ENH: Use lazy copy for dropna (#50429)

pandas/core/frame.py

@@ -6346,7 +6346,7 @@ def dropna(
             raise ValueError(f"invalid how option: {how}")
 
         if np.all(mask):
-            result = self.copy()
+            result = self.copy(deep=None)
         else:
             result = self.loc(axis=axis)[mask]
 

pandas/core/internals/managers.py

@@ -1955,9 +1955,17 @@ def _blklocs(self):
         """compat with BlockManager"""
         return None
 
-    def getitem_mgr(self, indexer: slice | npt.NDArray[np.bool_]) -> SingleBlockManager:
+    def getitem_mgr(self, indexer: slice | np.ndarray) -> SingleBlockManager:
         # similar to get_slice, but not restricted to slice indexer
         blk = self._block
+        if (
+            using_copy_on_write()
+            and isinstance(indexer, np.ndarray)
+            and len(indexer) > 0
+            and com.is_bool_indexer(indexer)
+            and indexer.all()
+        ):
+            return type(self)(blk, self.index, [weakref.ref(blk)], parent=self)
         array = blk._slice(indexer)
         if array.ndim > 1:
             # This will be caught by Series._get_values

pandas/core/series.py

@@ -921,7 +921,7 @@ def _ixs(self, i: int, axis: AxisInt = 0) -> Any:
         """
         return self._values[i]
 
-    def _slice(self, slobj: slice, axis: Axis = 0) -> Series:
+    def _slice(self, slobj: slice | np.ndarray, axis: Axis = 0) -> Series:
         # axis kwarg is retained for compat with NDFrame method
         #  _slice is *always* positional
         return self._get_values(slobj)
@@ -5583,7 +5583,7 @@ def dropna(
                 return result
         else:
             if not inplace:
-                return self.copy()
+                return self.copy(deep=None)
         return None
 
     # ----------------------------------------------------------------------

pandas/tests/copy_view/test_methods.py

@@ -503,6 +503,40 @@ def test_add_suffix(using_copy_on_write):
     tm.assert_frame_equal(df, df_orig)
 
 
+@pytest.mark.parametrize("axis, val", [(0, 5.5), (1, np.nan)])
+def test_dropna(using_copy_on_write, axis, val):
+    df = DataFrame({"a": [1, 2, 3], "b": [4, val, 6], "c": "d"})
+    df_orig = df.copy()
+    df2 = df.dropna(axis=axis)
+
+    if using_copy_on_write:
+        assert np.shares_memory(get_array(df2, "a"), get_array(df, "a"))
+    else:
+        assert not np.shares_memory(get_array(df2, "a"), get_array(df, "a"))
+
+    df2.iloc[0, 0] = 0
+    if using_copy_on_write:
+        assert not np.shares_memory(get_array(df2, "a"), get_array(df, "a"))
+    tm.assert_frame_equal(df, df_orig)
+
+
+@pytest.mark.parametrize("val", [5, 5.5])
+def test_dropna_series(using_copy_on_write, val):
+    ser = Series([1, val, 4])
+    ser_orig = ser.copy()
+    ser2 = ser.dropna()
+
+    if using_copy_on_write:
+        assert np.shares_memory(ser2.values, ser.values)
+    else:
+        assert not np.shares_memory(ser2.values, ser.values)
+
+    ser2.iloc[0] = 0
+    if using_copy_on_write:
+        assert not np.shares_memory(ser2.values, ser.values)
+    tm.assert_series_equal(ser, ser_orig)
+
+
 @pytest.mark.parametrize(
     "method",
     [