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)[source]#

Class for writing DataFrame objects into excel sheets.

The default engine is chosen based on the file extension. The values below are the engine strings (i.e. valid values for the engine keyword); the package each one wraps is shown in parentheses:

.xlsx: "xlsxwriter" (XlsxWriter) if installed, otherwise "openpyxl" (openpyxl).
.xlsm: "openpyxl" (openpyxl).
.ods: "odf" (odfpy).

These defaults can be overridden via the engine argument or by setting the io.excel.<extension>.writer option.

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 xlsx, xlsm, or ods file.

engine{‘openpyxl’, ‘xlsxwriter’, ‘odf’}, optional

Engine to use for writing, given as the engine string (not the package name). Which engines are accepted depends on the file extension:

.xlsx: "openpyxl" or "xlsxwriter".
.xlsm: "openpyxl".
.ods: "odf" (provided by the odfpy package).

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

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.

Warning

In append mode the existing workbook is read and completely rewritten by the engine, so any content the engine cannot represent (e.g. VBA macros in .xlsm files, charts or images) is silently lost and the workbook may be otherwise altered.

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.

if_sheet_exists{‘error’, ‘new’, ‘replace’, ‘overlay’}, 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.
overlay: Write contents to the existing sheet without first removing, but possibly over top of, the existing contents.

engine_kwargsdict, optional

Keyword arguments to be passed into the engine. The bullets below are keyed by the engine string (not the package name); for each engine, engine_kwargs is forwarded as follows:

"xlsxwriter": xlsxwriter.Workbook(file, **engine_kwargs)
"openpyxl" (write mode): openpyxl.Workbook(**engine_kwargs)
"openpyxl" (append mode): openpyxl.load_workbook(file, **engine_kwargs)
"odf": odf.opendocument.OpenDocumentSpreadsheet(**engine_kwargs)

See also

read_excel: Read an Excel sheet values (xlsx) file into DataFrame.
read_csv: Read a comma-separated values (csv) file into DataFrame.
read_fwf: Read a table of fixed-width formatted lines into DataFrame.

Notes

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")

Here, the if_sheet_exists parameter can be set to replace a sheet if it already exists:

>>> with pd.ExcelWriter(
...     "path_to_file.xlsx",
...     mode="a",
...     engine="openpyxl",
...     if_sheet_exists="replace",
... ) as writer:
...     df.to_excel(writer, sheet_name="Sheet1")

You can also write multiple DataFrames to a single sheet. Note that the if_sheet_exists parameter needs to be set to overlay:

>>> with pd.ExcelWriter(
...     "path_to_file.xlsx",
...     mode="a",
...     engine="openpyxl",
...     if_sheet_exists="overlay",
... ) as writer:
...     df1.to_excel(writer, sheet_name="Sheet1")
...     df2.to_excel(writer, sheet_name="Sheet1", startcol=3)

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)

You can specify additional arguments to the underlying engine:

>>> with pd.ExcelWriter(
...     "path_to_file.xlsx",
...     engine="xlsxwriter",
...     engine_kwargs={"options": {"nan_inf_to_errors": True}},
... ) as writer:
...     df.to_excel(writer)

In append mode, engine_kwargs are passed through to openpyxl’s load_workbook:

>>> with pd.ExcelWriter(
...     "path_to_file.xlsx",
...     engine="openpyxl",
...     mode="a",
...     engine_kwargs={"keep_vba": True},
... ) as writer:
...     df.to_excel(writer, sheet_name="Sheet2")

Attributes

`book`	Book instance.
`date_format`	Format string for dates written into Excel files (e.g. 'YYYY-MM-DD').
`datetime_format`	Format string for dates written into Excel files (e.g. 'YYYY-MM-DD').
`engine`	Name of engine.
`if_sheet_exists`	How to behave when writing to a sheet that already exists in append mode.
`sheets`	Mapping of sheet names to sheet objects.
`supported_extensions`	Extensions that writer engine supports.

Methods

`check_extension`(ext)	checks that path's extension against the Writer's supported extensions.
`close`()	synonym for save, to make it more file-like