5 datasets found
  1. Residential Patterns in South Florida

    • redivis.com
    application/jsonl +7
    Updated Mar 20, 2023
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    Carnegie Mellon University Libraries (2023). Residential Patterns in South Florida [Dataset]. https://redivis.com/datasets/78y1-bnxtd190k
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    application/jsonl, stata, spss, csv, sas, avro, parquet, arrowAvailable download formats
    Dataset updated
    Mar 20, 2023
    Dataset provided by
    Redivis Inc.
    Authors
    Carnegie Mellon University Libraries
    Time period covered
    Jan 1, 2016 - Dec 1, 2016
    Area covered
    South Florida, Florida
    Description

    Abstract

    This dataset was curated for the digital humanities portion of the project "500 Years of Black History in South Florida" by Synatra Smith, Luling Huang, and Portia Hopkins.

    Methodology

    Data was curated at the U.S. Census Tract level for four counties in South Florida: Broward, Miami-Dade, Monroe, and Palm Beach.

    There are two tables in this dataset:

    • sociodem_enepov: This table contains several sociodemographic variables and energy burden level at the census tract level;
    • airqua: This table contains monthly median air quality data at the census tract level for Year 2016.

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    The sociodemographic data come from the American Community Survey (2020 5-year estimates). The variables include fraction of black population, median income, unemployment rate, and four education level variables for population 25 years or above: fraction of population below high school, fraction of population who had high school diploma only, fraction of population who had a college degree or equivalent only, and fraction of population who had a graduate degree. Here are the table numbers and relevant columns from the U.S. Census data portal:

    • Education: S1501
    • Black population: B01001B (column: B01001B_001E)
    • Total population: B01001 (for calculating fraction of black population)
    • Median income: S1903 (column: S1903_C03_001E)
    • Employment: S2301 (column: S2301_C04_001E)

    %3C!-- --%3E

    The energy burden data come from the U.S. Department of Energy's Low-Income Energy Affordability Data (LEAD) tool. The air quality (PM2.5 concentration) data come from the U.S. Centers for Disease Control and Prevention's Daily Census Tract-Level PM2.5 Concentrations, 2016.

    This project is conducted on behalf of the Association for the Study of African American Life and History and the National Park Service with additional funding from the Council on Library and Information Resources.

    References

    • Centers for Disease Control and Prevention. (n.d.). National Environmental Public Health Tracking Network [Data set]. www.cdc.gov/ephtracking

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    • U.S. Census Bureau. (2023). United States Census Bureau: Data [Data set]. U.S. Department of Commerce. https://data.census.gov/

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    Usage

    This dataset curates from data existing in the public domain and can be used for other purposes freely with attribution.

  2. U.S. median household income 2023, by education of householder

    • statista.com
    Updated Sep 17, 2024
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    Statista (2024). U.S. median household income 2023, by education of householder [Dataset]. https://www.statista.com/statistics/233301/median-household-income-in-the-united-states-by-education/
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    Dataset updated
    Sep 17, 2024
    Dataset authored and provided by
    Statistahttp://statista.com/
    Time period covered
    2023
    Area covered
    United States
    Description

    U.S. citizens with a professional degree had the highest median household income in 2023, at 172,100 U.S. dollars. In comparison, those with less than a 9th grade education made significantly less money, at 35,690 U.S. dollars. Household income The median household income in the United States has fluctuated since 1990, but rose to around 70,000 U.S. dollars in 2021. Maryland had the highest median household income in the United States in 2021. Maryland’s high levels of wealth is due to several reasons, and includes the state's proximity to the nation's capital. Household income and ethnicity The median income of white non-Hispanic households in the United States had been on the rise since 1990, but declining since 2019. While income has also been on the rise, the median income of Hispanic households was much lower than those of white, non-Hispanic private households. However, the median income of Black households is even lower than Hispanic households. Income inequality is a problem without an easy solution in the United States, especially since ethnicity is a contributing factor. Systemic racism contributes to the non-White population suffering from income inequality, which causes the opportunity for growth to stagnate.

