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)[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 or ‘columns’, default False: If True, write MultiIndex index and columns as merged cells. If ‘columns’, merge MultiIndex column cells only.
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.

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")  