This dataset presents ChatGPT usage patterns across U.S. Census regions, based on a 2025 nationwide survey. It tracks how often users followed, partially used, or never used ChatGPT by state region.

Annual Resident Population Estimates, Estimated Components of Resident Population Change, and Rates of the Components of Resident Population Change; for the United States, States, Metropolitan Statistical Areas, Micropolitan Statistical Areas, Counties, and Puerto Rico: April 1, 2010 to July 1, 2019 // Source: U.S. Census Bureau, Population Division // The contents of this file are released on a rolling basis from December through March. // Note: Total population change includes a residual. This residual represents the change in population that cannot be attributed to any specific demographic component. // Note: The estimates are based on the 2010 Census and reflect changes to the April 1, 2010 population due to the Count Question Resolution program and geographic program revisions. // The Office of Management and Budget's statistical area delineations for metropolitan, micropolitan, and combined statistical areas, as well as metropolitan divisions, are those issued by that agency in September 2018. // Current data on births, deaths, and migration are used to calculate population change since the 2010 Census. An annual time series of estimates is produced, beginning with the census and extending to the vintage year. The vintage year (e.g., Vintage 2019) refers to the final year of the time series. The reference date for all estimates is July 1, unless otherwise specified. With each new issue of estimates, the entire estimates series is revised. Additional information, including historical and intercensal estimates, evaluation estimates, demographic analysis, research papers, and methodology is available on website: https://www.census.gov/programs-surveys/popest.html.

The Annual Survey of Manufactures (ASM) provides key intercensal measures of manufacturing activity, products, and location for the public and private sectors. The ASM provides the best current measure of current U.S. manufacturing industry outputs, inputs, and operating status, and is the primary basis for updates of the Longitudinal Research Database (LRD). Census Bureau staff and academic researchers with sworn agent status use the LRD for micro data analysis.

The Annual Business Survey (ABS) provides information on selected economic and demographic characteristics for businesses and business owners by sex, ethnicity, race, and veteran status. Further, the survey measures research and development (for microbusinesses), new business topics such as innovation and technology, as well as other business characteristics. The U.S. Census Bureau and the National Center conduct the ABS jointly for Science and Engineering Statistics within the National Science Foundation. The ABS replaces the five-year Survey of Business Owners (SBO) for employer businesses, the Annual Survey of Entrepreneurs (ASE), the Business R&D and Innovation for Microbusinesses survey (BRDI-M), and the innovation section of the Business R&D and Innovation Survey (BRDI-S). https://www.census.gov/programs-surveys/abs.html

The Commodity Flow Survey (CFS) is undertaken through a partnership between the U.S. Census Bureau, U.S. Department of Commerce, and the Research and Innovation Technology Administration, Bureau of Transportation Statistics (BTS), U.S. Department of Transportation. This survey produces data on the movement of goods in the United States. It provides information on commodities shipped, their value, weight, and mode of transportation, as well as the origin and destination of shipments of manufacturing, mining, wholesale, and select retail and services establishments. The data from the CFS are used by public policy analysts and for transportation planning and decision making to access the demand for transportation facilities and services, energy use, and safety risk and environmental concerns. This dataset provides data for the Hazardous Materials Series.

[ARCHIVED] Community Counts data is retained for archival purposes only, such as research, reference and record-keeping. This data has not been maintained or updated. Users looking for the latest information should refer to Statistics Canada’s Census Program (https://www12.statcan.gc.ca/census-recensement/index-eng.cfm?MM=1) for the latest data, including detailed results about Nova Scotia. This table reports education by major field of study and sex. This data is sourced from the Census of Population (long form). Geographies available: provinces, counties, communities, municipalities, district health authorities, community health boards, economic regions, police districts, school boards, municipal electoral districts, provincial electoral districts, federal electoral districts, regional development authorities, watersheds

The Quarterly Census of Employment and Wages (QCEW) program serves as a near census of employment and wage information. The program produces a comprehensive tabulation of employment and wage information for workers covered by Connecticut Unemployment Insurance (UI) laws and Federal workers covered by the Unemployment Compensation for Federal Employees (UCFE) program. Data on the number of establishments, employment, and wages are reported by industry for Connecticut and for the counties, towns and Labor Market Areas (LMAs) and Workforce Investment Areas (WIAs).

Analysis of ‘Internet Access - ACS 2013-2017 - Tempe Tracts’ provided by Analyst-2 (analyst-2.ai), based on source dataset retrieved from https://catalog.data.gov/dataset/55e52c2a-6b5c-42cc-86cf-6631c877bfb6 on 11 February 2022.

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

Tempe Census Census Tracts and internet access by household. Data source: U.S. Census Bureau, 2013-2017 American Community Survey 5-Year Estimates, table BD28011 (Internet Subscription in Household).

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

Compares percent distribution of STEM (science, technology, engineering and math and computer science) and BHASE (non-STEM) fields of study between census divisions.

