Fill column based on look-up table in R

Question

Let's say I have the following "key" dataset:

key = read.table(text = "question r_answer d_answer
                  20 A B
                  21 B A 
                  22 A B
                  23 B A
                  24 A B
                  25 B A", header = T)

> key
  question r_answer d_answer
1       20        A        B
2       21        B        A
3       22        A        B
4       23        B        A
5       24        A        B
6       25        B        A

This tells me, for a given question, what answer an "R" would give, and what answer a "D" would give.

Now let's say this is the dataset:

data =  read.table(text = "person_id question answer
1 20 A
1 21 B
1 22 A
1 23 B
1 24 A
1 25 B
2 20 A
2 21 A
2 23 A
2 24 B
2 25 B", header = T)

>data
   person_id question answer
1          1       20      A
2          1       21      B
3          1       22      A
4          1       23      B
5          1       24      A
6          1       25      B
7          2       20      A
8          2       21      A
9          2       23      A
10         2       24      B
11         2       25      B

This tells me, for a given person, what their actual answers were. I want to create an answer_type column in data that is equal to either r_answer or d_answer depending on the values listed in key. The resulting output would be:

   person_id question answer answer_type
1          1       20      A    r_answer
2          1       21      B    r_answer
3          1       22      A    r_answer
4          1       23      B    r_answer
5          1       24      A    r_answer
6          1       25      B    r_answer
7          2       20      A    r_answer
8          2       21      A    d_answer
9          2       23      A    d_answer
10         2       24      B    d_answer
11         2       25      B    r_answer

I have a feeling that the answer will involve merging from dplyr, but I can't quite figure it out.

Answer 1

One dplyr and tidyr option could be:

data %>%
 left_join(key %>%
            pivot_longer(-question, names_to = "answer_type"), by = c("question" = "question",
                                                                      "answer" = "value"))

   person_id question answer answer_type
1          1       20      A    r_answer
2          1       21      B    r_answer
3          1       22      A    r_answer
4          1       23      B    r_answer
5          1       24      A    r_answer
6          1       25      B    r_answer
7          2       20      A    r_answer
8          2       21      A    d_answer
9          2       23      A    d_answer
10         2       24      B    d_answer
11         2       25      B    r_answer