use safe_cast_to_index to sanitize DataArrays for groupby (pydata#1133)

* groupby should pass ndarray to unique_value_groups pydata#1132

* use safe_cast_to_index to sanitize DataArrays for groupby pydata#1133

* add test for pydata#1133

* correct issue number

* minor cleanup

* add note to whats new

* fix formatting

* repair Marco's umlaut

* More descriptive what's new note

doc/whats-new.rst

@@ -199,7 +199,10 @@ Bug fixes
 - Fixed sub-optimal performance in certain operations with object arrays (:issue:`1121`).
   By `Yves Delley <https://github.com/burnpanck>`_.
 
-- Fixed a bug whith facetgrid (the ``norm`` keyword was ignored, :issue:`1159`).
+- Fix ``.groupby(group)`` when ``group`` has datetime dtype (:issue:`1132`).
+  By `Jonas Sølvsteen <https://github.com/j08lue>`_.
+
+- Fixed a bug with facetgrid (the ``norm`` keyword was ignored, :issue:`1159`).
   By `Fabien Maussion <https://github.com/fmaussion>`_.
 
 .. _whats-new.0.8.2:

xarray/core/groupby.py

@@ -260,7 +260,7 @@ def __init__(self, obj, group, squeeze=False, grouper=None, bins=None,
         else:
             # look through group to find the unique values
             unique_values, group_indices = unique_value_groups(
-                group, sort=(bins is None))
+                safe_cast_to_index(group), sort=(bins is None))
             unique_coord = IndexVariable(group.name, unique_values)
 
         # specification for the groupby operation

xarray/test/test_groupby.py

@@ -2,6 +2,7 @@
 from __future__ import division
 from __future__ import print_function
 import numpy as np
+import pandas as pd
 import xarray as xr
 from xarray.core.groupby import _consolidate_slices
 
@@ -46,11 +47,28 @@ def test_multi_index_groupby_sum():
     assert expected.equals(actual)
 
 
+def test_groupby_da_datetime():
+    # test groupby with a DataArray of dtype datetime for GH1132
+    # create test data
+    times = pd.date_range('2000-01-01', periods=4)
+    foo = xr.DataArray([1,2,3,4], coords=dict(time=times), dims='time')
+    # create test index
+    dd = times.to_datetime()
+    reference_dates = [dd[0], dd[2]]
+    labels = reference_dates[0:1]*2 + reference_dates[1:2]*2
+    ind = xr.DataArray(labels, coords=dict(time=times), dims='time', name='reference_date')
+    g = foo.groupby(ind)
+    actual = g.sum(dim='time')
+    expected = xr.DataArray([3,7], coords=dict(reference_date=reference_dates), dims='reference_date')
+    assert actual.equals(expected)
+
+
 def test_groupby_duplicate_coordinate_labels():
     # fix for http://stackoverflow.com/questions/38065129
     array = xr.DataArray([1, 2, 3], [('x', [1, 1, 2])])
     expected = xr.DataArray([3, 3], [('x', [1, 2])])
     actual = array.groupby('x').sum()
     assert expected.equals(actual)
 
+
 # TODO: move other groupby tests from test_dataset and test_dataarray over here