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 on the DCP Website: BYTES of the BIG APPLE. Current version: 25d

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

This resource is a member of a series. 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) System (MTS). The MTS represents a seamless national file with no overlaps or gaps between parts, however, each TIGER/Line shapefile is designed to stand alone as an independent data set, or they can be combined to cover the entire nation. Census tracts are small, relatively permanent statistical subdivisions of a county or equivalent entity and were defined by local participants as part of the 2020 Census Participant Statistical Areas Program. The Census Bureau delineated the census tracts in situations where no local participant existed or where all the potential participants declined to participate. The primary purpose of census tracts is to provide a stable set of geographic units for the presentation of census data and comparison back to previous decennial censuses. Census tracts generally have a population size between 1,200 and 8,000 people, with an optimum size of 4,000 people. When first delineated, census tracts were designed to be homogeneous with respect to population characteristics, economic status, and living conditions. The spatial size of census tracts varies widely depending on the density of settlement. Physical changes in street patterns caused by highway construction, new development, and so forth, may require boundary revisions. In addition, census tracts occasionally are split due to population growth, or combined because of substantial population decline. Census tract boundaries generally follow visible and identifiable features. They may follow legal boundaries such as minor civil division or incorporated place boundaries in some states and situations to allow for census tract-to-governmental unit relationships where the governmental boundaries tend to remain unchanged between censuses. State and county boundaries always are census tract boundaries in the standard Census Bureau geographic hierarchy. In a few rare instances, a census tract may consist of noncontiguous areas. These noncontiguous areas may occur where the census tracts are coextensive with all or parts of legal entities that are themselves noncontiguous.

Context

There are a number of Kaggle datasets that provide spatial data around New York City. For many of these, it may be quite interesting to relate the data to the demographic and economic characteristics of nearby neighborhoods. I hope this data set will allow for making these comparisons without too much difficulty.

Exploring the data and making maps could be quite interesting as well.

Content

This dataset contains two CSV files:

1. nyc_census_tracts.csv

   This file contains a selection of census data taken from the ACS DP03 and DP05 tables. Things like total population, racial/ethnic demographic information, employment and commuting characteristics, and more are contained here. There is a great deal of additional data in the raw tables retrieved from the US Census Bureau website, so I could easily add more fields if there is enough interest.

   I obtained data for individual census tracts, which typically contain several thousand residents.

2. census_block_loc.csv

   For this file, I used an online FCC census block lookup tool to retrieve the census block code for a 200 x 200 grid containing New York City and a bit of the surrounding area. This file contains the coordinates and associated census block codes along
   with the state and county names to make things a bit more readable to users.

   Each census tract is split into a number of blocks, so one must extract the census tract code from the block code.

Acknowledgements

The data here was taken from the American Community Survey 2015 5-year estimates (https://factfinder.census.gov/faces/nav/jsf/pages/index.xhtml).

The census block coordinate data was taken from the FCC Census Block Conversions API (https://www.fcc.gov/general/census-block-conversions-api)

As public data from the US government, this is not subject to copyright within the US and should be considered public domain.

These layers represent census tracts (or portions of tracts) in New York State that may qualify for New York State’s historic tax credit programs. These programs are administered by the New York State Division for Historic Preservation, also known as the New York State Historic Preservation Office (SHPO). For more information, see SHPO’s Tax Credit Programs web page: https://parks.ny.gov/shpo/tax-credit-programs/The current layers are effective April 1, 2025 through March 31, 2026. They derive from data in yearly updates to the American Community Survey 5-Year Estimates. The most recent data used in these layers are the 2019–2023 estimates.The basic qualifying criteria are based on Table B19113 of the American Community Survey 5-Year Estimates. This table represents Median Family Income in the Past 12 Months (in Inflation-adjusted Dollars). If a tract’s median family income minus its margin of error is less than or equal to the statewide median family income plus the statewide margin of error, then it qualifies for the commercial and state homeowner tax credit programs. Properties in certain cities may qualify for the state homeowner tax credit program, even if they are in census tracts that do not meet the basic qualifying criteria. The enhanced qualifying criteria are based on Table S1701 of the American Community Survey 5-Year Estimates. This table represents Poverty Status in the Past 12 Months as a percentage. If a city’s estimated percentage below poverty level plus the margin of error is greater than or equal to 15.5%, then all locations within the city boundary qualify for the state homeowner tax credit program.If a tract or city no longer meets the criteria, its qualifying status is extended for a two-year grace period.If you have questions about the tax credit programs or the information in these layers, please see SHPO’s Contact page for a list of staff who review projects in your county.

New York City census tract boundaries derived from the 2000 US Census- water included. These districts were created by the Department of City Planning to aid city agencies in administering public services.

