The graph shows the changes in the impact factor of ^ and its corresponding percentile for the sake of comparison with the entire literature. Impact Factor is the most common scientometric index, which is defined by the number of citations of papers in two preceding years divided by the number of papers published in those years.

Race and Etnicity:Percent Asian Alone: Basic demographics by census tracts in King County based on current American Community Survey 5 Year Average (ACS). Included demographics are: total population; foreign born; median household income; English language proficiency; languages spoken; race and ethnicity; sex; and age. 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.

Graph and download economic data for Consumer Unit Characteristics: Percent White, Asian, and All Other Races, Not Including African American by Number of Earners: Consumer Units of Two or More People, One Earner (CXUWHTNDOTHLB0705M) from 1984 to 2023 about asian, consumer unit, white, percent, persons, consumer, and USA.

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

This indicator shows the number of persons in each of the API races.

*Note: These numbers may include Hispanic and Non-Hispanic Asian/Pacific Islanders.

Source: U.S. Census Bureau; 2013-2017 American Community Survey 5-Year Estimates, Table B02015, B02016.

Splitgraph serves as an HTTP API that lets you run SQL queries directly on this data to power Web applications. For example:

See the Splitgraph documentation for more information.

About this dataset

Context

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

Key observations

The percent distribution of Los Angeles population by race (across all racial categories recognized by the U.S. Census Bureau): 37.32% are white, 8.51% are Black or African American, 1.16% are American Indian and Alaska Native, 12.03% are Asian, 0.15% are Native Hawaiian and other Pacific Islander, 25.09% are some other race and 15.74% 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 Los Angeles
• Population: The population of the racial category (excluding ethnicity) in the Los Angeles is shown in this column.
• % of Total Population: This column displays the percentage distribution of each race as a proportion of Los Angeles 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 Los Angeles Population by Race & Ethnicity. You can refer the same 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.

About this dataset

Context

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

Key observations

The percent distribution of Los Altos population by race (across all racial categories recognized by the U.S. Census Bureau): 51.77% are white, 0.97% are Black or African American, 0.07% are American Indian and Alaska Native, 37.51% are Asian, 1.94% are some other race and 7.74% 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 Los Altos
• Population: The population of the racial category (excluding ethnicity) in the Los Altos is shown in this column.
• % of Total Population: This column displays the percentage distribution of each race as a proportion of Los Altos 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 Los Altos Population by Race & Ethnicity. You can refer the same here