  3. c

    Demographics

    • s.cnmilf.com
    • datasets.ai
    • +4more
    Updated Nov 22, 2024
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    Lake County Illinois GIS (2024). Demographics [Dataset]. https://s.cnmilf.com/user74170196/https/catalog.data.gov/dataset/demographics-0be32
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    Dataset updated
    Nov 22, 2024
    Dataset provided by
    Lake County Illinois GIS
    Description

    Lake County, Illinois Demographic Data. Explanation of field attributes: Total Population – The entire population of Lake County. White – Individuals who are of Caucasian race. This is a percent.African American – Individuals who are of African American race. This is a percent.Asian – Individuals who are of Asian race. This is a percent. Hispanic – Individuals who are of Hispanic ethnicity. This is a percent. Does not Speak English- Individuals who speak a language other than English in their household. This is a percent. Under 5 years of age – Individuals who are under 5 years of age. This is a percent. Under 18 years of age – Individuals who are under 18 years of age. This is a percent. 18-64 years of age – Individuals who are between 18 and 64 years of age. This is a percent. 65 years of age and older – Individuals who are 65 years old or older. This is a percent. Male – Individuals who are male in gender. This is a percent. Female – Individuals who are female in gender. This is a percent. High School Degree – Individuals who have obtained a high school degree. This is a percent. Associate Degree – Individuals who have obtained an associate degree. This is a percent. Bachelor’s Degree or Higher – Individuals who have obtained a bachelor’s degree or higher. This is a percent. Utilizes Food Stamps – Households receiving food stamps/ part of SNAP (Supplemental Nutrition Assistance Program). This is a percent. Median Household Income - A median household income refers to the income level earned by a given household where half of the homes in the area earn more and half earn less. This is a dollar amount. No High School – Individuals who have not obtained a high school degree. This is a percent. Poverty – Poverty refers to families and people whose income in the past 12 months is below the poverty level. This is a percent.

  4. a

    US Department of Education College Scorecard 2015-2016

    • livingatlas-dcdev.opendata.arcgis.com
    Updated Aug 8, 2018
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    ArcGIS StoryMaps (2018). US Department of Education College Scorecard 2015-2016 [Dataset]. https://livingatlas-dcdev.opendata.arcgis.com/datasets/Story::us-department-of-education-college-scorecard-2015-2016/api
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    Dataset updated
    Aug 8, 2018
    Dataset authored and provided by
    ArcGIS StoryMaps
    Area covered
    Description

    This dataset consists of a selection of variables extracted from the U.S. Department of Education's College Scorecard 2015/2016. For the original, raw data visit the College Scorecard webpage. This dataset includes variables about institution types, proportion of degree types awarded, student enrollments and demographics, and a number of price and revenue variables. For 2005-2006 data, see here.Note: Data is not uniformly available for all schools on all variables. Variables for which there is no data (NULL), or where data is suppressed for reasons of privacy, are indicated by 999999999.

    ATTRIBUTE DESCRIPTION EXAMPLE

    ID2 1

    UNITIDUnit ID for institution 100654

    OPEID 8-digit OPE ID for institution 100200

    OPEID6 6-digit OPE ID for institution 1002

    State FIPS

    1

    State

    AL

    Zip

    35762

    City

    Normal

    Institution Name

    Alabama A & M University

    Institution Type 1 Public 2 Private nonprofit 3 Private for-profit 1

    Institution Level 1 4-year 2 2-year 3 Less-than-2-year 1

    In Operation 1 true 0 false 1

    Main Campus 1 true 0 false 1

    Branches Count of the number of branches 1

    Popular Degree 1 Predominantly certificate-degree granting 2 Predominantly associate's-degree granting 3 Predominantly bachelor's-degree granting 4 Entirely graduate-degree granting 3

    Highest Degree 0 Non-degree-granting 1 Certificate degree 2 Associate degree 3 Bachelor's degree 4 Graduate degree 4

    PCIP01 Percentage of degrees awarded in Agriculture, Agriculture Operations, And Related Sciences. 0.0446

    PCIP03 Percentage of degrees awarded in Natural Resources And Conservation. 0.0023

