Italy Petrol Stations Locations Dataset – Top 17 Petrol Station Brands

Italy Petrol Stations Locations Dataset – Top 17 Petrol Station Brands

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Top 17 Petrol Station Chains Across Italy: Premium Multi-Brand Location Dataset

Unlock a complete, ready-to-use dataset featuring the leading Petrol Station brands in Italy. This expertly compiled Top Brands dataset consolidates all major Petrol Station chains in Italy, delivering a clean, standardised and analysis-ready collection of 18,478 locations. Perfect for businesses seeking high-quality data for market sizing, competitive landscape analysis, network optimisation, and strategic planning.

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
  • Phone
  • Website
  • Fuel Type
  • Opening hours

Brand distribution

  • AS 24 – 192 locations in Italy
  • Beyfin – 118 locations in Italy
  • Costantin – 118 locations in Italy
  • EnerGas – 157 locations in Italy
  • Eni (Agip) – 4,523 locations in Italy
  • Esso – 2,441 locations in Italy
  • Europam – 182 locations in Italy
  • Ewa – 163 locations in Italy
  • IP – 5,060 locations in Italy
  • Keropetrol – 154 locations in Italy
  • Q8 – 3,085 locations in Italy
  • Retitalia – 233 locations in Italy
  • Shell – 183 locations in Italy
  • Star Oil – 137 locations in Italy
  • Tamoil – 1,592 locations in Italy
  • Vega – 140 locations in Italy

Petrol Stations distribution by Region

  • Lombardia: 2,652 petrol stations
  • Lazio: 1,842 petrol stations
  • Piemonte: 1,559 petrol stations
  • Emilia-Romagna: 1,410 petrol stations
  • Veneto: 1,391 petrol stations
  • Toscana: 1,345 petrol stations
  • Campania: 1,282 petrol stations
  • Sicilia: 1,260 petrol stations
  • Puglia: 1,192 petrol stations
  • Calabria: 706 petrol stations
  • Marche: 653 petrol stations
  • Sardigna: 554 petrol stations
  • Abruzzo: 543 petrol stations
  • Liguria: 487 petrol stations
  • Friuli-Venezia Giulia: 460 petrol stations
  • Umbria: 384 petrol stations
  • Trentino-Alto Adige: 327 petrol stations
  • Basilicata: 201 petrol stations
  • Molise: 135 petrol stations
  • Valle D'Aosta: 68 petrol stations

Direct access after purchase of the complete locations dataset for Italy

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 in GIS software?

A: Yes. The dataset is suitable for GIS platforms including QGIS, ArcGIS, GeoPandas, CARTO, and other spatial analysis environments.

Q: Does the dataset include latitude and longitude coordinates?

A: Yes. Each location record includes precise WGS84 latitude and longitude coordinates for geospatial analysis and mapping workflows.

Q: Can I analyze this dataset with AI tools?

A: Yes. The dataset is structured for compatibility with AI workflows including ChatGPT, Claude, Gemini, RAG pipelines, and Python-based analytics.

Q: Can I preview the dataset before purchasing?

A: Yes. A free sample is available so you can evaluate the structure, fields, and geospatial quality before purchase.

Q: Are postal codes included for all locations?

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

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 Italy for potential market expansion."
  • "Analyze the clustering behavior of this multi-brand locations to determine whether the network prioritizes convenience, coverage, or saturation strategies."
  • "Cross-reference these petrol stations with urban transit data to score each location's accessibility for non-driving customers."