Baselight

Covid-19 Deaths And Vaccinations Dataset

Analyze the data to find patterns and trends in Covid-19 deaths and vaccination

@kaggle.tohidkhanbagani_covid_19_deaths_and_vaccinations_dataset

Covid Vaccinations
@kaggle.tohidkhanbagani_covid_19_deaths_and_vaccinations_dataset.covid_vaccinations

  • 7.26 MB
  • 302749 rows
  • 45 columns
iso_code

Iso Code

continent

Continent

location

Location

date

Date

total_tests

Total Tests

new_tests

New Tests

total_tests_per_thousand

Total Tests Per Thousand

new_tests_per_thousand

New Tests Per Thousand

new_tests_smoothed

New Tests Smoothed

new_tests_smoothed_per_thousand

New Tests Smoothed Per Thousand

positive_rate

Positive Rate

tests_per_case

Tests Per Case

tests_units

Tests Units

total_vaccinations

Total Vaccinations

people_vaccinated

People Vaccinated

people_fully_vaccinated

People Fully Vaccinated

total_boosters

Total Boosters

new_vaccinations

New Vaccinations

new_vaccinations_smoothed

New Vaccinations Smoothed

total_vaccinations_per_hundred

Total Vaccinations Per Hundred

people_vaccinated_per_hundred

People Vaccinated Per Hundred

people_fully_vaccinated_per_hundred

People Fully Vaccinated Per Hundred

total_boosters_per_hundred

Total Boosters Per Hundred

new_vaccinations_smoothed_per_million

New Vaccinations Smoothed Per Million

new_people_vaccinated_smoothed

New People Vaccinated Smoothed

new_people_vaccinated_smoothed_per_hundred

New People Vaccinated Smoothed Per Hundred

stringency_index

Stringency Index

population_density

Population Density

median_age

Median Age

aged_65_older

Aged 65 Older

aged_70_older

Aged 70 Older

gdp_per_capita

Gdp Per Capita

extreme_poverty

Extreme Poverty

cardiovasc_death_rate

Cardiovasc Death Rate

diabetes_prevalence

Diabetes Prevalence

female_smokers

Female Smokers

male_smokers

Male Smokers

handwashing_facilities

Handwashing Facilities

hospital_beds_per_thousand

Hospital Beds Per Thousand

life_expectancy

Life Expectancy

human_development_index

Human Development Index

excess_mortality_cumulative_absolute

Excess Mortality Cumulative Absolute

excess_mortality_cumulative

Excess Mortality Cumulative

excess_mortality

Excess Mortality

excess_mortality_cumulative_per_million

Excess Mortality Cumulative Per Million

AFGAsiaAfghanistanFri Jan 03 2020 00:00:00 GMT+0000 (Coordinated Universal Time)nan54.4218.62.581.341803.99597.039.5937.750.564.830.51
AFGAsiaAfghanistanSat Jan 04 2020 00:00:00 GMT+0000 (Coordinated Universal Time)nan54.4218.62.581.341803.99597.039.5937.750.564.830.51
AFGAsiaAfghanistanSun Jan 05 2020 00:00:00 GMT+0000 (Coordinated Universal Time)nan54.4218.62.581.341803.99597.039.5937.750.564.830.51
AFGAsiaAfghanistanMon Jan 06 2020 00:00:00 GMT+0000 (Coordinated Universal Time)nan54.4218.62.581.341803.99597.039.5937.750.564.830.51
AFGAsiaAfghanistanTue Jan 07 2020 00:00:00 GMT+0000 (Coordinated Universal Time)nan54.4218.62.581.341803.99597.039.5937.750.564.830.51
AFGAsiaAfghanistanWed Jan 08 2020 00:00:00 GMT+0000 (Coordinated Universal Time)nan54.4218.62.581.341803.99597.039.5937.750.564.830.51
AFGAsiaAfghanistanThu Jan 09 2020 00:00:00 GMT+0000 (Coordinated Universal Time)nan54.4218.62.581.341803.99597.039.5937.750.564.830.51
AFGAsiaAfghanistanFri Jan 10 2020 00:00:00 GMT+0000 (Coordinated Universal Time)nan54.4218.62.581.341803.99597.039.5937.750.564.830.51
AFGAsiaAfghanistanSat Jan 11 2020 00:00:00 GMT+0000 (Coordinated Universal Time)nan54.4218.62.581.341803.99597.039.5937.750.564.830.51
AFGAsiaAfghanistanSun Jan 12 2020 00:00:00 GMT+0000 (Coordinated Universal Time)nan54.4218.62.581.341803.99597.039.5937.750.564.830.51

CREATE TABLE covid_vaccinations (
  "iso_code" VARCHAR,
  "continent" VARCHAR,
  "location" VARCHAR,
  "date" TIMESTAMP,
  "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,
  "excess_mortality_cumulative_absolute" DOUBLE,
  "excess_mortality_cumulative" DOUBLE,
  "excess_mortality" DOUBLE,
  "excess_mortality_cumulative_per_million" DOUBLE
);

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