India: Population ages 65 and above, percent of total: The latest value from 2023 is 6.92 percent, an increase from 6.7 percent in 2022. In comparison, the world average is 10.17 percent, based on data from 196 countries. Historically, the average for India from 1960 to 2023 is 4.41 percent. The minimum value, 3.3 percent, was reached in 1960 while the maximum of 6.92 percent was recorded in 2023.

This dataset is about countries per year in India. It has 64 rows. It features 3 columns: country, and median age.

dataset contains detailed financial and demographic data for 20,000 individuals, focusing on income, expenses, and potential savings across various categories. The data aims to provide insights into personal financial management and spending patterns.

• Income & Demographics:
  • Income: Monthly income in currency units.
  • Age: Age of the individual.
  • Dependents: Number of dependents supported by the individual.
  • Occupation: Type of employment or job role.
  • City_Tier: A categorical variable representing the living area tier (e.g., Tier 1, Tier 2).
• Monthly Expenses:
  • Categories like Rent, Loan_Repayment, Insurance, Groceries, Transport, Eating_Out, Entertainment, Utilities, Healthcare, Education, and Miscellaneous record various monthly expenses.
• Financial Goals & Savings:
  • Desired_Savings_Percentage and Desired_Savings: Targets for monthly savings.
  • Disposable_Income: Income remaining after all expenses are accounted for.
• Potential Savings:
  • Includes estimates of potential savings across different spending areas such as Groceries, Transport, Eating_Out, Entertainment, Utilities, Healthcare, Education, and Miscellaneous.

About this dataset

Context

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

Key observations

The largest age group in Indian Wells, CA was for the group of age 75 to 79 years years with a population of 683 (14.14%), according to the ACS 2019-2023 5-Year Estimates. At the same time, the smallest age group in Indian Wells, CA was the 20 to 24 years years with a population of 37 (0.77%). 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 Indian Wells is shown in this column.
• % of Total Population: This column displays the population of each age group as a proportion of Indian Wells 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 Indian Wells Population by Age. You can refer the same here

India: Life expectancy, in years: The latest value from 2023 is 72 years, an increase from 71.7 years in 2022. In comparison, the world average is 73.65 years, based on data from 196 countries. Historically, the average for India from 1960 to 2023 is 58.65 years. The minimum value, 45.56 years, was reached in 1965 while the maximum of 72 years was recorded in 2023.

About this dataset

Context

The dataset presents the distribution of median household income among distinct age brackets of householders in Indian Head Park. Based on the latest 2019-2023 5-Year Estimates from the American Community Survey, it displays how income varies among householders of different ages in Indian Head Park. It showcases how household incomes typically rise as the head of the household gets older. The dataset can be utilized to gain insights into age-based household income trends and explore the variations in incomes across households.

Key observations: Insights from 2023

In terms of income distribution across age cohorts, in Indian Head Park, the median household income stands at $226,538 for householders within the 25 to 44 years age group, followed by $143,201 for the 45 to 64 years age group. Notably, householders within the 65 years and over age group, had the lowest median household income at $73,929.

Content

When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates. All incomes have been adjusting for inflation and are presented in 2023-inflation-adjusted dollars.

Age groups classifications include:

• Under 25 years
• 25 to 44 years
• 45 to 64 years
• 65 years and over

Variables / Data Columns

• Age Of The Head Of Household: This column presents the age of the head of household
• Median Household Income: Median household income, in 2023 inflation-adjusted dollars for the specific age group

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 Indian Head Park median household income by age. You can refer the same here

Life expectancy at birth, male (years) in India was reported at 70.52 years in 2023, according to the World Bank collection of development indicators, compiled from officially recognized sources. India - Life expectancy at birth, male (years) - actual values, historical data, forecasts and projections were sourced from the World Bank on September of 2025.

Prison Inmates in India

Demographics, Age, Education, Caste, Wages, Rehabilitation, Technical Info

By Rajanand Ilangovan [source]

About this dataset

This dataset provides a detailed view of prison inmates in India, including their age, caste, and educational background. It includes information on inmates from all states/union territories for the year 2019 such as the number of male and female inmates aged 16-18 years, 18-30 year old inmates and those above 50 years old. The data also covers total number of penalized prisoners sentenced to death sentence, life imprisonment or executed by the state authorities. Additionally, it provides information regarding the crimehead (type) committed by an inmate along with its grand total across different age groups. This dataset not only sheds light on India’s criminal justice system but also highlights prevelance of crimes in different states and union territories as well as providing insight into crime trends across Indian states over time

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How to use the dataset

This dataset provides a comprehensive look at the demographics, crimes and sentences of Indian prison inmates in 2019. The data is broken down by state/union territory, year, crime head, age groups and gender.

