Introduction to Python for Science and Engineering
Series: Series in Computational Biophysics;
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Product details:
- Edition number 2
- Publisher CRC Press
- Date of Publication 23 September 2024
- ISBN 9781032673905
- Binding Paperback
- No. of pages444 pages
- Size 234x156 mm
- Weight 820 g
- Language English
- Illustrations 24 Illustrations, black & white; 78 Illustrations, color; 10 Halftones, black & white; 10 Halftones, color; 14 Line drawings, black & white; 68 Line drawings, color; 14 Tables, black & white 631
Categories
Short description:
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.
MoreLong description:
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.
MoreTable of Contents:
1. Introduction
2. Launching Python
3. Integrated Development Environments
4. Strings, Lists, Arrays, and Dictionaries
5. Input and Output
6. Conditionals and Loops
7. Functions
8. Plotting
9. Numerical Routines: SciPy and NumPy
10. Python Classes: Encapsulation
11. Data Manipulation and Analysis: Pandas
12. Animation
13. Speeding up numerical calculations
Appendix A Maintaining your installation Python
Appendix B Glossary
Appendix C Python Resources
Index Index
More
