This profile presents information from the 2021 Census of Population for various levels of geography, including provinces and territories, census metropolitan areas, communities and census tracts. Data are from the 2021 Census of Population and are available according to the major releases of the 2021 Census release dates: February 9, 2022 – Population and dwelling counts; April 27, 2022 – Age, Sex at birth and gender, Type of dwelling; July 13, 2022 – Families, households and marital status, Canadian military experience, Income; August 17, 2022 – Language; September 21, 2022 – Indigenous peoples, Housing; October 26, 2022 – Immigration, place of birth, and citizenship, Ethnocultural and religious diversity, Mobility and migration; November 30, 2022 – Education, Labour, Language of work, Commuting, Instruction in the official minority language. Geography: •Canada, Provinces and Territories •Census Metropolitan Areas and Census Agglomerations •Census Metropolitan Areas, Census Agglomerations and Census Subdivisions •Census Divisions •Canada, Provinces, Territories, Census Divisions and Census Subdivisions •Canada, Provinces and Territories, Census Divisions, Census Subdivisions and Dissemination Areas •Census Metropolitan Areas, Tracted Census Agglomerations and Census Tracts •Canada, Provinces, Territories and Economic Regions •Population Centres •Canada, Provinces and Territories and Federal Electoral Districts (2013 Representation Order) •Designated Places •Aggregate Dissemination Areas

Census 2021 occupation data for people aged 16 years and older and in employment, by age and sex, is part of The occupations and industries most dependent on older and younger workers: March 2021, a release of results from the 2021 Census for England and Wales. Figures may differ slightly in future releases because of the impact of removing rounding and applying further statistical processes.

Some shorthand may be used in this workbook. Individual estimates suppressed with "[c]" relate to statistics based on a small number of respondents (< 10). Such values have been suppressed on quality grounds and to maintain confidentiality.

Armed forces personnel and defence employees are included in the census and recorded as usually resident using the standard definitions. The instructions given to personnel on how to respond to the census mean that this group cannot be reliably identified in census data on industry and occupation. Information on the size and characteristics of the UK armed forces population is produced by the Ministry of Defence (MOD).

Quality assurance information can be found here

Occupation

Occupation is classified using the Standard Occupation Classification 2020 version. Details can be found here.

Industry

Industry is classified using the Standard Industrial Classifications 2007 version. Details can be found here.

Age

This is someone’s age on their last birthday on Census Day, 21 March 2021 in England and Wales.

Topics covered in the 2021 UK Census included:

• demography and migration
• ethnic group, national identity, language and religion
• labour market and travel to work
• housing
• education
• health, disability, and unpaid care
• Welsh and other languages
• UK armed forces veterans
• sexual orientation and gender identity.

The 2021 Census: Safeguarded Individual Microdata Sample at Grouped Local Authority Level dataset consists of a random sample of 5% of person records from the 2021 Census. It includes records for 3,021,611 persons. These data cover England and Wales only. The lowest level of geography is grouped local authority. This means groups of local authorities or single local authorities where the population reaches at least 120,000 persons. The dataset contains 87 variables and a low level of detail.

Census Microdata

Microdata are small samples of individual records from a single census from which identifying information have been removed. They contain a range of individual and household characteristics and can be used to carry out analysis not possible from standard census outputs, such as:

• creating tables using bespoke variable combinations
• investigating specific combinations of variables or categories in a high level of detail
• conducting non-tabular statistical analyses on record-level data.

The microdata samples are designed to protect the confidentiality of individuals and households. This is done by applying access controls and removing information that might directly identify a person, such as names, addresses and date of birth. Record swapping is applied to the census data used to create the microdata samples. This is a statistical disclosure control (SDC) method, which makes very small changes to the data to prevent the identification of individuals. The microdata samples use further SDC methods, such as collapsing variables and restricting detail. The samples also include records that have been edited to prevent inconsistent data and contain imputed persons, households, and data values. To protect confidentiality, imputation flags are not included in any 2021 Census microdata sample.

This file contains the National Statistics Postcode Lookup (NSPL) for the United Kingdom as at November 2024 in Comma Separated Variable (CSV) and ASCII text (TXT) formats. To download the zip file click the Download button. The NSPL relates both current and terminated postcodes to a range of current statutory geographies via ‘best-fit’ allocation from the 2021 Census Output Areas (national parks and Workplace Zones are exempt from ‘best-fit’ and use ‘exact-fit’ allocations) for England, Wales, Scotland and Northern Ireland. It supports the production of area-based statistics from postcoded data. The NSPL is produced by ONS Geography, who provide geographic support to the Office for National Statistics (ONS) and geographic services used by other organisations. The NSPL is issued quarterly. (File size - 191 MB).N.B. From the next release (February 2025) this will be known simply as the National Statistics Postcode Lookup (NSPL).[10/12/2024: Updated to correct county codes for all UAs in England to pseudo code E99999999.]

