Practical Python Data Wrangling and Data Quality
Language: English
Published by O'Reilly Media, 2021
- Softcover
- New
Condition: New
£ 54.85
Quantity: 1 available
Add to basketItem description from seller
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 visu.
Seller Inventory # 497646901
- Title
- Practical Python Data Wrangling and Data Quality
- Author
- Susan E. Mcgregor
- Publisher
- O'Reilly Media
- Publication year
- 2021
- Condition
- New
- Binding
- Soft cover
- Language
- English
- ISBN 10
- 1492091502
- ISBN 13
- 9781492091509
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 sources
- Understand 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
"Synopsis" may belong to another edition of this title.
About the Author
Susan E. McGregor is a researcher at Columbia University's Data Science Institute, where she also cochairs its Center for Data, Media and Society. For over a decade, she has been refining her approach to teaching programming and data analysis to non-STEM learners at the professional, graduate, and undergraduate levels.
McGregor has been a full-time faculty member and researcher at Columbia University since 2011, when she joined Columbia Journalism School and the Tow Center for Digital Journalism. While there, she developed the school's first data journalism curriculum and served as a primary academic advisor for its dual-degree program in Journalism and Computer Science. Her academic research centers on security and privacy issues affecting journalists and media organizations, and is the subject of her first book, Information Security Essentials: A Guide for Reporters, Editors, and Newsroom Leaders (CUP).
Prior to her work at Columbia, McGregor spent several years as the Senior Programmer on the News Graphics team at the Wall Street Journal. She was named a 2010 Gerald Loeb Award winner for her work on WSJ's original "What They Know" series, and has spoken and published at a range of leading academic security and privacy conferences. Her work has received support from the National Science Foundation, the Knight Foundation, Google, and multiple schools and offices of Columbia University. McGregor is also interested in how the arts can help stimulate critical thinking and introduce new perspectives around technology issues. She holds a master's degree in Educational Communication and Technology from NYU and a bachelor's degree in Interactive Information Design from Harvard University.
"About the title" may belong to another edition of this title.
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