forked from sundaygeek/bigdata-cloud-analysis
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cloud_in_oos.py
executable file
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/
cloud_in_oos.py
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#encoding=utf-8
import pandas as pd
import xlsxwriter
import os
from pandas import ExcelWriter
from util import main_function,plot_trend
def __readCsvOneFile(inCsvFileName):
try:
callFailData=pd.read_csv(inCsvFileName, dtype={'掉网时长':object,'呼叫对方号码':object,'运营商': object,
'imei': object,'起呼位置码': object,
'起呼基站编号': object})
return callFailData
except:
print('read error ... ')
return None
def __readCsvFile(inCsvFileName):
if(os.path.isfile(inCsvFileName)):
print('input is a file')
callFailData=__readCsvOneFile(inCsvFileName)
elif(os.path.isdir(inCsvFileName)):
print('input is a isdir')
callFailDataList=[]
absPath=os.path.abspath(inCsvFileName)
for li in os.listdir(absPath):
oldName=os.path.join(absPath,li)
print(oldName)
callFailData1=__readCsvOneFile(oldName)
if callFailData1 is not None:
callFailDataList.append(callFailData1)
callFailData = callFailDataList[0]
for i in range(1,len(callFailDataList)):
callFailData = callFailData.append(callFailDataList[i], ignore_index=True)
return callFailData
def __clean_data_all_data(callFailData):
callFailData=callFailData.fillna('null')
print('-----------------------------'+str(callFailData.shape[0]))
shape=callFailData.shape[0]
callFailData['PLMN_LAC1_CID1']=callFailData['运营商'].str.cat(callFailData['起呼位置码'],sep='/').str.cat(callFailData['起呼基站编号'],sep='/')
callFailData['PLMN_CS1']=callFailData['运营商'].str.cat(callFailData['起呼电话网络'],sep='/')
callFailData['PLMN_PS1']=callFailData['运营商'].str.cat(callFailData['开始数据网络'],sep='/')
callFailData['CS_NW']=callFailData['起呼电话网络'].str.cat(callFailData['结束电话网络'],sep='/')
callFailData['PS_NW']=callFailData['开始数据网络'].str.cat(callFailData['结束数据网络'],sep='/')
callFailData['CS_PS_NW']=callFailData['CS_NW'].str.cat(callFailData['PS_NW'],sep='/')
callFailData['PLMN_CS_NW'] = callFailData['运营商'].str.cat(callFailData['CS_NW'], sep='/')
callFailData['PLMN_PS_NW'] = callFailData['运营商'].str.cat(callFailData['PS_NW'], sep='/')
callFailData['PLMN_CS_PS_NW'] = callFailData['运营商'].str.cat(callFailData['CS_PS_NW'], sep='/')
callFailData['结束网络']=callFailData['结束电话网络'].str.cat(callFailData['结束数据网络'],sep='/')
#运营商
callFailData=callFailData[callFailData['运营商']!='99901']
callFailData=callFailData[callFailData['运营商']!='00000']
callFailData=callFailData[callFailData['运营商']!='00101']
callFailData=callFailData[callFailData['运营商']!='123456']
callFailData=callFailData[callFailData['运营商']!='null']
#
callFailData=callFailData[callFailData['起呼位置码']!=0]
callFailData=callFailData[callFailData['起呼位置码']!=1]
callFailData=callFailData[callFailData['起呼位置码']!='0']
callFailData=callFailData[callFailData['起呼位置码']!='1']
#
callFailData=callFailData[callFailData['起呼基站编号']!=0]
callFailData=callFailData[callFailData['起呼基站编号']!=1]
callFailData=callFailData[callFailData['起呼基站编号']!='0']
callFailData=callFailData[callFailData['起呼基站编号']!='1']
callFailData=callFailData[callFailData['起呼电话网络']!='Unknown']
callFailData=callFailData[callFailData['开始数据网络']!='Unknown']
rowLength_before=callFailData.shape[0]
callFailData['开始电话网络']=callFailData['起呼电话网络']
