Identify the column name of the last occurrence of a value in R data frame

Question

I have a dataset like below with columns of 1s and 0s. I would like to add a final column that identifies the column name of the final occurrence of 0 per row.

have = data.frame(a = c(1,0,1,1,0,0,1,1,1,0),
                  b = c(1,0,1,1,1,0,1,1,0,0),
                  c = c(0,0,0,1,0,1,1,1,1,0),
                  d = c(1,0,1,1,0,0,0,1,0,1),
                  e = c(1,1,1,1,1,1,1,1,1,1))
> have
   a b c d e
1  1 1 0 1 1
2  0 0 0 0 1
3  1 1 0 1 1
4  1 1 1 1 1
5  0 1 0 0 1
6  0 0 1 0 1
7  1 1 1 0 1
8  1 1 1 1 1
9  1 0 1 0 1
10 0 0 0 1 1

I would like the output to look like this where the final column specifies the column name of the last occurring 0 and if one does not exist return NA.

> want
   a b c d e last_0
1  1 1 0 1 1      c
2  0 0 0 0 1      d
3  1 1 0 1 1      c
4  1 1 1 1 1   <NA>
5  0 1 0 0 1      d
6  0 0 1 0 1      d
7  1 1 1 0 1      d
8  1 1 1 1 1   <NA>
9  1 0 1 0 1      d
10 0 0 0 1 1      c

I've tried using max.col but it returns the last column name if a zero does not exist. Any other solutions? A dplyr solution is preferred.

> have$last_0 = names(have)[max.col(have == 0, ties.method = "last")]
> have
   a b c d e last_0
1  1 1 0 1 1      c
2  0 0 0 0 1      d
3  1 1 0 1 1      c
4  1 1 1 1 1      e
5  0 1 0 0 1      d
6  0 0 1 0 1      d
7  1 1 1 0 1      d
8  1 1 1 1 1      e
9  1 0 1 0 1      d
10 0 0 0 1 1      c

Answer 1

Here is an approach with purrr::pmap:

library(dplyr);library(purrr)
have %>% 
   mutate(want = pmap_chr(cur_data(), 
                          ~ tail(c(NA,names(which(c(...)==0))),1)))
   a b c d e want
1  1 1 0 1 1    c
2  0 0 0 0 1    d
3  1 1 0 1 1    c
4  1 1 1 1 1 <NA>
5  0 1 0 0 1    d
6  0 0 1 0 1    d
7  1 1 1 0 1    d
8  1 1 1 1 1 <NA>
9  1 0 1 0 1    d
10 0 0 0 1 1    c

purrr:pmap is a very useful function because it will work row wise on data and it comes in various flavors so you can control what returns. You can refer to the entire row of data with c(...).

---

If you wanted to apply the procedure to only a subset of columns, you might use dplyr::select:

have %>% 
    mutate(want = pmap_chr(cur_data() %>% select(a,b,c), 
                           ~ tail(c(NA,names(which(c(...)==0))),1)))
   a b c d e want
1  1 1 0 1 1    c
2  0 0 0 0 1    c
3  1 1 0 1 1    c
4  1 1 1 1 1 <NA>
5  0 1 0 0 1    c
6  0 0 1 0 1    b
7  1 1 1 0 1 <NA>
8  1 1 1 1 1 <NA>
9  1 0 1 0 1    b
10 0 0 0 1 1    c