This book provides a thorough introduction to Python programming designed for engineers and scientists. It begins with foundational topics like development environments and program structures, then introduces key Python libraries such as NumPy, SymPy, SciPy, Matplotlib, and VPython. Clear explanations and practical exercises help readers write efficient, well-structured code while progressing through increasingly complex projects.
The content covers core programming paradigms including functions, branching, and object-oriented design, followed by numerical analysis with NumPy and symbolic math with SymPy. Detailed chapters on data visualization with Matplotlib and 3D animations with VPython enhance comprehension. Additional focus on statistical computations, Boolean algebra, and interactive GUI programming with Tkinter prepares readers for real-world applications. Each chapter ends with project tasks reinforcing hands-on learning.
Throughout the book, readers build a strong skill set combining programming expertise and scientific problem-solving. By the end, they will confidently use Python’s libraries to solve diverse engineering and scientific challenges. This practical, project-based approach ensures knowledge is both solid and immediately useful in research and professional work.

Osoby które kupowały "Python For Engineering and Scientific Computing. Practical Applications with NumPy, SciPy, Matplotlib, and More", wybierały także:

• Jak zhakowa 125,00 zł, (10,00 zł -92%)
• Windows Media Center. Domowe centrum rozrywki 66,67 zł, (8,00 zł -88%)
• Ruby on Rails. Ćwiczenia 18,75 zł, (3,00 zł -84%)
• Efekt piaskownicy. Jak szefować żeby roboty nie zabrały ci roboty 59,50 zł, (11,90 zł -80%)
• Przywództwo w świecie VUCA. Jak być skutecznym liderem w niepewnym środowisku 58,64 zł, (12,90 zł -78%)

Spis treści

Python For Engineering and Scientific Computing. Practical Applications with NumPy, SciPy, Matplotlib, and More eBook -- spis treści

• 1. Introduction
• 2. Program Structures
• 3. Numerical Calculations Using NumPy
• 4. Function Plots and Animations Using Matplotlib
• 5. Symbolic Computation Using SymPy
• 6. Numerical Computations and Simulations Using SciPy
• 7. 3D Graphics and Animations Using VPython
• 8. Computing with Complex Numbers
• 9. Statistical Computations
• 10. Boolean Algebra
• 11. Interactive Programming Using Tkinter