This is a presentation for the Coursera Data Class “Developing Data products”. The objective of the class was to write a shiny app. The app which was created is based on the iris dataset. The goal ist to give the user the opportunity to create a plot with to different variables from the iris dataset. The plot automatically creates to lines. One line is fixed and represents a linear model. The other lines lowess ist configurable via the app. The following slides show the R code for the ui and server side and on the last slide an example of one possible configuration of the plot is shown.

• The application can be found in the following link

• https://petergajda.shinyapps.io/ProgrammingAssignment_9-4/

• The source code is hosted in the following link

• https://github.com/petergajda/ProgrammingAssignment_9-4

library(datasets)
fluidPage(    
  titlePanel("Iris Data Set"),
  sidebarLayout(      
    sidebarPanel(
      selectInput("option1", "Option Y-Axis:", choices=colnames(iris[1:4])),
      selectInput("option2", "Option X-Axis:", choices=colnames(iris[1:4])),
      hr(), 
      helpText("Data from iris data set (1936)."),
      hr(),
      sliderInput("lowess", "Line lowess:", min = 0.01, max = 1, value = 0.5),
      hr(),
      helpText("Please use this app to create...")
      ),
    mainPanel(
      plotOutput("irisPlot")  
    )
  )
)

library(datasets)
function(input, output) {
 output$irisPlot <- renderPlot({
    plot(iris[,input$option1] ~ iris[,input$option2],
            main=paste("This graph shows", input$option1, "by", input$option2),
            pch = 3,
            ylab=input$option1,
            xlab=input$option2,
            col=c("red", "green", "blue"))
         abline(lm(iris[,input$option1] ~ iris[,input$option2]), col="black", 
                lwd=3, lty=4)
         lines(lowess(iris[,input$option1] ~ iris[,input$option2],
                      f = input$lowess), col = 'black', lwd=3, lty=4)
         legend('topright', legend = unique(iris$Species), 
                col = c("red", "green", "blue"), pch = 3)

Via iris[,input$option1] or iris[,input$option2] the app gets the information which column from the iris dataset has to be used. Via input$lowess in the f argument in the lines function the app gets the information about the lowess level.