Happy New Year!

January 1, 2014
By

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

It's a brand new year, and the Revolutions blog is now three weeks into its sixth year. Hard to believe that a little over five years ago this was the only R-related blog; now there are more than 450 and the R project and the R community continue to thrive and grow. 

To bring in the new year, I thought I'd take a look back at the 10 most popular R-related posts of 2013. In descending order starting with the post with the most pageviews in 2013, they are:

  1. Free e-book on Data Science with R
  2. Learn how to analyze data with R with Coursera's "Data Analysis" videos
  3. Statistics vs Data Science vs BI
  4. Visualize large data sets with the bigvis package
  5. Elements of Statistical Learning: free book download
  6. Trevor Hastie presents glmnet: lasso and elastic-net regularization in R
  7. Did an Excel error bring down the London Whale?
  8. Big Data Sets you can use with R
  9. Draw nicer Classification and Regression Trees with the rpart.plot package
  10. 10 R packages every data scientist should know about

Some popular posts not directly related to R were Nate Silver addresses assembled statisticians at this year's JSM and A great example of Simpson's Paradox: US median wage decline. The most popular "Because its Friday" posts were Game of Thrones Family Trees and Ten Tech Tips from David Pogue.

We've got plenty more to come in 2014: more guest bloggers, more data science and big data discussions, and of course much more R. I'd like to thank our many guest bloggers in 2013, especially Joe Rickert who featured several times in the top 10. I'd also like to thank my colleagues at Revolution Analytics for supporting this blog. And I'd especially like to thank the readers of this blog for insightful comments and great suggestions. Let us know what you'd like to see in the coming year the comments.

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

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