Pauline Pauline - 1 month ago 12
Python Question

Sum of several columns from a pandas dataframe

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 1
2 3 6 1


I can sum a and b that way:

In [4]: sum(df['a']) + sum(df['b'])
Out[4]: 18


However this is not very convenient for larger dataframe, where you have to sum multiple columns together.

Is there a neater way to sum columns (similar to the below)? What if I want to sum the entire DataFrame without specifying the columns?

In [4]: sum(df[['a', 'b']]) #that will not work!
Out[4]: 18
In [4]: sum(df) #that will not work!
Out[4]: 21

Answer

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
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