The U.S. Census defines Asian Americans as individuals having origins in any of the original peoples of the Far East, Southeast Asia, or the Indian subcontinent (U.S. Office of Management and Budget, 1997). As a broad racial category, Asian Americans are the fastest-growing minority group in the United States (U.S. Census Bureau, 2012). The growth rate of 42.9% in Asian Americans between 2000 and 2010 is phenomenal given that the corresponding figure for the U.S. total population is only 9.3% (see Figure 1). Currently, Asian Americans make up 5.6% of the total U.S. population and are projected to reach 10% by 2050. It is particularly notable that Asians have recently overtaken Hispanics as the largest group of new immigrants to the U.S. (Pew Research Center, 2015). The rapid growth rate and unique challenges as a new immigrant group call for a better understanding of the social and health needs of the Asian American population.

The East Asian Social Survey (EASS) is a biennial social survey project that serves as a cross-national network of the following four General Social Survey type surveys in East Asia: the Chinese General Social Survey (CGSS), the Japanese General Social Survey (JGSS), the Korean General Social Survey (KGSS), and the Taiwan Social Change Survey (TSCS), and comparatively examines diverse aspects of social life in these regions. Since its 1st module survey in 2006, EASS produces and disseminates its module survey datasets and this is the harmonized data for the 7th module survey, called 'Culture and Globalization in East Asia'. Survey information in this module is the same topic as the second module of the EASS 2008, and it focuses on cultural norms and expectations of respondents. Respondents were asked about their exposure to East Asian cultural activities and rituals as well as opinion on family responsibilities and roles. Other topics include sources of international news and discussion frequency, countries or regions traveled, as well as where acquaintances live. Additionally, respondents were asked how accepting they would be of people from other countries as coworkers, neighbors, and in marriage. Information was collected regarding foreign practices, whether the respondent was working for a foreign capital company, and the economic environment. Respondents were also asked to assess their own proficiency when reading, speaking, and writing in English. Demographic information specific to the respondent and their spouse includes age, sex, marital status, education, employment status and hours worked, occupation, earnings and income, religion, class, size of community, and region.

About this dataset

Context

This list ranks the 1 cities in the Denver County, CO by Asian population, as estimated by the United States Census Bureau. It also highlights population changes in each cities over the past five years.

Content

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

• 2019-2023 American Community Survey 5-Year Estimates
• 2018-2022 American Community Survey 5-Year Estimates
• 2017-2021 American Community Survey 5-Year Estimates
• 2016-2020 American Community Survey 5-Year Estimates
• 2015-2019 American Community Survey 5-Year Estimates

Variables / Data Columns

• Rank by Asian Population: This column displays the rank of cities in the Denver County, CO by their Asian population, using the most recent ACS data available.
• cities: The cities for which the rank is shown in the previous column.
• Asian Population: The Asian population of the cities is shown in this column.
• % of Total cities Population: This shows what percentage of the total cities population identifies as Asian. Please note that the sum of all percentages may not equal one due to rounding of values.
• % of Total Denver County Asian Population: This tells us how much of the entire Denver County, CO Asian population lives in that cities. Please note that the sum of all percentages may not equal one due to rounding of values.
• 5 Year Rank Trend: TThis column displays the rank trend across the last 5 years.

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/.

About this dataset

Context

This list ranks the 24 cities in the Pinellas County, FL by Multi-Racial Asian population, as estimated by the United States Census Bureau. It also highlights population changes in each cities over the past five years.

Content

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

• 2019-2023 American Community Survey 5-Year Estimates
• 2018-2022 American Community Survey 5-Year Estimates
• 2017-2021 American Community Survey 5-Year Estimates
• 2016-2020 American Community Survey 5-Year Estimates
• 2015-2019 American Community Survey 5-Year Estimates

Variables / Data Columns

• Rank by Multi-Racial Asian Population: This column displays the rank of cities in the Pinellas County, FL by their Multi-Racial Asian population, using the most recent ACS data available.
• cities: The cities for which the rank is shown in the previous column.
• Multi-Racial Asian Population: The Multi-Racial Asian population of the cities is shown in this column.
• % of Total cities Population: This shows what percentage of the total cities population identifies as Multi-Racial Asian. Please note that the sum of all percentages may not equal one due to rounding of values.
• % of Total Pinellas County Multi-Racial Asian Population: This tells us how much of the entire Pinellas County, FL Multi-Racial Asian population lives in that cities. Please note that the sum of all percentages may not equal one due to rounding of values.
• 5 Year Rank Trend: TThis column displays the rank trend across the last 5 years.

