code: def __call__(self, df_or_series):
      params = df_or_series.params.copy()
      shape_list = list(df_or_series.shape)
  
      if self._index is not None:
          if isinstance(
              df_or_series.index_value.value, IndexValue.RangeIndex
          ):
              params["index_value"] = parse_index(
                  None, (df_or_series.key, df_or_series.index_value.key)
              )
          shape_list[0] = np.nan
  
      if isinstance(df_or_series, DATAFRAME_TYPE):
          new_dtypes = self._filter_dtypes(df_or_series.dtypes)
          params["columns_value"] = parse_index(
              new_dtypes.index, store_data=True
          )
          params["dtypes"] = new_dtypes
          shape_list[1] = len(new_dtypes)
          self.output_types = [OutputType.dataframe]
      elif isinstance(df_or_series, SERIES_TYPE):
          self.output_types = [OutputType.series]
      else:
          self.output_types = [OutputType.index]
  
      params["shape"] = tuple(shape_list)
  
      inputs = [df_or_series]
      if isinstance(self._index, Entity):
          inputs.append(self._index)
      return self.new_tileable(inputs, **params)
  
imports: import warnings
  from collections import OrderedDict
  import numpy
  from ...None import opcodes
  from ...core import Entity, Chunk, CHUNK_TYPE, OutputType, recursive_tile
  from ...serialization.serializables import AnyField, StringField
  from ..core import IndexValue, DATAFRAME_TYPE, SERIES_TYPE, INDEX_CHUNK_TYPE
  from ..operands import DataFrameOperand, DataFrameOperandMixin
  from ..utils import parse_index, validate_axis
label_desc: Use image node_id 8 for calling the DataFrameDrop obj's underlying member method code with example usage: obj.__call__(df_or_series) and returns: self