100+ datasets found
  1. COVID-19 India

    • kaggle.com
    Updated Feb 4, 2023
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    swaptr (2023). COVID-19 India [Dataset]. https://www.kaggle.com/datasets/swaptr/covid19-state-data
    Explore at:
    CroissantCroissant is a format for machine-learning datasets. Learn more about this at mlcommons.org/croissant.
    Dataset updated
    Feb 4, 2023
    Dataset provided by
    Kaggle
    Authors
    swaptr
    License

    http://opendatacommons.org/licenses/dbcl/1.0/http://opendatacommons.org/licenses/dbcl/1.0/

    Area covered
    India
    Description

    This dataset is a comprehensive collection of data related to the spread of COVID-19 in India. It captures the number of confirmed cases and deaths in each state and union territory of India from the first reported case in January 2020 to the present day. The dataset was created to provide an understanding of the extent of the COVID-19 pandemic in India. It is important because it allows researchers, policy-makers and citizens to gain insights into the various factors that may be driving the spread of the virus in different states and regions of India. It also provides valuable information for researchers trying to understand the dynamics of the pandemic in India.

    This dataset is important because it allows us to understand the current situation of the pandemic in India and to monitor the progress of the virus in each state. It can also be used to measure the effectiveness of the strategies implemented by the Indian Government to contain the spread of the virus. The dataset is applicable to anyone interested in understanding the dynamics of the COVID-19 pandemic in India, such as policy-makers, researchers, citizens, NGOs and media. It can be used to gain insights into the current situation and to track the progress of the virus in each state. It can also be used to monitor the effectiveness of the strategies implemented by the Indian Government to contain the spread of the virus.

    Overall, this dataset provides a comprehensive view of the COVID-19 pandemic in India. It is updated on a daily basis, and provides essential information that is useful for researchers, policy-makers and citizens. It is an invaluable resource that can be used to understand the dynamics of the virus and to monitor the progress of the virus in each state.

  2. d

    COVID-19: Daily Cases Data

    • dataful.in
    Updated Aug 12, 2025
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    Dataful (Factly) (2025). COVID-19: Daily Cases Data [Dataset]. https://dataful.in/datasets/1311
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    application/x-parquet, xlsx, csvAvailable download formats
    Dataset updated
    Aug 12, 2025
    Dataset authored and provided by
    Dataful (Factly)
    License

    https://dataful.in/terms-and-conditionshttps://dataful.in/terms-and-conditions

    Area covered
    India
    Variables measured
    COVID-19 Cases
    Description

    This Dataset contains day-wise cumulative total positive cases, active cases, recoveries and death statistics due to COVID-19 in India up to 10 June 2024

  3. COVID-19 cases in India as of October 2023, by type

    • tokrwards.com
    • statista.com
    Updated Dec 4, 2024
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    Statista (2024). COVID-19 cases in India as of October 2023, by type [Dataset]. https://tokrwards.com/?_=%2Fstatistics%2F1101713%2Findia-covid-19-cases-by-type%2F%23D%2FIbH0Phabze5YKQxRXLgxTyDkFTtCs%3D
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    Dataset updated
    Dec 4, 2024
    Dataset authored and provided by
    Statistahttp://statista.com/
    Area covered
    India
    Description

    India reported over 44 million confirmed cases of the coronavirus (COVID-19) as of October 20, 2023. The number of people infected with the virus was declining across the south Asian country.

    What is the coronavirus?

    COVID-19 is part of a large family of coronaviruses (CoV) that are transmitted from animals to people. The name COVID-19 is derived from the words corona, virus, and disease, while the number 19 represents the year that it emerged. Symptoms of COVID-19 resemble that of the common cold, with fever, coughing, and shortness of breath. However, serious infections can lead to pneumonia, multi-organ failure, severe acute respiratory syndrome, and even death, if appropriate medical help is not provided.

