For the past several censuses, the Census Bureau has invited people to self-respond before following up in-person using census takers. The 2010 Census invited people to self-respond predominately by returning paper questionnaires in the mail. The 2020 Census allows people to self-respond in three ways: online, by phone, or by mail.The 2020 Census self-response rates are self-response rates for current census geographies. These rates are the daily and cumulative self-response rates for all housing units that received invitations to self-respond to the 2020 Census. The 2020 Census self-response rates are available for states, counties, census tracts, congressional districts, towns and townships, consolidated cities, incorporated places, tribal areas, and tribal census tracts.The Self-Response Rate of Los Angeles County is 65.1% for 2020 Census, which is slightly lower than 69.6% of California State rate.More information about these data is available in the Self-Response Rates Map Data and Technical Documentation document associated with the 2020 Self-Response Rates Map or review FAQs.Animated Self-Response Rate 2010 vs 2020 is available at ESRI site SRR Animated Maps and can explore Census 2020 SRR data at ESRI Demographic site Census 2020 SSR Data.Following Demographic Characteristics are included in this data and web maps to visualize their relationships with Census Self-Response Rate (SRR).1. Population Density: 2020 Population per square mile,2. Poverty Rate: Percentage of population under 100% FPL,3. Median Household income: Based on countywide median HH income of $71,538.4. Highschool Education Attainment: Percentage of 18 years and older population without high school graduation.5. English Speaking Ability: Percentage of 18 years and older population with less or none English speaking ability. 6. Household without Internet Access: Percentage of HH without internet access.7. Non-Hispanic White Population: Percentage of Non-Hispanic White population.8. Non-Hispanic African-American Population: Percentage of Non-Hispanic African-American population.9. Non-Hispanic Asian Population: Percentage of Non-Hispanic Asian population.10. Hispanic Population: Percentage of Hispanic population.

The Bureau of the Census has released Census 2000 Summary File 1 (SF1) 100-Percent data. The file includes the following population items: sex, age, race, Hispanic or Latino origin, household relationship, and household and family characteristics. Housing items include occupancy status and tenure (whether the unit is owner or renter occupied). SF1 does not include information on incomes, poverty status, overcrowded housing or age of housing. These topics will be covered in Summary File 3. Data are available for states, counties, county subdivisions, places, census tracts, block groups, and, where applicable, American Indian and Alaskan Native Areas and Hawaiian Home Lands. The SF1 data are available on the Bureau's web site and may be retrieved from American FactFinder as tables, lists, or maps. Users may also download a set of compressed ASCII files for each state via the Bureau's FTP server. There are over 8000 data items available for each geographic area. The full listing of these data items is available here as a downloadable compressed data base file named TABLES.ZIP. The uncompressed is in FoxPro data base file (dbf) format and may be imported to ACCESS, EXCEL, and other software formats. While all of this information is useful, the Office of Community Planning and Development has downloaded selected information for all states and areas and is making this information available on the CPD web pages. The tables and data items selected are those items used in the CDBG and HOME allocation formulas plus topics most pertinent to the Comprehensive Housing Affordability Strategy (CHAS), the Consolidated Plan, and similar overall economic and community development plans. The information is contained in five compressed (zipped) dbf tables for each state. When uncompressed the tables are ready for use with FoxPro and they can be imported into ACCESS, EXCEL, and other spreadsheet, GIS and database software. The data are at the block group summary level. The first two characters of the file name are the state abbreviation. The next two letters are BG for block group. Each record is labeled with the code and name of the city and county in which it is located so that the data can be summarized to higher-level geography. The last part of the file name describes the contents . The GEO file contains standard Census Bureau geographic identifiers for each block group, such as the metropolitan area code and congressional district code. The only data included in this table is total population and total housing units. POP1 and POP2 contain selected population variables and selected housing items are in the HU file. The MA05 table data is only for use by State CDBG grantees for the reporting of the racial composition of beneficiaries of Area Benefit activities. The complete package for a state consists of the dictionary file named TABLES, and the five data files for the state. The logical record number (LOGRECNO) links the records across tables.

