code: def ODF(odf_obj):
      
  
      # Handle all the various initialization types and get an IO object
      odf_io = _obtain_io(odf_obj)
  
      # Read the file as an array of lines
      raw_lines = odf_io.readlines()
  
      # Convert byte strings to unicode strings
      raw_lines = _bytes_to_str(raw_lines)
  
      try:
          # Read the header count
          header_count = _extract_header_number(raw_lines)
  
          # Read the header dict
          headers = _parse_header(raw_lines)
  
          # Read the model
          model = _extract_model(headers)
  
          # Read the column names, if available
          column_names = _extract_column_names(headers)
  
          # Assemble the data
          data_lines = _join_data_lines(raw_lines, header_count)
  
          # Put together new IO
          odf_string_io = io.StringIO(data_lines)
  
          # Load the ODF file into a DataFrame
          df = pd.read_csv(odf_string_io, sep='\t', header=None, names=column_names, skip_blank_lines=True)
  
          # Apply backwards compatible methods
          _apply_backwards_compatibility(df)
  
          # Apply ODF-specific properties
          _apply_odf_properties(df, headers, model)
  
          # Return the Dataframe
          return df
  
      # Catch any errors related to parsing the ODF file
      except Exception:
          raise TypeError('Error parsing ODF file')
docs: Create a Dataframe with the contents of the ODF file
  
      For more information on the ODF format see:
      http://software.broadinstitute.org/cancer/software/genepattern/file-formats-guide
  
      :odf_obj: The ODF file. Accepts a file-like object, a file path, a URL to the file
                or a string containing the raw data.