This map shows a comparison of diversity and median household income in the US by tract. Esri's Diversity Index measures the likelihood that two persons, chosen at random from the same area, belong to different races or ethnic groups. In theory, the index ranges from 0 (no diversity) to 100 (complete diversity). If an area's entire population is divided evenly into two race groups and one ethnic group, then the diversity index equals 50. As more race groups are evenly represented in the population, the diversity index increases. Minorities accounted for 30.9 percent of the population in 2000 and are expected to make up 42.3 percent of the population by 2023. Vintage of data: 2023Areas in a darker orange are less diverse than light blue areas with higher diversity. Median household income is symbolized by size. The national median household income is $58,100 and any household below the national value has the smallest symbol size. The largest size has a median household income over $100,000 per year. Esri Updated Demographics represent the suite of annually updated U.S. demographic data that provides current-year and five-year forecasts for more than two thousand demographic and socioeconomic characteristics, a subset of which is included in this layer. Included are a host of tables covering key characteristics of the population, households, housing, age, race, income, and much more. Esri's Updated Demographics data consists of point estimates, representing July 1 of the current and forecast years.Esri Updated Demographics DocumentationMethodologyUnderstanding Esri’s Updated Demographics portfolioEssential Esri Demographics vocabularyThis ready-to-use layer can be used within ArcGIS Pro, ArcGIS Online, its configurable apps, dashboards, Story Maps, custom apps, and mobile apps. This layer requires an ArcGIS Online subscription and does not consume credits. Please cite Esri when using this data.

This web map summarizes racial and ethnic diversity in the United States. The Diversity Index shows the likelihood that two persons chosen at random from the same area, belong to different race or ethnic groups. The index ranges from 0 (no diversity) to 100 (complete diversity). The diversity score for the entire United States in 2010 is 60. This data variable is included in Esri’s Updated Demographics (2010/2015). Diversity in the U.S. population is increasing. The states with the most diverse populations are California, Hawaii, and New Mexico. This map shows Esri's 2010 estimates using Census 2000 geographies. The geography depicts States at greater than 25m scale, Counties at 1m to 25m scale, Census Tracts at 250k to 1m scale, and Census Block Groups at less than 250k scale.Esri's Updated Demographics (2010/2015) – Population, age, income, sex, and race are among the variables included in the database. Each year, Esri's data development team employs its proven methodologies to update more than 2,000 demographic variables for a variety of geographies. See Updated Demographics for more information. Information about the USA Diversity Index map service used in this map is here.

