code: def is_numeric_v_string_like(a: ArrayLike, b) -> bool:
      """
      Check if we are comparing a string-like object to a numeric ndarray.
      NumPy doesn't like to compare such objects, especially numeric arrays
      and scalar string-likes.
  
      Parameters
      ----------
      a : array-like, scalar
          The first object to check.
      b : array-like, scalar
          The second object to check.
  
      Returns
      -------
      boolean
          Whether we return a comparing a string-like object to a numeric array.
  
      Examples
      --------
      >>> is_numeric_v_string_like(np.array([1]), "foo")
      True
      >>> is_numeric_v_string_like(np.array([1, 2]), np.array(["foo"]))
      True
      >>> is_numeric_v_string_like(np.array(["foo"]), np.array([1, 2]))
      True
      >>> is_numeric_v_string_like(np.array([1]), np.array([2]))
      False
      >>> is_numeric_v_string_like(np.array(["foo"]), np.array(["foo"]))
      False
      """
      is_a_array = isinstance(a, np.ndarray)
      is_b_array = isinstance(b, np.ndarray)
  
      is_a_numeric_array = is_a_array and a.dtype.kind in (
          "u",
          "i",
          "f",
          "c",
          "b",
      )
      is_b_numeric_array = is_b_array and b.dtype.kind in (
          "u",
          "i",
          "f",
          "c",
          "b",
      )
      is_a_string_array = is_a_array and a.dtype.kind in ("S", "U")
      is_b_string_array = is_b_array and b.dtype.kind in ("S", "U")
  
      is_b_scalar_string_like = not is_b_array and isinstance(b, str)
  
      return (
          (is_a_numeric_array and is_b_scalar_string_like)
          or (is_a_numeric_array and is_b_string_array)
          or (is_b_numeric_array and is_a_string_array)
      )
  
imports: from __future__ import annotations
  from typing import Any, Callable
  import warnings
  import numpy
  from pandas._libs import Interval, Period, algos, lib
  from pandas._libs.tslibs import conversion
  from pandas._typing import ArrayLike, DtypeObj
  from pandas.core.dtypes.base import _registry
  from pandas.core.dtypes.dtypes import CategoricalDtype, DatetimeTZDtype, ExtensionDtype, IntervalDtype, PeriodDtype
  from pandas.core.dtypes.generic import ABCIndex
  from pandas.core.dtypes.inference import is_array_like, is_bool, is_complex, is_dataclass, is_decimal, is_dict_like, is_file_like, is_float, is_hashable, is_integer, is_interval, is_iterator, is_list_like, is_named_tuple, is_nested_list_like, is_number, is_re, is_re_compilable, is_scalar, is_sequence
label_desc: Use image node_id 27 for calling a global function with example usage: is_numeric_v_string_like(a, b) and returns: unknown