issue_comments

The example above is now fixed:

```python

In [1]: ds=xr.Dataset(dict(a=(('z',), np.ones(10))), coords=dict(b=(('z'),np.arange(2).repeat(5)), c=(('z'),np.arange(5).repeat(2)))) ...:

In [2]: ds.set_index(bc=['b','c']).groupby('bc').sum() Out[2]: <xarray.Dataset> Dimensions: (bc: 6, z: 10) Coordinates: * bc (bc) object MultiIndex * b (bc) int64 0 0 0 1 1 1 * c (bc) int64 0 1 2 2 3 4 Dimensions without coordinates: z Data variables: a (bc, z) float64 1.0 1.0 1.0 1.0 1.0 1.0 ... 1.0 1.0 1.0 1.0 1.0 1.0 # <- correct ```

I got a solution which is not so flexible but works: Data: python import pandas as pd arrays = [np.array(['bar', 'bar', 'baz', 'baz', 'foo', 'foo']), np.array(['one', 'two', 'one', 'two', 'one', 'two'])] da = pd.DataFrame(np.random.randn(6, 4)).to_xarray().to_array() da.coords['index'] = pd.MultiIndex.from_arrays(arrays, names=['first', 'second']) da <xarray.DataArray (variable: 4, index: 6)> array([[ 0.379189, 1.082292, -2.073478, -0.84626 , -1.529927, -0.837407], [-0.267983, -0.2516 , -1.016653, -0.085762, -0.058382, -0.667891], [-0.013488, -0.855332, -0.038072, -0.385211, -2.149742, -0.304361], [ 1.749561, -0.606031, 1.914146, 1.6292 , -0.515519, 1.996283]]) Coordinates: * index (index) MultiIndex - first (index) object 'bar' 'bar' 'baz' 'baz' 'foo' 'foo' - second (index) object 'one' 'two' 'one' 'two' 'one' 'two' * variable (variable) int32 0 1 2 3 Groupby on levels: ```python def multi_groupby(data, levels): return (((k0,k1),v1) for k0,v0 in data.groupby(levels[0]) for k1,v1 in v0.groupby(levels[1]))

for k,v in multi_groupby(da,['second','variable']): print(k,v) ('one', 0) <xarray.DataArray (index: 3)> array([ 0.379189, -2.073478, -1.529927]) Coordinates: * index (index) MultiIndex - first (index) object 'bar' 'baz' 'foo' - second (index) object 'one' 'one' 'one' variable int32 0 ('one', 1) <xarray.DataArray (index: 3)> array([-0.267983, -1.016653, -0.058382]) Coordinates: * index (index) MultiIndex - first (index) object 'bar' 'baz' 'foo' - second (index) object 'one' 'one' 'one' variable int32 1 ('one', 2) <xarray.DataArray (index: 3)> array([-0.013488, -0.038072, -2.149742]) Coordinates: * index (index) MultiIndex - first (index) object 'bar' 'baz' 'foo' - second (index) object 'one' 'one' 'one' variable int32 2 ('one', 3) <xarray.DataArray (index: 3)> array([ 1.749561, 1.914146, -0.515519]) Coordinates: * index (index) MultiIndex - first (index) object 'bar' 'baz' 'foo' - second (index) object 'one' 'one' 'one' variable int32 3 ('two', 0) <xarray.DataArray (index: 3)> array([ 1.082292, -0.84626 , -0.837407]) Coordinates: * index (index) MultiIndex - first (index) object 'bar' 'baz' 'foo' - second (index) object 'two' 'two' 'two' variable int32 0 ('two', 1) <xarray.DataArray (index: 3)> array([-0.2516 , -0.085762, -0.667891]) Coordinates: * index (index) MultiIndex - first (index) object 'bar' 'baz' 'foo' - second (index) object 'two' 'two' 'two' variable int32 1 ('two', 2) <xarray.DataArray (index: 3)> array([-0.855332, -0.385211, -0.304361]) Coordinates: * index (index) MultiIndex - first (index) object 'bar' 'baz' 'foo' - second (index) object 'two' 'two' 'two' variable int32 2 ('two', 3) <xarray.DataArray (index: 3)> array([-0.606031, 1.6292 , 1.996283]) Coordinates: * index (index) MultiIndex - first (index) object 'bar' 'baz' 'foo' - second (index) object 'two' 'two' 'two' variable int32 3 ```

Are we making silent mistakes at the moment?

