Website alows the public full access to the 1940 Census images, census maps and descriptions.

Abstract

The Integrated Public Use Microdata Series (IPUMS) Complete Count Data include more than 650 million individual-level and 7.5 million household-level records. The microdata are the result of collaboration between IPUMS and the nation’s two largest genealogical organizations—Ancestry.com and FamilySearch—and provides the largest and richest source of individual level and household data.

Before Manuscript Submission

All manuscripts (and other items you'd like to publish) must be submitted to

phsdatacore@stanford.edu for approval prior to journal submission.

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For more information about how to cite PHS and PHS datasets, please visit:

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Documentation

Historic data are scarce and often only exists in aggregate tables. The key advantage of historic US census data is the availability of individual and household level characteristics that researchers can tabulate in ways that benefits their specific research questions. The data contain demographic variables, economic variables, migration variables and family variables. Within households, it is possible to create relational data as all relations between household members are known. For example, having data on the mother and her children in a household enables researchers to calculate the mother’s age at birth. Another advantage of the Complete Count data is the possibility to follow individuals over time using a historical identifier.

In sum: the historic US census data are a unique source for research on social and economic change and can provide population health researchers with information about social and economic determinants.

The historic US 1920 census data was collected in January 1920. Enumerators collected data traveling to households and counting the residents who regularly slept at the household. Individuals lacking permanent housing were counted as residents of the place where they were when the data was collected. Household members absent on the day of data collected were either listed to the household with the help of other household members or were scheduled for the last census subdivision.

Notes

• We provide household and person data separately so that it is convenient to explore the descriptive statistics on each level. In order to obtain a full dataset, merge the household and person on the variables SERIAL and SERIALP. In order to create a longitudinal dataset, merge datasets on the variable HISTID.

• Households with more than 60 people in the original data were broken up for processing purposes. Every person in the large households are considered to be in their own household. The original large households can be identified using the variable SPLIT, reconstructed using the variable SPLITHID, and the original count is found in the variable SPLITNUM.

• Coded variables derived from string variables are still in progress. These variables include: occupation and industry.

• Missing observations have been allocated and some inconsistencies have been edited for the following variables: SPEAKENG, YRIMMIG, CITIZEN, AGE, BPL, MBPL, FBPL, LIT, SCHOOL, OWNERSHP, MORTGAGE, FARM, CLASSWKR, OCC1950, IND1950, MARST, RACE, SEX, RELATE, MTONGUE. The flag variables indicating an allocated observation for the associated variables can be included in your extract by clicking the ‘Select data quality flags’ box on the extract summary page.

• Most inconsistent information was not edited for this release, thus there are observations outside of the universe for some variables. In particular, the variables GQ, and GQTYPE have known inconsistencies and will be improved with the next release.

%3C!-- --%3E

Section 2

This dataset was created on 2020-01-10 18:46:34.647 by merging multiple datasets together. The source datasets for this version were:

IPUMS 1920 households: This dataset includes all households from the 1920 US census.

IPUMS 1920 persons: This dataset includes all individuals from the 1920 US census.

IPUMS 1920 Lookup: This dataset includes variable names, variable labels, variable values, and corresponding variable value labels for the IPUMS 1920 datasets.

The Census Tree is the largest-ever database of record links among the historical U.S. censuses, with over 700 million links for people living in the United States between 1850 and 1940. These links allow researchers to construct a longitudinal dataset that is highly representative of the population, and that includes women, Black Americans, and other under-represented populations at unprecedented rates. This project contains the files necessary to closely replicate the links between the 1900 and 1910 censuses. For more information, consult the included Read Me file, and visit https://censustree.org.

About this dataset

Context

The dataset tabulates the Island 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 Island County. The dataset can be utilized to understand the population distribution of Island County by age. For example, using this dataset, we can identify the largest age group in Island County.

Key observations

The largest age group in Island County, WA was for the group of age 60-64 years with a population of 6,868 (7.99%), according to the 2021 American Community Survey. At the same time, the smallest age group in Island County, WA was the 85+ years with a population of 1,961 (2.28%). Source: U.S. Census Bureau American Community Survey (ACS) 2017-2021 5-Year Estimates.

Content

When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2017-2021 5-Year Estimates.