This layer shows median household income by race and by age of householder. This is shown by tract, county, and state boundaries. This service is updated annually to contain the most currently released American Community Survey (ACS) 5-year data, and contains estimates and margins of error. There are also additional calculated attributes related to this topic, which can be mapped or used within analysis. Median income and income source is based on income in past 12 months of survey. This layer is symbolized to show median household income. To see the full list of attributes available in this service, go to the "Data" tab, and choose "Fields" at the top right. Current Vintage: 2019-2023ACS Table(s): B19013B, B19013C, B19013D, B19013E, B19013F, B19013G, B19013H, B19013I, B19049, B19053Data downloaded from: Census Bureau's API for American Community Survey Date of API call: December 12, 2024National Figures: data.census.govThe United States Census Bureau's American Community Survey (ACS):About the SurveyGeography & ACSTechnical DocumentationNews & UpdatesThis ready-to-use layer can be used within ArcGIS Pro, ArcGIS Online, its configurable apps, dashboards, Story Maps, custom apps, and mobile apps. Data can also be exported for offline workflows. For more information about ACS layers, visit the FAQ. Please cite the Census and ACS when using this data.Data Note from the Census:Data are based on a sample and are subject to sampling variability. The degree of uncertainty for an estimate arising from sampling variability is represented through the use of a margin of error. The value shown here is the 90 percent margin of error. The margin of error can be interpreted as providing a 90 percent probability that the interval defined by the estimate minus the margin of error and the estimate plus the margin of error (the lower and upper confidence bounds) contains the true value. In addition to sampling variability, the ACS estimates are subject to nonsampling error (for a discussion of nonsampling variability, see Accuracy of the Data). The effect of nonsampling error is not represented in these tables.Data Processing Notes:This layer is updated automatically when the most current vintage of ACS data is released each year, usually in December. The layer always contains the latest available ACS 5-year estimates. It is updated annually within days of the Census Bureau's release schedule. Click here to learn more about ACS data releases.Boundaries come from the US Census TIGER geodatabases, specifically, the National Sub-State Geography Database (named tlgdb_(year)_a_us_substategeo.gdb). Boundaries are updated at the same time as the data updates (annually), and the boundary vintage appropriately matches the data vintage as specified by the Census. These are Census boundaries with water and/or coastlines erased for cartographic and mapping purposes. For census tracts, the water cutouts are derived from a subset of the 2020 Areal Hydrography boundaries offered by TIGER. Water bodies and rivers which are 50 million square meters or larger (mid to large sized water bodies) are erased from the tract level boundaries, as well as additional important features. For state and county boundaries, the water and coastlines are derived from the coastlines of the 2023 500k TIGER Cartographic Boundary Shapefiles. These are erased to more accurately portray the coastlines and Great Lakes. The original AWATER and ALAND fields are still available as attributes within the data table (units are square meters).The States layer contains 52 records - all US states, Washington D.C., and Puerto RicoCensus tracts with no population that occur in areas of water, such as oceans, are removed from this data service (Census Tracts beginning with 99).Percentages and derived counts, and associated margins of error, are calculated values (that can be identified by the "_calc_" stub in the field name), and abide by the specifications defined by the American Community Survey.Field alias names were created based on the Table Shells file available from the American Community Survey Summary File Documentation page.Negative values (e.g., -4444...) have been set to null, with the exception of -5555... which has been set to zero. These negative values exist in the raw API data to indicate the following situations:The margin of error column indicates that either no sample observations or too few sample observations were available to compute a standard error and thus the margin of error. A statistical test is not appropriate.Either no sample observations or too few sample observations were available to compute an estimate, or a ratio of medians cannot be calculated because one or both of the median estimates falls in the lowest interval or upper interval of an open-ended distribution.The median falls in the lowest interval of an open-ended distribution, or in the upper interval of an open-ended distribution. A statistical test is not appropriate.The estimate is controlled. A statistical test for sampling variability is not appropriate.The data for this geographic area cannot be displayed because the number of sample cases is too small.

Layer from Esri, which shows median household income by race and by age of householder. This is shown by tract, county, and state boundaries. This service is updated annually to contain the most currently released American Community Survey (ACS) 5-year data, and contains estimates and margins of error. There are also additional calculated attributes related to this topic, which can be mapped or used within analysis. Median income and income source is based on income in past 12 months of survey. This layer is symbolized to show median household income. To see the full list of attributes available in this service, go to the "Data" tab, and choose "Fields" at the top right. (This map is embedded in the Roanoke County Demographics Website, and thus the county has been filtered to be the only geography shown.)

This layer shows race data in Tucson by neighborhood, aggregated from block level data, between 2010-2019. For questions, contact GIS_IT@tucsonaz.gov. The data shown is from Esri's 2019 Updated Demographic estimates.Esri's U.S. Updated Demographic (2019/2024) Data - Population, age, income, sex, race, home value, and marital status are among the variables included in the database. Each year, Esri's Data Development team employs its proven methodologies to update more than 2,000 demographic variables for a variety of U.S. geographies.Additional Esri Resources:Esri DemographicsU.S. 2019/2024 Esri Updated DemographicsEssential demographic vocabularyPermitted use of this data is covered in the DATA section of the Esri Master Agreement (E204CW) and these supplemental terms.

