How can I use dplyr to apply a function to all non-group_by columns?

Question

I\'m trying to use the dplyr package to apply a function to all columns in a data.frame that are not being grouped, which I would do with aggregate():

Answer 1

If you're willing to try out an experimental dplyr, you can try out the new (and still experimental) summarise_each():

devtools::install_github("hadley/dplyr", ref = "colwise")

library(dplyr)
iris %.%
  group_by(Species) %.%
  summarise_each(funs(mean))
## Source: local data frame [3 x 5]
## 
##      Species Sepal.Length Sepal.Width Petal.Length Petal.Width
## 1     setosa        5.006       3.428        1.462       0.246
## 2 versicolor        5.936       2.770        4.260       1.326
## 3  virginica        6.588       2.974        5.552       2.026

iris %.%
  group_by(Species) %.%
  summarise_each(funs(min, max))
## Source: local data frame [3 x 9]
## 
##      Species Sepal.Length_min Sepal.Width_min Petal.Length_min
## 1     setosa              4.3             2.3              1.0
## 2 versicolor              4.9             2.0              3.0
## 3  virginica              4.9             2.2              4.5
## Variables not shown: Petal.Width_min (dbl), Sepal.Length_max (dbl),
##   Sepal.Width_max (dbl), Petal.Length_max (dbl), Petal.Width_max (dbl)

Feedback much appreciated!

This will appear in dplyr 0.2.

Answer 2

This will get you almost all the way in dplyr.

h = iris %.%
  group_by(Species) %.%
  do(function(d){
    sapply(Filter(is.numeric, d), mean)  
  })

as.data.frame(h)