/EPA_binder

Template repo that can run Jupyter Notebook and R(Studio) though Binder and VS Code through GitPod

Primary LanguageR

EPA_binder

Binder config that can run Jupyter Notebook (in Lab) and R with the packages and tools you'll likely need for EPA1315 and EPA1333.

How To

  1. Fork this repository (repo) – you'll need a GitHub account
  2. Upload the notebook files you need to run into your repo (this requires a "commit"). The "master" branch should be fine, though you should learn what this means.
  3. Launch your Binder (or Google Colab)
  4. Run the notebook or R files you need (or create a new one from the interface); make sure you're on the kernel you want
  5. Save and download the saved file to your own computer and then re-upload it to your GitHub repository

Example (with Jupyter Lab): Binder Example with RStudio: Binder

Launching your Binder

You have two options to access Binder:

  1. Go to mybinder.org and follow the instructions there – use your own repo
  2. Use this URL but paste in your own username: https://mybinder.org/v2/gh/jasonrwang/EPA_binder/master?urlpath=lab

Binder also lets you run RStudio directly instead of launching in Jupyter Lab. To do this, simply add ?urlpath=rstudio at the end of the URL (like in #2 above). For example, https://mybinder.org/v2/gh/jasonrwang/EPA_binder/master?urlpath=rstudio

Alternative Options

If you're only using Jupyter Notebook with Python, you can also launch this in Google Colab. It might be more user-friendly to use, but comes with a bunch of Google-specific stuff that might be annoying. You can easily integrate Google Colab with your GitHub account too, or you can keep the files in your Google Drive.

If you don't care about the Jupyter Notebook part (there are good reasons to!), then you can spin up an online VS Code Python environment with GitPod. It's the same logic as above; for me, it's https://gitpod.io/github.com/jasonrwang/EPA_binder.

Other

Comes with packages listed in:

  • requirements.yml (Conda for Python)
  • runtime.txt (specific version of Microsoft R – note this may differ from Conda's version)
  • install.R (for R)

Note that the melt and cast features of reshape2 can also be done in tidyr, which is part of tidyverse! See more here.

You can also run the binder in the older Jupyter Notebook by removing the "?urlpath=lab" part of the URL. There are many reasons to use Lab instead though!

Adding More Packages

Edit one of the above requirements/install files to include the package you want to use for next time you launch Binder. This may require Binder to recompile your working environment, which can take many, many

If you need to do something quickly, make a new cell and:

  • With a Python kernel, run %pip install package_name
  • With an R kernel, run install.packages("package_name")