Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
Context
The dataset tabulates the German town population distribution across 18 age groups. It lists the population in each age group along with the percentage population relative of the total population for German town. The dataset can be utilized to understand the population distribution of German town by age. For example, using this dataset, we can identify the largest age group in German town.
Key observations
The largest age group in German, New York was for the group of age 50 to 54 years years with a population of 35 (14.29%), according to the ACS 2018-2022 5-Year Estimates. At the same time, the smallest age group in German, New York was the 25 to 29 years years with a population of 0 (0%). Source: U.S. Census Bureau American Community Survey (ACS) 2018-2022 5-Year Estimates
When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2018-2022 5-Year Estimates
Age groups:
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 German town Population by Age. You can refer the same here
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
Context
The dataset tabulates the German town population over the last 20 plus years. It lists the population for each year, along with the year on year change in population, as well as the change in percentage terms for each year. The dataset can be utilized to understand the population change of German town across the last two decades. For example, using this dataset, we can identify if the population is declining or increasing. If there is a change, when the population peaked, or if it is still growing and has not reached its peak. We can also compare the trend with the overall trend of United States population over the same period of time.
Key observations
In 2022, the population of German town was 305, a 0.00% decrease year-by-year from 2021. Previously, in 2021, German town population was 305, a decline of 0.97% compared to a population of 308 in 2020. Over the last 20 plus years, between 2000 and 2022, population of German town decreased by 74. In this period, the peak population was 392 in the year 2007. The numbers suggest that the population has already reached its peak and is showing a trend of decline. Source: U.S. Census Bureau Population Estimates Program (PEP).
When available, the data consists of estimates from the U.S. Census Bureau Population Estimates Program (PEP).
Data Coverage:
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 German town Population by Year. You can refer the same here
In 2024, Russia had the largest population among European countries at ***** million people. The next largest countries in terms of their population size were Turkey at **** million, Germany at **** million, the United Kingdom at **** million, and France at **** million. Europe is also home to some of the world’s smallest countries, such as the microstates of Liechtenstein and San Marino, with populations of ****** and ****** respectively. Europe’s largest economies Germany was Europe’s largest economy in 2023, with a Gross Domestic Product of around *** trillion Euros, while the UK and France are the second and third largest economies, at *** trillion and *** trillion euros respectively. Prior to the mid-2000s, Europe’s fourth-largest economy, Italy, had an economy that was of a similar sized to France and the UK, before diverging growth patterns saw the UK and France become far larger economies than Italy. Moscow and Istanbul the megacities of Europe Two cities on the eastern borders of Europe were Europe’s largest in 2023. The Turkish city of Istanbul, with a population of 15.8 million, and the Russian capital, Moscow, with a population of 12.7 million. Istanbul is arguably the world’s most famous transcontinental city with territory in both Europe and Asia and has been an important center for commerce and culture for over 2,000 years. Paris was the third largest European city with a population of ** million, with London being the fourth largest at *** million.
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
Context
The dataset tabulates the German Flatts town population over the last 20 plus years. It lists the population for each year, along with the year on year change in population, as well as the change in percentage terms for each year. The dataset can be utilized to understand the population change of German Flatts town across the last two decades. For example, using this dataset, we can identify if the population is declining or increasing. If there is a change, when the population peaked, or if it is still growing and has not reached its peak. We can also compare the trend with the overall trend of United States population over the same period of time.
Key observations
In 2023, the population of German Flatts town was 12,079, a 0.29% decrease year-by-year from 2022. Previously, in 2022, German Flatts town population was 12,114, a decline of 0.76% compared to a population of 12,207 in 2021. Over the last 20 plus years, between 2000 and 2023, population of German Flatts town decreased by 1,577. In this period, the peak population was 13,656 in the year 2000. The numbers suggest that the population has already reached its peak and is showing a trend of decline. Source: U.S. Census Bureau Population Estimates Program (PEP).
When available, the data consists of estimates from the U.S. Census Bureau Population Estimates Program (PEP).
Data Coverage:
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 German Flatts town Population by Year. You can refer the same here
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
Context
The dataset tabulates the German town population over the last 20 plus years. It lists the population for each year, along with the year on year change in population, as well as the change in percentage terms for each year. The dataset can be utilized to understand the population change of German town across the last two decades. For example, using this dataset, we can identify if the population is declining or increasing. If there is a change, when the population peaked, or if it is still growing and has not reached its peak. We can also compare the trend with the overall trend of United States population over the same period of time.
