All 311 Service Requests from 2010 to present. This information is automatically updated daily.

Click here to download data from 2011 - https://data.cityofnewyork.us/dataset/311-Service-Requests-From-2011/fpz8-jqf4

Click here to download data from 2012 - https://data.cityofnewyork.us/dataset/311-Service-Requests-From-2012/as38-8eb5

Click here to download data from 2013 - https://data.cityofnewyork.us/dataset/311-Service-Requests-From-2013/hybb-af8n

Click here to download data from 2014 - https://data.cityofnewyork.us/dataset/311-Service-Requests-From-2014/vtzg-7562

Click here to download data from 2015 - https://data.cityofnewyork.us/dataset/311-Service-Requests-From-2015/57g5-etyj

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 bars 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 bars 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 bars 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 August 15, 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.

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.

About this dataset

Context

The dataset tabulates the Bar Nunn population distribution across 18 age groups. It lists the population in each age group along with the percentage population relative of the total population for Bar Nunn. The dataset can be utilized to understand the population distribution of Bar Nunn by age. For example, using this dataset, we can identify the largest age group in Bar Nunn.

Key observations

The largest age group in Bar Nunn, WY was for the group of age 5 to 9 years years with a population of 377 (12.65%), according to the ACS 2019-2023 5-Year Estimates. At the same time, the smallest age group in Bar Nunn, WY was the 85 years and over years with a population of 5 (0.17%). Source: U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates

Content

When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates

Age groups:

• Under 5 years
• 5 to 9 years
• 10 to 14 years
• 15 to 19 years
• 20 to 24 years
• 25 to 29 years
• 30 to 34 years
• 35 to 39 years
• 40 to 44 years
• 45 to 49 years
• 50 to 54 years
• 55 to 59 years
• 60 to 64 years
• 65 to 69 years
• 70 to 74 years
• 75 to 79 years
• 80 to 84 years
• 85 years and over

Variables / Data Columns

• Age Group: This column displays the age group in consideration
• Population: The population for the specific age group in the Bar Nunn is shown in this column.
• % of Total Population: This column displays the population of each age group as a proportion of Bar Nunn total population. Please note that the sum of all percentages may not equal one due to rounding of values.

Good to know

Margin of Error

Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.

Custom data

If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.

Inspiration

Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.

Recommended for further research

This dataset is a part of the main dataset for Bar Nunn Population by Age. You can refer the same here

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.

This statistic shows the number of packages of Quaker Chewy Granola Bars nutritional snacks eaten within one month in the United States in 2020. The data has been calculated by Statista based on the U.S. Census data and Simmons National Consumer Survey (NHCS). According to this statistic, **** million Americans consumed * or more packages in 2020.

This statistic shows the consumption of energy / diet snacks and bars in the United States from 2011 to 2020 and a forecast thereof until 2024. The data has been calculated by Statista based on the U.S. Census data and Simmons National Consumer Survey (NHCS). According to this statistic, 44.51 million Americans consumed energy / diet snacks and bars in 2020. This figure is projected to increase to 45.27 million in 2024.

The North America Protein Bar Market is segmented by Distribution Channel (Convenience Store, Online Retail Store, Supermarket/Hypermarket, Others) and by Country (Canada, Mexico, United States). Market Value in USD and Volume are both presented. Key data points observed include market segmental split by confections, confectionery variant, sugar content, and distribution channel.

This dataset tracks the updates made on the dataset "U.S. State and Territorial Orders Closing and Reopening Bars Issued from March 11, 2020 through May 31, 2021 by County by Day" as a repository for previous versions of the data and metadata.

This statistic shows the brands of energy / diet snacks and bars eaten most often in the United States in 2020. The data has been calculated by Statista based on the U.S. Census data and Simmons National Consumer Survey (NHCS). According to this statistic, ***** million Americans consumed Clif in 2020.

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

Graph and download economic data for Advance Retail Sales: Food Services and Drinking Places (RSFSDP) from Jan 1992 to May 2025 about beverages, retail trade, food, sales, retail, services, and USA.

