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
584429748,MDU6SXNzdWU1ODQ0Mjk3NDg=,3867,macos py38 CI failing,2448579,closed,0,,,3,2020-03-19T13:54:10Z,2020-03-29T22:13:26Z,2020-03-29T22:13:26Z,MEMBER,,,,"`import matplotlib` is failing when it imports `PIL`

```python

E       ImportError: dlopen(/usr/local/miniconda/envs/xarray-tests/lib/python3.8/site-packages/PIL/_imaging.cpython-38-darwin.so, 2): Library not loaded: @rpath/libwebp.7.dylib
E         Referenced from: /usr/local/miniconda/envs/xarray-tests/lib/libtiff.5.dylib
E         Reason: Incompatible library version: libtiff.5.dylib requires version 9.0.0 or later, but libwebp.7.dylib provides version 8.0.0

/usr/local/miniconda/envs/xarray-tests/lib/python3.8/site-packages/PIL/Image.py:69: ImportError
```

","{""url"": ""https://api.github.com/repos/pydata/xarray/issues/3867/reactions"", ""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,completed,13221727,issue
200364693,MDU6SXNzdWUyMDAzNjQ2OTM=,1201,pass projection argument to plt.subplot when faceting with cartopy transform,731499,closed,0,,,10,2017-01-12T13:18:52Z,2020-03-29T16:30:29Z,2020-03-29T16:30:29Z,CONTRIBUTOR,,,,"I have a `data` 3D DataArray with `Time`, `Latitude` and `Longitude` coordinates.

I want to plot maps of this dataset, faceted by Time. The following code

```
import cartopy.crs as ccrs
proj = ccrs.PlateCarree()
data.plot(transform=proj, col='Time', col_wrap=3, robust=True)
```

fails with

``` 
ValueError: Axes should be an instance of GeoAxes, got <class 'matplotlib.axes._subplots.AxesSubplot'> 
```

this is because to plot with a transform, the axes must be a GeoAxes, which is done with something like `plt.subplot(111, projection=proj)`. The implicit subplotting done when faceting does not do that. To make the faceting works, I had to do

```
import cartopy.crs as ccrs
proj = ccrs.PlateCarree()
data.plot(transform=proj, col='Time', col_wrap=3, robust=True, subplot_kws={'projection':proj})
```

I propose that, when plot faceting is requested with a `transform` kw, the content of that keyword should be passed to the subplot function as a `projection` argument automatically by default. If a projection is provided explicitely like in the call above, use that one.","{""url"": ""https://api.github.com/repos/pydata/xarray/issues/1201/reactions"", ""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,completed,13221727,issue
502060636,MDU6SXNzdWU1MDIwNjA2MzY=,3368,Shift DataArray along a coordinate for different values of each element of another coordinate,49461634,closed,0,,,1,2019-10-03T13:17:10Z,2020-03-29T14:18:11Z,2020-03-29T14:16:43Z,NONE,,,,"#### MCVE Code Sample
<!-- In order for the maintainers to efficiently understand and prioritize issues, we ask you post a ""Minimal, Complete and Verifiable Example"" (MCVE): http://matthewrocklin.com/blog/work/2018/02/28/minimal-bug-reports -->

```python
# Your code here

Original_DataArray =  <xarray.DataArray 'Conexões Domésticas e Piscinas' (projetos_resi: 9, res_segmentacao: 21, time: 133, bands: 10)>

Shift_Map = <xarray.DataArray 'Anos por Desconto' (res_segmentacao: 21)>
array([ 0,  0,  0, 24,  0, 24,  0,  0,  0,  0,  0,  0,  0,  0,  0,  0, 24, 36,
       60, 36,  0])

#""Multi"" Shift Function

def _fn(dataArray,over_shift_index,multi_shift_index,shift_map,initialValues=None):
    """"""    
        -dataArray: dataarray to shift
        -over_shift_index: index over apply shit of dataarray 
        -multi_shift_index: index with the elements to apply a different value shift
        -shift_map: datarray indexed by multi_shift_index with the values to shift for each element
    """"""

    _da = dataArray.copy()
    _shift_map = shift_map.astype(int)
    
    for name, sl in _da.groupby(multi_shift_index.name):
        _shift = subscript(_shift_map, multi_shift_index, name ).values.tolist()
        _sl = sl.squeeze(multi_shift_index.name).shift(time = _shift)
    
        _dict = {multi_shift_index.name : name}
        _da.loc[_dict] = _sl
        

    return _da.fillna(0.)
```

