This dataset provides a comprehensive overview of the demographic trends and population statistics of India. It includes various aspects of the population, such as total population figures, gender distribution, religious composition, linguistic diversity, and age group breakdowns. The dataset aims to facilitate research and analysis in the fields of sociology, economics, and public policy by offering valuable insights into the demographic dynamics of India.

Key Features: - Census Data: Detailed population statistics based on census years, including total population, male and female counts, and differences between genders. - Religious Demographics: Information on the population distribution among different religions, along with percentages. - Language Distribution: Data on the number of speakers for various languages in India and their corresponding percentages. - Vital Statistics: Key indicators such as live births, deaths, natural changes, crude birth rates, and total fertility rates. - Age Distribution: Breakdown of the population by age group, including gender-specific counts and percentages.

Purpose: This dataset serves as a valuable resource for researchers, policymakers, and educators interested in understanding the demographic landscape of India. It can be used for various analyses, including population growth trends, gender ratios, and the impact of cultural diversity on the social fabric of the nation.

In 2023, the annual population growth in India was 0.88 percent. Between 1961 and 2023, the figure dropped by 1.52 percentage points, though the decline followed an uneven course rather than a steady trajectory.

The National Medical Expenditure Survey (NMES) series provides information on health expenditures by or on behalf of families and individuals, the financing of these expenditures, and each person's use of services. The Survey of American Indians and Alaska Natives (SAIAN) was designed in collaboration with the Indian Health Service (IHS), and used the same data collection instruments, interview procedures, and time frame as the NMES Household Survey component. However, the SAIAN differed from the Household Survey in several respects. The SAIAN sample was interviewed only three times and was not given the supplements on long-term care, caregiving, and care-receiving. Also, SAIAN respondents were asked additional questions on topics such as use of IHS facilities and traditional medicine, and were given a modified self-administered questionnaire with separate versions for adults and children. Interviewers for the SAIAN were mainly American Indians or Alaska Natives, and about 20 percent of the interviews were not conducted entirely in English. Of these, approximately 40 percent were conducted entirely in the native language of the respondent. Public Use Tape 20P contains detailed information on eligibility status, interview dates, demographic characteristics (age, marital status, military service, education, income), employment and insurance, link variables, and other survey administration variables for all persons in the sample. The Round 1 person characteristics previously released in NATIONAL MEDICAL EXPENDITURE SURVEY, 1987: SURVEY OF AMERICAN INDIANS AND ALASKA NATIVES, ROUND 1 PERSON-LEVEL FILE PUBLIC USE TAPE 11 are being replaced by the data contained in this collection.

Dataset Description:

This dataset contains two distinct tables that offer valuable insights into the population trends and characteristics of Indian districts. Dataset 1 includes demographic data, such as population growth rate, sex ratio, and literacy rate, while Dataset 2 provides information about the geographical aspects, including district area and population count. Together, these datasets empower researchers and data enthusiasts to explore and analyze India's demographic and geographical dynamics, contributing to a deeper understanding of the nation's diverse regions and populations.

Dataset 1: Demographic Insights - District: The name of the district within India. - State: The state to which the district belongs. - Growth: The population growth rate of the district. - Sex_Ratio: The ratio of males to females in the population. - Literacy: The literacy rate of the district's population.

Dataset 2: Geographical Information - District: The name of the district within India. - State: The state to which the district belongs. - Area_km2: The geographical area of the district in square kilometers. - Population: The population count of the district.

These datasets provide a comprehensive view of both the demographic and geographical aspects of Indian districts, enabling in-depth analysis of population trends and regional characteristics.

Context

• This dataset is a beginner level basic problem containing Indian population data to predict India's Population. This dataset introduces to basic linear regression algorithm and basic feature engineering.

