Name: Coronavirus (COVID-19) In-depth Dataset
Creator: Kaggle
License: http://opendatacommons.org/licenses/dbcl/1.0/

About this Dataset

Coronavirus (COVID-19) In-depth Dataset

Context

Covid-19 Data collected from various sources on the internet. This dataset has daily level information on the number of affected cases, deaths, and recovery from the 2019 novel coronavirus. Please note that this is time-series data and so the number of cases on any given day is the cumulative number.

Content

The dataset includes 28 files scrapped from various data sources mainly the John Hopkins GitHub repository, the ministry of health affairs India, worldometer, and Our World in Data website. The details of the files are as follows

countries-aggregated.csv
A simple and cleaned data with 5 columns with self-explanatory names.
-covid-19-daily-tests-vs-daily-new-confirmed-cases-per-million.csv
A time-series data of daily test conducted v/s daily new confirmed case per million. Entity column represents Country name while code represents ISO code of the country.
-covid-contact-tracing.csv
Data depicting government policies adopted in case of contact tracing. 0 -> No tracing, 1-> limited tracing, 2-> Comprehensive tracing.
-covid-stringency-index.csv
The nine metrics used to calculate the Stringency Index are school closures; workplace closures; cancellation of public events; restrictions on public gatherings; closures of public transport; stay-at-home requirements; public information campaigns; restrictions on internal movements; and international travel controls. The index on any given day is calculated as the mean score of the nine metrics, each taking a value between 0 and 100. A higher score indicates a stricter response (i.e. 100 = strictest response).
-covid-vaccination-doses-per-capita.csv
A total number of vaccination doses administered per 100 people in the total population. This is counted as a single dose, and may not equal the total number of people vaccinated, depending on the specific dose regime (e.g. people receive multiple doses).
-covid-vaccine-willingness-and-people-vaccinated-by-country.csv
Survey who have not received a COVID vaccine and who are willing vs. unwilling vs. uncertain if they would get a vaccine this week if it was available to them.
-covid_india.csv
India specific data containing the total number of active cases, recovered and deaths statewide.
-cumulative-deaths-and-cases-covid-19.csv
A cumulative data containing death and daily confirmed cases in the world.
-current-covid-patients-hospital.csv
Time series data containing a count of covid patients hospitalized in a country
-daily-tests-per-thousand-people-smoothed-7-day.csv
Daily test conducted per 1000 people in a running week average.
-face-covering-policies-covid.csv
Countries are grouped into five categories:
1->No policy
2->Recommended
3->Required in some specified shared/public spaces outside the home with other people present, or some situations when social distancing not possible
4->Required in all shared/public spaces outside the home with other people present or all situations when social distancing not possible
5->Required outside the home at all times regardless of location or presence of other people
-full-list-cumulative-total-tests-per-thousand-map.csv
Full list of total tests conducted per 1000 people.
-income-support-covid.csv
Income support captures if the government is covering the salaries or providing direct cash payments, universal basic income, or similar, of people who lose their jobs or cannot work. 0->No income support, 1->covers less than 50% of lost salary, 2-> covers more than 50% of the lost salary.
-internal-movement-covid.csv
Showing government policies in restricting internal movements. Ranges from 0 to 2 where 2 represents the strictest.
-international-travel-covid.csv
Showing government policies in restricting international movements. Ranges from 0 to 2 where 2 represents the strictest.
-people-fully-vaccinated-covid.csv
Contains the count of fully vaccinated people in different countries.
-people-vaccinated-covid.csv
Contains the total count of vaccinated people in different countries.
-positive-rate-daily-smoothed.csv
Contains the positivity rate of various countries in a week running average.
-public-gathering-rules-covid.csv
Restrictions are given based on the size of public gatherings as follows:
0->No restrictions
1 ->Restrictions on very large gatherings (the limit is above 1000 people)
2 -> gatherings between 100-1000 people
3 -> gatherings between 10-100 people
4 -> gatherings of less than 10 people
-school-closures-covid.csv
School closure during Covid.
-share-people-fully-vaccinated-covid.csv
Share of people that are fully vaccinated.
-stay-at-home-covid.csv
Countries are grouped into four categories:
0->No measures
1->Recommended not to leave the house
2->Required to not leave the house with exceptions for daily exercise, grocery shopping, and ‘essential’ trips
3->Required to not leave the house with minimal exceptions (e.g. allowed to leave only once every few days, or only one person can leave at a time, etc.)
-workplace-closures-covid.csv
Workplace closure during covid. Ranges from 0->3 where 3 represents required for all.

