Context :

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

Dataset source

United States Census Bureau

Sample Query

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

Terms of use

This dataset is publicly available for anyone to use under the following terms provided by the Dataset Source - http://www.data.gov/privacy-policy#data_policy - and is provided "AS IS" without any warranty, express or implied, from Google. Google disclaims all liability for any damages, direct or indirect, resulting from the use of the dataset.

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

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

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

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

Starting in July, data.census.gov will be the primary way to access Census Bureau data, including upcoming releases from the 2018 American Community Survey, 2017 Economic Census, 2020 Census and more. After July 1, 2019, all new data (previously released on American FactFinder) will be released on this new data platform. (https://factfinder.census.gov/faces/nav/jsf/pages/index.xhtml)

About this dataset

Context

The dataset tabulates the United States median household income by race. The dataset can be utilized to understand the racial distribution of United States income.

Content

The dataset will have the following datasets when applicable

Please note: The 2020 1-Year ACS estimates data was not reported by the Census Bureau due to the impact on survey collection and analysis caused by COVID-19. Consequently, median household income data for 2020 is unavailable for large cities (population 65,000 and above).

• United States median household income breakdown by race betwen 2012 and 2022
• Median Household Income by Racial Categories in United States (2022)

Good to know

Margin of Error

Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.

Custom data

If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.

Inspiration

Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.

Interested in deeper insights and visual analysis?

Explore our comprehensive data analysis and visual representations for a deeper understanding of United States median household income by race. You can refer the same here

The Economic Census is the U.S. Government's official five-year measure of American business and the economy. It is conducted by the U.S. Census Bureau, and response is required by law. In October through December of the census year, forms are sent out to nearly 4 million businesses, including large, medium and small companies representing all U.S. locations and industries. Respondents were asked to provide a range of operational and performance data for their companies.This dataset presents data on major categories of products sold/services rendered for establishments of firms with payroll by kind of business.

The American Community Survey (ACS) is an ongoing survey that provides vital information on a yearly basis about our nation and its people by contacting over 3.5 million households across the country. The resulting data provides incredibly detailed demographic information across the US aggregated at various geographic levels which helps determine how more than $675 billion in federal and state funding are distributed each year. Businesses use ACS data to inform strategic decision-making. ACS data can be used as a component of market research, provide information about concentrations of potential employees with a specific education or occupation, and which communities could be good places to build offices or facilities. For example, someone scouting a new location for an assisted-living center might look for an area with a large proportion of seniors and a large proportion of people employed in nursing occupations. Through the ACS, we know more about jobs and occupations, educational attainment, veterans, whether people own or rent their homes, and other topics. Public officials, planners, and entrepreneurs use this information to assess the past and plan the future. For more information, see the Census Bureau's ACS Information Guide . This public dataset is hosted in Google BigQuery as part of the Google Cloud Public Datasets Program , with Carto providing cleaning and onboarding support. It is included in BigQuery's 1TB/mo of free tier processing. This means that each user receives 1TB of free BigQuery processing every month, which can be used to run queries on this public dataset. Watch this short video to learn how to get started quickly using BigQuery to access public datasets. What is BigQuery .

U.S. Census BlocksThis feature layer, utilizing National Geospatial Data Asset (NGDA) data from the U.S. Census Bureau (USCB), displays Census Blocks in the United States. A brief description of Census Blocks, per USCB, is that "Census blocks are statistical areas bounded by visible features such as roads, streams, and railroad tracks, and by nonvisible boundaries such as property lines, city, township, school district, county limits and short line-of-sight extensions of roads." Also, "the smallest level of geography you can get basic demographic data for, such as total population by age, sex, and race."Census Block 1007Data currency: This cached Esri federal service is checked weekly for updates from its enterprise federal source (Census Blocks) and will support mapping, analysis, data exports and OGC API – Feature access.NGDAID: 69 (Series Information for 2020 Census Block State-based TIGER/Line Shapefiles, Current)OGC API Features Link: (U.S. Census Blocks - OGC Features) copy this link to embed it in OGC Compliant viewersFor more information, please visit: What are census blocksFor feedback please contact: Esri_US_Federal_Data@esri.comNGDA Data SetThis data set is part of the NGDA Governmental Units, and Administrative and Statistical Boundaries Theme Community. Per the Federal Geospatial Data Committee (FGDC), this theme is defined as the "boundaries that delineate geographic areas for uses such as governance and the general provision of services (e.g., states, American Indian reservations, counties, cities, towns, etc.), administration and/or for a specific purpose (e.g., congressional districts, school districts, fire districts, Alaska Native Regional Corporations, etc.), and/or provision of statistical data (census tracts, census blocks, metropolitan and micropolitan statistical areas, etc.). Boundaries for these various types of geographic areas are either defined through a documented legal description or through criteria and guidelines. Other boundaries may include international limits, those of federal land ownership, the extent of administrative regions for various federal agencies, as well as the jurisdictional offshore limits of U.S. sovereignty. Boundaries associated solely with natural resources and/or cultural entities are excluded from this theme and are included in the appropriate subject themes."For other NGDA Content: Esri Federal Datasets

