Python Rgonomics
summary
Recommends swapping pandas for Polars (zero dependencies, Rust backend, native support in Seaborn/Scikit‑learn, column expressions, select helpers, streaming and in‑memory parity with dplyr ergonomics), using Plotnine or Seaborn objects for ggplot‑style plots (Seaborn objects supports multiple x/y facets), replacing notebooks with Quarto for plain‑text reproducible docs, and managing envs with PDM plus pyenv and linters (Ruff, ErrorLens); examples work end‑to‑end.
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chapters (8)
- 0:00Python ergonomics intro
- 1:50Unergonomic Python tools
- 3:15Polars for data wrangling
- 6:31Plotnine and Seaborn objects
- 9:46Quarto and Great Tables
- 12:14Python vs R dev experience
- 15:53VS Code and Positron
- 18:09Conclusion and Q&A
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