code: def gff3_to_dataframe(path, attributes=None, region=None, score_fill=-1,
                        phase_fill=-1, attributes_fill='.', tabix='tabix', **kwargs):
      
  
      import pandas
  
      # read records
      recs = list(iter_gff3(path, attributes=attributes, region=region,
                            score_fill=score_fill, phase_fill=phase_fill,
                            attributes_fill=attributes_fill, tabix=tabix))
  
      # load into pandas
      columns = ['seqid', 'source', 'type', 'start', 'end', 'score', 'strand', 'phase']
      if attributes:
          columns += list(attributes)
      df = pandas.DataFrame.from_records(recs, columns=columns, **kwargs)
  
      return df
docs: Load data from a GFF3 into a pandas DataFrame.
  
      Parameters
      ----------
      path : string
          Path to input file.
      attributes : list of strings, optional
          List of columns to extract from the "attributes" field.
      region : string, optional
          Genome region to extract. If given, file must be position
          sorted, bgzipped and tabix indexed. Tabix must also be installed
          and on the system path.
      score_fill : int, optional
          Value to use where score field has a missing value.
      phase_fill : int, optional
          Value to use where phase field has a missing value.
      attributes_fill : object or list of objects, optional
          Value(s) to use where attribute field(s) have a missing value.
      tabix : string, optional
          Tabix command.
  
      Returns
      -------
      pandas.DataFrame