根据条件分配行程编号

Question

I have a time series data. I would like to group and number rows when column "soak" > 3600. The first row when soak > 3600 is numbered as 1, and the consecutive rows are numbered as 1 too until another row met the condition of soak > 3600. Then that row and consequent rows are numbered as 2 until the third occurrence of soak > 3600.

A small sample of my data and the code I tried is also provided.

My code did the count, but seems using the ave() gave me some decimal numbers... Is there a way to output integer?

starts <- structure(list(datetime = structure(c(1440578907, 1440579205, 
1440579832, 1440579885, 1440579926, 1440579977, 1440580044, 1440580106, 
1440580195, 1440580256, 1440580366, 1440580410, 1440580476, 1440580529, 
1440580931, 1440580966, 1440587753, 1440587913, 1440587933, 1440587954
), class = c("POSIXct", "POSIXt"), tzone = ""), soak = c(NA, 
70L, 578L, 21L, 2L, 41L, 14L, 16L, 32L, 9L, 45L, 20L, 51L, 25L, 
364L, 4L, 6764L, 20L, 4L, 5L)), row.names = c(NA, -20L), class = c("data.table", 
"data.frame"), .internal.selfref = <pointer: 0x000000000a4d1ef0>)

starts$trip <- with(starts, ave(tdiff, cumsum(replace(soka, NA, 10000) > 3600)))

Answer 1

Using dplyr

library(dplyr)
starts %>% mutate(trip = cumsum(replace(soak, is.na(soak), 1) > 3600))

And with base R

starts$trip = with(starts, ave(soak, FUN=function(x) cumsum(replace(x, is.na(x), 1) > 3600)))