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.

California is home to 12 percent of the nation's population yet accounts for more than 20 percent of the people living in the nation’s hardest-to-count areas, according to the United States Census Bureau (U.S. Census Bureau). California's unique diversity, large population distributed across both urban and rural areas, and sheer geographic size present significant barriers to achieving a complete and accurate count. The state’s population is more racially and ethnically diverse than ever before, with about 18 percent of Californians speaking English “less than very well,” according to U.S. Census Bureau estimates. Because the 2020 Census online form was offered in only twelve non-English languages, which did not correspond with the top spoken language in California, and a paper questionnaire only in English and Spanish, many Californians may not have been able to access a census questionnaire or written guidance in a language they could understand. In order to earn the confidence of California’s most vulnerable populations, it was critical during the 2020 Census that media and trusted messengers communicate with them in their primary language and in accessible formats. An accurate count of the California population in each decennial census is essential to receive its equitable share of federal funds and political representation, through reapportionment and redistricting. It plays a vital role in many areas of public life, including important investments in health, education, housing, social services, highways, and schools. Without a complete count in the 2020 Census, the State faced a potential loss of congressional seats and billions of dollars in muchneeded federal funding. An undercount of California in 1990 cost an estimated $2 billion in federal funding. The potential loss of representation and critically needed funding could have long-term impacts; only with a complete count does California receive the share of funding the State deserves with appropriate representation at the federal, state, and local government levels. The high stakes and formidable challenges made this California Complete Count Census 2020 Campaign (Campaign) the most important to date. The 2020 Census brought an unprecedented level of new challenges to all states, beyond the California-specific hurdles discussed above. For the first time, the U.S. Census Bureau sought to collect data from households through an online form. While the implementation of digital forms sought to reduce costs and increase participation, its immediate impact is still unknown as of this writing, and it may have substantially changed how many households responded to the census. In addition, conditions such as the novel Coronavirus (COVID-19) pandemic, a contentious political climate, ongoing mistrust and distrust of government, and rising concerns about privacy may have discouraged people to open their doors, or use computers, to participate. Federal immigration policy, as well as the months-long controversy over adding a citizenship question to the census, may have deterred households with mixed documentation status, recent immigrants, and undocumented immigrants from participating. In 2017, to prepare for the unique challenges of the 2020 Census, California leaders and advocates reflected on lessons learned from previous statewide census efforts and launched the development of a high-impact strategy to efficiently raise public awareness about the 2020 Census. Subsequently, the State established the California Complete Count – Census 2020 Office (Census Office) and invested a significant sum for the Campaign. The Campaign was designed to educate, motivate, and activate Californians to respond to the 2020 Census. It relied heavily on grassroots messaging and outreach to those least likely to fill out the census form. One element of the Campaign was the Language and Communication Access Plan (LACAP), which the Census Office developed to ensure that language and communication access was linguistically and culturally relevant and sensitive and provided equal and meaningful access for California’s vulnerable populations. The Census Office contracted with outreach partners, including community leaders and organizations, local government, and ethnic media, who all served as trusted messengers in their communities to deliver impactful words and offer safe places to share information and trusted messages. The State integrated consideration of hardest-to-count communities’ needs throughout the Campaign’s strategy at both the statewide and regional levels. The Campaign first educated, then motivated, and during the census response period, activated Californians to fill out their census form. The Census Office’s mission was to ensure that Californians get their fair share of resources and representation by encouraging the full participation of all Californians in the 2020 Census. This report focuses on the experience of the Census Office and partner organizations who worked to achieve the most complete count possible, presenting an evaluation of four outreach and communications strategies.