Although the American Community Survey (ACS) produces population, demographic and housing unit estimates, it is the Census Bureau's Population Estimates Program that produces and disseminates the official estimates of the population for the nation, states, counties, cities, and towns and estimates of housing units for states and counties..Supporting documentation on code lists, subject definitions, data accuracy, and statistical testing can be found on the American Community Survey website in the Technical Documentation section.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, 2021 American Community Survey 1-Year Estimates.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..Employment and unemployment estimates may vary from the official labor force data released by the Bureau of Labor Statistics because of differences in survey design and data collection. For guidance on differences in employment and unemployment estimates from different sources go to Labor Force Guidance..The 2021 American Community Survey (ACS) data generally reflect the March 2020 Office of Management and Budget (OMB) delineations of metropolitan and micropolitan statistical areas. In certain instances the names, codes, and boundaries of the principal cities shown in ACS tables may differ from the OMB delineations due to differences in the effective dates of the geographic entities..Estimates of urban and rural populations, housing units, and characteristics reflect boundaries of urban areas defined based on Census 2010 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.

This dataset contains model-based census tract-level estimates for the PLACES 2021 release. PLACES is the expansion of the original 500 Cities project and covers the entire United States—50 states and the District of Columbia (DC)—at county, place, census tract, and ZIP Code Tabulation Area (ZCTA) levels. It represents a first-of-its kind effort to release information uniformly on this large scale for local areas at 4 geographic levels. Estimates were provided by the Centers for Disease Control and Prevention (CDC), Division of Population Health, Epidemiology and Surveillance Branch. PLACES was funded by the Robert Wood Johnson Foundation (RWJF) in conjunction with the CDC Foundation. The dataset includes estimates for 29 measures: 4 chronic disease-related health risk behaviors, 13 health outcomes, 3 health status, and 9 on use of preventive services. These estimates can be used to identify emerging health problems and to help develop and carry out effective, targeted public health prevention activities. Because the small area model cannot detect effects due to local interventions, users are cautioned against using these estimates for program or policy evaluations. Data sources used to generate these model-based estimates include Behavioral Risk Factor Surveillance System (BRFSS) 2019 or 2018 data, Census Bureau 2010 population data, and American Community Survey (ACS) 2015–019 or 2014–2018 estimates. The 2021 release uses 2019 BRFSS data for 22 measures and 2018 BRFSS data for 7 measures (all teeth lost, dental visits, mammograms, cervical cancer screening, colorectal cancer screening, core preventive services among older adults, and sleeping less than 7 hours a night). Seven measures are based on the 2018 BRFSS because the relevant questions are only asked every other year in the BRFSS. More information about the methodology can be found at www.cdc.gov/places.

Although the American Community Survey (ACS) produces population, demographic and housing unit estimates, it is the Census Bureau's Population Estimates Program that produces and disseminates the official estimates of the population for the nation, states, counties, cities, and towns and estimates of housing units for states and counties..Supporting documentation on code lists, subject definitions, data accuracy, and statistical testing can be found on the American Community Survey website in the Technical Documentation section.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, 2017-2021 American Community Survey 5-Year Estimates.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..Employment and unemployment estimates may vary from the official labor force data released by the Bureau of Labor Statistics because of differences in survey design and data collection. For guidance on differences in employment and unemployment estimates from different sources go to Labor Force Guidance..The 2017-2021 American Community Survey (ACS) data generally reflect the March 2020 Office of Management and Budget (OMB) delineations of metropolitan and micropolitan statistical areas. In certain instances, the names, codes, and boundaries of the principal cities shown in ACS tables may differ from the OMB delineation lists due to differences in the effective dates of the geographic entities..Estimates of urban and rural populations, housing units, and characteristics reflect boundaries of urban areas defined based on Census 2010 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.

