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pandas is uniquely terrible and to this day I cant understand why it's so popular.
If you want your data to be mangled beyond recognition with no way to debug why, pandas is for you!
If you only want to be able to process datasets that can fit into memory, pandas is for you!
If you like debugging OutOfMemory errors in pipelines at 2am because some genius on your team thought the source data would always fit into memory.... you guessed it! pandas is for you! -
@unsignedint I'm rolling my own. I'm far enough along programming-wise that it is within reach.
Never though I'd be able to write that, but here I am. -
@donkulator neither do I, and yet pandas do suck my balls.
If only pandas did what pandas was supposed to do, without all the ball sucking. But because pandas sucks so bad, I might as well have pandas suck on my balls.
No questions asked
As a Python user and the fucking unicode mess, this is sooooo mean!
I just started working on a little project to browse devrant from terminal. It converts images to ascii art!
pandas can suck my balls.
N
I
H
I'd rather roll my own.
edit: but also xgboost can suck my balls.
Treating every OBVIOUSLY continuous-valued entry as a 'category'.
All searches for this problem turn up tutorials and documentation on how to CONVERT continuous and numeric values into classes or categories.
Not a single fucking document addresses the problem of when pandas or xgboost refuses to treat numeric inputs as numerics and insists on pushing an error that your data is categorical when every fucking inspection shows the type as numeric.
rant
python
pandas
suck my balls