A global database of Census Data that provides an understanding of population distribution at administrative and zip code levels over 55 years, past, present, and future.

Leverage up-to-date census data with population trends for real estate, market research, audience targeting, and sales territory mapping.

Self-hosted commercial demographic dataset curated based on trusted sources such as the United Nations or the European Commission, with a 99% match accuracy. The global Census Data is standardized, unified, and ready to use.

Use cases for the Global Census Database (Consumer Demographic Data)

• Ad targeting

• B2B Market Intelligence

• Customer analytics

• Real Estate Data Estimations

• Marketing campaign analysis

• Demand forecasting

• Sales territory mapping

• Retail site selection

• Reporting

• Audience targeting

Census data export methodology

Our consumer demographic data packages are offered in CSV format. All Demographic data are optimized for seamless integration with popular systems like Esri ArcGIS, Snowflake, QGIS, and more.

Product Features

• Historical population data (55 years)

• Changes in population density

• Urbanization Patterns

• Accurate at zip code and administrative level

• Optimized for easy integration

• Easy customization

• Global coverage

• Updated yearly

• Standardized and reliable

• Self-hosted delivery

• Fully aggregated (ready to use)

• Rich attributes

Why do companies choose our demographic databases

• Standardized and unified demographic data structure

• Seamless integration in your system

• Dedicated location data expert

Note: Custom population data packages are available. Please submit a request via the above contact button for more details.

The Census data API provides access to the most comprehensive set of data on current month and cumulative year-to-date imports broken down by agricultural and nonagricultural commodities. The USDA endpoint in the Census data API provides value, shipping weight, and method of transportation totals at the district level for all U.S. trading partners. The Census data API will help users research new markets for their products, establish pricing structures for potential export markets, and conduct economic planning. If you have any questions regarding U.S. international trade data, please call us at 1(800)549-0595 option #4 or email us at eid.international.trade.data@census.gov.

[ARCHIVED] Community Counts data is retained for archival purposes only, such as research, reference and record-keeping. This data has not been maintained or updated. Users looking for the latest information should refer to Statistics Canada’s Census Program (https://www12.statcan.gc.ca/census-recensement/index-eng.cfm?MM=1) for the latest data, including detailed results about Nova Scotia. This table reports education by major field of study. This data is sourced from the Census of Population (long form). Geographies available: provinces, counties, communities, municipalities, district health authorities, community health boards, economic regions, police districts, school boards, municipal electoral districts, provincial electoral districts, federal electoral districts, regional development authorities, watersheds

This dataset contains polygons that represent the boundaries of statistical neighborhoods as defined by the DC Department of Health (DC Health). DC Health delineates statistical neighborhoods to facilitate small-area analyses and visualization of health, economic, social, and other indicators to display and uncover disparate outcomes among populations across the city. The neighborhoods are also used to determine eligibility for some health services programs and support research by various entities within and outside of government. DC Health Planning Neighborhood boundaries follow census tract 2010 lines defined by the US Census Bureau. Each neighborhood is a group of between one and seven different, contiguous census tracts. This allows for easier comparison to Census data and calculation of rates per population (including estimates from the American Community Survey and Annual Population Estimates). These do not reflect precise neighborhood locations and do not necessarily include all commonly-used neighborhood designations. There is no formal set of standards that describes which neighborhoods are included in this dataset. Note that the District of Columbia does not have official neighborhood boundaries. Origin of boundaries: each neighborhood is a group of between one and seven different, contiguous census tracts. They were originally determined in 2015 as part of an analytical research project with technical assistance from the Centers for Disease Control and Prevention (CDC) and the Council for State and Territorial Epidemiologists (CSTE) to define small area estimates of life expectancy. Census tracts were grouped roughly following the Office of Planning Neighborhood Cluster boundaries, where possible, and were made just large enough to achieve standard errors of less than 2 for each neighborhood's calculation of life expectancy. The resulting neighborhoods were used in the DC Health Equity Report (2018) with updated names. HPNs were modified slightly in 2019, incorporating one census tract that was consistently suppressed due to low numbers into a neighboring HPN (Lincoln Park incorporated into Capitol Hill). Demographic information were analyzed to identify the bordering group with the most similarities to the single census tract. A second change split a neighborhood (GWU/National Mall) into two to facilitate separate analysis.

This table is part of a series of tables that present a portrait of Canada based on the various census topics. The tables range in complexity and levels of geography. Content varies from a simple overview of the country to complex cross-tabulations; the tables may also cover several censuses.

