moral_hazard.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Moral Hazard\n",
    "-  Do government policies affect (un)employment policies?\n",
    " - In economics, moral hazard occurs when an entity has an incentive to increase its exposure to risk because it does not bear the full costs of that risk. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 91,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "import seaborn as sns\n",
    "import statsmodels.api as sm\n",
    "from statsmodels import regression"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Importing data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 92,
   "metadata": {},
   "outputs": [],
   "source": [
    "macro = pd.read_csv(r'Macroecomics indicators.csv', sep=';', parse_dates=True, index_col=0)\n",
    "macro = macro.sort_index(axis=0)\n",
    "pop = pd.read_csv(r'Popularity.csv', sep=';', parse_dates=True, index_col='DATA')\n",
    "pop = pop.sort_index(axis=0)\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Manipulating time series"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 93,
   "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>Desemprego</th>\n",
       "      <th>Inflação</th>\n",
       "      <th>Dívida/PIB</th>\n",
       "      <th>PRESIDENTE</th>\n",
       "      <th>POSITIVA</th>\n",
       "      <th>REGULAR</th>\n",
       "      <th>NEGATIVA</th>\n",
       "      <th>NS</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2012-03-31</th>\n",
       "      <td>7.9</td>\n",
       "      <td>5.77</td>\n",
       "      <td>52.72</td>\n",
       "      <td>Dilma Rousseff</td>\n",
       "      <td>62.0</td>\n",
       "      <td>29.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2012-06-30</th>\n",
       "      <td>7.5</td>\n",
       "      <td>5.00</td>\n",
       "      <td>53.42</td>\n",
       "      <td>Dilma Rousseff</td>\n",
       "      <td>62.0</td>\n",
       "      <td>29.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2012-09-30</th>\n",
       "      <td>7.1</td>\n",
       "      <td>5.24</td>\n",
       "      <td>54.05</td>\n",
       "      <td>Dilma Rousseff</td>\n",
       "      <td>62.0</td>\n",
       "      <td>29.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2012-12-31</th>\n",
       "      <td>6.9</td>\n",
       "      <td>5.61</td>\n",
       "      <td>53.67</td>\n",
       "      <td>Dilma Rousseff</td>\n",
       "      <td>62.0</td>\n",
       "      <td>29.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2013-03-31</th>\n",
       "      <td>8.0</td>\n",
       "      <td>6.35</td>\n",
       "      <td>54.05</td>\n",
       "      <td>Dilma Rousseff</td>\n",
       "      <td>43.0</td>\n",
       "      <td>35.0</td>\n",
       "      <td>20.0</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2013-06-30</th>\n",
       "      <td>7.4</td>\n",
       "      <td>6.56</td>\n",
       "      <td>53.61</td>\n",
       "      <td>Dilma Rousseff</td>\n",
       "      <td>43.0</td>\n",
       "      <td>35.0</td>\n",
       "      <td>20.0</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2013-09-30</th>\n",
       "      <td>6.9</td>\n",
       "      <td>6.07</td>\n",
       "      <td>52.95</td>\n",
       "      <td>Dilma Rousseff</td>\n",
       "      <td>43.0</td>\n",
       "      <td>35.0</td>\n",
       "      <td>20.0</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2013-12-31</th>\n",
       "      <td>6.2</td>\n",
       "      <td>5.84</td>\n",
       "      <td>51.54</td>\n",
       "      <td>Dilma Rousseff</td>\n",
       "      <td>43.0</td>\n",
       "      <td>35.0</td>\n",
       "      <td>20.0</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2014-03-31</th>\n",
       "      <td>7.2</td>\n",
       "      <td>5.81</td>\n",
       "      <td>51.79</td>\n",
       "      <td>Dilma Rousseff</td>\n",
       "      <td>40.0</td>\n",
       "      <td>32.0</td>\n",
       "      <td>27.0</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2014-06-30</th>\n",
       "      <td>6.8</td>\n",
       "      <td>6.39</td>\n",
       "      <td>52.75</td>\n",
       "      <td>Dilma Rousseff</td>\n",
       "      <td>40.0</td>\n",
       "      <td>32.0</td>\n",
       "      <td>27.0</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2014-09-30</th>\n",
       "      <td>6.8</td>\n",
       "      <td>6.59</td>\n",
       "      <td>55.11</td>\n",
       "      <td>Dilma Rousseff</td>\n",
       "      <td>40.0</td>\n",
       "      <td>32.0</td>\n",
       "      <td>27.0</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2014-12-31</th>\n",
       "      <td>6.5</td>\n",
       "      <td>6.52</td>\n",
       "      <td>56.28</td>\n",
       "      <td>Dilma Rousseff</td>\n",
       "      <td>40.0</td>\n",
       "      <td>32.0</td>\n",
       "      <td>27.0</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2015-03-31</th>\n",
       "      <td>7.9</td>\n",
       "      <td>7.66</td>\n",
       "      <td>59.49</td>\n",
       "      <td>Dilma Rousseff</td>\n",
       "      <td>9.0</td>\n",
       "      <td>21.0</td>\n",
       "      <td>68.0</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2015-06-30</th>\n",
       "      <td>8.3</td>\n",
       "      <td>8.51</td>\n",
       "      <td>60.74</td>\n",
       "      <td>Dilma Rousseff</td>\n",
       "      <td>9.0</td>\n",
       "      <td>21.0</td>\n",
       "      <td>68.0</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2015-09-30</th>\n",
       "      <td>8.9</td>\n",
       "      <td>9.53</td>\n",
       "      <td>63.64</td>\n",
       "      <td>Dilma Rousseff</td>\n",
       "      <td>10.0</td>\n",
       "      <td>21.0</td>\n",
       "      <td>69.0</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2015-12-31</th>\n",
       "      <td>8.9</td>\n",
       "      <td>10.36</td>\n",
       "      <td>65.50</td>\n",
       "      <td>Dilma Rousseff</td>\n",
       "      <td>9.0</td>\n",
       "      <td>20.0</td>\n",
       "      <td>70.0</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-03-31</th>\n",
       "      <td>10.9</td>\n",
       "      <td>10.14</td>\n",
       "      <td>66.34</td>\n",
       "      <td>Dilma Rousseff</td>\n",
       "      <td>10.0</td>\n",
       "      <td>19.0</td>\n",
       "      <td>69.0</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-06-30</th>\n",
       "      <td>11.3</td>\n",
       "      <td>9.15</td>\n",
       "      <td>67.53</td>\n",
       "      <td>Michel Temer</td>\n",
       "      <td>13.0</td>\n",
       "      <td>36.0</td>\n",
       "      <td>39.0</td>\n",
       "      <td>13.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-09-30</th>\n",
       "      <td>11.8</td>\n",
       "      <td>8.73</td>\n",
       "      <td>70.00</td>\n",
       "      <td>Michel Temer</td>\n",
       "      <td>14.0</td>\n",
       "      <td>34.0</td>\n",
       "      <td>39.0</td>\n",
       "      <td>12.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-12-31</th>\n",
       "      <td>12.0</td>\n",
       "      <td>7.04</td>\n",
       "      <td>69.84</td>\n",
       "      <td>Michel Temer</td>\n",
       "      <td>13.0</td>\n",
       "      <td>35.0</td>\n",
       "      <td>46.0</td>\n",
       "      <td>6.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-03-31</th>\n",
       "      <td>13.7</td>\n",
       "      <td>4.89</td>\n",
       "      <td>71.19</td>\n",
       "      <td>Michel Temer</td>\n",
       "      <td>10.0</td>\n",
       "      <td>31.0</td>\n",
       "      <td>55.0</td>\n",
       "      <td>4.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-06-30</th>\n",
       "      <td>13.0</td>\n",
       "      <td>3.56</td>\n",
       "      <td>72.65</td>\n",
       "      <td>Michel Temer</td>\n",
       "      <td>10.0</td>\n",
       "      <td>31.0</td>\n",
       "      <td>55.0</td>\n",
       "      <td>4.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-09-30</th>\n",
       "      <td>12.4</td>\n",
       "      <td>2.57</td>\n",
       "      <td>73.63</td>\n",
       "      <td>Michel Temer</td>\n",
       "      <td>3.0</td>\n",
       "      <td>16.0</td>\n",
       "      <td>77.0</td>\n",
       "      <td>3.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-12-31</th>\n",
       "      <td>11.8</td>\n",
       "      <td>2.82</td>\n",
       "      <td>73.74</td>\n",
       "      <td>Michel Temer</td>\n",
       "      <td>6.0</td>\n",
       "      <td>19.0</td>\n",
       "      <td>74.0</td>\n",
       "      <td>2.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018-03-31</th>\n",
       "      <td>13.1</td>\n",
       "      <td>2.79</td>\n",
       "      <td>74.94</td>\n",
       "      <td>Michel Temer</td>\n",
       "      <td>5.0</td>\n",
       "      <td>21.0</td>\n",
       "      <td>72.0</td>\n",
       "      <td>2.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018-06-30</th>\n",
       "      <td>12.4</td>\n",
       "      <td>3.34</td>\n",
       "      <td>76.83</td>\n",
       "      <td>Michel Temer</td>\n",
       "      <td>4.0</td>\n",
       "      <td>16.0</td>\n",
       "      <td>79.0</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018-09-30</th>\n",
       "      <td>11.9</td>\n",
       "      <td>4.40</td>\n",
       "      <td>77.02</td>\n",
       "      <td>Michel Temer</td>\n",
       "      <td>4.0</td>\n",
       "      <td>12.0</td>\n",
       "      <td>82.0</td>\n",
       "      <td>2.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018-12-31</th>\n",
       "      <td>11.6</td>\n",
       "      <td>4.12</td>\n",
       "      <td>76.53</td>\n",
       "      <td>Michel Temer</td>\n",
       "      <td>5.0</td>\n",
       "      <td>18.0</td>\n",
       "      <td>74.0</td>\n",
       "      <td>3.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-03-31</th>\n",
       "      <td>12.7</td>\n",
       "      <td>4.08</td>\n",
       "      <td>78.06</td>\n",
       "      <td>Jair Bolsonaro</td>\n",
       "      <td>34.0</td>\n",
       "      <td>34.0</td>\n",
       "      <td>25.0</td>\n",
       "      <td>8.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-06-30</th>\n",
       "      <td>12.0</td>\n",
       "      <td>4.32</td>\n",
       "      <td>78.02</td>\n",
       "      <td>Jair Bolsonaro</td>\n",
       "      <td>32.0</td>\n",
       "      <td>32.0</td>\n",
       "      <td>32.0</td>\n",
       "      <td>3.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "            Desemprego  Inflação  Dívida/PIB      PRESIDENTE  POSITIVA  \\\n",
       "2012-03-31         7.9      5.77       52.72  Dilma Rousseff      62.0   \n",
       "2012-06-30         7.5      5.00       53.42  Dilma Rousseff      62.0   \n",
       "2012-09-30         7.1      5.24       54.05  Dilma Rousseff      62.0   \n",
       "2012-12-31         6.9      5.61       53.67  Dilma Rousseff      62.0   \n",
       "2013-03-31         8.0      6.35       54.05  Dilma Rousseff      43.0   \n",
       "2013-06-30         7.4      6.56       53.61  Dilma Rousseff      43.0   \n",
       "2013-09-30         6.9      6.07       52.95  Dilma Rousseff      43.0   \n",
       "2013-12-31         6.2      5.84       51.54  Dilma Rousseff      43.0   \n",
       "2014-03-31         7.2      5.81       51.79  Dilma Rousseff      40.0   \n",
       "2014-06-30         6.8      6.39       52.75  Dilma Rousseff      40.0   \n",
       "2014-09-30         6.8      6.59       55.11  Dilma Rousseff      40.0   \n",
       "2014-12-31         6.5      6.52       56.28  Dilma Rousseff      40.0   \n",
       "2015-03-31         7.9      7.66       59.49  Dilma Rousseff       9.0   \n",
       "2015-06-30         8.3      8.51       60.74  Dilma Rousseff       9.0   \n",
       "2015-09-30         8.9      9.53       63.64  Dilma Rousseff      10.0   \n",
       "2015-12-31         8.9     10.36       65.50  Dilma Rousseff       9.0   \n",
       "2016-03-31        10.9     10.14       66.34  Dilma Rousseff      10.0   \n",
       "2016-06-30        11.3      9.15       67.53    Michel Temer      13.0   \n",
       "2016-09-30        11.8      8.73       70.00    Michel Temer      14.0   \n",
       "2016-12-31        12.0      7.04       69.84    Michel Temer      13.0   \n",
       "2017-03-31        13.7      4.89       71.19    Michel Temer      10.0   \n",
       "2017-06-30        13.0      3.56       72.65    Michel Temer      10.0   \n",
       "2017-09-30        12.4      2.57       73.63    Michel Temer       3.0   \n",
       "2017-12-31        11.8      2.82       73.74    Michel Temer       6.0   \n",
       "2018-03-31        13.1      2.79       74.94    Michel Temer       5.0   \n",
       "2018-06-30        12.4      3.34       76.83    Michel Temer       4.0   \n",
       "2018-09-30        11.9      4.40       77.02    Michel Temer       4.0   \n",
       "2018-12-31        11.6      4.12       76.53    Michel Temer       5.0   \n",
       "2019-03-31        12.7      4.08       78.06  Jair Bolsonaro      34.0   \n",
       "2019-06-30        12.0      4.32       78.02  Jair Bolsonaro      32.0   \n",
       "\n",
       "            REGULAR  NEGATIVA    NS  \n",
       "2012-03-31     29.0       7.0   1.0  \n",
       "2012-06-30     29.0       7.0   1.0  \n",
       "2012-09-30     29.0       7.0   1.0  \n",
       "2012-12-31     29.0       7.0   1.0  \n",
       "2013-03-31     35.0      20.0   1.0  \n",
       "2013-06-30     35.0      20.0   1.0  \n",
       "2013-09-30     35.0      20.0   1.0  \n",
       "2013-12-31     35.0      20.0   1.0  \n",
       "2014-03-31     32.0      27.0   1.0  \n",
       "2014-06-30     32.0      27.0   1.0  \n",
       "2014-09-30     32.0      27.0   1.0  \n",
       "2014-12-31     32.0      27.0   1.0  \n",
       "2015-03-31     21.0      68.0   1.0  \n",
       "2015-06-30     21.0      68.0   1.0  \n",
       "2015-09-30     21.0      69.0   1.0  \n",
       "2015-12-31     20.0      70.0   1.0  \n",
       "2016-03-31     19.0      69.0   1.0  \n",
       "2016-06-30     36.0      39.0  13.0  \n",
       "2016-09-30     34.0      39.0  12.0  \n",
       "2016-12-31     35.0      46.0   6.0  \n",
       "2017-03-31     31.0      55.0   4.0  \n",
       "2017-06-30     31.0      55.0   4.0  \n",
       "2017-09-30     16.0      77.0   3.0  \n",
       "2017-12-31     19.0      74.0   2.0  \n",
       "2018-03-31     21.0      72.0   2.0  \n",
       "2018-06-30     16.0      79.0   1.0  \n",
       "2018-09-30     12.0      82.0   2.0  \n",
       "2018-12-31     18.0      74.0   3.0  \n",
       "2019-03-31     34.0      25.0   8.0  \n",
       "2019-06-30     32.0      32.0   3.0  "
      ]
     },
     "execution_count": 93,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "macroQ = macro.asfreq(freq='Q', method='ffill')\n",
    "macroQ\n",
    "popQ = pop.asfreq(freq='Q', method='ffill')\n",
    "popQ\n",
    "\n",
    "serieI = pd.concat([macroQ, popQ], axis=1).dropna()\n",
    "serieI.columns\n",
    "serieI"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 120,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(0.9, 0.8)"
      ]
     },
     "execution_count": 120,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "(90/100, 80/100, )"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Linear regression"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 115,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<table class=\"simpletable\">\n",
       "<caption>OLS Regression Results</caption>\n",
       "<tr>\n",
       "  <th>Dep. Variable:</th>       <td>Desemprego</td>    <th>  R-squared:         </th> <td>   0.521</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Model:</th>                   <td>OLS</td>       <th>  Adj. R-squared:    </th> <td>   0.504</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Method:</th>             <td>Least Squares</td>  <th>  F-statistic:       </th> <td>   30.46</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Date:</th>             <td>Wed, 04 Aug 2021</td> <th>  Prob (F-statistic):</th> <td>6.72e-06</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Time:</th>                 <td>09:04:53</td>     <th>  Log-Likelihood:    </th> <td> -58.778</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>No. Observations:</th>      <td>    30</td>      <th>  AIC:               </th> <td>   121.6</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Df Residuals:</th>          <td>    28</td>      <th>  BIC:               </th> <td>   124.4</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Df Model:</th>              <td>     1</td>      <th>                     </th>     <td> </td>   \n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Covariance Type:</th>      <td>nonrobust</td>    <th>                     </th>     <td> </td>   \n",
       "</tr>\n",
       "</table>\n",
       "<table class=\"simpletable\">\n",
       "<tr>\n",
       "      <td></td>        <th>coef</th>     <th>std err</th>      <th>t</th>      <th>P>|t|</th>  <th>[0.025</th>    <th>0.975]</th>  \n",
       "</tr>\n",
       "<tr>\n",
       "  <th>const</th>    <td>   11.9520</td> <td>    0.527</td> <td>   22.682</td> <td> 0.000</td> <td>   10.873</td> <td>   13.031</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>POSITIVA</th> <td>   -0.0882</td> <td>    0.016</td> <td>   -5.519</td> <td> 0.000</td> <td>   -0.121</td> <td>   -0.055</td>\n",
       "</tr>\n",
       "</table>\n",
       "<table class=\"simpletable\">\n",
       "<tr>\n",
       "  <th>Omnibus:</th>       <td> 0.341</td> <th>  Durbin-Watson:     </th> <td>   0.349</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Prob(Omnibus):</th> <td> 0.843</td> <th>  Jarque-Bera (JB):  </th> <td>   0.505</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Skew:</th>          <td> 0.042</td> <th>  Prob(JB):          </th> <td>   0.777</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Kurtosis:</th>      <td> 2.370</td> <th>  Cond. No.          </th> <td>    53.6</td>\n",
       "</tr>\n",
       "</table><br/><br/>Notes:<br/>[1] Standard Errors assume that the covariance matrix of the errors is correctly specified."
