Dataset of 700,000 restaurants in the United States complete with detailed contact and geolocation data. The database includes multiple data points such as restaurant name, address, phone number, website, email, opening hours, latitude, longitude, and cuisine.

Context

This dataset contains lists of Restaurants and their menus in the USA that are partnered with Uber Eats. Data was collected via web scraping using python libraries.

*This dataset is dedicated to the awesome delivery drivers of Uber Eats, hence the cover image

Download

kaggle API Command !kaggle datasets download -d ahmedshahriarsakib/uber-eats-usa-restaurants-menus

Content

The dataset has two CSV files -

1. restaurants.csv (40k+ entries, 11 columns)

   • id (Restaurant id)
   • position (Restaurant position in the search result)
   • name (Restaurant name)
   • score (Restaurant score)
   • ratings (Ratings count)
   • category (Restaurant category)
   • price_range (Restaurant price range - $ = Inexpensive, $$ = Moderately expensive, $$$ = Expensive, $$$$ = Very Expensive) - Source - stackoverflow
   • full_address (Restaurant full address)
   • zip_code (Zip code)
   • lat (Latitude)
   • long (Longitude)

2. restaurant-menus.csv (3.71M entries, 5 columns)

   • restaurant_id (Restaurant id)
   • category (Menu category)
   • name (Menu Name)
   • description (Menu description)
   • price (Menu price)

Acknowledgements

Data was scraped from - - https://www.ubereats.com - An online food ordering and delivery platform launched by Uber in 2014. Users can read menus, reviews, ratings, order, and pay for food from participating restaurants using an application on the iOS or Android platforms, or through a web browser. Users are also able to tip for delivery. Payment is charged to a card on file with Uber. Meals are delivered by couriers using cars, scooters, bikes, or foot. It is operational in over 6,000 cities across 45 countries.

Cover Image -

Photo by eggbank on Unsplash

Disclaimer

The data and information in the data set provided here are intended to use for educational purposes only. I do not own any of the data and all rights are reserved to the respective owners.

Inspiration

• How many Restaurants are around the USA?
• What are the Most Popular/Highly Rated Restaurants and menus?
• Is there any relationship between the price level and the popularity of a restaurant?
• Which menus are more expensive?
• Which menus are very common in the USA?

Update Frequency

1. The dataset will be updated weekly

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

State and territorial executive orders, administrative orders, resolutions, and proclamations are collected from government websites and cataloged and coded using Microsoft Excel by one coder with one or more additional coders conducting quality assurance. Data were collected to determine when restaurants in states and territories were subject to closing and reopening requirements through executive orders, administrative orders, resolutions, and proclamations for COVID-19. Data can be used to determine when restaurants in states and territories were subject to closing and reopening requirements through executive orders, administrative orders, resolutions, and proclamations for COVID-19. Data consists exclusively of state and territorial orders, many of which apply to specific counties within their respective state or territory; therefore, data is broken down to the county level. These data are derived from publicly available state and territorial executive orders, administrative orders, resolutions, and proclamations (“orders”) for COVID-19 that expressly close or reopen restaurants found by the CDC, COVID-19 Community Intervention & Critical Populations Task Force, Monitoring & Evaluation Team, Mitigation Policy Analysis Unit, and the CDC, Center for State, Tribal, Local, and Territorial Support, Public Health Law Program from March 11, 2020 through May 31, 2021. These data will be updated as new orders are collected. Any orders not available through publicly accessible websites are not included in these data. Only official copies of the documents or, where official copies were unavailable, official press releases from government websites describing requirements were coded; news media reports on restrictions were excluded. Recommendations not included in an order are not included in these data. Effective and expiration dates were coded using only the date provided; no distinction was made based on the specific time of the day the order became effective or expired. These data do not necessarily represent an official position of the Centers for Disease Control and Prevention.

Comprehensive dataset of 1,257 Dim sum restaurants in United States as of June, 2025. Includes verified contact information (email, phone), geocoded addresses, customer ratings, reviews, business categories, and operational details. Perfect for market research, lead generation, competitive analysis, and business intelligence. Download a complimentary sample to evaluate data quality and completeness.

