R has emerged as the prominent language for statistical computing and data visualization, owing to its comprehensive collection of packages and tests. An Integrated Development Environment, or “IDE” for short, plays a crucial role in facilitating the usage of such a powerful language. 

If you’re a beginner, it might be a little confusing to settle on which IDE to use. Especially if you’re just getting started with the language, and don’t know how to use R or get the most out of an IDE. Given the complexity of some IDEs, even experts can have a hard time understanding all of the nuances between different features and tools.

Our guide compares the five best IDEs for R programming, assessing their features, pricing, and usability, to help you identify the IDE that best fits your unique programming needs. Whether you’re a complete novice or an experienced developer, we’ll help you decide on the best R IDE for your needs.

Key Takeaways

1. R Studio: Best for Comprehensive R Programming Support
2. RKWard: Best for Non-Programmers and Advanced Programmers Alike
3. PyCharm: Best for Integration with Python
4. Visual Studio Code: Best for Versatility and Extensibility
5. DataSpell: Best for Interactive Data Science and Scientific Computing

Best IDEs for R Programming of 2023

Side-by-side comparison

Pick #1 – R Studio: Best for Comprehensive R Programming Support

• Integrated R help and documentation
• Code completion
• Source editor and data viewer
• Package development tools
• Git integration

RStudio is probably the most popular IDE among programmers for R development. It provides a classic and conventional interface, that is equally user-friendly, making it easier to write and debug code. 

RStudio is widely used by data scientists and statisticians for data analysis and statistical computing. Its standout features include automatic code completion, a built-in data viewer for visualization and plotting, and a plethora of debugging tools.

RStudio also includes various tools for developing R packages, including a build pane to document, test, and build packages, and integrated Roxygen support for documentation.

Perhaps the most helpful feature is the extensive built-in help and documentation. Rstudio integrates directly with the official docs, making it easier for developers to find the information they need and focus more on getting things done.

When you first open R Studio, you’re ready to dive into typing R commands with the console at the left. If you need help or want to read the documentation, you can navigate to the built-in docs located at the right.

You can easily start a new project by selecting the Project dropdown menu in the upper right and loading your repository locally or from GitHub.

Once your project is open, you can load your data sets and begin tinkering with your R code. Your environment will load in the upper left, and the console will shift to the bottom. Of course, you can change all of this to your preferences. But, the simple, classic interface makes it extremely intuitive.

Pricing

RStudio is available in both free and commercial editions. The free version, RStudio Desktop Open Source License, is free to use and includes all the features necessary for an individual or a team to use R for data analysis. 

For commercial users, the price jumps significantly. RStudio offers RStudio Desktop Commercial License for $1045 per year. But with this increase, you get access to priority support and drivers, and the license to use the software commercially, of course.

Pros and cons of R Studio

Pros

• Comprehensive support for R programming.
• User-friendly interface that is easy to navigate.
• Powerful coding and debugging tools.
• Excellent integration with R help and documentation.

Cons

• Some users may find the interface a bit cluttered.
• It can be resource-intensive, especially on large datasets.

Pick #2 – RKWard: Best for Non-Programmers and Advanced Programmers Alike

• Import from SPSS, Stata, CSV
• Manage R packages
• GUI dialogs for stats and plots.
• Plot preview and history.
• Spreadsheet-style data editor.
• Syntax highlighting, code folding, and completion.

RKWard is a free and open-source IDE designed specifically for R, aimed at supporting both beginners and advanced programmers. RKWard is available on Windows, Mac, and Linux and is relatively easy to install and use.

When you’re new to the platform, RKWard sets you off on the right foot with a friendly setup assistant. This guide pops up when you first launch the program, walking you through the process of downloading and installing the necessary components and R packages.

The graphical user interface is conventional-looking yet with easy access to all of your most critical features. Some of the design choices make it appear less cluttered compared to R Studio, but this will also depend on how you configure your environment.

RKWard comes packed with a plethora of analysis tools, ranging from decision trees and clustering to regression analysis. If you’re a student, you’ll love the easy access to Documentation, which provides much-needed direction for new users.

Once you have a project started, you can quickly access tools like the R Console, which pops up on the bottom of your screen. Your workspaces and directories will show up on the left, and you’ll be able to look at your data in the main window.

Pricing

RKWard is completely free to use, making it an excellent choice for individual users, students, and organizations on a budget.

Pros and cons of RKWard

Pros

• Free and open-source.
• User-friendly spreadsheet-style data editor.
• Wide range of analysis tools.
• Active community support.

Cons

• The interface may seem less modern compared to other IDEs.

Pick #3 – PyCharm: Best for Integration with Python

• Easy Python integration
• Code editing and refactoring
• Built-in debugger
• Version control tools
• Code collaboration and review
• Plugins and integrations

PyCharm is an IDE created by JetBrains, specifically designed with Python software developers in mind. If you don’t use R all the time, and find yourself using Python as your language of choice, PyCharm lets you enjoy the best of both worlds. 

While many developers tout R Studio as having a superior interface and smoother R workflow, PyCharm is great at performing simple tasks in R. 

However, you can’t use PyCharm for R programming without installing the appropriate plugin first. Find this in the Plugins menu on the left when you first launch the app.

Once you have the plugin, you can get to work on your project. Thanks to the Git integration, you can use a local directory or open an existing repository. Just hit Get from VCS on the project selection screen.

