使用dplyr的case_when基于多变量时出现错误求助

全局更新R包后，原本正常运行的R Markdown文档中，使用dplyr的case_when基于多变量做条件判断时出现无法解读的错误。单独针对what或how变量执行case_when都能正常运行，但两次操作会覆盖结果；添加TRUE默认分支也会引发错误，而官方文档明确支持多变量条件分支。

基础示例代码（可正常运行） #

case_character_type <- function(height, mass, species) {
  case_when(
    height > 200 | mass > 200 ~ "large",
    species == "Droid"        ~ "robot",
    TRUE                      ~ "other"
  )
}

case_character_type(150, 250, "Droid")
#> [1] "large"
case_character_type(150, 150, "Droid")
#> [1] "robot"

报错复现代码 #

exp <- structure(list(exercise_tf = c(TRUE, TRUE, TRUE, TRUE, TRUE, 
                                       TRUE, TRUE, TRUE, TRUE, TRUE), 
                       how = c("walk", "bike", "bike", 
                               "drive", "walk", "bike", "bike", "drive_train", "drive", "drive_train"), 
                       time_commute_min = c(10, 25, 30, 15, 10, 25, 30, 26, 20, 26), 
                       what = c("to bjj", "to work", "home from work", "to f3", "to bjj", 
                                "to work", "home from work", "to bjj", "to f3", "to bjj")), 
                  row.names = c(NA, 
                                -10L), 
                  class = c("tbl_df", "tbl", "data.frame"))

# 单独运行正常
exp %>%
  mutate(ex_time =
           case_when(grepl("bike", how) ~ time_commute_min))

# 单独运行正常
exp %>% 
  mutate(ex_time = 
           case_when(grepl("to bjj", what) ~ 45L,
                     grepl("to f3", what) ~ 45L))

# 合并运行报错
exp %>%
  filter(exercise_tf) %>% 
  mutate(ex_time =
           case_when(
             grepl("bike", how) ~ time_commute_min,
             grepl("to bjj", what) ~ 45L,
             grepl("to f3", what) ~ 45L
           )
  )

报错信息 #

Error in mutate():
! Problem while computing ex_time = case_when(...).
Caused by error in case_when():

Backtrace:

1. exp %>% filter(exercise_tf) %>% ...
2. dplyr::case_when(...)
   Error in mutate(., ex_time = case_when(grepl("bike", how) ~ time_commute_min, :

Caused by error in case_when():

问题原因 #

报错核心是**case_when各分支返回值的类型不匹配**：

• time_commute_min是numeric（数值型）
• 45L是integer（整数型）

dplyr更新后对case_when的类型一致性检查更严格，不同类型的返回值会触发报错。单独运行时单个分支类型统一，所以没问题；合并后分支返回类型混杂，就会报错。添加默认分支如果类型不统一，同样会触发错误。

修复方案 #

只需将所有分支的返回值统一为相同类型即可，两种可选方式：

方式1：将数值型转为整数型 #

exp %>%
  filter(exercise_tf) %>% 
  mutate(ex_time =
           case_when(
             grepl("bike", how) ~ as.integer(time_commute_min),
             grepl("to bjj", what) ~ 45L,
             grepl("to f3", what) ~ 45L
           )
  )

方式2：将整数型转为数值型 #

exp %>%
  filter(exercise_tf) %>% 
  mutate(ex_time =
           case_when(
             grepl("bike", how) ~ time_commute_min,
             grepl("to bjj", what) ~ 45,
             grepl("to f3", what) ~ 45
           )
  )

补充：添加默认分支 #

建议统一类型后添加默认分支，避免未匹配情况：

exp %>%
  filter(exercise_tf) %>% 
  mutate(ex_time =
           case_when(
             grepl("bike", how) ~ time_commute_min,
             grepl("to bjj", what) ~ 45,
             grepl("to f3", what) ~ 45,
             TRUE ~ NA_real_  # 与数值型返回值匹配的NA
           )
  )

内容的提问来源于stack exchange，提问作者captaincaed