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

MealMe offers in-depth restaurant menu data, including prices, from the top 100,000 restaurants across the USA and Canada. Our proprietary technology collects accurate, real-time menu and pricing information, enabling businesses to make data-driven decisions in competitive intelligence, pricing optimization, and market research. With comprehensive coverage that spans major restaurant platforms and chains, MealMe ensures your business has access to the most reliable data to excel in a rapidly evolving industry.

Platforms and Restaurants Covered: MealMe's database includes data from leading restaurant platforms such as UberEats, Postmates, ToastTakeout, SkipTheDishes, Square, Appfront, Olo, TouchBistro, and Clover, as well as direct menu data from major restaurant chains including Raising Cane’s, Panda Express, Popeyes, Burger King, and Subway. This extensive coverage ensures a detailed view of the market, helping businesses monitor trends, pricing, and availability across a broad spectrum of restaurant types and sizes.

Key Features: Comprehensive Menu Data: Access detailed menu information, including item descriptions, categories, sizes, and customizations. Real-Time Pricing: Monitor up-to-date menu prices for accurate competitive analysis. Restaurant-Specific Insights: Analyze individual restaurant chains such as Raising Cane’s and Panda Express, or platforms like UberEats, for market trends and pricing strategies. Cross-Platform Analysis: Compare menu items and pricing across platforms like ToastTakeout, Olo, and SkipTheDishes for a holistic industry view. Regional Data: Understand geographic variations in menu offerings and pricing across the USA and Canada.

Use Cases: Competitive Intelligence: Track menu offerings, pricing strategies, and seasonal trends across platforms like UberEats and Postmates or chains like Popeyes and Subway. Market Research: Identify gaps in the market by analyzing menus and pricing from top restaurants. Pricing Optimization: Use real-time pricing data to inform dynamic pricing strategies and promotions. Trend Monitoring: Stay ahead by tracking popular menu items, regional preferences, and emerging food trends. Platform Analysis: Assess how restaurants perform across delivery platforms such as SkipTheDishes, Olo, and Square. Industries Benefiting from Our Data Restaurant Chains: Optimize menu offerings and pricing strategies with detailed competitor data. Food Delivery Platforms: Benchmark menu pricing and availability across competitive platforms. Market Research Firms: Conduct detailed analyses to identify opportunities and market trends. AI & Analytics Companies: Power recommendation engines and predictive models with robust menu data. Consumer Apps: Enhance app experiences with accurate menu and pricing data. Data Delivery and Integration

MealMe offers flexible integration options to ensure seamless access to our comprehensive menu data. Whether you need bulk exports for in-depth research or real-time updates via API, our solutions are designed to scale with your business needs.

Why Choose MealMe? Extensive Coverage: Menu data from 100,000+ restaurants, including major chains like Burger King and Raising Cane’s. Real-Time Accuracy: Up-to-date pricing and menu details for actionable insights. Customizable Solutions: Tailored datasets to meet your specific business objectives. Proven Expertise: Trusted by top companies for delivering reliable, actionable data. MealMe empowers businesses with the data needed to thrive in a competitive restaurant and food delivery market. For more information or to request a demo, contact us today!

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

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

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.

The Delta Food Outlets Study was an observational study designed to assess the nutritional environments of 5 towns located in the Lower Mississippi Delta region of Mississippi. It was an ancillary study to the Delta Healthy Sprouts Project and therefore included towns in which Delta Healthy Sprouts participants resided and that contained at least one convenience (corner) store, grocery store, or gas station. Data were collected via electronic surveys between March 2016 and September 2018 using the Nutrition Environment Measures Survey (NEMS) tools. Survey scores for the NEMS Corner Store, NEMS Grocery Store, and NEMS Restaurant were computed using modified scoring algorithms provided for these tools via SAS software programming. Because the towns were not randomly selected and the sample sizes are relatively small, the data may not be generalizable to all rural towns in the Lower Mississippi Delta region of Mississippi. Dataset one (NEMS-C) contains data collected with the NEMS Corner (convenience) Store tool. Dataset two (NEMS-G) contains data collected with the NEMS Grocery Store tool. Dataset three (NEMS-R) contains data collected with the NEMS Restaurant tool. Resources in this dataset:Resource Title: Delta Food Outlets Data Dictionary. File Name: DFO_DataDictionary_Public.csvResource Description: This file contains the data dictionary for all 3 datasets that are part of the Delta Food Outlets Study.Resource Software Recommended: Microsoft Excel,url: https://products.office.com/en-us/excel Resource Title: Dataset One NEMS-C. File Name: NEMS-C Data.csvResource Description: This file contains data collected with the Nutrition Environment Measures Survey (NEMS) tool for convenience stores.Resource Software Recommended: Microsoft Excel,url: https://products.office.com/en-us/excel Resource Title: Dataset Two NEMS-G. File Name: NEMS-G Data.csvResource Description: This file contains data collected with the Nutrition Environment Measures Survey (NEMS) tool for grocery stores.Resource Software Recommended: Microsoft Excel,url: https://products.office.com/en-us/excel Resource Title: Dataset Three NEMS-R. File Name: NEMS-R Data.csvResource Description: This file contains data collected with the Nutrition Environment Measures Survey (NEMS) tool for restaurants.Resource Software Recommended: Microsoft Excel,url: https://products.office.com/en-us/excel

