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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.
When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 5-Year Estimates, including:
Variables / Data Columns
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.
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/.
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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.
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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.
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
This dataset was collected from: https://www.worldometers.info/coronavirus/#countries
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!
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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.
When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 5-Year Estimates, including:
Variables / Data Columns
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.
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/.
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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.
When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 5-Year Estimates, including:
Variables / Data Columns
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.
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/.
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TwitterWorldPop Asia dataset details_DATASET: Alpha version 2010, 2015 and 2010 estimates of numbers of people per pixel (ppp) and people per hectare (pph), with national totals adjusted to match UN population division estimates (http://esa.un.org/wpp/) and remaining unadjusted.REGION: AsiaSPATIAL RESOLUTION: 0.000833333 decimal degrees (approx 100m at the equator)PROJECTION: Geographic, WGS 84UNITS: Estimated persons per grid squareMAPPING APPROACH: Random ForestFORMAT: Geotiff (zipped using 7-zip (open access tool): www.7-zip.org)FILENAMES: Example - ARM_ppp_v2c_2010_UNadj.tif = Armenia (ARM) population per pixel (ppp) modelling version 2c (v2c) map for 2010 (2010) adjusted to match UN national estimates (UNadj).DATE OF PRODUCTION: May 2016Also included: (i) Metadata html file, (ii) Population datasets produced using original census year data, (iii).kmz Google Earth file.
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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.
When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 5-Year Estimates, including:
Variables / Data Columns
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.
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/.
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Relative concentration of the Southern 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 13,312 block groups in the Southern 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 Southern 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.
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TwitterThe world population surpassed eight billion people in 2022, having doubled from its figure less than 50 years previously. Looking forward, it is projected that the world population will reach nine billion in 2038, and 10 billion in 2060, but it will peak around 10.3 billion in the 2080s before it then goes into decline. Regional variations The global population has seen rapid growth since the early 1800s, due to advances in areas such as food production, healthcare, water safety, education, and infrastructure, however, these changes did not occur at a uniform time or pace across the world. Broadly speaking, the first regions to undergo their demographic transitions were Europe, North America, and Oceania, followed by Latin America and Asia (although Asia's development saw the greatest variation due to its size), while Africa was the last continent to undergo this transformation. Because of these differences, many so-called "advanced" countries are now experiencing population decline, particularly in Europe and East Asia, while the fastest population growth rates are found in Sub-Saharan Africa. In fact, the roughly two billion difference in population between now and the 2080s' peak will be found in Sub-Saharan Africa, which will rise from 1.2 billion to 3.2 billion in this time (although populations in other continents will also fluctuate). Changing projections The United Nations releases their World Population Prospects report every 1-2 years, and this is widely considered the foremost demographic dataset in the world. However, recent years have seen a notable decline in projections when the global population will peak, and at what number. Previous reports in the 2010s had suggested a peak of over 11 billion people, and that population growth would continue into the 2100s, however a sooner and shorter peak is now projected. Reasons for this include a more rapid population decline in East Asia and Europe, particularly China, as well as a prolonged development arc in Sub-Saharan Africa.
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TwitterUse 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 Bureauās 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 ā A person having origins in any of the original peoples of Europe, the Middle East, or North Africa.Black or African American ā A person having origins in any of the Black racial groups of Africa.American Indian or Alaska Native ā 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 ā 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 ā 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.
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This list ranks the 269 cities in the South Carolina by Asian population, as estimated by the United States Census Bureau. It also highlights population changes in each cities over the past five years.
When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 5-Year Estimates, including:
Variables / Data Columns
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.
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/.
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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.
When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 5-Year Estimates, including:
Variables / Data Columns
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.
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/.
