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.

In 2024, white Americans remained the largest racial group in the United States, numbering just over 254 million. Black Americans followed at nearly 47 million, with Asians totaling around 23 million. Hispanic residents, of any race, constituted the nation’s largest ethnic minority. Despite falling fertility, the U.S. population continues to edge upward and is expected to reach 342 million in 2025. International migrations driving population growth The United States’s population growth now hinges on immigration. Fertility rates have long been in decline, falling well below the replacement rate of 2.1. On the other hand, international migration stepped in to add some 2.8 million new arrivals to the national total that year. Changing demographics and migration patterns Looking ahead, the U.S. population is projected to grow increasingly diverse. By 2060, the Hispanic population is expected to grow to 27 percent of the total population. Likewise, African Americans will remain the largest racial minority at just under 15 percent.

Despite comprising of a smaller share of the U.S. population than African Americans or Hispanics, the most represented non-white U.S. CEOs were of an Asian background. They made up 55 percent of CEO positions at Fortune 500 and S&P 500 companies in 2024. By comparison, 11 percent of CEOs at the time were African American. The rise of environmental, social, and corporate governance (ESG) Investments in ESG have risen dramatically over last few years. In November 2023 there were approximately 480 billion U.S. dollars in ESG ETF assets worldwide, compared to 16 billion U.S. dollars in 2015. ESG measures were put in place to encourage companies to act responsibly, with the leading reason for ESG investing stated to be brand and reputation according to managers and asset owners. Gender diversity With the general acceptance of ESG in larger companies, there has still been a significant employment gap of women working in senior positions. For example, the share of women working as a partner or principal at EY, one of the largest accounting firms in the world, was just only 28 percent in 2023.

This map is designed to work in the new ArcGIS Online Map Viewer. Open in Map Viewer to view map. What does this map show?This map shows the population in the US by race. The map shows this pattern nationwide for states, counties, and tracts. Open the map in the new ArcGIS Online Map Viewer Beta to see the dot density pattern. What is dot density?The density is visualized by randomly placing one dot per a given value for the desired attribute. Unlike choropleth visualizations, dot density can be mapped using total counts since the size of the polygon plays a significant role in the perceived density of the attribute.Where is the data from?The data in this map comes from the most current American Community Survey (ACS) from the U.S. Census Bureau. Table B03002. The layer being used if updated with the most current data each year when the Census releases new estimates. The layer can be found in ArcGIS Living Atlas of the World: ACS Race and Hispanic Origin Variables - Boundaries.What questions does this map answer?Where do people of different races live?Do people of a similar race live close to people of their own race?Which cities have a diverse range of different races? Less diverse?

About this dataset

Context

The dataset tabulates the Non-Hispanic population of United States by race. It includes the distribution of the Non-Hispanic population of United States across various race categories as identified by the Census Bureau. The dataset can be utilized to understand the Non-Hispanic population distribution of United States across relevant racial categories.

Key observations

Of the Non-Hispanic population in United States, the largest racial group is White alone with a population of 193.34 million (71.80% of the total Non-Hispanic population).

Content

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

Racial categories include:

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

Variables / Data Columns

• Race: This column displays the racial categories (for Non-Hispanic) for the United States
• Population: The population of the racial category (for Non-Hispanic) in the United States is shown in this column.
• % of Total Population: This column displays the percentage distribution of each race as a proportion of United States total Non-Hispanic population. Please note that the sum of all percentages may not equal one due to rounding of values.

Good to know

Margin of Error

Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.

Custom data

If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.

Inspiration

Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.

Recommended for further research

This dataset is a part of the main dataset for United States Population by Race & Ethnicity. You can refer the same here

Racial diversity is measured by a diversity index that is calculated using United States Census racial and ethnic population characteristics from the PL-94 data file. The diversity index is a quantitative measure of the distribution of the proportion of five major ethnic populations (non-Hispanic White, non-Hispanic Black, Asian and Pacific Islander, Hispanic, and Two or more races). The index ranges from 0 (low diversity meaning only one group is present) to 1 (meaning an equal proportion of all five groups is present). The diversity score for the United States in 2010 is 0.60. The diversity score for the San Francisco Bay Region is 0.84. Within the region, Solano (0.89) and Alameda (0.90) Counties are the most diverse and the remaining North Bay (0.55 - 0.64) Counties are the least diverse.

