In 2021, about 37.7 percent of the U.S. population who were aged 25 and above had graduated from college or another higher education institution, a slight decline from 37.9 the previous year. However, this is a significant increase from 1960, when only 7.7 percent of the U.S. population had graduated from college.

Demographics

Educational attainment varies by gender, location, race, and age throughout the United States. Asian-American and Pacific Islanders had the highest level of education, on average, while Massachusetts and the District of Colombia are areas home to the highest rates of residents with a bachelor’s degree or higher. However, education levels are correlated with wealth. While public education is free up until the 12th grade, the cost of university is out of reach for many Americans, making social mobility increasingly difficult.

Earnings

White Americans with a professional degree earned the most money on average, compared to other educational levels and races. However, regardless of educational attainment, males typically earned far more on average compared to females. Despite the decreasing wage gap over the years in the country, it remains an issue to this day. Not only is there a large wage gap between males and females, but there is also a large income gap linked to race as well.

Analysis of ‘International Educational Attainment by Year & Age’ provided by Analyst-2 (analyst-2.ai), based on source dataset retrieved from https://www.kaggle.com/yamqwe/international-comp-attainmente on 13 February 2022.

--- Dataset description provided by original source is as follows ---

About this dataset

The National Center for Education Statistics (NCES) is the primary federal entity for collecting and analyzing data related to education in the U.S. and other nations. NCES is located within the U.S. Department of Education and the Institute of Education Sciences. NCES fulfills a Congressional mandate to collect, collate, analyze, and report complete statistics on the condition of American education; conduct and publish reports; and review and report on education activities internationally.

• Table 603.10. Percentage of the population 25 to 64 years old who completed high school, by age group and country: Selected years, 2001 through 2012
• Table 603.20. Percentage of the population 25 to 64 years old who attained selected levels of postsecondary education, by age group and country: 2001 and 2012
• Table 603.30. Percentage of the population 25 to 64 years old who attained a bachelor's or higher degree, by age group and country: Selected years, 1999 through 2012
• Table 603.40 Percentage of the population 25 to 64 years old who attained a postsecondary vocational degree, by age group and country: Selected years, 1999 through 2012
• Table 603.50 Number of bachelor's degree recipients per 100 persons at the typical minimum age of graduation, by sex and country: Selected years, 2005 through 2012
• Table 603.60. Percentage of postsecondary degrees awarded to women, by field of study and country: 2013
• Table 603.70. Percentage of bachelor's or equivalent degrees awarded in mathematics, science, and engineering, by field of study and country: 2013
• Table 603.80. Percentage of master's or equivalent degrees and of doctoral or equivalent degrees awarded in mathematics, science, and engineering, by field of study and country: 2013
• Table 603.90. Employment to population ratios of -25 to 64-year-olds, by sex, highest level of educational attainment, and country: 2014

Source: https://nces.ed.gov/programs/digest/current_tables.asp

This dataset was created by National Center for Education Statistics and contains around 100 samples along with Unnamed: 20, Unnamed: 24, technical information and other features such as: - Unnamed: 11 - Unnamed: 16 - and more.

How to use this dataset

• Analyze Unnamed: 15 in relation to Unnamed: 6
• Study the influence of Unnamed: 1 on Unnamed: 10
• More datasets

Acknowledgements

If you use this dataset in your research, please credit National Center for Education Statistics

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--- Original source retains full ownership of the source dataset ---

United States US: Educational Attainment: At Least Master's or Equivalent: Population 25+ Years: Total: % Cumulative data was reported at 11.995 % in 2015. This records an increase from the previous number of 11.765 % for 2014. United States US: Educational Attainment: At Least Master's or Equivalent: Population 25+ Years: Total: % Cumulative data is updated yearly, averaging 11.765 % from Dec 2013 (Median) to 2015, with 3 observations. The data reached an all-time high of 11.995 % in 2015 and a record low of 11.566 % in 2013. United States US: Educational Attainment: At Least Master's or Equivalent: Population 25+ Years: Total: % Cumulative data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s USA – Table US.World Bank: Education Statistics. The percentage of population ages 25 and over that attained or completed Master's or equivalent.; ; UNESCO Institute for Statistics; ;

Graph and download economic data for Bachelor's Degree or Higher (5-year estimate) in New York County, NY (HC01ESTVC1736061) from 2010 to 2023 about New York County, NY; New York; tertiary schooling; educational attainment; NY; education; 5-year; and USA.

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.

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.