      ],
      "text/plain": [
       "<class 'statsmodels.iolib.summary.Summary'>\n",
       "\"\"\"\n",
       "                            OLS Regression Results                            \n",
       "==============================================================================\n",
       "Dep. Variable:             Desemprego   R-squared:                       0.521\n",
       "Model:                            OLS   Adj. R-squared:                  0.504\n",
       "Method:                 Least Squares   F-statistic:                     30.46\n",
       "Date:                Wed, 04 Aug 2021   Prob (F-statistic):           6.72e-06\n",
       "Time:                        09:04:53   Log-Likelihood:                -58.778\n",
       "No. Observations:                  30   AIC:                             121.6\n",
       "Df Residuals:                      28   BIC:                             124.4\n",
       "Df Model:                           1                                         \n",
       "Covariance Type:            nonrobust                                         \n",
       "==============================================================================\n",
       "                 coef    std err          t      P>|t|      [0.025      0.975]\n",
       "------------------------------------------------------------------------------\n",
       "const         11.9520      0.527     22.682      0.000      10.873      13.031\n",
       "POSITIVA      -0.0882      0.016     -5.519      0.000      -0.121      -0.055\n",
       "==============================================================================\n",
       "Omnibus:                        0.341   Durbin-Watson:                   0.349\n",
       "Prob(Omnibus):                  0.843   Jarque-Bera (JB):                0.505\n",
       "Skew:                           0.042   Prob(JB):                        0.777\n",
       "Kurtosis:                       2.370   Cond. No.                         53.6\n",
       "==============================================================================\n",
       "\n",
       "Notes:\n",
       "[1] Standard Errors assume that the covariance matrix of the errors is correctly specified.\n",
       "\"\"\""
      ]
     },
     "execution_count": 115,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "def reg (X, Y):\n",
    "    X = sm.add_constant(X)\n",
    "    model = regression.linear_model.OLS(Y, X).fit()\n",
    "    return model.summary()\n",
    "\n",
    "reg(serieI['POSITIVA'], serieI['Desemprego'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 116,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<table class=\"simpletable\">\n",
       "<caption>OLS Regression Results</caption>\n",
       "<tr>\n",
       "  <th>Dep. Variable:</th>       <td>Dívida/PIB</td>    <th>  R-squared:         </th> <td>   0.582</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Model:</th>                   <td>OLS</td>       <th>  Adj. R-squared:    </th> <td>   0.567</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Method:</th>             <td>Least Squares</td>  <th>  F-statistic:       </th> <td>   38.95</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Date:</th>             <td>Wed, 04 Aug 2021</td> <th>  Prob (F-statistic):</th> <td>9.59e-07</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Time:</th>                 <td>09:05:12</td>     <th>  Log-Likelihood:    </th> <td> -97.448</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>No. Observations:</th>      <td>    30</td>      <th>  AIC:               </th> <td>   198.9</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Df Residuals:</th>          <td>    28</td>      <th>  BIC:               </th> <td>   201.7</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Df Model:</th>              <td>     1</td>      <th>                     </th>     <td> </td>   \n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Covariance Type:</th>      <td>nonrobust</td>    <th>                     </th>     <td> </td>   \n",
       "</tr>\n",
       "</table>\n",
       "<table class=\"simpletable\">\n",
       "<tr>\n",
       "      <td></td>        <th>coef</th>     <th>std err</th>      <th>t</th>      <th>P>|t|</th>  <th>[0.025</th>    <th>0.975]</th>  \n",
       "</tr>\n",
       "<tr>\n",
       "  <th>const</th>    <td>   73.3266</td> <td>    1.912</td> <td>   38.343</td> <td> 0.000</td> <td>   69.409</td> <td>   77.244</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>POSITIVA</th> <td>   -0.3618</td> <td>    0.058</td> <td>   -6.241</td> <td> 0.000</td> <td>   -0.480</td> <td>   -0.243</td>\n",
       "</tr>\n",
       "</table>\n",
       "<table class=\"simpletable\">\n",
       "<tr>\n",
       "  <th>Omnibus:</th>       <td> 7.079</td> <th>  Durbin-Watson:     </th> <td>   0.259</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Prob(Omnibus):</th> <td> 0.029</td> <th>  Jarque-Bera (JB):  </th> <td>   5.313</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Skew:</th>          <td> 0.871</td> <th>  Prob(JB):          </th> <td>  0.0702</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Kurtosis:</th>      <td> 4.102</td> <th>  Cond. No.          </th> <td>    53.6</td>\n",
       "</tr>\n",
       "</table><br/><br/>Notes:<br/>[1] Standard Errors assume that the covariance matrix of the errors is correctly specified."
      ],
      "text/plain": [
       "<class 'statsmodels.iolib.summary.Summary'>\n",
       "\"\"\"\n",
       "                            OLS Regression Results                            \n",
       "==============================================================================\n",
       "Dep. Variable:             Dívida/PIB   R-squared:                       0.582\n",
       "Model:                            OLS   Adj. R-squared:                  0.567\n",
       "Method:                 Least Squares   F-statistic:                     38.95\n",
       "Date:                Wed, 04 Aug 2021   Prob (F-statistic):           9.59e-07\n",
       "Time:                        09:05:12   Log-Likelihood:                -97.448\n",
       "No. Observations:                  30   AIC:                             198.9\n",
       "Df Residuals:                      28   BIC:                             201.7\n",
       "Df Model:                           1                                         \n",
       "Covariance Type:            nonrobust                                         \n",
       "==============================================================================\n",
       "                 coef    std err          t      P>|t|      [0.025      0.975]\n",
       "------------------------------------------------------------------------------\n",
       "const         73.3266      1.912     38.343      0.000      69.409      77.244\n",
       "POSITIVA      -0.3618      0.058     -6.241      0.000      -0.480      -0.243\n",
       "==============================================================================\n",
       "Omnibus:                        7.079   Durbin-Watson:                   0.259\n",
       "Prob(Omnibus):                  0.029   Jarque-Bera (JB):                5.313\n",
       "Skew:                           0.871   Prob(JB):                       0.0702\n",
       "Kurtosis:                       4.102   Cond. No.                         53.6\n",
       "==============================================================================\n",
       "\n",
       "Notes:\n",
       "[1] Standard Errors assume that the covariance matrix of the errors is correctly specified.\n",
       "\"\"\""
      ]
     },
     "execution_count": 116,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "reg(serieI['POSITIVA'], serieI['Dívida/PIB'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 118,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<table class=\"simpletable\">\n",
       "<caption>OLS Regression Results</caption>\n",
       "<tr>\n",
       "  <th>Dep. Variable:</th>        <td>Inflação</td>     <th>  R-squared:         </th> <td>   0.001</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Model:</th>                   <td>OLS</td>       <th>  Adj. R-squared:    </th> <td>  -0.035</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Method:</th>             <td>Least Squares</td>  <th>  F-statistic:       </th> <td> 0.01882</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Date:</th>             <td>Wed, 04 Aug 2021</td> <th>  Prob (F-statistic):</th>  <td> 0.892</td> \n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Time:</th>                 <td>09:05:45</td>     <th>  Log-Likelihood:    </th> <td> -65.473</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>No. Observations:</th>      <td>    30</td>      <th>  AIC:               </th> <td>   134.9</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Df Residuals:</th>          <td>    28</td>      <th>  BIC:               </th> <td>   137.7</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Df Model:</th>              <td>     1</td>      <th>                     </th>     <td> </td>   \n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Covariance Type:</th>      <td>nonrobust</td>    <th>                     </th>     <td> </td>   \n",
       "</tr>\n",
       "</table>\n",
       "<table class=\"simpletable\">\n",
       "<tr>\n",
       "      <td></td>        <th>coef</th>     <th>std err</th>      <th>t</th>      <th>P>|t|</th>  <th>[0.025</th>    <th>0.975]</th>  \n",
       "</tr>\n",
       "<tr>\n",
       "  <th>const</th>    <td>    6.0632</td> <td>    0.659</td> <td>    9.205</td> <td> 0.000</td> <td>    4.714</td> <td>    7.413</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>POSITIVA</th> <td>   -0.0027</td> <td>    0.020</td> <td>   -0.137</td> <td> 0.892</td> <td>   -0.044</td> <td>    0.038</td>\n",
       "</tr>\n",
       "</table>\n",
       "<table class=\"simpletable\">\n",
       "<tr>\n",
       "  <th>Omnibus:</th>       <td> 1.102</td> <th>  Durbin-Watson:     </th> <td>   0.135</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Prob(Omnibus):</th> <td> 0.576</td> <th>  Jarque-Bera (JB):  </th> <td>   1.054</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Skew:</th>          <td> 0.313</td> <th>  Prob(JB):          </th> <td>   0.590</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Kurtosis:</th>      <td> 2.328</td> <th>  Cond. No.          </th> <td>    53.6</td>\n",
       "</tr>\n",
