[Numpy-discussion] Re: ENH: Introducing a pipe Method for Numpy arrays

We could expand this topic for a broader perspective. Pandas offers "custom accessors," empowering users to extend DataFrame functionality, while Polars introduces "Expression plugins" for customization, enhancing DataFrame operations. These features are pretty awesome. The obvious advantage, the

[Numpy-discussion] Introducing quarterly date units to datetime64 and timedelta64

an issue on GitHub to initiate the conversation if the proposal sounds reasonable. Your feedback would be appreciated. Best regards, Oyibo ___ NumPy-Discussion mailing list -- numpy-discussion@python.org To unsubscribe send an email to numpy-discussion

[Numpy-discussion] Re: Introducing quarterly date units to datetime64 and timedelta64

quarterly unit because it is more intuitive and aligns with other libraries like Pandas. You are moderately negative on this proposal. However, do you see a way to improve the user experience? Thank you for your feedback. Regards, Oyibo ___ NumPy-

[Numpy-discussion] Re: Introducing quarterly date units to datetime64 and timedelta64

For some reason scenarios 3 & 4 got butchered. 3) Unfamiliar user (pure Numpy): dates = np.asarray(dates, dtype=' Works, but ugly... 4) Advanced user: dates = np.asarray(dates, dtype=' Really, so easy... ___ NumPy-Discussion mailing list -- nu