id,node_id,number,title,user,state,locked,assignee,milestone,comments,created_at,updated_at,closed_at,author_association,active_lock_reason,draft,pull_request,body,reactions,performed_via_github_app,state_reason,repo,type
879033384,MDU6SXNzdWU4NzkwMzMzODQ=,5278,DataArray.clip() no longer supports the out argument,7441788,closed,0,,,12,2021-05-07T13:45:01Z,2023-12-02T05:52:07Z,2023-12-02T05:52:07Z,CONTRIBUTOR,,,,"As of xarray 0.18.0, `DataArray.clip()` no longer supports the `out` argument. This is due to #5184. Could you please restore `out` support?
@max-sixty ","{""url"": ""https://api.github.com/repos/pydata/xarray/issues/5278/reactions"", ""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,not_planned,13221727,issue
266133430,MDU6SXNzdWUyNjYxMzM0MzA=,1635,DataArray.argsort should be deleted,7441788,open,0,,,7,2017-10-17T13:52:54Z,2023-03-10T02:31:27Z,,CONTRIBUTOR,,,,"Originally posted to https://groups.google.com/forum/#!topic/xarray/wsxeiIPLhgM
`DataArray.argsort()` appears to simply wrap the result of `DataArray.values.argsort()` in a same-shape `DataArray`. This is semantically nonsensical. If anything the index on the resulting `argsort()` values should simply be `range(len(da))`, but that adds little to the underlying numpy structure. And there's not much reason to have `da.argsort()` simply return the (raw) result of `da.values.argsort()`. So really `DataArray.argsort()` should simply be deleted.
On the other hand a new function `DataArray.rank()` that wraps `da.values.argsort().argsort()` (note repeated call to `ndarray.argsort()`) in the structure of the original `DataArray` *would* make sense, and perhaps even be useful... (Note that I'm not claiming that `.argsort().argsort()` is the fastest way to calculate this, but it's probably good enough, at least for an initial implementation.)","{""url"": ""https://api.github.com/repos/pydata/xarray/issues/1635/reactions"", ""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,,13221727,issue
572875480,MDU6SXNzdWU1NzI4NzU0ODA=,3810,"{DataArray,Dataset}.rank() should support an optional list of dimensions",7441788,open,0,,,10,2020-02-28T16:57:08Z,2021-11-19T15:09:10Z,,CONTRIBUTOR,,,,"`{DataArray,Dataset}.rank()` requires a single `dim`. Why not support an optional list of dimensions (defaulting to all)?
```
In [1]: import numpy as np, xarray as xr
In [2]: d = xr.DataArray(np.arange(12).reshape((4,3)), dims=('abc', 'xyz'))
In [3]: d
Out[3]:
<xarray.DataArray (abc: 4, xyz: 3)>
array([[ 0, 1, 2],
[ 3, 4, 5],
[ 6, 7, 8],
[ 9, 10, 11]])
Dimensions without coordinates: abc, xyz
In [4]: d.rank()
---------------------------------------------------------------------------
TypeError Traceback (most recent call last)
<ipython-input-4-585571c1eca8> in <module>
----> 1 d.rank()
TypeError: rank() missing 1 required positional argument: 'dim'
In [5]: d.rank(dim=('xyz', 'abc'))
---------------------------------------------------------------------------
TypeError Traceback (most recent call last)
<ipython-input-5-006c73551ff8> in <module>
----> 1 d.rank(dim=('xyz', 'abc'))
~/.conda/envs/build/lib/python3.7/site-packages/xarray/core/dataarray.py in rank(self, dim, pct, keep_attrs)
3054 """"""
3055
-> 3056 ds = self._to_temp_dataset().rank(dim, pct=pct, keep_attrs=keep_attrs)
3057 return self._from_temp_dataset(ds)
3058
~/.conda/envs/build/lib/python3.7/site-packages/xarray/core/dataset.py in rank(self, dim, pct, keep_attrs)
5295 """"""
5296 if dim not in self.dims:
-> 5297 raise ValueError(""Dataset does not contain the dimension: %s"" % dim)
5298
5299 variables = {}
TypeError: not all arguments converted during string formatting
In [6]: xr.show_versions()
INSTALLED VERSIONS
------------------
commit: None
python: 3.7.6 | packaged by conda-forge | (default, Jan 7 2020, 22:33:48)
[GCC 7.3.0]
python-bits: 64
OS: Linux
OS-release: 3.10.0-693.el7.x86_64
machine: x86_64
processor: x86_64
byteorder: little
LC_ALL: None
LANG: en_US.UTF-8
LOCALE: en_US.UTF-8
