D.F.

Covid19 Data Exploration

3d computer image of the SARS-COV2 virus

Infection and death information

Tableau Public Viz

Summary:

This project contains my exploration into Covid19 infections and deaths data. It consists of getting data from the Our World in Data website and processing the downloaded spreadsheet into smaller spreadsheets. I separated the deaths data from the infections data and saved it as a separate Excel file. Then I uploaded the spreadsheets into BigQuery to explore the data with SQL queries. Finally I exported the resulting tables for use in the Covid data visualization project. I followed Alex the Analyst's YouTube video to complete this project. In the future I plan on exploring the data further to determine how different comorbidities affected a patient's outcome.

Data Source:

Our World in Data website (August 22, 2023).

Skills & Programs Used:

  • Excel
  • Data Exploration

Process

Gather Data

Download the data from the Our World in Data Covid 19 webpage.

Separate The Data

Open the dataset in Excel and separate deaths and infection data.

Explore the Covid deaths dataset

Upload the Covid deaths dataset into BigQuery and use queries to explore the data.

Explore Covid19's global impact

Determine the global scale of the pandamic by

Join the two tables together

Explore the total dataset by joining the vaccination table with the death table.

Calculate the max covid vaccination percentage

Craeate a temp table (CTE) to view the max vaccination percentage.

Prep data for Tableau Viz

Export the tables with calculated values as Excel spreadsheets.

Upload to GitHub

Upload the project's SQL queries to the project's GitHub page.

Results

The data set contained data from January 3, 2020 to August 16, 2023. The dataset contained 67 fields. The dataset was separated into two Excel spreadsheets, one relating to Covid19 deaths and the other to Covid19 vaccinations. The Covid19 deaths Excel spreadsheet contained all columns from the start of the dataset to the weekly_hosp_addmissions_per_million column. The Covid19 vaccinations spreadsheet included the first 4 columns (iso_code, continent,location, date) and all columns after the weekly_hosp_addmissions_per_million column. There was a total of 334,304 line items. Most countries did not start counting Covid19 cases until March 2020 and changed from daily to weekly counts in April 2023.

The columns calculated in this project were:

  1. DeathRate ( percent of infected population that died),
  2. PopulationPercent (percent of the population that got Covid19),
  3. HighestInfectionCount (max number of total cases per location),
  4. PercentPopulationInfected (max PopulationPercent per location),
  5. TotalDeathCount (max total deaths per location),
  6. Total_Cases (sum of all cases),
  7. Total_Deaths (sum of all deaths),
  8. DeathPercentage (death percentage of infected population of the world),
  9. VaccinatedPopulationPercent (percentage of vaccinated population by location).

Future Posibilities

  • Determine how different comorbidities affected a patient's outcome.
  • Check for updates to the dataset.
  • Redo the project in MS SQL Server.