R 计算计数类别内计数的比例+；依赖于其他分类变量

我希望这个令人费解的标题是有意义的，但我的问题不是那么容易理解

玩具数据集列出了客户访问以及客户豁免状态和访问类型：

df <- structure(list(Customer = structure(c(8L, 2L, 5L, 4L, 4L, 1L, 
1L, 6L, 6L, 7L, 7L, 7L, 3L, 3L, 3L), .Label = c("Aaron", "Elizabeth", 
"Frank", "John", "Mary", "Pam", "Rob", "Sam"), class = "factor"), 
    Exemption = structure(c(2L, 1L, 1L, 2L, 2L, 2L, 2L, 1L, 1L, 
    2L, 2L, 2L, 1L, 1L, 1L), .Label = c("Exempt", "Non-exempt"
    ), class = "factor"), Type = structure(c(1L, 1L, 2L, 1L, 
    2L, 2L, 2L, 2L, 2L, 2L, 2L, 1L, 1L, 1L, 2L), .Label = c("Type 1", 
    "Type 2"), class = "factor")), .Names = c("Customer", "Exemption", 
"Type"), class = "data.frame", row.names = c(NA, -15L))

    Customer  Exemption   Type
1        Sam Non-exempt Type 1
2  Elizabeth     Exempt Type 1
3       Mary     Exempt Type 2
4       John Non-exempt Type 1
5       John Non-exempt Type 2
6      Aaron Non-exempt Type 2
7      Aaron Non-exempt Type 2
8        Pam     Exempt Type 2
9        Pam     Exempt Type 2
10       Rob Non-exempt Type 2
11       Rob Non-exempt Type 2
12       Rob Non-exempt Type 1
13     Frank     Exempt Type 1
14     Frank     Exempt Type 1
15     Frank     Exempt Type 2

---

我用

dplyr

尝试了一些使用

groupby（Customer，Type）%%>%summary（n（））

的方法，但似乎不正确。

你可以使用

count

from

dplyr

来计算

豁免
和
Type
按
访问次数分组的次数：

library(dplyr)
library(tidyr)
res <- df %>% group_by(Customer) %>% 
              mutate(Number_of_visits=n()) %>% 
              group_by(Number_of_visits) %>% 
              count(Exemption, Type) %>%
              complete(Type, fill=list(n=0)) %>%
              group_by(Number_of_visits,Exemption) %>% 
              mutate(Proportion=n/sum(n))

客户
在预期输出中去了哪里？@mtoto：在预期输出中，访问次数将客户折叠为计数，例如，当
访问次数=1时，这对应于列表中的三个客户（Sam、Elizabeth、Mary）。其中一个是非豁免的1型，因此相应的
比例=1
。另外两个是免税的，一个是1型，一个是2型，所以比例各为0.5。
library(dplyr)
library(tidyr)
res <- df %>% group_by(Customer) %>% 
              mutate(Number_of_visits=n()) %>% 
              group_by(Number_of_visits) %>% 
              count(Exemption, Type) %>%
              complete(Type, fill=list(n=0)) %>%
              group_by(Number_of_visits,Exemption) %>% 
              mutate(Proportion=n/sum(n))

print(res)
##Source: local data frame [12 x 5]
##Groups: Number_of_visits, Exemption [6]
##
##   Number_of_visits  Exemption   Type     n Proportion
##              <int>     <fctr> <fctr> <dbl>      <dbl>
##1                 1     Exempt Type 1     1  0.5000000
##2                 1     Exempt Type 2     1  0.5000000
##3                 1 Non-exempt Type 1     1  1.0000000
##4                 1 Non-exempt Type 2     0  0.0000000
##5                 2     Exempt Type 1     0  0.0000000
##6                 2     Exempt Type 2     2  1.0000000
##7                 2 Non-exempt Type 1     1  0.2500000
##8                 2 Non-exempt Type 2     3  0.7500000
##9                 3     Exempt Type 1     2  0.6666667
##10                3     Exempt Type 2     1  0.3333333
##11                3 Non-exempt Type 1     1  0.3333333
##12                3 Non-exempt Type 2     2  0.6666667