Interactive bar chart with multiple conditioning variables and default shown distribution is unconditioned

Question

My aim is to make an interactive bar chart. The reader sees summary statistics of a variable, and can then choose to see the distribution of that variable conditioned on other variables. For example, they see the average total_bill for restaurant guests at lunch and dinner time. They can then choose to see how that varies by sex OR by age. Below is an example, which I modified from here.

library(ggplot)
library(plotly)

#Sex
dat1 <- data.frame(
  sex = c("Female", "Female", "Male", "Male", 'Any', 'Any'),
  time = c("Lunch", "Dinner", "Lunch", "Dinner", 'Lunch', 'Dinner'),
  total_bill = c(13.53, 16.81, 16.24, 17.42, 14.5, 17.3)
)

p <- ggplot(data=dat1, aes(x=time, y=total_bill, fill=sex)) +
  geom_bar(stat="identity", position=position_dodge())

fig1 <- ggplotly(p)

fig1

#Age
dat2 <- data.frame(
  age = c('Old', 'Old', 'Young', 'Young', 'Any', 'Any'),
  time = c("Lunch","Dinner","Lunch","Dinner", 'Lunch', 'Dinner'),
  total_bill = c(14.53, 15.81, 18.24, 19.42, 14.5, 17.3)
)

p <- ggplot(data=dat2, aes(x=time, y=total_bill, fill=age)) +
  geom_bar(stat="identity", position=position_dodge())

fig2 <- ggplotly(p)

fig2

Here are the problems with this approach:

1. in both plots, the total_bill for all three groups is shown per the default.
2. conditioning on sex and age occurs in two separate plots. It would be nice with a dropdown menu to the left, where the user could choose to condition on sex/age.

I am open to other interactive solutions. The issue with shiny is that it requires me to host it on a server, and I need to be able to send the report to people so they can also have it when they are offline. There is this solution, but I am hoping to achieve this without having to learn a new programming language (i.e., OJS).