.R File Extension

R Script File

Developer	The R Project for Statistical Computing
Popularity	Average rating 3.9 / 5. Vote count: 61
Category	Developer Files
Format	.R
Cross Platform	Update Soon

What is an R file?

The .R file extension is associated with R script files, which are used primarily for statistical computing and graphics. These files contain code written in the R programming language, a language and environment that is highly regarded for its capabilities in data analysis, statistical modeling, and data visualization.

.R script files are plain text files that can be created and edited with any text editor, but they are typically managed within specialized software environments like RStudio.

More Information.

R was inspired by the S programming language, which was developed at Bell Laboratories by John Chambers and colleagues. The primary motivation behind the creation of R was to provide a statistical programming environment that was both open source and highly extensible.

The initial purpose of R script files was to enable users to write and execute sequences of commands for data manipulation, statistical analysis, and graphical representation.

Over the years, R has evolved into a comprehensive tool for data science, and R script files have become a staple for researchers, statisticians, and data analysts worldwide.

The R community has contributed thousands of packages to extend the functionality of the base system, making R a versatile tool for a wide range of applications.

Origin Of This File.

The .R file extension originates in the development of the R programming language, which was created by Ross Ihaka and Robert Gentleman at the University of Auckland, New Zealand, in the early 1990s.

The language was designed to be a free software environment for statistical computing and graphics, providing a more flexible and powerful alternative to existing statistical software.

File Structure Technical Specification.

.R files are plain text files that contain sequences of R commands. The structure of an R script typically includes the following elements:

Comments: Lines beginning with a # are comments and are ignored by the R interpreter. Comments are used to annotate code, making it easier to understand and maintain.
Assignments: Variables are created and assigned values using the <- operator.
Functions: R scripts often include user-defined functions to encapsulate reusable blocks of code.
Control Structures: R supports standard control structures like loops (for, while) and conditional statements (if, else).
Packages: Scripts can load external libraries or packages using the library() function to extend functionality.

How to Convert the File?

.R files are plain text files, so converting them typically involves changing the file extension or formatting them for compatibility with other languages or tools. Here are a few common conversions:

To .txt: Simply change the file extension from .R to .txt. This does not change the content but makes it clear that the file is plain text.
To .py (Python): Manually translate the R code to Python syntax.
To .ipynb (Jupyter Notebook): Use tools like rpy2 to integrate R code within a Jupyter Notebook, which supports both Python and R.

Advantages And Disadvantages.

Advantage:

Open Source: R is open-source software, meaning it is freely available and can be modified and distributed by anyone.
Comprehensive Statistical Analysis: R provides various statistical techniques and models.
Extensibility: Thousands of packages are available to extend the base functionality.
Graphics: R excels in creating high-quality graphics and visualizations.
Community Support: A large and active community offers extensive support and resources.

Disadvantage:

Learning Curve: R has a steep learning curve for beginners, especially those without a programming background.
Performance: R can be slower than other languages like Python for certain tasks, particularly those involving large datasets.
Memory Management: R requires significant memory, which can be a limitation for very large datasets.

How to Open R?

Open In Windows

RStudio: The most popular integrated development environment (IDE) for R. Download and install from RStudio’s website.
R GUI: The basic graphical user interface that comes with the R installation. Download R from CRAN.
Text Editors: Notepad++, Sublime Text, Visual Studio Code (with R extensions) can be used to open and edit .R files.

Open In Linux

RStudio: Available for Linux; install via the package manager or download from RStudio’s website.
Command Line: Use the terminal to run R scripts directly by invoking the Rscript command.
Text Editors: gedit, Vim, Emacs (with ESS – Emacs Speaks Statistics).

Open In MAC

RStudio: Available for macOS; download from RStudio’s website.
R GUI: Comes with the R installation on macOS. Download from CRAN.
Text Editors: TextEdit, Sublime Text, Visual Studio Code (with R extensions).

Open In Android

Termux: An Android terminal emulator and Linux environment app. Install R via Termux using the package manager.
Online IDEs: Use online R IDEs such as RStudio Cloud through a web browser.

Open In IOS

Online IDEs: Access RStudio Cloud or other online R IDEs through the Safari browser.
Juno: An iOS app that provides an environment for running Jupyter Notebooks, which can include R kernels.

Open in Others

Jupyter Notebooks: R can be integrated into Jupyter Notebooks using the IRkernel.
VS Code: Visual Studio Code with the R extension provides a versatile environment for R scripting across various operating systems.