About this dataset

Context

The dataset tabulates the data for the Harlem, GA population pyramid, which represents the Harlem population distribution across age and gender, using estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 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

• Youth dependency ratio, which is the number of children aged 0-14 per 100 persons aged 15-64, for Harlem, GA, is 41.7.
• Old-age dependency ratio, which is the number of persons aged 65 or over per 100 persons aged 15-64, for Harlem, GA, is 28.9.
• Total dependency ratio for Harlem, GA is 70.6.
• Potential support ratio, which is the number of youth (working age population) per elderly, for Harlem, GA is 3.5.

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 for the Harlem population analysis. Total expected values are 18 and are define above in the age groups section.
• Population (Male): The male population in the Harlem for the selected age group is shown in the following column.
• Population (Female): The female population in the Harlem for the selected age group is shown in the following column.
• Total Population: The total population of the Harlem for the selected age group is shown in the following column.

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 Harlem Population by Age. You can refer the same here

This intermediate level data set was extracted from the census bureau database. There are 48842 instances of data set, mix of continuous and discrete (train=32561, test=16281).

The data set has 15 attribute which include age, sex, education level and other relevant details of a person. The data set will help to improve your skills in Exploratory Data Analysis, Data Wrangling, Data Visualization and Classification Models.

Feel free to explore the data set with multiple supervised and unsupervised learning techniques. The Following description gives more details on this data set:

• age: the age of an individual.
• workclass: The type of work or employment of an individual. It can have the following categories:
  • Private: Working in the private sector.
  • Self-emp-not-inc: Self-employed individuals who are not incorporated.
  • Self-emp-inc: Self-employed individuals who are incorporated.
  • Federal-gov: Working for the federal government.
  • Local-gov: Working for the local government.
  • State-gov: Working for the state government.
  • Without-pay: Not working and without pay.
  • Never-worked: Never worked before.
• Final Weight: The weights on the CPS files are controlled to independent estimates of the civilian noninstitutional population of the US. These are prepared monthly for us by Population Division here at the Census Bureau. We use 3 sets of controls.

These are: 1. A single cell estimate of the population 16+ for each state. 2. Controls for Hispanic Origin by age and sex. 3. Controls by Race, age and sex.

We use all three sets of controls in our weighting program and "rake" through them 6 times so that by the end we come back to all the controls we used.

People with similar demographic characteristics should have similar weights. There is one important caveat to remember about this statement. That is that since the CPS sample is actually a collection of 51 state samples, each with its own probability of selection, the statement only applies within state.

• education: The highest level of education completed.
• education-num: The number of years of education completed.
• marital-status: The marital status.
• occupation: Type of work performed by an individual.
• relationship: The relationship status.
• race: The race of an individual.
• sex: The gender of an individual.
• capital-gain: The amount of capital gain (financial profit).
• capital-loss: The amount of capital loss an individual has incurred.
• hours-per-week: The number of hours works per week.
• native-country: The country of origin or the native country.
• income: The income level of an individual and serves as the target variable. It indicates whether the income is greater than $50,000 or less than or equal to $50,000, denoted as (>50K, <=50K).

About this dataset

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

• Youth dependency ratio, which is the number of children aged 0-14 per 100 persons aged 15-64, for Person County, NC, is 26.9.
• Old-age dependency ratio, which is the number of persons aged 65 or over per 100 persons aged 15-64, for Person County, NC, is 31.4.
• Total dependency ratio for Person County, NC is 58.3.
• Potential support ratio, which is the number of youth (working age population) per elderly, for Person County, NC is 3.2.

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 for the Person County population analysis. Total expected values are 18 and are define above in the age groups section.
• Population (Male): The male population in the Person County for the selected age group is shown in the following column.
• Population (Female): The female population in the Person County for the selected age group is shown in the following column.
• Total Population: The total population of the Person County for the selected age group is shown in the following column.

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 Person County Population by Age. You can refer the same here

United States Population: All Ages data was reported at 325,719.000 Person th in 2017. This records an increase from the previous number of 323,406.000 Person th for 2016. United States Population: All Ages data is updated yearly, averaging 176,356.000 Person th from Jun 1900 (Median) to 2017, with 118 observations. The data reached an all-time high of 325,719.000 Person th in 2017 and a record low of 76,094.000 Person th in 1900. United States Population: All Ages 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.G002: Population by Age. Series Remarks Population data for the years 1900 to 1949 exclude the population residing in Alaska and Hawaii. Population data for the years 1940 to 1979 cover the resident population plus Armed Forces overseas. Population data for all other years cover only the resident population.

