docs: def to_matrix(self, index_regs=None, index_meta=None,
                    columns_regs=None, columns_meta=None,
                    values_regs=None, values_meta=None, **kwargs):
          """ Transforms the GDataframe to a pivot matrix having as index and columns the
          ones specified. This function is a wrapper around the pivot_table function of Pandas.
  
          :param index_regs: list of region fields to use as index
          :param index_meta: list of metadata attributes to use as index
          :param columns_regs: list of region fields to use as columns
          :param columns_meta: list of metadata attributes to use as columns
          :param values_regs: list of region fields to use as values
          :param values_meta: list of metadata attributes to use as values
          :param kwargs: other parameters to pass to the pivot_table function
          :return: a Pandas dataframe having as index the union of index_regs and index_meta, as
                   columns the union of columns_regs and columns_meta and as values ths union
                   of values_regs and values_meta
          """
  
          index_regs = index_regs if index_regs is not None else []
          index_meta = index_meta if index_meta is not None else []
          columns_regs = columns_regs if columns_regs is not None else []
          columns_meta = columns_meta if columns_meta is not None else []
          values_regs = values_regs if values_regs is not None else []
          values_meta = values_meta if values_meta is not None else []
  
          index_meta_s = set(index_meta)
          columns_meta_s = set(columns_meta)
          values_meta_s = set(values_meta)
  
          meta_to_project = list(index_meta_s.union(columns_meta_s)\
                                             .union(values_meta_s)\
                                             .difference(set(self.regs.columns)))
          res = self.project_meta(meta_to_project)
          pivot_columns = columns_meta + columns_regs
          pivot_index = index_meta + index_regs
          pivot_values = values_regs + values_meta
  
          return res.regs.pivot_table(index=pivot_index, columns=pivot_columns, values=pivot_values, **kwargs)