
df = pd.DataFrame([(1,2,3,4,5,6),
                   (1,2,3,4,5,6),
                   (1,2,3,4,5,6)], columns=['a','b','c','d','e','f'])

Out:
    a b c d e f
0   1 2 3 4 5 6
1   1 2 3 4 5 6 
2   1 2 3 4 5 6

and I want to get the sum of all the elements of the dataframe, always excluding one column. In this example the desired outcome would be:

60 57 54 51 48 45

I have found a solution that seems to do the job, but I'm pretty sure there must be a more efficient way to do the same:

for x in df.columns:
    df.drop(columns = x).sum().sum()

Answer 1

Use DataFrame.rsub for subtract from right side summed rows by df.sum(axis=1) , last add sum for sum per columns:

s = df.rsub(df.sum(axis=1), axis=0).sum()
print (s)
a    60
b    57
c    54
d    51
e    48
f    45
dtype: int64

Answer 2

Simply subtract the total sum with the sum per column. This is efficiently done using an assignment expression :

out = (s:=df.sum()).sum()-s

output:

a    60
b    57
c    54
d    51
e    48
f    45

Answer 3

Yet another way: Subtract the column sums from the total sum of the DataFrame using broadcasting:

out = df.sum().sum() - df.sum()

Output:

a    60
b    57
c    54
d    51
e    48
f    45
dtype: int64