Scraping Pro-Football Data and Interactive Charts using rCharts, ggplot2, and shiny

February 10, 2014

(This article was first published on Adventures in Analytics and Visualization, and kindly contributed to R-bloggers)

This post uses pro-football (American) boxscore data from 1966 through 2013 and generates few interactive charts using rCharts, ggplot2 and shiny.  It also provided a first time exposure to the power of dplyr. Data for these charts were scraped from the excellent reference site,, using a function written in R. (This site has been used previously by other bloggers as a source for their data as well. See here and here for two examples.) Rest of this post has been created using slidify. The code for this post and relevant data are available at github. The code for the shiny application can be found here on github. (shiny is amazing, thanks R-Studio team and a big thanks to Ramnath Vaidyanathan for his support on rCharts).

To leave a comment for the author, please follow the link and comment on their blog: Adventures in Analytics and Visualization. offers daily e-mail updates about R news and tutorials on topics such as: Data science, Big Data, R jobs, visualization (ggplot2, Boxplots, maps, animation), programming (RStudio, Sweave, LaTeX, SQL, Eclipse, git, hadoop, Web Scraping) statistics (regression, PCA, time series, trading) and more...

If you got this far, why not subscribe for updates from the site? Choose your flavor: e-mail, twitter, RSS, or facebook...

Comments are closed.

Search R-bloggers


Never miss an update!
Subscribe to R-bloggers to receive
e-mails with the latest R posts.
(You will not see this message again.)

Click here to close (This popup will not appear again)