       "</table><br/><br/>Notes:<br/>[1] Standard Errors assume that the covariance matrix of the errors is correctly specified."
      ],
      "text/plain": [
       "<class 'statsmodels.iolib.summary.Summary'>\n",
       "\"\"\"\n",
       "                            OLS Regression Results                            \n",
       "==============================================================================\n",
       "Dep. Variable:               Inflação   R-squared:                       0.001\n",
       "Model:                            OLS   Adj. R-squared:                 -0.035\n",
       "Method:                 Least Squares   F-statistic:                   0.01882\n",
       "Date:                Wed, 04 Aug 2021   Prob (F-statistic):              0.892\n",
       "Time:                        09:05:45   Log-Likelihood:                -65.473\n",
       "No. Observations:                  30   AIC:                             134.9\n",
       "Df Residuals:                      28   BIC:                             137.7\n",
       "Df Model:                           1                                         \n",
       "Covariance Type:            nonrobust                                         \n",
       "==============================================================================\n",
       "                 coef    std err          t      P>|t|      [0.025      0.975]\n",
       "------------------------------------------------------------------------------\n",
       "const          6.0632      0.659      9.205      0.000       4.714       7.413\n",
       "POSITIVA      -0.0027      0.020     -0.137      0.892      -0.044       0.038\n",
       "==============================================================================\n",
       "Omnibus:                        1.102   Durbin-Watson:                   0.135\n",
       "Prob(Omnibus):                  0.576   Jarque-Bera (JB):                1.054\n",
       "Skew:                           0.313   Prob(JB):                        0.590\n",
       "Kurtosis:                       2.328   Cond. No.                         53.6\n",
       "==============================================================================\n",
       "\n",
       "Notes:\n",
       "[1] Standard Errors assume that the covariance matrix of the errors is correctly specified.\n",
       "\"\"\""
      ]
     },
     "execution_count": 118,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "reg(serieI['POSITIVA'], serieI['Inflação'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Graphics "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 107,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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BmXrUqB/ep86aC1xydU5392RKpjSjwLvw35Cs+zv09laj/4e7e4iIxjxb7u5p27bF6jCGRKZSfSfb6qn0fcrkI6FW1aLolE8g5uDhfT6vD1FNg/AXjfnTl+3crZ9tzIWJuTAxFyY752Kw3T22vJJiN4M2235sNNu2PvcYHCcuhFpZA8fME8f0ZFuZTEAGW3n6MhHRGMciJccyabYVpeVQlyyDuqRmTE+2PfT0ZZ4RREQ0lnC5Jw/IRByObW8gvOZF6Dvf7nOfcuwsOCtr4Ji7+LCTbQvB4YbaCY/PGLs/BnJh58u32cZcmJgLE3NhsnMuuNyT54TLDU9VLfS5i6Ef2GdcXemebKu/sxXxd7YCTz4EdWH1gJNtxwoZi0DGIsbgt0AJDzQkIipgLFLyjDJuIlznXgbnORcjtX0LtMY6o9k2FoW29p/Q1v7TaLatrIG66BRj5PwYJOMxyHiMBxoSERWwnBYpuq7jjjvuQGlpKf7zP/8T4XAYK1euRGtrKyoqKnDdddfB7/cf/hNlQbYP3Iu/8DS0f70AxKOA2wv11LPhPvuiYX8+4XBAnTUP6qx5/Tfb/vVhJP76MOAvgrPmLDjPOH9MNtvKRAyyLTbkAw2JiCj/5fRd7aWXXsLkyZPTf1+9ejVmzZqFO++8E7NmzcLq1atzEkfPgXt6qAPw+aGHOhB/8iFoWzcP6/PFX3ga2gvPAIk44DAmzGovPIP4C09nJd6eZlvvzXfCecGVxmTWnuWecAjJvz2JyA9uQOJvTxpj+McgmUxAbz8AvWUf5CieJk1ERLmTsyKlra0Nb7zxBpYtW5a+rbm5GdXV1QCA6upqNDc35ySWbB+4p/3rBaNocCiAQPefwrg9i4QQSL25ESgpAyYfCZSNM0fdh0NIvvgMoj+6GdFf/wTaa2shk4msPr8dSC0BPdgKvWUvZCTc74GGRERkDzlb7nnsscdw2WWXIRaLpW/r7OxEaWkpAKC0tBShUKjfx9bV1aGurg4AsGLFCvi8vhHFEm1vhcMX6NN8Kl0eyPbWYX3ucDwGOBwwKpRuigLEYxl/PsWhZPSxfWIPFAOBYujJBPRgGxS3G3pHe7rZVjz1R7gXL4PnlNOhTpthi2bbTPOQkUQM0DUo/iIIf8AWX39vDocjZ8uf+Y65MDEXJubCVKi5yKhISaVSeOWVV7B9+3Z0dXX1+e30lltuOezjN23ahOLiYkyfPh1vv/32YT/+YLW1taitrU3/fbAtqhkpq0Aq1GFcQekmE3EoZRXD+9xuT/dST68LU7oOuD0Zf77Dbb1N6y92PQVlyjR4rrvZaLZtqkfqzY2Q0Qhi9S8gVv+C2Wy7sBoiUDTIE1gr4zwMRajTGAbn9UH4/LaZtWLnLYXZxlyYmAsTc2Gycy5KSkoGvC+jIuWxxx7Dtm3bUFtbi6effhoXXXQR/vWvf2HJkiUZBbBz5040NzfjjTfeQDKZRCwWw/3334/i4mIEg0GUlpYiGAyiqCg3b57O089F/MmHIAHA6QKSiREduKeeerbRk5LSjSsoug5ICfXUs7MaNzB47H2abbs6ob22Fsmmesi9H5nNts89DsdJC7on2540ZpptpZ4CwiHIcMjYEeQPsMmWiCjPZVSkbNy4Ed/5zndQUVGBZ555BmeeeSZOPPFE/PGPf8zoSS655BJccsklAIC3334bf//73/HFL34RTzzxBBoaGrB8+XI0NDRg/vz5w/5ChiLbB+717OLJ5u6egWQauwj0mmz74S5oTXXQNjYCsShSm9YjtWk9REk51CVLoVbWQKmYkPVY85VMxCATMQiHCuHzc+w+EVGeyqhISSQSKC8vBwC4XC7E43FMnjwZH3zwwYiefPny5Vi5ciXWrFmD8vJyXH/99SP6fEOhzpqb1VOA3WdfNCpFSX+GErsQAo5pM+CYNgOuC66EtnkDtKZ66Du3QXa0IfnSs0i+9OyYm2wLGCcw9xm77wuMma+diMgOMipSJk+ejPfeew9HH300pk+fjmeffRYejyfd9DoUxx9/PI4//ngAQCAQwI033jjkz0HDI1xuOBcvhXPxUmOy7fo1xmTbXs225mTbGihTj7Jds+nwSGMnUCRsLAUVFffp+SEiImtkdHbPrl27oCgKpk+fjn379uFPf/oTYrEYLrvsMsycOTMXcaYV4tk9wCg1jGZA6jpSb7+RbrZFKpW+z4pmW6vycDCjWLF27L6dG+GyjbkwMRcm5sJk51wMdnYPDxjME/nw5mw02zYg2VQHufcj8w6HA44TF0Ctqh31Ztt8yENvVl5ZsfMPnWxjLkzMhYm5MNk5FyM+YPC2227DySefjCVLlqR7U6jwGM2250CtPfvQZtvNG5DavGHMNdvKRAyytXvsvr8IIlszXIiI6LAyupLy+uuvo6mpCVu2bMH06dNRWVmJxYsXWzI4hldScksm4n2abXsbjWbbfM1DD2NHUKB7R9Dobt+2829G2cZcmJgLE3NhsnMusrbcE4vF0gXLjh07MGvWLHzta1/LWqCZKCkpQfuObZApLafPO9ry/c0ZAPQD+6Gtr08326Z5vFAXnAy1qnbEzbZ2yAMACKGYw+FGaUeQnX/oZBtzYWIuTMyFyc65GPFyTw+Px4PKykr4fD6kUim88cYbWQlwqJQJk41zaeIxyFh0TJ5RYwVl3AS4ll8K5zkXI/X2FmhNdUazbSwKreFlaA0vQ0yeCmdlbd5Pth0pKXUg0gUZ6TLOgPL6jaJlTOyGIiLKjYyupEgpsW3bNjQ2NmLjxo2oqKhAVVWVJT0q/VVcMpUC4lHIeAwyFgNgq15gAPa5gnAw2dUJ7fUGJBvrIffuNu8YZrOtXfMAoHv0vt+YZusY+XA4O/9mlG3MhYm5MDEXJjvnYsTLPTfddBPcbjeWLFmCqqoqTJ48OetBZmqwLwYwCirEY5DxKBCLGePQbcDOb86AkfeDm217DKXZ1u55MAgIj9dotB3BFmY7/9DJNubCxFyYmAuTnXMx4iLl3XffxYwZM7Ie2HAcrkg5mEwkzIJFy99locJ4czYM2mx7zAlwVtXCMWdRv9t6CykPAIxdQb7AsJaC7PxDJ9uYCxNzYWIuTHbOxbB6Ug4cOIBx48YBAIqKitDS0tLvx40fPz4LIY4e4XIZv80WlZjLQrEoZDwOOy4L2cGgk213bkN85zaz2bayBsqRRxdsL4dMJiA72iBCHZA+vzF6PwtLQUREY8GAV1K+9rWv4Ze//CUA4Mtf/vKAn+C3v/3t6EQ2gKFeSRmIuSwUM/60eLdQoV1BOJgx2bZXs22vybZGs20N1IWnwD9+YkHnYShLQXb+zSjbmAsTc2FiLkx2zkXBTZzNRpFyMKlpQKKnaIkbuzdyqNCLlN4Ga7Z1zV0CsfiUUZ9smw8OtxRk5x862cZcmJgLE3NhsnMuRlykPPLII7jyyisPuf3RRx/FZz7zmZFHOASjVaT0JqUEkgnzKksOtjiPpSKlh9lsWw9t47r+m22X1EAZV9iTbdO7ggIB4/+72fmHTrYxFybmwsRcmOyci8He1zP6VXXt2rX93r5u3brhR5XHhBAQLjeUohIo4yZCmTgFSmkFhNff502ERkYIAce0GXBf9nn4br0H7n/7MpzHnQgAkB1tSL70LKI/vgXRX/0PkhtehUzELY54dEg9BRnuhL7vY+gd7cZVPSIiGnyY25o1awAAuq6n/79HS0sLAoHA6EWWR4TSPV3U64OUEiIRN66yxKKW97IUCuFyQ110CnzLzkTXh+/1mWyr79yGxM5tSDz1R6gLqqBW1hZos62EjHRBRsLGa83ltDogIiJLDVqk9Fwp0TTtkKsmxcXFuPbaa0cvsjwlhADcHgi3ByguNXZvRKNALMKCJUv6TLbdvgVaY+/Jtq9Aa3ilT7Nt4U22lZDRMFL790LXdYiANacwExFZLaOelKeeegoXX3xxLuI5rFz0pAxXumCJRyG15JAeOxZ7UvozUB5kVwja62sHnmxbWQvH8YXVbNs7F8LlNnYEebwWR2UNO6+3ZxtzYWIuTHbOxbAaZ6WU6cvpuj7wThclx28K+Vyk9DbUgoVFiuFweZBSQt/9HrTGun6abcugLllWMM22/eVCqE4IfwDw+AqqIDscO/8AzjbmwmTHXCSbG5F47nHoLXuhjJ8E1/mXwzm/asSf14656DGsIuXrX/867r33XgCFOScll2QyARkbfOotixTDUPIgE3Gk3ngNyaZ66O9s7XOfcswJUCtroM5dbNulksFykT6F2R+AUAu/d8XOP4Czjbkw2S0XyeZGxB68F1CdgMsNJOKAloTnmq+PuFCxWy56G1aR0tbWlj48sLW1dcBPXlFRkYUQM2fHIqU3qWlGw2081r1bxUg/ixTDcPOgt+43Jts2rYHsaDPv8Hht22ybaS6Ey2MUKwW8FGTnH8DZxlyY7JaL8B03Qg+2GT2N3WQ8BqW0HP7v/2xEn9tuuehtWGPxe59ufHAhkkgkoCgKVHXQvlvqh1BVIFAEESgyDj+MdQ+QU+zz5pmPlIoJcH3yEjjPvgip7W8ak223vN632XZSd7PtomqIQLHVIWeNTMQgEzEIxWEsBfm4VZ4oH+ktewH/QY3+LrdxO/UroyrjiSeewOLFi3H00Udj8+bN+M1vfgMhBL785S9j3rx5ox1jwRKKw3hD8fnh8PmgtLcZy0J5MKbfroSiQD1hDtQT5nQ32zYg2VQH+fFuyL27kXjmESSef7y72bYGjuPnFExvh9RTkKEOINSZlVOYiSi7lPGToAfbgF5XUpCIQxk/ybqg8lxGRUpjYyMuuOACAMBzzz2HL3zhC/B6vXj88cdZpGSJEAKiZ2szjD4WxGPGYYg5mHhbiESgCM7as6HWnGU02zbVQ3u9AYhFkdq8AanNG4xm28VLjeWgAmi2NUjIWAQyFhnzu4KI8onr/MsRe/BeY5G/V0+K6/zLrQ4tb2VUpCQSCbjdbnR1daGlpQWLFi0CMHivCo2McLoApwsiUGwsCyUSkPGoca4Qr7IMiRACjiOPhuPIo+H61BV9mm1lRzuS/3gOyX88B+WY46FW1tq62fZgMhGHTMTH7K4gonzinF8FXINR2d1TqDIqUiZMmIB169Zh//79mD17NgAgFArB6Sz8XQX5QCgOwONN/zZs9WGIdtYz2VZddMohzbb6zreR2Pl2QU62lVoSsqMdorMD0uOF8PkLphAjshPn/CoWJUOQUZHy2c9+Fo899hgcDgc+//nPAwDefPNNnHjiiaMaHPVPqCqgBiB8AWOeTTIBGYsNa4jcWNZ/s+1Bk20nTYGzsrZgmm2l1IFoGDIahnCo3cc9+I3XFBFRnslo4mw+sfsW5IFka/uY1JLGFmeb9rJYvRX74GbbNIcDjtnzoVbVwjHzJAjH6O+eyWUuhMsN4fEBXm9e7gyy8/bKbGMuzIFoOLAPGDeRSyaw9+tiWHNSDrZt2zasW7cO7e3tKCsrQ1VVFWbNmpXVQDPBIiVzMpUyC5ZELKufe7RYXaT0GHSybXGpMdm2sgbKuImjFoM1uRAQHo9RsLg9edO/YucfwNk21nPReyCaw+NFKhbN2kA0O7Pz62LERUp9fT2eeuopLFu2DBUVFWhra8OaNWtw4YUXora2NusBD4ZFyvAYM1m6C5a4OUQu3+RLkdLb4JNtR6/Z1vpcCAi32+iF8lh7hcXOP4CzbaznovdANIeiIKXrWRuIZmd2fl0Ma5hbb3/729/wzW9+E0ceeWT6tiVLluDXv/51zosUGh5jJkt3H4uup7c3Ix5j4+1hHNJs21QPbf2rhzbbzq+CWlU4zbaANCYjx2NAR7uxRd5X2JNtKf9xINrYklGREg6HMXny5D63TZw40bZV21gnlO5zX7w+o/E2HjO2N8dixhUXGpBSMQGu5ZfCec7F3c229eZk23WvQFtXeM22PXoKlvR2Zq+/QIoxshMORBtbMipSjj32WDz++OO49NJL4Xa7EY/H8eSTT+KYY44Z7fholAkhzO3NJd2Nt/G4UbQkErzKMoA+k23DXdBeWwutqR76xx9C7v3ImGz73ONwnDjfnGybg2bbXEhvZw51QnqNicncHUS50nsgmvR4jSt9HIhWsDLqSQkGg7jvvvuwc+dO+Hw+RCIRHHPMMfjSl76E0tLSHIRpYk9K7kgpjeWgeCxno/qt78MYPqPZ9n1oTXXpybY9htNsa6dcjPZSUD5+f1iFueDunv7Y+XWRld09gHEyckdHB0pKSvocQJhLLFKskx7VH49BJhIYjeZbO70xD0YmE0ht3tB/s+2M46FW1UKdsxjCPXCzrR1zIRwqhM9vLAVl8cqRHb4/coW5MDEXJjvnYsSNswAQiUSwffv2dJEyd+5c+Hy+jB6bTCbx05/+FJqmIZVKYdGiRbjwwgsRDoexcuVKtLa2oqKiAtdddx38fn+mIVGO9R3VrwOJOHtZBiCcroEn2777NhLvvo3Ekw9BXXCycXVl2oyC6O+QKa37kMOO9NUVuD0F8bURUe5ldCVl69at+PWvf41JkyahvLwcbW1t2Lt3L77yla9kNCtFSol4PA6PxwNN0/DTn/4UV1xxBTZu3Ai/34/ly5dj9erVCIfDuOyyywb9XLySkp9kPAYZiwDR6Ij6WOx49SBTUtf7TrbttXxmNNvWQF10SrrZtlByIRSH0ajt8Q37VGa7f39kE3NhYi5Mds7FiK+kPPLII7j66quxZMmS9G0bNmzAww8/jNtvv/2wjxdCwOMxOrFTqRRSqRSEEGhubsZNN90EAKiursZdd9112CKF8lPPCc6yuHu3UDRsjOrP03ksVjik2fb1BmiNdb2abR9F4rkn0s22skDW2KWeAsIhyHDIGMXv8UF4vcaVOSKiQWRUpASDwfTJxz0WLFiA//u//8v4iXRdx+23346WlhacdtppmDFjBjo7O9ONt6WlpQiFQplHTnmp926hdONtzzwWLgmlCX8AzpqzoC47E/pH7xuTbbubbVNvvGYMjyspg2Px0lGfbJtLMqUB4U7IcCeE6jReKzw7iIgGkNFPhurqarz88ss444wz0re98sorqK6uzviJFEXBrbfeikgkgl/96lf46KOPMn5sXV0d6urqAAArVqwoyL4Vh8NRkF8XAgEA3TuFEnHo0Uj3lsH+dwopDgU+b2a9TgXjuNnAcbMhL/93xDc1Ibb2n0i+vQV6Rzv0fzyH5D+eg/PYWfCc8gm4F1RB9J4PYXcpDejqMM4O8vkhvL5+R/EX7PfHMDAXJubCVKi5yKgn5Sc/+Ql27dqFoqIilJWVob29HaFQCEcf3Xey5i233JLRkz7zzDNwu92or6/HTTfdhNLSUgSDQdx111244447Bn0se1IKQ3qn0EEHIRZKH8ZI6a0tEBvXIdrwMmSwzbzD7YG6oApqZW3BNNv2JYxCxRfo078y1r4/BsNcmJgLk51zMeKelJqaGtTU1Aw7gFAoBIfDAZ/Ph0Qiga1bt+KTn/wk5s2bh4aGBixfvhwNDQ2YP3/+sJ+D7KXPTqFUCohHjSsshfaeO0xKxXj4PnUF8InzkNrxFrTGOmOybTwGbd2/oK37F8TEI+CsqoW68BSIokKZbCuNfqZoGEJ1Qfj9gGeMXVkjorQhzUkZrt27d+OBBx6AruuQUmLx4sX41Kc+ha6uLqxcuRJtbW0oLy/H9ddff9jLVbySUth8Ph/Cba3c2oxDryod3GybpjgKcrJtDyEU+CoqEJXKsHcHFRL+rDAxFyY75yJrw9zyAYuUwnZwHmQi0d14GzVG9o8hAy19SSkPabbtMZzJtnbQkwuhOiG8fsDns/RUZivxZ4WJuTDZORcsUmzAzi+wbBosDzKZgIxGgGhkTFxhyaQ/RyYTxk6gpnroO97qc58y43iolTVQ5y4ZdLKtHRyaCwHh8RgFyxgbFsefFSbmwmTnXGRl4iyR1YTTBeF0QRaVcBZLN+F0QV1YDXVhNfTWFmOy7fp6yGCvybZP/bG72bYGyrRjCuQNXRpN17EohOKA7D7Vm7NXiAoLr6TkCTtXwdk01DxIPQVEIkbBUmDLQcPd6ZSebLu+Hqk3Xu872XbiEd2TbZfaqtk201wIp8s4O8jT/1bmQsCfFSbmwmTnXIx4uUfTNDz//PNoaGhAR0cHSktLcfLJJ+O8886DmuMhTCxSCttI8iATCchoGIhFC2I5KBvbsdPNtk110PfYt9l2qLkQQgG8XghvoOCabfmzwsRcmOycixEv9/zlL3/Brl27cPXVV6OiogKtra147rnnEIvFcMUVV2Q1WKLhEi6X8YZUUgaZiJuTbgvsCstQ9Jlsu/t9aOvrjWbbaCQ92TbdbLtkGZTxk6wOOSuk1IFIGDISNgbF+YsgPF6rwyKiIcqoSNmwYQNuvfVWBLqnh06aNAnTpk3DD3/4QxYplJeEyw3hMppFpZY0tjPHo5CJuMWRWUMIAceRR8Fx5FFwfeoKpN54HcmmOug73oLsDCLZPdm2kJpte8hEHDIR7567EjAOOyyIvhyiwjeitRopbdXOQmOUUJ1AwAkRKDKWgWIxY3BcPDaiE5vtymi2PRnqwpOht7VAaxobzbZSS0B2tEF0dQI+P+Dzj9ltzER2kVGRsmjRIvzyl7/E+eefn17uef7557F48eLRjo8oq4TiMN6cfH5I2XNic2TMFixK+Xi4PnkxnGdfaEy2baozmm0Pnmxrw2bbgciUBhnqAEKdEB6vcWZQIZ2HRFRAhtQ429jYiI6ODpSUlKCyshLnnXcenE5nLuJMY+NsYbMqD1JKo+G2p48lDwoWq84xysdm29HOhTEkzgd4/XnfRMyfFSbmwmTnXHCYmw3Y+QWWTfmQh54Tm9NLQhY13lp92GJ6sm2T2WzbQxSXQl281FgOykGzbS5zIVweo2DxePNyG3M+fI/kC+bCZOdcZKVI0TQNe/fuRVdXV59elFmzZmUnygyxSCls+ZgHo/E2ChmNQmqJwz8gS6wuUnozJtu+3j3Z9s0+9+Wi2daaXAhjOcjjNaba5knBko/fI1ZhLkx2zsWwtiBv2rQJxx9/PDweD3bs2IGVK1cimUwiFovB4/EgHo+jrKwMP/7xj0ctcKJ8YDbeFkNqmlGwjLGdQoc0265fA239Gsj21r7NtvMroVbVFkizrYSMRSBjEaTH8Hu6r7DY/msjsocBi5SWlha89NJLuPHGG/HYY4/hnHPOwVlnnYUbbrgBv/jFL/Dss8/CVWBDkogOR6gqECga0zuFlPLxcJ1zMZxnXQh9x1tI9m62bayD1ljXq9n2FIiiEqtDzoJ+xvD7AsbrgYhGzYDfYZqmYfr06QCA/fv344wzzuhz//Lly/Hd734X55xzzuhGSJSn+t0pFIsaV1rGQMEiFAWO40+C4/iTICNd0F4zm23lvj1IPPsYEs//GY7Z84xm2xPm5n1TaiakngLCIchwqHt3UIC7g4hGyYBFygsvvIBrr70WAOD1ehGLxeDz+VBSUoI9e/YgEAggHh87l7uJBiOEMJYBPF6jYIlFu5cKxsYBiMJnTLZ11pyF1O73+jTbpra8jtSW13PebJsL6asrqtP49/f6eXWFKIsG/G666aab8M477wAAFixYgDfeeANVVVVYtmwZ7rrrLjgcDixatChngRLZhRDCmGrq9UHqurFTKBE3/kzmrvHWKo6pR8ExdYDJtv98Hsl/Pg9lxkyoS2qgzqssiMm2UksCXUnIrk7jkEOv3zg7iMPiiEZkWFuQd+zYgVgshhNPPBFKjjveubunsBV6HtJFSzRiLA0NcpUln3b3jNTBzbZpbk9GzbZ2zYVweYzdQVksWAr9e2QomAuTnXMx4i3I7e3tcLlc8Pv96dvC4TCSySRKS0uzFmgmWKQUtrGUB6nr3VubI5CJ2CH32/WNeTBS16G/sxXJxjqktrwGaFr6PjHxCDiX1EBdfGizbSHkQrjc3fNXfCPazjyWvkcOh7kw2TkXg72vZ/Sd8r//+79ob2/vc1t7ezt+9atfIRKJYOvWrQiFQiOPlGgMEYoC4fNDqRgPZcIRUIpKIdTC3jEnFAWOmSfCc/VX4Lv1HrguvgrKEdMAwGi2fe4xRH74LcR+//+gvdUMmUpZHHH2yEQcekc75P6PoXe0QSYKf+mPaKQy6vDav38/pk6d2ue2qVOn4r333sMf/vAHeL1ePPzww7j99ttHJUiiQiccDnNrczJhnCdU4KM4hC8A57Iz4Vx2JlK734fWVHdos21RCdTFS+GqPRsoLrU65KyQUgciYchI2DiZ2eszepgKYOcTUbZlVKQEAgHs378fEyZMSN+2f/9+VFRU4Ctf+QqSySRuvPHGUQuSaCwRTpcxPM3vh9LeZhQssaix9bVAOaZOh2Pq1b2abY3JtjLUgeTLq9D+8iooR880JtvOW1IwW36lloAMJYBQ0Ph397BgIeoto56U559/Hhs2bMBFF12E8ePHo6WlBU8//TQWL16M8847D6lUCuFwGMXFo39CKntSChvzYDo4FzIRN5pto5GCLlh6GM22r0JbX99/s21lLZTphTDZ9lCDFSz8HjExFyY752LEjbO6ruPFF1/EmjVr0NbWhvLycixbtgxnnXUWd/dkiZ1fYNnEPJgGy4VMJIxx7bEoZErr92MKhdR1OD94F131Lw6p2bZQGAceersPPHTwe6QX5sJk51zwFGQbsPMLLJuYB1OmuUj3sBTwFZae3T0y0gXt9XXQGuug7/nA/ADFUXCTbQ8lINxu+CvGI5LS8+bAQyvx54XJzrkY1gGDB8uXU5CJqK+eHhZZVGJMuo2E+93SXAj6b7ZdB0TDhzTbqpU1UCZMtjrkLJKQ8Rj09lbo0SgPPKQxIaMrKfl0CjKvpBQ25sE0klxITYOMho1dJAVwdWWwOSkymUBqy+tINhrNtr0VYrPtwbkQQjGGxXn9EC77T+8dCv68MNk5FyO+ksJTkInsRaiq0aNRVGKcL5PBhFu7Ek4X1AUnQ11w8iHNtvqu7Ujs2o7E03+COq97sm2BNdv22dLsUCF8fsDrL9AlLxprMp6TwlOQiexJ9Bx8qKeMRttYFDIeRyEWLEr5eLjOuQjOsy7oO9k2HjOWhprqCrrZVqY0yFAHEOow/t29fmMsP5FNZVSk8BRkIvsTigPwBSB8AWMkfzwGGY8ZfxbAklBvPZNtHTNPNJttm+qhf/R+erJtYtWfC7rZNn1Cs+IAfH6e0Ey2lNErlqcgExUWoSjpk5qBXjNY4jHjRN8CMrabbWEUoF2dxgnNLk/3+UFe7g4iWxjWFuTt27cjHo/zFOQssnPTUzYxDyarcpGPTbfZPmDQaLbdiGRTHfQdbwG9diwqRx0Htao2b5tts5ELIRSjUPEFIGzcW8ifFyY754JzUmzAzi+wbGIeTFbnQkpp9LBEuiAT1i7tjuYpyHrbAWjr1/Q/2XZepXF15ahj86bZNtu5EKoLwt/dbJsnX2OmrP4eySd2zsWwipR77rkH3/jGNwAAP/nJTwZ88d5yyy3ZiTJDLFIKG/NgyqdcyGQCMhK27Ayh0SxSekhdN5ptm+qRemND38m2EyYbW5kXnQLF4oMORysXQnGklwCF0x5XV/Lpe8Rqds7FsLYgV1dXp/+/pqYm+1ERkW0IpwuixAWUlEHGY90j+Qur4XbQZtv9HyP53ONIrvozHLPmQa2shWNWYTXbSj0FhEOQ4VD36cxebmUmy3G5J0/YuQrOJubBlO+5kFIajbY9DbejWLDk4krKQFK734e2vh7aaw1A1Pz3sKrZNte5EC53d7OtL++abfP9eySX7JyLYS33rFmzJqNPvmzZssN+TFtbGx544AF0dHRACIHa2lqceeaZCIfDWLlyJVpbW1FRUYHrrrsOfr9/0M/FIqWwMQ8mO+UiXbDEo6NyhcXKIqVHz2RbrWkNUjvetKzZ1rpcCGMUv9cPuD150b9ip++R0WbnXAxruWfdunUZffJMihRFUfDpT38a06dPRywWw+23347Zs2dj7dq1mDVrFpYvX47Vq1dj9erVuOyyyzJ6XiLKH0IIY7eIxwtZLCGiYchwV0FtZ+472fYAtA3dk23bDkB/bwcS7+0wJ9vmWbNtdkhz9opQIL1eCI8vL3dAUeEYsEi56aabsvYkpaWlKC0tBQB4PB5MnjwZwWAQzc3N6eeprq7GXXfdxSKFyOaEEObQuFjUKFYK7MBDpXwcXGdfCOeZn4L+zjYkm+qMZtvek20nTIbaPdnW6mbbbOszit+GDbdkH0MePyil7HMK8lDnpBw4cAAffvghjj76aHR2dqaLl9LSUoRCoX4fU1dXh7q6OgDAihUrDrskZEcOh6Mgv66hYh5MBZELvx+oGAeZTELGo0bTbTw25In8ikOBr3vwXN6ZtxiYtxh6pAvx9WsQW/sytA93Gc22zz+O5Oo/w3XSQnhO+QRcJ86HcIxs6mte5qK76RaqCiWH020L4nskSwo1Fxm9itrb2/Hwww9jx44diET6roX+9re/zfjJYrEYfv3rX+OKK66A15v5eRK1tbWora1N/92u626DsfN6YjYxD6aCy4VwAB4/pNsH9Ey4zXBLcz70pByWUIDKWrgra6F+9D60JrPZNrF5AxKbN0AUFUNd1N1sO/GIYT1N3uci1Amgu+HW4zNOaFZGZ4dQwX2PjICdc1FSMvAZWhkVKX/84x/hcrnwrW99C3fddRduvvlmPPPMM5gzZ07GQWiahl//+teoqqrCwoULAQDFxcUIBoMoLS1FMBhEUVFRxp+PiOxJCGE0Xro9kMWlEPEYZDQMGYuhUA49dEyZDsfF0+E6/3KktmyE1lSP1I43IUOdSL6yGslXVhvNtpU1UOdXFmRfh0zEjSGAncHuww59POyQhiyjtZqdO3fimmuuwbRp0wAARx55JK655hq8+OKLGT2JlBJ/+MMfMHnyZJx99tnp2+fNm4eGhgYAQENDA+bPnz/E8InIzoQQEB4vlLJxUCZOhlJcBqE6rQ4ra4xm2yp4rrsJ3u+tgPOciyHKxwGA0Wz7+AOI3PYNxB/7HVK7dvRZSi8cEjIWgd5+APq+PdA7OwqqoZpGV0ZXUhRFSfee+Hw+hEIheDwetLe3Z/Qk77zzDtatW4cpU6bgtttuAwBccsklWL58OVauXIk1a9agvLwc119//TC/DCKyO6E4AH8Awh8welciYWNJqECurgzebFsPrakeYvwkqJW1BdlsC/QMjOuEDHeaA+M8Pp7OTAPKaJjbvffei6VLl2LhwoV46KGHsG/fPrhcLiQSiazuAsoE56QUNubBxFwAMpWCjHTBC4lIV/+N9XYmI2FoG9dBa6qDvvt98w5F6Z5sW9M92dZ8E8/7npRhMAoWn7FLaAgTbvk9YrJzLkZ8wGAkEoGUEn6/H4lEAi+88AJisRjOPPPM9O6cXGGRUtiYBxNzYfL7/ehqPWAcdhgvrO3MPVIHNdv2OLjZthCLlN6Eu3tgnMd72Dkz/B4x2TkXIy5SQqFQ3jS1skgpbMyDibkw9c6F1DTISBcQjRTU2UE9jMm2ZrNt38m2x8K39Ezos+cVfBOqEIqxM8gbgHD1P3+F3yMmO+diWBNne/vOd76DmTNnoqqqCgsWLIDb7c5qgEREmRKqClFcCllUYuwMKrCrKz3NtuqCKujtrdDWr+k12fYddL33DuByQ51fCbWytgAn2xr6DIxTnd3LQTzwcKzJ+ErKhg0b0NTUhA8//BBz585FVVUVTjrpJDhy/ILhlZTCxjyYmAvT4XIhUykgaryhyZSWw8hyQ+p6r2bb14Beu2MKvdn2YMLlSfevBAIBfo90s/PPixEv9/TW2tqKpqYmNDY2oqOjA3fffXdWgswUi5TCxjyYmAvTUHIhE3HIaBiIRo3fxguMR+oIrX0ZWlM99N3vmXcM0mxbiIRQ4KuoQFQKCBev7tv558WIl3t66+zsRGdnJ7q6uuDz5dloZiIa84TLDeFyGwcdxqLG1ZUCOjtI8QXgXHoGnEvPQGrPB93NtmuBSBipNzci9ebGrEy2zXdS6pDhMPRoxCjIvL6cjeOn3MnoSsqePXvQ1NSEpqYmJJNJLF68GJWVlTj66KNzEWMfvJJS2JgHE3NhGmku0stB0YjtB4n1t7tHJhNIvdkMrbGu32ZbtbIG6rzKgmu27S8XwuU2loM8ozeOPx/Z+efFiJd7brjhBixcuBCVlZU44YQT0k1auq4P+YDBkWKRUtiYBxNzYcpmLmQiYTTbRiOw46C4w21B1ttboW1YA63JaLZNc7mhzquEWlU4zbaD50JAuLvPD/J4IXL8XpVrdv55MeIiRdM0qL0uoe3evRsNDQ1obGzEXXfdlb1IM8AipbAxDybmwjQauZB6CjLcZewgsdFW5kznpEhdh75zG5JN9Uht3lCQzbaZz4wREB4PhNtbsAWLnX9eZKVxNhQKobGxEQ0NDfjwww9x3HHH4fTTT8fixYuzGuzhsEgpbMyDibkwjWYupJTGacw26V0ZzjA3GQlDa26E1lhXUM22wxtsJ7pPaO4uWApkS7Odf14Mu3FW0zRs2rQJa9euxZtvvokJEyagsrISra2tuO6661BcXDwqARMR5YoQorvp0tfduxKBjEUgkwmrQ8sa4fPDecon4DzlE2O62dYgIRMxoyDtbDdH8vt8Y6qHxS4GLVJuvPFGKIqCU045BRdccAGmT58OAHjllVdyERsRUU4JhwMIFEEEiiC1pNG3Eo0U1OwVxxHT4Ljos3Cdf3n3ZNs6pLa/CRnqRPKV1Ui+shrK9GOhVhVms+3BpJaADCWAUAeExwvh80O4PVaHRd0GLVKmTp2Kd955B++++y4mTJiAcePGwe/35yo2IiLLCNUJUVQCFJUYzbbRsLEsZKP+lcEI1WlMrZ1feUizrf7+O0i8/w4STz9sNNtW1kA5+riCaLYdmDSuoMW6tzR7fEbRMsBIfsqNw/aktLa2oqGhAQ0NDWhra8Ps2bOxfft2/PCHP0RZWVmu4kxjT0phYx5MzIUpn3IhY1HIaBgyFoMVu4NG84DBdLNtYx1Sb2wANPMKktFsWwN18dK8abbNxWGLQnEAPU23bk/eFmr59D0yVFmbOLtjxw40NDRgw4YNcDgcWLp0KS677LKsBZoJFimFjXkwMRemfMyF1FNAJGIULDmcvZKrU5AHbbY9YS7UqlrLm21zfSK0EArgdhvLQe78arrNx++RTGV1LD4AJJNJvP7661i3bh1uuOGGEQc4FCxSChvzYGIuTPmeCxmPQYZDOTnoMNdvzAAOabbtYXWzrRW56E2oLuPqSh4sC+X798hgsl6kWIlFSmFjHkzMhckuuZBaErIrNKqD4qx8Y5ZaEqk3NxqTbbcfNNnWgmZbq4uU3qxeFrLL90h/snp2DxER9U+oTojScsiiEsiI/QbFHY5QnUYj7bzezbZrINtaxmizrclY/jNO4jan3XrzblnIbnglJU/YuQrOJubBxFyY7JwLGY8ZZwZl6epKPl09AA5utn2tn8m2gzfbals3I/nyKuhtB6CUj4Pz9HOhzpqb0XPnWy4GIpwuc3ic6hyV57Dz9wiXe2zAzi+wbGIeTMyFqRByIXUdiEWMybYjGBSXz2/MMhqGtrERWlM99A93mXf0NNtW1sAxe1662VbbuhnxJx8CVBVwuoBkAtA0uC+5OqNCJZ9zMRChOo2rK14vhDN7fSx2/h7hcg8RkcWEogC+AIQvAJlMGMsCBTR3BQCEd5DJtm81I/VWMxAohnPxKVAra5F8eRWgqhAut/EJXG5IAMmXV2V8NcVupJYEtCRkuLNvH4vLXZBnCo0UixQiohwTThdEiQuyuBQi2r2NORG3Oqys6jPZ9s2N0JrqkXp7C9DVieQrf0Pylb8BDhUoKoZUneYbtNMFvffpzQXskD4WV/f2Zo9n1JaF7IZFChGRRYQQgM8P4fObV1eiEUipj/pzj6QXZCgObbZ9tXuybQuQ0oBgG9DRDun1A/4AAEApH5dR7NH2VqCsYtRiz61eZwqF0D311msULS73mGlAPhivLRER5QHhdEEpKYOYMNn4cxR/k+7pBdFDHYDPDz3UgfiTD0HbunnUnhMAlLIKuM66AN7v/gSer3wbyrGzjDukBCJdQMteoLUFonwc9M7gYWMXvkDOYs81mdIgwyHobS2Q+/ZAb281GrD10S9g8wmvpBAR5ZE+vSujNCTO6l4QoShwHDsL3mNnIdnchOTqv0C2txpXVvQUUuvXIPraWjhOmAO1srZPs23v2IUwlkgKvo9FdjddxyLouyzkhVAL+228sL86IiIbE24PhNtjDIkLh4BoNCufV287APgOOizWol4Q5/xKOOdXGnHt+RDJpjporzUAkS6k3tqE1Fub+jTb5lPs1ui9LBRMT72VzsJ8Oy/Mr4qIqIAI1QlRUg5ZpEMREiKRgExph3/gAJTyccZST8+VFABIJg7bCzLalCOOhPtwzbZur7E7pqgEcCh5E7tVpJYAtARSugY9Hge8fgifr2Aab1mkEBHZhFAUKH4/FOEwTmMOdxm/UQ+R8/RzEX/yIWO0XK/5JM7Tz816zMPRb7Pt+nrI1hYgHjX+C3Ui5fNDutyAEHkTu5WkngLCncb2ZqcLwusHvF5jq7NNsUghIrIh4fFCeLzGrqBw15Am2qqz5gKXXJ2T3T0j1dNs6zzjfOjvvo1kUx1SzU1AKtV99EAXREkZ9D0fQJ8ybcDJtmONTCaMoYGdQWNEv9dv9LDYbJcQJ87mCTtPC8wm5sHEXJiYC9NAuZCpFGTYeNPOxRZmK/VMttXXvwrtg53mHYrSb7PtWJDJ9N308Div32yazgOcOEtEVOCEwwFRXAIZKIKIhI1dQQU0zba3nsm2vjPOR9fOtwdstlUXnQJnVS2UiUdYHXJe6D08TigOY/5Kz/C4PF0S4pWUPMHfFA3Mg4m5MDEXpkxzIaUEomFjKajXoX+FpPfVA6klkXqzGVpTndFsK823NmX6MVAra6HOrzQO+itAIz3HyNgl5DausLhcOS1aeCWFiGiMMabZds9biXYfbDiMJlu7MJptl0Cdt+SQZlv9/Z1IvL8Tib/+yWjIrayBcvRM2/VnjKaeXUIyHALQXbS4XEbR4nZbdqWFRQoRUYETXh+E1wepaZDRsHHJv0CXgoABmm03bQASCWjr10BbvwZi3ESolTVQlyxjs20/0kVLpAtA9+nNru4rLW5Pzg5D5HJPnuDlbAPzYGIuTMyFKVu5kPGYcXUlFkWmu4LyzVCWOGQ0Am3jOmhN9dA/3GXe0bvZdtY8205wHelyz9AIY8eQx2fsGBphwWL5cs+DDz6IzZs3o6ioCLfddhsAIBwOY+XKlWhtbUVFRQWuu+46+P3+w3wmosKRbG5E4rnHobfshTJ+ElznXw7n/CqrwyKL5ep1kZ5mq6eAaNQoWLRE1p8nXwivD85TPgHnKZ+A/vGHSDbVQ9uw9qBm2yKoi5bCWVkDZdIUq0POiDWHLUqjyI3HgA4B4fGYBcsQltB6XuslK+4f8GNyciVl+/btcLvdeOCBB9JFyp///Gf4/X4sX74cq1evRjgcxmWXXXbYz8UrKYVtrOQh2dyI2IP3At2XUJGIA1oSnmu+nn5DGiu5yMRYyYXVrwuZSEBGuyAjmc9csdJIrx5ITes12faNvs2202ZAraqFOr8qb5ttew5bhKrC4fIglYgBmgb3JVdbMvNGCMUYHpfBFufer/Wp9z054Pt6ThaVZs6cechVkubmZlRXVwMAqqur0dzcnItQiPJC4rnHAdVp/DYrhLENUHUat9OYZfXrQrhcUErKoUw8AkpRacGMVh+IUFWo85bA86Vvwfv9n8G5/BKIivEAAP2Dd5F44kFEbrsB8UfuQ2rn28aOqTzS32GLUFXjdgtIqUNGwtBb90Pf/zH0zg5joFw/er/WB2PZ4ltnZydKS0sBAKWlpQiFQgN+bF1dHerq6gAAK1asKMhlIYfDUZBf11CNlTyED+yDI1Dc59Ko9HghD+xLf/1jJReZGCu5yKvXRVGR8fzxGPSuUHfvSn5RHAp8Xl92PpnXB3zqM5DnXY7kO1sRW/sy4hvXGc22G16FtuFVOMZPgqf6dLhPPhWO0vLsPO8IRNtb4fAFjNeLABxQIF0eyPbW7OVlJHQNCIcAVYXi9RsN3E6j8O3vtd4fW3QI1dbWora2Nv33QrzsO5YuZw+23p7NPOR1z8e4idD27gYiYUBLGpf3fX44Jk1Nf/1j5TWRiTGTi3ETkQq29fntUsZjUMZNtPZ14fFBOt3dY+jzZ2fQqDWLHnk01CuOhuOCz0BrboTWWAf9w11ItexF+JlHEH72UThOmAu1yuJm27IKpEIdEC43HFCQkjpkIg6lrCKHTbQZCnUC6N4l5PZClo+H3hk87JWU3Owh6kdxcTGCwSAAIBgMoqi7aqfC1bMGqQfbAH8R9GAbYg/ei2Rzo62faziU2fOAYDuQTAJCMf4Mthu305jlOv9y44TfeAxSGs2J0JLG7RYTDgeUohKICZOhlI2DcA3+5lIIhNcHZ/Xp8H7jVnhvuh1q7TmAvwiQEqmtmxB/8F5Ebv8m4s88Cn3vRzmPz3n6uYCmQSbixuslEc+rgyL7I7UkZLgTzmVnQsai0CODF9yWFSnz5s1DQ0MDAKChoQHz58+3KhTKkVyut1u9tn84+lubgNJywOkEpG78WVpu3E5jlnN+FTzXfB1KaTkQDkEpLe/TNJsPhBAQHi+UivFQxk+G8Bfn7Uj1bFImHwn3hVfC9993w/35/4DjhLmAEEBXCNq//oboiv8P0f93O5LrXsnZ0pg6ay7cl1wNpagEMtIFpajEsqbZoUrHHhj8AkVOrlH99re/xfbt29HV1YWbb74ZF1xwAZYvX46VK1dizZo1KC8vx/XXX5+LUMhCeste47eQ3lxu43YbP9dw6C17IYpLIUrK0rdJKfMmPrKOc35VXhUlgxGqapwXVFQMEY9BRrqMqz8FTKgq1LlLoM5dAj3YZvSrNNVDtu7vNdn2YeNjKmuhzBjdybbqrLlQZ83N8ZyU7OiJfdCPyUUgX/7yl/u9/cYbb8zF01OeUMZPMpZfeq9BJuJQxk+y9XMNR77HRzQUQghjRobHa1zOj3RPtS3w05iV0nK4zvwUnJ84D/q7b0Nrqoe2eUOfZtv0ZNvFS6H0+qWEMmPZcg+NPblcb8/ntX0g/+MjGi6hOqEUl0JMPAJKSZlxBkyBE4oCx7Gz4P63L8N36z1wXfZ5KNNmAADkgX1Irvozord/C7H7fw5t8wZITbM4YvvgWPw8MVZ2L3B3jymXubA75sJkx1zIhHEGjIxmd0hcvi9xGJNt10B7ba2xFbdHoAjqolPgrKzN2mTbfM/FYMpPOGnA93UWKXnCjj94RgPzYGIuTMyFyc65kHrKWAaKhCFTI7+aYJc3ZqlpSL3VPdl22+hMtrVLLvozWJFiizkpRERkf0JxAIFiiEAxZCw6JhptgYOabTvajZOYe5ptP3gXiQ/eReLph6HOy02zrZ2wSCEiopwT6UZbzRgSF43kzZC40aSUlBnNtmecbzbbbloPJNls2x8u9+QJO1/CzSbmwcRcmJgLU6HmQkppFCrRCGQis6srdl7i6E1GI9Cam6A11UH/4F3zDiHgOGEO1MoaOGYvGHSyrZ1zweUeIiLKa0IIwOeH8Pm7tzFHgGj+jOAfTcZk29PgrD4N+se7kWyqTzfbprZuRmrrZsDf3Wxblb1mWzvglZQ8Uai/HQ0V82BiLkzMhWms5ULGY8auoFj0kLkrdr56cDjpZtvGeqTe7qfZtrIW6gKz2dbOueCVFCIiykuH24ov3B4ItwdSSmOqbTSclycyZ1tGzbZ/7Wm2rYE8cYHVIY8KXknJE2Ptt6OBMA8m5sLEXJgKKRc9B4FCdQIuN5CIA1rysOcVSU2DDIfghY5IxJ5XD4ZDSgn93e3QmurSzbY9HOMnQVm8FOqSZbZrtuWVFCIiyju9DwIFALg9kN23D1akCFWFKCmDw+OBaNlnzF4ZC70rQsBxzPFwHHM8XBdfBW1jY7rZNtWyF6nVf0Hyb09m3GxrB/aOnoiIbGukB4EKh8M4AThQDBEJQ4ZDWRkSZwfC4+3TbIvXGxBtrOu/2bayBsrkqVaHPCwsUoiIyBLZOmhTCAH4A8buoGgEMtwFqSUO/8ACoUyeCt9ln4c45+K+k23DIWh1f4dW93ez2XZ+JYTXZ3XIGWORQkREWTHU87Jc51+O2IP3Gqf59OpJGe5Bm322MceiRrGS4cyVQnBws21i1V+Qam4EtGS/zbbKjOPzfrItixQiIhqxPk2w/iLowTbj79dgwELFOb8KuAajchBoeqJtMgHZFereEWSrfSIjou/5EKl33wbKKozty12dQCx66GTbJcvyutmWRQoREY3YcJtgnfOrRvV0cuF0QZRVQKZSkOGQ0WR70LyVQpR8eRWgqhAut3GDxwsZi0IIAeH1Qf/gXcgD+5DM82bb/ImEiIhsa6RNsKNNOBwQxaXdTbZdxlJQAe8I0tsOAD5/3xvdHshIGL4b/hv63o+QbKqDtmGAybZ50mzLIoWIiEYsW02wvQ21xyUTQlGAQDHgL8poR5C2dTOSL6+C3nYASvk4OE8/F+qsuSOKIReU8nHQQx1Gr0+PZAJK+Tjj/klT4L7gSrjO/TRSbzVDa6oboNm2Bur8KsuabRVLnpWIiAqK6/zLAS1pjLGXEjIeG1ETbE+Pix5s69PjkmxuzEq8QggIfwBi/CQopRUQTtchH6Nt3Yz4kw8Zb/Y+P/RQB+JPPgRt6+asxDCanKefC2gaZCJu/Hsk4oCmGbf3YjTbLobni9+C979+Due5l0GMmwgARrPtn/+AyG3fQPzh3yK1c5txEGQO8UoKERGNWLabYIfb4zJUQgjA64Pw+ow39HAoPXb/kL4Olxuy+/Z8v5qizpoLXHL1kK4CKSVlcJ1xPpyfOM+cbLt5PZBIQHttLbTX1kJUTDCuruSo2ZZFChERZUU2m2Ct6HERLjeEy22M3Y90QW8/AHgP6utwuox+DxtQZ80dVjF1yGTb5kZojcZkW9m6P6fNtixSiIgo74xGj0umhKpCFJdCmTgF+se7ISNdQEoDHCrg9UHpXg4ZC4THC+fJp8F58mlms+1ra4Gu3DTbsieFiIjyTrZ7XIbDceJ8oDMIpFKAUABNAzo7oBx7Qs5iyCc9zba+/7ob7mu+DseseYAQ6Wbb6F3fR/Se25BseBkymp2DH3klhYiI8s5oDnrLlP7WJqC0DIiEAS0JuFyA1wd91w4IoYyJeSv9EaoKdc4iqHMWQe9oh7Z+DbT1ayAP7IP+4S4kPtyFxF8fgWPuIjgra6Ecc8KwJ9uySCEiorw02oPeDkdv2QtRXAZRUp6+TUoJ2d4KMWFy9zlBY+dQw/4oJWVwnfkpOM84/5Bm29RrDUi91tDdbLsM6pKaITfbskghIiLqx2B9MUJReh1qGIYMdRb0cLjD6bfZtqke+vs7u5ttn0Tyb0/BcfwcqFWZN9uySCEiIupHJgcgGocaBgCv3xgO1zW2ixWgv2bbemivvWo0227bjNS2nmbbajgra4ETThr4cwWDQVuduFRSUoKOjg6rw8g6v9+PcDhsdRiWYx5MzIWJuTAxF6Zc5GKoU2+llEC4y1gGymGx4vP6EMlSs+pokJqG1NZN0BrrjCKl11C4I5/fMOD7Oq+kEBERDWCofTFCCCBQBPgDEBYUK/nqkGbbDa9Ca6qHPLBv0MexSCEiIsoyFisDO3iy7WBYpBAREY0SFisD62m2HQyLFCIiolHWp1hhg23GWKQQERHliBDC3LrMYuWwWKQQERHlGIuVzFhepGzZsgWPPvoodF1HTU0Nli9fbnVIREREOdGnWGHPyiEsPWBQ13U8/PDDuOGGG/DDH/4QTU1N2LNnj5UhERER5ZwQAiJQBDFhMpSiUgjFYXVIecHSImXXrl0YP348xo8fD1VVsWTJEjQ3N1sZEhERkWXSxcr4SVCKSsZ8sWJpkRIMBlFebh7cVFZWhmAwaF1AREREeUAoCkSgeMwXK5b2pEiZ2UT+uro61NXVAQBWrFgBv98/mmFZwuFwFOTXNVTMg4m5MDEXJubCNGZyUVQEqeuQ4RD0rhCg64d8iOJQ4PP6LAhudFlapJSVlaGtrS399/b2dpSWlh7ycbW1taitrU3/vRDPreB5HAbmwcRcmJgLE3NhGnO5UFTIQAkQ6YIMd/VpsM33s3sG4xnkPkuXe4466ijs378fLS0t0DQN69evx7x586wMiYiIKG+ll4EmTIZSUgahuqwOaVRZeiXF4XDg3/7t33DPPfdASomlS5diypQpVoZERESU94QQgC8A4QtAJuIQegqw6ZWUwVg+J2XOnDmYM2eO1WEQERHZknC54fD7oTjdkOEuIBoumFkrlhcpRERENHLC4YAoLoEsKoaIhiHDYUgtYXVYI8IihYiIqID0WQqKxyAjXZCxqNVhDQuLFCIiogIl3B4ItwdS0yAjXUA0YqulIBYpREREBU6oKkRxKWRRSfdSUBeklrQ6rMNikUJERDRG9FkKikWN05eT+du3wiKFiIhoDBIeL4THa/SthEOQ8ZjVIR2CRQoREdEYlu5bSSQgw5151WTLIoWIiIggXC4I1zhILQnZFYKMWn/kgKVj8YmIiCi/CNUJpbQcyvjJED4/AGFZLCxSiIiI6BBCVaGUlEOZMBnCXwQrihUu9xAREdGAjEm2pZCBIsiuLuMUZqnn5LlZpBAREdFhCaV77H6gCCLSZcxaGeXBcCxSiIiIKGNCUYBAsTFvJRI2ti+PUrHCIoWIiIiGzChWigB/ACLcNSrFCosUIiIiGjYhhFGs+PxAOASEs9ezwt09RERENGJCUaAUlUBMmJS13UAsUoiIiChrhOKAUlwKZfwkCI9vRJ+LRQoRERFlnVBVKGUVUComQDhdw/ocLFKIiIho1AiXG8q4iVBKyiEcQ2uFZeMsERERjTrh80P4/JDRiLETKJk47GNYpBAREVHOCK8PwuuDTMQhw6FBP5ZFChEREeWccLkhXO5BP4Y9KURERJSXWKQQERFRXmKRQkRERHmJRQoRERHlJRYpRERElJdYpBAREVFeYpFCREREeYlFChEREeUlFilERESUl1ikEBERUV5ikUJERER5iUUKERER5SUWKURERJSXWKQQERFRXhLBYFBaHcRQlJSUWB0CERERZVFHR0e/t6s5jmPEBvpC7O6OO+7A97//favDsBzzYGIuTMyFibkwMRemQs0Fl3uIiIgoL7FIISIiorzEIiVP1NbWWh1CXmAeTMyFibkwMRcm5sJUqLmwXeMsERERjQ28kkJERER5yXa7ewrJ3r17sXLlyvTfDxw4gAsvvBBnnnmmhVFZ58UXX0R9fT2EEJgyZQquvfZaOJ1Oq8OyxEsvvYT6+npIKVFbWzumXhMPPvggNm/ejKKiItx2220AgHA4jJUrV6K1tRUVFRW47rrr4Pf7LY509PWXiw0bNuCZZ57B3r178b3vfQ9HHXWUtUHmSH+5eOKJJ7B582Y4HA6MHz8e1157LXw+n8WRjr7+cvH000+jubkZQggUFxfj2muvRWlpqbWBZgGvpFho0qRJuPXWW3Hrrbfiv/7rv+ByubBgwQKrw7JEe3s7/vGPf+D73/8+brvtNui6jqamJqvDssRHH32E+vp6fO9738Ott96KzZs3Y9++fVaHlTOnnHIKbrjhhj63rV69GrNmzcKdd96JWbNmYfXq1RZFl1v95WLKlCn46le/iuOOO86iqKzRXy5mz56NH/zgB/jBD36AiRMnYtWqVRZFl1v95eKcc87BD37wA9x6662YO3cunn32WYuiyy4WKXli69atGD9+PCoqKqwOxTK6riOZTCKVSiGRSBTEbwHD8fHHH2PGjBlwu91wOByYOXMmNm7caHVYOTNz5sxDrpI0NzejuroaAFBdXY3m5mYLIsu9/nIxefJkTJo0yaKIrNNfLk488UQ4HA4AwIwZM9De3m5FaDnXXy68Xm/6/+PxOIQQuQ5rVHC5J0+sX78elZWVVodhmbKyMpx99tn49re/DafTidmzZ+PEE0+0OixLTJkyBU899RS6urrgdDrxxhtvYPr06VaHZanOzs500VpaWopQKGRtQJR3Xn31VSxZssTqMCz11FNPoaGhAV6vFzfddJPV4WQFr6TkAU3TsGnTJixevNjqUCwTDofR3NyMH//4x1ixYgUSiQTWrVtndViWmDx5Mj75yU/i7rvvxi9+8QtMnTo1/dsiER3q+eefh6IoqKqqsjoUS1188cX46U9/iqqqKvzzn/+0OpysYJGSB7Zs2YJp06ahuLjY6lAss3XrVowbNw5FRUVQVRULFizAzp07rQ7LMjU1Nfiv//ov3HLLLfD7/ZgwYYLVIVmquLgYwWAQABAMBlFUVGRtQJQ31q5di82bN+OLX/xiwSxxjFRVVRVef/11q8PIChYpeaCpqWlML/UAQHl5Od59913E43FIKbFt27Yxue7eo7OzEwDQ2tqKjRs3jvnXx7x589DQ0AAAaGhowPz5860NiPLCli1b8Le//Q1f+9rX4Ha7rQ7HUr2b65ubmwvm5yeHuVksHo/j29/+Nn70ox+Nia1zg/nrX/+KDRs2QFEUTJs2DZ/73OfG7Bbkn/zkJwiHw3A4HLj88ssxa9Ysq0PKmd/+9rfYvn07urq6UFRUhAsuuAALFizAypUr0dbWhvLyclx//fVjYgtyf7nw+/145JFH0NXVBa/XiyOPPBLf/OY3rQ511PWXi9WrV0PTtPRrYcaMGbj66qstjnT09ZeLLVu2YO/evRBCoKKiAldddRXKysqsDnXEWKQQERFRXuJyDxEREeUlFilERESUl1ikEBERUV5ikUJERER5iUUKERER5SUWKURUkJ555hncf//9VocxJA888ACeeuqpEX+eV199Fd/61rewdetW/O///i+i0WgWoiPKPZ7dQ5Sh73znO+js7ISiKFAUBUcccQROPvlk1NbWQlFY749UKpXC7373O2zZsgXHHHMMrrvuOng8HgDG2HOXy4WzzjrL4ijt4e2338Z3v/tdPP744ygqKupz+ByRnbBIIRqCr33ta5g9ezYikQi2b9+ORx99FLt27cK1115rdWjDkkql8uZcoJ4x3nfffTfuv/9+/Otf/8I555yDlpYWbNq0Cd/+9rctjtA+/v3f/x0A8B//8R8WR0I0MixSiIbB5/Nh/vz5KCkpwY9//GOcffbZmDJlCpLJJJ5++mls2LAByWQSCxYswBVXXAGXy4VQKITf//73eOeddyCEwBFHHIGbb74ZiqIgGAzikUcewfbt2+F2u3HWWWfhjDPOAGAsW+zZsweqqqK5uRnjxo3D9ddfj9dffx0vvfQSVFXF5z//+fSp0StWrMAxxxyDrVu3Yt++fZg5cyauvfZa+P1+HDhwAN/97nfxuc99Ds899xwqKipwyy23YM2aNfj73/+Ozs5OHHXUUfjc5z6HiooKAMCbb76JRx55BJ2dnaiqqsKePXtw8skno6amBrquY9WqVaivr0cymcSJJ56IK6+8cljTkw8cOIDjjz8eDocDxx9/PD766CMAwKOPPopPf/rThy2mWlpa8OCDD+L999/HjBkzDhkL/pvf/AY7duxAMpnE1KlT8dnPfhZTpkzp93MNlkPAGDv+5JNPIhgM4sgjj8RVV12FyZMnAzCuuNXW1mLdunXo6OjA/PnzcdVVV8HpdOLVV1/FmjVr+hRcX/rSl3DnnXcecj5TOBzG7373O+zatQu6ruOYY47BVVddhfLy8vT9jz/+ON58800kk0nMnDkT//Ef/3HYxwWDQfzxj3/Ejh074Pf78clPfhK1tbWZ/jMR5RSvURONwNFHH42ysjLs2LEDAPCXv/wF+/btw3//93/jRz/6EYLBIJ577jkAwIsvvoiysjL8/Oc/x89+9jNcfPHFEEJA13Xce++9mDp1KlasWIEbb7wRL730ErZs2ZJ+nk2bNuHkk0/GL37xCxx55JG45557IKXET3/6U5x//vl46KGH+sTV0NCAa665BitWrIDD4cAjjzzS5/7t27fjhz/8Ib7xjW9g48aNWLVqFb761a/i5z//OY477jjcd999AIBQKITf/OY3uOSSS3D33Xdj4sSJfQ5+XLt2LdauXYubbroJP/rRjxCPxw95rkxNmTIF27Ztg6ZpePvtt3HEEUfg9ddfRyAQwHHHHXfYx99///2YNm0a7r77bpx//vlYu3Ztn/tPOukk3HnnnfjZz36GadOmHbZfZaAc7t27F/fddx8+85nP4Oc//znmzJmDe++9F5qmpR/b2NiIb3zjG/jRj36Effv2pV8DQyGlxNKlS/E///M/+MlPfgKXy9Unt7/73e+QSCRw22234Wc/+xnOPPPMjB533333oaysDHfddReuv/56PPXUU9i6deuQ4yPKBRYpRCNUUlKCcDgMKSXq6+tx+eWXw+/3w+Px4Nxzz0VTUxMAwOFwoKOjA21tbVBVFTNnzoQQAu+99x66urrwqU99CqqqYvz48aipqcH69evTz3HcccfhpJNOgsPhwOLFi9HV1YXly5dDVVVUVlaitbUVkUgk/fEnn3wypkyZArfbjQsvvBAbNmyAruvp+y+44AK43W64XC7U1dVh+fLlmDx5MhwOB84991x8+OGHaG1txRtvvIEjjjgCCxcuhMPhwBlnnNHntO7GxkacddZZGD9+PDweDy655BKsX78eqVRqyHmcM2cOxo0bhzvuuANerxdLlizBs88+i0svvRRPPfUUfvrTn+JPf/pTn2KgR2trK9577z1cdNFFcDqdmDlzJubNm9fnY5YtWwaPxwOn04kLLrgAu3fv7pOzgw2Uww0bNmDOnDmYPXs2VFXF2WefjWQy2ad4O/3001FeXg6/34/zzjuvz79lpgKBABYtWgS3251+LW3fvh2AcTVky5YtuOqqq+D3+6GqKo4//vjDPq6trQ07duzApZdeCqfTiWnTpqGmpiZ9eCNRvuFyD9EIBYNB+P1+hEIhJBIJ3HHHHX3u7ykOzjnnHDzzzDO4++67AQC1tbVYvnw5WltbEQwG8Z//+Z99HtP76kHvwsDpdCIQCKSbdXsOYYzFYulllp5L+wBQUVGBVCqFrq6u9G29Dx5rbW3FY489hieeeCJ9m5QS7e3t6Ojo6POxQog+fw8Gg+llod7P1dnZecjhZr/4xS/SV5yuuuoqnHzyyX3uF0Lg0ksvxaWXXgoAeOKJJ3Dqqafi/fffx3vvvYebb74Z//d//4c1a9bgtNNO6/PYYDAIn8/X5yTciooKtLW1pfP51FNP4bXXXkMoFIIQAgDQ1dU14NLUQDk8+GtWFAVlZWVob2/v97Hl5eUIBoP9Psdg4vE4Hn/8cWzZsiVdTMViMei6jvb2dvj9/n4PWRzscT2v1Z6G5J743nvvvSHHR5QLLFKIRmDXrl0IBoM49thjEQgE4HK5cNttt/V7+qjH48Hll1+Oyy+/HB999BF+9rOf4aijjkJ5eTnGjRuHO++8M2tx9bw59/y/w+FAIBBI397zJg0YBcu55557SNEAAPv37+/zBttTvPQoLS1Fa2tr+u+tra1wOBx9iqoeN9xwQ8bxf/TRR9i5cycuvfRS/P3vf8f06dMhhMBRRx2F3bt3H/LxpaWliEQiiMfj6UKltbU1/XU2NjaiubkZ3/zmNzFu3DhEo9HDxjNQDktLS/vE0JOT3v/mBz+2tLQUAOB2u5FIJNL3dXR0DPj8L774Ivbu3Yvvfe97KCkpwQcffIDbb78dUkqUlZUhHA4jEokcUmQN9rjS0lKEw2HEYrF0odI7PqJ8w+UeomGIRqPYtGkT7rvvPlRVVWHq1KlQFAU1NTV47LHH0NnZCQBob29P95Zs2rQJ+/fvh5QSXq83vZX56KOPhsfjwerVq5FIJKDrOj766CPs2rVr2PGtW7cOe/bsQTwex1//+lcsWrRowG3Sp556KlavXp1uVI1EItiwYQMAYwlm9+7d2LhxI1KpFF5++eX01wYAlZWVeOmll9DS0oJYLIannnoKixcvHtGOISklHn74YXzmM5+BoigYN24c3nnnHWiahu3bt2PcuHGHPKaiogLTp0/HM888A03TsGPHDmzevDl9fywWg6qqCAQCSCQSGc0iGSiHixcvxhtvvIGtW7dC0zS88MILUFUVxxxzTPqxr7zyCtra2hAOh7Fq1SosXrwYADB16lTs2bMHH3zwAZLJJJ555pkBnz8Wi8HlcsHn8yEcDuPZZ59N31daWoqTTjoJf/rTnxAOh9O5OdzjysvLccwxx+DJJ59EMpnE7t27sWbNmn4LVKJ8wCspREPwy1/+Ml1cTJ48GWeddRZOPfXU9P2XXnopnn32Wfz4xz9GV1cXSktLcdppp+Gkk07C/v378cgjjyAUCsHn8+G0005L9xF8/etfx+OPP47vfve70DQNEydOxEUXXTTsOKurq/H73/8ee/fuxcyZM/HZz352wI9duHAh4vE47rvvPrS2tsLr9WL27NlYvHgxioqKcP311+ORRx7B73//e1RVVWH69OlQVeNHx9KlSxEMBrFixYo+u3tG4tVXX8URRxyBo446Kh3fxo0b8a1vfQtHH310n3z39qUvfQkPPPAAvvGNb2DGjBmorq5OL3dUV1fjzTffxM033wy/348LL7wQr7zyyqBxDJTDSZMm4Qtf+AIeeeSR9O6er33ta+mcAEbxds899yAYDGL+/Pk477zz0o89//zzcffdd8PpdOKSSy5BXV1dv89/5pln4r777sM3v/lNlJSU4Oyzz0Zzc3P6/i984Qt47LHH8O1vfxvxeBwLFizAzJkzD/u4L33pS/jjH/+Im266CX6/HxdccAFmz549aC6IrCKCwaC0Oggiyp4VK1aktwhnm67ruOWWW/DFL34RJ5xwQtY/f74YSQ6/853v4HOf+1zO3vjj8ThWrlzZp6eJqFBwuYeIBtXTgJlMJrFq1SoAwIwZMyyOigCjQHE4HNi/f3+/u56I7I7LPUQ0qHfffRf3338/NE3DEUccga9+9atwuVxWh0UAtm7divvuuw8nnHBCn+UmokLB5R4iIiLKS1zuISIiorzEIoWIiIjyEosUIiIiykssUoiIiCgvsUghIiKivMQihYiIiPLS/w/IA0c+MotxrAAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<Figure size 648x432 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.style.use('ggplot')\n",
