📘 Data Wrangling & EDA — Guidebooks and Guides

This section provides practical, structured resources for preparing, validating, and exploring datasets before modeling.
It includes Guidebooks for deep-dive learning and Guides for quick, actionable steps — helping analysts and data scientists move from raw data to meaningful insights efficiently and with confidence.

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📂 Sections & Links

Data Wrangling — 📘 Guides for Transformation & Validation

• 📘 Advanced Feature Transformation Guide — In-depth strategies for creating high-signal, domain-relevant features.
• 📘 Data Wrangling and Validation Guide — Ensuring clean, accurate, and well-structured datasets ready for analysis.
• 📘 Feature Transformation Guide — Practical feature engineering steps for improving model performance.

Exploratory Data Analysis (EDA) — 📊 Guides & 📘 Guidebooks

• 📊 Advanced EDA Visual Interpretation Guide — Expert-level visual analytics for pattern detection and anomaly spotting.
• 📊 EDA Statistical Interpretation Guide — How to interpret statistical outputs from EDA for deeper understanding.
• 📊 Visual EDA Interpretation Guide — Core visual analysis techniques for effective data storytelling.
• 📘 Advanced EDA Guidebook — Comprehensive, scenario-driven EDA methodology for advanced users.
• 📘 General EDA Guidebook — A foundational playbook for structured EDA in any project.