Final_Project.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "0bd05035",
   "metadata": {},
   "source": [
    "# Comparing Covid-19 Data"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "55981141",
   "metadata": {},
   "source": [
    "## Data source"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "89c99f21",
   "metadata": {},
   "source": [
    "This data is provided by the European Centre for Disease Prevention and Control https://www.ecdc.europa.eu/en/publications- data/download-todays-data-geographic-distribution-covid-19-cases-worldwide"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "11c4150c",
   "metadata": {},
   "source": [
    "![logojmu](https://jmusports.com/images/2020/7/7/JMU.png?width=2000)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "597a4399",
   "metadata": {},
   "source": [
    "By Hayden Knight and Rudolph Mallamas"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "20784175",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Looking in indexes: https://pypi.org/simple, https://pip.repos.neuron.amazonaws.com\r\n",
      "Requirement already satisfied: xlrd in /home/ec2-user/anaconda3/envs/python3/lib/python3.10/site-packages (2.0.1)\r\n"
     ]
    }
   ],
   "source": [
    "%matplotlib inline\n",
    "import pandas as pd\n",
    "!pip install xlrd"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "063e5f3d",
   "metadata": {},
   "source": [
    "# Data Synopsis"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "c351910e",
   "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>dateRep</th>\n",
       "      <th>day</th>\n",
       "      <th>month</th>\n",
       "      <th>year</th>\n",
       "      <th>cases</th>\n",
       "      <th>deaths</th>\n",
       "      <th>countriesAndTerritories</th>\n",
       "      <th>geoId</th>\n",
       "      <th>countryterritoryCode</th>\n",
       "      <th>popData2019</th>\n",
       "      <th>continentExp</th>\n",
       "      <th>Cumulative_number_for_14_days_of_COVID-19_cases_per_100000</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>14/12/2020</td>\n",
       "      <td>14</td>\n",
       "      <td>12</td>\n",
       "      <td>2020</td>\n",
       "      <td>746</td>\n",
       "      <td>6</td>\n",
       "      <td>Afghanistan</td>\n",
       "      <td>AF</td>\n",
       "      <td>AFG</td>\n",
       "      <td>38041757.0</td>\n",
       "      <td>Asia</td>\n",
       "      <td>9.013779</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>13/12/2020</td>\n",
       "      <td>13</td>\n",
       "      <td>12</td>\n",
       "      <td>2020</td>\n",
       "      <td>298</td>\n",
       "      <td>9</td>\n",
       "      <td>Afghanistan</td>\n",
       "      <td>AF</td>\n",
       "      <td>AFG</td>\n",
       "      <td>38041757.0</td>\n",
       "      <td>Asia</td>\n",
       "      <td>7.052776</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2020-12-12 00:00:00</td>\n",
       "      <td>12</td>\n",
       "      <td>12</td>\n",
       "      <td>2020</td>\n",
       "      <td>113</td>\n",
       "      <td>11</td>\n",
       "      <td>Afghanistan</td>\n",
       "      <td>AF</td>\n",
       "      <td>AFG</td>\n",
       "      <td>38041757.0</td>\n",
       "      <td>Asia</td>\n",
       "      <td>6.868768</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2020-11-12 00:00:00</td>\n",
       "      <td>11</td>\n",
       "      <td>12</td>\n",
       "      <td>2020</td>\n",
       "      <td>63</td>\n",
       "      <td>10</td>\n",
       "      <td>Afghanistan</td>\n",
       "      <td>AF</td>\n",
       "      <td>AFG</td>\n",
       "      <td>38041757.0</td>\n",
       "      <td>Asia</td>\n",
       "      <td>7.134266</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2020-10-12 00:00:00</td>\n",
       "      <td>10</td>\n",
       "      <td>12</td>\n",
       "      <td>2020</td>\n",
       "      <td>202</td>\n",
       "      <td>16</td>\n",
       "      <td>Afghanistan</td>\n",
       "      <td>AF</td>\n",
       "      <td>AFG</td>\n",
       "      <td>38041757.0</td>\n",
       "      <td>Asia</td>\n",
       "      <td>6.968658</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "               dateRep  day  month  year  cases  deaths  \\\n",
       "0           14/12/2020   14     12  2020    746       6   \n",
       "1           13/12/2020   13     12  2020    298       9   \n",
       "2  2020-12-12 00:00:00   12     12  2020    113      11   \n",
       "3  2020-11-12 00:00:00   11     12  2020     63      10   \n",
       "4  2020-10-12 00:00:00   10     12  2020    202      16   \n",
       "\n",
       "  countriesAndTerritories geoId countryterritoryCode  popData2019  \\\n",
       "0             Afghanistan    AF                  AFG   38041757.0   \n",
       "1             Afghanistan    AF                  AFG   38041757.0   \n",
       "2             Afghanistan    AF                  AFG   38041757.0   \n",
       "3             Afghanistan    AF                  AFG   38041757.0   \n",
       "4             Afghanistan    AF                  AFG   38041757.0   \n",
       "\n",
       "  continentExp  Cumulative_number_for_14_days_of_COVID-19_cases_per_100000  \n",
