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# Data audit

file SHA-256 rows (excl. header) cols
data/DGS10.csv 8187f89ab6523b3c964255e1736cfcf0e2ca854ed9e50343e04f4dc2945c5cd7 (matches README) 5217 2
data/README.md 32b825f02387ef3d552df6def82c585d7f248980667a28f30e58506e472e561a provenance text –
  • Schema: observation_date (YYYY-MM-DD), DGS10 (percent, string; empty on holidays).
  • Date range 2000-01-03 … 2019-12-31; monotonic increasing; 0 duplicate dates; only weekdays (Mon 1044, Tue 1044, Wed–Fri 1043 each).
  • Missing: 215 empty DGS10 fields (holidays). No non-empty unparseable values. Available values: 5002, range 1.37–6.79 %, mean 3.43 %.
  • After dropping empties and differencing: 5001 changes (2500 dated ≤2009-12-31, 2501 dated ≥2010-01-01).
  • 214 changes span a holiday (gap longer than the normal 1-day / Friday→Monday 3-day gap); none spans more than 4 calendar days. Kept per task rules (attributed to weekday of t).
  • Information-availability: the only input is the permitted file; no violation. The forecasting weekday means use train-period changes only (asserted in code).
  • Anomaly worth noting: Levene test rejects equal variances across weekdays (p≈1e-7), so the classical ANOVA's equal-variance assumption is violated; Kruskal–Wallis and Welch/HC1 checks reported as robustness.
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