Apriori gerando csv.txt

#Install needed packages
install.packages("arules")
install.packages("arulesViz")
install.packages("igraph")

#Load needed libraries 
library(arules)
library(arulesViz)
library(datasets)
library(igraph)

#options(digits=2)

#Change R directory to the files folder 
setwd("C:\\Projetos Alterix\\Nissei\\Nissei_NovaEntrega")

#Obsolete, don't use it.
#Read cluster data
#data <- read.csv("Cluster1.csv")

#Obsolete, don't use it.
#Transform basket_no to factor to showed as string
#data$basket_no <- as.factor(data$basket_no)

#Obsolete, don't use it.
#Get unique data from dataset, it is required to analysis.
#data <- unique(data)

#Obsolete, don't use it.
#Transform dataset to transactions data type
#cluster <- as(split(data[,"CLS_ID_DS"], data[,"basket_no"]), "transactions")

#The dataframe can be in either a normalized (single) form or a flat file (basket) form.
#When the file is in basket form it means that each record represents a transaction where the items in the basket are represented by columns.
#When the dataset is in single form it means that each record represents one single item and each item contains a transaction id.
cluster <- read.transactions("Base para Analise_Fralda.txt", format = "single", sep = ";", cols = c("lojacupom", "produto"), rm.duplicates = "true")

#Get the association rules with support = 0.01% and confidence = 1%
rules <- apriori(cluster, parameter = list(supp = 0.01, conf = 0.01))

#Sort rules by confidence
rules <- sort(rules, decreasing=TRUE,by="confidence")

#Show rules
inspect(rules)

#Transform data from transaction data type to data.frame
df <- as(rules, "data.frame")

#Create csv file with the association rules.
write.table(df, file = "Analise_geral_abril.csv", sep=";", row.names=FALSE)

#Create imagem from graph rules
png(filename = "cluster15.png" )
plot(rules,method="graph",interactive=FALSE)
dev.off()