标准 dplyr 动词的示例

NSE 函数应该用于交互式编程。但是，在新软件包中开发新功能时，最好使用 SE 版本。

加载 dplyr 和 lazyeval：

library(dplyr)
library(lazyeval)

过滤

NSE 版本

filter(mtcars, cyl == 8)
filter(mtcars, cyl < 6)
filter(mtcars, cyl < 6 & vs == 1)

SE 版本（在新软件包中编程函数时使用）

filter_(mtcars, .dots = list(~ cyl == 8))
filter_(mtcars, .dots = list(~ cyl < 6))
filter_(mtcars, .dots = list(~ cyl < 6, ~ vs == 1))

总结

NSE 版本

summarise(mtcars,  mean(disp))
summarise(mtcars,  mean_disp = mean(disp))

SE 版本

summarise_(mtcars, .dots = lazyeval::interp(~ mean(x), x = quote(disp)))
summarise_(mtcars, .dots = setNames(list(lazyeval::interp(~ mean(x), x = quote(disp))), "mean_disp"))
summarise_(mtcars, .dots = list("mean_disp" = lazyeval::interp(~ mean(x), x = quote(disp))))

变异

NSE 版本

mutate(mtcars, displ_l = disp / 61.0237)

SE 版本

mutate_(
    .data = mtcars, 
    .dots = list(
        "displ_l" = lazyeval::interp(
                        ~ x / 61.0237, x = quote(disp)
            )
         )
)