BUG: Fix groupby nth with axis=1

pandas/core/groupby/groupby.py

@@ -2545,18 +2545,25 @@ def nth(
                 # Drop NA values in grouping
                 mask = mask & (ids != -1)
 
-                out = self._selected_obj[mask]
+                if self.axis == 0:
+                    out = self._selected_obj[mask]
+                else:
+                    out = self._selected_obj.iloc[:, mask]
+
                 if not self.as_index:
                     return out
 
                 result_index = self.grouper.result_index
-                out.index = result_index[ids[mask]]
+                if self.axis == 0:
+                    out.index = result_index[ids[mask]]
+                    if not self.observed and isinstance(result_index, CategoricalIndex):
+                        out = out.reindex(result_index)
 
-                if not self.observed and isinstance(result_index, CategoricalIndex):
-                    out = out.reindex(result_index)
+                    out = self._reindex_output(out)
+                else:
+                    out.columns = result_index[ids[mask]]
 
-                out = self._reindex_output(out)
-                return out.sort_index() if self.sort else out
+                return out.sort_index(axis=self.axis) if self.sort else out
 
         # dropna is truthy
         if isinstance(n, valid_containers):
@@ -2599,7 +2606,9 @@ def nth(
                 mutated=self.mutated,
             )
 
-        grb = dropped.groupby(grouper, as_index=self.as_index, sort=self.sort)
+        grb = dropped.groupby(
+            grouper, as_index=self.as_index, sort=self.sort, axis=self.axis
+        )
         sizes, result = grb.size(), grb.nth(n)
         mask = (sizes < max_len)._values
 

pandas/tests/groupby/test_nth.py

@@ -706,3 +706,26 @@ def test_groupby_last_first_nth_with_none(method, nulls_fixture):
         result = getattr(data, method)()
 
     tm.assert_series_equal(result, expected)
+
+
+def test_groupby_nth_with_column_axis():
+    # GH43926
+    df = DataFrame(
+        [
+            [4, 5, 6],
+            [8, 8, 7],
+        ],
+        index=["z", "y"],
+        columns=["C", "B", "A"],
+    )
+    result = df.groupby(df.iloc[1], axis=1).nth(0)
+    expected = DataFrame(
+        [
+            [6, 4],
+            [7, 8],
+        ],
+        index=["z", "y"],
+        columns=[7, 8],
+    )
+    expected.columns.name = "y"
+    tm.assert_frame_equal(result, expected)