pandas.io.formats.style.Styler.to_excel
- Styler.to_excel(excel_writer, sheet_name='Sheet1', na_rep='', float_format=None, columns=None, header=True, index=True, index_label=None, startrow=0, startcol=0, engine=None, merge_cells=True, encoding=None, inf_rep='inf', verbose=True, freeze_panes=None)[source]
-
Write Styler to an Excel sheet.
To write a single Styler to an Excel .xlsx file it is only necessary to specify a target file name. To write to multiple sheets it is necessary to create an ExcelWriter object with a target file name, and specify a sheet in the file to write to.
Multiple sheets may be written to by specifying unique sheet_name. With all data written to the file it is necessary to save the changes. Note that creating an ExcelWriter object with a file name that already exists will result in the contents of the existing file being erased.
- Parameters
-
- excel_writer:path-like, file-like, or ExcelWriter object
-
File path or existing ExcelWriter.
- sheet_name:str, default ‘Sheet1’
-
Name of sheet which will contain DataFrame.
- na_rep:str, default ‘’
-
Missing data representation.
- float_format:str, optional
-
Format string for floating point numbers. For example
float_format="%.2f"
will format 0.1234 to 0.12. - columns:sequence or list of str, optional
-
Columns to write.
- header:bool or list of str, default True
-
Write out the column names. If a list of string is given it is assumed to be aliases for the column names.
- index:bool, default True
-
Write row names (index).
- index_label:str or sequence, optional
-
Column label for index column(s) if desired. If not specified, and header and index are True, then the index names are used. A sequence should be given if the DataFrame uses MultiIndex.
- startrow:int, default 0
-
Upper left cell row to dump data frame.
- startcol:int, default 0
-
Upper left cell column to dump data frame.
- engine:str, optional
-
Write engine to use, ‘openpyxl’ or ‘xlsxwriter’. You can also set this via the options
io.excel.xlsx.writer
,io.excel.xls.writer
, andio.excel.xlsm.writer
.Deprecated since version 1.2.0: As the xlwt package is no longer maintained, the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. - merge_cells:bool, default True
-
Write MultiIndex and Hierarchical Rows as merged cells.
- encoding:str, optional
-
Encoding of the resulting excel file. Only necessary for xlwt, other writers support unicode natively.
- inf_rep:str, default ‘inf’
-
Representation for infinity (there is no native representation for infinity in Excel).
- verbose:bool, default True
-
Display more information in the error logs.
- freeze_panes:tuple of int (length 2), optional
-
Specifies the one-based bottommost row and rightmost column that is to be frozen.
- storage_options:dict, 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
as header options. For other URLs (e.g. starting with “s3://”, and “gcs://”) the key-value pairs are forwarded tofsspec
. Please seefsspec
andurllib
for more details.New in version 1.2.0.
See also
to_csv
-
Write DataFrame to a comma-separated values (csv) file.
ExcelWriter
-
Class for writing DataFrame objects into excel sheets.
read_excel
-
Read an Excel file into a pandas DataFrame.
read_csv
-
Read a comma-separated values (csv) file into DataFrame.
Notes
For compatibility with
to_csv()
, to_excel serializes lists and dicts to strings before writing.Once a workbook has been saved it is not possible to write further data without rewriting the whole workbook.
Examples
Create, write to and save a workbook:
>>> df1 = pd.DataFrame([['a', 'b'], ['c', 'd']], ... index=['row 1', 'row 2'], ... columns=['col 1', 'col 2']) >>> df1.to_excel("output.xlsx")
To specify the sheet name:
>>> df1.to_excel("output.xlsx", ... sheet_name='Sheet_name_1')
If you wish to write to more than one sheet in the workbook, it is necessary to specify an ExcelWriter object:
>>> df2 = df1.copy() >>> with pd.ExcelWriter('output.xlsx') as writer: ... df1.to_excel(writer, sheet_name='Sheet_name_1') ... df2.to_excel(writer, sheet_name='Sheet_name_2')
ExcelWriter can also be used to append to an existing Excel file:
>>> with pd.ExcelWriter('output.xlsx', ... mode='a') as writer: ... df.to_excel(writer, sheet_name='Sheet_name_3')
To set the library that is used to write the Excel file, you can pass the engine keyword (the default engine is automatically chosen depending on the file extension):
>>> df1.to_excel('output1.xlsx', engine='xlsxwriter')
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https://pandas.pydata.org/pandas-docs/version/1.3.4/reference/api/pandas.io.formats.style.Styler.to_excel.html