19 datasets found
  1. N

    Indian Village, IN Population Breakdown by Gender Dataset: Male and Female...

    • neilsberg.com
    csv, json
    Updated Feb 24, 2025
    + more versions
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    Neilsberg Research (2025). Indian Village, IN Population Breakdown by Gender Dataset: Male and Female Population Distribution // 2025 Edition [Dataset]. https://www.neilsberg.com/research/datasets/b23a9bd0-f25d-11ef-8c1b-3860777c1fe6/
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    json, csvAvailable download formats
    Dataset updated
    Feb 24, 2025
    Dataset authored and provided by
    Neilsberg Research
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Area covered
    IN, Indian Village
    Variables measured
    Male Population, Female Population, Male Population as Percent of Total Population, Female Population as Percent of Total Population
    Measurement technique
    The data presented in this dataset is derived from the latest U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates. To measure the two variables, namely (a) population and (b) population as a percentage of the total population, we initially analyzed and categorized the data for each of the gender classifications (biological sex) reported by the US Census Bureau. For further information regarding these estimates, please feel free to reach out to us via email at research@neilsberg.com.
    Dataset funded by
    Neilsberg Research
    Description
    About this dataset

    Context

    The dataset tabulates the population of Indian Village by gender, including both male and female populations. This dataset can be utilized to understand the population distribution of Indian Village across both sexes and to determine which sex constitutes the majority.

    Key observations

    There is a majority of female population, with 56.64% of total population being female. 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.

    Scope of gender :

    Please note that American Community Survey asks a question about the respondents current sex, but not about gender, sexual orientation, or sex at birth. The question is intended to capture data for biological sex, not gender. Respondents are supposed to respond with the answer as either of Male or Female. Our research and this dataset mirrors the data reported as Male and Female for gender distribution analysis. No further analysis is done on the data reported from the Census Bureau.

    Variables / Data Columns

    • Gender: This column displays the Gender (Male / Female)
    • Population: The population of the gender in the Indian Village is shown in this column.
    • % of Total Population: This column displays the percentage distribution of each gender as a proportion of Indian Village 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 Village Population by Race & Ethnicity. You can refer the same here

  2. d

    All India, Gender, age-group-wise population distribution across different...

    • dataful.in
    Updated Jun 13, 2025
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    Dataful (Factly) (2025). All India, Gender, age-group-wise population distribution across different census years. [Dataset]. https://dataful.in/datasets/19745
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    xlsx, csv, application/x-parquetAvailable download formats
    Dataset updated
    Jun 13, 2025
    Dataset authored and provided by
    Dataful (Factly)
    License

    https://dataful.in/terms-and-conditionshttps://dataful.in/terms-and-conditions

    Area covered
    India
    Variables measured
    Amount
    Description

    This dataset contains the All-India, gender and age-group wise distribution of population for each census year.

  3. India's gender ratio 2005-2021

    • statista.com
    Updated May 14, 2024
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    Statista (2024). India's gender ratio 2005-2021 [Dataset]. https://www.statista.com/statistics/617361/gender-ratio-india/
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    Dataset updated
    May 14, 2024
    Dataset authored and provided by
    Statistahttp://statista.com/
    Area covered
    India
    Description

    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.

  4. w

    India - National Family Health Survey 1998-1999 - Dataset - waterdata

    • wbwaterdata.org
    Updated Mar 16, 2020
    + more versions
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    (2020). India - National Family Health Survey 1998-1999 - Dataset - waterdata [Dataset]. https://wbwaterdata.org/dataset/india-national-family-health-survey-1998-1999
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    Dataset updated
    Mar 16, 2020
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Area covered
    India
    Description

