R: manipulating data.frames containing strings and booleans

I have a data.frame in R; it's called p. Each element in the data.frame is either True or False. My variable p has, say, m rows and n columns. For every row there is strictly only one TRUE element.

It also has column names, which are strings. What I would like to do is the following:

1. For every row in p I see a TRUE I would like to replace with the name of the corresponding column
2. I would then like to collapse the data.frame, which now contains FALSEs and column names, to a single vector, which will have m elements.
3. I would like to do this in an R-thonic manner, so as to continue my enlightenment in R and contribute to a world without for-loops.

I can do step 1 using the following for loop:

for (i in seq(length(colna开发者_Go百科mes(p)))) {
    p[p[,i]==TRUE,i]=colnames(p)[i]
}

but theres's no beauty here and I have totally subscribed to this for-loops-in-R-are-probably-wrong mentality. Maybe wrong is too strong but they're certainly not great.

I don't really know how to do step 2. I kind of hoped that the sum of a string and FALSE would return the string but it doesn't. I kind of hoped I could use an OR operator of some kind but can't quite figure that out (Python responds to False or 'bob' with 'bob'). Hence, yet again, I appeal to you beautiful Rstats people for help!

Here's some sample data:

df <- data.frame(a=c(FALSE, TRUE, FALSE), b=c(TRUE, FALSE, FALSE), c=c(FALSE, FALSE, TRUE))

You can use apply to do something like this:

names(df)[apply(df, 1, which)]

Or without apply by using which directly:

idx <- which(as.matrix(df), arr.ind=T)
names(df)[idx[order(idx[,1]),"col"]]

Use apply to sweep your index through, and use that index to access the column names:

> df <- data.frame(a=c(TRUE,FALSE,FALSE),b=c(FALSE,FALSE,TRUE),
+                  c=c(FALSE,TRUE,FALSE))
> df
      a     b     c
1  TRUE FALSE FALSE
2 FALSE FALSE  TRUE
3 FALSE  TRUE FALSE
> colnames(df)[apply(df, 1, which)]
[1] "a" "c" "b"
>