Conditional cumulative subtraction - r

Question

This is what my data.table looks like:
library(data.table)
dt <- fread('
Year Total Shares Balance
2017 10 1 10
2016 12 2 9
2015 10 2 7
2014 10 3 6
2013 10 NA 3
')
**Balance** is my desired column. I am trying to find the cumulative subtractions by taking the first value of Total which is 10(it should also be the first value of Balance field) and then cumulatively subtracting values in Shares. So the second value is 10-1 =9 and the third value is 9-2 = 7 and such. There is one condition, if the Year is 2014, then subtract the Shares value after dividing it by 2. so the fourth value is 7-(2/2)=6 and the fifth value is 6-3=3. I want to end the calc as of the last row.
My attempt is:
dt[, Balance:= ifelse( Year == 2014, cumsum(Total[1]-Shares/2), cumsum(Total[1] - Shares))]

Answer 1

Here is one method.
dt[, Balance2 := Total[1] - cumsum(shift(Shares * (1 - (0.5 *(Year == 2015))), fill=0))]
shift is used to create a lag variable, and the first element is filled with 0, using fill=0. The other elements are calculated as Shares * (1 - (0.5 *(Year == 2015))) which return Shares except when Years == 2015, in which case Shares * 0.5 is returned.
which returns
dt
Year Total Shares Balance Balance2
1: 2017 10 1 10 10
2: 2016 12 2 9 9
3: 2015 10 2 7 7
4: 2014 10 3 6 6
5: 2013 10 NA 3 3

Answer 2

FWIW, I wanted to provide a functional alternative that would allow for more flexible calculations in the cumulative differences, indexing, etc. I also have read in the data with read.table.
dt <- read.table(header=TRUE, text='
Year Total Shares Balance
2017 10 1 10
2016 12 2 9
2015 10 2 7
2014 10 3 6
2013 10 NA 3
')
makeNewBalance <- function(dt) {
output <- NULL
for (i in 1:nrow(dt)) {
if (i==1) {
output[i] <- dt$Total[i]
} else {
output[i] <- output[i-1] - as.integer(ifelse(dt$Year[i]==2014,
dt$Shares[i-1]/2,
dt$Shares[i-1]))
}
}
return(output)
}
dt$NewBalance <- makeNewBalance(dt)
which also returns
> dt
Year Total Shares Balance NewBalance
1 2017 10 1 10 10
2 2016 12 2 9 9
3 2015 10 2 7 7
4 2014 10 3 6 6
5 2013 10 NA 3 3