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Are you wrapping your head around which is the best IDE for R programming? Do not worry! I have broken down a list of the Best 5 IDEs for R in this blog post.
Going forward we will see which IDE is suitable for you.
Before Going to the list, let’s understand first:
R is nothing but a programming language, a software environment that is meant for statistical computing and data science.
It is supported by the R foundation.
Since this programming language is a statistical software package, it is most loved by the data miners ( who apply R programming in conducting data mining surveys and data analysis).
I don’t know if you are aware or not that its source code was primarily written in C, FORTRAN, and R programming languages.
The best part is, it is available free for the users under the GNU license. Other than that, It has pre-compiled binary versions for most of the operating systems, allowing for customization.
On top of that, you can easily code in the R programming language as it can run on the command line or multiple operating systems such as Windows, Linux, Mac Os, etc.
I think it’s time to move forward towards our list of best R programming IDEs. So, Waiting for what ?. Let’s dive into them
R Studio is the most popular and widely used IDE to take control of R code.
It was founded by JJ Allaire. It is available in open source as well as in commercial editions. R studio can run on any operating system from Windows to Mac, and Linux.
It comes in two formats, the one is Rstudio desktop ( runs locally as a desktop application) whereas R studio server is the second.
Rstudio allows access to RStudio through a web browser while running remotely at the same time on a Linux server.
It comes with a free and open-source GNU AGPL v3 license which offers great liberty for sharing the code.
R studio is very easy to use and most loved by data miners as it is a complete package with proofing, plots, and debugging.
Jupyter lab is yet another web-based interactive and user-friendly Integrated development environment for Jupyter notebook, code, and data.
It is an open-source platform that allows the use of a variety of languages.
Machine learners love this flexible IDE as it allows them to configure and arrange the user interface so that it could support a wide range of workflows including data science, scientific computing, and machine learning.
Also, it is extendible and modular that ensures to write plugins that add new components and integrate with the existing ones
RTVS also named R Tools for visual studio is an amazing plug-in for the Microsoft Visual Studio IDE.
It is widely known as free and open-source software that comes under the Apache License 2.0, developed by Microsoft.
This powerful IDE provides you enhanced support to write lines of codes in the R programming language effortlessly and effectively.
Being a powerful and interactive IDE for coding, Visual Studio has revolutionized the coding experience of R programmers.
Additionally, it supports easy debugging, IntelliSense, remote execution, SQL integration, and many more.
StatET is one of the most popular Eclipse-based IDEs for R programmers.
It is open-source software and the most beautiful thing is, it runs on most operating systems.
Just because StatET is an eclipse-based IDE, that makes this platform integrates a wide range of numerous other tools on the Eclipse platform.
Now no more hassles in writing codes as this IDE has a set of unmatched tools for R code writing and package building.
On top of that, it supports multiple local and remote installations.
RKWard is one of the most popular and widely used IDEs for the development of projects from the R programming language.
It is a highly extensive and easy-to-use integrated development environment for R programming. RKWard was intended to be made for R programmers.
So if you love R writing codes in the R programming language, this IDE must be a great choice for you as it combines the power of the R language along with statistical tools.
R programming is one of the finest and reliable statistical and data mining languages present in the technological market.
The best talking point is that it is open-source therefore it makes sense to you to choose the IDEs that are open source and have interactive Graphical user interface.
There are numerous IDEs available for R. The IDEs that I have discussed above are somewhat purely designed for the R environment whereas there are some other universal editors and gain support for R through plugins.
So, No matter what the case is, you just choose an IDE that suits your requirements well and also with which you are familiar.
Still, if you have questions regarding any IDEs for R. Just let us know in the comment section given below. We always appreciate your valuable feedback and comments.