A 7-module Python refresher targeted at applied economist / data science interviews in tech. The goal: walk into a 30-minute Python coding portion and write any of the canonical analytical queries without thinking about syntax. Stack: pandas + statsmodels.
git clone https://github.com/fhoces/python-for-r-users cd python-for-r-users Rscript data/build_csvs.R # build the synthetic CSVs (requires R) python module-01/exercise.py
| # | Module | Status |
|---|---|---|
| 1 | Python for R Users — the cheat sheet | ✓ done |
| 2 | pandas basics — the dplyr → pandas translation | ✓ done |
| 3 | Joins, merges, group-by recipes — from one-liners to real analysis | ✓ done |
| 4 | Regression and A/B tests with statsmodels — the module where Python feels comfortable for an econometrician | ✓ done |
| 5 | End-to-end interview scenario — putting it all together | ✓ done |
| 6 | Reading and Reviewing Someone Else's Python — a real package, read leaves-first | ✓ done |
| 7 | Loading, Running SQL and Checking a Reproduction — the Python around one SQL file in a real replication, with a grader, an audio lesson and a walking quiz (quiz link) | ✓ done |
The BSZ code in this course — where the Python of one
reproduction (opa-prop40, bsz-analysis/py/)
appears across modules 1 to 5 and 7, module by module and file by file.