We’re in the middle of College Football’s bowl post-season and I’d been wanting to do a more in-depth post on networks using {tidygraph} and {ggraph} for a while. So now seemed like as good a time as any to explore some College Football data.
I love movies. I enjoy watching them, I enjoy reading about the industry (sometimes), and as a bit of a data-nerd (exhibit a: my blog), I enjoy learning about the outliers in the industry.
Since 1998, MTV’s The Challenge (formerly the Real World/Road Rules Challenge) has graced the airwaves where it is currently in Season 37. In a prior post I had mentioned that this is one of my guilty pleasure shows so this will likely not be the last post that is based around America’s 5th professional sport.
Introduction Between January 13th and January 27th, 2021 the stock price for Gamestop (GME) rose 10x from $31 to $347 dollars. This rise was in part due to increased popularity on the Reddit forum r/wallstreetbets looking to create a short squeeze and because they “liked the stock”.
I’m a big proponent of enabling the reading time option on this blog which uses Hugo’s academic theme. I always appreciate seeing it on other blogs so I know how much time to invest in the post.
On July 4th, 2020, I posted the first article to this humble R blog as a small hobby to do something new while working from home through COVID. Very recently, this blog celebrated its first year and I wanted to leverage Google Analytics to do a look back at the last year, what’s done well as well as when and where people were visiting from.
In the beginning of May, I used RSelenium to scrape the Google Play Store reviews for Instagram Lite to demonstrate how the package can be used to automate browser behavior.
During COVID I’ve started watching some older “classic” movies that I hadn’t seen before but felt for whatever reason I should have seen as a movie fan. Last week, I had watched The Third Man after listening to a podcast about Spy Movies.
When Normal Web Scraping Just Won’t Work I’ve used rvest in numerous posts to scrape information from static websites or through forms to get data. However, some websites don’t have static data that can be downloaded by just scraping the HTML.
In a previous post I created a cool-looking (in my opinion) heatmap of my Marathon training from years back. One of the downsides to that density-based method of making the heat map was that routes I only ran once didn’t show up very clearly.