Fastest way to reshape variable values as columns

Question

I have a dataset with about 3 million rows and the following structure:

PatientID| Year | PrimaryConditionGroup
---------------------------------------
1                 


        

Answer 1

There are probably more succinct ways of doing this, but for sheer speed, it's hard to beat a data.table-based solution:

df <- read.table(text="PatientID Year  PrimaryConditionGroup
1         Y1    TRAUMA
1         Y1    PREGNANCY
2         Y2    SEIZURE
3         Y1    TRAUMA", header=T)

library(data.table)
dt <- data.table(df, key=c("PatientID", "Year"))

dt[ , list(TRAUMA =    sum(PrimaryConditionGroup=="TRAUMA"),
           PREGNANCY = sum(PrimaryConditionGroup=="PREGNANCY"),
           SEIZURE =   sum(PrimaryConditionGroup=="SEIZURE")),
   by = list(PatientID, Year)]

#      PatientID Year TRAUMA PREGNANCY SEIZURE
# [1,]         1   Y1      1         1       0
# [2,]         2   Y2      0         0       1
# [3,]         3   Y1      1         0       0

EDIT: aggregate() provides a 'base R' solution that might or might not be more idiomatic. (The sole complication is that aggregate returns a matrix, rather than a data.frame; the second line below fixes that up.)

out <- aggregate(PrimaryConditionGroup ~ PatientID + Year, data=df, FUN=table)
out <- cbind(out[1:2], data.frame(out[3][[1]]))

2nd EDIT Finally, a succinct solution using the reshape package gets you to the same place.

library(reshape)
mdf <- melt(df, id=c("PatientID", "Year"))
cast(PatientID + Year ~ value, data=j, fun.aggregate=length)