100+ datasets found
  1. d

    Python code used to download U.S. Census Bureau data for public-supply water...

    • catalog.data.gov
    • data.usgs.gov
    Updated Nov 19, 2025
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    U.S. Geological Survey (2025). Python code used to download U.S. Census Bureau data for public-supply water service areas [Dataset]. https://catalog.data.gov/dataset/python-code-used-to-download-u-s-census-bureau-data-for-public-supply-water-service-areas
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    Dataset updated
    Nov 19, 2025
    Dataset provided by
    U.S. Geological Survey
    Description

    This child item describes Python code used to query census data from the TigerWeb Representational State Transfer (REST) services and the U.S. Census Bureau Application Programming Interface (API). These data were needed as input feature variables for a machine learning model to predict public supply water use for the conterminous United States. Census data were retrieved for public-supply water service areas, but the census data collector could be used to retrieve data for other areas of interest. This dataset is part of a larger data release using machine learning to predict public supply water use for 12-digit hydrologic units from 2000-2020. Data retrieved by the census data collector code were used as input features in the public supply delivery and water use machine learning models. This page includes the following file: census_data_collector.zip - a zip file containing the census data collector Python code used to retrieve data from the U.S. Census Bureau and a README file.

  2. US Means of Transportation to Work Census Data

    • kaggle.com
    zip
    Updated Feb 23, 2022
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    Sagar G (2022). US Means of Transportation to Work Census Data [Dataset]. https://www.kaggle.com/goswamisagard/american-census-survey-b08301-cleaned-csv-data
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    zip(3388809 bytes)Available download formats
    Dataset updated
    Feb 23, 2022
    Authors
    Sagar G
    Area covered
    United States
    Description

    US Census Bureau conducts American Census Survey 1 and 5 Yr surveys that record various demographics and provide public access through APIs. I have attempted to call the APIs through the python environment using the requests library, Clean, and organize the data in a usable format.

    Data Ingestion and Cleaning:

    ACS Subject data [2011-2019] was accessed using Python by following the below API Link: https://api.census.gov/data/2011/acs/acs1?get=group(B08301)&for=county:* The data was obtained in JSON format by calling the above API, then imported as Python Pandas Dataframe. The 84 variables returned have 21 Estimate values for various metrics, 21 pairs of respective Margin of Error, and respective Annotation values for Estimate and Margin of Error Values. This data was then undergone through various cleaning processes using Python, where excess variables were removed, and the column names were renamed. Web-Scraping was carried out to extract the variables' names and replace the codes in the column names in raw data.

    The above step was carried out for multiple ACS/ACS-1 datasets spanning 2011-2019 and then merged into a single Python Pandas Dataframe. The columns were rearranged, and the "NAME" column was split into two columns, namely 'StateName' and 'CountyName.' The counties for which no data was available were also removed from the Dataframe. Once the Dataframe was ready, it was separated into two new dataframes for separating State and County Data and exported into '.csv' format

    Data Source:

    More information about the source of Data can be found at the URL below: US Census Bureau. (n.d.). About: Census Bureau API. Retrieved from Census.gov https://www.census.gov/data/developers/about.html

    Final Word:

    I hope this data helps you to create something beautiful, and awesome. I will be posting a lot more databases shortly, if I get more time from assignments, submissions, and Semester Projects 🧙🏼‍♂️. Good Luck.

  3. Time Series International Trade: Monthly U.S. Exports by End-use Code

    • catalog.data.gov
    • s.cnmilf.com
    Updated Sep 30, 2025
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    U.S. Census Bureau (2025). Time Series International Trade: Monthly U.S. Exports by End-use Code [Dataset]. https://catalog.data.gov/dataset/time-series-international-trade-monthly-u-s-exports-by-end-use-code
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    Dataset updated
    Sep 30, 2025
    Dataset provided by
    United States Census Bureauhttp://census.gov/
    Area covered
    United States
    Description

    The Census data API provides access to the most comprehensive set of data on current month and cumulative year-to-date exports using the End-use classification system. The End-use endpoint in the Census data API also provides value, shipping weight, and method of transportation totals at the district level for all U.S. trading partners. The Census data API will help users research new markets for their products, establish pricing structures for potential export markets, and conduct economic planning. If you have any questions regarding U.S. international trade data, please call us at 1(800)549-0595 option #4 or email us at eid.international.trade.data@census.gov.

  4. US Census - ACS and Decennial files **

    • redivis.com
    application/jsonl +7
    Updated Jul 4, 2023
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    Environmental Impact Data Collaborative (2023). US Census - ACS and Decennial files ** [Dataset]. https://redivis.com/datasets/b2fz-a8gwpvnh4
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    avro, csv, spss, stata, sas, parquet, application/jsonl, arrowAvailable download formats
    Dataset updated
    Jul 4, 2023
    Dataset provided by
    Redivis Inc.
    Authors
    Environmental Impact Data Collaborative
    Area covered
    United States
    Description

    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.

  5. Census Bureau Planned Acquisition

    • data.wu.ac.at
    Updated Feb 27, 2015
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    US Census Bureau, Department of Commerce (2015). Census Bureau Planned Acquisition [Dataset]. https://data.wu.ac.at/odso/data_gov/YjU3Yzg4OWYtNGJjZS00MDA2LTgyMjMtM2ZlYzJhYWY1MmEz
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    Dataset updated
    Feb 27, 2015
    Dataset provided by
    United States Census Bureauhttp://census.gov/
    Description

    The Census Bureau updates and maintains address data to support the correct allocation of population and housing for censuses and surveys. Boundaries, streets, addresses, structure points, and selected other features are maintained in the Master Address File/Topologically Integrated Geographic Encoding and Referencing (MAF/TIGER) database. The Census Bureau collects geographic and address data from tribal, state, and local governments through a Geographic Support System Initiative (GSS-I) Partnership Program and through other geographic programs, such as the annual Boundary and Annexation Survey. When the Census Bureau updates the MAF/TIGER database with new or corrected street, address and structure point data, the boundary network must be updated concurrently to preserve geographic relationships.

