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, and io.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  Deprecated since version 1.2.0: As the xlwt package is no longer maintained, the xlwt engine will be removed in a future version of pandas.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 to fsspec. Please see fsspec and urllib 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')