Phase 3: add summary() descriptive statistics - #11
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Implement epydem.summary() for computing descriptive statistics on epidemiological DataFrames with conservative defaults (n-only when no column lists specified), date/numeric/categorical metrics, deterministic categorical tie-breaking, and long/wide output formats. Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
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CI still running ⏳ (pending). PR: #11 |
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CI still running ⏳ (pending). PR: #11 |
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Summary
epydem.summary(df, by, date_cols, numeric_cols, categorical_cols, top_k, output)for descriptive statistics on epidemiological DataFramesnwhen no column lists are specified (no auto-inference)nper group, missingness (missing_n,missing_pct), date (min/maxafterpd.to_datetimecoercion), numeric (count/mean/std/min/p25/median/p75/max), categorical (top-k with deterministic tie-break: count desc, string asc;<NA>token)"long"(default) and"wide"(pivoted)Checklist
epydem/summary.py— full implementationepydem/__init__.py— exportsummarytests/test_summary.py— 21 tests across 6 classesbyvs no-bynbehaviorsummary()Test plan
pytest tests/— all 32 tests pass (11 existing + 21 new)summary(df)with no column lists returns onlyn"NOT_A_DATE"are counted as missing after coercionCloses #10
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