Gas stations points of interest data in United States of America (USA)

Containing data on 196,643 gas stations within USA, this dataset offers a comprehensive view of the gas station landscape in the country. Each entry includes vital information such as the station’s name, address, contact details, website link, review counts, and 20 additional attributes. Notably, brand identification features are also provided, enhancing the depth of analysis.

List of Gas Stations in United States of America (USA)

The Gas/Petrol Stations POI dataset for the United States of America (USA) provides a comprehensive collection of real-world locations that are identifiable and named, specifically focusing on gas stations. These POIs play a crucial role in navigation systems and location-based services, facilitating efficient wayfinding and enhancing user experiences.

196,643

Total Number of records
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172,969

Number of POIs with Phone Numbers
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128,627

Number of POIs with Website
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136,630

Number of POIs with Ratings data
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Download United States of America's Gas Stations Points of Interest Data

This dataset employs various categorization methods to classify gas stations based on type, subtype, location, and attributes. The type categorization encompasses broad classifications like restaurants, parks, and shopping malls, while subtypes offer finer granularity such as specific types of restaurants or specialized parks. Location data pinpoints the exact geographical coordinates of each gas station, enabling precise mapping. Furthermore, the dataset offers an array of attributes that furnish additional information about these gas stations, including contact details, operational hours, and other relevant data.

Key Variables

The Gas/Petrol Stations POI dataset for the United States of America (USA) provides a comprehensive collection of real-world locations that are identifiable and named, specifically focusing on gas stations. These POIs play a crucial role in navigation systems and location-based services, facilitating efficient wayfinding and enhancing user experiences.

Name
Description
Type
services
Text describing services offered by the point of interest.
text
sequence
Sequence number used for ordering records.
bigint
geometry
Geometric data for mapping purposes.
USER-DEFINED
score
Numerical score associated with the point of interest.
double precision
suggested_brand
Text suggesting a brand associated with the point of interest.
text
is_brand
Numerical value indicating if the point of interest is a branded establishment.
double precision
tags
Tags categorizing the point of interest.
text
hotel_services
Numerical value indicating the level of services offered by a hotel.
double precision
collection_date
Date when the information was collected.
text
keywords_used_in_search
Keywords used in searches to find the point of interest.
text
img_links
Links to images related to the point of interest.
text
description
Numerical value for a detailed description of the point of interest.
double precision
poi_news
Numerical value indicating the presence of news articles related to the point of interest.
double precision
poi_time_zone
Time zone of the point of interest.
text
poi_website
Website specifically for the point of interest.
text
hotel_rank
Ranking of a hotel point of interest.
double precision
properties
Additional properties of the point of interest, in text.
text
rate
Numerical rating of the point of interest.
double precision
meal_weekly_trends
Trends of weekly traffic related to meals, for restaurants.
text
day_traffic_trends
Trends of daily traffic to the point of interest.
text
traffic_score
Numerical score representing traffic to the point of interest.
double precision
traffic_label
Label describing the traffic at the point of interest.
text
poi_type
Type of the point of interest (e.g., restaurant, museum).
text
online_visibility
Numerical score of the point of interest's online visibility.
double precision
is_closed
Text status indicating whether the point of interest is currently closed.
text
phone
Phone number of the point of interest.
text
photos
Links to photos of the point of interest.
text
reservations
Numerical value indicating the reservation status or count.
double precision
price_range
Numerical range indicating the cost bracket of the point of interest.
double precision
city
City where the point of interest is located.
text
reviews_no
Number of reviews for the point of interest.
double precision
province
Province where the point of interest is located.
text
map_link
Link to the map showing the point of interest's location.
text
price_range_icons
Numerical indicator of the price range, for icon display.
double precision
country
Country where the point of interest is located.
text
longitude
Longitude coordinate of the point of interest.
double precision
address_text
Textual address of the point of interest.
text
place_id
Unique identifier for the point of interest.
text
latitude
Latitude coordinate of the point of interest.
double precision
website
Website associated with the point of interest.
text
poi_name
Name of the point of interest.
text

Use Cases

How can this dataset benefit you?

Market Analysis

Researchers can utilize this dataset to analyze the distribution of gas stations across different regions and assess market competition.

Urban Planning

City planners can employ this dataset to understand the distribution of essential services like gas stations in various areas, aiding in urban development.

Business Insights

Businesses can leverage the dataset’s attributes, such as review counts and operational hours, to gain insights into consumer preferences and optimize their strategies.

Unleash the power of xMap

Distribution of Gas Stations in the U.S

The landscape of gas stations across the United States is characterized by a diverse and extensive distribution, covering urban centers, suburban neighborhoods, and remote rural areas. This wide distribution ensures that fueling services are accessible to all, from bustling city streets to the quietest country roads, reflecting the country's reliance on automobiles for transportation.

Distribution of Shell Gas Stations in the U.S.A (13,598 data points)

Shell Gas Stations, with a total of 13,598 locations across the United States, showcase a significant presence in the fueling industry. Their strategic placement spans major highways, urban hubs, and suburban areas, providing convenient access to quality fuel and services for millions of Americans and contributing substantially to the national energy infrastructure.

Traffic Score and Popularity of Gas Stations

The traffic score and popularity of gas stations across the U.S are influenced by various factors including location, service quality, and additional amenities. Stations situated on busy highways or in densely populated urban areas tend to have higher traffic scores and popularity, serving as crucial pit stops for commuters and travelers seeking fuel, food, and rest.

Ratings of Gas stations in the U.S

Customer ratings of gas stations in the U.S reflect the quality of service, cleanliness, pricing, and the availability of amenities such as convenience stores. High-rated stations often exceed in providing excellent customer service and maintaining clean, well-stocked facilities, thereby attracting more customers and setting industry standards.

Gas Stations in the U.S by States

The distribution of gas stations in the U.S varies by state, influenced by population density, geographic size, and transportation infrastructure. States with larger urban populations and extensive road networks, like California and Texas, have a higher concentration of gas stations to cater to the fueling needs of residents and transit traffic, while less populous states may have fewer stations, strategically placed to serve local and passing drivers efficiently.

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Frequently Asked Questions

Find answers to commonly asked questions about our spatial analyst platform.

How many gas stations in United States of America (USA)?

196,643

Can I integrate this data with other GIS tools?

Yes, our dataset is compatible with major GIS platforms, allowing for seamless integration and analysis.

Can this dataset be combined with other data for a more comprehensive analysis?

Absolutely. It can be integrated with economic, geographic, and other datasets for a multifaceted analysis of Oman’s socio-economic landscape.

Muneeb Rehman
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