BUG: ngroups and len(groups) do not equal when grouping with a list of Grouper and column label (GH26326) (#26374)

Author: shantanu-gontia

doc/source/whatsnew/v0.25.0.rst

@@ -447,9 +447,9 @@ Groupby/Resample/Rolling
 - Bug in :meth:`pandas.core.groupby.GroupBy.cumsum`, :meth:`pandas.core.groupby.GroupBy.cumprod`, :meth:`pandas.core.groupby.GroupBy.cummin` and :meth:`pandas.core.groupby.GroupBy.cummax` with categorical column having absent categories, would return incorrect result or segfault (:issue:`16771`)
 - Bug in :meth:`pandas.core.groupby.GroupBy.nth` where NA values in the grouping would return incorrect results (:issue:`26011`)
 - Bug in :meth:`pandas.core.groupby.SeriesGroupBy.transform` where transforming an empty group would raise error (:issue:`26208`)
+- Bug in :meth:`pandas.core.frame.DataFrame.groupby` where passing a :class:`pandas.core.groupby.grouper.Grouper` would return incorrect groups when using the ``.groups`` accessor (:issue:`26326`)
 - Bug in :meth:`pandas.core.groupby.GroupBy.agg` where incorrect results are returned for uint64 columns. (:issue:`26310`)
 
-
 Reshaping
 ^^^^^^^^^
 

pandas/core/groupby/grouper.py

@@ -280,7 +280,7 @@ def __init__(self, index, grouper=None, obj=None, name=None, level=None,
             if self.name is None:
                 self.name = grouper.result_index.name
             self.obj = self.grouper.obj
-            self.grouper = grouper
+            self.grouper = grouper._get_grouper()
 
         else:
             if self.grouper is None and self.name is not None:

pandas/core/groupby/ops.py

@@ -150,6 +150,15 @@ def _get_splitter(self, data, axis=0):
         comp_ids, _, ngroups = self.group_info
         return get_splitter(data, comp_ids, ngroups, axis=axis)
 
+    def _get_grouper(self):
+        """
+        We are a grouper as part of another's groupings.
+
+        We have a specific method of grouping, so cannot
+        convert to a Index for our grouper.
+        """
+        return self.groupings[0].grouper
+
     def _get_group_keys(self):
         if len(self.groupings) == 1:
             return self.levels[0]
@@ -707,6 +716,15 @@ def groups(self):
     def nkeys(self):
         return 1
 
+    def _get_grouper(self):
+        """
+        We are a grouper as part of another's groupings.
+
+        We have a specific method of grouping, so cannot
+        convert to a Index for our grouper.
+        """
+        return self
+
     def get_iterator(self, data, axis=0):
         """
         Groupby iterator

pandas/tests/groupby/test_groupby.py

@@ -1736,3 +1736,19 @@ def test_groupby_multiindex_series_keys_len_equal_group_axis():
     expected = pd.Series([3], index=ei)
 
     assert_series_equal(result, expected)
+
+
+def test_groupby_groups_in_BaseGrouper():
+    # GH 26326
+    # Test if DataFrame grouped with a pandas.Grouper has correct groups
+    mi = pd.MultiIndex.from_product([['A', 'B'],
+                                     ['C', 'D']], names=['alpha', 'beta'])
+    df = pd.DataFrame({'foo': [1, 2, 1, 2], 'bar': [1, 2, 3, 4]},
+                      index=mi)
+    result = df.groupby([pd.Grouper(level='alpha'), 'beta'])
+    expected = df.groupby(['alpha', 'beta'])
+    assert(result.groups == expected.groups)
+
+    result = df.groupby(['beta', pd.Grouper(level='alpha')])
+    expected = df.groupby(['beta', 'alpha'])
+    assert(result.groups == expected.groups)