I have a data set on the form below:
| Id | START DATE | END DATE |
|---|---|---|
| 1 | 2020-01-01 | 2021-01-01 |
| 2 | 2000-03-02 | 2021-01-01 |
I would like to split in 90 days interval from start to end date. I might be able to find a work around, but since I need to perform it multiple times, i am looking for a relatively simple code. I am thinking do.call might be the way to go?
The last interval can be less than 90 days in case the ending interval does not fit with a 90 day period.
| Id | START DATE | END DATE |
|---|---|---|
| 1 | 2020-01-01 | 2020-03-31 |
| 1 | 2020-03-31 | 2020-06-29 |
| ... | ||
| 2 | 2000-03-02 | 2000-05-31 |
I got some very good suggestions for solutions, unfortunate i do not have access to the updated version of dplyr, and thus not the reframe()function.
I found a solution but any other solutions is still very welcome
I have found a solution, however I dont think it is a very pretty one:
Assume dt is my data table, the following whileloop will solve the problem using the data.table package.
Before running the code i check that all end dates fall after start date.
continue <- TRUE
dt[,add_row:=end-start>90]
while(continu==TRUE{
dt1 <- dt[add_row==TRUE]
dt2 <- dt[add_row==TRUE]
dt3 <- dt[add_row==FALSE]
# dt1 updated with new enddate
d1[,end:=start+90]
#dt2 updated with new start
dt2[,start:=start+90]
#dt3 contains individuals not to be updated
dt <- rbind[dt1,dt2,dt2]
#check if loop should continue
dt[,add_row:=end-start>90]
continue <- any(tmp[,add_row])
}