code: def to_pandas_dataframe(self):
          
          import pandas as pd
  
          try:
              variable_order = sorted(self.linear)
          except TypeError:
              variable_order = list(self.linear)
  
          return pd.DataFrame(self.to_numpy_matrix(variable_order=variable_order),
                              index=variable_order,
                              columns=variable_order)
docs: Convert a binary quadratic model to pandas DataFrame format.
  
          Returns:
              :class:`pandas.DataFrame`: The binary quadratic model as a DataFrame. The DataFrame has
              binary vartype. The rows and columns are labeled by the variables in the binary quadratic
              model.
  
          Notes:
              The DataFrame representation of a binary quadratic model only makes sense for binary models.
              For a binary sample x, the energy of the model is given by:
  
              .. math::
  
                  E(x) = x^T Q x
  
  
              The offset is dropped when converting to a pandas DataFrame.
  
          Examples:
              This example converts a binary quadratic model to pandas DataFrame format.
  
              >>> import dimod
              >>> model = dimod.BinaryQuadraticModel({'a': 1.1, 'b': -1., 'c': .5},
              ...                                    {('a', 'b'): .5, ('b', 'c'): 1.5},
              ...                                    1.4,
              ...                                    dimod.BINARY)
              >>> model.to_pandas_dataframe()  # doctest: +SKIP
                   a    b    c
              a  1.1  0.5  0.0
              b  0.0 -1.0  1.5
              c  0.0  0.0  0.5