    The second National Family Health Survey (NFHS-2), conducted in 1998-99, provides information on fertility, mortality, family planning, and important aspects of nutrition, health, and health care. The International Institute for Population Sciences (IIPS) coordinated the survey, which collected information from a nationally representative sample of more than 90,000 ever-married women age 15-49. The NFHS-2 sample covers 99 percent of India's population living in all 26 states. This report is based on the survey data for 25 of the 26 states, however, since data collection in Tripura was delayed due to local problems in the state. IIPS also coordinated the first National Family Health Survey (NFHS-1) in 1992-93. Most of the types of information collected in NFHS-2 were also collected in the earlier survey, making it possible to identify trends over the intervening period of six and one-half years. In addition, the NFHS-2 questionnaire covered a number of new or expanded topics with important policy implications, such as reproductive health, women's autonomy, domestic violence, women's nutrition, anaemia, and salt iodization. The NFHS-2 survey was carried out in two phases. Ten states were surveyed in the first phase which began in November 1998 and the remaining states (except Tripura) were surveyed in the second phase which began in March 1999. The field staff collected information from 91,196 households in these 25 states and interviewed 89,199 eligible women in these households. In addition, the survey collected information on 32,393 children born in the three years preceding the survey. One health investigator on each survey team measured the height and weight of eligible women and children and took blood samples to assess the prevalence of anaemia. SUMMARY OF FINDINGS POPULATION CHARACTERISTICS Three-quarters (73 percent) of the population lives in rural areas. The age distribution is typical of populations that have recently experienced a fertility decline, with relatively low proportions in the younger and older age groups. Thirty-six percent of the population is below age 15, and 5 percent is age 65 and above. The sex ratio is 957 females for every 1,000 males in rural areas but only 928 females for every 1,000 males in urban areas, suggesting that more men than women have migrated to urban areas. The survey provides a variety of demographic and socioeconomic background information. In the country as a whole, 82 percent of household heads are Hindu, 12 percent are Muslim, 3 percent are Christian, and 2 percent are Sikh. Muslims live disproportionately in urban areas, where they comprise 15 percent of household heads. Nineteen percent of household heads belong to scheduled castes, 9 percent belong to scheduled tribes, and 32 percent belong to other backward classes (OBCs). Two-fifths of household heads do not belong to any of these groups. Questions about housing conditions and the standard of living of households indicate some improvements since the time of NFHS-1. Sixty percent of households in India now have electricity and 39 percent have piped drinking water compared with 51 percent and 33 percent, respectively, at the time of NFHS-1. Sixty-four percent of households have no toilet facility compared with 70 percent at the time of NFHS-1. About three-fourths (75 percent) of males and half (51 percent) of females age six and above are literate, an increase of 6-8 percentage points from literacy rates at the time of NFHS-1. The percentage of illiterate males varies from 6-7 percent in Mizoram and Kerala to 37 percent in Bihar and the percentage of illiterate females varies from 11 percent in Mizoram and 15 percent in Kerala to 65 percent in Bihar. Seventy-nine percent of children age 6-14 are attending school, up from 68 percent in NFHS-1. The proportion of children attending school has increased for all ages, particularly for girls, but girls continue to lag behind boys in school attendance. Moreover, the disparity in school attendance by sex grows with increasing age of children. At age 6-10, 85 percent of boys attend school compared with 78 percent of girls. By age 15-17, 58 percent of boys attend school compared with 40 percent of girls. The percentage of girls 6-17 attending school varies from 51 percent in Bihar and 56 percent in Rajasthan to over 90 percent in Himachal Pradesh and Kerala. Women in India tend to marry at an early age. Thirty-four percent of women age 15-19 are already married including 4 percent who are married but gauna has yet to be performed. These proportions are even higher in the rural areas. Older women are more likely than younger women to have married at an early age: 39 percent of women currently age 45-49 married before age 15 compared with 14 percent of women currently age 15-19. Although this indicates that the proportion of women who marry young is declining rapidly, half the women even in the age group 20-24 have married before reaching the legal minimum age of 18 years. On average, women are five years younger than the men they marry. The median age at marriage varies from about 15 years in Madhya Pradesh, Bihar, Uttar Pradesh, Rajasthan, and Andhra Pradesh to 23 years in Goa. As part of an increasing emphasis on gender issues, NFHS-2 asked women about their participation in household decisionmaking. In India, 91 percent of women are involved in decision-making on at least one of four selected topics. A much lower proportion (52 percent), however, are involved in making decisions about their own health care. There are large variations among states in India with regard to women's involvement in household decisionmaking. More than three out of four women are involved in decisions about their own health care in Himachal Pradesh, Meghalaya, and Punjab compared with about two out of five or less in Madhya Pradesh, Orissa, and Rajasthan. Thirty-nine percent of women do work other than housework, and more than two-thirds of these women work for cash. Only 41 percent of women who earn cash can decide independently how to spend the money that they earn. Forty-three percent of working women report that their earnings constitute at least half of total family earnings, including 18 percent who report that the family is entirely dependent on their earnings. Women's work-participation rates vary from 9 percent in Punjab and 13 percent in Haryana to 60-70 percent in Manipur, Nagaland, and Arunachal Pradesh. FERTILITY AND FAMILY PLANNING Fertility continues to decline in India. At current fertility levels, women will have an average of 2.9 children each throughout their childbearing years. The total fertility rate (TFR) is down from 3.4 children per woman at the time of NFHS-1, but is still well above the replacement level of just over two children per woman. There are large variations in fertility among the states in India. Goa and Kerala have attained below replacement level fertility and Karnataka, Himachal Pradesh, Tamil Nadu, and Punjab are at or close to replacement level fertility. By contrast, fertility is 3.3 or more children per woman in Meghalaya, Uttar Pradesh, Rajasthan, Nagaland, Bihar, and Madhya Pradesh. More than one-third to less than half of all births in these latter states are fourth or higher-order births compared with 7-9 percent of births in Kerala, Goa, and Tamil Nadu. Efforts to encourage the trend towards lower fertility might usefully focus on groups within the population that have higher fertility than average. In India, rural women and women from scheduled tribes and scheduled castes have somewhat higher fertility than other women, but fertility is particularly high for illiterate women, poor women, and Muslim women. Another striking feature is the high level of childbearing among young women. More than half of women age 20-49 had their first birth before reaching age 20, and women age 15-19 account for almost one-fifth of total fertility. Studies in India and elsewhere have shown that health and mortality risks increase when women give birth at such young ages?both for the women themselves and for their children. Family planning programmes focusing on women in this age group could make a significant impact on maternal and child health and help to reduce fertility. INFANT AND CHILD MORTALITY NFHS-2 provides estimates of infant and child mortality and examines factors associated with the survival of young children. During the five years preceding the survey, the infant mortality rate was 68 deaths at age 0-11 months per 1,000 live births, substantially lower than 79 per 1,000 in the five years preceding the NFHS-1 survey. The child mortality rate, 29 deaths at age 1-4 years per 1,000 children reaching age one, also declined from the corresponding rate of 33 per 1,000 in NFHS-1. Ninety-five children out of 1,000 born do not live to age five years. Expressed differently, 1 in 15 children die in the first year of life, and 1 in 11 die before reaching age five. Child-survival programmes might usefully focus on specific groups of children with particularly high infant and child mortality rates, such as children who live in rural areas, children whose mothers are illiterate, children belonging to scheduled castes or scheduled tribes, and children from poor households. Infant mortality rates are more than two and one-half times as high for women who did not receive any of the recommended types of maternity related medical care than for mothers who did receive all recommended types of care. HEALTH, HEALTH CARE, AND NUTRITION Promotion of maternal and child health has been one of the most important components of the Family Welfare Programme of the Government of India. One goal is for each pregnant woman to receive at least three antenatal check-ups plus two tetanus toxoid injections and a full course of iron and folic acid supplementation. In India, mothers of 65 percent of the children born in the three years preceding NFHS-2 received at least one antenatal

