The Power of the R Programming Language
BartlebyScrivener writes "The New York Times has an article on the R programming language. The Times describes it as: 'a popular programming language used by a growing number of data analysts inside corporations and academia. It is becoming their lingua franca partly because data mining has entered a golden age, whether being used to set ad prices, find new drugs more quickly or fine-tune financial models. Companies as diverse as Google, Pfizer, Merck, Bank of America, the InterContinental Hotels Group and Shell use it.'"
... most others keep thinking that M$ Excel is the silver bullet.
The folks I know who use Excel for analysis use it because it's the package that everyone gets in their organization, there's a shit load of material on the web that uses excel, there's plenty of add-ons for it (no need to reinvent the wheel), and when sharing data and analysis, everyone is familiar with it. An engineer I know who uses excel chose it because it was the fastest way to connect to his testing equipment. R is relatively new and as more folks come into the workforce who know it, we'll see it replace Excel for functions that it is better suited for.
My request is to those that are in the know to show me some example code, that does something useful. Then later, compare that code to code from other languages to accomplish the same task.
Include reasons to support the notion that the R language is [necessarily] better at what it does.
Are you kidding me? Are you really *(*$@#ing, Grade A kidding me?
Python/Perl/Ruby require interpreters. Scheme and Lisp are frequently run within interpreters. "stand-alone executable" require HARDWARE. Any programming system requires *something* underneath it unless you are programming in a purely physical system like an automated abacus with mechanical gears that buzz and whirr.
Programming languages are defined by their Turing completeness: can they do things repeatedly, can they assign values to memory locations and perform some basic set of operations (nand works nicely), can they make decisions. Everything else is fluff.
Perl has "fluff" that handles regular expressions very well.
Python (and others) have "fluff" that make networking and database ops easy.
R has "fluff" that makes it terribly convenient to work with data.
Matlab has "fluff" that makes it very easy to do numerical methods programming.
Mathematica has "fluff" that makes it very easy to do symbolic computation.
Each and every one of these, and most well-known languages, with all their warts and beauty marks are Turing complete and are deserving of the term "programming language".
Regards,
Mark
The flowchart programming of labview is a pain in the butt for many looped programs and programs with complicated timings. Mablab is easier for most things (and more powerful) if you can get your external equipment to work with it without jumping through hoops.