Estonia - Distribution of population by household types: Single person was 22.30% in December of 2024, according to the EUROSTAT. Trading Economics provides the current actual value, an historical data chart and related indicators for Estonia - Distribution of population by household types: Single person - last updated from the EUROSTAT on July of 2025. Historically, Estonia - Distribution of population by household types: Single person reached a record high of 22.30% in December of 2024 and a record low of 15.00% in December of 2009.

Working with partners across NIH, led by NIMHD and the NLM OBSSR-Behavioral Ontology Working Group, MeSH on November 29, 2022 added Federally recognized American Indian and Alaskan Native (AI/AN) tribal names and ethnic/ethnolinguistic minority terms as newly created type 5 SCR designated as “Population Groups”. These minority names (1,700+ terms) were mapped and reviewed by subject matter experts and scientists within NIH and from outside including Network of the National Library of Medicine members.

Structure: All type 5 SCRs have common fields 1. CC=5 Population Group 2. ST=T098 Population Groups 3. HM= At least one HM is to an MH under Population Groups [M01.686] 4. TH= NIMHD(2023)

This web map shows the Population distribution by quarter type in 2016 within the 18 districts of Hong Kong. It is a subset of the census data 2016 made available by the Census and Statistics Department under the Government of Hong Kong Special Administrative Region (the “Government”) at https://DATA.GOV.HK/ (“DATA.GOV.HK”). The source data is in XLSX format and has been processed and converted into Esri File Geodatabase format and then uploaded to Esri’s ArcGIS Online platform for sharing and reference purpose. The objectives are to facilitate our Hong Kong ArcGIS Online users to use the data in a spatial ready format and save their data conversion effort.For details about the data, source format and terms of conditions of usage, please refer to the website of DATA.GOV.HK at https://data.gov.hk.

About this dataset

Context

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

Key observations

Of the Non-Hispanic population in Hermosa Beach, the largest racial group is White alone with a population of 14,018 (80.80% of the total Non-Hispanic population).

Content

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

Racial categories include:

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

Variables / Data Columns

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

As a source of animal and plant population data, the Global Population Dynamics Database (GPDD) is unrivalled. Nearly five thousand separate time series are available here. In addition to all the population counts, there are taxonomic details of over 1400 species. The type of data contained in the GPDD varies enormously, from annual counts of mammals or birds at individual sampling sites, to weekly counts of zooplankton and other marine fauna. The project commenced in October 1994, following discussions on ways in which the collaborating partners could make a practical and enduring contribution to research into population dynamics. A small team was assembled and, with assistance and advice from numerous interested parties we decided to construct the database using the popular Microsoft Access platform. After an initial design phase, the major task has been that of locating, extracting, entering and validating the data in all the various tables. Now, nearly 5000 individual datasets have been entered onto the GPDD. The Global Population Dynamics Database comprises six Tables of data and information. The tables are linked to each other as shown in the diagram shown in figure 3 of the GPDD User Guide (GPDD-User-Guide.pdf). Referential integrity is maintained through record ID numbers which are held, along with other information in the Main Table. It's structure obeys all the rules of a standard relational database.

Spain - Distribution of population by household types: Single person was 11.30% in December of 2024, according to the EUROSTAT. Trading Economics provides the current actual value, an historical data chart and related indicators for Spain - Distribution of population by household types: Single person - last updated from the EUROSTAT on June of 2025. Historically, Spain - Distribution of population by household types: Single person reached a record high of 11.30% in December of 2024 and a record low of 8.40% in December of 2009.

Finland - Distribution of population by household types: Single person was 25.80% in December of 2024, according to the EUROSTAT. Trading Economics provides the current actual value, an historical data chart and related indicators for Finland - Distribution of population by household types: Single person - last updated from the EUROSTAT on July of 2025. Historically, Finland - Distribution of population by household types: Single person reached a record high of 25.80% in December of 2024 and a record low of 19.00% in December of 2010.

In Sweden, the most common type of household in 2022 was cohabiting people with children aged zero to 24 years. Over 1.9 million women and two million men lived in this type of household. Moreover, nearly 1.2 million men and the same number of women were cohabiting or married without children. Of the singles with children between zero and 24 years, there were significantly more women than men.

