pandas.ExcelWriter

class pandas.ExcelWriter(path, engine=None, date_format=None, datetime_format=None, mode='w', storage_options=None, if_sheet_exists=None, engine_kwargs=None, **kwargs)[source]

Class for writing DataFrame objects into excel sheets.

Default is to use : * xlwt for xls * xlsxwriter for xlsx if xlsxwriter is installed otherwise openpyxl * odf for ods. See DataFrame.to_excel for typical usage.

The writer should be used as a context manager. Otherwise, call close() to save and close any opened file handles.

Parameters
pathstr or typing.BinaryIO

Path to xls or xlsx or ods file.

enginestr (optional)

Engine to use for writing. If None, defaults to io.excel.<extension>.writer. NOTE: can only be passed as a keyword argument.

Deprecated since version 1.2.0: As the xlwt package is no longer maintained, the xlwt engine will be removed in a future version of pandas.

date_formatstr, default None

Format string for dates written into Excel files (e.g. ‘YYYY-MM-DD’).

datetime_formatstr, default None

Format string for datetime objects written into Excel files. (e.g. ‘YYYY-MM-DD HH:MM:SS’).

mode{‘w’, ‘a’}, default ‘w’

File mode to use (write or append). Append does not work with fsspec URLs.

storage_optionsdict, optional

Extra options that make sense for a particular storage connection, e.g. host, port, username, password, etc., if using a URL that will be parsed by fsspec, e.g., starting “s3://”, “gcs://”.

New in version 1.2.0.

if_sheet_exists{‘error’, ‘new’, ‘replace’}, default ‘error’

How to behave when trying to write to a sheet that already exists (append mode only).

  • error: raise a ValueError.

  • new: Create a new sheet, with a name determined by the engine.

  • replace: Delete the contents of the sheet before writing to it.

New in version 1.3.0.

engine_kwargsdict, optional

Keyword arguments to be passed into the engine.

New in version 1.3.0.

**kwargsdict, optional

Keyword arguments to be passed into the engine.

Deprecated since version 1.3.0: Use engine_kwargs instead.

Notes

None of the methods and properties are considered public.

For compatibility with CSV writers, ExcelWriter serializes lists and dicts to strings before writing.

Examples

Default usage:

>>> df = pd.DataFrame([["ABC", "XYZ"]], columns=["Foo", "Bar"])
>>> with pd.ExcelWriter("path_to_file.xlsx") as writer:
...     df.to_excel(writer)

To write to separate sheets in a single file:

>>> df1 = pd.DataFrame([["AAA", "BBB"]], columns=["Spam", "Egg"])
>>> df2 = pd.DataFrame([["ABC", "XYZ"]], columns=["Foo", "Bar"])
>>> with pd.ExcelWriter("path_to_file.xlsx") as writer:
...     df1.to_excel(writer, sheet_name="Sheet1")
...     df2.to_excel(writer, sheet_name="Sheet2")

You can set the date format or datetime format:

>>> from datetime import date, datetime
>>> df = pd.DataFrame(
...     [
...         [date(2014, 1, 31), date(1999, 9, 24)],
...         [datetime(1998, 5, 26, 23, 33, 4), datetime(2014, 2, 28, 13, 5, 13)],
...     ],
...     index=["Date", "Datetime"],
...     columns=["X", "Y"],
... )
>>> with pd.ExcelWriter(
...     "path_to_file.xlsx",
...     date_format="YYYY-MM-DD",
...     datetime_format="YYYY-MM-DD HH:MM:SS"
... ) as writer:
...     df.to_excel(writer)

You can also append to an existing Excel file:

>>> with pd.ExcelWriter("path_to_file.xlsx", mode="a", engine="openpyxl") as writer:
...     df.to_excel(writer, sheet_name="Sheet3")

You can store Excel file in RAM:

>>> import io
>>> df = pd.DataFrame([["ABC", "XYZ"]], columns=["Foo", "Bar"])
>>> buffer = io.BytesIO()
>>> with pd.ExcelWriter(buffer) as writer:
...     df.to_excel(writer)

You can pack Excel file into zip archive:

>>> import zipfile
>>> df = pd.DataFrame([["ABC", "XYZ"]], columns=["Foo", "Bar"])
>>> with zipfile.ZipFile("path_to_file.zip", "w") as zf:
...     with zf.open("filename.xlsx", "w") as buffer:
...         with pd.ExcelWriter(buffer) as writer:
...             df.to_excel(writer)

Attributes

None

Methods

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