libhdf5: 1.10.5
libnetcdf: 4.7.3
xarray: 0.15.0
pandas: 1.0.1
numpy: 1.18.1
scipy: 1.4.1
netCDF4: 1.5.3
pydap: None
h5netcdf: 0.8.0
h5py: 2.10.0
Nio: None
zarr: None
cftime: 1.0.4.2
nc_time_axis: None
PseudoNetCDF: None
rasterio: None
cfgrib: None
iris: None
bottleneck: 1.3.2
dask: 2.11.0
distributed: 2.11.0
matplotlib: 3.1.3
cartopy: None
seaborn: 0.10.0
numbagg: installed
setuptools: 45.2.0.post20200209
pip: 20.0.2
conda: 4.8.2
pytest: None
IPython: 7.12.0
sphinx: None
```","{""url"": ""https://api.github.com/repos/pydata/xarray/issues/3810/reactions"", ""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,,13221727,issue
483028482,MDU6SXNzdWU0ODMwMjg0ODI=,3236,ENH: apply_ufunc logging or callback,7441788,open,0,,,3,2019-08-20T18:59:36Z,2021-07-21T10:00:51Z,,CONTRIBUTOR,,,,"With long-running (think hours) `apply_ufunc(..., vectorize=True)` calls, it would be nice to be able to have logging of the input non-core dims being evaluated, perhaps via a call-back.","{""url"": ""https://api.github.com/repos/pydata/xarray/issues/3236/reactions"", ""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,,13221727,issue
309098246,MDU6SXNzdWUzMDkwOTgyNDY=,2017,np.minimum.accumulate(da) doesn't work,7441788,open,0,,,7,2018-03-27T19:15:06Z,2021-07-04T03:20:18Z,,CONTRIBUTOR,,,,"#### Code Sample, a copy-pastable example if possible
```
In [1]: import numpy as np
In [2]: import xarray as xr
In [3]: np.minimum.accumulate(np.array([3,2,4,1]))
Out[3]: array([3, 2, 2, 1], dtype=int32)
In [4]: np.minimum.accumulate(xr.DataArray([3,2,4,1]))
---------------------------------------------------------------------------
NotImplementedError Traceback (most recent call last)
<ipython-input-7-7205433fb365> in <module>()
----> 1 np.minimum.accumulate(xr.DataArray([3,2,4,1]))
~\Anaconda3\lib\site-packages\xarray\core\arithmetic.py in __array_ufunc__(self, ufunc, method, *inputs, **kwargs)
49 'alternative, consider explicitly converting xarray objects '
50 'to NumPy arrays (e.g., with `.values`).'
---> 51 .format(method, ufunc))
52
53 if any(isinstance(o, SupportsArithmetic) for o in out):
NotImplementedError: accumulate method for ufunc <ufunc 'minimum'> is not implemented on xarray objects, which currently only support the __call__ method. As an alternative, consider explicitly converting xarray objects to NumPy arrays (e.g., with `.values`).
```
#### Problem description
I would expect this to work, like `xr.apply_ufunc(np.minimum.accumulate, xr.DataArray([3,2,4,1]))`:
#### Expected Output
```
Out[4]: <xarray.DataArray (dim_0: 4)>
array([3, 2, 2, 1])
Dimensions without coordinates: dim_0
```
#### Output of ``xr.show_versions()``
<details>
```
commit: None
python: 3.6.4.final.0
python-bits: 64
OS: Windows
OS-release: 10
machine: AMD64
processor: Intel64 Family 6 Model 62 Stepping 4, GenuineIntel
byteorder: little
LC_ALL: None
LANG: None
LOCALE: None.None
xarray: 0.10.2
pandas: 0.22.0
numpy: 1.14.2
scipy: 1.0.0
netCDF4: None
h5netcdf: 0.5.0
h5py: 2.7.1
Nio: None
zarr: None
bottleneck: 1.2.1
cyordereddict: None
dask: 0.17.1
distributed: 1.21.3
matplotlib: 2.2.2
cartopy: None
seaborn: 0.8.1
setuptools: 39.0.1
pip: 9.0.2
conda: 4.3.34
pytest: 3.4.2
IPython: 6.2.1
sphinx: 1.7.1
```
</details>
Originally posted posted to https://groups.google.com/forum/#!topic/xarray/LiwxrJcJBwY.
","{""url"": ""https://api.github.com/repos/pydata/xarray/issues/2017/reactions"", ""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,,13221727,issue
207317762,MDU6SXNzdWUyMDczMTc3NjI=,1266,Coordinate type changing from string to object,7441788,open,0,,,2,2017-02-13T19:38:16Z,2020-10-27T16:33:46Z,,CONTRIBUTOR,,,,"Originally posted on https://groups.google.com/forum/#!topic/xarray/4k8ZAx998UU. I would expect `[2]`, `[3]`, and `[4]` to produce identical results, with coordinate `xyz` being of type `|S1` (in general `|Sn` where n is minimal to accommodate the coordinate values), not `object`. This behavior is observed with xarray versions 0.8.2 and 0.9.1.
