The programming language R was developed specifically for statistical calculations. It is used by most statisticians and data miners who use it for statistical data processing. The programming language R was written mainly in C and also contains Fortran and R at its core. It can be downloaded free of charge under the GNU General Public License.  
It has many similarities with the programming language S, developed by Bell Laboratories. However, R offers a variety of linear and non-linear modelling, analysis of time series, clustering and can be extensively extended. While S is currently the preferred option for exploring statistical analysis, R strongly competes for the title as the programming language of choice. R is fully open-source and is rapidly growing in popularity as it can produce plots ready for publication due to its high quality.  
R can be classified as an interpreted language. Usually accessed through a command line interpreter, it is also available as a precompiled executable and can run on several operating systems including Windows and macOS. R supports numerous arithmetic functions, including matrix arithmetic.   
R has several common data structures such as arrays and lists. Arrays are stored by the system as a column-large order and can be considered as homogeneous components. Lists consist of heterogeneous elements and can be considered as a generic type. While array storage is static, list storage is dynamic and random.  
Many of the functions of the programming language R were derived from Scheme. Data is represented in the same way as in S, and all functions are outstanding. You can treat functions in the same way as data objects. This enables multi-method, which greatly increases speed and efficiency.  
Efficiency is also increased by representing function arguments as a value instead of a reference. These arguments are also represented slowly so that they are only ever implemented when they are used and not when the function is called. R uses procedural programming with functions and can also implement object-oriented programming with generic functions.  
While R is completely open-source and available free of charge, many companies offer commercial support and extensions to the package. Companies like Microsoft have integrated R into their projects. Microsoft has integrated R into its suite of SQL Server applications and Visual Studio. IBM offers a programming model for parallel in-database analysis. R is updated and improved every day. This is likely to continue in the future.