How to reshape a dataframe with “reoccurring” columns?

Question

I am new to data analysis with R. I recently got a pre-formatted environmental observation-model dataset, an example subset of which is shown below:

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Answer 1

The fact that you have recurring column names is a bit of an oddity and is not normal R behaviour. Most of the time R forces you to have valid names via the make.names() function. Regardless, I'm able to duplicate your problem. Note I made my own example since yours isn't reproducible, but the logic is the same.

#Do not force unique names
s <- data.frame(id = 1:3, x = runif(3), x = runif(3), check.names = FALSE)
#-----
  id         x         x
1  1 0.6845270 0.5218344
2  2 0.7662200 0.6179444
3  3 0.4110043 0.1104774

#Now try to melt, note that 1/2 of your x-values are missing!
melt(s, id.vars = 1)
#-----
  id variable     value
1  1        x 0.6845270
2  2        x 0.7662200
3  3        x 0.4110043

The solution is to make your column names unique. As I said before, R does this by default in most cases. However, you can do it after the fact via make.unique()

names(s) <- make.unique(names(s))
#-----
[1] "id"  "x"   "x.1"

Note that the second column of x now has a 1 appended to it. Now melt() works as you'd expect:

melt(s, id.vars = 1)
#-----
  id variable     value
1  1        x 0.6845270
2  2        x 0.7662200
3  3        x 0.4110043
4  1      x.1 0.5218344
5  2      x.1 0.6179444
6  3      x.1 0.1104774

At this point, if you want to treat x and x.1 as the same variable, I think a little gsub() or other regex function to get rid of the offending characters. THis is a workflow I use quite often.