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# pandas.DataFrame.to_excel

DataFrame.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, inf_rep='inf', freeze_panes=None, storage_options=None, engine_kwargs=None, autofilter=False)

  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 overwrite the existing file because the default mode is write.

  Parameters:
    excel_writer path-like, file-like, 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` or `io.excel.xlsm.writer`.

    merge_cells bool or ‘columns’, default True

      If True, write MultiIndex index and columns as merged cells. If ‘columns’, merge MultiIndex column cells only.

    inf_rep str, default ‘inf’

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

    freeze_panes tuple of int (length 2), optional

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

    storage_options dict, optional

      Extra options that make sense for a particular storage connection, e.g. host, port, username, password, etc. For HTTP(S) URLs the key-value pairs are forwarded to `urllib.request.Request` as header options. For other URLs (e.g. starting with “s3://”, and “gcs://”) the key-value pairs are forwarded to `fsspec.open`. Please see `fsspec` and `urllib` for more details, and for more examples on storage options refer here.

    engine_kwargs dict, optional

      Arbitrary keyword arguments passed to excel engine.

    autofilter bool, default False

      If True, add automatic filters to all columns.

  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.

  `io.formats.style.Styler.to_excel`

    Add styles to Excel sheet.

  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 to write further data without rewriting the whole workbook.

  pandas will check the number of rows, columns, and cell character count does not exceed Excel’s limitations. All other limitations must be checked by the user.

  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")

  To specify the sheet name:

      >>> df1.to_excel("output.xlsx", sheet_name="Sheet_name_1")

  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:
      ...     df1.to_excel(writer, sheet_name="Sheet_name_1")
      ...     df2.to_excel(writer, sheet_name="Sheet_name_2")

  ExcelWriter can also be used to append to an existing Excel file:

      >>> with pd.ExcelWriter("output.xlsx", mode="a") as writer:
      ...     df1.to_excel(writer, sheet_name="Sheet_name_3")

  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")