def put(self, key, value, format=None, append=False, **kwargs):
if format is None:<EOL><INDENT>format = get_option("<STR_LIT>") or '<STR_LIT>'<EOL><DEDENT>kwargs = self._validate_format(format, kwargs)<EOL>self._write_to_group(key, value, append=append, **kwargs)<EOL>
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'