CarOfTheYear_Winners_Nominees.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Car of the Year Analysis - Winners & Nominees\n",
    "\n",
    "**Car of the Year is one of the most prestigious award for car manufacturers that produce and sell cars in Europe continent.**\n",
    "\n",
    "The dataset contains all manufacturer-model names (in places), as well as the points earned, starting from year 1964, up to the present.\n",
    "\n",
    "If you're ready for the analyses, let's load the necessary modules and the dataset first:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "import math\n",
    "import pandas as pd\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "import seaborn as sns\n",
    "coty_win_nom = pd.read_csv('carOfTheYear_winners_nominees.csv', index_col=0)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "These are the features (columns) to be used. You will see later why there are up 10 places included:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Index(['Winner', 'W_Pts', '2nd Place', '2P_Pts', '3rd Place', '3P_Pts',\n",
       "       '4th Place', '4P_Pts', '5th Place', '5P_Pts', '6th Place', '6P_Pts',\n",
       "       '7th Place', '7P_Pts', '8th Place', '8P_Pts', '9th Place', '9P_Pts',\n",
       "       '10th Place', '10P_Pts'],\n",
       "      dtype='object')"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "coty_win_nom.columns"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "First of all, let's see the winners between **2010** and **2020**:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "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>Winner</th>\n",
       "      <th>W_Pts</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Year</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2020</th>\n",
       "      <td>Peugeot 208</td>\n",
       "      <td>281</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019</th>\n",
       "      <td>Jaguar I-Pace</td>\n",
       "      <td>250</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018</th>\n",
       "      <td>Volvo XC40</td>\n",
       "      <td>325</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017</th>\n",
       "      <td>Peugeot 3008</td>\n",
       "      <td>319</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016</th>\n",
       "      <td>Opel/Vauxhall Astra</td>\n",
       "      <td>312</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2015</th>\n",
       "      <td>Volkswagen Passat</td>\n",
       "      <td>340</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2014</th>\n",
       "      <td>Peugeot 308</td>\n",
       "      <td>307</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2013</th>\n",
       "      <td>Volkswagen Golf</td>\n",
       "      <td>414</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2012</th>\n",
       "      <td>Opel Ampera/Chevrolet Volt</td>\n",
       "      <td>330</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2011</th>\n",
       "      <td>Nissan Leaf</td>\n",
       "      <td>257</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2010</th>\n",
       "      <td>Volkswagen Polo</td>\n",
       "      <td>347</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                          Winner  W_Pts\n",
       "Year                                   \n",
       "2020                 Peugeot 208    281\n",
       "2019               Jaguar I-Pace    250\n",
       "2018                  Volvo XC40    325\n",
       "2017                Peugeot 3008    319\n",
       "2016         Opel/Vauxhall Astra    312\n",
       "2015           Volkswagen Passat    340\n",
       "2014                 Peugeot 308    307\n",
       "2013             Volkswagen Golf    414\n",
       "2012  Opel Ampera/Chevrolet Volt    330\n",
       "2011                 Nissan Leaf    257\n",
       "2010             Volkswagen Polo    347"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "coty_win_nom.loc[2020:2010,['Winner', 'W_Pts']]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "While inspecting the winners, I asked myself that whether or not there are manufacturer(s) that won the award **more than once** with the same model. Does there exist any such cars?"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Volkswagen Golf    2\n",
       "Renault Clio       2\n",
       "Name: Winner, dtype: int64"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "winner_manu_model_cnt = coty_win_nom['Winner'].value_counts()\n",
    "winner_manu_model_cnt[winner_manu_model_cnt > 1]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Yes! Two cars, **Wolkswagen Golf** and **Renault Clio**. But, in which years?"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'Volkswagen Golf': [2013, 1992], 'Renault Clio': [2006, 1991]}"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "double_winners = winner_manu_model_cnt[winner_manu_model_cnt > 1].index\n",
    "double_winners_years = {}\n",
    "for i in range(2020,1963,-1):\n",
    "    winner_car = coty_win_nom.loc[i, 'Winner']\n",
    "    if winner_car in double_winners:\n",
    "        if winner_car in double_winners_years.keys():\n",
    "            double_winners_years[winner_car].append(i)\n",
    "        else:\n",
    "            double_winners_years[winner_car] = [i]\n",
    "double_winners_years"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "That's more like it! Volkswagen Golf won it with **Mk7** chassis in 2013, and **Mk3** in 1992. Likewise, the **3rd** and **1st generation** of Renault Clio also achieved it in 2006 and 1991, respectively.\n",
    "\n",
    "In a broader approach, now let's see which unique manufacturers have won the award **at least once** in all CotY organizations, and count how many for each. However, some necessary interventions were required to finalize it. Here are the reasons:\n",
    "\n",
    "* In 2012, **Chevrolet** has won with the model **Volt**, which is exactly the same model as **Opel Ampera**. Due to its name coming later in the corresponding field, I've got to manually add afterwards to make it fair. Well, it's the only year the American manufacturer got this award.\n",
    "\n",
    "* The Italian manufacturer, **Alfa Romeo** should not be called just as **Alfa**; that's why the name is updated to reflect the way it should be.\n",
    "\n",
    "* Be aware that **Opel** and **Opel/Vauxhall** are the same ones. So, it's better to combine them while counting their wins."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "22 different manufacturers have won the CotY award so far.\n"
     ]
    }
   ],
   "source": [
    "winners_split = coty_win_nom['Winner'].str.split()\n",
    "winners_manu_cnt = {}\n",
    "for i in range(2020,1963,-1):\n",
    "    winner_manu = winners_split[i][0]\n",
    "    if winner_manu in winners_manu_cnt.keys():\n",
    "        winners_manu_cnt[winner_manu] += 1\n",
    "    else:\n",
    "        winners_manu_cnt[winner_manu] = 1\n",
    "# Necessary interventions\n",
    "winners_manu_cnt['Chevrolet'] = 1\n",
    "winners_manu_cnt['Alfa Romeo'] = winners_manu_cnt['Alfa']\n",
    "del(winners_manu_cnt['Alfa'])\n",
    "winners_manu_cnt['Opel'] += winners_manu_cnt['Opel/Vauxhall']\n",
    "del winners_manu_cnt['Opel/Vauxhall']\n",
    "print(\"{} different manufacturers have won the CotY award so far.\".format(len(winners_manu_cnt)))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "A **bar chart** could be useful to easily see the counts for all winners. Well, which one has got the most wins?"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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L9LdQOj95mNL72UiGqvVZkZK0dtsP+HGUTmZ2pNQcPukEcQ5xXhkR51CagP02M4daZ2D069mcdO717H0WUV8XJ0YRzyxm77BgkDH2bluj3T88adustY4/pvzOy1Bq6PamJMQvHyaOTtkj7XPnKDOPjPLMsucAD2fmNRGxH/CPrhrXzmMQhtuvdGq+1qR0DjLUNjyLUks05LOugOnAUV3v5/jogYh4PiUxvRDYKp/cUcc1lER0rZ7PPYXS3PiInuFL1fktB2yYs/fk2HFJ7/yqNYFLhxi+LHO/T5PGnDVaUrO+TjnIfGuokVEebtm5CX0xntyjVO+N+6N1BeWK6NbdAyNifUpN29ycIHcSxic9NHgUMc0E1srMGUO85qVL8z9RrnY+dZh5dxKfxSj3oDx+ohMRr2b2ZmyjUpvV9ZY3UtL4Pkpi9m3K1e+X1tftlKSm835Oz9I6lbLvfmvP8G0pJ6Vz29V6Z93YjXI1+qyucWdQOmr5X0qTrsYT9sy8PjP3pjSf66c3ynW7O0qI8qyr1zF73FCaWN5L6SxlCqW519z4JvB/lPuBhtP0enYrZfvrXR6v6/Pz/cZzHPCyiHjhCPPqdPDQq/PQ7cdjrDW1m/YZY6P7h8y8K0tHOYcz5/XockrPq/N00TkzH83My2qStTKleel+XZOcTalx7u3UofO+0zvfRykXWrpfndrXTZj94kdvDDf1LLcrRoq5Ntk8ntIV/eu7m3N2zfNhyj72f3uW0VsoTVz/2DW/xShNYVcDNs2uXgV7/JGy7T6z67NTKbX8fxxi+tUo64g0IVmjJTUoM0+LiI8D+0R5YOWBlPuulqHcJ7Ijpdbgb5QD2Kcj4rOUB1m+mnIAm5fyH42I3SlXdg+h3FuyCqU3uquAn8/FbK+kXBV/T0TcSTnhumKIJiHDxZRRHoL5h3qPy+GUq7MrUm62viEz95mLuMjMU6J00/2bKM8o+yvl6vBUSu9jn673GP2JchJzYET8nHL1+Qs8ufZjYDonPhHxBeDozJwRpYe85YGfdd13NifHUhKf/aN0XX4J5bvuSOmIZdZcxnd5RNxGuYfpvFrb1HEBpfnZFpSOVhrpcjoizqKcXF1c5/9K4IX017TvVuC4KN3KP0SpAVuc0kPe4zLzgSjdk38MuDgzz5ybWDPzt5SONEbS6HpWt51fAztExJWUE87XUTrD6Ee/8XyHsl86ISL2ovwey1O62965buuXUmpS309JtB/MzIspScI1wLei9IjZ6XJ9kVF8x3naP0R53tK9lCT7tvo938kTTfOGcxqlx8sX0NPrakT8P8r69Pw66JURsTxwf2YeW6dZiJKAn0rp6GItSs3cJZQatc53fCQidqP8DvtT1qNnU/bLp1Ca7THEvWed+6cATs15eN5YzzxXoCRZC1Oaw67Z02L5gq4WGXtQluvhEfFDyr71W5ReEbsvCh1JSZZ2ARaP2R8hcE0+0f37T4APUX7vz1MuAnyZ8ky62e6drM2YX8rsSas0sYzUU4YvX77m7kU5QTiC0kb/P5TmXsdRepRaoE6zKOUAcjvlJOEoytW74Xpw67vXqVrORZSTnjsoTdRW6pmmr14H67Tvo1z5fISuHrioPbMNMf2Teruj3LtwFKUd/oP1s7+i9szVZxwJ7NUzbAHKwf2iOt9/1f+/Sanp6kz3YcqDOh+gnBxuQjnJOaVrmo0ZpofFhtaLzv1km9X3H6UkNaOdz1KUmpWbKbVYV1ISie7e9frudbDrM0fUzzypJ8C6/ibwxTn93sOts5QLDzO73n+DksT9i9IpyMV09Yw5Qpwz6/q7I080b7oAePUw069X4/ngKJbFkOt2zzSn0NPr4LysZwzRgx+lq/uDKcnHnZQaudfRZ6+D/cRTp1uB0vyss079g5LwLlLHL06pHbyrlt39O65V53kf5cLSxxm+18G9hlmWc9w/DLW86/B31XG31XXhOkryuNQcfr8FKUnnUOv0zBpv76v7e0+qMXdqHq+pv8Niw5T3TkqHMA/V5bwvsMQcYtyDhnsd7Fr/hntN7Zl+I0qy9WD9rt/t/Y5zmN/2PdNOoSRm91COfb/vLbNOt0H9/NpNfXdfvtp+dbqQlSRpvhQRX6Ek4ytn5j1jHY/Gj1ojui3wnPSEaFyp97qtnZnD3YMrjXveoyVJmi9FxIsiYmtKkjXdJEtD+A6l1nCrsQ5ET4iIp1FqKj831rFI88IaLUnSfCkiZlLu9fkz8M7s875C/XeJiM2AZTPz0LGORUW9x+tFmen9WZrQTLQkSZIkqWE2HZQkSZKkhploSZIkSVLDJtRztJZffvmcOnXqWIchSZIkSQCcd955szJzcu/wCZVoTZ06lRkzZox1GJIkSZIEQERcP9Rwmw5KkiRJUsNMtCRJkiSpYSZakiRJktQwEy1JkiRJapiJliRJkiQ1zERLkiRJkhpmoiVJkiRJDTPRkiRJkqSGtZ5oRcSbIuJvEfFQRFwXER9vOwZJkiRJGqRWE62I2AD4LfBXYAvgAOAbEfHRNuOQJEmSpEGa1HJ5uwNnZOaO9f1xEbEMsHtE/CgzH245HkmSJElqXNtNB9cBTugZdhywDLBey7FIkiRJ0kC0nWg9BeittXqo/n1ey7FIkiRJ0kC03XTwauClPcNeVv8uO9QHImInYCeAKVOmDC6yubDW7/7TWlmXbLlQa2VJkiRJmjdt12jtD7wxIt4bEctExGuBT9Rxjw71gcycnpnTMnPa5MmTWwtUkiRJkuZW24nWAZRkaz/gTkoPhF+q425tORZJkiRJGohWE63MfDQzPwRMBl4ArAicXUefPewHJUmSJGkCafseLQAy8y7gLoCI+ABwZmZePhaxSJIkSVLTWk20ImJd4BXAhcBSwDbAa+swSZIkSZovtH2P1n+AtwG/Bw4EFgM2yMy/tRyHJEmSJA1MqzVamXkeT+7eXZIkSZLmK23XaEmSJEnSfM9ES5IkSZIaZqIlSZIkSQ0z0ZIkSZKkhploSZIkSVLDTLQkSZIkqWEmWpIkSZLUMBMtSZIkSWqYiZYkSZIkNcxES5IkSZIaZqIlSZIkSQ0z0ZIkSZKkhploSZIkSVLDTLQkSZIkqWEmWpIkSZLUMBMtSZIkSWqYiZYkSZIkNcxES5IkSZIaZqIlSZIkSQ0z0ZIkSZKkhploSZIkSVLDWk+0ImLriDg/Iu6LiBsj4qCIWLntOCRJkiRpUFpNtCLiDcBhwJnAG4FPAxsBR0WEtWuSJEmS5guTWi7v7cD5mfmhzoCIuAf4A7AGcFnL8UiSJElS49quRVoI+FfPsLvr32g5FkmSJEkaiLYTrQOADSNiu4hYKiKeA+wFnJyZl7YciyRJkiQNRKuJVmYeDWwPTKfUbF0BLAi8uc04JEmSJGmQ2u4M41XA/sD3gFcBWwPLAr+LiAWH+cxOETEjImbcfvvt7QUrSZIkSXOp7c4w9gb+mJmf7gyIiAuByym9EP629wOZOZ1SA8a0adOypTglSZIkaa61fY/Wc4ELuwdk5hXAA8CzWo5FkiRJkgai7UTreuDF3QMi4nnAosDMlmORJEmSpIFou+ng/sB3IuIm4FhgRWB3SpJ1TMuxSJIkSdJAtJ1ofR94GHg/sDPlGVpnAJ/JzPtbjkWSJEmSBqLVRCszE9ivviRJkiRpvtT2PVqSJEmSNN8z0ZIkSZKkhploSZIkSVLDTLQkSZIkqWEmWpIkSZLUMBMtSZIkSWqYiZYkSZIkNcxES5IkSZIaZqIlSZIkSQ0z0ZIkSZKkhploSZIkSVLDTLQkSZIkqWEmWpIkSZLUMBMtSZIkSWqYiZYkSZIkNcxES5IkSZIaZqIlSZIkSQ0z0ZIkSZKkhploSZIkSVLDTLQkSZIkqWEmWpIkSZLUMBMtSZIkSWpYq4lWRJwSETnMa702Y5EkSZKkQZnUcnkfAJbqGfYl4EXAuS3HIkmSJEkD0WqilZmXdr+PiIWBacCvM/ORNmORJEmSpEEZ63u0NgOWAQ4b4zgkSZIkqTFjnWhtDdwInD7GcUiSJElSY8Ys0YqIxYAtKM0Gc4TpdoqIGREx4/bbb28vQEmSJEmaS2NZo7UFsARzaDaYmdMzc1pmTps8eXI7kUmSJEnSPBjLRGtr4OrMnDGGMUiSJElS48Yk0YqIpwL/DzvBkCRJkjQfGqsarS2BRTDRkiRJkjQfGqtEa2vgosy8bIzKlyRJkqSBaT3Riojlgf8BftV22ZIkSZLUhkltF5iZs4CF2i5XkiRJktoy1g8sliRJkqT5jomWJEmSJDXMREuSJEmSGmaiJUmSJEkNM9GSJEmSpIaZaEmSJElSw0y0JEmSJKlhJlqSJEmS1DATLUmSJElqmImWJEmSJDXMREuSJEmSGmaiJUmSJEkNM9GSJEmSpIaZaEmSJElSw0y0JEmSJKlhJlqSJEmS1DATLUmSJElqmImWJEmSJDXMREuSJEmSGmaiJUmSJEkNM9GSJEmSpIb1lWhFxAERsdow41aNiAP6LTAiJkXEbhFxVUQ8FBH/jIjv9Pt5SZIkSRrv+q3R2h6YPMy45YF3jaLMnwMfAb4NbArsBjwwis9LkiRJ0rg2aRTT5jDD1wZu72cGEbEZsDXwwsy8dBRlS5IkSdKEMWyiFRG7ALvUtwn8PiIe6pnsKcCKwIF9lvce4CSTLEmSJEnzs5FqtC4FjgQC+DhwMnBzzzQPA5cDh/dZ3suBP0bED4Dtavl/Aj6UmTeNIm5JkiRJGreGTbQy83jgeICIuBf4aWbeOI/lPY1yv9dFlCaESwLfBH4XEetm5nDNEyVJkiRpwujrHq3M3LOh8qK+3piZdwBExM3AqcCrgROf9IGInYCdAKZMmdJQGPOXla5bv7Wybl7tzHEfhyRJkjTW+u4MIyLeArwZeDrl3qzZZObL+pjNXcC1nSSrOoPSBHFNhki0MnM6MB1g2rRp1nhJkiRJGvf6SrQiYg9gd0qTv0spidHcuAxYZKgigMfmcp6SJEmSNK70W6O1A/D1zPzsPJZ3FLBnRCyfmbPqsI2AhShJnCRJkiRNeP0+sHhJhmjWNxemA3cA/xcRW0TE24GDgRMy84wG5i9JkiRJY67fROtXwGbzWlhm3kPp9OKuOs8fUhK4/53XeUuSJEnSeNFv08ETgW9ExPKULt/v7p0gM4/pZ0aZeTWwed8RSpIkSdIE02+i9ev6dyrwriHGJ7BgEwFJkiRJ0kTXb6K12kCjkCRJkqT5SL8PLL5+0IFIkiRJ0vyi3+dorTmnaTLz0nkPR5IkSZImvn6bDv6dch/WSLxHS5IkSZLoP9F61RDDlgU2ra9dGotIkiRJkia4fu/ROnWYUb+LiL0oz8E6qrGoJEmSJGkC6/eBxSM5GXhjA/ORJEmSpPlCE4nW6xjiAcaSJEmS9N+q314HDx9i8MLAc4HVgc82GZQkSZIkTWT9doYxeYhhDwKnAx/PzGOaC0mSJEmSJrZ+O8MYqtdBSZIkSdIQ+q3RelxELA8sA9yZmXc0H5IkSZIkTWx9d4YREW+LiMuAW4HLgdsi4rKIeOvAopMkSZKkCajfzjC2AX4JHAt8jZJsrQi8DfhVRCyYmb8aWJSSJEmSNIH023Twc8D0zNy5Z/hBEbE/8HnAREuSJEmS6L/p4LOBI4cZd2QdL0mSJEmi/0TrVmDaMOOm1fGSJEmSJPpvOvhzYI+IWBD4DSWxWgF4K6XZ4NcGE54kSZIkTTz9JlpfAhYCdgP27Br+APDtOl6SJEmSRP8PLH4M+FxEfBtYG1gJuBn4e2beNcD4JEmSJGnCGdUDi2tSdfqAYpEkSZKk+cKwnWFExPMi4o6I2HyEaTaPiFkR8cJ+CouI7SMih3j1dhsvSZIkSRPWSDVanwLOzMxjhpsgM4+JiNOBTwDbjaLcV1Pu7+q4dhSflSRJkqRxbaREa1NKAjUnvwL2HmW552bmfaP8jCRJkiRNCCM9R2t54J99zONGYHIz4UiSJEnSxDdSonUnsEof81ilTjsa10TEIxFxRUS8b5SflSRJkqRxbaSmg6cCOwC/nsM83lOn7cfNwBeAvwILAtsA+0fEYpn5naE+EBE7ATsBTJkypc9i9N9spevWb62sm1c7c9zGIEmSpLEzUqL1deCciETMiuAAACAASURBVDgA+GRmzlZrFRFLUx5W/Erg5f0Ulpl/Bv7cNejYiFgE+HxEfK8+r6v3M9OB6QDTpk3LfsqRJEmSpLE0bKKVmRdGxDbAgcA2ETEDuAFIYAowDXgEeHtmXjQPMfwG+F9gKvY+KEmSJGk+MNI9WmTmb4E1gK8BDwEvBl4CPAx8FVijTtMEa6skSZIkzRdGajoIQGbeDHxpgDFsBcwCrh9gGZIkSZLUmjkmWk2KiCMpHWH8jdIZxtvq6yND3Z8lSZIkSRNRq4kWcAWll8JnAAFcCmyXmQe3HIckSZIkDUyriVZmfhb4bJtlSpIkSVLbRuwMQ5IkSZI0enNMtCJikYj4XES8sI2AJEmSJGmim2OilZkPAZ8Dlh58OJIkSZI08fXbdPAcyvOzJEmSJElz0G9nGJ8CDo2Ih4FjgFvpecBwZv674dgkSZIkaULqN9E6p/79PvC9YaZZcN7DkSRJkqSJr99E6z301GBJkiRJkobWV6KVmQcOOA5JkiRJmm+M6oHFEbEmpVOMZwAHZOYtEfFs4NbMvHcQAUqSJEnSRNNXohURSwAHAG8B/lM/9yfgFuCrwA3AJwcUoyRJkiRNKP12774PsD7wP8CSQHSNOwbYrOG4JEmSJGnC6rfp4JuBXTLz5Ijo7V3wemDVZsOSJEmSpImr3xqtRYE7hhm3JPBoM+FIkiRJ0sTXb6J1LrDdMOPeApzZTDiSJEmSNPH123Tw88AJEXECcATlmVqbR8THKInWRgOKT5IkSZImnL5qtDLzDEpHGIsAP6B0hrEn8Exgk8w8d2ARSpIkSdIE0/dztDLzL8CGEbEosAxwd2b+e2CRSZIkSdIENaoHFgNk5gPAAwOIRZIkSZLmC30nWhExjdLN+9OBp/SMzsx8W5OBSZIkSdJE1VeiFRHvp9ybdQdwFfDwIIOSJEmSpIms3xqtTwI/B3bOzEcGGI8kSZIkTXj9PkdrBeCwppOsiFglIu6LiIyIJZqctyRJkiSNlX4TrWOBlw+g/G8B9w1gvpIkSZI0ZvptOvhDYHpELAQcD9zdO0FmXjqagiNiQ2Az4KuUhEuSJEmS5gv9Jlon179fBHbvGRdAAgv2W2hELAjsC3yJIZI2SZIkSZrI+k20XtVwuTtTuoj/IbBtw/OWJEmSpDHVV6KVmac2VWBELAd8GXhHZv4nIpqatSRJkiSNC30/sLgjIiYBC/cOz8x/9zmLrwDnZOYxfZa3E7ATwJQpU/oNUxKw0nXrt1bWzaud2VpZkiRJ411fvQ5GxFIR8YOIuAl4ELh3iFc/81kLeA+wZ0QsHRFLA4vV0U+NiEV7P5OZ0zNzWmZOmzx5cj/FSJIkSdKY6rdG68fA64GfApcCD89leasDCwFnDTHun8DPgB3nct6SJEmSNC70m2i9FvhYZv50Hss7gyd3rLEZ8Glgc+DaeZy/JEmSJI25fhOt+yk1TvMkM2cBp3QPi4ip9d/TM9OHF0uSJEma8Pq6RwvYG/hARPQ7vSRJkiT91+q3RmsV4IXAFRFxMk9+yHBm5qfnJoDMPBA4cG4+K0mSJEnjUb+J1luAx+r0rxlifFLus5IkSZKk/3r9PrB4tUEHIkmSJEnzC++5kiRJkqSGDVujFRGbA2dk5j31/xFl5jGNRiZJkiRJE9RITQePAtYF/lr/TyCGmTaBBZsNTZIkSZImppESrdWAm7v+lyRJkiT1YaREayXgJoDMvL6dcCRJkiRp4hsp0ToTeDAiZtT//wKcmZl3tBKZJEmSJE1QIyVam1Hu0VofeB/wKSAj4ipK0tVJvC4feJSSJEmSNIEMm2hl5nHAcQAREcBawAbAesCGwLspidddlITrDYMPV5IkSZLGv76eo5XF3zPzx5m5PbAG8GrgWGAZ4HWDC1GSJEmSJpaRmg4+LiIWB15OaUa4PqVJ4ZLApcBPgLMGFaAkSZIkTTQjPbD47TyRWL0AuBs4m9Ixxt7AOZl5XxtBSpIkSdJEMlKN1iHA/cBBwDsz85J2QpIkSZKkiW2ke7S+BVwAbA/8NSJOi4hvRMSbImLFVqKTJEmSpAlopF4HPw0QEZOAF1F6G1wf2AZ4ekRcR7k36yzgrMw8f/DhSpIkSdL4N8fOMDLzEeDc+vo+QESsQkm63gV8r995SZIkSdJ/g76To4hYBHgpT3SQsR4wuY6+ofnQJEmSJGliGqnXwZV5IqlaH1gHWBh4BLgQOAz4C/CXzLxp8KFKkiRJ0sQwUo3WP4EE7qLch7UnpWv3v2bmAy3EJkmSJEkT0kiJ1o7AmZl5eVvBSJIkSdL8YKReBw9oMxBJkiRJml+M9BytxkXEWyLizIi4IyIejIgrIuLzEbFwm3FIkiRJ0iC13SX7csDJlIch3w28DNgDeBrwoZZjkSRJkqSBaDXRyswf9ww6OSKWAj4YER/OzGwzHkmSJEkahFabDg7jDkq38ZIkSZI0X2i76SAAEbEgsAjwYuAjwH7WZkmSJEmaX4xJogXcT0m0AA4Cdh1uwojYCdgJYMqUKYOPTFLjVrpu/dbKunm1M1srS5IkaThj1XRwfWBD4BPAG4EfDDdhZk7PzGmZOW3y5MltxSdJkiRJc21MarQy8/z67xkRMQv4RUTsnZnXjEU8kiRJktSk8dAZRifpWm1Mo5AkSZKkhoyHRGuD+ve6MY1CkiRJkhrSatPBiPgTcAJwCfAoJcn6BPBrmw1KkiRJml+0fY/WucD2wFTgEeBa4DPA/i3HIUmSJEkD02qilZlfAL7QZpmSJEmS1LbxcI+WJEmSJM1XTLQkSZIkqWEmWpIkSZLUMBMtSZIkSWqYiZYkSZIkNcxES5IkSZIaZqIlSZIkSQ0z0ZIkSZKkhploSZIkSVLDTLQkSZIkqWEmWpIkSZLUMBMtSZIkSWqYiZYkSZIkNcxES5IkSZIaZqIlSZIkSQ0z0ZIkSZKkhploSZIkSVLDTLQkSZIkqWEmWpIkSZLUMBMtSZIkSWqYiZYkSZIkNazVRCsi3hoRf4yIGyPivog4LyK2aTMGSZIkSRq0SS2X93HgOuBjwCxgc+DQiFg+M/dtORZJkiRJGoi2E60tMnNW1/uTImJlSgJmoiVJkiRpvtBq08GeJKvjAmCFNuOQJEmSpEEaD51hrA9cOtZBSJIkSVJT2m46OJuI+B/gjcB7xjIOSZIkSWrSmCVaETEVOBT4Q2YeOMJ0OwE7AUyZMqWN0CTNp647ct3Wylptq7PHbQzGMX7jkCTNP8ak6WBELAscC9wAvGOkaTNzemZOy8xpkydPbiU+SZIkSZoXrSdaEbEYcBSwMPC6zLy/7RgkSZIkaZBabToYEZOAI4DVgQ0y87Y2y5ckSZKkNrR9j9aPKA8p3gVYNiK6G8VfkJkPtRyPJEmSJDWu7URr0/r3e0OMWw2Y2V4okiRJkjQYrSZamTm1zfIkSZIkaSyMhwcWS5IkSdJ8xURLkiRJkhpmoiVJkiRJDTPRkiRJkqSGmWhJkiRJUsNMtCRJkiSpYSZakiRJktQwEy1JkiRJapiJliRJkiQ1zERLkiRJkhpmoiVJkiRJDTPRkiRJkqSGmWhJkiRJUsNMtCRJkiSpYSZakiRJktQwEy1JkiRJapiJliRJkiQ1zERLkiRJkhpmoiVJkiRJDTPRkiRJkqSGmWhJkiRJUsNMtCRJkiSpYa0nWhHx7Ij4cURcFBGPRsQpbccgSZIkSYM0aQzKXAvYHDgbWHgMypckSZKkgRqLpoP/l5nPyMy3ApeMQfmSJEmSNFCtJ1qZ+VjbZUqSJElSm+wMQ5IkSZIaNhb3aI1KROwE7AQwZcqUMY5GkqTBuO7IdVsra7WtzjaOCRTHeIjBOMZnHOMhhvEUx3gz7mu0MnN6Zk7LzGmTJ08e63AkSZIkaY7GfaIlSZIkSRONiZYkSZIkNcxES5IkSZIa1npnGBGxGOWBxQCrAEtFxFvq+2My899txyRJkiRJTRqLXgdXAI7oGdZ5vxows9VoJEmSJKlhrSdamTkTiLbLlSRJkqS2eI+WJEmSJDXMREuSJEmSGmaiJUmSJEkNM9GSJEmSpIaZaEmSJElSw0y0JEmSJKlhJlqSJEmS1DATLUmSJElqmImWJEmSJDXMREuSJEmSGmaiJUmSJEkNM9GSJEmSpIaZaEmSJElSw0y0JEmSJKlhJlqSJEmS1DATLUmSJElqmImWJEmSJDXMREuSJEmSGmaiJUmSJEkNM9GSJEmSpIaZaEmSJElSw0y0JEmSJKlhJlqSJEmS1DATLUmSJElqmImWJEmSJDXMREuSJEmSGmaiJUmSJEkNi8wc6xj6FhG3A9ePdRwNWB6YNdZBMD7iGA8xgHH0Gg9xjIcYwDh6jYc4xkMMYBy9xkMc4yEGMI5e4yGO8RADGEev8RLHvFo1Myf3DpxQidb8IiJmZOY04xgfMRjH+IxjPMRgHOMzjvEQg3GMzzjGQwzGMT7jGA8xGMf4jWNQbDooSZIkSQ0z0ZIkSZKkhplojY3pYx1ANR7iGA8xgHH0Gg9xjIcYwDh6jYc4xkMMYBy9xkMc4yEGMI5e4yGO8RADGEev8RLHQHiPliRJkiQ1zBotSZIkSWqYiZYkSZKkVkREjHUMbTHR0n+1qMY6Do0frg+aWxGxQH25DlUR4XmGpMdFxAKZmRHxyohYeqzjGTR3gPqvExFLRsRKAFn1jG8t+apFjevtcKhl0ebyaaOcbvUAEJ3yx0syHhErdE7kxzoWDS0zH6uvMbv5eTysqx0RMQnYOSKeMtaxtK1rH/KCsY5lPBv0+jqetodu4+W4MkY6+8ejgFXHMpA2eMBuQUQsVP++KSIWHet4uo1lPF0Hond3Ep/ecQPyGuCwiJgeEV+MiK0jYp2IWBKGTr4GpRb1WOd9J/EaTzvgzrKIiEV6h7VRdk2Mn9pGeRHxwYh4cS13kezSNU2rv09ETIqI9wJnAQ8DMyLijzXWDduKo8ayRES8LyIWbrPc4UTEguNhW4mIhSLi7RFxUETsExGbtp1cdJbDUBeO2oyjp8yXAp/JzAfrMmpzuxnTE9m6D5kC/KTG8/hFkvr/pLZiiYinRcTk8XiRZtDHkiH23ePi+Np9XBmL437dd74kIl7de/41aHXbWAj4HXBnm2WPhdY29P9mmfmf+u9vM7Ozs+0cFB+NiOcBl7d9FTQingZ8GPhcRMQYXIVdAHgU+ApwWFdcC9bl8jLg/Mx8pOFybwSOBpamXE15AbAw8GBE3A5cDdwAnJKZsxou+3H1ZPU3wBnAXyjf9QGeuNrTmW6B7mSsDZ0yI+LpwLuAlYF/RsQ/KctmFnBDZt47wLKfAbwHWAO4PSLurGXfSNlebmi6bGBF4L76//4RsSpwHnARcAFwxQDWxyF1/e6vBD4DvL+OOgw4H9gX+ActXBHs2j9sAOyYmT+OiIUz8+FBlz2SzHx0LMuHx7fj6cBawInAmsB3gZMiYpe2YqwnLxtQ9mv3UfYn945l7RqwGHBCRCyRmffNceoG9ZxgB+WYO9CLaJ3tJCJeTNkuNwAerPF078NfCHwEePegYqnxbADsTtlfPwb8IyKuAv4FHD+I/XefcXX28c8HVszMEwZUzhqU/ebvgXPq8XVMRcSCwMaUixAXAWdn5l30HPcHVHZn/Xwp5bxrAeCROurwzPxZCzF0jmvPA54NHBIR22fmdYMue6yYaA1I1wq9PrArcBlwDcy+w42IVYA/ZOZzWoztqZn5L+BtwIY1pu6D0hRg3cw8fIAxrAx8PCLuBRYFVoyI+zNzVteJyS8oJy+NysxzgHPqCdJK9bUi8CzgGZTEa0vgemDWAJPQpYCbKCfS7wGWiIirgauAc4AzMvPytpOsqnNl7euUJOtWyjL6f8B/gIWAPSknlk1bgHJSsCvlhOR84CFgdeD5wLLAwcDPB1D2VzPzwfr/0ZQkbyrwDuCDwMMR8W/gHZl5xwDK79b5DV4H/Dkz/xwRuwHHZuaONek9FlpJxoNyIvAY5cIA3UlWPXlorclcLe8VwOuBaynryOV1v9aKrmW+EbAOZV96fz2BnEZJhN8L7N9SPJ8CtgCWp6y3K9b97DLAuS0npZ31ZSqwObBqRPwCuI6yX721aztrvvByAr8R5bh7Xl0v2kw4Xwm8mnIyfXNEfA64n7KuXgLsxBPb90BExBLAj4CTKRcPvw/8gXJx9STgT4Msfw46+/jtgbdHxHaZeXxETMrMRyJiKnBfAxc6lwH+h3Kus2JE3ArMoOw3j8rMG9q6yNz5bsAXKYlWAB8CVqoXeG8BPpqZpwwqhq7vOR34NfBX4AFgbWCPuk/7yaDKrzF0jlOTgSWBFYArI+IGynnPDOD3mXntIONok4nWgHSt0I9QThLfBywTEfcDVwKnUE5SX0S52tSm3aK0G58CXFaTvUnAnfUK1w6UhOPwAZ7ArVxfz6WctO8OPFJPHm8EngMMpOzOjrWeKF4fEf+gbPR/BBYHlgOeCVwMg2vakJmzIuKjlMRlXWBn4GWUWoodgK/WK7G/zcz3DSKGEWLrnJRtAayembfB4wfv51JOcq+tw5o+UHV+802BbTPzvFrOUyjr7Aupv02TotyUu3pE3AbMyszf1NrnJSgHg6cDqwGrtpBkwRMnhlMotWoA04Az6/9rUPYt57QQS8ergR0iYkVKk6jLMvOWtk7iO7XdwDaUk5QHKMn/6sB/aq3nDzPzG23EUz0fuKRTO1C3hxkR8XPgtbSQaEXEMyk1JK/KzKsi4s7MvD0ing18k5J0tKZrv70AcCiwCvBWyvr6L8q+/suZ+Y+myuxqCbEjpRb+AUqyS93H3wB8oaUT2Z8Df6YkN1dSvv/KlARsIcox5ouDiKHrmP0KYKHM/GhEPAe4KjO3jIivAgtn5r8HUX6fOuvHGyn7sw9ExDVdJ9d7Ab+i3MMz1zLzbOD5dT++KiXx3ZiS4G0XEbtm5uktJVudfeTOlOP7UfVi/CqUY9oWlHV2oGorlZUy8+tdg8+KiGuA3SPigDb255l5ImXf2bm4/6r6+hJlWX2va38/oZloDVhm/hXYOiK+TNnhXkCpLVkf2I5ywrhby2EdS2laMo1Sq3IacBcl6bqixrd3nXYgV90ycwblStbOlCuw11OuCq9R4/oXAzoQdXaoNWl4G+WEfgVgZma+OyKWojQbbOMK6EN1Z/tBypXOj1GamiwF7AK8HBhYzeJIorSh3p3ym9wGUJv/zKgv6rBGl1PXSdr3gbUj4qLMfKReAb+yvgZhc0ot2t8oCfgNlNrFG4HbM/Nq4JRo6T6HruWwP6XWFcr+YuOIuIWyD9mv5VguBQ6iNPv4CiWvuJvSzv5jnYS8BdsBR2fmlzsD6snkFpRa4oHrWibnA9vWq/IH1e15CUoN1+WDjKHrpHp9StJ7VUS8lbI/BVgQWK6tmsZenavjUe5HWoWyb38WZZ/S9MWKzu/xaWDvzNw/Ii6mHEfeWcttpelYZt4N3B0RH8jMKwHqcWUdyvHu7Mwc9Hq6Dk/sp7fkif3m1ZQkbMzUWt8FgGUzc6uI+Amwb0RsUdfnLSgtJuZJZ19d53ldfR1eL9p9E/hgRFzWQM3ZHNX9wiLAqXSdX2TmjZRjzDGDjqFajnJ8W7cmoh13A6u1mdhExHKUVgA3UFow/YKSBAPjo2l4E0y0WlAPhl/oGvT3nvGt3piZmacBp0XEg5m5d72iMo1yYvAy4FuUe4cGsqLX5k9XUKqtf5lPtBM/uO6Ing7cPahag66rJO+m7NAPo3z3xeskb6Yknr8cRPm94VBqLl4I7Ne1w78P+HREHEW5CtyarpO3TYHvADMjYlfg1EEfkLqa3D4f+AHlytYqEXEi5f6ouwdY/PGUZf0synawA6U26yLKvQ2P37tHbQY8aPWE4G/5xD0MP6RcBHk/cATl3r7e+z8G6ZfAIZSr8s+k1G5OpdRAD/ym5q790VmU/Uf3uCt54gJRazLz1Nos7jMR8QFKDeOLKfuQXwy47M7vfgNl81mVsi87vQ5/DWX9HRMRsTolqXoB8JfMPHJQZdX9xpLAMpnZqUV8BqUJ8HnAZ2l/WTwWETtQlsEFmXnYnD4wr7rWiQuBTq3VLOCOemL7JgZ8AWAkXbVH61Jac0Cp5fkj8JN60fGRzLxqXsvq3S92JV4PAh+pF5YHfuGs65j6dMo6eUREfJ1yTLt50OX3xHFRPa84LCIOpDQjXQb4APDbluJYiFLbvxWwfETcQ9mHnQVcmZljtn4OQozRha7/KjWRmkq5MXZVytWL6ykbWStXX3vi6bQVJiKWpWxkA0tsespeiHKi+jzKTdv/pNTknE659+OiHPB9Fl1NTE4BpmfmoRFxJOU+hq9HxKHApZm51wCbTvbG9FXKyf0HMvPKmnAuSTkgvqjJJjajiGkK8HZKErgxpdbvTsr6u0dm/n6AZT+FckIwjdI07NmUg3IrTcMi4iuUZOJkyhXADSnN1e4B3lRrZAdZfmcd3RJ4TWZ+oCsJXYnyW1zcYoLVieuplAR8eUqN0g11+GJtNUWq28ZJlGXwFcq9jFe3UfZIapLzGmA9yon9IZl5T0tlL0C5Qr80pfnNTykdUawDfC8H1NnAMLF01t3XAp+iXNBdCjghM3eNiNcDf8/MmQ2W2elc4YWU+5K2pGy3R2Tm2nWbuSwzB/7Mnq7vvznwccrFosUpTffeXbfpazNz4ElfrUW7j3KMP45yq8JRwCc7NW1jpa4fL8nMr9b3q1Caeq4KPJqZL5vH+a9EOXZdCdzSu3+Kch/YuZk5eV7KGWVMG1JaqjyN8rvcT7kgcyelKeFpLcTQ6TH2/ZQLzWtSaoO/BhyWmQO7YNa1nW4OfINy+8wjlJZFF1KaOB+Vmdu21JyzFSZaA9S1Ur2Y0gvVUynV9i+iVGEvCpyZmZ8cg5imUu5xeB/lnqBbKc0av9XWFZYo98S8CtiEciL7HMrVpRuBkzJzhwGXfzRweGb+Ikr75K0z89za3OQTmXlcG4lW3fE9Dfg2Zad3BeU3eQUl4dtukOX3K0ovletQEqCjMvOoaLENdZQepN4I3JiZjdc2diUyS1KaSi6ZXT0MRsQbKZ0vfDwH3FtXRKxDuQgxndK740e7l3U9UD09M6cPMo5aVufEcTPgE5SbtjcBfpqZX6ixnJ+Ztww6lhrPZMoJ7HMpTSofo3R7fysl6dq3jTi64nkmpYnvmpQT+7+1WX5XHEsCH6XcR7cQpUnjoZTe1lo70HetL2dT1pGfRsRJlGWzX0QcQekA6pCmT6bqvnRtyjFkAUrz40Xq677M3KqpskaIofP9T6Tc1L9v/c4XZuZXIuJgSgcd3x1gDItSLtxdll3Neetx/55Bnkz3q8b4UM7eOdjGlFrg/XL2e4jmZv7bUM5vZv7/9s47zIry+uOfI12xgChgx45i74otFizR2GKviT12jf2nJsZurDG22KIxJrGXWDCKHbsIgg0EBRWwgaAgyvn98X3HHTYLotyZ2ew9n+fhYffeuztn75155z3te1BZ3IcoazISqQxvifptd56V48yEHXOj99xz33dFwcPFUO/e8sAN7n5vkbak4/8JuDALdJQVTE7HysRObgI+cvcTzeyPKBBwDnK+rnQJo5SutlwUUTpYLJmyzv4oHbq/mV2ILvIHkPpP/xn8fBFkZYp/QBmCNVBEYU3Un9IepZCLObiye63dfUoqA7sr/cueXxwtgGVEmS4EzjOz75DE7Itmtg0q5cuU1Qq70HMb56PQtbgLijBtgkrWzkTnSSWkz+pX6KbwGvCQuz9ETq2qKCfL1NNxFOrreB9t2N5CUftCyG34uqIsaw/Uo5XxKsoOlCGJfD4qN+qCZML3RvL6mbz9GWgTXeaN8kzg+rRZ7o/eI5Ai43fIASscl8jDWWjz3AWJhSyKggClzK7Kbaa3Q+vmSPR5tQOON7MdUXa+zEybAee5+5lm1t4LVPWbEbk1YX7UjwIKoj2Xvl4JlSTXhJQleMXdJ7oEjl7JPfdHdD8biCS+C6fR359lvldFpdAgAYBCSghza8E2SBBkx9xzbdH52aaIY/8EJgG/SHa96u7vuHs/M1uHhn67WeEZVAreI/1bFVUVOfoMngbKCHLfDOyEFGvXROv3MG/o3WuNzpUiy+JJx5oTBfyfMrM7gT95KtEsKYOUfa5LIrEYgNWAq1z9pVPQe9GiCEerWLKTdnXU9wS62K9x99tMEsBTmvzJ4shO9I1QSVJWC/uumT0K/NvMVi+qNCplDKYCmNkJKCr9NNrID3SpDl2Rni/6wu+P6sIPAyaY2WAUFT+upDKo7LNYAngh/a33pn+VkMvqdEPRpc7I8TjF3edI2YtviixFSpHOv6Bym0mo1OIyM9sMRf9uKTiLNhSVDD6fon8D0HW6NRKDKBx339zMegF3AF+ioMx8qNTkA9TUn50nRQ/8zN7rrjRI6vegQe1wfeDsIm1owqYJZjYZmJQc8KyksOyBrKcj5+Y2M3uOBudzj2RLYY5WztlbHgUlFkPO+KfAMJNk9ECvoN/BGoaRbm9mVyD1u9fSutIReBFqJqRzCGkelZkdh8qwhqEN7UvAPmWXIKUg1S3AXmb2NjC3q5dvPlTS+ExRh07/90HlmZPSZzHV3b9JAQBH2YPKMLM5kAPSFQVpFk37gneRQz7LQhiusubvZy2a2iTmR+W1Q4FPS6hW6YCymt+Y2fwoSDkSiVEMRPeWt4APythzpCDhXma2MUoAnGpm17n7k2VcI7n3+3YaxHA+AXqYFFI3Q+XgUO44hkIJR6tAchuUQTQ0inegwbnaipJmrORsyiZyv4DKXYbknhtjZj1oUKwqyobsffkCXUzbo8yJmwQHvgDOLboUyTW88A9mdg/axH4BjHP3oWVEd3K/fwSwjpndWFYZ3gzIhkjvACzi7hub2SYoAwq6MW6ChpDWuuxnmrlE7r68SUZ8rbShnAoc6O6FCQzk/qbfmtkA1I+0GipHegiVuNCC0AAAIABJREFUopSCuw8ys93c/ZVkW3sUqOkFPJ6CEoWNH8iTyl36IwXVvyJn+z3TnKa27j5oxr+hprashwJXnwKj05rxFrphlyJ1n7tO56Jh09yDhqzNqkimuEiyTfXp6Lp9EGUseiAZ8e6oX6lURys5gFNSxPwGYGegjWnO1xrAzen5WV4/0r3sSnefnM7R9dJTjoISnwLvm9lHXoIQRbIpC1bdjRQ6HwbapWqW5YHrvLg+5GwjOztqT8Dd88HcDahwflZujd8YZaD7oF6lzui8XQ2VRM/SfTA5tCej1oDnANz9sxS8+g6tX4VXAaQ9xvXpnBhjZgujHs510P5rO5SVfzZ9XQru/riZDUFBiltTkP0Mr2Hf5A9wJfrMQdntK1FZ/iOeSq/LDo4USThaBZMiWxfSUNJyA1KT2xbNrSq0qb4p0k3ur8BNpubhgaicYGVU7jK2pDTyTaicowvawK8CnIQ2LhOKPHCKqJ2MFvdhaA7OY+m5MmuW50QlHosAW5rq+p9FCl01nxU1E2Sf+So03JD3oKHEdTnUDwMNTlmtWTl3vP1RthP0WRWqwJg2SCuixvVbzOx2oIu7jyzyuDNggpkdht7z4e7+CA1ztEohXQ/jzOwqtHE/Kj2+BiqbK0OdM7OlO3A1Grz6GXK4nkWllP1Q1rEsW9ojSeadzewy1MD/tklpr7W7vzbj3zBreEP/4CqoOmF4zrau6FotTfDAzOZz97HZJtndn0llYPujUqElgafc/bL0/CzfX5IT8VT6epyZ7YLKSJdH5YqLoOqNURRUrpeRgpSfZU5UyrSuZWa/QuJPk4E73P0vRdmQe0+vRRvoyei6GIfeix5IXbVqFkTCC1lp9kfAG2b2CLXJSm+BHJlz4fuWhLNQddEYJKbzf9P96RqR7SXSfeU01HN9O/Bo7jULIOGrwjGzzsnhXBqVOj+BnPJj0RiZ4SXYMAf6jD9K++NnUQCzG9UO0S6McLQKIKVAP3X3z9PCly83uguVinUBdq3CPgB3vzuVYh2IFqU50cZl3xJtmIRKw0ajkpvHzOwTYHnXvKYiuQNtXt9DJTe7mNkfgK2yUqSSmIQ2h/Ohm8CKqOflDNMAx/Vm9MO1JudgPo0GOl6BeipOTo+vDlyfvbygYz8J7JQ28uuhSD0oCvpEUz9bK5LjeyPwlWlW1QDgZVMT7/Aij52zISsJ2xPN/1kAbZQ6pY3TEe7+dBm2wPczbzq5+2OmYbC7oYzN9cClqASoUHLBj03Q3JVTzGwtpBrW28wuBj4vMyOcyrJuRY7mEUBH0wDy9Wgosaw5KVp/BbouXkZCS1ub2TVZ9sLdR6N1tUyuSpvGN9F6PgCJPhStEJo12P8MzQ17LLeBz5T3ytjIng6sbA3z9waigNGNZQXucjyOMqo7omumHVo/T3b3N2b0gyXxDbC5mY1Am+sx7j7J1WNXC7ZAPcXZNXAYGkdxNFpPDzGzZ939wen9glrgDWJog5CC78HZc7lg9lY0jGOoOWbWCmU62wG3mdna6Nz8CAUj3kX390IVD62hJ/1ktEY+gd6Xt9A68Y2VNKOybEJ1sABsWqnwI1CK9N/Au16x2k+urKE7kqpujRaeUV6CFLFNK8O7KHJ0PkUlexPNbFfgV+6+eYE29EQL23z5qGpyKr5z9yOKOnYjO5rMGqYoz9KoJKuKrFbWOH0ZcgC3R+U/O6Oo7JG1Po8bZxHN7FhUXrElikquizaOv3P392p57EZ2zIHUHudFEfjFkaM5L1IILTw4krtG3kLlHH9Pj8+DRDK+paQ+wtx6cRGS5y5rqGZjO7L35Fx0XRyTSrHmd/e9Tf2eXdz9txXY1Bk5xMuj/o8H3b1IR2tRlLHogc7PrITwChSpfwX4sFHJWKGkNWsrNCNo8WTb/Ghz9znaTA1GM+FqKgCVC0y8iErO78idt91QNunFooN3ppLWhVHgbnGUQeqEWgU+QA7oEOCusj4bUx/4mqiM8hlgaHMoyTKza9AcrfGoomQ06l36BL0/s7S2mdlTwMXufmfKZt0P/N7db0vP3wP8292vnpXjzIQds6F5h+NQZcip6BwYhfZcY0yKx9uVca9PGd8X0Hn5eXYvLbmKZ120VqyMkg7dkCLkW0jtubD7e1WEo1VjctG1d9CGbV/Uf7Qk2qSORHX8LyM5zzIUzBrbuCVK1W6MshLdUcSvlRcs7Z67AV6A+l+Go0X2XTTMbwukQHNRgcfeENjP3fdt9PzPgUvcfUkrWLY8Z8sCaJO2HdqkPQFc6+4vF3XsmSXZtjdycuZF2dib3H1sCceeDZ0LvdGmpS9qKi581lvOho6oB2cb5GSe7+4Pz/inanbsDuja6NYoGDAXigKu7jnZ5oJtMRStPwh4HTjH3fuVcewmbNkFWNDdLzKzo9Em+lhUSvigu18ww19Qe3t6IPn9ynorU9BqfWBblGmcCzlfZ7n7GSXbMhsSu+iIAnhZudrSKLDWxt03KejYnwKLufuX1jCYdqpJIXO3sjZwppLSeZCYT1dUorUUcsDmR2WeNd945e4p7ZCq3rLAWOTgfeLuE/Ovq/Xxfwymfrr50dq+ItofzYsUmbeb1U2/aejx3kj04xfoc9jD3T9Pzw8HfunuL87KcWbCjtlRoHINJNhyP7o2JiEncy7Ug7xYQcc/HlVOPYiynC+51J6bDaaRAzegz36bqpMRRRCOVgGkReRjd++Qe+x2pKSzJlJW6QOs6CUPojUNBXwcLUAPo16UOVLZxV7Ar8uIbJiamHuhbEEvdEP+Gi0ID3oBzcK5CPReqLfjGdTvkTXyHwp85WmAYhmY2X1ogbkJLcDro/r1g73kgZK592cpVNo6qKlAQK2d0FQC1s7TsMZ0/WyI3o9X0GDvUhYqM+sCfJ1tSnKPXwf0zSKiJdjREWUoJqESoA/TJmo54AkvcchmzqYFUOnN0ug6/WsZWbUm7OjoUh3sgZz/FVHFwEHuPqokG2ZD0tA7ok30OBQpfgro5wWKg6Rjt06lNp2yzWPu+TlQudg4dy+01LaxXWn9mAdo743EjNK9Zz6X+mCthXQWQEpme3tOUj/Z8oG7F1462PhvSpnHKe7+Yfq+G9DZ3QtRLs29/zeh4NgglE1rhzb1jioChhZx/B+LqUx7YeDNZHcXYAGv0Rw6UyvAKiiAu7e7DzBJqa8B3O7uC9biODNpSzcUBOmHeseyjOeXqFKgkH5O0+iDLdEa1RNlssYj5/tZtF695iqDrswBN7UJ7OjuJ1Zx/KIJR6uG5CJKfdDg3xXT4ysD97r7IhXalncyfuVSk9sGRT1XNLPewJ/T15VccGbWzt0LEzvIvQcHo0VvbnTz6YoW31eBO4FHgLFFZQxy50lP4OH8eZHKkM4HcPf9izj+DOzK3p8/Ab9G5Q1vIDGKl5Ak7jCv8XweMzscbYbuNikcnog2B1kD90DgVC+hR8rM/ozmQWXy0Fl07UHgF0VHQBvZsgGS2B+K6ulXRJHyO939vKKzrtOxqS3KnJyKVDpP8qTqVdKx3XNlVyl63wP1eBQeCc1du+sjIZ89kGpo1k/YG5inrE2caRDwH9CGyVM1RaHr6AxsyUr4zkWy2temp/ZFwbSLi7yGzexs9Hn8FpUpGnKE13P3zYo6bu742fq5DPAbVEraHVWy3OBJBKRgGzogsYclkMhBd5RJXAhdJyd5CS0C07Ete38WRzP5uqCs1qXufqOZLeKSZJ/V42yN+qFeRhm9h33aoc3HoEqB42f1WDNhS3ZN9ELDmd9p/FwZNiAxtk5or9ML7X9WQFnnHsDa7v5qkTak92Ff4JdoNEl/dx+Qnj8KVRmtVMV9rWhCDKO2GNq4b8C06i0boMZgUkQlU2Uq05nJjjWVhsF4G9Igh9wbbehADcXfUhBpw7QValAdiTJLryKFrMI2CGmRXxZlCaagjfxoFNnpjxaitdD7MoeZ7ZNFIwtiUTRPIys3NZci0NVojlSp5DKZb6EG5efQDXp7pND0JvCZmd2CBtfWqnH5ORrOvbOQuMBDyMlZADmep5nZUUVuElKE1VGWdTOkjDQG9Vg+WoaTldvId3b3J81se1Ry0hVlogeSxEGKvhnlbFkIZZu7IDGUNsjJOA2VHxfqaOVuvLsD25rZr1HPycZo0/DvdN2UGSBaBvWSPJTsG4KkvLOMUuGY2SKoKuKxRn/7smZ2KHBIGdUJObLj74lK9aaY2ZXo3J0bOMjMziwwC3omWtt3R/e5NdD97ZCCjjc9LkC9Rlehda0ncLSZfYuk6Is8R+dH10PmWAwnXZ9m1sElN14116LP5UK0jmT7kZPM7PoarLPfovVqNeRoHmxm2Wy1N9L/t8ziMWaW7LO+GQVE3jEpce6FxI1O8TSmozADtHZOBCaa2ShXW8JN8H2WeSl0XynaBlAQ8zN0jZ5gDUO0h6GgYoskMloFkG4ue6MN/OvApunr41FkYXwVEcdk27xoE/80qt29BEXLj0fqSLcVFVHIRTV+i6Ia/0Y35YWQk9oGNayeUcCxO6LF7Sy0sL+MSvZaoVLFK9LGpSspAujul9TYhmzjOodL+KM7mh8xEpVyjkFRpsNR9OvgGfy6QjApmg1Bf/+k3ONnoZ6DsSjbdaS731eD47UH7nH3Pun7j4AejY7dDmXUtikqIt5E2U9rdB5kil03eon9lGb2CjpHz3T3903lYl5Rpvlm5Gy/h27IXdA19CyaU1NkMCLf93oX6jE4y9SDsQuK3A8CDvUSS6JS5vlE5GyVktHLHTtbR36ORFE2avT4OsDf3H3xMu1KNsyBstOds69R8OobVDa1uhfcZ5mCaYuS5leW6VyYmSGRgXlyj7VC5VvHA9uX8Pcfi7Jpf6FhY/tlc8kSmJSFF3CVvn4ErOHuI019U318FlV/01qZDSeeC5UnLpwe2wKJMGzm7o/PynF+hD0d0B6rU7o+X6UhsDsZlTzXtEokd+xsTWiPxEcOQIHEIWjcwQMVZb9bo33fYuhzGgG84iUK+JRJZLQKwN0PMTVqL4ZqpTuhC3wDtFn50MxO84IH8k7Htk/N7EwUTVoZlQANBW5FDeWFR8rR3Kiz3P3vJgWag9CCuD0wy5v3PNagprMfsBPqQbsrOVULohvg2Wa2gLufgkpeispcZBnPl8xsa3cfZmbnAH9CDvlwlGkbiIb4lUbO0VgaGNnEwv9PVOKxkZlNQQIEtfispgIXJRs6oRvQKUw742QeJIAwvAbHmx4dTbK3HZEDvg66AXwJ/IwGaeCyOArNHzrTzK7zhv61VsDUshwuUy/lXSj73AH1nJQmSJLI1qPlaBicfTBwirvfa1IYW5KGrGgZbIAEbPY0s9eRnPcAVLLWv8hMUu6zfx9obWYHu/tVucc3Rb2NVTAH8ISZnYeCWH3d/R1Tj8qcRZ07ybnaBV2/mbT8VxVkcBYC3jOzzdy9L+h+amYPo0HNRf39WRDzOJTB64T2H6PRnmOsmd1TdPbkhzD10g0G5jOzcWgtG5kCFx1n1cmC7yszPgE+MfXojUAB3W1QoPtDdL0WSu6e2gsYkRyezYDZ0x5xEeDJopysRDbrch9UwtsfBXXXQYGiLsA1ZVQDpGD3aSjI/z6aC9mvyGM2FyKjVSKmJv9l0cbtMm/UcF/C8dug/oGx6fsOKIPySZkLsJmNBHq61KFGA2u6+wgz6wvsU8sIuTXUhb+AHIX/Gq5qkpQ/FDjQ3d+0AqVOTeVpo9199pxtdyLHoidJEKTkkp+8ffOgSNc8aEEeiqLRB6Bo9M/MbCfgBHdfo4Dj9wauQ5HwR5AjtjUSxKhphi/3/vdDTsRwFHzoiEpaDkEqUdejG2KpakimoZJZ5uZh4OxabER+gh2GbsjzogjsiLLPzxSlvg41coP61bZ2969SWdBKXpKwUKoKGAmcjUpeuqNN7YLp642L3uDnItUHoiDSYORcbYkysGdmznnZpGv4UtTbeQra7J8DrOLufWpVMZG7flcDbkPKtYNRlnNedE2/6yWMZGhk1/5oPuVFKIu3OLqOZ3f37Qs6ZnY+TEAOxWB0jayG7iurAnt5wUO0Z9LGk5CK68BkY2/gBGA5d9+xBseZHfXqLYcCMOujIPJAJPBU6lBck2jPeWjvNxqp515hZgegwO/aBR67bcocDgBO9NzcMFO/1AGoGmBAgTZkn/sSKKDfAwVCvkTvx1vo3tu/iuRDGYSjVQfkol3bAMegMqyB6GQfimqap6TXFBrZMJWmXYVK5p5HE9KPQBGO99y9fUHHHYU2QG/nLnxDM3kmp4XocFdfTM3fg9wxGwulrAjc79MKYlQqv5uijseiDcK3qMn/BdRIPcQ0pPV9r5FCkDWUhp2cjvMByuasjxytK5EARM0DE6Ya8UHohvw3JLoxIpU2DENNwoWWxs2EjUuhctLlULntbUXblNvEZvLpu9AwiuEZNAbh8xn8iiJsWhApMI4HbnH3l03iKdd6CWVyuWv4Z8Dx7r5FerwdCkzMj7I2zxZtS86mNsi5+iVy8p5DZa6lKsvlzpdfooHBn+ae64IEVEa6+yM1dLSy+9qZwMLuvm+6v8yD5v/1QCXYt8/qsWbCluzv3x6V6m2KMggLonvbrehzKUxJ1lSqeRuwk1fUmjA98ve0tOYeiM6JTiiw9QRqG5ildc0kqnA62tt8AtyBgmXfVpDdzJ8Xi6HrdBj6W9sjVdk3vASV4xRoPsEblUua2dvAzkU64Lnr9DeofPE1VNK6CGqxaYUybROBP3pONbSlEI5WHZDbIOyEStKmoLLROVGvxROoH+ROL08eeU7UuHw8WnQ/Q9GmvQo4VgfU/PmCu1+YouMGDWWSKRK4SFFZi9yCexawgrtvmx4/AtWLb1OrDUgtSDfDTJVoEFJ1m5jKHbYHHqpVdiV3fr4O7OvupZY9mVlX1L+3GboJnI6yAgNR2ceEMjI4ufehJyo5XhrdfJZEs2BaoQ3E88hZ/6gopzx3c3wEff6Xos3B2ij6fIe7/9+MfkeN7ZkT+Ar1cXZw98/Tdbwnkjq/vgQbsmt4c5TtvAh4uoqgiKnMdi00iPfT9Fhbr51AzU+160qUUboKrRFfZYGUAo6VXS8nA5O8idmLZa2pOVuGA73dfWR2fOQAjynqs8mdlyug0tpPgUKFg34KKSjQyiUlPjvqh54LlTZOqsX7k86/g1AP0t0kpVwUJJoATCzb4TKpTg/JO7/pnrMCMNDdRxd03OWBG1Eguxe6xx2L7iGdUAD1Ii9ohlfOjuxe8hrqKX0091xPFDx7HNgNVfTs5uWXpxdKOFp1QG4hvh/Vif8jPT4/UgBaBPWlLIRO8n+XbN9OpDk0XsD8rHSMXVH5yr6emy2Toq07o4bUlUrI6DVboZRk37xokz8/SumPRDPhiqwjzzYkFwEDGm+ay8jwJWd8F1Tq5Kiu/+vMIS4TU7P0G8jZmwg8hgIhrVE51AlIxW0XL3h4tKksb3HPDbk0syVRpHg7L3gIbO4mfTzqrfiHS81uSzQn6tmiNvJN2JJtpk9BPWuj0CDtkeh8GY02ToVdK7n34xBgS3ff1qQKuQfqQb3T3c8p6vgzYd+SSCznZ0g59PwiMtGNjvk7VD75J7RhG4NEMEoTr0l2tE02XNU4WFSkw5c7L/cE/kzDuvEGkv1/Cc12q2QQbAqIbIh6GicgAZ0BpvEV35DmONXweO1QKW9vNK90DRTUHYrWkNL641OA6AkUJBqD7qkvojK5oqsSFgLORc7sE2im2GboMxiOzpMb3P26Iu3I2dMfuMndr2z0+CDg5+4+PH29r7u/VIZNZRGOVp2QNpKfe6PSPJPy3dnuvp+ZnYoi1nsU6PB0B3ZAUfqPkZMxIIu+FRih74AWncNRI+zLaNFdGUV3TnT3vlZgf1bOlvY0CKX0RjLVX5GEUijxRpDsyRzxNZBISqdkx6JoM/kt6lE62wpSvzPVbz+CMmj3ohvDK6i0oky1P0OiFyehzcrewHNeohpSinZ+MSOH28y+BLq7+4QC7eiM+vWucfc7co+3RXPm5i7q2LljZZvIj4EtXMNuT0RlR71QhPSaou1oZNMaKDi1VPrXGTnnHYADsmxGQcfOymzvA55193PM7ELUh/MsilJf7rlejCows9WBM9A4gD+g4dY1z7CktfRa1JPVGZWVjkaO7/vAX0pYz7NzdHkkEDQeRelfLToQkbPh+2BDClqtB2ye/t8QOLiC6yR7XzZEIzpGomqaFdEohF3RPeYFpMZY2PBzq6g/3lTO2Rudn0ugctaVUWnrM15w/2Dabx2AgjAvo/f9G6TC+IoXWMrahC2boUDEv4AHUKZxH+BIVPo71VRZ1L3sIEnRhKNVJ5hEDq5Di935wIdpEVwKbWbbpovyNXfvWpANbVHZ0wR00XdP/9qgzfzWRZc7mHqitkebtAVQdOkKzw0SrIKqbgTp2Nnm7WaUJTjMzG5EpaVDUP/Hb10Kb4U4oqb+m/WBbmhGUVd0c5oXlamdXutjNmFD5nAaKus4DkUBt/cS68ZTVnFnFIl8Gjl6U3Of01zAju5+Qwm27Ix6Ca5D0djOSDp6bq9B4/pM2tAVGOzu86Z17B3U7zA7yoKuV0UWOPd5dEaSycs2jtYWcMxs8/oMcLK7P2HqLz3W3R81s+dQn0PhfUkzsLEVCtaMR8ODj0KZvwsbZ3pqfNzF0fW6Yvo3yd13K+p4TRx/BbSpzcQ4vkOlUF+gSpJ7any8VmjDulVaH36OMqojmnht4QHE6R3TNAT+O3c/PD3+d1QxcTwq4b8AZaqvKtO+sjGp7s2FxEp2Rtneh0s69vKoWmMT4AYkDPZRGcfO2dAalXrvh/q/50frwvmu3vjtgD+4e68y7SqDkHevE9z9C9Mg3DNQZuejVB/bnYZBcWsBNW9wz2Wp1gXaufsqqWRvbhTZWQiYr2gnC8DdXzezgahWvPByo5klZRCfp2GAdJlkN+DVUUkUSHjhlJTlWwyVdkLDAMaaYA19JWuj8paP08Z1XrQQL42cvcLJNiLpXH3dpOi2A8ruFUpu0749qqmfjEo7jgIGmdmR7j44XUvj0c2ySHtWRO/9K6i2fxcUmJiMAiNHFHn8RswHvGDqdeiDgkEvpfWrW5lOVtos7Ig2LO3NbDxwu6vJvPC5PLlM8pXATWY2GSlSPp0eX5qS15Cc83ccyqKMRCqV6yKn+BF0Lf/FzH5XgMMxl7uPdynnDkNlrZkjUiaD3P2IFDRbHF0vCyLlvyLKBjuiwfFT0/30dOAbM5uEPoNBKKD5qpcsXNOItVDWIqMLmj/3MoCZfYCu8RZH+ly+dveJqfpgAnC1ma2JghFFH7+Nu09x9zeA3VO55m7A6WZ2s7s/U7QNGWm/dSNwYwq6t0X7wU9T8HAs8Kuy7CmTcLTqCJfi02CUsl8EpezfBO4y9WttABRZXjAP8GSy5ROkCjQUvt/AlELarDQbJ6tqcpHOt2lwqGZHde2guu4z0mtr6mh5QwP0P1A5Ka5egs+Ad8zsa5RJKR1X38CtJR0rOx/PQMITD7j7aJOK2mXAMWZ2rBdU0pvHGuSXv0TO3oFo/MGx6ftlUalaKcI5SKr6BeT0/Z2GeWZ7UtK8KGvosTkCzUQci4RTFgCuMLO/uHuhs+9yDs28KBL8HgqUPQZMNvWhvuclydxn5NYERyW/36HrZjcUwR/nEsXYAfijmQ2e1QqC3HuxCnBYKkv6HAnY9EX9vkNyQb4yeCtlay5w91eBV5Oz9y9UhlxT3H2cmf3HzBZFAZDDUYBqMXSv7YGqN95BJVqlkruvrAJsYGZfuPugZFd+XV0DuLls+0ri98DHZjYMrZdZn9yWSDCmUFz9rJ2QczselTd3Rf1yu6Prs3BSNu8gVCnSD5Utvo4cT1LwsDSnr2yidLBOMPVfjUHRzneaqodOUYZWXmNVnlwJwT7AyahJ+la0WfkUCUDEiVgxZrYS+vxfSefLeiibtI27L1XA8RYCHkQbxb2AeRufByYxhoXLLKUsG1PfWydUYvS+uy/Y6PnZgVeBDb3g3r10QxyCHIpxaP5Ppg42GJWTDkQDxwurozezHt6ovyVtWud2989MM8aOR8p2Zcp3v43m7fXL2bR7+ndoY5trbEMmhHElsJC7b5N7rgPaYLdJG5hSaOTw/M3dl/uB108GOtfqejYpmb2Gej+eRfeWn6enV0iR/FIwqVH+GkXqr0EZ+kIU7nLn4x9Qz81lngRrzGxHlIkfRhqX4RXNzzL1KF2AgjOLokDNAki04xlSjzawQFN7kv9lTEIY56Jy+PnR8OAxqPx6hLvvXcAxs+txLVTGuigKmC2MqlReR/eS2YGX3f3yWtvQhE2zoTlmcyGBloPROfsdCo6sUHHGtXAio1UHpI3akiiasC3wrZmNQdmsMegG6V6Q/GwusrUCalJeB9XQf0TD1PqbWvrF1hzJLczd0KT2LGNyOxpyuTAqGytCqGQqKvPZCUVgvzOzsahvrh9aiD9ryU5WYm1gK5TNesHMLkMzyyaamSFHp3PRTlaiNxLiuAvAzD5Hm6GdUWlU4c39Kbv9upl1ThHZs9GG8fuBlq4m7v3T+1M4uTXsO5Q9yB7/DrjZzM6l+PtpZsMo5PTm7fuakkpsp0NPGqoT8jOTGq8ZC87q9Zxbs3oC87vmZ3VFYk/bmlQhPyzTyUr0RQJPBwK/Q5UiV3gxJfHZe7ob2riOAzCzS1F57SCUeX2pKicLIK1hx6BMShe08V8GlVMejRzk8S3QybIUiPpN+r41+ts3Qc7mjUUcN3etbYucqadR9c7lyMnqgDLMhYtN5K79dZGTtyyqpNoClZP+E3iqHvZ94WjVAals42QUWVkU9URtjkoIr3b3W8oosXD34+D7Zv/lUcakJypZbNGNsM0YQzftnYGlzOxidx/m7m+iqOj31PL8SOfbh8AZZvYsOi9vRqUuvVGGaxzl9gJVxe7IkfrWzP6IeiZvM7PnUQZpY1JJrxWvaon3AAAgAElEQVQ/F2hDFPzI2AANoL2vwGNOQ3of5sn9neuiBuquKUD0MtpAPOkl9hgkrgQuNrMTUER4gmlI79RZLYf7IXLXXyvgN8kJfhRdJ98UfF5Mj2z9eB/4yiTI0NfMvknBu2nWDFfJeK2OuTKQidSsR8N52w/NiyxcLCZP+ltfR6WMP0OBkwNM/ZU1vX6SozknWjf6mlkrUz/QIWgNzXorjzazfl5CyfEMbJ2EytA/R+XgQ5E640S08W6JdDSztVEfXVsUXJ4fZZd+hnr4jp7+j88a7n6KzUAApYT7CGid+hZdmy+noNlWwFB3H2sS31o62VNmiW/phKNVJ6RN7YekngYz+weKumVlJtnNqzBS1LEzyq4NcPcn0+Mt+iJrzuQW4sFIDONVk1jIjagsqyip6ovM7HJXA/sbqGZ7EurB+XtBx2yurII28ADPoQj1LsjBGo2u0/+k54tWDusEbGJmfVGJ4KbAM6Zm5Q78gOx8DdnczA5AG7I93H1UKo/LZsHsiqK265RgS547kg2Xwffyye+iMsbCSdUJm6Dz4GwUMR8MDDCzIe7etww7cmTr9hloA7k8ctZfN7O3UMXEB7Xc1OXWrPeAB1K567fI0dscqaSWIludy65l8t0bIJGnT1HFRm9UKlcES5CyiKmk9ECkOvhAsu164Ogqnaw81iBBfxZwrUtApsUMps2Vc/ZDa+VwFAzoiIYn7wrcj5Q4nyzanuk5Wem5woMy3tB3PAldC6AewmxPsSYN97PZKEYwplkQPVotmEYlFl+jiNIkFH2dYmY3Ienoq2YU/ZhFG7LFZy0kL7oMSp3/2d3PT48PKai8IviRmBSztkGbSYBbXI3dtTyGobll56Tv70LRr7HAB2iT9C7wrlc0ZLNMzOwT1DD/KCqtfauM0o4Z2JOf87Y+cvgmUuKcNzPrgzKq86KNqqVjD0BO56tllhtZgzpm9v1KqKRzMiqp/LTsgJFJznxN5Nisi0qw1i/r+I1s6YBGZmycbFkKbTa/A9YsqjzI1COXBQnPQ9Hzqaj0tvDNbM6OL5BozxCkoPcpUqEcjEYT1Px6Ng3mvRa912+g0qzrPQ18N7Od0PuwWq2P/VPI7Ue+BpZ392EtLchq6nMfhILJfwNOdfcRqXRwGLC2FzyouLlgGl7+BZoROpdLUXg51LPXFlWxHOTujxe1/2wuhKNVB5jZENR8+BaKUg9CkcejgU3d/dWiFjxraOB+DrjN3S81s2x21Y1mdgeaFn5vrY8dzJicE7w0aiD/Ct20V0CyxD2B0e7evYBjt0WzhxZGG6MFUUlrJrzwHYC771LrYzcnTIIgw4G70DU5OwqIDEVOxWuocbo0gYOmsJLnvJkaqDujvo65UYnRIun7XyRbNnX3x4q0I9nSGzgVXQ/9gCNcim+GsgpHABd7ecNp5wPao0j5+9lnUVI50ExjZgsAq2QZlgJ+/zT3LNMYiiWR+t5+ZQZpTMpuVnZgKP3NR6K142YUGPP0+AUoiHlamTbNiFTe+KS7L9dSN9epcmcvlHl/Dcnut0N7r17AhJb4d+cxjWi5Fe05R6B73ChUYrwVWjdvq/q+VhbhaNUB6Ya3OhI3WAv1an0A/N3dSynTMrOPkbrMWDMbBWzi7m+meu1feoGDLIOmyUUYD0YqUA+gErZvUA35t8Db7v50rW6KuWNug0Qw/u7uD6Xn2iEnay3ULP2eu/91Vo/ZnDGzPYG93L1P+n4BlKXojbKKy6D3oZJMRXPANKS4Pdq87Ik2LR3QoOKiSluzY3dB/WAPoYj0/ihSPRsq8cwyfbsXWaKVC4r0RqWkqyFnfBzpui0zw5dsyq7leVC53nbJpseBJzKnI1cyVoYtXYAx7j5bkcdr4vid0fXaC6moDqoyU2NmG6I+7FvcvUqRlOz6bYPGubRBKrJDq7SpaFKGdxdUxePI2fja3bet1LCSSIGHX6PKiCVRUOgbJBYzGJXED0eBgELX8OZAOFp1hJnNkYt+zl1W7XaKhl+FZiU9jkqjuqWL8R1371KGHUHTmNkiaJP0axoUim71AlQocxvGfwHPepo9lI9Om4blboeEWkbX2obmhJndgxTSDrE0XLKJ1yyYepRaZAS4KVIv0u4oUr8kKmG8h5SRz5zzAo+fbdx3AQ7LHF2TgtqFSDHrAjQX55OySj1N8vIXoz7GRdH7cixwcllBs2SHAW3dfbKZ3ZhsGYg2VqujbGRbYN9aBEtyn8cSSCBmFJrBMzl/TaTAxYnu3mtWjzkTNmVr2dZoQz0SzYQ6D4nXbIp6T2shAPJjbWuNNDMqy3DmqllORNUS17r71yb5+SWAvxZdglw16To5GjgJBWX2Ru0a/7XOt2RMvawroGD/Cmj+XxtUzXIzcF1LKiFtTDhaLZTcjWk+1DS9GIoKn+fu95tUvb4o0Z7NgStQ2eKqwHHoRoS7H1SWHcGMMbPVgY1QSd+Dtd7Q5s7LUcAW7j6wkZM1G+q5uAe4xN0freXxmxupzMTdfUxu45a9B55tIltaL0NT5P7+I5G4wgAUBb8TiWJ86wXNJZqBLdcAuPuB6fHjgNXcfbcy7Ghk03JIAbJbo8e3Ak5397XKtikdfxSwtScZ8bS57I56tV5x9eLUKiN+NbAjcureRufIYOAjd3/LzG5BpVkHz+qxZsKW7BwZDJzh7v80s3eBg939UTO7Gzjf3Z8t2pbmSO79GY5KOR83jWpYBanN3YbetxbpdOT+fkPOxXHob9/e3d+d8U//75PuY02KcqTnlkRl4LsCv3H3/uVaWB6hOthyyRqE/4YaZS9EDfdfm2RhzzCzK939rUKNUNP4MmgOzv7Ar9DQ5LVR9qQUta6gaZIjfh6KEHdF8y6WRFK0h5tZu1reCJOT1QE1yTaZMUtR0JVJilotmXzGLrshNXVjaulOFkzzdy+L+rLmQ0NN26NSueFmNgGYWJbDhfoG25rk3N9F5YuFD0jOk3OyxwP9zWx1d38p95IJaA5dWfZ0Bg5CMvujkDjJhOz5ZOuH5N6nWmVi3f2g5IgvhhQn+yAVt0nJ4dkeZcMLJ22i2wHzuPs/08PzoPeFZN+IMmxpjqT3pw16T/qlrw9CvUtjkfjP5aicrMWRW88dqXAeiAR+6kIMo/E1nxxOyz33NnCBmW2B1G5bLJHRasGkhW0M0CVtXkcjtZ9PzGwEsL67v1/AcbOsxYmoTnk86qk4AA1JPhb14iwD/Mnd/zPdXxYUipn1AM5HfSYj0fkyN+pB+cjd7651NsWkancR0M3dd2ji+RWAfu4+b62OGfxvkTawWWnc5qhvbRJyvktRPkx27IYy8F1Rn8GyNKhijk3//unuE6b7S2pjR9avt2/6/ybUM9Yj2TfQ3U8t0oacLasCf0CBkm9QUGYRdE2/jvo6S908W4NYy5pIea+UIecpUHU16m19BZWFLW1mywMPu/tCZdjRXEkZ+z8jefOFgQ3dvU9qGxjq7p0rNTCoHDNbB2W+yxgbUgnhaLVAco7OokjZZR0zWxh4xt0XMTXcD3D3+Qq0oSOSuj0CNWwfijYrc6NSj46o/OPssvobgv/GSlYqy52b66E+hn6oF+v19PxOqI59mLsfVZZdQfPHSlY+bHTsTI54EaSWuRhyMGYHdvACxB5y18oJwB5IMnwymrW2AIoCdwbuBf7iJYlhpEDJ4ihY1hO9J0uhzGNrVKngyAH9Vxk2VUHu89kdOBcFFNsi1cO90fywE6u0sTmQ3p9LUebzFHcfamanAn28jkV+gvohHK0WRm7xnx3d+E5Fm5P3UWP5Bqgxc21337bWG+3c8fsAF7r7CunxVYBngZ1RM3spUshB0+Tqx/+IBEoeds1W2x1t4G71gmbfZMdH9dmnIWn3VumpMWjjeG6Rxw+CmWFGvUXJ8VvAC1R1SwGrN1FD/efAYUiA4wRUkvVuVWWlZra0u7+dvu6MMhaLoYDaysC/vIXPyLFp1SB3RWXX8wA3IOe32cjtNxdSlms/pKb6j6rtCYKiCUerBZKcmv1Jc5BQP8wySOWlA8oo/S5Flmp6E8zdeM5Ccu7bpsePBDZ3961rdaxg1jGzccBK7j7czP6EmpQ7oIHShauYpeh4L1QCBSpf7F8PPUnB/xZN9BgUeqzpBKxWRmptK+ZfV6Qt07HvTFSVcJK7T2r0XGuU0bIiMn3NDTNr3/g9CEQqrfwlcr47o8DvVy1VACMImiLEMFomV6DegceQQlN/1IczPyo7GZk1k9d6w5D7fZ2BTcysLyoR3BR4xszmQhv5L1pyTW5zJreJWxl9DsPNbBl0Q1wHyTOfgCSkCyVtUF5K/4Kg2ZIcmrKcmkzMaAPUP5mxAUlgoUInawU04HyLJpystkhc51p3H1y2bWWS+gj3BI5MGb1BqBT6adSrVdfZrJSNvRRl+Z4G9nD3w81sNTNbEmU8W2SmMwjyhKPVwjDNRFrS3ddN3z+KZLIPKdMO11ygo1EpybqonGJLGjYOH5pZKQ3twbTkNmftgbdNs2dWRnLuw1JvXzsov4crCJojZTs1MxGwmhNob2bjywpY5d6DzYHh7j7aGg0jdvdvzOwtNJPv2DLsKhtrmHe3DRoefSrqn9sY2Bb4PfABmhVVd+SqZDYFerr7Kma2JnpvQAHfI6JsMKgXwtFqefRm2ghoG9S0PMN+gyJI0c4307/rkw35hvYQwagQd+9vZvejzcIjwOnpqV8jWW1IpVJBUM+kDHA7pMY5qSynazoBqy2oJmCVZdl6oZEhAN8HYXJOVxcketTiAjXJ2czK3pYGbnL3G9P396XXtEMOcr3TCwUHALYGXk1fL0rc+4M6IhytlsfawGJmdgha5HZHkrsgp6vScj13H4fmaD1fpR0BmNlS7n6pmV0BfJc2k0sjtci+6WVR2hHUHbny2vmA36Ce17fRmjrYzN4G3nH3kUXb0lwCVrkg3TPAzma2kLuPNLNWwGw5B2RzNL+xJXKOaQ7gAKQ42aZxj1bKMH5UlYFVkztPHgA2SKWma5HOXTT7rEUPog+CPCGG0cJIteIboBvwpkB31K/1APAOmkPTPzk8QZ2SRCj6o7km49Jj2eZyTeDllhSJDoIfQ5adMbM/oxKw89K/TmiD3Q04yt0vq9DMSkjO57+Bp4Az3H18erwNUpM7ENjR3VvcsF4zOwMN0m4NzIGGIz+P3ou3gbfQfKgvqrKxOZBUZQEuQH2/K6E9yPyol+08d/+gIvOCoFTC0WrhpDKGHmix2ww1Ma9VpCRx0PxJUejLgAnufkLu8X2AnUMdMqhncuqpI4Dd3f0ZM3sJiR+0R8PXL83kzeuNpIZ4LXI63kRjGaaiLNvR7n53heYVRhL72AI5Dq+g0RSLIwdiTlIFgLvvUpWNVWFm86CZam/kg3RmtjawIXJOJwLXeczODOqIcLSCoE5IEeep2U3QzJYFLgd+C3wNnIVkeG9w9+tbWn9FEMwMucxuO9SLtLK7TzCz0ai5/zMzGwJs4O5jq7W2OtJ6sg2wAhqg/CWSnn99hj/4P0junNgGBStvc/fH03PtUB/0WsBqaD7UX6uzthrMbGvgEjSiYywqr3wOzc0cU6VtQVAl0aMVBPXDicB3ZvYyuhm+i26Ef0dDUB8DDnb3T1JEP5ysoK5oFFxoj3qNVjWz14DXgK3M7EOge507WVlP1p1mNhQNTp5YtV0FkgmB7I1K7zMny1JP1lgzex9YFXi4OjMrZQBwJDAvyvLtBxyKBFvGof7GkcB99ZoJDuqTcLSCoH6YD1gTNfZ/B7wPDENZrCuBu4FJkckK6phLzexdd78E6ODup2dy3mZ2G3AhitafV62Z1ZLKKrN14hLgaOSItlSy0p91kXz7NJL/qSfpDeBs4FlgdBVGVkkShhkJYGZXIYfzDeBjoCdwFDAOzUwMRyuoG6J0MAjqjLQpWAWNAlgNRR8XBL5Cztc2+dk4QVAvpGzv5e5+o5ndhwbv3mtmhqTdewLjopG/ATP7Dpi9pQ+gT2qDLwE7uPtbjR2t5HyOBNZ39/dm+MtaII3ej8/dvVPuuTZIOGRrNENrfEVmBkHpREYrCOqA1JC8KtDX3d8BXk7/sufnRoIpyyS1tVIHtAZBM+Em4EQzWx4FIv4Pvh/y/R1STKt7cj1LywMvuvvkxsOLWyAOPAGcg5yt79fH5GStgLKgdedkwffXCGbWA/jEzHq7+9PpuSkpcHFJOFlBvREZrSCoA8xsP+BkFJWfDQ07fQnNxOnv7qNzr43SwaAuMbM5gF8C+yClNIDP0bDVfqiP8fm4PqbJ4szX0vvVco7lesA16Fy4OhP+MLOdUP/WMHc/qjpLmwdmdhy6ji5F18xCqHSwu7tvUqVtQVA24WgFQR2QZInnQX1aS6Ds1irAUsDcSAzjC+Bwd2/JvRZB8IOY2VLA74A9gB2A9VDGd3XgfXdfokLzKiVlv/sAXVCW54P0b4y7t+hBvans+hfAaajculV6agxwL3Cuu39ekXnNBjPrDhwM7I7uNyOB24EbW6IqZRDMiHC0gqCOSX0HywK90GbyHHcfEaWDQb1hZtsDSwNDgBHAJ+4+qtFrDOjW0h2KGWFmVwNbAi8CG6Byyo5IWOeYxu9ZSyQNfO+FZlSCHIn+sWY2kO4tHZAARjdgdAsvLQ2CJglHKwjqjDT3ZUekNvgiKoWaYmbtWnpDexBMDzP7PRKHmQx8gzK8H6NN9Ij07+N67jExs0VRb2c31OM9Gs2VOhMYBezl7lOrszCokhSI6INGiXyMqiW2BjoDU9x9XIXmBUElhBhGENQBuX6KlVGv1oLAROAENOfkBHfvW6mRQVAh7n6amS2IymmXRWqcSwAroTlKE4ApZvZbd/+kOkvLJ1s/kLz520kwpw/qSXrKzM4CfpnWmMiG1xm582N9JCBzK9AJ2CedE+sDywDnVmhmEFRCOFpBUB+0RlH6o4EPgRPc/T0z64gcr2PS/KC6VMwKAoBU9jYKiR1k2d8lgMXSv8XrzckCqeplXyIBHYBFaZiHtC7QPX09G1JoDOoHS/9vDbzp7leY2ZGoDBd0rqxTiWVBUDHhaAVBHeDu36QvVwAOSk6WufsE4GQzexpF8d+LiHRQr+Qi8wCkUtrBwOCU7ap3oYOHgKEpQPNvYD8zew2VW15eqWVBlWTXTDsahjX/DHgkfb0qECIYQV0SjlYQtHBS4/avgH8CTwKnmtlh7v5BbmPZA3gLGuahBEEdMoeZrYma+DsAG6FrYxKwJvAvlBWuV1oBryZRgwlmdgxSZewHPAgQ0vf1R+6ecTHwsJl9gubQnZUUPJcB/lyVfUFQJSGGEQQtHDNbGkWib0USu0ejJuWBKEK/I5Ks3q0yI4OgInL9i/2QczUcWBkp6d0FHATch4YZP+Xun1VkaiXkZkgtCZwE/M7d388/DxGgCYSZbQ3sCawBvA8siWZo3RXnSFCPhKMVBC2cNPtlfeAsVDr4COrTWghoi+a//Mvdv6jMyCCokDRnbhDaFP4NODWNOWiNZMvXdvcPq7SxKrIB5mZ2LLCZu2+RLy82sx2AOd39pmotDarEzOYCWrv7ZymLtSQwHnjX3UfP+KeDoOUyW9UGBEFQLO4+1d2fcPfewF7p4TbAae6+DfCXcLKCeib1MK4PHA/MDxyaSm7nSC+ZkAIW9cxKwBPZN2bWJn25EbB2eqzVf/9Y0JJJwQhQtvP4NCbkHXd/EHgB+LI664Kgeur9xhEELR4zmy23KXoAuBCYHbjazH5Lg2JUENQtKep+BfB31Hf0Oiq1fc3dx9frfKhcz9XDwMZmthKqhpmSHl8D9X6CVAmD+iL7zH8BPOnuk82sVQpMtAIuMrN1qzMvCKolSgeDoA4xs7lRr9YBaJ7Wiu4+qVqrgqB5kPqOjkZR+onA3sBzOeei7jCzeVCf2iTgeRSg2Qn14RxSb71rwbSY2RBgc3f/oNHjo4At3H1gNZYFQbWEoxUELRgzmxdYC5UKdgY2QXOBxqKyqHWA591945B1D4JpxDEM9TQeB6wCbO/u71ZrXbWY2RzIAV0D+AIJh1xdr/1rgUgVE+ehvqx9U59WWzQy5GF37z7DXxAELZhwtIKgBZJTCjsS2A8pqH0G9EUNyl8D/ZEAQGt3Hx+OVhD8N6lXawfgbnf/qmp7qiK9D92B0fX8PgT/TSoT7AH8CWgPvJT+7w3c7O4XVWheEFRKOFpB0IIxs87A3O7+Xvq+bW54cRAEwXTJZfd2BbLxD5PRWIhhwKfAA+7+UVU2BtWRU6S8GHgaeBbYAzlYHwG3uPszVdoYBFUTjlYQ1Bkx9yYIgh+Dmb0PXItKBedCoyHmBRYFjnT3N6uzLqiKXOXE08BR7v5S1TYFQXOj9Q+/JAiClkQ4WEEQzCypz3OKu5+Ze6w10BU5Wm9XZVtQLcnJagX8B9gKlQx+T5SjB0FktIIgCIIgmAFmthcabv4A8Lm7T67YpKCZYGY9gReBdun/vsBTwEsxnzEIwtEKgiAIgqARuf6sVdDsvXWA64F3gBHAJ8Bb7j62QjODijGzjsAywGLoHFk6fb048Dd3P6gy44KgGRCOVhAEQRAE05ATOngOeA0YijbPSwIdgE6oP+s/FZoZVEhTpYG5stIewHh3f70S44KgmRCOVhAEQRAETWJmHwBLu/vXuce6AqujGXyfRC9O/WJmCwH7AH3QbLVdgW9D3TYIRDhaQRAEQRD8F2lA8WFIzv0v7j61YpOCZoSZdQLuAD4EHgZucvfZzGwTNOz7sjhngnpntqoNCIIgCIKgeWAiUyT+BXAOcCVwjZntaWbLmFmH6iwMqiYNKAbYFOjg7nsC7wOZzP8UYOdwsoIgHK0gCIIgCBIuvjWz1u5+K7AicDAwP3A+8Dow0cyOrNLOoFmwCA3y/lsAA9LXq6IsaBDUPeFoBUEQBEEAgJmdamZzJWfL3H2Qu1/r7tu6+wLAHGhT/Wh6fatKDQ5KJ5epehxY1MxWQA75rWZmwMbAg1XZFwTNiRhYHARBEAQBqSSwq7uPTxvmJ83sQ2AIyla86u7DgUeyn3H37yoxNqiMlO381t1fMbNbgSeAeYA2wP5IofKfVdoYBM2FEMMIgiAIggD4XlFwLNo47w50Q1LdHYG5AQMGuvthlRkZlE6mLGlmvYCH0GDiISir9TmwHLAy8Ia731GdpUHQvIiMVhAEQRDUOTmJ9l5oVtY97v4nM2uLNtDrAOOQA/Zt+pnZQvCgPsjJ9/cEFgB+CYwCTgXaoUHWDwFdzKynuw+pxNAgaGZERisIgiAI6pzMaTKzh4EngUvcfaKZbQocAiwFfAWcEkOK65NUTmrAJsjxfge4D2gPbAlsDmwN3OzuIZYSBISjFQRBEARBwsw+AZZz9zHp+3eA54G/AbuhPpxD3T1U5eoYM9sAOAHoDvzJ3a+v2KQgaJaEoxUEQRAEAWbWHXjB3RdO328B3AZ0TtmuuZAoxkruPr5CU4OKyJWYZt9vhMoIuwLHAyNCICUIGogerSAIgiAIQL1Xz5jZUUjs4BDgX7k+rAWA2TNVQo9IbV2RBhXPlcpJFwImAqsj0ZQJQOtwsoJgWmKOVhAEQRAEuPtY4E7gOOBV1JP1e/h+k/0L4IX08tg/1Anpswc4CXgPZbA2ADZCAhjrAj9DPVtBEOSIjFYQBEEQBAC4+z/N7H40mPhrd5+QnloPWBu4pTLjgkrIZTQXRBL/vYB7gNeBL4DPgE+BtsDkKmwMguZK9GgFQRAEQTBDzKwz0An40N2/rtqeoBrMrB2wKLA+0AdYA/gGeBfJvZ/m7h9XZ2EQNC/C0QqCIAiCIAh+EmY2N7AsKh+8zN0nVmxSEDQbwtEKgiAIgiAIgiCoMdHMGgRBEARBEARBUGPC0QqCIAiCIAiCIKgx4WgFQRAEM8TMzjAzN7Mm5ZvN7N30/Bklm5a3YT0ze8XMJplZzWrizWzNKv+uIAiC4H+XcLSCIAiCmWES0MPMVs8/aGZrIBWySZVY1cDVSGq6D7BODX/vmsDpNfx9QRAEQZ0QjlYQBEEwM0wEHgN2bfT4runxqpXGlgXudvcn3L1/xbZMFzPrUMXPBkEQBOUTjlYQBEEws9wG7GxmBpD+3zk9/j1mto6Z3WtmH5rZRDN7zcz2aPSafVO54Qpm1je97k0z26HR64ab2YXT+dmOZrZRKhVsBVyaHr8xvW5vM3vazD4zs8/N7PHGGbn0ug3ScxPMbJyZ9TOzVcxsX+Dy9BpP//ql7280s5ca/Z7F0mt+nnvMzewYM7vEzMYCA9Pj7c3sfDP7wMwmm9kAM9uqib/9j2b2f2Y2EhifHl/ezB5Kf9dEMxtiZr+ZwecWBEEQVEDrqg0IgiAI/me4E7gS6A08hYaWzgfcBVyQe92iwDPAVaikcD3gBjOb6u5/b/Q7bwWuST9/OHCbmS3u7iNn0qZXUKngc8AfgduBsem5xYC/AkOBtsDuwJNm1svdhwGY2UZAX+BxYB+UmVsPWBB4IP3OY2koRxw/k3bl+S3wJLAXDQHO22koSxyKHNZ7zWx1d38t97O7A28Ah9Jwz74XeBPYE5gMLAPM9RPsCoIgCAokHK0gCIJgpnD3L8zsIVQu+FT6/6H0eP5132e4UtbrSWAh4ACgsaN1sbtfn177MjAa+Dly0mbGpvFA/3T84fmyQXf/fc6O2ZBDtQZyULLnzgEGAH28YbDkQ7mfG55+16yUI37s7rvkfucmwNbARu7+RHr4ETNbGjgF+GWjn/+5u09KP9sFWBzYzt0Hpuf/Mwu2BUEQBAURpYNBEATBj+E2YCczawfsRKOyQQAz62Rml5nZCGBK+ncgsHQTv++R7At3/xQYg5yyWcbMeprZXWY2Gvgu2bFMZoeZzQGsBdyUc7KK4IFG328KfAw8Y2ats3/IYWpc2vifzMlKfAZ8AFxlZruY2fyFWR0EQRDMEuFoBUEQBD+Ge4GOwFnAHMB9TbzmRmAXVA64OcoiXQ+0b+K1X6wsCq4AAALASURBVDT6/pvpvO5HYWZzIiduYeAYVOa4BspeZb+/E2DAR7N6vB9gdKPvuwDdaHBCs39nJHun+7PuPhW9px+j9/RjM3vKzFapvdlBEATBrBClg0EQBMFM4+4Tzex+4GjgX+4+jdqgmbVHZXGHuftVucd/amBvEuqvytN5Jn5uHZQZ28zd38zZMXfuNZ8DU4HuBdvVOFv2GTAK2G4mjvNfmbb09+xoZm2QA3ke8ICZLZQcsSAIgqAZEBmtIAiC4MdyJcpkNdVH1Q4pAE7OHkjZpW1/4rFGAj0bPbbZTPxcJoWet2NdJJAByGkEngf2zpQUm+Cb9LONs2wjgcUaPT4zdoFKBLsBE9z9pcb/ZvJ34O5T3P0x4CLkLM4zsz8bBEEQFE9ktIIgCIIfhbv3A/pN57lxZvYicJqZjUcZoxOBcfw0Zby7gMvN7GTgRWAHYPmZ+Ln+wATgWjM7H2W3zkCZpDwnAo8CD5rZNUh1cB3gJXe/H6n7ARxpZo8B4939LeBuJKjxlyQnvwqw30z+TX2Bh4G+ZnYeUhWcC1gZaO/uJ03vB81sReBC4B/AMFT+eAIwwN0/m8njB0EQBCUQGa0gCIKg1uwOvIek1S8F7khf/xSuAS4BjgD+iTJMf/ihH3L30Ui9rxtwD3AUcDDwbqPXPYkyUbMDtyAHZkOUsQKpK14AHImyX1ennxsE/Ao5Zfemn/nVzPxBSXhjB9RjdRRyuq5Ov+vpH/jxj1Hf1inAg8CfgSH89IxhEARBUBBWrNBSEARBEARBEARB/REZrSAIgiAIgiAIghoTjlYQBEEQBEEQBEGNCUcrCIIgCIIgCIKgxoSjFQRBEARBEARBUGPC0QqCIAiCIAiCIKgx4WgFQRAEQRAEQRDUmHC0giAIgiAIgiAIakw4WkEQBEEQBEEQBDUmHK0gCIIgCIIgCIIa8/8z6xEL3pzIVQAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<Figure size 1044x432 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "winners_manu_df = pd.Series(winners_manu_cnt, index=winners_manu_cnt.keys()).sort_values(ascending=False)\n",
    "colors = []\n",
    "for i in range(len(winners_manu_df)):\n",
    "    if winners_manu_df[i] > 6:    colors.append('#2aaefa')\n",
    "    elif winners_manu_df[i] > 2:  colors.append('#18de39')\n",
    "    else:    colors.append('#deac37')\n",
    "plt.figure(figsize=(14.5,6))\n",
