Housing / energy / sustainability analytics (Netherlands)
Data Engineering · Geospatial · Sustainability
Dutch Housing & Energy Intelligence
A decision-support platform on real Dutch open data (CBS): average dwelling energy use (gas, electricity, district heating) across all 342 municipalities, compared to the national baseline, with an indicative retrofit scenario lab. It runs live on this page.
Data ingestion pipeline, analytics, product engineering
Python (ingestion) · CBS OData · TypeScript · React
What you can try
Energy characteristics of housing vary sharply across the Netherlands. Dense cities lean on district heating, others on gas. Turning that into a comparable, explorable view needs real data, cleanly ingested.
The goal was a reproducible platform on real Dutch open data that compares municipalities' dwelling energy use against the national baseline and models, indicatively, how a retrofit-driven gas reduction would move CO₂.
Architecture
Source: CBS open data
Energy use of private dwellings by region, 2024 (table 86159NED)
Reproducible ingestion (Python)
Fetch curated municipalities, transform, export a JSON artifact
Derived indices
Gas and electricity indexed to the national average
Comparison & ranking
Municipalities against the national baseline
Retrofit scenario
Indicative gas reduction → CO₂ effect (standard factor)
Explorer UI
Municipality profile, ranking, scenario lab
- Reproducible Python ingestion of CBS StatLine table 86159NED (energy use of private dwellings, 2024), standard-library only
- Handles CBS OData constraints (no $skip; large-table query caps) by requesting a curated municipality set by region code
- Transforms to a compact JSON artifact and derives gas/electricity indices versus the national average
- Uses only official CBS figures for energy; CO₂ and retrofit numbers are clearly labeled indicative (standard 1.78 kg/m³ gas factor)
- Interactive explorer: municipality comparison, ranking, and a retrofit scenario lab
- Full data provenance, licensing (CC BY 4.0), and limitations documented
A working platform you can use on this page: pick a municipality to see its real dwelling energy profile versus the national baseline, scan the ranking, and model an indicative retrofit scenario. It shows the path from a real public dataset to an explorable decision tool, honestly separating official figures from indicative modeling.
Have a dataset worth exploring?
Play with the map above, then picture it on your own data. Want to turn it into a decision tool?