New York City census tract boundaries for 2000.

The 2023 cartographic boundary shapefiles are simplified representations of selected geographic areas from the U.S. Census Bureau's Master Address File / Topologically Integrated Geographic Encoding and Referencing (MAF/TIGER) Database (MTDB). These boundary files are specifically designed for small-scale thematic mapping. When possible, generalization is performed with the intent to maintain the hierarchical relationships among geographies and to maintain the alignment of geographies within a file set for a given year. Geographic areas may not align with the same areas from another year. Some geographies are available as nation-based files while others are available only as state-based files. Census tracts are small, relatively permanent statistical subdivisions of a county or equivalent entity, and were defined by local participants as part of the 2020 Census Participant Statistical Areas Program. The Census Bureau delineated the census tracts in situations where no local participant existed or where all the potential participants declined to participate. The primary purpose of census tracts is to provide a stable set of geographic units for the presentation of census data and comparison back to previous decennial censuses. Census tracts generally have a population size between 1,200 and 8,000 people, with an optimum size of 4,000 people. When first delineated, census tracts were designed to be homogeneous with respect to population characteristics, economic status, and living conditions. The spatial size of census tracts varies widely depending on the density of settlement. Physical changes in street patterns caused by highway construction, new development, and so forth, may require boundary revisions. In addition, census tracts occasionally are split due to population growth, or combined as a result of substantial population decline. Census tract boundaries generally follow visible and identifiable features. They may follow legal boundaries such as minor civil division (MCD) or incorporated place boundaries in some states and situations to allow for census tract-to-governmental unit relationships where the governmental boundaries tend to remain unchanged between censuses. State and county boundaries always are census tract boundaries in the standard census geographic hierarchy. In a few rare instances, a census tract may consist of noncontiguous areas. These noncontiguous areas may occur where the census tracts are coextensive with all or parts of legal entities that are themselves noncontiguous. For the 2010 Census and beyond, the census tract code range of 9400 through 9499 was enforced for census tracts that include a majority American Indian population according to Census 2000 data and/or their area was primarily covered by federally recognized American Indian reservations and/or off-reservation trust lands; the code range 9800 through 9899 was enforced for those census tracts that contained little or no population and represented a relatively large special land use area such as a National Park, military installation, or a business/industrial park; and the code range 9900 through 9998 was enforced for those census tracts that contained only water area, no land area.

Population Numbers By New York City Neighborhood Tabulation Areas

The data was collected from Census Bureaus' Decennial data dissemination (SF1). Neighborhood Tabulation Areas (NTAs), are aggregations of census tracts that are subsets of New York City's 55 Public Use Microdata Areas (PUMAs). Primarily due to these constraints, NTA boundaries and their associated names may not definitively represent neighborhoods. This report shows change in population from 2000 to 2010 for each NTA. Compiled by the Population Division – New York City Department of City Planning.

Map SummaryAbout this map:This web map shows the 2020 census boundaries that lie within the jurisdiction of the city of Rochester, NY, based on the 2020 boundaries established by the U.S. Census Bureau. Census tracts are small, relatively permanent statistical subdivisions of a county that are uniquely numbered with a numeric code. In this feature layer, you can identify the tracts by their FIPS (Federal Information Processing Standards) code. Nationally, census tracts are drawn to average about 4,000 inhabitants living within their boundaries. The U.S. Census Bureau reviews the census tract boundaries every 10 years (in conjunction with the decennial census) and may split or merge them, depending on population change: when the Census finds that a tract has grown to have more than 8,000 inhabitants, that tract is split into two or more tracts; tracts that have shrunk in population to less than 1,200 people are merged within a neighboring tract. This review and revision process also may make adjustments of boundaries due to changes in boundaries of governmental jurisdictions, changes to more accurately place boundaries relative to visible features, or decisions by courts.Census tracts are subdivided into block groups that contain between 600 and 3,000 inhabitants. For more information on census tracts and block groups, please see the U.S. Census Bureau's website.To view the data dictionary, select the desired layer of the map in the "Layers" section below for more information.

Census Blocks from the 2010 US Census for New York City including portions under water. 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. All previously released versions of this data are available on the DCP Website: BYTES of the BIG APPLE. Current version: 25d

Very often in my work I am requested to calculate disease rates for small areas for time periods that fall between censuses or span multiple censuses, such as 1995-2013. In the past I have used population estimates from private vendors, but these have had two important limitations: one, they are proprietary and cannot be shared, and two, they often contain significant omissions and errors. I decided instead to calculate my own populations using publicly available data and established interpolation methods.

