How to change the data source which is used for a plot depending on the selected dropdown menu in R-CodePudding

My situation is the following that I import a csv dataset from IMDB into my small Shiny app. It contains in the respective columns the values for runtime, IMDB-Rating, gross, votes, Meta-Score Rating etc...

I have in the UI-section a selectInput where the user can select the available columns as mentioned above.

In the Server-Section (before my output$graph <- renderPlot(...)) I want to describe/implement that the outputPlot changes depending on the selected column. I tried to solve it using observeEvent like this...

  observeEvent(~get(input$type) == "Meta-Score", {ratings <- moviesdb$Meta_score})
  observeEvent(~get(input$type) == "IMDB-Rating", {ratings <- moviesdb$IMDB_Rating})
  etc...

using the global operator <<- and even using some type of switch-case logic:

   x <- reactive(~get(input$type))
   y <- NULL
   test <- switch(c(x),
                  "Meta-Score" = {(ratings <- moviesdb$Meta_score)},
                  "IMDB-Rating" = {(ratings <- moviesdb$IMDB_Rating)},
                  "Film-Laufzeit" = {(ratings <- moviesdb$Runtime)})

I really appreciate any help/hints/tips or even mock-up code on how to solve this problem! Since yesterday I am googling but I just dont find any solution or question which seems to be similar to what I want to achieve.

Example Code:

library(shiny)
library(ggplot2)

moviesdb <- read.csv("imdb_top_1000.csv", header=TRUE)
moviesdb <- na.omit(moviesdb) #remove NA from data set

ui <- fluidPage(
  
  selectInput(
    inputId = "type",
    label = "choose type",
    choices = c("Meta-Score", "Votes"),
    selected = "Meta-Score",
    multiple = FALSE,
    selectize = TRUE,
    width = NULL,
    size = NULL
  ), 
  
  sliderInput(inputId = "num", label = "sample size", value = 500, min = 0, max = 800, step = 10), 
  plotOutput("distribution"),
  
)


server <- function(input, output) {
  
  ratings <- moviesdb$Meta_score
  # x <- reactive(~get(input$type))
  # y <- NULL
  # test <- switch(c(x),
  #                "Meta-Score" = {(ratings <- moviesdb$Meta_score)},
  #               "Votes" = {(ratings <- moviesdb$No_of_Votes)},
  # y

  # observeEvent(ratings, {
  #   print(paste0("You have chosen: ", ratings))
  # })

  
  output$distribution <- renderPlot(
    {
      
      filmratingssample <- (sample(ratings, input$num, replace = FALSE, prob = NULL))
      mean_films <- mean(filmratingssample)
      films <- data.frame(dnorm(filmratingssample, mean = mean_films, sd = 1, log = FALSE))
      
      ggplot(data = films)   aes(x=filmratingssample)  
        geom_histogram(aes(y=..density..), col = "white", binwidth=1)
      
      
      
    })

}

shinyApp(ui = ui, server = server)

Dataset from

NOTE:

I tested on data at https://raw.githubusercontent.com/peetck/IMDB-Top1000-Movies/master/IMDB-Movie-Data.csv