Demographic data are important to wildlife managers to gauge population health, to allow populations to be utilised sustainably, and to inform conservation efforts. We analysed published demographic data on the world’s wildfowl to examine taxonomic and geographic biases in study, and to identify gaps in knowledge. Wildfowl (order: Anseriformes) are a comparatively well studied bird group which includes 169 species of duck, goose and swan. In all, 1,586 wildfowl research papers published between 1911 and 2010 were found using Web of Knowledge (WoK) and Google Scholar. Over half of the research output involved just 15 species from seven genera. Research output was strongly biased towards ‘high income’ countries, common wildfowl species, and measures of productivity, rather than survival and movement patterns. There were significantly fewer demographic data for the world’s 31 threatened wildfowl species than for non-threatened species. Since 1994, the volume of demographic work on threatened species has increased more than for non-threatened species, but still makes up only 2.7% of total research output. As an aid to research prioritisation, a metric was created to reflect demographic knowledge gaps for each species related to research output for the species, its threat status, and availability of potentially useful surrogate data from congeneric species. According to the metric, the 25 highest priority species include thirteen threatened taxa and nine species each from Asia and South America, and six from Africa.

Table from the American Community Survey (ACS) 5-year series on household types and population related topics for City of Seattle Council Districts, Comprehensive Plan Growth Areas and Community Reporting Areas. Table includes B11003 Family Type by Presence and Age of Own Children under 18 Years, B11005 Households by Presence of People Under 18 Years by Household Type, B11007 Households by Presence of People 65 Years and Over by Household Type, B11001 Household Type (Including Living Alone), B11002 Household Type by Relatives and Nonrelatives for Population in Households, B25003 Tenure, B25008 Total Population in Occupied Housing Units by Tenure, B09019 Household Type (Including Living Alone) by Relationship. Data is pulled from block group tables for the most recent ACS vintage and summarized to the neighborhoods based on block group assignment.

About this dataset

Context

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

Key observations

The percent distribution of Rosemead population by race (across all racial categories recognized by the U.S. Census Bureau): 10.17% are white, 0.46% are Black or African American, 0.93% are American Indian and Alaska Native, 64.45% are Asian, 0.01% are Native Hawaiian and other Pacific Islander, 20.13% are some other race and 3.85% are multiracial.

https://i.neilsberg.com/ch/rosemead-ca-population-by-race.jpeg" alt="Rosemead 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 Rosemead
• Population: The population of the racial category (excluding ethnicity) in the Rosemead is shown in this column.
• % of Total Population: This column displays the percentage distribution of each race as a proportion of Rosemead 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 Rosemead Population by Race & Ethnicity. You can refer the same here