Content

Attribute information:

      1. Year
      2. "Yearly % Change"
      3. "Yearly Change"
      4. Migrants (net)
      5. Median Age
      6. Fertility Rate
      7. Density (P/Km²)
      8. "Urban Pop %"
      9. Urban Population
      10. "Country's Share of World Pop"
      11. World Population
      12. "India Global Rank"
      13. Population

      Dependent variable = Population

Source- Worldometer

The statistic shows the total population of India from 2020 to 2030. In 2024, the estimated total population in India amounted to approximately 1.44 billion people. Total population in India India currently has the second-largest population in the world and is projected to overtake top-ranking China within forty years. Its residents comprise more than one-seventh of the entire world’s population, and despite a slowly decreasing fertility rate (which still exceeds the replacement rate and keeps the median age of the population relatively low), an increasing life expectancy adds to an expanding population. In comparison with other countries whose populations are decreasing, such as Japan, India has a relatively small share of aged population, which indicates the probability of lower death rates and higher retention of the existing population. With a land mass of less than half that of the United States and a population almost four times greater, India has recognized potential problems of its growing population. Government attempts to implement family planning programs have achieved varying degrees of success. Initiatives such as sterilization programs in the 1970s have been blamed for creating general antipathy to family planning, but the combined efforts of various family planning and contraception programs have helped halve fertility rates since the 1960s. The population growth rate has correspondingly shrunk as well, but has not yet reached less than one percent growth per year. As home to thousands of ethnic groups, hundreds of languages, and numerous religions, a cohesive and broadly-supported effort to reduce population growth is difficult to create. Despite that, India is one country to watch in coming years. It is also a growing economic power; among other measures, its GDP per capita was expected to triple between 2003 and 2013 and was listed as the third-ranked country for its share of the global gross domestic product.

The total population in India was estimated at 1398.6 million people in 2024, according to the latest census figures and projections from Trading Economics. This dataset provides - India Population - actual values, historical data, forecast, chart, statistics, economic calendar and news.

This table is part of a series of tables that present a portrait of Canada based on the various census topics. The tables range in complexity and levels of geography. Content varies from a simple overview of the country to complex cross-tabulations; the tables may also cover several censuses.

This table is part of a series of tables that present a portrait of Canada based on the various census topics. The tables range in complexity and levels of geography. Content varies from a simple overview of the country to complex cross-tabulations; the tables may also cover several censuses.

This dataset provides a comprehensive overview of India's population, economy, education, health, and other key indicators. The data covers the period from 2010 to 2021 and includes information on population demographics, GDP, inflation, employment, education attainment, healthcare spending, and more. Researchers and analysts can use this dataset to gain insights into India's economic and social development, as well as to compare it with other countries in the region and around the world. The dataset is sourced from various official and publicly available data sources, including the World Bank, the United Nations, and the Indian government. This dataset can be used to analyse the situation of india and can predict the future of india

The AIAN Summary File contains data on population characteristics, such as sex, age, average household size, household type, and relationship to householder. The American Indian and Alaska Native Summary File (AIANSF) contains data on population characteristics, such as sex, age, average household size, household type, and relationship to householder. The file also includes housing characteristics, such as tenure (whether a housing unit is owner-occupied or renter- occupied) and age of householder for occupied housing units. Selected aggregates and medians also are provided. A complete listing of subjects in the AIANSF is found in Chapter 3, Subject Locator. The layout of the tables in the AIANSF is similar to that in Summary File 2 (SF 2). These data are presented in 47 population tables (identified with a "PCT") and 14 housing tables (identified with an "HCT") shown down to the census tract level; and 10 population tables (identified with a "PCO") shown down to the county level, for a total of 71 tables. Each table is iterated for the total population, the total American Indian and Alaska Native population alone, the total American Indian and Alaska Native population alone or in combination, and 1,567 detailed tribes and tribal groupings. Tribes or tribal groupings are included on the iterations list if they met a threshold of at least 100 people in the 2010 Census. In addition, the presentation of AIANSF tables for any of the tribes and tribal groupings is subject to a population threshold of 100 or more people in a given geography. That is, if there are fewer than 100 people in a specific population group in a specific geographic area, their population and housing characteristics data are not available for that geographic area in the AIANSF. See Appendix H, Characteristic Iterations, for more information.

