I am fairly new to R and DPLYR and I am stuck on a this issue:
I have two tables:
(1) Repairs done on cars
(2) Amount owed on each car over time
What I would like to do is create three extra columns on the repair table that gives me: (1) the amount owed on the car when the repair was done, (2) 3months down the road and (3) finally last payment record on file.
And if the case where the repair date does not match with any payment record, I need to use the closest amount owed on record.
So something like:
Any ideas how I can do that?
Here are the data frames:
Repairs done on cars:
df_repair <- data.frame(unique_id =
c("A1","A2","A3","A4","A5","A6","A7","A8"),
car_number = c(1,1,1,2,2,2,3,3),
repair_done = c("Front Fender","Front
Lights","Rear Lights","Front Fender", "Rear Fender","Rear Lights","Front
Lights","Front Fender"),
YearMonth = c("2014-03","2016-03","2016-07","2015-05","2015-08","2016-01","2018-01","2018-05"))
df_owed <- data.frame(car_number = c(1,1,1,1,1,1,1,1,1,1,1,1,1,2,2,2,2,3,3,3,3,3),
YearMonth = c("2014-02","2014-05","2014-06","2014-08","2015-06","2015-12","2016-03","2016-04","2016-05","2016-06","2016-07","2016-08","2015-05","2015-08","2015-12","2016-03","2018-01","2018-02","2018-03","2018-04","2018-05","2018-09"),
amount_owed = c(20000,18000,17500,16000,10000,7000,6000,5500,5000,4500,4000,3000,10000,8000,6000,0,50000,40000,35000,30000,25000,15000))