100+ datasets found
  1. a

    Racial Diversity Index - City

    • vital-signs-bniajfi.hub.arcgis.com
    Updated Feb 27, 2020
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    Baltimore Neighborhood Indicators Alliance (2020). Racial Diversity Index - City [Dataset]. https://vital-signs-bniajfi.hub.arcgis.com/datasets/racial-diversity-index-city
    Explore at:
    Dataset updated
    Feb 27, 2020
    Dataset authored and provided by
    Baltimore Neighborhood Indicators Alliance
    Area covered
    Description

    The percent chance that two people picked at random within an area will be of a different race/ethnicity. This number does not reflect which race/ethnicity is predominant within an area. The higher the value, the more racially and ethnically diverse an area. Source: U.S. Bureau of the Census, American Community Survey Years Available: 2010, 2011-2015, 2012-2016, 2013-2017, 2014-2018, 2015-2019, 2017-2021, 2018-2022, 2019-2023

  2. N

    Median Household Income by Racial Categories in Richmond city, VA (2022)

    • neilsberg.com
    csv, json
    Updated Jan 3, 2024
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    Neilsberg Research (2024). Median Household Income by Racial Categories in Richmond city, VA (2022) [Dataset]. https://www.neilsberg.com/research/datasets/364ac68b-8904-11ee-9302-3860777c1fe6/
    Explore at:
    json, csvAvailable download formats
    Dataset updated
    Jan 3, 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
    Richmond, Virginia
    Variables measured
    Median Household Income for Asian Population, Median Household Income for Black Population, Median Household Income for White Population, Median Household Income for Some other race Population, Median Household Income for Two or more races Population, Median Household Income for American Indian and Alaska Native Population, Median Household Income for Native Hawaiian and Other Pacific Islander Population
    Measurement technique
    The data presented in this dataset is derived from the latest U.S. Census Bureau American Community Survey (ACS) 2022 1-Year Estimates. To portray the median household income within each racial category idetified by the US Census Bureau, we conducted an initial analysis and categorization of the data. Subsequently, we adjusted these figures for inflation using the Consumer Price Index retroactive series via current methods (R-CPI-U-RS). It is important to note that the median household income estimates exclusively represent the identified racial categories and do not incorporate any ethnicity classifications. Households are categorized, and median incomes are reported based on the self-identified race of the head of the household. For additional information about these estimations, please contact us via email at research@neilsberg.com
    Dataset funded by
    Neilsberg Research
    Description
    About this dataset

    Context

    The dataset presents the median household income across different racial categories in Richmond city. It portrays the median household income of the head of household across racial categories (excluding ethnicity) as identified by the Census Bureau. The dataset can be utilized to gain insights into economic disparities and trends and explore the variations in median houshold income for diverse racial categories.

    Key observations

    Based on our analysis of the distribution of Richmond city population by race & ethnicity, the population is predominantly Black or African American. This particular racial category constitutes the majority, accounting for 45.24% of the total residents in Richmond city. Notably, the median household income for Black or African American households is $37,707. Interestingly, despite the Black or African American population being the most populous, it is worth noting that White households actually reports the highest median household income, with a median income of $81,904. This reveals that, while Black or African Americans may be the most numerous in Richmond city, White households experience greater economic prosperity in terms of median household income.

    https://i.neilsberg.com/ch/richmond-city-va-median-household-income-by-race.jpeg" alt="Richmond city median household income diversity across racial categories">

    Content

    When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2022 1-Year Estimates.

