在R中将一列拆分为多列

Question

I am trying to tidy some data on the number of students enrolled in different subjects at different year levels separated by gender over 14 years.

I'm not sure what dplyr function to use because I don't want to make the observations variable names I want to group them and put them in variables.

Row Labels    Year   students 
Biology       2004   26252
Female        2004   16091 
Year 9        2004   40
Year 10       2004   1857
Year 11       2004   8807
Year 12       2004   5386
Year 13       2004   1
Male          2004   10161
Year 9        2004   382
Year 10       2004   1301
Year 11       2004   5062
Year 12       2004   3118
Year 13       2004   298
Biotechnology 2004   2682
Female        2004   1257

I want it to look something like this with gender in one column, subject in another and year level in another.

Subject          Gender    Year  Year level  students
Biology          Female    2004  Year 9       16091
Biotechnology    Female    2004  Year 10      1257

---

df <- structure(list(`Row Labels` = c("Biology", "Female", "Year 9", 
"Year 10", "Year 11", "Year 12", "Year 13", "Male", "Year 9", 
"Year 10", "Year 11", "Year 12", "Year 13", "Biotechnology", 
"Female"), Year = c(2004, 2004, 2004, 2004, 2004, 2004, 2004, 
2004, 2004, 2004, 2004, 2004, 2004, 2004, 2004), students = c(26252, 
16091, 40, 1857, 8807, 5386, 1, 10161, 382, 1301, 5062, 3118, 
298, 2682, 1257)), row.names = c(NA, -15L), class = c("tbl_df", 
"tbl", "data.frame"))

Answer 1

This will do the trick but you have to manually specify all the subjects in your dataset:

library(tidyr)
library(dplyr)

subjects <- c("Biology", "Biotechnology")

df %>% 
  mutate(
    Subject = if_else(`Row Labels` %in% subjects, `Row Labels`, NA_character_),
    Gender = if_else(`Row Labels` %in% c("Male", "Female"), `Row Labels`, NA_character_)
  ) %>% 
  fill(Subject, Gender) %>% 
  filter(`Row Labels` != Subject, `Row Labels` != Gender) %>% 
  select(Subject, Gender, Year, `Year level` = `Row Labels`, students)