Davin Lawrence

Visualizing Covid 19

Using Pandas and Altair to visualize the spread of COVID-19.


Update: The data on this page is no longer being updated. I made this dashboard as a way to visualize the data early on in the pandemic. I could not find a source that was visualizing on the county level. As the pandemic shows no signs of slowing down, there have been a myriad of more full featured dashboard and visualizations. The numbers are up to date as of August 20th, 2020.

Original Post

It goes without saying how serious the COVID-19 pandemic is and how it has fundamentally changed the way we live. In this time I have had off, I used this opportunity to deepen my knowledge of both the pandas and altair libraries to create this dashboard. All data is sourced from Jon Hopkins University. As of March 22nd, the university dropped robust support of tracking recoveries as there is discrepency in recoveries reporting across different countries. I have followed suit with this chart. The charts are updated daily at 12:15 AM GMT.

The source for this project can be found at my gitlab. The world chart currently supports zoom and panning on desktop, and will be supported on mobile in the near future. State chart with time series data will be available again soon.

The recent changes to the Jon Hopkins dataset includes county-level data for the United States which is a powerful way to track the spread in the United States. It also highlights how incomplete testing and data reporting is in the United States.

Because the underlying data groups New York City as one datapoint, the data for NYC has been split evenly between Kings, Queens, and Richmond County, New York.