sample<- data.frame(
id=c("A","B","C","D","A","C","D","A","C","D","A","D","A","C"),
date=c("1/3/2013","1/3/2013", "1/3/2013","1/3/2013","2/3/2013","2/3/2013",
"2/3/2013","3/3/2013","3/3/2013",
"3/3/2013",
"4/3/2013",
"4/3/2013",
"5/3/2013",
"5/3/2013"), stringsAsFactors = F)
library(lubridate)
sample$date <- dmy(sample$date)
sample1 <- sample[order(sample$id, sample$date), ]
sample1$idu <- unlist(sapply(rle(sample1$id)$lengths, seq_len)) -1
id date idu
1 A 2013-03-01 0
5 A 2013-03-02 1
8 A 2013-03-03 2
11 A 2013-03-04 3
13 A 2013-03-05 4
2 B 2013-03-01 0
3 C 2013-03-01 0
6 C 2013-03-02 1
9 C 2013-03-03 2
14 C 2013-03-05 3
4 D 2013-03-01 0
7 D 2013-03-02 1
10 D 2013-03-03 2
12 D 2013-03-04 3
In order to add a time lag column, several options are available. I'd simply do
sample1$diff <- c(0, int_diff(sample1$date)/days(1))
# Remainder cannot be expressed as fraction of a period.
# Performing %/%.
> sample1
id date idu diff
1 A 2013-03-01 0 0
5 A 2013-03-02 1 1
8 A 2013-03-03 2 1
11 A 2013-03-04 3 1
13 A 2013-03-05 4 1
2 B 2013-03-01 0 -4
3 C 2013-03-01 0 0
6 C 2013-03-02 1 1
9 C 2013-03-03 2 1
14 C 2013-03-05 3 2
4 D 2013-03-01 0 -4
7 D 2013-03-02 1 1
10 D 2013-03-03 2 1
12 D 2013-03-04 3 1
And do further changes as needed. replacing all negative values with 0.