    Racial categories include:

    • White
    • Black or African American
    • American Indian and Alaska Native
    • Asian
    • Native Hawaiian and Other Pacific Islander
    • Some other race
    • Two or more races (multiracial)

    Variables / Data Columns

    • Race of the head of household: This column presents the self-identified race of the household head, encompassing all relevant racial categories (excluding ethnicity) applicable in Richmond city.
    • Median household income: Median household income, adjusting for inflation, presented in 2022-inflation-adjusted dollars

    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 Richmond city median household income by race. You can refer the same here

  3. O

    City Employee vs. Community Demographics: Race

    • data.mesaaz.gov
    • citydata.mesaaz.gov
    csv, xlsx, xml
    Updated Jan 23, 2025
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    US Census (2025). City Employee vs. Community Demographics: Race [Dataset]. https://data.mesaaz.gov/w/bt2n-zimw/c963-au5t?cur=MRqkQSv54zE&from=28M0_J-ghoj
    Explore at:
    xlsx, xml, csvAvailable download formats
    Dataset updated
    Jan 23, 2025
    Dataset authored and provided by
    US Census
    Description

    Comparing the percentage of employee race to the percentage of city resident race. Employee information comes from Employee Demographics: Ethnicity https://citydata.mesaaz.gov/Human-Resources/Employee-Demographics-Ethnicity/6kd3-uaks. Community information comes from Community Demographics: Race: https://citydata.mesaaz.gov/Diversity/Community-Demographics-Race/xaqj-9vxh/data

  4. s

    Data from: Regional ethnic diversity

    • ethnicity-facts-figures.service.gov.uk
    csv
    Updated Dec 22, 2022
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    Race Disparity Unit (2022). Regional ethnic diversity [Dataset]. https://www.ethnicity-facts-figures.service.gov.uk/uk-population-by-ethnicity/national-and-regional-populations/regional-ethnic-diversity/latest
    Explore at:
    csv(1 MB), csv(47 KB)Available download formats
    Dataset updated
    Dec 22, 2022
    Dataset authored and provided by
    Race Disparity Unit
    License

    Open Government Licence 3.0http://www.nationalarchives.gov.uk/doc/open-government-licence/version/3/
    License information was derived automatically

    Area covered
    England
    Description

    According to the 2021 Census, London was the most ethnically diverse region in England and Wales – 63.2% of residents identified with an ethnic minority group.

  5. N

    Tell City, IN annual income distribution by work experience and gender...

    • neilsberg.com
    csv, json
    Updated Feb 27, 2025
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    Neilsberg Research (2025). Tell City, IN annual income distribution by work experience and gender dataset: Number of individuals ages 15+ with income, 2023 // 2025 Edition [Dataset]. https://www.neilsberg.com/research/datasets/bac96a6f-f4ce-11ef-8577-3860777c1fe6/
    Explore at:
    json, csvAvailable download formats
    Dataset updated
    Feb 27, 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
    Tell City
    Variables measured
    Income for Male Population, Income for Female Population, Income for Male Population working full time, Income for Male Population working part time, Income for Female Population working full time, Income for Female Population working part time, Number of males working full time for a given income bracket, Number of males working part time for a given income bracket, Number of females working full time for a given income bracket, Number of females working part time for a given income bracket
    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 portray the number of individuals for both the genders (Male and Female), within each income bracket we conducted an initial analysis and categorization of the American Community Survey data. Households are categorized, and median incomes are reported based on the self-identified gender of the head of the household. For additional information about these estimations, please contact us via email at research@neilsberg.com
    Dataset funded by
    Neilsberg Research
    Description
    About this dataset

    Context

    The dataset presents the detailed breakdown of the count of individuals within distinct income brackets, categorizing them by gender (men and women) and employment type - full-time (FT) and part-time (PT), offering valuable insights into the diverse income landscapes within Tell City. The dataset can be utilized to gain insights into gender-based income distribution within the Tell City population, aiding in data analysis and decision-making..

    Key observations

    • Employment patterns: Within Tell City, among individuals aged 15 years and older with income, there were 2,714 men and 2,967 women in the workforce. Among them, 1,345 men were engaged in full-time, year-round employment, while 1,002 women were in full-time, year-round roles.
    • Annual income under $24,999: Of the male population working full-time, 8.25% fell within the income range of under $24,999, while 11.78% of the female population working full-time was represented in the same income bracket.
    • Annual income above $100,000: 12.79% of men in full-time roles earned incomes exceeding $100,000, while 4.99% of women in full-time positions earned within this income bracket.
    • Refer to the research insights for more key observations on more income brackets ( Annual income under $24,999, Annual income between $25,000 and $49,999, Annual income between $50,000 and $74,999, Annual income between $75,000 and $99,999 and Annual income above $100,000) and employment types (full-time year-round and part-time)
    Content

