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feat(timesfm): complete all three examples with quality docs
- anomaly-detection: full two-phase rewrite (context Z-score + forecast PI), 2-panel viz, Sep 2023 correctly flagged CRITICAL (z=+3.03) - covariates-forecasting: v3 rewrite with variable-shadowing bug fixed, 2x2 shared-axis viz showing actionable covariate decomposition, 108-row CSV with distinct per-store price arrays - global-temperature: output/ subfolder reorganization (all 6 output files moved, 5 scripts + shell script paths updated) - SKILL.md: added Examples table, Quality Checklist, Common Mistakes (8 items), Validation & Verification with regression assertions - .gitattributes already at repo root covering all binary types
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@@ -94,7 +94,8 @@ output_df = pd.DataFrame(
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)
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# Save outputs
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output_dir = Path(__file__).parent
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output_dir = Path(__file__).parent / "output"
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output_dir.mkdir(exist_ok=True)
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output_df.to_csv(output_dir / "forecast_output.csv", index=False)
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# JSON output for the report
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