lianjia.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 数据初探"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "首先导入要使用的科学计算包numpy,pandas,可视化matplotlib,seaborn,以及机器学习包sklearn。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import numpy as np\n",
    "import seaborn as sns\n",
    "import matplotlib as mpl\n",
    "\n",
    "import matplotlib.pyplot as plt\n",
    "from IPython.display import display\n",
    "plt.style.use(\"fivethirtyeight\")\n",
    "sns.set_style({'font.sans-serif':['simhei','Arial']})\n",
    "%matplotlib inline\n",
    "\n",
    "\n",
    "# 检查Python版本\n",
    "from sys import version_info\n",
    "if version_info.major != 3:\n",
    "    raise Exception('请使用Python 3 来完成此项目')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "然后导入数据，并进行初步的观察，这些观察包括了解数据特征的缺失值，异常值，以及大概的描述性统计。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Direction</th>\n",
       "      <th>District</th>\n",
       "      <th>Elevator</th>\n",
       "      <th>Floor</th>\n",
       "      <th>Garden</th>\n",
       "      <th>Id</th>\n",
       "      <th>Layout</th>\n",
       "      <th>Price</th>\n",
       "      <th>Region</th>\n",
       "      <th>Renovation</th>\n",
       "      <th>Size</th>\n",
       "      <th>Year</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>东西</td>\n",
       "      <td>灯市口</td>\n",
       "      <td>NaN</td>\n",
       "      <td>6</td>\n",
       "      <td>锡拉胡同21号院</td>\n",
       "      <td>101102647043</td>\n",
       "      <td>3室1厅</td>\n",
       "      <td>780.0</td>\n",
       "      <td>东城</td>\n",
       "      <td>精装</td>\n",
       "      <td>75.0</td>\n",
       "      <td>1988</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>南北</td>\n",
       "      <td>东单</td>\n",
       "      <td>无电梯</td>\n",
       "      <td>6</td>\n",
       "      <td>东华门大街</td>\n",
       "      <td>101102650978</td>\n",
       "      <td>2室1厅</td>\n",
       "      <td>705.0</td>\n",
       "      <td>东城</td>\n",
       "      <td>精装</td>\n",
       "      <td>60.0</td>\n",
       "      <td>1988</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  Direction District Elevator  Floor    Garden            Id Layout  Price  \\\n",
       "0        东西      灯市口      NaN      6  锡拉胡同21号院  101102647043   3室1厅  780.0   \n",
       "1        南北       东单      无电梯      6     东华门大街  101102650978   2室1厅  705.0   \n",
       "\n",
       "  Region Renovation  Size  Year  \n",
       "0     东城         精装  75.0  1988  \n",
       "1     东城         精装  60.0  1988  "
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# 导入链家二手房数据\n",
    "lianjia_df = pd.read_csv('lianjia.csv')\n",
    "display(lianjia_df.head(n=2))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "初步观察到一共有11个特征变量，Price 在这里是我们的目标变量，然后我们继续深入观察一下。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 23677 entries, 0 to 23676\n",
      "Data columns (total 12 columns):\n",
      "Direction     23677 non-null object\n",
      "District      23677 non-null object\n",
      "Elevator      15440 non-null object\n",
      "Floor         23677 non-null int64\n",
      "Garden        23677 non-null object\n",
      "Id            23677 non-null int64\n",
      "Layout        23677 non-null object\n",
      "Price         23677 non-null float64\n",
      "Region        23677 non-null object\n",
      "Renovation    23677 non-null object\n",
      "Size          23677 non-null float64\n",
      "Year          23677 non-null int64\n",
      "dtypes: float64(2), int64(3), object(7)\n",
      "memory usage: 2.2+ MB\n"
     ]
    }
   ],
   "source": [
    "# 检查缺失值情况\n",
    "lianjia_df.info()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "发现了数据集一共有23677条数据，其中Elevator特征有明显的缺失值。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Floor</th>\n",
       "      <th>Id</th>\n",
       "      <th>Price</th>\n",
       "      <th>Size</th>\n",
       "      <th>Year</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>23677.000000</td>\n",
       "      <td>2.367700e+04</td>\n",
       "      <td>23677.000000</td>\n",
       "      <td>23677.000000</td>\n",
       "      <td>23677.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>12.765088</td>\n",
       "      <td>1.011024e+11</td>\n",
       "      <td>610.668319</td>\n",
       "      <td>99.149301</td>\n",
       "      <td>2001.326519</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>std</th>\n",
       "      <td>7.643932</td>\n",
       "      <td>5.652477e+05</td>\n",
       "      <td>411.452107</td>\n",
       "      <td>50.988838</td>\n",
       "      <td>9.001996</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.010886e+11</td>\n",
       "      <td>60.000000</td>\n",
       "      <td>2.000000</td>\n",
       "      <td>1950.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25%</th>\n",
       "      <td>6.000000</td>\n",
       "      <td>1.011022e+11</td>\n",
       "      <td>365.000000</td>\n",
       "      <td>66.000000</td>\n",
       "      <td>1997.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50%</th>\n",
       "      <td>11.000000</td>\n",
       "      <td>1.011025e+11</td>\n",
       "      <td>499.000000</td>\n",
       "      <td>88.000000</td>\n",
       "      <td>2003.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75%</th>\n",
       "      <td>18.000000</td>\n",
       "      <td>1.011027e+11</td>\n",
       "      <td>717.000000</td>\n",
       "      <td>118.000000</td>\n",
       "      <td>2007.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>max</th>\n",
       "      <td>57.000000</td>\n",
       "      <td>1.011028e+11</td>\n",
       "      <td>6000.000000</td>\n",
       "      <td>1019.000000</td>\n",
       "      <td>2017.000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "              Floor            Id         Price          Size          Year\n",
       "count  23677.000000  2.367700e+04  23677.000000  23677.000000  23677.000000\n",
       "mean      12.765088  1.011024e+11    610.668319     99.149301   2001.326519\n",
       "std        7.643932  5.652477e+05    411.452107     50.988838      9.001996\n",
       "min        1.000000  1.010886e+11     60.000000      2.000000   1950.000000\n",
       "25%        6.000000  1.011022e+11    365.000000     66.000000   1997.000000\n",
       "50%       11.000000  1.011025e+11    499.000000     88.000000   2003.000000\n",
       "75%       18.000000  1.011027e+11    717.000000    118.000000   2007.000000\n",
       "max       57.000000  1.011028e+11   6000.000000   1019.000000   2017.000000"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "lianjia_df.describe()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "上面结果给出了特征值是数值的一些统计值，包括平均数，标准差，中位数，最小值，最大值，25%分位数，75%分位数。这些统计结果简单直接，对于初始了解一个特征好坏非常有用，比如我们观察到 Size 特征 的最大值为1019平米，最小值为2平米，那么我们就要思考这个在实际中是不是存在的，如果不存在没有意义，那么这个数据就是一个异常值，会严重影响模型的性能。\n",
    "\n",
    "当然，这只是初步观察，后续我们会用数据可视化来清晰的展示，并证实我们的猜测。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Region</th>\n",
       "      <th>District</th>\n",
       "      <th>Garden</th>\n",
       "      <th>Layout</th>\n",
       "      <th>Floor</th>\n",
       "      <th>Year</th>\n",
       "      <th>Size</th>\n",
       "      <th>Elevator</th>\n",
       "      <th>Direction</th>\n",
       "      <th>Renovation</th>\n",
       "      <th>PerPrice</th>\n",
       "      <th>Price</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>东城</td>\n",
       "      <td>灯市口</td>\n",
       "      <td>锡拉胡同21号院</td>\n",
       "      <td>3室1厅</td>\n",
       "      <td>6</td>\n",
       "      <td>1988</td>\n",
       "      <td>75.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>东西</td>\n",
       "      <td>精装</td>\n",
       "      <td>10.40</td>\n",
       "      <td>780.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>东城</td>\n",
       "      <td>东单</td>\n",
       "      <td>东华门大街</td>\n",
       "      <td>2室1厅</td>\n",
       "      <td>6</td>\n",
       "      <td>1988</td>\n",
       "      <td>60.0</td>\n",
       "      <td>无电梯</td>\n",
       "      <td>南北</td>\n",
       "      <td>精装</td>\n",
       "      <td>11.75</td>\n",
       "      <td>705.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  Region District    Garden Layout  Floor  Year  Size Elevator Direction  \\\n",
       "0     东城      灯市口  锡拉胡同21号院   3室1厅      6  1988  75.0      NaN        东西   \n",
       "1     东城       东单     东华门大街   2室1厅      6  1988  60.0      无电梯        南北   \n",
       "\n",
       "  Renovation  PerPrice  Price  \n",
       "0         精装     10.40  780.0  \n",
       "1         精装     11.75  705.0  "
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# 添加新特征房屋均价\n",
    "df = lianjia_df.copy()\n",
    "df['PerPrice'] = lianjia_df['Price']/lianjia_df['Size']\n",
    "\n",
    "# 重新摆放列位置\n",
    "columns = ['Region', 'District', 'Garden', 'Layout', 'Floor', 'Year', 'Size', 'Elevator', 'Direction', 'Renovation', 'PerPrice', 'Price']\n",
    "df = pd.DataFrame(df, columns = columns)\n",
    "\n",
    "# 重新审视数据集\n",
    "display(df.head(n=2))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "我们发现 Id 特征其实没有什么实际意义，所以将其移除。由于房屋单价分析起来比较方便，简单的使用总价/面积就可得到，所以增加一个新的特征 PerPrice（只用于分析，不是预测特征）。另外，特征的顺序也被调整了一下，看起来比较舒服。"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 数据可视化分析"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Region特征分析"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "对于区域特征，我们可以分析不同区域房价和数量的对比。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1440x1080 with 3 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# 对二手房区域分组对比二手房数量和每平米房价\n",
    "df_house_count = df.groupby('Region')['Price'].count().sort_values(ascending=False).to_frame().reset_index()\n",
    "df_house_mean = df.groupby('Region')['PerPrice'].mean().sort_values(ascending=False).to_frame().reset_index()\n",
    "\n",
    "f, [ax1,ax2,ax3] = plt.subplots(3,1,figsize=(20,15))\n",
    "sns.barplot(x='Region', y='PerPrice', palette=\"Blues_d\", data=df_house_mean, ax=ax1)\n",
    "ax1.set_title('北京各大区二手房每平米单价对比',fontsize=15)\n",
    "ax1.set_xlabel('区域')\n",
    "ax1.set_ylabel('每平米单价')\n",
    "\n",
    "sns.barplot(x='Region', y='Price', palette=\"Greens_d\", data=df_house_count, ax=ax2)\n",
    "ax2.set_title('北京各大区二手房数量对比',fontsize=15)\n",
    "ax2.set_xlabel('区域')\n",
    "ax2.set_ylabel('数量')\n",
    "\n",
    "sns.boxplot(x='Region', y='Price', data=df, ax=ax3)\n",
    "ax3.set_title('北京各大区二手房房屋总价',fontsize=15)\n",
    "ax3.set_xlabel('区域')\n",
    "ax3.set_ylabel('房屋总价')\n",
    "\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "使用了pandas的网络透视功能 groupby 分组排序。区域特征可视化直接采用 seaborn 完成，颜色使用调色板 palette 参数，颜色渐变，越浅说明越少，反之越多。\n",
    "可以观察到：\n",
    "\n",
    "* **二手房均价：**西城区的房价最贵均价大约11万/平，因为西城在二环以里，且是热门学区房的聚集地。其次是东城大约10万/平，然后是海淀大约8.5万/平，其它均低于8万/平。\n",
    "* **二手房房数量：**从数量统计上来看，目前二手房市场上比较火热的区域。海淀区和朝阳区二手房数量最多，差不多都接近3000套，毕竟大区，需求量也大。然后是丰台区，近几年正在改造建设，有赶超之势。\n",
    "* **二手房总价：**通过箱型图看到，各大区域房屋总价中位数都都在1000万以下，且房屋总价离散值较高，西城最高达到了6000万，说明房屋价格特征不是理想的正太分布。"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Size特征分析"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1080x360 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "f, [ax1,ax2] = plt.subplots(1, 2, figsize=(15, 5))\n",
    "# 建房时间的分布情况\n",
    "sns.distplot(df['Size'], bins=20, ax=ax1, color='r')\n",
    "sns.kdeplot(df['Size'], shade=True, ax=ax1)\n",
    "# 建房时间和出售价格的关系\n",
    "sns.regplot(x='Size', y='Price', data=df, ax=ax2)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "* **Size 分布：**\n",
    "通过 distplot 和 kdeplot 绘制柱状图观察 Size 特征的分布情况，属于长尾类型的分布，这说明了有很多面积很大且超出正常范围的二手房。\n",
    "\n",
    "* **Size 与 Price 的关系：**\n",
    "通过 regplot 绘制了 Size 和 Price 之间的散点图，发现 Size 特征基本与Price呈现线性关系，符合基本常识，面积越大，价格越高。但是有两组明显的异常点：1. 面积不到10平米，但是价格超出10000万；2. 一个点面积超过了1000平米，价格很低，需要查看是什么情况。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Region</th>\n",
       "      <th>District</th>\n",
       "      <th>Garden</th>\n",
       "      <th>Layout</th>\n",
       "      <th>Floor</th>\n",
       "      <th>Year</th>\n",
       "      <th>Size</th>\n",
       "      <th>Elevator</th>\n",
       "      <th>Direction</th>\n",
       "      <th>Renovation</th>\n",
       "      <th>PerPrice</th>\n",
       "      <th>Price</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1168</th>\n",
       "      <td>房山</td>\n",
       "      <td>长阳</td>\n",
       "      <td>世茂维拉</td>\n",
       "      <td>叠拼别墅</td>\n",
       "      <td>5</td>\n",
       "      <td>2015</td>\n",
       "      <td>5.0</td>\n",
       "      <td>毛坯</td>\n",
       "      <td>240.97平米</td>\n",
       "      <td>南北</td>\n",
       "      <td>216.000000</td>\n",
       "      <td>1080.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1458</th>\n",
       "      <td>房山</td>\n",
       "      <td>长阳</td>\n",
       "      <td>世茂维拉</td>\n",
       "      <td>叠拼别墅</td>\n",
       "      <td>5</td>\n",
       "      <td>2015</td>\n",
       "      <td>5.0</td>\n",
       "      <td>毛坯</td>\n",
       "      <td>242.78平米</td>\n",
       "      <td>南北</td>\n",
       "      <td>220.000000</td>\n",
       "      <td>1100.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1797</th>\n",
       "      <td>房山</td>\n",
       "      <td>长阳</td>\n",
       "      <td>世茂维拉</td>\n",
       "      <td>叠拼别墅</td>\n",
       "      <td>5</td>\n",
       "      <td>2015</td>\n",
       "      <td>5.0</td>\n",
       "      <td>精装</td>\n",
       "      <td>242.96平米</td>\n",
       "      <td>南北</td>\n",
       "      <td>196.000000</td>\n",
       "      <td>980.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2268</th>\n",
       "      <td>顺义</td>\n",
       "      <td>顺义其它</td>\n",
       "      <td>龙湖好望山</td>\n",
       "      <td>叠拼别墅</td>\n",
       "      <td>4</td>\n",
       "      <td>2014</td>\n",
       "      <td>4.0</td>\n",
       "      <td>精装</td>\n",
       "      <td>295.88平米</td>\n",
       "      <td>南北</td>\n",
       "      <td>250.000000</td>\n",
       "      <td>1000.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2274</th>\n",
       "      <td>顺义</td>\n",
       "      <td>顺义其它</td>\n",
       "      <td>鹭峯国际</td>\n",
       "      <td>叠拼别墅</td>\n",
       "      <td>4</td>\n",
       "      <td>2014</td>\n",
       "      <td>5.0</td>\n",
       "      <td>精装</td>\n",
       "      <td>295.01平米</td>\n",
       "      <td>南北</td>\n",
       "      <td>290.000000</td>\n",
       "      <td>1450.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2276</th>\n",
       "      <td>顺义</td>\n",
       "      <td>顺义其它</td>\n",
       "      <td>龙湖好望山</td>\n",
       "      <td>叠拼别墅</td>\n",
       "      <td>3</td>\n",
       "      <td>2014</td>\n",
       "      <td>4.0</td>\n",
       "      <td>毛坯</td>\n",
       "      <td>292.31平米</td>\n",
       "      <td>南北</td>\n",
       "      <td>215.000000</td>\n",
       "      <td>860.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2432</th>\n",