The Home Owners’ Loan Corporation (HOLC) was a U.S. government-sponsored program initiated in the 1930s to evaluate mortgage lending risk. The program resulted in hand-drawn ‘security risk’ maps intended to grade sections of cities where investment should be focused (greenlined areas) or limited (redlined zones). The security maps have since been widely criticized as being inherently racist and have been associated with high levels of segregation and lower levels of green amenities in cities across the country. Our goal was to explore the potential legacy effects of the HOLC grading practice on birds, their habitat, and the people who may experience them throughout a metropolis where the security risk maps were widely applied, Greater Los Angeles, California (L.A.). We used ground-collected, remotely sensed, and census data and descriptive and predictive modeling approaches to address our goal. Patterns of bird habitat and avian communities strongly aligned with the luxury-effect phenomenon, where green amenities were more robust, and bird communities were more diverse and abundant in the wealthiest parts of L.A. Our analysis also revealed potential legacy effects from the HOLC grading practice. Associations between bird habitat features and avian communities in redlined and greenlined zones were generally stronger than in areas of L.A. that did not experience the HOLC grading, in part because redlined zones, which included some of the poorest locations of L.A., had the highest levels of dense urban conditions, e.g., impervious surface cover. In contrast, greenlined zones, which included some of the city's wealthiest areas, had the highest levels of green amenities, e.g., tree canopy cover. The White population of L.A., which constitutes the highest percentage of a racial or ethnic group in greenlined areas, was aligned with a considerably greater abundance of birds affiliated with natural habitat features (e.g., trees and shrubs). Conversely, the Hispanic or Latino population, which is dominant in redlined zones, was positively related to a significantly greater abundance of synanthropic birds, which are species associated with dense urban conditions. Our results suggest that historical redlining and contemporary patterns of income inequality are associated with distinct avifaunal communities and their habitat, which potentially influence the human experience of these components of biodiversity throughout L.A. Redlined zones and low-income residential areas that were not graded by the HOLC can particularly benefit from deliberate urban greening and habitat enhancement projects, which would likely carry over to benefit birds and humans. Methods We used point count data to collect bird data, remote sensing, and field approaches for the predictor data. We also used Census data from existing products. Please reference our paper for the full methodology.

!!PLEASE NOTE!! When downloading the data, please select "File Geodatabase" to preserve long field names. Shapefile will truncate field names to 10 characters.Version: CurrentThe Racial and Social Equity Index combines information on race, ethnicity, and related demographics with data on socioeconomic and health disadvantages to identify where priority populations make up relatively large proportions of neighborhood residents. Click here for a User Guide.See the layer in action in the Racial and Social Equity ViewerClick here for an 11x17 printable pdf version of the map.The Composite Index includes sub-indices of: Race, English Language Learners, and Origins Index ranks census tracts by an index of three measures weighted as follows: Persons of color (weight: 1.0) English language learner (weight: 0.5) Foreign born (weight: 0.5)Socioeconomic Disadvantage Index ranks census tracts by an index of two equally weighted measures:Income below 200% of poverty level Educational attainment less than a bachelor’s degreeHealth Disadvantage Index ranks census tracts by an index of seven equally weighted measures:No leisure-time physical activityDiagnosed diabetes ObesityMental health not good AsthmaLow life expectancy at birthDisabilityThe index does not reflect population densities, nor does it show variation within census tracts which can be important considerations at a local level.Sources are as indicated below.Produced by City of Seattle Office of Planning & Community Development. For more information on the indices, including guidance for use, contact Diana Canzoneri (diana.canzoneri@seattle.gov).Sources: 2017-2021 Five-Year American Community Survey Estimates, U.S. Census Bureau; 2020 Decennial Census, U.S. Census Bureau; estimates from the Centers for Disease Control’ Behavioral Risk Factor Surveillance System (BRFSS) published in the “The 500 Cities Project,”; Washington State Department of Health’s Washington Tracking Network (WTN);, and estimates from the Public Health – Seattle & King County (based on the Community Health Assessment Tool).Language is for population age 5 and older. Educational attainment is for the population age 25 and over.Life expectancy is life expectancy at birth.Other health measures based on percentages of the adult population.

