Annual Housing Unit Estimates for the United States, States, and Counties: April 1, 2010 to July 1, 2019 // 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 // 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., V2019) 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 2020 Census Demographic and Housing Characteristics Noisy Measurement File is an intermediate output of the 2020 Census Disclosure Avoidance System (DAS) TopDown Algorithm (TDA) (as described in Abowd, J. et al [2022], and implemented in DAS_2020_DHC_Production_Code/das_decennial/programs/engine/primitives.py at main uscensusbureau/DAS_2020_DHC_Production_Code (github.com) The 2020 Census Demographic and Housing Characteristics Noisy Measurement File includes zero-Concentrated Differentially Private (zCDP) (Bun, M. and Steinke, T [2016]) noisy measurements, implemented via the discrete Gaussian mechanism (Cannone C., et al., [2023] ), which added positive or negative integer-valued noise to each of the resulting counts. These are estimated counts of individuals and housing units included in the 2020 Census Edited File (CEF), which includes confidential data collected in the 2020 Census of Population and Housing. The noisy measurements included in this file were subsequently post-processed by the TopDown Algorithm (TDA) to produce the Census Demographic and Housing Characteristics Summary File. In addition to the noisy measurements, constraints based on invariant calculations --- counts computed without noise --- are also included (with the exception of the state-level total populations, which can be sourced separately from data.census.gov). The Noisy Measurement File was produced using the official "production settings," the final set of algorithmic parameters and privacy-loss budget allocations that were used to produce the 2020 Census Redistricting Data (P.L. 94-171) Summary File and the 2020 Census Demographic and Housing Characteristics File. The noisy measurements are produced in an early stage of the TDA. Afterward, these noisy measurements are post-processed to ensure internal and hierarchical consistency within the resulting tables. The Census Bureau has released these noisy measurements to enable data users to evaluate the impact of disclosure avoidance variability on 2020 Census data. The 2020 Census Demographic and Housing Characteristics (DHC) Noisy Measurement File has been cleared for public dissemination by the Census Bureau Disclosure Review Board (CBDRB-FY22-DSEP-004). These data are available for download (i.e. not restricted access). Due to their size, they must be downloaded through the link on this metadata page and not through the standard ICPSR download. The link will take you to the Globus site where these data are housed. A README file is located in the Globus repository. Please refer to that for pertinent information. The Globus holding site requires users to create an account to access these data. Accounts can be created through existing institutional access and by personal access. Please see the Globus "How to get Started" page for more information.

The AHS is the largest, regular national housing sample survey in the United States. The U.S. Census Bureau conducts the AHS to obtain up-to-date housing statistics for the Department of Housing and Urban Development (HUD). The AHS national survey was conducted annually from 1973-1981 and biennially (every two years) since 1983. Metropolitan area surveys have been conducted annually or biennially since 1974.

Context :

The United States census count (also known as the Decennial Census of Population and Housing) is a count of every resident of the US. The census occurs every 10 years and is conducted by the United States Census Bureau. Census data is publicly available through the census website, but much of the data is available in summarized data and graphs. The raw data is often difficult to obtain, is typically divided by region, and it must be processed and combined to provide information about the nation as a whole. Update frequency: Historic (none)

Dataset source

United States Census Bureau

Sample Query

SELECT zipcode, population FROM bigquery-public-data.census_bureau_usa.population_by_zip_2010 WHERE gender = '' ORDER BY population DESC LIMIT 10

Terms of use

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.

See the GCP Marketplace listing for more details and sample queries: https://console.cloud.google.com/marketplace/details/united-states-census-bureau/us-census-data

