Remove reoccurring data from data.table

Question

I have a data.table like this:

data.table(a=rep(c("xx", "yy"), each=4), b=rep(c("zz", "nn"), each=2), vals=10:17)

    a  b vals
1: xx zz   10
2: xx zz   11
3: xx nn   12
4: xx nn   13
5: yy zz   14
6: yy zz   15
7: yy nn   16
8: yy nn   17

What i want is this, since it looks better in a table when exported to excel and then to words (I know, never use excel...):

    a  b vals
1: xx zz   10
2: NA NA   11
3: NA nn   12
4: NA NA   13
5: yy zz   14
6: NA NA   15
7: NA nn   16
8: NA NA   17

EDIT: forgot to say that if a numeric value is recurring, it should not be changed to NA, only character columns.

Answer 1

Using rleid from data.table we can create a function

library(data.table)

replace_duplicated <- function(x) {
  replace(x, duplicated(rleid(x)), NA)
}

and now apply it to selected columns (Thanks to @markus)

cols = names(df)[sapply(df, is.character)]
df[,(cols) := lapply(.SD, replace_duplicated ), .SDcols = cols]
df

#      a    b vals
#1:   xx   zz   10
#2: <NA> <NA>   11
#3: <NA>   nn   12
#4: <NA> <NA>   13
#5:   yy   zz   14
#6: <NA> <NA>   15
#7: <NA>   nn   16
#8: <NA> <NA>   17

---

In dplyr we can use mutate_if

library(dplyr)
df %>% mutate_if(is.character, replace_duplicated)

or mutate_at

df %>% mutate_at(cols, replace_duplicated)