Net change in housing units arising from new buildings, demolitions, or alterations for NYC Census Blocks since 2010. The NYC Department of City Planning's (DCP) Housing Database provide the 2010 census count of housing units, the net change in Class A housing units since the census, and the count of units pending completion for commonly used political and statistical boundaries. These tables are aggregated from the DCP Housing Database, which is derived from Department of Buildings (DOB)-approved housing construction and demolition jobs filed or completed in NYC since January 1, 2010. Net housing unit change is calculated as the sum of all three construction job types that add or remove residential units: new buildings, major alterations, and demolitions, and can be used to determine the change in legal housing units across time and space. All previously released versions of this data are available at BYTES of the BIG APPLE - Archive.

2020 Census data for the city of Boston, Boston neighborhoods, census tracts, block groups, and voting districts. In the 2020 Census, the U.S. Census Bureau divided Boston into 207 census tracts (~4,000 residents) made up of 581 smaller block groups. The Boston Planning and Development Agency uses the 2020 tracts to approximate Boston neighborhoods. The 2020 Census Redistricting data also identify Boston’s voting districts.

For analysis of Boston’s 2020 Census data including graphs and maps by the BPDA Research Division and Office of Digital Cartography and GIS, see 2020 Census Research Publications

For a complete official data dictionary, please go to 2020 Census State Redistricting Data (Public Law 94-171) Summary File, Chapter 6. Data Dictionary. 2020 Census State Redistricting Data (Public Law 94-171) Summary File

2020 Census Tracts In Boston

2020 Census Block Groups In Boston

Boston Neighborhood Boundaries Approximated By 2020 Census Tracts

Boston Voting District Boundaries

This is 2020 decennial census data at the county level. Technical documentation for the 2020 census is available here: https://www2.census.gov/programs-surveys/decennial/2020/technical-documentation/complete-tech-docs/summary-file/2020Census_PL94_171Redistricting_NationalTechDoc.pdf

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.

Census Tracts from the 2020 US Census for New York City clipped to the shoreline. These boundary files are derived from the US Census Bureau's TIGER project and have been geographically modified to fit the New York City base map. Because some census tracts are under water not all census tracts are contained in this file, only census tracts that are partially or totally located on land have been mapped in this file.

All previously released versions of this data are available at the DCP Website: BYTES of the BIG APPLE.

A. SUMMARY This dataset maps 2020 census tracts to Analysis Neighborhoods. The Department of Public Health and the Mayor’s Office of Housing and Community Development, with support from the Planning Department originally created the 41 Analysis Neighborhoods by grouping 2010 Census tracts, using common real estate and residents’ definitions for the purpose of providing consistency in the analysis and reporting of socio-economic, demographic, and environmental data, and data on City-funded programs and services. They are not codified in Planning Code nor Administrative Code. B. HOW THE DATASET IS CREATED This dataset is produced by mapping the 2020 Census tracts to Analysis neighborhoods. C. UPDATE PROCESS This dataset is static. Changes to the census tract boundaries are tracked in multiple datasets. See here for the 2010 census tracts assigned to neighborhoods D. HOW TO USE THIS DATASET This boundary file can be joined to other census datasets on GEOID, which is the primary key for census tracts in the dataset E. RELATED DATASET 2020 census tract boundaries for San Francisco can be found here

This GIS layer contains the geographical boundaries of the 2020 census tracts for Loudoun County, Virginia. The 2020 Census tract boundaries are used for Census Bureau statistical data tabulation purposes, including the 2020 Decennial Census and American Community Surveys. Census tracts are part of the sub-county census geography hierarchy of tracts, block groups, and blocks. The three census geographies nest to each other, forming a hierarchy of census tract, followed by block groups, and then blocks, with blocks being the smallest. A census tract consists of one or more census block groups and is a cluster of census blocks within the same census tract. Tracts are uniquely identified within a County by a six digit number. The last two digits will be zeros unless earlier divisions of the census tract occurred as a result of population growth. Tracts are designed to be relatively homogeneous units with respect to population characteristics, economic status, and living conditions. They generally have at least 1,200 people or 480 housing units, and no more than 8,000 people or 3,200 housing units, with an optimal size of 4,000 people or 1,600 housing units. This 2020 Census tract GIS layer's boundaries are based on the U.S. Census Bureau Census 2020 TIGER/Line files. The boundaries are an extract of aerial photography and cartographic information, such as roads and streams, from the Loudoun County GIS system. Census tracts are bounded on all sides by visible features, such as roads, streams, lakes, power lines, and railroad tracks, and/or by non-visible boundaries such as town and county boundaries, and short line-of-sight extensions of streets and roads.

Analysis of ‘2020 Census Tracts (water areas included) - Tabular’ provided by Analyst-2 (analyst-2.ai), based on source dataset retrieved from https://catalog.data.gov/dataset/ea43ac51-bbc0-4d4e-b943-01ed2896c230 on 13 February 2022.

--- Dataset description provided by original source is as follows ---

2020 Census Tracts (water areas included) from the US Census for New York City. These boundary files are derived from the US Census Bureau's TIGER data products and have been geographically modified to fit the New York City base map. All previously released versions of this data are available at BYTES of the BIG APPLE- Archive.

--- Original source retains full ownership of the source dataset ---

The United States Census Bureau regularly releases a geodatabase named TIGER. This dataset contains the 2020 census tracts. Tract areas vary tremendously, but in urban areas are roughly equivalent to a neighborhood. There are just over 85000 polygon features covering the United States, the District of Columbia, Puerto Rico, and the Island areas. For full technical details on all TIGER 2020 products, see the TIGER technical documentation.

