Data science notes and scratch notebooks — NumPy vectorization patterns, Jupyter/Polynote workflow tips, and Python language notes I wanted to keep a copy of.
This is a working notebook, not a package. Everything here is meant to be read and run in place.
| Notebook | What's in it |
|---|---|
Vectorization Example.ipynb |
Side-by-side loops vs. NumPy vectorization, with timing comparisons |
Convert Jupyter Notebook to Pdf.ipynb |
Notebook → PDF for sharing/publishing |
Polynote Usage Instructions.ipynb |
Setting up and using Polynote for mixed Python/R notebooks |
Polynote Example.ipynb |
Worked Polynote example |
Walrus Operator Example.ipynb |
Notes on the walrus operator (:=) and where it actually helps |
Requires Jupyter and the usual data-science stack:
pip install jupyter numpy pandas matplotlib
jupyter labMIT