I'd like to use dplyr to group a table by one column, then apply a function to the set of values in the second column of each group.
For instance, in the code example below, I'd like to return all of the 2-item combinations of foods eaten by each person. I cannot figure out how to properly supply the function with the proper column (foods) in the do() function.
library(dplyr)
person = c( 'Grace', 'Grace', 'Grace', 'Rob', 'Rob', 'Rob' )
foods = c( 'apple', 'banana', 'cucumber', 'spaghetti', 'cucumber', 'banana' )
eaten = data.frame(person, foods)
by_person = group_by(eaten, person)
# How to do this?
do( by_person, combn( x = foods, m = 2 ) )
Note that the example code in ?do fails on my machine
mods <- do(carriers, failwith(NULL, lm), formula = ArrDelay ~ date)
Let us define eaten like this:
eaten <- data.frame(person, foods, stringsAsFactors = FALSE)
1) Then try this:
eaten %.% group_by(person) %.% do(function(x) combn(x$foods, m = 2))
giving:
[[1]]
[,1] [,2] [,3]
[1,] "apple" "apple" "banana"
[2,] "banana" "cucumber" "cucumber"
[[2]]
[,1] [,2] [,3]
[1,] "spaghetti" "spaghetti" "cucumber"
[2,] "cucumber" "banana" "banana"
2) To be able to do something near to what @Hadley describes in the comments without waiting for a future version of dplyr try this where do2 is found here:
library(gsubfn)
eaten %.% group_by(person) %.% fn$do2(~ combn(.$foods, m = 2))
giving:
$Grace
[,1] [,2] [,3]
[1,] "apple" "apple" "banana"
[2,] "banana" "cucumber" "cucumber"
$Rob
[,1] [,2] [,3]
[1,] "spaghetti" "spaghetti" "cucumber"
[2,] "cucumber" "banana" "banana"
Note: The last line of the question giving the code in the help file also fails for me. This variation of it works for me: do(jan, lm, formula = ArrDelay ~ date) .
