Susan E. McGregor
Practical Python Data Wrangling and Data Quality: Getting Started with Reading, Cleaning, and Analyzing Data
Practical Python Data Wrangling and Data Quality: Getting Started with Reading, Cleaning, and Analyzing Data
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This book provides a practical guide to extracting, evaluating, and analyzing data, with examples and techniques for beginners and experienced data practitioners. It covers Python programming basics, data wrangling, statistical analyses, and visualization, helping readers harness the power of data.
Format: Paperback / softback
Length: 500 pages
Publication date: 17 December 2021
Publisher: O'Reilly Media, Inc, USA
Whether you already work with data or want to learn more about its possibilities, the examples and techniques in this practical book will help you more easily clean, evaluate, and analyze data so that you can generate meaningful insights and compelling visualizations.
The world around us is full of data that holds unique insights and valuable stories, and this book will help you uncover them. Whether you already work with data or want to learn more about its possibilities, the examples and techniques in this practical book will help you more easily clean, evaluate, and analyze data so that you can generate meaningful insights and compelling visualizations. Complementing foundational concepts with expert advice, author Susan E.
McGregor provides the resources you need to extract, evaluate, and analyze a wide variety of data sources and formats, along with the tools to communicate your findings effectively. This book delivers a methodical, jargon-free way for data practitioners at any level, from true novices to seasoned professionals, to harness the power of data. Use Python 3.8+ to read, write, and transform data from a variety of sourcesUnderstand and use programming basics in Python to wrangle data at scale
Organize, document, and structure your code using best practices
Collect data from structured data files, web pages, and APIs
Perform basic statistical analyses to make meaning from datasets
Visualize and present data in clear and compelling ways
Dimension: 233 x 178 (mm)
ISBN-13: 9781492091509
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