Code Editor for app.R

library(shiny)
library(dplyr)
library(ggplot2)

source("utils.R")

ui <- fluidPage(
  titlePanel("URL Data Explorer"),
  
  sidebarLayout(
    sidebarPanel(
      textInput("url", "Enter CSV URL:",
                value = "https://raw.githubusercontent.com/mwaskom/seaborn-data/master/penguins.csv"),
      numericInput("n_rows", "Number of rows to display:", value = 10, min = 1),
      checkboxInput("shuffle", "Randomly shuffle data", value = FALSE),
      selectInput("var1", "Select first variable:", choices = NULL),
      selectInput("var2", "Select second variable (optional):", choices = NULL, selected = NULL),
      actionButton("update", "Update Data")
    ),
    
    mainPanel(
      tabsetPanel(
        tabPanel("Data", dataTableOutput("data_table")),
        tabPanel("Visualization", plotOutput("plot"))
      )
    )
  )
)

server <- function(input, output, session) {
  # Reactive value to store the data
  data <- reactiveVal()
  
  # Function to read and process data
  observeEvent(input$update, {
    tryCatch({
      df <- read_and_cache_csv(input$url)
      data(df)
      
      # Update variable choices
      updateSelectInput(session, "var1",
                       choices = c("", colnames(df)))
      updateSelectInput(session, "var2",
                       choices = c("", colnames(df)))
    }, error = function(e) {
      showNotification(paste("Error loading data:", e$message),
                      type = "error")
    })
  })
  
  # Reactive expression for displayed data
  displayed_data <- reactive({
    req(data())
    df <- data()
    
    if (input$shuffle) {
      df <- df[sample(nrow(df)), ]
    }
    
    df
  })
  
  # Display data table
  output$data_table <- renderDataTable({
    head(displayed_data(), input$n_rows)
  })
  
  # Create visualization
  output$plot <- renderPlot({
    req(displayed_data(), input$var1)
    
    df <- displayed_data()
    
    if (input$var1 == "") return(NULL)
    
    if (input$var2 == "") {
      # Single variable visualization
      create_univariate_plot(df, input$var1)
    } else {
      # Two variable visualization
      create_bivariate_plot(df, input$var1, input$var2)
    }
  })
  
  # Initialize data on startup
  observeEvent(1, {
    click("update")
  }, once = TRUE)
}

shinyApp(ui = ui, server = server)