CLN: remove unused kwargs from BlockManager.downcast

pandas/core/internals/blocks.py

@@ -403,7 +403,9 @@ def _split_op_result(self, result) -> List["Block"]:
 
         return [result]
 
-    def fillna(self, value, limit=None, inplace: bool = False, downcast=None):
+    def fillna(
+        self, value, limit=None, inplace: bool = False, downcast=None
+    ) -> List["Block"]:
         """
         fillna on the block with the value. If we fail, then convert to
         ObjectBlock and try again
@@ -417,9 +419,9 @@ def fillna(self, value, limit=None, inplace: bool = False, downcast=None):
 
         if not self._can_hold_na:
             if inplace:
-                return self
+                return [self]
             else:
-                return self.copy()
+                return [self.copy()]
 
         if self._can_hold_element(value):
             # equivalent: _try_coerce_args(value) would not raise
@@ -428,7 +430,7 @@ def fillna(self, value, limit=None, inplace: bool = False, downcast=None):
 
         # we can't process the value, but nothing to do
         if not mask.any():
-            return self if inplace else self.copy()
+            return [self] if inplace else [self.copy()]
 
         # operate column-by-column
         def f(mask, val, idx):
@@ -442,7 +444,7 @@ def f(mask, val, idx):
 
         return self.split_and_operate(None, f, inplace)
 
-    def split_and_operate(self, mask, f, inplace: bool):
+    def split_and_operate(self, mask, f, inplace: bool) -> List["Block"]:
         """
         split the block per-column, and apply the callable f
         per-column, return a new block for each. Handle
@@ -1191,7 +1193,7 @@ def _interpolate_with_fill(
         fill_value=None,
         coerce=False,
         downcast=None,
-    ):
+    ) -> List["Block"]:
         """ fillna but using the interpolate machinery """
         inplace = validate_bool_kwarg(inplace, "inplace")
 
@@ -1233,15 +1235,15 @@ def _interpolate(
         inplace=False,
         downcast=None,
         **kwargs,
-    ):
+    ) -> List["Block"]:
         """ interpolate using scipy wrappers """
         inplace = validate_bool_kwarg(inplace, "inplace")
         data = self.values if inplace else self.values.copy()
 
         # only deal with floats
         if not self.is_float:
             if not self.is_integer:
-                return self
+                return [self]
             data = data.astype(np.float64)
 
         if fill_value is None:

pandas/core/internals/managers.py

@@ -565,8 +565,8 @@ def isna(self, func) -> "BlockManager":
     def where(self, **kwargs) -> "BlockManager":
         return self.apply("where", **kwargs)
 
-    def setitem(self, **kwargs) -> "BlockManager":
-        return self.apply("setitem", **kwargs)
+    def setitem(self, indexer, value) -> "BlockManager":
+        return self.apply("setitem", indexer=indexer, value=value)
 
     def putmask(self, **kwargs):
         return self.apply("putmask", **kwargs)
@@ -583,16 +583,30 @@ def shift(self, **kwargs) -> "BlockManager":
     def fillna(self, **kwargs) -> "BlockManager":
         return self.apply("fillna", **kwargs)
 
-    def downcast(self, **kwargs) -> "BlockManager":
-        return self.apply("downcast", **kwargs)
+    def downcast(self) -> "BlockManager":
+        return self.apply("downcast")
 
     def astype(
         self, dtype, copy: bool = False, errors: str = "raise"
     ) -> "BlockManager":
         return self.apply("astype", dtype=dtype, copy=copy, errors=errors)
 
-    def convert(self, **kwargs) -> "BlockManager":
-        return self.apply("convert", **kwargs)
+    def convert(
+        self,
+        copy: bool = True,
+        datetime: bool = True,
+        numeric: bool = True,
+        timedelta: bool = True,
+        coerce: bool = False,
+    ) -> "BlockManager":
+        return self.apply(
+            "convert",
+            copy=copy,
+            datetime=datetime,
+            numeric=numeric,
+            timedelta=timedelta,
+            coerce=coerce,
+        )
 
     def replace(self, value, **kwargs) -> "BlockManager":
         assert np.ndim(value) == 0, value

pandas/tests/generic/test_generic.py

@@ -159,27 +159,14 @@ def test_downcast(self):
 
         o = self._construct(shape=4, value=9, dtype=np.int64)
         result = o.copy()
-        result._data = o._data.downcast(dtypes="infer")
+        result._data = o._data.downcast()
         self._compare(result, o)
 
-        o = self._construct(shape=4, value=9.0)
-        expected = o.astype(np.int64)
-        result = o.copy()
-        result._data = o._data.downcast(dtypes="infer")
-        self._compare(result, expected)
-
         o = self._construct(shape=4, value=9.5)
         result = o.copy()
-        result._data = o._data.downcast(dtypes="infer")
+        result._data = o._data.downcast()
         self._compare(result, o)
 
-        # are close
-        o = self._construct(shape=4, value=9.000000000005)
-        result = o.copy()
-        result._data = o._data.downcast(dtypes="infer")
-        expected = o.astype(np.int64)
-        self._compare(result, expected)
-
     def test_constructor_compound_dtypes(self):
         # see gh-5191
         # Compound dtypes should raise NotImplementedError.