Quandl has now a feature that lets users export data as an R matrix, this way the data can be easily loaded into R. Damn awesome righto? Kudos to the guys from Quandl!

read.csv('http://www.quandl.com/api/v1/datasets/OFDP/ALUMINIUM_21.csv?&utf8=✓&trim_start=2012-01-03&trim_end=2013-02-07&sort_order=desc', colClasses=c('Date'='Date'))

Today’s idea is use Quandl approach in other applications. Jenkins exports some of its objects to its external JSON API. And there are stats being collected from plug-ins (like the download statistics). I am curious to know if there would have any gain in exporting parts of this data as R matrices and processing it directly with R.

This could be used in a lot of different applications, perhaps even using Hadoop and R. Instead of writing collectors to consume an RESTful service, you would simply write one R line to get the job done.

R does very fine in plotting too, so I wouldn’t be surprised to at least see some prettier charts :o)