使用 openpyxl 在 excel 下方附加数据框时，我的 excel 表中的切片器被破坏

Question

I am working with pandas and openpyxl.

INPUT FILES

I have total three input excel files in my program. With the help of dataframes I am processing input excel files and getting a final dataframe after processing.

OUTPUT

After getting final dataframe in my program, I am writing this dataframe below an existing excel file with the help of openpyxl. This excel file contains many worksheets. Some worksheets in this excel file also contains pivot table and slicer. Dataframe is successfully appending below excel file.

**But problem is Slicer of my pivot is getting destroyed while writing dataframe below excel file.**I am getting following warning during execution of my program

C:\Users\Desktop\PycharmProjects\MyProject\venv\lib\site-packages\openpyxl\worksheet\_reader.py:292: UserWarning: Slicer List extension is not supported and will be removed
      warn(msg)

1. I am using following method to append dataframe below an existing excel sheet with the help of openpyxl-

   HELPER FUNCTION TO APPEND DATAFRAME BELOW EXCEL FILE

   def append_df_to_excel(filename, df, sheet_name='Sheet1', startrow=None, truncate_sheet=False, **to_excel_kwargs): """ Append a DataFrame [df] to existing Excel file [filename] into [sheet_name] Sheet. If [filename] doesn't exist, then this function will create it.

    Parameters: filename : File path or existing ExcelWriter (Example: '/path/to/file.xlsx') df : dataframe to save to workbook sheet_name : Name of sheet which will contain DataFrame. (default: 'Sheet1') startrow : upper left cell row to dump data frame. Per default (startrow=None) calculate the last row in the existing DF and write to the next row... truncate_sheet : truncate (remove and recreate) [sheet_name] before writing DataFrame to Excel file to_excel_kwargs : arguments which will be passed to `DataFrame.to_excel()` [can be dictionary] Returns: None """ from openpyxl import load_workbook import pandas as pd # ignore [engine] parameter if it was passed if 'engine' in to_excel_kwargs: to_excel_kwargs.pop('engine') writer = pd.ExcelWriter(filename, engine='openpyxl', index=False, data_only = 'True') # Python 2.x: define [FileNotFoundError] exception if it doesn't exist try: FileNotFoundError except NameError: FileNotFoundError = IOError try: # try to open an existing workbook writer.book = load_workbook(filename) # get the last row in the existing Excel sheet # if it was not specified explicitly if startrow is None and sheet_name in writer.book.sheetnames: startrow = writer.book[sheet_name].max_row # truncate sheet if truncate_sheet and sheet_name in writer.book.sheetnames: # index of [sheet_name] sheet idx = writer.book.sheetnames.index(sheet_name) # remove [sheet_name] writer.book.remove(writer.book.worksheets[idx]) # create an empty sheet [sheet_name] using old index writer.book.create_sheet(sheet_name, idx) # copy existing sheets writer.sheets = {ws.title:ws for ws in writer.book.worksheets} except FileNotFoundError: # file does not exist yet, we will create it pass if startrow is None: startrow = 1 # write out the new sheet df.to_excel(writer, sheet_name, startrow=startrow, **to_excel_kwargs) # save the workbook writer.save()

2. Following line is used to call above helper function

   path_of_existing_excel_file = C:\\Users\\Desktop\\MyExcel.xlsx append_df_to_excel(path_of_existing_excel_file, df1, sheet_name='MY-DATA',index = False )

3.I am able to obtain desired output.The only Problem is pivot table in excel is getting destroyed. All the sheets in my excel file which contains pivot table is losing information

Here my output is useless because I lost all the information related to my pivot table.

Hope I am clear. Now I want to ask the way by which my pivot table will not destroy ? How to do so that sheets which contains pivot table will not be affected by openpyxl? Or How can write dataframe below excel sheet so that my pivot table will not getting affected? Any of answers to above question will help me

Answer 1

I have tried many solutions.But There is no solution available with openpyxl.

So this problem can be solved by using xlwings library which is very efficient for data processing