TYP: require _update_inplace gets Frame/Series, never BlockManager

pandas/core/base.py

@@ -13,7 +13,6 @@
 from pandas.compat.numpy import function as nv
 from pandas.errors import AbstractMethodError
 from pandas.util._decorators import cache_readonly, doc
-from pandas.util._validators import validate_bool_kwarg
 
 from pandas.core.dtypes.cast import is_nested_object
 from pandas.core.dtypes.common import (
@@ -1505,18 +1504,14 @@ def factorize(self, sort=False, na_sentinel=-1):
     def searchsorted(self, value, side="left", sorter=None) -> np.ndarray:
         return algorithms.searchsorted(self._values, value, side=side, sorter=sorter)
 
-    def drop_duplicates(self, keep="first", inplace=False):
-        inplace = validate_bool_kwarg(inplace, "inplace")
+    def drop_duplicates(self, keep="first"):
         if isinstance(self, ABCIndexClass):
             if self.is_unique:
                 return self._shallow_copy()
 
         duplicated = self.duplicated(keep=keep)
         result = self[np.logical_not(duplicated)]
-        if inplace:
-            return self._update_inplace(result)
-        else:
-            return result
+        return result
 
     def duplicated(self, keep="first"):
         if isinstance(self, ABCIndexClass):
@@ -1527,9 +1522,3 @@ def duplicated(self, keep="first"):
             return self._constructor(
                 duplicated(self, keep=keep), index=self.index
             ).__finalize__(self)
-
-    # ----------------------------------------------------------------------
-    # abstracts
-
-    def _update_inplace(self, result, verify_is_copy=True, **kwargs):
-        raise AbstractMethodError(self)

pandas/core/frame.py

@@ -3042,16 +3042,16 @@ def query(self, expr, inplace=False, **kwargs):
         res = self.eval(expr, **kwargs)
 
         try:
-            new_data = self.loc[res]
+            result = self.loc[res]
         except ValueError:
             # when res is multi-dimensional loc raises, but this is sometimes a
             # valid query
-            new_data = self[res]
+            result = self[res]
 
         if inplace:
-            self._update_inplace(new_data)
+            self._update_inplace(result)
         else:
-            return new_data
+            return result
 
     def eval(self, expr, inplace=False, **kwargs):
         """
@@ -4683,7 +4683,7 @@ def drop_duplicates(
             result.index = ibase.default_index(len(result))
 
         if inplace:
-            self._update_inplace(result._data)
+            self._update_inplace(result)
             return None
         else:
             return result
@@ -4802,10 +4802,11 @@ def sort_values(
         if ignore_index:
             new_data.axes[1] = ibase.default_index(len(indexer))
 
+        result = self._constructor(new_data)
         if inplace:
-            return self._update_inplace(new_data)
+            return self._update_inplace(result)
         else:
-            return self._constructor(new_data).__finalize__(self)
+            return result.__finalize__(self)
 
     def sort_index(
         self,
@@ -4937,10 +4938,11 @@ def sort_index(
         if ignore_index:
             new_data.axes[1] = ibase.default_index(len(indexer))
 
+        result = self._constructor(new_data)
         if inplace:
-            return self._update_inplace(new_data)
+            return self._update_inplace(result)
         else:
-            return self._constructor(new_data).__finalize__(self)
+            return result.__finalize__(self)
 
     def value_counts(
         self,

pandas/core/generic.py

@@ -147,7 +147,7 @@ def _single_replace(self, to_replace, method, inplace, limit):
     result = pd.Series(values, index=self.index, dtype=self.dtype).__finalize__(self)
 
     if inplace:
-        self._update_inplace(result._data)
+        self._update_inplace(result)
         return
 
     return result
@@ -988,7 +988,7 @@ def rename(
             result._clear_item_cache()
 
         if inplace:
-            self._update_inplace(result._data)
+            self._update_inplace(result)
             return None
         else:
             return result.__finalize__(self)
@@ -3957,15 +3957,15 @@ def _update_inplace(self, result, verify_is_copy: bool_t = True) -> None:
 
