In the COVID-19 repository I share a set of little software tools written in Python to visualize the evolution of the COVID-19 outbreak around the world. They are design to show data from the next databases:
I load the data from the National reports by Ministerio de Salud de la Nación Argentina manually in a spreadsheet exported to a csv file afterwards. Note that this file has a lot of holes because the reports are not complete (some data is not separated by province). Confirmed cases and deaths series are complete, but active cases, laboratory tests and dropped cases are not. If there is a difference between the total and the sum of all districts I add it in UNKNOWN field. To visualize data from 2019 Novel Coronavirus COVID-19 (2019-nCoV) Data Repository by Johns Hopkins CSSE or from the Datasets in datos.gob.ar you need to download the data first. Data on Argentina.csv is processed and save to a set of csv files with disctint information. For example: daily confirmed cases, daily deaths or dialy confirmed cases trend (taking averages for 3 o 5 days).
You can obtain different charts to visualize the data. You can plot the data by date or aligning it when a certain condition is fulfilled (selected number of confirmed cases or deahts). You can control which charts to show/save with a set of booblean varialbles you will find in the code. I save some of them in Argentina_Data/actual_charts.
The csv files and the charts made to show the data for the outbreak evolution in Argentina contains certain categories. Understand each one clearly is important to get the facts right. Take into account these definitions:
Now you can go back to home or continue to the blog. You can send your comments and questions to my mailbox too.