14 datasets found
  1. a

    Zip Codes

    • datahub-dc-dcgis.hub.arcgis.com
    • opendata.dc.gov
    • +4more
    Updated Jul 4, 2013
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    City of Washington, DC (2013). Zip Codes [Dataset]. https://datahub-dc-dcgis.hub.arcgis.com/items/5637d4bb43a34668b19fe630120d2b70
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    Dataset updated
    Jul 4, 2013
    Dataset authored and provided by
    City of Washington, DC
    License

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

    Area covered
    Description

    Zip Codes (5-digit). The dataset polygons represent location and attributes of zip codes, created as part of the DC Geographic Information System (DC GIS) for the D.C. Office of the Chief Technology Officer (OCTO) and participating D.C. government agencies. Zip Codes were identified from public records (US Postal Service) and created selecting arcs from the street centerlines and vector property map.

  2. V

    PLACES: ZCTA Data (GIS Friendly Format), 2021 release

    • data.virginia.gov
    • healthdata.gov
    • +4more
    csv, json, rdf, xsl
    Updated Aug 25, 2023
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    Centers for Disease Control and Prevention (2023). PLACES: ZCTA Data (GIS Friendly Format), 2021 release [Dataset]. https://data.virginia.gov/dataset/places-zcta-data-gis-friendly-format-2021-release
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    xsl, json, csv, rdfAvailable download formats
    Dataset updated
    Aug 25, 2023
    Dataset provided by
    Centers for Disease Control and Prevention
    Description

    This dataset contains model-based ZIP Code Tabulation Area (ZCTA) level estimates for the PLACES 2021 release in GIS-friendly format. PLACES is the expansion of the original 500 Cities Project and covers the entire United States—50 states and the District of Columbia (DC)—at county, place, census tract, and ZIP Code Tabulation Area (ZCTA) levels. It represents a first-of-its kind effort to release information uniformly on this large scale for local areas at 4 geographic levels. Estimates were provided by the Centers for Disease Control and Prevention (CDC), Division of Population Health, Epidemiology and Surveillance Branch. PLACES was funded by the Robert Wood Johnson Foundation (RWJF) in conjunction with the CDC Foundation. Data sources used to generate these model-based estimates include Behavioral Risk Factor Surveillance System (BRFSS) 2019 or 2018 data, Census Bureau 2010 population estimates, and American Community Survey (ACS) 2015–2019 or 2014–2018 estimates. The 2021 release uses 2019 BRFSS data for 22 measures and 2018 BRFSS data for 7 measures (all teeth lost, dental visits, mammograms, cervical cancer screening, colorectal cancer screening, core preventive services among older adults, and sleeping less than 7 hours a night). Seven measures are based on the 2018 BRFSS data because the relevant questions are only asked every other year in the BRFSS. These data can be joined with the census 2010 ZCTA boundary file in a GIS system to produce maps for 29 measures at the ZCTA level. An ArcGIS Online feature service is also available for users to make maps online or to add data to desktop GIS software. https://cdcarcgis.maps.arcgis.com/home/item.html?id=024cf3f6f59e49fe8c70e0e5410fe3cf

  3. V

    PLACES: ZCTA Data (GIS Friendly Format), 2022 release

    • data.virginia.gov
    • healthdata.gov
    • +3more
    csv, json, rdf, xsl
    Updated Aug 25, 2023
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    Centers for Disease Control and Prevention (2023). PLACES: ZCTA Data (GIS Friendly Format), 2022 release [Dataset]. https://data.virginia.gov/dataset/places-zcta-data-gis-friendly-format-2022-release
    Explore at:
    xsl, rdf, csv, jsonAvailable download formats
    Dataset updated
    Aug 25, 2023
    Dataset provided by
    Centers for Disease Control and Prevention
    Description

