问从已过滤的Excel文件写入CSV

EN

import os
import openpyxl
import csv


sheet_data = []   
wb = openpyxl.load_workbook('ProductFrequency 092719_021020 by Unit.xlsx')
ws = wb.active

recordDict = {}

for i in range(9, ws.max_row+1):
    itemNum=ws['A'+str(i)].value
    description=ws['B'+str(i)].value
    quantity=ws['H'+str(i)].value

    recordDict.setdefault(itemNum,{})
    recordDict[itemNum][description] = quantity
    #print(itemNum, description, quantity)

import pandas as pd
import numpy as np
pd.set_option('display.max_rows', 100000)


resultsFile = open('Results_UNIT_092719_021020.txt', 'w')
resultsFile.close()
c = csv.writer(open("Results_UNIT_092719_021020.csv", 'w'))


count=0


while count < 78:

    df = pd.read_excel('ProductFrequency 092719_021020 by Unit.xlsx', sheet_name=count, usecols=[0,1,2,7,8,9])
    unitName = df.iloc[0,0]


    df = pd.read_excel('ProductFrequency 092719_021020 by Unit.xlsx', sheet_name=count, skiprows=8, usecols=[0,1,2,7])
    df = df.fillna(value="")

    new_df = df.loc[(df['Dist #'].str.contains('4014320')) |(df['Description'].str.contains('ALFREDO')) | (df['Description'].str.contains('CARNITAS')) | (df['Description'].str.contains('PORK CHOP'))  | (df['Brand'].str.contains('AUSTBLU')) | (df['Brand'].str.contains('CMBLRSV')) | (df['Description'].str.contains('GRAVY SAUSAGE COUNTRY RTU')) | (df['Description'].str.contains('SCRATCH RDY')) | (df['Description'].str.contains('BEEF ROAST POT')) | (df['Description'].str.contains('SALISBURY')) |  (df['Description'].str.contains('FC')) |  (df['Description'].str.contains('BRAISED')) |  (df['Description'].str.contains('TROPICAL')) | (df['Brand'].str.contains('STCLAIR') | (df['Brand'].str.contains('AUBONPN')))]
    resultsFile = open('Results_UNIT_092719_021020.txt', 'a')
    resultsFile.write('In '+unitName+' the following items are not approved \n')
    resultsFile.write(str(new_df)+'\n')
    resultsFile.write('\n')
    resultsFile.write('\n')

    resultsFile.close()


    print('In '+unitName+' the following items are not approved'+'\n\n')
    print(new_df)
    print('\n')

    count +=1