Key observations
In 2023, the population of German town was 301, a 0.99% decrease year-by-year from 2022. Previously, in 2022, German town population was 304, a decline of 0.33% compared to a population of 305 in 2021. Over the last 20 plus years, between 2000 and 2023, population of German town decreased by 78. In this period, the peak population was 392 in the year 2007. The numbers suggest that the population has already reached its peak and is showing a trend of decline. Source: U.S. Census Bureau Population Estimates Program (PEP).
When available, the data consists of estimates from the U.S. Census Bureau Population Estimates Program (PEP).
Data Coverage:
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 German town Population by Year. You can refer the same here
This statistic shows the size of the urban and rural populations of Germany between 1960 and 2022. Over the years recorded here, the urban population of Germany has increased, while the rural population has declined. The population of Germany has remained at approximately 82 million during this period.
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
Chart and table of population level and growth rate for the Berlin, Germany metro area from 1950 to 2025.
CC0 1.0 Universal Public Domain Dedicationhttps://creativecommons.org/publicdomain/zero/1.0/
License information was derived automatically
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 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, 2018-2022 American Community Survey 5-Year Estimates.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..Ancestry listed in this table refers to the total number of people who responded with a particular ancestry; for example, the estimate given for German represents the number of people who listed German as either their first or second ancestry. This table lists only the largest ancestry groups; see the Detailed Tables for more categories. Race and Hispanic origin groups are not included in this table because data for those groups come from the Race and Hispanic origin questions rather than the ancestry question (see Demographic Table)..Data for year of entry of the native population reflect the year of entry into the U.S. by people who were born in Puerto Rico or U.S. Island Areas or born outside the U.S. to a U.S. citizen parent and who subsequently moved to the U.S..Methodological changes to citizenship edits may have affected citizenship data for those born in American Samoa. Users should be aware of these changes when using 2018 data or multi-year data containing data from 2018. For more information, see: American Samoa Citizenship User Note..The Census Bureau introduced a new set of disability questions in the 2008 ACS questionnaire. Accordingly, comparisons of disability data from 2008 or later with data from prior years are not recommended. For more information on these questions and their evaluation in the 2006 ACS Content Test, see the Evaluation Report Covering Disability..The category "with a broadband Internet subscription" refers to those who said "Yes" to at least one of the following types of Internet subscriptions: Broadband such as cable, fiber optic, or DSL; a cellular data plan; satellite; a fixed wireless subscription; or other non-dial up subscription types..An Internet "subscription" refers to a type of service that someone pays for to access the Internet such as a cellular data plan, broadband such as cable, fiber optic or DSL, or other type of service. This will normally refer to a service that someone is billed for directly for Internet alone or sometimes as part of a bundle..With a computer includes 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 "children of the householder" and "own children of the householder" concepts are combined in these estimates. For more information, please see the following User Note..The 2018-2022 American Community Survey (ACS) data generally reflect the March 2020 Office of Management and Budget (OMB) delineations of metropolitan and micropolitan statistical areas. In certain instances, the names, codes, and boundaries of the principal cities shown in ACS tables may differ from the OMB delineation lists due to differences in the effective dates of the geographic entities..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 obse...
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
Context
The dataset tabulates the population of German town by gender across 18 age groups. It lists the male and female population in each age group along with the gender ratio for German town. The dataset can be utilized to understand the population distribution of German town by gender and age. For example, using this dataset, we can identify the largest age group for both Men and Women in German town. Additionally, it can be used to see how the gender ratio changes from birth to senior most age group and male to female ratio across each age group for German town.
Key observations
Largest age group (population): Male # 50-54 years (23) | Female # 40-44 years (12). Source: U.S. Census Bureau American Community Survey (ACS) 2018-2022 5-Year Estimates.
When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2018-2022 5-Year Estimates.
Age groups:
Scope of gender :
Please note that American Community Survey asks a question about the respondents current sex, but not about gender, sexual orientation, or sex at birth. The question is intended to capture data for biological sex, not gender. Respondents are supposed to respond with the answer as either of Male or Female. Our research and this dataset mirrors the data reported as Male and Female for gender distribution analysis.
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 German town Population by Gender. You can refer the same here
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
Context
The dataset tabulates the German Flatts town population distribution across 18 age groups. It lists the population in each age group along with the percentage population relative of the total population for German Flatts town. The dataset can be utilized to understand the population distribution of German Flatts town by age. For example, using this dataset, we can identify the largest age group in German Flatts town.
