Might any kind soul out there be willing to help me write some code in either Python or R?
Everything I've found so far online about Time Series is always about FORECASTING, yet I'm just here trying to compare what's already happened.

I'm looking at the "audio features" of Spotify's Top 200 from 2018 until late 2021.
My two objectives are:
1) How to assess whether # of Covid cases/deaths had/has any significant effect on the daily averages for each country's features?
2) How to check if the average audio scores are different now/"post"-Covid than they were in the ~2 control years before it?

Here's a sample of the data for anyone willing to take a crack at it –

https://mega.nz/file/Q4JFBA7K#7zBGP4gJe_FwKUjJakI-yZoit6RvYOZy1VeKKo9Fohg

{There I've aggregated the Top200 of each country/day into 1 row of its averages, and the numbered columns like C1, C2, E1, etc. (the ones without the descriptors in the title) I was planning on having be dummy variables to do some regression or something}

Thank you greatly, everyone. I hope you stay well!