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, openpyxl for xlsx, 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

path:str or typing.BinaryIO

Path to xls or xlsx or ods file.

engine:str (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Deprecated since version 1.2.0: As the xlwt package is no longer maintained, the xlwt engine will be removed in a future version of pandas.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_format:str, default None

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

datetime_format:str, 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_options:dict, 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_kwargs:dict, optional

Keyword arguments to be passed into the engine.

New in version 1.3.0.

**kwargs:dict, 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 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 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 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 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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