R is a programming language, mainly dealing with the statistical computation of data and graphical representations. Many data science experts claim that R can be considered as a very different application, of its licensed contemporary tool, SAS. This data analytics tool was developed at Bell Laboratories, by John Chambers and his colleagues.
The various offerings of this tool include linear and non-linear modeling, classical statistical tests, time-series analysis, clustering, and graphical representation. It can be referred to as a more integrated suite of software facilities, for the purpose of data manipulation, calculation and data visualization. The R environment is more of a well-developed space for an R programming language, inclusive of user-defined recursive functions as well as input and output facilities. Since it is a relatively new data analytics tool in the IT-sphere, it is still considered to be very popular amongst a lot of data enthusiasts.
There are a number of advantages of this data analytics tool, which make it so very popular amongst Data Scientists. Firstly, the fact that it is by far the most comprehensive statistical analysis package available totally works in its favor. This tool strives to incorporate all of the standard statistical tests, models, and analyses as well as provides for an effective language so as to manage and manipulate data.
One of the biggest advantages of this tool is the fact that it is entirely open sourced. This means that it can be downloaded very easily and is free of cost. This is mainly the reason why there are also communities, which strive to develop the various aspects of this tool. Currently, there are about some 19 developers, including practicing professionals from the IT industry, who help in tweaking out this software. This is also the reason why most of the latest technological developments, are first to arrive on this software before they are seen anywhere else.
Why Learn R Programming
When it comes to a graphical representation, the related attributed to R are extremely exemplary. This is the reason why it is able to surpass most of the other statistical and graphical packages with great ease. The fact that it has no license restrictions, makes it literally the go-to software, for all of those who want to practice this in the earlier stages. It has over 4800 packages available, in its environment which belong to various repositories with specialization in various topics like econometrics, data mining, spatial analysis, and bioinformatics.
The best part about R programming is that it is more of a user-run software, which means that anyone is allowed to provide code enhancements and new packages. The quality of great packages on the R community environment is a testament to this very approach to developing certain software by sharing and encouraging inputs. This tool is also compatible across platforms and thereby it runs on many operating systems as well as hardware.
It can function with similar clarity for both the Linux as well as Microsoft Windows Operating Systems. In addition to this, the fact that R can also work well with other data analytics tools like SAS, SPSS and MySQL, have resulted in a number of takers for this data analytics tool. Imarticus Learning The Data Science Prodegree powered by KPMG is one such course which offers both SAS and R along with the opportunity to be a Data Scientist at KPMG.