There is no textbook. The references below are the working set: tools, tutorials, dataset documentation, and walkthrough scripts.

Slides and scripts (Week 0)

• Slides. Week 0 slide deck (PDF): intro, big question, overview of the three datasets.
• Walkthrough scripts. Five Python scripts that mirror the in-class demos. Each is self-contained and produces figures or tables.
  • 01_demo_basics.py: pandas / numpy basics; first toy dataset.
  • 02_census_explore.py: Census microdata: load, join, demographic indicators.
  • 03_eno_explore.py: ENO: parse semicolon-delimited CSV, clean nationality, rate calculations.
  • 04_grd_explore.py: GRD: load pipe-delimited yearly files, join CIE-10, top diagnoses.
  • assign_comunas.py: how the 21 teams were balanced by comuna population.

Tools and setup

• Python. 3.11 or newer recommended. Anaconda or a fresh venv both work.
• Core libraries. pandas, pyarrow (parquet), numpy, matplotlib, seaborn or plotly, geopandas, statsmodels.
• IDE. Any Jupyter-compatible IDE: Google Colab, JupyterLab, VS Code with the Python + Jupyter extensions, or PyCharm.
• Version control. GitHub (free academic accounts include private repos). One repo per pair.

Tutorials

• pandas (YouTube)
• geopandas (YouTube)
• matplotlib (YouTube)
• Google Colab walkthrough (YouTube, in Spanish; works for JupyterLab and VS Code too)
• Working with folders and files on Windows
• Working from the console

Reference

• R for Data Science (Spanish edition): very good even though the course is in Python.
• WHO ICD-10 browser: lookup for any GRD diagnosis code.
• geopandas documentation
• statsmodels documentation

Dataset documentation

Variable dictionaries, methodology PDFs, and download links live on the Data page. Short summary:

• Census 2024: manual de uso, diccionario de variables, glosas: INE portal.
• ENO: diccionario, metodología: MINSAL DEIS.
• GRD: CIE-10 lookup, master tables: bundled with each yearly download from MINSAL DEIS.