{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "1441\n"
     ]
    }
   ],
   "source": [
    "import pandas as pd\n",
    "import numpy as np\n",
    "import os\n",
    "folder_path = \"/home/liuzhongxiao/project/zlwl-algos/USER/liuzhongxiao/SOC_Fct/\" # 设置相对路径\n",
    "csv_files = [file for file in os.listdir(folder_path) if file.endswith('.csv')]\n",
    "# 遍历所有CSV文件并依次读取它们\n",
    "df_data_all = pd.DataFrame()\n",
    "for csv_file in csv_files:\n",
    "    filename = os.path.join(folder_path, csv_file)\n",
    "    df_data = pd.read_csv(filename)\n",
    "    df_data_all = df_data_all.append(df_data)\n",
    "print(len(df_data_all))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "                  sn                 time soc_ori soc_pre soc_error  odo  \\\n",
      "0  LY9139BB1MALBZ799  2022-08-29 01:39:02    [46]  [54.0]     [8.0]    0   \n",
      "1  LY9139BB1MALBZ799  2022-11-17 11:02:13    [46]  [50.1]     [4.1]    0   \n",
      "2  LY9139BB1MALBZ799  2022-01-22 01:52:57    [50]  [44.4]    [-5.6]    0   \n",
      "3  LY9139BB1MALBZ799  2022-06-18 11:10:30    [51]  [45.8]    [-5.2]    0   \n",
      "4  LY9139BB1MALBZ799  2022-02-12 12:45:13    [51]  [47.3]    [-3.7]    0   \n",
      "\n",
      "   method battery_type  soc_errorV  \n",
      "0       1          lfp         8.0  \n",
      "1       1          lfp         4.1  \n",
      "2       1          lfp         5.6  \n",
      "3       1          lfp         5.2  \n",
      "4       1          lfp         3.7  \n"
     ]
    }
   ],
   "source": [
    "print(df_data_all.head(5))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "0    8.0\n",
      "1    4.1\n",
      "2    5.6\n",
      "3    5.2\n",
      "4    3.7\n",
      "Name: soc_errorV, dtype: float64\n"
     ]
    }
   ],
   "source": [
    "df_data_all['soc_errorV'] = df_data_all['soc_error'].apply(lambda x: max(np.abs(eval(x))))\n",
    "df_data_all['soc_errorV'].iloc[0]\n",
    "print(df_data_all['soc_errorV'].iloc[0:5])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [],
   "source": [
    "# df_data_chs = df_data_all[df_data_all['soc_errorV'] > 10]\n",
    "# df_data_chs.reset_index(drop=True, inplace=True)\n",
    "df_data_all.to_csv('./' + 'SOC估计结果汇总V.csv',index=False,encoding='GB18030')"
   ]
  }
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