• Class 1: intro to python and pandas

  • Environments, pip, ipython, pandas, "hello world", introduce notebooks, have them read in the csv, and visualize complaints over time

• Class 2: Basics of interactive data analysis

  • data munging: sql, split / apply / combine patterns

• Class 3: intro to statistics

  • central tendencies, variances, plotting correlations, a/b tests & p-values

• Class 4:

  • machine learning in python with scikit-learn

Resources:

• https://learnxinyminutes.com/docs/python3/
• https://tryolabs.com/blog/2017/03/16/pandas-seaborn-a-guide-to-handle-visualize-data-elegantly/
• https://github.com/jvns/pandas-cookbook