{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import numpy as np\n",
    "import datetime\n",
    "import time, datetime\n",
    "import matplotlib.pyplot as plt\n",
    "\n",
    "data = pd.read_csv(r'D:\\Work\\Code_write\\data_analyze_platform\\USER\\lzx\\03骑享\\01数据处理\\thermal_runaway.csv',encoding='gbk')\n",
    "#----------------------------------------筛选充电后静置数据------------------------------------------------------------\n",
    "chrgr_rest_data_temp = data.loc[(data['充电状态'] == 0) & (data['SOC[%]'] > 95) & (data['总电流[A]'] < 0.1)]#接近慢充后静置数据\n",
    "chrgr_rest_data = chrgr_rest_data_temp.reset_index(drop=True)\n",
    "temp_rest_time = chrgr_rest_data['时间戳'].reset_index(drop=True)\n",
    "rest_time = pd.to_datetime(temp_rest_time)\n",
    "# rest_chrg_time = datetime(rest_time)\n",
    "# delta_time = np.diff(rest_chrg_time)\n",
    "delta_time = (np.diff(rest_time)/pd.Timedelta(1, 'min'))#计算时间差的分钟数\n",
    "pos = np.where(delta_time > 30)\n",
    "pos_ful_tem = np.insert(pos, 0, 0)\n",
    "pos_len = len(pos_ful_tem)\n",
    "data_len = len(rest_time)\n",
    "pos_ful = np.insert(pos_ful_tem, pos_len, data_len-1)\n",
    "splice_num = []\n",
    "for item in range(0,len(pos_ful)-1):\n",
    "    splice_num.extend(item*np.ones(pos_ful[item +1]-pos_ful[item]))\n",
    "splice_num = np.insert(splice_num, 0, 0)\n",
    "chrgr_rest_data['chrgr_rest'] = splice_num\n",
    "print(chrgr_rest_data)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {},
   "outputs": [
    {
     "ename": "KeyError",
     "evalue": "0",
     "output_type": "error",
     "traceback": [
      "\u001b[1;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[1;31mKeyError\u001b[0m                                  Traceback (most recent call last)",
      "\u001b[1;32mC:\\ProgramData\\Anaconda3\\lib\\site-packages\\pandas\\core\\indexes\\base.py\u001b[0m in \u001b[0;36mget_loc\u001b[1;34m(self, key, method, tolerance)\u001b[0m\n\u001b[0;32m   3079\u001b[0m             \u001b[1;32mtry\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m-> 3080\u001b[1;33m                 \u001b[1;32mreturn\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m_engine\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mget_loc\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mcasted_key\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m   3081\u001b[0m             \u001b[1;32mexcept\u001b[0m \u001b[0mKeyError\u001b[0m \u001b[1;32mas\u001b[0m \u001b[0merr\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;32mpandas\\_libs\\index.pyx\u001b[0m in \u001b[0;36mpandas._libs.index.IndexEngine.get_loc\u001b[1;34m()\u001b[0m\n",
      "\u001b[1;32mpandas\\_libs\\index.pyx\u001b[0m in \u001b[0;36mpandas._libs.index.IndexEngine.get_loc\u001b[1;34m()\u001b[0m\n",
      "\u001b[1;32mpandas\\_libs\\hashtable_class_helper.pxi\u001b[0m in \u001b[0;36mpandas._libs.hashtable.Int64HashTable.get_item\u001b[1;34m()\u001b[0m\n",
      "\u001b[1;32mpandas\\_libs\\hashtable_class_helper.pxi\u001b[0m in \u001b[0;36mpandas._libs.hashtable.Int64HashTable.get_item\u001b[1;34m()\u001b[0m\n",
      "\u001b[1;31mKeyError\u001b[0m: 0",
      "\nThe above exception was the direct cause of the following exception:\n",
      "\u001b[1;31mKeyError\u001b[0m                                  Traceback (most recent call last)",
      "\u001b[1;32m<ipython-input-36-0e36db861cd2>\u001b[0m in \u001b[0;36m<module>\u001b[1;34m\u001b[0m\n\u001b[0;32m     17\u001b[0m         \u001b[0mplt\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mrcParams\u001b[0m\u001b[1;33m[\u001b[0m\u001b[1;34m'font.family'\u001b[0m\u001b[1;33m]\u001b[0m\u001b[1;33m=\u001b[0m\u001b[1;33m[\u001b[0m\u001b[1;34m'SimHei'\u001b[0m\u001b[1;33m]\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m     18\u001b[0m         \u001b[0mplt\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mlegend\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m---> 19\u001b[1;33m         \u001b[0mtitle\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mdf_test_rest_time\u001b[0m\u001b[1;33m[\u001b[0m\u001b[1;36m0\u001b[0m\u001b[1;33m]\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mstrftime\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;34m'%y-%m-%d'\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;31m#df_fig['device_id'][0] + '-' +\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m     20\u001b[0m         \u001b[0mprint\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mtype\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mtitle\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m     21\u001b[0m         \u001b[0mplt\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mxlabel\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;34m'时间'\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mfontsize\u001b[0m\u001b[1;33m=\u001b[0m\u001b[1;36m14\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;32mC:\\ProgramData\\Anaconda3\\lib\\site-packages\\pandas\\core\\series.py\u001b[0m in \u001b[0;36m__getitem__\u001b[1;34m(self, key)\u001b[0m\n\u001b[0;32m    851\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    852\u001b[0m         \u001b[1;32melif\u001b[0m \u001b[0mkey_is_scalar\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m--> 853\u001b[1;33m             \u001b[1;32mreturn\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m_get_value\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mkey\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m    854\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    855\u001b[0m         \u001b[1;32mif\u001b[0m \u001b[0mis_hashable\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mkey\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;32mC:\\ProgramData\\Anaconda3\\lib\\site-packages\\pandas\\core\\series.py\u001b[0m in \u001b[0;36m_get_value\u001b[1;34m(self, label, takeable)\u001b[0m\n\u001b[0;32m    959\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    960\u001b[0m         \u001b[1;31m# Similar to Index.get_value, but we do not fall back to positional\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m--> 961\u001b[1;33m         \u001b[0mloc\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mindex\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mget_loc\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mlabel\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m    962\u001b[0m         \u001b[1;32mreturn\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mindex\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m_get_values_for_loc\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mself\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mloc\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mlabel\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    963\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;32mC:\\ProgramData\\Anaconda3\\lib\\site-packages\\pandas\\core\\indexes\\base.py\u001b[0m in \u001b[0;36mget_loc\u001b[1;34m(self, key, method, tolerance)\u001b[0m\n\u001b[0;32m   3080\u001b[0m                 \u001b[1;32mreturn\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m_engine\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mget_loc\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mcasted_key\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m   3081\u001b[0m             \u001b[1;32mexcept\u001b[0m \u001b[0mKeyError\u001b[0m \u001b[1;32mas\u001b[0m \u001b[0merr\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m-> 3082\u001b[1;33m                 \u001b[1;32mraise\u001b[0m \u001b[0mKeyError\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mkey\u001b[0m\u001b[1;33m)\u001b[0m \u001b[1;32mfrom\u001b[0m \u001b[0merr\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m   3083\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m   3084\u001b[0m         \u001b[1;32mif\u001b[0m \u001b[0mtolerance\u001b[0m \u001b[1;32mis\u001b[0m \u001b[1;32mnot\u001b[0m \u001b[1;32mNone\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;31mKeyError\u001b[0m: 0"
     ]
    },
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
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     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "#---------------------------判断数据点数大于30的数据段,对电压微分并画图--------------------------------------------\n",
    "import matplotlib.pyplot as plt\n",
    "cellvolt_name=['单体电压'+str(x) for x in range(1,21)]\n",
    "chrgr_rest_check_data = chrgr_rest_data.drop(['GSM信号','故障等级','故障代码','开关状态','单体压差','绝缘电阻','总电流[A]','总电压[V]','充电状态','单体压差','SOC[%]'],axis=1,inplace=False)\n",
    "chrgr_rest_check_data.fillna(value=0)\n",
    "df_rest_volt_diffdt = pd.DataFrame()\n",
    "k = 0\n",
    "for j in range(0,2):#len(pos_ful)-1\n",
    "    df_test_rest_data = chrgr_rest_check_data.loc[chrgr_rest_check_data['chrgr_rest'] == j]\n",
    "    if len(df_test_rest_data) > 25:\n",
    "        df_test_rest_time = pd.to_datetime(df_test_rest_data['时间戳'])\n",
    "        df_test_rest_time = df_test_rest_time.reset_index(drop=True)\n",
    "        df_test_rest_volt = df_test_rest_data[cellvolt_name]\n",
    "        df_fig = df_test_rest_volt\n",
    "        length = len(df_fig)\n",
    "        plt.plot(df_test_rest_time, df_test_rest_volt['单体电压1'],linewidth = 2, linestyle = '-', marker = 's',label='单体电压1')\n",
    "        plt.rcParams['font.family']=['SimHei']\n",
    "        plt.legend()\n",
    "        title = df_test_rest_time[0].strftime('%y-%m-%d')#df_fig['device_id'][0] + '-' + \n",
    "        print(type(title))\n",
    "        plt.xlabel('时间', fontsize=14)\n",
    "        plt.ylabel('电压的时间微分(mv/min)', fontsize=14)\n",
    "        plt.title(title)\n",
    "# for i in range(0,k):\n",
    "#     fig = plt.figure(figsize=(20,10))\n",
    "#     df_fig = df_rest_volt_diffdt.loc[df_rest_volt_diffdt['chrgr_rest'] == i]\n",
    "#     length = len(df_fig)\n",
    "#     for volt_num in cellvolt_name:\n",
    "#         # plt.scatter([x for x in range(0, length)], df_fig[volt_num][0:length], label=volt_num)\n",
    "#         plt.plot(df_fig['时间戳'], df_fig[volt_num],linewidth = 2, linestyle = '-', marker = 's',label=volt_num)\n",
    "#     plt.rcParams['font.family']=['SimHei']\n",
    "#     plt.legend()\n",
    "#     title = df_fig['时间戳'][0].strftime('%y-%m-%d')#df_fig['device_id'][0] + '-' + \n",
    "#     print(type(title))\n",
    "#     plt.xlabel('时间', fontsize=14)\n",
    "#     plt.ylabel('电压的时间微分(mv/min)', fontsize=14)\n",
    "#     plt.title(title)\n",
    "#     plt.savefig(r'D:\\Work\\Code_write\\data_analyze_platform\\USER\\lzx\\01算法开发\\02析锂检测\\liplated\\算法开发_检测\\\\'+title+'.png', dpi=300)"
   ]
  }
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