#### Expected Output

Same estructure DataArray shifted along the ""time"" coordinate by a different value for each element of the ""res_segmentacao"" coordinate.

```python
exp_output= multidynamic( Original_DataArray , time, res_segmentacao, Shift_Map )
```

#### Problem Description

I´ve reached my objective but I wanted to consult if anyone had donde this in a more efficient way. Thanks!


","{""url"": ""https://api.github.com/repos/pydata/xarray/issues/3368/reactions"", ""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,completed,13221727,issue
327392061,MDU6SXNzdWUzMjczOTIwNjE=,2196,inconsistent time coordinates types ,35919497,closed,0,,,1,2018-05-29T16:14:27Z,2020-03-29T14:09:26Z,2020-03-29T14:09:26Z,COLLABORATOR,,,,"#### Code Sample, a copy-pastable example if possible


```python
import numpy as np
import pandas as pd
import xarray as xr

time = np.arange('2005-02-01', '2007-03-01', dtype='datetime64')
arr = xr.DataArray(
    np.arange(time.size), coords=[time,], dims=('time',), name='data'
)
arr.resample(time='M').interpolate('linear')

---------------------------------------------------------------------------
ValueError                                Traceback (most recent call last)
<ipython-input-7-6a92b6afe08e> in <module>()
      7     np.arange(time.size), coords=[time,], dims=('time',), name='data'
      8 )
----> 9 arr.resample(time='M').interpolate('linear')

~/devel/c3s-cns/venv_op/lib/python3.6/site-packages/xarray/core/resample.py in interpolate(self, kind)
    108 
    109         """"""
--> 110         return self._interpolate(kind=kind)
    111 
    112     def _interpolate(self, kind='linear'):

~/devel/c3s-cns/venv_op/lib/python3.6/site-packages/xarray/core/resample.py in _interpolate(self, kind)
    218             elif self._dim not in v.dims:
    219                 coords[k] = v
--> 220         return DataArray(f(new_x), coords, dims, name=dummy.name,
    221                          attrs=dummy.attrs)
    222 

~/devel/c3s-cns/venv_op/lib/python3.6/site-packages/scipy/interpolate/polyint.py in __call__(self, x)
     77         """"""
     78         x, x_shape = self._prepare_x(x)
---> 79         y = self._evaluate(x)
     80         return self._finish_y(y, x_shape)
     81 

~/devel/c3s-cns/venv_op/lib/python3.6/site-packages/scipy/interpolate/interpolate.py in _evaluate(self, x_new)
    632         y_new = self._call(self, x_new)
    633         if not self._extrapolate:
--> 634             below_bounds, above_bounds = self._check_bounds(x_new)
    635             if len(y_new) > 0:
    636                 # Note fill_value must be broadcast up to the proper size

~/devel/c3s-cns/venv_op/lib/python3.6/site-packages/scipy/interpolate/interpolate.py in _check_bounds(self, x_new)
    664                              ""range."")
    665         if self.bounds_error and above_bounds.any():
--> 666             raise ValueError(""A value in x_new is above the interpolation ""
    667                              ""range."")
    668 

ValueError: A value in x_new is above the interpolation range.
```
#### Problem description
The internal format of _arr.time_ is  datetime64[D]

```python
arr.time 

<xarray.DataArray 'time' (time: 758)>
array(['2005-02-01', '2005-02-02', '2005-02-03', ..., '2007-02-26',
       '2007-02-27', '2007-02-28'], dtype='datetime64[D]')
Coordinates:
  * time     (time) datetime64[D] 2005-02-01 2005-02-02 2005-02-03 ...
```
Internally there is a cast to float,  for both the old time indices **_x_** and the new time indices **_new_x_**, but the new time indices are in  datetime64[ns], so they don't match.

