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thanks for the good effort you have put in this project already.
May I ask for an enhancement of the documentation?
It would be good to have an overview of the (overall) performance of the different functions.
My use case is that I have a numpy array and want to apply a rolling standard deviation window on one of the columns and put it in another column of this numpy array.
It would be good to compare the effort for this with the time it takes to do this for alternatives (like: use pandas directly).
Thanks in advance.
The text was updated successfully, but these errors were encountered:
Hi @haimivan, thank you for raising this ticket - I'm glad you're finding the project useful.
I think adding performance comparisons is a good idea and would certainly help put the different choices available for rolling window operations in context.
Hi,
thanks for the good effort you have put in this project already.
May I ask for an enhancement of the documentation?
It would be good to have an overview of the (overall) performance of the different functions.
My use case is that I have a numpy array and want to apply a rolling standard deviation window on one of the columns and put it in another column of this numpy array.
It would be good to compare the effort for this with the time it takes to do this for alternatives (like: use pandas directly).
Thanks in advance.
The text was updated successfully, but these errors were encountered: