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.

Default is to use:

xlsxwriter for xlsx files if xlsxwriter is installed otherwise openpyxl
odswriter for ods files

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.

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. 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.

Added in version 1.3.0.

Changed in version 1.4.0: Added overlay option

engine_kwargsdict, optional

Keyword arguments to be passed into the engine. These will be passed to the following functions of the respective engines:

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

Added in version 1.3.0.

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 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 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