Population, male (% of total population) in India was reported at 51.58 % in 2024, according to the World Bank collection of development indicators, compiled from officially recognized sources. India - Population, male (% of total) - 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) ...

About this dataset

Context

The dataset presents median income data over a decade or more for males and females categorized by Total, Full-Time Year-Round (FT), and Part-Time (PT) employment in Indian Beach. It showcases annual income, providing insights into gender-specific income distributions and the disparities between full-time and part-time work. The dataset can be utilized to gain insights into gender-based pay disparity trends and explore the variations in income for male and female individuals.

Key observations: Insights from 2021

Based on our analysis ACS 2017-2021 5-Year Estimates, we present the following observations: - All workers, aged 15 years and older: In Indian Beach, the median income for all workers aged 15 years and older, regardless of work hours, was $54,046 for males and $24,321 for females.

These income figures highlight a substantial gender-based income gap in Indian Beach. Women, regardless of work hours, earn 45 cents for each dollar earned by men. This significant gender pay gap, approximately 55%, underscores concerning gender-based income inequality in the town of Indian Beach.

As income data for both males and females was unavailable, conducting a comprehensive analysis of gender-based pay disparity in the town of Indian Beach was not possible.

https://i.neilsberg.com/ch/indian-beach-nc-income-by-gender.jpeg" alt="Indian Beach, NC gender based income disparity">

Content

When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2017-2021 5-Year Estimates. All incomes have been adjusting for inflation and are presented in 2022-inflation-adjusted dollars.

Gender classifications include:

• Male
• Female

Employment type classifications include:

• Full-time, year-round: A full-time, year-round worker is a person who worked full time (35 or more hours per week) and 50 or more weeks during the previous calendar year.
• Part-time: A part-time worker is a person who worked less than 35 hours per week during the previous calendar year.

Variables / Data Columns

• Year: This column presents the data year. Expected values are 2010 to 2022
• Male Total Income: Annual median income, for males regardless of work hours
• Male FT Income: Annual median income, for males working full time, year-round
• Male PT Income: Annual median income, for males working part time
• Female Total Income: Annual median income, for females regardless of work hours
• Female FT Income: Annual median income, for females working full time, year-round
• Female PT Income: Annual median income, for females working part time

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 Beach median household income by gender. You can refer the same here

Population, female (% of total population) in India was reported at 48.42 % in 2024, according to the World Bank collection of development indicators, compiled from officially recognized sources. India - Population, female (% of total) - actual values, historical data, forecasts and projections were sourced from the World Bank on September of 2025.

India Population: Census: Male: Age: 20 to 24 Year data was reported at 57,584.693 Person th in 2011. This records an increase from the previous number of 46,321.000 Person th for 2001. India Population: Census: Male: Age: 20 to 24 Year data is updated yearly, averaging 46,321.000 Person th from Mar 1991 (Median) to 2011, with 3 observations. The data reached an all-time high of 57,584.693 Person th in 2011 and a record low of 37,514.000 Person th in 1991. India Population: Census: Male: Age: 20 to 24 Year data remains active status in CEIC and is reported by Census of India. The data is categorized under India Premium Database’s Demographic – Table IN.GAD001: Census: Population: by Age Group.

India Population: Census: Male: Age: 25 to 29 year data was reported at 51,344.208 Person th in 2011. This records an increase from the previous number of 41,557.000 Person th for 2001. India Population: Census: Male: Age: 25 to 29 year data is updated yearly, averaging 41,557.000 Person th from Mar 1991 (Median) to 2011, with 3 observations. The data reached an all-time high of 51,344.208 Person th in 2011 and a record low of 34,546.000 Person th in 1991. India Population: Census: Male: Age: 25 to 29 year data remains active status in CEIC and is reported by Census of India. The data is categorized under India Premium Database’s Demographic – Table IN.GAD001: Census: Population: by Age Group.

Population ages 20-24, male (% of male population) in India was reported at 9.1077 % in 2024, according to the World Bank collection of development indicators, compiled from officially recognized sources. India - Population ages 20-24, male (% of male population) - actual values, historical data, forecasts and projections were sourced from the World Bank on September of 2025.