```
Python 2.7.12 (v2.7.12:d33e0cf91556, Jun 27 2016, 15:24:40) [MSC v.1500 64 bit (AMD64)]
Type ""copyright"", ""credits"" or ""license"" for more information.
IPython 5.1.0 -- An enhanced Interactive Python.
? -> Introduction and overview of IPython's features.
%quickref -> Quick reference.
help -> Python's own help system.
object? -> Details about 'object', use 'object??' for extra details.
In [1]: from xarray import DataArray
In [2]: DataArray([1.], dims=('xyz',), coords={'xyz': ['a']}) + \
...: DataArray([5.], dims=('xyz',), coords={'xyz': ['a']})
Out[2]:
<xarray.DataArray (xyz: 1)>
array([ 6.])
Coordinates:
* xyz (xyz) |S1 'a'
In [3]: DataArray([1., 2.], dims=('xyz',), coords={'xyz': ['a', 'b']}) + \
...: DataArray([5.], dims=('xyz',), coords={'xyz': ['a']})
Out[3]:
<xarray.DataArray (xyz: 1)>
array([ 6.])
Coordinates:
* xyz (xyz) object 'a'
In [4]: DataArray([1.], dims=('xyz',), coords={'xyz': ['a']}) + \
...: DataArray([5., 6.], dims=('xyz',), coords={'xyz': ['a', 'b']})
Out[4]:
<xarray.DataArray (xyz: 1)>
array([ 6.])
Coordinates:
* xyz (xyz) object 'a'
```","{""url"": ""https://api.github.com/repos/pydata/xarray/issues/1266/reactions"", ""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,,13221727,issue
683657289,MDU6SXNzdWU2ODM2NTcyODk=,4363,Indexing a datetime64[ns] coordinate with a scalar datetime.date produces a KeyError,7441788,open,0,,,2,2020-08-21T15:54:16Z,2020-09-19T19:16:37Z,,CONTRIBUTOR,,,,"Indexing a `datetime64[ns]` coordinate with a scalar `datetime.date` produces a `KeyError` (`[6]`).
Curiously, indexing with a `datetime.date` _slice_ does work (`[5]`).
I would expect `[6]` to work just like `[4]`.
This may well be related to (or a duplicate of) #3736, #4283, #4292, #4306, #4319, or #4370, but none of those actually mentions `datetime.date` objects, so I can't tell.
```python
In [1]: import xarray as xr, pandas as pd, datetime as dt
In [2]: x = xr.DataArray([1., 2., 3.], [('foo', pd.date_range('2010-01-01', periods=3))])
In [3]: x
Out[3]:
<xarray.DataArray (foo: 3)>
array([1., 2., 3.])
Coordinates:
* foo (foo) datetime64[ns] 2010-01-01 2010-01-02 2010-01-03
In [4]: x.loc[dt.datetime(2010, 1, 1)]
Out[4]:
<xarray.DataArray ()>
array(1.)
Coordinates:
foo datetime64[ns] 2010-01-01
In [5]: x.loc[dt.date(2010, 1, 1):dt.date(2010, 1, 3)]
Out[5]:
<xarray.DataArray (foo: 3)>
array([1., 2., 3.])
Coordinates:
* foo (foo) datetime64[ns] 2010-01-01 2010-01-02 2010-01-03
In [6]: x.loc[dt.date(2010, 1, 1)]
---------------------------------------------------------------------------
KeyError Traceback (most recent call last)
<ipython-input-5-8ef314626f7d> in <module>
----> 1 x.loc[dt.date(2010, 1, 1)]
~/.conda/envs/build/lib/python3.7/site-packages/xarray/core/dataarray.py in __getitem__(self, key)
196 labels = indexing.expanded_indexer(key, self.data_array.ndim)
197 key = dict(zip(self.data_array.dims, labels))
--> 198 return self.data_array.sel(**key)
199
200 def __setitem__(self, key, value) -> None:
~/.conda/envs/build/lib/python3.7/site-packages/xarray/core/dataarray.py in sel(self, indexers, method, tolerance, drop, **indexers_kwargs)
1152 method=method,
1153 tolerance=tolerance,
-> 1154 **indexers_kwargs,
1155 )
1156 return self._from_temp_dataset(ds)
~/.conda/envs/build/lib/python3.7/site-packages/xarray/core/dataset.py in sel(self, indexers, method, tolerance, drop, **indexers_kwargs)
2100 indexers = either_dict_or_kwargs(indexers, indexers_kwargs, ""sel"")
2101 pos_indexers, new_indexes = remap_label_indexers(
-> 2102 self, indexers=indexers, method=method, tolerance=tolerance
2103 )
2104 result = self.isel(indexers=pos_indexers, drop=drop)
