Grouped drilldown series names with highcharter package in R

I'd like to implement a grouped drilldown column chart using the highcharter package in R. I've figured out some clean syntax for maintaining groupings in the drilldowns, but when you click through the legend names default to "Series 1" and "Series 2". I'd like to make sure legend names are consistent throughout... Any ideas on how I can achieve that?

# load libraries
library(dplyr)
library(purrr)
library(tibble)
library(highcharter)

# example data
data <- as_tibble(datasets::HairEyeColor) |>
  rename_all(tolower)

# split into column and drilldown datasets
column <- data |>
  group_by(sex, hair) |>
  summarize(n = sum(n),
            # set column id to match drilldown id
            id = paste0(hair, "-", sex))

drilldown <- data |>
  group_nest(sex, hair) |>
  mutate(
    # set drilldown id to match column id
    id = paste0(hair, "-", sex),
    type = "column",
    data = data |> map(mutate, name = eye, y = n),
    data = data |> map(list_parse)
  )

# create highcharts plot
column |>
  hchart(
    "column",
    hcaes(x = hair, y = n, name = hair, drilldown = id, group = sex)
  ) |>
  hc_drilldown(
    activeAxisLabelStyle = list(textDecoration = "none"),
    allowPointDrilldown = FALSE,
    series = list_parse(drilldown)
  ) |>
  hc_yAxis(
    title = ""
  ) |>
  hc_xAxis(
    title = ""
  ) #|>
  # trying to alter legend labels
  # hc_legend(
  #   labelFormat = "{sex}"
  # )

I haven’t found an example of it successfully implemented but here’s a JSfiddle with the same functionality. You’ll notice when you click though, the legend label switches from 2010/2014 to Series1/Series2… trying to get the top-level legend labels to persist in the drilldown is proving to be challenging…

Is this what you're after? I'm using R < 4.0 so I had to replace |> with '%>%'.

You just need to add the name var to your drilldown table.

drilldown <- data %>%
  group_nest(sex, hair) %>%
  mutate(
    # set drilldown id to match column id
    id = paste0(hair, "-", sex),
    name = sex, # add 'series.name' to drilldown series
    type = "column",
    data = data %>% map(mutate, name = eye, y = n),
    data = data %>% map(list_parse)
  )