Millennials were the largest generation group in the United States in 2024, with an estimated population of ***** million. Born between 1981 and 1996, Millennials recently surpassed Baby Boomers as the biggest group, and they will continue to be a major part of the population for many years. The rise of Generation Alpha Generation Alpha is the most recent to have been named, and many group members will not be able to remember a time before smartphones and social media. As of 2024, the oldest Generation Alpha members were still only aging into adolescents. However, the group already makes up around ***** percent of the U.S. population, and they are said to be the most racially and ethnically diverse of all the generation groups. Boomers vs. Millennials The number of Baby Boomers, whose generation was defined by the boom in births following the Second World War, has fallen by around ***** million since 2010. However, they remain the second-largest generation group, and aging Boomers are contributing to steady increases in the median age of the population. Meanwhile, the Millennial generation continues to grow, and one reason for this is the increasing number of young immigrants arriving in the United States.

About this dataset

Context

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

Key observations

The largest age group in United States was for the group of age 25-29 years with a population of 22,854,328 (6.93%), according to the 2021 American Community Survey. At the same time, the smallest age group in United States was the 80-84 years with a population of 5,932,196 (1.80%). 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 United States is shown in this column.
• % of Total Population: This column displays the population of each age group as a proportion of United States 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 United States Population by Age. You can refer the same here

In 2024, Millennials were the largest generation group in the United States, making up about 21.81 percent of the population. However, Generation Z was not far behind, with Gen Z accounting for around 20.81 percent of the population in that year.

The statistic shows the number of people in the U.S. in 2011 and 2030, by generation. By 2030, the Millennial generation will have 78 million people whereas the Boomer generation will only have 56 million people in the United States.

About this dataset

Context

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

Key observations

The largest age group in Florida, OH was for the group of age 55 to 59 years years with a population of 58 (22.48%), according to the ACS 2018-2022 5-Year Estimates. At the same time, the smallest age group in Florida, OH was the 75 to 79 years years with a population of 1 (0.39%). 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 Florida is shown in this column.
• % of Total Population: This column displays the population of each age group as a proportion of Florida 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 Florida Population by Age. You can refer the same here

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.

analyze the current population survey (cps) annual social and economic supplement (asec) with r the annual march cps-asec has been supplying the statistics for the census bureau's report on income, poverty, and health insurance coverage since 1948. wow. the us census bureau and the bureau of labor statistics ( bls) tag-team on this one. until the american community survey (acs) hit the scene in the early aughts (2000s), the current population survey had the largest sample size of all the annual general demographic data sets outside of the decennial census - about two hundred thousand respondents. this provides enough sample to conduct state- and a few large metro area-level analyses. your sample size will vanish if you start investigating subgroups b y state - consider pooling multiple years. county-level is a no-no. despite the american community survey's larger size, the cps-asec contains many more variables related to employment, sources of income, and insurance - and can be trended back to harry truman's presidency. aside from questions specifically asked about an annual experience (like income), many of the questions in this march data set should be t reated as point-in-time statistics. cps-asec generalizes to the united states non-institutional, non-active duty military population. the national bureau of economic research (nber) provides sas, spss, and stata importation scripts to create a rectangular file (rectangular data means only person-level records; household- and family-level information gets attached to each person). to import these files into r, the parse.SAScii function uses nber's sas code to determine how to import the fixed-width file, then RSQLite to put everything into a schnazzy database. you can try reading through the nber march 2012 sas importation code yourself, but it's a bit of a proc freak show. this new github repository contains three scripts: 2005-2012 asec - download all microdata.R down load the fixed-width file containing household, family, and person records import by separating this file into three tables, then merge 'em together at the person-level download the fixed-width file containing the person-level replicate weights merge the rectangular person-level file with the replicate weights, then store it in a sql database create a new variable - one - in the data table 2012 asec - analysis examples.R connect to the sql database created by the 'download all microdata' progr am create the complex sample survey object, using the replicate weights perform a boatload of analysis examples replicate census estimates - 2011.R connect to the sql database created by the 'download all microdata' program create the complex sample survey object, using the replicate weights match the sas output shown in the png file below 2011 asec replicate weight sas output.png statistic and standard error generated from the replicate-weighted example sas script contained in this census-provided person replicate weights usage instructions document. click here to view these three scripts for more detail about the current population survey - annual social and economic supplement (cps-asec), visit: the census bureau's current population survey page the bureau of labor statistics' current population survey page the current population survey's wikipedia article notes: interviews are conducted in march about experiences during the previous year. the file labeled 2012 includes information (income, work experience, health insurance) pertaining to 2011. when you use the current populat ion survey to talk about america, subract a year from the data file name. as of the 2010 file (the interview focusing on america during 2009), the cps-asec contains exciting new medical out-of-pocket spending variables most useful for supplemental (medical spending-adjusted) poverty research. confidential to sas, spss, stata, sudaan users: why are you still rubbing two sticks together after we've invented the butane lighter? time to transition to r. :D

