Revolution Analytics' Joe Rickert has a new post on inside-R.org, demonstrating how you can use R and the RevoScaleR package to extract time series data from time-stamped logs (in this case, the “US Domestic Flights From 1990 to 2009” dataset on Infochimps):
Analyzing time series data of all sorts is a fundamental business analytics task to which the R language is beautifully suited. In addition to the time series functions built into base stats library there are dozens of R packages devoted to time series…
We have shown how data manipulation functions of the RevoScaleR package to extract time stamped data from a large data file, aggregate it, and form it into monthly time series that can easily be analyzed with standard R functions.
By the way, this post is an excellent example of the type of submission we're looking for for the Applications of R in Business contest. As an employee, Joe's not eligible to win prizes, but if you can create a similar article showing off R's capabilities, there's $20,000 in prizes up for grabs.
inside-R.org: Extracting Time Series from Large Data Sets