R（arules）将数据框转换为事务并删除 NA

Question

我有一组数据框。我的目的是将数据框转换为交易数据，以便使用 R 中的 Arules 包进行购物篮分析。我确实在网上做了一些关于将数据框转换为交易数据的研究，例如（) and (），但结果我得到的是不同的。

dput(df)

structure(list(Transaction_ID = c("A001", "A002", "A003", "A004", "A005", "A006"), 
Fruits = c(NA, "Apple", "Orange", NA, "Pear", "Grape"), 
Vegetables = c(NA, NA, NA, "Potato", NA, "Yam"), 
Personal = c("ToothP", "ToothP", NA, "ToothB", "ToothB", NA), 
Drink = c("Coff", NA, "Coff", "Milk", "Milk", "Coff"), 
Other = c(NA, NA, NA, NA, "Promo", NA)), 
.Names = c("Transaction_ID", "Fruits", "Vegetables", "Personal", "Drink", "Other"), 
class = c("tbl_df", "tbl", "data.frame"), row.names = c(NA, -6L))

下面是我的数据帧结构

Transaction_ID  Fruits  Vegetables  Personal  Drink  Other
      A001        NA        NA       ToothP   Coff    NA
      A002       Apple      NA       ToothP    NA     NA
      A003      Orange      NA         NA     Coff    NA
      A004        NA      Potato     ToothB   Milk    NA
      A005       Pear       NA       ToothB   Milk   Promo
      A006      Grape      Yam         NA     Coff    NA

class 每列

sapply(df, class)
Transaction_ID         Fruits     Vegetables       Personal          Drink          Other 
"character"    "character"    "character"    "character"    "character"    "character"

将数据帧转换为交易数据

data <- as(split(df[,"Fruits"], df[,"Vegetables"],df[,"Personal"], df[,"Drink"], df[,"Other"]), "transactions")
inspect(data)

我得到的结果

[1] {NA,NA,ToothP,Coff,NA}
[2] {Apple,NA,ToothP,NA,NA}
[3] {Orange,NA,NA,Coff,NA}
[4] {NA,Potato,ToothB,Milk,NA}
[5] {Pear,NA,ToothB,Milk,Promo}
[6] {Grape,Yam,NA,Coff,NA}

交易数据转换成功，但请问有什么方法可以去掉NA项吗？因为如果它们仍然保留在交易列表中，NA 会将其视为一个项目。

Answer 1

我可以向您推荐这个解决方案，但我不知道这是否是您正在寻找的解决方案。

dput(df)

df <- data.frame(structure(list(Transaction_ID = as.factor(c("A001", "A002", "A003", "A004", "A005", "A006")), 
               Fruits = as.factor(c(NA, "Apple", "Orange", NA, "Pear", "Grape")), 
               Vegetables = as.factor(c(NA, NA, NA, "Potato", NA, "Yam")), 
               Personal = as.factor(c("ToothP", "ToothP", NA, "ToothB", "ToothB", NA)), 
               Drink = as.factor(c("Coff", NA, "Coff", "Milk", "Milk", "Coff")), 
               Other = as.factor(c(NA, NA, NA, NA, "Promo", NA))), 
          .Names = c("Transaction_ID", "Fruits", "Vegetables", "Personal", "Drink", "Other"), 
          class = c("tbl_df", "tbl", "data.frame"), row.names = c(NA, -6L)))

Class 每列 注意classe都是"Factor"

sapply(df, class)
Transaction_ID         Fruits     Vegetables       Personal          Drink          Other 
      "factor"       "factor"       "factor"       "factor"       "factor"       "factor"

将数据帧转换为交易数据

data <- as(df, "transactions")
inspect(data)

我得到的结果

     items                 transactionID
[1] {Transaction_ID=A001,              
     Personal=ToothP,                  
     Drink=Coff}                      1
[2] {Transaction_ID=A002,              
     Fruits=Apple,                     
     Personal=ToothP}                 2
[3] {Transaction_ID=A003,              
     Fruits=Orange,                    
     Drink=Coff}                      3
[4] {Transaction_ID=A004,              
     Vegetables=Potato,                
     Personal=ToothB,                  
     Drink=Milk}                      4
[5] {Transaction_ID=A005,              
     Fruits=Pear,                      
     Personal=ToothB,                  
     Drink=Milk,                       
     Other=Promo}                     5
[6] {Transaction_ID=A006,              
     Fruits=Grape,                     
     Vegetables=Yam,                   
     Drink=Coff}                      6

我在这里 convert data frame in r to transaction or an itemMatrix 找到了部分解决方案。而且似乎你的命令

data <- as(split(df[,"Fruits"], df[,"Vegetables"],df[,"Personal"], df[,"Drink"], df[,"Other"]), "transactions")
inspect(data)

仅适用于仅包含两列的 data.frame。

Answer 2

奥古斯塔里是对的。这是同时处理事务 ID 的完整代码。

library("arules")
library("dplyr")  ### for dbl_df
df <- structure(list(Transaction_ID = c("A001", "A002", "A003", "A004", "A005", "A006"), 
  Fruits = c(NA, "Apple", "Orange", NA, "Pear", "Grape"), 
  Vegetables = c(NA, NA, NA, "Potato", NA, "Yam"), 
  Personal = c("ToothP", "ToothP", NA, "ToothB", "ToothB", NA), 
  Drink = c("Coff", NA, "Coff", "Milk", "Milk", "Coff"), 
  Other = c(NA, NA, NA, NA, "Promo", NA)), 
  .Names = c("Transaction_ID", "Fruits", "Vegetables", "Personal", "Drink", "Other"), 
  class = c("tbl_df", "tbl", "data.frame"), row.names = c(NA, -6L))

### remove transaction IDs
tid <- as.character(df[["Transaction_ID"]])
df <- df[,-1]

### make all columns factors
for(i in 1:ncol(df)) df[[i]] <- as.factor(df[[i]])

trans <- as(df, "transactions")

### set transactionIDs
transactionInfo(trans)[["transactionID"]] <- tid

inspect(trans)

   items                                          transactionID
[1] {Personal=ToothP,Drink=Coff}                   A001         
[2] {Personal=ToothP}                              A002         
[3] {Drink=Coff}                                   A003         
[4] {Vegetables=Potato,Personal=ToothB,Drink=Milk} A004         
[5] {Personal=ToothB,Drink=Milk,Other=Promo}       A005         
[6] {Vegetables=Yam,Drink=Coff}                    A006

R（arules）将数据框转换为事务并删除 NA

R (arules) Convert dataframe into transactions and remove NA

r

dataframe

transactions

na

arules