Added nunique section to whatsnew, removed series logic from DataFrameGroupby.nunique

Author: rhshadrach

doc/source/whatsnew/v1.1.0.rst

@@ -559,6 +559,35 @@ Assignment to multiple columns of a :class:`DataFrame` when some of the columns
    df[['a', 'c']] = 1
    df
 
+.. _whatsnew_110.api_breaking.groupby_nunique:
+
+Using groupby with ``nunique`` and ``as_index=True``
+^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
+
+Using :meth:`DataFrame.groupby` with ``as_index=True`` and the aggregation ``nunique`` would include the grouping column(s) in the columns of the result. Now, the grouping columns only appear in the index. This is now consistent with other aggregation functions. (:issue:`32579`)
+
+.. ipython:: python
+
+   df = pd.DataFrame({"a": ["x", "x", "y", "y"], "b": [1, 1, 2, 3]})
+   df
+
+*Previous behavior*:
+
+.. code-block:: ipython
+
+   In [3]: df.groupby("a", as_index=True).nunique()
+   Out[4]:
+      a  b
+   a
+   x  1  1
+   y  1  2
+
+*New behavior*:
+
+.. ipython:: python
+
+   df.groupby("a", as_index=True).nunique()
+
 .. _whatsnew_110.api_breaking.groupby_as_index_false:
 
 Using groupby with ``as_index=False``

pandas/core/groupby/generic.py

@@ -1877,39 +1877,36 @@ def nunique(self, dropna: bool = True):
         4   ham       5      x
         5   ham       5      y
         """
-        obj = self._obj_with_exclusions
+        from pandas.core.reshape.concat import concat
 
-        def groupby_series(obj, col=None):
-            return SeriesGroupBy(obj, selection=col, grouper=self.grouper).nunique(
-                dropna=dropna
-            )
+        # TODO: this is duplicative of how GroupBy naturally works
+        # Try to consolidate with normal wrapping functions
 
-        if isinstance(obj, Series):
-            results = groupby_series(obj)
+        obj = self._obj_with_exclusions
+        axis_number = obj._get_axis_number(self.axis)
+        other_axis = int(not axis_number)
+        if axis_number == 0:
+            iter_func = obj.items
         else:
-            # TODO: this is duplicative of how GroupBy naturally works
-            # Try to consolidate with normal wrapping functions
-            from pandas.core.reshape.concat import concat
+            iter_func = obj.iterrows
 
-            axis_number = obj._get_axis_number(self.axis)
-            other_axis = int(not axis_number)
-            if axis_number == 0:
-                iter_func = obj.items
-            else:
-                iter_func = obj.iterrows
-
-            results = [groupby_series(content, label) for label, content in iter_func()]
-            results = concat(results, axis=1)
+        results = concat(
+            [
+                SeriesGroupBy(content, selection=label, grouper=self.grouper).nunique(
+                    dropna
+                )
+                for label, content in iter_func()
+            ],
+            axis=1,
+        )
 
-            if axis_number == 1:
-                results = results.T
+        if axis_number == 1:
+            results = results.T
 
-            results._get_axis(other_axis).names = obj._get_axis(other_axis).names
+        results._get_axis(other_axis).names = obj._get_axis(other_axis).names
 
         if not self.as_index:
             results.index = ibase.default_index(len(results))
-            if results.ndim == 1:
-                results = results.to_frame()
             self._insert_inaxis_grouper_inplace(results)
         return results