Happiness .ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 477,
   "id": "a82b1dc6",
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import pandas as pd\n",
    "from sklearn.model_selection import train_test_split\n",
    "import matplotlib.pyplot as plt\n",
    "import re\n",
    "import seaborn as sns\n",
    "from sklearn.preprocessing import Normalizer\n",
    "from sklearn.pipeline import Pipeline\n",
    "from sklearn.linear_model import LinearRegression\n",
    "from sklearn.compose import ColumnTransformer\n",
    "from sklearn.preprocessing import OneHotEncoder\n",
    "from sklearn.preprocessing import StandardScaler\n",
    "from sklearn.preprocessing import OrdinalEncoder"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 478,
   "id": "39c548cf",
   "metadata": {},
   "outputs": [],
   "source": [
    "setOne = pd.read_csv(\"2015.csv\")\n",
    "setTwo = pd.read_csv(\"2016.csv\")\n",
    "setThree = pd.read_csv(\"2017.csv\")\n",
    "setFour = pd.read_csv(\"2018.csv\")\n",
    "setFive = pd.read_csv(\"2019.csv\")\n",
    "\n",
    "income = pd.read_csv(\"income_per_person.csv\")\n",
    "lifeExpectency = pd.read_csv(\"life_expectancy_years.csv\")\n",
    "population = pd.read_csv(\"population_total.csv\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "1e7a5074",
   "metadata": {},
   "source": [
    "## Melting country stats dataframes and Merging"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 479,
   "id": "f62f9cbe",
   "metadata": {},
   "outputs": [],
   "source": [
    "population = population[['country', '2015', '2016', '2017', '2018', '2019']]\n",
    "population = population.melt(var_name = 'Year', value_name = 'Population', id_vars=['country'])\n",
    "\n",
    "lifeExpectency = lifeExpectency[['country', '2015', '2016', '2017', '2018', '2019']]\n",
    "lifeExpectency = lifeExpectency.melt(var_name = 'Year', value_name = 'Life Expectancy', id_vars=['country'])\n",
    "\n",
    "income = income[['country', '2015', '2016', '2017', '2018', '2019']]\n",
    "income = income.melt(var_name = 'Year', value_name = 'GDP', id_vars=['country'])\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 480,
   "id": "41678fbb",
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
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       "\n",
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       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Country</th>\n",
       "      <th>Year</th>\n",
       "      <th>Life Expectancy</th>\n",
       "      <th>GDP</th>\n",
       "      <th>Population</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Afghanistan</td>\n",
       "      <td>2015</td>\n",
       "      <td>61.2</td>\n",
       "      <td>1770</td>\n",
       "      <td>34400000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Albania</td>\n",
       "      <td>2015</td>\n",
       "      <td>78.0</td>\n",
       "      <td>11000</td>\n",
       "      <td>2890000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Algeria</td>\n",
       "      <td>2015</td>\n",
       "      <td>77.1</td>\n",
       "      <td>13800</td>\n",
       "      <td>39700000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Andorra</td>\n",
       "      <td>2015</td>\n",
       "      <td>82.6</td>\n",
       "      <td>46600</td>\n",
       "      <td>78000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Angola</td>\n",
       "      <td>2015</td>\n",
       "      <td>63.3</td>\n",
       "      <td>6650</td>\n",
       "      <td>27900000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "       Country  Year  Life Expectancy    GDP  Population\n",
       "0  Afghanistan  2015             61.2   1770    34400000\n",
       "1      Albania  2015             78.0  11000     2890000\n",
       "2      Algeria  2015             77.1  13800    39700000\n",
       "3      Andorra  2015             82.6  46600       78000\n",
       "4       Angola  2015             63.3   6650    27900000"
      ]
     },
     "execution_count": 480,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "stats = lifeExpectency.merge(income, on = ['country', 'Year'])\n",
    "stats = stats.merge(population, on = ['country', 'Year'])\n",
    "stats = stats.rename({'country':'Country'}, axis=1)\n",
    "stats['Year'] =stats['Year'].astype(int)\n",
    "stats.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "19336380",
   "metadata": {},
   "source": [
    "## Add year into happiness report dataframe"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 481,
   "id": "6a797d6a",
   "metadata": {},
   "outputs": [],
   "source": [
    "setOne[\"Year\"] = 2015\n",
    "setTwo[\"Year\"] = 2016\n",
    "setThree[\"Year\"] = 2017\n",
    "setFour[\"Year\"] = 2018\n",
    "setFive[\"Year\"] = 2019"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 482,
   "id": "299a3829",
   "metadata": {},
   "outputs": [],
   "source": [
    "#we want life Expectancy, freedom, generosity, GDP, perception of corruption, score"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 483,
   "id": "8d45008b",
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
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       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Year</th>\n",
       "      <th>Country</th>\n",
       "      <th>GDP</th>\n",
       "      <th>Life Expectancy</th>\n",
       "      <th>Freedom</th>\n",
       "      <th>Generosity</th>\n",
       "      <th>Corruption</th>\n",
       "      <th>Score</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2015</td>\n",
       "      <td>Switzerland</td>\n",
       "      <td>1.39651</td>\n",
       "      <td>0.94143</td>\n",
       "      <td>0.66557</td>\n",
       "      <td>0.29678</td>\n",
       "      <td>0.41978</td>\n",
       "      <td>7.587</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2015</td>\n",
       "      <td>Iceland</td>\n",
       "      <td>1.30232</td>\n",
       "      <td>0.94784</td>\n",
       "      <td>0.62877</td>\n",
       "      <td>0.43630</td>\n",
       "      <td>0.14145</td>\n",
       "      <td>7.561</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2015</td>\n",
       "      <td>Denmark</td>\n",
       "      <td>1.32548</td>\n",
       "      <td>0.87464</td>\n",
       "      <td>0.64938</td>\n",
       "      <td>0.34139</td>\n",
       "      <td>0.48357</td>\n",
       "      <td>7.527</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2015</td>\n",
       "      <td>Norway</td>\n",
       "      <td>1.45900</td>\n",
       "      <td>0.88521</td>\n",
       "      <td>0.66973</td>\n",
       "      <td>0.34699</td>\n",
       "      <td>0.36503</td>\n",
       "      <td>7.522</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2015</td>\n",
       "      <td>Canada</td>\n",
       "      <td>1.32629</td>\n",
       "      <td>0.90563</td>\n",
       "      <td>0.63297</td>\n",
       "      <td>0.45811</td>\n",
       "      <td>0.32957</td>\n",
       "      <td>7.427</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   Year      Country      GDP  Life Expectancy  Freedom  Generosity  \\\n",
       "0  2015  Switzerland  1.39651          0.94143  0.66557     0.29678   \n",
       "1  2015      Iceland  1.30232          0.94784  0.62877     0.43630   \n",
       "2  2015      Denmark  1.32548          0.87464  0.64938     0.34139   \n",
       "3  2015       Norway  1.45900          0.88521  0.66973     0.34699   \n",