In 2021, the distribution by race and ethnicity reveals how diverse family caregivers are in the United States. That year, nearly ********** of family caregivers in the United States were white. However, with a ** percent share in 2021, the second-most common race and ethnicity of family caregivers was Hispanic, followed by Black/African American.

This map layer shows the prevalent generations that make up the population of the United States using multiple scales. As of 2018, the most predominant generations in the U.S. are Baby Boomers (born 1946-1964), Millennials (born 1981-1998), and Generation Z (born 1999-2016). Currently, Millennials are the most predominant population in the U.S.A generation represents a group of people who are born around the same time and experience world events and trends during the same stage of life through similar mediums (for example, online, television, print, or radio). Because of this, people born in the same generation are expected to have been exposed to similar values and developmental experiences, which may cause them to exhibit similar traits or behaviors over their lifetimes. Generations provide scientists and government officials the opportunity to measure public attitudes on important issues by people’s current position in life and document those differences across demographic groups and geographic regions. Generational cohorts also give researchers the ability to understand how different developmental experiences, such as technological, political, economic, and social changes, influence people’s opinions and personalities. Studying people in generational groups is significant because an individual’s age is a conventional predictor for understanding cultural and political gaps within the U.S. population.Though there is no exact equation to determine generational cutoff points, it is understood that we designate generational spans based on a 15- to 20-year gap. The only generational period officially designated by the U.S. Census Bureau is based on the surge of births after World War II in 1946 and a significant decline in birth rates after 1964 (Baby Boomers). From that point, generational gaps have been determined by significant political, economic, and social changes that define one’s formative years (for example, Generation Z is considered to be marked by children who were directly affected by the al Qaeda attacks of September 11, 2001).In this map layer, we visualize six active generations in the U.S., each marked by significant changes in American history:The Greatest Generation (born 1901-1924): Tom Brokaw’s 1998 book, The Greatest Generation, coined the term ‘the Greatest Generation” to describe Americans who lived through the Great Depression and later fought in WWII. This generation had significant job and education opportunities as the war ended and the postwar economic booms impacted America.The Silent Generation (born 1925-1945): The title “Silent Generation” originated from a 1951 essay published in Time magazine that proposed the idea that people born during this period were more cautious than their parents. Conflict from the Cold War and the potential for nuclear war led to widespread levels of discomfort and uncertainty throughout the generation.Baby Boomers (born 1946-1964): Baby Boomers were named after a significant increase in births after World War II. During this 20-year span, life was dramatically different for those born at the beginning of the generation than those born at the tail end of the generation. The first 10 years of Baby Boomers (Baby Boomers I) grew up in an era defined by the civil rights movement and the Vietnam War, in which a lot of this generation either fought in or protested against the war. Baby Boomers I tended to have great economic opportunities and were optimistic about the future of America. In contrast, the last 10 years of Baby Boomers (Baby Boomers II) had fewer job opportunities and available housing than their Boomer I counterparts. The effects of the Vietnam War and the Watergate scandal led a lot of second-wave boomers to lose trust in the American government. Generation X (born 1965-1980): The label “Generation X” comes from Douglas Coupland’s 1991 book, Generation X: Tales for An Accelerated Culture. This generation was notoriously exposed to more hands-off parenting, out-of-home childcare, and higher rates of divorce than other generations. As a result, many Gen X parents today are concerned about avoiding broken homes with their own kids.Millennials (born 1981-1998): During the adolescence of Millennials, America underwent a technological revolution with the emergence of the internet. Because of this, Millennials are generally characterized by older generations to be technologically savvy.Generation Z (born 1999-2016): Generation Z or “Zoomers” represent a generation raised on the internet and social media. Gen Z makes up the most ethnically diverse and largest generation in American history. Like Millennials, Gen Z is recognized by older generations to be very familiar with and/or addicted to technology.Questions to ask when you look at this mapDo you notice any trends with the predominant generations located in big cities? Suburbs? Rural areas?Where do you see big clusters of the same generation living in the same area?Which areas do you see the most diversity in generations?Look on the map for where you, your parents, aunts, uncles, and grandparents live. Do they live in areas where their generation is the most predominant?