~/.conda/envs/build/lib/python3.7/site-packages/xarray/core/coordinates.py in remap_label_indexers(obj, indexers, method, tolerance, **indexers_kwargs)
395
396 pos_indexers, new_indexes = indexing.remap_label_indexers(
--> 397 obj, v_indexers, method=method, tolerance=tolerance
398 )
399 # attach indexer's coordinate to pos_indexers
~/.conda/envs/build/lib/python3.7/site-packages/xarray/core/indexing.py in remap_label_indexers(data_obj, indexers, method, tolerance)
268 coords_dtype = data_obj.coords[dim].dtype
269 label = maybe_cast_to_coords_dtype(label, coords_dtype)
--> 270 idxr, new_idx = convert_label_indexer(index, label, dim, method, tolerance)
271 pos_indexers[dim] = idxr
272 if new_idx is not None:
~/.conda/envs/build/lib/python3.7/site-packages/xarray/core/indexing.py in convert_label_indexer(index, label, index_name, method, tolerance)
188 else:
189 indexer = index.get_loc(
--> 190 label.item(), method=method, tolerance=tolerance
191 )
192 elif label.dtype.kind == ""b"":
~/.conda/envs/build/lib/python3.7/site-packages/pandas/core/indexes/datetimes.py in get_loc(self, key, method, tolerance)
620 else:
621 # unrecognized type
--> 622 raise KeyError(key)
623
624 try:
KeyError: datetime.date(2010, 1, 1)
```
**Environment**:
<details><summary>Output of <tt>xr.show_versions()</tt></summary>
INSTALLED VERSIONS
------------------
commit: None
python: 3.7.8 | packaged by conda-forge | (default, Jul 31 2020, 02:25:08)
[GCC 7.5.0]
python-bits: 64
OS: Linux
OS-release: 3.10.0-693.el7.x86_64
machine: x86_64
processor: x86_64
byteorder: little
LC_ALL: None
LANG: en_US.UTF-8
LOCALE: en_US.UTF-8
libhdf5: 1.10.6
libnetcdf: 4.7.4
xarray: 0.16.0
pandas: 1.1.0
numpy: 1.19.1
scipy: 1.5.2
netCDF4: 1.5.4
pydap: None
h5netcdf: 0.8.1
h5py: 2.10.0
Nio: None
zarr: None
cftime: 1.2.1
nc_time_axis: None
PseudoNetCDF: None
rasterio: None
cfgrib: None
iris: None
bottleneck: 1.3.2
dask: 2.23.0
distributed: 2.23.0
matplotlib: 3.3.1
cartopy: None
seaborn: 0.10.1
numbagg: installed
pint: None
setuptools: 49.6.0.post20200814
pip: 20.2.2
conda: 4.8.4
pytest: None
IPython: 7.17.0
sphinx: None
</details>
","{""url"": ""https://api.github.com/repos/pydata/xarray/issues/4363/reactions"", ""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,,13221727,issue
614149170,MDU6SXNzdWU2MTQxNDkxNzA=,4044,"open_mfdataset(paths, combine='nested') with and without concat_dim=None",7441788,closed,0,,,2,2020-05-07T15:31:07Z,2020-05-07T22:34:43Z,2020-05-07T22:34:43Z,CONTRIBUTOR,,,,"Is there a good reason `open_mfdataset(paths, combine='nested')` produces an error rather than work as `open_mfdataset(paths, combine='nested', concat_dim=None)`?","{""url"": ""https://api.github.com/repos/pydata/xarray/issues/4044/reactions"", ""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,completed,13221727,issue
575564170,MDU6SXNzdWU1NzU1NjQxNzA=,3829,"{DataArray,Dataset} accessors with parameters",7441788,open,0,,,4,2020-03-04T16:41:55Z,2020-04-02T12:11:47Z,,CONTRIBUTOR,,,,"I would like to be able to create an DataArray accessor that takes parameters, e.g. `obj.weighted(w).sum(dim)`. This appears to be impossible using the existing `@register_{dataarray,dataset}_accessor`, which supports only accessors of the form `obj.weighted.sum(w, dim)`.
To support the desired syntax, one could simply change https://github.com/pydata/xarray/blob/master/xarray/core/extensions.py#L36
from
```
accessor_obj = self._accessor(obj)
```
to
```
accessor_obj = partial(self._accessor, obj)
```
But that would break the current syntax (i.e. would require `obj.accessor().foo()`, so is clearly not acceptable.
