html_url,issue_url,id,node_id,user,created_at,updated_at,author_association,body,reactions,performed_via_github_app,issue
https://github.com/pydata/xarray/issues/2666#issuecomment-569820784,https://api.github.com/repos/pydata/xarray/issues/2666,569820784,MDEyOklzc3VlQ29tbWVudDU2OTgyMDc4NA==,1312546,2019-12-30T22:58:23Z,2019-12-30T22:58:23Z,MEMBER,">  I think this is basically the same change.

Ah, I was mistaken. I was thinking we needed to plump a `dtype` argument all the way through there, but I don't think that's necessary. I may be able to submit a PR with a `dtypes` argument for `from_dataframe` tomorrow.","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,398107776
https://github.com/pydata/xarray/issues/2666#issuecomment-569819509,https://api.github.com/repos/pydata/xarray/issues/2666,569819509,MDEyOklzc3VlQ29tbWVudDU2OTgxOTUwOQ==,1217238,2019-12-30T22:51:36Z,2019-12-30T22:51:55Z,MEMBER,"> Just FYI, we're potentially enforcing this deprecation in [pandas-dev/pandas#30563](https://github.com/pandas-dev/pandas/pull/30563) (which would be included in a pandas release in a week or two). Is that likely to cause problems for xarray users?

I don't think so. Xarray users have been seeing this warning for a while, so they should expect something will change.

Also, I don't think there are that many users using DatetimeTZ in xarray.

> And there are a couple places that need updating, even with a `dtypes` argument to let the user specify things. We also hit this via `Dataset.__setitem__`

I think this is basically the same change. Is there a full example of the behavior that you are worried about?","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,398107776
https://github.com/pydata/xarray/issues/2666#issuecomment-569810375,https://api.github.com/repos/pydata/xarray/issues/2666,569810375,MDEyOklzc3VlQ29tbWVudDU2OTgxMDM3NQ==,1312546,2019-12-30T22:07:30Z,2019-12-30T22:07:30Z,MEMBER,"And there are a couple places that need updating, even with a `dtypes` argument to let the user specify things. We also hit this via `Dataset.__setitem__`

```pytb
~/sandbox/xarray/xarray/core/dataset.py in __setitem__(self, key, value)
   1268             )
   1269
-> 1270         self.update({key: value})
   1271
   1272     def __delitem__(self, key: Hashable) -> None:

~/sandbox/xarray/xarray/core/dataset.py in update(self, other, inplace)
   3521         """"""
   3522         _check_inplace(inplace)
-> 3523         merge_result = dataset_update_method(self, other)
   3524         return self._replace(inplace=True, **merge_result._asdict())
   3525

~/sandbox/xarray/xarray/core/merge.py in dataset_update_method(dataset, other)
    862                     other[key] = value.drop_vars(coord_names)
    863
--> 864     return merge_core([dataset, other], priority_arg=1, indexes=dataset.indexes)

~/sandbox/xarray/xarray/core/merge.py in merge_core(objects, compat, join, priority_arg, explicit_coords, indexes, fill_value)
    550         coerced, join=join, copy=False, indexes=indexes, fill_value=fill_value
    551     )
--> 552     collected = collect_variables_and_indexes(aligned)
    553
    554     prioritized = _get_priority_vars_and_indexes(aligned, priority_arg, compat=compat)

~/sandbox/xarray/xarray/core/merge.py in collect_variables_and_indexes(list_of_mappings)
    275                 append_all(coords, indexes)
    276
--> 277             variable = as_variable(variable, name=name)
    278             if variable.dims == (name,):
    279                 variable = variable.to_index_variable()

~/sandbox/xarray/xarray/core/variable.py in as_variable(obj, name)
    105     elif isinstance(obj, tuple):
    106         try:
--> 107             obj = Variable(*obj)
    108         except (TypeError, ValueError) as error:
    109             # use .format() instead of % because it handles tuples consistently

~/sandbox/xarray/xarray/core/variable.py in __init__(self, dims, data, attrs, encoding, fastpath)
    306             unrecognized encoding items.
    307         """"""
--> 308         self._data = as_compatible_data(data, fastpath=fastpath)
    309         self._dims = self._parse_dimensions(dims)
    310         self._attrs = None

~/sandbox/xarray/xarray/core/variable.py in as_compatible_data(data, fastpath)
    229     if isinstance(data, np.ndarray):
    230         if data.dtype.kind == ""O"":
--> 231             data = _possibly_convert_objects(data)
    232         elif data.dtype.kind == ""M"":
    233             data = np.asarray(data, ""datetime64[ns]"")

~/sandbox/xarray/xarray/core/variable.py in _possibly_convert_objects(values)
    165     datetime64 and timedelta64, according to the pandas convention.
    166     """"""
--> 167     return np.asarray(pd.Series(values.ravel())).reshape(values.shape)
    168
    169

~/sandbox/numpy/numpy/core/_asarray.py in asarray(a, dtype, order)
     83
     84     """"""
---> 85     return array(a, dtype, copy=False, order=order)
     86
     87

~/sandbox/pandas/pandas/core/series.py in __array__(self, dtype)
    730                 ""To keep the old behavior, pass 'dtype=\""datetime64[ns]\""'.""
    731             )
--> 732             warnings.warn(msg, FutureWarning, stacklevel=3)
    733             dtype = ""M8[ns]""
    734         return np.asarray(self.array, dtype)
```","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,398107776
https://github.com/pydata/xarray/issues/2666#issuecomment-569805431,https://api.github.com/repos/pydata/xarray/issues/2666,569805431,MDEyOklzc3VlQ29tbWVudDU2OTgwNTQzMQ==,1312546,2019-12-30T21:45:41Z,2019-12-30T21:48:39Z,MEMBER,"Just FYI, we're potentially enforcing this deprecation in https://github.com/pandas-dev/pandas/pull/30563 (which would be included in a pandas release in a week or two). Is that likely to cause problems for xarray users?

It's not clear to me what the desired behavior is (https://github.com/pydata/xarray/issues/3291 seems to want to preserve the tz, though it isn't clear they are willing to be forced into an object dtype array for it).","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,398107776
https://github.com/pydata/xarray/issues/2666#issuecomment-458925514,https://api.github.com/repos/pydata/xarray/issues/2666,458925514,MDEyOklzc3VlQ29tbWVudDQ1ODkyNTUxNA==,6623132,2019-01-30T12:25:15Z,2019-01-30T12:25:15Z,NONE,"The current implementation caused some issues, since files from different sources suddenly can't import and sort together like they used to. I'm fine with a dtypes argument, but where will you pass it? This is arising in .sort_index() for me.","{""total_count"": 1, ""+1"": 1, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,398107776
https://github.com/pydata/xarray/issues/2666#issuecomment-453356449,https://api.github.com/repos/pydata/xarray/issues/2666,453356449,MDEyOklzc3VlQ29tbWVudDQ1MzM1NjQ0OQ==,1217238,2019-01-11T02:54:32Z,2019-01-11T02:54:32Z,MEMBER,"I'm open to suggestions here, especially from users who use DatetimeTZ data in pandas.

As noted in https://github.com/pandas-dev/pandas/issues/24716,  I think the cleanest solution is probably to add a `dtypes` argument to `from_dataframe`, to allow users to specify their own desired dtypes for pandas -> numpy coercion.","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,398107776