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Mastering R in Deepnote: A comprehensive guide to collaborative data science

By Filip Žitný

Updated on March 6, 2024

Our collaborative data science notebook is designed to improve the workflow of data scientists and analysts. It supports various programming languages, including Python, SQL, and notably, R.

My guide will walk you through the basics of integrating R into your Deepnote projects, ensuring you have the necessary tools and knowledge to get started.

Choose your environment

Once you've created your Deepnote account, select 'Create a new project'. In the 'Create Project' interface, pick R as your environment.

Start coding

Deepnote's Interface brings you a blank notebook where you can start writing your R scripts right away.

Harness the power of Deepnote

Deepnote offers powerful features for R programming, including live multi-user collaboration, inline explanatory comments, and version control.

Execute your scripts

Just press Cmd/Ctrl + Enter to run your scripts and gander at the results in real time.

Collaborate and share

Share your notebooks with your team and collaborate in real-time, or publish them publicly to contribute to the larger R community.

Remember, Deepnote also supports importing existing Jupyter notebooks, so you can easily bring your R projects from other environments. It's time to take your R programming to a whole new level with Deepnote!

If you encounter further issues, please get in touch with our support. Happy doing scientific stuff with R in Deepnote!

Filip Žitný

Data Scientist

Follow Filip on Twitter, LinkedIn and GitHub

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