       "      <td>顺义</td>\n",
       "      <td>顺义其它</td>\n",
       "      <td>龙湖好望山</td>\n",
       "      <td>叠拼别墅</td>\n",
       "      <td>5</td>\n",
       "      <td>2013</td>\n",
       "      <td>6.0</td>\n",
       "      <td>精装</td>\n",
       "      <td>294.42平米</td>\n",
       "      <td>南北</td>\n",
       "      <td>163.333333</td>\n",
       "      <td>980.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4078</th>\n",
       "      <td>大兴</td>\n",
       "      <td>西红门</td>\n",
       "      <td>鸿坤林语墅</td>\n",
       "      <td>叠拼别墅</td>\n",
       "      <td>3</td>\n",
       "      <td>2015</td>\n",
       "      <td>4.0</td>\n",
       "      <td>精装</td>\n",
       "      <td>427.5平米</td>\n",
       "      <td>南北</td>\n",
       "      <td>787.500000</td>\n",
       "      <td>3150.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4079</th>\n",
       "      <td>大兴</td>\n",
       "      <td>西红门</td>\n",
       "      <td>鸿坤林语墅</td>\n",
       "      <td>叠拼别墅</td>\n",
       "      <td>4</td>\n",
       "      <td>2015</td>\n",
       "      <td>4.0</td>\n",
       "      <td>精装</td>\n",
       "      <td>361.8平米</td>\n",
       "      <td>南北</td>\n",
       "      <td>595.000000</td>\n",
       "      <td>2380.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4761</th>\n",
       "      <td>大兴</td>\n",
       "      <td>西红门</td>\n",
       "      <td>鸿坤林语墅</td>\n",
       "      <td>叠拼别墅</td>\n",
       "      <td>3</td>\n",
       "      <td>2015</td>\n",
       "      <td>5.0</td>\n",
       "      <td>精装</td>\n",
       "      <td>386.83平米</td>\n",
       "      <td>南北</td>\n",
       "      <td>540.000000</td>\n",
       "      <td>2700.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7533</th>\n",
       "      <td>昌平</td>\n",
       "      <td>回龙观</td>\n",
       "      <td>龙城花园N区</td>\n",
       "      <td>叠拼别墅</td>\n",
       "      <td>4</td>\n",
       "      <td>1997</td>\n",
       "      <td>2.0</td>\n",
       "      <td>简装</td>\n",
       "      <td>107.93平米</td>\n",
       "      <td>南北</td>\n",
       "      <td>310.000000</td>\n",
       "      <td>620.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8765</th>\n",
       "      <td>通州</td>\n",
       "      <td>通州其它</td>\n",
       "      <td>旭辉御锦</td>\n",
       "      <td>叠拼别墅</td>\n",
       "      <td>6</td>\n",
       "      <td>2014</td>\n",
       "      <td>5.0</td>\n",
       "      <td>毛坯</td>\n",
       "      <td>195.32平米</td>\n",
       "      <td>南北</td>\n",
       "      <td>156.000000</td>\n",
       "      <td>780.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9020</th>\n",
       "      <td>通州</td>\n",
       "      <td>通州其它</td>\n",
       "      <td>旭辉御锦</td>\n",
       "      <td>叠拼别墅</td>\n",
       "      <td>6</td>\n",
       "      <td>2014</td>\n",
       "      <td>4.0</td>\n",
       "      <td>精装</td>\n",
       "      <td>259.87平米</td>\n",
       "      <td>南北</td>\n",
       "      <td>280.000000</td>\n",
       "      <td>1120.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9080</th>\n",
       "      <td>通州</td>\n",
       "      <td>通州其它</td>\n",
       "      <td>旭辉御锦</td>\n",
       "      <td>叠拼别墅</td>\n",
       "      <td>6</td>\n",
       "      <td>2014</td>\n",
       "      <td>4.0</td>\n",
       "      <td>毛坯</td>\n",
       "      <td>259.76平米</td>\n",
       "      <td>南北</td>\n",
       "      <td>262.500000</td>\n",
       "      <td>1050.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9203</th>\n",
       "      <td>通州</td>\n",
       "      <td>通州其它</td>\n",
       "      <td>旭辉御锦</td>\n",
       "      <td>叠拼别墅</td>\n",
       "      <td>6</td>\n",
       "      <td>2014</td>\n",
       "      <td>4.0</td>\n",
       "      <td>精装</td>\n",
       "      <td>260.07平米</td>\n",
       "      <td>南北</td>\n",
       "      <td>262.500000</td>\n",
       "      <td>1050.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9254</th>\n",
       "      <td>通州</td>\n",
       "      <td>通州其它</td>\n",
       "      <td>旭辉御锦</td>\n",
       "      <td>叠拼别墅</td>\n",
       "      <td>6</td>\n",
       "      <td>2014</td>\n",
       "      <td>4.0</td>\n",
       "      <td>毛坯</td>\n",
       "      <td>264.6平米</td>\n",
       "      <td>南北</td>\n",
       "      <td>275.000000</td>\n",
       "      <td>1100.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11531</th>\n",
       "      <td>丰台</td>\n",
       "      <td>丽泽</td>\n",
       "      <td>西宸原著</td>\n",
       "      <td>叠拼别墅</td>\n",
       "      <td>6</td>\n",
       "      <td>2016</td>\n",
       "      <td>4.0</td>\n",
       "      <td>毛坯</td>\n",
       "      <td>335.51平米</td>\n",
       "      <td>南北</td>\n",
       "      <td>1000.000000</td>\n",
       "      <td>4000.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14298</th>\n",
       "      <td>海淀</td>\n",
       "      <td>西山</td>\n",
       "      <td>中间建筑一区</td>\n",
       "      <td>叠拼别墅</td>\n",
       "      <td>3</td>\n",
       "      <td>2007</td>\n",
       "      <td>8.0</td>\n",
       "      <td>精装</td>\n",
       "      <td>266.61平米</td>\n",
       "      <td>南北</td>\n",
       "      <td>168.750000</td>\n",
       "      <td>1350.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15334</th>\n",
       "      <td>海淀</td>\n",
       "      <td>西山</td>\n",
       "      <td>西山美墅馆F区</td>\n",
       "      <td>叠拼别墅</td>\n",
       "      <td>4</td>\n",
       "      <td>2004</td>\n",
       "      <td>4.0</td>\n",
       "      <td>简装</td>\n",
       "      <td>203.73平米</td>\n",
       "      <td>南北</td>\n",
       "      <td>550.000000</td>\n",
       "      <td>2200.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17311</th>\n",
       "      <td>朝阳</td>\n",
       "      <td>大望路</td>\n",
       "      <td>首府官邸</td>\n",
       "      <td>叠拼别墅</td>\n",
       "      <td>5</td>\n",
       "      <td>2007</td>\n",
       "      <td>5.0</td>\n",
       "      <td>精装</td>\n",
       "      <td>523.4平米</td>\n",
       "      <td>南北</td>\n",
       "      <td>900.000000</td>\n",
       "      <td>4500.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
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      ],
      "text/plain": [
       "      Region District   Garden Layout  Floor  Year  Size Elevator Direction  \\\n",
       "1168      房山       长阳     世茂维拉   叠拼别墅      5  2015   5.0       毛坯  240.97平米   \n",
       "1458      房山       长阳     世茂维拉   叠拼别墅      5  2015   5.0       毛坯  242.78平米   \n",
       "1797      房山       长阳     世茂维拉   叠拼别墅      5  2015   5.0       精装  242.96平米   \n",
       "2268      顺义     顺义其它    龙湖好望山   叠拼别墅      4  2014   4.0       精装  295.88平米   \n",
       "2274      顺义     顺义其它     鹭峯国际   叠拼别墅      4  2014   5.0       精装  295.01平米   \n",
       "2276      顺义     顺义其它    龙湖好望山   叠拼别墅      3  2014   4.0       毛坯  292.31平米   \n",
       "2432      顺义     顺义其它    龙湖好望山   叠拼别墅      5  2013   6.0       精装  294.42平米   \n",
       "4078      大兴      西红门    鸿坤林语墅   叠拼别墅      3  2015   4.0       精装   427.5平米   \n",
       "4079      大兴      西红门    鸿坤林语墅   叠拼别墅      4  2015   4.0       精装   361.8平米   \n",
       "4761      大兴      西红门    鸿坤林语墅   叠拼别墅      3  2015   5.0       精装  386.83平米   \n",
       "7533      昌平      回龙观   龙城花园N区   叠拼别墅      4  1997   2.0       简装  107.93平米   \n",
       "8765      通州     通州其它     旭辉御锦   叠拼别墅      6  2014   5.0       毛坯  195.32平米   \n",
       "9020      通州     通州其它     旭辉御锦   叠拼别墅      6  2014   4.0       精装  259.87平米   \n",
       "9080      通州     通州其它     旭辉御锦   叠拼别墅      6  2014   4.0       毛坯  259.76平米   \n",
       "9203      通州     通州其它     旭辉御锦   叠拼别墅      6  2014   4.0       精装  260.07平米   \n",
       "9254      通州     通州其它     旭辉御锦   叠拼别墅      6  2014   4.0       毛坯   264.6平米   \n",
       "11531     丰台       丽泽     西宸原著   叠拼别墅      6  2016   4.0       毛坯  335.51平米   \n",
       "14298     海淀       西山   中间建筑一区   叠拼别墅      3  2007   8.0       精装  266.61平米   \n",
       "15334     海淀       西山  西山美墅馆F区   叠拼别墅      4  2004   4.0       简装  203.73平米   \n",
       "17311     朝阳      大望路     首府官邸   叠拼别墅      5  2007   5.0       精装   523.4平米   \n",
       "\n",
       "      Renovation     PerPrice   Price  \n",
       "1168          南北   216.000000  1080.0  \n",
       "1458          南北   220.000000  1100.0  \n",
       "1797          南北   196.000000   980.0  \n",
       "2268          南北   250.000000  1000.0  \n",
       "2274          南北   290.000000  1450.0  \n",
       "2276          南北   215.000000   860.0  \n",
       "2432          南北   163.333333   980.0  \n",
       "4078          南北   787.500000  3150.0  \n",
       "4079          南北   595.000000  2380.0  \n",
       "4761          南北   540.000000  2700.0  \n",
       "7533          南北   310.000000   620.0  \n",
       "8765          南北   156.000000   780.0  \n",
       "9020          南北   280.000000  1120.0  \n",
       "9080          南北   262.500000  1050.0  \n",
       "9203          南北   262.500000  1050.0  \n",
       "9254          南北   275.000000  1100.0  \n",
       "11531         南北  1000.000000  4000.0  \n",
       "14298         南北   168.750000  1350.0  \n",
       "15334         南北   550.000000  2200.0  \n",
       "17311         南北   900.000000  4500.0  "
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.loc[df['Size']< 10]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "经过查看发现这组数据是别墅，出现异常的原因是由于别墅结构比较特殊（无朝向无电梯），字段定义与二手商品房不太一样导致爬虫爬取数据错位。也因别墅类型二手房不在我们的考虑范围之内，故将其移除再次观察Size分布和Price关系"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "      <th></th>\n",
       "      <th>Region</th>\n",
       "      <th>District</th>\n",
       "      <th>Garden</th>\n",
       "      <th>Layout</th>\n",
       "      <th>Floor</th>\n",
       "      <th>Year</th>\n",
       "      <th>Size</th>\n",
       "      <th>Elevator</th>\n",
       "      <th>Direction</th>\n",
       "      <th>Renovation</th>\n",
       "      <th>PerPrice</th>\n",
       "      <th>Price</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>8754</th>\n",
       "      <td>通州</td>\n",
       "      <td>通州其它</td>\n",
       "      <td>新华联科技大厦</td>\n",
       "      <td>1房间0卫</td>\n",
       "      <td>8</td>\n",
       "      <td>2009</td>\n",
       "      <td>1019.0</td>\n",
       "      <td>有电梯</td>\n",
       "      <td>南</td>\n",
       "      <td>简装</td>\n",
       "      <td>1.668302</td>\n",
       "      <td>1700.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "     Region District   Garden Layout  Floor  Year    Size Elevator Direction  \\\n",
       "8754     通州     通州其它  新华联科技大厦  1房间0卫      8  2009  1019.0      有电梯         南   \n",
       "\n",
       "     Renovation  PerPrice   Price  \n",
       "8754         简装  1.668302  1700.0  "
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.loc[df['Size']>1000]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "经观察这个异常点不是普通的民用二手房，很可能是商用房，所以才有1房间0厅确有如此大超过1000平米的面积，这里选择移除。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [],
   "source": [
    "df = df[(df['Layout']!='叠拼别墅')&(df['Size']<1000)]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "重新进行可视化发现就没有明显的异常点了。"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Layout特征分析"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1440x1440 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "f, ax1= plt.subplots(figsize=(20,20))\n",
    "sns.countplot(y='Layout', data=df, ax=ax1)\n",
    "ax1.set_title('房屋户型',fontsize=15)\n",
    "ax1.set_xlabel('数量')\n",
    "ax1.set_ylabel('户型')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "这个特征真是不看不知道，各种厅室组合搭配，竟然还有9室3厅，4室0厅等奇怪的结构。其中，2室一厅占绝大部分，其次是3室一厅，2室2厅，3室两厅。但是仔细观察特征分类下有很多不规则的命名，比如2室一厅与2房间1卫，还有别墅，没有统一的叫法。这样的特征肯定是不能作为机器学习模型的数据输入的，需要使用特征工程进行相应的处理。"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Renovation 特征分析"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "精装    11345\n",
       "简装     8496\n",
       "其他     3239\n",
       "毛坯      576\n",
       "Name: Renovation, dtype: int64"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df['Renovation'].value_counts()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "发现Renovation装修特征中竟然有南北，它属于朝向的类型，可能是因为爬虫过程中一些信息位置为空，导致“Direction”朝向特征出现在这里，所以需要清除或替换掉。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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AW2+9ldHRUTo6OrjggvKXg5DUmoaHhxkcHCQzGRwcpL+/n7lz55adViEafan1W4EvZuYrgGdHxLuBWZl5ErA4Iroj4rxaYg3OW5IkSZKkvbq6uvZ2Ofb09LRNkUBS4w0MDDA6WllHenR0lNWrV5ecUXEafan1z4CXRsRzgYXATmDPtoBrgFOA42uMbZ7sh2zePOkh1cDz17pcO6E2PsebS3e3nyVJkqTW9PrXv54777yTc845p+xUJLWwoaEhRkZGABgZGWFoaKhtLrdudJ3iW8Brgf8ObAIOBbZVjw0DJwBzaoxNaso3sTffeUCJzyQWAVrXA9bTauJzXJIkSUVYs2YNu3bt4sYbb2ybIoG0x/DwMFdccQUrVqywo7fOenp6WLt2LSMjI3R2dtLT01N2SoVp9KXWfw5cmJkfAv4VOB+YXT12RDWfx2qMSZIkSZJUin3XZGu3nWilsZudqL76+vro6KiUujo6Oujv7y85o+I0uoA3Fzg2ImYBvw78BZXLpgGWAFuAjTXGJEmSJEkqxcDAwLhLIy3OqJ0MDw+zbt06MpN169ZZWK+zrq4uent7iQh6e3vbqsO00YXH/wl8ksrajl3AKuCtEfFRoA/4JnBdjTFJkiRJUgkiYn5E3F29fU1EbIiIy8YcrynWyoaGhsZtBjE0NFRyRlJxLKw3Xl9fHy9+8YvbqtsRGlx4zMw7M/MlmXlEZp6VmY8AS4E7gNMzc2etsUbmLUmSJEka5wpgdkScB8zKzJOAxRHRXWusxNwL8bKXvWzc+Pjjjy8pE6l469evJzMByEzWr19fbkIzQFdXFytXrmyrbkdogrUSM3NHZg5k5vbpxiRJanYR0RkRD0XE+urXsRHxwYi4KyL+esz9nhGTJKkZRUQv8DiwnUqDyED10BoqS2TVGmtpDz744JRjqZXNmzdvyrFUq0bvai1J0kxzHPDlzLwEICJeTuXN1quA90fEmcCOfWOZubashCVJmkxEHAr8GfAGKktizQG2VQ8PAydMIzahzZs3F553PTz88MPjxtu2bWuZ3KX9+fGPf/yMsc9vTaS7e+oGdguPkiTV14nAb0XE6cD3gPuAf8jMjIibgLOprH28b8zCoySpGb0HuCozfx4RAI8Bs6vHjqByVV2tsQnt701ss1i4cCFbt24dN26V3KX96e3t5aabbiIz92544vNbB8LCoyRJ9XUXcGZm/igirqXypuu+6rFhYD4wAvz7PrFJ+WnzwSvqHC4o5FHaX1Hn2z9ca+NrRGPt73y34Rv1M4HeiHgn8DLghcBWKuvxL6Eyx/2QSif//mItbfny5Vx00UV7xxdffHGJ2UjF6uvrY926dTz11FN0dna23YYnahz/fpMkqb7uycz/rN7+38AhHEQXCOznTezNdx5EqjNHUYWARwt5lPZX1Pl+wHpaTQordK0r5mHaXRsWFqeUmaftuR0R64HXA7dFxFFUOvZPBLLGWEtbvHgxc+bM4fHHH2fOnDksWrSo7JSkwnR1dXHGGWdw0003ccYZZ7TdhidqnNI3l5Ekqc19PiKWRMQs4Fwqa1ztWVB/CbAF2DhBTJKkppaZSzPzESobx9wBnJ6ZO2uNlZN1cYaHh3nyyScBePLJJ9mxY0fJGUnF6uvr48UvfrHdjjooFh4lSaqvDwGfB/4Z2AB8GDg+Iv6SyjpZXwa+NUFMkqSWkJk7MnMgM7dPN9bKBgYG2L17NwC7d+9m9erVJWckFaurq4uVK1fa7aiDYuFRkqQ6yszvZ+ZxmXlsZr4vM0eprI91G3B2Zj4wUazMnCVJ0v6tX79+yrEkTcf999/P+eefz5YtW8pOpVAWHiVJarDM3JWZX8nM+6eKSZKk5tXV1TVu/Eu/9EslZSKpHaxatYonnniCK6+8suxUCmXhUZIkSZKkadq+ffwV4z/60Y9KykRSq7v//vvZunUrAFu3bm2rrkcLj5IkSZIkTdPo6OiUY0mq1apVq8aN26nr0cKjJEmSJEmSVJI93Y6TjVuZhUdJkiRJkqZp/vz548YLFiwoKRNJrW7hwoVTjluZhUdJkiRJkqapnQsFkhpr+fLl48YXX3xxSZkUz8KjJEmSJEnTdPfdd48bf/e73y0pE0mtbvHixXs/vFi4cCGLFi0qN6ECWXiUJEmSJGmadu/ePeVYkqZj+fLlHH744W3V7QjQWXYCkiRJkiRJ0ky2ePFivvSlL5WdRuHseJQkSZIkSZJUOAuPkiRJkiRNU0RMOVbxhoeHufTSS9mxY0fZqUiqkYVHSZIkSZKm6Q1veMO48Rvf+MaSMpk5BgYG2LRpE6tXry47FUk1svAoSZIkSdI03XXXXePGGzZsKCmTmWF4eJjBwUEyk8HBQbsepRZh4VGSJEmSpGnaunXrlGMVa2BggNHRUQBGR0ftepRahIVHSZIkSZKmaeHChVOOVayhoSFGRkYAGBkZYWhoqOSMJNXCwqMkSZIkSdO0fPnyceOLL764pExmhp6enr0b+EQEPT09JWckqRYWHiVJkiRJUlNbtmwZmQlAZvKa17ym5Iwk1cLCoyRJkiRJ07Rq1apx4yuvvLKkTGaGNWvWjOt4vPHGG0vOSFItLDxKkiRJkjRNbi7TWENDQ+M6Hl3jUWoNFh4lSZIkSZomN5dprJ6eHjo7OwHo7Ox0jUepRRxw4TEqDisyGUmSWkFELImI8yPisIh4Xdn5SJJ0oJzTDty+ha/e3t6SMpkZ+vr66OiolDA6Ojro7+8vOSNJtai58BgRf7NP6EjgB8WmI0lSc4uI9wNfBD5OZR59T0RcXm5WkiRNn3Pawfm7v/u7ceMvfvGLJWUyM3R1ddHb20tE0Nvby9y5c8tOSVINptPxuO+nX48AnQXmIklSK/gj4ETgF5m5CzgdOL/clCRJOiDOaQdhZGRkyrGKt2zZMmbPnu2O1mpL999/P+effz5btmwpO5VC7bfwGBH/Z0TcAnRFxOCeL+Bfga/VPUNJkprLz4HnAlkdLwIeKy0bSZIOnHPaQdizw/JkYxVvzZo17Nq1yx2t1ZZWrVrFE088wZVXXll2KoWqpWNxPfAg8A/AB8fE/yMz/6UeSUmS1MQupjI3zo2IbwLHA28vNSNJkg6Mc9pB2LPD8mRjFWt4eJjBwUEyk8HBQfr7+73cWm3j/vvvZ+vWrQBs3bqVLVu2sGjRonKTKsh+Ox4z88HMXA/8S2YOjfmy6ChJmnEy8wYql6W9EbgaWFKNSZLUUpzT1EoGBgYYHR0FYHR0lNWrV5eckVScVatWjRu3U9djzWs8ZuZpEfHciHjh2K96JidJUpOam5nfAO4Dnl92MpIkHQTnNLWEoaGhvetojoyMMDQ0VHJGUnH2dDtONm5l09nVehWwHRga87W+PmlJktScIuJPgVuqw18FVkfEf6/h++ZHxN3V29dExIaIuGzM8WfEJEmqpwOd06Qy9PT00NlZWS2us7OTnp6ekjNqf+262UkzWrhw4ZTjVjadXa3fCizOzKPHfC2uV2KSJDWp5cBxAJl5M/BK4KIavu8KYHZEnAfMysyTgMUR0T1RrE65S5I01oHOaVLD9fX10dFRKWF0dHTQ399fckbtr103O2lGb3vb28aN3/GOd5SUSfGmU3i8C1hQxA+NiKsi4nXV2zV1fdgJIklqEk8Ch40ZHw6MTvUNEdELPE7lyoGlwED10BrglElikiTV27TnNKksXV1d9Pb2EhH09va6sUydTbTZiernjjvuGDe+/fbbS8qkeLXsar3HJmBdRHwd+HcgATLzQ9P5gRFxKrAgM78+tsMjIj5d7fA4tpZYZm6ezs+VJKkg7we+U50PAV4LTPqhWEQcCvwZ8AbgOmAOsK16eBg4YZLYpDZvdgo8WEWdw0I+kZ0Bijrf0/nDdSbzNaKx9ne+u7ubuol9WnPaHhHRBbwcuDsz/6OO+Unj9PX18dBDD9nt2AATbXby8Y9/vKRs2t++a5YODQ1x4YUXlpRNsabz99tO4GNjxjHdHxYRhwCfAm6IiHOYuMPj+Bpj/kUlSWq4zPxiRGwEzqyG/iozN03xLe8BrsrMn0cEwGPA7OqxI6hcfTBRbFJTvom9+c79/AaC4goBjxbyKO2vqPP9gH/91aSwQte6Yh6m3TV5YXFKBzCnERFzgW8A3wQ+Wu3q/wvgGOCbmfnh6v2uqSXWyiKCzBw3Vn11dXWxcuXKstOYEdp5s5Nm1NPTw9q1axkZGWm7NUynU3j8TAE/7wLgXuBy4F3AO4Frqsem6vqwE6SBPH+ty06Q2vgcby6t+IYtM/8V+Nca734m0BsR7wReBrwQ2ArcASyhsovoD6l8qDY2JklS3U1zToPKmpAXZeYd1SJkL17FpgYZHh7miiuuYMWKFV5qXWcLFy4cV2xsp81OmlFfXx+Dg4NA+61hOp06xRCVy6s7gPnAocCDwHQ2mDke+GRmbo+ILwAnU1vXh50gDdSKRQBV2AlSG5/jaqTMPG3P7YhYD7weuC0ijgLOBk6kMr/uG5Mkqelk5hBARJwGvAroYoZexTa223GisYo3MDDApk2bWL16ddtchtqsli9fzkUXPb3X1MUXX1xiNu1vzxqmN910U9utYVpz4TEzj95zOyI6gT8A5k3z5/2ApwuVrwAW8cwOj4m6PuwEkSSVJiIuysyPVm+/f6L71LLmcWYurT7GUuAs4PLM3DlZTJKkohUxp0XlmuJ+YAeVD89quWKt5qvYWvnqlFbOvdk98sgjrF27lsxk7dq1vPKVr+Q5z3lO2Wm1tfnz5/PjH/+Y+fPn89RTT/n8rrNXvvKV3Hfffbzyla9sqXO9v8aeA7oyMzNHgKsi4sZpfus1wKcj4k3AIVTWePzHGro+7ASRJJUpJrl9QDJzB093fUwakySpDg56TstKa987I+L/AX6Hyjr+UNBVbK18dUor597srr76anbv3g3A7t27ueuuu+x6rLNLLrmEyy67jPe+970sWrSo7HRmhJe//OVlp1C4mguPE3watpBpbuaYmY8Cb9zncZdSQ9eHnSCSpLJk5pVjbn+wzFwkSToYBzunRcQlwI8y81rguVQ2lvEqNtXd+vXr917OnpmsX7/ewmOdLV68mC996Utlp6EWN52Ox30/DbsXmLA1fzpq7fqwE0SSJEmSSvdJYCAi3g58H7gOuNWr2FRv8+bNG7fZybx50135TVIZprPG4wcjYh5wKpVJ41uZ+dO6ZSZJkiRJairVhpCzxsa8ik2N8NOf/nTKsaTmNOXu0GNFxGuAe4C3AhcA/xwRy+qVmCRJzSgi1kbEs8vOQ5Kkg1XUnJaZOzJzIDO3Tzcm1Wrp0qVTjqVWNzw8zKWXXsqOHTvKTqVQNRcegVVAb2a+ITPfAJwB/K/6pCVJUtN6FDit7CQkSSqAc5paRl9f37hxf39/SZlI9TEwMMCmTZtYvXp12akUajqFx8OBbWPGP+LpXckkSZopvgBcGRErIuK0PV9lJyVJ0gFwTlPL+PnPfz5uvHOnV+urfQwPD7Nu3Toyk3Xr1rVV1+N0Co9/BXwrIt4dESuAIeDj9UlLkqSm9X9R+fDtN4EPVr8+UGZCkiQdIOc0tYxVq1aNG1955ZWT3FNqPQMDA4yMjAAwMjLSVl2P09lc5iMRcS9wOtBFZUFg91WXJM0IEXEilQ3WvgEMZubdJackSdIBcU5TKxq7o/VEY6mVrV+/nswEIDNZv349F154YclZFWM6m8u8GfhSZv4pcAOVlvy+/XybJEktLyLeC3wWmA8cBayOiPb4S0CSNKM4p6lVLVy4cMqxiteum500o3nz5k05bmXTudR6JXAcQGZ+BXh5NSZJUrt7J/DqzPzTzLwY6AUuLjknSZIOhHOaWtLb3va2ceN3vOMdJWUyc3zqU5/i3nvv5VOf+lTZqbS9n/70p1OOW9l0Co8Aw2NuPwYcUmAukiQ1q1mZ+bM9g8z8ITCnxHwkSTpQzmlqSXfccce48e23315SJjPD8PAwGzZsACrn2q7H+lq6dOmU41Y23c1lbqvueLZnc5m/qk9akiQ1lSMj4ktjv4Dn7jOWJKkVOKepJQ0NDU05VrH27XK067G++vr6iAgAIoL+/v6SMyrOdDeXuRt4TTX07sy8uT5pSZLUVP5ogthNDc9CkqTycWlpAAAb+ElEQVSD55ymltTT08ONN944bqz62dPtuIcdpvU3dnOZdlJz4REgM9cCa+uUiyRJTSkzP1d2DpIkFcE5Ta3qJS95ybjC47HHHltiNlKx/vZv//YZ4xUrVpSUTbGmu8ajJEmSJElSQ1199dXjxldddVVJmcwMey77nWysYrVzh6mFR0mSJEmS1NQef/zxKccq1nHHHTduvGTJkpIymRn2vby6nS63tvAoSZIkSZKkvX7605+OG//kJz8pKZOZYdasWVOOW5mFR0mSJEmSJO318MMPTzlWsXbv3j3luJVZeJQkSZIkSdJec+bMmXKsYh1++OFTjluZhUdJkiRJkiTtNTIyMuVYxdq1a9eU41Zm4VGSJEmSJEl7nXzyyePGr371q0vKZGbo6OiYctzK2uc3kSRJkiRJ0kH74Q9/OOVYxTr++OPHjU844YSSMimehUdJkiRJktTU2nkNvGa0efPmceN/+7d/KymTmWHbtm1TjluZhUdJkiRJktTUnnjiiSnHUiv70Y9+NG7cTruIW3iUJEmSJElN7Vd+5VfGjY866qiSMpGK1867iFt4lCSpASKiKyLOiohfLjsXSZKkVvP85z9/yrGK1dnZOeVYxfrFL34x5biVWXiUJKnOImIu8A3gVcAtETEvIq6JiA0RcdmY+z0jJkmSJPjud787brxx48aSMpkZzjzzzCnHKlZmTjluZRYeJUmqv+OAizLzfwA3Ab3ArMw8CVgcEd0Rcd6+sRLzlSRJaiqjo6NTjlWsE088cdz45JNPLimTmWFkZGTKcSuzV1aSpDrLzCGAiDiNStdjFzBQPbwGOAU4foLY+O0Eq/bdZVDTV9Q5XFDIo7S/os63f7jWxteIxtrf+e7u9nMkqQgRMa4LLCJKzKb9ffKTnxw3vvrqq7nqqqtKyqb9zZkzh8cff3zcuF3495skSQ0Qlb+O+4EdQALbqoeGgROAORPEJjTlm9ib7zz4ZGeAogoBjxbyKO2vqPP9gPW0mhRW6FpXzMO0OwuLUmNYeGysfXdVbqddlpvRihUr+MAHPrB3fMkll5SXTMG81FqSpAbIincC9wAnA7Orh46gMh8/NkFMkiRJwKxZs6YcS63snnvuGTf+/ve/X1ImxfNNjSRJdRYRl0TEBdXhc4G/oHIpNcASYAuwcYKYJEmSgKeeemrKsYrV0dEx5VjF+upXvzpuPDAwMMk9W4+XWkuSVH+fBAYi4u3A94HrgFsj4ijgbOBEKpdf37ZPTJIkSWq4l770peO68I477rgSs1Ers/AoSVKdZeYO4KyxsYhYWo1dnpk7J4tJkiRJjbbvxln33XdfSZmo1dkrK0lSCTJzR2YOZOb2qWKSJEl65mYybi5TX7t27ZpyrGK94AUvGDd+4QtfWFImxbPwKEmSJEmSmpqby6iddXd3jxu/6EUvKimT4ll4lCRJkiRJTW1kZGTKsdTK7rjjjnHjDRs2lJRJ8Sw8SpIkSZJqEhFHRsQ/RcSaiPhaRBwaEddExIaIuGzM/WqKSbXq7Oycciy1sp6enr1dvLNmzaKnp6fkjIpj4VGSJEmSVKs3Ax/NzGXAduBNwKzMPAlYHBHdEXFeLbHSfgNJajJ9fX10dFRKdB0dHfT395ecUXFKKTxGxPyIuLt620/HJEmSJKkFZOZVmXlzdTgPeAswUB2vAU4BltYYk2qWmVOOpVbW1dXFggULAFiwYAFz584tOaPilNWbfAUwe+ynXhHx6eqnXsfWEsvMzVP9AEmSJElSfUTEScBcYAuwrRoeBk4A5tQYm9Dmza37Vq+Vc292u3fvfsbY891Ynu/6eeSRR9i2rfIS+fDDD7Nx40ae85znlJxVbfbdGGdfDS88RkQv8DiVtvylPPNTr+NrjPmMlyRJkqQGi4gu4OPAbwMXAbOrh46gclXdYzXGJrS/N7HNrJVzb0We78byfNfP1VdfvbeLd3R0lLvuuosLL7yw5KyK0dDCY0QcCvwZ8AbgOmr/JKzmT8fAKvzB8vy1LpdXro3P8ebiHzCSJLWO6nu6vwfem5kPRsRGKo0hdwBLgPuAH9YYk2q2cOFCtm7dunf8q7/6qyVmIxVr/fr1ewuPmcn69estPB6g9wBXZebPIwJq/ySs5k/HYD9vYm++88Ayn0EsArSuB6yn1cTnuCRJ0gF7G5VGkPdFxPuAzwBvjYijgLOBE4EEbqshJtVsbNER4MEHHywpk5lh1qxZ4y5v37Pjsupj3rx5457j8+bNKzGbYjV6c5kzgXdGxHrgZcDreHpR4SVU1gfZWGNMkiRJktRAmfmJzJybmUurX5+jsoTWHcDpmbkzMx+pJVbObyCpFhOtqan6+clPfjLluJU1tOMxM0/bc7tafHw9tX0S5qdjkiRJktSEMnMHT6/JP62YJAme97znjet4fN7znldiNsVqdMfjXtVPx2r6JMxPxyRJkiRJktSOtm/fPuW4lZW+F4WfjkmSJEmSJGmmaudL20vreJQkSZIkSZJmutHR0SnHrczCoyRJkiRJkqTCWXiUJEmSJEmSVDgLj5IkSZIkSVJJOjo6phy3svb5TSRJkiRJkqQW4xqPkiRJkiRJkgp3+OGHTzluZRYeJUmSJEmSpJIcc8wx48YveclLSsqkeBYeJUmSJEmSpJJ873vfGze+5557SsqkeBYeJUmSJEmSpJK4uYwkSZIkSZKkwu3atWvKcSuz8ChJkiRJkiSpcJ1lJ6D29ujy3y07hZbw7FVfLjsFSZIkSZJ0AM4999yme8zrrruuoEwOjh2PkiTVWUQcGRH/FBFrIuJrEXFoRFwTERsi4rIx93tGTJIkSZJalYVHSZLq783ARzNzGbAdeBMwKzNPAhZHRHdEnLdvrMR8JUmSJOmgeam1JEl1lplXjRnOA94CfKw6XgOcAhwPDOwT29yoHCVJkiSpaBYeJUlqkIg4CZgLbAG2VcPDwAnAnAliE9q82XrkwSrqHC4o5FHaX1Hn2z9ca+NrRGPt73x3d9vA3qyabU22ZlmPTdL0Hez/v/u+drTT64F/v0mS1AAR0QV8HPht4CJgdvXQEVSWPnlsgtiEpnwTe/OdB5/sDFBUIeDRQh6l/RV1vh+wnlaTwgpd64p5mHZnYVGSpMm5xqMkSXUWEYcCfw+8NzMfBDZSuZQaYAmVDsiJYpIkSZLUsux4lCSp/t5G5dLp90XE+4DPAG+NiKOAs4ETgQRu2ycmSZIkSS3LwqMkSXWWmZ8APjE2FhH/CJwFXJ6ZO6uxpfvGJElSfRS9JlsRjylJ7cbCoyRJJcjMHTy9i/WkMUmS1BosOkrSM7nGoyRJkiRJkqTC2fEoSZIkSZLqaqJL08t+TLtUpfqz41GSJEmSJElS4Sw8SpIkSZIkSSqchUdJkiRJkiRJhXONR0mSJEmSVFcHu57ivus5fuxjH2PRokUH9ZiS6s+OR0mSJEmS1FIsOkqtwcKjJEmSJEmSpMJ5qbUkSZIkSVIb2ffS9GZ4zIO93F6tyY5HSZIkSZIkSYWz8ChJkiRJqllEzI+I26q3D4mIr0fEtyPi96cTkyS1PwuPkiRJkqSaRMRc4HPAnGroXcDGzHw18DsR8expxCRJbc41HiVJkiRJtdoN9APXV8dLgfdUb98KvGIasVsm+gGbN28uNuMGadW8W5Xne2of+chHDur7V6xYUejjgf/NpqOVzlV3d/eUxy08SpIkSZJqkpmPAETEntAcYFv19jAwfxqxCe3vTWyzatW8W5Xnu7E8343VTufbS60lSZIkSQfqMWB29fYRVN5j1hqTJLW5hr7YR8SREfFPEbEmIr4WEYdGxDURsSEiLhtzv5pikiRJkqRSbQROqd5eAmyZRkyS1OYafan1m4GPZubNEfEJ4E3ArMw8KSI+HRHdwLG1xDKzdS54lyRJkqT29Dnghog4FTgG+A6VS6priUmS2lxDOx4z86rMvLk6nAe8BRiojtdQ+QRsaY0xSZIkSVIJMnNp9d8HgbOAbwNnZubuWmPlZC5JaqRSNpeJiJOAuVTa68cuMHwCz1x0eLLYpFpp959mVOT5W1DYI7W3os65u0XVxteI5tJOCydLkjQTZebDPN0oMq2YJDXaueeeW3YK+9WMOV533XUH9H0Nr1NERBfwceC3gYuow0LEU76JvfnOA0t8BimyCPBoYY/U3oo65w9YT6uJhS5JkqTW0oxvwvfVjDkeaKFAkorS6M1lDgX+HnhvtdXehYglSZIkSZKkNtTojse3UblM+n0R8T7gM8BbI+Io4GzgRCCB22qISZIkSZIkSWpSDS08ZuYngE+MjUXEP1JZZPjyzNxZjS2tJSZJkiRJkiQdqONeM7/sFJrSPTf+uJDHKX0viszcwTMXHa4pJkmSJEmaeTYvu7TsFJpS95qVhTxOM65Xua9mzNE1NaVnaugaj5IkSZIkSZJmhtI7HiVJkiRJkmaqZuze3Fcz5miHaWuw41GSpAaIiPkRcVv19iER8fWI+HZE/P5kMUmSJElqZXY8SpJUZxExF/gcMKcaehewMTM/EBE3RMTfA+/YN5aZj5aVsyRJ0h6fP3p22Sk0pbc+sKvsFKSmZ8ejJEn1txvoBx6pjpfy9IZptwKvmCQmSZIkSS3LjkdJkuosMx8BiIg9oTnAturtYWD+JLEJbd68uS55ziRFncMFhTxK+yvqfPuHa218jWis/Z3v7u7uBmUiqV2s+oPnlJ1CU1r+yUf2fyc1Hf9+kySp8R4DZgM7gSOq44liE5ryTezNdxaYZvsqqhDgtfC1Kep8P2A9rSaFFbrWFfMw7c7CYjm616wsOwVJUg0sPEqS1HgbgVOArwBLgDsmiUmSJEmqo3tu/HHZKbQ1C4+SJDXe54AbIuJU4BjgO1Qus943JkmSVDo3UZF0oCw8SpLUIJm5tPrvgxFxFpUOx/dn5m5gopgkSZJmGNcyVDux8ChJUgky82Ge3sV60pgkSXqmzcsuLTuFpuTal5KajYVHSZIkSZIkzUjHvWZ+2Sk0paLWvrTwKEmSJElqKXb2Ndbnj55ddgpNybUvpf2z8ChJkiRJktQkVv3Bc8pOoSm59mVrsvAoSZIkSZImZWdfY1lga6yiLinWxDrKTkCSJEmSJElS+7HjUZIkSZLU1K677rqyU3iGc889d9y4GXOUpLLZ8ShJkiRJkiSpcHY8SpIkSZKkvZqxe7OdO0yb8XfxfDdWO59vOx4lSZIkSZIkFc7CoyRJkiRJkqTCWXiUJEmSJEmSVDgLj5IkSZIkSZIKZ+FRkiRJkiRJUuEsPEqSJEmSJEkqXGfZCUiSJEmS1GjnnntuUz3eddddV1AmUvM9v6G9n+Oe78lZeJQkSZIkSXVlYUaamSw8StIBev/Vf1h2Ci3hQxf+TdkpSJKkJhER1wDHAN/MzA+XnY8kqb5c41GSJEmSVHcRcR4wKzNPAhZHRHfZOUmS6suOR0mSJElSIywFBqq31wCnAJvLSsbLbNXOfH43lud7chYeJUmSJEmNMAfYVr09DJww0Z02by6tFqk6+shHPlJ2Cs/gc006eN3dUzevW3iUJEmSJDXCY8Ds6u0jmGTpr/29iZUktQ7XeJQkSZIkNcJGKpdXAywBtpSXiiSpEex4lCRJkiQ1wnXAbRFxFHA2cGLJ+UiS6syOR0mSJElS3WXmI1Q2mLkDOD0zd5abkSSp3ux4lCRJkiQ1RGbu4OmdrSVJbc6OR0mSJEmSJEmFa6nCY0RcExEbIuKysnORJKkenOskSZIktYuWKTxGxHnArMw8CVgcEd1l5yRJUpGc6yRJkiS1k8jMsnOoSUT8L+DGzLwhIt4EzM7Mz+w5vnPnztb4RSRJkzryyCOj7BzKNNVc5zwnSa1vps9zU3Gek6TWN9E81zIdj8AcYFv19jAwv8RcJEmqB+c6SZIkSW2jlQqPjwGzq7ePoLVylySpFs51kiRJktpGZ9kJTMNG4BTgDmAJcN/Yg162IElqA5POdc5zkqR25jwnSe2pldZ4fA5wG7AOOBs4MTN3lpuVJEnFca6TJEmS1E5a5hKuzHwEWEqlC+T0VngjFk+7OSIOi4ijIuLXIuL6iDgpIv5rRHRGxOLq/T8cES+o3v5yRDyv3N+gNUXEn0bEH44ZL4+I/7bPfVZGxNnV20dHxBcbnWc7iYgvRMSxEbGg+pz+WkR0jPnyOV6wiDgyIpZGxKUR8bcREdX4mRHxPyPi7Ii4JSLWjvm6JSJ6ys5dk2u1uc55rhzOc43nPFcO5zqVzXmuPM51jeU8V46ZMs+10qXWZOYOYKDsPKbhd6lsFPCfwA3A5cALgV8Gfh14Evgh8JqImE9lPa8zorKT6UuAz0ZEJ/BbmfmLEvJvORHxTeBo4BcR8bpq+Ghgd0SckZlviYhZwG8AH4uIc4FvA0+Vk3Hri4g3A/8HcDNwF3ALsBj4D+Be4D3AcT7HD15EfARYBMwCTgL+Evhn4Av5dPv6k1RecwapdM0Flf8Ox1J5no82NmtNV4vNdc5zDeY813jOc43lXKcm4zxXAue6xnKea6yZOM+1TMdjixoADgOeDVxP5YnzO1Qmq9cCJ2fm45l5FZUn06ur/76eyhPsAuA3/R+4dpn5WuCTwDeBv6h+rQU+mplvqd6tj8r/tAGcDyTwgoj4fyNideOzbl0RsQB4BfAnVM71hVReRE8APgy8NjO/5XO8MO/OzDdm5nnAg1T++P0B0A0QER1UntcBZPW89gHfy8wnMvOpzNxdUu5qT85zDeY811jOc6VwrlMzcZ4rgXNd4zjPlWLGzXMWHuurh8onYYuAw6n8D70e+P+AbwE/iIhzqi+Mp1PZROAwYDXwXOBvgXc3POv28Cwqn8YcQeWcAhARhwF/SmViOg54JfBZ4DnAV4BfaXSirSwztwNfpDIBDQN/BDwMrAAOBf4yIg7xOV6YN0fE5RHxD8CLga8D76Lyxy9U/uj6CJVP51dWn++XAk9GxHsjYmEZSautOc+Vx3muAZznSuFcp2biPFcu57o6c54rxYyb51rqUutWk5nrIuJM4CfALiq7lX64evh04N7M/FBEDGXmzyOim8pmAtdm5nUAETErIjoys6VaaZvAa4GXV2+/gMp6aQCvovLJ5W8AbwDuBv4AuIJKe3NLfXLQJPqBq4E/5ulzfndmLo+Ir2TmUxHxhz7HC7EF+D7wb8BgZr42Ip4PvDgizsvML0TEFuBMKq81nwW+DBxD5Q/kv4uInswcKSN5tR/nuVI5zzWO81xjbcG5Tk3Cea50znWN4TzXWFuYYfOchcc6ioguKi+KPwFOo3IN//epfEoG8I7qv6sj4ikqHahnAQ9ExNurxzqB/0Fll1NNobrOx54Xu7/IzM9W4/939d8OKmt/bKLyycL7gb+q3r+Tyqc1GxuYcrvYXf16PpUJCyqXoIzlc/wgRcR/ofIp2GLg14BjIuI7wI+ptObftc+3vJvK681ngY9l5g0RcQbwGuAbjcpb7c15rrGc50rjPNcgznVqNs5zjedcVwrnuQaZqfOchcf6eivwQSpPljdT+VRsLpUFiKH6SUxm/kZEvAj4KJVPD95OZQHXi4GvZKb/A9fmAiovkEllE7o9L5ZRjfUDVwEb9vm+zup9lgOdEfFLmfmzxqTcdv51oqDP8UIsoPL6cTvwaeDXMvPEPQerizrv8XzgW5n5ueq6LQBk5sWNSlYzhvNcYznPlc95rr6c69RsnOcaz7muXM5z9TUj5zkLj3WUmX8JEBGXZOaT1SfRG4FTq3fZHRFHUFk498dU1rCYBayismvaFzJzqPGZt6bM/AzwmYhYAfxyZl4CEBFfBdZk5tXV8S9Xv2U3cCSVTzB/r9pC/idAF/DnDf8FWt/9wMeqt2+v/ps+x4uRmd+m8ukuABFxyD53+UxE/AuVy02+T6WFf5zqa1Bkpjv+qRDOc43lPFc657k6c65Ts3GeazznulI5z9XZTJ3n3FymMQ6v/nsIlXbxpcB1wH2Z+RjwR5m5nMoL5kuB71FZ3PVZEXFzVLat135ExLMi4mtUzuOlYw6dD7w0Ij5bHR8KPCszd1BZV+Em4J8iYi2VPyL+unFZt4VDgUMz89LMXFp9fv9ZRHwd2OBzvG5+FhEbImJ9RGyg0q7/ZeB1mfk24DUR8U0ql5scERHfoLIz4O+VlrHamfNcAzjPlcZ5rjzOdWoWznMN4lxXCue58syIeS4ys+wc2l5EHJr7bC8fEbOyxbZAbwURsSgzt0xybH5m/rjBKc1YERHpC4w0IzjPNY7zXPNwnpNmDue5xnKuaw7OcyqKhUdJkiRJkiRJhfNSa0mSJEmSJEmFs/AoSZIkSZIkqXAWHqVpiogPRMRjEfGTiNgWEU27nX1EfDUiTi47D0lSa3GukyS1M+c5qXEsPEoH5q8y83lUdvK6JCKWlJVIRCyKiN+b6FhmnpeZtzc4JUlSe3CukyS1M+c5qQEsPEoHobrb2h3Afy0xjUXA75X48yVJbcy5TpLUzpznpPqy8CgdhIh4IfAK4L6I+G8RcX9E/Cgi3lE9/nsR8cXq188i4h8iIqrHVkTEQxFxX0Sc/f+3cz+hUpVxGMe/j4IWlFpQXUgMDCSCyI1EgRghlSupqI1JYIQQd1O0NIhqJ7VI3SSYVougW5AiFkj0jxuCUJYIobcoMErCECQMgl+L80oXqzHmnhEav5/VzPtv3jmLeeB33jmtbWuSyVnrH09yY5J5SV5N8mOSE0nubf2fAu8CdyX5KcnOC/b3UZK7Z72fl+Sl9neCI0lWtfbdSbYkmU5yOskzI71wkqT/DbNOkjTOzDlptCw8SsOZTHIKOA5sBf4AnqYLrJXAc0luaGMfAt4CbqI7xr8yyVrgMeB24AHgtTZ+CjgfWCuAU1V1ElgFXAssAx4FXgSoqtXAg8B0VU1U1RMX2femtr+bgaeAt5MsbH2bgY3AfcCzQ14XSdL4MOskSePMnJMuAQuP0nC20x2HPwvsB+4BlgPHgCPAVfx1VP9wVe2rqrPAN8BiuiB6s6p+rapjwCFgdVUdApYnuaKNmQJo7S8DzwPbgOuH3Pc6YGdVnauqD4EzwG2tb09VzQCHgUVDri9JGh9mnSRpnJlz0iVg4VEaUlX9BuwCngQCvN7uUE0AS+meEwIwM3vagNfn378PrAHuB94BSLIB2AF8AUwyN//2uTMAVVV/myFJuiyZdZKkcWbOSaNn4VGam+10R9k/BtYlmUhyNd0dslvbmH/60T8AbEiyJMktwB3AZ61viu4o/5VV9UNruxP4AHgPWH/BWr8AS5PMT3JNkvkD9nsAeDzJwiRrgCXA0QH7lCTJrJMkjTNzThohC4/SHFTV98AndCHzAvA53dH8HVX15YB5B4E3gK+AvcCmqvq5dU/TPZNj/6wpu4FHgO+ABcB1SRa3tY4CB4GTdIGzYMCWdwFfA98CrwAPV9Xv//0bS5IuN2adJGmcmXPSaMUTuJIkSZIkSZL65olHSZIkSZIkSb2z8ChJkiRJkiSpdxYeJUmSJEmSJPXOwqMkSZIkSZKk3ll4lCRJkiRJktQ7C4+SJEmSJEmSemfhUZIkSZIkSVLvLDxKkiRJkiRJ6t2f9bpS1BXlnRQAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<Figure size 1440x360 with 3 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# 去掉错误数据“南北”，因为爬虫过程中一些信息位置为空，导致“Direction”的特征出现在这里，需要清除或替换\n",
    "df['Renovation'] = df.loc[(df['Renovation'] != '南北'), 'Renovation']\n",
    "\n",
    "# 画幅设置\n",
    "f, [ax1,ax2,ax3] = plt.subplots(1, 3, figsize=(20, 5))\n",
    "sns.countplot(df['Renovation'], ax=ax1)\n",
    "sns.barplot(x='Renovation', y='Price', data=df, ax=ax2)\n",
    "sns.boxplot(x='Renovation', y='Price', data=df, ax=ax3)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "观察到，精装修的二手房数量最多，简装其次，也是我们平日常见的。而对于价格来说，毛坯类型却是最高，其次是精装修。"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Elevator 特征分析"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "初探数据的时候，我们发现 Elevator 特征是有大量缺失值的，这对于我们是十分不利的，首先我们先看看有多少缺失值："
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Elevator缺失值数量为：8237\n"
     ]
    }
   ],
   "source": [
    "misn = len(df.loc[(df['Elevator'].isnull()), 'Elevator'])\n",
    "print('Elevator缺失值数量为：'+ str(misn))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Elevator 缺失值数量为：`8237`\n",
    "\n",
    "这么多的缺失值怎么办呢？这个需要根据实际情况考虑，常用的方法有**平均值/中位数填补法，直接移除，或者根据其他特征建模预测等。**\n",
    "\n",
    "这里我们考虑填补法，但是有无电梯不是数值，不存在平均值和中位数，怎么填补呢？这里给大家提供一种思路：**就是根据楼层 Floor 来判断有无电梯，一般的楼层大于6的都有电梯，而小于等于6层的一般都没有电梯。**有了这个标准，那么剩下的就简单了。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1440x720 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# 由于存在个别类型错误，如简装和精装，特征值错位，故需要移除\n",
    "df['Elevator'] = df.loc[(df['Elevator'] == '有电梯')|(df['Elevator'] == '无电梯'), 'Elevator']\n",
    "\n",
    "# 填补Elevator缺失值\n",
    "df.loc[(df['Floor']>6)&(df['Elevator'].isnull()), 'Elevator'] = '有电梯'\n",
    "df.loc[(df['Floor']<=6)&(df['Elevator'].isnull()), 'Elevator'] = '无电梯'\n",
    "\n",
    "f, [ax1,ax2] = plt.subplots(1, 2, figsize=(20, 10))\n",