This layer shows total population counts by sex, age, and race groups data from the 2020 Census Demographic and Housing Characteristics. This is shown by Nation, State, County, Census Tract, Block Group 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, P2, P3, P5, P12, P13, P17, PCT12 (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, State, County, Census Tract, Block GroupNational 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 CSV file shows total population counts by sex, age, and race groupsdata from the2020 CensusDemographic andHousing Characteristics. Thisisshown by Nation, Consolidated City, Census Designated Place, Incorporated Placeboundaries. Eachgeographylayercontainsa common set of Census countsbased on available attributes from the U.S. Census Bureau. There are alsoadditionalcalculated attributes related to this topic, which can be mapped or used within analysis.  Vintageof boundaries and attributes:2020Demographic andHousing CharacteristicsTable(s): P1, H1, H3, P2, P3, P5, P12, P13, P17, PCT12 (Not all lines of these DHC tables are available in this file.)Data downloaded from: U.S. Census Bureau’s data.census.gov siteDatethe Data was Downloaded: May 25, 2023Geography Levels included: Nation, Consolidated City, Census Designated Place, Incorporated PlaceNational Figures: included in Nation layerThe United States Census BureauDemographic andHousing Characteristics:2020 Census Results2020 Census Data QualityGeography &2020 CensusTechnical DocumentationData 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 & UpdatesData 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. ForCensustractsand 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 metersor larger (mid tolarge sizedwater bodies) are erased from the tractand block groupboundaries, 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 tomore 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 layercontainsall 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 beidentifiedby 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 theDemographic Profile and Demographic andHousing 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 usingdifferential privacy techniquesby the U.S. Census Bureau.

This dataset contains model-based census tract level estimates for the PLACES project 2020 release in GIS-friendly format. The PLACES project 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 Areas (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. The project was funded by the Robert Wood Johnson Foundation (RWJF) in conjunction with the CDC Foundation. Data sources used to generate these model-based estimates include Behavioral Risk Factor Surveillance System (BRFSS) 2018 or 2017 data, Census Bureau 2010 population estimates, and American Community Survey (ACS) 2014-2018 or 2013-2017 estimates. The 2020 release uses 2018 BRFSS data for 23 measures and 2017 BRFSS data for 4 measures (high blood pressure, taking high blood pressure medication, high cholesterol, and cholesterol screening). Four measures are based on the 2017 BRFSS data because the relevant questions are only asked every other year in the BRFSS. These data can be joined with the census tract 2015 boundary file in a GIS system to produce maps for 27 measures at the census tract level. An ArcGIS Online feature service is also available at https://www.arcgis.com/home/item.html?id=8eca985039464f4d83467b8f6aeb1320 for users to make maps online or to add data to desktop GIS software.

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) 2022 or 2021 data, Census Bureau 2010 population estimates, and American Community Survey (ACS) 2015–2019 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. These data can be joined with the Census tract 2022 boundary file in a GIS system to produce maps for 40 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=3b7221d4e47740cab9235b839fa55cd7

Although the American Community Survey (ACS) produces population, demographic and housing unit estimates, for 2020, the 2020 Census provides the official counts of the population and housing units for the nation, states, counties, cities, and towns. For 2016 to 2019, the Population Estimates Program provides estimates of the population for the nation, states, counties, cities, and towns and intercensal housing unit estimates for the nation, 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, 2016-2020 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..Data about computer and Internet use were collected by asking respondents to select "Yes" or "No" to each type of computer and each type of Internet subscription. Therefore, respondents were able to select more than one type of computer and more than one type of Internet subscription..The category "Has 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. The category "No computer" consists of those who said "No" to all of these types of computers..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..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. The category "Without an Internet subscription" includes those who accessed the Internet without a subscription and also those with no Internet access at all..In 2016, changes were made to the computer and Internet use questions, involving the wording as well as the response options. A crosswalk was used to map pre-2016 data to the post-2016 categories, enabling creation of 5-year data. For more detailed information about the 2016 changes, see the 2016 American Community Survey Content Test Report for Computer and Internet Use located at https://www.census.gov/library/working-papers/2017/acs/2017_Lewis_01.html or the user note regarding changes in the 2016 questions located at https://www.census.gov/programs-surveys/acs/technical-documentation/user-notes/2017-03.html. For more detailed information about the crosswalk, see the user note regarding the crosswalk located at https://www.census.gov/programs-surveys/acs/technical-documentation/user-notes.html..The 2016-2020 American Community Survey (ACS) data generally reflect the September 2018 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.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...

