In India, the share of the population that earned at least the equivalent of the highest ** percent of global income earners as of 2022 in purchasing power parity (PPP) terms was ** percent. Hyderabad topped the list with the highest share of middle-class and above category of consumers. Cities from south India topped the list with the first four ranks, followed by the national capital, Delhi.

In the financial year 2021, a majority of Indian households fell under the aspirers category, earning between ******* and ******* Indian rupees a year. On the other hand, about ***** percent of households that same year, accounted for the rich, earning over * million rupees annually. The middle class more than doubled that year compared to ** percent in financial year 2005. Middle-class income group and the COVID-19 pandemic During the COVID-19 pandemic specifically during the lockdown in March 2020, loss of incomes hit the entire household income spectrum. However, research showed the severest affected groups were the upper middle- and middle-class income brackets. In addition, unemployment rates were rampant nationwide that further lead to a dismally low GDP. Despite job recoveries over the last few months, improvement in incomes were insignificant. Economic inequality While India maybe one of the fastest growing economies in the world, it is also one of the most vulnerable and severely afflicted economies in terms of economic inequality. The vast discrepancy between the rich and poor has been prominent since the last ***** decades. The rich continue to grow richer at a faster pace while the impoverished struggle more than ever before to earn a minimum wage. The widening gaps in the economic structure affect women and children the most. This is a call for reinforcement in in the country’s social structure that emphasizes access to quality education and universal healthcare services.

This dataset is one which highlights the demographics of Upper-Middle Class people living in Gachibowli, Hyderabad, India and attempts to, through various methods of statistical analysis, establish a relationship between several of these demographic details.

India Revenue per Passenger Kilometres: Non-Suburban: Upper Class data was reported at 1.356 INR in 2017. This records an increase from the previous number of 1.306 INR for 2016. India Revenue per Passenger Kilometres: Non-Suburban: Upper Class data is updated yearly, averaging 1.064 INR from Mar 2004 (Median) to 2017, with 14 observations. The data reached an all-time high of 1.356 INR in 2017 and a record low of 0.905 INR in 2004. India Revenue per Passenger Kilometres: Non-Suburban: Upper Class data remains active status in CEIC and is reported by Ministry of Railways. The data is categorized under India Premium Database’s Transportation, Post and Telecom Sector – Table IN.TB009: Railway Statistics: Revenue and Expenditure.

India Revenue: Passenger Kilometres: Non-Suburban: Upper Class data was reported at 149,641.800 INR mn in 2017. This records an increase from the previous number of 137,558.600 INR mn for 2016. India Revenue: Passenger Kilometres: Non-Suburban: Upper Class data is updated yearly, averaging 66,253.700 INR mn from Mar 2005 (Median) to 2017, with 13 observations. The data reached an all-time high of 149,641.800 INR mn in 2017 and a record low of 25,206.400 INR mn in 2005. India Revenue: Passenger Kilometres: Non-Suburban: Upper Class data remains active status in CEIC and is reported by Ministry of Railways. The data is categorized under India Premium Database’s Transportation, Post and Telecom Sector – Table IN.TB009: Railway Statistics: Revenue and Expenditure.

In the financial year 2021, the number of super-rich households earning more than ** million Indian rupees went up to **** million from **** million in the financial year 2016. This was an annual growth of **** percent. The number is expected to grow to over **** million in the financial year 2031 and ** million households in the financial year 2047. This will be the fastest growth across all income categories. On the other hand, destitute classified Indian households with earnings of less than *** thousand annually decreased only marginally to ***** million in financial year 2021 from **** million in 2016. However, it is estimated that the number of destitute households will fall to just *** million by the financial year 2047.

