Python for Engineering and Scientific Computing: Practical Applications with NumPy, SciPy, Matplotlib, and More (Rheinwerk Computing)
$58.61
$68.95
ISBN 9781493225590
Book info: Python for Engineering and Scientific Computing: Practical Applications with NumPy, SciPy, Matplotlib, and More (Rheinwerk Computing) (Paperback, 511 pages) – Rheinwerk Computing, 2024. Language: English. It’s finally here—your guide to Python for engineers and scientists, by an engineer and scientist! Get to know your development environments and the...
Book info: Python for Engineering and Scientific Computing: Practical Applications with NumPy, SciPy, Matplotlib, and More (Rheinwerk Computing) (Paperback, 511 pages) – Rheinwerk Computing, 2024. Language: English.
It’s finally here—your guide to Python for engineers and scientists, by an engineer and scientist! Get to know your development environments and the key Python modules you’ll need: NumPy, SymPy, SciPy, Matplotlib, and VPython. Understand basic Python program structures and walk through practical exercises that start simple and increase in complexity as you work your way through the book. With information on statistical calculations, Boolean algebra, and interactive programming with Tkinter, this Python guide belongs on every scientist’s shelf!
- A practical guide to Python for nonprogrammers
- Work with NumPy, SymPy, SciPy, Matplotlib, and VPython
- Automate numerical calculations, create simulations and visualizations, perform statistical analysis, and more
Python for ScientistsDo you already know how to solve problems in mathematics, physics, or engineering? In this guide you’ll find the tools you need to map your existing calculations with Python.
Python ModulesLearn how NumPy, SymPy, SciPy, Matplotlib, and VPython can help you with your scientific work. From solving linear equations and creating animations to using discrete fourier transformations to reconstruct a noisy signal, you’ll find the practical advice you need.
Python in ActionStart simple by seeing how to size a shaft and then move on to increasingly advanced exercises: animating a pendulum, simulating a rolling bearing defect, creating a predator-prey model, and more. For every exercise, the complete source code, with extensive code comments, are presented and the output analyzed to help you to see how to solve scientific problems with Python programs.
Editorial Reviews About the AuthorDr. Veit Steinkamp studied electrical engineering and German to become a teacher and pass on his knowledge at vocational schools and technical colleges. He teaches electrical engineering, application development, and mechanical engineering technology. He has also taught theoretical electrical engineering and the fundamentals of electrical engineering.