Excel table:

Expected CSV table:

however, due to excel data format issue, the Column B is automatically accepting the column values as date (e.g. 01/03/2021, 01/04/2021 and 01/12/2021).

from pathlib import Path

for path in Path(excel_dir).rglob('*.xlsx'):
    print(path.name)
    df= pd.read_excel(path)
    if 'Wave' in  df.columns:
      df = pd.read_excel((path), dtype = {'Wave': str})
    else:
      df = pd.read_excel(path)

    file_name = os.path.basename(path).split('.')[0]

    csv_file_name = f'{file_name}.csv'

    df.to_csv(os.path.join(csv_dir,csv_file_name), index = False)

Using dtype as str I am not able to convert Column B as expected column values. Rather it is giving me result like 01/11/2021 12:00:00 am.

How can I convert excel into csv without changing Column B values?

CodePudding user response：

Pandas Module support XLSX file format, check link XLSX File format Read in Pandas

import pandas as pd
data = pd.read_excel('path/of/xlsx')
data['Column B'] = data['Column B'].astype(str)

try the above code. It will convert the Column data to string

CodePudding user response：

Maybe this would work as you want:
df['Date'] = df['Date'].apply(lambda x: str(x))