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Solve the following problem using Python, implementing the functions described below, one line at a time
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Description:
 def to_excel(self, path, na_rep='', engine=None, **kwargs):
 """ Write each DataFrame in Panel to a separate excel sheet. Parameters path : string or ExcelWriter object File path or existing ExcelWriter na_rep : string, default '' Missing data representation engine : string, default None write engine to use - you can also set this via the options ``io.excel.xlsx.writer``, ``io.excel.xls.writer``, and ``io.excel.xlsm.writer``. Other Parameters float_format : string, default None Format string for floating point numbers cols : sequence, optional Columns to write header : boolean or list of string, default True Write out column names. If a list of string is given it is assumed to be aliases for the column names index : boolean, default True Write row names (index) index_label : string or sequence, default None Column label for index column(s) if desired. If None is given, and `header` and `index` are True, then the index names are used. A sequence should be given if the DataFrame uses MultiIndex. startrow : upper left cell row to dump data frame startcol : upper left cell column to dump data frame Notes ----- Keyword arguments (and na_rep) are passed to the ``to_excel`` method for each DataFrame written. """

        from pandas.io.excel import ExcelWriter

        if isinstance(path, str):
            writer = ExcelWriter(path, engine=engine)
        else:
            writer = path
        kwargs['na_rep'] = na_rep

        for item, df in self.iteritems():
            name = str(item)
            df.to_excel(writer, name, **kwargs)
        writer.save()