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/.

This dataset provides a comprehensive look at population and migration trends in five South Asian countries: Afghanistan, Bangladesh, India, Pakistan, and Sri Lanka, covering the years 1960 to 2023. The data is sourced directly from the World Bank API and contains detailed statistics on total population and net migration for each year.

This dataset is ideal for:

• Time-series analysis to study population trends over six decades.
• Migration studies to assess policy impacts and demographic shifts.
• Data visualization for dashboards and presentations.
• Machine learning applications in predictive analytics.

Columns: - Country: Name of the country. - Year: Year of the recorded data. - Total Population: The total population of the country. - Net Migration: Net migration balance (positive for immigration surplus, negative for emigration surplus).

Key Insights: - Afghanistan: Significant migration shifts due to conflicts and crises. - India: Continuous population growth with varying migration trends. - Bangladesh: A history of large emigration and its impact on demographics. - Pakistan: Migration surpluses in some years and large outflows in others. - Sri Lanka: Gradual population growth and consistent emigration patterns.

The following data set is information obtained about counties in the United States from 2010 through 2019 through the United States Census Bureau. Information described in the data includes the age distributions, the education levels, employment statistics, ethnicity percents, houseold information, income, and other miscellneous statistics. (Values are denoted as -1, if the data is not available)

Data Dictionary

About this dataset

Context

This list ranks the 39 cities in the Rhode Island by Asian population, as estimated by the United States Census Bureau. It also highlights population changes in each cities over the past five years.

Content

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

• 2019-2023 American Community Survey 5-Year Estimates
• 2018-2022 American Community Survey 5-Year Estimates
• 2017-2021 American Community Survey 5-Year Estimates
• 2016-2020 American Community Survey 5-Year Estimates
• 2015-2019 American Community Survey 5-Year Estimates

Variables / Data Columns

• Rank by Asian Population: This column displays the rank of cities in the Rhode Island by their Asian population, using the most recent ACS data available.
• cities: The cities for which the rank is shown in the previous column.
• Asian Population: The Asian population of the cities is shown in this column.
• % of Total cities Population: This shows what percentage of the total cities population identifies as Asian. Please note that the sum of all percentages may not equal one due to rounding of values.
• % of Total Rhode Island Asian Population: This tells us how much of the entire Rhode Island Asian population lives in that cities. Please note that the sum of all percentages may not equal one due to rounding of values.
• 5 Year Rank Trend: TThis column displays the rank trend across the last 5 years.

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/.

Introduction

Welcome to the East Asian Human Face with Occlusion Dataset, carefully curated to support the development of robust facial recognition systems, occlusion detection models, biometric identification technologies, and KYC verification tools. This dataset provides real-world variability by including facial images with common occlusions, helping AI models perform reliably under challenging conditions.

Facial Image Data

The dataset comprises over 5,000 high-quality facial images, organized into participant-wise sets. Each set includes:

Diversity & Representation

Image Quality & Capture Conditions

To ensure robustness and real-world utility, images were captured under diverse conditions:

Metadata

Each image is paired with detailed metadata to enable advanced filtering, model tuning, and analysis:

This rich metadata helps train models that can recognize faces even when partially obscured.

Use Cases & Applications

This dataset is ideal for a wide range of real-world and research-focused applications, including:

Secure & Ethical Collection

About this dataset

Context

This list ranks the 90 cities in the Arizona by Asian population, as estimated by the United States Census Bureau. It also highlights population changes in each cities over the past five years.

