2

对大型数据框进行子集化会给我们留下一个需要重新排序和删除缺失因子的因子变量。一个代表如下：

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)

根据这个答案，下面的代码实现了我们想要的，但我们希望将因素的重新排序和删除集成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

任何指针将不胜感激！

4

1 回答 1

2

我不确定我是否理解。您能否详细说明为什么将所有内容都包含在一个mutate电话中是不够的？

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))))
于 2018-10-18T08:44:14.433 回答