Prior Proper Planning Before I jump into the historical stock prices, I want to create a plan of attack. A good place to start will be to look at what I have so far: I have my list of S&P 500 companies, now I need to find a website from which I can scrape their […]Read more "Rvest: Web Scrapping in R – Part II"
The inspiration for this post comes from R. Duncan McIntosh’s post on Florida’s 2016 Primaries, by way of his post as seen on R-Bloggers. EDIT: GitHub repo: https://github.com/SeaSmith1018/TexasPrimary2016 Texas Let’s take a look at some of the 2016 Texas Primary results. I will be using McIntosh’s example except I will be working with Texas data (of […]Read more "2016 Texas Primaries: Mapped"
Keep it simple Rvest is a super easy way to scrape data from a website. Why keep it this simple? I prefer R over something like VBA because VBA relies on a web browser called Edge and at one point it relied on Internet Explorer – enough said! Example To demonstrate rvest’s ability, I’ll use a simple […]Read more "Rvest: Web Scraping in R – Part I"
Where? Found some really awesome R cheat sheets courtesy of RStudio at this link. My favorite cheat sheet is Data Wrangling with dplyr and tidyr. Those two packages, by far, are the most useful CRAN packages for converting datasets into “tidy” data (normalized data). What? In case you missed it, R is the de facto data analysis programming-language, […]Read more "R you in need of help?"