100+ datasets found
  1. d

    Hydrologic Derivatives for Modeling and Analysis (HDMA) database -- South...

    • catalog.data.gov
    • data.usgs.gov
    • +2more
    Updated Jul 6, 2024
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    U.S. Geological Survey (2024). Hydrologic Derivatives for Modeling and Analysis (HDMA) database -- South America [Dataset]. https://catalog.data.gov/dataset/hydrologic-derivatives-for-modeling-and-analysis-hdma-database-south-america
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    Dataset updated
    Jul 6, 2024
    Dataset provided by
    United States Geological Surveyhttp://www.usgs.gov/
    Area covered
    South America
    Description

    This contains the South American portion of the Hydrologic Derivatives for Modeling and Analysis (HDMA) database. The HDMA database provides comprehensive and consistent global coverage of raster and vector topographically derived layers, including raster layers of digital elevation model (DEM) data, flow direction, flow accumulation, slope, and compound topographic index (CTI); and vector layers of streams and catchment boundaries. The coverage of the data is global (-180º, 180º, -90º, 90º) with the underlying DEM being a hybrid of three datasets: HydroSHEDS (Hydrological data and maps based on SHuttle Elevation Derivatives at multiple Scales), Global Multi-resolution Terrain Elevation Data 2010 (GMTED2010) and the Shuttle Radar Topography Mission (SRTM). For most of the globe south of 60º North, the raster resolution of the data is 3-arc-seconds, corresponding to the resolution of the SRTM. For the areas North of 60º, the resolution is 7.5-arc-seconds (the smallest resolution of the GMTED2010 dataset) except for Greenland, where the resolution is 30-arc-seconds. The streams and catchments are attributed with Pfafstetter codes, based on a hierarchical numbering system, that carry important topological information.

  2. o

    Counties - United States of America

    • public.opendatasoft.com
    • data.smartidf.services
    • +1more
    csv, excel, geojson +1
    Updated Jun 6, 2024
    + more versions
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    (2024). Counties - United States of America [Dataset]. https://public.opendatasoft.com/explore/dataset/georef-united-states-of-america-county/
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    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.

  3. q

    NALENND® North American Local Exchange NPA NXX Database™

    • quentinsagerconsulting.com
    Updated Jun 11, 2019
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    Quentin Sager Consulting Inc. (2019). NALENND® North American Local Exchange NPA NXX Database™ [Dataset]. https://www.quentinsagerconsulting.com/nalennd-npa-nxx-database.htm
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    Dataset updated
    Jun 11, 2019
    Authors
    Quentin Sager Consulting Inc.
    License

    https://www.quentinsagerconsulting.com/licenseoverview.htmhttps://www.quentinsagerconsulting.com/licenseoverview.htm

    Description

    The NALENND® NPA NXX Database products provide comprehensive coverage of all active telephone exchange area code, central office prefix and thousands-block assignments and associated jurisdictional wire center, rate center, LATA and carrier data within the North American Numbering Plan (NANP). The North American Numbering Plan (NANP) is an integrated telephone numbering plan serving 20 North American countries that share its numbering resources. These countries include the United States and its territories, Canada, Bermuda, Anguilla, Antigua & Barbuda, the Bahamas, Barbados, the British Virgin Islands, the Cayman Islands, Dominica, the Dominican Republic, Grenada, Jamaica, Montserrat, Sint Maarten, St. Kitts and Nevis, St. Lucia, St. Vincent and the Grenadines, Trinidad and Tobago, and Turks & Caicos.

  4. U

    United States BoP: Brazil: CA: Exp: PI: II: Reserve Asset

    • ceicdata.com
    Updated Mar 15, 2018
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    CEICdata.com (2018). United States BoP: Brazil: CA: Exp: PI: II: Reserve Asset [Dataset]. https://www.ceicdata.com/en/united-states/balance-of-payments-bpm6-latin-america-and-other-western-hemisphere/bop-brazil-ca-exp-pi-ii-reserve-asset
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    Dataset updated
    Mar 15, 2018
    Dataset provided by
    CEICdata.com
    License

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

    Time period covered
    Jun 1, 2015 - Mar 1, 2018
    Area covered
    United States
    Description

    United States BoP: Brazil: CA: Exp: PI: II: Reserve Asset data was reported at 0.000 USD mn in Mar 2018. This stayed constant from the previous number of 0.000 USD mn for Dec 2017. United States BoP: Brazil: CA: Exp: PI: II: Reserve Asset data is updated quarterly, averaging 0.000 USD mn from Mar 2003 (Median) to Mar 2018, with 61 observations. United States BoP: Brazil: CA: Exp: PI: II: Reserve Asset data remains active status in CEIC and is reported by Bureau of Economic Analysis. The data is categorized under Global Database’s USA – Table US.JB007: Balance of Payments: BPM6: Latin America and Other Western Hemisphere.

