data_analyze_platform/LIB/MIDDLE/SaftyCenter/DataDiag_Static/DiagDataMerge.py

import pandas as pd
import datacompy


class DiagDataMerge():
    def DetaMerge(df_Diag_Ram_sn,df_Diag_Batdiag_update,df_OprtnSta,df_Diag_Ram_sn_else):
        df_Diag_Ram_add = pd.DataFrame()
        df_Diag_Ram_Update_change = pd.DataFrame()
        
        df_Diag_Cal_finish = pd.DataFrame(columns=['start_time', 'end_time', 'product_id', 'code', 'level', 'info','advice','Batpos'])
        df_Diag_Cal_unfinish = pd.DataFrame(columns=['start_time', 'end_time', 'product_id', 'code', 'level', 'info','advice','Batpos'])
        print('处理前',df_Diag_Cal_unfinish)
        if not df_Diag_Batdiag_update.empty:
            #------------------------------合并两者故障，并将同一sn号下的车辆故障放一起----------------------------------------------
            df_Diag_Cal_finish = df_Diag_Batdiag_update[df_Diag_Batdiag_update['end_time'] != '0000-00-00 00:00:00']
            df_Diag_Cal_unfinish = df_Diag_Batdiag_update[df_Diag_Batdiag_update['end_time'] == '0000-00-00 00:00:00']
            df_Diag_Cal_finish['Batpos'] = [1]*len(df_Diag_Cal_finish)
            if len(df_OprtnSta):
                if df_OprtnSta.loc[0,'status'] !=1:#0禁用 1正常 2故障 3返修 4 损毁 5丢失已赔偿，6丢失未赔偿
                    if df_Diag_Cal_unfinish['level'].max()>3:
                        if df_OprtnSta.loc[0,'status'] ==3:
                            df_Diag_Cal_unfinish['Batpos'] = [1]*len(df_Diag_Cal_unfinish)
                        else:
                            df_Diag_Cal_unfinish['Batpos'] = [0]*len(df_Diag_Cal_unfinish)
                    else:
                        df_Diag_Cal_unfinish['Batpos'] = [1]*len(df_Diag_Cal_unfinish)
                else:
                    df_Diag_Cal_unfinish['Batpos'] = [0]*len(df_Diag_Cal_unfinish)
                    
        print('处理后',df_Diag_Cal_unfinish)
        df_Diag_Cal_Update=pd.concat([df_Diag_Cal_finish,df_Diag_Cal_unfinish])    
        df_Diag_Ram_add = pd.concat([df_Diag_Cal_Update,df_Diag_Ram_sn,df_Diag_Ram_sn]).drop_duplicates(subset=['start_time','code'],keep=False)#此次判断中新增故障
        df_Diag_Ram_Update_old = pd.concat([df_Diag_Cal_Update,df_Diag_Ram_add,df_Diag_Ram_add]).drop_duplicates(subset=['start_time','code'],keep=False)#此次判断中新增故障
        df_Diag_Ram_Update_change = pd.concat([df_Diag_Ram_Update_old,df_Diag_Ram_sn,df_Diag_Ram_sn]).drop_duplicates(subset=['start_time','code','Batpos'],keep=False)#此次判断中新增故障
        # df_Diag_Ram = pd.concat([df_Diag_Ram_sn_else,df_Diag_Cal_unfinish])    
        return df_Diag_Ram_add,df_Diag_Ram_Update_change