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@@ -336,7 +336,7 @@ def change_new(df_sts_chrg,chrg_last):
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if len(chrg_last)>0:
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time_last=chrg_last['time_end']
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time_first=df_sts_chrg.loc[0,'time_st']
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- time_last=datetime.datetime.strptime(time_last,'%Y-%m-%d %H:%M:%S')
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+ time_last=datetime.datetime.strptime(str(time_last),'%Y-%m-%d %H:%M:%S')
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if (chrg_last['status']==df_sts_chrg.loc[0,'status']) & ((time_first-time_last).total_seconds()/60<10) & \
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(round(chrg_last['gps_lat'],2)==round(df_sts_chrg.loc[0,'gps_lat'],2)) & \
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(round(chrg_last['gps_lon'],2)==round(df_sts_chrg.loc[0,'gps_lon'],2)) :
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@@ -349,8 +349,6 @@ def change_new(df_sts_chrg,chrg_last):
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chrg_last['temp_min']=np.min([df_sts_chrg.loc[0,'temp_min'],chrg_last['temp_min']])
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chrg_last['temp_incr']=df_sts_chrg.loc[0,'temp_incr']+chrg_last['temp_incr']
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chrg_last['temp_mean']=round(np.mean([df_sts_chrg.loc[0,'temp_mean'],chrg_last['temp_mean']]),1)
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- #chrg_last['temp_end_max']=df_sts_chrg.loc[0,'temp_end_max']
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- #chrg_last['temp_end_min']=df_sts_chrg.loc[0,'temp_end_min']
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chrg_last['temp_end_mean']=df_sts_chrg.loc[0,'temp_end_mean']
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chrg_last['difftem_max']=np.max([df_sts_chrg.loc[0,'difftem_max'],chrg_last['difftem_max']])
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delta_soc=chrg_last['soc_end']-chrg_last['soc_st']
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@@ -425,7 +423,13 @@ def mkdf_chrg(chrg,data_new,param):
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df_sts_chrg=df_sts_chrg.append(df_sts_chrg_temp)
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return df_sts_chrg
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-def pro_output(df_merge,sn,gpscity,chrg_last):
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+def pro_output(df_merge,sn,gpscity,df_diag_ram_sn):
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+ chrg_last=pd.Series()
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+ if len(df_diag_ram_sn)>0:
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+ df_diag_ram_sn['time_end']=list(map(lambda x: datetime.datetime.strptime(str(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.reset_index(inplace=True,drop=True)
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+ chrg_last=df_diag_ram_sn.iloc[-1]
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new=pd.DataFrame()
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change=pd.DataFrame()
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if len(df_merge)>0:
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