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 layer shows race and ethnicity data from the 2020 Census Demographic and Housing Characteristics. This is shown by Nation, Consolidated City, Census Designated Place, Incorporated Place boundaries. Each geography layer contains a common set of Census counts based on available attributes from the U.S. Census Bureau. There are also additional calculated attributes related to this topic, which can be mapped or used within analysis.   To see the full list of attributes available in this service, go to the "Data" tab above, and then choose "Fields" at the top right. Each attribute contains definitions, additional details, and the formula for calculated fields in the field description.Vintage of boundaries and attributes: 2020 Demographic and Housing Characteristics Table(s): P1, H1, H3, P5, P9 Data downloaded from: U.S. Census Bureau’s data.census.gov siteDate the Data was Downloaded: May 25, 2023Geography Levels included: Nation, Consolidated City, Census Designated Place, Incorporated PlaceNational Figures: included in Nation layer The United States Census Bureau Demographic and Housing Characteristics: 2020 Census Results 2020 Census Data Quality Geography & 2020 Census Technical Documentation Data Table Guide: includes the final list of tables, lowest level of geography by table and table shells for the Demographic Profile and Demographic and Housing Characteristics.News & Updates This layer is ready to be used in ArcGIS Pro, ArcGIS Online and its configurable apps, Story Maps, dashboards, Notebooks, Python, custom apps, and mobile apps. Data can also be exported for offline workflows. Please cite the U.S. Census Bureau when using this data. Data Processing Notes: These 2020 Census boundaries come from the US Census TIGER geodatabases. These are Census boundaries with water and/or coastlines erased for cartographic and mapping purposes. For Census tracts and block groups, the water cutouts are derived from a subset of the 2020 Areal Hydrography boundaries offered by TIGER. Water bodies and rivers which are 50 million square meters or larger (mid to large sized water bodies) are erased from the tract and block group boundaries, as well as additional important features. For state and county boundaries, the water and coastlines are derived from the coastlines of the 2020 500k TIGER Cartographic Boundary Shapefiles. These are erased to more accurately portray the coastlines and Great Lakes. The original AWATER and ALAND fields are unchanged and available as attributes within the data table (units are square meters).  The layer contains all US states, Washington D.C., and Puerto Rico. Census tracts with no population that occur in areas of water, such as oceans, are removed from this data service (Census Tracts beginning with 99). Block groups that fall within the same criteria (Block Group denoted as 0 with no area land) have also been removed.Percentages and derived counts, are calculated values (that can be identified by the "_calc_" stub in the field name). Field alias names were created based on the Table Shells file available from the Data Table Guide for the Demographic Profile and Demographic and Housing Characteristics. Not all lines of all tables listed above are included in this layer. Duplicative counts were dropped. For example, P0030001 was dropped, as it is duplicative of P0010001.To protect the privacy and confidentiality of respondents, their data has been protected using differential privacy techniques by the U.S. Census Bureau.

Due to the nature of this program, it is important to track long-term quality, cost, and delivery schedule goals. The Census Bureau has embarked on a multi-year research and testing program focused on major innovations to the design of the census and oriented around major cost drivers.

Census 2020 blocks in King County with selected P.L. 94-171 redistricting data.For more information about the P.L. 94-171 redistricting data, please visit the U.S. Census Bureau. For a detailed description of the data included please see the 2020 Census State Redistricting Data Summary File. Important note: The Census Bureau advises analysts to aggregate blocks together to form larger geographic units before using the 2020 Census data. Background: The Bureau used a new tool, called Differential Privacy, to inject statistical noise into the 2020 Census data in order to protect privacy. The resulting noise can cause substantial inaccuracy at the block level; combining data for blocks and other small geographies reduces the inaccuracy. For more information see Redistricting Data: What to Expect and When (census.gov), 2020 Census Data Products: Disclosure Avoidance Modernization.

For more information about the P.L. 94-171 redistricting data, please visit the U.S. Census Bureau. For a detailed description of the data included please see the 2020 Census State Redistricting Data Summary File. Important note: The Census Bureau advises analysts to aggregate blocks together to form larger geographic units before using the 2020 Census data. Background: The Bureau used a new tool, called Differential Privacy, to inject statistical noise into the 2020 Census data in order to protect privacy. The resulting noise can cause substantial inaccuracy at the block level; combining data for blocks and other small geographies reduces the inaccuracy. For more information see Redistricting Data: What to Expect and When (census.gov), 2020 Census Data Products: Disclosure Avoidance Modernization.

