ENH: droplevel copy keyword

doc/source/whatsnew/v1.5.0.rst

@@ -297,6 +297,7 @@ Other enhancements
 - :meth:`DataFrame.quantile` gained a ``method`` argument that can accept ``table`` to evaluate multi-column quantiles (:issue:`43881`)
 - :class:`Interval` now supports checking whether one interval is contained by another interval (:issue:`46613`)
 - Added ``copy`` keyword to :meth:`Series.set_axis` and :meth:`DataFrame.set_axis` to allow user to set axis on a new object without necessarily copying the underlying data (:issue:`47932`)
+- :meth:`DataFrame.droplevel` and :meth:`Series.droplevel` support a ``copy`` argument. if ``False``, the underlying data is not copied (:issue:`48117`)
 - :meth:`Series.add_suffix`, :meth:`DataFrame.add_suffix`, :meth:`Series.add_prefix` and :meth:`DataFrame.add_prefix` support a ``copy`` argument. If ``False``, the underlying data is not copied in the returned object (:issue:`47934`)
 - :meth:`DataFrame.set_index` now supports a ``copy`` keyword. If ``False``, the underlying data is not copied when a new :class:`DataFrame` is returned (:issue:`48043`)
 

pandas/core/generic.py

@@ -843,7 +843,9 @@ def swapaxes(
 
     @final
     @doc(klass=_shared_doc_kwargs["klass"])
-    def droplevel(self: NDFrameT, level: IndexLabel, axis: Axis = 0) -> NDFrameT:
+    def droplevel(
+        self: NDFrameT, level: IndexLabel, axis: Axis = 0, copy: bool_t = True
+    ) -> NDFrameT:
         """
         Return {klass} with requested index / column level(s) removed.
 
@@ -862,6 +864,11 @@ def droplevel(self: NDFrameT, level: IndexLabel, axis: Axis = 0) -> NDFrameT:
 
             For `Series` this parameter is unused and defaults to 0.
 
+        copy : bool, default True
+            Whether to make a copy of the underlying data.
+
+            .. versionadded:: 1.5.0
+
         Returns
         -------
         {klass}
@@ -904,7 +911,7 @@ def droplevel(self: NDFrameT, level: IndexLabel, axis: Axis = 0) -> NDFrameT:
         """
         labels = self._get_axis(axis)
         new_labels = labels.droplevel(level)
-        return self.set_axis(new_labels, axis=axis, inplace=False)
+        return self.set_axis(new_labels, axis=axis, copy=copy)
 
     def pop(self, item: Hashable) -> Series | Any:
         result = self[item]

pandas/core/reshape/pivot.py

@@ -241,7 +241,7 @@ def __internal_pivot_table(
 
     # discard the top level
     if values_passed and not values_multi and table.columns.nlevels > 1:
-        table = table.droplevel(0, axis=1)
+        table = table.droplevel(0, axis=1, copy=False)
     if len(index) == 0 and len(columns) > 0:
         table = table.T
 

pandas/core/reshape/reshape.py

@@ -535,10 +535,7 @@ def _unstack_extension_series(series: Series, level, fill_value) -> DataFrame:
     df = series.to_frame()
     result = df.unstack(level=level, fill_value=fill_value)
 
-    # equiv: result.droplevel(level=0, axis=1)
-    #  but this avoids an extra copy
-    result.columns = result.columns.droplevel(0)
-    return result
+    return result.droplevel(level=0, axis=1, copy=False)
 
 
 def stack(frame: DataFrame, level=-1, dropna: bool = True):

pandas/tests/frame/methods/test_droplevel.py

@@ -34,3 +34,28 @@ def test_droplevel(self, frame_or_series):
             # test that droplevel raises ValueError on axis != 0
             with pytest.raises(ValueError, match="No axis named columns"):
                 df.droplevel(1, axis="columns")
+
+    def test_droplevel_copy(self, frame_or_series):
+        cols = MultiIndex.from_tuples(
+            [("c", "e"), ("d", "f")], names=["level_1", "level_2"]
+        )
+        mi = MultiIndex.from_tuples([(1, 2), (5, 6), (9, 10)], names=["a", "b"])
+        df = DataFrame([[3, 4], [7, 8], [11, 12]], index=mi, columns=cols)
+        if frame_or_series is not DataFrame:
+            df = df.iloc[:, 0]
+
+        # Check that we DID make a copy
+        res = df.droplevel("a", axis="index", copy=True)
+        if frame_or_series is DataFrame:
+            for i in range(df.shape[1]):
+                assert not tm.shares_memory(df.iloc[:, i], res.iloc[:, i])
+        else:
+            assert not tm.shares_memory(res, df)
+
+        # Check that we did NOT make a copy
+        res = df.droplevel("a", axis="index", copy=False)
+        if frame_or_series is DataFrame:
+            for i in range(df.shape[1]):
+                assert tm.shares_memory(df.iloc[:, i], res.iloc[:, i])
+        else:
+            assert tm.shares_memory(res, df)