def getPaymentStatistics(**context):
    token = context.get("ti").xcom_pull(key="token")
    PaymentData = getSheetData(token, "69045bd4e7623895abe44568")
    FinalStatsData = getSheetData(token, "69045f64c641945865aafd76")

    # PostgreSQL Database Connection Parameters
    host           = 'drowdatewarehouse.crlwwhgepgi7.ap-east-1.rds.amazonaws.com'
    dbUserName     = 'dRowAdmin'
    dbUserPassword = 'drowsuper'
    database       = 'drowDateWareHouse'
    charSet        = "utf8mb4"
    port           = "5432"
    conn_string    = ('postgres://' +
                        dbUserName + ':' + 
                        dbUserPassword +
                        '@' + host + ':' + port +
                      '/' + database)

    db = create_engine(conn_string)
    conn = db.connect()
    latest_ip = 0

    with conn as conn:
        df = pd.DataFrame()
        Mappings = {}
        for x in PaymentData:
            df_nested_list = json_normalize(x)
            latest_ip = df_nested_list['IP No.'].max()

            df = df.append(df_nested_list, ignore_index=True)
        df.rename(columns=Mappings, inplace=True)
        df.columns = df.columns.str.replace(' ', '_').str.replace('.', '').str.replace('(', '_').str.replace(')', '').str.replace('%', 'percent').str.replace('/', '_')
        print("Payment Statistics df:", df)
        df.to_sql('ssm519_payment_statistics', con=conn, if_exists='replace', index=False)

    
        df = pd.DataFrame()
        Mappings = {}
        print("Latest IP No.:", latest_ip)

        for x in FinalStatsData:
            df_nested_list = json_normalize(x)
            df = df.append(df_nested_list, ignore_index=True)
        df.rename(columns=Mappings, inplace=True)
        df.columns = df.columns.str.replace(' ', '_').str.replace('.', '').str.replace('(', '_').str.replace(')', '').str.replace('%', 'percent').str.replace('/', '_')
        df['Contract_Number'] = 'SSM519'
        df['Latest_IP_No'] = latest_ip

        main_df = pd.read_sql('SELECT * FROM scc_final_stats', con=conn)
        # Remove the old data for this contract number
        main_df = main_df[main_df['Contract_Number'] != 'SSM519']
        # Add the new data
        main_df = pd.concat([main_df, df], ignore_index=True)
        # Replace the SQL table with updated data
        main_df.to_sql('scc_final_stats', con=conn, if_exists='replace', index=False)