Age groups:

• Under 5 years
• 5 to 9 years
• 10 to 14 years
• 15 to 19 years
• 20 to 24 years
• 25 to 29 years
• 30 to 34 years
• 35 to 39 years
• 40 to 44 years
• 45 to 49 years
• 50 to 54 years
• 55 to 59 years
• 60 to 64 years
• 65 to 69 years
• 70 to 74 years
• 75 to 79 years
• 80 to 84 years
• 85 years and over

Variables / Data Columns

• Age Group: This column displays the age group in consideration
• Population: The population for the specific age group in the Island County is shown in this column.
• % of Total Population: This column displays the population of each age group as a proportion of Island County 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 Island County Population by Age. You can refer the same here

Abstract

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 facillitate 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.

Geographic coverage

National coverage

Analysis unit

UNITS IDENTIFIED: - Dwellings: Yes - Vacant units: No - Households: Yes - Individuals: Yes - Group quarters: Not available in microdata sample - Special populations: No

UNIT DESCRIPTIONS: - Dwellings: Separated space with independent access that serves as a human lodging - Households: Individuals living in the same dwelling and sharing at least one meal. - Group quarters: Group of persons who share a common roof and food because of work, health, religion, etc.

Universe

The entire population of the country, including all households and dwellings.

Kind of data

Census/enumeration data [cen]

Sampling procedure

MICRODATA SOURCE: National Statistical Service of Greece

SAMPLE DESIGN: Systematic Sampling (random start, then 1 out of every 2.5 private households from the processed 25% households) by MPC.

SAMPLE UNIT: Household

SAMPLE FRACTION: 10%

SAMPLE UNIVERSE: Microdata are available for 25% of the population.

SAMPLE SIZE (person records): 845,473

Mode of data collection

Face-to-face [f2f]

Research instrument

P1 for private households

Response rate

COVERAGE: 100%

An Act for ascertaining the Number of the Inhabitants of the Colony of New South Wales in the Year One thousand eight hundred and forty-one, 1840 (4 Victoria Act No. 26) required every householder, employer of servants and proprietor and occupier of land to complete the census schedule on the second day ('or on the days immediately subsequent thereto') of March 1841.

The 1841 Census was more complete than its predecessors, as the population was recorded in police districts, counties and towns. There was a broader tabulation of results which included age groups, conjugal condition (married or unmarried), religious denomination and civil condition. Civil condition provided statistical information on the number of bond (convict) or free males and females in a household, whether they were born in the colony, arrived free, held a ticket of leave, and whether they were in government employment or private assignment.

The Census was taken by specially appointed collectors generally responsible to a Commissioner or a Bench of Magistrates, the collector completed printed forms, known as Form ‘A’ for each household in the allotted territory. After the Census magistrates were instructed to check the returns and send abstracts to the Colonial Secretary, designated Form ‘C’. The returns were then gathered together, statistics extracted and the final returns made.

This series comprises bound volumes of Form C . (NRS 1281).

The Form C records: number of return, name of establishment (usually head of household), number of each age group for males, and then for females (the age divisions are under two, two and under seven, seven and under 14, 14 and under 21, 21 and under 45, 45 and under 60, 60 and upwards); married or single; civil condition: free (born in colony, arrived free, other free persons), bond (ticket of leave, in government employment, in private assignment); then religion divided into Church of England, Church of Scotland, Wesleyan Methodists, other Protestant dissenters, Roman Catholics, Jews, Mohammedans and Pagans; occupation divided into land proprietors, merchants, bankers, and professional men; shopkeepers and other retail dealers; mechanics and artificers; shepherds and others in the care of sheep; gardeners, stockmen and persons employed in agriculture; domestic servants; all other persons not included in the foregoing classes; totals for males, for females, and for both; houses - further divided into stone or brick, wood, total; finished or unfinished; inhabited or uninhabited. The columns are totalled at the bottom of each sheet.

As well as these Abstracts of returns, there are also a number of "condensed" abstracts of returns, filled in on Form C. These enumerate the running numbers covered by each sheet of abstracts eg. one-20, 21-40 and give sums for each group as well as grand total.

Form C abstracts are arranged by district following the order in the Returns of the Colony for 1841. 'Condensed' Abstracts are filed with the district abstracts to which they pertain.

Berrima-Port Phillip (X946-49)
Queanbeyan-Yass (X950-51)

References
1) State Records New South Wales Website, "Concise Guide to the State Archives (Ca - Commissioners): Colonial Secretary, later Chief Secretary, later Services; s. Population and Statistics, a. Musters and Census Records, ii. Census,23. 1841 Census: Abstracts of returns, CGS 1282."
2) State Records New South Wales Website, "Introduction to the 1841 Census: Index to the 1841 Census, Background".
3) State Records New South Wales Website, "Short Guide 12 - Muster and Census Records, 1788 - 1901".

