docs/interactive/shiny/_examples/k-means/shiny-k-means.qmd

---
title: "Iris K-Means Clustering"
format: 
  html:
    page-layout: full
    code-tools:
      source: https://github.com/quarto-dev/quarto-web/blob/main/docs/interactive/shiny/_examples/k-means/shiny-k-means.qmd
server: shiny
---

```{r}
#| panel: sidebar
vars <- setdiff(names(iris), "Species")
selectInput('xcol', 'X Variable', vars)
selectInput('ycol', 'Y Variable', vars, selected = vars[[2]])
numericInput('clusters', 'Cluster count', 3, min = 1, max = 9)
```

```{r}
#| panel: fill
plotOutput('plot1')
```

```{r}
#| context: server
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)
})
```