hwajar.blogg.se - R programming software for mac

Versatility - Hundreds of packages for specific purposes being developed and improved on a daily basis by the developer community.

Superior Graphics - Compatibility with aesthetic graphical libraries like ggplot2 and plotly ensures publication-quality graphics visualizations.

Frequent releases - Resulting in timely bug fixes and less frustration.

Portable - Easy to run on mobiles, tablets and gaming consoles.

Platform independent - Runs on several computing platforms such as Windows, Linux, and Mac OS.

S programming language was later developed into S-plus by TIBCO corporation that bought it from AT&T, by adding some advanced analytical abilities and OOP capabilities.

R was developed under GNU public license and openly distributable. The mono-letter name R was inspired by S again, taking the first letter of both the authors’ first names. R initially differed from S as it added lexical scoping semantics on top of the existing S functionalities. The first version was released in 1995 and the first stable beta version came up in the year 2000. R was developed by Ross Ihaka and Ross Gentleman in a project that was conceived in 1992 at the University of Auckland, New Zealand.

The single-letter name S was inspired by the ubiquitous C language for programming at the time. AT&T began its work on S in 1976, as a part of its internal statistical analysis environment, which was earlier implemented as FORTRAN libraries. R has a precursor named S (S stands for statistics) language, developed by AT&T for statistical computation. Recommended Read: Python Data Science Libraries History of R Programming Language R has also been adapted to deep learning these days and this helped several statisticians take on to deep learning in their respective fields easily, making R an indispensable part of the current burgeoning AI scenario.

The demand of R programmers has been constantly on the rise since the early 2010s and R still enjoys the status as a go-to programming language among data scientists. R is one of the most popular scripting languages for statistical programming today.