« Because it's Friday: Surprise Russian meteor | Main | Visualize major league pitching data with PitchRx »

February 18, 2013

TrackBack

TrackBack URL for this entry:
http://www.typepad.com/services/trackback/6a010534b1db25970b017ee897dae5970d

Listed below are links to weblogs that reference 10 R packages every data scientist should know about:

Comments

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

I would add data.table to that list, perhaps in place of plyr if it has to be one or the other. data.table is very fast.

Very informative blog. I just used RODBC and SQLDF for the first time. Are there any R packages to handle big data?

I would add package ff to that list, perhaps in place of sqldf. sqldf allows to write a subset of native R queries in yet another language at a huge cost in terms of RAM (twice) and CPU (e.g. factor 40 slower). ff enhances R for big datasets and operations that are not possible in pure R given its RAM needs. For Revolution R Enterprise users, ff is less attractive on that list, because it has its own methods for big datasets on disk.

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