This dataset shows census data for Nigeria from government data sources and the World Bank data portal.

About this dataset

Context

The dataset tabulates the New Freedom 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 New Freedom. The dataset can be utilized to understand the population distribution of New Freedom by age. For example, using this dataset, we can identify the largest age group in New Freedom.

Key observations

The largest age group in New Freedom, PA was for the group of age 45-49 years with a population of 427 (8.73%), according to the 2021 American Community Survey. At the same time, the smallest age group in New Freedom, PA was the 85+ years with a population of 68 (1.39%). Source: U.S. Census Bureau American Community Survey (ACS) 2017-2021 5-Year Estimates.

Content

When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2017-2021 5-Year Estimates.

Age groups:

• Under 5 years
• 5 to 9 years
• 10 to 14 years
• 15 to 19 years
• 20 to 24 years
• 25 to 29 years
• 30 to 34 years
• 35 to 39 years
• 40 to 44 years
• 45 to 49 years
• 50 to 54 years
• 55 to 59 years
• 60 to 64 years
• 65 to 69 years
• 70 to 74 years
• 75 to 79 years
• 80 to 84 years
• 85 years and over

Variables / Data Columns

• Age Group: This column displays the age group in consideration
• Population: The population for the specific age group in the New Freedom is shown in this column.
• % of Total Population: This column displays the population of each age group as a proportion of New Freedom 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 New Freedom Population by Age. You can refer the same here

Abstract

The 2005 Republic of Palau Census of Population and Housing will be used to give a snapshot of Republic of Palau's population and housing at the mid-point of the decade. This Census is also important because it measures the population at the beginning of the implementation of the Compact of Free Association. The information collected in the census is needed to plan for the needs of the population. The government uses the census figures to allocate funds for public services in a wide variety of areas, such as education, housing, and job training. The figures also are used by private businesses, academic institutions, local organizations, and the public in general to understand who we are and what our situation is, in order to prepare better for our future needs.

The fundamental purpose of a census is to provide information on the size, distribution and characteristics of a country's population. The census data are used for policymaking, planning and administration, as well as in management and evaluation of programmes in education, labour force, family planning, housing, health, transportation and rural development. A basic administrative use is in the demarcation of constituencies and allocation of representation to governing bodies. The census is also an invaluable resource for research, providing data for scientific analysis of the composition and distribution of the population and for statistical models to forecast its future growth. The census provides business and industry with the basic data they need to appraise the demand for housing, schools, furnishings, food, clothing, recreational facilities, medical supplies and other goods and services.

Geographic coverage

A hierarchical geographic presentation shows the geographic entities in a superior/subordinate structure in census products. This structure is derived from the legal, administrative, or areal relationships of the entities. The hierarchical structure is depicted in report tables by means of indentation. The following structure is used for the 2005 Census of the Republic of Palau:

Republic of Palau State Hamlet/Village Enumeration District Block

Analysis unit

Individuals Families Households General Population

Universe

The Census covered all the households and respective residents in the entire country.

Kind of data

Census/enumeration data [cen]

Sampling procedure

Not applicable to a full enumeration census.

Mode of data collection

Face-to-face [f2f]

Research instrument

The 2005 Palau Census of Population and Housing comprises three parts: 1. Housing - one form for each household 2. Population - one for for each member of the household 3. People who have left home - one form for each household.

Cleaning operations

Full scale processing and editing activiities comprised eight separate sessions either with or separately but with remote guidance of the U.S. Census Bureau experts to finalize all datasets for publishing stage.

Processing operation was handled with care to produce a set of data that describes the population as clearly and accurately as possible. To meet this objective, questionnaires were reviewed and edited during field data collection operations by crew leaders for consistency, completeness, and acceptability. Questionnaires were also reviewed by census clerks in the census office for omissions, certain inconsistencies, and population coverage. For example, write-in entries such as "Don't know" or "NA" were considered unacceptable in certain quantities and/or in conjunction with other data omissions.

As a result of this review operation, a telephone or personal visit follow-up was made to obtain missing information. Potential coverage errors were included in the follow-up, as well as questionnaires with omissions or inconsistencies beyond the completeness and quality tolerances specified in the review procedures.

