code: def _calc_dataframe_params(cls, chunk_index_to_chunks, chunk_shape):
      dtypes = pd.concat(
          [
              chunk_index_to_chunks[0, i].dtypes
              for i in range(chunk_shape[1])
              if (0, i) in chunk_index_to_chunks
          ]
      )
      columns_value = parse_index(dtypes.index, store_data=True)
      pd_indexes = [
          chunk_index_to_chunks[i, 0].index_value.to_pandas()
          for i in range(chunk_shape[0])
          if (i, 0) in chunk_index_to_chunks
      ]
      pd_index = reduce(lambda x, y: x.append(y), pd_indexes)
      index_value = parse_index(pd_index)
      return {
          "dtypes": dtypes,
          "columns_value": columns_value,
          "index_value": index_value,
      }
  
imports: from collections import OrderedDict
  from functools import reduce
  import numpy
  import pandas
  from ..core import FuseChunkData, FuseChunk, ENTITY_TYPE, OutputType
  from ..core.operand import Operand, TileableOperandMixin, Fuse, ShuffleProxy, FuseChunkMixin
  from ..tensor.core import TENSOR_TYPE
  from ..tensor.datasource import tensor
  from ..tensor.operands import TensorOperandMixin
  from ..utils import calc_nsplits
  from .core import DATAFRAME_CHUNK_TYPE, SERIES_CHUNK_TYPE, INDEX_CHUNK_TYPE, DATAFRAME_TYPE, SERIES_TYPE, INDEX_TYPE, DATAFRAME_GROUPBY_TYPE, SERIES_GROUPBY_TYPE, CATEGORICAL_TYPE
  from .utils import parse_index
label_desc: Use image node_id 16 for calling the DataFrameOperandMixin obj's underlying member method code with example usage: obj._calc_dataframe_params(cls, chunk_index_to_chunks, chunk_shape) and returns: dict