Learning scientific programming with Python - Info and Reading Options
By Christian Hill
"Learning scientific programming with Python" was published by Cambridge University Press in 2015 - enk, it has 452 pages and the language of the book is English.
“Learning scientific programming with Python” Metadata:
- Title: ➤ Learning scientific programming with Python
- Author: Christian Hill
- Language: English
- Number of Pages: 452
- Publisher: Cambridge University Press
- Publish Date: 2015
- Publish Location: enk
“Learning scientific programming with Python” Subjects and Themes:
- Subjects: ➤ Science - Python (Computer program language) - Data processing - Mathematics - Science, data processing - Science, mathematics - SCIENCE / Mathematical Physics - Python (computer program language) - Sciences - Informatique - Mathématiques - Python (Langage de programmation) - SCIENCE - Mathematical Physics - Wissenschaftliches Rechnen - Python
Edition Specifications:
- Pagination: vii, 452 pages
Edition Identifiers:
- The Open Library ID: OL27208567M - OL20028518W
- Online Computer Library Center (OCLC) ID: 910802419 - 961001536
- Library of Congress Control Number (LCCN): 2015017085
- ISBN-13: 9781107075412 - 9781107428225
- ISBN-10: 1107075416 - 110742822X
- All ISBNs: 1107075416 - 110742822X - 9781107075412 - 9781107428225
AI-generated Review of “Learning scientific programming with Python”:
"Learning scientific programming with Python" Table Of Contents:
- 1- 1. Introduction
- 2- 2. The core Python language I
- 3- 3. Interlude: simple plotting with pylab
- 4- 4. The core Python language II
- 5- 5. IPython and IPython notebook
- 6- 6. NumPy
- 7- 7. Matplotlib
- 8- 8. SciPy
- 9- 9. General scientific programming
- 10- Appendix A. Solutions.
"Learning scientific programming with Python" Description:
The Open Library:
"Learn to master basic programming tasks from scratch with real-life scientifically relevant examples and solutions drawn from both science and engineering. Students and researchers at all levels are increasingly turning to the powerful Python programming language as an alternative to commercial packages and this fast-paced introduction moves from the basics to advanced concepts in one complete volume, enabling readers to quickly gain proficiency. Beginning with general programming concepts such as loops and functions within the core Python 3 language, and moving onto the NumPy, SciPy and Matplotlib libraries for numerical programming and data visualisation, this textbook also discusses the use of IPython notebooks to build rich-media, shareable documents for scientific analysis. Including a final chapter introducing challenging topics such as floating-point precision and algorithm stability, and with extensive online resources to support advanced study, this textbook represents a targeted package for students requiring a solid foundation in Python programming"--
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