R is definitely an excellent environment for data analysis and display. It has quickly become the tool that I use to bind together different models and process the resulting data into reports and graphics. The Sweave package can be especially useful for accomplishing this.
R has also been integrated into some GIS environments, the GRASS system is a good example of this. The book "Open Source GIS: A GRASS GIS Approach" by M.Netler and H. Mitasova. provides an overview of this capability. The following post in the QGIS blog also shows how R can be used to output data as shapefiles which can then be loaded into a GIS application: http://blog.qgis.org/node/112 Monica Pisica wrote: > > > Cons: > > - R has a very steep learning curve. > > Based on my my experience conducting data analysis and visualization using Fortran and MATLAB, R was refreshingly easy to learn. The demo() and example() functions provide tremendous insight into the use of different tools in R by executing code and showing the results. I also found it extremely easy to obtain consistent graphical output from R. Producing standardized views of different datasets in MATLAB can be an exercise in frustration compared to what I am able to achieve using R. -- View this message in context: http://www.nabble.com/Pros-and-Cons-of-R-tp17407521p17451695.html Sent from the R help mailing list archive at Nabble.com. ______________________________________________ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.