100+ datasets found
  1. o

    Geonames - All Cities with a population > 1000

    • public.opendatasoft.com
    • data.smartidf.services
    • +2more
    csv, excel, geojson +1
    Updated Mar 10, 2024
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    (2024). Geonames - All Cities with a population > 1000 [Dataset]. https://public.opendatasoft.com/explore/dataset/geonames-all-cities-with-a-population-1000/
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    csv, json, geojson, excelAvailable download formats
    Dataset updated
    Mar 10, 2024
    License

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

    Description

    All cities with a population > 1000 or seats of adm div (ca 80.000)Sources and ContributionsSources : GeoNames is aggregating over hundred different data sources. Ambassadors : GeoNames Ambassadors help in many countries. Wiki : A wiki allows to view the data and quickly fix error and add missing places. Donations and Sponsoring : Costs for running GeoNames are covered by donations and sponsoring.Enrichment:add country name

  2. d

    National Incorporated Places and Counties

    • catalog.data.gov
    • s.cnmilf.com
    Updated Sep 8, 2023
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    data.iowa.gov (2023). National Incorporated Places and Counties [Dataset]. https://catalog.data.gov/dataset/national-incorporated-places-and-counties
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    Dataset updated
    Sep 8, 2023
    Dataset provided by
    data.iowa.gov
    Description

    This dataset contains a listing of incorporated places (cities and towns) and counties within the United States including the GNIS code, FIPS code, name, entity type and primary point (location) for the entity. The types of entities listed in this dataset are based on codes provided by the U.S. Census Bureau, and include the following: C1 - An active incorporated place that does not serve as a county subdivision equivalent; C2 - An active incorporated place legally coextensive with a county subdivision but treated as independent of any county subdivision; C3 - A consolidated city; C4 - An active incorporated place with an alternate official common name; C5 - An active incorporated place that is independent of any county subdivision and serves as a county subdivision equivalent; C6 - An active incorporated place that partially is independent of any county subdivision and serves as a county subdivision equivalent or partially coextensive with a county subdivision but treated as independent of any county subdivision; C7 - An incorporated place that is independent of any county; C8 - The balance of a consolidated city excluding the separately incorporated place(s) within that consolidated government; C9 - An inactive or nonfunctioning incorporated place; H1 - An active county or statistically equivalent entity; H4 - A legally defined inactive or nonfunctioning county or statistically equivalent entity; H5 - A census areas in Alaska, a statistical county equivalent entity; and H6 - A county or statistically equivalent entity that is areally coextensive or governmentally consolidated with an incorporated place, part of an incorporated place, or a consolidated city.

  3. o

    US Cities: Demographics

    • public.opendatasoft.com
    • data.smartidf.services
    • +3more
    csv, excel, json
    Updated Jul 27, 2017
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    (2017). US Cities: Demographics [Dataset]. https://public.opendatasoft.com/explore/dataset/us-cities-demographics/
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    excel, csv, jsonAvailable download formats
    Dataset updated
    Jul 27, 2017
    License

    https://en.wikipedia.org/wiki/Public_domainhttps://en.wikipedia.org/wiki/Public_domain

    Area covered
    United States
    Description

    This dataset contains information about the demographics of all US cities and census-designated places with a population greater or equal to 65,000. This data comes from the US Census Bureau's 2015 American Community Survey. This product uses the Census Bureau Data API but is not endorsed or certified by the Census Bureau.

  4. 500 Cities: Local Data for Better Health, 2019 release

    • catalog.data.gov
    • healthdata.gov
    • +5more
    Updated Jun 28, 2025
    + more versions
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    Centers for Disease Control and Prevention (2025). 500 Cities: Local Data for Better Health, 2019 release [Dataset]. https://catalog.data.gov/dataset/500-cities-local-data-for-better-health-2019-release
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    Dataset updated
    Jun 28, 2025
    Dataset provided by
    Centers for Disease Control and Preventionhttp://www.cdc.gov/
    Description

    This is the complete dataset for the 500 Cities project 2019 release. This dataset includes 2017, 2016 model-based small area estimates for 27 measures of chronic disease related to unhealthy behaviors (5), health outcomes (13), and use of preventive services (9). Data 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. It represents a first-of-its kind effort to release information on a large scale for cities and for small areas within those cities. It includes estimates for the 500 largest US cities and approximately 28,000 census tracts within these cities. These estimates can be used to identify emerging health problems and to inform development and implementation of effective, targeted public health prevention activities. Because the small area model cannot detect effects due to local interventions, users are cautioned against using these estimates for program or policy evaluations. Data sources used to generate these measures include Behavioral Risk Factor Surveillance System (BRFSS) data (2017, 2016), Census Bureau 2010 census population data, and American Community Survey (ACS) 2013-2017, 2012-2016 estimates. Because some questions are only asked every other year in the BRFSS, there are 7 measures (all teeth lost, dental visits, mammograms, pap tests, colorectal cancer screening, core preventive services among older adults, and sleep less than 7 hours) from the 2016 BRFSS that are the same in the 2019 release as the previous 2018 release. More information about the methodology can be found at www.cdc.gov/500cities.

