How to count the number of combinations of boolean data in R - r

Question

What is the best way to determine a factor or create a new category field based on a number of boolean fields? In this example, I need to count the number of unique combinations of medications.
> MultPsychMeds
ID OLANZAPINE HALOPERIDOL QUETIAPINE RISPERIDONE
1 A 1 1 0 0
2 B 1 0 1 0
3 C 1 0 1 0
4 D 1 0 1 0
5 E 1 0 0 1
6 F 1 0 0 1
7 G 1 0 0 1
8 H 1 0 0 1
9 I 0 1 1 0
10 J 0 1 1 0
Perhaps another way to state it is that I need to pivot or cross tabulate the pairs. The final results need to look something like:
Combination Count
OLANZAPINE/HALOPERIDOL 1
OLANZAPINE/QUETIAPINE 3
OLANZAPINE/RISPERIDONE 4
HALOPERIDOL/QUETIAPINE 2
This data frame can be replicated in R with:
MultPsychMeds <- structure(list(ID = structure(1:10, .Label = c("A", "B", "C",
"D", "E", "F", "G", "H", "I", "J"), class = "factor"), OLANZAPINE = c(1L,
1L, 1L, 1L, 1L, 1L, 1L, 1L, 0L, 0L), HALOPERIDOL = c(1L, 0L,
0L, 0L, 0L, 0L, 0L, 0L, 1L, 1L), QUETIAPINE = c(0L, 1L, 1L, 1L,
0L, 0L, 0L, 0L, 1L, 1L), RISPERIDONE = c(0L, 0L, 0L, 0L, 1L,
1L, 1L, 1L, 0L, 0L)), .Names = c("ID", "OLANZAPINE", "HALOPERIDOL",
"QUETIAPINE", "RISPERIDONE"), class = "data.frame", row.names = c(NA,
-10L))

Answer 1

Here's one approach using the reshape and plyr packages:
library(reshape)
library(plyr)
#Melt into long format
dat.m <- melt(MultPsychMeds, id.vars = "ID")
#Group at the ID level and paste the drugs together with "/"
out <- ddply(dat.m, "ID", summarize, combos = paste(variable[value == 1], collapse = "/"))
#Calculate a table
with(out, count(combos))
x freq
1 HALOPERIDOL/QUETIAPINE 2
2 OLANZAPINE/HALOPERIDOL 1
3 OLANZAPINE/QUETIAPINE 3
4 OLANZAPINE/RISPERIDONE 4

Answer 2

Just for fun, a base R solution (that can be turned into a oneliner :-) ):
data.frame(table(apply(MultPsychMeds[,-1], 1, function(currow){
wc<-which(currow==1)
paste(colnames(MultPsychMeds)[wc+1], collapse="/")
})))

Answer 3

Another way could be:
subset(
as.data.frame(
with(MultPsychMeds, table(OLANZAPINE, HALOPERIDOL, QUETIAPINE, RISPERIDONE)),
responseName="count"
),
count>0
)
which gives
OLANZAPINE HALOPERIDOL QUETIAPINE RISPERIDONE count
4 1 1 0 0 1
6 1 0 1 0 3
7 0 1 1 0 2
10 1 0 0 1 4
It's not an exact way you want it, but is fast and simple.
There is shorthand in plyr package:
require(plyr)
count(MultPsychMeds, c("OLANZAPINE", "HALOPERIDOL", "QUETIAPINE", "RISPERIDONE"))
# OLANZAPINE HALOPERIDOL QUETIAPINE RISPERIDONE freq
# 1 0 1 1 0 2
# 2 1 0 0 1 4
# 3 1 0 1 0 3
# 4 1 1 0 0 1