Although the American Community Survey (ACS) produces population, demographic and housing unit estimates, the decennial census is the official source of population totals for April 1st of each decennial year. In between censuses, the Census Bureau's Population Estimates Program produces and disseminates the official estimates of the population for the nation, states, counties, cities, and towns and estimates of housing units and the group quarters population for states and counties..Information about the American Community Survey (ACS) can be found on the ACS website. Supporting documentation including code lists, subject definitions, data accuracy, and statistical testing, and a full list of ACS tables and table shells (without estimates) can be found on the Technical Documentation section of the ACS website.Sample size and data quality measures (including coverage rates, allocation rates, and response rates) can be found on the American Community Survey website in the Methodology section..Source: U.S. Census Bureau, 2023 American Community Survey 1-Year Estimates.ACS data generally reflect the geographic boundaries of legal and statistical areas as of January 1 of the estimate year. For more information, see Geography Boundaries by Year..Data are based on a sample and are subject to sampling variability. The degree of uncertainty for an estimate arising from sampling variability is represented through the use of a margin of error. The value shown here is the 90 percent margin of error. The margin of error can be interpreted roughly as providing a 90 percent probability that the interval defined by the estimate minus the margin of error and the estimate plus the margin of error (the lower and upper confidence bounds) contains the true value. In addition to sampling variability, the ACS estimates are subject to nonsampling error (for a discussion of nonsampling variability, see ACS Technical Documentation). The effect of nonsampling error is not represented in these tables..Users must consider potential differences in geographic boundaries, questionnaire content or coding, or other methodological issues when comparing ACS data from different years. Statistically significant differences shown in ACS Comparison Profiles, or in data users' own analysis, may be the result of these differences and thus might not necessarily reflect changes to the social, economic, housing, or demographic characteristics being compared. For more information, see Comparing ACS Data..Estimates of urban and rural populations, housing units, and characteristics reflect boundaries of urban areas defined based on 2020 Census data. As a result, data for urban and rural areas from the ACS do not necessarily reflect the results of ongoing urbanization..Explanation of Symbols:- The estimate could not be computed because there were an insufficient number of sample observations. For a ratio of medians estimate, one or both of the median estimates falls in the lowest interval or highest interval of an open-ended distribution. For a 5-year median estimate, the margin of error associated with a median was larger than the median itself.N The estimate or margin of error cannot be displayed because there were an insufficient number of sample cases in the selected geographic area. (X) The estimate or margin of error is not applicable or not available.median- The median falls in the lowest interval of an open-ended distribution (for example "2,500-")median+ The median falls in the highest interval of an open-ended distribution (for example "250,000+").** The margin of error could not be computed because there were an insufficient number of sample observations.*** The margin of error could not be computed because the median falls in the lowest interval or highest interval of an open-ended distribution.***** A margin of error is not appropriate because the corresponding estimate is controlled to an independent population or housing estimate. Effectively, the corresponding estimate has no sampling error and the margin of error may be treated as zero.

The Decennial Census provides population estimates and demographic information on residents of the United States.

The Census Summary Files contain detailed tables on responses to the decennial census. Data tables in Summary File 1 provide information on population and housing characteristics, including cross-tabulations of age, sex, households, families, relationship to householder, housing units, detailed race and Hispanic or Latino origin groups, and group quarters for the total population. Summary File 2 contains data tables on population and housing characteristics as reported by housing unit.

Researchers at NYU Langone Health can find guidance for the use and analysis of Census Bureau data on the Population Health Data Hub (listed under "Other Resources"), which is accessible only through the intranet portal with a valid Kerberos ID (KID).

