Python Data Science Handbook
by Jake VanderPlas
Publisher: O'Reilly Media 2016
Number of pages: 548
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. The book was written and tested with Python 3.5.
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by John C. Lusth - The University of Alabama
Contents: Starting Out; Literals; Combining Literals; Precedence and Associativity; Variables; Assignment; Conditionals; Functions; Python Programs and Using Files; Input and Output; Scope; Loops; Recursion; Arrays; Sorting; Footnotes; etc.
by Richard L. Halterman - Southern Adventist University
The focus is on introducing programming techniques and developing good habits. Our approach avoids some more esoteric features of Python and concentrates on the programming basics that transfer directly to other imperative programming languages.
by Katja Schuerer, Catherine Letondal - Pasteur Institute
This course is designed for biologists who already have some programming knowledge in other languages. The focus is on biological examples that are used throughout the course, as well as the suggested exercises drawn from the field of biology.
by Mike Pirnat - O'Reilly Media
Even the best programmers make mistakes, some are simple and silly, others embarrassing and downright costly. In this book, Mike Pirnat dissects some of his most memorable blunders, peeling them back layer-by-layer to reveal just what went wrong.