switch 未矢量化,因此为了提高效率,您需要使用 ifelse 或 case_when -但是你的问题是关于 ,您可以通过矢量化实现您想要的,例如。

convert_am <- Vectorize(function(x) {
    x <- as.character(x)
    switch(x,
       "0" = FALSE,
       "1" = TRUE,
       NA)
})

或

convert_am <- function(x) {
    x <- as.character(x)
    sapply(x, function(xx) switch(xx,
       "0" = FALSE,
       "1" = TRUE,
       NA))
}

它们都是低效的,因为它们涉及引擎盖下的环路。

This is simple enough to handle with ifelse directly:
        
            Test <- tibble::tibble(
              am = c(-1:5,NA,1, 0)
            ) 
        
            Test %>%
              mutate(
                newam = ifelse(am == 1, TRUE,
                       ifelse(am == 0, FALSE, NA))
              )
        
        
With more categories, use a named vector:
            Test %>%
              mutate(
                newam = ifelse(is.na(am) | !am %in% c(1,3,5), NA,
                               c("1" = "in1", "3" = "in3", "5" = "in5")[as.character(am)])
              )
        
In fact if the value is not in the named list it will default to an NA
I think this will be pretty efficient
            Test %>%
              mutate(
                newam = c("1" = "in1", "3" = "in3", "5" = "in5")[as.character(am)]
              )