code: def __call__(self, df_or_series):
      if isinstance(df_or_series, SERIES_TYPE):
          inputs = filter_inputs([df_or_series, self.other])
          return self.new_scalar(inputs, dtype=np.dtype(np.float_))
      else:
  
          def _filter_numeric(obj):
              if not isinstance(obj, DATAFRAME_TYPE):
                  return obj
              num_dtypes = (
                  build_empty_df(obj.dtypes)._get_numeric_data().dtypes
              )
              if len(num_dtypes) != len(obj.dtypes):
                  return obj[list(num_dtypes.index)]
              return obj
  
          df_or_series = _filter_numeric(df_or_series)
          self.other = _filter_numeric(self.other)
  
          inputs = filter_inputs([df_or_series, self.other])
          if self.axis is None:
              dtypes = pd.Series(
                  [np.dtype(np.float_)] * len(df_or_series.dtypes),
                  index=df_or_series.dtypes.index,
              )
              return self.new_dataframe(
                  inputs,
                  shape=(df_or_series.shape[1],) * 2,
                  dtypes=dtypes,
                  index_value=df_or_series.columns_value,
                  columns_value=df_or_series.columns_value,
              )
          else:
              new_index_value = df_or_series.axes[
                  1 - self.axis
              ].index_value
              if isinstance(self.other, DATAFRAME_TYPE):
                  align_dtypes = pd.concat(
                      [self.other.dtypes, df_or_series.dtypes], axis=1
                  )
                  align_shape = (np.nan, align_dtypes.shape[0])
                  new_index_value = parse_index(align_dtypes.index)
              else:
                  align_shape = df_or_series.shape
  
              shape = (
                  (np.nan,)
                  if self.drop
                  else (align_shape[1 - self.axis],)
              )
              return self.new_series(
                  inputs,
                  shape=shape,
                  dtype=np.dtype(np.float_),
                  index_value=new_index_value,
              )
  
imports: import numpy
  import pandas
  from ...None import opcodes
  from ...core import ENTITY_TYPE, recursive_tile
  from ...serialization.serializables import BoolField, AnyField, KeyField, Int32Field
  from ...tensor.utils import filter_inputs
  from ...utils import has_unknown_shape
  from ..core import SERIES_TYPE, DATAFRAME_TYPE
  from ..operands import DataFrameOperand, DataFrameOperandMixin
  from ..utils import build_empty_df, validate_axis, parse_index
label_desc: Use image node_id 2 for calling the DataFrameCorr obj's underlying member method code with example usage: obj.__call__(df_or_series) and returns: self, obj, self, self, obj, obj