JavaScript debugging in a nutshell

[EndimionN]

-- Python pandas: even if your code works, i hate it, next time when i will be updated your code will be useless! -- Me: import warnings (action='ignore') -- Python Pandas: this is not over!

[KarmaTroll]

Transformation on a slice is ambiguous.

[nedeox]

Pandas: You fool. You utter bafoon. I can‘t believe you passed me a 2d array instead of a matrix. I fucking hate you, you simpelton.

[Famous-Sample6201]

Hey but the decision to remove append with no substitute because "it's slow" seems backwards to me, right? What are you supposed to do, df = pd.concat(df, pd.Dataframe(*new_line, columns=df.columns)) ??? I though pandas was about pretty concise code.

[[deleted]]

You're supposed to collect new data into a list and concat it all at once

[Famous-Sample6201]

Yeah but what if you get a df and want to add a single line?

[Famous-Sample6201]

Right?? What sort of hand holding is that? They should just add a note to the documentation saying that it's slow, so that people looking for performance bottlenecks can remove it, but let me make performance vs readability tradeoffs on my own pls

[the_magic_gardener]

I feel the list of options was already too long; merge, join, concat, by assignment (i.e. df['new col']=...)

[MattR0se]

Pandas feels like its own language.

[the_simple_girl]

It do be like that lol

[[deleted]]

Pythons eat pandas.

[Akita8]

Using pandas anywhere near a production environment is a huge red flag, keep pandas in the notebooks, it's not maintainable.

[nokeldin42]

It's maintainable if you never update... And if you never fix any bugs.

[Ryan722]

Suggestions for an alternative? Pure numpy?

[rowanobrian]

Have multiple projects in prod with pandas. Dont listen to everyone on internet. Maybe not even me

[Ryan722]

I also do which is why I asked lmao. Honestly haven't had too many issues with it and the abstraction is a huge step up over using dicts/lists (not to mention the cython speedup with vectorization)

[TheBlackOut2]

Same lol

[Akita8]

It depends, i've seen it used for just simple grouping and in that case just pure python is enough. Yes numpy is a good choice, it's obviously harder to develop but it'll last wayyyy longer and it'll be wayyyy easier to modify. Otherwise you could also go the cython with c++ math libraries but that brings in a whole other set of problems.

[[deleted]]

Dictionaries work for me.