reconnectIris.rmd

---
title: "Iris K-Means Clustering"
output:
  flexdashboard::flex_dashboard:
    orientation: columns
    social: menu
    source_code: embed
runtime: shiny_prerendered
---

```{r global, include=FALSE}
# Running this app with the Knit button in RStudio may not work correctly.
# Use the following command, then connect to http://localhost:9000/
#
# rmarkdown::run("reconnectIris.Rmd",
#   shiny_args = list(launch.browser = FALSE, port = 9000))


# load data in 'global' chunk so it can be shared by all users of the dashboard
library(datasets)
data(iris)
```


Column {.sidebar}
-----------------------------------------------------------------------

```{r}
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)
```

Column
-----------------------------------------------------------------------

### K Means

```{r}
plotOutput("kmeans")
```


```{r, context="server"}
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)
})

output$kmeans <- renderPlot({
  par(mar = c(5.1, 4.1, 0, 1))
  plot(selectedData(),
       col = clusters()$cluster,
       pch = 20, cex = 3)
  points(clusters()$centers, pch = 4, cex = 4, lwd = 4)
})

session$allowReconnect("force")
```