Delhi was the largest city in terms of number of inhabitants in India in 2023.The capital city was estimated to house nearly 33 million people, with Mumbai ranking second that year. India's population estimate was 1.4 billion, ahead of China that same year.

Population in largest city in India was reported at 33807403 in 2024, according to the World Bank collection of development indicators, compiled from officially recognized sources. India - Population in largest city - actual values, historical data, forecasts and projections were sourced from the World Bank on June of 2025.

Population in the largest city (% of urban population) in India was reported at 6.3201 % in 2024, according to the World Bank collection of development indicators, compiled from officially recognized sources. India - Population in the largest city - actual values, historical data, forecasts and projections were sourced from the World Bank on July of 2025.

The population in New Delhi was approximately 28.5 million, the most among the leading Indian cities in 2019. Mumbai and Kolkata rounded up the three most populated cities across the country that year.

Chart and table of population level and growth rate for the Delhi, India metro area from 1950 to 2025.

As per the Census data dated 2011, the slum dwellers population in Mumbai was the highest among all other major metropolitan cities of India, at around ************. Hyderabad and Delhi followed it. A total of about ** million people were estimated to be living in slums across the country.

Japan’s largest city, greater Tokyo, had a staggering 37.19 million inhabitants in 2023, making it the most populous city across the Asia-Pacific region. India had the second largest city after Japan with a population consisting of approximately 33 million inhabitants. Contrastingly, approximately 410 thousand inhabitants populated Papua New Guinea's largest city in 2023. A megacity regionNot only did Japan and India have the largest cities throughout the Asia-Pacific region but they were among the three most populated cities worldwide in 2023. Interestingly, over half on the world’s megacities were situated in the Asia-Pacific region. However, being home to more than half of the world’s population, it does not seem surprising that by 2025 it is expected that more than two thirds of the megacities across the globe will be located in the Asia Pacific region. Other megacities are also expected to emerge within the Asia-Pacific region throughout the next decade. There have even been suggestions that Indonesia’s Jakarta and its conurbation will overtake Greater Tokyo in terms of population size by 2030. Increasing populationsIncreased populations in megacities can be down to increased economic activity. As more countries across the Asia-Pacific region have made the transition from agriculture to industry, the population has adjusted accordingly. Thus, more regions have experienced higher shares of urban populations. However, as many cities such as Beijing, Shanghai, and Seoul have an aging population, this may have an impact on their future population sizes, with these Asian regions estimated to have significant shares of the population being over 65 years old by 2035.

In 2022, the union territory of Delhi had the highest urban population density of over 18 thousand persons per square kilometer. While the rural population density was highest in union territory of Puducherry, followed by the state of Bihar.

Chart and table of population level and growth rate for the Bangalore, India metro area from 1950 to 2025.

About this dataset

Context

The dataset tabulates the median household income in Indian Village. It can be utilized to understand the trend in median household income and to analyze the income distribution in Indian Village by household type, size, and across various income brackets.

Content

The dataset will have the following datasets when applicable

Please note: The 2020 1-Year ACS estimates data was not reported by the Census Bureau due to the impact on survey collection and analysis caused by COVID-19. Consequently, median household income data for 2020 is unavailable for large cities (population 65,000 and above).

• Indian Village, IN Median Household Income Trends (2010-2021, in 2022 inflation-adjusted dollars)
• Median Household Income Variation by Family Size in Indian Village, IN: Comparative analysis across 7 household sizes
• Income Distribution by Quintile: Mean Household Income in Indian Village, IN
• Indian Village, IN households by income brackets: family, non-family, and total, in 2022 inflation-adjusted dollars

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/.

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Explore our comprehensive data analysis and visual representations for a deeper understanding of Indian Village median household income. You can refer the same here

In 2023, approximately a third of the total population in India lived in cities. The trend shows an increase of urbanization by more than 4 percent in the last decade, meaning people have moved away from rural areas to find work and make a living in the cities. Leaving the fieldOver the last decade, urbanization in India has increased by almost 4 percent, as more and more people leave the agricultural sector to find work in services. Agriculture plays a significant role in the Indian economy and it employs almost half of India’s workforce today, however, its contribution to India’s GDP has been decreasing while the services sector gained in importance. No rural exodus in sightWhile urbanization is increasing as more jobs in telecommunications and IT are created and the private sector gains in importance, India is not facing a shortage of agricultural workers or a mass exodus to the cities yet. India is a very densely populated country with vast areas of arable land – over 155 million hectares of land was cultivated land in India as of 2015, for example, and textiles, especially cotton, are still one of the major exports. So while a shift of the workforce focus is obviously taking place, India is not struggling to fulfill trade demands yet.

As of the year 2024, the population of the capital city of India, Delhi was over ** million people. This was a 2.63 percent growth from last year. The historical trends show that the population doubled between 1990 and 2010. The UN estimated that the population was expected to reach around ** million by 2030. Reasons for population growth   As per the Delhi Economic Survey, migration added over *** thousand people to Delhi’s population in 2022. The estimates showed relative stability in natural population growth for a long time before the pandemic. The numbers suggest a sharp decrease in birth rates from 2020 onwards and a corresponding increase in death rates in 2021 due to the Covid-19 pandemic. The net natural addition or the remaining growth is attributed to migration. These estimates are based on trends published by the Civil Registration System. National Capital Region (NCR) Usually, population estimates for Delhi represent the urban agglomeration of Delhi, which includes Delhi and some of its adjacent suburban areas. The National Capital Region or NCR is one of the largest urban agglomerations in the world. It is an example of inter-state regional planning and development, centred around the National Capital Territory of Delhi, and covering certain districts of neighbouring states Haryana, Uttar Pradesh, and Rajasthan. Noida, Gurugram, and Ghaziabad are some of the key cities of NCR. Over the past decade, NCR has emerged as a key economic centre in India.

Abstract

The National Family Health Survey (NFHS) was carried out as the principal activity of a collaborative project to strengthen the research capabilities of the Population Reasearch Centres (PRCs) in India, initiated by the Ministry of Health and Family Welfare (MOHFW), Government of India, and coordinated by the International Institute for Population Sciences (IIPS), Bombay. Interviews were conducted with a nationally representative sample of 89,777 ever-married women in the age group 13-49, from 24 states and the National Capital Territoty of Delhi. The main objective of the survey was to collect reliable and up-to-date information on fertility, family planning, mortality, and maternal and child health. Data collection was carried out in three phases from April 1992 to September 1993. THe NFHS is one of the most complete surveys of its kind ever conducted in India.

The households covered in the survey included 500,492 residents. The young age structure of the population highlights the momentum of the future population growth of the country; 38 percent of household residents are under age 15, with their reproductive years still in the future. Persons age 60 or older constitute 8 percent of the population. The population sex ratio of the de jure residents is 944 females per 1,000 males, which is slightly higher than sex ratio of 927 observed in the 1991 Census.

The primary objective of the NFHS is to provide national-level and state-level data on fertility, nuptiality, family size preferences, knowledge and practice of family planning, the potentiel demand for contraception, the level of unwanted fertility, utilization of antenatal services, breastfeeding and food supplemation practises, child nutrition and health, immunizations, and infant and child mortality. The NFHS is also designed to explore the demographic and socioeconomic determinants of fertility, family planning, and maternal and child health. This information is intended to assist policymakers, adminitrators and researchers in assessing and evaluating population and family welfare programmes and strategies. The NFHS used uniform questionnaires and uniform methods of sampling, data collection and analysis with the primary objective of providing a source of demographic and health data for interstate comparisons. The data collected in the NFHS are also comparable with those of the Demographic and Health Surveys (DHS) conducted in many other countries.

Geographic coverage

National

Analysis unit

• Household
• Data collected for women 13-49, indicators calculated for women 15-49

Universe

The population covered by the 1992-93 DHS is defined as the universe of all women age 13-49 who were either permanent residents of the households in the NDHS sample or visitors present in the households on the night before the survey were eligible to be interviewed.

Kind of data

Sample survey data

Sampling procedure

SAMPLE DESIGN

The sample design for the NFHS was discussed during a Sample Design Workshop held in Madurai in Octber, 1991. The workshop was attended by representative from the PRCs; the COs; the Office of the Registrar General, India; IIPS and the East-West Center/Macro International. A uniform sample design was adopted in all the NFHS states. The Sample design adopted in each state is a systematic, stratified sample of households, with two stages in rural areas and three stages in urban areas.

SAMPLE SIZE AND ALLOCATION

The sample size for each state was specified in terms of a target number of completed interviews with eligible women. The target sample size was set considering the size of the state, the time and ressources available for the survey and the need for separate estimates for urban and rural areas of the stat. The initial target sample size was 3,000 completed interviews with eligible women for states having a population of 25 million or less in 1991; 4,000 completed interviews for large states with more than 25 million population; 8,000 for Uttar Pradesh, the largest state; and 1,000 each for the six small northeastern states. In States with a substantial number of backward districts, the initial target samples were increased so as to allow separate estimates to be made for groups of backward districts.

The urban and rural samples within states were drawn separetly and , to the extent possible, sample allocation was proportional to the size of the urban-rural populations (to facilitate the selection of a self-weighting sample for each state). In states where the urban population was not sufficiently large to provide a sample of at least 1,000 completed interviews with eligible women, the urban areas were appropriately oversampled (except in the six small northeastern states).

THE RURAL SAMPLE: THE FRAME, STRATIFICATION AND SELECTION

A two-stage stratified sampling was adopted for the rural areas: selection of villages followed by selection of households. Because the 1991 Census data were not available at the time of sample selection in most states, the 1981 Census list of villages served as the sampling frame in all the states with the exception of Assam, Delhi and Punjab. In these three states the 1991 Census data were used as the sampling frame.

Villages were stratified prior to selection on the basis of a number of variables. The firts level of stratification in all the states was geographic, with districts subdivided into regions according to their geophysical characteristics. Within each of these regions, villages were further stratified using some of the following variables : village size, distance from the nearest town, proportion of nonagricultural workers, proportion of the population belonging to scheduled castes/scheduled tribes, and female literacy. However, not all variables were used in every state. Each state was examined individually and two or three variables were selected for stratification, with the aim of creating not more than 12 strata for small states and not more than 15 strata for large states. Females literacy was often used for implicit stratification (i.e., the villages were ordered prior to selection according to the proportion of females who were literate). Primary sampling Units (PSUs) were selected systematically, with probaility proportional to size (PPS). In some cases, adjacent villages with small population sizes were combined into a single PSU for the purpose of sample selection. On average, 30 households were selected for interviewing in each selected PSU.

In every state, all the households in the selected PSUs were listed about two weeks prior to the survey. This listing provided the necessary frame for selecting households at the second sampling stage. The household listing operation consisted of preparing up-to-date notional and layout sketch maps of each selected PSU, assigning numbers to structures, recording addresses (or locations) of these structures, identifying the residential structures, and listing the names of the heads of all the households in the residentiak structures in the selected PSU. Each household listing team consisted of a lister and a mapper. The listing operation was supervised by the senior field staff of the concerned CO and the PRC in each state. Special efforts were made not to miss any household in the selected PSU during the listing operation. In PSUs with fewer than 500 households, a complete household listing was done. In PSUs with 500 or more households, segmentation of the PSU was done on the basis of existing wards in the PSU, and two segments were selected using either systematic sampling or PPS sampling. The household listing in such PSUs was carried out in the selected segments. The households to be interviewed were selected from provided with the original household listing, layout sketch map and the household sample selected for each PSU. All the selected households were approached during the data collection, and no substitution of a household was allowed under any circumstances.