DataArrayResample._interpolate

```python
       x = self._obj[self._dim].astype('float')
       y = self._obj.data

       axis = self._obj.get_axis_num(self._dim)

       f = interp1d(x, y, kind=kind, axis=axis, bounds_error=True,
                    assume_sorted=True)
       new_x = self._full_index.values.astype('float')
```
With a cast to datetime64[ns]  it works:

```python
import numpy as np
import pandas as pd
import xarray as xr

time = np.arange('2005-02-01', '2007-03-01', dtype='datetime64').astype('datetime64[ns]')
arr = xr.DataArray(
    np.arange(time.size), coords=[time,], dims=('time',), name='data'
)
arr.resample(time='M').interpolate('linear')
<xarray.DataArray 'data' (time: 25)>
array([ 27.,  58.,  88., 119., 149., 180., 211., 241., 272., 302., 333., 364.,
       392., 423., 453., 484., 514., 545., 576., 606., 637., 667., 698., 729.,
       757.])
Coordinates:
  * time     (time) datetime64[ns] 2005-02-28 2005-03-31 2005-04-30 ...
```

#### Expected Output

```python
<xarray.DataArray 'data' (time: 25)>
array([ 27.,  58.,  88., 119., 149., 180., 211., 241., 272., 302., 333., 364.,
       392., 423., 453., 484., 514., 545., 576., 606., 637., 667., 698., 729.,
       757.])
Coordinates:
  * time     (time) datetime64[ns] 2005-02-28 2005-03-31 2005-04-30 ...
```

#### Output of ``xr.show_versions()``

<details>

INSTALLED VERSIONS
------------------
commit: None
python: 3.6.0.final.0
python-bits: 64
OS: Linux
OS-release: 4.13.0-43-generic
machine: x86_64
processor: x86_64
byteorder: little
LC_ALL: None
LANG: en_GB.UTF-8
LOCALE: en_GB.UTF-8

xarray: 0.10.4
pandas: 0.20.3
numpy: 1.13.1
scipy: 1.0.0
netCDF4: 1.3.1
h5netcdf: None
h5py: None
Nio: None
zarr: None
bottleneck: None
cyordereddict: None
dask: 0.16.1
distributed: None
matplotlib: 2.0.2
cartopy: None
seaborn: None
setuptools: 38.4.0
pip: 10.0.1
conda: None
pytest: 3.4.0
IPython: 6.1.0
sphinx: None
</details>
","{""url"": ""https://api.github.com/repos/pydata/xarray/issues/2196/reactions"", ""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,completed,13221727,issue
445355249,MDU6SXNzdWU0NDUzNTUyNDk=,2970,decode_cf,6872529,closed,0,,,1,2019-05-17T09:41:28Z,2020-03-29T14:02:24Z,2020-03-29T14:02:24Z,NONE,,,,"To me this name is a bit confusing as it actually _encodes_ an in memory object to look like a _decoded_ netcdf file.

I have a class which inherits (I know about `dataset_accessor`, still seems easier to simply inherit...) ``xarray.Dataset`` to which I've added a method `_make_cf`:

```python
import xarray as xr
class XResult(xr.Dataset):
    def __init__(self, data=None, coords=None, attrs=None, **kwargs):
        if isinstance(data, str):
            kwargs = dict(READ_KWARGS, **kwargs)
            with xr.open_dataset(data, **kwargs) as data:
                attrs = data.attrs

        super().__init__(data, coords, attrs)
        self._make_cf()

    def _make_cf(self):
        self = xr.decode_cf(self)
```
I expect the XResult object to be _decoded_ but it is not.

if I do `xresult = xarray.decode_cf(XResult(...))` than the object is indeed _decoded_ but is no longer an `XResult` object and loses the attached functionality.

It would be quite convenient to have a `decode_cf` or `encode_cf` method part of the `Dataset` class that will operate inplace.","{""url"": ""https://api.github.com/repos/pydata/xarray/issues/2970/reactions"", ""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,completed,13221727,issue
438694589,MDU6SXNzdWU0Mzg2OTQ1ODk=,2932,Facetgrid: colors beyond range (extend) not saturated,7933853,closed,0,,,5,2019-04-30T09:56:46Z,2020-03-29T13:26:43Z,2020-03-29T13:26:42Z,NONE,,,,"#### Code Sample, a copy-pastable example if possible

![Screen Shot 2019-04-30 at 11 59 30](https://user-images.githubusercontent.com/7933853/56954588-70238b00-6b3f-11e9-90ad-81045e500987.png)


Minimal example here:
https://github.com/lvankampenhout/bug-reports/blob/master/Facetgrid_cmap_extend.ipynb

#### Problem description

The extreme colors of neither the pcolormesh or colorbar (using extend='both') are not saturated as they should when faceting.