The following data set is information obtained about counties in the United States from 2010 through 2019 through the United States Census Bureau. Information described in the data includes the age distributions, the education levels, employment statistics, ethnicity percents, houseold information, income, and other miscellneous statistics. (Values are denoted as -1, if the data is not available)

Data Dictionary

About this dataset

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.

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

This data set includes socioeconomic factors within the Town of Dumfries such as people in the labor force, people without health insurance, etc. This information comes from the most recent U.S. Census provided by the United States Census Bureau. Data will be updated accordingly with the schedule of the U.S Census. https://data.census.gov/cedsci/profile?g=1600000US5123760

Splitgraph serves as an HTTP API that lets you run SQL queries directly on this data to power Web applications. For example:

See the Splitgraph documentation for more information.

Evolution of data on Persons (2006-2021) by demographic characteristics, type of ICT use and period. National.

In August of 2018, FSSA’s Office of Healthy Opportunities deployed a social risk assessment survey. The 10-question survey was made available to anyone applying online through FSSA for health coverage, the Supplemental Nutritional Assistance Program or Temporary Assistance for Needy Families. The results of this survey are aggregated and presented below and can help communities better understand the social risk factors affecting the health of those applying for our services. Please read and review the following information regarding the use of this data prior to viewing the tool. This survey was made available to those individuals who applied online ONLY and does not represent anyone who applied in-person, by telephone, by mail or any other method. In 2018, online applications accounted for 79% of those who applied for SNAP, TANF or health coverage. Survey completion is voluntary and does not impact eligibility for SNAP, TANF or health coverage. Applications are filed at a household level and may represent several individuals. The application process identifies a primary contact person for the household, and that individual’s demographics are represented on the dashboard; for example, person’s gender, race and education level. An individual who completes more than one application and survey over any given time period is represented once for each instance, and the survey answers and demographic details are based on each application’s responses. For example, an applicant’s age, education level and survey answers can change over time, and the reporting reflects any such changes. All information is presented in aggregate to ensure personally identifiable information is protected. To protect the privacy of individuals, data representing 20 or less individuals in any county will not be displayed. I.e. it will show as blank

Demographic data about a person such as birth data, death data, sex, marital status, ethnic group and biometric identifier

Graph and download economic data for Population Estimate, Total (5-year estimate) in District of Columbia, DC (B03002001E011001) from 2009 to 2023 about DC, estimate, 5-year, persons, population, and USA.

Abstract

The L2 Voter and Demographic data 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 data is current as of February 06 2023.

Methodology

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.

Usage

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 data with the L2 Consumer Dataset.

The 'LALVOTERID' variable can also be used to validate the state. For example, let's look at the 'LALVOTERID' LALCA123456789. 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, 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 695 consistent variables. For more information about these variables, see 2022-12-31-L2-Voter-Demographic-File-Layout.xlsx.

The voter history files have different variables depending on the state. The ***2023-02-06-L2-Voter-Data-Dictionaries.tar.gz ***file expands into a folder with .csv data dictionaries for each state's demographic and voter files. While the demographic file data dictionaries should complement the 2021-11-03-L2-Voter-Demographic-File-Layout.xlsx file, the voter file data dictionaries will be unique to each state.

***Experian_Mosaic_Guide.pdf *** is a codebook for two variables which appear in the demographic tables: 'CommercialData_MosaicZ4' and 'CommercialData_MosaicZ4Global.'

***L2_Data_Dictionary.pdf ***has information about where variables were sourced from.

***2022-12-31-National-File-Notes.pdf ***contains L2 Voter and Demographic Dataset ("National File") release notes from between 2018 and 2022.

***2022-06-03_Nationwide_Congressional_District_Redistricting_Analysis.xlsx ***summarizes the redistricting that has occurred following the 2020 census.

Bulk Data Access

Data access is required to view this section.

DataMapping Tool

Data access is required to view this section.

Estimated number of persons on July 1, by 5-year age groups and gender, and median age, for Canada, provinces and territories.

Data on marriages and divorces at national level are transmitted by the National Statistics Institutes on voluntary basis in the context of the annual demographic data collections in the field of demography carried out by Eurostat.

