Python Programming and Visualization for Scientists  (2nd Ed.)

Python Programming and Visualization for Scientists (2nd Ed.)

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Expanded and Improved New Edition:

  • With Python 3
  • New chapters on Pandas, Cartopy, and more.
  • Appendices for Jupyter and LaTeX markup.
  • Color syntax highlighting for all code samples. 
  • Color figures throughout

Instructors:  Request an evaluation copy here

View an excerpt, including table of contents and the first two chapters HERE 

DESCRIPTION

Python continues to gain dominance as a language of choice for analyzing and visualizing scientific data.  Although it has concise, intuitive syntax, learning how to plot and visualize data requires scouring the internet for documentation and examples.  This book was written from the perspective of “What book would the authors want to have had when they were transitioning to Python?”

A second edition of the book was made necessary by the transition to Python 3, which did not maintain full backward compatibility with earlier versions of the language.  The second edition has been completely revised to ensure that all code examples work in Python 3.  Additional chapters on the Pandas library and Cartopy have been included, as well as an appendix on Jupyter notebooks, which have become an important tool for developing and communicating code in both the research and educational settings.


The first edition of the book has proven useful not only as a classroom text but also as a guide and reference for students, educators, and researchers who already have programming experience and want to start creating plots and analyzing data using Python.  The second edition will serve the same role.  It is not meant for the person who is completely new to programming, nor is it an introductory computer science textbook. The authors' assumptions are that the reader has some experience programming with a language other than Python.

Although the new Python programmer may wish to read the book cover to cover, the book is organized such that an experienced programmer can readily jump to the appropriate chapter.  An extensive index aids in searching for functions and methods useful for data visualization and analysis.
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Topics Covered

I. Basic Python programming

  • Getting started
  • Syntax and data types
  • Strings
  • Mathematical operators and functions
  • Structure and control
  • File I/O
  • Numpy arrays
  • Functions and modules
  • Defining classes and methods

II. Plotting and visualization with Matplotlib

  • 1-D plotting
  • Multi-panel plots
  • 2-D plotting
  • Cartopy for plotting maps
  • 3-D plotting

III. Additional topics

  • Dates and times
  • Pandas
  • Reading scientific data sets
  • Regular expressions
  • Linear algebra
  • Fourier analysis

IV. Miscellany

  • Interpolation and resampling
  • Linear regression
  • Numerical differentiation and integration
  • Smoothing of data
  • Saving and loading arbitrary Python objects
  • Physical constants
  • Physical dimensions and units
  • Special mathematical functions
  • Speed and optimization of code

Appendices

  • Jupyter notebooks - a primer
  • LaTeX quick reference

The book includes numerous figures (many in color), tables, and executable example programs.

Alex DeCaria is a professor of meteorology at Millersville University, where among other courses he teaches a class in Python programming and visualization for undergraduate meteorology and ocean sciences majors. He is coauthor of A First Course in Atmospheric Numerical Modeling, also published by Sundog Publishing.

Grant Petty is a professor of atmospheric science at the University of Wisconsin-Madison, where he teaches courses in atmospheric physics, meteorological measurements, and satellite meteorology.  Data analysis using Python plays a central role in many lab exercises in his courses as well as in his research.  He is also the author of A First Course in Atmospheric Radiation and A First Course in Atmospheric Thermodynamics.

Resources

1. Errata

This document lists all known errors that have been found in earlier printings and editions of this book.  They are corrected in later printings.

2. Sample data files and Jupyter notebooks

Selected code samples from the book are provided as Jupyter notebooks, along with required sample data sets in this GitHub repository.  See the README information at the bottom of the repository listing for download instructions.

Book Details

Author: Alex J. DeCaria and Grant W. Petty

Pages: 346
Publisher: Sundog Publishing LLC
Publication Date: 2021
ISBN-13: 978-09729033-5-6
Binding: perfect paperback 8.25 x 11"
Figures:  90