  5. k

    Worldbank - Gender Statistics

    • datasource.kapsarc.org
    Updated Jul 11, 2025
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    (2025). Worldbank - Gender Statistics [Dataset]. https://datasource.kapsarc.org/explore/dataset/worldbank-gender-statistics-gcc/
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    Dataset updated
    Jul 11, 2025
    Description

    Explore gender statistics data focusing on academic staff, employment, fertility rates, GDP, poverty, and more in the GCC region. Access comprehensive information on key indicators for Bahrain, China, India, Kuwait, Oman, Qatar, and Saudi Arabia.

    academic staff, Access to anti-retroviral drugs, Adjusted net enrollment rate, Administration and Law programmes, Age at first marriage, Age dependency ratio, Cause of death, Children out of school, Completeness of birth registration, consumer prices, Cost of business start-up procedures, Employers, Employment in agriculture, Employment in industry, Employment in services, employment or training, Engineering and Mathematics programmes, Female headed households, Female migrants, Fertility planning status: mistimed pregnancy, Fertility planning status: planned pregnancy, Fertility rate, Firms with female participation in ownership, Fisheries and Veterinary programmes, Forestry, GDP, GDP growth, GDP per capita, gender parity index, Gini index, GNI, GNI per capita, Government expenditure on education, Government expenditure per student, Gross graduation ratio, Households with water on the premises, Inflation, Informal employment, Labor force, Labor force with advanced education, Labor force with basic education, Labor force with intermediate education, Learning poverty, Length of paid maternity leave, Life expectancy at birth, Mandatory retirement age, Manufacturing and Construction programmes, Mathematics and Statistics programmes, Number of under-five deaths, Part time employment, Population, Poverty headcount ratio at national poverty lines, PPP, Primary completion rate, Retirement age with full benefits, Retirement age with partial benefits, Rural population, Sex ratio at birth, Unemployment, Unemployment with advanced education, Urban population

    Bahrain, China, India, Kuwait, Oman, Qatar, Saudi Arabia

    Follow data.kapsarc.org for timely data to advance energy economics research.

  6. m

    Data for “Missing Women in India: Gender-Specific Effects of Early-Life...

    • data.mendeley.com
    Updated Apr 6, 2021
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    Jagadeesh Sivadasan (2021). Data for “Missing Women in India: Gender-Specific Effects of Early-Life Rainfall Shocks” [Dataset]. http://doi.org/10.17632/8m4y7cdnv3.1
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    Dataset updated
    Apr 6, 2021
    Authors
    Jagadeesh Sivadasan
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Area covered
    India
    Description

    This folder includes datasets and do-files for our paper "Missing Women in India: Gender-Specific Effects of Early-Life Rainfall Shocks". It contains rainfall data for each Indian district from 1911 to 2011, and has population by single age for each district in Census years (1991, 2001, and 2011).

  7. India Sex Ratio at Birth: Female per 1000 Male: Uttar Pradesh

    • ceicdata.com
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    CEICdata.com, India Sex Ratio at Birth: Female per 1000 Male: Uttar Pradesh [Dataset]. https://www.ceicdata.com/en/india/memo-items-sex-ratio-at-birth/sex-ratio-at-birth-female-per-1000-male-uttar-pradesh
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    Dataset provided by
    CEIC Data
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Time period covered
    Dec 1, 2009 - Dec 1, 2020
    Area covered
    India
    Variables measured
    Vital Statistics
    Description

    Sex Ratio at Birth: Female per 1000 Male: Uttar Pradesh data was reported at 905.000 NA in 2020. This records an increase from the previous number of 894.000 NA for 2019. Sex Ratio at Birth: Female per 1000 Male: Uttar Pradesh data is updated yearly, averaging 878.000 NA from Dec 2006 (Median) to 2020, with 15 observations. The data reached an all-time high of 905.000 NA in 2020 and a record low of 869.000 NA in 2014. Sex Ratio at Birth: Female per 1000 Male: Uttar Pradesh 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.GAJ001: Memo Items: Sex Ratio at Birth.

  8. I

    India Population: Census: Female: Age: 20 to 24 Year

    • ceicdata.com
    Updated Mar 15, 2023
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    CEICdata.com (2023). India Population: Census: Female: Age: 20 to 24 Year [Dataset]. https://www.ceicdata.com/en/india/census-population-by-age-group/population-census-female-age-20-to-24-year
    Explore at:
    Dataset updated
    Mar 15, 2023
    Dataset provided by
    CEICdata.com
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Time period covered
    Mar 1, 1991 - Mar 1, 2011
    Area covered
    India
    Variables measured
    Population
    Description

    India Population: Census: Female: Age: 20 to 24 Year data was reported at 53,839.529 Person th in 2011. This records an increase from the previous number of 43,443.000 Person th for 2001. India Population: Census: Female: Age: 20 to 24 Year data is updated yearly, averaging 43,443.000 Person th from Mar 1991 (Median) to 2011, with 3 observations. The data reached an all-time high of 53,839.529 Person th in 2011 and a record low of 36,959.000 Person th in 1991. India Population: Census: Female: 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.

  9. Indian population (States)

    • kaggle.com
    Updated Nov 27, 2020
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    Suresh Raj256 (2020). Indian population (States) [Dataset]. https://www.kaggle.com/sureshraj256/india-state-population/code
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    CroissantCroissant is a format for machine-learning datasets. Learn more about this at mlcommons.org/croissant.
    Dataset updated
    Nov 27, 2020
    Dataset provided by
    Kagglehttp://kaggle.com/
    Authors
    Suresh Raj256
    License

    https://creativecommons.org/publicdomain/zero/1.0/https://creativecommons.org/publicdomain/zero/1.0/

    Area covered
    India
    Description

    Dataset include statics of Indian population of male and female state wise.

    what are the other fundamentals indicators would be looked at or added to this data set in the future version ?