United States US: Population: as % of Total: Female: Aged 15-64 data was reported at 64.768 % in 2017. This records a decrease from the previous number of 65.038 % for 2016. United States US: Population: as % of Total: Female: Aged 15-64 data is updated yearly, averaging 64.683 % from Dec 1960 (Median) to 2017, with 58 observations. The data reached an all-time high of 66.046 % in 2009 and a record low of 59.938 % in 1962. United States US: Population: as % of Total: Female: Aged 15-64 data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s USA – Table US.World Bank: Population and Urbanization Statistics. Female population between the ages 15 to 64 as a percentage of the total female population. Population is based on the de facto definition of population, which counts all residents regardless of legal status or citizenship.; ; World Bank staff estimates based on age/sex distributions of United Nations Population Division's World Population Prospects: 2017 Revision.; Weighted average; Relevance to gender indicator: Knowing how many girls, adolescents and women there are in a population helps a country in determining its provision of services.

Graph and download economic data for Population, Total for United States (POPTOTUSA647NWDB) from 1960 to 2024 about population and USA.

Abstract (en): Extracted from the 2002 Census of Governments, this dataset provides the number of general-purpose local governments in each United States Metropolitan Statistical Area (MSA). Data from Consolidated Metropolitan Statistical Areas (CMSAs) and their component Primary Metropolitan Statistical Areas (PMSAs) are included. There are nine variables in this study. They contain information on locations (city and state); Metropolitan Statistical Areas; population at each location in the year 2000; number of General-Purpose Governments at each location as well as per 100,000 people; water, land, and total area in square miles; and General-Purpose Governments per 100,000 square miles of land area. ICPSR data undergo a confidentiality review and are altered when necessary to limit the risk of disclosure. ICPSR also routinely creates ready-to-go data files along with setups in the major statistical software formats as well as standard codebooks to accompany the data. In addition to these procedures, ICPSR performed the following processing steps for this data collection: Created variable labels and/or value labels.; Checked for undocumented or out-of-range codes.. Number of General Purpose Local Governments in United States Metropolitan Statistical Areas Smallest Geographic Unit: Metropolitan Statistical Areas

Context

There are a number of Kaggle datasets that provide spatial data around New York City. For many of these, it may be quite interesting to relate the data to the demographic and economic characteristics of nearby neighborhoods. I hope this data set will allow for making these comparisons without too much difficulty.

Exploring the data and making maps could be quite interesting as well.

Content

This dataset contains two CSV files:

1. nyc_census_tracts.csv

   This file contains a selection of census data taken from the ACS DP03 and DP05 tables. Things like total population, racial/ethnic demographic information, employment and commuting characteristics, and more are contained here. There is a great deal of additional data in the raw tables retrieved from the US Census Bureau website, so I could easily add more fields if there is enough interest.

   I obtained data for individual census tracts, which typically contain several thousand residents.

2. census_block_loc.csv

   For this file, I used an online FCC census block lookup tool to retrieve the census block code for a 200 x 200 grid containing New York City and a bit of the surrounding area. This file contains the coordinates and associated census block codes along
   with the state and county names to make things a bit more readable to users.

