Practice notebooks on African migration — 33 Google Colab notebooks, one per data-science/DH technique, with open UN DESA, UNHCR and World Bank datasets.
# African Migration Practice Pack
Practice notebooks on **African migration**, one per data-science and Digital
Humanities technique. Built from open sources: UN DESA, UNHCR, the World Bank
and ISO-3166. Companion to the housing-and-migration pack, same method arc,
different domain.
## Using them
Each notebook is self-contained — open any one without having run the others.
**In Google Colab:** click the badge at the top of a notebook, then run the
first cell. It will ask you to upload the CSVs; pick them from this pack's
`data/` folder. The upload is remembered for the rest of the session.
**Locally:** put the notebook in the same folder as the CSVs and run it.
Needs `pandas`, `numpy`, `matplotlib`, `scipy`, `scikit-learn`, `statsmodels`.
**Inside CourseHub:** every notebook is also the 📓 Lab Notebook tab on its
lesson, next to the quiz. Nothing to install and no upload step.
## Data
Bilateral migration between African countries of origin and every destination
in the world, 1990-2020, with a country-year context panel and forced-displacement
counts. All figures are national aggregates; nothing here is individual-level.
See `data/PROVENANCE.md` for sources, retrieval date and every transformation.
| File | What it is |
|---|---|
| `migration_corridors.csv` | UN DESA bilateral migrant stock, African origins x world destinations (17,368 rows) |
| `country_indicators.csv` | World Bank panel: net migration, population, urbanisation, GDP per capita, unemployment (1,836 rows) |
| `displacement.csv` | UNHCR refugees, asylum seekers and IDPs by origin and country of asylum (1,157 rows) |
| `country_meta.csv` | ISO-3166 codes with UN M49 and region labels, the join key throughout (249 rows) |
## The notebooks
| # | Notebook | Technique |
|---|---|---|
| | **Module 00 — Introduction to African Migration Data** | |
| `00` | A First Look at African Migration Data | Loading and inspecting a bilateral migration table with pandas |
| | **Module 01 — Framing the Right Que …