Calculate the maximum density of a numeric variable grouped by 2 categorical variables

[davidhodge931]

Hi everyone,

I have created a function that calculates the maximum in a density plot grouped by 1 categorical variable.

library(dplyr)
library(ggplot2)
library(purrr)

max_density <- function(data, num_var, group_var1) {
  
  data %>% 
    group_split( {{group_var1}}) %>% 
    map(~select(., density_var = {{num_var}} )) %>%
    map(~pull(., .data$density_var)) %>% 
    map(~stats::density(., na.rm = TRUE)[[2]]) %>% 
    map_dbl(~max(.)) %>% 
    max() 
}  

max_density(penguins, body_mass_g, sex)

ggplot(filter(penguins, !is.na(sex))) +
  geom_density(aes(body_mass_g, col = sex, fill = sex), alpha = 0.1) +
  scale_y_continuous(labels = scales::comma)

Now I would like to come up with a function to calculate the maximum density where there are 2 grouping variables.

I am not sure how to do this, as it requires calculating the density of each sex/species group and then summing each of sex value groups - and then find of the max of these.

This can be visualised by the graph below.

ggplot(filter(penguins, !is.na(sex))) +
  geom_density(aes(body_mass_g, col = sex, fill = sex), alpha = 0.1) +
  scale_y_continuous(labels = scales::comma) +
  facet_wrap(~species)

Any help appreciated

Thanks!
David