Have a look at the MWE below:
df <- data.frame(date=as.Date(c("06/07/2000","15/09/2000","15/10/2000","03/01/2001","17/03/2001","23/05/2001","26/08/2001"), "%d/%m/%Y"), event=c(0,0,1,0,1,1,0)) id date event 01 2000-07-06 0 01 2000-09-15 0 01 2000-10-15 1 01 2001-01-03 0 02 2001-03-17 1 02 2001-05-23 1 02 2001-08-26 0 02 2001-08-28 0 03 2001-08-29 1 03 2001-09-05 1 03 2001-09-30 0 03 2001-10-12 1 I want, grouped per ID, the number of days since the last event. My question is similar to this one. Only, I want the result grouped per ID:
id date event tae 01 2000-07-06 0 NA 01 2000-09-15 0 NA 01 2000-10-15 1 0 01 2001-01-03 0 80 02 2001-03-17 1 0 02 2001-05-23 1 67 02 2001-08-26 0 95 02 2001-08-28 0 97 03 2001-08-29 1 0 03 2001-09-05 1 7 03 2001-09-30 0 25 03 2001-10-12 1 38 I tried the following:
I tried using the steps proposed in the link in a ddply function as below. But this does not seem to do the job.
ddply(df, .(id), transform, last_event_index <- cumsum(df$event) + 1)) ddply(df, .(id), transform, last_event_index <- c(1, last_event_index[1:length(last_event_index) - 1])) df<- ddply(operationaltemp, .(id), transform, last_event_date = df[which(df$event==1), "date"])[df$last_event_index]) I hope somebody knows how this can be done.