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on March 04, 2015

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LPU University

Day 1 Module 1 Excel Shortcut Module 2 Day 2 Module 5,6,7 Module 8 (Financial Function) Module 9 (Day 3) Dashboard Work Assessment Day 3 XLookup Daily Zipped File Today's Test Day 4 Final Assessment Contact Details

Gmail configuration for 2 step verification

Open the page using link: https://myaccount.google.com/u/2/?tab=kk Step-1). Now this below page will come up, and click on highlighted "Security" Step-2). Now click on 2-Step Verification as per below highlighted. Step-3). Now it'll again ask for your Gmail id confirmation so confirm it with your normal Gmail login password(which you use always normally). Step-4). Now you will find the below screen (scroll downward and you'll see below highlighted area). Step-5). Now, here you'll give any name like (Test_Email) and click to create. Step-5). Now, final password has been generated and copy this password and click on Done. as below image. Notice: for example password is b g b x t n g o y f h c n k t s but you'll take without space so the real password is like b g b x t n g o y f h c n k t s Now its done. It takes lot's of efforts to make content like this so please share with more person to grow our p...

Sending Email to multiple user (using file records)

import pandas as pd df=pd.read_csv( r"C:\Users\Home\Downloads\apple_products2.csv" , usecols =[ 'ID' , 'msg' , 'sub' ], low_memory = True ) df=pd.DataFrame(df) import smtplib from email.mime.text import MIMEText subject = "Test Email Subject" sender = "sk9775589@gmail.com" #recipients = ["sabhajeetkumar1@gmail.com"] password = "qwsnxvnheoqyauij" def send_email (subject, body, sender, recipients, password): msg = MIMEText(body) msg[ 'Subject' ] = subject msg[ 'From' ] = sender msg[ 'To' ] = ', ' .join(recipients) with smtplib.SMTP_SSL( 'smtp.gmail.com' , 465 ) as smtp_server: smtp_server.login(sender, password) smtp_server.sendmail(sender, recipients, msg.as_string()) print ( "Message sent!" ) for x in range ( len (df)): send_email(df.loc[x, 'sub' ], df.loc[x, 'msg' ], sender, df.loc[x, 'ID' ], pas...

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