How to set up and run Python and R Data Science Development Environment with Jupyter on Docker

Presenter: Wasin Waeosri from Refinitiv

Length: 9.50 mins

One of the hardest parts of being Data Developers is the step to set up those tools. You need to install a lot of software and libraries in the correct order to set up your Data Science development environment.

The good news is you can reduce the effort to set up the workbench with the Docker containerization platform. You may think Docker is for the DevOps or the hardcore Developers only, but the Jupyter Docker Stacks simplifies how to create a ready-to-use Jupyter application with Data Science/Financial libraries in a few commands.

The video demonstrates how to set up and run the Jupyter environment on Docker for the Python and R Data Science development projects.

Full article and details about the steps to run Jupyter with Docker can be found in the following articles:

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