{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "This tutorial was downloaded from https://www.ritchieng.com/machine-learning-evaluate-linear-regression-model/ and slightly modified to include the use of datascience (Berkeley) tables.\n",
    "\n",
    "Contents\n",
    "1.\tIntroduction\n",
    "2.\tLibraries\n",
    "3.\tExample: Advertising Data\n",
    "4.\tQuestions About the Advertising Data\n",
    "5.\tSimple Linear Regression\n",
    "6.\tEstimating (\"Learning\") Model Coefficients\n",
    "7.\tInterpreting Model Coefficients\n",
    "8.\tUsing the Model for Prediction\n",
    "9.\tPlotting the Least Squares Line\n",
    "10.\tConfidence in our Model\n",
    "11.\tHypothesis Testing and p-values\n",
    "12.\tHow Well Does the Model Fit the data?\n",
    "13.\tMultiple Linear Regression\n",
    "14.\tFeature Selection\n",
    "15.\tModel Evaluation Metrics for Regression\n",
    "16.\tModel Evaluation Using Train/Test Split\n",
    "17.\tHandling Categorical Features with Two Categories\n",
    "18.\tHandling Categorical Features with More than Two Categories\n",
    "This tutorial is derived from Kevin Markham's tutorial on Linear Regression but modified for compatibility with Python 3.\n",
    "\n",
    "\n",
    "1. Introduction\n",
    "•\tRegression problems are supervised learning problems in which the response is continuous\n",
    "o\tLinear regression is a technique that is useful for regression problems.\n",
    "•\tClassification problems are supervised learning problems in which the response is categorical\n",
    "Benefits of linear regression\n",
    "•\twidely used\n",
    "•\truns fast\n",
    "•\teasy to use (not a lot of tuning required)\n",
    "•\thighly interpretable\n",
    "•\tbasis for many other methods\n",
    "2. Libraries\n",
    "\n",
    "•\thttp://www.statsmodels.org/stable/index.html\n",
    "•\thttps://scikit-learn.org/stable/\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "# imports\n",
    "import pandas as pd\n",
    "import seaborn as sns\n",
    "import statsmodels.formula.api as smf\n",
    "from sklearn.linear_model import LinearRegression\n",
    "from sklearn import metrics\n",
    "from sklearn.model_selection import train_test_split\n",
    "import numpy as np\n",
    "\n",
    "# allow plots to appear directly in the notebook\n",
    "%matplotlib inline\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "3. Example: Advertising Data\n",
    "Let's take a look at some data, ask some questions about that data, and then use linear regression to answer those questions!\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
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       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
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       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>TV</th>\n",
       "      <th>radio</th>\n",
       "      <th>newspaper</th>\n",
       "      <th>sales</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>230.1</td>\n",
       "      <td>37.8</td>\n",
       "      <td>69.2</td>\n",
       "      <td>22.1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>44.5</td>\n",
       "      <td>39.3</td>\n",
       "      <td>45.1</td>\n",
       "      <td>10.4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>17.2</td>\n",
       "      <td>45.9</td>\n",
       "      <td>69.3</td>\n",
       "      <td>9.3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>151.5</td>\n",
       "      <td>41.3</td>\n",
       "      <td>58.5</td>\n",
       "      <td>18.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>180.8</td>\n",
       "      <td>10.8</td>\n",
       "      <td>58.4</td>\n",
       "      <td>12.9</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "      TV  radio  newspaper  sales\n",
       "1  230.1   37.8       69.2   22.1\n",
       "2   44.5   39.3       45.1   10.4\n",
       "3   17.2   45.9       69.3    9.3\n",
       "4  151.5   41.3       58.5   18.5\n",
       "5  180.8   10.8       58.4   12.9"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# read data into a DataFrame\n",
    "\n",
    "path_data = 'http://www.millerjw.com/dom/mgmt462/pfiles/'\n",
    "\n",
    "data = pd.read_csv(path_data + 'Advertising.csv', index_col=0)\n",
    "data.head()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(200, 4)"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# shape of the DataFrame\n",
    "data.shape\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<seaborn.axisgrid.PairGrid at 0x1a19310048>"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
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\n",
      "text/plain": [
       "<Figure size 1058.4x504 with 3 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# visualize the relationship between the features and the response using scatterplots\n",
    "sns.pairplot(data, x_vars=['TV','radio','newspaper'], y_vars='sales', height=7, aspect=0.7)\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/Users/james/anaconda3/lib/python3.7/site-packages/datascience/tables.py:132: FutureWarning: read_table is deprecated, use read_csv instead.\n",
      "  df = pandas.read_table(filepath_or_buffer, *args, **vargs)\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<table border=\"1\" class=\"dataframe\">\n",
       "    <thead>\n",
       "        <tr>\n",
       "            <th>Unnamed: 0</th> <th>TV</th> <th>radio</th> <th>newspaper</th> <th>sales</th>\n",
       "        </tr>\n",
       "    </thead>\n",
       "    <tbody>\n",
       "        <tr>\n",
       "            <td>1         </td> <td>230.1</td> <td>37.8 </td> <td>69.2     </td> <td>22.1 </td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>2         </td> <td>44.5 </td> <td>39.3 </td> <td>45.1     </td> <td>10.4 </td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>3         </td> <td>17.2 </td> <td>45.9 </td> <td>69.3     </td> <td>9.3  </td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>4         </td> <td>151.5</td> <td>41.3 </td> <td>58.5     </td> <td>18.5 </td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>5         </td> <td>180.8</td> <td>10.8 </td> <td>58.4     </td> <td>12.9 </td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>6         </td> <td>8.7  </td> <td>48.9 </td> <td>75       </td> <td>7.2  </td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>7         </td> <td>57.5 </td> <td>32.8 </td> <td>23.5     </td> <td>11.8 </td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>8         </td> <td>120.2</td> <td>19.6 </td> <td>11.6     </td> <td>13.2 </td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>9         </td> <td>8.6  </td> <td>2.1  </td> <td>1        </td> <td>4.8  </td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>10        </td> <td>199.8</td> <td>2.6  </td> <td>21.2     </td> <td>10.6 </td>\n",
       "        </tr>\n",
       "    </tbody>\n",
       "</table>\n",
       "<p>... (190 rows omitted)</p>"
      ],
      "text/plain": [
       "Unnamed: 0 | TV    | radio | newspaper | sales\n",
       "1          | 230.1 | 37.8  | 69.2      | 22.1\n",
       "2          | 44.5  | 39.3  | 45.1      | 10.4\n",
       "3          | 17.2  | 45.9  | 69.3      | 9.3\n",
       "4          | 151.5 | 41.3  | 58.5      | 18.5\n",
       "5          | 180.8 | 10.8  | 58.4      | 12.9\n",
       "6          | 8.7   | 48.9  | 75        | 7.2\n",
       "7          | 57.5  | 32.8  | 23.5      | 11.8\n",
       "8          | 120.2 | 19.6  | 11.6      | 13.2\n",
       "9          | 8.6   | 2.1   | 1         | 4.8\n",
       "10         | 199.8 | 2.6   | 21.2      | 10.6\n",
       "... (190 rows omitted)"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#JWM Dominican University insert\n",
    "from datascience import *\n",
    "%matplotlib inline\n",
    "import matplotlib.pyplot as plots\n",
    "plots.style.use('fivethirtyeight')\n",
    "datasci = Table.read_table(path_data + 'Advertising.csv')\n",
    "datasci"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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InFRHDaPYcOLvDEcPp2dErvWzHuKInCjs+TvD0eq+o+QfR+REYc7fGU5zk/B9RyOdFq6ayBE5qRI3DSC10MJVEzkiJ1UKtpZcC6MntVOiD9X8e/M3Way29goekf/tb3/D1q1bPT+fPHkS11xzDbKysvCzn/0MVqtVkgZSZAq2llwLoye1U6IP1fx783cxMrW1V3Agf/zxx9HQ0OD5efXq1Th79ixuvfVW7N+/H+vWrZOkgRSZgr2SXzgtJlKK3H1YW9+EvZWf4bPDx/DlNydgt3eq6vfmb7JYbZ8zwamV48ePIy+v+xrE7e3t2LNnD5599llcf/31GD16NDZs2IBHH31UsoZSZAl2RWQ4LSYSQopTfLn7sHhzORxdDjhdLnTY7DhafQazr5go6XuK4W+yWG2fM8GB3GazIS4uDgDw4YcfoqurC7NmzQIA5Obm4ttvv5WmhRSRgq0lH8iSeLXlPQPxbufXx04hMyMNcbGGkK3QDNVlBYT2Z2NzC0ZdkgVz9Rl0dnZBr49SfTmkGi694E1wIM/OzkZlZSX+8z//E3/729+Qn5+P5ORkAMC5c+eQlJQkWSOJhBrIYiKtXKzLu52W861o77Ahz5QTslP8UC3IEtqfqcmJ6LB1Is+UA6fLhcyMVFV+gXpT26I1wYH8tttuw4MPPojXX38dn3/+OTZs2OC576OPPsLo0aMlaSBpj1ZGtj2pLe8ZiHc7Y2OiYbd3ApB216JgCO1PtY1utUhwIC8sLERaWho++ugj/OIXv0BBwXedbbVa8ZOf/ETQ67z//vt46qmn8Nlnn6GmpgabN2/GokWLfN5n+3bfGeDJkyfj73//u9CmksKUGNmG4stDbXnPQLzbeWn2UHx7rhEGQ7TnuNXyRSq0P9U2utUiUQuCFixYgPXr1/sEcQDYuHFjr9sCaW1txbhx47Bu3TrEx8f7fcyVV16JI0eOeP699tprYppJClNiZBuKcjCtXKzLu52XDB+C1//4CF7acD82rSlExuAU1ZTGaaU/w4GoBUEulwtvvvkm9u/fj8bGRqxcuRLZ2dnYt28fRo4ciaFDh/b7GnPmzMGcOXMAAHfffbffx8TGxsJoNIppGqmIEiPbUHx5uEeG7hHtb4r/oMrUUH8jWLWkiMJ1pK2WMx5vgkfkFosFc+bMwaJFi/DnP/8Z5eXlaGxsBAD8+c9/xpNPPhmyRh04cAC5ubmYNGkS7rnnHpw7dy5kr03SU2IkFsod5JUc0Yq9NIG/x4eyL6g3tZzxeNNZLBaXkAf+8pe/xD/+8Q+8+OKLmDhxItLT07F3717k5+dj27ZteOqpp1BZWSnqzYcNG4bS0lKfHPnOnTsRHx+PESNG4OTJk3j00UfhdDrx7rvvIjY21u/rmM1mUe9L4afB0oIt29+GpaUNyYkXYUnBHKSlBBfA7i99CZ1dDs/PMdF6lN5/S6ia2qfHynbiXON56HQ6uFwuZKQmYVXhjaIe/4uCOSHri2DVN53HlvI9aFawDaHS81jONTZDp/tuDCzl50PoJt+CUytvvPEGHnnkEUydOhUOh8PnvqysLJw5c0ZcCwO48cbvPrR5eXnIz8/HhAkTsHv3bsybN8/vc4QerJuYXdDVSKr2y3XKKEX7TQCmTwnNIpLsrKE+qaHMjFSf9kr5+XEgCgkJCZ6fuxDV53u12bpQfbYenV1diImOxqBBgzB9ysR++0Lqv4Gn15ah1eaAITYOrTYHyt/8IKRpFjn/hnseS12TFTlZQwJ+PoQIdfsFB/LW1lZkZmb6vc9ms8HlEjSwF23o0KHIzMxEVVWVJK9P3/GuNjl+6ltcu/hBjBk5XDV5QLn0LIe7q2Aulnntb1nww2mQKoSInV84froW7TY7onQ6tNvsOH5aHQvz1JKnD4Wex5KTZcQwY6qqyiUFB/Lc3Fy88847uPLKK3vd9/7772PcuHGhbJdHQ0MDampqOPkpA+8PbNXJGtg7O33ygOE4ceVPz0m6ZWvLfMopt2x/W9ToX8yZjtia6pwsI9rbbbB3diHeEIOcLHX8nWillFOInseSmZGmur8FwYH8zjvvxPLly5GUlISbbroJANDc3IytW7fiueeew8aNGwW9jtVq9YyunU4nTp8+jUOHDuHiiy/GxRdfjHXr1mHevHkwGo04efIkHn74YaSnp+NHP/pREIdHYnh/YG2dXYiNiQGg/RHVQPUckVla2kQ9v7+6+oGktDIz0gDofE7z1SCcFvlo4VgEB/Jbb70Vx48fR0lJCYqLiwEAN9xwA6KiorBs2TIsWLBA0Ot8+umnuO666zw/l5SUoKSkBAUFBdiwYQMOHz6M8vJyNDc3w2g0YsaMGfif//kfJCZq9xtdK7w/sClJgy4ECVY+9ByRJSdeJOr5/aUZBrKASq1BJpxKD7VwLKLqyB966CHccccdePfdd3Hu3DmkpqZi1qxZyMnJEfwaM2bMgMUSuKRq165dYppEIeT9ga2rt6gyQCihZ7As+OE0Uc/vL80wkHyyFoIMSU/0DkHZ2dn42c9+JkVbSEW0ECDkqrLp2Rdiy137GzWHUz6ZlNFnID916pSoFxs+fPiAGkMkhlauVtjfl6J3oI+LNaCt3YZbfl0acdVCFLw+A/lll10G3YVTPiHcKz2J+hOK0XS4lLh5B/qeFTJq/XIidekzkD/99NOiAjmRUKEYTYdjSiJcvpxIXn0Gcu+l80ShFIqApdaKjYEIxy8nkp7oyU6iUAhFwNLChKxY4fjlRNITFcjPnTuHHTt24OjRo+jo6PC5T6fT4emnnw5p40gaargMJwOWf+H45UTSExzIzWYzZs+eDafTidbWVqSlpaGpqQkOhwMpKSncs1ND1FDtwYBFFDqCA/mDDz6ISZMmYdu2bcjMzMRrr72G8ePHY/v27Vi3bh22bt0qZTsphDih5ksNZyjhIlBfso+lJXhjiU8//RSLFy/2XBPc5XIhOjoat9xyC+666y4UFRVJ1kgKrVBsPCB2AwQ1U+NGAVoVqC/Zx9ISdRnbiy++GFFRUUhKSkJDQ4Pnvvz8fJSWlkrSQAq9UOSn1ZCeGcgoz/u5n311DCOHZ8JgiOEZygAFOtvr7yyQI/aBETwiz87ORl1dHYDujRz+8pe/eO7bvXs3kpOTQ986koQ7P+29Ya9YakjPDGSU5/1ch8OJb06cBsALhA1UoLO9/s4COWIfGMGB/Morr8TevXsBAEuXLsW2bdswefJkTJ8+Hc8++yxrziOMGvaFHMiXifdzc0cMg16v527vIRBov9b+9nFVw8BAywSnVtasWQObzQag+/K1cXFx+N///V+0tbVhyZIluPXWWyVrJKmPOz1ztrYBJ07XAnBh2doyWU+JxdSi9zx1jzMY0GHrRJROB4MhBrOmfw+b1qizikaOtEOo3iNQNVJ/VUpcCDUw+pUrVz4k5IFRUVGIjo5GVFT3IN5kMiE+Ph6xsbGYPn06hgwZImU7Q6qxsRFpaWlKNyNoamj/oIvi8P9+MAX7Pv4Ser0eUboonG9tx2dfHcP/+8GUPp8bqvZPGm/CZ18dg72zCxlpKVi9tACDLorz+9jV61/E2bpGOJ0unG9tx0XxBqSmJAp6rlTtD6S2vgmr17+Ilyv24p+Vh7D7X//GuabznrYL6eP+9DyGnv0TivcQQ8zvElDH30BPPX9vk8abAh5DqNsveES+ePFiGAwGbNmyBQDwwgsvYPny5XC5XIiJicGrr77qdxs4Cm9KnhKLqUXv2c62Dju2FN8rZfOC1nMi+UjVKYwdmQ1Auj5WOrUh9boCOc5qlCwAEJwj/+ijjzBnzhzPz7///e9xyy234OTJk7juuuvw+OOPS9JAkk8wJYVqyJULoXQ7xfRtz6AKuCRvu9L9IzU5JlOV/DIUHMjr6+sxdOhQAEBVVRWqq6tx5513IjExEYsWLcLhw4claySFTl8BJZgPe3+TWGqhdDvF9G3PoDo9f6zkbVeqf+RajyBHkFXyy1BwaiUxMdFzvfF9+/YhLS0N48ePBwDo9XrPRCipW1+nf8F82KU4JZbiNFjpSwKI6Vt/df5STyAr1T9ypSPkmExV8vpBggP51KlTsXHjRkRHR6OsrAzXXHON576qqipkZmZK0kAKrb4CiloqB9Sw2CjUxPSt0l86cnJ/HjtsdhyrPosvvj4uSfWTHEFWyd+b4ED+8MMPY8GCBSgoKEBOTg5WrlzpuW/Xrl2YMkW+GW4KXl8BRS1XJJQ71yjHRJha+jYQMX0Qyv5yfx6PVZ9Fu82O+FiDJF/e4f7lKDiQjxw5Ev/+97/R2NiI1NRUn/vWrVsHo9EY8sZR6PUVUNTyYZf7zECOMwC19G0gYvoglP3l/jx+8fVxxMcaYMoZxgVBQRC9sUTPIA4AeXl5IWkMSa+/gKKGa17IPXpVuvRODcT0QSj7y/159N6rNJRf3mr4PMtBcNUKRQY1XPMiFNeCESPcS++EENMHUvSXVFUzavg8y4FbvZEPtY1Oe46o7lo4F38ofzOkIyy156/lIKYPBtpfgUbJUqSe1PZ5lgoDeZgI1SlkanIiTpyuxbHqs7B3diI5KQF19RbFTkd75mNvu/8J5GQNCWk+W+35azmI6YOB9pecVUnBzLdoMR3D1EqYCNUp5OqlBaipa4CtswuGmBgMTU9V9HS054jKam3X/AjLvQjmx0sfxZT5v8SCpY9JuhhG6kU3Yl9fzlFyMCkbLaZjOCLXCO9Rgh5OlK5a4jNKCNUfR8bgFIweORx2e5fnNiWDZc8RVUJCPJwul+fnuFgDlq0t09ToyR0ovjKfRLvNjvYOG1yAZCNTfyPgpQWzQ/76dnsnPvnCjL2VBzFren7A34WcVUnBnD1oMR3DEblGeI8SzjWe7zVKCOUElBKTf4FGdT1HVH9av9znZ7igudGTO1DYO7sQpdOh88J/pQoYUgems3UN+MpcjQ8Pfo36xvNoa+vo83eh9OUS+qPFyW+OyDXC+49R5+ePMZQTdqF8LX/5Rn8C5U39jai8f77l16WaGz25R6SGmGi02+yIjY6RNGC436+rswvfHD8NfbQej5Xt7HVWF6wTp2vRbrPD4XTC6XKhrcPe5+9C7XMSWpz8ZiDXCO/TUZefP3qxfxxy7XYu9LQ+2FGjWi4rIIY7UAAuVJ+uRU7WEAyVcGTqfr93DhwEdMAlWUM8Z3WhCKiXZA1Be4cNre0diHK6cFF8rGZ+F/6o/YvGHwZyjfAeJaSnJg34jz7QCDjUFQVCA3SwAVns6EkNFQlyBwr3+93y61LP3EdrV2fIzl6GZqTCBXSP+E+chl6vV2XKJJwxkGuE9x+/2WwecPAJdrdzsYQG6GBPZ8UGxXC8IJdQ/Z3VBcv7dzf7iomamHAONwzkESpQgA11qsJfgG5uOtfrcUICcjCj6Z7PqblwbIB2cuqhEuqzOjctpiLCDQO5wpQ61e8ZYO9aOBfL1pahpq4RJ05/i5wsIzIz0gb8x+7vj9xfIBcimNF0z+d0H9sQTeXUQyXUZ3WkHgzkCqqtb8KPFv8WjU3NaLd1Ij4uFvs/OYy//fER2TcS8L5oUU7WEAwzpqpulBVM2qfnc3KyjBhmTNVURQJRfxjIFVS8uRyW862wttm6S7ecTuijdIrkbeVaBFFb34THynbCgSjRZyDBpH16PiczI011X1BEA8UFQQpqbG5BbEw0XO6Vik4XDDExiuRtg1kE4V7Es+DCUvMfL3203yXaxZvLca7xfFALeIJZSKL2xSdy8l509VjZTskuCUDy44hcQanJibg0eygam1vQeeHaJiNHZMqWt/XOz8cZDEhNHoS2DrvglEOvpebtNgB9n1E0NrdAF+TIP5hJNbkm4tRQ1tgf7/kCq9UaURU74Y6BXEHuCcfY2JheC0PkCAzef9gdtk4MM6ZiS/G9gp/vTsd0dnX5LDnvKzinJieisbF7JOh0uRBn0N61UvzRQlljf6uDSbsYyBXU12jRe/JRqsAw0Ly4O/8cE9291Dze0P9S89VLC7Ci+Fl0XciRt3fYFA+AtfVNeOCJP+GDg18B0GHa98bgseW3ifpC0cKFlqSqIyflyZ4jf//997Fw4UKMHTsWKSkp2LZtm8/9LpcLJSUlGDNmDIYMGYJrr70WX331ldzNVGgvhvkAABWqSURBVJwcgWGgFwdy55/HmUYgNSURY03Z/eahMwanYFXhjZ7df9ptdsUDYPHmcuz/+Eu0tdvR1taB/Z98KfriW1q40JL3fEEo68hJebKPyFtbWzFu3DgUFBRgyZIlve7ftGkTNm/ejM2bN8NkMqG0tBQ33HADPvroIyQmqu+PQwq19U34/Mhx1NQ1IQpActIgzJgyIeTvM9CLA4Ui/6yGa6U0Nregy+GADgB0OnR2Ovx+objTXSdP1yA7a6hPGkgLF1piHXn4kj2Qz5kzB3PmzAEA3H333T73uVwulJWV4d5778X8+fMBAGVlZTCZTNixYwduv/12uZuriOLN5ejo6ARcTjhcwPmWNkRJcO6khhV5agiAqcmJiNbrYXN2AS4XDIZov18o7jx4Z5ejVxpIDX1JkUtVOfLq6mrU1tbiqquu8twWHx+Pyy+/HB988EHEBPLG5hY4nU4kJQwCAERF6dDWYZflveWuvlBDAFy9tAAdNhsOfPpdjtzfF4oW8uAUmVQVyGtrawEA6enpPrenp6ejpqYm4PPMZrPo9wrmOXLRwwkdXLB3dUEHICYmGno4fdosVfsfK9uJc43nodPp0NhowYriZ7Gq8MaQv4/a+n/57dcCt1/r+bm56VyvSwno4YTVaoXuQvleemqS6o5DDC23HYiM9ptMJkGvpapA7uauM3ZzuVy9bvMm9GDdzGaz6OfIqXTVEjzwxIuoPPg1ABem54/Fo7/5roqir/b71IbHGgAX0GG3C96B3oEoJCQkeH7uQlRQfdVXOwp+OA3Tp0wU/ZpKK121BMXPbEf1qd45cq1R+99Af9h+X6oK5EajEQBQV1eHrKwsz+319fW9RunhLGNwCv5QIrye25t3PfMnn5sBHTB+1CWCd6AP1eRjX+3Ysv1tTQZydxpI60GEwo+qluiPGDECRqMRe/fu9dzW0dGBAwcOYNq0aQq2TD4D3fHcO4/b5XCgs9MBQPgO9KFa0u7dDltnJxqbWvDpl0fxlbkatQ3NQb0mEfkn+4jcarWiqqoKAOB0OnH69GkcOnQIF198MYYPH47CwkI88cQTMJlMyM3NxeOPP45BgwbhpptukrupQfE3WeiCS/AE4kBXCHqPqKP1euBCRsrfDvT+RtuhmnxMTU7EidO1OFZ9Fo1N3V8Y8V1dcDidOFvXOODXJ6LvyD4i//TTTzFz5kzMnDkT7e3tKCkpwcyZM1FcXAwAWLZsGe6++27cd999mDVrFr799lvs2rVLMzXk3rvduwOxv9sCGWhlhPeI+orJebhiUl7AHegDjbYHelbgbkdNXQNsnV3dk7V6Hdo77IiPNWCYMVX06xFRYLKPyGfMmAGLJXBg0Ol0KCoqQlFRkYytEq6/8rxAgVhocB5ojrq/EfXG3xZ6juE3xX/wewyhuG5IxuAUjB45HHZ7F7785gQ67J2I0ukw1jQCg2L1ol6LiPqmqhy5FgQaXbtHsZ99VYUvjhyH3d7pCcRilm/LcdnV/s4QQlUv7T5uU84wxBqiERdnQGZGKpYUzBnwMRDRd1RVtaIFgYKcOzhekjUER6vP4Nips5g1Pd8TiIWuXpRjgUx/gTpUlSuBNuXVev0vkdowkIsUKMi5g2NcrAHjR10CgyEam9Z8F5CVXr3orb9AHapl82pYtUkUCRjIRQoU5NRw8Seh+gvUDMBE2sJALlKgIOcdHOMMBrR32HDLr0tVuVmCmECthZ1viCIdA7kIfQU17+Aox6YQQts1UEIrWBjwiZTDqhURhNaDy32VPKHtCqY+XOixiKmVJ6LQYiAXob+g1lcJopLtcgsm2AotneQlXomUw0AuQn9BzbsEETrg2KmzIa0Fd39R3F/6ks+IWspgK7SuXQtbnRGFKwZyEfoLaj1LEL83diQ2rSkMeb7ae4caIe1yCybYunP/7j02Ax2LHAuZiMg/TnaK0F+1h9QliIFG1EKrUKTcVo0li0TKYSAPIan3n3R/UQDdI+q4WAOWrS0TXCnCYEsUnhjIRRJagigF9xdF9SkbMjNS0dZuk7XMkYjUiTlykZQss3N/UZTefws2rSlEh93OShEiYiAXS01ldqwUISKAgVw0NQVPVooQEcAcuWjuPPWZ2gacOF0LHbqX5Ae7JH0gS9s5eUlEAEfkormDZ2ZGGnKyhkDnNdEYDC5tJ6KBYiAPUqhy5WrKuRORNjGQBylUuXI15dyJSJuYIw+gv9y1kMU/QvLfUi8iIqLwx0DuxTvwfn3sFDIz0hAXa/C72MbfRGPPwN3WboOlpbXPBTucsCSigWJqxYv3xKPlfCuOnTwLQHjuuufE5Qeffc38NxFJjiNyL94Tj7Ex0bDbOwH0zl0HSpn0nLgEXHC6XJrYx5OItIsjci/eE4+XZg9FSlKC38U2gUoG3c+32zvxxZHjcDicqD79LVwuFxfsEJFkOCL34j3xOCT9Yjy/7ld+F+cEKhl0P/+dAwcBHZA7YhgMhhhkGlOZByciyTCQexE68RhnMOCTL8zo7HQgJkaPyyfm+Tz/ll+Xwm7v8jyeuXEikhIDuRehy+V1OsDhcOJ8axtcLhc+/vwb1NVbPI+VeoMJIiJvzJF7Ebpcvt1mR7Rej4SL4pE06CJY2zp8HsuLWRGRnDgi9yJ0uXxqciLsnZ3QAXC5XIgzxPg8lrXhRCQnjsi9CF0uv3ppAVKSEoALGy1fmj2U6RMiUgwDuRehKZGMwSl4/Y+P4NpZU/D98bm4ZPgQpk+ISDFMrXgRkxJh+oSI1IIjciIijeOIXKSB7OhDRCQFjshF4o4+RKQ2HJF7ETLa5o4+RKQ2DORe3KNt7+uHF9290Ce4x8ca0GHr5KpNIlINBvILauubsLfyIGy2TsRER8OUMwwNlpZewf3ipEEYZkzljj5EpBoM5BcUby6Hw+Hs/ufsxDcnTmP2FRN7pVLabXb8oeRehVtLRPSdiJ/srK1vwrK1ZXj7X/+Gw+FEdHQ0onQ66PV6rF5agDiDAV98cxyffnkUX3xzHHEGg9JNJiLyEfEjcnfqRK+PQrvNjvhYA8aOuQSZGanIGJyCC4NxXNjwB1ER/9VHRGqjurBUUlKClJQUn3+jRo2S7P3cqRNTzjDExxngcDh9lue32+wYP+oS5I/LxfjRl6Ctwy5ZW4iIgqHKEbnJZMLrr7/u+Vmv10v2Xu5rhxsMMRibOwKZGanYtKaw1/2sUiEitVLdiBwAoqOjYTQaPf8GDx4s2Xv1d6EsXluciNROlSPyEydOYOzYsYiJicHkyZPx29/+Fjk5OZK8V38Xv+LFsYhI7XQWi8WldCO87dmzB1arFSaTCfX19Vi/fj3MZjMqKyuRmprq9zlmszkk713fdB5byveguaUNyYkXYUnBHKSlMJVCRMowmUyCHqe6QN6T1WpFfn4+7r33Xvz3f/93SF7TbDb77aBla8t88uHDjKmqHI0Har9WsP3K0/oxsP2+VJkj95aQkIAxY8agqqpK8vfidVSISItUH8g7OjpgNpthNBolfy+hW70REamJ6gL5Aw88gH379uHEiRP4+OOPceutt6KtrQ0FBdJXi7BChYi0SHVVK2fPnsXPf/5zNDQ0YPDgwZg8eTL27NmD7Oxsyd+bFSpEpEWqC+QvvPCC0k0gItIU1aVWiIhIHAZyIiKNYyAnItI4BnIiIo1jICci0jgGciIijWMgJyLSOAZyIiKNYyAnItI41a3slFNtfROKN5ejsbkFqcmJWL20ABmDU5RuFhGRKBE9Ii/eXI6zdY2w27twtq4Rxc9sV7pJRESiRXQg5/XHiSgcRHQg5/XHiSgcRHQg5/XHiSgcRPRkJ68/TkThIKJH5ERE4YCBnIhI4xjIiYg0joGciEjjGMiJiDSOgZyISOMYyImINI6BnIhI4xjIiYg0joGciEjjGMiJiDQu4q61UlvfhMfKdsKBKG4mQURhIeJG5MWby3Gu8Tw3kyCisBFxgbyxuQU6biZBRGEk4gJ5anIiXNxMgojCSMQF8tVLC5CRmsTNJIgobETcZGfG4BSsKrwRJpNJ6aYQEYVExI3IiYjCDQM5EZHGMZATEWkcAzkRkcYxkBMRaRwDORGRxjGQExFpHAM5EZHG6SwWi0vpRhARUfA4Iici0jgGciIijWMgJyLSOAZyIiKNYyAnItK4iAvkzz//PC677DIYjUb84Ac/wP79+5VuUi8lJSVISUnx+Tdq1CjP/S6XCyUlJRgzZgyGDBmCa6+9Fl999ZWCLQbef/99LFy4EGPHjkVKSgq2bdvmc7+QNlssFtx1113Izs5GdnY27rrrLlgsFlW0v7CwsNfvZPbs2T6PsdlsuO+++3DppZciMzMTCxcuxJkzZyRv+4YNGzBr1iwMHz4cI0eOxM0334zDhw/7PEbN/S+k/WrufwB47rnncPnll2P48OEYPnw4rrnmGuzevdtzv9T9H1GBfNeuXVi5ciV+85vf4F//+hemTp2KH//4xzh16pTSTevFZDLhyJEjnn/eXzibNm3C5s2b8bvf/Q7vvPMO0tPTccMNN6ClRblt61pbWzFu3DisW7cO8fHxve4X0uaf//znOHToEF577TXs2LEDhw4dwi9+8QtVtB8ArrzySp/fyWuvveZzf1FREf7617/ij3/8I9544w20tLTg5ptvhsPhkLTt+/btw+LFi7F7925UVFQgOjoa119/PZqamjyPUXP/C2k/oN7+B4DMzEysXbsW//znP7F3717MnDkTixYtwhdffAFA+v6PqDryq6++Gnl5efj973/vuW3ixImYP38+1qxZo2DLfJWUlKCiogIHDhzodZ/L5cKYMWNw5513Yvny5QCA9vZ2mEwmPPLII7j99tvlbm4vw4YNQ2lpKRYtWgRAWJuPHDmCadOm4a233sL06dMBAAcOHMDcuXPx0UcfyboRSM/2A90jwsbGRrzyyit+n9Pc3Izc3Fxs3rwZCxYsAACcPn0aEyZMwI4dO3D11VfL0nYAsFqtyM7OxrZt2zB37lzN9X/P9gPa6n+3nJwcrFmzBrfddpvk/R8xI3K73Y6DBw/iqquu8rn9qquuwgcffKBQqwI7ceIExo4di8suuwx33HEHTpw4AQCorq5GbW2tz3HEx8fj8ssvV+VxAMLa/OGHHyIhIQHTpk3zPGb69OkYNGiQao7rwIEDyM3NxaRJk3DPPffg3LlznvsOHjyIzs5On2PMysrC6NGjZW+/1WqF0+lESkoKAO31f8/2u2ml/x0OB3bu3InW1lZMnTpVlv6PmK3eGhoa4HA4kJ6e7nN7eno66urqFGqVf5MnT8YzzzwDk8mE+vp6rF+/HnPmzEFlZSVqa2sBwO9x1NTUKNHcfglpc11dHdLS0qDT6Tz363Q6DB48WBW/n9mzZ+O6667DiBEjcPLkSTz66KOYN28e3n33XcTGxqKurg56vR5paWk+z1Pi87Vy5UpMmDABU6dOBaC9/u/ZfkAb/f/ll19izpw56OjowKBBg7B161bk5eV5ArGU/R8xgdzNu6OA7tP+nrcp7ZprrvH5efLkycjPz8fLL7+MKVOmANDGcfTUX5v9tV8tx3XjjTd6/j8vLw/5+fmYMGECdu/ejXnz5gV8ntztX7VqFSorK/HWW29Br9f73KeF/g/Ufi30v8lkwnvvvYfm5mZUVFSgsLAQr7/+uud+Kfs/YlIraWlp0Ov1vb7d6uvre31Tqk1CQgLGjBmDqqoqGI1GANDUcQhpc0ZGBurr6+FyfTdl43K50NDQoMrjGjp0KDIzM1FVVQWgu/0OhwMNDQ0+j5Pz91JUVISdO3eioqICOTk5ntu10v+B2u+PGvvfYDDg0ksvxfe//32sWbMGEyZMwDPPPCNL/0dMIDcYDMjPz8fevXt9bt+7d69PXkqNOjo6YDabYTQaMWLECBiNRp/j6OjowIEDB1R7HELaPHXqVFitVnz44Yeex3z44YdobW1V5XE1NDSgpqbG80ean5+PmJgYn2M8c+aMZxJLaitWrMCOHTtQUVHhU6oKaKP/+2q/P2rrf3+cTifsdrss/a9fuXLlQyE/ApVKTExESUkJhgwZgri4OKxfvx779+/H008/jeTkZKWb5/HAAw/AYDDA6XTi6NGjuO+++1BVVYUnn3wSKSkpcDgcePLJJ5GbmwuHw4HVq1ejtrYWGzduRGxsrCJttlqt+Prrr1FbW4uXXnoJ48aNQ1JSEux2O5KTk/tt8+DBg/Hxxx9jx44duOyyy3DmzBn86le/wsSJE2Upgeur/Xq9Hg8//DASEhLQ1dWFzz//HL/85S/hcDiwfv16xMbGIi4uDt9++y2ee+45jB8/Hs3NzfjVr36FpKQkrF27FlFR0o2Zli9fjvLycrz44ovIyspCa2srWltbAXQPYHQ6nar7v7/2W61WVfc/ADz00EOev9kzZ86grKwMr776Kh566CGMHDlS8v6PqPJDoHtB0KZNm1BbW4uxY8eiuLgYV1xxhdLN8nHHHXdg//79aGhowODBgzF58mSsXr0aY8aMAdB9yrVu3Tq8+OKLsFgsmDRpEh5//HGMGzdOsTa/9957uO6663rdXlBQgLKyMkFtbmpqwooVK/Dmm28CAObOnYvS0tJe1Qtyt3/Dhg1YtGgRDh06hObmZhiNRsyYMQOrV69GVlaW57EdHR148MEHsWPHDnR0dGDmzJl44oknfB4jhUD9s2LFChQVFQEQ9plRqv/7a397e7uq+x/oLo987733UFdXh6SkJOTl5eGee+7xlD1K3f8RF8iJiMJNxOTIiYjCFQM5EZHGMZATEWkcAzkRkcYxkBMRaRwDORGRxkXctVaI/BFSqzt8+HAkJSXB4XCgsrLS72OOHz+O73//+z413ERSYyAnArBnzx6fn3/6059i/PjxWLlypec2g8GA9957Dw888AAOHjyI/Pz8Xq+zfft2AN0LiYjkwkBOBHiuKulmMBiQlpbW6/ahQ4fioYcewvbt2/0G8ldffRX/8R//0e9Fn4hCiTlyIhEyMjJw9dVXY+fOnejq6vK5b//+/Thx4gRH4yQ7BnIikQoKClBfX49//OMfPre/8soriI+Px/z58xVqGUUqBnIikebOnYuUlBSUl5d7brPZbPjLX/6Ca6+9VlVX0qTIwEBOJFJsbCz+67/+C2+++Saam5sBAG+88Qaam5uxcOFChVtHkYiBnCgIBQUF6OjowP/93/8BAMrLyzFkyBDMmjVL4ZZRJGIgJwrClClTYDKZUF5e7smXL1iwoNc+mURyYCAnCtLChQtx4MABPPHEE+jq6mJahRTDQE4UpJtvvhk6nQ7PPvssvve97ym6QxNFNgZyoiBlZWVhxowZcLlcHI2TorjVGxGRxnFETkSkcQzkREQax0BORKRxDORERBrHQE5EpHEM5EREGsdATkSkcQzkREQax0BORKRx/x/Z4wXogRV3hAAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<Figure size 360x360 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 360x360 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 360x360 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "datasci.scatter('TV','sales')\n",