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

    Income brackets:

    • $1 to $2,499 or loss
    • $2,500 to $4,999
    • $5,000 to $7,499
    • $7,500 to $9,999
    • $10,000 to $12,499
    • $12,500 to $14,999
    • $15,000 to $17,499
    • $17,500 to $19,999
    • $20,000 to $22,499
    • $22,500 to $24,999
    • $25,000 to $29,999
    • $30,000 to $34,999
    • $35,000 to $39,999
    • $40,000 to $44,999
    • $45,000 to $49,999
    • $50,000 to $54,999
    • $55,000 to $64,999
    • $65,000 to $74,999
    • $75,000 to $99,999
    • $100,000 or more

    Variables / Data Columns

    • Income Bracket: This column showcases 20 income brackets ranging from $1 to $100,000+..
    • Full-Time Males: The count of males employed full-time year-round and earning within a specified income bracket
    • Part-Time Males: The count of males employed part-time and earning within a specified income bracket
    • Full-Time Females: The count of females employed full-time year-round and earning within a specified income bracket
    • Part-Time Females: The count of females employed part-time and earning within a specified income bracket

    Employment type classifications include:

    • Full-time, year-round: A full-time, year-round worker is a person who worked full time (35 or more hours per week) and 50 or more weeks during the previous calendar year.
    • Part-time: A part-time worker is a person who worked less than 35 hours per week during the previous calendar year.

    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 Tell City median household income by race. You can refer the same here

  6. V

    City Council District Look Up

    • data.virginia.gov
    Updated May 21, 2025
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    Virginia Beach (2025). City Council District Look Up [Dataset]. https://data.virginia.gov/dataset/city-council-district-look-up
    Explore at:
    html, arcgis geoservices rest apiAvailable download formats
    Dataset updated
    May 21, 2025
    Dataset provided by
    City of Virginia Beach - Online Mapping
    Authors
    Virginia Beach
    Description

    GIS Web Map Application of the 10 City Council Voter Districts


    Search for an address to find out where it is located within one of the 10 City Council Voter Districts. These are the voter districts imposed by the U.S. District Court 2022.
    * Please note that the City of Virginia Beach is complying with the District Court’s ruling while simultaneously appealing the ruling to the U.S. Court of Appeals for the Fourth Circuit. These voter districts are also subject to pre-clearance approval by the Virginia Attorney General.

    If you don't know the voter district an address falls within, use one of these search methods:

    Click the search box and type in an address or choose Use current location
    Click within the map

    Results include Demographics for each voter district sourced from the US Census 2020 Public Law (P.L.) 94-171 Redistricting Files :
    Layer includes associated Demographics for each voter district sourced from the US Census 2020 Public Law (P.L.) 94-171 Redistricting Files:
    American Indian or Alaska Native: A person having origins in any of the original peoples of North and South America (including Central America), and who maintains tribal affiliation or community attachment.
    Asian: A person having origins in any of the original peoples of the Far East, Southeast Asia, or the Indian subcontinent including, for example, Cambodia, China, India, Japan, Korea, Malaysia, Pakistan, the Philippine Islands, Thailand, and Vietnam.
    Black or African American: A person having origins in any of the black racial groups of Africa.
    Hispanic or Latino: A person of Cuban, Mexican, Puerto Rican, South or Central American, or other Spanish culture or origin, regardless of race.
    Native Hawaiian or Other Pacific Islander: A person having origins in any of the original peoples of Hawaii, Guam, Samoa, or other Pacific Islands.
    White: A person having origins in any of the original peoples of Europe, the Middle East, or North Africa.
    The Diversity Index: Provided from Esri derived from 2020 US Census data that represents the likelihood that two persons, chosen
    at random from the same area, belong to different race or ethnic groups. Ethnic
    diversity, as well as racial diversity, is included in their definition of the Diversity
    Index. Esri's diversity calculations accommodate up to seven race groups: six
    single-race groups (White, Black, American Indian, Asian, Pacific Islander, Some
    Other Race) and one multiple-race group (two or more races). Each race group
    is divided into two ethnic origins, Hispanic and non-Hispanic. If an area is
    ethnically diverse, then diversity is compounded.


