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  • spencerkclark · 7 ✖

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  • Preserve formatting of reference time units under pandas 2.0.0 · 7 ✖

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  • MEMBER · 7 ✖
id html_url issue_url node_id user created_at updated_at ▲ author_association body reactions performed_via_github_app issue
1492956264 https://github.com/pydata/xarray/pull/7441#issuecomment-1492956264 https://api.github.com/repos/pydata/xarray/issues/7441 IC_kwDOAMm_X85Y_LRo spencerkclark 6628425 2023-04-01T12:22:31Z 2023-04-01T12:22:31Z MEMBER

Thanks for cleaning up the merge error I must have introduced; I agree this should be ready to go.

 
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   Preserve formatting of reference time units under pandas 2.0.0 1533980729
1492724527 https://github.com/pydata/xarray/pull/7441#issuecomment-1492724527 https://api.github.com/repos/pydata/xarray/issues/7441 IC_kwDOAMm_X85Y-Ssv spencerkclark 6628425 2023-03-31T23:41:20Z 2023-03-31T23:41:20Z MEMBER

Thanks @keewis for fixing this upstream (https://github.com/pandas-dev/pandas/pull/52220)!

 
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   Preserve formatting of reference time units under pandas 2.0.0 1533980729
1465318583 https://github.com/pydata/xarray/pull/7441#issuecomment-1465318583 https://api.github.com/repos/pydata/xarray/issues/7441 IC_kwDOAMm_X85XVvy3 spencerkclark 6628425 2023-03-12T22:37:20Z 2023-03-12T22:37:20Z MEMBER

Still mulling this over a bit, but one other thing that occurs to me is that if we go with a strftime solution we should be careful (if it exists) to preserve any sub-second information of the Timestamp as well.

 
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   Preserve formatting of reference time units under pandas 2.0.0 1533980729
1460037064 https://github.com/pydata/xarray/pull/7441#issuecomment-1460037064 https://api.github.com/repos/pydata/xarray/issues/7441 IC_kwDOAMm_X85XBmXI spencerkclark 6628425 2023-03-08T11:46:04Z 2023-03-08T11:46:04Z MEMBER

Hmm I guess I should have run the tests before saying anything. We could probably work around the NaT issue fairly easily, but I forgot about timezones. The ability to include a colon in the UTC offset, which we expect in the failing test, with strftime was only recently added to Python (https://github.com/python/cpython/pull/95983), which makes things a little messier. I'll think about this a little more.

 
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   Preserve formatting of reference time units under pandas 2.0.0 1533980729
1459255349 https://github.com/pydata/xarray/pull/7441#issuecomment-1459255349 https://api.github.com/repos/pydata/xarray/issues/7441 IC_kwDOAMm_X85W-ng1 spencerkclark 6628425 2023-03-08T03:08:31Z 2023-03-08T03:08:31Z MEMBER

Thanks @keewis--great suggestion--I think this should be ready for review now too!

 
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   Preserve formatting of reference time units under pandas 2.0.0 1533980729
1397354953 https://github.com/pydata/xarray/pull/7441#issuecomment-1397354953 https://api.github.com/repos/pydata/xarray/issues/7441 IC_kwDOAMm_X85TSfHJ spencerkclark 6628425 2023-01-19T17:33:16Z 2023-01-19T17:33:16Z MEMBER

Issue reported here: https://github.com/pandas-dev/pandas/issues/50867. Thanks again for noting that @keewis. I was too narrowly focused on fixing this in xarray.

We may still want to be careful about non-nanosecond-precision Timestamp objects leaking into our code for the time being, but that's a different conversation.

 
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   Preserve formatting of reference time units under pandas 2.0.0 1533980729
1397286186 https://github.com/pydata/xarray/pull/7441#issuecomment-1397286186 https://api.github.com/repos/pydata/xarray/issues/7441 IC_kwDOAMm_X85TSOUq spencerkclark 6628425 2023-01-19T16:45:24Z 2023-01-19T17:16:31Z MEMBER

Thanks @keewis.

I think this is a bug in pandas: pd.Timestamp("1-01-01 00:00:00") returns a date in 2001.

I suspect this may be related to the comment here.

In any case, t.isoformat(sep=" ") should return the year with 4 digits so maybe we should use that instead? (once again, it doesn't, but that I think is also a bug, maybe the same one?)

Though indeed the isoformat behavior is definitely a bug and it would be fair to at least expect this kind of roundtrip to hold, but it doesn't: ```

import pandas as pd pd.Timestamp(str(pd.Timestamp("0001-01-01"))) Timestamp('2001-01-01 00:00:00') ```

I can report that to pandas. It's not necessarily surprising considering that it previously was not possible to write pd.Timestamp("0001-01-01"). 

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   Preserve formatting of reference time units under pandas 2.0.0 1533980729

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