如何为R的DataFrame按school_type与staff_type子组添加总计行？

原始数据 #

data <- data.frame(school_type = c("nursery", "nursery", "nursery", "nursery", "primary", "primary", "primary", "primary"), 
                   staff_type = c("manager", "manager", "teacher", "teacher", "manager", "manager", "teacher", "teacher"),
                   age_group = c("20-30","30-40","20-30","30-40","20-30","30-40","20-30","30-40"), 
                   number_staff = c(40, 10, 20, 30, 40, 10, 20, 30), 
                   perc_staff = c(80, 20,40,60,80, 20,40,60))

需求说明 #

为每个school_type和staff_type的组合子组添加总计行，汇总number_staff和perc_staff字段。

修改后的解决方案 #

方案1：基于split函数的实现 #

将原代码的单字段拆分改为按两个字段的组合拆分，即可实现双分组添加总计：

library(dplyr)
library(purrr)
library(janitor)

data %>%
  arrange(school_type, staff_type) %>%
  split(list(.$school_type, .$staff_type)) %>%
  map_df(adorn_totals, where = "row")

方案2：基于group_split的tidyverse风格实现 #

更符合tidyverse语法习惯的写法，用group_by定义分组后拆分：

library(dplyr)
library(purrr)
library(janitor)

data %>%
  arrange(school_type, staff_type) %>%
  group_by(school_type, staff_type) %>%
  group_split() %>%
  map_df(~ adorn_totals(.x, where = "row"))

代码说明 #

• arrange(school_type, staff_type)：按两个分组字段排序，确保子组内数据顺序统一
• split(list(.$school_type, .$staff_type)) / group_by(...) %>% group_split()：将数据按school_type和staff_type的组合拆分为多个子数据框
• map_df(adorn_totals, where = "row")：对每个子数据框添加行总计，自动汇总数值型字段（如number_staff求和，perc_staff求和），最后合并为一个完整的数据框

内容的提问来源于stack exchange，提问作者fe108