    Let me know it in comments section.

  10. d

    National Family Health Survey (NFHS): State- and Region-wise Statistical...

    • dataful.in
    Updated May 22, 2025
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    Dataful (Factly) (2025). National Family Health Survey (NFHS): State- and Region-wise Statistical Indicators Data on Family Profile and Health Status in India [Dataset]. https://dataful.in/datasets/18683
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    xlsx, csv, application/x-parquetAvailable download formats
    Dataset updated
    May 22, 2025
    Dataset authored and provided by
    Dataful (Factly)
    License

    https://dataful.in/terms-and-conditionshttps://dataful.in/terms-and-conditions

    Area covered
    India
    Variables measured
    National Nutrition and Health Status of India
    Description

    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

  11. w

    National Family Survey 2019-2021 - India

    • microdata.worldbank.org
    • catalog.ihsn.org
    • +1more
    Updated May 12, 2022
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    International Institute for Population Sciences (IIPS) (2022). National Family Survey 2019-2021 - India [Dataset]. https://microdata.worldbank.org/index.php/catalog/4482
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    Dataset updated
    May 12, 2022
    Dataset provided by
    Ministry of Health and Family Welfare (MoHFW)
    International Institute for Population Sciences (IIPS)
    Time period covered
    2019 - 2021
    Area covered
    India
    Description

    Abstract

    The National Family Health Survey 2019-21 (NFHS-5), the fifth in the NFHS series, provides information on population, health, and nutrition for India, each state/union territory (UT), and for 707 districts.

    The primary objective of the 2019-21 round of National Family Health Surveys is to provide essential data on health and family welfare, as well as data on emerging issues in these areas, such as levels of fertility, infant and child mortality, maternal and child health, and other health and family welfare indicators by background characteristics at the national and state levels. Similar to NFHS-4, NFHS-5 also provides information on several emerging issues including perinatal mortality, high-risk sexual behaviour, safe injections, tuberculosis, noncommunicable diseases, and the use of emergency contraception.

    The information collected through NFHS-5 is intended to assist policymakers and programme managers in setting benchmarks and examining progress over time in India’s health sector. Besides providing evidence on the effectiveness of ongoing programmes, NFHS-5 data will help to identify the need for new programmes in specific health areas.

    The clinical, anthropometric, and biochemical (CAB) component of NFHS-5 is designed to provide vital estimates of the prevalence of malnutrition, anaemia, hypertension, high blood glucose levels, and waist and hip circumference, Vitamin D3, HbA1c, and malaria parasites through a series of biomarker tests and measurements.

    Geographic coverage

    National coverage

    Analysis unit

    • Household
    • Individual
    • Children age 0-5
    • Woman age 15-49
    • Man age 15 to 54

    Universe

    The survey covered all de jure household members (usual residents), all women aged 15-49, all men age 15-54, and all children aged 0-5 resident in the household.

    Kind of data

    Sample survey data [ssd]

    Sampling procedure

    A uniform sample design, which is representative at the national, state/union territory, and district level, was adopted in each round of the survey. Each district is stratified into urban and rural areas. Each rural stratum is sub-stratified into smaller substrata which are created considering the village population and the percentage of the population belonging to scheduled castes and scheduled tribes (SC/ST). Within each explicit rural sampling stratum, a sample of villages was selected as Primary Sampling Units (PSUs); before the PSU selection, PSUs were sorted according to the literacy rate of women age 6+ years. Within each urban sampling stratum, a sample of Census Enumeration Blocks (CEBs) was selected as PSUs. Before the PSU selection, PSUs were sorted according to the percentage of SC/ST population. In the second stage of selection, a fixed number of 22 households per cluster was selected with an equal probability systematic selection from a newly created list of households in the selected PSUs. The list of households was created as a result of the mapping and household listing operation conducted in each selected PSU before the household selection in the second stage. In all, 30,456 Primary Sampling Units (PSUs) were selected across the country in NFHS-5 drawn from 707 districts as on March 31st 2017, of which fieldwork was completed in 30,198 PSUs.

    For further details on sample design, see Section 1.2 of the final report.

    Mode of data collection

    Computer Assisted Personal Interview [capi]

    Research instrument

    Four survey schedules/questionnaires: Household, Woman, Man, and Biomarker were canvassed in 18 local languages using Computer Assisted Personal Interviewing (CAPI).

    Cleaning operations

    Electronic data collected in the 2019-21 National Family Health Survey were received on a daily basis via the SyncCloud system at the International Institute for Population Sciences, where the data were stored on a password-protected computer. Secondary editing of the data, which required resolution of computer-identified inconsistencies and coding of open-ended questions, was conducted in the field by the Field Agencies and at the Field Agencies central office, and IIPS checked the secondary edits before the dataset was finalized.

    Field-check tables were produced by IIPS and the Field Agencies on a regular basis to identify certain types of errors that might have occurred in eliciting information and recording question responses. Information from the field-check tables on the performance of each fieldwork team and individual investigator was promptly shared with the Field Agencies during the fieldwork so that the performance of the teams could be improved, if required.

    Response rate

    A total of 664,972 households were selected for the sample, of which 653,144 were occupied. Among the occupied households, 636,699 were successfully interviewed, for a response rate of 98 percent.

    In the interviewed households, 747,176 eligible women age 15-49 were identified for individual women’s interviews. Interviews were completed with 724,115 women, for a response rate of 97 percent. In all, there were 111,179 eligible men age 15-54 in households selected for the state module. Interviews were completed with 101,839 men, for a response rate of 92 percent.

