European Power Plant Registry
Every conventional power plant in Europe in one clean table: name, operator, country, net capacity, fuel/technology, commissioning year and location - assembled and de-duplicated from Open Power System Data. The asset reference table that joins to generation, capacity and carbon analytics by country and fuel.
- Source
- OPSD
- 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
- Conventional power plants across Europe - one cleaned, de-duplicated table
- Capacity (MW), fuel/technology, commissioning year, lat/lon, operator
- Partitioned by country; joins to the energy catalog by country + fuel
- Source: Open Power System Data (CC-BY-4.0)
Schema
| Column | Type | Description | Filled | Distinct |
|---|---|---|---|---|
| name | str | Plant name | 100.0% | 5,936 |
| company | str | Operator / owner | 75.2% | 1,289 |
| country | str | Country | 100.0% | 18 |
| capacity_mw | float | Net capacity, MW | 100.0% | 1,611 |
| energy_source | str | Primary energy source / fuel | 100.0% | 14 |
| technology | str | Generation technology | 81.5% | 11 |
| commissioned_year | int | Year commissioned | 82.2% | 122 |
| lat | float | Latitude | 45.8% | 1,899 |
| lon | float | Longitude | 45.8% | 1,898 |
| eic_code | str | ENTSO-E EIC code (where available) | 16.6% | 696 |
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: OPSD (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("european-power-plant-registry_sample.parquet") df.info() # typed columns, gap-aware, ready to join⬇ Download free Parquet sample or CSV for Excel
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