Although the American Community Survey (ACS) produces population, demographic and housing unit estimates, for 2020, the 2020 Census provides the official counts of the population and housing units for the nation, states, counties, cities, and towns. For 2016 to 2019, the Population Estimates Program provides estimates of the population for the nation, states, counties, cities, and towns and intercensal housing unit estimates for the nation, 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, 2016-2020 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..Data about computer and Internet use were collected by asking respondents to select "Yes" or "No" to each type of computer and each type of Internet subscription. Therefore, respondents were able to select more than one type of computer and more than one type of Internet subscription..The category "Has 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. The category "No computer" consists of those who said "No" to all of these types of computers..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..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. The category "Without an Internet subscription" includes those who accessed the Internet without a subscription and also those with no Internet access at all..In 2016, changes were made to the computer and Internet use questions, involving the wording as well as the response options. A crosswalk was used to map pre-2016 data to the post-2016 categories, enabling creation of 5-year data. For more detailed information about the 2016 changes, see the 2016 American Community Survey Content Test Report for Computer and Internet Use located at https://www.census.gov/library/working-papers/2017/acs/2017_Lewis_01.html or the user note regarding changes in the 2016 questions located at https://www.census.gov/programs-surveys/acs/technical-documentation/user-notes/2017-03.html. For more detailed information about the crosswalk, see the user note regarding the crosswalk located at https://www.census.gov/programs-surveys/acs/technical-documentation/user-notes.html..The Hispanic origin and race codes were updated in 2020. For more information on the Hispanic origin and race code changes, please visit the American Community Survey Technical Documentation website..The 2016-2020 American Community Survey (ACS) data generally reflect the September 2018 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...

Although the American Community Survey (ACS) produces population, demographic and housing unit estimates, for 2020, the 2020 Census provides the official counts of the population and housing units for the nation, states, counties, cities, and towns. For 2016 to 2019, the Population Estimates Program provides estimates of the population for the nation, states, counties, cities, and towns and intercensal housing unit estimates for the nation, 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, 2016-2020 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..Data about computer and Internet use were collected by asking respondents to select "Yes" or "No" to each type of computer and each type of Internet subscription. Therefore, respondents were able to select more than one type of computer and more than one type of Internet subscription..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..Examples of "Internet access without a subscription" include cases such as free Internet service provided by a respondent's town or city or free Internet service a university may provide for their students..Internet access refers to whether or not a household uses or connects to the Internet, regardless of whether or not they pay for the service to do so. Data about Internet access was collected by asking if the respondent or any member of the household accessed the Internet. The respondent then selected one of the following three categories: "Yes, by paying a cell phone company or Internet service provider"; "Yes, without paying a cell phone company or Internet service provider"; or "No access to the Internet at the house, apartment or mobile home". Only respondents who answered "Yes, by paying a cell phone company or Internet service provider" were asked the subsequent question about the types of service they had access to such as dial-up, broadband (high speed) service such as cable, fiber-optic, or DSL, a cellular data plan, satellite or some other service..In 2016, changes were made to the computer and Internet use questions, involving the wording as well as the response options. A crosswalk was used to map pre-2016 data to the post-2016 categories, enabling creation of 5-year data. For more detailed information about the 2016 changes, see the 2016 American Community Survey Content Test Report for Computer and Internet Use located at https://www.census.gov/library/working-papers/2017/acs/2017_Lewis_01.html or the user note regarding changes in the 2016 questions located at https://www.census.gov/programs-surveys/acs/technical-documentation/user-notes/2017-03.html. For more detailed information about the crosswalk, see the user note regarding the crosswalk located at https://www.census.gov/programs-surveys/acs/technical-documentation/user-notes.html..The 2016-2020 American Community Survey (ACS) data generally reflect the September 2018 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 est...

