Reshape a ragged, wide array with repeated variables to long in r - r

Question

I have a table like
+------+---------+---------+---------+----------+---------+
| Code | Display | Synonym | Synonym | Synonym | Synonym |
+------+---------+---------+---------+----------+---------+
| 1 | A | Cat | Dog | Lion | |
| 2 | B | Horse | Penguin | | |
| 3 | C | Donkey | Giraffe | Mongoose | Rabbit |
+------+---------+---------+---------+----------+---------+
I want to output a table like
+------+---------+----------+
| Code | Display | Synonym |
+------+---------+----------+
| 1 | A | Cat |
| 1 | A | Dog |
| 1 | A | Lion |
| 2 | B | Horse |
| 2 | B | Penguin |
| 3 | C | Donkey |
| 3 | C | Giraffe |
| 3 | C | Mongoose |
| 3 | C | Rabbit |
+------+---------+----------+
In other words, I want to pair off Code and Display with each Synonym that is presented, and each Code can have 1 to several synonyms. I've seen examples of reshape used in other contexts, but haven't been able to figure out how to apply it here.

Answer 1

You can use standard reshaping on a ragged array - with melt() from reshape2, you can use the na.rm argument to remove NAs as you go, otherwise you can do it afterward:
library(reshape2)
dat.m <- melt(dat, id.vars = c("Code", "Display"), value.name = "Synonym", na.rm = TRUE)
# Code Display variable Synonym
#1 1 A Synonym Cat
#2 2 B Synonym Horse
#3 3 C Synonym Donkey
#4 1 A Synonym.1 Dog
#5 2 B Synonym.1 Penguin
#6 3 C Synonym.1 Giraffe
#7 1 A Synonym.2 Lion
#9 3 C Synonym.2 Mongoose
#12 3 C Synonym.3 Rabbit
You can drop the variable column if you like:
dat.m$variable <- NULL

Answer 2

Here are two base R approaches.
stack
cbind(mydf[1:2], stack(lapply(mydf[-c(1:2)], as.character)))
# Code Display values ind
# 1 1 A Cat Synonym
# 2 2 B Horse Synonym
# 3 3 C Donkey Synonym
# 4 1 A Dog Synonym.1
# 5 2 B Penguin Synonym.1
# 6 3 C Giraffe Synonym.1
# 7 1 A Lion Synonym.2
# 8 2 B Synonym.2
# 9 3 C Mongoose Synonym.2
# 10 1 A Synonym.3
# 11 2 B Synonym.3
# 12 3 C Rabbit Synonym.3
reshape
Make life easier by renaming your columns first to a pattern like "Synonym_1", "Synonym_2" and so on. Actually, R likes "Synonym.1", "Synonym.2" and so on better....
A <- grep("Synonym", names(mydf))
names(mydf)[A] <- paste0("Synonym_", seq_along(A))
Now, reshape...
reshape(mydf, direction = "long", varying = A, sep = "_")
# Code Display time Synonym id
# 1.1 1 A 1 Cat 1
# 2.1 2 B 1 Horse 2
# 3.1 3 C 1 Donkey 3
# 1.2 1 A 2 Dog 1
# 2.2 2 B 2 Penguin 2
# 3.2 3 C 2 Giraffe 3
# 1.3 1 A 3 Lion 1
# 2.3 2 B 3 2
# 3.3 3 C 3 Mongoose 3
# 1.4 1 A 4 1
# 2.4 2 B 4 2
# 3.4 3 C 4 Rabbit 3

Answer 3

I figured out a maybe indirect way to do this shortly after asking the question:
allergies_output <- reshape(allergies_input,varying=list(grep('Synonym',names(allergies_input),value=TRUE)),direction='long',idvar=c('Code','Display'),v.names='Synonym',names(allergies_input))
This gives some wonky results, but nothing that can't be fixed by dropping some column names.