This dataset includes 2020 census places as identified or delineated by the U.S. Census Bureau and made available through their TIGER/Line files. Places include both Incorporated Places (usually cities, towns, or villages) and Census Designated Places (statistical entities). Incorporated places are those reported to the Census Bureau as legally in existence as of January 1, 2020. Incorporated places may extend across counties. Census Designated Places (CDPs) are the statistical counterparts of incorporated places. They are settled concentrations of population that are identifiable by name but not legally incorporated under the laws of the state in which the CDPs are located. The Census Bureau defines CDP boundaries in cooperation with local partners. CDP boundaries usually coincide with visible features or the boundary of an adjacent Incorporated Place or another legal entity boundary. They have no legal status, no elected officials to serve traditional municipal functions, and no population size requirements for classification. For more information about census geographies, see https://www2.census.gov/geo/pdfs/maps-data/data/tiger/tgrshp2020/TGRSHP2020_TechDoc_Ch4.pdf . This file is for reference use only. NCTCOG and its members are not responsible for errors or inaccuracies in the file.

About this dataset

Context

The dataset tabulates the Huntingdon County population by gender and age. The dataset can be utilized to understand the gender distribution and demographics of Huntingdon County.

Content

The dataset constitues the following two datasets across these two themes

• Huntingdon County, PA Population Breakdown by Gender
• Huntingdon County, PA Population Breakdown by Gender and Age

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/.

Census tracts are created by the U.S. Census Bureau to be small, relatively permanent statistical subdivisions of a county. Census tracts average about 4,000 inhabitants: minimum population –1,200 and maximum population –8,000. Census tracts are split or merged every 10 years, depending on population change, with local feedback through the Participant Statistical Areas Program (PSAP).

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.

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.

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.

Analysis of ‘Loudoun 2020 Census Block Groups’ provided by Analyst-2 (analyst-2.ai), based on source dataset retrieved from https://catalog.data.gov/dataset/e511936d-7b08-4831-9218-b35999e55bb2 on 27 January 2022.

--- Dataset description provided by original source is as follows ---

--- Original source retains full ownership of the source dataset ---

About this dataset

Context

The dataset presents median income data over a decade or more for males and females categorized by Total, Full-Time Year-Round (FT), and Part-Time (PT) employment in Brookside. It showcases annual income, providing insights into gender-specific income distributions and the disparities between full-time and part-time work. The dataset can be utilized to gain insights into gender-based pay disparity trends and explore the variations in income for male and female individuals.

Key observations: Insights from 2023

Based on our analysis ACS 2019-2023 5-Year Estimates, we present the following observations: - All workers, aged 15 years and older: In Brookside, the median income for all workers aged 15 years and older, regardless of work hours, was $32,222 for males and $23,646 for females.

These income figures indicate a substantial gender-based pay disparity, showcasing a gap of approximately 27% between the median incomes of males and females in Brookside. With women, regardless of work hours, earning 73 cents to each dollar earned by men, this income disparity reveals a concerning trend toward wage inequality that demands attention in thetown of Brookside.

As there was no available median income data for females, conducting a comprehensive assessment of gender-based pay disparity in Brookside was not feasible.

Content

When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates. All incomes have been adjusting for inflation and are presented in 2023-inflation-adjusted dollars.

Gender classifications include:

• Male
• Female

Employment type classifications include:

• Full-time, year-round: A full-time, year-round worker is a person who worked full time (35 or more hours per week) and 50 or more weeks during the previous calendar year.
• Part-time: A part-time worker is a person who worked less than 35 hours per week during the previous calendar year.

Variables / Data Columns

• Year: This column presents the data year. Expected values are 2010 to 2023
• Male Total Income: Annual median income, for males regardless of work hours
• Male FT Income: Annual median income, for males working full time, year-round
• Male PT Income: Annual median income, for males working part time
• Female Total Income: Annual median income, for females regardless of work hours
• Female FT Income: Annual median income, for females working full time, year-round
• Female PT Income: Annual median income, for females working part time

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 Brookside median household income by race. You can refer the same here

This GIS layer contains the geographical boundaries of the 2020 census block groups for Loudoun County, Virginia. The 2020 Census block group boundaries are used for Census Bureau statistical data tabulation purposes, including the 2020 Decennial Census and American Community Surveys. Census block groups are part of the sub-county census geography hierarchy of tracts, block groups, and blocks. The three census geographies nest to each other, forming a hierarchy of census tract, followed by block groups, and then blocks, with blocks being the smallest. A census block group is a cluster of census blocks within the same census tract that have the same first digit of their four-digit census block numbers within a census tract. For example, block group 3 within census tract 610700 is a cluster of all the blocks numbered from 3000 to 3999 in that census tract. Block groups are uniquely numbered within census tracts, with the block group's valid range being 0 to 9. Block Groups are designed to be relatively homogeneous units with respect to population characteristics, economic status, and living conditions, census tracts and generally contain between 600 and 3,000 people or 240 and 1,200 housing units. This 2010 Census block group GIS layer's boundaries are based on the U.S. Census Bureau Census 2020 TIGER/Line files. The boundaries are an extract of aerial photography and cartographic information, such as roads and streams, from the Loudoun County GIS system. Census block groups are bounded on all sides by visible features, such as roads, streams, lakes, power lines, and railroad tracks, and/or by non-visible boundaries such as town and county boundaries, and short line-of-sight extensions of streets and roads.