To generate the data here, I began with the census tract populations by age (5-year age groups) and sex published in the 1990, 2000, and 2010 federal censuses (citations to exact tables to be added). These were converted to 2010 census definitions using the Longitudinal Tract Data Base (LTDB), available here: http://www.s4.brown.edu/us2010/Researcher/Bridging.htm. The LTDB provides precise conversions between different censuses. For example, 45.4% of the population of 1990 Bronx census tract 50 is assigned to 2010 tract 50.01, while 54.6% is assigned to tract 50.02. Census tracts with zero population in all three decades, consisting of water and certain parks and cemeteries in New York City, were omitted. The resulting file has data for 4,893 tracts.

Each age-sex group was summed to the county total, and compared with the county total as published by the National Cancer Institute’s SEER program. The SEER counts make adjustments to the counts by race and ethnicity, adjust the counts to reflect totals as of July rather than April, and other small enhancements, all of which are documented on their web page, http://seer.cancer.gov/popdata/. The census tract counts were then proportionally adjusted to match the SEER totals. For example, if the census tracts in a particular county added to 127 males aged 5-9, and the SEER total for this county was 131, then the count in each tract was multiplied by 131/127. This resulted in fractional populations, which were retained. Any user not desirous of fractional populations can simply round the values given here.

Next, geometric interpolation between census years was used to estimate tract-level counts for all of the non-census years, using the Das Gupta method that has been used extensively by the Census Bureau and described here: https://www.census.gov/popest/methodology/intercensal_nat_meth.pdf. For census tracts that are growing in population, this method results in more of the growth occurring later in the period. For census tracts that are shrinking, it results in more of the shrinkage occurring earlier in the period. For the relatively small numbers seen in individual census tracts by age and sex, the results are not very different than those that would have been obtained from linear interpolation. (For the years after 2010, this step was skipped because the 2020 census obviously does not yet exist). These interpolated counts were then proportionally adjusted to match the SEER totals by year and county, using the same procedure as above.

Data dictionary

The data file is a comma-separated file containing the following variables:

Year

Geoid10 – 11 digit code consisting of state FIPS code (36 for New York), county FIPS code (001-123 for New York), and census tract (6 digits, with leading and trailing zeroes as needed). These are the identical values used in many Census tables.

M0 – male population aged 0

M1 – male population aged 1-4

M2 – male population aged 5-9

…

M17 – male population aged 80-84

M18 – male population aged 85+

F0 – female population aged 0

…

F18 – female population aged 85+

Future work

Future versions of these data may add some or all of the following:

• Additional states

• Counts by race and ethnicity

• Incorporation of a method to capture abrupt changes in census tract populations, such as when a new retirement community is constructed. The idea is to use American Community Survey population estimates to identify such instances.

• Incorporation of post-censal corrections. Here, I have used the official tables published after each census. They do not incorporate the various small corrections that were made as a result of appeals and identification of errors. These corrections are mainly given in narrative form rather than in tables, and so incorporating them may be somewhat involved.

  • Francis BoscoeUniversity at Albany

Department of Epidemiology and Biostatistics

Send questions, comments to fboscoe@albany.edu

This file shows the relationship between New York City’s 2020 census tracts, 2020 Neighborhood Tabulation Areas (NTAs), and Community District Tabulation Areas (CDTAs). 2020 census tracts nest within 2020 NTAs, and 2020 NTAs nest within CDTAs, so each census tract is listed only once. Note that CDTAs sometimes cross borough boundaries, and therefore will not add up to borough totals for the Bronx, Queens, and Manhattan. As they are nested within CDTAs, NTAs will likewise not add up to borough totals. Also note that census tracts in New York City’s water areas are excluded from this file.

This file contains population estimates by age and sex and single year for census tracts in New York State, from 1990-2016.Iterative proportional fitting was used to develop populations that are consistent with official Census Bureau tract-level populations from 1990, 2000, and 2010 and single-year county-level population estimates published by the SEER program of the National Cancer Institute (https://seer.cancer.gov/popdata/). The Longitudinal Tract Database (LTDB) (https://s4.ad.brown.edu/projects/diversity/researcher/bridging.htm) was used to report populations using 2010 census tract boundaries.In effect, the approach assumes that population growth or reduction at the tract level mirrors what is happening at the county level. This is an improvement over linear or geometric interpolation between census years, but is still far from perfect. Census tracts can undergo rapid year-to-year population change, such as when new housing is constructed or, less frequently, demolished. An extreme example is census tract 1.04 in Westchester County, New York, which had a population of 0 in all 3 census years, as it was located entirely within an industrial area. Since 2010, multiple large high-rise condominiums have been constructed here, so that the population in 2018 is probably now in the thousands, though any estimation or projection method tied to the 2010 census will still count 0 people here. It is conceivable that address files from the United States Postal Service or other sources could be used to capture these kinds of changes; I am unaware of any attempts to do this.The file contains data for 4893 census tracts. It has been restricted to census tracts with nonzero populations in at least one of the census years. There are other census tracts consisting entirely of water, parkland, or non-residential areas as in the example above, which have been omitted.These data are used for the calculation of small-area cancer rates in New York State.

