« NYT uses R to investigate NFL draft picks | Main | Extending RevoScaleR for Mining Big Data - Naive Bayes »

May 02, 2013

TrackBack

TrackBack URL for this entry:
http://www.typepad.com/services/trackback/6a010534b1db25970b017eeabb6576970d

Listed below are links to weblogs that reference How R Grows:

Comments

Feed You can follow this conversation by subscribing to the comment feed for this post.

It grew up so fast :)

Interesting, I'd be interested to see how r-forge and github have grown as unstable development repos.

The large number of package let me think that we need to develop a collaborative comprehensive handbook such as the R Programming wikibook (http://en.wikibooks.org/wiki/R_Programming) to find the best way to deal with each task.

I guess the CRAN packages by date page only shows when the packages were last updated, right? It would be interesting to know how many new packages were added each year. Another chart to show which packages get updated most frequently would be good too.

A fascinating study. Thank you for doing the work and posting it.

Anyone who uses R enough will encounter some of the frustrating features of the language. But the strength of R is not the language but the packages. This post shows why R is so popular and continues to be popular.

That's a very different perspective from my similar growth curve here:

http://r4stats.com/2013/03/19/r-2012-growth-exceeds-sas-all-time-total/

The first version I plot is 1.3, which was released in 2001, and I stopped at 2012. I'll email you so we can figure out why there's such a big difference.

Cheers,
Bob

The comments to this entry are closed.


R for the Enterprise

Got comments or suggestions for the blog editor?
Email David Smith.
Follow revodavid on Twitter Follow David on Twitter: @revodavid

Search Revolutions Blog