{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {
    "collapsed": false
   },
   "source": [
    "# 微信指数与本案和竞争对手相关性分析"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 项目背景介绍"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "> 微信指数是微信官方提供的基于微信大数据分析的移动端指数。\n",
    "应用场景有以下三种，\n",
    "* 1.捕捉热词，看懂趋势\n",
    "微信指数整合了微信上的搜索和浏览行为数据，基于对海量数据的分析，可以形成当日、7日、30日以及90日的“关键词”动态指数变化情况，方便看到某个词语在一段时间内的热度趋势和最新指数动态。\n",
    "\n",
    "> * 2.监测舆情动向，形成研究结果\n",
    "微信指数可以提供社会舆情的监测，能实时了解互联网用户当前最为关注的社会问题、热点事件、舆论焦点等等，方便政府、企业对舆情进行研究，从而形成有效的舆情应对方案。\n",
    "\n",
    "> * 3.洞察用户兴趣，助力精准营销\n",
    "微信指数提供的关键词的热度变化，可以间接获取用户的兴趣点及变化情况，比如日常消费、娱乐、出行等，从而对品牌企业的精准营销和投放形成决策依据，也能对品牌投放效果形成有效监测、跟踪和反馈。\n",
    "\n",
    "由于本产品的主战场在移动端，而微信作为占据中国用户使用时间最长的移动应用，与本产品的用户人群重合度极高，合理充分的分析各个竞争对手与微信指数间的相关性，能够比较客观的发现本产品与竞争对手间的实力差别，甚至可以进一步发现产品内部各个部门间与微信指数的关系，客观评价各个部门对公司的贡献程度。  "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "引入科学计算和绘图相关包"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "%matplotlib inline\n",
    "import matplotlib\n",
    "from sklearn import preprocessing\n",
    "import warnings\n",
    "warnings.filterwarnings(\"ignore\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 数据获取"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "> 微信指数的获取方法如下\n",
    "> * 1.打开微信。在顶部搜索框内输入“微信指数”四个关键字。\n",
    "\n",
    "> * 2.再点击“微信指数”进入主页面，然后再点击微信指数里面的搜索框，输入自己想要的关键词得出的数据。\n",
    "\n",
    "> * 3.目前微信指数只支持7日、30日、90日内的三个阶段的数据。\n",
    "\n",
    "按照上述方法分别输入与本产品相关的关键词，依次输入各个竞争对手的关键词得到相应的微信指数，并且在相同时间段内收集以下数据，包括PV、访客数量、新访客数量、启动次数、部门1带来的新增注册用户数、部门2带来的新增注册用户数、部门3带来的新增注册用户数、部门4带来的新增注册用户数、自然流量产生的新增注册用户数、总计新增注册用户数，然后对上述数据进行相关性分析。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "df = pd.read_csv(\"wechat_data.csv\", encoding='gbk', \n",
    "                  parse_dates=[u'date', u'current', u'competitor_keyword1', u'competitor_keyword2', \n",
    "                               u'competitor_keyword3', u'competitor_keyword4', u'pv', u'uv', u'new_uv', \n",
    "                               u'launches', u'department1', u'department2', u'department3', u'department4', 'natural_flow', 'all'])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "原始数据加载成功后，以dataframe形式存储，通过以下方法非常容易可以对数据进行探查。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>date</th>\n",
       "      <th>current</th>\n",
       "      <th>competitor_keyword1</th>\n",
       "      <th>competitor_keyword2</th>\n",
       "      <th>competitor_keyword3</th>\n",
       "      <th>competitor_keyword4</th>\n",
       "      <th>pv</th>\n",
       "      <th>uv</th>\n",
       "      <th>new_uv</th>\n",
       "      <th>launches</th>\n",
       "      <th>department1</th>\n",
       "      <th>department2</th>\n",
       "      <th>department3</th>\n",
       "      <th>department4</th>\n",
       "      <th>natural_flow</th>\n",
       "      <th>all</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2016-12-28</td>\n",
       "      <td>55154</td>\n",
       "      <td>32639</td>\n",
       "      <td>6264</td>\n",
       "      <td>42789</td>\n",
       "      <td>14368</td>\n",
       "      <td>1422294</td>\n",
       "      <td>68229</td>\n",
       "      <td>9183</td>\n",
       "      <td>145258</td>\n",
       "      <td>93</td>\n",
       "      <td>1982</td>\n",
       "      <td>1448</td>\n",
       "      <td>126</td>\n",
       "      <td>1825</td>\n",
       "      <td>5519</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2016-12-29</td>\n",
       "      <td>66562</td>\n",
       "      <td>47962</td>\n",
       "      <td>9410</td>\n",
       "      <td>37535</td>\n",
       "      <td>13130</td>\n",
       "      <td>1696813</td>\n",
       "      <td>79281</td>\n",
       "      <td>10830</td>\n",
       "      <td>163905</td>\n",
       "      <td>82</td>\n",
       "      <td>2102</td>\n",
       "      <td>1487</td>\n",
       "      <td>97</td>\n",
       "      <td>2370</td>\n",
       "      <td>6182</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2016-12-30</td>\n",
       "      <td>61442</td>\n",
       "      <td>29138</td>\n",
       "      <td>6611</td>\n",
       "      <td>39865</td>\n",
       "      <td>16680</td>\n",
       "      <td>1688683</td>\n",
       "      <td>80199</td>\n",
       "      <td>11188</td>\n",
       "      <td>167161</td>\n",
       "      <td>107</td>\n",
       "      <td>2245</td>\n",
       "      <td>1685</td>\n",
       "      <td>132</td>\n",
       "      <td>1846</td>\n",
       "      <td>6102</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2016-12-31</td>\n",
       "      <td>48100</td>\n",
       "      <td>24858</td>\n",
       "      <td>5900</td>\n",
       "      <td>33460</td>\n",
       "      <td>12298</td>\n",
       "      <td>1410730</td>\n",
       "      <td>72485</td>\n",
       "      <td>11926</td>\n",
       "      <td>148706</td>\n",
       "      <td>103</td>\n",
       "      <td>3735</td>\n",
       "      <td>1783</td>\n",
       "      <td>111</td>\n",
       "      <td>2184</td>\n",
       "      <td>7983</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2017-01-01</td>\n",
       "      <td>79754</td>\n",
       "      <td>30667</td>\n",
       "      <td>3504</td>\n",
       "      <td>25985</td>\n",
       "      <td>9430</td>\n",
       "      <td>1141197</td>\n",
       "      <td>57703</td>\n",
       "      <td>10153</td>\n",
       "      <td>105198</td>\n",
       "      <td>49</td>\n",
       "      <td>1613</td>\n",
       "      <td>1938</td>\n",
       "      <td>72</td>\n",
       "      <td>1930</td>\n",
       "      <td>5621</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "        date current competitor_keyword1 competitor_keyword2  \\\n",
       "0 2016-12-28   55154               32639                6264   \n",
       "1 2016-12-29   66562               47962                9410   \n",
       "2 2016-12-30   61442               29138                6611   \n",
       "3 2016-12-31   48100               24858                5900   \n",
       "4 2017-01-01   79754               30667                3504   \n",
       "\n",
       "  competitor_keyword3 competitor_keyword4       pv     uv new_uv launches  \\\n",
       "0               42789               14368  1422294  68229   9183   145258   \n",
       "1               37535               13130  1696813  79281  10830   163905   \n",
       "2               39865               16680  1688683  80199  11188   167161   \n",
       "3               33460               12298  1410730  72485  11926   148706   \n",
       "4               25985                9430  1141197  57703  10153   105198   \n",
       "\n",
       "  department1 department2 department3 department4 natural_flow   all  \n",
       "0          93        1982        1448         126         1825  5519  \n",
       "1          82        2102        1487          97         2370  6182  \n",
       "2         107        2245        1685         132         1846  6102  \n",
       "3         103        3735        1783         111         2184  7983  \n",
       "4          49        1613        1938          72         1930  5621  "
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 数据清洗"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "由于微信指数与产品间的访客数、应用的启动次数不在同一数量级上，本文主要分析各种指标间的相关性，不同评价指标往往具有不同的量纲和量纲单位，这样的情况会影响到数据分析的结果，为了消除指标之间的量纲影响，需要进行数据标准化处理，以解决数据指标之间的可比性，本文拟采用离差标准化，转换函数如下 $$x^*=\\frac{x-min}{max-min}$$ \n",
    "该函数是对原始数据的线性变换，使结果值映射到[0 - 1]之间，其中max为样本数据的最大值，min为样本数据的最小值。"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "下面的df_normalized方法能够将原始数据标准化处理，使各指标处于同一数量级，适合进行综合对比评价。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "def df_normalized(df):\n",
    "    result = pd.DataFrame()\n",
    "    min_max_scaler = preprocessing.MinMaxScaler()\n",
    "    for item in df.columns:\n",
    "        if item == 'date':\n",
    "            result[item] = df[item]\n",
    "        else:\n",
    "            np_scale = min_max_scaler.fit_transform(df[item])\n",
    "            st = item + '_nor'\n",
    "            result[st] = pd.DataFrame(np_scale)\n",
    "    return result"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "normalized = df_normalized(df)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>date</th>\n",
       "      <th>current_nor</th>\n",
       "      <th>competitor_keyword1_nor</th>\n",
       "      <th>competitor_keyword2_nor</th>\n",
       "      <th>competitor_keyword3_nor</th>\n",
       "      <th>competitor_keyword4_nor</th>\n",
       "      <th>pv_nor</th>\n",
       "      <th>uv_nor</th>\n",
       "      <th>new_uv_nor</th>\n",
