The problem of gathering multiple sets of columns was already addressed here: Gather multiple sets of columns, but in my case, the columns are not unique.
I have the following data:
input <- data.frame(
id = 1:2,
question = c("a", "b"),
points = 0,
max_points = c(3, 5),
question = c("c", "d"),
points = c(0, 20),
max_points = c(5, 20),
check.names = F,
stringsAsFactors = F
)
input
#> id question points max_points question points max_points
#> 1 1 a 0 3 c 0 5
#> 2 2 b 0 5 d 20 20
The first column is an id, then I have many repeated columns (the original dataset has 133 columns):
- identifier for question
- points given
- maximum points
I would like to end up with this structure:
expected <- data.frame(
id = c(1, 2, 1, 2),
question = letters[1:4],
points = c(0, 0, 0, 20),
max_points = c(3, 5, 5, 20),
stringsAsFactors = F
)
expected
#> id question points max_points
#> 1 1 a 0 3
#> 2 2 b 0 5
#> 3 1 c 0 5
#> 4 2 d 20 20
I have tried several things:
tidyr::gather(input, key, val, -id)
reshape2::melt(input, id.vars = "id")
Both do not deliver the desired output. Furthermore, with more columns than shown here, gather
doesn't work any more, because there are too many duplicate columns.
As a workaround I tried this:
# add numbers to make col headers "unique"
names(input) <- c("id", paste0(1:(length(names(input)) - 1), names(input)[-1]))
# gather, remove number, spread
input %>%
gather(key, val, -id) %>%
mutate(key = stringr::str_replace_all(key, "[:digit:]", "")) %>%
spread(key, val)
which gives an error: Duplicate identifiers for rows (3, 9), (4, 10), (1, 7), (2, 8)
This problem was already discussed here: Unexpected behavior with tidyr, but I don't know why/how I should add another identifier. Most likely this is not the main problem, because I probably should approach the whole thing differently.
How could I solve my problem, preferably with tidyr
or base? I don't know how to use data.table
, but in case there is a simple solution, I will settle for that too.