News Classification is the latest buzz word in NLP for identifying the type of news and figuring out its a fake or not. There is a dataset available Urdu News extracted from web and has multiple classes and can be used for news classificaiton and other purposes. Preprocessing: News dataset is in multiple excel files, for the sake of classification, we need to convert it to single csv file. Here is how I did it import pandas as pd import glob files = glob.glob( "data/*.xlsx" ) df = pd.DataFrame() # if you want to use xlrd then 1.2.0 is good to go, openpyxl has a lot of issues. for file in files: excel_file = pd.read_excel(file , index_col= None , na_values=[ 'NA' ] , usecols=[ "category" , "summery" , "title" ] , engine= "xlrd" ) df = df.append(excel_file , ignore_index= True ) df.drop_duplicates(inplace= True ) # use single word for classification. df.category = df.category.str.replace( "weird ne