       "      <th>launches_nor</th>\n",
       "      <th>department1_nor</th>\n",
       "      <th>department2_nor</th>\n",
       "      <th>department3_nor</th>\n",
       "      <th>department4_nor</th>\n",
       "      <th>natural_flow_nor</th>\n",
       "      <th>all_nor</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2016-12-28</td>\n",
       "      <td>0.673861</td>\n",
       "      <td>0.209573</td>\n",
       "      <td>0.419770</td>\n",
       "      <td>0.449234</td>\n",
       "      <td>0.188282</td>\n",
       "      <td>0.796087</td>\n",
       "      <td>0.755430</td>\n",
       "      <td>0.723850</td>\n",
       "      <td>0.822929</td>\n",
       "      <td>0.138675</td>\n",
       "      <td>0.436600</td>\n",
       "      <td>0.226955</td>\n",
       "      <td>0.952756</td>\n",
       "      <td>0.400720</td>\n",
       "      <td>0.473989</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2016-12-29</td>\n",
       "      <td>0.825105</td>\n",
       "      <td>0.347860</td>\n",
       "      <td>0.637547</td>\n",
       "      <td>0.381769</td>\n",
       "      <td>0.169433</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.981243</td>\n",
       "      <td>0.889661</td>\n",
       "      <td>0.973677</td>\n",
       "      <td>0.121726</td>\n",
       "      <td>0.464468</td>\n",
       "      <td>0.239352</td>\n",
       "      <td>0.724409</td>\n",
       "      <td>0.578999</td>\n",
       "      <td>0.543808</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2016-12-30</td>\n",
       "      <td>0.757225</td>\n",
       "      <td>0.177978</td>\n",
       "      <td>0.443791</td>\n",
       "      <td>0.411688</td>\n",
       "      <td>0.223484</td>\n",
       "      <td>0.993961</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.925702</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.160247</td>\n",
       "      <td>0.497678</td>\n",
       "      <td>0.302289</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.407589</td>\n",
       "      <td>0.535383</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2016-12-31</td>\n",
       "      <td>0.580342</td>\n",
       "      <td>0.139352</td>\n",
       "      <td>0.394573</td>\n",
       "      <td>0.329443</td>\n",
       "      <td>0.156765</td>\n",
       "      <td>0.787497</td>\n",
       "      <td>0.842388</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.850804</td>\n",
       "      <td>0.154083</td>\n",
       "      <td>0.843706</td>\n",
       "      <td>0.333439</td>\n",
       "      <td>0.834646</td>\n",
       "      <td>0.518155</td>\n",
       "      <td>0.733467</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2017-01-01</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.191777</td>\n",
       "      <td>0.228714</td>\n",
       "      <td>0.233458</td>\n",
       "      <td>0.113097</td>\n",
       "      <td>0.587288</td>\n",
       "      <td>0.540363</td>\n",
       "      <td>0.821504</td>\n",
       "      <td>0.499070</td>\n",
       "      <td>0.070878</td>\n",
       "      <td>0.350906</td>\n",
       "      <td>0.382708</td>\n",
       "      <td>0.527559</td>\n",
       "      <td>0.435067</td>\n",
       "      <td>0.484730</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "        date  current_nor  competitor_keyword1_nor  competitor_keyword2_nor  \\\n",
       "0 2016-12-28     0.673861                 0.209573                 0.419770   \n",
       "1 2016-12-29     0.825105                 0.347860                 0.637547   \n",
       "2 2016-12-30     0.757225                 0.177978                 0.443791   \n",
       "3 2016-12-31     0.580342                 0.139352                 0.394573   \n",
       "4 2017-01-01     1.000000                 0.191777                 0.228714   \n",
       "\n",
       "   competitor_keyword3_nor  competitor_keyword4_nor    pv_nor    uv_nor  \\\n",
       "0                 0.449234                 0.188282  0.796087  0.755430   \n",
       "1                 0.381769                 0.169433  1.000000  0.981243   \n",
       "2                 0.411688                 0.223484  0.993961  1.000000   \n",
       "3                 0.329443                 0.156765  0.787497  0.842388   \n",
       "4                 0.233458                 0.113097  0.587288  0.540363   \n",
       "\n",
       "   new_uv_nor  launches_nor  department1_nor  department2_nor  \\\n",
       "0    0.723850      0.822929         0.138675         0.436600   \n",
       "1    0.889661      0.973677         0.121726         0.464468   \n",
       "2    0.925702      1.000000         0.160247         0.497678   \n",
       "3    1.000000      0.850804         0.154083         0.843706   \n",
       "4    0.821504      0.499070         0.070878         0.350906   \n",
       "\n",
       "   department3_nor  department4_nor  natural_flow_nor   all_nor  \n",
       "0         0.226955         0.952756          0.400720  0.473989  \n",
       "1         0.239352         0.724409          0.578999  0.543808  \n",
       "2         0.302289         1.000000          0.407589  0.535383  \n",
       "3         0.333439         0.834646          0.518155  0.733467  \n",
       "4         0.382708         0.527559          0.435067  0.484730  "
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "normalized.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "如上述表中所示，各个指标通过线性变换被映射[0 - 1]之间。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "data = normalized.set_index('date')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>current_nor</th>\n",
       "      <th>competitor_keyword1_nor</th>\n",
       "      <th>competitor_keyword2_nor</th>\n",
       "      <th>competitor_keyword3_nor</th>\n",
       "      <th>competitor_keyword4_nor</th>\n",
       "      <th>pv_nor</th>\n",
       "      <th>uv_nor</th>\n",
       "      <th>new_uv_nor</th>\n",
       "      <th>launches_nor</th>\n",
       "      <th>department1_nor</th>\n",
       "      <th>department2_nor</th>\n",
       "      <th>department3_nor</th>\n",
       "      <th>department4_nor</th>\n",
       "      <th>natural_flow_nor</th>\n",
       "      <th>all_nor</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>date</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2016-12-28</th>\n",
       "      <td>0.673861</td>\n",
       "      <td>0.209573</td>\n",
       "      <td>0.419770</td>\n",
       "      <td>0.449234</td>\n",
       "      <td>0.188282</td>\n",
       "      <td>0.796087</td>\n",
       "      <td>0.755430</td>\n",
       "      <td>0.723850</td>\n",
       "      <td>0.822929</td>\n",
       "      <td>0.138675</td>\n",
       "      <td>0.436600</td>\n",
       "      <td>0.226955</td>\n",
       "      <td>0.952756</td>\n",
       "      <td>0.400720</td>\n",
       "      <td>0.473989</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-12-29</th>\n",
       "      <td>0.825105</td>\n",
       "      <td>0.347860</td>\n",
       "      <td>0.637547</td>\n",
       "      <td>0.381769</td>\n",
       "      <td>0.169433</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.981243</td>\n",
       "      <td>0.889661</td>\n",
       "      <td>0.973677</td>\n",
       "      <td>0.121726</td>\n",
       "      <td>0.464468</td>\n",
       "      <td>0.239352</td>\n",
       "      <td>0.724409</td>\n",
       "      <td>0.578999</td>\n",
       "      <td>0.543808</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-12-30</th>\n",
       "      <td>0.757225</td>\n",
       "      <td>0.177978</td>\n",
       "      <td>0.443791</td>\n",
       "      <td>0.411688</td>\n",
       "      <td>0.223484</td>\n",
       "      <td>0.993961</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.925702</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.160247</td>\n",
       "      <td>0.497678</td>\n",
       "      <td>0.302289</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.407589</td>\n",
       "      <td>0.535383</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-12-31</th>\n",
       "      <td>0.580342</td>\n",
       "      <td>0.139352</td>\n",
       "      <td>0.394573</td>\n",
       "      <td>0.329443</td>\n",
       "      <td>0.156765</td>\n",
       "      <td>0.787497</td>\n",
       "      <td>0.842388</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.850804</td>\n",
       "      <td>0.154083</td>\n",
       "      <td>0.843706</td>\n",
       "      <td>0.333439</td>\n",
       "      <td>0.834646</td>\n",
       "      <td>0.518155</td>\n",
