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US Subway Store Geographical Locations
Data Science and Analytics
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About
This collection of data details the location of Subway restaurants across the United States. Given that a significant majority of all Subway stores globally are situated within the US, this data is invaluable for understanding the geographical footprint of this major fast-food franchise. It provides essential location coordinates and address information, making it suitable for geographical analysis and proximity studies.
Columns
The data structure consists of 23 columns, primarily housed in a CSV file format:
- name: The established name of the Subway store (String).
- url: The web address for the store's specific website (String).
- street_address: The physical street location of the outlet (String).
- city: The municipality where the store is located (String).
- state: The US state where the store resides (String).
- zip_code: The postal code associated with the location (String).
- country: The nation where the store is located (USA) (String).
- phone_number_1/phone_number_2/fax_1/fax_2/email_1/email_2/website/facebook/twitter/instagram/pinterest/youtube: Various contact details and social media links. (Note: Many of these columns are entirely missing or null for all records.)
- open_hours: The documented hours of operation for the specific Subway store (String).
- latitude: The latitudinal coordinate of the store (Float).
- longitude: The longitudinal coordinate of the store (Float).
Distribution
The information is available in a data file named
subway.csv, which is approximately 9.18 MB in size. The dataset contains approximately 25,500 records detailing unique store locations. Core geographical fields such as street address, city, state, and coordinates are highly populated, though many of the auxiliary contact and social media fields contain zero valid records.Usage
This data product is ideally suited for several analytical and practical applications:
- Identifying the closest Subway outlet from any specified location.
- Conducting market research to map and understand the geographic spread of fast-food franchises.
- Assisting business planners in strategising the expansion of the Subway franchise into new territories.
- Performing research to uncover potential patterns in store location that might correlate with socio-economic indicators, such as local income or education levels.
Coverage
The geographic scope is limited strictly to the United States. The dataset provides current location data, but its expected update frequency is noted as 'Never', meaning it reflects a static capture of store locations. The data does not contain explicit demographic details, but its location specificity allows researchers to incorporate external socio-economic data for advanced analysis.
License
Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0)
Who Can Use It
The dataset is intended for non-commercial use only. Ideal users include:
- Consumers and App Developers: For proximity searches and navigation tools to locate the nearest store.
- Academics and Researchers: For studies on franchise distribution, retail geography, and socio-economic influences on business location.
- Market Analysts: For benchmarking location strategies and assessing market penetration within the US fast-food sector.
Dataset Name Suggestions
- US Subway Store Geographical Locations
- Fast Food Location Data: United States Subway Outlets
- Subway Restaurant Locations in the United States
Attributes
Original Data Source: US Subway Store Geographical Locations
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