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######################## Docstring (pandas.ExcelWriter) ########################
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Class for writing DataFrame objects into excel sheets.

Default is to use xlwt for xls, xlsxwriter 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:: 1.2.0

        As the `xlwt <https://pypi.org/project/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`__ package is no longer
        maintained, the ``xlwt`` engine will be removed in a future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://".

    .. versionadded:: 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.

    .. versionadded:: 1.3.0
engine_kwargs : dict, optional
    Keyword arguments to be passed into the engine.

    .. versionadded:: 1.3.0
**kwargs : dict, optional
    Keyword arguments to be passed into the engine.

    .. deprecated:: 1.3.0

        Use engine_kwargs instead.

Attributes
----------
None

Methods
-------
None

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)

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