Starting in mid-July of 2020, despite many delays due to Covid-19, census takers began interviewing households who had not yet responded online or via the mail to the U.S. 2020 Census. The federal census, required by the United States’ Constitution, happens once every 10 years and each time, there are new variations in enumeration (counting) techniques and what statistical data to collect. There are processes around “how” to count and then also “what” to count; the data collected needs to be useful for governance and allocation yet also respectful of privacy and remain fair and impartial for the entire U.S. population. In 2019 and 2020, hundreds of thousands of temporary workers from local communities were hired to go out into the field as census takers as well as staff offices and provide supervision. This 22nd federal census count began in January 2020 with remote portions of Alaska, where the territory was still frozen and traversable. These employed citizens are just one aspect of how the census is truly a community event. Let’s dive into the history of the U.S. Census and also learn why this count is so important.

Census Blocks are statistical areas bounded on all sides by visible features, such as streets, roads, streams, and railroad tracks, and/or by nonvisible boundaries such as city, town, township, and county limits, and short line-of-sight extensions of streets and roads. Census blocks are relatively small in area; for example, a block in a city bounded by streets. However, census blocks in remote areas are often large and irregular and may even be many square miles in area. A common misunderstanding is that data users think census blocks are used geographically to build all other census geographic areas, rather all other census geographic areas are updated and then used as the primary constraints, along with roads and water features, to delineate the tabulation blocks. As a result, all 2020 Census blocks nest within every other 2020 Census geographic area, so that Census Bureau statistical data can be tabulated at the block level and aggregated up to the appropriate geographic areas. Blocks are the smallest geographic areas for which the Census Bureau publishes data from the decennial census. Block Groups (BGs) are defined before tabulation block delineation and numbering, but are clusters of blocks within the same census tract that have the same first digit of their 4-digit census block number from the same decennial census. Census 2020 BGs generally contained between 600 and 3,000 people, with an optimum size of 1,500 people. Most BGs were delineated by local participants in the Census Bureau's Participant Statistical Areas Program (PSAP). The primary purpose of census tracts is to provide a stable set of geographic units for the presentation of census data and comparison back to previous decennial censuses. Census tracts generally have a population size between 1,200 and 8,000 people, with an optimum size of 4,000 people. When first delineated, census tracts were designed to be homogeneous with respect to population characteristics, economic status, and living conditions. Census tract boundaries generally follow visible and identifiable features. State and county boundaries always are census tract boundaries in the standard census geographic hierarchy. In a few rare instances, a census tract may consist of noncontiguous areas.This is a MD iMAP hosted service layer. Find more information at https://imap.maryland.gov.Feature Service Layer Link:https://mdgeodata.md.gov/imap/rest/services/Demographics/MD_CensusBoundaries/MapServer/0**Please note, due to the size of this dataset, you may receive an error message when trying to download the dataset. You can download this dataset directly from MD iMAP Services at: https://mdgeodata.md.gov/imap/rest/services/Demographics/MD_CensusBoundaries/MapServer/exts/MDiMAPDataDownload/customLayers/0**

This data layer is an element of the Oregon GIS Framework. The TIGER/Line shapefiles and related database files (.dbf) are an extract of selected geographic and cartographic information from the U.S. Census Bureau's Master Address File / Topologically Integrated Geographic Encoding and Referencing (MAF/TIGER) Database (MTDB). The MTDB represents a seamless national file with no overlaps or gaps between parts, however, each TIGER/Line shapefile is designed to stand alone as an independent data set, or they can be combined to cover the entire nation. Census tracts are small, relatively permanent statistical subdivisions of a county or equivalent entity, and were defined by local participants as part of the 2020 Census Participant Statistical Areas Program. The Census Bureau delineated the census tracts in situations where no local participant existed or where all the potential participants declined to participate. The primary purpose of census tracts is to provide a stable set of geographic units for the presentation of census data and comparison back to previous decennial censuses. Census tracts generally have a population size between 1,200 and 8,000 people, with an optimum size of 4,000 people. When first delineated, census tracts were designed to be homogeneous with respect to population characteristics, economic status, and living conditions. The spatial size of census tracts varies widely depending on the density of settlement. Physical changes in street patterns caused by highway construction, new development, and so forth, may require boundary revisions. In addition, census tracts occasionally are split due to population growth, or combined as a result of substantial population decline. Census tract boundaries generally follow visible and identifiable features. They may follow legal boundaries such as minor civil division (MCD) or incorporated place boundaries in some States and situations to allow for census tract-to-governmental unit relationships where the governmental boundaries tend to remain unchanged between censuses. State and county boundaries always are census tract boundaries in the standard census geographic hierarchy. In a few rare instances, a census tract may consist of noncontiguous areas. These noncontiguous areas may occur where the census tracts are coextensive with all or parts of legal entities that are themselves noncontiguous. For the 2010 Census and beyond, the census tract code range of 9400 through 9499 was enforced for census tracts that include a majority American Indian population according to Census 2000 data and/or their area was primarily covered by federally recognized American Indian reservations and/or off-reservation trust lands; the code range 9800 through 9899 was enforced for those census tracts that contained little or no population and represented a relatively large special land use area such as a National Park, military installation, or a business/industrial park; and the code range 9900 through 9998 was enforced for those census tracts that contained only water area, no land area.

