| --- |
| license: cc-by-4.0 |
| language: |
| - en |
| - es |
| pretty_name: "ds4bolivia — Bolivian municipalities: SDGs, satellite embeddings & nighttime lights" |
| tags: |
| - bolivia |
| - sdg |
| - sustainable-development |
| - satellite-embeddings |
| - nighttime-lights |
| - remote-sensing |
| - geospatial |
| size_categories: |
| - n<1K |
| --- |
| |
| # Bolivian Municipalities — SDGs, Satellite Embeddings & Nighttime Lights |
|
|
| Socioeconomic, satellite, and geographic measures for Bolivia's **339 municipalities** |
| across its **9 departments** — the analysis data for the project *"Predicting the |
| Sustainable Development of Bolivian Municipalities with Satellite Embeddings and Machine |
| Learning"* (Carlos Mendez, Nagoya University). |
|
|
| This dataset is a public **mirror** of the `data/` folder in |
| [`cmg777/project2026e`](https://github.com/cmg777/project2026e). Every file is keyed on |
| `asdf_id` (integer, `0`–`338`), the universal join key across all datasets. To attach |
| municipality/department labels, merge any file to `regionNames/regionNames.csv` on `asdf_id`. |
|
|
| ## Contents |
|
|
| | Path | Description | |
| | ---- | ----------- | |
| | `ds4bolivia_v20250523.csv` | Analysis-ready **merged master** (339 × 351) — all subfolders joined on `asdf_id`. | |
| | `definitions_ds4bolivia_v20250523.csv` | **Data dictionary** for the master file (`varname` → `varlabel`). | |
| | `regionNames/` | Administrative IDs & names — the join foundation. | |
| | `sdg/` | IMDS + 14 composite SDG indices (0–100 scale). | |
| | `sdgVariables/` | 64 individual SDG indicators across all 17 goals. | |
| | `satelliteEmbeddings/` | 64-dim Google Satellite Embeddings — simple-mean (2017) and population-weighted (**2017–2025** panel). | |
| | `nighttimeLights/` | VIIRS nighttime lights (simple-average & population-weighted, **2017–2021**), plus `rasters/` GeoTIFF. | |
| | `predictions/` | Out-of-sample predictions for SDG 1, 7 and 13 (four-view: actual, lights, embeddings, combined) plus space-time forward projections. | |
| | `maps/` | Municipality boundary polygons (GeoJSON), keyed by `asdf_id`. | |
| | `sdg/`, `regionNames/`, … | Each subfolder ships its own `README.md` with a full variable dictionary. | |
|
|
| ## Provenance & coverage |
|
|
| - **Spatial unit:** 339 Bolivian municipalities (9 departments); **version** `v20250523`. |
| - **Source:** [`quarcs-lab/ds4bolivia`](https://github.com/quarcs-lab/ds4bolivia); the 64-dim |
| satellite embeddings are Google Satellite Embeddings (Google Earth Engine); SDG indices and |
| the IMDS index follow Andersen et al. (2020). |
| - **Time coverage:** population 2001–2020; nighttime lights 2012–2021; most SDG variables 2012–2019; |
| satellite embeddings 2017 (simple-mean) and 2017–2025 (population-weighted panel). |
|
|
| ## Load from Python |
|
|
| Load any file straight from the Hub (no full clone needed): |
|
|
| ```python |
| import pandas as pd |
| from huggingface_hub import hf_hub_download |
| |
| path = hf_hub_download( |
| repo_id="cmg777/project2026e", |
| repo_type="dataset", |
| filename="satelliteEmbeddings/bolivia_pop_weighted_2017.csv", |
| ) |
| df = pd.read_csv(path) |
| ``` |
|
|
| The companion repo ships a `code/hf_data.py` helper with a `data_path()` function that |
| prefers a local copy and otherwise streams the file from this dataset. |
|
|