  5. e

    LinkedIn US city ID's

    • datarepository.eur.nl
    txt
    Updated May 31, 2023
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    Paul Kievits (2023). LinkedIn US city ID's [Dataset]. http://doi.org/10.25397/eur.19932221.v1
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    txtAvailable download formats
    Dataset updated
    May 31, 2023
    Dataset provided by
    Erasmus University Rotterdam (EUR)
    Authors
    Paul Kievits
    License

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

    Area covered
    United States
    Description

    This is a very small but useful dataset if you are ever looking to get jobs for a certain US city in LinkedIn. It contains a list of US cities and states and it's corresponding LinkedIn ID (which is usually externally hidden).

    The cities list was retreived from here: https://github.com/kelvins/US-Cities-Database and the names of the ciiadjusted to match the name used in LinkedIn (which could differ in subtle ways).

    Some cities do not have an ID, this is because the city is either too small or because there was a difference in the name on LinkedIn which I did not detect (human error). If you ever run in to one of these feel free to enhance this dataset.

  6. d

    500 Cities: City Boundaries

    • catalog.data.gov
    • healthdata.gov
    • +5more
    Updated Feb 3, 2025
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    Centers for Disease Control and Prevention (2025). 500 Cities: City Boundaries [Dataset]. https://catalog.data.gov/dataset/500-cities-city-boundaries
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    Dataset updated
    Feb 3, 2025
    Dataset provided by
    Centers for Disease Control and Prevention
    Description

    This city boundary shapefile was extracted from Esri Data and Maps for ArcGIS 2014 - U.S. Populated Place Areas. This shapefile can be joined to 500 Cities city-level Data (GIS Friendly Format) in a geographic information system (GIS) to make city-level maps.

  7. f

    A unified and validated traffic dataset for 20 U.S. cities

    • figshare.com
    zip
    Updated Aug 31, 2024
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    Xiaotong Xu; Zhenjie Zheng; Zijian Hu; Kairui Feng; Wei Ma (2024). A unified and validated traffic dataset for 20 U.S. cities [Dataset]. http://doi.org/10.6084/m9.figshare.24235696.v4
    Explore at:
    zipAvailable download formats
    Dataset updated
    Aug 31, 2024
    Dataset provided by
    figshare
    Authors
    Xiaotong Xu; Zhenjie Zheng; Zijian Hu; Kairui Feng; Wei Ma
    License

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

    Area covered
    United States
    Description

    Update NotesMar 16 2024, remove spaces in the file and folder names.Mar 31 2024, delete the underscore in the city names with a space (such as San Francisco) in the '02_TransCAD_results' folder to ensure correct data loading by TransCAD (software version: 9.0).Aug 31 2024, add the 'cityname_link_LinkFlows.csv' file in the '02_TransCAD_results' folder to match the link from input data and the link from TransCAD results (LinkFlows) with the same Link_ID.IntroductionThis is a unified and validated traffic dataset for 20 US cities. There are 3 folders for each city.01 Input datathe initial network data obtained from OpenStreetMap (OSM)the visualization of the OSM dataprocessed node / link / od data02 TransCAD results (software version: 9.0)cityname.dbd : geographical network database of the city supported by TransCAD (version 9.0)cityname_link.shp / cityname_node.shp : network data supported by GIS software, which can be imported into TransCAD manually. Then the corresponding '.dbd' file can be generated for TransCAD with a version lower than 9.0od.mtx : OD matrix supported by TransCADLinkFlows.bin / LinkFlows.csv : traffic assignment results by TransCADcityname_link_LinkFlows.csv: the input link attributes with the traffic assignment results by TransCADShortestPath.mtx / ue_travel_time.csv : the traval time (min) between OD pairs by TransCAD03 AequilibraE results (software version: 0.9.3)cityname.shp : shapefile network data of the city support by QGIS or other GIS softwareod_demand.aem : OD matrix supported by AequilibraEnetwork.csv : the network file used for traffic assignment in AequilibraEassignment_result.csv : traffic assignment results by AequilibraEPublicationXu, X., Zheng, Z., Hu, Z. et al. (2024). A unified dataset for the city-scale traffic assignment model in 20 U.S. cities. Sci Data 11, 325. https://doi.org/10.1038/s41597-024-03149-8Usage NotesIf you use this dataset in your research or any other work, please cite both the dataset and paper above.A brief introduction about how to use this dataset can be found in GitHub. More detailed illustration for compiling the traffic dataset on AequilibraE can be referred to GitHub code or Colab code.ContactIf you have any inquiries, please contact Xiaotong Xu (email: kid-a.xu@connect.polyu.hk).

  8. N

    Florida City, FL Age Group Population Dataset: A Complete Breakdown of...