These are full-resolution boundary files, derived from TIGER/Line Shapefiles, the fully-supported, core geographic products from the US Census Bureau. They are extracts of selected geographic and cartographic information from the US Census Bureau's Master Address File/Topologically Integrated Geographic Encoding and Referencing (MAF/TIGER) database. These include information for the 50 states, the District of Columbia, Puerto Rico, and the Island areas (American Samoa, the Commonwealth of the Northern Mariana Islands, Guam, and the United States Virgin Islands). These include polygon boundaries of geographic and statistical areas, linear features including roads and hydrography, and point features. These files are converted and made available in BigQuery by the Cloud Public Datasets Program to support geospatial analysis through BigQuery GIS . The dataset describes the boundaries of the following US areas: States Counties 115th & 116th US Congressional Districts Metropolitan and Micropolitan Statistical Areas Urban Areas City Limits Combined Statistical Areas Coastline Populated Places National border For more details on each dataset, see the technical documentation published by the Census Bureau. This public dataset is hosted in Google BigQuery and is included in BigQuery's 1TB/mo of free tier processing. This means that each user receives 1TB of free BigQuery processing every month, which can be used to run queries on this public dataset. Watch this short video to learn how to get started quickly using BigQuery to access public datasets. What is BigQuery .</

This dataset contains data from the P.L. 94-171 2020 Census Redistricting Program. The 2020 Census Redistricting Data Program provides states the opportunity to delineate voting districts and to suggest census block boundaries for use in the 2020 Census redistricting data tabulations (Public Law 94-171 Redistricting Data File). In addition, the Redistricting Data Program will periodically collect state legislative and congressional district boundaries if they are changed by the states. The program is also responsible for the effective delivery of the 2020 Census P.L. 94-171 Redistricting Data statutorily required by one year from Census Day. The program ensures continued dialogue with the states in regard to 2020 Census planning, thereby allowing states ample time for their planning, response, and participation. The U.S. Census Bureau will deliver the Public Law 94-171 redistricting data to all states by Sept. 30, 2021. COVID-19-related delays and prioritizing the delivery of the apportionment results delayed the Census Bureau’s original plan to deliver the redistricting data to the states by April 1, 2021.

Data in this dataset contains information on population, diversity, race, ethnicity, housing, household, vacancy rate for 2020 for various geographies (county, MCD, Philadelphia Planning Districts (referred to as county planning areas [CPAs] internally, Census designated places, tracts, block groups, and blocks)

For more information on the 2020 Census, visit https://www.census.gov/programs-surveys/decennial-census/about/rdo/summary-files.html

PLEASE NOTE: 2020 Decennial Census data has had noise injected into it because of the Census's new Disclosure Avoidance System (DAS). This can mean that population counts and characteristics, especially when they are particularly small, may not exactly correspond to the data as collected. As such, caution should be exercised when examining areas with small counts. Ron Jarmin, acting director of the Census Bureau posted a discussion of the redistricting data, which outlines what to expect with the new DAS. For more details on accuracy you can read it here: https://www.census.gov/newsroom/blogs/director/2021/07/redistricting-data.html

2010-2018. US Census Annual Estimates of the Resident Population for Selected Age Groups by Sex for the United States. The estimates are based on the 2010 Census and reflect changes to the April 1, 2010 population due to the Count Question Resolution program and geographic program revisions. Median age is calculated based on single year of age. For population estimates methodology statements, see http://www.census.gov/popest/methodology/index.html.

