r - Summarize with dplyr "other then" groups

Question

I need to summarize in a grouped data_frame (warn: a solution with dplyr is very much appreciated but isn't mandatory) both something on each group (simple) and the same something on "other" groups.

minimal example

if(!require(pacman)) install.packages(pacman)
pacman::p_load(dplyr)

df <- data_frame(
    group = c('a', 'a', 'b', 'b', 'c', 'c'),
    value = c(1, 2, 3, 4, 5, 6)
)

res <- df %>%
    group_by(group) %>%
    summarize(
        median        = median(value)
#        median_other  = ... ??? ... # I need the median of all "other"
                                     # groups
#        median_before = ... ??? ... # I need the median of groups (e.g
                                 #    the "before" in alphabetic order,
                                 #    but clearly every roule which is
                                 #    a "selection function" depending
                                 #    on the actual group is fine)
    )

my expected result is the following

group    median    median_other    median_before
  a        1.5         4.5               NA
  b        3.5         3.5               1.5
  c        5.5         2.5               2.5

I've searched on Google strings similar to "dplyr summarize excluding groups", "dplyr summarize other then group",I've searched on the dplyr documentation but I wasn't able to find a solution.

here, this (How to summarize value not matching the group using dplyr) does not apply because it runs only on sum, i.e. is a solution "function-specific" (and with a simple arithmetic function that did not consider the variability on each group). What about more complex function request (i.e. mean, sd, or user-function)? :-)

Thanks to all

PS: summarize() is an example, the same question leads to mutate() or other dplyr-functions working based on groups.

Answer 1

I don't think it is in general possible to perform operations on other groups within summarise() (i.e. I think the other groups are not "visible" when summarising a certain group). You can define your own functions and use them in mutate to apply them to a certain variable. For your updated example you can use

calc_med_other <- function(x) sapply(seq_along(x), function(i) median(x[-i]))
calc_med_before <- function(x) sapply(seq_along(x), function(i) ifelse(i == 1, NA, median(x[seq(i - 1)])))

df %>%
    group_by(group) %>%
    summarize(med = median(value)) %>%
    mutate(
        med_other = calc_med_other(med),
        med_before = calc_med_before(med)
    )
#   group   med med_other med_before
#   (chr) (dbl)     (dbl)      (dbl)
#1     a   1.5       4.5         NA
#2     b   3.5       3.5        1.5
#3     c   5.5       2.5        2.5