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@@ -53,25 +53,25 @@ def cell_platd_sorvol_test():
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[df_diag_sor_add, df_diag_vol_add, df_diag_sorvol_add] = Diag_sorvol_temp.volsor_cal()
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if not df_Diag_lipltd_add.empty:
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df_Diag_lipltd_temp = df_Diag_lipltd.append(df_Diag_lipltd_add)
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- df_Diag_lipltd = df_Diag_lipltd_temp.drop_duplicates(subset = ['sn','time'], keep = 'first', inplace = True)
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+ df_Diag_lipltd = df_Diag_lipltd_temp.drop_duplicates(subset = ['sn','time'], keep = 'first', inplace = False)
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df_Diag_lipltd.reset_index(drop = True)
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df_Diag_lipltd.sort_values(by = ['sn'], axis = 0, ascending=True,inplace=True)#对故障信息按照时间进行排序
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df_Diag_lipltd.to_csv(r'D:\Work\Code_write\data_analyze_platform\USER\lzx\01算法开发\02析锂检测\01下载数据\格林美-力信7255\SNnums_6040_liplated_sn.csv',index=False,encoding='GB18030')
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if not df_diag_sor_add.empty:
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- df_diag_sor = df_diag_sor.append(df_diag_sor_add)
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- df_diag_sor = df_diag_sor.drop_duplicates(subset = ['sn','time'], keep = 'first', inplace = False)
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+ df_diag_sor_temp = df_diag_sor.append(df_diag_sor_add)
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+ df_diag_sor = df_diag_sor_temp.drop_duplicates(subset = ['sn','time'], keep = 'first', inplace = False)
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df_diag_sor.reset_index(drop = True)
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df_diag_sor.sort_values(by = ['sn'], axis = 0, ascending=True,inplace=True)#对故障信息按照时间进行排序
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df_diag_sor.to_csv(r'D:\Work\Code_write\data_analyze_platform\USER\lzx\01算法开发\05内阻及电压估计\02算法检测\判断结果\内阻偏离.csv',index=False,encoding='GB18030')
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if not df_diag_vol_add.empty:
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- df_diag_vol = df_diag_vol.append(df_diag_vol_add)
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- df_diag_vol = df_diag_vol.drop_duplicates(subset = ['sn','time'], keep = 'first', inplace = False)
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+ df_diag_vol_temp = df_diag_vol.append(df_diag_vol_add)
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+ df_diag_vol = df_diag_vol_temp.drop_duplicates(subset = ['sn','time'], keep = 'first', inplace = False)
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df_diag_vol.reset_index(drop = True)
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df_diag_vol.sort_values(by = ['sn'], axis = 0, ascending=True,inplace=True)#对故障信息按照时间进行排序
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df_diag_vol.to_csv(r'D:\Work\Code_write\data_analyze_platform\USER\lzx\01算法开发\05内阻及电压估计\02算法检测\判断结果\电压偏离.csv',index=False,encoding='GB18030')
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if not df_diag_sorvol_add.empty:
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- df_diag_volsor = df_diag_volsor.append(df_diag_sorvol_add)
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- df_diag_volsor = df_diag_volsor.drop_duplicates(subset = ['sn','time'], keep = 'first', inplace = False)
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+ df_diag_volsor_temp = df_diag_volsor.append(df_diag_sorvol_add)
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+ df_diag_volsor = df_diag_volsor_temp.drop_duplicates(subset = ['sn','time'], keep = 'first', inplace = False)
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df_diag_volsor.reset_index(drop = True)
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df_diag_volsor.sort_values(by = ['sn'], axis = 0, ascending=True,inplace=True)#对故障信息按照时间进行排序
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df_diag_volsor.to_csv(r'D:\Work\Code_write\data_analyze_platform\USER\lzx\01算法开发\05内阻及电压估计\02算法检测\判断结果\电压内阻偏离.csv',index=False,encoding='GB18030')
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