Learning Scientific Programming with Python
eBook - PDF

Learning Scientific Programming with Python

  1. English
  2. PDF
  3. Available on iOS & Android
eBook - PDF

Learning Scientific Programming with Python

About this book

Learn to master basic programming tasks from scratch with real-life, scientifically relevant examples and solutions drawn from both science and engineering. Students and researchers at all levels are increasingly turning to the powerful Python programming language as an alternative to commercial packages and this fast-paced introduction moves from the basics to advanced concepts in one complete volume, enabling readers to gain proficiency quickly. Beginning with general programming concepts such as loops and functions within the core Python 3 language, and moving on to the NumPy, SciPy and Matplotlib libraries for numerical programming and data visualization, this textbook also discusses the use of Jupyter Notebooks to build rich-media, shareable documents for scientific analysis. The second edition features a new chapter on data analysis with the pandas library and comprehensive updates, and new exercises and examples. A final chapter introduces more advanced topics such as floating-point precision and algorithm stability, and extensive online resources support further study. This textbook represents a targeted package for students requiring a solid foundation in Python programming.

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Yes, you can access Learning Scientific Programming with Python by Christian Hill in PDF and/or ePUB format, as well as other popular books in Physical Sciences & Mathematical & Computational Physics. We have over one million books available in our catalogue for you to explore.

Table of contents

  1. Cover
  2. Half-title
  3. Title page
  4. Copyright information
  5. Contents
  6. Acknowledgments
  7. Code Listings
  8. 1 Introduction
  9. 2 The Core Python Language I
  10. 3 Interlude: Simple Plots and Charts
  11. 4 The Core Python Language II
  12. 5 IPython and Jupyter Notebook
  13. 6 NumPy
  14. 7 Matplotlib
  15. 8 SciPy
  16. 9 Data Analysis with pandas
  17. 10 General Scientific Programming
  18. Appendix A Solutions
  19. Appendix B Differences Between Python Versions 2 and 3
  20. Appendix C SciPy's odeint Ordinary Differential Equation Solver
  21. Glossary
  22. Index