I have a set of variables coded as binomial.
Pre VALUE_1 VALUE_2 VALUE_3 VALUE_4 VALUE_5 VALUE_6 VALUE_7 VALUE_8
1 1 0 0 0 0
A quick solution would be something like
Res <- cbind(df[1], VALUE = factor(max.col(df[-1]), ordered = TRUE))
Res
# Pre VALUE
# 1 1 6
# 2 1 5
# 3 1 5
# 4 1 5
str(Res)
# 'data.frame': 4 obs. of 2 variables:
# $ Pre : int 1 1 1 1
# $ VALUE: Ord.factor w/ 2 levels "5"<"6": 2 1 1 1
OR if you want the actual names of the columns (as Pointed by @BondedDust), you can use the same methodology to extract them
factor(names(df)[1 + max.col(df[-1])], ordered = TRUE)
# [1] VALUE_6 VALUE_5 VALUE_5 VALUE_5
# Levels: VALUE_5 < VALUE_6
OR you can use your own which
strategy in the following way (btw, which
is vectorized so no need in using apply
with a margin of 1 on it)
cbind(df[1], VALUE = factor(which(df[-1] == 1, arr.ind = TRUE)[, 2], ordered = TRUE))
OR you can do matrix
multiplication (contributed by @akrun)
cbind(df[1], VALUE = factor(as.matrix(df[-1]) %*% seq_along(df[-1]), ordered = TRUE))