[improvement] write examples using SE functions

[pachevalier]

Dplyr NSE (non standard evaluation) functions are easy to use. SE functions however are much more difficult and there are only few examples in the documentation.

The NSE vignette provides nice examples for summarise_ but not for the other verbs such as group_by_(), filter_(), etc.

The documentation for select() provides some examples.

I would suggest to add SE examples for filter_() :

filter(mtcars, cyl == 8)
filter_(mtcars, .dots = list(~ cyl == 8))

filter(mtcars, cyl < 6)
filter_(mtcars, .dots = list(~ cyl < 6))

# Multiple criteria
filter(mtcars, cyl < 6 & vs == 1)
filter_(mtcars, .dots = list(~ cyl < 6, ~ vs == 1))

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

I would suggest the following examples for summarise_ and groupby :

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))))

summarise(group_by(mtcars, cyl), mean(disp))
summarise_(group_by_(mtcars, ~ cyl), .dots = list("mean_disp" = lazyeval::interp(~ mean(x), x = quote(disp))))

summarise(group_by(mtcars, cyl), m = mean(disp), sd = sd(disp))
summarise_(group_by_(mtcars, ~ cyl), .dots = list("m" = lazyeval::interp(~ mean(x), x = quote(disp)), "sd" = lazyeval::interp(~ sd(x), x = quote(disp))))

For mutate_, I would add :

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

[krlmlr]

Thanks. This feels related to #2386 (shelved for now), we should wait a bit to see if alternative APIs become available before updating documentation.

[hadley]

Yeah, this is all going to change as part of the switch to tidyeval. We'll definitely improve the docs.