Content

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

• 2019-2023 American Community Survey 5-Year Estimates
• 2018-2022 American Community Survey 5-Year Estimates
• 2017-2021 American Community Survey 5-Year Estimates
• 2016-2020 American Community Survey 5-Year Estimates
• 2015-2019 American Community Survey 5-Year Estimates

Variables / Data Columns

• Rank by Asian Population: This column displays the rank of cities in the Arizona by their Asian population, using the most recent ACS data available.
• cities: The cities for which the rank is shown in the previous column.
• Asian Population: The Asian population of the cities is shown in this column.
• % of Total cities Population: This shows what percentage of the total cities population identifies as Asian. Please note that the sum of all percentages may not equal one due to rounding of values.
• % of Total Arizona Asian Population: This tells us how much of the entire Arizona Asian population lives in that cities. Please note that the sum of all percentages may not equal one due to rounding of values.
• 5 Year Rank Trend: TThis column displays the rank trend across the last 5 years.

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/.

Relative concentration of the Northern California region's Asian American population. The variable ASIANALN records all individuals who select Asian as their SOLE racial identity in response to the Census questionnaire, regardless of their response to the Hispanic ethnicity question. Both Hispanic and non-Hispanic in the Census questionnaire are potentially associated with the Asian race alone.

"Relative concentration" is a measure that compares the proportion of population within each Census block group data unit that identify as ASIANALN alone to the proportion of all people that live within the 1,207 block groups in the Northern California RRK region that identify as ASIANALN alone. Example: if 5.2% of people in a block group identify as HSPBIPOC, the block group has twice the proportion of ASIANALN individuals compared to the Northern California RRK region (2.6%), and more than three times the proportion compared to the entire state of California (1.6%). If the local proportion is twice the regional proportion, then ASIANALN individuals are highly concentrated locally.

This dataset includes all personal names listed in the Wikipedia category “American people by ethnic or national origin” and all subcategories fitting the pattern “American People of [ ] descent”, in total more than 25,000 individuals. Each individual is represented by a row, with columns indicating binary membership (0/1) in each ethnic/national category.

Ethnicity inference is an essential tool for identifying disparities in public health and social sciences. Existing datasets linking personal names to ethnic or national origin often neglect to recognize multi-ethnic or multi-national identities. Furthermore, existing datasets use coarse classification schemes (e.g. classifying both Indian and Japanese people as “Asian”) that may not be suitable for many research questions. This dataset remedies these problems by including both very fine-grain ethnic/national categories (e.g. Afghan-Jewish) and more broad ones (e.g. European). Users can chose the categories that are relevant to their research. Since many Americans on Wikipedia are associated with multiple overlapping or distinct ethnicities/nationalities, these multi-ethnic associations are also reflected in the data.

Data were obtained from the Wikipedia API and reviewed manually to remove stage names, pen names, mononyms, first initials (when full names are available on Wikipedia), nicknames, honorific titles, and pages that correspond to a group or event rather than an individual.

This dataset was designed for use in training classification algorithms, but may also be independently interesting inasmuch as it is a representative sample of Americans who are famous enough to have their own Wikipedia page, along with detailed information on their ethnic/national origins.

DISCLAIMER: Due to the incomplete nature of Wikipedia, data may not properly reflect all ethnic national associations for any given individual. For example, there is no guarantee that a given Cuban Jewish person will be listed in both the “American People of Cuban descent” and the “American People of Jewish descent” categories.

About this dataset

Context

The dataset tabulates the population of Fernandina Beach by race. It includes the population of Fernandina Beach across racial categories (excluding ethnicity) as identified by the Census Bureau. The dataset can be utilized to understand the population distribution of Fernandina Beach across relevant racial categories.

Key observations

The percent distribution of Fernandina Beach population by race (across all racial categories recognized by the U.S. Census Bureau): 85.53% are white, 7.33% are Black or African American, 1.13% are Asian, 0.23% are some other race and 5.77% are multiracial.

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 (excluding ethnicity) for the Fernandina Beach
• Population: The population of the racial category (excluding ethnicity) in the Fernandina Beach is shown in this column.
• % of Total Population: This column displays the percentage distribution of each race as a proportion of Fernandina Beach total 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 Fernandina Beach Population by Race & Ethnicity. You can refer the same here

About the Data:

A year ago, when WHO declared COVID-19 outbreak a pandemic, countries in WHO South-East Asia Region were either responding to their first cases of importation or cluster of cases or keeping a strict vigil against importation of the new coronavirus.

