Data Science & Analytics
Scientific DATA PREPROCESSING
⚠️ CRITICAL USER EXPERIENCE-BASED SKILL - ALWAYS CONSULT BEFORE DATA PREPROCESSING ⚠️ Prevents catastrophic errors (88.9% error rate in V1.0 case study) through multi-level feature analysis, data leakage detection, and semantic validation. MANDATORY for: data preprocessing, feature engineering, standardization, normalization, interpolation, missing value handling, feature selection, or ANY data transformation task. Covers grouped time-series, cross-sectional, panel data. Detects: time travel leakage, causal inversion, ID misuse, semantic-numeric fallacies, distribution blindness. User's hard-won lessons from real project failures.
- Publisher / source
- foryourhealth111-pixel/Vibe-Skills (found on GitHub top repositories)
- Upstream record
- foryourhealth111-pixel/Vibe-Skills
- Version
- Version 1
- Published
- Publication review
- Approved for publication · recorded passed scan 2026-11-05
- Content fingerprint
659d073666eade183d7280a85f7dbd772d394ac43f250bf82f9b159c0b695428