ggplot to plot conversion stacked bar graph show only individual points in R

I have made a stacked bar graph in R using ggploty . It's filtered based on a test description. However, every time I filter something, it is showing individual points not the stacked bar graph. I can make the same work in shiny but I want it ploty because it's easier to share.

output plot

library(ggplot2)
library(plotly)
library(dplyr)
library(lubridate)
library(crosstalk)
library(DT)

test <- dataset %>%
  group_by(Collected.Date, Test.Point.Description, Test.Result) %>%
  dplyr::summarise(Count = n(), .groups = 'drop')

shared_data <- SharedData$new(test, ~Test.Point.Description)

p <- ggplot(shared_data, aes(x = Collected.Date, y = Count, fill = Test.Result)) +
  geom_bar(stat = "identity", position = "stack") +
  scale_fill_manual(values = c("Pass" = "blue", "Fail" = "red")) +
  labs(title = "Test Results Over Time",
       x = "Collected Date",
       y = "Count of Test Result") +
  theme_minimal() +
  theme(axis.text.x = element_text(angle = 90, vjust = 0.5, hjust=1)) +
  coord_cartesian(xlim = as.Date(c("2023-07-23", "2024-01-22")))

p_interactive <- ggplotly(p)

filter_select <- filter_select(id = "filter_select", label = "Select Test Point Description", sharedData = shared_data, group = ~Test.Point.Description)

bscols(filter_select, p_interactive)

I attached image in R when I click on a specific filter. it just shows the dots.

here is the data set example

structure(list(Collected.Date = structure(c(19577, 19577, 19577, 19577, 19577, 19577), class = "Date"), Test.Point.Description = c("screen", "auger", "Boot", "blades", "wall", "seam"), Test.Result = c("Pass", "Pass", "Pass", "Pass", "Pass", "Fail")), row.names = c(NA, 6L), class = "data.frame")

After a look at your issue I'm afraid that this is one of the cases where the conversion from ggplot2 to plotly fails to account for the correct grouping. Instead I would suggest to create your chart using plot_ly().

Note: I use some fake random example data.

library(plotly)
library(crosstalk)
library(DT)

set.seed(123)

test <- expand.grid(
  Collected.Date = seq.Date(
    as.Date("2023-08-08"), as.Date("2024-01-23"),
    by = "week"
  ),
  Test.Point.Description = c("screen", "auger", "Boot", "blades", "wall", "seam"),
  Test.Result = c("Pass", "Pass", "Pass", "Pass", "Pass", "Fail")
)
test$Count <- sample(seq(10), size = nrow(dataset), replace = TRUE)

shared_data <- SharedData$new(test, ~Test.Point.Description)

p_interactive <- shared_data |>
  plot_ly(
    x = ~Collected.Date,
    y = ~Count,
    color = ~Test.Result
  ) |>
  add_bars(colors = c("blue", "red")) |>
  layout(
    barmode = "stack",
    title = "Test Results Over Time",
    xaxis = list(
      title = "Collected Date",
      range = as.Date(c("2023-07-23", "2024-01-22"))
    ),
    yaxis = list(title = "Count of Test Result")
  )

filter_select <- filter_select(
  id = "filter_select",
  label = "Select Test Point Description",
  sharedData = shared_data,
  group = ~Test.Point.Description
)

bscols(filter_select, p_interactive)