callFailData['开始位置码']=callFailData['起呼位置码']
callFailData['开始基站编号']=callFailData['起呼基站编号']
callFailData['省直辖市']=callFailData['省/直辖市']
callFailData['县区']=callFailData['县/区']
callFailData['市1']=callFailData['省直辖市'].str.cat(callFailData['市'],sep='/')
callFailData['县区1']=callFailData['市1'].str.cat(callFailData['县区'],sep='/')
callFailData['cell_add1']=callFailData['PLMN_LAC1_CID1'].str.cat(callFailData['详细地址'],sep='/')
callFailData['发生时间t']=pd.to_datetime(callFailData['发生时间'],infer_datetime_format=True)
callFailData['发生时间h']=callFailData['发生时间t'].apply(__getHour)
callFailData.loc[callFailData['保留字段一']=='0','保留字段一']='15'
callFailData.loc[callFailData['保留字段一']=='1','保留字段一']='3'
callFailData['掉网时长']=callFailData['保留字段一']
callFailData.loc[callFailData['出现异常的卡']==0,'出现异常的卡']='卡1'
callFailData.loc[callFailData['出现异常的卡']==1,'出现异常的卡']='卡2'
callFailData['机型'] = callFailData['外部机型']
callFailData['失败原因1']=callFailData['log信息']
callFailData['失败类型']=callFailData['失败原因']
callFailData.loc[callFailData['失败原因1']==-1,'失败原因1']='null'
callFailData.loc[callFailData['失败原因1']=='-1','失败原因1']='null'
callFailData.loc[callFailData['失败类型']==-1,'失败类型']='null'
callFailData.loc[callFailData['失败类型']=='-1','失败类型']='null'
callFailData['信号强度']=callFailData['呼叫对方号码'].apply(__getRSRP)
callFailData['失败原因2'] = callFailData['失败类型'].str.cat(callFailData['失败原因1'], sep='/')
callFailData['失败时长'] = callFailData['失败原因2'].str.cat(callFailData['掉网时长'], sep='/')
callFailData['失败信号'] = callFailData['失败原因2'].str.cat(callFailData['起呼电话网络'], sep='/').str.cat(callFailData['开始数据网络'], sep='/').str.cat(callFailData['信号强度'], sep='/')
rowLength_after=callFailData.shape[0]
print('数据量大小为：'+str(rowLength_before)+'/'+str(rowLength_after))
#callFailData = callFailData[callFailData['机型'] == 'PD1616']
callFailData=callFailData.drop(['外部机型','内部机型','emmcid','地区码','上报时间','异常进程名','进程版本名',
'进程版本号','异常进程包名','软件系统类型','异常类型','isim支持情况',
'MBN版本信息','VOLTE配置信息','保留字段一','保留字段二','呼叫对方号码',
'异常次数','日志路径','log信息','省/直辖市','县/区','发生时间','市',
'县区','发生时间t','起呼位置码','结束位置码','起呼基站编号','结束基站编号',
'起呼电话网络','开始数据网络','结束电话网络','结束数据网络','发生时间h','市1','县区1',
'cell_add1','开始位置码','开始基站编号','国家','呼入呼出','起呼电话网络','开始数据网络',
'是否volte','PLMN_CS1','PLMN_PS1','开始电话网络','失败原因',
],axis=1)
return callFailData,callFailData,shape
def __getRSRP(name):
name=str(name)
returnName = name.strip()
rsrp_list = []
returnValue = 0
if(name=='-1' or name=='null'):
returnValue = str(-1)
else:
rsrp_list = returnName.split(',')
min = 0
for i in rsrp_list[:-2]:
temp = eval(i)
if(min > temp):
min = temp
returnValue = int(min / 5) * 5
return str(returnValue)
def __do_merchant(x,y):
if(x=='Unknown' and y!='Unknown'):
return('CS掉网')
elif(x!='Unknown' and y=='Unknown'):
return('PS掉网')
elif(x=='Unknown' and y=='Unknown'):
return('CSPS掉网')
else:
return('null')
def __getHour(name):
returnName=name.to_pydatetime().hour
return returnName
def __read_one_csv_file(inCsvFileName):
try:
callFailData=pd.read_csv(inCsvFileName,
dtype={'保留字段一':object,'出现异常的卡':object,'运营商': object,
'imei': object,'起呼位置码': object,
'起呼基站编号': object,'结束位置码': object,
'结束基站编号': object})
#print(callFailData.columns)
#print(callFailData.shape)
return callFailData
except:
return None
def __read_csv_directory(inCsvFileName):
callFailDataList=[]
absPath=os.path.abspath(inCsvFileName)
print(absPath)
for li in os.listdir(absPath):