Although the American Community Survey (ACS) produces population, demographic and housing unit estimates, the decennial census is the official source of population totals for April 1st of each decennial year. In between censuses, the Census Bureau's Population Estimates Program produces and disseminates the official estimates of the population for the nation, states, counties, cities, and towns and estimates of housing units and the group quarters population for states and counties..Information about the American Community Survey (ACS) can be found on the ACS website. Supporting documentation including code lists, subject definitions, data accuracy, and statistical testing, and a full list of ACS tables and table shells (without estimates) can be found on the Technical Documentation section of the ACS website.Sample size and data quality measures (including coverage rates, allocation rates, and response rates) can be found on the American Community Survey website in the Methodology section..Source: U.S. Census Bureau, 2019-2023 American Community Survey 5-Year Estimates.ACS data generally reflect the geographic boundaries of legal and statistical areas as of January 1 of the estimate year. For more information, see Geography Boundaries by Year..Data are based on a sample and are subject to sampling variability. The degree of uncertainty for an estimate arising from sampling variability is represented through the use of a margin of error. The value shown here is the 90 percent margin of error. The margin of error can be interpreted roughly as providing a 90 percent probability that the interval defined by the estimate minus the margin of error and the estimate plus the margin of error (the lower and upper confidence bounds) contains the true value. In addition to sampling variability, the ACS estimates are subject to nonsampling error (for a discussion of nonsampling variability, see ACS Technical Documentation). The effect of nonsampling error is not represented in these tables..Users must consider potential differences in geographic boundaries, questionnaire content or coding, or other methodological issues when comparing ACS data from different years. Statistically significant differences shown in ACS Comparison Profiles, or in data users' own analysis, may be the result of these differences and thus might not necessarily reflect changes to the social, economic, housing, or demographic characteristics being compared. For more information, see Comparing ACS Data..Data about computer and Internet use were collected by asking respondents to select "Yes" or "No" to each type of computer and each type of Internet subscription. Therefore, respondents were able to select more than one type of computer and more than one type of Internet subscription..The category "Has one or more types of computing devices" refers to those who said "Yes" to at least one of the following types of computers: Desktop or laptop; smartphone; tablet or other portable wireless computer; or some other type of computer. The category "No computer" consists of those who said "No" to all of these types of computers.."Desktop or laptop" refers to those who selected that category regardless of whether or not they indicated they also had another type of computer. However, "Desktop or laptop with no other type of computing device" refers to those who said "Yes" to owning or using a desktop or laptop and "No" to smartphone, tablet or other wireless computer, and other computer. Similarly, the same holds true for "Smartphone" compared to "Smartphone with no other type of computing device", "Tablet or other portable wireless computer" compared to "Tablet or other portable wireless computer with no other type of computing device", and "Other computer" compared to "Other computer with no other type of computing device.".Caution should be used when comparing data for computer and Internet use before and after 2016. Changes in 2016 to the questions involving the wording as well as the response options resulted in changed response patterns in the data. Most noticeable are increases in overall computer ownership or use, the total of Internet subscriptions, satellite subscriptions, and cellular data plans for a smartphone or other mobile device. For more detailed information about these changes, see the 2016 American Community Survey Content Test Report for Computer and Internet Use located at https://www.census.gov/library/working-papers/2017/acs/2017_Lewis_01.html or the user note regarding changes in the 2016 questions located at https://www.census.gov/programs-surveys/acs/technical-documentation/user-notes/2017-03.html..Estimates of urban and rural populations, housing units, and characteristics reflect boundaries of urban areas defined based on 2020 Census data. As a result, data for urban and rural areas from the ACS do not necessarily reflect the results of ongoing urbanization..Explanation of Symbols:- The estimate could not be computed becau...

About this dataset

Context

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

Key observations

Of the Non-Hispanic population in Mountain Home, the largest racial group is White alone with a population of 11,612 (85.84% 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 Mountain Home
• Population: The population of the racial category (for Non-Hispanic) in the Mountain Home is shown in this column.
• % of Total Population: This column displays the percentage distribution of each race as a proportion of Mountain Home 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 Mountain Home Population by Race & Ethnicity. You can refer the same here

This layer shows the Hong Kong Population Distribution by Housing Type by Small Tertiary Planning Unit Group in 2021. It is a subset of the 2021 Population Census made available by the Census and Statistics Department under the Government of Hong Kong Special Administrative Region (the "Government") at https://portal.csdi.gov.hk ("CSDI Portal"). The source data is in CSV format and has been processed and converted into Esri File Geodatabase format and then uploaded to Esri’s ArcGIS Online platform for sharing and reference purpose. The objectives are to facilitate our Hong Kong ArcGIS Online users to use the data in a spatial ready format and save their data conversion effort.For details about the data, source format and terms of conditions of usage, please refer to the website of CSDI Portal at https://portal.csdi.gov.hk.