Subsequent to field operations, remaining incomplete or inconsistent information on the questionnaires was assigned using imputation procedures during the final automated edit of the collected data. Allocations, or computer assignments of acceptable data in place of unacceptable entries or blanks, were needed most often when an entry for a given item was lacking or when the information reported for a person or housing unit on that item was inconsistent with other information for that same person or housing unit. As in previous censuses, the general procedure for changing unacceptable entries was to assign an entry for a person or housing unit that was consistent with entries for persons or housing units with similar characteristics. The assignment of acceptable data in lace of blanks or unacceptable entries enhanced the usefulness of the data.

Another way to make corrections during the computer editing process is substitution. Substitution is the assignment of a full set of characteristics for a person or housing unit. Because of the detailed field operations, substitution was not needed for the 2005 Census.

Sampling error estimates

Sampling Error is not applicable to full enumeration censuses.

Data appraisal

In any large-scale statistical operation, such as the 2005 Census of the Republic of Palau, human- and machine-related errors were anticipated. These errors are commonly referred to as nonsampling errors. Such errors include not enumerating every household or every person in the population, not obtaining all required information form the respondents, obtaining incorrect or inconsistent information, and recording information incorrectly. In addition, errors can occur during the field review of the enumerators' work, during clerical handling of the census questionnaires, or during the electronic processing of the questionnaires.

To reduce various types of nonsampling errors, a number of techniques were implemented during the planning, data collection, and data processing activities. Quality assurance methods were used throughout the data collection and processing phases of the census to improve the quality of the data.

What you get:

Upvote! The database contains +40,000 records on US Gross Rent & Geo Locations. The field description of the database is documented in the attached pdf file. To access, all 325,272 records on a scale roughly equivalent to a neighborhood (census tract) see link below and make sure to upvote. Upvote right now, please. Enjoy!

Get the full free database with coupon code: FreeDatabase, See directions at the bottom of the description... And make sure to upvote :) coupon ends at 2:00 pm 8-23-2017

Gross Rent & Geographic Statistics:

• Mean Gross Rent (double)
• Median Gross Rent (double)
• Standard Deviation of Gross Rent (double)
• Number of Samples (double)
• Square area of land at location (double)
• Square area of water at location (double)

Geographic Location:

• Longitude (double)
• Latitude (double)
• State Name (character)
• State abbreviated (character)
• State_Code (character)
• County Name (character)
• City Name (character)
• Name of city, town, village or CPD (character)
• Primary, Defines if the location is a track and block group.
• Zip Code (character)
• Area Code (character)

Abstract

The data set originally developed for real estate and business investment research. Income is a vital element when determining both quality and socioeconomic features of a given geographic location. The following data was derived from over +36,000 files and covers 348,893 location records.

License

Only proper citing is required please see the documentation for details. Have Fun!!!

Golden Oak Research Group, LLC. “U.S. Income Database Kaggle”. Publication: 5, August 2017. Accessed, day, month year.

For any questions, you may reach us at research_development@goldenoakresearch.com. For immediate assistance, you may reach me on at 585-626-2965

please note: it is my personal number and email is preferred

Check our data's accuracy: Census Fact Checker

Access all 325,272 location for Free Database Coupon Code:

Don't settle. Go big and win big. Optimize your potential**. Access all gross rent records and more on a scale roughly equivalent to a neighborhood, see link below:

• Website: Golden Oak Research make sure to upvote

A small startup with big dreams, giving the every day, up and coming data scientist professional grade data at affordable prices It's what we do.

The TIGER/Line shapefiles and related database files (.dbf) are an extract of selected geographic and cartographic information from the U.S. Census Bureau's Master Address File / Topologically Integrated Geographic Encoding and Referencing (MAF/TIGER) Database (MTDB). The MTDB represents a seamless national file with no overlaps or gaps between parts, however, each TIGER/Line shapefile is designed to stand alone as an independent data set, or they can be combined to cover the entire nation. ZIP Code Tabulation Areas (ZCTAs) are approximate area representations of U.S. Postal Service (USPS) ZIP Code service areas that the Census Bureau creates to present statistical data for each decennial census. The Census Bureau delineates ZCTA boundaries for the United States, Puerto Rico, American Samoa, Guam, the Commonwealth of the Northern Mariana Islands, and the U.S. Virgin Islands once each decade following the decennial census. Data users should not use ZCTAs to identify the official USPS ZIP Code for mail delivery. The USPS makes periodic changes to ZIP Codes to support more efficient mail delivery. The Census Bureau uses tabulation blocks as the basis for defining each ZCTA. Tabulation blocks are assigned to a ZCTA based on the most frequently occurring ZIP Code for the addresses contained within that block. The most frequently occurring ZIP Code also becomes the five-digit numeric code of the ZCTA. These codes may contain leading zeros. Blocks that do not contain addresses but are surrounded by a single ZCTA (enclaves) are assigned to the surrounding ZCTA. Because the Census Bureau only uses the most frequently occurring ZIP Code to assign blocks, a ZCTA may not exist for every USPS ZIP Code. Some ZIP Codes may not have a matching ZCTA because too few addresses were associated with the specific ZIP Code or the ZIP Code was not the most frequently occurring ZIP Code within any of the blocks where it exists. The ZCTA boundaries in this release are those delineated following the 2020 Census.

