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.

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.

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

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;

United States US: Account at a Financial Institution: 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 at a Financial Institution: 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 at a Financial Institution: 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. Account at a financial institution denotes the percentage of respondents who report having an account (by themselves or together with someone else) at a bank or another type of financial institution.; ; Demirguc-Kunt et al., 2015, Global Financial Inclusion Database, World Bank.; Weighted average;

Context

The dataset is from the U.S. Small Business Administration (SBA)

The U.S. SBA was founded in 1953 on the principle of promoting and assisting small enterprises in the U.S. credit market (SBA Overview and History, US Small Business Administration (2015)). Small businesses have been a primary source of job creation in the United States; therefore, fostering small business formation and growth has social benefits by creating job opportunities and reducing unemployment.

There have been many success stories of start-ups receiving SBA loan guarantees such as FedEx and Apple Computer. However, there have also been stories of small businesses and/or start-ups that have defaulted on their SBA-guaranteed loans.

Content

Shape of the data: 899164 rows and 27 columns

Data Dictionary

Description of the first two digits of NAICS.

Acknowledgements

Original data set id from “Should This Loan be Approved or Denied?”: A Large Dataset with Class Assignment Guidelines. by: Min Li, Amy Mickel & Stanley Taylor

To link to this article: https://doi.org/10.1080/10691898.2018.1434342

Inspiration

Good luck with predictions!

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 filewith no overlaps or gaps between parts, however, each TIGER/Line File is designed to stand alone as an independent dataset, or they can be combined to cover the entire nation. The Area Hydrography Shapefile contains the geometry and attributes of both perennial and intermittent area hydrography features, including ponds, lakes, oceans, swamps (up to the U.S. nautical three-mile limit), glaciers, and the area covered by large rivers, streams, and/or canals that are represented as double-line drainage. Single-line drainage water features can be found in the Linear Hydrography Shapefile (LINEARWATER.shp). Linear water features includes single-line drainage water features and artificial path features, where they exist, that run through double-line drainage features such as rivers, streams, and/or canals, and serve as a linear representation of these features.

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/

While most Americans appear to acknowledge the large gap between the rich and the poor in the U.S., it is not clear if the public is aware of recent changes in income inequality. Even though economic inequality has grown substantially in recent decades, studies have shown that the public's perception of growing income disparities has remained mostly unchanged since the 1980s. This research offers an alternative approach to evaluating how public perceptions of inequality are developed. Centrally, it conceptualizes the public's response to growing economic disparities by applying theories of macro-political behavior and place-based contextual effects to the formation of aggregate perceptions about income inequality. It is argued that most of the public relies on basic information about the economy to form attitudes about inequality and that geographic context---in this case, the American states---plays a role in how views of income disparities are produced. A new measure of state perceptions of growing economic inequality over a 25-year period is used to examine whether the public is responsive to objective changes in economic inequality. Time-series cross-sectional analyses suggest that the public's perceptions of growing inequality are largely influenced by objective state economic indicators and state political ideology. This research has implications for how knowledgeable the public is of disparities between the rich and the poor, whether state context influences attitudes about inequality, and what role the public will have in determining how expanding income differences are addressed through government policy.

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 Address Ranges Feature Shapefile (ADDRFEAT.dbf) contains the geospatial edge geometry and attributes of all unsuppressed address ranges for a county or county equivalent area. The term "address range" refers to the collection of all possible structure numbers from the first structure number to the last structure number and all numbers of a specified parity in between along an edge side relative to the direction in which the edge is coded. Single-address address ranges have been suppressed to maintain the confidentiality of the addresses they describe. Multiple coincident address range feature edge records are represented in the shapefile if more than one left or right address ranges are associated to the edge. The ADDRFEAT shapefile contains a record for each address range to street name combination. Address range associated to more than one street name are also represented by multiple coincident address range feature edge records. Note that the ADDRFEAT shapefile includes all unsuppressed address ranges compared to the All Lines Shapefile (EDGES.shp) which only includes the most inclusive address range associated with each side of a street edge. The TIGER/Line shapefile contain potential address ranges, not individual addresses. The address ranges in the TIGER/Line Files are potential ranges that include the full range of possible structure numbers even though the actual structures may not exist.

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

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.

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

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

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

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