issues: 181099871

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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
181099871 MDU6SXNzdWUxODEwOTk4NzE= 1039 NetCDF4 backend fails with single-value dimension 5184063 closed 0 1217238   1 2016-10-05T09:03:52Z 2017-06-17T00:14:32Z 2017-06-17T00:14:32Z NONE      

Exporting and xarray object with a string dimension which only consists of a single value fails using python 3 and xarray 0.8.2.

Here is an example to reproduce the error using the toy weather data from the tutorials:

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

times = pd.date_range('2000-01-01', '2001-12-31', name='time') annual_cycle = np.sin(2 * np.pi * (times.dayofyear / 365.25 - 0.28))

base = 10 + 15 * annual_cycle.reshape(-1, 1) tmin_values = base + 3 * np.random.randn(annual_cycle.size, 3) tmax_values = base + 10 + 3 * np.random.randn(annual_cycle.size, 3)

ds = xr.Dataset({'tmin': (('time', 'location'), tmin_values), 'tmax': (('time', 'location'), tmax_values)}, {'time': times, 'location': ['IA', 'IN', 'IL']}) ```

The following function call fails for me with a TypeError: len() of unsized object:

python ds.sel(location="IA").to_netcdf("asdf", engine="netcdf4")

The lower part of the traceback:

``` pytb D:\Anaconda3\lib\site-packages\xarray\backends\netCDF4_.py in prepare_variable(self, name, variable, check_encoding) 250 251 if self.format == 'NETCDF4': --> 252 variable, datatype = _nc4_values_and_dtype(variable) 253 else: 254 variable = encode_nc3_variable(variable)

D:\Anaconda3\lib\site-packages\xarray\backends\netCDF4_.py in _nc4_values_and_dtype(var) 75 if var.dtype.kind == 'U': 76 # this entire clause should not be necessary with netCDF4>=1.0.9 ---> 77 if len(var) > 0: 78 var = var.astype('O') 79 dtype = str

D:\Anaconda3\lib\site-packages\xarray\core\utils.py in len(self) 371 return self.shape[0] 372 except IndexError: --> 373 raise TypeError('len() of unsized object') 374 375 ```

The export works fine both without the selection:

python ds.to_netcdf("asdf", engine="netcdf4")

And with dropping the dimension after:

python ds.sel(location="IA").drop("location").to_netcdf("asdf", engine="netcdf4")

 
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