在dplyr中有效地折叠，排序和放置因子

Question

为大型数据帧设置子集将给我们留下一个因子变量，该因子变量需要重新排序和删除缺失的因子。下面是一个代表：

library(tidyverse)

set.seed(1234)

data <- c("10th Std. Pass", "11th Std. Pass", "12th Std. Pass", "5th Std. Pass", 
          "6th Std. Pass", "Diploma / certificate course", "Graduate", "No Education")

education <-  factor(sample(data, size = 5, replace = TRUE), 
                     levels = c(data, "Data not available"))

survey <-  tibble(education)

下面的代码as per this answer实现了我们想要的功能，但是我们希望将因子的重新排序和删除整合到调查的管道编码中。

recoded_s <- survey %>% mutate(education =
  fct_collapse(education,
"None" = "No Education",
"Primary" = c("5th Std. Pass", "6th Std. Pass"),
"Secondary" = c("10th Std. Pass", "11th Std. Pass", "12th Std. Pass"), 
"Tertiary" = c("Diploma / certificate course", "Graduate")
  ))

recoded_s$education
#> [1] Secondary Primary   Primary   Primary   Tertiary 
#> Levels: Secondary Primary Tertiary None Data not available


# Re-ordering and dropping variables
factor(recoded_s$education, levels = c("None", "Primary", "Secondary", "Tertiary"))
#> [1] Secondary Primary   Primary   Primary   Tertiary 
#> Levels: None Primary Secondary Tertiary

任何指针将不胜感激！

Answer 1

我不确定我是否理解。您能详细说明为什么将所有内容包装在mutate调用中还不够吗？

library(tidyverse)
library(forcats)
survey %>%
    mutate(
        education = fct_collapse(
            education,
            "None" = "No Education",
            "Primary" = c("5th Std. Pass", "6th Std. Pass"),
            "Secondary" = c("10th Std. Pass", "11th Std. Pass", "12th Std. Pass"),
            "Tertiary" = c("Diploma / certificate course", "Graduate")),
        education = factor(education, levels = c("None", "Primary", "Secondary", "Tertiary")))

---

替代使用dplyr::recode

lvls <- list(
    "No Education" = "None",
    "5th Std. Pass" = "Primary",
    "6th Std. Pass" = "Primary",
    "10th Std. Pass" = "Secondary",
    "11th Std. Pass" = "Secondary",
    "12th Std. Pass" = "Secondary",
    "Diploma / certificate course" = "Tertiary",
    "Graduate" = "Tertiary")
survey %>%
    mutate(
        education = factor(recode(education, !!!lvls), unique(map_chr(lvls, 1))))