  12. Powerful Women in India

    • redivis.com
    application/jsonl +7
    Updated Oct 6, 2021
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    Data for Development Initiative (2021). Powerful Women in India [Dataset]. https://redivis.com/datasets/q707-5rwxymgw0
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    arrow, sas, application/jsonl, spss, avro, stata, parquet, csvAvailable download formats
    Dataset updated
    Oct 6, 2021
    Dataset provided by
    Redivis Inc.
    Authors
    Data for Development Initiative
    Area covered
    India
    Description

    Section 7

    Survey instruments:

    Section 9

    Survey instruments:

    Section 8

    Survey instrument:

    Section 14

    Survey instrument:

    Section 15

    Survey instrument:

    Section 16

    Survey instrument:

    Section 4

    Survey instruments:

    Section 6

    Survey instrument:

    Section 3

    Survey instruments:

    Section 2

    Description and codebook for subset of harmonized variables:

    Section 13

    Survey instrument:

    Documentation

    Full Project Name: Impact of Female Leadership on Aspirations and Educational Attainment for Teenage Girls in India

    Unique ID: 498

    PIs: Lori Beaman, Esther Duflo, Rohini Pande, Petia Topalova

    Location: Birbhum District, West Bengal, India

    Sample: 495 villages

    Timeline: 2006 to 2007

    Target Group: Parents Men and boys Rural population Women and girls Youth

    Outcome of Interest: Discrimination Enrollment and attendance Women’s/girls’ decision-making Self-esteem/self-efficacy Aspirations Gender attitudes and norms

    Associated publications: http://science.sciencemag.org/content/335/6068/582

    More information: https://www.povertyactionlab.org/evaluation/impact-female-leadership-aspirations-and-educational-attainment-teenage-girls-india

    Dataverse: Lori Beaman; Raghabendra Chattopadhyay; Esther Duflo; Rohini Pande; Petia Topalova, 2012, “Powerful women and aspirations in India”, https://doi.org/10.7910/DVN/O3UKFO, Harvard Dataverse, V3.

    Section 5

    Survey instrument:

    Section 10

    Survey instrument:

    Section 17

    This dataset was created on 2021-10-06 20:34:42.626 by merging multiple datasets together. The source datasets for this version were:

    Powerful Women in India Adult Survey: Adult survey data, excluding section F5 on education; Only one round of data collection

    Powerful Women in India Adult Education: Adult survey data from section F5 on education; Only one round of data collection

    Powerful Women in India:

    Powerful Women in India Facilities Anganwadi: Data collected from facilities survey on school facility quality only from the Anganwadi section

    Powerful Women in India Facilities Math Test: Data collected from facilities survey on school facility quality only from the Math Test section

    Powerful Women in India Facilities School Details: Data collected from facilities survey on school facility quality only from the School Details section

    Powerful Women in India Household Roster: Data collected from household survey section A1 - household roster

    Section 11

    Survey instrument:

    Section 12

    This dataset was created on 2021-10-06 18:52:27.489 by merging multiple datasets together. The source datasets for this version were:

    Powerful Women in India Facilities Survey: Data collected from facilities survey on school facility quality, excluding the following sections: -Anganwadi -Math test -Reading test -School Details

    Powerful Women in India Facilities Reading Test: Data collected from facilities survey on school facility quality only from the Reading Test section

    Powerful Women in India Household Survey: Data collected from household survey, excluding section A1

    Powerful Women in India Participatory Resource Appraisal: Data from the assessment of village resources through a participatory resource appraisal exercise

    Powerful Women in India Pradhan Survey: Data from current and previous Pradhans and their spouses about economic condition and political activities

    Powerful Women in India Pradhan Seats Reserved for Women: Data at community/village level regarding current and previous Pradhan seats

    Powerful Women in India Teenager Survey: Data from teenagers interviewed (children aged 11-16 years)

  13. k

    Development Indicators

    • datasource.kapsarc.org
    Updated Apr 26, 2025
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    (2025). Development Indicators [Dataset]. https://datasource.kapsarc.org/explore/dataset/saudi-arabia-world-development-indicators-1960-2014/
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    Dataset updated
    Apr 26, 2025
    License

    Open Database License (ODbL) v1.0https://www.opendatacommons.org/licenses/odbl/1.0/
    License information was derived automatically

    Description

    Explore the Saudi Arabia World Development Indicators dataset , including key indicators such as Access to clean fuels, Adjusted net enrollment rate, CO2 emissions, and more. Find valuable insights and trends for Saudi Arabia, Bahrain, Kuwait, Oman, Qatar, China, and India.

