Tourist Arrivals in the United States decreased to 5634382 in May from 5957985 in April of 2025. This dataset provides - United States Tourist Arrivals- actual values, historical data, forecast, chart, statistics, economic calendar and news.

Tourism Revenues in the United States decreased to 21229 USD Million in May from 21636 USD Million in April of 2025. This dataset provides - United States Tourism Revenues- actual values, historical data, forecast, chart, statistics, economic calendar and news.

United States US: International Tourism: Number of Arrivals data was reported at 75,608,000.000 Person in 2016. This records a decrease from the previous number of 77,465,000.000 Person for 2015. United States US: International Tourism: Number of Arrivals data is updated yearly, averaging 51,107,500.000 Person from Dec 1995 (Median) to 2016, with 22 observations. The data reached an all-time high of 77,465,000.000 Person in 2015 and a record low of 41,218,000.000 Person in 2003. United States US: International Tourism: Number of Arrivals data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s United States – Table US.World Bank.WDI: Tourism Statistics. International inbound tourists (overnight visitors) are the number of tourists who travel to a country other than that in which they have their usual residence, but outside their usual environment, for a period not exceeding 12 months and whose main purpose in visiting is other than an activity remunerated from within the country visited. When data on number of tourists are not available, the number of visitors, which includes tourists, same-day visitors, cruise passengers, and crew members, is shown instead. Sources and collection methods for arrivals differ across countries. In some cases data are from border statistics (police, immigration, and the like) and supplemented by border surveys. In other cases data are from tourism accommodation establishments. For some countries number of arrivals is limited to arrivals by air and for others to arrivals staying in hotels. Some countries include arrivals of nationals residing abroad while others do not. Caution should thus be used in comparing arrivals across countries. The data on inbound tourists refer to the number of arrivals, not to the number of people traveling. Thus a person who makes several trips to a country during a given period is counted each time as a new arrival.; ; World Tourism Organization, Yearbook of Tourism Statistics, Compendium of Tourism Statistics and data files.; Gap-filled total;

United States US: International Tourism: Number of Departures data was reported at 73,453,000.000 Person in 2015. This records an increase from the previous number of 68,176,000.000 Person for 2014. United States US: International Tourism: Number of Departures data is updated yearly, averaging 61,061,000.000 Person from Dec 1995 (Median) to 2015, with 21 observations. The data reached an all-time high of 73,453,000.000 Person in 2015 and a record low of 51,285,000.000 Person in 1995. United States US: International Tourism: Number of Departures data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s United States – Table US.World Bank.WDI: Tourism Statistics. International outbound tourists are the number of departures that people make from their country of usual residence to any other country for any purpose other than a remunerated activity in the country visited. The data on outbound tourists refer to the number of departures, not to the number of people traveling. Thus a person who makes several trips from a country during a given period is counted each time as a new departure.; ; World Tourism Organization, Yearbook of Tourism Statistics, Compendium of Tourism Statistics and data files.; Gap-filled total;

This table contains 45 series, with data for years 2014 - 2014 (not all combinations necessarily have data for all years). This table contains data described by the following dimensions (Not all combinations are available): Geography (1 item: Canada) State visited (15 items: Florida; New York; Washington; California; ...) Travel characteristics (3 items: Visits; Nights; Spending in country).

DRAKO is a Mobile Location Data provider with a programmatic trading desk specializing in geolocation analytics and programmatic advertising. Our Tourism Data has helped cities, counties, and states better understand who their visitors are so that they can effectively develop and deliver advertising campaigns. We’re in a unique position to deliver enriched insight beyond traditional surveying or other data sources because of our rich dataset, proprietary modelling capabilities, and analytical capabilities.

MAIDs (Mobile Advertising IDs) are unique device identifiers associated with consenting mobile devices that can be utilized for geolocation based analyses and audiences. Drako uses MAIDs to fuel our Tourism Data utilizing our Home Location Model. The Home Location of a MAID is determined based on where that MAID is seen most frequently between the hours of 11pm and 6am (local time). Using this we are able to determine the Home Location of a user which in turn allows us to identify when and where they are travelling.

