49 datasets found
  1. T

    India Population

    • tradingeconomics.com
    • id.tradingeconomics.com
    • +13more
    csv, excel, json, xml
    Updated Oct 10, 2012
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    TRADING ECONOMICS (2012). India Population [Dataset]. https://tradingeconomics.com/india/population
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    json, excel, xml, csvAvailable download formats
    Dataset updated
    Oct 10, 2012
    Dataset authored and provided by
    TRADING ECONOMICS
    License

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

    Time period covered
    Dec 31, 1950 - Dec 31, 2024
    Area covered
    India
    Description

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

  2. Total population of India 2029

    • statista.com
    Updated Nov 18, 2024
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    Statista (2024). Total population of India 2029 [Dataset]. https://www.statista.com/statistics/263766/total-population-of-india/
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    Dataset updated
    Nov 18, 2024
    Dataset authored and provided by
    Statistahttp://statista.com/
    Area covered
    India
    Description

    The statistic shows the total population of India from 2019 to 2029. In 2023, the estimated total population in India amounted to approximately 1.43 billion people.

    Total population in India

    India currently has the second-largest population in the world and is projected to overtake top-ranking China within forty years. Its residents comprise more than one-seventh of the entire world’s population, and despite a slowly decreasing fertility rate (which still exceeds the replacement rate and keeps the median age of the population relatively low), an increasing life expectancy adds to an expanding population. In comparison with other countries whose populations are decreasing, such as Japan, India has a relatively small share of aged population, which indicates the probability of lower death rates and higher retention of the existing population.

    With a land mass of less than half that of the United States and a population almost four times greater, India has recognized potential problems of its growing population. Government attempts to implement family planning programs have achieved varying degrees of success. Initiatives such as sterilization programs in the 1970s have been blamed for creating general antipathy to family planning, but the combined efforts of various family planning and contraception programs have helped halve fertility rates since the 1960s. The population growth rate has correspondingly shrunk as well, but has not yet reached less than one percent growth per year.

    As home to thousands of ethnic groups, hundreds of languages, and numerous religions, a cohesive and broadly-supported effort to reduce population growth is difficult to create. Despite that, India is one country to watch in coming years. It is also a growing economic power; among other measures, its GDP per capita was expected to triple between 2003 and 2013 and was listed as the third-ranked country for its share of the global gross domestic product.

  3. World Population Statistics - 2023

    • kaggle.com
    Updated Jan 9, 2024
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    Bhavik Jikadara (2024). World Population Statistics - 2023 [Dataset]. https://www.kaggle.com/datasets/bhavikjikadara/world-population-statistics-2023
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    CroissantCroissant is a format for machine-learning datasets. Learn more about this at mlcommons.org/croissant.
    Dataset updated
    Jan 9, 2024
    Dataset provided by
    Kagglehttp://kaggle.com/
    Authors
    Bhavik Jikadara
    License

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

    Area covered
    World
    Description
    • The current US Census Bureau world population estimate in June 2019 shows that the current global population is 7,577,130,400 people on Earth, which far exceeds the world population of 7.2 billion in 2015. Our estimate based on UN data shows the world's population surpassing 7.7 billion.
    • China is the most populous country in the world with a population exceeding 1.4 billion. It is one of just two countries with a population of more than 1 billion, with India being the second. As of 2018, India has a population of over 1.355 billion people, and its population growth is expected to continue through at least 2050. By the year 2030, India is expected to become the most populous country in the world. This is because India’s population will grow, while China is projected to see a loss in population.
    • The following 11 countries that are the most populous in the world each have populations exceeding 100 million. These include the United States, Indonesia, Brazil, Pakistan, Nigeria, Bangladesh, Russia, Mexico, Japan, Ethiopia, and the Philippines. Of these nations, all are expected to continue to grow except Russia and Japan, which will see their populations drop by 2030 before falling again significantly by 2050.
    • Many other nations have populations of at least one million, while there are also countries that have just thousands. The smallest population in the world can be found in Vatican City, where only 801 people reside.
    • In 2018, the world’s population growth rate was 1.12%. Every five years since the 1970s, the population growth rate has continued to fall. The world’s population is expected to continue to grow larger but at a much slower pace. By 2030, the population will exceed 8 billion. In 2040, this number will grow to more than 9 billion. In 2055, the number will rise to over 10 billion, and another billion people won’t be added until near the end of the century. The current annual population growth estimates from the United Nations are in the millions - estimating that over 80 million new lives are added yearly.
    • This population growth will be significantly impacted by nine specific countries which are situated to contribute to the population growth more quickly than other nations. These nations include the Democratic Republic of the Congo, Ethiopia, India, Indonesia, Nigeria, Pakistan, Uganda, the United Republic of Tanzania, and the United States of America. Particularly of interest, India is on track to overtake China's position as the most populous country by 2030. Additionally, multiple nations within Africa are expected to double their populations before fertility rates begin to slow entirely.

    Content

    • In this Dataset, we have Historical Population data for every Country/Territory in the world by different parameters like Area Size of the Country/Territory, Name of the Continent, Name of the Capital, Density, Population Growth Rate, Ranking based on Population, World Population Percentage, etc. >Dataset Glossary (Column-Wise):
    • Rank: Rank by Population.
    • CCA3: 3 Digit Country/Territories Code.
    • Country/Territories: Name of the Country/Territories.
    • Capital: Name of the Capital.
    • Continent: Name of the Continent.
    • 2022 Population: Population of the Country/Territories in the year 2022.
    • 2020 Population: Population of the Country/Territories in the year 2020.
    • 2015 Population: Population of the Country/Territories in the year 2015.
    • 2010 Population: Population of the Country/Territories in the year 2010.
    • 2000 Population: Population of the Country/Territories in the year 2000.
    • 1990 Population: Population of the Country/Territories in the year 1990.
    • 1980 Population: Population of the Country/Territories in the year 1980.
    • 1970 Population: Population of the Country/Territories in the year 1970.
    • Area (km²): Area size of the Country/Territories in square kilometers.
    • Density (per km²): Population Density per square kilometer.
    • Growth Rate: Population Growth Rate by Country/Territories.
    • World Population Percentage: The population percentage by each Country/Territories.
  4. Worldwide digital population 2025

