python: excel 换行符(_x000D_)

 

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data4 = dataframe1.loc[4:34] for idx, datavalue in data4.iterrows():     #strnum=Common.Utils.Utils.getAnnualLeave(data)     print("[{}]: {}".format(idx, datavalue))     slist=datavalue.tolist()     hbll=BLL.EmpLoyeeHolidaysGet.EmpLoyeeHolidaysGet() #病假4小時_x000D_事假0.5小時 未处理     #print(slist)     for i in range(len(slist)):         #strvalue=str(slist[i]).replace(r'\s+|\\n', ' ', regex=True)  _x000D_         strvalue = str(slist[i]).replace('_x000D_', ' ')  # 规换单元格的换行符，否则处理不了正确数据         strnums = hbll.getHolidays(strvalue)  # float str         for sn in range(len(strnums)):               print("str:",strnums[sn].HolidayName,strnums[sn].WorkTime)       print("类型：",type(datavalue)) print("*************")

　　

 

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insura=[] objlist=[] datalist = [] dulist=[] # 查询某文件夹下的文件名 folderPath = Path(r'C:\\Users\\geovindu\\PycharmProjects\\pythonProject2\\') fileList = folderPath.glob('*.xls') for i in fileList:     stname = i.stem     print(stname) # 查询文件夹下的文件  print(os.path.join(path, "User/Desktop", "file.txt")) dufile = ReadExcelData.ReadExcelData.ReadFileName(folderPath, 'xls') for f in dufile:     fileurl = os.path.join(folderPath, f)     dulist1 = ReadExcelData.ReadExcelData.ReadDataFile(fileurl)  # object is not callable 变量名称冲突的原因     for duobj in dulist1:         dulist.append(duobj)     print(os.path.join(folderPath, f))   ylsum = 0  # 养老 llsum = 0  # 医疗 totalsum = 0  # 一年费用 for geovindu in dulist:     # duobj = Insurance.Insurance     print(geovindu)     name = geovindu.getInsuranceName()     duname = name.convert_dtypes()     # yname = duname['Unnamed: 2']     print(type(duname))     print("保险类型：", duname)  # class 'pandas.core.series.Series     strname = pd.Series(duname).values[0]     coas1 = geovindu.getInsuranceCost()     # coast = int(geovindu.getInsuranceCost())     coas = coas1.convert_dtypes()     coast = pd.Series(coas).values[0]  # int(coas)     # print("casa",int(coas))     totalsum = totalsum + coast     if (strname == "养老"):         ylsum = ylsum + coast     if (strname == "医疗"):         llsum = llsum + coast     print("费用：", coast)     month = int(geovindu.getIMonth())     print("月份：", month)     datalist.append([strname, coast, month])     #SQLServerDAL.SQLclass.insertStr(strname, coast, month)  # 插入数据库中 print("一年养老", ylsum) print("一年医疗", llsum) print("一年费用", totalsum) # https: // pandas.pydata.org / pandas - docs / stable / reference / api / pandas.DataFrame.groupby.html # 导出数据生成EXCEL dataf = pd.DataFrame(datalist, columns=['保险类型', '交费金额', '交费月份'])  # 增加列名称 dataf2 = pd.DataFrame({"统计类型": ["一年养老", "一年医疗", "一年费用"], "金额": [ylsum, llsum, totalsum]}) dataf.sort_values('交费月份', inplace=True)  # 指定列排序 print(sqldf('''SELECT 交费金额,交费月份 FROM dataf group by 交费月份 LIMIT 25''')) #staicmont=sqldf('''SELECT 交费金额,交费月份 FROM dataf group by 交费月份 LIMIT 25''') # 交费用分份统计 # print(sqldf('''SELECT 交费金额,交费月份 FROM dataf group by 交费月份  LIMIT 25''')) staicmonth = sqldf('''SELECT 交费金额,交费月份 FROM dataf group by 交费月份 LIMIT 25''')   with pd.ExcelWriter('geovindu.xlsx') as writer:     dataf.to_excel(writer, sheet_name='2023年保险费用详情', index=False)     dataf2.to_excel(writer, sheet_name='保险统计', index=False)     staicmonth.to_excel(writer, sheet_name='月份统计', index=False)