Beyond identifying that users are tourists, we can also classify them into different bins by their frequency / dwell time over their estimated number of visits. Using our data and frequency, we can identify: overnight visitors, weekend visits, short-term stays, long-term stays, or frequent holiday visitors !

Beyond Tourism Data in your defined geography alone, we are also able to provide: - Home location - Find out where your audience is coming from using our home location technology - Movement - Quantify how far users have travelled between locations. - Demographics - Discover neighborhood level characteristics such as income, ethnicity, and more - Brand index - Learn which major brands and retailers your audience is visiting the most. - Visitation index - See which destinations your visitors are visiting the most - Addressable audience - Customize your audiences for your campaigns using our analytic insights

Moreover, if you’re looking to activate your Tourism Data for advertising, we’re always able to further refine or filter your desired audience with our other Audience Data, such as: Brand visits, Geodemographics, Ticketed Event visits, Purchase Intent (in Canada), Purchase History (in USA), and more !

Data Compliance: All of our Tourism Data is fully CCPA compliant and 100% sourced from SDKs (Software Development Kits), the most reliable and consistent mobile data stream with end user consent available with only a 4-5 day delay. This means that our location and device ID data comes from partnerships with over 1,500+ mobile apps. This data comes with an associated location which is how we are able to segment using geofences.

Data Quality: In addition to partnering with trusted SDKs, DRAKO has additional screening methods to ensure that our mobile location data is consistent and reliable. This includes data harmonization and quality scoring from all of our partners in order to disregard MAIDs with a low quality score.

This dataset contains data and analysis from the article Do State Department Travel Warnings Reflect Real Danger?

Key findings

• On the whole, there is a significant relationship between the number of American deaths abroad per capita and the number of travel warnings a country receives
• Mexico, Mali, and Israel have been targeted by the most travel warnings in recent years, but Americans are more likely to be killed in Thailand, Pakistan, and the Philippines
• Several countries with relatively high rates of American death have not been issued a single travel warning in ~7 years, including Belize, Guyana, and Guatemala
• Several countries with relatively low rates of American death have been issued a relatively high number of travel warnings in ~7 years, including Israel, Turkey, and Saudi Arabia
• Overall, countries subject to travel warnings do not see notable declines in American visitors in the 6 months after a warning is issued

Data sources

• BTSOriginUS_10_09_to_06_16.csv Air Carrier Statistics Database export, Bureau of Transportation Statistics
• SDamerican_deaths_abroad_10_09_to_06_16.csv U.S. State Department
• SDwarnings_10_09to06_16.csv U.S. State Department via Internet Archive

Charts / data visualizations

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The dataset shows the indicator for the number of international tourists who visited El Salvador, Nicaragua, Honduras, and Guatemala between 1995 and 2022, broken down by total number of tourists and regions of origin: Africa, the Americas, East Asia, and the Pacific. These statistics come from reliable reports that allow monitoring the development of tourism in the region. They have been assessed based on information obtained from the World Tourism Organization (UNWTO).

For more information contact GIS4Tech: info@gis4tech.com. You can also visit the PREDISAN platform https://predisan.gis4tech.com/ca4 for detailed, accurate information.

This table contains 45 series, with data for years 2014 - 2014 (not all combinations necessarily have data for all years). This table contains data described by the following dimensions (Not all combinations are available): Geography (1 item: Canada) Country of origin (15 items: United States; United Kingdom; France; China; ...) Traveller characteristics (3 items: Trips; Nights; Spending in Canada).

Context

Cultural diversity in the U.S. has led to great variations in names and naming traditions and names have been used to express creativity, personality, cultural identity, and values. Source: https://en.wikipedia.org/wiki/Naming_in_the_United_States

Content

This public dataset was created by the Social Security Administration and contains all names from Social Security card applications for births that occurred in the United States after 1879. Note that many people born before 1937 never applied for a Social Security card, so their names are not included in this data. For others who did apply, records may not show the place of birth, and again their names are not included in the data.

All data are from a 100% sample of records on Social Security card applications as of the end of February 2015. To safeguard privacy, the Social Security Administration restricts names to those with at least 5 occurrences.

