code: def is_numeric_v_string_like(a, b):
      """
      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(1, 1)
      False
      >>> is_numeric_v_string_like("foo", "foo")
      False
      >>> is_numeric_v_string_like(1, "foo")  # non-array numeric
      False
      >>> is_numeric_v_string_like(np.array([1]), "foo")
      True
      >>> is_numeric_v_string_like("foo", np.array([1]))  # symmetric check
      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 is_numeric_dtype(a)
      is_b_numeric_array = is_b_array and is_numeric_dtype(b)
      is_a_string_array = is_a_array and is_string_like_dtype(a)
      is_b_string_array = is_b_array and is_string_like_dtype(b)
  
      is_a_scalar_string_like = not is_a_array and is_string_like(a)
      is_b_scalar_string_like = not is_b_array and is_string_like(b)
  
      return (
          (is_a_numeric_array and is_b_scalar_string_like)
          or (is_b_numeric_array and is_a_scalar_string_like)
          or (is_a_numeric_array and is_b_string_array)
          or (is_b_numeric_array and is_a_string_array)
      )
  
imports: import warnings
  import numpy
  from pandas._libs import algos, lib
  from pandas._libs.tslibs import conversion
  from pandas.compat import PY3, PY36, string_types
  from pandas.core.dtypes.dtypes import CategoricalDtype, DatetimeTZDtype, ExtensionDtype, IntervalDtype, PandasExtensionDtype, PeriodDtype, registry
  from pandas.core.dtypes.generic import ABCCategorical, ABCDateOffset, ABCDatetimeIndex, ABCIndexClass, ABCPeriodArray, ABCPeriodIndex, ABCSeries
  from pandas.core.dtypes.inference import is_array_like, is_bool, is_complex, 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, is_string_like
label_desc: Use image node_id 35 for calling a global function with example usage: is_numeric_v_string_like(a, b) and returns: unknown