Dataset contains information on Tempeans receiving post-secondary education, licenses, certificates. Data supports City's Achieve65Tempe goal that 65 percent of Tempe’s adult population access post-secondary education, resulting in a certification to an advanced degree by 2030.This page provides data for the Post-Secondary School Achievement Rate performance measure. Information on Tempe resident post-secondary attainment including 2-year degrees, 4-year degrees, and graduate degrees. Data supports City's Achieve65 Tempe goal that 65 percent of Tempe’s adult population access post-secondary education, resulting in a certification to an advanced degree by 2030. Data shows breakdown of post-secondary attainment by degree, by gender, for individuals 25 years and older.The performance measure dashboard is available at 3.09 Post-Secondary Achievement Rate.Additional InformationSource: US Census 1-year ACSContact: Marie RaymondContact E-Mail: Marie_Raymond@tempe.govData Source Type: ExcelPreparation Method: Numbers retrieved from US Census and entered into a detailed spreadsheet.Publish Frequency: AnnuallyPublish Method: ManualData Dictionary

Table contains count and percent of county residents ages 25 years and older with less than bachelors' education attainment. The measure is summarized at county, city, zip code and census tract. Data are presented for zip codes (ZCTAs) fully within the county. Source: U.S. Census Bureau, 2016-2020 American Community Survey 5-year estimates, Table B15002; data accessed on May 17, 2022 from https://api.census.gov. The 2020 Decennial geographies are used for data summarization.METADATA:notes (String): Lists table title, notes, sourcesgeolevel (String): Level of geographyGEOID (Numeric): Geography IDNAME (String): Name of geographypop (Numeric): Population ages 25 and olderpct_lt_bach (Numeric): Number of people ages 25 and older with less than bachelors' educationlt_bachelor (Numeric): Percent of people ages 25 and older with less than bachelors' education

United States US: Labour Force With Advanced Education: Female: % of Female Working-age Population data was reported at 77.809 % in 2017. This records a decrease from the previous number of 78.336 % for 2016. United States US: Labour Force With Advanced Education: Female: % of Female Working-age Population data is updated yearly, averaging 82.936 % from Dec 1994 (Median) to 2017, with 24 observations. The data reached an all-time high of 86.467 % in 1994 and a record low of 77.809 % in 2017. United States US: Labour Force With Advanced Education: Female: % of Female Working-age Population data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s USA – Table US.World Bank: Labour Force. The percentage of the working age population with an advanced level of education who are in the labor force. Advanced education comprises short-cycle tertiary education, a bachelor’s degree or equivalent education level, a master’s degree or equivalent education level, or doctoral degree or equivalent education level according to the International Standard Classification of Education 2011 (ISCED 2011).; ; International Labour Organization, ILOSTAT database. Data retrieved in September 2018.; Weighted average;

Approximately 43 million people (about 14 percent of the U.S. population) rely on domestic wells as their source of drinking water. Unlike community water systems, which are regulated by the Safe Drinking Water Act, there is no comprehensive national program to ensure that the water is tested to ensure that is it safe to drink. A study published in 2009 from the National Water-Quality Assessment Program of the U.S. Geological Survey that assessed water-quality conditions from 2,100 domestic wells within 48 states reported that more than one in five (23 percent) of the sampled wells contained one or more contaminants at a concentration greater than a human-health benchmark. In addition, there are many activities, e.g., resource extraction, climate change-induced drought, and changes in land use patterns that could potentially affect the quality of the ground water source for domestic wells. The Health Studies Branch (HSB) of the National Center for Environmental Health, Centers for Disease Control and Prevention, created a Clean Water for Health Program to help address domestic well concerns. The goals of this program are to identify emerging public health issues associated with using domestic wells for drinking water and begin to develop a plan to address these issues. As part of this effort, HSB in cooperation with the U.S. Geological Survey has created models to estimate the probability of arsenic occurring at various concentrations in domestic wells in the U.S. Similar work has been done by public health professionals on a state and regional basis. We will present preliminary results of the project, including estimates of the domestic well population that is likely to have arsenic greater than 10 micrograms per liter. Nationwide, we estimate this to be just over 2 million people. Logistic regression model results showing probabilities of arsenic greater than 10 micrograms per liter in domestic wells in the U.S., based on data for arsenic concentrations in domestic wells across the U.S. will be described, as well as the use of data on domestic well use by county in the U.S., to estimate the affected population.

