鉴于dplyr工作流程:

require(dplyr)                                      
mtcars %>% 
    tibble::rownames_to_column(var = "model") %>% 
    filter(grepl(x = model, pattern = "Merc")) %>% 
    group_by(am) %>% 
    summarise(meanMPG = mean(mpg))

我有兴趣filter根据价值有条件地申请applyFilter.

解

对于applyFilter <- 1使用"Merc"字符串过滤行,而不使用过滤器返回所有行.

applyFilter <- 1


mtcars %>%
  tibble::rownames_to_column(var = "model") %>%
  filter(model %in%
           if (applyFilter) {
             rownames(mtcars)[grepl(x = rownames(mtcars), pattern = "Merc")]
           } else
           {
             rownames(mtcars)
           }) %>%
  group_by(am) %>%
  summarise(meanMPG = mean(mpg))

问题

建议的解决方案效率低,因为ifelse始终会评估调用; 更可取的方法只会评估filter步骤applyFilter <- 1.

尝试

在低效的 …