COVID 19 Worldwide Case
COVID 19 dataset from Jan 1st, 2020 to Feb 8th, 2023
@kaggle.sandhyakrishnan02_latest_covid_19_dataset_worldwide
COVID 19 dataset from Jan 1st, 2020 to Feb 8th, 2023
@kaggle.sandhyakrishnan02_latest_covid_19_dataset_worldwide
There are two datasets.
Dataset Attribute Details:
iso_code: ISO 3166-1 alpha-3 – three-letter country codes
continent: Continent of the geographical location
location: Geographical location
date: Date of observation
total_cases: Total confirmed cases of COVID-19
new_cases: New confirmed cases of COVID-19
new_cases_smoothed: New confirmed cases of COVID-19 (7-day smoothed)
total_cases_per_million: Total confirmed cases of COVID-19 per 1,000,000 people
new_cases_per_million: New confirmed cases of COVID-19 per 1,000,000 people
new_cases_smoothed_per_million: New confirmed cases of COVID-19 (7-day smoothed) per 1,000,000 people
total_deaths: Total deaths attributed to COVID-19
new_deaths: New deaths attributed to COVID-19
new_deaths_smoothed: New deaths attributed to COVID-19 (7-day smoothed)
total_deaths_per_million: Total deaths attributed to COVID-19 per 1,000,000 people
new_deaths_per_million: New deaths attributed to COVID-19 per 1,000,000 people
new_deaths_smoothed_per_million: New deaths attributed to COVID-19 (7-day smoothed) per 1,000,000 people
excess_mortality: Percentage difference between the reported number of weekly or monthly deaths in 2020–2021 and the projected number of deaths for the same period based on previous years.
excess_mortality_cumulative: Percentage difference between the cumulative number of deaths since 1 January 2020 and the cumulative projected deaths for the same period based on previous years.
excess_mortality_cumulative_absolute: Cumulative difference between the reported number of deaths since 1 January 2020 and the projected number of deaths for the same period based on previous years.
excess_mortality_cumulative_per_million: Cumulative difference between the reported number of deaths since 1 January 2020 and the projected number of deaths for the same period based on previous years, per million people.
icu_patients: Number of COVID-19 patients in intensive care units (ICUs) on a given day
icu_patients_per_million: Number of COVID-19 patients in intensive care units (ICUs) on a given day per 1,000,000 people
hosp_patients: Number of COVID-19 patients in the hospital on a given day
hosp_patients_per_million: Number of COVID-19 patients in hospital on a given day per 1,000,000 people
weekly_icu_admissions: Number of COVID-19 patients newly admitted to intensive care units (ICUs) in a given week
weekly_icu_admissions_per_million: Number of COVID-19 patients newly admitted to intensive care units (ICUs) in a given week per 1,000,000 people
weekly_hosp_admissions: Number of COVID-19 patients newly admitted to hospitals in a given week
weekly_hosp_admissions_per_million: Number of COVID-19 patients newly admitted to hospitals in a given week per 1,000,000 people
stringency_index: Government Response Stringency Index: composite measure based on 9 response indicators including school closures, workplace closures, and travel bans, rescaled to a value from 0 to 100 (100 = strictest response)
reproduction_rate: Real-time estimate of the effective reproduction rate (R) of COVID-19.