    COVID-19 in India

    India reported its first case of this coronavirus in late January 2020 in the southern state of Kerala. That led to a nation-wide lockdown between March and June that year to curb numbers from rising. After marginal success, the economy opened up leading to some recovery for the rest of 2020. In March 2021, however, the second wave hit the country causing record-breaking numbers of infections and deaths, crushing the healthcare system. The central government has been criticized for not taking action this time around, with "#ResignModi" trending on social media platforms in late April. The government's response was to block this line of content on the basis of fighting misinformation and reducing panic across the country.

  4. T

    India Coronavirus COVID-19 Cases

    • tradingeconomics.com
    csv, excel, json, xml
    Updated Dec 15, 2017
    + more versions
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    TRADING ECONOMICS (2017). India Coronavirus COVID-19 Cases [Dataset]. https://tradingeconomics.com/india/coronavirus-cases
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    excel, xml, csv, jsonAvailable download formats
    Dataset updated
    Dec 15, 2017
    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
    Jan 4, 2020 - May 17, 2023
    Area covered
    India
    Description

    India recorded 44983152 Coronavirus Cases since the epidemic began, according to the World Health Organization (WHO). In addition, India reported 531794 Coronavirus Deaths. This dataset includes a chart with historical data for India Coronavirus Cases.

  5. COVID-19 confirmed, recovered and deceased cumulative cases in India...

    • statista.com
    • tokrwards.com
    Updated Dec 4, 2024
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    Statista (2024). COVID-19 confirmed, recovered and deceased cumulative cases in India 2020-2023 [Dataset]. https://www.statista.com/statistics/1104054/india-coronavirus-covid-19-daily-confirmed-recovered-death-cases/
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    Dataset updated
    Dec 4, 2024
    Dataset authored and provided by
    Statistahttp://statista.com/
    Time period covered
    Jan 29, 2020 - Oct 20, 2023
    Area covered
    India
    Description

    India reported almost 45 million cases of the coronavirus (COVID-19) as of October 20, 2023, with more than 44 million recoveries and about 532 thousand fatalities. The number of cases in the country had a decreasing trend in the past months.

    Burden on the healthcare system

    With the world's second largest population in addition to an even worse second wave of the coronavirus pandemic seems to be crushing an already inadequate healthcare system. Despite vast numbers being vaccinated, a new variant seemed to be affecting younger age groups this time around. The lack of ICU beds, black market sales of oxygen cylinders and drugs needed to treat COVID-19, as well as overworked crematoriums resorting to mass burials added to the woes of the country. Foreign aid was promised from various countries including the United States, France, Germany and the United Kingdom. Additionally, funding from the central government was expected to boost vaccine production.

    Situation overview
    Even though days in April 2021 saw record-breaking numbers compared to any other country worldwide, a nation-wide lockdown has not been implemented. The largest religious gathering - the Kumbh Mela, sacred to the Hindus, along with election rallies in certain states continue to be held. Some states and union territories including Maharashtra, Delhi, and Karnataka had issued curfews and lockdowns to try to curb the spread of infections.

  6. COVID-19 cases in Indian states 2023, by type

    • statista.com
    • tokrwards.com
    Updated Dec 4, 2024
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    Statista (2024). COVID-19 cases in Indian states 2023, by type [Dataset]. https://www.statista.com/statistics/1103458/india-novel-coronavirus-covid-19-cases-by-state/
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    Dataset updated
    Dec 4, 2024
    Dataset authored and provided by
    Statistahttp://statista.com/
    Area covered
    India
    Description

    The Indian state of Punjab reported the highest number of active coronavirus (COVID-19) cases of over one thousand cases as of October 20, 2023. Kerala and Karnataka followed, with relatively lower casualties. That day, there were a total of over 44 million confirmed infections across India.

  7. COVID-19 India Status

    • kaggle.com
    Updated May 16, 2020
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    Abhinav Medhekar (2020). COVID-19 India Status [Dataset]. https://www.kaggle.com/datasets/medhekarabhinav5/covid19-india-stateut-wise
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    CroissantCroissant is a format for machine-learning datasets. Learn more about this at mlcommons.org/croissant.
    Dataset updated
    May 16, 2020
    Dataset provided by
    Kaggle
    Authors
    Abhinav Medhekar
    Area covered
    India
    Description

    As COVID-19 is continuously creating havoc on earth, data analysis regarding it is necessary to take proper actions. Attached data is taken from "data.gov.in.". It is divided as per the States and Union Territories of India. Data is latest updated on 16th May 2020.

