You can consider cSplit with direction = "long" from my "splitstackshape" package.
Usage would be:
cSplit(mydf, "V2", ",", "long")
## V1 V2
## 1: 1 a
## 2: 1 b
## 3: 1 c
## 4: 2 a
## 5: 2 c
## 6: 3 b
## 7: 3 d
## 8: 4 e
## 9: 4 f
Old answer....
Here is one approach using base R. It assumes we're starting with a data.frame named "mydf". It uses read.csv to read in the second column as a separate data.frame, which we combine with the first column from your source data. Finally, you use reshape to convert the data into a long form.
temp <- data.frame(Ind = mydf$V1,
read.csv(text = as.character(mydf$V2), header = FALSE))
temp1 <- reshape(temp, direction = "long", idvar = "Ind",
timevar = "time", varying = 2:ncol(temp), sep = "")
temp1[!temp1$V == "", c("Ind", "V")]
# Ind V
# 1.1 1 a
# 2.1 2 a
# 3.1 3 b
# 4.1 4 e
# 1.2 1 b
# 2.2 2 c
# 3.2 3 d
# 4.2 4 f
# 1.3 1 c
Another fairly direct alternative is:
stack(
setNames(
sapply(strsplit(mydf$V2, ","),
function(x) gsub("^\\s|\\s$", "", x)), mydf$V1))
values ind
1 a 1
2 b 1
3 c 1
4 a 2
5 c 2
6 b 3
7 d 3
8 e 4
9 f 4
