r - 根据是否满足 tidyverse 的一系列条件对类别进行分组

Question

我有一个关于如何根据变量是否满足特定条件重新分类的问题。也就是说，如果该类别不符合标准，它将被分配到另一个符合标准的类别。

我的数据具有以下形式:

data = data.frame(firm_size = c("Micro", "Small", "Medium","Big"), 
                  employees = c(5,10,100,1000))

> data 
     firm_size employees
1     Micro         5
2     Small        10
3    Medium       100
4       Big      1000

所以，如果我的条件是我必须将员工少于 10 人的公司归为一组，然后将它们与其他符合条件的类别合并

> new_data 
     firm_size    employees
1    Micro-Small     15
3    Medium          100
4    Big             1000

我想做的是编写一个函数来泛化这个过程，例如，如果我的数据是，它也可以工作

> data 
     firm_size employees
1     Micro       5
2     Small       8
3    Medium       9
4       Big      1000


> new_data 
     firm_size            employees
1    Micro-Small-Medium   22
4    Big                  1000

我认为这可以使用 tidyverse 的工具来完成。

提前致谢

Answer 1

这是一个使用 tally 的方法:

library(dplyr)
size <- 10

data %>% 
  arrange(firm_size,desc(employees)) %>%
  group_by(firm_size = c(as.character(firm_size[employees > size]),
                         rep(paste(firm_size[employees <= size], collapse = "-"),
                             sum(employees <= size)))) %>%
  tally(employees, name = "employees")
## A tibble: 3 x 2
#  firm_size   employees
#  <chr>           <dbl>
#1 Big              1000
#2 Medium            100
#3 Small-Micro        15

对于您的第二组数据:

data2 %>% 
  arrange(firm_size,desc(employees)) %>%
  group_by(firm_size = c(as.character(firm_size[employees > size]),
                         rep(paste(firm_size[employees <= size], collapse = "-"),
                             sum(employees <= size)))) %>%
  tally(employees, name = "employees")
## A tibble: 2 x 2
#  firm_size          employees
#  <chr>                  <int>
#1 Big                     1000
#2 Medium-Small-Micro        22

数据

data <- structure(list(firm_size = structure(c(3L, 4L, 2L, 1L), .Label = c("Big", 
"Medium", "Micro", "Small"), class = "factor"), employees = c(5, 
10, 100, 1000)), class = "data.frame", row.names = c(NA, -4L))


data2 <- structure(list(firm_size = structure(c(3L, 4L, 2L, 1L), .Label = c("Big", 
"Medium", "Micro", "Small"), class = "factor"), employees = c(5L, 
8L, 9L, 1000L)), class = "data.frame", row.names = c("1", "2", 
"3", "4"))