The web application was built to demonstriate the shiny apps by analysing the iris data. Working application can be accessed at https://ramch.shinyapps.io/shiny_app/ Source code can be found at github repository url https://github.com/raamch/shiny

• This app is based on the iris data set. More details on iris data set can be dound at https://archive.ics.uci.edu/ml/datasets/iris
• The application allows user to perform k-means clustering on iris data set
• The user can select any 2 variables of interest for analysis.
• The user can select the number of clusters.

summary(iris)

##   Sepal.Length    Sepal.Width     Petal.Length    Petal.Width   
##  Min.   :4.300   Min.   :2.000   Min.   :1.000   Min.   :0.100  
##  1st Qu.:5.100   1st Qu.:2.800   1st Qu.:1.600   1st Qu.:0.300  
##  Median :5.800   Median :3.000   Median :4.350   Median :1.300  
##  Mean   :5.843   Mean   :3.057   Mean   :3.758   Mean   :1.199  
##  3rd Qu.:6.400   3rd Qu.:3.300   3rd Qu.:5.100   3rd Qu.:1.800  
##  Max.   :7.900   Max.   :4.400   Max.   :6.900   Max.   :2.500  
##        Species  
##  setosa    :50  
##  versicolor:50  
##  virginica :50  
##                 
##                 
## 

selectedData <- reactive({ iris[, c(input\(xcol, input\)ycol)] })

clusters <- reactive({ kmeans(selectedData(), input$clusters) })