       "4  2015       Canada  1.32629          0.90563  0.63297     0.45811   \n",
       "\n",
       "   Corruption  Score  \n",
       "0     0.41978  7.587  \n",
       "1     0.14145  7.561  \n",
       "2     0.48357  7.527  \n",
       "3     0.36503  7.522  \n",
       "4     0.32957  7.427  "
      ]
     },
     "execution_count": 483,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "a = list(setOne.columns)\n",
    "b = list(setTwo.columns)\n",
    "c = list(setThree.columns)\n",
    "d = list(setFour.columns)\n",
    "e = list(setFive.columns)\n",
    "\n",
    "totalSet = pd.DataFrame()\n",
    "allColumns = [a,b,c,d,e]\n",
    "\n",
    "for x in allColumns:\n",
    "    for col in range(len(x)):\n",
    "        if \"GDP\" in x[col].upper():\n",
    "            x[col] = \"GDP\"    \n",
    "        if \"freedom\" in x[col].lower():\n",
    "            x[col] = \"Freedom\"\n",
    "        if \"life\" in x[col].lower():\n",
    "            x[col] = \"Life Expectancy\"\n",
    "        if \"score\" in x[col].lower():\n",
    "            x[col] = \"Score\"\n",
    "        if \"generosity\" in x[col].lower():\n",
    "            x[col] = \"Generosity\"\n",
    "        if \"corruption\" in x[col].lower():\n",
    "            x[col] = \"Corruption\"\n",
    "        if \"country\" in x[col].lower():\n",
    "            x[col] = \"Country\"\n",
    "        \n",
    "            \n",
    "allSet = [setOne, setTwo, setThree, setFour, setFive]\n",
    "\n",
    "for x in range(len(allSet)):\n",
    "    allSet[x].columns = allColumns[x]\n",
    "    allSet[x] = allSet[x][[ \"Year\", \"Country\",\"GDP\", \"Life Expectancy\", \"Freedom\",\"Generosity\",\"Corruption\", \"Score\"]]\n",
    "    totalSet = pd.concat([totalSet, allSet[x]], axis = 0)\n",
    "\n",
    "totalSet.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 484,
   "id": "5747ddab",
   "metadata": {
    "scrolled": false
   },
   "outputs": [],
   "source": [
    "#merge data for prediction\n",
    "predictionSet = totalSet[[\"Year\", \"Country\", 'Score', \"Freedom\", \"Generosity\", \"Corruption\"]].merge(stats, how=\"left\", on = [\"Year\", \"Country\"])\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 485,
   "id": "29a0405a",
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "196"
      ]
     },
     "execution_count": 485,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "## Testing and Dropping NaN values\n",
    "predictionSet.isnull().sum().sum()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 486,
   "id": "444f7a0d",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "\n",
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       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Year</th>\n",
       "      <th>Country</th>\n",
       "      <th>Score</th>\n",
       "      <th>Freedom</th>\n",
       "      <th>Generosity</th>\n",
       "      <th>Corruption</th>\n",
       "      <th>Life Expectancy</th>\n",
       "      <th>GDP</th>\n",
       "      <th>Population</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2015</td>\n",
       "      <td>Switzerland</td>\n",
       "      <td>7.587</td>\n",
       "      <td>0.66557</td>\n",
       "      <td>0.29678</td>\n",
       "      <td>0.41978</td>\n",
       "      <td>83.5</td>\n",
       "      <td>57300.0</td>\n",
       "      <td>8300000.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2015</td>\n",
       "      <td>Iceland</td>\n",
       "      <td>7.561</td>\n",
       "      <td>0.62877</td>\n",
       "      <td>0.43630</td>\n",
       "      <td>0.14145</td>\n",
       "      <td>82.7</td>\n",
       "      <td>44200.0</td>\n",
       "      <td>330000.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2015</td>\n",
       "      <td>Denmark</td>\n",
       "      <td>7.527</td>\n",
       "      <td>0.64938</td>\n",
       "      <td>0.34139</td>\n",
       "      <td>0.48357</td>\n",
       "      <td>80.9</td>\n",
       "      <td>45800.0</td>\n",
       "      <td>5690000.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2015</td>\n",
       "      <td>Norway</td>\n",
       "      <td>7.522</td>\n",
       "      <td>0.66973</td>\n",
       "      <td>0.34699</td>\n",
       "      <td>0.36503</td>\n",
       "      <td>82.3</td>\n",
       "      <td>64000.0</td>\n",
       "      <td>5200000.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2015</td>\n",
       "      <td>Canada</td>\n",
       "      <td>7.427</td>\n",
       "      <td>0.63297</td>\n",
       "      <td>0.45811</td>\n",
       "      <td>0.32957</td>\n",
       "      <td>81.7</td>\n",
       "      <td>43100.0</td>\n",
       "      <td>36000000.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   Year      Country  Score  Freedom  Generosity  Corruption  Life Expectancy  \\\n",
       "0  2015  Switzerland  7.587  0.66557     0.29678     0.41978             83.5   \n",
       "1  2015      Iceland  7.561  0.62877     0.43630     0.14145             82.7   \n",
       "2  2015      Denmark  7.527  0.64938     0.34139     0.48357             80.9   \n",
       "3  2015       Norway  7.522  0.66973     0.34699     0.36503             82.3   \n",
       "4  2015       Canada  7.427  0.63297     0.45811     0.32957             81.7   \n",
       "\n",
       "       GDP  Population  \n",
       "0  57300.0   8300000.0  \n",
       "1  44200.0    330000.0  \n",
       "2  45800.0   5690000.0  \n",
       "3  64000.0   5200000.0  \n",
       "4  43100.0  36000000.0  "
      ]
     },
     "execution_count": 486,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "predictionSet = predictionSet.dropna()\n",
    "predictionSet.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 487,
   "id": "dfedba36",
   "metadata": {},
   "outputs": [],
   "source": [
    "X_train, X_test, y_train, y_test = train_test_split(predictionSet.drop(columns = [\"Score\"]), predictionSet[\"Score\"], test_size=0.4)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "5ef73239",
   "metadata": {},
   "source": [
    "## EDA"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "f0a0a834",
   "metadata": {},
   "source": [
    "### GDP vs Score"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 488,
   "id": "d560c428",
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:xlabel='GDP', ylabel='Score'>"
      ]
     },
     "execution_count": 488,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.regplot(x='GDP', y=\"Score\", data=predictionSet)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 489,
   "id": "00f046d8",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(array([159.,  65.,  61.,  57.,  47.,  60.,  22.,  23.,  29.,  20.,  15.,\n",
       "         23.,  18.,  16.,  13.,  24.,  16.,   4.,   3.,   5.,   3.,   2.,\n",
       "         11.,   1.,   4.,   0.,   0.,   0.,   1.,   1.,   1.,   2.,   5.,\n",
       "          0.,   0.,   0.,   0.,   0.,   3.,   2.]),\n",
       " array([   625.   ,   3509.375,   6393.75 ,   9278.125,  12162.5  ,\n",
       "         15046.875,  17931.25 ,  20815.625,  23700.   ,  26584.375,\n",
       "         29468.75 ,  32353.125,  35237.5  ,  38121.875,  41006.25 ,\n",
       "         43890.625,  46775.   ,  49659.375,  52543.75 ,  55428.125,\n",
       "         58312.5  ,  61196.875,  64081.25 ,  66965.625,  69850.   ,\n",
       "         72734.375,  75618.75 ,  78503.125,  81387.5  ,  84271.875,\n",
