Book

Cleaning Data for Effective Data Science

Data in its raw state is rarely ready for productive analysis. This book not only teaches you data preparation, but also what questions you should ask of your data. It focuses on the thought processes necessary for successful data cleaning as much as on concise and precise code examples that express these thoughts.

Offered byPackt Logo

Difficulty Level
Intermediate
Completion Time
16h36m approx.
Language
English
Certification
Not available

About Course

Book Content

chapters 16h36m total length

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

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