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/3659#issuecomment-570068215,https://api.github.com/repos/pydata/xarray/issues/3659,570068215,MDEyOklzc3VlQ29tbWVudDU3MDA2ODIxNQ==,14136435,2020-01-01T17:09:23Z,2020-01-05T10:58:18Z,CONTRIBUTOR,"The solution that makes sense to me is:

Multiindex level name conflicts should only be checked for coordinates, not data variables.

But I've only spent a few hours digging through the codebase to try and understand this problem - I'm not quite sure what the implications would be.

Here is another place where it feels like it makes more sense to only check the MultiIndex level names of coords:

```python
>>> da = xr.DataArray([0, 1], dims=[""location""], coords={""lat"": (""location"", [10, 11]), ""lon"": (""location"", [20, 21])}).set_index(location=[""lat"", ""lon""])
>>> location = da[""location""]

# you cannot directly make a dataset with `location` as a data variable
>>> xr.Dataset({""data"": location})
Traceback (most recent call last):
  File ""<stdin>"", line 1, in <module>
  File ""/home/harry/code/xarray/xarray/core/dataset.py"", line 541, in __init__
    variables, coord_names, dims, indexes = merge_data_and_coords(
  File ""/home/harry/code/xarray/xarray/core/merge.py"", line 466, in merge_data_and_coords
    return merge_core(
  File ""/home/harry/code/xarray/xarray/core/merge.py"", line 556, in merge_core
    assert_unique_multiindex_level_names(variables)
  File ""/home/harry/code/xarray/xarray/core/variable.py"", line 2363, in assert_unique_multiindex_level_names
    raise ValueError(""conflicting MultiIndex level name(s):\n%s"" % conflict_str)
ValueError: conflicting MultiIndex level name(s):
'lat' (location), 'lat' (data)
'lon' (location), 'lon' (data)

# but if you go a round-about way, you can exploit that assign_coords only checks 
# the multiindex names of coordinates, not data variables
```python
>>> ds = xr.Dataset({""data"": xr.DataArray(data=location.variable._data, dims=[""location""])})
>>> ds = ds.assign_coords({""location"": location})
>>> ds
<xarray.Dataset>
Dimensions:   (location: 2)
Coordinates:
  * location  (location) MultiIndex
  - lat       (location) int64 10 11
  - lon       (location) int64 20 21
Data variables:
    data      (location) object (10, 20) (11, 21)
>>> ds[""data""].variable._data
PandasIndexAdapter(array=MultiIndex([(10, 20),
            (11, 21)],
           names=['lat', 'lon']), dtype=dtype('O'))
```

If making `variable.assert_unique_multiindex_level_names` only check coords is the way to go, I'm keen + happy to try putting together a pull request for this.","{""total_count"": 1, ""+1"": 1, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,544375718
https://github.com/pydata/xarray/pull/3658#issuecomment-570539403,https://api.github.com/repos/pydata/xarray/issues/3658,570539403,MDEyOklzc3VlQ29tbWVudDU3MDUzOTQwMw==,14136435,2020-01-03T10:53:05Z,2020-01-03T10:53:05Z,CONTRIBUTOR,"> 
> 
> Thanks, @hazbottles, for your contribution.
> 
> This looks nice.
> Please add your contribution to what's new in
> /doc/whats-new.rst

Done.","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,544371732
https://github.com/pydata/xarray/issues/364#issuecomment-341598412,https://api.github.com/repos/pydata/xarray/issues/364,341598412,MDEyOklzc3VlQ29tbWVudDM0MTU5ODQxMg==,14136435,2017-11-03T00:40:14Z,2017-11-03T00:40:39Z,CONTRIBUTOR,"Hi, being able to pass a `pd.TimeGrouper` to `.groupby()` would be really handy. Here is my use-case and work around at the moment (`.resample()` doesn't serve my needs because I need to iterate over the groups):

```python
import pandas as pd
import xarray as xr

dates = pd.DatetimeIndex(['2017-01-01 15:00', '2017-01-02 14:00', '2017-01-02 23:00'])
da = xr.DataArray([1, 2, 3], dims=['time'], coords={'time': dates})
time_grouper = pd.TimeGrouper(freq='24h', base=15)

# digging around the source code for xr.DataArray.resample i found this
grouped = xr.core.groupby.DataArrayGroupBy(da, 'time', grouper=time_grouper)

for _, sub_da in grouped:
    print(sub_da)
```

which prints: 
```
<xarray.DataArray (time: 2)>
array([1, 2])
Coordinates:
  * time     (time) datetime64[ns] 2017-01-01T15:00:00 2017-01-02T14:00:00
<xarray.DataArray (time: 1)>
array([3])
Coordinates:
  * time     (time) datetime64[ns] 2017-01-02T23:00:00
```

Would it be possible to add a `grouper` kwarg to `.groupby()`, e.g.
```python
da.groupby('time', grouper=time_grouper)
```
","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,60303760