  8. COVID-19 Related Shocks Survey in Rural India 2020, Round 1 - India

    • microdata.worldbank.org
    • catalog.ihsn.org
    Updated Jan 14, 2021
    + more versions
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    World Bank (2021). COVID-19 Related Shocks Survey in Rural India 2020, Round 1 - India [Dataset]. https://microdata.worldbank.org/index.php/catalog/3769
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    Dataset updated
    Jan 14, 2021
    Dataset provided by
    World Bank Grouphttp://www.worldbank.org/
    Authors
    World Bank
    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

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

    Analysis unit

    Household

    Kind of data

    Sample survey data [ssd]

    Sampling procedure

    The samples for these surveys were drawn from surveys and impact evaluations previously conducted by the World Bank, the Ministry of Rural Development, India and IDInsight. A detailed note on the sampling frames is available for download.

    Sampling deviation

    Details will be made available after all rounds of data collection and analysis is complete.

    Mode of data collection

    Computer Assisted Telephone Interview [cati]

    Research instrument

    The survey questionnaire consists of the following modules: - Module 0: Introduction - Module 1: Migration - Module 2: Labor and Income - Module 3: Consumption - Module 4: Agriculture - Module 5: Access to Relief - Module 6: Health

    Response rate

    ~55%

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

    • catalog.ihsn.org
    • datacatalog.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://catalog.ihsn.org/catalog/9553
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    Dataset updated
    Mar 22, 2021
    Dataset provided by
    World Bank Grouphttp://www.worldbank.org/
    Authors
    World Bank
    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%

  10. d

    India COVID-19 Case Data with Basemap (STC)

    • search.dataone.org
    • dataverse.harvard.edu
    Updated Nov 22, 2023
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    NSF Spatiotemporal Innovation Center (2023). India COVID-19 Case Data with Basemap (STC) [Dataset]. http://doi.org/10.7910/DVN/9QZGZB
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    Dataset updated
    Nov 22, 2023
    Dataset provided by
    Harvard Dataverse
    Authors
    NSF Spatiotemporal Innovation Center
    Description

    Case data from 03-10-2020 to 08-16-2020, this data repository stores COVID-19 virus case data for India, including the daily case, summary data, and base map. Each zip file contains weekly case data from Monday to Sunday.

  11. Latest Coronavirus COVID-19 figures for India

    • covid19-today.pages.dev
    json
    Updated Jul 30, 2025
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    Worldometers (2025). Latest Coronavirus COVID-19 figures for India [Dataset]. https://covid19-today.pages.dev/countries/india/
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    jsonAvailable download formats
    Dataset updated
    Jul 30, 2025
    Dataset provided by
    Worldometershttps://dadax.com/
    CSSE at JHU
    License

    https://github.com/disease-sh/API/blob/master/LICENSEhttps://github.com/disease-sh/API/blob/master/LICENSE

    Area covered
    India
    Description

    In past 24 hours, India, Asia had 68 new cases, N/A deaths and N/A recoveries.

  12. f

    IWB During COVID-19 in Combined UK, Greece, India Dataset

    • brunel.figshare.com
    bin
    Updated Sep 15, 2023
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    Pauldy Otermans; Maria Spanoudaki; Stanley Gaines; Dev Aditya (2023). IWB During COVID-19 in Combined UK, Greece, India Dataset [Dataset]. http://doi.org/10.17633/rd.brunel.24083472.v1
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    binAvailable download formats
    Dataset updated
    Sep 15, 2023
    Dataset provided by
    Brunel University London
    Authors
    Pauldy Otermans; Maria Spanoudaki; Stanley Gaines; Dev Aditya
    License