       "0         Asia                                           9.013779           \n",
       "1         Asia                                           7.052776           \n",
       "2         Asia                                           6.868768           \n",
       "3         Asia                                           7.134266           \n",
       "4         Asia                                           6.968658           "
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df = pd.read_excel('s3://ia-241-mallamas/covid_data.xls')\n",
    "df.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "e07c836d",
   "metadata": {},
   "source": [
    "# 1. Which Country has the highest number of cases?"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "5ebb9223",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot: xlabel='countriesAndTerritories'>"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sum_case_by_country = df.groupby('countriesAndTerritories')['cases'].sum()\n",
    "sum_case_by_country.nlargest(10).plot.bar()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "1f2b26b8",
   "metadata": {},
   "source": [
    "# Explanation\n",
    "\n",
    "This data illustrates the top 10 countries in the world that experience the most COVID-19 cases in a bar chart per 50,000 cases. The data shows the United States having the largest COVID-19 cases compared to the top 9 countries. This information can help in the future to provide examples of proper protocols for pandemics to lower cases."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "d1c4391d",
   "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>dateRep</th>\n",
       "      <th>day</th>\n",
       "      <th>month</th>\n",
       "      <th>year</th>\n",
       "      <th>cases</th>\n",
       "      <th>deaths</th>\n",
       "      <th>countriesAndTerritories</th>\n",
       "      <th>geoId</th>\n",
       "      <th>countryterritoryCode</th>\n",
       "      <th>popData2019</th>\n",
       "      <th>continentExp</th>\n",
       "      <th>Cumulative_number_for_14_days_of_COVID-19_cases_per_100000</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>59001</th>\n",
       "      <td>14/12/2020</td>\n",
       "      <td>14</td>\n",
       "      <td>12</td>\n",
       "      <td>2020</td>\n",
       "      <td>189723</td>\n",
       "      <td>1340</td>\n",
       "      <td>United_States_of_America</td>\n",
       "      <td>US</td>\n",
       "      <td>USA</td>\n",
       "      <td>329064917.0</td>\n",
       "      <td>America</td>\n",
       "      <td>873.211592</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>59002</th>\n",
       "      <td>13/12/2020</td>\n",
       "      <td>13</td>\n",
       "      <td>12</td>\n",
       "      <td>2020</td>\n",
       "      <td>216017</td>\n",
       "      <td>2315</td>\n",
       "      <td>United_States_of_America</td>\n",
       "      <td>US</td>\n",
       "      <td>USA</td>\n",
       "      <td>329064917.0</td>\n",
       "      <td>America</td>\n",
       "      <td>857.089241</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>59003</th>\n",
       "      <td>2020-12-12 00:00:00</td>\n",
       "      <td>12</td>\n",
       "      <td>12</td>\n",
       "      <td>2020</td>\n",
       "      <td>234633</td>\n",
       "      <td>3343</td>\n",
       "      <td>United_States_of_America</td>\n",
       "      <td>US</td>\n",
       "      <td>USA</td>\n",
       "      <td>329064917.0</td>\n",
       "      <td>America</td>\n",
       "      <td>838.514183</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>59004</th>\n",
       "      <td>2020-11-12 00:00:00</td>\n",
       "      <td>11</td>\n",
       "      <td>12</td>\n",
       "      <td>2020</td>\n",
       "      <td>224680</td>\n",
       "      <td>2748</td>\n",
       "      <td>United_States_of_America</td>\n",
       "      <td>US</td>\n",
       "      <td>USA</td>\n",
       "      <td>329064917.0</td>\n",
       "      <td>America</td>\n",
       "      <td>830.394205</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>59005</th>\n",
       "      <td>2020-10-12 00:00:00</td>\n",
       "      <td>10</td>\n",
       "      <td>12</td>\n",
       "      <td>2020</td>\n",
       "      <td>220025</td>\n",
       "      <td>3124</td>\n",
       "      <td>United_States_of_America</td>\n",
       "      <td>US</td>\n",
       "      <td>USA</td>\n",
       "      <td>329064917.0</td>\n",
       "      <td>America</td>\n",
       "      <td>794.356027</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>59006</th>\n",
       "      <td>2020-09-12 00:00:00</td>\n",
       "      <td>9</td>\n",
       "      <td>12</td>\n",
       "      <td>2020</td>\n",
       "      <td>217344</td>\n",
       "      <td>2564</td>\n",
       "      <td>United_States_of_America</td>\n",
       "      <td>US</td>\n",
       "      <td>USA</td>\n",
       "      <td>329064917.0</td>\n",
       "      <td>America</td>\n",
       "      <td>784.195114</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>59007</th>\n",
       "      <td>2020-08-12 00:00:00</td>\n",
       "      <td>8</td>\n",
