Overview

The shiny app have following features

• plots graph against miles per gallon (mpg) for different variables like Displacement,Gross Horsepower,Rear axle ratio,Weigh,Number of forward gears,Number of carburetors, number of cylinders from the mtcars dataset.

• Displays relationship between various car features with respect to miles per gallon (MPG)

• Motor Trend Car Road Tests Datasets was extracted from the 1974 Motor Trend US magazine, and comprises fuel consumption and 10 aspects of automobile design and performance for 32 automobiles (1973-74 models).

• Source is Henderson and Velleman (1981), Building multiple regression models interactively. Biometrics, 37, 391-411.

Shiny App and reproducible pitch

• Shiny Application - This is a task for the data science coursera course about developing data products for week 4. As part of this, I have created a shiny app and deployed it on the shiny server. The link is https://prabeeti.shinyapps.io/DevelopingDataProducts_Week4Project/.

• Reproducible Pitch - There are 5 slides (inclusive of the title slide) to pitch shiny app. I have created a web page using Rstudio Presenter with an html5 slide deck. http://rpubs.com/prabeeti/558006

• URL: *https://github.com/prabeeti/Developing-Data-Products*- All the data that have been use for this presentation and also for the creation of Shiny application and deploy it on Rstudio’s servers.

mtcars Dataset - A data frame with 32 observations on 11 variables.

##                mpg cyl disp  hp drat    wt  qsec vs am gear carb
## Mazda RX4     21.0   6  160 110 3.90 2.620 16.46  0  1    4    4
## Mazda RX4 Wag 21.0   6  160 110 3.90 2.875 17.02  0  1    4    4
## Datsun 710    22.8   4  108  93 3.85 2.320 18.61  1  1    4    1

Analysis - Main Code

  formulaTextPoint <- reactive({
    paste("mpg ~", "as.integer(", input$variable, ")")  })
  
  fit <- reactive({
    lm(as.formula(formulaTextPoint()), data=mtcars)  })
  ...
  output$fit <- renderPrint({
    summary(fit()) })
  
  output$mpgPlot <- renderPlot({
    with(mtcars, {
      plot(as.formula(formulaTextPoint()))
      abline(fit(), col=2)
    })  })