Global POI Density
How many points of interest of each kind exist in each country - the amenity-mix / retail-footprint reference table, aggregated from Overture Maps' global Places layer (~60M+ POIs) without shipping a single raw point. Overture publishes Places as Parquet on public cloud storage; we run a remote pushdown aggregation straight against it and ship the clean result: one row per (country x Overture primary category) with the POI count and that category's share of the country's total POIs. Hundreds of categories - restaurants, cafes, clinics, schools, hotels, supermarkets, banks, gyms, offices, places of worship - across ~230 countries. Keyed by ISO-2 country + category so it joins any country reference table. Aggregate counts only - no place names, no coordinates, no personal data. CDLA-Permissive-2.0.
- Source
- POIDENSITY
- Licence
- Redistributable open data
- Quality
- QC clean · 0 failures
- Format
- Apache Parquet + dictionary
Safe to train on
Built only from a named, redistributable official source under a documented open licence - not scraped web data. No copyright grey zone, no personal data. Ships machine-readable Croissant metadata (ML Commons - loads in Hugging Face / Kaggle / Google), an AI training-licence manifest documenting source, licence and provenance for your model's data governance, and a machine-readable data dictionary (drop it into an agent / RAG prompt so the model knows every column) - all inspectable before you buy.
What's included
- POI counts by category x country - amenity mix / retail-footprint reference for ~230 countries
- Hundreds of Overture primary categories (restaurant, cafe, clinic, school, hotel, bank, gym, …)
- Each category's share of its country's total POIs (composition %) computed in
- Aggregated from Overture's ~60M+ global Places layer - no raw points shipped, no PII
- Keyed by ISO-2 country + category; joins any country-keyed dataset
- CDLA-Permissive-2.0 - commercial reuse & redistribution permitted
- Source: (c) Overture Maps Foundation - Places (CDLA-Permissive-2.0)
Schema
| Column | Type | Description | Filled | Distinct |
|---|---|---|---|---|
| country | str | Country ISO 3166-1 alpha-2 code (from the POI's address; join key) | 100.0% | 258 |
| category | str | Overture primary category (e.g. restaurant, cafe, school, hotel) | 100.0% | 2,081 |
| poi_count | int | Number of POIs of this category in this country | 100.0% | 6,324 |
| country_total | int | Total POIs (all categories) in this country | 100.0% | 253 |
| pct_of_country | float | This category's share of the country's total POIs (%) | 100.0% | 10,823 |
| release | str | Overture Maps data release the counts were aggregated from | 100.0% | 1 |
Sample & preview
Every purchase ships as Apache Parquet with a data dictionary and the full QC report. A free sample (first rows + schema) is downloadable here - confirm fit before you buy. Source: POIDENSITY (redistributable open data; attribution passes through - see our Licence).
Don't trust screenshots - drop the sample into your notebook right now.
import pandas as pd df = pd.read_parquet("global-poi-density_sample.parquet") df.info() # typed columns, gap-aware, ready to join⬇ Download free Parquet sample or CSV for Excel
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