2019 Novel Coronavirus (2019-nCoV) is a virus (more specifically, a coronavirus) identified as the cause of an outbreak of respiratory illness first detected in Wuhan, China. Early on, many of the patients in the outbreak in Wuhan, China reportedly had some link to a large seafood and animal market, suggesting animal-to-person spread. However, a growing number of patients reportedly have not had exposure to animal markets, indicating person-to-person spread is occurring. At this time, it’s unclear how easily or sustainably this virus is spreading between people – CDC
This dataset has daily level information on the number of confirmed cases and deaths from the 2019 novel coronavirus. Please note that this is a time series data and so the number of cases on any given day is the cumulative number.
The data is available from 3rd Jan, 2020 to 6th October, 2020.
In order to get the right information, I looked for data as well as visualization on World Health Organisation website.
This interactive dashboard/map provides the latest global numbers and numbers by country of COVID-19 cases on a daily basis. However, the data seemed clustered on one page and the colours don’t really help differentiate.
The best source to get real time data on coronavirus would be the World Health Organisation.
I downloaded the daily data on Covid -19 confirmed cases and deaths – worldwide from 3rd Jan, 2020 to 6th October 2020.
The data was refined and very well captured thus, I imported the data directly to Tableau.
With the help of tableau I was able to turn the data into actionable insights with speed and ease. It was as simple as dragging and dropping. Tableau already comes with a preset of visualization, which you can choose from according to the information that you want to represent.
The visualisation had to be put out in a simpler way thus, the colors that were used are bright and bold with a dark background to depict the meaning of the data at first glance.
The blue color shows the cumulative of confirmed cases and the cumulative deaths are shown in red color.
The visualization is divided in three parts, however it was put on a single story/dashboard.
- The global number of confirmed coronavirus cases and deaths worldwide on 6th October 2020.
- Growth in the number of confirmed coronavirus cases and deaths worldwide from 2nd Jan 2020 to 6th October 2020.
- Top 10 countries with the highest number of confirmed coronavirus cases and deaths.
Global number of confirmed coronavirus cases and deaths worldwide on 6th October, 2020.
The visualization makes it easy for users to interpret the data worldwide on coronavirus. The colours help the users differentiate as to what information they are looking at and the sizing of the circles helps the user understand how badly the country has been affected.
As seen in the visualisation – United States of America, India and Brazil look the worst affected countries indicated with a big circle which is interactive – when you hover on it shows the data of the cumulative coronavirus confirmed cases and deaths dates 6th October, 2020.
Growth in the number of confirmed coronavirus cases and deaths worldwide from 2nd Jan, 2020 to 6th October, 2020.
This visualization makes it easy for a user to understand the growth in the number of confirmed coronavirus cases and deaths in a period of time.
As seen in the visualisation which is interactive – when you hover on it shows the data of the cumulative coronavirus confirmed cases and deaths on a specific date.
Top 10 countries with the highest number of confirmed coronavirus cases and deaths.
As seen in the visualisation which is interactive – when you hover on it shows the data of the cumulative coronavirus confirmed cases and deaths dated 6th October, 2020.
Using Tableau Software was super fun. It is one of the most user-friendly data visualization tools available. It requires minimal technical knowledge (assuming the data has been cleaned and prepped) and the only coding required adopts a similar syntax to that of Python’s!
Tableau is the type of tool that you can pick up right away and start exploring and building dashboards. However it does have advanced capabilities that require experience and training.
In future, I’d like to understand how to make animations on the dashboard. Example I could show the top 10 countries fluctuating with the total number of cases from a set point of date to the end point.