循环函数，以避免使用 R 进行分层采样中的重复代码

Question

我正在使用下面的代码对人群进行分层随机抽样，并根据性别和地区确定了先前的目标。可以看出，相同的代码重复了 3 次（每次使用 rbind 时）。有没有办法写一个循环函数，可以重复这个过程，这样我就不用写好几次了？

library(tidyverse)
population<- data.frame(region=rep(c("North", "South", "North", "South"),50000),
                        sex=rep(c("Male", "Female", "Female", "Male"),50000))

targets<- data.frame(region=c("North", "South", "North", "South"),
                     sex=c("Male", "Female", "Female", "Male"),
                     total=c(20,25,20,30)) 


n=0
n=n+1
sample<- population %>% filter(region==targets$region[[1]], 
                           sex==targets$sex[[1]]) %>% 
  slice_sample(n=targets$total[[1]])
n=n+1
sample<- sample %>%  rbind(population %>% filter(region==targets$region[[n]], 
                               sex==targets$sex[[n]]) %>% 
  slice_sample(n=targets$total[[n]]))
n=n+1
sample<- sample %>%  rbind(population %>% filter(region==targets$region[[n]], 
                               sex==targets$sex[[n]]) %>% 
  slice_sample(n=targets$total[[n]]))
n=n+1
sample<- sample %>%  rbind(population %>% filter(region==targets$region[[n]], 
                               sex==targets$sex[[n]]) %>% 
  slice_sample(n=targets$total[[n]]))

Answer 1

感谢Harry Smith 提供的帮助，我找到了答案。它由他的代码的一个小调整组成：

n = 4  
sample_list <- list()
for(i in 1:n){
  sample<- population %>% filter(region==targets$region[[i]], 
                                                   sex==targets$sex[[i]]) %>% 
                               slice_sample(n=targets$total[[i]])
  sample_list[[i]] <- sample
}

a<-bind_rows(sample_list)

Answer 2

类似的东西。它将dfs保存在一个列表中。

n = 4  
sample_list <- list()
for(i in 1:n){
sample<-rbind(population %>% filter(region==targets$region[[i]], 
                                                 sex==targets$sex[[i]]) %>% 
                             slice_sample(n=targets$total[[i]]))
sample_list[[i]] <- sample
}