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

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.

We will build you a custom India crime dataset based on your needs. Data points may include date, time, location, crime type, crime description, victim demographics, offender demographics, arrest records, charges filed, court outcomes, police department response time, incident outcome, weapon used, property stolen or damaged, crime location type, and other related data.

Use our India crime datasets for a range of applications to enhance public safety and policy effectiveness. Analyzing these datasets can help organizations understand crime patterns and trends across different regions of India, enabling them to tailor their strategies and interventions accordingly. Depending on your needs, you may access the entire dataset or a customized subset.

Popular use cases include: improving public safety measures, designing targeted crime prevention programs, resource allocation for law enforcement, and more.

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?

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.

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. The Project Tycho team has pre-processed datasets by adding new variables, such as standard disease and location identifiers, that improve data interpretabilty. We also formatted the data into a standard data format.

Each Project Tycho dataset contains case counts for a specific condition (e.g. measles) and for a specific country (e.g. The United States). Case counts are reported per time interval. In addition to case counts, datsets include information about these counts (attributes), such as the location, age group, subpopulation, diagnostic certainty, place of aquisition, and the source from which we extracted case counts. One dataset can include many series of case count time intervals, such as "US measles cases as reported by CDC", or "US measles cases reported by WHO", or "US measles cases that originated abroad", etc.

Depending on the intended use of a dataset, we recommend a few data processing steps before analysis:

• Analyze missing data: Project Tycho datasets do not inlcude time intervals for which no case count was reported (for many datasets, time series of case counts are incomplete, due to incompleteness of source documents) and users will need to add time intervals for which no count value is available. Project Tycho datasets do include time intervals for which a case count value of zero was reported.
• Separate cumulative from non-cumulative time interval series. Case count time series in Project Tycho datasets can be "cumulative" or "fixed-intervals". Cumulative case count time series consist of overlapping case count intervals starting on the same date, but ending on different dates. For example, each interval in a cumulative count time series can start on January 1st, but end on January 7th, 14th, 21st, etc. It is common practice among public health agencies to report cases for cumulative time intervals. Case count series with fixed time intervals consist of mutually exxclusive time intervals that all start and end on different dates and all have identical length (day, week, month, year). Given the different nature of these two types of case count data, we indicated this with an attribute for each count value, named "PartOfCumulativeCountSeries".

Context

This is a Covid 19 data set for India. The data set is updated frequently and is analysed using tableau. Click on the link to visit the tableau story. Click each of the caption in the story to unveil its content.

https://public.tableau.com/profile/ambili.nair#!/vizhome/COVID19Indiastory/Indiastory?publish=yes

The first Covid 19 case in India was reported on 30th January 2020 in South Indian state of Kerala on a medical student who was pursuing the studies at Wuhan University, China. Two more students were found to be infected in Kerala in the consecutive days. The Kerala government was successful in containing the disease with its proactive measures back then. The second outbreak of Covid 19 in India started in the first week of March from various parts of India in various people who visited the foreign countries and in some of the tourists from different countries.

The tableau story consists of the following data analysis : 1. State-wise number of infected and number of death count in India map. Hover the mouse on each state in the India map to know the count. 2. Click on the next caption to know the state-wise number of confirmed, active, recovered and deceased cases in the form of bar chart. 3. The next caption takes you to the bar chart which shows the number of cases getting confirmed in India each day starting from January 30, 2020. 4. Next caption takes us to an analysis of the Mortality rate and the Recovery rate (in percentage) of each of the Indian state. We get an idea how hard each of the state is hit by the pandemic. 5. Next caption gives a detailed analysis of the state Kerala which has the mortality rate of 0.806% and the recovery rate of 74.4% as of now. Hover the mouse to know the count in each district. Don't forget to have a look at the line graph of 'number of active cases' in Kerala. It looks almost flattened ! As everyday we hear the increasing number of cases and deaths across the country, this graph may make you feel better...! 6. Finally the caption takes you to the statistics from the topmost district of Kerala - Kasaragod. The total number of cases reported is 179 at Kasaragod. The active number of cases is just 12 as of now... !!! Have a look at the statistics from Kasaragod and the story of 'Kasaragod model' as some of the national media in India call it !!!

