code: def cast_scalar_to_array(shape, value, dtype=None):
      """
      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
  
imports: from datetime import datetime, timedelta
  import numpy
  from pandas._libs import lib, tslib, tslibs
  from pandas._libs.tslibs import NaT, OutOfBoundsDatetime, Period, iNaT
  from pandas.compat import PY3, string_types, text_type, to_str
  from .common import _INT64_DTYPE, _NS_DTYPE, _POSSIBLY_CAST_DTYPES, _TD_DTYPE, ensure_int8, ensure_int16, ensure_int32, ensure_int64, ensure_object, is_bool, is_bool_dtype, is_categorical_dtype, is_complex, is_complex_dtype, is_datetime64_dtype, is_datetime64_ns_dtype, is_datetime64tz_dtype, is_datetime_or_timedelta_dtype, is_datetimelike, is_dtype_equal, is_extension_array_dtype, is_extension_type, is_float, is_float_dtype, is_integer, is_integer_dtype, is_object_dtype, is_scalar, is_string_dtype, is_timedelta64_dtype, is_timedelta64_ns_dtype, is_unsigned_integer_dtype, pandas_dtype
  from .dtypes import DatetimeTZDtype, ExtensionDtype, PandasExtensionDtype, PeriodDtype
  from .generic import ABCDatetimeArray, ABCDatetimeIndex, ABCPeriodArray, ABCPeriodIndex, ABCSeries
  from .inference import is_list_like
  from .missing import isna, notna
label_desc: Use image node_id 22 for calling a global function with example usage: cast_scalar_to_array(shape, value, dtype) and returns: values