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/2795#issuecomment-709991825,https://api.github.com/repos/pydata/xarray/issues/2795,709991825,MDEyOklzc3VlQ29tbWVudDcwOTk5MTgyNQ==,38673295,2020-10-16T11:34:05Z,2020-10-16T11:34:05Z,NONE,"Hi, I also vote for this function, My typical use-case. 

There is some structure in 3D space and I need to ""flatten it"" to 2D. Let us say it is axially symetric so I assign R and Z coordinate to points (or r and theta in polar).  And I want to simplify this using `interp`; however, it requuires unique coordinates. 

I have some solution here: https://stackoverflow.com/questions/51058379/drop-duplicate-times-in-xarray

and adapted this into actuall function: 

```python
def distribure_uniform(ds, N_points=512):

    ds_theta = ds.sortby(""theta"").swap_dims({""idx"": ""theta""})
    _, index = np.unique(ds_theta['theta'], return_index=True)

    ds_theta = ds_theta.isel(theta=index)

    ds_theta = ds_theta.interp(
        theta=np.linspace(ds.theta.min(), ds.theta.max(), N_points))

    ds_theta = ds_theta.swap_dims({""theta"": ""idx""})
    return ds_theta
```

In an idal case I would like to write something like this: 

```python
def distribure_uniform(ds, N_points=512):

    ds_theta= ds.unique(""theta"", sorted=False, sort=True)

    ds_theta = ds_theta.swap_dims({""idx"": ""theta""})
    ds_theta = ds_theta.interp(
        theta=np.linspace(ds.theta.min(), ds.theta.max(), N_points))
    ds_theta = ds_theta.swap_dims({""theta"": ""idx""})
    return ds_theta
```

","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,415774106
https://github.com/pydata/xarray/issues/2795#issuecomment-469477745,https://api.github.com/repos/pydata/xarray/issues/2795,469477745,MDEyOklzc3VlQ29tbWVudDQ2OTQ3Nzc0NQ==,15331990,2019-03-05T00:01:58Z,2019-03-05T00:01:58Z,CONTRIBUTOR,"Right, it would return a 1D numpy or dask array.

I suppose I'm used to simply typing pd.Series().unique() rather than np.unique(pd.Series()).

I use it in for loops primarily.
`for season in da['time.season'].unique():`
vs
`for season in np.unique(da['time.season'].data):`

","{""total_count"": 1, ""+1"": 1, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,415774106
https://github.com/pydata/xarray/issues/2795#issuecomment-469153520,https://api.github.com/repos/pydata/xarray/issues/2795,469153520,MDEyOklzc3VlQ29tbWVudDQ2OTE1MzUyMA==,1217238,2019-03-04T07:58:23Z,2019-03-04T07:58:23Z,MEMBER,"What would `.unique()` return on xarray.DataArray? For consistency with pandas, I guess it would return a 1D numpy or dask array?

I don't see a lot of value in adding this to xarray, given that all the xarray metadata gets lost by the `unique()` operation. You might as well just write `np.unique(my_data_array.data)`.","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,415774106