This dataset contains model-based county-level estimates for the PLACES 2021 release. PLACES is the expansion of the original 500 Cities Project and covers the entire United States—50 states and the District of Columbia (DC)—at county, place, census tract, and ZIP Code Tabulation Area (ZCTA) levels. It represents a first-of-its kind effort to release information uniformly on this large scale for local areas at 4 geographic levels. Estimates were provided by the Centers for Disease Control and Prevention (CDC), Division of Population Health, Epidemiology and Surveillance Branch. PLACES was funded by the Robert Wood Johnson Foundation (RWJF) in conjunction with the CDC Foundation. The dataset includes estimates for 29 measures: 4 chronic disease-related health risk behaviors, 13 health outcomes, 3 health status, and 9 on using preventive services. These estimates can be used to identify emerging health problems and to help develop and carry out effective, targeted public health prevention activities. Because the small area model cannot detect effects due to local interventions, users are cautioned against using these estimates for program or policy evaluations. Data sources used to generate these model-based estimates include Behavioral Risk Factor Surveillance System (BRFSS) 2019 or 2018 data, Census Bureau 2019 or 2018 county population estimate data, and American Community Survey (ACS) 2015–2019 or 2014–2018 estimates. The 2021 release uses 2019 BRFSS data for 22 measures and 2018 BRFSS data for 7 measures (all teeth lost, dental visits, mammograms, cervical cancer screening, colorectal cancer screening, core preventive services among older adults, and sleeping less than 7 hours a night). Seven measures are based on the 2018 BRFSS because the relevant questions are only asked every other year in the BRFSS. More information about the methodology can be found at www.cdc.gov/places.

Although the American Community Survey (ACS) produces population, demographic and housing unit estimates, it is the Census Bureau's Population Estimates Program that produces and disseminates the official estimates of the population for the nation, states, counties, cities, and towns and estimates of housing units for states and counties..Supporting documentation on code lists, subject definitions, data accuracy, and statistical testing can be found on the American Community Survey website in the Technical Documentation section.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, 2021 American Community Survey 1-Year Estimates.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..Divorce estimates may vary from the divorce data released by the National Center for Health Statistics (NCHS) because of differences in methodology and data collection. NCHS uses information collected on divorce decrees from states providing them. From these administrative records, NCHS then publishes information about couples who divorced in a calendar year. In contrast, the ACS collects survey-based reports from individuals as to whether or not they divorced in the last 12 months. We recommend using caution when comparing the NCHS estimates to the ACS estimates of divorces..The 2021 American Community Survey (ACS) data generally reflect the March 2020 Office of Management and Budget (OMB) delineations of metropolitan and micropolitan statistical areas. In certain instances the names, codes, and boundaries of the principal cities shown in ACS tables may differ from the OMB delineations due to differences in the effective dates of the geographic entities..Estimates of urban and rural populations, housing units, and characteristics reflect boundaries of urban areas defined based on Census 2010 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.

This dataset provides Census 2021 estimates that classify usual residents in England and Wales by their length of residence in the UK. The estimates are as at Census Day, 21 March 2021.

This update provides unrounded migration estimates. The accompanying data are provided at Country level down to Output Areas.

Area type

Census 2021 statistics are published for a number of different geographies. These can be large, for example the whole of England, or small, for example an output area (OA), the lowest level of geography for which statistics are produced.

For higher levels of geography, more detailed statistics can be produced. When a lower level of geography is used, such as output areas (which have a minimum of 100 persons), the statistics produced have less detail. This is to protect the confidentiality of people and ensure that individuals or their characteristics cannot be identified.

Coverage

Census 2021 statistics are published for the whole of England and Wales. Data are also available in these geographic types:

• country - for example, Wales
• region - for example, London
• local authority - for example, Cornwall
• health area – for example, Clinical Commissioning Group
• statistical area - for example, MSOA or LSOA

Length of residence in the UK

The length of residence in the UK is derived from the date that a person most recently arrived to live in the UK. It does not include returning from a holiday or short stay outside the UK.

Length of residence is only applicable to usual residents who were not born in the UK. It does not include usual residents born in the UK who have emigrated and since returned -

these are recorded in the category “born in the UK”.

