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Personal demographic data extended beyond those specified by ISO 22220.
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
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Context
The dataset tabulates the Person County 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 Person County. The dataset can be utilized to understand the population distribution of Person County by age. For example, using this dataset, we can identify the largest age group in Person County.
Key observations
The largest age group in Person County, NC was for the group of age 60-64 years with a population of 3,165 (8.12%), according to the 2021 American Community Survey. At the same time, the smallest age group in Person County, NC was the 80-84 years with a population of 807 (2.07%). Source: U.S. Census Bureau American Community Survey (ACS) 2017-2021 5-Year Estimates.
When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2017-2021 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 Person County Population by Age. You can refer the same here
This transformed view of Employee Demographics - Public dataset counts the number of and percentage of city employees by race as self-reported by employee based on EEOC classification. This information is used by "City Employee vs. Community Demographics dataset" at https://citydata.mesaaz.gov/Economic-Development/Chart-Data-for-City-Employee-vs-Community-Demograp/bt2n-zimw
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Person additional demographic data according to ISO 22220: sex and mother's family name
Summary File 4 is repeated or iterated for the total population and 335 additional population groups: 132 race groups,78 American Indian and Alaska Native tribe categories, 39 Hispanic or Latino groups, and 86 ancestry groups.Tables for any population group excluded from SF 2 because the group's total population in a specific geographic area did not meet the SF 2 threshold of 100 people are excluded from SF 4. Tables in SF 4 shown for any of the above population groups will only be shown if there are at least 50 unweighted sample cases in a specific geographic area. The same 50 unweighted sample cases also applied to ancestry iterations. In an iterated file such as SF 4, the universes households, families, and occupied housing units are classified by the race or ethnic group of the householder. The universe subfamilies is classified by the race or ethnic group of the reference person for the subfamily. In a husband/wife subfamily, the reference person is the husband; in a parent/child subfamily, the reference person is always the parent. The universes population in households, population in families, and population in subfamilies are classified by the race or ethnic group of the inidviduals within the household, family, or subfamily without regard to the race or ethnicity of the householder. Notes follow selected tables to make the classification of the universe clear. In any population table where there is no note, the universe classification is always based on the race or ethnicity of the person. In all housing tables, the universe classification is based on the race or ethnicity of the householder.
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
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Context
The dataset tabulates the data for the Person County, NC population pyramid, which represents the Person County population distribution across age and gender, using estimates from the U.S. Census Bureau American Community Survey 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) 2017-2021 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 Person County Population by Age. You can refer the same here
This dataset was created by Mohamed Khalil Brik
https://www.icpsr.umich.edu/web/ICPSR/studies/36854/termshttps://www.icpsr.umich.edu/web/ICPSR/studies/36854/terms
The American Community Survey (ACS) is an ongoing statistical survey that samples a small percentage of the population every year -- giving communities the information they need to plan investments and services. The 5-year public use microdata sample (PUMS) for 2011-2015 is a subset of the 2011-2011 ACS sample. It contains the same sample as the combined PUMS 1-year files for 2011, 2012, 2013, 2014 and 2015. This data collection provides a person-level subset of 129,895 respondents whose occupations were coded as arts-related in the 2011-2015 ACS PUMS. The 2011-2015 PUMS is the seventh 5-year file published by the ACS. This data collection contains five years of data for the population from households and the group quarters (GQ) population. The GQ population and population from households are all weighted to agree with the ACS counts which are an average over the five year period (2011-2015). The ACS sample was selected from all counties across the nation. The ACS provides social, housing, and economic characteristics for demographic groups covering a broad spectrum of geographic areas in the United States. Demographic variables include sex, age, relationship of person to the selected respondent, race, and Hispanic origin. Social characteristics variables include school enrollment, educational attainment, marital status, fertility, grandparents caring for children, veteran status, type of disability, health insurance, place of birth, United States citizenship status, year of entry, year of naturalization, language spoken at home, and ancestry. Variables focusing on economic characteristics include employment status, commuting to work, occupation, industry, class of worker, income and benefits, and poverty status.
2016-2020 ACS 5-Year estimates of demographic variables (see below) compiled at the Place level. These variables include Sex By Age, Hispanic Or Latino Origin By Race, Household Type (Including Living Alone), Households By Presence Of People Under 18 Years By Household Type, Households By Presence Of People 60 Years And Over By Household Type, Nativity By Language Spoken At Home By Ability To Speak English For The Population 5 Years And Over, Average Household Size Of Occupied Housing Units By Tenure, and Sex by Educational Attainment for the Population 18 Years and Over.
https://www.ine.es/aviso_legalhttps://www.ine.es/aviso_legal
Vital Statistics: Deaths Statistics: Demographic phenomena of people with residence abroad by years and type of demographic phenomenon. National.
