import os import numpy as np import pandas as pd from sqlalchemy import create_engine ######################################################################################################## # 将小米的订单中,属于小米后台的数据剔除 # data目录:小米后台下载的对账单 # 0730-0809目录:我方ftp下载的对账单 # out目录:给小米生成的新的对账单 ######################################################################################################## curr_path = os.path.dirname(os.path.abspath(__file__)) # 小米后台数据 data_path = os.path.join(curr_path,"data") print( data_path ) r_dict = {} for root,dirs,files in os.walk( data_path ): for file in files: file_item = os.path.join(root,file) print( file_item ) df = pd.read_csv( file_item, usecols=[2] ,encoding='utf8') for value in df.values: order_id = value[0].strip() print( order_id ) r_dict[ order_id ] = 1 #print( r_dict ) # 蓝色火焰后台数据 my_path = os.path.join(curr_path,"0729-0824") out_path = os.path.join(curr_path,"out") print( my_path ) print( out_path ) for root,dirs,files in os.walk( my_path ): result = [['订单号','手机号码','规格','商户订单号','收单日期','回调日期','归属地','价格','充值状态','状态描述']] for file in files: file_item = os.path.join(root,file) print( file_item ) df = pd.read_csv( file_item ) #result = [['订单号','手机号码','规格','商户订单号','收单日期','回调日期','归属地','价格','充值状态','状态描述']] for value in df.values: order_id = value[3].strip() #print( order_id ) if order_id in r_dict: #print( order_id ) pass elif value[8] == 6: result.append( value ) ''' #print( result ) dt = np.dtype((str, 32)) f_value = np.array( result, dtype=dt) print( f_value ) frame = pd.DataFrame(f_value) f_path = os.path.basename(file_item) print( f_path ) write_path = os.path.join(out_path,f_path) print( write_path ) frame.to_csv(write_path, index=False, header=0 , sep=',',encoding='utf-8') #f_path = os.path.splitext(file_item) #write_path = f_path[0] + ".xlsx" #print( write_path ) #frame = pd.DataFrame(f_value, index=['订单号','手机号码','规格','商户订单号','收单日期','回调日期','归属地','价格','充值状态','状态描述']) #frame = pd.DataFrame(f_value) #frame.to_excel( write_path ) ''' #print( result ) dt = np.dtype((str, 32)) f_value = np.array( result, dtype=dt) print( f_value ) frame = pd.DataFrame(f_value) f_path = os.path.basename(file_item) print( f_path ) write_path = os.path.join(out_path,f_path) print( write_path ) frame.to_csv(write_path, index=False, header=0 , sep=',',encoding='utf-8-sig')