15 datasets found
  1. h

    100-richest-people-in-world

    • huggingface.co
    Updated Aug 2, 2023
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    Nate Raw (2023). 100-richest-people-in-world [Dataset]. https://huggingface.co/datasets/nateraw/100-richest-people-in-world
    Explore at:
    CroissantCroissant is a format for machine-learning datasets. Learn more about this at mlcommons.org/croissant.
    Dataset updated
    Aug 2, 2023
    Authors
    Nate Raw
    License

    https://choosealicense.com/licenses/cc0-1.0/https://choosealicense.com/licenses/cc0-1.0/

    Area covered
    World
    Description

    Dataset Card for 100 Richest People In World

      Dataset Summary
    

    This dataset contains the list of Top 100 Richest People in the World Column Information:-

    Name - Person Name NetWorth - His/Her Networth Age - Person Age Country - The country person belongs to Source - Information Source Industry - Expertise Domain

      Join our Community
    
    
    
    
    
    
    
    
    
      Supported Tasks and Leaderboards
    

    [More Information Needed]

      Languages
    

    [More Information Needed]… See the full description on the dataset page: https://huggingface.co/datasets/nateraw/100-richest-people-in-world.

  2. United States US: Account: Income: Richest 60%: % Aged 15+

    • ceicdata.com
    Updated Mar 15, 2023
    + more versions
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    CEICdata.com (2023). United States US: Account: Income: Richest 60%: % Aged 15+ [Dataset]. https://www.ceicdata.com/en/united-states/banking-indicators/us-account-income-richest-60--aged-15
    Explore at:
    Dataset updated
    Mar 15, 2023
    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

    Area covered
    United States
    Variables measured
    undefined
    Description

    United States US: Account: Income: Richest 60%: % Aged 15+ data was reported at 97.904 % in 2014. This records an increase from the previous number of 92.810 % for 2011. United States US: Account: Income: Richest 60%: % Aged 15+ data is updated yearly, averaging 95.357 % from Dec 2011 (Median) to 2014, with 2 observations. The data reached an all-time high of 97.904 % in 2014 and a record low of 92.810 % in 2011. United States US: Account: Income: Richest 60%: % Aged 15+ data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s United States – Table US.World Bank.WDI: Banking Indicators. Denotes the percentage of respondents who report having an account (by themselves or together with someone else). For 2011, this can be an account at a bank or another type of financial institution, and for 2014 this can be a mobile account as well (see year-specific definitions for details) (income, richest 60%, % age 15+). [ts: data are available for multiple waves].; ; Demirguc-Kunt et al., 2015, Global Financial Inclusion Database, World Bank.; Weighted average;

  3. i

    Richest Zip Codes in United States Virgin Islands

    • incomebyzipcode.com
    Updated Dec 18, 2024
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    Cubit Planning, Inc. (2024). Richest Zip Codes in United States Virgin Islands [Dataset]. https://www.incomebyzipcode.com/unitedstatesvirginislands
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    Dataset updated
    Dec 18, 2024
    Dataset authored and provided by
    Cubit Planning, Inc.
    License

    https://www.incomebyzipcode.com/terms#TERMShttps://www.incomebyzipcode.com/terms#TERMS

    Area covered
    U.S. Virgin Islands
    Description

    A dataset listing the richest zip codes in United States Virgin Islands per the most current US Census data, including information on rank and average income.

  4. U.S. median household income 2023, by state

    • statista.com
    • ai-chatbox.pro
    Updated Sep 16, 2024
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    Statista (2024). U.S. median household income 2023, by state [Dataset]. https://www.statista.com/statistics/233170/median-household-income-in-the-united-states-by-state/
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    Dataset updated
    Sep 16, 2024
    Dataset authored and provided by
    Statistahttp://statista.com/
    Time period covered
    2023
    Area covered
    United States
    Description

    In 2023, the real median household income in the state of Alabama was 60,660 U.S. dollars. The state with the highest median household income was Massachusetts, which was 106,500 U.S. dollars in 2023. The average median household income in the United States was at 80,610 U.S. dollars.

  5. d

    Hydrologic Data Sites for Rich County, Utah

    • search.dataone.org
    • data.usgs.gov
    • +3more
    Updated Oct 29, 2016
    + more versions
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    U.S. Geological Survey (2016). Hydrologic Data Sites for Rich County, Utah [Dataset]. https://search.dataone.org/view/82a27cbc-bba7-4a27-bd85-28c56c94f6e6
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    Dataset updated
    Oct 29, 2016
    Dataset provided by
    United States Geological Surveyhttp://www.usgs.gov/
    Authors
    U.S. Geological Survey
    Area covered
    Description

    This map shows the USGS (United States Geologic Survey), NWIS (National Water Inventory System) Hydrologic Data Sites for Rich County, Utah.