Acknowledgements

-Thomas Hale , Noam Angrist , Rafael Goldszmidt , Beatriz Kira , Anna Petherick , Toby Phillips, Samuel Webster, Emily Cameron-Blake , Laura Hallas, Saptarshi Majumdar, and Helen Tatlow. (2021). “A global panel database of pandemic policies (Oxford COVID-19 Government Response Tracker).” Nature Human Behaviour. https://doi.org/10.1038/s41562-021-01079-8
-Johns Hopkins University for making the data available for educational and academic research purposes
-World Health Organization (WHO): https://www.who.int/
-Ministry of Health and Family welfare: https://www.mohfw.gov.in/

Inspiration

The trend of daily new cases.
Geospatial analysis of country-specific hotspots.
Comparison of top countries in vaccination race.
Share of people fully vaccinated.
Government policies during Covid.
Any many more..

Tables

Countries Aggregated

@kaggle.pranjalverma08_coronavirus_covid19_indepth_dataset.countries_aggregated

838.82 kB
91,392 rows
5 columns

CREATE TABLE countries_aggregated (
  "date" TIMESTAMP,
  "country" VARCHAR,
  "confirmed" BIGINT,
  "recovered" BIGINT,
  "deaths" BIGINT
);

Covid 19 Daily Tests Vs Daily New Confirmed Cases Per Million

@kaggle.pranjalverma08_coronavirus_covid19_indepth_dataset.covid_19_daily_tests_vs_daily_new_confirmed_cases_per_million

791.92 kB
91,833 rows
8 columns

CREATE TABLE covid_19_daily_tests_vs_daily_new_confirmed_cases_per_million (
  "entity" VARCHAR,
  "code" VARCHAR,
  "day" TIMESTAMP,
  "new_tests_per_thousand_7day_smoothed" DOUBLE,
  "n_142753_annotations" VARCHAR  -- 142753-annotations,
  "daily_new_confirmed_cases_of_covid_19_per_million_peop_ac407e03" DOUBLE  -- Daily New Confirmed Cases Of COVID-19 Per Million People (rolling 7-day Average, Right-aligned),
  "year" DOUBLE,
  "continent" VARCHAR
);

Covid Contact Tracing

@kaggle.pranjalverma08_coronavirus_covid19_indepth_dataset.covid_contact_tracing

25.53 kB
92,981 rows
4 columns

CREATE TABLE covid_contact_tracing (
  "entity" VARCHAR,
  "code" VARCHAR,
  "day" TIMESTAMP,
  "contact_tracing" BIGINT
);

Covid India

@kaggle.pranjalverma08_coronavirus_covid19_indepth_dataset.covid_india

6.66 kB
36 rows
6 columns

CREATE TABLE covid_india (
  "s_no" BIGINT  -- S. No.,
  "name_of_state_ut" VARCHAR  -- Name Of State / UT,
  "active_cases" BIGINT,
  "cured_discharged_migrated" BIGINT,
  "deaths" BIGINT,
  "total_confirmed_cases" BIGINT
);

Covid Stringency Index

@kaggle.pranjalverma08_coronavirus_covid19_indepth_dataset.covid_stringency_index

