India Census: Number of Households: Delhi: by Size: 6 to 8 Members data was reported at 853,773.000 Unit in 2011. India Census: Number of Households: Delhi: by Size: 6 to 8 Members data is updated yearly, averaging 853,773.000 Unit from Mar 2011 (Median) to 2011, with 1 observations. India Census: Number of Households: Delhi: by Size: 6 to 8 Members 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.GAF013: Census: Number of Households: by Size: Delhi.

Content

The Dataset is fully dedicated for the developers who want to train the model on Weather Forecasting for Indian climate. This dataset provides data from 1st January 2013 to 24th April 2017 in the city of Delhi, India. The 4 parameters here are meantemp, humidity, wind_speed, meanpressure.

Acknowledgements

This dataset has been collected from Weather Undergroud API. Dataset ownership and credit goes to them.

Submission Deadline

Assignment 4 must be submitted by October 19, 2019 (10:00 PM). Any kernel published after this deadline will be evaluated for only 50% of the total marks.

Inspiration

This dataset was developed as a part Assignment 4 of Data Analytics Course, 2019 at PES University, Bangalore.

In India's capital territory of Delhi, the share of males with multiple disability was at 1.4 percent and with locomotor disabilities at 0.9 percent in 2018. The same among females was less prevalent. According to the 76th round of the NSO survey conducted between July and December 2018, a higher percentage of disabled men than disabled women were present in India. The National Statistical Office (NSO) is the statistical wing of the Ministry of Statistics and Programme Implementation (MOSPI), mainly responsible for laying down standards for statistical analysis, data collection, and implementation.

In the year 2022, *** thousand people were estimated to have migrated to Delhi. This was a decrease from 2021. Migration contributed more to Delhi's population growth than the number of births, standing at *** thousand.

This dataset contains year, state and district wise number of Asthma Cases in children of age group 0-5 years

Note: Asthma is a condition in which your airways narrow and swell and may produce extra mucus. This can make breathing difficult and trigger coughing, a whistling sound (wheezing) when you breathe out and shortness of breath. For some people, asthma is a minor nuisance.

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

Context

A Google Forms Survey Was Conducted In May 2021 Among College Students Of Delhi. The Data Was Aimed At Opinions Regarding Employment Among The Indian Urban Youth.

Image Credits-Unsplash

Inspiration

Analyse The Data And Find Some Insights Regarding The Opinion Of Youngsters. Try to find patterns among the choices.

This database is a unique achievement to which we are happy to give you a free access. It covers the members of the lower house of the Indian parliament (the House of the People or Lok Sabha) who have been elected between the first general elections of 1951-52 and the fourteenth ones in 2004 in the Hindi-speaking states (Bihar, Chandigarh, Chhattisgarh, Delhi, Haryana, Himachal Pradesh, Jharkhand, Madhya Pradesh, Rajasthan, Uttar Pradesh, Uttarakhand). Many of these states did not exist in 1951-52. We have done as if they did by pooling together the constituencies which were to form them in order to make inter-temporal comparisons possible. For each Lok Sabha MP, this database provides their surname, first name, constituency, state of birth, party, gender, date of birth, religion, caste, level of education, and occupation. These data draw from the Election Commission publications, the website Who's Who in Lok Sabha [the only website I found today is the Parliament of India, Lok Sabha, https://loksabha.nic.in/]. and individual interviews with the MPs themselves or party old timers. Such a database can only result from a collective endeavour. It was initiated by Christophe Jaffrelot who collected most of the data year after year from the mid-1990s onwards. Elisabeth Theunissen, Cyril Robin, Virginie Dutoya, and Zuheir Desai played a major role successively over the last fifteen years. These data have been analysed in two books dealing with the growing presence of the low caste groups on the Indian political scene: Christophe Jaffrelot, India's silent revolution - The rise of the lower castes in North Indian politics (New York, Columbia University Press, 2003), and Christophe Jaffrelot, "Introduction", in Christophe Jaffrelot and Sanjay Kumar (eds), Rise of the plebeians ? The changing face of Indian legislative assemblies, New Delhi, Routledge, 2009.

Abstract

Objectives: The National Sample Survey Organisation (NSSO) carried out the first country wide comprehensive survey of physically disabled persons during the 36th round survey (July - December, 1981). The next survey on the subject was carried out after a period of ten years in NSS 47th round (July - December, 1991). In NSS 36th and 47th round surveys, information was collected on three types of physical disabilities - visual, communication and locomotor - along with the cause of disability, aid/appliance acquired by the disabled, general and vocational educational level of the disabled etc. In addition, data on developmental milestones and behavioural pattern of all children of age 5-14 years, regardless of whether they were physically disabled or not, were collected. The Ministry of Social Justice and Empowerment (MSJE) made a request for conducting a survey on disability in order to meet the data needs for evolving specific strategies and interventions during the 10th Five Year Plan. The need for a detailed survey on disability was strongly felt by MSJE since its data requirement included not only the number of disabled persons, but also the socio-economic characteristics of the disabled persons such as their age structure, literacy, vocational training, employment, causative factors of disability, age at the onset of disability etc. Keeping in view the urgent data need of the MSJE, the Governing Council of NSSO, in its 81st meeting, decided that the survey on disability may also be carried out as a part of NSS 58th round during July - December 2002. It has been decided that: (i) The survey of disabled persons also covers persons with mental disability apart from the physically disabled persons since the Ministry of Social Justice and Empowerment (MSJE) also requested for information on mentally disabled persons. The decision to include mental disability in the survey has been taken on the basis of a pre-test of the questions on mental disability, both for the listing and detailed schedules, carried out in the four cities of Kolkata, Mumbai, Hyderabad and Delhi. (ii) The information for different types of disabilities is collected for persons of all age-groups. Separate information on the developmental milestones of children are not collected.

Reference Period: July-December 2002

Periodicity of Data Collection:

Geographic coverage

The whole of the Indian Union, except (i) Leh and Kargil districts of Jammu & Kashmir, (ii) interior villages of Nagaland situated beyond five kilometres of the bus route and (iii) villages in Andaman and Nicobar Islands, which remain inaccessible throughout the year.

Analysis unit

Individuals

Universe

Population groups: All age groups

Total population covered: Na

Economic activities: All economic activities

Sectors covered: Na

Labor force status: Employed persons, unemployed persons, persons outside labour force

Status in Employment: All

Establishments: NR

Other limitations: Na

Classifications: Na

Cross-classification: Na

Kind of data

Sample survey data [ssd]

Frequency of data collection

Periodicity of Data collection:

Abstract

The UNHCR Results Monitoring Survey (RMS) is a household-level survey covering people who are directly or indirectly assisted by UNHCR. In India, respondents included the refugees and asylum seekers registered with UNHCR. The survey did not cover the refugees registered with the government and the people in refugee like situations. The objective of the survey is to monitor impact and outcome level indicators on education, healthcare, livelihoods, protection concerns, shelter, and water and sanitation. The results contribute to an evidence base for reporting against UNHCR’s multi-year strategies to key stakeholders.

The RMS can be implemented in any operational context. A standard structured questionnaire has been developed for the RMS, which can be conducted as a stand-alone survey or flexibly integrated with other data collection exercises. The questionnaire was adapted to the India context and programme objectives by including additional modules from the Health Access and Utilization Survey. A mixed methodology of remote and in-person interview was applied to allow for inclusion of respondents in areas not accessible to data collectors. Delhi, Hyderabad and Mewat were visited physically. The data includes indicators collected at both the household and individual (household-member) level. The survey covered 558 households amounting to 1932 individuals.

Analysis unit

Households

Universe

Refugees and Asylum Seekers registeredby UNHCR in India 2024

Kind of data

Sample survey data [ssd]

Mode of data collection

Computer Assisted Personal Interview [capi],Computer Assisted Telephone Interview [cati]

Intermittent Schedule Vizualization David Meyer 2022-10-24 The repository contains the data, code, and figures associated with the paper Meyer et al. 2023. Over a billion people get water from water supply networks that regularly interrupt their service. Unfortunately, the intermittent operations induce inequalities within the network. In our work, we created the tools needed to use Water Supply Schedules to quantify and compare the inequality of water supply schedules between and within cities. We apply these tools to the largest and most complicated intermittent water systems ever described in peer-reviewed papers: Delhi and Bangalore; they supply water to 25 million people according to 3278 schedules. Uniquely, we propose to use publicly posted water supply schedules to estimate service quality and service equality within intermittent systems at a novel scale: the supply schedule scale. While we demonstrate and visualize the use of supply schedules in Delhi and Bangalore, the implications of our work are much broader: we showcase a new scale at which intermittent systems could and should be researched and regulated and we provide the methods required to do so. Research into intermittent water supplies is often limited by data availability. Against this trend, we openly share our digitized versions of each city’s water supply schedules and the code required to process them in this repository. In doing so, we hope to enable other researchers to explore and model the operations of intermittent systems in ways that reflect the complexity and inequalities of intermittent supply. In this repository, you’ll find the: 1. original schedule data from both cities 2. manually transcribed schedule data 3. processed schedules in long and wide formats 4. code to process the transcribed schedules 5. visual summaries of the schedules 6. code to generate these visual summaries We extended our analysis by intersecting schedule census data using GIS. We include: 7. Census data 8. Our intersected data 9. Code to generate visual summaries of the equity data Relevant files are contained in Data, Code, and Figure subfolders.

While men constituted more than half of the active internet users in India, female users accounted for 46 percent in 2023. Over the years, the gender gap among Indian internet users appears to have been closing. In 2023, the overall number of internet users in the country amounted to over 800 million, with most of them residing in rural India.

