All Petrol Station Locations in France: Complete Geographic Dataset

All Petrol Station Locations in France: Complete Geographic Dataset

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All Petrol Stations locations in France - complete national dataset

This dataset contains a complete, geocoded collection of Petrol Stations in France, including branded chains and independent locations. It provides a complete national coverage with 14,565 verified locations suitable for territory planning, market sizing and spatial analysis.

Last updated: 7 July 2026.

Dataset fields included in the CSV:

  • GUID
  • Title
  • Group
  • Latitude
  • Longitude
  • Street No
  • Street
  • City
  • Admin_level_1
  • Admin_level_2
  • Commune
  • Region
  • Population
  • Postal Code
  • Address
  • Wheelchair
  • Popularity Score
  • Phone
  • Website
  • Fuel Type
  • Opening hours

Brand distribution

  • AS 24 – 275 locations in France
  • Auchan – 319 locations in France
  • AVIA – 835 locations in France
  • bp – 241 locations in France
  • Carrefour – 1,255 locations in France
  • E.Leclerc – 786 locations in France
  • Elan – 336 locations in France
  • Eni – 242 locations in France
  • Esso – 904 locations in France
  • Intermarché – 1,945 locations in France
  • Shell – 89 locations in France
  • tankpool24 – 96 locations in France
  • TOTAL – 3,068 locations in France

Petrol Stations distribution by Region

  • Auvergne-Rhône-Alpes: 2,063 petrol stations
  • Bourgogne-Franche-Comté: 992 petrol stations
  • Bretagne: 741 petrol stations
  • Centre-Val De Loire: 711 petrol stations
  • Grand Est: 1,238 petrol stations
  • Hauts-De-France: 1,099 petrol stations
  • Normandie: 847 petrol stations
  • Nouvelle-Aquitaine: 1,691 petrol stations
  • Occitanie: 1,644 petrol stations
  • Pays De La Loire: 705 petrol stations
  • Provence-Alpes-Côte D'Azur: 1,275 petrol stations
  • Île-De-France: 1,348 petrol stations
  • Corse: 206 petrol stations

Direct access after purchase of the complete locations dataset for France

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.

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 for competitor benchmarking?

A: Yes. The dataset is frequently used to compare retail footprints, market density, and regional presence against competing brands.

Q: Can this data be combined with demographics datasets?

A: Yes. Many customers combine these locations with demographics, income, mobility, and administrative boundary datasets for deeper spatial analysis.

Q: What coordinate reference system is used?

A: Coordinates are provided in the global WGS84 geographic coordinate system (EPSG:4326).

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: Are postal codes included for all locations?

A: Postal codes are included wherever available and validated as part of the standardization workflow.

Q: Can this dataset support territory optimization?

A: Yes. The dataset is suitable for defining service territories, balancing regional coverage, and optimizing operational footprints.

Q: Is this dataset useful for accessibility studies?

A: Yes. Analysts can combine the coordinates with mobility, transport, and demographics datasets to evaluate accessibility and service coverage.

Q: Does the dataset include all locations in the country?

A: The dataset is designed to provide a complete and standardized list of known all locations operating in France as of July 2026.

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 France for potential market expansion."
  • "Identify this multi-brand sites with large footprints in France that are optimal candidates for EV charging infrastructure overlays."
  • "Detect clusters where this multi-brand sites are in close proximity to analyze potential self-cannibalization in France."