如何根据其他变量非NA值替换tibble中dispone变量的NA值？

我有一个字符类型的tibble数据，其中dispone变量存在多个NA值。需要根据comp至comp_reu变量中是否存在非NA的"Sí"或"No"值，将dispone的NA值替换为"Sí"。以下是我尝试的几种dplyr写法及报错：

尝试1：错误的mutate格式 #

trans <- trans %>% mutate(dispone,
 ~ case_when("Sí" %in% c(across(comp:comp_reu)) ~ "Sí",
 "No" %in% c(across(comp:comp_reu)) ~ "Sí",
                             TRUE ~ .))

报错信息：

x `..2` must be a vector, not a `formula` object.

尝试2：使用rowwise但条件分支错误 #

trans <- trans %>% 
   rowwise() %>% 
   mutate(dispone = case_when("Sí" %in% c(across(comp:comp_reu)) ~ "Sí", "No" %in% c(across(comp:comp_reu)) ~ "Sí",TRUE ~ .))

报错信息：

Error in `mutate()`:! Problem while computing `dispone = case_when(...)`.
i The error occurred in row 1.
Caused by error in `` names(message) <- `*vtmp*` ``:
! 'names' attribute [1] must be the same length as the vector [0]
Run `rlang::last_error()` to see where the error occurred.

尝试3：使用c_across但分支逻辑错误 #

trans <- trans %>%
           rowwise() %>% 
           mutate(dispone = case_when("Sí" %in% c_across(comp:comp_reu) ~ "Sí",
                             "No" %in% c_across(comp:comp_reu) ~ "Sí",
                             TRUE ~ .))

报错信息：

Error in `mutate()`:
! Problem while computing `dispone = case_when(...)`.
i The error occurred in row 1.
Caused by error in `` names(message) <- `*vtmp*` ``:
! 'names' attribute [1] must be the same length as the vector [0]
Run `rlang::last_error()` to see where the error occurred.

尝试4：错误的列范围使用方式 #

trans <- trans %>%
           mutate(dispone = case_when(!is.na(comp:comp_reu) ~ "Sí",
                 TRUE ~ .)) 

报错信息：

Error in `mutate()`:
! Problem while computing `dispone = case_when(!is.na(comp:comp_reu) ~ "Sí", TRUE 
~ .)`.
Caused by error in `comp:comp_reu`:
! NA/NaN argument
Run `rlang::last_error()` to see where the error occurred.
Warning messages:
1: Problem while computing `dispone = case_when(!is.na(comp:comp_reu) ~ "Sí", TRUE 
~ .)`.
i numerical expression has 968 elements: only the first used

尝试5：错误的非NA检测写法 #

trans<- trans %>% 
           rowwise() %>% 
           mutate(dispone = case_when(!is.na %in% c_across(comp:comp_reu) ~ "Sí",
                             TRUE ~ .))

正确解法 #

方法1：使用rowwise + c_across（适合小数据集） #

trans <- trans %>%
  rowwise() %>%
  mutate(
    dispone = case_when(
      # 仅当dispone为NA，且目标列存在非NA的"Sí"或"No"时替换
      is.na(dispone) & any(c_across(comp:comp_reu) %in% c("Sí", "No"), na.rm = TRUE) ~ "Sí",
      # 其他情况保持原变量值
      TRUE ~ dispone
    )
  ) %>%
  ungroup() # 取消行分组，避免后续操作性能下降

方法2：使用if_any（无需rowwise，性能更优，推荐） #

trans <- trans %>%
  mutate(
    dispone = case_when(
      is.na(dispone) & if_any(comp:comp_reu, ~ .x %in% c("Sí", "No"), na.rm = TRUE) ~ "Sí",
      TRUE ~ dispone
    )
  )

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