# load data in 'global' chunk so it can be shared by all users of the dashboard library(datasets) data(iris)
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)
palette(c("#E41A1C", "#377EB8", "#4DAF4A", "#984EA3", "#FF7F00", "#FFFF33", "#A65628", "#F781BF", "#999999")) # Combine the selected variables into a new data frame selectedData <- reactive({ iris[, c(input$xcol, input$ycol)] }) clusters <- reactive({ kmeans(selectedData(), input$clusters) }) renderPlot({ par(mar = c(5.1, 4.1, 0, 1)) plot(selectedData(), col = clusters()$cluster, pch = 20, cex = 3) points(clusters()$centers, pch = 4, cex = 4, lwd = 4) })
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