What would be the fastest way to do the sum product of the below DF
| A | B |
|---|---|
| 2 | 6 |
| 5 | 5 |
| 7 | 5 |
| 8 | 2 |
| 6 | 11 |
I have a for loop :
for i in range(len(DF)) :
Sumproduct = 0
What I aim to do in this for loop is for example if
i=1 then sumproduct = 2*6
i=2 then sumproduct = 2*6 5*5
i=3 then sumproduct = 2*6 5*5 7*5
Explanation in table :
| A | B | SumProduct |
|---|---|---|
| 2 | 6 | |
| 5 | 5 | 2x6 |
| 7 | 5 | 2x6 5x5 |
| 8 | 2 | 2x6 5x5 7x5 |
| 6 | 11 | 2x6 5x5 7x5 8x2 |
ect...
CodePudding user response：
You could use prod() and cumsum() with shift()
df.prod(axis=1).cumsum().shift()
CodePudding user response：
That'll be cumsum on the product of the two columns then shift down:
df['SumProduct'] = df['A'].mul(df['B']).cumsum().shift()