Python Scripting for Computational Science
by Hans Petter Langtangen
Publisher: Springer 2009
Number of pages: 747
With a primary focus on examples and applications of relevance to computational scientists, this brilliantly useful book shows computational scientists how to develop tailored, flexible, and human-efficient working environments built from small scripts written in the easy-to-learn, high-level Python language.
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by Jake VanderPlas - O'Reilly Media
The book introduces the core libraries essential for working with data in Python: particularly IPython, NumPy, Pandas, Matplotlib, Scikit-Learn, etc. Familiarity with Python as a language is assumed. The book was written and tested with Python 3.5.
by Boudewijn Rempt - OpenDocs, LLC
This book covers application development using the library extension PyQt, which forms the basis for GUI programming. First part explains concepts using small examples, in the second part the author develops a complete, complex application.
by Charles R. Severance - PythonLearn
This book is designed to introduce students to programming and software development through the lens of exploring data. You can think of the Python programming language as a tool to solve data problems that are beyond the capability of a spreadsheet.
by Jeffrey Elkner, at al.
The goal of this book is twofold: to teach you how to program in Python; and to teach you to think like a computer scientist. This way of thinking combines some of the best features of mathematics, engineering, and natural science.