Expanding data.frame rows based on single field - r

Question

I have a simple data set in the form:
From,To,Date,Subject
I would like to reshape this data such that lines as:
e1,e2;e3;e4,d1,s1
Get expanded too:
e1,e2,d1,s1
e1,e3,d1,s1
e1,e4,d1,s1
Now, I get this done with a for loop over my data frame and constructing a new one on the fly, but I wondered if there is more "R"-way of doing this?
Edit:
This is what I currently have, it works but is kind of ugly (and showing my still somewhat limited R-skills):
filteredEmailsExpanded <- NULL
toCol <- 2
for (row in 1:nrow(filteredEmails)) {
receivers <- sapply(strsplit(filteredEmails[row, toCol], ","), function(x) gsub(" ", "", ))
for (receiver in receivers) {
newRow <- rep(filteredEmails[row,], times = 1)
newRow$To <- receiver
rbind(filteredEmailsExpanded, newRow)
}
}

Answer 1

How about you first expand your data frame (call it d), repeating the ith row n(i) times, where n(i) is the number of occurences of ';' in d$To[i], and then you replace d$To by these occurences? I've added an extra row to your example data to illustrate this better
d <- data.frame(
From = c("e1", "e5"),
To = c("e2;e3;e4", "e6;e7"),
Date = c("d1", "d2"),
Subject = c("s1", "s2"),
stringsAsFactors = FALSE)
v <- strsplit(d$To, ";")
lengths <- sapply(v, length)
d <- d[rep(1:nrow(d), lengths), ]
d$To <- unlist(v)

Answer 2

You may want to look at my "splitstackshape" package, in particular, the function concat.split.multiple which has a "long" argument.
Using #konvas's sample data, try:
library(splitstackshape)
concat.split.multiple(d, "To", ";", "long")
# From Date Subject time To
# 1 e1 d1 s1 1 e2
# 2 e5 d2 s2 1 e6
# 3 e1 d1 s1 2 e3
# 4 e5 d2 s2 2 e7
# 5 e1 d1 s1 3 e4
# 6 e5 d2 s2 3 <NA>
Alternatively, check out its successor function (which hasn't yet made it into the package). The successor is presently called cSplit and is available as a Gist. It is much faster but just as easy to use:
## cSplit(indt = d, splitCols = "To", sep = ";", direction = "long")
cSplit(d, "To", ";", "long")
# From To Date Subject
# 1: e1 e2 d1 s1
# 2: e1 e3 d1 s1
# 3: e1 e4 d1 s1
# 4: e5 e6 d2 s2
# 5: e5 e7 d2 s2