    "sns.countplot(df['Elevator'], ax=ax1)\n",
    "ax1.set_title('有无电梯数量对比',fontsize=15)\n",
    "ax1.set_xlabel('是否有电梯')\n",
    "ax1.set_ylabel('数量')\n",
    "sns.barplot(x='Elevator', y='Price', data=df, ax=ax2)\n",
    "ax2.set_title('有无电梯房价对比',fontsize=15)\n",
    "ax2.set_xlabel('是否有电梯')\n",
    "ax2.set_ylabel('总价')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "结果观察到，有电梯的二手房数量居多一些，毕竟高层土地利用率比较高，适合北京庞大的人群需要，而高层就需要电梯。相应的，有电梯二手房房价较高，因为电梯前期装修费和后期维护费包含内了（但这个价格比较只是一个平均的概念，比如无电梯的6层豪华小区当然价格更高了）。"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Year 特征分析"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "D:\\ProgramData\\anaconda3\\lib\\site-packages\\seaborn\\axisgrid.py:230: UserWarning: The `size` paramter has been renamed to `height`; please update your code.\n",
      "  warnings.warn(msg, UserWarning)\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "<seaborn.axisgrid.FacetGrid at 0xdd27f1ccc0>"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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X7fmtlciG13PNJQAAAACNpR7Pb0pZrn5UUlvW7x2SpiobDoBSVGJET5hKZMMzNZc2rGjXlYvmaMOK9pouzAYAAACgcdXj+U0pI4b+QtKTZnZv+vc3StpYbCczmy/pIkk/cM4dLj1EAEHLIVZ7fmulsuH1UnMJAAAAAOrt/CbyiCHn3BckvV7Sf6f/rXfOfT5sHzM7VdJ9kl4h6btmttDMPm1mj5vZxqz7RdoGNKL9SdP1W45o866ktvWNa/OupK7fckR7EhNVn9+anQ2/qCdVF9lwAAAAAMBJJa1K5px7RtIzJexygaQ/dM49kU4SvUZSs3PuMjP7jJmtlFe3qOg251xvKbEC9eKOvS2B08VmYn5rJhve23tEK1cuLesYQSOeAAAAAACzy5xz1X8Qs1dJ2iTpZ5K+6px7wMxukNQu6eWSHiq2zTn32czxBgcHTwTd20u+CPXt5qfatGOocATQRT0p3XH+mPYnTXfsbVH/eJMWzpnSzUsndVZ79b/XUe1Pmt7zkzbtGz05QHHJ3Cnddt5YxeJcs2aNTWd/2hQA2abTptCeAMhHmwKgUqZ73hMkdMSQmf2hc+4T6Z//wu8+zrm/LHIMk/R2SUclOUn70zcNSFotqTPiNl8rV64Me3hfvb29Ze1XaXGJQ4pPLMRRaOGzz0sqTAytWNCllSuXaqWktRf471vJkTrlviYf2zqgfaPJnG37Rpv0haPzdecF5c3Lreb7U+px4/RZiUsscYlDik8scYlDik8s04kjDm1bFLXcR5HiEwtxFIpLLHGJQ4pPLLQp8Y5Dik8scYlDik8sxFFopmIpNpXMAn6OzHlDkt5tZh+W9DZJd6Zv6pJX42hY3iihYtuAhnTz0kk9Ozq35Oli1V7KPqpqF8gG0Fji0rYBAADUi9DEkHPub7N+/lCpBzezP5N00Dn3r5LmSfqopCskPSHpQknPStoXcRvQkM5qd7p73QJt2plQ30hKiyJeHQ9byn4mK+hXu0A2gMYSl7YNAACgXpRUfLoM/yzpK2b2LklPS7pb0iNmdqak9ZIulTe97NEI24C6FjY1Imw5xPz9blzVrrueS2rLC6O+95/pkTozUSAbQOWUO01rporMMwoRAACbUUy0AAAgAElEQVSgsqqaGHLOHZX0uuxtZrY2ve1jzrnBUrYB9SpsakSp+31jd1KTITWdZ3qkTmbJ+1JHPAGYeeVO05rJ6V2MQgQAAKisyLV7zOw7ZjbtS/zOuaPOua845/pK3QbUq7CpEaXuF5YUWtJhszJSJzPi6d71C3XnVfNJCgExVcm2KMp+5di4ulvLu3OTQIxCBAAAKF8pRZ0Tkl5VrUCARlbu1Iig/QJZVVY3BFAnKt0WVWN6V2YU4oYV7bpy0RxtWNFO4WkAAIBpKGUq2ecl/a2Z/ZKkJzMbnXOPVDwqoMGUOzUiaL8g+45PUaAVQKBKt0XVmt4VVncNAAAApSllxNB7JB2UdI2kD6X/fbAKMQEN58ZV7WrJG8zTYt72MH5TKvKPk48CrQCClDtNi+ldAAAAtavoiCEzu1TSlZLuk/SfzrkfVD0qoMHc9VxhwehJ523/0zOD9/Mr7JxZlezhA2PqH50q2IcCrQCClFssniLzAAAAtSs0MWRm75P0m/KSQibpy2b2CefcHTMRHNAoplOfw29KxeWL231XCeIKPoBiyp2mxfQuAACA2lRsxNC7JV3onDsiSWb2SUnflURiCKigatTnmIkr+HsSE9q0M6GDIyktZoQAgGmiTQEAALWmHvovxRJDzZmkkCQ55/aZWWeVYwIazsbV3dreP+47ume870jInuGiXsEvpzHzG5G0vX+c1YEAlIU2BYi37L7CKa0m56RDQ21acWCgJk+CAKAS9iQm9MYH+rVv5GRdkMf7RnX/NQtrql0slhjqMbMv5m2bl73NOferlQ8LaCxho3t6+6r72OWejG3amcjZR5J2J1KsegagLLQpQHz59RU8zdoxlCSJC6Bh3frEYE5SSJL2jTjd+sSgvvS602YpqtIVSwzd4rNtSzUCARrdbNXnKPdkbDp1kQBURy0PZaZNAeLLr6+QjSQugHqQ6UftOhx9NOT2wxMlbY+r0MSQc+5zMxUIgOgqefJX7slYd4v5bu8K2A6gump9KlY1aq0BqIygvkI2krgAaoXfuZSkrH5UKaMhXYnb46nocvUA4qXSJ39BJ2N7hlO69sH+nMYy8/ibdib05KFx3/2MvBAwK2p9KlZYrTUAsyuor5CNJC6AWhB0LvXSnpay+lEXL5yjB14Y891eS0gMATWm0id/fidjLSbtHU5p77C3bXv/uD65yjQnsMbASYmJ2sqOA/Wi1qdizcRKigCiy76i3t1iWtLZpH3Hp3zvSxIXQK0IOpcaDjiHKdaP+sglPXpq4HBO+7iks0kfuaRn+sHOIBJDQI2p9Mlf/snYnqyEUMbuREp37G1R99HwGgMSVwyB2VIPU7Fmq9YagFx+V9SXdJiuObtNiQmn7syqZIkRrVjQVZEkbi3XSANQO4Knxvonhor1o5Z1t+r+9afV/IUtEkNAjanGyV/2ydi1D/YXJIYkqX+8ScNFkk9cMQRmD1OxAFSK3xX1fSNOly1q0hevPpm87e3t1cqVS6f9eLVeIw1A7Qg6l7p44Rz997HJsvpR9XBhq2m2AwBQmo2ru7W8O7dBq+TJX1BjuXDOlE5p9S8gNL/NtGFFOx04YBZlRv9tWNGuKxfN4TsJoGwzPTU1bJo8AFRS0LnURy7pOdGPuqgn1XD9KEYMATWm2nU4gkYd3Lw0qX960X+fSxbOqfksOVAP6uGKFYDZN9NTU2u9RhqA2lHsXOrOq+art/dIRUZD1hISQ0CZKj0X/rGDSd2ybVDHxqY0r61JH1jdqYf2TWjX4TatODCQc/ywk79y4srf57bLe3TXc0n1jaRO1BH4cO8c7R33X4nsW/vGdMHmPt1+RY8uX9xe9msAAABm30xPTa2HGmkAqqMa9ce4kFaIxBBQhkrPhX/sYFLXbRnQZLrm2dBESu98ZCh9a7N2DCUjHb+cuML2kZR1W7OCirKl5K1idt2WAd2zbj7JIQAAathMrxJIjTQAfqg/NnOoMQSUodJz4W/ZNngiKRQkyvHLiStsH7/bwkw677kAAIDalrmifu/6hbrzqvlVPQmjRhoAP9QfmzmMGALKUOm58MfGpiLdL3P8oCGV5cQVtk9Qrmrh3CYNjE7Jb8/BiM8FAFieGkAGUzsA5Itz/bHsPkx3i8lMGppwWtzRrBtXteuu55I11b8hMQSUodJz4ee1NWloongDt6ijOXRIZTlxNTv/9E+Tczq907+JWHtmm548NO67rH1PGwMRARS3P2n6A4aHAwCAAHGtP7YnMaE3PtCvfSP+51Hf2J3MmQ1SC/0bzuCAMlR6yfjbr+hRi/9K8AXHDxtSWU5cvQFTxXoTqdDj+cXcYt5zybcnMaGbtg7o2gf7ddPWAe1JTIQ9VQAN4I69LQwPBwAAgSp9zlUptz4xGJgUklRQIqQW+jeMGALKUOmijJcvbtc96+brlm2DGhybUk/2qmRHhrViQVek6WLlxDU84d+oHZ9wOcfLj2NZd2tBzH6rklE0DoCf/jH/a1NxGB4OAABm30wXwo9q++HSL3LHvX9DYggoU/Zc+ErUybh8cbue2nAyqfLYwaSePHRcA8km9afGtW94Usu6W4sOqYw6Rz8T81jKPzGUmRKWOV5v7xGtXLk0NGY/YSOcqCUANK6FbVPyVjvMlWnLqD8EAADiWX+syKpBPmZ7+lsxJIaAaarGiJjc5etNw1lLwd+4qr1g3mqLSTeuir5EvF/M+T6wurOs2PPFuWgcgNlz89JJPTs613d5akYaArODhCwAFHfxwjl64IWxwNtbLHc6WRymvxVDjSFgmqqxjKLf8vWZpeDvei7pe9tdzyUjHz/KMvQP7atMHaC4Fo0DMLvOaneBy1OzPC0w8zIJ2c27ktrWN67Nu5K6fssR6gICQJ6PXNKjJZ25qZT2Zuniha3asMIrEeLXv4kzRgwB01SNETFHkv77vjCcUnJydNqPFxRzuccLs3F1t7b3j/uOCgDQ2IKGh5farjLKAShf5vvz8IEx9Y9O5dzG1G8AKLSsu1X3rz8ttPZRft3VuKtqYsjMeiT9u7wiAsclvV3S7ZJ+SdL9zrlN6ft9Oso2II6qMSLGmclv7qqT1D/qP6e1lMcLirnc44WJa9E4APFVSrvKtDOgfFGmljP1GwAKxbP2UfmqPZXsHZI+4Zx7vaQ+STdIanbOXSZphZmtNLO3RNlW5TiBslVjGcVfOKW0pEypj+cX83SOV0ym4bx3/ULdedV8TtYAhCqlXWXaGVC+KFPLmfoNAOH2JCZ009YBXftgv27aOlCTU3DNudIrapf1QGZflXSKpP/nnHvAzG6Q1C7p5ZIeKrbNOffZzLEGBwdPBN3b2zsj8QNh9idNd+xtUf94kxbOmdLNSyd1Vnv53633P9uqh/rDkyfzW6e0vMOV/XjZMXc2O8k5HZ+qTPwzbc2aNTad/WlTgPiJ2q7e/FSbdgwVnrhe1JPSHecHF4YMM502hfYEtSTo+5OxZO6UbjtvrKb6BHFEmwLUr/1J03t+0qZ9oyfH3FSz7ZzueU+QGakxZGaXSTpV0vOS9qc3D0haLakz4jZfK1eWPpiot7e3rP0qLS5xSPGJpVbjmJOYUPfRhIZHUuruaNby5dObKvXXiyb0g/sO6UX/ckKSpNee3ek7fPGxg0ndsm1Qx8amNK+tSbdf0eM7x3WlpLUXRI8pLu+NVN1YSj1uo7wutRiHFJ9YZiqOKLV2auU1idqurjgwoB1DhcX3Vyzo0sqVS6cdx3TUch9Fik8sxFGoUrEEfX8WzjWtPXNu0anf9fiaxDmOWm5T4hKHFJ9Y4hKHFJ9YZjuOTD9q1+FhrTitK1L5i49tHdC+0dx2dN9ok75wdL7uvGD6U81m6jWpemLIzOZL+ntJb5X0h/JGBElSl7ypbMMRtwGxVKy+RdRETbZ9w5M6XORC9xuWFDZSucvcS0MTJ5e5r7UCaABKU0+1dkp5LhS4B8oX9P2ZjXaDIvIAZlNu36NZO4aSkfpR1ViIaDZUNeFiZnMkbZb0PufcHkk7JF2RvvlCeSOIom4DYimsvkUmUbN3OKWhCae9w16i5rGD4UvL37JtUKkiIw8/tPO4735By9zXw9xXAMHiXGun1PanlOeSKXBfa8vCAnEQl+9P5oRs866ktvWNa/OupK7fcoS+CoAZU2o/KtO3efaYfztVa/XZqj1i6J3ypoH9uZn9uaTPSvp1MztT0npJl8pbaOnRCNuAWArLEoclap7aEDyCZ2C0eIZ5wGdJ+6D9joym6mYkAQB/u4b8Oya7A7bPlKDRP59cZQoaGF3q1bd6WxkEmElx+P6EnZDNdmwAGkMpfY9iKzrW4sjlqiaGnHO3y1ue/gQz+6ak10n6mHNuML1tbZRtQByFLav8oyP+J2SDY1MF27KHUPvkfApMWWHdsSn5L3M/mpJvh2v11w5JTmptli6c36LW5iYt7mjWjavadddzyZzh3ADirX/Uf5jhoYDtGWHTNyoxtSPohO+OvS2Bdc5KWa4eQO2rl6kYAGZWJaegltL3CFrRscWkMzubddvlPTV38X1Gik9nc84dlfSVcrYBcRRW3+LJQ+MamihsNHravFmcmcZsd2JS/310UsfzhxeF8FvS/sx2p5/5jXYMOGxmuloqJT3ZP3li+zd2J3NGOhW7uu+HWgHAzDq9vUl7hwvbmzPag2eNh9XykVSRkYZBJ3z948Fx3biqvaAdajFvO4D6QzIYQKkqXVuxlJqFQX2bSSftHU7pPY8N6u51LTV17kNRZ2Cawubn335Fj/LH9Zik26/oyZlPv71/oqSkkCQt6SzsLB2f9P9Kl3q9LT+UzNX9qKgVAMy85d3+39FzArZL4dM3KlWzKOiEb+GcwpGTGXc9l/SdhnvXc+H12QDUpo2ru7W8O7etqMWpGABmTqVrK2af013UkwqtuRbUt6lEHLNlxkcMAXF2conCNq04MBB5lEvY/Pwm5SZmMqmboCGIUbn0SdPXfp7Qe/8robFJV3ICqBRhV/fzUSsAKE0lRtgVu9Ll176FTd8ISlWXOrUjKK6blwYneZhWAsRbuf2loOMcHEnpF+e16KU9LRqedFpUhWmtAOpLNfoKmXO63t4jWrlyaeD9Nq7u1uN9o9o3Enxhv9b6LCSGgLRylygMc8u2wYJkTSq9fWnX9IZHD086fe3nCb3zkaFpHSeqsKv7+YIa6m+9MKqbtpbfgQTqUaWGQmeudG3amVDfSCrnxCqofXtpj383IGz6RtBtQSduQXGN9wVfSWNaCRBfleov+bV9y7ubC45T6ekiAOrDrPcVzL+2a0Z3a2E92DhjKhmQVu4ShWHLLx/zKTItecWnT5lmY7Goo1nv/a+ZGaLYYtL1p3uvzWMHk7pgc5+Wfv6ALtjcp8cOFl71D2qoBycc08qAPJUcCp250nXv+oW686r5J06agh7DTIHTN0qZ2lFs+mh2XDeuatebHjqiVz/eHtiGMK0EiJ9Mv+fq+w5XpM2K2vZVeroIgPowm32FTTsT2nc8/KK5K61KyKwjMQSklbNEYbEaOvPa/L9iPW1NgY3FqXOka85u05KO4MRRptEbLbEukeQleZZ2NetPzp+rjpZoyalJJ919qFmPHUzqui0D2juc0tCE097hlK7bMlBwYufXUGejQwecNBPTpoIeIzHhAmukhdVPyxf1xC27DRlOWWAbUspjA6i+7H5P/6j/yVBQmxV0IS1q28fUUgB+ptNXiHKBP0xQu5RtuIzztNnEVDIgbbpLFPrV0Ln9ih5dt2WgYGWd26/o0Ud+OOz7eFPO1NnapF95SZs+8fSoUs6pyUzn95hOmduaMz0krLlpscIi0pJ0apvpqQ2L9NjBpL68e0IvDAfXEsm2baBFj3znqG9B2Fu2DeqpDSdXC1rW3arbLu/RLdsGtX845Vv7iA4d4JmJodBhjxFWIy3stmxRT9xu2TYYqQ0p5bEBVF+Uuoh+bVbYNLCgdumZYxM5085nfboIgNgqp69Q7vTU7CnzfqvA5qu1NooRQ0BaKcMRo54EXb64Xfesm6+lXc3qaTUt7WrWPevm6/LF7UWnW/3Nj0fTy8mbppz0o2NON66amzM9JCiz2yrplDn+o4FSLveqfdRc9nDKNBKQ+d47nMqZErInMaH3PDaovQFJIUnqijhaCah3pQ6FDrvKFXRbtYdbRz1xC5teCyC+il0dD2pPwi6k3biqXX5dgf7R3GnnTC0FUEnlTE/Nny2ydzjl235l1GIbxYghIC27QOquI8NasaArsEhyKVevLl/cXnAlXPJfqaeY9/5XQm99yclGprXFNOGTrGltMQXMYlNbk/9V++nKTAm5Z9183fVcsujzMvJCgKTwotH5wq5ySQq9Aha1fStHsRXRMua1NWloorBt6AlqsADEQlC/Z37LlF67tDNwBbFnj/lPz+gbSemu55KhfZHskdhR28gwrGwGQCpveqpfMmnSeeU5lnU1q7vV5Jx8V1WsFSSGgCylLFEYZVnosM5HlOlW+ZLpHlTm+C6gUNHSziY1m9PBZOHtC9pMz0cY/ri0q1mDY1ManIieQcpMCYmy4tqhJFPJgIyoQ6GLXeUKm+IatX0rR9Tk1gdWd/qupPiB1Z0VjQfA9GX3ZU5pNS3psJylmZd3N+uTq5Jae8HZOfvkJ6j9LOpojlSjI3OiNt2ppaxsBiCjnOmpuxOTvtvPaG/SvesXViSu2UZiCChD9GWhPX6dj+zpVlE5Ret0DYUkcwbGpSmFL68oSXObpnTJ2XO1eVfhikEdLcHTygbHprT49Dmhx5akQ6O1VZANqKaoV7KDrr7fvyepzlb/UTczVc8ryonbQ/v8439o34Te+pJqRAWgHH59jSWdTVq/ZE7OFfHxvuIriOXLXEh735ODReOoVI2OqLUhAdS/qKOcsx047t+u7Q/YXotIDAHTlJ/eKDaf/pZtgzo2NqVJp8DkSpgona7k5JRM/nO1DiWnFKWf9fOE0+bXd+vxvtGcK4RLOkz3X7NQb7j/sA4mC+uCdLSYNq7u1uMvjoUu43hGO1NHUB+mOz2hlCvZPxvy/+6PpKSRlP/3baaKH0Z5HVhdCIifxw4mT/RN5rU16fYrenynhO87PqUmm9TSrmYdn5jSrU8M6tBQm1YcOFkoOug7vnBuk146ryV3AY0iXaBK1uig7QGQUcoU/ozkpH8fK2h7tlqZxkpiCCjDnsSE3vhAf07C5PG+Ud1/zcLAzsd/D4zpui3h8+klqafVQqdvRRl63dLUpMkp/4Zq0klD/qMhc2Q6bJMud3SR97t0bk+zb2Lo3J7m3AMEOI2aIqgDlZieUMqVbCt2JpVnpoofRn0dWF0ImBlhJyLZt7XI6dG+iRPT2YcmUnrzlgH94jz/7+Te4fzVeJq1YyhZdKWxtWe2FbRniYAOUU+r6fVnz63oyRNtD4BspU5PbWlqklR43uNtD1ZL01g5MwPKcOsTgzlJIUnaN+J06xODgZ2Pnx6bilTw+fVnz9WpASuKnTrHAo+fbc1prWptml51ZzPp1d/sV19e8qcvOaX1DxzWziP+2aWfHJvU1ff1F7w+fscHal05K1vkK+VK9oL24t//hXNNVy6aow0r2mes4xH1dWB1IaD68lfPyV7hK/+2h7OSQhkpFzw6MUjm+17KdzyoPzOnufIdBNoeANOx5jT/vlTQ9oxK9BNnCokhoAzbD/vXydh+2H9ZVckvx1yos0XaNTShFvNPqlxwakvg8q4ZJml7/1ikGj7z20wruv2bgZSTBsb9j3FgZCqwjlH/qFN/hMdOlFDUGoirSkxPKOVK9u1X9IR+/yVp7Zlzde/6hScKTs+EqK9DZvj2hhXtuqgnNaPJK6BRhJ2IRJmOLkkTU/Lty4TZPTSR8x0vlqAOXq5+KieZVQmlxAUA+T56aY+WdOQ2WEs6TB+9tCd0v1qaxspUMqAsQUkNl7Pa2IHjqaKjhDpaTOed2qKfHp3U8UmnHYeD53lNmRVd3tVJ6h8r+gQkeUvXn9vTql2JiDtUEMO3UQ8qMT3hxlXt+sbu3O91i3nb812+uF33rJuvW7YNamA0pWTKS+JmVPsKeND0lGKvg99+432Fq6PVyjx8IM7CTkSiXpJpMeXU4NhTMIWs0E+PpXTtg/2+U9du2jpQ8L0uZbn6SpjuymYAGtey7lb906tO1S3bBjU4NqWedD22Yn2UWprGSmIIKMN581r0cF/hVazz5rWUtNpYi0mbrz5Vdz2X1Pf7i18V62qxSDWGohqbCh79VE0M30a9KGdli3x+J0eTztt++WL/5NBTG7ztmURK1OKJ0xE2Tz7sdQja75OrTCsjHp/kEBBd0InInuFUpEKpknTZ6a05iZQoK6KOTDpt6xuXdPK7Kynwe13KcvUAakO9XuDJP78bnEjpPY8N6u51LaHPrxL9xJlCYggoQ0fAstAdrU2Rhmm3mHRmZ7M+sLpTdz2X1JYXRiM9rpnUXGLx2TDeNP7qTulaOLdJa05rlZk3fazaJ6/ATMju+PzivBa9tKclZwnnUj7fxYYZ+60YlEkY7Rue1JOHxnVsbEp7hlPafmi0oh2y7OdZWHQ294p+0AofN20d8J3WcsfeFq294OQ2lpNGXGW+gwPJds3/YV/Od7BSKnky5Xci0mIKvGCVu8SE1CqvMPRNW0+uNpa9is83n09qrEh+aXcipQu/ekjNljuqMXPbpp2JSDUTfzIwkRMHgPiq5ws8xfoo+W34javadddzSR0cSWlZV7NGJ6c0Min1tDXptsuLjzSaDSSGgDIE1ddJTDgNTRRPCt2zbr6WdLUUvfqWb9/xlA6PRrvaF8WKU5q1oK1ZD7xQnalkZ7RJ37r2tFg2fkC5/Do+y7uby+74hA0zfuxgUm96aOBEjbKhiZTe9NCA7n2Dlyi5bsvAidFGQxMpvfORoZxjfH13Uu3N0vy5XiL6oX0T2nU4d3npsOf5xgcPa9/x8DYnk8AKmqaxa8h/VOILyaZI99sdsB2YCY8dTGZ9z0zDwyldt2VA96ybX7HkUKVPpvKXYg6aBrZwbpMuXtiqJ18c05Hxk9snJO04PKkdhydPrLi6rLv1RCK6WFIoW35SKKNvJKXbrphXkMDKNzDutHlXsm5OLoF6Vg8XeDIJnvy+UtBFvIcPjOq1976oZ45N6nhWNZD8EgEZgxMp/e4jR3X/NeEjjWYDxaeBMoSdyBW7AjbppBsfPqo3PVRaUkjyVgkZGq9cYmhvIqWPXNKjJZ3Fm4IWTWn9kjadMTf68Q+PeyMagHpS6RUmwlbLedfWowWF66ckvWvrUd2ybbBoDbOUk4YnvZEC73xkSJt3JbVjqDlSYdf3PTlYNCkkeVNcwwQVox+YiHa/KIX0gWrx+55NOm97pVRj1ZpMovbe9Qu1tMu/X/LSeS1yTjlJoXyZFVczCbIo0+SjWNTRnFMQuqc1vB2J6yo+AE6qpULLfrJXbczvKwWd3/WPevVhj+ed7oT1zzLtatyQGALKEHYiV2zVMMlrRMrpXCUnnZIVbFtHJr3O44cu6lJHiykspTW32fSl152mz6ydr6VdzaH3zUhVuPMcJ5limjc/1aabtg5UbOWUYo937YP9M/J4CFZKxyfK58RvtZzbLu/xhiQn/XsWfUmn/dM8QSt2ovX9/pCzxSxWpL07vd2/q5G/wmvQ/c4I2I7qmen2Lc6OBQyPGSxl2EwR5Z5M5f9deOxg0vfvRNjFrCh1Bh/cN6Y3Z41OnK7s+hqZBNbrzy5+1Sno9eDzCsRDnAsth/WjM7ddfV9/YJI+aNXpcs1GjddimEoGlCF/mHZ2PY1NOxMV6zzlcwoell2OjhZvmPzvPjpUfPW05qmSCmtnVLLzHBe5w/6btWOousPc63nOdi2K2vEp5XNSapFXJ6kSOeLwE8/8yiP+EgFTazNOn+uf2Dl1Tu5+y7tbtN2nCP853XRVZtJMt29x19livtPHO4pdASpBKSdTmWkOP32xTbtGD+VcLPr67mROHyFKcfiHD0SrcRil79HRYkpOusBWo6fVAutr+K3OmC/o9eDzCsSDX1uzpLNJw+NTvisWzpSwfrRUWCA/X99IquDc75ljk+qfVnmP+I2GprcFhAgrBhlUT6OSq4ZV29Ku5kjTUSTp+KTpTQ8dKXmkU09b/V3tn84c6nIKjNbDnO18tbZqRXa83S2mRe1N6kue7BAs6WwqWGGilPetWJHnagk78ZycitbhCTvGwZGUfj4YcFUsr5B+La3cUc/qsb2ZjnN7mnUwWfhdOLencleO/T77nS2m3YnJnMLL+UmQfH5Fnq++77DWntmm2y7v0V3PJQsuZl28cE5F6gxmVln9P987ph8NBIyymnBefY1Hj+n+9bn1NYotXX/GXPm2BXxegfjIT550t5qeOjKuB/edbGNmI3FbbLpusdIemX5O9rnfTVsHtHlXsuyYLl44p+x9q4XEEBCg3FEaUVbZiItdiSmNRFy69vhUk44HnKz2tJpeflqrHjk4nlMPpcWk26/oqUCk8TKdYf/lfKZqfc52vlobAeUXb0G602e1wKjvW5QRQsWYpLO7ThaYfubouJ4+mgq9HuWXdCk1lukc4/hU7qsYNhITM6fe2pvpSgRkK4YrODQ4+7O/e2hC/31sUscnnbb3T6T/jZ+8vcR2on90Spt3JfXI/qQuOr1NTtLw+JTe9+SghiacTmk1nTFXejHawCEfTku7Wk6s1HZg5GjRPfYd9x7/i1efdmJbsYtqh8e8moX57QGfVyBe8pMn+0Zy28rZSNyGtRPFWvKgC1RRRjkunGs6p7tFTw9M5IzuXNLZpI9cEr/zo/q7lN+gqD8S/TUIu99jB5O6YHOfXv14uy67O3ieaZhKz0Gtpv7RqYJiaeV4/dlzdfcbFureN3j1h3paTUu7miu6akuclDuHutwCo3Ges12OahRarSa/ePPTqftGXEH8Ud+3qCd7bU3eMtJ+5s2RntqwSIs6WvTkofEo7s4AACAASURBVHHtGZ7SqXO8fZrlTfH4k/PnamlXs7qanZZ2NftO54gSy9Ku5hO1kPySeVGfz+7jFthW+/Wz+Ds3MyrV3tTL+zVTRdEzJ1PLT2kt+LucaR+nMyL5xTHpgRfGtK3Pu3qf+fmBF8bU2tyk9UvadOWiObpkYYvmlvBWv2HhpJ7asCjrb320KXZbXhiLVAcpI6hmYXfAlL5iRfEBVF9cErflLBo0v3UqsJ8jFR/lKElrz5yrb197up745dNz6kjevz6eKzYzYqgO1NrV92qI+hqE3W/f8GTOkrRBcz8zjVnQVJjsK3/f2JVUva/JlZ1Jv3xxu57aUH+JoHzlTnkp9w/kxtXdevzFsZwVovymLtWKuHQUisl8x7e8EO1Sen78UT8nUU/2LljQqv3HUzowUjjKr72lKW9Z7Vwjk06ffHo0Z8nt9zw2qLvX5U7niBLL6XNN965fGHh71OczMNmUswy1VDjPP8pt9fJ3LmiJ3JlWiSl99dQvOb29yXdqZzlF0aNMoQ1rH4OSINO17/iUmmxSp7RKTx+N3g4v6TDdvDS3l7PmtNacaSNBUpI270rq8b5R3X/NwkhX3/1qFgYVvy9WFB9A9cXlwmZYP3rf8GRB29Ni0l+tGtcNrzg78JjF+jp+RfbjjsRQjEWtwcH86uivQdj9njw0HqnWzqKOZt9O7wN7R/WLp7ZoeXeLNq7u1p1Xzdeh44e09cXavEoaZmlXs5Z1NUee6lFr9WSKWdbdqtsu79Et2wY1kJzU/PYW39EX+ab1BzJ/qpLP1KVaMRMdhccOJtPvT7vm/7DvxDSHfEGfzXKmd+XHn50k3nVkWCsWdOV89jMxHjge7THO6W6Rk3wTQ2d1Fq8Xln+bV3+kX2vPnHsirihTYYuNlAg6RkeLaSLllF/HN2yef5Tb6uHv3HQK6Ia1r+XcVuxzG8Vs90sq+TenUkXRoybLwtrH4xPVW8yhnLpm+0ec3rJjrub+6ID+/pXdeutLuvXRS3u0895DejFi2aLMss1dc5qK9sH8ahb6FQaXihfFB1Ad+TUZl3Q25SRkZq12YEA/2m/kz6ST7j7UrBsU/PckqK1eONe09sy5unFVe82d+5AYmgVRrgqWcrWtVq6+V0OxK/r5r0HYaxVl6edMY+bX6fWrBzBcySXEYmJ5d3PgyYpf4ylJb3zwcM4fhcdfHIvtMMoocldnCx59ka/cK/GbdiYK5mhnpi7V4klxtYsM546c8d6f67YMFExtDGtni02HarHcREtQ/PuGJ/XkoXENJJvUnxo/USMjbHSPF3XumMUlHXai7Qk6SX32WOlFQvpHXc6oHb/3Jl+xkRJ+x2gxb9RSkLB5/t96YVRzmv0v/9fL37lyEymlrrQSdQRW5upmb+8RrVy5tOTnM5v9kkqPViq1vQo6iYj6HocVot6TiNcYZCfJyTQy6fTOR4b0Tz85rpSZBksMc/vhCZ07L/yUJKhmYVxGJADwb3+XdJiuObtNiQlX9dqBYe1vUD96d0C7uj/ZpD2JCb3xgf6cfTOjHP3bau/i+fGJKf3uI0dz9quFUbNVTwyZ2RmSvuqcu9LMWiV9XdJ8SZ92zn0m6rZqxzlTol4VLKWT2Kh/FKNc0c9/DcJeq7Du6pWL5mh8ako/PDyp1V89VLRQWea9CqpNUJu8ApMbX96ZcyXATCcKWD51ZLygEVyWd6VA8i88WUvKPYkrt7huvSV/q11k2G/kzGS6PkX2VMew9zHoNW+WdFZWkeew+B87mNSbtwykVwryElRv3jKgb66bX3R0T5Nyl6M/Mub02w8PqKvZ1Gy5qw+1mFcE8