pandas.Series.to_excel

Series.to_excel(excel_writer, sheet_name='Sheet1', na_rep='', float_format=None, columns=None, header=True, index=True, index_label=None, startrow=0, startcol=0, engine=None, merge_cells=True, encoding=None, inf_rep='inf', verbose=True) [source]

Write Series to an excel sheet

New in version 0.20.0.

Parameters:

excel_writer : string or ExcelWriter object File path or existing ExcelWriter sheet_name : string, default ‘Sheet1’ Name of sheet which will contain DataFrame na_rep : string, default ‘’ Missing data representation float_format : string, default None Format string for floating point numbers columns : sequence, optional Columns to write header : boolean or list of string, default True Write out the column names. If a list of strings 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 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. merge_cells : boolean, default True Write MultiIndex and Hierarchical Rows as merged cells. encoding: string, default None encoding of the resulting excel file. Only necessary for xlwt, other writers support unicode natively. inf_rep : string, default ‘inf’ Representation for infinity (there is no native representation for infinity in Excel) freeze_panes : tuple of integer (length 2), default None Specifies the one-based bottommost row and rightmost column that is to be frozen New in version 0.20.0.

Notes

If passing an existing ExcelWriter object, then the sheet will be added to the existing workbook. This can be used to save different DataFrames to one workbook:

>>> writer = pd.ExcelWriter('output.xlsx')
>>> df1.to_excel(writer,'Sheet1')
>>> df2.to_excel(writer,'Sheet2')
>>> writer.save()

For compatibility with to_csv, to_excel serializes lists and dicts to strings before writing.