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Notes -
I personally think copying and pasting data into your python file (takes maybe 5 seconds?) is more convenient than downloading the file, copying the file path into your text editor, and then (the real pain point) learning how pandas handles "sheets" (I expect I'm not alone in not knowing how to do that).
As a data scientist, I'm cringing at the thought of anyone doing that (but that's more of my problem than yours), but no point in being elitist about a twitter survey. A good 95% of the time, I work with datasets so large that you would have to be a madman to even think about manually copy-pasting data in, on top of all the other reasons you don't manually copy paste in data. But I would do it the hard way just because.
Moreover, you don't really need to download the data. the
read_csv()function can parse web hosted files, and if its more complicated, you can use the requests module, and if its still a pain, there are packages to read google sheet data. As for pandas parsing sheets, it's a keyword argument into theread_<filetype>function. In the case of google sheets, you can specify it in the API endpoint.Damn - TIL
Pandas is a powerful library.
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