Although the American Community Survey (ACS) produces population, demographic and housing unit estimates, the decennial census is the official source of population totals for April 1st of each decennial year. In between censuses, the Census Bureau's Population Estimates Program produces and disseminates the official estimates of the population for the nation, states, counties, cities, and towns and estimates of housing units and the group quarters population for states and counties..Information about the American Community Survey (ACS) can be found on the ACS website. Supporting documentation including code lists, subject definitions, data accuracy, and statistical testing, and a full list of ACS tables and table shells (without estimates) can be found on the Technical Documentation section of the ACS website.Sample size and data quality measures (including coverage rates, allocation rates, and response rates) can be found on the American Community Survey website in the Methodology section..Source: U.S. Census Bureau, 2023 American Community Survey 1-Year Estimates.ACS data generally reflect the geographic boundaries of legal and statistical areas as of January 1 of the estimate year. For more information, see Geography Boundaries by Year..Data are based on a sample and are subject to sampling variability. The degree of uncertainty for an estimate arising from sampling variability is represented through the use of a margin of error. The value shown here is the 90 percent margin of error. The margin of error can be interpreted roughly as providing a 90 percent probability that the interval defined by the estimate minus the margin of error and the estimate plus the margin of error (the lower and upper confidence bounds) contains the true value. In addition to sampling variability, the ACS estimates are subject to nonsampling error (for a discussion of nonsampling variability, see ACS Technical Documentation). The effect of nonsampling error is not represented in these tables..Users must consider potential differences in geographic boundaries, questionnaire content or coding, or other methodological issues when comparing ACS data from different years. Statistically significant differences shown in ACS Comparison Profiles, or in data users' own analysis, may be the result of these differences and thus might not necessarily reflect changes to the social, economic, housing, or demographic characteristics being compared. For more information, see Comparing ACS Data..Data about computer and Internet use were collected by asking respondents to select "Yes" or "No" to each type of computer and each type of Internet subscription. Therefore, respondents were able to select more than one type of computer and more than one type of Internet subscription..The category "Has one or more types of computing devices" refers to those who said "Yes" to at least one of the following types of computers: Desktop or laptop; smartphone; tablet or other portable wireless computer; or some other type of computer. The category "No computer" consists of those who said "No" to all of these types of computers.."Desktop or laptop" refers to those who selected that category regardless of whether or not they indicated they also had another type of computer. However, "Desktop or laptop with no other type of computing device" refers to those who said "Yes" to owning or using a desktop or laptop and "No" to smartphone, tablet or other wireless computer, and other computer. Similarly, the same holds true for "Smartphone" compared to "Smartphone with no other type of computing device", "Tablet or other portable wireless computer" compared to "Tablet or other portable wireless computer with no other type of computing device", and "Other computer" compared to "Other computer with no other type of computing device.".Estimates of urban and rural populations, housing units, and characteristics reflect boundaries of urban areas defined based on 2020 Census data. As a result, data for urban and rural areas from the ACS do not necessarily reflect the results of ongoing urbanization..Explanation of Symbols:- The estimate could not be computed because there were an insufficient number of sample observations. For a ratio of medians estimate, one or both of the median estimates falls in the lowest interval or highest interval of an open-ended distribution. For a 5-year median estimate, the margin of error associated with a median was larger than the median itself.N The estimate or margin of error cannot be displayed because there were an insufficient number of sample cases in the selected geographic area. (X) The estimate or margin of error is not applicable or not available.median- The median falls in the lowest interval of an open-ended distribution (for example "2,500-")median+ The median falls in the highest interval of an open-ended distribution (for example "250,000+").** The margin of error could not be computed because there were an insufficient n...

Population by region, sex and type of locality, Total Country (2010)

About this dataset

Context

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

Key observations

The percent distribution of Las Vegas population by race (across all racial categories recognized by the U.S. Census Bureau): 45.52% are white, 1.79% are Black or African American, 2.77% are American Indian and Alaska Native, 0.31% are Asian, 21.09% are some other race and 28.52% 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 Las Vegas
• Population: The population of the racial category (excluding ethnicity) in the Las Vegas is shown in this column.
• % of Total Population: This column displays the percentage distribution of each race as a proportion of Las Vegas 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 Las Vegas Population by Race & Ethnicity. You can refer the same here

The statistic displays the disabled population in India in 2011, by type of disability and gender. In that year, the male and female disability in seeing was 2.6 million and 2.3 million respectively. Mental illness had lesser males and females affected than other disabilities.

The statistic for disability-adjusted life years attributable to disorders worldwide in 2004 can be found here.

Living Conditions Survey (LCS): Distribution of the total population and the poor population broken down by household's work intensity. National.

Population Projections: Dependency rate of the population over 64 years of age per year. Annual. Provinces.