print(li)
oldName=os.path.join(absPath,li)
callFailData1=__read_one_csv_file(oldName)
if callFailData1 is not None:
callFailDataList.append(callFailData1)
callFailData = callFailDataList[0]
for i in range(1,len(callFailDataList)):
callFailData = callFailData.append(callFailDataList[i], ignore_index=True)
print(callFailData.shape)
return callFailData
def __process_zhejiang_IMEI(callFailData,path,file_pre,cs_ps):
model_list_fp=open(os.path.join('.','config','云诊断内销浙江统计机型列表.txt'),'r')
modelList=[]
for model in model_list_fp.readlines():
modelList.append(model.strip())
xls_fileName=os.path.join(path,file_pre+'_数据分析结果_浙江IMEI'+cs_ps+'.xls')
workbook = xlsxwriter.Workbook(xls_fileName)
#---对每一个型号进行过滤和对比
#如果包含在写入excel表格
list_result=[]
for model in modelList:
model0=model.split('_')[0]
model1=model.split('_')[1]
worksheet = workbook.add_worksheet(model)
worksheet.set_column('A:A',20)
before=str(callFailData.shape[0])
callFailData_after=callFailData[callFailData['外部机型']==model0]
after=str(callFailData_after.shape[0])
print('开始过滤'+model+'...'+after+'/'+before)
#获取dataframe中的所有IMEI数据
imeiList_a=[]
for imei in callFailData_after['imei'].tolist():
imeiList_a.append(str(imei).strip())
#获取文件中浙江的IMEI列表
imeiList_b=[]
fileName=os.path.join('.','zhejiang_imei',model1+'.txt')
imeiFile_fp=open(fileName,'r')
imei_zhejiang=imeiFile_fp.readlines()
for imei in imei_zhejiang:
imeiList_b.append(imei.strip())
#获得浙江IMEI列表和dataframe IMEI中的交集
IMEI_intersection=list(set(imeiList_a).intersection(set(imeiList_b)))
#print('a='+str(len(imeiList_a))+',b='+str(len(imeiList_b))+',intersection='+str(len(IMEI_intersection)))
#按照dataframe的数量排序，获取浙江输出到excel
callFailData_IMEI=callFailData_after['imei'].value_counts()
allIMEI=callFailData_IMEI.index.tolist()
row_i=0
for imei_i in range(len(allIMEI)):
for imei_filtered in IMEI_intersection:
if(imei_filtered==allIMEI[imei_i]):
worksheet.write(row_i,0,imei_filtered)
worksheet.write(row_i,1,callFailData_IMEI.values[imei_i])
list_result.append((imei_filtered,callFailData_IMEI.values[imei_i]),)
row_i += 1
#---对所有过滤出来的浙江IMEI计算Top
print('ouput all...')
worksheet = workbook.add_worksheet('all')
worksheet.set_column('A:A',20)
mylist=sorted(list_result,key=lambda t:t[1],reverse=True)
for i in range(len(mylist)):
worksheet.write(i,0,mylist[i][0])
worksheet.write(i,1,mylist[i][1])
workbook.close()
length_mylist=0
if(len(mylist) < 1):
callFailData_internal = pd.DataFrame(columns=callFailData.columns)
else:
if(len(mylist) < 10):
length_mylist=len(mylist)
else:
length_mylist=10
callFailDataList=[]
for i in range(length_mylist):
callFailData_internal=callFailData[callFailData['imei']==mylist[i][0]]
callFailDataList.append(callFailData_internal)
callFailData_internal = pd.DataFrame(columns=callFailData.columns)
for i in range(1,len(callFailDataList)):
callFailData_internal = callFailData_internal.append(callFailDataList[i], ignore_index=True)
xls_fileName1=os.path.join(path,file_pre+'_数据分析结果_浙江IMEI详细信息'+cs_ps+'.xlsx')
writer = ExcelWriter(xls_fileName1)
callFailData_internal.to_excel(writer,'data')
writer.save()
def __process_trial_IMEI(callFailData,path,inCsvFileName_head,cs_ps):
modelList=[]
for model in open(os.path.join('.','config','云诊断内销掉话试用机列表.txt'),'r').readlines():
modelList.append(model.strip())