The POPSTAT (population statistics) questionnaire collects annual mandatory and voluntary demographic data from the National Statistical Institutes. It is the most in-depth annual national and regional demographic and migration data collection. The data relate to populations, births, deaths, immigrants, emigrants, marriages and divorces, and is broken down into several categories (Article 3 of Regulation (EU) No 1260/2013 and Article 3 of Regulation (EC) No 862/2007).

The completeness of the demographic data collected on a voluntary basis depends on the availability and completeness of information provided by the National Statistical Institutes.

The following statistics on marriages and divorces are collected from the National Statistical Institutes:

• Marriages by previous legal union status of marrying persons;
• First-time marrying persons by age, year of birth and sex;
• Marriages by country of citizenship of marrying persons;
• Marriages by country of birth of marrying persons;
• Divorces by duration and year of the marriage;
• Divorces by country of citizenship of spouses;
• Divorces by country of birth of spouses.

Statistics on marriages and divorces: based on the different breakdowns of data on marriages and divorces received, Eurostat produces the following:

• Statistics available in the online table Marriage indicators (demo_nind):
  • Total number of marriages;
  • Crude marriage rate;
  • Mean age at first marriage – male;
  • Mean age at first marriage – female;
  • Total first marriage rate – male;
  • Total first marriage rate – female;
  • Proportion of first marriages – male;
  • Proportion of first marriages – female.
• Statistics available in the online table Divorce indicators (demo_ndivind):
  • Total number of divorces;
  • Crude divorce rate;
  • Divorces per 100 marriages.

Graph and download economic data for Population Estimate, Total (5-year estimate) in Person County, NC (B03002001E037145) from 2009 to 2023 about Person County, NC; Durham; NC; estimate; 5-year; persons; population; and USA.

Table of INEBase Summary of data on Persons by nationality, demographic characteristics and type of ICT use. Survey on Equipment and Use of Information and Communication Technologies in Households

Graph and download economic data for Population Estimate, Total, Not Hispanic or Latino, White Alone (5-year estimate) in District of Columbia, DC (B03002003E011001) from 2009 to 2023 about white, non-hispanic, estimate, 5-year, persons, population, and USA.

About this dataset

Context

The dataset tabulates the data for the Soddy-Daisy, TN population pyramid, which represents the Soddy-Daisy population distribution across age and gender, using estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 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

• Youth dependency ratio, which is the number of children aged 0-14 per 100 persons aged 15-64, for Soddy-Daisy, TN, is 23.2.
• Old-age dependency ratio, which is the number of persons aged 65 or over per 100 persons aged 15-64, for Soddy-Daisy, TN, is 31.7.
• Total dependency ratio for Soddy-Daisy, TN is 54.9.
• Potential support ratio, which is the number of youth (working age population) per elderly, for Soddy-Daisy, TN is 3.2.

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 for the Soddy-Daisy population analysis. Total expected values are 18 and are define above in the age groups section.
• Population (Male): The male population in the Soddy-Daisy for the selected age group is shown in the following column.
• Population (Female): The female population in the Soddy-Daisy for the selected age group is shown in the following column.
• Total Population: The total population of the Soddy-Daisy for the selected age group is shown in the following column.

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 Soddy-Daisy Population by Age. You can refer the same here

United States US: Population Projection: Mid Year data was reported at 420,267,733.000 Person in 2060. This records an increase from the previous number of 418,161,420.000 Person for 2059. United States US: Population Projection: Mid Year data is updated yearly, averaging 295,516,599.000 Person from Jun 1950 (Median) to 2060, with 111 observations. The data reached an all-time high of 420,267,733.000 Person in 2060 and a record low of 151,868,000.000 Person in 1950. United States US: Population Projection: Mid Year data remains active status in CEIC and is reported by US Census Bureau. The data is categorized under Global Database’s USA – Table US.US Census Bureau: Demographic Projection.

Population: Census: Gansu: Lanzhou data was reported at 4,359.446 Person th in 12-01-2020. This records an increase from the previous number of 3,616.163 Person th for 12-01-2010. Population: Census: Gansu: Lanzhou data is updated decadal, averaging 3,616.163 Person th from Dec 2000 (Median) to 12-01-2020, with 3 observations. The data reached an all-time high of 4,359.446 Person th in 12-01-2020 and a record low of 3,142.523 Person th in 12-01-2000. Population: Census: Gansu: Lanzhou data remains active status in CEIC and is reported by Lanzhou Municipal Bureau of Statistics. The data is categorized under China Premium Database’s Socio-Demographic – Table CN.GE: Population: Prefecture Level City: By Census.