Digging into data does not have to be painful. With Data Wrangling Using Python, you'll learn how to clean and analyze data, create compelling stories, and scale that data as necessary. Num Pages: 450 pages. BIC Classification: UMW; UNC. Category: (XV) Technical / Manuals. Dimension: 250 x 150 x 15. Weight in Grams: 666. . 2016. 1st Edition. Paperback. . . . .

Bestandsnummer des Verk�ufers V9781491948811

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Titel: Data Wrangling with Python
Verlag: O?Reilly Media, Inc, USA
Erscheinungsjahr: 2016
Sprache: Englisch
ISBN-10: 1491948817
ISBN-13: 9781491948811
Einband: Softcover
Auflage: 1. Auflage
Zustand: New

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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 that� 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, you� ll learn how to acquire, clean, analyze, and present data efficiently. You� 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

�ber 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.

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