This map shows median age in the US by country, state, county, tract, and congressional district for 2023. ArcGIS Online account required for use.The pop-up is configured to show median age, median age by sex, child age (under 18) population, senior age (over 65) population, the age dependency ratio, and population by 5 year age increments. Blending is used at the Tract level to highlight areas of human settlement. Congressional district is turned off by default and can be enabled in the Layers pane.Esri 2023 Age Dependency Ratio is the estimated ratio of the child population (Age 0-17) and senior population (Age 65+) to the working-age population (Age 18-64) in the geographic area. This ratio is then multiplied by 100. Higher ratios denote that a greater burden is carried by working-age people. Lower ratios mean more people are working who can support the dependent population. Read more. See Updated Demographics for more information on Esri Demographic variables.Esri Updated Demographics represent the suite of annually updated U.S. demographic data that provides current-year and five-year forecasts for more than two thousand demographic and socioeconomic characteristics, a subset of which is included in this layer. Included are a host of tables covering key characteristics of the population, households, housing, age, race, income, and much more. Esri's Updated Demographics data consists of point estimates, representing July 1 of the current and forecast years.Get started with U.S. Updated DemographicsHow to use and interpret U.S. Updated DemographicsEsri Updated Demographics DocumentationMethodologyEssential Esri Demographics vocabularyThis ready-to-use layer can be used within ArcGIS Pro, ArcGIS Online, its configurable apps, dashboards, Story Maps, custom apps, and mobile apps. This layer requires an ArcGIS Online subscription and does not consume credits. Please cite Esri when using this data. For information about purchasing additional Esri's Updated Demographics data, contact datasales@esri.com. Feedback: we would like to hear from you while this layer is in beta release. If you have any feedback regarding this item or Esri Demographics, please use this survey. Fields available:GEOIDNameState NameState Abbreviation2023 Total Population (Esri)2023 Household Population (Esri)2023 Group Quarters Population (Esri)2023 Population Density (Pop per Square Mile) (Esri)2023 Total Households (Esri)2023 Average Household Size (Esri)2023 Total Housing Units (Esri)2023 Owner Occupied Housing Units (Esri)2023 Renter Occupied Housing Units (Esri)2023 Vacant Housing Units (Esri)2020-2023 Population: Compound Annual Growth Rate (Esri)2020-2023 Households: Compound Annual Growth Rate (Esri)2023 Housing Affordability Index (Esri)2023 Percent of Income for Mortgage (Esri)2023 Wealth Index (Esri)2023 Socioeconomic Status Index (Esri)2023 Generation Alpha Population (Born 2017 or Later) (Esri)2023 Generation Z Population (Born 1999 to 2016) (Esri)2023 Millennial Population (Born 1981 to 1998) (Esri)2023 Generation X Population (Born 1965 to 1980) (Esri)2023 Baby Boomer Population (Born 1946 to 1964) (Esri)2023 Silent & Greatest Generations Population (Born 1945/Earlier) (Esri)2023 Population by Generation Base (Esri)2023 Child Population (Age <18) (Esri)2023 Working-Age Population (Age 18-64) (Esri)2023 Senior Population (Age 65+) (Esri)2023 Child Dependency Ratio (Esri)2023 Age Dependency Ratio (Esri)2023 Senior Dependency Ratio (Esri)2023 Total Population Age 0-4 (Esri)2023 Total Population Age 5-9 (Esri)2023 Total Population Age 10-14 (Esri)2023 Total Population Age 15-19 (Esri)2023 Total Population Age 20-24 (Esri)2023 Total Population Age 25-29 (Esri)2023 Total Population Age 30-34 (Esri)2023 Total Population Age 35-39 (Esri)2023 Total Population Age 40-44 (Esri)2023 Total Population Age 45-49 (Esri)2023 Total Population Age 50-54 (Esri)2023 Total Population Age 55-59 (Esri)2023 Total Population Age 60-64 (Esri)2023 Total Population Age 65-69 (Esri)2023 Total Population Age 70-74 (Esri)2023 Total Population Age 75-79 (Esri)2023 Total Population Age 80-84 (Esri)2023 Total Population Age 85+ (Esri)2023 Median Age (Esri)2023 Male Population (Esri)2023 Median Male Age (Esri)2023 Female Population (Esri)2023 Median Female Age (Esri)2023 Total Population by Five-Year Age Base (Esri)2023 Total Daytime Population (Esri)2023 Daytime Population: Workers (Esri)2023 Daytime Population: Residents (Esri)2023 Daytime Population Density (Pop per Square Mile) (Esri)2023 Civilian