REF: remove no-longer-needed _validate_numeric_casting (#46131)

Author: jbrockmendel

pandas/core/array_algos/putmask.py

@@ -14,10 +14,7 @@
 )
 from pandas.compat import np_version_under1p20
 
-from pandas.core.dtypes.cast import (
-    convert_scalar_for_putitemlike,
-    infer_dtype_from,
-)
+from pandas.core.dtypes.cast import infer_dtype_from
 from pandas.core.dtypes.common import is_list_like
 
 from pandas.core.arrays import ExtensionArray
@@ -36,9 +33,6 @@ def putmask_inplace(values: ArrayLike, mask: npt.NDArray[np.bool_], value: Any)
     value : Any
     """
 
-    if lib.is_scalar(value) and isinstance(values, np.ndarray):
-        value = convert_scalar_for_putitemlike(value, values.dtype)
-
     if (
         not isinstance(values, np.ndarray)
         or (values.dtype == object and not lib.is_scalar(value))

pandas/core/dtypes/cast.py

@@ -1849,65 +1849,6 @@ def maybe_cast_to_integer_array(
     raise ValueError(f"values cannot be losslessly cast to {dtype}")
 
 
-def convert_scalar_for_putitemlike(scalar: Scalar, dtype: np.dtype) -> Scalar:
-    """
-    Convert datetimelike scalar if we are setting into a datetime64
-    or timedelta64 ndarray.
-
-    Parameters
-    ----------
-    scalar : scalar
-    dtype : np.dtype
-
-    Returns
-    -------
-    scalar
-    """
-    if dtype.kind in ["m", "M"]:
-        scalar = maybe_box_datetimelike(scalar, dtype)
-        return _maybe_unbox_datetimelike(scalar, dtype)
-    else:
-        _validate_numeric_casting(dtype, scalar)
-    return scalar
-
-
-def _validate_numeric_casting(dtype: np.dtype, value: Scalar) -> None:
-    """
-    Check that we can losslessly insert the given value into an array
-    with the given dtype.
-
-    Parameters
-    ----------
-    dtype : np.dtype
-    value : scalar
-
-    Raises
-    ------
-    ValueError
-    """
-    # error: Argument 1 to "__call__" of "ufunc" has incompatible type
-    # "Union[Union[str, int, float, bool], Union[Any, Timestamp, Timedelta, Any]]";
-    # expected "Union[Union[int, float, complex, str, bytes, generic],
-    # Sequence[Union[int, float, complex, str, bytes, generic]],
-    # Sequence[Sequence[Any]], _SupportsArray]"
-    if (
-        issubclass(dtype.type, (np.integer, np.bool_))
-        and is_float(value)
-        and np.isnan(value)  # type: ignore[arg-type]
-    ):
-        raise ValueError("Cannot assign nan to integer series")
-
-    elif dtype.kind in ["i", "u", "f", "c"]:
-        if is_bool(value) or isinstance(value, np.timedelta64):
-            # numpy will cast td64 to integer if we're not careful
-            raise ValueError(
-                f"Cannot assign {type(value).__name__} to float/integer series"
-            )
-    elif dtype.kind == "b":
-        if is_scalar(value) and not is_bool(value):
-            raise ValueError(f"Cannot assign {type(value).__name__} to bool series")
-
-
 def can_hold_element(arr: ArrayLike, element: Any) -> bool:
     """
     Can we do an inplace setitem with this element in an array with this dtype?