Content

This data set consists of the following data: 1. state-wise statistics - Confirmed, Active, Recovered, Deceased cases 2. day-wise count of infected and deceased from various states 3. Statistics from Kerala - day-wise count of confirmed, Active, Recovered, Deceased cases 4. Statistics from Kasaragod district, Kerala - day-wise count of confirmed, Active, Recovered, Deceased cases 5. Count of confirmed cases from various districts of India

Acknowledgements

Ministry of Health and Family Welfare - India covid19india.org Wikipedia page - Covid 19 Pandemic India Govt. of Kerala dashboard - official Kerala Covid 19 statistics

Inspiration

Inspiration

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

This dataset contains the State and Year-wise dengue cases and deaths in India.

Note: The data is till December 2024 only

In 2024, the number of data compromises in the United States stood at 3,158 cases. Meanwhile, over 1.35 billion individuals were affected in the same year by data compromises, including data breaches, leakage, and exposure. While these are three different events, they have one thing in common. As a result of all three incidents, the sensitive data is accessed by an unauthorized threat actor. Industries most vulnerable to data breaches Some industry sectors usually see more significant cases of private data violations than others. This is determined by the type and volume of the personal information organizations of these sectors store. In 2024 the financial services, healthcare, and professional services were the three industry sectors that recorded most data breaches. Overall, the number of healthcare data breaches in some industry sectors in the United States has gradually increased within the past few years. However, some sectors saw decrease. Largest data exposures worldwide In 2020, an adult streaming website, CAM4, experienced a leakage of nearly 11 billion records. This, by far, is the most extensive reported data leakage. This case, though, is unique because cyber security researchers found the vulnerability before the cyber criminals. The second-largest data breach is the Yahoo data breach, dating back to 2013. The company first reported about one billion exposed records, then later, in 2017, came up with an updated number of leaked records, which was three billion. In March 2018, the third biggest data breach happened, involving India’s national identification database Aadhaar. As a result of this incident, over 1.1 billion records were exposed.

India Cyber Crime: IPC Section: Number of Cases Registered data was reported at 33,798.000 Unit in 2022. This records an increase from the previous number of 25,384.000 Unit for 2021. India Cyber Crime: IPC Section: Number of Cases Registered data is updated yearly, averaging 738.000 Unit from Dec 2002 (Median) to 2022, with 21 observations. The data reached an all-time high of 33,798.000 Unit in 2022 and a record low of 176.000 Unit in 2008. India Cyber Crime: IPC Section: Number of Cases Registered data remains active status in CEIC and is reported by National Crime Records Bureau. The data is categorized under India Premium Database’s Crime – Table IN.CRA001: Crime Statistics.

Social media platforms have become integral tools in the conduct of foreign policy for many nations, including India. This dataset serves as a resource for analyzing ‘Social Media and India’s Foreign Policy: The Case Study of ‘X’ Diplomacy during the Covid-19 Pandemic.’ The data were collected through a web-based questionnaire distributed primarily to people aged 18 – 61 and above in India. A total of 171 valid data were collected from 17 states offering extensive geographic coverage and stored in Mendeley. The 15 contributor states are Goa, Maharashtra, Tamil Nadu, Gujarat, Delhi, Assam, Haryana, Jammu and Kashmir, Karnataka, Kerala, Punjab, Rajasthan, Tripura, Uttar Pradesh and West Bengal. It encompasses diverse question formats, including single-choice, multiple-choice, quizzes, and open-ended. The study underscores the opportunities and challenges of employing 'X' diplomacy in India's foreign policy. Thus, there were two hypotheses. First, India's effective use of 'X' diplomacy positively impacts public perception of India's foreign policy effectiveness. Second, India's adept use of 'X' diplomacy during the COVID-19 pandemic enhances its ability to manage and respond to the crisis effectively. This data shows public perception of the effective use of social media by the Government of India, particularly in the crisis situation. Data also highlight the significant change in India’s narrative through its ‘X’ diplomacy, effectively setting the narratives, public perceptions, and diplomatic strategies. This data can be fully utilized in the study of the significance of social media in India’s foreign policy, the role of social media like ‘X’ in the making of India’s foreign policy, how effective social media like ‘X’ was during the Covid-19 pandemic and how Indian government utilized social media like ‘X’ to delivered messages and to set the narrative in the international politics.

