按条件和更改类型复制行

Question

我正在处理学校数据，我需要复制那些只为ES或HS提供更大年级跨度的行。一些示例代码来说明我的问题：

# data
schools <- tibble(name = c("school a", "school b", "school c", "school z"), 
                  type = c("es", "NA", "hs", "es"),
                  gslo = c("01", "08", "09", "KG"),
                  gshi = c("12", "12", "12", "05"))
schools
  name     type  gslo  gshi 
  <chr>    <chr> <chr> <chr>
1 school a es    01    12   
2 school b NA    08    12   
3 school c hs    09    12   
4 school z es    KG    05   

其中gslo和gshi分别是服务的最低和最高等级。在美国，这些学校将分为高中、中学或小学，即type。

一些学校提供的不仅仅是小学年级的服务，但现在只被算作type=="；es"；。

schools_attempt <- schools %>%
# add row based on condition and change type 
# not generalized 
  rbind(schools %>% filter(gslo == "01", gshi == "12") %>% mutate(type = "hs"))
> schools_attempt
# A tibble: 5 x 4
  name     type  gslo  gshi 
  <chr>    <chr> <chr> <chr>
1 school a es    01    12   
2 school b NA    08    12   
3 school c hs    09    12   
4 school z es    KG    05   
5 school a hs    01    12   

这是有效的，但不是一般性的。有可能避免一个大案子吗？注意已更改的学校类型分类(es->hs(

schools_want <- tibble(name = c("school a", "school b", "school c", "school z", "school a"), 
                       type = c("es", "NA", "hs", "es", "hs"),
                       gslo = c("01", "08", "09", "KG", "01"),
                       gshi = c("12", "12", "12", "05", "12"))
> schools_want
# A tibble: 5 x 4
  name     type  gslo  gshi 
  <chr>    <chr> <chr> <chr>
1 school a es    01    12   
2 school b NA    08    12   
3 school c hs    09    12   
4 school z es    KG    05   
5 school a hs    01    12 

谢谢！

Answer 1

作为一种通用方法，这可能就足够了。如果它从九年级以上开始，那就是一所高中。如果它在九年级之前结束，那就是小学。否则，两者都有，我们可以分成两行。

library(dplyr)
schools %>% 
  mutate(across(gslo:gshi, ~if_else(.x == "KG", 0, as.numeric(.x))),
         type2 = case_when(
           gslo >= 9 ~ "hs",
           gshi <= 8 ~ "es",
           TRUE ~ "hs, es"
         )) %>%
  separate_rows(type2)

# A tibble: 6 x 5
  name     type   gslo  gshi type2
  <chr>    <chr> <dbl> <dbl> <chr>
1 school a es        1    12 hs   
2 school a es        1    12 es   
3 school b NA        8    12 hs   
4 school b NA        8    12 es   
5 school c hs        9    12 hs   
6 school z es        0     5 es  

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Edit：如果您想保持gslo/gshi列的原样，请将.names = "{.col}_num"),添加到across()调用中，并在case _when中使用gslo_num和gshi_num。