This repository contains general course materials, including:

• Course Syllabus
• Package Cheat Sheets
• A Guide to Anaconda, including:
  • Installing Anaconda
  • Managing environments and installing packages
  • Frequently encountered problems
• A environment.yml file specifying the Python packages needed in this course

• Throughout the course, the environment.yml file in this repository will be updated to include all necessary packages.
• The syllabus in this repository will also be updated with links to each week's materials and assignments.

The The Python Data Science Handbook is a free, online textbook covering the Python basics needed in this course. In particular, the first four chapters are excellent:

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

Note that you can click on the "Open in Colab" button for each chapter and run the examples interactively using Google Colab.

There are also a few good resources from the Berkeley Data Science Institute:

• https://bids.github.io/2016-01-14-berkeley/python/00-python-intro.html (notebook version)
• Python for Social Science, a free online book
• Many more resources are listed here: http://python.berkeley.edu/resources/