Cleaning Data for Effective Data Science

Cleaning Data for Effective Data Science

Doing the other 80% of the work with Python, R, and command-line tools

Mertz, David

Packt Publishing Limited

03/2021

498

Mole

Inglês

9781801071291

15 a 20 dias

Descrição não disponível.

Table of Contents

Data Ingestion - Tabular Formats
Data Ingestion - Hierarchical Formats
Data Ingestion - Repurposing Data Sources
The Vicissitudes of Error - Anomaly Detection
The Vicissitudes of Error - Data Quality
Rectification and Creation - Value Imputation
Rectification and Creation - Feature Engineering
Ancillary Matters - Closure/Glossary

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Data cleansing;Python for data science;R for data science;Data science for business;R for data analysis;R programming for data science;data science python;data interpretation;data cleaning python