This layer was developed by the Research & Analytics Group of the Atlanta Regional Commission, using data from the U.S. Census Bureau’s American Community Survey 5-year estimates for 2013-2017, to show population by race/ethnicity and change data by county in the Atlanta region. The user should note that American Community Survey data represent estimates derived from a surveyed sample of the population, which creates some level of uncertainty, as opposed to an exact measure of the entire population (the full census count is only conducted once every 10 years and does not cover as many detailed characteristics of the population). Therefore, any measure reported by ACS should not be taken as an exact number – this is why a corresponding margin of error (MOE) is also given for ACS measures. The size of the MOE relative to its corresponding estimate value provides an indication of confidence in the accuracy of each estimate. Each MOE is expressed in the same units as its corresponding measure; for example, if the estimate value is expressed as a number, then its MOE will also be a number; if the estimate value is expressed as a percent, then its MOE will also be a percent. The user should also note that for relatively small geographic areas, such as census tracts shown here, ACS only releases combined 5-year estimates, meaning these estimates represent rolling averages of survey results that were collected over a 5-year span (in this case 2013-2017). Therefore, these data do not represent any one specific point in time or even one specific year. For geographic areas with larger populations, 3-year and 1-year estimates are also available. For further explanation of ACS estimates and margin of error, visit Census ACS website. Naming conventions: Prefixes:NoneCountpPercentrRatemMedianaMean (average)tAggregate (total)chChange in absolute terms (value in t2 - value in t1)pchPercent change ((value in t2 - value in t1) / value in t1)chpChange in percent (percent in t2 - percent in t1)Suffixes:NoneChange over two periods_eEstimate from most recent ACS_mMargin of Error from most recent ACS_00Decennial 2000 Attributes: SumLevelSummary level of geographic unit (e.g., County, Tract, NSA, NPU, DSNI, SuperDistrict, etc)GEOIDCensus tract Federal Information Processing Series (FIPS) code NAMEName of geographic unitPlanning_RegionPlanning region designation for ARC purposesAcresTotal area within the tract (in acres)SqMiTotal area within the tract (in square miles)CountyCounty identifier (combination of Federal Information Processing Series (FIPS) codes for state and county)CountyNameCounty NameTotPop_e# Total population, 2017TotPop_m# Total population, 2017 (MOE)Hisp_e# Hispanic or Latino (of any race), 2017Hisp_m# Hispanic or Latino (of any race), 2017 (MOE)pHisp_e% Hispanic or Latino (of any race), 2017pHisp_m% Hispanic or Latino (of any race), 2017 (MOE)Not_Hisp_e# Not Hispanic or Latino, 2017Not_Hisp_m# Not Hispanic or Latino, 2017 (MOE)pNot_Hisp_e% Not Hispanic or Latino, 2017pNot_Hisp_m% Not Hispanic or Latino, 2017 (MOE)NHWhite_e# Not Hispanic, White alone, 2017NHWhite_m# Not Hispanic, White alone, 2017 (MOE)pNHWhite_e% Not Hispanic, White alone, 2017pNHWhite_m% Not Hispanic, White alone, 2017 (MOE)NHBlack_e# Not Hispanic, Black or African American alone, 2017NHBlack_m# Not Hispanic, Black or African American alone, 2017 (MOE)pNHBlack_e% Not Hispanic, Black or African American alone, 2017pNHBlack_m% Not Hispanic, Black or African American alone, 2017 (MOE)NH_AmInd_e# Not Hispanic, American Indian and Alaska Native alone, 2017NH_AmInd_m# Not Hispanic, American Indian and Alaska Native alone, 2017 (MOE)pNH_AmInd_e% Not Hispanic, American Indian and Alaska Native alone, 2017pNH_AmInd_m% Not Hispanic, American Indian and Alaska Native alone, 2017 (MOE)NH_Asian_e# Not Hispanic, Asian alone, 2017NH_Asian_m# Not Hispanic, Asian alone, 2017 (MOE)pNH_Asian_e% Not Hispanic, Asian alone, 2017pNH_Asian_m% Not Hispanic, Asian alone, 2017 (MOE)NH_PacIsl_e# Not Hispanic, Native Hawaiian and Other Pacific Islander alone, 2017NH_PacIsl_m# Not Hispanic, Native Hawaiian and Other Pacific Islander alone, 2017 (MOE)pNH_PacIsl_e% Not Hispanic, Native Hawaiian and Other Pacific Islander alone, 2017pNH_PacIsl_m% Not Hispanic, Native Hawaiian and Other Pacific Islander alone, 2017 (MOE)NH_OthRace_e# Not Hispanic, some other race alone, 2017NH_OthRace_m# Not Hispanic, some other race alone, 2017 (MOE)pNH_OthRace_e% Not Hispanic, some other race alone, 2017pNH_OthRace_m% Not Hispanic, some other race alone, 2017 (MOE)NH_TwoRace_e# Not Hispanic, two or more races, 2017NH_TwoRace_m# Not Hispanic, two or more races, 2017 (MOE)pNH_TwoRace_e% Not Hispanic, two or more races, 2017pNH_TwoRace_m% Not Hispanic, two or more races, 2017 (MOE)NH_AsianPI_e# Non-Hispanic Asian or Pacific Islander, 2017NH_AsianPI_m# Non-Hispanic Asian or Pacific Islander, 2017 (MOE)pNH_AsianPI_e% Non-Hispanic Asian or Pacific Islander, 2017pNH_AsianPI_m% Non-Hispanic Asian or Pacific Islander, 2017 (MOE)NH_Other_e# Non-Hispanic other (Native American, other one race, two or more races), 2017NH_Other_m# Non-Hispanic other (Native American, other one race, two or more races), 2017 (MOE)pNH_Other_e% Non-Hispanic other (Native American, other one race, two or more races), 2017pNH_Other_m% Non-Hispanic other (Native American, other one race, two or more races), 2017 (MOE)last_edited_dateLast date the feature was edited by ARC Source: U.S. Census Bureau, Atlanta Regional CommissionDate: 2013-2017 For additional information, please visit the Census ACS website.

This graph shows the number of racist hate crimes against people of Asian ethnicity in Northern Ireland from 2007/08 to 2017/18. The number of offences declined steadily from 2007/08 to 2012/13, when a minimum was reached. Thereafter, the crime rate began to rise sharply. In 2017/18 there were ** rate crimes reported against people with Asian ethnicity.

Source: U.S. Census Bureau; 2011-2015 American Community Survey 5-Year Estimates, Table B02015, B02016.

Graph and download economic data for Consumer Unit Characteristics: Number of People in CU by Race: Asian (CXU980010LB0904M) from 2003 to 2023 about asian, consumer unit, persons, and USA.

In the fiscal year of 2019, 21.39 percent of active-duty enlisted women were of Hispanic origin. The total number of active duty military personnel in 2019 amounted to 1.3 million people.

Ethnicities in the United States The United States is known around the world for the diversity of its population. The Census recognizes six different racial and ethnic categories: White American, Native American and Alaska Native, Asian American, Black or African American, Native Hawaiian and Other Pacific Islander. People of Hispanic or Latino origin are classified as a racially diverse ethnicity.

The largest part of the population, about 61.3 percent, is composed of White Americans. The largest minority in the country are Hispanics with a share of 17.8 percent of the population, followed by Black or African Americans with 13.3 percent. Life in the U.S. and ethnicity However, life in the United States seems to be rather different depending on the race or ethnicity that you belong to. For instance: In 2019, native Hawaiians and other Pacific Islanders had the highest birth rate of 58 per 1,000 women, while the birth rae of white alone, non Hispanic women was 49 children per 1,000 women.