This dataset can be used to understand the demographic composition of the prison population in India as well as the types of crimes committed. It can also be used to gain insight into any changes or trends related to sentencing patterns in India over time. Furthermore, this data can provide valuable insight into potential correlations between different demographic factors (such as gender and caste) and specific types of crimes or length of sentences handed out.

To use this dataset effectively there are a few important things to keep in mind: •State/UT - This column refers to individual states or union territories in India where prisons are located •Year – This column indicates which year(s) the data relates to •Both genders - Female columns refer only to female prisoners while male columns refers only to male prisoners •Age Groups – 16-18 years old = 21-30 years old = 31-50 years old = 50+ years old •Crime Head – A broad definition for each type of crime that inmates have been convicted for •No Capital Punishment – The total number sentenced with capital punishment No Life Imprisonment – The total number sentenced with life imprisonment No Executed– The total number executed from death sentence Grand Total–The overall totals for each category

By using this information it is possible to answer questions regarding topics such as sentencing trends, types of crimes committed by different age groups or genders and state-by-state variation amongst other potential queries

Research Ideas

• Using the age and gender information to develop targeted outreach strategies for prisons in order to reduce recidivism rates.
• Creating an AI-based predictive model to predict crime trends by analyzing crime head data from a particular region/state and correlating it with population demographics, economic activity, etc.
• Analyzing the caste of inmates across different states in India in order to understand patterns of discrimination within the criminal justice system

Acknowledgements

If you use this dataset in your research, please credit the original authors. Data Source

License

License: Attribution-ShareAlike 4.0 International (CC BY-SA 4.0) - You are free to: - Share - copy and redistribute the material in any medium or format for any purpose, even commercially. - Adapt - remix, transform, and build upon the material for any purpose, even commercially. - You must: - Give appropriate credit - Provide a link to the license, and indicate if changes were made. - ShareAlike - You must distribute your contributions under the same license as the original.

Columns

File: SLL_Crime_headwise_distribution_of_inmates_who_convicted.csv | Column name | Description | |:--------------------------|:---------------------------------------------------------------------------------------------------| | STATE/UT | Name of the state or union territory where the jail is located. (String) | | YEAR | Year when the inmate population data was collected. (Integer) ...

This dataset is about countries per year in India. It has 64 rows. It features 4 columns: country, fertility rate, and median age.

Life expectancy at birth, female (years) in India was reported at 73.6 years in 2023, according to the World Bank collection of development indicators, compiled from officially recognized sources. India - Life expectancy at birth, female (years) - actual values, historical data, forecasts and projections were sourced from the World Bank on September of 2025.

UNICEF's country profile for India, including under-five mortality rates, child health, education and sanitation data.

This dataset is about countries per year in India. It has 1 row and is filtered where the date is 2021. It features 4 columns: country, continent, and median age.

Life expectancy in India was 25.4 in the year 1800, and over the course of the next 220 years, it has increased to almost 70. Between 1800 and 1920, life expectancy in India remained in the mid to low twenties, with the largest declines coming in the 1870s and 1910s; this was because of the Great Famine of 1876-1878, and the Spanish Flu Pandemic of 1918-1919, both of which were responsible for the deaths of up to six and seventeen million Indians respectively; as well as the presence of other endemic diseases in the region, such as smallpox. From 1920 onwards, India's life expectancy has consistently increased, but it is still below the global average.

The median age in India was 27 years old in 2020, meaning half the population was older than that, half younger. This figure was lowest in 1970, at 18.1 years, and was projected to increase to 47.8 years old by 2100. Aging in India India has the second largest population in the world, after China. Because of the significant population growth of the past years, the age distribution remains skewed in favor of the younger age bracket. This tells a story of rapid population growth, but also of a lower life expectancy. Economic effects of a young population Many young people means that the Indian economy must support a large number of students, who demand education from the economy but cannot yet work. Educating the future workforce will be important, because the economy is growing as well and is one of the largest in the world. Failing to do this could lead to high youth unemployment and political consequences. However, a productive and young workforce could provide huge economic returns for India.

India IN: Mortality from CVD, Cancer, Diabetes or CRD between Exact Ages 30 and 70: Female data was reported at 19.800 NA in 2016. This records a decrease from the previous number of 20.000 NA for 2015. India IN: Mortality from CVD, Cancer, Diabetes or CRD between Exact Ages 30 and 70: Female data is updated yearly, averaging 21.200 NA from Dec 2000 (Median) to 2016, with 5 observations. The data reached an all-time high of 23.400 NA in 2000 and a record low of 19.800 NA in 2016. India IN: Mortality from CVD, Cancer, Diabetes or CRD between Exact Ages 30 and 70: Female data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s India – Table IN.World Bank.WDI: Health Statistics. Mortality from CVD, cancer, diabetes or CRD is the percent of 30-year-old-people who would die before their 70th birthday from any of cardiovascular disease, cancer, diabetes, or chronic respiratory disease, assuming that s/he would experience current mortality rates at every age and s/he would not die from any other cause of death (e.g., injuries or HIV/AIDS).; ; World Health Organization, Global Health Observatory Data Repository (http://apps.who.int/ghodata/).; Weighted average;

This dataset is about countries per year in India. It has 64 rows. It features 4 columns: country, armed forces personnel, and median age.

