Python Data Science Handbook

Python Data Science Handbook

The book introduces the core libraries essential for working with data in Python: particularly IPython, NumPy, Pandas, Matplotlib, Scikit-Learn, and related packages. Familiarity with Python as a language is assumed.

Publication date: 01 Nov 2016

ISBN-10: n/a

ISBN-13: 9781491912058

Paperback: 548 pages

Views: 3,800

Type: Book

Publisher: O’Reilly Media, Inc.

License: Creative Commons Attribution-NonCommercial-NoDerivs 3.0 United States

Post time: 28 Jul 2020 05:00:00

Python Data Science Handbook

Python Data Science Handbook The book introduces the core libraries essential for working with data in Python: particularly IPython, NumPy, Pandas, Matplotlib, Scikit-Learn, and related packages. Familiarity with Python as a language is assumed.
Tag(s): Data Science Python
Publication date: 01 Nov 2016
ISBN-10: n/a
ISBN-13: 9781491912058
Paperback: 548 pages
Views: 3,800
Document Type: Book
Publisher: O’Reilly Media, Inc.
License: Creative Commons Attribution-NonCommercial-NoDerivs 3.0 United States
Post time: 28 Jul 2020 05:00:00
Summary/Excerpts of (and not a substitute for) the Creative Commons Attribution-NonCommercial-NoDerivs 3.0 United States:
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From the Book Description:
For many researchers, Python is a first-class tool mainly because of its libraries for storing, manipulating, and gaining insight from data. Several resources exist for individual pieces of this data science stack, but only with the Python Data Science Handbook do you get them all—IPython, NumPy, Pandas, Matplotlib, Scikit-Learn, and other related tools.

Working scientists and data crunchers familiar with reading and writing Python code will find this comprehensive desk reference ideal for tackling day-to-day issues: manipulating, transforming, and cleaning data; visualizing different types of data; and using data to build statistical or machine learning models. Quite simply, this is the must-have reference for scientific computing in Python.

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About The Author(s)


Jake VanderPlas was formerly both the Director of Open Software and the Director of Research in Physical Sciences for the eScience Institute; he now works at Google. He comes from a background of machine learning and data-intensive astronomy and astrophysics.

Jake Vanderplas

Jake VanderPlas was formerly both the Director of Open Software and the Director of Research in Physical Sciences for the eScience Institute; he now works at Google. He comes from a background of machine learning and data-intensive astronomy and astrophysics.


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