So any suggestions (short of simply creating slightly modified copies of `register_{dataarray,dataset}_accessor`) for supporting both the existing `obj.accessor.foo()` syntax as well as my desired `obj.accessor(*args, **kwargs).foo()` syntax?","{""url"": ""https://api.github.com/repos/pydata/xarray/issues/3829/reactions"", ""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,,13221727,issue
558204984,MDU6SXNzdWU1NTgyMDQ5ODQ=,3736,BUG: datetime.date slicing doesn't work with Pandas 1.0.0,7441788,closed,0,,,3,2020-01-31T15:39:44Z,2020-02-05T21:09:43Z,2020-02-05T21:09:43Z,CONTRIBUTOR,,,,"The following code used to work before I upgraded Pandas to 1.0.0. I would expect `[5]` to produce the same result as `[4]`. I don't know if the failure of `datetime.date` slicing is (a) expected behavior; (b) a Pandas bug; or (c) an xarray bug due to not being updated to reflect an intended change in Pandas.
```python
Python 3.7.6 | packaged by conda-forge | (default, Jan 7 2020, 22:33:48)
Type 'copyright', 'credits' or 'license' for more information
IPython 7.11.1 -- An enhanced Interactive Python. Type '?' for help.
In [1]: import xarray as xr, pandas as pd, datetime as dt
In [2]: x = xr.DataArray([1., 2., 3.], [('foo', pd.date_range('2010-01-01', periods=3))])
In [3]: x
Out[3]:
<xarray.DataArray (foo: 3)>
array([1., 2., 3.])
Coordinates:
* foo (foo) datetime64[ns] 2010-01-01 2010-01-02 2010-01-03
In [4]: x.loc['2010-01-02':'2010-01-04']
Out[4]:
<xarray.DataArray (foo: 2)>
array([2., 3.])
Coordinates:
* foo (foo) datetime64[ns] 2010-01-02 2010-01-03
In [5]: x.loc[dt.date(2010, 1, 2):dt.date(2010, 1, 4)]
---------------------------------------------------------------------------
TypeError Traceback (most recent call last)
pandas/_libs/index.pyx in pandas._libs.index.DatetimeEngine.get_loc()
pandas/_libs/hashtable_class_helper.pxi in pandas._libs.hashtable.Int64HashTable.get_item()
TypeError: an integer is required
During handling of the above exception, another exception occurred:
KeyError Traceback (most recent call last)
~/.conda/envs/build/lib/python3.7/site-packages/pandas/core/indexes/base.py in get_loc(self, key, method, tolerance)
2645 try:
-> 2646 return self._engine.get_loc(key)
2647 except KeyError:
pandas/_libs/index.pyx in pandas._libs.index.DatetimeEngine.get_loc()
pandas/_libs/index.pyx in pandas._libs.index.DatetimeEngine.get_loc()
pandas/_libs/index.pyx in pandas._libs.index.DatetimeEngine._date_check_type()
KeyError: datetime.date(2010, 1, 4)
During handling of the above exception, another exception occurred:
TypeError Traceback (most recent call last)
pandas/_libs/index.pyx in pandas._libs.index.DatetimeEngine.get_loc()
pandas/_libs/hashtable_class_helper.pxi in pandas._libs.hashtable.Int64HashTable.get_item()
TypeError: an integer is required
During handling of the above exception, another exception occurred:
KeyError Traceback (most recent call last)
~/.conda/envs/build/lib/python3.7/site-packages/pandas/core/indexes/datetimes.py in get_loc(self, key, method, tolerance)
714 try:
--> 715 return Index.get_loc(self, key, method, tolerance)
716 except (KeyError, ValueError, TypeError):
~/.conda/envs/build/lib/python3.7/site-packages/pandas/core/indexes/base.py in get_loc(self, key, method, tolerance)
2647 except KeyError:
-> 2648 return self._engine.get_loc(self._maybe_cast_indexer(key))
2649 indexer = self.get_indexer([key], method=method, tolerance=tolerance)
pandas/_libs/index.pyx in pandas._libs.index.DatetimeEngine.get_loc()
pandas/_libs/index.pyx in pandas._libs.index.DatetimeEngine.get_loc()
pandas/_libs/index.pyx in pandas._libs.index.DatetimeEngine._date_check_type()
KeyError: datetime.date(2010, 1, 4)
During handling of the above exception, another exception occurred:
KeyError Traceback (most recent call last)
pandas/_libs/index.pyx in pandas._libs.index.DatetimeEngine.get_loc()
pandas/_libs/hashtable_class_helper.pxi in pandas._libs.hashtable.Int64HashTable.get_item()
pandas/_libs/hashtable_class_helper.pxi in pandas._libs.hashtable.Int64HashTable.get_item()
KeyError: 1262563200000000000
During handling of the above exception, another exception occurred:
KeyError Traceback (most recent call last)
~/.conda/envs/build/lib/python3.7/site-packages/pandas/core/indexes/base.py in get_loc(self, key, method, tolerance)
