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unumpy.sin()
and similar functions should behave with Pandas object like NumPy functions do
#150
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I'm looking to do two things:
Anybody else interested/able to help and/or guide? This is mostly new territory for me (but I have done big lifts in the past). |
This is a nuisance that will have to be fixed: https://stackoverflow.com/questions/70908349/pandas-rolling-operation-on-categorical-column |
I'd be happy to punctually give a hand and brainstorm some; precisely, if you keep posting in the issues, I'll do my best to help. I don't know how related this can be, but |
Wonderful! I just read through that history. Thus far, I've made very good progress by simply deleting from PintType (in Pint-Pandas) the code that forces conversion to float when casting via I'm now confronting how code I wrote messes with Pint's assumption that it can read and understand what it writes. I think it's relatively common idiom (unless I'm an idiot) to create a quantity somewhere and then read that quantity back via the unit registry like so:
When the unit registry sees an uncertainty, it gets confused:
But so much else works, except for needing to change my nan handling (unp.isnan). I'll report more as I get my code passing its first full run-trough of a test case. |
Made some good progress, updated here: os-climate/ITR#159 Forks to Pint and Pandas mentioned in PR above and described at bottom of this thread: hgrecco/pint#1605 |
More specifically,
numpy.sin()
applied to a Pandas Series returns a Pandas Series, whereasunumpy.sin()
returns a NumPy array.See #133 (comment).
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