BUG: Bug in xs ignored droplevel

doc/source/whatsnew/v1.2.0.rst

@@ -475,6 +475,7 @@ Indexing
 - Bug in :meth:`Series.loc` and :meth:`DataFrame.loc` raises when numeric label was given for object :class:`Index` although label was in :class:`Index` (:issue:`26491`)
 - Bug in :meth:`DataFrame.loc` returned requested key plus missing values when ``loc`` was applied to single level from :class:`MultiIndex` (:issue:`27104`)
 - Bug in indexing on a :class:`Series` or :class:`DataFrame` with a :class:`CategoricalIndex` using a listlike indexer containing NA values (:issue:`37722`)
+- Bug in :meth:`DataFrame.xs` ignored ``droplevel=False`` for columns (:issue:`19056`)
 
 Missing
 ^^^^^^^

pandas/core/generic.py

@@ -3708,18 +3708,21 @@ class   animal   locomotion
             return result
 
         if axis == 1:
-            return self[key]
+            if drop_level:
+                return self[key]
+            index = self.columns
+        else:
+            index = self.index
 
-        index = self.index
         if isinstance(index, MultiIndex):
             try:
-                loc, new_index = self.index._get_loc_level(
+                loc, new_index = index._get_loc_level(
                     key, level=0, drop_level=drop_level
                 )
             except TypeError as e:
                 raise TypeError(f"Expected label or tuple of labels, got {key}") from e
         else:
-            loc = self.index.get_loc(key)
+            loc = index.get_loc(key)
 
             if isinstance(loc, np.ndarray):
                 if loc.dtype == np.bool_:
@@ -3729,9 +3732,9 @@ class   animal   locomotion
                     return self._take_with_is_copy(loc, axis=axis)
 
             if not is_scalar(loc):
-                new_index = self.index[loc]
+                new_index = index[loc]
 
-        if is_scalar(loc):
+        if is_scalar(loc) and axis == 0:
             # In this case loc should be an integer
             if self.ndim == 1:
                 # if we encounter an array-like and we only have 1 dim
@@ -3747,7 +3750,10 @@ class   animal   locomotion
                 name=self.index[loc],
                 dtype=new_values.dtype,
             )
-
+        elif is_scalar(loc):
+            result = self.iloc[:, [loc]]
+        elif axis == 1:
+            result = self.iloc[:, loc]
         else:
             result = self.iloc[loc]
             result.index = new_index

pandas/tests/frame/indexing/test_xs.py

@@ -297,3 +297,25 @@ def test_xs_levels_raises(self, klass):
         msg = "Index must be a MultiIndex"
         with pytest.raises(TypeError, match=msg):
             obj.xs(0, level="as")
+
+    def test_xs_multiindex_droplevel_false(self):
+        # GH#19056
+        mi = MultiIndex.from_tuples(
+            [("a", "x"), ("a", "y"), ("b", "x")], names=["level1", "level2"]
+        )
+        df = DataFrame([[1, 2, 3]], columns=mi)
+        result = df.xs("a", axis=1, drop_level=False)
+        expected = DataFrame(
+            [[1, 2]],
+            columns=MultiIndex.from_tuples(
+                [("a", "x"), ("a", "y")], names=["level1", "level2"]
+            ),
+        )
+        tm.assert_frame_equal(result, expected)
+
+    def test_xs_droplevel_false(self):
+        # GH#19056
+        df = DataFrame([[1, 2, 3]], columns=Index(["a", "b", "c"]))
+        result = df.xs("a", axis=1, drop_level=False)
+        expected = DataFrame({"a": [1]})
+        tm.assert_frame_equal(result, expected)

pandas/tests/series/indexing/test_xs.py

@@ -50,3 +50,18 @@ def test_series_getitem_multiindex_xs(xs):
 
         result = ser.xs("20130903", level=1)
         tm.assert_series_equal(result, expected)
+
+    def test_series_xs_droplevel_false(self):
+        # GH: 19056
+        mi = MultiIndex.from_tuples(
+            [("a", "x"), ("a", "y"), ("b", "x")], names=["level1", "level2"]
+        )
+        df = Series([1, 1, 1], index=mi)
+        result = df.xs("a", axis=0, drop_level=False)
+        expected = Series(
+            [1, 1],
+            index=MultiIndex.from_tuples(
+                [("a", "x"), ("a", "y")], names=["level1", "level2"]
+            ),
+        )
+        tm.assert_series_equal(result, expected)