    "fig, ax = plt.subplots(figsize=(9, 6), facecolor=\"#f0f0f0\")\n",
    "ax.set_facecolor(\"#f0f0f0\")\n",
    "sns.regplot(data=serieI, \n",
    "            x='Desemprego',\n",
    "            y='POSITIVA')\n",
    "plt.ylabel('Avaliação positiva')\n",
    "plt.xlabel('Desemprego - % da população')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 114,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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1IPnWKiTfWgVt7ATV7mDeIoj8QquHPWxkMgHZ2gQRaoXkacBERNRPObmclKkTe0eaeeqEOh148zrIxpNdFzQNrqmzoM9fDNesin4tv9h9OelshMen+lT5/Fk3O+OU6V27Ydytw9hbxymxd9RyUrbSRp0Dz1U3wH3l9TAPH4SxeR2Mho1ANILUnu1I7dkO+PzQ51SqdgeTLoLQcrI2GzIRg0zEIDQXZ2eIiKhXnImxOZlMILVnG4z6WpXEdCsIFsWl0OcvVu0OzhnT4/uyfSamN8LjhfAHbV8745TfjOyGcbcOY28dp8SeMzFZSrg90OcsgD5nAWR7G4yGjTA218I88h5kcyOSb76M5JsvQxs/WSU05VUQeflWD3tYyEQcMhHvVjuTZ+tO4kRENLxsNRNjmiYefPBBFBUV4e6770Y4HMaKFSvQ2NiI0tJS3HHHHQgGg2e8R/eZmEw1Vcx0c8ZMMI8fhbGlDsbmWsjmxq4LLhdc0+bAc/5ExPbvgmxuyuiY7RYL4fWpTtpen2VjOJ1TfjOyG8bdOoy9dZwS+6zoYv3666/j/fffRzQaxd13340//OEPCAaDWLp0KVavXo1wOIxly5ad8R6dSUxnU0XoOuD2qB5HhgHvTV8e0A/dTN1nuEjThHloP4z6dTC2bQLisa6LQqh2Bh4vAAHvX/yfIY3ZzrHo7NckAnmWjgNwzoeK3TDu1mHsreOU2Nu+i3VTUxN27NiBiy++OP1aQ0MDqqurAQDV1dVoaGjo9/26N1UUQqjmirquXh+ATN1nuAhNg2vKNHi/8FcI/OMv4P3SnV19mKQEwu1AcyPQ1ozE87+F2Xhi0O9l51hIIwmztRnmyWOQOVYLREREvbNNQcGzzz6LZcuWIRbrmkloa2tDUVERAKCoqAihUKjX712zZg3WrFkDAFi+fDkC/gCizY1wBfJ6FIBKjw+yuREBf6Df48rUfUaEPwAs/jQaVz0PFJUCkXaY4XY1Y5JKQTafQvT/uw/6lKnwVV0Kb8UiaAOYuciaWMSjgGlAKyiC5vOP+Nu7XK6zLntS5jHu1mHsreP02Nsiidm2bRsKCgowYcIE7Nu3b8DfX1NTg5qamvTfI9EIUFyKVKhVzRZ0kIk4tOLSge3aydR9RlJxKRBqg8wrgMgrgEwmgFArEI8DKQPGu/vQ/u4+tD/3JFwzyqFXLoFr2mwI11keh2yKRRRAW6s6DTivAGIEkxmnTO/aDeNuHcbeOk6JfWFh7we+9iuJSaVSePvtt7F//360t7dDyq4ymvvuu2/Ig3v33XfR0NCAHTt2IJlMIhaL4YknnkBBQQFaWlpQVFSElpYW5Of3f9eN+7KrEX/hd5BAj/qNgTZVzNR9RpL7squRfPE/IRNSjVlKwBeA55avQdN1daDejnogkUBqez1S2+uBYD70eVVqu/b5k3rdwpyNsZDJBGTzqXTNDPxBW2/PJiKi/utXYe/TTz+NvXv3oqamBn/84x9xww034H//93+xYMECXHfddRkd0L59+/CnP/0Jd999N37/+98jLy9vUIW9QG7vTjob13t70f7aH/scs4zHYOzYrNodHNytEp0Oomw09MolKqEpLu1x32yMRXdCcwGBIIQ/OGzbs53ym5HdMO7WYeyt45TYD+mcmK1bt+L+++9HaWkpXnrpJVx++eWYOXMm/vM//zPjA+1u6dKlWLFiBdauXYuSkhLceeedA/r+wTRqHM77jCTvzAqkJk/r87rw+uCuXAJ35RKYLU0wtqxX7Q6OfQR58hiSq59HcvXz0KZMU+fPzF0A4fNnZSy6k2YKaG+DbG9TS03+oOqmrbmsHhoREQ1Qv5KYRCKBkhLVVdnj8SAej2PMmDE4cuRIxgc0depUTJ06FQCQl5eHe++9N+PvQT1pRSXwfPpquC9bCvOjI2q5aUsd0N4G8929SLy7F4kXfgfXrApVP3PRTAhX9v/Ql8mEqhdqa4Hw+dTheTY6b4aIiM6sX0nMmDFjcPjwYUyaNAkTJkzAyy+/DJ/Pl945RLlBCAHXuAlwjZsAz7U3I7V/F4z6dUjt3AIYSaQaNiDVsAEivwCuimqV0Jw33uphZ4CEjEUhY1EI3QMRDLJ2hogoC/SrJubQoUPQNA0TJkzA8ePH8V//9V+IxWJYtmwZLrroopEYZ7/lWu+kwcpk7yQZi8LYtkm1O3h3b49rYsw4tdxUUQ2tsDgj72cHQmgdtTOBfnUN784pa9R2w7hbh7G3jlNinxUn9mYCkxhluBpAmk2nYGyphVFfC3nyWNcFIaBdOAPuyiVwzZoP4fX2fZMsI3Q3hD+gZmf6sYzmlA8Vu2HcrcPYW8cpsR9SYe8Pf/hDLFq0CAsWLEjXxpAzaSWj4Ln8Org/8zmYHxxS7Q62blAH6+3fhfj+XYDHC31OJfT5S6BdMA1Cs83B0IMijSRkqBUItUJ4fCqh8fmz/t9FRJTt+jUTs2XLFmzcuBE7d+7EhAkTsHDhQlRWVtrylMDCwkK0HPsYMhEHEglII2H1kCwxXDMxvZGGgdTe7ap+Zvc2IGWkr4nCYugd9TPa6LEjMp6RISB8fpXQeH096mec8puR3TDu1mHsreOU2GdkOSkWi6UTmgMHDmD69On45je/mdGBDtXp/1BpplQyk4gDiThkMgkgp1bQejWSSUx3MhKGsW0jjPp1MA8f7HFNGzcB+vwl0OctgsgvGPGxDRehuQB/ACIQhNDdjvlQsRvG3TqMvXWcEvshLSd18vl8WLhwIQKBAFKpFHbs2JGxAQ4XobnU1H/HsfPSNIFkt6QmkYATkpqRIgJBuKsvg7v6MpinjsOor4WxuRay6STMD99H4sP3kXh5JVxTZ0OfvxiuWfMGXDhrN9JMAeEQZDgE4fHBFICUkrubiIiGWb9mYqSU2Lt3LzZs2ICtW7eitLQUVVVVtqyR6Stb64s0za5kJhFT54bkAKtmYnojpYR56IA6f6ZhAxCLdl30+aHPWaCWmyZdmBN1JgF/ANF4HPD5IHwBnj0zQpzyG6kdMfbWcUrsh7Sc9J3vfAderxcLFixAVVUVxowZMyyDzISBJjGnk6kUEI9BxmPqf6WZwdGNHDslMd3JZAKp3dtgbK5Fas92wEylr4niUrVdu3IJtLLRFo5yaE6PfXq5yReA8GT3rJOdOeXD3I4Ye+s4JfZDSmLee+89TJ48eVgGlmlDTWK6k1KqWZrOhMZIZuS+I8GuSUx3sr0NxtYN6vyZDw71uKaNn6wSmnmLVOPGLHKm2AvdAxFgq4Ph4JQPczti7K3jlNgPOIk5deoURo0aBQA4efJknzcuKyvL0BAzI5NJzOmkYXTM0kQh43HYuZYmG5KY7szjR9Vy0+ZayJamrgsuF1zT5qjTgWfMhdDd1g2yn/oXe6EO0gsEITy5c6aOlZzyYW5HjL11nBL7AScx3/zmN/Ev//IvAICvf/3rfd7417/+dYaGmBnDmcR0J6VMJzSIxVRxp41kWxLTSZomzPf2qYLg7ZuAeKzroj8IvXyhWm6aMMW2hbMDjb06TC8IBAKcnRkCp3yY2xFjbx2nxN5RJ/aORBJzOplMpGtpZCI+4u9/umxNYrqTiThSO7eq+pn9OwGzqz5JjDq34/yZxdBKz7FwlJ80+NhzdmYonPJhbkeMvXWcEvshJTHPPPMMbr311k+8vnLlStxyyy2ZGWGGWJXEdCfNFBDvVktjwSxNLiQx3ZltLUht3aDOnznas3u6NukiVT9TvkDNaFgsE7EXLl0VA/uDEPqATkJwLKd8mNsRY28dp8R+SOfE1NbW9prErF+/3nZJjB2kd6P4AwAAmUioZad47mzhHmlaQRG0S6+C+9KrYH78gVpu2lIH2dYC89B+JA7tR+KP/wnXzHnq/Jlps1UikKVkygDa2yDb29jqgIioD2f8lF+7di0AwDTN9J87nTx5Enl52bVrxCrC41Fba/MLu50gnACSCcBI2q6exu60MefD87kvwH3N52Ee2I3k5nVI7dgMJBJIbduE1LZNQF4+9PIqVT8zbqJt62f6QyZikIkY0CogvF4IX0CdQcP6GSJyuDMmMevXrwcAGIaR/nOngoICfPWrXx2+keWo008QBjp2PRlJNUtjJIFkUv0mTmckNA2uqbPgmjoLMh6DsWMzjPpamAd3A+0hGGvfhLH2TYhzz1PLTRXV0IpLrR72EEhVcxXvSGg83o7u2oGsTtKIiAarXzUxL774Im688caRGM+Q2aEmJhO6ThKOD+qMmlyriRkIs6UJxpb1MOrXQh4/2nVBCGhTpqmEZk5lj0Qyk0Y69kJoXb2bsryFw1A4pTbAjhh76+R67JMNG5B45Tmct/yJgRX2du/9Ypp9n1qr2WyNPleSmNP1OEk4ET/rEpSTk5hOUkqYH72vzp/Zsh5ob+u66PbANatCnT9z4QwIV+aWZqyMvdA9EMEg4A86bnYm1z/M7Yyxt04uxz7ZsAGxp34J6G6M+7cXBlbYe/fdd+OXv/wlAODOO+/s803sdk5MrhIuFxAIqtNeATUzE4+rWol4PGvbIwwnIQRc4ybCNW4iPNfejNS+nTDqa5HatQVIJpDauh6presh8gvhqqiGu3IJtPPOt3rYQyKNBGRrAiLUBukPQgTzMpqgERGNlMQrzwG6+4z95/qciWlqako3d2xsbOzzBqWl9qoxyNWZmLORyURHwbDqzu33eh0/E9MXGY3A2L5J1c+8t6/HNW3M+dArF8NVUQ2toGhQ97fXLJiA8PnVUlOON6LM5d9I7Y6xt04uxz50zxeBYD6EEBj7L08PbCame3fq0xOVRCIBTdOg8/wK2xBuD+D2pPsMuXxeaM3NHUlNAtLg1u5Owh+Au+pSuKsuhdl0EsbmOtXu4OQxmB9/gMTLzwKvPAfXhTNVQjNrPoQ3Ww+fk5CxCGQs0lFUzs7aRJQdtLLRMFuagDN8XvUrC/n973+PyspKTJo0Cdu3b8fjjz8OIQS+/vWvY+7cuRkbMGWOcOnq9NfOs2pME0gmsrKZ5XDSSsrgueI6uC//HMwj78GoXwejYQMQCSO1f6c6Kdjrgz57PvT5S6BdMC1rz2qRZgqIhCEj4a5dcg4vBiYi+/JcezNiT/3yjF0K+5XEbNiwAddddx0A4JVXXsFf/dVfwe/347nnnmMSkyWEpgFeX/o3cFUoHO1IalhTI4SAa8IUuCZMgef625Das021O9jdAMRjKrmpXwdRWAK9YpE6f2b0WKuHPWgqoWmHjLSrYmB/gL2biMhW3OVVwO0dtTF96FcSk0gk4PV60d7ejpMnT2L+/PkAzlwrQ/amCoXzIAJq+Sl9qnAirg7is3GH7uEmdF3NvMyeDxlph9GwEcbmWpiHD0K2NiH51iok31oFbdwE6POXQJ+3CCK/wOphD5o0EpChBBBqhfD5IAJ5XG4iIltwl1epZKYP/UpizjnnHKxfvx4nTpzAjBkzAAChUAhutzszoyTLpU8VRrczamJRy3o/2YUI5MG9+NNwL/40zFPHVbuDzbWQTSdhfvg+Eh++j8TLK+GaOltt155ZDnQs4WUfCRmLQsaijt6qTUTZo19JzBe/+EU8++yzcLlc+MpXvgIA2LVrF2bOnDmsgyNrCE3rcapwukN3LOro3k/aqHPh+eyNcF91A8xDB9T5Mw0bgFgUqT3bkNqzDfD5Yc6vBsqroE28MHvrZzq3are1QgaCqr6KtTNENII6D7ozTx5D4VOv9Po1/TqxN5s4dYv16YZr2500U0As1tHQkrU0MplAavc2GPXrkNq7A+g2ayVKRqnTgecvhlY22sJRZobQ3R1tDoK2PHsml7ea2h1jb51cjX33g+7g8WLcvz4z+C7WALB3716sX78ezc3NKC4uRlVVFaZPn57RQZP9Ca3r0D0pJUQi3lUc7MBt3MLtgT53AfS5CyDb22Bs3QBzy3oYR96FbDqF5BsvIfnGS9AmTFEJTXlVeht8tpFGEjLUqmpnPB2NKP1+FgMTUcb156A7oJ8zMe+88w5efPFFXHzxxSgtLUVTUxPWrl2L66+/HjU1NRkbdCZwJkaxIjvvvuNJxmJwanFwwB9A++GDarlpcy1kS1PXRZcLrhnl0Ocvhmv6HAg9++vKhMcH4ferJUgLE5pc/Y00GzD21snV2Hc/6A7AwA+76+61117Dt7/9bZx/fteR7AsWLMBjjz1muySGrNN9x5M0zXQdDeIxxy07aeeeB8/Vy+D+7E0w39unCoK3bwLiMaR2bEZqx2YgEIReXgW9cjG08VOytoBWJmKq/UVrS0dnbesTGiLKbv056A7oZxITDocxZsyYHq+de+65OZn9UWYIraOzsj+glp06E5pY1FEJjdA0uC6YDtcF0+G56UtI7dyizp/ZtxOIhGHU/hlG7Z8hRp0LvXIx9IrF0ErLrB72IMluCU1z15KTz2/LGhoisq8eB915+j4xvV9JzAUXXIDnnnsOf/EXfwGv14t4PI4XXngBU6ZMydBwKZcJIdK7ndIJTTTSr27cuUR4vNArqqFXVMNsa0FqS53q3/TxB5CnjiP52otIvvYitEkXqYRm7gIIf9DqYQ+aTMRV24u2Zgi3p6OGJsCEhojOqvtBd+bJY31+Xb9qYlpaWvBv//ZvePfddxEIBBCJRDBlyhR87WtfQ1FRUQaHPXSsiVGyZZ1UGsmuA/YScciUYfWQhmygDSDNox/A2LwOxpb1kG0tXRd0Ha6Z89T5M1NnQbhyo1fZcCU02fLM5yLG3jpOiX1fP9sHtMW6qakJra2tKCws7NEgcqiSySR+9rOfwTAMpFIpzJ8/H9dffz3C4TBWrFiBxsZGlJaW4o477kAweObfTJnEKNn6YEsj2bGFO6Z+i8/C4uDBdrGWponUgd1qu/bOzUCi226vvHzo8xap/k3jJmRt/czpMpnQZOsznwsYe+s4JfZDTmIikQi2b9+eTmLmzJmDQCAzJ5NKKRGPx+Hz+WAYBn72s5/hC1/4ArZu3YpgMIilS5di9erVCIfDWLZs2RnvxSRGyYUHu8fJwVlUSzPYJKY7GYvC2LFZtTs4uAeQXf+ZinPPU9u1K6qhFZee4S7ZRSU0ftXjaxAH6+XCM5+tGHvrOCX2ff1s79f89J49e/DYY49h9OjRKCkpQVNTE55++mncddddGTkrRggBn09VIKdSKaRSKQgh0NDQgO985zsAgOrqajz00ENnTWIod3Q/OViaJkQsChmNqMLRHCd8frgXXAz3gothNjfC2FKntmsfPwp5/CiSq/6A5OrnoU2ZBr1yCfTZ89MnLGcrmUyoE6FDrWrprOP/9+IMRX1E5Gz9SmKeeeYZfPnLX8aCBQvSr9XX1+Ppp5/GAw88kJGBmKaJBx54ACdPnsSnPvUpTJ48GW1tbemam6KiIoRCoV6/d82aNVizZg0AYPny5WddcnICl8uVe3HIzwcAyJShkplotGPJyV40l4ZAJvsn+QPAeedDXvN5GB8cQnzDGsQ2rYVsb4N5cA8SB/cg8fxv4S1fCF9VDdzT5mRtu4MeOjptIx6F8Pmg+YOAx9vnUlpOPvNZgrG3jtNj368kpqWlJd25utO8efPw29/+NmMD0TQNP/jBDxCJRPCrX/0KH330Ub+/t6ampsd5NU6YWjubnJ9iFOpMGunzq6WmWBQybo8amkwsJ/WpbDS0a2+Gf+lNSO3bCaO+FqldW4BkAvFNaxHftBYivxCuimq4K5dAO+/8s98zG7SHAJxUZ894vF3LTt2StZx/5m2MsbeOU2JfWFjY6+v9SmKqq6vx1ltv4TOf+Uz6tbfffhvV1dWZGV03gUAAF110EXbu3ImCggK0tLSgqKgILS0tyO/4TZyok2qD0HHAnpRAMqHaICQSWVsY3B/CpUOfUQ59RjlkNAxjW72qn3lvH2SoFcb/vgbjf1+DNuZ8dTpwxSJohcVWD3vIVO+uCGQsAkB0nEWjDtcjIufpV2HvT3/6Uxw6dAj5+fkoLi5Gc3MzQqEQJk2a1GNq97777hvUIEKhEFwuFwKBABKJBB5++GF89rOfxf79+5GXl8fC3kFwSnZ+Jp1JDTrPK0kkRqQ4eFhnYs7CbDyp6mfq10GeOt51QQi4LpqpEppZ8yG8uVdnEiwsQtSUqpYmB9o5ZBN+3ljHKbEf0u6k2trafr3J4sWLBz4yAB9++CGefPJJmKYJKSUqKyvxuc99Du3t7VixYgWamppQUlKCO++8k1us+8kpD/ZAyWRCNauMRdSfh4GVSUwnKSXMI+/BqF8Ho2EDEOn2LHh90GfPh165BNqUablRP4Oecbd7x+1cw88b6zgl9hk5JyYbMIlRnPJgD4VMpYBoBDKe2QJhOyQx3UnDQGrPNtXuYHcDkOo6JVkUlahThCuXQDv3POsGmQF9xV14fBCBoJqhyZHzdeyGnzfWcUrsmcQ4jFMe7EyRZkrN0CQ66mmM5KDvZbckpjsZboexbSOM+nUw33+3xzXt/Enq/Jl5VRB5BRaNcPDOFnchNMDvh/AHuW07w/h5Yx2nxJ5JjMM45cEeLjKVUt2347EB93iycxLTnXnyGIzNter8maZTXRc0F1zTZql2BzPKB3XwnBUGEnehudINSrPl32dn/LyxjlNizyTGYZzyYI8UmYhDxmIqsTHOXEuTLUlMJ2maMA8fUPUz2zYBsWjXRZ8f+twFarlp0kW2Xo4ZbNyFS1fbtX3+M55DQ33j5411nBJ7JjEO45QH2wrSMDq2+UZ7LQ7OtiSmO5lMILWrAcbmdUjt3QGYXbu5REmZWm6qXAxt1LkWjrJ3mYi7EBrg9UJ4fYDXz6LgfuLnjXWcEvshJTGGYeDVV19FXV0dWltbUVRUhEWLFuGaa66Brtursy6TGMUpD7bVeisOzuYkpjsZaoPRsEGdP/PBoR7XtAlTVLuD8oUQgTyLRtjTcMRduD1qlsbrh/Bw2akv/LyxjlNiP6Qk5tlnn8WhQ4fwuc99DqWlpWhsbMQrr7yCiRMn4gtf+MKwDHiwmMQoTnmw7USmUkAsCr8Awq3NVg8no8xjH3XUz9RBtjZ1XXC54JpRrs6fmT4XwsJfaoY7eRSaC/CphAYeb85sTc8Eft5YxymxH1IDyPr6evzgBz9AXp76jWv06NEYP348fvSjH9kuiSGyinC5gGAeXMEgNG+3dgg50LBSGz0Wnms+D/fSv4D57l5VP7NjMxCPIbVjM1I7NgOBIPTyKrXcNH5KztWWSDMFRMKQkTB6nBbs96sEh4hG3JB+bZIyp8ppiDKmM6ERwbyOo/Kj3RpWZu9/N0LT4LpwBlwXzoDnpv+D1K4tMOrXIbV/FxAJw6j9M4zaP0OMOlctN82vhlZSZvWwh4GETMRUgtrWAuHzQfiDaukpx5I3Ijvr13LSypUrcfjwYVx77bXp5aRXX30VEyZMwC233DIS4+w3LicpTplitKMzxV6aptrhFIuq/x2BNggjwWxrQWpLnaqfOfpBj2va5KmqIHjuAnWK7jCxQy1Seuu2x+uohIafN9ZxSuwzUti7YcMGtLa2orCwEAsXLsQ111wDt9tePUqYxChOebDtqL+xl1KqM2iiEchoBNk8Q9Nd6ugR1V17Sx1kqNt/i7obrpnzoFcuhmvqLLW1OYPskMT01LHk5PUCHl9OFwbz88Y6Tok9t1g7jFMebDsaTOylmQKiUchI+Kzn0GQLmUohdWC3anewY7NqxtkpLx/6vEXq/JmxEzIyY2G/JKYnoblUQbDXp2Zpcmj7Nj9vrOOU2A85iTEMA8eOHUN7e3uPWpjp06dnbpQZwCRGccqDbUdDjb1MJCCj7SqpyZHlJhmLwtixWbU7