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Doing Science with Python

An Introduction to Coding, Anaconda, JupyterLab, and the Scientific Libraries
by Lee Vaughan
October 2022, 472 pp
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Doing Science with Python introduces you to the most popular coding tools for scientific research, such as Anaconda, Spyder, Jupyter Notebooks, and JupyterLab, as well as dozens of important Python libraries for working with data, including NumPy, matplotlib, and pandas. No prior programming experience is required.

You’ll set up a professional programming environment, receive a crash course on programming with Python, and tour the many tools and libraries available for working with data, creating visualizations, simulating natural events, and more. In the book’s applied projects, you’ll use these tools to write programs that perform tasks like simulating globular star clusters, building ships for a wargame simulator, creating an interactive science slideshow, and classifying animal species.

You’ll learn:

  • The best way to set up your computer for science and engineering work with Python
  • The basics of Python programming, including the language’s syntax and best practices
  • The purpose of dozens of Python’s most popular scientific libraries, with deep dives into NumPy, matplotlib, seaborn, pandas, and scikit-learn
  • How to choose the best plotting library for your needs

Even established scientists sometimes struggle to implement Python at work, partly because so many choices are available. This book guides you through the ecosystem of Python’s libraries and tools, so you can find the ones best suited to your needs. Regardless of your field of study, Doing Science with Python is an indispensable owner’s manual for setting up and using your computer for science.

Author Bio 

Lee Vaughan is a programmer, pop culture enthusiast, educator, and author of Impractical Python Projects and Real-World Python (No Starch Press). As a former executive-level scientist at ExxonMobil, he spent decades constructing and reviewing complex computer models, developed and tested software, and trained geoscientists and engineers.

Table of contents 

Part 1: Setting up for Science
Chapter 1: Installing Anaconda and Launching Navigator
Chapter 2: Keeping Organized with Conda Environments
Chapter 3: Simple Scripting in Jupyter Qt Console
Chapter 4: Serious Scripting with Spyder
Chapter 5: Jupyter Notebook: An Interactive Journal for Computational Research
Chapter 6: JupyterLab: Your Center for Science
Part 2: Python Primer
Chapter 7: Integers, Floats, and Strings
Chapter 8: Variables
Chapter 9: The Container Data Types
Chapter 10: Flow Control
Chapter 11: Functions and Modules
Chapter 12: Files and Folders
Chapter 13: Object Oriented Programming
Chapter 14: Documenting your Work

Part 3: The Scientific and Visualization Libraries
Chapter 15: The Scientific Libraries
Chapter 16: The InfoVis and SciVis Visualization Libraries
Chapter 17: The GeoVis Libraries
Part 4: The Essential Libraries
Chapter 18: Numpy: Numerical Python
Chapter 19: Demystifying Matplotlib
Chapter 20: Pandas, Seaborn, and Scikit-learn
Chapter 21: Managing Dates and Times with Python and Pandas
Appendix A: Answers to the "Test your Knowledge" Challenges

The chapters in red are included in the Early Access PDF.