    PCIP04 Percentage of degrees awarded in Architecture And Related Services. 0.0094

    PCIP05 Percentage of degrees awarded in Area, Ethnic, Cultural, Gender, And Group Studies. 0

    PCIP09 Percentage of degrees awarded in Communication, Journalism, And Related Programs. 0

    PCIP10 Percentage of degrees awarded in Communications Technologies/Technicians And Support Services. 0.0164

    PCIP11 Percentage of degrees awarded in Computer And Information Sciences And Support Services. 0.0634

    PCIP12 Percentage of degrees awarded in Personal And Culinary Services. 0

    PCIP13 Percentage of degrees awarded in Education. 0.1268

    PCIP14 Percentage of degrees awarded in Engineering. 0.1432

    PCIP15 Percentage of degrees awarded in Engineering Technologies And Engineering-Related Fields. 0.0587

    PCIP16 Percentage of degrees awarded in Foreign Languages, Literatures, And Linguistics. 0

    PCIP19 Percentage of degrees awarded in Family And Consumer Sciences/Human Sciences. 0.0188

    PCIP22 Percentage of degrees awarded in Legal Professions And Studies. 0

    PCIP23 Percentage of degrees awarded in English Language And Literature/Letters. 0.0235

    PCIP24 Percentage of degrees awarded in Liberal Arts And Sciences, General Studies And Humanities. 0.0423

    PCIP25 Percentage of degrees awarded in Library Science. 0

    PCIP26 Percentage of degrees awarded in Biological And Biomedical Sciences. 0.1009

    PCIP27 Percentage of degrees awarded in Mathematics And Statistics. 0.0094

    PCIP29 Percentage of degrees awarded in Military Technologies And Applied Sciences. 0

    PCIP30 Percentage of degrees awarded in Multi/Interdisciplinary Studies. 0

    PCIP31 Percentage of degrees awarded in Parks, Recreation, Leisure, And Fitness Studies. 0

    PCIP38 Percentage of degrees awarded in Philosophy And Religious Studies. 0

    PCIP39 Percentage of degrees awarded in Theology And Religious Vocations. 0

    PCIP40 Percentage of degrees awarded in Physical Sciences. 0.0188

    PCIP41 Percentage of degrees awarded in Science Technologies/Technicians. 0

    PCIP42 Percentage of degrees awarded in Psychology. 0.0282

    PCIP43 Percentage of degrees awarded in Homeland Security, Law Enforcement, Firefighting And Related Protective Services. 0.0282

    PCIP44 Percentage of degrees awarded in Public Administration And Social Service Professions. 0.0516

    PCIP45 Percentage of degrees awarded in Social Sciences. 0.0399

    PCIP46 Percentage of degrees awarded in Construction Trades. 0

    PCIP47 Percentage of degrees awarded in Mechanic And Repair Technologies/Technicians. 0

    PCIP48 Percentage of degrees awarded in Precision Production. 0

    PCIP49 Percentage of degrees awarded in Transportation And Materials Moving. 0

    PCIP50 Percentage of degrees awarded in Visual And Performing Arts. 0.0258

    PCIP51 Percentage of degrees awarded in Health Professions And Related Programs. 0

    PCIP52 Percentage of degrees awarded in Business, Management, Marketing, And Related Support Services. 0.1479

    PCIP54 Percentage of degrees awarded in History. 0

    Admission Rate

    0.6538

    Average RetentionRate of retention averaged between full-time and part-time students. 0.4428

    Retention, Full-Time Students

    0.5779

    Retention, Part-Time Students

    0.3077

    Completion Rate

    0.1104

    Enrollment Number of enrolled students 4505

    Male Students Percentage of the student body that is male. 0.4617

    Female Students Percentage of the student body that is female. 0.5383

    White Percentage of the student body that identifies as white. 0.034

    Black Percentage of the student body that identifies as African American. 0.9216

    Hispanic Percentage of the student body that identifies as Hispanic or Latino. 0.0058

    Asian Percentage of the student body that identifies as Asian. 0.0018

    American Indian and Alaskan Native Percentage of the student body that identifies as American Indian or Alaskan Native. 0.0022