       "      <td>0.733467</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-01-01</th>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.191777</td>\n",
       "      <td>0.228714</td>\n",
       "      <td>0.233458</td>\n",
       "      <td>0.113097</td>\n",
       "      <td>0.587288</td>\n",
       "      <td>0.540363</td>\n",
       "      <td>0.821504</td>\n",
       "      <td>0.499070</td>\n",
       "      <td>0.070878</td>\n",
       "      <td>0.350906</td>\n",
       "      <td>0.382708</td>\n",
       "      <td>0.527559</td>\n",
       "      <td>0.435067</td>\n",
       "      <td>0.484730</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "            current_nor  competitor_keyword1_nor  competitor_keyword2_nor  \\\n",
       "date                                                                        \n",
       "2016-12-28     0.673861                 0.209573                 0.419770   \n",
       "2016-12-29     0.825105                 0.347860                 0.637547   \n",
       "2016-12-30     0.757225                 0.177978                 0.443791   \n",
       "2016-12-31     0.580342                 0.139352                 0.394573   \n",
       "2017-01-01     1.000000                 0.191777                 0.228714   \n",
       "\n",
       "            competitor_keyword3_nor  competitor_keyword4_nor    pv_nor  \\\n",
       "date                                                                     \n",
       "2016-12-28                 0.449234                 0.188282  0.796087   \n",
       "2016-12-29                 0.381769                 0.169433  1.000000   \n",
       "2016-12-30                 0.411688                 0.223484  0.993961   \n",
       "2016-12-31                 0.329443                 0.156765  0.787497   \n",
       "2017-01-01                 0.233458                 0.113097  0.587288   \n",
       "\n",
       "              uv_nor  new_uv_nor  launches_nor  department1_nor  \\\n",
       "date                                                              \n",
       "2016-12-28  0.755430    0.723850      0.822929         0.138675   \n",
       "2016-12-29  0.981243    0.889661      0.973677         0.121726   \n",
       "2016-12-30  1.000000    0.925702      1.000000         0.160247   \n",
       "2016-12-31  0.842388    1.000000      0.850804         0.154083   \n",
       "2017-01-01  0.540363    0.821504      0.499070         0.070878   \n",
       "\n",
       "            department2_nor  department3_nor  department4_nor  \\\n",
       "date                                                            \n",
       "2016-12-28         0.436600         0.226955         0.952756   \n",
       "2016-12-29         0.464468         0.239352         0.724409   \n",
       "2016-12-30         0.497678         0.302289         1.000000   \n",
       "2016-12-31         0.843706         0.333439         0.834646   \n",
       "2017-01-01         0.350906         0.382708         0.527559   \n",
       "\n",
       "            natural_flow_nor   all_nor  \n",
       "date                                    \n",
       "2016-12-28          0.400720  0.473989  \n",
       "2016-12-29          0.578999  0.543808  \n",
       "2016-12-30          0.407589  0.535383  \n",
       "2016-12-31          0.518155  0.733467  \n",
       "2017-01-01          0.435067  0.484730  "
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 数据探查"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "下图为本产品的微信指数(current_nor)与对应的日活跃用户数(all_nor)间的关系。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
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AAED5xsbG1NLSolWrVmlmZkZf//rX9dhjj9Xktd785jfr6aef1q233qrp6WnddttteuKJ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nw9fUdfXUcJ6QmIcI9QuitSE8Ldw5GUZ7xxtfTidKQVp6FXgO6t7V18u6CqtkqwicZEy4KEIz3B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\nBjP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rGjQKPbYTuAMfuDs60mHAVeGgUeiYrcDD+J/ZQakZrYiIZJHrItymhDeaWTfgLOCN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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x134685f8>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plot = data[['current_nor', 'all_nor']].plot(figsize=(20, 10), fontsize=20)\n",
    "fig = plot.get_figure()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 数据计算"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "通过pandas中计算相关关系的方法得到各指标间的相关关系系数矩阵。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>current_nor</th>\n",
       "      <th>competitor_keyword1_nor</th>\n",
       "      <th>competitor_keyword2_nor</th>\n",
       "      <th>competitor_keyword3_nor</th>\n",
       "      <th>competitor_keyword4_nor</th>\n",
       "      <th>pv_nor</th>\n",
       "      <th>uv_nor</th>\n",
       "      <th>new_uv_nor</th>\n",
       "      <th>launches_nor</th>\n",
       "      <th>department1_nor</th>\n",
       "      <th>department2_nor</th>\n",
       "      <th>department3_nor</th>\n",
       "      <th>department4_nor</th>\n",
       "      <th>natural_flow_nor</th>\n",
       "      <th>all_nor</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>current_nor</th>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.319319</td>\n",
       "      <td>0.256360</td>\n",
       "      <td>0.216808</td>\n",
       "      <td>0.057774</td>\n",
       "      <td>0.419055</td>\n",
       "      <td>0.590282</td>\n",
       "      <td>0.565802</td>\n",
       "      <td>0.590984</td>\n",
       "      <td>-0.487185</td>\n",
       "      <td>0.646741</td>\n",
       "      <td>-0.180519</td>\n",
       "      <td>0.516910</td>\n",
       "      <td>0.730586</td>\n",
       "      <td>0.511528</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>competitor_keyword1_nor</th>\n",
       "      <td>0.319319</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.224956</td>\n",
       "      <td>0.176306</td>\n",
       "      <td>0.159633</td>\n",
       "      <td>0.095338</td>\n",
       "      <td>0.215642</td>\n",
       "      <td>0.168993</td>\n",
       "      <td>0.167436</td>\n",
       "      <td>-0.208761</td>\n",
       "      <td>0.135216</td>\n",
       "      <td>-0.009691</td>\n",
       "      <td>0.111955</td>\n",
       "      <td>0.184174</td>\n",
       "      <td>0.145282</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>competitor_keyword2_nor</th>\n",
       "      <td>0.256360</td>\n",
       "      <td>0.224956</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.586304</td>\n",
       "      <td>0.407344</td>\n",
       "      <td>0.500739</td>\n",
       "      <td>0.476628</td>\n",
       "      <td>0.461982</td>\n",
       "      <td>0.521846</td>\n",
       "      <td>0.098612</td>\n",
       "      <td>0.185298</td>\n",
       "      <td>0.216245</td>\n",
       "      <td>0.392396</td>\n",
       "      <td>0.373121</td>\n",
       "      <td>0.374738</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>competitor_keyword3_nor</th>\n",
       "      <td>0.216808</td>\n",
       "      <td>0.176306</td>\n",
       "      <td>0.586304</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.778984</td>\n",
       "      <td>0.539522</td>\n",
       "      <td>0.453107</td>\n",
       "      <td>0.440469</td>\n",
       "      <td>0.514007</td>\n",
       "      <td>0.113688</td>\n",
       "      <td>0.002295</td>\n",
       "      <td>0.273704</td>\n",
       "      <td>0.395398</td>\n",
       "      <td>0.357437</td>\n",
       "      <td>0.310819</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>competitor_keyword4_nor</th>\n",
       "      <td>0.057774</td>\n",
       "      <td>0.159633</td>\n",
       "      <td>0.407344</td>\n",
       "      <td>0.778984</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.332215</td>\n",
       "      <td>0.271995</td>\n",
       "      <td>0.302536</td>\n",
       "      <td>0.309042</td>\n",
       "      <td>0.137202</td>\n",
       "      <td>-0.014225</td>\n",
       "      <td>0.208515</td>\n",
       "      <td>0.227351</td>\n",
       "      <td>0.143965</td>\n",
       "      <td>0.177798</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>pv_nor</th>\n",
       "      <td>0.419055</td>\n",
       "      <td>0.095338</td>\n",
       "      <td>0.500739</td>\n",
       "      <td>0.539522</td>\n",
       "      <td>0.332215</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.878603</td>\n",
       "      <td>0.740295</td>\n",
       "      <td>0.907580</td>\n",
       "      <td>0.226514</td>\n",
