Covid cases project

It’s a simple project, I used some matplotlib, and pandas to analyze the data and make some graphs.
Any feedback is welcome
PD: I don’t know how to show properly, its a jupyter notebook file. If you click the link it will be shown properly

Ah, nice one. I like it. I don’t think there’s a proper way to show a .ipynb file on the forums and for something this size it’s better off on something like github anyway.

Since this is publicly available it would be worth adding a README with some details about the project. A basic description of what your repo is about and where the data is from would be an good start; have a web search if you want to expand on it.

I think most of my comments are on presentation so they’re very much opinion based and optional, perhaps you’d rather keep your current style.

If you’re using a pie chart then consider also adding some numerical or percentage values for (active, recovered, deaths) as interpreting the relative size of the slices can be quite difficult. If the labels become too big consider a label/key.

Could the timestamp: 1607120880000 be formatted to a more human readable version? Perhaps a similar thing might be useful for the larger case numbers too (4395389234 could be 4.40 e9 or 4.40 (B)illion for example) but that’s up to you. I believe pandas has some methods for just this purpose.

Unless it’s incredibly obvious what the data is then an x-axis label on some of the barplots would be helpful (at a glance the viewer should be able to tell what’s plotted). I think you could expand on your titles a little and consider removing any abbreviations that aren’t obvious.
“Comparison of deaths in Brazil and Argnetina” tells me exactly what the plot is before I even look at the actual figure.

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Thanks so much for the feedback. I wanted to make the timestamp more readable but i don’t know how to do it, I don’t know how is formatted either. If you could help me with that, I would greatly appreciate it. Thanks again for the feedback! I will upload the project as soon as I can

Well it looks like UNIX epoch time but there seem to be a few extra zeros (compared to a timestamp in seconds) so best check the docs for your covid library if you wanted to double check the dates for the sake of your sanity.
A pretty quick web search will land you the relevant links for rounding and conversion. Here’s something from the panda docs on time formatting

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