R is an open-source programming language and is a free software environment for statistical computing. R was developed in 1993 at the University of Auckland, New Zealand by Robert Gentleman and Ross Ihaka. Show R is the most popular language in the data science world. It is used in analyzing both structured and unstructured types of data. This makes R the standard language for performing statistical operations. R allows various features that differentiate it from other data science languages. In this article, we will explain why you should learn R and how it would benefit you in the field of Data Science. R can be run with a command-line interface and in an integrated development environment. R is available for major operating systems like Windows, Linux, and macOS. R is great for Machine Learning, Statistics, and Data Analysis. Objects, functions, and packages can easily be created by R. R software environment is a GNU package. It is written in C, FORTRAN, and R. Much of its libraries are written in R. But C, C++ codes are preferred for performing some rare tasks. This language is the most popular among data scientists and data miners and can be used in data analysis and data mining. Feature and Advantage
1. RStudioRStudio Initial release: 28 February 2011; 10 years ago. JJ Allaire is a software engineer and entrepreneur who has created a wide variety of products including ColdFusion, Open Live Writer, Lose It!, and RStudio. RStudio is an Integrated Development Environment (IDE) for R, which is a programming language for statistical computing and graphics. It is available in two formats: RStudio Desktop is a regular desktop application while RStudio Server runs on a remote server and allows access to RStudio using a web browser. However, RStudio is more than just a script editor. Your code is entered in the Script Editor (or Source Editor) in the top left pane. As soon as you start your first script in Chapter 2, you’ll see this pane! The code entered is then sent to the main R console in the lower-left pane, which is the analytic engine where the magic happens. The history of the commands you send to the R console is stored in the history pane in the upper right corner, also called the R workspace. This workspace stores any objects that you create in R’s memory. In the lower right pane, RStudio provides a way to navigate and organize files, view and save plots you’ve created, install packages, and get help. RStudio is available in two versions: RStudio Desktop, where programs are run locally as a regular desktop application; and RStudio Server, which allows RStudio to be accessed using a web browser while still running on a remote Linux server. Pre-packaged distributions of RStudio Desktop are available for Windows, macOS, and Linux. Feature and Advantage of using
Best Alternative of RStudi
Free Video Tutorials of2. Sublime TextSublime Text was created by John Skinner – it is Sublime HQ Pty Ltd. is a product of. Sublime Text is a cross-platform text and source code editor with Python Application Programming Interface (API). The graphical user interface design was inspired by Vim. An initial version of Sublime Text was released to the public on January 18, 2008. Sublime Text is a Commercial Source Code Editor. It supports several programming languages and markup languages natively. Users can extend their functionality with plugins, which are usually community-built and maintained under a free-software license. Sublime Text has a Python API for the convenience of plugins. Sublime Text 3 (ST3) is an earlier version of one of the most commonly used plain text editors by web developers, coders, and programmers. It is a source code editor that contains a Python programming surface or API. It is able to support C++ and Python programming languages. Also, tasks can be added by any user with the plugin. We use Sublime Text because it is a colored and highlighted syntax text editor and we can easily recognize the code. Furthermore, Sublime Text is available for OS X, Windows, and Linux. Feature and Advantage
3. Visual Studio CodeVisual Studio Code was first announced by Microsoft at the 2015 Build conference on April 29, 2015. A preview build was released soon after. On November 18, 2015, the source for Visual Studio Code was released under the MIT license and was made available on GitHub. Extension support has also been announced. Visual Studio Code is a source code editor created by Microsoft for Windows, Linux, and macOS. Features include debugging, syntax highlighting, intelligent code completion, support for snippets, code refactoring, and embedded Git. Feature and Advantage
Visual Studio makes use of Microsoft software development platforms such as Windows API, Windows Forms, Windows Presentation Foundation, Windows Store, and Microsoft Silverlight. It can output both native codes and managed code. Free Video Tutorials of—-4. Nodepad++Notepad ++ is a text and source code editor for use with Microsoft Windows. It supports tabbed editing, which allows working with multiple open files in the same window. The name of the product comes from the C increment operator. Notepad ++ is a text and source code editor for use with Microsoft Windows. It supports tabbed editing, which allows working with multiple open files in the same window. The name of the product comes from the C increment operator. Notepad++ is distributed as Free Software. Feature and Advantage
RIDE - R-Brain IDE (RIDE) for R & Python, Other Data Science R IDEs, Other Data Science Python IDEs. Flexible layout. Multiple language support. Jupyter notebook - The Jupyter Notebook App is a server-client application that allows editing and running notebook documents via a web browser. The Jupyter Notebook App can be executed on a local desktop Jupyter lab - An extensible environment for interactive and reproducible computing, based on the Jupyter Notebook and Architecture. Radiant – Open-source platform-independent browser-based interface for business analytics in R, based on the Shiny package and can be run locally or on a server. R Tools for Visual Studio (RTVS) - A free, open-source extension for Visual Studio 2017, RTVS is presently supported only in Visual Studio on Windows and not Visual Studio for Mac. Architect - Architect is an integrated development environment (IDE) that focuses specifically on the needs of the data scientist. All data science tasks from analyzing data to writing reports can be performed in a single environment with a common logic. displayr - Simple and powerful. Automation by menu or code. Elegant visualizations. Instant publishing. Collaboration. Reproducibility. Auto-updating. Secure cloud platform. Rbox - This package is a collection of several packages to run R via Atom editor. Use below for more IDEs: R AnalyticFlow - data analysis software that utilizes the R environment for statistical computing. Nvim-R - Vim plugin for editing R code. How to Turn Vim Into an IDE for R |