          Additional sources of data are required to ensure complete coverage of all street centerlines and addresses for the fifty States, the District of Columbia, Puerto Rico, and the Island Areas. Some government partners are unable to provide street and address data that meets the Census
          Bureau's requirements. Therefore, the Census Bureau is requesting proposals for provision of address data from commercial vendors that can be easily integrated into the MAF/TIGER database.
    
  6. d

    i16 Census Tract EconomicallyDistressedAreas 2023

    • catalog.data.gov
    • data.cnra.ca.gov
    • +5more
    Updated Sep 23, 2025
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    California Department of Water Resources (2025). i16 Census Tract EconomicallyDistressedAreas 2023 [Dataset]. https://catalog.data.gov/dataset/i16-census-tract-economicallydistressedareas-2023
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    Dataset updated
    Sep 23, 2025
    Dataset provided by
    California Department of Water Resources
    Description

    The IRWM web based EDA mapping tool uses this GIS layer. Created by joining ACS 2019-2023 5 year estimates to the 2020 Census Tract feature class. The TIGER/Line Files are shapefiles and related database files (.dbf) that 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 File 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 2020 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 2020 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.

  7. San Francisco Bay Region 2020 Census Tracts

    • opendata-mtc.opendata.arcgis.com
    • opendata.mtc.ca.gov
    Updated Dec 2, 2021
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    MTC/ABAG (2021). San Francisco Bay Region 2020 Census Tracts [Dataset]. https://opendata-mtc.opendata.arcgis.com/datasets/san-francisco-bay-region-2020-census-tracts/about
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    Dataset updated
    Dec 2, 2021
    Dataset provided by
    Metropolitan Transportation Commission
    Authors
    MTC/ABAG
    Area covered
    Description

    2020 Census tracts for the San Francisco Bay Region. Features were extracted from California 2021 TIGER/Line shapefile by the Metropolitan Transportation Commission.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.The Census Bureau uses suffixes to help identify census tract changes for comparison purposes. Local participants have an opportunity to review the existing census tracts before each census. If local participants split a census tract, the split parts usually retain the basic number, but receive different suffixes. In a few counties, local participants request major changes to, and renumbering of, the census tracts. Changes to individual census tract boundaries usually do not result in census tract numbering changes.Relationship to Other Geographic Entities—Within the standard census geographic hierarchy, census tracts never cross state or county boundaries, but may cross the boundaries of county subdivisions, places, urban areas, voting districts, congressional districts, and American Indian, Alaska Native, and Native Hawaiian areas.

  8. U

    TIGER/Line Initial Voting District Codes Files, 1990

    • dataverse-staging.rdmc.unc.edu
    • search.gesis.org
    Updated Nov 30, 2007
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    UNC Dataverse (2007). TIGER/Line Initial Voting District Codes Files, 1990 [Dataset]. https://dataverse-staging.rdmc.unc.edu/dataset.xhtml?persistentId=hdl:1902.29/C-199015
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    Dataset updated
    Nov 30, 2007
    Dataset provided by
    UNC Dataverse
    License

    https://dataverse-staging.rdmc.unc.edu/api/datasets/:persistentId/versions/1.0/customlicense?persistentId=hdl:1902.29/C-199015https://dataverse-staging.rdmc.unc.edu/api/datasets/:persistentId/versions/1.0/customlicense?persistentId=hdl:1902.29/C-199015

    Area covered
    United States
    Description

    "This file provides digital data for all 1990 precensus map features, the associated 1990 census initial tabulation geographic area codes, such as 1990 census block numbers, and the codes for the Jan. 1, 1990 political areas on both sides of each line segment of every mapped feature. The data contain basic information on 1990 census geographic area codes, feature names, and address ranges in the form of ten ""Record Types."" The Census Bureau added four new record types in response to some us er and vendor requests to provide point and area information contained in the Census Bureau's Precensus Map sheets that is not contained in the Precensus TIGER/Line files. The record types include: Basic data records (individual Feature Segment Records), shape coordinate points (feature shape records), additional decennial census geographic area codes, index to alternate feature names, feature name list, additional address range and zip code data, landmark features, area landmarks, area boundaries, and polygon location. Each segment record contains appropriate decennial census and FIPS geographic area codes, latitude/longitude coordinates, the name of the feature (including the relevant census feature class code identifying the segment by category), and, for areas formerly covered by the GBF/DIME-Files, the address ranges and ZIP code associated with those address ranges for each side of street segments. For other areas, the TIGER?Line files do not contain address ranges or ZIP Codes. The shape records provide coordinate values that describe the shape of those feature segments that are not straight."

  9. a

    Somerset County Census Tracts

    • hub.arcgis.com
    Updated Jan 3, 2023
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    Somerset County GIS (2023). Somerset County Census Tracts [Dataset]. https://hub.arcgis.com/datasets/9941fdc08c8041d6a1268ec506c6793c
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    Dataset updated
    Jan 3, 2023
    Dataset authored and provided by
    Somerset County GIS
    Area covered
    Description

    Census tracts are small and relatively permanent statistical subdivisions of a county or equivalent entity. Local participants review and update census tracts prior to each decennial census as part of the Census Bureau’s PSAP. The Census Bureau updates census tracts in situations where no local participant existed or where local or tribal governments declined to participate. The primary purpose of census tracts is to provide a stable set of geographic units for the presentation of decennial census data. Census tracts generally have a population size of 1,200 to 8,000 people with an optimum size of 4,000 people. The spatial size of census tracts varies widely depending on the density of settlement. Ideally, census tract boundaries remain stable over time to facilitate statistical comparisons from census to census. However, physical changes in street patterns caused by highway construction, new development, and so forth, may require boundary revisions. In addition, significant changes in population may result in splitting or combining census tracts. Census tract boundaries generally follow visible and identifiable features. Census tract boundaries may follow legal boundaries (e.g., MCD or incorporated place boundaries in some states 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. Census Tract Codes and Numbers—Census tract numbers have up to a 4-character basic number and may have an optional 2-character suffix. For example, 1457.02. The census tract numbers (used as names) eliminate any leading zeroes and append a suffix only if required. The 6-digit census tract codes, however, include leading zeroes and have an implied decimal point for the suffix. Census tract codes (000100 to 998999) are unique within a county or equivalent area. The Census Bureau assigned a census tract code of 9900 to represent census tracts delineated to cover large bodies of water. In addition, census tract codes in the 9400s represent American Indian Areas and codes in the 9800s represent special land use areas. The Census Bureau uses suffixes to help identify census tract changes for comparison purposes. Local participants have an opportunity to review the existing census tracts before each census. If local participants split a census tract, the split parts usually retain the basic number, but receive different suffixes. In a few counties, local participants request major changes to, and renumbering of, the census tracts. Changes to individual census tract boundaries usually do not result in census tract numbering changes. Relationship to Other Geographic Entities—Within the standard census geographic hierarchy, census tracts never cross state or county boundaries, but may cross the boundaries of county subdivisions, places, urban areas, voting districts, congressional districts, and AIANNH areas. Census Tract Numbers and Codes: 000100 to 939999 - Basic number range for census tracts940000 to 949999 - American Indian Areas950000 to 979999 - Basic number range for census tracts980000 to 989999 - Special land use areas990000 to 990099 - Basic number range for census tracts in water areas990100 to 998900 - Basic number range for census tracts 2020 Census legal boundaries (TIGER/Line Shapefiles) were downloaded from the Census website. Data pertaining to Somerset County was extracted and processed by the Somerset County Office of GIS Services (SCOGIS)