THE RURAL URBAN SAMPLE: THE FRAME, STRATIFICATION AND SELECTION

A three-stage sample design was adopted for the urban areas in each state: selection of cities/towns, followed by urban blocks, and finally households. Cities and towns were selected using the 1991 population figures while urban blocks were selected using the 1991 list of census enumeration blocks in all the states with the exception of the firts phase states. For the first phase states, the list of urban blocks provided by the National Sample Survey Organization (NSSSO) served as the sampling frame.

All cities and towns were subdivided into three strata: (1) self-selecting cities (i.e., cities with a population large enough to be selected with certainty), (2) towns that are district headquaters, and (3) other towns. Within each stratum, the cities/towns were arranged according to the same kind of geographic stratification used in the rural areas. In self-selecting cities, the sample was selected according to a two-stage sample design: selection of the required number of urban blocks, followed by selection of households in each of selected blocks. For district headquarters and other towns, a three stage sample design was used: selection of towns with PPS, followed by selection of two census blocks per selected town, followed by selection of households from each selected block. As in rural areas, a household listing was carried out in the selected blocks, and an average of 20 households per block was selected systematically.

Mode of data collection

Face-to-face

Research instrument

Three types of questionnaires were used in the NFHS: the Household Questionnaire, the Women's Questionnaire, and the Village Questionnaire. The overall content

This horizontal bar chart displays urban population living in areas where elevation is below 5 meters (% of total population) by capital city using the aggregation average, weighted by population in India. The data is about countries per year.

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.

Abstract

The Employment and Unemployment surveys of National sample Survey (NSS) are primary sources of data on various indicators of labour force at National and State levels. These are used for planning, policy formulation, decision support and as input for further statistical exercises by various Government organizations, academicians, researchers and scholars. NSS surveys on employment and un-employment with large sample size of households have been conducted quinquennially from 27th. round(October'1972 - September'1973) onwards. Cotinuing in this series the fourth such all-india survey on the situation of employment and unemployment in India was carried out during the period july 1987 - june 1988 .

The working Group set up for planning of the entire scheme of the survey, among other things, examined also in detail some of the key results generated from the 38th round data and recommended some stream-lining of the 38th round schedule for the use in the 43rd round. Further, it felt no need for changing the engaging the easting conceptual frame work. However, some additional items were recommended to be included in the schedule to obtain the necessary and relevant information for generating results to see the effects on participation rates in view of the ILO suggestions.5.0.1. The NSSO Governing Council approved the recommendations of the working Group and also the schedule of enquiry in its 44th meeting held on 16 January, 1987. In this survey, a nation-wide enquiry was conducted to provide estimates on various characteristics pertaining to employment and unemployment in India and some characteristics associated with them at the national and state levels. Information on various facets of employment and unemployment in India was collected through a schedule of enquiry (schedule 10).

Geographic coverage

The survey covered the whole of Indian Union excepting i) Ladakh and Kargil districts of Jammu & Kashmir ii) Rural areas of Nagaland

Analysis unit

Randomly selected households based on sampling procedure and members of the household

Kind of data

Sample survey data [ssd]

Sampling procedure

It may be mentioned here that in order to net more households of the upper income bracket in the Sample , significant changes have been made in the sample design in this round (compares to the design of the 38th round).