       "      <td>12</td>\n",
       "      <td>2020</td>\n",
       "      <td>197334</td>\n",
       "      <td>1433</td>\n",
       "      <td>United_States_of_America</td>\n",
       "      <td>US</td>\n",
       "      <td>USA</td>\n",
       "      <td>329064917.0</td>\n",
       "      <td>America</td>\n",
       "      <td>769.896719</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>59008</th>\n",
       "      <td>2020-07-12 00:00:00</td>\n",
       "      <td>7</td>\n",
       "      <td>12</td>\n",
       "      <td>2020</td>\n",
       "      <td>173432</td>\n",
       "      <td>1111</td>\n",
       "      <td>United_States_of_America</td>\n",
       "      <td>US</td>\n",
       "      <td>USA</td>\n",
       "      <td>329064917.0</td>\n",
       "      <td>America</td>\n",
       "      <td>762.794473</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>59009</th>\n",
       "      <td>2020-06-12 00:00:00</td>\n",
       "      <td>6</td>\n",
       "      <td>12</td>\n",
       "      <td>2020</td>\n",
       "      <td>211933</td>\n",
       "      <td>2203</td>\n",
       "      <td>United_States_of_America</td>\n",
       "      <td>US</td>\n",
       "      <td>USA</td>\n",
       "      <td>329064917.0</td>\n",
       "      <td>America</td>\n",
       "      <td>757.944062</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>59010</th>\n",
       "      <td>2020-05-12 00:00:00</td>\n",
       "      <td>5</td>\n",
       "      <td>12</td>\n",
       "      <td>2020</td>\n",
       "      <td>231930</td>\n",
       "      <td>2680</td>\n",
       "      <td>United_States_of_America</td>\n",
       "      <td>US</td>\n",
       "      <td>USA</td>\n",
       "      <td>329064917.0</td>\n",
       "      <td>America</td>\n",
       "      <td>746.870564</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                   dateRep  day  month  year   cases  deaths  \\\n",
       "59001           14/12/2020   14     12  2020  189723    1340   \n",
       "59002           13/12/2020   13     12  2020  216017    2315   \n",
       "59003  2020-12-12 00:00:00   12     12  2020  234633    3343   \n",
       "59004  2020-11-12 00:00:00   11     12  2020  224680    2748   \n",
       "59005  2020-10-12 00:00:00   10     12  2020  220025    3124   \n",
       "59006  2020-09-12 00:00:00    9     12  2020  217344    2564   \n",
       "59007  2020-08-12 00:00:00    8     12  2020  197334    1433   \n",
       "59008  2020-07-12 00:00:00    7     12  2020  173432    1111   \n",
       "59009  2020-06-12 00:00:00    6     12  2020  211933    2203   \n",
       "59010  2020-05-12 00:00:00    5     12  2020  231930    2680   \n",
       "\n",
       "        countriesAndTerritories geoId countryterritoryCode  popData2019  \\\n",
       "59001  United_States_of_America    US                  USA  329064917.0   \n",
       "59002  United_States_of_America    US                  USA  329064917.0   \n",
       "59003  United_States_of_America    US                  USA  329064917.0   \n",
       "59004  United_States_of_America    US                  USA  329064917.0   \n",
       "59005  United_States_of_America    US                  USA  329064917.0   \n",
       "59006  United_States_of_America    US                  USA  329064917.0   \n",
       "59007  United_States_of_America    US                  USA  329064917.0   \n",
       "59008  United_States_of_America    US                  USA  329064917.0   \n",
       "59009  United_States_of_America    US                  USA  329064917.0   \n",
       "59010  United_States_of_America    US                  USA  329064917.0   \n",
       "\n",
       "      continentExp  Cumulative_number_for_14_days_of_COVID-19_cases_per_100000  \n",
       "59001      America                                         873.211592           \n",
       "59002      America                                         857.089241           \n",
       "59003      America                                         838.514183           \n",
       "59004      America                                         830.394205           \n",
       "59005      America                                         794.356027           \n",
       "59006      America                                         784.195114           \n",
       "59007      America                                         769.896719           \n",
       "59008      America                                         762.794473           \n",
       "59009      America                                         757.944062           \n",
       "59010      America                                         746.870564           "
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "US_data = df.loc[(df['countriesAndTerritories']) == 'United_States_of_America']\n",
    "\n",
    "US_data[:10]"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "882dbe2d",
   "metadata": {},
   "source": [
    "# 2. What Country has the lowest number of cases?"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "c4f73fb6",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot: xlabel='countriesAndTerritories'>"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "least_cases_by_country = df.groupby('countriesAndTerritories')['cases'].sum()\n",
