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
159536177,MDU6SXNzdWUxNTk1MzYxNzc=,878,Allow passing a default value (instead of ndarray) for data argument for DataArray,1063143,closed,0,,,3,2016-06-10T00:18:12Z,2019-08-26T20:36:36Z,2019-08-26T20:36:36Z,NONE,,,,"Hi,

First of all, thanks a lot for the amazing module. It seems when I create a DataArray, I have to pass a numpy.ndarray with a correct size for the `data` argument. It works well when I already have some data, but sometimes I want to create an ""empty"" DataArray with known coordinates and fill up the data later. For these cases, it would be great if xarray allows passing just a value for the `data` argument, and fill up all the elements of the array with the value. For example, with pandas, I can do:

``` python
import pandas as pd
test = pd.DataFrame(data=.1, index=range(100), columns=['col1', 'col2'])
```

and the resulting `DataFrame` would be:

``` python
    col1  col2
0    0.1   0.1
1    0.1   0.1
2    0.1   0.1
..   ...   ...
97   0.1   0.1
98   0.1   0.1
99   0.1   0.1

[100 rows x 2 columns]
```

Thanks a lot!
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173494017,MDU6SXNzdWUxNzM0OTQwMTc=,987,Return a scalar instead of DataArray when the return value is a scalar,1063143,closed,0,,,11,2016-08-26T16:37:36Z,2016-08-28T20:19:19Z,2016-08-28T20:19:19Z,NONE,,,,"Hi,

I'm not sure how devs will feel about this, but I wanted to ask because I'm getting into this issue frequently.

Currently many methods such as `.min()`, `.max()`, `.mean()` returns a DataArray even for the cases where the return value is a scaler. For example,

``` python
import numpy as np
import xarray as xr
test = xr.DataArray(data=np.ones((10, 10)))

In [6]: test.min()
Out[6]: 
<xarray.DataArray ()>
array(1.0)
```

which makes a lot of other things break down and I have to use `test.min().values` or `float(test.min())`. 
I think it would be great that these methods return a scalar when the return value is a scaler. For example, 

``` python
In [7]: np.ones((10, 10)).mean()
Out[7]: 1.0
```

Thank you!
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