故障排除案例_当 function 在 R 中使用 tidyverse 时

Question

Simple question, what don't I understand about how case_when works. In the example below, I expected 4 levels in season but I get only two.

Thanks

data <- tibble(day = 1:366) %>% 
  mutate(
    season = case_when(
      day <= 60 | day > 335 ~ "winter",
      day > 60  | day <= 151 ~ "spring",
      day > 151 | day <= 242 ~ "summer",
      day > 242 | day <= 335 ~ "autumn"
    )
  )

Answer 1

The expressions 2 to 4 would be & instead of | . Reason is that | will overwrite some of the values from the first condition because of overlap

library(dplyr)
data <- tibble(day = 1:366) %>% 
  mutate(
    season = case_when(
      day <= 60 | day > 335 ~ "winter",
      day > 60  & day <= 151 ~ "spring",
      day > 151 & day <= 242 ~ "summer",
      day > 242 & day <= 335 ~ "autumn"
    )
  )

-checking

> n_distinct(data$season)
[1] 4

Answer 2

actually you can reduce this case_when() statement a bit, because case_when breaks as soon as one condition is met. So if the value is lower/equal to 60 or larger then 335, the next condition is suficiently definied with lower than 151:

library(dplyr)
data <- tibble(day = 1:366) %>% 
  mutate(
    season = case_when(
      day <= 60 | day > 335 ~ "winter",
      day <= 151 ~ "spring",
      day <= 242 ~ "summer",
      day <= 335 ~ "autumn"
    )
  )

also you can make use of the TRUE case as it is used when all prior conditions are not met:

data <- tibble(day = 1:366) %>% 
  mutate(
    season = case_when(
      day <= 60 ~ "winter",
      day <= 151 ~ "spring",
      day <= 242 ~ "summer",
      day <= 335 ~ "autumn",
      TRUE ~ "winter"
    )
  )

Answer 3

Stop using case_when and use cut instead.

tibble(day = 1:366) |>
     mutate(
       season = cut(day, 
                      c(0, 60, 151, 242, 335, 366),
                      c("winter", "spring", "summer", "autumn", 
                          "winter")
                )
     )