- Course Logistics
- Using Jupyter Notebooks
- Introduction to Pandas
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- From Zero to Python
- Conda user guide
- Jupyter notebook documentation:
- Recommended tutorial for students with little Python background: Practical Python Programming
A number of resources are listed on the course website.
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/
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.
Particularly for the Data Science Handbook, there is too much to get through in one week, but the book should serve as your first reference on pandas, numpy, and matplotlib throughout the course.
