code: def __call__(self, df):
      if isinstance(df, DATAFRAME_TYPE):
          empty_df = build_empty_df(df.dtypes)
          new_df = empty_df.astype(
              self.dtype_values, errors=self.errors
          )
          dtypes = []
          for dt, new_dt in zip(df.dtypes, new_df.dtypes):
              if new_dt != dt and isinstance(new_dt, CategoricalDtype):
                  dtypes.append(CategoricalDtype())
              else:
                  dtypes.append(new_dt)
          dtypes = pd.Series(dtypes, index=new_df.dtypes.index)
          return self.new_dataframe(
              [df],
              shape=df.shape,
              dtypes=dtypes,
              index_value=df.index_value,
              columns_value=df.columns_value,
          )
      else:
          empty_series = build_empty_series(df.dtype)
          new_series = empty_series.astype(
              self.dtype_values, errors=self.errors
          )
          if new_series.dtype != df.dtype:
              dtype = (
                  CategoricalDtype()
                  if isinstance(new_series.dtype, CategoricalDtype)
                  else new_series.dtype
              )
          else:  # pragma: no cover
              dtype = df.dtype
  
          if isinstance(df, SERIES_TYPE):
              return self.new_series(
                  [df],
                  shape=df.shape,
                  dtype=dtype,
                  name=df.name,
                  index_value=df.index_value,
              )
          else:
              new_index = df.index_value.to_pandas().astype(
                  self.dtype_values
              )
              new_index_value = parse_index(
                  new_index, store_data=df.index_value.has_value()
              )
              return self.new_index(
                  [df],
                  shape=df.shape,
                  dtype=dtype,
                  name=df.name,
                  index_value=new_index_value,
              )
  
imports: import numpy
  import pandas
  from pandas.api.types import CategoricalDtype
  from ...None import opcodes
  from ...core import recursive_tile
  from ...serialization.serializables import AnyField, StringField, ListField
  from ...tensor.base import sort
  from ...utils import pd_release_version
  from ..core import DATAFRAME_TYPE, SERIES_TYPE
  from ..operands import DataFrameOperand, DataFrameOperandMixin
  from ..utils import build_empty_df, build_empty_series, parse_index
label_desc: Use image node_id 10 for calling the DataFrameAstype obj's underlying member method code with example usage: obj.__call__(df) and returns: self, self, self