Population Age 16+ in Labor Force (Esri)2023 Employed Civilian Population Age 16+ (Esri)2023 Unemployed Population Age 16+ (Esri)2023 Unemployment Rate (Esri)2023 Civilian Population 16-24 in Labor Force (Esri)2023 Employed Civilian Population Age 16-24 (Esri)2023 Unemployed Population Age 16-24 (Esri)2023 Unemployment Rate: Population Age 16-24 (Esri)2023 Civilian Population 25-54 in Labor Force (Esri)2023 Employed Civilian Population Age 25-54 (Esri)2023 Unemployed Population Age 25-54 (Esri)2023 Unemployment Rate: Population Age 25-54 (Esri)2023 Civilian Population 55-64 in Labor Force (Esri)2023 Employed Civilian Population Age 55-64 (Esri)2023 Unemployed Population Age 55-64 (Esri)2023 Unemployment Rate: Population Age 55-64 (Esri)2023 Civilian Population 65+ in Labor Force (Esri)2023 Employed Civilian Population Age 65+ (Esri)2023 Unemployed Population Age 65+ (Esri)2023 Unemployment Rate: Population Age 65+ (Esri)2023 Child Economic Dependency Ratio (Esri)2023 Working-Age Economic Dependency Ratio (Esri)2023 Senior Economic Dependency Ratio (Esri)2023 Economic Dependency Ratio (Esri)2023 Hispanic Population (Esri)2023 White Non-Hispanic Population (Esri)2023 Black/African American Non-Hispanic Population (Esri)2023 American Indian/Alaska Native Non-Hispanic Population (Esri)2023 Asian Non-Hispanic Population (Esri)2023 Pacific Islander Non-Hispanic Population (Esri)2023 Other Race Non-Hispanic Population (Esri)2023 Multiple Races Non-Hispanic Population (Esri)2023 Diversity Index (Esri)2023 Population by Race Base (Esri)2023 Population Age 25+: Less than 9th Grade (Esri)2023 Population Age 25+: 9-12th Grade/No Diploma (Esri)2023 Population Age 25+: High School Diploma (Esri)2023 Population Age 25+: GED/Alternative Credential (Esri)2023 Population Age 25+: Some College/No Degree (Esri)2023 Population Age 25+: Associate's Degree (Esri)2023 Population Age 25+: Bachelor's Degree (Esri)2023 Population Age 25+: Graduate/Professional Degree (Esri)2023 Educational Attainment Base (Pop 25+)(Esri)2023 Household Income less than $15,000 (Esri)2023 Household Income $15,000-$24,999 (Esri)2023 Household Income $25,000-$34,999 (Esri)2023 Household Income $35,000-$49,999 (Esri)2023 Household Income $50,000-$74,999 (Esri)2023 Household Income $75,000-$99,999 (Esri)2023 Household Income $100,000-$149,999 (Esri)2023 Household Income $150,000-$199,999 (Esri)2023 Household Income $200,000 or greater (Esri)2023 Median Household Income (Esri)2023 Average Household Income (Esri)2023 Per Capita Income (Esri)2023 Households by Income Base (Esri)2023 Gini Index (Esri)2023 P90-P10 Ratio of Income Inequality (Esri)2023 P90-P50 Ratio of Income Inequality (Esri)2023 P50-P10 Ratio of Income Inequality (Esri)2023 80-20 Share Ratio of Income Inequality (Esri)2023 90-40 Share Ratio of Income Inequality (Esri)2023 Households in Low Income Tier (Esri)2023 Households in Middle Income Tier (Esri)2023 Households in Upper Income Tier (Esri)2023 Disposable Income less than $15,000 (Esri)2023 Disposable Income $15,000-$24,999 (Esri)2023 Disposable Income $25,000-$34,999 (Esri)2023 Disposable Income $35,000-$49,999 (Esri)2023 Disposable Income $50,000-$74,999 (Esri)2023 Disposable Income $75,000-$99,999 (Esri)2023 Disposable Income $100,000-$149,999 (Esri)2023 Disposable Income $150,000-$199,999 (Esri)2023 Disposable Income $200,000 or greater (Esri)2023 Median Disposable Income (Esri)2023 Home Value less than $50,000 (Esri)2023 Home Value $50,000-$99,999 (Esri)2023 Home Value $100,000-$149,999 (Esri)2023 Home Value $150,000-$199,999 (Esri)2023 Home Value $200,000-$249,999 (Esri)2023 Home Value $250,000-$299,999 (Esri)2023 Home Value $300,000-$399,999 (Esri)2023 Home Value $400,000-$499,999 (Esri)2023 Home Value $500,000-$749,999 (Esri)2023 Home Value $750,000-$999,999 (Esri)2023 Home Value $1,000,000-$1,499,999 (Esri)2023 Home Value $1,500,000-$1,999,999 (Esri)2023 Home Value $2,000,000 or greater (Esri)2023 Median Home Value (Esri)2023 Average Home Value (Esri)2028 Total Population (Esri)2028 Household Population (Esri)2028 Population Density (Pop per Square Mile) (Esri)2028 Total Households (Esri)2028 Average Household Size (Esri)2023-2028 Population: Compound Annual Growth Rate (Esri)2023-2028 Households: Compound Annual Growth Rate (Esri)2023-2028 Per Capita Income: Compound Annual Growth Rate (Esri)2023-2028 Median Household Income: Compound Annual Growth Rate (Esri)2028 Diversity Index (Esri)2028 Median Household Income (Esri)2028 Average Household Income (Esri)2028 Per Capita Income (Esri)