The 2010 Census Production Settings Demographic and Housing Characteristics Demonstration Noisy Measurement File (2023-04-03) is an intermediate output of the 2020 Census Disclosure Avoidance System (DAS) TopDown Algorithm (TDA) (as described in Abowd, J. et al [2022], and implemented in DAS 2020 Redistricting Production Code). The NMF was produced using the official "production settings," the final set of algorithmic parameters and privacy-loss budget allocations, that were used to produce the 2020 Census Redistricting Data (P.L. 94-171) Summary File and the 2020 Census Demographic and Housing Characteristics File. The NMF consists of the full set of privacy-protected statistical queries (counts of individuals or housing units with particular combinations of characteristics) of confidential 2010 Census data relating to the 2010 Demonstration Data Products Suite - Redistricting and Demographic and Housing Characteristics File - Production Settings (2023-04-03). These statistical queries, called "noisy measurements" were produced under the zero-Concentrated Differential Privacy framework (Bun, M. and Steinke, T [2016]; see also Dwork C. and Roth, A. [2014]) implemented via the discrete Gaussian mechanism (Cannone C., et al., [2023]), which added positive or negative integer-valued noise to each of the resulting counts. The noisy measurements are an intermediate stage of the TDA prior to the post-processing the TDA then performs to ensure internal and hierarchical consistency within the resulting tables. The Census Bureau has released these 2010 Census demonstration data to enable data users to evaluate the expected impact of disclosure avoidance variability on 2020 Census data. The 2010 Census Production Settings Demographic and Housing Characteristics (DHC) Demonstration Noisy Measurement File (2023-04-03) has been cleared for public dissemination by the Census Bureau Disclosure Review Board (CBDRB-FY22-DSEP-004). The 2010 Census Production Settings Demographic and Housing Characteristics Demonstration Noisy Measurement File (2023-04-03) includes zero-Concentrated Differentially Private (zCDP) (Bun, M. and Steinke, T [2016]) noisy measurements, implemented via the discrete Gaussian mechanism. These are estimated counts of individuals and housing units included in the 2010 Census Edited File (CEF), which includes confidential data initially collected in the 2010 Census of Population and Housing. The noisy measurements included in this file were subsequently post-processed by the TopDown Algorithm (TDA) to produce the 2010 Census Production Settings Privacy-Protected Microdata File - Redistricting (P.L. 94-171) and Demographic and Housing Characteristics File (2023-04-03) (Demonstration Data Products Suite/2023-04-03/). As these 2010 Census demonstration data are intended to support study of the design and expected impacts of the 2020 Disclosure Avoidance System, the 2010 CEF records were pre-processed before application of the zCDP framework. This pre-processing converted the 2010 CEF records into the input-file format, response codes, and tabulation categories used for the 2020 Census, which differ in substantive ways from the format, response codes, and tabulation categories originally used for the 2010 Census. The NMF provides estimates of counts of persons in the CEF by various characteristics and combinations of characteristics including their reported race and ethnicity, whether they were of voting age, whether they resided in a housing unit or one of 7 group quarters types, and their census block of residence after the addition of discrete Gaussian noise (with the scale parameter determined by the privacy-loss budget allocation for that particular query under zCDP). Noisy measurements of the counts of occupied and vacant housing units by census block are also included. Lastly, data on constraints--information into which no noise was infused by the Disclosure Avoidance System (DAS) and used by the TDA to post-process the noisy measurements into the 2010 Census Production Settings Privacy-Protected Microdata File - Redistricting (P.L. 94-171) and Demographic and Housing Characteristics File (2023-04-03) --are provided. These data are available for download (i.e. not restricted access). Due to their size, they must be downloaded through the link on this metadata page and not through the standard ICPSR downloa

This product will include topics such as age, sex, race, Hispanic or Latino origin, household type, family type, relationship to householder, group quarters population, housing occupancy and housing tenure. Some tables will be iterated by race and ethnicity.

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.

Abstract

IPUMS-International is an effort to inventory, preserve, harmonize, and disseminate census microdata from around the world. The project has collected the world's largest archive of publicly available census samples. The data are coded and documented consistently across countries and over time to facillitate comparative research. IPUMS-International makes these data available to qualified researchers free of charge through a web dissemination system.

The IPUMS project is a collaboration of the Minnesota Population Center, National Statistical Offices, and international data archives. Major funding is provided by the U.S. National Science Foundation and the Demographic and Behavioral Sciences Branch of the National Institute of Child Health and Human Development. Additional support is provided by the University of Minnesota Office of the Vice President for Research, the Minnesota Population Center, and Sun Microsystems.

Geographic coverage

National coverage

Analysis unit

Households and Group Quarters

UNITS IDENTIFIED: - Dwellings: No - Vacant units: Yes - Households: Yes - Individuals: Yes - Group quarters: Yes

UNIT DESCRIPTIONS: - Households: Dwelling places with fewer than ten persons unrelated to a household head, excluding institutions and transient quarters. - Group quarters: Institutions, transient quarters, and dwelling places with ten or more persons unrelated to a household head.

Universe

Residents of the 50 states (not the outlying areas).

Kind of data

Census/enumeration data [cen]

Sampling procedure

MICRODATA SOURCE: U.S. Census Bureau

SAMPLE UNIT: Household

SAMPLE FRACTION: 5%

SAMPLE SIZE (person records): 11,343,120

Mode of data collection

Face-to-face [f2f]

Research instrument

The 1980 census employed a single long form questionnaire completed by one-half of housing units in places with a population under 2,500 and one-sixth of other housing units.

