Python Data Cleaning Cookbook 2nd Edition

Grab attention with clean, reliable data: Python Data Cleaning Cookbook, 2nd Edition by Michael Walker is an indispensable, hands-on guide for anyone who prepares data for analysis. Whether you’re a data analyst, scientist, engineer, or business professional, this practical cookbook helps you tame messy datasets quickly and confidently.

Explore clear, real-world recipes that solve common data problems using the modern Python ecosystem. Walker focuses on tested techniques with pandas, NumPy, regular expressions, datetime handling, and scalable approaches for larger datasets. Each chapter delivers step-by-step solutions for missing values, inconsistent formats, outliers, text cleaning, and pipeline automation — all aimed at improving data quality and accelerating analytics projects.

Imagine spending less time wrangling files and more time delivering insights. This second edition includes updated strategies for performance, reproducibility, and best practices that translate across industries and geographies — from finance teams in New York to healthcare analysts in London and engineers in Bangalore. The book balances theory and practice, so you learn why methods work and how to apply them to your own datasets.

If you want a practical reference that makes data cleaning predictable, efficient, and repeatable, Python Data Cleaning Cookbook is the tool to keep on your shelf. Order your copy today and start transforming noisy data into dependable, analysis-ready information.

Note: eBooks do not include supplementary materials such as CDs, access codes, etc.