About this Dataset

Contact information for over 20,000 restaurants across the US. All restaurants from the NAICS code 72251: Restaurants and Other Eating Places. This includes all set down, fast casual, fast food, and ethnic restaurants. List includes name, address, phone number, website, contact email address, and a brief description. Data was collected from a combination of web scrapping and manual data entry. Similar lists cost over $1500 from lead generation and business data companies.

Category

Lead Generation

Keywords

restaurants,contact,mailing

Row Count

21210

Price

$499.00

Dataset

This dataset was created by Slamet Hariyadi

Released under Apache 2.0

Contents

Dive into the "1500 North American Restaurants Comprehensive Dataset," featuring a rich selection of dining establishments from cozy local eateries to renowned culinary destinations. This meticulously curated collection spans a diverse range of cuisines, dining experiences, and geographical locations across North America. Each entry encapsulates key details such as cuisine types, service options, and customer ratings, making it an indispensable resource for food enthusiasts, researchers, and industry analysts seeking insights into the continent's vibrant restaurant scene.

Column Descriptions:

name: The name of the restaurant. city: The city where the restaurant is located. state: The state or province where the restaurant is located. zipcode: The postal code of the restaurant. country: The country of the restaurant (US or CA). cuisines: The types of cuisines offered by the restaurant. pickup_enabled: Indicates if pickup service is available (TRUE or FALSE). delivery_enabled: Indicates if delivery service is available (TRUE or FALSE). weighted_rating_value: The average rating of the restaurant on a scale from 0 to 5. aggregated_rating_count: The total number of ratings the restaurant has received.

Dive into this dataset for captivating data visualizations mapping North America's culinary landscape, NLP-driven sentiment analysis on cuisine types, and machine learning models predicting restaurant success. It's perfect for enthusiasts keen on uncovering trends through viz, extracting insights via NLP, or enhancing recommendation systems with predictive analytics. A playground for data science exploration!

Image attributes : Image By freepik

Xtract.io's comprehensive McDonald's location data provides a detailed view of the global fast-food chain's network. Restaurant investors, market researchers, and business analysts can utilize this dataset to analyze market penetration, identify expansion opportunities, and develop a sophisticated understanding of McDonald's geographical strategy.

Point of Interest (POI) data, also known as places data, provides the exact location of buildings, stores, or specific places. It has become essential for businesses to make smarter, geography-driven decisions in today's competitive landscape.

LocationsXYZ, the POI data product from Xtract.io, offers a comprehensive database of 6 million locations across the US, UK, and Canada, spanning 11 diverse industries, including:

-Retail -Restaurants -Healthcare -Automotive -Public utilities (e.g., ATMs, park-and-ride locations) -Shopping malls, and more

Why Choose LocationsXYZ? At LocationsXYZ, we: -Deliver POI data with 95% accuracy -Refresh POIs every 30, 60, or 90 days to ensure the most recent information -Create on-demand POI datasets tailored to your specific needs -Handcraft boundaries (geofences) for locations to enhance accuracy -Provide POI and polygon data in multiple file formats

Unlock the Power of POI Data With our point-of-interest data, you can: -Perform thorough market analyses -Identify the best locations for new stores -Gain insights into consumer behavior -Achieve an edge with competitive intelligence

LocationsXYZ has empowered businesses with geospatial insights, helping them scale and make informed decisions. Join our growing list of satisfied customers and unlock your business's potential with our cutting-edge POI data.

Xtract.io's Restaurant POI data delivers a comprehensive view of the brand's extensive QSR and fast food restaurant locations across the United States and Canada. Franchise investors, business analysts, and market researchers can utilize this QSR and fast food location data to understand Subway and other fast food market penetration, identify potential growth areas, and develop targeted strategic insights for quick service restaurant analysis.

Point of Interest (POI) data, also known as places data, provides the exact location of buildings, stores, or specific places. It has become essential for businesses to make smarter, geography-driven decisions in today's competitive restaurant location intelligence landscape.

LocationsXYZ, the POI data product from Xtract.io, offers a comprehensive database of 6 million locations across the US, UK, and Canada, spanning 11 diverse industries, including: -Retail -Restaurant chain locations -Healthcare -Automotive -Public utilities (e.g., ATMs, park-and-ride locations) -Shopping malls, and more

Why Choose LocationsXYZ for Fast Food POI Data? At LocationsXYZ, we: -Deliver restaurant POI data with 95% accuracy -Refresh QSR location data every 30, 60, or 90 days to ensure the most recent information -Create on-demand fast food chain datasets tailored to your specific needs -Handcraft boundaries (geofences) for restaurant locations to enhance accuracy -Provide restaurant POI data and polygon data in multiple file formats

Unlock the Power of Restaurant Location Data With our point-of-interest data for food service establishments, you can: -Perform thorough market analyses for QSR expansion -Identify the best locations for new restaurant stores -Gain insights into consumer behavior and dining patterns -Achieve an edge with competitive intelligence in the fast food industry

LocationsXYZ has empowered businesses with geospatial insights and restaurant location intelligence, helping them scale and make informed decisions. Join our growing list of satisfied customers and unlock your business's potential with our cutting-edge Subway restaurant POI data.