Census 2020 blocks with the Washington State Office of Financial Management Small Area Estimates Program (SAEP) estimates. Enhanced with City of Seattle council districts and growth management areas.PLEASE BE AWARE, the urban village and comprehensive plan area designations are subject to change annually.Estimates are annual April, 1 for the 2010-202X with the most current year added Q4 of that year.(SAEP) estimates are meant to provide a consistent set of small area population and housing data for statewide applications. SAEP estimates are generated by the Washington State Office of Financial Management for census areas and other areas of statewide significance.Before using the SAEP estimates, please see the SAEP User Guide to gain a better understanding of the data and methods behind the estimates as well as limitations in their use. For more specific information about the 2020 data release, please see the User Notes and Errata document.Please note that SAEP estimates are NOT the official state population estimates used for revenue distribution and program administration related to cities and counties. Users interested in city and county estimates should see the state's official April 1 population estimates program.

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

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.

This dataset was developed by the Research & Analytics Group at the Atlanta Regional Commission using data from the U.S. Census Bureau across all standard and custom geographies at statewide summary level where applicable.

For a deep dive into the data model including every specific metric, see the ACS 2016-2020 Data Manifest. The manifest details ARC-defined naming conventions, field names/descriptions and topics, summary levels; source tables; notes and so forth for all metrics.

Prefixes:

None

Count

p

Percent

r

Rate

m

Median

a

Mean (average)

t

Aggregate (total)

ch

Change in absolute terms (value in t2 - value in t1)

pch

Percent change ((value in t2 - value in t1) / value in t1)

chp

Change in percent (percent in t2 - percent in t1)

s

Significance flag for change: 1 = statistically significant with a 90% CI, 0 = not statistically significant, blank = cannot be computed

Suffixes:

_e20

Estimate from 2016-20 ACS

_m20

Margin of Error from 2016-20 ACS

_e10

2006-10 ACS, re-estimated to 2020 geography

_m10

Margin of Error from 2006-10 ACS, re-estimated to 2020 geography

_e10_20

Change, 2010-20 (holding constant at 2020 geography)

Geographies

AAA = Area Agency on Aging (12 geographic units formed from counties providing statewide coverage)

ARWDB7 = Atlanta Regional Workforce Development Board (7 counties merged to a single geographic unit)

Census Tracts (statewide)

CFGA23 = Community Foundation for Greater Atlanta (23 counties merged to a single geographic unit)

City (statewide)

City of Atlanta Council Districts (City of Atlanta)

City of Atlanta Neighborhood Planning Unit (City of Atlanta)

City of Atlanta Neighborhood Planning Unit STV (subarea of City of Atlanta)

City of Atlanta Neighborhood Statistical Areas (City of Atlanta)

County (statewide)

Georgia House (statewide)

Georgia Senate (statewide)

MetroWater15 = Atlanta Metropolitan Water District (15 counties merged to a single geographic unit)

Regional Commissions (statewide)

State of Georgia (statewide)

Superdistrict (ARC region)

US Congress (statewide)

UWGA13 = United Way of Greater Atlanta (13 counties merged to a single geographic unit)

WFF = Westside Future Fund (subarea of City of Atlanta)

ZIP Code Tabulation Areas (statewide)

The user should note that American Community Survey data represent estimates derived from a surveyed sample of the population, which creates some level of uncertainty, as opposed to an exact measure of the entire population (the full census count is only conducted once every 10 years and does not cover as many detailed characteristics of the population). Therefore, any measure reported by ACS should not be taken as an exact number – this is why a corresponding margin of error (MOE) is also given for ACS measures. The size of the MOE relative to its corresponding estimate value provides an indication of confidence in the accuracy of each estimate. Each MOE is expressed in the same units as its corresponding measure; for example, if the estimate value is expressed as a number, then its MOE will also be a number; if the estimate value is expressed as a percent, then its MOE will also be a percent.

