Python for Engineering and Scientific Computing — Practical Applications with NumPy, SciPy, Matplotlib, and more: https://t.co/Zh9vSeCF1r [511 pages] https://t.co/lN8zFaNqKo

Python for Engineering and Scientific Computing: Practical Applications with NumPy, SciPy, Matplotlib, and More (Rheinwerk Computing): 9781493225590: Computer Science Books @ Amazon.com

Source: https://www.amazon.com/dp/1493225596/ref=cm_sw_r_as_gl_api_gl_i_29QF3NZPC1TA82QGVWTS?linkCode=ml1&tag=kirkdborne-20&linkId=0b3887e6985d35b336f2beba11ed5e1d 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 Scientists Do 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 Modules Learn 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 Action Start 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.