All Petrol Station Locations in Norway: Complete Geographic Dataset
All Petrol Station Locations in Norway: Complete Geographic Dataset
All Petrol Stations locations in Norway - complete national dataset
This dataset contains a complete, geocoded collection of Petrol Stations in Norway, including branded chains and independent locations. It provides a complete national coverage with 2,697 verified locations suitable for territory planning, market sizing and spatial analysis.
Last updated: 7 July 2026.
Dataset fields included in the CSV:
- GUID
- Title
- Latitude
- Longitude
- Street No
- Street
- Town
- Admin_level_1
- Admin_level_2
- Municipality
- Region
- Population
- Postal Code
- Address
- Wheelchair
- Popularity Score
- Phone
- Website
- Fuel Type
- Opening hours
Brand distribution
- Bunker Oil – 79 locations in Norway
- Circle K – 489 locations in Norway
- Esso – 330 locations in Norway
- Shell – 47 locations in Norway
- St1 – 239 locations in Norway
Petrol Stations distribution by Region
- Innlandet: 285 petrol stations
- Nord-Norge: 398 petrol stations
- Trøndelag: 299 petrol stations
- Vestlandet: 740 petrol stations
- Agder Og Sør-Østlandet: 454 petrol stations
- Oslo Og Viken: 521 petrol stations
Direct access after purchase of the complete locations dataset for Norway
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 Norway: Map these petrol stations locations against highly precise administrative polygons for territory analysis and spatial structuring.
- Demographics dataset for Norway: Overlay demographic indicators to deeply understand the population structures and household types surrounding these petrol stations locations.
- Explore demographics data insights for Norway: Methodology, use cases, and definitions explaining how demographic metrics support your location intelligence workflows.
- Explore a rich library of Norway-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 Norway
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: Does the dataset include accessibility-related attributes?
A: Yes. Certain datasets include accessibility-related indicators such as wheelchair accessibility where publicly available.
Q: Does the dataset include unique identifiers?
A: Yes. Each record includes a GUID field to support deduplication, joins, and downstream database operations.
Q: Is this dataset useful for franchise analysis?
A: Yes. The dataset can support franchise territory planning, network expansion analysis, and regional performance benchmarking.
Q: Can this dataset be used for logistics planning?
A: Yes. Many customers use these datasets to optimize delivery territories, distribution networks, route planning, and last-mile logistics analysis.
Q: Can I request the data in GeoJSON or Shapefile format?
A: Yes. Alternative delivery formats such as GeoJSON, Shapefile, Excel, and PostgreSQL imports are available upon request.
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: Is the dataset standardized for analytics workflows?
A: Yes. Address formatting, administrative areas, and geospatial fields are standardized to improve consistency across analytical environments.
Q: Does the dataset include administrative regions?
A: Yes. Administrative fields such as province, district, municipality, postal code, and city are included where available.
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 Norway for potential market expansion.""Rank the top-performing urban areas in Norway for future this multi-brand expansion based on existing location density and regional population.""Create a prioritized shortlist of expansion zones in Norway based on distance gaps between existing this multi-brand locations."