Webinar: 7 Ways to Increase Your R Productivity

REvolution R Enterprise 3 Integrated Development Environment for Windows

 

Presented:	Tuesday, February 23, 2010
Presenter:	David Smith, Vice President of Marketing, REvolution Computing
Downloads:	The webinar slides are packed full of helpful links to resources and references! Download the webinar slides in PDF View the recorded webinar, approximately 50 minutes [Windows Media file .wmv]

 

The R language is quickly evolving from an open-source academic research tool into a commercial application for industrial use. And as R programs become more and more complex, there is an increasing need for developer features that increase productivity and improve performance.

 

Discover how easy it is to increase your productivity with the new R Integrated Development Environment for Windows.

1. Organize, view, add, remove, rearrange, and deploy R scripts with the visual Solution Explorer
   
   • Organize scripts: Use the Solution Explorer to view, add, remove, and rearrange R scripts within one or more Projects contained in the Solution
     
   • Start a new R session: From the File menu, select one of your existing R Solutions to start a new R session with easy access to all of the relevant scripts and data
   • Create Project Templates: Save a Project as a template, and then automatically create a set of customized scripts for a new project. Easily Distribution Solutions to Others: Just zip up your solution directory and give it to colleagues to load and use
     
     
2. Use the enhanced R script editor and get new and occasional R users up and going quickly and greatly improve productivity of experienced users
   
• Hover-over help, word completion, find-across-files capability, automatic syntax checking, bookmarks, and navigation buttons
  
  
3. View all the data and function objects that are available, including those in loaded and installed R packages in the Object Browser
   
   • Browse all available objects
     
   • Get object-specific information
     
   • Plot and edit data
     
     
4. Debug R scripts, with step-in, step-over, and step-out capability, allowing users to inspect and modify R objects as they are debugging
   
   • Debug mode for scripts : step through progress line-by-line
     
   • Set visual breakpoints directly in R source code
     
   • Step into and out of functions while debugging
     
   • Inspect variables while debugging
     
     
5. Automatically generate fill-in-the-blank sections of R code for a variety of analyses
   
• Write your own code snippet and share with others
  
  
6. Search the text of all of installed R package help files or all of the included electronic manuals with enhanced help features
   
   • Hover-over tooltips for functions and data objects
     
     
7. Analyze larger data sets with 64-bit Windows support