This feature layers contain demographics about age, gender, education, employment, assets & amenities as reported by Office of the Registrar General & Census Commissioner, India in the Census 2011. These attributes cover topics such as male and female population counts by age, literacy, occupation, and household characteristics.Census of India counts every resident in India at village level. It is mandated by The Census Act 1948 of the Constitution and takes place every 10 years.Other demographics layers are also available:State DemographicsDistrict DemographicsSub-district DemographicsVillage DemographicsCombined DemographicsEach layer contains the same set of demographic attributes. Each geography level has a viewing range optimal for the geography size, and the map has increasing detail as you zoom in to smaller areas.Data source: Explore Census DataAdmin boundary source (country, states, and districts): Survey of India, 2020For more information: 2011 Census Demographic ProfileFor feedback please contact: content@esri.inData Processing notes:Country, State and District boundaries are simplified representations offered from the Survey of India database.Sub-districts and village boundaries are developed based on the census provided maps.Field names and aliases are processed by Esri India as created for the ArcGIS Platform.For a list of fields and alias names, access the following excel document.Disclaimer:The boundaries may not be perfectly align with AGOL imagery. The Census PDF maps are georeferenced using Survey of India boundaries and notice alignment issues with AGOL Imagery/ Maps. 33k villages are marked as point location on Census PDFs either because of low scale maps where small villages could not have been drawn or digitization has not been completed. These villages are marked as 100m circular polygons in the data.This web layer is offered by Esri India, for ArcGIS Online subscribers. If you have any questions or comments, please let us know via content@esri.in.

About this dataset

Context

The dataset presents the the household distribution across 16 income brackets among four distinct age groups in Indian Trail: Under 25 years, 25-44 years, 45-64 years, and over 65 years. The dataset highlights the variation in household income, offering valuable insights into economic trends and disparities within different age categories, aiding in data analysis and decision-making..

Key observations

• Upon closer examination of the distribution of households among age brackets, it reveals that there are 184(1.41%) households where the householder is under 25 years old, 4,951(37.86%) households with a householder aged between 25 and 44 years, 5,924(45.30%) households with a householder aged between 45 and 64 years, and 2,019(15.44%) households where the householder is over 65 years old.
• The age group of 25 to 44 years exhibits the highest median household income, while the largest number of households falls within the 45 to 64 years bracket. This distribution hints at economic disparities within the town of Indian Trail, showcasing varying income levels among different age demographics.

Content

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

Income brackets:

• Less than $10,000
• $10,000 to $14,999
• $15,000 to $19,999
• $20,000 to $24,999
• $25,000 to $29,999
• $30,000 to $34,999
• $35,000 to $39,999
• $40,000 to $44,999
• $45,000 to $49,999
• $50,000 to $59,999
• $60,000 to $74,999
• $75,000 to $99,999
• $100,000 to $124,999
• $125,000 to $149,999
• $150,000 to $199,999
• $200,000 or more

Variables / Data Columns

• Household Income: This column showcases 16 income brackets ranging from Under $10,000 to $200,000+ ( As mentioned above).
• Under 25 years: The count of households led by a head of household under 25 years old with income within a specified income bracket.
• 25 to 44 years: The count of households led by a head of household 25 to 44 years old with income within a specified income bracket.
• 45 to 64 years: The count of households led by a head of household 45 to 64 years old with income within a specified income bracket.
• 65 years and over: The count of households led by a head of household 65 years and over old with income within a specified income bracket.

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 Indian Trail median household income by age. You can refer the same here

India: Dependent people as percent of the working age population: The latest value from 2024 is 46.56 percent, a decline from 47.01 percent in 2023. In comparison, the world average is 58.13 percent, based on data from 196 countries. Historically, the average for India from 1960 to 2024 is 68.95 percent. The minimum value, 46.56 percent, was reached in 2024 while the maximum of 82.62 percent was recorded in 1966.

India Projection: Population: 10 Years: Age: 10-19 data was reported at 257,710,442.000 Person in 2031. This records an increase from the previous number of 255,229,168.000 Person for 2021. India Projection: Population: 10 Years: Age: 10-19 data is updated yearly, averaging 256,469,805.000 Person from Mar 2021 (Median) to 2031, with 2 observations. The data reached an all-time high of 257,710,442.000 Person in 2031 and a record low of 255,229,168.000 Person in 2021. India Projection: Population: 10 Years: Age: 10-19 data remains active status in CEIC and is reported by CEIC Data. The data is categorized under India Premium Database’s Demographic – Table IN.GAI002: Population Projection: 10 Years: by Age Group.