modin.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, inf_rep='inf', freeze_panes=None, storage_options: Optional[dict[str, Any]] = None, engine_kwargs=None) → None[source] (https://github.com/snowflakedb/snowpark-python/blob/v1.42.0/.tox/docs/lib/python3.9/site-packages/modin/pandas/base.py#L3310-L3351)

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 (path-like, file-like, or ExcelWriter object) – File path or existing ExcelWriter.

  • sheet_name (str, default ‘Sheet1’) – Name of sheet which will contain Series.

  • 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 Series 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, default True) – Write MultiIndex and Hierarchical Rows as merged cells.

  • 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.

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.

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")
Copy

To specify the sheet name:

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

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')
Copy

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')
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