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/pull/3159#issuecomment-525015879,https://api.github.com/repos/pydata/xarray/issues/3159,525015879,MDEyOklzc3VlQ29tbWVudDUyNTAxNTg3OQ==,23618263,2019-08-26T20:20:17Z,2019-08-26T20:20:17Z,CONTRIBUTOR,"> Great, looking good @DangoMelon - I merged master to resolve a conflict - then we can get this in!

Thanks for the help! I'm glad to contribute to this project.","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,472100381
https://github.com/pydata/xarray/pull/3159#issuecomment-519524084,https://api.github.com/repos/pydata/xarray/issues/3159,519524084,MDEyOklzc3VlQ29tbWVudDUxOTUyNDA4NA==,23618263,2019-08-08T13:44:22Z,2019-08-08T13:44:22Z,CONTRIBUTOR,"> 
> That's a good point. I think in this case, given that it's passed to an arg expected an array, we should raise on 0d.
>

I was expecting to rely on the current implementation of `is_scalar` to do the type checking since I'm moving `_check_data_shape` above `as_compatible_data` to do something like this

```python
if utils.is_scalar(data) and coords is not None:
```

Otherwise everything would be filter out since `as_compatible_data` returns a 0d given a scalar value.
https://github.com/pydata/xarray/blob/8d46bf09f20e022baca98b4050584d93c0ea118b/xarray/core/variable.py#L195-L196

I can only imagine copying `is_scalar` but removing `getattr(value, 'ndim', None) == 0` to filter out the 0d to only do the duplication on scalars.","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,472100381
https://github.com/pydata/xarray/pull/3159#issuecomment-518876089,https://api.github.com/repos/pydata/xarray/issues/3159,518876089,MDEyOklzc3VlQ29tbWVudDUxODg3NjA4OQ==,23618263,2019-08-06T23:07:34Z,2019-08-06T23:07:34Z,CONTRIBUTOR,"Thanks for the feedback.
>
>My inclination is to treat these like multi-dimensional arrays, in which case we should raise an error to avoid hiding errors.
>
I wasn't sure on how to treat 0-dimensional arrays and just assumed it to be the same as a scalar since this function considers them as so

https://github.com/pydata/xarray/blob/1ab7569561db50eaccbae977b0ef69993e0c0d0c/xarray/core/utils.py#L238-L248

Should I treat them like multi-dimensional arrays or leave the current behavior for consistency with the snippet above? 

>
> If the default value is `NaN`, we could reuse xarray's pre-existing sentinel value for NA:
>
Thanks for the advice, I'll be using this.","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,472100381
https://github.com/pydata/xarray/pull/3159#issuecomment-518747403,https://api.github.com/repos/pydata/xarray/issues/3159,518747403,MDEyOklzc3VlQ29tbWVudDUxODc0NzQwMw==,23618263,2019-08-06T16:36:42Z,2019-08-06T16:36:42Z,CONTRIBUTOR,"So far, this addition can do the following:

- Use a scalar value
```python
>>> xr.DataArray(5, coords=[('x', np.arange(3)), ('y', ['a', 'b'])])

<xarray.DataArray (x: 3, y: 2)>
array([[5, 5],
       [5, 5],
       [5, 5]])
Coordinates:
  * x        (x) int64 0 1 2
  * y        (y) <U1 'a' 'b'
```

- Use a scalar array
```python
>>> xr.DataArray(np.array(1.0), coords=[('x', np.arange(3)), ('y', ['a', 'b'])])

<xarray.DataArray (x: 3, y: 2)>
array([[1., 1.],
       [1., 1.],
       [1., 1.]])
Coordinates:
  * x        (x) int64 0 1 2
  * y        (y) <U1 'a' 'b'
```

- Match any number of dims
```python
>>> xr.DataArray(0, coords={'x': pd.date_range('20190101', '20190131'), 
                           'y': ['north', 'south'], 'z': np.arange(4)}, 
                    dims=['w', 'x', 'y', 'p', 'z'])

<xarray.DataArray (w: 1, x: 31, y: 2, p: 1, z: 4)>
array([[[[[0, ..., 0]],

         [[0, ..., 0]]],


        ...,


        [[[0, ..., 0]],

         [[0, ..., 0]]]]])
Coordinates:
  * x        (x) datetime64[ns] 2019-01-01 2019-01-02 ... 2019-01-30 2019-01-31
  * y        (y) <U5 'north' 'south'
  * z        (z) int64 0 1 2 3
Dimensions without coordinates: w, p
```

- Use `None` to get an empty array

```python
>>> xr.DataArray(None, coords={'x': np.datetime64('2019-01-01'),
                               'y': np.arange(100),
                               'z': 'ST1',
                               'p': np.arange(10)}, dims=['y', 'p'])

<xarray.DataArray (y: 100, p: 10)>
array([[ 4.047386e-320,  6.719293e-321,  0.000000e+000, ...,  6.935425e-310,
         6.935319e-310,  0.000000e+000],
       [ 4.940656e-324,  6.935107e-310,  6.935432e-310, ...,  6.935432e-310,
         1.086944e-322,  6.935430e-310],
       [ 6.935432e-310,  6.935319e-310,  2.758595e-313, ...,  6.935432e-310,
         6.935432e-310,  6.935432e-310],
       ...,
       [ 6.781676e+194,  3.328071e-113,  9.124901e+192, ...,  2.195875e-157,
        -4.599251e-303, -2.217863e-250],
       [ 7.830998e+247, -8.407382e+089,  1.299071e+193, ...,  9.124901e+192,
        -4.661908e-303,  2.897933e+193],
       [ 1.144295e-309,  7.041423e+053, -8.538757e-210, ...,  1.473665e+256,
        -6.525461e-210, -1.665001e-075]])
Coordinates:
    x        datetime64[ns] 2019-01-01
  * y        (y) int64 0 1 2 3 4 5 6 7 8 9 10 ... 90 91 92 93 94 95 96 97 98 99
    z        <U3 'ST1'
  * p        (p) int64 0 1 2 3 4 5 6 7 8 9
```

Any comment on what is missing or needs to be fixed is welcome.
","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,472100381
https://github.com/pydata/xarray/pull/3159#issuecomment-518398866,https://api.github.com/repos/pydata/xarray/issues/3159,518398866,MDEyOklzc3VlQ29tbWVudDUxODM5ODg2Ng==,23618263,2019-08-05T21:02:27Z,2019-08-05T21:02:27Z,CONTRIBUTOR,"Hi @max-sixty, I managed to fix it up a bit. It previously showed all the commits made by others collaborators since I forked the repo. I did a `git rebase`, solved all the merge conflicts and then force pushed it. It seems like some commits got duplicated though.","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,472100381
https://github.com/pydata/xarray/pull/3159#issuecomment-518306142,https://api.github.com/repos/pydata/xarray/issues/3159,518306142,MDEyOklzc3VlQ29tbWVudDUxODMwNjE0Mg==,23618263,2019-08-05T16:33:22Z,2019-08-05T16:33:22Z,CONTRIBUTOR,I am not sure what happened to the commit history. I might have messed up trying to update my local fork. Is there anything I can do to revert this?,"{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,472100381
https://github.com/pydata/xarray/pull/3159#issuecomment-514611709,https://api.github.com/repos/pydata/xarray/issues/3159,514611709,MDEyOklzc3VlQ29tbWVudDUxNDYxMTcwOQ==,23618263,2019-07-24T12:30:57Z,2019-07-24T12:30:57Z,CONTRIBUTOR,Just realised most things broke with the change I made. I'll refactor it and try again.,"{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,472100381