    "datasci.scatter('radio','sales')\n",
    "datasci.scatter('newspaper','sales')\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "4. Questions About the Advertising Data\n",
    "\n",
    "•\tLet's pretend you work for the company that manufactures and markets this widget\n",
    "\n",
    "•\tThe company might ask you the following: On the basis of this data, how should we spend our advertising money in the future?\n",
    "\n",
    "\n",
    "•\tThis general question might lead you to more specific questions:\n",
    "1.\tIs there a relationship between ads and sales?\n",
    "2.\tHow strong is that relationship?\n",
    "3.\tWhich ad types contribute to sales?\n",
    "4.\tWhat is the effect of each ad type of sales?\n",
    "5.\tGiven ad spending in a particular market, can sales be predicted?\n",
    "\n",
    "\n",
    "We will explore these questions below.\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "5. Simple Linear Regression\n",
    "•\tSimple linear regression is an approach for predicting a quantitative response using a single feature (or \"predictor\" or \"input variable\")\n",
    "•\tIt takes the following form:\n",
    "•\ty=β0+β1x\n",
    "•\t\n",
    "\n",
    "\n",
    "What does each term represent?\n",
    "•\ty\n",
    "•  is the response \n",
    "\n",
    "•  x\n",
    "•  is the feature \n",
    "\n",
    "•  β0\n",
    "•  is the intercept \n",
    "\n",
    "•  β1\n",
    "•  is the coefficient for x\n",
    "\n",
    "•  β0\n",
    "and β1\n",
    "•\tare called the model coefficients\n",
    "\n",
    "To create your model, you must \"learn\" the values of these coefficients. Once we've learned these coefficients, we can use the model to predict Sales.\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "6. Estimating (\"Learning\") Model Coefficients\n",
    "\n",
    "•\tCoefficients are estimated using the least squares criterion\n",
    "o\tIn other words, we find the line (mathematically) which minimizes the sum of squared residuals (or \"sum of squared errors\"):\n",
    " \n",
    "What elements are present in the diagram?\n",
    "•\tThe black dots are the observed values of x and y\n",
    "•\tThe blue line is our least squares line\n",
    "•\tThe red lines are the residuals, which are the distances between the observed values and the least squares line\n",
    "\n",
    "How do the model coefficients relate to the least squares line?\n",
    "•\tβ0 is the intercept (the value of y when x=0) \n",
    "•  β1 is the slope (the change in y divided by change in x)\n",
    "Here is a graphical depiction of those calculations:\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Intercept    2.921100\n",
       "TV           0.045755\n",
       "radio        0.187994\n",
       "dtype: float64"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "### STATSMODELS ###\n",
    "\n",
    "# create a fitted model\n",
    "lm1 = smf.ols(formula='sales ~ TV + radio', data=data).fit()\n",
    "\n",
    "\n",
    "# print the coefficients\n",
    "lm1.params\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "2.9210999124051362\n",
      "[0.04575482 0.18799423]\n"
     ]
    }
   ],
   "source": [
    "### SCIKIT-LEARN ###\n",
    "\n",
    "# create X and y\n",
    "feature_cols = ['TV','radio']\n",
    "X = data[feature_cols]\n",
    "y = data.sales\n",
    "\n",
    "# instantiate and fit\n",
    "lm2 = LinearRegression()\n",
    "lm2.fit(X, y)\n",
    "\n",
    "# print the coefficients\n",
    "print(lm2.intercept_)\n",
    "print(lm2.coef_)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "7. Interpreting Model Coefficients\n",
    "Interpreting the TV coefficient (β1)\n",
    "\n",
    "Let's do this again using just the feature or X variable TV.  We will ignore radio.\n",
    "\n",
    "•\tA \"unit\" increase in TV ad spending is associated with a 0.047537 \"unit\" increase in Sales\n",
    "\n",
    "•\tOr more clearly: An additional $1,000 spent on TV ads is associated with an increase in sales of 47.537 widgets\n",
    "\n",
    "•\tNote here that the coefficients represent associations, not causations\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "7.032593549127693\n",
      "[0.04753664]\n"
     ]
    }
   ],
   "source": [
    "### SCIKIT-LEARN ###\n",
    "\n",
    "# create X and y\n",
    "feature_cols = ['TV']\n",
    "X = data[feature_cols]\n",
    "y = data.sales\n",
    "\n",
    "# instantiate and fit\n",
    "lm3 = LinearRegression()\n",
    "lm3.fit(X, y)\n",
    "\n",
    "# print the coefficients\n",
    "print(lm3.intercept_)\n",
    "print(lm3.coef_)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "8. Using the Model for Prediction\n",
    "\n",
    "Let's say that there was a new market where the TV advertising spend was $50,000. \n",
    "\n",
    "What would we predict for the Sales in that market?\n",
    "y=β0+β1x\n",
    "y=7.032594+0.047537×50\n",
    "\n",
    "We would use 50 instead of 50,000 because the original data consists of examples that are divided by 1000\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "9.409444"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#8a.  Manual Prediction\n",
    "7.032594 + 0.047537*50"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "   TV\n",
      "0  50\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "0    9.409426\n",
       "dtype: float64"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#8b. Statsmodels Prediction\n",
    "### STATSMODELS ###\n",
    "lm9 = smf.ols(formula='sales ~ TV', data=data).fit()\n",
    "# you have to create a DataFrame since the Statsmodels formula interface expects it\n",
    "X_TVSpending = pd.DataFrame({'TV': [50]})\n",
    "print (X_TVSpending)\n",
    "\n",
    "# predict for a new observation\n",
    "lm9.predict(X_TVSpending)\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<seaborn.axisgrid.PairGrid at 0x1a1a7356a0>"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1058.4x504 with 3 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#Plotting the Least Squares\n",
    "sns.pairplot(data, x_vars=['TV','radio','newspaper'], y_vars='sales', height=7, aspect=0.7, kind='reg')\n",
    "\n",
    "\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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8ov9bQIGLYoVGHp1tN9YDf6uzY6HbkEll1jzQWXxeJzECLZ8///nPHD58mE8//RSA1157jaSkJAYPHtzMLYsNJIZAiCqiYQlfY2ICJJ4gsugrd2A9OBHFU64pdxs7UpH9NOjM9V4bjhiBaPh+hkowc/rRSufOnbnssstYtWoVAwYMYNWqVfzpT3/CbK7/cxcCRzwEQlQRDUv4GmNJihUaOQzlX2PNe7COGLCn3EB5l9dQTRkRb0M0fD9bO7fddhvvv/8+77zzDj///LNMF4QR8RAIUUU0uNx9W5IljbhWaCyGE5uIPzQNRXVqyu2pw7FljDn1nYkw0fD9bO1cd911TJgwgfvuu48+ffrQo0eP5m5SzCAeAiGqkMCv6CIa8vsbyz4iPv+hOmLAlv7XJhUDIN/PaMBsNvPHP/6R0tJS8Q6EGREEQlQhLvfoorld5KZjb2E5/BgKbk15Vebfsafd0aRiAOT72RTccMMNlJaWNlhn/vz5lJaWcvvttzdRq1oHMmUgRBXico8umtNFbip5FUvRUk2Zio6q9hNxplzbZO3QPF++n0IMIx4CQRDqpVlc5KqK+chKH2JAT1XHR5pNDAhCrCOCQBCEemlyF7nqIa7wKeKKX9QWKyYqs+bgTLo6ss8XhFaMTBkIglAvTeoiV91YCuZjKntPW6yzUJE1D7f1tyHfuiXnDxCEpkIEgSBEAa1+wFKdWA49hunEp5pijy6RyuwFuC09G3V7fxsbCYIggkBoocTaANqqByyPnfj8hzBWfKkt1qdSkb0IT1zXRj9C8gcIgn9EEAhRib8BP9YG0FY7YLkrseZPwlD5X02xx5BBRfaTeMzZYXmMpJQWBP9IUKEQlfhb/x5rA2hzJrwxeEqbJfmQ4j6ONW9sHTHgNmZR3nlp2MQASP4AQQgE8RAIUYm/AT/WLD572l2Yi1dUe0SMSU06YHVQ30LndDSpt0VxlWDNexC9fa+m3G3uQkX2IlRD2/qvDWG6SPIHCIJ/xEMgRCX+LOZYs/hqBqyqTrMC2mY5nBgob1Jvi+L8FeuBe+uIAVfc2VTkPN2gGIDmz54oRDf/+te/SElJ8R6/8sordOzYsRlb1HIQD4EQlfizmMXiCx8uEkB1NIm3Rec4iPXAWHSuIm0b4ntTkTUf9PF+7xFr00VCZLnxxhsZOHBgczejRSCCQIhKZMBvOg4rfyDZ+EnEpyt0tr1Y8x5A59bGKDitF1GZNRN0ge1pH2vTRYJvHA4HJpOp0fexWCxYLJYwtCj2EUEgCK0cly454uJLX/Uj8Xnj0HlOaModiVdS1XEaKMaA79Wc8RYtmZRXfmnS55XeemZQ9QcPHky3bt2Ij4/ntddeIzs7m5tuuolXX32V/fv3k5yczIABA3jsscc0UwKvvfYas2bNoqSkhMsvv5wBAwZo7vvKK68wceJEDh065C174YUXeOqpp8jPzycrK4v7779fNkpCBIEgtCp8BeRFGn3Fd1jzJ6F4qjTljuTfU9V+Eij6oO4n3qPY5Y033uD222/ngw8+QFVVPvnkE+bMmUPnzp05ePAgEydOZOLEiTz33HMAfPPNN9xzzz1MnTqVIUOGsGnTJmbMmNHgM9555x0mTJjA7Nmzueqqq/jkk08YN24cGRkZDBo0qCm6GbWIIBCEKCLSCZd85W+AG8N2/9oYyr8kPn8qiurQlNvb3Iwt8++gSFyzcIrs7GxmzZrlPe7WrZv33zk5OcyYMYPhw4fz7LPPotPpePbZZ7niiisYP348AF27duW7777j5ZdfrvcZzzzzDLfccgujRo3yXrNt2zYWL17c6gWB3/+NixYt4sorr6RTp0506dKFW265hR9//FFTZ8yYMaSkpGj+1Hbb2O12JkyYwJlnnkmHDh0YOnSoxoUjCELkI+ibMiDPcPxT4g/+o44YsLW9HVvmWBEDQh169+6tOd64cSNDhgyhR48eZGVlMWLECBwOB4WFhQDs2rWLCy64QHNN7ePa7Nq1i379+mnKLrroIn766acw9KBl49dDsHnzZu68805++9vfoqoqs2fPZsiQIWzZsoU2bdp46/Xv35/ly5d7j2sHg0yePJn333+f559/njZt2jB16lRuueUWNm7ciF4fnMtQEGKVSA/YTRWQZyx9F0vBfBQ8mvKqjDE42t4akWcKDRPsnH5zYLVavf/Oy8vjlltu4bbbbmPKlCmkpqayfft27rzzThyOapGp1ixNDhKl5v+Yn7LWhl9BsG7dOs3x8uXLyc7O5quvvtK4V8xmM5mZmT7vUVZWxssvv8ySJUu48sorvffp1asXGzZs4OqrZUtTQYDID9g+A/LKS8L6DNPRNVgKF2vKVMBl6SViQAiY//73vzgcDubMmeM1GtevX6+p0717d7755htNWe3j2nTr1o2vvvqKESNGeMu+/PJLunfvHqaWt1yCjiEoLy/H4/Foojyh+oV27dqV5ORkLrnkEh5++GHS09MB2LZtG06nk6uuuspbPysri27durFlyxYRBIJwksZE0AcSf+ArIM/g2VudsrixcQuqirnkf4k7op3mUAG3ORdV33I3nxKani5duuDxeFi6dCnXXXcd33zzDc8++6ymzt13383AgQNZtGgRN9xwA5s3b+bdd99t8L733Xcfd9xxB7179+aqq67i448/Zs2aNQ3GHbQWlNLS0qB8LnfccQd79+5lw4YNXtX25ptvYrFYyMnJIS8vj5kzZ+LxeNiwYQNms5k1a9YwevRoiouLNW6Z6667ji5duvDkk0/6fNaePXsa0TVBaF1ku1/EpB7zehccShvy9HdE7DoNqkqWZw3t1A+0xShUkoOTpNDuG4Pk5uZG9P5lZWUkJydH9BmRYPDgwfTo0YPHH3/cW/bss8+yePFijh07Rt++fRk5ciQjR45k+/bt5OTkALBq1Srmzp1LcXExl156KQMHDmTixImUlpYCvpcd/vOf/+Tpp5/m4MGDdOrUqVUtO2zo+xGUIJgyZQrr1q1j/fr1dO7cud56BQUF9OrVi3/+859cf/319QqCa6+9ltzcXJ544onAe9OC2bNnT8R/DJqLWO4btIz+WQ5ORcHpPVYxUtVpVgNXVOP+aSyJ1lNJgQK97tQFHuJ+XYS59C1tsWLGGX8eKOZm26K6JXxu4aalCgKhaWjo+xHwlMHkyZNZt24d77zzToNiAKB9+/Z06NCBX36pToSRkZGB2+2mpKSEtLQ0b73i4mIuvvjiQJsgCEIDhBp/0KjUxaoLy+E5mI5/qC3WWanoNB93/LnBdEEQhGYkoHU/kyZNYu3atbz99tucddZZfuuXlJRQUFDgDTLs3bs3RqORzz77zFvn0KFDPpd/CIIQGqFu+HRY+UNoG0V5HMTnP1xHDHj0KZRnPxVVYkBxljTLFs+C0JLw6yEYP348q1evZtWqVaSkpHjXf1qtVhISEigvL2fu3Llcf/31ZGZmkpeXx4wZM0hPT+faa68FIDk5mREjRjBt2jTS09O9yw579uxJ//79I9pBQWgthJrBL6TUxZ4q4vOnYKz4WltsSKMi+wk85jOCbkck8ZWQSbIdCoIWv4Jg5cqVANxwww2a8kmTJjF58mT0ej0//vgjr7/+OmVlZWRmZnLZZZfxwgsvkJiY6K0/e/Zs9Ho9I0eOxGazcfnll/Pss89KDgJBaGm4T2A9OBFD1feaYo8hE6elJ+ailc0WM1AfskOiIPjHryCoidSsD4vFUidXgS/i4uJ4/PHHNRGkghAogab0jXTq38a0LRZQXMew5o1Db9+tKXebOuOK64rOXRGSFR7pdyg7JAqCfyR3qNAiCDSlb6RT/55Ozby09cBoDOVbUDwVEX9mU+Frzl1xHsF64L66YsB8FhU5T6N4nCFb4ZH+3EKNrxCE1oRsbiS0CLwuX48TnSMPnW03ccyrY0k2pWvYO4h57KB60Dny8MR1bTZ3dDit7Dpz7oVPYrTtROcs0NRzWXpR0Wk+6BMbZYVHPGWz7JAoCH4RD4HQIlANSaCq6Bx51QOwovdpSdbUqz5Qq48jRM0gpirG6kFMdUX8mQ0RTitbM0CrVZjKN9cRA07rBVRkLwJ9daxQY6zwpvzcBEHwjXgIhKjDl6Vbk9JXZ9uNqjPhMWX7tCQbk/o3WGosYo8pG539ACi6ZnVHh9PK9lr7ngoMVT+i4NKcdyZcRmXH6aA7tYlZY6zwpvzcBEHwjQgCIeqob4mYrf0k4pjnPefLLd2UruHTBzFXYr9mDyYMZ+CcPe0u4n6dh7HqBxTcmnOOpIFUdZgCSvh+PsSlLwjNjwgCIepoyNIN1JJsisj/aBvEwmll6+17MVZ8W0cM2FOGYGv3ICgy2ygIsYYIAiHqaMjSDXQQbo2JaMIlUAwn/kP8oUdQVKem3J46HFvGmFNiTRCEJsfj8aCqakRy+IggEKKOcFi6kogmNIxlH2I5PLuOZ8CWfhf2trcFLAZaU26GlsI541P8VwojOxY0nMOmNoMHD6Z79+4kJyfz4osvotPpGDp0KDNmzECn0+FwOJg1axZr1qyhtLSUbt268dBDD3H11VcDcPXVV3Pddddx//33A3DXXXexZs0adu3aRWZmJpWVleTk5PDOO+9w4YUX8vnnn/PII4+wc+dO9Ho9ubm5PP300/To0cO7Q+LKlSt56KGHyM/P54ILLuCZZ57x7uWzb98+pkyZwrfffkt5eTldu3ZlypQp/O53v/P2qVevXgwfPpx9+/bx3nvvYbVaue+++7jvvvu8dcrKypg2bRrvvfceNpuNc845h1mzZnHeeecBp3ZrfOGFF3jkkUfYvXs3mzZtokePHo35eHwifj8h6qixdKs6zcLWflJIA4lErdfFXz5/07G3sByeWUcMVGX+HXva7UF5BpoyH4QQO6xZswa9Xs9HH33E448/zrJly7yJ7+69914+//xzVqxYwRdffMGwYcMYOnQo339fnTHz0ksvZdOmTd57ff7557Rt25bNmzcDsGXLFoxGI3369MHlcjF8+HAuvPBCNm/ezMcff8zo0aM1VrfdbmfevHksWbKEjz76CLfbza233op68nelvLyc//mf/+H//u//2Lx5M9dffz0jRoxg925tno6lS5dy1llnsXHjRiZPnsyMGTN4++23AVBVlVtuuYWCggJWr17Nf/7zHy6++GKuv/56fv31V+89bDYbCxYs4IknnmDLli106tQpAm9fPARCjNIYL4Mv69bf+ZZg/TY0jWIqeRVL0VJNfRUdVe0n4ky51uf9GnoP4qERQqFbt25MnToVgK5du/LSSy+xceNG+vTpw9q1a9mxY4d3MBw1ahQbNmzgxRdfZOHChVx66aWsXLkSl8vFgQMHOH78OHfffTebNm3ipptuYvPmzfTt2xej0cixY8coKyvjd7/7HWecUb3vRu2N+1wuF3PnzuXCCy8EYPny5fTu3ZuNGzfSv39/evXqRa9evbz1x48fz/r16/nXv/7FhAkTvOV9+vRh/Pjx3j599913LF26lOuvv57//Oc/fP/99/z8889YLBYAHnroIdavX8/q1asZO3YsAG63m/nz59O7d+9IvHYvIgiEmKQx8+m+Bk64scHzLSE+wecgrap0cK/DUvSOpq6KnqqO03AmXV3v/Rp6D5IqWAiFnj17ao7btWvHkSNH2L59O6qqegfnGux2O5dffjkAF110EXa7ne+++46dO3dy0UUXccUVV/Dggw8CsHnzZv7nf/4HgDZt2jB8+HBuuukmrrjiCi6//HKGDBlCVlaW9946nY4+ffp4j7Ozs2nfvj0//fQT/fv3p6Kignnz5vHhhx/y66+/4nK5sNlsdfpwwQUX1Dl+553q/2/bt2+nsrKSrl27aurYbDb27dvnPTYYDBrxESlEEAgxSWOseH/WbUu1fusM0oZE4goXk6zWEgOKicqsWbgSLmrwfuFYDSI0HcHO6TcHRqNRc6woCqqq4vF4UBSFTz/9tE6duLg4ABISEjj33HPZtGkTP/30E5dddhl9+/bl4MGD7N27l++++47p06d7r1u6dCljxozhk08+4YMPPmDmzJm88sor3pgEfzz88MN8/PHHPPbYY3Tp0oX4+HhGjx6Nw+EIuL8ej4eMjAw++OCDOudO3xzQbDY3yXZtgI0AACAASURBVEaAIgiEqCDcbvjGWPH+rNuWav1qBmlDIorHhqnsXU0dVWehImsebutv/d4vHKtBBCEQzjnnHFRVpbCw0OsR8EVNHMHu3bsZM2YMcXFx9OnThwULFnjjB06nxu1///33c/PNN/Paa695BYHH4+G7776jX79+ABw8eJCCggK6desGwFdffcXQoUO9OwHXWPVdunTRPOObb76pc1xzj3PPPZeioiJ0Op03WLE5kaBCodlRnCXE592H8fgmDBVbMZZuJD7vb3WC3oK6ZyOseH8peFvqRjneYM2sR1E8FZhOfKw579ElUpG9OCAxAC33PQgtj65du/KnP/2Je+65h3/961/s37+f//73vzz99NPeAD04JQjKy8s599xzvWVvvPGGN34AYP/+/Tz66KNs2bKFvLw8/vOf//DDDz94B2qodtNPnjyZrVu3smPHDsaMGUP37t3p378/AF26dOHdd99l27Zt/PDDD4waNQq73V6n7d988w2LFi1i7969vPTSS7z++uvcc889APTv358LL7yQ4cOH8+9//5v9+/ezdetWZs+ezRdffBGp11kv4iEQmh1z8Up0rhMoaiWoHlTc6NzljZqbb4wV79u6LfFzvoXgsROf/xDGii+1xfpUKrKfwBPXpZ4L69Ki34PQ4liyZAkLFixg2rRpHD58mDZt2vDb3/6Wyy67zFvnoosuQlEULrroIq+L/bLLLmP+/Plceuml3nrx8fH8/PPP3HHHHZSUlJCRkcEf//hH75JFqHbTjxs3jtGjR5Ofn8/555/PqlWrUE4aGrNmzeK+++7j97//PSkpKYwZM8anILjnnnv44YcfWLhwIfHx8UyZMsXrVVAUhTfeeIOZM2cyduxYjhw5QkZGBv369WPYsGEReY8NoZSWlqpN/tRWyp49e8jNzW3uZkSExvTNcnAqettP6FzVHgEVUA1tcMedTVWnWSHdU3EePc093vgpiJb+2SnOEsxHnsV44gt0njLNOTdm3PHnoJratZgVE77wNe20e39Ji/7cQqGsrIzk5OTmbkaLpmbt/6FDhxp1n169ejFq1ChN3oHmpqHvh3gIhGZHNSThMXZCcZdV7xioGPAYO3lzB4QSXyDWqxZz0VKM5Z+j85Rryj06K+WeTsTrjC1qxYQv/K0OEQShYUQQCM1OTbCbqjOicx7CY+iAakr3zkm31GV+4aJRKyacJZiLnsF0/NM6CYfc5i649RmoVZUnK7ecFRO+aKmrPwQhWhBBIDQ7/qz51v5D3xhBZC56CtOJz+uIAY8+hYqcpzEXLYPKA9WFEVgxoREzihlQUVRHRBI6tdTVH0L0ceutt3Lrrbc2+j41WRRbCrLKQIh6YjUNsb9Uwt56IQoineMgphObUVSbptxjaEt5zrOo+upB2aG0idhKgdNTGBsqt2Go2h6xdMay6kEQGod4CISoJ1aT3Ggsf3sB8Xl/w2M6o471HIrlq7P9jDXvQRRVG/XsNmRQ3uU10Jmr721MJU9/B+ZOkQm8O13MKLiqI0YhIp4ef6tDBEFoGBEEQtQTiwGCirMEQ8U3KB47qmIE1Y2CBxVnnWmBYAWRvuoH4vPGo/Oc0JS7je2pyH7GKwbC2Zf6YhxOFzMqBqjZH0lc+hFFVVXv8jhBqKFmY6b6EEEgCM2AuXglqG5QPSg4UNwVeAwnt6etZT0HI4j0Fd9hzZ+E4qnSlDuSB1PVfiIo4U9/2lCMw+lixhXfG28MQQx5eqINq9VKaWkpKSkpIgoEL6qqUlpaqkmJXBsRBILQDCiu43hM2egceSiqC1XR4zGe3NLUj/Vcn0VuKP+S+PypKKo2l7q9zc3YMv8OSmRChhqKcQiHd6el7i7ZXBgMBhITEzl+vHUF3wr+SUxMxGCof9gXQSAIjSSkPAmGJBSnA09cV1BVPLpE0JsDmhbwZZG7redjOTSjzmoCW9od2NPuPDVgR4BIR/e39mWnoWAwGCQ5kRA0IggEoZGEMmD5igsIdTdGfdUuTKXvoeDR1KvKuAdH2+Eh9SkYIh302dqXnQpCUyGCQIh6GrLAo8GdHMqA1RhX+ukWuc5xGL1jv/Y8CrZ243C0GRLS/YNuT4SDPiW/gCA0DZKHQIh6Tl/LXnv9ekPnmoqmzpNgT7sLj6Etik8xoKeqw8NNJgaCIdC8C7WR/AKC0DSIh0CIehqywKPBndzUeRJUQxvQJ2GoLQYUI1WZ49FX/hfD8Y1RF4AXaixALC47FYRoxK+HYNGiRVx55ZV06tSJLl26cMstt/Djjz9q6qiqypw5c+jevTvt2rVj8ODB7Ny5U1OntLSUUaNGkZ2dTXZ2NqNGjaK0tDS8vRFikoYs8GjIYlgzYFV1moWt/aQ6A3ColrHvh3mI+3Uh5qOvaouVOCqz5qO3/b9m95jURzSIN0EQ6sevINi8eTN33nknH374IW+//TYGg4EhQ4Zw7Ngxb53FixezZMkS5s2bx6effkp6ejp/+MMfOHHiVGKUv/71r+zYsYM1a9awdu1aduzYwd133x2ZXgkxRUMu45bgTg7btIbqwnJ4JubSt7TFOisV2YtwJVwQ1YNuNIg3QRDqx++Uwbp16zTHy5cvJzs7m6+++opBgwahqirLli3j/vvv54YbbgBg2bJl5ObmsnbtWkaOHMmuXbv4+OOPWb9+Pf369QPgiSeeYNCgQS1+n3kh8jTkMq7vXGHxMWYveZ2jZSdITU5k6r3DyEhLiXRTfRKWQdrjIP7QIxjLN2mL9SlUdFqIx9INiO4AvFhNQS0IsULQMQTl5eV4PB5SUqp/XA8cOEBhYSFXXXWVt47FYuHiiy9my5YtjBw5kq1bt5KQkOAVAwAXXnghVquVLVu2iCCIUQJZARCpVQKzl7zO4aKj6BSFw0VHmb30NZ6cNqbR9w2FRg/Sniri86dgrPhae18ljsqOs7xiAKJ70A0lFiCc349oEomCEI0ELQj+8Y9/0KtXL/r27QtAYWEhAOnp6Zp66enpFBQUAFBUVETbtm01aTQVRSEtLY2ioqJ6n7Vnz55gmxf1xGKfaqjdt2z3i3jUYycHwmM4yhaSp7+j3jqKWoSxdBQ2pSMuEjis/AGXrv7kKsXHjrP89X9TdqKS5MR4Rg8bSNuU6rScefkFOF2nkvQcOGhv9LsP9fo41/mcyTL02HATxy8MwlYe2L30aiW57icw8rOm3I2JCjUH28E3yNPH17rqxlP/LC8hkA1+ovV7Gch3yB81fZu17E2OHD2OoigcPVrKpNnPMmXMTeFvtB/EABKilaAEwZQpU/jqq69Yv349er02J3rtnNm1N9fwlVPb3wYcsfYfJ1amR3xZWmXHjtTpm+UgKCR4j+Ohzq56p9fR2QpQPE6M8WZQHSQbP2nQonxm+jIq7G5M5jgq7G5e/2CL1wuQndXe6yHwqCodMlIb9e4b89nFFaxD5zyjOm+AqpJr/Bpb+6v8Xqe4jmHNG4ferRUDqmLBY+mBRWcmjrrvNFii+XsZyHeoIU7vmxsdCQmn7uVCF7X9FoTmIOA8BJMnT+bNN9/k7bffpnPnzt7yzMxMgDqWfnFxsddrkJGRQXFxsWanJVVVKSkpqeNZEMJDYfExxk5fxogH5zN2+jKKisO3oqPGHe9wuLzueF8EEkR2eh1FdaHqTNUnAphrP1p2At1JQalTFEpKTwWxTr13GB0zUzGZDHTISGXqvcOC7WbYCCWGQHEewXrgb+jtuzXlHn0SLkvP6h0LW0hgXmNWWYQzEDE1ORHPyXt5VJXU5Po3eRGE1khAgmDSpEmsXbuWt99+m7POOktzLicnh8zMTD777DNvmc1m48svv/TGDPTt25fy8nK2bt3qrbN161YqKio0cQVC+Ah00A6Fhgbi0wlkBYCmjj5Bu8GPnx//hn7gM9JSeHLaGF5eNJHFj4xp1rlif4NabfF2tPAnEg7cg95xQFPPZelFefZyPKb2Qa+qiKRA9EdjVlmEcxVJNIlEQYhG/E4ZjB8/ntWrV7Nq1SpSUlK8MQNWq5WEhAQURWHMmDEsXLiQ3NxcunbtyoIFC7Bardx8880AdOvWjQEDBvDAAw+wePFiVFXlgQce4JprrhGX3WmEM+gp0EE7FFKTEzXu+PosrUCCyE6voziPBhUQN/XeYcxe+holpafeV6QweEqrrdsQgtv8BfqdHgBpcB4g5dB96Cza7Yud1guozJoNOktAgXm1g/GefsnI4aKqZgmybMwqi3AmJaoRiYIg+MavIFi5ciWAd0lhDZMmTWLy5MkAjB07lqqqKiZMmEBpaSl9+vRh3bp1mn2XV6xYwaRJk7jxxuqAp0GDBjF//vywdSQWCGdkfKCDdijUDMSHC0vYn18IqMxa9ibzp4xulCUe7I9/U/7Ad1DfQud0hLTjnr9+1Yi3rmllzLz+a1Is2u2LnQmXUdlxOtRMpwRA7ayAg886xJ783wDhF4j+iOalkIIgnMKvIAgkm6CiKEyePNkrEHzRpk0bnnvuueBa18oIp1UfSeu5ZiAeO30ZKgo6ReHI0eP1CphYWO5loBwUc/VBmBP+dM4wMLTXl/TNKcagVzXnHEnXUNVhMijBLQiqbZW3TVDxqGpEBKI/onkppCAIp5C9DKKIQKz6QAfXprCeTxcwSgMCJppyAoSKiwRQHT6t3MYKntk3H8BiL0av04oBe8oQbO0eBCX4PchqW+W5XXvQMTO1SaZX6rRF9iIQhBaBCIIoIhCrPpoG19MFjNqA1RnJeIZw4517dxxB5zqMx9gR1ZjGQfVqko1fe61cR/JN3piCQ9sPUXmiEw6HJejPxHDiP8Q7v0OpLQbaDseWPuaUlR8kta1yXfu7eHJadGxyJAhCdCKCIIoIxKqPpsH1dAGTnprE1HuH+bSWIxnPEG5q5t51jl9QPA4Ujx0PkKF8gq39LG+9uIJ53jl6q+E4t1/4M09v6BXUZ2Is+xDL4dkoaMXALyWptO0euhgAscoFQQgeEQQtjGgaXE8XMHv27CEjLYWx05fV8WA05WqAxlIz966orpN/O0FRqmMIfNQDMBmNJJqrAwED/UxMx94i7teFdcTADwUpzP34fJ65NHQxEK3EQiyJIMQyIghaGNE+uPryYLSk5V41c++qYkDxOKoTJakqLhKoyc2pOEvQOfahc51A1ZnIzW7H17sqMJkMAX0mppJXsRQt1ZS5PbB4Qy/e3pbJ4aIjjHhwfrMOmpHYYyKaprt8IYJFaO2IIGhhRGpwDdePYTR5MEKhZu5dVVVNDMFh5WrOOFnHXLwSVZ+O6rGhqE7M+mP89ppnePlaPwOmqmI+spK4kpe0xehZvuUiNuxN5XDRQdqnp2oSSjXHoFl72WIwyyzrI5qmu3wR7YJFECKNCAIBCN+PYSQ8GE1pudU39+46bTMixXUc9GY8+q7V12D0bz2rHuIKn8J8bK22WDFRmTWLW8++iFuBEQ/Ox+FwAc07aNaXTKgxnoNoF4vRLlgEIdIEv55JiEnC9WNY48FYMKV6rfm42c81OlVuQ2mYG5MnP1SCzq+vurEUzK0rBnQWKjotwJVwkbcsWvLt19fHxqQhjvbUwdHy7gWhuRAPgQCE33oL1ePgyxtQW6wcLiypzvlfdoIHrvqRC7qnYDabwuba9kdQiXZUJ5ZDMzCd+ExT7NElUpm9ELelh6Y8WmJE6utjY9IQR3ssSbS8e0FoLkQQCED4fwxD8TgUFh/j2junUXa8HJPRSJecDsxe+lodsbI/v9CbIVGvnuDnA1X0PCsn7BkE6yPgJX0eO/H5UzFWfKUt1qdSkf0EnrgudS6JlkGzvj7GchriaHn3gtBciCAQgPD/GIbicZi95HVKj1eACjaHk715h0lKjGfhlFEasQLVKXhTLDZyUstJMLvQ2Zx4jJ1QzW3D1odG4a7Emj8RQ+U2TbHHkEFFzmI8pk4RieQPheJjx3nmpMfFX4yGpCEWhNhFBIEQEULxOBwtO4HZaMBmd6AoCg6Hk9TkxDpipSbXwW399lBcbsZqVlE8ThT3EexpjwTUvkgOxor7OPF54zDYdmrK3aYsKrKfRDW2AyITyR8Ky1//NxV2d0DTO6094ZEsTRRiGREEQkQIxuNQ8yO7fecvOF0ujEYDLreH5CSrTyFRIzaSLS70BgtxbbrgNhkDi/Y/ib/BuLZgMHiuDui+iqsEa94D6O2/aMrd5i5UZD+Bakg9rW7o8/HhpOxEJSZzHCDR9f6QpYlCLCOCIEZpSZZMzY9sVmYa23buRVUhq30aLz0+vsGNm+IKjnsH9WDns/0NxrUFQwf1/4DzG76n81esB+5H78zXlLvizqYyeyGqXtu+aJmPT06M93oIJLq+YWRpohDLyLLDGKWhpXrRRs2PbN7hIuItcSRaLXTOasdzr7/f4HX2tLvwGNNQMeIxpgU1n61ZVue2o1b+zO6PhvHluuE8NHcRjsoSjWConbq4Njp7Hgn776krBuLPoyJ7cR0x0Nj2h5PRwwZG9XLAaEKWJgqxjHgIYpRALJlo8SLUBCA6XS5QVUwmY0DWV2Pms08PjtO589l92IXb5SElDn7X5Wu+3WnmknPSvdb76amLa6Oz/Yw17wF07mOacmfCxVR2fAx05rC3vz5CiY1om5Iobu8AkaWJQiwjHoIYJRBLJlq8CDUJazqmwRMjinn53iPcd8UOcjIip1drBuOqTrPwmM6gyg6gAApJcQ6e/+JMPMY0bA6VzTuOMHqpy2eCJX3VDyQc+FsdMeBIvIrKrFn1ioFI0ZjEQYJ/aqarXl40kcWPjInaaThBCAXxEMQogVgy0TIfWvMjq+w9hOPYQXRU4UHHZb89hkrkPRmqIQmTUY/N7gTguM2E3pyOrf2YkysaUqiqrKTcrQ0i01d8hzV/EoqnSnM/R/JgqtpPBKU+n0I1kehXtAQqCoLQ8hBBEKPUjvIvLD7mze5XM/hEW255q7qLhKQ477Gq/kQ5kY/stqfdReczHOz5+UdKyhXW7z3fK6DqE02GE18Qf+ghFNWhvVebP2LLvA8U/863SPSrvkDFaMl5IAhC9CKCoJXga/CJuvlQVQVVxaOqVFTZqHTYmPzKMgpOthuqB2W37Uj1vgVhGtxUYyrKmQ9z1pnVxxeddq5GNMGpqRfj8U+wHJqBgltzH1vaHdjT7jxlofshEh6a+hIHRUvOA