Python for Scientists

Welcome to the website for the Python for Scientists textbook! This website has materials for students and instructors alike. This textbook is still in pre-production, and not all resources may be available yet.

Downloads

If you are looking to download the textbook, click here. This link will take you to the releases page for the Python for Scientists textbook, where you can download the latest version of the textbook as a PDF file for free. You can also click on the Download PDF Now button below to immediately download the latest version of the Python for Scientists textbook.
Hint: Open up the Assets dropdown on the releases page to find the PDF.

The current version of the textbook is 0.1.9040 (beta-9040).

Releases Download PDF Now

Careful! If your instructor gave you a custom version of the textbook, you should use that version instead. It might have changes to material or exercises that your instructor made.

Supplemental Materials

Find supplemental materials for the Python for Scientists textbook by clicking on the buttons below.

Data Files Scraping Pages POGIL Activites Instructor Resources

Contribute

If you would like to contribute to Python for Scientists, please visit the GitHub repository. We welcome proposed changes using GitHub issues. If you don't know how to make a GitHub issue, you can also send us an email at pythonforscientists@protonmail.com.

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About Python for Scientists

Python for Scientists is an open-source Python textbook designed for introductory courses in computer science or scientific computing. As opposed to other textbooks, which only cover the fundamentals of coding itself, Python for Scientists also provides students with good programming and development skills. Written for students at Kenyon College, it should also serve students at similar, small liberal arts institutions with its emphasis in Python as a tool in scientific computing.

This book includes:

  • Fundamentals of programming
  • Good coding practices
  • Python in scientific computing using Jupyter Notebooks
  • Data manipulation with Pandas and plotting with Matplotlib
  • Basic statistical tests with statsmodels
  • Web scraping tables with Beautiful Soup 4