Python Tools for Scientists An Introduction to Using Anaconda, JupyterLab, and Python's Scientific Libraries

An introduction to the Python programming language and its most popular tools for scientists, engineers, students, and anyone who wants to use Python for research, simulations, and collaboration.

Python Tools for Scientists will introduce you to Python tools you can use in your scientific research, including Anaconda, Spyder, Jupyter Notebooks, JupyterLab, and numerous Python libraries. You’ll learn to use Python for tasks such as creating visualizations, representing geospatial information, simulating natural events, and manipulating numerical data.

Once you’ve built an optimal programming environment with Anaconda, you’ll learn how to organize your projects and use interpreters, text editors, notebooks, and development environments to work with your code. Following the book’s fast-paced Python primer, you’ll tour a range of scientific tools and libraries like scikit-learn and seaborn that you can use to manipulate and visualize your data, or analyze it with machine learning algorithms.

You’ll also learn how to:

• Create isolated projects in virtual environments, build interactive notebooks, test code in the Qt console, and use Spyder’s interactive development features
• Use Python’s built-in data types, write custom functions and classes, and document your code
• Represent data with the essential NumPy, Matplotlib, and pandas libraries
• Use Python plotting libraries like Plotly, HoloViews, and Datashader to handle large datasets and create 3D visualizations

Regardless of your scientific field, Python Tools for Scientists will show you how to choose the best tools to meet your research and computational analysis needs.

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.

Introduction
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 and Floats and Strings, Oh My!
Chapter 8: A Variable by any Other Name
Chapter 9: Here we go A-tupleing: the Container Data Types
Chapter 10: Going with the Flow Control
Chapter 11: Fun with Functions and Modules
Chapter 12: Finding Your own Path: Working with Files and Folders
Chapter 13: The Entire Jungle: Object-Oriented Programming
Chapter 14: What I Meant to Say: 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 LIBR ARIES
Chapter 18: Numpy: Numerical Python
Chapter 19: Demystifying Matplotlib
Chapter 20: A Closer Look at Pandas
Chapter 21: Managing Dates and Times with Python and Pandas
Appendix A: Chapter 7-20 Test Question Answers