    This dataset contains model-based ZIP Code Tabulation Area (ZCTA) level estimates for the PLACES 2022 release in GIS-friendly format. PLACES covers the entire United States—50 states and the District of Columbia (DC)—at county, place, census tract, and ZIP Code Tabulation Area levels. It provides information uniformly on this large scale for local areas at 4 geographic levels. Estimates were provided by the Centers for Disease Control and Prevention (CDC), Division of Population Health, Epidemiology and Surveillance Branch. PLACES was funded by the Robert Wood Johnson Foundation in conjunction with the CDC Foundation. Data sources used to generate these model-based estimates include Behavioral Risk Factor Surveillance System (BRFSS) 2020 or 2019 data, Census Bureau 2010 population estimates, and American Community Survey (ACS) 2015–2019 estimates. The 2022 release uses 2020 BRFSS data for 25 measures and 2019 BRFSS data for 4 measures (high blood pressure, taking high blood pressure medication, high cholesterol, and cholesterol screening) that the survey collects data on every other year. These data can be joined with the census 2010 ZCTA boundary file in a GIS system to produce maps for 29 measures at the ZCTA level. An ArcGIS Online feature service is also available for users to make maps online or to add data to desktop GIS software. https://cdcarcgis.maps.arcgis.com/home/item.html?id=3b7221d4e47740cab9235b839fa55cd7

  4. d

    Identify Your Watershed and Sewer System Area App

    • catalog.data.gov
    • s.cnmilf.com
    Updated Nov 21, 2025
    + more versions
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    Department of Energy and Environment (2025). Identify Your Watershed and Sewer System Area App [Dataset]. https://catalog.data.gov/dataset/identify-your-watershed-and-sewer-system-area-app
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    Dataset updated
    Nov 21, 2025
    Dataset provided by
    Department of Energy and Environment
    Description

    This app displays a series of general information for an address, location, or where the user clicks in DC. Some information returned are:Municipal Separate Storm Sewer System (MS4) areaCombined Sewer System (CSS) areaWatershed, Subwatershed, HUC12, HUC14, HUC16Ward, ANC, SMD, and the address of the locationCensus Tract and zip code For addresses along the borders of watersheds and sewer areas, further investigation should be taken. For hydrologic calculations and determinations, the USGS Watershed Boundary Dataset (WBD) should be referenced.DC Water operates a "separate" (MS4) and "combined" (CSS) sewers. Since the early 1900's, sewers constructed within the District have been separate systems and no new combined sewer systems have been built. These two independent piping systems: CSS mixes "sanitary" (sewage from homes and businesses) with stormwater while the MS4 is for "stormwater" only. In the District, approximately two thirds of the District is served by the MS4. The remaining one-third is served by the CSS.Areas highlighted in blue are MS4, in orange are CSS, and in green are direct drain areas that drain directly to streams and rivers.The MS4 system discharges into portions of the Potomac, Anacostia and Rock Creek drainage areas. The CSS drains to Blue Plains Advance Wastewater Treatment Facility.Visit DOEE - Water in the District Page or DOEE Environmental Mapping.For the USGS Hydrologic and Watershed Boundary Data for DC, visit this Link.https://dcgis.maps.arcgis.com/home/item.html?id=54da82ed8d264bbbb7f9087df8c947c3

  5. PLACES: ZCTA Data (GIS Friendly Format), 2020 release

    • chronicdata.cdc.gov
    • data.virginia.gov
    • +5more
    Updated Oct 7, 2021
    + more versions
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    Centers for Disease Control and Prevention, National Center for Chronic Disease Prevention and Health Promotion, Division of Population Health (2021). PLACES: ZCTA Data (GIS Friendly Format), 2020 release [Dataset]. https://chronicdata.cdc.gov/500-Cities-Places/PLACES-ZCTA-Data-GIS-Friendly-Format-2020-release/bdsk-unrd
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    kmz, kml, xlsx, xml, csv, application/geo+jsonAvailable download formats
    Dataset updated
    Oct 7, 2021
    Dataset provided by
    Centers for Disease Control and Preventionhttp://www.cdc.gov/
    Authors
    Centers for Disease Control and Prevention, National Center for Chronic Disease Prevention and Health Promotion, Division of Population Health
    License

    U.S. Government Workshttps://www.usa.gov/government-works
    License information was derived automatically

