Feature request: drop unused levels in R Plotly

NB: I’ve read around quite a bit and it seems this Q has been asked before but the feature has not been implemented yet.
eg python - Plotly: How to remove unused values from x_axis - Stack Overflow

Also, I’m not interested in Shiny answers as I can’t use that at my university, so I’m making a static HTML dashboard that can be hosted on a local network drive

I have created a dashboard using r flexdashboard where a Plotly object is linked to a filterable and reactive DT object. All works great except when I select data to show the Plotly object does not drop the unused levels

There appears to be options to do this in Plotly.py using x_axis_config arguments but no such analogous feature in R plotly

I have also tried writing a python code chunk into my R markdown doc to make use of this feature but the r reticulate package can’t work with a shared data frame created with r crosstalk so you lose the interactive function between the plot, sidebar, and datatable

It seems like a fairly simple feature addition, no?

Sample Rmd:

title: "Test"
    orientation: rows
    vertical_layout: scroll
    theme: yeti
    source_code: embed


AllResultsRaw <- as.data.frame(read.csv("CSVs/AllResultsCompiled.csv", header = TRUE, na.strings = c("NA", "n/a", "", "#DIV/0!"), strip.white = T))

AllResultsRaw <- tibble(AllResultsRaw)

AllResultsRaw <- unite(AllResultsRaw, Treatment, Concentration, col = "Condition", sep = "_")

AllResultsRaw <- AllResultsRaw %>% mutate(across(Cell.line, as.factor))
AllResultsRaw <- AllResultsRaw %>% mutate(across(Condition, as.factor))

shared_df <- SharedData$new(AllResultsRaw)

# Sidebar {.sidebar}


filter_select("Condition", "Treatment", shared_df, ~Condition, multiple = T)

filter_checkbox("Cell line", "Cell line", shared_df, ~Cell.line, allLevels = F, inline = F)

Also, no feature here to have a select all/none checkbox - another request??

summaryColours2 = c('grey', 'cornflowerblue', 'blue', 'grey', 'brown1', 'firebrick3')
  figure_1 <- plot_ly(shared_df, x = ~Donor,
                     y = ~BCD,
                     color = ~Condition,
                     colors = summaryColours2,
                     type = "bar")

datatable(shared_df, filter = 'top')

Resulting graph does not drop the unused levels from the $Donor factor column, resulting in large gaps