       "         87156.25 ,  90040.625,  92925.   ,  95809.375,  98693.75 ,\n",
       "        101578.125, 104462.5  , 107346.875, 110231.25 , 113115.625,\n",
       "        116000.   ]),\n",
       " <BarContainer object of 40 artists>)"
      ]
     },
     "execution_count": 489,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.hist(predictionSet[\"GDP\"], bins=40)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "f0066fda",
   "metadata": {},
   "source": [
    "### Life Expectancy vs Score"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 490,
   "id": "4caa1da2",
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:xlabel='Life Expectancy', ylabel='Score'>"
      ]
     },
     "execution_count": 490,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.regplot(x='Life Expectancy', y=\"Score\", data=predictionSet)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 491,
   "id": "5b490b71",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(array([ 2.,  1.,  2.,  0.,  1.,  1.,  2.,  0.,  0.,  5., 13.,  8., 17.,\n",
       "        13., 15., 20., 18., 10., 18., 12., 23., 22., 27., 27., 16., 20.,\n",
       "        29., 36., 40., 24., 44., 29., 31., 30., 17., 49., 43., 35.,  8.,\n",
       "         8.]),\n",
       " array([50.5  , 51.365, 52.23 , 53.095, 53.96 , 54.825, 55.69 , 56.555,\n",
       "        57.42 , 58.285, 59.15 , 60.015, 60.88 , 61.745, 62.61 , 63.475,\n",
       "        64.34 , 65.205, 66.07 , 66.935, 67.8  , 68.665, 69.53 , 70.395,\n",
       "        71.26 , 72.125, 72.99 , 73.855, 74.72 , 75.585, 76.45 , 77.315,\n",
       "        78.18 , 79.045, 79.91 , 80.775, 81.64 , 82.505, 83.37 , 84.235,\n",
       "        85.1  ]),\n",
       " <BarContainer object of 40 artists>)"
      ]
     },
     "execution_count": 491,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.hist(predictionSet['Life Expectancy'], bins=40)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "0cad2652",
   "metadata": {},
   "source": [
    "### Population vs Score"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 492,
   "id": "c1203811",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:xlabel='Population', ylabel='Score'>"
      ]
     },
     "execution_count": 492,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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Xds+i+SDw/5Rm0IwDv9Lm11sVR+DD79m96r5zRyDv+UzM5Lnj7VtbXDpjjFmdtgZ4VX0W2NPO12iFD79nN3fdfPmSx6RiLum81/CxXFFxBPoTEZ4YP8td7SikMcas0KZdyVptueAOcPXOAXrj7oL7hWBP16jjMJf3eOnN6TaU0BhjVm7TB/hIkz+B/XtH2doT59KhHq68oL+ykUjEEUQExwnuWS6DpTHGrJdNG+CF4M1fNtTcoGj9Rh0RVxCg6CuZgke24OH7SqzZGsMYY9qsq/PBLyUedeiNR/jorW9t+jnVG3Xc+plDHH1zBh8QpbI34FBvvPWFNcaYVdh0Ad4R2NoTY/dw35pSC6gqIkJMBBFQBU8VVeuiMcZ0hk0X4C8cSPL43Tet+TyzeY/BVIQzcwV8DSqObT1R5haZaVPPEpcZY9pt0wX4iZlc08cuFYR7Yy4np7JEHafSgp9MF7lsaPkumkaJyyyPjTGm1UI9IijLH7KA32QXSjkIT8xka4JwedcnEZkvRPlf9f1LOHBonKgb5K+xPDbGmHYJdYBfTW+3qja1Nd9yQXgmV+TCgQQRR/B8JeIIFw4kmG0iac3xyTTJaO2cestjY4xptVAH+GZI1VdHYHtvvKmW8nJBeGQwRcR1GB3qZWxHP6NDvURcZ9FslNVGBlNkCrV99UtlsjTGmNXo+gAfizillrjLyGCK7b2L53yvNjKY4sxcjvFTsxw5Oc34qVnOzOUqQXj/3lEKnpLOF1ENvi6VjbLaWp5rjDHN6vpBVs9XLhxI0p+MApDOFxe0lO9/9CgPfvMYc3mPnpjLB268hHeObuU7r5zFkcbJxPaNDXMvQVfOick0O1cwE2YtzzXGmGZ1fYAHeHMmS18iQqbgLWgp3//oUe577GUcCdIWZAoe9z32Muf3xxnqjTGTLZL3fGKuQ19dMrHqhU8rYVMkjTHroekuGhFJishb2lmYdrhwIIEqTGUKDPclFuR8f/Cbx0rB3cERp/QVXjuXZTpTqAT3ob540907S1ludo4xxrRKUy14EflfgU8DMeASEbkGuFdVb2tj2VpiLu/xtvP7uf+Oa3EdwRFhYiaLI8Ht2VyRiEPNClT1FQUKvuI6QtFXXj+XZVtvdM0belTPzgFIxSKk88VFN/s2xpjVaraL5uPAO4CDEOR5F5GL21Ok1prKFPjIPxuh4PkUGiwyTUZdMgUPVZ9ySplyqFdVfC+401flzGyef//enUxMZ5FSioKgogBBEGf++3IF4jrBv7Ljk2kGSuMB1WVodGVgXTnGmLVoNsAXVXWqmUU86yniQHGZfbddEcbPzDExmyUZjdATd0nFXHpiEVJxl+svGuDQS2cqx5eDuwD9iWip394n6jokIg5X7xpoaq57vfLPbntvnLNzOZLR+R99plBkqDfOa+cylcrhiZfP8Kmv/ZCIK/TGXN6YyvDbf/U8H7t1jJ+4fAiR+Smg9esBpOr1gtvl+2X+dqlSoubx2vJWpphKcwu4jGlGzdVy6eZya1qazfE03zgrf6+sND3Ucn/qsqollou/hgBuKe14qzUb4J8XkX8JuCKyG7gL+FbLS7NCsYhLcZncL9mizwOrWCGqwGS6QCLq0BOP4quSiEb4q2deIxWP0BMrVRTxCKmYSyoW3BeLOA1/UeU/0PfvGeG+x15CtUgi6pAt+BR95ef2jJCrusT43LdewRGIuw6+Qsx18HyPBx8/xtsu6F/x+2mV5SqO1VrqQ7jWc9c/f7HXqg4KNc+vqwibLVc78841+zNZ7r1C7fttZZmrT2VJ+Ja2czBFLLJxAf6DwG8DOeB/AH8P/KeWl2aFIs7yP5CoG3SVeL7ia9CnXmhyUw4FMgWfTCG4TJjJFrn/sZeXfI7rSCn4B1cIldtVlcGVF/Tzg9dneHM6x9ZUjPdeeR59yQivnpkLKoq4y+tTabYko8zmikym85WriNlsoamyt0v5g6qV/2pudKluf3+mW8lyNauIuMDfq+rN7S7Mnj179PDhw00f/7Z7vrroPqlllw/3MpcvcnYuT67ok4y6/Natb+WKC/v52Je+z4snZ5Z9HVfgvP4EW1JR0jmP2XyRTN5b9rXXqno8oLoqu/6iQS7alqp0M5WvHoIKpXRFUbnKiNSMARhjNt53xs/yhe8e543pDOf3J/k3776Um6/YsapzichTqtpw7+tlW/Cq6olIWkS2qOrUqkrQJs0E2KMTs5XbEYFsweMPDr7Mh27azdl0nqi7eIs+4gRXCUN9CYq+8ss3XMw7RrdWHvdVSec9MnmPuXyRuVyRdCnwP39iiifGzzCVLZCKRrhke4psweeliVmyBQ8lOHfUdcgVPfwGRdBFbh9+dZLDr04u+97LEhGHVKUrqbpCKF1ZlO+L141R1FUUtluVMWv3nfGz3PfYS0QcwRX4wckp7vz8U7zlvD7uvmWspRMpmu2iyQLfF5GvA3PlO1X1rsWf0nmKCjFXSEYdvvzsa1y0tQdUOTWbXxBggwSRwvbeOKlYhEyhyJ8fPs67LtuOr0F3jyNCbzxCbzzCEPNpgr8zfpZvjZ8h4ggXbElUAnvB88kXvco+sEG/vsM9P/VWrto1EFQUuSJz+aCi+O0vfZ9cVeVTbodHXeH6i7ZWjkvni8zlvErKg3rZok+2mOfs3IKHVqQ8vbOmoqi+gqiqEILuqPkri+pKJbHIOIUx3e4742f5vb/9AZmChyuU9pIIAv2x03MtTxvebID/29K/0Ct4iucrr5/L8Hvvu5J7HnmB4T5hJlsM9lUlGGhKRh2G+xP0JYIpjVE3yunZHLu2zac5KPfr+6r4PpXbf/n0CeIRh2TURYGeuMPETJZcUYm5VaPlvjKXL/Lnh0/wjy/dRjLqsrUnVjl/xHXw1MN1nKrXDPrif/9nrmz4/vJFn3R+/kpi/qqiyFzpvuoKofaY+dv1ydDKP7upTIGpzNrGARxhwbhE7bjFwquH8pVFdUWRjLrW/WRCo9xyzxY8XIfKtG1HwHEET7WSsXZdA7yq/omIxIDLS3f9UFU3drRvlZRgleplQz0Nc8K8c3QrD37zGOm8x6mZHKrQn4w2zPboOoLbYMrUG9PBKtXqVmp5OmfeUxzRyopZz1dOz2a5YCCJr1qqNMD3lXjEIVfwKHo+vs5308SXGDeJRRxikRgDa0xM6flaGmcIKobqimI255GpVBjlyqJ8u6qyKI1V1F8d+QqzuWIw3XQFG7A0kozWjj3Udj1FSFbd16gSKY9jRF3rfjLt9YXvHifiCLGIQ9FTyp/ogq/gB4G+6PktTRve7ErWfcCfAK8Q9BSMiMgvq+qhlpVknZWDb3U+mXIagZ64Sybvkfd8Xp/KkCt6xCJu09keRwZTTMxkK6tVT05l8KqinK9Q8HxcR4i4DiNbe0jUpSYGeMuOfo6cnOJculhZhOU4QVfTq6fn+InLh/BKlUJ1xeCr4pWuKoKvStFf2X6xriP0JiL0JtaWrkhVyRb9IPDnqsYqCl7l+3TeI52rv8JYeFVRbDBQkSkEVxtnyK+pnFFXFg5aV3VBBVcbtY/VVBSlSiVu3U9mEW9MZ+hPRBhMxZiYyS543BGpND5bpdlP7/8JvFdVfwggIpcDDwHXt6wk62ixjTnKaQS2JBPEIy6nZnJki0GQ+cTPXtX0ZdP+vaPc88gLpPNFip7PqdmFwUeBoq8MpKKLVhz7946y//NPEXGD1bCqQffR1p4oDzx+jHe/9bwVZYvzfa1UCL4GQd8vVQ41FYXfug3ERYRk1A1y668tywP5os9srthwULthV1TVeEb1MbkGq+MKnnIuU+BcC7qfeqquIOq7mhZUFPHaK4nyc5IxF8cqiq5yfn+S187NMZvz8Or+BKNOqZvG15Y2EJqND9FycAdQ1aMiEl3qCZ3KkaBve7gvseCx45NpXIHxU7OVJGM7B5L4urJBj+qun6d/HMx2iZRy2tT7pRsuWvTc+8aG6UtEmMkUyJXm4scjDjHXWdVlnOMIDkKDi4WG5q8M5r+Wg399JbHSK4TViEUctkZisMYGTtHzK11I5VlQ8xVHUBFk8sF02PLt6uPLVx6ZvLdghryvwXqJmWyRYNnI6pUHsxtdWVSvsai5yqgfx4i5RKz7qSNcO7KF7712rhSD5vvgIw6VWXU7+uOrWim/mGYD/GER+W/An5W+/wXgqZaVYh2psujmGn3xCEffnKn0dxc8j7mzGUYGkyt+nXLXz57/9HXys/lKcK+e256IODXphxsZ6o1zLl0orZANyv/auSy7h9fYHG5CfR6d5Xi+UvR9fJ+ar+UKoejNVwwbKeI69Cedyh4Bq+Wrki14NQPWjSqKuUaD2lVdVHO5YsNpsuUrj9Nr7H6KR5yGq64XTpNduCivusKIuu1ZTr9ZPHN8iq2pKHP5IP1JeSvnaGlnOEeEdL7YsPG5Ws0G+H8N/AZBigIBDgF/1LJSrAOnFFl7E5EFKYPLZrIFGk2Jf+1choNHJlY8sn3wyAQz2SKOQ+WSrHrh0nn9y6cfrrSKK0k26u7vIEGFUL48WPwyodxVtOCKoHx/dVdSC7uLWs2R8rTRCFRNk10pVSVf9CuD1vUVRU1XU/W4RWXAu3y78TTZXNEnV/SZTK+t+yniyMKKoqpSaHy1ERxfXVEkoptznOKN6QyDPTG29gTvfTZXLM2u84Od3RrsV7FWzQb4CHCfqv5fUFnduvq/6HUmwHBfnFjEXTS4A7w53fiS2ldWNXXpwKFxBlNRzszlqb+YH+qNLdpVVG0273HhQILTs/lKt9GO3jhzbV5F207lrqKVqO4uKvqK5wWVQNH3K4+V/4WNiBCPusTrpsmuRqHc/bTg6qFq8LpQ283U6Gqj0TTZoq9MZ4tMZ9fWheAIpdlNCyuKBesmlriySMbCNU32/P4kZ+Zylb2ee+MR8sUomYLPdKbAyNaelmeMbTbAfwO4GSgvC00CXwPetdSTROQVYAbwCDJSNlxO225KELx/8+bdS/7wiku0ElfT5318Ms323jjxiMub01myRb+SpKsvGW2qti7PyBkdmu+SafVlXBg0212kOj9oXH110KiCKPrLpCINoajrsCXpsGWN3U+er2QKtYPX1QPVDSuFBVNqg+c1miY7lwu6ttYqEXWWWDdRO3V2o6fJvv/tQaLBTMGrJBqMRlw+8t4xfvb6nW1ZKd5sgE