This is an R Markdown presentation documenting Shiny Application, called IrisApps. The application provide visualization of Iris dataset in the form of Histogram, depending on the Iris's attribute that the user select.

The IrisApps can be found at: https://sitisoraya.shinyapps.io/IrisAppsV2/

The ui.r and server.r are hosted on: https://github.com/SitiSoraya/DP-Assignment-Week-4

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  
##                 
##                 
## 

• Form of input used: radio button and slider input.
• The ui consists of two layouts:
  • the sidebar panel, consists of radio buttons representing Iris's attributes, where the user can select to view in the form of histogram. The sidebar panel also consists of a slider input to specify bins range.
  • the main panel shows the generated histogram.

library(shiny)

ui <- fluidPage(

titlePanel("IrisApps"),

sidebarLayout(
    sidebarPanel(
        helpText("This Apps provide visualization of Iris dataset 
        in the form of Histogram, depending on the Iris's attribute 
        that the user select."),
        radioButtons("option", "Choose Iris attribute:",
        list("Sepal.Length"='a', "Sepal.Width"='b', "Petal.Length"='c',
        "Petal.Width"='d')),
        sliderInput("bins", "Specify the bins range:", min = 1, max = 50, 
        value = 30)
    ),
mainPanel(mainPanel(plotOutput("distPlot")) )))

server <- function(input, output) {

output$distPlot <- renderPlot({
    if(input$option=='a'){       
        i<-1     }     
    if(input$option=='b'){       
        i<-2     }     
    if(input$option=='c'){       
        i<-3     }     
    if(input$option=='d'){       
        i<-4     }
    
    x    <- iris[, i] 
    bins <- seq(min(x), max(x), length.out = input$bins + 1)
    
    hist(x, main = "Histogram of Iris Dataset", xlab = "Iris Attribute", 
    ylab = "Frequency", breaks = bins, col = 'blue', border = 'white')
}) }