Reputation: 3
I'm attempting to roll a value forward using dplyr
's mutate()
and lag()
. I'm trying the below code to make it work. Instead of it working as I expect it to, I get ZEROs in the BegFund
column after the first row. I've tried using data.table shift()
with no luck, and stats::lag()
with no luck as well. Anyone have any ideas?
Below is a simplified example of what I'm attempting to do. Reproduces when I test.
library(dplyr) # 0.4.3
payments <- 1:10
fund.start <- 1000
payment.percent <- .05
fund.value <- data.frame(payments)
fund.value <- fund.value %>%
transmute(Payment = payments) %>%
mutate(EndFund = 0) %>%
mutate(BegFund = ifelse(Payment == 1, fund.start, lag(EndFund, 1)),
PmtAmt = BegFund * payment.percent,
EndFund = BegFund - PmtAmt) %>%
select(Payment, BegFund, PmtAmt, EndFund)
head(fund.value)
EDIT: Below is the output I'd like to get out of R for this. Please excuse the awful formatting, I'm very new at this.
Payment BegFund PmtAmt EndFund
1 1000 50 950
2 950 47.5 902.5
3 902.5 45.125 857.375
4 857.375 42.86875 814.50625
5 814.50625 40.7253125 773.7809375
6 773.7809375 38.68904688 735.0918906
Upvotes: 0
Views: 1016
Reputation: 118799
Here's one way:
EndFund = fund.start * (1 - payment.percent) * (1-payment.percent)^(payments-1L)
BegFund = c(fund.start, head(EndFund, -1L))
PymtAmt = BegFund - EndFund
Just noticed that @Eddi also has covered this under comment.
Upvotes: 1
Reputation: 99
I know this is not the way the OP wanted to do it, but it may help
fund.value <- data.frame(payments, BegFund=0, PmtAmt=0,EndFund=0)
fund.value$BegFund[1]<-fund.start
fund.value$PmtAmt[1] = fund.value$BegFund[1] * payment.percent
fund.value$EndFund[1] = fund.value$BegFund[1] - fund.value$PmtAmt[1]
for(i in 2:dim(fund.value)[1]){
fund.value$BegFund[i]<-fund.value$EndFund[i-1]
fund.value$PmtAmt[i] = fund.value$BegFund[i] * payment.percent
fund.value$EndFund[i] = fund.value$BegFund[i] - fund.value$PmtAmt[i]
}
Out is
payments BegFund PmtAmt EndFund
1 1 1000.0000 50.00000 950.0000
2 2 950.0000 47.50000 902.5000
3 3 902.5000 45.12500 857.3750
4 4 857.3750 42.86875 814.5063
5 5 814.5063 40.72531 773.7809
6 6 773.7809 38.68905 735.0919
Upvotes: 0