    • neilsberg.com
    csv, json
    Updated Feb 22, 2025
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    Neilsberg Research (2025). Florida City, FL Age Group Population Dataset: A Complete Breakdown of Florida City Age Demographics from 0 to 85 Years and Over, Distributed Across 18 Age Groups // 2025 Edition [Dataset]. https://www.neilsberg.com/research/datasets/4522fba4-f122-11ef-8c1b-3860777c1fe6/
    Explore at:
    csv, jsonAvailable download formats
    Dataset updated
    Feb 22, 2025
    Dataset authored and provided by
    Neilsberg Research
    License

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

    Area covered
    Florida City, Florida
    Variables measured
    Population Under 5 Years, Population over 85 years, Population Between 5 and 9 years, Population Between 10 and 14 years, Population Between 15 and 19 years, Population Between 20 and 24 years, Population Between 25 and 29 years, Population Between 30 and 34 years, Population Between 35 and 39 years, Population Between 40 and 44 years, and 9 more
    Measurement technique
    The data presented in this dataset is derived from the latest U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates. To measure the two variables, namely (a) population and (b) population as a percentage of the total population, we initially analyzed and categorized the data for each of the age groups. For age groups we divided it into roughly a 5 year bucket for ages between 0 and 85. For over 85, we aggregated data into a single group for all ages. For further information regarding these estimates, please feel free to reach out to us via email at research@neilsberg.com.
    Dataset funded by
    Neilsberg Research
    Description
    About this dataset

    Context

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

    Key observations

    The largest age group in Florida City, FL was for the group of age 15 to 19 years years with a population of 1,187 (9.28%), according to the ACS 2019-2023 5-Year Estimates. At the same time, the smallest age group in Florida City, FL was the 80 to 84 years years with a population of 79 (0.62%). Source: U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates

    Content

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

    Age groups:

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

    Variables / Data Columns

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

    Good to know

    Margin of Error

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

    Custom data

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

    Inspiration

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

    Recommended for further research

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

  9. N

    Kenneth City, FL Age Group Population Dataset: A complete breakdown of...

    • neilsberg.com
    csv, json
    Updated Sep 16, 2023
    + more versions
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    Neilsberg Research (2023). Kenneth City, FL Age Group Population Dataset: A complete breakdown of Kenneth City age demographics from 0 to 85 years, distributed across 18 age groups [Dataset]. https://www.neilsberg.com/research/datasets/708ca8b0-3d85-11ee-9abe-0aa64bf2eeb2/
    Explore at:
    csv, jsonAvailable download formats
    Dataset updated
    Sep 16, 2023
    Dataset authored and provided by
    Neilsberg Research
    License

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

    Area covered
    Florida, Kenneth City
    Variables measured
    Population Under 5 Years, Population over 85 years, Population Between 5 and 9 years, Population Between 10 and 14 years, Population Between 15 and 19 years, Population Between 20 and 24 years, Population Between 25 and 29 years, Population Between 30 and 34 years, Population Between 35 and 39 years, Population Between 40 and 44 years, and 9 more
    Measurement technique
    The data presented in this dataset is derived from the latest U.S. Census Bureau American Community Survey (ACS) 2017-2021 5-Year Estimates. To measure the two variables, namely (a) population and (b) population as a percentage of the total population, we initially analyzed and categorized the data for each of the age groups. For age groups we divided it into roughly a 5 year bucket for ages between 0 and 85. For over 85, we aggregated data into a single group for all ages. For further information regarding these estimates, please feel free to reach out to us via email at research@neilsberg.com.
    Dataset funded by
    Neilsberg Research
    Description
    About this dataset

    Context

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

    Key observations

    The largest age group in Kenneth City, FL was for the group of age 60-64 years with a population of 504 (9.99%), according to the 2021 American Community Survey. At the same time, the smallest age group in Kenneth City, FL was the 10-14 years with a population of 102 (2.02%). Source: U.S. Census Bureau American Community Survey (ACS) 2017-2021 5-Year Estimates.

    Content

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

    Age groups:

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

    Variables / Data Columns

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

    Good to know

    Margin of Error

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

    Custom data

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

    Inspiration

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

    Recommended for further research

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

  10. NYC Open Data

    • kaggle.com
    zip
    Updated Mar 20, 2019
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    NYC Open Data (2019). NYC Open Data [Dataset]. https://www.kaggle.com/datasets/nycopendata/new-york
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    zip(0 bytes)Available download formats
    Dataset updated
    Mar 20, 2019
    Dataset authored and provided by
    NYC Open Data
    License

    https://creativecommons.org/publicdomain/zero/1.0/https://creativecommons.org/publicdomain/zero/1.0/

    Description

    Context

    NYC Open Data is an opportunity to engage New Yorkers in the information that is produced and used by City government. We believe that every New Yorker can benefit from Open Data, and Open Data can benefit from every New Yorker. Source: https://opendata.cityofnewyork.us/overview/

    Content

    Thanks to NYC Open Data, which makes public data generated by city agencies available for public use, and Citi Bike, we've incorporated over 150 GB of data in 5 open datasets into Google BigQuery Public Datasets, including:

    • Over 8 million 311 service requests from 2012-2016

    • More than 1 million motor vehicle collisions 2012-present

    • Citi Bike stations and 30 million Citi Bike trips 2013-present

    • Over 1 billion Yellow and Green Taxi rides from 2009-present

    • Over 500,000 sidewalk trees surveyed decennially in 1995, 2005, and 2015

    This dataset is deprecated and not being updated.