Fork this kernel to get started with this dataset.

Acknowledgements

https://bigquery.cloud.google.com/dataset/bigquery-public-data:usa_names

https://cloud.google.com/bigquery/public-data/usa-names

Dataset Source: Data.gov. This dataset is publicly available for anyone to use under the following terms provided by the Dataset Source — http://www.data.gov/privacy-policy#data_policy — and is provided "AS IS" without any warranty, express or implied, from Google. Google disclaims all liability for any damages, direct or indirect, resulting from the use of the dataset.

Banner Photo by @dcp from Unplash.

Inspiration

What are the most common names?

What are the most common female names?

Are there more female or male names?

Female names by a wide margin?

Brazil Visitor Arrival: USA data was reported at 696.512 Person th in 2024. This records an increase from the previous number of 668.478 Person th for 2023. Brazil Visitor Arrival: USA data is updated yearly, averaging 581.130 Person th from Dec 1989 (Median) to 2024, with 36 observations. The data reached an all-time high of 793.559 Person th in 2005 and a record low of 91.471 Person th in 1993. Brazil Visitor Arrival: USA data remains active status in CEIC and is reported by Ministry of Tourism. The data is categorized under Global Database’s Brazil – Table BR.QB002: No of Visitors Arrivals: by Country: Annual.

Context

The Bureau of Labor Statistics (BLS) is a unit of the United States Department of Labor. It is the principal fact-finding agency for the U.S. government in the broad field of labor economics and statistics and serves as a principal agency of the U.S. Federal Statistical System. The BLS is a governmental statistical agency that collects, processes, analyzes, and disseminates essential statistical data to the American public, the U.S. Congress, other Federal agencies, State and local governments, business, and labor representatives. Source: https://en.wikipedia.org/wiki/Bureau_of_Labor_Statistics

Content

Bureau of Labor Statistics including CPI (inflation), employment, unemployment, and wage data.

Update Frequency: Monthly

Querying BigQuery Tables

Fork this kernel to get started.

Acknowledgements

https://bigquery.cloud.google.com/dataset/bigquery-public-data:bls

https://cloud.google.com/bigquery/public-data/bureau-of-labor-statistics

Dataset Source: http://www.bls.gov/data/

This dataset is publicly available for anyone to use under the following terms provided by the Dataset Source - http://www.data.gov/privacy-policy#data_policy - and is provided "AS IS" without any warranty, express or implied, from Google. Google disclaims all liability for any damages, direct or indirect, resulting from the use of the dataset.

Banner Photo by Clark Young from Unsplash.

Inspiration

What is the average annual inflation across all US Cities? What was the monthly unemployment rate (U3) in 2016? What are the top 10 hourly-waged types of work in Pittsburgh, PA for 2016?

The number of international tourist arrivals in Asia was forecast to continuously increase between 2024 and 2029 by in total 174.7 million arrivals (+33.49 percent). After the ninth consecutive increasing year, the arrivals is estimated to reach 696.34 million arrivals and therefore a new peak in 2029. Depicted is the number of inbound international tourists. According to World Bank this refers to tourists travelling to a country which is not their usual residence, whereby the main purpose is not work related and the planned visitation period does not exceed 12 months. The forecast has been adjusted for the expected impact of COVID-19.The shown data are an excerpt of Statista's Key Market Indicators (KMI). The KMI are a collection of primary and secondary indicators on the macro-economic, demographic and technological environment in more than 150 countries and regions worldwide. All input data are sourced from international institutions, national statistical offices, and trade associations. All data has been are processed to generate comparable datasets (see supplementary notes under details for more information).Find more key insights for the number of international tourist arrivals in countries like North America and Caribbean.