The user should also note that for relatively small geographic areas, such as census tracts shown here, ACS only releases combined 5-year estimates, meaning these estimates represent rolling averages of survey results that were collected over a 5-year span (in this case 2016-2020). Therefore, these data do not represent any one specific point in time or even one specific year. For geographic areas with larger populations, 3-year and 1-year estimates are also available.

For further explanation of ACS estimates and margin of error, visit Census ACS website.

Source: U.S. Census Bureau, Atlanta Regional Commission Date: 2016-2020 Data License: Creative Commons Attribution 4.0 International (CC by 4.0)

Link to the manifest: https://opendata.atlantaregional.com/documents/GARC::acs-2020-data-manifest/about

This dataset was developed by the Research & Analytics Group at the Atlanta Regional Commission using data from the U.S. Census Bureau across all standard and custom geographies at statewide summary level where applicable.

For a deep dive into the data model including every specific metric, see the ACS 2016-2020 Data Manifest. The manifest details ARC-defined naming conventions, field names/descriptions and topics, summary levels; source tables; notes and so forth for all metrics.

Prefixes:

None

Count

p

Percent

r

Rate

m

Median

a

Mean (average)

t

Aggregate (total)

ch

Change in absolute terms (value in t2 - value in t1)

pch

Percent change ((value in t2 - value in t1) / value in t1)

chp

Change in percent (percent in t2 - percent in t1)

s

Significance flag for change: 1 = statistically significant with a 90% CI, 0 = not statistically significant, blank = cannot be computed

Suffixes:

_e20

Estimate from 2016-20 ACS

_m20

Margin of Error from 2016-20 ACS

_e10

2006-10 ACS, re-estimated to 2020 geography

_m10

Margin of Error from 2006-10 ACS, re-estimated to 2020 geography

_e10_20

Change, 2010-20 (holding constant at 2020 geography)

Geographies

AAA = Area Agency on Aging (12 geographic units formed from counties providing statewide coverage)

ARWDB7 = Atlanta Regional Workforce Development Board (7 counties merged to a single geographic unit)

Census Tracts (statewide)

CFGA23 = Community Foundation for Greater Atlanta (23 counties merged to a single geographic unit)

City (statewide)

City of Atlanta Council Districts (City of Atlanta)

City of Atlanta Neighborhood Planning Unit (City of Atlanta)

City of Atlanta Neighborhood Planning Unit STV (subarea of City of Atlanta)

City of Atlanta Neighborhood Statistical Areas (City of Atlanta)

County (statewide)

Georgia House (statewide)

Georgia Senate (statewide)

MetroWater15 = Atlanta Metropolitan Water District (15 counties merged to a single geographic unit)

Regional Commissions (statewide)

State of Georgia (statewide)

Superdistrict (ARC region)

US Congress (statewide)

UWGA13 = United Way of Greater Atlanta (13 counties merged to a single geographic unit)

WFF = Westside Future Fund (subarea of City of Atlanta)

ZIP Code Tabulation Areas (statewide)

The user should note that American Community Survey data represent estimates derived from a surveyed sample of the population, which creates some level of uncertainty, as opposed to an exact measure of the entire population (the full census count is only conducted once every 10 years and does not cover as many detailed characteristics of the population). Therefore, any measure reported by ACS should not be taken as an exact number – this is why a corresponding margin of error (MOE) is also given for ACS measures. The size of the MOE relative to its corresponding estimate value provides an indication of confidence in the accuracy of each estimate. Each MOE is expressed in the same units as its corresponding measure; for example, if the estimate value is expressed as a number, then its MOE will also be a number; if the estimate value is expressed as a percent, then its MOE will also be a percent.