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

    Area covered
    Greece, United Kingdom, India
    Description

    We examined the construct validity of a 28-item survey that was designed to measure inner wellbeing (i.e., individuals’ thoughts and feelings about what they can do and be; White et al., 2014) among individuals in (1) the Global South nation of India (n = 205), (2) the Global North nation of the United Kingdom (n = 392), and (3) the nation of Greece, which is not readily categorized as Global South or Global North (n = 354) during COVID lockdown. Using a series of multiple-group confirmatory factor analyses via LISREL 10.20 (Joreskog & Sorbom, 2019), we tested the hypothesis that a model specifying seven factors (i.e., economic confidence, agency/participation, social connections, close relationships, physical/mental health, competence/self-worth, and values/meaning as intercorrelated domains) would provide a significantly better fit to the correlational data than would a model specifying a one factor (i.e., unidimensional inner wellbeing).

  13. a

    Transmission Heatmap of COVID-19 India & Kerala (Viswaprabha)

    • hub.arcgis.com
    Updated Mar 13, 2020
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    viswaprabha (2020). Transmission Heatmap of COVID-19 India & Kerala (Viswaprabha) [Dataset]. https://hub.arcgis.com/maps/4665d945ad8e425482a2990bde73c8cd
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    Dataset updated
    Mar 13, 2020
    Dataset authored and provided by
    viswaprabha
    Area covered
    Description

    City-wise confirmed Covid-19 cases within India and specifically within KeralaFor discussions, please visit and follow the Facebook profile: https://www.facebook.com/viswaprabhaTo see the underlying live data, please visit this Google Sheet

  14. I

    India COVID-19: As on Date: Total Number of Active Cases

    • ceicdata.com
    Updated Nov 15, 2019
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    CEICdata.com (2019). India COVID-19: As on Date: Total Number of Active Cases [Dataset]. https://www.ceicdata.com/en/india/disease-outbreaks-coronavirus-2019-mohfw/covid19-as-on-date-total-number-of-active-cases
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    Dataset updated
    Nov 15, 2019
    Dataset provided by
    CEICdata.com
    License

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

    Time period covered
    Dec 23, 2024 - Mar 24, 2025
    Area covered
    India
    Description

    India COVID-19: As on Date: Total Number of Active Cases data was reported at 35.000 Case in 05 May 2025. This records an increase from the previous number of 29.000 Case for 28 Apr 2025. India COVID-19: As on Date: Total Number of Active Cases data is updated daily, averaging 44,029.000 Case from Mar 2020 (Median) to 05 May 2025, with 1587 observations. The data reached an all-time high of 3,745,237.000 Case in 10 May 2021 and a record low of 1.000 Case in 24 Feb 2025. India COVID-19: As on Date: Total Number of Active Cases data remains active status in CEIC and is reported by Ministry of Health and Family Welfare. The data is categorized under High Frequency Database’s Disease Outbreaks – Table IN.HLF006: Disease Outbreaks: Coronavirus 2019: MOHFW.

  15. Breathe India: Covid-19 Effect On Pollution

    • hub.tumidata.org
    csv, url, zip
    Updated Jun 4, 2024
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    TUMI (2024). Breathe India: Covid-19 Effect On Pollution [Dataset]. https://hub.tumidata.org/dataset/breathe_india_covid19_effect_on_pollution_ahmedebad
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    csv(14461), zip(673133), url, zip(2421568), zip(51717659), zip(14790953)Available download formats
    Dataset updated
    Jun 4, 2024
    Dataset provided by
    Tumi Inc.http://www.tumi.com/
    Area covered
    India
    Description

    Breathe India: Covid-19 Effect On Pollution
    This dataset falls under the category Environmental Data Air Quality Data.
    It contains the following data: The dataset contains air quality data and AQI (Air Quality Index) at hourly and daily level of various stations across multiple cities in India.
    This dataset was scouted on 2022-02-26 as part of a data sourcing project conducted by TUMI. License information might be outdated: Check original source for current licensing. The data can be accessed using the following URL / API Endpoint: https://www.kaggle.com/parulpandey/breathe-india-covid-19-effect-on-pollution/data

  16. H

    COVID-19-related knowledge, attitudes, and practices among adolescents and...