This dataset is based on a report 'Crimes against Women(2022)' by National Crime Records Bureau. It contains number of cases been registered across all Indian States/UTs against the crimes been committed against Women (includes adults & minors) that are recognizable within the Indian Penal Code. The gist of crimes mentioned within the dataset are: 1. Murder with Rape/Gang Rape 2. Dowry Deaths (Sec. 304B IPC) 3. Abetment to Suicide of Women (Sec. 305/306 IPC) 4. Miscarriage (Sec. 313 & 314 IPC) 5. Acid Attack (Sec. 326A IPC) 6. Attempt to Acid Attack (Sec. 326B IPC) 7. Cruelty by Husband or his relatives (Sec. 498 A IPC) 8. Kidnapping & Abduction of Women 9. Human Trafficking (Sec. 370 & 370A IPC) 10. Selling of Minor Girls (Sec. 372 IPC) 11. Buying of Minor Girls (Sec. 373 IPC) 12. Rape (Sec. 376 IPC) 13. Attempt to Commit Rape (Sec. 376/511 IPC) 14. Assault on Women with Intent to Outrage her Modesty (Sec. 354 IPC) 15. Insult to the Modesty of Women (Sec. 509 IPC) 16. Dowry Prohibition Act, 1961 17. Immoral Traffic (Prevention) Act 1956 (Women Victims cases only) 18. Protection of Women from Domestic Violence Act 19. Cyber Crimes/Information Technology Act (Women Centric Crimes only) 20. Protection of Children from Sexual Violence Act (Girl Child Victims only) 21. Indecent Representation of Women (Prohibition) Act, 1986

The gender ratio in India was 900 between 2013 and 2015. This meant, for every 1,000 males, 900 females were present. Among its states, Chhattisgarh had the highest gender ratio at 961 in 2015 and 2016, while Haryana recorded the least at 833.

India Population: Census: Age: 15 to 19 Year data was reported at 120,526.449 Person th in 03-01-2011. This records an increase from the previous number of 100,216.000 Person th for 03-01-2001. India Population: Census: Age: 15 to 19 Year data is updated decadal, averaging 100,216.000 Person th from Mar 1991 (Median) to 03-01-2011, with 3 observations. The data reached an all-time high of 120,526.449 Person th in 03-01-2011 and a record low of 79,035.000 Person th in 03-01-1991. India Population: Census: Age: 15 to 19 Year data remains active status in CEIC and is reported by Office of the Registrar General & Census Commissioner, India. The data is categorized under India Premium Database’s Demographic – Table IN.GAD001: Census: Population: by Age Group.

This statistic depicts the age distribution of India from 2013 to 2023. In 2023, about 25.06 percent of the Indian population fell into the 0-14 year category, 68.02 percent into the 15-64 age group and 6.92 percent were over 65 years of age. Age distribution in India India is one of the largest countries in the world and its population is constantly increasing. India’s society is categorized into a hierarchically organized caste system, encompassing certain rights and values for each caste. Indians are born into a caste, and those belonging to a lower echelon often face discrimination and hardship. The median age (which means that one half of the population is younger and the other one is older) of India’s population has been increasing constantly after a slump in the 1970s, and is expected to increase further over the next few years. However, in international comparison, it is fairly low; in other countries the average inhabitant is about 20 years older. But India seems to be on the rise, not only is it a member of the BRIC states – an association of emerging economies, the other members being Brazil, Russia and China –, life expectancy of Indians has also increased significantly over the past decade, which is an indicator of access to better health care and nutrition. Gender equality is still non-existant in India, even though most Indians believe that the quality of life is about equal for men and women in their country. India is patriarchal and women still often face forced marriages, domestic violence, dowry killings or rape. As of late, India has come to be considered one of the least safe places for women worldwide. Additionally, infanticide and selective abortion of female fetuses attribute to the inequality of women in India. It is believed that this has led to the fact that the vast majority of Indian children aged 0 to 6 years are male.

India: Population density, people per square km: The latest value from 2021 is 473 people per square km, an increase from 470 people per square km in 2020. In comparison, the world average is 456 people per square km, based on data from 196 countries. Historically, the average for India from 1961 to 2021 is 305 people per square km. The minimum value, 153 people per square km, was reached in 1961 while the maximum of 473 people per square km was recorded in 2021.

Abstract

In order to develop various methods of comparable data collection on health and health system responsiveness WHO started a scientific survey study in 2000-2001. This study has used a common survey instrument in nationally representative populations with modular structure for assessing health of indviduals in various domains, health system responsiveness, household health care expenditures, and additional modules in other areas such as adult mortality and health state valuations.

The health module of the survey instrument was based on selected domains of the International Classification of Functioning, Disability and Health (ICF) and was developed after a rigorous scientific review of various existing assessment instruments. The responsiveness module has been the result of ongoing work over the last 2 years that has involved international consultations with experts and key informants and has been informed by the scientific literature and pilot studies.

Questions on household expenditure and proportionate expenditure on health have been borrowed from existing surveys. The survey instrument has been developed in multiple languages using cognitive interviews and cultural applicability tests, stringent psychometric tests for reliability (i.e. test-retest reliability to demonstrate the stability of application) and most importantly, utilizing novel psychometric techniques for cross-population comparability.

