R-使用功能存储在全球环境中的策略

Question

假设我们有以下数据框架：

# Data
Id <- c(1,2,3,4,5,6,7,8,9,10)
Type <- c("Beginner", "Expert", "Intermediate", "Beginner", 
  "Professional", "Expert", "Intermediate", "Professional", 
  "Professional", "Expert")
Response<- c(1,1,2,2,1,2,1,2,1,1)
Successful <- data.frame(Id, Type, Response)
Successful
# Dataframe
#   Successful
Id  Type             Response    
1   Beginner         1
2   Expert           1
3   Intermediate     2
4   Beginner         2
5   Professional     1
6   Expert           2
7   Intermediate     1
8   Professional     2
9   Professional     1
10  Expert           1

我知道我可以通过执行以下操作在全球环境中将其存储为对象(dfResptype(：

 DFRespType <- 
  as.data.frame(round(100*prop.table(table(Successful$Response, 
                                   Successful$Type),2), 1))

但是，我想创建一个函数，以使对象变得更加有效。下面我尝试使Stordorf函数：

StoreDF <- function(DFName, dataset, variable1, variable2){
  DFName <- as.data.frame(round(100*prop.table(table(dataset$variable1, 
                                              dataset$variable2),2), 1))
}

但是，当我尝试以以下方式使用它时，没有存储任何内容：

StoreDF(DFRespType, Successful, Response, Type)

对此的任何帮助将不胜感激。

Answer 1

不要从函数内部存储对象。而是从功能返回数据框。还使用引用变量来子集数据框架。

StoreDF <- function(dataset, variable1, variable2){
    as.data.frame(round(100* prop.table(table(dataset[[variable1]], 
                        dataset[[variable2]]),2), 1))
}
DFRespType <- StoreDF(Successful, "Response", "Type")
DFRespType
#  Var1         Var2 Freq
#1    1     Beginner 50.0
#2    2     Beginner 50.0
#3    1       Expert 66.7
#4    2       Expert 33.3
#5    1 Intermediate 50.0
#6    2 Intermediate 50.0
#7    1 Professional 66.7
#8    2 Professional 33.3