Response rate

UNDERCOUNT: No official estimates

This documentation has been created by ICPSR for the restricted version of Census 1980 distributed by the Bureau of the Census. The restricted data is based on questions from the long form questionnaire, and was collected from one in six households in the United States. Topics covered include income, ancestry, citizenship status, home values, commute time to work, occupation, education, veteran status, language ability, migration, place of birth, and many others. The documentation available here provides files summaries, variable information, and facilitates sorting of the data by race or by a wide variety of geographical units. ICPSR is not distributing the restricted data, only the documentation for the restricted data. Users who wish to access the restricted data can find more information at the Michigan Census Research Data Center Web site. Users should also note that the data for the public versions of Census 1980 are available from ICPSR.

Public Law 94-171, enacted in 1975, requires the Census Bureau to provide redistricting data in a format requested by state governments. Within one year following the 1990 decennial Census (by April 1, 1991), the Census Bureau provided the governor and legislature of each state with the population data needed to redraw legislative districts. This collection contains the same substantive and geographic variables as the original Public Law 94-171 files [see CENSUS OF POPULATION AND HOUSING, 1990 [UNITED STATES]: PUBLIC LAW (P.L.) 94-171 DATA (ICPSR 9516)] but with the population counts adjusted for undernumeration. Adjusted Public Law 94-171 counts are supplied for a sample of one-half of blocks in the United States and a complete selection of areas with 1,000 or more persons. Each state file provides data for the state and its subareas in the following order: state, county, voting district, county subdivision, place, and block. Additionally, complete summaries are provided for the following geographic areas: county subdivision, place, consolidated city, state portion of American Indian and Alaska Native area, and county portion of American Indian and Alaska Native area. Area characteristics such as land area, water area, latitude, and longitude are provided. Summary statistics are provided for all persons, for persons 18 years old and over, and for housing units in the geographic areas. Counts by race and by Hispanic and non-Hispanic origin are also recorded.

The United States census count (also known as the Decennial Census of Population and Housing) is a count of every resident of the US. The census occurs every 10 years and is conducted by the United States Census Bureau. Census data is publicly available through the census website, but much of the data is available in summarized data and graphs. The raw data is often difficult to obtain, is typically divided by region, and it must be processed and combined to provide information about the nation as a whole. The United States census dataset includes nationwide population counts from the 2000 and 2010 censuses. Data is broken out by gender, age and location using zip code tabular areas (ZCTAs) and GEOIDs. ZCTAs are generalized representations of zip codes, and often, though not always, are the same as the zip code for an area. GEOIDs are numeric codes that uniquely identify all administrative, legal, and statistical geographic areas for which the Census Bureau tabulates data. GEOIDs are useful for correlating census data with other censuses and surveys. This public dataset is hosted in Google BigQuery and is included in BigQuery's 1TB/mo of free tier processing. This means that each user receives 1TB of free BigQuery processing every month, which can be used to run queries on this public dataset. Watch this short video to learn how to get started quickly using BigQuery to access public datasets. What is BigQuery .

