Add group-level outputs to PrePostNEGD.summary()

[drbenvincent]

Summary

• add experiment-specific output to PrePostNEGD.summary() with group-level n, pre_mean, and post_mean
• keep existing causal impact and model coefficient reporting unchanged while improving interpretability
• add integration-test assertions and rerun ancova_pymc.ipynb so docs show updated summary output

Test plan

• conda run -n CausalPy pytest causalpy/tests/test_integration_pymc_examples.py -k test_ancova -v --no-cov
• conda run -n CausalPy pre-commit run --all-files
• Re-ran docs/source/notebooks/ancova_pymc.ipynb

Closes #727

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Documentation build overview

📚 causalpy | 🛠️ Build #32078068 | 📁 Comparing b8fced1 against latest (55256f5)

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404.html	📝 modified
notebooks/ancova_pymc.html	📝 modified
_modules/causalpy/experiments/prepostnegd.html	📝 modified

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Codecov Report

✅ All modified and coverable lines are covered by tests.
✅ Project coverage is 93.49%. Comparing base (eec45f7) to head (b8fced1).

Additional details and impacted files

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  Branches      658      662       +4     
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+ Hits        10538    10557      +19     
  Misses        544      544              
  Partials      190      190              

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[drbenvincent]

bugbot run

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PR Summary

Low Risk
Low risk: adds additional printed summary output and a small helper method, plus updates one integration test to assert the new output; core modeling/plotting logic is unchanged.

Overview
PrePostNEGD.summary() now prints group-level descriptive stats (per-group n, pre_mean, post_mean) before the existing causal impact and coefficient output, backed by a new _group_level_summary_stats() helper with optional rounding.

The test_ancova integration test is updated to capture stdout and assert the new section/columns and rounding behavior. .gitignore is expanded to ignore dashed variants of generated GitHub summary/comment directories.

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Inconsistent rounding semantics within summary() output

Medium Severity

_group_level_summary_stats uses DataFrame.round(round_to) which interprets round_to as decimal places, while _causal_impact_summary_stat and print_coefficients use round_num() which interprets round_to as significant figures. When summary(round_to=2) is called, group-level means get rounded to 2 decimal places (e.g., 3.14) but the causal impact and coefficients get rounded to 2 significant figures (e.g., 3.1). This makes the single round_to parameter behave inconsistently within the same output.

Additional Locations (1)

• causalpy/experiments/prepostnegd.py#L214-L223

 

[drbenvincent]

Good catch — this was indeed inconsistent. Fixed in 1fb0a82: _group_level_summary_stats now uses round_num() (significant figures) element-wise via .map(), matching the behavior of _causal_impact_summary_stat and print_coefficients. The integration test assertions were updated accordingly.