       "      <td>0.330349</td>\n",
       "      <td>0.545246</td>\n",
       "      <td>0.667853</td>\n",
       "      <td>0.540394</td>\n",
       "      <td>0.653283</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>uv_nor</th>\n",
       "      <td>0.590282</td>\n",
       "      <td>0.215642</td>\n",
       "      <td>0.476628</td>\n",
       "      <td>0.453107</td>\n",
       "      <td>0.271995</td>\n",
       "      <td>0.878603</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.775979</td>\n",
       "      <td>0.978876</td>\n",
       "      <td>-0.034607</td>\n",
       "      <td>0.455185</td>\n",
       "      <td>0.267750</td>\n",
       "      <td>0.733953</td>\n",
       "      <td>0.583961</td>\n",
       "      <td>0.597389</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>new_uv_nor</th>\n",
       "      <td>0.565802</td>\n",
       "      <td>0.168993</td>\n",
       "      <td>0.461982</td>\n",
       "      <td>0.440469</td>\n",
       "      <td>0.302536</td>\n",
       "      <td>0.740295</td>\n",
       "      <td>0.775979</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.801466</td>\n",
       "      <td>-0.035052</td>\n",
       "      <td>0.430017</td>\n",
       "      <td>0.217168</td>\n",
       "      <td>0.798144</td>\n",
       "      <td>0.506814</td>\n",
       "      <td>0.543992</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>launches_nor</th>\n",
       "      <td>0.590984</td>\n",
       "      <td>0.167436</td>\n",
       "      <td>0.521846</td>\n",
       "      <td>0.514007</td>\n",
       "      <td>0.309042</td>\n",
       "      <td>0.907580</td>\n",
       "      <td>0.978876</td>\n",
       "      <td>0.801466</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.008752</td>\n",
       "      <td>0.444853</td>\n",
       "      <td>0.254610</td>\n",
       "      <td>0.782249</td>\n",
       "      <td>0.615709</td>\n",
       "      <td>0.593885</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>department1_nor</th>\n",
       "      <td>-0.487185</td>\n",
       "      <td>-0.208761</td>\n",
       "      <td>0.098612</td>\n",
       "      <td>0.113688</td>\n",
       "      <td>0.137202</td>\n",
       "      <td>0.226514</td>\n",
       "      <td>-0.034607</td>\n",
       "      <td>-0.035052</td>\n",
       "      <td>0.008752</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>-0.302279</td>\n",
       "      <td>0.296323</td>\n",
       "      <td>-0.063312</td>\n",
       "      <td>-0.283212</td>\n",
       "      <td>-0.077217</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>department2_nor</th>\n",
       "      <td>0.646741</td>\n",
       "      <td>0.135216</td>\n",
       "      <td>0.185298</td>\n",
       "      <td>0.002295</td>\n",
       "      <td>-0.014225</td>\n",
       "      <td>0.330349</td>\n",
       "      <td>0.455185</td>\n",
       "      <td>0.430017</td>\n",
       "      <td>0.444853</td>\n",
       "      <td>-0.302279</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>-0.097642</td>\n",
       "      <td>0.441653</td>\n",
       "      <td>0.693517</td>\n",
       "      <td>0.756185</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>department3_nor</th>\n",
       "      <td>-0.180519</td>\n",
       "      <td>-0.009691</td>\n",
       "      <td>0.216245</td>\n",
       "      <td>0.273704</td>\n",
       "      <td>0.208515</td>\n",
       "      <td>0.545246</td>\n",
       "      <td>0.267750</td>\n",
       "      <td>0.217168</td>\n",
       "      <td>0.254610</td>\n",
       "      <td>0.296323</td>\n",
       "      <td>-0.097642</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.036021</td>\n",
       "      <td>0.054704</td>\n",
       "      <td>0.464905</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>department4_nor</th>\n",
       "      <td>0.516910</td>\n",
       "      <td>0.111955</td>\n",
       "      <td>0.392396</td>\n",
       "      <td>0.395398</td>\n",
       "      <td>0.227351</td>\n",
       "      <td>0.667853</td>\n",
       "      <td>0.733953</td>\n",
       "      <td>0.798144</td>\n",
       "      <td>0.782249</td>\n",
       "      <td>-0.063312</td>\n",
       "      <td>0.441653</td>\n",
       "      <td>0.036021</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.459646</td>\n",
       "      <td>0.438035</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>natural_flow_nor</th>\n",
       "      <td>0.730586</td>\n",
       "      <td>0.184174</td>\n",
       "      <td>0.373121</td>\n",
       "      <td>0.357437</td>\n",
       "      <td>0.143965</td>\n",
       "      <td>0.540394</td>\n",
       "      <td>0.583961</td>\n",
       "      <td>0.506814</td>\n",
       "      <td>0.615709</td>\n",
       "      <td>-0.283212</td>\n",
       "      <td>0.693517</td>\n",
       "      <td>0.054704</td>\n",
       "      <td>0.459646</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.790531</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>all_nor</th>\n",
       "      <td>0.511528</td>\n",
       "      <td>0.145282</td>\n",
       "      <td>0.374738</td>\n",
       "      <td>0.310819</td>\n",
       "      <td>0.177798</td>\n",
       "      <td>0.653283</td>\n",
       "      <td>0.597389</td>\n",
       "      <td>0.543992</td>\n",
       "      <td>0.593885</td>\n",
       "      <td>-0.077217</td>\n",
       "      <td>0.756185</td>\n",
       "      <td>0.464905</td>\n",
       "      <td>0.438035</td>\n",
       "      <td>0.790531</td>\n",
       "      <td>1.000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                         current_nor  competitor_keyword1_nor  \\\n",
       "current_nor                 1.000000                 0.319319   \n",
       "competitor_keyword1_nor     0.319319                 1.000000   \n",
       "competitor_keyword2_nor     0.256360                 0.224956   \n",
       "competitor_keyword3_nor     0.216808                 0.176306   \n",
       "competitor_keyword4_nor     0.057774                 0.159633   \n",
       "pv_nor                      0.419055                 0.095338   \n",
       "uv_nor                      0.590282                 0.215642   \n",
       "new_uv_nor                  0.565802                 0.168993   \n",
       "launches_nor                0.590984                 0.167436   \n",
       "department1_nor            -0.487185                -0.208761   \n",
       "department2_nor             0.646741                 0.135216   \n",
       "department3_nor            -0.180519                -0.009691   \n",
       "department4_nor             0.516910                 0.111955   \n",
       "natural_flow_nor            0.730586                 0.184174   \n",
       "all_nor                     0.511528                 0.145282   \n",
       "\n",
       "                         competitor_keyword2_nor  competitor_keyword3_nor  \\\n",
       "current_nor                             0.256360                 0.216808   \n",
       "competitor_keyword1_nor                 0.224956                 0.176306   \n",
       "competitor_keyword2_nor                 1.000000                 0.586304   \n",
       "competitor_keyword3_nor                 0.586304                 1.000000   \n",
       "competitor_keyword4_nor                 0.407344                 0.778984   \n",
       "pv_nor                                  0.500739                 0.539522   \n",
       "uv_nor                                  0.476628                 0.453107   \n",
       "new_uv_nor                              0.461982                 0.440469   \n",
       "launches_nor                            0.521846                 0.514007   \n",
       "department1_nor                         0.098612                 0.113688   \n",
       "department2_nor                         0.185298                 0.002295   \n",
       "department3_nor                         0.216245                 0.273704   \n",
       "department4_nor                         0.392396                 0.395398   \n",
       "natural_flow_nor                        0.373121                 0.357437   \n",
       "all_nor                                 0.374738                 0.310819   \n",
       "\n",
       "                         competitor_keyword4_nor    pv_nor    uv_nor  \\\n",
       "current_nor                             0.057774  0.419055  0.590282   \n",
       "competitor_keyword1_nor                 0.159633  0.095338  0.215642   \n",
       "competitor_keyword2_nor                 0.407344  0.500739  0.476628   \n",