  10. undefined undefined: undefined | undefined (undefined)

    • data.census.gov
    Updated Jan 23, 2025
    + more versions
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    United States Census Bureau (2025). undefined undefined: undefined | undefined (undefined) [Dataset]. https://data.census.gov/table/ECNECOMM2022.EC2231ECOMM?q=Roach+Michael+E
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    Dataset updated
    Jan 23, 2025
    Dataset provided by
    United States Census Bureauhttp://census.gov/
    License

    CC0 1.0 Universal Public Domain Dedicationhttps://creativecommons.org/publicdomain/zero/1.0/
    License information was derived automatically

    Description

    Key Table Information.Table Title.Manufacturing: E-Commerce Statistics for the U.S.: 2022.Table ID.ECNECOMM2022.EC2231ECOMM.Survey/Program.Economic Census.Year.2022.Dataset.ECN Core Statistics Manufacturing: E-Commerce Statistics for the U.S.: 2022.Release Date.2025-01-23.Release Schedule.The Economic Census occurs every five years, in years ending in 2 and 7.The data in this file come from the 2022 Economic Census data files released on a flow basis starting in January 2024 with First Look Statistics. Preliminary U.S. totals released in January 2024 are superseded with final data shown in the releases of later economic census statistics through March 2026.For more information about economic census planned data product releases, see 2022 Economic Census Release Schedule..Dataset Universe.The dataset universe consists of all establishments that are in operation for at least some part of 2022, are located in one of the 50 U.S. states, associated offshore areas, or the District of Columbia, have paid employees, and are classified in one of nineteen in-scope sectors defined by the 2022 North American Industry Classification System (NAICS)..Methodology.Data Items and Other Identifying Records.Sales, value of shipments, or revenue ($1,000)E-Shipments value ($1,000) E-Shipments as percent of total sales, value of shipments, or revenue (%) Range indicating imputed percentage of total sales, value of shipments, or revenueDefinitions can be found by clicking on the column header in the table or by accessing the Economic Census Glossary..Unit(s) of Observation.The reporting units for the economic census are employer establishments. An establishment is generally a single physical location where business is conducted or where services or industrial operations are performed. A company or firm is comprised of one or more in-scope establishments that operate under the ownership or control of a single organization. For some industries, the reporting units are instead groups of all establishments in the same industry belonging to the same firm..Geography Coverage.The data are shown for the U.S. level only. For information about economic census geographies, including changes for 2022, see Geographies..Industry Coverage.The data are shown at the 2- through 3-digit 2022 NAICS code levels for the U.S. For information about NAICS, see Economic Census Code Lists..Sampling.The 2022 Economic Census sample includes all active operating establishments of multi-establishment firms and approximately 1.7 million single-establishment firms, stratified by industry and state. Establishments selected to the sample receive a questionnaire. For all data on this table, establishments not selected into the sample are represented with administrative data. For more information about the sample design, see 2022 Economic Census Methodology..Confidentiality.The Census Bureau has reviewed this data product to ensure appropriate access, use, and disclosure avoidance protection of the confidential source data (Project No. 7504609, Disclosure Review Board (DRB) approval number: CBDRB-FY23-099).To protect confidentiality, the U.S. Census Bureau suppresses cell values to minimize the risk of identifying a particular business’ data or identity.To comply with disclosure avoidance guidelines, data rows with fewer than three contributing firms or three contributing establishments are not presented. Additionally, establishment counts are suppressed when other select statistics in the same row are suppressed. More information on disclosure avoidance is available in the 2022 Economic Census Methodology..Technical Documentation/Methodology.For detailed information about the methods used to collect data and produce statistics, survey questionnaires, Primary Business Activity/NAICS codes, NAPCS codes, and more, see Economic Census Technical Documentation..Weights.No weighting applied as establishments not sampled are represented with administrative data..Table Information.FTP Download.https://www2.census.gov/programs-surveys/economic-census/data/2022/sector31/.API Information.Economic census data are housed in the Census Bureau Application Programming Interface (API)..Symbols.D - Withheld to avoid disclosing data for individual companies; data are included in higher level totalsN - Not available or not comparableS - Estimate does not meet publication standards because of high sampling variability, poor response quality, or other concerns about the estimate quality. Unpublished estimates derived from this table by subtraction are subject to these same limitations and should not be attributed to the U.S. Census Bureau. For a description of publication standards and the total quantity response rate, see link to program methodology page.X - Not applicableA - Relative standard error of 100% or morer - Reviseds - Relative standard error exceeds 40%For a complete list of symbols, see Economic Census Data Dictionary..Data-Specific Notes.Data users who create their own es...

