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@@ -72,7 +72,10 @@ def diag_cal():
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df_diag_ram_sn=df_diag_ram[df_diag_ram['sn']==sn]
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df_diag_ram_sn=df_diag_ram[df_diag_ram['sn']==sn]
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if not df_diag_ram_sn.empty: #该sn相关结果非空
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if not df_diag_ram_sn.empty: #该sn相关结果非空
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df_diag_ram_sn.reset_index(inplace=True,drop=True)
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df_diag_ram_sn.reset_index(inplace=True,drop=True)
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+ df_diag_ram_sn['time_end']=list(map(lambda x: datetime.datetime.strptime(x,'%Y-%m-%d %H:%M:%S'),list(df_diag_ram_sn['time_end'])))
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+ df_diag_ram_sn = df_diag_ram_sn.sort_values(by = 'time_end')
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df_diag_ram_sn=df_diag_ram_sn.iloc[-1]
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df_diag_ram_sn=df_diag_ram_sn.iloc[-1]
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+ time_end =df_diag_ram_sn['time_end']
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df_diag_ram_sn.reset_index(inplace=True,drop=True)
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df_diag_ram_sn.reset_index(inplace=True,drop=True)
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df_diag_new,df_diag_change=pro_output(df_merge,sn,gpscity,df_diag_ram_sn)
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df_diag_new,df_diag_change=pro_output(df_merge,sn,gpscity,df_diag_ram_sn)
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kmeans1 = joblib.load('kmeans1.pkl')
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kmeans1 = joblib.load('kmeans1.pkl')
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@@ -81,7 +84,7 @@ def diag_cal():
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df_diag_new=prediction(df_diag_new,kmeans1,kmeans2,kmeans3)
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df_diag_new=prediction(df_diag_new,kmeans1,kmeans2,kmeans3)
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df_diag_change=prediction(df_diag_change,kmeans1,kmeans2,kmeans3)
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df_diag_change=prediction(df_diag_change,kmeans1,kmeans2,kmeans3)
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if not df_diag_change.empty: #需变更的结果非空
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if not df_diag_change.empty: #需变更的结果非空
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- cursor.execute("DELETE FROM algo_charge_info WHERE time_end = '0000-00-00 00:00:00' and sn='{}'".format(sn))
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+ cursor.execute("DELETE FROM algo_charge_info WHERE time_end = '{}' and sn='{}'".format(time_end,sn))
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mysql.commit()
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mysql.commit()
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df_diag_change.to_sql("algo_charge_info",con=db_res_engine, if_exists="append",index=False)
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df_diag_change.to_sql("algo_charge_info",con=db_res_engine, if_exists="append",index=False)
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