Add check for complete categories when constructing contingency tables

[jarq6c]

This adds a check and corrects missing boolean categories in Categorical series input to compute_contingency_table.

Additions

• Checks for both True and False in observed and simulated input series.

Removals

• None

Changes

• Update original test to use categorical series instead of raw categories per the original docstring and intended use of compute_contingency_table.

Testing

1. Four new test scenarios for compute_contingency_table that check for all True and all False cases.

Notes

• Fixes contingency_table computed from compute_contingency_table doesn’t contain both True and False for the observed or the simulated series  #183

Todos

• None

Checklist

• PR has an informative and human-readable title
• PR is well outlined and documented. See #12 for an example
• Changes are limited to a single goal (no scope creep)
• Code can be automatically merged (no conflicts)
• Code follows project standards (see CONTRIBUTING.md)
• Passes all existing automated tests
• Any change in functionality is tested
• New functions are documented (with a description, list of inputs, and expected output) using numpy docstring formatting
• Placeholder code is flagged / future todos are captured in comments
• Reviewers requested with the Reviewers tool ➡️

[jarq6c]

Tagging @aaraney

[jarq6c]

@hellkite500 @aaraney any feedback on this PR?

[jarq6c]

@hellkite500 @aaraney Following last week's meeting, I replaced all the complicated categorical checks with a simple pandas.Series creation. This removed the need for a lot of code and as a nice side-effect made compute_contingency_table compatible with any array-like, instead of just pandas.Series. This means the compute_contingency_table interface is more like the other metrics.

I was also able to remove a step from the README example since the categorical conversion is now covered by the _validation.convert_to_boolean_categorical_series method.

The only warning that's still raised is if the method encounters something that isn't one of the prescribed categories. These values are treated as NaN and the user is warned.

[hellkite500]

Nice work on the refactor, by the way! Much simpler, and even more general! I like it!

[jarq6c]

Nice work on the refactor, by the way! Much simpler, and even more general! I like it!

Thanks for the review!

[hellkite500]

Approved, but I'll give @aaraney a chance to look it over before merging.

[jarq6c]

This has been published to PyPI.

[aaraney]

sorry for being slow to get to this. having looked at it now, I would have approved the merge. like @hellkite500's noted, I think the refactor was done nicely. Nice work!

[jarq6c]

sorry for being slow to get to this. having looked at it now, I would have approved the merge. like @hellkite500's noted, I think the refactor was done nicely. Nice work!

Thanks @aaraney !