    Fork this kernel to get started with this dataset.

    Acknowledgements

    https://opendata.cityofnewyork.us/

    https://cloud.google.com/blog/big-data/2017/01/new-york-city-public-datasets-now-available-on-google-bigquery

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

    By accessing datasets and feeds available through NYC Open Data, the user agrees to all of the Terms of Use of NYC.gov as well as the Privacy Policy for NYC.gov. The user also agrees to any additional terms of use defined by the agencies, bureaus, and offices providing data. Public data sets made available on NYC Open Data are provided for informational purposes. The City does not warranty the completeness, accuracy, content, or fitness for any particular purpose or use of any public data set made available on NYC Open Data, nor are any such warranties to be implied or inferred with respect to the public data sets furnished therein.

    The City is not liable for any deficiencies in the completeness, accuracy, content, or fitness for any particular purpose or use of any public data set, or application utilizing such data set, provided by any third party.

    Banner Photo by @bicadmedia from Unplash.

    Inspiration

    On which New York City streets are you most likely to find a loud party?

    Can you find the Virginia Pines in New York City?

    Where was the only collision caused by an animal that injured a cyclist?

    What’s the Citi Bike record for the Longest Distance in the Shortest Time (on a route with at least 100 rides)?

    https://cloud.google.com/blog/big-data/2017/01/images/148467900588042/nyc-dataset-6.png" alt="enter image description here"> https://cloud.google.com/blog/big-data/2017/01/images/148467900588042/nyc-dataset-6.png

  11. o

    Counties - United States of America

    • public.opendatasoft.com
    • bfortune.opendatasoft.com
    csv, excel, geojson +1
    Updated Jun 6, 2024
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    (2024). Counties - United States of America [Dataset]. https://public.opendatasoft.com/explore/dataset/georef-united-states-of-america-county/
    Explore at:
    excel, json, geojson, csvAvailable download formats
    Dataset updated
    Jun 6, 2024
    License

    https://en.wikipedia.org/wiki/Public_domainhttps://en.wikipedia.org/wiki/Public_domain

    Area covered
    United States
    Description

    This dataset is part of the Geographical repository maintained by Opendatasoft. This dataset contains data for counties and equivalent entities in United States of America. The primary legal divisions of most states are termed counties. In Louisiana, these divisions are known as parishes. In Alaska, which has no counties, the equivalent entities are the organized boroughs, city and boroughs, municipalities, and for the unorganized area, census areas. The latter are delineated cooperatively for statistical purposes by the State of Alaska and the Census Bureau. In four states (Maryland, Missouri, Nevada, and Virginia), there are one or more incorporated places that are independent of any county organization and thus constitute primary divisions of their states. These incorporated places are known as independent cities and are treated as equivalent entities for purposes of data presentation. The District of Columbia and Guam have no primary divisions, and each area is considered an equivalent entity for purposes of data presentation. The Census Bureau treats the following entities as equivalents of counties for purposes of data presentation: Municipios in Puerto Rico, Districts and Islands in American Samoa, Municipalities in the Commonwealth of the Northern Mariana Islands, and Islands in the U.S. Virgin Islands. The entire area of the United States, Puerto Rico, and the Island Areas is covered by counties or equivalent entities.Processors and tools are using this data. Enhancements Add ISO 3166-3 codes. Simplify geometries to provide better performance across the services. Add administrative hierarchy.

  12. Counties

    • catalog.data.gov
    • datasets.ai
    • +3more
    Updated Jul 17, 2025
    + more versions
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    United States Census Bureau (USCB) (Point of Contact) (2025). Counties [Dataset]. https://catalog.data.gov/dataset/counties2
    Explore at:
    Dataset updated
    Jul 17, 2025
    Dataset provided by
    United States Census Bureauhttp://census.gov/
    Description