This table contains data on the percent of the population in the labor force who are unemployed (unemployment rate), for California, its regions, counties, county divisions, cities/towns, and census tracts. Data is from the Local Area Unemployment Statistics (LAUS), Bureau of Labor Statistics (BLS), and the U.S. Census Bureau, American Community Survey (ACS). The table is part of a series of indicators in the Healthy Communities Data and Indicators Project of the Office of Health Equity. Unemployment is associated with higher rates of self-reported poor health, long-term illnesses, higher incidence of risky health behaviors (alcoholism, smoking), and increased mortality. Various explanations have been proposed for the link between poor health and unemployment; for example, economic deprivation that results in reduced access to essential goods and services. Another explanation is that unemployment causes the loss of latent functions (social contact, social status, time structure and personal identity) which can result in stigma, isolation and loss of self-worth. More information about the data table and a data dictionary can be found in the About/Attachments section.

This layer was developed by the Research & Analytics Group of the Atlanta Regional Commission, using data from the U.S. Census Bureau’s American Community Survey 5-year estimates for 2011-2015, to show various demographic data by zip code in the Atlanta region (including the following categories: total population, age, race/ethnicity, household composition, grandparents, school enrollment, educational attainment, veteran status, disability, foreign born status, linguistic isolation, unemployment, commuting mode, occupation, income, health insurance, poverty, housing characteristics, vehicle availability, housing values, and housing affordability).The user should note that American Community Survey data represent estimates derived from a surveyed sample of the population, which creates some level of uncertainty, as opposed to an exact measure of the entire population (the full census count is only conducted once every 10 years and does not cover as many detailed characteristics of the population). Therefore, any measure reported by ACS should not be taken as an exact number. The Census Bureau also calculates a corresponding margin of error (MOE) for ACS measures (although margins of error are not included in this dataset).The user should also note that for relatively small geographic areas, such as census tracts shown here, ACS only releases combined 5-year estimates, meaning these estimates represent rolling averages of survey results that were collected over a 5-year span (in this case 2011-2015). Therefore, these data do not represent any one specific point in time or even one specific year. For geographic areas with larger populations, 3-year and 1-year estimates are also available.For further explanation of ACS estimates and margin of error, refer to Census Bureau documentation.- - - - - -Base Attributes:ZIP = Zip code (text)ZIP_dbl = Zip code (numeric)Total_Population_2010= Total Population, 2010 CensusTotal_Population_2011_2015_ACS= Total Population, 2011-2015 American Community Survey (ACS)- - - - - -Attributes from ACS:Workers_16_years_and_over= Number, Workers, 16 years and overCar_Truck_or_Van_drove_alone= Number, Car, truck, or van – drove alonePct_Car_Truck_Van_drove_alone= Percent, Car, truck, or van – drove aloneCar_truck_or_van_carpooled= Number, Car, truck, or van – carpooledPct_Car_Truck_Van_carpooled= Percent, Car, truck, or van – carpooledPublic_Transport_excluding_Taxi= Number, Public transportation (excluding taxicab)Pct_Public_Transp_exclude_Taxi= Percent, Public transportation (excluding taxicab)Worked_at_home= Number, Worked at homePct_Worked_at_home= Percent, Worked at homeMean_Travel_Time_to_Work_min= Mean travel time to work (minutes)- - - - - -Civilian_nonInstitutional_Pop= Total Civilian Noninstitutionalized PopulationCiv_nonInstitution_Pop_wDisabil= #, Civilian Noninstitutionalized Population With a disabilityPct_Civ_nonInstitut_Pop_wDisab= %, Civilian Noninstitutionalized Population With a disabilityCiv_nonInstitut_Pop_under_18yrs= #, Civilian Noninstitutionalized Population Under 18 yearsCiv_nonInst_under18_wDisab= #, Civilian Noninstitutionalized Under 18 years With a disabilityPct_Civ_nonInst_under18_wDisab= %, Civilian Noninstitutionalized Under 18 years With a disabilityCiv_nonInst_Pop_18_to_64= #, Civilian Noninstitutionalized Population 18 to 64 yearsCiv_nonInst_18_to_64_wDisab= #, Civilian Noninstitutionalized 18 to 64 years With a disabilityPct_Civ_nonInst_18to64_wDisab= %, Civilian Noninstitutionalized 18 to 64 years With a disabilityCiv_nonInst_Pop_65years_up= #, Civilian Noninstitutionalized Population 65 years and overCiv_nonInst_65up_wDisab= #, Civilian Noninstitutionalized 65 years and over With a disabilityPct_Civ_nonInst_65up_wDisab= %, Civilian Noninstitutionalized 65 years and over With a disability- - - - - -Population_25_years_and_over= #, Population 25 years and overLess_than_HS_or_GED= #, Less than HS or GEDPercent_Less_than_HS_or_GED= %, Less than HS or GEDBA_or_Higher= #, BA or HigherPercent_BA_or_Higher= %, BA or Higher- - - - - -US_Native= #, U.S. NativePercent_US_Native= %, U.S. NativeUSnative_Born_in_US= #, U.S. Native, Born in the United StatesPct_USnative_Born_US= %, U.S. Native, Born in the United StatesUSnative_Born_State_Resid= #, U.S. Native, Born in State of ResidencePct_USnative_Born_State_Resid= %, U.S. Native, Born in State of ResidenceUS_Native_Born_Diff_State= #, U.S. Native, Born in Different StatePct_US_Natv_Born_inDiff_State= %, U.S. Native, Born in Different StateForeign_Born= #, Foreign BornPercent_Foreign_Born= %, Foreign BornForBorn_Nat_UScitizen= #, Foreign Born, Naturalized U.S. CitizenPct_ForBorn_Nat_UScitizen= %, Foreign Born, Naturalized U.S. CitizenForeignBorn_notUS_Citizen= #, Foreign Born, Not a U.S. CitizenPct_ForBorn_notUS_Citizen= %, Foreign Born, Not a U.S. Citizen- - - - - -GParents_Liv_wOwn_GChild_und18= #, Grandparents living with own grandchildren under 18 yearsGParents_RespFor_Gchildren= #, Grandparents Responsible for grandchildrenPct_GPar_RespFor_Gchildren= %, Grandparents Responsible for grandchildren- - - - - -Pop_wHealth_Insurance= #, Civilian noninstitutionalized population with health insurance coveragePct_Pop_wHealth_Ins= %, Civilian noninstitutionalized population with health insurance coveragePop_wPriv_Health_Ins= #, Civilian noninstitutionalized population with private health insurancePct_Pop_wPriv_Health_Ins= %, Civilian noninstitutionalized population with private health insurancePopulation_with_public_coverage= #, Civilian noninstitutionalized population with public coveragePct_Pop_with_public_coverage= %, Civilian noninstitutionalized population with public coveragePop_wNo_Health_Ins= #, Civilian noninstitutionalized population with no health insurance coveragePct_Pop_wNo_Health_Ins= %, Civilian noninstitutionalized population with no health insurance coveragePop_u18_wNo_Health_Ins= #, Civilian Noninstitutionalized Population Under 18 years with no health insurancePct_Pop_u18_wNo_Health_Ins= %, Civilian Noninstitutionalized Population Under 18 years with no health insurancePop_18to64_Employed= #, Civilian noninstitutionalized ages 18 to 64, employedPop_18to64_Empl_wNo_Health_Ins= #, Civilian noninstitutionalized ages 18 to 64, employed