    "plt.bar(winners_manu_df.index, winners_manu_df, color=colors)\n",
    "plt.title(\"Car of the Year - # of Wins by Manufacturers (1964 - 2020)\", fontsize=16)\n",
    "plt.xlabel('Manufacturers', fontsize=15)\n",
    "plt.ylabel('Winner Count', fontsize=15)\n",
    "plt.xticks(rotation=78, fontsize=12)\n",
    "plt.yticks(range(1,10), range(1,10), fontsize=15)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Wow! It's **Fiat** which achieved this a total of **9** times! Right then, let's reveal which models have reached the top in their respective years:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "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>Winner</th>\n",
       "      <th>W_Pts</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Year</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2008</th>\n",
       "      <td>Fiat 500</td>\n",
       "      <td>385</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2004</th>\n",
       "      <td>Fiat Panda</td>\n",
       "      <td>281</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1996</th>\n",
       "      <td>Fiat Bravo/Brava</td>\n",
       "      <td>378</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1995</th>\n",
       "      <td>Fiat Punto</td>\n",
       "      <td>370</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1989</th>\n",
       "      <td>Fiat Tipo</td>\n",
       "      <td>356</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1984</th>\n",
       "      <td>Fiat Uno</td>\n",
       "      <td>346</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1972</th>\n",
       "      <td>Fiat 127</td>\n",
       "      <td>239</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1970</th>\n",
       "      <td>Fiat 128</td>\n",
       "      <td>235</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1967</th>\n",
       "      <td>Fiat 124</td>\n",
       "      <td>144</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                Winner  W_Pts\n",
       "Year                         \n",
       "2008          Fiat 500    385\n",
       "2004        Fiat Panda    281\n",
       "1996  Fiat Bravo/Brava    378\n",
       "1995        Fiat Punto    370\n",
       "1989         Fiat Tipo    356\n",
       "1984          Fiat Uno    346\n",
       "1972          Fiat 127    239\n",
       "1970          Fiat 128    235\n",
       "1967          Fiat 124    144"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "coty_win_nom[coty_win_nom['Winner'].str.contains('Fiat')][['Winner', 'W_Pts']]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "This clearly shows that Fiat is still seeking another win for more than 10 years!\n",
    "\n",
    "Beyond that, I'd like to see the top 3 of which models have earned **the most points** among the winners:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "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>Winner</th>\n",
       "      <th>W_Pts</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Year</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1988</th>\n",
       "      <td>Peugeot 405</td>\n",
       "      <td>464</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1998</th>\n",
       "      <td>Alfa Romeo 156</td>\n",
       "      <td>454</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1999</th>\n",
       "      <td>Ford Focus</td>\n",
       "      <td>444</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "              Winner  W_Pts\n",
       "Year                       \n",
       "1988     Peugeot 405    464\n",
       "1998  Alfa Romeo 156    454\n",
       "1999      Ford Focus    444"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "coty_win_nom[['Winner','W_Pts']].sort_values('W_Pts', ascending=False).head(3)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Oh, it's **Peugeot 405** with the most points earned, and still holding the record since 1988!\n",
    "\n",
    "In contrast, the top 3 of the winners with **the least points** earned are:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "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>Winner</th>\n",
       "      <th>W_Pts</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Year</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1964</th>\n",
       "      <td>Rover 2000</td>\n",
       "      <td>76</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1965</th>\n",
       "      <td>Austin 1800</td>\n",
       "      <td>78</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1966</th>\n",
       "      <td>Renault 16</td>\n",
       "      <td>98</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "           Winner  W_Pts\n",
       "Year                    \n",
       "1964   Rover 2000     76\n",
       "1965  Austin 1800     78\n",
       "1966   Renault 16     98"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "coty_win_nom[['Winner','W_Pts']].sort_values('W_Pts').head(3)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Ah, the **first three years** of CotY! Perhaps, that's because there were less cars nominated in the 60s, similarly much less juries attended to vote for.\n",
    "\n",
    "Now another aspect: let's show the winners with **the least point gaps** against the runner-ups (i.e. 2nd place):"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "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>Winner</th>\n",
       "      <th>W_Pts</th>\n",
       "      <th>2nd Place</th>\n",
       "      <th>2P_Pts</th>\n",
       "      <th>Won By</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Year</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2019</th>\n",
       "      <td>Jaguar I-Pace</td>\n",
       "      <td>250</td>\n",
       "      <td>Alpine A110</td>\n",
       "      <td>250</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2009</th>\n",
       "      <td>Opel/Vauxhall Insignia</td>\n",
       "      <td>321</td>\n",
       "      <td>Ford Fiesta</td>\n",
       "      <td>320</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2007</th>\n",
       "      <td>Ford S-Max</td>\n",
       "      <td>235</td>\n",
       "      <td>Opel/Vauxhall Corsa</td>\n",
       "      <td>233</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                      Winner  W_Pts            2nd Place  2P_Pts  Won By\n",
       "Year                                                                    \n",
       "2019           Jaguar I-Pace    250          Alpine A110     250       0\n",
       "2009  Opel/Vauxhall Insignia    321          Ford Fiesta     320       1\n",
       "2007              Ford S-Max    235  Opel/Vauxhall Corsa     233       2"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "coty_win_nom['Won By'] = coty_win_nom['W_Pts'] - coty_win_nom['2P_Pts']\n",
    "coty_win_nom.sort_values('Won By')[['Winner', 'W_Pts', '2nd Place', '2P_Pts', 'Won By']].head(3)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Whoa! Can you believe this? **Jaguar I-Pace** and the new generation of **Alpine A110** have both earned the same points in 2019! The juries had chosen the former car to crown for the win. Moreover, I couldn't find any specific reasons why Alpine A110 stayed in 2nd. The only statement I found in the CotY website was:\n",
    "\n",
    "_The enjoyable Alpine A110, with the same amount of points, has also flown well over its affordability and seating limitation._\n",
    "\n",
    "Maybe, we should read the juries' comments on both cars for a better understanding.\n",
    "\n",
    "Remarkably, the years **2009** and **2007** have seen the big competitions at the scene, almost head-to-head!\n",
    "\n",
    "On the other hand, let's see the winners that achieved with **the most point gaps**:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {
    "scrolled": true
   },
   "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>Winner</th>\n",
       "      <th>W_Pts</th>\n",
       "      <th>2nd Place</th>\n",
       "      <th>2P_Pts</th>\n",
       "      <th>Won By</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Year</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2013</th>\n",
       "      <td>Volkswagen Golf</td>\n",
       "      <td>414</td>\n",
       "      <td>Subaru BRZ/Toyota GT86</td>\n",
       "      <td>202</td>\n",
       "      <td>212</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1988</th>\n",
       "      <td>Peugeot 405</td>\n",
       "      <td>464</td>\n",
       "      <td>Citröen AX</td>\n",
       "      <td>252</td>\n",
       "      <td>212</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1998</th>\n",
       "      <td>Alfa Romeo 156</td>\n",
       "      <td>454</td>\n",
       "      <td>Volkswagen Golf</td>\n",
       "      <td>266</td>\n",
       "      <td>188</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "               Winner  W_Pts               2nd Place  2P_Pts  Won By\n",
       "Year                                                                \n",
       "2013  Volkswagen Golf    414  Subaru BRZ/Toyota GT86     202     212\n",
       "1988      Peugeot 405    464              Citröen AX     252     212\n",
       "1998   Alfa Romeo 156    454         Volkswagen Golf     266     188"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "coty_win_nom.sort_values('Won By', ascending=False)[['Winner', 'W_Pts', '2nd Place', '2P_Pts', 'Won By']].head(3)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Ah! It's **Volkswagen Golf** and **Peugeot 405** again with this great dominations, an astounding gap of **212** points!\n",
    "\n",
    "Now, another important analysis; this time let's count **the total number of nominations** for all manufacturers that appeared in CotY's all times.\n",
    "\n",
    "_For this purpose, it's convenient to separate both the manufacturer-model names and their points earned in different Series._"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [],
   "source": [
    "coty_all_nominees = coty_win_nom[['Winner', '2nd Place', '3rd Place', '4th Place', '5th Place',\n",
    "                                 '6th Place', '7th Place', '8th Place', '9th Place', '10th Place']].fillna('N/A')\n",
    "coty_all_points = coty_win_nom[['W_Pts', '2P_Pts', '3P_Pts', '4P_Pts', '5P_Pts',\n",
    "                                 '6P_Pts', '7P_Pts', '8P_Pts', '9P_Pts', '10P_Pts']].fillna(0)\n",
    "all_manu_nominees_cnt = {}\n",
    "all_manu_points = {}\n",
    "for i in range(2020,1963,-1):\n",
    "    nominees = coty_all_nominees.loc[i].values\n",
    "    points = coty_all_points.loc[i].values\n",
    "    for j in range(len(nominees)):\n",
    "        if nominees[j] == 'N/A':   continue\n",
    "        manu = nominees[j].split()[0]\n",
    "        if nominees[j].split()[0] not in all_manu_nominees_cnt.keys():\n",
    "            all_manu_nominees_cnt[manu] = 1\n",
    "            all_manu_points[manu] = points[j]\n",
    "        else:\n",
    "            all_manu_nominees_cnt[manu] += 1\n",
    "            all_manu_points[manu] += points[j]\n",
    "all_manu_nominees_cnt['Rolls Royce'] = all_manu_nominees_cnt.pop('Rolls')\n",
    "all_manu_points['Rolls Royce'] = all_manu_points.pop('Rolls')\n",
    "all_manu_nominees_cnt['Alfa Romeo'] = all_manu_nominees_cnt.pop('Alfa')\n",
    "all_manu_points['Alfa Romeo'] = all_manu_points.pop('Alfa')\n",
    "all_manu_nominees_cnt['Range Rover'] = all_manu_nominees_cnt.pop('Range')\n",
    "all_manu_points['Range Rover'] = all_manu_points.pop('Range')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Again, it's necessary to rename some manufacturers to their original double-worded ones.\n",
    "\n",
    "OK, let's pay attention to the visualization below:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 864x936 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "all_manu_nominees_sr = pd.Series(all_manu_nominees_cnt, index=all_manu_nominees_cnt.keys()).sort_values()\n",
    "colors = []\n",
    "for v in all_manu_nominees_sr:\n",