Although the American Community Survey (ACS) produces population, demographic and housing unit estimates, the decennial census is the official source of population totals for April 1st of each decennial year. In between censuses, the Census Bureau's Population Estimates Program produces and disseminates the official estimates of the population for the nation, states, counties, cities, and towns and estimates of housing units and the group quarters population for states and counties..Information about the American Community Survey (ACS) can be found on the ACS website. Supporting documentation including code lists, subject definitions, data accuracy, and statistical testing, and a full list of ACS tables and table shells (without estimates) can be found on the Technical Documentation section of the ACS website.Sample size and data quality measures (including coverage rates, allocation rates, and response rates) can be found on the American Community Survey website in the Methodology section..Source: U.S. Census Bureau, 2023 American Community Survey 1-Year Estimates.ACS data generally reflect the geographic boundaries of legal and statistical areas as of January 1 of the estimate year. For more information, see Geography Boundaries by Year..Users must consider potential differences in geographic boundaries, questionnaire content or coding, or other methodological issues when comparing ACS data from different years. Statistically significant differences shown in ACS Comparison Profiles, or in data users' own analysis, may be the result of these differences and thus might not necessarily reflect changes to the social, economic, housing, or demographic characteristics being compared. For more information, see Comparing ACS Data..Data are based on a sample and are subject to sampling variability. The degree of uncertainty for an estimate arising from sampling variability is represented through the use of a margin of error. The value shown here is the 90 percent margin of error. The margin of error can be interpreted roughly as providing a 90 percent probability that the interval defined by the estimate minus the margin of error and the estimate plus the margin of error (the lower and upper confidence bounds) contains the true value. In addition to sampling variability, the ACS estimates are subject to nonsampling error (for a discussion of nonsampling variability, see ACS Technical Documentation). The effect of nonsampling error is not represented in these tables..Ancestry listed in this table refers to the total number of people who responded with a particular ancestry; for example, the estimate given for German represents the number of people who listed German as either their first or second ancestry. This table lists only the largest ancestry groups; see the Detailed Tables for more categories. Race and Hispanic origin groups are not included in this table because data for those groups come from the Race and Hispanic origin questions rather than the ancestry question (see Demographic Table)..Data for year of entry of the native population reflect the year of entry into the U.S. by people who were born in Puerto Rico or U.S. Island Areas or born outside the U.S. to a U.S. citizen parent and who subsequently moved to the U.S..The category "with a broadband Internet subscription" refers to those who said "Yes" to at least one of the following types of Internet subscriptions: Broadband such as cable, fiber optic, or DSL; a cellular data plan; satellite; a fixed wireless subscription; or other non-dial up subscription types..An Internet "subscription" refers to a type of service that someone pays for to access the Internet such as a cellular data plan, broadband such as cable, fiber optic or DSL, or other type of service. This will normally refer to a service that someone is billed for directly for Internet alone or sometimes as part of a bundle.."With a computer" includes those who said "Yes" to at least one of the following types of computers: Desktop or laptop; smartphone; tablet or other portable wireless computer; or some other type of computer..Estimates of urban and rural populations, housing units, and characteristics reflect boundaries of urban areas defined based on 2020 Census data. As a result, data for urban and rural areas from the ACS do not necessarily reflect the results of ongoing urbanization..Explanation of Symbols:- The estimate could not be computed because there were an insufficient number of sample observations. For a ratio of medians estimate, one or both of the median estimates falls in the lowest interval or highest interval of an open-ended distribution. For a 5-year median estimate, the margin of error associated with a median was larger than the median itself.N The estimate or margin of error cannot be displayed because there were an insufficient number of sample cases in the selected geographic area. (X) The estimate or margin of error is not applicable or not available.median- ...

This layer shows housing units by tenure (owner or renter), and vacancy status data from the 2020 Census Demographic and Housing Characteristics. This is shown by Nation, Consolidated City, Census Designated Place, Incorporated Place boundaries. Each geography layer contains a common set of Census counts based on available attributes from the U.S. Census Bureau. There are also additional calculated attributes related to this topic, which can be mapped or used within analysis.   To see the full list of attributes available in this service, go to the "Data" tab above, and then choose "Fields" at the top right. Each attribute contains definitions, additional details, and the formula for calculated fields in the field description.Vintage of boundaries and attributes: 2020 Demographic and Housing Characteristics Table(s): P1, H1, H2, H3, H4, H4B, H4C, H4D, H4E, H4F, H4G, H4H, H4I, H5, H9, H12, H12B, H12C, H12D, H12E, H12F, H12G, H12H, H12I, H13, H13B, H13C, H13D, H13E, H13F, H13G, H13H, H13I, H15, HCT2 (Not all lines of these DHC tables are available in this feature layer.)Data downloaded from: U.S. Census Bureau’s data.census.gov siteDate the Data was Downloaded: May 25, 2023Geography Levels included: Nation, Consolidated City, Census Designated Place, Incorporated PlaceNational Figures: included in Nation layer The United States Census Bureau Demographic and Housing Characteristics: 2020 Census Results 2020 Census Data Quality Geography & 2020 Census Technical Documentation Data Table Guide: includes the final list of tables, lowest level of geography by table and table shells for the Demographic Profile and Demographic and Housing Characteristics.News & Updates This layer is ready to be used in ArcGIS Pro, ArcGIS Online and its configurable apps, Story Maps, dashboards, Notebooks, Python, custom apps, and mobile apps. Data can also be exported for offline workflows. Please cite the U.S. Census Bureau when using this data. Data Processing Notes: These 2020 Census boundaries come from the US Census TIGER geodatabases. These are Census boundaries with water and/or coastlines erased for cartographic and mapping purposes. For Census tracts and block groups, the water cutouts are derived from a subset of the 2020 Areal Hydrography boundaries offered by TIGER. Water bodies and rivers which are 50 million square meters or larger (mid to large sized water bodies) are erased from the tract and block group boundaries, as well as additional important features. For state and county boundaries, the water and coastlines are derived from the coastlines of the 2020 500k TIGER Cartographic Boundary Shapefiles. These are erased to more accurately portray the coastlines and Great Lakes. The original AWATER and ALAND fields are unchanged and available as attributes within the data table (units are square meters).  The layer contains all US states, Washington D.C., and Puerto Rico. Census tracts with no population that occur in areas of water, such as oceans, are removed from this data service (Census Tracts beginning with 99). Block groups that fall within the same criteria (Block Group denoted as 0 with no area land) have also been removed.Percentages and derived counts, are calculated values (that can be identified by the "_calc_" stub in the field name). Field alias names were created based on the Table Shells file available from the Data Table Guide for the Demographic Profile and Demographic and Housing Characteristics. Not all lines of all tables listed above are included in this layer. Duplicative counts were dropped. For example, P0030001 was dropped, as it is duplicative of P0010001.To protect the privacy and confidentiality of respondents, their data has been protected using differential privacy techniques by the U.S. Census Bureau.