Selected demographics by census tracts in King County based on current American Community Survey 5 Year Average (ACS). Included demographics are: AGE AND SEX [Percent 65 and Over, Percent between 18 and 65, Percent 17 and Under, Percent Female, Percent Male], RACE AND ETHNICITY [Percent People of Color, Percent Hispanic/Latino, Percent Hawaiian/Pacific Islander Alone, Percent Asian Alone, Percent American Indian/Native Alaskan Alone, Percent Black/African American Alone, Percent White Alone], INCOME [Median Household Income, 200% of Federal Poverty Level], LANGUAGES [Percent Spanish Speakers, Percent Vietnamese Speakers, Percent Russian Speakers, Percent African Languages Speakers, Percent Chinese Speakers, Percent Korean Speakers]. Numbers and derived percentages are estimates based on the current year's ACS. GEO_ID_TRT is the key field and may be used to join to other demographic Census data tables

County_Centroids

This layer shows the age statistics in Tucson by neighborhood, aggregated from block level data, between 2010-2019. For questions, contact GIS_IT@tucsonaz.gov. The data shown is from Esri's 2019 Updated Demographic estimates.Esri's U.S. Updated Demographic (2019/2024) Data - Population, age, income, sex, race, home value, and marital status are among the variables included in the database. Each year, Esri's Data Development team employs its proven methodologies to update more than 2,000 demographic variables for a variety of U.S. geographies.Additional Esri Resources:Esri DemographicsU.S. 2019/2024 Esri Updated DemographicsEssential demographic vocabularyPermitted use of this data is covered in the DATA section of the Esri Master Agreement (E204CW) and these supplemental terms.

Home Owners’ Loan Corporation (HOLC) maps illustrated patterns of segregation in United States cites in the 1930s. As the causes and drivers of demographic and land use segregation vary over years, these maps provide an important spatial lens in determining how patterns of segregation spatially and temporally developed during the course of the past century. Using a high-resolution land-use time series (1937-2018) of Denver Colorado USA, in conjunction with 80 years of U.S. Census data, we found divergent land-use and demographics patterns across HOLC categories were both pre-existent to the establishment of HOLC mapping, and continued to develop over time. Over this period, areas deemed “declining” or “hazardous” had more diverse land use compared “desirable” areas. “Desirable” areas were dominated by one land-use type (single-family residential), while single-family residential diminished in prominence in the “declining/hazardous” areas. This divergence became more established decades after HOLC mapping, with impact to racial metrics and low-income households. We found changes in these demographic patterns also occurred between 2000 and 2019, highlighting how processes like gentrification can develop from both rapid demographic and land-use changes. This study demonstrates how the legacy of urban segregation develops over decades and can simultaneously persist in some neighborhoods while providing openings for fast-paced gentrification in others.