       "competitor_keyword3_nor                 0.778984  0.539522  0.453107   \n",
       "competitor_keyword4_nor                 1.000000  0.332215  0.271995   \n",
       "pv_nor                                  0.332215  1.000000  0.878603   \n",
       "uv_nor                                  0.271995  0.878603  1.000000   \n",
       "new_uv_nor                              0.302536  0.740295  0.775979   \n",
       "launches_nor                            0.309042  0.907580  0.978876   \n",
       "department1_nor                         0.137202  0.226514 -0.034607   \n",
       "department2_nor                        -0.014225  0.330349  0.455185   \n",
       "department3_nor                         0.208515  0.545246  0.267750   \n",
       "department4_nor                         0.227351  0.667853  0.733953   \n",
       "natural_flow_nor                        0.143965  0.540394  0.583961   \n",
       "all_nor                                 0.177798  0.653283  0.597389   \n",
       "\n",
       "                         new_uv_nor  launches_nor  department1_nor  \\\n",
       "current_nor                0.565802      0.590984        -0.487185   \n",
       "competitor_keyword1_nor    0.168993      0.167436        -0.208761   \n",
       "competitor_keyword2_nor    0.461982      0.521846         0.098612   \n",
       "competitor_keyword3_nor    0.440469      0.514007         0.113688   \n",
       "competitor_keyword4_nor    0.302536      0.309042         0.137202   \n",
       "pv_nor                     0.740295      0.907580         0.226514   \n",
       "uv_nor                     0.775979      0.978876        -0.034607   \n",
       "new_uv_nor                 1.000000      0.801466        -0.035052   \n",
       "launches_nor               0.801466      1.000000         0.008752   \n",
       "department1_nor           -0.035052      0.008752         1.000000   \n",
       "department2_nor            0.430017      0.444853        -0.302279   \n",
       "department3_nor            0.217168      0.254610         0.296323   \n",
       "department4_nor            0.798144      0.782249        -0.063312   \n",
       "natural_flow_nor           0.506814      0.615709        -0.283212   \n",
       "all_nor                    0.543992      0.593885        -0.077217   \n",
       "\n",
       "                         department2_nor  department3_nor  department4_nor  \\\n",
       "current_nor                     0.646741        -0.180519         0.516910   \n",
       "competitor_keyword1_nor         0.135216        -0.009691         0.111955   \n",
       "competitor_keyword2_nor         0.185298         0.216245         0.392396   \n",
       "competitor_keyword3_nor         0.002295         0.273704         0.395398   \n",
       "competitor_keyword4_nor        -0.014225         0.208515         0.227351   \n",
       "pv_nor                          0.330349         0.545246         0.667853   \n",
       "uv_nor                          0.455185         0.267750         0.733953   \n",
       "new_uv_nor                      0.430017         0.217168         0.798144   \n",
       "launches_nor                    0.444853         0.254610         0.782249   \n",
       "department1_nor                -0.302279         0.296323        -0.063312   \n",
       "department2_nor                 1.000000        -0.097642         0.441653   \n",
       "department3_nor                -0.097642         1.000000         0.036021   \n",
       "department4_nor                 0.441653         0.036021         1.000000   \n",
       "natural_flow_nor                0.693517         0.054704         0.459646   \n",
       "all_nor                         0.756185         0.464905         0.438035   \n",
       "\n",
       "                         natural_flow_nor   all_nor  \n",
       "current_nor                      0.730586  0.511528  \n",
       "competitor_keyword1_nor          0.184174  0.145282  \n",
       "competitor_keyword2_nor          0.373121  0.374738  \n",
       "competitor_keyword3_nor          0.357437  0.310819  \n",
       "competitor_keyword4_nor          0.143965  0.177798  \n",
       "pv_nor                           0.540394  0.653283  \n",
       "uv_nor                           0.583961  0.597389  \n",
       "new_uv_nor                       0.506814  0.543992  \n",
       "launches_nor                     0.615709  0.593885  \n",
       "department1_nor                 -0.283212 -0.077217  \n",
       "department2_nor                  0.693517  0.756185  \n",
       "department3_nor                  0.054704  0.464905  \n",
       "department4_nor                  0.459646  0.438035  \n",
       "natural_flow_nor                 1.000000  0.790531  \n",
       "all_nor                          0.790531  1.000000  "
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "corr_result = data.corr()\n",
    "corr_result"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 数据可视化"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "上述的相关关系矩阵尽管能够说明各个指标间的相关关系，但是尚未做到一目了然，不能够直接观察出各个指标间的重要程度。下面通过数据可视化的方式表述相关关系矩阵。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "myfont = matplotlib.font_manager.FontProperties(fname='D:\\Update\\simsun.ttc')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "data.columns = df.columns[1:]\n",
    "data = data.rename(columns={'current':u'本产品', 'competitor_keyword1':u'竞对1', 'competitor_keyword2':'竞对2',\n",
    "                            'competitor_keyword3':'竞对3','competitor_keyword4':'竞对4', 'uv':u'访客', 'new_uv':u'新访客',\n",
    "                            'launches':u'启动次数', 'department1':u'部门1','department2':u'部门2', \n",
    "                            'department3':u'部门3', 'department4':u'部门4', 'natural_flow':u'自然流量', 'all':u'总计'})"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "import sys\n",
    "reload(sys)\n",
    "sys.setdefaultencoding('utf8') "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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P1b/HEeEXSKhfgMITE3TyTKLOp6dr1aF/1fCSqzPEZZuOvis6SrLZ5J25cxmf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nW7fsd2Fiau5IFh9uMIlFdUsHzzJgZ07OSkzE6vPu3a8+ljT/LCHXcze+ECZ6dzyvVp155PH32C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7lm/ZTOrNm0xf9S0GDKhVKtZMmUZ8cjKTli1FbzBgMOjp1LQ5rRo9Wd5NKqJly5aE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k1eZGVlMW7cOEwmEx9//HH1RS4iIiIiIiIiV4RKJS8aN27MqlWryj03YsQIxo8fz+bNmxkz\nZgwvvvgijRs3ZvHixYwZM4Zrr722WgIWERERERERkStLlVcb+bPWRUhICI0bN+b222/nww8/ZNas\nWRQUFHDLLbfQqVMnnJ2dL3qwIiIiIiIiInLlqVLy4o8//uDRRx9l2LBhBAUFsX//fgBcXFx49tln\nWbZsGcXFxbzzzju888471RKwiIiIiIiIiFxZKl2wE6BZs2a0aNGCzz77jE2bNjFr1izy8vJ47rnn\nCAoKok2bNnzyySe4ubnRunXr6opZREREREREpNaoXmfNq1TyIiUlhcmTJ/PYY49hMpmw2WxMmTKF\n8ePHEx4eziuvvMIjjzxCZGQkDzzwQHXHLCIiIiIiIiJXkEpNGykoKKBZs2ZMmDCBHTt28MYbb/Dv\nf/+bgoICnnjiCV5++WVmzZpFWloaW7duZefOnRQXF1d37CIiIiIiIiJyBahU8iIkJIRHH32UOXPm\nMH/+fOx2Oy+//DJ79+7lm2++wcfHh4kTJzJ//nxCQkL4+uuv6devH7m5udUdv4iIiIiIiIhc5qpU\n8wIgIiKCCRMmkJqayowZM4iOjiYyMhIXFxc6duxIYWEhr7zyCosWLcJut1dHzCIiIiIiIiK1xlDR\nixpX5eTFn/z9/XnuuedISEgofa5FixYUFhYCMGDAgAuPTkRERERERESueFVaKvVMgoODyz12cXG5\n0JcUERERERERESlV5eTFjh07qiMOEREREREREZEzqtK0kX379nH77bcTFBSExWL5y7aGYRAWFsYn\nn3xyIfGJiIiIiIiIyBWuSsmLqKgorr76aj7//HMARo0axaxZsyr8+8/HSlyIiIiIiIjI5caugp01\nrsrTRszmU7uYTKYz/vtMj0VEREREREREzkeVkxdll4TR8jAiIiIiIiIiUt0qlbw4ePAg06ZNq+5Y\nREREREREREQqqFTNi5ycHGJiYpg0aRI5OTnVHZOIiIiIiIiIw1LNi5pXqeRFmzZtmDJlCgUFBYwc\nObK6YxIRERERERERKVWlmheurq54enqWPlZRThERERERERGpblVaKjUzM5OEhAS6d++O2WzGZDLR\nq1cvTCYThmHQq1cvoKSQZ1FREXfeeSdffPFFhddxa97s4kR/CTC5utR2CFJNzG5utR1CjTKKimo7\nhBpTnJxa2yHUKLN7ndoOocYYBfm1HUKNMlkstR1CjYkMCartEGpU4RU0jTfzx6W1HUKNMjlV6fT8\nkubatHFth1CjCqIP1nYIIpe0Kh0dvb29WbJkSXXFIiIiIiIiIuLwtPJmzavyUqkiIiIiIiIiIjVJ\nyQsRERERERERcWhKXoiIiIiIiIiIQ1PyQkREREREREQc2pVTzlhERERERETkIlDBzpqnkRciIiIi\nIiIi4tCUvBARERERERERh6bkhYiIiIiIiIg4NNW8EBEREREREakCu0pe1DiNvBARERERERERh6bk\nhYiIiIiIiIg4NCUvRERERERERMShqeaFiIiIiIiISBUYhope1DSNvBARERERERERh6bkhYiIiIiI\niIg4NCUvRERERERERMShVTl5YbfbKSwsrI5YREREREREREQqqHLy4ptvviE5Obk6YhERERERERFx\neIZhXLY/jqrKq40MHz4cFxeX6ohFRERERERERKSCKo+8cHFxISsrqzpiERERERERERGp4JzJi4SE\nhArPmUymaglGREREREREROR055w2MnHiRHbv3o2zs3Np0qKgoAA3N7dy7QzDIC8vj3r16jFv3rzq\niVZERERERESkltkduDbE5eqcyYsPPvigwnMvvPAC//rXv6olIBERERERERGRsqpcsBMgNDT0Ysdx\nQTYcOcy01SsxDINBLVpx17Udym3feuI4z/+wgBAfHwC6N27Kve07AfDvZYtZe/gQ/u7ufHbnvTUd\n+nlZ+/sWpsycgd0wGNa7D/ffPKLc9iMnTjDx7WnsPXSQcaPu5u6bhpZu6/+30Xi6u2MymXFysjD7\nv1NrOvwqWb9/H1N//A673WDIde25p3uvctt/3bOb939ejNlkwsli4YmBQ2gbHsHRpCT+/uUsTCYT\nhmEQk5rK2D59ua1z11rqSeWs27