r - 使用 sum 对数据进行分类的 Case_when 问题 - R/dplyr 解决方案

Question

我可能在这里做了一些愚蠢的事情，但希望得到一些帮助。我正在尝试对一些填写错误的数据进行分类。

df <- data.frame(ID = c("A", "A", "A","A", "A", "B", "B", "B", "B", "B"),
                 headache_y_n = c("Yes", "Yes", "Yes", "No", "Yes", "No", "No", "No", "Yes", "No"),
                 headache_days =c("2", "2", "2", "2", "2", "1", "1", "1", "1", "1"))

我希望能够说，如果每个 ID 的头痛_y_n 为"is"超过 3 次，则满足“延长”的标准，否则应为“短”。

因此，我想要以下输出:

output <- data.frame(ID = c("A", "A", "A","A", "A", "B", "B", "B", "B", "B"),
                 headache_y_n = c("Yes", "Yes", "Yes", "No", "Yes", "No", "No", "No", "Yes", "No"),
                 headache_days =c("2", "2", "2", "2", "2", "1", "1", "1", "1", "1"),
                 criteria =c("prolonged", "prolonged", "prolonged", "prolonged", "prolonged", "short", "short", "short", "short", "short"))

我的代码如下:

library(dplyr)
df %>% group_by(ID) %>% mutate(criteria=case_when(
    sum(any(headache_y_n=="Yes") >= 3) ~ "prolonged",
    TRUE ~ "short"
))

不幸的是，它不起作用，我收到以下错误:

Error: Problem with `mutate()` input `criteria`.
x LHS of case 1 (`sum(any(headache_y_n == "Yes") >= 3)`) must be a logical vector, not an integer vector.
ℹ Input `criteria` is `case_when(...)`.
ℹ The error occurred in group 1: ID = "A".

我不够聪明，无法弄清楚我哪里出了问题，因此我恳请您的帮助!

谢谢!

Answer 1

any和sum应该切换，即按“ID”分组后，我们正在计算"is"的数量，即 sum逻辑表达式 ( headache_y_n == 'Yes' )，然后在 sum 之后创建第二个表达式>=3 ，用 any 包裹它匹配(这里可能不需要，因为 sum 只是一个值)

library(dplyr)
df %>%
     group_by(ID) %>%
     mutate(criteria=case_when(
        any(sum(headache_y_n=="Yes") >= 3) ~ "prolonged",
         TRUE ~ "short"
    ))

即即使删除 any ，它返回相同的

df %>%
      group_by(ID) %>%
      mutate(criteria=case_when(
         sum(headache_y_n=="Yes") >= 3 ~ "prolonged",
          TRUE ~ "short"
     ))
# A tibble: 10 x 4
# Groups:   ID [2]
#   ID    headache_y_n headache_days criteria 
#   <chr> <chr>        <chr>         <chr>    
# 1 A     Yes          2             prolonged
# 2 A     Yes          2             prolonged
# 3 A     Yes          2             prolonged
# 4 A     No           2             prolonged
# 5 A     Yes          2             prolonged
# 6 B     No           1             short    
# 7 B     No           1             short    
# 8 B     No           1             short    
# 9 B     Yes          1             short    
#10 B     No           1             short