World wide COVID-19 Pandemic dataset

This dataset contains COVID-19 information of 212 countries from December 31, 2019, to September 27, 2020.

covid_raw

Format

Data frame with columns

iso_code, continent, location

Location information

date

Date in YYYY-MM-DD format.

total_cases, new_cases, new_cases_smoothed, total_cases_per_million, new_cases_per_million, new_cases_smoothed_per_million

Case-related numbers

total_deaths, new_deaths, new_deaths_smoothed, total_deaths_per_million, new_deaths_per_million, new_deaths_smoothed_per_million

Death-related numbers

new_tests, total_tests, total_tests_per_thousand, new_tests_per_thousand, new_tests_smoothed, new_tests_smoothed_per_thousand, tests_per_case, positive_rate, tests_units

Test-related numbers

Source

Our World in Data https://ourworldindata.org/coronavirus

Details

The data contains the daily summary of COVID-19 cases (confirmed and death), by country.

Examples

library(COVID19dashboard)
covid_raw
#> # A tibble: 46,484 x 41
#>    iso_code continent location date       total_cases new_cases new_cases_smoot…
#>    <chr>    <chr>     <chr>    <date>           <dbl>     <dbl>            <dbl>
#>  1 AFG      Asia      Afghani… 2019-12-31           0         0               NA
#>  2 AFG      Asia      Afghani… 2020-01-01           0         0               NA
#>  3 AFG      Asia      Afghani… 2020-01-02           0         0               NA
#>  4 AFG      Asia      Afghani… 2020-01-03           0         0               NA
#>  5 AFG      Asia      Afghani… 2020-01-04           0         0               NA
#>  6 AFG      Asia      Afghani… 2020-01-05           0         0               NA
#>  7 AFG      Asia      Afghani… 2020-01-06           0         0                0
#>  8 AFG      Asia      Afghani… 2020-01-07           0         0                0
#>  9 AFG      Asia      Afghani… 2020-01-08           0         0                0
#> 10 AFG      Asia      Afghani… 2020-01-09           0         0                0
#> # … with 46,474 more rows, and 34 more variables: total_deaths <dbl>,
#> #   new_deaths <dbl>, new_deaths_smoothed <dbl>, total_cases_per_million <dbl>,
#> #   new_cases_per_million <dbl>, new_cases_smoothed_per_million <dbl>,
#> #   total_deaths_per_million <dbl>, new_deaths_per_million <dbl>,
#> #   new_deaths_smoothed_per_million <dbl>, new_tests <lgl>, total_tests <lgl>,
#> #   total_tests_per_thousand <lgl>, new_tests_per_thousand <lgl>,
#> #   new_tests_smoothed <lgl>, new_tests_smoothed_per_thousand <lgl>,
#> #   tests_per_case <lgl>, positive_rate <lgl>, tests_units <lgl>,
#> #   stringency_index <dbl>, population <dbl>, population_density <dbl>,
#> #   median_age <dbl>, aged_65_older <dbl>, aged_70_older <dbl>,
#> #   gdp_per_capita <dbl>, extreme_poverty <dbl>, cardiovasc_death_rate <dbl>,
#> #   diabetes_prevalence <dbl>, female_smokers <dbl>, male_smokers <dbl>,
#> #   handwashing_facilities <dbl>, hospital_beds_per_thousand <dbl>,
#> #   life_expectancy <dbl>, human_development_index <dbl>