  7. a

    Org - City Workforce Diversity - Ethnicity DEV

    • egishub-phoenix.hub.arcgis.com
    Updated Jun 11, 2024
    + more versions
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    City of Phoenix (2024). Org - City Workforce Diversity - Ethnicity DEV [Dataset]. https://egishub-phoenix.hub.arcgis.com/datasets/org-city-workforce-diversity-ethnicity-dev
    Explore at:
    Dataset updated
    Jun 11, 2024
    Dataset authored and provided by
    City of Phoenix
    Description

    A dashboard used by government agencies to monitor key performance indicators (KPIs) and communicate progress made on strategic outcomes with the general public and other interested stakeholders.

  8. p

    Trends in Diversity Score (1999-2023): City Day Community School District...

    • publicschoolreview.com
    + more versions
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    Public School Review, Trends in Diversity Score (1999-2023): City Day Community School District vs. Ohio [Dataset]. https://www.publicschoolreview.com/ohio/city-day-community-school-district/3900029-school-district
    Explore at:
    Dataset authored and provided by
    Public School Review
    License

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

    Area covered
    Ohio
    Description

    This dataset tracks annual diversity score from 1999 to 2023 for City Day Community School District vs. Ohio

  9. N

    Rose City, TX annual income distribution by work experience and gender...

    • neilsberg.com
    csv, json
    Updated Feb 27, 2025
    + more versions
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    Neilsberg Research (2025). Rose City, TX annual income distribution by work experience and gender dataset: Number of individuals ages 15+ with income, 2023 // 2025 Edition [Dataset]. https://www.neilsberg.com/insights/rose-city-tx-income-by-gender/
    Explore at:
    csv, jsonAvailable download formats
    Dataset updated
    Feb 27, 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
    Rose City, Texas
    Variables measured
    Income for Male Population, Income for Female Population, Income for Male Population working full time, Income for Male Population working part time, Income for Female Population working full time, Income for Female Population working part time, Number of males working full time for a given income bracket, Number of males working part time for a given income bracket, Number of females working full time for a given income bracket, Number of females working part time for a given income bracket
    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 portray the number of individuals for both the genders (Male and Female), within each income bracket we conducted an initial analysis and categorization of the American Community Survey data. Households are categorized, and median incomes are reported based on the self-identified gender of the head of the household. For additional information about these estimations, please contact us via email at research@neilsberg.com
    Dataset funded by
    Neilsberg Research
    Description
    About this dataset

    Context

    The dataset presents the detailed breakdown of the count of individuals within distinct income brackets, categorizing them by gender (men and women) and employment type - full-time (FT) and part-time (PT), offering valuable insights into the diverse income landscapes within Rose City. The dataset can be utilized to gain insights into gender-based income distribution within the Rose City population, aiding in data analysis and decision-making..

    Key observations

    • Employment patterns: Within Rose City, among individuals aged 15 years and older with income, there were 161 men and 120 women in the workforce. Among them, 81 men were engaged in full-time, year-round employment, while 60 women were in full-time, year-round roles.
    • Annual income under $24,999: Of the male population working full-time, none fell within the income range of under $24,999, while 26.67% of the female population working full-time was represented in the same income bracket.
    • Annual income above $100,000: 14.81% of men in full-time roles earned incomes exceeding $100,000, while 3.33% of women in full-time positions earned within this income bracket.
    • Refer to the research insights for more key observations on more income brackets ( Annual income under $24,999, Annual income between $25,000 and $49,999, Annual income between $50,000 and $74,999, Annual income between $75,000 and $99,999 and Annual income above $100,000) and employment types (full-time year-round and part-time)
    Content