This layer shows total population counts by sex, age, and race groups data from the 2020 Census Demographic and Housing Characteristics. This is shown by Nation, Tribal Subdivision, Tribal Census Tract, Tribal Block Group, Alaska Native Regional Corporation, American Indian, Alaska Native, or Native Hawaiian Area boundaries. Each geography layer contains a common set of Census counts based on available attributes from the U.S. Census Bureau. There are also additional calculated attributes related to this topic, which can be mapped or used within analysis.   To see the full list of attributes available in this service, go to the "Data" tab above, and then choose "Fields" at the top right. Each attribute contains definitions, additional details, and the formula for calculated fields in the field description.Vintage of boundaries and attributes: 2020 Demographic and Housing Characteristics Table(s): P1, H1, H3, P2, P3, P5, P12, P13, P17, PCT12 (Not all lines of these DHC tables are available in this feature layer.)Data downloaded from: U.S. Census Bureau’s data.census.gov siteDate the Data was Downloaded: May 25, 2023Geography Levels included: Nation, Tribal Subdivision, Tribal Census Tract, Tribal Block Group, Alaska Native Regional Corporation, American Indian Alaska Native Native Hawaiian AreaNational Figures: included in Nation layer The United States Census Bureau Demographic and Housing Characteristics: 2020 Census Results 2020 Census Data Quality Geography & 2020 Census Technical Documentation Data Table Guide: includes the final list of tables, lowest level of geography by table and table shells for the Demographic Profile and Demographic and Housing Characteristics.News & Updates This layer is ready to be used in ArcGIS Pro, ArcGIS Online and its configurable apps, Story Maps, dashboards, Notebooks, Python, custom apps, and mobile apps. Data can also be exported for offline workflows. Please cite the U.S. Census Bureau when using this data. Data Processing Notes: These 2020 Census boundaries come from the US Census TIGER geodatabases. These are Census boundaries with water and/or coastlines erased for cartographic and mapping purposes. For Census tracts and block groups, the water cutouts are derived from a subset of the 2020 Areal Hydrography boundaries offered by TIGER. Water bodies and rivers which are 50 million square meters or larger (mid to large sized water bodies) are erased from the tract and block group boundaries, as well as additional important features. For state and county boundaries, the water and coastlines are derived from the coastlines of the 2020 500k TIGER Cartographic Boundary Shapefiles. These are erased to more accurately portray the coastlines and Great Lakes. The original AWATER and ALAND fields are unchanged and available as attributes within the data table (units are square meters).  The layer contains all US states, Washington D.C., and Puerto Rico. Census tracts with no population that occur in areas of water, such as oceans, are removed from this data service (Census Tracts beginning with 99). Block groups that fall within the same criteria (Block Group denoted as 0 with no area land) have also been removed.Percentages and derived counts, are calculated values (that can be identified by the "_calc_" stub in the field name). Field alias names were created based on the Table Shells file available from the Data Table Guide for the Demographic Profile and Demographic and Housing Characteristics. Not all lines of all tables listed above are included in this layer. Duplicative counts were dropped. For example, P0030001 was dropped, as it is duplicative of P0010001.To protect the privacy and confidentiality of respondents, their data has been protected using differential privacy techniques by the U.S. Census Bureau.

This table is part of a series of tables that present a portrait of Canada based on the various census topics. The tables range in complexity and levels of geography. Content varies from a simple overview of the country to complex cross-tabulations; the tables may also cover several censuses.

The changing population age structure has a significant influence on the economy, society, and numerous other aspects of a country. This paper has innovatively applied the method of compositional data forecasting for the prediction of population age changes of the young (aged 0–14), the middle-aged (aged 15–64), and the elderly (aged older than 65) in China, India, and Vietnam by 2030 based on data from 1960 to 2016. To select the best-suited forecasting model, an array of data transformation approaches and forecasting models have been extensively employed, and a large number of comparisons have been made between the aforementioned methods. The best-suited model for each country is identified considering the root mean squared error and mean absolute percent error values from the compositional data. As noted in this study, first and foremost, it is predicted that by the year 2030, China will witness the disappearance of population dividend and get mired in an aging problem far more severe than that of India or Vietnam. Second, Vietnam’s trend of change in population age structure resembles that of China, but the country will sustain its good health as a whole. Finally, the working population of India demonstrates a strong rising trend, indicating that the age structure of the Indian population still remains relatively “young”. Meanwhile, the continuous rise in the proportion of elderly population and the gradual leveling off growth of the young population have nevertheless become serious problems in the world. The present paper attempts to offer crucial insights into the Asian population size, labor market and urbanization, and, moreover, provides suggestions for a sustainable global demographic development.