This web map contains layers that contain some of the more commonly used variables from the General Community Profile information from the Australian Bureau of Statistics 2021 census. Data is available for Country, Greater Capital City Statistical Area (GCCSA), Local Government Area (LGA), Statistical Area Level 1 (SA1) and 2 (SA2), and Suburb and Localities (SAL) boundaries.The General Community Profile contains a series of tables showing the characteristics of persons, families and dwellings in a selected geographic area. The data is based on place of usual residence (that is, where people usually live, rather than where they were counted on Census night). Community Profiles are excellent tools for researching, planning and analysing geographic areas for a number of social, economic and demographic characteristics.Download the data here.Data and Geography notes:View the Readme files located in the DataPacks and GeoPackages zip files.To access the 2021 DataPacks, visit https://www.abs.gov.au/census/find-census-data/datapacksGlossary terms and definitions of classifications can be found in the 2021 Census DictionaryMore information about Census data products is available at https://www.abs.gov.au/census/guide-census-data/about-census-tools/datapacksDetailed geography information: https://www.abs.gov.au/statistics/standards/australian-statistical-geography-standard-asgs-edition-3/jul2021-jun2026/main-structure-and-greater-capital-city-statistical-areas: 2021 Statistical Area Level 1 (SA1), 2021 Statistical Area Level 2 (SA2), 2021 Greater Capital City Statistical Areas (GCCSA), 2021 Australia (AUS)https://www.abs.gov.au/statistics/standards/australian-statistical-geography-standard-asgs-edition-3/jul2021-jun2026/non-abs-structures: 2021 Suburbs and Localities (SAL), 2021 Local Government Areas (LGA)Please note that there are data assumptions that should be considered when analysing the ABS Census data. These are detailed within the Census documents referenced above. These include:Registered Marital StatusIn December 2017, amendments to the Marriage Act 1961 came into effect enabling marriage equality for all couples. For 2021, registered marriages include all couples.Core Activity Need for AssistanceMeasures the number of people with a profound or severe core activity limitation. People with a profound or severe core activity limitation are those needing assistance in their day to day lives in one or more of the three core activity areas of self-care, mobility and communication because of a long-term health condition (lasting six months or more), a disability (lasting six months or more), or old age. Number of Motor VehiclesExcludes motorbikes, motor scooters and heavy vehicles.Please note that there are small random adjustments made to all cell values to protect the confidentiality of data. These adjustments may cause the sum of rows or columns to differ by small amounts from table totals.Source: Australian Bureau of Statistics

This dataset contains model-based census tract-level estimates for the PLACES 2021 release. PLACES is the expansion of the original 500 Cities project and covers the entire United States—50 states and the District of Columbia (DC)—at county, place, census tract, and ZIP Code Tabulation Area (ZCTA) levels. It represents a first-of-its kind effort to release information uniformly on this large scale for local areas at 4 geographic levels. Estimates were provided by the Centers for Disease Control and Prevention (CDC), Division of Population Health, Epidemiology and Surveillance Branch. PLACES was funded by the Robert Wood Johnson Foundation (RWJF) in conjunction with the CDC Foundation. The dataset includes estimates for 29 measures: 4 chronic disease-related health risk behaviors, 13 health outcomes, 3 health status, and 9 on use of preventive services. These estimates can be used to identify emerging health problems and to help develop and carry out effective, targeted public health prevention activities. Because the small area model cannot detect effects due to local interventions, users are cautioned against using these estimates for program or policy evaluations. Data sources used to generate these model-based estimates include Behavioral Risk Factor Surveillance System (BRFSS) 2019 or 2018 data, Census Bureau 2010 population data, and American Community Survey (ACS) 2015–019 or 2014–2018 estimates. The 2021 release uses 2019 BRFSS data for 22 measures and 2018 BRFSS data for 7 measures (all teeth lost, dental visits, mammograms, cervical cancer screening, colorectal cancer screening, core preventive services among older adults, and sleeping less than 7 hours a night). Seven measures are based on the 2018 BRFSS because the relevant questions are only asked every other year in the BRFSS. More information about the methodology can be found at www.cdc.gov/places.

Household type, Education, Disability, Language, Computer/Internet Use, and more. This service is updated annually with American Community Survey (ACS) 5-year data. Contact: District of Columbia, Office of Planning. Email: planning@dc.gov. Geography: District-wide. Current Vintage: 2021. ACS Table(s): DP02. Data downloaded from: Census Bureau's API for American Community Survey. Date of API call: January 11, 2023. National Figures: data.census.gov. Please cite the Census and ACS when using this data. Data Note from the Census: 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 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 Accuracy of the Data). The effect of nonsampling error is not represented in these tables. Data Processing Notes: This layer is updated automatically when the most current vintage of ACS data is released each year, usually in December. The layer always contains the latest available ACS 5-year estimates. It is updated annually within days of the Census Bureau's release schedule. Boundaries come from the US Census TIGER geodatabases. Boundaries are updated at the same time as the data updates (annually), and the boundary vintage appropriately matches the data vintage as specified by the Census. These are Census boundaries with water and/or coastlines clipped for cartographic purposes. For census tracts, the water cutouts are derived from a subset of the 2020 AWATER (Area Water) boundaries offered by TIGER. For state and county boundaries, the water and coastlines are derived from the coastlines of the 500k TIGER Cartographic Boundary Shapefiles. The original AWATER and ALAND fields are still available as attributes within the data table (units are square meters). Field alias names were created based on the Table Shells file available from the American Community Survey Summary File Documentation page. Data processed using R statistical package and ArcGIS Desktop. Margin of Error was not included in this layer but is available from the Census Bureau. Contact the Office of Planning for more information about obtaining Margin of Error values.

