code: def _parse_pandas_dataframe(self, data_object, truncate=True):
      headers = list(data_object.columns)
      data = data_object
      if truncate:
          data = data_object.head()
      index_column = data.index
  
      # We explicitly cast the `index_column` object to an `Index` or `MultiIndex` having JSON-castable values.
      if index_column.__class__.__name__ == "MultiIndex":
          from pandas import MultiIndex
  
          cols = [
              self._parse_pandas_column(
                  index_column.get_level_values(name).to_series()
              )
              for name in index_column.names
          ]
          index_column = MultiIndex.from_arrays(
              cols, names=index_column.names
          )
      else:
          from pandas import Index
  
          index_column = Index(
              self._parse_pandas_column(index_column.to_series())
          )
  
      for col in data.columns:
          data[col] = self._parse_pandas_column(data[col])
  
      data_vals = data.values.tolist()
      for row, idx in zip(data_vals, index_column.values.tolist()):
          row.insert(0, idx)
      return dict(
          full_size=(
              # full_size is a tuple of (num_rows,num_columns)
              len(data_object),
              len(headers),
          ),
          headers=[""] + headers,
          data=data_vals,
          truncated=truncate,
      )
  
imports: import json
  import sys
  import base64
  import datetime
  from collections import namedtuple
label_desc: Use image node_id 26 for calling the TaskToDict obj's underlying member method code with example usage: obj._parse_pandas_dataframe(data_object, truncate) and returns: dict