  11. San Francisco Bay Region 2010 Census Tracts (clipped)

    • opendata.mtc.ca.gov
    • hub.arcgis.com
    Updated Jun 20, 2019
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    ABAG/MTC (2019). San Francisco Bay Region 2010 Census Tracts (clipped) [Dataset]. https://opendata.mtc.ca.gov/datasets/795ff16162684d08827e8ad89b76abb4
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    Dataset updated
    Jun 20, 2019
    Dataset provided by
    Association of Bay Area Governmentshttps://abag.ca.gov/
    Authors
    ABAG/MTC
    License

    MIT Licensehttps://opensource.org/licenses/MIT
    License information was derived automatically

    Area covered
    Description

    2010 Census tracts for the San Francisco Bay Region, clipped to remove major coastal and bay water areas. Features were extracted from, and clipped using, California 2018 TIGER/Line shapefiles by the Metropolitan Transportation Commission.Census tracts are small, relatively permanent statistical subdivisions of a county or equivalent entity, and are reviewed and updated by local participants prior to each decennial census as part of the Census Bureau’s Participant Statistical Areas Program (PSAP). The Census Bureau updates census tracts in situations where no local participant existed or where local or tribal governments declined to participate. The primary purpose of census tracts is to provide a stable set of geographic units for the presentation of decennial census data.Census tracts generally have a population size between 1,200 and 8,000 people with an optimum size of 4,000 people. The spatial size of census tracts varies widely depending on the density of settlement. Ideally, census tract boundaries remain stable over time to facilitate statistical comparisons from census to census. However, physical changes in street patterns caused by highway construction, new development, and so forth, may require boundary revisions. In addition, significant changes in population may result in splitting or combining census tracts.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 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.Census Tract Codes and Numbers—Census tract numbers have up to a 4-character basic number and may have an optional 2-character suffix; for example, 1457.02. The census tract numbers (used as names) eliminate any leading zeroes and append a suffix only if required. The 6-character numeric census tract codes, however, include leading zeroes and have an implied decimal point for the suffix. Census tract codes range from 000100 to 998999 and are unique within a county or equivalent area. The Census Bureau assigned a census tract code of 9900 to represent census tracts delineated to cover large bodies of water. In addition, census tract codes in the 9400s represent American Indian Areas and codes in the 9800s represent special land use areas.The Census Bureau uses suffixes to help identify census tract changes for comparison purposes. Local participants have an opportunity to review the existing census tracts before each census. If local participants split a census tract, the split parts usually retain the basic number, but receive different suffixes. In a few counties, local participants request major changes to, and renumbering of, the census tracts. Changes to individual census tract boundaries usually do not result in census tract numbering changes.Relationship to Other Geographic Entities—Within the standard census geographic hierarchy, census tracts never cross state or county boundaries, but may cross the boundaries of county subdivisions, places, urban areas, voting districts, congressional districts, and American Indian, Alaska Native, and Native Hawaiian areas.

  12. a

    Census 2020 Tracts

    • chelsea-open-data-chelseamass.hub.arcgis.com
    Updated Feb 23, 2023
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    City of Chelsea (2023). Census 2020 Tracts [Dataset]. https://chelsea-open-data-chelseamass.hub.arcgis.com/maps/0fca1123f74f408083bdd6031fe886a7
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    Dataset updated
    Feb 23, 2023
    Dataset authored and provided by
    City of Chelsea
    Area covered
    Description

    2020 Census tracts are small, relatively permanent statistical subdivisions of a county or equivalent entity, and are reviewed and updated by local participants prior to each decennial census as part of the Census Bureau’s Participant Statistical Areas Program (PSAP). The primary purpose of census tracts is to provide a stable set of geographic units for the presentation of decennial census data. Census tracts generally have a total population size between 1,200 and 8,000 people with an optimum size of 4,000 people. The spatial size of census tracts varies widely depending on the density of settlement. Ideally, census tract boundaries remain stable over time to facilitate statistical comparisons from census to census. However, physical changes in street patterns caused by highway construction, new development, and so forth, may require boundary revisions. In addition, significant changes in population may result in splitting or combining census tracts. State and county boundaries always are census tract boundaries in the standard census geographic hierarchy, but tracts can cross the same kinds of boundaries that block groups can. Census tract numbers have up to a 4-character basic number and may have an optional 2-character suffix. The census tract numbers (used as names) eliminate any leading zeroes and append a suffix only if required. The 6-digit census tract codes, however, include leading zeroes and have an implied decimal point for the suffix. Census tract codes (000100 to 998999) are unique within a county or equivalent area.

  13. TIGER Road Network

    • search.dataone.org
    Updated Oct 14, 2013
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    Cary Institute Of Ecosystem Studies; Jarlath O'Neil-Dunne (2013). TIGER Road Network [Dataset]. https://search.dataone.org/view/knb-lter-bes.86.570
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    Dataset updated
    Oct 14, 2013
    Dataset provided by
    Long Term Ecological Research Networkhttp://www.lternet.edu/
    Authors
    Cary Institute Of Ecosystem Studies; Jarlath O'Neil-Dunne
    Time period covered
    Jan 1, 2004 - Nov 17, 2011
    Area covered
    Description

    TIGER road data for the MSA. When compared to high-resolution imagery and other transportation datasets positional inaccuracies were observed. As a result caution should be taken when using this dataset. TIGER, TIGER/Line, and Census TIGER are registered trademarks of the U.S. Census Bureau. ZCTA is a trademark of the U.S. Census Bureau. The Census 2000 TIGER/Line files are an extract of selected geographic and cartographic information from the Census TIGER data base. The geographic coverage for a single TIGER/Line file is a county or statistical equivalent entity, with the coverage area based on January 1, 2000 legal boundaries. A complete set of census 2000 TIGER/Line files includes all counties and statistically equivalent entities in the United States, Puerto Rico, and the Island Areas. The Census TIGER data base represents a seamless national file with no overlaps or gaps between parts. However, each county-based TIGER/Line file is designed to stand alone as an independent data set or the files can be combined to cover the whole Nation. The Census 2000 TIGER/Line files consist of line segments representing physical features and governmental and statistical boundaries. The boundary information in the TIGER/Line files are for statistical data collection and tabulation purposes only; their depiction and designation for statistical purposes does not constitute a determination of jurisdictional authority or rights of ownership or entitlement. The Census 2000 TIGER/Line files do NOT contain the Census 2000 urban areas which have not yet been delineated. The files contain information distributed over a series of record types for the spatial objects of a county. There are 17 record types, including the basic data record, the shape coordinate points, and geographic codes that can be used with appropriate software to prepare maps. Other geographic information contained in the files includes attributes such as feature identifiers/census feature class codes (CFCC) used to differentiate feature types, address ranges and ZIP Codes, codes for legal and statistical entities, latitude/longitude coordinates of linear and point features, landmark point features, area landmarks, key geographic features, and area boundaries. The Census 2000 TIGER/Line data dictionary contains a complete list of all the fields in the 17 record types. This is part of a collection of 221 Baltimore Ecosystem Study metadata records that point to a geodatabase. The geodatabase is available online and is considerably large. Upon request, and under certain arrangements, it can be shipped on media, such as a usb hard drive. The geodatabase is roughly 51.4 Gb in size, consisting of 4,914 files in 160 folders. Although this metadata record and the others like it are not rich with attributes, it is nonetheless made available because the data that it represents could be indeed useful. This is part of a collection of 221 Baltimore Ecosystem Study metadata records that point to a geodatabase. The geodatabase is available online and is considerably large. Upon request, and under certain arrangements, it can be shipped on media, such as a usb hard drive. The geodatabase is roughly 51.4 Gb in size, consisting of 4,914 files in 160 folders. Although this metadata record and the others like it are not rich with attributes, it is nonetheless made available because the data that it represents could be indeed useful.