with no health insurancePct_Pop_18to64_Emp_wNo_Hlth_Ins= %, Civilian noninstitutionalized ages 18 to 64, employed with no health insurancePop_18to64_Unemployed= #, Civilian noninstitutionalized ages 18 to 64, unemployedPop_18to64_Unemp_wNo_Health_Ins= #, Civilian noninstitutionalized ages 18 to 64, unemployed with no health insurancePct_Pop_18to64_Unemp_No_HlthIns= %, Civilian noninstitutionalized ages 18 to 64, unemployed with no health insurancePop_18to64_Not_in_Labor_Force= #, Civilian noninstitutionalized ages 18 to 64, not in labor forcePop_18to64_Not_LabFor_NoHlthIns= #, Civilian noninstitutionalized ages 18 to 64, not in labor force with no health insurancePctPop_18to64_NotLFor_NoHlthIns= %, Civilian noninstitutionalized ages 18 to 64, not in labor force with no health insurance- - - - - -HousUnits_MonthOwnerCosts_toInc= #, Housing units for which Selected Monthly Owner Costs as % of income are computedSel_Mo_Own_Costs_30pct_of_Incom= #, Selected Monthly Owner Costs (SMOCAPI) are 30% or more of household incomePct_Sel_Mo_Own_Costs_30pct_Inc= %, Selected Monthly Owner Costs (SMOCAPI) are 30% or more of household incomeHousUnits_Compute_RentPctIncome= #, Housing units for which Gross rent as a percentage of income is computedRent_Pct_of_Inc_More30Pct= #, Gross rent as a percentage of household income (GRAPI) is 30% or morePctRent_PctIncome_More30Pct= %, Gross rent as a percentage of household income (GRAPI) is 30% or moreHousUnits_OwnRent_Compute= #, Housing units for which SMOCAPI or GRAPI are computedHousCosts_Units_30pctMore_Inc= #, Housing costs (GRAPI or SMOCAPI) are 30% or more of household incomePctHousCost_30pctMore_Income= %, Housing costs (GRAPI or SMOCAPI) are 30% or more of household income- - - - - -Total_housing_units= Total housing unitsOccupied_housing_units= #, Occupied housing unitsPercent_Occupied_housing_units= %, Occupied housing unitsVacant_housing_units= #, Vacant housing unitsPercent_Vacant_housing_units= %, Vacant housing unitsHomeowner_vacancy_rate= Homeowner vacancy rateRental_vacancy_rate= Rental vacancy rateOne_unit_detatched_housing_unit= #, 1-unit detached housing unitsPercent_1Unit_Detached= %, 1-unit detached housing unitsHousing_units_built_since_2000= #, Housing units built since 2000Pct_Units_Built_Since_2000= %, Housing units built since 2000Units_Built_1980_to_1999= #, Housing units built 1980 to 1999Pct_Units_Built_1980_to_1999= %, Housing units built 1980 to 1999Units_Built_1979_or_Earlier= #, Housing units built 1979 or earlierPct_Units_Built_1979_or_Earlier= %, Housing units built 1979 or earlierOwner_occupied_housing_units= Housing Tenure: #, Owner occupied housing unitsPct_Owner_Occ_HousUnits= Housing Tenure: %, Owner occupied housing unitsRenter_occupied_housing_units= Housing Tenure: #, Renter occupied housing unitsPct_Renter_Occ_Units= Housing Tenure: %, Renter occupied housing units- - - - - -OwnOcc_units_valued_less_100k= #, Owner occupied housing units valued less than $100,000Pct_OwnOcc_units_val_less_100k= %, Owner occupied housing units valued less than $100,000OwnOcc_units_valued_100k_300k= #, Owner occupied housing units valued $100,000-$299,999Pct_OwnOcc_units_val_100k_300k= %, Owner occupied housing units valued $100,000-$299,999OwnOcc_units_valued_300k_more= #, Owner occupied housing units valued $300,000 or morePct_OwnOcc_units_val_300k_more= %, Owner occupied housing units valued $300,000 or moreMedian_value_own_occ_units= Median value, owner occupied housing units- - - - - -Income_Total_households = Income: Total householdsHousehold_inc_less_35k= #, Household income less than $35,000Pct_Household_inc_less_35k= %, Household income less than $35,000Household_inc_35k_75k= #, Household income

