Python: programming for scientists

This lecture is to a large part based on the lecture by Thomas Robitaille. Additions to the original lecture were made by Markus Demleitner, Robert Schmidt, and myself. Below you can find the text and the IPython notebooks that are used for this lecture.

Day 1:

• 00. About the course [notebook]
• 01. What is Python [notebook]
• 02. How to run Python code [notebook]
• 03. Using the IPython notebook [notebook]
• 04. Numbers, Strings, and Lists [notebook]
• 05. Booleans, Tuples, Sets, and Dictionaries [notebook]
• 06. Control Flow [notebook]
• 06.B Comments [notebook]
• Practice Problem - Cryptography [notebook]
• Day 1 exercise solutions

• 07. Functions [notebook]
• 08. Reading and writing files [notebook]
• 09. Modules and Variable Scope [notebook]
• Practice Problem - Temperatures [notebook]
• Problem Set 1 [notebook]
• Day 2 exercise solutions

• 10. Introduction to Numpy [notebook]
• 11. Introduction to Matplotlib [notebook]
• 12. Files and paths [notebook]
• 13. String Formatting [notebook]
• Practice Problem - Monte-Carlo Error Propagation [notebook]
• Problem Set 2 [notebook]
• Day 3 exercise solutions

• 14. Python variables - behind the scenes [notebook]
• 15. Fitting models to data [notebook]
• 16. Interpolation and Integration [notebook]
• 17. Object-oriented programming [notebook]
• Practice Problem - Radioactive Decay [notebook]
• Problem Set 3 [notebook]
• Day 4 exercise solutions

• 18. Understanding Python errors [notebook]
• 19. Accessing remote resources [notebook]
• 20. Python insights during the course [notebook]
• Day 5 exercise solutions