This dataset tracks the updates made on the dataset "U.S. State and Territorial Orders Closing and Reopening Bars Issued from March 11, 2020 through May 31, 2021 by County by Day" as a repository for previous versions of the data and metadata.

The North America Cafes & Bars Market report segments the industry into Cuisine (Bars & Pubs, Cafes, Juice/Smoothie/Desserts Bars, Specialist Coffee & Tea Shops), Outlet (Chained Outlets, Independent Outlets), Location (Leisure, Lodging, Retail, Standalone, Travel), and Country (Canada, Mexico, United States, Rest of North America). Get five years of historical data alongside five-year market forecasts.

About this dataset

Context

The dataset tabulates the Gold Bar population distribution across 18 age groups. It lists the population in each age group along with the percentage population relative of the total population for Gold Bar. The dataset can be utilized to understand the population distribution of Gold Bar by age. For example, using this dataset, we can identify the largest age group in Gold Bar.

Key observations

The largest age group in Gold Bar, WA was for the group of age 5 to 9 years years with a population of 219 (9.14%), according to the ACS 2019-2023 5-Year Estimates. At the same time, the smallest age group in Gold Bar, WA was the 85 years and over years with a population of 7 (0.29%). Source: U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates

Content

When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates

Age groups:

• Under 5 years
• 5 to 9 years
• 10 to 14 years
• 15 to 19 years
• 20 to 24 years
• 25 to 29 years
• 30 to 34 years
• 35 to 39 years
• 40 to 44 years
• 45 to 49 years
• 50 to 54 years
• 55 to 59 years
• 60 to 64 years
• 65 to 69 years
• 70 to 74 years
• 75 to 79 years
• 80 to 84 years
• 85 years and over

Variables / Data Columns

• Age Group: This column displays the age group in consideration
• Population: The population for the specific age group in the Gold Bar is shown in this column.
• % of Total Population: This column displays the population of each age group as a proportion of Gold Bar total population. Please note that the sum of all percentages may not equal one due to rounding of values.

Good to know

Margin of Error

Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.

Custom data

If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.

Inspiration

Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.

Recommended for further research

This dataset is a part of the main dataset for Gold Bar Population by Age. You can refer the same here

About this dataset

Context

The dataset tabulates the population of Diamond Bar by race. It includes the population of Diamond Bar across racial categories (excluding ethnicity) as identified by the Census Bureau. The dataset can be utilized to understand the population distribution of Diamond Bar across relevant racial categories.

Key observations

The percent distribution of Diamond Bar population by race (across all racial categories recognized by the U.S. Census Bureau): 21.28% are white, 3.51% are Black or African American, 0.88% are American Indian and Alaska Native, 59.39% are Asian, 0.13% are Native Hawaiian and other Pacific Islander, 7.18% are some other race and 7.63% are multiracial.

Content

When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2018-2022 5-Year Estimates.

Racial categories include:

• White
• Black or African American
• American Indian and Alaska Native
• Asian
• Native Hawaiian and Other Pacific Islander
• Some other race
• Two or more races (multiracial)

Variables / Data Columns

• Race: This column displays the racial categories (excluding ethnicity) for the Diamond Bar
• Population: The population of the racial category (excluding ethnicity) in the Diamond Bar is shown in this column.
• % of Total Population: This column displays the percentage distribution of each race as a proportion of Diamond Bar total population. Please note that the sum of all percentages may not equal one due to rounding of values.

Good to know

Margin of Error

Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.

Custom data

If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.

Inspiration

Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.

Recommended for further research

This dataset is a part of the main dataset for Diamond Bar Population by Race & Ethnicity. You can refer the same here

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!

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

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

The US Snack Bar Market is segmented by Confectionery Variant (Cereal Bar, Fruit & Nut Bar, Protein Bar) and by Distribution Channel (Convenience Store, Online Retail Store, Supermarket/Hypermarket, Others). Market Value in USD and Volume are both presented. Key data points observed include market segmental split by confections, confectionery variant, sugar content, and distribution channel.