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/1846#issuecomment-374583416,https://api.github.com/repos/pydata/xarray/issues/1846,374583416,MDEyOklzc3VlQ29tbWVudDM3NDU4MzQxNg==,10050469,2018-03-20T12:42:21Z,2018-03-20T12:42:21Z,MEMBER,"Reopening this issue as there is still a list of possible TODOs, as per @shoyer [comment](https://github.com/pydata/xarray/pull/1972#issuecomment-373954379):

- [ ] Consistency with pandas for groupby/rolling aggregations.
- [ ] Roundtrip writing/reading data to netCDF. There are a couple of known exceptions (e.g., dtypes not supported by netCDF and MultiIndex) but otherwise every xarray object should be serializable to netCDF and back without data loss.
- [ ]  Roundtrip to/from pandas Series/DataFrame with `to_series()`/`to_dataframe()`/`to_xarray()`.
- [ ]  Indexing consistency tests for backends: all indexing operations should be supported consistently on data accessed from any backend.
- [ ]  NumPy vs Dask: any operation on dask arrays should be consistent with the operation on numpy arrays (e.g., `f(xarray_obj.chunk()).compute() == f(xarray_obj)`).
-  [ ] Indexing followed by `xarray.concat`: should get back the same result.
-  [ ] Binary arithmetic on xarray objects with Python operators  (`+`, `-`, etc) and NumPy ufuncs (`np.add`, `np.subtract`, etc).","{""total_count"": 2, ""+1"": 2, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,290244473