Applying a dplyr function to all variables at once

I have a dataframe with a numeric variable ("numeric") and several factor variables (factors 0 and 1 (FALSE, TRUE) or 0 to 4 (states in a pathology)). I would like to summarise median and IQR for "numeric" for each of the groups (0 to 1, 0 to 4).

Would there a way to apply this function to every factor column in the dataset without having to type one variable by one?

`library(dplyr)
 group_by(df, othervariable) %>%
  summarise(
  count = n(),
  median = median(numeric, na.rm = TRUE),
  IQR = IQR(numeric, na.rm = TRUE)
)`

The output:

othevariable count median   IQR
      <dbl> <int>  <dbl> <dbl>
1       0   100   2.46  2.65
2       1   207   3.88  5.86    

If your dataset contains only the grouping variables of interest and numeric, you can use purrr's function map to apply the summarise statement to each group.

library(dplyr)

purrr::map(names(df %>% select(-numeric)), function(i) {
  df %>% 
    group_by(!!sym(i)) %>% 
    summarize(
      count = n(),
      median = median(numeric, na.rm = TRUE),
      IQR = IQR(numeric, na.rm = TRUE)
    )
})

The output should be a list of dataframes, each element corresponding to a grouping variable along with its summary result.