Key observations
The largest age group in German Flatts, New York was for the group of age 10 to 14 years years with a population of 1,017 (8.28%), according to the ACS 2018-2022 5-Year Estimates. At the same time, the smallest age group in German Flatts, New York was the 75 to 79 years years with a population of 297 (2.42%). Source: U.S. Census Bureau American Community Survey (ACS) 2018-2022 5-Year Estimates
When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2018-2022 5-Year Estimates
Age groups:
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 German Flatts town Population by Age. You can refer the same here
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
Chart and table of population level and growth rate for the Munich, Germany metro area from 1950 to 2025.
CC0 1.0 Universal Public Domain Dedicationhttps://creativecommons.org/publicdomain/zero/1.0/
License information was derived automatically
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 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, 2018-2022 American Community Survey 5-Year Estimates.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..Ancestry listed in this table refers to the total number of people who responded with a particular ancestry; for example, the estimate given for German represents the number of people who listed German as either their first or second ancestry. This table lists only the largest ancestry groups; see the Detailed Tables for more categories. Race and Hispanic origin groups are not included in this table because data for those groups come from the Race and Hispanic origin questions rather than the ancestry question (see Demographic Table)..Methodological changes to citizenship edits may have affected citizenship data for those born in American Samoa. Users should be aware of these changes when using 2018 data or multi-year data containing data from 2018. For more information, see: American Samoa Citizenship User Note..The Census Bureau introduced a new set of disability questions in the 2008 ACS questionnaire. Accordingly, comparisons of disability data from 2008 or later with data from prior years are not recommended. For more information on these questions and their evaluation in the 2006 ACS Content Test, see the Evaluation Report Covering Disability..The category "with a broadband Internet subscription" refers to those who said "Yes" to at least one of the following types of Internet subscriptions: Broadband such as cable, fiber optic, or DSL; a cellular data plan; satellite; a fixed wireless subscription; or other non-dial up subscription types..An Internet "subscription" refers to a type of service that someone pays for to access the Internet such as a cellular data plan, broadband such as cable, fiber optic or DSL, or other type of service. This will normally refer to a service that someone is billed for directly for Internet alone or sometimes as part of a bundle..With a computer includes 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 "children of the householder" and "own children of the householder" concepts are combined in these estimates. For more information, please see the following User Note..The 2018-2022 American Community Survey (ACS) data generally reflect the March 2020 Office of Management and Budget (OMB) delineations of metropolitan and micropolitan statistical areas. In certain instances, the names, codes, and boundaries of the principal cities shown in ACS tables may differ from the OMB delineation lists due to differences in the effective dates of the geographic entities..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...
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
Context
The dataset tabulates the data for the German, New York population pyramid, which represents the German town population distribution across age and gender, using estimates from the U.S. Census Bureau American Community Survey (ACS) 2018-2022 5-Year Estimates. It lists the male and female population for each age group, along with the total population for those age groups. Higher numbers at the bottom of the table suggest population growth, whereas higher numbers at the top indicate declining birth rates. Furthermore, the dataset can be utilized to understand the youth dependency ratio, old-age dependency ratio, total dependency ratio, and potential support ratio.
Key observations
When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2018-2022 5-Year Estimates.
Age groups:
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 German town Population by Age. You can refer the same here
CC0 1.0 Universal Public Domain Dedicationhttps://creativecommons.org/publicdomain/zero/1.0/
License information was derived automatically
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 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, 2022 American Community Survey 1-Year Estimates.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..Ancestry listed in this table refers to the total number of people who responded with a particular ancestry; for example, the estimate given for German represents the number of people who listed German as either their first or second ancestry. This table lists only the largest ancestry groups; see the Detailed Tables for more categories. Race and Hispanic origin groups are not included in this table because data for those groups come from the Race and Hispanic origin questions rather than the ancestry question (see Demographic Table)..Data for year of entry of the native population reflect the year of entry into the U.S. by people who were born in Puerto Rico or U.S. Island Areas or born outside the U.S. to a U.S. citizen parent and who subsequently moved to the U.S..The Census Bureau introduced a new set of disability questions in the 2008 ACS questionnaire. Accordingly, comparisons of disability data from 2008 or later with data from prior years are not recommended. For more information on these questions and their evaluation in the 2006 ACS Content Test, see the Evaluation Report Covering Disability..The category "with a broadband Internet subscription" refers to those who said "Yes" to at least one of the following types of Internet subscriptions: Broadband such as cable, fiber optic, or DSL; a cellular data plan; satellite; a fixed wireless subscription; or other non-dial up subscription types..An Internet "subscription" refers to a type of service that someone pays for to access the Internet such as a cellular data plan, broadband such as cable, fiber optic or DSL, or other type of service. This will normally refer to a service that someone is billed for directly for Internet alone or sometimes as part of a bundle..With a computer includes 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..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..The 2022 American Community Survey (ACS) data generally reflect the March 2020 Office of Management and Budget (OMB) delineations of metropolitan and micropolitan statistical areas. In certain instances the names, codes, and boundaries of the principal cities shown in ACS tables may differ from the OMB delineations due to differences in the effective dates of the geographic entities..Estimates of urban and rural populations,...
