Sum of several columns from a pandas dataframe

Question

So say I have the following table:

In [2]: df = pd.DataFrame({\'a\': [1,2,3], \'b\':[2,4,6], \'c\':[1,1,1]})

In [3]: df
Out[3]: 
   a  b  c
0  1  2  1
1  2  4           


        

Answer 1

I think you can use double sum - first DataFrame.sum create Series of sums and second Series.sum get sum of Series:

print (df[['a','b']].sum())
a     6
b    12
dtype: int64

print (df[['a','b']].sum().sum())
18

You can also use:

print (df[['a','b']].sum(axis=1))
0    3
1    6
2    9
dtype: int64

print (df[['a','b']].sum(axis=1).sum())
18

Thank you pirSquared for another solution - convert df to numpy array by values and then sum:

print (df[['a','b']].values.sum())
18

---

print (df.sum().sum())
21

Answer 2

Maybe you are looking something like this:

df["result"] = df.apply(lambda row: row['a' : 'c'].sum(),axis=1)