    Native Hawaiian and Pacific Islander Percentage of the student body that identifies as Native Hawaiian or Pacific islander. 0.0018

    Two or More Races Percentage of the student body that identifies as two or more races. 0

    Non-Resident Aliens Percentage of the student body that are non-resident aliens. 0.0062

    Race Unknown Percentage of the student body for whom racial identity is unknown. 0.0266

    Percent Parents no HS Diploma Percentage of parents of students whose highest level of education is less than high school. 0.019298937

    Percent Parents HS Diploma Percentage of parents of students whose highest level of education is high school 0.369436786

    Percent Parents Post-Secondary Ed. Percentage of parents of students whose highest level of education is college or above. 0.611264277

    Title IV Students Percentage of student body identified as Title IV 743

    HCM2 Cash Monitoring Schools identified by the Department of Ed for Higher Cash Monitoring Level 2 0

    Net Price

    13435

    Cost of Attendance

    20809

    In-State Tuition and Fees

    9366

    Out-of-State Tuition and Fees

    17136

    Tuition and Fees (Program) Tuition and fees for program-year schools NULL

    Tution Revenue per Full-Time Student

    9657

    Expenditures per Full-Time Student

    7941

    Average Faculty Salary

    7017

    Percent of Students with Federal Loan

    0.8159

    Share of Students with Federal Loan

    0.896382157

    Share of Students with Pell Grant

    0.860906217

    Median Loan Principal Amount upon Entering Repayment

    14600

    Median Debt for Completed Students Median debt for student who completed a course of study 35000

    Median Debt for Incompleted Students Median debt for student who did not complete a course of study 9500

    Median Debt for Family Income $0K-$30K Median debt for students of families with less thank $30,000 income 14457

    Median Debt for Family Income $30K-$75K Median debt for students of families with $30,000-$75,000 income 15000

    Median Debt for Family Income over $75K Median debt for students of families with over $75,000 income 14250

    Median Debt Female Students

    16000

    Median Debt Male Students

    13750

    Median Debt 1st Gen. Students Median debt for first generation college student 14307.5

    Median Debt Not 1st Gen. Students Median debt for not first generation college students 14953

    Cumulative Loan Debt Greater than 90% of Students (90th Percentile)

    48750

    Cumulative Loan Debt Greater than 75% of Students (75th Percentile)

    32704

    Cumulative Loan Debt Greater than 25% of Students (25th Percentile)

    5500

    Cumulative Loan Debt Greater than 10% of Students (10th Percentile)

    3935.5

    Accrediting Agency

    Southern Association of Colleges and Schools Commission on Colleges

    Website

    www.aamu.edu/

    Price Calculator

    www2.aamu.edu/scripts/netpricecalc/npcalc.htm

    Latitude

    34.783368

    Longitude

    -86.568502

  5. Divergent trends in life expectancy across the rural-urban gradient and...

    • catalog.data.gov
    Updated Nov 12, 2020
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    U.S. EPA Office of Research and Development (ORD) (2020). Divergent trends in life expectancy across the rural-urban gradient and association with specific racial proportions in the contiguous United States 2000-2005 [Dataset]. https://catalog.data.gov/dataset/divergent-trends-in-life-expectancy-across-the-rural-urban-gradient-and-association-w-2000
    Explore at:
    Dataset updated
    Nov 12, 2020
    Dataset provided by
    United States Environmental Protection Agencyhttp://www.epa.gov/
    Area covered
    Contiguous United States, United States
    Description

