R同时使用melt（）和dcast（）以及分类和数值变量

Question

我是使用R编程的新手，这是我在Stackoverflow上遇到的第一个问题。

假设我有一个包含4列的数据框：（1）个人编号（数字）；（2）个人的道德（因素）；（3）城市（因素）；（4）拥有的书数（数字）。

Person_ID <- c(1,2,3,4,5,6,7,8,9,10) 
Morality <- c("Bad guy","Bad guy","Bad guy","Bad guy","Bad guy",
          "Good guy","Good guy","Good guy","Good guy","Good guy") 
City <- c("NiceCity", "UglyCity", "NiceCity", "UglyCity", "NiceCity", 
         "UglyCity", "NiceCity", "UglyCity", "NiceCity", "UglyCity") 
Books <- c(0,3,6,9,12,15,18,21,24,27)
mydf <- data.frame(Person_ID, City, Morality, Books)

我正在使用此代码来获取每个城市中变量Morality的每个类别的计数：

mycounts<-melt(mydf,
               idvars = c("City"),
               measure.vars = c("Morality"))%>%
  dcast(City~variable+value,
        value.var="value",fill=0,fun.aggregate=length)

代码使用总和给出这种表：

names(mycounts)<-gsub("Morality_","",names(mycounts))
mycounts
      City Bad guy Good guy
1 NiceCity       3        2
2 UglyCity       2        3

我想知道是否有类似的方法将dcast()用于数字变量（在同一脚本内），例如为了求和每个城市中所有个人拥有的Books：

#> City Bad guy Good guy Books#>1 NiceCity 3 2 [Total number of books in NiceCity]#>2 UglyCity 2 3 [Total number of books in UglyCity]

Answer 1

您的意思是这样的吗：

mydf %>% 
  melt(
    idvars = c("City"),
    measure.vars = c("Morality")
  ) %>%
  dcast(
    City ~ variable + value,
    value.var = "Books", 
    fill = 0,
    fun.aggregate = sum
  )
#>       City Morality_Bad guy Morality_Good guy
#> 1 NiceCity               18                42
#> 2 UglyCity               12                63