    • dataverse.harvard.edu
    Updated Oct 1, 2020
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    Rajib Acharya; Mukta Gundi; Thoai D. Ngo; Neelanjana Pandey; Sangram K. Patel; Jessie Pinchoff; Shilpi Rampal; Niranjan Saggurti; K.G. Santhya; Corinne White; A.J.F. Zavier (2020). COVID-19-related knowledge, attitudes, and practices among adolescents and young people in Bihar and Uttar Pradesh, India [Dataset]. http://doi.org/10.7910/DVN/8ZVOKW
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    CroissantCroissant is a format for machine-learning datasets. Learn more about this at mlcommons.org/croissant.
    Dataset updated
    Oct 1, 2020
    Dataset provided by
    Harvard Dataverse
    Authors
    Rajib Acharya; Mukta Gundi; Thoai D. Ngo; Neelanjana Pandey; Sangram K. Patel; Jessie Pinchoff; Shilpi Rampal; Niranjan Saggurti; K.G. Santhya; Corinne White; A.J.F. Zavier
    License

    CC0 1.0 Universal Public Domain Dedicationhttps://creativecommons.org/publicdomain/zero/1.0/
    License information was derived automatically

    Area covered
    India, India
    Description

    To control the spread of COVID-19 in India and to aid the efforts of the Ministry of Health and Family Welfare (MOHFW), the Population Council and other non-governmental organizations are conducting research to assess residents’ ability to follow sanitation and social distancing precautions under a countrywide lockdown. The Population Council COVID-19 study team is implementing rapid phone-based surveys to collect information on knowledge, attitudes and practices, as well as needs, among 2,041 young people (ages 19–23 years) and/or an adult household member, sampled from an existing prospective cohort study with a total sample size of 20,594 in Bihar (n=10,433) and Uttar Pradesh (n=10,161). Baseline was conducted from April 3–22; subsequent iterations of the survey are planned to be conducted on a monthly basis. Baseline findings on awareness of COVID-19 symptoms, perceived risk, awareness of and ability to carry out preventive behaviors, misconceptions, and fears will inform the development of government and other stakeholders’ interventions and/or strategies. We are committed to openly sharing the latest versions of the study description, questionnaires, de-identified or aggregated datasets, and preliminary results. Data and findings can also be shared with partners working on the COVID-19 response.

  17. i

    Tweets Originating from India During COVID-19 Lockdowns

    • ieee-dataport.org
    Updated Dec 12, 2024
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    Rabindra Lamsal (2024). Tweets Originating from India During COVID-19 Lockdowns [Dataset]. https://ieee-dataport.org/open-access/tweets-originating-india-during-covid-19-lockdowns
    Explore at:
    Dataset updated
    Dec 12, 2024
    Authors
    Rabindra Lamsal
    License

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

    Area covered
    India
    Description

    please visit the primary dataset page.Announcements:

  18. COVID 19 India Dataset

    • kaggle.com
    Updated Jul 4, 2020
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    Aman Jain (2020). COVID 19 India Dataset [Dataset]. https://www.kaggle.com/sspiegels/covid-19-india-dataset/discussion
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    CroissantCroissant is a format for machine-learning datasets. Learn more about this at mlcommons.org/croissant.
    Dataset updated
    Jul 4, 2020
    Dataset provided by
    Kagglehttp://kaggle.com/
    Authors
    Aman Jain
    Area covered
    India
    Description

    Dataset

    This dataset was created by Aman Jain

    Contents

  19. A

    ‘Latest Covid-19 India Statewise Data’ analyzed by Analyst-2

    • analyst-2.ai
    Updated Nov 15, 2021
    + more versions
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    Analyst-2 (analyst-2.ai) / Inspirient GmbH (inspirient.com) (2021). ‘Latest Covid-19 India Statewise Data’ analyzed by Analyst-2 [Dataset]. https://analyst-2.ai/analysis/kaggle-latest-covid-19-india-statewise-data-bcf7/8830dce4/?iid=001-295&v=presentation
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    Dataset updated
    Nov 15, 2021
    Dataset authored and provided by
    Analyst-2 (analyst-2.ai) / Inspirient GmbH (inspirient.com)
    License

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

    Area covered
    India
    Description

    Analysis of ‘Latest Covid-19 India Statewise Data’ provided by Analyst-2 (analyst-2.ai), based on source dataset retrieved from https://www.kaggle.com/anandhuh/latest-covid19-india-statewise-data on 12 November 2021.

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

    About

    This dataset contains latest Covid-19 India state-wise data as on November 07, 2021. This dataset can be used to analyze covid in India. This dataset is great for Exploratory Data Analysis

    Attribute Information

    1. State/UTs - Names of Indian States and Union Territories.
    2. Total Cases - Total number of confirmed cases
    3. Active - Total number of active cases
    4. Discharged - Total number of discharged cases
    5. Deaths - Total number of deaths
    6. Active Ratio (%) - Ratio of number of active cases to total cases
    7. Discharge Ratio (%) - Ratio of number of discharged cases to total cases
    8. Death Ratio (%) - Ratio of number of deaths to total cases

    Source

    Link : https://www.mygov.in/covid-19

    Other Updated Covid Datasets

    https://www.kaggle.com/anandhuh/datasets

    Thank You

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

  20. Cumulative COVID-19 tests India 2020-2023

    • statista.com
    • tokrwards.com
    Updated Dec 4, 2024
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    Statista (2024). Cumulative COVID-19 tests India 2020-2023 [Dataset]. https://www.statista.com/statistics/1113465/india-coronavirus-covid-19-tests-cumulative/
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    Dataset updated
    Dec 4, 2024
    Dataset authored and provided by
    Statistahttp://statista.com/
    Time period covered
    Apr 9, 2020 - Oct 20, 2023
    Area covered
    India
    Description

    India tested over 935 million samples for the coronavirus (COVID-19) as of October 20, 2023. The number of people infected with the virus was coming down across the south Asian country. The country was hit with a second wave in March 2021, leading to a collapse of the healthcare system.

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swaptr (2023). COVID-19 India [Dataset]. https://www.kaggle.com/datasets/swaptr/covid19-state-data
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COVID-19 India

Latest statewise data of COVID-19 in India

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2 scholarly articles cite this dataset (View in Google Scholar)
CroissantCroissant is a format for machine-learning datasets. Learn more about this at mlcommons.org/croissant.
Dataset updated
Feb 4, 2023
Dataset provided by
Kaggle
Authors
swaptr
License

http://opendatacommons.org/licenses/dbcl/1.0/http://opendatacommons.org/licenses/dbcl/1.0/

Area covered
India
Description

This dataset is a comprehensive collection of data related to the spread of COVID-19 in India. It captures the number of confirmed cases and deaths in each state and union territory of India from the first reported case in January 2020 to the present day. The dataset was created to provide an understanding of the extent of the COVID-19 pandemic in India. It is important because it allows researchers, policy-makers and citizens to gain insights into the various factors that may be driving the spread of the virus in different states and regions of India. It also provides valuable information for researchers trying to understand the dynamics of the pandemic in India.

This dataset is important because it allows us to understand the current situation of the pandemic in India and to monitor the progress of the virus in each state. It can also be used to measure the effectiveness of the strategies implemented by the Indian Government to contain the spread of the virus. The dataset is applicable to anyone interested in understanding the dynamics of the COVID-19 pandemic in India, such as policy-makers, researchers, citizens, NGOs and media. It can be used to gain insights into the current situation and to track the progress of the virus in each state. It can also be used to monitor the effectiveness of the strategies implemented by the Indian Government to contain the spread of the virus.

Overall, this dataset provides a comprehensive view of the COVID-19 pandemic in India. It is updated on a daily basis, and provides essential information that is useful for researchers, policy-makers and citizens. It is an invaluable resource that can be used to understand the dynamics of the virus and to monitor the progress of the virus in each state.

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