Inpdata=inpdata.map(lambda x: len(x.split())) # Module Creation #įor CID, cid_data in all_oupby('CID'):
Mod = pd.read_excel(r"Payroll_dict.xlsx", sheetname='Payroll Dictionary')Īll_info = all_info)]ĬategoryDict = mod.loc = module, 'Header'] #Removing Special Characteres to avoid import #Name issueĪll_info= all_info.map(lambda x: x.lstrip('+-')) # inpdata = pd.read_table(os.path.join(path_TXT, each_file), header=None,encoding = "ISO-8859-1",sep='\n', error_bad_lines=False) Str_err = "Could not process the file %s" % (each_file)
Inpdata = pd.read_table(os.path.join(path_TXT, each_file), header=None, engine='python',encoding = "ISO-8859-1",sep='\n',error_bad_lines=False) # cnd_id = (re.findall('\d', each_file )) Inpdata = pd.read_table(os.path.join(path_TXT, each_file), header=None,encoding = "ISO-8859-1",sep='\n') #error_file=pd.DataFrame(index=,columns=) # only in case extra file is gettign created #all_text = for filename in os.listdir(path_TXT)] Subprocess.call([os.path.join(path_PDF, "pdftotext.exe"), '-raw', '-eol', 'dos','-layout', Txt_filename = each_file.partition('.') + ".txt" With subprocess.Popen(, stdout=subprocess.PIPE) as proc: #Converting CVs from Various format to txt Format # Os.chdir(r"C:\Analytics\Microsoft\One_Time_Payment") Import re,os, subprocess, pandas as pd, numpy as np