    The scope and purpose of NWIS is defined on the web site:

    http://water.usgs.gov/public/pubs/FS/FS-027-98/

  6. Z

    Large-scale and fine-grained phenological stage annotation of herbarium...

    • data.niaid.nih.gov
    Updated Jan 24, 2020
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    Hervé Goëau (2020). Large-scale and fine-grained phenological stage annotation of herbarium specimens datasets [Dataset]. https://data.niaid.nih.gov/resources?id=zenodo_2548629
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    Dataset updated
    Jan 24, 2020
    Dataset provided by
    Patrick W. Sweeney
    Alexis Joly
    Gil Nelson
    Katelin D. Pearson
    Elizabeth R. Ellwood
    Jenn M. Yost
    Pierre Bonnet
    Titouan Lorieul
    Jean-François Molino
    Pamela S. Soltis
    Joel Sachs
    Erick Mata-Montero
    Hervé Goëau
    License

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

    Description

    This upload is constituted of four datasets of specimens from American herbaria covering different levels of information precision and different floras - from temperate to equatorial.

    Three of these datasets consist of selected specimens from herbaria located in different geographic and environmental regions. Each specimen of these three datasets was annotated with the following fields: family, genus, species name, fertile / non-fertile, presence / absence of flower(s), presence / absence of fruit(s). The resulting dataset was composed of 163,233 herbarium specimens belonging to 7,782 species, 1,906 genera, and 236 families. Specimens were annotated as “fertile” if any reproductive structures were present, such as sporangia (ferns), cones (gymnosperms), flowers, or fruits (angiosperms). Non-fertile specimens were those that lacked any reproductive structures.

    The fourth dataset consists of 20,371 herbarium specimens from 11 genera in the sunflower family (Asteraceae). The main difference in this dataset is that it is annotated with fine-grained phenophase scores rather than presence/absence attributes (see description below).

    Each of these datasets is described below:

    NEVP: this dataset of New England vascular plant (NEVP) specimens was produced by members of the Consortium of Northeastern Herbaria. The dataset comprises 42,658 digitized specimens that belong to 1,375 species and come from several North American institutions. Most of the specimens in this dataset are from the north-temperate region of the northeastern United States.

    FSU: this dataset was produced by the Florida State University's Robert K. Godfrey Herbarium (FSU), a collection that focuses on northern Florida and the U.S. Southeast Coastal Plain, one of North America's biodiversity hotspots. This dataset contains 54,263 digitized herbarium specimen records that belong to 3,870 species, making it the taxonomically richest dataset in this study. Most species in this dataset grow under subtropical or warm temperate conditions in the southeastern region of the United States.

    CAY: this dataset comes from the IRD’s Herbarium of French Guiana (CAY). CAY is dedicated to the Guayana Shield flora, with a strong focus on tropical tree species. This dataset is composed of 66,312 herbarium specimens that belong to 3,024 species. All digitized specimens of this herbarium are accessible online. Most specimens were collected in the tropical rainforests of French Guiana, with the remaining specimens coming mostly from Suriname and Guyana.

    PHENO: this dataset includes 20,371 herbarium specimens of 139 species in the Asteraceae produced in a study of phenological trends in the U.S. Southeast Coastal Plain. The dataset is composed of specimen records from 57 herbaria. Each recorded specimen was annotated for quartile percentages (0, 25, 50, 75, or 100%) of (i) closed buds, (ii) buds transformed into flowers, and (iii) fruits. According to the distribution of these three categories for each specimen, a phenophase code was computed.

    Datasets format

    These datasets are grouped in 3 tasks:

    fertility detection

    flowers and/or fruit detection

    phenophase classification

    The first 2 tasks are carried on the first 3 previous datasets and thus are based on the same set of images, unlike the third task which has its own disjoint set of images. This is why the dataset is presented into two separated files, one for each set of images.