Visitor Arrivals: Air: Central America & Caribbean: Costa Rica data was reported at 0.920 Person th in Dec 2018. This records a decrease from the previous number of 0.925 Person th for Nov 2018. Visitor Arrivals: Air: Central America & Caribbean: Costa Rica data is updated monthly, averaging 0.433 Person th from Jan 1989 (Median) to Dec 2018, with 360 observations. The data reached an all-time high of 5.177 Person th in Jun 2014 and a record low of 0.033 Person th in Apr 1993. Visitor Arrivals: Air: Central America & Caribbean: Costa Rica data remains active status in CEIC and is reported by Ministry of Tourism. The data is categorized under Brazil Premium Database’s Tourism Sector – Table BR.QB003: No of Visitors Arrivals: by Mode of Transport. According Ministry of Tourism, the monthly Visitor Arrivals will release in annual basis due to Tourism Ministry receive once in the year some input data from the Federal Policy, based on these data they perform the estimation for all the months in the year

The total population in the United States was estimated at 341.2 million people in 2024, according to the latest census figures and projections from Trading Economics. This dataset provides - United States Population - actual values, historical data, forecast, chart, statistics, economic calendar and news.

The Google Reviews & Ratings Dataset provides businesses with structured insights into customer sentiment, satisfaction, and trends based on reviews from Google. Unlike broad review datasets, this product is location-specific—businesses provide the locations they want to track, and we retrieve as much historical data as possible, with daily updates moving forward.

This dataset enables businesses to monitor brand reputation, analyze consumer feedback, and enhance decision-making with real-world insights. For deeper analysis, optional AI-driven sentiment analysis and review summaries are available on a weekly, monthly, or yearly basis.

Dataset Highlights

• Location-Specific Reviews – Reviews and ratings for the locations you provide.
• Daily Updates – New reviews and rating changes updated automatically.
• Historical Data Access – Retrieve past reviews where available.
• AI Sentiment Analysis (Optional) – Summarized insights by week, month, or year.
• Competitive Benchmarking – Compare performance across selected locations.

Use Cases

• Franchise & Retail Chains – Monitor brand reputation and performance across locations.
• Hospitality & Restaurants – Track guest sentiment and service trends.
• Healthcare & Medical Facilities – Understand patient feedback for specific locations.
• Real Estate & Property Management – Analyze tenant and customer experiences through reviews.
• Market Research & Consumer Insights – Identify trends and analyze feedback patterns across industries.

Data Updates & Delivery

• Update Frequency: Daily
• Data Format: CSV for easy integration
• Delivery: Secure file transfer (SFTP or cloud storage)

Data Fields Include:

• Business Name
• Location Details
• Star Ratings
• Review Text
• Timestamps
• Reviewer Metadata

Optional Add-Ons:

• AI Sentiment Analysis – Aggregate trends by week, month, or year.
• Custom Location Tracking – Tailor the dataset to fit your specific business needs.

Ideal for

• Marketing Teams – Leverage real-world consumer feedback to optimize brand strategy.
• Business Analysts – Use structured review data to track customer sentiment over time.
• Operations & Customer Experience Teams – Identify service issues and opportunities for improvement.
• Competitive Intelligence – Compare locations and benchmark against industry competitors.

Why Choose This Dataset?

• Accurate & Up-to-Date – Daily updates ensure fresh, reliable data.
• Scalable & Customizable – Track only the locations that matter to you.
• Actionable Insights – AI-driven summaries for quick decision-making.
• Easy Integration – Delivered in a structured format for seamless analysis.

By leveraging Google Reviews & Ratings Data, businesses can gain valuable insights into customer sentiment, enhance reputation management, and stay ahead of the competition.

Supermarket XYZ has been operating since 2008 and business flourished until 2016. They have a large database but they do not use them to achieve better business solutions. Their annual revenues have declined 10% and it seems to stay that way every year.

These datasets are used to analyse a supermarket in United States for the purpose of increasing revenue.

1. 50_Supermarket_Branches.csv contains the information of 50 supermarket branches such as their spending on the advertisement, administration and promotion, states and profits.

2. Ads_CTR_Optimisation.csv is based on the Click-Through Rates (CTR) from 10000 users in 10 different advertisements.

3. Market_Basket_Optimisation.csv . This dataset contains 7500 sales transactions in a week.

4. Supermarket_CustomerMembers.csv . This dataset can be used for customer segmentation.

These datasets in 'U.S. Supermarket Data' are available and legal for everyone who needs it for any kind of analytics project.