total_tests: Total tests for COVID-19
new_tests: New tests for COVID-19 (only calculated for consecutive days)
total_tests_per_thousand: Total tests for COVID-19 per 1,000 people
new_tests_per_thousand: New tests for COVID-19 per 1,000 people
new_tests_smoothed: New tests for COVID-19 (7-day smoothed). For countries that don't report testing data on a daily basis, we assume that testing changed equally on a daily basis over any periods in which no data was reported. This produces a complete series of daily figures, which is then averaged over a rolling 7-day window
new_tests_smoothed_per_thousand: New tests for COVID-19 (7-day smoothed) per 1,000 people
positive_rate: The share of COVID-19 tests that are positive, given as a rolling 7-day average (this is the inverse of tests_per_case)
tests_per_case: Tests conducted per new confirmed case of COVID-19, given as a rolling 7-day average (this is the inverse of positive_rate)
tests_units: Units used by the location to report its testing data
total_vaccinations: Total number of COVID-19 vaccination doses administered
people_vaccinated: Total number of people who received at least one vaccine dose
people_fully_vaccinated: Total number of people who received all doses prescribed by the vaccination protocol
total_boosters: Total number of COVID-19 vaccination booster doses administered (doses administered beyond the number prescribed by the vaccination protocol)
new_vaccinations: New COVID-19 vaccination doses administered (only calculated for consecutive days)
new_vaccinations_smoothed: New COVID-19 vaccination doses administered (7-day smoothed). For countries that don't report vaccination data on a daily basis, we assume that vaccination changed equally on a daily basis over any periods in which no data was reported. This produces a complete series of daily figures, which is then averaged over a rolling 7-day window
total_vaccinations_per_hundred: Total number of COVID-19 vaccination doses administered per 100 people in the total population
people_vaccinated_per_hundred: Total number of people who received at least one vaccine dose per 100 people in the total population
people_fully_vaccinated_per_hundred: Total number of people who received all doses prescribed by the vaccination protocol per 100 people in the total population
total_boosters_per_hundred: Total number of COVID-19 vaccination booster doses administered per 100 people in the total population
new_vaccinations_smoothed_per_million: New COVID-19 vaccination doses administered (7-day smoothed) per 1,000,000 people in the total population
new_people_vaccinated_smoothed: Daily number of people receiving their first vaccine dose (7-day smoothed)
new_people_vaccinated_smoothed_per_hundred: Daily number of people receiving their first vaccine dose (7-day smoothed) per 100 people in the total population
population: latest available values of population
population_density: Number of people divided by land area, measured in square kilometers, most recent year available
median_age: Median age of the population, UN projection for 2020
aged_65_older: Share of the population that is 65 years and older, most recent year available
aged_70_older: Share of the population that is 70 years and older in 2015
gdp_per_capita: Gross domestic product at purchasing power parity (constant 2011 international dollars), most recent year available
extreme_poverty: Share of the population living in extreme poverty, most recent year available since 2010
cardiovasc_death_rate: Death rate from cardiovascular disease in 2017 (annual number of deaths per 100,000 people)
diabetes_prevalence: Diabetes prevalence (% of the population aged 20 to 79) in 2017
female_smokers: Share of women who smoke, most recent year available
male_smokers: Share of men who smoke, most recent year available
handwashing_facilities: Share of the population with basic handwashing facilities on-premises, most recent year available
hospital_beds_per_thousand: Hospital beds per 1,000 people, most recent year available since 2010
life_expectancy: Life expectancy at birth in 2019
human_development_index: A composite index measuring average achievement in three basic dimensions of human development—a long and healthy life, knowledge, and a decent standard of living.
Hasell, J., Mathieu, E., Beltekian, D. et al. A cross-country database of COVID-19 testing. Sci Data 7, 345 (2020)
Creative Commons BY license.
visualize the data with the dataset for insights.********
CREATE TABLE owid_covid_data (
"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,
"total_tests" DOUBLE,
"new_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,
"total_boosters" DOUBLE,
"new_vaccinations" DOUBLE,
"new_vaccinations_smoothed" DOUBLE,
"total_vaccinations_per_hundred" DOUBLE,
"people_vaccinated_per_hundred" DOUBLE,
"people_fully_vaccinated_per_hundred" DOUBLE,
"total_boosters_per_hundred" DOUBLE,
"new_vaccinations_smoothed_per_million" DOUBLE,
"new_people_vaccinated_smoothed" DOUBLE,
"new_people_vaccinated_smoothed_per_hundred" DOUBLE,
"stringency_index" 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,
"population" DOUBLE,
"excess_mortality_cumulative_absolute" DOUBLE,
"excess_mortality_cumulative" DOUBLE,
"excess_mortality" DOUBLE,
"excess_mortality_cumulative_per_million" DOUBLE
);Anyone who has the link will be able to view this.