This dataset was created by EIDC on Thu, 16 Jun 2022 14:12:12 GMT.

This layer shows households data from the 2020 Census Demographic and Housing Characteristics. This is shown by Nation, Consolidated City, Census Designated Place, Incorporated Place boundaries. Each geography layer contains a common set of Census counts based on available attributes from the U.S. Census Bureau. There are also additional calculated attributes related to this topic, which can be mapped or used within analysis.   To see the full list of attributes available in this service, go to the "Data" tab above, and then choose "Fields" at the top right. Each attribute contains definitions, additional details, and the formula for calculated fields in the field description.Vintage of boundaries and attributes: 2020 Demographic and Housing Characteristics Table(s): P1, H1, H3, P16, P16B, P16C, P16D, P16E, P16F, P16G, P16H, P16I, P19, P20, PCT5, PCT6, PCT14, PCT14B, PCT14C, PCT14D, PCT14E, PCT14F, PCT14G, PCT14H, PCT14I, PCT15, H14, H9, H12, H15 Data downloaded from: U.S. Census Bureau’s data.census.gov siteDate the Data was Downloaded: May 25, 2023Geography Levels included: Nation, Consolidated City, Census Designated Place, Incorporated PlaceNational Figures: included in Nation layer The United States Census Bureau Demographic and Housing Characteristics: 2020 Census Results 2020 Census Data Quality Geography & 2020 Census Technical Documentation Data Table Guide: includes the final list of tables, lowest level of geography by table and table shells for the Demographic Profile and Demographic and Housing Characteristics.News & Updates This layer is ready to be used in ArcGIS Pro, ArcGIS Online and its configurable apps, Story Maps, dashboards, Notebooks, Python, custom apps, and mobile apps. Data can also be exported for offline workflows. Please cite the U.S. Census Bureau when using this data. Data Processing Notes: These 2020 Census boundaries come from the US Census TIGER geodatabases. These are Census boundaries with water and/or coastlines erased for cartographic and mapping purposes. For Census tracts and block groups, the water cutouts are derived from a subset of the 2020 Areal Hydrography boundaries offered by TIGER. Water bodies and rivers which are 50 million square meters or larger (mid to large sized water bodies) are erased from the tract and block group boundaries, as well as additional important features. For state and county boundaries, the water and coastlines are derived from the coastlines of the 2020 500k TIGER Cartographic Boundary Shapefiles. These are erased to more accurately portray the coastlines and Great Lakes. The original AWATER and ALAND fields are unchanged and available as attributes within the data table (units are square meters).  The layer contains all US states, Washington D.C., and Puerto Rico. Census tracts with no population that occur in areas of water, such as oceans, are removed from this data service (Census Tracts beginning with 99). Block groups that fall within the same criteria (Block Group denoted as 0 with no area land) have also been removed.Percentages and derived counts, are calculated values (that can be identified by the "_calc_" stub in the field name). Field alias names were created based on the Table Shells file available from the Data Table Guide for the Demographic Profile and Demographic and Housing Characteristics. Not all lines of all tables listed above are included in this layer. Duplicative counts were dropped. For example, P0030001 was dropped, as it is duplicative of P0010001.To protect the privacy and confidentiality of respondents, their data has been protected using differential privacy techniques by the U.S. Census Bureau.

