dcast() - 添加 R 中不存在的列

Question

我遇到了一个问题，我确信有一个简单的解决方案，但我找不到它。我基本上总结了我的表格以获得因子变量的每个级别的值的总和：

 NOdependants <- unique(claimsMonthly[policyID == policy, .(exposure = sum(exposure)),
                                        by = c("productID", "Year", "product", "QualityCheck", "dependant")][order(Year)])

   productID       Year product QualityCheck dependant exposure
1:           1      2016  ELI18            0  EMPLOYEE 17.041096
2:           1      2016  ELI18            0    SPOUSE 40.484932
3:           1      2016  ELI18            0     CHILD 5.164384

然后我执行以下操作：

NOdependants <- dcast(NOdependants,  productID + Year ~ dependant, value.var = "exposure", fill = 0, drop = FALSE, fun.aggregate = sum)
setnames(NOdependants, c("CHILD", "EMPLOYEE", "SPOUSE"), c("childno", "employeeno", "spouseno"), skip_absent=TRUE)

> NOdependants
   productRank startYear  childno employeeno spouseno
1:           1      2016 5.164384   17.041096 41.484932

到目前为止，一切都很好。问题是当产品没有关于依赖因素之一的任何数据时。假设没有孩子：

 NOdependants <- unique(claimsMonthly[policyID == policy, .(exposure = sum(exposure)),
                                        by = c("productID", "Year", "product", "QualityCheck", "dependant")][order(Year)])

   productID       Year product QualityCheck dependant exposure
1:           1      2016  ELI18            0  EMPLOYEE 17.041096
2:           1      2016  ELI18            0    SPOUSE 40.484932

然后我的 dcast 执行以下操作：

> NOdependants
   productRank startYear  employeeno spouseno
1:           1      2016  17.041096 41.484932

这对我来说是个问题，我需要拥有所有三列。所以我需要的是人为地创建一个额外的列，以防因子级别没有数据（比如这里的孩子），所以我会得到这样的东西：

> NOdependants
   productRank startYear  childno employeeno spouseno
1:           1      2016       0   17.041096 41.484932

现在我已经创建了一个工作区，我首先创建一个空的 data.table，然后使用 rbindlist 和 fill=0 合并这些论文，但必须有一些更简单的解决方案。

有什么想法吗？

注意：我正在处理大量数据，并且此操作是循环的一部分，该循环将重复大约 80 次左右，因此理想情况下可以实现高效。

带有数据的简化示例：

#

> claimsMonthly <- data.table(productID = c(rep(1,6), rep(2,3), rep(3,2)),
+                      Year = c(rep(2015,9), 2016, 2016),
+                      product = c(rep("ELI18",6), rep("JCI22",3), rep("ZDP01",2)),
+                      dependant = c(rep(c("EMPLOYEE", "SPOUSE", "CHILD"), 3),"EMPLOYEE", "SPOUSE"),
+                      QualityCheck = c(rep(0,11)),
+                      exposure = c(abs(rnorm(11))))
> 
> productIDs <- unique(claimsMonthly$productID)
> for(prod in productIDs){
+  
+   NOdependants <- unique(claimsMonthly[ productID == prod, .(exposure = sum(exposure)),
+                                         by = c("productID", "Year", "product", "QualityCheck", "dependant")][order(Year)])
+   
+   NOdependants <- dcast(NOdependants,  productID + Year ~ dependant, value.var = "exposure", fill = 0, drop = FALSE, fun.aggregate = sum)
+   setnames(NOdependants, c("CHILD", "EMPLOYEE", "SPOUSE"), c("childno", "employeeno", "spouseno"), skip_absent=TRUE) 
+ 
+   NOdependants[order(childno)]
+     
+ }
Error in .checkTypos(e, names_x) : 
  Object 'childno' not found amongst productID, Year, employeeno, spouseno

Answer 1

您在 data.table 括号之外使用“唯一”可能会使 data.table 感到困惑。请看：https://www.rdocumentation.org/packages/data.table/versions/1.12.8/topics/duplicated

我想知道您的代码是否可以更简单并同样达到您的结果。 rdata.table 的一些优点在于它能够消除对循环和控制结构的需求。将您的示例数据用于“claimsMonthly”：

claimsMonthly[, .(exposure = sum(exposure)),
.(productID,Year,product,QualityCheck,dependant)][
,dcast(.SD, productID + Year ~ dependant,
value.var = "exposure", drop = FALSE, fun.aggregate = sum)][
         CHILD == 0 &
         EMPLOYEE == 0 &
         SPOUSE == 0,.(productID,Year,CHILD,EMPLOYEE,SPOUSE)]

       productID Year CHILD EMPLOYEE SPOUSE
    1:         1 2016     0        0      0
    2:         2 2016     0        0      0
    3:         3 2015     0        0      0