This dataset contains model-based census tract estimates. PLACES covers the entire United States—50 states and the District of Columbia—at county, place, census tract, and ZIP Code Tabulation Area levels. It provides information uniformly on this large scale for local areas at four geographic levels. Estimates were provided by the Centers for Disease Control and Prevention (CDC), Division of Population Health, Epidemiology and Surveillance Branch. PLACES was funded by the Robert Wood Johnson Foundation in conjunction with the CDC Foundation. The dataset includes estimates for 40 measures: 12 for health outcomes, 7 for preventive services use, 4 for chronic disease-related health risk behaviors, 7 for disabilities, 3 for health status, and 7 for health-related social needs. These estimates can be used to identify emerging health problems and to help develop and carry out effective, targeted public health prevention activities. Because the small area model cannot detect effects due to local interventions, users are cautioned against using these estimates for program or policy evaluations. Data sources used to generate these model-based estimates are Behavioral Risk Factor Surveillance System (BRFSS) 2022 or 2021 data, Census Bureau 2020 population data, and American Community Survey 2018–2022 estimates. The 2024 release uses 2022 BRFSS data for 36 measures and 2021 BRFSS data for 4 measures (high blood pressure, high cholesterol, cholesterol screening, and taking medicine for high blood pressure control among those with high blood pressure) that the survey collects data on every other year. More information about the methodology can be found at www.cdc.gov/places.

This web map contains layers that contain some of the more commonly used variables from the General Community Profile information from the Australian Bureau of Statistics 2021 census. Data is available for Country, Greater Capital City Statistical Area (GCCSA), Local Government Area (LGA), Statistical Area Level 1 (SA1) and 2 (SA2), and Suburb and Localities (SAL) boundaries.The General Community Profile contains a series of tables showing the characteristics of persons, families and dwellings in a selected geographic area. The data is based on place of usual residence (that is, where people usually live, rather than where they were counted on Census night). Community Profiles are excellent tools for researching, planning and analysing geographic areas for a number of social, economic and demographic characteristics.Download the data here.Data and Geography notes:View the Readme files located in the DataPacks and GeoPackages zip files.To access the 2021 DataPacks, visit https://www.abs.gov.au/census/find-census-data/datapacksGlossary terms and definitions of classifications can be found in the 2021 Census DictionaryMore information about Census data products is available at https://www.abs.gov.au/census/guide-census-data/about-census-tools/datapacksDetailed geography information: https://www.abs.gov.au/statistics/standards/australian-statistical-geography-standard-asgs-edition-3/jul2021-jun2026/main-structure-and-greater-capital-city-statistical-areas: 2021 Statistical Area Level 1 (SA1), 2021 Statistical Area Level 2 (SA2), 2021 Greater Capital City Statistical Areas (GCCSA), 2021 Australia (AUS)https://www.abs.gov.au/statistics/standards/australian-statistical-geography-standard-asgs-edition-3/jul2021-jun2026/non-abs-structures: 2021 Suburbs and Localities (SAL), 2021 Local Government Areas (LGA)Please note that there are data assumptions that should be considered when analysing the ABS Census data. These are detailed within the Census documents referenced above. These include:Registered Marital StatusIn December 2017, amendments to the Marriage Act 1961 came into effect enabling marriage equality for all couples. For 2021, registered marriages include all couples.Core Activity Need for AssistanceMeasures the number of people with a profound or severe core activity limitation. People with a profound or severe core activity limitation are those needing assistance in their day to day lives in one or more of the three core activity areas of self-care, mobility and communication because of a long-term health condition (lasting six months or more), a disability (lasting six months or more), or old age. Number of Motor VehiclesExcludes motorbikes, motor scooters and heavy vehicles.Please note that there are small random adjustments made to all cell values to protect the confidentiality of data. These adjustments may cause the sum of rows or columns to differ by small amounts from table totals.Source: Australian Bureau of Statistics

