Question

我有一个设定的数据框。我的目的是将数据框转换为交易数据，以便使用R中的Arules包进行市场购物篮分析。我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（How to prep transaction data into basket for arules）和（{{3 }}，但我得到的结果是不同的。

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))

以下是我的数据框架结构

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

每列的类

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

将数据框转换为交易数据

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}

交易数据已成功转换，但我想知道有没有办法删除NA项目？因为如果NA仍然留在交易清单中，NA将作为项目考虑。

Answer 1

我可以向你提出这个解决方案，但我不知道你是否正在寻找。

<强> 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)))

每列的类 请注意，classe都是“因子”

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

将数据框转换为交易数据

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

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

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

奥古斯塔是对的。以下是处理事务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）将数据帧转换为事务并删除NA

2 个答案: