LSTM_feature_adding.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/usr/local/lib/python2.7/dist-packages/sklearn/cross_validation.py:44: DeprecationWarning: This module was deprecated in version 0.18 in favor of the model_selection module into which all the refactored classes and functions are moved. Also note that the interface of the new CV iterators are different from that of this module. This module will be removed in 0.20.\n",
      "  \"This module will be removed in 0.20.\", DeprecationWarning)\n"
     ]
    }
   ],
   "source": [
    "import pandas as pd\n",
    "from pandas import Series,DataFrame\n",
    "import numpy as np\n",
    "import os\n",
    "from sklearn.metrics import mean_squared_error\n",
    "import datetime\n",
    "import tensorflow as tf\n",
    "from tensorflow.contrib import learn\n",
    "from tensorflow.python.ops import rnn, rnn_cell\n",
    "import matplotlib.pyplot as plt\n",
    "import cPickle\n",
    "import gzip\n",
    "%matplotlib inline"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 提取主力合约"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "collapsed": true
   },
   "outputs": [
    {
     "ename": "KeyboardInterrupt",
     "evalue": "",
     "output_type": "error",
     "traceback": [
      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[0;31mKeyboardInterrupt\u001b[0m                         Traceback (most recent call last)",
      "\u001b[0;32m<ipython-input-3-928b747df4f3>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m()\u001b[0m\n\u001b[1;32m     12\u001b[0m         \u001b[0;32mfor\u001b[0m \u001b[0mj\u001b[0m \u001b[0;32min\u001b[0m \u001b[0mrange\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mlen\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mtrain_data\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     13\u001b[0m             \u001b[0;32mif\u001b[0m \u001b[0mnewtime\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0miloc\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0mj\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mmonth\u001b[0m \u001b[0;34m!=\u001b[0m \u001b[0mmain_month\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m---> 14\u001b[0;31m                  \u001b[0mtrain_data\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mdrop\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mj\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0minplace\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mTrue\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;31m# 如果不是主力合约的数据直接删除\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m     15\u001b[0m         \u001b[0mtrain_data\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mto_csv\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mtrainset_main_path\u001b[0m \u001b[0;34m+\u001b[0m \u001b[0mfile_list\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0mi\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0msplit\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m'.'\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;36m0\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m+\u001b[0m \u001b[0;34m'_main'\u001b[0m \u001b[0;34m+\u001b[0m \u001b[0;34m'.csv'\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0msep\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;34m','\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;31m# 将提取的主力合约另存为csv文件\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     16\u001b[0m         \u001b[0mmain_last_time\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mtrain_data\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m'Time'\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0miloc\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m-\u001b[0m\u001b[0;36m10\u001b[0m\u001b[0;34m]\u001b[0m \u001b[0;31m# 取上一个合约最后一个交割日的时间\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m/usr/lib/python2.7/dist-packages/pandas/core/generic.pyc\u001b[0m in \u001b[0;36mdrop\u001b[0;34m(self, labels, axis, level, inplace, errors)\u001b[0m\n\u001b[1;32m   1609\u001b[0m         \u001b[0maxis\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0maxis_\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_get_axis\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0maxis\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0maxis\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   1610\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 1611\u001b[0;31m         \u001b[0;32mif\u001b[0m \u001b[0maxis\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mis_unique\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m   1612\u001b[0m             \u001b[0;32mif\u001b[0m \u001b[0mlevel\u001b[0m \u001b[0;32mis\u001b[0m \u001b[0;32mnot\u001b[0m \u001b[0mNone\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   1613\u001b[0m                 \u001b[0;32mif\u001b[0m \u001b[0;32mnot\u001b[0m \u001b[0misinstance\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0maxis\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mMultiIndex\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32mpandas/src/properties.pyx\u001b[0m in \u001b[0;36mpandas.lib.cache_readonly.__get__ (pandas/lib.c:44341)\u001b[0;34m()\u001b[0m\n",
      "\u001b[0;32m/usr/lib/python2.7/dist-packages/pandas/core/index.pyc\u001b[0m in \u001b[0;36mis_unique\u001b[0;34m(self)\u001b[0m\n\u001b[1;32m    810\u001b[0m     \u001b[0;32mdef\u001b[0m \u001b[0mis_unique\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    811\u001b[0m         \u001b[0;34m\"\"\" return if the index has unique values \"\"\"\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 812\u001b[0;31m         \u001b[0;32mreturn\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_engine\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mis_unique\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    813\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    814\u001b[0m     \u001b[0;34m@\u001b[0m\u001b[0mproperty\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;31mKeyboardInterrupt\u001b[0m: "
     ]
    }
   ],
   "source": [
    "trainset_path = '/home/chocolate/Train_data/'\n",
    "trainset_main_path = '/home/chocolate/Train_data_main/'\n",
    "file_list = os.listdir(trainset_path)\n",
    "for i in range(len(file_list)):\n",
    "    train_data = pd.read_csv(trainset_path + file_list[i],encoding=\"gbk\")\n",
    "    train_data = train_data.sort_values(by='Time')  # 对原数据重新按时间排序，因为有些数据顺序被打乱了。\n",
    "#     train_data = train_data[:-5] # 最后5分钟的数据不可取，去除\n",
    "    newtime = pd.to_datetime(train_data['Time']) # 将时间转换为datetime格式\n",
    "    newtime_list = list(train_data['Time']) # 将时间Series格式转换为list\n",
    "    main_month = newtime.iloc[-1].month # 提取主力合约的月份\n",
    "    if i == 0:\n",
    "        for j in range(len(train_data)):\n",
    "            if newtime.iloc[j].month != main_month:\n",
    "                 train_data.drop(j,inplace=True) # 如果不是主力合约的数据直接删除\n",
    "        train_data.to_csv(trainset_main_path + file_list[i].split('.')[0]+ '_main' + '.csv',sep=',') # 将提取的主力合约另存为csv文件\n",
    "        main_last_time = train_data['Time'].iloc[-10] # 取上一个合约最后一个交割日的时间\n",
    "        print \"第一个合约交割日时间：\",main_last_time\n",
    "    else:\n",
    "        main_last_index = newtime_list.index(main_last_time) # 返回上一个合约的交割日在当前合约中的索引\n",
    "        print \"上个合约交割时间所在当前合约的索引：\",main_last_index\n",
    "        for k in range(len(train_data)):\n",
    "            if k< main_last_index:\n",
    "                train_data.drop(k,inplace=True) # 如果不是主力合约的数据直接删除\n",
    "        print \"当前主力合约起始时间：\",train_data['Time'].iloc[1]\n",
    "        train_data.to_csv(trainset_main_path + file_list[i].split('.')[0]+ '_main' + '.csv',sep=',') # 将提取的主力合约另存为csv文件\n",
    "        main_last_time = train_data['Time'].iloc[-10] # 取上一个合约最后一个交割日的时间\n",
    "        print \"当前合约交割日时间：\",main_last_time"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 进行数据筛选和清理，生成清理后的主力合约文件，并提取出训练集"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "# 读取已经提取好的主力合约文件\n",
    "path = '/home/chocolate/LSTM-source/'\n",
    "data = pd.read_csv(path + 'MINU_IF_zhuli_201406-_201609.csv') \n",
    "data['Time'] = pd.to_datetime(data['Time']) \n",
    "data.index = range(len(data))\n",
    "delete_list = []\n",
    "# 选择2016年1-8月的主力合约数据作为训练集，在主力合约中进行提取\n",
    "# 删除非正常交易时间的数据，交易时间为上午9：30-11：30，下午1:00到3:00\n",
    "# 因为每天开盘的前10分钟和收盘的最后10分钟数据波动较大，暂时在训练时去掉这些数据\n",
    "for k in range(len(data)):\n",
    "    if data['Time'].iloc[k].year != 2016:\n",
    "        delete_list.append(k)\n",
    "    elif data['Time'].iloc[k].month >=9:\n",
    "        delete_list.append(k)\n",
    "    elif data['Time'].iloc[k].hour < 9:\n",
    "        delete_list.append(k)\n",
    "    elif data['Time'].iloc[k].hour == 9 and data['Time'].iloc[k].minute <= 39:\n",
    "        delete_list.append(k)\n",
    "    elif data['Time'].iloc[k].hour == 14 and data['Time'].iloc[k].minute >= 50:\n",
    "         delete_list.append(k)\n",
    "    elif data['Time'].iloc[k].hour >= 15:\n",
    "        delete_list.append(k)\n",
    "        \n",
    "for j in range(len(data)):\n",
    "    if j in delete_list:\n",
    "        data.drop(j,inplace=True)\n",
    "data= data.sort_values(by = 'Time')\n",
    "\n",
    "# 一分钟之内，最大股价和最低股价相差超过50点的，那么应该尽量删掉这些数据。\n",
    "# 删除一分钟成交量大于1000的，这些数据可能会影响整体数据\n",
    "for k in range(len(data)):\n",
    "    if data['MaxPrice'].iloc[k] - data['MinPrice'].iloc[k] > 50:\n",
    "       delete_list.append(k)\n",
    "    elif data['Volume'].iloc[k] > 1000:\n",
    "       delete_list.append(k)\n",
    "data.to_csv(path + 'cleaned_train_data.csv')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 59,
   "metadata": {
    "collapsed": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<bound method DataFrame.describe of        Unnamed: 0                      Date                 Time  Latestprice  \\\n",
       "0          106856  2016-01-04T01:40:00.000Z  2016-01-04 09:40:00       3640.4   \n",
       "1          106857  2016-01-04T01:41:00.000Z  2016-01-04 09:41:00       3625.8   \n",
       "2          106858  2016-01-04T01:42:00.000Z  2016-01-04 09:42:00       3618.8   \n",
       "3          106859  2016-01-04T01:43:00.000Z  2016-01-04 09:43:00       3617.0   \n",
       "4          106860  2016-01-04T01:44:00.000Z  2016-01-04 09:44:00       3618.0   \n",
       "5          106862  2016-01-04T01:44:00.000Z  2016-01-04 09:44:00       3621.0   \n",
       "6          106861  2016-01-04T01:46:00.000Z  2016-01-04 09:46:00       3614.2   \n",
       "7          106863  2016-01-04T01:46:00.000Z  2016-01-04 09:46:00       3601.2   \n",
       "8          106864  2016-01-04T01:47:00.000Z  2016-01-04 09:47:00       3602.2   \n",
       "9          106865  2016-01-04T01:49:00.000Z  2016-01-04 09:49:00       3604.6   \n",
       "10         106867  2016-01-04T01:50:00.000Z  2016-01-04 09:50:00       3602.4   \n",
       "11         106869  2016-01-04T01:51:00.000Z  2016-01-04 09:51:00       3605.2   \n",
       "12         106868  2016-01-04T01:52:00.000Z  2016-01-04 09:52:00       3605.8   \n",
       "13         106870  2016-01-04T01:53:00.000Z  2016-01-04 09:53:00       3605.0   \n",
       "14         106871  2016-01-04T01:54:00.000Z  2016-01-04 09:54:00       3606.0   \n",
       "15         106872  2016-01-04T01:55:00.000Z  2016-01-04 09:55:00       3608.8   \n",
       "16         106873  2016-01-04T01:56:00.000Z  2016-01-04 09:56:00       3607.0   \n",
       "17         106874  2016-01-04T01:57:00.000Z  2016-01-04 09:57:00       3601.4   \n",
       "18         106875  2016-01-04T01:57:00.000Z  2016-01-04 09:57:00       3606.8   \n",
       "19         106876  2016-01-04T01:58:00.000Z  2016-01-04 09:58:00       3607.0   \n",
       "20         106877  2016-01-04T01:59:00.000Z  2016-01-04 09:59:00       3613.0   \n",
       "21         106878  2016-01-04T02:01:00.000Z  2016-01-04 10:01:00       3607.8   \n",
       "22         106879  2016-01-04T02:02:00.000Z  2016-01-04 10:02:00       3593.8   \n",
       "23         106880  2016-01-04T02:03:00.000Z  2016-01-04 10:03:00       3589.8   \n",
       "24         106881  2016-01-04T02:04:00.000Z  2016-01-04 10:04:00       3597.4   \n",
       "25         106882  2016-01-04T02:05:00.000Z  2016-01-04 10:05:00       3591.4   \n",
       "26         106883  2016-01-04T02:06:00.000Z  2016-01-04 10:06:00       3588.0   \n",
       "27         106884  2016-01-04T02:06:00.000Z  2016-01-04 10:06:00       3580.0   \n",
       "28         106886  2016-01-04T02:08:00.000Z  2016-01-04 10:08:00       3568.0   \n",
       "29         106885  2016-01-04T02:09:00.000Z  2016-01-04 10:09:00       3568.0   \n",
       "...           ...                       ...                  ...          ...   \n",
       "35728      146189  2016-08-31T06:20:00.000Z  2016-08-31 14:20:00       3301.6   \n",
       "35729      146191  2016-08-31T06:21:00.000Z  2016-08-31 14:21:00       3302.4   \n",
       "35730      146190  2016-08-31T06:22:00.000Z  2016-08-31 14:22:00       3304.4   \n",
       "35731      146192  2016-08-31T06:23:00.000Z  2016-08-31 14:23:00       3304.6   \n",
       "35732      146193  2016-08-31T06:23:00.000Z  2016-08-31 14:23:00       3304.6   \n",
       "35733      146194  2016-08-31T06:24:00.000Z  2016-08-31 14:24:00       3303.6   \n",
       "35734      146195  2016-08-31T06:26:00.000Z  2016-08-31 14:26:00       3304.2   \n",
       "35735      146197  2016-08-31T06:27:00.000Z  2016-08-31 14:27:00       3307.0   \n",
       "35736      146196  2016-08-31T06:28:00.000Z  2016-08-31 14:28:00       3308.8   \n",
       "35737      146198  2016-08-31T06:29:00.000Z  2016-08-31 14:29:00       3309.8   \n",
       "35738      146199  2016-08-31T06:29:00.000Z  2016-08-31 14:29:00       3308.0   \n",
       "35739      146200  2016-08-31T06:30:00.000Z  2016-08-31 14:30:00       3307.2   \n",
       "35740      146201  2016-08-31T06:32:00.000Z  2016-08-31 14:32:00       3306.8   \n",
       "35741      146202  2016-08-31T06:33:00.000Z  2016-08-31 14:33:00       3307.0   \n",
       "35742      146203  2016-08-31T06:33:00.000Z  2016-08-31 14:33:00       3307.0   \n",
       "35743      146204  2016-08-31T06:34:00.000Z  2016-08-31 14:34:00       3307.0   \n",
       "35744      146205  2016-08-31T06:36:00.000Z  2016-08-31 14:36:00       3305.2   \n",
       "35745      146207  2016-08-31T06:37:00.000Z  2016-08-31 14:37:00       3306.6   \n",
       "35746      146206  2016-08-31T06:37:00.000Z  2016-08-31 14:37:00       3306.0   \n",
       "35747      146208  2016-08-31T06:39:00.000Z  2016-08-31 14:39:00       3305.8   \n",
       "35748      146210  2016-08-31T06:40:00.000Z  2016-08-31 14:40:00       3307.0   \n",
       "35749      146211  2016-08-31T06:41:00.000Z  2016-08-31 14:41:00       3307.2   \n",
       "35750      146212  2016-08-31T06:41:00.000Z  2016-08-31 14:41:00       3306.2   \n",
       "35751      146213  2016-08-31T06:42:00.000Z  2016-08-31 14:42:00       3306.2   \n",
       "35752      146214  2016-08-31T06:44:00.000Z  2016-08-31 14:44:00       3306.6   \n",
       "35753      146215  2016-08-31T06:45:00.000Z  2016-08-31 14:45:00       3306.6   \n",
       "35754      146216  2016-08-31T06:46:00.000Z  2016-08-31 14:46:00       3306.2   \n",
       "35755      146218  2016-08-31T06:47:00.000Z  2016-08-31 14:47:00       3304.2   \n",
       "35756      146217  2016-08-31T06:47:00.000Z  2016-08-31 14:47:00       3304.8   \n",
       "35757      146219  2016-08-31T06:49:00.000Z  2016-08-31 14:49:00       3305.0   \n",
       "\n",
       "       MaxPrice  MinPrice  Stockup   Turnover  Position  Volume  \\\n",
       "0        3646.0    3640.2      -63  115844340     28315     106   \n",
       "1        3641.4    3624.4      -79  228902820     28236     210   \n",
       "2        3626.8    3612.6     -110  301745580     28126     278   \n",
       "3        3620.2    3616.0      -81  162817740     28045     150   \n",
       "4        3618.8    3613.0      -66  143205060     27979     132   \n",
       "5        3621.6    3618.0      -47  111857580     27931     103   \n",
       "6        3621.4    3614.2      -46  120504420     27885     111   \n",
       "7        3615.6    3600.0      -98  372121500     27787     344   \n",
       "8        3608.6    3600.4      -68  195712320     27719     181   \n",
       "9        3608.4    3599.0      -70  198897300     27649     184   \n",
       "10       3606.0    3599.0      -39  127536900     27610     118   \n",
       "11       3607.6    3602.2      -28   83269080     27582      77   \n",
       "12       3605.8    3602.2       -9   65952540     27573      61   \n",
       "13       3606.0    3602.8      -13   50825100     27560      47   \n",
       "14       3606.0    3604.2      -27   78953280     27533      73   \n",
       "15       3609.0    3605.4      -23  102802020     27510      95   \n",
       "16       3609.2    3605.4      -19   60597360     27491      56   \n",
       "17       3607.0    3601.4      -44  128675580     27447     119   \n",
       "18       3606.8    3594.0      -16  176006520     27431     163   \n",
       "19       3607.8    3603.4       -4   97367760     27428      90   \n",
       "20       3613.6    3605.4      -35  123478800     27391     114   \n",
       "21       3613.6    3607.8      -30   72574440     27361      67   \n",
       "22       3607.8    3591.2      -58  201761820     27303     187   \n",
       "23       3594.4    3588.4      -39  170214000     27264     158   \n",
       "24       3597.8    3589.0      -37   95919060     27227      89   \n",
       "25       3597.4    3589.2       -7   89435100     27220      83   \n",
       "26       3592.8    3588.0      -13   91545060     27207      85   \n",
       "27       3588.6    3580.0       -4  167710680     27203     156   \n",
       "28       3580.2    3567.2       -1  190875540     27202     178   \n",
       "29       3571.4    3565.0      -17  135944700     27185     127   \n",
       "...         ...       ...      ...        ...       ...     ...   \n",
       "35728    3301.6    3299.2       14   30692160     37376      31   \n",
       "35729    3304.4    3300.2       29   61434300     37405      62   \n",
       "35730    3305.0    3302.4       22   42620280     37427      43   \n",
       "35731    3305.6    3303.2       22   75345540     37449      76   \n",
       "35732    3305.4    3301.4       40   85243080     37489      86   \n",
       "35733    3304.6    3303.2        7   30726180     37496      31   \n",
       "35734    3304.2    3303.2        8   21803700     37504      22   \n",
       "35735    3309.0    3303.4        9   61494420     37513      62   \n",
       "35736    3309.0    3305.6       12   47622960     37525      48   \n",
       "35737    3309.8    3306.8       26   70471860     37551      71   \n",
       "35738    3309.8    3307.8        8   37720740     37559      38   \n",
       "35739    3308.6    3307.0       -3   19846320     37556      20   \n",
       "35740    3308.2    3306.6        5   33737580     37561      34   \n",
       "35741    3308.0    3306.4        1   38690940     37562      39   \n",
       "35742    3307.2    3306.2        6   31743660     37568      32   \n",
       "35743    3308.0    3306.6        4   30758820     37572      31   \n",
       "35744    3307.0    3305.0       10   32726820     37582      33   \n",
       "35745    3307.6    3305.4        9   32736780     37593      33   \n",
       "35746    3306.6    3305.2        2   27770820     37584      28   \n",
       "35747    3307.4    3305.8       13   38687640     37606      39   \n",
       "35748    3307.0    3305.4       17   47606100     37623      48   \n",
       "35749    3308.0    3306.4       16   47622480     37639      48   \n",
       "35750    3307.4    3305.6       27   60509280     37666      61   \n",
       "35751    3307.0    3306.0       13   39678300     37679      40   \n",
       "35752    3307.4    3305.8        6   46622640     37685      47   \n",
       "35753    3307.2    3305.8        4   38684280     37689      39   \n",
       "35754    3307.2    3305.6        7   51579780     37696      52   \n",
       "35755    3306.8    3304.2       29   80316660     37725      81   \n",
       "35756    3305.4    3303.8       11   60475860     37736      61   \n",
       "35757    3306.2    3304.0       12   74366280     37748      75   \n",
       "\n",
       "       First.Latestprice  Last.Buy1price  Last.Buy1quantity  Last.Sell1price  \\\n",
       "0                 3644.8          3640.2                  2           3641.4   \n",
       "1                 3640.4          3625.0                  4           3626.8   \n",
       "2                 3625.4          3619.2                  1           3620.0   \n",
       "3                 3618.8          3616.8                  5           3618.0   \n",
       "4                 3616.8          3618.0                  2           3618.2   \n",
       "5                 3618.2          3621.0                  1           3621.2   \n",
       "6                 3621.0          3612.8                  2           3613.8   \n",
       "7                 3614.2          3601.0                  1           3602.8   \n",
       "8                 3601.2          3602.2                  2           3603.0   \n",
       "9                 3602.0          3603.4                  1           3604.6   \n",
       "10                3604.6          3602.8                  1           3603.8   \n",
       "11                3602.4          3603.4                  2           3605.6   \n",
       "12                3603.4          3604.6                  1           3605.4   \n",
       "13                3605.8          3604.2                  5           3604.8   \n",
       "14                3604.2          3605.2                  1           3605.4   \n",
       "15                3606.0          3608.6                  1           3609.0   \n",
       "16                3609.0          3607.0                  1           3608.0   \n",
       "17                3606.4          3601.4                  3           3603.2   \n",
       "18                3601.4          3604.2                  1           3606.8   \n",
       "19                3604.4          3606.6                  3           3607.0   \n",
       "20                3607.0          3612.4                  1           3613.6   \n",
       "21                3612.4          3607.8                  3           3609.8   \n",
       "22                3607.8          3592.2                  3           3595.0   \n",
       "23                3592.2          3589.2                  1           3590.6   \n",
       "24                3589.0          3594.8                  1           3597.0   \n",
       "25                3597.4          3589.2                  1           3591.8   \n",
       "26                3591.4          3588.0                  5           3589.0   \n",
       "27                3586.8          3580.0                  2           3580.4   \n",
       "28                3580.2          3567.2                  1           3567.6   \n",
       "29                3567.2          3566.6                  1           3568.0   \n",
       "...                  ...             ...                ...              ...   \n",
       "35728             3300.8          3300.2                  2           3301.2   \n",
       "35729             3301.6          3302.4                  1           3302.8   \n",
       "35730             3302.4          3303.2                  2           3304.6   \n",
       "35731             3304.6          3304.6                  2           3305.4   \n",
       "35732             3304.6          3304.2                  1           3304.4   \n",
       "35733             3304.2          3303.6                  2           3304.0   \n",
       "35734             3303.6          3303.2                  2           3304.2   \n",
       "35735             3304.2          3307.2                  1           3308.0   \n",
       "35736             3307.0          3307.6                  3           3309.0   \n",
       "35737             3308.8          3308.6                  2           3309.6   \n",
       "35738             3309.8          3308.0                  1           3308.4   \n",
       "35739             3308.0          3307.0                  1           3308.0   \n",
       "35740             3307.2          3306.6                  1           3306.8   \n",
       "35741             3307.0          3306.4                  3           3307.0   \n",
       "35742             3306.4          3306.4                  2           3307.0   \n",
       "35743             3307.2          3306.2                  2           3307.6   \n",
       "35744             3307.0          3305.0                  6           3305.8   \n",
       "35745             3305.4          3306.6                  1           3307.2   \n",
       "35746             3305.8          3305.4                  2           3306.0   \n",
       "35747             3306.6          3306.0                  1           3306.4   \n",
       "35748             3305.8          3306.4                  2           3307.0   \n",
       "35749             3307.0          3307.2                  1           3307.4   \n",
       "35750             3307.2          3305.8                  1           3306.8   \n",
       "35751             3306.2          3306.0                  4           3307.2   \n",
       "35752             3307.2          3306.2                  3           3307.4   \n",
       "35753             3306.2          3306.6                  1           3306.8   \n",
       "35754             3306.6          3305.8                  2           3306.8   \n",
       "35755             3305.8          3304.2                  3           3305.2   \n",
       "35756             3304.2          3304.8                  1           3305.0   \n",
       "35757             3305.0          3305.0                  1           3305.4   \n",
       "\n",
       "       Last.Sell1quantity  \n",
       "0                       1  \n",
       "1                       1  \n",
       "2                      11  \n",
       "3                       5  \n",
       "4                       2  \n",
       "5                       2  \n",
       "6                       1  \n",
       "7                       1  \n",
       "8                       2  \n",
       "9                       1  \n",
       "10                      2  \n",
       "11                      1  \n",
       "12                      1  \n",
       "13                      1  \n",
       "14                      1  \n",
       "15                      1  \n",
       "16                      1  \n",
       "17                      1  \n",
       "18                      1  \n",
       "19                      1  \n",
       "20                      1  \n",
       "21                      1  \n",
       "22                      1  \n",
       "23                      1  \n",
       "24                      1  \n",
       "25                      1  \n",
       "26                      2  \n",
       "27                      2  \n",
       "28                      1  \n",
       "29                      1  \n",
       "...                   ...  \n",
       "35728                   1  \n",
       "35729                   1  \n",
       "35730                   1  \n",
       "35731                   1  \n",
       "35732                   2  \n",
       "35733                   1  \n",
       "35734                   1  \n",
       "35735                   1  \n",
       "35736                   4  \n",
       "35737                   1  \n",
       "35738                   1  \n",
       "35739                   3  \n",
       "35740                   2  \n",
       "35741                   1  \n",
       "35742                   1  \n",
       "35743                   2  \n",
       "35744                   1  \n",
       "35745                   1  \n",
       "35746                   1  \n",
       "35747                   1  \n",
       "35748                   7  \n",
       "35749                   3  \n",
       "35750                   2  \n",
       "35751                   2  \n",
       "35752                   2  \n",
       "35753                   1  \n",
       "35754                   1  \n",
       "35755                   1  \n",
       "35756                   1  \n",
       "35757                   1  \n",
       "\n",
       "[35758 rows x 15 columns]>"
      ]
     },
     "execution_count": 59,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data.describe"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 加入MA、EMA、MACD指标"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 加入5分钟、12分钟、26分钟的MA、EMA指标"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "collapsed": true
   },
   "outputs": [
    {
     "ename": "IOError",
     "evalue": "File /home/chocolate/LSTM-source/cleaned_train_data.csv does not exist",
     "output_type": "error",
     "traceback": [
      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[0;31mIOError\u001b[0m                                   Traceback (most recent call last)",
      "\u001b[0;32m<ipython-input-3-52074bdeb5da>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m()\u001b[0m\n\u001b[1;32m      2\u001b[0m \u001b[0;32mimport\u001b[0m \u001b[0mdatetime\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m      3\u001b[0m \u001b[0mpath\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0;34m'/home/chocolate/LSTM-source/'\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m----> 4\u001b[0;31m \u001b[0mdata\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mpd\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mread_csv\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mpath\u001b[0m \u001b[0;34m+\u001b[0m \u001b[0;34m'cleaned_train_data.csv'\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m      5\u001b[0m \u001b[0mdata\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m      6\u001b[0m \u001b[0mnewTime\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mpd\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mto_datetime\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mdata\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m'Time'\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;31m# 将时间转换成datetime格式\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m/usr/lib/python2.7/dist-packages/pandas/io/parsers.pyc\u001b[0m in \u001b[0;36mparser_f\u001b[0;34m(filepath_or_buffer, sep, dialect, compression, doublequote, escapechar, quotechar, quoting, skipinitialspace, lineterminator, header, index_col, names, prefix, skiprows, skipfooter, skip_footer, na_values, true_values, false_values, delimiter, converters, dtype, usecols, engine, delim_whitespace, as_recarray, na_filter, compact_ints, use_unsigned, low_memory, buffer_lines, warn_bad_lines, error_bad_lines, keep_default_na, thousands, comment, decimal, parse_dates, keep_date_col, dayfirst, date_parser, memory_map, float_precision, nrows, iterator, chunksize, verbose, encoding, squeeze, mangle_dupe_cols, tupleize_cols, infer_datetime_format, skip_blank_lines)\u001b[0m\n\u001b[1;32m    496\u001b[0m                     skip_blank_lines=skip_blank_lines)\n\u001b[1;32m    497\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 498\u001b[0;31m         \u001b[0;32mreturn\u001b[0m \u001b[0m_read\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mfilepath_or_buffer\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mkwds\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    499\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    500\u001b[0m     \u001b[0mparser_f\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m__name__\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mname\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m/usr/lib/python2.7/dist-packages/pandas/io/parsers.pyc\u001b[0m in \u001b[0;36m_read\u001b[0;34m(filepath_or_buffer, kwds)\u001b[0m\n\u001b[1;32m    273\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    274\u001b[0m     \u001b[0;31m# Create the parser.\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 275\u001b[0;31m     \u001b[0mparser\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mTextFileReader\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mfilepath_or_buffer\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m**\u001b[0m\u001b[0mkwds\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    276\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    277\u001b[0m     \u001b[0;32mif\u001b[0m \u001b[0;34m(\u001b[0m\u001b[0mnrows\u001b[0m \u001b[0;32mis\u001b[0m \u001b[0;32mnot\u001b[0m \u001b[0mNone\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;32mand\u001b[0m \u001b[0;34m(\u001b[0m\u001b[0mchunksize\u001b[0m \u001b[0;32mis\u001b[0m \u001b[0;32mnot\u001b[0m \u001b[0mNone\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m/usr/lib/python2.7/dist-packages/pandas/io/parsers.pyc\u001b[0m in \u001b[0;36m__init__\u001b[0;34m(self, f, engine, **kwds)\u001b[0m\n\u001b[1;32m    588\u001b[0m             \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0moptions\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m'has_index_names'\u001b[0m\u001b[0;34m]\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mkwds\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m'has_index_names'\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    589\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 590\u001b[0;31m         \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_make_engine\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mengine\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    591\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    592\u001b[0m     \u001b[0;32mdef\u001b[0m \u001b[0m_get_options_with_defaults\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mengine\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m/usr/lib/python2.7/dist-packages/pandas/io/parsers.pyc\u001b[0m in \u001b[0;36m_make_engine\u001b[0;34m(self, engine)\u001b[0m\n\u001b[1;32m    729\u001b[0m     \u001b[0;32mdef\u001b[0m \u001b[0m_make_engine\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mengine\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;34m'c'\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    730\u001b[0m         \u001b[0;32mif\u001b[0m \u001b[0mengine\u001b[0m \u001b[0;34m==\u001b[0m \u001b[0;34m'c'\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 731\u001b[0;31m             \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_engine\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mCParserWrapper\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mf\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m**\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0moptions\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    732\u001b[0m         \u001b[0;32melse\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    733\u001b[0m             \u001b[0;32mif\u001b[0m \u001b[0mengine\u001b[0m \u001b[0;34m==\u001b[0m \u001b[0;34m'python'\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m/usr/lib/python2.7/dist-packages/pandas/io/parsers.pyc\u001b[0m in \u001b[0;36m__init__\u001b[0;34m(self, src, **kwds)\u001b[0m\n\u001b[1;32m   1101\u001b[0m         \u001b[0mkwds\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m'allow_leading_cols'\u001b[0m\u001b[0;34m]\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mindex_col\u001b[0m \u001b[0;32mis\u001b[0m \u001b[0;32mnot\u001b[0m \u001b[0mFalse\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   1102\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 1103\u001b[0;31m         \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_reader\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0m_parser\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mTextReader\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0msrc\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m**\u001b[0m\u001b[0mkwds\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m   1104\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   1105\u001b[0m         \u001b[0;31m# XXX\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32mpandas/parser.pyx\u001b[0m in \u001b[0;36mpandas.parser.TextReader.__cinit__ (pandas/parser.c:3246)\u001b[0;34m()\u001b[0m\n",
      "\u001b[0;32mpandas/parser.pyx\u001b[0m in \u001b[0;36mpandas.parser.TextReader._setup_parser_source (pandas/parser.c:6111)\u001b[0;34m()\u001b[0m\n",
      "\u001b[0;31mIOError\u001b[0m: File /home/chocolate/LSTM-source/cleaned_train_data.csv does not exist"
     ]
    }
   ],
   "source": [
    "import seaborn as sns\n",
    "import datetime\n",
    "path = '/home/chocolate/LSTM-source/'\n",
    "data = pd.read_csv(path + 'cleaned_train_data.csv')\n",
    "data\n",
    "newTime = pd.to_datetime(data['Time']) # 将时间转换成datetime格式\n",
    "ma_list = [5, 12, 26]\n",
    "newdata1 = []\n",
    "#  添加收盘价的移动平均线MA和指数平滑移动平均线EMA\n",
    "newdata1 = pd.concat([newTime,data[['Latestprice','MaxPrice','MinPrice','Stockup','Turnover','Position','Volume','First.Latestprice','Last.Buy1price','Last.Buy1quantity','Last.Sell1price','Last.Sell1quantity']]], axis = 1)\n",
    "for ma in ma_list:\n",
    "    newdata1['MA_' + str(ma)] = pd.rolling_mean(data['Latestprice'], ma)\n",
    "    # 计算移动平均线之间的距离\n",
    "newdata1['Dis_MA5_26'] = newdata1['MA_5'] - newdata1['MA_26']\n",
    "    # 计算指数平滑移动平均线\n",
    "for ma in ma_list:\n",
    "    newdata1['EMA_' + str(ma)] = pd.ewma(newdata1['Latestprice'], span=ma)\n",
    "    # 计算指数平滑移动平均线之间的距离\n",
    "newdata1['Dis_EMA5_26'] = newdata1['EMA_5'] - newdata1['EMA_26']\n",
    "    \n",
    "# 添加成交量的移动平均线MA和指数平滑移动平均线EMA\n",
    "for ma in ma_list:\n",
    "    newdata1['Vol_MA_'+str(ma)] =  pd.rolling_mean(data['Volume'], ma)\n",
    "# 计算成交量移动平均线之间的距离\n",
    "newdata1['Dis_Vol_MA5_26'] = newdata1['Vol_MA_5'] - newdata1['Vol_MA_26']\n",
    "# 添加成交量的指数平滑移动平均线\n",
    "for ma in ma_list:\n",
    "    newdata1['Vol_EMA_'+str(ma)] = pd.ewma(newdata1['Volume'], span=ma)\n",
    "# 计算指数平滑移动平均线之间的距离\n",
    "newdata1['Dis_Vol_EMA5_26'] = newdata1['Vol_EMA_5'] - newdata1['Vol_EMA_26']  \n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {
    "collapsed": true
   },
   "outputs": [
    {
     "data": {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Time</th>\n",
       "      <th>Latestprice</th>\n",
       "      <th>MaxPrice</th>\n",
       "      <th>MinPrice</th>\n",
       "      <th>Stockup</th>\n",
       "      <th>Turnover</th>\n",
       "      <th>Position</th>\n",
       "      <th>Volume</th>\n",
       "      <th>First.Latestprice</th>\n",
       "      <th>Last.Buy1price</th>\n",
       "      <th>...</th>\n",
       "      <th>EMA_26</th>\n",
       "      <th>Dis_EMA5_26</th>\n",
       "      <th>Vol_MA_5</th>\n",
       "      <th>Vol_MA_12</th>\n",
       "      <th>Vol_MA_26</th>\n",
       "      <th>Dis_Vol_MA5_26</th>\n",
       "      <th>Vol_EMA_5</th>\n",
       "      <th>Vol_EMA_12</th>\n",
       "      <th>Vol_EMA_26</th>\n",
       "      <th>Dis_Vol_EMA5_26</th>\n",
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       "      <th>0</th>\n",
       "      <td>2016-01-04 09:40:00</td>\n",
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       "      <td>28315</td>\n",
       "      <td>106</td>\n",
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       "      <td>3640.2</td>\n",
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       "      <td>NaN</td>\n",
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       "      <td>106.000000</td>\n",
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       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2016-01-04 09:41:00</td>\n",
       "      <td>3625.8</td>\n",
       "      <td>3641.4</td>\n",
       "      <td>3624.4</td>\n",
       "      <td>-79</td>\n",
       "      <td>228902820</td>\n",
       "      <td>28236</td>\n",
       "      <td>210</td>\n",
       "      <td>3640.4</td>\n",
       "      <td>3625.0</td>\n",
       "      <td>...</td>\n",
       "      <td>3632.819231</td>\n",
       "      <td>-1.179231</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>168.400000</td>\n",
       "      <td>162.333333</td>\n",
       "      <td>160.000000</td>\n",
       "      <td>8.400000</td>\n",
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       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2016-01-04 09:42:00</td>\n",
       "      <td>3618.8</td>\n",
       "      <td>3626.8</td>\n",
       "      <td>3612.6</td>\n",
       "      <td>-110</td>\n",
       "      <td>301745580</td>\n",
       "      <td>28126</td>\n",
       "      <td>278</td>\n",
       "      <td>3625.4</td>\n",
       "      <td>3619.2</td>\n",
       "      <td>...</td>\n",
       "      <td>3627.782257</td>\n",
       "      <td>-2.224363</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>220.315789</td>\n",
       "      <td>207.478060</td>\n",
       "      <td>202.396254</td>\n",
       "      <td>17.919535</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2016-01-04 09:43:00</td>\n",
       "      <td>3617.0</td>\n",
       "      <td>3620.2</td>\n",
       "      <td>3616.0</td>\n",
       "      <td>-81</td>\n",
       "      <td>162817740</td>\n",
       "      <td>28045</td>\n",
       "      <td>150</td>\n",
       "      <td>3618.8</td>\n",
       "      <td>3616.8</td>\n",
       "      <td>...</td>\n",
       "      <td>3624.768009</td>\n",
       "      <td>-2.764932</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>191.107692</td>\n",
       "      <td>189.334483</td>\n",
       "      <td>187.748551</td>\n",
       "      <td>3.359141</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2016-01-04 09:44:00</td>\n",
       "      <td>3618.0</td>\n",
       "      <td>3618.8</td>\n",
       "      <td>3613.0</td>\n",
       "      <td>-66</td>\n",
       "      <td>143205060</td>\n",
       "      <td>27979</td>\n",
       "      <td>132</td>\n",
       "      <td>3616.8</td>\n",
       "      <td>3618.0</td>\n",
       "      <td>...</td>\n",
       "      <td>3623.198480</td>\n",
       "      <td>-2.732129</td>\n",
       "      <td>175.2</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>168.417062</td>\n",
       "      <td>173.756909</td>\n",
       "      <td>174.820232</td>\n",
       "      <td>-6.403171</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>2016-01-04 09:44:00</td>\n",
       "      <td>3621.0</td>\n",
       "      <td>3621.6</td>\n",
       "      <td>3618.0</td>\n",
       "      <td>-47</td>\n",
       "      <td>111857580</td>\n",
       "      <td>27931</td>\n",
       "      <td>103</td>\n",
       "      <td>3618.2</td>\n",
       "      <td>3621.0</td>\n",
       "      <td>...</td>\n",
       "      <td>3622.758142</td>\n",
       "      <td>-2.096789</td>\n",
       "      <td>174.6</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>144.512782</td>\n",
       "      <td>156.559257</td>\n",
       "      <td>160.435213</td>\n",
       "      <td>-15.922431</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>2016-01-04 09:46:00</td>\n",
       "      <td>3614.2</td>\n",
       "      <td>3621.4</td>\n",
       "      <td>3614.2</td>\n",
       "      <td>-46</td>\n",
       "      <td>120504420</td>\n",
       "      <td>27885</td>\n",
       "      <td>111</td>\n",
       "      <td>3621.0</td>\n",
       "      <td>3612.8</td>\n",
       "      <td>...</td>\n",
       "      <td>3621.236121</td>\n",
       "      <td>-2.862444</td>\n",
       "      <td>154.8</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>132.647402</td>\n",
       "      <td>146.392868</td>\n",
       "      <td>151.643416</td>\n",
       "      <td>-18.996015</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>2016-01-04 09:46:00</td>\n",
       "      <td>3601.2</td>\n",
       "      <td>3615.6</td>\n",
       "      <td>3600.0</td>\n",
       "      <td>-98</td>\n",
       "      <td>372121500</td>\n",
       "      <td>27787</td>\n",
       "      <td>344</td>\n",
       "      <td>3614.2</td>\n",
       "      <td>3601.0</td>\n",
       "      <td>...</td>\n",
       "      <td>3618.007805</td>\n",
       "      <td>-5.591120</td>\n",
       "      <td>168.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>205.958763</td>\n",
       "      <td>187.630431</td>\n",
       "      <td>182.636828</td>\n",
       "      <td>23.321935</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>2016-01-04 09:47:00</td>\n",
       "      <td>3602.2</td>\n",
       "      <td>3608.6</td>\n",
       "      <td>3600.4</td>\n",
       "      <td>-68</td>\n",
       "      <td>195712320</td>\n",
       "      <td>27719</td>\n",
       "      <td>181</td>\n",
       "      <td>3601.2</td>\n",
       "      <td>3602.2</td>\n",
       "      <td>...</td>\n",
       "      <td>3615.664742</td>\n",
       "      <td>-6.744570</td>\n",
       "      <td>174.2</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>197.416984</td>\n",
       "      <td>186.318696</td>\n",
       "      <td>182.394214</td>\n",
       "      <td>15.022770</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>2016-01-04 09:49:00</td>\n",
       "      <td>3604.6</td>\n",
       "      <td>3608.4</td>\n",
       "      <td>3599.0</td>\n",
       "      <td>-70</td>\n",
       "      <td>198897300</td>\n",
       "      <td>27649</td>\n",
       "      <td>184</td>\n",
       "      <td>3602.0</td>\n",
       "      <td>3603.4</td>\n",
       "      <td>...</td>\n",
       "      <td>3614.137915</td>\n",
       "      <td>-6.683214</td>\n",
       "      <td>184.6</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>192.865730</td>\n",
       "      <td>185.879304</td>\n",
       "      <td>182.615797</td>\n",
       "      <td>10.249933</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>2016-01-04 09:50:00</td>\n",
       "      <td>3602.4</td>\n",
       "      <td>3606.0</td>\n",
       "      <td>3599.0</td>\n",
       "      <td>-39</td>\n",
       "      <td>127536900</td>\n",
       "      <td>27610</td>\n",
       "      <td>118</td>\n",
       "      <td>3604.6</td>\n",
       "      <td>3602.8</td>\n",
       "      <td>...</td>\n",
       "      <td>3612.615504</td>\n",
       "      <td>-6.865410</td>\n",
       "      <td>187.6</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>167.618604</td>\n",
       "      <td>173.459028</td>\n",
       "      <td>174.235108</td>\n",
       "      <td>-6.616503</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>2016-01-04 09:51:00</td>\n",
       "      <td>3605.2</td>\n",
       "      <td>3607.6</td>\n",
       "      <td>3602.2</td>\n",
       "      <td>-28</td>\n",
       "      <td>83269080</td>\n",
       "      <td>27582</td>\n",
       "      <td>77</td>\n",
       "      <td>3602.4</td>\n",
       "      <td>3603.4</td>\n",
       "      <td>...</td>\n",
       "      <td>3611.704392</td>\n",
       "      <td>-6.139087</td>\n",
       "      <td>180.8</td>\n",
       "      <td>166.166667</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>137.177785</td>\n",
       "      <td>156.308929</td>\n",
       "      <td>162.288243</td>\n",
       "      <td>-25.110458</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>2016-01-04 09:52:00</td>\n",
       "      <td>3605.8</td>\n",
       "      <td>3605.8</td>\n",
       "      <td>3602.2</td>\n",
       "      <td>-9</td>\n",
       "      <td>65952540</td>\n",
       "      <td>27573</td>\n",
       "      <td>61</td>\n",
       "      <td>3603.4</td>\n",
       "      <td>3604.6</td>\n",
       "      <td>...</td>\n",
       "      <td>3611.012694</td>\n",
       "      <td>-5.368753</td>\n",
       "      <td>124.2</td>\n",
       "      <td>162.416667</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>111.654043</td>\n",
       "      <td>139.759679</td>\n",
       "      <td>150.422343</td>\n",
       "      <td>-38.768300</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>2016-01-04 09:53:00</td>\n",
       "      <td>3605.0</td>\n",
       "      <td>3606.0</td>\n",
       "      <td>3602.8</td>\n",
       "      <td>-13</td>\n",
       "      <td>50825100</td>\n",
       "      <td>27560</td>\n",
       "      <td>47</td>\n",
       "      <td>3605.8</td>\n",
       "      <td>3604.2</td>\n",
       "      <td>...</td>\n",
       "      <td>3610.337397</td>\n",
       "      <td>-4.908841</td>\n",
       "      <td>97.4</td>\n",
       "      <td>148.833333</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>90.028618</td>\n",
       "      <td>123.965667</td>\n",
       "      <td>138.806783</td>\n",
       "      <td>-48.778166</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>2016-01-04 09:54:00</td>\n",
       "      <td>3606.0</td>\n",
       "      <td>3606.0</td>\n",
       "      <td>3604.2</td>\n",
       "      <td>-27</td>\n",
       "      <td>78953280</td>\n",
       "      <td>27533</td>\n",
       "      <td>73</td>\n",
       "      <td>3604.2</td>\n",
       "      <td>3605.2</td>\n",
       "      <td>...</td>\n",
       "      <td>3609.868197</td>\n",
       "      <td>-4.248723</td>\n",
       "      <td>75.2</td>\n",
       "      <td>131.750000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>84.339420</td>\n",
       "      <td>115.428045</td>\n",
       "      <td>131.688101</td>\n",
       "      <td>-47.348682</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>2016-01-04 09:55:00</td>\n",
       "      <td>3608.8</td>\n",
       "      <td>3609.0</td>\n",
       "      <td>3605.4</td>\n",
       "      <td>-23</td>\n",
       "      <td>102802020</td>\n",
       "      <td>27510</td>\n",
       "      <td>95</td>\n",
       "      <td>3606.0</td>\n",
       "      <td>3608.6</td>\n",
       "      <td>...</td>\n",
       "      <td>3609.756454</td>\n",
       "      <td>-3.075189</td>\n",
       "      <td>70.6</td>\n",
       "      <td>127.166667</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>87.898365</td>\n",
       "      <td>112.052150</td>\n",
       "      <td>127.850225</td>\n",
       "      <td>-39.951860</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>2016-01-04 09:56:00</td>\n",
       "      <td>3607.0</td>\n",
       "      <td>3609.2</td>\n",
       "      <td>3605.4</td>\n",
       "      <td>-19</td>\n",
       "      <td>60597360</td>\n",
       "      <td>27491</td>\n",
       "      <td>56</td>\n",
       "      <td>3609.0</td>\n",
       "      <td>3607.0</td>\n",
       "      <td>...</td>\n",
       "      <td>3609.476650</td>\n",
       "      <td>-2.689032</td>\n",
       "      <td>66.4</td>\n",
       "      <td>120.833333</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>77.254774</td>\n",
       "      <td>102.893605</td>\n",
       "      <td>120.556799</td>\n",
       "      <td>-43.302026</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>2016-01-04 09:57:00</td>\n",
       "      <td>3601.4</td>\n",
       "      <td>3607.0</td>\n",
       "      <td>3601.4</td>\n",
       "      <td>-44</td>\n",
       "      <td>128675580</td>\n",
       "      <td>27447</td>\n",
       "      <td>119</td>\n",
       "      <td>3606.4</td>\n",
       "      <td>3601.4</td>\n",
       "      <td>...</td>\n",
       "      <td>3608.678691</td>\n",
       "      <td>-3.688162</td>\n",
       "      <td>78.0</td>\n",
       "      <td>122.166667</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>91.179271</td>\n",
       "      <td>105.500394</td>\n",
       "      <td>120.402990</td>\n",
       "      <td>-29.223719</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>2016-01-04 09:57:00</td>\n",
       "      <td>3606.8</td>\n",
       "      <td>3606.8</td>\n",
       "      <td>3594.0</td>\n",
       "      <td>-16</td>\n",
       "      <td>176006520</td>\n",
       "      <td>27431</td>\n",
       "      <td>163</td>\n",
       "      <td>3601.4</td>\n",
       "      <td>3604.2</td>\n",
       "      <td>...</td>\n",
       "      <td>3608.497558</td>\n",
       "      <td>-2.903600</td>\n",
       "      <td>101.2</td>\n",
       "      <td>126.500000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>115.130318</td>\n",
       "      <td>114.732720</td>\n",
       "      <td>124.509958</td>\n",
       "      <td>-9.379640</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>2016-01-04 09:58:00</td>\n",
       "      <td>3607.0</td>\n",
       "      <td>3607.8</td>\n",
       "      <td>3603.4</td>\n",
       "      <td>-4</td>\n",
       "      <td>97367760</td>\n",
       "      <td>27428</td>\n",
       "      <td>90</td>\n",
       "      <td>3604.4</td>\n",
       "      <td>3606.6</td>\n",
       "      <td>...</td>\n",
       "      <td>3608.356327</td>\n",
       "      <td>-2.293547</td>\n",
       "      <td>104.6</td>\n",
       "      <td>105.333333</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>106.751026</td>\n",
       "      <td>110.788050</td>\n",
       "      <td>121.255407</td>\n",
       "      <td>-14.504382</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>2016-01-04 09:59:00</td>\n",
       "      <td>3613.0</td>\n",
       "      <td>3613.6</td>\n",
       "      <td>3605.4</td>\n",
       "      <td>-35</td>\n",
       "      <td>123478800</td>\n",
       "      <td>27391</td>\n",
       "      <td>114</td>\n",
       "      <td>3607.0</td>\n",
       "      <td>3612.4</td>\n",
       "      <td>...</td>\n",
       "      <td>3608.785576</td>\n",
       "      <td>-0.409925</td>\n",
       "      <td>108.4</td>\n",
       "      <td>99.750000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>109.167835</td>\n",
       "      <td>111.297454</td>\n",
       "      <td>120.584737</td>\n",
       "      <td>-11.416902</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>2016-01-04 10:01:00</td>\n",
       "      <td>3607.8</td>\n",
       "      <td>3613.6</td>\n",
       "      <td>3607.8</td>\n",
       "      <td>-30</td>\n",
       "      <td>72574440</td>\n",
       "      <td>27361</td>\n",
       "      <td>67</td>\n",
       "      <td>3612.4</td>\n",
       "      <td>3607.8</td>\n",
       "      <td>...</td>\n",
       "      <td>3608.696115</td>\n",
       "      <td>-0.512373</td>\n",
       "      <td>110.6</td>\n",
       "      <td>90.000000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>95.110011</td>\n",
       "      <td>104.305246</td>\n",
       "      <td>115.720827</td>\n",
       "      <td>-20.610816</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>2016-01-04 10:02:00</td>\n",
       "      <td>3593.8</td>\n",
       "      <td>3607.8</td>\n",
       "      <td>3591.2</td>\n",
       "      <td>-58</td>\n",
       "      <td>201761820</td>\n",
       "      <td>27303</td>\n",
       "      <td>187</td>\n",
       "      <td>3607.8</td>\n",
       "      <td>3592.2</td>\n",
       "      <td>...</td>\n",
       "      <td>3607.366193</td>\n",
       "      <td>-3.977459</td>\n",
       "      <td>124.2</td>\n",
       "      <td>95.750000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>125.742737</td>\n",
       "      <td>117.306330</td>\n",
       "      <td>122.084617</td>\n",
       "      <td>3.658120</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>2016-01-04 10:03:00</td>\n",
       "      <td>3589.8</td>\n",
       "      <td>3594.4</td>\n",
       "      <td>3588.4</td>\n",
       "      <td>-39</td>\n",
       "      <td>170214000</td>\n",
       "      <td>27264</td>\n",
       "      <td>158</td>\n",
       "      <td>3592.2</td>\n",
       "      <td>3589.2</td>\n",
       "      <td>...</td>\n",
       "      <td>3605.821377</td>\n",
       "      <td>-6.962490</td>\n",
       "      <td>123.2</td>\n",
       "      <td>102.500000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>136.495797</td>\n",
       "      <td>123.682599</td>\n",
       "      <td>125.243107</td>\n",
       "      <td>11.252689</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>2016-01-04 10:04:00</td>\n",
       "      <td>3597.4</td>\n",
       "      <td>3597.8</td>\n",
       "      <td>3589.0</td>\n",
       "      <td>-37</td>\n",
       "      <td>95919060</td>\n",
       "      <td>27227</td>\n",
       "      <td>89</td>\n",
       "      <td>3589.0</td>\n",
       "      <td>3594.8</td>\n",
       "      <td>...</td>\n",
       "      <td>3605.090910</td>\n",
       "      <td>-6.718338</td>\n",
       "      <td>123.0</td>\n",
       "      <td>104.833333</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>120.663237</td>\n",
       "      <td>118.263609</td>\n",
       "      <td>122.099394</td>\n",
       "      <td>-1.436157</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>2016-01-04 10:05:00</td>\n",
       "      <td>3591.4</td>\n",
       "      <td>3597.4</td>\n",
       "      <td>3589.2</td>\n",
       "      <td>-7</td>\n",
       "      <td>89435100</td>\n",
       "      <td>27220</td>\n",
       "      <td>83</td>\n",
       "      <td>3597.4</td>\n",
       "      <td>3589.2</td>\n",
       "      <td>...</td>\n",
       "      <td>3603.918218</td>\n",
       "      <td>-7.869899</td>\n",
       "      <td>116.8</td>\n",
       "      <td>107.833333</td>\n",
       "      <td>130.615385</td>\n",
       "      <td>-13.815385</td>\n",
       "      <td>108.108493</td>\n",
       "      <td>112.767026</td>\n",
       "      <td>118.750345</td>\n",
       "      <td>-10.641852</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>2016-01-04 10:06:00</td>\n",
       "      <td>3588.0</td>\n",
       "      <td>3592.8</td>\n",
       "      <td>3588.0</td>\n",
       "      <td>-13</td>\n",
       "      <td>91545060</td>\n",
       "      <td>27207</td>\n",
       "      <td>85</td>\n",
       "      <td>3591.4</td>\n",
       "      <td>3588.0</td>\n",
       "      <td>...</td>\n",
       "      <td>3602.570357</td>\n",
       "      <td>-9.204857</td>\n",
       "      <td>120.4</td>\n",
       "      <td>108.833333</td>\n",
       "      <td>129.807692</td>\n",
       "      <td>-9.407692</td>\n",
       "      <td>100.405527</td>\n",
       "      <td>108.447692</td>\n",
       "      <td>115.892563</td>\n",
       "      <td>-15.487036</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>2016-01-04 10:06:00</td>\n",
       "      <td>3580.0</td>\n",
       "      <td>3588.6</td>\n",
       "      <td>3580.0</td>\n",
       "      <td>-4</td>\n",
       "      <td>167710680</td>\n",
       "      <td>27203</td>\n",
       "      <td>156</td>\n",
       "      <td>3586.8</td>\n",
       "      <td>3580.0</td>\n",
       "      <td>...</td>\n",
       "      <td>3600.679276</td>\n",
       "      <td>-11.768995</td>\n",
       "      <td>114.2</td>\n",
       "      <td>113.916667</td>\n",
       "      <td>127.730769</td>\n",
       "      <td>-13.530769</td>\n",
       "      <td>118.937235</td>\n",
       "      <td>115.832122</td>\n",
       "      <td>119.253006</td>\n",
       "      <td>-0.315771</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28</th>\n",
       "      <td>2016-01-04 10:08:00</td>\n",
       "      <td>3568.0</td>\n",
       "      <td>3580.2</td>\n",
       "      <td>3567.2</td>\n",
       "      <td>-1</td>\n",
       "      <td>190875540</td>\n",
       "      <td>27202</td>\n",
       "      <td>178</td>\n",
       "      <td>3580.2</td>\n",
       "      <td>3567.2</td>\n",
       "      <td>...</td>\n",
       "      <td>3597.967546</td>\n",
       "      <td>-16.027413</td>\n",
       "      <td>118.2</td>\n",
       "      <td>124.083333</td>\n",
       "      <td>123.884615</td>\n",
       "      <td>-5.684615</td>\n",
       "      <td>138.624978</td>\n",
       "      <td>125.472289</td>\n",
       "      <td>124.127839</td>\n",
       "      <td>14.497139</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29</th>\n",
       "      <td>2016-01-04 10:09:00</td>\n",
       "      <td>3568.0</td>\n",
       "      <td>3571.4</td>\n",
       "      <td>3565.0</td>\n",
       "      <td>-17</td>\n",
       "      <td>135944700</td>\n",
       "      <td>27185</td>\n",
       "      <td>127</td>\n",
       "      <td>3567.2</td>\n",
       "      <td>3566.6</td>\n",
       "      <td>...</td>\n",
       "      <td>3595.502786</td>\n",
       "      <td>-18.209389</td>\n",
       "      <td>125.8</td>\n",
       "      <td>124.750000</td>\n",
       "      <td>123.000000</td>\n",
       "      <td>2.800000</td>\n",
       "      <td>134.749965</td>\n",
       "      <td>125.708897</td>\n",
       "      <td>124.364067</td>\n",
       "      <td>10.385898</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>35728</th>\n",
       "      <td>2016-08-31 14:20:00</td>\n",
       "      <td>3301.6</td>\n",
       "      <td>3301.6</td>\n",
       "      <td>3299.2</td>\n",
       "      <td>14</td>\n",
       "      <td>30692160</td>\n",
       "      <td>37376</td>\n",
       "      <td>31</td>\n",
       "      <td>3300.8</td>\n",
       "      <td>3300.2</td>\n",
       "      <td>...</td>\n",
       "      <td>3301.519410</td>\n",
       "      <td>-0.199559</td>\n",
       "      <td>24.8</td>\n",
       "      <td>32.166667</td>\n",
       "      <td>35.961538</td>\n",
       "      <td>-11.161538</td>\n",
       "      <td>26.889536</td>\n",
       "      <td>30.047989</td>\n",
       "      <td>33.567610</td>\n",
       "      <td>-6.678075</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>35729</th>\n",
       "      <td>2016-08-31 14:21:00</td>\n",
       "      <td>3302.4</td>\n",
       "      <td>3304.4</td>\n",
       "      <td>3300.2</td>\n",
       "      <td>29</td>\n",
       "      <td>61434300</td>\n",
       "      <td>37405</td>\n",
       "      <td>62</td>\n",
       "      <td>3301.6</td>\n",
       "      <td>3302.4</td>\n",
       "      <td>...</td>\n",
       "      <td>3301.584639</td>\n",
       "      <td>0.095262</td>\n",
       "      <td>31.8</td>\n",
       "      <td>33.750000</td>\n",
       "      <td>37.307692</td>\n",
       "      <td>-5.507692</td>\n",
       "      <td>38.593024</td>\n",
       "      <td>34.963683</td>\n",
       "      <td>35.673713</td>\n",
       "      <td>2.919311</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>35730</th>\n",
       "      <td>2016-08-31 14:22:00</td>\n",
       "      <td>3304.4</td>\n",
       "      <td>3305.0</td>\n",
       "      <td>3302.4</td>\n",
       "      <td>22</td>\n",
       "      <td>42620280</td>\n",
       "      <td>37427</td>\n",
       "      <td>43</td>\n",
       "      <td>3302.4</td>\n",
       "      <td>3303.2</td>\n",
       "      <td>...</td>\n",
       "      <td>3301.793184</td>\n",
       "      <td>0.793416</td>\n",
       "      <td>36.2</td>\n",
       "      <td>33.333333</td>\n",
       "      <td>37.384615</td>\n",
       "      <td>-1.184615</td>\n",
       "      <td>40.062016</td>\n",
       "      <td>36.200039</td>\n",
       "      <td>36.216401</td>\n",
       "      <td>3.845615</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>35731</th>\n",
       "      <td>2016-08-31 14:23:00</td>\n",
       "      <td>3304.6</td>\n",
       "      <td>3305.6</td>\n",
       "      <td>3303.2</td>\n",
       "      <td>22</td>\n",
       "      <td>75345540</td>\n",
       "      <td>37449</td>\n",
       "      <td>76</td>\n",
       "      <td>3304.6</td>\n",
       "      <td>3304.6</td>\n",
       "      <td>...</td>\n",
       "      <td>3302.001097</td>\n",
       "      <td>1.256637</td>\n",
       "      <td>46.2</td>\n",
       "      <td>37.083333</td>\n",
       "      <td>38.923077</td>\n",
       "      <td>7.276923</td>\n",
       "      <td>52.041344</td>\n",
       "      <td>42.323110</td>\n",
       "      <td>39.163334</td>\n",
       "      <td>12.878010</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>35732</th>\n",
       "      <td>2016-08-31 14:23:00</td>\n",
       "      <td>3304.6</td>\n",
       "      <td>3305.4</td>\n",
       "      <td>3301.4</td>\n",
       "      <td>40</td>\n",
       "      <td>85243080</td>\n",
       "      <td>37489</td>\n",
       "      <td>86</td>\n",
       "      <td>3304.6</td>\n",
       "      <td>3304.2</td>\n",
       "      <td>...</td>\n",
       "      <td>3302.193608</td>\n",
       "      <td>1.511548</td>\n",
       "      <td>59.6</td>\n",
       "      <td>39.916667</td>\n",
       "      <td>40.307692</td>\n",
       "      <td>19.292308</td>\n",
       "      <td>63.360896</td>\n",
       "      <td>49.042632</td>\n",
       "      <td>42.632717</td>\n",
       "      <td>20.728179</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>35733</th>\n",
       "      <td>2016-08-31 14:24:00</td>\n",
       "      <td>3303.6</td>\n",
       "      <td>3304.6</td>\n",
       "      <td>3303.2</td>\n",
       "      <td>7</td>\n",
       "      <td>30726180</td>\n",
       "      <td>37496</td>\n",
       "      <td>31</td>\n",
       "      <td>3304.2</td>\n",
       "      <td>3303.6</td>\n",
       "      <td>...</td>\n",
       "      <td>3302.297785</td>\n",
       "      <td>1.372319</td>\n",
       "      <td>59.6</td>\n",
       "      <td>40.750000</td>\n",
       "      <td>38.192308</td>\n",
       "      <td>21.407692</td>\n",
       "      <td>52.573931</td>\n",
       "      <td>46.266842</td>\n",
       "      <td>41.771034</td>\n",
       "      <td>10.802896</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>35734</th>\n",
       "      <td>2016-08-31 14:26:00</td>\n",
       "      <td>3304.2</td>\n",
       "      <td>3304.2</td>\n",
       "      <td>3303.2</td>\n",
       "      <td>8</td>\n",
       "      <td>21803700</td>\n",
       "      <td>37504</td>\n",
       "      <td>22</td>\n",
       "      <td>3303.6</td>\n",
       "      <td>3303.2</td>\n",
       "      <td>...</td>\n",
       "      <td>3302.438690</td>\n",
       "      <td>1.408046</td>\n",
       "      <td>51.6</td>\n",
       "      <td>40.250000</td>\n",
       "      <td>37.807692</td>\n",
       "      <td>13.792308</td>\n",
       "      <td>42.382620</td>\n",
       "      <td>42.533482</td>\n",
       "      <td>40.306513</td>\n",
       "      <td>2.076107</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>35735</th>\n",
       "      <td>2016-08-31 14:27:00</td>\n",
       "      <td>3307.0</td>\n",
       "      <td>3309.0</td>\n",
       "      <td>3303.4</td>\n",
       "      <td>9</td>\n",
       "      <td>61494420</td>\n",
       "      <td>37513</td>\n",
       "      <td>62</td>\n",
       "      <td>3304.2</td>\n",
       "      <td>3307.2</td>\n",
       "      <td>...</td>\n",
       "      <td>3302.776565</td>\n",
       "      <td>2.121259</td>\n",
       "      <td>55.4</td>\n",
       "      <td>42.166667</td>\n",
       "      <td>38.384615</td>\n",
       "      <td>17.015385</td>\n",
       "      <td>48.921747</td>\n",
       "      <td>45.528331</td>\n",
       "      <td>41.913438</td>\n",
       "      <td>7.008309</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>35736</th>\n",
       "      <td>2016-08-31 14:28:00</td>\n",
       "      <td>3308.8</td>\n",
       "      <td>3309.0</td>\n",
       "      <td>3305.6</td>\n",
       "      <td>12</td>\n",
       "      <td>47622960</td>\n",
       "      <td>37525</td>\n",
       "      <td>48</td>\n",
       "      <td>3307.0</td>\n",
       "      <td>3307.6</td>\n",
       "      <td>...</td>\n",
       "      <td>3303.222745</td>\n",
       "      <td>2.975804</td>\n",
       "      <td>49.8</td>\n",
       "      <td>43.916667</td>\n",
       "      <td>38.807692</td>\n",
       "      <td>10.992308</td>\n",
       "      <td>48.614498</td>\n",
       "      <td>45.908588</td>\n",
       "      <td>42.364294</td>\n",
       "      <td>6.250203</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>35737</th>\n",
       "      <td>2016-08-31 14:29:00</td>\n",
       "      <td>3309.8</td>\n",
       "      <td>3309.8</td>\n",
       "      <td>3306.8</td>\n",
       "      <td>26</td>\n",
       "      <td>70471860</td>\n",
       "      <td>37551</td>\n",
       "      <td>71</td>\n",
       "      <td>3308.8</td>\n",
       "      <td>3308.6</td>\n",
       "      <td>...</td>\n",
       "      <td>3303.709949</td>\n",
       "      <td>3.689084</td>\n",
       "      <td>46.8</td>\n",
       "      <td>48.083333</td>\n",
       "      <td>40.423077</td>\n",
       "      <td>6.376923</td>\n",
       "      <td>56.076332</td>\n",
       "      <td>49.768805</td>\n",
       "      <td>44.485458</td>\n",
       "      <td>11.590874</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>35738</th>\n",
       "      <td>2016-08-31 14:29:00</td>\n",
       "      <td>3308.0</td>\n",
       "      <td>3309.8</td>\n",
       "      <td>3307.8</td>\n",
       "      <td>8</td>\n",
       "      <td>37720740</td>\n",
       "      <td>37559</td>\n",
       "      <td>38</td>\n",
       "      <td>3309.8</td>\n",
       "      <td>3308.0</td>\n",
       "      <td>...</td>\n",
       "      <td>3304.027731</td>\n",
       "      <td>3.571625</td>\n",
       "      <td>48.2</td>\n",
       "      <td>49.083333</td>\n",
       "      <td>41.038462</td>\n",
       "      <td>7.161538</td>\n",
       "      <td>50.050888</td>\n",
       "      <td>47.958220</td>\n",
       "      <td>44.005054</td>\n",
       "      <td>6.045834</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>35739</th>\n",
       "      <td>2016-08-31 14:30:00</td>\n",
       "      <td>3307.2</td>\n",
       "      <td>3308.6</td>\n",
       "      <td>3307.0</td>\n",
       "      <td>-3</td>\n",
       "      <td>19846320</td>\n",
       "      <td>37556</td>\n",
       "      <td>20</td>\n",
       "      <td>3308.0</td>\n",
       "      <td>3307.0</td>\n",
       "      <td>...</td>\n",
       "      <td>3304.262714</td>\n",
       "      <td>3.203523</td>\n",
       "      <td>47.8</td>\n",
       "      <td>49.166667</td>\n",
       "      <td>40.846154</td>\n",
       "      <td>6.953846</td>\n",
       "      <td>40.033925</td>\n",
       "      <td>43.656955</td>\n",
       "      <td>42.226901</td>\n",
       "      <td>-2.192976</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>35740</th>\n",
       "      <td>2016-08-31 14:32:00</td>\n",
       "      <td>3306.8</td>\n",
       "      <td>3308.2</td>\n",
       "      <td>3306.6</td>\n",
       "      <td>5</td>\n",
       "      <td>33737580</td>\n",
       "      <td>37561</td>\n",
       "      <td>34</td>\n",
       "      <td>3307.2</td>\n",
       "      <td>3306.6</td>\n",
       "      <td>...</td>\n",
       "      <td>3304.450661</td>\n",
       "      <td>2.793497</td>\n",
       "      <td>42.2</td>\n",
       "      <td>49.416667</td>\n",
       "      <td>40.884615</td>\n",
       "      <td>1.315385</td>\n",
       "      <td>38.022617</td>\n",
       "      <td>42.171270</td>\n",
       "      <td>41.617501</td>\n",
       "      <td>-3.594884</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>35741</th>\n",
       "      <td>2016-08-31 14:33:00</td>\n",
       "      <td>3307.0</td>\n",
       "      <td>3308.0</td>\n",
       "      <td>3306.4</td>\n",
       "      <td>1</td>\n",
       "      <td>38690940</td>\n",
       "      <td>37562</td>\n",
       "      <td>39</td>\n",
       "      <td>3307.0</td>\n",
       "      <td>3306.4</td>\n",
       "      <td>...</td>\n",
       "      <td>3304.639501</td>\n",
       "      <td>2.523271</td>\n",
       "      <td>40.4</td>\n",
       "      <td>47.500000</td>\n",
       "      <td>41.384615</td>\n",
       "      <td>-0.984615</td>\n",
       "      <td>38.348411</td>\n",
       "      <td>41.683382</td>\n",
       "      <td>41.423612</td>\n",
       "      <td>-3.075201</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>35742</th>\n",
       "      <td>2016-08-31 14:33:00</td>\n",
       "      <td>3307.0</td>\n",
       "      <td>3307.2</td>\n",
       "      <td>3306.2</td>\n",
       "      <td>6</td>\n",
       "      <td>31743660</td>\n",
       "      <td>37568</td>\n",
       "      <td>32</td>\n",
       "      <td>3306.4</td>\n",
       "      <td>3306.4</td>\n",
       "      <td>...</td>\n",
       "      <td>3304.814353</td>\n",
       "      <td>2.294162</td>\n",
       "      <td>32.6</td>\n",
       "      <td>46.583333</td>\n",
       "      <td>40.384615</td>\n",
       "      <td>-7.784615</td>\n",
       "      <td>36.232274</td>\n",
       "      <td>40.193631</td>\n",
       "      <td>40.725567</td>\n",
       "      <td>-4.493293</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>35743</th>\n",
       "      <td>2016-08-31 14:34:00</td>\n",
       "      <td>3307.0</td>\n",
       "      <td>3308.0</td>\n",
       "      <td>3306.6</td>\n",
       "      <td>4</td>\n",
       "      <td>30758820</td>\n",
       "      <td>37572</td>\n",
       "      <td>31</td>\n",
       "      <td>3307.2</td>\n",
       "      <td>3306.2</td>\n",
       "      <td>...</td>\n",
       "      <td>3304.976252</td>\n",
       "      <td>2.096091</td>\n",
       "      <td>31.2</td>\n",
       "      <td>42.833333</td>\n",
       "      <td>39.923077</td>\n",
       "      <td>-8.723077</td>\n",
       "      <td>34.488183</td>\n",
       "      <td>38.779226</td>\n",
       "      <td>40.005155</td>\n",
       "      <td>-5.516972</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>35744</th>\n",
       "      <td>2016-08-31 14:36:00</td>\n",
       "      <td>3305.2</td>\n",
       "      <td>3307.0</td>\n",
       "      <td>3305.0</td>\n",
       "      <td>10</td>\n",
       "      <td>32726820</td>\n",
       "      <td>37582</td>\n",
       "      <td>33</td>\n",
       "      <td>3307.0</td>\n",
       "      <td>3305.0</td>\n",
       "      <td>...</td>\n",
       "      <td>3304.992826</td>\n",
       "      <td>1.455402</td>\n",
       "      <td>33.8</td>\n",
       "      <td>38.416667</td>\n",
       "      <td>39.346154</td>\n",
       "      <td>-5.546154</td>\n",
       "      <td>33.992122</td>\n",
       "      <td>37.890114</td>\n",
       "      <td>39.486254</td>\n",
       "      <td>-5.494132</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>35745</th>\n",
       "      <td>2016-08-31 14:37:00</td>\n",
       "      <td>3306.6</td>\n",
       "      <td>3307.6</td>\n",
       "      <td>3305.4</td>\n",
       "      <td>9</td>\n",
       "      <td>32736780</td>\n",
       "      <td>37593</td>\n",
       "      <td>33</td>\n",
       "      <td>3305.4</td>\n",
       "      <td>3306.6</td>\n",
       "      <td>...</td>\n",
       "      <td>3305.111876</td>\n",
       "      <td>1.386943</td>\n",
       "      <td>33.6</td>\n",
       "      <td>38.583333</td>\n",
       "      <td>39.423077</td>\n",
       "      <td>-5.823077</td>\n",
       "      <td>33.661415</td>\n",
       "      <td>37.137789</td>\n",
       "      <td>39.005791</td>\n",
       "      <td>-5.344376</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>35746</th>\n",
       "      <td>2016-08-31 14:37:00</td>\n",
       "      <td>3306.0</td>\n",
       "      <td>3306.6</td>\n",
       "      <td>3305.2</td>\n",
       "      <td>2</td>\n",
       "      <td>27770820</td>\n",
       "      <td>37584</td>\n",
       "      <td>28</td>\n",
       "      <td>3305.8</td>\n",
       "      <td>3305.4</td>\n",
       "      <td>...</td>\n",
       "      <td>3305.177663</td>\n",
       "      <td>1.154883</td>\n",
       "      <td>31.4</td>\n",
       "      <td>39.083333</td>\n",
       "      <td>38.500000</td>\n",
       "      <td>-7.100000</td>\n",
       "      <td>31.774276</td>\n",
       "      <td>35.731975</td>\n",
       "      <td>38.190547</td>\n",
       "      <td>-6.416271</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>35747</th>\n",
       "      <td>2016-08-31 14:39:00</td>\n",
       "      <td>3305.8</td>\n",
       "      <td>3307.4</td>\n",
       "      <td>3305.8</td>\n",
       "      <td>13</td>\n",
       "      <td>38687640</td>\n",
       "      <td>37606</td>\n",
       "      <td>39</td>\n",
       "      <td>3306.6</td>\n",
       "      <td>3306.0</td>\n",
       "      <td>...</td>\n",
       "      <td>3305.223762</td>\n",
       "      <td>0.931269</td>\n",
       "      <td>32.8</td>\n",
       "      <td>37.166667</td>\n",
       "      <td>39.192308</td>\n",
       "      <td>-6.392308</td>\n",
       "      <td>34.182851</td>\n",
       "      <td>36.234748</td>\n",
       "      <td>38.250507</td>\n",
       "      <td>-4.067656</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>35748</th>\n",
       "      <td>2016-08-31 14:40:00</td>\n",
       "      <td>3307.0</td>\n",
       "      <td>3307.0</td>\n",
       "      <td>3305.4</td>\n",
       "      <td>17</td>\n",
       "      <td>47606100</td>\n",
       "      <td>37623</td>\n",
       "      <td>48</td>\n",
       "      <td>3305.8</td>\n",
       "      <td>3306.4</td>\n",
       "      <td>...</td>\n",
       "      <td>3305.355335</td>\n",
       "      <td>1.081352</td>\n",
       "      <td>36.2</td>\n",
       "      <td>37.166667</td>\n",
       "      <td>39.961538</td>\n",
       "      <td>-3.761538</td>\n",
       "      <td>38.788567</td>\n",
       "      <td>38.044787</td>\n",
       "      <td>38.972691</td>\n",
       "      <td>-0.184124</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>35749</th>\n",
       "      <td>2016-08-31 14:41:00</td>\n",
       "      <td>3307.2</td>\n",
       "      <td>3308.0</td>\n",
       "      <td>3306.4</td>\n",
       "      <td>16</td>\n",
       "      <td>47622480</td>\n",
       "      <td>37639</td>\n",
       "      <td>48</td>\n",
       "      <td>3307.0</td>\n",
       "      <td>3307.2</td>\n",
       "      <td>...</td>\n",
       "      <td>3305.491977</td>\n",
       "      <td>1.199148</td>\n",
       "      <td>39.2</td>\n",
       "      <td>35.250000</td>\n",
       "      <td>40.307692</td>\n",
       "      <td>-1.107692</td>\n",
       "      <td>41.859045</td>\n",
       "      <td>39.576358</td>\n",
       "      <td>39.641381</td>\n",
       "      <td>2.217664</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>35750</th>\n",
       "      <td>2016-08-31 14:41:00</td>\n",
       "      <td>3306.2</td>\n",
       "      <td>3307.4</td>\n",
       "      <td>3305.6</td>\n",
       "      <td>27</td>\n",
       "      <td>60509280</td>\n",
       "      <td>37666</td>\n",
       "      <td>61</td>\n",
       "      <td>3307.2</td>\n",
       "      <td>3305.8</td>\n",
       "      <td>...</td>\n",
       "      <td>3305.544423</td>\n",
       "      <td>0.982993</td>\n",
       "      <td>44.8</td>\n",
       "      <td>37.166667</td>\n",
       "      <td>41.615385</td>\n",
       "      <td>3.184615</td>\n",
       "      <td>48.239363</td>\n",
       "      <td>42.872303</td>\n",
       "      <td>41.223501</td>\n",
       "      <td>7.015862</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>35751</th>\n",
       "      <td>2016-08-31 14:42:00</td>\n",
       "      <td>3306.2</td>\n",
       "      <td>3307.0</td>\n",
       "      <td>3306.0</td>\n",
       "      <td>13</td>\n",
       "      <td>39678300</td>\n",
       "      <td>37679</td>\n",
       "      <td>40</td>\n",
       "      <td>3306.2</td>\n",
       "      <td>3306.0</td>\n",
       "      <td>...</td>\n",
       "      <td>3305.592985</td>\n",
       "      <td>0.825293</td>\n",
       "      <td>47.2</td>\n",
       "      <td>38.833333</td>\n",
       "      <td>42.346154</td>\n",
       "      <td>4.853846</td>\n",
       "      <td>45.492909</td>\n",
       "      <td>42.430410</td>\n",
       "      <td>41.132871</td>\n",
       "      <td>4.360038</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>35752</th>\n",
       "      <td>2016-08-31 14:44:00</td>\n",
       "      <td>3306.6</td>\n",
       "      <td>3307.4</td>\n",
       "      <td>3305.8</td>\n",
       "      <td>6</td>\n",
       "      <td>46622640</td>\n",
       "      <td>37685</td>\n",
       "      <td>47</td>\n",
       "      <td>3307.2</td>\n",
       "      <td>3306.2</td>\n",
       "      <td>...</td>\n",
       "      <td>3305.667578</td>\n",
       "      <td>0.811274</td>\n",
       "      <td>48.8</td>\n",
       "      <td>39.916667</td>\n",
       "      <td>43.153846</td>\n",
       "      <td>5.646154</td>\n",
       "      <td>45.995273</td>\n",
       "      <td>43.133424</td>\n",
       "      <td>41.567473</td>\n",
       "      <td>4.427799</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>35753</th>\n",
       "      <td>2016-08-31 14:45:00</td>\n",
       "      <td>3306.6</td>\n",
       "      <td>3307.2</td>\n",
       "      <td>3305.8</td>\n",
       "      <td>4</td>\n",
       "      <td>38684280</td>\n",
       "      <td>37689</td>\n",
       "      <td>39</td>\n",
       "      <td>3306.2</td>\n",
       "      <td>3306.6</td>\n",
       "      <td>...</td>\n",
       "      <td>3305.736647</td>\n",
       "      <td>0.782588</td>\n",
       "      <td>47.0</td>\n",
       "      <td>39.916667</td>\n",
       "      <td>43.923077</td>\n",
       "      <td>3.076923</td>\n",
       "      <td>43.663515</td>\n",
       "      <td>42.497513</td>\n",
       "      <td>41.377290</td>\n",
       "      <td>2.286225</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>35754</th>\n",
       "      <td>2016-08-31 14:46:00</td>\n",
       "      <td>3306.2</td>\n",
       "      <td>3307.2</td>\n",
       "      <td>3305.6</td>\n",
       "      <td>7</td>\n",
       "      <td>51579780</td>\n",
       "      <td>37696</td>\n",
       "      <td>52</td>\n",
       "      <td>3306.6</td>\n",
       "      <td>3305.8</td>\n",
       "      <td>...</td>\n",
       "      <td>3305.770969</td>\n",
       "      <td>0.641854</td>\n",
       "      <td>47.8</td>\n",
       "      <td>41.583333</td>\n",
       "      <td>44.730769</td>\n",
       "      <td>3.069231</td>\n",
       "      <td>46.442343</td>\n",
       "      <td>43.959434</td>\n",
       "      <td>42.164157</td>\n",
       "      <td>4.278186</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>35755</th>\n",
       "      <td>2016-08-31 14:47:00</td>\n",
       "      <td>3304.2</td>\n",
       "      <td>3306.8</td>\n",
       "      <td>3304.2</td>\n",
       "      <td>29</td>\n",
       "      <td>80316660</td>\n",
       "      <td>37725</td>\n",
       "      <td>81</td>\n",
       "      <td>3305.8</td>\n",
       "      <td>3304.2</td>\n",
       "      <td>...</td>\n",
       "      <td>3305.654601</td>\n",
       "      <td>0.020614</td>\n",
       "      <td>51.8</td>\n",
       "      <td>45.750000</td>\n",
       "      <td>45.461538</td>\n",
       "      <td>6.338462</td>\n",
       "      <td>57.961562</td>\n",
       "      <td>49.657983</td>\n",
       "      <td>45.040887</td>\n",
       "      <td>12.920676</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>35756</th>\n",
       "      <td>2016-08-31 14:47:00</td>\n",
       "      <td>3304.8</td>\n",
       "      <td>3305.4</td>\n",
       "      <td>3303.8</td>\n",
       "      <td>11</td>\n",
       "      <td>60475860</td>\n",
       "      <td>37736</td>\n",
       "      <td>61</td>\n",
       "      <td>3304.2</td>\n",
       "      <td>3304.8</td>\n",
       "      <td>...</td>\n",
       "      <td>3305.591297</td>\n",
       "      <td>-0.207820</td>\n",
       "      <td>56.0</td>\n",
       "      <td>48.083333</td>\n",
       "      <td>46.153846</td>\n",
       "      <td>9.846154</td>\n",
       "      <td>58.974375</td>\n",
       "      <td>51.402908</td>\n",
       "      <td>46.223043</td>\n",
       "      <td>12.751332</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>35757</th>\n",
       "      <td>2016-08-31 14:49:00</td>\n",
       "      <td>3305.0</td>\n",
       "      <td>3306.2</td>\n",
       "      <td>3304.0</td>\n",
       "      <td>12</td>\n",
       "      <td>74366280</td>\n",
       "      <td>37748</td>\n",
       "      <td>75</td>\n",
       "      <td>3305.0</td>\n",
       "      <td>3305.0</td>\n",
       "      <td>...</td>\n",
       "      <td>3305.547497</td>\n",
       "      <td>-0.291846</td>\n",
       "      <td>61.6</td>\n",
       "      <td>51.583333</td>\n",
       "      <td>46.115385</td>\n",
       "      <td>15.484615</td>\n",
       "      <td>64.316250</td>\n",
       "      <td>55.033230</td>\n",
       "      <td>48.354670</td>\n",
       "      <td>15.961580</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>35758 rows × 29 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                     Time  Latestprice  MaxPrice  MinPrice  Stockup  \\\n",
       "0     2016-01-04 09:40:00       3640.4    3646.0    3640.2      -63   \n",
       "1     2016-01-04 09:41:00       3625.8    3641.4    3624.4      -79   \n",
       "2     2016-01-04 09:42:00       3618.8    3626.8    3612.6     -110   \n",
       "3     2016-01-04 09:43:00       3617.0    3620.2    3616.0      -81   \n",
       "4     2016-01-04 09:44:00       3618.0    3618.8    3613.0      -66   \n",
       "5     2016-01-04 09:44:00       3621.0    3621.6    3618.0      -47   \n",
       "6     2016-01-04 09:46:00       3614.2    3621.4    3614.2      -46   \n",
       "7     2016-01-04 09:46:00       3601.2    3615.6    3600.0      -98   \n",
       "8     2016-01-04 09:47:00       3602.2    3608.6    3600.4      -68   \n",
       "9     2016-01-04 09:49:00       3604.6    3608.4    3599.0      -70   \n",
       "10    2016-01-04 09:50:00       3602.4    3606.0    3599.0      -39   \n",
       "11    2016-01-04 09:51:00       3605.2    3607.6    3602.2      -28   \n",
       "12    2016-01-04 09:52:00       3605.8    3605.8    3602.2       -9   \n",
       "13    2016-01-04 09:53:00       3605.0    3606.0    3602.8      -13   \n",
       "14    2016-01-04 09:54:00       3606.0    3606.0    3604.2      -27   \n",
       "15    2016-01-04 09:55:00       3608.8    3609.0    3605.4      -23   \n",
       "16    2016-01-04 09:56:00       3607.0    3609.2    3605.4      -19   \n",
       "17    2016-01-04 09:57:00       3601.4    3607.0    3601.4      -44   \n",
       "18    2016-01-04 09:57:00       3606.8    3606.8    3594.0      -16   \n",
       "19    2016-01-04 09:58:00       3607.0    3607.8    3603.4       -4   \n",
       "20    2016-01-04 09:59:00       3613.0    3613.6    3605.4      -35   \n",
       "21    2016-01-04 10:01:00       3607.8    3613.6    3607.8      -30   \n",
       "22    2016-01-04 10:02:00       3593.8    3607.8    3591.2      -58   \n",
       "23    2016-01-04 10:03:00       3589.8    3594.4    3588.4      -39   \n",
       "24    2016-01-04 10:04:00       3597.4    3597.8    3589.0      -37   \n",
       "25    2016-01-04 10:05:00       3591.4    3597.4    3589.2       -7   \n",
       "26    2016-01-04 10:06:00       3588.0    3592.8    3588.0      -13   \n",
       "27    2016-01-04 10:06:00       3580.0    3588.6    3580.0       -4   \n",
       "28    2016-01-04 10:08:00       3568.0    3580.2    3567.2       -1   \n",
       "29    2016-01-04 10:09:00       3568.0    3571.4    3565.0      -17   \n",
       "...                   ...          ...       ...       ...      ...   \n",
       "35728 2016-08-31 14:20:00       3301.6    3301.6    3299.2       14   \n",
       "35729 2016-08-31 14:21:00       3302.4    3304.4    3300.2       29   \n",
       "35730 2016-08-31 14:22:00       3304.4    3305.0    3302.4       22   \n",
       "35731 2016-08-31 14:23:00       3304.6    3305.6    3303.2       22   \n",
       "35732 2016-08-31 14:23:00       3304.6    3305.4    3301.4       40   \n",
       "35733 2016-08-31 14:24:00       3303.6    3304.6    3303.2        7   \n",
       "35734 2016-08-31 14:26:00       3304.2    3304.2    3303.2        8   \n",
       "35735 2016-08-31 14:27:00       3307.0    3309.0    3303.4        9   \n",
       "35736 2016-08-31 14:28:00       3308.8    3309.0    3305.6       12   \n",
       "35737 2016-08-31 14:29:00       3309.8    3309.8    3306.8       26   \n",
       "35738 2016-08-31 14:29:00       3308.0    3309.8    3307.8        8   \n",
       "35739 2016-08-31 14:30:00       3307.2    3308.6    3307.0       -3   \n",
       "35740 2016-08-31 14:32:00       3306.8    3308.2    3306.6        5   \n",
       "35741 2016-08-31 14:33:00       3307.0    3308.0    3306.4        1   \n",
       "35742 2016-08-31 14:33:00       3307.0    3307.2    3306.2        6   \n",
       "35743 2016-08-31 14:34:00       3307.0    3308.0    3306.6        4   \n",
       "35744 2016-08-31 14:36:00       3305.2    3307.0    3305.0       10   \n",
       "35745 2016-08-31 14:37:00       3306.6    3307.6    3305.4        9   \n",
       "35746 2016-08-31 14:37:00       3306.0    3306.6    3305.2        2   \n",
       "35747 2016-08-31 14:39:00       3305.8    3307.4    3305.8       13   \n",
       "35748 2016-08-31 14:40:00       3307.0    3307.0    3305.4       17   \n",
       "35749 2016-08-31 14:41:00       3307.2    3308.0    3306.4       16   \n",
       "35750 2016-08-31 14:41:00       3306.2    3307.4    3305.6       27   \n",
       "35751 2016-08-31 14:42:00       3306.2    3307.0    3306.0       13   \n",
       "35752 2016-08-31 14:44:00       3306.6    3307.4    3305.8        6   \n",
       "35753 2016-08-31 14:45:00       3306.6    3307.2    3305.8        4   \n",
       "35754 2016-08-31 14:46:00       3306.2    3307.2    3305.6        7   \n",
       "35755 2016-08-31 14:47:00       3304.2    3306.8    3304.2       29   \n",
       "35756 2016-08-31 14:47:00       3304.8    3305.4    3303.8       11   \n",
       "35757 2016-08-31 14:49:00       3305.0    3306.2    3304.0       12   \n",
       "\n",
       "        Turnover  Position  Volume  First.Latestprice  Last.Buy1price  \\\n",
       "0      115844340     28315     106             3644.8          3640.2   \n",
       "1      228902820     28236     210             3640.4          3625.0   \n",
       "2      301745580     28126     278             3625.4          3619.2   \n",
       "3      162817740     28045     150             3618.8          3616.8   \n",
       "4      143205060     27979     132             3616.8          3618.0   \n",
       "5      111857580     27931     103             3618.2          3621.0   \n",
       "6      120504420     27885     111             3621.0          3612.8   \n",
       "7      372121500     27787     344             3614.2          3601.0   \n",
       "8      195712320     27719     181             3601.2          3602.2   \n",
       "9      198897300     27649     184             3602.0          3603.4   \n",
       "10     127536900     27610     118             3604.6          3602.8   \n",
       "11      83269080     27582      77             3602.4          3603.4   \n",
       "12      65952540     27573      61             3603.4          3604.6   \n",
       "13      50825100     27560      47             3605.8          3604.2   \n",
       "14      78953280     27533      73             3604.2          3605.2   \n",
       "15     102802020     27510      95             3606.0          3608.6   \n",
       "16      60597360     27491      56             3609.0          3607.0   \n",
       "17     128675580     27447     119             3606.4          3601.4   \n",
       "18     176006520     27431     163             3601.4          3604.2   \n",
       "19      97367760     27428      90             3604.4          3606.6   \n",
       "20     123478800     27391     114             3607.0          3612.4   \n",
       "21      72574440     27361      67             3612.4          3607.8   \n",
       "22     201761820     27303     187             3607.8          3592.2   \n",
       "23     170214000     27264     158             3592.2          3589.2   \n",
       "24      95919060     27227      89             3589.0          3594.8   \n",
       "25      89435100     27220      83             3597.4          3589.2   \n",
       "26      91545060     27207      85             3591.4          3588.0   \n",
       "27     167710680     27203     156             3586.8          3580.0   \n",
       "28     190875540     27202     178             3580.2          3567.2   \n",
       "29     135944700     27185     127             3567.2          3566.6   \n",
       "...          ...       ...     ...                ...             ...   \n",
       "35728   30692160     37376      31             3300.8          3300.2   \n",
       "35729   61434300     37405      62             3301.6          3302.4   \n",
       "35730   42620280     37427      43             3302.4          3303.2   \n",
       "35731   75345540     37449      76             3304.6          3304.6   \n",
       "35732   85243080     37489      86             3304.6          3304.2   \n",
       "35733   30726180     37496      31             3304.2          3303.6   \n",
       "35734   21803700     37504      22             3303.6          3303.2   \n",
       "35735   61494420     37513      62             3304.2          3307.2   \n",
       "35736   47622960     37525      48             3307.0          3307.6   \n",
       "35737   70471860     37551      71             3308.8          3308.6   \n",
       "35738   37720740     37559      38             3309.8          3308.0   \n",
       "35739   19846320     37556      20             3308.0          3307.0   \n",
       "35740   33737580     37561      34             3307.2          3306.6   \n",
       "35741   38690940     37562      39             3307.0          3306.4   \n",
       "35742   31743660     37568      32             3306.4          3306.4   \n",
       "35743   30758820     37572      31             3307.2          3306.2   \n",
       "35744   32726820     37582      33             3307.0          3305.0   \n",
       "35745   32736780     37593      33             3305.4          3306.6   \n",
       "35746   27770820     37584      28             3305.8          3305.4   \n",
       "35747   38687640     37606      39             3306.6          3306.0   \n",
       "35748   47606100     37623      48             3305.8          3306.4   \n",
       "35749   47622480     37639      48             3307.0          3307.2   \n",
       "35750   60509280     37666      61             3307.2          3305.8   \n",
       "35751   39678300     37679      40             3306.2          3306.0   \n",
       "35752   46622640     37685      47             3307.2          3306.2   \n",
       "35753   38684280     37689      39             3306.2          3306.6   \n",
       "35754   51579780     37696      52             3306.6          3305.8   \n",
       "35755   80316660     37725      81             3305.8          3304.2   \n",
       "35756   60475860     37736      61             3304.2          3304.8   \n",
       "35757   74366280     37748      75             3305.0          3305.0   \n",
       "\n",
       "            ...              EMA_26  Dis_EMA5_26  Vol_MA_5   Vol_MA_12  \\\n",
       "0           ...         3640.400000     0.000000       NaN         NaN   \n",
       "1           ...         3632.819231    -1.179231       NaN         NaN   \n",
       "2           ...         3627.782257    -2.224363       NaN         NaN   \n",
       "3           ...         3624.768009    -2.764932       NaN         NaN   \n",
       "4           ...         3623.198480    -2.732129     175.2         NaN   \n",
       "5           ...         3622.758142    -2.096789     174.6         NaN   \n",
       "6           ...         3621.236121    -2.862444     154.8         NaN   \n",
       "7           ...         3618.007805    -5.591120     168.0         NaN   \n",
       "8           ...         3615.664742    -6.744570     174.2         NaN   \n",
       "9           ...         3614.137915    -6.683214     184.6         NaN   \n",
       "10          ...         3612.615504    -6.865410     187.6         NaN   \n",
       "11          ...         3611.704392    -6.139087     180.8  166.166667   \n",
       "12          ...         3611.012694    -5.368753     124.2  162.416667   \n",
       "13          ...         3610.337397    -4.908841      97.4  148.833333   \n",
       "14          ...         3609.868197    -4.248723      75.2  131.750000   \n",
       "15          ...         3609.756454    -3.075189      70.6  127.166667   \n",
       "16          ...         3609.476650    -2.689032      66.4  120.833333   \n",
       "17          ...         3608.678691    -3.688162      78.0  122.166667   \n",
       "18          ...         3608.497558    -2.903600     101.2  126.500000   \n",
       "19          ...         3608.356327    -2.293547     104.6  105.333333   \n",
       "20          ...         3608.785576    -0.409925     108.4   99.750000   \n",
       "21          ...         3608.696115    -0.512373     110.6   90.000000   \n",
       "22          ...         3607.366193    -3.977459     124.2   95.750000   \n",
       "23          ...         3605.821377    -6.962490     123.2  102.500000   \n",
       "24          ...         3605.090910    -6.718338     123.0  104.833333   \n",
       "25          ...         3603.918218    -7.869899     116.8  107.833333   \n",
       "26          ...         3602.570357    -9.204857     120.4  108.833333   \n",
       "27          ...         3600.679276   -11.768995     114.2  113.916667   \n",
       "28          ...         3597.967546   -16.027413     118.2  124.083333   \n",
       "29          ...         3595.502786   -18.209389     125.8  124.750000   \n",
       "...         ...                 ...          ...       ...         ...   \n",
       "35728       ...         3301.519410    -0.199559      24.8   32.166667   \n",
       "35729       ...         3301.584639     0.095262      31.8   33.750000   \n",
       "35730       ...         3301.793184     0.793416      36.2   33.333333   \n",
       "35731       ...         3302.001097     1.256637      46.2   37.083333   \n",
       "35732       ...         3302.193608     1.511548      59.6   39.916667   \n",
       "35733       ...         3302.297785     1.372319      59.6   40.750000   \n",
       "35734       ...         3302.438690     1.408046      51.6   40.250000   \n",
       "35735       ...         3302.776565     2.121259      55.4   42.166667   \n",
       "35736       ...         3303.222745     2.975804      49.8   43.916667   \n",
       "35737       ...         3303.709949     3.689084      46.8   48.083333   \n",
       "35738       ...         3304.027731     3.571625      48.2   49.083333   \n",
       "35739       ...         3304.262714     3.203523      47.8   49.166667   \n",
