data.matrix() when character involved - r

Question

In order to calculate the highest contribution of a row per ID I have a beautiful script which works when the IDs are a numeric. Today however I found out that it is also possible that IDs can have characters (for instance ABC10101). For the function to work, the dataset is converted to a matrix. However data.matrix(df) does not support characters. Can the code be altered in order for the function to work with all kinds of IDs (character, numeric, etc.)? Currently I wrote a quick workaround which converts IDs to numeric when ID=character, but that will slow the process down for large datasets.
Example with code (function: extract the first entry with the highest contribution, so if 2 entries have the same contribution it selects the first):
Note: in this example ID is interpreted as a factor and data.matrix() converts it to a numeric value. In the code below the type of the ID column should be character and the output should be as shown at the bottom. Order IDs must remain the same.
tc <- textConnection('
ID contribution uniqID
ABCUD022221 40 101
ABCUD022221 40 102
ABCUD022222 20 103
ABCUD022222 10 104
ABCUD022222 90 105
ABCUD022223 75 106
ABCUD022223 15 107
ABCUD022223 10 108 ')
df <- read.table(tc,header=TRUE)
#Function that needs to be altered
uniqueMaxContr <- function(m, ID = 1, contribution = 2) {
t(
vapply(
split(1:nrow(m), m[,ID]),
function(i, x, contribution) x[i, , drop=FALSE]
[which.max(x[i,contribution]),], m[1,], x=m, contribution=contribution
)
)
}
df<-data.matrix(df) #only works when ID is numeric
highestdf<-uniqueMaxContr(df)
highestdf<-as.data.frame(highestdf)
In this case the outcome should be:
ID contribution uniqID
ABCUD022221 40 101
ABCUD022222 90 105
ABCUD022223 75 106

Answer 1

Others might be able to make it more concise, but this is my attempt at a data.table solution:
tc <- textConnection('
ID contribution uniqID
ABCUD022221 40 101
ABCUD022221 40 102
ABCUD022222 20 103
ABCUD022222 10 104
ABCUD022222 90 105
ABCUD022223 75 106
ABCUD022223 15 107
ABCUD022223 10 108 ')
df <- read.table(tc,header=TRUE)
library(data.table)
dt <- as.data.table(df)
setkey(dt,uniqID)
dt2 <- dt[,list(contribution=max(contribution)),by=ID]
setkeyv(dt2,c("ID","contribution"))
setkeyv(dt,c("ID","contribution"))
dt[dt2,mult="first"]
## ID contribution uniqID
## [1,] ABCUD022221 40 101
## [2,] ABCUD022222 90 105
## [3,] ABCUD022223 75 106
EDIT -- more concise solution
You can use .SD which is the subset of the data.table for the grouping, and then use which.max to extract a single row.
in one line
dt[,.SD[which.max(contribution)],by=ID]
## ID contribution uniqID
## [1,] ABCUD022221 40 101
## [2,] ABCUD022222 90 105
## [3,] ABCUD022223 75 106