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.

In 2023, the annual household consumption expenditure in India amounted to 2.14 trillion U.S. dollars. This was an increase as compared to the previous year, when the annual household consumption expenditure amounted to just over two trillion U.S. dollars. Household consumption expenditure is the market value of goods and services purchased by households, including slow-moving consumer goods (computers, cars, and washing machines).

The objective of the Survey of Jails in Indian Country is to gather data on all adult and juvenile jail facilities and detention centers in Indian country, which is defined for purposes of this collection as reservations, pueblos, rancherias, and other Native American and Alaska Native communities throughout the United States. The survey, a complete enumeration of all 69 confinement facilities operated by tribal authorities or the Bureau of Indian Affairs (BIA), provides data on number of inmates, staffing, and facility characteristics and needs. Variables describe each facility, including who operated it, facility age, facility function, rated capacity, authority to house juveniles, number of juveniles held, number of admission and discharges in last 30 days, number of inmate deaths, the peak population during June, number of inmates held by sex and conviction status on June 30, number of facility staff by sex and function, facility crowding, renovation and building plans, types of programs available to inmates, and overview of facility and staffing needs.

The 2022 cartographic boundary shapefiles are simplified representations of selected geographic areas from the U.S. Census Bureau's Master Address File / Topologically Integrated Geographic Encoding and Referencing (MAF/TIGER) Database (MTDB). These boundary files are specifically designed for small-scale thematic mapping. When possible, generalization is performed with the intent to maintain the hierarchical relationships among geographies and to maintain the alignment of geographies within a file set for a given year. Geographic areas may not align with the same areas from another year. Some geographies are available as nation-based files while others are available only as state-based files. Census tracts are small, relatively permanent statistical subdivisions of a county or equivalent entity, and were defined by local participants as part of the 2020 Census Participant Statistical Areas Program. The Census Bureau delineated the census tracts in situations where no local participant existed or where all the potential participants declined to participate. The primary purpose of census tracts is to provide a stable set of geographic units for the presentation of census data and comparison back to previous decennial censuses. Census tracts generally have a population size between 1,200 and 8,000 people, with an optimum size of 4,000 people. When first delineated, census tracts were designed to be homogeneous with respect to population characteristics, economic status, and living conditions. The spatial size of census tracts varies widely depending on the density of settlement. Physical changes in street patterns caused by highway construction, new development, and so forth, may require boundary revisions. In addition, census tracts occasionally are split due to population growth, or combined as a result of substantial population decline. Census tract boundaries generally follow visible and identifiable features. They may follow legal boundaries such as minor civil division (MCD) or incorporated place boundaries in some states and situations to allow for census tract-to-governmental unit relationships where the governmental boundaries tend to remain unchanged between censuses. State and county boundaries always are census tract boundaries in the standard census geographic hierarchy. In a few rare instances, a census tract may consist of noncontiguous areas. These noncontiguous areas may occur where the census tracts are coextensive with all or parts of legal entities that are themselves noncontiguous. For the 2010 Census and beyond, the census tract code range of 9400 through 9499 was enforced for census tracts that include a majority American Indian population according to Census 2000 data and/or their area was primarily covered by federally recognized American Indian reservations and/or off-reservation trust lands; the code range 9800 through 9899 was enforced for those census tracts that contained little or no population and represented a relatively large special land use area such as a National Park, military installation, or a business/industrial park; and the code range 9900 through 9998 was enforced for those census tracts that contained only water area, no land area.

p-Likelihood ratio test for no difference between the three groups for age and standard of living index ignoring the correlated data. For the remaining factors p-value is the result of a simple χ2 test for independence.SD, standard deviation.

Study population characteristics by sex and migration status. Indian migration study, 2005–2007.