Data from: American Community Survey, 5-year Series

This layer presents the 2020 U.S. Census State boundaries of the United States in the 50 states and the District of Columbia. This layer is updated annually. The geography is sourced from U.S. Census Bureau 2020 TIGER FGDB (National Sub-State) and edited using TIGER Hydrography to add a detailed coastline for cartographic purposes. Attribute fields include 2020 total population from the U.S. Census Public Law 94 data.This ready-to-use layer can be used in ArcGIS Pro and in ArcGIS Online and its configurable apps, dashboards, StoryMaps, custom apps, and mobile apps. The data can also be exported for offline workflows. Cite the 'U.S. Census Bureau' when using this data.

All addresses in Self Response enumeration areas (TEA 1) received one of two mailing strategies – Internet First or Internet Choice. This table is the daily and cumulative self-response and return rates by mode as well as undeliverable as addressed (UAA) rates for all addresses in areas receiving the Internet Choice mailing..For more information about the different types of enumeration areas, go to the 2020 Census Type of Enumeration (TEA) viewer page by clicking here: Type of Enumeration Area..Internet Choice mailings:.Mailing 1 – Letter and Questionnaire.Mailing 2 – Letter.Mailing 3 – Postcard.Mailing 4 – Letter and Questionnaire.Mailing 5 – “It’s Not Too Late Postcard”.Mailing 6 – Pre-NRFU COVID-19 Postcard.Mailing 7 – Letter and Questionnaire.Mailings 3-7 were targeted to nonrespondents.Mailings 6 and 7 were added during the census due to the COVID-19 pandemic.For more information about the impacts of the COVID-19 pandemic on the 2020 Census, click here: COVID-19 Decennial Census..Self-response rates presented in this table may differ from those presented in the self-response map that was updated daily during the 2020 Census. The map used raw data as it was being processed in real-time while these rates used post processed data..To read the report that provides background information about the rate, go to the Evaluations, Experiments, and Assessment page on census.gov by clicking here: Evaluations Experiments and Assessments..Key Column Terms:.Daily – percentage of housing units whose self-responses were received on a particular date.Cumulative – percentage of housing units whose self-responses were received from the start of the census through a particular date.Internet – percentage of housing units providing a self-response by internet questionnaire.Paper – percentage of housing units providing a self-response by paper questionnaire.CQA – percentage of housing units providing a self-response by phone.Total – percentage of housing units providing a self-response by internet, paper, or phone.Self-Response Rate – percentage of addresses in Self Response (TEA 1) or Update Leave (TEA 6) areas providing a sufficient self-response by internet, paper, or phone.Return Rate – percentage of occupied housing units in Self Response (TEA 1) or Update Leave (TEA 6) areas providing a sufficient self-response by internet, paper, or phone.UAA Rate – percentage of addresses in Self Response areas (TEA 1) identified as undeliverable as addressed (UAA).NOTE: The Census Bureau's Disclosure Review Board and Disclosure Avoidance Officers have reviewed this information product for unauthorized disclosure of confidential information and have approved the disclosure avoidance practices applied to this release. (CBDRB-FY24-0271).Source: U.S. Census Bureau, 2020 Census

The Census Planning Database is produced by the U.S. Census Bureau. It assembles a range of housing, demographic, socioeconomic, and census operational data that can be used for survey and census planning.

