Python for Scientists

Learn Python starting from the very basics all the way to numerical and symbolic math, quantitative analysis, and beyond.

John M. Stewart (Author), Michael Mommert (Author)

9781009014809, Cambridge University Press

Paperback / softback, published 17 August 2023

304 pages
24.3 x 16.9 x 1.6 cm, 0.53 kg

'… this book is still an excellent starting point to put you on the tracks to master the language and enjoy the marvels of the latest version of Python.' Adhemar Bultheel, European Mathematical Society (euro-math-soc.eu)

The third edition of this practical introduction to Python has been thoroughly updated, with all code migrated to Jupyter notebooks. The notebooks are available online with executable versions of all of the book's content (and more). The text starts with a detailed introduction to the basics of the Python language, without assuming any prior knowledge. Building upon each other, the most important Python packages for numerical math (NumPy), symbolic math (SymPy), and plotting (Matplotlib) are introduced, with brand new chapters covering numerical methods (SciPy) and data handling (Pandas). Further new material includes guidelines for writing efficient Python code and publishing code for other users. Simple and concise code examples, revised for compatibility with Python 3, guide the reader and support the learning process throughout the book. Readers from all of the quantitative sciences, whatever their background, will be able to quickly acquire the skills needed for using Python effectively.

1. Introduction
2. About Python
3. Basic Python
4. NumPy – Numerical math
5. SciPy – Numerical methods
6. Matplotlib – Plotting
7. SymPy – Symbolic math
8. Pandas – Data handling
9. Performance Python
10. Software development tools
Index.

Subject Areas: Numerical analysis [PBKS]