Release Date: 2024-03-14.Release Schedule:.The NES data in this file will be released on March 14, 2024...Key Table Information:.Beginning with reference year 2005, Nonemployer data are released using the Noise Infusion methodology to protect confidentiality. See Program Methodology for complete information on the coverage and methodology of the Nonemployer Statistics data series....Data Items and Other Identifying Records:.This table contains data on the total number of firms and receipts..Number of nonemployer establishments.Nonemployer sales, value of shipments, or revenue ($1,000).Noise range for nonemployer sales, value of shipments, or revenue...Geography Coverage:.The data are shown at the U.S. and State level for LFO and the U.S. level for Receipt Size Class. All other data is shown at the U.S., State, County, Combined Statistical Area, and Metropolitan/Micropolitan Statistical Areas....Industry Coverage:.The data are shown at the 2- through (where available) 6-digit NAICS code levels for all sectors with published data. Data for nonemployers generally are provided at broader levels of industry detail than data for employers. For specific exclusions and inclusions, see Program Methodology...FTP Download:.Download the entire table at: https://www2.census.gov/programs-surveys/nonemployer-statistics/data/2021/NS2100NONEMP.zip...API Information:.Nonemployer Statistics data are housed in the Nonemployer Statistics API. For more information, see Nonemployer Statistics APIs....Methodology:.The universe of this file is all firms with no paid employees or payroll with receipts of $1,000 or more (or $1 for the construction sector) and are subject to federal income tax. The universe is limited to industries in approximately 470 of the nearly 1,200 recognized North American Industry Classification System industries. The universe contains only those codes that are available through administrative records sources and are common to all three legal forms of organization applicable to nonemployer businesses. This is generally a broader level of detail than would typically be provided for employer data. For specific exclusions and inclusions, see Program Methodology.....Nonemployer Statistics originate from tax return information of the Internal Revenue Service. The data are subject to nonsampling error such as errors of self-classification by industry on tax forms, as well as errors of response, nonreporting and coverage. Values provided by each firm are slightly modified to protect the respondent's confidentiality. For further information about methodology and data limitations, see Program Methodology...Symbols:.G - Low noise; cell value was changed by less than 2 percent by the application of noise.H - Moderate noise; cell value was changed by 2 percent or more but less than 5 percent by the application of noise.J - High noise; cell value was changed by 5 percent or more by the application of noise..S - Withheld because estimate did not meet publication standards.N - Not available or not comparable.For a complete list of symbols, see Program Glossary: Abbreviations and Symbols....Source:..U.S. Census Bureau, 2021 Nonemployer Statistics..For more information about Nonemployer Statistics, see Nonemployer Statistics website...Contact Information:..U.S. Census Bureau.Economy-Wide Statistics Division .Business Statistics Branch .(301) 763-2580 .ewd.nonemployer.statistics@census.gov

Although the American Community Survey (ACS) produces population, demographic and housing unit estimates, it is the Census Bureau's Population Estimates Program that produces and disseminates the official estimates of the population for the nation, states, counties, cities, and towns and estimates of housing units for states and counties..Supporting documentation on code lists, subject definitions, data accuracy, and statistical testing can be found on the American Community Survey website in the Technical Documentation section.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, 2021 American Community Survey 1-Year Estimates.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..Employment and unemployment estimates may vary from the official labor force data released by the Bureau of Labor Statistics because of differences in survey design and data collection. For guidance on differences in employment and unemployment estimates from different sources go to Labor Force Guidance..Starting with 2013 data products, same-sex married couples are shown along with all married couples. For more information, see: User Notes..Selected labor force, employment, and work-status estimates for same- and opposite-sex married people using 2020 American Community Survey (ACS) 1-year data are available for the nation, states and the District of Columbia, and for selected metropolitan areas. At the national level, estimates are available by sex, race, and Hispanic origin. For more information, see the “Employment and Labor Force Characteristics for Same-Sex and Opposite-Sex Married Householders and their Spouses: 2020” table package on the Labor Force Statistics webpage..The 2021 American Community Survey (ACS) data generally reflect the March 2020 Office of Management and Budget (OMB) delineations of metropolitan and micropolitan statistical areas. In certain instances the names, codes, and boundaries of the principal cities shown in ACS tables may differ from the OMB delineations due to differences in the effective dates of the geographic entities..Estimates of urban and rural populations, housing units, and characteristics reflect boundaries of urban areas defined based on Census 2010 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.

