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/5223#issuecomment-827675422,https://api.github.com/repos/pydata/xarray/issues/5223,827675422,MDEyOklzc3VlQ29tbWVudDgyNzY3NTQyMg==,14808389,2021-04-27T15:00:40Z,2021-04-27T18:15:02Z,MEMBER,"> [`xarray-simlab`] stores the `_FillValue` as an attribute which in turn is used by netcdf
that might be a bug in `xarray-simlab` (cc @benbovy). Usually, the fill value is used to replace missing values on disk. For example,
```python
np.array([0, np.nan, 2, np.nan, np.nan, 5])
```
with a fill value of `-1` could be encoded as `[0, -1, 2, -1, -1, 5]` before writing to disk, which can be saved as a `int` (`int8`, even) instead of a `float`. Same for datetimes: `[""2020-01-01"", ""NaT"", ""2020-12-01""]` with a fill value of `-1` can be encoded as `[0, -1, 11]` with `units = ""months since 2020-01-01""` and the standard calendar. As far as I understand it, using `np.datetime64(""NaT"")` as fill value does not make much sense because netCDF does not support datetime dtypes:
traceback when trying to save a datetime array attribute
```pytb
TypeError Traceback (most recent call last)
in
1 import numpy as np
2 import xarray as xr
----> 3 xr.Dataset(attrs={""_FillValue"": np.array(""NaT"", dtype=""M"")}).to_netcdf(""test.nc"")
.../xarray/core/dataset.py in to_netcdf(self, path, mode, format, group, engine, encoding, unlimited_dims, compute, invalid_netcdf)
1752 from ..backends.api import to_netcdf
1753
-> 1754 return to_netcdf(
1755 self,
1756 path,
.../xarray/backends/api.py in to_netcdf(dataset, path_or_file, mode, format, group, engine, encoding, unlimited_dims, compute, multifile, invalid_netcdf)
1066 # TODO: allow this work (setting up the file for writing array data)
1067 # to be parallelized with dask
-> 1068 dump_to_store(
1069 dataset, store, writer, encoding=encoding, unlimited_dims=unlimited_dims
1070 )
.../xarray/backends/api.py in dump_to_store(dataset, store, writer, encoder, encoding, unlimited_dims)
1113 variables, attrs = encoder(variables, attrs)
1114
-> 1115 store.store(variables, attrs, check_encoding, writer, unlimited_dims=unlimited_dims)
1116
1117
.../xarray/backends/common.py in store(self, variables, attributes, check_encoding_set, writer, unlimited_dims)
263 variables, attributes = self.encode(variables, attributes)
264
--> 265 self.set_attributes(attributes)
266 self.set_dimensions(variables, unlimited_dims=unlimited_dims)
267 self.set_variables(
.../xarray/backends/common.py in set_attributes(self, attributes)
280 """"""
281 for k, v in attributes.items():
--> 282 self.set_attribute(k, v)
283
284 def set_variables(self, variables, check_encoding_set, writer, unlimited_dims=None):
.../xarray/backends/netCDF4_.py in set_attribute(self, key, value)
449 self.ds.setncattr_string(key, value)
450 else:
--> 451 self.ds.setncattr(key, value)
452
453 def encode_variable(self, variable):
src/netCDF4/_netCDF4.pyx in netCDF4._netCDF4.Dataset.setncattr()
src/netCDF4/_netCDF4.pyx in netCDF4._netCDF4._set_att()
TypeError: illegal data type for attribute b'_FillValue', must be one of dict_keys(['S1', 'i1', 'u1', 'i2', 'u2', 'i4', 'u4', 'i8', 'u8', 'f4', 'f8']), got M8
```