如何将数据框重塑为分类数据的百分比

Question

我有一个包含纵向信息（长格式）的数据框。

mydata<-structure(list(record_id = c("a", "a", "a", "b", "b", "b", "c", "c","c"),event = structure(c(1L, 2L, 3L, 1L, 2L, 3L, 1L, 2L, 3L), .Label =c("e2", "e3", "e4"), class = "factor"), var1 = structure(c(2L, 1L, 1L, 1L,1L, 1L, 1L, 1L, 1L), .Label = c("no", "yes"), class = "factor"),var2 =structure(c(1L, 1L, 1L, 2L, 2L, 1L, 1L, 1L, 1L), .Label = c("no", "yes"), class = "factor"), var3 = structure(c(2L, 2L, 1L, 2L, 2L, 1L, 1L, 1L, 1L),.Label = c("no", "yes"), class = "factor")), row.names = c(NA, -9L), class= c("tbl_df", "tbl", "data.frame"))

而且我需要将这些数据转换成一个数据框，以根据事件（e2，e3，e4）总结每个变量（var1，var2，var3）的“是”计数的百分比，以具有如下所示的内容：

mydata_result<-structure(list(Event = structure(c(1L, 1L, 1L, 2L, 2L, 2L,3L, 3L, 3L), .Label = c("e2", "e3", "e4"), class = "factor"), Variable =structure(c(1L, 2L, 3L, 1L, 2L, 3L, 1L, 2L, 3L), .Label = c("var1", "var2", "var3"), class = "factor"), percentage_of_yes = c(0.33, 0.33, 0.66, 0, 0.33, 0.66, 0, 0, 0)), row.names = c(NA, -9L), class = c("tbl_df", "tbl","data.frame"))

谢谢！

Answer 1

使用tidyverse ，我们可以转换为长格式，按变量和事件分组，然后进行百分比计数，即

library(tidyverse)

mydata %>% 
  gather(var, val, -c(1:2)) %>% 
  group_by(event, var) %>% 
  summarise(new = sum(val == 'yes')/n())

这使，

 # A tibble: 9 x 3 # Groups: event [?] event var new <fct> <chr> <dbl> 1 e2 var1 0.333 2 e2 var2 0.333 3 e2 var3 0.667 4 e3 var1 0 5 e3 var2 0.333 6 e3 var3 0.667 7 e4 var1 0 8 e4 var2 0 9 e4 var3 0 

Answer 2

这是data.table的替代data.table

library(data.table)
melt(setDT(mydata), id.vars = c("record_id", "event"))[, 
 .(percentage_of_yes = round(mean(value == "yes"), 3)), 
        .(event, Variable = variable)]
#    event Variable percentage_of_yes
#1:    e2     var1             0.333
#2:    e3     var1             0.000
#3:    e4     var1             0.000
#4:    e2     var2             0.333
#5:    e3     var2             0.333
#6:    e4     var2             0.000
#7:    e2     var3             0.667
#8:    e3     var3             0.667
#9:    e4     var3             0.000