The following months were unprecedented, and for many reasons. Scientists, experts, governments, societies, communities and even individuals responded to the new virus with urgency and measures never witnessed before.

Metadata:

ID: Unique Identifier Country: Name of Country TotalCases: Total Number of cases recorded so far TotalDeaths: Total Deaths recorded so far TotalRecovered: How many people survived ActiveCases: Number of people who currently has the virus TotalCasesPerMillion: How many cases are recorded per million individual TotalDeathsPerMillion: How many deaths recorded per million individual TotalTests: Total number of COVID19 tests conducted RTPCR + RAT + any other tests TotalTestsPerMillion: How many tests were conducted per million individual TotalPopulation: Population of the country

Acknowledgements:

This dataset was collected from: https://www.worldometers.info/coronavirus/#countries

Call For Code:

Fellow Data Scientist and ML engineers, can you identify which countries are doing relatively well and which ones need immediate attention? Your insights can save millions of lives in Asia!

Use this application to view the pattern of concentrations of people by race and Hispanic or Latino ethnicity. Data are provided at the U.S. Census block group level, one of the smallest Census geographies, to provide a detailed picture of these patterns. The data is sourced from the U.S Census Bureau, 2020 Census Redistricting Data (Public Law 94-171) Summary File. Definitions: Definitions of the Census Bureau’s categories are provided below. This interactive map shows patterns for all categories except American Indian or Alaska Native and Native Hawaiian or Other Pacific Islander. The total population countywide for these two categories is small (1,582 and 263 respectively). The Census Bureau uses the following race categories:Population by RaceWhite – A person having origins in any of the original peoples of Europe, the Middle East, or North Africa.Black or African American – A person having origins in any of the Black racial groups of Africa.American Indian or Alaska Native – A person having origins in any of the original peoples of North and South America (including Central America) and who maintains tribal affiliation or community attachment.Asian – A person having origins in any of the original peoples of the Far East, Southeast Asia, or the Indian subcontinent including, for example, Cambodia, China, India, Japan, Korea, Malaysia, Pakistan, the Philippine Islands, Thailand, and Vietnam.Native Hawaiian or Other Pacific Islander – A person having origins in any of the original peoples of Hawaii, Guam, Samoa, or other Pacific Islands.Some Other Race - this category is chosen by people who do not identify with any of the categories listed above. People can identify with more than one race. These people are included in the Two or More Races Hispanic or Latino PopulationThe Hispanic/Latino population is an ethnic group. Hispanic/Latino people may be of any race.Other layers provided in this tool included the Loudoun County Census block groups, towns and Dulles airport, and the Loudoun County 2021 aerial imagery.

About this dataset

Context

This list ranks the 525 cities in the Georgia by Asian population, as estimated by the United States Census Bureau. It also highlights population changes in each cities over the past five years.

Content

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

• 2019-2023 American Community Survey 5-Year Estimates
• 2018-2022 American Community Survey 5-Year Estimates
• 2017-2021 American Community Survey 5-Year Estimates
• 2016-2020 American Community Survey 5-Year Estimates
• 2015-2019 American Community Survey 5-Year Estimates

Variables / Data Columns

• Rank by Asian Population: This column displays the rank of cities in the Georgia by their Asian population, using the most recent ACS data available.
• cities: The cities for which the rank is shown in the previous column.
• Asian Population: The Asian population of the cities is shown in this column.
• % of Total cities Population: This shows what percentage of the total cities population identifies as Asian. Please note that the sum of all percentages may not equal one due to rounding of values.
• % of Total Georgia Asian Population: This tells us how much of the entire Georgia Asian population lives in that cities. Please note that the sum of all percentages may not equal one due to rounding of values.
• 5 Year Rank Trend: TThis column displays the rank trend across the last 5 years.

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/.

Know Your Customer Dataset, Face Detection and Re-identification, Asian People

The dataset is created on the basis of Selfies and ID Dataset

9,900+ photos including 1,300+ document photos from 660 people from 27 countries. The dataset includes 2 photos of a person from his documents and 13 selfies. All people presented in the dataset are South Asian, East Asian or Middle Asian. The dataset contains a variety of images capturing individuals from diverse backgrounds and age groups.