PyCharm is known for its user-friendly interface and low learning curve, making it accessible for beginners and seasoned developers alike. You’ll see a helpful “Tip of the Day” whenever you launch PyCharm. 

All of the tools and functionality are right within reach and conveniently placed by default. You’ll notice a much more modern take on the design elements compared to more cluttered interfaces like R Studio and RKWard.

Pricing

JetBrains offers a free version of PyCharm, referred to as the Community Edition. While it does not have the full suite of features, it is still a highly potent IDE for students and casual users. 

The Professional version is available for $249 per year, significantly cheaper than commercial versions of competitors like R Studio.

Pros and Cons of PyCharm

Pros

• Extensive language support, including Python and R with the R extension.
• Built-in Git commands.
• Powerful debugging tools.
• Highly customizable and extensible with a wide range of extensions available.
• Project management support.

Cons

• Some users find the number of configuration options and extensions overwhelming.
• As a Python-focused IDE, it might not offer some of the R-specific features that specialized IDEs do.

Pick #4 – Visual Studio Code: Best for Versatility and Extensibility

• Extensive language support
• Git integration
• Debugging tools
• Customizable and extensible
• Live Share feature

Visual Studio Code, also known as “VS Code,” is a free, open-source code editor developed by Microsoft. It’s known for its versatility and extensibility, supporting a wide range of programming languages out of the box. 

VS Code is lightweight and fast, making it a favorite among developers. It offers features like IntelliSense for smart completions based on function definitions, variable types, and imported modules. The built-in Git commands make it easy to pull from or push to your repositories.

One of the standout features of VS Code is its debugging support. You can debug code directly in the editor with breakpoints, call stacks, and an interactive console.

VS Code also offers a Live Share feature, which allows developers to share their workspace with others, making real-time collaborative coding possible. This is a valuable feature if you are a student since you can collaborate with your professors in real time if you have any questions about your R code.

Before you get started with R programming in VS Code, you’ll need to install the R extension. Fortunately, this is a super easy task. After you download and install the IDE, search R in the extension marketplace. Then, click to install it.

Once installed, you can start on your first R project. Like R Studio, VS Code integrates with Git, so you can open a local or remote repository. The interface is clean and customizable. You can change the theme, keyboard shortcuts, preferences, and install extensions to make the editor your own.

You’ll find the most essential navigation links on the left, such as the file explorer, search bar, extensions, debugging, and preferences.

Pricing

When it comes to price, you can’t beat Visual Studio Code. It is completely free for private and commercial use. The downside is that you should not expect as much technical support as you get with some of the more expensive options.

Pros and Cons of Visual Studio Code

Pros

• Extensive language support, including R with the R extension.
• Built-in Git commands.
• Powerful debugging tools.
• Highly customizable and extensible with a wide range of extensions available.
• Live Share feature for collaborative coding.

Cons

• Some users find the number of configuration options and extensions overwhelming.
• As a general-purpose editor, it doesn’t offer some of the R-specific features that specialized IDEs like RStudio do.

Pick #5 – DataSpell: Best for Interactive Data Science and Scientific Computing

• Highly interactive environment
• Intelligent coding assistance
• Support for local and remote Jupyter notebooks
• Interactive Python and R scripts
• Built-in tools and integrations

DataSpell is another product by JetBrains, specially tuned for high interactivity during data analysis and scientific computing. It allows seamless switching between command and editor modes with a single keystroke, and easy navigation over cells using arrow keys. It also offers standard Jupyter shortcuts and fully interactive outputs right under each cell.

While not aimed specifically at beginners, it is incredibly easy to use and get started with the help of the onboarding tour. You can start the tour when you launch the app, and get a piece-by-piece introduction to each component.

DataSpell supports viewing data and visualizations in place via interactive controls. Popular Python scientific libraries, such as Plotly, Bokeh, Altair, ipywidgets, are all supported. Moreover, interactive Python scripts can be executed within DataSpell.

By now, integration with version control is a necessity for most developers. You can clone Git projects, commit and push changes, work with several branches, manage changelists, and stage updates before committing them, using the built-in tools (accessed via the left sidebar of your environment).

DataSpell also includes database tools, which enable users to access, query, and alter databases right from the IDE, with smart coding assistance for SQL code. Additional features such as an RMarkdown editor, Conda support, a Debugger, and basic support for R make DataSpell an encompassing environment for data science and scientific computing.

Pricing

While it’s not completely free, it’s worth the investment for data science professionals and researchers, given its rich feature set. You’ll pay $10 per month for personal use, or $100 per year if you pay annually. The commercial use license runs double the price, at around $229 per year.

Pros and Cons of DataSpell

Pros

• Designed specifically for data science projects
• Smart coding assistance for error-free and efficient coding.
• Support for both local and remote Jupyter notebooks.
• Integrated tools for version control, terminal operations, and database handling.

Cons

• Currently, only Python and R are supported. Support for other languages like Julia may be provided in the future.
• Features are limited if you need an IDE for something other than data science.
• No free version is available.

FAQs

Tyler Harz

Tyler Von Harz is a developer and prolific writer with a passion for technology. He has a knack for simplifying complex coding topics, and as an author, he contributes to various tech platforms, combining his technical expertise and writing skills to produce impactful content. His work is driven by an insatiable curiosity and a commitment to a deeper understanding of technology.

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