+oamXNv6rOikizM63fraqnV1605cUjTsMZEY0o8KdPvspVOwcWDfKuBFMQG6mfA9+McnDuT0bpT0aZyRY4OZVFgeG+RFO1dfWMnHLuetuge3EiQsSV5vNge0E2T6+qe6joL+wm6sbKYCmuM79Key3K02TTudKVRKFYk89pruZKYukFeI0mKWQLPtlCnjMtWKXd7mmy7xjdyofYzRe+e5yT0xl29Cd5/9tHatKftFqzv705EblOVZ8GEJE9QKZtpWrSUE+UE1PNz1SYzS29c9JlQ7388M3ZBTMjIg6rCqj1wdl1hOH+hdsGLsU26G6viOsQaXJWUdGrGjCumj1UfYWwHrOJwqR6muwaN0OrrNJeMKhdGuieq9xuPJhdnjqb3eBpslePbOGd8W30xFwyRY/vvnKW07M53rKjf81XXvWaDfAfBr4oIq8TNIYvAH6+iecp8DURUeCAqj5Qf4CI3AncCbBr164mixM4s8JBo4KnS3a1fPTWt/KRh59jOlOg4Glp6hLcddPSXTuLaVVwXu3m3qa1Iq7T1AemchWgtVcG9V1Hvt8Zs4rCopWrtKtXaC86VlG3Irv+aiOda+002Qd/aQ83v+28tb25Okv+vYrI24HjqvpdERkD9gM/C3wVONbE+f+Jqr4uIsPA10XkSP3q11LQfwCCdMErKXw5T3uzPF+X7GrZNzbMp2+/uqWtZQvOm4/jCLEVDP6pzl8J1K8tqL9KsMpg7VxH6EtEK3mmVstXJVfwl150t8jVRvVjc3kPz1d61tgd1shyZzxAMLgK8E7gtwg2/7iGICjfvtSTVfX10tcJEfkywb6uG5reYLmullYGZNtT1TRDRIi6zS1A06ouourBYq+qIrBuovXhiJAsrTre3ru2abLDfQmSsSb7CldguQDvqurZ0u2fBx5Q1b8E/lJEnl3qiSLSAziqOlO6/V7g3rUWeC1caV0azuWU89pEXWEgGWViJtvyVKBm86kMIi8TC8qLzjxfKxlUKxVBhyw4M4HyNNl2rDheNsCLSERVi8B7KPWVN/nc84Avl0aUI8D/UNWvrrqkLRCPug1b1UDLW9rlvDblhGOpWIR0fulBXmNapXbRWWPV3T8F3y9dDdRWBmFcV2DmLRekHwL+p4icJpg18ziAiFwGLLm7k6qOA1e3opCLKS/db+pYghZ8fav63z38HApsSUZb2tI+PplmoG5EPBl1W5oK1Ji1qB4rSC6y8rh6fKB6LKAmFYVVBB1ryQCvqr8vIt8Azge+pvMdew5BX/yG2pqMNj2TRgmWbNe3ql+bzIDA+VuSlfta0dKuTxkMNMwpb0wna3Z8oHpsoHYx2cLVxzY+sH6a2ZP1yQb3HW1PcVYmFY80FeDLCb4KnlaWCZcVfb9mYcJ0psDp2RyvnElzxwNPrrq7xhYomc2k2bEBWJiUrtG6Ahsobo3Wz8tZRxNN7gakBJccPkHKgelssbQXYvCg6yjjp2bJFn18XxEJMj2upbvGFigZ09hKktJVrzKuzBiqyk5aXmtgGgt1gPdWsHy8fOS5zHyipPLfhe9DoSp5l2qQCKjZ7prFpkPaHHhjVq/Z9QTV3UO1lYF1D4U6wMdcl6K/+oRF1bnZ601li5y3ZfmBUZsOaczGakX3UH03UbdUBKEO8Km4S7pBWtNmVf8K62fk5Ev5KpYbGD1waJx80ePMbLGSzrcvEbHpkMZ0oGa7h2rzC/l134dnZXGoA3zTcySbVN+iT+eLyw6MHn1zmulsEfUVH5jzysuV15a0yBizcWrTUy8/TtCp+xSEOsCfXeMONdXq6wrXaS6lb6GyKrDqXMBszl/VLlDGmPBY7ThB/ayhdu1bEuoAv9ZK0ZH5c5Rb7wL0xV3uv+O6poJzLOKg2dI5qi4BHFndLlDGmM7QylxSKxknaKVNu926ANt6Ypy/JU7UKd1BsJXYB36i+V/k7uE+HCk9XYMgH3GFeMSxVavGhFR58sTETLZm8sTBIxMbXbQVCXULfi0UODWbpy/uMpCK0Z+MVhYk/dmTr/IX3/0xp+aCLqDR7T3cfctYw6C/f+8oT/94El8V1xFUg+6eLamorVo1JqS6JZfUpm3Bl+WKPv3JKKlYBBHB85Wzc3lem8qhpXmzL03M8u8efq5h7b1vbJjf2HdpsDVZwS/NvlFbtWpMiB2fTC9Y9R7GXFKbPsDn69IXnJrJ4WnQwi+WU62qci6d58Ch8YbnuGrnAKmoiyPzz8uvYfqmMWZjjQymyNR9hsOYSyrUAT7eol3Iz8zNpzzIe/OrY/1SoFeFgg8vvTnd8Pmf+MqLpAs+UcchEXGIOg7pgs8nvvJiS8pnjFlf+/eOUvCCrf1Utakp050o1AHeXWT38pWIOMLZuULlF7nUOfNe42k7x86kcSSYMiUiOI7gSHC/MSZ89o0Nc+9tVzDcl+DkVIZTM7lKH3yYBlpDHeDz3tq7QQZTEfriLsN9CaYyBYb6Gm+9JQRTIo0xm8O+sWH27x0lFY8y1BdnR38idLNpQh2xhLW34KcyRXaf189Dd97A43ffRG88suhZt/fEGt4/ur0HX4NNeJVgVZuvwf3GmPCqnk0jEnyNurLoeFynCXWAbz6X5OLyVf1qB49McHRituGqMgXOzOUb1tx33zLGYCqKAEXPR4DBVJS7bxlrQQmNMRsl7LNpQh3gW5HfQZjP+liurSOOs6AVn4g49CejDWvufWPDfOr2q7l21yDnb0ly7a5BPnX71aGaL2uMWajRbJrTszmmMgVu/ORj3PHAkx3dXbNpFzqVVY+pHp9Mc15fnNensgvSCBd85eRUlql0vuF5LPe7Md2nfme207M5Ts3mGe6LhSI9eKhb8K02Mpgi4jpcsCW5oJsm6gh5z2cm53V0jW2MaZ3q2TRTmQLpvMdwX4ztvYlQ9MmHOsC3IgNbdRbJ8tzXiCuMDCYr3TQxV0qJyIStPY27aYwx3Wnf2HBlEkZ/Msq2ntqZdp3cJx/qAP+W8/rW9HxHoC9R20uVijqcmMxwcjqHIxAvBfeII1wwkGBbT7xjf5nGmPYK2wrXUAf4tcxSibrBoqQP3HgJMJ89ruAru4d72TmYJOI6bO2NMbajn9GhXvoS0Y7+ZRpj2qt6het0Js9LEzO8cibNuXTjGXYbLdQBfqWDGtU9OhFH+NBNl3HXzZcDtfNdZ7JFTk5lKXg+J6dznJrJhnq5sjGmNcp98lFHOHEuAwo7BxLkPb8jF0CFOsCvVLm73RW4eFtPJbjD/HzX6UyB16cyFD0l6goOMJkucHIqw3Bfgntvu6IjR8uNMetj39gwgz1xLt7Ww+7z+uhPxjp2sDXU0yRXW1t6Ci9PzNbcNzKYYmImy+nZHA5BPhlfIRF12LElwXBfgofuvKEVxTbGhNzxyTQDyWjNfZ042BrqFvyBQ+P0xle3B1ahbpFUuW8tV/RBgnQDqjDUF+/IX5wxZuOEZbA11AH++GSabYvkh1mpct9aKuZS9LUya8YGVo0x9cKSTjjUAX5kMMWbM7kWpBwL7Bsb5v73X8uFAyl2bEnQG4907C/OGLNx6hdADfcluP26CzlwaLyjUhi0PcCLiCsiz4jI37T63OVadDVS0cZdO41+cTawaoypV70Aav/eUR5++rWO26R7PQZZPwS8CPS3+sT7xoZJRR1mcivPC//r/3TxFrnllTHGrESnbtLd1ha8iOwEfgp4sB3nv//RoysO7iLwM9ecXzNF0hhj1qJT0wq3u4vmM8C/Z4nU7SJyp4gcFpHDp06dWtHJ//Dgj1Z0vOsIv/me3fyX91+3oucZY8xSOnVWTdsCvIj8NDChqk8tdZyqPqCqe1R1z9DQ0IpeI1dsfssPBxjui/Hw069teL+YMaa7dOqsmna24P8JcJuIvAJ8AbhJRD7fxtdbkusK23sTHbnazBgTbp06OaNtg6yq+jHgYwAisg/4iKr+YrtebzkFT5nOFOhLRDa8X8wY0306cXJGqOfB961gFasQbLXVCf1ixhizHtYlwKvqQVX96Vafd0ui+QsQBTJ5ryP6xYwxZj2EugU/Mdt4f9TF+IDv+/zOXz/fMSvNjDGmXUId4POrWMU6MZPrqJVmxhjTLqEO8KuR95SZbLFj8zcbY0yrhDrAu6vIMlYebIXOWGlmjDHtEuoAv3u4F2eFQV6BubzH+KlZTs/mbEaNMaZrhTrAf/TWt9IbW/mGHwLkPZ9Ts3neObq19QUzxpgOEOoAv29smAsGkit+ngAx12G4L8YT42dbXzBjjOkAod6TFeDEueb70IUg4Vg84jA61IuqWh+8MaZrhboFf/DIBHO5FSQccyDiCHkveI6tajXGdLNQB/gDh8ZXNMjq+VDwfWKu0zHZ3owxpl1C3UVzfDJNxBG8FSx48n1IRh2G+xLs3zvaccmBjDGmVUId4EcGU7xxLtP08Y7A1lSUw//hvW0slTHGdIZQd9G8c3QrzTTeHSDqCsN9cXaf1/KtYY0xpiOFugXf7BTHZMylLxEhFnGtz90Ys2mEOsAfb3KK49aeGDsHU9bnbozZVELdRTMymKKZSTS98YgFd2PMphPqFvz+vaP84I0ppjLFJY978eQMv/Znh/npf7SDk9N5jk+mGbEWvTGmy4W6Bb9vbJj7fv5apIlmfMFTvvzsG7xyZtbywRtjNoVQB3gIgvy2VLTp48/O5jl2eo4fn00zMZPlE195sY2lM8aYjRP6AH/wyARn5gpLHlPdwM95StFTXBF8X3np1Ky14o0xXSn0Af7AoXGWmwpf/bgAjiOIBP+ijmO7OhljulKoB1khmCopsGSQL7fgtXQ7V/TwNbi9vTdqGSWNMV0p9C34kcHUognHIk7wDwmySEYdwYdKcHcdYTJdpGcVm4YYY0ynC32A3793FEQWvJEtcZeBZJQLBlKMbu/hLTv6KrNtIg7Eow5uqWaQZqbhGGNMyIQ+wO8bG+by4V5iEYeoK/TEXC7elmJ7f4K8p0RdIRWLICIoQXD3FTxfiTjChQMJZnNLz6M3xpgwCn2AB7j7ljGG+xPs2priku09uI5Q8JRYxCEZne9+ibkOjgiuI4zt6Gd0qJeI69imH8aYrtQVAX7f2DD33nYFw30JpjIFhvsS3HvbFewe7iNT8CrHDfXF8TXoe1dV2/TDGNPVQj+LBuD+R4/y4DePMZsrIiJMpnMcODTOO0e38vDTr5HOF0lGXVxHGExF2dYTYypTsARkxpiuFvoAf/+jR7nvsZcBxVdAldmc8uIbU7x2LsPt113IE+NnOTGZZudgiv/wU2+zgG6M2RRCH+Af/OYxHAn2WxUAAVWYzhbZ1hvnifGzPHTnDRtdTGOMWXdtC/AikgAOAfHS6zysqr/b6teZy3tEHCiWVzGVVjz5Cm+cyzCVWTqNgTHGdKt2DrLmgJtU9WrgGuAWEWl5U7on5gYLl0rBvXpFa8FXZrJFyzVjjNmU2hbgNTBb+jZa+tfEDqor84EbL6kE+OqTl9/YYCpquWaMMZtSW6dJiogrIs8CE8DXVfXbDY65U0QOi8jhU6dOrfg17rr5cj5002X0xGp7m5Ixlwu2JNneG7dcM8aYTamtAV5VPVW9BtgJvENErmxwzAOqukdV9wwNDa3qde66+XKuOL+v5j7f9+lPRskUPFvIZIzZlNZloZOqngMOAre04/x3HPgWTxybrLkvU1R++MaULWQyxmxabQvwIjIkIgOl20ngZuBIO16rPriX5X2497YrbN67MWZTauc8+POBPxERl6Ai+QtV/ZtWv8hyM2QsuBtjNqu2BXhV/R5wbbvOX2YzZIwxprHQJxsr7+jUSDwS+rdnjDGrFvoIODKYIh51FgR5Aa7bNbgRRTLGmI4Q+gC/f+8ovfEIriPE3OBfxBG298Zs9owxZlMLfYDfNzbML91wEVFXyHtKwVPO35LgU7dfbQOsxphNLfTZJA8emeDhp1/jgoEkyahLpuBR8FqeEcEYY0In9C34A4fGa/ZdTcUiRF2x2TXGmE0v9AH++GS6Zt9VgGTUtfwzxphNL/QBfmQwVbPvKmD5Z4wxhi4I8Pv3jlLwgg20bSNtY4yZF/oAv29smHtvu4LhvgRTmQLDfQnLP2OMMXTBLBoIgrwFdGOMqRX6FrwxxpjGLMAbY0yXsgBvjDFdygK8McZ0KQvwxhjTpUS1c/K2iMgp4NVVPn07cLqFxWmXsJQTwlPWsJQTrKztEJZyQnvKepGqDjV6oKMC/FqIyGFV3bPR5VhOWMoJ4SlrWMoJVtZ2CEs5Yf3Lal00xhjTpSzAG2NMl+qmAP/ARhegSWEpJ4SnrGEpJ1hZ2yEs5YR1LmvX9MEbY4yp1U0teGOMMVUswBtjTJcKVYAXkVtE5Ici8rKIfLTB4yIi95ce/56IXLcR5SyVZbmy/kKpjN8TkW+JyNUbUc5SWZYsa9VxbxcRT0RuX8/yVb3+suUUkX0i8qyIvCAi/3O9y1hVjuV+/1tE5P8VkedKZf2VDSrnH4vIhIg8v8jjHfGZaqKcnfR5WrKsVce1//OkqqH4B7jAj4BRIAY8B7yt7pifBL4CCHAD8O0OLuu7gMHS7Vs7uaxVxz0G/B1weyeWExgAfgDsKn0/3Kk/U+C3gE+Wbg8BZ4HYBpR1L3Ad8Pwij3fKZ2q5cnbE56mZslb9jbT98xSmFvw7gJdVdVxV88AXgPfVHfM+4E818CQwICLnr3dBaaKsqvotVZ0sffsksHOdy1jWzM8V4IPAXwIT61m4Ks2U818CX1LVHwOoaieXVYE+ERGglyDAF9e3mKCqh0qvvZiO+EwtV84O+jw18zOFdfo8hSnAXwgcr/r+ROm+lR6zHlZajl8laCVthGXLKiIXAj8D/Nd1LFe9Zn6mlwODInJQRJ4SkV9at9LVaqasfwC8FXgd+D7wIVX116d4K9Ipn6mV2MjP07LW8/MUph2dpMF99XM8mzlmPTRdDhF5N8Ef5I1tLdHiminrZ4C7VdULGpwboplyRoDrgfcASeAJEXlSVY+2u3B1minr/wI8C9wEXAp8XUQeV9XpNpdtpTrlM9WUDvg8NeMzrNPnKUwB/gQwUvX9ToLWz0qPWQ9NlUNErgIeBG5V1TPrVLZ6zZR1D/CF0h/jduAnRaSoqn+1LiUMNPv7P62qc8CciBwCrgbWO8A3U9ZfAT6hQYfsyyJyDBgDvrM+RWxap3ymltUhn6dmrN/naaMGIlYxcBEBxoFLmB+4uqLumJ+idkDoOx1c1l3Ay8C7Ov3nWnf859iYQdZmfqZvBb5ROjYFPA9c2aFl/Szw8dLt84DXgO0b9DdwMYsPXnbEZ6qJcnbE56mZstYd19bPU2ha8KpaFJF/A/w9wQj0H6vqCyLy66XH/yvBiPRPEvyi0wStpE4t6z3ANuCPSjV5UTcgI16TZd1wzZRTVV8Uka8C3wN84EFVXXKq2kaVFfg94HMi8n2C4Hm3qq57ylsReQjYB2wXkRPA7wLRqnJ2xGeqiXJ2xOepybKuX1lKtYgxxpguE6ZZNMYYY1bAArwxxnQpC/DGGNOlLMAbY0yXsgBvjDEbpNnEZKVjLxKRb5QSqh0UkWXTMViAN6FXysj3rIg8LyJfFJFUi89/UESWnHInIh+ufl0R+TsRGWhlOUxX+hxwS5PHfpogL9BVwL3Af17uCRbgTTfIqOo1qnolkAd+fQPK8GGCxVUAqOpPquq5DSiHCRFtkJhMRC4Vka+W8ik9LiJjpYfeRrCQD+AfaJwUsIYFeNNtHgcuE5GtIvJXpcvZJ0vL2BGRj4vIn4nIYyLykoj8Wun+fSLyN+WTiMgfiMi/qj+5iHxWRA6Xcrj/x9J9dwEXAP8gIv9Quu8VEdleuv1vS1cXz4vIh0v3XSwiL4rI/10619dEJNnWn4wJiweAD6rq9cBHgD8q3f8c8C9Kt3+GIBvptqVOFJqVrMYsR0QiBLnAvwr8R+AZVf3nInIT8KfANaVDryJYdt8DPCMif7uCl/ltVT0rIi7wDRG5SlXvF5F/C7y7fjWqiFxPsPrzHxOsWP22BBuRTAK7gTtU9ddE5C8IPryfX9WbN11BRHoJctt/sSoRWbz09SNAueFxiCC9xZIppi3Am26QFJFnS7cfB/4b8G1KrR1VfUxEtonIltIxf62qGSBTanG/AzjX5Gv9nIjcSfDZOZ/gsvl7Sxx/I/BlDRKgISJfAn4CeAQ4pqrlcj9FkL/EbG4OcE5Vr6l/QFVfB34WKhXBv1DVqaVOZgHedINM/QdCGudh1bqv1fcXqe2yTNQ/WUQuIWhFvV1VJ0Xkc42Oq3/aEo/lqm57BCmOzSamqtMickxE/jdV/WLp7/gqVX2u1OV3VoN9Az4G/PFy57M+eNOtDgG/AEH/OkEa4XKu9feJSKLUf7kP+C7wKvA2EYmXWvrvaXDOfmAOmBKR8wi6g8pmgL5FyvHPRSQlIj0EfaePr/G9mS5RSkz2BPAWETkhIr9K8Hf7qyLyHPAC84Op+4AfishRggykv7/c+a0Fb7rVx4H/LiLfI8iC+MtVj30H+FuCFLO/V7r0pdQP/j3gJeCZ+hOWWlHPEHzoxoH/r+rhB4CviMgbqvruquc8XWrpl/O8P6iqz4jIxa14kybcVPWORR5aMHVSVR8GHl7J+S2bpNlUROTjwKyqfnqjy2JMu1kXjTHGdClrwRtjTJeyFrwxxnQpC/DGGNOlLMAbY0yXsgBvjDFdygK8McZ0qf8f2G98JjdqvfoAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.regplot(x='Population', y=\"Score\", data=predictionSet)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 493,
   "id": "19d53a1b",
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(array([530.,  96.,  32.,  13.,  10.,  14.,   1.,   5.,   1.,   4.,   0.,\n",
       "          0.,   0.,   0.,   0.,   0.,   0.,   0.,   0.,   0.,   0.,   0.,\n",
       "          0.,   0.,   0.,   0.,   0.,   0.,   0.,   0.,   0.,   0.,   0.,\n",
       "          0.,   0.,   0.,   2.,   2.,   1.,   5.]),\n",
       " array([3.30000000e+05, 3.60717500e+07, 7.18135000e+07, 1.07555250e+08,\n",
       "        1.43297000e+08, 1.79038750e+08, 2.14780500e+08, 2.50522250e+08,\n",
       "        2.86264000e+08, 3.22005750e+08, 3.57747500e+08, 3.93489250e+08,\n",
       "        4.29231000e+08, 4.64972750e+08, 5.00714500e+08, 5.36456250e+08,\n",
       "        5.72198000e+08, 6.07939750e+08, 6.43681500e+08, 6.79423250e+08,\n",
       "        7.15165000e+08, 7.50906750e+08, 7.86648500e+08, 8.22390250e+08,\n",
       "        8.58132000e+08, 8.93873750e+08, 9.29615500e+08, 9.65357250e+08,\n",
       "        1.00109900e+09, 1.03684075e+09, 1.07258250e+09, 1.10832425e+09,\n",
       "        1.14406600e+09, 1.17980775e+09, 1.21554950e+09, 1.25129125e+09,\n",
       "        1.28703300e+09, 1.32277475e+09, 1.35851650e+09, 1.39425825e+09,\n",
       "        1.43000000e+09]),\n",
       " <BarContainer object of 40 artists>)"
      ]
     },
     "execution_count": 493,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.hist(predictionSet[\"Population\"], bins=40)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "6f1b460a",
   "metadata": {},
   "source": [
    "### Freedom vs Score"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 494,
   "id": "60d09e5c",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:xlabel='Freedom', ylabel='Score'>"
      ]
     },
     "execution_count": 494,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.regplot(x='Freedom', y=\"Score\", data=totalSet)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "2646d2e4",
   "metadata": {},
   "source": [
    "### Generosity vs Score"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 495,
   "id": "8bda3eee",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:xlabel='Generosity', ylabel='Score'>"
      ]
     },
     "execution_count": 495,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.regplot(x='Generosity', y=\"Score\", data=totalSet)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 496,
   "id": "dd59954d",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(array([ 8., 16., 28., 42., 36., 55., 46., 48., 75., 59., 56., 56., 54.,\n",
       "        33., 21., 34., 17., 19., 14., 11.,  7.,  5., 14., 11.,  5.,  0.,\n",
       "         2.,  4.,  2.,  1.,  0.,  0.,  0.,  0.,  0.,  0.,  0.,  1.,  0.,\n",
       "         2.]),\n",
       " array([0.        , 0.02095188, 0.04190376, 0.06285564, 0.08380752,\n",
       "        0.1047594 , 0.12571127, 0.14666315, 0.16761503, 0.18856691,\n",
       "        0.20951879, 0.23047067, 0.25142255, 0.27237443, 0.29332631,\n",
       "        0.31427819, 0.33523006, 0.35618194, 0.37713382, 0.3980857 ,\n",
       "        0.41903758, 0.43998946, 0.46094134, 0.48189322, 0.5028451 ,\n",
       "        0.52379698, 0.54474885, 0.56570073, 0.58665261, 0.60760449,\n",
       "        0.62855637, 0.64950825, 0.67046013, 0.69141201, 0.71236389,\n",
       "        0.73331577, 0.75426764, 0.77521952, 0.7961714 , 0.81712328,\n",
       "        0.83807516]),\n",
       " <BarContainer object of 40 artists>)"
      ]
     },
     "execution_count": 496,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.hist(totalSet[\"Generosity\"], bins=40)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 497,
   "id": "f4fcb10e",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Pipeline(steps=[('ct',\n",
       "                 ColumnTransformer(transformers=[('ss', StandardScaler(),\n",
       "                                                  ['Life Expectancy', 'GDP',\n",
       "                                                   'Freedom']),\n",
       "                                                 ('ohe',\n",
       "                                                  OneHotEncoder(drop='first'),\n",
       "                                                  ['Year'])])),\n",
       "                ('lr', LinearRegression())])"
      ]
     },
     "execution_count": 497,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ct = ColumnTransformer(\n",
    "    [(\"ss\", StandardScaler(), [\"Life Expectancy\", \"GDP\", \"Freedom\"]),\n",
    "     (\"ohe\", OneHotEncoder(drop=\"first\"), [\"Year\"])\n",
    "    ], remainder = \"drop\")\n",
    "\n",
    "pl = Pipeline([(\"ct\", ct), (\"lr\", LinearRegression())])\n",
    "pl.fit(X_train, y_train)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 499,
   "id": "49ede406",
   "metadata": {},
   "outputs": [],
   "source": [
    "pred = pl.predict(X_test)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 500,
   "id": "34eb0c35",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.35103908009791723"
      ]
     },
     "execution_count": 500,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "np.mean((y_test-pred)**2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 501,
   "id": "bb53d4c1",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.5924855104539833"
      ]
     },
     "execution_count": 501,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "np.mean((y_test-pred)**2)**(1/2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 502,
   "id": "a2e159b5",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:ylabel='Density'>"
      ]
     },
     "execution_count": 502,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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FHG+llNqilMpRSj131bE4pdQ+pdQepVS4NXMKUWoRs4yd4zpPsHWS0nFwNhYUPLxShruKElmtQCil7IEvgRFACHCHUirkqmYpwBPAR8VcZoDWuqPWOsxaOYUoNZMJdnxvLK3RsIOt05Res0Fw/hgkH7F1ElHJWfMOoisQo7WO1VrnAjOBGy9voLU+q7XeAeRZMYcQlnVkNSRFQbeHbZ2kbGS4qzCTNQuEP3Disq/jC18zlwZWKKV2KqUmFddIKTVJKRWulApPTEwsY1QhSmHz5+DuB23G2jpJ2XgFg3czKRCiRNYsEKqI10rT6dlLax2K0UX1mFKqb1GNtNbTtNZhWuswX1/fsuQUwnwJu+Hoeug2CRycbJ2m7JoNgbiNkJth6ySiEnOw4rXjgcDLvg4AEsw9WWudUPj5rFJqHkaXlSxFKWxr3fvGHs9hDxTb5FxGLvsT0jhwKpWE89mcvZBN4oUccvJNmLTGZILazg7UdXPEy80JP09Xgn3daOJTm6b13HB2sLf+36PlCNj2NRxZC61HW//7iSrJmgViB9BcKRUMnATGA3eac6JSyg2w01pfKPzzUOAtqyUVwhwnd0L0Mhj4yhXbiqZl57E5Jon10Yn8HZPEiZSsS8fcnR3w9XCmnrsz3m5O2CmFUpCek09cUiY7j50nKT3nUntHe0WInyedAuvQMbAOoY3qEujlilJF3ZCXQ+Oe4OJpbHQkBUIUw2oFQmudr5SaAiwH7IEftNb7lVIPFx6fqpRqAIQDHoBJKfUUxognH2Be4Q+FA/C71nqZtbIKUSKtYeXr4OoFXSeTnVfA6oNnmbc7nnVRieSbNO7ODvRo6s3d3RrTxs+TNn4e1HUruRsqM9coFkcS04lMSGXP8fP8seMEP22OAyDQy5X+LerRv6UvPZp6U8vJAj+29o7QYrhR8Arywd6a7xVFVaV0NRoLHRYWpsPDZcqEsIIDC2DWvZwc8Ck/Z/Rg5vbjpGXnU9/DmTEd/BgS0oBOjergaG+Zx3r5BSaiz6QTfiyF9VGJbD6STFZeAU4OdvRq6s1NnfwZGtIAV6dydEftnw+z74MJi43lykWNpJTaWdxUAikQQpQkJ53Dn93IZ1nDWJLdFoARbRtwe5dAejb1wd7Owt0/RUXIL2DH0XOsizrL0sjTnDyfhZuTPTd08OOhvk1o6lu7DBe9AB82hS4PwvB3LR9aVAlSIIQoo1OpWXz6w2/MOdOAWo723NkjmPt6BuFfx9VmmUwmzbajKczdFc/CvQnkFpgYFtKAxwY0o12AZ+kuNv1WSIyCJ/eCpZ9ziCrhegVCOh6FKEJ+gYlvNsTy2aoodIEvEwNO8djECXiZ8UzB2uzsFD2aetOjqTf/GtGKnzbF8fOWOJbtP83YTv68NKIV9TxczLtYq1FweAWcPQD121g3uKhyZLE+Ia5yICGNm77axP8tj2Kg3W5W+03l1Ul3V4ricDWf2s48N6wlm18cyKP9m7J43ymGfLqBebvjzbtAixGAMkYzCXEVKRBCFNJa893GWMZ88Tenz2fxVb0FfO36NYF3fg5OtWwd77rcXRx5YXgrlj7Zh2b1avP0H3t5fvZesvMKSjixPgR0gQMLKyaoqFKkQAgBZOUW8OTMPby9+CCDWvmyMuh3Rl6YDeO+BZ/mto5ntqa+tZk1uQePD2zG7J3x3D5t6xXzLIrUdhyc2QeJ0RUTUlQZUiBEjRd/LpNxX29mUUQCzw9pxlTnL6h7ZB4M/wBajbR1vFKzt1M8O7Ql39zTmajTaYz7ajMnUjKLPyHkJkAZ+1sIcRkpEKJGO5qUwW1TtxB/LpMf7unEY0lvow7Oh6FvG+stVWHD2jRgxkPdOZ+Zy/hpW4svEh4NjXkQkX/KHhHiClIgRI11+MwFbvtmC9n5Jv54IIwBEc/DwYUw7F3o+bit41lEp0Z1+f2h7qTn5HP399uK725qOw6SouFMZMUGFJWaFAhRIx08lcbt07YC8McDnQnZ9AQc+svoVurxmI3TWVZbf09+nNiFM2nZTPxxB5m5+dc2an0jKHvjLkKIQlIgRI1z8nwW9/2wHSd7O2Y9GEbzDY8bxWHEh9C9im4CVILQRnX54o5Q9iek8vzsCK6ZIOvmDU0HQORc6WYSl0iBEDVKamYeE37YTlZeAb9MCCV43WXFodtkW8ezqsEh9XlheCsW7zvF1PWx1zZoM87YivTkrooPJyolKRCixsjJL2Dyb+HEJWfwzV2htNj0dOEzh/eqfXG4aHLfJoxq35CPV0Sx58T5Kw+2GgX2zrB3hk2yicpHCoSoMV6ZF8nW2BQ+urUDPY99BfvnweA3oMejto5WYZRSvDu2HfU9XHhq5m4yci57HuFaB0LGwL5ZkJdV7DVEzWFWgVBK/amUGqWUkoIiqqRZO04we2c8Twxsxo3qb/j7Ewi9D3o9ZetoFc7T1ZFPbuvAsZRM3lp04MqDofdCdqrMrBaA+XcQX2PsBndYKfW+UqqVFTMJYVEHEtJ4dUEkvZv58GTLVFj4ODTuDSM/qrErmHZr4s0j/ZryR/gJlu479c+BoD7g1QR2/Wy7cKLSMKtAaK1Xaa3vAkKBOGClUmqzUmqiUsrRmgGFKI+07Dwenb6TOrUc+e9NQdj/ORHcG8Dtv4JD5Vt8ryI9NbgF7fw9eXVBJOczc40XlYJO98CxTZB02LYBhc2Z3WWklPIGJgAPAruB/2EUjJVWSSaEBfx7XiQnzmXxxZ2h+Kx9EdJPw60/Qi0vW0ezOScHO96/uR3nMvP4YNmhfw50vMuYE7HrF9uFE5WCuc8g5gIbgVrADVrrMVrrP7TWjwNl2MpKCOtbuDeBRXsTeGpQc7pk/m2sNdT/RfDvbOtolUYbP0/u7xXEjO0nCI9LMV50rw8tR8Ce3yE/17YBhU2ZewfxndY6RGv9ntb6FIBSyhmguJ2IhLClM2nZvDo/ko6BdXikuy8seR4atINeT9s6WqXz1OAW+Hm68PK8feTmm4wXQ++DzCRjGLCoscwtEG8X8doWSwYRwlK01rwwJ4Kc/AI+ua0DDhveg4yzcMNnYC+bKF7NzdmBt25sS/SZdL77u3ACXbPB4NUUtnwhM6trsOsWCKVUA6VUZ8BVKdVJKRVa+NEfo7tJiEpnxvYTrI9O5KURrWnCSdj+LXSeAP6hto5WaQ0Oqc/QkPp8vjqGM2nZYGdnzA9J2A3Ht9o6nrCRku4ghgEfAQHAJ8DHhR/PAC9bN5oQpXcmLZv3lhykZ1Nv7uneGFa8Ck61YcC/bR2t0ntlVAgFJs2Hy6KMFzrcAa51YdP/bBtM2Mx1C4TW+met9QBggtZ6wGUfY7TWsruIqHTe+usAOQUm3h3bDruT4XB4OfR5Gtx8bB2t0mvkXYuJvYP4c1c8EfHnwckNuj8K0UvhVISt4wkbKKmL6e7CPwYppZ65+qMC8glhtnVRZ1kccYopA5oR5OMG696DWt7QtWpv/FORpgxohk9tJ/7z1wFjxdeuk8DZEzZ8aOtowgZK6mJyK/xcG3Av4kOISiErt4BXF0TSxNeNyf2awIntcGQ19HrSeCcszOLu4sizQ1uyI+4cS/adNtZn6v4wHFxkPI8QNcp1h3Rorb8p/PxmxcQRomw+X3OYEylZ/P5QN5wd7GHd+8bdQ5cHbR2tyrktLJCfN8fx3tKDDGpdD5ceU2DHd7DyNbh3YY1dnqQmMnei3IdKKQ+llKNSarVSKumy7ichbCr6zAWmbYhlXKg/PZv6yN1DOdnbKV4bHUL8uSx+2HQUXDyg7wtwdAMcXmHreKICmTsPYqjWOg0YDcQDLYDnrZZKCDOZTJpX5kVS28WBf49sbby48RO5eyinns18GBJSny/XxHD2QjaE3Q8+LWDpC7IUeA1iboG4uCDfSGCG1jrFSnmEKJU5O+PZHpfCSyNa4V3bGZKPQPQyCHtA7h7K6eWRrcktMPHJimhjYcORH8G5ONjwka2jiQpiboFYpJQ6BIQBq5VSvkC29WIJUbLk9BzeXXqQLkF1ubVzoPHi9mlg5wBdHrBtuGog2MeNe3sE8Uf4CQ4kpEGTfsbciL8/hZM7bR1PVABzl/t+EegBhGmt84AM4EZrBhOiJO8uOUR6dj7vjG2HnZ2C7DTYPR3ajDWW9Bbl9sTA5ni6OvLOksJhr8PfN/5t506GnHRbxxNWVpod4loDtyul7gVuAYZaJ5IQJdtyJJk/d8UzqW8TWtQvHHG9ZzrkXoDuj9g2XDXiWcuRpwY1Z1NMMmsOnTWGvd70NaQcgYVTZJ2mas7cUUy/Yiy50RvoUvghq7gKm8jJL+Df8/cR6OXK4wObGy+aCmDbNxDYTdZcsrC7ujemia8b7yw5SF6ByehqGvSasaf3RnkeUZ2Zu7RlGBCitbxdELY3bX0ssYkZ/DixC65O9saLh1fCuaPGLy5hUY72dvx7ZGse+Dmc6VuPMaFXsLGX95kDsOZtcKsHne+zdUxhBeZ2MUUC0qkrbC4uKYPP18Ywql1DBrSs98+BnT9B7frQ+gabZavOBraqR69m3vx39WFSM/OMyXI3fglNB8GiJ2DrVFtHFFZgboHwAQ4opZYrpRZe/LBmMCGuprXm1QWRONvb8doNIf8cSEswFuXreCfYyxbp1qCU4pVRIaRm5fHZmsK9qh2cYPzv0Go0LPsXrH5LnklUM+Z2Mb1hzRBCmGPh3gQ2Hk7izTFtqO/h8s+BPb+DNkGne2wXrgZo3dCD2wuX4RjfJZDm9d3B0QVu+wX+eho2fgznT8DoT8FZdiKuDswd5roeiAMcC/+8A9hlxVxCXCE1K4///HWQ9gGe3N298T8HTCbY9QsE9QHvprYLWEM8P6wlbs4OvLogkkuPJO3s4Yb/wYBXYN9s+HYAnNlv26DCIswdxfQQMAf4pvAlf2C+GecNV0pFKaVilFIvFnG8lVJqi1IqRyn1XGnOFTXL+0sPkZKRw7tj22Fvd9licXEb4PwxYw9lYXXetZ351/BWbI1NYf6ek/8cUAr6PQ/3LoDsVPh2IOz8Wbqcqjhzn0E8BvQC0gC01oeBetc7QSllD3wJjABCgDuUUiFXNUsBnsAYQlvac0UNsS02mRnbj3N/r2Da+nteeXDnz+BSRx5OV6DxXQLpEFiHdxYfJDUr78qDTfrBw39Do+7Gw+t5kyE30zZBRbmZWyBytNa5F79QSjkAJb016ArEaK1jC8+dyVWzr7XWZ7XWO4C80p4raobsvAJemrePgLquPDO0xZUHM1Pg0F/QYbzRFy4qhJ2d4p2b2pKSkcvHK6KubVC7Htw919jmNWIWfD8UUo5WfFBRbuYWiPVKqZcBV6XUEGA2sKiEc/yBE5d9HV/4mjnKc66oRr5aG0NsYgbvjm1HLaerxlRE/gkFucboJVGh2vp7cm+PIH7deoztR4tYu9POHvq9AHfNhtTjMK0/xK6v8JyifMwtEC8CicA+YDKwBHilhHOK2lXE3A5Js89VSk1SSoUrpcITExPNvLyoCqLPXODr9UcY28mfvi18r20Q8QfUawMN2ld8OMHzw1oSWLcWz87eQ3pOftGNmg+BSevAvSFMvwUOLKjQjKJ8zB3FZMJ4KP2o1voWrfW3ZsyqjgcCL/s6AEgwM5fZ52qtp2mtw7TWYb6+RfwSEVWSyaR58c8Iajs78Mqo1tc2SIqB+B1G95LscGYTbs4OfHRrB+LPZfHO4oPFN/RqAvcvBb9OMHuisX2pqBKuWyCU4Q2lVBJwCIhSSiUqpcxZz2AH0FwpFayUcgLGA+ZOrivPuaIa+G3bMXYdP8+ro0OMfR6uFjETlB20u7Xiw4lLugZ7MalPE2ZsP87aQ2eLb+haF+7+01gna879cHRjxYUUZVbSHcRTGKOXumitvbXWXkA3oJdS6unrnai1zgemAMuBg8AsrfV+pdTDSqmHAZRSDZRS8cAzwCtKqXillEdx55b9rymqkvhzmXy4LIo+zX0Y26mIR08mE+z9A5r0B4+GFZ5PXOnpIS1oUb82L/wZQVJ6TvENnd2NZxJ1g2HWPZASW3EhRZmo6/UUKaV2A0O01klXve4LrNBad7JyvlIJCwvT4eHhto4hysFk0tz9/Tb2njjPsqf6EuhV69pGcZvgp5Ew7ltof1vFhxTXOJCQxtivNhHaqC6/PtAVB/vrvPdMiTXmSXj4w4OrZQSajSmldmqti1ydu6Q7CMeriwOA1jqRf7YhFcJipm87xuYjybwyOqTo4gCwdwY41YZWoyo2nChWiJ8Hb9/Uli2xyXyw7ND1G3s1gbHT4EwkrHy1YgKKMimpQOSW8ZgQpXYsOYN3lxyibwtfxncJLLpRXhbsnw+tx8ie05XMrWGB3NO9Md9uPMqM7cev37jFUOj+qLFFbOy6CsknSq+kAtFBKZVWxMcFoF1FBBQ1g8mkeX52BA72ig9ubocqbmTSocXGrnEdxldsQGGW128IoV8LX16ZH8mK/aev33jQa+DVFBY9KbOtK6nrFgittb3W2qOID3ettXQxCYv5cXMc2+NSeG10CA09XYtvGPEHeAQYi/OJSsfB3o4v7wqlrb8nU37fzbqo64xscnSFMZ/BuTjY8H8VllGYrzR7UgthFUcS0/lw2SEGtarHLZ0Dim+YfhZiVhsPpu3kf93KqrazA79M7EqzerV56JdwFkecKr5xUG9ofzts+VKW46iE5KdM2FSBSfPc7L24ONrz3rjrdC0B7JsDukC6l6oAz1qOzJjUnY6BdZgyYxdfrYuh2BGTg98wluZY9XqFZhQlkwIhbOrbjbHsPn6et25sQz2PEoY7RsyEhh3Bt2WFZBPl4+nqyC/3d2N0ez8+XBbF5F93kpJRxNgWDz/o+YSxDMepiIoPKoolBULYTPSZC3yyIprhbRowpoPf9RufPQSn9srdQxXj6mTPZ+M78sqo1qyLSmTopxuYv/vktXcT3R8BZ09Y/4FtgooiSYEQNpFXYOLZWXup7eLA22PbXr9rCQqX1rCHtjdXTEBhMUopHuzThAVTeuFXx4Wn/tjDTV9uYlnkaUymwkLhWgd6PGos335qr03zin9IgRA28dXaI+w7mcq7Y9viU9RaS5czmSBiNjQdaOw1IKqk1g09mP9oLz68uT3nMvN4+LedDP50Pb9tPUZqZh50exhcPGGd3EVUFlIgRIWLPJnK52sOc1NHP4a3NWMtpWObIC1eupeqATs7xW1dAlnzbD8+v6MTLg72vDI/krB3VvLQ7Bj+avwSmYdWyV1EJeFQchMhLCcnv4BnZu3Bu7YTb45pa95JETPByR1ajrRuOFFhHOztuKGDH6PbNyTyZBrz95xk0d4EVl5ohCtTGfjzZkaPqkf/lvVwdbK3ddwaSwqEqFCfrjxM9Jl0fpzYBc9aZsy1zMuCAwshZAw4FbM2k6iylFK0C/CkXYAnL49szfajKfy1ZAHLTtZh8fRd1HKy58aOfkzsFUyL+u62jlvjSBeTqDA7j6UwbcMR7ugayICWZj5LiFoKOWmyamsNYG+n6NHUm3fuGcI2l8eZ3ukgo9s3ZO6ukwz9dAP3fL+NbbHJto5Zo0iBEBUiMzefZ2ftxa+OK/8eFWL+iRF/gLufLK1Rk9QJxCFkFL2OfsaHY5qx5aVBPD+sJVGnL3D7tK1M/jWc06nZtk5ZI0iBEBXiw2VRxCVn8uEt7antbGbPZkYSxKyC9rcaM21FzdH9UchOhb0z8HJz4rEBzVj//ACeHdKC9dGJDPl0PQv3mruDsSgrKRDC6rbGJvPT5jgm9AyiZ1Mf80+MnAumfGgvo5dqnMCu4BcKW6caw5wxJt09Pqg5y57sS4v67jwxYzdvLtpPfoHJxmGrLykQwqqy8wp4ee4+GnnV4l/DW5Xu5IiZ0KAd1C9Fl