In 2022, more than *** million FIRs were filled for crimes under Indian Penal Code and Special and Local Laws in India. This was a decrease from the previous year's value. However, this was a significant decrease from the cases filed in 2015.

viber1/indian-law-dataset dataset hosted on Hugging Face and contributed by the HF Datasets community

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.

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.

COVID-19: As on Date: Number of Confirmed Cases: Bihar data was reported at 855,691.000 Case in 05 May 2025. This stayed constant from the previous number of 855,691.000 Case for 28 Apr 2025. COVID-19: As on Date: Number of Confirmed Cases: Bihar data is updated daily, averaging 830,695.000 Case from Mar 2020 (Median) to 05 May 2025, with 1580 observations. The data reached an all-time high of 855,691.000 Case in 05 May 2025 and a record low of 2.000 Case in 23 Mar 2020. COVID-19: As on Date: Number of Confirmed Cases: Bihar 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.

In 2022, the total number of rape cases reported in India amounted to over 31 thousand. This was a slight decrease in rape cases compared to the previous year. Even though many rapes are not reported in the country, it is an issue that continuously makes news headlines, some leading to public protests. Although reports of rape have increased in recent years, it was still associated with shame for the victim, rather than the perpetrator. The justice system  A victim of rape in India not only experiences social stigmatization but what is more, her fight for justice is not made easy due to the system that often faults the victim for their misfortune. Instances have been reported where victims are confronted with hostile conditions at police stations and have been often pressured to withdraw their cases. However, once a case goes to trial, it can take decades before anything is resolved. Rape cases in particular, face huge backlog where the number of new cases supersede the number of cases disposed every year. The process is arduous and could add so much trauma to the victim’s life that they often buckle under pressure from family of their own or that of the perpetrator.  Women in India India is known to be one of the most dangerous countries in the world for women. Indian women are constantly in a state of high alert when alone on the streets, at work or in the markets. Due to India’s predominantly patriarchal nature, domestic violence is known to be culturally acceptable. Studies reveal that even a majority of working women suffer domestic abuse from their husbands. A non-earning woman’s position further exacerbates vulnerability and dependence on their male partner as opposed to a woman who contributors financially to the household. Rampant poverty across the country is the main driver for low literacy rates and consequently, disempowerment and abuse among women.

This layer contains the data of state level India Dengue 2015-2024 and contains information about number of dengue cases in 2023, number of dengue deaths in 2023, number of dengue cases in 2024, number of dengue deaths in 2024 etc.About Dengue:Dengue is a mosquito-borne viral infection, found in tropical and sub-tropical climates worldwide, mostly in urban and semi-urban areas.The virus responsible for causing dengue, is called dengue virus (DENV). There are four DENV serotypes, meaning that it is possible to be infected four times.While many DENV infections produce only mild illness, DENV can cause an acute flu-like illness. Occasionally this develops into a potentially lethal complication, called severe dengue.The global incidence of dengue has grown dramatically in recent decades. About half of the world's population is now at risk. There are an estimated 100-400 million infections each year.Dengue prevention and control depends on effective vector control measures. Sustained community involvement can improve vector control efforts substantially.SymptomsDengue should be suspected when a high fever (40°C/104°F) is accompanied by 2 of the following symptoms during the febrile phase:Severe headachePain behind the eyesMuscle and joint painsNauseaVomitingSwollen glandsRash. The attributes are given below for this web map:No. of Dengue Cases in 2015No. of Dengue Deaths in 2015No. of Dengue Cases in 2016No. of Dengue Deaths in 2016No. of Dengue Cases in 2017No. of Dengue Deaths in 2017No. of Dengue Cases in 2018No. of Dengue Deaths in 2018No. of Dengue Cases in 2019No. of Dengue Deaths in 2019No. of Dengue Cases in 2020No. of Dengue Deaths in 2020No. of Dengue Cases in 2021No. of Dengue Deaths in 2021No. of Dengue Cases in 2022No. of Dengue Deaths in 2022No. of Dengue Cases in 2023No. of Dengue Deaths in 2023No. of Dengue Cases in 2024(P)No. of Dengue Deaths in 2024(P)Source: https://ncvbdc.mohfw.gov.in/index4.php?lang=1&level=0&linkid=431&lid=3715This web layer is offered by Esri India, for ArcGIS Online subscribers. If you have any questions or comments, please let us know via content@esri.in.