SAMPLE DESIGN AND SAMPLE SIZE The survey had a two-stage stratified design. The first stage units (f.s.u.'s) are villages in the rural sector and urban blocks in the urban sector. The second stage units are households in both the sectors. Sampling frame for f.s.u.'s : The lists of 1981 census villages constituted the sampling frame for rural sector in most districts. But the 1981 census frame could not be used for a few districts because, either the 1981 census was not held there or the list of 1981 census villages could not be obtained or the lists obtained from the census authorities were found to be grossly incomplete. In such cases 1971 census frame were used. In the urban sector , the Urban Frame Survey (U.F.S.) blocks constituted the sampling frame. STRATIFICATION : States were first divided into agro-economic regions which are groups of contiguous districts , similar with respect to population density and crop pattern. In Gujarat, however , some districts have been split for the purpose of region formation In consideration of the location of dry areas and the distribution of the tribal population in the state. The composition of the regions is given in the Appendix. RURAL SECTOR: In the rural sector, within each region, each district with 1981Census rural population less 1.8 million formed a single stratum. Districts with larger population were divided into two or more strata, depending on population, by grouping contiguous tehsils similar, as for as possible, in respect of rural population Density and crop pattern. (In Gujarat, however , in the case of districts extending over more than one region, even if the rural population was less than 1.8 million, the portion of a district falling in each region constituted a separate stratum. Further ,in Assam the old "basic strata" formed on the basis of 1971 census rural population exactly in the above manner, but with cut-off population as 1.5 million have been retained as the strata for rural sampling.) URBAN SECTOR : In the urban sector , strata were formed , again within NSS region , on the basis of the population size class of towns . Each city with population 10 lakhs or more is self-representative , as in the earlier rounds . For the purpose of stratification, in towns with '81 census population 4 lakhs or more , the blocks have been divided into two categories , viz . : One consisting of blocks in areas inhabited by the relatively affluent section of the population and the other consisting of the remaining blocks. The strata within each region were constituted as follows :

Table (1.2) : Composition of urban strata

Stratum population class of town

number

(1) (2)

1 all towns with population less than 50,000 2 -do- 50,000 - 199,999 3 -do- 200,000 - 399,999 4 -do- 400,000 - 999,999 ( affluent area) 5 (other area) 6 a single city with population 1 million and above (affluent area) 7 " (other area) 8 another city with population 1 million and above

9 " (other area)

Note : There is no region with more than one city with population 1 million and above. The stratum number have been retained as above even if in some regions some of the strata are empty. Allocation for first stage units : The total all-India sample size was allocated to the states /U.T.'s proportionate to the strength of central field staff. This was allocated to the rural and urban sectors considering the relative size of the rural and urban population. Now the rural samples were allocated to the rural strata in proportion to rural population. The urban samples were allocated to the urban strata in proportion to urban population with double weight age given to those strata of towns with population 4 lakhs or more which lie in area inhabited by the relatively affluent section. All allocations have been adjusted such that the sample size for stratum was at least a multiple of 4 (preferably multiple of 8) and the total sample size of a region is a multiple of 8 for the rural and urban sectors separately.
Selection of f.s.u.'s : The sample villages have been selected circular systematically with probability proportional to population in the form of two independent interpenetrating sub-samples (IPNS) . The sample blocks have been selected circular systematically with equal probability , also in the form of two IPNS' s. As regards the rural areas of Arunachal Pradesh, the procedure of 'cluster sampling' was:- The field staff will be supplied with a list of the nucleus villages of each cluster and they selected the remaining villages of the cluster according to the procedure described in Section Two. The nucleus villages were selected circular systematically with equal probability, in the form of two IPNS 's. Hamlet-group and sub-blocks : Large villages and blocks were sub- divided into a suitable number of hamlet-groups and sub-blocks respectively having equal population convent and one them was selected at random for surveys. Hamlet-group and sub-blocks : Large villages and blocks were sub- divided into a suitable number of hamlet-groups and sub-blocks respectively having equal population convent and one them was selected at random for surveys. Selection of households : rural : In order to have adequate number of sample households from the affluent section of the society, some new procedures were introduced for selection of sample households, both in the rural and urban sectors. In the rural sector , while listing households, the investigator identified the households in village/ selected hamlet- group which may be considered to be relatively more affluent than the rest. This was done largely on the basis of his own judgment but while exercising his judgment considered factors generally associated with rich people in the localitysuch as : living in large pucca house in well-maintained state, ownership/possession of cultivated/irrigated land in excess of certain norms. ( e.g.20 acres of cultivated land or 10 acres of irrigated land), ownership of motor vehicles and costly consumer durables like T.V. , VCR, VCP AND refrigerator, ownership of large business establishment , etc. Now these "rich" households will form sub-stratum 1. (If the total number of households listed is 80 or more , 10 relatively most affluent households will form sub-stratum 1. If it is below 80, 8 such households will form sub-stratum 1. The remaining households will 'constitute sub-stratum 2. At the time of listing, information relating to each household' s major sources of income will be collected, on the basis of which its means of livelihood will be identified as one of the following : "self-employed in non-agriculture " "rural labour" and "others" (see section Two for definition of these terms) . Also the area of land possessed as on date of survey will be ascertained from all households while listing. Now the households of sub-stratum 2 will be arranged in the order : (1)self-employed in non-agriculture, (2) rural labour, other households, with land possessed (acres) : (3) less than 1.00 (4) 1.00-2.49,(5)2.50-4.99, (6)

