Row by row application in R [duplicate] - r

Question

I have my data in the form of a data.table given below
structure(list(atp = c(1, 0, 1, 0, 0, 1), len = c(2, NA, 3, NA,
NA, 1), inv = c(593, 823, 668, 640, 593, 745), GU = c(36, 94,
57, 105, 48, 67), RUTL = c(100, NA, 173, NA, NA, 7)), .Names = c("atp",
"len", "inv", "GU", "RUTL"), row.names = c(NA, -6L), class = c("data.table",
"data.frame"), .internal.selfref = <pointer: 0x0000000000320788>)
I need to form 4 new columns csi_begin,csi_end, IRQ and csi_order. the value of csi_begin and csi_end when atp=1 depends directly on inv and gu values.
But when atp is not equal to 1 csi_begin and csi_end depends on inv and gu values and IRQ value of previous row
The value of IRQ depends on csi_order of that row if atp==1 else its 0 and csi_order value depends on two rows previous csi_begin value.
I have written the condition with the help of for loop.
Below is the code given
lostsales<-function(transit)
{
if (transit$atp==1)
{
transit$csi_begin[i]<-(transit$inv)[i]
transit$csi_end[i]<-transit$csi_begin[i]-transit$GU[i]
}
else
{
transit$csi_begin[i]<-(transit$inv)[i]+transit$IRQ[i-1]
transit$csi_end[i]<-transit$csi_begin[i]-transit$GU[i]
}
if (transit$csi_begin[i-2]!= NA)
{
transit$csi_order[i]<-transit$csi_begin[i-2]
}
else
{ transit$csi_order[i]<-0}
if (transit$atp==1)
{
transit$IRQ[i]<-transit$csi_order[i]-transit$RUTL[i]
}
else
{
transit$IRQ[i]<-0
}
}
Can anyone help me how to do efficient looping with data.tables using setkeys? As my data set is very large and I cannot use for loop else the timing would be very high.

Answer 1

Adding the desired outcome to your example would be very helpful, as I'm having trouble following the if/then logic. But I took a stab at it anyway:
library(data.table)
# Example data:
dt <- structure(list(atp = c(1, 0, 1, 0, 0, 1), len = c(2, NA, 3, NA, NA, 1), inv = c(593, 823, 668, 640, 593, 745), GU = c(36, 94, 57, 105, 48, 67), RUTL = c(100, NA, 173, NA, NA, 7)), .Names = c("atp", "len", "inv", "GU", "RUTL"), row.names = c(NA, -6L), class = c("data.table", "data.frame"), .internal.selfref = "<pointer: 0x0000000000320788>")
# Add a row number:
dt[,rn:=.I]
# Use this function to get the value from a previous (shiftLen is negative) or future (shiftLen is positive) row:
rowShift <- function(x, shiftLen = 1L) {
r <- (1L + shiftLen):(length(x) + shiftLen)
r[r<1] <- NA
return(x[r])
}
# My attempt to follow the seemingly circular if/then rules:
lostsales2 <- function(transit) {
# If atp==1, set csi_begin to inv and csi_end to csi_begin - GU:
transit[atp==1, `:=`(csi_begin=inv, csi_end=inv-GU)]
# Set csi_order to the value of csi_begin from two rows prior:
transit[, csi_order:=rowShift(csi_begin,-2)]
# Set csi_order to 0 if csi_begin from two rows prior was NA
transit[is.na(csi_order), csi_order:=0]
# Initialize IRQ to 0
transit[, IRQ:=0]
# If ATP==1, set IRQ to csi_order - RUTL
transit[atp==1, IRQ:=csi_order-RUTL]
# If ATP!=1, set csi_begin to inv + IRQ value from previous row, and csi_end to csi_begin - GU
transit[atp!=1, `:=`(csi_begin=inv+rowShift(IRQ,-1), csi_end=inv+rowShift(IRQ,-1)-GU)]
return(transit)
}
lostsales2(dt)
## atp len inv GU RUTL rn csi_begin csi_end csi_order IRQ
## 1: 1 2 593 36 100 1 593 557 0 -100
## 2: 0 NA 823 94 NA 2 NA NA 0 0
## 3: 1 3 668 57 173 3 668 611 593 420
## 4: 0 NA 640 105 NA 4 640 535 0 0
## 5: 0 NA 593 48 NA 5 593 545 668 0
## 6: 1 1 745 67 7 6 745 678 640 633
Is this output close to what you were expecting?