  5. Data marketing challenges in North America 2020

    • statista.com
    Updated Dec 10, 2024
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    Statista (2024). Data marketing challenges in North America 2020 [Dataset]. https://www.statista.com/statistics/256122/greatest-challenges-in-using-big-data-for-marketing/
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    Dataset updated
    Dec 10, 2024
    Dataset authored and provided by
    Statistahttp://statista.com/
    Time period covered
    Apr 2020 - May 2020
    Area covered
    North America
    Description

    During a 2020 survey carried among data marketers primarily from North America, 34 percent of respondents named the decline of cookies/change in availability of third-party data as the issue they expected to occupy most of their attention and resources in 2020. Business recovery from COVID-19 was the top worry, mentioned by 62.3 percent of responding marketers.

  6. A

    Australia Visitor Arrivals: By Country: Americas: United States of America

    • ceicdata.com
    Updated Dec 24, 2024
    + more versions
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    CEICdata.com (2024). Australia Visitor Arrivals: By Country: Americas: United States of America [Dataset]. https://www.ceicdata.com/en/australia/visitor-arrivals-short-term-by-countries/visitor-arrivals-by-country-americas-united-states-of-america
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    Dataset updated
    Dec 24, 2024
    Dataset provided by
    CEICdata.com
    License

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

    Time period covered
    Jan 1, 2024 - Dec 1, 2024
    Area covered
    Australia
    Variables measured
    Tourism Statistics
    Description

    Australia Visitor Arrivals: By Country: Americas: United States of America data was reported at 95,060.000 Movement in Dec 2024. This records an increase from the previous number of 63,230.000 Movement for Nov 2024. Australia Visitor Arrivals: By Country: Americas: United States of America data is updated monthly, averaging 36,350.000 Movement from Jan 1991 (Median) to Dec 2024, with 408 observations. The data reached an all-time high of 100,900.000 Movement in Dec 2018 and a record low of 180.000 Movement in Apr 2020. Australia Visitor Arrivals: By Country: Americas: United States of America data remains active status in CEIC and is reported by Australian Bureau of Statistics. The data is categorized under Global Database’s Australia – Table AU.Q006: Visitor Arrivals: Short Term: by Countries. [COVID-19-IMPACT]

  7. d

    Mass Killings in America, 2006 - present

    • data.world
    csv, zip
    Updated Mar 25, 2025
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    The Associated Press (2025). Mass Killings in America, 2006 - present [Dataset]. https://data.world/associatedpress/mass-killings-public
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    zip, csvAvailable download formats
    Dataset updated
    Mar 25, 2025
    Authors
    The Associated Press
    Time period covered
    Jan 1, 2006 - Feb 21, 2025
    Area covered
    Description

    THIS DATASET WAS LAST UPDATED AT 8:10 PM EASTERN ON MARCH 24

    OVERVIEW

    2019 had the most mass killings since at least the 1970s, according to the Associated Press/USA TODAY/Northeastern University Mass Killings Database.

    In all, there were 45 mass killings, defined as when four or more people are killed excluding the perpetrator. Of those, 33 were mass shootings . This summer was especially violent, with three high-profile public mass shootings occurring in the span of just four weeks, leaving 38 killed and 66 injured.

    A total of 229 people died in mass killings in 2019.

    The AP's analysis found that more than 50% of the incidents were family annihilations, which is similar to prior years. Although they are far less common, the 9 public mass shootings during the year were the most deadly type of mass murder, resulting in 73 people's deaths, not including the assailants.

    One-third of the offenders died at the scene of the killing or soon after, half from suicides.