         Parameters
         ----------
+        result : same type as self
         verify_is_copy : bool, default True
             Provide is_copy checks.
         """
         # NOTE: This does *not* call __finalize__ and that's an explicit
         # decision that we may revisit in the future.
-
         self._reset_cache()
         self._clear_item_cache()
-        self._data = getattr(result, "_data", result)
+        self._data = result._data
         self._maybe_update_cacher(verify_is_copy=verify_is_copy)
 
     def add_prefix(self: FrameOrSeries, prefix: str) -> FrameOrSeries:
@@ -6107,15 +6107,15 @@ def fillna(
                     value=value, limit=limit, inplace=inplace, downcast=downcast
                 )
             elif isinstance(value, ABCDataFrame) and self.ndim == 2:
-                new_data = self.where(self.notna(), value)
+                new_data = self.where(self.notna(), value)._data
             else:
                 raise ValueError(f"invalid fill value with a {type(value)}")
 
+        result = self._constructor(new_data)
         if inplace:
-            self._update_inplace(new_data)
-            return None
+            return self._update_inplace(result)
         else:
-            return self._constructor(new_data).__finalize__(self)
+            return result.__finalize__(self)
 
     def ffill(
         self: FrameOrSeries,
@@ -6627,10 +6627,11 @@ def replace(
                         f'Invalid "to_replace" type: {repr(type(to_replace).__name__)}'
                     )
 
+        result = self._constructor(new_data)
         if inplace:
-            self._update_inplace(new_data)
+            return self._update_inplace(result)
         else:
-            return self._constructor(new_data).__finalize__(self)
+            return result.__finalize__(self)
 
     _shared_docs[
         "interpolate"
@@ -7231,7 +7232,7 @@ def _clip_with_scalar(self, lower, upper, inplace: bool_t = False):
             result[mask] = np.nan
 
         if inplace:
-            self._update_inplace(result)
+            return self._update_inplace(result)
         else:
             return result
 
@@ -8641,7 +8642,8 @@ def _where(
             new_data = self._data.putmask(
                 mask=cond, new=other, align=align, axis=block_axis,
             )
-            self._update_inplace(new_data)
+            result = self._constructor(new_data)
+            return self._update_inplace(result)
 
         else:
             new_data = self._data.where(
@@ -8652,8 +8654,8 @@ def _where(
                 try_cast=try_cast,
                 axis=block_axis,
             )
-
-            return self._constructor(new_data).__finalize__(self)
+            result = self._constructor(new_data)
+            return result.__finalize__(self)
 
     _shared_docs[
         "where"

pandas/core/indexes/base.py

@@ -534,10 +534,6 @@ def _shallow_copy_with_infer(self, values, **kwargs):
         attributes.pop("tz", None)
         return Index(values, **attributes)
 
-    def _update_inplace(self, result, **kwargs):
-        # guard when called from IndexOpsMixin
-        raise TypeError("Index can't be updated inplace")
-
     def is_(self, other) -> bool:
         """
         More flexible, faster check like ``is`` but that works through views.

pandas/core/ops/methods.py

@@ -98,7 +98,7 @@ def f(self, other):
             # this makes sure that we are aligned like the input
             # we are updating inplace so we want to ignore is_copy
             self._update_inplace(
-                result.reindex_like(self, copy=False)._data, verify_is_copy=False
+                result.reindex_like(self, copy=False), verify_is_copy=False
             )
 
             return self

pandas/core/series.py

@@ -418,10 +418,6 @@ def _set_axis(self, axis: int, labels, fastpath: bool = False) -> None:
             # The ensure_index call aabove ensures we have an Index object
             self._data.set_axis(axis, labels)
 
-    def _update_inplace(self, result, **kwargs):
-        # we want to call the generic version and not the IndexOpsMixin
-        return generic.NDFrame._update_inplace(self, result, **kwargs)
-
     # ndarray compatibility
     @property
     def dtype(self) -> DtypeObj:
@@ -1802,7 +1798,7 @@ def unique(self):
         result = super().unique()
         return result
 
-    def drop_duplicates(self, keep="first", inplace=False) -> "Series":
+    def drop_duplicates(self, keep="first", inplace=False) -> Optional["Series"]:
         """
         Return Series with duplicate values removed.
 
@@ -1877,7 +1873,13 @@ def drop_duplicates(self, keep="first", inplace=False) -> "Series":
         5     hippo
         Name: animal, dtype: object
         """
-        return super().drop_duplicates(keep=keep, inplace=inplace)
+        inplace = validate_bool_kwarg(inplace, "inplace")
+        result = super().drop_duplicates(keep=keep)
+        if inplace:
+            self._update_inplace(result)
+            return None
+        else:
+            return result
 
     def duplicated(self, keep="first") -> "Series":
         """