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Description
Romania EV Charging Stations Locations Dataset – Top 15 EV Charging Station BrandsQuick links: Overview Dataset Fields Brand Distribution Distribution by County Download FAQ Analyze with AI Top 15 EV Charging Station Chains Across Romania: Premium Multi Brand Location Dataset Unlock a complete, ready to use dataset featuring the leading EV Charging Station brands in Romania. This expertly compiled Top Brands dataset consolidates all major EV Charging Station chains in Romania, delivering a clean, standardised and analysis ready
Top 15 EV Charging Station Chains Across Romania: Premium Multi-Brand Location Dataset
Unlock a complete, ready-to-use dataset featuring the leading EV Charging Station brands in Romania. This expertly compiled Top Brands dataset consolidates all major EV Charging Station chains in Romania, delivering a clean, standardised and analysis-ready collection of 2,803 locations. Perfect for businesses seeking high-quality data for market sizing, competitive landscape analysis, network optimisation, and strategic planning.
Last updated: 2 June 2026.
Dataset fields included in the CSV:
- GUID
- Title
- Latitude
- Longitude
- Street No
- Street
- City
- Admin_level_1
- Admin_level_2
- Municipality
- County
- Population
- Postal Code
- Address
Brand distribution
- E.ON – 163 locations in Romania
- Eldrive – 145 locations in Romania
- EV Connect – 49 locations in Romania
- EV Spots – 34 locations in Romania
- GigaCharger – 20 locations in Romania
- iHunt – 637 locations in Romania
- Kaufland – 186 locations in Romania
- Lidl – 169 locations in Romania
- OMV – 53 locations in Romania
- Petrom – 78 locations in Romania
- Plugpoint – 244 locations in Romania
- Polyfazer – 71 locations in Romania
- PPC Blue – 315 locations in Romania
- Renovatio e-charge – 271 locations in Romania
- Voltrelli – 368 locations in Romania
EV Charging Stations distribution by County
- București: 207 stations
- Ilfov: 186 stations
- Brașov: 154 stations
- Constanța: 126 stations
- Suceava: 108 stations
- Maramureș: 100 stations
- Prahova: 100 stations
- Timiș: 100 stations
- Mureș: 91 stations
- Bihor: 88 stations
- Iași: 84 stations
- Sibiu: 83 stations
- Hunedoara: 76 stations
- Cluj: 69 stations
- Arad: 68 stations
- Vâlcea: 67 stations
- Argeș: 63 stations
- Buzău: 63 stations
- Dâmbovița: 63 stations
- Dolj: 61 stations
- Neamț: 53 stations
- Alba: 52 stations
- Bacău: 49 stations
- Bistrița-Năsăud: 49 stations
- Galați: 49 stations
- Gorj: 48 stations
- Harghita: 46 stations
- Vrancea: 41 stations
- Olt: 38 stations
- Giurgiu: 37 stations
- Sălaj: 36 stations
- Brăila: 35 stations
- Teleorman: 35 stations
- Caraș-Severin: 34 stations
- Mehedinți: 34 stations
- Tulcea: 34 stations
- Călărași: 31 stations
- Ialomița: 29 stations
- Satu Mare: 29 stations
- Vaslui: 29 stations
- Botoșani: 29 stations
- Covasna: 28 stations
Direct access after purchase of the complete locations dataset for Romania
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 Romania: Map these ev charging stations locations against highly precise administrative polygons for territory analysis and spatial structuring.
- Demographics dataset for Romania: Overlay demographic indicators to deeply understand the population structures and household types surrounding these ev charging stations locations.
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 [email protected].
Frequently Asked Questions
Q: Can this dataset be imported into Power BI or Tableau?
A: Yes. The CSV structure is compatible with Power BI, Tableau, Looker Studio, and other business intelligence platforms.
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 support territory optimization?
A: Yes. The dataset is suitable for defining service territories, balancing regional coverage, and optimizing operational footprints.
Q: Does the dataset include accessibility-related attributes?
A: Yes. Certain datasets include accessibility-related indicators such as wheelchair accessibility where publicly 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 Romania for potential market expansion.""Detect clusters where this multi-brand sites are in close proximity to analyze potential self-cannibalization in Romania.""Compare the spatial distribution of this multi-brand locations against major competitor clusters to identify overlap and whitespace opportunities in Romania."
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