Learning scientific programming with Python / Christian Hill.
Material type:
TextPublisher: New York : Cambridge University Press, 2020Edition: Second editionDescription: 1 online resourceContent type: text Media type: computer Carrier type: online resourceISBN: 9781108778039Subject(s): Science -- Data processing | Science -- Mathematics | Python (Computer program language)Additional physical formats: Print version:: Learning scientific programming with PythonDDC classification: 005.133 LOC classification: Q183.9Summary: "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 gain proficiency quickly. Beginning with general programming concepts such as loops and functions within the core Python 3 language, and moving on to the NumPy, SciPy and Matplotlib libraries for numerical programming and data visualization, this textbook also discusses the use of Jupyter Notebooks to build rich-media, shareable documents for scientific analysis. The second edition features a new chapter on data analysis with the pandas library and comprehensive updates, and new exercises and examples. A final chapter introduces more advanced topics such as floating-point precision and algorithm stability, and extensive online resources support further study. This textbook represents a targeted package for students requiring a solid foundation in Python programming"-- Provided by publisher.
| Item type | Current location | Home library | Call number | Status | Date due | Barcode | Item holds |
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Book
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School of Civil and Environmental Engineering (SCEE) | School of Civil and Environmental Engineering (SCEE) | 005.133 HIL (Browse shelf) | Available | 13627 |
Includes bibliographical references and index.
"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 gain proficiency quickly. Beginning with general programming concepts such as loops and functions within the core Python 3 language, and moving on to the NumPy, SciPy and Matplotlib libraries for numerical programming and data visualization, this textbook also discusses the use of Jupyter Notebooks to build rich-media, shareable documents for scientific analysis. The second edition features a new chapter on data analysis with the pandas library and comprehensive updates, and new exercises and examples. A final chapter introduces more advanced topics such as floating-point precision and algorithm stability, and extensive online resources support further study. This textbook represents a targeted package for students requiring a solid foundation in Python programming"-- Provided by publisher.
Description based on print version record and CIP data provided by publisher; resource not viewed.
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