Although the American Community Survey (ACS) produces population, demographic and housing unit estimates, the decennial census is the official source of population totals for April 1st of each decennial year. In between censuses, the Census Bureau's Population Estimates Program produces and disseminates the official estimates of the population for the nation, states, counties, cities, and towns and estimates of housing units and the group quarters population for states and counties..Information about the American Community Survey (ACS) can be found on the ACS website. Supporting documentation including code lists, subject definitions, data accuracy, and statistical testing, and a full list of ACS tables and table shells (without estimates) can be found on the Technical Documentation section of the ACS website.Sample size and data quality measures (including coverage rates, allocation rates, and response rates) can be found on the American Community Survey website in the Methodology section..Source: U.S. Census Bureau, 2023 American Community Survey 1-Year Estimates.ACS data generally reflect the geographic boundaries of legal and statistical areas as of January 1 of the estimate year. For more information, see Geography Boundaries by Year..Data are based on a sample and are subject to sampling variability. The degree of uncertainty for an estimate arising from sampling variability is represented through the use of a margin of error. The value shown here is the 90 percent margin of error. The margin of error can be interpreted roughly as providing a 90 percent probability that the interval defined by the estimate minus the margin of error and the estimate plus the margin of error (the lower and upper confidence bounds) contains the true value. In addition to sampling variability, the ACS estimates are subject to nonsampling error (for a discussion of nonsampling variability, see ACS Technical Documentation). The effect of nonsampling error is not represented in these tables..Users must consider potential differences in geographic boundaries, questionnaire content or coding, or other methodological issues when comparing ACS data from different years. Statistically significant differences shown in ACS Comparison Profiles, or in data users' own analysis, may be the result of these differences and thus might not necessarily reflect changes to the social, economic, housing, or demographic characteristics being compared. For more information, see Comparing ACS Data..The health insurance coverage category names were modified in 2010. See https://www.census.gov/topics/health/health-insurance/about/glossary.html#par_textimage_18 for a list of the insurance type definitions..Beginning in 2017, selected variable categories were updated, including age-categories, income-to-poverty ratio (IPR) categories, and the age universe for certain employment and education variables. See user note entitled "Health Insurance Table Updates" for further details..Estimates of urban and rural populations, housing units, and characteristics reflect boundaries of urban areas defined based on 2020 Census data. As a result, data for urban and rural areas from the ACS do not necessarily reflect the results of ongoing urbanization..Explanation of Symbols:- The estimate could not be computed because there were an insufficient number of sample observations. For a ratio of medians estimate, one or both of the median estimates falls in the lowest interval or highest interval of an open-ended distribution. For a 5-year median estimate, the margin of error associated with a median was larger than the median itself.N The estimate or margin of error cannot be displayed because there were an insufficient number of sample cases in the selected geographic area. (X) The estimate or margin of error is not applicable or not available.median- The median falls in the lowest interval of an open-ended distribution (for example "2,500-")median+ The median falls in the highest interval of an open-ended distribution (for example "250,000+").** The margin of error could not be computed because there were an insufficient number of sample observations.*** The margin of error could not be computed because the median falls in the lowest interval or highest interval of an open-ended distribution.***** A margin of error is not appropriate because the corresponding estimate is controlled to an independent population or housing estimate. Effectively, the corresponding estimate has no sampling error and the margin of error may be treated as zero.

The included data are from the Housing Tenure & Costs tables of the US Census Bureau's American Community Survey's (ACS) 5 year estimates by County. It includes data on Housing Units, Occupancy Status, Tenure, Mortgage Status, and Housing Costs. For additional information about the data, visit https://www.census.gov/data/developers/data-sets/acs-5year.html.

Graph and download economic data for Median Sales Price of Houses Sold for the United States (MSPUS) from Q1 1963 to Q2 2025 about sales, median, housing, and USA.