   Each census tract is split into a number of blocks, so one must extract the census tract code from the block code.

Acknowledgements

The data here was taken from the American Community Survey 2015 5-year estimates (https://factfinder.census.gov/faces/nav/jsf/pages/index.xhtml).

The census block coordinate data was taken from the FCC Census Block Conversions API (https://www.fcc.gov/general/census-block-conversions-api)

As public data from the US government, this is not subject to copyright within the US and should be considered public domain.

When I was searching for COVID-19 datasets online, I soon realized that there were no comprehensive datasets of the United States on a county level basis which included social, economic, and demographic factors in addition to the general case information that was already available on several sites. To quench my thirst for clean and relevant data, I proceeded to gather information from several various sources to compile the dataset I was looking for.

I started by looking for a reliable dataset that has general information such as confirmed cases, deaths, etc. I found John Hopkin's COVID-19 dataset to be the best one for this purpose as it is well organized and updated daily. Then, I set out looking for economic factors and population data for each county in the United States. I found a collection of such files compiled by the Economic Research Service branch of the USDA on their website. Finally, I had to find a dataset which had racial and demographic information for each county, which I found on the US Census Bureau's website under a page which was dedicated to county population data by several characteristics. Now that I had all the data I was looking for, I proceeded to find which counties were common in all datasets. After several hours of cleaning each dataset and extracting relevant information, I combined all the information into one CSV file with 2959 counties of clean information - exactly what I was looking for.

I hope that the Kaggle community will use this dataset to answer important questions regarding COVID-19 in the United States and the role that external economic, social, and demographic factors play in the shaping of the pandemic. I know that there are several patterns to be discovered and I sincerely hope that this helps our community understand just a little more about the pandemic than we do right now.

Graph and download economic data for Infra-Annual Labor Statistics: Working-Age Population Total: From 15 to 64 Years for United States (LFWA64TTUSM647S) from Jan 1977 to May 2025 about working-age, 15 to 64 years, population, and USA.

United States US: Population: Female: Aged 15-64 data was reported at 106,545,028.000 Person in 2017. This records an increase from the previous number of 106,254,414.000 Person for 2016. United States US: Population: Female: Aged 15-64 data is updated yearly, averaging 81,112,897.000 Person from Dec 1960 (Median) to 2017, with 58 observations. The data reached an all-time high of 106,545,028.000 Person in 2017 and a record low of 54,897,168.000 Person in 1960. United States US: Population: Female: Aged 15-64 data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s USA – Table US.World Bank: Population and Urbanization Statistics. Female population between the ages 15 to 64. Population is based on the de facto definition of population, which counts all residents regardless of legal status or citizenship.; ; World Bank staff estimates using the World Bank's total population and age/sex distributions of the United Nations Population Division's World Population Prospects: 2017 Revision.; Sum; Relevance to gender indicator: Knowing how many girls, adolescents and women there are in a population helps a country in determining its provision of services.

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.

GapMaps GIS data for USA and Canada sourced from Applied Geographic Solutions (AGS) includes an extensive range of the highest quality demographic and lifestyle segmentation products. All databases are derived from superior source data and the most sophisticated, refined, and proven methodologies.

GIS Data attributes include:

1. Latest Estimates and Projections The estimates and projections database includes a wide range of core demographic data variables for the current year and 5- year projections, covering five broad topic areas: population, households, income, labor force, and dwellings.

2. Crime Risk Crime Risk is the result of an extensive analysis of a rolling seven years of FBI crime statistics. Based on detailed modeling of the relationships between crime and demographics, Crime Risk provides an accurate view of the relative risk of specific crime types (personal, property and total) at the block and block group level.

3. Panorama Segmentation AGS has created a segmentation system for the United States called Panorama. Panorama has been coded with the MRI Survey data to bring you Consumer Behavior profiles associated with this segmentation system.

4. Business Counts Business Counts is a geographic summary database of business establishments, employment, occupation and retail sales.

