pandas.ExcelWriter — pandas 0.25.3 documentation (original) (raw)
class pandas.
ExcelWriter
(path, engine=None, date_format=None, datetime_format=None, mode='w', **engine_kwargs)[source]¶
Class for writing DataFrame objects into excel sheets, default is to use xlwt for xls, openpyxl for xlsx. See DataFrame.to_excel for typical usage.
Parameters: | path : string Path to xls or xlsx file. engine : string (optional) Engine to use for writing. If None, defaults toio.excel..writer. NOTE: can only be passed as a keyword argument. date_format : string, default None Format string for dates written into Excel files (e.g. ‘YYYY-MM-DD’) datetime_format : string, 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). New in version 0.24.0. |
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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:
with ExcelWriter('path_to_file.xlsx') as writer: ... df.to_excel(writer)
To write to separate sheets in a single file:
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:
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') as writer: ... df.to_excel(writer, sheet_name='Sheet3')
Attributes
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Methods
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