Comprehensive dataset containing 12,653 verified Indian restaurant businesses in United States with complete contact information, ratings, reviews, and location data.

This is a list of 10,000 fast food restaurants provided by Datafiniti's Business Database. The dataset includes the restaurant's address, city, latitude and longitude coordinates, name, and more.

Note that this is a sample of a large dataset. The full dataset is available through Datafiniti.

What You Can Do With This Data

You can use this data to rank cities with the most and least fast food restaurants across the U.S. E.g.:

• Cities with the most and least McDonald's per capita
• Fast food restaurants per capita for all states
• Fast food restaurants with the most locations nationally
• Major cities with the most and least fast food restaurants per capita
• Small cities with the most fast food restaurants per capita
• States with the most and least fast food restaurants per capita
• The number of fast food restaurants per capita

Original Data

Acknowlegement

Foto von Haseeb Jamil auf Unsplash

Eateries in in New York City Department of Parks & Recreation properties including snack bars, food carts, mobile food trucks, and restaurants.

Comprehensive dataset containing 9,016 verified Southern restaurant (US) businesses in United States with complete contact information, ratings, reviews, and location data.

Graph and download economic data for Retail Sales: Restaurants and Other Eating Places (MRTSSM7225USN) from Jan 1992 to Aug 2025 about restaurant, retail trade, sales, retail, and USA.

Title:

380K Restaurants - Mostly USA Based

Subtitle:

An extensive dataset of restaurants spanning the USA, with select international entries.

Description:

Dataset Overview:
This dataset provides a comprehensive compilation of 380,000 restaurants. While the majority are from the USA, there is also a representation from international locales. It's an invaluable resource for researchers, business analysts, and enthusiasts looking into the restaurant industry.

Dataset Contents:
The dataset encompasses various attributes for each restaurant:

• Title: The name of the restaurant.
• Link: A direct link to the restaurant's online presence or review site.
• Category: The type or genre of the restaurant (e.g., "Fast Food" or "Sushi").
• Rating: A numerical representation of customer reviews and feedback.
• Website: The official website of the restaurant.
• Phone: Contact number for reservations or inquiries.
• Address: Physical location or address of the restaurant.
• Images: Visual representations or photographs related to the restaurant.
• Categories: Further details on the restaurant's specialties.
• Geo_Coordinates: Geographical data points related to the restaurant's location.
• Time_Zone: The time zone in which the restaurant operates.
• Latitude & Longitude: Geographical coordinates for map integrations.

Potential Use Cases:
- Regional Analysis: Study restaurant distributions across different states or regions. - Rating Trends: Analyze the correlation between restaurant categories and their ratings. - Mapping Projects: Visualize restaurant locations to identify dense clusters or potential opportunities. - Time-Based Analysis: Investigate restaurant operations across different time zones.

Feedback and Collaboration:

Share insights, visualizations, or projects derived from this dataset with the wider community.

Dataset updated:

Feb 14, 2024

Dataset provided by:

data.world, Inc.

Authors:

Datafiniti

Area covered:

North Pacific Ocean, Pacific Ocean

Data Description:

This is a list of 10,000 fast food restaurants provided by Datafiniti's Business Database. The dataset includes the restaurant's address, city, latitude and longitude coordinates, name, and more. Note that this is a sample of a large dataset. The full dataset is available through Datafiniti. You can use this data to rank cities with the most and least fast food restaurants across the U.S. E.g.:

Cities with the most and least McDonald's per capita
Fast food restaurants per capita for all states
Fast food restaurants with the most locations nationally
Major cities with the most and least fast food restaurants per capita
Small cities with the most fast food restaurants per capita
States with the most and least fast food restaurants per capita
The number of fast food restaurants per capita

About this Data

This is a list of 19,439 restaurants and similar businesses with menu items containing "burrito" or "taco" in their names provided by Datafiniti's Business Database.

The dataset includes the category, cuisine, restaurant information, and more for a menu item. Each row corresponds to a single menu item from the restaurant, and the entirety of each restaurant's menu is not listed. Only burrito or taco items are listed.

Note that this is a sample of a large dataset. The full dataset is available through Datafiniti.

What You Can Do with this Data

You can use this data to discover which parts of the country offer the most for Mexican food aficionados. E.g.:

What is the ratio of burritos and tacos on restaurant menus from each city? What is the ratio of burritos and tacos on restaurant menus from cities with the most restaurants per capita (10,000 residents)? What is the ratio of cities with the most authentic Mexican restaurants per capita (10,000 residents)? Which cities have the most authentic Mexican restaurants? Which cities have the most Mexican restaurants? Which Mexican restaurants have the most locations nationally?

Data Schema

A full schema for the data is available in support documentation.

About Datafiniti

Datafiniti provides instant access to web data. We compile data from thousands of websites to create standardized databases of business, product, and property information. Learn more.

