Succinct way to summarize different columns with different functions

Question

My question builds on a similar one by imposing an additional constraint that the name of each variable should appear only once.

Consider a data frame

Answer 1

Here's a hacky function that uses unexported functions from dplyr so it is not future proof, but you can specify a different summary for each column.

summarise_with <- function(.tbl, .funs) {
  funs <- enquo(.funs)
  syms <- syms(tbl_vars(.tbl))
  calls <- dplyr:::as_fun_list(.funs, funs, caller_env())
  stopifnot(length(syms)==length(calls))
  cols <- purrr::map2(calls, syms, ~dplyr:::expr_substitute(.x, quote(.), .y))
  cols <- purrr::set_names(cols, purrr::map_chr(syms, rlang::as_string))
  summarize(.tbl, !!!cols)
}

Then you could do

df %>% summarise_with(list(mean, sum))

and not have to type the column names at all.