0EQohcRBK0EX4NPtKVqdVl6YajazonjZVRUufnyZyMfb/4Os9lIl5yOXk/GyIt/QedMD+vgVp8FXSOaDhy00yEjlXl/aYvl0HQUPJrrqzLuwdF2eFDPjISHpr5ARZlKEATBHyIIWgnRNj3gC3vmfVC8gi++3UDJcYW576Rid7pQUemYmer1ZJx/dkZ1/B+EbXCrbUF7Di7h/pfTvFMsk0YN4fIuP2MpfEpznYqCrd04HG2GBPSc04XHkyPimLbGyv5CV4MemuLCveR9/RgmpQKHaiXngkdom3lGUP2LlpwHgiBELyIIWglRNz3ggxrr9p6X9lFZaUM5OXgZDAaNJ8NUMA8aGNxCCdarbUHv+flHDhf95uQUSwklPy3BkrBL2170VHWYijN5YMB9PF14WA0OHr/N5Ne7kff1Y1h0pYAOi1LKga+n0/baFwN+JsgeBIIg+EcEQSsh2qYHGqLfud354rsfcDrdmEwG+p3bXXPe3+AWbLBeYfExDm0/hNVwHJPRSNec9pSUKyenWFRGXbKLm8/bp7lGVYxUdpyBK/GyoPoWiuvepFRwaoWw7uRxcLT2PQgEQfCPCAIh6pg1/o4GvRmnD26FxceYPVvrDQg2WG/2ktepPNGJ2y/8mUSzg29+KuW93eejqpX8vf8PDP7NQe3zlTgqs+bgSrgg6L6F4rp3qFYsSrWHADw4VHH3C4IQfkQQxBDRknmwsQTjzfDlDQg2XuJo2QkcDgtPb+gFgMlkYOHk2yj+9n4uyqklBnRWKjo9jjv+nJD6ForrPueCRzjw9fSTMQRJ5FwQ2I6OgiAIwSCCIIZorp3YCouPMWvZm7jRNbkQ8eUNWDhlVFDxErUFRGabeDrbFpKbs19Tz6UkMWP9JWw7sJ7U5M9D6mcorvu2mWcEHTMgCIIQLCIIfNBSLe3myjw4e8nrHDl6nISEBK8QWTz5T02SCMeXNyDYeInTAy7bpVp4cuhPGMu3aeo4SOGR9y/l271udIpLtr4VBCHmkL0MfBAtOf6Dpbl2YjtadqJ6RQCnhEhT5dSv2QehMTv1efPTPz6GpX/+kXinVgx4jO35ST+FH/J1XsHlcrr49MttjHhwvs89DgRBEFoa4iHwQbTk+A+W5lpamJqcyNGj1QNijRBRXPlNkggnXKsnFNcxrHkPorfv0ZS7TZ2pyH4Cx/5SjTdi9758UNCIxmjwFrRU75YgCM1PQB6Czz//nKFDh3L22WeTkpLCK6+8ojk/ZswYUlJSNH8GDBigqWO325kwYQJnnnkmHTp0YOjQoRw6dCh8PQkjLXXP8+baiW3qvcPISE3SWOmqIak6FTFUR9MbGo6Mr9lroTksbsV5BOuBv9UVA+azqMh5GtWYDmi9EXqDnq45HQH/orEp+9ZSvVuCIDQ/AQmCiooKevTowdy5c7FYLD7r9O/fn127dnn/rFmzRnN+8uTJvPPOOzz//PO8//77nDhxgltuuQW32+3zfs1JONzQrYmMtBSmjLlJI0TsaXfhMaahYsRjTPMbTd9cA5niOETCgXvQOw5oyl2WXpTnPIVqaOMtO11wXXnhuZhMRkArGn0N/pHom+IsIa5gHpaDU6v3dXBW77fQUr1bgiA0PwFNGQwcOJCBA6uzsd1zzz0+65jNZjIzM32eKysr4+WXX2bJkiVceeWVACxfvpxevXqxYcMGrr766lDaHjFaUhKfaKC4cC8l3z+CfbdTk1o3mGj65hjIdPZ9WPPuR+cq0ZQ7rRdQmTUbdL7FL9Q/PeNrpYe/voWyE2F9mxW1hBTVgiBEJ2ELKvzyyy/p2rUrffr04e9//ztHjhzxntu2bRtOp5OrrrrKW5aVlUW3bt3YsmVLuJogNBN5Xz9GgvEEesWNRVedWrc2/tzmTT1No6vahfXAfXXFQMJlVGbNa1AMQP3TM74Gf399CyUAs76Mh+LdEgQhVMISVDhgwACuu+46cnJyyMvLY+bMmVx//fVs2LABs9lMUVERer2etm3baq5LT0+nqKio3vvu2bOn3nMtlVjsk85dBjoFt9tVfewpq9PPWcve5MjR4yiKwtGjpUya/SxTxtzkPT/s9/1Y/tpHlJ6oJDkxnmG/7xfSuyo+dpzlr/+bspP3GT1sIG1TtANwgrqbru4n0VGlKT9KH1zlCobdE3CRwGHlD7h0yd7zgbRHj4fy8nIURUFVVdJTk/z27Uz3YXS4vMceDvNLecPPynaDSS33Zjx0KG3IO3nPe4edit8pO3aEsmNH6rtNUH1rqezZsyeg70VTkZub2yzPFQR/hEUQ3HTTqR/2nj170rt3b3r16sWHH37I9ddfX+91qqp6l6v5Itb+4+zZsyfm+gTw3a5kUEvQ6414PG4Kjnl4ddn/aaLc3ehISEjwXuNCp3kXucCFF/y20W15ZvoyKuxuTOY4KuxuXv9gi2b6x1D+NfH5i1Cwa66zpwzBqrqqPQaKGVQHycZPvNMegX5286eMrjOVkJGW0mDf4go6eN3/qCoeYxq57Rt+luIcdyrjoSEJXdpd5IaY5yFWv5dwqm/+vheCIERo2WH79u3p0KEDv/zyCwAZGRm43W5KSkpIS0vz1isuLubiiy+ORBOEJiTngkfY8/lUEnRODha7ee3bs3Go2uV49c1th3uZXEPz9YbjG4k//CiK6tRcY287HFv6GCz5DzV6qWQo8SehpDOWzYqCQ4ItBcE/EUlMVFJSQkFBgTfIsHfv3hiNRj777DNvnUOHDrFr1y769esXiSYITUjbzDNo22s6vxm8hld3XMIJu4Ufdu9nx869fPrlNoqKS+ud2w53BH598/XGsg+JPzStjhiwpY/Clj4GFCXopZLhomZwr+o0C1v7SRHJ6NjaaalLiQWhKQnIQ1BeXu619j0eD/n5+ezYsYM2bdrQpk0b5s6dy/XXX09mZiZ5eXnMmDGD9PR0rr32WgCSk5MZMWIE06ZNIz09nTZt2jB16lR69uxJ//79I9Y5oelJTU7ku+/3YHe6QFVxuz1eL4Evyznclpuv6H/Tsf/D8uvCOnWrMsfiSP2j99iXpV6zAuBM92HiCjpELAVzuAnU89Kc+1A0Jc2VtEsQWhJKaWmp6q/Spk2buO666+qUDxs2jEWLFnHrrbeyY8cOysrKyMzM5LLLLmPq1KlkZWV569psNh5++GHWrl2LzWbj8ssvZ+HChZo6sU5rmKstKi5lwIh/YLM5MBkNdMnpQFJiPAum3OVzgBo7fZlmKqFDRiqLHwnf3K6p5BUsRcs0ZSo6qtpPwpky2O/1cQXz0DmLqaisxBoffzKnwl+bZJ+GxlD7vXbMTPUpyMZOX8bP+w6SkJDQYL2WSiz/nxOEcBOQIBDCQyz/ONX0TXGW8O2H49CrJyi3m3jxq67EJ3YA8DlAFRWX+gzCazSqivnICuJK/ldbjIHKjtNwJV1Vz4VaLAenouCkoqICq9WKirE6iK9WEGC0zeePeHA+DseplQsmk4GXF030We/YsTKsVqumXqykQI7l/3OCEG5kLwMhKPwNFObCZ7i0aynlFeU43ZAUryOz7zjGzX7O59RAIEF4QSfuUT3EFczHXPautlgxUZk1C1fCRQH3VzUkoTiLTx6oqMakenMARBOBJijytQ8FNN9W2oIgNB+y26EQFP6CAA1V36NXXCQnWkhLjuOiXDsZaSmNCuoKKnGP6sZSMLeuGEBPRaeFQYkBwJuC2YPBm4K5uYIPg2Ha6GuYMmgPDw/6L5MH7WHa6N/5rOdrHwo4FdvhcDjZuecAH278VnZ1FIQYRzwEQsAUFh/jXkyeVQAAIABJREFUs6+2Ybc7MRoM5HbuWDcIUFE01nPNv/0FdTXkeQjYIledxOc/hLH8c20xBlyWXrit5wXd55oVAL+U7/HmBghlmWBT09Gzhk7npIOSUT2t4XkDG3WnNWr2oajtVq/xMOzZf4gquwOL2SSeAkGIccRDIATM7CWv43Z7cLs92BxOdu/Pr2Ppu+J6oWIEFFSMuOJ6VUeyL2k4TqAhz0NAFrnHTvzByT7EgA6XpQcec/iCV8O5TLC+TYoaS2OnNWqWibrdHixmE11yOsj6fUGIcUQQCAFztOwEXXM6Emc2oVMU9Hp9HUvfnvk3XIn9cFl64Urshz3zbz4H+9oDodt+pN7lh353TnRXYD04DmPFV5piFR0eXRIec05UWvEQ2j4GgVBbRFU6zUFtwVwT2zHw8j6cnZtDnNkk6/cFIcaRKYMooKVEdKcmJ2KzO+l5VmfvEsHa7fSVQc9XroHau/X95aIjzFmf6zMIrqGsfIr7OPF54zDYdmrbocThiuuBx9wx6lYAnE6kAhRrT2s8/KoxpCBBWb8vCK2HmBMELWVwPZ2WEtEd6uDgK+JdceVrBsLze2TQ8b+pAd+7sPgYS55/gfGXfURSm3LNOY8uEVfcb1BNPrwJUYZ3FcPJJYyqse50SCjbI9cWUQeK5oeUAEq2AheE1kPMCYKWMrieTkvJs14zONSIrnGznwto8PYlJFTncs1AaIpPC+pzWv7CSiZe/m86plRqyj36FMq7vIqqj77If18EEqBY25tiLl4RtNcj0GWIgiC0XmJOELSUwfV0WtqPtS/RdfqWu7WpERJeS7fqcVTFhEeXhKLago7U19nz+Ef/j0hP0G5f7NEn4Yrr2WLEAAS2SVE4phVag+vfl3dQEITAiTlB0NIGV4ieH+tAp1tCFV0aS9fjwGNMo6r9w0G1UWf7GWveAyTWEgNlNjPxqd2jLoVwOAhkWsEfrcH1H6xQFQRBS8wJgmgZXIMh0B/rSMdHBDrdEqjoqt3ep/9cQpwpdEtXX/UD1rxxKB5tzEDhiQTiU3+Dx5Qe9TEDodAS8h5EAy3ROygI0UTMCYJYtoQiHR8R6A+qL9FVduyI3/Z+u7OIS85JD8nS1Vd8h/XgJBRV6xlwJA8mrvtEPIoeWxB9DSehBP0FQyDTCoHQEgNug6ElegcFIZqQPAQtiEhbQIGmF64RXS8vmsjiR8bUO6jUbu/zX5zZcD6BejCc+ALrwfF1xIC9zR+paj8JFH2gXQyZ4mPH613HH6lcAuHGX9rplk5NMqXaaZgFQQiMmPMQxDKRtoDCPd1Su716czq29r49GvVZr8bjn2A5NAMFt6a+Le0O7Gl3ngq2izCr33qHP573E0lxTo7bjDz9fBWPTXoQiFwugXAT6y51X95BX54rQRB8I4KgBVF7wB41bBBjpy8Lmws43NMtwQgMX9MhS/7eCUvBPBS0O3RXZdyDo+3wsLUzEG489wfaWl2AQlurnd/nfuM9F46gv6ZAXOqCIDSECIIWhIrqzUYLsPiFtzh2vCJqcy4EIzA89iPcf+VOEs0OTthNHK2MJ77gFU0dFQVbu3E42gyp9z7BzOcHU7dtwqkX7/Go4CpjxIPzSU1OZNroP9HR+EbUB/21xIBbQRCaDhEELYjaVvSuX/I4u0sO0PJdwCMv/gWLrgpQ6NWhhE5tDmrOq+ip6jAVZ/LABu8TTBKfYOp26nQGJUcO4HC6qbLZcXoSvXPxkxf/C4s5iaNlysmBVkdGWkivIaLEcsCtIAiNR4IKWxC154BBCSgIMBwUFh8LanOcYDn/7AzizCZyUivo1EabfVBVjFRmzfQrBiC4+fxg6paYb+HsHn3o3bM7dtqw6tvuQPXn8NV/d8Z0sJ4gCK0DEQQtiNqrAPqd273JoqojHaFusqTSK9tN++RaYgA9BQkPcO+i/xeQGAloq+QQ6rp0yd4tj1///jKOVZoBTn4eSkwH6wmC0DqQKYMWhK854KZaRx6OCPV65+xVFzr3CfSuQk19FT3uuLPZ9d91HC7K9U6VPLToRSxms89gymCS+NSum6/7I48FEKRZ+3NISbRSeqJCgvUEQWjRiCBoQTTnHHA4ItR9ztln3k/8oUcxlm/S1FUx4LL0AH0CJl2JV4y4lQq++vVNEpL0GLBwougSTTBlMEl8atd9bPqygBI/1f4cfti9n5ETFnKivIqEBAvTx/456HcjCILQ3MiUgRAQ4Uj6UmfO3nmM+PxJdcWAYsajS0LvyEdX9TPozN6pkiOGzWCsAsWDUynnqPGLkLwVvmIiQvWCPPfaB+RkteOcs8+kc1Y7nnv9/aDbIwiC0NyIh0AIiHB4JzTr9T1ODPaf0bmPaep4jO1xmrpgsO8G1QUK/CY3h46ZqZSUnsBodJNiTMTpcqOg4KIyJG+Fr7wHoXpBYj3hT6DEempkQYh1RBAITYZ3zt5ZjMG+C51bG9XvNnWmIvsJ4n59Ek9cV2+5BbxiZPqaQ+QfyePnvAIcTicJxhSf3gp/g5OvQXzhlFEhrdOvERKp8XZG9N1NRrJCXMG8sO9pEA4iuUVwpPfaEAQhsoggaGJasxWlGlOxp43EmvdAXTEQdxYVnRahGlLqzfynOEsYd14SizcXknyGSmLKBdz7+xmkJdZ9f/4GJ1/egFC9IDVBhrf8ZhPtkj107dzRu6dBTYxCpDdACpRIbhEsnhJBaNnEpCD4ae9Blr78DvEWM1ZLHJY4s/ff8RYz8fFxxMeZiD95XLuOwRC5zXKi1YpqCqGiOA6RkHc/OmeBptxl6UVFp8dBnwDUv1LAXLwSi8nGrKsvBVXFY0zDlpjh81n+BqdwZu2rERKWg/koOE/197S8BsEkQYokkRy0JTWyILRsYlIQHDhUyP+u+zjk601GQ7VYqC0aLNWiId4Sh9Viris0LHHEx9WtY42vPq6sslNSejzsP8jhGMwjLVR09n1Y8+5H5yrRlDutfanKHEdc0RKN9exrsAwmkZC/wSkSKzYa2tMgWjZAiuSgLamRBaFlE5OCoLLK3qjrHU4XDmc5pRH6zdbpFPQ6PXq9DrPJSP+hEzTCwhJnxlojMGqJEV91Hl++huJjxzEa9ByyOUIazCNpOeqqfsJ6cBw6d5mm3Jl4OZUdHiWu8ImArOdgNhFqjsGpoRwITb0BUn0i0dd78bUjYCgiU1IjC0LLJiYFQUWVrbmb0CAej4rH48LpApvdwbYf94b1/nq9jvc+3VpHWMSf5uGoPVVypKSUExU2DHo9Op1CZloK237cq/F2xFviMBkNKH62HD59vhycGCu3oXi0GQgdSddQ1WEyKIaAredgkg6FOjg1xtvSUA6EYNoeDurz+AS6RXC0Tm0JghA5YlIQ9Du3O088fPf/Z+/N4+uq6/z/5+csd01ys6dN2nShKS37UiygqLiwqDMuI/rrKDqoOAUGCwhiKYIFKVDZpRTcka+CwjA46oiDijiytGVtgZamW9I2603ulruc/ffHTW5zk5vkJk3btJzn45FHcj85+zn3fN6f9+f1fr9JZXRS6QyptEay/3d60N+pdCZvmVQ6QzKt4TjO2DuZwliWTXdvbOwFx+Dp514e1ibLUt60SMDvJeDzgmNTXVVB0O+j1NlCUNU5cVaaL5+5FyHnX88d2lk0d32GQGI3Qb+XioSPUjlNwCejyow4eh5P0qGRGEvct2rNY+za08n2ljZ0w+DFV9/m9z+5eb/2CZNz7ONhfz0+rkDQxeXdR1EGwfPPP88PfvAD3njjDdrb21mzZg1f+MIXcv93HIfbbruNhx9+mGg0yqmnnsodd9zBwoULc8tEo1G+9a1v8fTTTwNw3nnnsXr1asrLJ19h3zSngaY5DRNa13EcNN3INyIyGsnUYCNCyzMgcsuMYGgMtCdTaTKaMfZBTGEsyyaRTJNIpkdd7lOnadzx+RjqEH3m7b8N8O1fbQG+U3A9VREE/O0E/V/rnybx5Xs5Chgj+R4PT56mIxgY0HpkNSHBMcR9vbEE21vayOgGAojEk5OqxD9Y7K9WYCoJBN/NkTkuLgeTogyCZDLJMcccw5IlS1i6dOmw/997772sWbOGNWvW0NTUxOrVq/n0pz/Nhg0bKC3Nvki+9rWvsWfPHh5//HGEEHzjG9/g3//93/n1r389uWe0nwgh8Hk9+LweKssn9yXY3NzMUUcdRXrAWBhiNKT7DY08wyI90jLZ/w9dR9MPvcHxxbPS/OySBEODNa57NMitTwWAkaccDNMhlkgRS6RGXGZ/8HkEAa8g6JP6f+/FW3Z9v9Hh5e2tLfRE4rlD9CgKL29q5r/rQszd0VVAVLrPYPH7PGNOpxws9ldDMZUEgjfe90Peiv8BizS7In5u/EGCtSu/dciOx8XlSEVEo9Fx+ccbGhpYvXp1zkPgOA4LFizg4osv5uqrrwYgnU7T1NTEzTffzEUXXcQ777zD4sWLefrppzn99NMBePHFFzn//PPZsGEDTU1Nk3xaU5Pm5uYDfq6WZQ03NNIFDI1ijJFh29ExTHPU/S/9aIq1X+sb1n75z0q4/+nAgTrtKcMwD0ael2NADLrPg2FZFs+t24SmG5SXBfnipz7M9NpKgoHhkStej3pADI6D8VzuDx+86oNoThyBwMHBK8r4211/K2rdgXNzvQwuLmOz3xqClpYWOjs7+dCHPpRr8/v9nHnmmaxbt46LLrqI9evXU1JSwuLFi3PLnH766QSDQdatWzelX0aHG7IsUxr0Uxr0H5DtG4aZ550Y+Lt52w7ObHyDU8ry8/jbDvzqpVqSdhmfe79NSoMEcwdNt+wzRsaahjgcSGU0UhkNIhMLUfnbSxtH/J8kSXnhrkO9E3nhr0UYIwOGRiKZxjBMVHVqSook1QB9wBAS2c/jxBVJuriMzX6/ATo7syVra2pq8tprampob88moOnq6qKqqipvdCOEoLq6mq6urhG33dzcvL+HN+U43M9JsaPMsH9NHdnzSNDEXv/nOeH4TUx3hhgDyCTE0XziDIVPnJkNt9NFBa3yFwptmuvv/hWvvr0T07SRJMEx82Zw8ec+Qjqjk9ENMhmdtKbnPqczOpkRPqc1nYxmDPt8OGPbxek3JoosS/i9Hvw+D36vB5/Pg8+jjvrZ7/Xg86oFP/t9nv7pt+xnWZ5YLbWFs2bzxvbNmKaNrEgsnDV7XN+j5uZmWve0Y5hWrq1lt3bIvovuAMhlqjJpQ4KhrkzHcYYZAEMZusxQjrQvzlR3zY6FMHoItN6IpHcCDuClUt5OhXwfir4zb1lHeEjPuAXhPRrfQLidUoZUfTFNg1T9g1X/V5/Tyjc7ZDoiCqoqM72uhn8+7+xJO37HcXL6jUJejlRa2ycYTWWXyXovMnR0dSMrHlJpjVff2oZpWliWjWVnf2RJIqPpk3ashwLLsulLZehLHZiwXa9HHRbuOmqSL382MdjxlRcQ7foDmt1HeWkZnzn1K5giPxeH3+dBkoYbHAPfucYZ0/NEkvW1lYf1d9HF5UCw3wZBXV0dkPUCzJgxI9ceDodzXoPa2lrC4XCeAeA4Dj09PcM8Cy5TF2/4x0hmAoEJ2DjoSFYSYeXHsTuSn+SM1VjBkwFGDbfzhn+MkWxnW0s76BGu+ZiHn64/DY9HJT3JHawQIudKrx7nus3NzcyfXYk3/GM2btLpijn8Yv18Iikv9bWV3HvjJXn6jWxkynBD4ye/fpqeaALbtjEtC7VfeZlMa8iSRGN9DaZlZY2RIZEsY+k3pjqabqDpBpHYcI1J8XTzxCO3F/xPwOcdlsALx6a6shxZktjZ2o5pWQQDPhbMncEPfv5UvzFRKF+HL287B0q/4eIyldhvg2DWrFnU1dXx7LPPcsoppwCQyWR48cUXuemmmwB4z3veQ19fH+vXr8/pCNavX08ymczTFbhMbYQZx5E8CNsGHAQgsPOWsaVSUo13YvmPKXqb21rayWg6jpAo8xk0t+xl4bxZUy4X/kA9goVHTUPdtZeLztjGY5vOyinwi9FvPPXMC5SW7BNXejwKj9xVnGLeMMxhIa8DHoycxyOt5wlDuyMxXnp1C6l0BkmSmDG9Gsuy85bp6w+HtSx77IOYwgzoN3oiYy/71taWcW1bkqRcKvOSoJ9Xfne/ayC4HHEUZRD09fWxY8cOIDuPuWfPHjZu3EhFRQUzZ87kkksu4c4776SpqYl58+Zxxx13EAwG+exnPwvA0UcfzUc+8hGuvPJK7r33XhzH4corr+Tcc8913XaTyIFWUjtKGbY6E2H2IjCGBQ/aciXJxruxfUeNa5u6YQCCoN9LV8zCMm3qayunXC78gYyKXo/KsfNncwwqZ3xmfMK0/YnvV1WFkKoQKg0Wvc6ylWuZPXNabn8NdZXDxHTNzc3MmzcP3TD3GRpjRJwUzL2Rzk/y1dLWlTe1cjhj2/umU5KpjGsMuByRFGUQvPbaa/zTP/1T7vOtt97KrbfeypIlS1i7di3Lli0jnU5zzTXX5BITPfnkk7kcBAA/+tGPuPbaa/nMZz4DwPnnn8/q1asn+XTe3eyPkrqY8rxa9cV4ux9ASQ/PJKBRhT77fmzPzKL2N2C8WJrGx5ssplVKpIwAv90yj3PeX8+9N049Bfhk1CM42PH9xWYcFP2GjtejUjFJnpllK9fmnkfLtqmrKuemq740tqEx7hBZ7aDqN/w+z0Hbl4vLwaQog+Css84iGo2O+H8hBMuXL2f58uUjLlNRUcEPf/jD8R+hS9HsT7rZeMs93Pd//0tU0yj3ell2Vh8l84ak7BUystaSV+IXwFLrece+illDjIHRjIx9xovC2udPoqO7l6OPmjnuTvJgxpfvTz2Cocd553VfPyhx8Icy42Ah46eqooyqiskv7GTbdt50yoChsHXbdioqqwfpOEZJ8jVKvg7d2KffCPh9k378Li5TgakZeOwyIfbn5X/f//2FjmQKSQg6kinu/cdfWDHIIBBGmODuq5C1HXnrWd6jSDbejb6zZ+gmc3PuhdIEDzZe/D4vRx81s+i59MHc/+OfccEx6ynzGcQzKj/4SZqbr71q3NsphrHqEYxmnByqOPhDmXHwYFY/lCSJkoCfkkC+fiPkF5MyLWmaVs6IGBy+6OJyJOEaBEcQ+/Pyj+gWUv9EgIQgou176Qmjg2DLFcjGnrx1TN8xpBrvwJHLgOEGgdC7kfQdCMfEEUpe0aixjJdiR/4fm/8y5T4NEFQFNT7WNLwg08FitE7/UBULcksSTw6KIhMqDY5Lv+HicrjhGgRHEPvz8i8tP5lweAMSFraQKS3PhgxKWivB1iuQzPwEUmbgFJIzbgN55HTEktmGsPWsh8DWkcy23P/GMl6KHVFXlThYZv7nYvQQ4yUciXP/yrWjGiijdfpTqViQi4uLSyFcg8AFgMs+dhMPPL2KaKqHykAll523AinTTLD1KiQrP47LKDmTVMPNIHlH3aatNiBsDeEYOJIHW91XgXI04yUc7+SN2K/R1SQKfqrN99ETVQsu2zTvGHbt3IRuWHhUhdlzjhl1qmKiPPTYMyQ1a1QDZbROfyoVC5ps3DoBLi5HBq5B4AJAdWktN1xwT+6znH6TYMvVCDs/iYxe+iHSDd8BUbiDHoyjVmezFORU+fnpgEbqSNb8aRUoaRzDxqCPbuUfzAwV7kClmZex0P+jPG+A6Lgzu09AM0w2b3mdm7+/er86q1gihcebFZON5PIfrdM/kl33bp0AF5cjA9cgcBmGnHyV4O5rEU5+znw99AnS068BIY+wZj5jqfJH6khiqV7mz5lBc8vebNEdxeLrS85nWQGXfSGh3+DwwG279tIVk9B1c786q1BpIOchGMnlfyR3+qNxqPQRLi4uk8vEqo24HLEoiecJ7r56mDGgVX6O9PRrizYGYJ8qPz3zFjLTrx02j1+oI+kMR3hrcwdvbdsFDiw8aiYfWLSIHz76R9q6evM69pHQqi/GVqtxUOmIKfxi/fy8fUyEpUvOoaGuEo9HmZJJkw4llaFS7H7BqKuPcHE5fHE9BC451N6n8HfeicDJa89UX4RW/ZWcG36iDJ0i8Hs9ZDQjb9S9as1j+BOLSKsvoFkpWnf3ceuFK7jyxZ8XPQod7DV47KdriaR6kcT+dVZV5aWjah7W/GkVsVQvoX79RXVp7YT2czhyJOsjXFzeTbgGwUFmqgqw1Ojv8XfeMSwDYbr2UvSqf52UfQydIqgoC9JQV5nXkXxz1Q/xilKmm+cC4NEUqktrJ6zSH62zGnovblh6Lg324+OOTljzp1V0xdoQQqIr1sYDT6/K02Mc6bxbp0pcXI40XIPgIDNZAqzJNCw8vb/B33lfXpsDWN6mSTMGYPgUQVrT+eGtV+QtM1LHP9FR6Gid1dB70brhJmaeUDPu6IRYqhchsrNvQkhEU8NzMri4uLhMdVyD4CAzWQKsSTEsHAdv+GF84R8PbUZT5iD8C3JthWL7wcm1NVogjG+OOqIuZpR/w9Jzad1wEwE5RkNFhlD10ajtt1NXffGkj0KH3gtVJEH0u/qFyBYzKoJQoDLnIXAcm1Bg/3IeTAbv9mkMFxeX8eMaBAeZyUpQM7gzs0SS16PPcNXDLxT/8nccfF0P4O3NF+dZNmzpDNGdkjnl3H1RAYVi+4Fcm8fpG3NEPXSUf8PSc/G1355nZDTYjzPzhBokLY6wZRxnN7ah5m17shIPDb0XuhMES0cydiNsHVspRRi9Y277svNW5HI4DFz/sTjQU0eFpjEuPXe5ayS4uLiMiBtlcJBZcdmSSVGrD1Z2dyv/ACWNbuq5l/+oOBa+ju8PMwbShsQX1zby4e/V8eU1Xjpj+x6PgdK/2Q/Z0XOhtpEQRg818fu49PS/c+n7XqfUm6Yy+UskI4zAQOo3Mga2KRyz/7cxbNsDxonAoCfays2/+gxXPXwhKx9fRjjRNeIxDGXovZh12o0Iq6s/kZKKI9fkDJ/RGMjhcNeXH+HGC+4tqpMd8PAUEzUxEQpNYwwYCUU/Jy4uLu8qXA/BQWayBFiDR9uqajFv9gygiDlsx8Tfdgue+DN5zSldZcmael7Y6gHHxrLsvGmIkUr/5rUpI1ex84Z/zOadb2KZBuU+OO+oDTRvg5MW9ldI7O/0B/bjCAVh6ziSJ7e/gVH1xYteJuiTmDe7nnteeoXOZBrHXzduQV+he2Hrc3AGVXMsdtpgvBzo2P1C0xgHW+twuE1bHG7H6+Iy2bgegsOUgc7skbu+xQcWLUJVs7dy1DlsWyOw5/phxoAtlxOuvYPXd5ciCYHP62HerIa8TmpwbL+tVqNVX5zXpouKvMRDwujB1347/t0rstMCRhjdsAABCMp8Oj19WUOi/8Bz7n9brcbyzMVWyrC8c3P7GxhVx9IKGU1j2642opkMkpTNmjgZnZyjlA07pgPBRGP3O8MRlq1cy4VXrWbZyrV0hQuXJb/svBXUhRrwKB5qQ/Vcdt4KQoFKHMcGxnhOJonDzSNxuB2vi8tk43oIjgCKmsO2UwR3L0dJvZLfrNSQbLybkHc2Z5++vqC+YfjIaRnV/fPqA/P6rc3NNA2aax+qORDGXjyqTEbLjr7jGQ9Pb1/E2WcYeZkMRysxPDCqfnhdE19a3Ey5YxIKlNOhZ+feJ6OTGyu74mQx0aiJYsWkQ1NRw8S0DvtDLNWLYVg079qNYZp4lDaWnh2dEmG2hXCjRVze7bgGwRFAoZd/HlaC4O5voaQ35Ter9SQb78Hx1AMjd1Jr/ngD4fDLSFiE+2Qe+J8buOHzD456TEP1BbZSz+w5IZq3vU1Pn+Dp7Yu48qJPgf140ec5IAKMpX3c++xx1NdW8p2r/qVgJzcwvWBr3Vx05g4WLazFE6gaU4A4mkEymUx06mi0qYaxhIpjPieTSDjeyfaOLezubgNbQnUqEFpgStc5mIrRIi4uBxPXIDjCEWaEYOtVyFpzXrvlmZ01BgYVHBqpk0pEX0dyDGzHIZXqY2f8r7z6+3/L62SHMkxz4KlBTL+W+XOz/z8D8LXfPq6qhCsuW8L9P/kp5ze9TFWJQ9O8Y5B8SsFObmAkfcXZm/FLabbvSnNskzMplQ8PJaNFqUylIkNr/rSKmrLp7OnqwMbCEn3UGJ+Y0nUODrYHxcVlquEaBEcwwugi2Holst6S12755pOceReOUt6/3MhhfOF4J83dHURSaSSg1uNhfo0PvxTN62ThM3n7GOx679Il7npxJ7HMhXlirfFEKUDWYFn9JQPJaOg3NOLYI3TwAyPpUq8OSOiGOa7cAkOJpMKsfPz+Qy44G22qYSoVGYqlevF5/JQpDWR0A+FIyE7wkNY5GEs0eDA9KC4uUxFXVHiEIul7KWm5bJgxYPpPoK/xvpwxAPlhfNKgHAOQHen5UVGEwLBtoobBV+bXMlYnO7iw0V2vxelK9AwTa01EwFesETEg2ktoHsDGoyr7JRJ8bMNDh0xwNlhIeMuaR7nu0iU8cte3uPfGS/KmBKZSkaEBAWPT7Aa8HgWPFDzkRaFc0aCLy+i4BsERiKTtINhyKZLRntduBN9DsvFOkEvy2kfrZGOpXjpiZUzzlzErWEqlGmTb3jLG08mOJNYqFLkwFsUaEQM5Bh59dSFpq5yjZs/CVqvZI11QlEp/KAktNqbgLBzvZOXjyyaUE2E0is1ZMFk5LiaDgSiHkkCAsxedzhMrfzPMgDnYuKJBF5fRcacMjjCk9BaCu7+JZMXy2o3S95Oq/y5InmHrjJRjALIjPYTKzp4yLNsiFRc81FLDw/8eprbcRhh70auXQp894jGNJNaaiICv2CiAoXoIG8gAN69cO6F59lJvCM1J5p3DsOqNc98gofVMepGjYqcCplKRoQPpfp9olkdXNOjiMjquh+AIQk69QUnrsmHGgB46l1TDTXT2JguOjkcbqV923gpOP/4UAl4fAbmc981cwhPfmU9t/XEQXICjNuCJPTHqcRWKiZ8og6ciMtOvHXfK4onOsy85belf54KrAAAgAElEQVSwcxg6ct/w1qYDMgKdSlMBU4GJZnmczOfQxeVIxPUQHCEofesJ7FmOcLS8dq38U2SmXQVCGlGFPtpIvbq0ltsuXJvX5m+5GknbgXBMHKHgDLjwR2AqibUmWkuiPFA17ByGGheWruI49qSPQIcKCb++5HyWrVx7UEpoH+rsfYX2P1Gjbio9hy4uUxHXIDgCUOLPEWj7bjbv/yAyVV9Aq1ma0wdMlgpdMtsQtp7VG9g6ktm2fyewH4y3w5poQqBCDDUuFpR8jLpQ26SHrQ2dCli2ci0tXa30qs+zPZLmwjuf5JfX/TLvvAeuS1esnT09O5lRNTs3Kh5Phz60SNJdv7ser+o/aAbCmj+tYk93C9taOtBNgxde+QKzvB8noxn7XSDMxcUlH9cgOIRMRsU7NfY0/rZbEVh57Zmar6NVfymvbbIqLdpqA8LW+osAebDVBtDGXq8YxlvJcGiHdcdTN5DeceKI13Qy59kLGRfjuX8THX33xhL0qs9jiD4Egj69d5heYeC6NHdsRtPTpI00wLh1DUOFeK/tfIm5dUdPuk5itP1va+nIhi4CiUwU/NBQVzkpRp2Li8s+XA3BIWR/K955ep8k0Pa9YcZAuu6KYcYAjK5CH157oHfE/TpqNbZ3LpZ/AbZ3bl5yo/1ltBDIQgztsNa/uYm2rl6SepRXI4+y5I6PT6rifzCD60lMREE/0TC4ylApJmkEAgfwKOowvcLAdTEtAyFJGKY+IV3D0PoHwEFV6nukID3RGPG+JIlkEmF5SWs699xwCXd/98tUHrOF2/5w+QG7xy4u7yZcg+AQsj8ufE/4/+HvvCuvzUEiNf069MrPFlxntA5sPB3xRMIFi2W8yYqGdli2oSIJQVj5B6boQzO0KRtzPtEwuBWXLaHUX46QwOdRmTdr+jC9wsB1UWQVx7ZRFc+IuoZwJD5iKOZQId6Jsxcf1AJJ0ea52LoPxxKYGS/RbbMJljisfHwZF/7gozy/5c8k0vEpe49dXA4n3CmDQ8iEXPiOg7f7h/h6HslvRiHVcCNm2dkjrjqaO348HXFhEeLkjBRHC4EsxNB0s1bJafT0GJikAYGqKFM25rzYMLhCUwu/vO6Xo6bZHbguCMGecL6GYCgPPfYMSc0qGIo5VIi3eddWrnjwMpJ6nKCnjMuXHthOONkHRymfZHtLG7phovo8lDftpCvWg2ZqWLZFS3g786cfOyXvsYvL4cSkGAS33nort99+e15bbW0tW7duBcBxHG677TYefvhhotEop556KnfccQcLFy6cjN0ftoxb4ObY+DrvwxvJD/NzhIfUjFswS84YdfWhFQgH5/Ufb0dcLOPVSRSTZ2C0ufeus6OseuBRuqNBUNI0zW6YUjHng4/do/gIBSrJGKlRRYhDdRID8/ajzd2PR1EfS6TweH3A2J6qBx/+C2WJD1IuBLbm8OAv/sw9NzSNuv2Bc+6MdLJ9Rw8V+hnUhaYXpbmoDJWS0QyOnT8b23Gor61Et19ACAlFVrFtC8PUp9Q9dnE5XJk0D0FTUxO///3vc59lWc79fe+997JmzRrWrFlDU1MTq1ev5tOf/jQbNmygtPTdqxAel8DNMfG3r8YT+5/8ZilAcsbtWMGTx9zEaF6AA1X2d6yCOwUNhjGSFY3UQcK+axpOFK6CeKgY6BRf2vospm0xp24+qpGhLtTAqn99aNR1D3SGvVBpIOchGMtTNZFproH7tXn7btK6Ttp5DqvrnKKSQhUymtc+u4WuWBuza5vY1bkVWZLHzCtwqMMnXVwOBybNIFAUhbq6umHtjuOwdu1arrjiCj75yU8CsHbtWpqamnjiiSe46KKLJusQDkuKelE5BoG9K1ETf8trNkWAHzQ38uZLdxX1khvmBZA8WQFhkYr+AQp14iMxVgcy2GBo6Wrlwjsv4NgF00Y9n2I6yP2JOS90T0ZqL7ZTGegUM0YGx7Fp6WqmqUg394HOsLd0yTk89sd1RXmqJjLNNXC/DNNEQmCSKtqYqK0uZ/k1F7NqY4RezeKW7QaXfOBafvPcaqKpHt674CNF3YfRjEgXF5cskyYq3LVrFwsXLuSEE07gK1/5Crt27QKgpaWFzs5OPvShD+WW9fv9nHnmmaxbt26ydn/YMqbS3M4Q2P3tYcZAVJe4+K8xXumI0adrPNuyi8/+7HqWreumK20W3NdQMSCIcSn6BxhPdMRYWfYGDIaAr4dkxcOkeJ23dv2NPd1bRxSJDRUSDu0g96emQGfa5PM/X8F/bnybPze38eeX13PHUzcC+1ccZ6BTVBUPDmBYRtGd+4HOsFdVXlp0tMRE6iUM3C9VUbBxUPAXbUx0pk0+8Uwbf9zdx2s9GrsSOg/uVLnhgnu468uPcOMF9+aMgc60ybJ13Vz4945h34PORA9vx0xe79V4O2bSmQgXcWUKH89I+3BxOdyZFA/BokWLeOCBB2hqaiIcDvP973+fc845h5deeonOzk4Aampq8tapqamhvb290OZyNDc3T8bhTSmGntOerlZMa19Cod1aS24ZyUnTZN2Lyjt563SnBd99NchrHW3Mra6hOSXQHRBmmG3dca79vxjXzRkpe+C+MsVzrfuR2PdCs2ljR9/Y17x1TzuGuS/UsWW3VvDcAJZ8bDEPPfq/RBMpQqUBlnxscd5yMjZ9fX2UNzxNJpZNdpTRNXZ1bgLHV3CbH5u/hEdffohEJkqpN8TH5i/JW27tc7fQm+xGCEFvtJdVv7mWS95/3ajnFEmFeWzDQ7zcG6e3501seRqO5KFX9vHCa6/w1dNHv1djkdFk3uhJYlCPabYQUiW8BIcd+0gsOemyfcfaESPSERtl6fEznu/aZUs+kvs7FukmFukedfnFs5dw+z8eIlU+nXRaoix8NEGfnPcshCNxHnrsGWL9z8nSJedQVV7KLTsFPWnRb0TZvBMxkfQ0zc3Di1LdslPQrQuEgN44/d+D7Lltjqn0aQZCCDTH4e2YOqH3S+F9jJ6pcyhNTaNrLlxcDhWTYhB89KMfzfu8aNEiTjrpJH71q19x2mmnASAG5q77cRxnWNtQjrQvTnNz87BzmvF6Y547uDZUT1NTE8KMEdj9TRQr3xhoT8vc9lY1MSTKgxUEAn7QDGTbRvVXUVISxJSgqWnamMfja6/PiQxxHGy1mqbpw695Z9rMuWwrvTLVs2YRbe/IuY3ra7Oj3KHn1hmOcP+v/oyJROOMwiKy1dctzc4R45CSSrEdC8mBUttkRm3jCM9AE6edePrIJ/aCRUnJoIqOijnms7Ty8ftJ2H1EDRMHwO7AYia25RCNmvREE8yozd4rwzLZ2bUVRZL51ev3F+Wytvdei/TGXShGDG/pLBaceBV3fXDhpM9t5wR8iR62p4NUNF1OXaiOFSdUUOsv/HUv9FyOxNBnYbTtDnD/unKqT1qVe14aAgr3LM4fINy/ci1JzcLj9ZHULB774zruueESrPYOAh6NjGUj+tdvrCqhqalm2H6s9g5KBtXuMiWABE1NTdQd+02sLfdh6lEUT4i6Bcsm9H4ptI9ivmsuLocDByQPQUlJCQsWLGDHjh05XUFXV77bNhwOD/MavBsp5A4WRphg63+gZLbkLaups3hw13H02QFqQ/V8/0sP59ZVfHWEZn2Rtje+w95XvlGUq1yrvpikWcbrm3fzl5f3cvXDasFywKs2RmhLmeg2tKVMpLPOzXMb37D0XBqtn+eSGoV73mHl48tY8v1P8GrkUZJ6dMSphZwIMLAQNTATSfJgOYKMVD5h1/hYUwqFiKV62ZawcGwdhI1kxZCtvVi2F6v9GB569H9z92p3eDsCmFE1p+ipg6RUQf2JNzNz0X3Un3gzfVIFsH/TEIXICfgiSWJ97bRtuY+2lMmN67ZOSmnmoc/Cqo2RMdfp7RcsZkybzVGdP+1NDXO3j6Q1qfTKzC1R8MnZV1XIkzVCClHplfOnp7z7hM11oTrqjl/JzEX3UXf8TdSFhuudRsJ2HNpTJhvCGWK6TUfKLLgPF5fDnQOShyCTydDc3MxZZ53FrFmzqKur49lnn+WUU07J/f/FF1/kpptuOhC7P6wYKn4TRgfBlm8gG3vyljN9x6A13sFV8/LDAW+44B6W9o/aXl93HbLRxbyQtyjhlKNWcsUj1bR1HYeu+tg281j++z/f5uyTmvJGfgMvdMi+rFNC4aFB6nBf++2knQiCEoQR5sE/fY1wMsXM8hiGCV2x56jKfHxUEVno6OtJbb4NRQ0ie8qYvvDbRY2UCwkcB+cm8HjKaa9ZyoV/7xh1RBsKVKJbMRStBdOxsOQQpjoLb3uEeTPOIJpIYSmV9DSuINHahoqBkFWEEEUJAyu9ctaYGhDjebPHMNkRBDkBn+0gCQlTjyIJweaNdyMFokWL6kbyBAx9Fno0a8RtDGxnS1QnatgkDRuvJAiqUs6YGPAUjCRWXHFCBas2Rgh55TE9EgPL9mgWlV6FFSdUENuTNXAvqE9z+a9XYuhRFE85V37+u7n1dMthb8qkNWmyO2myJ2myO2mwu//z3n4DCMdAMhNUqDqNJXNz+3BxOVKYFIPg+uuv57zzzmPGjBk5DUEqlWLJkiUIIbjkkku48847aWpqYt68edxxxx0Eg0E++9nCGfXerUhaK8HWK5DM/NGbGTiF5IzbQA4UXK/Wn3XBXrUlg276+luL66g6Y+10qn+jt8SPnViHqVxIW2pO/st6UGfmWBplqXXc8rN7iOgWpeUnc/UJMlXsQU6DI1Tife1IBFAkgVBs6ivDpPeOLiKrq5iBddI9uQ6hLjD6ozngGn/u5ZcxNJka831kuoxcKNtAZ7dsXTc9KRNp0Ih2qLsasp6aF37xHVKxzaiqD8Q0ZNugtMTBY6gEvXJudCypIdLpTprjcExIKcoDUaizguIiCMbjph/YnioJ0qaFxxPCdhwkKzYuw+P69R288M4eTMNEURUymRk89IEZuWfB0sJ0v3Mfqh3j23vriE6/lKRUMez4Vm2MUB+QSScc4jbowEll6jBjYqScHAPPdjHXo9CyMSBh2Hzrd2tJiGqMkvnYooQL//gsjZUz6Uz0Ek1FEFYcyYwh9f+WB32uHmi3UwBYvrk88oVXR71+Li6HI5NiELS1tfG1r32Nnp4eqqurWbRoEc888wyNjY0ALFu2jHQ6zTXXXJNLTPTkk0++q3MQQH4Y28JKH1fMb0Oy88ViRsmZpBpuBsk75vYmEp4W8byIrvXh4EUye5Hjv0ISp+W/rAd1ZjX2VgJt99KRSSAhCIc3cO8LOt87swFQEbZGuVfQrjkEAj6SyTQ+1cfmY9+HaJrLsnXdBTu0kTrMkdjnatewhE1YeZ7p5rnDvBDFjmirS2t55CtruPCnl9GXbKdECJyeLmQpSH1tJUs+tpg16ey2qucvI7z1PgwjSm1o+phTGwVzLfgVOsMRdrw9m9esvSD6qK2azuX/PDwHQ84QESJn1Czvv15DO8VchkIpzLYBDUFAoaGmhtc79mA6AkU4nN4wuvdl3eZWNMNCAJpm8OKWVvjAjNx9en3TfTlv1Et7W7G67qL+xJuHGV29moVPkTm2Qmajo9GrWbwd1VEEvLfOn9ufEyzBOfezoFnglSFYMsKRZa/H3qQBVopd8QhX/nUT59WZtER72BvvoSvRS28yQjwdIZWOYBlxJCuOx4zht+IIRweyuTUVYNyVOMw4lz/8VaoDJW4+A5cjikkxCH7605+O+n8hBMuXL2f58uWTsbsjhoFObV6pySWzd6HY+WplvezDpOu/A6K42zQ0jW8xc/Dz5lbx9o4EKWwcWSHoNfJc2pA/SvPv/gH/sTW5r5PFoleXsfEgA46kcuVpTdyyvoNX27OeDlNdSG1jOW/32bwe6+PFzjS//2h9nlFQaHQ3GvvC+BQs3cAkVTCUbSRXfSFq/Qq//NLN+67h7Nm5F35zczOVdnZbqq+auuNXUh9QuHHQMY80ch0pOdOqNY/xcskxaJ5FALR7VR7cqXLPkP6lkFFTyEi4Z3FNblojrlksGHQMS9P/gdVzF7YRw1JDxKZfOvoFzqRAHmSEplO5azTgjepLyTRvayXsKQW5jWrdwONR84yuvOtvW8gCHAQIwHGwbItEOsb1L26nPd6DY8bp0qNc0pzgI7UG0WSE9kQv3X29RJMREukI8VQUx4znFfXaNMJpqP0/k4lsRUkbppvPwOWI44irZTARFfShIpbq5diQwZULe/DJQ4yB0CdIT78GxD7R0ljnNpFkPLUVdTDPwnAEW2MaeCqoDxQeoXemTW5v/iCvpbeA1sOCQBRFlinxBtjYIuMg4VFlgvVn8kr6NRKecjyyIKk7RDbdTXTWCiThYOHkOrCCSYAcZ0zl/YA3pGl2A1t37QHDXzAufryeh9Gu4VjbGqmTHkkw1xlrx7GfxWMnQC7FrLiQHm32sP0O7lS1dBfRHWvYmYkgqSGq5y9D9VXnOuGRjmFA1DhA3xhy4sV9Lbzgn4Gh+vAYGRan8zUtoUAlr761Fc0wEbKJKYVo3raJuTNK8cl9PPuWQzwV4ehEDzta2ulLR/HG2wkk38axMuBYrBeCk5/qG/EYRgsKHD0+6cAgCQlZkpElFY+TREiyWz/B5YhiavaU+8FIL8SpyBl1El+aGcYz5OWsVX6OTO3l+9IM9zOecxtayKg1+BVu2cyILuZoqoezZ03v73wLb3PVxgjtznyq5/4bndseYavm5f2Nc0hsq6fNv5HKEofuhMS1287AMd4AuYw0EDcNHGKAg2U7ZPQMvensuK1QBjkHZ8yscnnHvej0EV234/U8jFZ7YaxtjTQ9MZJgLuJ5EdkwsWUFzF7U+K+o9A4PpxxsiER3rKFR7WFbxiKd7iS89T7qjl+Z83x0xjro3HIfph5D8YSQFywDakb0lITjnax97hZ4waLMX8FXP3wlqqzylU8vRP/1k/T29eLzOxx/xnzu/v2NxNIRYqkIPYkuonYrlmyBbqLqNuz4M7t2wC7gtRGu0egSxIODIxSEEsLjLeeoiiqqSyqpCFagekK8GvOhS2WEAhV8acEMZpVXEwpUUBYop8Rbxs3/eeUBzRrp4nIoOeIMgvGqoA8VavwvfHXWrmEjnUz1RWjVXxlmDMDY5zbYg1BjbmLlzCR1PgNhhLnt5ddpE8cNMybG41Xo1SyE7MX0zgY1hGYAkpc9PSZ3bDuaYDCYXW6BSo2nHCPdiRASkmMj1FJwbGTh4Een2t4CzBxRZT+0rVB8fWnt1fB/f6K7t4eb3/7PoorljMVYtRcKMXDd3+jVsDJhQh1rwYxR6q8kfPLNIwrm5s2tIr2zlagjgSRTGTAKejCc/h8AQ48gPBJNZRLNcTCMaJ5HJ9J8P1qqAwmbjB6h882VvDDrEs4kzONtbUTSERQrjlqS5vK3orzZ+irJTALLsTAtgyfX/yJ/5xKgwTt/K3zuh2KkPoAt+bHlMhylDJQQkhqiMVRFZbCC2tJKGsqq8OkWp81fiKXLPPifL/J6yQKEv4LTj5nF994zbdzew4lMy7m4HC4ccQbBeOaMDxVq5Hf4O1YjyJ8mSNdeil71ryOuN9a55XkQMirfbX0Pa+f/HYQgoktIvvEbSoONjDd70qTD3Uh770S2I1SU+umKtRFW3yAZ0OlVDGT8BOxjqGz6Bt2bV5OOvIpsm4Q8Ap/TgiZXU66k+W7jS8BH84SQGT3N7vCOrFDQtphVMw+P4iEUqNwXXx8zSRpx9r5xN+HabyLVncxp4WfJDOq8Bx9z0O6lvH0tuh4tKvHPRIr3DFz3o0pVmreuoU/vpsqv0Kj25LwbhYyK2oo6jpcGTdeoFdyyMZLz3hiWkZ1ffyk7v24bcZLpKBvjPVR7wWPqBGQFfeMlXPFSVkTXHdmdl00xAyz90TPD9r1nWMuhw5ZLseUyLLkMWwlhD/mN5EEgIQkbGYuAZPO9j1/GE7t1EoaNR8p+k+oDCvcO8eAMJF1atnIt6S6NhV0bsR2HQHcltR8osrDYIPanRoaLy1Rn6vWW+8l454wPNp7e3+DvvC+vzUGQnnY1RsUnR113rHPL8yBICr1GvyjMcajw2PQ5zrgNpcFGRqq7i4RQKbfiYJvQ242onIkIhpFNDyAhyxqL/f/F9h0+MpFXkbA4ocLHXiOCr/N+Tjn2M9w0/Y9UBk8lAyx579e55pGL6NMSpLUk8+uPw6N62dW5lT09Ozl9/tlcdt4KVj35zVx8fdoC245gO+A4fWwve4GyeCvd0SDhxL+w6m2RO+Zdb9yNbHRxXIVvTBFYON5Jl+cZEnYUBT+VxnuZFspGyoR1uH9dd0H9xsB198iCMqkPyStzbHk2nV001UPGSBNPRYmlsu72eL/bvbpsGm/ufpWWaATTcTCcHv7y2/N49r/iBKQ0KX3k+fXWQXbK7p6dRd3LA4mDjK2UYcuhbAc/qEPP6+jl0L7llDKEUkJ90MfsoMLM/p/G/t8zggozAgrnP/DvaP3eJsex8frr+OScSs6YZg76PoycsAgmZui5uLzbOOIMgvHOGR80HIfp9m/xdz6V34xMun4FRuicMTcx1rkF7V52vXE3lhFDVko4Yf75OKg4ahnLF53ELZsZ1VAqJFocbGRgGASMFNKeTmwlSVSS0bQ6FFmiaVZ9bspge8drzKs7GkMxsWyL7mSSE6osvCLM2rn/hS2XkKq+mHC8k2se+Tfi6Siq4kWVVfb0tmIFmjB8TXgUD5d84k6q/UpefL3tOKCWIwlBSdcPcawYjrBBSfPA06vorft27pgtI4bjZP8eK/5+zZ9W0dhYwrbWBLqRJO17mRWXZcMAH9wDfVIMx4gR7Y1ydWcfX5zlEEtFSOzYQyQVwTZiZGJvgpnk5WjWBW9aJu9ZPn3Mewsg2JtzwaeKWmPycYQHSwkN6rjLho3Ys6P5/I7dkYIFp7kAFAGlqqDGp/D5OSX9Hb/KzKDCNL+MIo0+8bDghKt46427sIwYihpiwQlXAeP7rk+kSqOLy7uNI84gmJI4Dr6uNYTsIcaAUEk13IRZehaw/zXby9vXIhtdOI5ANnsojf0f6ZlZb0QNcM/i0dcvJFocPE3h80rMKdnDV98f4sk9fWzc69C6u4+Tj1tMR7it/1SzKYOFkFBkFdu20B0ftvDiUf1c+2KcXjtAqGRlduScjuEAmpEhY6ZJWKCqFqlUBkvy8omf/YPff+4kLjtvBXf97nqUjpeQ0xamXEqFJ4lkRpGFg8+j0jS7gWiqJ++YZTWEbHTljq3MX54bqQ/+iacivLbzJTQjjRw0kQ2NHm03/3z3sViWhWYZ4Awq6AS8Psq1PNQ18GwpOGzEXtAlP6xj94298UHIZgKPthe/3UON16SMOCGpjxs+/k18MqzdEqNXt/cr4uemxU2s8q8qyhMwEiPpOFxcXPYhotHo+Ep1uYwPx8LXcSfe6H/nNWccL/ellvPpYz+Ye0mufHxZnoK5LtQwrvnKqx6+EN3Uc589ioe7vvxI0etf+PeObIrWgfUluPO06pxbtkJ7g/d33s+ze7eQNE18SpBo52e4f+V/sOo314JiEgpUkjHShKNdbN21h4TViSxkPnzieQjZJp6K5M5vR+c7WI6NbmSgP049JUJkRD0WQczQF0Eq4+OxzdxzwyW562M4gneiaRylAgWDWqkb4VgYlo5P9XP8nA/wtz0dJDMR0HtwktvQzTSmZWJaBg6HzyPv94bweCuQ1GwHnhalxOxS9IGRuxzCUoZ27KUgJif63icLfLKgwiPx6VklzAhk3fn/7+EnaA4/guP0oIlukCxqyiuZN20htaF6brzg3knZ//4ynsJNLi7vdlwPwYHEMfG3fQ9P/M95zX12gO9Er+Mt/Wg2DwodnGhe+wHPwubdr2GZMeZWhFAVL6Hq04o+1HC8k65NN5JI96J4yqls+gbTKqcNS0p02Vs76bMshCSRNNNEPC9SXXoTl7z/utyLN5zo4gu3fAFDF5Qwh0rjvWR2NiLNeiHv/BzHYUbVbFq7t6EZOn6Pn7p5X+fNljYwEyiJ36KYUV5J7uGra/+HzXvfwDB1DMvAHjRaH1rZfmPry0Wf98FACIEiqaiyiubIIHnxV59J1CrBkMsI+iqI2iXoBMExMT31GN7pOHIJiANSfwwASUCJIkibNpaTLekrA++t83H9iZU8vC1Oe8pkV5/JnNJswqGlR5dR61f4RbgD7ChCCDxOJYbTi2lbuQJdLi4uhx+uQXCgsDUCe29E7ftHXnPMLuO6yPVsN+di2jZ/bU/lCu/4PeVoRkdRMc6D8ww8+Nfn6dbLmR1S2BG2aI1GeW9jA8tOLV5LseZPq3Lx7Xqmk/SO+1nxwTV5yzhKGbYqocgytmODpDBvbhW2bZPUEuzp2UU8nRXPqXoDJU45Fhmi6gZeiz2Pb3eEpJbAtAwMy8CyTdqiu/ddmzR0vLJ8WGa5mIAN29/hUCNkPx5PiFnlVYQCFfjUALt7dmKYJvGYQYk5n8rANC785McJlE8nQSkRu5RHX32GLl0lJirodcrQ5UqcQSP47gN0vJJjM7/cy+yS7Hx9pUdiXTiDaTvUBxRuPrkSIQQn/dcuhCSQgIAisT1hMCOoIITgnbiBZTsYtpMXruqrrCKuNeLYMSRsys0A71/4ninjGXBxcRk/rkFwILBTBHcvR0m9ktesU8FtqZtoNqYhCdga00EI4rrNqz0asnQR07WHmOdPUltWNepIyxv+MZIRBiGIpaLITh+yBAtqq/HIErd85AM42KSLPORYqhevMFngacG0dBxjF+9s+y3rdXPfPHtfB1sjCfq0NKbtYNgSVuxZTrm2OmsgDEZieHHt4ZWVDwmSUorsCaGLMmylDJ+xF8c2UWUP0wIeKktr+NRpX+TPG3/H+s4IScNPOrgEf1kjc+Y0sPxYwbLfPkB3eDem8j5QZ6CVVmF6pmF7Gnj6nQCOGCwPfO8B+aZJgCJBtVfmgjkl/Hz9DgcCSyAAACAASURBVJLerLBTsi1qEt289MUP5a0zWDi6alOUFSdUEFLBEAIhBI7jACKnJ8lYYDvQHDc4tsKbC1cVZ52L82Y9TvfPcejDWze34PO6v7oYFxeXg4drEEw2VoLg7mtQ0m/mN6v1bLGv4JONtTz7xHdJZiLIdgkzF17B9kQIzbKRlUrKjvku6pAc+YUQZjyn6i73qXTGe5EkgW3blPoq6OpLEjH9dBkvEB8soOsfwQ+09fR1szvahZbpxXHycxOsf/irk3ttJhFJSIQCFeimQcZ2EEJFkhTqyyo5/6RPUeYvJxSo6M8yV5H7+4aNOh2ZbOjZqz0ZvJJglj9BeOt92EaUk2dO5wsfvo69SYtoSZiueAa9rA7dN4+oGqC9I8P/dslQ9jUoG/s4J3x+jkmp6GNhdRVb97yGpLfhsSJIRi8py0GafTk+WWJuicKcMg8rT67ix6+3IxwnWyZASMTKhj9DhYSjJ5bApoyEYYNHFiyu9u4LpZQgYzkYNnnhqmmhcNyxJwMnA1m9SaGOvlAmSjeO38VlauIaBJOIMCMEW69C1vKzsFue2SQb70HfFeE3f1/NPG8vwifxZqSH+PYfoM+4HhCoksglDXIch5TWl3PBZ3+iuRj2ZNfLxFJRYppGuK+X7dEUGdPBtC0sp5cnNm/v3/uPD/p1GA+q7KE8WEmZv4JQoJzmPhkttYeUYWJLJWhlZxMMP4Zka5T5PeBARbCS3177MpIk8aG7PweGnu0EgaTq4ZJzvj3i/q470eCG13qznSKgSrA1XUa6/joM2+F+0+Gep5P9S38CDtBgNqAIFAG67SABHkkgyHbIp1V5uOM9NUwLZKcVlv4txVtv/CEbTqqGOPX4ZVSUlgxT3ZeXBQn3ZXD6802ESoaXyy6U7fKKRofH+gJ527tlULKlbQkDWZCXEbHYBGAT1cW4uLgcfFyDYJIQRhfB1iuQ9da8dsPbREf1d4nFEmzreosdnVtI62lMyyBg6nQndkD8WmQrDmaUbXIazDin/j6GaR/q4LXicZBBUsC2EEKiuqSCRDqGIqvUhqajSCqKrFBTNg3NyFBZUsPlH/sODRWNiEHx6x+570uk4tuQTA0hdJT0dlBmo+g7UGUPsiSTMTJc/ciXCQUqMfGCk8mK7xwbQ65ke9xgd9KgNWmye8hPW8rEPAhBBjU+OZtcJ6BQ5ZV4K6rj4DDNr3DDiZX8YHOUv7Sn0SwbEKQMmwqfzHEVXjTH4bZN0ZyYs1DYXaHwvUWhPl7ZcTe2EUNSQ5zacNWwZQp15FUehsXzD06C9ZH6wLB9FkqSVWh6YCIluV1cXA4NbthhkRiWQXzQCH3wTyLRSrLrD8TScWKaRXTgR4e4bvTPyx4+SEJQ7vOzcMYiKkQ75T6Vcp+PpyJHs9uaSZpyUMqw5VL8PRnkxE+xvB4QAsnS8Jp7eP9Rp/BO25uktRQIkCUFj+Jlds1Ro4ZVfvimYwn3hXFsGwdQbB8l9hxkj8ZxR89mU9t2evUyhNqE5a3FqGhCU6rQRBBTqcSUSg78BXJsZKMbWe9AMXrwazHmVdoEiRG0e5hdGuDmz92ZW/zi5zt5oTON6WST9Lyvzk/KcljXreVCIOO6TcgjszCksj1hYDlwTsPwjng0vv3o5by0txXTESjC4fSGWdy2JD8rZld6eHa/2J6dkxKaVyhs9tLzrhuW+/9gagjcsEMXl+J513kIMkY6LxlNIXf8sP+no6S0kdPITjUUSaHEX4EulYISwu8rx6e1EOnrzBonQuCRPRzfeCpL3reUm/5wJ+HwWwgBJaqCzxPguJknc9eXH8HXfntOvPjOO+9F7k2zc+fvsfQ4lihlkbWIYOM0Xtr1EmAhCZWz5r+Xu770Y779y4t5dccLGJaBAHQjk+c+bo12c9p/t9JnOpQogp+9r4aYKWMEFmJ6pqMrtVhqPVrgvWSCKm9RijF3fIlzJoStIxs9KPpePEYHqh2npv4T3P2Bo5kZVPnyLf9Ep9AwVS/YDl59B2n7GJKAKgnKRDBvc+u6M2h2VvKh2fBid4azpwdQJdCsrIhPAH2GxbqwhWNDpU/KzfEvP0oZsQLjYHQ9ynEVvkGfI8OWKZTdb1cqzMrH799v4V+h6QE397+Ly+HDEWkQrGt+jj+8+puCnb1uaof68IrGp/r7BXHlhPwVtHRvoy/dg+NYGDZYTlYx7wnUoXqrmXn8d/nJh44h4C3hipf20BltQcLERqF7yz0EjGQuGkAg8Hn8nLXwIzw64wS++sDHiSZ7yZgZhBBs79hCONFFTfXFeMM/Qphxbpi3k8/94U1CIo4nIDOvVGNmRQsp3UNIAYSEKkv45GynoJsZ5tcflzuf5o5m4pSTkirpI8RmvY5ETMuOkYXgfX9sh6OfGnYdJjvrfKVXyiXYGfh5pi3FpuZ3cHofxRv7C0JSkNQGykrKQFKZH/r/OLPWD4BdFcTqEzgIhAymUIhoFqUembRpsS0dLLDXbMc/8HvFCRWkDYuXwtnnMSDLaJZF1MgaDoJ9epJVa54oqgLjRN3zj214CI3kfgv/xtq/G3Hg4jK1OSINgt09O3lqwy8P9WHkKPGVUeYvxycHqK2Ylqd8l20fz724hUxKUBGs5NJ//Rfm1DdSFijHp/rztvO9hz/I7nCGXfE0PWkDR6j4SmYiK37Aod4XJ+jL5miPJXYg9Vefl9CxEahOCt3K6hJUTzkexcfKx5cRS/VyzMyT2bhrA5IuoSpeasqm5zqGzPRsPv8QcGzJhfQpMru6m9neZ7Cneytzpy1gdlUTnmAFSVHONquGn2yNs9HzT3SjkJSy7enZZeQVzPUcmOstkU26IwkIKoLvnFiV7fhLsnP6JWp+PGRn2uShd2KI8M9QtL3IVh9YFpgx4vIJKMGZnFPusKy/uFGvXYYsaciSAMdBKzkJj+oHKYHHE6Ki6fK87S+u9vJCt5an4q/1K/zwfdOAbEf52Z9fj67HUJ0SMg2XYjnVuTn+YgvzTLQ0b0KL4fVlb8b+CP/G2v9oEQcTMRY6w5GiPCcuLi7FcUQaBGX+ya9wKAlpXyibV6VStFHuFZR75f4fhWDlewhM+1fKgpW5ZUv9IVQ5qxYfaT7zso9nf+eSDcXjOKkytOqLcdR9o6wrF5/Evf/oIORV2BpJUelV2WULdMem1OfLlRQGKDH2sHHLU9hmAkkpZcGsxdSV7OSV9g5w4OTpFdhC5F7Qup7ANns5oaYChIKtKrmOQRg9eLp/TDitoyHzSl8V6eB8dLUW0zOdTVIdWkUthrRvZPzMhjCwaNKfMMkxkDIdyOkwqt6N32fglR2mz/kXvBK80r6Xio4HwYyBEsJp/A++Mn/OqNtctTGS9bbYcWRjD47wIsiAY+Kxumk89k5WtwqaqrJiPH3mZRg71yBZURw5RF/9pUjeKixVQhGwIJhvyN1yavWoVfnW/GkV6F04tiBgh2HvWqSmG3Kq/lueLq4wz0Td86XeEJqT3G/h31j7Hy3iYCLhiavWPFaU58TFxaU4jkiDIBQYeZSgyp4h8elZd/zQePXcMv5yygLllHjLkCQJJf4cgb03ImjM226m6gtoNUtHrPg2EoMTxdSYm1g5M0mdz0AYYbzhH+VG5wCGbza9jTfQa/iYOaud8r33U211EgpUceXpC6kMesgMXIPOnyAbFg4KstFFXe8j3Hn+ubltOahc8tfWfS9oow1NrqZdnkdKqiNBHZbnOD7z13b2xDrZnfkUaVvNPjHTxnWK48LjpFHsBJIeRkpvQzE6kDKtVEt9HPv/t3fn4VHV9+LH3+ecWTIz2clGIIkSEhJEpIUKpT9v1SJaF7TFDX264LWPIrWi1SsIvbiDRWxdkNpar7e3tmJdrvRWoC60ahHqCipUNkkI2ZeZZPY5y++PIUMGwpKQxeDn9Tw8DzkzOef7nW+e+X6+e24uOz/7lA69lhQrN77MMH0YqWmZZDsvByCt9lcQa0JRFaxIE86ax+lu6WXXz31za4QSj0ZVSjZWIAaqhoUHS3UScJyM4hiGvyN44NRHezbtJYtQFdDN+CCAwyQ+aXB/r0FXRzuVzxdspTzDyY72GDFFJdXWwbPnjkhMJuzJwTy9aTV/e9zlPPb3O/FHOkh1pnLTBXcd8f091Zmmzb69YAtRfvJI7HY1KfDozfJEOdJYiL51QgYEowsqWXzZI4dU9umuTFwOd9Iyt56we9fgqluCQvKufOHc64jkfK9X90zaKCZs587q01lZ/iYoSnzzoS4W111Kg74bjXZCSgmOsuWsGPMuihXFssV7FDp59XQckfdRDAO7ptEcKeBfgQyqI2lUh1PZE8tng+MbtChOgmomQWc6VoaWnDgTqAvRlzvwONX4YTkem0JucANNtduImh2ooU+x600MyywhrJsE/Z+DGUXBQEHBdLjZ1uakOW00WqyAmO7DHfaDrqPZM+LJtSzy7X46TIWYCRYKKZaPmzY1HTJb//4tbVS11tG641FMfyvVtgxGjfkhn7/7AVasHVQHhrMEQ8tguy+KR43fP95Kh3xX/LMKGya+iIWlQFA3sasabzeGEttRLxyfhRprOWJ3eIY7m0isllMyHViWSV7G8KS05uVkHnPLtzet5jWfPMfIYSWJHoJn3/51n04E7ExTtjKVJvNtdlXV828TJyUNKfRm/oMcaSxE3zohA4JhaXnMnPz9Pr2no/VFXA0PHXI9lD+PaPalx3yfrmcQWLZ02oIzsUfqwdJRrCCt0f173FsWlj25Im6N2bDc5YmjdRtVCI88H8uyaIuaVHfo1AQC7A3o/M08G3/+d4ja84na8thky+SPyTspx2ndXOsluwoj9k/W29MRw6EppGgqLk1hn7eR7IYnsGKtaPYMTjntFu4951tc/bu/sa91H4Q+AcVBW2M9luIEK4SVNgFTdWJZkOpy0l76IL72IEqokaz6xwkodvIthfLTbsGvQrbTRmlhPh2Berb6dEK6gcOZmbQHf+KzjBi07niUWKgBj6YSijbRUfV7nKc9RXD3Y6B7MdQMQnlX4t51N6c42mhpyCOr7EYyHOkMd2n8q10HFCwsDCveU9AWNtBUiJoknptVfWh3+A3nLkgECQ5byv5TIoM9GvvvTm9azX01h+BoaVJJpVA/D0fUxuLL/iPpPb2Z/yBHGgvRt07IgOB4de1OznZqPFj8Chne3yS9x0IlNHw+sczze3TvrmcQKLFmcvX32Wfmoipg4CDb1oKFHct+oMVvmBb1YQPdtKjqiFEbMvbvcKcwafVe6kI6gYN320m78Lg+g+5oZhC33kgs2gFGO+G0KSiWRaa/md9/M5cplaPjE+2AmzY18Xl7lN1+nUbTwrVnGZHAB5imjqraSKmyyDnzSfJOvYu9G+9ADaah6F6wDBQMQIVwFaqnHBMLmyOTmGmR6k4hSC5m7o3YNZU/Xjo2qUt8e9H13PY/s/G1e1FtHnIrbk3M1u8q26mxK+pFUVRUYJjLxlcyQsy/cDwXvnonbTGTFFUhr+oeHEoLihHEat+O7913+Naob+JLv4E9mhvDhHSnQjBmxedLKvEDguDAToBqN93hXcfMI7Ewac5hGHumstPXwT1bX+j1BLnetJr7ag7B8aSpN/MfetJzIoQ4OgkIunGgGx/OVX9HjvelpNctbARHLEZPP6vH9+56BgGKwt3DV3NH/VXURjxoisIYj8Gi1p+yN6BT82mYvYFq9gUOt7uexc6OWM8zeBiqaZAV9TOpJIfRWW6KPDZeWLUaW6ADn/FnTLMBm6rSmJZPzJFLOG0KlqLiTcvjN/ugbJRxYNx7fBYXvFpL1DBxaipaYDOmESXdoWFZOp/V/BOIV8xqtAmwwIrnRUEjJfNUjHAtTqeTIOlkl/2E1rCCbloMS/dQWZxFoduG5UlNzP7Pdmq4dv+KkcNKaCOHjvbd1L43B3fOVE457Ra6Tn5YOD6L772XjT9Qh1PTGJ2mkeHOJs9l47/OyOOHbzXi1y38wTbS7QpbW/aiWFHSHTY6AvUMb3qC1y58kPu3tPHGnmrce1eQqnTgt9Kwin8MFCZWCXTXHX7wmPk/P/mYYf6i45og19zegGvUZlpDH2NE7VSknn9MreZZX7ueNduf7fHqhGMlLXkhhgYJCLrRGjHQFIvr0/6Li91rkl6zFAfBkfehp379qPfpnEzV4A9jz85h4pTTWGs/hdW7m2g2swlr+RiOPBr1A0MDa9tK6I9jATv3ou/cTrfYY+OvtUHsqkLN3lr0cBgt1kx+9S9o3mEwduIkLj1vIdvw83k0SHvhbMyOZ7BFt2GLBDFs6aixVkxHDoqi0BS1uH9LG4sqzURXuL3VgT/1h4Sd+RToJpq1fxweMEyDu/50E3pHC3b/hxiWBoodLAOnTcPtdEPaVE6bfD/Xlafx6+0dOII6n3fEGJ6isqcjRlQ3+drqvdg1cO0/6CdQ30BluoojWhWfW2GqaLFGMutWAgd27ctz2Xjm+/d020396+0dnJRmR1UUPrVn4Is0oZkxLAUChg1FUWnw7WPl//0UNdhKUe022tUcLCWFLKUFZ/OvcBTendjSVx17aHf4irX3JQUJZsx+zF39h1uit2Ld/XREWqgsG7l/p8DaY+plyHQP69fNg6QlL8TQcMIFBH2x+UmOE660r2C66+9J1y3VTWDkAxierySumZZFY9iIt+i77JlfHdB57/M6QqO/SZD47nF/rgWYEh+37xy776PjClRMXGoMtxrDoxnMLvgXRR4oGHEJRR47w11afAZ8F00Rg9qgTk00Ej9Yx/t7dMWPFTsw1r1w7p1c8NxmopaGI+ImxT2G9kgEp/8D8nfMJpw+mfCIG1CUbFoiBivWLaHRV0tUj+Jr2EZG4wacaZOJpFTgDH2KN2piU21oaNS07cOpaaQ5HISiIeK7/ZtEYjqptgxWXnkXFXnxcf9fTj6wA99Nm5pw2nW2NdRi//wxFN1HyJbB+yNuoEi3sXHbP4jSHp/6qdhpbf2MWnf8T/1Y/j66HgAUHfljbHsfwxZyABZ2z0lYlklNyx4g3roPRtpx2cKUDz8FAIctxEP/1nUpxqHd4QePmRupX6OlJXZMXf2HW6InBwkJIY7HCRcQHPdxq1aMhwseIS34JgBRU6Mmls3nejE7Um+galceNcGm/RV/jJqATtQ8zL0cGcefof2yHColjhby7e3URFJRsch16Mz9ymk8/+lGWqMKmmJhmSFGODq4vbR6/z4GrsPes/OAms80FSPcQap/H6Bgt9kSFUpeTiYV48YQNaF6U5BIx07skRawYljYcPk24CKKlX032U4tUSlVNe9CNcKg2bFFmzBt6YTSp+KinczUYURDDezsMDglUyPF4cYXDmBqHkwLLMVOVVBl1gu7WHeZ+5BWbmeFbX6+HKfvfUAHxQZGhFYzhlOxYVkKCvHzEEwjwkd1u4Fj+/voegCQXYkfJ2z3lGJE9mHX7ORlFMbngOzfZMlucxDbvwPmsY7BHzxm3niW97Dd6gcHMZ3ph+SKXw4SEkIcjxMuIOhpK8kfMw+chucPUVf/BjWBU6iO/htV0RxqY5nEO7k7Hbo//PFSMBlh91Hk9FHsilGcEmR4wbcO2V3Ptfc3KByYM2BhJ1Q4ldN8f+c/tlXSprvIsoWYX7qN8PC7j/rczvXxn45QufrPW2nJHo0WayHH7SBiGOSmxyuUzgoyFqzGMMIoibF+A8XwYrW+TnCHgzmn38eq6mxq2vbREgpjqRqWYgMzgtP/IVF3Jboji4bc67HXrAC9GYDiYaNo6GjFtEAxw4CBq20dgXA931tu8LMbnuLmDy38ukWKpqCbBhEDbB0foljR+JwMM4oz+CG6sxwzZRRWdCeqGQRM0JyYzpHAsf19dD3Jr6DpV8SUFqKKgjutmCkjSlh82cNJB/mU5JbS6K3FYXP0agy+ub2BlevvRy1pZXRlZ6/FgSDo4CCmpqUqaZlgZ8V/LDP1u+shOVyaZJthIb5cTriAoGsrybRM7K4RfNgSoToQO+Qo3L0BHe8hzfuJfZ4mBzEKNC/FrjAjXSH21m3GFqtjuLKPm8e7GJ8exEGY+lgG/9lwJTvC2TS2RbiwyJ20Ht2ypaPsX6HQdVli9a5qbkvZQnzTXpO9uzLJqTz29P16n0msoBgrYx5KzeN4dR/VsWEs2V9ZdFaQNe5iFDNMJEbilD4sA03VKFEbee7vP2fueQu5+nc/w1Kd2DSdkL0Ye6QaxbKwKTpqrAn2riAwfA6x2pV85PXjSRlO9vBpNNZvwlJBMQKAhT36Of5YKj9edRe+4oWEDIuIGc9lrktLtNDZnxbVNLG0dIgFQHFgKRaW5gRXGY6UeGV2LK3orhsJ3fJ5mKg7hUAggMeTkjgwqGvlm5tewJKrftPrCnPFuvupadlDVfMuYnqUD3a/w29v+L/E/Q4OYkbmnESaI5t/fvIxZsyOkfo1Gs/ykpdz9Jn63fWQzJow95jeN5QPKZIAR4ijO+ECgrnnLeT6v7zMu/p4AkomeszOE2v39esz0+1q0kE5xR4bIz02ip1BSsN/IF9tQrGns639W4x1/xWlMgY4UMMmiuXFcI7CilazuPZC9hlZ4Cwm0M3a+UiXg4a6Lkt8asMorvzqNtKdUToiLv74wSh+9q3kpZNHOka3NRI/LElx5qCX/icmkJebkvjCtAIdWGufx+nz4bSlozt09KgPixiKoqLZ01EUJXG6Xd6pd+EpbaZ5+yO4Qg0Ewx1kpbhpj+wk5izB0H1E7MNQR/2M3GwnW9vC+IMtpDe8i4KKoihYqhsLnZa0fMxwK0HDSmwHZQJYJrHUCdja30PBwEIj5joVV+pMTGsVJmCZTRgpRbhdeTx+xZ1Az9e7dwYQkDwc0LXLv7m9gRVr7+t1ZeMLtlLVvItoLAyKQnuoLakCPjiIycsopHVrRWJVQktL7KirEjorxDe3/TUewOWU4rSnHLYHbSjORzhS78eJFuAI0R8GPCB48skneeSRR2hoaKCiooIlS5YwderUPrt/Tloe53zlcl57r+++wDyWl8qc/KRKP/7PzkiPjQyH2u3vNYRSWFx1daJSnpXqpbJLK9+0F6EYjTSG4JebWtnU9AKKI4uc8puwp+QcsnbesmcntjJuCOnc/0EbrZF6/jXym1S/7UZBYWfROLTiNC58tZZCt0aKTTtwjO7+lv7BQUK2U0s6itemxocJOnXuNOe0n84+5S+YhoGiOlDUDDRNIyVtFJZlkeHO5pO2MOtrgwRiDqys28jy34tbTcMXjaEoEWzhPWTln0HMruJUFXa0x/DGwNCGEU6fgi3ahD28E8UIg2pHUVUMLYOoGd/4COLL/b0xC6vwZjysQIu1YWnpqO6ZjKmtYsTMR5LODegaCHVW5J2Vx/0v/vSIlXhnALE3UkVeRmG3AcTxVjYZ7mxienzow7IsHAdV1N0FMTe/83SPNiDqTKOmakSiIaqad1FWUHnYeQaWafHuzrcwzHgP0NQx3zrm/AyWI/V+DMUAR4iBNqABwYsvvsj8+fNZvnw5U6ZM4cknn+Syyy5j48aNFBUV9ckzlFgLpZG/AP/vmN5vV3SK7C0UO1oocbRQ4mhmhDPAW7v3EA3VMsLRwU/POJvU0ff0OC2LN23n082/wIj52GPPoHnUtYwquoal731EW1Qly2GyYNIEHl93L42xXGyKTijUQPP2R8g/9S6ynYcvnq5bHheWnkwdFuGoDu5USk8awScdBqEOi1OytAPH6HbdJrlLD8TC8Vm0hmK80RDGtCzSXTauKz8wy73BV8c+51t4HXWASSylDEWxY2rppDhSsNv8VJkewhk/4vy/1hGJRuNzBxQFVe8gZi9C1WtwKDqaplFYcROhsEqhW+NfvhiWFW/1+wpuIKN+JaZlYY/tQ3eMBEcu5ogb0PaPDqRo4FEhYIKWkkNg5Px4gGJZ5Lbto9DjOOK5AZ2OtRLvDCAOdzAVHH9lM/e8hfxz55s0+uoAsCkaDtuBVRXdbdrT0w2IOtN4Ul4ZVY070E0jEeC01fsOef/2+k8xTCO+C6NpsL3u0x7laTBOIjxSOciESyGObkADghUrVnDVVVfxgx/8AIBly5bx+uuv89RTT7F48eI+eYaz+UlKbAd28UnVYhSlupNa9EUeGyX2FsZ4F1Oo7EJTDrxfd3+VYMF/8IPSZ1D04YkzArrdF+go/rXlF+jhBhRFRQ83sGf7r7gv7+fUKuNQUxT8lsV920jsZFeWbmdHO8Ri3sRJd4fTdWlcitPBmHEVAIkVD07VJGrEf0gco9vld7ru3pfnspHtsjMx22K3X6dDN/nBW4385ZxC8lw22hzv0KECRhQFC3ukipirDJUwavkSynOc1HoDWA4PESOIgYpiWViKgmnLQDPDmJ5yUuww/eSTWTx9HI37d4P83K9jU8E0wXAMo614USKPCmBX4vMFpuU68di1RMs/pJs0hHR2+KDFH8IWizE1VHPMm970ZYvxeCubnLQ8xpd8jfd3/QN9/06OqtJ9r1Onnm7205lGh+ZgdEEleRmFLL7sYYBuA4JwLEyqK73Lz6Ee5WkwTiI8Ujn09mhoIb5MBiwgiEajfPTRR9x4Y/JZ8WeffTabNm3qs+coejtjPCabvvonSpx+Mm0m4eL7kt6jhnfgqb4ZVU3eACiWOpXgiHtAdSadMthbquGDzi92RUUzfN1WyqM7v6xVlbEZNvIyhrP4KK3crkvjOit8IHFtVKqN+pCBY/8e/wvHZ3Fflx6Crr8D8QBjt18nbJgoioIvaiR6EEaPGkbdvlYwbWBFUawYimXhcGZy1nA3rREjsfmipkJUUeIBARa+guvJrnscRfGT6slJfBF3TtxrDOkser+Zv+wLopvx0wPjn1f8j9OmwdRcJ/dNzEnq+u8MKNIdGtkjU/cPDUw45rLpyxZjX1Q2kViI8sJxiZ/DseAR39/TzX56msZUZyreQCuKqmKZJqmu1GN+FgzOpsNdSAAADahJREFUSYTd5bEz2Ont0dBCfJkMWEDQ0tKCYRjk5iZXdLm5uTQ2Nnb7Ozt27Ojxc4oNcFg+ypV2iFj4ollUd7mPx9pFmfEQKslfuK3K6Xwemo21q7rHzzycSo+bzS1BdBQ0LE4dlkMg7McfVToXCpDrsDi/fBZ/fO8JOsJe0pwZnF8+66h5n5UKT/gUvDpk2GBWarwPo/Natg3uKLUY5oivj/fVeLv9nR074kGRFlYIRpVET4hDhaoWHzt2eHGqKaSlOAjbTiISrMJEw3LkMqbsOmalevmVT8GyFAKBAOVO2G4qGJEIuqlhs9xooxcxLl1hXrFFW73vkBbpbflwTRY8sU+hIQK1ERiRArkOuH6ExTBHB76aDg5ux87tUof7aryHvH4kvfnMj/R615n63eXxqGIa/oA/PqHSssj25Pbq7/9IjpTGg5914zfvZvlrCwhG/bjtqdz4zbt7lB4NE7//QH5ys9P7PD/dOTiP0Lvvkf50uKEnIQab4vV6e9Mb3mN1dXVUVlbyyiuvJE0iXLp0KS+88ALvvvtunzxHibUemInf2d1vj9ccWuB9PHvno1jJ3Z/RjAsJDb8NlD48+g9o7mhMarGcXz6LkvJJiTXuR5v9P5AaQzoXvFqLL2rg0FRK02yclObg4cm5NHc08uD/3cu79fUYWgYV42/h7slliXQ3hnRuf2sPekrqFypPfelIcwj6wsF/KwO5LK4/8tbYfOhGS/09h6A7/V1uQpxIBiwgiEajDB8+nN/+9rdccsklieu33norW7du5ZVXXunX59s63sa97z/jG9l0Ecm+nHDejQcOHOpHX/Qvp85u+N4EK1/0vB2vEzl/kjchBAzgkIHD4WDChAmsX78+KSBYv349M2bM6Ndn232v4aq9Z/+xugeEc2YTyblmQIKBoaDrhjxCCCG+XAa0X3fu3Llcd911TJw4kcmTJ/PUU09RX1/P7Nmz++2Z9rY/46r/OcpB6wRCeXOJDpNjWIUQQggY4IDgu9/9Lq2trSxbtoyGhgYqKyt57rnnKC4u7pfnOVpW4Wp8NOmahUKo4FZiWRf3yzOFEEKIoWjAZ35de+21XHvttf37EMvC2fxfpDQ/lXwZjVDhImIZ5/Tv84UQQogh5sSaCg5gWaQ0rsDZ+mzyZcVOcMQ96GnHtoOhEEII8WVywgUEjtbnugkGUggULcHwfG2QUiWEEEJ8sR15f9QhKJp5IXpKReJnS00lUPwLCQaEEEKIIzjhAgI0D8Gi5RjOkzG1TPwlj2K4Tx3sVAkhhBBfaCfckAGAZcsgUPQLFDOA6SwZ7OQIIYQQX3gnZEAAYNlzsMgZ7GQIIYQQQ8KJN2QghBBCiB6TgEAIIYQQEhAIIYQQQgICIYQQQiABgRBCCCGQgEAIIYQQSEAghBBCCCQgEEIIIQQSEAghhBACULxerzXYiRBCCCHE4JIeAiGEEEJIQCCEEEIICQiEEEIIgQQEQgghhEACAiGEEEIgAUG/W7JkCZmZmUn/ysvLBztZvfKPf/yDK6+8ksrKSjIzM3nmmWeSXrcsiyVLllBRUUFBQQEXXHAB27ZtG6TU9szR8jZnzpxDynHatGmDlNqeeeihhzjrrLMoKiqitLSUK664gq1btya9Z6iW3bHkbSiXnRADSQKCAVBWVsZnn32W+Ldhw4bBTlKvBAIBxo4dy9KlS3G5XIe8/vDDD7NixQoeeOAB3njjDXJzc/nOd75DR0fHIKS2Z46WN4AzzzwzqRz/9Kc/DXAqe+ftt9/m3//931m3bh2rV6/GZrNxySWX0NbWlnjPUC27Y8kbDN2yE2Ig2QY7AV8GNpuN/Pz8wU7GcZs+fTrTp08H4IYbbkh6zbIsVq5cybx587j44osBWLlyJWVlZTz//PPMnj17wNPbE0fKWyen0zkky/HFF19M+vmJJ56guLiYjRs38u1vf3tIl93R8tZpqJadEANJeggGwJ49e6isrGT8+PFcc8017NmzZ7CT1OeqqqpoaGjg7LPPTlxzuVxMnTqVTZs2DWLK+s4777zD6NGjmThxIj/5yU9oamoa7CT1it/vxzRNMjMzgROr7A7OW6cTpeyE6E/SQ9DPJk2axOOPP05ZWRnNzc0sW7aM6dOns3HjRrKzswc7eX2moaEBgNzc3KTrubm51NXVDUaS+tS0adO46KKLKCkpobq6mnvvvZcZM2bwt7/9DafTOdjJ65H58+dz6qmncvrppwMnVtkdnDc4scpOiP4kAUE/O+ecc5J+njRpEhMmTOAPf/gDP/7xjwcpVf1HUZSkny3LOuTaUDRz5szE/0855RQmTJjAqaeeyrp165gxY8Ygpqxn7rjjDjZu3MjatWvRNC3ptaFedofL24lSdkL0NxkyGGCpqalUVFSwe/fuwU5Kn+ocn21sbEy63tzcfEjL80QwfPhwCgsLh1Q5LliwgBdeeIHVq1dz0kknJa6fCGV3uLx1ZyiWnRADQQKCARYOh9mxY8cJN8GppKSE/Px81q9fn7gWDod55513mDx58iCmrH+0tLRQV1c3ZMrx9ttv5/nnn2f16tWHLHsd6mV3pLx1Z6iVnRADRYYM+tmiRYs477zzGDlyZGIOQTAYZNasWYOdtB7z+/2JVpVpmtTU1LBlyxaysrIoKipizpw5LF++nLKyMkaPHs2DDz6Ix+Ph0ksvHeSUH92R8paVlcXSpUuZMWMG+fn5VFdXc/fdd5Obm8uFF144yCk/ultvvZVVq1bx+9//nszMzMScAY/HQ2pqKoqiDNmyO1re/H7/kC47IQaSHH/cz6655ho2bNhAS0sLOTk5TJo0iYULF1JRUTHYSeuxt956i4suuuiQ67NmzWLlypVYlsXSpUt5+umn8Xq9TJw4kQcffJCxY8cOQmp75kh5e+ihh7j66qvZsmULPp+P/Px8zjjjDBYuXMjIkSMHIbU9c/CM+0633347CxYsABiyZXe0vIVCoSFddkIMJAkIhBBCCCFzCIQQQgghAYEQQgghkIBACCGEEEhAIIQQQggkIBBCCCEEEhAIIYQQAgkIxJfcM888Q2ZmJlVVVYOdFCGEGFQSEAghhBBCAgIhhBBCSEAghBBCCCQgEEOU3+9n0aJFjB8/nvz8fMrKyrjooot46623ANiwYQM//OEPGTduHHl5eVRUVDBv3jy8Xu8x3f/DDz/kiiuuoLi4mIKCAs4++2zWrl2b9B5d11m2bBkTJ06koKCAUaNGMX36dF5++eU+z68QQvQ3Oe1QDEm33HIL//u//8u1115LRUUFPp+P9957j48//pgzzjiDl156iba2Nr7//e+Tn5/PJ598wu9+9zu2bdvGunXrjnjvt99+m5kzZzJ27Fhuu+02HA4HL730ErNmzeK///u/mTFjBgBLly5l+fLlfO9732PixIkEAgG2bNnCe++9x8UXXzwQH4MQQvQZOdxIDEklJSVcfvnlLFu2rNvXg8Egbrc76dqqVau47rrrWLt2LVOmTAHiqwzmzp3L5s2bKSkpwbIsTj/9dAoKCnj55ZdR1XgnmmmanHvuuTQ1NfHRRx8BcMYZZ1BYWMiqVav6MadCCDEwZMhADElpaWm8//771NbWdvt6ZzBgWRbt7e20tLQwefJkgESF3p2PP/6YHTt2cPnll9PW1kZLSwstLS20tbUxbdo09uzZQ3V1dSIN27ZtY+fOnX2cOyGEGHgSEIgh6a677mLr1q2MGzeOM888k3vvvZfPPvss8XpNTQ3XXHMNxcXFFBcXU1payoQJEwDw+XyHve+uXbsAuPHGGyktLU36t2TJEgCam5sBWLBgAT6fj0mTJjFlyhTuuOMOPvjgg/7KshBC9CuZQyCGpJkzZ/KNb3yDNWvW8MYbb/DEE0/wy1/+khUrVnDZZZfx3e9+l+bmZm6++WbKy8vxeDyYpsnMmTMxTfOw9+187c4770wEEAcbPXo0EB8y2Lx5M2vWrGH9+vU8++yzrFy5kp/97GfccsstfZ9pIYToRxIQiCGroKCA2bNnM3v2bLxeL+eccw4PPPAAlZWVbN++nccff5yrrroq8f7O1v+RnHzyyQCkpqZy5plnHvX9mZmZzJo1i1mzZhEKhbj00kt54IEHuOmmm9A0rdd5E0KIgSZDBmLIMQzjkG7/zMxMSkpK8Hq9iYrYspLnyz766KNHvfeECRMoLS3l0Ucf7XZooXO4AKC1tTXpNZfLxZgxY4hEIgSDwWPOjxBCfBFID4EYcjo6Ohg7diwXXXQR48aNIz09nY0bN/Laa6/xox/9iPLyckpLS1m0aBG1tbVkZWXx6quvHnYCYleqqvLYY48xc+ZMpkyZwtVXX01xcTH19fW8++677N27l40bNwJw+umnM3XqVL761a+SnZ2dWNp47rnnkpaW1t8fgxBC9CkJCMSQ43a7ufbaa1m/fj1r1qxB13VKSkq45557mDNnDjabjWeffZb58+fz6KOPoqoq06ZN44UXXqC8vPyo9//617/O66+/zs9//nOefvpp2tvbyc3NZdy4cSxYsCDxvjlz5rBmzRrefPNNwuEwI0aMYN68ecybN68/sy+EEP1C9iEQQgghhMwhEEIIIYQEBEIIIYRAAgIhhBBCIAGBEEIIIZCAQAghhBBIQCCEEEIIJCAQQgghBBIQCCGEEAIJCIQQQgiBBARCCCGEAP4/ZEriILWawj4AAAAASUVORK5CYII=\n",
      "text/plain": [
       "<Figure size 360x360 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "datasci.scatter('sales', fit_line=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "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
}