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. ZIP Code Tabulation Areas (ZCTAs) are approximate area representations of U.S. Postal Service (USPS) ZIP Code service areas that the Census Bureau creates to present statistical data for each decennial census. The Census Bureau delineates ZCTA boundaries for the United States, Puerto Rico, American Samoa, Guam, the Commonwealth of the Northern Mariana Islands, and the U.S. Virgin Islands once each decade following the decennial census. Data users should not use ZCTAs to identify the official USPS ZIP Code for mail delivery. The USPS makes periodic changes to ZIP Codes to support more efficient mail delivery. The Census Bureau uses tabulation blocks as the basis for defining each ZCTA. Tabulation blocks are assigned to a ZCTA based on the most frequently occurring ZIP Code for the addresses contained within that block. The most frequently occurring ZIP Code also becomes the five-digit numeric code of the ZCTA. These codes may contain leading zeros. Blocks that do not contain addresses but are surrounded by a single ZCTA (enclaves) are assigned to the surrounding ZCTA. Because the Census Bureau only uses the most frequently occurring ZIP Code to assign blocks, a ZCTA may not exist for every USPS ZIP Code. Some ZIP Codes may not have a matching ZCTA because too few addresses were associated with the specific ZIP Code or the ZIP Code was not the most frequently occurring ZIP Code within any of the blocks where it exists. The ZCTA boundaries in this release are those delineated following the 2020 Census.

About this dataset

Context

The dataset presents the mean household income for each of the five quintiles in Black Earth, WI, as reported by the U.S. Census Bureau. The dataset highlights the variation in mean household income across quintiles, offering valuable insights into income distribution and inequality.

Key observations

• Income disparities: The mean income of the lowest quintile (20% of households with the lowest income) is 17,947, while the mean income for the highest quintile (20% of households with the highest income) is 162,641. This indicates that the top earners earn 9 times compared to the lowest earners.
• *Top 5%: * The mean household income for the wealthiest population (top 5%) is 197,891, which is 121.67% higher compared to the highest quintile, and 1102.64% higher compared to the lowest quintile.

Content

When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2017-2021 5-Year Estimates.

Income Levels:

• Lowest Quintile
• Second Quintile
• Third Quintile
• Fourth Quintile
• Highest Quintile
• Top 5 Percent

Variables / Data Columns

• Income Level: This column showcases the income levels (As mentioned above).
• Mean Household Income: Mean household income, in 2022 inflation-adjusted dollars for the specific income level.

Good to know

Margin of Error

Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.

Custom data

If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.

Inspiration

Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.

Recommended for further research

This dataset is a part of the main dataset for Black Earth median household income. You can refer the same here

This layer presents the 2020 U.S. Census Tract 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.

About this dataset

Context

The dataset tabulates the State Line population distribution across 18 age groups. It lists the population in each age group along with the percentage population relative of the total population for State Line. The dataset can be utilized to understand the population distribution of State Line by age. For example, using this dataset, we can identify the largest age group in State Line.

Key observations

The largest age group in State Line, ID was for the group of age 25 to 29 years years with a population of 3 (100%), according to the ACS 2019-2023 5-Year Estimates. At the same time, the smallest age group in State Line, ID was the Under 5 years years with a population of 0 (0%). Source: U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates

Content

When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates

Age groups:

• Under 5 years
• 5 to 9 years
• 10 to 14 years
• 15 to 19 years
• 20 to 24 years
• 25 to 29 years
• 30 to 34 years
• 35 to 39 years
• 40 to 44 years
• 45 to 49 years
• 50 to 54 years
• 55 to 59 years
• 60 to 64 years
• 65 to 69 years
• 70 to 74 years
• 75 to 79 years
• 80 to 84 years
• 85 years and over

Variables / Data Columns

• Age Group: This column displays the age group in consideration
• Population: The population for the specific age group in the State Line is shown in this column.
• % of Total Population: This column displays the population of each age group as a proportion of State Line total population. Please note that the sum of all percentages may not equal one due to rounding of values.

Good to know

Margin of Error

Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.

Custom data

If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.

Inspiration

Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.

Recommended for further research

This dataset is a part of the main dataset for State Line Population by Age. You can refer the same here

Content

More details about each file are in the individual file descriptions.

Context

This is a dataset from the U.S. Census Bureau hosted by the Federal Reserve Economic Database (FRED). FRED has a data platform found here and they update their information according the amount of data that is brought in. Explore the U.S. Census Bureau using Kaggle and all of the data sources available through the U.S. Census Bureau organization page!

• Update Frequency: This dataset is updated daily.

Acknowledgements

This dataset is maintained using FRED's API and Kaggle's API.

Cover photo by Cole Mader on Unsplash
Unsplash Images are distributed under a unique Unsplash License.

About this dataset

Context

The dataset presents median household incomes for various household sizes in United States, as reported by the U.S. Census Bureau. The dataset highlights the variation in median household income with the size of the family unit, offering valuable insights into economic trends and disparities within different household sizes, aiding in data analysis and decision-making.

