PERF: improve efficiency of BaseMaskedArray.__setitem__

pandas/core/apply.py

@@ -85,7 +85,7 @@ def frame_apply(
     args=None,
     kwargs=None,
 ) -> FrameApply:
-    """construct and return a row or column based frame apply object"""
+    """Construct and return a row- or column-based frame apply object."""
     axis = obj._get_axis_number(axis)
     klass: type[FrameApply]
     if axis == 0:
@@ -693,7 +693,7 @@ def dtypes(self) -> Series:
         return self.obj.dtypes
 
     def apply(self) -> DataFrame | Series:
-        """compute the results"""
+        """Compute the results."""
         # dispatch to agg
         if is_list_like(self.f):
             return self.apply_multiple()
@@ -1011,7 +1011,7 @@ def result_columns(self) -> Index:
     def wrap_results_for_axis(
         self, results: ResType, res_index: Index
     ) -> DataFrame | Series:
-        """return the results for the columns"""
+        """Return the results for the columns."""
         result: DataFrame | Series
 
         # we have requested to expand

pandas/core/arrays/boolean.py

@@ -365,6 +365,9 @@ def map_string(s):
     def _coerce_to_array(self, value) -> tuple[np.ndarray, np.ndarray]:
         return coerce_to_array(value)
 
+    def _validate_setitem_value(self, value):
+        return lib.is_bool(value)
+
     @overload
     def astype(self, dtype: npt.DTypeLike, copy: bool = ...) -> np.ndarray:
         ...

pandas/core/arrays/floating.py

@@ -270,6 +270,9 @@ def _from_sequence_of_strings(
     def _coerce_to_array(self, value) -> tuple[np.ndarray, np.ndarray]:
         return coerce_to_array(value, dtype=self.dtype)
 
+    def _validate_setitem_value(self, value):
+        return lib.is_float(value)
+
     @overload
     def astype(self, dtype: npt.DTypeLike, copy: bool = ...) -> np.ndarray:
         ...

pandas/core/arrays/integer.py

@@ -338,6 +338,9 @@ def _from_sequence_of_strings(
     def _coerce_to_array(self, value) -> tuple[np.ndarray, np.ndarray]:
         return coerce_to_array(value, dtype=self.dtype)
 
+    def _validate_setitem_value(self, value):
+        return lib.is_integer(value)
+
     @overload
     def astype(self, dtype: npt.DTypeLike, copy: bool = ...) -> np.ndarray:
         ...

pandas/core/arrays/masked.py

@@ -50,6 +50,7 @@
 from pandas.core.dtypes.inference import is_array_like
 from pandas.core.dtypes.missing import (
     array_equivalent,
+    is_valid_na_for_dtype,
     isna,
     notna,
 )
@@ -82,7 +83,7 @@
 
 class BaseMaskedDtype(ExtensionDtype):
     """
-    Base class for dtypes for BasedMaskedArray subclasses.
+    Base class for dtypes for BaseMaskedArray subclasses.
     """
 
     name: str
@@ -213,19 +214,23 @@ def fillna(
     def _coerce_to_array(self, values) -> tuple[np.ndarray, np.ndarray]:
         raise AbstractMethodError(self)
 
-    def __setitem__(self, key, value) -> None:
-        _is_scalar = is_scalar(value)
-        if _is_scalar:
-            value = [value]
-        value, mask = self._coerce_to_array(value)
-
-        if _is_scalar:
-            value = value[0]
-            mask = mask[0]
+    def _validate_setitem_value(self, value) -> bool:
+        raise AbstractMethodError(self)
 
+    def __setitem__(self, key, value) -> None:
         key = check_array_indexer(self, key)
-        self._data[key] = value
-        self._mask[key] = mask
+        if is_scalar(value):
+            if self._validate_setitem_value(value):
+                self._data[key] = value
+                self._mask[key] = False
+            elif isna(value) and is_valid_na_for_dtype(value):
+                self._mask[key] = True
+            else:
+                raise TypeError(f"Invalid value '{value}' for dtype {self.dtype}")
+        else:
+            value, mask = self._coerce_to_array(value)
+            self._data[key] = value
+            self._mask[key] = mask
 
     def __iter__(self):
         if self.ndim == 1: