My question involves how to calculate the number of days since an event last that occurred in R.
Below is a minimal example of the data:
df <- data.frame(date=as.Date(c("06/07/2000","15/09/2000","15/10/2000","03/01/2001","17/03/2001","23/05/2001","26/08/2001"), "%d/%m/%Y"),
event=c(0,0,1,0,1,1,0))
date event
1 2000-07-06 0
2 2000-09-15 0
3 2000-10-15 1
4 2001-01-03 0
5 2001-03-17 1
6 2001-05-23 1
7 2001-08-26 0
A binary variable(event) has values 1 indicating that the event occurred and 0 otherwise. Repeated observations are done at different times(date
)
The expected output is as follows with the days since last event(tae
):
date event tae
1 2000-07-06 0 NA
2 2000-09-15 0 NA
3 2000-10-15 1 0
4 2001-01-03 0 80
5 2001-03-17 1 153
6 2001-05-23 1 67
7 2001-08-26 0 95
I have looked around for answers to similar problems but they don't address my specific problem. I have tried to implement ideas from
from a similar post (Calculate elapsed time since last event) and below is the closest I
got to the solution:
library(dplyr)
df %>%
mutate(tmp_a = c(0, diff(date)) * !event,
tae = cumsum(tmp_a))
Which yields the output shown below that is not quite the expected:
date event tmp_a tae
1 2000-07-06 0 0 0
2 2000-09-15 0 71 71
3 2000-10-15 1 0 71
4 2001-01-03 0 80 151
5 2001-03-17 1 0 151
6 2001-05-23 1 0 151
7 2001-08-26 0 95 246
Any assistance on how to fine tune this or a different approach would be greatly appreciated.
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