dplyr group_by and mutate, how to access the data frame?

Question

When using dplyr's "group_by" and "mutate", if I understand correctly, the data frame is split in different sub-dataframes according to the group_by argument. For example, with the following code :

 set.seed(7)
 df <- data.frame(x=runif(10),let=rep(letters[1:5],each=2))
 df %>% group_by(let) %>% mutate(mean.by.letter = mean(x))

mean() is applied successively to the column x of 5 sub-dfs corresponding to a letter between a & e.

So you can manipulate the columns of the sub-dfs but can you access the sub-dfs themselves ? To my surprise, if I try :

 set.seed(7)
 data <- data.frame(x=runif(10),let=rep(letters[1:5],each=2))
 data %>% group_by(let) %>% mutate(mean.by.letter = mean(.$x))

the result is different. From this result, one can infer that the "." df doesn't represent successively the sub-dfs but just the "data" one (the group_by function doens't change anything).
The reason is that I want to use a stat function that take a data frame as an arguments on each of this sub-dfs. Thanks !

Answer 1

We can use within do

data %>%
    group_by(let ) %>% 
    do(mutate(., mean.by.letter = mean(.$x)))