India Passenger Traffic: Annual: Passengers Originating: Non-Suburban: Upper Class data was reported at 150.000 Unit mn in 2017. This records an increase from the previous number of 145.000 Unit mn for 2016. India Passenger Traffic: Annual: Passengers Originating: Non-Suburban: Upper Class data is updated yearly, averaging 22.000 Unit mn from Mar 1951 (Median) to 2017, with 49 observations. The data reached an all-time high of 150.000 Unit mn in 2017 and a record low of 6.000 Unit mn in 1977. India Passenger Traffic: Annual: Passengers Originating: Non-Suburban: Upper Class data remains active status in CEIC and is reported by Ministry of Railways. The data is categorized under India Premium Database’s Transportation, Post and Telecom Sector – Table IN.TB002: Railway Statistics: Passenger and Freight Traffic: Annual.

India Passenger Traffic: Annual: Passengers Kilometres: Non-Suburban: Upper Class data was reported at 110,355.000 km mn in 2017. This records an increase from the previous number of 105,315.000 km mn for 2016. India Passenger Traffic: Annual: Passengers Kilometres: Non-Suburban: Upper Class data is updated yearly, averaging 9,751.000 km mn from Mar 1951 (Median) to 2017, with 49 observations. The data reached an all-time high of 110,355.000 km mn in 2017 and a record low of 3,190.000 km mn in 1975. India Passenger Traffic: Annual: Passengers Kilometres: Non-Suburban: Upper Class data remains active status in CEIC and is reported by Ministry of Railways. The data is categorized under India Premium Database’s Transportation, Post and Telecom Sector – Table IN.TB002: Railway Statistics: Passenger and Freight Traffic: Annual.

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.

In the financial year 2021, the average annual saving of rich households in India was over 606 thousand Indian rupees, a stark contrast to destitute category which saved only five thousand Indian rupees. The middle-class saved almost 130 thousand Indian rupees annually. During the year, a rich household spent almost 25 times that of a destitute household, eight times that of an aspirer household, and almost three times that of a middle-class household.

India Passenger Traffic: Annual: Average Lead: Non-Suburban: Upper Class data was reported at 736.300 km in 2017. This records an increase from the previous number of 726.800 km for 2016. India Passenger Traffic: Annual: Average Lead: Non-Suburban: Upper Class data is updated yearly, averaging 570.200 km from Mar 1951 (Median) to 2017, with 49 observations. The data reached an all-time high of 736.300 km in 2017 and a record low of 151.600 km in 1951. India Passenger Traffic: Annual: Average Lead: Non-Suburban: Upper Class data remains active status in CEIC and is reported by Ministry of Railways. The data is categorized under India Premium Database’s Transportation, Post and Telecom Sector – Table IN.TB002: Railway Statistics: Passenger and Freight Traffic: Annual.

By 2030, the middle-class population in Asia-Pacific is expected to increase from 1.38 billion people in 2015 to 3.49 billion people. In comparison, the middle-class population of sub-Saharan Africa is expected to increase from 114 million in 2015 to 212 million in 2030.

Worldwide wealth

While the middle-class has been on the rise, there is still a huge disparity in global wealth and income. The United States had the highest number of individuals belonging to the top one percent of wealth holders, and the value of global wealth is only expected to increase over the coming years. Around 57 percent of the world’s population had assets valued at less than 10,000 U.S. dollars; while less than one percent had assets of more than million U.S. dollars. Asia had the highest percentage of investable assets in the world in 2018, whereas Oceania had the highest percent of non-investable assets.

The middle-class

The middle class is the group of people whose income falls in the middle of the scale. China accounted for over half of the global population for middle-class wealth in 2017. In the United States, the debate about the middle class “disappearing” has been a popular topic due to the increase in wealth to the top billionaires in the nation. Due to this, there have been arguments to increase taxes on the rich to help support the middle-class.