The UNI-CEN Digital Boundary File Series facilitates the mapping of UNI-CEN census data tables. Boundaries are provided in multiple formats for different use cases: Esri Shapefile (SHP), geoJson, and File Geodatabase (FGDB). SHP and FGDB files are provided in two projections: NAD83 CSRS for print cartography and WGS84 for web applications. The geoJson version is provided in WGS84 only. The UNI-CEN Standardized Census Data Tables are readily merged to these boundary files. For more information about file sources, the methods used to create them, and how to use them, consult the documentation at https://borealisdata.ca/dataverse/unicen_docs. For more information about the project, visit https://observatory.uwo.ca/unicen.

About this dataset

Context

The dataset tabulates the Freedom 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 Freedom. The dataset can be utilized to understand the population distribution of Freedom by age. For example, using this dataset, we can identify the largest age group in Freedom.

Key observations

The largest age group in Freedom, PA was for the group of age 20 to 24 years years with a population of 212 (13.54%), according to the ACS 2019-2023 5-Year Estimates. At the same time, the smallest age group in Freedom, PA was the 85 years and over years with a population of 9 (0.57%). Source: U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates

Content

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

Age groups:

• Under 5 years
• 5 to 9 years
• 10 to 14 years
• 15 to 19 years
• 20 to 24 years
• 25 to 29 years
• 30 to 34 years
• 35 to 39 years
• 40 to 44 years
• 45 to 49 years
• 50 to 54 years
• 55 to 59 years
• 60 to 64 years
• 65 to 69 years
• 70 to 74 years
• 75 to 79 years
• 80 to 84 years
• 85 years and over

Variables / Data Columns

• Age Group: This column displays the age group in consideration
• Population: The population for the specific age group in the Freedom is shown in this column.
• % of Total Population: This column displays the population of each age group as a proportion of Freedom 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 Freedom Population by Age. You can refer the same here

About this dataset

Context

The dataset tabulates the Forest View 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 Forest View. The dataset can be utilized to understand the population distribution of Forest View by age. For example, using this dataset, we can identify the largest age group in Forest View.

Key observations

The largest age group in Forest View, IL was for the group of age 0-4 years with a population of 172 (13.25%), according to the 2021 American Community Survey. At the same time, the smallest age group in Forest View, IL was the 85+ years with a population of 14 (1.08%). Source: U.S. Census Bureau American Community Survey (ACS) 2017-2021 5-Year Estimates.

Content

When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2017-2021 5-Year Estimates.

Age groups:

• Under 5 years
• 5 to 9 years
• 10 to 14 years
• 15 to 19 years
• 20 to 24 years
• 25 to 29 years
• 30 to 34 years
• 35 to 39 years
• 40 to 44 years
• 45 to 49 years
• 50 to 54 years
• 55 to 59 years
• 60 to 64 years
• 65 to 69 years
• 70 to 74 years
• 75 to 79 years
• 80 to 84 years
• 85 years and over

Variables / Data Columns

• Age Group: This column displays the age group in consideration
• Population: The population for the specific age group in the Forest View is shown in this column.
• % of Total Population: This column displays the population of each age group as a proportion of Forest View 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 Forest View Population by Age. You can refer the same here

About this dataset

Context

The dataset tabulates the Lake View 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 Lake View. The dataset can be utilized to understand the population distribution of Lake View by age. For example, using this dataset, we can identify the largest age group in Lake View.

