Comments (4)
Thanks for opening your first issue here at xarray! Be sure to follow the issue template!
If you have an idea for a solution, we would really welcome a Pull Request with proposed changes.
See the Contributing Guide for more.
It may take us a while to respond here, but we really value your contribution. Contributors like you help make xarray better.
Thank you!
from xarray.
It would be even better if skewness and kurtosis functions could be added. Thanks a lot!
from xarray.
Someone would need to look more, but possibly this is hooking up bottleneck's move_rank
in the same way bottleneck's other move_
functions.
from xarray.
Hi, max-sixty. Thanks for your reply!
I have conducted tests on pandas
, xarray
, and bottleneck
using a randomly generated 5000*5000 ndarray containing NaN
values. I found that xarray and bottleneck exhibit similar speeds, with xarray being slightly faster (based on tests involving rolling sum, mean, etc. Their results are the same. Bottleneck's move_rank
does not provide a pct
parameter). I noticed a statement in the xarray documentation: "rolling window aggregations are faster and use less memory when bottleneck is installed".
If it's possible to perform rolling rank
, skew
, kurt
, and other related calculations using xarray's native functions, that would be fantastic. I've become reliant on xarray since I first learned about it and use it, and it has provided significant convenience for my project. It is fast, and the parameters are similar to those in pandas. Thanks to all the maintainers for providing us with such a great library.
I'm looking forward to the emergence of new features and your reply. Thanks again for taking the time!
:)
from xarray.
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