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.

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

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.

The dataset consists of total cases, new cases, new death, total test per day, etc. This can be used to predict future covid cases in India.

Please give credit to this dataset if you download it.

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

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.

Dataset

This dataset was created by Kumar Sambhawam

Released under CC0: Public Domain

Contents

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.

A majority of the coronavirus (COVID-19) cases in India affected people between ages 31 and 40 years as of October 18, 2021. Of these, the highest share of deaths during the measured time period was observed in people under the age of 50 years.

Context

This dataset provides a timeseries of COVID-19 reported cases including cured/migrated information of states of India. The data is available from 30th January 2020 onwards.

Content

The data is in CSV format and has 5 columns.

Date: Date in DD-MM-YYYY format State: Name if the state Total Confirmed Cases: Total number of confirmed cases as on Date Cured/Discharged/Migrated: Total number of cured, discharged or migrated cases as on Date Death: Total number of deaths as on Date

All figures are cumulative.

Acknowledgements

This dataset is created and maintained using the data available in public domain. The state-wise COVID-19 cases in India are published by Ministry of Health and Family Welfare, Government of India on their website https://www.mohfw.gov.in/. A snapshot of the data on the above website is taken at 11PM IST(UTC+05.30) daily and appended to this dataset. Part of the data for initial period is taken from India Today COVID-19 Tracker at https://www.indiatoday.in/india/story/coronavirus-cases-in-india-covid19-states-cities-affected-1653852-2020-03-09.

Banner Photo by Martin Sanchez on Unsplash

Context

There's a story behind every dataset and here's your opportunity to share yours.

Content

What's inside is more than just rows and columns. Make it easy for others to get started by describing how you acquired the data and what time period it represents, too.

Acknowledgements

https://www.mohfw.gov.in/

We wouldn't be here without the help of others. If you owe any attributions or thanks, include them here along with any citations of past research.

Inspiration

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

Content

This dataset contains around 467538 entry and 17 columns which contains information of the patient and where he/she got covid affected.

Column Description

• Patient Number: Global patient number for all patients being reported
• State Patient Number: A field to represent the state patient number if the state bulletin provided a state patient number
• Date Announced: The date on which the case(s) was reported by the state/central
• Age Bracket: The age of the case/patient
• Gender: The gender of the case/patient
• Detected City: The city where the case(s) were reported
• Detected District: The District where the case(s) were reported
• Detected State: The State where the case(s) were reported
• State code: A two-letter code to represent the state/UT
• Current Status: This can have: Hospitalized, Recovered, Deceased or Migrated_Others, These represent the status of the case
• Contracted from which Patient (Suspected): This field gives the patient id from whom the current patient is believed to have contracted the virus. This is based on state bulletins.
• Nationality: The nationality of the case/patient
• Type of transmission:
• Status Change Date: A field to represent the change of status of patients
• Num Cases: This field can any integer value as following - If the value is == 1: The row indicates an individual record (age and gender info are subject to state bulletin releases). - If the value != 1 (greater than or less than 1): The row indicates a district-level record. - If the value > 0 and (detected district == ‘’ or detected district == ‘Unknown’): The row added without district details as state bulletin did not have district details at the point of data entry. - If the value < 0 and (detecteddistrict == ‘’ or detecteddistrict == ‘Unknown’) : The row added to adjust a previously added bulk entry as stated above - If the value < 0 and (detecteddistrict != ‘’ and detecteddistrict != ‘Unknown’) : The row added due to state bulletins providing a reduced count for that district/day/category combination. - If the value == 0 : Ingore the record. This would’ve been an entry made and ignored later due to clarifications from state bulletins.

Acknowledgements

• https://www.covid19india.org making data available public for learning purposes.

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 28 January 2022.

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

About

This dataset contains latest Covid-19 India state-wise data as on January 13, 2022. 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
9. Population - Population of State/UT

Source

Covid Data : https://www.mygov.in/covid-19 Population Data : https://www.indiacensus.net/

Other Updated Covid Datasets

https://www.kaggle.com/anandhuh/datasets Please appreciate the effort with an upvote 👍

Thank You

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

Project Tycho datasets contain case counts for reported disease conditions for countries around the world. The Project Tycho data curation team extracts these case counts from various reputable sources, typically from national or international health authorities, such as the US Centers for Disease Control or the World Health Organization. These original data sources include both open- and restricted-access sources. For restricted-access sources, the Project Tycho team has obtained permission for redistribution from data contributors. All datasets contain case count data that are identical to counts published in the original source and no counts have been modified in any way by the Project Tycho team, except for aggregation of individual case count data into daily counts when that was the best data available for a disease and location. The Project Tycho team has pre-processed datasets by adding new variables, such as standard disease and location identifiers, that improve data interpretability. We also formatted the data into a standard data format. All geographic locations at the country and admin1 level have been represented at the same geographic level as in the data source, provided an ISO code or codes could be identified, unless the data source specifies that the location is listed at an inaccurate geographical level. For more information about decisions made by the curation team, recommended data processing steps, and the data sources used, please see the README that is included in the dataset download ZIP file.

Delhi confirmed almost two million cases of the coronavirus (COVID-19) as of October 20, 2023, with over 26 thousand fatalities and over two million recoveries. The Delhi government, led by Arvind Kejriwal and the Aam Aadmi Party implemented a night and weekend curfew to curb infection numbers in late April 2021. The capital region faced acute shortage of oxygen and ICU beds during this time period.

COVID-19: As on Date: Number of Confirmed Cases: Kerala data was reported at 6,921,277.000 Case in 05 May 2025. This records an increase from the previous number of 6,921,265.000 Case for 28 Apr 2025. COVID-19: As on Date: Number of Confirmed Cases: Kerala data is updated daily, averaging 6,547,507.000 Case from Mar 2020 (Median) to 05 May 2025, with 1587 observations. The data reached an all-time high of 6,921,277.000 Case in 05 May 2025 and a record low of 22.000 Case in 15 Mar 2020. COVID-19: As on Date: Number of Confirmed Cases: Kerala 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.

COVID-19: As on Date: Number of Active Cases: Maharashtra data was reported at 5.000 Case in 05 May 2025. This records an increase from the previous number of 2.000 Case for 28 Apr 2025. COVID-19: As on Date: Number of Active Cases: Maharashtra data is updated daily, averaging 6,087.000 Case from Mar 2020 (Median) to 05 May 2025, with 1587 observations. The data reached an all-time high of 701,614.000 Case in 23 Apr 2021 and a record low of 0.000 Case in 21 Apr 2025. COVID-19: As on Date: Number of Active Cases: Maharashtra 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.

India COVID-19: As on Date: Total Number of Confirmed Cases data was reported at 45,044,752.000 Case in 28 Apr 2025. This records an increase from the previous number of 45,044,668.000 Case for 21 Apr 2025. India COVID-19: As on Date: Total Number of Confirmed Cases data is updated daily, averaging 43,124,585.500 Case from Mar 2020 (Median) to 28 Apr 2025, with 1586 observations. The data reached an all-time high of 45,044,752.000 Case in 28 Apr 2025 and a record low of 110.000 Case in 15 Mar 2020. India COVID-19: As on Date: Total Number of Confirmed 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.

The following is the dataset consisting of Covid19 cases in India since 10th march on a daily basis. It also contains statewide data. It has got separate for active, total, discharged cases and deaths.

Acknowledgements

This dataset is built by converting the JSON file available from the opensource website https://api.rootnet.in. URL for the json datafile: https://api.rootnet.in/covid19-in/stats/history

Inspiration

I struggled a lot to find data in the form of csv file for doing analysis of Covid19 impact on India but I wa u unable to find any good dataset. Hence I had to spend a lot of time learning how to extract JSON files and write codes to convert that into a usable form. Hence I thought I will upload it so that in future aspiring Data analysts can have easy access to the dataset.

This dataset is collected from JHP updated GitHub profile till late March 2020. It contains time series data and other data of coordinates of India etc please refer to the files for understanding.

Dataset Name Entries Attributes Covid complete.csv 19220 Province/State, Country/Region, Latitude, Longitude, Confirmed, Death and Recovered. Covid cases in India.xlsx 25 states S.No., Name of State/UT, Total Confirmed cases (Indian National), Total confirmed cases (Foreign National), Cured and Death Indian Coordinates.xlsx 36 states/UT Name of State/UT, Latitude and Longitude Per day cases.csv 56 Date, Total case, New case and Days after surpassing 100 cases Time series confirmed global.csv 242 67 Time series deaths global.csv 242 67 Time series recovered global.csv 242 67

JHU GitHub: https://github.com/CSSEGISandData/COVID-19