    "    if v >= 20:      colors.append('#00c0fa')\n",
    "    elif v >= 15:    colors.append('#00a8db')\n",
    "    elif v >= 10:    colors.append('#0093bf')\n",
    "    elif v >= 5:     colors.append('#00799e')\n",
    "    else:            colors.append('#005c78')\n",
    "plt.figure(figsize=(12,13))\n",
    "plt.barh(all_manu_nominees_sr.index, all_manu_nominees_sr, color=colors)\n",
    "plt.axis([0,25,-0.8,len(all_manu_nominees_sr)])\n",
    "plt.title('Car of the Year - Total # of Nominations by Manufacturers (1964 - 2020)', fontsize=17)\n",
    "for i in range(len(all_manu_nominees_sr)):\n",
    "    plt.text(all_manu_nominees_sr[i]+0.15,i-0.25,all_manu_nominees_sr[i], fontsize=12)\n",
    "plt.xlabel('Total Nominations', fontsize=14)\n",
    "plt.ylabel('Manufacturers', fontsize=15)\n",
    "plt.xticks([5,10,15,20], [5,10,15,20], fontsize=14)\n",
    "plt.yticks(fontsize=13)\n",
    "plt.grid(axis='x', linestyle=':')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Wow! It's **Citröen** that has been nominated **23** times in total, the most of all times! Then, **Ford** comes after with **22** nominations. By the way, one can realize that **Opel** and **Opel/Vauxhall** have appeared in the nominations a total of **21** times, although I did not combine them here.\n",
    "\n",
    "But, what makes me surprised is that several well-known manufacturers had **only 1** nomination in CotY, such as **Range Rover**, **Seat**, **Hyundai**, **Dacia**, **Mini**, **Rolls Royce**, **Subaru**. And, even no **Mitsubishi** at all!\n",
    "\n",
    "Now, moving to similar aspect, the next visualization is for **summing up all points** for the manufacturers by considering all their nominated models:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 864x936 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "all_manu_points_sr = pd.Series(all_manu_points, index=all_manu_points.keys()).sort_values()\n",
    "colors = []\n",
    "for v in all_manu_points_sr:\n",
    "    if v >= 5000:     colors.append('#00aaf2')\n",
    "    elif v >= 4000:   colors.append('#00eaf2')\n",
    "    elif v >= 3000:   colors.append('#00f220')\n",
    "    elif v >= 2000:   colors.append('#baf200')\n",
    "    elif v >= 1000:   colors.append('#f2ea00')\n",
    "    elif v >= 500:    colors.append('#f29900')\n",
    "    else:             colors.append('#f20000')\n",
    "plt.figure(figsize=(12,13))\n",
    "plt.barh(all_manu_points_sr.index, all_manu_points_sr, color=colors)\n",
    "plt.axis([0,all_manu_points_sr.max()+400,-0.8,len(all_manu_points_sr)])\n",
    "for i in range(len(all_manu_points_sr)):\n",
    "    plt.text(all_manu_points_sr.iloc[i]+20,i-0.2,int(all_manu_points_sr.iloc[i]), fontsize=13)\n",
    "plt.title('Car of the Year - Total Points Earned by Manufacturers (1964 - 2020)', fontsize=17)\n",
    "plt.xlabel('Points', fontsize=14)\n",
    "plt.ylabel('Manufacturers', fontsize=14)\n",
    "plt.xticks([1000,2000,3000,4000,5000],[1000,2000,3000,4000,5000],fontsize=14)\n",
    "plt.yticks(fontsize=13)\n",
    "plt.grid(axis='x', linestyle=':')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Ah! **Ford** has accumulated the most points in CotY history, amassing **more than 5000** points! **Fiat**, the manufacturer with the most wins, comes in second place. Later, the French car maker **Citröen** which is praised for having the most nominations.\n",
    "\n",
    "Of course, when combined, **Opel** and **Opel/Vauxhall** together would have been in 2nd place, another manufacturer that could surpass 5000 points.\n",
    "\n",
    "We've got the nomination counts and total points; now we are able to get **the average points earned per nominated model** for each manufacturer, and print the top 10. Will there be something unfamiliar?\n",
    "\n",
    "_For this analysis, I've decided to exclude the manufacturers with a single nomination, in advance._"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "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>Nominated</th>\n",
       "      <th>Points</th>\n",
       "      <th>Average Pts</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>Opel</th>\n",
       "      <td>6</td>\n",
       "      <td>1719.0</td>\n",
       "      <td>286.50</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Lancia</th>\n",
       "      <td>3</td>\n",
       "      <td>851.0</td>\n",
       "      <td>283.67</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Fiat</th>\n",
       "      <td>18</td>\n",
       "      <td>4679.0</td>\n",
       "      <td>259.94</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Volkswagen</th>\n",
       "      <td>16</td>\n",
       "      <td>4039.0</td>\n",
       "      <td>252.44</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Porsche</th>\n",
       "      <td>2</td>\n",
       "      <td>483.0</td>\n",
       "      <td>241.50</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Mazda</th>\n",
       "      <td>6</td>\n",
       "      <td>1448.0</td>\n",
       "      <td>241.33</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Ford</th>\n",
       "      <td>22</td>\n",
       "      <td>5302.0</td>\n",
       "      <td>241.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Toyota</th>\n",
       "      <td>9</td>\n",
       "      <td>2117.0</td>\n",
       "      <td>235.22</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Opel/Vauxhall</th>\n",
       "      <td>15</td>\n",
       "      <td>3526.0</td>\n",
       "      <td>235.07</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Tesla</th>\n",
       "      <td>2</td>\n",
       "      <td>458.0</td>\n",
       "      <td>229.00</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "               Nominated  Points  Average Pts\n",
       "Opel                   6  1719.0       286.50\n",
       "Lancia                 3   851.0       283.67\n",
       "Fiat                  18  4679.0       259.94\n",
       "Volkswagen            16  4039.0       252.44\n",
       "Porsche                2   483.0       241.50\n",
       "Mazda                  6  1448.0       241.33\n",
       "Ford                  22  5302.0       241.00\n",
       "Toyota                 9  2117.0       235.22\n",
       "Opel/Vauxhall         15  3526.0       235.07\n",
       "Tesla                  2   458.0       229.00"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "all_manu_nom_pts = pd.concat([all_manu_nominees_sr, all_manu_points_sr], axis=1, keys=['Nominated', 'Points'])\n",
    "all_manu_nom_pts['Average Pts'] = round(all_manu_nom_pts['Points'] / all_manu_nom_pts['Nominated'], 2)\n",
    "single_nom = []\n",
    "for i in range(len(all_manu_nom_pts)):\n",
    "    if all_manu_nom_pts.iloc[i,0] == 1:\n",
    "        single_nom.append(all_manu_nom_pts.index[i])\n",
    "all_manu_nom_pts.drop(index=single_nom, inplace=True)\n",
    "all_manu_nom_pts.sort_values('Average Pts', ascending=False).head(10)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Oh, it's **Opel** which potentially had the most average points per nomination! **Fiat** with 18 nominees is in the 3rd place. Interestingly, the sports car maker **Porsche** and the electric one, **Tesla** have made it to the list!\n",
    "\n",
    "If you wonder the placement when **Opel** and **Opel/Vauxhall** were merged, the average point would be:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Average point for Opel when combined: 249.76\n"
     ]
    }
   ],
   "source": [
    "opel_pts = all_manu_nom_pts.loc['Opel','Points'] + all_manu_nom_pts.loc['Opel/Vauxhall','Points']\n",
    "opel_nom = all_manu_nom_pts.loc['Opel','Nominated'] + all_manu_nom_pts.loc['Opel/Vauxhall','Nominated']\n",
    "print('Average point for Opel when combined: {:.2f}'.format(opel_pts / opel_nom))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Surely, that could put them in the **4th** place.\n",
    "\n",
    "How about **Citröen** as we did not see the French company in the list?"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Nominated        23.00\n",
       "Points         4514.00\n",
       "Average Pts     196.26\n",
       "Name: Citröen, dtype: float64"
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "all_manu_nom_pts.loc['Citröen']"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Now, let's go to a specific exploration: **Car of the Year 2001**\n",
    "\n",
    "It's the only year that there were up to **10** nominees participated for winning the award. And, that's the reason why the related dataset was extended to hold at most ten places. Anyway, let's visualize for how it was resulted:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1008x432 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(14,6))\n",
    "colors = []\n",
    "for i in range(1,20,2):\n",
    "    if i < 2:    colors.append('#c400f5')\n",
    "    elif i < 6:  colors.append('#9d00d9')\n",
    "    elif i < 14: colors.append('#7100b5')\n",
    "    else:        colors.append('#4c0087')\n",
    "plt.bar(coty_win_nom.iloc[19,range(0,20,2)], coty_win_nom.iloc[19,range(1,20,2)], width=0.5, color=colors)\n",
    "plt.axis([-0.4,9.4,0,255])\n",
    "for i in range(1,20,2):\n",
    "    pt = coty_win_nom.iloc[19,i]\n",
    "    if  pt >= 100:   plt.text((i/2)-0.66,pt+4,int(pt), fontsize=13)\n",
    "    elif pt >= 10:   plt.text((i/2)-0.6,pt+4,int(pt), fontsize=13) \n",
    "    else:            plt.text((i/2)-0.55,pt+4,int(pt), fontsize=13)\n",
    "plt.title('Car of the Year 2001 - Nominees & Points', fontsize=18)\n",
    "plt.xlabel('Nominees', fontsize=14)\n",
    "plt.ylabel('Points', fontsize=14)\n",
    "plt.xticks(fontsize=11, rotation=80)\n",
    "plt.yticks([50,100,150,200],[50,100,150,200],fontsize=13)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "In that year, **Alfa Romeo 147** had breasted the rope to take the win with **238** points. In contrast, it's the year **Citröen** does not want to remember; its MPV-class model **Xsara Picasso** only scored **8** points, not even a double digit! That's the lowest in the CotY history, unfortunately.\n",
    "\n",
    "_Did you wonder what Citröen Xsara Picasso looked like? Don't forget to Google it._\n",
    "\n",
    "In the last visualization, let's observe **the points in each place** for CotY's last 5 years.\n",
    "\n",
