ddply multiple quantiles by group

Question

how can I do this calculation:

library(ddply)
quantile(baseball$ab)
  0%  25%  50%  75% 100% 
  0   25  131  435  705 

by groups, say by \"

Answer 1

A slightly different approach using dplyr:

library(tidyverse)

baseball %>% 
  group_by(team) %>% 
  nest() %>% 
  mutate(
    ret = map(data, ~quantile(.$ab, probs = c(0.25, 0.75))),
    ret = invoke_map(tibble, ret)
  ) %>%
  unnest(ret)

Here you can specify the needed quantiles in the probs argument.

The invoke_map call seems to be necessary, as quantile does not return a data frame; see this answer.

You can also put that all into a function:

get_quantiles <- function(.data, .var, .probs = c(0.25, 0.75), .group_vars = vars()) {
  .var = deparse(substitute(.var))
  return(
    .data %>% 
    group_by_at(.group_vars) %>% 
    nest() %>% 
    mutate(
      ret = map(data, ~quantile(.[[.var]], probs = .probs)),
      ret = invoke_map(tibble, ret)
    ) %>%
    unnest(ret, .drop = TRUE)
  )
}

mtcars %>% get_quantiles(wt, .group_vars = vars(cyl))

---

A new approach would be to use group_modify() from dplyr. Then you'd call:

baseball %>%
  group_by(team) %>% 
  group_modify(~{
    quantile(.x$ab, probs = c(0.25, 0.75)) %>% 
    tibble::enframe()
  }) %>%
  spread(name, value)