Key observations

• Of the 7 household sizes (1 person to 7-or-more person households) reported by the census bureau, all of the household sizes were found in United States. Across the different household sizes in United States the mean income is $94,149, and the standard deviation is $26,829. The coefficient of variation (CV) is 28.50%. This high CV indicates high relative variability, suggesting that the incomes vary significantly across different sizes of households.
• In the most recent year, 2021, The smallest household size for which the bureau reported a median household income was 1-person households, with an income of $38,463. It then further increased to $114,329 for 7-person households, the largest household size for which the bureau reported a median household income.

https://i.neilsberg.com/ch/united-states-median-household-income-by-household-size.jpeg" alt="United States median household income, by household size (in 2022 inflation-adjusted dollars)">

Content

When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2017-2021 5-Year Estimates.

Household Sizes:

• 1-person households
• 2-person households
• 3-person households
• 4-person households
• 5-person households
• 6-person households
• 7-or-more-person households

Variables / Data Columns

• Household Size: This column showcases 7 household sizes ranging from 1-person households to 7-or-more-person households (As mentioned above).
• Median Household Income: Median household income, in 2022 inflation-adjusted dollars for the specific household size.

Good to know

Margin of Error

Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.

Custom data

If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.

Inspiration

Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.

Recommended for further research

This dataset is a part of the main dataset for United States median household income. You can refer the same here

blockgroupdemographics A selection of variables from the US Census Bureau's American Community Survey 5YR and TIGER/Line publications. Overview The U.S. Census Bureau published it's American Community Survey 5 Year with more than 37,000 variables. Most ACS advanced users will have their personal list of favorites, but this conventional wisdom is not available to occasional analysts. This publication re-shares 174 select demographic data from the U.S. Census Bureau to provide an supplement to Open Environments Block Group publications. These results do not reflect any proprietary or predictive model. Rather, they extract from Census Bureau results. For additional support or more detail, please see the Census Bureau citations below. The first 170 demographic variables are taken from popular variables in the American Community Survey (ACS) including age, race, income, education and family structure. A full list of ACS variable names and definitions can be found in the ACS 'Table Shells' here https://www.census.gov/programs-surveys/acs/technical-documentation/table-shells.html. The dataset includes 4 additional columns from the Census' TIGER/Line publication. See Open Environment's 2023blockgroupcartographics publication for the shapes of each block group. For each block group, the dataset includes land area (ALAND), water area (AWATER), interpolated latitude (INTPTLAT) and longitude (INTPTLON). These are valuable for calculating population density variables which combine ACS populations and TIGER land area. Files The resulting dataset is available with other block group based datasets on Harvard's Dataverse https://dataverse.harvard.edu/ in Open Environment's Block Group Dataverse https://dataverse.harvard.edu/dataverse/blockgroupdatasets/. This data simply requires csv reader software or pythons pandas package. Supporting the data file, is acsvars.csv, a list of the Census variable names and their corresponding description. Citations “American Community Survey 5-Year Data (2019-2023).” Census.gov, US Census Bureau, https://www.census.gov/data/developers/data-sets/acs-5year.html. 2023 "American Community Survey, Table Shells and Table List” Census.gov, US Census Bureau, https://www.census.gov/programs-surveys/acs/technical-documentation/table-shells.html Python Package Index - PyPI. Python Software Foundation. "A simple wrapper for the United States Census Bureau’s API.". Retrieved from https://pypi.org/project/census/

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 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. Census blocks cover all territory in the United States, Puerto Rico, and the Island Areas (American Samoa, Guam, the Commonwealth of the Northern Mariana Islands, and the U.S. Virgin Islands). Blocks are the smallest geographic areas for which the Census Bureau publishes data from the decennial census. A block may consist of one or more faces.

U.S. Census Populated Place Areas represents the 2020 U.S. Census populated place areas of the United States that include incorporated places, cities, and census designated places identified by the U.S. Census Bureau.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. The Population Class field values represent population ranges as follows:Population from 0 - 249Population from 250 - 499Population from 500 - 999Population from 1,000 - 2,499Population from 2,500 - 9,999Population from 10,000 - 49,999Population from 50,000 - 99,999Population from 100,000 - 249,999Population from 250,000 - 499,999Population 500,000 and overThis 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.

The United States Census Bureau TIGER dataset contains the 2018 boundaries for the primary governmental divisions of the United States. In addition to the fifty states, the Census Bureau treats the District of Columbia, Puerto Rico, and each of the island areas (American Samoa, the Commonwealth of the Northern Mariana …