Tutorial Notebooks

This is a collection of notebooks with tips and consolidated references for the various Python and Pandas topics that we are discussing.

  1. Fun with Numbers
  2. Writing and Using Functions
  3. Selecting Data
  4. Reshaping Data
  5. Building Data — building up arrays and data series
  6. Indexing
  7. Missing Data
  8. Drawing Charts
  9. Chart Finishing Touches
  10. Penguin Inference
  11. One Sample T-test and Distribution Comparision
  12. Correlation
  13. Regressions (goes with Week 8)
  14. Example: Sessionization
  15. Logistic Regression
  16. SciKit-Learn Logistic Regression
  17. SciKit-Learn Pipelines and Regularization — also includes a significance test
  18. Advanced SciKit-Learn pipeline and logistic regression example (on Towards Data Science)
  19. Tricks with Boolean Series
  20. Movie Decomposition
  21. K-Means Example (uses the chi-papers data from Week 13)
  22. Fetching CHI Papers creates the chi-papers.csv file from Internet sources
  23. Tuning Hyperparameters
  24. MovieLens Time Series
  25. Git repo & workflow example