Photo documents contains only a photo of a person. All personal information from the document is hidden https://www.googleapis.com/download/storage/v1/b/kaggle-user-content/o/inbox%2F12421376%2F63f531bd9930fa2149f3d257f68d65ca%2FFrame%2015.png?generation=1712234429707103&alt=media" alt="">

Documents in the dataset

• Passports
• International passport
• Driver licenses
• Student cards
• Health certificate
• Pensioner's ID
• Pass to work
• Other documents

The dataset can be utilized for a wide range of tasks, including face recognition, emotion detection, age estimation, gender classification, or any problem related to human image analysis.

👉 Legally sourced datasets and carefully structured for AI training and model development. Explore samples from our dataset of 95,000+ human images & videos - Full dataset

Metadata for the full dataset:

• assignment_id - unique identifier of the media file
• worker_id - unique identifier of the person
• age - age of the person
• gender - gender of the person
• country - country of the person
• ethnicity - ethnicity of the person
• photo_1_extension, photo_2_extension, …, photo_15_extension - photo extensions in the dataset
• photo_1_resolution, photo_2_resolution, …, photo_15_resolution - photo resolution in the dataset

Statistics for the dataset

https://www.googleapis.com/download/storage/v1/b/kaggle-user-content/o/inbox%2F12421376%2Fba893bc048ad9f8fe029c6f1833a8df9%2FFrame%2099.png?generation=1712235055301722&alt=media" alt="">

🧩 This is just an example of the data. Leave a request here to learn more

Content

The dataset consists of: - files - includes 5 folders corresponding to each person and including 15 images (2 id photos and 13 selfies), - .csv file - contains information about the images and people in the dataset

File with the extension .csv

• id: id of the person,
• age - age of the person,
• gender - gender of the person,
• country - country of the person,
• id_1, id_2: link to access id photos,
• selfie_1, selfie_2, ..., selfie_13: link to access each of the 13 selfies of the person

🚀 You can learn more about our high-quality unique datasets here

keywords: biometric system, biometric dataset, face recognition database, face recognition dataset, face detection dataset, facial analysis, object detection dataset, deep learning datasets, computer vision datset, human images dataset, human faces dataset, machine learning, image-to-image, re-identification, id photos, selfies and paired id, photos, id verification models, passport, id card image, digital photo-identification, asian people, asian dataset

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.

About this dataset

Context

The dataset tabulates the population of London by race. It includes the population of London across racial categories (excluding ethnicity) as identified by the Census Bureau. The dataset can be utilized to understand the population distribution of London across relevant racial categories.

Key observations

The percent distribution of London population by race (across all racial categories recognized by the U.S. Census Bureau): 91.78% are white, 2.40% are Black or African American, 0.12% are American Indian and Alaska Native, 1.70% are Asian, 0.14% are some other race and 3.87% are multiracial.

https://i.neilsberg.com/ch/london-oh-population-by-race.jpeg" alt="London population by race">

Content

When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2017-2021 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 (excluding ethnicity) for the London
• Population: The population of the racial category (excluding ethnicity) in the London is shown in this column.
• % of Total Population: This column displays the percentage distribution of each race as a proportion of London total 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 London Population by Race & Ethnicity. You can refer the same here

Institute for the Study of Contemporary Antisemitism (ISCA) at Indiana University Dataset on bias against Asians, Blacks, Jews, Latines, and Muslims

About this dataset

Context

The dataset tabulates the population of United States by race. It includes the population of United States across racial categories (excluding ethnicity) as identified by the Census Bureau. The dataset can be utilized to understand the population distribution of United States across relevant racial categories.

Key observations

The percent distribution of United States population by race (across all racial categories recognized by the U.S. Census Bureau): 65.88% are white, 12.47% are Black or African American, 0.84% are American Indian and Alaska Native, 5.77% are Asian, 0.19% are Native Hawaiian and other Pacific Islander, 6.05% are some other race and 8.80% are multiracial.

Content

When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2018-2022 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 (excluding ethnicity) for the United States
• Population: The population of the racial category (excluding ethnicity) 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 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