Practical Python Data Wrangling and Data Quality: Getting Started with Reading, Cleaning, and Analyzing Data

McGregor, Susan E.

  • 出版商: O'Reilly
  • 出版日期: 2021-12-28
  • 售價: $2,050
  • 貴賓價: 9.5$1,948
  • 語言: 英文
  • 頁數: 416
  • 裝訂: Quality Paper - also called trade paper
  • ISBN: 1492091502
  • ISBN-13: 9781492091509
  • 相關分類: Python
  • 立即出貨 (庫存 < 3)



There are awesome discoveries to be made and valuable stories to be told in datasets--and this book will help you uncover them. Whether you already work with data or just want to understand its possibilities, the techniques and advice in this practical book will help you learn how to better clean, evaluate, and analyze data to generate meaningful insights and compelling visualizations.

Through foundational concepts and worked examples, author Susan McGregor provides the tools you need to evaluate and analyze all kinds of data and communicate your findings effectively. This book provides a methodical, jargon-free way for practitioners of all levels 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
  • Complete exercises either on your own machine or on the web
  • Collect data from structured data files, web pages, and APIs
  • Perform basic statistical analysis to make meaning from data sets
  • Visualize and present data in clear and compelling ways


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.