code: def is_na(self):
      if self.block is None:
          return True
  
      if not self.block._can_hold_na:
          return False
  
      # Usually it's enough to check but a small fraction of values to see if
      # a block is NOT null, chunks should help in such cases.  1000 value
      # was chosen rather arbitrarily.
      values = self.block.values
      if self.block.is_categorical:
          values_flat = values.categories
      elif is_sparse(self.block.values.dtype):
          return False
      elif self.block.is_extension:
          values_flat = values
      else:
          values_flat = values.ravel(order="K")
      total_len = values_flat.shape[0]
      chunk_len = max(total_len // 40, 1000)
      for i in range(0, total_len, chunk_len):
          if not isna(values_flat[i : i + chunk_len]).all():
              return False
  
      return True
  
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 5 for calling the JoinUnit obj's underlying member method code with example usage: obj.is_na() and returns: True, True, False, False, False