Learning scientific programming with Python

Christian Hill

ISBN 10: 1108745911 / ISBN 13: 9781108745918

Published by Cambridge University Press New York, 2020

About this Item

English Learning Scientific Programming with Python. Second Edition. 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. CONTENTS Acknowledgments Code Listings 1. Introduction 1.1 About This Book 1.2 About Python 1.3 Installing Python 1.4 The Command Line 2. The Core Python Language I 2.1 The Python Shell 2.2 Numbers, Variables, Comparisons and Logic 2.3 Python Objects I: Strings 2.4 Python Objects II: Lists, Tuples and Loops 2.5 Control Flow 2.6 File Input/Output 2.7 Functions 3. Interlude: Simple Plots and Charts 3.1 Basic Plotting 3.2 Labels, Legends and Customization 3.3 More Advanced Plotting 4. The Core Python Language II 4.1 Errors and Exceptions 4.2 Python Objects III: Dictionaries and Sets 4.3 Pythonic Idioms: ?Syntactic Sugar? 4.4 Operating-System Services 4.5 Modules and Packages 4.6 An Introduction to Object-Oriented Programming 5. IPython and Jupyter Notebook 5.1 IPython 5.2 Jupyter Notebook 6. NumPy 6.1 Basic Array Methods 6.2 Reading and Writing an Array to a File 6.3 Statistical Methods 6.4 Polynomials 6.5 Linear Algebra 6.6 Random Sampling 6.7 Discrete Fourier Transforms 7. Matplotlib 7.1 Line Plots and Scatter Plots 7.2 Plot Customization and Refinement 7.3 Bar Charts, Pie Charts and Polar Plots 7.4 Annotating Plots 7.5 Contour Plots and Heatmaps 7.6 Three-Dimensional Plots 7.7 Animation 8. SciPy 8.1 Physical Constants and Special Functions 8.2 Integration and Ordinary Differential Equations 8.3 Interpolation 8.4 Optimization, Data-Fitting and Root-Finding 9. Data Analysis with pandas 9.1 Introduction to pandas 9.2 Reading and Writing series and DataFrames 9.3 More Advanced Indexing 9.4 Data Cleaning and Exploration 9.5 Data Grouping and Aggregation 9.6 Examples 10. General Scientific Programming 10.1 Floating-Point Arithmetic 10.2 Stability and Conditioning 10.3 Programming Techniques and Software Development Appendix A Solutions Appendix B Differences Between Python Versions 2 and 3 Appendix C SciPy?s odeint Ordinary Differential Equation Solver Glossary Index.

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Bibliographic Details

• Title: Learning scientific programming with Python
• Publisher: Cambridge University Press New York
• Publication Date: 2020
• Language: English
• ISBN 10: 1108745911
• ISBN 13: 9781108745918
• Binding: Paperback
• Edition: 2.
• Condition: Very Good
• Seller catalogs:
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About this title

Synopsis

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.

About the Author

Christian Hill is a physicist and physical chemist currently working at the International Atomic Energy Agency. He has over 25 years' experience of programming in the physical sciences and has been programming in Python for 15 years. His research uses Python to produce, analyze, process, curate and visualize large data sets in the area of spectroscopy and plasma physics and material science.