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/6490#issuecomment-1101519903,https://api.github.com/repos/pydata/xarray/issues/6490,1101519903,IC_kwDOAMm_X85Bp9wf,5635139,2022-04-18T15:57:10Z,2022-04-18T15:57:10Z,MEMBER,"OK, cheers @javedali99 !","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,1206496679
https://github.com/pydata/xarray/issues/6490#issuecomment-1101518164,https://api.github.com/repos/pydata/xarray/issues/6490,1101518164,IC_kwDOAMm_X85Bp9VU,15319503,2022-04-18T15:54:30Z,2022-04-18T15:54:30Z,NONE,"Thanks @dcherian @max-sixty. 

I solved the issue with re-installing `xarray` and `cfgrib`  individually and re-starting the kernel.","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,1206496679
https://github.com/pydata/xarray/issues/6490#issuecomment-1101504397,https://api.github.com/repos/pydata/xarray/issues/6490,1101504397,IC_kwDOAMm_X85Bp5-N,2448579,2022-04-18T15:35:23Z,2022-04-18T15:35:23Z,MEMBER,"
```
# subsetting the data based on boundary coordinates
ds_sel = ds2011_2014.isel(lon=(ds2011_2014.lon >= left) & (ds2011_2014.lon <= right),
                          lat=(ds2011_2014.lat >= bottom) & (ds2011_2014.lat <= top),
                          )
```

Please use the `sel` method instead of a boolean mask. This will work for this dataset because `lat` and `lon` are dimension coordinates.

See https://docs.xarray.dev/en/stable/user-guide/indexing.html
","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,1206496679
https://github.com/pydata/xarray/issues/6490#issuecomment-1101071306,https://api.github.com/repos/pydata/xarray/issues/6490,1101071306,IC_kwDOAMm_X85BoQPK,5635139,2022-04-18T04:08:39Z,2022-04-18T04:08:39Z,MEMBER,"I'm getting a different error around the encoding — please could the MVCE not use external data? Check out the link on the label, or the issue template, for more tips. Thanks

<details>

```python
---------------------------------------------------------------------------
KeyError                                  Traceback (most recent call last)
File /srv/conda/envs/notebook/lib/python3.8/site-packages/xarray/backends/file_manager.py:199, in CachingFileManager._acquire_with_cache_info(self, needs_lock)
    198 try:
--> 199     file = self._cache[self._key]
    200 except KeyError:

File /srv/conda/envs/notebook/lib/python3.8/site-packages/xarray/backends/lru_cache.py:53, in LRUCache.__getitem__(self, key)
     52 with self._lock:
---> 53     value = self._cache[key]
     54     self._cache.move_to_end(key)

KeyError: [<class 'netCDF4._netCDF4.Dataset'>, ('/home/jovyan/precip.V1.0.2014.nc',), 'r', (('clobber', True), ('diskless', False), ('format', 'NETCDF4'), ('persist', False))]

During handling of the above exception, another exception occurred:

OSError                                   Traceback (most recent call last)
Input In [5], in <module>
      1 # combine netcdf files
----> 2 ds2011_2014 = xr.open_mfdataset('precip.V1.0.*.nc', concat_dim='time', combine='nested', engine='netcdf4')

File /srv/conda/envs/notebook/lib/python3.8/site-packages/xarray/backends/api.py:908, in open_mfdataset(paths, chunks, concat_dim, compat, preprocess, engine, data_vars, coords, combine, parallel, join, attrs_file, combine_attrs, **kwargs)
    905     open_ = open_dataset
    906     getattr_ = getattr
--> 908 datasets = [open_(p, **open_kwargs) for p in paths]
    909 closers = [getattr_(ds, ""_close"") for ds in datasets]
    910 if preprocess is not None:

File /srv/conda/envs/notebook/lib/python3.8/site-packages/xarray/backends/api.py:908, in <listcomp>(.0)
    905     open_ = open_dataset
    906     getattr_ = getattr
--> 908 datasets = [open_(p, **open_kwargs) for p in paths]
    909 closers = [getattr_(ds, ""_close"") for ds in datasets]
    910 if preprocess is not None:

File /srv/conda/envs/notebook/lib/python3.8/site-packages/xarray/backends/api.py:495, in open_dataset(filename_or_obj, engine, chunks, cache, decode_cf, mask_and_scale, decode_times, decode_timedelta, use_cftime, concat_characters, decode_coords, drop_variables, backend_kwargs, *args, **kwargs)
    483 decoders = _resolve_decoders_kwargs(
    484     decode_cf,
    485     open_backend_dataset_parameters=backend.open_dataset_parameters,
   (...)
    491     decode_coords=decode_coords,
    492 )
    494 overwrite_encoded_chunks = kwargs.pop(""overwrite_encoded_chunks"", None)
--> 495 backend_ds = backend.open_dataset(
    496     filename_or_obj,
    497     drop_variables=drop_variables,
    498     **decoders,
    499     **kwargs,
    500 )
    501 ds = _dataset_from_backend_dataset(
    502     backend_ds,
    503     filename_or_obj,
   (...)
    510     **kwargs,
    511 )
    512 return ds

File /srv/conda/envs/notebook/lib/python3.8/site-packages/xarray/backends/netCDF4_.py:553, in NetCDF4BackendEntrypoint.open_dataset(self, filename_or_obj, mask_and_scale, decode_times, concat_characters, decode_coords, drop_variables, use_cftime, decode_timedelta, group, mode, format, clobber, diskless, persist, lock, autoclose)
    532 def open_dataset(
    533     self,
    534     filename_or_obj,
   (...)
    549     autoclose=False,
    550 ):
    552     filename_or_obj = _normalize_path(filename_or_obj)
--> 553     store = NetCDF4DataStore.open(
    554         filename_or_obj,
    555         mode=mode,
    556         format=format,
    557         group=group,
    558         clobber=clobber,
    559         diskless=diskless,
    560         persist=persist,
    561         lock=lock,
    562         autoclose=autoclose,
    563     )
    565     store_entrypoint = StoreBackendEntrypoint()
    566     with close_on_error(store):

File /srv/conda/envs/notebook/lib/python3.8/site-packages/xarray/backends/netCDF4_.py:382, in NetCDF4DataStore.open(cls, filename, mode, format, group, clobber, diskless, persist, lock, lock_maker, autoclose)
    376 kwargs = dict(
    377     clobber=clobber, diskless=diskless, persist=persist, format=format
    378 )
    379 manager = CachingFileManager(
    380     netCDF4.Dataset, filename, mode=mode, kwargs=kwargs
    381 )
--> 382 return cls(manager, group=group, mode=mode, lock=lock, autoclose=autoclose)

File /srv/conda/envs/notebook/lib/python3.8/site-packages/xarray/backends/netCDF4_.py:330, in NetCDF4DataStore.__init__(self, manager, group, mode, lock, autoclose)
    328 self._group = group
    329 self._mode = mode
--> 330 self.format = self.ds.data_model
    331 self._filename = self.ds.filepath()
    332 self.is_remote = is_remote_uri(self._filename)

File /srv/conda/envs/notebook/lib/python3.8/site-packages/xarray/backends/netCDF4_.py:391, in NetCDF4DataStore.ds(self)
    389 @property
    390 def ds(self):
--> 391     return self._acquire()

File /srv/conda/envs/notebook/lib/python3.8/site-packages/xarray/backends/netCDF4_.py:385, in NetCDF4DataStore._acquire(self, needs_lock)
    384 def _acquire(self, needs_lock=True):
--> 385     with self._manager.acquire_context(needs_lock) as root:
    386         ds = _nc4_require_group(root, self._group, self._mode)
    387     return ds

File /srv/conda/envs/notebook/lib/python3.8/contextlib.py:113, in _GeneratorContextManager.__enter__(self)
    111 del self.args, self.kwds, self.func
    112 try:
--> 113     return next(self.gen)
    114 except StopIteration:
    115     raise RuntimeError(""generator didn't yield"") from None

File /srv/conda/envs/notebook/lib/python3.8/site-packages/xarray/backends/file_manager.py:187, in CachingFileManager.acquire_context(self, needs_lock)
    184 @contextlib.contextmanager
    185 def acquire_context(self, needs_lock=True):
    186     """"""Context manager for acquiring a file.""""""
--> 187     file, cached = self._acquire_with_cache_info(needs_lock)
    188     try:
    189         yield file

File /srv/conda/envs/notebook/lib/python3.8/site-packages/xarray/backends/file_manager.py:205, in CachingFileManager._acquire_with_cache_info(self, needs_lock)
    203     kwargs = kwargs.copy()
    204     kwargs[""mode""] = self._mode
--> 205 file = self._opener(*self._args, **kwargs)
    206 if self._mode == ""w"":
    207     # ensure file doesn't get overridden when opened again
    208     self._mode = ""a""

File src/netCDF4/_netCDF4.pyx:2307, in netCDF4._netCDF4.Dataset.__init__()

File src/netCDF4/_netCDF4.pyx:1925, in netCDF4._netCDF4._ensure_nc_success()

OSError: [Errno -101] NetCDF: HDF error: b'/home/jovyan/precip.V1.0.2014.nc'

</details>","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,1206496679
https://github.com/pydata/xarray/issues/6490#issuecomment-1101061409,https://api.github.com/repos/pydata/xarray/issues/6490,1101061409,IC_kwDOAMm_X85BoN0h,15319503,2022-04-18T03:38:43Z,2022-04-18T03:38:43Z,NONE,"> @javedali99 please could you supply an MVCE?

```python
# download data
for yr in range(2011,2015): 
    url = f'https://downloads.psl.noaa.gov/Datasets/cpc_us_precip/RT/precip.V1.0.{yr}.nc'
    savename = url.split('/')[-1]
    urllib.request.urlretrieve(url,savename)

# combine netcdf files
ds2011_2014 = xr.open_mfdataset('precip.V1.0.*.nc', concat_dim='time', combine='nested')

# coordinates
top = 40
bottom = 37
left = 258
right = 265.4 

# subsetting the data based on boundary coordinates
ds_sel = ds2011_2014.isel(lon=(ds2011_2014.lon >= left) & (ds2011_2014.lon <= right),
                          lat=(ds2011_2014.lat >= bottom) & (ds2011_2014.lat <= top),
                          )
```
","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,1206496679
https://github.com/pydata/xarray/issues/6490#issuecomment-1100958666,https://api.github.com/repos/pydata/xarray/issues/6490,1100958666,IC_kwDOAMm_X85Bn0vK,5635139,2022-04-17T22:19:43Z,2022-04-17T22:19:43Z,MEMBER,@javedali99 please could you supply an MVCE?,"{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,1206496679