Interested in the Full Dataset?

Get this data and more by creating a free Datafiniti account or requesting a demo.

This dataset was created by Datafiniti and contains around 77,000 samples along with City, Categories Restaureant, Menus_amount Max, technical information, and other features such as:

• Cuisines
• Menu_description
• priceRangeMin and priceRangeMax
• and more.

How to use this dataset

• Exploratory Data Analysis
• Study the influence of price on menus_name
• Study the words that are most often used to describe burritos and tacos dishes

Acknowledgements

If you use this dataset in your research, please credit Datafiniti

Start A New Notebook!

This data set is a list of the number and proportion of different types of restaurant in each electoral county in the United States. It also contains other socio-economic and public health data.

This dataset provides restaurant inspections, violations, grades and adjudication information

About this dataset

Do you love the convenience of being able to drive through and pick up your food without having to wait? Well, you're not alone. According to a new study by Datafiniti, there are over 10,000 fast food restaurants across the United States.

That's a lot of restaurants! But what does that mean for the average person living in America? Well, it means that there are more than enough options for those who want to grab a quick bite on the go. And it also means that there are plenty of opportunities for those who want to open their own fast food restaurant.

So, if you're thinking about starting your own fast food business, or if you're just curious about where the most (and least) fast food options are in America, then this dataset is for you!

How to use the dataset

To find out where the most fast food restaurants are in the United States, you can use this dataset. The dataset includes the restaurant's name, address, city, state, and website. You can use this information to rank cities with the most and least fast food options

Research Ideas

1. Fast food delivery service that delivers from multiple restaurants

2. An app that allows users to find the healthiest fast food options near them

3. A website that ranks cities by their number of fast food restaurants per capita

Acknowledgements

The original source of the data is Datafiniti's Business Database. The dataset includes the restaurant's address, city, latitude and longitude coordinates, name, and more

Columns

File: Datafiniti_Fast_Food_Restaurants.csv | Column name | Description | |:----------------|:---------------------------------------------------------------------| | dateAdded | The date the restaurant was added to the database. (Date) | | dateAdded | The date the restaurant was added to the database. (Date) | | dateUpdated | The date the restaurant was last updated in the database. (Date) | | dateUpdated | The date the restaurant was last updated in the database. (Date) | | address | The street address of the restaurant. (String) | | address | The street address of the restaurant. (String) | | categories | The category or categories the restaurant is classified as. (String) | | categories | The category or categories the restaurant is classified as. (String) | | city | The city the restaurant is located in. (String) | | city | The city the restaurant is located in. (String) | | country | The country the restaurant is located in. (String) | | country | The country the restaurant is located in. (String) | | keys | The unique identifier for the restaurant. (String) | | keys | The unique identifier for the restaurant. (String) | | latitude | The latitude coordinate of the restaurant. (Float) | | latitude | The latitude coordinate of the restaurant. (Float) | | longitude | The longitude coordinate of the restaurant. (Float) | | longitude | The longitude coordinate of the restaurant. (Float) | | name | The name of the restaurant. (String) | | name | The name of the restaurant. (String) | | postalCode | The postal code of the restaurant. (String) | | postalCode | The postal code of the restaurant. (String) | | province | The province or state the restaurant is located in. (String) | | province | The province or state the restaurant is located in. (String) | | sourceURLs | The source URL of the restaurant. (String) | | sourceURLs | The source URL of the restaurant. (String) | | websites | The website of the restaurant. (String) | | websites | The website of the restaurant. (String) |

File: FastFoodRestaurants.csv | Column name | Description | |:---------------|:-------------------------------------------------------------| | address | The street address of the restaurant. (String) | | address | The street address of the restaurant. (String) | | city | The city the restaurant is located in. (String) | | city | The city the restaurant is located in. (String) | | country | The country the restaurant i...

About this Dataset

This is an email list of restaurants nationwide. The list has 12,795 contacts. It comes with their full name and email.

Category

Lead Generation

Keywords

Restaurants,US restaurants,Nationwide Restaurants,Email List,Restaurant Email List

Row Count

12795

Price

$12799.00

The Temporary Program, is no longer accepting applications. *Visit Permanent Dining Out website for information: https://www.diningoutnyc.info/ The New York City Open Restaurant is an effort to implement a citywide multi-phase program to expand outdoor seating options for food establishments to promote open space, enhance social distancing, and help them rebound in these difficult economic times. For real time updates on restaurants registered in the program, please visit NYC Open Restaurants dashboard: https://bit.ly/2Z00kn8 ** Please note this Open Restaurant Applications dataset may contain multiple entries (e.g. restaurants submitting 2 or more applications). The Open Restaurants dashboard website containing real time update, noted above, will have fewer total records due to the removal of multiple applications and only list the newest entry.

This dataset provides restaurant inspections, violations, grades and adjudication information

Comprehensive dataset containing 182 verified Southern restaurant (US) businesses in California, United States with complete contact information, ratings, reviews, and location data.