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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)
| Key | List of... | Comment | Example Value |
|---|---|---|---|
| County | String | County name | "Abbeville County" |
| State | String | State name | "SC" |
| Age.Percent 65 and Older | Float | Estimated percentage of population whose ages are equal or greater than 65 years old are produced for the United States states and counties as well as for the Commonwealth of Puerto Rico and its municipios (county-equivalents for Puerto Rico). | 22.4 |
| Age.Percent Under 18 Years | Float | Estimated percentage of population whose ages are under 18 years old are produced for the United States states and counties as well as for the Commonwealth of Puerto Rico and its municipios (county-equivalents for Puerto Rico). | 19.8 |
| Age.Percent Under 5 Years | Float | Estimated percentage of population whose ages are under 5 years old are produced for the United States states and counties as well as for the Commonwealth of Puerto Rico and its municipios (county-equivalents for Puerto Rico). | 4.7 |
| Education.Bachelor's Degree or Higher | Float | Percentage for the people who attended college but did not receive a degree and people who received an associate's bachelor's master's or professional or doctorate degree. These data include only persons 25 years old and over. The percentages are obtained by dividing the counts of graduates by the total number of persons 25 years old and over. Tha data is collected from 2015 to 2019. | 15.6 |
| Education.High School or Higher | Float | Percentage of people whose highest degree was a high school diploma or its equivalent people who attended college but did not receive a degree and people who received an associate's bachelor's master's or professional or doctorate degree. These data include only persons 25 years old and over. The percentages are obtained by dividing the counts of graduates by the total number of persons 25 years old and over. Tha data is collected from 2015 to 2019 | 81.7 |
| Employment.Nonemployer Establishments | Integer | An establishment is a single physical location at which business is conducted or where services or industrial operations are performed. It is not necessarily identical with a company or enterprise which may consist of one establishment or more. The data was collected from 2018. | 1416 |
| Ethnicities.American Indian and Alaska Native Alone | Float | Estimated percentage of population having origins in any of the original peoples of North and South America (including Central America) and who maintains tribal affiliation or community attachment. This category includes people who indicate their race as "American Indian or Alaska Native" or report entries such as Navajo Blackfeet Inupiat Yup'ik or Central American Indian groups or South American Indian groups. | 0.3 |
| Ethnicities.Asian Alone | Float | Estimated percentage of population 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. This includes people who reported detailed Asian responses such as: "Asian Indian " "Chinese " "Filipino " "Korean " "Japanese " "Vietnamese " and "Other Asian" or provide other detailed Asian responses. | 0.4 |
| Ethnicities.Black Alone | Float | Estimated percentage of population having origins in any of the Black racial groups of Africa. It includes people who indicate their race as "Black or African American " or report entries such as African American Kenyan Nigerian or Haitian. | 27.6 |
| Ethnicities.Hispanic or Latino | Float |
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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.
The dataset comprises over 5,000 high-quality facial images, organized into participant-wise sets. Each set includes:
To ensure robustness and real-world utility, images were captured under diverse conditions:
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.
This dataset is ideal for a wide range of real-world and research-focused applications, including:
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Dataset contains ethnic group census usually resident population counts from the 2013, 2018, and 2023 Censuses, as well as the percentage change in the ethnic group population count between the 2013 and 2018 Censuses, and between the 2018 and 2023 Censuses. Data is available by regional council.
The ethnic groups are:
Map shows percentage change in the census usually resident population count for ethnic groups between the 2018 and 2023 Censuses.
Download lookup file from Stats NZ ArcGIS Online or embedded attachment in Stats NZ geographic data service. Download data table (excluding the geometry column for CSV files) using the instructions in the Koordinates help guide.
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Footnotes
Geographical boundaries
Statistical standard for geographic areas 2023 (updated December 2023) has information about geographic boundaries as of 1 January 2023. Address data from 2013 and 2018 Censuses was updated to be consistent with the 2023 areas. Due to the changes in area boundaries and coding methodologies, 2013 and 2018 counts published in 2023 may be slightly different to those published in 2013 or 2018.
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Subnational census usually resident population
The census usually resident population count of an area (subnational count) is a count of all people who usually live in that area and were present in New Zealand on census night. It excludes visitors from overseas, visitors from elsewhere in New Zealand, and residents temporarily overseas on census night. For example, a person who usually lives in Christchurch city and is visiting Wellington city on census night will be included in the census usually resident population count of Christchurch city.
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Caution using time series
Time series data should be interpreted with care due to changes in census methodology and differences in response rates between censuses. The 2023 and 2018 Censuses used a combined census methodology (using census responses and administrative data), while the 2013 Census used a full-field enumeration methodology (with no use of administrative data).
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About the 2023 Census dataset
For information on the 2023 dataset see Using a combined census model for the 2023 Census. We combined data from the census forms with administrative data to create the 2023 Census dataset, which meets Stats NZ's quality criteria for population structure information. We added real data about real people to the dataset where we were confident the people who hadnāt completed a census form (which is known as admin enumeration) will be counted. We also used data from the 2018 and 2013 Censuses, administrative data sources, and statistical imputation methods to fill in some missing characteristics of people and dwellings.