Visitor Arrivals: Marine: Central America & Caribbean: Cuba data was reported at 0.002 Person th in Dec 2018. This records an increase from the previous number of 0.000 Person th for Nov 2018. Visitor Arrivals: Marine: Central America & Caribbean: Cuba data is updated monthly, averaging 0.000 Person th from Jan 1989 (Median) to Dec 2018, with 360 observations. The data reached an all-time high of 0.035 Person th in Jan 2008 and a record low of 0.000 Person th in Nov 2018. Visitor Arrivals: Marine: Central America & Caribbean: Cuba data remains active status in CEIC and is reported by Ministry of Tourism. The data is categorized under Brazil Premium Database’s Tourism Sector – Table BR.QB003: No of Visitors Arrivals: by Mode of Transport. According Ministry of Tourism, the monthly Visitor Arrivals will release in annual basis due to Tourism Ministry receive once in the year some input data from the Federal Policy, based on these data they perform the estimation for all the months in the year

Context

Since 2008, guests and hosts have used Airbnb to travel in a more unique, personalized way. As part of the Airbnb Inside initiative, this dataset describes the listing activity of homestays in Seattle, WA.

Content

The following Airbnb activity is included in this Seattle dataset: * Listings, including full descriptions and average review score * Reviews, including unique id for each reviewer and detailed comments * Calendar, including listing id and the price and availability for that day

Inspiration

• Can you describe the vibe of each Seattle neighborhood using listing descriptions?
• What are the busiest times of the year to visit Seattle? By how much do prices spike?
• Is there a general upward trend of both new Airbnb listings and total Airbnb visitors to Seattle?

For more ideas, visualizations of all Seattle datasets can be found here.

Acknowledgement

This dataset is part of Airbnb Inside, and the original source can be found here.

Context

NYC Open Data is an opportunity to engage New Yorkers in the information that is produced and used by City government. We believe that every New Yorker can benefit from Open Data, and Open Data can benefit from every New Yorker. Source: https://opendata.cityofnewyork.us/overview/

Content

Thanks to NYC Open Data, which makes public data generated by city agencies available for public use, and Citi Bike, we've incorporated over 150 GB of data in 5 open datasets into Google BigQuery Public Datasets, including:

• Over 8 million 311 service requests from 2012-2016

• More than 1 million motor vehicle collisions 2012-present

• Citi Bike stations and 30 million Citi Bike trips 2013-present

• Over 1 billion Yellow and Green Taxi rides from 2009-present

• Over 500,000 sidewalk trees surveyed decennially in 1995, 2005, and 2015

This dataset is deprecated and not being updated.

Fork this kernel to get started with this dataset.

Acknowledgements

https://opendata.cityofnewyork.us/

https://cloud.google.com/blog/big-data/2017/01/new-york-city-public-datasets-now-available-on-google-bigquery

This dataset is publicly available for anyone to use under the following terms provided by the Dataset Source - https://data.cityofnewyork.us/ - and is provided "AS IS" without any warranty, express or implied, from Google. Google disclaims all liability for any damages, direct or indirect, resulting from the use of the dataset.

By accessing datasets and feeds available through NYC Open Data, the user agrees to all of the Terms of Use of NYC.gov as well as the Privacy Policy for NYC.gov. The user also agrees to any additional terms of use defined by the agencies, bureaus, and offices providing data. Public data sets made available on NYC Open Data are provided for informational purposes. The City does not warranty the completeness, accuracy, content, or fitness for any particular purpose or use of any public data set made available on NYC Open Data, nor are any such warranties to be implied or inferred with respect to the public data sets furnished therein.

The City is not liable for any deficiencies in the completeness, accuracy, content, or fitness for any particular purpose or use of any public data set, or application utilizing such data set, provided by any third party.

Banner Photo by @bicadmedia from Unplash.

Inspiration

On which New York City streets are you most likely to find a loud party?

Can you find the Virginia Pines in New York City?

Where was the only collision caused by an animal that injured a cyclist?

What’s the Citi Bike record for the Longest Distance in the Shortest Time (on a route with at least 100 rides)?

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