r - Last observation carried forward conditional on multiple columns -

i have dataset structure:

id = c(1,1,1,1,2,2,2,3,3,3,3)  l40 = c(1, na, na, na, 1, na, na, na, 1, na, na)  k50 = c(na, na, na, na, na, 1, na, na, na, na, 1)  df = data.frame(id, l40, k50) 

when missing values occur in columns l40 , k50, want carry forward last non-missing value in column, conditional on id being same previous id , values in l40 , k50 in current row being empty. applied following code:

library(tidyr) df2 <- df %>% group_by(id) %>% fill(l40:k50) 

this not achieve looking for. want previous non-missing value carried forward next row when other columns (except id) in row empty. want:

id = c(1,1,1,1,2,2,2,3,3,3,3)  l40 = c(1, 1, 1, 1, 1, na, na, na, 1, 1, na) k50 = c(na, na, na, na, na, 1, 1, na, na, na, 1)   df3 = data.frame(id, l40, k50) 

we can use na.locf

library(data.table) library(zoo) setdt(df)[, if(any(is.na(k50[-1]))) lapply(.sd, na.locf) else .sd , = id] #   id l40 k50 #1:  1   1  na #2:  1   1  na #3:  1   1  na #4:  1   1  na #5:  2   1  na #6:  2  na   1 #7:  3  na   1 #8:  3  na   1 #9:  3  na   1 

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an option using dplyr be

library(dplyr) df %>%     mutate(ind = rowsums(is.na(.))) %>%    group_by(id)  %>%    mutate_each(funs(if(any(ind>1)) na.locf(., na.rm=false) else .), l40:k50) %>%    select(-ind) #      id   l40   k50 #   <dbl> <dbl> <dbl> #1     1     1    na #2     1     1    na #3     1     1    na #4     1     1    na  #5     2     1    na #6     2    na     1 #7     3    na     1 #8     3    na     1 #9     3    na     1