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
361237908,MDU6SXNzdWUzNjEyMzc5MDg=,2419,Document ways to reshape a DataArray,9844249,open,0,,,5,2018-09-18T10:27:36Z,2022-04-09T02:21:15Z,,NONE,,,,"#### Code Sample, a copy-pastable example if possible

A ""Minimal, Complete and Verifiable Example"" will make it much easier for maintainers to help you:
http://matthewrocklin.com/blog/work/2018/02/28/minimal-bug-reports

```python
# Your code here

def xr_reshape(A, dim, newdims, coords):
    """""" Reshape DataArray A to convert its dimension dim into sub-dimensions given by
    newdims and the corresponding coords.
    Example: Ar = xr_reshape(A, 'time', ['year', 'month'], [(2017, 2018), np.arange(12)]) """"""


    # Create a pandas MultiIndex from these labels
    ind = pd.MultiIndex.from_product(coords, names=newdims)

    # Replace the time index in the DataArray by this new index,
    A1 = A.copy()

    A1.coords[dim] = ind

    # Convert multiindex to individual dims using DataArray.unstack().
    # This changes dimension order! The new dimensions are at the end.
    A1 = A1.unstack(dim)

    # Permute to restore dimensions
    i = A.dims.index(dim)
    dims = list(A1.dims)

    for d in newdims[::-1]:
        dims.insert(i, d)

    for d in newdims:
        _ = dims.pop(-1)


    return A1.transpose(*dims)


```
#### Problem description

[this should explain **why** the current behavior is a problem and why the expected output is a better solution.]

It would be great to have the above function as a DataArray's method. 

#### Expected Output

A reshaped DataArray. In the example in the function comment it would correspond to an array like

In[1] Ar.dims
Out[1]: ('year', 'month', 'lat', 'lon')

#### Output of ``xr.show_versions()``

<details>
# Paste the output here xr.show_versions() here

INSTALLED VERSIONS
------------------
commit: None
python: 3.6.3.final.0
python-bits: 64
OS: Linux
OS-release: 3.10.0-693.5.2.el7.x86_64
machine: x86_64
processor: x86_64
byteorder: little
LC_ALL: None
LANG: fr_FR.UTF-8
LOCALE: fr_FR.UTF-8
xarray: 0.10.4
pandas: 0.23.0
numpy: 1.13.3
scipy: 0.19.1
netCDF4: 1.3.1
h5netcdf: None
h5py: 2.7.0
Nio: None
zarr: None
bottleneck: 1.2.1
cyordereddict: None
dask: 0.15.3
distributed: 1.19.1
matplotlib: 2.1.0
cartopy: 0.16.0
seaborn: 0.8.1
setuptools: 36.5.0.post20170921
pip: 18.0
conda: 4.4.7
pytest: 3.2.1
IPython: 6.1.0
sphinx: 1.6.3

</details>
","{""url"": ""https://api.github.com/repos/pydata/xarray/issues/2419/reactions"", ""total_count"": 2, ""+1"": 2, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,,13221727,issue
221845134,MDU6SXNzdWUyMjE4NDUxMzQ=,1373,Dataset.combine_first() coordinates attribute,9844249,closed,0,,,2,2017-04-14T16:46:02Z,2019-04-14T23:22:23Z,2019-04-14T23:22:23Z,NONE,,,,"Hi guys!

Thanks for the great job you are doing!

Here is a possible bug in the `Dataset.combine_first()` method (I'm using xarray 0.9.2 with Python 3.5.2). 

The Dataset/DataArray coordinates are correctly treated if specified without commas, e.g. (as seen with ncdump):  ``MyVar:coordinates = ""alt lat lon"" ; ``.  In this case _lon, lat_, and _alt_ are recognized as the Dataset's (and its DataArrays') `.coords`.

However, the `Dataset.combine_first() `method only treats coordinates correctly if specified with commas, i.e., `MyVar:coordinates = ""alt, lat, lon""`.  

","{""url"": ""https://api.github.com/repos/pydata/xarray/issues/1373/reactions"", ""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,completed,13221727,issue