    • statista.com
    • ai-chatbox.pro
    Updated Apr 1, 2025
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    Statista (2025). Worldwide digital population 2025 [Dataset]. https://www.statista.com/statistics/617136/digital-population-worldwide/
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    Dataset updated
    Apr 1, 2025
    Dataset authored and provided by
    Statistahttp://statista.com/
    Time period covered
    Feb 2025
    Area covered
    World
    Description

    As of February 2025, 5.56 billion individuals worldwide were internet users, which amounted to 67.9 percent of the global population. Of this total, 5.24 billion, or 63.9 percent of the world's population, were social media users. Global internet usage Connecting billions of people worldwide, the internet is a core pillar of the modern information society. Northern Europe ranked first among worldwide regions by the share of the population using the internet in 20254. In The Netherlands, Norway and Saudi Arabia, 99 percent of the population used the internet as of February 2025. North Korea was at the opposite end of the spectrum, with virtually no internet usage penetration among the general population, ranking last worldwide. Eastern Asia was home to the largest number of online users worldwide – over 1.34 billion at the latest count. Southern Asia ranked second, with around 1.2 billion internet users. China, India, and the United States rank ahead of other countries worldwide by the number of internet users. Worldwide internet user demographics As of 2024, the share of female internet users worldwide was 65 percent, five percent less than that of men. Gender disparity in internet usage was bigger in African countries, with around a ten percent difference. Worldwide regions, like the Commonwealth of Independent States and Europe, showed a smaller usage gap between these two genders. As of 2024, global internet usage was higher among individuals between 15 and 24 years old across all regions, with young people in Europe representing the most significant usage penetration, 98 percent. In comparison, the worldwide average for the age group 15–24 years was 79 percent. The income level of the countries was also an essential factor for internet access, as 93 percent of the population of the countries with high income reportedly used the internet, as opposed to only 27 percent of the low-income markets.

  5. Distribution of the global population by continent 2024

    • statista.com
    • ai-chatbox.pro
    Updated Mar 27, 2025
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    Statista (2025). Distribution of the global population by continent 2024 [Dataset]. https://www.statista.com/statistics/237584/distribution-of-the-world-population-by-continent/
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    Dataset updated
    Mar 27, 2025
    Dataset authored and provided by
    Statistahttp://statista.com/
    Area covered
    World
    Description

    In the middle of 2023, about 60 percent of the global population was living in Asia.The total world population amounted to 8.1 billion people on the planet. In other words 4.7 billion people were living in Asia as of 2023. Global populationDue to medical advances, better living conditions and the increase of agricultural productivity, the world population increased rapidly over the past century, and is expected to continue to grow. After reaching eight billion in 2023, the global population is estimated to pass 10 billion by 2060. Africa expected to drive population increase Most of the future population increase is expected to happen in Africa. The countries with the highest population growth rate in 2024 were mostly African countries. While around 1.47 billion people live on the continent as of 2024, this is forecast to grow to 3.9 billion by 2100. This is underlined by the fact that most of the countries wit the highest population growth rate are found in Africa. The growing population, in combination with climate change, puts increasing pressure on the world's resources.

  6. Population of India 1800-2020

    • statista.com
    Updated Aug 9, 2024
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    Statista (2024). Population of India 1800-2020 [Dataset]. https://www.statista.com/statistics/1066922/population-india-historical/
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    Dataset updated
    Aug 9, 2024
    Dataset authored and provided by
    Statistahttp://statista.com/
    Area covered
    India
    Description

    In 1800, the population of the region of present-day India was approximately 169 million. The population would grow gradually throughout the 19th century, rising to over 240 million by 1900. Population growth would begin to increase in the 1920s, as a result of falling mortality rates, due to improvements in health, sanitation and infrastructure. However, the population of India would see it’s largest rate of growth in the years following the country’s independence from the British Empire in 1948, where the population would rise from 358 million to over one billion by the turn of the century, making India the second country to pass the billion person milestone. While the rate of growth has slowed somewhat as India begins a demographics shift, the country’s population has continued to grow dramatically throughout the 21st century, and in 2020, India is estimated to have a population of just under 1.4 billion, well over a billion more people than one century previously. Today, approximately 18% of the Earth’s population lives in India, and it is estimated that India will overtake China to become the most populous country in the world within the next five years.

  7. d

    Premium GIS Data | Asia/ MENA | Latest Estimates on Population, Consuming...

    • datarade.ai
    .json, .csv
    Updated Nov 23, 2024
    + more versions
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    GapMaps (2024). Premium GIS Data | Asia/ MENA | Latest Estimates on Population, Consuming Class, Retail Spend, Demographics | Map Data | Demographic Data [Dataset]. https://datarade.ai/data-products/gapmaps-premium-demographics-gis-data-asia-mena-150m-x-1-gapmaps
    Explore at:
    .json, .csvAvailable download formats
    Dataset updated
    Nov 23, 2024
    Dataset authored and provided by
    GapMaps
    Area covered
    Philippines, Malaysia, Indonesia, India, Singapore, Saudi Arabia, Asia
    Description

    Sourcing accurate and up-to-date demographics GIS data across Asia and MENA has historically been difficult for retail brands looking to expand their store networks in these regions. Either the data does not exist or it isn't readily accessible or updated regularly.

    GapMaps uses known population data combined with billions of mobile device location points to provide highly accurate and globally consistent geodemographic datasets across Asia and MENA at 150m x 150m grid levels in major cities and 1km grids outside of major cities.

    With this information, brands can get a detailed understanding of who lives in a catchment, where they work and their spending potential which allows you to:

    • Better understand your customers
    • Identify optimal locations to expand your retail footprint
    • Define sales territories for franchisees
    • Run targeted marketing campaigns.

    Premium demographics GIS data for Asia and MENA includes the latest estimates (updated annually) on:

    1. Population (how many people live in your local catchment)
    2. Demographics (who lives within your local catchment)
    3. Worker population (how many people work within your local catchment)
    4. Consuming Class and Premium Consuming Class (who can can afford to buy goods & services beyond their basic needs and /or shop at premium retailers)
    5. Retail Spending (Food & Beverage, Grocery, Apparel, Other). How much are consumers spending on retail goods and services by category.

    Primary Use Cases for GapMaps Demographics GIS Data:

    1. Retail (eg. Fast Food/ QSR, Cafe, Fitness, Supermarket/Grocery)
    2. Customer Profiling: get a detailed understanding of the demographic profile of your customers, where they work and their spending potential
    3. Analyse your trade areas at a granular 150m x 150m grid levels using all the key metrics
    4. Site Selection: Identify optimal locations for future expansion and benchmark performance across existing locations.
    5. Target Marketing: Develop effective marketing strategies to acquire more customers.
    6. Integrate GapMaps demographic data with your existing GIS or BI platform to generate powerful visualizations.

    7. Commercial Real-Estate (Brokers, Developers, Investors, Single & Multi-tenant O/O)

    8. Tenant Recruitment

    9. Target Marketing

    10. Market Potential / Gap Analysis

    11. Marketing / Advertising (Billboards/OOH, Marketing Agencies, Indoor Screens)

    12. Customer Profiling

    13. Target Marketing

    14. Market Share Analysis

  8. g

    Store Location Data | Asia/ MENA | Latest Estimates on Population,...

    • datastore.gapmaps.com
    Updated Nov 20, 2024
    + more versions
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    GapMaps (2024). Store Location Data | Asia/ MENA | Latest Estimates on Population, Demographics, Consuming Class, Retail Spend | GIS Data | Demographic Data [Dataset]. https://datastore.gapmaps.com/products/gapmaps-premium-store-location-data-asia-mena-demographics-gapmaps
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    Dataset updated
    Nov 20, 2024
    Dataset authored and provided by
    GapMaps
    Area covered
    Indonesia, Philippines, Singapore, Saudi Arabia, Malaysia, India, Asia
    Description

    GapMaps Store Location Data uses known population data combined with billions of mobile device location points to provide highly accurate demographics insights at 150m grid levels across Asia and MENA. Understand who lives in a catchment, where they work and their spending potential.

  9. f

    Data_Sheet_1_Projecting wheat demand in China and India for 2030 and 2050:...

    • frontiersin.figshare.com
    docx
    Updated Jun 21, 2023
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    Khondoker Abdul Mottaleb; Gideon Kruseman; Aymen Frija; Kai Sonder; Santiago Lopez-Ridaura (2023). Data_Sheet_1_Projecting wheat demand in China and India for 2030 and 2050: Implications for food security.docx [Dataset]. http://doi.org/10.3389/fnut.2022.1077443.s001
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    docxAvailable download formats
    Dataset updated
    Jun 21, 2023
    Dataset provided by
    Frontiers
    Authors
    Khondoker Abdul Mottaleb; Gideon Kruseman; Aymen Frija; Kai Sonder; Santiago Lopez-Ridaura
    License

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

    Area covered
    China, India
    Description

    IntroductionThe combined populations of China and India were 2.78 billion in 2020, representing 36% of the world population (7.75 billion). Wheat is the second most important staple grain in both China and India. In 2019, the aggregate wheat consumption in China was 96.4 million ton and in India it was 82.5 million ton, together it was more than 35% of the world's wheat that year. In China, in 2050, the projected population will be 1294–1515 million, and in India, it is projected to be 14.89–1793 million, under the low and high-fertility rate assumptions. A question arises as to, what will be aggregate demand for wheat in China and India in 2030 and 2050?MethodsApplying the Vector Error Correction model estimation process in the time series econometric estimation setting, this study projected the per capita and annual aggregate wheat consumptions of China and India during 2019-2050. In the process, this study relies on agricultural data sourced from the Food and Agriculture Organization of the United States (FAO) database (FAOSTAT), as well as the World Bank's World Development Indicators (WDI) data catalog. The presence of unit root in the data series are tested by applying the augmented Dickey-Fuller test; Philips-Perron unit root test; Kwiatkowski-Phillips-Schmidt-Shin test, and Zivot-Andrews Unit Root test allowing for a single break in intercept and/or trend. The test statistics suggest that a natural log transformation and with the first difference of the variables provides stationarity of the data series for both China and India. The Zivot-Andrews Unit Root test, however, suggested that there is a structural break in urban population share and GDP per capita. To tackle the issue, we have included a year dummy and two multiplicative dummies in our model. Furthermore, the Johansen cointegration test suggests that at least one variable in both data series were cointegrated. These tests enable us to apply Vector Error Correction (VEC) model estimation procedure. In estimation the model, the appropriate number of lags of the variables is confirmed by applying the “varsoc” command in Stata 17 software interface. The estimated yearly per capita wheat consumption in 2030 and 2050 from the VEC model, are multiplied by the projected population in 2030 and 2050 to calculate the projected aggregate wheat demand in China and India in 2030 and 2050. After projecting the yearly per capita wheat consumption (KG), we multiply with the projected population to get the expected consumption demand.ResultsThis study found that the yearly per capita wheat consumption of China will increase from 65.8 kg in 2019 to 76 kg in 2030, and 95 kg in 2050. In India, the yearly per capita wheat consumption will increase to 74 kg in 2030 and 94 kg in 2050 from 60.4 kg in 2019. Considering the projected population growth rates under low-fertility assumptions, aggregate wheat consumption of China will increase by more than 13% in 2030 and by 28% in 2050. Under the high-fertility rate assumption, however the aggregate wheat consumption of China will increase by 18% in 2030 and nearly 50% in 2050. In the case of India, under both low and high-fertility rate assumptions, aggregate wheat demand in India will increase by 32-38% in 2030 and by 70-104% in 2050 compared to 2019 level of consumption.DiscussionsOur results underline the importance of wheat in both countries, which are the world's top wheat producers and consumers, and suggest the importance of research and development investments to maintain sufficient national wheat grain production levels to meet China and India's domestic demand. This is critical both to ensure the food security of this large segment of the world populace, which also includes 23% of the total population of the world who live on less than US $1.90/day, as well as to avoid potential grain market destabilization and price hikes that arise in the event of large import demands.

  10. n

    Data from: Estimation of non-health Gross Domestic Product (NHGDP) loss due...

    • data.niaid.nih.gov
    • datadryad.org
    zip
    Updated Oct 2, 2023
    + more versions
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    Paramita Bhattacharya; Denny John; Nirmalya Mukherjee; M. S. Narassima; Jaideep Menon; Amitava Banerjee (2023). Estimation of non-health Gross Domestic Product (NHGDP) loss due to COVID-19 deaths in West Bengal, India [Dataset]. http://doi.org/10.5061/dryad.573n5tbc4
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    zipAvailable download formats
    Dataset updated
    Oct 2, 2023
    Dataset provided by
    Manbhum Ananda Ashram Nityananda Trust
    University College London
    Great Lakes Institute of Management
    Manbhum Ananda Asharan Nityananda Trust
    Amrita Institute of Medical Sciences and Research Centre
    Authors
    Paramita Bhattacharya; Denny John; Nirmalya Mukherjee; M. S. Narassima; Jaideep Menon; Amitava Banerjee
    License

    https://spdx.org/licenses/CC0-1.0.htmlhttps://spdx.org/licenses/CC0-1.0.html

    Area covered
    West Bengal, India
    Description

    This study estimates the economic losses (GDP), particularly the impact of COVID-19 deaths on non-health components of GDP in West Bengal state. The NHGDP losses were evaluated using cost-of-illness approach. Future NHGDP losses were discounted at 3%. Excess death estimates by the World Health Organisation (WHO) and Global Burden of Disease (GBD) were used. Sensitivity analysis was carried out by varying discount rates and Average Age of Death (AAD). 21,532 deaths in West Bengal since 17th March 2020 till 31st December 2022 decreased the future NHGDP by $0.92 billion. Nearly 90% of loss was due to deaths occurring in above 30 years age-group. The majority of the loss was borne among the 46–60 years age-group. The NHGDP loss/death was $42,646, however, the average loss/death declined with a rise in age. The loss increased to $9.38 billion and $9.42 billion respectively based on GBD and WHO excess death estimates. The loss increased to $1.3 billion by considering the lower age of the interval as AAD. At 5% and 10% discount rates, the losses reduced to $0.769 billion and $0.549 billion respectively. Results from the study suggest that COVID-19 contributed to major economic loss in West Bengal. The mortality and morbidity caused by COVID-19, the substantial economic costs at individual and population levels in West Bengal, and probably across India and other countries, is another argument for better infection control strategies across the globe to end the impact of this epidemic. Methods Various open domains were used to gather data on COVID-19 deaths in West Bengal and the aforementioned estimates. Economic losses in terms of Non-Health Gross Domestic Product (NHGDP)among six age-group brackets viz. 0–15, 16–30, 31–45, 46–60, 61–75 and 75 and above were estimated to facilitate comparisons and to initiate advocacy for an increase in health investments against COVID-19. This study used midpoint age as the age of death for all the age brackets. The legal minimum age for working i.e., 15 years. A sensitivity analysis was conducted to determine the effect of age on the overall total NHGDP loss estimate. The model was re-estimated assuming an average age at death to be the starting age of each age-group bracket. Based on existing literature discounted rate of interest to measure the value of life is taken as 2.9%. As a sensitivity analysis, NHGDP loss has also been computed using 5% and 10% of discounted rates of interest.

  11. Internet penetration rate in India 2014-2025

    • statista.com
    • ai-chatbox.pro
    Updated Jul 14, 2025
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    Statista (2025). Internet penetration rate in India 2014-2025 [Dataset]. https://www.statista.com/statistics/792074/india-internet-penetration-rate/
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    Dataset updated
    Jul 14, 2025
    Dataset authored and provided by
    Statistahttp://statista.com/
    Area covered
    India
    Description

    The internet penetration rate in India rose over 55 percent in 2025, from about 14 percent in 2014. Although these figures seem relatively low, it meant that more than half of the population of 1.4 billion people had internet access that year. This also ranked the country second in the world in terms of active internet users. Internet availability and accessibility By 2021, the number of internet connections across the country tripled with urban areas accounting for a higher density of connections than rural regions. Despite incredibly low internet prices, internet usage in India has yet to reach its full potential. Lack of awareness and a tangible gender gap lie at the heart of the matter, with affordable mobile handsets and mobile internet connections presenting only a partial solution. Reliance Jio was the popular choice among Indian internet subscribers, offering them wider coverage at cheap rates. Digital living Home to one of the largest bases of netizens in the world, India is abuzz with internet activities being carried out every moment of every day. From information and research to shopping and entertainment to living in smart homes, Indians have welcomed digital living with open arms. Among these, social media usage was one of the most common reasons for accessing the internet.