#### Output of ``xr.show_versions()``

<details>
INSTALLED VERSIONS
------------------
commit: None
python: 3.6.8 |Anaconda custom (x86_64)| (default, Dec 29 2018, 19:04:46) 
[GCC 4.2.1 Compatible Clang 4.0.1 (tags/RELEASE_401/final)]
python-bits: 64
OS: Darwin
OS-release: 17.7.0
machine: x86_64
processor: i386
byteorder: little
LC_ALL: C
LANG: None
LOCALE: None.None
libhdf5: 1.10.1
libnetcdf: 4.4.1.1

xarray: 0.12.1
pandas: 0.23.4
numpy: 1.14.2
scipy: 0.18.1
netCDF4: 1.3.1
pydap: None
h5netcdf: None
h5py: 2.7.1
Nio: None
zarr: None
cftime: 1.0.0b1
nc_time_axis: None
PseudonetCDF: None
rasterio: None
cfgrib: None
iris: None
bottleneck: 1.2.0
dask: 0.13.0
distributed: None
matplotlib: 3.0.2
cartopy: 0.16.0
seaborn: 0.7.1
setuptools: 38.5.1
pip: 9.0.1
conda: 4.6.14
pytest: 3.0.5
IPython: 5.1.0
sphinx: 1.5.1
</details>
","{""url"": ""https://api.github.com/repos/pydata/xarray/issues/2932/reactions"", ""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,completed,13221727,issue
561312864,MDU6SXNzdWU1NjEzMTI4NjQ=,3759,Truncate long lines in repr of coords,5635139,closed,0,,,1,2020-02-06T22:41:13Z,2020-03-29T09:58:46Z,2020-03-29T09:58:45Z,MEMBER,,,,"#### MCVE Code Sample
<!-- In order for the maintainers to efficiently understand and prioritize issues, we ask you post a ""Minimal, Complete and Verifiable Example"" (MCVE): http://matthewrocklin.com/blog/work/2018/02/28/minimal-bug-reports -->

```python
xr.DataArray(coords=dict(a=' '.join(['hello world' for _ in range(100)])))

<xarray.DataArray ()>
array(nan)
Coordinates:
    a        <U5999 'hello world hello world hello world hello world hello world hello world hello world hello world hello world hello world hello world hello world hello world hello world hello world hello world hello world hello world hello world hello world hello world hello world hello world hello world hello world hello world hello world hello world hello world hello world hello world hello world hello world hello world hello  world hello world hello world hello world hello world hello world hello world hello world hello world hello world hello world hello world hello world hello world hello world hello world hello world hello world hello world hello world hello world hello world hello world hello world hello world hello world hello world hello world hello world hello world hello world hello world hello world hello world hello world hello world hello world hello world hello world hello world hello world hello world hello world hello world hello world hello world hello world hello world hello world hello world hello world hello world hello world hello world hello world hello world hello world hello world hello world hello world hello world hello world hello world hello world hello world hello world hello world hello world hello world hello world hello world hello world hello world hello world hello world hello world hello world hello world hello world hello world hello world hello world hello world hello world hello world hello world hello world hello world hello world hello world'
```

#### Expected Output

```
<xarray.DataArray ()>
array(nan)
Coordinates:
    a        <U5999 'hello world ... hello world'
```

#### Problem Description
<!-- this should explain why the current behavior is a problem and why the expected output is a better solution -->

I think mostly the same as https://github.com/pydata/xarray/issues/1319 but for coords