    "Frankly, the **bar chart** below tells you everything what's in mind. I'll leave the interpretation to you..."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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Uf+J7th/Fn+MP4IeDXokf1nns2HfOPWJm6/FBzD/i70G61cx+GfQMpZRzrsHM/oYPYJOV0HvSzJbg73XbgO+N/RtQj7/XaQ0JnFcTbONBwfOpMBuidGEKmkTi9wz+ht6bCGYVasVsYATwZefcE5ELgokRklWOD8JOGLZlZgPxF00tXQjGI1Xf2hUDnwJ2Oef+0trKbfQuvr694gwArgdebX7R0qyHJxnX4e/5CattacVguxn4i6kXiD7hw0fwE2jMwR+HXUEir+FfgSwzS3PO1bVQ3j78xBP92xjEtUVx8HyoHbYZ8/3jnDuAD/J/FvQMLcPf+zUXP3lAS5rwF/0jgd1BWZVmlo3vxXgWf274vXPupRZLSVwJ8CkzOyNKb/g4fE/8/hOztVlrr982/BdZD5j/Ae43gWVm9pNWepC2Bc9jgc2JVirY1mfw93Atbrbs0hbqGsIHsD81P7PkWuALZrYiGEKash4SM0vHHxtvpKC4RN+T1+OHQ18R2WNqZp9qy8YTaOPwOWdb8zJEUkn3NInE76f4yQD+2czmRlvBzKYEwxPgg29Urdk6l9Hy/UxxCz6UfgtMivKhlIN/fz+bxCbCw2QGxVyrdWuD56UWfSrqpMehO+cq8PegzLNguulm27BgyFzYUU5sl74cP1NXMvXZ5Jx7MeKxqZUsn8f3SD7inPt18wf+gvow/p6nriKR1/Dn+KE532m+IAgYwsfzz/H3b0Wdij4Vx0ozf8AHGDlmdsJxbma9g4C2LaK+f8yse3ABeExwAbgl2vpRhO+1eiDyHqLgPbAA3yYj8ZMCpNI6/DklJzLRzK7Az4z2X3EMLUxEDTAwfHxEbG9Q83ungiDuPXwPW3or5b4SPJ9wnohTS+f1TPwXapFpfazZVNvOz64YnoU03NYJn2uD+6iiuQ//hfhv4y2rJW14Tx4lGP4YsTw8jDdubWjjjwN7XQf+Vp+cntTTJBIn59xhM/sMfrrTdWa2Ad8zUIEf+z0Lf+/SA0GW/8XPzLUiGIqzBz/u/3r8UL0JKajW3fib2deZ2UP4HpcZwLX4YSMtDVWLR/ibyuVm9nP8TF3bgm//4uace8vM7sHfXPy2mT2NH7aRCUzBD79o6w9yRroF/5q/GoyH34K/yDsX/+39k/j7EMBPmfxVM/slfujJcHxAUkHnWIQPin4fbWFw7D0PfNbMPuScK+vQ2kWXyGu4CrgK+I75H4DegD+exuPvRwt/Q/9t/JTWvzKzX+GPwXr8UMcrgTz8fQ4p4Zw7ZP6Hk9cB75jZavx76Az8zfzz8BMgvNKG4t/C9wp9O+j5PYS/6HsHCJmf3nkLPmg7B3/8VtL6xe4TQb0+D1wQvE7l+NfyBvxEDoeAh82sxDn3v22oezRrgIX4H7sdjT+/jMFPPb2X+HrfE/EGvkfnQTP7I/6C/CXgn4Bvmll4mvgG/LC3y4FfOedi9urij6Ed+OOppaF8X26hdyTPOfd8cO7/opnV8sFQ3K/i2zcymDkP+J+grtvw7ZuFb+v3CCYtcc5VmNm7wOfN/w7cXnzvZ6xj4TvBF0QvA7vw97deif8cehP4f7Ffhrgl8p78NX6ikOfN7Df4IZD/hG+jRNxAnG0cDIP/JLHvSxRJDdfO0/Ppocep9sB/0/VN/AV6Jf6EvhcfTF0PdI9Y9yP4C+FK/FC6V/An+DUEXzBHrPsKUabYjaM+5+B7c8rxH2Y78L930qfZejNJYMrxIM9dQXkNREyJS+zpyEuBV6Kkfxr/zf4B/IxSu4HngVsS3N+ZkXVptmwI/kbov+Ivyg/iA9RVwLhmbfhD/L1GR/DDtHLwQyqPe42IMXV0io6ncUH5z7Sy3heC9e5uqV6JtHFE/s/Fse4J7Z3Iaxisn46/ANse0TZvAV+L8v76btButcH75i/433GZFk+7BOlroqSvodn7Lki/ED9Urgz/HtqLv2fou8Cg1t6jtDBlND7IKAzKdMH2e+EvLP+EDzDr8O+Z1cDYOI+Z7vj7yfLwwXZt8Hrdiw/4zsGfDw4CE1N4HPQN6r4j2Kdy/Lnn7NZej5ZeoxjHV1/872zt5YMejJn4L55y8RfTh/DDAgvw97ykxfn63YW/B2l4C/Vo6fFIsN4Q/MiDv+GP5a34WQaPOybxAdS/4YdJHwza6V38Pa6Zzbb9Mfxv6R0KyjjhOGu2/lz8+bQsqMOhYDt3A+nxnn+itE+0902878nu+Pt138Uf1zvxXyJmRTkeZtLCuSqRNsa/xxxwYaL7rIceiT7MOU02IiIiIqcH89NYFwOPOedOGDIqJw8zywN2OufmdXZd5NSne5pERETktOH8bzTdA3wjxr1B0sWZ2Wfxw9y/1dl1kdODeppERERERERiUE+TiIiIiIhIDAqaREREREREYlDQJCIiIiIiEsNp8TtNQ4YMcaNHj+7saoiIiIiISBeVl5e33zk3NNqy0yJoGj16NJs3b+7saoiIiIiISBdlZjtbWqbheSIiIiIiIjEoaBIREREREYlBQZOIiIiIiEgMp8U9TSIiIiIiEl1DQwN79uzhyJEjnV2VDpGens7IkSPp2bNn3HkUNImIiIiInMb27NlDRkYGo0ePxsw6uzrtyjlHRUUFe/bs4Zxzzok7n4bniYiIiIicxo4cOcLgwYNP+YAJwMwYPHhwwr1qCppERERERE5zp0PAFNaWfVXQJCIiIiIinWb37t3MmjWLrKwsxo8fz6pVqwA4cOAA2dnZjB07luzsbCorKwF44YUXmDJlChMmTGDKlCm89NJLx8rKy8tjwoQJjBkzhm984xs451JSR93TJCIiIiIixywtSG15d18Ue3mPHj1YsWIFkydPprq6milTppCdnc2aNWuYPXs2OTk5LFu2jGXLlrF8+XKGDBnCb3/7W0aMGMG2bdu4/PLLKSsrA+CWW27h0Ucf5eMf/zhXXnklv//977niiiuS3gf1NImIiIiISKfJzMxk8uTJAGRkZJCVlUVZWRnr169n4cKFACxcuJB169YBMGnSJEaMGAHA+PHjOXLkCHV1dYRCIaqqqrj44osxM2644YZjeZKloElERERERLqE0tJStmzZwrRp09i7dy+ZmZmAD6zKy8tPWP+ZZ55h0qRJpKWlUVZWxsiRI48tGzly5LEeqGRpeJ6IiIiIiHS6mpoa5s+fz8qVK+nfv3+r62/fvp1vfetbbNiwASDq/UupmuBCPU0iIiIiItKpGhoamD9/Ptdddx3z5s0DYPjw4YRCIQBCoRDDhg07tv6ePXu4+uqrefLJJ/nwhz8M+J6lPXv2HLdOeBhfstTTdLrpf0dy+atWpKYeIiIiIiL4HqJFixaRlZXFkiVLjqXPmTOH3NxccnJyyM3NZe7cuQAcPHiQT3/609x///184hOfOLZ+ZmYmGRkZvPHGG0ybNo0nn3ySr3/96ympo3qaRERERESk02zatIm1a9fy0ksvMXHiRCZOnMhzzz1HTk4OL7zwAmPHjuWFF14gJycHgAcffJB3332X++6779j64fudHn74YW666SbGjBnDhz/84ZTMnAdgqZq7vCubOnWq27x5c2dXo2tQT5OIiIiIRPjLX/5CVlZWZ1ejQ0XbZzPLc85Njba+eppERERERERiUNAkIiIiIiISg4ImERERERGRGDR7niRkdfUlSeX/csZLKaqJiIiIiEjHUE+TiIiIiIhIDAqaREREREREYlDQJCIiIiIinWb37t3MmjWLrKwsxo8fz6pVqwA4cOAA2dnZjB07luzsbCorKwGoqKhg1qxZ9OvXj1tvvfW4sn75y1/ykY98hPHjx3PXXXelrI66p0lERERERD7w9tjUljexOObiHj16sGLFCiZPnkx1dTVTpkwhOzubNWvWMHv2bHJycli2bBnLli1j+fLlpKenc99997Ft2za2bdt2rJyKigruvPNO8vLyGDp0KAsXLmTjxo3Mnj076V1QT5OIiIiIiHSazMxMJk+eDEBGRgZZWVmUlZWxfv16Fi5cCMDChQtZt24dAH379mX69Omkp6cfV86OHTs477zzGDp0KACXXnopzzzzTErqqKBJRERERES6hNLSUrZs2cK0adPYu3cvmZmZgA+sysvLY+YdM2YMRUVFlJaW0tjYyLp169i9e3dK6qXhedKhVv24us15b1uSkcKaiIiIiEhXUlNTw/z581m5ciX9+/dPOP/AgQN5+OGHufbaa+nWrRv/8A//wI4dO1JSN/U0iYiIiIhIp2poaGD+/Plcd911zJs3D4Dhw4cTCoUACIVCDBs2rNVyrrrqKt58801ef/11zj//fMaOTc39WQqaRERERESk0zjnWLRoEVlZWSxZsuRY+pw5c8jNzQUgNzeXuXPntlpWeAhfZWUlDz30EDfddFNK6qjheSIiIiIi0mk2bdrE2rVrmTBhAhMnTgRg6dKl5OTksGDBAh5//HFGjRrF008/fSzP6NGjqaqqor6+nnXr1rFhwwbGjRvHbbfdRkFBAQDf+973OO+881JSRwVNIiIiIiLygVamCE+16dOn45yLumzjxo1R00tLS6OmP/XUU6mq1nE0PE9ERERERCQGBU0iIiIiIiIxKGgSERERERGJoUODJjP7VzN7z8yqzKzczH5tZqMilt9gZiVmdtjM3jSzKc3yTzWzPwXLS8zsix1ZfxEREREROf10dE/TWmCic64/MBrYBfwCwMymAw8DtwADgWeA58ysf7B8APB8kD4QWAw8YmYXd/A+iIiIiIjIaaRDgybnXJFz7v3gXwOagPOD/78C/MY5t8E5Vwf8EKgDrg6WzwNqgQecc3XOuReAZ4GbO2wHRERERETktNPh9zSZ2T+Z2ftADXAbcG+w6CIgL7ye8/MObgnSw8vz3fHzEeZHLG++nZvNbLOZbQ6FQuzfv59QKERZWRmVlZWUlJRQW1tLYWEhTU1N5OfnA5CX56uQn59PU1MThYWF1NbWUlJSQmVlJWVlZYTLKy0tpaamhqKiIhobG4/NCR8uI/y8detW6urqKC4upqqqil27dlFeXk55eTm7du2iqqqK4uJi6urq2Lp1a9QyCgoKaGxspKioiJqaGkpLS9u2T92gcMFoagelUXLZCCrPzaBs2lBCkwax//wBlM46k5rh6RRdPYrGtG4U3DjGl7HYx7b9tl8OQJ/iGVh9b9J3TqF7zWDSQln0rBhFz4pRpIWy6F4zmPSdU7D63vQpnnFc3iHDtgMwaMg7mDUyYOB79Oh5mH4ZZaSlV9K7zz769N1Lr7QqMgbspnv3I5wxqOT0aiftk/ZJ+6R90j5pn7RP2qcO2qf6+noADh06dNzz4cOHaWpq4siRIxw9epS6ujoaGhpoaGigrq6Oo0ePcuTIEZqamjh8+HCLZTjnqK2tPa6M+vp66uvraWxspLi4mFmzZnHBBRcwfvx4HnjgAQB2795NdnY2Y8aMITs7m7/97W80NTVRVlbGzJkz6devH7fccstx9cnNzWXChAlceOGFfOpTn2Lnzp1R96mhoeGEdorFWpoTvb2Z2ZnAImCTc+4VMysBfuCceyJinVygwTl3k5k9DvRwzi2MWP4l4NvOuTGxtjV16lS3efPm9tmRk03/O5LKvrpsS1L5qx9b3+a8ty3JSGrbIiIiInKiv/zlL2RlZX2QkOT14gmqVsRcHAqFCIVCTJ48merqaqZMmcK6detYs2YNgwYNIicnh2XLllFZWcny5cs5dOgQW7ZsYdu2bWzbto0HH3wQgMbGRkaMGEFhYSFDhgzhrrvuok+fPtx7770nbPOEfQbMLM85NzVaHTtt9jzn3N+Bx4DfmdkgoBoY0Gy1M4Cq4O/WlouIiIiIyEkmMzOTyZMnA5CRkUFWVhZlZWWsX7+ehQt9f8nChQtZt24dAH379mX69Omkp6cfV45zDucchw4dwjlHVVUVI0aMSEkdO3vK8R5AX2AEUABMDi8wMwMmBukEz5Oa5Z8UsVxERERERE5ipaWlbNmyhWnTprF3714yMzMBH1i1NoSuZ8+ePPzww0yYMOFYj9OiRYtSUq8eKSklDmbWDfga8CvnXLmZjQT+H1AKFOF7nX4fDMl7DfgGkI6f7IHg+QEzuxNYBXwSPzlEdkftg8jJYHX1JUnl/3LGSymqiYiIiP6ij6AAACAASURBVEj8ampqmD9/PitXrqR///4J529oaODhhx9my5YtnHvuuXz961/n/vvv5zvf+U7SdevonqYrgW1mdgh4EzgMXOqca3TO/S8+qHoMeB9YAFzpnKsCcM4dDPJfEyx/DFjsnHu9g/dBRERERERSqKGhgfnz53Pdddcxb948AIYPH04oFAL8fU/Dhg2LWcbbb78NwIc//GHMjAULFvDHP/4xJfXrsJ4m51wTPuiJtc6TwJMxlr8FfCzFVRORCKt+XJ1Ufk3YISIiIolwzrFo0SKysrJYsmTJsfQ5c+aQm5tLTk4Oubm5zJ07N2Y5H/rQhygsLGTfvn0MHTqUF1544YTJHtqqw4ImERERERGR5jZt2sTatWuZMGECEydOBGDp0qXk5OSwYMECHn/8cUaNGsXTTz99LM/o0aOpqqqivr6edevWsWHDBsaNG8c999zDjBkz6NmzJ2effTZr1qxJSR0VNImIiIiIyAdamSI81aZPn05LP4O0cePGqOmlpaVR0xcvXszixYtTVbVjOnv2PBERERERkS5NQZOIiIiIiEgMCppERERERERiUNAkIiIiIiISg4ImERERERGRGBQ0iYiIiIiIxKCgSUREREREOs3u3buZNWsWWVlZjB8/nlWrVgFw4MABsrOzGTt2LNnZ2VRWVgJQUVHBrFmz6NevH7feeuuxcqqrq5k4ceKxx5AhQ7j99ttTUkf9TpOIiIiIiByzuvqSlJb35YyXYi7v0aMHK1asYPLkyVRXVzNlyhSys7NZs2YNs2fPJicnh2XLlrFs2TKWL19Oeno69913H9u2bWPbtm3HysnIyODtt98+9v+UKVOYN29eSvZBPU0iIiIiItJpMjMzmTx5MuADn6ysLMrKyli/fj0LFy4EYOHChaxbtw6Avn37Mn36dNLT01sss7i4mPLycj75yU+mpI7qaepgSwuSy3/3Ramph4iIiIhIV1NaWsqWLVuYNm0ae/fuJTMzE/CBVXl5edzlPPXUU1x77bWYWUrqpZ4mERERERHpdDU1NcyfP5+VK1fSv3//pMr6xS9+wRe+8IUU1UxBk4iIiIiIdLKGhgbmz5/Pddddd+w+pOHDhxMKhQAIhUIMGzYsrrIKCgpobGxkypQpKaufgiYREREREek0zjkWLVpEVlYWS5YsOZY+Z84ccnNzAcjNzWXu3LlxlffUU0+ltJcJdE+TiIiIiIh0ok2bNrF27VomTJjAxIkTAVi6dCk5OTksWLCAxx9/nFGjRvH0008fyzN69Giqqqqor69n3bp1bNiwgXHjxgHwq1/9iueeey6ldVTQJCIiIiIix7Q2RXiqTZ8+Hedc1GUbN26Mml5aWtpieTt27EhFtY6j4XkiIiIiIiIxKGgSERERERGJQUGTiIiIiIhIDAqaREREREREYlDQJCIiIiIiEoOCJhERERERkRgUNImIiIiISKfZvXs3s2bNIisri/Hjx7Nq1SoADhw4QHZ2NmPHjiU7O5vKykoAKioqmDVrFv369ePWW289rqz6+npuvvlmzjvvPC644AKeeeaZlNRRv9MkIiIiIiLHrPpxdUrLu21JRszlPXr0YMWKFUyePJnq6mqmTJlCdnY2a9asYfbs2eTk5LBs2TKWLVvG8uXLSU9P57777mPbtm1s27btuLL+9V//lWHDhvHXv/6VpqYmDhw4kJJ9UNAkIiIiIiKdJjMzk8zMTAAyMjLIysqirKyM9evX88orrwCwcOFCZs6cyfLly+nbty/Tp0/n3XffPaGs1atXU1RUBEC3bt0YMmRISuqo4XkiIiIiItIllJaWsmXLFqZNm8bevXuPBVOZmZmUl5fHzHvw4EEAvvvd7zJ58mSuueYa9u7dm5J6KWgSEREREZFOV1NTw/z581m5ciX9+/dPOH9jYyN79uzhE5/4BPn5+Vx88cX88z//c0rqpqBJREREREQ6VUNDA/Pnz+e6665j3rx5AAwfPpxQKARAKBRi2LBhMcsYPHgwffr04eqrrwbgmmuuIT8/PyX1U9AkIiIiIiKdxjnHokWLyMrKYsmSJcfS58yZQ25uLgC5ubnMnTs3ZjlmxlVXXXXsPqiNGzcybty4lNRRE0GIiIiIiEin2bRpE2vXrmXChAlMnDgRgKVLl5KTk8OCBQt4/PHHGTVqFE8//fSxPKNHj6aqqor6+nrWrVvHhg0bGDduHMuXL+f666/n9ttvZ+jQoTzxxBMpqaOCJhEREREROaa1KcJTbfr06Tjnoi7buHFj1PTS0tKo6WeffTavvvpqqqp2jIbniYiIiIiIxKCgSUREREREJAYFTSIiIiIiIjEoaBIREREROc21dE/Rqagt+6qgSURERETkNJaenk5FRcVpETg556ioqCA9PT2hfB02e56ZLQc+A5wF1AD/DXzLOXcgWH4jsBo4HJHtt865L0SUMRV4CLgQCAH3OOd+1iE7ICIiIiJyCho5ciR79uxh3759nV2VDpGens7IkSMTytORU44fBb4IbAPOAJ4EngAif6Vqh3NuTLTMZjYAeB74EfBJYAbwrJmVOOdeb8+Ki4iIiIicqnr27Mk555zT2dXo0jpseJ5z7m7n3BbnXINzbh/wIDAzgSLmAbXAA865OufcC8CzwM2pr62IiIiIiIjXmfc0zQb+3CztLDP7u5ntNrNfmFlkyHsRkO+OH2yZH6SLiIiIiIi0i04JmsxsPvAV4LaI5FeBCcAI4KPAEeAFM+sbLM8A3m9W1EGgfwvbuNnMNpvZ5lAoxP79+wmFQpSVlVFZWUlJSQm1tbUUFhbS1NREfn4+AHl5eQDk5+fT1NREYWEhtbW1lJSUUFlZSVlZGeHySktLqampoaioiMbGRgoKCo4rI/y8detW6urqKC4uJq2+igE1u+hbW07f2nIG1Owirb6Kwe8X0/1oHWce2ArAh/blHfecWVFAt6ZGil75GjVvXUzpa19k/xuXE/rjXMo2fY7KNy+h5NUvUbt5KoUvf4OmLeeT/+J34O2x5L34PXh7LPkvfoemblC4YDS1g9IouWwEledmUDZtKKFJg9h//gBKZ51JzfB0iq4eRWNaNwpu9KMl8xafD0C/7ZcD0Kd4Blbfm/SdU+heM5i0UBY9K0bRs2IUaaEsutcMJn3nFKy+N32KZxyXd8iw7QAMGvIOZo0MGPgePXoepl9GGWnplfTus48+fffSK62KjAG76d79CGcMKunQdqqqqmLXrl2Ul5dTXl7Orl27qKqqori4mLq6OrZu3Rq1jIKCAhrzxyfXTinYp2TaKdw+p3w7NTZSVFRETU0NpaWlXeYcoX3SPmmftE/aJ+2T9qlz9ikW6+hZMszsGuA/gPnOuZdjrNcTHyRd5ZzbaGYrgdHOuc9GrPNN4Hrn3ORY25w6darbvHlzanYgSUsLkst/txubXAEz5iSVfXXZlqTyVz+2vs15b1uSkdS2O8zbSbbRxOKksq+uviSp/Mm0EZxE7SQiIiISwczynHNToy3r0J4mM/sSPmC6KlbAFHDBw4L/C4BJzdaZFKSLiIiIiIi0i46ccvwbwD3A5c65t6Is/zQ+ACoDBgL3A/uBN4JVngUeMLM7gVX4GfTmAdntX3sROeUk0yOYZG+giIiInFw6sqdpFf7+o5fNrCb8iFg+E/gT/jectgODgWznXA2Ac+4gcCVwDX7Y3mPAYk03LiIiIiIi7anDepqcc9bK8juBO1tZ5y3gY6msl4iIiIiISCydOeW4iIiIiIhIl6egSUREREREJIYOG54ncjJJZmr4u5PdeP87kstflmwFRERERCSSeppERERERERiUNAkIiIiIiISg4ImERERERGRGBQ0iYiIiIiIxKCgSUREREREJAbNniciIl3T22OTyz+xODX1EBGR0556mkRERERERGJQ0CQiIiIiIhKDgiYREREREZEYFDSJiIiIiIjEoKBJREREREQkBgVNIiIiIiIiMShoEhERERERiUFBk4iIiIiISAz6cVsRkUT1vyO5/FUrUlMPERER6RDqaRIREREREYlBQZOIiIiIiEgMCppERERERERi0D1NInJSWlqQXP67U1MNEREROQ2op0lERERERCQGBU0iIiIiIiIxKGgSERERERGJQUGTiIiIiIhIDAqaREREREREYlDQJCIiIiIiEoOCJhERERERkRgUNImIiIiIiMSgoElERERERCSGHp1dAREROTUtLUgu/92pqYaIiEjSFDSJiIhI27w9Nrn8E4tTUw8RkXamoElEROQ0pd5AEZH46J4mERERERGRGBQ0iYiIiIiIxKCgSUREREREJAYFTSIiIiIiIjF02EQQZrYc+AxwFlAD/DfwLefcgYh1bgDuATKBrcDXnHN5EcunAg8BFwIh4B7n3M86ah9EROQk0v+OtuetWpG6eoiIyEmvI3uajgJfBAYDFwEjgSfCC81sOvAwcAswEHgGeM7M+gfLBwDPB+kDgcXAI2Z2cQfug4iIiIiInGY6rKfJORc5M+k+M3sQ+M+ItK8Av3HObQAwsx8CtwJXA7nAPKAWeMA554AXzOxZ4Gbg9Q7YBRGRLmHVj6uTyn/bkowU1UREROT00Jn3NM0G/hzx/0XAsaF4QWC0JUgPL88P0sPyI5aLiIiIiIikXKcETWY2H9+zdFtEcgbwfrNVDwL941zefBs3m9lmM9scCoXYv38/oVCIsrIyKisrKSkpoba2lsLCQpqamsjPzwcgL8/Hbfn5+TQ1NVFYWEhtbS0lJSVUVlZSVlZGuLzS0lJqamooKiqisbGRgoKC48oIP2/dupW6ujqKi4tJq69iQM0u+taW07e2nAE1u0irr2Lw+8V0P1rHmQe2AvChfXnHPWdWFNCtqZGig9nUNAyhtHoa+4+cS+jwOMoOXURl3VmUVE2ntnEAhZVX0OS6kb//Wl+P/V/w+7T/Wpq6QeGC0dQOSqPkshFUnptB2bShhCYNYv/5AyiddSY1w9MpunoUjWndKLhxjC9j8fkA9Nt+OQB9imdg9b1J3zmF7jWDSQtl0bNiFD0rRpEWyqJ7zWDSd07B6nvTp3jGcXmHDNsOwKAh72DWyICB79Gj52H6ZZSRll5J7z776NN3L73SqsgYsJvu3Y9wxqCSk6adGpt6JddON5/Xqe0Ubp+u3k6D3z+J2ynGsVdVVcWuXbsoLy+nvLycXbt2UVVVRXFxMXV1dWzdujXpduqo8173o8m1U0HFvJO+nZqXUVBQQGNjI0VFRdTU1FBaWtqpn09nHujkdmrnc/mp0k7aJ+2T9qlj9ikWO77jpv2Z2TXAfwDznXMvR6S/Daxxzq2MSFsPlDjnlpjZSmC0c+6zEcu/CVzvnJsca5tTp051mzdvTvWutEnSv77uxiZXwIw5SWVfXbYlqfzVj61vc96OHFKUTDudzm0EHddOnfpeSrKNkp1k4GQZnndSn+9Ok4kgOr2NJhYnl19EJIXMLM85NzXasg7taTKzL+EDpqsiA6ZAATA5Yl0DJgbp4eWTmuWZFLFcREREREQk5TpyyvFv4KcTv9w591aUVR4Dfm9mucBrwDeAdODZYPmzwANmdiewCvgkfnKI7Pauu4hIKq2uviTJEpLrDRQREZHEdFjQhA90GoGXfSeS55zrFzz/r5l9DR88hX+n6UrnXFWw/KCZXQn8BPg+/neaFjvnNHOeiIiIiIi0m46cctziWOdJ4MkYy98CPpbKeomIiIiIiMTSmVOOi4iIiIiIdHkdOTxPRERERDrS25rhUCQV1NMkIiIiIiISg4ImERERERGRGBIanmdmQwGcc/uC/ycA1wLbnXNPpb56IiIiJ5+T5QeIRUQkPon2NP0KuArAzIYArwJXA4+Y2R0prpuIiIiIiEinSzRo+gjwRvD354B3nXPjgRuAr6ayYiIiIiIiIl1BokFTb6Am+PtS4L+Cv/OBs1JVKRERERERka4i0aCpGJhnZmcBlwEbgvThwMFUVkxERERERKQrSDRo+hdgOVAKvOGcezNIvxzYksJ6iYiIiIiIdAkJzZ7nnPuNmY0CRgAFEYteBJ5JZcVERERERES6goR6mszse0C1c26Lc64pYtGfgQUprZmIiIiIiEgXkOjwvHuAflHS+wTLRERERERETimJBk0GuCjpk4ADyVdHRERERESka4nrniYzq8YHSw7YYWaRgVN3IB14JPXVExERERER6VzxTgRxK76XaTXwbeD9iGX1QKlz7vUU101ERERERKTTxRU0OedyAczsPeCPzrmGdq2ViIiIiIhIF5HolOP/A2BmI4BhNLsnyjmXn7qqiYiIiIiIdL6EgiYzmwT8DLgAP1wvksPf3yQiIiIiInLKSChoAh4FdgNfAf5G9Jn0REREREREThmJBk3jgEnOub+2R2VERES6gtXVlyRZwvqU1ENERLqGRIOmrcCZgIImERERSU7/O5LLX7UiNfUQEWlFoj9uezfwgJldambDzWxQ5KM9KigiIiIiItKZEu1pejF43sDx9zMZmghCRERE5NSi3kARIPGgaVa71EJERERERKSLatPvNImIiIiIiJwuWg2azGwy8LZzrin4u0X6cVsRERHpKMnMcvjljJdSWBMROdXF09O0GT9jXnnwt+PEH7YF3dMkIiIiIhGSnb5fwa10FfEETecA+yL+FhEREREROW20GjQ553ZG+1tERETkZLXqx9VJ5b9tSUaKaiKSJM1w2CESnT0PMxsO/B9gHH5IXiHwkHNub4rrJiIiIiIi0ukS+nFbM/sE8C7wT0AtcAS4Dig2s4tTXz0REREREZHOlWhP04+Ap4DFzrkmADPrBjwCrAD+IbXVExERERER6VyJBk0TgRvDARNAMBX5j4EtKa2ZiIiIiIhIF5DQ8DzgfaLPoHcOcDD56oiIiIiIiHQtifY0/QJ43MzuAv6InwhiOrAMP2xPRERERETklJJo0HRX8Lw6Im8D8DCQk6pKiYiIiIiIdBVxBU1m1gf4IfBZoCewDngQP1zvXefc4XaroYiIiIiISCeK956mfwFuBP4bPwzvEuAbzrk/JxIwmdnnzew1M6sys8Zmy240syYzq4l4PNVsnalm9iczO2xmJWb2xXi3LSIiIiIi0hbxDs+bByxyzv0CwMx+Dmwys+7OuaMJbK8SeAjoDTwaZfkO59yYaBnNbADwPH7a808CM4BnzazEOfd6AnUQERERERGJW7xB01nAa+F/nHN/CnqKRgC7492Yc+4PAGY2M4E6hs3D/6DuA845B7xgZs8CNwMKmkREROSUtLSg7XnvTl01RE5r8Q7P6w7UN0trJPGJJFpzlpn93cx2m9kvzCxyevOLgPwgYArLD9JPYGY3m9lmM9scCoXYv38/oVCIsrIyKisrKSkpoba2lsLCQpqamsjPzwcgLy/PF5yfT1NTE4WFhdTW1lJSUkJlZSVlZWWEyystLaWmpoaioiIaGxspKCg4rozw89atW6mrq6O4uJi0+ioG1Oyib205fWvLGVCzi7T6Kga/X0z3o3WceWArAB/al3fcc2ZFAd2aGik6mE1NwxBKq6ex/8i5hA6Po+zQRVTWnUVJ1XRqGwdQWHkFTa4b+fuv9fXY/wW/T/uvpakbFC4YTe2gNEouG0HluRmUTRtKaNIg9p8/gNJZZ1IzPJ2iq0fRmNaNght9x1/e4vMB6Lf9cgD6FM/A6nuTvnMK3WsGkxbKomfFKHpWjCItlEX3msGk75yC1femT/GM4/IOGbYdgEFD3sGskQED36NHz8P0yygjLb2S3n320afvXnqlVZExYDfdux/hjEElJ007NTb1Sq6dbj6vU9sp3D5dvZ0Gv3/ytlO4fTqrnTrqvNf9aHLtVFAx76Rtp4GDi5Nqp476fDrzQCe301fP77R26tatPql26sjriGTaKfxe6Kx26vvOrKTaqa6ujq1bt0Z9XQoKCmhsbKSoqIiamhpKS0u7zPVeVVUVu3btory8nPLycnbt2kVVVRXFxcWp36ebz0uunbriPnVSO8Vix8cgLaxk1gS8ANRFJF8B/A9w7J4m59ycVgvjWE/Ti865HhFp5+KDsHeBYfhpzKcDFznnDpnZ40AP59zCiDxfAr7d0pC+sKlTp7rNmzfHU7V2l8y3RQB3u7HJFTAjriZq0eqy5H7DuPqx9W3Oe9uSjKS2nYikvtU7jdsIOq6dOvW9pDaKy8l8vlMbxedkPt+dLG0Ep/dn0pczXkoq/2mh/x3J5a9akZp6nALMLM85NzXasnh7inKjpP2s7VU6kXNuR8S/fzezr+Bn5/s4sBGoBkY3y3YGUJXKeoiIiIiIiESKK2hyzn2pvSsSbbPBw4L/C4Crm60zKUgXERERkVPMqh9XtzlvR/YGyqkv3nuaUsLMuptZOtAr+D89eJiZfdrMRgZ/DwJ+AuwH3giyPwv0MbM7zayXmc3GTw4RbRY+ERERERGRlOjQoAm4Hj8D3h/wk0vUBo+zgZnAn4AaYDswGMh2ztUAOOcOAlcC1+CH7T0GLNZ04yIiIiIi0p5SPftdTM65NcCaFhbfGTxi5X8L+FhqayUiIiIiItKyDg2aRERERETk1JHMfWdw8tx71tHD80RERERERE4qCppERERERERiUNAkIiIiIiISg4ImERERERGRGBQ0iYiIiIiIxKCgSUREREREJAYFTSIiIiIiIjHod5pERERERE5Tq6svSbKE9SmpR1enniYREREREZEY1NMkIiIiIpKEpQXJ5b/7otTUQ9qPeppERERERERiUNAkIiIiIiISg4ImERERERGRGBQ0iYiIiIiIxKCgSUREREREJAYFTSIiIiIiIjEoaBIREREREYlBQZOIiIiIiEgMCppERERERERiUNAkIiIiIiISg4ImERERERGRGBQ0iYiIiIiIxKCgSUREREREJAYFTSIiIiIiIjEoaBIREREREYmhR2dXQERERETktPb22CQyz0lZNaRl6mkSERERERGJQUGTiIiIiIhIDAqaREREREREYlDQJCIiIiIiEoOCJhERERERkRgUNImIiIiIiMSgoElERERERCQGBU0iIiIiIiIxKGgSERERERGJQUGTiIiIiIhIDAqaREREREREYujQoMnMPm9mr5lZlZk1Rll+g5mVmNlhM3vTzKY0Wz7VzP4ULC8xsy92XO1FREREROR01NE9TZXAQ8DtzReY2XTgYeAWYCDwDPCcmfUPlg8Ang/SBwKLgUfM7OKOqbqIiIiIiJyOOjRocs79wTn3FLAjyuKvAL9xzm1wztUBPwTqgKuD5fOAWuAB51ydc+4F4Fng5g6ouoiIiIiInKa60j1NFwF54X+ccw7YEqSHl+cH6WH5EcuPY2Y3m9lmM9scCoXYv38/oVCIsrIyKisrKSkpoba2lsLCQpqamsjPzwcgL89XIT8/n6amJgoLC6mtraWkpITKykrKysoIl1daWkpNTQ1FRUU0NjZSUFBwXBnh561bt1JXV0dxcTFp9VUMqNlF39py+taWM6BmF2n1VQx+v5juR+s488BWAD60L++458yKAro1NVJ0MJuahiGUVk9j/5FzCR0eR9mhi6isO4uSqunUNg6gsPIKmlw38vdf6+ux/wt+n/ZfS1M3KFwwmtpBaZRcNoLKczMomzaU0KRB7D9/AKWzzqRmeDpFV4+iMa0bBTeO8WUsPh+AftsvB6BP8QysvjfpO6fQvWYwaaEselaMomfFKNJCWXSvGUz6zilYfW/6FM84Lu+QYdsBGDTkHcwaGTDwPXr0PEy/jDLS0ivp3WcfffrupVdaFRkDdtO9+xHOGFRy0rRTY1Ov5Nrp5vM6tZ3C7dPV22nw+ydvO4Xbp7PaqaPOe92PJtdOBRXzTtp2Gji4OKl26qjPpzMPdHI7ffX8Tmunbt3qk2qnjryOSKadwu+Fzmqnvu/M6rR26ujrvU5rp5vPS6qdaOyZVDv1P2PnSdVOkdd7VVVV7Nq1i/LycsrLy4nFjo9BOoaZzQRedM71iEgrAX7gnHsiIi0XaHDO3WRmjwM9nHMLI5Z/Cfi2c25MrO1NnTrVbd68OdW70SZLC5LLf7cbm1wBM+YklX112Zak8lc/tr7NeW9bkpHUthORTDudzm0EHddOnfpeUhvF5WQ+36mN4nMyn+9OljYCfSa11cnSRqDPpK7CzPKcc1OjLetKPU3VwIBmaWcAVXEuFxERERERSbmuFDQVAJPD/5iZAROD9PDySc3yTIpYLiIiIiIiknIdPeV4dzNLB3oF/6cHDwMeA+aZ2Wwz6wXcAaTjJ3sgeO5jZneaWS8zm42fHOLRjtwHEfn/7d179B1lfe/x9ycBwj1IAKkiIF6o2CUWUI9H1ChqhXoFFXu8FLssUDxq0dZaPaelF7QctOo5igoqEdTT46Uutd4Bb2i9QCwiKYiBcImBEAgJgRAI+Z4/5vnBZpsMIfld9i95v9aatffMM8/Ms+e7Z+/9nWdmtiRJ0tZlsnuaXkN3B7xvAjPb89XAflV1IXASXfK0AngFcFRVrQSoqluBo4CXt/KzgBOr6t8n+TVIkiRJ2ops88CzjJ+qmgfM6yk/Bzinp/xnwJPHvWGSJEmStAGjdE2TJEmSJI0ckyZJkiRJ6mHSJEmSJEk9TJokSZIkqYdJkyRJkiT1MGmSJEmSpB4mTZIkSZLUw6RJkiRJknqYNEmSJElSD5MmSZIkSeph0iRJkiRJPUyaJEmSJKmHSZMkSZIk9TBpkiRJkqQeJk2SJEmS1MOkSZIkSZJ6mDRJkiRJUg+TJkmSJEnqYdIkSZIkST1MmiRJkiSph0mTJEmSJPUwaZIkSZKkHiZNkiRJktTDpEmSJEmSepg0SZIkSVIPkyZJkiRJ6mHSJEmSJEk9TJokSZIkqYdJkyRJkiT1MGmSJEmSpB4mTZIkSZLUw6RJkiRJknqYNEmSJElSD5MmSZIkSeph0iRJkiRJPUyaJEmSJKmHSZMkSZIk9TBpkiRJkqQeI5M0laTkMAAAFFFJREFUJZmX5O4kqwaGk4bmeW2ShUnuSPKTJIdOVXslSZIkbR1GJmlqPllVOw8MZ4wVJDkc+DDwZ8BDgC8AX0uy6xS1VZIkSdJWYNSSpj5/CvxrVX2rqtYApwNrgJdObbMkSZIkbclGLWk6JsktSX6V5PQkOw+UHQxcPDZSVQX8vE3/LUmOT3JRkouWLFnCsmXLWLJkCYsXL2b58uUsXLiQ1atXs2DBAtatW8f8+fMBuPjibhXz589n3bp1LFiwgNWrV7Nw4UKWL1/O4sWLGVveokWLWLVqFZdffjlr167lkksuud8yxh4vvfRS1qxZw5VXXsmsu1Yye9W17LR6KTutXsrsVdcy666VzFlxJTPvWcPet1wKwMNvuvh+j79z8yXMWLeWy299Lqvu3oNFtz2FZXcewJI7DmLx7QezfM0jWLjycFavnc2C5UeyrmYwf9mxXTuW/VH3mpYdy7oZsOAV+7N691ksfN7DWH7ALix+yp4s+f3dWXbgbBY9a29WPXR7Ln/pvqydNYNLjnt0t4wTDwRg58v+AIAdr3wGuWsHtr/mUGaumsOsJY9j25v3Zdub92XWkscxc9Uctr/mUHLXDux45TPuV3ePvS4DYPc9riBZy+yHXM02297BzrssZtb2y9lhx5vYcacb2W7WSnaZfR0zZ97JbrsvnDZxWrtuu82L0/GPndI4jcVn1OM0Z8X0jdNYfKYqTpP1uTfzns2L0yU3Hz1t4/SQOVduVpwm6/tp71umOE4nHDhlcZox467NitNk/o7YnDiN7QtTFaedrnjWlMVpsn/vTVmcjn/sZsWJtdtuVpx23e2aaRWnwd97K1eu5Nprr2Xp0qUsXbqUPulyj6nXrk+6HrgJeBxwNrCwqv6olS8E/rGqzh6o80ng7qp6fd+yDzvssLrooosmrO0Pxrsu2bz676jHbN4CnvGizar+icU/36z6t531pU2u++a37LJZ634wNidOW3OMYPLiNKX7kjHaKNP5884YbZzp/Hk3XWIEfidtqukSI/A7aVQkubiqDltf2cj0NFXVxVV1Y1Wtq6rLgJOBlyWZ1Wa5DZg9VG03YOVktlOSJEnS1mVkkqb1WNce0x4vAQ4ZK0wS4IltuiRJkiRNiJFJmpK8Mslu7fljgPcCX66qO9ssZwFHJzkiyXbAW4HtgS9OSYMlSZIkbRVGJmkCTgSuSnI78C3gx8Drxgqr6kLgJLrkaQXwCuCoqvL0PEmSJEkTZpupbsCYqpq7EfOcA5wz8a2RJEmSpM4o9TRJkiRJ0sgxaZIkSZKkHiZNkiRJktTDpEmSJEmSepg0SZIkSVIPkyZJkiRJ6mHSJEmSJEk9TJokSZIkqYdJkyRJkiT1MGmSJEmSpB4mTZIkSZLUw6RJkiRJknqYNEmSJElSD5MmSZIkSeph0iRJkiRJPUyaJEmSJKmHSZMkSZIk9TBpkiRJkqQeJk2SJEmS1MOkSZIkSZJ6mDRJkiRJUg+TJkmSJEnqYdIkSZIkST1MmiRJkiSph0mTJEmSJPUwaZIkSZKkHiZNkiRJktTDpEmSJEmSepg0SZIkSVIPkyZJkiRJ6mHSJEmSJEk9TJokSZIkqYdJkyRJkiT1MGmSJEmSpB4mTZIkSZLUw6RJkiRJknqYNEmSJElSj2mXNCWZmeT0JDcluS3JF5LsMdXtkiRJkrRlmnZJE/B24MXAU4B92rRzp645kiRJkrZk20x1AzbB8cDfV9VVAEneBvw6yf5VtWhKWyZJkiRpizOtepqSzAb2BS4em1ZVC4GVwBOmql2SJEmStlypqqluw0ZL8gjgWuCAqrp6YPo1wDur6lMD046n65UCOBC4YjLbOo3tASyb6kaolzEafcZoejBOo88YjT5jNPqM0cbbr6r2XF/BdDs977b2OHto+m50vU33qqozgTMno1FbkiQXVdVhU90ObZgxGn3GaHowTqPPGI0+YzT6jNH4mFan51XVrXQ9TYeMTUtyALAr8IupapckSZKkLde0SpqaM4G/SvLIJLsCpwHf9CYQkiRJkibCdDs9D+CfgIcAPwNmAd8GXj2lLdqyeErj6DNGo88YTQ/GafQZo9FnjEafMRoH0+pGEJIkSZI02abj6XmSJEmSNGlMmrYCSfZNsirJw6a6LdqwJB9LMm8z6leSw8exSRqQ5Lwkp2xi3f1bfPYZ52ZttZIcl+TX47xM96FxZIymB+M0+ozRaDBpmoaSvHl450nyprYDPH9g2g5J7gQOrqqdq+o3k97YLVSS05JclmRlkt8kOSvJ7hO8zkVJ7mwJ8PIkP0wydyLXuSVIcmqSq1uslib5fJJ9J2A9leSOFp9lSb6V5ODxXs+WLMmMJD8aTjCTnJLkvHFYvvvQJkoyL8ndbduNDScNlBujEZHkOUl+PPBZdMZAmXGaYu23w+B+tLp95h3Syo3RiDJpmp7OAx6VZL+Bac8GLgOOGJj2NGAm8N3Ja9r6Jdl2qtswzu6huwHJHOBgYB/g7ElY7+uramfgYcDFwFeSDP9vme7vXOCJVbUrsD/d3xb8y4Zm3sz36vNafB4FrAC+shnL2hqdDNwxwetwH9p0n2wH4MaGMx64yiYxRpuo/Sj+PPAeuu+nfYCPTdDqjNMmqKrHD+5HwD8DC6pq/gSszhiNI5OmaaiqLgOW0BKkJDOBZwKncP+k6Qjgp8CcwSO37SjG+Une1Y68L03yd2OVksxNsjbJsUkWJlmR5LNJdhmYZ06Sjye5LslNrfyhA+WLkvxNku8kuR04ZuK2yOSrqndU1c+r6u6qugn4IDB3rLwdlT239UDdmmRxkhMGl5HkT9r2XZnkXGD7B7H+1XR3w9kZePRweZJ9knyjxWZFkh8kOXRonqOTXNTKb0hy6kDZ05NcmOSW1sa3JsnGtm+UVNXlVbWijQZYBxw4Vt5i9ekkZye5Bfjf6fx1kuvbNnhfq7ux61wBfBJ4RJI5w+VJDk7yvXYUeHmSryd51EB5khyf5NL2/rguyRsGyl+S5OL23vrPJK960BtmxCR5LHAS8BdD048F3gHMHTgye8BA+ZtanJYn+Wj7PHxA7kPjxxiNlHcDH6mqz1fVmqq6c+zHuHEaPUm2Af4E+GgbN0ajrKocpuEAfAr4dHv+ZOA/gW3pjm7PadN/Cvwd3dH1AvZp008B7gZOpLvt/FPa+NNa+dw2/8fpdrCHAlcC72zlAX5Ad/RqNrBjm/f8gfYtAq4Dfr/Nv8NUb7MJjsc/Az8YGJ8HrAZeRHdw4ui2jfdr5U9v5c9tMXhtK5/Xs45FwKvb852A/wPcCuzSphVweHu+b1v3jsAOwAeAa4BtW/mRwG3AC9r6dx2o+/hW9mK6nsrfBa4GXjvV23kz4vPf2r5RbTu/cShWdwHHtte7I/AaYClwKLAd8M5W75SedQxu/4fQHe29qo0P74NPAJ5F97cJs4HPAf8+sKw/A34DHN7eP3sAT25lzwVubu+hGXT7/3LgGVO9nTcjPjOAC9t+cr9t1cpPAc4bqnNci8mpbTs+GrgFeJX70ITEaF57n90C/Ao4HdjZGI3O0LbXPS0W84FldGeaHGacRnMAXkbXu76bMRr9Ycob4LCJget2oCXt+V8DH2rPv952wtnAWrofVvvz20nTZUPL+xnw5vZ8bpt/z4Hy04EvtueHtZ181kD5nKF1LAL+Zqq30yTF4pj2gXHIwLR5wFeH5rsJeHF7fhZw7lD5D3ngpOn29qF3I3A+LdFt5fd+AK6n7i6t/KA2/jXg9A3M+0HgE0PT3srQh/h0HIC96RKguUOxumBovm8D/zAwPoPuIMApPcuu9j64lS7h+TLw+FZ2v31wPXV/r5Xv1MYXAG/YwLz/Nrxv0X0Zfmyqt+9mxOVk4PMb2lZs+EfESmDmwLTPAe/rWY/70KbH6FC6A2gz6H4k/RT4v8ZodAa6U/EKWEx3YGY7ul6LpbQf5cZptAa675qzh6YZoxEdpuOf26pzPrB3koPormf6SJv+nTZ+N11Pxo+Bh6+n/pKh8dvpdpIx91R32tn6yh9Jd6TjxqHe1zvpjlZc38YXbfzLmZ6SvJyuW/1F9dvnI/dt432Ai4bKr96IVZ5QVZ/aiHbtQdf7NRfYje6UNIA92+P+wBc3UP2RwLOTHD0wbSxpmNaq6oYkZwFXJdm3qm5pRYuGZt1ncFpVrUtyzUas4siquvCBZkp3Kt7pdL28Y19O0PUo3U4Xn19toPojgWclecvAtJl0vb/TTpJH033BHrYJ1ZdW1T0D48OfY+vjPrQJqurigdHLkpwMfDfJcVW1pqeqMZo8t7XHs6vqFwBJ3g38JfBf6X74bohxmmTte+AI4KkbWcUYTTGvaZqmquo6uh9Vf0i3w323FV1AtxMeAXy/qu6egNVfQ7ez7l5Vuw0MO1TVjwbmW7eB+luEJK+jS5heWFXfeZDVF9N9CA165Hi0q3k38DvAU6q7AcIj2vSxLHcR8JgN1L2G7qjRYGx3rarHj2P7ptI2dKcqDN6Cf/i9er/4tHOz9xvHNnyE7gfOE1p8nja2qva4iP74nDIUn12q6qhxbN9kOpzui/mXSZbRnVYE8Ivcd3e2qfgscR/qNxaTDI1PJmM0oLprKRdx30GY+xW3R+M0Ok4ALqmqnwxNN0YjyqRpejsfeAtwZVXd3KbNB/YCXk53l72JcBHwH8AH0i5yT7JnkldO0PpGTpI30d2d6A+q6oebsIhzgJclOSLJNkleTXdtynjZle4UyuVJdgZOGyr/EHBikiPb+ndNMvbD/QzglUlemGTbVn5QkmeOY/smRbpbWP/3JHu18X3oXvsi4PKequcCxyc5JN3d9N5Od2rfeNmVdtpEO8L390PlHwLekeSp7TXskeRJrez9wJ+3C29nJtkuyaFJNqWnZhR8lu5ug09sw1jy9zy6/QTgBmDfJNtNYrvchwYkeWWS3drzxwDvBb5cVXe2WYzRaDgDeF17LdvQ9TLdCYwd0DROI6Bt/+O47yyhQcZoRJk0TW/n0f2Qu2BsQlWtA77fpk9I0tTW8RK698/FSW4DfsLA3eO2Ah+g+5D5Tgb+b2FjK1fV94E30t1M4xbg+cD/G8f2/S1d8nwz8Au6L8x7u/Wr6qvA64F3tfVf0dpAVf2S7mLPP6c7xXAp3XU/ezI9HUXXi3E73fv0DuA5VbW2p845dNcJfYXuXPC96Par8XIy3fWGK+lOq/u3ofIz6I78fZzuBhbzgScBVNW3gOPpTu9bRhej99HdtGXaqao7qur6sYHuBwPADVU1tk99ju5UjxvS3TFwPHtlN8R96P5OpDut9XbgW3Snfr9uoNwYjYb3AJ+g+12wjO4C/iPrvjuIGqfRcDTdDRc+vZ4yYzSiUrW+XlxJkiRJEtjTJEmSJEm9TJokSZIkqYdJkyRJkiT1MGmSJEmSpB4mTZIkSZLUw6RJkiRJknqYNEmSJl2S/ZPUNP5TXknSVsSkSZI0IZLMa4lRJbk7yVVJ3pNkp6lu22RLMrdthz2mui2SpAdvm6lugCRpi3Ye8BpgW+DpwMeAnYDTprJRkiQ9GPY0SZIm0pqquqGqrquqzwCfBl4yPFOSmUk+nuTqJKuTXJnkbUlmDM33x0kuTbImyY1J5g2UzU5yZpKlSW5L8r3B0/+SHJdkVZIjk1ye5I4kX271XtbWuSLJuUl2GKiX1paFrW2XJnn1QPnYqYbHJPl2W+6CJM8dKwe+02a/qc07r5U9I8mPW7tWJPlJkt/b/M0uSRpP9jRJkibTarpep2EzgMXAK4CbgCcDZwI3Ax8HSHIC8AHgHcBXgZ2BZ7eytGkrgBcAtwB/DFyQ5MCqWtLWMwt4K/AqYDvgC8DngTuBY4A5wL8CJwHvbXX+EXgZ8AbgCuCpwFlJllfVVwdew6nAX7a6/wP4lyT7Ade1ZX8BeHxr2+ok2wBfaq/vVW27HALcs5HbUpI0SVJVU90GSdIWqPWm7FFVL2jjTwa+BpwP/BVwNfCkqrpoA/X/CTisqp7Txq8HPlVVb1/PvM8GvgzsWVWrB6b/B/CZqvpfSY4DzgZ+t6quaOXvAU4GHlpVy4bb3a6/WgY8r6p+MLDc9wOPraqjWk/S1cCJVfXRVv5w4Hrg6VV1YZK5dL1New6sZ3e6pHBuVX1vozesJGnS2dMkSZpIz0+yiu77Zlu6npU3AjsOz5jkROD1wH7ADm3+a1rZXsDD6RKu9Tm0LfOmrtPpXtsDjxoYXzOWMDU3AjeMJTID0w5qzw9qy/hGksGjjNsCi4ba8IuB579pj3ttoL1U1S0tQftmkvPpXtvnquq6DdWRJE0NkyZJ0kT6PnA8cDfwm6q6G+69zudeSY4F3g/8BfAjYCXd6XAvHZvlAdYzgy7Zefp6ylYOPF87VFatbcPTxq6lGnt8IXDt0HzD9e4dr6pqyVvvtcNV9brWa/V84EXAqUleUlXf7KsnSZpcJk2SpIl0R1X9eiPmOxz4SVV9cGxCknt7iKrqxiSLgSOAb6+n/nzgocC6qrpqM9s8aAGwBtivqi7YjOXc1R5nDhdU1SXAJcBpSb5Ody2WSZMkjRCTJknSKPgVcFySI4FfA68EngksH5jnVOB9SW6ku+nDjsARVfVeulub/xD4UpK3AZcDe9P14Jw3eD3Sg1FVt7Xrnt7TbjbxfbobUPwXugTtzI1c1DV0PVh/mOQrdDfE2BM4ge5arMXAAcATgA9vSlslSRPHW45LkkbBR4HPAp8Bfgbsz313rwOgqj5Md8renwK/BL5Bdzc6qrur0VHABcBZdHe5+yxwIPddX7Sp/idwCt2pg5fR9XQdQ3fzh41SVYuBv6VL/G4EPgjcATwW+Bxd0vhJuluy+x9WkjRivHueJEmSJPWwp0mSJEmSepg0SZIkSVIPkyZJkiRJ6mHSJEmSJEk9TJokSZIkqYdJkyRJkiT1MGmSJEmSpB4mTZIkSZLUw6RJkiRJknr8f0KZPGKvlys1AAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<Figure size 1008x432 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "pos = np.array(range(7))\n",
    "plt.figure(figsize=(14,6))\n",
    "plt.bar(pos-0.3, coty_win_nom.iloc[0,range(1,14,2)], width=0.15, label='2020', color='#85d0ff')\n",
    "plt.bar(pos-0.15, coty_win_nom.iloc[1,range(1,14,2)], width=0.15, label='2019', color='#ffcf24')\n",
    "plt.bar(pos, coty_win_nom.iloc[2,range(1,14,2)], width=0.15, label='2018', color='#ff0d72')\n",
    "plt.bar(pos+0.15, coty_win_nom.iloc[3,range(1,14,2)], width=0.15, label='2017', color='#9df241')\n",
    "plt.bar(pos+0.3, coty_win_nom.iloc[4,range(1,14,2)], width=0.15, label='2016', color='#908df2')\n",
    "plt.title('Car of the Year - All Placements & Points (Last 5 Years)',fontsize=18)\n",
    "plt.xlabel('Placements',fontsize=14)\n",
    "plt.ylabel('Points',fontsize=14)\n",
    "plt.xticks(range(7),['Winner','2nd Place','3rd Place','4th Place','5th Place','6th Place','7th Place'],fontsize=13)\n",
    "plt.yticks(fontsize=13)\n",
    "plt.grid(axis='y', linestyle=':')\n",
    "plt.legend()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### That's it, everyone! We've come to end of the analyses of Car of the Year.\n",
    "\n",
    "### Thank you for joining me; hope you learned many things from these outcomes and visualizations!"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.8.3"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 4
}