    Fertility detection & flower/fruit detection

    These tasks are contained into the herbarium_fertility_annotations.zip archive. It consists of 3 files:

    metadata.csv: general information about all the herbarium specimens for these tasks

    id: specimen identifier

    collection: which of NEVP, FSU or CAY does the specimen come from

    herbarium: institution of origin of the specimen, especially for NEVP collection

    clade, family, genus, species: classification of the specimen

    URL: URL of the scan

    fertility_task.csv: specific information regarding the fertility detection task

    id: specimen identifier

    is_fertile: True if the specimen has an expression of fertility, False otherwise

    train_test_set: which subset does the specimen belong to; possible values are: train, random_test, species_test and herbarium_test

    flower_fruit_task.csv: specific information regarding the flower/fruit detection task

    id: specimen identifier, note that in this case not all the specimen described in metadata.csv are included in this task

    has_flower: True if the specimen has at least one flower, False otherwise

    has_fruit: True if the specimen has at least one fruit, False otherwise

    train_test_set: which subset does the specimen belong to; possible values are: train, random_test, species_test and herbarium_test

    Phenophase classification

    These tasks are contained into the herbarium_asteraceae_phenophase_annotations.zip archive. It consists of a single file:

    annotations.csv:

    id: specimen identifier

    URL: URL of the scan

    genus: genus of the specimen

    phenophase: integer from 1 to 9 describing the phenophase of the specimen

    train_test_set: which subset does the specimen belong to; possible values are: train and test

    Additional ressources

    More information can be found in the related paper: Lorieul, T., K. D. Pearson, E. R. Ellwood, H. Goëau, J.-F. Molino, P. W. Sweeney, J. M. Yost, J. Sachs, E. Mata-Montero, G. Nelson, P. S. Soltis, P. Bonnet, and A. Joly. 2019. Toward a large-scale and deep phenological stage annotation of herbarium specimens: Case studies from temperate, tropical, and equatorial floras. Applications in Plant Sciences 7(3): e1233.

    For an example of usage of these datasets as well as a baseline, see: http://doi.org/10.5281/zenodo.2549996

  7. c

    20 Richest Cities in California

    • california-demographics.com
    Updated Jun 20, 2024
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    Kristen Carney (2024). 20 Richest Cities in California [Dataset]. https://www.california-demographics.com/richest_cities
    Explore at:
    Dataset updated
    Jun 20, 2024
    Dataset provided by
    Cubit Planning, Inc.
    Authors
    Kristen Carney
    License

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

    Area covered
    California
    Description

    A dataset listing the 20 richest cities in California for 2024, including information on rank, city, county, population, average income, and median income.

  8. i

    Richest Zip Codes in Missouri

    • incomebyzipcode.com
    Updated Dec 18, 2024
    + more versions
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    Cubit Planning, Inc. (2024). Richest Zip Codes in Missouri [Dataset]. https://www.incomebyzipcode.com/missouri
    Explore at:
    Dataset updated
    Dec 18, 2024
    Dataset authored and provided by
    Cubit Planning, Inc.
    License

    https://www.incomebyzipcode.com/terms#TERMShttps://www.incomebyzipcode.com/terms#TERMS

    Area covered
    Missouri
    Description

    A dataset listing the richest zip codes in Missouri per the most current US Census data, including information on rank and average income.

  9. TIGER/Line Shapefile, 2022, County, Rich County, UT, Topological Faces...

    • s.cnmilf.com
    • catalog.data.gov
    Updated Jan 28, 2024
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    U.S. Department of Commerce, U.S. Census Bureau, Geography Division, Spatial Data Collection and Products Branch (Point of Contact) (2024). TIGER/Line Shapefile, 2022, County, Rich County, UT, Topological Faces (Polygons With All Geocodes) [Dataset]. https://s.cnmilf.com/user74170196/https/catalog.data.gov/dataset/tiger-line-shapefile-2022-county-rich-county-ut-topological-faces-polygons-with-all-geocodes
    Explore at:
    Dataset updated
    Jan 28, 2024
    Dataset provided by
    United States Department of Commercehttp://www.commerce.gov/
    United States Census Bureauhttp://census.gov/
    Area covered
    Rich County
    Description

    The TIGER/Line shapefiles and related database files (.dbf) are an extract of selected geographic and cartographic information from the U.S. Census Bureau's Master Address File / Topologically Integrated Geographic Encoding and Referencing (MAF/TIGER) Database (MTDB). The MTDB represents a seamless national file with no overlaps or gaps between parts, however, each TIGER/Line shapefile is designed to stand alone as an independent data set, or they can be combined to cover the entire nation. Face refers to the areal (polygon) topological primitives that make up MTDB. A face is bounded by one or more edges; its boundary includes only the edges that separate it from other faces, not any interior edges contained within the area of the face. The Topological Faces Shapefile contains the attributes of each topological primitive face. Each face has a unique topological face identifier (TFID) value. Each face in the shapefile includes the key geographic area codes for all geographic areas for which the Census Bureau tabulates data for both the 2020 Census and the annual estimates and surveys. The geometries of each of these geographic areas can then be built by dissolving the face geometries on the appropriate key geographic area codes in the Topological Faces Shapefile.

