sum of multiplication of cells in the same row but different column for pandas data frame

Question

I have a data frame

df = pd.DataFrame({'A':[1,2,3],'B':[2,3,4]})

My data looks like this

Index   A   B
0       1   2
1       2   3
2       3   4

I would like to calculate the sum of multiplication between A and B in each row. The expected result should be (1x2)+(2x3)+(3x4) = 2 + 6 + 12 = 20. May I know the pythonic way to do this instead of looping?

Answer 1

You can try multiple columns A and B and then use sum :

import pandas as pd
import numpy as np

df = pd.DataFrame({'A':[1,2,3],'B':[2,3,4]})
print df
   A  B
0  1  2
1  2  3
2  3  4

print df['A'] * df['B']
0     2
1     6
2    12
dtype: int64

print (df['A'] * df['B']).sum()
20

Or use prod for multiple all columns:

print df.prod(axis=1)
0     2
1     6
2    12
dtype: int64

print df.prod(axis=1).sum()
20

Thank you ajcr for comment:

If you have just two columns, you can also use df.A.dot(df.B) for extra speed, but for three or more columns this is the way to do it!