Programming means giving instructions to the computer which are written in a language that the computer can understand.
The instructions can be of various types – subtracting two numbers, identifying a palindrome, etc.
R is one of the programming languages used for statistical analysis, graphics representation, and reporting.
It was created by Ross Ihaka and Robert Gentleman at the University of Auckland, New Zealand.
The core of R is interpreted computer language and it allows branching and looping.
You can also perform modular programming using functions in R. R is mainly written in C, FORTRAN, and some of it is written in R. R is available to everyone free of cost under the GNU General Public Licence. You can find various pre-compiled binary versions for Windows, Linux, and Mac operating systems.
Features of R
- R is a very efficient and well-written language, it includes conditionals, loops, user-defined recursive functions, and I/O facilities.
- The data handling and storage facility in R is excellent.
- Developers have various options of operators for calculations on lists, arrays, vectors, and matrices.
- The availability of different data analysis tools within R is immense and it can be smoothly included in your code.
- The graphical facilities on R are unmatchable.
What is an IDE?
An Integrated Development Environment (IDE) is software that can be used to build applications. IDE comprises common developer tools merged into a single graphical user interface (GUI). An IDE has:
- Source Code Editor: It is a form of text editor in which developers can code. It includes features like – syntax highlights, visual cues, auto-completion functionality, and checking if there are any bugs or not.
- Local Build Automation: Functions like compiling computer source code into binary code, packaging binary code, running automated tests are useful for developers and these simple repeatable tasks are required for creating a local build of the software.
- Debugger: It highlights the place of a bug in the original code graphically.
R can run on the command line interfaces and graphical interfaces in integrated development environments. Below are some of the best R programming IDE and Editors:
RStudio:
R has gained popularity nowadays. Since we are living in the age of data, a language like R which has great statistics and data analysis support is a boon for various stakeholders. RStudio is one of the most popular IDE for R. It is accessible in two formats:
RStudio Desktop which is nothing but a regular desktop application and RStudio Server which runs on a remote server and allows access through a web browser. The primary aim of the RStudio organization is to develop free and open-source software for data science, research, and technical communication. The IDE has various features:
Code Friendly: The platform is extremely code-friendly. This requirement is very necessary because we can see that problems are becoming complex and code communication is becoming a priority.
Modular Platform for impactful data science: Instead of providing a monolithic data science platform that requires great capital investment, RStudio provides modular functionality for open source data science.
Scalable, enterprise-friendly, and production-ready: The software tool is scalable to a large number of users and data, and it can be combined with existing enterprise systems, standards, and processes.
Rattle:
It is a graphical user interface for data mining using R. It can be used to construct supervised and unsupervised machine learning models. One of the key features of Rattle is that all the interactions you (user) have with the graphical user interface are captured in an R Script. This script can be used for executing the written program independently of the Rattle interface. Rattle is free open-source software and you can obtain the source from GitHub easily.
StatET:
It is an eclipse-based IDE for R programming. StatET is offering a good set of tools for R coding and package building. It is a fully functional R console and an integrated R graphics view. The graphics view is like a lifeline of R programming. It contains an object browser which is useful in exploring the objects R has in memory. Finally, it also contains a debugger that helps the developer in correcting mistakes during coding.
ESS:
Emacs is a large household of text editors. GNU Emacs is an extensible, customizable, and free text editor. It is an interpreter for emacs lisp, which is a dialect of Lisp programming language and it supports text editing functionalities. You can experience the feature of coloring according to the syntax and content-aware editing modes.
It has full-scale Unicode support which supports nearly all human scripts. ESS or Emacs Speaks Statistics is an add-on package for GNU Emacs. This package is designed in such a way that it supports various statistical analysis programs like R, S-plus, SAS, Stata, etc. The graphical user interface (GUI) is very sophisticated and elegant.
R AnalyticalFlow:
R AnalyticalFlow uses an R environment for statistical computing. The tagline for R AnalyticalFlow is “Designed for Data Analysis. Great for everyone.” It can be used by the users of Windows, Linux, and Mac operating systems free of charge. One of the interesting features of this software is that it organizes the data analysis processes in a workflow. The user interface is intuitive and the software provides advanced features for R experts.
Radiant:
Radiant is a new browser-based interface for statistical analytics in R, based on the shiny package. Radiant requires an R 4.0 or higher version to execute. A detailed video is available for running and integrating Radiant. It contains an option to run locally or on a server.
Rbox:
Rbox is nothing but an integrated R package for Atom Editor. Atom is one of the most liked editors by the developers for its flexibility and customization. It is developed by Github. The features include the use of hydrogen to execute a line or block at a time, it gives access to various terminals, and it contains useful snippets to run R.
Conclusion:
Data is becoming the next best product nowadays. Businesses left, right, and center are looking for professionals who can collect and understand the data available with them.
R programming is one of the most efficient statistical and data mining languages available in the market. The language is open-source and selecting the best R programming IDE becomes a priority for the users. The article highlights various IDEs available in the market. Select the best according to your requirements and start R programming.