Are you doing data science? Statistics? No?
Then for god’s sake don’t use pandas, you just look dumb af when you pull several MB of a package just to load csv. If you find yourself doing that, just stop programming and look for another job
Thanks for attention
If you find yourself doing that, just stop programming and look for another job
I don’t think that is an appropriate response to someone misunderstanding a package. Just educate them in a kind and respectful manner and they’ll learn.
fair enough.
For those that don’t know, the standard library includes a
csvpackage so you can justimport csv.Documented at https://docs.python.org/3/library/csv.html
I use
DictReaderall the time, along with a library to hande the type detection. This is the way to go, especially if you need to process line by line or filter columns and rows out first.Regardless, I’ll avoid pandas wherever I can. It’s not something I want in production level code if I can help it.
Wait what, people are loading data from csv in their websites?
Makes sense if you want to give the user the ability to import data from csv (see django import export package). Beyond importing data from user or another service i dont see other uses, but they do exist.
Pandas is more efficient than Python at operating on large datasets. Can you suggest alternarives?
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