The Planning Database uses selected Census and selected 2012-2016 American Community Survey (ACS) estimates. In addition to variables extracted from the census and ACS databases, operational variables include the 2010 Census Mail Return Rate for each block group and tract.

This dataset is a subset of the 2018 Census Planning Database, filtered for the state of Connecticut, and including variables relating to hard to count populations. This dataset also includes two variables from the Federal Communications Commission dataset "Residential Fixed Internet Access Service Connections per 1000 Households by Census Tract." More information about the FCC data can be found here: https://www.fcc.gov/reports-research/maps/residential-fixed-internet-access-service-connections-per-1000-households-by-census-tract-dec-2016/

Other variables from the Census Planning Database relating to geography, population, households, housing units, and census operations at the tract and block level can also be found on the CT Data Portal with the tag "Census 2020."

2020 census block groups for the City of Seattle.

Although the American Community Survey (ACS) produces population, demographic and housing unit estimates, for 2020, the 2020 Census provides the official counts of the population and housing units for the nation, states, counties, cities, and towns. For 2016 to 2019, the Population Estimates Program provides estimates of the population for the nation, states, counties, cities, and towns and intercensal housing unit estimates for the nation, 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, 2016-2020 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..Data about computer and Internet use were collected by asking respondents to select "Yes" or "No" to each type of computer and each type of Internet subscription. Therefore, respondents were able to select more than one type of computer and more than one type of Internet subscription..The category "Has one or more types of computing devices" refers to 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. The category "No computer" consists of those who said "No" to all of these types of computers..In 2016, changes were made to the computer and Internet use questions, involving the wording as well as the response options. A crosswalk was used to map pre-2016 data to the post-2016 categories, enabling creation of 5-year data. For more detailed information about the 2016 changes, see the 2016 American Community Survey Content Test Report for Computer and Internet Use located at https://www.census.gov/library/working-papers/2017/acs/2017_Lewis_01.html or the user note regarding changes in the 2016 questions located at https://www.census.gov/programs-surveys/acs/technical-documentation/user-notes/2017-03.html. For more detailed information about the crosswalk, see the user note regarding the crosswalk located at https://www.census.gov/programs-surveys/acs/technical-documentation/user-notes.html..The 2016-2020 American Community Survey (ACS) data generally reflect the September 2018 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.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.

All addresses in Self Response (TEA 1) and Update Leave (TEA 6) enumeration areas were invited to respond by internet, paper, or phone. Within these areas, tracts were delineated to either an English or bilingual questionnaire based on demographic characteristics. This table is the daily and cumulative self-response and return rates for the bilingual questionnaire by mode as well as undeliverable as addressed (UAA) rates for the nation..For more information about the different types of enumeration areas, go to the 2020 Census Type of Enumeration (TEA) viewer page by clicking here: Type of Enumeration Area..Self-response rates presented in this table may differ from those presented in the self-response map that was updated daily during the 2020 Census. The map used raw data as it was being processed in real-time while these rates used post processed data..To read the report that provides background information about the rate, go to the Evaluations, Experiments, and Assessment page on census.gov by clicking here: Evaluations Experiments and Assessments..Key Column Terms:.Daily – percentage of housing units whose self-responses were received on a particular date.Cumulative – percentage of housing units whose self-responses were received from the start of the census through a particular date.Internet – percentage of housing units providing a self-response by internet questionnaire.Paper – percentage of housing units providing a self-response by paper questionnaire.CQA – percentage of housing units providing a self-response by phone.Total – percentage of housing units providing a self-response by internet, paper, or phone.Self-Response Rate – percentage of addresses in Self Response (TEA 1) or Update Leave (TEA 6) areas providing a sufficient self-response by internet, paper, or phone.Return Rate – percentage of occupied housing units in Self Response (TEA 1) or Update Leave (TEA 6) areas providing a sufficient self-response by internet, paper, or phone.UAA Rate – percentage of addresses in Self Response areas (TEA 1) identified as undeliverable as addressed (UAA).NOTE: The Census Bureau's Disclosure Review Board and Disclosure Avoidance Officers have reviewed this information product for unauthorized disclosure of confidential information and have approved the disclosure avoidance practices applied to this release. (CBDRB-FY24-0271).Source: U.S. Census Bureau, 2020 Census