       "35740       ...         3304.450661     2.793497      42.2   49.416667   \n",
       "35741       ...         3304.639501     2.523271      40.4   47.500000   \n",
       "35742       ...         3304.814353     2.294162      32.6   46.583333   \n",
       "35743       ...         3304.976252     2.096091      31.2   42.833333   \n",
       "35744       ...         3304.992826     1.455402      33.8   38.416667   \n",
       "35745       ...         3305.111876     1.386943      33.6   38.583333   \n",
       "35746       ...         3305.177663     1.154883      31.4   39.083333   \n",
       "35747       ...         3305.223762     0.931269      32.8   37.166667   \n",
       "35748       ...         3305.355335     1.081352      36.2   37.166667   \n",
       "35749       ...         3305.491977     1.199148      39.2   35.250000   \n",
       "35750       ...         3305.544423     0.982993      44.8   37.166667   \n",
       "35751       ...         3305.592985     0.825293      47.2   38.833333   \n",
       "35752       ...         3305.667578     0.811274      48.8   39.916667   \n",
       "35753       ...         3305.736647     0.782588      47.0   39.916667   \n",
       "35754       ...         3305.770969     0.641854      47.8   41.583333   \n",
       "35755       ...         3305.654601     0.020614      51.8   45.750000   \n",
       "35756       ...         3305.591297    -0.207820      56.0   48.083333   \n",
       "35757       ...         3305.547497    -0.291846      61.6   51.583333   \n",
       "\n",
       "        Vol_MA_26  Dis_Vol_MA5_26   Vol_EMA_5  Vol_EMA_12  Vol_EMA_26  \\\n",
       "0             NaN             NaN  106.000000  106.000000  106.000000   \n",
       "1             NaN             NaN  168.400000  162.333333  160.000000   \n",
       "2             NaN             NaN  220.315789  207.478060  202.396254   \n",
       "3             NaN             NaN  191.107692  189.334483  187.748551   \n",
       "4             NaN             NaN  168.417062  173.756909  174.820232   \n",
       "5             NaN             NaN  144.512782  156.559257  160.435213   \n",
       "6             NaN             NaN  132.647402  146.392868  151.643416   \n",
       "7             NaN             NaN  205.958763  187.630431  182.636828   \n",
       "8             NaN             NaN  197.416984  186.318696  182.394214   \n",
       "9             NaN             NaN  192.865730  185.879304  182.615797   \n",
       "10            NaN             NaN  167.618604  173.459028  174.235108   \n",
       "11            NaN             NaN  137.177785  156.308929  162.288243   \n",
       "12            NaN             NaN  111.654043  139.759679  150.422343   \n",
       "13            NaN             NaN   90.028618  123.965667  138.806783   \n",
       "14            NaN             NaN   84.339420  115.428045  131.688101   \n",
       "15            NaN             NaN   87.898365  112.052150  127.850225   \n",
       "16            NaN             NaN   77.254774  102.893605  120.556799   \n",
       "17            NaN             NaN   91.179271  105.500394  120.402990   \n",
       "18            NaN             NaN  115.130318  114.732720  124.509958   \n",
       "19            NaN             NaN  106.751026  110.788050  121.255407   \n",
       "20            NaN             NaN  109.167835  111.297454  120.584737   \n",
       "21            NaN             NaN   95.110011  104.305246  115.720827   \n",
       "22            NaN             NaN  125.742737  117.306330  122.084617   \n",
       "23            NaN             NaN  136.495797  123.682599  125.243107   \n",
       "24            NaN             NaN  120.663237  118.263609  122.099394   \n",
       "25     130.615385      -13.815385  108.108493  112.767026  118.750345   \n",
       "26     129.807692       -9.407692  100.405527  108.447692  115.892563   \n",
       "27     127.730769      -13.530769  118.937235  115.832122  119.253006   \n",
       "28     123.884615       -5.684615  138.624978  125.472289  124.127839   \n",
       "29     123.000000        2.800000  134.749965  125.708897  124.364067   \n",
       "...           ...             ...         ...         ...         ...   \n",
       "35728   35.961538      -11.161538   26.889536   30.047989   33.567610   \n",
       "35729   37.307692       -5.507692   38.593024   34.963683   35.673713   \n",
       "35730   37.384615       -1.184615   40.062016   36.200039   36.216401   \n",
       "35731   38.923077        7.276923   52.041344   42.323110   39.163334   \n",
       "35732   40.307692       19.292308   63.360896   49.042632   42.632717   \n",
       "35733   38.192308       21.407692   52.573931   46.266842   41.771034   \n",
       "35734   37.807692       13.792308   42.382620   42.533482   40.306513   \n",
       "35735   38.384615       17.015385   48.921747   45.528331   41.913438   \n",
       "35736   38.807692       10.992308   48.614498   45.908588   42.364294   \n",
       "35737   40.423077        6.376923   56.076332   49.768805   44.485458   \n",
       "35738   41.038462        7.161538   50.050888   47.958220   44.005054   \n",
       "35739   40.846154        6.953846   40.033925   43.656955   42.226901   \n",
       "35740   40.884615        1.315385   38.022617   42.171270   41.617501   \n",
       "35741   41.384615       -0.984615   38.348411   41.683382   41.423612   \n",
       "35742   40.384615       -7.784615   36.232274   40.193631   40.725567   \n",
       "35743   39.923077       -8.723077   34.488183   38.779226   40.005155   \n",
       "35744   39.346154       -5.546154   33.992122   37.890114   39.486254   \n",
       "35745   39.423077       -5.823077   33.661415   37.137789   39.005791   \n",
       "35746   38.500000       -7.100000   31.774276   35.731975   38.190547   \n",
       "35747   39.192308       -6.392308   34.182851   36.234748   38.250507   \n",
       "35748   39.961538       -3.761538   38.788567   38.044787   38.972691   \n",
       "35749   40.307692       -1.107692   41.859045   39.576358   39.641381   \n",
       "35750   41.615385        3.184615   48.239363   42.872303   41.223501   \n",
       "35751   42.346154        4.853846   45.492909   42.430410   41.132871   \n",
       "35752   43.153846        5.646154   45.995273   43.133424   41.567473   \n",
       "35753   43.923077        3.076923   43.663515   42.497513   41.377290   \n",
       "35754   44.730769        3.069231   46.442343   43.959434   42.164157   \n",
       "35755   45.461538        6.338462   57.961562   49.657983   45.040887   \n",
       "35756   46.153846        9.846154   58.974375   51.402908   46.223043   \n",
       "35757   46.115385       15.484615   64.316250   55.033230   48.354670   \n",
       "\n",
       "       Dis_Vol_EMA5_26  \n",
       "0             0.000000  \n",
       "1             8.400000  \n",
       "2            17.919535  \n",
       "3             3.359141  \n",
       "4            -6.403171  \n",
       "5           -15.922431  \n",
       "6           -18.996015  \n",
       "7            23.321935  \n",
       "8            15.022770  \n",
       "9            10.249933  \n",
       "10           -6.616503  \n",
       "11          -25.110458  \n",
       "12          -38.768300  \n",
       "13          -48.778166  \n",
       "14          -47.348682  \n",
       "15          -39.951860  \n",
       "16          -43.302026  \n",
       "17          -29.223719  \n",
       "18           -9.379640  \n",
       "19          -14.504382  \n",
       "20          -11.416902  \n",
       "21          -20.610816  \n",
       "22            3.658120  \n",
       "23           11.252689  \n",
       "24           -1.436157  \n",
       "25          -10.641852  \n",
       "26          -15.487036  \n",
       "27           -0.315771  \n",
       "28           14.497139  \n",
       "29           10.385898  \n",
       "...                ...  \n",
       "35728        -6.678075  \n",
       "35729         2.919311  \n",
       "35730         3.845615  \n",
       "35731        12.878010  \n",
       "35732        20.728179  \n",
       "35733        10.802896  \n",
       "35734         2.076107  \n",
       "35735         7.008309  \n",
       "35736         6.250203  \n",
       "35737        11.590874  \n",
       "35738         6.045834  \n",
       "35739        -2.192976  \n",
       "35740        -3.594884  \n",
       "35741        -3.075201  \n",
       "35742        -4.493293  \n",
       "35743        -5.516972  \n",
       "35744        -5.494132  \n",
       "35745        -5.344376  \n",
       "35746        -6.416271  \n",
       "35747        -4.067656  \n",
       "35748        -0.184124  \n",
       "35749         2.217664  \n",
       "35750         7.015862  \n",
       "35751         4.360038  \n",
       "35752         4.427799  \n",
       "35753         2.286225  \n",
       "35754         4.278186  \n",
       "35755        12.920676  \n",
       "35756        12.751332  \n",
       "35757        15.961580  \n",
       "\n",
       "[35758 rows x 29 columns]"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "newdata1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {
    "collapsed": false,
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "移动平均线\n"
     ]
    },
    {
     "data": {
      "image/png": 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JS0sjIODyiZbq1WvQtGkwq1erfJiIiIiIiIhcm8FgwMWlLLt27bjq2pYtG/H29snTFhNz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bFnTymPPnoBrbYfMlltwsIWIghin/YrEhLacPr0KXJzc6s7FEBMtNRoV8pLO3fuQnLyuQpv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hhBBCCCGEEMJNOp2OmJg4lwItjtQ0rBf1wfj+XK+tn5m5A8BrGS3an7ahzdqD+ZprvTKf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\nTYayMoIWAAAAAEC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      "text/plain": [
       "<matplotlib.figure.Figure at 0x7fd1de88e850>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "指数平滑移动平均线\n"
     ]
    },
    {
     "data": {
      "image/png": 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Kj8/NEy0VKlSkbt0AVq1S+TARERERERG5PYPBQJEihdm+fWuma5s2rcfV1S1DW3T0CaKj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+famULWuiRw975sxRYZRftYUQz4nAwL2o1WoCAprRvXsvbt26yZkzpywyt16v5+bN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BeavUgD2wa1jkMkktKw4bvY2rYjI2MWCQntcHIaTIMGr2Nj0+iWa7OysoiJ2ccnn3xm1hpj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hYeTm5nRo7KjwsYR6aFme/H6Hxte3Dmta0VJTV0N2WZZUtAghhBBCCCGE6DQREVGtJloA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\noghaAMCpgpbZg2frx2MbtT1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      "text/plain": [
       "<matplotlib.figure.Figure at 0x7fd1df629f90>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#作出某一段的MA和EMA图\n",
    "plt.figure(figsize=(20,8))\n",
    "print u\"移动平均线\"\n",
    "plt.plot(newdata1['Latestprice'][1200:1400],\"black\", label=\"Latestprice\",linewidth=1)\n",
    "plt.plot(newdata1['MA_5'][1200:1400], \"r-\", label=\"MA_5\",linewidth=1)\n",
    "plt.plot(newdata1['MA_12'][1200:1400], \"y\", label=\"MA_12\",linewidth=1)\n",
    "plt.plot(newdata1['MA_26'][1200:1400], \"blue\", label=\"MA_26\",linewidth=1)\n",
    "plt.legend()\n",
    "plt.show()\n",
    "print u\"指数平滑移动平均线\"\n",
    "plt.figure(figsize=(20,8))\n",
    "plt.plot(newdata1['Latestprice'][1200:1400], \"black\", label=\"Latestprice\",linewidth=1)\n",
    "plt.plot(newdata1['MA_5'][1200:1400], \"g-\", label=\"MA_5\",linewidth=1)\n",
    "plt.plot(newdata1['MA_12'][1200:1400], \"y-\", label=\"MA_12\",linewidth=1)\n",
    "plt.plot(newdata1['EMA_26'][1200:1400], \"b-\", label=\"EMA_26\",linewidth=1)\n",
    "plt.legend()\n",
    "plt.show() "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "均线分析\n",
    "\n",
    "移动平均线对价格波动较为明显，抗干扰能力比较差。\n",
    "指数平滑移动平均线对价格波动不是较为明显，反应的是一个大体趋势，对微小震荡有比较好的容忍能力。\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 添加平滑异同平均线MACD指标"
   ]
  },
  {
   "cell_type": "raw",
   "metadata": {},
   "source": [
    "参数设置：SHORT=12,LONG=26,MID=9\n",
    "\n",
    "    选择慢速指数移动平均线SHORT=10和快速移动平均线LONG=20\n",
    "    计算离差值DIFF，反应两种移动平均线的之间的距离.\n",
    "    计算DIFF的MID日指数平滑移动平均，记为DEA\n",
    "    用DIFF减去DEA,得到MACD.\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "指数平滑移动平均线\n"
     ]
    },
    {
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i0YyxsUclSXXqFH9Fi729verWvUvR0dGWigUAAAAAwHWFhNTT5s07rR2jzKHQ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\niEwI45Czc4Vk9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doCSZuyFG1aNkFpAQXUERyHcVccRRFHUcYFBhxBUQRFmAHcBvVGxRv3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\nbi9Xub3s2D8ry5RflqcHv7lfc354T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      "text/plain": [
       "<matplotlib.figure.Figure at 0x7fd1df75cfd0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "DIFF与DEA离差值，柱状图\n"
     ]
    },
    {
     "data": {
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IkhYtcmrp0iO/g1BcLH32mV3Tp7t0221u/fAD82FVBALSvfeGyTQNRUaaeuih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\ndfD6607++kvHCy8YmTDB3mhERXOZAD+RvXslSkq0P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loeRqMKyRu0L4cGe9ze6RyPUwGd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\nulaJEhERERERERHpVPLy4B//CJGfvyUhMnRogpkzG3nssXCrJ0o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      "text/plain": [
       "<matplotlib.figure.Figure at 0x7fd1dc2ca890>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# EMA_12是快速指数移动平均线，EMA_26是慢速指数移动平均线      \n",
    "# 计算DIFF\n",
    "newdata1['DIFF_12_26'] = newdata1['EMA_12'] - newdata1['EMA_26']\n",
    "# 计算离差平均值DEA，也就是计算离差值的指数平滑移动平均，设置为5分钟的指数平滑曲线\n",
    "newdata1['DEA_12_26'] =  pd.ewma(newdata1['DIFF_12_26'],span = 9)\n",
    "# 计算MACD值\n",
    "newdata1['MACD'] = 2*(newdata1['DIFF_12_26'] - newdata1['DEA_12_26'])\n",
    "# 对MACD柱状图进行处理，便于画图\n",
    "macd_pos = [] \n",
    "macd_neg = []\n",
    "for j in range(len(newdata1['MACD'])):\n",
    "    if newdata1['MACD'].iloc[j] >= 0:\n",
    "        macd_pos.append(newdata1['MACD'].iloc[j])\n",
    "        macd_neg.append(0)\n",
    "    else:\n",
    "        macd_neg.append(newdata1['MACD'].iloc[j])\n",
    "        macd_pos.append(0)\n",
    "print u\"指数平滑移动平均线\"\n",
    "plt.figure(figsize=(20,8))\n",
    "plt.plot(newdata1['Latestprice'][1200:1400], \"black\", label=\"Latestprice\",linewidth=1)\n",
    "plt.plot(newdata1['EMA_12'][1200:1400], \"g-\", label=\"EMA_12\",linewidth=1)\n",
    "plt.plot(newdata1['EMA_26'][1200:1400], \"b-\", label=\"EMA_26\",linewidth=1)        \n",
    "plt.legend()\n",
    "plt.show()\n",
    "print u\"DIFF与DEA离差值，柱状图\"\n",
    "plt.figure(figsize=(20,8))\n",
    "plt.plot(newdata1['DIFF_12_26'][1200:1400],'b',label='DIFF')\n",
    "plt.plot(newdata1['DEA_12_26'][1200:1400],\"y\",label='DEA')\n",
    "plt.bar(range(1200,1400),macd_pos[1200:1400],0.6,color=\"red\", label=\"MACD_POS\")\n",
    "plt.bar(range(1200,1400),macd_neg[1200:1400],0.6,color=\"green\", label=\"MACD_NEG\")\n",
    "plt.legend()\n",
    "plt.show()\n",
    "train_data_addMA = newdata1\n",
    "train_data_addMA.to_csv(path + 'train_data_addMA.csv') # 存储为加MA特征的数据"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {
    "collapsed": true
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Time</th>\n",
       "      <th>Latestprice</th>\n",
       "      <th>MaxPrice</th>\n",
       "      <th>MinPrice</th>\n",
       "      <th>Stockup</th>\n",
       "      <th>Turnover</th>\n",
       "      <th>Position</th>\n",
       "      <th>Volume</th>\n",
       "      <th>First.Latestprice</th>\n",
       "      <th>Last.Buy1price</th>\n",
       "      <th>...</th>\n",
       "      <th>Vol_MA_12</th>\n",
       "      <th>Vol_MA_26</th>\n",
       "      <th>Dis_Vol_MA5_26</th>\n",
       "      <th>Vol_EMA_5</th>\n",
       "      <th>Vol_EMA_12</th>\n",
       "      <th>Vol_EMA_26</th>\n",
       "      <th>Dis_Vol_EMA5_26</th>\n",
       "      <th>DIFF_12_26</th>\n",
       "      <th>DEA_12_26</th>\n",
       "      <th>MACD</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2016-01-04 09:40:00</td>\n",
       "      <td>3640.4</td>\n",
       "      <td>3646.0</td>\n",
       "      <td>3640.2</td>\n",
       "      <td>-63</td>\n",
       "      <td>115844340</td>\n",
       "      <td>28315</td>\n",
       "      <td>106</td>\n",
       "      <td>3644.8</td>\n",
       "      <td>3640.2</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>106.000000</td>\n",
       "      <td>106.000000</td>\n",
       "      <td>106.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2016-01-04 09:41:00</td>\n",
       "      <td>3625.8</td>\n",
       "      <td>3641.4</td>\n",
       "      <td>3624.4</td>\n",
       "      <td>-79</td>\n",
       "      <td>228902820</td>\n",
       "      <td>28236</td>\n",
       "      <td>210</td>\n",
       "      <td>3640.4</td>\n",
       "      <td>3625.0</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>168.400000</td>\n",
       "      <td>162.333333</td>\n",
       "      <td>160.000000</td>\n",
       "      <td>8.400000</td>\n",
       "      <td>-0.327564</td>\n",
       "      <td>-0.181980</td>\n",
       "      <td>-0.291168</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2016-01-04 09:42:00</td>\n",
       "      <td>3618.8</td>\n",
       "      <td>3626.8</td>\n",
       "      <td>3612.6</td>\n",
       "      <td>-110</td>\n",
       "      <td>301745580</td>\n",
       "      <td>28126</td>\n",
       "      <td>278</td>\n",
       "      <td>3625.4</td>\n",
       "      <td>3619.2</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>220.315789</td>\n",
       "      <td>207.478060</td>\n",
       "      <td>202.396254</td>\n",
       "      <td>17.919535</td>\n",
       "      <td>-0.634451</td>\n",
       "      <td>-0.367419</td>\n",
       "      <td>-0.534064</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2016-01-04 09:43:00</td>\n",
       "      <td>3617.0</td>\n",
       "      <td>3620.2</td>\n",
       "      <td>3616.0</td>\n",
       "      <td>-81</td>\n",
       "      <td>162817740</td>\n",
       "      <td>28045</td>\n",
       "      <td>150</td>\n",
       "      <td>3618.8</td>\n",
       "      <td>3616.8</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>191.107692</td>\n",
       "      <td>189.334483</td>\n",
       "      <td>187.748551</td>\n",
       "      <td>3.359141</td>\n",
       "      <td>-0.823469</td>\n",
       "      <td>-0.521908</td>\n",
       "      <td>-0.603123</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2016-01-04 09:44:00</td>\n",
       "      <td>3618.0</td>\n",
       "      <td>3618.8</td>\n",
       "      <td>3613.0</td>\n",
       "      <td>-66</td>\n",
       "      <td>143205060</td>\n",
       "      <td>27979</td>\n",
       "      <td>132</td>\n",
       "      <td>3616.8</td>\n",
       "      <td>3618.0</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>168.417062</td>\n",
       "      <td>173.756909</td>\n",
       "      <td>174.820232</td>\n",
       "      <td>-6.403171</td>\n",
       "      <td>-0.869050</td>\n",
       "      <td>-0.625175</td>\n",
       "      <td>-0.487751</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>2016-01-04 09:44:00</td>\n",
       "      <td>3621.0</td>\n",
       "      <td>3621.6</td>\n",
       "      <td>3618.0</td>\n",
       "      <td>-47</td>\n",
       "      <td>111857580</td>\n",
       "      <td>27931</td>\n",
       "      <td>103</td>\n",
       "      <td>3618.2</td>\n",
       "      <td>3621.0</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>144.512782</td>\n",
       "      <td>156.559257</td>\n",
       "      <td>160.435213</td>\n",
       "      <td>-15.922431</td>\n",
       "      <td>-0.751834</td>\n",
       "      <td>-0.659506</td>\n",
       "      <td>-0.184655</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>2016-01-04 09:46:00</td>\n",
       "      <td>3614.2</td>\n",
       "      <td>3621.4</td>\n",
       "      <td>3614.2</td>\n",
       "      <td>-46</td>\n",
       "      <td>120504420</td>\n",
       "      <td>27885</td>\n",
       "      <td>111</td>\n",
       "      <td>3621.0</td>\n",
       "      <td>3612.8</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>132.647402</td>\n",
       "      <td>146.392868</td>\n",
       "      <td>151.643416</td>\n",
       "      <td>-18.996015</td>\n",
       "      <td>-0.971763</td>\n",
       "      <td>-0.738530</td>\n",
       "      <td>-0.466465</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>2016-01-04 09:46:00</td>\n",
       "      <td>3601.2</td>\n",
       "      <td>3615.6</td>\n",
       "      <td>3600.0</td>\n",
       "      <td>-98</td>\n",
       "      <td>372121500</td>\n",
       "      <td>27787</td>\n",
       "      <td>344</td>\n",
       "      <td>3614.2</td>\n",
       "      <td>3601.0</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>205.958763</td>\n",
       "      <td>187.630431</td>\n",
       "      <td>182.636828</td>\n",
       "      <td>23.321935</td>\n",
       "      <td>-1.721885</td>\n",
       "      <td>-0.974849</td>\n",
       "      <td>-1.494072</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>2016-01-04 09:47:00</td>\n",
       "      <td>3602.2</td>\n",
       "      <td>3608.6</td>\n",
       "      <td>3600.4</td>\n",
       "      <td>-68</td>\n",
       "      <td>195712320</td>\n",
       "      <td>27719</td>\n",
       "      <td>181</td>\n",
       "      <td>3601.2</td>\n",
       "      <td>3602.2</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>197.416984</td>\n",
       "      <td>186.318696</td>\n",
       "      <td>182.394214</td>\n",
       "      <td>15.022770</td>\n",
       "      <td>-2.165518</td>\n",
       "      <td>-1.249899</td>\n",
       "      <td>-1.831237</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>2016-01-04 09:49:00</td>\n",
       "      <td>3604.6</td>\n",
       "      <td>3608.4</td>\n",
       "      <td>3599.0</td>\n",
       "      <td>-70</td>\n",
       "      <td>198897300</td>\n",
       "      <td>27649</td>\n",
       "      <td>184</td>\n",
       "      <td>3602.0</td>\n",
       "      <td>3603.4</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>192.865730</td>\n",
       "      <td>185.879304</td>\n",
       "      <td>182.615797</td>\n",
       "      <td>10.249933</td>\n",
       "      <td>-2.325090</td>\n",
       "      <td>-1.490804</td>\n",
       "      <td>-1.668572</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>2016-01-04 09:50:00</td>\n",
       "      <td>3602.4</td>\n",
       "      <td>3606.0</td>\n",
       "      <td>3599.0</td>\n",
       "      <td>-39</td>\n",
       "      <td>127536900</td>\n",
       "      <td>27610</td>\n",
       "      <td>118</td>\n",
       "      <td>3604.6</td>\n",
       "      <td>3602.8</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>167.618604</td>\n",
       "      <td>173.459028</td>\n",
       "      <td>174.235108</td>\n",
       "      <td>-6.616503</td>\n",
       "      <td>-2.524999</td>\n",
       "      <td>-1.717080</td>\n",
       "      <td>-1.615838</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>2016-01-04 09:51:00</td>\n",
       "      <td>3605.2</td>\n",
       "      <td>3607.6</td>\n",
       "      <td>3602.2</td>\n",
       "      <td>-28</td>\n",
       "      <td>83269080</td>\n",
       "      <td>27582</td>\n",
       "      <td>77</td>\n",
       "      <td>3602.4</td>\n",
       "      <td>3603.4</td>\n",
       "      <td>...</td>\n",
       "      <td>166.166667</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>137.177785</td>\n",
       "      <td>156.308929</td>\n",
       "      <td>162.288243</td>\n",
       "      <td>-25.110458</td>\n",
       "      <td>-2.483403</td>\n",
       "      <td>-1.881654</td>\n",
       "      <td>-1.203498</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>2016-01-04 09:52:00</td>\n",
       "      <td>3605.8</td>\n",
       "      <td>3605.8</td>\n",
       "      <td>3602.2</td>\n",
       "      <td>-9</td>\n",
       "      <td>65952540</td>\n",
       "      <td>27573</td>\n",
       "      <td>61</td>\n",
       "      <td>3603.4</td>\n",
       "      <td>3604.6</td>\n",
       "      <td>...</td>\n",
       "      <td>162.416667</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>111.654043</td>\n",
       "      <td>139.759679</td>\n",
       "      <td>150.422343</td>\n",
       "      <td>-38.768300</td>\n",
       "      <td>-2.385718</td>\n",
       "      <td>-1.988332</td>\n",
       "      <td>-0.794773</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>2016-01-04 09:53:00</td>\n",
       "      <td>3605.0</td>\n",