```python

In [1]: import xarray as xr In [2]: import pandas as pd

In [4]: import numpy as np

In [5]: ds=xr.Dataset(dict(a=(('z',), np.ones(10))), coords=dict(b=(('z'),np.arange(2).repeat(5)), c=(('z'),np.arange(5).repeat(2))))

In [6]: ds Out[6]: <xarray.Dataset> Dimensions: (z: 10) Coordinates: b (z) int64 0 0 0 0 0 1 1 1 1 1 c (z) int64 0 0 1 1 2 2 3 3 4 4 Dimensions without coordinates: z Data variables: a (z) float64 1.0 1.0 1.0 1.0 1.0 1.0 1.0 1.0 1.0 1.0

In [7]: ds.set_index(bc=['b','c']).groupby('bc').sum() Out[7]: <xarray.Dataset> Dimensions: (bc: 6) Coordinates: * bc (bc) MultiIndex - bc_level_0 (bc) int64 0 0 0 1 1 1 - bc_level_1 (bc) int64 0 1 2 2 3 4 Data variables: a (bc) float64 10.0 10.0 10.0 10.0 10.0 10.0 # <--- this is wrong? ```

With a DataArray, we do raise:

```python In [19]: ds['a'].set_index(bc=['b','c']) Out[19]: <xarray.DataArray 'a' (z: 10)> array([1., 1., 1., 1., 1., 1., 1., 1., 1., 1.]) Coordinates: * bc (bc) MultiIndex - b (bc) int64 0 0 0 0 0 1 1 1 1 1 - c (bc) int64 0 0 1 1 2 2 3 3 4 4 Dimensions without coordinates: z

In [20]: ds['a'].set_index(bc=['b','c']).groupby('bc')

KeyError Traceback (most recent call last) <ipython-input-20-82bf6782525c> in <module>() ----> 1 ds['a'].set_index(bc=['b','c']).groupby('bc')

/usr/local/lib/python3.6/site-packages/xarray/core/common.py in groupby(self, group, squeeze) 472 core.groupby.DatasetGroupBy 473 """ --> 474 return self._groupby_cls(self, group, squeeze=squeeze) 475 476 def groupby_bins(self, group, bins, right=True, labels=None, precision=3,

/usr/local/lib/python3.6/site-packages/xarray/core/groupby.py in init(self, obj, group, squeeze, grouper, bins, cut_kwargs) 213 group_dim, = group.dims 214 --> 215 expected_size = obj.sizes[group_dim] 216 if group.size != expected_size: 217 raise ValueError('the group variable\'s length does not '

/usr/local/lib/python3.6/site-packages/xarray/core/utils.py in getitem(self, key) 306 307 def getitem(self, key): --> 308 return self.mapping[key] 309 310 def iter(self):

KeyError: 'bc' ```

The "Edit on GitHub" link at the top right of doc page is probably the most convenient way for primary doc pages. It should walk you through making a pull request if you hit the "Edit this file" icon (next to the trash bin) at the top right of the file on GitHub.

To clarify on level: it's not supported, but instead you can simply pass the name of a MultiIndex level directly as a name. Multiple arguments are truly not supported yet (https://github.com/pydata/xarray/issues/324).

Makes sense. Just needs a doc update, then.

What's the preferred means to contribute doc (including little edits like this)? Pull requests?

We should clarify: we support a subset of the pandas API. The level argument and grouping by multiple variables at once is not yet supported.