code: def put(self, key, value, format=None, append=False, **kwargs):
          
          if format is None:
              format = get_option("io.hdf.default_format") or 'fixed'
          kwargs = self._validate_format(format, kwargs)
          self._write_to_group(key, value, append=append, **kwargs)
docs: Store object in HDFStore
  
          Parameters
          ----------
          key      : object
          value    : {Series, DataFrame}
          format   : 'fixed(f)|table(t)', default is 'fixed'
              fixed(f) : Fixed format
                         Fast writing/reading. Not-appendable, nor searchable
              table(t) : Table format
                         Write as a PyTables Table structure which may perform
                         worse but allow more flexible operations like searching
                         / selecting subsets of the data
          append   : boolean, default False
              This will force Table format, append the input data to the
              existing.
          data_columns : list of columns to create as data columns, or True to
              use all columns. See
              `here <http://pandas.pydata.org/pandas-docs/stable/io.html#query-via-data-columns>`__ # noqa
          encoding : default None, provide an encoding for strings
          dropna   : boolean, default False, do not write an ALL nan row to
              the store settable by the option 'io.hdf.dropna_table'