    Description

    This dataset contains model-based ZIP Code tabulation Areas (ZCTA) level estimates for the PLACES project 2020 release in GIS-friendly format. The PLACES project is the expansion of the original 500 Cities project and covers the entire United States—50 states and the District of Columbia (DC)—at county, place, census tract, and ZIP Code tabulation Areas (ZCTA) levels. It represents a first-of-its kind effort to release information uniformly on this large scale for local areas at 4 geographic levels. Estimates were provided by the Centers for Disease Control and Prevention (CDC), Division of Population Health, Epidemiology and Surveillance Branch. The project was funded by the Robert Wood Johnson Foundation (RWJF) in conjunction with the CDC Foundation. Data sources used to generate these model-based estimates include Behavioral Risk Factor Surveillance System (BRFSS) 2018 or 2017 data, Census Bureau 2010 population estimates, and American Community Survey (ACS) 2014-2018 or 2013-2017 estimates. The 2020 release uses 2018 BRFSS data for 23 measures and 2017 BRFSS data for 4 measures (high blood pressure, taking high blood pressure medication, high cholesterol, and cholesterol screening). Four measures are based on the 2017 BRFSS data because the relevant questions are only asked every other year in the BRFSS. These data can be joined with the census 2010 ZCTA boundary file in a GIS system to produce maps for 27 measures at the ZCTA level. An ArcGIS Online feature service is also available at https://www.arcgis.com/home/item.html?id=8eca985039464f4d83467b8f6aeb1320 for users to make maps online or to add data to desktop GIS software.

  6. d

    Census Tracts in 2000

    • catalog.data.gov
    • datasets.ai
    • +6more
    Updated May 7, 2025
    + more versions
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    D.C. Office of the Chief Technology Officer (2025). Census Tracts in 2000 [Dataset]. https://catalog.data.gov/dataset/census-tracts-in-2000
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    Dataset updated
    May 7, 2025
    Dataset provided by
    D.C. Office of the Chief Technology Officer
    Description

    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. Face refers to the areal (polygon) topological primitives that make up MTDB. A face is bounded by one or more edges; its boundary includes only the edges that separate it from other faces, not any interior edges contained within the area of the face. The Topological Faces Shapefile contains the attributes of each topological primitive face. Each face has a unique topological face identifier (TFID) value. Each face in the shapefile includes the key geographic area codes for almost all geographic areas for which the Census Bureau tabulates data for both the 2010 Census and Census 2000. The geometries of each of these geographic areas can then be built by dissolving the face geometries on the appropriate key geographic area codes in the Topological Faces Shapefile.

  7. TIGER/Line Shapefile, 2022, State, District of Columbia, DC, Census Tract

    • catalog.data.gov
    Updated Jan 27, 2024
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    U.S. Department of Commerce, U.S. Census Bureau, Geography Division, Spatial Data Collection and Products Branch (Point of Contact) (2024). TIGER/Line Shapefile, 2022, State, District of Columbia, DC, Census Tract [Dataset]. https://catalog.data.gov/dataset/tiger-line-shapefile-2022-state-district-of-columbia-dc-census-tract
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    Dataset updated
    Jan 27, 2024
    Dataset provided by
    United States Census Bureauhttp://census.gov/
    Area covered
    District of Columbia, Washington
    Description

    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.

  8. a

    Census Blocks in 2010

    • hub.arcgis.com
    • opdatahub.dc.gov
    • +2more
    Updated Aug 4, 2013
    + more versions
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    City of Washington, DC (2013). Census Blocks in 2010 [Dataset]. https://hub.arcgis.com/maps/DCGIS::census-blocks-in-2010
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    Dataset updated
    Aug 4, 2013
    Dataset authored and provided by
    City of Washington, DC
    Area covered
    Description

    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. Face refers to the areal (polygon) topological primitives that make up MTDB. A face is bounded by one or more edges; its boundary includes only the edges that separate it from other faces, not any interior edges contained within the area of the face. The Topological Faces Shapefile contains the attributes of each topological primitive face. Each face has a unique topological face identifier (TFID) value. Each face in the shapefile includes the key geographic area codes for almost all geographic areas for which the Census Bureau tabulates data for both the 2010 Census and Census 2000. The geometries of each of these geographic areas can then be built by dissolving the face geometries on the appropriate key geographic area codes in the Topological Faces Shapefile.