This dataset contains model-based census tract level estimates in GIS-friendly format. PLACES covers the entire United States—50 states and the District of Columbia—at county, place, census tract, and ZIP Code Tabulation Area levels. It provides information uniformly on this large scale for local areas at four geographic levels. Estimates were provided by the Centers for Disease Control and Prevention (CDC), Division of Population Health, Epidemiology and Surveillance Branch. PLACES was funded by the Robert Wood Johnson Foundation in conjunction with the CDC Foundation. Data sources used to generate these model-based estimates are Behavioral Risk Factor Surveillance System (BRFSS) 2021 or 2020 data, Census Bureau 2010 population estimates, and American Community Survey (ACS) 2015–2019 estimates. The 2023 release uses 2021 BRFSS data for 29 measures and 2020 BRFSS data for 7 measures (all teeth lost, dental visits, mammograms, cervical cancer screening, colorectal cancer screening, core preventive services among older adults, and sleeping less than 7 hours) that the survey collects data on every other year. These data can be joined with the census tract 2015 boundary file in a GIS system to produce maps for 36 measures at the census tract level. An ArcGIS Online feature service is also available for users to make maps online or to add data to desktop GIS software. https://cdcarcgis.maps.arcgis.com/home/item.html?id=2c3deb0c05a748b391ea8c9cf9903588

This service contains the 2017-2021 release of data from the American Community Survey (ACS) 5-year data about Veteran Status, and contains estimates and margins of error. There are also additional calculated attributes related to this topic, which can be mapped or used within analysis. This layer is symbolized to show the percentage of the civilian population over the age of 18 that are Veterans.To see the full list of attributes available in this service, go to the "Data" tab, and choose "Fields" at the top right. Current Vintage: 2017-2021ACS Table(s): DP02Data downloaded from: CensusBureau's API for American Community Survey Date of API call: February 16, 2023National Figures: data.census.govThe United States Census Bureau's American Community Survey (ACS):About the SurveyGeography & ACSTechnical DocumentationNews & UpdatesThis ready-to-use layer can be used within ArcGIS Pro, ArcGIS Online, its configurable apps, dashboards, Story Maps, custom apps, and mobile apps. Data can also be exported for offline workflows. Please cite the Census and ACS when using this data.Data Note from the Census: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 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 Accuracy of the Data). The effect of nonsampling error is not represented in these tables.Data Processing Notes:Boundaries come from the Cartographic Boundaries via US Census TIGER geodatabases. Boundaries are updated at the same time as the data updates, and the boundary vintage appropriately matches the data vintage as specified by the Census. These are Census boundaries with water and/or coastlines clipped for cartographic purposes. For state and county boundaries, the water and coastlines are derived from the coastlines of the 500k TIGER Cartographic Boundary Shapefiles. The original AWATER and ALAND fields are still available as attributes within the data table (units are square meters). The States layer contains 52 records - all US states, Washington D.C., and Puerto Rico. The Counties (and equivalent) layer contains 3221 records - all counties and equivalent, Washington D.C., and Puerto Rico municipios. See Areas Published. Percentages and derived counts, and associated margins of error, are calculated values (that can be identified by the "_calc_" stub in the field name), and abide by the specifications defined by the American Community Survey.Field alias names were created based on the Table Shells.Margin of error (MOE) values of -555555555 in the API (or "*****" (five asterisks) on data.census.gov) are displayed as 0 in this dataset. The estimates associated with these MOEs have been controlled to independent counts in the ACS weighting and have zero sampling error. So, the MOEs are effectively zeroes, and are treated as zeroes in MOE calculations. Other negative values on the API, such as -222222222, -666666666, -888888888, and -999999999, all represent estimates or MOEs that can't be calculated or can't be published, usually due to small sample sizes. All of these are rendered in this dataset as null (blank) values.

