Spin up a codespace to use for data science: Python, R, Julia

In this 10 minute video, I show you how to spin up a codespace for data science with the core data science R packages. Note, in the video I add the R extension. I forgot to mention that you should click on the "cog" icon of the extension and add it to your devcontainer.json so it'll be there next time you start your codespace. Also I didn't show how to get back to your codespace after you close it: click the "codespaces" tab at the top and then you'll see your codespaces listed below. BTW, your codespace will stop after inactivity but you can pre-empt that and stop right away so that you don't burn up your 60 hours.

For the NMFS Openscapes fall 2022 cohorts.

1. Create a repo
2. Click on Codespaces (top nav bar)
3. Ignore templates and click the green button to add a codespace
4. Associate the codespace with your repo (it's fairly obvious)
5. Your codespace will spin-up and now you need to add your data science container. You only do this the first time.
6. Click in the lower left corner and when the pop-up shows up, click "Add dev container" (something like that)
7. Start typing "data science" in the search and pick the Jupyter Data Science container.
In lower right, click to rebuild your container.
8. Click the boxes icon on the left and add the R extension.
9. Click the branch icon and push your changes (the dev container files) to your repo.
10. Done! Now start adding files and coding.