Add characters to existing cells with condition R - r

Question

I have the following table:
structure(list(Id = structure(c(1L, 1L, 2L, 2L, 1L, 3L, 3L, 3L
), .Label = c("a", "b", "c"), class = "factor"), stops = c(1,
1, 1, 1, 1, 2, 2, 2)), .Names = c("Id", "stops"), row.names = c(NA,
-8L), class = "data.frame")
I would like to add to $stops new characters when the stop did not change but the $Id did.
For example, I would like to get:
structure(list(Id = structure(c(1L, 1L, 2L, 2L, 1L, 3L, 3L, 3L
), .Label = c("a", "b", "c"), class = "factor"), stops = structure(c(1L,
1L, 2L, 2L, 3L, 4L, 4L, 4L), .Label = c("1", "1-1", "1-2", "2"
), class = "factor")), .Names = c("Id", "stops"), row.names = c(NA,
-8L), class = "data.frame")
I just would like to do so if the Id is different than the previous one, and if the Stops is the same than the previous one...
I tried with mutate() but it seems I am quite far away to get something working here...

Answer 1

Here's a looples attempt using data.table
library(data.table)
setDT(df)[, `:=`(stops = as.character(stops), Idindx = rleid(Id))]
indx <- unique(df, by = "Idindx")[, counter := (1:.N) - 1L, by = rleid(stops)]
df[indx[counter > 0], stops := paste(stops, i.counter, sep = "-"), on = "Idindx"]
# Id stops Idindx
# 1: a 1 1
# 2: a 1 1
# 3: b 1-1 2
# 4: b 1-1 2
# 5: a 1-2 3
# 6: c 2 4
# 7: c 2 4
# 8: c 2 4
The first step is to create an unique index for each Id (as they aren't unique) and convert stops to a character (per your desired output)
Then, operating on unique indexes identify counts of same stops and join back to the original data

Answer 2

You could write a loop to solve your problem:
# Original data
data <- structure(list(Id = structure(c(1L, 1L, 2L, 2L, 1L, 3L, 3L, 3L
), .Label = c("a", "b", "c"), class = "factor"), stops = c(1,
1, 1, 1, 1, 2, 2, 2)), .Names = c("Id", "stops"), row.names = c(NA,
-8L), class = "data.frame")
# Add new column, which will be converted in the following loop
data$stops_new <- as.character(data$stops)
new <- 1
for(i in 2:nrow(data)) {
# Convert values of stops_new, if your specified conditions appear
if(data$Id[i] != data$Id[i - 1] & data$stops[i] == data$stops[i - 1]) {
data$stops_new[i] <- paste(data$stops_new[i], "-", new, sep = "")
# Repeat the convertion for all values with the same ID and stop-value
j <- i + 1
while(data$Id[i] == data$Id[j] & data$stops[i] == data$stops[j]) {
data$stops_new[j] <- paste(data$stops[i], "-", new, sep = "")
j <- j + 1
}
new <- new + 1
}
}
data

Answer 3

this is a base R solution.
create indicators showing you whether Id has changed (id.ind) and whether stops has changed (stops.ind) from the previous line (convention being that these indicators are set to "0", i.e. no change, for the first row):
stops.ind <- c(0, diff(dat$stops))
id.ind <- c(0, diff(as.numeric(dat$Id)))
create new stops vector:
stops <- new.stops <- dat$stops
row by row check whether a) there is a change in id and no change in stops or b) there is no change in either from the previous row. in case a) increase k by one and append "-k" to stops value b) use previous value of stops:
k <- 0
for(i in 2 : nrow(dat)){
if(id.ind[i] != 0 & stops.ind[i] == 0){
k <- k + 1
new.stops[i] <- paste0(stops[i], "-", k)
}
if(id.ind[i] == 0 & stops.ind[i] == 0)
new.stops[i] <- new.stops[i - 1]
}
new.stops
# [1] "1" "1" "1-1" "1-1" "1-2" "2" "2" "2"
new.dat <- data.frame(Id = dat$Id, stops = new.stops)