Tabular data of population by age groups, race and gender, and the poverty by race is attached to the split tract geography to create this split tract with population and poverty data. Split tract data is the product of 2020 census tracts split by 2021 incorporated city boundaries and unincorporated community/countywide statistical areas (CSA) boundaries. The census tract boundaries have been altered and aligned where necessary with legal city boundaries and unincorporated areas, including shoreline/coastal areas. Census Tract:Every 10 years the Census Bureau counts the population of the United States as mandated by Constitution. The Census Bureau (https://www.census.gov/) released 2020 geographic boundaries data including census tracts for the analysis and mapping of demographic information across the United States. City Boundary:City Boundary data is the base map information for the County of Los Angeles. These City Boundaries are based on the Los Angeles County Seamless Cadastral Landbase. The Landbase is jointly maintained by the Los Angeles County Assessor and the Los Angeles County Department of Public Works (DPW). This layer represents current city boundaries within Los Angeles County. The DPW provides the most current shapefiles representing city boundaries and city annexations. True, legal boundaries are only determined on the ground by surveyors licensed in the State of California.Countywide Statistical Areas (CSA): The countywide Statistical Area (CSA) was defined to provide a common geographic boundary for reporting departmental statistics for unincorporated areas and incorporated Los Angeles city to the Board of Supervisors. The CSA boundary and CSA names are established by the CIO and the LA County Enterprise GIS group worked with the Los Angeles County Board of Supervisors Unincorporated Area and Field Deputies that reflect as best as possible the general name preferences of residents and historical names of areas. This data is primarily focused on broad statistics and reporting, not mapping of communities. This data is not designed to perfectly represent communities, nor jurisdictional boundaries such as Angeles National Forest. CSA represent board approved geographies comprised of Census block groups split by cities.Data Field:CT20: 2020 Census tractFIP21: 2021 City FIP CodeCITY: City name for incorporated cities and “Unincorporated” for unincorporated areas (as of July 1, 2021) CSA: Countywide Statistical Area (CSA) - Unincorporated area community names and LA City neighborhood names.CT20FIP21CSA: 2020 census tract with 2021 city FIPs for incorporated cities, unincorporated areas and LA neighborhoods. SPA22: 2022 Service Planning Area (SPA) number.SPA_NAME: Service Planning Area name.HD22: 2022 Health District (HD) number: HD_NAME: Health District name.POP21_AGE_0_4: 2021 population 0 to 4 years oldPOP21_AGE_5_9: 2021 population 5 to 9 years old POP21_AGE_10_14: 2021 population 10 to 14 years old POP21_AGE_15_17: 2021 population 15 to 17 years old POP21_AGE_18_19: 2021 population 18 to 19 years old POP21_AGE_20_44: 2021 population 20 to 24 years old POP21_AGE_25_29: 2021 population 25 to 29 years old POP21_AGE_30_34: 2021 population 30 to 34 years old POP21_AGE_35_44: 2021 population 35 to 44 years old POP21_AGE_45_54: 2021 population 45 to 54 years old POP21_AGE_55_64: 2021 population 55 to 64 years old POP21_AGE_65_74: 2021 population 65 to 74 years old POP21_AGE_75_84: 2021 population 75 to 84 years old POP21_AGE_85_100: 2021 population 85 years and older POP21_WHITE: 2021 Non-Hispanic White POP21_BLACK: 2021 Non-Hispanic African AmericanPOP21_AIAN: 2021 Non-Hispanic American Indian or Alaska NativePOP21_ASIAN: 2021 Non-Hispanic Asian POP21_HNPI: 2021 Non-Hispanic Hawaiian Native or Pacific IslanderPOP21_HISPANIC: 2021 HispanicPOP21_MALE: 2021 Male POP21_FEMALE: 2021 Female POV21_WHITE: 2021 Non-Hispanic White below 100% Federal Poverty Level POV21_BLACK: 2021 Non-Hispanic African American below 100% Federal Poverty Level POV21_AIAN: 2021 Non-Hispanic American Indian or Alaska Native below 100% Federal Poverty Level POV21_ASIAN: 2021 Non-Hispanic Asian below 100% Federal Poverty Level POV21_HNPI: 2021 Non-Hispanic Hawaiian Native or Pacific Islander below 100% Federal Poverty Level POV21_HISPANIC: 2021 Hispanic below 100% Federal Poverty Level POV21_TOTAL: 2021 Total population below 100% Federal Poverty Level POP21_TOTAL: 2021 Total PopulationAREA_SQMIL: Area in square milePOP21_DENSITY: Population per square mile.POV21_PERCENT: Poverty percentage.How this data created?The tabular data of population by age groups, by ethnic groups and by gender, and the poverty by ethnic groups is attributed to the split tract geography to create this data. Split tract polygon data is created by intersecting 2020 census tract polygons, LA Country City Boundary polygons and Countywide Statistical Areas (CSA) polygon data. The resulting polygon boundary aligned and matched with the legal city boundary whenever possible. Note:1. Population and poverty data estimated as of July 1, 2021. 2. 2010 Census tract and 2020 census tracts are not the same. Similarly, city and community boundary are not the same because boundary is reviewed and updated annually.