       "      <td>3606.0</td>\n",
       "      <td>3602.8</td>\n",
       "      <td>-13</td>\n",
       "      <td>50825100</td>\n",
       "      <td>27560</td>\n",
       "      <td>47</td>\n",
       "      <td>3605.8</td>\n",
       "      <td>3604.2</td>\n",
       "      <td>...</td>\n",
       "      <td>148.833333</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>90.028618</td>\n",
       "      <td>123.965667</td>\n",
       "      <td>138.806783</td>\n",
       "      <td>-48.778166</td>\n",
       "      <td>-2.327979</td>\n",
       "      <td>-2.059386</td>\n",
       "      <td>-0.537186</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>2016-01-04 09:54:00</td>\n",
       "      <td>3606.0</td>\n",
       "      <td>3606.0</td>\n",
       "      <td>3604.2</td>\n",
       "      <td>-27</td>\n",
       "      <td>78953280</td>\n",
       "      <td>27533</td>\n",
       "      <td>73</td>\n",
       "      <td>3604.2</td>\n",
       "      <td>3605.2</td>\n",
       "      <td>...</td>\n",
       "      <td>131.750000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>84.339420</td>\n",
       "      <td>115.428045</td>\n",
       "      <td>131.688101</td>\n",
       "      <td>-47.348682</td>\n",
       "      <td>-2.195391</td>\n",
       "      <td>-2.087579</td>\n",
       "      <td>-0.215624</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>2016-01-04 09:55:00</td>\n",
       "      <td>3608.8</td>\n",
       "      <td>3609.0</td>\n",
       "      <td>3605.4</td>\n",
       "      <td>-23</td>\n",
       "      <td>102802020</td>\n",
       "      <td>27510</td>\n",
       "      <td>95</td>\n",
       "      <td>3606.0</td>\n",
       "      <td>3608.6</td>\n",
       "      <td>...</td>\n",
       "      <td>127.166667</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>87.898365</td>\n",
       "      <td>112.052150</td>\n",
       "      <td>127.850225</td>\n",
       "      <td>-39.951860</td>\n",
       "      <td>-1.897371</td>\n",
       "      <td>-2.048436</td>\n",
       "      <td>0.302129</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>2016-01-04 09:56:00</td>\n",
       "      <td>3607.0</td>\n",
       "      <td>3609.2</td>\n",
       "      <td>3605.4</td>\n",
       "      <td>-19</td>\n",
       "      <td>60597360</td>\n",
       "      <td>27491</td>\n",
       "      <td>56</td>\n",
       "      <td>3609.0</td>\n",
       "      <td>3607.0</td>\n",
       "      <td>...</td>\n",
       "      <td>120.833333</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>77.254774</td>\n",
       "      <td>102.893605</td>\n",
       "      <td>120.556799</td>\n",
       "      <td>-43.302026</td>\n",
       "      <td>-1.757935</td>\n",
       "      <td>-1.988997</td>\n",
       "      <td>0.462124</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>2016-01-04 09:57:00</td>\n",
       "      <td>3601.4</td>\n",
       "      <td>3607.0</td>\n",
       "      <td>3601.4</td>\n",
       "      <td>-44</td>\n",
       "      <td>128675580</td>\n",
       "      <td>27447</td>\n",
       "      <td>119</td>\n",
       "      <td>3606.4</td>\n",
       "      <td>3601.4</td>\n",
       "      <td>...</td>\n",
       "      <td>122.166667</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>91.179271</td>\n",
       "      <td>105.500394</td>\n",
       "      <td>120.402990</td>\n",
       "      <td>-29.223719</td>\n",
       "      <td>-1.982649</td>\n",
       "      <td>-1.987704</td>\n",
       "      <td>0.010111</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>2016-01-04 09:57:00</td>\n",
       "      <td>3606.8</td>\n",
       "      <td>3606.8</td>\n",
       "      <td>3594.0</td>\n",
       "      <td>-16</td>\n",
       "      <td>176006520</td>\n",
       "      <td>27431</td>\n",
       "      <td>163</td>\n",
       "      <td>3601.4</td>\n",
       "      <td>3604.2</td>\n",
       "      <td>...</td>\n",
       "      <td>126.500000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>115.130318</td>\n",
       "      <td>114.732720</td>\n",
       "      <td>124.509958</td>\n",
       "      <td>-9.379640</td>\n",
       "      <td>-1.784824</td>\n",
       "      <td>-1.946535</td>\n",
       "      <td>0.323422</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>2016-01-04 09:58:00</td>\n",
       "      <td>3607.0</td>\n",
       "      <td>3607.8</td>\n",
       "      <td>3603.4</td>\n",
       "      <td>-4</td>\n",
       "      <td>97367760</td>\n",
       "      <td>27428</td>\n",
       "      <td>90</td>\n",
       "      <td>3604.4</td>\n",
       "      <td>3606.6</td>\n",
       "      <td>...</td>\n",
       "      <td>105.333333</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>106.751026</td>\n",
       "      <td>110.788050</td>\n",
       "      <td>121.255407</td>\n",
       "      <td>-14.504382</td>\n",
       "      <td>-1.597776</td>\n",
       "      <td>-1.875970</td>\n",
       "      <td>0.556387</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>2016-01-04 09:59:00</td>\n",
       "      <td>3613.0</td>\n",
       "      <td>3613.6</td>\n",
       "      <td>3605.4</td>\n",
       "      <td>-35</td>\n",
       "      <td>123478800</td>\n",
       "      <td>27391</td>\n",
       "      <td>114</td>\n",
       "      <td>3607.0</td>\n",
       "      <td>3612.4</td>\n",
       "      <td>...</td>\n",
       "      <td>99.750000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>109.167835</td>\n",
       "      <td>111.297454</td>\n",
       "      <td>120.584737</td>\n",
       "      <td>-11.416902</td>\n",
       "      <td>-1.037152</td>\n",
       "      <td>-1.706644</td>\n",
       "      <td>1.338984</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>2016-01-04 10:01:00</td>\n",
       "      <td>3607.8</td>\n",
       "      <td>3613.6</td>\n",
       "      <td>3607.8</td>\n",
       "      <td>-30</td>\n",
       "      <td>72574440</td>\n",
       "      <td>27361</td>\n",
       "      <td>67</td>\n",
       "      <td>3612.4</td>\n",
       "      <td>3607.8</td>\n",
       "      <td>...</td>\n",
       "      <td>90.000000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>95.110011</td>\n",
       "      <td>104.305246</td>\n",
       "      <td>115.720827</td>\n",
       "      <td>-20.610816</td>\n",
       "      <td>-0.939550</td>\n",
       "      <td>-1.552085</td>\n",
       "      <td>1.225070</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>2016-01-04 10:02:00</td>\n",
       "      <td>3593.8</td>\n",
       "      <td>3607.8</td>\n",
       "      <td>3591.2</td>\n",
       "      <td>-58</td>\n",
       "      <td>201761820</td>\n",
       "      <td>27303</td>\n",
       "      <td>187</td>\n",
       "      <td>3607.8</td>\n",
       "      <td>3592.2</td>\n",
       "      <td>...</td>\n",
       "      <td>95.750000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>125.742737</td>\n",
       "      <td>117.306330</td>\n",
       "      <td>122.084617</td>\n",
       "      <td>3.658120</td>\n",
       "      <td>-1.803848</td>\n",
       "      <td>-1.602737</td>\n",
       "      <td>-0.402222</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>2016-01-04 10:03:00</td>\n",
       "      <td>3589.8</td>\n",
       "      <td>3594.4</td>\n",
       "      <td>3588.4</td>\n",
       "      <td>-39</td>\n",
       "      <td>170214000</td>\n",
       "      <td>27264</td>\n",
       "      <td>158</td>\n",
       "      <td>3592.2</td>\n",
       "      <td>3589.2</td>\n",
       "      <td>...</td>\n",
       "      <td>102.500000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>136.495797</td>\n",
       "      <td>123.682599</td>\n",
       "      <td>125.243107</td>\n",
       "      <td>11.252689</td>\n",
       "      <td>-2.728825</td>\n",
       "      <td>-1.829023</td>\n",
       "      <td>-1.799605</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>2016-01-04 10:04:00</td>\n",
       "      <td>3597.4</td>\n",
       "      <td>3597.8</td>\n",
       "      <td>3589.0</td>\n",
       "      <td>-37</td>\n",
       "      <td>95919060</td>\n",
       "      <td>27227</td>\n",
       "      <td>89</td>\n",
       "      <td>3589.0</td>\n",
       "      <td>3594.8</td>\n",
       "      <td>...</td>\n",
       "      <td>104.833333</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>120.663237</td>\n",
       "      <td>118.263609</td>\n",
       "      <td>122.099394</td>\n",
       "      <td>-1.436157</td>\n",
       "      <td>-2.887792</td>\n",
       "      <td>-2.041580</td>\n",
       "      <td>-1.692425</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>2016-01-04 10:05:00</td>\n",
       "      <td>3591.4</td>\n",
       "      <td>3597.4</td>\n",
       "      <td>3589.2</td>\n",
       "      <td>-7</td>\n",
       "      <td>89435100</td>\n",
       "      <td>27220</td>\n",
       "      <td>83</td>\n",
       "      <td>3597.4</td>\n",
       "      <td>3589.2</td>\n",
       "      <td>...</td>\n",
       "      <td>107.833333</td>\n",
       "      <td>130.615385</td>\n",
       "      <td>-13.815385</td>\n",
       "      <td>108.108493</td>\n",
       "      <td>112.767026</td>\n",
       "      <td>118.750345</td>\n",
       "      <td>-10.641852</td>\n",
       "      <td>-3.398996</td>\n",
       "      <td>-2.313886</td>\n",
       "      <td>-2.170221</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>2016-01-04 10:06:00</td>\n",
       "      <td>3588.0</td>\n",
       "      <td>3592.8</td>\n",
       "      <td>3588.0</td>\n",
       "      <td>-13</td>\n",
       "      <td>91545060</td>\n",
       "      <td>27207</td>\n",
       "      <td>85</td>\n",
       "      <td>3591.4</td>\n",
       "      <td>3588.0</td>\n",
       "      <td>...</td>\n",
       "      <td>108.833333</td>\n",
       "      <td>129.807692</td>\n",
       "      <td>-9.407692</td>\n",
       "      <td>100.405527</td>\n",
       "      <td>108.447692</td>\n",
       "      <td>115.892563</td>\n",
       "      <td>-15.487036</td>\n",
       "      <td>-3.998578</td>\n",
       "      <td>-2.651641</td>\n",
       "      <td>-2.693873</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>2016-01-04 10:06:00</td>\n",
       "      <td>3580.0</td>\n",
       "      <td>3588.6</td>\n",
       "      <td>3580.0</td>\n",
       "      <td>-4</td>\n",
       "      <td>167710680</td>\n",
       "      <td>27203</td>\n",
       "      <td>156</td>\n",
       "      <td>3586.8</td>\n",
       "      <td>3580.0</td>\n",
       "      <td>...</td>\n",
       "      <td>113.916667</td>\n",
       "      <td>127.730769</td>\n",
       "      <td>-13.530769</td>\n",
       "      <td>118.937235</td>\n",
       "      <td>115.832122</td>\n",
       "      <td>119.253006</td>\n",
       "      <td>-0.315771</td>\n",
       "      <td>-4.991522</td>\n",
       "      <td>-3.120524</td>\n",
       "      <td>-3.741995</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28</th>\n",
       "      <td>2016-01-04 10:08:00</td>\n",
       "      <td>3568.0</td>\n",
       "      <td>3580.2</td>\n",
       "      <td>3567.2</td>\n",
       "      <td>-1</td>\n",
       "      <td>190875540</td>\n",
       "      <td>27202</td>\n",
       "      <td>178</td>\n",
       "      <td>3580.2</td>\n",
       "      <td>3567.2</td>\n",
       "      <td>...</td>\n",
       "      <td>124.083333</td>\n",
       "      <td>123.884615</td>\n",
       "      <td>-5.684615</td>\n",
       "      <td>138.624978</td>\n",
       "      <td>125.472289</td>\n",
       "      <td>124.127839</td>\n",
       "      <td>14.497139</td>\n",
       "      <td>-6.573239</td>\n",
       "      <td>-3.812137</td>\n",
       "      <td>-5.522204</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29</th>\n",
       "      <td>2016-01-04 10:09:00</td>\n",
       "      <td>3568.0</td>\n",
       "      <td>3571.4</td>\n",
       "      <td>3565.0</td>\n",
       "      <td>-17</td>\n",
       "      <td>135944700</td>\n",
       "      <td>27185</td>\n",
       "      <td>127</td>\n",
       "      <td>3567.2</td>\n",
       "      <td>3566.6</td>\n",
       "      <td>...</td>\n",
       "      <td>124.750000</td>\n",
       "      <td>123.000000</td>\n",
       "      <td>2.800000</td>\n",
       "      <td>134.749965</td>\n",
       "      <td>125.708897</td>\n",
       "      <td>124.364067</td>\n",
       "      <td>10.385898</td>\n",
       "      <td>-7.731735</td>\n",
       "      <td>-4.597029</td>\n",
       "      <td>-6.269413</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>35728</th>\n",
       "      <td>2016-08-31 14:20:00</td>\n",
       "      <td>3301.6</td>\n",
       "      <td>3301.6</td>\n",
       "      <td>3299.2</td>\n",
       "      <td>14</td>\n",
       "      <td>30692160</td>\n",
       "      <td>37376</td>\n",
       "      <td>31</td>\n",
       "      <td>3300.8</td>\n",
       "      <td>3300.2</td>\n",
       "      <td>...</td>\n",
       "      <td>32.166667</td>\n",
       "      <td>35.961538</td>\n",
       "      <td>-11.161538</td>\n",
       "      <td>26.889536</td>\n",
       "      <td>30.047989</td>\n",
       "      <td>33.567610</td>\n",
       "      <td>-6.678075</td>\n",
       "      <td>-0.404311</td>\n",
       "      <td>-0.697110</td>\n",
       "      <td>0.585599</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>35729</th>\n",
       "      <td>2016-08-31 14:21:00</td>\n",
       "      <td>3302.4</td>\n",
       "      <td>3304.4</td>\n",
       "      <td>3300.2</td>\n",
       "      <td>29</td>\n",
       "      <td>61434300</td>\n",
       "      <td>37405</td>\n",
       "      <td>62</td>\n",
       "      <td>3301.6</td>\n",
       "      <td>3302.4</td>\n",
       "      <td>...</td>\n",
       "      <td>33.750000</td>\n",
       "      <td>37.307692</td>\n",
       "      <td>-5.507692</td>\n",
       "      <td>38.593024</td>\n",
       "      <td>34.963683</td>\n",
       "      <td>35.673713</td>\n",
       "      <td>2.919311</td>\n",
       "      <td>-0.271863</td>\n",
       "      <td>-0.612061</td>\n",
       "      <td>0.680396</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>35730</th>\n",
       "      <td>2016-08-31 14:22:00</td>\n",
       "      <td>3304.4</td>\n",
       "      <td>3305.0</td>\n",
       "      <td>3302.4</td>\n",
       "      <td>22</td>\n",
       "      <td>42620280</td>\n",
       "      <td>37427</td>\n",
       "      <td>43</td>\n",
       "      <td>3302.4</td>\n",
       "      <td>3303.2</td>\n",
       "      <td>...</td>\n",
       "      <td>33.333333</td>\n",
       "      <td>37.384615</td>\n",
       "      <td>-1.184615</td>\n",
       "      <td>40.062016</td>\n",
       "      <td>36.200039</td>\n",
       "      <td>36.216401</td>\n",
       "      <td>3.845615</td>\n",
       "      <td>-0.005450</td>\n",
       "      <td>-0.490739</td>\n",
       "      <td>0.970576</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>35731</th>\n",
       "      <td>2016-08-31 14:23:00</td>\n",
       "      <td>3304.6</td>\n",
       "      <td>3305.6</td>\n",
       "      <td>3303.2</td>\n",
       "      <td>22</td>\n",
       "      <td>75345540</td>\n",
       "      <td>37449</td>\n",
       "      <td>76</td>\n",
       "      <td>3304.6</td>\n",
       "      <td>3304.6</td>\n",
       "      <td>...</td>\n",
       "      <td>37.083333</td>\n",
       "      <td>38.923077</td>\n",
       "      <td>7.276923</td>\n",
       "      <td>52.041344</td>\n",
       "      <td>42.323110</td>\n",
       "      <td>39.163334</td>\n",
       "      <td>12.878010</td>\n",
       "      <td>0.219294</td>\n",
       "      <td>-0.348732</td>\n",
       "      <td>1.136052</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>35732</th>\n",
       "      <td>2016-08-31 14:23:00</td>\n",
       "      <td>3304.6</td>\n",
       "      <td>3305.4</td>\n",
       "      <td>3301.4</td>\n",
       "      <td>40</td>\n",
       "      <td>85243080</td>\n",
       "      <td>37489</td>\n",
       "      <td>86</td>\n",
       "      <td>3304.6</td>\n",
       "      <td>3304.2</td>\n",
       "      <td>...</td>\n",
       "      <td>39.916667</td>\n",
       "      <td>40.307692</td>\n",
       "      <td>19.292308</td>\n",
       "      <td>63.360896</td>\n",
       "      <td>49.042632</td>\n",
       "      <td>42.632717</td>\n",
       "      <td>20.728179</td>\n",
       "      <td>0.392876</td>\n",
       "      <td>-0.200410</td>\n",
       "      <td>1.186573</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>35733</th>\n",
       "      <td>2016-08-31 14:24:00</td>\n",
       "      <td>3303.6</td>\n",
       "      <td>3304.6</td>\n",
       "      <td>3303.2</td>\n",
       "      <td>7</td>\n",
       "      <td>30726180</td>\n",
       "      <td>37496</td>\n",
       "      <td>31</td>\n",
       "      <td>3304.2</td>\n",
       "      <td>3303.6</td>\n",
       "      <td>...</td>\n",
       "      <td>40.750000</td>\n",
       "      <td>38.192308</td>\n",
       "      <td>21.407692</td>\n",
       "      <td>52.573931</td>\n",
       "      <td>46.266842</td>\n",
       "      <td>41.771034</td>\n",
       "      <td>10.802896</td>\n",
       "      <td>0.444624</td>\n",
       "      <td>-0.071403</td>\n",
       "      <td>1.032056</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>35734</th>\n",
       "      <td>2016-08-31 14:26:00</td>\n",
       "      <td>3304.2</td>\n",
       "      <td>3304.2</td>\n",
       "      <td>3303.2</td>\n",
       "      <td>8</td>\n",
       "      <td>21803700</td>\n",
       "      <td>37504</td>\n",
       "      <td>22</td>\n",
       "      <td>3303.6</td>\n",
       "      <td>3303.2</td>\n",
       "      <td>...</td>\n",
       "      <td>40.250000</td>\n",
       "      <td>37.807692</td>\n",
       "      <td>13.792308</td>\n",
       "      <td>42.382620</td>\n",
       "      <td>42.533482</td>\n",
       "      <td>40.306513</td>\n",
       "      <td>2.076107</td>\n",
       "      <td>0.527964</td>\n",
       "      <td>0.048470</td>\n",
       "      <td>0.958988</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>35735</th>\n",
       "      <td>2016-08-31 14:27:00</td>\n",
       "      <td>3307.0</td>\n",
       "      <td>3309.0</td>\n",
       "      <td>3303.4</td>\n",
       "      <td>9</td>\n",
       "      <td>61494420</td>\n",
       "      <td>37513</td>\n",
       "      <td>62</td>\n",
       "      <td>3304.2</td>\n",
       "      <td>3307.2</td>\n",
       "      <td>...</td>\n",
       "      <td>42.166667</td>\n",
       "      <td>38.384615</td>\n",
       "      <td>17.015385</td>\n",
       "      <td>48.921747</td>\n",
       "      <td>45.528331</td>\n",
       "      <td>41.913438</td>\n",
       "      <td>7.008309</td>\n",
       "      <td>0.810604</td>\n",
       "      <td>0.200897</td>\n",
       "      <td>1.219415</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>35736</th>\n",
       "      <td>2016-08-31 14:28:00</td>\n",
       "      <td>3308.8</td>\n",
       "      <td>3309.0</td>\n",
       "      <td>3305.6</td>\n",
       "      <td>12</td>\n",
       "      <td>47622960</td>\n",
       "      <td>37525</td>\n",
       "      <td>48</td>\n",
       "      <td>3307.0</td>\n",
       "      <td>3307.6</td>\n",
       "      <td>...</td>\n",
       "      <td>43.916667</td>\n",
       "      <td>38.807692</td>\n",
       "      <td>10.992308</td>\n",
       "      <td>48.614498</td>\n",
       "      <td>45.908588</td>\n",
       "      <td>42.364294</td>\n",
       "      <td>6.250203</td>\n",
       "      <td>1.166398</td>\n",
       "      <td>0.393997</td>\n",
       "      <td>1.544801</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>35737</th>\n",
       "      <td>2016-08-31 14:29:00</td>\n",
       "      <td>3309.8</td>\n",
       "      <td>3309.8</td>\n",
       "      <td>3306.8</td>\n",
       "      <td>26</td>\n",
       "      <td>70471860</td>\n",
       "      <td>37551</td>\n",
       "      <td>71</td>\n",
       "      <td>3308.8</td>\n",
       "      <td>3308.6</td>\n",
       "      <td>...</td>\n",
       "      <td>48.083333</td>\n",
       "      <td>40.423077</td>\n",
       "      <td>6.376923</td>\n",
       "      <td>56.076332</td>\n",
       "      <td>49.768805</td>\n",
       "      <td>44.485458</td>\n",
       "      <td>11.590874</td>\n",
       "      <td>1.511633</td>\n",
       "      <td>0.617524</td>\n",
       "      <td>1.788218</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>35738</th>\n",
       "      <td>2016-08-31 14:29:00</td>\n",
       "      <td>3308.0</td>\n",
       "      <td>3309.8</td>\n",
       "      <td>3307.8</td>\n",
       "      <td>8</td>\n",
       "      <td>37720740</td>\n",
       "      <td>37559</td>\n",
       "      <td>38</td>\n",
       "      <td>3309.8</td>\n",
       "      <td>3308.0</td>\n",
       "      <td>...</td>\n",
       "      <td>49.083333</td>\n",
       "      <td>41.038462</td>\n",
       "      <td>7.161538</td>\n",
       "      <td>50.050888</td>\n",
       "      <td>47.958220</td>\n",
       "      <td>44.005054</td>\n",
       "      <td>6.045834</td>\n",
       "      <td>1.621301</td>\n",
       "      <td>0.818280</td>\n",
       "      <td>1.606042</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>35739</th>\n",
       "      <td>2016-08-31 14:30:00</td>\n",
       "      <td>3307.2</td>\n",
       "      <td>3308.6</td>\n",
       "      <td>3307.0</td>\n",
       "      <td>-3</td>\n",
       "      <td>19846320</td>\n",
       "      <td>37556</td>\n",
       "      <td>20</td>\n",
       "      <td>3308.0</td>\n",
       "      <td>3307.0</td>\n",
       "      <td>...</td>\n",
       "      <td>49.166667</td>\n",
       "      <td>40.846154</td>\n",
       "      <td>6.953846</td>\n",
       "      <td>40.033925</td>\n",
       "      <td>43.656955</td>\n",
       "      <td>42.226901</td>\n",
       "      <td>-2.192976</td>\n",
       "      <td>1.624928</td>\n",
       "      <td>0.979609</td>\n",
       "      <td>1.290638</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>35740</th>\n",
       "      <td>2016-08-31 14:32:00</td>\n",
       "      <td>3306.8</td>\n",
       "      <td>3308.2</td>\n",
       "      <td>3306.6</td>\n",
       "      <td>5</td>\n",
       "      <td>33737580</td>\n",
       "      <td>37561</td>\n",
       "      <td>34</td>\n",
       "      <td>3307.2</td>\n",
       "      <td>3306.6</td>\n",
       "      <td>...</td>\n",
       "      <td>49.416667</td>\n",
       "      <td>40.884615</td>\n",
       "      <td>1.315385</td>\n",
       "      <td>38.022617</td>\n",
       "      <td>42.171270</td>\n",
       "      <td>41.617501</td>\n",
       "      <td>-3.594884</td>\n",
       "      <td>1.577344</td>\n",
       "      <td>1.099156</td>\n",
       "      <td>0.956375</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>35741</th>\n",
       "      <td>2016-08-31 14:33:00</td>\n",
       "      <td>3307.0</td>\n",
       "      <td>3308.0</td>\n",
       "      <td>3306.4</td>\n",
       "      <td>1</td>\n",
       "      <td>38690940</td>\n",
       "      <td>37562</td>\n",
       "      <td>39</td>\n",
       "      <td>3307.0</td>\n",
       "      <td>3306.4</td>\n",
       "      <td>...</td>\n",
       "      <td>47.500000</td>\n",
       "      <td>41.384615</td>\n",
       "      <td>-0.984615</td>\n",
       "      <td>38.348411</td>\n",
       "      <td>41.683382</td>\n",
       "      <td>41.423612</td>\n",
       "      <td>-3.075201</td>\n",
       "      <td>1.538042</td>\n",
       "      <td>1.186933</td>\n",
       "      <td>0.702217</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>35742</th>\n",
       "      <td>2016-08-31 14:33:00</td>\n",
       "      <td>3307.0</td>\n",
       "      <td>3307.2</td>\n",
       "      <td>3306.2</td>\n",
       "      <td>6</td>\n",
       "      <td>31743660</td>\n",
       "      <td>37568</td>\n",
       "      <td>32</td>\n",
       "      <td>3306.4</td>\n",
       "      <td>3306.4</td>\n",
       "      <td>...</td>\n",
       "      <td>46.583333</td>\n",
       "      <td>40.384615</td>\n",
       "      <td>-7.784615</td>\n",
       "      <td>36.232274</td>\n",
       "      <td>40.193631</td>\n",
       "      <td>40.725567</td>\n",
       "      <td>-4.493293</td>\n",
       "      <td>1.489722</td>\n",
       "      <td>1.247491</td>\n",
       "      <td>0.484462</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>35743</th>\n",
       "      <td>2016-08-31 14:34:00</td>\n",
       "      <td>3307.0</td>\n",
       "      <td>3308.0</td>\n",
