Analyzing COVID-19 US data with Tableau and creating Dashboards
Being a Business Analytics graduate student, I’ve always leveraged python’s open libraries: Matplotlib, Ggplot, Bokeh and Seaborn for data visualizations. From data analytics and visualization point of view these libraries are remarkable but the lengthy code part can sometimes be a tad time consuming. This is where Tableau comes in handy. A no-code interactive data visualization software that is useful for creating dashboards and analyzing data for data-driven decision making of a business.
Dataset
To illustrate how easy it is to use Tableau, we’ll create a dashboard and conduct analysis on the COVID-19 in USA dataset available on Kaggle. This data is obtained from COVID-19 Tracking project and NYTimes and has information on COVID-19 cases from 50 US states and the District of Columbia at daily level.
Getting started with Tableau
To get started with Tableau you can either download Tableau Desktop (the paid version) or Tableau Public (the free version). With Tableau Public you can use most of the software functions, however, the only caveat is it does not allow you to save your workbooks locally.
Creating Heatmaps, Charts and Graphs
After uploading the data on Tableau the next step is to create relevant charts and graphs on worksheets.
Tip: A brief Tableau tutorial that covers the basic Tableau functionality like uploading & cleaning the data, working on worksheets, formatting and creating charts and graphs.
Creating a Dashboard
The worksheets created can then be compiled together on a dashboard.If you closely look at the dashboard you’d see that we’re able to select a particular date, a state or multiple states to visualize Total Cases, Total Positive Cases, Total Recovered Cases, Daily Positive Cases and Daily Deaths all at once.
We can also select a state by just clicking on the bubble (belonging to that state) drawn on the map.
Currently the dashboard shows the Total Cases, Total Positive Cases, Total Recovered Cases, Daily Positive Cases and Daily Deaths for all the states in the US. We can clearly see how the daily positive cases and daily deaths started rising in March end, the reason why most of the states issued lockdown orders. After over 2 months of lockdown the cases appear to decrease, also the time when most states eased down on the lockdown orders and scheduled their Phase-I reopening.
Here’s a quick tutorial on creating the above dashboard in under 4 minutes
One can create multiple dashboards and add them as tabs. Another way of presenting multiple tabs in Tableau is by using the “Story” option. For the purpose of our analysis, I’ve created another dashboard - a heatmap for the Toal Tests Conducted Daily in the 50 US states.
Insights
Let’s have a look at few states:
New York (NY)
- The Daily Positive Cases appears to be low in March, but starting April beginning there was an exponential rise. One of the reasons for the low daily positive cases, as per the heatmap, can be the fact that the number of tests conducted in March were significantly low.
- The Daily Positive Cases and Daily Deaths were significantly high during the month of April and May, which is when the state issued the lockdown order and banned international travel.
- Mid May onwards the number of cases started to decrease and June 8th the state scheduled it’s Phase-I reopening.
Washington (WA)
- In January, Washington was the first state to announce a confirmed coronavirus case. And since Jan, the state experienced an exponential rise both in Daily Positive Cases and Daily Deaths. Finally in mid March, the state prohibited gatherings of over 250 people followed by lockdown order. Between mid March and May number of cases were flat but is experiencing a spike after reopening.
California (CA)
- California was the first state in US to order lockdown in March. Consequently, the cases were significantly low. But as the restrictions to curb the pandemic are being relaxed across US, California, Texas and few other states have recorded their worst week yet for new coronavirus infections.
Conclusion
Tableau is a great and easy to learn business intelligence software that helps businesses in making better data driven-decisions. Apart from its diverse visualizations advantages, Tableau easily integrates with Python and R. This functionality offers people the flexibility to directly import Python and R scripts in Tableau and take advantage of its visualizations. If you’re interested in learning more about Tableau, check out the free learning videos on their website.
Happy learning!