Maybe as Numeric

I submitted final course grades today. The semester is over, hurrah!

Of course, getting the grades out of my university’s learning management system (we use Canvas) was a pain. It exported to csv, but the first three rows contained some meta-information instead of students’ grades. And there were some rows that weren’t students. So this meant that when I imported this into R, all the columns in my data.frame were of type character instead of numeric:

grades <- data.frame(student = c("","Joe Schmoe","Jane Schmane"),
                     quiz = c("","87","98"), stringsAsFactors = FALSE)
       student quiz
2   Joe Schmoe   87
3 Jane Schmane   98

Easy solution, though. I can just drop the problematic rows and then run:

map_df(grades, as.numeric)

and all will be well, right?

Wrong. Some of the columns are actually character (names, Ids), and will return NAs if we try to treat them as numeric. No good.

One solution, probably easier than what I came up with, would be to just manually run as.numeric over the offending columns. But that seemed unsatisfying since that’s a lot of manual typing (there were many columns). So I wrote a quick function that only converts character to numeric if the vector is actually a numeric.1

maybe_as_numeric <- function(v){
  if (is(tryCatch(as.numeric(v),
                  warning = function(w) w),
  } else{

There’s probably a better way to do this, but this seems to work at least for now. Hopefully someone else finds it useful. Now we can map_df(grades, maybe_as_numeric) and all goes well. Our secretly-numeric columns are now actually numeric, and we keep important things like students’ names and ID’s.

  1. “Actually” being defined as as.numeric not throwing a warning ^