       "      <td>3306.6</td>\n",
       "      <td>4</td>\n",
       "      <td>30758820</td>\n",
       "      <td>37572</td>\n",
       "      <td>31</td>\n",
       "      <td>3307.2</td>\n",
       "      <td>3306.2</td>\n",
       "      <td>...</td>\n",
       "      <td>42.833333</td>\n",
       "      <td>39.923077</td>\n",
       "      <td>-8.723077</td>\n",
       "      <td>34.488183</td>\n",
       "      <td>38.779226</td>\n",
       "      <td>40.005155</td>\n",
       "      <td>-5.516972</td>\n",
       "      <td>1.434888</td>\n",
       "      <td>1.284970</td>\n",
       "      <td>0.299834</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>35744</th>\n",
       "      <td>2016-08-31 14:36:00</td>\n",
       "      <td>3305.2</td>\n",
       "      <td>3307.0</td>\n",
       "      <td>3305.0</td>\n",
       "      <td>10</td>\n",
       "      <td>32726820</td>\n",
       "      <td>37582</td>\n",
       "      <td>33</td>\n",
       "      <td>3307.0</td>\n",
       "      <td>3305.0</td>\n",
       "      <td>...</td>\n",
       "      <td>38.416667</td>\n",
       "      <td>39.346154</td>\n",
       "      <td>-5.546154</td>\n",
       "      <td>33.992122</td>\n",
       "      <td>37.890114</td>\n",
       "      <td>39.486254</td>\n",
       "      <td>-5.494132</td>\n",
       "      <td>1.231984</td>\n",
       "      <td>1.274373</td>\n",
       "      <td>-0.084778</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>35745</th>\n",
       "      <td>2016-08-31 14:37:00</td>\n",
       "      <td>3306.6</td>\n",
       "      <td>3307.6</td>\n",
       "      <td>3305.4</td>\n",
       "      <td>9</td>\n",
       "      <td>32736780</td>\n",
       "      <td>37593</td>\n",
       "      <td>33</td>\n",
       "      <td>3305.4</td>\n",
       "      <td>3306.6</td>\n",
       "      <td>...</td>\n",
       "      <td>38.583333</td>\n",
       "      <td>39.423077</td>\n",
       "      <td>-5.823077</td>\n",
       "      <td>33.661415</td>\n",
       "      <td>37.137789</td>\n",
       "      <td>39.005791</td>\n",
       "      <td>-5.344376</td>\n",
       "      <td>1.170656</td>\n",
       "      <td>1.253630</td>\n",
       "      <td>-0.165948</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>35746</th>\n",
       "      <td>2016-08-31 14:37:00</td>\n",
       "      <td>3306.0</td>\n",
       "      <td>3306.6</td>\n",
       "      <td>3305.2</td>\n",
       "      <td>2</td>\n",
       "      <td>27770820</td>\n",
       "      <td>37584</td>\n",
       "      <td>28</td>\n",
       "      <td>3305.8</td>\n",
       "      <td>3305.4</td>\n",
       "      <td>...</td>\n",
       "      <td>39.083333</td>\n",
       "      <td>38.500000</td>\n",
       "      <td>-7.100000</td>\n",
       "      <td>31.774276</td>\n",
       "      <td>35.731975</td>\n",
       "      <td>38.190547</td>\n",
       "      <td>-6.416271</td>\n",
       "      <td>1.061403</td>\n",
       "      <td>1.215184</td>\n",
       "      <td>-0.307564</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>35747</th>\n",
       "      <td>2016-08-31 14:39:00</td>\n",
       "      <td>3305.8</td>\n",
       "      <td>3307.4</td>\n",
       "      <td>3305.8</td>\n",
       "      <td>13</td>\n",
       "      <td>38687640</td>\n",
       "      <td>37606</td>\n",
       "      <td>39</td>\n",
       "      <td>3306.6</td>\n",
       "      <td>3306.0</td>\n",
       "      <td>...</td>\n",
       "      <td>37.166667</td>\n",
       "      <td>39.192308</td>\n",
       "      <td>-6.392308</td>\n",
       "      <td>34.182851</td>\n",
       "      <td>36.234748</td>\n",
       "      <td>38.250507</td>\n",
       "      <td>-4.067656</td>\n",
       "      <td>0.947755</td>\n",
       "      <td>1.161698</td>\n",
       "      <td>-0.427887</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>35748</th>\n",
       "      <td>2016-08-31 14:40:00</td>\n",
       "      <td>3307.0</td>\n",
       "      <td>3307.0</td>\n",
       "      <td>3305.4</td>\n",
       "      <td>17</td>\n",
       "      <td>47606100</td>\n",
       "      <td>37623</td>\n",
       "      <td>48</td>\n",
       "      <td>3305.8</td>\n",
       "      <td>3306.4</td>\n",
       "      <td>...</td>\n",
       "      <td>37.166667</td>\n",
       "      <td>39.961538</td>\n",
       "      <td>-3.761538</td>\n",
       "      <td>38.788567</td>\n",
       "      <td>38.044787</td>\n",
       "      <td>38.972691</td>\n",
       "      <td>-0.184124</td>\n",
       "      <td>0.943641</td>\n",
       "      <td>1.118087</td>\n",
       "      <td>-0.348892</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>35749</th>\n",
       "      <td>2016-08-31 14:41:00</td>\n",
       "      <td>3307.2</td>\n",
       "      <td>3308.0</td>\n",
       "      <td>3306.4</td>\n",
       "      <td>16</td>\n",
       "      <td>47622480</td>\n",
       "      <td>37639</td>\n",
       "      <td>48</td>\n",
       "      <td>3307.0</td>\n",
       "      <td>3307.2</td>\n",
       "      <td>...</td>\n",
       "      <td>35.250000</td>\n",
       "      <td>40.307692</td>\n",
       "      <td>-1.107692</td>\n",
       "      <td>41.859045</td>\n",
       "      <td>39.576358</td>\n",
       "      <td>39.641381</td>\n",
       "      <td>2.217664</td>\n",
       "      <td>0.945618</td>\n",
       "      <td>1.083593</td>\n",
       "      <td>-0.275950</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>35750</th>\n",
       "      <td>2016-08-31 14:41:00</td>\n",
       "      <td>3306.2</td>\n",
       "      <td>3307.4</td>\n",
       "      <td>3305.6</td>\n",
       "      <td>27</td>\n",
       "      <td>60509280</td>\n",
       "      <td>37666</td>\n",
       "      <td>61</td>\n",
       "      <td>3307.2</td>\n",
       "      <td>3305.8</td>\n",
       "      <td>...</td>\n",
       "      <td>37.166667</td>\n",
       "      <td>41.615385</td>\n",
       "      <td>3.184615</td>\n",
       "      <td>48.239363</td>\n",
       "      <td>42.872303</td>\n",
       "      <td>41.223501</td>\n",
       "      <td>7.015862</td>\n",
       "      <td>0.856619</td>\n",
       "      <td>1.038198</td>\n",
       "      <td>-0.363159</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>35751</th>\n",
       "      <td>2016-08-31 14:42:00</td>\n",
       "      <td>3306.2</td>\n",
       "      <td>3307.0</td>\n",
       "      <td>3306.0</td>\n",
       "      <td>13</td>\n",
       "      <td>39678300</td>\n",
       "      <td>37679</td>\n",
       "      <td>40</td>\n",
       "      <td>3306.2</td>\n",
       "      <td>3306.0</td>\n",
       "      <td>...</td>\n",
       "      <td>38.833333</td>\n",
       "      <td>42.346154</td>\n",
       "      <td>4.853846</td>\n",
       "      <td>45.492909</td>\n",
       "      <td>42.430410</td>\n",
       "      <td>41.132871</td>\n",
       "      <td>4.360038</td>\n",
       "      <td>0.777128</td>\n",
       "      <td>0.985984</td>\n",
       "      <td>-0.417712</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>35752</th>\n",
       "      <td>2016-08-31 14:44:00</td>\n",
       "      <td>3306.6</td>\n",
       "      <td>3307.4</td>\n",
       "      <td>3305.8</td>\n",
       "      <td>6</td>\n",
       "      <td>46622640</td>\n",
       "      <td>37685</td>\n",
       "      <td>47</td>\n",
       "      <td>3307.2</td>\n",
       "      <td>3306.2</td>\n",
       "      <td>...</td>\n",
       "      <td>39.916667</td>\n",
       "      <td>43.153846</td>\n",
       "      <td>5.646154</td>\n",
       "      <td>45.995273</td>\n",
       "      <td>43.133424</td>\n",
       "      <td>41.567473</td>\n",
       "      <td>4.427799</td>\n",
       "      <td>0.737902</td>\n",
       "      <td>0.936368</td>\n",
       "      <td>-0.396932</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>35753</th>\n",
       "      <td>2016-08-31 14:45:00</td>\n",
       "      <td>3306.6</td>\n",
       "      <td>3307.2</td>\n",
       "      <td>3305.8</td>\n",
       "      <td>4</td>\n",
       "      <td>38684280</td>\n",
       "      <td>37689</td>\n",
       "      <td>39</td>\n",
       "      <td>3306.2</td>\n",
       "      <td>3306.6</td>\n",
       "      <td>...</td>\n",
       "      <td>39.916667</td>\n",
       "      <td>43.923077</td>\n",
       "      <td>3.076923</td>\n",
       "      <td>43.663515</td>\n",
       "      <td>42.497513</td>\n",
       "      <td>41.377290</td>\n",
       "      <td>2.286225</td>\n",
       "      <td>0.698759</td>\n",
       "      <td>0.888846</td>\n",
       "      <td>-0.380173</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>35754</th>\n",
       "      <td>2016-08-31 14:46:00</td>\n",
       "      <td>3306.2</td>\n",
       "      <td>3307.2</td>\n",
       "      <td>3305.6</td>\n",
       "      <td>7</td>\n",
       "      <td>51579780</td>\n",
       "      <td>37696</td>\n",
       "      <td>52</td>\n",
       "      <td>3306.6</td>\n",
       "      <td>3305.8</td>\n",
       "      <td>...</td>\n",
       "      <td>41.583333</td>\n",
       "      <td>44.730769</td>\n",
       "      <td>3.069231</td>\n",
       "      <td>46.442343</td>\n",
       "      <td>43.959434</td>\n",
       "      <td>42.164157</td>\n",
       "      <td>4.278186</td>\n",
       "      <td>0.628221</td>\n",
       "      <td>0.836721</td>\n",
       "      <td>-0.417001</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>35755</th>\n",
       "      <td>2016-08-31 14:47:00</td>\n",
       "      <td>3304.2</td>\n",
       "      <td>3306.8</td>\n",
       "      <td>3304.2</td>\n",
       "      <td>29</td>\n",
       "      <td>80316660</td>\n",
       "      <td>37725</td>\n",
       "      <td>81</td>\n",
       "      <td>3305.8</td>\n",
       "      <td>3304.2</td>\n",
       "      <td>...</td>\n",
       "      <td>45.750000</td>\n",
       "      <td>45.461538</td>\n",
       "      <td>6.338462</td>\n",
       "      <td>57.961562</td>\n",
       "      <td>49.657983</td>\n",
       "      <td>45.040887</td>\n",
       "      <td>12.920676</td>\n",
       "      <td>0.406252</td>\n",
       "      <td>0.750627</td>\n",
       "      <td>-0.688751</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>35756</th>\n",
       "      <td>2016-08-31 14:47:00</td>\n",
       "      <td>3304.8</td>\n",
       "      <td>3305.4</td>\n",
       "      <td>3303.8</td>\n",
       "      <td>11</td>\n",
       "      <td>60475860</td>\n",
       "      <td>37736</td>\n",
       "      <td>61</td>\n",
       "      <td>3304.2</td>\n",
       "      <td>3304.8</td>\n",
       "      <td>...</td>\n",
       "      <td>48.083333</td>\n",
       "      <td>46.153846</td>\n",
       "      <td>9.846154</td>\n",
       "      <td>58.974375</td>\n",
       "      <td>51.402908</td>\n",
       "      <td>46.223043</td>\n",
       "      <td>12.751332</td>\n",
       "      <td>0.275578</td>\n",
       "      <td>0.655617</td>\n",
       "      <td>-0.760078</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>35757</th>\n",
       "      <td>2016-08-31 14:49:00</td>\n",
       "      <td>3305.0</td>\n",
       "      <td>3306.2</td>\n",
       "      <td>3304.0</td>\n",
       "      <td>12</td>\n",
       "      <td>74366280</td>\n",
       "      <td>37748</td>\n",
       "      <td>75</td>\n",
       "      <td>3305.0</td>\n",
       "      <td>3305.0</td>\n",
       "      <td>...</td>\n",
       "      <td>51.583333</td>\n",
       "      <td>46.115385</td>\n",
       "      <td>15.484615</td>\n",
       "      <td>64.316250</td>\n",
       "      <td>55.033230</td>\n",
       "      <td>48.354670</td>\n",
       "      <td>15.961580</td>\n",
       "      <td>0.186013</td>\n",
       "      <td>0.561696</td>\n",
       "      <td>-0.751368</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>35758 rows × 32 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                     Time  Latestprice  MaxPrice  MinPrice  Stockup  \\\n",
       "0     2016-01-04 09:40:00       3640.4    3646.0    3640.2      -63   \n",
       "1     2016-01-04 09:41:00       3625.8    3641.4    3624.4      -79   \n",
       "2     2016-01-04 09:42:00       3618.8    3626.8    3612.6     -110   \n",
       "3     2016-01-04 09:43:00       3617.0    3620.2    3616.0      -81   \n",
       "4     2016-01-04 09:44:00       3618.0    3618.8    3613.0      -66   \n",
       "5     2016-01-04 09:44:00       3621.0    3621.6    3618.0      -47   \n",
       "6     2016-01-04 09:46:00       3614.2    3621.4    3614.2      -46   \n",
       "7     2016-01-04 09:46:00       3601.2    3615.6    3600.0      -98   \n",
       "8     2016-01-04 09:47:00       3602.2    3608.6    3600.4      -68   \n",
       "9     2016-01-04 09:49:00       3604.6    3608.4    3599.0      -70   \n",
       "10    2016-01-04 09:50:00       3602.4    3606.0    3599.0      -39   \n",
       "11    2016-01-04 09:51:00       3605.2    3607.6    3602.2      -28   \n",
       "12    2016-01-04 09:52:00       3605.8    3605.8    3602.2       -9   \n",
       "13    2016-01-04 09:53:00       3605.0    3606.0    3602.8      -13   \n",
       "14    2016-01-04 09:54:00       3606.0    3606.0    3604.2      -27   \n",
       "15    2016-01-04 09:55:00       3608.8    3609.0    3605.4      -23   \n",
       "16    2016-01-04 09:56:00       3607.0    3609.2    3605.4      -19   \n",
       "17    2016-01-04 09:57:00       3601.4    3607.0    3601.4      -44   \n",
       "18    2016-01-04 09:57:00       3606.8    3606.8    3594.0      -16   \n",
       "19    2016-01-04 09:58:00       3607.0    3607.8    3603.4       -4   \n",
       "20    2016-01-04 09:59:00       3613.0    3613.6    3605.4      -35   \n",
       "21    2016-01-04 10:01:00       3607.8    3613.6    3607.8      -30   \n",
       "22    2016-01-04 10:02:00       3593.8    3607.8    3591.2      -58   \n",
       "23    2016-01-04 10:03:00       3589.8    3594.4    3588.4      -39   \n",
       "24    2016-01-04 10:04:00       3597.4    3597.8    3589.0      -37   \n",
       "25    2016-01-04 10:05:00       3591.4    3597.4    3589.2       -7   \n",
       "26    2016-01-04 10:06:00       3588.0    3592.8    3588.0      -13   \n",
       "27    2016-01-04 10:06:00       3580.0    3588.6    3580.0       -4   \n",
       "28    2016-01-04 10:08:00       3568.0    3580.2    3567.2       -1   \n",
       "29    2016-01-04 10:09:00       3568.0    3571.4    3565.0      -17   \n",
       "...                   ...          ...       ...       ...      ...   \n",
       "35728 2016-08-31 14:20:00       3301.6    3301.6    3299.2       14   \n",
       "35729 2016-08-31 14:21:00       3302.4    3304.4    3300.2       29   \n",
       "35730 2016-08-31 14:22:00       3304.4    3305.0    3302.4       22   \n",
       "35731 2016-08-31 14:23:00       3304.6    3305.6    3303.2       22   \n",
       "35732 2016-08-31 14:23:00       3304.6    3305.4    3301.4       40   \n",
       "35733 2016-08-31 14:24:00       3303.6    3304.6    3303.2        7   \n",
       "35734 2016-08-31 14:26:00       3304.2    3304.2    3303.2        8   \n",
       "35735 2016-08-31 14:27:00       3307.0    3309.0    3303.4        9   \n",
       "35736 2016-08-31 14:28:00       3308.8    3309.0    3305.6       12   \n",
       "35737 2016-08-31 14:29:00       3309.8    3309.8    3306.8       26   \n",
       "35738 2016-08-31 14:29:00       3308.0    3309.8    3307.8        8   \n",
       "35739 2016-08-31 14:30:00       3307.2    3308.6    3307.0       -3   \n",
       "35740 2016-08-31 14:32:00       3306.8    3308.2    3306.6        5   \n",
       "35741 2016-08-31 14:33:00       3307.0    3308.0    3306.4        1   \n",
       "35742 2016-08-31 14:33:00       3307.0    3307.2    3306.2        6   \n",
       "35743 2016-08-31 14:34:00       3307.0    3308.0    3306.6        4   \n",
       "35744 2016-08-31 14:36:00       3305.2    3307.0    3305.0       10   \n",
       "35745 2016-08-31 14:37:00       3306.6    3307.6    3305.4        9   \n",
       "35746 2016-08-31 14:37:00       3306.0    3306.6    3305.2        2   \n",
       "35747 2016-08-31 14:39:00       3305.8    3307.4    3305.8       13   \n",
       "35748 2016-08-31 14:40:00       3307.0    3307.0    3305.4       17   \n",
       "35749 2016-08-31 14:41:00       3307.2    3308.0    3306.4       16   \n",
       "35750 2016-08-31 14:41:00       3306.2    3307.4    3305.6       27   \n",
       "35751 2016-08-31 14:42:00       3306.2    3307.0    3306.0       13   \n",
       "35752 2016-08-31 14:44:00       3306.6    3307.4    3305.8        6   \n",
       "35753 2016-08-31 14:45:00       3306.6    3307.2    3305.8        4   \n",
       "35754 2016-08-31 14:46:00       3306.2    3307.2    3305.6        7   \n",
       "35755 2016-08-31 14:47:00       3304.2    3306.8    3304.2       29   \n",
       "35756 2016-08-31 14:47:00       3304.8    3305.4    3303.8       11   \n",
       "35757 2016-08-31 14:49:00       3305.0    3306.2    3304.0       12   \n",
       "\n",
       "        Turnover  Position  Volume  First.Latestprice  Last.Buy1price  \\\n",
       "0      115844340     28315     106             3644.8          3640.2   \n",
       "1      228902820     28236     210             3640.4          3625.0   \n",
       "2      301745580     28126     278             3625.4          3619.2   \n",
       "3      162817740     28045     150             3618.8          3616.8   \n",
       "4      143205060     27979     132             3616.8          3618.0   \n",
       "5      111857580     27931     103             3618.2          3621.0   \n",
       "6      120504420     27885     111             3621.0          3612.8   \n",
       "7      372121500     27787     344             3614.2          3601.0   \n",
       "8      195712320     27719     181             3601.2          3602.2   \n",
       "9      198897300     27649     184             3602.0          3603.4   \n",
       "10     127536900     27610     118             3604.6          3602.8   \n",
       "11      83269080     27582      77             3602.4          3603.4   \n",
       "12      65952540     27573      61             3603.4          3604.6   \n",
       "13      50825100     27560      47             3605.8          3604.2   \n",
       "14      78953280     27533      73             3604.2          3605.2   \n",
       "15     102802020     27510      95             3606.0          3608.6   \n",
       "16      60597360     27491      56             3609.0          3607.0   \n",
       "17     128675580     27447     119             3606.4          3601.4   \n",
       "18     176006520     27431     163             3601.4          3604.2   \n",
       "19      97367760     27428      90             3604.4          3606.6   \n",
       "20     123478800     27391     114             3607.0          3612.4   \n",
       "21      72574440     27361      67             3612.4          3607.8   \n",
       "22     201761820     27303     187             3607.8          3592.2   \n",
       "23     170214000     27264     158             3592.2          3589.2   \n",
       "24      95919060     27227      89             3589.0          3594.8   \n",
       "25      89435100     27220      83             3597.4          3589.2   \n",
       "26      91545060     27207      85             3591.4          3588.0   \n",
       "27     167710680     27203     156             3586.8          3580.0   \n",
       "28     190875540     27202     178             3580.2          3567.2   \n",
       "29     135944700     27185     127             3567.2          3566.6   \n",
       "...          ...       ...     ...                ...             ...   \n",
       "35728   30692160     37376      31             3300.8          3300.2   \n",
       "35729   61434300     37405      62             3301.6          3302.4   \n",
       "35730   42620280     37427      43             3302.4          3303.2   \n",
       "35731   75345540     37449      76             3304.6          3304.6   \n",
       "35732   85243080     37489      86             3304.6          3304.2   \n",
       "35733   30726180     37496      31             3304.2          3303.6   \n",
       "35734   21803700     37504      22             3303.6          3303.2   \n",
       "35735   61494420     37513      62             3304.2          3307.2   \n",
       "35736   47622960     37525      48             3307.0          3307.6   \n",
       "35737   70471860     37551      71             3308.8          3308.6   \n",
       "35738   37720740     37559      38             3309.8          3308.0   \n",
       "35739   19846320     37556      20             3308.0          3307.0   \n",
       "35740   33737580     37561      34             3307.2          3306.6   \n",
       "35741   38690940     37562      39             3307.0          3306.4   \n",
       "35742   31743660     37568      32             3306.4          3306.4   \n",
       "35743   30758820     37572      31             3307.2          3306.2   \n",
       "35744   32726820     37582      33             3307.0          3305.0   \n",
       "35745   32736780     37593      33             3305.4          3306.6   \n",
       "35746   27770820     37584      28             3305.8          3305.4   \n",
       "35747   38687640     37606      39             3306.6          3306.0   \n",
       "35748   47606100     37623      48             3305.8          3306.4   \n",
       "35749   47622480     37639      48             3307.0          3307.2   \n",
       "35750   60509280     37666      61             3307.2          3305.8   \n",
       "35751   39678300     37679      40             3306.2          3306.0   \n",
       "35752   46622640     37685      47             3307.2          3306.2   \n",
       "35753   38684280     37689      39             3306.2          3306.6   \n",
       "35754   51579780     37696      52             3306.6          3305.8   \n",
       "35755   80316660     37725      81             3305.8          3304.2   \n",
       "35756   60475860     37736      61             3304.2          3304.8   \n",
       "35757   74366280     37748      75             3305.0          3305.0   \n",
       "\n",
       "         ...      Vol_MA_12   Vol_MA_26  Dis_Vol_MA5_26   Vol_EMA_5  \\\n",
       "0        ...            NaN         NaN             NaN  106.000000   \n",
       "1        ...            NaN         NaN             NaN  168.400000   \n",
       "2        ...            NaN         NaN             NaN  220.315789   \n",
       "3        ...            NaN         NaN             NaN  191.107692   \n",
       "4        ...            NaN         NaN             NaN  168.417062   \n",
       "5        ...            NaN         NaN             NaN  144.512782   \n",
       "6        ...            NaN         NaN             NaN  132.647402   \n",
       "7        ...            NaN         NaN             NaN  205.958763   \n",
       "8        ...            NaN         NaN             NaN  197.416984   \n",
       "9        ...            NaN         NaN             NaN  192.865730   \n",
       "10       ...            NaN         NaN             NaN  167.618604   \n",
       "11       ...     166.166667         NaN             NaN  137.177785   \n",
       "12       ...     162.416667         NaN             NaN  111.654043   \n",
       "13       ...     148.833333         NaN             NaN   90.028618   \n",
       "14       ...     131.750000         NaN             NaN   84.339420   \n",
       "15       ...     127.166667         NaN             NaN   87.898365   \n",
       "16       ...     120.833333         NaN             NaN   77.254774   \n",
       "17       ...     122.166667         NaN             NaN   91.179271   \n",
       "18       ...     126.500000         NaN             NaN  115.130318   \n",
       "19       ...     105.333333         NaN             NaN  106.751026   \n",
       "20       ...      99.750000         NaN             NaN  109.167835   \n",
       "21       ...      90.000000         NaN             NaN   95.110011   \n",
       "22       ...      95.750000         NaN             NaN  125.742737   \n",
       "23       ...     102.500000         NaN             NaN  136.495797   \n",
       "24       ...     104.833333         NaN             NaN  120.663237   \n",
       "25       ...     107.833333  130.615385      -13.815385  108.108493   \n",
       "26       ...     108.833333  129.807692       -9.407692  100.405527   \n",
       "27       ...     113.916667  127.730769      -13.530769  118.937235   \n",
       "28       ...     124.083333  123.884615       -5.684615  138.624978   \n",
