Update app.R

app.R

@@ -1,9 +1,9 @@
 library(shiny)
 library(dplyr)
 library(shinythemes)
-library(highcharter)
+library(plotly)
 
-# Generate synthetic data with U-shaped & inverted U-shaped effects
+# Generate synthetic data
 generate_complex_data <- function() {
   set.seed(123)
   days <- 30
@@ -19,30 +19,18 @@ generate_complex_data <- function() {
     pricePoint = sample(40:100, days, replace = TRUE),
     stockAvailability = sample(40:100, days, replace = TRUE)
   )
-  
-  # U-shaped effect on pricePoint
-  price_factor <- -0.7 * (data$pricePoint - 70)^2
-  
-  # Inverted U-shaped effect on foot traffic
-  foot_traffic_effect <- 2.5 * (data$footTraffic - 400) + 80
-  
-  # Realistic effect of stock availability (moderate stock works better)
-  stock_effect <- 0.60 * (data$stockAvailability - 70) + 50
-  
-  # Final sales equation
+
+  price_factor <- -1.7 * (data$pricePoint - 70)^2
+  foot_traffic_effect <- 2.5 * (data$footTraffic - 200) + 80
+  stock_effect <- 0.80 * (data$stockAvailability - 70) + 50
+
   data$sales <- round(
-    foot_traffic_effect +      # Inverted U-shaped
-      data$adSpend * 0.2 +     
-      data$discountPercent * 10 + 
-      data$socialMediaEngagement * 0.1 + 
-      (data$competitorDistance) * 45 + 
-      data$websiteVisits * 0.15 + 
-      price_factor +           # U-shaped
-      stock_effect +           # Realistic stock effect
-      runif(days, -100, 100)   # Random noise
+    foot_traffic_effect + data$adSpend * 0.2 + data$discountPercent * 60 +
+      data$socialMediaEngagement * 0.5 + data$competitorDistance * 150 +
+      data$websiteVisits * 0.15 + price_factor + stock_effect + runif(days, -40, 40)
   )
-  
-  data$sales <- pmax(data$sales, 0) # Ensure non-negative sales
+
+  data$sales <- pmax(data$sales, 0)
   return(data)
 }
 
@@ -51,33 +39,33 @@ store_data <- generate_complex_data()
 # UI
 ui <- fluidPage(
   theme = shinytheme("cosmo"),
-  
-  titlePanel("Fashion Sales Simulator - Highcharter Edition"),
-  
+  titlePanel("Fashion Sales Simulator - Plotly Edition"),
   tabsetPanel(
     tabPanel("Guided Analysis",
              sidebarLayout(
                sidebarPanel(
                  selectInput("selected_metric", "Select a Variable:", 
                              choices = names(store_data)[-c(1,2,10)],
-                             selected = "footTraffic")
+                             selected = "footTraffic"),
+                 checkboxInput("show_trend", "Show Linear Trend Line", FALSE)
                ),
                mainPanel(
-                 highchartOutput("guided_plot"),
+                 plotlyOutput("guided_plot"),
                  verbatimTextOutput("correlation")
                )
              )
     ),
-    
+
     tabPanel("Free Exploration",
              sidebarLayout(
                sidebarPanel(
                  selectInput("x_var", "Select X Variable:", choices = names(store_data)[-c(1,2,10)]),
                  selectInput("y_var", "Select Y Variable:", choices = names(store_data)[-c(1,2,10)]),
+                 checkboxInput("show_trend_explore", "Show Linear Trend Line", FALSE),
                  actionButton("compute_corr", "Compute Correlation")
                ),
                mainPanel(
-                 highchartOutput("free_explore_plot"),
+                 plotlyOutput("free_explore_plot"),
                  verbatimTextOutput("free_corr_output")
                )
              )
@@ -87,70 +75,47 @@ ui <- fluidPage(
 
