Coursera Developing Data Products Week 4 Assignment

• This presentation is part of the assignment for week 4 of Developing Data Products course from Coursera (https://www.coursera.org/learn/data-products). It is meant to describe and pitch information about an app developed through Shiny to help property investors determine profitability of a specific property they are interested in investing in.

• The assignment was to develop a web application using R and the Shiny package. The application was named Property Investing and can be found here: https://tkasten-coursera.shinyapps.io/attempt4/

• A description of the Shiny package and examples of its functionality can be found here: http://shiny.rstudio.com

• In the application, anyone who is interested in purchasing property for investment purposes can input the purchase price or market value of a property and derive a range of weekly rents necessary to make a profit on the property. The output is generated through calculations programmed in R.

• The application allows users to include associated costs for owning property that might affect profitability like water usage and community fees (taxes).

An example of how the R code calculates the weekly profit or deficit for the property investor is below. Assuming the property costs the investor $200 per week and the weekly rent is $350. After deducting the quarterly water fees of $50 and the weekly community fees of $10, the property inverstor will earn a $136 weekly profit.

rent<-350
water<-50
fees<-10
mortgage<-200
  result <- (rent * 52 - (water) * 4 - fees * 52 - mortgage * 52) / 52
  return(round(result, digits = 2))

[1] 136.15

This app can be a very useful tool for property investors looking to do a quick calculation to deterine profitability. The github repository containing the Shiny programs (ui.R and server.R) are found here:

https://github.com/Tlkasten/Developing-Data-Products-Week-4-Assignment