  14. Data from: [Dataset:] Barro Colorado Forest Census Plot Data (Version 2012)

    • smithsonian.figshare.com
    • search.dataone.org
    pdf
    Updated Apr 18, 2024
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    Richard Condit; Suzanne Lao; Rolando Pẽrez; Steven B. Dolins; Robin Foster; Stephen Hubbell (2024). [Dataset:] Barro Colorado Forest Census Plot Data (Version 2012) [Dataset]. http://doi.org/10.5479/data.bci.20130603
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    pdfAvailable download formats
    Dataset updated
    Apr 18, 2024
    Dataset provided by
    Smithsonian Tropical Research Institute
    Authors
    Richard Condit; Suzanne Lao; Rolando Pẽrez; Steven B. Dolins; Robin Foster; Stephen Hubbell
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Area covered
    Barro Colorado Island
    Description

    Abstract:The 50-hectare plot at Barro Colorado Island, Panama, is a 1000 meter by 500 meter rectangle of forest inside of which all woody trees and shrubs with stems at least 1 cm in stem diameter have been censused. Every individual tree in the 50 hectares was permanently numbered with an aluminum tag in 1982, and every individual has been revisited six times since (in 1985, 1990, 1995, 2000, 2005, and 2010). In each census, every tree was measured, mapped and identified to species. Details of the census method are presented in Condit (Tropical forest census plots: Methods and results from Barro Colorado Island, Panama and a comparison with other plots; Springer-Verlag, 1998), and a description of the seven-census results in Condit, Chisholm, and Hubbell (Thirty years of forest census at Barro Colorado and the Importance of Immigration in maintaining diversity; PLoS ONE, 7:e49826, 2012).Description:CITATION TO DATABASE: Condit, R., Lao, S., Pérez, R., Dolins, S.B., Foster, R.B. Hubbell, S.P. 2012. Barro Colorado Forest Census Plot Data, 2012 Version. DOI http://dx.doi.org/10.5479/data.bci.20130603 CO-AUTHORS: Stephen Hubbell and Richard Condit have been principal investigators of the project for over 30 years. They are fully responsible for the field methods and data quality. As such, both request that data users contact them and invite them to be co-authors on publications relying on the data. More recent versions of the data, often with important updates, can be requested directly from R. Condit (conditr@gmail.com). ACKNOWLEDGMENTS: The following should be acknowledged in publications for contributions to the 50-ha plot project: R. Foster as plot founder and the first botanist able to identify so many trees in a diverse forest; R. Pérez and S. Aguilar for species identification; S. Lao for data management; S. Dolins for database design; plus hundreds of field workers for the census work, now over 2 million tree measurements; the National Science Foundation, Smithsonian Tropical Research Institute, and MacArthur Foundation for the bulk of the financial support. File 1. RoutputFull.pdf: Detailed documentation of the 'full' tables in Rdata format (File 5). File 2. RoutputStem.pdf: Detailed documentation of the 'stem' tables in Rdata format (File 7). File 3. ViewFullTable.zip: A zip archive with a single ascii text file named ViewFullTable.txt holding a table with all census data from the BCI 50-ha plot. Each row is a single measurement of a single stem, with columns indicating the census, date, species name, plus tree and stem identifiers; all seven censuses are included. A full description of all columns in the table can be found at http://dx.doi.org/10.5479/data.bci.20130604 (ViewFullTable, pp. 21-22 of the pdf). File 4. ViewTax.txt: An ascii text table with information on all tree species recorded in the 50-ha plot. There are columns with taxonomics names (family, genus, species, and subspecies), plus the taxonomic authority. The column 'Mnemonic' gives a shortened code identifying each species, a code used in the R tables (Files 5, 7). The column 'IDLevel' indicates the depth to which the species is identified: if IDLevel='species', it is a fully identified, but if IDLevel='genus', the genus is known but not the species. IDLevel can also be 'family', or 'none' in case the species is not even known to family. File 5. bci.full.Rdata31Aug2012.zip: A zip archive holding seven R Analytical Tables, versions of the BCI 50 ha plot census data in R format. These are designed for data analysis. There are seven files, one for each of the 7 censuses: 'bci.full1.rdata' for the first census through 'bci.full7.rdata' for the seventh census. Each of the seven files is a table having one record per individual tree, and each includes a record for every tree found over the entire seven censuses (i.e. whether or not they were observed alive in the given census, there is a record). Detailed documentation of these tables is given in RoutputFull.pdf (File 1). File 6. bci.spptable.rdata: A list of the 1064 species found across all tree plots and inventories in Panama, in R format. This is a superset of species found in the BCI censuses: every BCI species is included, plus additional species never observed at BCI. The column 'sp' in this table is a code identifying the species in the R census tables (File 5, 7), and matching 'mnemomic' in ViewFullTable (File 3). File 7. bci.stem.Rdata31Aug2012.zip: A zip archive holding seven R Analytical Tables, versions of the BCI 50 ha plot census data in R format. These are designed for data analysis. There are seven files, one for each of the 7 censuses: 'bci.stem1.rdata' for the first census through 'bci.stem7.rdata' for the seventh census. Each of the seven files is a table having one record per individual stem, necessary because some individual trees have more than one stem. Each includes a record for every stem found over the entire seven censuses (i.e. whether or not they were observed alive in the given census, there is a record). Detailed documentation of these tables is given in RoutputStem.pdf (File 2). File 8. TSMAttributes.txt: An ascii text table giving full descriptions of measurement codes, which are also referred to as TSMCodes. These short codes are used in the column 'code' in R tables and in the column 'ListOfTSM' in ViewFullTable.txt, in both cases with individual codes separated by commas. File 9. bci_31August2012_mysql.zip: A zip archive holding one file, 'bci.sql', which is a mysqldump of the complete MySQL database (version 5.0.95, http://www.mysql.com) created 31 August 2012. The database includes data collected from seven censuses of the BCI 50 ha plot plus censuses of many additional plots elsewhere in Panama, plus transects where only species identifications were collected and trees were not tagged nor measurements made. Detailed documentation of all tables within the database can be found at (http://dx.doi.org/10.5479/data.bci.20130604). This version of the data is intended for experienced SQL users; for most, the R Analytical Tables in Rtables.zip are more useful.