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
Context
The dataset tabulates the population of German Flatts town by gender across 18 age groups. It lists the male and female population in each age group along with the gender ratio for German Flatts town. The dataset can be utilized to understand the population distribution of German Flatts town by gender and age. For example, using this dataset, we can identify the largest age group for both Men and Women in German Flatts town. Additionally, it can be used to see how the gender ratio changes from birth to senior most age group and male to female ratio across each age group for German Flatts town.
Key observations
Largest age group (population): Male # 10-14 years (529) | Female # 30-34 years (571). Source: U.S. Census Bureau American Community Survey (ACS) 2018-2022 5-Year Estimates.
When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2018-2022 5-Year Estimates.
Age groups:
Scope of gender :
Please note that American Community Survey asks a question about the respondents current sex, but not about gender, sexual orientation, or sex at birth. The question is intended to capture data for biological sex, not gender. Respondents are supposed to respond with the answer as either of Male or Female. Our research and this dataset mirrors the data reported as Male and Female for gender distribution analysis.
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 German Flatts town Population by Gender. You can refer the same here
The city of Paris in France had an estimated gross domestic product of 757.6 billion Euros in 2021, the most of any European city. Paris was followed by the spanish capital, Madrid, which had a GDP of 237.5 billion Euros, and the Irish capital, Dublin at 230 billion Euros. Milan, in the prosperous north of Italy, had a GDP of 228.4 billion Euros, 65 billion euros larger than the Italian capital Rome, and was the largest non-capital city in terms of GDP in Europe. The engine of Europe Among European countries, Germany had by far the largest economy, with a gross domestic product of over 4.18 trillion Euros. The United Kingdom or France have been Europe's second largest economy since the 1980s, depending on the year, with forecasts suggesting France will overtake the UK going into the 2020s. Germany however, has been the biggest European economy for some time, with five cities (Munich, Berlin, Hamburg, Stuttgart and Frankfurt) among the 15 largest European cities by GDP. Europe's largest cities In 2023, Moscow was the largest european city, with a population of nearly 12.7 million. Paris was the largest city in western Europe, with a population of over 11 million, while London was Europe's third-largest city at 9.6 million inhabitants.
In 2023, the population of the United Kingdom was around **** million, with approximately **** million women and **** million men. Since 1953, the male population of the UK has grown by around *** million, while the female population has increased by approximately *** million. Throughout this provided time period, the female population of the UK has consistently outnumbered the male population. UK population one of the largest in Europe As of 2022, the population of the United Kingdom was the largest it has ever been, and with growth expected to continue, the forecasted population of the United Kingdom is expected to reach over ** million by the 2030s. Despite the relatively small size of its territory, the UK has one of the largest populations among European countries, slightly larger than France but smaller than Russia and Germany. As of 2022, the population density of the UK was approximately *** people per square kilometer, with London by far the most densely populated area, and Scotland the most sparsely populated. Dominance of London As seen in the data regarding population density, the population of the United Kingdom is not evenly distributed across the country. Within England, London has a population of almost **** million, making it significantly bigger than the next largest cities of Birmingham and Manchester. As of 2022, Scotland's largest city, Glasgow had a population of around *** million, with the largest cities in Northern Ireland, and Wales being Belfast and Cardiff, which had populations of ******* and ******* respectively.
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Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
Context
The dataset tabulates the German town population distribution across 18 age groups. It lists the population in each age group along with the percentage population relative of the total population for German town. The dataset can be utilized to understand the population distribution of German town by age. For example, using this dataset, we can identify the largest age group in German town.
Key observations
The largest age group in German, New York was for the group of age 50 to 54 years years with a population of 35 (14.29%), according to the ACS 2018-2022 5-Year Estimates. At the same time, the smallest age group in German, New York was the 25 to 29 years years with a population of 0 (0%). Source: U.S. Census Bureau American Community Survey (ACS) 2018-2022 5-Year Estimates
When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2018-2022 5-Year Estimates
Age groups:
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 German town Population by Age. You can refer the same here