R technology has a clever name. An improvised implementation of S technology, not only stands above in alphabetical system but also in nature. It is Free software under GNU’s General Public License project and a language and program for graphing and statistical computing. It is available in source code form. R technology was the baby of Bell technologies, and now Lucent technologies. They took cues from S technology and even took some of the codes are from S tech, however it is majorly known for the differences between them. The R-technology of programming is also called visual programming.
R-technology is not dependent on any operating system or programming language. Following ISO 8631H, this package is applied to computers like mainframes IBM 370, Minis (VAX) or Micros (IBM/PC), and many high-level languages like PASCAL, ASSEMBLER, RTRAN, FORTRAN and more. It is so diverse that it can also be run and compiled on varied platforms like UNIX, and systems including FreeBSD, Linux, Windows and MAC OS. The R advantage is that it provides a great variety of graphical and statistical techniques. Some of the statistical techniques are classical statistical tests, linear and non-linear modelling, clustering, classification, time-series analysis, etcetera. The technology is considered highly extensible and provides full control to the users. The creators of R – Technology, John Chambers and his team deserve a round of applause for the ease of producing well-designed publication-quality plots that R is capable of producing. It also produces formulae and mathematical symbols as needed.
The R-Technology and S- Technology are used in tandem with each other. When S-technology is used for research in statistical methodology, R-Technology compliments by providing an Open-Source route to support the program. The technology has impeccable defaults for the minutest design choices in graphics. The R-Core Team and R Foundation for Statistical Computing support the R-technology. Major users for the programming language are data miners, and statisticians, to be used for data analysis, statistics-based software.
As studied by the TIOBE Index, a measure of the popularity of programming language survey, R stands at 12th position as of July 2021. The polls, data mining surveys etc. tools have shown that R has gained substantial popularity. This easily accessible, powerful language for data science is also a tool extensively used in Stock Analysis Market. R is coded on the software RStudio and a few more platforms.
There are many features of the R environment, which is an integrated suite of software facilities with use in data manipulation, graphical display and calculations. The R-Technology includes
A dependable data handling and facility for storage
graphical facilities for data analysis and on-screen or on hardcopy display
An array of operators for calculations on arrays and matrices.
a robust, intelligible, integrated collection of intermediate tools for data analysis a simple, effective and well-developed, programming language. It includes loops, conditionals, user-defined recursive functions and input and output facilities.
Since the programming language has been developed as a fully planned, and coherent system instead of an upgraded version of S-technology and inheriting its limitations, this is quite an environment. Most of the program is written in the R dialect of S, thus users are well conversant and follow the algorithm quite easily. It also allows the users to define new features and add additional functionality. For intensive computations, the system can work by linking C, C++ and FORTRAN codes at the runtime. If you have enough experience with R and C languages and understand them well, then you can get away with manipulating the R code by writing C Code directly. Due to its heavy use in the statistical system, it is often confused with being a statistics system itself. However, it should be understood as an environment for the implementation of statistical techniques.
R, as we said is highly extensible, comes with about eight packages and is also available through the CRAN family of internet sites (with a wide range of modern statistics). R can be extended with these packages. Its documentation format is comprehensive and is available both online and as hard copy.
The Open-Source tag attached with R is very beneficial for it. Traditionally it has been used for researches and academics. Being open-source helps the institutes or individuals to save costs. The second advantage is that it helps in heavy calculations. It is a common adage in the R circles that ‘R is meant to get the job done, not to ease your computer. The third advantage is that being open-source latest techniques and versions get released quickly. Fourth is the easy availability of documents on the internet and its cost-effectiveness.
Another striking feature is its active communities. The communities are spread worldwide and actively learns, network, and share ideas. They conduct events, like conferences, meetups, etc. to bring the community closer. R-Ladies group is a ladies’ exclusive group that promotes gender diversity and ease of networking and learning together. These communities help the seasoned developers in getting and implementing ideas in a better way, whereas they work as an incubator for the new entrants in the field. The annual function of the R user is called useR! Started in 2004 and going strong.
Since R s going strong through the years, there are a lot of jobs for R developers. Most of the big organizations preferentially work on R, so do the organizations preferring cost efficiency. As per market speculations about the number of jobs, they see an increase in their numbers in coming years. Some credit to this increase also goes to the growing number of startups who manage to keep their budgets in check by using dependable, open-source programs.
Usually, the requirements for R Developers are looking for the following responsibilities. However, the lists here are not exhaustive as they may vary from one organization to another, depending on the projects.