Add value from previous row under conditions - r

Question

I have a df data and I would like to add to a new column a value that exist in a previous column and row if the factor is the same.
Here is a sample:
data <- structure(list(Id = c("a", "b", "b", "b", "a", "a", "b", "b",
"a", "a"), duration.minutes = c(NA, 139L, 535L, 150L, NA, NA,
145L, 545L, 144L, NA), event = structure(c(1L, 4L, 3L, 4L, 2L,
1L, 4L, 3L, 4L, 2L), .Label = c("enter", "exit", "stop", "trip"
), class = "factor")), .Names = c("Id", "duration.minutes", "event"
), class = "data.frame", row.names = 265:274)
and I would like to add a new column called "duration.minutes.past" like this:
data <- structure(list(Id = c("a", "b", "b", "b", "a", "a", "b", "b",
"a", "a"), duration.minutes = c(NA, 139L, 535L, 150L, NA, NA,
145L, 545L, 144L, NA), event = structure(c(1L, 4L, 3L, 4L, 2L,
1L, 4L, 3L, 4L, 2L), .Label = c("enter", "exit", "stop", "trip"
), class = "factor"), duration.minutes.past = c(NA, NA, 139,
NA, NA, NA, NA, 145, NA, NA)), .Names = c("Id", "duration.minutes",
"event", "duration.minutes.past"), row.names = 265:274, class = "data.frame")
As you can see, I added in this new column duration.minutes.past the duration.minutes of the previous trip for the same Id. if the Id is different or if is it not a stop, then the value for duration.minutes.past is NA.
Help is much appreciated!

Answer 1

A possible solution using dplyr,
library(dplyr)
df %>%
group_by(Id) %>%
mutate(new = replace(lag(duration.minutes), event != 'stop', NA))
#Source: local data frame [10 x 4]
#Groups: Id [2]
# Id duration.minutes event new
# <chr> <int> <fctr> <int>
#1 a NA enter NA
#2 b 139 trip NA
#3 b 535 stop 139
#4 b 150 trip NA
#5 a NA exit NA
#6 a NA enter NA
#7 b 145 trip NA
#8 b 545 stop 145
#9 a 144 trip NA
#10 a NA exit NA

Answer 2

We can do this with data.table. Convert the 'data.frame' to 'data.table' (setDT(data)), grouped by 'Id', we create the lag column of 'duration.minutes' using shift), then change the value to 'NA' where the 'event' is not equal to 'stop'
library(data.table)
setDT(data)[, duration.minutes.past := shift(duration.minutes),
Id][event != "stop", duration.minutes.past := NA][]
data
# Id duration.minutes event duration.minutes.past
#1: a NA enter NA
#2: b 139 trip NA
#3: b 535 stop 139
#4: b 150 trip NA
#5: a NA exit NA
#6: a NA enter NA
#7: b 145 trip NA
#8: b 545 stop 145
#9: a 144 trip NA
#10: a NA exit NA
Or this can be done with base R using ave
data$duration.minutes.past <- with(data, NA^(event != "stop") *
ave(duration.minutes, Id, FUN = function(x) c(NA, x[-length(x)])))