I am trying to calculate percent of percent. per, per1, and per1-per are in percentages
date per per1 per1-per
1/1/2021 0 0 0
2/1/2021 0 0 0
3/1/2021 2 3 1
4/1/2021 0 2 2
5/1/2021 5 1 -4
6/1/2021 0 0 0
my desired output would be
date per per1 per1-per per_of_per
1/1/2021 0 0 0 0
2/1/2021 0 0 0 0
3/1/2021 2 3 1 1
4/1/2021 0 2 2 3.02
5/1/2021 5 1 -4 -1.10
6/1/2021 0 0 0 -1.10
How per_of_per is calculated is:
- for first time,
per_of_per[0] = (1+per1-per[0])-1 - for second time,
per_of_per[1] = (1+per1-per[0])*(1+per1-per[1])-1 - for third time,
per_of_per[2] = (1+per1-per[0])*(1+per1-per[1])*(1+per1-per[2])-1
and so on..
>Solution :
Use cumprod after converting percent to int, adding 1, then perform the reverse process to give back percent:
df['pre_per'] = df['per1-per'].div(100).add(1).cumprod().sub(1).mul(100)
output:
date per per1 per1-per pre_per
0 1/1/2021 0 0 0 0.0000
1 2/1/2021 0 0 0 0.0000
2 3/1/2021 2 3 1 1.0000
3 4/1/2021 0 2 2 3.0200
4 5/1/2021 5 1 -4 -1.1008
5 6/1/2021 0 0 0 -1.1008