    The Counties dataset was updated on October 31, 2023 from the United States Census Bureau (USCB) and is part of the U.S. Department of Transportation (USDOT)/Bureau of Transportation Statistics (BTS) National Transportation Atlas Database (NTAD). This resource is a member of a series. The TIGER/Line shapefiles and related database files (.dbf) are an extract of selected geographic and cartographic information from the U.S. Census Bureau's Master Address File / Topologically Integrated Geographic Encoding and Referencing (MAF/TIGER) 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. The primary legal divisions of most states are termed counties. In Louisiana, these divisions are known as parishes. In Alaska, which has no counties, the equivalent entities are the organized boroughs, city and boroughs, municipalities, and for the unorganized area, census areas. The latter are delineated cooperatively for statistical purposes by the State of Alaska and the Census Bureau. In four states (Maryland, Missouri, Nevada, and Virginia), there are one or more incorporated places that are independent of any county organization and thus constitute primary divisions of their states. These incorporated places are known as independent cities and are treated as equivalent entities for purposes of data presentation. The District of Columbia and Guam have no primary divisions, and each area is considered an equivalent entity for purposes of data presentation. The Census Bureau treats the following entities as equivalents of counties for purposes of data presentation: Municipios in Puerto Rico, Districts and Islands in American Samoa, Municipalities in the Commonwealth of the Northern Mariana Islands, and Islands in the U.S. Virgin Islands. The entire area of the United States, Puerto Rico, and the Island Areas is covered by counties or equivalent entities. The boundaries for counties and equivalent entities are mostly as of January 1, 2023, as reported through the Census Bureau's Boundary and Annexation Survey (BAS). A data dictionary, or other source of attribute information, is accessible at https://doi.org/10.21949/1529015

  13. California Overlapping Cities and Counties and Identifiers

    • data.ca.gov
    • gis.data.ca.gov
    • +2more
    Updated Feb 20, 2025
    + more versions
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    California Department of Technology (2025). California Overlapping Cities and Counties and Identifiers [Dataset]. https://data.ca.gov/dataset/california-overlapping-cities-and-counties-and-identifiers
    Explore at:
    xlsx, gpkg, gdb, zip, kml, txt, html, geojson, csv, arcgis geoservices rest apiAvailable download formats
    Dataset updated
    Feb 20, 2025
    Dataset authored and provided by
    California Department of Technologyhttp://cdt.ca.gov/
    Area covered
    California
    Description

    WARNING: This is a pre-release dataset and its fields names and data structures are subject to change. It should be considered pre-release until the end of 2024. Expected changes:

    • Metadata is missing or incomplete for some layers at this time and will be continuously improved.
    • We expect to update this layer roughly in line with CDTFA at some point, but will increase the update cadence over time as we are able to automate the final pieces of the process.
    This dataset is continuously updated as the source data from CDTFA is updated, as often as many times a month. If you require unchanging point-in-time data, export a copy for your own use rather than using the service directly in your applications.

    Purpose

    County and incorporated place (city) boundaries along with third party identifiers used to join in external data. Boundaries are from the authoritative source the California Department of Tax and Fee Administration (CDTFA), altered to show the counties as one polygon. This layer displays the city polygons on top of the County polygons so the area isn"t interrupted. The GEOID attribute information is added from the US Census. GEOID is based on merged State and County FIPS codes for the Counties. Abbreviations for Counties and Cities were added from Caltrans Division of Local Assistance (DLA) data. Place Type was populated with information extracted from the Census. Names and IDs from the US Board on Geographic Names (BGN), the authoritative source of place names as published in the Geographic Name Information System (GNIS), are attached as well. Finally, coastal buffers are removed, leaving the land-based portions of jurisdictions. This feature layer is for public use.

    Related Layers

    This dataset is part of a grouping of many datasets:

    1. Cities: Only the city boundaries and attributes, without any unincorporated areas
    2. Counties: Full county boundaries and attributes, including all cities within as a single polygon
    3. Cities and Full Counties: A merge of the other two layers, so polygons overlap within city boundaries. Some customers require this behavior, so we provide it as a separate service.
    4. Place Abbreviations
    5. Unincorporated Areas (Coming Soon)
    6. Census Designated Places (Coming Soon)
    7. Cartographic Coastline
    Working with Coastal Buffers
    The dataset you are currently viewing includes the coastal buffers for cities and counties that have them in the authoritative source data from CDTFA. In the versions where they are included, they remain as a second polygon on cities or counties that have them, with all the same identifiers, and a value in the COASTAL field indicating if it"s an ocean or a bay buffer. If you wish to have a single polygon per jurisdiction that includes the coastal buffers, you can run a Dissolve on the version that has the coastal buffers on all the fields except COASTAL, Area_SqMi, Shape_Area, and Shape_Length to get a version with the correct identifiers.

    Point of Contact

    California Department of Technology, Office of Digital Services, odsdataservices@state.ca.gov