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Data quality
The quality of data in the 2023 Census is assessed using the quality rating scale and the quality assurance framework to determine whether data is fit for purpose and suitable for release. Data quality assurance in the 2023 Census has more information.
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Quality rating of a variable
The quality rating of a variable provides an overall evaluation of data quality for that variable, usually at the highest levels of classification. The quality ratings shown are for the 2023 Census unless stated. There is variability in the quality of data at smaller geographies. Data quality may also vary between censuses, for subpopulations, or when cross tabulated with other variables or at lower levels of the classification. Data quality ratings for 2023 Census variables has more information on quality ratings by variable.
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Ethnicity concept quality rating
Ethnicity is rated as high quality.
Ethnicity ā 2023 Census: Information by concept has more information, for example, definitions and data quality.
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Using data for good
Stats NZ expects that, when working with census data, it is done so with a positive purpose, as outlined in the MÄori Data Governance Model (Data Iwi Leaders Group, 2023). This model states that "data should support transformative outcomes and should uplift and strengthen our relationships with each other and with our environments. The avoidance of harm is the minimum expectation for data use. MÄori data should also contribute to iwi and hapÅ« tino rangatiratangaā.
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Confidentiality
The 2023 Census confidentiality rules have been applied to 2013, 2018, and 2023 data. These rules protect the confidentiality of individuals, families, households, dwellings, and undertakings in 2023 Census data. Counts are calculated using fixed random rounding to base 3 (FRR3) and suppression of āsensitiveā counts less than six, where tables report multiple geographic variables and/or small populations. Individual figures may not always sum to stated totals. Applying confidentiality rules to 2023 Census data and summary of changes since 2018 and 2013 Censuses has more information about 2023 Census confidentiality rules.
ā
Symbol
-998 Not applicable
ā
Percentages
To calculate percentages, divide the figure for the category of interest by the figure for āTotal statedā where this applies.
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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.
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:
Variables / Data Columns
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.
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 is a part of the main dataset for Fernandina Beach Population by Race & Ethnicity. You can refer the same here
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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">
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:
Variables / Data Columns
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.
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 is a part of the main dataset for London Population by Race & Ethnicity. You can refer the same here
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RCS data Asia is essential if youāre considering implementing telemarketing or SMS marketing for your organization. It is an accurate and actual mobile number database. As we know Asia is the worldās biggest continent. Also, the maximum number of people use phones in this area. Here the RCS database can play a crucial factor any day. Again, this new type brought by Google message will grow more very soon. So, consider this RCS data Asia as soon as you can and step forward with your business. RCS data Asia offers you clean and fresh contacts to promote your company all across the continent. All our information comes from various trusted sources and is verified by our team. Therefore, this number list offers fantastic features to reach many consumers. Similar to others, this database can be accessed via long-distance and international calls and messages in order to promote your goods and services through telemarketing and cold-calling campaigns. Asia RCS data will help you on so many occasions. Talk to our data expert if you want to build a targeted phone list. You can find all the most recent, accurate lists of mobile phone numbers here. No matter what type of business you own, these contacts will undoubtedly help you. With the help of this dataset, you may grow your company and manage it more productively. In the end, Asia RCS data contains thousands of updated and genuine contacts. This is a one-time payment and an instant downloadable software which can be an Excel or CSV file type. We will provide everything you need for your product advertising. Moreover, the Asia RCS data has 95% correct data collected by our personnel. So, if you are here then buy the library and promote your business and service all over Asia.
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This list ranks the 1299 cities in the Illinois by Hispanic Asian population, as estimated by the United States Census Bureau. It also highlights population changes in each cities over the past five years.
When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 5-Year Estimates, including:
Variables / Data Columns
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.
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/.
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The dataset tabulates the population of Greenland by race. It includes the population of Greenland across racial categories (excluding ethnicity) as identified by the Census Bureau. The dataset can be utilized to understand the population distribution of Greenland across relevant racial categories.
Key observations
The percent distribution of Greenland population by race (across all racial categories recognized by the U.S. Census Bureau): 79.14% are white, 7.06% are Black or African American, 0.99% are American Indian and Alaska Native, 0.15% are Asian, 0.83% are some other race and 11.84% are multiracial.
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:
Variables / Data Columns
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.
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 is a part of the main dataset for Greenland Population by Race & Ethnicity. You can refer the same here
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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.
When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 5-Year Estimates, including:
Variables / Data Columns
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.
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/.