Counterfactual generation using pymc do-operator example notebook

[shekharkhandelwal1983]

This notebook provides a detailed steps required to generate counterfactuals, and demonstrates the newly introduced do-operator capabilities. And how it can be used to achieve Causality.

• Issue id - Counterfactual generation using pymc do-operator #568

• Notebook follows style guide https://docs.pymc.io/en/latest/contributing/jupyter_style.html
• PR description contains a link to the relevant issue:
  • a tracker one for existing notebooks (tracker issues have the "tracker id" label)
  • or a proposal one for new notebooks
• Check the notebook is not excluded from any pre-commit check: https://github.com/pymc-devs/pymc-examples/blob/main/.pre-commit-config.yaml

Helpful links

• https://github.com/pymc-devs/pymc-examples/blob/main/CONTRIBUTING.md

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📚 Documentation preview 📚: https://pymc-examples--569.org.readthedocs.build/en/569/

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[drbenvincent]

Might overlap with #554 which I'm working on with @juanitorduz. Not necessarily the end of the world though - there's a clear opportunity for stuff on this topic. Would like to review this - but just became a father (yesterday!) so there might be a minor delay

[twiecki]

What I really like about this NB is how it lays out the new workflow with creating the skeleton model first. Maybe that should be the focus.

[twiecki]

@shekharkhandelwal1983 Can you update the NB to focus on the new workflow? Mainly I think the title needs to be changed and some of the narrative.
Also, since pymc 5.8.0 the do and observe functions are now in pymc!

[aloctavodia]

In case this is still useful, I updated this to work with new versions of PyMC and ArviZ. If not useful, feel free to close.