5. Non-Resident Population The AGS non-resident population estimates utilize a wide range of data sources to model the factors which drive tourists to particular locations, and to match that demand with the supply of available accommodations.

6. Consumer Expenditures AGS provides current year and 5-year projected expenditures for over 390 individual categories that collectively cover almost 95% of household spending.

7. Retail Potential This tabulation utilizes the Census of Retail Trade tables which cross-tabulate store type by merchandise line.

8. Environmental Risk The environmental suite of data consists of several separate database components including: -Weather Risks -Seismological Risks -Wildfire Risk -Climate -Air Quality -Elevation and terrain

Primary Use Cases for GapMaps GIS Data:

1. Retail (eg. Fast Food/ QSR, Cafe, Fitness, Supermarket/Grocery)
2. Customer Profiling: get a detailed understanding of the demographic & segmentation profile of your customers, where they work and their spending potential
3. Analyse your trade areas at a granular census block level using all the key metrics
4. Site Selection: Identify optimal locations for future expansion and benchmark performance across existing locations.
5. Target Marketing: Develop effective marketing strategies to acquire more customers.

6. Integrate AGS demographic data with your existing GIS or BI platform to generate powerful visualizations.

7. Finance / Insurance (eg. Hedge Funds, Investment Advisors, Investment Research, REITs, Private Equity, VC)

8. Network Planning

9. Customer (Risk) Profiling for insurance/loan approvals

10. Target Marketing

11. Competitive Analysis

12. Market Optimization

13. Commercial Real-Estate (Brokers, Developers, Investors, Single & Multi-tenant O/O)

14. Tenant Recruitment

15. Target Marketing

16. Market Potential / Gap Analysis

17. Marketing / Advertising (Billboards/OOH, Marketing Agencies, Indoor Screens)

18. Customer Profiling

19. Target Marketing

20. Market Share Analysis

This dataset was utilized a join from enriched tables from ESRI which was curated from the 2020 Census from the United States Census Bureau, American Community Survey (ACS) and for county boundaries created by Office of Information Technology Services Next Generation 9-1-1 team in collaboration with all 44 counties of Idaho. This layer has information for all cities within Idaho regarding the county population common behaviors for 2024.For more information on how the data is curated for the Enrich tool please go the link below. 2024/2029 Esri Updated Demographics

This data collection contains current population estimates and per capita money income for counties and minor civil divisions in each state. These estimates were developed to provide updates of the data elements in Federal Revenue Sharing allocations under the state and local Fiscal Assistance Act of 1972. Population estimates recorded in the dataset are for July 1, 1976, while per capita income estimates are for 1975. The units recorded in the data collection include counties, incorporated places, certain towns in New England, New York, and Wisconsin, and townships in other states. Certain Midwestern states may have active minor civil divisions in some counties, but not in others. In additional to these estimates, April 1, 1970, population and 1969 and 1975 per capita money income are included for each area. POPULATION AND INCOME ESTIMATES FOR THE UNITED STATES, 1969-1973 (ICPSR 0078) and POPULATION AND PER CAPITA INCOME ESTIMATES, 1969-1975 (ICPSR 7577) contain similar data for earlier years.

The Profiles of General Demographic Characteristics data are released as individual files for each of the 50 states, the District of Columbia, and Puerto Rico, as well as for all 50 states combined (Part 61) and for the entire United States (Part 60). The files contain the 100-percent data, which is the information compiled from questions asked of all people and about every housing unit. The population items include sex, age, race, Hispanic or Latino, household relationship, household type, group quarters population, housing occupancy, and housing tenure. The profiles include a total of 71 population and 25 housing data items. (Source: downloaded from ICPSR 7/13/10)

Please Note: This dataset is part of the historical CISER Data Archive Collection and is also available at ICPSR at https://doi.org/10.3886/ICPSR03192.v1. We highly recommend using the ICPSR version as they may make this dataset available in multiple data formats in the future.

Graph and download economic data for Population (POPTHM) from Jan 1959 to May 2025 about population and USA.