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

You can do a rolling self-join, supported by data.table:

require(data.table)
setDT(df)   ## change it to data.table in place
setkey(df, houseID, year)     ## needed for fast join
df.woNA <- df[!is.na(price)]  ## version without the NA rows

# rolling self-join will return what you want
df.woNA[df, roll=TRUE]  ## will match previous year if year not found