The user should also note that for relatively small geographic areas, such as census tracts shown here, ACS only releases combined 5-year estimates, meaning these estimates represent rolling averages of survey results that were collected over a 5-year span (in this case 2016-2020). Therefore, these data do not represent any one specific point in time or even one specific year. For geographic areas with larger populations, 3-year and 1-year estimates are also available.

For further explanation of ACS estimates and margin of error, visit Census ACS website.

Source: U.S. Census Bureau, Atlanta Regional Commission Date: 2016-2020 Data License: Creative Commons Attribution 4.0 International (CC by 4.0)

Link to the manifest: https://opendata.atlantaregional.com/documents/GARC::acs-2020-data-manifest/about

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

VDOT's MS4 Permit VA0092975, effective June 27, 2024 updates the MS4 regulated area to "Census urban areas with a population of 50,000 or more people as defined by the 2020 U.S. Census Bureau in the Commonwealth of Virginia, as well as previously identified urbanized areas as defined by the 2000 and 2010 U.S. Census Bureau."

This layer is a subset of the 2020 CUA; clipped to Virginia and filtered to show only areas with >50k population.

Link Function: information

Abstract

Dataset quality **: Medium/high quality dataset, not quality checked or modified by the EIDC team

Census data plays a pivotal role in academic data research, particularly when exploring relationships between different demographic characteristics. The significance of this particular dataset lies in its ability to facilitate the merging of various datasets with basic census information, thereby streamlining the research process and eliminating the need for separate API calls.

The American Community Survey is an ongoing survey conducted by the U.S. Census Bureau, which provides detailed social, economic, and demographic data about the United States population. The ACS collects data continuously throughout the decade, gathering information from a sample of households across the country, covering a wide range of topics

Methodology

The Census Data Application Programming Interface (API) is an API that gives the public access to raw statistical data from various Census Bureau data programs.

We used this API to collect various demographic and socioeconomic variables from both the ACS and the Deccenial survey on different geographical levels:

ZCTAs:

ZIP Code Tabulation Areas (ZCTAs) are generalized areal representations of United States Postal Service (USPS) ZIP Code service areas. The USPS ZIP Codes identify the individual post office or metropolitan area delivery station associated with mailing addresses. USPS ZIP Codes are not areal features but a collection of mail delivery routes.

Census Tract:

Census Tracts are small, relatively permanent statistical subdivisions of a county or statistically equivalent entity that can be updated by local participants prior to each decennial census as part of the Census Bureau’s Participant Statistical Areas Program (PSAP).

Census tracts generally have a population size between 1,200 and 8,000 people, with an optimum size of 4,000 people. A census tract usually covers a contiguous area; however, the spatial size of census tracts varies widely depending on the density of settlement. Census tract boundaries are delineated with the intention of being maintained over a long time so that statistical comparisons can be made from census to census.

Block Groups:

Block groups (BGs) are the next level above census blocks in the geographic hierarchy (see Figure 2-1 in Chapter 2). A BG is a combination of census blocks that is a subdivision of a census tract or block numbering area (BNA). (A county or its statistically equivalent entity contains either census tracts or BNAs; it can not contain both.) A BG consists of all census blocks whose numbers begin with the same digit in a given census tract or BNA; for example, BG 3 includes all census blocks numbered in the 300s. The BG is the smallest geographic entity for which the decennial census tabulates and publishes sample data.

Census Blocks:

Census blocks, the smallest geographic area for which the Bureau of the Census collects and tabulates decennial census data, are formed by streets, roads, railroads, streams and other bodies of water, other visible physical and cultural features, and the legal boundaries shown on Census Bureau maps.