Annual Housing Unit Estimates for the United States, States, and Counties // Source: U.S. Census Bureau, Population Division // Note: The estimates are based on the 2010 Census and reflect changes to the April 1, 2010 housing units due to the Count Question Resolution program and geographic program revisions. For the housing unit estimates methodology statement, see http://www.census.gov/popest/methodology/index.html.// Each year, the Census Bureau's Population and Housing Unit Estimates Program utilizes current data on new residential construction, placements of manufactured housing, and housing unit loss to calculate change in the housing stock since the most recent decennial census, and produces a time series of housing unit estimates.. The annual time series of estimates begins with the most recent decennial census data and extends to the vintage year. The vintage year (e.g., V2015) refers to the final year of the time series. The reference date for all estimates is July 1, unless otherwise specified. With each new issue of estimates, the Census Bureau revises estimates for years back to the last census. As each vintage of estimates includes all years since the most recent decennial census, the latest vintage of data available supersedes all previously produced estimates for those dates. The Population and Housing Unit Estimates Program provides additional information including population estimates, historical and intercensal estimates, evaluation estimates, demographic analysis, and research papers on its website: http://www.census.gov/popest/index.html.

The Project on Human Development in Chicago Neighborhoods (PHDCN) is a large-scale, interdisciplinary study of how families, schools, and neighborhoods affect child and adolescent development. The crosswalk file contains census tract to neighborhood cluster level data, enabling researchers to merge and aggregate additional crime and census data with the PHDCN data. Access to these data is restricted. Users must provide justification for their request to access the crosswalk file, as well as a description of any datasets they plan to link to the PHDCN data.

Drone-Assisted Wildlife Population Census Market Outlook

According to our latest research, the global Drone-Assisted Wildlife Population Census market size reached USD 512.6 million in 2024, driven by the rapid adoption of advanced drone technologies across conservation and wildlife management sectors. The market is projected to grow at a robust CAGR of 13.2% from 2025 to 2033, reaching an estimated USD 1,473.2 million by 2033. This impressive growth is fueled by increasing investments in ecological monitoring, stricter wildlife protection regulations, and the widespread integration of high-resolution imaging and AI-powered data analytics in wildlife research.

The primary growth factor for the Drone-Assisted Wildlife Population Census market is the urgent need for accurate, efficient, and minimally invasive wildlife monitoring methods. Traditional wildlife census techniques often involve manual surveys, which are time-consuming, expensive, and potentially disruptive to animal habitats. Drones, equipped with advanced imaging technologies such as thermal, multispectral, and LiDAR sensors, offer a transformative alternative. These aerial systems enable researchers and conservationists to conduct large-scale surveys over challenging terrains, collect high-resolution data, and monitor elusive or endangered species without direct human interference. As biodiversity conservation becomes a global priority, especially in the face of climate change and habitat loss, the demand for drone-assisted census solutions is expected to rise significantly.

Another significant driver is the evolution of regulatory frameworks and governmental support for wildlife conservation initiatives. Many countries are enacting policies that encourage the use of unmanned aerial vehicles (UAVs) in environmental monitoring, anti-poaching efforts, and habitat mapping. This regulatory backing not only legitimizes the use of drones in protected areas but also opens up funding opportunities for research institutes and conservation organizations. Furthermore, collaborations between government agencies, NGOs, and private technology providers are fostering innovation in drone hardware and software, making these solutions more accessible and cost-effective for end-users worldwide. The growing ecosystem of partnerships and supportive policies is a critical catalyst in expanding the market’s reach.

Technological advancements in drone platforms and imaging sensors are also reshaping the landscape of wildlife population census. The integration of AI-driven analytics, real-time data transmission, and cloud-based processing has dramatically improved the accuracy and efficiency of wildlife monitoring. Drones now offer extended flight durations, improved payload capacities, and enhanced obstacle avoidance, making them suitable for diverse ecological environments. The ability to process vast amounts of visual and thermal data using machine learning algorithms allows for automated species identification, population estimation, and behavioral analysis. These innovations not only enhance data quality but also reduce operational costs, further accelerating the adoption of drone-assisted census methods across multiple regions and applications.

From a regional perspective, North America and Europe are leading the market, supported by strong research infrastructure, proactive conservation policies, and substantial funding for environmental initiatives. The Asia Pacific region is emerging as a high-growth market, fueled by increasing awareness of biodiversity loss, expanding protected areas, and rapid technological adoption. Latin America and the Middle East & Africa, with their rich biodiversity and expansive wildlife reserves, are also witnessing growing investments in drone-based monitoring solutions. However, regional disparities in regulatory frameworks, technological access, and funding availability continue to influence market dynamics, shaping the competitive landscape and growth opportunities across different geographies.

Drone Type Analysis

The Census data API provides access to the most comprehensive set of data on current month and cumulative year-to-date imports using the North American Industry Classification System (NAICS). The NAICS endpoint in the Census data API also provides value, shipping weight, and method of transportation totals at the district level for all U.S. trading partners. The Census data API will help users research new markets for their products, establish pricing structures for potential export markets, and conduct economic planning. If you have any questions regarding U.S. international trade data, please call us at 1(800)549-0595 option #4 or email us at eid.international.trade.data@census.gov.

This table is part of a series of tables that present a portrait of Canada based on the various census topics. The tables range in complexity and levels of geography. Content varies from a simple overview of the country to complex cross-tabulations; the tables may also cover several censuses.