  12. COVID-19-Related Shocks in Rural India 2020, Rounds 1-3 - India

    • datacatalog.ihsn.org
    • catalog.ihsn.org
    • +1more
    Updated Mar 22, 2021
    + more versions
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    World Bank (2021). COVID-19-Related Shocks in Rural India 2020, Rounds 1-3 - India [Dataset]. https://datacatalog.ihsn.org/catalog/9553
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    Dataset updated
    Mar 22, 2021
    Dataset authored and provided by
    World Bankhttps://www.worldbank.org/
    Time period covered
    2020
    Area covered
    India
    Description

    Abstract

    An effective policy response to the economic impacts of the COVID-19 pandemic requires an enormous range of data to inform the design and response of programs. Public health measures require data on the spread of the disease, beliefs in the population, and capacity of the health system. Relief efforts depend on an understanding of hardships being faced by various segments of the population. Food policy requires measurement of agricultural production and hunger. In such a rapidly evolving pandemic, these data must be collected at a high frequency. Given the unexpected nature of the shock and urgency with which a response was required, Indian policymakers needed to formulate policies affecting India’s 1.4 billion people, without the detailed evidence required to construct effective programs. To help overcome this evidence gap, the World Bank, IDinsight, and the Development Data Lab sought to produce rigorous and responsive data for policymakers across six states in India: Jharkhand, Rajasthan, Uttar Pradesh, Andhra Pradesh, Bihar, and Madhya Pradesh.

    Geographic coverage

    Andhra Pradesh, Bihar, Jharkhand, Madhya Pradesh, Rajasthan, and Uttar Pradesh

    Analysis unit

    Household

    Kind of data

    Sample survey data [ssd]

    Sampling procedure

    This dataset includes observations covering six states (Andhra Pradesh, Bihar, Jharkhand, Madhya Pradesh, Rajasthan, Uttar Pradesh) and three survey rounds. The survey did not have a single, unified frame from which to sample phone numbers. The final sample was assembled from several different sample frames, and the choice of frame sample frames varied across states and survey rounds.

    These frames comprise four prior IDinsight projects and from an impact evaluation of the National Rural Livelihoods project conducted by the Ministry of Rural Development. Each of these surveys sought to represent distinct populations, and employed idiosyncratic sample designs and weighting schemes.

    A detailed note covering key features of each sample frame is available for download.

    Mode of data collection

    Computer Assisted Telephone Interview [cati]

    Research instrument

    The survey questionnaires covered the following subjects:

    1. Agriculture: COVID-19-related changes in price realisation, acreage decisions, input expenditure, access to credit, access to fertilisers, etc.

    2. Income and consumption: Changes in wage rates, employment duration, consumption expenditure, prices of essential commodities, status of food security etc.

    3. Migration: Rates of in-migration, migrant income and employment status, return migration plans etc.

    4. Access to relief: Access to in-kind, cash and workfare relief, quantities of relief received, and constraints on the access to relief.

    5. Health: Access to health facilities and rates of foregone healthcare, knowledge of COVID-19 related symptoms and protective behaviours.

    While a number of indicators were consistent across all three rounds, questions were added and removed as and when necessary to account for seasonal changes (i.e: in the agricultural cycle).

    Response rate

    Round 1: ~55% Round 2: ~46% Round 3: ~55%

  13. d

    Map Data | Asia & MENA | Premium Demographics & Point-of-Interest Data To...

    • datarade.ai
    .json, .csv
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    GapMaps, Map Data | Asia & MENA | Premium Demographics & Point-of-Interest Data To Optimise Business Decisions | GIS Data | Demographic Data [Dataset]. https://datarade.ai/data-products/gapmaps-global-map-data-asia-mena-150m-x-150m-grids-cu-gapmaps
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    .json, .csvAvailable download formats
    Dataset authored and provided by
    GapMaps
    Area covered
    Malaysia, India, Philippines, Saudi Arabia, Indonesia, Singapore, Asia
    Description

    Sourcing accurate and up-to-date map data across Asia and MENA has historically been difficult for retail brands looking to expand their store networks in these regions. Either the data does not exist or it isn't readily accessible or updated regularly.

    GapMaps Map Data uses known population data combined with billions of mobile device location points to provide highly accurate and globally consistent demographics data across Asia and MENA at 150m x 150m grid levels in major cities and 1km grids outside of major cities.

    GapMaps Map Data also includes the latest Point-of-Interest (POI) Data for leading retail brands across a range of categories including Fast Food/ QSR, Health & Fitness, Supermarket/Grocery and Cafe sectors which is updated monthly.

    With this information, brands can get a detailed understanding of who lives in a catchment, where they work and their spending potential which allows you to:

    • Better understand your customers
    • Identify optimal locations to expand your retail footprint
    • Define sales territories for franchisees
    • Run targeted marketing campaigns.

    GapMaps Map Data for Asia and MENA can be utilized in any GIS platform and includes the latest estimates (updated annually) on:

    1. Population (how many people live in your local catchment)
    2. Demographics (who lives within your local catchment)
    3. Worker population (how many people work within your local catchment)
    4. Consuming Class and Premium Consuming Class (who can can afford to buy goods & services beyond their basic needs and /or shop at premium retailers)
    5. Retail Spending (Food & Beverage, Grocery, Apparel, Other). How much are consumers spending on retail goods and services by category.

    Primary Use Cases for GapMaps Map Data:

    1. Retail Site Selection - identify optimal locations for future expansion and benchmark performance across existing locations.
    2. Customer Profiling: get a detailed understanding of the demographic profile of your customers, where they work and their spending potential
    3. Analyse your trade areas at a granular 150m x 150m grid levels using all the key metrics
    4. Target Marketing: Develop effective marketing strategies to acquire more customers.
    5. Integrate GapMaps demographic data with your existing GIS or BI platform to generate powerful visualizations.
    6. Marketing / Advertising (Billboards/OOH, Marketing Agencies, Indoor Screens)
    7. Customer Profiling
    8. Target Marketing
    9. Market Share Analysis
  14. Distribution of projected population growth India 2011-2036 by state

    • statista.com
    Updated Jul 9, 2025
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    Statista (2025). Distribution of projected population growth India 2011-2036 by state [Dataset]. https://www.statista.com/statistics/1155340/india-distribution-of-projected-population-growth-by-state/
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    Dataset updated
    Jul 9, 2025
    Dataset authored and provided by
    Statistahttp://statista.com/
    Area covered
    India
    Description

    The share of projected population increase in Uttar Pradesh, India from 2011 until 2036 is expected to grow by nearly ** percent. By contrast, the estimated population increase in Uttarakhand is expected to be less than *** percent during the same time period.

    Why project population?
    Population projections for a country are becoming increasingly important now than ever before. They are used primarily by government policy makers and planners to better understand and gauge future demand for basic services that predominantly include water, food and energy. In addition, they also support in indicating major movements that may affect economic development and in turn, employment and labour productivity. Consequently, this leads to amending policies in order to better adapt to the needs of society and to various circumstances.

    Demographic projections and health interventions Demographic figures serve the foremost purpose of improving health and health related services among the population. Some of the government interventions include antenatal and neonatal care with the aim of reducing maternal and neonatal mortality and morbidity rates. In addition, it also focuses on improving immunization coverage across the country. Further, demographic estimates help in better preempting the needs of growing populations, such as the geriatric population within a country.

  15. a

    Global Cities

    • hub.arcgis.com
    Updated May 10, 2023
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    MapMaker (2023). Global Cities [Dataset]. https://hub.arcgis.com/maps/aa8135223a0e401bb46e11881d6df489
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    Dataset updated
    May 10, 2023
    Dataset authored and provided by
    MapMaker
    License

    Attribution 3.0 (CC BY 3.0)https://creativecommons.org/licenses/by/3.0/
    License information was derived automatically

    Area covered
    Description

    It is estimated that more than 8 billion people live on Earth and the population is likely to hit more than 9 billion by 2050. Approximately 55 percent of Earth’s human population currently live in areas classified as urban. That number is expected to grow by 2050 to 68 percent, according to the United Nations (UN).The largest cities in the world include Tōkyō, Japan; New Delhi, India; Shanghai, China; México City, Mexico; and São Paulo, Brazil. Each of these cities classifies as a megacity, a city with more than 10 million people. The UN estimates the world will have 43 megacities by 2030.Most cities' populations are growing as people move in for greater economic, educational, and healthcare opportunities. But not all cities are expanding. Those cities whose populations are declining may be experiencing declining fertility rates (the number of births is lower than the number of deaths), shrinking economies, emigration, or have experienced a natural disaster that resulted in fatalities or forced people to leave the region.This Global Cities map layer contains data published in 2018 by the Population Division of the United Nations Department of Economic and Social Affairs (UN DESA). It shows urban agglomerations. The UN DESA defines an urban agglomeration as a continuous area where population is classified at urban levels (by the country in which the city resides) regardless of what local government systems manage the area. Since not all places record data the same way, some populations may be calculated using the city population as defined by its boundary and the metropolitan area. If a reliable estimate for the urban agglomeration was unable to be determined, the population of the city or metropolitan area is used.Data Citation: United Nations Department of Economic and Social Affairs. World Urbanization Prospects: The 2018 Revision. Statistical Papers - United Nations (ser. A), Population and Vital Statistics Report, 2019, https://doi.org/10.18356/b9e995fe-en.

  16. Population Health Management Market Analysis, Size, and Forecast 2025-2029:...

    • technavio.com
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    Technavio, Population Health Management Market Analysis, Size, and Forecast 2025-2029: North America (US and Canada), Europe (France, Germany, Italy, UK), Asia (China, India, Japan, South Korea), and Rest of World (ROW) [Dataset]. https://www.technavio.com/report/population-health-management-market-industry-analysis
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    Dataset provided by
    TechNavio
    Authors
    Technavio
    Time period covered
    2021 - 2025
    Area covered
    Global
    Description

    Snapshot img

    Population Health Management Market Size and Forecast 2025-2029

    The population health management market size estimates the market to reach by USD 19.40 billion, at a CAGR of 10.7% between 2024 and 2029. North America is expected to account for 68% of the growth contribution to the global market during this period. In 2019 the software segment was valued at USD 16.04 billion and has demonstrated steady growth since then.

        Report Coverage
    
    
        Details
    
    
    
    
        Base year
    
    
        2024
    
    
    
    
        Historic period
    
        2019-2023
    
    
    
        Forecast period
    
    
        2025-2029
    
    
    
        Market structure
        Fragmented
    
    
    
        Market growth 2025-2029
    
    
        USD 19.40 billion
    
    
    
    
    
    
    The market is experiencing significant growth, driven by the increasing adoption of healthcare IT and the rising focus on personalized medicine. Healthcare providers are recognizing the value of population health management platforms in improving patient outcomes and reducing costs. The implementation of these systems enables proactive care management, disease prevention, and population health analysis. However, the market faces challenges as well. The cost of installing population health management platforms can be a significant barrier for smaller healthcare organizations. Additionally, ensuring data security and interoperability across various systems remains a major concern.
    Effective data management and integration are essential for population health management to deliver its full potential. Companies seeking to capitalize on market opportunities must address these challenges and provide cost-effective, secure, and interoperable solutions. By focusing on these areas, they can help healthcare providers optimize their population health management initiatives and improve patient care.
    

    What will be the Size of the Population Health Management Market during the forecast period?

    Explore in-depth regional segment analysis with market size data - historical 2019-2023 and forecasts 2025-2029 - in the full report.
    Request Free Sample

    The market continues to evolve, driven by advancements in technology and a growing focus on value-based care. Risk adjustment models, which help account for the variability in health risks among patient populations, are increasingly being adopted to improve care coordination and health outcome measures. For instance, a leading healthcare organization implemented risk stratification models, resulting in a 20% reduction in hospital readmissions. Remote patient monitoring, public health surveillance, and disease outbreak response are crucial applications of population health management. These technologies enable real-time health data collection, allowing for early intervention and improved health equity initiatives. Chronic disease management, a significant focus area, benefits from electronic health records, care coordination models, and health information exchange.

    Value-based care programs, predictive modeling healthcare, and telehealth platforms are transforming the landscape of healthcare delivery. Healthcare data analytics, interoperability standards, and population health dashboards facilitate data-driven decision-making, enhancing health intervention efficacy. Behavioral health integration and preventive health services are gaining prominence, with health literacy programs and clinical decision support tools supporting personalized medicine strategies. The market is expected to grow at a robust rate, with industry growth estimates reaching 15% annually. This growth is fueled by the ongoing need for healthcare cost reduction, quality improvement initiatives, and the integration of technology into healthcare delivery.

    How is this Population Health Management Industry segmented?

    The population health management industry research report provides comprehensive data (region-wise segment analysis), with forecasts and estimates in 'USD billion' for the period 2025-2029, as well as historical data from 2019-2023 for the following segments.

    Component
    
      Software
      Services
    
    
    End-user
    
      Large enterprises
      SMEs
    
    
    Delivery Mode
    
      On-Premise
      Cloud-Based
      Web-Based
    
    
    End-Use
    
      Providers
      Payers
      Employer Groups
      Government Bodies
    
    
    Geography
    
      North America
    
        US
        Canada
    
    
      Europe
    
        France
        Germany
        Italy
        UK
    
    
      APAC
    
        China
        India
        Japan
        South Korea
    
    
      Rest of World (ROW)
    

    By Component Insights

    The software segment is estimated to witness significant growth during the forecast period.

    The market's software segment is experiencing significant growth and innovation, driven by various components that enhance healthcare organizations' capacity to manage and enhance the health outcomes of diverse populations. Population health management platforms aggregate and integrate data from multiple sources, includin

  17. World population by age and region 2024

    • statista.com
    • ai-chatbox.pro
    Updated Mar 11, 2025
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    Statista (2025). World population by age and region 2024 [Dataset]. https://www.statista.com/statistics/265759/world-population-by-age-and-region/
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    Dataset updated
    Mar 11, 2025
    Dataset authored and provided by
    Statistahttp://statista.com/
    Area covered
    World
    Description

    Globally, about 25 percent of the population is under 15 years of age and 10 percent is over 65 years of age. Africa has the youngest population worldwide. In Sub-Saharan Africa, more than 40 percent of the population is below 15 years, and only three percent are above 65, indicating the low life expectancy in several of the countries. In Europe, on the other hand, a higher share of the population is above 65 years than the population under 15 years. Fertility rates The high share of children and youth in Africa is connected to the high fertility rates on the continent. For instance, South Sudan and Niger have the highest population growth rates globally. However, about 50 percent of the world’s population live in countries with low fertility, where women have less than 2.1 children. Some countries in Europe, like Latvia and Lithuania, have experienced a population decline of one percent, and in the Cook Islands, it is even above two percent. In Europe, the majority of the population was previously working-aged adults with few dependents, but this trend is expected to reverse soon, and it is predicted that by 2050, the older population will outnumber the young in many developed countries. Growing global population As of 2025, there are 8.1 billion people living on the planet, and this is expected to reach more than nine billion before 2040. Moreover, the global population is expected to reach 10 billions around 2060, before slowing and then even falling slightly by 2100. As the population growth rates indicate, a significant share of the population increase will happen in Africa.

  18. India Total Loans

    • ceicdata.com
    Updated Mar 26, 2025
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    CEICdata.com (2025). India Total Loans [Dataset]. https://www.ceicdata.com/en/indicator/india/total-loans
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    Dataset updated
    Mar 26, 2025
    Dataset provided by
    CEIC Data
    License

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

    Time period covered
    Mar 1, 2022 - Dec 1, 2024
    Area covered
    India
    Description

    Key information about India Total Loans

    • India Total Loans was reported at 2,048.209 USD bn in Dec 2024
    • This records an increase from the previous number of 2,037.410 USD bn for Sep 2024
    • India Total Loans data is updated quarterly, averaging 898.708 USD bn from Dec 1998 to Dec 2024, with 105 observations
    • The data reached an all-time high of 2,048.209 USD bn in Dec 2024 and a record low of 82.701 USD bn in Dec 1998
    • India Total Loans data remains active status in CEIC and is reported by CEIC Data
    • The data is categorized under World Trend Plus’s Global Economic Monitor – Table: Total Loans: USD: Quarterly

    CEIC converts quarterly Total Loans into USD. The Reserve Bank of India provides Total Loans in local currency. The Federal Reserve Board period end market exchange rate is used for currency conversions. Total Loans cover lenders as Scheduled Commercial Banks.

  19. W

    India Night Lights

    • cloud.csiss.gmu.edu
    Updated Feb 3, 2017
    + more versions
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    default (2017). India Night Lights [Dataset]. https://cloud.csiss.gmu.edu/uddi/dataset/india-night-lights
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    Dataset updated
    Feb 3, 2017
    Dataset provided by
    default
    Area covered
    India
    Description

    The India Lights platform shows light output at night for 20 years for 600,000 villages across India. The Defense Meteorological Satellite Program (DMSP) has taken pictures of the Earth every night from 1993 to 2013. Researchers at the University of Michigan, in collaboration with the World Bank, used the DMSP images to extract the data you see on the India Lights platform. Each point you see on the map represents the light output of a specific village at a specific point in time. On the district level, the map also allows you to filter to view villages that have participated in India’s flagship electrification program. This tremendous trove of data can be used to look at changes in light output, which can be used to complement research about electrification in the country.

