# 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, freeze_panes=None)

  Write object to an Excel sheet.

  To write a single object to an Excel .xlsx file it is only necessary to specify a target file name. To write to multiple sheets it is necessary to create an ExcelWriter object with a target file name, and specify a sheet in the file to write to.

  Multiple sheets may be written to by specifying unique sheet_name. With all data written to the file it is necessary to save the changes. Note that creating an ExcelWriter object with a file name that already exists will result in the contents of the existing file being erased.

  Parameters:

  excel_writer : str or ExcelWriter object

  > File path or existing ExcelWriter.

  sheet_name : str, default ‘Sheet1’

  > Name of sheet which will contain DataFrame.

  na_rep : str, default ‘’

  > Missing data representation.

  float_format : str, optional

  > Format string for floating point numbers. For example `float_format="%.2f"` will format 0.1234 to 0.12.

  columns : sequence or list of str, optional

  > Columns to write.

  header : bool or list of str, default True

  > Write out the column names. If a list of string is given it is assumed to be aliases for the column names.

  index : bool, default True

  > Write row names (index).

  index_label : str or sequence, optional

  > Column label for index column(s) if desired. If not specified, and header and index are True, then the index names are used. A sequence should be given if the DataFrame uses MultiIndex.

  startrow : int, default 0

  > Upper left cell row to dump data frame.

  startcol : int, default 0

  > Upper left cell column to dump data frame.

  engine : str, optional

  > Write engine to use, ‘openpyxl’ or ‘xlsxwriter’. You can also set this via the options `io.excel.xlsx.writer`, `io.excel.xls.writer`, and `io.excel.xlsm.writer`.

  merge_cells : bool, default True

  > Write MultiIndex and Hierarchical Rows as merged cells.

  encoding : str, optional

  > Encoding of the resulting excel file. Only necessary for xlwt, other writers support unicode natively.

  inf_rep : str, default ‘inf’

  > Representation for infinity (there is no native representation for infinity in Excel).

  verbose : bool, default True

  > Display more information in the error logs.

  freeze_panes : tuple of int (length 2), optional

  > Specifies the one-based bottommost row and rightmost column that is to be frozen.

  > New in version 0.20.0..

  See also

  `to_csv`
    Write DataFrame to a comma-separated values (csv) file.
  `ExcelWriter`
    Class for writing DataFrame objects into excel sheets.
  `read_excel`
    Read an Excel file into a pandas DataFrame.
  `read_csv`
    Read a comma-separated values (csv) file into DataFrame.

  Notes

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

  Once a workbook has been saved it is not possible write further data without rewriting the whole workbook.

  Examples

  Create, write to and save a workbook:

      >>> df1 = pd.DataFrame([['a', 'b'], ['c', 'd']],
      ...                    index=['row 1', 'row 2'],
      ...                    columns=['col 1', 'col 2'])
      >>> df1.to_excel("output.xlsx")  # doctest: +SKIP

  To specify the sheet name:

      >>> df1.to_excel("output.xlsx",
      ...              sheet_name='Sheet_name_1')  # doctest: +SKIP

  If you wish to write to more than one sheet in the workbook, it is necessary to specify an ExcelWriter object:

      >>> df2 = df1.copy()
      >>> with pd.ExcelWriter('output.xlsx') as writer:  # doctest: +SKIP
      ...     df1.to_excel(writer, sheet_name='Sheet_name_1')
      ...     df2.to_excel(writer, sheet_name='Sheet_name_2')

  To set the library that is used to write the Excel file, you can pass the engine keyword (the default engine is automatically chosen depending on the file extension):

      >>> df1.to_excel('output1.xlsx', engine='xlsxwriter')  # doctest: +SKIP

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