Creating reactive renderUI - r

Question

I am following this tutorial to learn to build Shiny apps. In the final version, the renderUI() for "Country" just takes all of the countries in the dataset. Is there a way to make this list reactive/filtered based on the price range selected with the slider?
Here is the relevant code:
output$countryOutput <- renderUI({
selectInput("countryInput", "Country",
sort(unique(bcl$Country)),
selected="CANADA")
})
And here is the entire. very simple app:
library(shiny)
library(ggplot2)
library(dplyr)
bcl <- read.csv("bcl-data.csv", stringsAsFactors = FALSE)
ui <- fluidPage(
titlePanel("BC Liquor Prices", windowTitle = "Mmmmm yeh"),
sidebarLayout(
sidebarPanel(
sliderInput("priceInput", "Price",
min = 0, max = 100,
value = c(25, 40), pre = "$"
),
radioButtons("typeInput", "Product type",
choices = c("BEER", "REFRESHMENT", "SPIRITS", "WINE"),
selected = "WINE"
),
uiOutput("countryOutput")
),
mainPanel(plotOutput("coolplot"),
br(),
br(),
tableOutput("results")
)
)
)
server <- function(input, output, session) {
filtered <- reactive({
if (is.null(input$countryInput)) {return(NULL)}
bcl %>%
filter(
Price >= input$priceInput[1],
Price <= input$priceInput[2],
Type == input$typeInput,
Country == input$countryInput
)
})
output$countryOutput <- renderUI({
selectInput("countryInput", "Country",
sort(unique(bcl$Country)),
selected="CANADA")
})
output$coolplot <- renderPlot({
if (is.null(filtered())) {return()}
ggplot(filtered(), aes(Alcohol_Content)) + geom_histogram()
})
output$results <- renderTable({
filtered()
})
}
shinyApp(ui = ui, server = server)

Answer 1

Try this code...You need two different reactive values: 1) One to generate the country list based on first two inputs and 2) Two two generate the plot and table results based on the selected country.
Also, I changed the names to reflect the actual column names I get when reading that file. You may need to change back IF you changed them in some other part of the code.
library(shiny)
library(ggplot2)
library(dplyr)
bcl <- read.csv("bcl-data.csv", stringsAsFactors = FALSE)
ui <- fluidPage(
titlePanel("BC Liquor Prices", windowTitle = "Mmmmm yeh"),
sidebarLayout(
sidebarPanel(
sliderInput("priceInput", "Price",
min = 0, max = 100,
value = c(25, 40), pre = "$"
),
radioButtons("typeInput", "Product type",
choices = c("BEER", "REFRESHMENT", "SPIRITS", "WINE"),
selected = "BEER"
),
uiOutput("countryOutput")
),
mainPanel(plotOutput("coolplot"),
br(),
br(),
tableOutput("results")
)
)
)
server <- function(input, output, session) {
filteredForCountry <- reactive({
bcl %>%
filter(
CURRENT_DISPLAY_PRICE >= input$priceInput[1],
CURRENT_DISPLAY_PRICE <= input$priceInput[2],
PRODUCT_SUB_CLASS_NAME == input$typeInput
)
})
output$countryOutput <- renderUI({
df <- filteredForCountry()
if (!is.null(df)) {
selectInput("countryInput", "Country",
sort(unique(df$PRODUCT_COUNTRY_ORIGIN_NAME)),
selected="CANADA")
}
})
filteredFull <- reactive({
if (is.null(input$countryInput)) {
return (filteredForCountry())
}
bcl %>%
filter(
CURRENT_DISPLAY_PRICE >= input$priceInput[1],
CURRENT_DISPLAY_PRICE <= input$priceInput[2],
PRODUCT_SUB_CLASS_NAME == input$typeInput,
PRODUCT_COUNTRY_ORIGIN_NAME == input$countryInput
)
})
output$coolplot <- renderPlot({
if (is.null(filteredFull())) {return()}
ggplot(filteredFull(), aes(PRODUCT_ALCOHOL_PERCENT)) +
geom_histogram(binwidth = 0.05)
})
output$results <- renderTable({
filteredFull()
})
}
shinyApp(ui = ui, server = server)