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@@ -9,6 +9,7 @@ class DiagDataMerge():
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df_Diag_Cal_finish = pd.DataFrame(columns=['start_time', 'end_time', 'product_id', 'code', 'level', 'info','advice','Batpos'])
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df_Diag_Cal_unfinish = pd.DataFrame(columns=['start_time', 'end_time', 'product_id', 'code', 'level', 'info','advice','Batpos'])
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+ print('处理前',df_Diag_Cal_unfinish)
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if not df_Diag_Batdiag_update.empty:
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#------------------------------合并两者故障，并将同一sn号下的车辆故障放一起----------------------------------------------
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df_Diag_Cal_finish = df_Diag_Batdiag_update[df_Diag_Batdiag_update['end_time'] != '0000-00-00 00:00:00']
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@@ -16,11 +17,17 @@ class DiagDataMerge():
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df_Diag_Cal_finish['Batpos'] = [1]*len(df_Diag_Cal_finish)
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if len(df_OprtnSta):
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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
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- df_Diag_Cal_unfinish['Batpos'] = [1]*len(df_Diag_Cal_unfinish)
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+ if df_Diag_Cal_unfinish['level'].max()>3:
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+ if df_OprtnSta.loc[0,'status'] ==3:
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+ df_Diag_Cal_unfinish['Batpos'] = [1]*len(df_Diag_Cal_unfinish)
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+ else:
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+ df_Diag_Cal_unfinish['Batpos'] = [0]*len(df_Diag_Cal_unfinish)
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+ else:
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+ df_Diag_Cal_unfinish['Batpos'] = [1]*len(df_Diag_Cal_unfinish)
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else:
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df_Diag_Cal_unfinish['Batpos'] = [0]*len(df_Diag_Cal_unfinish)
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-
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+ print('处理后',df_Diag_Cal_unfinish)
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df_Diag_Cal_Update=pd.concat([df_Diag_Cal_finish,df_Diag_Cal_unfinish])
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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
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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
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