REF: simplify casting of scalars to array (#38313)

Author: jbrockmendel

pandas/core/dtypes/cast.py

@@ -33,7 +33,7 @@
     ints_to_pytimedelta,
 )
 from pandas._libs.tslibs.timezones import tz_compare
-from pandas._typing import AnyArrayLike, ArrayLike, Dtype, DtypeObj, Scalar, Shape
+from pandas._typing import AnyArrayLike, ArrayLike, Dtype, DtypeObj, Scalar
 from pandas.util._validators import validate_bool_kwarg
 
 from pandas.core.dtypes.common import (
@@ -1563,35 +1563,6 @@ def find_common_type(types: List[DtypeObj]) -> DtypeObj:
     return np.find_common_type(types, [])
 
 
-def cast_scalar_to_array(
-    shape: Shape, value: Scalar, dtype: Optional[DtypeObj] = None
-) -> np.ndarray:
-    """
-    Create np.ndarray of specified shape and dtype, filled with values.
-
-    Parameters
-    ----------
-    shape : tuple
-    value : scalar value
-    dtype : np.dtype, optional
-        dtype to coerce
-
-    Returns
-    -------
-    ndarray of shape, filled with value, of specified / inferred dtype
-
-    """
-    if dtype is None:
-        dtype, fill_value = infer_dtype_from_scalar(value)
-    else:
-        fill_value = value
-
-    values = np.empty(shape, dtype=dtype)
-    values.fill(fill_value)
-
-    return values
-
-
 def construct_1d_arraylike_from_scalar(
     value: Scalar, length: int, dtype: DtypeObj
 ) -> ArrayLike:

pandas/core/frame.py

@@ -78,7 +78,6 @@
 )
 
 from pandas.core.dtypes.cast import (
-    cast_scalar_to_array,
     construct_1d_arraylike_from_scalar,
     find_common_type,
     infer_dtype_from_scalar,
@@ -615,9 +614,8 @@ def __init__(
                 if arr.ndim != 0:
                     raise ValueError("DataFrame constructor not properly called!")
 
-                values = cast_scalar_to_array(
-                    (len(index), len(columns)), data, dtype=dtype
-                )
+                shape = (len(index), len(columns))
+                values = np.full(shape, arr)
 
                 mgr = init_ndarray(
                     values, index, columns, dtype=values.dtype, copy=False
@@ -3914,20 +3912,11 @@ def reindexer(value):
 
         else:
             # cast ignores pandas dtypes. so save the dtype first
-            infer_dtype, _ = infer_dtype_from_scalar(value, pandas_dtype=True)
+            infer_dtype, fill_value = infer_dtype_from_scalar(value, pandas_dtype=True)
 
-            # upcast
-            if is_extension_array_dtype(infer_dtype):
-                value = construct_1d_arraylike_from_scalar(
-                    value, len(self.index), infer_dtype
-                )
-            else:
-                # pandas\core\frame.py:3827: error: Argument 1 to
-                # "cast_scalar_to_array" has incompatible type "int"; expected
-                # "Tuple[Any, ...]"  [arg-type]
-                value = cast_scalar_to_array(
-                    len(self.index), value  # type: ignore[arg-type]
-                )
+            value = construct_1d_arraylike_from_scalar(
+                fill_value, len(self), infer_dtype
+            )
 
             value = maybe_cast_to_datetime(value, infer_dtype)
 

pandas/tests/dtypes/cast/test_infer_dtype.py

@@ -3,11 +3,7 @@
 import numpy as np
 import pytest
 
-from pandas.core.dtypes.cast import (
-    cast_scalar_to_array,
-    infer_dtype_from_array,
-    infer_dtype_from_scalar,
-)
+from pandas.core.dtypes.cast import infer_dtype_from_array, infer_dtype_from_scalar
 from pandas.core.dtypes.common import is_dtype_equal
 
 from pandas import (
@@ -19,7 +15,6 @@
     Timestamp,
     date_range,
 )
-import pandas._testing as tm
 
 
 @pytest.fixture(params=[True, False])
@@ -176,23 +171,3 @@ def test_infer_dtype_from_scalar_errors():
 def test_infer_dtype_from_array(arr, expected, pandas_dtype):
     dtype, _ = infer_dtype_from_array(arr, pandas_dtype=pandas_dtype)
     assert is_dtype_equal(dtype, expected)
-
-
-@pytest.mark.parametrize(
-    "obj,dtype",
-    [
-        (1, np.int64),
-        (1.1, np.float64),
-        (Timestamp("2011-01-01"), "datetime64[ns]"),
-        (Timestamp("2011-01-01", tz="US/Eastern"), object),
-        (Period("2011-01-01", freq="D"), object),
-    ],
-)
-def test_cast_scalar_to_array(obj, dtype):
-    shape = (3, 2)
-
-    exp = np.empty(shape, dtype=dtype)
-    exp.fill(obj)
-
-    arr = cast_scalar_to_array(shape, obj, dtype=dtype)
-    tm.assert_numpy_array_equal(arr, exp)