How to extract time series from large timestamped logs with R

September 16, 2011
By

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

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

 

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

R-bloggers.com offers daily e-mail updates about R news and tutorials on topics such as: visualization (ggplot2, Boxplots, maps, animation), programming (RStudio, Sweave, LaTeX, SQL, Eclipse, git, hadoop, Web Scraping) statistics (regression, PCA, time series, trading) and more...



If you got this far, why not subscribe for updates from the site? Choose your flavor: e-mail, twitter, RSS, or facebook...

Tags: , ,

Comments are closed.