    Field and Abbreviation Definitions

    • COPRI: county number followed by the 3-digit city primary number used in the Board of Equalization"s 6-digit tax rate area numbering system
    • Place Name: CDTFA incorporated (city) or county name
    • County: CDTFA county name. For counties, this will be the name of the polygon itself. For cities, it is the name of the county the city polygon is within.
    • Legal Place Name: Board on Geographic Names authorized nomenclature for area names published in the Geographic Name Information System
    • GNIS_ID: The numeric identifier from the Board on Geographic Names that can be used to join these boundaries to other datasets utilizing this identifier.
    • GEOID: numeric geographic identifiers from the US Census Bureau Place Type: Board on Geographic Names authorized nomenclature for boundary type published in the Geographic Name Information System
    • Place Abbr: CalTrans Division of Local Assistance abbreviations of incorporated area names
    • CNTY Abbr: CalTrans Division of Local Assistance abbreviations of county names
    • Area_SqMi: The area of the administrative unit (city or county) in square miles, calculated in EPSG 3310 California Teale Albers.
    • COASTAL: Indicates if the polygon is a coastal buffer. Null for land polygons. Additional values include "ocean" and "bay".
    • GlobalID: While all of the layers we provide in this dataset include a GlobalID field with unique values, we do not recommend you make any use of it. The GlobalID field exists to support offline sync, but is not persistent, so data keyed to it will be orphaned at our next update. Use one of the other persistent identifiers, such as GNIS_ID or GEOID instead.

    Accuracy

    CDTFA"s source data notes the following about accuracy:

    City boundary changes and county boundary line adjustments filed with the Board of Equalization per Government Code 54900. This GIS layer contains the boundaries of the unincorporated county and incorporated cities within the state of California. The initial dataset was created in March of 2015 and was based on the State Board of Equalization tax rate area boundaries. As of April 1, 2024, the maintenance of this dataset is provided by the California Department of Tax and Fee Administration for the purpose of determining sales and use tax rates. The boundaries are continuously being revised to align with aerial imagery when areas of conflict are discovered between the original boundary provided by the California State Board of Equalization and the boundary made publicly available by local, state, and federal government. Some differences may occur between actual recorded boundaries and the boundaries used for sales and use tax purposes. The boundaries in this map are representations of taxing jurisdictions for the purpose of determining sales and use tax rates and should not be used to determine precise city or county boundary line locations. COUNTY = county name; CITY = city name or unincorporated territory; COPRI =

  14. Most populated cities in the U.S. - median household income 2022

    • statista.com
    Updated Aug 30, 2024
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    Statista (2024). Most populated cities in the U.S. - median household income 2022 [Dataset]. https://www.statista.com/statistics/205609/median-household-income-in-the-top-20-most-populated-cities-in-the-us/
    Explore at:
    Dataset updated
    Aug 30, 2024
    Dataset authored and provided by
    Statistahttp://statista.com/
    Time period covered
    2022
    Area covered
    United States
    Description

    In 2022, San Francisco had the highest median household income of cities ranking within the top 25 in terms of population, with a median household income in of 136,692 U.S. dollars. In that year, San Jose in California was ranked second, and Seattle, Washington third.

    Following a fall after the great recession, median household income in the United States has been increasing in recent years. As of 2022, median household income by state was highest in Maryland, Washington, D.C., Utah, and Massachusetts. It was lowest in Mississippi, West Virginia, and Arkansas. Families with an annual income of 25,000 and 49,999 U.S. dollars made up the largest income bracket in America, with about 25.26 million households.

    Data on median household income can be compared to statistics on personal income in the U.S. released by the Bureau of Economic Analysis. Personal income rose to around 21.8 trillion U.S. dollars in 2022, the highest value recorded. Personal income is a measure of the total income received by persons from all sources, while median household income is “the amount with divides the income distribution into two equal groups,” according to the U.S. Census Bureau. Half of the population in question lives above median income and half lives below. Though total personal income has increased in recent years, this wealth is not distributed throughout the population. In practical terms, income of most households has decreased. One additional statistic illustrates this disparity: for the lowest quintile of workers, mean household income has remained more or less steady for the past decade at about 13 to 16 thousand constant U.S. dollars annually. Meanwhile, income for the top five percent of workers has actually risen from about 285,000 U.S. dollars in 1990 to about 499,900 U.S. dollars in 2020.

  15. Z

    New York City Multi-scalar Street Segment Data

    • data.niaid.nih.gov
    Updated Aug 4, 2024
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    Shi, Ge (2024). New York City Multi-scalar Street Segment Data [Dataset]. https://data.niaid.nih.gov/resources?id=zenodo_10628027
    Explore at:
    Dataset updated
    Aug 4, 2024
    Dataset authored and provided by
    Shi, Ge
    License

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

    Area covered
    New York
    Description

    This dataset compiles a comprehensive database containing 90,327 street segments in New York City, covering their street design features, streetscape design, Vision Zero treatments, and neighborhood land use. It has two scales-street and street segment group (aggregation of same type of street at neighborhood). This dataset is derived based on all publicly available data, most from NYC Open Data. The detailed methods can be found in the published paper, Pedestrian and Car Occupant Crash Casualties Over a 9-Year Span of Vision Zero in New York City. To use it, please refer to the metadata file for more information and cite our work. A full list of raw data source can be found below:

    Motor Vehicle Collisions – NYC Open Data: https://data.cityofnewyork.us/Public-Safety/Motor-Vehicle-Collisions-Crashes/h9gi-nx95

    Citywide Street Centerline (CSCL) – NYC Open Data: https://data.cityofnewyork.us/City-Government/NYC-Street-Centerline-CSCL-/exjm-f27b

