The problem I am trying to solve is that I have a data frame with a sorted POSIXct variable in it. Each row is categorized and I want to get the time differences between each row for each level and add that data back into a new variable. The reproducible problem is as below. The below function is just for creating sample data with random times for the purpose of this question.
random.time <- function(N, start, end) {
st <- as.POSIXct(start)
en <- as.POSIXct(end)
dt <- as.numeric(difftime(en, st, unit="sec"))
ev <- sort(runif(N, 0, dt))
rt <- st + ev
return(rt)
}
The code for simulating the problem is as below:
set.seed(123)
category <- sample(LETTERS[1:5], 20, replace=TRUE)
randtime <- random.time(20, '2015/06/01 08:00:00', '2015/06/01 18:00:00')
df <- data.frame(category, randtime)
The expected resulting data frame is as below:
>category randtime timediff (secs)
>A 2015-06-01 09:05:00 0
>A 2015-06-01 09:06:30 90
>A 2015-06-01 09:10:00 210
>B 2015-06-01 10:18:58 0
>B 2015-06-01 10:19:58 60
>C 2015-06-01 08:14:00 0
>C 2015-06-01 08:16:30 150
Each subgroup in the output will have the first row with timediff value of 0 as there is no previous row. I was able to group by category and call the following function to calculate the differences but could not get it to collate the final output for all category groups.
getTimeDiff <- function(x) {
no_rows <- nrow(x)
if(no_rows > 1) {
for(i in 2:no_rows) {
t <- x[i, "randtime"] - x[i-1, "randtime"]
}
}
}
I have been at this for two days now without luck so would greatly appreciate any help. Thanks.