    About this Dataset

    The Associated Press/USA TODAY/Northeastern University Mass Killings database tracks all U.S. homicides since 2006 involving four or more people killed (not including the offender) over a short period of time (24 hours) regardless of weapon, location, victim-offender relationship or motive. The database includes information on these and other characteristics concerning the incidents, offenders, and victims.

    The AP/USA TODAY/Northeastern database represents the most complete tracking of mass murders by the above definition currently available. Other efforts, such as the Gun Violence Archive or Everytown for Gun Safety may include events that do not meet our criteria, but a review of these sites and others indicates that this database contains every event that matches the definition, including some not tracked by other organizations.

    This data will be updated periodically and can be used as an ongoing resource to help cover these events.

    Using this Dataset

    To get basic counts of incidents of mass killings and mass shootings by year nationwide, use these queries:

    Mass killings by year

    Mass shootings by year

    To get these counts just for your state:

    Filter killings by state

    Definition of "mass murder"

    Mass murder is defined as the intentional killing of four or more victims by any means within a 24-hour period, excluding the deaths of unborn children and the offender(s). The standard of four or more dead was initially set by the FBI.

    This definition does not exclude cases based on method (e.g., shootings only), type or motivation (e.g., public only), victim-offender relationship (e.g., strangers only), or number of locations (e.g., one). The time frame of 24 hours was chosen to eliminate conflation with spree killers, who kill multiple victims in quick succession in different locations or incidents, and to satisfy the traditional requirement of occurring in a “single incident.”

    Offenders who commit mass murder during a spree (before or after committing additional homicides) are included in the database, and all victims within seven days of the mass murder are included in the victim count. Negligent homicides related to driving under the influence or accidental fires are excluded due to the lack of offender intent. Only incidents occurring within the 50 states and Washington D.C. are considered.

    Methodology

    Project researchers first identified potential incidents using the Federal Bureau of Investigation’s Supplementary Homicide Reports (SHR). Homicide incidents in the SHR were flagged as potential mass murder cases if four or more victims were reported on the same record, and the type of death was murder or non-negligent manslaughter.

    Cases were subsequently verified utilizing media accounts, court documents, academic journal articles, books, and local law enforcement records obtained through Freedom of Information Act (FOIA) requests. Each data point was corroborated by multiple sources, which were compiled into a single document to assess the quality of information.

    In case(s) of contradiction among sources, official law enforcement or court records were used, when available, followed by the most recent media or academic source.

    Case information was subsequently compared with every other known mass murder database to ensure reliability and validity. Incidents listed in the SHR that could not be independently verified were excluded from the database.

    Project researchers also conducted extensive searches for incidents not reported in the SHR during the time period, utilizing internet search engines, Lexis-Nexis, and Newspapers.com. Search terms include: [number] dead, [number] killed, [number] slain, [number] murdered, [number] homicide, mass murder, mass shooting, massacre, rampage, family killing, familicide, and arson murder. Offender, victim, and location names were also directly searched when available.

    This project started at USA TODAY in 2012.

    Contacts

    Contact AP Data Editor Justin Myers with questions, suggestions or comments about this dataset at jmyers@ap.org. The Northeastern University researcher working with AP and USA TODAY is Professor James Alan Fox, who can be reached at j.fox@northeastern.edu or 617-416-4400.

  8. d

    BIGDBM US Commercial Property/Real Estate Data

    • datarade.ai
    + more versions
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    BIGDBM, BIGDBM US Commercial Property/Real Estate Data [Dataset]. https://datarade.ai/data-products/bigdbm-us-commercial-property-real-estate-data-bigdbm
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    Dataset authored and provided by
    BIGDBM
    Area covered
    United States of America
    Description

    The US Consumer Commercial Property/Real Estate file has 30 million+ non-residential properties which include property characteristics, site details, purchase details, tax details, and ownership information.

    We have developed this file to be tied to our Consumer and B2B Database so additional data fields can be applied to the owners. Each record is ranked by confidence and only the highest quality data is used.

    Note - all Consumer packages can include necessary PII (address, email, phone, DOB, etc.) for merging, linking, and activation of the data.

