Flattening a delimited composite column

Question

I got a data frame in R where one of the fields is composite (delimited). Here\'s an example of what I got:

users=c(1,2,3)
items=c(\"23 77 49\", \"10 18 28\"         


        

Answer 1

items <- strsplit(df$items, " ")
data.frame(user = rep(df$users, sapply(items, length)), item = unlist(items))

##   user item                                                                                                                                                                                                                                
## 1    1   23                                                                                                                                                                                                                                
## 2    1   77                                                                                                                                                                                                                                
## 3    1   49                                                                                                                                                                                                                                
## 4    2   10                                                                                                                                                                                                                                
## 5    2   18                                                                                                                                                                                                                                
## 6    2   28                                                                                                                                                                                                                                
## 7    3   20                                                                                                                                                                                                                                
## 8    3   31                                                                                                                                                                                                                                
## 9    3   84  

or

library(data.table)

DT <- data.table(df)    
DT[, list(item = unlist(strsplit(items, " "))), by = users]

##    users item                                                                                                                                                                                                                              
## 1:     1   23                                                                                                                                                                                                                              
## 2:     1   77                                                                                                                                                                                                                              
## 3:     1   49                                                                                                                                                                                                                              
## 4:     2   10                                                                                                                                                                                                                              
## 5:     2   18                                                                                                                                                                                                                              
## 6:     2   28                                                                                                                                                                                                                              
## 7:     3   20                                                                                                                                                                                                                              
## 8:     3   31                                                                                                                                                                                                                              
## 9:     3   84