R 规则为交易准备数据集

Question

我准备了一个数据集，用于使用 R 中的 arules 包将其作为事务读取。但是，当我使用命令 itemFrequencyplot 时，我的一个数据预处理导致了一个问题，具体来说，频率最高的项目是“” .有没有人有解决这个问题的建议？

原始数据：

data <- as.data.frame(matrix(NA, nrow = 10, ncol = 3))
colnames(data) <- c("Customer", "OrderDate", "Product")
data$Customer <- c("John", "John", "John", "Tom", "Tom", "Tom", "Sally", "Sally", "Sally", "Sally")
data$OrderDate <- c("1-Oct", "2-Oct", "2-Oct", "2-Oct","2-Oct", "2-Oct", "3-Oct", "3-Oct", "3-Oct", "3-Oct")
data$Product <- c("Milk", "Eggs", "Bread", "Butter", "Eggs", "Milk", "Bread", "Butter", "Eggs", "Wine")

我做如下改造

library(reshape2)
library(dplyr)

newdata <- data  %>% 
  group_by(Customer, OrderDate) %>%
  mutate(ProductValue = paste0("Product", 1:n()) ) %>%
  dcast(Customer + OrderDate ~ ProductValue, value.var = "Product") %>%
  arrange(OrderDate)

newdata[is.na(newdata)] <- " "
newdata <- newdata[ , 3:6]
newdata[sapply(newdata, is.character)] <- lapply(newdata[sapply(newdata, is.character)], as.factor) #converting is.character columns into as.factor

使用write.table创建不带列名的csv文件以通过arules读取

write.table(newdata, "transactions.csv", row.names = FALSE, col.names = FALSE, sep = ",")

使用arules包读取csv文件作为交易

library(arules)

transactiondata <- read.transactions("transactions.csv", sep = ",", format = "basket")

不起作用 - 抛出错误，在阅读了之前关于 Whosebug 的查询后，我能够按如下方式解决它

transactiondata <- read.transactions("transactions.csv", sep = ",", format = "basket", rm.duplicates = TRUE)

itemFrequencyPlot(transactiondata, topN = 5)

该图的结果将“ ”列为频率最高的项目，但实际上并非如此，这是我对数据进行预处理的结果。解决问题的建议将不胜感激！

Answer 1

我会这样做（遵循事务手册页中的示例）：

data_list <- split(data$Product, paste(data$OrderDate, data$Customer))
trans <- as(data_list, "transactions")
inspect(trans)

    items                    transactionID
[1] {Milk}                   1-Oct John   
[2] {Bread,Eggs}             2-Oct John   
[3] {Butter,Eggs,Milk}       2-Oct Tom    
[4] {Bread,Butter,Eggs,Wine} 3-Oct Sally

itemFrequencyPlot(trans, topN = 5)

希望对您有所帮助！

R 规则为交易准备数据集

R arules preparing dataset for transactions

r

transactions

arules