    BIGDBM Privacy Policy: https://bigdbm.com/privacy.html

  9. NOAA/WDS Paleoclimatology - Miller, N.G., Princeton Site (PRINCETN) North...

    • catalog.data.gov
    • s.cnmilf.com
    Updated Dec 1, 2024
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    (Point of Contact); NOAA World Data Service for Paleoclimatology (Point of Contact) (2024). NOAA/WDS Paleoclimatology - Miller, N.G., Princeton Site (PRINCETN) North American Plant Macrofossil Database [Dataset]. https://catalog.data.gov/dataset/noaa-wds-paleoclimatology-miller-n-g-princeton-site-princetn-north-american-plant-macrofossil-d2
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    Dataset updated
    Dec 1, 2024
    Dataset provided by
    National Oceanic and Atmospheric Administrationhttp://www.noaa.gov/
    Description

    This archived Paleoclimatology Study is available from the NOAA National Centers for Environmental Information (NCEI), under the World Data Service (WDS) for Paleoclimatology. The associated NCEI study type is Plant Macrofossil. The data include parameters of plant macrofossil (population abundance) with a geographic location of Ohio, United States Of America. The time period coverage is from 22763 to 22750 in calendar years before present (BP). See metadata information for parameter and study location details. Please cite this study when using the data.

  10. NOAA/WDS Paleoclimatology - Global Database of Borehole Temperatures and...

    • catalog.data.gov
    • s.cnmilf.com
    Updated May 1, 2024
    + more versions
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    NOAA National Centers for Environmental Information (Point of Contact); NOAA World Data Service for Paleoclimatology (Point of Contact) (2024). NOAA/WDS Paleoclimatology - Global Database of Borehole Temperatures and Climate Reconstructions - US-NY7-79 [Dataset]. https://catalog.data.gov/dataset/noaa-wds-paleoclimatology-global-database-of-borehole-temperatures-and-climate-reconstructio-792
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    Dataset updated
    May 1, 2024
    Dataset provided by
    National Centers for Environmental Informationhttps://www.ncei.noaa.gov/
    National Oceanic and Atmospheric Administrationhttp://www.noaa.gov/
    Description

    This archived Paleoclimatology Study is available from the NOAA National Centers for Environmental Information (NCEI), under the World Data Service (WDS) for Paleoclimatology. The associated NCEI study type is Borehole. The data include parameters of borehole with a geographic location of United States Of America. The time period coverage is from 450 to -16 in calendar years before present (BP). See metadata information for parameter and study location details. Please cite this study when using the data.

  11. NOAA/WDS Paleoclimatology - Global Database of Borehole Temperatures and...

    • catalog.data.gov
    • s.cnmilf.com
    Updated May 1, 2024
    + more versions
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    NOAA National Centers for Environmental Information (Point of Contact); NOAA World Data Service for Paleoclimatology (Point of Contact) (2024). NOAA/WDS Paleoclimatology - Global Database of Borehole Temperatures and Climate Reconstructions - US-CO5-8 [Dataset]. https://catalog.data.gov/dataset/noaa-wds-paleoclimatology-global-database-of-borehole-temperatures-and-climate-reconstructions-553
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    Dataset updated
    May 1, 2024
    Dataset provided by
    National Centers for Environmental Informationhttps://www.ncei.noaa.gov/
    National Oceanic and Atmospheric Administrationhttp://www.noaa.gov/
    Description

    This archived Paleoclimatology Study is available from the NOAA National Centers for Environmental Information (NCEI), under the World Data Service (WDS) for Paleoclimatology. The associated NCEI study type is Borehole. The data include parameters of borehole with a geographic location of United States Of America. The time period coverage is from 450 to -18 in calendar years before present (BP). See metadata information for parameter and study location details. Please cite this study when using the data.

  12. American Hospital Association (AHA) Annual Survey Database - 2017

    • archive.ciser.cornell.edu
    Updated Apr 11, 2024
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    American Hospital Association (2024). American Hospital Association (AHA) Annual Survey Database - 2017 [Dataset]. https://archive.ciser.cornell.edu/studies/2891
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    Dataset updated
    Apr 11, 2024
    Dataset authored and provided by
    American Hospital Associationhttp://www.aha.org/
    Variables measured
    Organization
    Description

    AHA Annual Survey Database™ for Fiscal Year 2017 is a comprehensive hospital database for peer review benchmarking, market analysis, and health services research. It is produced primarily from the AHA Annual Survey of Hospitals, which has been administered by the American Hospital Association (AHA) since 1946. The survey responses are supplemented by data drawn the U.S. Census Bureau, hospital accrediting bodies, and other organizations.

