Cleaning Data for Effective Data Science

Table of Contents

1. Data Ingestion – Tabular Formats
2. Data Ingestion - Hierarchical Formats
3. Data Ingestion - Repurposing Data Sources
4. The Vicissitudes of Error - Anomaly Detection
5. The Vicissitudes of Error - Data Quality
6. Rectification and Creation - Value Imputation
7. Rectification and Creation - Feature Engineering
8. Ancillary Matters - Closure/Glossary