Data Visualization of COVID-19

Fawwaz
5 min readMay 31, 2021

Hello, Guys!!! This is my first article in Medium, I would like to introduce myself! I am Fawwaz, I’m a Data Enthusiast and a language-learner, I really like to learn new things (especially language!).

So, I think that’s a proper way to introduce myself, right?

Let’s jump straight to the topic, in this article, I would like to visualize a Data about COVID-19 (Something that’s shock the world lately). I use the data from the sources like WHO, CDC and the Ministry of Health from Multiple countries.

In this article, you will visualize COVID-19 data from the first several weeks of the outbreak to see at what point this virus became a global pandemic.

Please note that information and data regarding COVID-19 is frequently being updated. The data used in this project was pulled on March 17, 2020, and should not be considered to be the most up to date data available.

Started by loading the library

Then, print out the data that we have to the Notebook (I only insert the first 5 rows of the data, due to the insufficient space and memory of Medium).

The people who got affected by the COVID-19 from WHO, CDC and Ministry of Health

The table above shows the cumulative confirmed cases of COVID-19 worldwide by date. Just reading the numbers in the table makes it hard to get a sense of the scale and growth of the outbreak.

Now, this is a line plot to visualize the confirmed cases worldwide, notice how it rapidly increasing day by day

Cumulative confirmed cases Feb-Mar

The y-axis in that plot is pretty scary, with the total number of confirmed cases around the world approaching 200,000. Beyond that, some weird things are happening: there is an odd jump in mid February, then the rate of new cases slows down for a while, then speeds up again in March. We need to dig deeper to see what is happening.

Early on in the outbreak, the COVID-19 cases were primarily centered in China. Let’s plot confirmed COVID-19 cases in China and the rest of the world separately to see if it gives us any insight.

Wow! The two lines have very different shapes. In February, the majority of cases were in China. That changed in March when it really became a global outbreak: around March 14, the total number of cases outside China overtook the cases inside China. This was days after the WHO declared a pandemic.

There were a couple of other landmark events that happened during the outbreak. For example, the huge jump in the China line on February 13, 2020 wasn’t just a bad day regarding the outbreak; China changed the way it reported figures on that day (CT scans were accepted as evidence for COVID-19, rather than only lab tests).

There is a clear surge of cases around February 13, 2020, with the reporting change in China. However, a couple of days after, the growth of cases in China slows down. How can we describe COVID-19’s growth in China after February 15, 2020?

From the plot above, the growth rate in China is slower than linear. That’s great news because it indicates China has at least somewhat contained the virus in late February and early March.

How does the rest of the world compare to linear growth?

From the plot above, we can see a straight line does not fit well at all, and the rest of the world is growing much faster than linearly. What if we added a logarithmic scale to the y-axis?

With the logarithmic scale, we get a much closer fit to the data. From a data science point of view, a good fit is great news. Unfortunately, from a public health point of view, that means that cases of COVID-19 in the rest of the world are growing at an exponential rate, which is terrible news.

Not all countries are being affected by COVID-19 equally, and it would be helpful to know where in the world the problems are greatest. Let’s find the countries outside of China with the most confirmed cases in our dataset.

Even though the outbreak was first identified in China, there is only one country from East Asia (South Korea) in the above table. Four of the listed countries (France, Germany, Italy, and Spain) are in Europe and share borders. To get more context, we can plot these countries’ confirmed cases over time.

From the above table, Italy has been the worst countries that got affected by COVID-19, the stats show that it rapidly increasing and it could be one of the worst countries that struck by COVID-19.

So, that’s it guys! I hope you enjoy reading and understanding this article! I hope we all can get through this pandemic, bless you all!

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Fawwaz

Entrepreneur, Data Enthusiast and whatever you wanna call me!