The SCAG_ATDB_Demographics shapefile contains Census tract level population, race, employment, English speaking, income, and elderly data of the SCAG region. Race data includes the percentage of population that is white, black, Asian, Latino, Pacific Islander, Native American, multiple races, or other. Population data includes 2010 population 2015 population, and population density. Employment data includes 2015 employment, unemployment, and employment density. English speaking data includes the percentage of the population that speaks English well. This shapefile also includes median household income and percentage of the population that is 65 years or older. This data was sourced mostly from Census data as well as the Healthy Places Index (HPI). Original data sources are listed in the relevant fields.

The demographic data displayed in this theme of Florida’s Roadmap to Living Healthy are quantitative measures that exhibit the socioeconomic state of Florida’s communities. The data sets comprising this themed map include topics such as population, race, income level, age, education, housing, and lifestyle data for all of Florida’s 67 counties, and other basic demographic characteristics. The Florida Department of Agriculture and Consumer Services has utilized the most current demographic statistical data from trusted sources such as the U.S. Census Bureau, U.S. Department of Housing and Urban Development, U.S. Department of Labor Bureau of Labor Statistics, Florida Department of Children and Families, and Esri to craft this custom visualization. Demographics provide profound perspective to your data analytics and will help you recognize the distinctive characteristics of a population based on its location. This demographic-themed mapping tool will simplify your ability to identify the specific socioeconomic needs of every community in Florida.

For source data: https://data.census.gov/table/ACSDP5Y2023.DP03. Layer published for the Equity Explorer, a web experience developed by the LA County CEO Anti-Racism, Diversity, and Inclusion (ARDI) initiative in collaboration with eGIS and ISD. Visit the Equity Explorer to explore Income and other equity related datasets and indices, including the COVID Vulnerability and Recovery Index. Income per capita for census tracts in LA County from the US Census American Communities Survey (ACS), 2023. Estimates are based on 2020 census tract boundaries, and tracts are joined to 2021 Supervisorial Districts, Service Planning Areas (SPA), and Countywide Statistical Areas (CSA). For more information about this dataset, please contact egis@isd.lacounty.gov.

This web map displays data from the voter registration database as the percent of registered voters by census tract in King County, Washington. The data for this web map is compiled from King County Elections voter registration data for the years 2013-2019. The total number of registered voters is based on the geo-_location of the voter's registered address at the time of the general election for each year. The eligible voting population, age 18 and over, is based on the estimated population increase from the US Census Bureau and the Washington Office of Financial Management and was calculated as a projected 6 percent population increase for the years 2010-2013, 7 percent population increase for the years 2010-2014, 9 percent population increase for the years 2010-2015, 11 percent population increase for the years 2010-2016 & 2017, 14 percent population increase for the years 2010-2018 and 17 percent population increase for the years 2010-2019. The total population 18 and over in 2010 was 1,517,747 in King County, Washington. The percentage of registered voters represents the number of people who are registered to vote as compared to the eligible voting population, age 18 and over. The voter registration data by census tract was grouped into six percentage range estimates: 50% or below, 51-60%, 61-70%, 71-80%, 81-90% and 91% or above with an overall 84 percent registration rate. In the map the lighter colors represent a relatively low percentage range of voter registration and the darker colors represent a relatively high percentage range of voter registration. PDF maps of these data can be viewed at King County Elections downloadable voter registration maps. The 2019 General Election Voter Turnout layer is voter turnout data by historical precinct boundaries for the corresponding year. The data is grouped into six percentage ranges: 0-30%, 31-40%, 41-50% 51-60%, 61-70%, and 71-100%. The lighter colors represent lower turnout and the darker colors represent higher turnout. The King County Demographics Layer is census data for language, income, poverty, race and ethnicity at the census tract level and is based on the 2010-2014 American Community Survey 5 year Average provided by the United States Census Bureau. Since the data is based on a survey, they are considered to be estimates and should be used with that understanding. The demographic data sets were developed and are maintained by King County Staff to support the King County Equity and Social Justice program. Other data for this map is located in the King County GIS Spatial Data Catalog, where data is managed by the King County GIS Center, a multi-department enterprise GIS in King County, Washington. King County has nearly 1.3 million registered voters and is the largest jurisdiction in the United States to conduct all elections by mail. In the map you can view the percent of registered voters by census tract, compare registration within political districts, compare registration and demographic data, verify your voter registration or register to vote through a link to the VoteWA, Washington State Online Voter Registration web page.

