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  • keewis · 5 ✖

issue 1

  • Fix indexing with datetime64[ns] with pandas=1.1 · 5 ✖

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id html_url issue_url node_id user created_at updated_at ▲ author_association body reactions performed_via_github_app issue
691656286 https://github.com/pydata/xarray/pull/4292#issuecomment-691656286 https://api.github.com/repos/pydata/xarray/issues/4292 MDEyOklzc3VlQ29tbWVudDY5MTY1NjI4Ng== keewis 14808389 2020-09-13T10:58:59Z 2020-09-13T21:56:22Z MEMBER

it seems we have to cast because label may also be something like a Variable object, which is not accepted by index.get_loc. I pushed my original fix (falling back to .item() for non-datetime / timedelta dtypes), I hope that's okay?

 
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   Fix indexing with datetime64[ns] with pandas=1.1 669307837
691665611 https://github.com/pydata/xarray/pull/4292#issuecomment-691665611 https://api.github.com/repos/pydata/xarray/issues/4292 MDEyOklzc3VlQ29tbWVudDY5MTY2NTYxMQ== keewis 14808389 2020-09-13T12:29:44Z 2020-09-13T12:29:44Z MEMBER

it seems pandas warns about our usage of pandas.Grouper: ``` /home/docs/checkouts/readthedocs.org/user_builds/xray/checkouts/4292/xarray/core/common.py:1134: FutureWarning: 'base' in .resample() and in Grouper() is deprecated. The new arguments that you should use are 'offset' or 'origin'.

df.resample(freq="3s", base=2)

becomes:

df.resample(freq="3s", offset="2s")

grouper = pd.Grouper( `` this was introduced in1.1.0. We're supportingpandas>=0.25(maybe even>=0.24`) so we can't switch yet. I added a warning filter and a todo comment, but we might also need a tracking issue.

 
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   Fix indexing with datetime64[ns] with pandas=1.1 669307837
687749906 https://github.com/pydata/xarray/pull/4292#issuecomment-687749906 https://api.github.com/repos/pydata/xarray/issues/4292 MDEyOklzc3VlQ29tbWVudDY4Nzc0OTkwNg== keewis 14808389 2020-09-06T10:25:56Z 2020-09-06T10:25:56Z MEMBER

gentle ping, @shoyer. Any updates on this?

 
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   Fix indexing with datetime64[ns] with pandas=1.1 669307837
682420487 https://github.com/pydata/xarray/pull/4292#issuecomment-682420487 https://api.github.com/repos/pydata/xarray/issues/4292 MDEyOklzc3VlQ29tbWVudDY4MjQyMDQ4Nw== keewis 14808389 2020-08-28T09:13:42Z 2020-08-28T09:13:42Z MEMBER

there are lots of people that stumble into this, so I think it might be good to get this to work as soon as possible and issue a bugfix release.

 
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   Fix indexing with datetime64[ns] with pandas=1.1 669307837
669162768 https://github.com/pydata/xarray/pull/4292#issuecomment-669162768 https://api.github.com/repos/pydata/xarray/issues/4292 MDEyOklzc3VlQ29tbWVudDY2OTE2Mjc2OA== keewis 14808389 2020-08-05T12:25:10Z 2020-08-05T14:29:38Z MEMBER

you should be able to isolate this to just indexing.convert_label_indexer, e.g. with this in test_indexing.py: ```python def test_convert_label_indexer_datetime(self): index = pd.to_datetime(["2000-01-01", "2001-01-01", "2002-01-01"]) actual = indexing.convert_label_indexer(index, "2001-01-01") expected = (1, None) assert actual == expected

    actual = indexing.convert_label_indexer(index, index.to_numpy()[1])
    assert actual == expected

```

The failing tests are due to label[()] returning a numpy.str_ instead of a plain python str. Maybe we can fix that by using item as long as the dtype is not "datetime64" or "timedelta64": python if label.dtype.kind in "mM": label_value = label[()] else: label_value = label.item() Edit: stable is affected by this, too

 
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   Fix indexing with datetime64[ns] with pandas=1.1 669307837

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