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/3381#issuecomment-541160571,https://api.github.com/repos/pydata/xarray/issues/3381,541160571,MDEyOklzc3VlQ29tbWVudDU0MTE2MDU3MQ==,1634164,2019-10-11T17:49:09Z,2019-10-11T17:49:09Z,NONE,"Thanks both for the comments. I understand sparse's behaviour; to clarify, the bug (IMO) is that xarray doesn't handle this for the user. To condense my example:
```python
# Same as above to ---
import numpy as np
import pandas as pd
import xarray as xr

foo = [f'foo{i}' for i in range(6)]
bar = [f'bar{i}' for i in range(6)]
raw = np.random.rand(len(foo) // 2, len(bar))

b_series = pd.DataFrame(raw, index=foo[3:], columns=bar) \
             .stack() \
             .rename_axis(index=['foo', 'bar'])
# ---

b = xr.DataArray.from_series(b_series, sparse=True)
c = b.sum(dim='foo').expand_dims({'foo': ['total']})
d = xr.concat([b, c], dim='foo')
```

This succeeds when `sparse=False` and fails when `sparse=True`.
- Shouldn't it succeed automatically? I feel like it should.
- If it does, what should be the fill value on `d`?  I'm not clear what the intended behaviour is.

I haven't touched xarray internals before, but if time allows I will try to add some tests.","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,503711327