code: def _get_chunk_index_min_max(index_chunks):
      chunk_index_min_max = []
      for chunk in index_chunks:
          min_val = chunk.min_val
          min_val_close = chunk.min_val_close
          max_val = chunk.max_val
          max_val_close = chunk.max_val_close
          if min_val is None or max_val is None:
              chunk_index_min_max.append((None, True, None, True))
          else:
              chunk_index_min_max.append(
                  (min_val, min_val_close, max_val, max_val_close)
              )
      return chunk_index_min_max
  
imports: import itertools
  import operator
  import numpy
  import pandas
  from ..None import opcodes
  from ..core import OutputType
  from ..core.operand import OperandStage, MapReduceOperand
  from ..serialization.serializables import FieldTypes, AnyField, BoolField, Int32Field, KeyField, ListField
  from .core import SERIES_CHUNK_TYPE
  from .utils import hash_dtypes, filter_dtypes
  from .operands import DataFrameOperandMixin, DataFrameShuffleProxy
  from .utils import parse_index, split_monotonic_index_min_max, build_split_idx_to_origin_idx, filter_index_value, hash_index, is_index_value_identical, validate_axis
label_desc: Use image node_id 1 for calling a global function with example usage: _get_chunk_index_min_max(index_chunks) and returns: chunk_index_min_max