Data SourcesAmerican Community Survey (ACS):Conducted by: U.S. Census BureauDescription: The ACS is an ongoing survey that provides detailed demographic and socio-economic data on the population and housing characteristics of the United States.Content: The survey collects information on various topics such as income, education, employment, health insurance coverage, and housing costs and conditions.Frequency: The ACS offers more frequent and up-to-date information compared to the decennial census, with annual estimates produced based on a rolling sample of households.Purpose: ACS data is essential for policymakers, researchers, and communities to make informed decisions and address the evolving needs of the population.CDC/ATSDR Social Vulnerability Index (SVI):Created by: ATSDR’s Geospatial Research, Analysis & Services Program (GRASP)Utilized by: CDCDescription: The SVI is designed to identify and map communities that are most likely to need support before, during, and after hazardous events.Content: SVI ranks U.S. Census tracts based on 15 social factors, including unemployment, minority status, and disability, and groups them into four related themes. Each tract receives rankings for each Census variable and for each theme, as well as an overall ranking, indicating its relative vulnerability.Purpose: SVI data provides insights into the social vulnerability of communities at the census tract level, helping public health officials and emergency response planners allocate resources effectively.Utilization and IntegrationBy integrating data from both the ACS and the SVI, this dataset enables an in-depth analysis and understanding of various socio-economic and demographic indicators at the census tract level. This integrated data is valuable for research, policymaking, and community planning purposes, allowing for a comprehensive understanding of social and economic dynamics across different geographical areas in the United States.ApplicationsLocalized Interventions: Facilitates the development of localized interventions to address the needs of vulnerable populations within specific census tracts.Resource Allocation: Assists emergency response planners in allocating resources more effectively based on community vulnerability at the census tract level.Research: Provides a detailed dataset for academic and applied research in socio-economic and demographic studies at a granular census tract level.Community Planning: Supports the planning and development of community programs and initiatives aimed at improving living conditions and reducing vulnerabilities within specific census tract areas.Note: Due to limitations in the data environment, variable names may be truncated. Refer to the provided table for a clear understanding of the variables.CSV Variable NameShapefile Variable NameDescriptionStateNameStateNameName of the stateStateFipsStateFipsState-level FIPS codeState nameStateNameName of the stateCountyNameCountyNameName of the countyCensusFipsCensusFipsCounty-level FIPS codeState abbreviationStateFipsState abbreviationCountyFipsCountyFipsCounty-level FIPS codeCensusFipsCensusFipsCounty-level FIPS codeCounty nameCountyNameName of the countyAREA_SQMIAREA_SQMITract area in square milesE_TOTPOPE_TOTPOPPopulation estimates, 2014-2018 ACSEP_POVEP_POVPercentage of persons below poverty estimateEP_UNEMPEP_UNEMPUnemployment Rate estimateEP_HBURDEP_HBURDHousing cost burdened occupied housing units with annual income less than $75,000EP_UNINSUREP_UNINSURUninsured in the total civilian noninstitutionalized population estimate, 2014-2018 ACSEP_PCIEP_PCIPer capita income estimate, 2014-2018 ACSEP_DISABLEP_DISABLPercentage of civilian noninstitutionalized population with a disability estimate, 2014-2018 ACSEP_SNGPNTEP_SNGPNTPercentage of single parent households with children under 18 estimate, 2014-2018 ACSEP_MINRTYEP_MINRTYPercentage minority (all persons except white, non-Hispanic) estimate, 2014-2018 ACSEP_LIMENGEP_LIMENGPercentage of persons (age 5+) who speak English "less than well" estimate, 2014-2018 ACSEP_MUNITEP_MUNITPercentage of housing in structures with 10 or more units estimateEP_MOBILEEP_MOBILEPercentage of mobile homes estimateEP_CROWDEP_CROWDPercentage of occupied housing units with more people than rooms estimateEP_NOVEHEP_NOVEHPercentage of households with no vehicle available estimateEP_GROUPQEP_GROUPQPercentage of persons in group quarters estimate, 2014-2018 ACSBelow_5_yrBelow_5_yrUnder 5 years: Percentage of Total populationBelow_18_yrBelow_18_yrUnder 18 years: Percentage of Total population18-39_yr18_39_yr18-39 years: Percentage of Total population40-64_yr40_64_yr40-64 years: Percentage of Total populationAbove_65_yrAbove_65_yrAbove 65 years: Percentage of Total populationPop_malePop_malePercentage of total population malePop_femalePop_femalePercentage of total population femaleWhitewhitePercentage population of white aloneBlackblackPercentage population of black or African American aloneAmerican_indianamerican_iPercentage population of American Indian and Alaska native aloneAsianasianPercentage population of Asian aloneHawaiian_pacific_islanderhawaiian_pPercentage population of Native Hawaiian and Other Pacific Islander aloneSome_othersome_otherPercentage population of some other race aloneMedian_tot_householdsmedian_totMedian household income in the past 12 months (in 2019 inflation-adjusted dollars) by household size – total householdsLess_than_high_schoolLess_than_Percentage of Educational attainment for the population less than 9th grades and 9th to 12th grade, no diploma estimateHigh_schoolHigh_schooPercentage of Educational attainment for the population of High school graduate (includes equivalency)Some_collegeSome_collePercentage of Educational attainment for the population of Some college, no degreeAssociates_degreeAssociatesPercentage of Educational attainment for the population of associate degreeBachelor’s_degreeBachelor_sPercentage of Educational attainment for the population of Bachelor’s degreeMaster’s_degreeMaster_s_dPercentage of Educational attainment for the population of Graduate or professional degreecomp_devicescomp_devicPercentage of Household having one or more types of computing devicesInternetInternetPercentage of Household with an Internet subscriptionBroadbandBroadbandPercentage of Household having Broadband of any typeSatelite_internetSatelite_iPercentage of Household having Satellite Internet serviceNo_internetNo_internePercentage of Household having No Internet accessNo_computerNo_computePercentage of Household having No computer