  13. d

    Digital data set describing surficial geology in the conterminous US

    • catalog.data.gov
    • data.usgs.gov
    • +2more
    Updated Nov 1, 2024
    + more versions
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    U.S. Geological Survey (2024). Digital data set describing surficial geology in the conterminous US [Dataset]. https://catalog.data.gov/dataset/digital-data-set-describing-surficial-geology-in-the-conterminous-us
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    Dataset updated
    Nov 1, 2024
    Dataset provided by
    United States Geological Surveyhttp://www.usgs.gov/
    Area covered
    Contiguous United States, United States
    Description

    This digital data set describes surficial geology of the conterminous United States. The data set was generated from a U.S. Geological Survey 1:7,500,000-scale map of surficial geology published as part of the U.S. Geological Survey National Atlas map series.

  14. N

    Norwood Young America, MN Age Group Population Dataset: A Complete Breakdown...

    • neilsberg.com
    csv, json
    Updated Jul 24, 2024
    + more versions
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    Neilsberg Research (2024). Norwood Young America, MN Age Group Population Dataset: A Complete Breakdown of Norwood Young America Age Demographics from 0 to 85 Years and Over, Distributed Across 18 Age Groups // 2024 Edition [Dataset]. https://www.neilsberg.com/research/datasets/aaab0446-4983-11ef-ae5d-3860777c1fe6/
    Explore at:
    csv, jsonAvailable download formats
    Dataset updated
    Jul 24, 2024
    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
    Minnesota, Norwood Young America, United States
    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) 2018-2022 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 Norwood Young America 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 Norwood Young America. The dataset can be utilized to understand the population distribution of Norwood Young America by age. For example, using this dataset, we can identify the largest age group in Norwood Young America.

    Key observations

    The largest age group in Norwood Young America, MN was for the group of age 35 to 39 years years with a population of 316 (8.20%), according to the ACS 2018-2022 5-Year Estimates. At the same time, the smallest age group in Norwood Young America, MN was the 75 to 79 years years with a population of 76 (1.97%). Source: U.S. Census Bureau American Community Survey (ACS) 2018-2022 5-Year Estimates

    Content

    When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2018-2022 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 Norwood Young America is shown in this column.
    • % of Total Population: This column displays the population of each age group as a proportion of Norwood Young America 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 Norwood Young America Population by Age. You can refer the same here

  15. U

    Leishmania in the Americas DB

    • research-data.urosario.edu.co
    • produccioncientifica.usal.es
    tsv
    Updated Aug 25, 2021
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    Universidad del Rosario (2021). Leishmania in the Americas DB [Dataset]. http://doi.org/10.34848/FK2_leshmania_ds
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    tsv(630337), tsv(694063), tsv(571488)Available download formats
    Dataset updated
    Aug 25, 2021
    Dataset provided by
    Universidad del Rosario
    License

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

    Description

    This database contains geo-referenced points of Leishmania species occurrence in America.

  16. u

    2020 Census Tracts New Mexico

    • gstore.unm.edu
    csv, geojson, gml +5
    Updated Sep 10, 2021
    + more versions
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    Earth Data Analysis Center (2021). 2020 Census Tracts New Mexico [Dataset]. https://gstore.unm.edu/apps/rgis/datasets/27ac29fd-b6b9-4a93-9258-33091f06e3b1/metadata/FGDC-STD-001-1998.html
    Explore at:
    gml(5), zip(5), geojson(5), xls(5), json(5), kml(5), shp(5), csv(5)Available download formats
    Dataset updated
    Sep 10, 2021
    Dataset provided by
    Earth Data Analysis Center
    Time period covered
    May 23, 2020
    Area covered
    Federal Information Processing Standards (FIPS), ANSI, and feature names., New Mexico, West Bounding Coordinate -109.050431 East Bounding Coordinate -103.002043 North Bounding Coordinate 37.000233 South Bounding Coordinate 31.33216, United States
    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. 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 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.

