Simply use aggregate
:
aggregate(df$text, list(df$group), paste, collapse="")
## Group.1 x
## 1 a a1a2a3
## 2 b b1b2
## 3 c c1c2c3
Or with plyr
library(plyr)
ddply(df, .(group), summarize, text=paste(text, collapse=""))
## group text
## 1 a a1a2a3
## 2 b b1b2
## 3 c c1c2c3
ddply
is faster than aggregate
if you have a large dataset.
EDIT :
With the suggestion from @SeDur :
aggregate(text ~ group, data = df, FUN = paste, collapse = "")
## group text
## 1 a a1a2a3
## 2 b b1b2
## 3 c c1c2c3
For the same result with earlier method you have to do :
aggregate(x=list(text=df$text), by=list(group=df$group), paste, collapse="")
EDIT2 : With data.table
:
library("data.table")
dt <- as.data.table(df)
dt[, list(text = paste(text, collapse="")), by = group]
## group text
## 1: a a1a2a3
## 2: b b1b2
## 3: c c1c2c3
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