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United States US: Number of Births data was reported at 4,413,478.000 Person in 2050. This records an increase from the previous number of 4,397,629.000 Person for 2049. United States US: Number of Births data is updated yearly, averaging 4,195,844.000 Person from Jun 2001 (Median) to 2050, with 50 observations. The data reached an all-time high of 4,413,478.000 Person in 2050 and a record low of 3,921,308.000 Person in 2013. United States US: Number of Births data remains active status in CEIC and is reported by US Census Bureau. The data is categorized under Global Database’s United States – Table US.US Census Bureau: Demographic Projection.
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Demographic data from Chapter 4 "Measuring audio visualization performance" from the PhD thesis "Semantic Audio Tools for Radio Production" by Chris Baume.
https://search.gesis.org/research_data/datasearch-httpwww-da-ra-deoaip--oaioai-da-ra-de441757https://search.gesis.org/research_data/datasearch-httpwww-da-ra-deoaip--oaioai-da-ra-de441757
Abstract (en): This data collection supplies standard monthly labor force data as well as supplemental data on work experience, income, and migration. Comprehensive information is given on the employment status, occupation, and industry of persons 14 years old and older. Additional data are available concerning weeks worked and hours per week worked, reason not working full-time, total income and income components, and residence. Information on demographic characteristics, such as age, sex, race, educational attainment, marital status, veteran status, household relationship, and Hispanic origin, is available for each person in the household enumerated. Persons in the civilian noninstitutional population of the United States living in households and members of the armed forces living in civilian housing units in 1969. A national probability sample was used in selecting housing units. (1) This hierarchical file contains 202,112 records. There are approximately 157 variables and two record types: family and person. Family records contain approximately 58 variables, and person records contain approximately 99 variables. (2) Each family and person record contains a weight, which must be used in any analysis. (3) This data file was obtained from the Data Program and Library Service (DPLS), University of Wisconsin. Some data management operations intended to store the data more efficiently were performed by DPLS. That organization also revised the original Census Bureau documentation. (4) The codebook is provided by ICPSR as a Portable Document Format (PDF) file. The PDF file format was developed by Adobe Systems Incorporated and can be accessed using PDF reader software, such as the Adobe Acrobat Reader. Information on how to obtain a copy of the Acrobat Reader is provided on the ICPSR Web site.
CC0 1.0 Universal Public Domain Dedicationhttps://creativecommons.org/publicdomain/zero/1.0/
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This data contains information related to officer-initated stops by the City of Boulder Police Department. Information on the demographics of the person stopped (sex, race, ethnicity, year of birth, whether they are a Boulder resident) is included in this file. See the "Outcomes of Police Stops" dataset for more details on the outcome of the stop (stop location, duration, search, and result). This demographic data is collected at the stop level, and no individual-level identifiers are recorded in the system during a stop.The data published are limited to stops where the officer initiated, or had discretion, in making a stop. Instances where an officer is responding to a community or police call are considered non-discretionary, and demographics information is not collected for those stops and not included here. There are some instances of non-discretion within a stop interaction as well. For example, there may be instances where there is an outstanding felony warrant for the person stopped, and by law the officer must arrest that person.Please read the methodology and data dictionary documents for more information. The fields for this demographics dataset are referred to as the "Main" file in the data dictionary.
In 2021, 2,078 cases of human trafficking involving minors were reported to the National Human Trafficking hotline in the United States. 306 cases reported to the hotline in that year involved foreign nationals.
The L2 Voter and Demographic Dataset includes demographic and voter history tables for all 50 states and the District of Columbia. The dataset is built from publicly available government records about voter registration and election participation. These records indicate whether a person voted in an election or not, but they do not record whom that person voted for. Voter registration and election participation data are augmented by demographic information from outside data sources.
The L2 Voter and Demographic Dataset is current as of April 7 2025.
To create this file, L2 processes registered voter data on an ongoing basis for all 50 states and the District of Columbia, with refreshes of the underlying state voter data typically at least every six months and refreshes of telephone numbers and National Change of Address processing approximately every 30 to 60 days. These data are standardized and enhanced with propriety commercial data and modeling codes and consist of approximately 185,000,000 records nationwide.