  17. United States FFC: MA: Foreign: Other

    • ceicdata.com
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    CEICdata.com, United States FFC: MA: Foreign: Other [Dataset]. https://www.ceicdata.com/en/united-states/us-financial-firms-claims-on-foreigner-quarterly/ffc-ma-foreign-other
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    Dataset provided by
    CEIC Data
    License

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

    Time period covered
    Mar 1, 2015 - Dec 1, 2017
    Area covered
    United States
    Variables measured
    International Reserves
    Description

    United States FFC: MA: Foreign: Other data was reported at 9.000 USD mn in Mar 2018. This stayed constant from the previous number of 9.000 USD mn for Dec 2017. United States FFC: MA: Foreign: Other data is updated quarterly, averaging 3.000 USD mn from Mar 2003 (Median) to Mar 2018, with 61 observations. The data reached an all-time high of 44.000 USD mn in Dec 2011 and a record low of 0.000 USD mn in Dec 2010. United States FFC: MA: Foreign: Other data remains active status in CEIC and is reported by US Department of Treasury. The data is categorized under Global Database’s USA – Table US.KA023: US Financial Firms Claims on Foreigner: Quarterly.

  18. Data from: Berry Slave Value Database, 10 U.S. States, 1797-1865

    • icpsr.umich.edu
    ascii, delimited, r +3
    Updated Jul 3, 2018
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    Berry, Daina Ramey (2018). Berry Slave Value Database, 10 U.S. States, 1797-1865 [Dataset]. http://doi.org/10.3886/ICPSR37099.v1
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    stata, r, spss, sas, delimited, asciiAvailable download formats
    Dataset updated
    Jul 3, 2018
    Dataset provided by
    Inter-university Consortium for Political and Social Researchhttps://www.icpsr.umich.edu/web/pages/
    Authors
    Berry, Daina Ramey
    License

    https://www.icpsr.umich.edu/web/ICPSR/studies/37099/termshttps://www.icpsr.umich.edu/web/ICPSR/studies/37099/terms

    Time period covered
    1797 - 1865
    Area covered
    Maryland, Texas, Alabama, Georgia, Louisiana, Tennessee, Virginia, South Carolina, North Carolina, United States
    Description

    This study uses historical records from 36 archives in the United States to analyze 8,437 enslaved people's sale and/or appraisal prices from 1797 to 1865.

  19. NOAA/WDS Paleoclimatology - Global Database of Borehole Temperatures and...

    • catalog.data.gov
    Updated May 1, 2024
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    NOAA National Centers for Environmental Information (Point of Contact); NOAA World Data Service for Paleoclimatology (Point of Contact) (2024). NOAA/WDS Paleoclimatology - Global Database of Borehole Temperatures and Climate Reconstructions - US-CO3-73 [Dataset]. https://catalog.data.gov/dataset/noaa-wds-paleoclimatology-global-database-of-borehole-temperatures-and-climate-reconstructio-731
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    Dataset updated
    May 1, 2024
    Dataset provided by
    National Centers for Environmental Informationhttps://www.ncei.noaa.gov/
    National Oceanic and Atmospheric Administrationhttp://www.noaa.gov/
    Description

    This archived Paleoclimatology Study is available from the NOAA National Centers for Environmental Information (NCEI), under the World Data Service (WDS) for Paleoclimatology. The associated NCEI study type is Borehole. The data include parameters of borehole with a geographic location of United States Of America. The time period coverage is from 450 to -20 in calendar years before present (BP). See metadata information for parameter and study location details. Please cite this study when using the data.

  20. Water Quality Portal

    • catalog.data.gov
    • agdatacommons.nal.usda.gov
    • +1more
    Updated Mar 30, 2024
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    Agricultural Research Service (2024). Water Quality Portal [Dataset]. https://catalog.data.gov/dataset/water-quality-portal-a4e85
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    Dataset updated
    Mar 30, 2024
    Dataset provided by
    Agricultural Research Servicehttps://www.ars.usda.gov/
    Description