xls_fileName=os.path.join(path,inCsvFileName_head+'_数据分析结果_试用机IMEI'+cs_ps+'.xls')
workbook = xlsxwriter.Workbook(xls_fileName)
xls_fileName1=os.path.join(path,inCsvFileName_head+'_数据分析结果_试用机IMEI详细信息'+cs_ps+'.xlsx')
writer = ExcelWriter(xls_fileName1)
#---对每一个试用机机型进行过滤和比对
for model in modelList:
model0=model.split('_')[0]
model1=model.split('_')[1]
worksheet = workbook.add_worksheet(model)
before=str(callFailData.shape[0])
private_callFailData=callFailData[callFailData['外部机型']==model0]
after=str(private_callFailData.shape[0])
print('开始过滤'+model+'...'+after+'/'+before)
imeiList_a=[]
for imei in private_callFailData['imei'].tolist():
imeiList_a.append(str(imei).strip())
fileName=os.path.join('.','trial_imei',model1+'.txt')
imeiFile_fp=open(fileName,'r')
imeiList_b=[]
for imei in imeiFile_fp.readlines():
imeiList_b.append(imei.split()[0].strip())
imeiList_b.append(imei.split()[1].strip())
IMEI_intersection=list(set(imeiList_a).intersection(set(imeiList_b)))
print('a='+str(len(imeiList_a))+',b='+str(len(imeiList_b))+'intersection='+str(len(IMEI_intersection)))
private_callFailData1=pd.DataFrame(columns=callFailData.columns)
for imei_i in range(len(IMEI_intersection)):
worksheet.write(imei_i,0,IMEI_intersection[imei_i])
private_callFailData1=private_callFailData1.append(private_callFailData[callFailData['imei']==IMEI_intersection[imei_i]])
private_callFailData1.to_excel(writer,model)
writer.save()
def cloud_in_oos_main(path_raw_data,path_result):
main_function('云诊断内销掉网', path_raw_data, path_result, __read_one_csv_file, __read_csv_directory,
__clean_data_all_data)
def cloud_in_oos_plot_trend(path_raw_data,path_result):
sheet_name_list=['SIM卡', '失败原因', '呼入或呼出', '运营商', '电话网络', '发生时间h', '机型', '系统版本', 'PLMN_CS']
trend_dics_list={}
trend_dics_list['出现异常的卡']=['卡1','卡2']
trend_dics_list['系统版本']=['PD1616B_A_1.6.18', 'PD1616B_A_1.7.1', 'PD1616B_A_1.7.7', 'PD1616B_A_1.7.8', 'PD1616B_A_1.7.10', 'PD1616B_A_1.7.13', 'PD1616B_A_1.8.5', 'PD1616B_A_1.8.9']
trend_dics_list['运营商']=['46000','46001','46011','46003']
trend_dics_list['机型']=['PD1635','PD1624','PD1616B','PD1619','PD1610','PD1616']
trend_dics_list['CS_NW']=['GSM/Unknown','LTE/Unknown','UMTS/Unknown','1xRTT/Unknown',
'TD-SCDMA/Unknown','CDMA-IS95A/Unknown']
trend_dics_list['PS_NW']=['EDGE/Unknown','LTE/Unknown','HSPA/Unknown','HSDPA/Unknown',
'GPRS/Unknown','UMTS/Unknown','HSPAP/Unknown','LTE_CA/Unknown']
trend_dics_list['省直辖市']=['广东省','河南省','甘肃省','江苏省','河北省','山西省','浙江省','新疆维吾尔自治区',
'广西壮族自治区','安徽省','山东省','福建省','湖南省','贵州省','陕西省','云南省',
'黑龙江省','四川省','吉林省','辽宁省','湖北省','内蒙古自治区','宁夏回族自治区',
'北京市','上海市','江西省','重庆市','青海省','海南省','天津市','西藏自治区']
trend_dics_list['掉网时长']=['15','3']
trend_dics_list['失败类型'] = ['CS', 'PS', 'CS_PS']
trend_dics_list['失败原因1']=['0 Unspecified_failure',
'21 REJECT_CAUSE_Synch_failure',
'15 REJECT_CAUSE_No_suitable_cells_in_tracking_area',
'13 REJECT_CAUSE_Roaming_not_allowed_in_this_tracking_area',
'7 REJECT_CAUSE_EPS_services_not_allowed',
'17 REJECT_CAUSE_Network_failure',
'11 REJECT_CAUSE_PLMN_not_allowed']
trend_dics_list['移除正常cause之后大小'] = ['移除正常cause之后大小']
plot_trend('云诊断内销掉网', path_raw_data, path_result, trend_dics_list)
if __name__ == '__main__':
path=os.path.abspath('D:/tools/pycharm_projects/bigdata_analysis/cloud_in_oos_raw_data/cloud_in_oos_raw_data_weeks/test')
cloud_in_oos_main(path, path)