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

    Income brackets:

    • $1 to $2,499 or loss
    • $2,500 to $4,999
    • $5,000 to $7,499
    • $7,500 to $9,999
    • $10,000 to $12,499
    • $12,500 to $14,999
    • $15,000 to $17,499
    • $17,500 to $19,999
    • $20,000 to $22,499
    • $22,500 to $24,999
    • $25,000 to $29,999
    • $30,000 to $34,999
    • $35,000 to $39,999
    • $40,000 to $44,999
    • $45,000 to $49,999
    • $50,000 to $54,999
    • $55,000 to $64,999
    • $65,000 to $74,999
    • $75,000 to $99,999
    • $100,000 or more

    Variables / Data Columns

    • Income Bracket: This column showcases 20 income brackets ranging from $1 to $100,000+..
    • Full-Time Males: The count of males employed full-time year-round and earning within a specified income bracket
    • Part-Time Males: The count of males employed part-time and earning within a specified income bracket
    • Full-Time Females: The count of females employed full-time year-round and earning within a specified income bracket
    • Part-Time Females: The count of females employed part-time and earning within a specified income bracket

    Employment type classifications include:

    • Full-time, year-round: A full-time, year-round worker is a person who worked full time (35 or more hours per week) and 50 or more weeks during the previous calendar year.
    • Part-time: A part-time worker is a person who worked less than 35 hours per week during the previous calendar year.

    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 Rose City median household income by race. You can refer the same here

  10. a

    General Government - City Workforce Diversity - Gender - Non-Sworn AGOL

    • egishub-phoenix.hub.arcgis.com
    Updated Oct 3, 2023
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    City of Phoenix (2023). General Government - City Workforce Diversity - Gender - Non-Sworn AGOL [Dataset]. https://egishub-phoenix.hub.arcgis.com/datasets/general-government-city-workforce-diversity-gender-non-sworn-agol
    Explore at:
    Dataset updated
    Oct 3, 2023
    Dataset authored and provided by
    City of Phoenix
    Description

    A dashboard used by government agencies to monitor key performance indicators (KPIs) and communicate progress made on strategic outcomes with the general public and other interested stakeholders.

  11. p

    Trends in Diversity Score (2019-2023): The City vs. California vs. The City...

    • publicschoolreview.com
    Updated Apr 25, 2024
    + more versions
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    Public School Review (2024). Trends in Diversity Score (2019-2023): The City vs. California vs. The City School District [Dataset]. https://www.publicschoolreview.com/the-city-profile
    Explore at:
    Dataset updated
    Apr 25, 2024
    Dataset authored and provided by
    Public School Review
    License

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

    Description

    This dataset tracks annual diversity score from 2019 to 2023 for The City vs. California and The City School District

  12. p

    Trends in Diversity Score (2019-2023): Central City Value School District...

    • publicschoolreview.com
    + more versions
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    Public School Review, Trends in Diversity Score (2019-2023): Central City Value School District vs. California [Dataset]. https://www.publicschoolreview.com/california/central-city-value-school-district/602131-school-district
    Explore at:
    Dataset authored and provided by
    Public School Review
    License

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

    Area covered
    California
    Description

    This dataset tracks annual diversity score from 2019 to 2023 for Central City Value School District vs. California

  13. p

    Trends in Diversity Score (2002-2023): Johnston City High School vs....

    • publicschoolreview.com
    Updated Feb 9, 2025
    + more versions
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    Public School Review (2025). Trends in Diversity Score (2002-2023): Johnston City High School vs. Illinois vs. Johnston City Community Unit School District 1 [Dataset]. https://www.publicschoolreview.com/johnston-city-high-school-profile
    Explore at:
    Dataset updated
    Feb 9, 2025
    Dataset authored and provided by
    Public School Review
    License

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

    Area covered
    Johnston City, Johnston City Community Unit School District 1
    Description

    This dataset tracks annual diversity score from 2002 to 2023 for Johnston City High School vs. Illinois and Johnston City Community Unit School District 1

  14. p

    Trends in Diversity Score (1997-2023): Pearl City Jr High School vs....