    The Water Quality Portal (WQP) is a cooperative service sponsored by the United States Geological Survey (USGS), the Environmental Protection Agency (EPA), and the National Water Quality Monitoring Council (NWQMC). It serves data collected by over 400 state, federal, tribal, and local agencies. Water quality data can be downloaded in Excel, CSV, TSV, and KML formats. Fourteen site types are found in the WQP: aggregate groundwater use, aggregate surface water use, atmosphere, estuary, facility, glacier, lake, land, ocean, spring, stream, subsurface, well, and wetland. Water quality characteristic groups include physical conditions, chemical and bacteriological water analyses, chemical analyses of fish tissue, taxon abundance data, toxicity data, habitat assessment scores, and biological index scores, among others. Within these groups, thousands of water quality variables registered in the EPA Substance Registry Service (https://iaspub.epa.gov/sor_internet/registry/substreg/home/overview/home.do) and the Integrated Taxonomic Information System (https://www.itis.gov/) are represented. Across all site types, physical characteristics (e.g., temperature and water level) are the most common water quality result type in the system. The Water Quality Exchange data model (WQX; http://www.exchangenetwork.net/data-exchange/wqx/), initially developed by the Environmental Information Exchange Network, was adapted by EPA to support submission of water quality records to the EPA STORET Data Warehouse [USEPA, 2016], and has subsequently become the standard data model for the WQP. Contributing organizations: ACWI The Advisory Committee on Water Information (ACWI) represents the interests of water information users and professionals in advising the federal government on federal water information programs and their effectiveness in meeting the nation's water information needs. ARS The Agricultural Research Service (ARS) is the U.S. Department of Agriculture's chief in-house scientific research agency, whose job is finding solutions to agricultural problems that affect Americans every day, from field to table. ARS conducts research to develop and transfer solutions to agricultural problems of high national priority and provide information access and dissemination to, among other topics, enhance the natural resource base and the environment. Water quality data from STEWARDS, the primary database for the USDA/ARS Conservation Effects Assessment Project (CEAP) are ingested into WQP via a web service. EPA The Environmental Protection Agency (EPA) gathers and distributes water quality monitoring data collected by states, tribes, watershed groups, other federal agencies, volunteer groups, and universities through the Water Quality Exchange framework in the STORET Warehouse. NWQMC The National Water Quality Monitoring Council (NWQMC) provides a national forum for coordination of comparable and scientifically defensible methods and strategies to improve water quality monitoring, assessment, and reporting. It also promotes partnerships to foster collaboration, advance the science, and improve management within all elements of the water quality monitoring community. USGS The United States Geological Survey (USGS) investigates the occurrence, quantity, quality, distribution, and movement of surface waters and ground waters and disseminates the data to the public, state, and local governments, public and private utilities, and other federal agencies involved with managing the United States' water resources. Resources in this dataset:Resource Title: Website Pointer for Water Quality Portal. File Name: Web Page, url: https://www.waterqualitydata.us/ The Water Quality Portal (WQP) is a cooperative service sponsored by the United States Geological Survey (USGS), the Environmental Protection Agency (EPA), and the National Water Quality Monitoring Council (NWQMC). It serves data collected by over 400 state, federal, tribal, and local agencies. Links to Download Data, User Guide, Contributing Organizations, National coverage by state.

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U.S. Geological Survey (2024). Hydrologic Derivatives for Modeling and Analysis (HDMA) database -- South America [Dataset]. https://catalog.data.gov/dataset/hydrologic-derivatives-for-modeling-and-analysis-hdma-database-south-america

Hydrologic Derivatives for Modeling and Analysis (HDMA) database -- South America

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Dataset updated
Jul 6, 2024
Dataset provided by
United States Geological Surveyhttp://www.usgs.gov/
Area covered
South America
Description

This contains the South American portion of the Hydrologic Derivatives for Modeling and Analysis (HDMA) database. The HDMA database provides comprehensive and consistent global coverage of raster and vector topographically derived layers, including raster layers of digital elevation model (DEM) data, flow direction, flow accumulation, slope, and compound topographic index (CTI); and vector layers of streams and catchment boundaries. The coverage of the data is global (-180º, 180º, -90º, 90º) with the underlying DEM being a hybrid of three datasets: HydroSHEDS (Hydrological data and maps based on SHuttle Elevation Derivatives at multiple Scales), Global Multi-resolution Terrain Elevation Data 2010 (GMTED2010) and the Shuttle Radar Topography Mission (SRTM). For most of the globe south of 60º North, the raster resolution of the data is 3-arc-seconds, corresponding to the resolution of the SRTM. For the areas North of 60º, the resolution is 7.5-arc-seconds (the smallest resolution of the GMTED2010 dataset) except for Greenland, where the resolution is 30-arc-seconds. The streams and catchments are attributed with Pfafstetter codes, based on a hierarchical numbering system, that carry important topological information.

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