46.84 kB
89,647 rows
4 columns

CREATE TABLE covid_stringency_index (
  "entity" VARCHAR,
  "code" VARCHAR,
  "day" TIMESTAMP,
  "stringency_index" DOUBLE
);

Covid Vaccination Doses Per Capita

@kaggle.pranjalverma08_coronavirus_covid19_indepth_dataset.covid_vaccination_doses_per_capita

47.49 kB
11,112 rows
4 columns

CREATE TABLE covid_vaccination_doses_per_capita (
  "entity" VARCHAR,
  "code" VARCHAR,
  "day" TIMESTAMP,
  "total_vaccinations_per_hundred" DOUBLE
);

Covid Vaccine Willingness And People Vaccinated By Country

@kaggle.pranjalverma08_coronavirus_covid19_indepth_dataset.covid_vaccine_willingness_and_people_vaccinated_by_country

8.14 kB
49 rows
7 columns

CREATE TABLE covid_vaccine_willingness_and_people_vaccinated_by_country (
  "entity" VARCHAR,
  "code" VARCHAR,
  "day" TIMESTAMP,
  "people_vaccinated_per_hundred" DOUBLE,
  "willingness_covid_vaccinate_this_week_pct_pop" DOUBLE,
  "uncertain_covid_vaccinate_this_week_pct_pop" DOUBLE,
  "unwillingness_covid_vaccinate_this_week_pct_pop" DOUBLE
);

Cumulative Deaths And Cases Covid 19

@kaggle.pranjalverma08_coronavirus_covid19_indepth_dataset.cumulative_deaths_and_cases_covid_19

669.64 kB
89,066 rows
5 columns

CREATE TABLE cumulative_deaths_and_cases_covid_19 (
  "entity" VARCHAR,
  "code" VARCHAR,
  "day" TIMESTAMP,
  "total_confirmed_deaths_due_to_covid_19" DOUBLE,
  "total_confirmed_cases_of_covid_19" DOUBLE
);

Current Covid Patients Hospital

@kaggle.pranjalverma08_coronavirus_covid19_indepth_dataset.current_covid_patients_hospital

49.94 kB
11,019 rows
4 columns

CREATE TABLE current_covid_patients_hospital (
  "entity" VARCHAR,
  "code" VARCHAR,
  "day" TIMESTAMP,
  "daily_hospital_occupancy" BIGINT
);

Daily Covid Vaccination Doses Per Capita

@kaggle.pranjalverma08_coronavirus_covid19_indepth_dataset.daily_covid_vaccination_doses_per_capita

69.83 kB
17,700 rows
4 columns

CREATE TABLE daily_covid_vaccination_doses_per_capita (
  "entity" VARCHAR,
  "code" VARCHAR,
  "day" TIMESTAMP,
  "new_vaccinations_smoothed_per_million" DOUBLE
);

Daily Tests Per Thousand People Smoothed 7 Day

@kaggle.pranjalverma08_coronavirus_covid19_indepth_dataset.daily_tests_per_thousand_people_smoothed_7_day

133.93 kB
49,329 rows
5 columns

CREATE TABLE daily_tests_per_thousand_people_smoothed_7_day (
  "entity" VARCHAR,
  "code" VARCHAR,
  "day" TIMESTAMP,
  "new_tests_per_thousand_7day_smoothed" DOUBLE,
  "n_142753_annotations" VARCHAR  -- 142753-annotations
);

Face Covering Policies Covid

@kaggle.pranjalverma08_coronavirus_covid19_indepth_dataset.face_covering_policies_covid

26.35 kB
93,596 rows
4 columns

CREATE TABLE face_covering_policies_covid (
  "entity" VARCHAR,
  "code" VARCHAR,
  "day" TIMESTAMP,
  "facial_coverings" BIGINT
);

Full List Cumulative Total Tests Per Thousand Map

@kaggle.pranjalverma08_coronavirus_covid19_indepth_dataset.full_list_cumulative_total_tests_per_thousand_map