       "29       ...     124.750000  123.000000        2.800000  134.749965   \n",
       "...      ...            ...         ...             ...         ...   \n",
       "35728    ...      32.166667   35.961538      -11.161538   26.889536   \n",
       "35729    ...      33.750000   37.307692       -5.507692   38.593024   \n",
       "35730    ...      33.333333   37.384615       -1.184615   40.062016   \n",
       "35731    ...      37.083333   38.923077        7.276923   52.041344   \n",
       "35732    ...      39.916667   40.307692       19.292308   63.360896   \n",
       "35733    ...      40.750000   38.192308       21.407692   52.573931   \n",
       "35734    ...      40.250000   37.807692       13.792308   42.382620   \n",
       "35735    ...      42.166667   38.384615       17.015385   48.921747   \n",
       "35736    ...      43.916667   38.807692       10.992308   48.614498   \n",
       "35737    ...      48.083333   40.423077        6.376923   56.076332   \n",
       "35738    ...      49.083333   41.038462        7.161538   50.050888   \n",
       "35739    ...      49.166667   40.846154        6.953846   40.033925   \n",
       "35740    ...      49.416667   40.884615        1.315385   38.022617   \n",
       "35741    ...      47.500000   41.384615       -0.984615   38.348411   \n",
       "35742    ...      46.583333   40.384615       -7.784615   36.232274   \n",
       "35743    ...      42.833333   39.923077       -8.723077   34.488183   \n",
       "35744    ...      38.416667   39.346154       -5.546154   33.992122   \n",
       "35745    ...      38.583333   39.423077       -5.823077   33.661415   \n",
       "35746    ...      39.083333   38.500000       -7.100000   31.774276   \n",
       "35747    ...      37.166667   39.192308       -6.392308   34.182851   \n",
       "35748    ...      37.166667   39.961538       -3.761538   38.788567   \n",
       "35749    ...      35.250000   40.307692       -1.107692   41.859045   \n",
       "35750    ...      37.166667   41.615385        3.184615   48.239363   \n",
       "35751    ...      38.833333   42.346154        4.853846   45.492909   \n",
       "35752    ...      39.916667   43.153846        5.646154   45.995273   \n",
       "35753    ...      39.916667   43.923077        3.076923   43.663515   \n",
       "35754    ...      41.583333   44.730769        3.069231   46.442343   \n",
       "35755    ...      45.750000   45.461538        6.338462   57.961562   \n",
       "35756    ...      48.083333   46.153846        9.846154   58.974375   \n",
       "35757    ...      51.583333   46.115385       15.484615   64.316250   \n",
       "\n",
       "       Vol_EMA_12  Vol_EMA_26  Dis_Vol_EMA5_26  DIFF_12_26  DEA_12_26  \\\n",
       "0      106.000000  106.000000         0.000000    0.000000   0.000000   \n",
       "1      162.333333  160.000000         8.400000   -0.327564  -0.181980   \n",
       "2      207.478060  202.396254        17.919535   -0.634451  -0.367419   \n",
       "3      189.334483  187.748551         3.359141   -0.823469  -0.521908   \n",
       "4      173.756909  174.820232        -6.403171   -0.869050  -0.625175   \n",
       "5      156.559257  160.435213       -15.922431   -0.751834  -0.659506   \n",
       "6      146.392868  151.643416       -18.996015   -0.971763  -0.738530   \n",
       "7      187.630431  182.636828        23.321935   -1.721885  -0.974849   \n",
       "8      186.318696  182.394214        15.022770   -2.165518  -1.249899   \n",
       "9      185.879304  182.615797        10.249933   -2.325090  -1.490804   \n",
       "10     173.459028  174.235108        -6.616503   -2.524999  -1.717080   \n",
       "11     156.308929  162.288243       -25.110458   -2.483403  -1.881654   \n",
       "12     139.759679  150.422343       -38.768300   -2.385718  -1.988332   \n",
       "13     123.965667  138.806783       -48.778166   -2.327979  -2.059386   \n",
       "14     115.428045  131.688101       -47.348682   -2.195391  -2.087579   \n",
       "15     112.052150  127.850225       -39.951860   -1.897371  -2.048436   \n",
       "16     102.893605  120.556799       -43.302026   -1.757935  -1.988997   \n",
       "17     105.500394  120.402990       -29.223719   -1.982649  -1.987704   \n",
       "18     114.732720  124.509958        -9.379640   -1.784824  -1.946535   \n",
       "19     110.788050  121.255407       -14.504382   -1.597776  -1.875970   \n",
       "20     111.297454  120.584737       -11.416902   -1.037152  -1.706644   \n",
       "21     104.305246  115.720827       -20.610816   -0.939550  -1.552085   \n",
       "22     117.306330  122.084617         3.658120   -1.803848  -1.602737   \n",
       "23     123.682599  125.243107        11.252689   -2.728825  -1.829023   \n",
       "24     118.263609  122.099394        -1.436157   -2.887792  -2.041580   \n",
       "25     112.767026  118.750345       -10.641852   -3.398996  -2.313886   \n",
       "26     108.447692  115.892563       -15.487036   -3.998578  -2.651641   \n",
       "27     115.832122  119.253006        -0.315771   -4.991522  -3.120524   \n",
       "28     125.472289  124.127839        14.497139   -6.573239  -3.812137   \n",
       "29     125.708897  124.364067        10.385898   -7.731735  -4.597029   \n",
       "...           ...         ...              ...         ...        ...   \n",
       "35728   30.047989   33.567610        -6.678075   -0.404311  -0.697110   \n",
       "35729   34.963683   35.673713         2.919311   -0.271863  -0.612061   \n",
       "35730   36.200039   36.216401         3.845615   -0.005450  -0.490739   \n",
       "35731   42.323110   39.163334        12.878010    0.219294  -0.348732   \n",
       "35732   49.042632   42.632717        20.728179    0.392876  -0.200410   \n",
       "35733   46.266842   41.771034        10.802896    0.444624  -0.071403   \n",
       "35734   42.533482   40.306513         2.076107    0.527964   0.048470   \n",
       "35735   45.528331   41.913438         7.008309    0.810604   0.200897   \n",
       "35736   45.908588   42.364294         6.250203    1.166398   0.393997   \n",
       "35737   49.768805   44.485458        11.590874    1.511633   0.617524   \n",
       "35738   47.958220   44.005054         6.045834    1.621301   0.818280   \n",
       "35739   43.656955   42.226901        -2.192976    1.624928   0.979609   \n",
       "35740   42.171270   41.617501        -3.594884    1.577344   1.099156   \n",
       "35741   41.683382   41.423612        -3.075201    1.538042   1.186933   \n",
       "35742   40.193631   40.725567        -4.493293    1.489722   1.247491   \n",
       "35743   38.779226   40.005155        -5.516972    1.434888   1.284970   \n",
       "35744   37.890114   39.486254        -5.494132    1.231984   1.274373   \n",
       "35745   37.137789   39.005791        -5.344376    1.170656   1.253630   \n",
       "35746   35.731975   38.190547        -6.416271    1.061403   1.215184   \n",
       "35747   36.234748   38.250507        -4.067656    0.947755   1.161698   \n",
       "35748   38.044787   38.972691        -0.184124    0.943641   1.118087   \n",
       "35749   39.576358   39.641381         2.217664    0.945618   1.083593   \n",
       "35750   42.872303   41.223501         7.015862    0.856619   1.038198   \n",
       "35751   42.430410   41.132871         4.360038    0.777128   0.985984   \n",
       "35752   43.133424   41.567473         4.427799    0.737902   0.936368   \n",
       "35753   42.497513   41.377290         2.286225    0.698759   0.888846   \n",
       "35754   43.959434   42.164157         4.278186    0.628221   0.836721   \n",
       "35755   49.657983   45.040887        12.920676    0.406252   0.750627   \n",
       "35756   51.402908   46.223043        12.751332    0.275578   0.655617   \n",
       "35757   55.033230   48.354670        15.961580    0.186013   0.561696   \n",
       "\n",
       "           MACD  \n",
       "0      0.000000  \n",
       "1     -0.291168  \n",
       "2     -0.534064  \n",
       "3     -0.603123  \n",
       "4     -0.487751  \n",
       "5     -0.184655  \n",
       "6     -0.466465  \n",
       "7     -1.494072  \n",
       "8     -1.831237  \n",
       "9     -1.668572  \n",
       "10    -1.615838  \n",
       "11    -1.203498  \n",
       "12    -0.794773  \n",
       "13    -0.537186  \n",
       "14    -0.215624  \n",
       "15     0.302129  \n",
       "16     0.462124  \n",
       "17     0.010111  \n",
       "18     0.323422  \n",
       "19     0.556387  \n",
       "20     1.338984  \n",
       "21     1.225070  \n",
       "22    -0.402222  \n",
       "23    -1.799605  \n",
       "24    -1.692425  \n",
       "25    -2.170221  \n",
       "26    -2.693873  \n",
       "27    -3.741995  \n",
       "28    -5.522204  \n",
       "29    -6.269413  \n",
       "...         ...  \n",
       "35728  0.585599  \n",
       "35729  0.680396  \n",
       "35730  0.970576  \n",
       "35731  1.136052  \n",
       "35732  1.186573  \n",
       "35733  1.032056  \n",
       "35734  0.958988  \n",
       "35735  1.219415  \n",
       "35736  1.544801  \n",
       "35737  1.788218  \n",
       "35738  1.606042  \n",
       "35739  1.290638  \n",
       "35740  0.956375  \n",
       "35741  0.702217  \n",
       "35742  0.484462  \n",
       "35743  0.299834  \n",
       "35744 -0.084778  \n",
       "35745 -0.165948  \n",
       "35746 -0.307564  \n",
       "35747 -0.427887  \n",
       "35748 -0.348892  \n",
       "35749 -0.275950  \n",
       "35750 -0.363159  \n",
       "35751 -0.417712  \n",
       "35752 -0.396932  \n",
       "35753 -0.380173  \n",
       "35754 -0.417001  \n",
       "35755 -0.688751  \n",
       "35756 -0.760078  \n",
       "35757 -0.751368  \n",
       "\n",
       "[35758 rows x 32 columns]"
      ]
     },
     "execution_count": 30,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "train_data_addMA"
   ]
  },
  {
   "cell_type": "raw",
   "metadata": {},
   "source": [
    "MACD 指标分析：\n",
    "\n",
    "绿色能量柱表示空头市场，红色能量柱表示多头市场\n",
    "MACD金叉：DIFF由下向上突破DEA,为做多信号，并且当DIFF线在DEA线之上时为上涨行情\n",
    "\n",
    "MACD死叉：DIFF由上向下突破DEA,为做空信号，并且当DIFF线在DEA线之上时为下跌行情\n",
    "当DIFF与DEA均为正值，即都在零轴线上，大势属于多头市场，DIFF向上突破DEA，可以作为做多买入信号。\n",
    "当DIFF与DEA均为负值，即都在零轴线下时，大势属于空头市场，DIFF向下跌破DEA,可以作为做空卖出信号。"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 添加RSI指标"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 添加布林带指标"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 提取出清理后的测试集"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "collapsed": true
   },
   "outputs": [
    {
     "ename": "NameError",
     "evalue": "name 'pd' is not defined",
     "output_type": "error",
     "traceback": [
      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[0;31mNameError\u001b[0m                                 Traceback (most recent call last)",
      "\u001b[0;32m<ipython-input-1-2ffca3d69226>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m()\u001b[0m\n\u001b[1;32m      1\u001b[0m \u001b[0;31m# 读取已经提取好的主力合约文件\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m      2\u001b[0m \u001b[0mpath\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0;34m'/home/chocolate/LSTM-source/'\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m----> 3\u001b[0;31m \u001b[0mdata\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mpd\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mread_csv\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mpath\u001b[0m \u001b[0;34m+\u001b[0m \u001b[0;34m'MINU_IF_zhuli_201406-_201609.csv'\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m      4\u001b[0m \u001b[0mdata\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m'Time'\u001b[0m\u001b[0;34m]\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mpd\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mto_datetime\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mdata\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m'Time'\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m      5\u001b[0m \u001b[0mdata\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mindex\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mrange\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mlen\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mdata\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;31mNameError\u001b[0m: name 'pd' is not defined"
     ]
    }
   ],
   "source": [
    "# 读取已经提取好的主力合约文件\n",
    "path = '/home/chocolate/LSTM-source/'\n",
    "data = pd.read_csv(path + 'MINU_IF_zhuli_201406-_201609.csv') \n",
    "data['Time'] = pd.to_datetime(data['Time']) \n",
    "data.index = range(len(data))\n",
    "delete_list = []\n",
    "# 选择2016年9月的主力合约数据作为测试集，在主力合约中进行提取\n",
    "# 删除非正常交易时间的数据，交易时间为上午9：30-11：30，下午1:00到3:00\n",
    "# 因为每天开盘的前10分钟和收盘的最后10分钟数据波动较大，暂时在测试时去掉这些数据\n",
    "# 一分钟之内，最大股价和最低股价相差超过50点的，那么应该尽量删掉这些数据。\n",
    "# 删除一分钟成交量大于1000的，这些数据可能会影响整体数据\n",
    "for k in range(len(data)):\n",
    "    if data['Time'].iloc[k].year < 2016:\n",
    "        delete_list.append(k)\n",
    "    elif data['Time'].iloc[k].month < 9:\n",
    "        delete_list.append(k)\n",
    "    elif data['Time'].iloc[k].hour == 9 and data['Time'].iloc[k].minute <= 39:\n",
    "        delete_list.append(k)\n",
    "    elif data['Time'].iloc[k].hour == 14 and data['Time'].iloc[k].minute >= 50:\n",
    "         delete_list.append(k)\n",
    "    elif data['Time'].iloc[k].hour >= 15:\n",
    "        delete_list.append(k)\n",
    "    elif data['MaxPrice'].iloc[k] - data['MinPrice'].iloc[k] > 50:\n",
    "         delete_list.append(k)\n",
    "    elif data['Volume'].iloc[k] > 1000:\n",
    "         delete_list.append(k)\n",
    "        \n",
    "for j in range(len(data)):\n",
    "    if j in delete_list:\n",
    "        data.drop(j,inplace=True)\n",
    "test_data= data.sort_values(by = 'Time')\n",
    "\n",
    "test_data.to_csv(path + 'test_data.csv')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 利用LSTM对训练集进行训练"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 每次执行可从此处开始"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 66,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "import tensorflow as tf\n",
    "from tensorflow.python.ops import rnn, rnn_cell\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "from __future__ import print_function\n",
    "import pandas as pd\n",
    "from pandas import Series,DataFrame\n",
    "import os\n",
    "from sklearn.metrics import mean_squared_error\n",
    "import datetime\n",
    "import tensorflow as tf\n",
    "from tensorflow.contrib import learn\n",
    "import cPickle\n",
    "import gzip\n",
    "%matplotlib inline\n",
    "\n",
    "# 提取训练数据和测试数据\n",
    "path = '/home/chocolate/LSTM-source/'\n",
    "train_data = pd.read_csv(path + 'train_data_addMA.csv')\n",
    "test_data = pd.read_csv(path + 'test_data.csv')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 67,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(4399,)"
      ]
     },
     "execution_count": 67,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# 打标签\n",
    "# 根据当前分钟收盘价相对于开盘价的涨跌幅，将训练集和测试集分成五类——大涨、小涨、平稳、大跌、小跌\n",
    "train_data['RaiseDown'] = (train_data['Latestprice'] - train_data['First.Latestprice'])/train_data['First.Latestprice']\n",
    "test_data['RaiseDown'] = (test_data['Latestprice'] - test_data['First.Latestprice'])//test_data['First.Latestprice']\n",
    "train_data = train_data.fillna(0)\n",
    "\n",
    "test_label.shape\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 68,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(10, 31)"
      ]
     },
     "execution_count": 68,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "train_data1 = train_data.ix[1:100,3:]\n",
    "train_data1.shape\n",
    "test_data = train_data.ix[101:110,3:]\n",
    "test_data.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 69,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "test_data\n",
    "train_label = []\n",
    "for i in train_data1['RaiseDown']:\n",
    "    if i > 0.002:\n",
    "        train_label.append(1)\n",
    "    elif i > 0.0005:\n",
    "        train_label.append(2)\n",
    "    elif i> -0.0005:\n",
    "        train_label.append(3)\n",
    "    elif i > -0.002:\n",
    "        train_label.append(4)\n",
    "    else:\n",
    "        train_label.append(5)\n",
    "train_label = np.array(train_label)\n",
    "# train_data.shape\n",
    "# train_label.shape\n",
    "# train_data['RaiseDown']\n",
    "test_label = []\n",
    "for i in test_data['RaiseDown']:\n",
    "    if i > 0.002:\n",
    "        test_label.append(1)\n",
    "    elif i > 0.0005:\n",
    "        test_label.append(2)\n",
    "    elif i> -0.0005:\n",
    "        test_label.append(3)\n",
    "    elif i > -0.002:\n",
    "        test_label.append(4)\n",
    "    else:\n",
    "        test_label.append(5)\n",
    "test_label = np.array(test_label)\n",
    "tf.reset_default_graph()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 用回归模型进行测试"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 70,
   "metadata": {
    "collapsed": false,
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Step #100, epoch #100, avg. train loss: 2.35973\n",
      "Step #200, epoch #200, avg. train loss: 0.53918\n",
      "Step #300, epoch #300, avg. train loss: 0.53255\n",
      "Step #400, epoch #400, avg. train loss: 0.52749\n",
      "Step #500, epoch #500, avg. train loss: 0.52316\n",
      "Step #600, epoch #600, avg. train loss: 0.51888\n",
      "Step #700, epoch #700, avg. train loss: 0.51489\n",
      "Step #800, epoch #800, avg. train loss: 0.51084\n",
      "Step #900, epoch #900, avg. train loss: 0.50692\n",
      "Step #1000, epoch #1000, avg. train loss: 0.50319\n",
      "Step #1100, epoch #1100, avg. train loss: 0.49943\n",
      "Step #1200, epoch #1200, avg. train loss: 0.49558\n",
      "Step #1300, epoch #1300, avg. train loss: 0.49164\n",
      "Step #1400, epoch #1400, avg. train loss: 0.48760\n",
      "Step #1500, epoch #1500, avg. train loss: 0.48346\n",
      "Step #1600, epoch #1600, avg. train loss: 0.47923\n",
      "Step #1700, epoch #1700, avg. train loss: 0.47492\n",
      "Step #1800, epoch #1800, avg. train loss: 0.47054\n",
      "Step #1900, epoch #1900, avg. train loss: 0.46611\n",
      "Step #2000, epoch #2000, avg. train loss: 0.46166\n",
      "Step #2100, epoch #2100, avg. train loss: 0.45719\n",
      "Step #2200, epoch #2200, avg. train loss: 0.45268\n",
      "Step #2300, epoch #2300, avg. train loss: 0.44814\n",
      "Step #2400, epoch #2400, avg. train loss: 0.44356\n",
      "Step #2500, epoch #2500, avg. train loss: 0.43892\n",
      "Step #2600, epoch #2600, avg. train loss: 0.43418\n",
      "Step #2700, epoch #2700, avg. train loss: 0.42942\n",
      "Step #2800, epoch #2800, avg. train loss: 0.42476\n",
      "Step #2900, epoch #2900, avg. train loss: 0.42022\n",
      "Step #3000, epoch #3000, avg. train loss: 0.41577\n",
      "Step #3100, epoch #3100, avg. train loss: 0.41141\n",
      "Step #3200, epoch #3200, avg. train loss: 0.40714\n",
      "Step #3300, epoch #3300, avg. train loss: 0.40293\n",
      "Step #3400, epoch #3400, avg. train loss: 0.39884\n",
      "Step #3500, epoch #3500, avg. train loss: 0.39490\n",
      "Step #3600, epoch #3600, avg. train loss: 0.39103\n",
      "Step #3700, epoch #3700, avg. train loss: 0.38732\n",
      "Step #3800, epoch #3800, avg. train loss: 0.38390\n",
      "Step #3900, epoch #3900, avg. train loss: 0.38066\n",
      "Step #4000, epoch #4000, avg. train loss: 0.37758\n",
      "Step #4100, epoch #4100, avg. train loss: 0.37464\n",
      "Step #4200, epoch #4200, avg. train loss: 0.37185\n",
      "Step #4300, epoch #4300, avg. train loss: 0.36926\n",
      "Step #4400, epoch #4400, avg. train loss: 0.36675\n",
      "Step #4500, epoch #4500, avg. train loss: 0.36430\n",
      "Step #4600, epoch #4600, avg. train loss: 0.36187\n",
      "Step #4700, epoch #4700, avg. train loss: 0.35958\n",
      "Step #4800, epoch #4800, avg. train loss: 0.35735\n",
      "Step #4900, epoch #4900, avg. train loss: 0.35515\n",
      "Step #5000, epoch #5000, avg. train loss: 0.35298\n",
      "Step #5100, epoch #5100, avg. train loss: 0.35080\n",
      "Step #5200, epoch #5200, avg. train loss: 0.34861\n",
      "Step #5300, epoch #5300, avg. train loss: 0.34640\n",
      "Step #5400, epoch #5400, avg. train loss: 0.34415\n",
      "Step #5500, epoch #5500, avg. train loss: 0.34184\n",
      "Step #5600, epoch #5600, avg. train loss: 0.33948\n",
      "Step #5700, epoch #5700, avg. train loss: 0.33704\n",
      "Step #5800, epoch #5800, avg. train loss: 0.33451\n",
      "Step #5900, epoch #5900, avg. train loss: 0.33189\n",
      "Step #6000, epoch #6000, avg. train loss: 0.32914\n",
      "Step #6100, epoch #6100, avg. train loss: 0.32627\n",
      "Step #6200, epoch #6200, avg. train loss: 0.32325\n",
      "Step #6300, epoch #6300, avg. train loss: 0.32013\n",
      "Step #6400, epoch #6400, avg. train loss: 0.31699\n",
      "Step #6500, epoch #6500, avg. train loss: 0.31392\n",
      "Step #6600, epoch #6600, avg. train loss: 0.31097\n",
      "Step #6700, epoch #6700, avg. train loss: 0.30818\n",
      "Step #6800, epoch #6800, avg. train loss: 0.30555\n",
      "Step #6900, epoch #6900, avg. train loss: 0.30305\n",
      "Step #7000, epoch #7000, avg. train loss: 0.30066\n",
      "Step #7100, epoch #7100, avg. train loss: 0.29835\n",
      "Step #7200, epoch #7200, avg. train loss: 0.29608\n",
      "Step #7300, epoch #7300, avg. train loss: 0.29380\n",
      "Step #7400, epoch #7400, avg. train loss: 0.29147\n",
      "Step #7500, epoch #7500, avg. train loss: 0.28924\n",
      "Step #7600, epoch #7600, avg. train loss: 0.28710\n",
      "Step #7700, epoch #7700, avg. train loss: 0.28502\n",
      "Step #7800, epoch #7800, avg. train loss: 0.28300\n",
      "Step #7900, epoch #7900, avg. train loss: 0.28104\n",
      "Step #8000, epoch #8000, avg. train loss: 0.27913\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "TensorFlowRNNRegressor(batch_size=2000, bidirectional=False, cell_type='lstm',\n",
       "            clip_gradients=5.0, config=None, continue_training=False,\n",
       "            initial_state=None,\n",
       "            input_op_fn=<function input_fn at 0x7f1a94d2ba28>,\n",
       "            learning_rate=0.003, n_classes=0, num_layers=1,\n",
       "            optimizer='Adagrad', rnn_size=31, sequence_length=None,\n",
       "            steps=8000, verbose=2)"
      ]
     },
     "execution_count": 70,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "TIME_STEP = 31\n",
    "TRAINING_STEPS = 8000\n",
    "BATCH_SIZE = 2000\n",
    "# 利用tensorflow构建rnn回归预测模型\n",
    "def input_fn(X):\n",
    "    # 将时间窗口序列分割为时间点数据\n",
    "    return tf.split(1, TIME_STEP, X)\n",
    "\n",
    "train_data1 = np.array(train_data1)\n",
    "# def exp_decay(global_step):\n",
    "#     # 将本函数作为参数带入learn_rate可让回归器训练过程中动态调整训练步长\n",
    "#     return tf.train.exponential_decay(learning_rate=0.003,\n",
    "#                                       global_step=global_step,\n",
    "#                                       decay_steps=1000,\n",
    "#                                       decay_rate=0.3)\n",
    "\n",
    "# 设置rnn回归模型参数\n",
    "regressor = learn.TensorFlowRNNRegressor(rnn_size=TIME_STEP,\n",
    "                                         cell_type='lstm',\n",
    "                                         steps=TRAINING_STEPS,\n",
    "                                         num_layers=1,\n",
    "                                         learning_rate=0.003,\n",
    "                                         batch_size=BATCH_SIZE,\n",
    "                                         verbose=2, input_op_fn=input_fn)\n",
    "# 开始训练\n",
    "regressor.fit(train_data1, train_label)\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 72,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([1, 3, 2, 2, 4, 4, 2, 5, 3, 3])"
      ]
     },
     "execution_count": 72,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "predicted = regressor.predict(test_data)\n",
    "\n",
    "test_label"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 73,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[ 2.19979048],\n",
       "       [ 3.21953058],\n",
       "       [ 3.18161392],\n",
       "       [ 5.20945644],\n",
       "       [ 2.79030132],\n",
       "       [ 2.41684341],\n",
       "       [ 2.90925455],\n",
       "       [ 2.64601231],\n",
       "       [ 2.71511602],\n",
       "       [ 3.05825138]], dtype=float32)"
      ]
     },
     "execution_count": 73,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "predicted"
   ]
  }
 ],
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