    NYC Building Footprints – NYC Open Data: https://data.cityofnewyork.us/Housing-Development/Building-Footprints/nqwf-w8eh

    Practical Canopy for New York City: https://zenodo.org/record/6547492

    New York City Bike Routes – NYC Open Data: https://data.cityofnewyork.us/Transportation/New-York-City-Bike-Routes/7vsa-caz7

    Sidewalk Widths NYC (originally from Sidewalk – NYC Open Data): https://www.sidewalkwidths.nyc/

    LION Single Line Street Base Map - The NYC Department of City Planning (DCP): https://www.nyc.gov/site/planning/data-maps/open-data/dwn-lion.page

    NYC Planimetric Database Median – NYC Open Data: https://data.cityofnewyork.us/Transportation/NYC-Planimetrics/wt4d-p43d

    NYC Vision Zero Open Data (including multiple datasets including all the implementations): https://www.nyc.gov/content/visionzero/pages/open-data

    NYS Traffic Data - New York State Department of Transportation Open Data: https://data.ny.gov/Transportation/NYS-Traffic-Data-Viewer/7wmy-q6mb

    Smart Location Database - US Environmental Protection Agency: https://www.epa.gov/smartgrowth/smart-location-mapping

    Race and ethnicity in area - American Community Survey (ACS): https://www.census.gov/programs-surveys/acs

  16. M

    Counties and Cities & Townships, Twin Cities Metropolitan Area

    • gisdata.mn.gov
    • data.wu.ac.at
    ags_mapserver, fgdb +4
    Updated Jul 28, 2025
    + more versions
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    Metropolitan Council (2025). Counties and Cities & Townships, Twin Cities Metropolitan Area [Dataset]. https://gisdata.mn.gov/dataset/us-mn-state-metc-bdry-metro-counties-and-ctus
    Explore at:
    jpeg, ags_mapserver, gpkg, html, fgdb, shpAvailable download formats
    Dataset updated
    Jul 28, 2025
    Dataset provided by
    Metropolitan Council
    Area covered
    Twin Cities
    Description

    This is a polygon dataset for county boundaries as well as for city, township and unorganized territory (CTU) boundaries in the Twin Cities 7-county metropolitan area. The linework for this dataset comes from individual counties and is assembled by the Metropolitan Council for the MetroGIS community. This is a MetroGIS Regionally Endorsed dataset https://metrogis.org/.

    The County CTU Lookup Table here https://gisdata.mn.gov/dataset/us-mn-state-metc-bdry-counties-and-ctus-lookup
    is also included in this dataset and contains various data related to cities, townships, unorganized territories (CTUs) and any divisions created by county boundaries splitting them is also included in the dataset.

    This dataset is updated quarterly. This dataset is composed of three shape files and one dbf table.
    - Counties.shp = county boundaries
    - CTUs.shp = city, township and unorganized territory boundaries
    - CountiesAndCTUs.shp = combined county and CTU boundaries
    - CountyCTULookupTable.dbf = various data related to CTUs and any divisions created by county boundaries splitting them is also included in the dataset, described here: https://gisdata.mn.gov/dataset/us-mn-state-metc-bdry-counties-and-ctus-lookup

    NOTES:

    - On 3/17/2011 it was discovered that the CTU ID used for the City of Lake St. Croix Beach was incorrect. It was changed from 2394379 to 2395599 to match GNIS.

    - On 3/17/2011 it was discovered that the CTU ID used for the City of Lilydale was incorrect. It was changed from 2394457 to 2395708 to match GNIS.

    - On 11/9/2010 it was discovered that the CTU ID used for the City of Crystal was incorrect. It was changed from 2393541 to 2393683 to match GNIS.

    - Effective April 2008, a change was made in GNIS to match the FIPS place codes to the "civil" feature for each city instead of the "populated place" feature. Both cities and townships are now "civil" features within GNIS. This means that the official GNIS unique ID for every city in Minnesota has changed.

    - The five digit CTU codes in this dataset are identical to the Federal Information Processing Standard (FIPS) ''Place'' codes. They are also used by the Census Bureau and many other organizations and are proposed as a MN state data coding standard.

    - Cities and townships have also been referred to as ''MCDs'' (a census term), however this term technically refers to the part of each city or township within a single county. Thus, a few cities in the metro area that are split by county boundaries are actually comprised of two different MCDs. This was part of the impetus for a proposed MN state data standard that uses the ''CTU'' terminology for clarity.

    - The boundary line data for this dataset comes from each county.

    - A variety of civil divisions of the land exist within the United States. In Minnesota, only three types exist - cities, townships and unorganized territories. All three of these exist within the Twin Cities seven county area. The only unorganized territory is Fort Snelling (a large portion of which is occupied by the MSP International Airport).

    - Some cities are split between two counties. Only those parts of cities within the 7-county area are included.

    - Prior to the 2000 census, the FIPS Place code for the City of Greenwood in Hennepin County was changed from 25928 to 25918. This dataset reflects that change.

