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  • xarray · 2 ✖
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
425905002 MDU6SXNzdWU0MjU5MDUwMDI= 2854 Assign values to DataArray after interpolating Dataset produces an error dalonsoa 6095790 closed 0     2 2019-03-27T11:27:46Z 2019-04-04T21:58:24Z 2019-04-04T21:58:24Z NONE      

Code Sample, a copy-pastable example if possible

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

da = xr.DataArray( np.random.random((3, 4)), dims=["assets", "year"], coords={"year": range(2010, 2018, 2)} )

Interpolate directly the DataArray

new_da = da.interp(year=[2011, 2015]) new_da.loc[{"year": 2015}] = 42 # WORKS! print(new_da)

Interpolate DataArray as part of a Dataset

dset = xr.Dataset({"my_array": da.copy()}).interp(year=[2011, 2015]) new_da = dset.my_array new_da.loc[{"year": 2015}] = 42 # DOESN'T WORK! print(new_da) ```

Problem description

Assigning a value to some locations of a DataArray after it has been interpolated raises an IndexError. This does not occur when the DataArray is interpolated independently, only occurs when the DataArray has been interpolated as part of a Dataset.

This problem is not present in xarray<0.12.0

Expected Output

The above example should print new_da in both cases, with the values corresponding to year 2015 replaced by 42. That works in the first case, but fails in the second raising IndexError.

Although I am not sure if it is the cause of this error, I have found that in the first case the array indexes are present and contain [2011, 2015], but they are an empty OrderDict in the second case.

Output of xr.show_versions()

INSTALLED VERSIONS ------------------ commit: None python: 3.7.1 (default, Nov 6 2018, 18:46:03) [Clang 10.0.0 (clang-1000.11.45.5)] python-bits: 64 OS: Darwin OS-release: 18.2.0 machine: x86_64 processor: i386 byteorder: little LC_ALL: None LANG: None LOCALE: en_GB.UTF-8 libhdf5: 1.10.2 libnetcdf: 4.4.1.1 xarray: 0.12.0 pandas: 0.23.4 numpy: 1.15.4 scipy: 1.1.0 netCDF4: 1.4.2 pydap: None h5netcdf: None h5py: None Nio: None zarr: None cftime: 1.0.3.4 nc_time_axis: None PseudonetCDF: None rasterio: None cfgrib: None iris: None bottleneck: 1.2.1 dask: None distributed: None matplotlib: 3.0.2 cartopy: None seaborn: 0.9.0 setuptools: 40.5.0 pip: 18.1 conda: None pytest: 4.0.2 IPython: 7.1.1 sphinx: None 
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   completed xarray 13221727 issue
427398236 MDU6SXNzdWU0MjczOTgyMzY= 2856 Roundtripping between a dimension coordinate and scalar coordinate on a Dataset spencerkclark 6628425 closed 0     4 2019-03-31T13:42:39Z 2019-04-04T21:58:24Z 2019-04-04T21:58:24Z MEMBER      

Code Sample, a copy-pastable example if possible

In xarray 0.12.0 the following example produces a Dataset with no indexes: ``` In [1]: import xarray as xr

In [2]: da = xr.DataArray([1], [('x', [0])], name='a')

In [3]: da.to_dataset().isel(x=0).expand_dims('x').indexes Out[3]: ```

Expected Output

In xarray 0.11.3 the roundtrip sequence above properly recovers the initial index along the 'x' dimension: ``` In [1]: import xarray as xr

In [2]: da = xr.DataArray([1], [('x', [0])], name='a')

In [3]: da.to_dataset().isel(x=0).expand_dims('x').indexes Out[3]: x: Int64Index([0], dtype='int64', name='x') ```

Output of xr.show_versions()

``` INSTALLED VERSIONS ------------------ commit: None python: 3.6.7 | packaged by conda-forge | (default, Feb 28 2019, 02:16:08) [GCC 4.2.1 Compatible Clang 4.0.1 (tags/RELEASE_401/final)] python-bits: 64 OS: Darwin OS-release: 18.2.0 machine: x86_64 processor: i386 byteorder: little LC_ALL: None LANG: en_US.UTF-8 LOCALE: en_US.UTF-8 libhdf5: 1.10.1 libnetcdf: 4.6.1 xarray: 0.12.0 pandas: 0.24.2 numpy: 1.13.1 scipy: 0.19.1 netCDF4: 1.4.0 pydap: None h5netcdf: 0.5.1 h5py: 2.8.0 Nio: None zarr: None cftime: 1.0.0 nc_time_axis: None PseudonetCDF: None rasterio: None cfgrib: None iris: None bottleneck: 1.2.0 dask: 0.17.5 distributed: 1.21.8 matplotlib: 2.0.2 cartopy: None seaborn: None setuptools: 40.5.0 pip: 9.0.1 conda: None pytest: 3.10.0 IPython: 6.4.0 sphinx: 1.7.4 ``` 

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   completed xarray 13221727 issue

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