inst/Apps/BeginnerExample/app.R

ui<- pageWithSidebar(
  headerPanel('Iris k-means clustering'),
  sidebarPanel(
    selectInput('xcol', 'X Variable', names(iris)),
    selectInput('ycol', 'Y Variable', names(iris),
                selected=names(iris)[[2]]),
    numericInput('clusters', 'Cluster count', 3,
                 min = 1, max = 9),
    h4("Some things to consider:"),
    p("What are reactive({}) expressions?"),
    p("How do input$ values work?"),
    p("What do they correspond to in the UI? (ie the \"xcol\" in \"input$xcol\""),
    p("What is k-means?"),
    p("How could you offer another clustering option?")
  ),

  mainPanel(
    plotOutput('plot1')
  )
)

server <- function(input, output, session) {

  # Combine the selected variables into a new data frame
  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 the application
shinyApp(ui = ui, server = server)
chasemc/Jan2018ShinyMeetupCRUG documentation built on May 13, 2019, 8:23 a.m.