Data

Shapefile for 2010 Census Tracts of New York City by Department of City Planning (DCP) for mapping.

Source

NYC Open Data

Table of Census Demographics represented at the NTA level. NTAs are aggregations of census tracts that are subsets of New York City's 55 Public Use Micro data Areas (PUMAs)

Content

Table of Census Demographics represented at the NTA level. NTAs are aggregations of census tracts that are subsets of New York City's 55 Public Use Micro data Areas (PUMAs)

Context

This is a dataset hosted by the City of New York. The city has an open data platform found here and they update their information according the amount of data that is brought in. Explore New York City using Kaggle and all of the data sources available through the City of New York organization page!

• Update Frequency: This dataset is updated annually.

Acknowledgements

This dataset is maintained using Socrata's API and Kaggle's API. Socrata has assisted countless organizations with hosting their open data and has been an integral part of the process of bringing more data to the public.

Cover photo by Asael Peña on Unsplash
Unsplash Images are distributed under a unique Unsplash License.

Dataset Summary About this data: This layer presents the USA 2020 Census tracts within the City of Rochester boundary. The geography is sourced from US Census Bureau 2020 TIGER FGDB (National Sub-State) and cut by the City of Rochester boundary. Data Dictionary: STATE_ABBR: The two-letter abbreviation for a state (such as NY). STATE_FIPS: The two-digit Federal Information Processing Standards (FIPS) code assigned to each US state. New York State is 36. COUNTY_FIP: The three-digit Federal Information Processing Standards (FIPS) code assigned to each US county. Monroe County is 055. STCO_FIPS: The five-digit Federal Information Processing Standards (FIPS) code assigned to iedntify a unique county, typically as a concatenation of the State FIPS code and the County FIPS code. TRACT_FIPS: The six-digit number assigned to each census tract in a US county. FIPS: A unique geographic identifier, typically as a concatenation of State FIPS code, County FIPS code, and Census tract code. POPULATION: The population of a census tract. POP_SQMI: The population per square mile of a census tract. SQMI: The size of a census tract in square miles. Division: The name of the City of Rochester data division that the census tract falls in to. Source: This data comes from the Census Bureau.

The 2020 cartographic boundary shapefiles are simplified representations of selected geographic areas from the U.S. Census Bureau's Master Address File / Topologically Integrated Geographic Encoding and Referencing (MAF/TIGER) Database (MTDB). These boundary files are specifically designed for small-scale thematic mapping. When possible, generalization is performed with the intent to maintain the hierarchical relationships among geographies and to maintain the alignment of geographies within a file set for a given year. Geographic areas may not align with the same areas from another year. Some geographies are available as nation-based files while others are available only as state-based files. Census tracts are small, relatively permanent statistical subdivisions of a county or equivalent entity, and were defined by local participants as part of the 2020 Census Participant Statistical Areas Program. The Census Bureau delineated the census tracts in situations where no local participant existed or where all the potential participants declined to participate. The primary purpose of census tracts is to provide a stable set of geographic units for the presentation of census data and comparison back to previous decennial censuses. Census tracts generally have a population size between 1,200 and 8,000 people, with an optimum size of 4,000 people. When first delineated, census tracts were designed to be homogeneous with respect to population characteristics, economic status, and living conditions. The spatial size of census tracts varies widely depending on the density of settlement. Physical changes in street patterns caused by highway construction, new development, and so forth, may require boundary revisions. In addition, census tracts occasionally are split due to population growth, or combined as a result of substantial population decline. Census tract boundaries generally follow visible and identifiable features. They may follow legal boundaries such as minor civil division (MCD) or incorporated place boundaries in some states and situations to allow for census tract-to-governmental unit relationships where the governmental boundaries tend to remain unchanged between censuses. State and county boundaries always are census tract boundaries in the standard census geographic hierarchy. In a few rare instances, a census tract may consist of noncontiguous areas. These noncontiguous areas may occur where the census tracts are coextensive with all or parts of legal entities that are themselves noncontiguous. For the 2010 Census and beyond, the census tract code range of 9400 through 9499 was enforced for census tracts that include a majority American Indian population according to Census 2000 data and/or their area was primarily covered by federally recognized American Indian reservations and/or off-reservation trust lands; the code range 9800 through 9899 was enforced for those census tracts that contained little or no population and represented a relatively large special land use area such as a National Park, military installation, or a business/industrial park; and the code range 9900 through 9998 was enforced for those census tracts that contained only water area, no land area.

2020 Census Tracts 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.