  10. T

    GOLD RESERVES by Country Dataset

    • tradingeconomics.com
    csv, excel, json, xml
    Updated May 26, 2014
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    TRADING ECONOMICS (2014). GOLD RESERVES by Country Dataset [Dataset]. https://tradingeconomics.com/country-list/gold-reserves
    Explore at:
    excel, xml, csv, jsonAvailable download formats
    Dataset updated
    May 26, 2014
    Dataset authored and provided by
    TRADING ECONOMICS
    License

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

    Time period covered
    2025
    Area covered
    World
    Description

    This dataset provides values for GOLD RESERVES reported in several countries. The data includes current values, previous releases, historical highs and record lows, release frequency, reported unit and currency.

  11. v

    20 Richest Cities in Virginia

    • virginia-demographics.com
    Updated Jun 20, 2024
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    Kristen Carney (2024). 20 Richest Cities in Virginia [Dataset]. https://www.virginia-demographics.com/richest_cities
    Explore at:
    Dataset updated
    Jun 20, 2024
    Dataset provided by
    Cubit Planning, Inc.
    Authors
    Kristen Carney
    License

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

    Area covered
    Virginia
    Description

    A dataset listing the 20 richest cities in Virginia for 2024, including information on rank, city, county, population, average income, and median income.

  12. m

    20 Richest Counties in Maryland

    • maryland-demographics.com
    Updated Jun 20, 2024
    + more versions
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    Kristen Carney (2024). 20 Richest Counties in Maryland [Dataset]. https://www.maryland-demographics.com/richest_counties
    Explore at:
    Dataset updated
    Jun 20, 2024
    Dataset provided by
    Cubit Planning, Inc.
    Authors
    Kristen Carney
    License

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

    Area covered
    Maryland
    Description

    A dataset listing the 20 richest counties in Maryland for 2024, including information on rank, county, population, average income, and median income.

  13. v

    20 Richest Counties in Virginia

    • virginia-demographics.com
    Updated Jun 20, 2024
    + more versions
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    Kristen Carney (2024). 20 Richest Counties in Virginia [Dataset]. https://www.virginia-demographics.com/richest_counties
    Explore at:
    Dataset updated
    Jun 20, 2024
    Dataset provided by
    Cubit Planning, Inc.
    Authors
    Kristen Carney
    License

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

    Area covered
    Virginia
    Description

    A dataset listing the 20 richest counties in Virginia for 2024, including information on rank, county, population, average income, and median income.

  14. i

    Richest Zip Codes in South Carolina

    • incomebyzipcode.com
    Updated Dec 18, 2024
    + more versions
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    Cubit Planning, Inc. (2024). Richest Zip Codes in South Carolina [Dataset]. https://www.incomebyzipcode.com/southcarolina
    Explore at:
    Dataset updated
    Dec 18, 2024
    Dataset authored and provided by
    Cubit Planning, Inc.
    License

    https://www.incomebyzipcode.com/terms#TERMShttps://www.incomebyzipcode.com/terms#TERMS

    Area covered
    South Carolina
    Description

    A dataset listing the richest zip codes in South Carolina per the most current US Census data, including information on rank and average income.

  15. g

    20 Richest Counties in Georgia

    • georgia-demographics.com
    Updated Jun 20, 2024
    + more versions
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    Kristen Carney (2024). 20 Richest Counties in Georgia [Dataset]. https://www.georgia-demographics.com/richest_counties
    Explore at:
    Dataset updated
    Jun 20, 2024
    Dataset provided by
    Cubit Planning, Inc.
    Authors
    Kristen Carney
    License

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

    Area covered
    Georgia
    Description

    A dataset listing the 20 richest counties in Georgia for 2024, including information on rank, county, population, average income, and median income.

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

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Nate Raw (2023). 100-richest-people-in-world [Dataset]. https://huggingface.co/datasets/nateraw/100-richest-people-in-world

100-richest-people-in-world

nateraw/100-richest-people-in-world

Explore at:
CroissantCroissant is a format for machine-learning datasets. Learn more about this at mlcommons.org/croissant.
Dataset updated
Aug 2, 2023
Authors
Nate Raw
License

https://choosealicense.com/licenses/cc0-1.0/https://choosealicense.com/licenses/cc0-1.0/

Area covered
World
Description

Dataset Card for 100 Richest People In World

  Dataset Summary

This dataset contains the list of Top 100 Richest People in the World Column Information:-

Name - Person Name NetWorth - His/Her Networth Age - Person Age Country - The country person belongs to Source - Information Source Industry - Expertise Domain

  Join our Community









  Supported Tasks and Leaderboards

[More Information Needed]

  Languages

[More Information Needed]… See the full description on the dataset page: https://huggingface.co/datasets/nateraw/100-richest-people-in-world.

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