Replace missing values (NA) with most recent non-NA by group

Question

I would like to solve the following problem with dplyr. Preferable with one of the window-functions. I have a data frame with houses and buying prices. The following is an e

Answer 1

Without dplyr:

  prices$price <-unlist(lapply(split(prices$price,prices$houseID),
function(x) zoo::na.locf(x,na.rm=FALSE)))

prices
   houseID year price
1        1 1995    NA
2        1 1996   100
3        1 1997   100
4        1 1998   120
5        1 1999   120
6        2 1995    NA
7        2 1996    NA
8        2 1997    NA
9        2 1998    30
10       2 1999    30
11       3 1995    NA
12       3 1996    44
13       3 1997    44
14       3 1998    44
15       3 1999    44