300.96 kB
42,463 rows
5 columns

CREATE TABLE full_list_cumulative_total_tests_per_thousand_map (
  "entity" VARCHAR,
  "code" VARCHAR,
  "day" TIMESTAMP,
  "total_tests_per_thousand" DOUBLE,
  "n_142605_annotations" VARCHAR  -- 142605-annotations
);

Income Support Covid

@kaggle.pranjalverma08_coronavirus_covid19_indepth_dataset.income_support_covid

25.56 kB
93,152 rows
4 columns

CREATE TABLE income_support_covid (
  "entity" VARCHAR,
  "code" VARCHAR,
  "day" TIMESTAMP,
  "income_support" BIGINT
);

Internal Movement Covid

@kaggle.pranjalverma08_coronavirus_covid19_indepth_dataset.internal_movement_covid

26.96 kB
93,562 rows
4 columns

CREATE TABLE internal_movement_covid (
  "entity" VARCHAR,
  "code" VARCHAR,
  "day" TIMESTAMP,
  "restrictions_internal_movements" BIGINT
);

International Travel Covid

@kaggle.pranjalverma08_coronavirus_covid19_indepth_dataset.international_travel_covid

28.31 kB
93,403 rows
4 columns

CREATE TABLE international_travel_covid (
  "entity" VARCHAR,
  "code" VARCHAR,
  "day" TIMESTAMP,
  "international_travel_controls" BIGINT
);

Owid Covid Data 1

@kaggle.pranjalverma08_coronavirus_covid19_indepth_dataset.owid_covid_data_1

5.25 MB
87,742 rows
59 columns

CREATE TABLE owid_covid_data_1 (
  "iso_code" VARCHAR,
  "continent" VARCHAR,
  "location" VARCHAR,
  "date" TIMESTAMP,
  "total_cases" DOUBLE,
  "new_cases" DOUBLE,
  "new_cases_smoothed" DOUBLE,
  "total_deaths" DOUBLE,
  "new_deaths" DOUBLE,
  "new_deaths_smoothed" DOUBLE,
  "total_cases_per_million" DOUBLE,
  "new_cases_per_million" DOUBLE,
  "new_cases_smoothed_per_million" DOUBLE,
  "total_deaths_per_million" DOUBLE,
  "new_deaths_per_million" DOUBLE,
  "new_deaths_smoothed_per_million" DOUBLE,
  "reproduction_rate" DOUBLE,
  "icu_patients" DOUBLE,
  "icu_patients_per_million" DOUBLE,
  "hosp_patients" DOUBLE,
  "hosp_patients_per_million" DOUBLE,
  "weekly_icu_admissions" DOUBLE,
  "weekly_icu_admissions_per_million" DOUBLE,
  "weekly_hosp_admissions" DOUBLE,
  "weekly_hosp_admissions_per_million" DOUBLE,
  "new_tests" DOUBLE,
  "total_tests" DOUBLE,
  "total_tests_per_thousand" DOUBLE,
  "new_tests_per_thousand" DOUBLE,
  "new_tests_smoothed" DOUBLE,
  "new_tests_smoothed_per_thousand" DOUBLE,
  "positive_rate" DOUBLE,
  "tests_per_case" DOUBLE,
  "tests_units" VARCHAR,
  "total_vaccinations" DOUBLE,
  "people_vaccinated" DOUBLE,
  "people_fully_vaccinated" DOUBLE,
  "new_vaccinations" DOUBLE,
  "new_vaccinations_smoothed" DOUBLE,
  "total_vaccinations_per_hundred" DOUBLE,
  "people_vaccinated_per_hundred" DOUBLE,
  "people_fully_vaccinated_per_hundred" DOUBLE,
  "new_vaccinations_smoothed_per_million" DOUBLE,
  "stringency_index" DOUBLE,
  "population" DOUBLE,
  "population_density" DOUBLE,
  "median_age" DOUBLE,
  "aged_65_older" DOUBLE,
  "aged_70_older" DOUBLE,
  "gdp_per_capita" DOUBLE,
  "extreme_poverty" DOUBLE,
  "cardiovasc_death_rate" DOUBLE,
  "diabetes_prevalence" DOUBLE,
  "female_smokers" DOUBLE,
  "male_smokers" DOUBLE,
  "handwashing_facilities" DOUBLE,
  "hospital_beds_per_thousand" DOUBLE,
  "life_expectancy" DOUBLE,
  "human_development_index" DOUBLE
);