About this dataset

Context

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

Key observations

Based on our analysis of the distribution of United States population by race & ethnicity, the population is predominantly White. This particular racial category constitutes the majority, accounting for 68.17% of the total residents in United States. Notably, the median household income for White households is $79,933. Interestingly, despite the White population being the most populous, it is worth noting that Asian households actually reports the highest median household income, with a median income of $106,954. This reveals that, while Whites may be the most numerous in United States, Asian households experience greater economic prosperity in terms of median household income.

https://i.neilsberg.com/ch/united-states-median-household-income-by-race.jpeg" alt="United States median household income diversity across racial categories">

Content

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

Racial categories include:

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

Variables / Data Columns

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

Good to know

Margin of Error

Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.

Custom data

If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.

Inspiration

Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.

Recommended for further research

This dataset is a part of the main dataset for United States median household income by race. You can refer the same here

This statistic shows the public opinion on the racial diversity of selected music genres in the United States as of May 2018, by age. During the survey, 25 percent of respondents stated that they considered rap/hip-hop to be the most racially diverse music genre.

Curator's Choice

• The Behavioral Health Market size is expected to be worth around USD 227.5 Bn by 2032 from USD 140.1 Bn in 2022, growing at a CAGR of 5.1% during the forecast period from 2022 to 2032.
• Generation Z comprises approximately 26% of the global population.
• The birth years for Generation Z typically range from the mid-1990s to the early 2010s. However, there is no universally agreed-upon definition for the exact birth year range.
• Generation Z is the most racially and ethnically diverse generation in the United States, with 48% being non-white.
• Around 95% of Generation Z owns or has access to a smartphone, making them the first truly "digital native" generation.
• Generation Z is highly active on social media platforms, with 98% of individuals aged 18-24 using at least one social media platform regularly.
• In terms of education, 59% of Generation Z plans to pursue a college degree.
• Approximately 61% of Generation Z is concerned about the environment and believes that companies should take more action to address climate change.
• Mental health issues are a significant concern for Generation Z, with 91% reporting experiencing symptoms of stress and anxiety.

(Source: Pew Research Center, Statista, McKinsey & Company, American Psychological Association)

Percentage point difference between the share of the total population who is Hispanic and the share of total physician workforce who is Hispanic, 2023. Notes: Persons of Hispanic origin may be of any race but are categorized as Hispanic for this analysis; other groups are non-Hispanic.

Percentage point difference between the share of the total population who is Black and the share of total physician workforce who is Black, 2023. Notes: Persons of Hispanic origin may be of any race but are categorized as Hispanic for this analysis; other groups are non-Hispanic. For WY, the share of the total physician workforce that is Black has been masked due to small cell sizes.

Context

There has been a lot of discussion of the ways in which the workforce for Silicon Valley tech companies differs from that of the United States as a whole. In particular, a lot of evidence suggests that tech workers (who tend to be more highly paid than workers in many other professions) are more likely to be white and male. This dataset will allow you to investigate the demographics for 23 Silicon Valley tech companies for yourself.

Updates!

NEW June 2018: The spreadsheet Distributions_data_2016.csv contains workforce distributions by job category and race for 177 of the largest tech companies headquartered in Silicon Valley.

Each figure in the dataset represents the percentage of each job category that is made up of employees with a given race/gender combination, and are based on each company's EEO-1 report.

This dataset was created through a unique collaboration with the Center for Employment Equity and Reveal. The equity center provided Reveal with anonymized data for 177 large companies, and Reveal identified companies that have publicly released their data in this anonymized dataset. The equity center and Reveal analyzed the data independently.

For more information on the data, read our post here.

The spreadsheet Reveal_EEO1_for_2016.csv has been updated to include EEO-1s from companies PayPal, NetApp and Sanmina for 2016. The race and job categories have been modified to ensure consistency across all the datasets.

NEW April 2018: The spreadsheet Tech_sector_diversity_demographics_2016.csv contains aggregated diversity data for 177 large Silicon Valley tech companies. We calculated averages for the largest race and gender groups across job categories. For information on the aggregated data, read our post here.

This repository also contains EEO-1 reports filed by Silicon Valley tech companies. Please read our complete methodology for details on this data.

The data was compiled by Reveal from The Center for Investigative Reporting.

