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