What is RStudio?
An integrated development environment for R, with a console, syntax-highlighting editor that supports direct code execution. Publish and distribute data products across your organization. One button deployment of Shiny applications, R Markdown reports, Jupyter Notebooks, and more. Collections of R functions, data, and compiled code in a well-defined format. You can expand the types of analyses you do by adding packages.
RStudio is a tool in the Languages category of a tech stack.
RStudio is an open source tool with 2.9K GitHub stars and 708 GitHub forks. Here’s a link to RStudio's open source repository on GitHub
Who uses RStudio?
12 companies reportedly use RStudio in their tech stacks, including Apptopia, DataGlen, and iCook.
27 developers on StackShare have stated that they use RStudio.
Why developers like RStudio?
Here’s a list of reasons why companies and developers use RStudio
Be the first to leave a pro
- Enhanced Security and Authentication
- Administrative Tools
- Metrics and Monitoring
- Advanced Resource Management
- Session Load Balancing
- Team Productivity Enhancements
- Priority Email Support.
RStudio Alternatives & Comparisons
What are some alternatives to RStudio?
See all alternatives
Python is a general purpose programming language created by Guido Van Rossum. Python is most praised for its elegant syntax and readable code, if you are just beginning your programming career python suits you best.
The Jupyter Notebook is a web-based interactive computing platform. The notebook combines live code, equations, narrative text, visualizations, interactive dashboards and other media.
At GitHub, we're building the text editor we've always wanted. A tool you can customize to do anything, but also use productively on the first day without ever touching a config file. Atom is modern, approachable, and hackable to the core. We can't wait to see what you build with it.
A free and open-source distribution of the Python and R programming languages for scientific computing, that aims to simplify package management and deployment. Package versions are managed by the package management system conda.
Using MATLAB, you can analyze data, develop algorithms, and create models and applications. The language, tools, and built-in math functions enable you to explore multiple approaches and reach a solution faster than with spreadsheets or traditional programming languages, such as C/C++ or Java.