code: def dispatch_missing(op, left, right, result):
      """
      Fill nulls caused by division by zero, casting to a diffferent dtype
      if necessary.
  
      Parameters
      ----------
      op : function (operator.add, operator.div, ...)
      left : object (Index for non-reversed ops)
      right : object (Index fof reversed ops)
      result : ndarray
  
      Returns
      -------
      result : ndarray
      """
      opstr = "__{opname}__".format(opname=op.__name__).replace(
          "____", "__"
      )
      if op in [
          operator.truediv,
          operator.floordiv,
          getattr(operator, "div", None),
      ]:
          result = mask_zero_div_zero(left, right, result)
      elif op is operator.mod:
          result = fill_zeros(result, left, right, opstr, np.nan)
      elif op is divmod:
          res0 = mask_zero_div_zero(left, right, result[0])
          res1 = fill_zeros(result[1], left, right, opstr, np.nan)
          result = (res0, res1)
      return result
  
imports: from distutils.version import LooseVersion
  import operator
  import numpy
  from pandas._libs import algos, lib
  from pandas.compat import range, string_types
  from pandas.core.dtypes.cast import infer_dtype_from_array
  from pandas.core.dtypes.common import ensure_float64, is_datetime64_dtype, is_datetime64tz_dtype, is_float_dtype, is_integer, is_integer_dtype, is_numeric_v_string_like, is_scalar, is_timedelta64_dtype, needs_i8_conversion
  from pandas.core.dtypes.missing import isna
label_desc: Use image node_id 19 for calling a global function with example usage: dispatch_missing(op, left, right, result) and returns: result