Python Tools for Scientists

Python Tools for Scientists
官网链接:No Starch Press


Python Tools for Scientists 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, Python Tools for Scientists 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.


Python for Geospatial Data Analysis

2022-10-24 18:45:24


Ansible for DevOps, 2nd Edition

2022-10-24 19:04:28