Python Resources

MUSA 550 assumes some general familiarity with programming concepts, but there aren’t any formal Python prerequisites for MUSA 550. For students interested in learning more about core Python concepts, there are a number of online resources available.

Intro to Python

The following tutorials assume no background in Python and provide a fairly comprehensive introduction to Python and its core concepts.

• Practical Python Programming by David Beazley
• Python 3 Introductory Course by SoloLearn (works in the browser)
• Scientific Python Basics from the Berkeley Institute for Data Science (notebook version)
• Python for Social Science (in particular, the first four chapters)

More Advanced Resources

The The Python Data Science Handbook by Jake VanderPlas is a free, online textbook covering the Python basics needed for this course. It is a bit more advanced than the resources in the previous section and assumes some familiarity with Python.

In particular, the first four chapters are excellent:

• Chapter 1: IPython/Jupyter
• Chapter 2: Numpy
• Chapter 3: Pandas
• Chapter 4: matplotlib

The data analysis library pandas and the visualization library matplotlib will be covered extensively in this course, but the above chapters provide additional background material on this foundational Python tools.

Note: You can click on the “Open in Colab” button for each chapter and run the examples interactively in a cloud computing environment directly in the browser (using Google Colab).

Additional Resources

• The Berkeley Institute for Data Science has compiled a number of Python resources
• The subreddit r/learnpython is a good place for Python resources — it maintains a comprehensive wiki of resources and tutorials.