eHcv0O0zRJx7nlpumr8YWlHJoN/D7knM6YTugfD7AV/A0l1dmcDPG+s4JfYDTmK2bduGqVOnwufz4cCBA1ixYgWSySRisRh8Ph/i8TiKi4vx4x//eNgHPxBMYhSnPNh2lKnYSynVGTTRSE7scOpkNjfC2LoeRv06yONHuy4IAW3KNFUQPHu+2vkzANmWxHSX7QkNP2+s45TYD3iL9cmTJ/Hmm2/i3nvvxbPPPourrroKV1xxBe655x784he/wMsvvwxPDq/xEllNCAEEghCBYMehemp7r0wZVg9tSLTiUng+fQ3cl10N88P3YWxeB2PreqA9BPPgHiQO7kHi+d/CNXu+On/mopk5fyaLNBKQoQQQaoVwe1QC5/ND6PaqOSSymz6TGMMwMGHCBADAiRMn8JnPfKbH9aVLl+J73/serrrqquEdIRGp+om8Aoi8AtXHKRrO+uUmIQRc50+E6/yJ8HzuC0jt26kKgndtAZIJpLbUIbWlDqKgCHrFIujzl0A773yrhz3sZDKh2lmEWiF0jzpgzx9gQkPUiz6TmNdffx1f/epXAQB+vx+xWAyBQACFhYU4evQo8vLyEI/HR2ygRKQIjxfC44XMNyFi0ZxYbhIuHfqMcugzyiGjYRjb6mFsXgfzvf2QbS1Ivv0akm+/Bu2881V37XmLoBUUWT3sYSeNBNCegGxvU0mMz8+EhqibPmtijh49ioMHD6KmpgYrV67EpEmTUFVVhddffx2vvfYaXC4XZs2aha985SsjPeYzYk2M4pR1UjuyIvbp5aZoBNJIjuh7Dyez8SSMLbUw6mshTx3vuiAEXFNnqeWmWRUQHm9W18QMlNA7ejr5fOpMGovx88Y6Tol9RrdYHzhwALFYDDNnzoRms7VqJjGKUx5sO7I69jKZUAfpxWOQiQRy4fwZKSXMI+/CqK+FsXUDEO0WX68P+pxKBBd/GslxE3O+fuZ0PbZu+3yWtECw+pl3MqfEfkhJTHNzMzweD4LBYPq1cDiMZDKJoqKijA50qJjEKE55sO3ITrFPnxCciAHxeNYXBQOANJJI7dmu2h3s2QakUulroqika7v2uedZOErrWNF5207PvNM4JfZDSmIefPBB3H777Rg3blz6tQ8//BC//e1v8a1vfQvvv/8+xo0bh/z8/MyOehCYxChOebDtyM6xl4YBJGKQ8bg6LdhMnf2bbEyG22E0bFDtDt5/t8c17fxJKqGZVwWRV2DRCK0lNFfHstPwdt628zOf65wS+yF1sT5x4kSPBAYAxo0bh8OHD+M3v/kN/H4/nn76aTzwwAOZGS0RDQuh64CeBxHIg5QSIhKGjLRnbR2NCObBveQzcC/5DDxtLWiv/TOMzbWQTadgfnAIiQ8OIfHSSrimzVYFwTPmqpkKh1AnQYfVbrZ0GwRfx/bt7DuPhuh0/XqK8/LycOLECZxzzjnp106cOIHS0lLcddddSCaTuPfee4dtkESUeUKIrk7bsShkONTRZTs76eeeB89nb4L7yhtgHj4AY3MtjIaNQCyK1O4GpHY3AD4/9PIqtdw06ULHNGhUunXeDrWoHU5en0pqPF6HxYJyRb+Wk1599VXU19fjhhtuQFlZGU6ePIk//vGPqKysxDXXXINUKoVwOIyCAuunbLmcpDhlitGOsjn2MplQzSijkaxbauptd5JMJpDa1aDqZ/btAMyuc3VESZlabqpcDG3UuSM9XFsRQutKaAbR1ymbn/ls55TYD6kmxjRNvPHGG1i7di2amppQUlKCiy++GFdccQV3J9mUUx5sO8qV2Mt4TCU0sew4VO9sW6xlqBXG1o76mQ8P97imTbgAeuVi6OULIQJ5wzxS+xvoFu5ceeazkVNizy7WDuOUB9uOci320jSBWAQybO8O2wM5J8Y89pFabtpcB9na1HXBpcM1Y66qn5k2h3Uj6F9xcK4989nEKbFnF2uHccqDbUe5HHuZSKhC4GgEdjt/ZjCH3UnThPnuXhj162Ds2AzEu518HMiDXr4QeuUSaOMns2YEACAgvF6V0Hj96WWnXH7m7c4psR9SEsMu1tnHKQ+2HTkh9tJMARF7NaQc6om9Mh5Haudm1b/pwC6g2y9romx0x/kz1dBKyjIx3JzQ2dspr6QUkaQ9ngOnccLnDTDELdbsYk1E3QmtW0PKWBQy3J79/Zu83vRBeWZrM1Jb1qv6mY8/gDx5DMnXXkDytRegTZ6q6mfmLIDwB6wetqU6ezulUgbMeLxncbDN6iUpN/X7nBh2sSai3gifH8LnhzSSkJGIOpcky3Y2nU4rLIZ22VK4L1uK1NEjanZmSx1kqBXme/uQeG8fEi/8J1yz5qn+TVNnQbicXT/T65k0Pr86k2aAu52I+qtf/9WxizURnY3Q3RAFhUBBoZqdiUYgY1HYrXZmoFznjYfruvGQ13weqQO71XbtnVuAZAKpho1INWwE8gqgVyyCPn8JtLHjWT/T/UyatmYItwfCF+Ahe5Rx/Xqa5s2bhx07dqCqqgoXX3wxHnroIbhcLsyfP3+4x0dEWSg9O2Oaaot2PAoZiyGbExrhckGfNhv6tNmQsSiM7fVquendvUB7G4w1r8NY8zrE6LHQ5y9R9TOFxVYP2xZkMqEak3Yestd5cvAwtkIgZxjUFuv9+/cjHo+zi7WNOaXYy44Y+95JKVUzyo5ZmkwnNEMt7B0ss7kRxpY6GPXrIE983HVBCGgXTIdeuQT67Pnqh3aOGnzsO1sheFUdjYNaQmSKUz5veE6MwzjlwbYjxv7spGmqU4Ez2LfJqiSmk5QS5oeH1XbtrRuAcKjroscD1+z5cM9fAu3CGTk3+5Cp2AvNBfhUB27O0vSPUz5vBpzEPPLII/jWt74FAPjpT3/a5xrvfffdl7lRZgCTGMUpD7YdMfYDIxNxtbtpiPUzVicx3cmUgdS+nap+ZtdWwOjafiwKiqBXVKt2B2POt3CUmTM8se/esNKnlqHoE5zyeTPgLdbV1dXpP19yySXDM6oOTU1NePLJJ9Ha2gohBGpqanD55ZcjHA5jxYoVaGxsRGlpKe644w4Eg8FhHQsRjSzh8UJ4vF1nz4Tbs353k3Dp0GeUQ59RDhkNw2jYpOpnDu2HbGtB8u3VSL69Gtp546FXLoZr3iJoBUVWD9tmujesBBtWUq9ssZzU0tKC1tZWTJgwAbFYDA888AD++q//GrW1tQgGg1i6dClWr16NcDiMZcuWnfFenIlRnJKd2xFjP3SDOXvGTjMxfTEbT8DYXAdjcy3kqeNdF4SAa+os6POXwDVrXr/6FdnJSMdeNazsLA72OXrHk1M+bwY8E7N27dp+3fjiiy8e/Kg6FBUVoaioCADg8/kwZswYtLS0oKGhAd/5zncAqJmhhx566KxJDBFlv66zZwx17kgk+8+eAQCt9Bx4rrwe7iuug/n+u6p/09YNQDSM1N4dSO3dAXh90OcsUMtNk6eyLqQXUnbseotFAYA7nhyszyRm/fr1/bpBJpKY7k6dOoUPPvgAkyZNQltbWzq5KSoqQigU6vV71qxZgzVr1gAAli9fziUnAC6Xi3GwCGOfYYWFAAAzFlVtDmKRXktnNJeGQDadoDt9DjB9DuQX/gqJnVsQ27gGiZ1bgHgMxqZ3YGx6B1rJKPgWXAJvVQ300WOtHnGfbBF7qRqVIh6B8HR04Pb6Idy5XUvj9M+bPpOYzhmQkRSLxfDYY4/hC1/4Avx+f7+/r6amBjU1Nem/O2Fq7WycMsVoR4z9MPL6Id0eIBKBjIZ77GzKhuWkPk2bDfe02dDD7TAaNsCoXwfzyHswm04h8qcXEfnTi9DOn6TaIsyrgsgrsHrEPdgu9pGusQiX3rMdQo7V0jjl86aw45eZ0w14IVFK2aOLdabOiTEMA4899hiqqqpQUVEBACgoKEBLSwuKiorQ0tKC/Pz8jLwXEWUv1bcpHyIvHzIe65idiVo9rIwQwTy4l3wG7iWfgXnymNquvbkWsrkR5geHkPjgEBIvrYRr2mzolUvgmjGXZ6uchUwZQKQdMtKOdBdur18lNA6upckV/fr/YHNzM55++mkcOHAAkUjPbPvXv/71kAchpcRvfvMbjBkzBldeeWX69blz56Kurg5Lly5FXV0dysvLh/xeRJQ7RMdv2NJMQYOESCRs01V7qLSy0fAs/Qu4r7oR5qEDKqHZvgmIRZHa3YDU7gbAH4A+dyH0yiXQJl6Qc7MMmSdV4htXBePc8ZT9+rU76Ze//CU8Hg+WLl2Khx56CN/97nfx0ksvYfbs2T2WcQbrwIED+NnPfoaxY8emH6KbbroJkyZNwooVK9DU1ISSkhLceeedZ1374+4kxSlTjHbE2FujM+7qRODcmZ3pTiYTSO1qUOfP7NsBmGb6migt6+jCvQTaqHNGdFy2W04ahB47nrzZ07TSKZ83Qzqx91vf+hZ++tOfwuv14u6778ajjz6KcDiMn/zkJ3jggQeGZcCDxSRGccqDbUeMvTVOj7tMpdQSQo7sbDqdDLXB2LoexuZ1MD98v8c1beIFqt3B3IUQgeEv+syFJOZ0QveoWRqfz9Zb3p3yeTPgLdbdaZqWrn0JBAIIhULw+Xxobm7O7CiJiDJEuFwQ+YVAfkdX7Uh7ehkhF4j8ArhrroS75kqYxz5Sy01b6iBbm2EePojE4YNIvPhfcM0shz5/MVzT5rAGZACkkQCMBGS4TdVhdT89WMuOWRon6NcTPWnSJOzYsQMVFRWYOXMmVqxYAY/Hg4kTJw7z8IiIhi597kzn7Ew0kjO1MwCgjR4Lz7U3w331MpgH98LYvA7G9nogEUdqez1S2+uBQB70eVWqfub8Saz/GABppoBYRG3vbwWE2wPh8wO+ABNDi/VrOSkSiUBKiWAwiEQigddffx2xWAyXX355+hwXu+BykuKUKUY7YuytMdC4d3bTHmrPJruS8TiMHfWq3cGB3UC3XaWibDT0ysXQKxZDKxk15PfKxeWk/lIJTQDwByypo3HK582QamJCoVDWbG9mEqM45cG2I8beGoONe67XzgCA2doMY0tHu4OPP+xxTZsyFfr8JdDnLlCzC4Pg5CSmO+H2dO12cntGZLbLKZ83Q0pi/vqv/xoXXXQRqqqqMG/ePHi99i1yYhKjOOXBtiPG3hpDjbuUUi0zRdohk4kMjsxeUh+9D2NzLVJb1kOGun1W6m64ZlWohpQXzRrQrAKTmE8aqf5OTvm8GfJMTH19PTZu3IgPPvgAc+bMQVVVFWbNmgWXzbahMYlRnPJg2xFjb41Mxl0mEpDhUM4uNQFqBip1YBeM+lqkdmwGup1+LPIL4Jq3SG3XHjv+rDMKTGLObrj6Oznl82ZISUx3jY2N2LhxIzZs2IDW1lY8/PDDGRtkJjCJUZzyYNsRY2+N4Yi7E5aaAFUfZGzvqJ85uKfHNTF6rFpuml8NrbC41+9nEjNQAsLj6Zql8Qz+1GWnfN4MaYt1d21tbWhra0N7ezsCgSxqtkZENECd27RlXgFEDi81CZ8f7oWXwL3wEpjNjap+pn4d5ImPIY99hOSrzyG56vfQLpihCoJnz1c/gGmQJGQiDpmIA2jlFu4h6NdMzNGjR7Fx40Zs3LgRyWQSlZWVWLhwISZNmjQSYxwQzsQoTsnO7Yixt8ZIxV0mEyqZiUSQq0tNgKoRMj88rM6f2boBCIe6Lnq80GfPhz5/MbQLZyAYzONMTAZ1FQj7zzpL45TPmyEtJ91zzz2oqKjAwoULMW3atPT6qGmaGWsAmSlMYhSnPNh2xNhbY6TjLs1Ur920c5FMGUjt3aHaHexqALqdsSMKiuBbWAOUL4Q2Zpx1g8xRQnN168Lt/cQsjVM+b4aUxBiGAb1bZfWHH36Iuro6bNiwAQ899FBmRzpETGIUpzzYdsTYW8PKuKtu2u052a/pdDIShrFtk6qfObS/xzXtvPGqu/a8KmgFRdYMMMeJzmUnrw/C7XHM582QC3tDoRA2bNiAuro6fPDBB7jwwgtx2WWXobKyMuODHQomMYpTHmw7YuytYYe4y1QKMtwORHO7ELiT2XhC7W7aWgfz5PGuC5oG10Wz1HbtWRVqeYQyTmguBEpKEE3JjO54sqNBFfYahoFt27ahtrYWu3btwjnnnIOFCxeisbERd9xxBwoKCoZtwERE2Ua4XBAFhUBBYcfsTDint2lrpefAc9UN8F9/K9o7lpuMho1ANIzU3u1I7d0O+PzQ51SqdgeTLsrpH7QjTZopyHAYZjSCHjueOmZpnOCMScy9994LTdOwePFiXHfddZgwYQIA4O233x6JsRERZS3RUccgTVP13YlGOnaj5B4hBFwTL4Br4gXw3HAbUru3qfqZPduBWBTGxndgbHwHorgU+vzFqiD4nDFWDzvHdNvxFOq+48mr/ld3Wz3AYXHGJGbcuHE4ePAg3nvvPZxzzjkYNWoUgsHhb+tORJQrhKYBgTyIQB6kYUBGwznXgLI7obvVzMucSsj2EIyGDap+5sh7kM2NSL75MpJvvgxt/GSV0JRXQeRlR1ubbNKjaSW6FQh7vOp/bXZQ7WCdtSamsbERdXV1qKurQ1NTE2bMmIH9+/fjRz/6EYqLez/4yEqsiVHsUB/gVIy9NbIt7jKRgIy2A9EopDStHs6Q9OewO/PExzA216r+Tc2NXRc0F1zT56j6mRnlOTtjMFwGe9DgcJ0gPFwycmLvgQMHUFdXh/r6erhcLixZsgTLli3L6ECHikmMkm0f6LmEsbdGtsY9vdwUDkMa2XmQ3kB+kErThHloP4z6WhjbNgLxWNdFfwB6+ULV7mDiBSPSQDHbZea0ZNG168nns2UimbG2AwCQTCaxZcsWrF+/Hvfcc09GBpgpTGKUbP1AzwWMvTVyIe6dszPZcpCesWc7km+tApobgeJSuC+7Gvr0Of3+fplMILVzi2pIuW8nYHbNSInSc7rqZ0adMxzDzwnD0fJBuPSupSeP1xZLTxlNYuyMSYySCx/o2Yqxt0YuxV2aZldHbZsepGfs2Y74C78DdB0ujw+pRAwwDHhv+vKAEplOMtQKY+t6GPW1MD96v8c1beIF0CuXQJ+7ECLAuszuRqJvlXDpKpnxeC1ri8AkxmFy6QM92zD21sjVuNv1IL3or34CM9QK4fHCJTSkpAmZiEPLL4T/G/cP6d7mxx921c+0tXRdcOlwzSyHPn8JXNNmQ+gDbv+Xc6xovil0jzo9uLOeZgSW/TLWAJKIiEZOequ2kYQMt0NGwrDDUpPZdAo4fVbE7VGvD5E2Zhw8194M99XLYB7coxKa7fVAIo7U9nqkttcDwXxVP1O5BNr5k1g/M4KkkQCMBGQ4BCE0SI8HwucHvP4RX3riTEyOytXfSrMBY2+NbI17smEDEq88B/PkMWhlo9UP7/KqPr9e9WwKq4TGglOBO+tgzPffBQSAgmLogbyMzsT0RsbjSO3cjGT9OpgHdgOy60eXKButlpsqqqGVjMr4e9uZFTMxZyJ0t0pmfB01NRnC5SSHydYP9FzA2FsjG+OebNiA2FO/BDq2uyIRB4wkfLf/zRkTGUB1mUY0opKZEdrV1L0OBkYKaFGzLqJ4FKTLNaSamIEwW5thbKmDUV8LeezDHte0KVOhz18Cfe4CNTuQ4+yWxHTXdeCeb8i1NExiHCYbP9BzBWNvjWyMe/jBe2G2NKkP+Q4yHoNWVILg93/e7/vIWFQlM4nY2b94CLrXwQCAjEaAtmZAAtqEKQPenTRUUkqYR4+k+zfJUFvXRd0N16wK1ZDyopm22GEzHOycxJwufTbNIHY9sSaGiMhmzJPHgOBpp9V6vOr1ARA+P4TPD5lMqGQmOjxbtE+vgxH+AKTPDy0aGZYlpLMRQsA1dgJcYydAXnszUvt3qXYHO7cARhKphg1INWyAyC+Aa1612q49djzrZywijSRgJCEj7QA6t3J7Ibz+QR+4xySGiMgiWtlomC1NQLeZGCTi0MpGD+p+wu2BKCqBzC9U3bQj7Rk9DVgrGQUz1KqWvjolE3DZ4BwX4XJBnz4H+vQ5kLEojO31MOrXwXx3L2SoDcaaP8FY8yeI0eM6zp+phlZov1PnnUSmDCBidBSrqwaWavnJr/7cD1xOylHZOLWeKxh7a2Rj3IdSE9Mf0jRVEXCkPSO9mnrUxLg9QDIBGAYKbv0rpCZPG/L9h4PZdArGllpVP9N9hksIaBfMgF65GPrs+T2W9LJJNi0nDUSPBpZeP4pKSlgT4yTZ+IGeKxh7a2Rr3Ae6O2kwpJRALAoZDkEmh1YEnN6d1HQKWskouC+7GgUVi2z/g1RKCfODQzDq18Fo2AiEQ10XPV7os+er7doXTLd9H6HucjWJ6U4EC1B8/ngmMU6SrR/ouYCxtwbj3j8yHlPJTDxzRcDZ9oNUpgyk9uyAsXkdUrsagG6zVKKwGHpFtUpoRo+1bpD9lG2xH4wzJTGsiSEicpCeh+eFsqZPUyYJlw591jzos+ZBRsIwtm1S9TOHD0C2NiP51iok31oFbewEtdw0bxFEfqHVw6ZecCYmR/G3Uusw9tZg3AdHplKqCDgaHvThebkyG2CeOtHR7mAdZOPJrguaBtfUWdDnL4ZrVgWEu39FpyMhV2J/JpyJISKiXgmXC6KgEDIvHyIaUbMzGSgCzkbaqHPgueoGuK+8HubhgzA2d9TPRCNI7dmO1J7tgM8PfU6lWm6adFFW1c/kIs7E5Cj+Vmodxt4ajHvmyM5kpp9FwLk8GyCTCaT2bFMH6u3ZDnSbrRLFpR3btRdDO2eMJePL5dh34kwMERH1m/AH1EF28Rhke2jYTwK2M+H2QJ+zAPqcBZDtbTAaNqr6mQ8OQTY3Ivnmy0i++TK08ZNVQlNeBZGXf/YbU0bYZibmqaeewvbt25Gfn48f/vCHAIBwOIwVK1agsbERpaWluOOOOxAMBs94H87EKPyt1DqMvTISW4e7G+64j/S/x05kIgHZ3trnjqZMzwb0to17ONsZDOb9zONHVf+mzbWQzY1dFzQXXNPnQK9cDNeMcnXU/jBy+kyMbZKY/fv3w+v14sknn0wnMX/4wx8QDAaxdOlSrF69GuFwGMuWLTvjfZjEKPxBah3GfvgPcevNcMbdin+PHclkArK9DTIW7fF6Jn+Q9nWg3nA1lhzq+0nThPnePhj1tTC2bwK6J3r+IPTyBdDnL4E28YJhaXfg9CTGNhVJF1100SdmWRoaGlBdXQ0AqK6uRkNDgwUjI6KBSrzyHKC71XZeIdRpqLpbvZ6Fcu3fM1jC7YFWPAraqHMhfIFheY/kW6sAXYfweFWsPV5A19XrNnw/oWlwXTAd3lv+CoF//AW8X7oTrmlzAE0DomEYdW8j9i//hOiP/x8k/vRHmI0nhuXf4VS2rolpa2tDUVERAKCoqAihUKjXr1uzZg3WrFkDAFi+fPlZl5ycwOVyMQ4WYeyB8KnjcOUV9PjNU/r8kKeOD1tshjPuVvx77C0IFBVDJhMwQ20QiRgC/swkNdHmRrgCeT1j7fFBNjdm7D2G7f38AWDxp4HFn4bZ1oLYprWIb3wHxgeHIBtPIPn6H5F8/Y/Qp0yFr+pSeCsWQQvkDWn8mksblrjYiRbs+99n6ySmv2pqalBTU5P+u9On8gEuaViJsQcw6lykWpp69KOR8Ri0UecOW2yGNe4W/HuyhtePQH4hoiePA9HI0BtOFpciFWpVMyIdZCIOrbh0eJZNhuv93B5g8afhXfxpuD/+sOP8mVrIthYY7+5D+7v70P7sk3DNLIc+fwlc02ZD6AP/keyI5SRNh6ek92u2TmIKCgrQ0tKCoqIitLS0ID+fFd808oa7oDMXC0Y9196M2FO/VOfAdqsh8Vx7s2VjGkqc7fjvsRPhdkMrLIbML4QYYsNJ92VXI/7C71Ssu9WouC+7OqNjHsn308aMU8/b1ctgHtyDZP1apHZsBhIJpLbXI7W9HgjmQy9fqM6fOX/SsNTP5CLb1MT0Zu7cuairqwMA1NXVoby83NoBkeN0FnSaLU1AMB9mSxNiT/0SyYYNWXF/q7jLq+C7/W+gFZUA4RC0ohJLi2CHGme7/XvsSmgaRF4+tHPGQCseBeEZeGdoffoceG/6MrT8QiAShpZfOGxFvSP9fkLT4LpoJny33YHAPz4Kz61fg3bhTEAIIByCse5/EPvFjxD92d8h8ebLMLvveqJe2WZ30q9//Wvs378f7e3tyM/Px3XXXYd58+ZhxYoVaGpqQklJCe68805use4nLmlkRvjBe2H2toxQVILg93/e6/cMJPaDuT/17kxxZ5yH15lir3Y0hTp2NNnix43tmK3NMDbXqXYHxz7qcU2bMg165RLocyohfP5PfK8jlpOy4bC7r3/9672+fu+9947wSIi6mCePAcHTljE9XvV6FtyfFMbZOsLtgSgu7ejRFAIi4aHXzeQYrbAYnk9fDfdlS2F+dETVz2ypA9rbYL67F4l39yLxwu/gmlWhzp+5cCaEy2X1sG3BNkkMkR1pZaPVEkS33+CRiEMrG50V9yeFcbae6tFUBJmXD4TbVTIzyIaTuUoIAde4CXCNmwDPtTcjtX+nanewcwuQTCC1dT1SW9dD5BfCVbEIeuUSYMo0q4dtKVvXxBBZzXPtzYCRVMevS6lOLM1gQedw358Uxtk+hOaCll8IUTYaWn4RhMYZhd4Ilwv69LnwffkuBP7xF/Dc/JfQpkwFAMhQK4z//RNiP/9/0fTgd5B4axXM1maLR2wN29TEZAprYhTWxGTOQHe1DDT2ubg7yQpnizvjPHyG8nkjpQSiYchwO6SRzPDIco/ZdFK1O6ivhey+HCoEXBfOVMtNs+ZDeL193yTLZEXbgUxhEqMwibEOY28Nxt06mYq9jEZUEbDRv+7ZTialhPnBIaBhI2Kb1gKR9q6LHi/0OZWq3cEF0yC07F50yYrCXiIicrYe3bPDoT4bTlJH/cz4yQhMnQXt6mVI7d0OY3MtUrsagEQcRv06GPXrIAqLoVdUq/NnRo+1etgZxySGiIhsRXh9EF4fpJGEDLdn5iTgHCZ0HfqsCuizKiAj7TAaNsKor4X5/kHI1mYk31qF5FuroI2dAL1yMfR5iyDyC60edkZwOSlHcWrdOoy9NRh36wx37KVpqt1M4RB3NJ3mTOfEmKeOd7U7aDzZdUHT4Jo6G/r8xXDNmgfh9ozQaAeHy0lERJS1hKYBeflAME+1NWhvYzLTD9qoc+G56ka4r7wB5uGDaolp20YgGkFqzzak9mwDfH7ocxao5aZJF2Zd/QxnYnIUfyu1DmNvDcbdOiMd+/SOpvbQoHs0DTdjz3Yk31oFs+kUtJJRcF929bC0Mhjoib0ymUBqzzZ1/sye7UC3ZFCUjOqqn7HRGUrcneRA/EC3DmNvDcbdOlbFXiUzkY7t2fbZ0WTs2Y74C78DdL1HU8nh6Mk0lLYDsr0NxtYNMDbXqp1O3WjjJ6t2B+VVEMG8TAx10LicREREOUcIAQSCEIEgZCyqamYScauHheRbqwBdh/B0nNXi8UJ2vD5cjSwHQ+QVwH3JFXBfcgXM40fT7Q5kcyPMI+8hceQ9JP77abimz1X1MzPmQuhuq4fdA5MYIiLKesLnh/D5IRNxNTNjYcNJs+kUEDitWbHbo163Ke3c8+C5ehncn70J5nv7YNTXwti+CYjHkNq5RbU+8Aehly+EPn8xtIkXqCTSYkxiiIgoZwiPF8LjVQ0nI9b0aNJKRsEMtQKebqfmJhPQSkaN6DgGQ2gaXBdMh+uC6fDc9CWkdm5R58/s2wlEwzDq3oJR9xbEqHOhz1+sEprSMuvGy5qY3MT6AOsw9tZg3K1j59hLKYHOpabkyNTNDGdNzOkFw3mfvQGpycPfBNJsa0HitReR2roeOG3JTpt8kUpo5i6A8Af7uMPgsbDXgez8oZLrGHtrMO7WyZbYy0Rcbc8egZOAh2N3Um/JkZZKwX3jl4a91qbHewNAexsQjQLdDyHUdbhmzlP1M9NmQ7gys9jDwl4iInI84fFClJR1nAQcgoxEMFx1M/r0ORlPLHorGEYiMSIFw59475IyyHgMQndDO28cUjs2A4kEUts2IbVtE5CXD728Sm3XHjdx2OpnmMQQEZGjCN0NUVgCmVcIGQ6pupksaGvQW8Gw8HiRGoGC4V6LlT1eyEgYvtvugIzHYOzYDKN+HcyDe4D2EIy1b8JY+ybEOWPUdu2KamjFpRkdF5MYIiJyJOFyQRQUQeblA2FrioAHoreCYZmIj0jBcF/FysLnQ/RXP0kvm2kXTFPLdic+BgwDSCYgT3yM5Ko/ILn6eWhTpqn6mTmVED7/0Mc15DsQERFlMaG5oOUXQpSNhpZfBKG5rB5Sr9yXXQ0YhkoSpFRn4qQM9boV7x0JQ4baVHITCKpeTa+/BNnSBJSUAUUlQEERXDPnAXkFgJQwD+5B4tl/R+Qf70HsPx+HsXc7ZGrwiSMLe3NUthTa5SLG3hqMu3VyLfZSSiDcbsuGk1btTurtvc1wO2Cm0nUy6dkXXYc4Z4x6LRGHll8I3x3fQWrfTrVde+dWwEim7yvyC+GqqIZeuRiu88Z/4n25O8mBcu1DJZsw9tZg3K2Tq7GXUqrZBhs3nBxK24GhCj/4HXVickfRrvz4A0BogDQhxpyvXuuIYfD7D6W/T0YjMLZvglFfC/O9fT3uqY05X+1uqlgErbAYAHcnERERDZgQAgjmqR/U/UxmRqrxox18ok7GpadnYtJ6OeRP+ANwV10Kd9WlMJtOwthSB6O+FvLkMZgff4DEK88Crz4H10UzVf1M1af6HANnYnJUrv5mlA0Ye2sw7tZxSuzPNjMzko0fO1k5E/OJf297G9DWChQUqhqYAfz7pZQwj7wHo34djIYNQKTb8+T14fwX1nImhoiIaLB6zMz0UjOTLY0fM0WfPge46ctdM0+jzoW26FKYB/cOeCZKCAHXhClwTZgCz/W3IbV3O4z6dUjtbgDOcDghkxgiIqIBEEIAeflAMK9HMpONjR+HqtdD/a4c2j2FrkOfVQF9VgVkpB2pPTv6/FpusSYiIhoEIQREXj7EOWOg5RepRoin92fKksaPdiUCeXDXXNXndSYxREREQ9CZzHhu/CJgmj3PUjFG5hwXp+JyEhERUQZ45lVDCA3xl5+FeeJjaMWlcH9qaU7Ww9gFkxgiIqIMcZdXwV1eBaDbbqZwCDJlWDyy3MQkhoiIaBh07mYSwTzIaEQlM6fXzNCQMIkhIiIaZsIfgPAHVL1MOAQZi1o9pJzAJIaIiGiECI8XwuOFNAzISDsQjdi2pUE2YBJDREQ0woSuQxQUQeYXQkTDkOEwpMGlpoFiEkNERGQRIQQQyIMI5EHGomqpKRG3elhZIyuSmJ07d2LlypUwTROXXHIJli5davWQiIiIMkr4/BA+P2Q8Btkegkz0fdw+KbZPYkzTxNNPP41vf/vbKC4uxj/90z9h7ty5OO+886weGhERUcYJrw/C64NMJCBDrUxmzsD2J/YeOnQIZWVlKCsrg67rWLBgARoaGqweFhER0bASHg+00jJoped0NZWkHmw/E9PS0oKSkpL034uLi3Ho0KEeX7NmzRqsWbMGALB8+XIEg6c14HIgl8vFOFiEsbcG424dxn6YBYNAcQlkPAazrQUy0VUArLk0BPwBCwc3/LRg3/8+2ycxUsqzfk1NTQ1qamrSfw+Hw8M5pKwQDAYZB4sw9tZg3K3D2I+gQD6kFoVsb4NMJhDwBxCJRqwe1bASmg5PSe/XbJ/EFBcXo6mpKf335uZmFBUVWTcgIiIiC6ULgGNRCNMAcjyJORPb18RMnDgRJ06cwMmTJ2EYBjZt2oS5c+daPSwiIiJLCZ8frrLR0ErKHFszY/uZGJfLhdtuuw2PPPIIpJRYsmQJxo4da/WwiIiIbKHHbqb2Vsi4c3Yz2T6JAYDZs2dj9uzZVg+DiIjItoTHA1FSBplMqHNmYrm/zJQVSQwRERH1j3B7IIpLIY1CyHAbZCQC4OybZLIRkxgiIqIcJHQdorAEMq8QMhwCImFIaVo9rIxiEkNERJTDhMulmk3m5QPhdpXM5EjnbCYxREREDiA0F0R+IWQwHyISVs0mszyZYRJDRETkIELTgLx8IJgHEQ2rIuCUYfWwBoVJDBERkQMJIYBAHkQgDzIaUcmMkTj7N9oIkxgiIiKHE/4AhD8AGetqaZANmMQQERERgG4tDRJxlczY/OA8JjFERETUg/B4s+LgPCYxRERE1Kuug/MK1G4mmx2cxySGiIiIzkjoblsenMckhoiIiPrFbgfnMYkhIiKiAbHLwXlMYoiIiGhQrD44j0kMERERDYlVB+cxiSEiIqKM6XFwXjgEmYgP23sxiSEiIqKMG4mD85jEEBER0bDpeXBeG2QsmrF7M4khIiKiYacOzhsFaSQhQ20ZOQWYSQwRERGNGKG7O04BLoQMtw3pFGAts0MjIiIiOjuh69AKS6CdMwYikAdADPgenIkhIiIiywiXC6KwGDKvYMAtDZjEEBERkeU+0dIg3H7WZIZJDBEREdlGz5YG7TjTMhOTGCIiIrId1dKg4Ixfw8JeIiIiykpMYoiIiCgrMYkhIiKirMQkhoiIiLISkxgiIiLKSkxiiIiIKCsxiSEiIqKsxCSGiIiIshKTGCIiIspKlp/YW19fj5deegnHjh3D3/3d32HixInpa6tWrcLatWuhaRpuueUWzJo1y7qBEhERka1YPhMzduxYfOMb38CFF17Y4/WjR49i06ZN+OEPf4h77rkHTz/9NEyzf10tiYiIKPdZnsSMGTMGo0eP/sTrDQ0NWLBgAdxuN8rKylBWVoZDhw5ZMEIiIiKyI8uXk/rS0tKCyZMnp/9eXFyMlpaWXr92zZo1WLNmDQBg+fLlCAaDIzFEW3O5XIyDRRh7azDu1mHsreP02I9IEvPP//zPaG1t/cTrN954I8rLy3v9Hillv+9fU1ODmpqa9N/D4fCAx5hrgsEg42ARxt4ajLt1GHvrOCX2hYWFvb4+IknM3/7t3w74e4qLi9HU1JT+e3NzM4qKivr1vX39Y52GcbAOY28Nxt06jL11nBx72y4nzZ07F0888QSuuOIKtLS04MSJE5g0adJZv6+3GR8nevDBB/H973/f6mE4EmNvDcbdOoy9dZwee8uTmC1btuCZZ55Be3s7Hn30UZx//vn49re/jbFjx6KyshI/+MEPoGkabrvtNmia5XXIREREZBOWJzEVFRWoqKjo9do111yDa665ZoRHRERERNmAUxs5qnuhM40sxt4ajLt1GHvrOD32oqWlpf/bgIiIiIhsgjMxRERElJUsr4mhobv//vvh8/kghIDL5cL3v/99vPTSS3jnnXeQl5cHALjpppswe/Zsi0eaeyKRCH7zm9/g6NGjAIDbb78do0ePxooVK9DY2IjS0lLccccdjj6Marj0Fvtdu3bxuR9Gx44dw4oVK9J/P3XqFK6//npUV1fzmR9mfcU+Eok4+pnnclIOuP/++/H3f//3yM/PT7/20ksvwev14qqrrrJwZLnvySefxIUXXohLLrkEhmEgkUhg1apVCAaDWLp0KVavXo1wOIxly5ZZPdSc01vs33zzTT73I8Q0TXz3u9/F3/3d3+Gtt97iMz+Cusd+3bp1jn7muZxENEjRaBT79+/HxRdfDADQdR2BQAANDQ2orq4GAFRXV6OhocHCUeamvmJPI2fPnj0oKytDaWkpn/kR1j32TsflpBzxyCOPAAAuvfTSdLX6W2+9hbq6OkycOBGf//znOb2bYSdPnkR+fj7+4z/+Ax9++CEmTJiAW265BW1tbenTpYuKihAKhawdaA7qK/YAn/uRsmnTJixcuBAA+MyPsO6xB5z9zDOJyQH3338/ioqK0NbWhocffhijR4/Gpz71KVx77bUAgP/+7//G73//e9x+++3WDjTHmKaJI0eO4NZbb8XkyZOxcuVKrF692uphOUJfsf/0pz/N534EGIaBbdu24aabbrJ6KI5zeuyd/lnP5aQc0PkbUEFBAebNm4dDhw6hoKAAmqZB0zRccsklOHTokLWDzEHFxcUoLi5Od1uvqKjAkSNHUFBQkO643tLS0qNWiTLjTLHncz/8du7cifHjx6OgoAAA+MyPoN5i7+RnnklMlovH44jFYuk/7969G2PHjk1/oADA1q1bMXbsWItGmLsKCwtRXFyMY8eOAQD27t2LMWPGYO7cuairqwMA1NXV9dmpnQavr9jzuR8ZGzdu7LGcwWd+5Jwee6c/81xOynJtbW341a9+BQBIpVKoqqrCrFmz8O///u/44IMPAACjRo3Cl770JSuHmbNuvfVWPPHEEzAMA2VlZbj99tshpcSKFSuwdu1alJSU4M4777R6mDmpt9ivXLmSz/0w6/xlqXtsly5dymd+BPQW++eff97Rzzy3WBMREVFW4nISERERZSUmMURERJSVmMQQERFRVmISQ0RERFmJSQwRERFlJSYxRERElJWYxBBRxuzevRvf+ta3sH79eqxcuRIffvjhsL7f+++/j7//+79HOBw+49f94he/QG1tba/XTp06ha997WtIpVLDMUQiGkY87I7Ige6//360tbVB0zR4vV7MnDkTt912G3w+35Duu2/fPtxzzz14++23EQ6Hcd555w3qPi+99BJWrVoFXVcfUYWFhZg5cyauvvrqdJuNZDKJ3/3ud/j6179+1oZ399xzz6DG0ZdXX30V8XgcM2fOxM9//nN4PB4AqgXI0qVLsWTJEpw6dQrf+9738Pjjj8PlcuHJJ5/Exo0b0/+mc889FzfffDOmTp2a0bEROQmTGCKH+uY3v4kZM2agtbUVjzzyCFavXo0bb7xxSPfs/P5JkyYNeXyVlZX4v//3/8IwDBw/fhwvvfQSHnzwQXz/+99HUVERjh8/juuvvx4TJkwY8nsN1M6dO3HTTTfBNE0UFhZi+fLlkFKioaEBjz/+OCZNmpRObLq76qqrcOONN8I0Taxbtw6PPfYY/vmf/xmaxklxosFgEkPkcJ2zHJ1HlwPA6tWr8c4776CtrQ0lJSW44YYbUFFRAQD44Q9/iJMnT6a/Nh6P4zvf+Q6mTp2Kxx9/HAcOHEAymcS4cePwxS9+Md3LJRKJ4JlnnsHOnTvh8XhwySWX4Oqrrz7rD3Bd1zF27FjccccdeOCBB/DGG2/g85//PMLhMH77299i+fLlWL16NQ4fPoy77ror/X0rV66ElBK33norli9fjkWLFuGSSy6BaZp4/vnnUVtbC5/PhyuvvLLH+61btw6vvfYampubkZ+fj89+9rO49NJL09fD4TCOHz+OKVOm4MCBA+nXhRCYN28eAoEAPv744zMmV5qmYeHChfjtb3+Ltra29OwSEQ0Mkxgih2tqasLOnTsxbdq09GtlZWW47777UFBQgM2bN+Pf//3fMXnyZBQVFeEHP/hB+uvWrFmDN954A+PHjwcAzJo1C7fffjtcLheef/55PPHEE+mvf+aZZxCNRvHjH/8Y7e3tePjhh1FYWIhLLrmkX+PUNA3l5eXYtWvXJ64tXLgQr7zyCqLRKPx+P0zTRH19fY+kpvuYt2/fjn/4h3+A1+vFY4891uN6fn4+/uZv/gZlZWXYv38/Hn30UUycODGdlOzatQvTpk37RPJlmiYaGhoQjUbP2oTPNE3U1dVh1KhR6W7ERDRwTGKIHKqzcWg8Hse0adNw3XXXpa9VVlam/7xgwQKsWrUKhw8f7tGd+MCBA/jjH/+I++67D36/HwBw8cUXp69fd911uOeeexCJRODz+VBfX49/+Id/gM/nS8+ArF+/vt9JDKBmjXor4i0tLcX48eOxdetWLF68GHv37oXH48GUKVM+8bX19fX4zGc+g5KSEgCqeeG+ffvS1+fMmZP+89SpUzFjxgwcOHAgncTs2LEDs2fPTn9Na2sr7r77bgghUFJSgr/8y7/E6NGjcerUqU+89+uvv4633noLyWQSAPCVr3yFS0lEQ8AkhsihvvGNb2DGjBnYt28fnnjiCbS3tyMQCAAAamtr8cYbb6CxsRGASnRCoVD6e5uamrBixQp89atfxejRowGo2YUXX3wRmzdvRigUghACANDe3g7DMGAYBkpLS9P3KC0tRUtLy4DG3NLS0mcR78KFC7Fp0yYsXrwYGzZswMKFC3v9utbW1nQC0zmO7nbs2IGXX34Zx48fh5QSiUQiPbNimiZ2796Nm2++Of31nTUx/XHllVfixhtvhJQSR48excMPP4xgMNgjKSKi/uOvAEQON3XqVCxevBi///3vAQCNjY343e9+h9tuuw2PPPIIHn300R67jBKJBP71X/8Vl19+eY8fvhs2bEBDQwO+/e1v49FHH8VPfvKT9LW8vDy4XK50UgSoRGggtSCmaWLbtm248MILe71eWVmJffv2oampCVu3bkVVVVWvX1dYWIimpqYe4+iUTCbx+OOP46qrrsLPf/5zPProo5g9ezaklACAw4cPo7S0FPn5+f0ed2+EEBg7diwuuOAC7NixY0j3InIyJjFEhMsvvxy7d+/GkSNHEI/HASD9g3rdunU4evRo+mufeuopjB49Gp/97Gd73CMWi0HXdeTl5SGRSODFF19MX9M0DZWVlXjxxRcRi8XQ2NiIN954A4sWLTrr2AzDwMcff4x/+7d/Q1tbG6644opevy4/Px9Tp07FU089hVGjRmHMmDG9fl1lZSX+/Oc/o6mpCeFwGKtXr05fS6VSSCaT6aRrx44d2L17d/r66UtJQ/Hxxx/j4MGDg96GTkRcTiIiqASguroar776Ku666y5ceeWV+PGPfwxN07Bo0SJccMEF6a/dtGkTPB4PvvnNb6Zfu/vuu1FdXY1du3bhu9/9LoLBIK6//nq8/fbb6a+59dZb8cwzz+B73/se3G43LrnkEixZsqTPMdXX16OhoQFSShQVFWHGjBnp7dV9WbhwIZ588kksW7asz6+55JJLcPz4cfzoRz+Cz+fDVVddhb179wIAfD4fbr31VqxYsQKGYWDu3LmYO3du+nt37NiBL33pS2cK5Rn96U9/wv/8z/9ASom8vDwsXrwYNTU1g74fkdOJlpYWafUgiIjsrq2tDT/60Y+wfPnydL0PEVmLy0lERP0QiUTw+c9/ngkMkY1wJoaIiIiyEmdiiIiIKCsxiSEiIqKsxCSGiIiIshKTGCIiIspKTGKIiIgoKzGJISIioqz0/wO5v7UENKXaTQAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<Figure size 648x432 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.style.use('ggplot')\n",
    "fig, ax = plt.subplots(figsize=(9, 6), facecolor=\"#f0f0f0\")\n",
    "ax.set_facecolor(\"#f0f0f0\")\n",
    "sns.regplot(data=serieI, \n",
    "            x='Dívida/PIB',\n",
    "            y='POSITIVA')\n",
    "plt.ylabel('Avaliação positiva')\n",
    "plt.xlabel('Razão Dívida/PIB')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 113,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 648x432 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.style.use('ggplot')\n",
    "fig, ax = plt.subplots(figsize=(9, 6), facecolor=\"#f0f0f0\")\n",
    "ax.set_facecolor(\"#f0f0f0\")\n",
    "sns.regplot(data=serieI, \n",
    "            x='Inflação',\n",
    "            y='POSITIVA')\n",
    "plt.ylabel('Avaliação positiva')\n",
    "plt.xlabel('Índice de inflacão')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Others graphics"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 108,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 3 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 4 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 4 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 4 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 4 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 4 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 4 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 4 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 4 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "macro.plot(subplots=True)\n",
    "plt.show()\n",
    "\n",
    "\n",
    "pop.groupby('PRESIDENTE').plot(subplots=True)\n",
    "plt.show()"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "polls",
   "language": "python",
   "name": "polls"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.9.6"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 4
}