India Proportion of People Living Below 50 Percent Of Median Income: % data was reported at 9.800 % in 2021. This records a decrease from the previous number of 10.000 % for 2020. India Proportion of People Living Below 50 Percent Of Median Income: % data is updated yearly, averaging 6.200 % from Dec 1977 (Median) to 2021, with 14 observations. The data reached an all-time high of 10.300 % in 2019 and a record low of 5.100 % in 2004. India Proportion of People Living Below 50 Percent Of Median Income: % data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s India – Table IN.World Bank.WDI: Social: Poverty and Inequality. The percentage of people in the population who live in households whose per capita income or consumption is below half of the median income or consumption per capita. The median is measured at 2017 Purchasing Power Parity (PPP) using the Poverty and Inequality Platform (http://www.pip.worldbank.org). For some countries, medians are not reported due to grouped and/or confidential data. The reference year is the year in which the underlying household survey data was collected. In cases for which the data collection period bridged two calendar years, the first year in which data were collected is reported.;World Bank, Poverty and Inequality Platform. Data are based on primary household survey data obtained from government statistical agencies and World Bank country departments. Data for high-income economies are mostly from the Luxembourg Income Study database. For more information and methodology, please see http://pip.worldbank.org.;;The World Bank’s internationally comparable poverty monitoring database now draws on income or detailed consumption data from more than 2000 household surveys across 169 countries. See the Poverty and Inequality Platform (PIP) for details (www.pip.worldbank.org).

This dataset contains the gender-wise details of enrolment at different levels of education such as primary, upper primary, elementary, secondary, and higher secondary, irrespective of the type of school.

Note: 1. Data for 2012-13 and 2013-14 is Provisional. 2. Pre-Primary is below Class 1, Primary is from classes 1 to 5, Upper primary from classes 6 to 8, Elementary from classes 1 to 8, secondary from classes 9 to 10, Higher secondary from classes 11 to 12.

India Railway Budget: Receipts: Gross Traffic: Passenger Earnings: Upper Class data was reported at 205,743.000 INR mn in 2020. This records an increase from the previous number of 182,418.100 INR mn for 2019. India Railway Budget: Receipts: Gross Traffic: Passenger Earnings: Upper Class data is updated yearly, averaging 136,151.850 INR mn from Mar 2011 (Median) to 2020, with 10 observations. The data reached an all-time high of 205,743.000 INR mn in 2020 and a record low of 62,256.200 INR mn in 2011. India Railway Budget: Receipts: Gross Traffic: Passenger Earnings: Upper Class data remains active status in CEIC and is reported by Ministry of Railways. The data is categorized under India Premium Database’s Transportation, Post and Telecom Sector – Table IN.TB019: Railway Budget: Overview.

This dataset tracks annual american indian student percentage from 2006 to 2023 for Hot Springs World Class High School vs. Arkansas and Hot Springs School District

Introduction

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

Dataset Content

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

Video Data

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

Metadata

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

Introduction

This Indian English Call Center Speech Dataset for the Travel industry is purpose-built to power the next generation of voice AI applications for travel booking, customer support, and itinerary assistance. With over 30 hours of unscripted, real-world conversations, the dataset enables the development of highly accurate speech recognition and natural language understanding models tailored for English -speaking travelers.

Created by FutureBeeAI, this dataset supports researchers, data scientists, and conversational AI teams in building voice technologies for airlines, travel portals, and hospitality platforms.

Speech Data

The dataset includes 30 hours of dual-channel audio recordings between native Indian English speakers engaged in real travel-related customer service conversations. These audio files reflect a wide variety of topics, accents, and scenarios found across the travel and tourism industry.

Topic Diversity

Inbound and outbound conversations span a wide range of real-world travel support situations with varied outcomes (positive, neutral, negative).

These scenarios help models understand and respond to diverse traveler needs in real-time.

Transcription

Each call is accompanied by manually curated, high-accuracy transcriptions in JSON format.

Metadata

Extensive metadata enriches each call and speaker for better filtering and AI training:

Usage and Applications

This dataset is ideal for a variety of AI use cases in the travel and tourism space:

Based on the results of a survey about WhatsApp users across India in 2018, about ** percent of respondents who belonged to the poor economic class were active users of the messaging app. While this was about ** percent for upper middle class and rich respondents during the survey period.

In the 3 years to March 2021, black households were most likely out of all ethnic groups to have a weekly income of under £600.