Release Date: 2022-11-10.The Census Bureau has reviewed this data product for unauthorized disclosure of confidential information and has approved the disclosure avoidance practices applied (Approval ID: CBDRB-FY22-308)...Release Schedule:.Data in this file come from estimates of business ownership by sex, ethnicity, race, and veteran status from the 2021 Annual Business Survey (ABS) collection. Data are also obtained from administrative records, the 2017 Economic Census, and other economic surveys...Note: The collection year is the year in which the data are collected. A reference year is the year that is referenced in the questions on the survey and in which the statistics are tabulated. For example, the 2021 ABS collection year produces statistics for the 2020 reference year. The "Year" column in the table is the reference year...For more information about ABS planned data product releases, see Tentative ABS Schedule...Key Table Information:.This is one of four tables in the ABS series to provide select economic and demographic characteristics of businesses (CB) for U.S. employer firms that reported the sex, ethnicity, race, and veteran status for up to four persons owning the largest percentage(s) of the business. The data include U.S. firms with paid employees operating during the reference year with receipts of $1,000 or more, which are classified in the North American Industry Classification System (NAICS), Sectors 11 through 99, except for NAICS 111, 112, 482, 491, 521, 525, 813, 814, and 92 which are not covered. Employer firms with more than one domestic establishment are counted in each geographic area and industry in which they operate, but only once in the U.S. and state totals for all sectors. Firms are asked to report their employees as of the March 12 pay period...Data Items and Other Identifying Records:.Data include estimates on:.Number of employer firms (firms with paid employees). Percent of employer firms (%). Sales and receipts of employer firms (reported in $1,000s of dollars). Percent of sales and receipts of employer firms (%). Number of employees (during the March 12 pay period). Percent of employees (%). Annual payroll (reported in $1,000s of dollars). Percent of annual payroll (%)...These data are aggregated by the following demographic classifications of firm for:.All firms. Classifiable (firms classifiable by sex, ethnicity, race, and veteran status). . Sex. Female. Male. Equally male/female. . Ethnicity. Hispanic. Equally Hispanic/non-Hispanic. Non-Hispanic. . Race. White. Black or African American. American Indian and Alaska Native. Asian. Native Hawaiian and Other Pacific Islander. Minority (Firms classified as any race and ethnicity combination other than non-Hispanic and White). Equally minority/nonminority. Nonminority (Firms classified as non-Hispanic and White). . Veteran Status (defined as having served in any branch of the U.S. Armed Forces). Veteran. Equally veteran/nonveteran. Nonveteran. . . . Unclassifiable (firms not classifiable by sex, ethnicity, race, and veteran status). ...Data Notes:.. Business ownership is defined as having 51 percent or more of the stock or equity in the business. Data are provided for businesses owned equally (50% / 50%) by men and women, by Hispanics and non-Hispanics, by minorities and nonminorities, and by veterans and nonveterans.. The detail may not add to the total or subgroup total because a Hispanic or Latino firm may be of any race, and because a firm could be tabulated in more than one racial group. For example, if a firm responded as both Chinese and Black majority owned, the firm would be included in the detailed Asian and Black estimates but would only be counted once toward the higher level all firms' estimates.. References such as "Hispanic- or Latino-owned" businesses refer only to businesses operating in the 50 states and the District of Columbia that self-identified 51 percent or more of their ownership in 2020 to be by individuals of Mexican, Puerto Rican, Cuban or other Hispanic or Latino origin. The ABS does not distinguish between U.S. residents and nonresidents. Companies owned by foreign governments or owned by other companies, foreign or domestic, are included in the category "Unclassifiable."...Business Characteristics:.The ABS was designed to include select questions about business characteristics from multiple reference periods and to incorporate new content each survey year based on topics of relevance...Respondent firms include all firms that responded to the characteristics tabulated in this dataset and reported sex, ethnicity, race, or veteran status, or that were not classifiable by sex, ethnicity, race, or veteran status. Percentages are for r...

U.S. Census Bureau 2020 block groups within the City of Seattle with American Community Survey (ACS) 5-year series data of frequently requested topics. Data is pulled from block group tables for the most recent ACS vintage. Seattle neighborhood geography of Council Districts, Comprehensive Plan Growth Areas are also included based on block group assignment.