Data you can expect: - Metadata (country, region, city, coordinates, address, categories, description, operating hours, and more) - Contacts (phone contacts, email, website) - Social profiles (LinkedIn, Twitter, Instagram, Facebook) - Reviews (reviews and ratings on different sites) - Menus (categories, items, prices, descriptions and photos) - Other info (awards, Michelin stars, executive chef, popular dishes, average meal price, and more) - Photos (ambience, food, menu photos)

Let us know if you have a specific request, and we'll try to fulfil it.

How we deliver data: - We transform it to fit your system's data schema, (ease the pain and cost of having data engineers from your side) - We are completely flexible on the delivery format and method.

Graph and download economic data for All Employees: Full-Service Restaurants in California (SMU06000007072251101A) from 1990 to 2024 about restaurant, CA, services, employment, and USA.

Snapshot img

US Fast Casual Restaurants Market Size 2025-2029

US fast casual restaurants market size is forecast to increase by USD 84.5 billion at a CAGR of 13.7% between 2024 and 2029.

US Fast Casual Restaurants Market is experiencing significant growth, driven by the increasing demand for innovation and customization in food menus. Consumers are seeking more personalized dining experiences, leading to the popularity of fast casual concepts that offer a unique blend of affordability, quality, and convenience. Additionally, the market is witnessing an increasing focus on digitalization of services, with contactless ordering and payment options gaining traction in response to the ongoing pandemic. However, the market faces challenges as well. Intense competition from quick-service restaurants and the need to maintain consistent supply chains pose significant hurdles for market growth.
Regulatory compliance and labor costs also add complexity to the operational landscape. To capitalize on opportunities and navigate challenges effectively, companies must stay abreast of consumer trends and invest in digital technologies to enhance the customer experience. Innovation in menu offerings, sustainable sourcing, and strategic partnerships will be key differentiators in this dynamic market.

What will be the size of the US Fast Casual Restaurants Market during the forecast period?

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 US Fast Casual Restaurants market is experiencing significant growth, driven by various factors. Menu innovation, with an emphasis on vegetarian, vegan, and gluten-free options, caters to diverse dietary preferences and allergies. Customer experience is prioritized through personalized dining, contactless ordering, and mobile payments. Data-driven decision-making and restaurant automation, including artificial intelligence and predictive analytics, optimize operations and reduce labor costs. Franchise models and in-house delivery services expand reach and cater to Generation Z's preference for convenience. Supply chain management and food traceability ensure transparency and sustainability, while omni-channel strategies engage customers through loyalty programs and subscription services.Restaurant analytics provide valuable customer feedback, enabling continuous improvement and operational optimization.

How is this market segmented?

The market research report provides comprehensive data (region-wise segment analysis), with forecasts and estimates in 'USD billion' for the period 2025-2029, as well as historical data from 2019-2023 for the following segments.

Channel

  Dine-in
  Takeaway


Application

  Franchised
  Standalone


Food Type

  Burger/Sandwich
  Pizza/Pasta
  Asian
  Latin American
  Chicken
  Others


Target Audience

  Millennials
  Working Professionals
  Families


Distribution Channel Specificity

  Specialty Chains
  Online Platforms
  Retail Foodservice


Geography

  North America

    US

By Channel Insights

The dine-in segment is estimated to witness significant growth during the forecast period.

