I remember the day that I started to use R programming. I had a basic interface to write and execute the code. After that experience, R Studio emerged as a powerful IDE for R programming for me. It provided a user-friendly interface, integrated tools, and features that enhance productivity and streamline the coding process and was a huge shift for me in my R programming journey.

In July 2022, R Studio was rebranded to Posit. Apparently, a new era was about to start because the world’s needs were evolving, and R had a stronger companion in the Python programming language.

R Studio Interface (Source: biocorecrg.github.io)

To satisfy the needs of both R and Python users, Posit introduced a new product called Positron. It is a data science-oriented IDE that supports both R and Python programming languages, in contrast to R Studio. Of course, this emerging tool has tempted some R Studio users who are also using VSCode since it offers some advantages over R Studio.

Positron Interface (Source: https://positron.posit.co/)

The main difference between Positron and R Studio is their multi-language support. Positron allows users to work with both R and Python in a single environment, making it easier for data scientists who use both languages. Additionally, Positron offers better integration with Jupyter Notebooks, which are widely used in the data science community.

AI-based assistants are also integrated into Positron, providing users with suggestions and code completions based on their coding patterns. This feature can significantly enhance productivity and reduce the learning curve for new users.

If you are playing with the data, it offers more flexibility and versatility compared to R Studio. You can examine not only the data frames on your enviroment, but also .csv and parquet without importing them.

Another advantage of Positron is to offer extensions that make the IDE more customizable and adaptable to different workflows. Users can install extensions to add new features, improve functionality, and tailor the environment to their specific needs.

Package versions and R versions crashes sometimes becomes annoying if you have encounter this during your R Studio experiment. But, with Positron, you can manage different R versions at the same time on the same machine without conflicts. This is particularly useful for users who work on multiple projects with different R version requirements.

Lastly, it is being improved continuously with frequent updates and new features being added regularly. This ensures that users have access to the latest tools and technologies in the data science field.

So the question is: Should we give up on using R Studio?

Actually, no. Because it is not going away, and it still provides some advantages over Positron.

R Studio still has strong properties that tempt users use it. You can use RMarkdown and Quarto to create dynamic documents, reports, and presentations that combine code, text, and visualizations. R Studio also has a robust ecosystem of packages and extensions that enhance its functionality and provide specialized tools for various data analysis tasks.

You can save and reload your workspace. Besides, you have several panels that help you to manage your files, plots, packages, and help documents easily. You can track your codes written in the past and bring them back easily without spending long time. And, you can import your datasets without typing code!

From a developer perspective, R Studio has specific tools that makes developing packages and app easier compared to Positron.

In conclusion, both Positron and R Studio have their own strengths and weaknesses. The choice between the two ultimately depends on the user’s specific needs and preferences. If you require multi-language support, better Jupyter integration, and AI-based assistance, Positron may be the better choice. However, if you prioritize RMarkdown, a robust package ecosystem, and workspace management, R Studio may be more suitable.