Abstract

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.

Geographic coverage

• National (29 states )
• Regional (for HIV Prevalence : Andhra Pradesh, Karnataka, Maharashtra, Manipur, and Tamil Nadu)
• Local (population and health indicators for slum and non-slum populations for eight cities, namely Chennai, Delhi, Hyderabad, Indore, Kolkata, Meerut, Mumbai, and Nagpur)

Analysis unit

• Household
• Women age 15-49
• Men age 15-59

Universe

The population covered by the 2005 DHS is defined as the universe of all ever-married women age 15-49, NFHS-3 included never married women age 15-49 and both ever-married and never married men age 15-54 as eligible respondents.

Kind of data

Sample survey data

Sampling procedure

SAMPLE SIZE

Since a large number of the key indicators to be estimated from NFHS-3 refer to ever-married women in the reproductive ages of 15-49, the target sample size for each state in NFHS-3 was estimated in terms of the number of ever-married women in the reproductive ages to be interviewed.

The initial target sample size was 4,000 completed interviews with ever-married women in states with a 2001 population of more than 30 million, 3,000 completed interviews with ever-married women in states with a 2001 population between 5 and 30 million, and 1,500 completed interviews with ever-married women in states with a population of less than 5 million. In addition, because of sample-size adjustments required to meet the need for HIV prevalence estimates for the high HIV prevalence states and Uttar Pradesh and for slum and non-slum estimates in eight selected cities, the sample size in some states was higher than that fixed by the above criteria. The target sample was increased for Andhra Pradesh, Karnataka, Maharashtra, Manipur, Nagaland, Tamil Nadu, and Uttar Pradesh to permit the calculation of reliable HIV prevalence estimates for each of these states. The sample size in Andhra Pradesh, Delhi, Maharashtra, Tamil Nadu, Madhya Pradesh, and West Bengal was increased to allow separate estimates for slum and non-slum populations in the cities of Chennai, Delhi, Hyderabad, Indore, Kolkata, Mumbai, Meerut, and Nagpur.

The target sample size for HIV tests was estimated on the basis of the assumed HIV prevalence rate, the design effect of the sample, and the acceptable level of precision. With an assumed level of HIV prevalence of 1.25 percent and a 15 percent relative standard error, the estimated sample size was 6,400 HIV tests each for men and women in each of the high HIV prevalence states. At the national level, the assumed level of HIV prevalence of less than 1 percent (0.92 percent) and less than a 5 percent relative standard error yielded a target of 125,000 HIV tests at the national level.

Blood was collected for HIV testing from all consenting ever-married and never married women age 15-49 and men age 15-54 in all sample households in Andhra Pradesh, Karnataka, Maharashtra, Manipur, Tamil Nadu, and Uttar Pradesh. All women age 15-49 and men age 15-54 in the sample households were eligible for interviewing in all of these states plus Nagaland. In the remaining 22 states, all ever-married and never married women age 15-49 in sample households were eligible to be interviewed. In those 22 states, men age 15-54 were eligible to be interviewed in only a subsample of households. HIV tests for women and men were carried out in only a subsample of the households that were selected for men's interviews in those 22 states. The reason for this sample design is that the required number of HIV tests is determined by the need to calculate HIV prevalence at the national level and for some states, whereas the number of individual interviews is determined by the need to provide state level estimates for attitudinal and behavioural indicators in every state. For statistical reasons, it is not possible to estimate HIV prevalence in every state from NFHS-3 as the number of tests required for estimating HIV prevalence reliably in low HIV prevalence states would have been very large.