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

In 2022, the majority of Indian adults had a wealth of 10,000 U.S. dollars or less. On the other hand, about *** percent were worth more than *********** dollars that year. India The Republic of India is one of the world’s largest and most economically powerful states. India gained independence from Great Britain on August 15, 1947, after having been under their power for 200 years. With a population of about *** billion people, it was the second most populous country in the world. Of that *** billion, about **** million lived in New Delhi, the capital. Wealth inequality India suffers from extreme income inequality. It is estimated that the top 10 percent of the population holds ** percent of the national wealth. Billionaire fortune has increase sporadically in the last years whereas minimum wages have remain stunted.

The Report Covers India Cake Market Top Companies and is segmented by Category (Packaged and Unpackaged/Artisanal), Product Type (Sponge Cakes, Cup Cakes, Cheesecakes, and Other Cakes), and Distribution Channel (Supermarkets/Hypermarkets, Convenience Stores, Specialist Retailers, Online Channels, and Other Distribution Channels).

In 2022, more than 21 million Indian nationals departed on outbound travels from India, marking a significant increase from the previous year. The coronavirus pandemic in 2020 restricted traveling around the world. Travel bug and the economy
Indian nationals are traveling more than ever before. However, far fewer Indians travel internationally compared to domestic travels. Since 2012, over one billion Indian nationals have traveled within the country. The various tax exemptions announced by the government in recent years was one of the reasons for an increase in disposable incomes among people. This seems to have been a welcome move, since a large section of the society in India travel on a need basis. The newly growing economy seems to have triggered an increase in travel and tourism expenditures especially by the middle and lower class of people who have built more capacity for savings. India’s busiest airport    The aviation industry has also grown drastically over the last decade, with over 125 operational airports in the country as of today. The Indira Gandhi International Airport in Delhi was the busiest airport in terms of passenger traffic in 2019, while the United Arab Emirates was the leading destination for passengers traveling from India. The UAE was both, a leisure and business destination for many Indians.

Per capita carbon dioxide (CO₂) emissions in India have soared in recent decades, climbing from 0.4 metric tons per person in 1970 to a high of 2.07 metric tons per person in 2023. Total CO₂ emissions in India also reached a record high in 2023. Greenhouse gas emissions in India India is the third-largest CO₂ emitter globally, behind only China and the United States. Among the various economic sectors of the country, the power sector accounts for the largest share of greenhouse gas emissions in India, followed by agriculture. Together, these two sectors were responsible for more than half of India's total emissions in 2023. Coal emissions One of the main reasons for India's high emissions is the country's reliance on coal, the most polluting of fossil fuels. India's CO₂ emissions from coal totaled roughly two billion metric tons in 2023, a near sixfold increase from 1990 levels.

In India, there were over *** airports and airstrips, while 135 were operational. Passenger traffic amounted to around *** million at airports across India in financial year 2024, out of which over ** million were international passengers. This year's passenger traffic surpassed the previous record of 2019, grew nine percent in comparison with 2024. India’s leading air carriers IndiGo airline was the leading passenger carrier in India, with around ** percent of market share in financial year 2023. It was established back in 2006 as a low-cost airline based at IGI Airport, Delhi. Following IndiGo airline was Vistara, a full-service airline with a much less **** percent market share. Vistara is a joint venture between Tata Sons and Singapore Airlines. And just a few years ago, in February 2016, Jet Airways was the largest airline in India. However, due to tough competition, and financial issues, it ceased operations in April 2019, but is expected to resume its flight operations by the end of 2024 Air freight The total air freight tonnage handled in India was around *** million metric tons in financial year 2023. It was an increase from the previous year recovering from the impact of the coronavirus (COVID-19) pandemic. IGI Airport in Delhi was the busiest in terms of volume of freight handled. In financial year 2021, India saw the highest volume of air freight of **** million metric tons. It was on a steady growth trend until the start of the pandemic.

Census: Number of Migrants: Delhi data was reported at 7,224,514.000 Person in 03-01-2011. This records an increase from the previous number of 6,014,458.000 Person for 03-01-2001. Census: Number of Migrants: Delhi data is updated decadal, averaging 6,014,458.000 Person from Mar 1991 (Median) to 03-01-2011, with 3 observations. The data reached an all-time high of 7,224,514.000 Person in 03-01-2011 and a record low of 3,723,462.000 Person in 03-01-1991. Census: Number of Migrants: Delhi 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.GAG001: Census of India: Migration: Number of Migrants: by States.

Non Resident Visits: Delhi Circle: Red Fort data was reported at 84,177.000 Person in 2024. This records an increase from the previous number of 49,060.000 Person for 2023. Non Resident Visits: Delhi Circle: Red Fort data is updated yearly, averaging 126,093.000 Person from Dec 2008 (Median) to 2024, with 17 observations. The data reached an all-time high of 163,963.000 Person in 2012 and a record low of 1,438.000 Person in 2021. Non Resident Visits: Delhi Circle: Red Fort data remains active status in CEIC and is reported by Ministry of Tourism. The data is categorized under India Premium Database’s Tourism Sector – Table IN.QD004: Non Resident Visits: by Monuments.