Coronavirus (COVID-19) Deaths

(Technology: Excel, SQL)

In this project I dove into the COVID-19 deaths dataset from https://ourworldindata.org/covid-deaths. The data in this dataset explores the COVID-19 related deaths from January 3, 2020 to December 13, 2023. 

First I tried to get the sense of the data using Excel and then to explore the dataset even more I used SQL.

After downloading the data,  the whole dataset was divided into two Excel spreadsheets: one containing the population deaths information other one containing vaccinations information. And the reason for doing so, was to be able to use JOINS in SQL later on. 

Once I had the excel files ready, I went ahead and created the Database in SQL Server Management Studio and  imported the excel files into that newly created Database in the form of tables. 

Next, to see if the imported data make sense I will run Select * query from both tables (CovidDeaths table, CovidVaccinations table). Based on the query results the output does make sense, meaning I could move on with the rest of the project.

Next, I am going to dig into the data by writing different queries. 

So my first official query would be to find out the Death Percentage, and what I mean by that is I want to know how total deaths and total cases in one country are related. For that, I will take the total death and divide it by total cases for the same country.

Note: As you can see in the above mentioned queries I used CAST () function to change the data type in total_deaths column from nvarchar(255) to float. The reason for doing so is because otherwise it was giving me an error :) In the query I also filtered for United States (Where location = 'United States'), but if you want to see the results for every country in the dataset you could skip this filtering. Or if you want to filter for any other country, you could put that country's name instead of United States. 

My next question would be to find the percent of population who got covid versus the total population of that same country. For that, I will take the total cases and divide it by total population for the same country.

Note: As you can see in the above mentioned queries I filtered for continent (Where continent is not null). The reason for doing so was because in some places in this dataset I had continent = NULL and in those cases the location would have continent's name. I hope I didn't get you more confused than you initially were :) ok let me show you an example of how it would look like if I didn't add filter to the query.  I will also add continent column to the Select clause so it is even more clear :)

Here, I want to find countries with Highest Infection Percent of Covid-19 compared to its total population. I am going to use aggregate functions in the following query. 

Next I want to find Total Deaths Count for the continent. In order to do so I am going to use an aggregate function MAX as before and I am going to change the data type (total_deaths) using CAST function.  

In the following query I want to see Death Percentage in the World. As you can see below I have used Sum(new_cases) aggregate function to find the total number of cases and I did the same with new_deaths column to get total deaths.  

Next, I want to find what the daily total number of vaccinated people vs total population of every country in the World. I am going to use Sum aggregate function on new_vaccinations column to get the total number of vaccinated people. I am also converting the data type of that same (new_vaccinations) column to float using CAST function. Then by using OVER clause with PARTITION BY subclause I am going to get the total number of vaccinations by location over time. 

Now, instead of daily total number of vaccinated people vs total population of every country in the World I want to find the Percentage of those same people. For that I am going to use CTE (Common Table Expression) to store the result of PopvsVac query, so I can reference it later in the main query.

Here I am going to do the same thing as above but using Temp table (temporary table) to store needed data temporarily.

Last but not the least I am going to create a Views (VaccinatedPopulation)

Thank you for taking time and going over my project.