Python For Engineering and Scientific Computing : Practical Applications with NumPy, SciPy, Matplotlib, and More
Explore a comprehensive guide focused on Python programming for engineering and scientific computing. Learn essential modules and apply them through projects to solve real-world problems. Key Features: Comprehensive coverage of Python libraries essential for engineering and scientific tasks; Integra...
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| Auteur principal: | |
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| Format: | Livre numérique |
| Langue: | Anglais |
| Publié: |
Birmingham :
Packt Publishing
2025.
Paris : Cyberlibris |
| Accès en ligne: | Accès Université d'Orléans et IFPM |
| Note: |
Couverture. https://static2.cyberlibris.com/books_upload/300pix/9781806106042.jpg Cyberlibris (ScholarVox) corpus Informatique |
| Autres localisations: | Voir dans le Sudoc |
| Edition sous un autre format: | • Python For Engineering and Scientific Computing, Practical Applications with NumPy, SciPy, Matplotlib, and More, Veit Steinkamp, Birmingham, Packt Publishing, 2025, 1 vol. (515 p.), 978-18-0610-605-9 |
| Résumé: | Explore a comprehensive guide focused on Python programming for engineering and scientific computing. Learn essential modules and apply them through projects to solve real-world problems. Key Features: Comprehensive coverage of Python libraries essential for engineering and scientific tasks; Integration of practical projects to reinforce learning and application of concepts; Step-by-step guidance from basic programming to advanced simulations and interactive applications. Book Description: 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. What you will learn: Understand Python syntax and program structures for engineering tasks; Apply numerical methods using NumPy for scientific computing needs; Create data visualizations with Matplotlib for clear analysis; Perform symbolic mathematics using SymPy for complex equations; Develop interactive applications with Tkinter for user interfaces; Simulate physical systems and animations using VPython tools. Who this book is for: Ideal for engineers, scientists, and students with basic programming knowledge looking to apply Python in technical fields. A foundational understanding of programming concepts and mathematics is recommended to fully benefit from the practical computational and visualization techniques covered |
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| Description: | Couverture. https://static2.cyberlibris.com/books_upload/300pix/9781806106042.jpg Cyberlibris (ScholarVox) corpus Informatique |
| ISBN: | 9781806106042 |
| Accès: | L'accès en ligne est réservé aux établissements ou bibliothèques ayant souscrit l'abonnement. Cyberlibris |