    About the Data:
    The DMSP raster images have a resolution of 30 arc-seconds, equal to roughly 1 square kilometer at the equator. Each pixel of the image is assigned a number on a relative scale from 0 to 63, with 0 indicating no light output and 63 indicating the highest level of output. This number is relative and may change depending on the gain settings of the satellite’s sensor, which constantly adjusts to current conditions as it takes pictures throughout the day and at night.

    Methodology

    To derive a single measurement, the light output values were extracted from the raster image for each date for the pixels that correspond to each village's approximate latitude and longitude coordinates. We then processed the data through a series of filtering and aggregation steps.

    First, we filtered out data with too much cloud cover and solar glare, according to recommendations from the National Oceanic and Atmospheric Administration (NOAA). We aggregated the resulting 4.4 billion data points by taking the median measurement for each village over the course of a month. We adjusted for differences among satellites using a multiple regression on year and satellite to isolate the effect of each satellite. To analyze data on the state and district level, we also determined the median village light output within each administrative boundary for each month in the twenty-year time span. These monthly aggregates for each village, district, and state are the data that we have made accessible through the API.

    To generate the map and light curve visualizations that are presented on this site, we performed some additional data processing. For the light curves, we used a rolling average to smooth out the noise due to wide fluctuations inherent in satellite measurements. For the map, we took a random sample of 10% of the villages, stratified over districts to ensure good coverage across regions of varying village density.

    Acknowledgments

    The India Lights project is a collaboration between Development Seed, The World Bank, and Dr. Brian Min at the University of Michigan.
    •Satellite base map © Mapbox.
    •India village locations derived from India VillageMap © 2011-2015 ML Infomap.
    •India population data and district boundaries © 2011-2015 ML Infomap.
    •Data for reference map of Uttar Pradesh, India, from Natural Earth Data
    •Banerjee, Sudeshna Ghosh; Barnes, Douglas; Singh, Bipul; Mayer, Kristy; Samad, Hussain. 2014. Power for all : electricity access challenge in India. A World Bank study. Washington, DC ; World Bank Group.
    •Hsu, Feng-Chi, Kimberly Baugh, Tilottama Ghosh, Mikhail Zhizhin, and Christopher Elvidge. "DMSP-OLS Radiance Calibrated Nighttime Lights Time Series with Intercalibration." Remote Sensing 7.2 (2015): 1855-876. Web.
    •Min, Brian. Monitoring Rural Electrification by Satellite. Tech. World Bank, 30 Dec. 2014. Web.
    •Min, Brian. Power and the Vote: Elections and Electricity in the Developing World. New York and Cambridge: Cambridge University Press. 2015.
    •Min, Brian, and Kwawu Mensan Gaba. Tracking Electrification in Vietnam Using Nighttime Lights. Remote Sensing 6.10 (2014): 9511-529.
    •Min, Brian, and Kwawu Mensan Gaba, Ousmane Fall Sarr, Alassane Agalassou. Detection of Rural Electrification in Africa using DMSP-OLS Night Lights Imagery. International Journal of Remote Sensing 34.22 (2013):8118-8141.

    Disclaimer
    Country borders or names do not necessarily reflect the World Bank Group's official position. The map is for illustrative purposes and does not imply the expression of any opinion on the part of the World Bank, concerning the legal status of any country or territory or concerning the delimitation of frontiers or boundaries.

  20. Literacy rate in India 1981-2022, by gender

    • statista.com
    • ai-chatbox.pro
    Updated May 30, 2025
    + more versions
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    Aaron O'Neill (2025). Literacy rate in India 1981-2022, by gender [Dataset]. https://www.statista.com/topics/10801/demographics-of-india/
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    Dataset updated
    May 30, 2025
    Dataset provided by
    Statistahttp://statista.com/
    Authors
    Aaron O'Neill
    Area covered
    India
    Description

    Literacy in India has been increasing as more and more people receive a better education, but it is still far from all-encompassing. In 2022, the degree of literacy in India was about 76.32 percent, with the majority of literate Indians being men. It is estimated that the global literacy rate for people aged 15 and above is about 86 percent. How to read a literacy rateIn order to identify potential for intellectual and educational progress, the literacy rate of a country covers the level of education and skills acquired by a country’s inhabitants. Literacy is an important indicator of a country’s economic progress and the standard of living – it shows how many people have access to education. However, the standards to measure literacy cannot be universally applied. Measures to identify and define illiterate and literate inhabitants vary from country to country: In some, illiteracy is equated with no schooling at all, for example. Writings on the wallGlobally speaking, more men are able to read and write than women, and this disparity is also reflected in the literacy rate in India – with scarcity of schools and education in rural areas being one factor, and poverty another. Especially in rural areas, women and girls are often not given proper access to formal education, and even if they are, many drop out. Today, India is already being surpassed in this area by other emerging economies, like Brazil, China, and even by most other countries in the Asia-Pacific region. To catch up, India now has to offer more educational programs to its rural population, not only on how to read and write, but also on traditional gender roles and rights.

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TRADING ECONOMICS (2012). India Population [Dataset]. https://tradingeconomics.com/india/population

India Population

India Population - Historical Dataset (1950-12-31/2024-12-31)

Explore at:
23 scholarly articles cite this dataset (View in Google Scholar)
json, excel, xml, csvAvailable download formats
Dataset updated
Oct 10, 2012
Dataset authored and provided by
TRADING ECONOMICS
License

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

Time period covered
Dec 31, 1950 - Dec 31, 2024
Area covered
India
Description

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

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