    • publicschoolreview.com
    + more versions
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    Public School Review, Trends in Diversity Score (1997-2023): Pearl City Jr High School vs. Illinois vs. Pearl City Community Unit School District 200 [Dataset]. https://www.publicschoolreview.com/pearl-city-jr-high-school-profile
    Explore at:
    Dataset authored and provided by
    Public School Review
    License

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

    Area covered
    Illinois, Pearl City Community Unit School District 200
    Description

    This dataset tracks annual diversity score from 1997 to 2023 for Pearl City Jr High School vs. Illinois and Pearl City Community Unit School District 200

  15. p

    Trends in Diversity Score (2001-2021): Jewel City Community Day vs....

    • publicschoolreview.com
    Updated Nov 13, 2022
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    Public School Review (2022). Trends in Diversity Score (2001-2021): Jewel City Community Day vs. California vs. Glendale Unified School District [Dataset]. https://www.publicschoolreview.com/jewel-city-community-day-profile
    Explore at:
    Dataset updated
    Nov 13, 2022
    Dataset authored and provided by
    Public School Review
    License

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

    Area covered
    Glendale Unified School District
    Description

    This dataset tracks annual diversity score from 2001 to 2021 for Jewel City Community Day vs. California and Glendale Unified School District

  16. N

    Virginia City, MT annual income distribution by work experience and gender...

    • neilsberg.com
    csv, json
    Updated Feb 27, 2025
    + more versions
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    Neilsberg Research (2025). Virginia City, MT annual income distribution by work experience and gender dataset: Number of individuals ages 15+ with income, 2023 // 2025 Edition [Dataset]. https://www.neilsberg.com/insights/virginia-city-mt-income-by-gender/
    Explore at:
    csv, jsonAvailable download formats
    Dataset updated
    Feb 27, 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
    Virginia City, Montana
    Variables measured
    Income for Male Population, Income for Female Population, Income for Male Population working full time, Income for Male Population working part time, Income for Female Population working full time, Income for Female Population working part time, Number of males working full time for a given income bracket, Number of males working part time for a given income bracket, Number of females working full time for a given income bracket, Number of females working part time for a given income bracket
    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 portray the number of individuals for both the genders (Male and Female), within each income bracket we conducted an initial analysis and categorization of the American Community Survey data. Households are categorized, and median incomes are reported based on the self-identified gender of the head of the household. For additional information about these estimations, please contact us via email at research@neilsberg.com
    Dataset funded by
    Neilsberg Research
    Description
    About this dataset

    Context

    The dataset presents the detailed breakdown of the count of individuals within distinct income brackets, categorizing them by gender (men and women) and employment type - full-time (FT) and part-time (PT), offering valuable insights into the diverse income landscapes within Virginia City. The dataset can be utilized to gain insights into gender-based income distribution within the Virginia City population, aiding in data analysis and decision-making..

    Key observations

    • Employment patterns: Within Virginia City, among individuals aged 15 years and older with income, there were 75 men and 56 women in the workforce. Among them, 17 men were engaged in full-time, year-round employment, while 10 women were in full-time, year-round roles.
    • Annual income under $24,999: Of the male population working full-time, 29.41% fell within the income range of under $24,999, while none of the female population working full-time was represented in the same income bracket.
    • Annual income above $100,000: 11.76% of men in full-time roles earned incomes exceeding $100,000, while none of women in full-time positions earned within this income bracket.
    • Refer to the research insights for more key observations on more income brackets ( Annual income under $24,999, Annual income between $25,000 and $49,999, Annual income between $50,000 and $74,999, Annual income between $75,000 and $99,999 and Annual income above $100,000) and employment types (full-time year-round and part-time)
    Content

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

    Income brackets:

    • $1 to $2,499 or loss
    • $2,500 to $4,999
    • $5,000 to $7,499
    • $7,500 to $9,999
    • $10,000 to $12,499
    • $12,500 to $14,999
    • $15,000 to $17,499
    • $17,500 to $19,999
    • $20,000 to $22,499
    • $22,500 to $24,999
    • $25,000 to $29,999
    • $30,000 to $34,999
    • $35,000 to $39,999
    • $40,000 to $44,999
    • $45,000 to $49,999
    • $50,000 to $54,999
    • $55,000 to $64,999
    • $65,000 to $74,999
    • $75,000 to $99,999
    • $100,000 or more

    Variables / Data Columns

    • Income Bracket: This column showcases 20 income brackets ranging from $1 to $100,000+..
    • Full-Time Males: The count of males employed full-time year-round and earning within a specified income bracket
    • Part-Time Males: The count of males employed part-time and earning within a specified income bracket
    • Full-Time Females: The count of females employed full-time year-round and earning within a specified income bracket
    • Part-Time Females: The count of females employed part-time and earning within a specified income bracket

    Employment type classifications include:

    • Full-time, year-round: A full-time, year-round worker is a person who worked full time (35 or more hours per week) and 50 or more weeks during the previous calendar year.
    • Part-time: A part-time worker is a person who worked less than 35 hours per week during the previous calendar year.

    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 Virginia City median household income by race. You can refer the same here

  17. p

    Trends in Diversity Score (2022-2023): Magic City Acceptance Academy vs....

    • publicschoolreview.com
    Updated Feb 9, 2025
    + more versions
    Share
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    Public School Review (2025). Trends in Diversity Score (2022-2023): Magic City Acceptance Academy vs. Alabama vs. Magic City Acceptance Academy School District [Dataset]. https://www.publicschoolreview.com/magic-city-acceptance-academy-profile
    Explore at:
    Dataset updated
    Feb 9, 2025
    Dataset authored and provided by
    Public School Review
    License

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

    Description

    This dataset tracks annual diversity score from 2022 to 2023 for Magic City Acceptance Academy vs. Alabama and Magic City Acceptance Academy School District

  18. p

    Trends in Diversity Score (2006-2023): Albert City-truesdale Elementary...

    • publicschoolreview.com
    + more versions
    Share
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    Public School Review, Trends in Diversity Score (2006-2023): Albert City-truesdale Elementary School vs. Iowa vs. Albert City-Truesdale Community School District [Dataset]. https://www.publicschoolreview.com/albert-city-truesdale-elementary-school-profile
    Explore at:
    Dataset authored and provided by
    Public School Review
    License

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

    Area covered
    Albert City
    Description

    This dataset tracks annual diversity score from 2006 to 2023 for Albert City-truesdale Elementary School vs. Iowa and Albert City-Truesdale Community School District

  19. p

    Trends in Diversity Score (2001-2023): Tulare City Community Day vs....

    • publicschoolreview.com
    Updated Oct 26, 2025
    Share
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    Public School Review (2025). Trends in Diversity Score (2001-2023): Tulare City Community Day vs. California vs. Tulare City School District [Dataset]. https://www.publicschoolreview.com/tulare-city-community-day-profile
    Explore at:
    Dataset updated
    Oct 26, 2025
    Dataset authored and provided by
    Public School Review
    License

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

    Area covered
    Tulare
    Description

    This dataset tracks annual diversity score from 2001 to 2023 for Tulare City Community Day vs. California and Tulare City School District

  20. N

    Plain City, UT annual income distribution by work experience and gender...

    • neilsberg.com
    csv, json
    Updated Feb 27, 2025
    + more versions
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
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    Close
    Cite
    Neilsberg Research (2025). Plain City, UT annual income distribution by work experience and gender dataset: Number of individuals ages 15+ with income, 2023 // 2025 Edition [Dataset]. https://www.neilsberg.com/research/datasets/babf375c-f4ce-11ef-8577-3860777c1fe6/
    Explore at:
    csv, jsonAvailable download formats
    Dataset updated
    Feb 27, 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
    Plain City, Utah
    Variables measured
    Income for Male Population, Income for Female Population, Income for Male Population working full time, Income for Male Population working part time, Income for Female Population working full time, Income for Female Population working part time, Number of males working full time for a given income bracket, Number of males working part time for a given income bracket, Number of females working full time for a given income bracket, Number of females working part time for a given income bracket
    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 portray the number of individuals for both the genders (Male and Female), within each income bracket we conducted an initial analysis and categorization of the American Community Survey data. Households are categorized, and median incomes are reported based on the self-identified gender of the head of the household. For additional information about these estimations, please contact us via email at research@neilsberg.com
    Dataset funded by
    Neilsberg Research
    Description
    About this dataset

