How to make new variable across conditions - r

Question

I need to calculate new variable from data using conditions. New Pheno.
Data set is huge.
I have data set: Animal, Record, Days, Pheno
A R D P
1 1 240 300
1 2 230 290
2 1 305 350
2 2 260 290
3 1 350 450
Conditions are:
Constant pheno per day is 2.
If record days is more than 305 old pheno should be keept.
If record is less than 305 but has next records Pheno should be keept.
If record is less than 305 and have no next records it should be calculated as : 305-days*constant+pheno = (305 - 260)*2+300
Example for animal 1 having less than 305 for both records. So First record will be same in new pheno, but secon record is las and has less than 305, so we need to re-calculate... (305-230)*2+290=440
Finaly data will be like:
A R D P N_P
1 1 240 300 300
1 2 230 290 440
2 1 305 350 350
2 2 260 290 380
3 1 350 450 450
How to do it in R or linux ...

Answer 1

Here is a solution with base R
df <- read.table(header=TRUE, text=
"A R D P
1 1 240 300
1 2 230 290
2 1 305 350
2 2 260 290
3 1 350 450")
newP <- function(d) {
np <- numeric(nrow(d))
for (i in 1:nrow(d)) {
if (d$D[i] > 305) { np[i] <- d$P[i]; next }
if (d$D[i] <= 305 && i<nrow(d)) { np[i] <- d$P[i]; next }
np[i] <- (305-d$D[i])*2 + d$P[i]
}
d$N_P <- np
return(d)
}
D <- split(df, df$A)
D2 <- lapply(D, newP)
do.call(rbind, D2)

Answer 2

Check this out (I assume R is the number of records sorted, so if you have 10 records the last will have R=10)
library(dplyr)
df <- data.frame(A=c(1,1,2,2,3),
R=c(1,2,1,2,1),
D=c(240,230,305,260,350),
P=c(300,290,350,290,450))
df %>% group_by(A) %>%
mutate(N_P=ifelse(( D<305 & R==n()), # check if D<305 & Record is last record
((305-D)*2)+P # calculate new P
,P)) # Else : use old P
Source: local data frame [5 x 5]
Groups: A [3]
A R D P N_P
<dbl> <dbl> <dbl> <dbl> <dbl>
1 1 1 240 300 300
2 1 2 230 290 440
3 2 1 305 350 350
4 2 2 260 290 380
5 3 1 350 450 450
If you have predefined constants that depend on R value in the df, for example :
const <- c(1,2,1.5,2.5,3)
You can replace R in the code by const[R]
df %>% group_by(A) %>%
mutate(N_P=ifelse(( D<305 & R==n()), # check if D<305 & Record is last record
((305-D)*const[R])+P # calculate new P
,P)) # Else : use old P