#### Output of ``xr.show_versions()``
<details>
INSTALLED VERSIONS
------------------
commit: None
python: 3.7.3 | packaged by conda-forge | (default, Jul  1 2019, 21:52:21) 
[GCC 7.3.0]
python-bits: 64
OS: Linux
OS-release: [...]
machine: x86_64
processor: x86_64
byteorder: little
LC_ALL: None
LANG: en_US.utf8
LOCALE: en_US.UTF-8
libhdf5: 1.10.5
libnetcdf: 4.7.1

xarray: 0.15.0
pandas: 0.25.3
numpy: 1.17.3
scipy: 1.3.2
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: 1.2.1
dask: 2.7.0
distributed: 2.7.0
matplotlib: 3.1.2
cartopy: None
seaborn: 0.9.0
numbagg: None
setuptools: 41.6.0.post20191101
pip: 19.3.1
conda: None
pytest: 5.2.2
IPython: 7.9.0
sphinx: 2.2.1
</details>
","{""url"": ""https://api.github.com/repos/pydata/xarray/issues/3759/reactions"", ""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,completed,13221727,issue
588821932,MDU6SXNzdWU1ODg4MjE5MzI=,3899,_indexes of DataArray are not deep copied,2272878,closed,0,,,4,2020-03-27T01:19:07Z,2020-03-29T02:01:20Z,2020-03-29T02:01:20Z,CONTRIBUTOR,,,,"In `DataArray.copy`, the `_indexes` attributes is not deep copied.  After pull request #3840, this causes deleting a coordinate of a copy will also delete that coordinate from the original, even for deep copies.

#### MCVE Code Sample
<!-- In order for the maintainers to efficiently understand and prioritize issues, we ask you post a ""Minimal, Complete and Verifiable Example"" (MCVE): http://matthewrocklin.com/blog/work/2018/02/28/minimal-bug-reports -->

```python
a0 = xr.DataArray(
    np.array([[1, 2, 3], [4, 5, 6]]),
    dims=[""y"", ""x""],
    coords={""x"": [""a"", ""b"", ""c""], ""y"": [-1, 1]},
)

a1 = a0.copy()
del a1.coords[""y""]

xr.tests.assert_identical(a0, a0)
```

The result is:

```
xarray/testing.py:272: in _assert_internal_invariants
    _assert_dataarray_invariants(xarray_obj)
xarray/testing.py:222: in _assert_dataarray_invariants
    _assert_indexes_invariants_checks(da._indexes, da._coords, da.dims)
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _

indexes = {'x': Index(['a', 'b', 'c'], dtype='object', name='x')}, possible_coord_variables = {'x': <xarray.IndexVariable 'x' (x: 3)>
array(['a', 'b', 'c'], dtype='<U1'), 'y': <xarray.IndexVariable 'y' (y: 2)>
array([-1,  1])}
dims = ('y', 'x')

    def _assert_indexes_invariants_checks(indexes, possible_coord_variables, dims):
        assert isinstance(indexes, dict), indexes
        assert all(isinstance(v, pd.Index) for v in indexes.values()), {
            k: type(v) for k, v in indexes.items()
        }
    
        index_vars = {
            k for k, v in possible_coord_variables.items() if isinstance(v, IndexVariable)
        }
        assert indexes.keys() <= index_vars, (set(indexes), index_vars)
    
        # Note: when we support non-default indexes, these checks should be opt-in
        # only!
        defaults = default_indexes(possible_coord_variables, dims)
>       assert indexes.keys() == defaults.keys(), (set(indexes), set(defaults))
E       AssertionError: ({'x'}, {'y', 'x'})

xarray/testing.py:185: AssertionError
```

#### Expected Output

The test should pass.

#### Problem Description

Doing a deep copy should make a copy of everything.  Changing a deep copy should not alter the original in any way.","{""url"": ""https://api.github.com/repos/pydata/xarray/issues/3899/reactions"", ""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,completed,13221727,issue
29136905,MDU6SXNzdWUyOTEzNjkwNQ==,60,Implement DataArray.idxmax(),1217238,closed,0,,741199,14,2014-03-10T22:03:06Z,2020-03-29T01:54:25Z,2020-03-29T01:54:25Z,MEMBER,,,,"Should match the pandas function: http://pandas.pydata.org/pandas-docs/stable/generated/pandas.DataFrame.idxmax.html
","{""url"": ""https://api.github.com/repos/pydata/xarray/issues/60/reactions"", ""total_count"": 2, ""+1"": 2, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,completed,13221727,issue