2645 try:
-> 2646 return self._engine.get_loc(key)
2647 except KeyError:
pandas/_libs/index.pyx in pandas._libs.index.DatetimeEngine.get_loc()
pandas/_libs/index.pyx in pandas._libs.index.DatetimeEngine.get_loc()
KeyError: Timestamp('2010-01-04 00:00:00')
During handling of the above exception, another exception occurred:
KeyError Traceback (most recent call last)
pandas/_libs/index.pyx in pandas._libs.index.DatetimeEngine.get_loc()
pandas/_libs/hashtable_class_helper.pxi in pandas._libs.hashtable.Int64HashTable.get_item()
pandas/_libs/hashtable_class_helper.pxi in pandas._libs.hashtable.Int64HashTable.get_item()
KeyError: 1262563200000000000
During handling of the above exception, another exception occurred:
KeyError Traceback (most recent call last)
~/.conda/envs/build/lib/python3.7/site-packages/pandas/core/indexes/datetimes.py in get_loc(self, key, method, tolerance)
727 stamp = stamp.tz_localize(self.tz)
--> 728 return Index.get_loc(self, stamp, method, tolerance)
729 except KeyError:
~/.conda/envs/build/lib/python3.7/site-packages/pandas/core/indexes/base.py in get_loc(self, key, method, tolerance)
2647 except KeyError:
-> 2648 return self._engine.get_loc(self._maybe_cast_indexer(key))
2649 indexer = self.get_indexer([key], method=method, tolerance=tolerance)
pandas/_libs/index.pyx in pandas._libs.index.DatetimeEngine.get_loc()
pandas/_libs/index.pyx in pandas._libs.index.DatetimeEngine.get_loc()
KeyError: Timestamp('2010-01-04 00:00:00')
During handling of the above exception, another exception occurred:
KeyError Traceback (most recent call last)
~/.conda/envs/build/lib/python3.7/site-packages/pandas/core/indexes/base.py in get_slice_bound(self, label, side, kind)
4841 try:
-> 4842 slc = self.get_loc(label)
4843 except KeyError as err:
~/.conda/envs/build/lib/python3.7/site-packages/pandas/core/indexes/datetimes.py in get_loc(self, key, method, tolerance)
729 except KeyError:
--> 730 raise KeyError(key)
731 except ValueError as e:
KeyError: datetime.date(2010, 1, 4)
During handling of the above exception, another exception occurred:
TypeError Traceback (most recent call last)
<ipython-input-7-d06631d74971> in <module>
----> 1 x.loc[dt.date(2010, 1, 2): dt.date(2010, 1, 4)]
~/.conda/envs/build/lib/python3.7/site-packages/xarray/core/dataarray.py in __getitem__(self, key)
194 labels = indexing.expanded_indexer(key, self.data_array.ndim)
195 key = dict(zip(self.data_array.dims, labels))
--> 196 return self.data_array.sel(**key)
197
198 def __setitem__(self, key, value) -> None:
~/.conda/envs/build/lib/python3.7/site-packages/xarray/core/dataarray.py in sel(self, indexers, method, tolerance, drop, **indexers_kwargs)
1049 method=method,
1050 tolerance=tolerance,
-> 1051 **indexers_kwargs,
1052 )
1053 return self._from_temp_dataset(ds)
~/.conda/envs/build/lib/python3.7/site-packages/xarray/core/dataset.py in sel(self, indexers, method, tolerance, drop, **indexers_kwargs)
2012 indexers = either_dict_or_kwargs(indexers, indexers_kwargs, ""sel"")
2013 pos_indexers, new_indexes = remap_label_indexers(
-> 2014 self, indexers=indexers, method=method, tolerance=tolerance
2015 )
2016 result = self.isel(indexers=pos_indexers, drop=drop)
~/.conda/envs/build/lib/python3.7/site-packages/xarray/core/coordinates.py in remap_label_indexers(obj, indexers, method, tolerance, **indexers_kwargs)
390
391 pos_indexers, new_indexes = indexing.remap_label_indexers(
--> 392 obj, v_indexers, method=method, tolerance=tolerance
393 )
394 # attach indexer's coordinate to pos_indexers
~/.conda/envs/build/lib/python3.7/site-packages/xarray/core/indexing.py in remap_label_indexers(data_obj, indexers, method, tolerance)
258 coords_dtype = data_obj.coords[dim].dtype
259 label = maybe_cast_to_coords_dtype(label, coords_dtype)
--> 260 idxr, new_idx = convert_label_indexer(index, label, dim, method, tolerance)
261 pos_indexers[dim] = idxr
262 if new_idx is not None:
~/.conda/envs/build/lib/python3.7/site-packages/xarray/core/indexing.py in convert_label_indexer(index, label, index_name, method, tolerance)
122 _sanitize_slice_element(label.start),
123 _sanitize_slice_element(label.stop),
--> 124 _sanitize_slice_element(label.step),
125 )
126 if not isinstance(indexer, slice):