  17. 2020 Cartographic Boundary File (SHP), Current Consolidated City for United...

    • catalog.data.gov
    • datasets.ai
    Updated Dec 14, 2023
    + more versions
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    U.S. Department of Commerce, U.S. Census Bureau, Geography Division, Customer Engagement Branch (Point of Contact) (2023). 2020 Cartographic Boundary File (SHP), Current Consolidated City for United States, 1:500,000 [Dataset]. https://catalog.data.gov/dataset/2020-cartographic-boundary-file-shp-current-consolidated-city-for-united-states-1-500000
    Explore at:
    Dataset updated
    Dec 14, 2023
    Dataset provided by
    United States Census Bureauhttp://census.gov/
    Area covered
    United States
    Description

    The 2020 cartographic boundary shapefiles are simplified representations of selected geographic areas from the U.S. Census Bureau's Master Address File / Topologically Integrated Geographic Encoding and Referencing (MAF/TIGER) Database (MTDB). These boundary files are specifically designed for small-scale thematic mapping. When possible, generalization is performed with the intent to maintain the hierarchical relationships among geographies and to maintain the alignment of geographies within a file set for a given year. Geographic areas may not align with the same areas from another year. Some geographies are available as nation-based files while others are available only as state-based files. A consolidated city is a unit of local government for which the functions of an incorporated place and its county or minor civil division (MCD) have merged. This action results in both the primary incorporated place and the county or MCD continuing to exist as legal entities, even though the county or MCD performs few or no governmental functions and has few or no elected officials. Where this occurs, and where one or more other incorporated places in the county or MCD continue to function as separate governments, even though they have been included in the consolidated government, the primary incorporated place is referred to as a consolidated city. The Census Bureau classifies the separately incorporated places within the consolidated city as place entities and creates a separate place (balance) record for the portion of the consolidated city not within any other place. The generalized boundaries of the consolidated cities in this file are based on those as of January 1, 2020, as reported through the Census Bureau's Boundary and Annexation Survey (BAS).

  18. N

    2020 Census Tracts

    • data.cityofnewyork.us
    • catalog.data.gov
    Updated May 29, 2025
    + more versions
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    Department of City Planning (DCP) (2025). 2020 Census Tracts [Dataset]. https://data.cityofnewyork.us/City-Government/2020-Census-Tracts/63ge-mke6
    Explore at:
    csv, application/rssxml, tsv, kml, kmz, xml, application/rdfxml, application/geo+jsonAvailable download formats
    Dataset updated
    May 29, 2025
    Dataset authored and provided by
    Department of City Planning (DCP)
    Description

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

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

  19. D

    Smart City Challenge Finalists Project Proposals - Calibration Data

    • transportation.gov
    • data.virginia.gov
    • +4more
    Updated Jan 3, 2017
    + more versions
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    Booz Allen Hamilton and TSS-Transport Simulation Systems (2017). Smart City Challenge Finalists Project Proposals - Calibration Data [Dataset]. https://www.transportation.gov/smartcity
    Explore at:
    xml, application/geo+json, csv, application/rssxml, kml, kmz, application/rdfxml, tsvAvailable download formats
    Dataset updated
    Jan 3, 2017
    Dataset authored and provided by
    Booz Allen Hamilton and TSS-Transport Simulation Systems
    License

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

    Description

    Analysis of the projects proposed by the seven finalists to USDOT's Smart City Challenge, including challenge addressed, proposed project category, and project description.

    The time reported for the speed profiles are between 2:00PM to 8:00PM in increments of 10 minutes.

  20. w

    Washington Cities by Population

    • washington-demographics.com
    Updated Jun 20, 2024
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    Kristen Carney (2024). Washington Cities by Population [Dataset]. https://www.washington-demographics.com/cities_by_population
    Explore at:
    Dataset updated
    Jun 20, 2024
    Dataset provided by
    Cubit Planning, Inc.
    Authors
    Kristen Carney
    License

    https://www.washington-demographics.com/terms_and_conditionshttps://www.washington-demographics.com/terms_and_conditions

    Area covered
    Washington, Tacoma
    Description

    A dataset listing Washington cities by population for 2024.

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(2024). Geonames - All Cities with a population > 1000 [Dataset]. https://public.opendatasoft.com/explore/dataset/geonames-all-cities-with-a-population-1000/

Geonames - All Cities with a population > 1000

Explore at:
15 scholarly articles cite this dataset (View in Google Scholar)
csv, json, geojson, excelAvailable download formats
Dataset updated
Mar 10, 2024
License

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

Description

All cities with a population > 1000 or seats of adm div (ca 80.000)Sources and ContributionsSources : GeoNames is aggregating over hundred different data sources. Ambassadors : GeoNames Ambassadors help in many countries. Wiki : A wiki allows to view the data and quickly fix error and add missing places. Donations and Sponsoring : Costs for running GeoNames are covered by donations and sponsoring.Enrichment:add country name

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