将 Dplyr Join 和 Set 操作合并到自定义函数中

Question

我有下面两个简单的数据框。我想使用 dplyr 和 tidyverse 来查找第二个数据帧（Df2）的“Task2”中不在第一个数据帧（Df）的“Task”中的类别。我想为此使用 dplyr 的“setdiff”功能。另外，我想保留第二个数据帧（Df2）的“时间”列中的相应时间。

因此，最终产品应包括两行，一排为客户“Chris”的“Iron shirt”，总时间为 30 次，一排为客户“Eric”，带有“Buy groceries”，以及对应的时间为 8。

我还想删除日期列。

我在想一种方法是使用 dplyr 的“setdiff”函数（我意识到必须更改 Task 和 Task2 列名以便它们匹配）将两行分开，然后重新加入总数加入函数的时间。

最后，我希望这是一个自定义函数，因为我将不得不重复执行此任务。我想要一个像“Differences(Df1,Df2)”这样的函数......所以我可以输入两个数据帧，然后得到结果。

我希望这不是要求太多！我是自定义函数的新手，尤其是包含 dplyr 和管道的函数。

希望有人可以帮助我！

CaseWorker<-c("John","John","Kim")

Client<-c("Chris","Chris","Eric")

Task<-c("Feed cat","Make dinner","Do homework")

Date<-c("10/27/2016","09/22/2016","10/11/2016")

Df<-data.frame(CaseWorker,Client,Date,Task)

第二个数据帧...

CaseWorker<-c("John","John","John","John","John","John","John","John","John",
          "John","Kim","Kim","Kim")

Client<-c("Chris","Chris","Chris","Chris","Chris","Chris","Chris","Chris","Chris","Chris","Eric","Eric","Eric")

Date<-c("11/10/2016","10/10/2016","11/13/2016","09/18/2016","11/11/2016","09/19/2016","08/08/2016","10/10/2016","08/05/2016","11/12/2016","09/09/2016","11/11/2016","09/10/2016")

Task2<-c("Feed cat","Feed cat","Feed cat","Feed cat","Feed cat","Make dinner","Make dinner","Make dinner","Iron shirt","Iron shirt","Do homework",
"Do homework","Buy groceries")

Time<-c(20,34,11,10,5,6,55,30,20,10,12,10,8)

Df2<-data.frame(CaseWorker,Client,Date,Task2,Time)

Answer 1

我们可以使用anti_join

library(dplyr)
anti_join(Df2, Df, by = c("Task2"="Task")) %>%
         group_by(CaseWorker,Client, Task2) %>% 
         summarise(Time = sum(Time))
#    CaseWorker Client         Task2  Time
#        <fctr> <fctr>        <fctr> <dbl>
#1       John  Chris    Iron shirt    30
#2        Kim   Eric Buy groceries     8

如果我们需要转换为函数

DiffGoals <- function(dat1, dat2) {
            anti_join(dat1, dat2, by = c("Task2" = "Task")) %>%
                   group_by(CaseWorker, Client, Task2) %>%
                   summarise(Time = sum(Time))
 }

DiffGoals(Df2, Df)