This layer shows employment data in Tucson by neighborhood, aggregated from block level data for 2019. For questions, contact GIS_IT@tucsonaz.gov. The data shown is from Esri's 2019 Updated Demographic estimates.Esri's U.S. Updated Demographic (2019/2024) Data - Population, age, income, sex, race, home value, and marital status are among the variables included in the database. Each year, Esri's Data Development team employs its proven methodologies to update more than 2,000 demographic variables for a variety of U.S. geographies.Additional Esri Resources:Esri DemographicsU.S. 2019/2024 Esri Updated DemographicsEssential demographic vocabularyPermitted use of this data is covered in the DATA section of the Esri Master Agreement (E204CW) and these supplemental terms.

This map shows median household income in the US by state, county, and tract for 2023. ArcGIS Online account required for use.The pop-up is configured to show median household income in 2023 with the forecasted rate of change to 2028, and disposable income by income range. Median Household Income is the amount that divides household income (annual income for all household earners age 15+) into two equal groups in a geographic area; half of the population will have income higher than the median and half will have lower income. If the median falls in the upper income interval of $200,000+, it is represented by the value of $200,001. Esri uses the U.S. Census definition of income. For each person 15 years of age or older, money income received in the preceding calendar year is summed from earnings, unemployment compensation, Social Security, Supplemental Security Income, public assistance, veterans' payments, survivor benefits, disability benefits, pension or retirement income, interest, dividends, rent, royalties, estates and trusts, educational assistance, alimony, child support, financial assistance from outside the household, and other income; reference Esri Essential Vocabulary.Esri Updated Demographics represent the suite of annually updated U.S. demographic data that provides current-year and five-year forecasts for more than two thousand demographic and socioeconomic characteristics, a subset of which is included in this layer. Included are a host of tables covering key characteristics of the population, households, housing, age, race, income, and much more. Esri's Updated Demographics data consists of point estimates, representing July 1 of the current and forecast years.Esri Updated Demographics DocumentationMethodologyUnderstanding Esri’s Updated Demographics portfolioEssential Esri Demographics vocabularyThis ready-to-use layer can be used within ArcGIS Pro, ArcGIS Online, its configurable apps, dashboards, Story Maps, custom apps, and mobile apps. This layer requires an ArcGIS Online subscription and does not consume credits. Please cite Esri when using this data. For information about purchasing additional Esri's Updated Demographics data, contact datasales@esri.com. Feedback: we would like to hear from you while this layer is in beta release. If you have any feedback regarding this item or Esri Demographics, please use this survey.

Race, Ethnicity, Gender - Demographic Indicators (From 2010 Census)Link: https://www2.minneapolismn.gov/census/2010/index.htmHousehold IncomeLinks: Poverty GuidelinesACS 2019 5 Year Estimates Household IncomeDisability - One or more people with disability per household vs no people with disabilityLink: ACS 2019 5 Year Estimates Disability by HouseholdSex and AgeLink: Sex by Age ACS 2019 5 Year Estimates

Retirement Notice: This item is in mature support as of June 2023 and will be retired in December 2025. A replacement item has not been identified at this time. Esri recommends updating your maps and apps to phase out use of this item.This map displays the dominant LifeMode Summary Group in the USA by country, state, county, ZIP Code, tract, and block group, based on Esri's Tapestry Segmentation system. The popup refers to state, county, ZIP Code, tract, and block group values depending on scale. Each popup is configured to display the following information within each geography level:Dominant Tapestry SegmentLink to more information about the predominant Tapestry SegmentTotal populationMedian age (Median Age web map)Diversity Index (Diversity Index web map)Median household income (Median Household Income web map)Median disposable income (Median Disposable Income web map)Count of households by Tapestry LifeMode Summary GroupCount of population by race/ethnicityLink to more information about Esri's Demographics Permitted use of this data is covered in the DATA section of the Esri Master Agreement (E204CW) and these supplemental terms.