I have a data.frame object which I obtain by converting an object of class rules into data.frame in this way:
trx.cpf.rules.df <- as(trx.cpf.rules, "data.frame")
(You can build the trx.cpf.rules.df object from the structure dputed here).
The head of this data frame looks like this:
> head(trx.cpf.rules.df)
rules support confidence lift
66 {Product_Group_1,Product_Group_49} => {Product_Group_48} 0.1060016 0.7371274 6.683635
12 {Product_Group_48} => {Product_Group_49} 0.1067810 0.9681979 6.386621
68 {Product_Group_1,Product_Group_23} => {Product_Group_49} 0.1079501 0.9052288 5.971252
16 {Product_Group_23} => {Product_Group_49} 0.1098987 0.8392857 5.536265
71 {Product_Group_1,Product_Group_23} => {Product_Group_34} 0.1024942 0.8594771 4.702384
19 {Product_Group_34} => {Product_Group_23} 0.1079501 0.5906183 4.510496
Is there a fast way (dedicated function or sth like that) to convert each of the trx.cpf.rules.df$rules into two vectors contatining relue;s element? For example, for the first row it would be:
> (lhs.el <- c("Product_Group_1", "Product_Group_49"))
[1] "Product_Group_1" "Product_Group_49"
> (rhs.el <- c("Product_Group_48"))
[1] "Product_Group_48"
This will give you a list structure with lhs/rhs vectors:
l <- lapply( strsplit(as.character(trx.cpf.rules.df$rules), " => ", fixed = TRUE), function(x) {
strsplit( gsub("[{}]", "", x), ",", fixed = TRUE)
})
To inspect the first rule:
l[[1]]
# [[1]]
# [1] "Product_Group_1" "Product_Group_49"
#
# [[2]]
# [1] "Product_Group_48"
To inspect the left-hand-sides of all rules (head):
head(sapply(l, "[", 1))
# [[1]]
# [1] "Product_Group_1" "Product_Group_49"
#
# [[2]]
# [1] "Product_Group_48"
#
# [[3]]
# [1] "Product_Group_1" "Product_Group_23"
#
# [[4]]
# [1] "Product_Group_23"
#
# [[5]]
# [1] "Product_Group_1" "Product_Group_23"
#
# [[6]]
# [1] "Product_Group_34"