A Whirlwind Tour of Python
This free e-book is a fast-paced intro to Python aimed at researchers and engineers.
Tag(s): Data Science Python
Publication date: 01 Aug 2016
ISBN-10: n/a
ISBN-13: 9781491964644
Paperback: 98 pages
Views: 15,819
Type: Book
Publisher: O’Reilly Media, Inc.
License: Creative Commons CC0 “No Rights Reserved”
Post time: 29 Jul 2020 06:00:00
A Whirlwind Tour of Python
This free e-book is a fast-paced intro to Python aimed at researchers and engineers.
Publication date: 01 Aug 2016
ISBN-10: n/a
ISBN-13: 9781491964644
Paperback: 98 pages
Views: 15,819
Document Type: Book
Publisher: O’Reilly Media, Inc.
License: Creative Commons CC0 “No Rights Reserved”
Post time: 29 Jul 2020 06:00:00
In contrast to CC’s licenses that allow copyright holders to choose from a range of permissions while retaining their copyright, CC0 empowers yet another choice altogether – the choice to opt out of copyright and database protection, and the exclusive rights automatically granted to creators – the “no rights reserved” alternative to our licenses.
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To tap into the power of Python's open data science stack—including NumPy, Pandas, Matplotlib, Scikit-learn, and other tools—you first need to understand the syntax, semantics, and patterns of the Python language. This report provides a brief yet comprehensive introduction to Python for engineers, researchers, and data scientists who are already familiar with another programming language.
Author Jake VanderPlas, an interdisciplinary research director at the University of Washington, explains Python’s essential syntax and semantics, built-in data types and structures, function definitions, control flow statements, and more, using Python 3 syntax.
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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 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.