ObN+bOwTAMhnS6nnv79C23fdXO7bz/w/eYzCaczBaevPkW2jVq\nDMBLX8xize6d+Ht589WEf9RG+FWyduvvvP7xx9gNO8N63cB9w4aX234kJoaJ773LvsOHGHfHnYwa\nPKR026zvv2fBimWYTWaahIXx0iOP4uzsXNNdqJKN8bG8u/03DMNgQHgT7ohqWaHN1sR43tuxhWK7\nHV9XN97q3geA2xbNx/Pk6Dcnk5n3b+hf0+Gft40xx3ln83rshsHAppHc2apdhTZb42N5d/MGio2S\nfk/rO6gWIj1/G44d4e11q7EbBoOiWnDXVdeW27419gQTFv9AiHfJ36BuEY2595r2pdvthsEDc7/C\n6uHJf/oPrtHYq+pc7+e2+DheWLmUel5eAHQLC+eeNlcDMGfvLn6I3gfA4KZRjGjeqmaDr4Jp/53C\nhnVrqeNWhwmTJtM0MrJCm7jYWCb//XkyMzOJjGrO3ye/jJOTE1/O+oxli38Ck4ni4mKOHTnMwp9X\nkJ6ayosvPA8mExgGsTExjB77ECNuH1kLPaxoU0oS/zuwB7th0L9eA25v2Ljc9m+OHWJ5QiwmoNiw\ncyw3h3mde+Pp7Ex2cRFT9+3kSE4WJkw8HdWG5j6+tdORStpw6CBvrVhacu7Yph2jOlx/xnZ74mIZ\n88UnvDxkOD2aRQGQXZDPvxf/yKGkRMwmEy/0H0zLEMc6Ny5r/cFo3vp5MQYGg9tezahOXc7Ybk9s\nDA9+9iGvDB1Bj6gWpc/bDTv3ffR/BHl78/otd9RU2Odtc1oK/zvyB3bDoF9QCLfXDy+3fU7MUZYn\nx2PCdPKznMvc9l3xdHJmXuwxfkqMBWBAcCjD6jWohR5cPNOyktlckIuv2cK7/o77GRWprConL/Ly\n8ujWrVvp49zcXJycnGptBRK7YTB11XLeHnYLgR6ejP76c7o2akJD/4By7dqG1mfK4GEV9h/QohU3\nt72aV5YuqqmQL4jdbuffH3zA/738ClZ/f+58+kl6duhARP1TB1cfby+ef3AMKzZuqLC/yWTiw1f/\njbenZ02GfV7sdjuvL5zPew+Mwertwz3vTaN781aEBwWVtmnfpCndWpRcBB6Ij+OF2bP45slnaWi1\n8vljT5a+zqDXXqFHy9a10o/KstvtTJnzNf8b9zhWH1/ufv01erRuS3jduqVtOkQ2p3vrtgAciI3h\n+Y9m8u0/JgEwpGMnbuveg0mzPq2V+KvCbrfz2ocz+WDSi1j9/Lnz+Wfp0b49EaH1S9v4eHnx/OgH\nWLlpY7l9E1NT+eqnRSyY9jbOzs48O/W/LF67hsE9etZ0NyrNbhhM27qJqd16E1jHnTHLf6JzSH0a\nnryYBcguKmTats283vUGrHXcSS/IL91mNpl4q3sfvFxcayP882Y3DN7atI43+wwg0N2DB3+cT5cG\n4TQsc1GTXVjImxvX8kafAVjdPUjPz/+LV3Q8dsPgzTWrmDZ4GIHuHjww72u6hjeioZ9/uXZt64We\nNTExZ8c2wv38ySksrImQz1tl3k+ANsF1ea1X+cTr4fRUfozez4yBw7CYTDyzfDHX1w8jxMu7JrtQ\nKRvWriXmxAm+nPcde3bt5I3XXuX9jz+r0O79d6Zx252j6Nm7D2+89i9+XLiAm4aPYOSouxk56m4A\n1q3+lTlfzsbLywsvLy8+/OJLoOQYePPAfnR1kOOW3TB4N3o3r7frQICLK49sWcv1gcGEeZw6V7g1\nrBG3hjUCYENyAnNPHMHzZNJ4evQe2gdYmdjqamx2O/l2W630o7LshsEbyxbz9m13YvX0YvSsj+ja\npBnhAYEV2v1v1Qo6hDcq9/xby5fSqVFjXr3pZortdgqKimoy/CqxG3beWLqId+64B6unF/d//H90\nbRpJeKC1QrvpK5fRoVHjCq/x9eaNRARaySksqKmwz5vdMHj38H6mtLiq5LO8YzPX+1sJc/cobXNL\naENuCW0IwIbUZObFHcPTyZkjudksTozjvTbtsZhMvLBnGx39AqnnVqe2unPBert5MriOF1Mzk2s7\nFJGLosqrjdSpU4emTZuWPnZ3d+eTTz7h+PHjFzWwytoTH0cDX1/qevvgZLHQu1kUqw8dqNjwLHOS\n2obUx9v10rkg2BX9B2Eh9QgJCsLZyYm+XbqycmP5izs/bx9aNGmCk8VSYX/DMLDb7TUV7gXZfeI4\nDQIDqefnj5PFwo1t2rFq765ybdzKJM1yCwrOWEx204FoQgMCCPZ17LtAu48eIcxqpZ5/QEl/r76W\nX3ZuL9fm9P6ay/S3XeMmeLu711i8F2LXgWjC6tYjxFryOe7XuQu/bNpUro2ftzctGjfGcobPsd1u\nI6+ggGKbjfyCQqz+/hXaOJK9qcnU9/SmrocnTmYzvRo0ZG3siXJtlh87QrfQMKx1St5DX9dTdYUM\nw8B+CU6r3JucSH0vb+p6epX0O7wxa44fKddm2eEDdG8YgfXkiaXvafWUHN2exHjq+/hS18sbJ4uF\nG5o0Y/WRQxXaGZz5DUzMzmL9sSMMOsNIHEdTmffzbI5mpNMi0IqLxYLFbKZtcF1WHavcvjVtza+/\n0HfAQABatGpNdnY2qSkpFdr9/ttmuve6AYB+AwexeuXKCm2WLVnCDX37VXj+t00bCa1fn+Ayyena\ntC8zndA6HgS71cHJbKZHUAjrkisWbP/TisQ4egWFAJBTXMTO9DT6nbxDbTGb8XBy7JFwe+JiaODn\nTz0f35LvbVQLVh/4o0K7OVs20zOyOX4epy58cwoK2HbiGINal4w6cjKb8XDg88g9sTE08Aso7Wvv\nFq1YHb2/Qrs5mzfRK6oFfmUu8gESMzNYfyCaIe2urqmQL8i+7ExC3dxLP8s9A4NZl5p01vYrk+Pp\nGVjyPTyWm0OUpzcuZjMWk4k23r6sSUmsqdCrRUtnNzxNFc+j5OIwDOOy/XFUlUpefPvttyxadGpk\nQnZ2drnt9957L6+88grffffdxY2uEpJysgnyPHXnJsjTi6Sc7ArtdsXHcc/sT3l64VwOp1y62cfE\nlBTqlsmWBwcGkniGk6qzMZlMjJn0T+546gnmLl1SHSFeNEmZGQSXuaMX5ONDUkZmhXa/7N7FrVOn\n8NRnH/HPm2+tsP3nndvp26biUHVHk5iRTnCZu7VBfr4kZaRXaPfL9m2MeGUyT3wwnYl3jqrJEC+a\nxNRUggNP3eEKDgggMTW1UvsG+fszavBN9Bv7IDc++ABeHh50bNO2ukK9KJLz8ggqk1iy1nEnOT+3\nXJvjWZlkFhYwftXPjFm+iKVHT10Am0wmnl69jDHLF/HDoegai/tCJeXmElTmzm2QhwfJuaf1OzOD\nzIICHl/yAw/+OJ8lBy+d/gEk5+QQ5Fm2j54k5+RUaLc7IZ5758zmmUULOZx66pj99rrVPNKpC5fC\nIl6VeT8BdiclcP/3c3l2+WKOpKcBEOHrz47EeLIKCsgvLmZDzHESz/C32hEkJyYSFHwqqWC1BpGU\nVP4CJiM9HS9vb8zmktMoa1AwycnlL5AK8vPZtGFdaYKjrBU/L+WGGysmNWpLckE+1jIJU6urG8kF\nZx4FVWCzsTklia7Wkv9H8fl5+Dg78/re7YzdvIap+3ZSYHPskRdJWVkElRn1E+TlTVJWVoU2q6P3\nM/yqa8qdyMdmpONbx51XFi3k3k9m8triHx165EVSVhbB3mX66u1NUlbmaW0y+fWPfQy/5roK+7+1\nbAmP3tAHuAQOUkBKYQHWMsmkQFdXUs4yYqTAZmNzegpdA0rOq8PdPdmVlU5WcRH5Nhub0lNILLy0\nRgOKXO7OOW1k8+bNrFixggkTJgCwevVqJk2aRL169cq1y87O5rXXXqNt27aEh4dXS7DnKzIomHn3\nPYibszPrjxxiwo/f8dXdo2s7rFrx6WtTsPr7k5qRwdhJ/ySifn2ubuH4d/z+So+WrejRshXbjhzm\n/Z8X8+7oMaXbim02Vu/dzaN9B9RihBdXj7bt6NG2HdsOHmD6DwuZ/ujjtR1SjcrMyeGXzZv46X8f\n4OnuztNvvM6i1b8yoGu3c+/swGyGQXRaKlO79yG/uJhHVi6mRYCV+p5evNvjRgJOTiV56tflhHn7\n0CYw6Nwvegmw2e38kZrMWzcOJL+omId++o6W1iDql5lSc6mLtAYx9877Sv4GHTvChCU/8tXIu1l7\n9DD+ddxpGmjl95gTZx2dcSlpFhDInJvvwM3JiQ0xx3lh5VJmD7uNhj6+3NGqLU8uW0QdJ2ea+gdi\nuRQyNhdg7epfad22HV4n63/8qbi4iLW/rmLso4/VUmQXZn1KIq18/UqnjNgMg+jsTMY1a0mkty/T\no/fw1bGD3BPRrJYjvTDTVizl4R69Kjxvs9vZnxDPU7370bxeCG8tX8qsjet4oEv3Wojy4njr58U8\n3Kt3hefXHvgDfw8PmgXX4/ejh882iPmStSEtmVZevnieHCkU5u7BrSENeW73VupYLDT28MRyiSRt\nRK4U50xeFBYWMn369NLHXbt2xdPTk88//7zCEP2ioqIaL5pn9fAkoUwGOTE7C6tH+XoO7mWG2ncK\nb8QbvywjMz8P70twDltQQABxSafu7iQkJxMUEPAXe5T35/B6fx8fenXsxK7oaIdNXli9fYhPPzXy\nIDEjA6vP2edHtwuPICY1lYzcXHxO3uVet38fUSH18bsEanwE+fgSn3Zq9EFiWjrWvyh41q5xE2JS\nksnIycHHw+Os7RxRkL8/8WXuUiakpBBUyakfG3dsJzQ4GJ+TFwQ3dOjI9v37HTp5EVinDgm5p+7G\nJ+XlEuhWfoqPtY47Pq6uuFosuFostAkM4mB6GvU9vQgoM5Wka2gD9qUmXxLJC6u7Owll7q4n5uQQ\neNrUJquHBz5ubrhanHC1ONE2uB4H0lIvmeRFoIcHCdmn7tgm5mQTeNr30d25zN+gsHCmrv6FzPx8\ndsXHseboIdYfOzGkOCMAACAASURBVEKhrZjcwiJeXrGUf/a6scbir4rKvJ/uZc4BOoY2YKphJ7Mg\nH29XNwY0iWRAk5LClzO2bibI3XGOW/PnfMMPC+aDyURUixYkJsQDJSO6khITsVrLf998fH3JzsrC\nbrdjNptJSkyo0Gb50iX0PsOUkQ1r1xEZ1RxfP79q609VBbq6kViQV/o4qSCfQNczT+H6JSG2dMoI\nlIzSsLq6Eeld8veqq7UuXx+rOHXKkVi9vEjIyih9nJiVifW0JNO++DgmLpyPgUFGbh4bDh/EYjLT\nMiSEYC9vmtcr+X/QMzKKzzeur9H4q8Lq5UV8Zpm+ZmZiPa3WzL74WCYu+BbDgIy8XNYfjMZiNrMr\n9gRrovez/mA0BUXF5BYWMHnhPCYNGX76r3EYAS6uJJYZNZRcUEDAWepFrUxOoKf1/9u777imzv0P\n4J8kDJUhIiIO3AO31moVavE6US/WUXeLoypa0Uoptlqqtmptta12XL1or3vg3lStq0UUr1sEqYiL\noayAGBkJ5Pz+4Ob8iAkoCslRPu/Xy9fL5Jwkz/cknPE9z/N9auo951WzNrxqFn63a+7F6fXiICLz\ne+awEQ8PD4PnBgwYYLRugjmq/beo6YKER5l4mPUImoICHLsZg7cbNdFbR1nkoiH64QMIAvQSF8L/\n/r0KWjVpivgHD5CUkgKNRoMjp8PQvfNbxa5ftKtjTl4usnMKT06yc3Nx9vJlNKlXr9zb/KJa1nVF\nQnoaHmQoocnPx9FrV/BOC/1ES0KRIUAxiQnQFOSLiQsAOHr1Mvq0k/6QEQBoWb8B4lNT8UCZXhjv\npQvwbNNWb52EIomrmPj7yM8v0EtcCAIkPU5Np1XjJoh/+BBJqYW/48Php+HZqXOx6xeNycWpBiJj\nbyJPrYYgCDgXGalX6FOK3ByrI1H1GA+fqKDRFuBE/D141NZvs0ftuohMS0GBoEVufj5uKNNR394e\nufn5yM4v7JKck5+PC8kP0NBe2vVbdNyq10Di4yw8VD2GpqAAJ+7GwaNufb113nZtgMiU5MIif/n5\niE5LQQOJz1JQVIsaNZH46BEePs6CpqAAx2/dxNtPFfdTFhlaEZ38EIIgwL5SJfi+5Y7d70/AjjHj\nML+XF96oU1eyiQvg+b5PZU6RWNNSAAGw/99FcGZu4fEnWaXCX/fvoldD/WO1OQ0eNhz/2bwV/9m0\nBW97dseR0EMAgKjIa7C1s4WjkZsEHTq+iZPH/gAAHD50EG97dheXqVSPcfXyJbz9juHd+ONHDxut\ng2FOze0dkJSTjeTcHGi0WpxKSUJXp5oG66nyNbiaqYR7kWXVrKzhbF0ZCdmFia3LGemobyPtGwYt\nXGojISMDDx5lFv7dxkSjWxP9niI7ff2w09cPu3yno3tzN3zaux+6NW0GRxtbONvZ4/7/hn9duHfX\noNCnlLSoVQcJGcr/xZqPY9HX0a2p/uw5uz6aiV0fzcTuaTPxD7eWCOw7AN2auWFq917Y6/cJdn00\nE18Peg8dGzSUdOICAJrb2iMpN0f8LZ9MS0ZXxxoG6z3Jz8e1rAy4V9NflqkpLJyckpeLcGUKejhJ\noy7NyxBei359RIVeaKrUCRMmGC2iZw4KuRyfePbEzL07C6e7atUGDRyrY2/kVchkwLut2+Fk7E3s\nibwCC7kC1hYW+LpIxff5hw/iUmI8snJyMWRNMD7s4o4BLaU7K4VCocBsX19MmTcXgqDFoF690cjV\nFTsO/w6ZTIb3+nohPTMDoz75BNm5OZDJZNhyYD/2/LoCyqxH+GTxNwBkKNAWoP87nnDvIN0CTAq5\nHIEDB2P6mtWFU4e+2RkNnWti97mzkMlkGNy5C05cj0To5QuwVFjA2tIS34z6/xoQuWo1/hsXi9lD\n3ivhU6RDIZdj1rARmPavnyEIAt7t4oGGLrWw63QYZDJgiEc3HL96GYf+GyHGu3jCRPH1X6z7Dy7G\nxuJR9hMMmDsHvv3/iYFdjE/9Zm4KhQKffzgRUxd8Da1WwOCePdGobl3sPHoEkMnwXu8+SM/MxOjP\nAvEkJwdyuRxbQg9h97Kf0KZpU/Tq0hUjAwNgobBA84YNMbR3b3OHVCKFTI6PO3RGYNhxaAH0b9AY\n9e2rYv/tm5BBBu9GTVHfvio61ayND/84BLlMBu9GTdDA3gEPnqgQdOZPyGRAgVZAr3oN0Mml9jM/\nUwoUcjlmdnZHwLHfC6fWbNIcDRyqYd/NG5ABGNisBepXdUCn2nUx/sAuyGVyDGzqhgYO0rkj/SwK\nuRz+b3vC/+BeCIKAAS1aoUE1R+yNjoQMMrzbsjVO3o7F3qhIWMjlsLawwFe9X52pbot6nu/z1L07\n2HfzBixkclhZKDD/nf+v9xB06hgeq/NgIZPjk7c8YGOmWcqepavH24gIP41RgweiUuXK+HzufHHZ\nrJkz8FnQXFR3coKv3wx89cVs/Cd4JZo2a44B774rrhd26hQ6d+kK66cK0Obm5uDCf88hcI60prNW\nyGTwa9oKn135LwQI8Krlivo2tjiYeB+QAf+sXXij40xqMt50dIL1U+eA05q1xDfRV1EgaFGrUhV8\n2qKtsY+RDIVcjoBeXvDfvqVwiuO27dGguhP2XrkIQIZBTxWnfLqnsX+vvph/cC8KtFrUruqAL/pL\nd4pjhVyOgD79MXPrRmgFAd7tOqCBUw3suXQBMhkw6KmpnV91CpkMfg2b4/PoK9BCQD/n2qhfxQYH\nHyZABhkGuBROFxquTMWbDtUNfstf/x2JxxoNFHIZZjRyg43FC10qScbSrFREanKRpS3A+PR4jLZx\nQO9Kds9+IT2XV7GY+qtOJpTRbdqQkBAIgoBRo549X3nav1aXxUe+Emx7vrpjIEsrL9qwevXrTG4r\nnS7PpmBRy/Au3OsqM2S3uZtgUvIqr94QuhdVkWIFAG12zrNXel1Mn2ruFpiUepa0EiDlqUon6d5o\nKQ+yV/yCuTRUp8LM3QSTyouNM3cTTKrpaWlPDvCy/Na8vueLv06QZi+rUk+Vaszp06exadMmtGzZ\nsizejoiIiIiIiIhI9Nyp3bi4OPj7+6Nz584QBAFarRZqtRoBAQE4f/48du7cCSsrKyQmJqJOnTrl\n2WYiIiIiIiIiqkBKTF4IgoBTp07hH//4B1xdXaFQKNCv3/+P1V20aBEsLCwwduxYnDhxAsePH0dk\nZCSOHj1a7g0nIiIiIiIiMgetYDiBBZWvEpMXcXFx+OWXX3Dx4kX4+/vD1tYWHTt2FJfb2NjA3r5w\nuqX+/fujf//+GDRoUPm2mIiIiIiIiIgqlBJrXjRp0gS7d+9Gv3798NtvvyE3N1dvua768o4dO3Dl\nyhUAQJWn5nwnIiIiIiIiInoZz1Wws1WrVvD19UWlp6b8EgQBe/fuRWhoKKpWrVouDSQiIiIiIiKi\niu2ZBTsFQcCBAwfQpk0bg3muAUCj0WDt2rXiY2PrEBERERERERG9qGcmL7755hskJSXBycnJYJlM\nJsOwYcOwadMm1KpVC3l5eUhKSiqXhhIRERERERFJgSCYuwUVT4nJC7VajaFDh8LNzQ0AsHjxYuzd\nuxdAYY+MtLQ0xMTEIDU1FUqlEnK5HHPmzCn/VhMRERERERFRhVFi8sLKykpMXKSkpKB///5IS0uD\nhYUF8vPzMXDgQACAv79/+beUiIiIiIiIiCqkZw4b0XF2dsbUqVONLjt8+DB27doFNzc3BAQElFnj\niIiIiIiIiIieO3lREi8vL3Tu3Bn+/v7IysqCvb19WbwtERERERERkeQILHphcmWSvAAAR0dHrF+/\nvqzejoiIiIiIiIgIACA3dwOIiIiIiIiIiErC5AURERERERERSVqZDRshIiIiIiIiqgi0rHlhcux5\nQURERERERESSxuQFEREREREREUkakxdEREREREREJGlMXhARERERERGRpLFgJxEREREREVEpCCzY\naXJMXhARERERERHRS3v06BH8/f2RmJiIunXrYvny5bCzszNYb926ddi5cydkMhmaNWuGxYsXw8rK\nqsT35rARIiIiIiIiInppq1atQteuXXHkyBG89dZbCA4ONlgnOTkZGzduxO7du3HgwAEUFBQgNDT0\nme/N5AURERERERERvbTjx49j8ODBAIDBgwfj2LFjRtfTarXIyclBfn4+cnNz4ezs/Mz35rARIiIi\nIiIiolJgzQvjlEolnJycAAA1atSAUqk0WKdmzZoYP348unfvjsqVK8PDwwPu7u7PfG+zJC+cpk0y\nx8dSOavk1szcTSAqE5XbtDJ3E4iISvbvZeZuAdFLcxw7ytxNIKIXMH78eKSlpRk8P3PmTIPnZDKZ\nwXNZWVk4fvw4Tp48CTs7O8yYMQMHDhyAt7d3iZ/LnhdERERERERE9FzWrl1b7LLq1asjLS0NTk5O\nSE1NhaOjo8E6Z86cgaurKxwcHAAAvXv3xuXLl5+ZvGDNCyIiIiIiIiJ6aT169MDu3bsBAHv27EHP\nnj0N1qlduzauXr2KvLw8CIKAiIgING7c+JnvzeQFERERERERUSlohdf338uYNGkSzpw5g759+yIi\nIgKTJ08GAKSkpMDX1xcA0LZtW/Tt2xeDBg3CwIEDIQgChg8f/sz3lgmsNEJERERERET03CasDDF3\nE8rNmqkjzd0Eo9jzgoiIiIiIiIgk7ZVLXly8eLHUr4mKioJGoynVax4/fmz0eWNVVYmIiIiIiExF\nrVYbPHfr1i1O30mvtVcueTFx4kTExsaW6jV2dnYYOXIk0tPTn/s1AQEB+OCDD+Dj4yP+Gz16NN59\n9108efKktM1+aaGhodi7d+9Lv49Go0FYWFgZtKh8VaR4K1KsQMWLt6LLyckp1fqvc4K4tNsCKN/t\noVKpkJeXV27vX5zMzEzEx8c/9/qXL1+GSqXSe+7atWsvtD1LkpKSUqbvJ3UVKd6KFCvw+sR77do1\nxMXFPde6SUlJRs/zn/f1RaWnp2Pbtm3Iz89/5rqXL19GUlISkpOTDf6dPXsW169fL/XnP6/bt29j\n0aJFesmKWbNm4dSpU0bXDw8Px/nz540u8/X1RXJycnk0k6hMvXLJi6pVq6Jp06alek29evXQsmVL\nJCUlic8JgoCFCxfixo0bRl8jk8nw3XffYcOGDeK/4OBgNGrUCDY2Ni8Vw4vo06cPfv75Z72TtRfZ\nISsUCsyaNQsZGRll2bwyV5HirUixAhUv3ori0KFDRr/Hffv2Yc+ePc/9PufOncOHH36I7Ozssmze\nC7t37x6WLVtW7PK8vDysXbsWiYmJ4nNltS2A8t0eFhYWmDBhAmJiYl74PTZv3oyjR48aXZacnAyl\nUmnwfHh4OCZNmoTc3Nxi3zc7OxsnTpwAUFip/MyZM0hKShK/i2XLliEkpGzHGv/00084c+aM3nNF\nv1cAePjwod7js2fPPvM7leoFQUWKtyLFCrw+8W7atAkHDx58rnV3796Nr776yuB53T7u0qVLRl9n\nrEd39erV8eDBA2zcuFF8LioqymhPh7179yIiIgL37t0z+HfmzBmcPXv2udr/Itzc3JCUlIQDBw6I\nbXR3d8c//vEPo+t7eHhg7dq12Llzp8GyqKgo1KxZs9za+roSBOG1/SdVFuZuQGnJ5Yb5ll9++QVj\nxoyBo6Mjli5dirCwMDg4OIgbXiaTAQCWLl2q92XIZDJs3rwZCxcuNHhPhUJRThE8n/Pnz+Pnn3/W\ne87S0hK+vr5iDDExMfDz88PYsWMBACEhIZDL5ahcuTIEQUB0dDTS0tLw/fffi+8hl8vh5OSEatWq\nmS6Y51CR4q1IsQIVL96KqmfPnvD29samTZv0ToCGDh2KPn36YMCAAbCysjJ43enTp/H222+LjwcM\nGIDr16/jyZMnqFKlivj8pUuX0KBBA6NzhZen+vXr49atW1AqlYiLi0PVqlVhYWGB0NBQ1KxZE/fu\n3YODgwPi4+NRp04dAC++LYDy3x5ff/21Xu/FS5cuYfDgwXjzzTcBANWqVYO3tzd69+5t9PUxMTFQ\nqVTi+tnZ2cUeL2vUqAF/f3+MHDkSXbt2hUqlgq2tLc6dO4cZM2agUqVKxbazSpUqOHXqFHJzc2Fl\nZYU6deogJCQEnp6e0Gq1SE5Oxrhx40oV+7P07NkT586dg7u7O0JDQ9GrVy9s2rQJtra2qFevHlJT\nU7F161b8/vvvsLAoPH3q2rUrxo4di6ysLIwePRoff/yxXi8RrVaLGzduYP/+/eLvQyoqUrwVKVbg\n1Y43KysL9vb2yMvLQ+XKlfHxxx/rLY+JiYGbm5vB6/78808sXrwYAHDz5k00a9YMQGHvazc3N8yc\nORMJCQkYOHCg3ut0sx8EBweL+0eZTIZHjx5Bq9Xi5MmTEAQB169fx5gxY/Dpp5/qvV6hUGDr1q2o\nXLmyQZvS0tIwfvz4l9oexUlJSYGzszPGjBmDWrVqASg8fvj7+0OtViM+Pt7otJOzZ89GZGSkwfOW\nlpbl0k6isibZ5MUPP/yAv/76C1WrVhWfi4+PR2pqKry9vcULFkEQIJPJYGVlBV9fXwQGBiIwMBBA\nYVb5xIkTGD16tPgeJ0+exNGjR7Fw4cISExRardYg62TKTFSnTp3w/fffw9LSEvv374ePj4+YuFm2\nbBk6deqkd4ILACNH6leFPXfunME6Orm5ubh79654AEhPT0d4eDh27NiB8ePHo0ePHuUQVfFMHW9K\nSgr27dsHBwcHPHz4UPz9mIKpY42Li8Nff/0Fa2trxMbGok+fPujatWs5RGacqeMtKjg4GJUrV4aP\nj08ZRUPFqVSpEqZNm2ZwAmRpaYlff/1VvFhPTExEXFwc3nnnHeTl5WHevHniibDuAl0mkyEgIEB8\nD0EQEBcXh06dOuGnn34ySTwrV65EaGioeKyZMmUKCgoK0KFDB4wcORKJiYnw8/Mz+toX2RYATLI9\nTp8+jZkzZ4qPR40apbf8yJEjejWf1qxZgz/++AOWlpbi8bZWrVro2LEjZDIZ5HJ5scdFuVyOqVOn\nYvLkyfjjjz9w/fp1dO7cGVFRUZg/f77euleuXEGtWrX0kj1jxowRe25kZGTAw8MDdnZ2uHLlCnr3\n7i3emNBoNPj777/RunXrUm0LXby//PKLXhLogw8+EGOytLRE586d0alTJ2zbtg2+vr7ixV5UVBTc\n3NwwadIkZGVlwdLSEgsWLICdnZ1ecqp79+56F3vmPN6aI15zHW/NEas5j7fmiLeosjreDhs2DDVr\n1hQTJx988AGAwhuOWq0Wly5dQkhICNq2bSu+5s6dO4iNjcXXX38t3vD49ddf0bVrV/Fc//3338eW\nLVsMkhf9+vXD7t27kZ2djenTp8PS0hJWVlbw8fHBokWLjCYAitJqtZg9ezYaNWpksOzQoUMoKCh4\nqe1RnF27dukdowRBQG5uLk6fPg2VSoWCggLs37/f4HWurq5wdXU1eF63PyWSOskmLwICAvRO1rRa\nLQYNGoS8vDxMnjwZffr0gbW1dYnv4eLigujoaGzfvh3Dhw+HRqPB0aNHMXPmzGf2rNBqtQgICNDb\naefn50Or1b5cYKWgO4lTqVTYtWsXhg0bhrS0NPEkDgCUSiWsrKxga2uLuLg4qNVqtGjRAkDhHbU2\nbdrggw8+EHdKgiAgISEB7777LnJzc8UTiurVq2PgwIEIDw83W1chU8b7+eefY8WKFeKdv4CAAISH\nh4uf8zrFGhQUhB9++AG1a9eGWq3GgAEDsH//fqN3CV6HeHVu3ryJI0eOYNCgQSaLs6IbNGgQMjIy\nMGzYMPFvKzIyUu8kEyi8u+/u7o6NGzfin//8J/z9/QEUJq2mTJki/iZycnKgVCphYWGB1atX6110\nl7epU6eiSZMmsLKygqenJw4dOoTz588jKCgId+7ceebrS7stLCwsTLI9LC0t0b9//2KX3759W++m\nwYQJEzBhwgSD9Q4cOIDt27fj4cOHqFSpEjZs2ACNRoMmTZpgwYIF4npubm4ICgpCWFgYPD09ERYW\nhszMTIwbN05MhgiCgNjYWLRt2xarVq0CAAQGBuLevXuwtrbGrVu3cOnSJSgUCmRlZaFLly64evUq\nLl++jIKCAqSnp0Or1SIkJKTUPVH69u2Lxo0bw9raWjyhX7lyJdq1awd3d3fcvHlTXPfy5cv4+uuv\nxce//fYb3N3dMWzYMPG56tWrG3zG0+cb5jzemiNecx1vzRGrOY+35ohXpyyPt7m5udiwYUOxy7t3\n726wHw0JCcGoUaMQEBAAhUKBIUOGGCSNOnbsiP/+979Qq9UGPd9Wr16N9PR0ZGRkoEmTJvj5558x\nc+ZMNG7cGDExMahSpQrq1atntD02NjZQKpVG/5atrKzQpEkTAIUJloYNGz7XNngelpaW+PDDD41u\n84sXL+L33383+rqwsDB069YNQOExxdhvU61WY/fu3Rg+fLjRHu9E5iTZ5MXT9u/fDw8PDxw9ehQe\nHh5Yt25dsZn7HTt2IDQ0FPn5+bh27Rp27dqFgwcP4vHjx7C0tERgYCAEQUBOTg4GDx6MMWPGGLyH\nvb09vv32W70ToezsbAQHB5dbjEDhnbaZM2ciLy9PPLFTqVRQKBQ4cOAAUlNT4ejoiLFjx4oXb506\ndcKSJUvQuHFjbNmyBS4uLlCpVHB1dcWQIUPQu3dvvYOQt7e3OD7uaabeSZkr3itXruDmzZviAbB5\n8+aIiYkp15Mpc8VatPu3lZUV7O3toVQqy72bqzl/ywUFBThx4oTJexA9j2PHjuGLL77A7NmzER8f\nj4KCAigUCkyfPh3//ve/sXbtWqxduxYtW7bE3r17sXnzZvz4449G75RIQUpKCmJjYyGXy3HixAnM\nmTMHO3bsAFB4R3zMmDF6J6JarVbcz9SpUwddunQBAKxbtw4JCQkIDg5GcHAwBEHAgwcPUKVKFaxc\nuRJBQUEmj61Hjx4YNGgQPD09ER8fj7lz5yInJ8fgDpVGo0FBQQGysrJeeFsAptkeZTEk8tChQ3Bz\nc8PatWuxevVqtG3bFh4eHrh27Rp2795tsH6fPn2wY8cOWFpaYuvWrVi7di1SU1ORnp6OPn36ICcn\nB35+fnq9MRYsWIBKlSrht99+Q0JCAjw9PdGnTx+0aNECvr6++Oyzz9C1a1eEh4fjjz/+MOjJURoN\nGzbE6NGjsXLlSjg4OCA8PFy826uTk5MDV1dXvYsehUKBBg0avPDnmuuiwNTxmuN4q2PqWM11vNUx\nx2+5rI+3z/q7eHofplQqER0djS+//BIjRozArFmz0LFjR8yYMQNJSUlITEyEt7c3HBwcIJPJULNm\nTQwdOhRpaWlYs2YNJk+eDAcHB0RERGDAgAHYs2cP2rVrJ+6L3dzcMHHiREybNg0dOnQAUNgT/Isv\nvhDbYGwYRlGZmZlIS0vD/v374eTk9CKbxYCu10xxiiZTNBoN1qxZg0OHDkGlUmH79u2wtbXFrVu3\n8NdffyExMRF5eXlQqVQQBAF2dnZ45513kJ+fX+wQRyqkhXRrQ7yuXonkhVKpxKZNm7B+/XocPXoU\njo6OYrdLYwe/06dPw8/PDx07dizV56hUKqSkpKBRo0b4/vvvER8fj+zsbNStWxdXr15Fq1atxDti\np0+fhru7e5mffNjY2GDp0qWwtbWFUqmEjY2N0QKhV65cQfv27Q2eHzp0KBYvXoz69euL46ovX76M\nbt26PbOnijmYK941a9bodfH7+++/MXTo0LIJqhjmirXoXdOYmBi4uLiY5ETKnL/l7du3Y8SIEdi8\neXOZxVNWevXqhfXr10Oj0WD69OkAgO+++w6hoaGYMmUKjhw5It6dcXFxwfz58yWbuAAAZ2dnODs7\nIzExEY8ePdK7sNdqtbhz5w58fHwgCALy8vLg4uIi1kDp168fAODMmTP4+++/sXnzZkRFRaF///64\nfPkyfvjhB3z77bcmH0+enZ2NoKAgODk5oVGjRhg1ahSaNm2KZcuWQaVSoU+fPggLC4OPjw8SEhJg\nb2+P1q1bY86cOfDw8HihbWGq7aHVakvs1p2YmCjuG5VKJaZOnQpra2ukp6fD2toatra2AID27dvj\nk08+waNHj8SeGmq12ujfeFRUFBo2bIjIyEi0adMG9erVw9mzZ3Hy5En06dMH58+fx9KlS/VuFlSq\nVAm7du2Ck5OT2PV+8eLF8Pb2xogRI8RZBdLS0uDi4vLC2wMovBjy9PSEWq3Gn3/+iYCAAFhaWiIi\nIkJc5+zZs3jvvff0Xveq3pE0dbzmON7qmDpWcx1vdczxWy7r461MJhP3k08/b6x3w+rVq9G5c2fc\nv38fM2fOxIEDB/DBBx+gefPmiIuLw/Lly9GlSxeDG5VOTk5o164dgoKC8Ouvv0KlUiEmJgbffvst\nPD09ERUVBWdnZzg4OKBXr17417/+hd9++w1A4dCL5cuXw9HREWfPnkX9+vWNxpKbm4vk5ORyGTqU\nn59fYs+toj3FLS0tMXHiREyePBnvv/++mEBp06YN2rRpA6CwTopu/w4AtWvXLvM2E5WFVyJ5sWjR\nIsydO1fvpMjPzw9Dhw7Fl19+KY4X1pHL5S9UeCYnJwcjRoxAixYtIAgC0tLS0LRpU/z888/Ys2cP\n5s2bB3t7ewiCgJiYGCxZsqTYir4vQ9f1/eLFi/jxxx/FQjw6giDgxo0bWLFiBTp37qy3zNraGv36\n9cPHH38sTpVUo0YNfPzxx/j3v/9d5m0tC+aIt+jF8s2bN6HRaODu7l5GERXPXN9tQUEBfvjhB1y9\nehU//vhj2QX0DOaIV3fCKPVCnkUTr926dcP+/fvRv39/eHp64s8//4SXlxdiYmLKvCihKWVkZODt\nt98WZ4g4efKkwRRu586dw507d8RCaxqNBgEBAVCpVAgODjbL7E5VqlTR+zsJDAzElClTxJ5Aqamp\n8PT0xKJFi7B8+XJ4eHigU6dOJb7n82wLoPy3h1qtxoYNG5Cfn2/0zl1KSoqYRHB0dMS2bdsAAAsX\nLoRKpcK3/xh88AAAFaNJREFU335rsL6zs7PYVmPveeLECXz00UdiV2ygcNYC3UXd08dwtVqN48eP\no0WLFmjZsiXi4uLQuHFjBAcH49SpU+jRo4c4C8C9e/fEwnwvsi3Gjh0LhUIBuVyud4EHFN45153A\nN2/eHJGRkXo1OV615IW54jXH8dac3605jrfmire8jrclDRvp2bOn+P/k5GQMGjQITZs2xfDhw7Fs\n2TLk5OSgefPmAAoLhnft2hXW1ta4du2awXCTvn37wtnZGadOnUK7du3g7OwMHx8fTJkyBVeuXEHb\ntm2RkJAAJycnvPXWW3qv1e0nf/zxR3zzzTcACs9pPv/8c3z33XcAgNjYWISFhZVb8mL16tXYs2eP\n3gQFgiDgyZMn4rBbHXNPREBUViSfvPjpp5/Qs2dPcYej+wO1t7fH5MmTMW3aNIwYMQLjx48XT4Sy\nsrJeaEdqaWmJFi1aiDvNPXv2IDMzE0Bh96wvvvhCPEH18fERu4+VF0tLS4wePdpopeIxY8YUe7Ks\nVqshl8sRGxuLNm3aoF27drh58yYSEhJQt27dcm3zyzBHvEqlEtu3b9ebxcIUTB2rblpRpVKJTz/9\nFEuWLCmzrovPw1Tx5ufnIywsDJMmTSrzGMqTrncKUHgytWrVKnh5eb3y3TXj4+P1prbOzMwUx/8C\nhXeGXF1dxZPCnJwchIaG4o033sCtW7ewaNEi9OvXD506dSpxZorysH37dnFI0u3btxEfHy9WwZ81\na5aYIH/emgXP2haAabZHfn4+gMLfWZ06dQzan5SUhHnz5uklFLKysnD16lWsW7cOSqVSr4dEamqq\nmLzIzc01uHGQkpIChUKBR48e4aOPPhJ7o9y6dQu9evUqdhy4rhfKnTt3cOTIEfj6+uL+/fvo1asX\nAODRo0cACu/iP12A73lZWVlh69atuHXrFho2bCie3GdmZiI9PR2NGzfG8uXLARQO6Tl9+jRiY2NL\nPV27VJg7XlMeb80ZqzmOt+aIt7yOt6UpHFmzZk0xCfOf//wHX375pTikTq1W49ChQwgODoaFhQUm\nTZqEhQsXGvRk7NChA77++mvMnTsX8fHxuHDhAhQKBVavXo2pU6fiyZMn+OOPPzBv3jyjbbCwsBDr\n/AiCgPj4ePHxkydPSt0L/Hl1794d3bt3h5ubmzgsT1f/IisrS9zXlyQ7O1tvFiuiV4Gkkxdr1qyB\nk5MTQkJCEBISAkEQkJ6eDh8fH+Tk5OD+/fuYPn06VqxYgWPHjmHdunVo0KABHj9+/ELd9ErKSj6d\nlTZFka2CggJs2bJFnOu+qJs3b0KtVht0n1er1Vi/fj2Cg4Mxb948cfzxhx9+KPkuYKaONzMzE+vX\nr8esWbNMfpForu/W0dER7u7u2LZtG6ZNm/bygTwnU8V75coV2NnZITQ0VHxvGxsbhIaGllik0NzS\n09PFru8tWrTAnTt3EB4ebnCn51URERGBpk2b4vLly3jjjTfE59PT0/X2zXK5XCxs9+effyInJwcT\nJkwQu65euHABfn5+yMrKQr169dCsWTMEBQWJF8vlaciQIejVqxccHR0xa9YsTJ8+XTzpPXXqFGrU\nqPFc7/O82wIo/+2RnJwsJh7s7e2N3t2cPXu2XsFOANi0aRO+/PJL2NjYYPPmzejduzcaNmyIzMxM\n2Nvbi+vl5eXp7Ut37NiB9evXi92rdXQ1bry8vLBlyxaD5IVCocDo0aNRUFCA1NRU2NraYurUqbh1\n6xZmz56NgQMHwtraGvHx8YiPj3+puhMAsH79ekRFRYm9Wor2uiyqZ8+eWLp0qXhX9VWtzm+OeM11\nvDXnd2uO460p4y2v460gCMUObSvu3FutVmPp0qWYNm0anJ2dkZ2djSVLlmD+/PnixfnHH3+MUaNG\nYdSoURg3bpy4ja5duwY7OzsAhQlj3bFYoVCgfv36uHHjhtHipTparRYrVqwQ2zdp0iTx8Y0bN4ot\nnPkyDh8+DC8vLyxbtgwXLlzA+++/j/Hjx0Oj0WDYsGHIz8/H+vXrjc7mBhRur3Xr1r3SPTulwlyT\nHFRkkkxeqFQqHDx4EL1794arqyuGDRsmHux69OhhcML1zjvvwNnZGY6OjlCr1XB0dHyhLnDGpkfV\njRkrburU8mRvb4+vvvoK0dHRsLe3x/DhwzFmzBhs3rwZu3fvFrvn3r9/X6yCvGLFCkyfPh1t2rRB\n5cqVERERYXSsnxSZMt7s7GysWrUKM2fOFH9bxc0dXh5MGeuMGTMQGBgoXnhVqlRJHC9uKqaK9803\n38Sbb74pPr59+zbs7e0lmbhISEgQkzC///67XpV3Dw8PbNu2zeCEU+oEQcCqVavQokULVK9eHdev\nX8fkyZPF5cnJyeIFvFqtRmxsLARBgLW1NZYsWYJatWqJBS51LCws4OvrC61WizfeeMMkiQvd5y5Y\nsEA88UtLS8P69evh7++PmJgYtGzZssTXl2ZbAKbZHjExMWjXrp3YvpJi17l37x6qVq0q9n4cMWIE\nxo0bhw0bNuDYsWPw8vIS19VN7aozbNgw7N2716AmxfHjx9G7d29YWVkhNTXV4O6fQqHAli1bIAgC\npkyZgp9//hn5+fmYOnWq2MuiW7duCAwMLJMEn4WFBRYuXCh+p3v37jV619LS0hJRUVHi41f1pNXU\n8ZrzeGvqWM19vDVlvOV5vH3eYSMAEB0djYiICAQEBKBatWqIj4/HtWvXMHv2bL2bIu3bt8eSJUvE\n+lsqlQpbt27FunXrxGNtSkpKiTc/jc1U8s477yAuLg4AxMkAdI9zcnLEfW5ZUSqV2LVrF7y8vKBQ\nKMThuHPnzhV7pEVERGDq1Kl477338P777+tNP69SqTB9+nQEBQXpxfKq7s+o4pFk8kIul+v9oRX9\n41Kr1QbrFz0AHj9+HGPHjn2hz9XVstAVCkpPT8fgwYPFZd98841Y8+Lvv/8u9z903Ri5jRs3IjAw\nUGwHUHhXUOfixYuoV68eTp06hVatWok7yh49eiAuLk6smPw8jCVpTMWU8a5cuRIfffSR+Nu6c+cO\nzpw5Y7LkhaliFQQBFy5c0Dt5uXjx4kvPw15a5vgtS11UVBTi4+Nx9+5ddOjQQW/oTN++fXH27Fkz\ntq700tPTceTIEbRr1w7dunVDSEiIXuV9oPBCWHdiKJPJ0KpVK3FZjRo1jJ6wzpo1C8OGDTN5z7G0\ntDTk5ORg6NChiIiIQM2aNdG6dWusW7cOV69eFe9YGdtflnZbAKbZHidPnizVEIvc3FwEBgaiZcuW\nmDt3LurWrYvq1aujadOmOHLkCE6ePImffvpJXP/Ro0cG3eMLCgqgUqnE3iNqtRo7d+7EDz/8AKBw\nJpLFixfrTa+qk5SUhFatWmHDhg2IjIzUOy9wcXHB33//XeysY6VhYWGhV9xOEAS97zU+Ph5hYWGI\njIxE48aNX/rzdMx1vDV1vOY83poyVikcb831WzYXtVoNOzs7DBgwAHfv3kW1atVw5MgRjBs3DhYW\nFtixYwe8vLxgZ2eHbdu2oUaNGmK9FVtbW0yaNAnbt28Xe39dvXpVLyHztLNnz8LT01N8/K9//Qvn\nzp3DuXPnxOeSkpLE/RtQOBOJIAhlNm27v7+/mEyWy+XIy8sDAL0ebMePH4eXlxcWLVqE6Oho8XmN\nRoOUlBRMmDDBYPhMTk5OmbSPqLxJMnlR0vir3NzcYpfl5eUhMzNTHCtbWmq1Wq/mxeHDh8Wdvkaj\nwVdffSVeTPn7+5ukWNeff/4JW1tbsVL30xl0lUqFffv2oXXr1qhUqRK6d+8uLvP29hbbHxUVhYyM\nDFhYWBhtd1paGk6cOIGzZ8/iwYMHyMrK0ruoNBVTxHvr1i1s2bJFHM8uCAKUSqXYfdJUTBGrTCbD\nihUrcPDgQTg5OSEjIwN9+/Yt93otxpjqtwwUfqf79u3DX3/9BYVCgdq1a4tj5aWib9++xV6Atm3b\n1qCwmNQ1btxYrGQeHh6OtLQ0jBw5EikpKXj48CEcHR0RHx8vjk9+ujZC0RPuogRBKHZZedq4caNY\nhE33+d7e3ggJCYG3t7dYc6KgoMDgArS02wIo/+2RkZGBnJwcsbdHWlqawUWVIAi4c+cORo8eDaDw\nrnH//v3RqVMnvcRK165dsXbtWvj6+ur10khKSjIoEnf//n0kJyfDxcUFBQUF+Pbbb+Hv7y922W7X\nrh127NiB7777Dp9++qne8M06depg4sSJWLp0KZo1a4Y1a9bg0aNH6NevHxYsWIClS5di+fLlsLGx\nMSj4Wxr5+fmYO3cubG1t9Yan6ri6uqJLly64e/cu5s6dKz5fUFBQ7HsqlUpoNBrk5uYa7KfMfbw1\nZbzmPt6aMlYpHG9N/VsGyv54W5qEnpWVFVxdXREUFIQRI0aIr1+5ciWmT5+OunXrYvr06Vi3bh2G\nDx+Ovn37wt7eXtxfqNVqJCcnw87ODhkZGYiNjRWH+BRN/Oi2T2RkJLp16yZuh7Fjx8LHx0ccdgIA\no0ePNkg8q1Qq3L59W2/WnRf1yy+/iMP1mjdvjm+++QabN28W25qdnY3s7Gw8ePAA7dq10+v5oZuu\n2thQu6cLqhNJlSSTFyX57LPPil2mUqn07syUlp2dHRYuXCg+Ltod9rPPPtOr8q6rGF9eYmJicOTI\nEVSpUgVLliwRn+/YsSOGDBkCBwcHCIKA1NRUVK1aFa6urgaFl4p2J27VqhVOnjyJL774wuhJkpOT\nE4YPH47hw4eXX1AlMGW8TZo0wcWLF8s3oBKY+rtt37690alITcXU8QKFJ5GDBg0qszsdZenixYuI\nj4/Hzp074evrK8kpjF+EjY0N/Pz8EBoaCisrK/j5+QEo/O6uX7+O0aNH49NPPy329SkpKcVeTH/0\n0Ufl2nZjbRkyZAiys7OxYsUKnDlzBgsWLEBiYiJkMhm8vb3FdbVarUGPwJfdFro2lOX22LFjB+bM\nmSM+dnBwMNqz48svv9RLIBgbE33u3DmxkHZ8fDy2bt0KQRDw119/ibOJ6EyePBkuLi5ITEzEtm3b\nMGHCBINiu3PmzMHEiRPh4+OD77//HrVq1YJarcbhw4dx//59TJ48GbVq1YKfnx9CQkLw22+/Yf78\n+bCzs0PdunXh6+uL9u3bY968eXq1NZ5Xfn4+Fi1aJCZe9u3bZzBrSu3atQ2GcRn77nUqVaqEsLAw\nLFq0CN26ddNbZu7jrSnjNffx1tTfrbmPt6aOFyj7461Goymx5sXTyY3Q0FBERERg/vz5AAqn/zx/\n/jyAwqEtq1atAqBfS0dHpVKhWrVqePz4MbZv3653DaBWq6FWq1G3bl0EBQXh6tWrSElJwaBBg+Di\n4oIZM2ZApVIZtCc2NtZgqtfExETY2Nhg9+7dLzQbYlFF6wz17t3boFffsxRXI0hXV4xI6mQCBzlJ\nikqlwvnz5+Hk5ITWrVuXeUGwzMxMcfpKKahI8VakWIGKFy8VDpeoUqUKKleubLDs7t27JRZWPHDg\ngF5SQCciIgJvvPGG2WZe0Wq1uH//Pho0aGB0qr3w8HC0aNHC4KL5ZbYFULbbQ61WIz09Xe/O2oMH\nD4zeaStuClWdw4cPw83NTa/92dnZCAoKwtChQ/WmANa5ceMGlEql0WU6OTk5UKlUqFGjBlQqFaKj\no9GqVSvxpoFGo0FERARq165t0N09LS0NeXl5L1SoGyi8sCjutaGhoejYsaNeLxmd6OhoNG3atMSL\nkejoaDRp0kRSMwdVpHgrUqzA6xGvrh5WccaNG4d169aJj1UqFeRy+UvNmmFsf5iWllbiLDGpqamw\nt7d/bW5A0It5/5dN5m5Cudk0/X1zN8EoJi+IiIiIiIiISoHJC9Mr/6INREREREREREQvgckLIiIi\nIiIiIpK0V65gJxEREREREZE5sfqC6bHnBRERERERERFJGpMXRERERERERCRpTF4QERERERERkaSx\n5gURERERERFRKWhZ8sLk2POCiIiIiIiIiCSNyQsiIiIiIiIikjQmL4iIiIiIiIhI0pi8ICIiIiIi\nIiJJY8FOIiIiIiIiolIQBFbsNDX2vCAiIiIiIiIiSWPygoiIiIiIiIgkjckLIiIiIiIiIpI01rwg\nIiIiIiIiKgUBrHlhaux5QURERERERESSxuQFEREREREREUkakxdEREREREREJGlMXhARERERERGR\npLFgJxEREREREVEpaAUW7DQ19rwgIiIiIiIiIklj8oKIiIiIiIiIJI3JCyIiIiIiIiKSNNa8ICIi\nIiIiIioFgTUvTI49L4iIiIiIiIhI0pi8ICIiIiIiIiJJY/KCiIiIiIiIiCSNNS+IiIiIiIiISkHL\nkhcmx54XRERERERERCRpTF4QERERERERkaQxeUFEREREREREksbkBRERERERERFJGgt2EhERERER\nEZWCILBip6mx5wURERERERERSRqTF0REREREREQkaUxeEBEREREREZGkseYFERERERERUSmw5oXp\nsecFEREREREREUkakxdEREREREREJGlMXhARERERERGRpLHmBREREREREVEpaFnzwuTY84KIiIiI\niIiIJI3JCyIiIiIiIiKSNCYviIiIiIiIiEjSmLwgIiIiIiIiIkljwU4iIiIiIiKiUmDBTtNjzwsi\nIiIiIiIikjQmL4iIiIiIiIhI0pi8ICIiIiIiIiJJY80LIiIiIiIiolIQWPPC5NjzgoiIiIiIiIgk\njckLIiIiIiIiIpI0Ji+IiIiIiIiISNJY84KIiIiIiIioFFjywvTY84KIiIiIiIiIJI3JCyIiIiIi\nIiKSNCYviIiIiIiIiEjSmLwgIiIiIiIiIkljwU4iIiIiIiKiUtCyYqfJsecFEREREREREUkakxdE\nREREREREJGlMXhARERERERGRpLHmBREREREREVEpCKx5YXLseUFEREREREREksbkBRERERERERFJ\nGpMXRERERERERCRpTF4QERERERERkaSxYCcRERERERFRKWhZsNPk2POCiIiIiIiIiCSNyQsiIiIi\nIiIikjQmL4iIiIiIiIhI0ljzgoiIiIiIiKgUBNa8MDn2vCAiIiIiIiIiSWPygoiIiIiIiIgkjckL\nIiIiIiIiIpI01rwgIiIiIiIiKgWWvDA99rwgIiIiIiIiIklj8oKIiIiIiIiIJI3JCyIiIiIiIiKS\nNCYviIiIiIiIiEjSWLCTiIiIiIiIqBS0rNhpcux5QURERERERESSxuQFEREREREREUkakxdERERE\nREREJGmseUFERERERERUCgJrXpgce14QERERERERkaQxeUFEREREREREksbkBRERERERERFJmkzg\nYB0iIiIiIiIikjD2vCAiIiIiIiIiSWPygoiIiIiIiIgkjckLIiIiIiIiIpI0Ji+IiIiIiIiISNKY\nvCAiIiIiIiIiSWPygoiIiIiIiIgk7f8ALoBrFGgsSo4AAAAASUVORK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x1f0dc438>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import seaborn as sns\n",
    "\n",
    "f, ax = plt.subplots(figsize=(20, 20))\n",
    "corr = data.corr()\n",
    "ax.set_xticklabels(data.columns, fontproperties=myfont, fontsize=15)\n",
    "ax.set_yticklabels(data.columns, fontproperties=myfont, fontsize=15)\n",
    "plot = sns.heatmap(corr, mask=np.zeros_like(corr, dtype=np.bool), cmap=sns.diverging_palette(220, 10, as_cmap=True),\n",
    "            square=True, ax=ax, annot=True)\n",
    "fig = plot.get_figure()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "相关关系矩阵中行与列交叉的部分为对应行与列之间的相关系数，相关系数越高颜色越趋近于红色，1表示完全正相关，通俗讲就是A增长B一定会增长，负数表示负相关关系，即A增长B减小。"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 相关关系矩阵得出的结论"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "如果微信指数出现剧烈波动的情况下，本产品下属各部门在相应时间段内原因排查优先级如下：\n",
    "* 1.优先排查部门2是否有相应活动\n",
    "* 2.部门4是否有相应动作\n",
    "* 3.部门3是否采取了相应措施\n",
    "* 4.其余部门是否有相应活动\n",
    "* 5.如果以上部门都不相关，接下来考虑是否被竞争对手抹黑导致微信指数热度提升\n",
    "\n",
    "#### 推论：当前情况下，部门2能够带来大量用户，并提升本产品的微信指数，扩大影响力。"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 推理过程"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "* 1.在本产品的各个部门中，本产品的微信指数与自然流量的相关系数为0.73、与部门2的相关系数0.65、与部门4的相关系数为0.52，因此我们判断与微信指数相关的优先级分别为自然流量、部门2、部门4\n",
    "* 2.除本产品的微信指数和总计指标外，自然流量与部门2相关系数最高，达到0.65，与部门3的相关系数最小，仅为0.055，说明自然流量中部门3带来的新增用户没有被划分到自然流量中，部门2由于统计规则（技术或产品原因）的原因有一部分用户被计入自然流量中，自然流量受部门2影响最大，此时我们判断与微信指数相关的优先级调整为部门2、部门4\n",
    "* 3.部门4与新访客相关系数最高，为0.8，与启动次数相关系数为0.78，与访客、pv的相关系数分别为0.73、0.67，与本产品微信指数间的相关系数为0.52，主要原因与部门4的使用场景有关（结合业务使用场景很容易分析）\n",
    "* 4.部门3与PV相关系数最高，为0.55，与本产品微信指数相关系数最低，为-0.18，原因主要与部门3的业务流程有关\n",
    "* 5.部门2与总计的相关性最高，为0.79，说明部门2对总计贡献度大\n",
    "* 6.部门1与其他指标相关性均比较低，说明部门1对其余各项指标包括本产品微信指数在内贡献度低\n",
    "* 7.PV、访客、新访客、启动次数四个因素间相互有强相关关系\n",
    "* 8.各个相关竞争对手中，本产品与竞对1相关性最高，为0.32\n",
    "* 9.竞争对手间，竞对3与竞对4相关性最高，为0.78"
   ]
  }
 ],
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