For each state, there are two available tables: demographic and voter history. The demographic and voter tables can be joined on the LALVOTERID
variable. One can also use the LALVOTERID
variable to link the L2 Voter and Demographic Dataset with the L2 Consumer Dataset.
In addition, the LALVOTERID
variable can be used to validate the state. For example, let's look at the LALVOTERID = LALCA3169443
. The characters in the fourth and fifth positions of this identifier are 'CA' (California). The second way to validate the state is by using the RESIDENCE_ADDRESSES_STATE
variable, which should have a value of 'CA' (California).
The date appended to each table name represents when the data was last updated. These dates will differ state by state because states update their voter files at different cadences.
The demographic files use 698 consistent variables. For more information about these variables, see 2025-01-10-VM2-File-Layout.xlsx.
The voter history files have different variables depending on the state. The ***2025-04-07-L2-Voter-Dictionaries.tar.gz file contains .csv data dictionaries for each state's demographic and voter files. While the demographic file data dictionaries should mirror the 2025-01-10-VM2-File-Layout.xlsx*** file, the voter file data dictionaries will be unique to each state.
***2025-01-10-National-File-Notes.pdf ***contains L2 Voter and Demographic Dataset ("National File") release notes from 2018 to 2025.
***2025-04-07-L2-Voter-Fill-Rate.tar.gz ***contains .tab files tracking the percent of non-null values for any given field.
Data access is required to view this section.
Data access is required to view this section.
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Demographic data, Studies 1–4.
IPUMS-International is an effort to inventory, preserve, harmonize, and disseminate census microdata from around the world. The project has collected the world's largest archive of publicly available census samples. The data are coded and documented consistently across countries and over time to facilitate comparative research. IPUMS-International makes these data available to qualified researchers free of charge through a web dissemination system. The IPUMS project is a collaboration of the Minnesota Population Center, National Statistical Offices, and international data archives. Major funding is provided by the U.S. National Science Foundation and the Demographic and Behavioral Sciences Branch of the National Institute of Child Health and Human Development. Additional support is provided by the University of Minnesota Office of the Vice President for Research, the Minnesota Population Center, and Sun Microsystems. Detailed metadata will be found in ipumsi_6.3_nl_1971_ddic.html within the Data Package. The related metadata describes the content of the extraction of the specified sample from the IPUMS International on-line extraction system.
The data is prepared using AmeriCorps members who began service on any day in fiscal year (FY) 2017. The members may have served 1 to 365 days during their term. Members who are in never served, disqualified, pre-service, or deferred statuses were excluded from this analysis. AmeriCorps VISTA and AmeriCorps NCCC race and ethnicity data come from the member application to serve. The code to extract the data between the two programs is the same. The ASN race and ethnicity data comes from the enrollment form. The enrollment form may exist multiple times if the member enrolled in more than one term. It is not uncommon for each enrollment form to have conflicting information about the member’s race and ethnicity. The member may have enrollment form data for terms served outside of the timeframe of the dataset. For example, if we are reporting on members who began service in FY17, then a member who also served in FY16 may have race and ethnicity information in the FY16 enrollment form and no race or ethnicity information or conflicting information in the FY17 enrollment form. In the case of conflicting information, this analysis assumes each instance of race designation is correct. If a member reports themselves as “Asian or Asian American” in one enrollment form and “White” in another enrollment form, then the analysis categorizes this person as someone who identifies with multiple race selections vs. one or the other. In the case of ethnicity, if a member indicates that they are not Hispanic or Latino/a in one form, but that they are in another, this analysis assumes the affirmative—and they will be categorized as Hispanic or Latino/a. Lastly, the totals include the total results from the query plus the difference between the query and the raw count of members who started service in that fiscal year. The members who did not have a record in the invite table and enrollment table were added to the non-response category. Senior Corps Figures come from the Annual Progress Report Supplement as of April 11, 2018. Percentages are calculated from totals of the subcategories, excluding the non-response categories.
Open Government Licence - Canada 2.0https://open.canada.ca/en/open-government-licence-canada
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Characteristics from the 2016 Census of Population related to marital status, living arrangements, education, place of birth, housing, and health limitations among people who overdosed in Simcoe Muskoka between 2018 and 2019.
Attribution-ShareAlike 3.0 (CC BY-SA 3.0)https://creativecommons.org/licenses/by-sa/3.0/
License information was derived automatically
Personal demographic data extended beyond those specified by ISO 22220.