Changing the ID value based on another column - r

Question

I have a large data set that looks something like this:
Conv. Rev. ID Order path_no
0 0 1 1 1
1 50 1 2 1
0 0 1 3 2
1 100 1 4 2
0 0 2 1 1
0 0 2 2 1
1 150 2 3 1
1 100 2 4 2
I want to make a new ID column based on when there is a new path_no, then the ID will change. So I am hoping it will look something like this:
Conv. Rev. ID Order path_no
0 0 1 1 1
1 50 1 2 1
0 0 2 3 2
1 100 2 4 2
0 0 3 1 1
0 0 3 2 1
1 150 3 3 1
1 100 4 4 2

Answer 1

I think rleid from data.table should do the trick. Here's one solution that uses data.table and dplyr:
dplyr::mutate(df, ID = data.table::rleid(path_no))
Conv. Rev. ID Order path_no
1 0 0 1 1 1
2 1 50 1 2 1
3 0 0 2 3 2
4 1 100 2 4 2
5 0 0 3 1 1
6 0 0 3 2 1
7 1 150 3 3 1
8 1 100 4 4 2
Or with data.table only:
dt <- setDT(df)
dt[, ID := rleid(path_no)][]
Conv. Rev. ID Order path_no
1: 0 0 1 1 1
2: 1 50 1 2 1
3: 0 0 2 3 2
4: 1 100 2 4 2
5: 0 0 3 1 1
6: 0 0 3 2 1
7: 1 150 3 3 1
8: 1 100 4 4 2
Data:
text <- "Conv. Rev. ID Order path_no
0 0 1 1 1
1 50 1 2 1
0 0 1 3 2
1 100 1 4 2
0 0 2 1 1
0 0 2 2 1
1 150 2 3 1
1 100 2 4 2"
df <- read.table(text = text, stringsAsFactors = FALSE, header = TRUE)

Answer 2

Can go for a simple for loop:
vals <- c(1, 1, 1, 2, 2, 2, 1, 1, 2)
nobs <- length(vals)
idx <- rep(1, nobs)
for (i in 2:nobs) {
if (vals[i] != vals[i-1]) {
idx[i] <- idx[i-1] + 1
} else {
idx[i] <- idx[i-1]
}
}