Data Wrangling with Python

Kazil, Jacqueline; Jarmul, Katharine

ISBN 10: 1491948817 / ISBN 13: 9781491948811

Verlag: O'Reilly Media, 2016

Beschreibung

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Bestandsnummer des Verkäufers 22301541-5

Bibliografische Details

• Titel: Data Wrangling with Python
• Verlag: O'Reilly Media
• Erscheinungsjahr: 2016
• Sprache: Englisch
• ISBN-10: 1491948817
• ISBN-13: 9781491948811
• Einband: Softcover
• Zustand: good

Über diesen Titel

Inhaltsangabe

How do you take your data analysis skills beyond Excel to the next level? By learning just enough Python to get stuff done. This hands-on guide shows non-programmers like you how to process information thatâ s initially too messy or difficult to access. You don't need to know a thing about the Python programming language to get started.

Through various step-by-step exercises, youâ ll learn how to acquire, clean, analyze, and present data efficiently. Youâ ll also discover how to automate your data process, schedule file- editing and clean-up tasks, process larger datasets, and create compelling stories with data you obtain.

• Quickly learn basic Python syntax, data types, and language concepts
• Work with both machine-readable and human-consumable data
• Scrape websites and APIs to find a bounty of useful information
• Clean and format data to eliminate duplicates and errors in your datasets
• Learn when to standardize data and when to test and script data cleanup
• Explore and analyze your datasets with new Python libraries and techniques
• Use Python solutions to automate your entire data-wrangling process

Über die Autorin bzw. den Autor

Jacqueline Kazil is a Presidential Innovation Fellow working on Disaster Response and Recovery at the Federal Emergency Management Agency (FEMA). Jackie is a software developer passionate about human behavior and open data. Most recently, she worked for CACI, where she was lead developer on a contract at The Library of Congress, working on projects such as Chronicling America and Congress.gov. Previously, Jackie worked for The Washington Post on news-driven data applications - including the notable Top Secret America series, which received multiple awards including the 2010 George Polk Award for Journalism and was a SXSW Finalist for Technical Achievement. She has experience in software development using best practices, data analysis, modeling and simulation, social network analysis, data handling, data storage, mapping, and geospatial analysis. She is also active in open-source community development. She founded PyLadies DC and Geo DC. She also runs Django District and assists with DC Python. Jackie received her MA in Convergence Journalism from the University of Missouri, and she is currently working on her PhD in Computational Social Science at George Mason University.