All Petrol Station Locations in Denmark: Complete Geographic Dataset
All Petrol Station Locations in Denmark: Complete Geographic Dataset
All Petrol Stations locations in Denmark - complete national dataset
This dataset contains a complete, geocoded collection of Petrol Stations in Denmark, including branded chains and independent locations. It provides a complete national coverage with 2,935 verified locations suitable for territory planning, market sizing and spatial analysis.
Last updated: 8 July 2026.
Dataset fields included in the CSV:
- GUID
- Title
- Latitude
- Longitude
- Street No
- Street
- City
- Kommune
- Region
- Population
- Postal Code
- Address
- Wheelchair
- Popularity Score
- Phone
- Website
- Fuel Type
- Opening hours
Brand distribution
- Circle K – 245 locations in Denmark
- F24 – 137 locations in Denmark
- Go'on – 198 locations in Denmark
- INGO – 196 locations in Denmark
- OIL! tank & go – 71 locations in Denmark
- OK – 792 locations in Denmark
- Q8 – 123 locations in Denmark
- Shell – 217 locations in Denmark
- tankpool24 – 71 locations in Denmark
- Uno-X – 368 locations in Denmark
Petrol Stations distribution by Region
- Region Hovedstaden: 450 petrol stations
- Region Midtjylland: 759 petrol stations
- Region Nordjylland: 409 petrol stations
- Region Sjælland: 505 petrol stations
- Region Syddanmark: 809 petrol stations
Direct access after purchase of the complete locations dataset for Denmark
Download the dataset immediately in a clean, analysis-ready CSV format. Ideal for geospatial analysis, competitor benchmarking, market studies, site planning, and retail location intelligence workflows.
Evaluate the dataset before purchase
A free sample is available for download, allowing you to inspect the structure, fields, and geospatial precision before purchasing the full dataset.
Related geospatial datasets
- Administrative boundaries and full polygon dataset for Denmark: Map these petrol stations locations against highly precise administrative polygons for territory analysis and spatial structuring.
- Demographics dataset for Denmark: Overlay demographic indicators to deeply understand the population structures and household types surrounding these petrol stations locations.
- Explore demographics data insights for Denmark: Methodology, use cases, and definitions explaining how demographic metrics support your location intelligence workflows.
- Income indicators dataset for Denmark (small-area income analysis): Download an analysis-ready dataset on income distribution across small geographic units - ideal for segmentation, customer analytics, location planning, and socio-economic scoring.
- Income distribution and socio-economic patterns in Denmark - expert analysis: A detailed blog post explaining income geography, disparities, and how income-based indicators can support location intelligence and market analytics.
- Explore a rich library of Denmark-specific datasets on our dedicated country page: detailed demographics, wealth indicators, multi-level boundaries, and a broad spectrum of retail POIs. View demographics, retail POI, and administrative boundary datasets for Denmark
Need the data in another format?
We can deliver this dataset in alternative formats upon request (GeoJSON, Shapefile, Excel, PostgreSQL import files, etc.). Contact us at contact@geolocet.com.
Frequently Asked Questions
Q: Can I use this dataset in GIS software?
A: Yes. The dataset is suitable for GIS platforms including QGIS, ArcGIS, GeoPandas, CARTO, and other spatial analysis environments.
Q: Can I combine this dataset with administrative boundaries?
A: Yes. The coordinates can be spatially joined with municipalities, census units, postal areas, and other administrative polygons.
Q: Does the dataset contain duplicate locations?
A: Duplicate detection and validation workflows are applied during processing to improve consistency and reduce redundant records.
Q: What file format is included with the download?
A: The dataset is delivered as a CSV file compatible with Excel, Python, R, QGIS, Power BI, Tableau, PostgreSQL, and most GIS or analytics platforms.
Analyze this data with AI
Use these prompts with ChatGPT, Claude, or Gemini to extract strategic insights from this dataset:
"Analyze this this multi-brand dataset to identify underserved regions in Denmark for potential market expansion.""Create a prioritized shortlist of expansion zones in Denmark based on distance gaps between existing this multi-brand locations.""Using this this multi-brand data, find high-traffic retail corridors in Denmark with low petrol stations density for competitive positioning."