Learning R

R is a fascinating programming language. The language has grown significantly in popularity and is now used in a range of professions including software development, business analysis, statistical reporting and scientific research. R is especially suited for data-intensive work as the demand for tools like R for processing, data-mining and visualization is increasing.

R originated as an open-source version of the S programming language in the 90s. Since then, it has gained the support of a number of companies, most notably RStudio and Revolution Analytics which created tools, packages, and services related to the language. R now also has support from large companies that power some of the largest relational databases in the world. Oracle has incorporated R into its offerings and Microsoft is including the language in SQLServer 2016.

R was created by Ross Ihaka and Robert Gentleman at the University of Auckland in New Zealand and it’s been widely adopted in graduate programs that include intensive statistical study. Graduate programs that involve data crunching are bound to encounter R and its introduction in education programs naturally leads to its wider adoption in industry. Many packages exist to perform e.g. stock market analysis, create maps, engage in high-throughput genomic analysis and do natural language processing.

And R is also fun. R is able to generate charts and plots in very few lines of code. Tasks that would require several hundred lines of code in another language could be accomplished in only a few lines. The plot() function in R is highly adaptable. It takes in data in a variety forms and responds with a reasonable graphical plot of the data provided. It can take many options to influence its behavior.

R is worth learning for these reasons and more. Its growth and maturity have led to widespread adoption. You can expect to hear more about R in the years to come. SpiralTrain is developing a course to learn R.