A structured and graph-ready dataset representing the Bengaluru (Bangalore) Namma Metro network, including station metadata, geospatial coordinates, and network connectivity.
This dataset is designed to support developers, researchers, and students working on transportation systems, smart city solutions, and data-driven metro applications.
Contains metadata for all metro stations.
Columns:
station_name— Name of the metro stationstation_code— Unique short code for each stationline— Metro line (Purple Line, Green Line, Yellow Line)
Represents the metro system as a graph structure with connectivity and geospatial data.
Columns:
station_code— Unique station identifierstation_name— Name of the stationline— Metro linesequence— Order of station within the lineis_interchange— Interchange flag (1 = Yes, 0 = No)next_station_code— Next station in route (NULLfor terminal stations)latitude— Geographic latitudelongitude— Geographic longitudedistance_to_next_km— Distance to next station (in km)line_color— Hex color representing metro line
- Complete graph-based metro network structure
- Accurate geospatial coordinates for mapping
- Distance between stations using Haversine formula
- Interchange station modeling
- Multi-line coverage (Purple, Green, Yellow)
- Ready for graph algorithms and routing systems
This dataset can be used for:
- 🚇 Route optimization (Dijkstra / shortest path)
- 🗺 Metro network visualization (Leaflet, Mapbox, GIS)
- 📊 Transportation analytics & simulations
- 🧠 Smart city and urban mobility research
- 📈 Demand prediction (with external ridership data)
- 🎫 Building metro ticketing or navigation systems
This dataset can be combined with metro ridership datasets (available on Kaggle) for:
- Passenger demand prediction
- Peak hour analysis
- Congestion modeling
👉 Kaggle Dataset: View on Kaggle
- Terminal stations have
next_station_code = NULL - Distances are calculated between consecutive stations
- Coordinates are manually curated and verified for accuracy
- Dataset will be updated as new metro lines/stations are added
This dataset is released under CC0 (Public Domain).
You are free to use, modify, and distribute it without restrictions.
This dataset was created to address the lack of structured metro datasets publicly available and to help developers and researchers build real-world transportation solutions.
If you use this dataset, consider giving credit or sharing your work 🙌
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