This dataset was developed by the Research & Analytics Group at the Atlanta Regional Commission using data from the U.S. Census Bureau across all standard and custom geographies at statewide summary level where applicable.

For a deep dive into the data model including every specific metric, see the ACS 2016-2020 Data Manifest. The manifest details ARC-defined naming conventions, field names/descriptions and topics, summary levels; source tables; notes and so forth for all metrics.

Prefixes:

None

Count

p

Percent

r

Rate

m

Median

a

Mean (average)

t

Aggregate (total)

ch

Change in absolute terms (value in t2 - value in t1)

pch

Percent change ((value in t2 - value in t1) / value in t1)

chp

Change in percent (percent in t2 - percent in t1)

s

Significance flag for change: 1 = statistically significant with a 90% CI, 0 = not statistically significant, blank = cannot be computed

Suffixes:

_e20

Estimate from 2016-20 ACS

_m20

Margin of Error from 2016-20 ACS

_e10

2006-10 ACS, re-estimated to 2020 geography

_m10

Margin of Error from 2006-10 ACS, re-estimated to 2020 geography

_e10_20

Change, 2010-20 (holding constant at 2020 geography)

Geographies

AAA = Area Agency on Aging (12 geographic units formed from counties providing statewide coverage)

ARWDB7 = Atlanta Regional Workforce Development Board (7 counties merged to a single geographic unit)

Census Tracts (statewide)

CFGA23 = Community Foundation for Greater Atlanta (23 counties merged to a single geographic unit)

City (statewide)

City of Atlanta Council Districts (City of Atlanta)

City of Atlanta Neighborhood Planning Unit (City of Atlanta)

City of Atlanta Neighborhood Planning Unit STV (subarea of City of Atlanta)

City of Atlanta Neighborhood Statistical Areas (City of Atlanta)

County (statewide)

Georgia House (statewide)

Georgia Senate (statewide)

MetroWater15 = Atlanta Metropolitan Water District (15 counties merged to a single geographic unit)

Regional Commissions (statewide)

State of Georgia (statewide)

Superdistrict (ARC region)

US Congress (statewide)

UWGA13 = United Way of Greater Atlanta (13 counties merged to a single geographic unit)

WFF = Westside Future Fund (subarea of City of Atlanta)

ZIP Code Tabulation Areas (statewide)

The user should note that American Community Survey data represent estimates derived from a surveyed sample of the population, which creates some level of uncertainty, as opposed to an exact measure of the entire population (the full census count is only conducted once every 10 years and does not cover as many detailed characteristics of the population). Therefore, any measure reported by ACS should not be taken as an exact number – this is why a corresponding margin of error (MOE) is also given for ACS measures. The size of the MOE relative to its corresponding estimate value provides an indication of confidence in the accuracy of each estimate. Each MOE is expressed in the same units as its corresponding measure; for example, if the estimate value is expressed as a number, then its MOE will also be a number; if the estimate value is expressed as a percent, then its MOE will also be a percent.

The user should also note that for relatively small geographic areas, such as census tracts shown here, ACS only releases combined 5-year estimates, meaning these estimates represent rolling averages of survey results that were collected over a 5-year span (in this case 2016-2020). Therefore, these data do not represent any one specific point in time or even one specific year. For geographic areas with larger populations, 3-year and 1-year estimates are also available.

For further explanation of ACS estimates and margin of error, visit Census ACS website.

Source: U.S. Census Bureau, Atlanta Regional Commission Date: 2016-2020 Data License: Creative Commons Attribution 4.0 International (CC by 4.0)

Link to the manifest: https://opendata.atlantaregional.com/documents/GARC::acs-2020-data-manifest/about

The purpose of this data package is to offer demographic data for U.S. cities. The data sources are multiple, the most important one being the U.S. Census Bureau, American Community Survey. In this case, the data was organized by the Big Cities Health Coalition (BCHC). Others are the New York City Department of City Planning and Department of Parks and Recreation, data being available through the NYC Open Data.