    Indicator, Access to clean fuels and technologies for cooking, rural (% of rural population), Access to electricity (% of population), Adjusted net enrollment rate, primary, female (% of primary school age children), Adjusted net national income (annual % growth), Adjusted savings: education expenditure (% of GNI), Adjusted savings: mineral depletion (current US$), Adjusted savings: natural resources depletion (% of GNI), Adjusted savings: net national savings (current US$), Adolescents out of school (% of lower secondary school age), Adolescents out of school, female (% of female lower secondary school age), Age dependency ratio (% of working-age population), Agricultural methane emissions (% of total), Agriculture, forestry, and fishing, value added (current US$), Agriculture, forestry, and fishing, value added per worker (constant 2015 US$), Alternative and nuclear energy (% of total energy use), Annualized average growth rate in per capita real survey mean consumption or income, total population (%), Arms exports (SIPRI trend indicator values), Arms imports (SIPRI trend indicator values), Average working hours of children, working only, ages 7-14 (hours per week), Average working hours of children, working only, male, ages 7-14 (hours per week), Cause of death, by injury (% of total), Cereal yield (kg per hectare), Changes in inventories (current US$), Chemicals (% of value added in manufacturing), Child employment in agriculture (% of economically active children ages 7-14), Child employment in manufacturing, female (% of female economically active children ages 7-14), Child employment in manufacturing, male (% of male economically active children ages 7-14), Child employment in services (% of economically active children ages 7-14), Child employment in services, female (% of female economically active children ages 7-14), Children (ages 0-14) newly infected with HIV, Children in employment, study and work (% of children in employment, ages 7-14), Children in employment, unpaid family workers (% of children in employment, ages 7-14), Children in employment, wage workers (% of children in employment, ages 7-14), Children out of school, primary, Children out of school, primary, male, Claims on other sectors of the domestic economy (annual growth as % of broad money), CO2 emissions (kg per 2015 US$ of GDP), CO2 emissions (kt), CO2 emissions from other sectors, excluding residential buildings and commercial and public services (% of total fuel combustion), CO2 emissions from transport (% of total fuel combustion), Communications, computer, etc. (% of service exports, BoP), Condom use, population ages 15-24, female (% of females ages 15-24), Container port traffic (TEU: 20 foot equivalent units), Contraceptive prevalence, any method (% of married women ages 15-49), Control of Corruption: Estimate, Control of Corruption: Percentile Rank, Upper Bound of 90% Confidence Interval, Control of Corruption: Standard Error, Coverage of social insurance programs in 4th quintile (% of population), CPIA building human resources rating (1=low to 6=high), CPIA debt policy rating (1=low to 6=high), CPIA policies for social inclusion/equity cluster average (1=low to 6=high), CPIA public sector management and institutions cluster average (1=low to 6=high), CPIA quality of budgetary and financial management rating (1=low to 6=high), CPIA transparency, accountability, and corruption in the public sector rating (1=low to 6=high), Current education expenditure, secondary (% of total expenditure in secondary public institutions), DEC alternative conversion factor (LCU per US$), Deposit interest rate (%), Depth of credit information index (0=low to 8=high), Diarrhea treatment (% of children under 5 who received ORS packet), Discrepancy in expenditure estimate of GDP (current LCU), Domestic private health expenditure per capita, PPP (current international $), Droughts, floods, extreme temperatures (% of population, average 1990-2009), Educational attainment, at least Bachelor's or equivalent, population 25+, female (%) (cumulative), Educational attainment, at least Bachelor's or equivalent, population 25+, male (%) (cumulative), Educational attainment, at least completed lower secondary, population 25+, female (%) (cumulative), Educational attainment, at least completed primary, population 25+ years, total (%) (cumulative), Educational attainment, at least Master's or equivalent, population 25+, male (%) (cumulative), Educational attainment, at least Master's or equivalent, population 25+, total (%) (cumulative), Electricity production from coal sources (% of total), Electricity production from nuclear sources (% of total), Employers, total (% of total employment) (modeled ILO estimate), Employment in industry (% of total employment) (modeled ILO estimate), Employment in services, female (% of female employment) (modeled ILO estimate), Employment to population ratio, 15+, male (%) (modeled ILO estimate), Employment to population ratio, ages 15-24, total (%) (national estimate), Energy use (kg of oil equivalent per capita), Export unit value index (2015 = 100), Exports of goods and services (% of GDP), Exports of goods, services and primary income (BoP, current US$), External debt stocks (% of GNI), External health expenditure (% of current health expenditure), Female primary school age children out-of-school (%), Female share of employment in senior and middle management (%), Final consumption expenditure (constant 2015 US$), Firms expected to give gifts in meetings with tax officials (% of firms), Firms experiencing losses due to theft and vandalism (% of firms), Firms formally registered when operations started (% of firms), Fixed broadband subscriptions, Fixed telephone subscriptions (per 100 people), Foreign direct investment, net outflows (% of GDP), Forest area (% of land area), Forest area (sq. km), Forest rents (% of GDP), GDP growth (annual %), GDP per capita (constant LCU), GDP per unit of energy use (PPP $ per kg of oil equivalent), GDP, PPP (constant 2017 international $), General government final consumption expenditure (current LCU), GHG net emissions/removals by LUCF (Mt of CO2 equivalent), GNI growth (annual %), GNI per capita (constant LCU), GNI, PPP (current international $), Goods and services expense (current LCU), Government Effectiveness: Percentile Rank, Government Effectiveness: Percentile Rank, Lower Bound of 90% Confidence Interval, Government Effectiveness: Standard Error, Gross capital formation (annual % growth), Gross capital formation (constant 2015 US$), Gross capital formation (current LCU), Gross fixed capital formation, private sector (% of GDP), Gross intake ratio in first grade of primary education, male (% of relevant age group), Gross intake ratio in first grade of primary education, total (% of relevant age group), Gross national expenditure (current LCU), Gross national expenditure (current US$), Households and NPISHs Final consumption expenditure (constant LCU), Households and NPISHs Final consumption expenditure (current US$), Households and NPISHs Final consumption expenditure, PPP (constant 2017 international $), Households and NPISHs final consumption expenditure: linked series (current LCU), Human capital index (HCI) (scale 0-1), Human capital index (HCI), male (scale 0-1), Immunization, DPT (% of children ages 12-23 months), Import value index (2015 = 100), Imports of goods and services (% of GDP), Incidence of HIV, ages 15-24 (per 1,000 uninfected population ages 15-24), Incidence of HIV, all (per 1,000 uninfected population), Income share held by highest 20%, Income share held by lowest 20%, Income share held by third 20%, Individuals using the Internet (% of population), Industry (including construction), value added (constant LCU), Informal payments to public officials (% of firms), Intentional homicides, male (per 100,000 male), Interest payments (% of expense), Interest rate spread (lending rate minus deposit rate, %), Internally displaced persons, new displacement associated with conflict and violence (number of cases), International tourism, expenditures for passenger transport items (current US$), International tourism, expenditures for travel items (current US$), Investment in energy with private participation (current US$), Labor force participation rate for ages 15-24, female (%) (modeled ILO estimate), Development

    Saudi Arabia, Bahrain, Kuwait, Oman, Qatar, China, India Follow data.kapsarc.org for timely data to advance energy economics research..

