Behind the NCAA Visualizer: Python, R and JavaScript

April 9, 2013

(This article was first published on Revolutions, and kindly contributed to R-bloggers)

Rodrigo Zamith's NCAA Tournament Visualizer is a great example of an interactive data visualization. If you want to create something similar, Rodrigo has shared detailed behind-the-scenes information on how it was created. He used a mix of tools:

  • Python was used to scrape team statistics fromt the NCAA website
  • R was used to prepare the data for analysis, and to generate the visualizations (using the ggplot2 package)
  • JavaScript and HTML was used to create the interactive interface

Many thanks go to Rodriguo for making all of the code behind the application available on GitHub as open source.

Rodrigo Zamith: Going Under the Hood of the NCAA Tournament Visualization

To leave a comment for the author, please follow the link and comment on their blog: Revolutions. 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.


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)