  15. T

    Bay Area Census Tracts - Cartographic (2020)

    • data.bayareametro.gov
    Updated Jan 11, 2024
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    United States Census Bureau (2024). Bay Area Census Tracts - Cartographic (2020) [Dataset]. https://data.bayareametro.gov/w/j63r-vtey/_variation_?cur=18y1HbP6lUa&from=root
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    kmz, xlsx, application/geo+json, kml, xml, csvAvailable download formats
    Dataset updated
    Jan 11, 2024
    Dataset authored and provided by
    United States Census Bureau
    Area covered
    San Francisco Bay Area
    Description

    Tracts; January 1, 2019 vintage; Generalized

    Features provide a view of 2020 Census tracts for the San Francisco Bay Region. Features are a subset of the Census Tracts 500k service at https://data.bayareametro.gov/dataset/Census-Tracts-500K/dg5p-pxcu.

    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 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.

    The Census Bureau uses suffixes to help identify census tract changes for comparison purposes. Local participants have an opportunity to review the existing census tracts before each census. If local participants split a census tract, the split parts usually retain the basic number, but receive different suffixes. In a few counties, local participants request major changes to, and renumbering of, the census tracts. Changes to individual census tract boundaries usually do not result in census tract numbering changes.

    Relationship to Other Geographic Entities—Within the standard census geographic hierarchy, census tracts never cross state or county boundaries, but may cross the boundaries of county subdivisions, places, urban areas, voting districts, congressional districts, and American Indian, Alaska Native, and Native Hawaiian areas.

  16. Time Series International Trade: Monthly U.S. Imports by Department of...

    • catalog.data.gov
    • datasets.ai
    Updated Sep 30, 2025
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    U.S. Census Bureau (2025). Time Series International Trade: Monthly U.S. Imports by Department of Agriculture Code [Dataset]. https://catalog.data.gov/dataset/time-series-international-trade-monthly-u-s-imports-by-department-of-agriculture-code
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    Dataset updated
    Sep 30, 2025
    Dataset provided by
    United States Census Bureauhttp://census.gov/
    Area covered
    United States
    Description

    The Census data API provides access to the most comprehensive set of data on current month and cumulative year-to-date imports broken down by agricultural and nonagricultural commodities. The USDA endpoint in the Census data API provides value, shipping weight, and method of transportation totals at the district level for all U.S. trading partners. The Census data API will help users research new markets for their products, establish pricing structures for potential export markets, and conduct economic planning. If you have any questions regarding U.S. international trade data, please call us at 1(800)549-0595 option #4 or email us at eid.international.trade.data@census.gov.

  17. undefined undefined: undefined | undefined (undefined)

    • data.census.gov
    Updated Dec 6, 2024
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    United States Census Bureau (2024). undefined undefined: undefined | undefined (undefined) [Dataset]. https://data.census.gov/table/ECNCOMM2022.EC2242COMM?q=Arent+Jill+E+Attorney
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    Dataset updated
    Dec 6, 2024
    Dataset provided by
    United States Census Bureauhttp://census.gov/
    License

    CC0 1.0 Universal Public Domain Dedicationhttps://creativecommons.org/publicdomain/zero/1.0/
    License information was derived automatically

