Why R? It's free, open source, powerful and highly extensible. "You have a lot of prepackaged stuff that's already available, so you're standing on the shoulders of giants," Google's chief economist told The New York Times back in 2009.
Free Resources on R Language
- Part 1: Introduction
- Part 2: Getting your data into R
- Part 3: Easy ways to do basic data analysis
- Part 4: Painless data visualization
- Part 5: Syntax quirks you'll want to know
- Part 6: Useful resources
Details of R LanguageBecause it's a programmable environment that uses command-line scripting, you can store a series of complex data-analysis steps in R. That lets you re-use your analysis work on similar data more easily than if you were using a point-and-click interface, notes Hadley Wickham, author of several popular R packages and chief scientist with RStudio.
That also makes it easier for others to validate research results and check your work for errors -- an issue that cropped up in the news recently after an Excel coding error was among several flaws found in an influential economics analysis report known as Reinhart/Rogoff.
Why not R
Well, R can appear daunting at first. That's often because R syntax is different from that of many other languages, not necessarily because it's any more difficult than others.
How R is different from Excel
- The R Language is different from Excel. In R you can use complex problems. Multiple sources of data you can do analyze in R Language.
- In Excel, the capability of handling data sources is limited.
- Connectivity to modern visualization tools like Tableau is cumbersome in Excel.