 # Server
 server <- function(input, output, session) {
-  
-  # Compute correlation dynamically
   compute_correlation <- function(x, y) {
     cor(store_data[[x]], store_data[[y]], use = "complete.obs")
   }
-  
-  # Guided Analysis Highchart Plot
-  output$guided_plot <- renderHighchart({
-    data_points <- lapply(1:nrow(store_data), function(i) {
-      list(store_data[[input$selected_metric]][i], store_data$sales[i])
-    })
-    
-    highchart() %>%
-      hc_chart(type = "scatter") %>%
-      hc_title(text = paste("Sales vs", input$selected_metric)) %>%
-      hc_xAxis(title = list(text = input$selected_metric)) %>%
-      hc_yAxis(title = list(text = "Sales")) %>%
-      hc_add_series(
-        data = data_points,
-        type = "scatter",
-        name = "Data Points",
-        marker = list(radius = 4),
-        color = "blue"
-      ) %>%
-      hc_tooltip(pointFormat = paste0(
-        "<b>", input$selected_metric, ":</b> {point.x}<br>",
-        "<b>Sales:</b> {point.y}"
-      )) %>%
-      hc_exporting(enabled = TRUE)
+
+  output$guided_plot <- renderPlotly({
+    p <- plot_ly(store_data, x = ~get(input$selected_metric), y = ~sales, type = 'scatter', mode = 'markers',
+                 marker = list(color = 'blue')) %>%
+      layout(title = paste("Sales vs", input$selected_metric),
+             xaxis = list(title = input$selected_metric),
+             yaxis = list(title = "Sales"))
+
+    if (input$show_trend) {
+      model <- lm(sales ~ get(input$selected_metric), data = store_data)
+      trend_line <- data.frame(x = store_data[[input$selected_metric]], y = predict(model))
+      trend_line <- trend_line[order(trend_line$x), ]
+      p <- p %>% add_lines(x = ~trend_line$x, y = ~trend_line$y, name = "Trend Line", line = list(color = 'red'))
+    }
+    p
   })
-  
+
   output$correlation <- renderText({
     corr_value <- compute_correlation(input$selected_metric, "sales")
     paste("Correlation with Sales:", round(corr_value, 3))
   })
-  
-  # Free Exploration Scatter Plot with Highcharter
-  output$free_explore_plot <- renderHighchart({
-    req(input$x_var, input$y_var)
-    
-    data_points <- lapply(1:nrow(store_data), function(i) {
-      list(store_data[[input$x_var]][i], store_data[[input$y_var]][i])
-    })
-    
-    highchart() %>%
-      hc_chart(type = "scatter") %>%
-      hc_title(text = paste(input$x_var, "vs", input$y_var)) %>%
-      hc_xAxis(title = list(text = input$x_var)) %>%
-      hc_yAxis(title = list(text = input$y_var)) %>%
-      hc_add_series(
-        data = data_points,
-        type = "scatter",
-        name = "Data Points",
-        marker = list(radius = 4),
-        color = "red"
-      ) %>%
-      hc_tooltip(pointFormat = paste0(
-        "<b>", input$x_var, ":</b> {point.x}<br>",
-        "<b>", input$y_var, ":</b> {point.y}"
-      )) %>%
-      hc_exporting(enabled = TRUE)
+
+  output$free_explore_plot <- renderPlotly({
+    p <- plot_ly(store_data, x = ~get(input$x_var), y = ~get(input$y_var), type = 'scatter', mode = 'markers',
+                 marker = list(color = 'green4')) %>%
+      layout(title = paste(input$x_var, "vs", input$y_var),
+             xaxis = list(title = input$x_var),
+             yaxis = list(title = input$y_var))
+
+    if (input$show_trend_explore) {
+      model <- lm(get(input$y_var) ~ get(input$x_var), data = store_data)
+      trend_line <- data.frame(x = store_data[[input$x_var]], y = predict(model))
+      trend_line <- trend_line[order(trend_line$x), ]
+      p <- p %>% add_lines(x = ~trend_line$x, y = ~trend_line$y, name = "Trend Line", line = list(color = 'red'))
+    }
+    p
   })
-  
-  # Compute correlation in Free Exploration
+
   observeEvent(input$compute_corr, {
     output$free_corr_output <- renderText({
       corr_value <- compute_correlation(input$x_var, input$y_var)
@@ -159,5 +124,4 @@ server <- function(input, output, session) {
   })
 }
 
-# Run App
 shinyApp(ui, server)