Shiny Dashboard of Breast Cancer Wisconsin Data

library(shiny)

## Warning: package 'shiny' was built under R version 4.2.2

library(shinydashboard)

## Warning: package 'shinydashboard' was built under R version 4.2.2

## 
## Attaching package: 'shinydashboard'

## The following object is masked from 'package:graphics':
## 
##     box

library(ggplot2)

## Warning: package 'ggplot2' was built under R version 4.2.2

# Load the data
data <- read.csv("https://archive.ics.uci.edu/ml/machine-learning-databases/breast-cancer-wisconsin/wdbc.data", header = FALSE)

# Preprocess the data
data <- data[-1]
data$V2 <- as.factor(data$V2)

# Define the UI
ui <- dashboardPage(
  dashboardHeader(title = "Breast Cancer Wisconsin 20BDS0177"),
  dashboardSidebar(
    selectInput("variable1", "Select variable 1", names(data)[-1]),
    selectInput("variable2", "Select variable 2", names(data)[-1])
  ),
  dashboardBody(
    fluidRow(
      box(
        plotOutput("scatterplot"),
        width = 6
      ),
      box(
        plotOutput("boxplot"),
        width = 6
      )
    ),
    fluidRow(
      box(
        plotOutput("histogram"),
        width = 6
      ),
      box(
        plotOutput("densityplot"),
        width = 6
      )
    ),
    fluidRow(
      box(
        tableOutput("summary"),
        width = 12
      )
    ),
    fluidRow(
      box(
        downloadButton("downloadData", "Download Data"),
        width = 12
      )
    )
  )
)

# Define the server
server <- function(input, output) {
  
  # Create the scatterplot
  output$scatterplot <- renderPlot({
    ggplot(data, aes_string(x = input$variable1, y = input$variable2, color = "V2")) +
      geom_point()
  })
  
  # Create the boxplot
  output$boxplot <- renderPlot({
    ggplot(data, aes_string(x = "V2", y = input$variable1)) +
      geom_boxplot()
  })
  
  # Create the histogram
  output$histogram <- renderPlot({
    ggplot(data, aes_string(x = input$variable1, fill = "V2")) +
      geom_histogram(alpha = 0.5, position = "identity", bins = 30)
  })
  
  # Create the densityplot
  output$densityplot <- renderPlot({
    ggplot(data, aes_string(x = input$variable1, fill = "V2")) +
      geom_density(alpha = 0.5) +
      labs(title = paste("Density plot of", input$variable1))
  })
  
  # Create the summary table
  output$summary <- renderTable({
    summary(data)
  })
  
  # Download the data
  output$downloadData <- downloadHandler(
    filename = function() {
      paste("breast-cancer-wisconsin-", Sys.Date(), ".csv", sep = "")
    },
    content = function(file) {
      write.csv(data, file)
    }
  )
}

# Run the app
shinyApp(ui, server)

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