在 dplyr 中有效地折叠、排序和丢弃因子

Question

子集化大型数据框给我们留下了一个需要重新排序和删除缺失因子的因子变量。代表如下：

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，但我们希望将因素的重新排序和删除整合到我们对调查的管道重新编码中。

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

如有指点，将不胜感激！

Answer 1

我不确定我是否理解。您能否详细说明为什么将所有内容包装在 mutate 调用中是不够的？

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))))

在 dplyr 中有效地折叠、排序和丢弃因子

Collapse, order and drop factors efficiently in dplyr

r

dplyr

forcats

替代使用dplyr::recode

替代使用`dplyr::recode`