code: def get_reindexed_values(self, empty_dtype, upcasted_na):
      if upcasted_na is None:
          # No upcasting is necessary
          fill_value = self.block.fill_value
          values = self.block.get_values()
      else:
          fill_value = upcasted_na
  
          if self.is_na:
              if getattr(self.block, "is_object", False):
                  # we want to avoid filling with np.nan if we are
                  # using None; we already know that we are all
                  # nulls
                  values = self.block.values.ravel(order="K")
                  if len(values) and values[0] is None:
                      fill_value = None
  
              if getattr(
                  self.block, "is_datetimetz", False
              ) or is_datetime64tz_dtype(empty_dtype):
                  if self.block is None:
                      array = empty_dtype.construct_array_type()
                      return array(
                          np.full(self.shape[1], fill_value.value),
                          dtype=empty_dtype,
                      )
                  pass
              elif getattr(self.block, "is_categorical", False):
                  pass
              elif getattr(self.block, "is_sparse", False):
                  pass
              elif getattr(self.block, "is_extension", False):
                  pass
              else:
                  missing_arr = np.empty(self.shape, dtype=empty_dtype)
                  missing_arr.fill(fill_value)
                  return missing_arr
  
          if not self.indexers:
              if not self.block._can_consolidate:
                  # preserve these for validation in _concat_compat
                  return self.block.values
  
          if self.block.is_bool and not self.block.is_categorical:
              # External code requested filling/upcasting, bool values must
              # be upcasted to object to avoid being upcasted to numeric.
              values = self.block.astype(np.object_).values
          elif self.block.is_extension:
              values = self.block.values
          else:
              # No dtype upcasting is done here, it will be performed during
              # concatenation itself.
              values = self.block.get_values()
  
      if not self.indexers:
          # If there's no indexing to be done, we want to signal outside
          # code that this array must be copied explicitly.  This is done
          # by returning a view and checking `retval.base`.
          values = values.view()
  
      else:
          for ax, indexer in self.indexers.items():
              values = algos.take_nd(
                  values, indexer, axis=ax, fill_value=fill_value
              )
  
      return values
  
imports: from collections import defaultdict
  import copy
  import numpy
  from pandas._libs import internals, tslibs
  from pandas.util._decorators import cache_readonly
  from pandas.core.dtypes.cast import maybe_promote
  from pandas.core.dtypes.common import _get_dtype, is_categorical_dtype, is_datetime64_dtype, is_datetime64tz_dtype, is_extension_array_dtype, is_float_dtype, is_numeric_dtype, is_sparse, is_timedelta64_dtype
  import pandas.core.dtypes.concat
  from pandas.core.dtypes.missing import isna
  import pandas.core.algorithms
label_desc: Use image node_id 6 for calling the JoinUnit obj's underlying member method code with example usage: obj.get_reindexed_values(empty_dtype, upcasted_na) and returns: values, self, array, missing_arr