5SoHpQy7iKSD8ORNVccCvJxY+ak7kzoGcSPm+J47PddZOcV2Cho9SYFQljVF2tiiE3K4J2xbUs3XDHpMJzcKXcPNVnIjVDLB3b+eM0hR3s73hjThtdvCGH5/jM89Es4OflSJCxNCoSwmqjTF5i6/gjjOvnTp7lv6U6O+AOUHbS7xTrhROXn4ASd7jJGsqUVvWT4xF7BfHhzezYeTuLx33dLd5OFSYEQVlFg0rw4NwIPV0deGV3KLiKTCfb+AU36g3sDq+QTVUTofcYS77t/K7bJbV0Cef2GEFYcOMPbiw9WYLjqTwqEsIrfth5j9/HzvDq6NV5uTqU7+eg6SD0One62SjZRhXg3heB+sOtnMBXfhTSxVzD39wrmp81xJe+HLcwmBUJYXML5LD5cdog+zX24qaN/6S+w+zdwrQutRls+nKh6wiZC6olrHlZf7eWRrejT3IfXF+5nf0JqBYWr3qRACIt7feF+CrTmnZtK2CGuKJkpcPAvaHcbOJSwyquoGVqOAjdfCL/2YfXlHOzt+O/tHalby5HHf99NRk5+BQWsvqRACItaG3WWlQfO8OSgFjTyLsPaSfvmQEEOhN5j+XCianJwgo53QfQySLv+5Djv2s789/ZOHE3O4INlhyooYPUlBUJYTG6+if8sOkCwjxv39w4q20V2/wINOxjzH4S4qHPJD6sv6tHUm4k9g/llyzE2H0mqgHDVlxQIYTE/bT5KbFIGr40OwdmhDEtjnNoLp/dBJ7l7EFfxagJNBsDO6z+svuj5YS0J9nHjpbn7ZH5EOUiBEBZxNi2b/606zMBW9RjQqoy7vu38GeydZe6DKFrnCcbGUTGrSmzq6mTPWze24VhyJt9tPGr9bNWUFAhhER8siyK3wMSrpZ3zcFF2mjE5ru3NxggmIa7WahS41YOdP5nVvE9zX4a1qc8Xa2I4lZpl3WzVlBQIUW67j5/jz13xPNC7CcE+bmW7SMQfkJsOXR60bDhRfdg7GjOrzXhYfdEro0Io0Jr3lsgD67KQAiHKxWTSvLFwP/XcnZkysFnZLqI1hP8ADTuCf6hF84lqJvQ+0CbY9atZzQO9avFw3yYs3JvA9qMpVg5X/UiBEOXy56549san8tLIVubv83C141vg7AHj7qG08yZEzeIVbDys3vWLWQ+rAR7p3ww/TxfeWLgfk0lbOWD1IgVClFl2XgGfrIymQ4Bn2WZMX7TjO3DxNJ4/CFGSsIlmP6wG44H1c8NacuBUGksii170TxRNCoQosx83xXEqNZuXRrYu/Yzpi9LPwoGFxkQopzJMrBM1T8uRpXpYDXBjR3+a16vNJyujZcXXUpACIcrkXEYuX62LYWCrenRv4l32C23/1tg1LuwBy4UT1Zu9o7GQY/QySD1p3il2imeGtCA2MYP5e2SrUnNJgRBl8sXaGDJy8ku/S9zlcjNhx7fGO0KfMj7gFjVT6L3Gw2ozZlZfNLxtA9r6e/C/1dHk5stdhDmkQIhSO5GSya9bjnFL5wBaNnAv+4X2TIesc9DrCcuFEzWDVzA0HViqh9VKKZ4d2pITKVnMCj9h5YDVgxQIUWofr4hCKXh6SIuyX8RUAFu+gIAuENjNcuFEzVGKmdUX9W/hS1jjunyxJkaW4DCDFAhRKpEnU5m/J4H7ewfT0NO17Bc6uAjOxUHPJ2RoqyibliOhdn3jOZaZlFI8Mag5p9OymbfLvOcXNZkUCFEq7y89RJ1ajjzcr2nZL6I1bP4c6gYbyycIURb2jhB2P8SshOQjZp/Wp7kP7fw9mbr+CAUyL+K6rFoglFLDlVJRSqkYpdSLRRxXSqnPCo9HKKVCLzsWp5Tap5Tao5QKt2ZOYZ4N0Yn8HZPE4wOb4+nqWPYLxa6Fk+HQcwrYlWHVVyEu6jwR7Bxh+zSzT1FK8Wj/psQlZ7Jkn8yLuB6rFQillD3wJTACCAHuUEpdvZLbCKB54cck4Ourjg/QWnfUWodZK6cwj8mkeX/pIQLqunJ390Zlv5DWsPZd8AiQZb1F+bnXh7bjYPd0Y8FHMw1r04Amvm58te4IWstdRHGseQfRFYjRWsdqrXOBmcCNV7W5EfhFG7YCdZRSDa2YSZTRgr0nOXAqjeeHtSzbXg8XxayC+B3Q9znZUlRYRrfJkHsB9vxu9il2dopH+jXl4Kk01kUnWjFc1WbNAuEPXD6WLL7wNXPbaGCFUmqnUmpScd9EKTVJKRWulApPTJT/0NaQnVfAR8ujaevvwQ3t/cp+Ia1h7TtQp5Exc1oIS/DvDAFdYfs3YDJ/fsONHf3x83Thq7UxVgxXtVmzQBQ1NOXqe7nrtemltQ7F6IZ6TCnVt6hvorWeprUO01qH+fr6lj2tKNavW45x8nwWL41ojZ1dOUYcRS+DhN3Q9wVjn2EhLKXbZEiJhcMrzD7FycGOSX2bsCPuHDviZKXXolizQMQDgZd9HQBcPce92DZa64ufzwLzMLqsRAVLzczji7Ux9G3hS69mPmW/kKkA1rxtjFzqMN5yAYUACLkRPBvB358Yd6pmur1LI7zdnOQuohjWLBA7gOZKqWCllBMwHlh4VZuFwL2Fo5m6A6la61NKKTellDuAUsoNGApEWjGrKMZX62NIy87jxfIsqQGw+1c4EwmDXzeGJwphSfaOxoz8E9vg2GazT3N1smdiryDWRiWyPyHVigGrJqsVCK11PjAFWA4cBGZprfcrpR5WSj1c2GwJEAvEAN8Cjxa+Xh/4Wym1F9gOLNZaL7NWVlG0k+ez+HFTHGM7+RPi51H2C2Wnwur/QKOeEHKTxfIJcYVOd4ObL2z8uFSn3dMjiNrODny9zvy5FDVFGXd4MY/WeglGEbj8tamX/VkDjxVxXizQwZrZRMk+XhEFwLNDW5bvQhs+gsxkGP6uzJoW1uPoCt0fhdVvQsIe8Oto1mmero7c1b0R326IJS4pg6CybptbDclMalGkyJOpzN11kom9gvCvU44lNZKPwNavjVFLfp0sF1CIonR5AJw9jGcRpfBAr2Ac7O2YtjHWSsGqJikQ4hpaa95efAAvNyceG1COZbi1hiXPG/MdBr1quYBCFMfFE7o+ZGxCdeaA2afV83Dhls4BzAmP52xathUDVi1SIMQ1Vh44w9bYFJ4e3BwPl3I8UI6YBUdWw6DXwL2B5QIKcT09poCzO6x+q1SnTe7bhHyTie83HbVSsKpHCoS4Ql6BifeXHqKprxt3dC3HkhoZSbDsRWMCU5cHLRdQiJLU8oJeT0L0Uji2xezTGnu7Maq9H9O3Hic1K8+KAasOKRDiCtO3HiM2KYOXR7bGwb4c/3ss/RfkpsOYz2VBPlHxuj9iLAW+6o1SzYt4uF8T0nPy+W3rMetlq0KkQIhLUjPz+O/qw/Rq5s3AVvXKfqGDf0HkHOjzHNQr5/wJIcrCyQ36/QtObIXo5Waf1sbPk34tfPlx01Gy82RDISkQ4pIv1h4mNSuPf48MQZV1OGpaAiycAg07QO+nLRtQiNIIvRe8msKq16HA/C6jR/s3JSk9l9myLakUCGGIS8rg583HuCU0oOyT4kwmmDcZ8nPg5u9lvSVhW/aOMPRtSDwE26aW3L5Q12AvQhvV4ZsNseQXmL/4X3UkBUKgteaNRftxcrDjuWHlmBS3+TM4ugFGfAA+zS0XUIiyajUSWgyHte9BqnlbjCqleKR/M+LPZfFXRM3eUEgKhGD5/jOsi0rk6SEtqO/hUraLHN8Ka/5jLJomGwGJymTEB6ALYPnLZp8yqFU9mterzdc1fEMhKRA1XGZuPm8t2k+rBu7c16Nx2S5y4QzMug88A+GGz2Q5DVG51A0yBkwcmG9sWGUGOzvFI/2bEnXmAmsOnbVqvMpMCkQN98WaGBJSs/nPTW3LNqy1IA9mT4CcNBg/HVzrWDqiEOXX6wnwbgaLnjZ7a9IbOvjhX8eVz1YfrrF3EVIgarCYsxf4dmMsN4cG0CXIq2wXWfEKHN9szHeo38ayAYWwFAdnuOlrSIs3u6vJ0d6Oxwc2Y298KqsP1sy7CCkQNVSBSfPc7AjcnB14aWQZ5yps/9YYHdJjCrS7xbIBhbC0wK7GDOvdv5o9N+LmzgE09q7FJyujMZlq3l2EFIga6vu/Y9lz4jxvjmmDT23n0l8gegUsfQFajoQhpVvzRgib6f8S1G8LCx+HzJK3GXW0t+PJQc05cCqN5ftPV0DAykUKRA0Uczadj1ZEMzSkPmM6+JX+Aqf3wZyJxg/auG9lKQ1RdTg4w9ipRnGY/4gxd6cEN3b0p6mvG5+uiqaght1FSIGoYQpMmhfm7MXV0Z63x7Yt/YzptASYfpuxrPKds8C5tnWCCmEtDdrBsHchehls+bzE5vZ2iqcGtyD6TDp/RSRUQMDKQwpEDTN1/RF2HT/PG2NCqOdeyjkP2anw+23GiKU7/wCPhtYJKYS1dX3I2P521Ztmrfg6ql1DWjVw56MVUTVqjSYpEDXI9qMpfLwiijEd/Lipo3/pTs7Lghl3wNmDcOtPxrswIaoqpWDMZ1C3sdFdmn79UUp2dopXR4dwIiWLH2rQfhFSIGqIlIxcnpixm0ZetXintF1LF+c6HNsMY7+B5kOsllOICuPiCbf9YtwZz7zLWEPsOno182Fw6/p8uSaGsxdqxq5zUiBqAJNJ8+ysPaRk5PLFnaG4l2aXOJMJFjxm9NeO+kiGs4rqpUE7Y35E/Hb46+kS947496jW5BaY+Gh5VAUFtC0pEDXA52tiWBuVyKujW9PW39P8E7U2doWL+AMGviI7w4nqqc1N0O9F2DMdtnxx3abBPm5M6BnE7J3xRJ5MrZh8NiQFoppbsOckn66KZlyoP3d3L8VaS1rDyldh+zfGRLg+z1kvpBC21u9fxkKTK16FyLnXbfr4oOZ41XLitQWR1X7YqxSIamznsRSenxNB12Av3hvXzvznDheLw+bPoctDxpr6sgCfqM7s7Izna426G3uaHN1QbFMPF0deGd2aXcfP82M1f2AtBaKaOpacwaRfduLn6cI3d3fG2cHMyWxXF4eR/yfFQdQMjq5wxwxjF7oZd8KpiGKb3tTRn8Gt6/F/y6OITUyvwJAVSwpENXQiJZM7v91Ggdb8MKELdd3M3NlNioOo6Vzrwt1/gosHTL8FzsUV2UwpxTtj2+HsYMcLcyKqbVeTFIhq5kRKJuOnbSU9J5/fHuhGE18zZzqbCoxRHFIcRE3n6Q93zzWGvf46Fi4UvQZTfQ8XXr+hDeHHzlXbriYpENVI/LlM7vh2Kxey8/jtgW7mj1jKy4bZ98HOH6H3M1IchKjXCu6abUyg+2l0sUViXKjR1fThsij2xVe/UU1SIKqJiPjzjP1qM6lZefz2YDfaBZhZHLJTjVvpg4tg+Psw+HUpDkKAsTz4XXOM9cd+vsHYOfEqSik+vKUD3rWdeGT6TlIz82wQ1HqkQFQDyyJPc9s3W3Cyt+PPR3rSPqCOeSemnYIfR8HxLTDuO+j+iFVzClHlNO4Bd8+B1JPw00g4f/yaJl5uTnx5Vyhn0rJ59Ped5BWUvEJsVSEFogorMGk+W32YR6bvpFUDD+Y/1osW9d3NO/nEDpjWH1JijYX32t9q1axCVFmNe8I9cyEjEb4fCmcOXNMktFFd3hvXnk0xybw6P7LabFEqBaKKOpWaxZ3fbuWTldGM6eDHzEnd8XU3c+Of3dONd0OOLvDgKmg22LphhajqGnWHiUuNkX4/Doe4Tdc0uaVzAFMGNGPmjhO8v/RQtSgSDrYOIEpHa83CvQm8tmA/eQUmPrq1AzeH+ps3CS7nAix5Afb+Dk36wy0/Qq0y7kUtRE1Tvw08sAJ+uxl+GQMjPoCwB654Zvfs0Bacz8rlmw2x2NkpXhjWsvR7rlQiUiCqkMNnLvDagv1siU2mQ4Ann97e0fxhrCd3wZ8PwrmjxrICfV8Ae/nPL0Sp1G1s3HXPfQgWP2tMphvxoXE3jvHQ+q0xbSkwwdfrjpCWlcebY9rgYF81O2vkN0QVcDYtm6/WHeG3rceo5WTPf25qy51dG2FvZ85dQzqsew+2fg3uDeC+vyCol/VDC1FdudaBO2bC2ndh40dwYpuxjalfJ8DYO+LdsW3xdHVk6vojHEvO5PM7Opk/YbUSUdWhn+yisLAwHR4ebusYFnM6NZtvNhzh923HyTdpbu0cwPPDWuJd24xnDSYTHFwAy1+BtHjoPNEYwupa1/rBhagpYlbBginGA+w+z0Hvp4wlOwrNCj/BK/Mi8XJz4pPbOtCzmY/tshZDKbVTax1W5DEpEJWLyaTZdCSJ6VuPs/KgMe765lB/HhvQjMbebiVfQGvjf9o1/4FTe6FeCIz+LzTqZt3gQtRUWeeMZ3v7ZoFnIAx6HdrebCwACESeTOWJGbuJTcrgls4BvDC8Zem3+7UiKRCVnNaavfGpLNl3iiX7ThF/Lou6tRy5LSyQu7s3JtCrVskXyc00/gfd/i2ciYQ6jaH/S9D+NrAzc6E+IUTZHd0Ay/8NpyOMjYh6TIE248DBiazcAj5bc5hvN8Rib6e4o2sjJvVtgl8d15Kva2VSICoZrTUJqdlsPZLMpiNJbI5J5nRaNo72it7NfBjT0Y8RbRvi4ljCL/b8HDiyFg4sgEOLIScV6rczNmTvcAc4VL0+TyGqNJPJ2GDr708hKQpq1zd+FtvcBA07cjQ5k6/XxTB310mUgqFtGnBD+4b0b1mv5J93K7FZgVBKDQf+B9gD32mt37/quCo8PhLIBCZorXeZc25RKmOBOJ+Zy9GkDOKSM4hNzGB/QhoR8akkpRv733q5OdGjqTcDWtZjSOv6eNa6znag6WeNu4P4nRC3EU5sh/wsY2/dVqOh0z3GeO0qPKxOiGpBaziyGrZ9AzGrQRcYd/VN+kGjnsR7hvJdRB6LIk6RnJGLm5M9PZv5ENa4LmFBdQlp6ImrU8UUDJsUCKWUPRANDAHigR3AHVrrA5e1GQk8jlEgugH/01p3M+fcopS3QJhMmnyTpsCkyTeZyC+48usCkyavQJOZm09GTgGZufmk5+STmVtAenY+SRk5JF3IJTE9h6QLOZxKzeLcZWuzKAVNfdxo7+dGh4a1CPOvRWsfe+xMeZCXCdlpkJNmrI+UmWxM70+LNz6fi4PMpH/C1m8LQb2NSW7B/eRuQYjKKjMFDv1l3OUf22Lc6QM41iLfuwVbHbuxOL0lW1K9iMv85+fY392eYC9nAuq44O3uildtV3zcXfByd6WWsyO1nOxxdbTH1cn48CjNXvOXsVWB6AG8obUeVvj1SwBa6/cua/MNsE5rPaPw6yigPxBU0rlFKWuBaPf6ctJz80var7xEjvYK39rO+Lg741vbmXoeLgT71CLYpzbBh74lcO+nOKt88y/o4GosPezhD3UCoV4bY7JOg3YywU2IqshkgrMH4GQ4JEbB2YPG+k7pZyA3nUTtwU5TC6J0IEdNDYnVDTmlvUjBgwKKv6PwdnNi56tDyhTpegXCmvMg/IETl30dj3GXUFIbfzPPBUApNQmYVPhlemGRsZkY8AGSSmxoljTgDLDLMpe7lgWzWlVVyQlVJ2tVyQk1Kmsaxq+70jkGqNdKdcrlOYvdrN6aBaKojvCr36MX18acc40XtZ4GTCtdNOtRSoUXV40rm6qStarkhKqTtarkBMlqDebmtGaBiAcCL/s6AEgws42TGecKIYSwImsuELIDaK6UClZKOQHjgYVXtVkI3KsM3YFUrfUpM88VQghhRVa7g9Ba5yulpgDLMYaq/qC13q+Uerjw+FRgCcYIphiMYa4Tr3eutbJaWKXp7jJDVclaVXJC1claVXKCZLUGs3JWq4lyQgghLKdqrkErhBDC6qRACCGEKJIUCAtRSgUqpdYqpQ4qpfYrpZ60daaiKKVclFLblVJ7C3O+aetMJVFK2Suldiul/rJ1luIopeKUUvuUUnuUUpVrvZerKKXqKKXmKKUOFf7/2sPWmYqilGpZ+O958SNNKfWUrXMVRSn1dOHPU6RSaoZSqvIs13oVpdSThTn3l/TvKc8gLEQp1RBoqLXepZRyB3YCN5W0PEhFK1z/yk1rna6UcgT+Bp7UWm+1cbRiKaWeAcIAD631aFvnKYpSKg4I01pX+gldSqmfgY1a6+8KRwnW0lqft3Gs6ypcfuck0E1rfczWeS6nlPLH+DkK0VpnKaVmAUu01j/ZNtm1lFJtgZlAVyAXWAY8orU+XFR7uYOwEK31qYsLDWqtLwAHMWaEVyrakF74pWPhR6V9l6CUCgBGAd/ZOkt1oJTyAPoC3wNorXMre3EoNAg4UtmKw2UcAFellANQi8o7b6s1sFVrnam1zgfWA2OLaywFwgqUUkFAJ2CbjaMUqbDLZg9wFlipta6UOQv9F3gBMNk4R0k0sEIptbNw+ZfKqgmQCPxY2G33nVLKjJ2obG48MMPWIYqitT4JfAQcB05hzOdaYdtUxYoE+iqlvJVStTCmGQQW11gKhIUppWoDfwJPaa3TbJ2nKFrrAq11R4wZ6l0LbzsrHaXUaOCs1nqnrbOYoZfWOhQYATymlOpr60DFcABCga+11p2ADOBF20a6vsJusDHAbFtnKYpSqi5wIxAM+AFuSqm7bZuqaFrrg8AHwEqM7qW9QLEriEqBsKDCPv0/gela67m2zlOSwq6FdcBw2yYpVi9gTGH//kxgoFLqN9tGKprWOqHw81lgHkYfb2UUD8Rfdtc4B6NgVGYjgF1a6zO2DlKMwcBRrXWi1joPmAv0tHGmYmmtv9dah2qt+wIpQJHPH0AKhMUUPvz9Hjiotf7E1nmKo5TyVUrVKfyzK8b/3IdsGqoYWuuXtNYBWusgjC6GNVrrSvfOTCnlVjgwgcLumqEYt/KVjtb6NHBCKdWy8KVBQKUaSFGEO6ik3UuFjgPdlVK1Cn8PDMJ4BlkpKaXqFX5uBIzjOv+21lysr6bpBdwD7Cvs3wd4WWu9xHaRitQQ+LlwVIgdMEtrXWmHj1YR9YF5xu8GHIDftdbLbBvpuh4Hphd23cRSuMRNZVTYTz4EmGzrLMXRWm9TSs3BWJc/H9hN5V5y40+llDeQBzymtT5XXEMZ5iqEEKJI0sUkhBCiSFIghBBCFEkKhBBCiCJJgRBCCFEkKRBCCCGKJAVCCCFEkaRACCGEKNL/A+dO6WgAKHU2AAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "cal = pd.DataFrame()\n",
    "cal[\"Actual\"] = y_test\n",
    "cal[\"Predicted\"] = pred\n",
    "sns.kdeplot(data=cal)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 503,
   "id": "494e0c65",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Year</th>\n",
       "      <th>Country</th>\n",
       "      <th>Freedom</th>\n",
       "      <th>Generosity</th>\n",
       "      <th>Corruption</th>\n",
       "      <th>Life Expectancy</th>\n",
       "      <th>GDP</th>\n",
       "      <th>Population</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>778</th>\n",
       "      <td>2019</td>\n",
       "      <td>Tanzania</td>\n",
       "      <td>0.417000</td>\n",
       "      <td>0.276000</td>\n",
       "      <td>0.147000</td>\n",
       "      <td>67.7</td>\n",
       "      <td>2980.0</td>\n",
       "      <td>58000000.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>447</th>\n",
       "      <td>2017</td>\n",
       "      <td>Uganda</td>\n",
       "      <td>0.443186</td>\n",
       "      <td>0.325766</td>\n",
       "      <td>0.057070</td>\n",
       "      <td>65.7</td>\n",
       "      <td>1770.0</td>\n",
       "      <td>41200000.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>639</th>\n",
       "      <td>2019</td>\n",
       "      <td>Luxembourg</td>\n",
       "      <td>0.526000</td>\n",
       "      <td>0.194000</td>\n",
       "      <td>0.316000</td>\n",
       "      <td>82.0</td>\n",
       "      <td>94300.0</td>\n",
       "      <td>616000.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>349</th>\n",
       "      <td>2017</td>\n",
       "      <td>Qatar</td>\n",
       "      <td>0.604131</td>\n",
       "      <td>0.330474</td>\n",
       "      <td>0.439299</td>\n",
       "      <td>80.2</td>\n",
       "      <td>113000.0</td>\n",
       "      <td>2720000.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>381</th>\n",
       "      <td>2017</td>\n",
       "      <td>Belarus</td>\n",
       "      <td>0.295400</td>\n",
       "      <td>0.155138</td>\n",
       "      <td>0.156314</td>\n",
       "      <td>74.0</td>\n",
       "      <td>17200.0</td>\n",
       "      <td>9450000.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>203</th>\n",
       "      <td>2016</td>\n",
       "      <td>El Salvador</td>\n",
       "      <td>0.372690</td>\n",
       "      <td>0.088770</td>\n",
       "      <td>0.106130</td>\n",
       "      <td>73.8</td>\n",
       "      <td>7120.0</td>\n",
       "      <td>6360000.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>514</th>\n",
       "      <td>2018</td>\n",
       "      <td>Kuwait</td>\n",
       "      <td>0.554000</td>\n",
       "      <td>0.167000</td>\n",
       "      <td>0.106000</td>\n",
       "      <td>83.2</td>\n",
       "      <td>65500.0</td>\n",
       "      <td>4140000.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>473</th>\n",
       "      <td>2018</td>\n",
       "      <td>Iceland</td>\n",
       "      <td>0.677000</td>\n",
       "      <td>0.353000</td>\n",
       "      <td>0.138000</td>\n",
       "      <td>82.9</td>\n",
       "      <td>48600.0</td>\n",
       "      <td>337000.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>590</th>\n",
       "      <td>2018</td>\n",
       "      <td>Burkina Faso</td>\n",
       "      <td>0.312000</td>\n",
       "      <td>0.175000</td>\n",
       "      <td>0.128000</td>\n",
       "      <td>62.1</td>\n",
       "      <td>1760.0</td>\n",
       "      <td>19800000.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>528</th>\n",
       "      <td>2018</td>\n",
       "      <td>Russia</td>\n",
       "      <td>0.399000</td>\n",
       "      <td>0.065000</td>\n",
       "      <td>0.025000</td>\n",
       "      <td>72.3</td>\n",
       "      <td>25400.0</td>\n",
       "      <td>146000000.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>429 rows × 8 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "     Year       Country   Freedom  Generosity  Corruption  Life Expectancy  \\\n",
       "778  2019      Tanzania  0.417000    0.276000    0.147000             67.7   \n",
       "447  2017        Uganda  0.443186    0.325766    0.057070             65.7   \n",
       "639  2019    Luxembourg  0.526000    0.194000    0.316000             82.0   \n",
       "349  2017         Qatar  0.604131    0.330474    0.439299             80.2   \n",
       "381  2017       Belarus  0.295400    0.155138    0.156314             74.0   \n",
       "..    ...           ...       ...         ...         ...              ...   \n",
       "203  2016   El Salvador  0.372690    0.088770    0.106130             73.8   \n",
       "514  2018        Kuwait  0.554000    0.167000    0.106000             83.2   \n",
       "473  2018       Iceland  0.677000    0.353000    0.138000             82.9   \n",
       "590  2018  Burkina Faso  0.312000    0.175000    0.128000             62.1   \n",
       "528  2018        Russia  0.399000    0.065000    0.025000             72.3   \n",
       "\n",
       "          GDP   Population  \n",
       "778    2980.0   58000000.0  \n",
       "447    1770.0   41200000.0  \n",
       "639   94300.0     616000.0  \n",
       "349  113000.0    2720000.0  \n",
       "381   17200.0    9450000.0  \n",
       "..        ...          ...  \n",
       "203    7120.0    6360000.0  \n",
       "514   65500.0    4140000.0  \n",
       "473   48600.0     337000.0  \n",
       "590    1760.0   19800000.0  \n",
       "528   25400.0  146000000.0  \n",
       "\n",
       "[429 rows x 8 columns]"
      ]
     },
     "execution_count": 503,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "X_train"
   ]
  }
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