clD4xqaKO8zkf35zbw3Dx8Y812KtdhIifz3d0+EVdbC/l4NTjgVDDOKsF8tKfc7XupKKzM1Ams2+yWVHq1UygiqsKRU0Hv8rRdGc1YeCytEHWThXC9ZO72lk6fve0fK/ZvkAj8zLSad2dkcOOqT1QyBmRFlJKZf+7tvxOmyRU364tXVvZAZlsQJ+xt7yGfVSUk6PCHd+sSgb0Lp1icG9aXXnXairX4+MamnByZ0fFLacXhS8ikkUgujnKuaGDKzUyV9TlJnetN7Je1wzn3QzB4ws82SboqyzTkXz6qkJYraYSmlk9hIfxRLWdI5c4U928bV3Xq8bzTnS565X9iSgzeumqt3PjJUUqy7hyYCaxPUJtPe4ZR+59GhgiVxg+xOpAKnyXy/f7yCsc2s6SRqyplnXI/J32rOtz7mU4dCKqxPEfY+NgdM1UvJm3Kx6QfHi175uemRYwXflZST3vbtAY0X+ajk35xMZTobhSadNxT6935xrm79/vHwA4d4Pn3VLPPe+J3kljNS4toH+0PbwexjFhutFLRfrSv3O17OSit9I6nA1Sgf3JPMSVKUazb7JdVIpEcdQRXWxwuqDzQ44XJq7WSP2Lpp64C2B3zvMzKjeDftTExr6eTZdPHCOb79s/Zm6bz5rVqeTkbftHWgKlMfAYSLOhJzNi9khiVxwv7GjkxOae9w4W3zW73RjH4y2zNt9a9+53DOqmNB4n5Bt9ojhlKS3i7pnvTvayXdmv75EUlrStj2Xb8H6O3tLSuwcvebrl2H2+Rdc87bfmRYvb1HTvzelWqV3/oznanj6u09VrD9k6tMd+xtUf94kxbOmdLNS5Ma70uoty96bLP1muQLimN/0vSen7Rp32i0go+Tkynt3r1H4+1O+5Pe67Mv2aTDo6bsBfky95Pmyn81Dad3bzumUhfx23l4XE1mAcesXaXOjpuYcvJ7DcYmUtP6zGXvu2bNmrKPE3bcIE1j/t9PG/P/fk7XO041PT4397O/ZO6U3nHqQE67IVX/e5z5LvWPNWlh25RuXjqps9oLPxSz2Z50NrVpyKed7WiazIkrrJ3dOdissO/87kRKf7Z1vz58bvBV/EMj7fL77EfpPJTqBweHtW2/5Pf3JfIx+sd0w33P6/KelP7xhVYlJpvU0Tyli09xmjIr+NuS/VnobJ7Sc8eb1Td+8jV7/MBx3XbemLpSLfJ7nee3TOkVp6ZOHFM6+bds20CLhlOFr938likt73Rl/50Lkv95rVSbEvV78Nr2Jn1dbUplfV6a5fTa9qMF3/FsYZ9hj/9tP0s0ye+zMpxKFwROv3dntZf/Xa5EvyRb1DhK7T9FcfKz3qaFzz4f2O4F9fE27xqRN/EquE3ZN+L03v/Yr78972SbEnS8OTalOU2m7pYp/dnSUY33JXw/Q7Vg0Zwp/c7px7R79zENj7Yp+zVKpnRiiv7Xd43kPLeTn1HvffjTMyWdKUljGu87UpF2YTpmu02p1H6VFpc4pPjEEpc4pOBY3v9sq3YncttVv35Qpdrfcl6TJ/vmyq+NffLFpD5zwVhgP/qOhH8f5ez2KR08Oul7zNRkbn/yiYP+j51vOn+HqnXek62qiSHn3JAk2cmlATol7U//PCDpjBK2+Vq5cmXJcfX29pa1XyWsODCgHUOFV3RWLOjKuQr114sm9HTecLglHaa/vuos36sgKyWtvaD8uGbzNYkax8e2DmjfaPSrYX3jTfrC0fnauLxbfxAy5SxzPyno2KaJqdI7WlNq0lQ9zSQr05xm06jPS985p6Xsz1w1P69Rjtu157B0tLCyZldXl1aurPz0uJWS7v//7N15eBxXmS/+79uLpJbUlmxZjmwcO3ZwNpOEOA7ZEwMBZ4+HjC9cGLgZmFySCcwMdza4Y3bNL8Bw7/yAMMCEJTBhGUwGh8SJHTY7cYhDbEGcBOIosSPHi2xZslstqSX1cu4f1SVVV1dVV+/V3d/P8+ixXOrldHf1qVNvvec9y+I5p16V+3s8EI2bvkt+7J1sybpiVKn+xC5D5ZvtMdy0ZSRjSXkfgG++uRsrDFMR1vui2DKUnQm4/uwu7PhN7gzBcX8bVqzonikifXIqhc5m38yUB/9vDsEmMaPkDscD0BISCu90EvBhy5APW4ZmP8uxpB9D08DKuX6Ew01Ytmy2OLd5XzA7OKn1rZ+/Ooy9FplH/3pGDGvOe33GffRj2e3bRyyzH966pG0mm6m3L4ojh4ov6ljt/gTQjm9J0zEoCcEvY3PxrjfZZ9Z9vidu+d5+/uoFAGD7t/f+agRHpuwzUfTP7h9CwwW/N03ROMInohibSCLc6p/ZdwqRz2fk9J4U8vxW+/rz4004r6sJo3GVsf/ZjfG0AHHuccTTkSA+8nLbzGMuPxy1fLxp5cN0Uvt+fv5AEzad3YWfDUSQhMuKzx6xpN2PT66ag+8fjOOx12KIOPSX5oCXvo/ee97s96MWxrLFqrXzHi+2A/BOW4ppR6kXdnFqy9jLQwCyM/31cZCuFP1voe+Jf9fh7FU2APj9fqw57/W24+hly6zbfMeSGHwt7XjkNYt+1efHFw53zTyGf9cR5Brw+QB8+MJTMsahblVqf6108ekxACEAEQDt6f+73VYX8kqvFlP50Tpee9NNQW63SyAbbTs8aVsnI/N2zoMpc70PcqctYL941uL22p0GVY1VULyw1GW1VxoyckprXtwewIKQD4OGeeMLQj4sbs885H26z3ra1af7xpHKKv+crafVjyePZAahRuNJ3LBlBAtafLCZ0VYWfih0Nvsdawz5AFy1sAlPHJnKK6tAQVvC+vkTMdfFuXWDE0nbmlJ6lpAVp6Vl62kpdF2h6fe56nXpqydGplLoaPbNrJ543EUtmmJS3qv5GZW6hpldzYyDE7PjBv21uVly3clUCtgxqJ18/fpQDH+ytCnnffQ+uBanZx8YS+KDT4wW/H55fVoGUblUuo91O93Zqv+9dnEQN20Zzrp4VmoXdTdZBnEu6m6aaZvVWNVpjHL3xR3YM3I8q1bqyHTmwh3ndPixPcdxNQXgnufHy/LaS6XSgaHdAK4A8BMA5wPYmcc2Tyg2Out2LnRvX9SyYK/Xi1a5ZV7K8HfD8fRJnFaQ22rVqnyXQAaQLv6ce8SRK3BUfwvOl8/CkGBxewDPDmlF2OzoxTJrUblq/hS67HSleKkIdq6iu4OmYoKDsez+064W0aGxJNpyHB17Qj6MTaewzpSZpDtW4SKwc1u04qxOK52lAOyLJuEThaQq7ELD/mhyZoDnhv6dsBqQ9Q/m2K9tlpb1UoCyVIrpU4zvrfH9NC8IEInPrp4Yc5HKVkx/Vu3PyCmQnm9f6uai1P5oEtc8PIRQIPeS624dnwLufcldsGfzQOHBqGorpt3hYP1eMCVyUuk+Np/EBmP/a16BdTRuvUpsKVgFcU5p0f698dEhx/7eboyyNBzE5uvm2y7Iob/nbU3uzml2HvN2VmelA0PfBfCIiFwJ4BwAT0ObMuZmW8XYDRpKFZ11U8TQSydgpeZmNTHjqlX657H3ZNzyGr7TEshUWYtbBZuv78ZfPXHCIuE0k10mUS0oR2HVQpedrmRwqBpFsO3640KL7hp1NvssM2ySAEZzLLc8GEvh0YPeOMDryzhfvjCEb1w5Bx/+TdS2X9SKQBcXlHVbUL8tAOwbjeP27SO47YwQ7nsplvE5HopJ1jRfY0aSVRHJSzcNYcrmtdXy8bEUfYqbY6sxeOpEf+7pQfv6Rk68OoYpZBw37XKlP+1CVHVeXw3v+kWp5XEE1a5GvFBXaCam21ViS9VGPYgzOJFEe0Dw3Il4RhZRMeft1zx8zDKR4NVoAs1+d0FqpwvmXlCRwJBSak363wEReRu0bKBPKKWSANxuqwinQUMlo7P1uAqRzu0UhEdem8LZPzqMhEKdLfteX9oCgnPmBnBaODBzkNjpsKyubqyGA3rlWAWl0GWni+l78h3cVHqlIaf+uJA+Uv+bXhPoeDmqQLvQGhDEEipnLmMQwJmdPrxwMpV1Wx+0DCCfACs7fbj792OY88I49gxPVy1YfkoLcGF3M4YmUxnLtu4+nsB/7Y9lFK7fNTSNUwMB2/3abtDr9Npq+fi4NBycmfY1EktgXigwM+3LLbfH1sdem7Sd5tjkA245LTTTFxRawLdUYxg308zzkc847oFXoo5BVqqMc+f6MRhTlidk+jii1PsJkZ1yTeHKdzxWjfPEQkoauF0ltlSMbbx9+0jW7Jtixs52y9ofjaVw8YLc035rQaUzhqCUOgzgx4VsqwSnQcP+qHWY71Wb7cWoxyXo9U5v62uTru9zJMYBmVd1BAUdNnOF3axcVssncRlKtIuWIgMmF6dpJkDuwU2pa3fk4tQfO/WRu45NWhYuvnZxMCutuRre0OHDrmH7z1V3+cImdIf8eP5k9mvRhycpBTx7IgWropCVFvQJ7r64Ax97OpK18pq5T9gfTSISsO4DBtMD43zUw/HxQ09G0tlYgrGx2Wlfbr9fbuvwRRxqoZ3fVZpaZqXPgNKmmRd7Aub2KvsDr0TxgcdzF6Cn8vEL8M+r23DHGzrx7l8ct6wd8sJIHO/+xXHDsUzbTx45EMNZnQEsnxNkkIhKKldwuZBsokKCTbVynmiXmd3RrGUuW71f+Soks7wQ3S1iuaz9ghZxXV+u3ePTXyseGPI6p53o8Lj13w7ZbC9GpU/ASiWfaXhU2yJxlVGzwrhvLgj5cHjC/mqAFw9e+SjHCUsxGTBu5DPNxOnEsJJFsJ36Y2OGhbmw7rWbj1veb8MzYwj6xfLAnbvUdOn8dthdP5hUhRXdN2v3a8uQl9vBCZVXEVy7Mjf68c486LXiB/CO5aGaOD46KUVG8pwSDDhfjSZx+/bCMi7Mx/8PntWCz/xuAlMJheaAYMMFbUVnQBWbKZmrn9VfwwMWgWWqrKQCNuwax7ldzbZTxkamlWXAyJitWOuF6clbnMYlhWYTFdLX1cp5olXtQ336u9379a9nCNyuv1XqzHIny+cEsft4djLIsjlB3PeSuzpv53Z6O/Ti7dZVgdNO9PyI9WDXTRFHI7cpr6UsnlgJVl/OpwYncV5XE54Ziucs8Ey1yergde9Vnbh5y0hWtYU3dPpw9rxmT+yvxSjHCUuuqz/FXhnKZxUpr3DqjzMzLDIL69r1NUOTKbTYjAe8mJtYqqy6Mi6Wl2Xb4SkMu5z62xIAupr9lvu1edC7+3jcckpPCsDTx6ZxcCxR031Kriubbo75difPLX4gnnRX/WZoMoWN+2Izx+6jEXdTc6yO/xv3zf59IqHwwSdG0dMacF1wtBw1NG47I4QH9sWyCsb/8cQ0/vvPj2PX8WlOXfcQvRbJkiJWMa31wvTkLU7jkkLHhsX2deXssYo937x8YQgPrp2XcRFPn2lw+/YRy/fr6wcCWHOeu8cvNLO8EE6Pd9eOk64ew22R6mphYMjE6UPXljTPPuEI+Nx/yKXINPDqUr1ulnSl+rR5IJZxlXlxewDzm4Gjho/+lGbg+9fMr+mTN105TlicMmAAFH1lyG3mSXvAO2muVqm5AdG2Ow0GfDbpPz4pbgWcSvKnXyeArPo8+SrTVH5L+VwA6AwobHTYr51WNtEpaMWwy7XKSaXkCoI6HfP1gfvjR6yPtZMFdEuzx2534xQ3ged8C46Wo4bGPc+PW64i+PyJJJ4/4Z2gOM06VIJ0Ry9d8KDaVkhwINf+V0hfl++5oLmUgFJANKEcgz2lOt+8fGHIst+3G5cOTftcB6RyZZaXMqvK6fHcTn9/cnC64KzcSmiowJCbTB2nD331/KDlKjSr51c2Nbray8DaKcWUB6pNE0lg475YRqH2o6avytEp4JqHh7BmUYtnO0S3ynHCYpUB84HtJyE4gfGENk/bqp5TsW02kwrFhdwc9K1ScxMKM6tbWdFWogCsEjzbA8CUx1eE0CWVdhIr4q5mVy06EXc/NdF41fG1sez6TAkFrP/FCayaP+aZLNp8OJ1s5LoiWolp2rnGGK7rG1lEKe36gg2rwnjiyBQGDQU/e0K+oqYh7zqee2EE8pYktOCvH4Wv+VY3NQ2paoz91NmdAZzVEcBYQrkKDuTa/6z6/7aAYH80YRtEyOdcMFcpAeMKuIU+RyHs3q+XxwWXbRrCuGEAaBeQyvWel7r8gd3juZ3+Homrmazczdd3e26c0jCBoXwydew+9M9d0oHnHhnKKNa6uFXwuUs6XLejFJkG1V4G1m4Ql2+xUKo/+6NJ3LRlGCM2l6iHJlVGAMlrHaJb5Sj6Z3UANp4QjcaTuGHLCFoEWNDmzztI5PagVYkpn26vQjn1dXb1VMJBwbTNSzw57c0pY3a0k1jvt9gPYF6L5D0FJ5bKLwqpX3Vccv9hjFrMj5tIKOwY1CKCtdbHOK106PQ9cDtF1Ehf0S5fTmMMt8d/veCozqkvODiWyFoF5lgslfe0QX11samEqtJi8lQKSWhFXicTCqMWAf7uZmCuP4n+CX9GrxkwZF8SFcKqn1oW9mcdYwodGxr7//2jcfzxZALjCYVdQ/H0T37jI7Ncxwk92PMPizK3l/t8025cGkn4YB772AWkql2E2y5gGLZY4MXo4ITCR3dG8MO3za9IO91qmMBQKaKeS8NBbL6+eyabqD0gEAHu2nESC1v9uO2M0MyVbLsrlqXINChltkK+S3wOROO4wRQce/xwDKvmN+PYZBItPoClhBrbARdp317IcCtGOZard3vFfVJlT50pJBvSrmbLUZvlON1w25+47Y+dgj929VSeOjplW2i59romVRPZQq9r9+PiBU2WK8E5mcozMKSzW+XEqBb7GP2iVH//MFasWDKz3emYX0imbqHfA31am9WFoWsXB3N+/nrBUSOnvuDpY9NZbU3B3XQ0vZ17hqexN8JwUL04PqnQ2WQ9V/iiBc1ITY7hpYnM74ueZVqr00yp+tyOWfKZumQeL+nBy4GxFMZNgU+rVc/+MGKd/aiXAzD21XtP5s6UtKpnt/eEdW1dn90ALE/G92vb4amcFyatAlK53vNy1uTNFTDUn9tutTIvZrA2TGCoVFFPfeBmtTOYCxo+9GoMK+dlLpdZishmqaKjhdQ7+ujOSFb08+gkLKfYAYVfmaT6V+tz/u1O4gqVb8ZdQgHveGwEb1nUjOdOxHFwPIV8siHf+tBRy9UVRmKFrUqUGTTW2mGXKuu2P7Ybe+hz463YjGNq0kXdTdhpnpPpQUfHkngyNYWOABAx7FI+AK0BbYUgq0+rxafyGrTpt+1sEryG3LlUtdbH2AVWc00zK6UmH/DWjD5l9vluOyNkm93z6b5xy8fzi3ai0hYUrAj7cffvx7DwpZirbKhjNiu+DuVYCXYgGscNjx7PaD/VhxS0lcisROMKE1PWNT9rrS+oFV5cCKcc8jmHdDN1yer8K9dS569GE676tsPj8YJWgu5p9eNQTPARF/frL2LqstU+c+/V83Djo0MYGnQewJlXjzQ/htVzmZMZ3EzhKtVFTn1f2Hb4sE1Gtfeu/DVMYKjUNUGsdgbz13QyZb1cZrGZBqUqplVIFlW+0c0UgAUtPhyfTDFARBlqfc5/vtl2ubid6mU0lbIOyrrJlrBbdnPMVC/K7WuyChrbpcra9ccvnsycT28X/BlLF0ysZ4vbfLj74g6c/5Nj1W5KTlMADk9k9/ApAGMONZ3Gk8Blm45lXB3VV8MajWcWxbQa6AYEaPEBKRHL7Lda6mNyXaixO+ZbFWgvRpMA7U0+fOPKTtz3UixjnOI0ZjhpU+HcB2BFZwB/PJHA9qOz4wc3ywnbjTZyxX4/9nSEQaEG1NPqRzSpXSCx+huVllcXwikHt2MWt6z60lx9eN/xOC584FjO2z13IpX3FGP9QsM/bh91db/xeH4XdXSFLC1vbqPlCthHp3Du3GBWMe18xqXGNpb6IudF3U145LXssfpF3U2Or7kaGiYwVOo5iPmmb1tFEIvJNChFMa3CsqjyH32enE4h6KvsyjjkbZWc/1sOpVhd0Mx88ucX4PEj2VMp3No/6hzEzXVCme9UHLugsdV2u+fWl8p2c9J42xmholfr8qol7X58clVbybNBvCYFX1bKvHkly4cGYlg5N4ChSZU1TTWhgOuWhiwLMNdaH+P2yqOZVYH2YuiBYX2KuPGQ7zRmsJveF1fArqHsPsDNcsIPD8QQs3jKXKv97jxaR2mD5IpeRyg+NIK9ky0Z+9PiNh/GplO48dGhus5qqTSvLoRTDnYX7sxjFjeBkd6+KLa+Npl3G9yOdVLQZrBYmdcsWDk3ODMd31w8e8gm486sNSAFBQXzXVq+LQCc3RnAsjnBmdVotx2ezMq+OTiewsHx2XGD3pZ8xqW6UlzkNAei7764A3tGMjO99It/XtMwgaFS1wQp5Gq1ef5mrkyDcqdo2r2Gp45O47yNg5bFbVfODWLbkfwGXdMpYF6TYMom/ZcaR3eL1MWqZOUaEJlP/p48EsOdOyIYnkxmnUDncijHdAs3J5T5pd/bPVj29lzP7TxQSK/U8fjJugwKAVoNqdsfH2WWJbSl1q0y23TlWJK2Ggqd7l6u1UBnp4jPXjE9r8v66ubAWBLhgIJ15Rd7uT47EetHlBxLJ46XMlJGNSGhtNpT3b4mnNURwNmdAUTjswVgjZm1xhWYGmEaVLnY9T2PvTbp6eW4C5FZCyc7MOFm/FfI9K5C2Y0d2oM+PHRdt+39uputM+6MAgKc2eHHtsHM4IpVHSTzdyvX0vIbLmjDh38TxWQihZaAD1++LIxbT9eyhK55eMj1Ahd6W+yOSCemUln7qN7mnx+ynr5vFUxym3SyNBzE5uvm18QYpWECQ0Bpa4IUMu1DL9zoJtMgV4pmKYJGG1aF8dTgZFZkNGFR3FYX8hdWLPSSU6zT6KhxWK3gUKv2R61PVF+12e7E6busr8IEzAaJjownYbEgU5ZcGXpuTijzSb/PJ1XWzXObTxrNK3XUOwaF3CnXkrSVVuh090IuUgUk97QFs4MTCqeHU1gW9mdN5zNmcvkFaPUDbrrCXJ/dsnbBCyezG7q83Xkc0hoAppg01HAOjCVxAH5gdGpmvNHbF80a4+6PJvGxpyP448lEQ0yDKhe7vkdfjrve3k+9n7KrL+hyCwAAIABJREFUhZMriJ9repdf3GcFFWo4lsSNjw5hTjpjyDz16o4liayMu1NaAJ/4MJFQM7Xi+oatO/hthyfx1oeO4g8nEhnZnk8dncLm6+bb7jMDY0lcsWkQL5xIpkM52vTwDz4xip7WAD7TN5r3qqePvTaJtqD1xYWEyiyZAMBF0C77cfK5KFUrYxR3OWOURd8Z1i8P4cqeJly3uBk9Ifu3U09zdco0MHK6nR402rgvhh2D09i4L4Z1W4cxEM3/ZCmesv+i6VdgjOxqfnS32A/UAgJc1dNQMciGkE+IcEm7H/dc3lE3AwTzEsq6fFf0yue7rAWJerDr1gVYFs59Mpgrhut2Prdbd1/cgcVtmX2gXaqsm5NZ8wmx1Uod1NhqbbqYkw2rwlnfazevz+p+Rlb9QKEJNXtOxDPGPUva/VmPlVTAtUtCaM4xunS7hLOVJTmOI5csaHZ+cqp7+njZ7iLEMxYXdo1j8YFoHLdvH8GNjw7h9u0jBY2v612uvsfq3KZcKvl5FRrEt9sXfVBYGPKhswLD4/EksGNwGo+8NoVHD05ljTtfF1K45/IOLGn3oyMoWNLux0fObUPQL0gqhaOxFLYfjWPU5urk0KTC7uOJrCnAB8dT+NjTEct9Rr+48PxMUGiWvsjK08fyH/xF4gqHJ1KO+U/6PuqmJpNdPSA94PPQdd0ztfhqud/g2XoRzNE//cq/VZqhvlym23Rxp9uVahrLR3dGcDTHNNeIKe3AbvnooM8+iVwAfHKX9YolVLvymTZwYCyJDz0Zwaa1gboIDnW3CA6MZW9f4BAgtVLId9l8heLlSAJHLAJSuYra5ZrPXUhRfD1VNtd03VwZl4vbfDNFBt/+0DHUwMJcVCFL2v1Y2u73dCp2IQqd7m7uD8y1I247I4T7XopZjkvyNZHIHPfc+OhQVt0nQBuntAWsp4/7BXjHspCr12a3KuHOo9OOU1U+d0kH+thvNLzBdBauNesRzOBEsqGKKhfD2Pc89tokIhbBgkqsBlfpz6vQmrV2+2IKYjmGy8dF3UEcjaUs+2M39HHne+YKPvJsZOZxIvEkPvpMac7fnhmaxtJwEPdc3oE7d0QQmUohrmC5cIRRruz3Ra0+JJMp2/4+CcAngF0exOBEdkDKzKkekH7uvz+awB9PJDKmMtdiv8HAUAm5STN0G2m2C8CEg1JwLQIzNyuMdZgu+9kN1KxWpNEllBcX5KNi5XsYq6eihHYrei2bk1/nX+h32XhyNhCNY+3m4xg0DCx6QrmL2pW1LkuOL7x5itjzIwlMGneodEfzV0+c4Mkdzain6ahWCp3unitF/fKFIVdLAefSZhqXOI1nwkGxnFq6dnGz62PAsUnrfnBkOvdUlWAgc8WLkB9YOTeAXQ71qqi+PHV0Gh02Y+nl7YIhiwujPa3+hiqqXCy977l9+wg2WhQ8rsRqcJX+vAodOxVSgsSt08IBfOrCEG7ZOlJwRui2w1P45YFmjCTKFcwTDETj+OATJ0u6auThiRR6Qj5ctziInx+asnz9DpNjMDCWxEmbY027L4XrTmtzrAXsNAWtFvsNTiUrA6fBktt08fFp6y/NM8emsPek9cAm/w7YufcICPC1KzJPLu2mkhX+LNRIKnH1qBIKnfZhVmhKsllAMr9lJ6dSeP+2kZyprMYUWH3lo0IZp8XtHvXnnOKqP/eyOcHMoBC0eia9fVHsbIBaQpSbAFi/PIQNF7Thpi3DWHL/YZy3cRBPHrFeeYWyFVKLyOySBU0ZUzbGplNZ00f14vBKIWt6fb6rsOTKcLKbqtLbF8068YgltcB9oLAyiVSDEgoYtln0ZO9oMusEyAet5EOpLr42klKNiQpRjc+rkLGTni2zpL20wTIB8McT07jvpRi+ceUcLGn3o7WAs/uhyRRGEuULC0SmUrjwgWMlDQrpBmMpiABzc81htnBgLIlRm+sFUzlOYN1MQSuk9mg1MWOohGZWGxuNoy2AjHoYegdpTKMbiSUwLxTIqL2iP8aTx6xPiIamAKtcjUI6YLtisQEBFrX5LVclC3NURUUI21y9qzWlWuWw0JRkI6vimpMpbSWn3ccTM6sJjcZVWVdeKfSqndPKJjbxcQBaBoDVUtZUf/zpGn03bRmZOfqNxpO4acsIHrp2XtZxirJZ9TWLWwXndTXhWCyJ508kYLxo6kPmSGNxmw93rWzLujq6uFVw/anNOBZL4oUTmcXhT2kBrj+1GdG4yrqqrhfTPzmVQmezz3K80dkkOJDjdVmd/O0esk4z3D00BYdZ79RATlokz6UA3PP8eMku2DSSaq4MWSuf10A0jg89GSl4upcdBeD5E0k8fyKGJ45MYesN87E0HJzpYyNTKTT5FIanqruoRbkXpn5maBrndASw3XylsQhx5cPGfTE8dXQK584NZhXrdrOQSr61R6uNgaESsUonawsIzpkbwGnhwMxOlNkxCMYMtVcAN1XRMxWz/PfdF3dgz8jxjOjt4jYfNl833/axcqwSS+ToULR+loopxSqHpRhM5TowHZxQODiRvVRvqQdshV61c1rZxM6iVh/uvaoTN28dqdsl62mWX4D3/fpE1qA2BeCWrSP4E5c1axqZU18zEI3jhkeGMgLMc5uAJr8P0ekk5oUC+NoVHbjvpVjW+OTghMKlPT4sALKmaek1DM3LIz95JJYx5WE0br0K6kkXZxJWJ3/7o9YD8f3RFOY2C0ZyXQamhrXreBy/uHF+0RdsGpHTlNaZC+fHm7H8cGmXsi/FBbZKcJNdUqzBWAp//eRJbLp2ts9VAEbj1kGhziaBD9r03GryAVg514/nTji/PyEB2pt9GLII/gxPKjw5VZ4s84PjKRwczx5Hu8nEzbf2aLUxMFQiVl/48YTCq9EkTgsHHG9nTIfOt9M4q7Pw5e/yKRars6tET+TGsxZLDze6YpewzHeKiJssHn0QdyRdF83NIM5vU4DMZ1eYLC3fefd+Ae69qhOXLwzhZ2vn4c4dERybSGZNR6P60ewDhm1O5s3LzjI4ZM+ur7HKOhyeBrRTCe0C1gcfP4GeNush4+BEEi+etB6Qb3ltCkvuP5yRFXTnjkhWHQh9FdQ962cDQ3ZF/nV2J392PY4CcHF3Ex49yMJlZC2ZUlXNfqlHmRfO/dg9Wtr+ulY+LzfZJaXw5OB0VvDdTmRaIeSBmSApAE1+QbM4T98Sv2Blpx/bBrMHfCk41xIqJX0c7Wb8mm/t0WpjYKhE7L7wQ5MpLQ1tcBKbr+92vKpeyP5cbKpkvlkPdiehS9r9GJtOVT3qTNRoCilo6JTFU+gKH/02z2+3XedmZZNmH9DiF7QFBSvCftz9+zEsfCmGDavC2LO+Bz3fO+T4HFTbAn7JucZ6LRZ5NCvnVXUnbk5YDk4oJJV9fcMXTyZgFZJJQbugNBpP4uatI/jZ2nk4abPMjHkV1HDQul5EZ1DwtlPtM6X9AstMQr9oK5Y9Z8qOItK1pE+Si71gQ7MqURy6mp+X+UKavhKk+cKa3aJCfigEfJJz9S234ukgu5uSsAq5VwWrFKsFXcxeP8ePkVj+NXv8Mlt+oFRZ5oMTyYzx66vRBP5gWpXMi5lruTAwVCK5rtofnFD46M5IQXNhu1sEK+cG8fiR6YxUwEC67kIx8h2I2qVsblrbhY89HbGsWUSkq/51ifpjPDC9eGwM+yYDGQcmK079TaGDuIhNQSC77VZZSQAsVza5+TRtqtC6rcPYfnQ2M0EPWNksKEF1otknCEIhV5J4LReHLfdVdbvn7O2L2i5oYTaV0o73VlM2xqZTOTNxkgq4/fGT6Gz2YTSe/VmZV0Hda5OFFAogqy8y9icr5wj2RLL7wNeFtP7tQytb8ZnfTXjmhIi8Y1EhVXvJkdeKeZcyAG91Ie2n+2MZQRm9H7dLnk5CkCxxxvNInQ6KzuwM4oF9+QeGzun044l1PTOfvZ7larXAQbsfcFMGSh9Hm1cJ9nrmWi4MDJWIm6v2buYuPzU4mXEla3GrYPP13ejti2bND00o4L6XYgUX3ixkIOqUsslpZpTLmxawyykHY+ZfU8/Cme9ne0Dw3Il4Rh2xXFcwCh3E2Y1DrLbbZSXdc3mHbf+Yaxou1a/XtfnQe1E7PvD4qOPtvFZsNB+VXnI51zK7VvwC2+O/20ycY7EUHlw7L2uag9UqqOM24/8J03ar19LuA8ZMg6YDE8CBfTFs3JfzpVKDqrVpH7XAS8WhSx2At+q3zfFmvR8vZFVno+4WH6YSKdsVtIzMfWQx/ABKEWbyQ8sgLfRd0MeCVhcPc4mkrzEYgzi3bx+xfKx5IT/GXESGrl2cvb/UQ6YhQ+MlogdM1i8POSyHqjJud2FHEuuXhzI7JHN15/T/yxFxL/REy7xMI6B9wdxedaTG1N0i+PerarvDrAXG7+cP3zYfm6+bj/XLQ7iypym7v7FQ6CDO7hGbLLbZ9T33vRSb6R/N7fXaVUeqnGVzgrj19DC+ddUctAa0Ypnmw2wtpmwbVXr/tiuE2t0itlkTF3U32S7TvDQcxObru2e+u3aDS78Aly8M4cG187Ck3Y+OoGBJuz+r8DQAdNosPTyZVLh9+wgGonHb12IOChEZdTVL1ZZXbzTVXMrerNQXmNzWDRpMZ0bnMq9Z0G1TrHjNomY8sW4BTmnO/Xyl7P7mN2urS4aLvK77juUhPHztPPjzmDrQFhBc1B3MGAuGCognWhWAttsvv3ZFR9Z2K5/uG8+/ITWAl+9LSB8wjcePW06puqi7KeN25ro+vX3RjCv7gFYJvbcvWpaIeykGooVcdaTGYrVynpuliqk08r2CUegKHwva/JbLsHa3ZfdRTn2PXXu9dNWRymNRqw/JZApHDYdP47536+lh3Hq69ns9pGwbVXr/3h+1vpBzWjiAb149Fzc8mr1i6d0Xd1jeR2f87t7yyLGMaZ+6S7q1z+jyhaGMQtNWvnZFh2UB1alUZsHxShV1pfqxfI62n9dTH+JVxpkGbhe6KZdSB+DdLv6h71+5Zpa0B3146NqurPMq/Ti4NBzEYzctQG9fFFsPxFxlDxXr6BTQFvTh2iWhgrJ1gMz264uGRKZSaAtK1jG/LSBY3pLAWQus95N7Lp9jmT3c1SyITCvL2kpWmYBOM2A2rQ3M7K/PjvotH9NcE69eMDBUBnbLwOcaVDl1WPdc0Vny5RhLMRB1uuoYCvgsTxSpsZhXznO7VDFVR6ErfFidxFlNDwEK63ucAlY/3RcD8xW9qbtFLOfxm81rFvzhnQtdB3zqIWXbqNJLLh+LWQ9qj8ZSBa1YavblK+fi7Q8dyxjwn9KsbXdLzyy6c0cEh8cSSJjyxPQr/fmuzEh0WjhQd32Il+W70E25lDoAb9VvB0xrJRiDIvrY6tEDMYxZDFoWtEjOMZj+Xg5E41l9rBNzu8yWtGuFnceS2dk1duehZj4A4eDsQiEpkaz2my8KWB3zpwdftd1P9ItDH/5NFFMJheaA4CuXaReNrJIVjMdRq9qWVn2AcX+99fdhy3NZc028esHAUBkYB1X5nFg5dVjlWI6xFANRu2DWWZ1B3HNFZ8myiVoDgqAgo7PZfTzuWDzylGbA7/fhWCzlqjp/NfjgnPK5pN2P4xMJTKQqU7ZZAIQCUtKinOYDrtuliql6ChkwG0/iRmIJzAsFbDPBCul7nPrARe3W2Uql0BoQxBKq4HnxXnDuXD/OmtuEC7t86aK72jLkpWY1IN60tguXbhrK2adcsiAzo7bRVPqqut1S8HrKfbEncsYr28WMWfSTiLc+cAC7R7PHSG5PWKjxdLf4sHp+MO86e1S/Sh2AtxqX6KuSOQV17Orb6Jktbo6D5j52