if statement with ddply function - r

Question

I am trying to use the if statement with ddply but am having issues with the if statement.
An example dataset is:
data<-data.frame(Gear=c(rep("S",10),rep("C",10)),TowSurvey=c(0,0,1,1,0,1,1,1,1,0),TowCom=c(0,1,1,1,0,1,1,1,1,0),
StationID=c(1,2,3,4,5,6,7,8,9,10),Totwght=c(2,8,6,4,12,9,56,7,89,10),Totexpwght=c(5,8,12,45,89,56,23,78,56,41),
Expnum=c(1,5,6,98,45,2,6,3,7,45),Exp=c(56,25,85,74,1,23,56,45,89,75))
My first try was
if(data$Gear=="S" & data$TowSurvey== 1 | data$Gear=="C" & data$TowCom== 1){
datad<-ddply(data, .(StationID,Gear), summarize,Totwghtpertow=sum(Totwght),
Totexppertow=sum(Totexpwght),Totnum =sum(Expnum),Totexpnum=sum(Exp))}
print(datad)
But the records that don't meet the if statement criteria are included in datad.
Then I found this post: Aggregate (count) rows that match a condition, group by unique values. Aggregate (count) rows that match a condition, group by unique values
So my second attempt based on the answer from the post was
datad<-ddply(data, .(StationID,Gear), summarize,Totwghtpertow=sum(Totwght[Gear=="S" & TowSurvey== 1 | Gear=="C" & TowCom== 1]))
I only tried with one column as a test and am getting the same results. Any help would be appreciated in trying to figure this out.
Thanks

Answer 1

If you run your first attempt you should actually get an error message since if can only evaluate a logical vector of length 1.
You really don't need an if statement here. Subsetting your data will do just fine.
data_sub <- subset(data, (data$Gear=="S" & data$TowSurvey== 1) | (data$Gear=="C" & data$TowCom== 1))
You can run your ddply statement using data_sub rather than data.
Or if you're going to be using the a lot you can wrap it in a function:
datad_func <- function(data){
data_sub <- subset(data, (data$Gear=="S" & data$TowSurvey== 1) | (data$Gear=="C" & data$TowCom== 1))
datad<-ddply(data_sub, .(StationID,Gear), summarize,Totwghtpertow=sum(Totwght),
Totexppertow=sum(Totexpwght),Totnum =sum(Expnum),Totexpnum=sum(Exp))
rm('data_sub')
print(datad)
}
datad_func(data)
StationID Gear Totwghtpertow Totexppertow Totnum Totexpnum
1 2 C 8 8 5 25
2 3 C 6 12 6 85
3 3 S 6 12 6 85
4 4 C 4 45 98 74
5 4 S 4 45 98 74
6 6 C 9 56 2 23
7 6 S 9 56 2 23
8 7 C 56 23 6 56
9 7 S 56 23 6 56
10 8 C 7 78 3 45
11 8 S 7 78 3 45
12 9 C 89 56 7 89
13 9 S 89 56 7 89

Answer 2

plyr is not so good at subsetting in the function, so you can do it before or after like #scribbles said.
You could also try dplyr and pipe them together:
library(dplyr)
data %>% filter((data$Gear == "S" & data$TowSurvey == 1) | (data$Gear == "C" & data$TowCom == 1)) %>%
group_by(StationID, Gear) %>%
summarise_each(funs(sum), Totwght, Totexpwght, Expnum, Exp)