Code Editor for app.R

library(shiny)
library(ggplot2)
library(dplyr)
source("data_prep.R")

ui <- fluidPage(
    titlePanel("Titanic Survival Prediction"),
    
    splitLayout(
        cellWidths = c("50%", "50%"),
        # Left panel
        wellPanel(
            selectInput("pclass", "Passenger Class:",
                       choices = c("1st" = "1", "2nd" = "2", "3rd" = "3")),
            selectInput("sex", "Sex:",
                       choices = c("Male", "Female")),
            numericInput("age", "Age:", value = 30, min = 0, max = 100),
            numericInput("sibsp", "Number of Siblings/Spouses:", value = 0, min = 0),
            numericInput("parch", "Number of Parents/Children:", value = 0, min = 0),
            actionButton("predict", "Predict Survival")
        ),
        # Right panel
        wellPanel(
            plotOutput("survivalPlot"),
            verbatimTextOutput("predictionText")
        )
    )
)

server <- function(input, output, session) {
    # Reactive value for prediction
    prediction <- eventReactive(input$predict, {
        new_passenger <- data.frame(
            Pclass = as.numeric(input$pclass),
            Sex = tolower(input$sex),
            Age = input$age,
            SibSp = input$sibsp,
            Parch = input$parch
        )
        predict(survival_model, newdata = new_passenger, type = "prob")[,2]
    })
    
    # Output prediction text
    output$predictionText <- renderText({
        prob <- prediction()
        paste("Survival Probability:", round(prob * 100, 1), "%")
    })
    
    # Output survival plot
    output$survivalPlot <- renderPlot({
        # Create plot showing survival rates by class and sex
        titanic_data %>%
            group_by(Pclass, Sex) %>%
            summarise(
                SurvivalRate = mean(Survived),
                .groups = 'drop'
            ) %>%
            ggplot(aes(x = factor(Pclass), y = SurvivalRate, fill = Sex)) +
            geom_bar(stat = "identity", position = "dodge") +
            scale_y_continuous(labels = scales::percent) +
            labs(x = "Passenger Class",
                 y = "Survival Rate",
                 title = "Survival Rates by Class and Sex") +
            theme_minimal()
    })
}

shinyApp(ui = ui, server = server)