SAMPLE DESIGN

The urban and rural samples within each state were drawn separately and, to the extent possible, unless oversampling was required to permit separate estimates for urban slum and non-slum areas, the sample within each state was allocated proportionally to the size of the state's urban and rural populations. A uniform sample design was adopted in all states. In each state, the rural sample was selected in two stages, with the selection of Primary Sampling Units (PSUs), which are villages, with probability proportional to population size (PPS) at the first stage, followed by the random selection of households within each PSU in the second stage. In urban areas, a three-stage procedure was followed. In the first stage, wards were selected with PPS sampling. In the next stage, one census enumeration block (CEB) was randomly selected from each sample ward. In the final stage, households were randomly selected within each selected CEB.

SAMPLE SELECTION IN RURAL AREAS

In rural areas, the 2001 Census list of villages served as the sampling frame. The list was stratified by a number of variables. The first level of stratification was geographic, with districts being subdivided into contiguous regions. Within each of these regions, villages were further stratified using selected variables from the following list: village size, percentage of males working in the nonagricultural sector, percentage of the population belonging to scheduled castes or scheduled tribes, and female literacy. In addition to these variables, an external estimate of HIV prevalence, i.e., 'High', 'Medium' or 'Low', as estimated for all the districts in high HIV prevalence states, was used for stratification in high HIV prevalence states. Female literacy was used for implicit stratification (i.e., villages were

Analysis of ‘Swiggy Restaurants Dataset of Metro Cities’ provided by Analyst-2 (analyst-2.ai), based on source dataset retrieved from https://www.kaggle.com/aniruddhapa/swiggy-restaurants-dataset-of-metro-cities on 28 January 2022.

--- Dataset description provided by original source is as follows ---

Context

This dataset contains swiggy registered restaurants details of major metropoliton cities of India. I have considered only metropoliton cities with population 4.5 million. As per the Census of India 2011 definition of more than 4 million population, some of the major Metropolitan Cities in India are:

Mumbai (more than 18 Million) Delhi (more than 16 Million) Kolkata (more than 14 Million) Chennai (more than 8.6 million) Bangalore (around 8.5 million) Hyderabad (around 7.6 million) Ahmedabad (around 6.3 million) Pune (around 5.05 million) Surat (around 4.5 million)

Content

I have scrapped the data using python. It may not have all the restaurants of a particular city because if during webscrapping any restaurant has not enabled swiggy as their delivery partner, that restaurant's details will not be scrapped. Though I have scrapped same cities multiple times, to include maximum restaurant details. The data is collected on 12th Jan 2022.

Acknowledgements

Thank you swiggy for the dataset.

Inspiration

Your data will be in front of the world's largest data science community. What questions do you want to see answered?

--- Original source retains full ownership of the source dataset ---

Background: Particulate matter (PM) is one among the crucial air pollutants and has the potential to cause a wide range of health effects. Indian cities ranked top places in the World Health Organization list of most polluted cities by PM. Objectives: Present study aims to assess the trends, short- and long-term health effects of PM in major Indian cities. Methods: PM-induced hospital admissions and mortality are quantified using AirQ+ software. Results: Annual PM concentration in most of the cities is higher than the National Ambient Air Quality Standards of India. Trend analysis showed peak PM concentration during post-monsoon and winter seasons. The respiratory and cardiovascular hospital admissions in the male (female) population are estimated to be 31,307 (28,009) and 5460 (4882) cases, respectively. PM2.5 has accounted for a total of 1,27,014 deaths in 2017. Conclusion: Cities with high PM concentration and exposed population are more susceptible to mortality and hospital admissions.

Descriptive analysis of under-5 children in total slum population of eight Indian cities, NFHS-4, 2015–16.