COVID-19 PROJECT
Introduction
In our world today, we have been going through a global pandemic for many months. With all the data obtained from this pandemic, I was interested in what insights I could get from all of the data which is why I decided to explore the data using SQL Server and visualize it with a dashboard in Tableau. I take a look into the tests, cases, deaths and vaccinations with a focus in the different countries, continents and globally to learn about how these things evolved over the months and how it differs between each area. In this project, some skills I used from SQL include aggregate functions, joins, window functions, subqueries and CTEs/with functions to achieve my objectives.
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Link for Data: https://ourworldindata.org/covid-deaths
Data Exploration using SQL Server
Link to SQL Code: https://github.com/tracylam1/Portfolio/blob/main/CovidSQLExploration.sql
In this section, I will be going over some of the queries I used to explore the COVID-19 data.
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In the code below, I am focusing on the different countries. In these queries, I wanted to take a look at the amount of tests given out, the rate of getting COVID and the total amount of deaths in each country. In these queries, I used aggregate functions to get the information I needed. As a result of these queries, we can see that the United States was on the top for all of the questions I had. India is also quite high up also in terms of tests, infection rate and death count. These results are quite expected as we can see some daily news reports.
In the queries below, I am focusing on how often the vaccine is taken among the different continents. I wanted to take a look at the continents rather than the countries since I have heard about many continents not having as much access to the vaccine as others. As we can see from the results of the queries below, as expected, North America had the highest vaccination rates with both single and double doses. As seen from living in America, the vaccine is very accessible as it is free and there are many stations throughout the nation for people to get the vaccine unlike other continents where it is very difficult to obtain a single dose as I have commonly seen through the news.
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In the queries below, I am utilizing joins and subqueries to fulfill my objective. I used an inner join so that I did not have any missing information between the deaths and vaccinations. I also used a subquery in my second query so that I could use the information I got from my subquery to achieve my question.
In the code below, I am using a CTE/with function to find the death rate from each case by each day at each location. My first query was a way for me to check if the query is working properly for the with function since there is a window function within this query. After doing so, I used the CTE to make an addition calculation to the results of the query inside the CTE. I did not include the picture of the results since it is too long; however, the death rate fluctuates in certain periods of time. For instance, when the vaccine came out, we saw that the deaths started to somewhat decrease especially in the USA.
Data Visualization using Tableau
Dashboard Link: https://public.tableau.com/app/profile/tracy.lam/viz/COVIDDataVisualization_16282972610740/Dashboard1
In this section, I will be showcasing my Tableau dashboard about COVID-19. To have an interactive and better view, click the link above.
In the dashboard below, I focused on deaths, cases and vaccinations again. For the 'Top 7 Countries Avg Cases' section, I decided to use a line graph since I believe that it is a good way to showcase the progression of COVID cases through the months starting from January 2020. As seen in the graph, a lot of countries had a peak where cases were high; however, it appears to decreases in majority of the countries. For the United States, the cases had decreased but is starting to pick back up again. We can also see that based on the bar chart, China, India and the U.S. has administer a lot of vaccines.