  14. Literacy rate in India 1981-2023, by gender

    • statista.com
    Updated Jul 10, 2025
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    Statista (2025). Literacy rate in India 1981-2023, by gender [Dataset]. https://www.statista.com/statistics/271335/literacy-rate-in-india/
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    Dataset updated
    Jul 10, 2025
    Dataset authored and provided by
    Statistahttp://statista.com/
    Area covered
    India
    Description

    Literacy in India has been increasing as more and more people receive a better education, but it is still far from all-encompassing. In 2023, the degree of literacy in India was about 77 percent, with the majority of literate Indians being men. It is estimated that the global literacy rate for people aged 15 and above is about 86 percent. How to read a literacy rateIn order to identify potential for intellectual and educational progress, the literacy rate of a country covers the level of education and skills acquired by a country’s inhabitants. Literacy is an important indicator of a country’s economic progress and the standard of living – it shows how many people have access to education. However, the standards to measure literacy cannot be universally applied. Measures to identify and define illiterate and literate inhabitants vary from country to country: In some, illiteracy is equated with no schooling at all, for example. Writings on the wallGlobally speaking, more men are able to read and write than women, and this disparity is also reflected in the literacy rate in India – with scarcity of schools and education in rural areas being one factor, and poverty another. Especially in rural areas, women and girls are often not given proper access to formal education, and even if they are, many drop out. Today, India is already being surpassed in this area by other emerging economies, like Brazil, China, and even by most other countries in the Asia-Pacific region. To catch up, India now has to offer more educational programs to its rural population, not only on how to read and write, but also on traditional gender roles and rights.

  15. d

    India - National Family Health Survey 2005-2006 - Dataset - waterdata

    • waterdata3.staging.derilinx.com
    Updated Mar 16, 2020
    + more versions
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    (2020). India - National Family Health Survey 2005-2006 - Dataset - waterdata [Dataset]. https://waterdata3.staging.derilinx.com/dataset/india-national-family-health-survey-2005-2006
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    Dataset updated
    Mar 16, 2020
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Area covered
    India
    Description

    The National Family Health Surveys (NFHS) programme, initiated in the early 1990s, has emerged as a nationally important source of data on population, health, and nutrition for India and its states. The 2005-06 National Family Health Survey (NFHS-3), the third in the series of these national surveys, was preceded by NFHS-1 in 1992-93 and NFHS-2 in 1998-99. Like NFHS-1 and NFHS-2, NFHS-3 was designed to provide estimates of important indicators on family welfare, maternal and child health, and nutrition. In addition, NFHS-3 provides information on several new and emerging issues, including family life education, safe injections, perinatal mortality, adolescent reproductive health, high-risk sexual behaviour, tuberculosis, and malaria. Further, unlike the earlier surveys in which only ever-married women age 15-49 were eligible for individual interviews, NFHS-3 interviewed all women age 15-49 and all men age 15-54. Information on nutritional status, including the prevalence of anaemia, is provided in NFHS3 for women age 15-49, men age 15-54, and young children. A special feature of NFHS-3 is the inclusion of testing of the adult population for HIV. NFHS-3 is the first nationwide community-based survey in India to provide an estimate of HIV prevalence in the general population. Specifically, NFHS-3 provides estimates of HIV prevalence among women age 15-49 and men age 15-54 for all of India, and separately for Uttar Pradesh and for Andhra Pradesh, Karnataka, Maharashtra, Manipur, and Tamil Nadu, five out of the six states classified by the National AIDS Control Organization (NACO) as high HIV prevalence states. No estimate of HIV prevalence is being provided for Nagaland, the sixth high HIV prevalence state, due to strong local opposition to the collection of blood samples. NFHS-3 covered all 29 states in India, which comprise more than 99 percent of India's population. NFHS-3 is designed to provide estimates of key indicators for India as a whole and, with the exception of HIV prevalence, for all 29 states by urban-rural residence. Additionally, NFHS-3 provides estimates for the slum and non-slum populations of eight cities, namely Chennai, Delhi, Hyderabad, Indore, Kolkata, Meerut, Mumbai, and Nagpur. NFHS-3 was conducted under the stewardship of the Ministry of Health and Family Welfare (MOHFW), Government of India, and is the result of the collaborative efforts of a large number of organizations. The International Institute for Population Sciences (IIPS), Mumbai, was designated by MOHFW as the nodal agency for the project. Funding for NFHS-3 was provided by the United States Agency for International Development (USAID), DFID, the Bill and Melinda Gates Foundation, UNICEF, UNFPA, and MOHFW. Macro International, USA, provided technical assistance at all stages of the NFHS-3 project. NACO and the National AIDS Research Institute (NARI) provided technical assistance for the HIV component of NFHS-3. Eighteen Research Organizations, including six Population Research Centres, shouldered the responsibility of conducting the survey in the different states of India and producing electronic data files. The survey used a uniform sample design, questionnaires (translated into 18 Indian languages), field procedures, and procedures for biomarker measurements throughout the country to facilitate comparability across the states and to ensure the highest possible data quality. The contents of the questionnaires were decided through an extensive collaborative process in early 2005. Based on provisional data, two national-level fact sheets and 29 state fact sheets that provide estimates of more than 50 key indicators of population, health, family welfare, and nutrition have already been released. The basic objective of releasing fact sheets within a very short period after the completion of data collection was to provide immediate feedback to planners and programme managers on key process indicators.

  16. d

    State, Year and Gender-wise Literacy in India from Census

    • dataful.in
    Updated Jun 13, 2025
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    Dataful (Factly) (2025). State, Year and Gender-wise Literacy in India from Census [Dataset]. https://dataful.in/datasets/560
    Explore at:
    xlsx, application/x-parquet, csvAvailable download formats
    Dataset updated
    Jun 13, 2025
    Dataset authored and provided by
    Dataful (Factly)
    License

    https://dataful.in/terms-and-conditionshttps://dataful.in/terms-and-conditions

    Area covered
    India
    Variables measured
    Literacy Rate
    Description

    The data shows the year-wise and state or union territory-wise literacy and rural and urban literacy, for male, female, and total literacy, in India according to Census.