~/.conda/envs/build/lib/python3.7/site-packages/pandas/core/indexes/datetimes.py in slice_indexer(self, start, end, step, kind)
806
807 try:
--> 808 return Index.slice_indexer(self, start, end, step, kind=kind)
809 except KeyError:
810 # For historical reasons DatetimeIndex by default supports
~/.conda/envs/build/lib/python3.7/site-packages/pandas/core/indexes/base.py in slice_indexer(self, start, end, step, kind)
4711 slice(1, 3)
4712 """"""
-> 4713 start_slice, end_slice = self.slice_locs(start, end, step=step, kind=kind)
4714
4715 # return a slice
~/.conda/envs/build/lib/python3.7/site-packages/pandas/core/indexes/base.py in slice_locs(self, start, end, step, kind)
4930 end_slice = None
4931 if end is not None:
-> 4932 end_slice = self.get_slice_bound(end, ""right"", kind)
4933 if end_slice is None:
4934 end_slice = len(self)
~/.conda/envs/build/lib/python3.7/site-packages/pandas/core/indexes/base.py in get_slice_bound(self, label, side, kind)
4843 except KeyError as err:
4844 try:
-> 4845 return self._searchsorted_monotonic(label, side)
4846 except ValueError:
4847 # raise the original KeyError
~/.conda/envs/build/lib/python3.7/site-packages/pandas/core/indexes/base.py in _searchsorted_monotonic(self, label, side)
4794 def _searchsorted_monotonic(self, label, side=""left""):
4795 if self.is_monotonic_increasing:
-> 4796 return self.searchsorted(label, side=side)
4797 elif self.is_monotonic_decreasing:
4798 # np.searchsorted expects ascending sort order, have to reverse
~/.conda/envs/build/lib/python3.7/site-packages/pandas/core/indexes/datetimes.py in searchsorted(self, value, side, sorter)
851 elif not isinstance(value, DatetimeArray):
852 raise TypeError(
--> 853 ""searchsorted requires compatible dtype or scalar, ""
854 f""not {type(value).__name__}""
855 )
TypeError: searchsorted requires compatible dtype or scalar, not date
```
```
commit: None
python: 3.7.6 | packaged by conda-forge | (default, Jan 7 2020, 22:33:48) [GCC 7.3.0]
python-bits: 64
OS: Linux
OS-release: 3.10.0-693.el7.x86_64
machine: x86_64
processor: x86_64
byteorder: little
LC_ALL: None
LANG: en_US.UTF-8
LOCALE: en_US.UTF-8
libhdf5: 1.10.5
libnetcdf: 4.7.3
xarray: 0.14.1
pandas: 1.0.0
numpy: 1.17.5
scipy: 1.4.1
netCDF4: 1.5.3
pydap: None
h5netcdf: 0.7.4
h5py: 2.10.0
Nio: None
zarr: None
cftime: 1.0.4.2
nc_time_axis: None
PseudoNetCDF: None
rasterio: None
cfgrib: None
iris: None
bottleneck: 1.3.1
dask: 2.10.1
distributed: 2.10.0
matplotlib: 3.1.2
cartopy: None
seaborn: 0.9.0
numbagg: installed
setuptools: 45.1.0.post20200119
pip: 20.0.2
conda: 4.8.2
pytest: None
IPython: 7.11.1
sphinx: None
```
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468157549,MDU6SXNzdWU0NjgxNTc1NDk=,3133,Add StringAccessor.format(),7441788,closed,0,,,0,2019-07-15T14:23:10Z,2019-07-15T19:49:09Z,2019-07-15T19:49:09Z,CONTRIBUTOR,,,,"Actually, on further thought I'm not sure how this should work, so I'm going to close this.","{""url"": ""https://api.github.com/repos/pydata/xarray/issues/3133/reactions"", ""total_count"": 1, ""+1"": 1, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,completed,13221727,issue
341664808,MDExOlB1bGxSZXF1ZXN0MjAxNzQ5NDg2,2293,ENH: format_array_flat() always displays first and last items.,7441788,closed,0,,,7,2018-07-16T20:21:47Z,2018-07-20T16:05:05Z,2018-07-20T16:04:51Z,CONTRIBUTOR,,0,pydata/xarray/pulls/2293," - [x] Closes #1186 (remove if there is no corresponding issue, which should only be the case for minor changes)
- [x] Tests added (for all bug fixes or enhancements)
- [x] Tests passed (for all non-documentation changes)
- [x] Fully documented, including `whats-new.rst` for all changes and `api.rst` for new API (remove if this change should not be visible to users, e.g., if it is an internal clean-up, or if this is part of a larger project that will be documented later)
","{""url"": ""https://api.github.com/repos/pydata/xarray/issues/2293/reactions"", ""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,,13221727,pull
197709208,MDU6SXNzdWUxOTc3MDkyMDg=,1186,Including last coordinate values when displaying coordinates,7441788,closed,0,,,2,2016-12-27T14:18:19Z,2018-07-20T16:04:51Z,2018-07-20T16:04:51Z,CONTRIBUTOR,,,,"I first posted this to https://groups.google.com/forum/#!topic/xarray/wjPtXMr91sg .