  9. a

    2016 USA Organic Food Consumption (Washington, DC)

    • hub.arcgis.com
    Updated Jun 21, 2017
    + more versions
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    Blue Raster (2017). 2016 USA Organic Food Consumption (Washington, DC) [Dataset]. https://hub.arcgis.com/maps/24788660719842beba681980fac6f431
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    Dataset updated
    Jun 21, 2017
    Dataset authored and provided by
    Blue Raster
    Area covered
    Description

    This layer shows the market potential for an adult to regularly eat organic food in the U.S. in 2016 in a multiscale map (by country, state, county, ZIP Code, tract, and block group). The pop-up is configured to include the following information for each geography level:Market Potential Index and count of adults expected to regularly eat organic foodMarket Potential Index and count of adults expected to follow various dietary habitsEsri's 2016 Market Potential (MPI) data measures the likely demand for a product or service in an area. The database includes an expected number of consumers and a Market Potential Index (MPI) for each product or service. An MPI compares the demand for a specific product or service in an area with the national demand for that product or service. The MPI values at the US level are 100, representing average demand for the country. A value of more than 100 represents higher demand than the national average, and a value of less than 100 represents lower demand than the national average. For example, an index of 120 implies that demand in the area is 20 percent higher than the US average; an index of 80 implies that demand is 20 percent lower than the US average. See Market Potential database to view the methodology statement and complete variable list.Esri's Psychographics & Advertising Data Collection includes measurements of environmental concern, buying habits such as propensity to buy American products, likelihood to have healthy habits, and advertisement awareness. The database includes an expected number of consumers and a Market Potential Index (MPI) for each product or service. See the United States Data Browser to view complete variable lists for each Esri demographics collection.Additional Esri Resources:U.S. 2016/2021 Esri Updated DemographicsEssential demographic vocabularyEsri's arcgis.com demographic map layers

  10. d

    Census Tracts in 2020

    • opendata.dc.gov
    • opdatahub.dc.gov
    • +4more
    Updated Aug 27, 2021
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    City of Washington, DC (2021). Census Tracts in 2020 [Dataset]. https://opendata.dc.gov/datasets/DCGIS::census-tracts-in-2020
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    Dataset updated
    Aug 27, 2021
    Dataset authored and provided by
    City of Washington, DC
    License

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

    Area covered
    Description

    Census Tracts from 2020. The TIGER/Line shapefiles 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 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 2010 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.

  11. PLACES: County Data (GIS Friendly Format), 2022 release

    • catalog.data.gov
    • data.virginia.gov
    • +4more
    Updated Jun 28, 2025
    + more versions
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    Centers for Disease Control and Prevention (2025). PLACES: County Data (GIS Friendly Format), 2022 release [Dataset]. https://catalog.data.gov/dataset/places-county-data-gis-friendly-format-2022-release
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    Dataset updated
    Jun 28, 2025
    Dataset provided by
    Centers for Disease Control and Preventionhttp://www.cdc.gov/
    Description

    This dataset contains model-based county-level estimates for the PLACES 2022 release in GIS-friendly format. PLACES covers the entire United States—50 states and the District of Columbia (DC)—at county, place, census tract, and ZIP Code Tabulation Area levels. It provides information uniformly on this large scale for local areas at 4 geographic levels. Estimates were provided by the Centers for Disease Control and Prevention (CDC), Division of Population Health, Epidemiology and Surveillance Branch. Project was funded by the Robert Wood Johnson Foundation in conjunction with the CDC Foundation. Data sources used to generate these model-based estimates include Behavioral Risk Factor Surveillance System (BRFSS) 2020 or 2019 data, Census Bureau 2020 or 2019 county population estimates, and American Community Survey (ACS) 2016–2020 or 2015–2019 estimates. The 2022 release uses 2020 BRFSS data for 25 measures and 2019 BRFSS data for 4 measures (high blood pressure, taking high blood pressure medication, high cholesterol, and cholesterol screening) that the survey collects data on every other year. These data can be joined with the census 2020 county boundary file in a GIS system to produce maps for 29 measures at the county level. An ArcGIS Online feature service is also available for users to make maps online or to add data to desktop GIS software. https://cdcarcgis.maps.arcgis.com/home/item.html?id=3b7221d4e47740cab9235b839fa55cd7

  12. a

    State EV Registration By ZIPCODE

    • southeast-michigan-ev-resource-kit-and-planning-hub-semcog.hub.arcgis.com
    • mievtoolkit.com
    Updated Apr 16, 2021
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    Southeast Michigan Council of Governments (2021). State EV Registration By ZIPCODE [Dataset]. https://southeast-michigan-ev-resource-kit-and-planning-hub-semcog.hub.arcgis.com/maps/SEMCOG::state-ev-registration-by-zipcode
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    Dataset updated
    Apr 16, 2021
    Dataset authored and provided by
    Southeast Michigan Council of Governments
    Area covered
    Description

    This data shows the State EV Registration Data by ZIP Code. A snapshot of 1/27/2020, sourced from Atlas Public Policy in Washington, DC.

  13. HouseTS Dataset

    • kaggle.com
    zip
    Updated May 15, 2025
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    SK W. (2025). HouseTS Dataset [Dataset]. https://www.kaggle.com/datasets/shengkunwang/housets-dataset
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    zip(738473375 bytes)Available download formats
    Dataset updated
    May 15, 2025
    Authors
    SK W.
    License

    Attribution-NonCommercial-ShareAlike 4.0 (CC BY-NC-SA 4.0)https://creativecommons.org/licenses/by-nc-sa/4.0/
    License information was derived automatically

    Description

    HouseTS is a large-scale multimodal dataset for long-term U.S. house-price forecasting and socioeconomic analysis. It contains monthly observations from 2012 – 2023 for ≈ 6 000 ZIP codes spanning 30 major metropolitan areas. Each record (one ZIP × one month) provides 33 engineered features sourced from four complementary modalities:

    • Housing-market metrics — Zillow Research & Redfin Data Center: median sale/list prices, inventory, new listings, days on market, transaction volumes, and more.
    • Socioeconomic indicators — U.S. Census Bureau ACS 5-Year: income, population, labor-force size, poverty rate, rent burden, median commute time, etc.
    • Points of Interest (POIs) — OpenStreetMap via ohsome API: monthly counts of amenities such as restaurants, schools, supermarkets, parks, and transit stations.
    • Aerial imagery — USDA NAIP (1 m RGB): annual snapshots for a subset of ZIP codes in the Washington D.C.–Maryland–Virginia (DMV) region, enabling vision-based analyses.

    Typical use-cases

    • Spatio-temporal house-price prediction
    • Socioeconomic modeling that blends census and amenity data
    • Multimodal learning with tabular + satellite inputs
    • Urban-change detection through remote sensing and vision–language models

    Getting started & baselines

    Starter notebooks, data-loading utilities, and a full suite of statistical, machine-learning, and foundation-model baselines are available on GitHub:

    → GitHub repository:

  14. z

    ZIP Code 20060 Profile

    • zip-codes.com
    Updated Nov 1, 2025
    + more versions
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    ZIP-Codes.com (2025). ZIP Code 20060 Profile [Dataset]. https://www.zip-codes.com/zip-code/20060/zip-code-20060.asp
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    Dataset updated
    Nov 1, 2025
    Dataset provided by
    ZIP-Codes.com
    License

    https://www.zip-codes.com/tos-database.asphttps://www.zip-codes.com/tos-database.asp

    Area covered
    PostalCode:20060
    Description

    Demographics, population, housing, income, education, schools, and geography for ZIP Code 20060 (Washington, DC). Interactive charts load automatically as you scroll for improved performance.

  15. Not seeing a result you expected?
    Learn how you can add new datasets to our index.

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City of Washington, DC (2013). Zip Codes [Dataset]. https://datahub-dc-dcgis.hub.arcgis.com/items/5637d4bb43a34668b19fe630120d2b70

Zip Codes

Explore at:
Dataset updated
Jul 4, 2013
Dataset authored and provided by
City of Washington, DC
License

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

Area covered
Description

Zip Codes (5-digit). The dataset polygons represent location and attributes of zip codes, created as part of the DC Geographic Information System (DC GIS) for the D.C. Office of the Chief Technology Officer (OCTO) and participating D.C. government agencies. Zip Codes were identified from public records (US Postal Service) and created selecting arcs from the street centerlines and vector property map.

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