    Description

    Key Table Information.Table Title.Wholesale Trade: Sales and Commissions of Electronic Markets, Agents, Brokers, and Commission Merchants for the U.S.: 2022.Table ID.ECNCOMM2022.EC2242COMM.Survey/Program.Economic Census.Year.2022.Dataset.ECN Sector Statistics Sector 42: Wholesale Trade.Source.U.S. Census Bureau, 2022 Economic Census, Sector Statistics.Release Date.2025-07-10.Release Schedule.The Economic Census occurs every five years, in years ending in 2 and 7.The data in this file come from the 2022 Economic Census data files released on a flow basis starting in January 2024 with First Look Statistics. Preliminary U.S. totals released in January 2024 are superseded with final data shown in the releases of later economic census statistics through March 2026.For more information about economic census planned data product releases, see 2022 Economic Census Release Schedule..Dataset Universe.The dataset universe consists of all establishments that are in operation for at least some part of 2022, are located in one of the 50 U.S. states, associated offshore areas, or the District of Columbia, have paid employees, and are classified in one of nineteen in-scope sectors defined by the 2022 North American Industry Classification System (NAICS)..Methodology.Data Items and Other Identifying Records.Number of establishmentsSales, value of shipments, or revenue ($1,000)Sales on own account ($1,000)Sales made on the account of others ($1,000)Sales made on the account of others as percent of total sales, value of shipments, or revenue (%)Commissions received for sales made on the account of others ($1,000)Commissions received for sales made on the account of others as percent of sales on the account of others (%)Definitions can be found by clicking on the column header in the table or by accessing the Economic Census Glossary..Unit(s) of Observation.The reporting units for the economic census are employer establishments. An establishment is generally a single physical location where business is conducted or where services or industrial operations are performed. A company or firm is comprised of one or more in-scope establishments that operate under the ownership or control of a single organization. For some industries, the reporting units are instead groups of all establishments in the same industry belonging to the same firm..Geography Coverage.The data are shown for the U.S. level only. For information about economic census geographies, including changes for 2022, see Geographies..Industry Coverage.The data are shown at the 3- through 8-digit 2022 NAICS code levels within subsector 425. For information about NAICS, see Economic Census Code Lists..Business Characteristics.For Wholesale Trade (42), data are presented by Type of Operation (All establishments) only..Sampling.The 2022 Economic Census sample includes all active operating establishments of multi-establishment firms and approximately 1.7 million single-establishment firms, stratified by industry and state. Establishments selected to the sample receive a questionnaire. For some data on this table, estimates come only from the establishments selected into the sample. For more information about the sample design, see 2022 Economic Census Methodology..Confidentiality.The Census Bureau has reviewed this data product to ensure appropriate access, use, and disclosure avoidance protection of the confidential source data (Project No. 7504609, Disclosure Review Board (DRB) approval number: CBDRB-FY23-099).To protect confidentiality, the U.S. Census Bureau suppresses cell values to minimize the risk of identifying a particular business’ data or identity.To comply with disclosure avoidance guidelines, data rows with fewer than three contributing firms or three contributing establishments are not presented. Additionally, establishment counts are suppressed when other select statistics in the same row are suppressed. More information on disclosure avoidance is available in the 2022 Economic Census Methodology..Technical Documentation/Methodology.For detailed information about the methods used to collect data and produce statistics, survey questionnaires, Primary Business Activity/NAICS codes, NAPCS codes, and more, see Economic Census Technical Documentation..Weights.For some data on this table, estimates come only from the establishments selected into the sample. For these estimates, selected establishments have sampling weights equal to the inverse of their selection probability, generally between 1 and 40. There is further weighting to account for nonresponse and to ensure that detailed estimates sum to basic statistics where applicable. For more information on weighting, see 2022 Economic Census Methodology..Table Information.FTP Download.https://www2.census.gov/programs-surveys/economic-census/data/2022/sector42/.API Information.Economic census data are housed in the Census Bureau Application Programming Interface (API)..Symbols.D - Withheld to avoid disclosing da...

  18. H

    PRISM data converted into FIPS, ZIP Code, and census tract summaries in the...

    • dataverse.harvard.edu
    • search.dataone.org
    Updated Sep 8, 2025
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    Robbie Parks (2025). PRISM data converted into FIPS, ZIP Code, and census tract summaries in the USA [Dataset]. http://doi.org/10.7910/DVN/5P6EGE
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    CroissantCroissant is a format for machine-learning datasets. Learn more about this at mlcommons.org/croissant.
    Dataset updated
    Sep 8, 2025
    Dataset provided by
    Harvard Dataverse
    Authors
    Robbie Parks
    License

    CC0 1.0 Universal Public Domain Dedicationhttps://creativecommons.org/publicdomain/zero/1.0/
    License information was derived automatically

    Area covered
    United States
    Description

    PRISM data converted into FIPS, ZIP Code, and census tract summaries in the USA Introduction: Parameter-elevation Regressions on Independent Slopes Model (PRISM) by PRISM Climate group Oregon State temperature, precipitation 4km daily weather variable grids that I have converted to daily county FIPS, ZIP Code, and census tract summaries for use in several papers. Available for download (see Data below) in RDS (compact) format. CSV available on request. In Python it is easy to load RDS files and much more compact files than CSVs too. Note that ZIP Code throughout is actually ZIP Code Tabulation Area (ZCTA), which was developed to overcome the difficulties in precisely defining the land area covered by each ZIP Code. Defining the extent of an area is necessary in order to tabulate census data for that area.

  19. 2022 Economic Census: EC2221LOCMINE | Mining: Location of Mining...

    • data.census.gov
    Updated Dec 6, 2024
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    ECN (2024). 2022 Economic Census: EC2221LOCMINE | Mining: Location of Mining Establishments by Employment Size for the U.S., States, and Offshore Areas: 2022 (ECN Sector Statistics Economic Census: Mining: Location of Mines by Employment Size for Subsectors and Industries for the U.S., States, and Offshore Areas) [Dataset]. https://data.census.gov/table/ECNLOCMINE2022.EC2221LOCMINE?q=EC2221LOCMINE
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    Dataset updated
    Dec 6, 2024
    Dataset provided by
    United States Census Bureauhttp://census.gov/
    Authors
    ECN
    License

    CC0 1.0 Universal Public Domain Dedicationhttps://creativecommons.org/publicdomain/zero/1.0/
    License information was derived automatically

