Perform a different simple custom function based on group

I have data with three groups and would like to perform a different custom function on each of the three groups. Rather than write three separate functions, and calling them all separately, I'm wondering whether I can easily wrap all three into one function with a 'group' parameter.

For example, say I want the mean for group A:

library(tidyverse)

data(iris)

iris$Group <- c(rep("A", 50), rep("B", 50), rep("C", 50))

f_a <- function(df){
  out <- df %>% 
    group_by(Species) %>% 
    summarise(mean = mean(Sepal.Length))
  return(out)
}

The median for group B

f_b <- function(df){
  out <- df %>% 
    group_by(Species) %>% 
    summarise(median = median(Sepal.Length))
  return(out)
}

And the standard deviation for group C

f_c <- function(df){
  out <- df %>% 
    group_by(Species) %>% 
    summarise(sd= sd(Sepal.Length))
  return(out)
}

Is there any way I can combine the above functions and run them according to a group parameter?? Like: fx(df, group = "A") Which would produce the results of the above f_a function??

Keeping in mind that in my actual use context, I can't simply group_by(group) in the original function, since the actual functions are more complex. Thanks!!

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