issue_comments: 207531654

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https://github.com/pydata/xarray/pull/818#issuecomment-207531654 https://api.github.com/repos/pydata/xarray/issues/818 207531654 MDEyOklzc3VlQ29tbWVudDIwNzUzMTY1NA== 1197350 2016-04-08T17:39:10Z 2016-04-08T18:07:11Z MEMBER

I have tried adding a new keyword bins arg to groupby, which should accomplish what I want and more. (It will also work on regular one-dimensional groupby operations.)

The way it works is like this:

``` python

ar = xr.DataArray(np.arange(4), dims='dim_0') ar <xarray.DataArray (dim_0: 4)> array([0, 1, 2, 3]) Coordinates: * dim_0 (dim_0) int64 0 1 2 3 ar.groupby('dim_0', bins=[2,4]).sum() <xarray.DataArray (dim_0: 2)> array([1, 5]) Coordinates: * dim_0 (dim_0) int64 2 4 ```

The only problem is that it seems to overwrite the original dimension of the array! After calling groupby

``` python

ar <xarray.DataArray (dim_0: 4)> array([0, 1, 2, 3]) Coordinates: * dim_0 (dim_0) int64 2 4 ```

I think that resample overcomes this issue by renaming the dimension: https://github.com/pydata/xarray/blob/master/xarray/core/common.py#L437

I guess something similar should be possible here...

 
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