    Context

    The dataset presents the detailed breakdown of the count of individuals within distinct income brackets, categorizing them by gender (men and women) and employment type - full-time (FT) and part-time (PT), offering valuable insights into the diverse income landscapes within Plain City. The dataset can be utilized to gain insights into gender-based income distribution within the Plain City population, aiding in data analysis and decision-making..

    Key observations

    • Employment patterns: Within Plain City, among individuals aged 15 years and older with income, there were 2,568 men and 2,396 women in the workforce. Among them, 1,684 men were engaged in full-time, year-round employment, while 878 women were in full-time, year-round roles.
    • Annual income under $24,999: Of the male population working full-time, 4.04% fell within the income range of under $24,999, while 5.13% of the female population working full-time was represented in the same income bracket.
    • Annual income above $100,000: 49.17% of men in full-time roles earned incomes exceeding $100,000, while 19.82% of women in full-time positions earned within this income bracket.
    • Refer to the research insights for more key observations on more income brackets ( Annual income under $24,999, Annual income between $25,000 and $49,999, Annual income between $50,000 and $74,999, Annual income between $75,000 and $99,999 and Annual income above $100,000) and employment types (full-time year-round and part-time)
    Content

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

    Income brackets:

    • $1 to $2,499 or loss
    • $2,500 to $4,999
    • $5,000 to $7,499
    • $7,500 to $9,999
    • $10,000 to $12,499
    • $12,500 to $14,999
    • $15,000 to $17,499
    • $17,500 to $19,999
    • $20,000 to $22,499
    • $22,500 to $24,999
    • $25,000 to $29,999
    • $30,000 to $34,999
    • $35,000 to $39,999
    • $40,000 to $44,999
    • $45,000 to $49,999
    • $50,000 to $54,999
    • $55,000 to $64,999
    • $65,000 to $74,999
    • $75,000 to $99,999
    • $100,000 or more

    Variables / Data Columns

    • Income Bracket: This column showcases 20 income brackets ranging from $1 to $100,000+..
    • Full-Time Males: The count of males employed full-time year-round and earning within a specified income bracket
    • Part-Time Males: The count of males employed part-time and earning within a specified income bracket
    • Full-Time Females: The count of females employed full-time year-round and earning within a specified income bracket
    • Part-Time Females: The count of females employed part-time and earning within a specified income bracket

    Employment type classifications include:

    • Full-time, year-round: A full-time, year-round worker is a person who worked full time (35 or more hours per week) and 50 or more weeks during the previous calendar year.
    • Part-time: A part-time worker is a person who worked less than 35 hours per week during the previous calendar year.

    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 Plain City median household income by race. You can refer the same here

Share
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TwitterTwitter
Email
Click to copy link
Link copied
Close
Cite
Baltimore Neighborhood Indicators Alliance (2020). Racial Diversity Index - City [Dataset]. https://vital-signs-bniajfi.hub.arcgis.com/datasets/racial-diversity-index-city

Racial Diversity Index - City

Explore at:
Dataset updated
Feb 27, 2020
Dataset authored and provided by
Baltimore Neighborhood Indicators Alliance
Area covered
Description

The percent chance that two people picked at random within an area will be of a different race/ethnicity. This number does not reflect which race/ethnicity is predominant within an area. The higher the value, the more racially and ethnically diverse an area. Source: U.S. Bureau of the Census, American Community Survey Years Available: 2010, 2011-2015, 2012-2016, 2013-2017, 2014-2018, 2015-2019, 2017-2021, 2018-2022, 2019-2023

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