    Time period covered
    2022
    Area covered
    United States
    Description

    Key Table Information.Table Title.Mining: Location of Mining Establishments by Employment Size for the U.S., States, and Offshore Areas: 2022.Table ID.ECNLOCMINE2022.EC2221LOCMINE.Survey/Program.Economic Census.Year.2022.Dataset.ECN Sector Statistics Economic Census: Mining: Location of Mines by Employment Size for Subsectors and Industries for the U.S., States, and Offshore Areas.Source.U.S. Census Bureau, 2022 Economic Census, Sector Statistics.Release Date.2025-05-15.Release Schedule.The Economic Census occurs every five years, in years ending in 2 and 7.The data in this file come from the 2022 Economic Census data files released on a flow basis starting in January 2024 with First Look Statistics. Preliminary U.S. totals released in January 2024 are superseded with final data shown in the releases of later economic census statistics through March 2026.For more information about economic census planned data product releases, see 2022 Economic Census Release Schedule..Dataset Universe.The dataset universe consists of all establishments that are in operation for at least some part of 2022, are located in one of the 50 U.S. states, associated offshore areas, or the District of Columbia, have paid employees, and are classified in one of nineteen in-scope sectors defined by the 2022 North American Industry Classification System (NAICS)..Methodology.Data Items and Other Identifying Records.Employment size of establishmentsNumber of establishmentsDefinitions can be found by clicking on the column header in the table or by accessing the Economic Census Glossary..Unit(s) of Observation.The reporting units for the economic census are employer establishments. An establishment is generally a single physical location where business is conducted or where services or industrial operations are performed. A company or firm is comprised of one or more in-scope establishments that operate under the ownership or control of a single organization. For some industries, the reporting units are instead groups of all establishments in the same industry belonging to the same firm..Geography Coverage.The data are shown for the U.S., State, and Offshore Area levels that vary by industry. For information about economic census geographies, including changes for 2022, see Geographies..Industry Coverage.The data are shown at the 2- through 6-digit 2022 NAICS code levels for U.S., States, and Offshore Area. For information about NAICS, see Economic Census Code Lists..Sampling.The 2022 Economic Census sample includes all active operating establishments of multi-establishment firms and approximately 1.7 million single-establishment firms, stratified by industry and state. Establishments selected to the sample receive a questionnaire. For all data on this table, establishments not selected into the sample are represented with administrative data. For more information about the sample design, see 2022 Economic Census Methodology..Confidentiality.The Census Bureau has reviewed this data product to ensure appropriate access, use, and disclosure avoidance protection of the confidential source data (Project No. 7504609, Disclosure Review Board (DRB) approval number: CBDRB-FY23-099).To protect confidentiality, the U.S. Census Bureau suppresses cell values to minimize the risk of identifying a particular business’ data or identity.To comply with disclosure avoidance guidelines, data rows with fewer than three contributing firms or three contributing establishments are not presented. Additionally, establishment counts are suppressed when other select statistics in the same row are suppressed. More information on disclosure avoidance is available in the 2022 Economic Census Methodology..Technical Documentation/Methodology.For detailed information about the methods used to collect data and produce statistics, survey questionnaires, Primary Business Activity/NAICS codes, NAPCS codes, and more, see Economic Census Technical Documentation..Weights.No weighting applied as establishments not sampled are represented with administrative data..Table Information.FTP Download.https://www2.census.gov/programs-surveys/economic-census/data/2022/sector21/.API Information.Economic census data are housed in the Census Bureau Application Programming Interface (API)..Symbols.D - Withheld to avoid disclosing data for individual companies; data are included in higher level totalsN - Not available or not comparableS - Estimate does not meet publication standards because of high sampling variability, poor response quality, or other concerns about the estimate quality. Unpublished estimates derived from this table by subtraction are subject to these same limitations and should not be attributed to the U.S. Census Bureau. For a description of publication standards and the total quantity response rate, see link to program methodology page.X - Not applicableA - Relative standard error of 100% or morer - Reviseds - Relative standard error exceeds 40%For a complete list of sy...

  20. V

    Virginia Disability Characteristics by Census Tract (ACS 5-Year)

    • data.virginia.gov
    csv
    Updated Jan 2, 2025
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    Office of INTERMODAL Planning and Investment (2025). Virginia Disability Characteristics by Census Tract (ACS 5-Year) [Dataset]. https://data.virginia.gov/dataset/virginia-disability-characteristics-by-census-tract-acs-5-year
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    csv(31160488)Available download formats
    Dataset updated
    Jan 2, 2025
    Dataset authored and provided by
    Office of INTERMODAL Planning and Investment
    Description

    2013-2023 Virginia Disability Characteristics by Census Tract. Contains estimates and margins of error.

    Special data considerations: Large negative values do exist (more detail below) and should be addressed prior to graphing or aggregating the data. A null value in the estimate means there is no data available for the requested geography.

    A value of -888,888,888 indicates that the estimate or margin of error is not applicable or not available.

    U.S. Census Bureau; American Community Survey, American Community Survey 5-Year Estimates, Table S1810 Data accessed from: Census Bureau's API for American Community Survey (https://www.census.gov/data/developers/data-sets.html)

    The United States Census Bureau's American Community Survey (ACS): -What is the American Community Survey? (https://www.census.gov/programs-surveys/acs/about.html) -Geography & ACS (https://www.census.gov/programs-surveys/acs/geography-acs.html) -Technical Documentation (https://www.census.gov/programs-surveys/acs/technical-documentation.html)

    Supporting documentation on code lists, subject definitions, data accuracy, and statistical testing can be found on the American Community Survey website in the Technical Documentation section. (https://www.census.gov/programs-surveys/acs/technical-documentation/code-lists.html)

    Sample size and data quality measures (including coverage rates, allocation rates, and response rates) can be found on the American Community Survey website in the Methodology section. (https://www.census.gov/acs/www/methodology/sample_size_and_data_quality/)

    Although the American Community Survey (ACS) produces population, demographic and housing unit estimates, it is the Census Bureau's Population Estimates Program that produces and disseminates the official estimates of the population for the nation, states, counties, cities, and towns and estimates of housing units for states and counties.

    Data are based on a sample and are subject to sampling variability. The degree of uncertainty for an estimate arising from sampling variability is represented through the use of a margin of error. The value shown here is the 90 percent margin of error. The margin of error can be interpreted roughly as providing a 90 percent probability that the interval defined by the estimate minus the margin of error and the estimate plus the margin of error (the lower and upper confidence bounds) contains the true value. In addition to sampling variability, the ACS estimates are subject to nonsampling error (for a discussion of nonsampling variability, see ACS Technical Documentation https://www.census.gov/programs-surveys/acs/technical-documentation.html). The effect of nonsampling error is not represented in these tables.

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U.S. Geological Survey (2025). Python code used to download U.S. Census Bureau data for public-supply water service areas [Dataset]. https://catalog.data.gov/dataset/python-code-used-to-download-u-s-census-bureau-data-for-public-supply-water-service-areas

Python code used to download U.S. Census Bureau data for public-supply water service areas

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Dataset updated
Nov 19, 2025
Dataset provided by
U.S. Geological Survey
Description

This child item describes Python code used to query census data from the TigerWeb Representational State Transfer (REST) services and the U.S. Census Bureau Application Programming Interface (API). These data were needed as input feature variables for a machine learning model to predict public supply water use for the conterminous United States. Census data were retrieved for public-supply water service areas, but the census data collector could be used to retrieve data for other areas of interest. This dataset is part of a larger data release using machine learning to predict public supply water use for 12-digit hydrologic units from 2000-2020. Data retrieved by the census data collector code were used as input features in the public supply delivery and water use machine learning models. This page includes the following file: census_data_collector.zip - a zip file containing the census data collector Python code used to retrieve data from the U.S. Census Bureau and a README file.

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