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pandas.Series.to_excel — pandas 2.3.1 documentation

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=None, engine_kwargs=None)[source]#

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_writerpath-like, file-like, or ExcelWriter object

File path or existing ExcelWriter.

sheet_namestr, default ‘Sheet1’

Name of sheet which will contain DataFrame.

na_repstr, default ‘’

Missing data representation.

float_formatstr, optional

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

columnssequence or list of str, optional

Columns to write.

headerbool 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.

indexbool, default True

Write row names (index).

index_labelstr 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.

startrowint, default 0

Upper left cell row to dump data frame.

startcolint, default 0

Upper left cell column to dump data frame.

enginestr, 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_cellsbool, default True

Write MultiIndex and Hierarchical Rows as merged cells.

inf_repstr, default ‘inf’

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

freeze_panestuple of int (length 2), optional

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

storage_optionsdict, 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.

Added in version 1.2.0.

engine_kwargsdict, optional

Arbitrary keyword arguments passed to excel engine.

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")  

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')  

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