European Energy Poverty
The housing-meets-energy affordability crisis in one clean Parquet: the share of people who can't keep their home adequately warm and the share behind on utility bills - each split by the whole population versus those at risk of poverty, so you see the poverty gradient, not just the average. Eurostat EU-SILC (ilc_mdes01/07), annual, per country. Energy poverty is one of the most-watched social-policy indicators of the decade, and a direct affordability-and-ESG signal for residential property portfolios - cold homes and utility arrears are where housing stress shows up first. The clean cross-country panel for ESG, real-estate, policy, utility and social-research analysis; joins the housing-conditions, rents and energy-price products on country code.
- Source
- Eurostat
- Licence
- Redistributable open data
- Updates
- Annual
- Data through
- 2025-01-01
- 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
- 4 series - cannot-keep-warm + utility-arrears, each for total vs at-risk-of-poverty population
- Annual, per European country; the housing×energy affordability crossover
- Poverty-gradient split (total vs poor) makes the social impact legible, not just an average
- country × year × series; joins european-housing-conditions, european-energy-prices
- Source: Eurostat EU-SILC (CC-BY-4.0, Decision 2011/833/EU) - aggregate, no personal data
Schema
| Column | Type | Description | Filled | Distinct |
|---|---|---|---|---|
| zone | str | Geo / country code (DE, FR, PL, …) | 100.0% | 37 |
| ts | timestamp (UTC) | Year | 100.0% | 21 |
| indicator | str | Keep-warm or utility-arrears, total or at-risk-of-poverty | 100.0% | 4 |
| value | float | % of the relevant population | 100.0% | 535 |
| unit | str | Unit | 100.0% | 2 |
| res_min | int | Native resolution (annual) | 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: Eurostat (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-energy-poverty_sample.parquet") df.info() # typed columns, gap-aware, ready to join⬇ Download free Parquet sample or CSV for Excel
Coverage: 37 zones
AL · AT · BE · BG · CH · CY · CZ · DE · DK · EE · EL · ES · FI · FR · HR · HU · IE · IS · IT · LT · LU · LV · ME · MK · MT · NL · NO · PL · PT · RO · RS · SE · SI · SK · TR · UK · XK
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