Key observations

The largest age group in Lake View, SC was for the group of age 45 to 49 years years with a population of 81 (12.25%), according to the ACS 2019-2023 5-Year Estimates. At the same time, the smallest age group in Lake View, SC was the 85 years and over years with a population of 9 (1.36%). Source: U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates

Content

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

Age groups:

• Under 5 years
• 5 to 9 years
• 10 to 14 years
• 15 to 19 years
• 20 to 24 years
• 25 to 29 years
• 30 to 34 years
• 35 to 39 years
• 40 to 44 years
• 45 to 49 years
• 50 to 54 years
• 55 to 59 years
• 60 to 64 years
• 65 to 69 years
• 70 to 74 years
• 75 to 79 years
• 80 to 84 years
• 85 years and over

Variables / Data Columns

• Age Group: This column displays the age group in consideration
• Population: The population for the specific age group in the Lake View is shown in this column.
• % of Total Population: This column displays the population of each age group as a proportion of Lake View 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 Lake View Population by Age. You can refer the same here

About this dataset

Context

The dataset tabulates the Southern View 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 Southern View. The dataset can be utilized to understand the population distribution of Southern View by age. For example, using this dataset, we can identify the largest age group in Southern View.

Key observations

The largest age group in Southern View, IL was for the group of age 55 to 59 years years with a population of 187 (10.17%), according to the ACS 2019-2023 5-Year Estimates. At the same time, the smallest age group in Southern View, IL was the Under 5 years years with a population of 26 (1.41%). Source: U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates

Content

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

Age groups:

• Under 5 years
• 5 to 9 years
• 10 to 14 years
• 15 to 19 years
• 20 to 24 years
• 25 to 29 years
• 30 to 34 years
• 35 to 39 years
• 40 to 44 years
• 45 to 49 years
• 50 to 54 years
• 55 to 59 years
• 60 to 64 years
• 65 to 69 years
• 70 to 74 years
• 75 to 79 years
• 80 to 84 years
• 85 years and over

Variables / Data Columns

• Age Group: This column displays the age group in consideration
• Population: The population for the specific age group in the Southern View is shown in this column.
• % of Total Population: This column displays the population of each age group as a proportion of Southern View 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 Southern View Population by Age. You can refer the same here

About this dataset

Context

The dataset tabulates the Freedom 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 Freedom town. The dataset can be utilized to understand the population distribution of Freedom town by age. For example, using this dataset, we can identify the largest age group in Freedom town.

Key observations

The largest age group in Freedom, New Hampshire was for the group of age 70 to 74 years years with a population of 206 (15.42%), according to the ACS 2018-2022 5-Year Estimates. At the same time, the smallest age group in Freedom, New Hampshire was the 25 to 29 years years with a population of 4 (0.30%). Source: U.S. Census Bureau American Community Survey (ACS) 2018-2022 5-Year Estimates

Content

When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2018-2022 5-Year Estimates

Age groups:

• Under 5 years
• 5 to 9 years
• 10 to 14 years
• 15 to 19 years
• 20 to 24 years
• 25 to 29 years
• 30 to 34 years
• 35 to 39 years
• 40 to 44 years
• 45 to 49 years
• 50 to 54 years
• 55 to 59 years
• 60 to 64 years
• 65 to 69 years
• 70 to 74 years
• 75 to 79 years
• 80 to 84 years
• 85 years and over

Variables / Data Columns

• Age Group: This column displays the age group in consideration
• Population: The population for the specific age group in the Freedom town is shown in this column.
• % of Total Population: This column displays the population of each age group as a proportion of Freedom town 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 Freedom town Population by Age. You can refer the same here

About this dataset

Context

The dataset tabulates the Harbor View 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 Harbor View. The dataset can be utilized to understand the population distribution of Harbor View by age. For example, using this dataset, we can identify the largest age group in Harbor View.

Key observations

The largest age group in Harbor View, OH was for the group of age 25 to 29 years years with a population of 31 (29.25%), according to the ACS 2019-2023 5-Year Estimates. At the same time, the smallest age group in Harbor View, OH was the Under 5 years years with a population of 0 (0%). Source: U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates

Content

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

Age groups:

• Under 5 years
• 5 to 9 years
• 10 to 14 years
• 15 to 19 years
• 20 to 24 years
• 25 to 29 years
• 30 to 34 years
• 35 to 39 years
• 40 to 44 years
• 45 to 49 years
• 50 to 54 years
• 55 to 59 years
• 60 to 64 years
• 65 to 69 years
• 70 to 74 years
• 75 to 79 years
• 80 to 84 years
• 85 years and over

Variables / Data Columns

• Age Group: This column displays the age group in consideration
• Population: The population for the specific age group in the Harbor View is shown in this column.
• % of Total Population: This column displays the population of each age group as a proportion of Harbor View 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 Harbor View Population by Age. You can refer the same here