I have an Excel file where some of the cells got merged and some cells have warp Text with Strike and Non Strike in it.

I want to write the data that non strike records to one Excel and other Strike records to another Excel along with the strike in the cell.

My output1:

col1        |   col2          |  col3    | col4    |col5  |
Sampletext1 | Combines TextC2 |Sample3   | text4   |text5 |
Sampletext2 | Combines TextC2 |Sample3_1 | text4_1 |text5 |
Sampletext2 | Combines TextC2 |Sample3_1 | text4_2 |text5 |

My output2:

col1        |   col2          |  col3    | col4    |col5  |
Sampletext2 | Combines TextC2 |Sample3_1 | text4_3 |text5 |

‘text4_3` should be striked out in the output file as well.

I have tried using openpyxl in python

from openpyxl import load_workbook
from openpyxl import Workbook
import pandas as pd

input_file = 'myexecel.xslx'

Workbook = load_workbook(input_file)
for i in Workbook.worksheets:
    if i.sheet_state == "visible":
         sheetname = str(i).replace('<Worksheet "', '').replace('">', '').strip()
         ws = Workbook[sheetname]

         #unmerging the cells
        for merged_cell in ws.merged_cells:
            min_row, min_col, max_row, max_col = merged_cell.min_row, merged_cell.min_col, merged_cell.max_row, merged_cell.max_col
            data = ws.cell(row=min_row, column=min_col).value
            ws.unmerge_cells(start_row=min_row, start_column=min_col, end_row=max_row, end_column=max_col)

            for row in ws.iter_rows(min_row=min_row, min_col=min_col, max_row=max_row, max_col=max_col):
                for cell in row:
                    cell.value = data


        data_all = [[cell for cell in row] for row in ws.iter_rows(values_only=True)]
        df_raw = pd.DataFrame(data_all[1:], columns=headercols)
        df_raw["strike_flag"] = [any(cell.font.strikethrough for cell in row) for row in ws.iter_rows(min_row=2)]

with the above code I was able to find whether the cell have strike through or not. But not sure how to separate strike through and non strike through records.