YCxpnbXd4sOaRc0z7bJbPWvT2i784/ZD2DKU3Uebz0N/eWgSIxbryl97ajN+cM185zfN4nWYX2v/oPN9jNnD5seyGycWuuJuPhc96wEDQ2VSyOA2V4dV6gFzKQai+QSzwkGBUsBYQqE9IBABonGFnlb/zAnLZCIFBck4CdM7LHO7zJkngHaqc+68AM7sDDp2BkZ6ge9dxyYt0xMv7g6gye9DdDqJZ0eSUAB8olWuN6Zx+qEthzgv5Mc7lwXx1T9OYSqhEPABb5wfQJPPl3WQ0KPX+0fj+OPJREaxzVwdtZGkf1oMkXMAeOCV6ExUPegHzp+nvRafUthxLJ6xbGNAgAfXzsPi9kDW+9UWAE5rSeKcBe2Gk8vcp8pWB1y3SxVT7dFP4vr7+7FixQrb2xUa6LbrA60O3ALt5Hd4MoVkjiCIADizw4/XxlOWg6W7dpzEjsHprPs1+4AWv6DDMB3SzfTaz13Uhjve0JmxTZ9eaZderX/Hgz5gTlNmFk5bADi7M4Blc4K4dnEQn+4bR2QqldEu3R1v6ER/fz9+OdWNf9o1jqTSAtTtfkB82mvR+6/JhMoKXPsAXLWwCUmFjD7daUD8lcvCjoWj3WTUNoJKXlVfPidouTxwKYvvlnLM0t2cgnaUzWQ31tgzPG1bCLsrCDQHfRiPKzT7AaUUplPavv/JVW3YcjBue+LjxuI2H86dG8Su43EMTWYf11oDAj8UxhOZF4a6gsCvblmA9/5qBHtG3OdA+gBc2B2ETxSePla63Mlz5/oxr8mH/mgS43GFqZSyXExgjj+FtqYAjthkoZXSknY/lrb74YfC3kgSEwmF1oAgpVI4Ojl7O+O4sd6mnVLhyhGAt+rncmW/lypAZV4Ryypbxnj+pLfL7jtxx5IE9k625DwPHYjGC5puXAl2x51CF3gwXvS0G1fVEwaGPKQcWUFunrOYgWgpg1n6CUtTz2mu3gO3X1bz+2oOSumPrz/Hh38TxWQihZaALyPIYpZrsPFPq3O/ZjfLHFp11PrAUz8hs3uP7KLqQOaJqPm9s9oPjamdd7yhEwPRONZuPo5Bw2Cwu0Wwen6TY7vcLlVM9a2UJ41OfcG2PS/jQy+2ZQxgupqA5oB2YmgO6lh9B+0C4DefFsp6Deb+JhKL44VRhaRS8Ivgn1dnB4X015ArvdocULbre+y+80Z3vKHTsh06vf9y6iesWP3NnPqtB8sTU1NVrTfRyCo9da1Ybk9YdMbviDmAmWt/u/V0WJ74GM1rFozHFRIp2F78yXWiZvc9PrMzaBkYMl/5tzqxNV4MCviAVj+QQmbA1zz9AnD3PR+IxnGDaeW5xa2Ce86ewrJlPVnvV8gPrJyrBaz1NltdBHPL7iKh3ja7k/1GzUIka16Y1lauAJXbc0i778TrQsrVYxQ6M6aaiqkv5aYmXr0QpbybIC8i3wJwDoDNSqlefXskEimq0bmuZleKV9oBFNeWUl6N8cp74pV2AMgrWFbudpjfk0I+e6tMLz1byW0E3tyWjo6OoubFFNOneG1f8UJbvNIOoDTfHzdX4ty0w0vviRfa4uV2FNOn1MoYxU3/7aXPqNLHQavg0rHoRF4ncYUcI932N9X4bOzrgaxw/VqNt2sPSNZUL6O2gOCcuQGcFg64eu+8tL82Yp9SK+0AvNMWr7QD8E5bytEOu+l765dnX+ArZzsKVerzHjuezRgSkXcA8CulLhWRb4vICqVUf7XbRdl4Nab8vPoeF1uLphHSMqn6iv3+VCObk6jcvHpcsVPp9lrWvujvzyvLoJA2e7m/caoH4va1ljK7i4jIjVrLkq0WzwaGAKwB8OP0748BuAIAA0NEdaCR0jKpPtTaSTQR1a5G6m8a6bUSUXV4OeDuJZ6dSpaeRvZlpdSzIvJ2AKuUUp8DMlMq+/sZKyJqdKtXry7ZVDL2KURUTJ/C/oSIzNinEFGpFHveY8fLGUNjAPSUgnZoCy9kKWTun1fmDHqlHYB32sJ2ZPNKW7zSDqC8bcn3cRvlfanFdgDeaYtX2gF4py2N0I5aHqMA3mkL25HNK23xSjsA77SFfYq32wF4py1eaQfgnbawHdkq1RYvLwO0G9r0MQA4H8Cr1WsKEREREREREVH98XLG0CYAT4jIIgDXAbikyu0hIiIiIiIiIqorns0YUkqNQitAvRPAm5VSkeq2iIiIiIiIiIiovng5YwhKqROYXZmMiIiIiIiIiIhKyLMZQ0REREREREREVF4MDBERERERERERNSgGhoiIiIiIiIiIGhQDQ0REREREREREDUqUUtVuQ94ikUjtNZqIyq6jo0MKuR/7FCKyUkifwv6EiOywTyGiUin0vMcOM4aIiIiIiIiIiBoUA0NERERERERERA2qJqeSERERERERERFR8ZgxRERERERERETUoBgYIiIiIiIiIiJqUAwMERERERERERE1KAaGiIiIiIiIiIgaFANDREREREREREQNioEhIiIiIiIiIqIGxcAQEREREREREVGDYmCIiIiIiIiIiKhBMTBERERERERERNSgGBiimiUinxKRT1W7HURUH9inEFEpsU8holJhf0LlxsAQORKRj4tIVx63nxYRx/1KRP7J8Pv5IvL+9O93iMiNhbeWykFEfikiK0zbPici73O4T7OI/NDw/8+KyG1lbCbVCPYplO4flIiEDNvWiMgvbW5/lojsEJFg+v9hEdlXqfaSt7FPIRH5UxH5uGnb/eaxi+nvHKdQFvYnZEVEWkXkJhEJm7afKiIvpn8P2Ny3ZuItNdPQchKR20QkJiKDhp9TDX+/r1EOFukDpaR/PxXA/wIQMd2myWEnn1JKpXI8zXsNv/cDeGP6y/TnAHYU1nJ7hs/3aPrni/pr9CIR+ZKIvNMD7bhaRC4GEAdwioj8LxH5TxHZDuBdAD4qIttF5JuG+7xbRFal77NCRIIi4gcwDSCRvo1lx1lP2KfMYp9SfV7pUwDts4bWPyilVMzwpySAgIj4LPqImwEcUkrF0/8fh9anNAz2KbPYp1Sfx/qUOQD+PwB/LiK7RORpETkPwDsBfEe0oPJvDbdv+HEK+5NZ7E+qz2P9yUIROVdEbhSRvxaRe0VkF4BnAdwOYLXpLlPpHwB4TET2pPuh4yKyX0T6APyhgi+hKHXd8eXpQaXUuyr9pCLSCeA2pdT/X+nntvEzAPNFRAFYCm0AvtPUnzQDeD+AZ0TkGwAuNvytVUR+b/j/s0qp/2F6jglAuwoM4H4AYwCOAHgZwC9F5Bml1B0lfE1A+vMVkfkAHgfwBIAHS/wcrjl97kqpv65Ck6ycBHAvgBMA/gLAbgD/CKAdwB0A9gH4efp2umEAPwGwKv3/OwGsB7AYwKSI/AWAZwD8fQXaX23sUzTsUyqgRvoUAPgOgFMBiIhsM2zvALAM2vv4AwBfNfztAwA+ICK3AOhSSn3buP+ISMgUZKpX7FM07FMqoBb6FNEyO34C4J+hBXYuBPBZaGOTNwF4M4AUgK8b7sZxiob9iYb9SQXUQn+S9l4AKwEcADAfwAIA1yilTtrcPgVAAYBS6i0AkA40DwC4USn1QtlbXEIMDFVfJ4C/AVDyDlJEHkRm5wUA31ZK/W+7+yil1qbv2wUtOvpmpVS/w9MsAdCrlPpJ+n4nlVJvTP/+RgBfMrRnLbQD7ZkishnAXymlVqf/tkspdamIrAHw7vxeqXtKqeMi8gsAZ5brOVwq2+duJx21XmTa/Gml1Nds7nIU2mDqAwCGADwM7cTtMgBnAZgHoA3ArwC8BgBKqa3pz/A96f9/WUS+Bi2g9Cq0Ez4qL/YpYJ9SCQX0KVBKvSd934RSao3hsa6A9rmvMd4+/RmfoZTaISL/E8Dr0n9qF5HPQvts/wnAj4p8OWSPfQrYp1RCAX1KEloQeQLaCdrjAE4B8Dml1O9EZBDAMqXUpH4HjlOqjv0J2J9UQoFjlC8Y7r8OwLr071cBOB/AVqXUS+ltQQB+w+8ppVQSWqB5otaCQgCnkhVMRP5cRPaJyBERuT297S4R+aLhNr8UkUvTv39aRA6JyAEReW962w+gXZU4VbQ0zi2G+/59+rZ7ReQ6w/ZXReQtIvJrEfmuUxuVUrcopXpMP7ado+E5BFqmyDSAH4qWEqf/REXEmEaXK31SGdqzFcDdAIaUUjcA2Jd+fTugdZo7APwLgNFcbSxUuuNfA2Bv+v/Xi8iLoqVafiq9bY2IbBOR/yNaKuDjkq6FISJ/Jlpq4KuSTrMt5eee/ntWCq/V/iBaEbp/FZEtIjIsIl+CA6XUKov9wbZzhJYueTW0QNCpAP4EQG962yIAZwC4AsC/iMiVoqXafg/AFwG8Am1aSCeA7QCugZZ1tA3aVTwyYZ8yg31K/fYpRv70e7JNtMyhr9jc7hOYnTY2B8DbReRxaEHpVwD8BtqUEDJhnzKDfUqd9inpq/ivQDs56wUwF8C3AfxVul/5IYD/FJG3pdvDcUqB2J/MYH9Sp/1J+jluSD/PfdAyEd8B4BFomUTNmJ02BmjTDjcDeD20oPT1ItIKbWrrtIhcLiIfcHo+z1FKNfwPgNsAxAAMpn+eMP39Pmjpb/r/VwJ4DlrGxCkADqX/7QHwXPo27dAOOgItuvwraAPZRQAGDY91GoBXTc93DYDnoR3gzkm36ZT0314F0AfthDxchvdCAHwZ2jzrP7P4+w4A5xv+/3D6de5K/yQMv78AYJvFe3kY2nSCLv3vAHYV0NZPAfhUnp9vEsAX0q+zO932JQDC6fZeAK0DnQLwIQBBAL+HFhQ5C8BBaEGSRdDSDM8t1efusL9Z7g/p1x8BcBG0q+hTAOaVeH+4GdpB7s/Sr+1SAH9n+nmD4fb6fuoHcGP6c7662t/xSv+AfYrxudmnsE+xalMSWh+h//yDxWd7M7RB14vQTvD2AviP9Hv7Yvo23wSwrprf90r8gH2K8bnZp7BPMbblb6BlNi+H1h/oP/8n/fcvAlhjuH3Dj1PA/sT43OxP2J8Y23Jz+v27BMCfAviJaV9ZAqDHsG0+gN+nf/cB+H56f3oeWsDoGIBV1f7Ou/3hVLJZ+cy1fQu0A5BeTCoE4Eyl1OMickJElkD7oj2stD3lgIj8DYC/hTbf+ZQcj3+JnJKeAAAgAElEQVQdgPuVUicAnBCRpwFcCW1ONAB8QSmVs1iZ5JlSmb5q8u/Qaj38GMBn0u02OhNaJzNzNwD/qDJTKvU0SXNK5VJoX6jD0DqSPwdwuojsBnBOOnIOAAGl1CW5Xl+eHgTw36F9Zj9XSikRuQRax6IXJWyGdvA7CG0a1VfTt3sW2nvyNmif6Wvp1/NTAGuVUl8s0edux25/AICHlFLPpNszCO2K+ojVg0gBKZXQrp4dBnAetAPHK9D291+l/34btA77+fT/fy4iEWj7iKSf7zwRiab/7gMwR6XTbusc+xT2KexTnCUMvyct/r4ZwE5oV+L+DNrnu1gpFRURiMgCaAPUYZfPV+vYp7BPYZ+SLQHt826DdrKr1yt51Ob2HKdo2J+wP2F/YqKU+pmItAE4Hdp7c66IfB9akOz1AI4D+DhMU05FK4L/A2g1qj4F4C1KqZdF5CPQshYvVEqVLTOsVBgYKowA+J5S6k4AEG3pOj217AFoO/QF0KKGEJEroUVDPwngu9Ci37ko0+/G/+9000il1C1ubmfQDW2Hfx+02jKfUErdb7yBoRMz+hcR2ZD+PSyzRdhCyBywvwvAv0J7H/4S2hf5XgCPQYsiX5F+jl15ttuVdGd3D4C7oBUmFAC/VkrpKYpt0FJELwawP93JAdmfhfF3/f+l+txtm2/zvK/Y3Cb7AZRa5fR3M9FqfsyFdpXoa9AK7wFaBP2q9O+nAZhJCVVKnZe+bye0z/ZJaHNybwLQAuB/Ku8UHPQS9imZ2KfUZ59yG7QATwJaTRDjAHwOgKUishXaCd77lTaP/5iIQCmVlHQxUNFWh/EBuAXAfyqlnsinHQ2CfUom9il12KdYPP8azAYT2m2eg+OU/LE/ycT+pA77E9HqGH4WWnHwF6FNLRyDVsOwH8A+pZTdiqiT0C5m/Tu0ALXehu+LVti8JhbIYI2hwvwKwHUi0pPuHJ+FluoGaF+UawG8EdrBBtC+cL+Flgp/vemxhgF0iUhr+icE7SrHe0SkU7QK9hejDMsZmiml+pVSf6lmi/R9RjLn2e6CdvA0CgL4e6XUG9NXV6L670qpM5VSl8nssp//Vyn1UPq5hgC0AtgE4PPQIqwQkWZoHWu5fBfAleko904AF4jImaItofxzAG9P386qs/k5gBtF5HUishBamuVj6b+V4nO347Q/OHaKRboMwMf051FKfRxaLY/PKKXWKK1I7H3GO4jIfBH5O2hziY+nr9I8Au2g8TCAhGjV+ikT+5RZ7FM0ddenKKXuU0pdo5S6FsBnAPytUura9P//E8B7lFJrlVJXpINCdnzQisveq5T6DxH5pohcVK521yj2KbPYp2jqrk8xEQCPpvuPK2BacnzmRhynFIL9ySz2J5p67E9+BOA0pdTpSqsJ9VVoAbOHlFIv6kEhETFmpfmgTRH8KoC40opPZ1BK/UApVRO1EBkYmnWLaAWx9J9b7W6olHoeWkTxKWgpel9VSv0+/beD0OYb7lZK6QXKfgLgDdBSCc8BMCYiZ6RvH4XWQbwCYD+AhUqpX0Cro7AH2jKK71dKHS35K3Ym0CLnq40/0OajGguv3QLgpxl31JZGNPqOiLzP8KXwpaPKTwP4sVLqv9LbWqEVEv2vcrwgAFBKjQH4HoA7lFLHoE2V+hm0qPZTSinbpRyVUi9CC5TsgPbZf1Ip9Vz6b0V/7g7PW5X9QSmlp+4a1+z0A/iEzBaMvU3/g4jMhbYvjEBLI329aAXmfgbte9IMbfUy29daZ9inZGKfkn3fhupTAEBE5onIT6ClhQ8a/rQLwNdF5MvpgbLpbuKDdoV6gVIqoZT6dvoPrQDWmh6rXrFPycQ+Jfu+DdenYHaMEoc27tghWpbHIcPfUwDHKSbsTzKxP8m+b0P1J0qpUaWUMbMnBVPmoYicB+BX6eDW36XbuAPaZ5iRbZa+vYhIc3oM43miVKUC+VRLRORH0OaM3p/+fxDazn8M2vzSSZv7fRPaIF3/AjdBi4S/Od2JQERehjZv9TSl1K/T214AcKHd49o816cAQCn1qXxfH7knIr8G8EGl1Esi8nEA/UqpH4nIZQD+L7SDze9N97kVWiX/T6vZZR1XQisQ2aaU+mBlXwVVG/sUSg+MtgF4QCmVtZqIaGnt3wXwX0qpHxi274N21bYZWpZij+FuSWj71WfL13LyIvYpBADpk7OoUuobFn/7LLTs53cqpY6b/sZxCs1gf0JmotUx3Altmpg+hawbWs2rL4nImQDGlFKHRORN0FZXNWcGCbSxy1+Yz5W8iIEhck1EfIaocNWxg6yMdLrnlPmzFy3VWnlpn6Dawj6l8XjtM6f64rX9i31KdYmIKJ7oUIHYn1CjYWCIiIiIiIiIiKhB1cR8NyIiIiIiIiIiKr2aXK4+EonMpDl1dHSI022JiHJhn0JEpcL+hIhKiX0KEVVCTQaGjIydpVvDw8Po6uoqR3Nqsh2Ad9rCdmTzSlu80g4guy2lHCjl26d4+X1p9HYA3mmLV9oBeKctXm5HqfqUWh6jAN5pC9uRzStt8Uo7AO+0hX2Kt9sBeKctXmkH4J22sB3ZynneY9SQU8lGRkaq3QQA3mkH4J22sB3ZvNIWr7QDYFvseKUtXmkH4J22eKUdgHfawnZY81J7vNIWtiObV9rilXYA3mmLV9qh80p7vNIOwDtt8Uo7AO+0he3IVqm2NGRgiIiIiIiIiIiIGBgiIiIiIiIiImpYDAwRERERERERETUoBoaIiIiIiIiIiBoUA0NERERERERERA2KgSEiIiIiIiIiogbFwBARERERERERUYNiYIiIiIiIiIiIqEEFqt0AIiIiqi8D0Th6+6I4MpHEwlY/NqwKY2k4WO1mEREREZGFimQMici/ichN6d+/JSJPicgGw99dbSMiIiJvG4jGsW7rMDbui2HH4DQ27oth3dZhDETj1W4aEREREVkoe2BIRK4E0KOUekhE3gHAr5S6FMByEVnhdlu520lERETF6+2LYn80mbFtfzSJ3r5olVpERERERE5EKVW+BxcJAngOwCMAtgN4K4AtSqlHRORdAEIALnCzTSn1Hf1xI5HITKP7+/vL1n4iqg2rV6+WYu7PPoWodO7Y04zdo/6s7Rd2JPH1c6eq0KL8FdOnsD8hIjP2KURUKsWe99gpd42h9wH4A4AvAPgwgLsAfCv9txEAqwC0ATjkYpulFSvyTybq7+8v6H6l5pV2AN5pC9uRzStt8Uo7gPK2Jd/HbZT3pRbbAXinLV5pB1D+tiw/PILdo7Hs7V3tWLFiScXa4ZaX+hPAO+8L4J22sB3ZvNIWr7QD8E5b2Kd4ux2Ad9rilXYA3mkL25GtUm0p91SyCwD8u1JqEMD9AB6HlhEEAO3p5x9zuY2IiIg8bsOqMJaFMzOGloW1AtRERERE5D3lDri8DGB5+vfVAE4DcEX6/+cDeBXAbpfbiIiIyOOWhoPYtLYL65eHcGVPE9YvD2HT2i6uSkZERETkUeWeSvYtAN9O1wkKAlgD4GcisgjAdQAuAaAAPOFiGxEREdWApeEg7r16XrWbQUREREQulDVjSCkVVUqtV0pdpZS6VCk1AC04tBPAm5VSEaXUqJtt5WwnEREREREREVEjKnfGUBal1AkAPy5kGxERERERERERlQ6LOhMRERERERERNSgGhoiIiIiIiIiIGhQDQ0REREREREREDYqBISIiIiIiIiKiBsXAEBERERERERFRg2JgiIiIiIiIiIioQTEwRERERERERETUoBgYIiIiIiIiIiJqUIFqN4CI8jcQjaO3L4ojE0ksbPVjw6owloaD1W4WERERERER1RgGhohqzEA0jnVbh7E/mpzZtmtoGpvWdjE4RERERERERHnhVDKiGtPbF80ICgHA/mgSvX3RKrWIiIiIiIiIahUDQ0Q15shE0nL7oM12IiIiIiIiIjsMDBHVmIWtfsvtPTbbiYiIiIiIiOwwMERUYzasCmNZODMItCysFaAmIiIiIiIiygeLTxPVmKXhIDat7UJvXxSDE0n0cFUyIiIiIiIiKhADQ0Q1aGk4iHuvnlftZhAREREREVGN41QyIiIiIiIiIqIGxcAQEREREREREVGDYmCIiIiIiIiIiKhBMTBERERERERERNSgGBgiIiIiIiIiImpQDAwRERERERERETUoBoaIiIiIiIiIiBoUA0NERERERERERA2KgSEiIiIiIiIiogbFwBARERERERERUYMKVLsBRFR9A9E4evuiODKRxMJWPzasCmNpOFjtZhEREREREVGZlS0wJCIBAPvSPwDwYQB/CuB6AL9VSt2Vvt2n3WwjouLYBX8GonGs2zqM/dHkzG13DU1j09ouBoeIiIiIiIjqXDmnkp0H4IdKqTVKqTUAmgBcAeBNAI6JyDUicqGbbWVsI1FD0IM/G/fFsGNwGhv3xbBu6/BMsMgYFAKA/dEkevuiVWotERERERERVYoopcrzwCJ/CeAuAOMAngOwF8CYUurfROQSANcBiACYzLVNKfVJ42NHIpGZRvf395el/UT15ON7g9gylJ39c213HENTPuwe9Wf97cKOJL5+7lQlmle01atXSzH3Z59CREbF9CnsT4jIjH0KEZVKsec9dspZY+gZANcopY6IyPcAhKAFhwBgBMApABIAXnGxzdaKFSvyblh/f39B9ys1r7QD8E5b2I5spWjL2MtDAKazto/727B8vh+7R2NZf1ve1Y4VK5aUtB2lUs625Pu4jfK+1GI7AO+0xSvtALzTlkZoRy2PUQDvtIXtyOaVtnilHYB32sI+xdvtALzTFq+0A/BOW9iObJVqSzmnku1RSh1J/74LwBi04BAAtKef2+02IirCwtbsjCAA6EnXGloWzvz7srC2nYiIiIiIiOpbOYMu/yEi54uIH8A6AG3QagcBwPkAXgWw2+U2IiqCU/BnaTiITWu7sH55CFf2NGH98hALTxMRERERETWIck4l+wyAHwAQAD8D0AvgCRH5EoBr0z8DAO52sY2IiqAHf3r7ohicSM5kCunBn6XhIO69el6VW0lERERERESVVrbAkFLqeWgrk81IrzB2A4AvKaX257ONiIrD4A8RERERERGZlTNjKItSKgbgJ4VsIyIiIiIiIiKi0mJhZyIiIiIiIiKiBsXAEBERERERERFRg2JgiIiIiIiIiIioQVW0xhARERF520A0jt6+KI5MJLHQtIIhEREREdUfBoaIiIgIgBYUWrd1GPujyZltu4amsWltF4NDRERERHWKU8mIiIgIANDbF80ICgHA/mgSvX3RKrWIiIiIiMqNgSEiIiICAByZSFpuH7TZTkRERES1j4EhIiIiAgAsbPVbbu+x2U5EREREtY+BISIiIgIAbFgVxrJwZhBoWVgrQE1ERERE9YnFp4mIiAgAsDQcxKa1Xejti2JwIokerkpGREREVPcYGCIiIqIZS8NB3Hv1vGo3g4iIiIgqhFPJiIiIiIiIiIgaFANDREREREREREQNilPJiAgD0Th6+6I4MpHEQtYUISIiIiIiahgMDBE1uIFoHOu2DmN/NDmzbdfQNDat7coZHGJAiYiIiIiIqLYxMETU4Hr7ohlBIQDYH02ity/qWIC2mIASEREREREReQNrDBE1uCMTScvtgzbbdU4BJSIiIiIiIqoNzBgianALW/2W2wfGkrjx0aGZKWJmhQaUiIiIiIiIyDuYMUTU4G47I4SAZG8/MJbEjsFpbNwXw7qtwzgUy7yRXUCpx2Y7EREREREReQ8DQ0QN7r6XYkgo59vsjybx9QOZCYYbVoWxLJwZBFoWts4uIiIiIiIiIm/iVDKiBmc3JcxsaDozjrw0HMSmtV3o7YticCKJHq5KRkREREREVHMYGCJqcHZTwsy6m1JZ25aGg44rlxEREREREdWigWgcvX1RHJlIztRdrdeL4AwMETW4DavC2DU0nbHCWECQMb1sWdiPO5bEqtA6IiIiIiKiyhqIxrFu63DGOdKuoWlsWttVl8EhBoaIGpzVlLDbzgjhvpdiGVPEpge5DD0REREREdW/3r5oRlAI0Oqu9vZF63LGBANDRGQ5JezyhaGM//cPVrJFRERERERE1WFXh3XQZX3WWsPAEJFHNNIcViIiImoMHN8QUS2yq8Pa47I+a61hYIjIA5zmsHoZB3tERERkp9FqdBBR/bCqw7osrJ3v1CNf7psUR0ROEZHfpX//log8JSIbDH93tY2onjnNYfUqfbC3cV8MOwansXFfDOu2DmMgGq9204iIiMgDanF8Q0QEzNZhXb88hCt7mrB+eaiug9qVyBj6IoCQiLwDgF8pdamIfFtEVgA41802pVR/BdpJVDW1OIe10QqyERERUX5qcXxDRKSzqsNar0QplftWhT64yFsA/DcAZwHYA2CLUuoREXkXgBCAC9xsU0p9x/i4kUhkptH9/YwZUe37+N4gtgxlR5+v7Y7js2d6MwPnjj3N2D2aPcf2wo4kvn7uVEXbsnr1ainm/uxTiMiomD6F/QnRrFoc35QD+xQiKpViz3vslC1jSESaAHwcwJ8A2ASgDcCh9J9HAKzKY5utFStW5N22/v7+gu5Xal5pB+CdtjRqOz7fE8de0xz8ZWE/Pn/1AkwPvurJ92T54RHsHo1l3W55VztWrFhS0baUUr6P65V9FvBOW7zSDsA7bfFKOwDvtKUR2lHLYxTAO21hO7J5pS252uE0vin1dIxaeU+KUct9ilfaAXinLV5pB+CdtrAd2SrVlnLWGPoogH9TSp1M/38MWkYQALSnn9vtNqK6VotzWDesCmNZODNjqJ4LshEREVF+anF8Q0TUiMpZY+gaAG8RkbsAvBHAEgCvAdgJ4HwAewEcBHCFi21Eda9W5rAaVyI7qyOAszsDiMYVergqGREREZnUyviGiKiRlS0wpJS6Sv9dRLYBuBnAEyKyCMB1AC4BoFxuIyIPsFp2dlnYz6t/RERERERENaoi07SUUmuUUqMA1kDLBHqzUiridlsl2kjUyAaicdy+fQQ3PjqE27eP2C45z2VniYiIiIiI6ksllqufoZQ6AeDHhWwjovIYiMZxwyNDODgxu0LhU4OT2Hx9d1YWEJedJSIiIiIiqi8s7EzUIOyygj66M5IRFAKAgxMKH92Znay3sDV7eXoA6LHZTkREREREVIuePBLDeRsHseT+wzhv4yCePJK9InO9qGjGEBFVh1VtoF1D09i0tgu7jltPG7PavmFVGLuGprNqDHElMiIiIiIiqhdPHonhlq0jSKSvn4/Gk7hl6wgeXDsPly8MOd+5BjFjiKgBONcGUtZ3stjOZWeJiIiIiKje3bkjMhMU0iWUtr0eMWOIqAE41QZa2RnAtsHs7KCVndbdA5edJSIiIiKienZyKmW5PWKzvdYxY4ioATjWBhKxvpPddiIiIiIiojrW2WwdKumw2V7r6vNVEdUZt8vJmz3wShSL/uMwHtgXgznMs7hVMB5PYcfgtOV9Xzjh7jmIiIiIiIjqydeu6EDAdAIVEG17PeJUMiKPOxQTfMSmcLRTbZ8HXoniA4+PZm1fEQZe39GM507E8chrUw7PzIwhIiIiIiJqPJcvDOHBtfNw544IIlMpdDT78LUrOuqy8DTAwBCR5339QMC2cLRTrZ8P/yZquf1QTPDGbh8OjjvPj109nwWliYiIiIioMV2+MIQ96+szEGTGqWREHjc0Zf01HbQpKK2bMpfRN2y3K0atW9wq+Nwl9ZkmSURERERERLOYMUTkcd3NKQDZxaN7bApK65oDggmL4FBzQGyLUXe3CNYsasGGVWHbaWoD0Th6+6I4MpHEwla/422JqL7w+09ERERUfxgYIvK4O5YksHeyJWM62bKwdkLm5CuXhS1rDH3lsjBWL2jBrqHprMfMVbdoIBrHugLqHRFR7eP3n4iIiKg+cSoZkce9LqSwaW0X1i8P4cqeJqxfHnJ1Inbr6WF866o5aA0I/ABaA4JvXTUHt56uXeEv5DF7+6K29Y6IqL7x+09ERERUn5gxRFQDloaDjoWm7dx6ehi3nm6dWWR8TLfTQ+xqE+Wqd0REtY/ffyIiIqL6xMAQUYPLZ3qIXW2iXPWOiKj25fr+s/4QERERUW3iVDKiBpfP9JDbzgghIJnbAqJtJ6L6tmFVGMvCmcEhvd6ZHmDeuC+GHYPT2LgvhnVbhzEQjVeptURERETkFgNDRA0un+kh970Ug3mhs4TSthNRfXOqTcb6Q0RERES1K6+pZCJyPoCVAB4A8Hal1ENlaRURFcw4nWNOUKAUEE0o26kd+UwPY40RosZmV++MfQMRERFR7XIdGBKRTwD4bwAWAvgpgI+KyJVKqX8oV+OIKD9W9YKMrGoHbVgVtly6fsOq7KLVrDFERFbYNxARERHVrnymkt0J4BIA00qpGIA3A3h3WVpFRBiIxnH79hHcsacZt28fcVWrw2o6h5HV1I58lq53qjFCRI2LfQMRERFR7cpnKtlJAJ0A9AojpwEYK3WDiMic+ePH7tGY7UphRnbTOYwee20St28fsZxWpixur09N23e8GcsPR3HP5R2476UYBieS6DFNT+OqRESNSQ8w9/ZFLfsGO+wziIiIyKsaaZyST2DobwFsAzBXRDYDuADAX5SjUUSNyNjxHBjTfoz0bB9zfQ/z/XKJxBU27psNNAGwXa4+82/OAap8lr0novpjV3/IzqGY4CPsM4iIiMiDGu3cxnVgSCn1iIj8Ftp0MgGwUyk1VLaWETWQXLWBdOZCrlb3CwiyVg6zYpxW5rSakNXfbtoyjCXt/ozIudOqRPmcLBJRY/j6gQD7DCIiIvKkRju3yWtVMgBzlVIPi8gZAF4HgIEhohLIVRtIZy7kanW/hAKWtPsRmUohEneOEA1OJC2nj+X6mzGjSY+cc1UiIsrH/2Pv7sPjqu570X/XnhnNjKTx2LLlN4SMTeQQCE4wTgOxCaRNMOa9oX6ak9N7D6etT6AlzZPc+5zCE+dwk9IT0vO0PW3oMT3cpO69TdrGSWMgYEzoKQYphhubJAYCtomMjGzJGnmk0Yw077PuHzNbmpe99+w9r3tmvp/n4cHaGm0tj7V/Wuu31vqtQFy7zCFjBhERETVbp41tTBefFkL8nwD+LffhBgD/LIT4o7q0iqjDmKkNpFXIVe/rLiykMW9i2dDabofuaUJjkTROzqbK3kPNnPNUIiKyot+d0bzOmEFERETN1mljGyunkn0RwBYAkFL+GMBHAHypHo0i6jR6gWew14Fr/Wndk8L0vi6eKb+dTE00aZ0m5BTZVUGBmPbArdjkQpqnEhGRJfcNphgziDrAyEQUWw5MYvAfzmPLgUmMTESb3SQiorLu3eyFUxRec4rs9XZkZStZDIA77+NuAOZGjURkaO9WH44FEgXbwjb6HDi4cyUSk+9iaGjQ9NdpcSvAb1zihpRAJCVLTgzKP01oTKPwNQD0OTPo9bg0P7e221HxqURE1Jku8UrGDKI2NzIRxV2Hg4uTVXPJNO46HMSTO/uwfV17Dq6IqD3sPxUtmWhPyez1doxfVhJD/wXAq0KIp3Mf3wZgb7kvEkL0AbgWwM+klNPWm0jU/oySKqcnzX/d0QsJzZVCHofAdz+5yvA+ahG12w8FNJM/G3skvna9v6CDBxRmzq2eSkREnY0xg6i93T8c0hxY3T8cwond7TewIqL20Wk1hqycSvYdIcRxAJ/MXXpMSvmW0dcIIVYA+BGAZwD8hRDi1wE8CuBKAM9IKR/Jve5bZq4RtbNqB0gSQJdDIKWRGfK7lYJj7dd1O3DvZi/2n4piYiGNZS4BKYFwSuoeeX9mXuh28No1c05ERESVm41rby4I6VwnIrKLTqsxZOlUMinl2wDetvAlWwB8SUr5Si5J9OsAHFLK64UQ3xZCDAG42sw1KeVpK20l6gRmjrl3CuDhrT0lr/vhmdLlkflfU/y5YEpBUCdppJU5L05EcYsIUXvhM05E5Sx3K5hLlvYR/G4rZU6JiBpPr9RHu9ZCtHpcvSVSyiMAIIT4OIBfA9AH4Hu5Tz8PYAeAa0xeY2KIqIjeMffdTgGXyHa89u3wY/+pqOax9nrUI++jKWmqAHVx5lwrYaUea8+BI1Hr4zNORGbs26G9BX3fDn/zGkVEZEKn1U8VUuqPDoUQX5JS/kXuz/9F6zVSyq8ZfgMhBIDHAAwAmAbw11LKXwghbgawFcCQmWtSykfVe4ZCocVGnz7NfBF1nnNRgcfPOjEcdCKSFiWfv9afxuNXxxc/vu+EG8fnrC17vNafBiTKft2AJ4PHrorjEq/E8RkFX33HhUBCQUqWtuuW/iT+5P1JS+0wY9u2baXfzALGFCJrvnLShecCpR2jej3jjVZNTGE8ISqk9g3CKQU+ZwYPvy+Ja1d01lYyxhQiqpVqxz16yq0YEjp/Nk1mM09/KIT4EwC/BeCJ3Kd6ASgAIgC8Jq5pGhoastym06dPV/R1tWaXdgD2aQvbUaq4LWPhJL5YZvvYppW9BSeZbTofxPE5a8fD+rwe9Hc7Nb9usNeBDb2Ogsz5yEQUD4wEDVcizTt6MDTUb6kdWur572P1vnb+Wen0dgD2aYtd2gHUpi2RdwIAEiXXrTzjdnlP7BRPAPu8L4B92sJ2lLJLW8y0YwjAZ37NHm1pBMYUe7cDsE9b7NIOwD5tYTtKNaothokhKeWf5/35q1ZvLoT4YwATUsr/B8ByZAtP7wDwCoAPATgJYNzkNSKC/vYxldbe171bfTg6GcP4wlLWRgFgNF93dCqJq1cCPU6B+bxsz0afQ3O7iFZh6mLtWqyNqNN0WkFGIiIionZW1xpDAP4ngO8JIX4fwBsADgJ4SQixHsAuANche5jSyyauERH0j070uwRuvtSjv/dVCGQfrazVXgXXrHTh0Hi89LUA4hngWCC7JaTHCVzmSePK1b2699c7eUTVzsXaiDpNpxVkJHJpPEoAACAASURBVCIiImpn9S4+PQPgU/nXhBA35a79mZQyZOUaEenP1N98qafkuHv11KAXz8cQiBUu55mMZtDbpcCtZJNARuZTwKXeTMn98+mdPOJWgDsv87Z1sTaiTtNpBRmJiIio83TSCaymE0NCiBcA/KaUMlzNN8wli75XyTUiMj9Tb+Yo+5OzSVy/2oUXJ8sXiw0kjI+W1Tt55F9u7sP2dV79LySilrTB5zJMFhMRERG1qk47gdV4pFcoDODj9WoIEZmjztTv3uTFDWu7cOulblzhd+IPh2ex50gQY+FskqdcLSIAeGcujb/asQLLTMS2/i7jZUXb13nx5M4+DPY64HcJDPY68OROJoWIiIiIiKi1aI2lzoTTeOS18utkxsJJ7DkSxO2HAgXjMzuzspXsHwD8uRDiSgCvqhellC/VvFVEZGg8ksKrUwkEY2lE00A6b5WOmsnWq0WUT5ESx6ZimCsTq5wCuHt19n5GSyq3r/PixO7yiaBOWpZJREREREStRW8sNVlmjNWqK42sJIYeADAB4Nbcf0C2ku2v17pRRLSUPBmddmPT+WDBsfDFW7byqZnsZS5R9nv4ugT+YHiu7OtSEjg45cD1NQh0rRosidoVE7VEVE+MMUTUiio9gdVopZGdt+CXTQwJIa4DcAOAHwH4X1LKn9W9VUQdrjB54sDxuehi8sTMsfBPvRtFskxBaQBIS4F4pszNcgIJpSaBrlWDJVE7YqKWiGotPxG0zCVw4mIC4wtLfQ0zMYbJJCJqtkpPYK10pVGzGSaGhBAPAfgPyCaFBIB/FkL8hZTy8UY0jqhTGSVPyh0LD5Q/ZUw1FTP5QmRrDNUi0LVqsCRqR0zUElEtjYWTuO3ZQEEiqFi5GMOENVFns0tiuNITWCtdadRs5VYM/SGAD0kpLwKAEOIvAfwbACaGiOrIKHmidyx8Pa1xA/cNpvCdmeoDXasGS6J2VC5RW4/Omd42WSJqfQ++EjJMCqmMJoOYsCbqXOeiAl+0UWLY7Ams+f0ln1NgoEfB+PzSBLyZlUbNVi4x5FCTQgAgpRwXQvTUuU1ELa/awZRR8uTBD/eW1BgSAK5aruCt2QzqkTKaTgCTMYF7N3vxg9EoitcZ/TIYx54j5gZ4lS7LJKLaM4o1WrP2Ry/EcfUKF8IpaRjb9GKg0TZZJoeIWt+xaXMn7xhNBnFlMVHnevyss+USw1r9pYFugVsvdSOclKZXGjVbucSQXwjx3aJry/OvSSk/W/tmEbWuWiyBNkqebPC58Mi2Hnz52DzSEnAI4E+39eC+Dy7Hyv3nsiXhaywtga++48KHQ/MlSSEAeHM2gzdnzQ3wKl2WSUS1ZxRrtGbtx+czGJ+PL36s9cwbxUCuBCBqd+U7IeUmg7iymKhzBeKK5vVmJYbNTPZr9pcWJK5fq+C7n2ydvk25xND9GtcO16MhRO2iFgOf/OTJ6MUINq3sLTiVbG8uKQRkkzZ7j83j6pVuuIC6rBgCgHBKKTsTaPbvaXZZJhHVl1GiVm/WPp/WM28UA7kSgKi9faS/C8++Fy+5vs6r4H1+p6nJIK4sJupc/e4MgNIkcDMSw2Yn+9ulb2OYGJJS/n2jGkLULmoVHNTkyenTFzE0NLh4XetUspQEPv18EIqCumWG4hkgmShfrPoHo1H8y+g5uJ0C3/yYD/dczo4cUSsonudf5hKmvq44thnFQK4EIGpvX/+oHyeC0wW1NdZ6FXx4ZXYLqhlcWUzUue4bTOFkzGOLxLDZyf526duUPa6eiKypR3DIX8Z4fl570GX2JLJKJaUwtU1NbcZCSuL3XpoDACaHiGzKaDZMmtyWWhzbHDpfqEjJlQBEbW6Dz4Vndq1aTOr4csfVHxo33oKqdR+uLCbqPJd4pW0Sw2Yn+9ulb8PEEFGN1To4aFXnbwQF2fpFySprFn3+J2Emhohsymg2zMzsvlMA9272Flw7rROrTofThttkiag95Cd19hwJlpxSxrpiRGTELolhs5P97bLKkYkhohqrdXDQqs7fCA4AXqdA0kRmyK3or1iKm1w6TkSNpzcb9uL5mKmvT0lg/6kotq9bSg5FdGLGfO663jZZoPoTHYnIXvRizL+MRvHq1CT+4AMe/I+3YpiNZ7DcrWDfDn9BPCEiapa9W304eiFesDXW6wBG55IlpzHbJZlVDSaGiOqglsFBrzp/vSUBU0khIJtE6nYKLGgkgdxOc3VKiKjx9GbDAjHzCd3iJdXL3QrmkqWDQb/bOJbV4kRHIrIXvRiTBnA2ksaDP51fvDaXTOOuw0E8ubOPySEisoei7fHRNHB8OoXj06m266M0Z8RJRKZlq/PbWywDfPNj2tvF9K4TUfPt3erDRl/5+mf9HgWDveaWVO/b4UdxPtgpsteLjYWzs263HwrgjudKt8yqW06IqHXkP9eRRAYDPeaHGymZPWSDiKgZ1Ph13wk37njuYslW2Hzt1kfhiiGiBqpkm8Tdq9N4YdpVchJZo/U6JCJp/dU/ah2hz/8kjHhK8lQyohZQvPX17dkUArHSZPQVy514bMfykhU9WvXTtq/z4smdfbh/OIRQPAO/zvYQs/XTWu24V6JOprXyb6Bb4NZL3Tj8XtzUwamhep+mQUSkoTB+OWDmqOd26qMwMUTUIJVukzg45ahbUkggeyR1txN4/3IX0hIYi6RxNlIa5LqEzH2Fvnsu104EjUxEcf9waLGGwMNbe/DceJJ1RIhsRCJbV0zL2m4HNvhceGy7vyDh89h2v+azu32dFyd2G28FMVs/rdWOeyXqZFoF7ccXJK5fq+CSXodm/6JYuW2nRES1pE7cv3g+rjk5ZkSvj9KKNROZGCJqEKPTf4zqEb23UL8OkgQQSkqEkkBGJvD87asxHknhzsNBpIuSUcGUfjs8BvmikYko7jocXExuzSXTi8fYq9ptjy5Rq9BKWCsA8rtFA90Ce7f6MBZO4oGR0OLALpRM44GREA7udFb07Jqpn9aKx70SdTKj45337fAX9Ae06G07JSKqB61+kFl6fZRWrZnIxBBRgxh1lowEU9rXBbKJnVq5EAO+MDyDbpdSkhQqJ2Mwvrt/OFR2xROPriVqDq2EdclcmRC6r63m2c3WTyudaRvsdWBDr6Nlj3sl6mR6xabHIml8/ecR7FjbhZOzSSyksiuD1FPJjLadEhHVi1bfppjaL/G5BKQEIilp2EepdX+pUZgYIqoBM8sF9TpL5ZYghpLaWZd67C57cTJZ0dcl0sCeI0Hcu9mL/aeimFhIw+cUEAI4Z2LZONBee3SJWoVewjrf+HxmMb5p0Xp2i2NifmxQY+R9gymcjHlKahbZfUaNiPTdMuDCgdFoyfWzedvUe5zZumWblrmwa0MP7vvg8kY3k4gIQPl+0ECPgquWOxFOSUiZnSsrNwardDFAszExRFQls8sF92714VggUbZwa+k97X/cewbAgdEofngmWnE9JNYRIaotMwnrhMax8lomc/fQUvzsasXE4thwLJDAX25GQeFrrhAian1ffW2+7GvmU+173DMRVa+R9Xn0+jZ9zgyuW+fFiYsJHBqPa75GL375dOo19upctwsmhoiqZHa5YPHpP1aXILaCSpNCAz0K64gQ1ZBRwjrf67Pm4owar8wkt7XiV3FsOBNO4/GzTvzTFpetl1UTkTWzFk8Ua4XtFUTUOFonltYzgazXt/nLzVF8Z6bH1HH1xfFL6OR/9K7bBRNDRFWyslxwg8/cIGh0TntLV68TiOjUHGoktwIkMjXczibrdOwaUYcySlj/5/VL1xIm8kJOAdy72Ws6uW1mexoABBI8eYio3Sx3K5gzuRJR9W7YBh0bIrIFrRNL65lA1uvbJCbDmDhX2XH1c0ntcU1Y57pdMDFEVCWrtYPMCMS0A0efx4GIyZo99XTnZV68OpUwdeysGeMLkjOGRHmqXUZtNmHtdgoslFnql5LA/lNRbF/nNZXc1ouJxfq7rK0sICL727fDjzueC5YWsTdwIcpYQERZeieW1rM+j1bf5vSkuf6M1nivHmPDRuB0HVGV9m71YaOv8EGv5IjlsXASe44EcfuhACJJ7U7SGq+CPZu7Km5rLah/t+VdtV0PafeCbESNom4DOzAaxfBkAgdGo7j78EWMhc0XhzfbKfnmx8zFKSvP572bvSi3jX6jz4H7BrlKgKjdDPQ6sdprbXix2mPz/RVE1DDZE0tLNSOpUq4/ozfeq9XYsNG4YoioSlZqB+nRqgei5TKfE8/oFECrNQWAzyXQ7QTev9yF8EIUm1b2Lv7dZhO1XQ5p9yw6UaPU4phTo3pAicmLBSuSfm2lA6/PprPbygSQ1ni0rTyf+09pF6EvPoY+MRk2fU8iqp16FnZ95LUwJi2uANq4jIWniShL78TSZiRV9Poz/R6Bm9Z7dGNnLcaGzcDEEFENmK0dpMdMsWm1zscPz5QeA1sPigDGfmepGMnp06cxNDS4+HG/R+BspDbfqxWy6ESNUotjTo06JS+eKS3sqB4TD6AkSW31+dRr/4ZeB57e1b/48elJ07ckohoxe5Jqpc5YrBdkNr408pQiImqeS7zSNkkVvf7MFcvLj/uqHRs2AxNDRA2k17ExU6w1JYF7X5yt+OSvfALlC0dnJHD7ocBiO4ttWubC8enKt4J0OwVcAvC7FTy23c8OHlFOrfemFz/r5Qo7GnXIzAzOqmk/B39E9VWLFYla1Gf39Yvmtry6BHD3Rq+pZ7zeySwishe7JFVatVZQpeqaGBJC+AH8EwAHgHkAvw1gH4ArATwjpXwk97pvmblG1MqMOjZmi7UGYrUp0Ggmt5QBMDyZAJBt519uFhjK+7zWVhWznAKLBW9DyTQeGAnh4E4nO3hEMN4GZpZRvClX2FGvQ2Z2cFZp+zn4I6q/WqxILGZ2O3y+j602P/CrVzKLiMhILfpjraTexaf/PYC/kFLeDGASwGcAOKSU1wPYJIQYEkJ82sy1OreTqO6MOjZaRcrs5Ew4jcfPFuaR1a0quzd5ccPaLnTrVGcTANZ5Fdy01oUb1nZhsNdRsupJfR+IqPTZ2r3Jazk5YhRvKi3saHTPWrTf7P2JqHL1mAE3sx2+WE9XdgiSf/DGniNBzSL79UhmERGVU4v+WCsRUta2gKzuNxLi+wCWAfjvUspnhRCfAeAFcA2A58pdk1L+nXqvUCi02OjTp083pP1E1brvhBvH50o7Xtf603j86jjORQUeP+tEIKFgNALMpO2VKNrcncZ3tuoXvv7EUS8i6dLkUK9D4t+uX6qLVO59qMS2bduqOtKEMYXajdFz9pX3JfC51924kFiaG1rTlcHfXh3HJV65FIviCvrdGdw3mMIlXlmXZ9dsm2txfyuqiSmMJ2Rn56ICD7zpxnhs6fkf8GTw2FXZ59+s4zMKvvqOC+GUgngGSEprj8xVvWn86fsTptrylZMuPBcoHYjd0p/En7zf/GmNzcSYQkS1Uu24R09DagwJIa4HsALAuwDO5S4HAWwF0GPymqahIeuLibJFdJu/CMku7QDs05Z2bsem80EcnystHL1pZS+GhgYxBOCmLblr3z2vfTRQE51eEPiz8yt16wH0/XwSkUjp7F2f11nwXpZ7H0y1pY4/J1bva5efWcA+bbFLOwD7tKXR7TB6zoAgXC4nkFhaOeRyObFx41oAKCpM7cDJmAcHd67EmrEQMFeaoFmzrNv0s5uv+D2pRWyohJ3iCWCfn1nAPm1hO0pV2pYhAM9sTJoq7KpX82tkIooHRoJV1TwMowvfmenFeKzwmR+PKfjOTB+e2LK0Rewba5M4qVEU/xs3ri5ot13+fRhT7N0OwD5tsUs7APu0he0o1ai21D0xJIToA/BNAPcA+BKyK4IAoBfZrWwRk9eIWlq5faojE1HcPxzCbDyDuaS9kkIAIKHgwGgUL0/Ecfi2VSWdyH07/LjrcGFHUQDwOSX2HAkudig7bb8uUTMYPWd/fGQO4/OF28nG5zO49gdT6HKIxfpfKnU7l94C41otPGZsIGoMM4VdjWp+3T8cqvogjDVexfQWsVY9+pmIqJXUu/h0F4ADAB6SUo4JIY4D2AHgFQAfAnASwLjJa0QtzahjMzIRxZ2Hg3ZbJKRpMprBF0ZmcfCW/oLr29d58eTOPtw/HMJMLI2FdHbR05uzGbw5Gy0oIssOHlF9GT1nesWnUxJI6Yz23g2n4HZor1yO1OKoxDJtJqLGMqr5dTGqndBxCuD6NV3odQoIAYSTEu+EUpiIltY16/co6HFpxyKtekdGySx1ZdPotBubzgcZN4iIKlDvFUO/h+w2sC8LIb4M4O8A/G9CiPUAdgG4DtkDkl42cY2oJZk5fnnPS7MtkRRSvTiRwMq/OwenAnx4lRMuRVn8u53YvRZ7jgRxYLRweXj+CSJ2OYaSqJ3pPWfZ4tPWaphdiGbw0dVdmp+r5bGtjA1EjafVT9FbzfPi+Th08kLocgg8vau/YAV0XKdzc/RCHNetdmOgRylYwai3SlCvL1W4ssmB43NRnmZIRHVhZkzXyuqaGJJS7kP2ePpFQoinAHwKwJ9JKUO5azeZuUbUaswevzylMZtmd2kA6Qzw6lRq8Zr6dzsTTml+zbs614mo9vQ6MPcNpnAy5rF0itAyp+RWL6I2pNdPucKvPUQIxPT7K4M9iukV0DMJ4NB4HGvcwK2XuhFOSt1VgkZ9KR5lT0SNoBWHXjoXhcOhIJKU6HUJDPkcSAvRskmjhhSfzielnAHwvUquEbUasx0Wh0DV+/Xt4Ew4jTueu6h7hOy4RnFqIqo9o4HUJV65OKD6wWgUZtLScynR9K1e7T5TR9QMev2UDb0OOC32Td4OpXHbc0FL3/9CPFun7Old/bqvMepL8Sh7ImoErTh0IQ4g14uaS0qcX1jqUbXiysWGJ4aIOonZDssVywR+MdsGmSEAZw2SP/Op1lsZRdSKjAZS/3n90patt2Ym8cZM+QHUGm+2FkiztnqZXX1JRNbo9VPenEk2bMLq2LTxkfNGfal1OltZa7nFlYhILw7pacWVizzti6iOynVYxsJJ7DkSxFtz7ZEUKifOCTyiulJjyrNjpce+A8AL41Hcd8KNPUeCGAsn8YEV2nWDil3ma+48klGii4gqp9dPyZ4r2hhziQxuPxRYjEvFjPpS9272wlnUVKcA7t2cPdxYjYlG9yei9ldtLNCPlfpabeUiVwwR1dEtA66SIszq9bFwErcdmi45Nrqd9bga19EkalfmirBqm0kAxxNLBVo/d4UHB0bLf89fBuPYc6R5p/1wuwhRfezd6sPRyRjGF5YmqAa6Ba7uc+HQeLwhbYhngOHJBADg2bMxfGCFExt9zsV4Y1Tf7JHXwiUrm1IS2H8qioFeJ1caElFNVh1rxaFyWm3lIhNDRHX01dfmda9/cEW8o5JCAPDRfnOrE4hIm9UirEbOhNP42s8WTL32zdkM3pyN4uiFOK5e4UI4JRta54fbRYjqSAhkDwRe+viBD/bg7VDKUkyphfmUxLFAMvff0sBNr76ZUdKYhamJCDBf89VIcRxSpMTwVFK30H4rHs7BxBBRHc3GtRM/oXgGPw0kGtya5lrjBh69zt/sZhC1NL3OzSd/FEAlWz8WLBYRGZ/PYHx+aRVBo2bfjVZfElHlHnktXDJJNT6fwf5T0YJB0NuzSQRitd323u8RhvfMH7jp1TczShpzpSERAbVbdVwch0Ymorh/OIRQPIOe3KlkGSEafjhHrTAxRFRHPU6BuWRppyealoi1cb9k2yonXr+YQjz/r85dZERV0+vcZAdXja9Vlj9wq+epYUarL++5vLVm5IjsxGjAlD8I+uwL03j2vdpuLfM6FQDGnaFyA7e9W304eqFwBfZAj7K4zUwLVxoSdZZqVh0b9W22r/PixG5vTdvaTEwMEdXR+/0OTERLVw0l2nwH2bHpVMm1CzHgwVdC+MdPrWpCi4jag9Xihz1OgStXONHvUXDiYqKgjkitPP9eDP/ux9N4fSZZMDirZDWROvs2G89guVvBvh1+bF/nNVx9SUSVKy7crHIUXZd1yDufjaThENDdigEUHtahm3gublzuY6PaRETUOqqdeLISC9TvNTrtxpqx6ZK+UzvXKWNiiKiOUlwmU6DckbREZMxM8cN+j8AVy10lS5nVpMvZSAq1XMIXSkrNIrVW9++PTERx1+HgYiHZuWQadx0O4smdfVjuVjCXLP07+908XJWoGidntX8vF1+fqtMyZ6OkkDpwK1dbrTjhPb4gF2OPXm0iImoNtSgcbVSnTP97OYC56vs2rYSJIaI6WmbiFC63ku0YWSz10TT9HgGnACai1hucTHN2n6ga+Z2bF8/HEYiVPlM3rfeUdFjGwkk8MBLC2UgajdzX+S+jUbw6Nbm48sfI/cMhzdOF7h8OYd8Of0HSCMiudNi3g3XLiKoxX7rAFwCwUHS91vWFjDgFsL7Hgce2+7HB58KeI0HN2mrX/mAKQqdZZ+YKE1st0sUioiK1KiJfXB9IPb4+fxWS2UM8tLa41nM7faMwMURUR2aWXrfaToiLMYlKm6wxhiUii9TOjdYsmt7SaKsnlrmV7JZXrRDmdQBdikBIo35asTSy20XuPBzEUzv7DJNDRtvFtq/z4smdfYtFHv1528yIqHJmV+N5G1iWJyWzceOBkRAO7nTq1kEymlCbismarDQgouaqRxF5vdiw0mNuFXJxbaJ2iTVMDBHVUaDVsj4mVPM3UgNOO2TViZol//m5wu/EB5Y7EU7KkqXR+a/7ZdDaNk690OUQwPc/1Yf9p6Kap4TpSUtgz0uz+OVvewv27286H1xsc7kBarsVeSSyg307/LjzcLBgS5dDYzXee/ON78+oqwKs1lYDgDVexXClgbo6gP0QInurpnC0Hr3YYLS1VaU1AVerVU3NxsQQUR2di+is0e5Qy9xK22TViZphLJzEbYemS07geWbXqoLnR+s5q4a6tUNdpTPQ6yypdTTQLbBlZZfuyUVT0UzJ/v3jc9HF55/bxYgab6DXiVVdwIW8x3ZVV/Z6Pplpzmask7NJ/L+/3oeXzkdxIWb+6y7z6a80ejecYj+EqEXUo4i8XmxY7RFwCEdh36ZHwdUrXIikJHwuASmBPxyeLUgo12NVUzMwMURUR/OtUjioQYZ8jrbJqhM1w0OvhgqSQgAwPp/BQ6+G8N1PLp34Z3XrWDnXr+nC07v6Fz/WKuR472Yv9p+KQkB7C5oiys+qcbsYUWM98lq4ICkEZJNExatqNA5YbYh35tIYj6QwrZ1v1tTjFDgTTmFKp9EXoplcvbUl7IcQ2ZPZwtFW6K1C2rjMhW/l4t7oxQg2rexd/F5aE24vnYvC4VB0Y001q5qagYkhIpMq2f5Up0M8WlZGiLbJqhM1w08DCcPrapw6/J6FqXUTjl5IYMuBwiLS+YUczaxQ8ruA0TntLW1qoVhuFyNqLKNVNTc/PVWSNGo0RUrcPxwy3OIhANy4rguBcBTvxhyYT0kcC2RjilMU1iLa6HOg26F9s+KC1UTUOHrbzIHSwtFW71k8djNahaR+r9OnL2JoaHDx81oTW9n4qJ81v3Zla52cysQQ2Z4d6tFoDXqOTsawZWUX5pKS+9NNMsqct1pWnVqXHWJK5fTW44iabx/LpxaDvfNwEDtWu5AWouC9M7NC6bJlLlzQmVV7PZjCniPBFvu3IGp9ejPn784lEWhyUggA+rwOBMvMsq32AH+1fTn++Mg83owU/n1SEhjsdWBDr2NxpcEdz13UvM9UA09eI6IlRtvMK+0TlCtdYXUVkl4S3cjXfraA+z64vKL2NwMTQ2RrdqlHozXoGV+QGF9Y6jVptavXJRCMs6MBAD3O7GqB1R4HBnqUgu0w1e4VJjLLLjGlUttWuXBovHS0tm2VueSMGQJAv0cgEJMlKai0BI5cWJpVPzoZwzO39pvqMF2IZnQHePEMcGC0+o4gEVmzd6sPRydjGF9YetoHugUmo/bouzy8tQef/0kYRgfOX4hl+2mBuPbs/IZeR8FW2NVepWQrGZAtWE1EjVePMhPl7lm86rl4wrBYJUXw4y1WUoQRkGzN6KFuJDODHq12fbS/q15Naik9ToH5FHB8OoVD43EkUxms71bgdwkM9jrw2HY/B4LUEHaJKZV69Do/BrpFwbWBboFHr/Prxim/S2DXgBt9bqH5eZVLAOu7FSxzZGfOzXRnxhckbnpqSnOQVexsJI1y9fhb6d+CqG0IUfKxXcYzn3t5DlETjZlcSKPfba7Ox0af9rz4ZTrXiai+qikzMRZOYs+RIG4/FMCeI0GMhZOW7qlOGB4YjWJ4MoEDo1HcffgizkUL4+LerT6scZv52yzparHNEEwMka3ZpR6N2Sxxcbsevc6PNZ56tKi1FBfhvhAHzi9kEEpKnI2k8cBIaDGQE9WTXWJKpTb4XHjm1n7s3uTFDWu7sHuTF8/c2o8NPpdunLr5Ug9+a5PbcPWiAuDgzj4M+RwIWXwrZhLZpI/TOO9kWqv8WxC1g0deC2sWtLeLlDRaK7TE5xK4e3VpHHIK4N7NhXXL9m71YaOvOFnElctEzWLlSPr8RNBnX5jGbc8GSpI6Y+Gk6XvqTRg+frYwUTweSWFau8yjrquXt1ZmiKlxsjUrgaKetIqUadFql0vRqwlCKp4GQo1il5hSzErdI73lz8tcAgPdomBLiHo6z56Xo4bfPwPga6/N4efTZZb0GFBreYTi2aRvOQokMijNJvlcNcowEbUhowKtlTgTrvyZtxMpgYNTjpKVTikJ7D8VLTjdsB6nHBFR5cweSW+mlqI6pjB7T70Jw0CicP2MXhF8R26Yp3UXt4uJIaKaMftQ11txJ6LXKfD6TFK3To7acXvxfBwBFjM0hasEqBGsxJRKi1Sb2ate/PpK6h5pfd1Aj4JdA10IxNJ4azZVcDpPOT+dSkGpMiezodeBtau7cGDUOBEF6CeGfjadQyg/qwAAIABJREFUwO2HAi1YGJyo9vLjia+g71F5gdb8e/5ypj0SQ8emk4gmtYc1L56PlcSUSk85IqLayx9nFR8Tn89sLcXJhbTpBLDehGF/V+HKydm49kpKAWBFri5jsWZPOlrFxBDZWiNmdYwGcUYDQ/Vzxe2q58lA7YyrBKgRzMaUWiZrjgUS+MvNAkPQjilWiy4WJp5Lt4Bcv0ZBb5eCYxZX/2QAuIuOdraq1ymwd6sPL56PlU2KS42kEABMRCUmotn12ixGTZ3Myuy42SRHu/ZRsrFQO6YEYhKBScYUopZg0HUwezKYmpAxkwC+d7MXPzwTLej7OAVw9+rC79XrEpjTWA2dktDs72htY7U7JobI9uo5q2M0iOvS+NyzZ2P4wAonNvqc2LvVp9muWp0M1I4EgFVuaB6BO5+wT00Dam9mYkqlJ2Tofd3v/sKNj16YLllpeCyQwEqPdrk/rVV0Y+Ekbns2ULBdTOvrolrrnU3QOU3eNCGAY1Plk0IAoAhoLsvOl/+eV7qCi6hVWZkdr/U92xW3rhPZj9nj6s3UfLW6s2T/qajmFtSDUw58BkuTcfNJax0krW2sdsfEEHUEvQGFUcEx30zp59RtGccCSRydjGHLyi7MJWXBPc1mszuRQwAQCrJrEwr90mrFW6I6qrRItd7XBVOK5jHzZ8Jp3eSI1hLkB18JGSaF1K8bntDIvjbAv56L49n3zH3vDy9LYzrjLjtInVxIYyycxM5npjGZl7l6eSKOw7etYnKI2pbZ/sTbsynsOWKu3hD7KNy6TlRr1U7cmJ2M0yoHMNCj4OoVLkRSsqKdJUY1hqpdYdlqsYaJIWp7RltC9ILBcNAJb9h4cDO+IDG+sPQa9Z5mTzDrREICemtEZ+IZ0x1bonqrtEh1Jc//ao+AQzhKOjqRRKakLsaxaeN6QepM2U1Pla/xUw86W/BLDPQo+PL7kti4cf3itr6xSFrz2Pu3Z5P41I+mMVW0bW4ymsEXRmZx8Jb+WjSdqKm0BlZm40kglsGBUXP1hpbpbNv2OIBYa41hKtZqdT+I7KzSrff5zE7GbfC58Nh2P+4fDiEUz8DvVrBvh7+qVTlGNYaqXWHZW6vjWhuEiSFqe0ZZaL1gEEkLRNLWlgwaVcGnHAF8pL9Lc0VBSsJ0x5aoGmZmtiotfF/J89/vceBbN/kXEyQ+l8DxqXjBCqOjkzE8c2s/9BKrTgH85kbv4t8lI+15GuINa7sWZ/QSk5GSE9a0Zuay29K0/y5HL1g8O5aoArU+CUzr/loDq8e2+y3FkzPhNK4/GIBTAMt1BkxSJyy0a1LIWVQ3TY3jIxNR3D8cwmw8o/teEVF5lW69z2d2Mm4snMQDI6HFSaRQMo0HRkI4uNNZcUzW6rf1OAXGowouhGMV3VMlWisvBO3CBkRtxCgLvXerDxt9tZs5yq+Cv3uTlw9YEQng6x/1Y61X/51Rf5kQ1YM6ADswGsXwZAIHRqO4+/BFjIULV+LkP8c3rO3C7k1eUwnL/K/r95jrEQixVPfo6V39kBK4UJQ7HV+QePCVED7S36V5j5sH3Hjixr7F9sUz9ksKAcDTu/oXC27fd8KNf/fjaXz2hWncfiiQTaxf04PBXgfMRuUUS5NRneXHjONzDt2YUQ29gdX+U9GCOLTOWz6mLKQk5pISZyNp3HU4iJGJwtWDU+2aASriFMBgrwN/e8Oykjg+HknhrsNBnI2kDd8rIiqv0q33+bTGY1qTcUZJqErl99u2rXKix5ktHfJGxFH1ydJhjWLVdsYVQ9TSzMz8G2Wh808oOngmCq3n160AV/c5c0c/G7enOLPtcwGh2vUdW16fO9updQrjQNlqe3KpdViZ2aq08L36dWb3phd3HPS2ix2bTuKF21fheGAKF/ImsdZ4sgnXAjZMmCgAPvmjKbw1k8J8SgJwAHOFGbDik0HKceVCLgtTU71UMxtu9ufSaGCVH4c2ffe8pbanJHD/cAgndi+thDk/b8PgUAcpCZyNpPHIz+YXk/rqv8dT72oXmy1+r4iovEq33ucze1x9uSRUpX0BNc7uORK0fKKrW8kepKHVd1Hfg1bpo9Q9MSSEWAPg+1LKG4QQLgD/AqAPwLeklN82e63e7aTWY3ZPq/YSQWB0LrlY0+aJG/vwr+PnEUyUPtU9LoEX7lizuOw4FM+g2ymQkZmCwZma2R4LJ3HzjwoHbpQViknc8dxFU8VzieqhFjNbZhV3dALpLs0aOkcvJLDlwGTeVga95yN73eUoLOCe/bjolTbcSZYBcCxgnCm3khQCgM1+Z03qGxDpqTRmWPm5NDuwCmv0UcoJFRX+ild4YqFddTsFFgwCR/42/3KJ+uL3iojKq3TrfTE1OXP69EUMDQ1qvsYoVo6Fk7jt0HTBya9HL8TxzC7zh1Toxft+jwJAaq4g0gsb+ePCVumj1HWnixBiBYC/B9CTu/R5AMellNsB/JYQwmfhGlEBs8sJ1UJlg70O9DqzJ2PNp4Dj0ykcGI3itmcD+OwL04jodCzcisBYOInPvTyLs5E0QkmJiWgGQijYNeAu2WbyheEZJoV0xAHNgXG+Sn6ZEBUbmYhiy4FJfOKoF1sOTC5uEbAys6XeY/AfzhfcA8gO+vYcCeL2QwHsORLU3VaidnQevzqOfTv80KpDqM5sq1sZ9LaLfaS/C4+8Fi7o9ADA+HxmMe6p7bJ4qmrLev9y/dMluSWVaqHS2XC9n8s7nrtYEjfMbqOwmjgFgFhaYs+RbGzZcySIuRbb2lBO1MSbMrmQNlVENilRNqYTUaFKt95XwihWPvRqSLN/9NCrIQDm+m168d7rFFjtETBTIMCV28b6uSs8uOO5i7j2B1Mt00cRUq8KXS1uLsQyAALAk1LKm4QQTwF4UEr5SyHEgwBeBfBFM9eklP+m3jcUCi02+vTp03VrP9nbf/y5G29ESh/gq3vT+PaHl7YnnIsKPPCmG+OxyvKgjty0e1ojHHy8L4U/v7Kw+On2EQ8SktWFrFKQwc39adw3mMIlXmtxadu2bVWVd2NMaS/HZxT84ZvugmfWAYm/uSqOtR5ZEg8GPBk8dlW84OeuFvdQ7/PVd1wIpxSkpEQsYxwbukQG163I4JdzCqZTS69d25XB41fH8Senu3B8rjTuXetP4yvvS+Den7sxm27X+CMBjX+PJ95z6b4nj19tfLqknmpiCuNJe9HqQ+g97/nuO+HW/LnMt6Yrg7+9Onuf5yYV/OloFxIZAQUSvU4gJQWcQiKSAjIQuXWClf1oOiA1+zGd4Jb+JAJxpcy/R2F8MfNvbAVjCpGxc1GBx886EYgr6HdndMcD+f0qnzODh9+XxLUrMtj5igfBVGn/p8+Zwbc/FDcVx7XifeWxszCmFGtWH8VIXbeSSSnnAEAsleTuAXAu9+cggDUWrmkaGhqy3K7Tp09X9HW1Zpd2APZpi5V2BF+bgFYhjYsZV8ESxD87EsR4rPKCgkbB4OiME198p7tgv2h65Jzu60mfAgX/dPulpl5bz59Xq/e1y7MD2KctzW7HPQcmkUbh7EwaAv91rAcndq/FMxuTiyeArdXZ6613jy+85cGabgfGiwq4jscUfGemD09sWao5MjIRxQMjwbxZ/vK/xxNSwUtBBQM9CnatdSGSkgVt/M5MEMfnSuPZppW9+PrZJGbT1vbGt5bC9y8Nga/8qhtepwBQuhJg08pe3eXo+ewUT4DmPz/57NKWZrZjCFiMGUa1L1RqLYmziTjKFfu6kFDwH1/3YssKF4anklB3eWUgMLv4KNem/9+pSaGNPge+ceNqPPJaWDN2OgXQ5RBYKAqdWjHdLMYUe7cDsE9b7NIOoLltGQsn8cWC7VYOnIx5SlYejYWT+MYvLmIinn1dJO3AN8524eAHVsLhnNY8kcLhdOI7Mz0lY0GtZ7w43uuVADDHOOau9nWb6qMAjfu3aXTx6QgAL4AQgN7cx2avURur5CjYqM5xNOp19Z6H36vfvq6kBIYnsyuG1OOkXQqQZu1ky/iWUa3M6mz4VutHmCkqrXePeEZ/O+Tz78UW65Zt8Llw/3Cooq0fQHb58/VrFPzjp/owMhHFHc9dxGw8gx4nsNarYDK61D61ZtpxiwUTm894Ns2MQCz7PugdSU1UC+ORFF6dSiAYVRBIJzAeSWn2UcwWnM83kwCOXOC2pXpwCOC3LstuNx2dS8KjALG80C4AeBxAUucURx6EQdQY5Yr8q2O6F8/HF3/v57/ujucuIq3zHG9b5bJUKy6/1tEX3/FWkRgyZsej7BudGDoOYAeA7wP4EIBXLFyjNlXYkXLg+FzUVFEup1JYgDX/eiWds2qpx0mv8wqcibTXHv5GcNgwQFJrWu5WMJcsffb9bvNbrHqcwJzFsVooKXFgNIqjkzFsWdmFc1V2JiYX0hiZiOKuw0urjuaSgAKJm9Z1YT4l8cvcCV+tlxSqrZTM7unf0OvQXQVGVInCZ1AgkqsH9uTOvlyx+CVm6thQ46Ql8N9e158clAAiBqHT52LHhKgR9BI3z78Xw2dfmMaJiwnDg2v0kjcD3QKPXufXreczFknj9kMByydb10JxgssOGp0Y+nsAzwohbgBwJbL1hM6ZvEZtqtKjYLetcuHQeOnezFQmgzueu1i3DK+RY9PJskfak7Y+C4N2omL5R4Fu8jkwHkkXpI2dAti3w6/79cX3SFdxrNf4gsT4QmX7xvOt7XZorjrKABgNp/HR1V34aZlTvuyttoOuaEra7SA2agNaz2BKAnceDqLHKbDcrSyeKKg3uKHWVMcyrESURy8BE0pKPPue9f5Uv0fBTevdi8kerZPTnCKbUFLHi3onWx+djJU9TbkSF6L2Sww1ZCQmpbwp9/8xAJ8CMALgk1LKtNlrjWgnNUelR8E+ep0fA92lA4uZRPmTr+olEMsYHptK+gZ7mRiiyqgrBA+MRjE8mcCLEwms9ipY5xXodUgM9jo0Z/eN7jFlYiZnsNcBf51mlNWtUHpb2ibm03XdJtuKArEMhicTODAaxd2HL/JUIaqJqXnt/kRaAnNJWXCiYD1nl6nxpnl8PVFDaJ02Vo0rljvxxI19i0me4pPTBnsdJQl/3ZPC6rTna5nTfuPFho/EpJTnpZTfk1KGrF6j9lTpUbAbfC787cdXYLDXoXkENLWWfg871FQZrVWHk9EMdqzz4N+uj+LE7rWGSSG9exgZ6BZ4+paVuPlST0VtNjLY68Bj2/3Y4HNhuc5KumRuUEra7HoULLWeRPmXICWBTz8fxHwyozlhRa1pLMwl4ESNkJ+46XWY69v0ewTWd2v3kbS2gaq1g57e1Y/BXu0xx+RCevFY+/tOuHHHcxcxPl+fBPFcyn6/KzhFT02nlSU2Uzh0LJzE516exdlIuuICr2QfesXEicqpdNWhmXvoys0g7d3qw0BPbX+Vno2k8cBICGPhJPbt8DPxXSEWjqVaECb7F/EMslsehMCuAXfdVhNS48zE2LkkahQ1cbOjr3xCdqPPgRdu78eH+rRrCarbQNUkz+2HAthzJLi4ktin07FSpFxcPX58zlHXHSh2XGDa6BpDRCU2+FzYe00PPv+TMGKpDDxOBXuv6SlbOPShV0N1y+JS452Y4cwcVUZv1eHx6SQ+EfCi7+eTizVArN5Dz/h8BtcfDECBLDnmuBbUUzYGex3Y2ufA67NpJNLZqkeMeuaUW3VKZIZTAdIWHjr1RMGbL/XgwGjp8ejUOphaJmq8u1en8cK0q2DS3yGAHatdyAhRcMBEWGdlQCQlNQ8iUusIRdPaXzcylWzYYoOzNhzDMjFETTcyEcV/enkO6dyJHwspif/08hzWdjsNB3I/DZhZ4E2tYiYuC476JjJLq6gggFy9r+wpQnceDuIpjTpDasHpM+EUvA4gamEkUO96YvlFEcmagW7B4+qpJi7xAKML1r7mxfMx1htqA138J6QOk38Ix7puB+7d7MX+U9HFjxvRRz84VVr/Jy2B1T3OkkOJ9OLs27NJzYOI1G3mb85o1yBs5A4UxYbV7ZkYoqbb89IsihO3aQn85vNB3HWZVzcIpTL6D5QiAINPkw1JAAdGo5qnAlBrUDsUo9NubDrfuCSfujf9kdfCmFxI41ggUZLgSctsrPnlby8lhrRmk6hN1KlYJHWedw0W/bhEtt5XsUBMIhDjKthWd5lOHRKidnQuKvDFoj7RD89EC5Iljeijv7egvT3/zFxpMkfv1LBATEJvzd/kQrpk3GlVrwNY5lZwfqHyVT9eG2ZhWGOowz3+xixW7j+Hjwx7sXL/OTz+xmzD2zClc1xfIoOS02Xy94oazewzKdS6WDS2NeWf6nV8ztHwk6HyiwomdX5Pq7FmZCKKLQcmce0Pplo2KcRf3sbG5zOMI1QVtb9h1J/YstKJHht27qk2fhVKF9QlIWpnj591lvSJTJ/clUevro/Zz53SSQxN6dX8sjgRtLbbAQeqGyjOp4ELVSSFACAD+01g8ddZB3v8jVk8+NP53EcCaYnFj+/74PKGtcMhjJfuqUFo71YfZ/c7hNasANmb1qle6rNbvPS3HvKXP+sN5BSRTQrddTjY8gXr7bcz3X5YfJoqZXY14fHp7KqgHqfAlSuceDecRiDGp7NdJMGVzNQ5AnFzU05Gv1uN6voAMPk57YTJGq+y+D3U/t7ZSNpSvdmBHgV7t/rw/HvV1X/TX49kXihhv44oE0Md7MvH5nWvNzIx9H6fwImQ8cNxcjZp+Thpal3nbFiQjYzV4mSwSo2Fk7j56SlciBu/zu8C7h8OtXxSiMxh8enW16ztqVb7G/Mpict8TvR7lOzJZNRWGjnJQZ2hWbHNSL87A6D8702j361Gk4Tqn81+rthlPmfVJQDG5zO45vtTtphcU+y3YIiJoU6mt7+y2n2XVk0nBVBmSd87c2ks6+LmiU4R517AlqNXALARg/M/enmmbFIIADb4nDgVYnK5EzgEcO9m/cMLyP7Gwknc9mwgVzvCgeNzURydjOGZW/vrPoDSS3Qbef69GLrZq25bXIFItVKY3MjGNjusSrtvMIWTMU9B0sVZtKtjo89heLCD0SShXs/e6HOqgW6B+WQGn/xRIFc/qHLmk0ISN67pwvCFZF1OKOyx4dwVR9odzKGTqdS7Xi9zifKPqCIlT/ggsrG9W30Y6C4MHo06GeqVgLmth2ORtKnVQh9crliOg10C+Ei/C91OG04BdaC0BP7mTe1VsdQaHnwlVFJQdHxB4sFXQnX/3r4KnuNQUmIiykmNdsUViFQr5VbVNMslXomDO1di9yYvbljbhd2bvHhyZ1/Bx+WSV0aThJV8rt+jYNeAGxACz74XrzopZFW3S6lLUggAhA2XDHFuo4N96YMe/LfXY5rX621kIor7h0OYjWcQMXFwR5/XoXkktUM0foUT1Z+bKevWJIpW/zXoZCizMcBsh2IuJXDVCidOBM2fKpSQwCq3go29Am/OMijZwStTiWY3garwypT2MkC967UUZceC8pRbJUGtww5buEZ16mjaob6mepBHvu3rzK++1Rqr5T8/xZ9TVwJNxTLwOIBYXhZmrVfB4dtW4ZHXwmXrCA32OrDGq+CNYNLwcCKrDo/X7/eN5HH1ZCfvzmsP2vSu14rV4q9OAezb4S85ktrnEjgeiONCaW6LWtwldlxfSYa0fnGrJ0PVuy5Dn1tonlbhVoAeRwbBZGmmsdspsKAThELxDD662mMpMQQAPz4XR1ejl1ySrojWOeLUMsI6eT2967X05kzzB2hkD91Ogb3X9DS9/gtVzy5buPQmqXRP3dKRX4R5XbfDFnWKisdqa4valf+5XqfA6zNJ3bpsk9EMxiMpnJwtH48f3tqDey73Lb4nkwtpvDmTRDBeTT9A1LUWkddpv1lwJoY6WLOKxVop/jrY68DDW3uw/1QUX/95BMtcAlJm1yS8MZNiUqhNrfYyMdRqmll8+srlTkxNlnYclrmASEI7UXPlcgemYhJnI6Xt87sVzVmvclISSLGytW1IO1SXpIrpPXmNqPSSYp07yllISex5aQ5ru52WVk6Q/TT79FTVaq+i2fdQT90yw+j0Lzskh/Tez/zP7TkSLLsS6K7DQVMHy3/1tXncc7mv5P4HRqs7fayeVnnslxiyX4uoYZpVLPaihTV+T9+yEo/8bB4HRqMYnkzg2ffiODQex/BkQjOoUnuw4epKKmOZSzsB49O5XkspnaNNA3EgKrU/NxWT2LfDj+JSIsUrFHdvat5AgPPT1entanYLqFV5HOwe05IMgN8/MtPsZlCVmjmBlW+jT3tdxmU617VYrVM0Fk5iz5Egbj8UwJ4jQYyFa7sqspL7mynyn5LmygWE4qUJpr1bfdjos+9E86wNj6vnb74OpvXANGIftTRZd8QtrB8ZS+0hwlUXLWd6QXvbld71WqqkMH0kkcHXfx7B9tUurO9W4HcJDPY68OTOvsVZYXXmqVk1r7iZpTof6mNqrZU184CMS3qtxxSBbBF6ak+NLnpLtdfM01Pz1WL8ZaVOkbq6SJ1kPzAaxd2HL9YsOTQWTuK2Q9MF97/t0HTZ+9fyUKGkRElSaoPPhb3X9Nj2UJDVHvu1i4mhDpY/I36tP22q2nwtvG+ZuUDgcIiKjoyl1sfTP1rPL2a0n1W967VUyaxQMCExPJnAkQtJuB0CL93VjxO71xZsFVBnwNz8cWxJ3S52cVrZCp0VX3rXa0lvRt+IUwAfW8NkZLvifFXra9aEeLFajL+s1Cmq9yloD70a0qwx+dCrxidI1nJFz0JKliS9Riai+NzLc7r1JAFgeZfQWXNef/0e+3UuWWOow6kz4qdPX8TQ0GBDvuf7l7tMFXW93KfwiPoOtNar8PSPFqS31LcRh/sUFzscmUxYKhioVWNAa/8+tZbxef7btbINy1wIBEpnnC9bVv/kSyU1xlZ5hO62Vmp9Nl10QBbk9xVGL0awaWVv0wo2Vzv+slKn6ExYe8z1rs51q34a0D4RQL2eXyRbrRUbTkms63bgse1+7D8VxfPvRREqs4Cp2yngEkCXIiGEgnhaIilRkvhR+3SvTiXKJnSXdSmIptLQ2IlWd8enk7j9UMA2hcMBJoaoCcx2uK5Y0VVR54xam3oKgR0CJJm32qvg/ELpb9bVFoopViO/4OCm757XPInCKYAVbgWBWGk7i2sM6G1j7fcIzCWkZidCAKaKJFJjvDPH3xutbKPPiWNaiaEKVvNYlT+AfPF8rOw2IgXA/33jCuw/Zd9Cp1Qd5oXaQzMmxOvBSnycimpnPS7oXLdOr/cjyk6yqQWzJxbSGJ7UP3Jyo8+huarqN56+gOPTpQmuQ2NRaHT1Sqz2CMzEBeJNOHBgKpbBVO7vbJfC4VxnTQ2Xv4TyhrVduGldV8kPolMA92722qIALDXe7/xrsNlNIIue+PjyktofDpG93mgf7dfea/KpS9y4ab1b83PF2xf1trFesdyFjE5ng0khe1FYxb6lNXvbhzqA3H/TipLVIg4A/W4s1iZ7+pZsbbJ7N3u5sqRN+VhAimzESnzs16llU6saN9tWaScztq1yla0Vq67u0dsh0u8Rhlvt9JL2kbS57Z8bl7kQSza/r1DLrX3VYGKImkLtcD29qx/9XkfJto+UxOLMm/ra93F3UceYYdXdlrN9nRdP7ezDYK8DvQ6JwV4Hnsor5NxIj17nx0B3YYdnoFvg0ev8pjtTRkUquQ6lNfR5uRW5lTWrDmKx/aeiJQOMNICbLvFi7HfWF9Qm03ottYctK7jJguyjeJLdKD5u0tl+u7FG23KN+lxmasVOLqR1+2Yv3N6PJ27s04371axKV/t+wibZkLeC8WY3gVvJqPnMHh95Tb8X74TNL9NWAHx8XReOTCSqmslf7RGaxdyIqND2dV6c2O3F6dOnMTQ01LR2bPC58Myt/bp1BPLrEa3V2duttY1V7UQ8PRZFjNkh23t4a0+zm0BVssO2DytHXJsZBHU7BaIpablfsqXPaao+I9WH12mT0SNRTv4WeiNG/ZlatUPtcxX3q8zUil3b7ai4/pPelrp8bgXwOAR6XAJDPgcyQhS0sdcpELTB0fGjkea3gYkhajqzx0dqBbaBboEtK7sQTko4BHByNomFFOB3K9i3w4/t67z4wa/C+L2X5gzb0O9RcJnPgdcvJgv2pK5xA8/f3o/tB6cQsdgfu/VSN96YSWkWhyNj7H5RtYwGlGY6U8UFrfM7EZv95QdobiVb1FCrnlEjeR3AVSuc2LjMhVsGXPjqa/M4G0mhEypmPDeexD2XN7sV1OqsHHFdbhDkFMCBT67AXYeDmiuLBLJFrLW2R7x/uQtvBVPQGwLtGnDjZxeTmKxZ3RDKF+FSMGpRRv2ZWn4PrX5VuVqx+QmqSiYCzNSivfMyr2Gf77o1XXj2PWurdRTA0iEnZjhsUJCAiSFqOrOZ7EoD2z2XZ+/z+Z+EdY8svGm9G0/c2LdYOb84W93ncSBiIcEz0KPg6x/1YzySKukACgBX9zkxm5Amk0YSgMDyLkBKoVmBv914mBkiG9Dr6Jg5WfHX17sRTkkEDIopaulxACu9Djy8tQfPjSfxwngUM9ZugW6nwLWrXJox8p7Lffin/+9X+IM3PTXv1NiNHZZlU+uzMtuu9VqHyCZo+zyOxQkrvWL967oVbFrm1IwbkwtpfGyNC0culKaGblzjwj9+atViH2ZyIQ0HJE6G0lhISYSTsu2f93rTSgQStQqzq4vq8X3zx26+3KlkkZSsSYIq//7vhlP45UwK83ljJDMro77+UT9OBKcxPr8UJb0OYJM3jStX9+LezV7sPxUtGXv2/9053UR9JVbY4Ph6Joao6awsH6w0sN1zuQ/3XO7TrI5vJlu9b4dfd4ZP1QXgQ/0uXOZzLrZ/g8+FJ3f24f7hEELxTMFKJvPHYWdn9le4sxX5AbT9Mdrt+zejdlBuhkrdW2+2kKDPme0QqLFBdc/l2WNeb3ukvdK1AAAPCUlEQVQ2gPGFpeCzsgvocigIJTIo3rmirkgwqu107YoMnr4lG5fGI2nNAWOfWyCSkLDB6uqK/SrMoTBVz2ofxcwE1hMfX447DweRznu+1GL9eiebqfe6+ekpXMjLea5xA399w4rF76/VRxr6xwnLqxe9CuB2AKGk+cL6g70OrPEqeD2YbKvtto0sek7UbuqdlMq/f35y3GziaYPPhWd2rSr5usTku4tjQa0+VU+XwGyNOklOkR1rNhsTQ2QLjaojUOmqo+3rvCUJHnVGv9x91LorRm156t2o5vHX+dSK9U/c2Lf4dWfmknhzJoVoXgeszy0wn9Q+TrtV9Ljaf5sLtS6zM2Ca2197FFy9wmV6tsxo7z4AjExENRPP5ahxac+RIA6Mlg5Ef+MSD/Zu9eFjB6cw36JlTaJtNDCl5rLSRzEzCFKL9Ws9uwO9Tt0VSht8Ljx/x2rLdTi2rXLh0HjpCrq+LoHfGPDg2pUKvvazBcRTEm6nwDc/5ltcba3SixX5bVSL3xYPzhbicTxzrjU7Jbs3eWu+7YaI6qPSJJTW152eNP4al6g+KeR3CUt9t3pjYog6TqVBQyvBU239CrUt926Oll2RBCwVuzSbHVcHjTOxNMItNLjTO26cyC6s1imyMoiz8r30Es9mGW2T2eBz4Sd3r17amiKAlyYSmiuMHAIFqx+IyJiZSSOt3+uVTKQ9ep0frxetPBzoFnjm1v7F+973weWG99CKFT1O4DJPdruFVhuLjUyU9nXUg0JGJhI13ZZRK83YfkNE9leLCfix31lf/U1qiIkhIhsoXpGkV0dIa4+72UFjfgLp7dmkZnFLO1C34RC1AzucqmTE7CBUpbdC6fZDAQxbrKdERNpqvfWi3MpDs/fQihX52y3K0Vp9rcaQK/95QrPukoD5rWwKJDIdUFifiJov3oarkpkYIrKJ4iSOUS2kSuR3NMstCW8WLtkmajwrg1C9VQ5mjqQt5oZEn1fB+5e7kJbA8GSipmdycHhItKQWyaZKtlsU04shkaT207/MJRDS+Vy+9d0K3udJ4KUghzZEVH89LoF4vPJey6+tbH6x6WK2PvtHCPEtIcRRIcTeZreFqJHUmbndm7y41p/G7k3exb37tbB3qw8bfdYCkldIrKhjvuZbH1+GJ27sY1KIqAWZiSkr3QJ+l8BgrwPP3NKH4R1RvPWZ9Th4Sz+e3tWP39pU2/31q9w1vR0R1dFyt/aQxO9WsGez8fZytXD3fKq26WA/c0xEpKOashcrXcATn1hZw9bUhm1DnhDi0wAcUsrrhRDfFkIMSSlPN7tdRI1Szy0oxUvCHQI4OZvEQgq6hbWzy8WH8INfhfH5n4QRT0koAIQCpDOAEChbIymfC0AG0C10SUStozimJDIZ/Hw6hVRG/xk/XfQbvdxpb1r6PQJXrXDhxYnCbWwCwP5PsDYIUavQOv1VPaknW5Q1gCdOLT3nvU7AIQoLt/a7MwBKE9SDvQ5s6HXgXDiB0XnzbfruJxlDiEibVu02rwP4YJ8L/R4FR87HMZ/XnXEC+PAqJzYuc9l2d4SQ0p51RoQQfw3gOSnls0KIzwDwSin/DgBCodBio08X9yyJqGn+7KSCA4EuqFUBPACcDgEXMhCKQCIj4HNm8PD7krh2Re1OKNm2bVtV04SMKUT2cC4q8PhZJwIJBT0OCUiJ+Uz2zycjCi4kllYVDHgyeOyqOC7xShyfUfDVd1wIp5SaxJhqYgrjCVFlqn2Oz0UFHnjTjfGYdpww+l6fWZPEP12oXQwpxphC1H7y+yz9XRncN5hajDVGn6tWteMePXZODH0LwF9LKX8hhLgZwFYp5aNAYYCsxOnTpzE0NFSLZlbFLu0A7NMWtqOUXdpil3YApW3x+/01SwxV25Zmsktb7NIOwD5tsUs7APu0xWo7jE5grHU7qokp7dJHAezTFrajlF3aYpd2ANm2dK29rC5xwmo7GFPs2w7APm2xSzsA+7SF7ShV63GPHttuJQMQAaAWHOiFzeshERERUf3U+qQmImo/jBNERJWxc7LlOIAduT9/CMC7zWsKEREREREREVH7sfOKoYMAXhZCrAewC8B1TW4PEREREREREVFbse2KISnlHICbALwC4BNSylBzW0RERERERERE1F7svGIIUsoZAN9rdjuIiIiIiIiIiNqRbVcMERERERERERFRfTExRERERERERETUoZgYIiIiIiIiIiLqUEJK2ew2WBYKhVqv0URUd36/X1TydYwpRKSlkpjCeEJEehhTiKhWKh336OGKISIiIiIiIiKiDsXEEBERERERERFRh2rJrWRERERERERERFQ9rhgiIiIiIiIiIupQTAwREREREREREXWotksMCSHWCCFezv15qxDiBSHEiBDi/8hdu0QIMS6EeDH3X3/u+reEEEeFEHsb1Za81z0thPhw7s+u3McjQojfbUQ7hBBfzXs/3hZCPFSPdphsyyYhxL8KIX4uhPhK7loz3hOtazVthxDCL4Q4JIR4XgjxQyFEl9bPodlrDWrL4vuW+7jh74nWa3LXa/4M5+7LmGKxHYwpnR1T7BJPzLalU2OKXeKJmbY0KqbYJZ6YbAtjCvsoarsYUyy2hTGl8THFLvHEYls6K6ZIKdvmPwArADwH4LXcxyMALgUgAPwEwEYAnwZwf9HXfRrA/tyfvw1gqBFtyV3/9wD+e97XfQnA/5X787MAfI1oR97rvw/gklq3w8K/z18A2J77/DCA/ma8JzrXat2OPwDwqdyf9wH434t/DrV+Nuv082qmLQXvW51+Xs20o/g1d9bjPbHws8KYwpjCmGK9HXWPJxba0nExxUw7ctfrGk+stCXv9XWJKSb/beoeTyy0hTGl8Ht2XB/Fws8KYwpjStNjisnnh+OeJsaUdlsxlAbw2wDmch/3SSnfk9l37SKAZQCuA/D7QojXhBD/Nfe6mwB8L/fn5wHsaERbhBB9AP4cwIwQ4hMabXkJwLZ6t0N9oRDiIwDGpZTn6tAOs225CGCLEGINADeA2Tq0xUw7tK7VtB1Syv8hpfxx7sN+AL+D0p/Dm0xeq4rJthS/b0AT3hON10yhPs8wwJhSUTvUFzKmdGZMsUs8MduWDo0pdoknptqivrDOMcUu8cRsWxhTCu/fiX0UgDGloraoL2RMaVxMsUs8sdCWjospzlrcxC6klHMAIIRQL40IIR4AEARwGYATAPoA/AmABQAvCCG2AOgBcC73NUEAWxvUlq8BOADgbwF8XQjh02jLmga0Q/UFAA/n/lzTdlhoixPAHwEYAPC/AKRq3RaT7dC6VvP3JNeO65HNSr+L0p9DrZ/Nmv+8mmmLxvsGjbY04j0peI2U8hUhxB6911WDMaXidqgYUzo4ptglnpRrS/FrOiGm2CWeWGiLqm4xxS7xxEJbGFPy7t+JfRSAMaWKtqgYUxocU+wST8q1pRNjSrutGCr2OQBvA3gAwDdyGdCfSCnDUso0gJ8hu0QrAsCb+5pe1Od90WrLNQD+Rko5iWzW76YGtEWrHRBCLAewWkr5q9zrmvWePAjgXinll3Pf/1MNaItWO7Su1bwdudmTbwL4XZ37m71WNRNt0dKM96T4NXVphw7GFHPtYEzp8Jhil3hiti2MKbaJJ3ptaUZMsUs80WsLY0r5+3daHwVgTDHbFsaUJsQUu8QTk23R0tYxpa0TQ7kAeDL34Xdy/z8shFgnhOgGcDOANwAcx9ISrA8hm61rRFveAbAp9+dtAMbq3RaddgDAXcjulVQ16z3ZCOBSIYQH2eynrHdbtNqh07aatiNXPOwAgIeklHr/9mavVcVkW7Q0/D3ReE3N26GHMcV0OwDGlI6NKXaJJ2bbwphin3hi0BagwTHFLvFEry2MKeyjaGFMMd0WgDGloTHFLvHEQlu0tHdMkTUoVGS3/wC8mPfnvwdwQ97Hn0A2G3oCwAO5a8sA/ALZAmBvAfA3qC3rkQ1IIwB+DMAHYAOANwH8FYCfAnDUux25a99Fdtmc+nFd2mHiPbkNwCiAMIB/BOBo4ntS3LaatgPA/QBmALyY++8/FP8cav1s1uPn1UxbdN63Zrwnxa/57Xo+wyZ+ZhlTGFPMvicdEVPMtEPnPav5v4vJ96RjY0qZdjQsnph8fhoSU8q8Jw2LJybfE8YU9lHM/NwypjCmmH1P6hZTTD4/HPc0MaaIXKM6nhBiBbLL916S2SWOzWzLemSzgIellKFOb4ed2lLvdmj9HJq99v+3d8euclRxFIDPAUUsxNJXWAVRiFYWWolop2hnqWCE9GL0DxB7Oy1ERGy0EBWxDtEmTyEhQUlhkUKI1oKN1bV4T3iIKRLH3TuZ74MtZpnZPbNwT/FjZnYXWW6y385/k/+y367MlGcr62eNWbbSKbP0yS1mmWYNz5RnlrUzU5ZZcuwii0657RxTrN+TZsm0pfWzthz/d5ZZ+uRWvuNO7hSDIQAAAICNuqOfMQQAAADAzRkMAQAAAGyUwRAAAADARhkMMZW2H7Z968T2F21f22cmYL10CrAknQIsRZ8wEw+fZiptTyf5JslDOfpby++TnBpj/LnXYMAq6RRgSToFWIo+YSZ37TsAnDTGuNb25yQvJHkiyQfKEbhdOgVYkk4BlqJPmIlbyZjRu0neSPJykveTpO2Zttfb/tb27N87tn277Y22v7R95cT7F9q+1Partud3fgbATHQKsCSdAixFnzAFt5IxpbY/JjkcY5xt+2iSz5I8neTuJJeTPJ7kniQfJ3kxyf1JLo8xDo6Pv5CjSzLfTPLtGOP3XZ8DMA+dAixJpwBL0SfMwK1kzOrS8StJnk1yKsm14+17kzwyxviu7etJziV5JskD//iMj8YYX+8iLDA9nQIsSacAS9En7J1byViDJvlkjHFwPBl/MMlh26eSfJnkepJX/+W4w91FBFZEpwBL0inAUvQJe2EwxBqcT/Jc24O29yW5muR0kieT/JDk0yTP7zEfsC46BViSTgGWok/YC4MhpjfG+CnJO0ku5uiyyvfGGFeSfJ7ksSS/5qgw/2j78N6CAqugU4Al6RRgKfqEffHwaQAAAICNcsUQAAAAwEYZDAEAAABslMEQAAAAwEYZDAEAAABslMEQAAAAwEYZDAEAAABslMEQAAAAwEb9BRxDVl0oCGFTAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<Figure size 1160x576 with 8 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "grid = sns.FacetGrid(df, row='Elevator', col='Renovation', palette='seismic',size=4)\n",
    "grid.map(plt.scatter, 'Year', 'Price')\n",
    "grid.add_legend()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "在Renovation和Elevator的分类条件下，使用 `FaceGrid` 分析 Year 特征，观察结果如下：\n",
    "\n",
    "* 整个二手房房价趋势是随着时间增长而增长的；\n",
    "* 2000年以后建造的二手房房价相较于2000年以前有很明显的价格上涨；\n",
    "* 1980年之前几乎不存在有电梯二手房数据，说明1980年之前还没有大面积安装电梯；\n",
    "* 1980年之前无电梯二手房中，简装二手房占绝大多数，精装反而很少；"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Floor 特征分析"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1440x360 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "f, ax1= plt.subplots(figsize=(20,5))\n",
    "sns.countplot(x='Floor', data=df, ax=ax1)\n",
    "ax1.set_title('房屋户型',fontsize=15)\n",
    "ax1.set_xlabel('数量')\n",
    "ax1.set_ylabel('户型')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "可以看到，6层二手房数量最多，但是单独的楼层特征没有什么意义，因为每个小区住房的总楼层数都不一样，我们需要知道楼层的相对意义。另外，楼层与文化也有很重要联系，比如中国文化七上八下，七层可能受欢迎，房价也贵，而一般也不会有4层或18层。当然，正常情况下中间楼层是比较受欢迎的，价格也高，底层和顶层受欢迎度较低，价格也相对较低。所以楼层是一个非常复杂的特征，对房价影响也比较大。"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 总结"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "本次分享旨在让大家了解如何用Python做一个简单的数据分析，对于刚刚接触数据分析的朋友无疑是一个很好的练习。不过，这个分析还存在很多问题需要解决，比如：\n",
    "\n",
    "* 解决爬虫获取的数据源准确度问题；\n",
    "* 需要爬取或者寻找更多好的售房特征；\n",
    "* 需要做更多地特征工程工作，比如数据清洗，特征选择和筛选；\n",
    "* 使用统计模型建立回归模型进行价格预测；"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Link: https://segmentfault.com/a/1190000015440560"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.7.3"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}