CLN: remove no-op BlockManager.downcast

pandas/core/generic.py

@@ -6359,9 +6359,6 @@ def fillna(
                     raise NotImplementedError()
                 result = self.T.fillna(method=method, limit=limit).T
 
-                # need to downcast here because of all of the transposes
-                result._mgr = result._mgr.downcast()
-
                 return result
 
             new_data = self._mgr.interpolate(
@@ -6415,9 +6412,6 @@ def fillna(
 
                     result = self.T.fillna(value=value, limit=limit).T
 
-                    # need to downcast here because of all of the transposes
-                    result._mgr = result._mgr.downcast()
-
                     new_data = result
                 else:
 

pandas/core/internals/array_manager.py

@@ -388,9 +388,6 @@ def fillna(self: T, value, limit, inplace: bool, downcast) -> T:
             "fillna", value=value, limit=limit, inplace=inplace, downcast=downcast
         )
 
-    def downcast(self: T) -> T:
-        return self.apply_with_block("downcast")
-
     def astype(self: T, dtype, copy: bool = False, errors: str = "raise") -> T:
         return self.apply(astype_array_safe, dtype=dtype, copy=copy, errors=errors)
 

pandas/core/internals/blocks.py

@@ -511,8 +511,9 @@ def _maybe_downcast(self, blocks: list[Block], downcast=None) -> list[Block]:
 
         # no need to downcast our float
         # unless indicated
-        if downcast is None and self.dtype.kind in ["f", "m", "M"]:
-            # TODO: complex?  more generally, self._can_hold_na?
+        if downcast is None and self.dtype.kind in ["f", "c", "m", "M"]:
+            # passing "infer" to maybe_downcast_to_dtype (via self.downcast)
+            #  would be a no-op, so we can short-circuit
             return blocks
 
         return extend_blocks([b.downcast(downcast) for b in blocks])

pandas/core/internals/managers.py

@@ -394,9 +394,6 @@ def fillna(self: T, value, limit, inplace: bool, downcast) -> T:
             "fillna", value=value, limit=limit, inplace=inplace, downcast=downcast
         )
 
-    def downcast(self: T) -> T:
-        return self.apply("downcast")
-
     def astype(self: T, dtype, copy: bool = False, errors: str = "raise") -> T:
         return self.apply("astype", dtype=dtype, copy=copy, errors=errors)
 

pandas/tests/generic/test_generic.py

@@ -164,19 +164,6 @@ def test_nonzero(self):
         with pytest.raises(ValueError, match=msg):
             not obj1
 
-    def test_downcast(self):
-        # test close downcasting
-
-        o = self._construct(shape=4, value=9, dtype=np.int64)
-        result = o.copy()
-        result._mgr = o._mgr.downcast()
-        self._compare(result, o)
-
-        o = self._construct(shape=4, value=9.5)
-        result = o.copy()
-        result._mgr = o._mgr.downcast()
-        self._compare(result, o)
-
     def test_constructor_compound_dtypes(self):
         # see gh-5191
         # Compound dtypes should raise NotImplementedError.