The study was carried out in 61 countries completing 71 surveys because two different modes were intentionally used for comparison purposes in 10 countries. Surveys were conducted in different modes of in- person household 90 minute interviews in 14 countries; brief face-to-face interviews in 27 countries and computerized telephone interviews in 2 countries; and postal surveys in 28 countries. All samples were selected from nationally representative sampling frames with a known probability so as to make estimates based on general population parameters.

The survey study tested novel techniques to control the reporting bias between different groups of people in different cultures or demographic groups ( i.e. differential item functioning) so as to produce comparable estimates across cultures and groups. To achieve comparability, the selfreports of individuals of their own health were calibrated against well-known performance tests (i.e. self-report vision was measured against standard Snellen's visual acuity test) or against short descriptions in vignettes that marked known anchor points of difficulty (e.g. people with different levels of mobility such as a paraplegic person or an athlete who runs 4 km each day) so as to adjust the responses for comparability . The same method was also used for self-reports of individuals assessing responsiveness of their health systems where vignettes on different responsiveness domains describing different levels of responsiveness were used to calibrate the individual responses.

This data are useful in their own right to standardize indicators for different domains of health (such as cognition, mobility, self care, affect, usual activities, pain, social participation, etc.) but also provide a better measurement basis for assessing health of the populations in a comparable manner. The data from the surveys can be fed into composite measures such as "Healthy Life Expectancy" and improve the empirical data input for health information systems in different regions of the world. Data from the surveys were also useful to improve the measurement of the responsiveness of different health systems to the legitimate expectations of the population.

Kind of data

Sample survey data [ssd]

Sampling procedure

The survey was conducted in one state of India, Andhra Pradesh, and a sample of 5,000 respondents was used. The sampling procedure for the selection of clusters was a multistage, stratified and random procedure. The following strata were sampled: Rural, Urban (Municipalities), Urban (Municipal Corporations), Hyderabad.

Electoral rosters were used to select households. More females (53.3%) than males (46.7%) were interviewed.

The main problem that India faced was the floods in August, which delayed fieldwork as it affected infrastructure and communications. Some areas inland could only be reached once the rain had stopped.

Mode of data collection

Face-to-face [f2f]

Cleaning operations

Data Coding At each site the data was coded by investigators to indicate the respondent status and the selection of the modules for each respondent within the survey design. After the interview was edited by the supervisor and considered adequate it was entered locally.

Data Entry Program A data entry program was developed in WHO specifically for the survey study and provided to the sites. It was developed using a database program called the I-Shell (short for Interview Shell), a tool designed for easy development of computerized questionnaires and data entry (34). This program allows for easy data cleaning and processing.

The data entry program checked for inconsistencies and validated the entries in each field by checking for valid response categories and range checks. For example, the program didn’t accept an age greater than 120. For almost all of the variables there existed a range or a list of possible values that the program checked for.

In addition, the data was entered twice to capture other data entry errors. The data entry program was able to warn the user whenever a value that did not match the first entry was entered at the second data entry. In this case the program asked the user to resolve the conflict by choosing either the 1st or the 2nd data entry value to be able to continue. After the second data entry was completed successfully, the data entry program placed a mark in the database in order to enable the checking of whether this process had been completed for each and every case.

Data Transfer The data entry program was capable of exporting the data that was entered into one compressed database file which could be easily sent to WHO using email attachments or a file transfer program onto a secure server no matter how many cases were in the file. The sites were allowed the use of as many computers and as many data entry personnel as they wanted. Each computer used for this purpose produced one file and they were merged once they were delivered to WHO with the help of other programs that were built for automating the process. The sites sent the data periodically as they collected it enabling the checking procedures and preliminary analyses in the early stages of the data collection.

Data quality checks Once the data was received it was analyzed for missing information, invalid responses and representativeness. Inconsistencies were also noted and reported back to sites.

Data Cleaning and Feedback After receipt of cleaned data from sites, another program was run to check for missing information, incorrect information (e.g. wrong use of center codes), duplicated data, etc. The output of this program was fed back to sites regularly. Mainly, this consisted of cases with duplicate IDs, duplicate cases (where the data for two respondents with different IDs were identical), wrong country codes, missing age, sex, education and some other important variables.

In 2023, India had over 1.2 billion internet users across the country. This figure was projected to grow to over 1.6 billion users by 2050, indicating a big market potential in internet services for the South Asian country. In fact, India was ranked as the second largest online market worldwide in 2022, second only to China. The number of internet users was estimated to increase in both urban as well as rural regions, indicating a dynamic growth in access to internet.