    We used individual-level death data to estimate county-level life expectancy at 25 (e25) for Whites, Black, AIAN and Asian in the contiguous US for 2000-2005. Race-sex-stratified models were used to examine the associations among e25, rurality and specific race proportion, adjusted for socioeconomic variables. Individual death data from the National Center for Health Statistics were aggregated as death counts into five-year age groups by county and race-sex groups for the contiguous US for years 2000-2005 (National Center for Health Statistics 2000-2005). We used bridged-race population estimates to calculate five-year mortality rates. The bridged population data mapped 31 race categories, as specified in the 1997 Office of Management and Budget standards for the collection of data on race and ethnicity, to the four race categories specified under the 1977 standards (the same as race categories in mortality registration) (Ingram et al. 2003). The urban-rural gradient was represented by the 2003 Rural Urban Continuum Codes (RUCC), which distinguished metropolitan counties by population size, and nonmetropolitan counties by degree of urbanization and adjacency to a metro area (United States Department of Agriculture 2016). We obtained county-level sociodemographic data for 2000-2005 from the US Census Bureau. These included median household income, percent of population attaining greater than high school education (high school%), and percent of county occupied rental units (rent%). We obtained county violent crime from Uniform Crime Reports and used it to calculate mean number of violent crimes per capita (Federal Bureau of Investigation 2010). This dataset is not publicly accessible because: EPA cannot release personally identifiable information regarding living individuals, according to the Privacy Act and the Freedom of Information Act (FOIA). This dataset contains information about human research subjects. Because there is potential to identify individual participants and disclose personal information, either alone or in combination with other datasets, individual level data are not appropriate to post for public access. Restricted access may be granted to authorized persons by contacting the party listed. It can be accessed through the following means: Request to author. Format: Data are stored as csv files. This dataset is associated with the following publication: Jian, Y., L. Neas, L. Messer, C. Gray, J. Jagai, K. Rappazzo, and D. Lobdell. Divergent trends in life expectancy across the rural-urban gradient among races in the contiguous United States. International Journal of Public Health. Springer Basel AG, Basel, SWITZERLAND, 64(9): 1367-1374, (2019).

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Carnegie Mellon University Libraries (2023). Residential Patterns in South Florida [Dataset]. https://redivis.com/datasets/78y1-bnxtd190k
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Residential Patterns in South Florida

Explore at:
application/jsonl, stata, spss, csv, sas, avro, parquet, arrowAvailable download formats
Dataset updated
Mar 20, 2023
Dataset provided by
Redivis Inc.
Authors
Carnegie Mellon University Libraries
Time period covered
Jan 1, 2016 - Dec 1, 2016
Area covered
South Florida, Florida
Description

Abstract

This dataset was curated for the digital humanities portion of the project "500 Years of Black History in South Florida" by Synatra Smith, Luling Huang, and Portia Hopkins.

Methodology

Data was curated at the U.S. Census Tract level for four counties in South Florida: Broward, Miami-Dade, Monroe, and Palm Beach.

There are two tables in this dataset:

  • sociodem_enepov: This table contains several sociodemographic variables and energy burden level at the census tract level;
  • airqua: This table contains monthly median air quality data at the census tract level for Year 2016.

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The sociodemographic data come from the American Community Survey (2020 5-year estimates). The variables include fraction of black population, median income, unemployment rate, and four education level variables for population 25 years or above: fraction of population below high school, fraction of population who had high school diploma only, fraction of population who had a college degree or equivalent only, and fraction of population who had a graduate degree. Here are the table numbers and relevant columns from the U.S. Census data portal:

  • Education: S1501
  • Black population: B01001B (column: B01001B_001E)
  • Total population: B01001 (for calculating fraction of black population)
  • Median income: S1903 (column: S1903_C03_001E)
  • Employment: S2301 (column: S2301_C04_001E)

%3C!-- --%3E

The energy burden data come from the U.S. Department of Energy's Low-Income Energy Affordability Data (LEAD) tool. The air quality (PM2.5 concentration) data come from the U.S. Centers for Disease Control and Prevention's Daily Census Tract-Level PM2.5 Concentrations, 2016.

This project is conducted on behalf of the Association for the Study of African American Life and History and the National Park Service with additional funding from the Council on Library and Information Resources.

References

  • Centers for Disease Control and Prevention. (n.d.). National Environmental Public Health Tracking Network [Data set]. www.cdc.gov/ephtracking

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  • U.S. Census Bureau. (2023). United States Census Bureau: Data [Data set]. U.S. Department of Commerce. https://data.census.gov/

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Usage

This dataset curates from data existing in the public domain and can be used for other purposes freely with attribution.

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