R - apriori() not recognising lhs from numerical transaction - r

Question

I am having real trouble getting my data to produce any rules using the arules package. I have managed to get 100000 rows of transaction data and in SAS the rules are shown. I cannot get it to work in R.
[5] {19,29,40,119,134}
[6] {24,40,45,67,141}
[7] {17,18,57,74,412}
[8] {16,79,90,150,498}
[9] {18,57,111,161,267}
[10] {11,75,131,427,429}
[11] {57,99,111,143,236}
The transactions data looks like this and originally came from a table where all the numbers were separate.
arules <- read.transactions('tid.csv', format = c("basket", "single"),
sep=",")
rules <- apriori(arules,parameter = list(supp = 0.1, conf = 0.1, target =
"rules"))
summary(rules)
For reference the supports and confidence settings make no difference. Sometimes I get this when I inspect the rules.
lhs rhs support confidence lift count
[1] {} => {8,11,96,112,432} 9.710623e-06 9.710623e-06 1 1
[2] {} => {62,134,222,254,412} 9.710623e-06 9.710623e-06 1 1
Any idea why apriori can't separate the items in the transaction? Does this need to be recast into long format and if so how would I do that form this data frame?
V2 V3 V4 V5 V6
8 11 96 112 432
10 35 39 76 119
18 38 68 141 267
29 36 57 61 63
19 29 40 119 134
24 40 45 67 141
17 18 57 74 412

Answer 1

If I understood you correctly then you should try this and let us know if it helped.
library(arules)
library(arulesViz)
#sample data
df <- read.table(text="V2 V3 V4 V5 V6
8 11 96 112 432
10 35 39 76 119
18 38 68 141 267
29 36 57 61 63
19 29 40 119 134
24 40 45 67 141
17 18 57 74 412", header=T)
write.csv(df, "apriori_demo.csv", row.names = F)
#convert sample data into transactions format for apriori algorithm
trx <- read.transactions("apriori_demo.csv", format="basket", sep=",", skip=1)
#apriori rules
apriori_rule <- apriori(trx, parameter = list(supp = 0.1, conf = 0.1))
#obviously you need to have better parameters compared to the one you have used in your post!
inspect(apriori_rule)
plot(apriori_rule, method="graph")