The problem might arise because of the meta-text in the .csv or .txt file that is not really written there but is copied when its content is loaded somewhere.

I think it is better to first import your text in an array or a string and then split it and save into the dataframe specifically when your data is not too large.

import csv 
arrays = []
path = "C:\\Users\\Souro\\Downloads\\AXISBANK.csv"
with open(path, 'r') as f: 
   reader = csv.reader(f) 
   for row in reader: 
       row = str(row).replace('\\', '') #deleting backslash
       arrays.append(row)

Then take a look at arrays[:10] to find where the meta data ends and delete the unwanted data (meta data) and then converting the 'arrays' array into the dataframe. for instance:

arrays = arrays[9:]
df = pd.DataFrame(arrays[1:], columns=arrays[0]) #arrays[0] is the columns names