inst/k-means-clustering/app.R

In Poduval/rshinytool: rshinytool

library(shiny)

# ==== Define UI ====

vars <- setdiff(names(iris), "Species")

ui <- pageWithSidebar(
  headerPanel('Iris k-means clustering'),
  sidebarPanel(
    selectInput('xcol', 'X Variable', vars),
    selectInput('ycol', 'Y Variable', vars, selected = vars[[2]]),
    numericInput('clusters', 'Cluster count', 3, min = 1, max = 9)
  ),
  mainPanel(
    plotOutput('plot1')
  )
)

# ==== Define server ====
server <- function(input, output, session) {
  
  selectedData <- reactive({
    iris[, c(input$xcol, input$ycol)]
  })
  
  clusters <- reactive({
    kmeans(selectedData(), input$clusters)
  })
  
  output$plot1 <- renderPlot({
    palette(c("#E41A1C", "#377EB8", "#4DAF4A", "#984EA3",
              "#FF7F00", "#FFFF33", "#A65628", "#F781BF", "#999999"))
    
    par(mar = c(5.1, 4.1, 0, 1))
    plot(selectedData(),
         col = clusters()$cluster,
         pch = 20, cex = 3)
    points(clusters()$centers, pch = 4, cex = 4, lwd = 4)
  })
}

# ==== run app ====
shinyApp(ui = ui, server = server)