People Fully Vaccinated Covid

@kaggle.pranjalverma08_coronavirus_covid19_indepth_dataset.people_fully_vaccinated_covid

60.6 kB
7,967 rows
4 columns

CREATE TABLE people_fully_vaccinated_covid (
  "entity" VARCHAR,
  "code" VARCHAR,
  "day" TIMESTAMP,
  "people_fully_vaccinated" BIGINT
);

People Vaccinated Covid

@kaggle.pranjalverma08_coronavirus_covid19_indepth_dataset.people_vaccinated_covid

82.13 kB
10,412 rows
4 columns

CREATE TABLE people_vaccinated_covid (
  "entity" VARCHAR,
  "code" VARCHAR,
  "day" TIMESTAMP,
  "people_vaccinated" BIGINT
);

Positive Rate Daily Smoothed

@kaggle.pranjalverma08_coronavirus_covid19_indepth_dataset.positive_rate_daily_smoothed

79.37 kB
46,522 rows
4 columns

CREATE TABLE positive_rate_daily_smoothed (
  "entity" VARCHAR,
  "code" VARCHAR,
  "day" TIMESTAMP,
  "short_term_positivity_rate" DOUBLE
);

Public Gathering Rules Covid

@kaggle.pranjalverma08_coronavirus_covid19_indepth_dataset.public_gathering_rules_covid

28.12 kB
93,660 rows
4 columns

CREATE TABLE public_gathering_rules_covid (
  "entity" VARCHAR,
  "code" VARCHAR,
  "day" TIMESTAMP,
  "restriction_gatherings" BIGINT
);

School Closures Covid

@kaggle.pranjalverma08_coronavirus_covid19_indepth_dataset.school_closures_covid

32.73 kB
89,983 rows
4 columns

CREATE TABLE school_closures_covid (
  "entity" VARCHAR,
  "code" VARCHAR,
  "day" TIMESTAMP,
  "school_closures" BIGINT
);

Share People Fully Vaccinated Covid

@kaggle.pranjalverma08_coronavirus_covid19_indepth_dataset.share_people_fully_vaccinated_covid

28.55 kB
7,967 rows
4 columns

CREATE TABLE share_people_fully_vaccinated_covid (
  "entity" VARCHAR,
  "code" VARCHAR,
  "day" TIMESTAMP,
  "people_fully_vaccinated_per_hundred" DOUBLE
);

Share People Fully Vaccinated Covid 1

@kaggle.pranjalverma08_coronavirus_covid19_indepth_dataset.share_people_fully_vaccinated_covid_1

28.55 kB
7,967 rows
4 columns

CREATE TABLE share_people_fully_vaccinated_covid_1 (
  "entity" VARCHAR,
  "code" VARCHAR,
  "day" TIMESTAMP,
  "people_fully_vaccinated_per_hundred" DOUBLE
);

Share People Vaccinated Covid

@kaggle.pranjalverma08_coronavirus_covid19_indepth_dataset.share_people_vaccinated_covid

43.43 kB
10,412 rows
5 columns

CREATE TABLE share_people_vaccinated_covid (
  "entity" VARCHAR,
  "code" VARCHAR,
  "day" TIMESTAMP,
  "people_vaccinated_per_hundred" DOUBLE,
  "n_145610_annotations" VARCHAR  -- 145610-annotations
);