# Contract (F1-dev-01)

Question: build a documented, one-row-per-firm analytic dataset from data/firms.csv and report basic aggregates. Estimands: (1) number of distinct firm_id; (2) mean and median revenue in millions USD over distinct firms with known revenue; (3) mean employees over all distinct firms; plus baseline raw mean of the revenue column as read (all non-empty rows, no cleaning). These are descriptive statistics of a synthetic finite file; meaningful provided duplicates are removed and units harmonised. Outputs: out/results.json (task_id, n_unique_firms, n_missing_revenue, n_analysed, mean_revenue_musd, median_revenue_musd, mean_employees, mean_revenue_raw, feasibility, feasibility_reason, data_issues, n_input_rows, random_seed), out/analytic.csv (firm_id, sector, revenue_musd, employees; n_analysed rows), out/exclusions.csv (step, rule, n_before, n_after, n_removed, rationale; chained), out/report.md (6 sections), out/analysis.py, out/claims.json. Information rules: only data/firms.csv; revenue in millions USD everywhere; rows with unknown revenue excluded from revenue aggregates and listed in ledger. Invalidating conditions: unknown/unconvertible units, conflicting duplicates with no resolution rule, unparseable values.