The Black population living in the United States has the highest poverty rate with of all Census races and ethnicities in the United States. About 19.5 percent of the Black population was living with an income lower than the 2020 poverty threshold. The Asian population has the smallest poverty rate in the United States, with about 8.1 percent living in poverty.

The median annual family income in the United States in 2020 earned by Black families was about 57,476 U.S. dollars, while the average family income earned by the Asian population was about 109,448 U.S. dollars. This is more than 25,000 U.S. dollars higher than the U.S. average family income, which was 84,008 U.S. dollars.

NELS File with imputed missing cases

Graph and download economic data for Homeownership Rates by Race and Ethnicity: All Other Races: Asian, Native Hawaiian and Pacific Islander Alone in the United States (ANHPIHORUSQ156N) from Q1 2016 to Q2 2025 about native hawaiin, Pacific Islands, asian, homeownership, rate, and USA.

This dataset primarily provides catalog information about the indigenous peoples of Southeast Asia on the Cultural Heritage website.

About this dataset

Context

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

Key observations

Of the Non-Hispanic population in Citrus Heights, the largest racial group is White alone with a population of 58,182 (83.03% 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 Citrus Heights
• Population: The population of the racial category (for Non-Hispanic) in the Citrus Heights is shown in this column.
• % of Total Population: This column displays the percentage distribution of each race as a proportion of Citrus Heights 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 Citrus Heights Population by Race & Ethnicity. You can refer the same here

This data was collected from university students. The study examined ethnic-racial identity's effects on disordered eating and ethnicity. Data was analyzed using SPSS, including the PROCESS macro for moderation analyses.

Biometric Attack Dataset, Asian People

The similar dataset that includes all ethnicities - Anti Spoofing Real Dataset

The dataset for face anti spoofing and face recognition includes images and videos of asian people. 30,600+ photos & video of 15,300 people from 32 countries. All people presented in the dataset are South Asian, East Asian or Middle Asian. The dataset helps in enchancing the performance of the model by providing wider range of data for a specific ethnic group.

The videos were gathered by capturing faces of genuine individuals presenting spoofs, using facial presentations. Our dataset proposes a novel approach that learns and detects spoofing techniques, extracting features from the genuine facial images to prevent the capturing of such information by fake users.

The dataset contains images and videos of real humans with various resolutions, views, and colors, making it a comprehensive resource for researchers working on anti-spoofing technologies.

People in the dataset

https://www.googleapis.com/download/storage/v1/b/kaggle-user-content/o/inbox%2F12421376%2Ff545aa561432738d251c09f09e1f5e92%2FFrame%20104.png?generation=1713356643038606&alt=media" alt="">

Types of files in the dataset:

• photo - selfie of the person
• video - real video of the person

Our dataset also explores the use of neural architectures, such as deep neural networks, to facilitate the identification of distinguishing patterns and textures in different regions of the face, increasing the accuracy and generalizability of the anti-spoofing models.

👉 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
• true_gender - gender of the person
• country - country of the person
• ethnicity - ethnicity of the person
• video_extension - video extensions in the dataset
• video_resolution - video resolution in the dataset
• video_duration - video duration in the dataset
• video_fps - frames per second for video in the dataset
• photo_extension - photo extensions in the dataset
• photo_resolution - photo resolution in the dataset

Statistics for the dataset

https://www.googleapis.com/download/storage/v1/b/kaggle-user-content/o/inbox%2F12421376%2F6de78d350a9213d8437f766b085d4551%2Fasian_video_liveness.png?generation=1713356627116331&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 10 folders corresponding to each person and including 1 image and 1 video, - .csv file - contains information about the files and people in the dataset

File with the extension .csv

• id: id of the person,
• selfie_link: link to access the photo,
• video_link: link to access the video,
• age: age of the person,
• country: country of the person,
• gender: gender of the person,
• video_extension: video extension,
• video_resolution: video resolution,
• video_duration: video duration,
• video_fps: frames per second for video,
• photo_extension: photo extension,
• photo_resolution: photo resolution

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

keywords: liveness detection systems, liveness detection dataset, biometric dataset, biometric data dataset, biometric system attacks, anti-spoofing dataset, face liveness detection, deep learning dataset, face spoofing database, face anti-spoofing, ibeta dataset, face anti spoofing, large-scale face anti spoofing, rich annotations anti spoofing dataset, asian people, asian classification, asian image dataset

About this dataset

Context

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

Key observations

The percent distribution of Many population by race (across all racial categories recognized by the U.S. Census Bureau): 47.54% are white, 48.48% are Black or African American, 1.01% are Asian, 0.23% are some other race and 2.73% 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 Many
• Population: The population of the racial category (excluding ethnicity) in the Many is shown in this column.
• % of Total Population: This column displays the percentage distribution of each race as a proportion of Many 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 Many Population by Race & Ethnicity. You can refer the same here