For anyone interested in COVID-19 data analysis, I will be running a study group on that very topic, starting Monday, September 28! It will accompany my course on Wolfram U, which I highly encourage you to watch.
Sign up here for the study group.
Do you have anything specific you would like to see covered? Let me know.
Challenge #1: using epidemic dataset, find the top 20 US counties with largest confirmed cases (Hint: use TakeLargestBy on the last value of confirmed cases for US counties)
Challenge #2: using epidemic dataset, find the top 10 US states with largest confirmed cases per 10,000 inhabitants (Hints: find US state population using entities)
Challenge #3: using epidemic dataset, generates a plot in which the US states are colored according to the last values of confirmed cases per 100,000 inhabitants (Hint: use GeoRegionValuePlot)
Thanks a lot for letting us know. The quotation marks seem to have been lost with deployment. Question 2 is also meant to not include the “nucleotide status is complete” requirement. We will get this straightened out as soon as possible.
While completing the quiz, I have noticed that you mention SEIRQD model. Can you briefly explain what Q represents? If you have any modified epidemic models that you haven’t showed us in the daily study group program, would you be willing to share with me or suggest a more advanced reference?
(It’s been a great opportunity to learn more about Wolfram Language and how to use it to analyze the current pandemic situation through both modeling and estimating parameters. Thanks for offering and leading this informative course) .
Thanks.
On the Quiz @ P1, it seems the answer is missing the constraint …'for the 10 states with the most COVID-19 confirmed cases". Using the hint from Challenge#1 above, I believe the ‘All’ should be replaced by:
Is there a better way to extract the keys in each of the COVID-19 datasets. I used the following but it does not work very well as I need to separate out the ResourceType Function from the list of datasets. I’m looking for a data set with patient related data like blood type.