    Note: 1. Literacy rate is defined as the population of literates in the population aged 7 year and above. 2. The 1991 data (Excluding Jammu & Kashmir)and 2001 data (Excludes figures of Paomata, Mao Maran and Pura sub-divisions of Senapati district of Manipur for 2001) refer to Census of India.

  17. g

    Ministry of Home Affairs, Department of Home, Registrar General and Census...

    • gimi9.com
    Updated May 9, 2025
    + more versions
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    (2025). Ministry of Home Affairs, Department of Home, Registrar General and Census Commissioner, India - Ever married and currently married population by age at marriage and duration of marriage - India and States [Dataset]. https://gimi9.com/dataset/in_ever-married-and-currently-married-population-age-marriage-and-duration-marriage-india-and/
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    Dataset updated
    May 9, 2025
    License

    CC0 1.0 Universal Public Domain Dedicationhttps://creativecommons.org/publicdomain/zero/1.0/
    License information was derived automatically

    Area covered
    India
    Description

    Ever married women or men are persons who have been married at least once in their lives although their current marital status may not be married. Currently married women or men are persons who have been married and are not either divorced, widowed or separated. Persons living in consensual unions or in visiting partnerships are also included in the currently married category. It include details on ever married and currently married population by age at marriage, duration of marriage and religious community.

  18. f

    Gender-wise distribution of the sample by select background characteristics....

    • plos.figshare.com
    xls
    Updated Jun 3, 2023
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    Shreya Banerjee; Pallabi Gogoi (2023). Gender-wise distribution of the sample by select background characteristics. [Dataset]. http://doi.org/10.1371/journal.pone.0280887.t001
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    xlsAvailable download formats
    Dataset updated
    Jun 3, 2023
    Dataset provided by
    PLOS ONE
    Authors
    Shreya Banerjee; Pallabi Gogoi
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Description

    Gender-wise distribution of the sample by select background characteristics.

  19. Instagram: distribution of global audiences 2024, by gender

    • statista.com
    • davegsmith.com
    Updated Jun 17, 2025
    + more versions
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    Stacy Jo Dixon (2025). Instagram: distribution of global audiences 2024, by gender [Dataset]. https://www.statista.com/topics/1164/social-networks/
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    Dataset updated
    Jun 17, 2025
    Dataset provided by
    Statistahttp://statista.com/
    Authors
    Stacy Jo Dixon
    Description

    As of January 2024, Instagram was slightly more popular with men than women, with men accounting for 50.6 percent of the platform’s global users. Additionally, the social media app was most popular amongst younger audiences, with almost 32 percent of users aged between 18 and 24 years.

                  Instagram’s Global Audience
    
                  As of January 2024, Instagram was the fourth most popular social media platform globally, reaching two billion monthly active users (MAU). This number is projected to keep growing with no signs of slowing down, which is not a surprise as the global online social penetration rate across all regions is constantly increasing.
                  As of January 2024, the country with the largest Instagram audience was India with 362.9 million users, followed by the United States with 169.7 million users.
    
                  Who is winning over the generations?
    
                  Even though Instagram’s audience is almost twice the size of TikTok’s on a global scale, TikTok has shown itself to be a fierce competitor, particularly amongst younger audiences. TikTok was the most downloaded mobile app globally in 2022, generating 672 million downloads. As of 2022, Generation Z in the United States spent more time on TikTok than on Instagram monthly.
    
  20. Not seeing a result you expected?
    Learn how you can add new datasets to our index.

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Neilsberg Research (2025). Indian Village, IN Population Breakdown by Gender Dataset: Male and Female Population Distribution // 2025 Edition [Dataset]. https://www.neilsberg.com/research/datasets/b23a9bd0-f25d-11ef-8c1b-3860777c1fe6/

Indian Village, IN Population Breakdown by Gender Dataset: Male and Female Population Distribution // 2025 Edition

Explore at:
json, csvAvailable download formats
Dataset updated
Feb 24, 2025
Dataset authored and provided by
Neilsberg Research
License

Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically

Area covered
IN, Indian Village
Variables measured
Male Population, Female Population, Male Population as Percent of Total Population, Female Population as Percent of Total Population
Measurement technique
The data presented in this dataset is derived from the latest U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates. To measure the two variables, namely (a) population and (b) population as a percentage of the total population, we initially analyzed and categorized the data for each of the gender classifications (biological sex) reported by the US Census Bureau. For further information regarding these estimates, please feel free to reach out to us via email at research@neilsberg.com.
Dataset funded by
Neilsberg Research
Description
About this dataset

Context

The dataset tabulates the population of Indian Village by gender, including both male and female populations. This dataset can be utilized to understand the population distribution of Indian Village across both sexes and to determine which sex constitutes the majority.

Key observations

There is a majority of female population, with 56.64% of total population being female. 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.

Scope of gender :

Please note that American Community Survey asks a question about the respondents current sex, but not about gender, sexual orientation, or sex at birth. The question is intended to capture data for biological sex, not gender. Respondents are supposed to respond with the answer as either of Male or Female. Our research and this dataset mirrors the data reported as Male and Female for gender distribution analysis. No further analysis is done on the data reported from the Census Bureau.

Variables / Data Columns

  • Gender: This column displays the Gender (Male / Female)
  • Population: The population of the gender in the Indian Village is shown in this column.
  • % of Total Population: This column displays the percentage distribution of each gender as a proportion of Indian Village 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 Village Population by Race & Ethnicity. You can refer the same here

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