Using match and apply in R

Question

> df = data.frame(id = 1:5, ch_1 = 11:15,ch_2= 10:14,selection = c(11,13,12,14,12))
> df
  id ch_1 ch_2 selection
1  1   11   10        11
2  2   12   11        13
3  3   13   12        12
4  4   14   13        14
5  5   15   14        12

Given this data set I need an additional column that follow the rules:

1. if selection is one of the two choices (ch_1 and ch_2), return the number of the choice (1 or 2)
2. if the selection is not of the two choices, return 3

I need a way to do this for every row. For a single row, doing the following code works just fine, but I can't seem to find a way to use it with apply to run it to each single row of a dataframe.Looking for a solution that can be applied to more than just two columns and that runs faster than doing a traditional loop

df=df[1,]

if (df$selection %in% df[,paste("ch_",1:2,sep="")]) {
  a = which(df[,paste("ch_",1:2,sep="")]==df$selection)
} else {
  a = 3
}
# OR
ifelse(df$selection %in% df[,paste("ch_",1:2,sep="")],1,3)
# OR
match(df$selection,df[,paste("ch_",1:2,sep="")])

Answer 1

Compare the vector to the other columns with ==, add a final column which is always TRUE, and then take the index of the first TRUE in each row using max.col

max.col(cbind(df$selection == df[c("ch_1","ch_2")], TRUE), "first")
#[1] 1 3 2 1 3

This should easily extend to n columns then.

Answer 2

You could do this with nested ifelse,

with(df, ifelse(selection == ch_1, 1L, ifelse(selection == ch_2, 2L, 3L)))
# [1] 1 3 2 1 3

but I'm rarely fond of nesting them. If this is all you need (and you never need more than two), then this might suffice.

One alternative is using dplyr::case_when,

with(df, dplyr::case_when(selection == ch_1 ~ 1, selection == ch_2 ~ 2, TRUE ~ 3))

and it can be easily used within a dplyr::mutate if you are already using the package.