I'm afraid I'm not set up to submit a PR, but I think something like the following should work once one has created a ``last_n_items()`` similar to the existing ``first_n_items()``.
Also, I wonder if it would make sense to change the minimum number of items displayed from 1 to min(2, items_ndarray.size).
```
def format_array_flat(items_ndarray, max_width):
""""""Return a formatted string for as many items in the flattened version of
items_ndarray that will fit within max_width characters
""""""
# every item will take up at least two characters, but we always want to
# print at least one item
max_possibly_relevant = max(int(np.ceil(max_width / 2.0)), 1)
relevant_items = sum(([x, y] for (x, y) in
zip(first_n_items(items_ndarray, (max_possibly_relevant + 1) // 2),
reversed(last_n_items(items_ndarray, max_possibly_relevant // 2)))),
[])
pprint_items = format_items(relevant_items)
cum_len = np.cumsum([len(s) + 1 for s in pprint_items]) - 1
if (max_possibly_relevant < items_ndarray.size or
(cum_len > max_width).any()):
padding = u' ... '
count = max(np.argmax((cum_len + len(padding)) > max_width), 1)
else:
count = items_ndarray.size
padding = u'' if (count <= 1) else u' '
pprint_str = u' '.join(np.take(pprint_items, range(0, count, 2))) + padding + \
u' '.join(np.take(pprint_items, range(count - (count % 2) - 1, 0, -2)))
return pprint_str
```
","{""url"": ""https://api.github.com/repos/pydata/xarray/issues/1186/reactions"", ""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,completed,13221727,issue
341149017,MDExOlB1bGxSZXF1ZXN0MjAxMzkyMDMx,2285,ENH: format_array_flat() always displays first and last items.,7441788,closed,0,,,4,2018-07-13T20:25:03Z,2018-07-16T20:23:50Z,2018-07-16T20:20:39Z,CONTRIBUTOR,,0,pydata/xarray/pulls/2285," - [ ] Closes #1186 (remove if there is no corresponding issue, which should only be the case for minor changes)
- [ ] Tests added (for all bug fixes or enhancements)
- [ ] Tests passed (for all non-documentation changes)
- [ ] Fully documented, including `whats-new.rst` for all changes and `api.rst` for new API (remove if this change should not be visible to users, e.g., if it is an internal clean-up, or if this is part of a larger project that will be documented later)
","{""url"": ""https://api.github.com/repos/pydata/xarray/issues/2285/reactions"", ""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,,13221727,pull
292550002,MDU6SXNzdWUyOTI1NTAwMDI=,1864,BUG: ds['...'].sel(...).values throws exception for a ds loaded from file,7441788,closed,0,,,1,2018-01-29T20:31:52Z,2018-01-30T09:19:09Z,2018-01-30T09:19:09Z,CONTRIBUTOR,,,,"```python
import xarray as xr
ds = xr.Dataset(data_vars={'foo': xr.DataArray([1.], dims='abc', coords={'abc': ['a']})})
ds.to_netcdf(path='ds.nc', engine='h5netcdf')
ds1 = xr.open_dataset('ds.nc', engine='h5netcdf')
# ds1['foo'].values # uncomment to eliminate exception
ds1['foo'].sel(abc=['a']).values # throws ""TypeError: PointSelection __getitem__ only works with bool arrays""
```
#### Problem description
Accessing the DataArray's `.sel()` before `.values` leads to `TypeError: PointSelection __getitem__ only works with bool arrays`.
Accessing the DataArray's `.values` before the `.sel().values` eliminates the error.
#### Expected Output
array([ 1.])
#### Output of ``xr.show_versions()``
INSTALLED VERSIONS
------------------
commit: None
python: 3.6.4.final.0
python-bits: 64
OS: Windows
OS-release: 10
machine: AMD64
processor: Intel64 Family 6 Model 62 Stepping 4, GenuineIntel
byteorder: little
LC_ALL: None
LANG: None
LOCALE: None.None
xarray: 0.10.0
pandas: 0.22.0
numpy: 1.13.3
scipy: 1.0.0
netCDF4: None
h5netcdf: 0.5.0
Nio: None
bottleneck: 1.2.1
cyordereddict: None
dask: 0.16.1
matplotlib: 2.1.2
cartopy: None
seaborn: 0.8.1
setuptools: 38.4.0
pip: 9.0.1
conda: 4.3.33
pytest: 3.3.2
IPython: 6.2.1
sphinx: 1.6.6
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