COVID-19: As on Date: Number of Confirmed Cases: Telangana data was reported at 844,923.000 Case in 05 May 2025. This stayed constant from the previous number of 844,923.000 Case for 28 Apr 2025. COVID-19: As on Date: Number of Confirmed Cases: Telangana data is updated daily, averaging 792,627.000 Case from Mar 2020 (Median) to 05 May 2025, with 1587 observations. The data reached an all-time high of 844,923.000 Case in 05 May 2025 and a record low of 3.000 Case in 16 Mar 2020. COVID-19: As on Date: Number of Confirmed Cases: Telangana 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.

It has never been easier to solve any database related problem using any sequel language and the following gives an opportunity for you guys to understand how I was able to figure out some of the interline relationships between databases using Panoply.io tool.

I was able to insert coronavirus dataset and create a submittable, reusable result. I hope it helps you work in Data Warehouse environment.

The following is list of SQL commands performed on dataset attached below with the final output as stored in Exports Folder QUERY 1 SELECT "Province/State" As "Region", Deaths, Recovered, Confirmed FROM "public"."coronavirus_updated" WHERE Recovered>(Deaths/2) AND Deaths>0 Description: How will we estimate where Coronavirus has infiltrated, but there is effective recovery amongst patients? We can view those places by having Recovery twice more than the Death Toll.

Query 2 SELECT country, sum(confirmed) as "Confirmed Count", sum(Recovered) as "Recovered Count", sum(Deaths) as "Death Toll" FROM "public"."coronavirus_updated" WHERE Recovered>(Deaths/2) AND Confirmed>0 GROUP BY country

Description: Coronavirus Epidemic has infiltrated multiple countries, and the only way to be safe is by knowing the countries which have confirmed Coronavirus Cases. So here is a list of those countries

Query 3 SELECT country as "Countries where Coronavirus has reached" FROM "public"."coronavirus_updated" WHERE confirmed>0 GROUP BY country Description: Coronavirus Epidemic has infiltrated multiple countries, and the only way to be safe is by knowing the countries which have confirmed Coronavirus Cases. So here is a list of those countries.

Query 4 SELECT country, sum(suspected) as "Suspected Cases under potential CoronaVirus outbreak" FROM "public"."coronavirus_updated" WHERE suspected>0 AND deaths=0 AND confirmed=0 GROUP BY country ORDER BY sum(suspected) DESC

Description: Coronavirus is spreading at alarming rate. In order to know which countries are newly getting the virus is important because in these countries if timely measures are taken, it could prevent any causalities. Here is a list of suspected cases with no virus resulted deaths.

Query 5 SELECT country, sum(suspected) as "Coronavirus uncontrolled spread count and human life loss", 100*sum(suspected)/(SELECT sum((suspected)) FROM "public"."coronavirus_updated") as "Global suspected Exposure of Coronavirus in percentage" FROM "public"."coronavirus_updated" WHERE suspected>0 AND deaths=0 GROUP BY country ORDER BY sum(suspected) DESC Description: Coronavirus is getting stronger in particular countries, but how will we measure that? We can measure it by knowing the percentage of suspected patients amongst countries which still doesn’t have any Coronavirus related deaths. The following is a list.

Data Provided by: SRK, Data Scientist at H2O.ai, Chennai, India