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
666880880,MDU6SXNzdWU2NjY4ODA4ODA=,4278,Skipna not working in DataArray.rolling.mean ,12862013,closed,0,,,5,2020-07-28T08:32:41Z,2022-09-06T10:39:02Z,2020-07-29T11:17:23Z,CONTRIBUTOR,,,,"**What happened**:
I tried to calculate a rolling mean or median, ignoring nan's

**Minimal Complete Verifiable Example**:

```python
>>> da = xr.DataArray([1.0, 2, 3, np.nan, 5, 6])
>>> da.rolling(dim_0 = 3).mean(skipna=True)
<xarray.DataArray (dim_0: 6)>
array([nan, nan,  2., nan, nan, nan])
Dimensions without coordinates: dim_0
```

I expected this array to have have no nans. There is a simple workaround that does give the answer I was looking for:

```python
>>> da.rolling(dim_0 = 3).construct(""new"").mean(""new"", skipna=True)
<xarray.DataArray (dim_0: 6)>
array([1. , 1.5, 2. , 2.5, 4. , 5.5])
Dimensions without coordinates: dim_0
```

**Anything else we need to know?**:
Love the project ;-)

**Environment**:

<details><summary>Output of <tt>xr.show_versions()</tt></summary>

INSTALLED VERSIONS
------------------
commit: None
python: 3.8.3 (default, May 16 2020, 07:08:28)
[GCC 8.3.0]
python-bits: 64
OS: Linux
OS-release: 4.19.76-linuxkit
machine: x86_64
processor:
byteorder: little
LC_ALL: None
LANG: C.UTF-8
LOCALE: en_US.UTF-8
libhdf5: None
libnetcdf: None

xarray: 0.16.0
pandas: 1.0.5
numpy: 1.19.1
scipy: None
netCDF4: None
pydap: None
h5netcdf: None
h5py: None
Nio: None
zarr: None
cftime: None
nc_time_axis: None
PseudoNetCDF: None
rasterio: None
cfgrib: None
iris: None
bottleneck: None
dask: None
distributed: None
matplotlib: None
cartopy: None
seaborn: None
numbagg: None
pint: None
setuptools: 46.4.0
pip: 20.1.1
conda: None
pytest: None
IPython: 7.16.1
sphinx: None

</details>
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546791416,MDU6SXNzdWU1NDY3OTE0MTY=,3671,rolling.construct alignment,12862013,closed,0,,,4,2020-01-08T11:03:28Z,2020-01-11T02:24:21Z,2020-01-11T02:24:21Z,CONTRIBUTOR,,,,"Hello xarray team

I was trying to implement functionality similar to Scikit Image's  [view_as_windows](https://scikit-image.org/docs/dev/api/skimage.util.html#skimage.util.view_as_windows), but I was having a hard time with the boundary conditions. I understand this request is very similar to rolling with periodic boundary conditions #2007.

#### MCVE Code Sample
```python
>>> arr = xr.DataArray(np.arange(4), dims=(""x"",))
>>> arr.rolling(x=2).construct(""roll_x"", stride=2)
<xarray.DataArray (x: 2, roll_x: 2)>
array([[nan,  0.],
       [ 1.,  2.]])
Dimensions without coordinates: x, roll_x
```

#### Expected Output
It would be nice to be able to easily get an output of:
```python
<xarray.DataArray (x: 2, roll_x: 2)>
array([[0., 1.],
       [2., 3.]])
Dimensions without coordinates: x, roll_x
```

#### Possible workarounds
With the upcoming features of pad (#3596) and rolling: periodic (#2011) it is actually not that hard to work around with:

```python
arr.pad(x=(1,0)).rolling(x=2).construct(""roll_x"", stride=2).isel(x=slice(1,None))
# or
arr.roll(x=-1).rolling(x=2, boundary=""periodic"").construct(""roll_x"", stride=2)
```

#### Idea
Would it be possible to add a keyword argument to either `rolling()` or `construct()` that expects an alignment of ""left"", ""right"" or ""center"". I understand that this could break interface copied from Pandas, but I hope it could be useful to others as well.
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