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Synopsis
Introduction to Python for Science and Engineering offers a quick and incisive introduction to the Python programming language for use in any science or engineering discipline. The approach is pedagogical and “bottom up,” which means starting with examples and extracting more general principles from that experience. No prior programming experience is assumed.
Readers will learn the basics of Python syntax, data structures, input and output, conditionals and loops, user-defined functions, plotting, animation, and visualization. They will also learn how to use Python for numerical analysis, including curve fitting, random numbers, linear algebra, solutions to nonlinear equations, numerical integration, solutions to differential equations, and fast Fourier transforms.
Readers learn how to interact and program with Python using JupyterLab and Spyder, two simple and widely used integrated development environments.
All the major Python libraries for science and engineering are covered, including NumPy, SciPy, Matplotlib, and Pandas. Other packages are also introduced, including Numba, which can render Python numerical calculations as fast as compiled computer languages such as C but without their complex overhead.
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About the Author
David J. Pine has taught physics and chemical engineering for over 40 years at four different institutions: Cornell University (as a graduate student), Haverford College, UCSB, and NYU, where he is a Professor of Physics, Mathematics, and Chemical & Biomolecular Engineering. He has taught a broad spectrum of courses, including numerical methods. He does research on optical materials and in experimental soft-matter physics, which is concerned with materials such as polymers, emulsions, and colloids.
"About this title" may belong to another edition of this title.
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Introduction to Python for Science and Engineering (Hardcover)
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Taylor & Francis Ltd, London, 2024
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Hardcover. Condition: new. Hardcover. Introduction to Python for Science and Engineering offers a quick and incisive introduction to the Python programming language for use in any science or engineering discipline. The approach is pedagogical and bottom up, which means starting with examples and extracting more general principles from that experience. No prior programming experience is assumed.Readers will learn the basics of Python syntax, data structures, input and output, conditionals and loops, user-defined functions, plotting, animation, and visualization. They will also learn how to use Python for numerical analysis, including curve fitting, random numbers, linear algebra, solutions to nonlinear equations, numerical integration, solutions to differential equations, and fast Fourier transforms.Readers learn how to interact and program with Python using JupyterLab and Spyder, two simple and widely used integrated development environments.All the major Python libraries for science and engineering are covered, including NumPy, SciPy, Matplotlib, and Pandas. Other packages are also introduced, including Numba, which can render Python numerical calculations as fast as compiled computer languages such as C but without their complex overhead. Introduction to Python for Science and Engineering offers an incisive introduction to the Python programming language for use in any science or engineering discipline. The approach is pedagogical, which means starting with examples and extracting more general principles from that experience. No prior programming experience is assumed. Shipping may be from multiple locations in the US or from the UK, depending on stock availability. Seller Inventory # 9781032650333
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Introduction to Python for Science and Engineering (Series in Computational Biophysics)
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Condition: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. David J. Pine has taught physics and chemical engineering for over 40 years at four different institutions: Cornell University (as a graduate student), Haverford College, UCSB, and NYU, where he is a Professor of Physics, Mathematics, and Chemical. Seller Inventory # 1508419619
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