Mobile connectivity

Of the total internet users in the country, a majority of the people access the internet via their mobile phones. There were nearly the same amount of smartphone users as internet users across the country. Cheap availability of mobile data, a growing smartphone user base in the country along with the utility value of smartphones compared to desktops and tablets are some of the factors contributing to the mobile heavy internet access in India.

Growth is on the cards

Despite the large number of internet users in the country, the internet penetration levels took longer to catch up equally. At the same time, the number of women who have access to internet is much lower than men in the country, and the bias is even more evident in rural India. Similarly, internet usage is lower among older adults in the country due to internet literacy and technological know-how. By encouraging internet accessibility among marginalized groups including women, older people and rural inhabitants in the country, India’s digital footprint has significant headroom to grow.

Introduction

Welcome to the Indian English Language Visual Speech Dataset! This dataset is a collection of diverse, single-person unscripted spoken videos supporting research in visual speech recognition, emotion detection, and multimodal communication.

Dataset Content

This visual speech dataset contains 1000 videos in Indian English language each paired with a corresponding high-fidelity audio track. Each participant is answering a specific question in a video in an unscripted and spontaneous nature.

Video Data

While recording each video extensive guidelines are kept in mind to maintain the quality and diversity.

Metadata

The dataset provides comprehensive metadata for each video recording and participant:

The internet penetration rate in India rose over 55 percent in 2025, from about 14 percent in 2014. Although these figures seem relatively low, it meant that more than half of the population of 1.4 billion people had internet access that year. This also ranked the country second in the world in terms of active internet users. Internet availability and accessibility By 2021, the number of internet connections across the country tripled with urban areas accounting for a higher density of connections than rural regions. Despite incredibly low internet prices, internet usage in India has yet to reach its full potential. Lack of awareness and a tangible gender gap lie at the heart of the matter, with affordable mobile handsets and mobile internet connections presenting only a partial solution. Reliance Jio was the popular choice among Indian internet subscribers, offering them wider coverage at cheap rates. Digital living Home to one of the largest bases of netizens in the world, India is abuzz with internet activities being carried out every moment of every day. From information and research to shopping and entertainment to living in smart homes, Indians have welcomed digital living with open arms. Among these, social media usage was one of the most common reasons for accessing the internet.

India Population: Census: Male: Age: 50 to 54 Year data was reported at 25,843.266 Person th in 2011. This records an increase from the previous number of 19,852.000 Person th for 2001. India Population: Census: Male: Age: 50 to 54 Year data is updated yearly, averaging 19,852.000 Person th from Mar 1991 (Median) to 2011, with 3 observations. The data reached an all-time high of 25,843.266 Person th in 2011 and a record low of 16,905.000 Person th in 1991. India Population: Census: Male: Age: 50 to 54 Year data remains active status in CEIC and is reported by Census of India. The data is categorized under India Premium Database’s Demographic – Table IN.GAD001: Census: Population: by Age Group.

Population ages 80 and above, male (% of male population) in India was reported at 0.8939 % in 2024, according to the World Bank collection of development indicators, compiled from officially recognized sources. India - Population ages 80 and above, male (% of male population) - actual values, historical data, forecasts and projections were sourced from the World Bank on September of 2025.

The dataset contains state-wise National Family Health Survey (NFHS) compiled data on various family planning, childbirth, population, medical, health and other parameters which provide statistical indicators data on family profile and health status in India. There are 100+ indicators covered in the survey which broadly fall in the following categories: Health and Wellness, Maternal and Child Health, Family Planning and Reproductive Health, Disease Screening and Prevention, Social and Economic Factors, General Healthcare and Treatment

The different types of health data contained in the dataset include Anaemia among women and children, blood sugar levels and hypertension among men and women, tobacco and alcohol consumption among adults, delivery care and child feeding practices of women, quality of family planning services, screening of cancer among women, marriage and family, maternity care, nutritional status of women, child vaccinations and vitamin A supplementation, treatment of childhood diseases, etc.

Within these categories of health data, the dataset contains indicators data such as births attended by skilled health care professionals and caesarean section, number of children with under and heavy weight, stunted growth, their different vaccations status, male and female sterilization, consumption of iron folic acid among mothers, mother who had antenatal, postnatal, neonatal services, women who are obese and at the risk of weight to hip ratio, educational status among women and children, sanitation, birth and sex ratio, etc.

All of the data is compiled from the NFHS 4th and 5th survey reports. The The NFHS is a collaborative project of the International Institute for Population Sciences(IIPS), aimed at providing health data to strengthen India's health policies and programmes.

There are 100+ indicators covered in the survey which broadly fall in the following categories: Health and Wellness, Maternal and Child Health, Family Planning and Reproductive Health, Disease Screening and Prevention, Social and Economic Factors, General Healthcare and Treatment