Contents

This database contains EEO-1 reports filed by Silicon Valley tech companies. It was compiled by Reveal from The Center for Investigative Reporting.

There are six columns in this dataset:

• company: Company name
• year: For now, 2016 only
• race: Possible values: "American_Indian_Alaskan_Native", "Asian", "Black_or_African_American", "Latino", "Native_Hawaiian_or_Pacific_Islander", "Two_or_more_races", "White", "Overall_totals"
• gender: Possible values: "male", "female". Non-binary gender is not counted in EEO-1 reports.
• job_category: Possible values: "Administrative support", "Craft workers", "Executive/Senior officials & Mgrs", "First/Mid officials & Mgrs", "laborers and helpers", "operatives", "Professionals", "Sales workers", "Service workers", "Technicians", "Previous_totals", "Totals"
• count: Mostly integer values, but contains "na" for a no-data variable.

Acknowledgements:

The EEO-1 database is licensed under the Open Database License (ODbL) by Reveal from The Center for Investigative Reporting.

You are free to copy, distribute, transmit and adapt the spreadsheet, so long as you:

• credit Reveal (including this link if it’s distributed online);
• inform Reveal that you are using the data in your work by emailing Sinduja Rangarajan at srangarajan@revealnews.org; and
• offer any new work under the same license.

Inspiration:

• How does each company’s workforce compare to the United States population as a whole? You can find county level diversity information here.
• Which company is the most diverse? Least diverse?

Rice (Oryza sativa) is the second leading cereal crop in the world and is one of the most important field crops in the US, valued at approximately $2.5 billion. Kernel smut (Tilletia horrida Tak.), once considered as a minor disease, is now an emerging economically important disease in the US. In this study, we used multi-locus sequence analysis to investigate the genetic diversity of 63 isolates of T. horrida collected from various rice-growing areas across in the US. Three different phylogeny analyses (maximum likelihood, neighbor-joining, and minimum evolution) were conducted based on the gene sequence sets, consisting of all four genes concatenated together, two rRNA regions concatenated together, and only ITS region sequences. The results of multi-gene analyses revealed the presence of four clades in the US populations, with 59% of the isolates clustering together. The populations collected from Mississippi and Louisiana were found to be the most diverse, whereas the populations from Arkansas and California were the least diverse. Similarly, ITS region-based analysis revealed that there were three clades in the T. horrida populations, with a majority (76%) of the isolates clustering together along with the 22 Tilletia spp. from eight different countries (Australia, China, India, Korea, Pakistan, Taiwan, The US, and Vietnam) that were grouped together. Two of the three clades in the ITS region-based phylogeny consisted of the isolates reported from multiple countries, suggesting potential multiple entries of T. horrida into the US. This is the first multi-locus analysis of T. horrida populations. The results will help develop effective management strategies, especially breeding for resistant cultivars, for the control of kernel smut in rice.

According to 2024 estimates, ** percent of Generation Z in the United States was white and non-Hispanic. Among Generation Alpha, the share was ** percent, making it the first generation in the country without a white majority.

Distribution of people who identify as AIAN by racial subgroup:

Total AIAN Population: 7.2 million. Notes: AIAN refers to American Indian or Alaska Native people. Includes people who identify as AIAN alone and in combination with another race or ethnicity. AIAN and Other includes individuals who identify as AIAN and Asian, AIAN and other race, and AIAN and two or more races. Persons of Hispanic origin are categorized as AIAN and Hispanic for this analysis; other groups are non-Hispanic. Data includes people residing in the 50 states and DC; excludes U.S. territories. Totals may not sum to 100 due to rounding.

Percentage point difference between the share of the total population who is White and the share of total physician workforce who is White, 2023. Notes: Persons of Hispanic origin may be of any race but are categorized as Hispanic for this analysis; other groups are non-Hispanic.

Notes: Persons of Hispanic origin may be of any race but are categorized as Hispanic for this analysis; other groups are non-Hispanic. Other includes people with more than one race, American Indian or Alaska Native people, and Native Hawaiian or Pacific Islander people.

The statistic presents the results of a survey on the share of adults who would watch more superhero movies if they were more diverse in the United States as of March 2019. During the survey, *** percent of respondents stated that they strongly agreed with the statement that they would watch more superhero movies if they were more diverse.