Introduction To R Programming Language
R programming, primarily arriving in the early 1990s amidst the beginning of the digitization of the computer age, it is a programming language for introduction sake. It is generally a software base for statistical computing and data mining. It is run by the R Foundation for Statistical Computing. It was developed by Ross Ihaka and Robert Gentleman. R programming language is a platform used commonly by statistician and data miner; it is used as a base to develop advanced and sophisticated statistical and data mining & analysis software for various purposes like in surveys, research-based software, polls and etc. R programming is mostly used to develop software’s to handle large & huge quantity of data and organize them into a more presentable & user-friendly manner.
Table of contents
Definition of R Programming Language
As previously mentioned in the introduction, R is a programming language for statistical computing, data mining and data analysis. It is a GNU project which was developed at Bell Laboratories. Furthermore, R has a wide variety of advanced techniques such as machine learning algorithms, time-series analysis, linear regression, time series, linear and nonlinear modeling, classical statistical tests and clustering.
R uses these advanced and sophisticated techniques to analyze, investigate, inspect and survey data to produce more refined, well-designed and best quality products and results for data sciences. The approach of R is through a series of steps like programming, discovering, transforming, modeling and communicating using the advanced techniques mentioned previously. R follows these specific rules and regulations to produce itself as a fully planned and coherent and methodical system to produce the state-of-the-art data manipulation, mining, analysis and graphical display software for various requirements.
Steps to Install R Programming Language
R Programming Language can be installed in any platforms like Windows 10 or Mac OS. Now installing R is not the only step to use R programming language, we also need to learn the installation process for RStudio, which is an IDE or Integrated Development Environment to use R fluently and also installing of R packages is needed to experience the overall and complete performance of R Programming Language.
Steps of Installing R in Windows 10 and Mac OS is similar, so explaining one installation step will automatically explain the other one’s rules of installation also which are as follows:
- Steps 1: Firstly, the easiest ways to install R is through CRAN (Comprehensive R Archive Network) and then we have to visit the CRAN download page and find the download link in the page and click download, after download finishes, an executable file namely “.exe” depending on the version type is obtained and then runt this ‘.exe’ file to complete the process. Then you can find desktop shortcuts also during the installation process only.
- Steps 2: Now after the installation of R, we need to install RStudio. RStudio IDE is installed mainly to have upgraded and refined conditions to work on the R scripts. The process for installation is quite easy and straightforward, we can simply go RStudio download page and similarly find the download link and click download, after downloading completes we will find another ‘.exe’ file which we need to run for the installation process to be completed just like before but we need to keep in mind that R must be installed beforehand mandatorily to have a successful installation.
- Steps 3: Finally, we need to install the R packages like dplyr or ggplot2 to run R smoothly and efficiently as without R packages R programming is only limited to a certain number of works. This is why the R packages like ‘dplyr’ is used for data-wrangling capabilities and ‘ggplot2’ is used for data visualizations are used to improve R’s capabilities. There are mainly two ways to install R Packages generally.
Features of R Programming
Few features of R programming are as follows:
- It is an open-sourced software-based platform and comprehensive programming language.
- Provides a wide array of packages.
- In possession of a number of graphical libraries.
- Having an IDE platform can run code without a compiler.
- Being an open-source it is free of cost and requires no license.
- It can run on any OS in any software background or hardware configuration.
- Performs fast calculations on a variety of complex operations using various advanced techniques.
- Being flexible in nature it can be integrated with other programming languages like C, C , Java, FORTRAN.
- It is now being used in various types of industries besides the normal academic arenas, which requires data mining and analysis of huge data.
Advantages of R Programming
Given below are the advantages of R programming:
- It is an open-source language so we do not require any purchase of a license to use it as it is completely free.
- It can run on all platforms being platform-independent in nature.
- It performs a wide variety of operations like data manipulation, graphical surveys and statistical modeling.
- The most important usage of R is for statistics and various statistical methods and data sciences.
- It has a huge, vast, vigorous community and resource bank consisting of various works, projects and ideas.
- It uses very sophisticated and advanced techniques following certain specific steps to obtain high-quality results for data sciences and statistics.
Conclusion
In a nutshell, we can say that R programming is an open-sourced and free platform that can be integrated with any other programming languages to perform high velocity and high performing tasks using complicated techniques but producing easily understandable and best outcomes to ease, better and enhance performance capabilities of a number of industries by helping them increase their outputs profit ratio. Thus, we can say that the R Programming Language is a far advanced yet user-friendly and adaptable language for the future and upcoming generations of various digital platforms.
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