{"app.R": "library(shiny)\nlibrary(dplyr)\nlibrary(ggplot2)\n\nsource(\"ui.R\")\nsource(\"server.R\")\n\nshinyApp(ui = ui, server = server)", "server.R": "library(magrittr)\nlibrary(DT)\nlibrary(shiny)\nlibrary(dplyr)\nlibrary(ggplot2)\n\ncache <- new.env()\n\nserver <- function(input, output, session) {\n data <- reactive({\n input$refresh # Add dependency on refresh button\n \n # Check if data is in cache\n if (!is.null(cache[[input$url]])) {\n df <- cache[[input$url]]\n } else {\n df <- read.csv(input$url)\n cache[[input$url]] <- df\n }\n \n if (input$shuffle) {\n df <- df[sample(nrow(df)), ]\n }\n \n df\n })\n \n # Update variable select inputs when data changes\n observe({\n df <- data()\n updateVarSelectInput(session, \"var1\", data = df)\n updateVarSelectInput(session, \"var2\", data = df)\n })\n \n # Render table\n output$table <- renderDataTable({\n head(data(), input$n_rows)\n })\n \n # Render plot\n output$plot <- renderPlot({\n req(input$var1)\n df <- data()\n \n if (is.null(input$var2) || input$var2 == \"\") {\n # Single variable visualization\n if (is.numeric(df[[input$var1]])) {\n # Histogram for numeric variables\n ggplot(df, aes(!!input$var1)) +\n geom_histogram(bins = 30, fill = \"steelblue\", color = \"white\") +\n theme_minimal() +\n labs(title = paste(\"Distribution of\", input$var1))\n } else {\n # Bar plot for categorical variables\n ggplot(df, aes(!!input$var1)) +\n geom_bar(fill = \"steelblue\") +\n theme_minimal() +\n labs(title = paste(\"Distribution of\", input$var1)) +\n theme(axis.text.x = element_text(angle = 45, hjust = 1))\n }\n } else {\n # Two variable visualization\n if (is.numeric(df[[input$var1]]) && is.numeric(df[[input$var2]])) {\n # Scatter plot for two numeric variables\n ggplot(df, aes(!!input$var1, !!input$var2)) +\n geom_point(alpha = 0.6) +\n theme_minimal() +\n labs(title = paste(input$var1, \"vs\", input$var2))\n } else if (!is.numeric(df[[input$var1]]) && is.numeric(df[[input$var2]])) {\n # Box plot for categorical x numeric\n ggplot(df, aes(!!input$var1, !!input$var2)) +\n geom_boxplot(fill = \"steelblue\", alpha = 0.6) +\n theme_minimal() +\n labs(title = paste(input$var2, \"by\", input$var1)) +\n theme(axis.text.x = element_text(angle = 45, hjust = 1))\n } else if (is.numeric(df[[input$var1]]) && !is.numeric(df[[input$var2]])) {\n # Box plot for numeric x categorical (flipped)\n ggplot(df, aes(!!input$var2, !!input$var1)) +\n geom_boxplot(fill = \"steelblue\", alpha = 0.6) +\n theme_minimal() +\n labs(title = paste(input$var1, \"by\", input$var2)) +\n theme(axis.text.x = element_text(angle = 45, hjust = 1))\n } else {\n # Heatmap for two categorical variables\n df %>%\n count(!!input$var1, !!input$var2) %>%\n ggplot(aes(!!input$var1, !!input$var2, fill = n)) +\n geom_tile() +\n scale_fill_viridis_c() +\n theme_minimal() +\n labs(title = paste(input$var1, \"vs\", input$var2)) +\n theme(axis.text.x = element_text(angle = 45, hjust = 1))\n }\n }\n })\n}", "ui.R": "library(DT)\nlibrary(shiny)\n\nui <- fluidPage(\n titlePanel(\"Penguins Data Visualization\"),\n \n sidebarLayout(\n sidebarPanel(\n textInput(\"url\", \"CSV URL:\", \n value = \"https://raw.githubusercontent.com/mwaskom/seaborn-data/master/penguins.csv\"),\n \n numericInput(\"n_rows\", \"Number of rows to display:\", \n value = 10, min = 1, max = 1000),\n \n checkboxInput(\"shuffle\", \"Randomly shuffle data\", FALSE),\n \n varSelectInput(\"var1\", \"Select first variable:\", data = NULL),\n varSelectInput(\"var2\", \"Select second variable (optional):\", \n data = NULL, multiple = FALSE),\n \n actionButton(\"refresh\", \"Refresh Data\")\n ),\n \n mainPanel(\n tabsetPanel(\n tabPanel(\"Data\", dataTableOutput(\"table\")),\n tabPanel(\"Plot\", plotOutput(\"plot\"))\n )\n )\n )\n)", "install.R": "install.packages('DT')\ninstall.packages('dplyr')\ninstall.packages('ggplot2')\ninstall.packages('magrittr')\ninstall.packages('shiny')", "startApp.R": "\nlibrary(shiny)\noptions(shiny.host = '0.0.0.0')\noptions(shiny.port = 80)\nrunApp('app.R')\n"}