Fast casual restaurants in the US and Canada offer a unique dining experience, blending the speed and convenience of fast food with the quality and ambiance of casual dining. These establishments, which have gained popularity in recent years, use fresh ingredients, digital ordering systems, and self-service kiosks to streamline the dining process while maintaining food quality. Employee training is a key focus to ensure consistent customer service and food safety. Menu innovation and healthy options cater to various consumer preferences, including Generation Z and those seeking sustainable practices. In addition, many fast casual restaurants offer catering services, in-house delivery, and third-party delivery through food delivery platforms.

The franchise model is also common in the fast casual industry, allowing for efficient expansion and operational efficiency. Restaurant technology plays a significant role in fast casual operations, with kitchen display systems, labor scheduling, and point-of-sale systems helping to manage inventory and improve efficiency. Digital marketing and social media marketing are essential for customer engagement and loyalty programs. Food trucks and ghost kitchens are emerging trends in the fast casual industry, offering alternative business models and lower overhead costs. Food safety and food quality are top priorities, with strict adherence to industry standards and regulations. The fast casual industry continues to evolve, with dining trends such as virtual brands, subscription services, and data analytics shaping the future of this dynamic market.

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The Dine-in segment was valued at USD 48.90 billion in 2019 and showed a gradual increase during the forecast period.

Market Dynamics

Our researchers analyzed the data with 2024 as the base year,

United States Retail Sales: FS: ow: Full Service Restaurants data was reported at 27.702 USD bn in May 2018. This records an increase from the previous number of 25.823 USD bn for Apr 2018. United States Retail Sales: FS: ow: Full Service Restaurants data is updated monthly, averaging 14.362 USD bn from Jan 1992 (Median) to May 2018, with 317 observations. The data reached an all-time high of 27.702 USD bn in May 2018 and a record low of 6.675 USD bn in Feb 1993. United States Retail Sales: FS: ow: Full Service Restaurants data remains active status in CEIC and is reported by US Census Bureau. The data is categorized under Global Database’s USA – Table US.H001: Retail Sales: By NAIC System.

Graph and download economic data for All Employees: Leisure and Hospitality: Full-Service Restaurants in New York City, NY (SMU36935617072251101SA) from Jan 1990 to May 2025 about restaurant, New York, NY, services, employment, and USA.

United States - Retail Sales: Full Service Restaurants was -9.40000 % Chg. from Preceding Period in January of 2020, according to the United States Federal Reserve. Historically, United States - Retail Sales: Full Service Restaurants reached a record high of 16.80000 in December of 2017 and a record low of -13.10000 in January of 2018. Trading Economics provides the current actual value, an historical data chart and related indicators for United States - Retail Sales: Full Service Restaurants - last updated from the United States Federal Reserve on July of 2025.

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

Analysis of ‘🍕 Pizza restaurants and Pizzas on their Menus’ provided by Analyst-2 (analyst-2.ai), based on source dataset retrieved from https://www.kaggle.com/yamqwe/pizza-restaurants-and-pizzas-on-their-menuse on 13 February 2022.

--- Dataset description provided by original source is as follows ---

About this dataset

About this Data

This is a list of over 3,500 pizzas from multiple restaurants provided by Datafiniti's Business Database. The dataset includes the category, name, address, city, state, menu information, price range, and more for each pizza restaurant.

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 how much you can expect to pay for pizza across the country. E.g.:

• What are the least and most expensive cities for pizza?
• What is the number of restaurants serving pizza per capita (100,000 residents) across the U.S.?
• What is the median price of a large plain pizza across the U.S.?
• Which cities have the most restaurants serving pizza per capita (100,000 residents)?

Data Schema

A full schema for the data is available in our 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 10000 samples along with Longitude, Price Range Max, technical information and other features such as: - Date Updated - Categories - and more.

How to use this dataset

• Analyze Date Added in relation to Province
• Study the influence of Price Range Min on Address
• More datasets

Acknowledgements

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

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--- Original source retains full ownership of the source dataset ---

Comprehensive dataset of 57 Toast restaurants in United States as of June, 2025. Includes verified contact information (email, phone), geocoded addresses, customer ratings, reviews, business categories, and operational details. Perfect for market research, lead generation, competitive analysis, and business intelligence. Download a complimentary sample to evaluate data quality and completeness.