    "least_cases_by_country.nsmallest(10).plot.bar()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "41d4757b",
   "metadata": {},
   "source": [
    "# Explanation:\n",
    "This data illustrates in a bar chart the top 10 countries that experienced the lowest number of COVID-19 cases in the world. The top countries like Vanuatu and Walis and Futuna have low COVID-19 cases likely because of their low population counts. Tnis data can help set examples and analyze why these countries had low cases to use on larger countries."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "6ecb0610",
   "metadata": {},
   "source": [
    "# 3. What Country has the most deaths?"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "bea18af7",
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot: xlabel='countriesAndTerritories'>"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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ERESKxSBEREREisUgRERERIrFIERERESKxSBEREREisUgRERERIrFIERERESKxSBEREREisUgRERERIrFIERERESKxSBEREREisUgRERERIrFIERERESKxSBEREREisUgRERERIpVoSA0f/58tGvXDhYWFrCxscGAAQNw7tw5vRohBGbPng2tVgtTU1N07twZp0+f1qvJy8vD+PHjYW1tDXNzc/Tr1w9Xr17Vq8nMzISfnx80Gg00Gg38/PyQlZWlV5OSkoK+ffvC3Nwc1tbWmDBhAvLz8/VqTp06BS8vL5iamqJhw4aYM2cOhBAVOWwiIiKqpioUhPbv34+xY8ciJiYGkZGRePDgAXx8fJCTkyPVLFy4EEuWLMHKlSsRGxsLOzs7dO/eHXfu3JFqJk6ciNDQUISEhCA6Ohp3795Fnz59UFhYKNX4+voiISEB4eHhCA8PR0JCAvz8/KT9hYWF6N27N3JychAdHY2QkBDs3LkTkydPlmqys7PRvXt3aLVaxMbGYsWKFVi0aBGWLFnyTF8sIiIiql5U4jmGR27evAkbGxvs378fnTp1ghACWq0WEydOxGeffQbg4eiPra0tvv76a4wePRo6nQ7169fHli1bMHjwYADA9evXYW9vj927d6NHjx5ISkqCq6srYmJi4OHhAQCIiYmBp6cnzp49C2dnZ/zxxx/o06cPUlNTodVqAQAhISHw9/dHRkYGLC0tsWrVKkybNg03btyAWq0GACxYsAArVqzA1atXoVKpnnqM2dnZ0Gg00Ol0sLS0LNfXxfHzsAp/LSsqeUHvl/4ZREREhqq8v7+fa46QTqcDANStWxcAcPnyZaSnp8PHx0eqUavV8PLywqFDhwAAcXFxKCgo0KvRarVwc3OTag4fPgyNRiOFIABo3749NBqNXo2bm5sUggCgR48eyMvLQ1xcnFTj5eUlhaDimuvXryM5ObnUY8rLy0N2drbeg4iIiKqnZw5CQggEBQXhzTffhJubGwAgPT0dAGBra6tXa2trK+1LT0+HiYkJrKysyqyxsbEp8Zk2NjZ6NY9/jpWVFUxMTMqsKX5eXPO4+fPnS/OSNBoN7O3tn/KVICIiIkP1zEFo3LhxOHnyJH788ccS+x4/5SSEeOppqMdrSqt/ETXFZwKf1M+0adOg0+mkR2pqapl9ExERkeF6piA0fvx4/Pbbb/jrr7/QqFEjabudnR2AkqMtGRkZ0kiMnZ0d8vPzkZmZWWbNjRs3SnzuzZs39Woe/5zMzEwUFBSUWZORkQGg5KhVMbVaDUtLS70HERERVU8VCkJCCIwbNw4///wz9u7dCycnJ739Tk5OsLOzQ2RkpLQtPz8f+/fvR4cOHQAAbdq0Qc2aNfVq0tLSkJiYKNV4enpCp9Ph6NGjUs2RI0eg0+n0ahITE5GWlibVREREQK1Wo02bNlLNgQMH9C6pj4iIgFarhaOjY0UOnYiIiKqhCgWhsWPH4vvvv8cPP/wACwsLpKenIz09Hbm5uQAenm6aOHEi5s2bh9DQUCQmJsLf3x9mZmbw9fUFAGg0GowaNQqTJ09GVFQU4uPjMWzYMLi7u8Pb2xsA4OLigp49eyIgIAAxMTGIiYlBQEAA+vTpA2dnZwCAj48PXF1d4efnh/j4eERFRWHKlCkICAiQRnF8fX2hVqvh7++PxMREhIaGYt68eQgKCirXFWNERERUvdWoSPGqVasAAJ07d9bbvnHjRvj7+wMApk6ditzcXAQGBiIzMxMeHh6IiIiAhYWFVL906VLUqFEDgwYNQm5uLrp164bg4GAYGxtLNVu3bsWECROkq8v69euHlStXSvuNjY0RFhaGwMBAdOzYEaampvD19cWiRYukGo1Gg8jISIwdOxZt27aFlZUVgoKCEBQUVJHDJiIiomrqudYRUgKuI0RERGR4KmUdISIiIiJDxiBEREREisUgRERERIrFIERERESKxSBEREREisUgRERERIrFIERERESKxSBEREREisUgRERERIrFIERERESKxSBEREREisUgRERERIrFIERERESKxSBEREREisUgRERERIpVQ+4GqOpy/DzspX9G8oLeL/0ziIiInoQjQkRERKRYDEJERESkWAxCREREpFgMQkRERKRYDEJERESkWAxCREREpFgMQkRERKRYDEJERESkWAxCREREpFgMQkRERKRYDEJERESkWAxCREREpFgMQkRERKRYDEJERESkWAxCREREpFgMQkRERKRYDEJERESkWAxCREREpFgMQkRERKRYDEJERESkWAxCREREpFgMQkRERKRYDEJERESkWAxCREREpFgMQkRERKRYDEJERESkWAxCREREpFgMQkRERKRYDEJERESkWAxCREREpFgMQkRERKRYDEJERESkWBUOQgcOHEDfvn2h1WqhUqnwyy+/6O339/eHSqXSe7Rv316vJi8vD+PHj4e1tTXMzc3Rr18/XL16Va8mMzMTfn5+0Gg00Gg08PPzQ1ZWll5NSkoK+vbtC3Nzc1hbW2PChAnIz8/Xqzl16hS8vLxgamqKhg0bYs6cORBCVPSwiYiIqBqqcBDKyclBy5YtsXLlyifW9OzZE2lpadJj9+7devsnTpyI0NBQhISEIDo6Gnfv3kWfPn1QWFgo1fj6+iIhIQHh4eEIDw9HQkIC/Pz8pP2FhYXo3bs3cnJyEB0djZCQEOzcuROTJ0+WarKzs9G9e3dotVrExsZixYoVWLRoEZYsWVLRwyYiIqJqqEZFX9CrVy/06tWrzBq1Wg07O7tS9+l0OmzYsAFbtmyBt7c3AOD777+Hvb099uzZgx49eiApKQnh4eGIiYmBh4cHAGDdunXw9PTEuXPn4OzsjIiICJw5cwapqanQarUAgMWLF8Pf3x9z586FpaUltm7divv37yM4OBhqtRpubm44f/48lixZgqCgIKhUqooePhEREVUjL2WO0L59+2BjY4PmzZsjICAAGRkZ0r64uDgUFBTAx8dH2qbVauHm5oZDhw4BAA4fPgyNRiOFIABo3749NBqNXo2bm5sUggCgR48eyMvLQ1xcnFTj5eUFtVqtV3P9+nUkJyeX2nteXh6ys7P1HkRERFQ9vfAg1KtXL2zduhV79+7F4sWLERsbi65duyIvLw8AkJ6eDhMTE1hZWem9ztbWFunp6VKNjY1Nife2sbHRq7G1tdXbb2VlBRMTkzJrip8X1zxu/vz50rwkjUYDe3v7in4JiIiIyEBU+NTY0wwePFj6bzc3N7Rt2xYODg4ICwvDwIEDn/g6IYTeqarSTlu9iJriidJPOi02bdo0BAUFSc+zs7MZhoiIiKqpl375fIMGDeDg4IALFy4AAOzs7JCfn4/MzEy9uoyMDGm0xs7ODjdu3CjxXjdv3tSreXxUJzMzEwUFBWXWFJ+me3ykqJharYalpaXeg4iIiKqnlx6Ebt26hdTUVDRo0AAA0KZNG9SsWRORkZFSTVpaGhITE9GhQwcAgKenJ3Q6HY4ePSrVHDlyBDqdTq8mMTERaWlpUk1ERATUajXatGkj1Rw4cEDvkvqIiAhotVo4Ojq+tGMmIiIiw1DhIHT37l0kJCQgISEBAHD58mUkJCQgJSUFd+/exZQpU3D48GEkJydj37596Nu3L6ytrfHOO+8AADQaDUaNGoXJkycjKioK8fHxGDZsGNzd3aWryFxcXNCzZ08EBAQgJiYGMTExCAgIQJ8+feDs7AwA8PHxgaurK/z8/BAfH4+oqChMmTIFAQEB0iiOr68v1Go1/P39kZiYiNDQUMybN49XjBERERGAZ5gjdOzYMXTp0kV6XjyfZvjw4Vi1ahVOnTqFzZs3IysrCw0aNECXLl2wbds2WFhYSK9ZunQpatSogUGDBiE3NxfdunVDcHAwjI2NpZqtW7diwoQJ0tVl/fr101u7yNjYGGFhYQgMDETHjh1hamoKX19fLFq0SKrRaDSIjIzE2LFj0bZtW1hZWSEoKEhvDhAREREpl0pwmeUyZWdnQ6PRQKfTlXu+kOPnYS+5KyB5Qe+X/hnV5TiIiEh5yvv7+4VfNUZU1bzsQMcwR0RkuHjTVSIiIlIsBiEiIiJSLAYhIiIiUiwGISIiIlIsBiEiIiJSLAYhIiIiUiwGISIiIlIsBiEiIiJSLAYhIiIiUiwGISIiIlIsBiEiIiJSLAYhIiIiUiwGISIiIlIsBiEiIiJSLAYhIiIiUiwGISIiIlIsBiEiIiJSLAYhIiIiUiwGISIiIlIsBiEiIiJSLAYhIiIiUiwGISIiIlIsBiEiIiJSLAYhIiIiUiwGISIiIlIsBiEiIiJSLAYhIiIiUiwGISIiIlIsBiEiIiJSLAYhIiIiUiwGISIiIlIsBiEiIiJSLAYhIiIiUiwGISIiIlKsGnI3QERP5/h52Ev/jOQFvV/6ZxARVTUcESIiIiLFYhAiIiIixWIQIiIiIsViECIiIiLFYhAiIiIixWIQIiIiIsViECIiIiLFYhAiIiIixWIQIiIiIsViECIiIiLFYhAiIiIixapwEDpw4AD69u0LrVYLlUqFX375RW+/EAKzZ8+GVquFqakpOnfujNOnT+vV5OXlYfz48bC2toa5uTn69euHq1ev6tVkZmbCz88PGo0GGo0Gfn5+yMrK0qtJSUlB3759YW5uDmtra0yYMAH5+fl6NadOnYKXlxdMTU3RsGFDzJkzB0KIih42ERERVUMVDkI5OTlo2bIlVq5cWer+hQsXYsmSJVi5ciViY2NhZ2eH7t27486dO1LNxIkTERoaipCQEERHR+Pu3bvo06cPCgsLpRpfX18kJCQgPDwc4eHhSEhIgJ+fn7S/sLAQvXv3Rk5ODqKjoxESEoKdO3di8uTJUk12dja6d+8OrVaL2NhYrFixAosWLcKSJUsqethERERUDVX47vO9evVCr169St0nhMCyZcswffp0DBw4EACwadMm2Nra4ocffsDo0aOh0+mwYcMGbNmyBd7e3gCA77//Hvb29tizZw969OiBpKQkhIeHIyYmBh4eHgCAdevWwdPTE+fOnYOzszMiIiJw5swZpKamQqvVAgAWL14Mf39/zJ07F5aWlti6dSvu37+P4OBgqNVquLm54fz581iyZAmCgoKgUqme6YtGRERE1cMLnSN0+fJlpKenw8fHR9qmVqvh5eWFQ4cOAQDi4uJQUFCgV6PVauHm5ibVHD58GBqNRgpBANC+fXtoNBq9Gjc3NykEAUCPHj2Ql5eHuLg4qcbLywtqtVqv5vr160hOTi71GPLy8pCdna33ICIiourphQah9PR0AICtra3edltbW2lfeno6TExMYGVlVWaNjY1Nife3sbHRq3n8c6ysrGBiYlJmTfHz4prHzZ8/X5qXpNFoYG9v//QDJyIiIoP0Uq4ae/yUkxDiqaehHq8prf5F1BRPlH5SP9OmTYNOp5MeqampZfZNREREhuuFBiE7OzsAJUdbMjIypJEYOzs75OfnIzMzs8yaGzdulHj/mzdv6tU8/jmZmZkoKCgosyYjIwNAyVGrYmq1GpaWlnoPIiIiqp5eaBBycnKCnZ0dIiMjpW35+fnYv38/OnToAABo06YNatasqVeTlpaGxMREqcbT0xM6nQ5Hjx6Vao4cOQKdTqdXk5iYiLS0NKkmIiICarUabdq0kWoOHDigd0l9REQEtFotHB0dX+ShExERkQGqcBC6e/cuEhISkJCQAODhBOmEhASkpKRApVJh4sSJmDdvHkJDQ5GYmAh/f3+YmZnB19cXAKDRaDBq1ChMnjwZUVFRiI+Px7Bhw+Du7i5dRebi4oKePXsiICAAMTExiImJQUBAAPr06QNnZ2cAgI+PD1xdXeHn54f4+HhERUVhypQpCAgIkEZxfH19oVar4e/vj8TERISGhmLevHm8YoyIiIgAPMPl88eOHUOXLl2k50FBQQCA4cOHIzg4GFOnTkVubi4CAwORmZkJDw8PREREwMLCQnrN0qVLUaNGDQwaNAi5ubno1q0bgoODYWxsLNVs3boVEyZMkK4u69evn97aRcbGxggLC0NgYCA6duwIU1NT+Pr6YtGiRVKNRqNBZGQkxo4di7Zt28LKygpBQUFSz0RERKRsKsFllsuUnZ0NjUYDnU5X7vlCjp+HveSugOQFvV/6Z/A4yqc6HANQOcdBRFRZyvv7m/caIyIiIsViECIiIiLFYhAiIiIixWIQIiIiIsViECIiIiLFYhAiIiIixWIQIiIiIsViECIiIiLFYhAiIiIixWIQIiIiIsViECIiIiLFYhAiIiIixWIQIiIiIsViECIiIiLFYhAiIiIixWIQIiIiIsViECIiIiLFYhAiIiIixWIQIiIiIsViECIiIiLFYhAiIiIixWIQIiIiIsViECIiIiLFYhAiIiIixWIQIiIiIsViECIiIiLFYhAiIiIixWIQIiIiIsViECIiIiLFYhAiIiIixWIQIiIiIsViECIiIiLFYhAiIiIixWIQIiIiIsViECIiIiLFqiF3A0SkHI6fh730z0he0PulfwYRVR8MQkREFcAwR1S98NQYERERKRaDEBERESkWgxAREREpFoMQERERKRaDEBERESkWgxAREREpFi+fJyJSIC4DQPQQR4SIiIhIsRiEiIiISLEYhIiIiEixGISIiIhIsV54EJo9ezZUKpXew87OTtovhMDs2bOh1WphamqKzp074/Tp03rvkZeXh/Hjx8Pa2hrm5ubo168frl69qleTmZkJPz8/aDQaaDQa+Pn5ISsrS68mJSUFffv2hbm5OaytrTFhwgTk5+e/6EMmIiIiA/VSRoRee+01pKWlSY9Tp05J+xYuXIglS5Zg5cqViI2NhZ2dHbp37447d+5INRMnTkRoaChCQkIQHR2Nu3fvok+fPigsLJRqfH19kZCQgPDwcISHhyMhIQF+fn7S/sLCQvTu3Rs5OTmIjo5GSEgIdu7cicmTJ7+MQyYiIiID9FIun69Ro4beKFAxIQSWLVuG6dOnY+DAgQCATZs2wdbWFj/88ANGjx4NnU6HDRs2YMuWLfD29gYAfP/997C3t8eePXvQo0cPJCUlITw8HDExMfDw8AAArFu3Dp6enjh37hycnZ0RERGBM2fOIDU1FVqtFgCwePFi+Pv7Y+7cubC0tHwZh05ERJXoZS8DwCUAqr+XMiJ04cIFaLVaODk54V//+hcuXboEALh8+TLS09Ph4+Mj1arVanh5eeHQoUMAgLi4OBQUFOjVaLVauLm5STWHDx+GRqORQhAAtG/fHhqNRq/Gzc1NCkEA0KNHD+Tl5SEuLu6Jvefl5SE7O1vvQURERNXTCw9CHh4e2Lx5M/7880+sW7cO6enp6NChA27duoX09HQAgK2trd5rbG1tpX3p6ekwMTGBlZVVmTU2NjYlPtvGxkav5vHPsbKygomJiVRTmvnz50vzjjQaDezt7Sv4FSAiIiJD8cKDUK9evfDuu+/C3d0d3t7eCAt7OGy5adMmqUalUum9RghRYtvjHq8prf5Zah43bdo06HQ66ZGamlpmX0RERGS4Xvrl8+bm5nB3d8eFCxekeUOPj8hkZGRIozd2dnbIz89HZmZmmTU3btwo8Vk3b97Uq3n8czIzM1FQUFBipOhRarUalpaWeg8iIiKqnl76vcby8vKQlJSEt956C05OTrCzs0NkZCRatWoFAMjPz8f+/fvx9ddfAwDatGmDmjVrIjIyEoMGDQIApKWlITExEQsXLgQAeHp6QqfT4ejRo3jjjTcAAEeOHIFOp0OHDh2kmrlz5yItLQ0NGjQAAERERECtVqNNmzYv+7CJiIjKhfd9k9cLD0JTpkxB37590bhxY2RkZOCrr75CdnY2hg8fDpVKhYkTJ2LevHl45ZVX8Morr2DevHkwMzODr68vAECj0WDUqFGYPHky6tWrh7p162LKlCnSqTYAcHFxQc+ePREQEIA1a9YAAD766CP06dMHzs7OAAAfHx+4urrCz88P//d//4fbt29jypQpCAgI4CgPERHRC2aoge6FB6GrV69iyJAh+Oeff1C/fn20b98eMTExcHBwAABMnToVubm5CAwMRGZmJjw8PBAREQELCwvpPZYuXYoaNWpg0KBByM3NRbdu3RAcHAxjY2OpZuvWrZgwYYJ0dVm/fv2wcuVKab+xsTHCwsIQGBiIjh07wtTUFL6+vli0aNGLPmQiIiIyUC88CIWEhJS5X6VSYfbs2Zg9e/YTa2rVqoUVK1ZgxYoVT6ypW7cuvv/++zI/q3Hjxvj999/LrCEiIiLl4r3GiIiISLEYhIiIiEixGISIiIhIsRiEiIiISLEYhIiIiEixGISIiIhIsRiEiIiISLEYhIiIiEixGISIiIhIsRiEiIiISLEYhIiIiEixGISIiIhIsRiEiIiISLEYhIiIiEixGISIiIhIsRiEiIiISLEYhIiIiEixGISIiIhIsRiEiIiISLEYhIiIiEixGISIiIhIsRiEiIiISLEYhIiIiEixGISIiIhIsRiEiIiISLEYhIiIiEixGISIiIhIsRiEiIiISLEYhIiIiEixGISIiIhIsRiEiIiISLEYhIiIiEixGISIiIhIsRiEiIiISLEYhIiIiEixGISIiIhIsRiEiIiISLEYhIiIiEixGISIiIhIsRiEiIiISLEYhIiIiEixGISIiIhIsRiEiIiISLEYhIiIiEixGISIiIhIsRiEiIiISLEYhIiIiEixGISIiIhIsRQRhP773//CyckJtWrVQps2bXDw4EG5WyIiIqIqoNoHoW3btmHixImYPn064uPj8dZbb6FXr15ISUmRuzUiIiKSWbUPQkuWLMGoUaPw4YcfwsXFBcuWLYO9vT1WrVold2tEREQksxpyN/Ay5efnIy4uDp9//rnedh8fHxw6dKjU1+Tl5SEvL096rtPpAADZ2dnl/tyivHvP0G3FVKSfZ8XjKJ/qcAwAj6O8qsMxADyO8qoOxwAo8ziKa4UQZReKauzatWsCgPj777/1ts+dO1c0b9681NfMmjVLAOCDDz744IMPPqrBIzU1tcysUK1HhIqpVCq950KIEtuKTZs2DUFBQdLzoqIi3L59G/Xq1Xvia55XdnY27O3tkZqaCktLy5fyGS9bdTgGgMdRlVSHYwCqx3FUh2MAeBxVSWUcgxACd+7cgVarLbOuWgcha2trGBsbIz09XW97RkYGbG1tS32NWq2GWq3W21anTp2X1aIeS0tLg/2mLlYdjgHgcVQl1eEYgOpxHNXhGAAeR1Xyso9Bo9E8taZaT5Y2MTFBmzZtEBkZqbc9MjISHTp0kKkrIiIiqiqq9YgQAAQFBcHPzw9t27aFp6cn1q5di5SUFIwZM0bu1oiIiEhm1T4IDR48GLdu3cKcOXOQlpYGNzc37N69Gw4ODnK3JlGr1Zg1a1aJU3KGpDocA8DjqEqqwzEA1eM4qsMxADyOqqQqHYNKiKddV0ZERERUPVXrOUJEREREZWEQIiIiIsViECIiIiLFYhAiIiIixWIQIiIiIsViECIiIiLFqvbrCBERERmywsJCBAcHIyoqChkZGSgqKtLbv3fvXpk6qx4YhGR25swZpKSkID8/X297v379ZOro6Vq1alXuG9AeP378JXfzYuzYsQPbt28v9f+FoRwDAGRlZWHDhg1ISkqCSqWCi4sLRo0aVa777VQV/v7+GDlyJDp16iR3Ky/E3bt3S/ziMqT7Q2VlZWHHjh24ePEiPv30U9StWxfHjx+Hra0tGjZsKHd7T3Xjxg1MmTJFChGPL51XWFgoU2fl98knnyA4OBi9e/eGm5vbS7sBeGWqSr/7GIRkcunSJbzzzjs4deoUVCqV9MNZ/A1elX84BwwYIHcLL9Ty5csxffp0DB8+HL/++itGjBiBixcvIjY2FmPHjpW7vXI7duwYevToAVNTU7zxxhsQQmDp0qWYN28eIiIi0Lp1a7lbLJc7d+7Ax8cH9vb2GDFiBIYPH24Qv3AfdfnyZYwbNw779u3D/fv3pe1CCKhUqir98/2okydPwtvbGxqNBsnJyQgICEDdunURGhqKK1euYPPmzXK3+FT+/v5ISUnBjBkz0KBBA4MMESEhIdi+fTvefvttuVt5blXyd58gWfTp00f0799fZGRkiNq1a4szZ86IgwcPijfeeEMcOHBA7vYUxdnZWfzwww9CCCFq164tLl68KIQQYsaMGWLs2LFytlYhb775pvD39xcFBQXStoKCAjF8+HDx1ltvydhZxf3zzz9i2bJl4vXXXxc1atQQPXv2FD/99JPIz8+Xu7Vy8fT0FJ6eniIkJET89ddfYt++fXoPQ9GtWzfx6aefCiH0fzb+/vtv4eDgIGNn5Ve7dm0RHx8vdxvPpUGDBuLcuXNyt/FCVMXffQxCMqlXr544ceKEEEIIS0tLcfbsWSGEEFFRUeL111+XszXFMTU1FcnJyUIIIerXry8SEhKEEEKcP39e1K1bV87WKqRWrVoiKSmpxPbTp08LU1NTGTp6MY4fPy7GjRsnatWqJaytrcXEiRPF+fPn5W6rTObm5tLPtCGztLQU//vf/4QQ+kEoOTlZqNVqOVsrNxcXF3H8+HG523guixYtEoGBgaKoqEjuVp5bVfzdx6vGZFJYWIjatWsDAKytrXH9+nUAgIODA86dOydna09Vt25d/PPPPwAAKysr1K1b94kPQ2BnZ4dbt24BePj1j4mJAfDw9IYwoFvxWVpaIiUlpcT21NRUWFhYyNDR80tLS0NERAQiIiJgbGyMt99+G6dPn4arqyuWLl0qd3tP1K5dO6SmpsrdxnOrVasWsrOzS2w/d+4c6tevL0NHFbds2TJ8/vnnSE5OlruVZxYdHY2tW7eiadOm6Nu3LwYOHKj3MCRV8Xcf5wjJxM3NDSdPnkSTJk3g4eGBhQsXwsTEBGvXrkWTJk3kbq9MS5culX6xLl261CDPuT+qa9eu2LVrF1q3bo1Ro0Zh0qRJ2LFjB44dO2ZQ/8gMHjwYo0aNwqJFi9ChQweoVCpER0fj008/xZAhQ+Rur9wKCgrw22+/YePGjYiIiECLFi0wadIkDB06VPq+CwkJwccff4xJkybJ3G3p1q9fjzFjxuDatWtwc3NDzZo19fa3aNFCps4qpn///pgzZw62b98O4OE8jpSUFHz++ed49913Ze6ufAYPHox79+6hadOmMDMzK/H/4vbt2zJ1Vn516tTBO++8I3cbL0RV/N3Hu8/L5M8//0ROTg4GDhyIS5cuoU+fPjh79izq1auHbdu2oWvXrnK3qBhFRUUoKipCjRoP/y7Yvn07oqOj0axZM4wZMwYmJiYyd1g++fn5+PTTT7F69Wo8ePAAAFCzZk18/PHHWLBgAdRqtcwdlo+1tTWKioowZMgQBAQE4PXXXy9Rk5mZidatW+Py5cuV32A5xMTEwNfXV28UonhiqCFNls7OzpZG4e7cuQOtVov09HR4enpi9+7dMDc3l7vFp9q0aVOZ+4cPH15JnRBQNX/3MQhVIbdv34aVlZVBjbB07doVXl5emDVrlt72zMxMvPvuu1zfQgb37t3DxYsXIYRAs2bNYGZmJndLFbJlyxa8//77qFWrltytPDNXV1e4uLhg6tSpsLW1LfEz7eDgIFNnz2bv3r04fvw4ioqK0Lp1a3h7e8vdElUjcv/uYxCSiU6nQ2FhYYl5NLdv30aNGjUMZp0RIyMj1KtXDx07dsTWrVulvxBv3LgBrVZbZf/yPXnyJNzc3GBkZISTJ0+WWWsopzGqy/dUdWBubo4TJ06gWbNmcrdCj8jNzUVBQYHetqr6c9G6dWtERUXBysrqqWu3GdJaZ1UR5wjJ5F//+hf69u2LwMBAve3bt2/Hb7/9ht27d8vUWcXt2bMHo0ePRvv27bFr1y44OjrK3dJTvf7660hPT4eNjQ1ef/11vfUsHmVIpzEM+XuqInOxfv7555fYyYvRtWvXahGEJkyYgGbNmmHChAl621euXIn//e9/WLZsmTyNVUBOTg4+++wzbN++Xboo4lFV9ee7f//+0ulsQ1+7beDAgQgODoalpeVTf9bl+PlmEJLJkSNHsGTJkhLbO3fujOnTp8vQ0bNr0KAB9u/fj5EjR6Jdu3b46aef4OLiIndbZbp8+bJ01UtVnWdSUYb8PWVIK1+XR9++fTFp0iScOnUK7u7uJSboVuWV4x+1c+dO/PbbbyW2d+jQAQsWLDCIIDR16lT89ddf+O9//4sPPvgA3377La5du4Y1a9ZgwYIFcrf3RI9ON3h86oGh0Wg00ohWlfxZl+WifRJmZmbi5MmTJbafPHnSoNZ8MTIyEjdu3JCef/nll0KtVouZM2cKIyMjGTtTnuryPVUdqFSqJz4M6edCrVaLCxculNh+4cIFg1lHyN7eXvz1119CCCEsLCyk49m8ebPo1auXjJ1RVcERIZm0a9cOa9euxYoVK/S2r169Gm3atJGpq4oTj51O+s9//gMXF5cqfyVGaX/lPomh/PVeXb6nqoPH7y1mqJo1a4bw8HCMGzdOb/sff/xR5Zf5KHb79m04OTkBeDgfqPhy+TfffBMff/yxnK2VW2FhIZYuXfrE+yEawhIAxXJzcyGEkC7iuHLlCkJDQ+Hq6gofHx9ZemIQksncuXPh7e2NEydOoFu3bgCAqKgoxMbGIiIiQubuyu/RU0zF3n33XTg7OyMuLk6mrp7u8XPuj88RenRiYlWdQ/C46vI9BVSfm+AauqCgIIwbNw43b96ULmuOiorC4sWLDeK0GAA0adIEycnJcHBwgKurK7Zv34433ngDu3btQp06deRur1y++OILrF+/HkFBQZgxYwamT5+O5ORk/PLLL5g5c6bc7VVI//79MXDgQIwZMwZZWVl44403YGJign/++QdLliyRJ5zKPCKlaPHx8cLX11e4urqKNm3aiBEjRlT5WwdUR5GRkaJ169YiPDxc6HQ6kZ2dLcLDw0Xbtm1FRESE3O1VSHX4nvrmm29E7dq1xdixY4WJiYkYPXq08Pb2FhqNRvz73/+Wu71y27dvn+jTp49o2rSpaNasmejbt69B3kfwv//9r2jYsKF0as/JyUls2rRJ7rbKbcmSJeKbb74RQgixd+9eYWpqKkxMTISRkZFYtmyZzN2VT5MmTcTvv/8uhHh4q5Pi25588803YsiQIXK2VmH16tUTiYmJQggh1q1bJ1q0aCEKCwvF9u3bxauvvipLT7x8np5bbGwsfvrpp1L/ejeEK3zc3NywevVqvPnmm3rbDx48iI8++ghJSUkydaZMr776KmbNmoUhQ4bAwsICJ06cQJMmTTBz5kzcvn0bK1eulLvFp/r+++8xYsQIDBw4EB07doQQAocOHUJoaCiCg4Ph6+srd4sVdvPmTZiamkq3RzBUKSkpOHbsGJo2bYqWLVvK3U65mJubIykpCY0bN0aDBg0QFhaG1q1b49KlS2jVqhV0Op3cLZabmZkZzp49i8aNG2PQoEF47bXXMGvWLKSmpsLZ2Rn37t2r9J54r7FK9Og9e7Kzs8t8GIqQkBB07NgRZ86cQWhoKAoKCnDmzBns3bu3al4dUIqLFy+W2qtGo6ny9yeqjt9TKSkp6NChAwDA1NQUd+7cAQD4+fnhxx9/lLO1cps7dy4WLlyIbdu2YcKECfjkk0+wbds2LFiwAF9++aXc7T2T+vXrG1wIKigoQJcuXXD+/HlpW+PGjTFw4ECDCUEA0KhRI6SlpQF4OG+r+FR3bGyswawYX6xZs2b45ZdfkJqaij///FOaF5SRkSHfmk6yjEMp1KNXWBVfPfL4w9CuKnF3dxcrV64UQvz/d6cuKioSAQEBYubMmTJ3Vz5vvfWW6Nq1q7h+/bq0LS0tTXh7e4tOnTrJ2NnTVcfvKScnJxEXFyeEEKJt27Zi9erVQggh/vzzT2FlZSVna+VmYmJi8FdbCSFEenq6GDZsmGjQoIEwNjYu8b1lCKytrQ3u9PDjPvvsMzF37lwhhBA//fSTqFGjhmjWrJkwMTERn332mczdVcxPP/0katasKYyMjET37t2l7fPmzRM9e/aUpSdOlq5Ee/fulVb9/euvv2Tu5sW4ePEievfuDQBQq9XIycmBSqXCpEmT0LVrV3zxxRcyd/h03333Hd555x04ODigcePGAB6OSjRv3hy//PKLvM09xaPfU3v37jWo27M8SXW4Ca69vT2ioqJKLKgYFRUFe3t7mbqqOH9/f6SkpGDGjBlo0KCBQX5/ffDBB9iwYUOVXjPoaR7t/b333kOjRo1w6NAhNGvWzGCuai323nvv4c0330RaWpreqFy3bt1ku7Esg1Al8vLyAgA8ePAA+/btw8iRIw3qH8XS1K1bVzp10bBhQyQmJsLd3R1ZWVmynOt9Fs2aNcPJkycRGRmJs2fPQggBV1dXeHt7V/l/+Iu/p4CHCydWB2vXrpUuPx8zZgzq1q2L6Oho9O3bF2PGjJG5u/KZPHkyJkyYgISEBHTo0AEqlQrR0dEIDg7GN998I3d75RYdHY2DBw+WeuNbQ5Gfn4/169cjMjISbdu2LXGj2NIWIa3q2rdvj/bt28vdxjOzs7ODnZ0dgIen9Pfu3QtnZ2e8+uqrsvTDydIysbCwwKlTpwzidhRl8fX1Rdu2bREUFIS5c+fim2++Qf/+/REZGYnWrVsbxGTp6mLGjBmYPXs2jI2N9bbrdDqMGTPGYObXpKSkwN7evkQIFUIgNTVVGrWr6kJDQ7F48WJpsr2Liws+/fRT9O/fX+bOys/V1RVbt25Fq1at5G7lmXXp0qXM/YYyOn/u3DmsWLECSUlJUKlUePXVVzF+/Hg4OzvL3VqFDBo0CJ06dcK4ceOQm5uLli1bIjk5GUIIhISE4N133630nhiEZDJgwAAMGDAA/v7+crfyXG7fvo379+9Dq9WiqKgIixYtQnR0NJo1a4YZM2bAyspK7hbLJSoqClFRUcjIyCixGN53330nU1cV4+DggAYNGmDr1q1o2rQpAGDfvn344IMP0LBhQxw+fFjmDsvH2NgYaWlpsLGx0dt+69Yt2NjYGMy6TtVBREQEFi9ejDVr1hj8H22GbMeOHRgyZAjatm0LT09PAEBMTAxiY2Pxww8/4P3335e5w/Kzs7PDn3/+iZYtW+KHH37ArFmzcOLECWzatAlr165FfHx8pffEICSTNWvWYPbs2Rg6dCjatGlTYrjWEM77PnjwAFu3bkWPHj2kYU5D9MUXX2DOnDlo27ZtqfMgQkNDZeqsYnQ6HUaPHo2wsDAsWbIE58+fxzfffIPPP/8cs2bNKjFSVFUZGRnhxo0bJRbqvHLlClxdXZGTkyNTZ8pjZWWFe/fu4cGDBzAzMytxz7SqvKJxeeaTqVQq7Ny5sxK6eT5NmjTBsGHDMGfOHL3ts2bNwpYtW3Dp0iWZOqs4U1NTnD9/Hvb29vjggw+g1WqxYMECpKSkwNXVFXfv3q30njhHSCbFq2eWdn7aUO54XqNGDXz88ccGv87O6tWrERwcDD8/P7lbeS4ajQYhISGYPn06Ro8ejRo1auCPP/6QVpmu6oKCggA8/P6fMWOGtAQ/8HB17yNHjlTpuSpWVlblnlNWlQPEowxl9ejSGMryHeWRnp6ODz74oMT2YcOG4f/+7/9k6OjZ2dvb4/Dhw6hbty7Cw8MREhICAMjMzEStWrVk6YlBSCbV5V5EHh4eiI+Ph4ODg9ytPLP8/Hxp3RpDt2LFCixduhRDhgxBXFwcJkyYgB9++MEg1kwpHhIXQuDUqVMwMTGR9pmYmKBly5aYMmWKXO091aOh4datW/jqq6/Qo0cP6VTG4cOH8eeff2LGjBkydVhxVf2egWXZuHGj3C28MJ07d8bBgwdLXIUYHR2Nt956S6auns3EiRMxdOhQ1K5dGw4ODtJFHgcOHIC7u7ssPfHUWBVw//592ZLw8/rpp5/w+eefY9KkSaWe4mvRooVMnZXfZ599htq1axvUL6jS9OrVC7GxsVi9ejXee+895ObmIigoCMHBwfjiiy8wdepUuVsslxEjRmD58uWwsLCQu5Vn9u6776JLly4lbla6cuVK7Nmzp8ovy1Ca3NxcFBQU6G2TbQE8hVm9ejVmzpyJQYMGSVeLxcTE4KeffsIXX3wBrVYr1RrCtIpjx44hNTUV3bt3lxbpDAsLQ506ddCxY8dK74dBSCaFhYWYN28eVq9ejRs3buD8+fNo0qQJZsyYAUdHR4waNUruFsvFyOjJi5Mbyim+Tz75BJs3b0aLFi3QokWLEvMgDOXy2u7du2PTpk16/ygCD/+B+fDDD6WVaauq8q4RZAhXItauXRsJCQkl/oK/cOECWrVqJcs8iGeRk5ODzz77DNu3b8etW7dK7DeEn+/qoKx/Zx9lKP/mVjU8NSaTuXPnYtOmTVi4cCECAgKk7e7u7li6dKnBBKHLly/L3cJzO3nypDT3JDExUd5mnkNkZGSp23v37o1Tp05VcjcVV53mdNSrVw+hoaH49NNP9bb/8ssvqFevnkxdVdzUqVPx119/4b///S8++OADfPvtt7h27RrWrFlj0AsUGprqMpUCAEaOHFnmfjmu0uWIkEyaNWuGNWvWoFu3bno3ljx79iw8PT2RmZkpd4vlcuvWLekf9tTUVKxbtw65ubno16+fwZ27rg4OHjyINWvW4OLFi9ixYwcaNmyILVu2wMnJqcRNZenlCQ4OxqhRo9CzZ0+9y53Dw8Oxfv16g1k2o3Hjxti8eTM6d+4MS0tLHD9+HM2aNcOWLVvw448/Yvfu3XK3WK0dOXIEt2/fRq9evaRtmzdvxqxZs5CTk4MBAwZgxYoVBnW/scdXjy4oKEBiYiKysrLQtWtXWUZ8OSIkk2vXrpUYNgceJv/Hz8NXRadOnULfvn2RmpqKV155BSEhIejZsydycnJgZGSEpUuXYseOHRgwYIDcrT5Rdbq8FgB27twJPz8/DB06FPHx8cjLywMA3LlzB/PmzeMvrUrk7+8PFxcXLF++HD///LO0Wvnff/8NDw8Pudsrt9u3b8PJyQnAw/lAxVe7vfnmm9KVr/TyzJ49G507d5aC0KlTpzBq1Cjp++v//u//oNVqMXv2bHkbrYDSliMpKipCYGAgmjRpIkNHvPu8bF577TUcPHiwxPaffvrJIFZxnTp1Ktzd3bF//3507twZffr0wdtvvw2dTofMzEyMHj26yg+dazSapz4MaTLoV199hdWrV2PdunV685w6dOiA48ePy9iZMnl4eGDr1q04fvw44uPjsXXrVoMKQcDD9WuSk5MBPFxlevv27QCAXbt2oU6dOvI1phAJCQl6y1+EhITAw8MD69atQ1BQEJYvXy79PzFkRkZGmDRpEpYuXSrL53NESCazZs2Cn58frl27hqKiIvz88884d+4cNm/ejN9//13u9p4qNjYWe/fuRYsWLfD6669j7dq1CAwMlCb1jR8/vsrfC6c6XV4LPFyCv1OnTiW2W1paIisrq/IbUrDs7OxSt6tUKqjVar2lAaqyESNG4MSJE/Dy8sK0adPQu3dvrFixAg8ePDCYiwgMWWZmJmxtbaXn+/fvR8+ePaXn7dq1Q2pqqhytvXAXL17EgwcPZPlsBiGZ9O3bF9u2bcO8efOgUqkwc+ZMtG7dGrt27UL37t3lbu+pbt++La0mXbt2bZibm0t3QQceLi5XfDNWqhwNGjTA//73vxK3QoiOjpZtyFmp6tSpU+biio0aNYK/vz9mzZpV7iuC5DBp0iTpv7t06YKzZ8/i2LFjaNq0qUGsTWXobG1tcfnyZdjb2yM/Px/Hjx/HF198Ie2/c+dOiatcq7rihVOLCSGQlpaG33//Xba5cwxCMurRowd69OghdxvP7PF/6Kv6ndqru9GjR+OTTz7Bd999B5VKhevXr+Pw4cOYMmUKZs6cKXd7ihIcHIzp06fD398fb7zxBoQQiI2NxaZNm/Cf//wHN2/exKJFi6BWq/Hvf/9b7nZLVVBQAB8fH6xZswbNmzcH8HDytKHc9LY66NmzJz7//HN8/fXX+OWXX2BmZqZ3EcrJkyel+woaiuPHj+v9rjAyMkL9+vWxZMkS9O7dW5aeGISqgLt375a4PNIQ5qb4+/tLVyvcv38fY8aMkRZULJ6oS5Vn6tSp0Ol06NKlC+7fv49OnTpBrVZjypQpJRb2o5dr06ZNWLx4MQYNGiRt69evH9zd3bFmzRpERUWhcePGmDt3bpUNQjVr1kRiYiL/wJHRV199hYEDB8LLywu1a9fGpk2b9E6rfvfdd/Dx8ZGxw4rbt29fiW3p6emYO3cuPvnkE+Tm5lZ6T7x8XiaXL1/GuHHjsG/fPty/f1/aLoQwiEWxRowYUa666jYPxxDcu3cPZ86cQVFREVxdXaWVW6nymJmZ4cSJE3jllVf0tl+4cAEtW7bEvXv3cPnyZbz22mu4d++eTF0+3eTJk1GzZs0qf+FDdafT6VC7du0SN06+ffs2ateubRBzzrKysjB27FhERETAxMQEn332GcaNG4cvvvgCixYtgqurK4KCgjBkyJBK740jQjIZOnQogIeJ3tbW1uD+6mLAqTqetkBZMTkWKlOqRo0aYcOGDSUCxIYNG2Bvbw/g4RpcVlZWcrRXbvn5+Vi/fj0iIyPRtm3bErfQ4YTpyvGkxUYfnZdZ1f373//GgQMHMHz4cPzxxx+YNGkSwsPDcf/+fezevRteXl6y9cYgJJOTJ08iLi4Ozs7OcrdCBi44OBgODg5o1aoVOMBbNSxatAjvv/8+/vjjD7Rr1w4qlQqxsbE4e/YsduzYAeDhlZeDBw+WudPSXbp0CY6OjkhMTETr1q0BAOfPn9erMbQ/3kheYWFh2LhxI7y9vREYGIhmzZqhefPmejcrlgtPjcmkS5cumD59Ory9veVuhQxcYGAgQkJC0LhxY4wcORLDhg0zqL8Uq6vk5GSsXr0a58+fhxACr776KkaPHl3iqr6qyNjYGGlpabCxsQEADB48GMuXL9e7lJuoImrWrIkrV65I90I0MzPD0aNH4ebmJnNnDEKyuXjxIsaMGYNhw4bBzc2txCWQhnDXdqo68vLy8PPPP+O7777DoUOH0Lt3b4waNQo+Pj78y50qzMjICOnp6VIQsrS0REJCApdhoGdmbGyM9PR01K9fHwBgYWGBkydPSiuXy4lBSCYxMTHw9fWVVm0FHg41G8pkaaq6rly5guDgYGzevBkFBQU4c+YMJ0zLICsrC0ePHkVGRkaJq0I/+OADmboqn8eD0KP3QyR6FkZGRujVq5d0pfGuXbvQtWvXEvPOeK8xBRk5ciRatWqFH3/80SAnS1PVpVKppFBdne5abUh27dqFoUOHIicnBxYWFno/3yqVqsoHoeLvoce3ET2r4cOH6z0fNmyYTJ2UxBEhmZibm+PEiROl3niVqKIePTUWHR2NPn36YMSIEejZs2eVXrm4umrevDnefvttzJs3D2ZmZnK3U2FV+a93oheNI0Iy6dq1K4MQvRCPTpYeMWIEQkJCUK9ePbnbUrRr165hwoQJBhmCgKr91zvRi8YRIZmsXbsWX331FUaOHAl3d/cSk6X79esnU2dkaIyMjNC4cWO0atWqzNMX/Ou98gwcOBD/+te/9FaWJqKqiUFIJmWdruBkaaoIf3//cs3f4CKYlWfDhg2YM2cORowYwT90iKo4BiEioheMf+gQGQ7Ooqxibt26VSVW2iSiZ1dUVPTEB0MQUdXCEaEqQAiBiIgIbNiwAb/++issLS1x8+ZNudsiIiKq9njVmIySk5Px3XffITg4GNeuXcPQoUMRFhaGLl26yN0aEVXQ8uXL8dFHH6FWrVpYvnx5mbUTJkyopK6I6Gk4IlTJitd7Wb9+PQ4dOoRevXrB19cXQ4YMwYkTJ+Dq6ip3i0T0DJycnHDs2DHUq1evzNsGqFQqXLp0qRI7I6KyMAhVMmtra7i6umLYsGF4//33YWVlBeDhDekYhIiIiCoXJ0tXssLCQmn5emNjY7nbIaIXaN++fU+tCQwMfPmNEFG5MQhVsrS0NHz00Uf48ccfYWdnh3fffRehoaG8jw9RNdC/f38cP378ifvHjh2LrVu3VmJHRPQ0DEKVrFatWhg6dCj27t2LU6dOwcXFBRMmTMCDBw8wd+5cREZG8vJaIgP14YcfolevXjh//nyJfePGjcPmzZvx+++/y9AZET0J5whVAUVFRfjzzz+xYcMG7Nq1CxYWFvjnn3/kbouInsHIkSMRFRWFQ4cOoWHDhgAeXiX23XffISwsDF5eXjJ3SESPYhCqYm7evIktW7YgKCgIAPDjjz+iX79+Je76TERVU1FREd577z0kJSXh4MGDmDt3LtauXYvff/+dS2MQVUEMQlWcpaUlEhIS0KRJE7lbIaJyys/PR+/evXHixAnk5OTgt99+Q7du3eRui4hKwQUVqzjmVCLD8ehCip07d8bBgwfRo0cPnD59GqdPn5b2cUFFoqqDI0JVnIWFBU6cOMERISIDUNZCisW4oCJR1cIRISKiF+Ty5ctyt0BEFcTL54mIZOLu7o7U1FS52yBSNAYhIiKZJCcno6CgQO42iBSNQagSLV++HPfv3wcApKSklGsitIODA2rWrPmyWyMiIlIkTpauRDVq1MD169dhY2MDY2NjpKWlwcbGRu62iEgmvBiCSH6cLF2JtFotdu7cibfffhtCCFy9elUaIXpc48aNK7k7IiIi5eGIUCVau3Ytxo8fjwcPHjyxRggBlUrF+40RKQBHhIjkxyBUye7cuYMrV66gRYsW2LNnD+rVq1dqXcuWLSu5MyKqbAxCRPLjqbFKZmFhATc3N2zcuBEdO3aEWq2WuyUiksmaNWtga2srdxtEisYRIZnFxcUhKSkJKpUKLi4uaN26tdwtEdEzePT2Gk/DW2wQVR0MQjLJyMjAv/71L+zbtw916tSBEAI6nQ5dunRBSEgI6tevL3eLRFQBj99e4+bNm7h37x7q1KkDAMjKyoKZmRlsbGx4iw2iKoTrCMlk/PjxyM7OxunTp3H79m1kZmYiMTER2dnZ/GuRyABdvnxZesydOxevv/46kpKScPv2bdy+fRtJSUlo3bo1vvzyS7lbJaJHcERIJhqNBnv27EG7du30th89ehQ+Pj7IysqSpzEiem5NmzbFjh070KpVK73tcXFxeO+993hPMqIqhCNCMikqKip1xeiaNWuiqKhIho6I6EVJS0sr9dYZhYWFuHHjhgwdEdGTMAjJpGvXrvjkk09w/fp1adu1a9cwadIkdOvWTcbOiOh5devWDQEBATh27Jh0K51jx45h9OjR8Pb2lrk7InoUT43JJDU1Ff3790diYiLs7e2hUqmQkpICd3d3/Prrr2jUqJHcLRLRM7p58yaGDx+O8PBwaeT3wYMH6NGjB4KDg3lrHaIqhEFIZpGRkTh79iyEEHB1deVfi0TVyPnz56WfbxcXFzRv3lzulojoMQxCVZy7uzt2794Ne3t7uVshogrKz8/H5cuX0bRpU9SowfVriaoizhGq4pKTk0uddElEVde9e/cwatQomJmZ4bXXXkNKSgqAhwspLliwQObuiOhRDEJERC/YtGnTcOLECezbtw+1atWStnt7e2Pbtm0ydkZEj+NYLRHRC/bLL79g27ZtaN++PVQqlbTd1dUVFy9elLEzInocR4SIiF6wmzdvlnplWE5Ojl4wIiL5MQgREb1g7dq1Q1hYmPS8OPysW7cOnp6ecrVFRKXgqTEiohds/vz56NmzJ86cOYMHDx7gm2++wenTp3H48GHs379f7vaI6BEcEapCSru/2Jo1a2Bra1v5zRDRM+vQoQP+/vtv3Lt3D02bNkVERARsbW1x+PBhtGnTRu72iOgRXEdIJl9//TUcHR0xePBgAMCgQYOwc+dO2NnZYffu3WjZsqXMHRIREVV/HBGSyZo1a6RFEiMjIxEZGYk//vgDvXr1wqeffipzd0T0PIyNjZGRkVFi+61bt2BsbCxDR0T0JJwjJJO0tDQpCP3+++8YNGgQfHx84OjoCA8PD5m7I6Ln8aSB9ry8PJiYmFRyN0RUFgYhmVhZWSE1NRX29vYIDw/HV199BeDhP6CFhYUyd0dEz2L58uUAHl4ltn79etSuXVvaV1hYiAMHDuDVV1+Vqz0iKgWDkEwGDhwIX19fvPLKK7h16xZ69eoFAEhISECzZs1k7o6InsXSpUsBPPyDZvXq1XqnwUxMTODo6IjVq1fL1R4RlYJBSCZLly6Fo6MjUlNTsXDhQukvx7S0NAQGBsrcHRE9i8uXLwMAunTpgp9//hlWVlYyd0RET8OrxoiIiEixOCIkoy1btmDNmjW4dOkSDh8+DAcHByxbtgxOTk7o37+/3O0RUQUEBQXhyy+/hLm5OYKCgsqsXbJkSSV1RURPwyAkk1WrVmHmzJmYOHEi5s6dK02QrlOnDpYtW8YgRGRg4uPjUVBQIP33k/BeY0RVC0+NycTV1RXz5s3DgAEDYGFhgRMnTqBJkyZITExE586d8c8//8jdIhERUbXHBRVlcvnyZbRq1arEdrVajZycHBk6IiIiUh6eGpOJk5MTEhIS4ODgoLf9jz/+gKurq0xdEdGLkJOTgwULFiAqKgoZGRkoKirS23/p0iWZOiOixzEIyeTTTz/F2LFjcf/+fQghcPToUfz444+YP38+1q9fL3d7RPQcPvzwQ+zfvx9+fn5o0KAB5wURVWGcIySjdevW4auvvkJqaioAoGHDhpg9ezZGjRolc2dE9Dzq1KmDsLAwdOzYUe5WiOgpGISqgH/++QdFRUWwsbGRuxUiegGcnJywe/duuLi4yN0KET0FJ0vLpGvXrsjKygIAWFtbSyEoOzsbXbt2lbEzInpeX375JWbOnIl79+7J3QoRPQVHhGRiZGSE9PT0EqNAGRkZaNiwobQeCREZnlatWuHixYsQQsDR0RE1a9bU23/8+HGZOiOix3GydCU7efKk9N9nzpxBenq69LywsBDh4eFo2LChHK0R0QvSv39/TpAmMhAcEapkRkZG0j+QpX3pTU1NsWLFCowcObKyWyMiIlIcBqFKduXKFQgh0KRJExw9ehT169eX9pmYmMDGxgbGxsYydkhEz+rRP3QeZWlpCWdnZ0ydOhUDBw6UoTMiehIGISKiF+TXX38tdXtWVhaOHj2KjRs3YtOmTXj//fcruTMiehIGIZmdOXMGKSkpyM/P19ver18/mToiopfl22+/xebNm3HkyBG5WyGi/4dBSCaXLl3CO++8g1OnTkGlUknzhYqH1YvvRk9E1ceFCxfwxhtvIDMzU+5WiOj/4TpCMvnkk0/g5OSEGzduwMzMDKdPn8aBAwfQtm1b7Nu3T+72iOglyM3NRa1ateRug4gewcvnZXL48GHs3bsX9evXh5GREYyMjPDmm29i/vz5mDBhAuLj4+VukYhesHXr1qFVq1Zyt0FEj2AQkklhYSFq164N4OHK0tevX4ezszMcHBxw7tw5mbsjomcRFBRU6nadTodjx47h4sWLOHjwYCV3RURlYRCSiZubG06ePIkmTZrAw8MDCxcuhImJCdauXYsmTZrI3R4RPYMnjeRaWlqiZ8+eCAwMhIODQyV3RURl4WRpmfz555/IycnBwIEDcenSJfTp0wdnz55FvXr1EBISgm7dusndIhERUbXHIFSF3L59G1ZWVlyan4iIqJLwqjGZjBw5Enfu3NHbVrduXdy7d4+31yAiIqokHBGSibGxMdLS0krcff6ff/6BnZ0dHjx4IFNnREREysHJ0pUsOzsbQggIIXDnzh29NUUKCwuxe/fuEuGIiIiIXg4GoUpWp04dqFQqqFQqNG/evMR+lUqFL774QobOiIiIlIenxirZ/v37IYRA165dsXPnTtStW1faZ2JiAgcHB2i1Whk7JCIiUg4GIZlcuXIFjRs35hViREREMuJVY5Xs9u3buHr1KhwcHKQQdPr0aYwYMQKDBg3CDz/8IHOHREREysEgVMnGjh2LJUuWSM8zMjLw1ltvITY2Fnl5efD398eWLVtk7JCIiEg5GIQqWUxMDPr16yc937x5M+rWrYuEhAT8+uuvmDdvHr799lsZOyQiIlIOBqFKlp6eDicnJ+n53r178c4776BGjYcX8PXr1w8XLlyQqz0iIiJFYRCqZJaWlsjKypKeHz16FO3bt5eeq1Qq5OXlydAZERGR8jAIVbI33ngDy5cvR1FREXbs2IE7d+6ga9eu0v7z58/D3t5exg6JiIiUgwsqVrIvv/wS3t7e+P777/HgwQP8+9//hpWVlbQ/JCQEXl5eMnZIRESkHFxHSAY3b97EoUOHYGdnBw8PD719YWFhcHV11ZtHRERERC8Hg1AV5+7ujt27d/N0GRER0UvAOUJVXHJyMgoKCuRug4iIqFpiECIiIiLFYhAiIiIixWIQIiIiIsViECIiIiLFYhAiIiIixWIQquLWrFkDW1tbudsgIiKqlriOUCVavnx5uWsnTJjwEjshIiIigEGoUj2+WvTNmzdx79491KlTBwCQlZUFMzMz2NjY4NKlSzJ0SEREpCw8NVaJLl++LD3mzp2L119/HUlJSbh9+zZu376NpKQktG7dGl9++aXcrRIRESkCR4Rk0rRpU+zYsQOtWrXS2x4XF4f33nsPly9flqkzIiIi5eCIkEzS0tJKvXVGYWEhbty4IUNHREREysMgJJNu3bohICAAx44dQ/Gg3LFjxzB69Gh4e3vL3B0REZEyMAjJ5LvvvkPDhg3xxhtvoFatWlCr1fDw8ECDBg2wfv16udsjIiJSBM4Rktn58+dx9uxZCCHg4uKC5s2by90SERGRYtSQuwGlc3R0hBACTZs2RY0a/N9BRERUmXhqTCb37t3DqFGjYGZmhtdeew0pKSkAHi6kuGDBApm7IyIiUgYGIZlMmzYNJ06cwL59+1CrVi1pu7e3N7Zt2yZjZ0RERMrBczEy+eWXX7Bt2za0b98eKpVK2u7q6oqLFy/K2BkREZFycERIJjdv3oSNjU2J7Tk5OXrBiIiIiF4eBiGZtGvXDmFhYdLz4vCzbt06eHp6ytUWERGRovDUmEzmz5+Pnj174syZM3jw4AG++eYbnD59GocPH8b+/fvlbo+IiEgROCIkkw4dOuDvv//GvXv30LRpU0RERMDW1haHDx9GmzZt5G6PiIhIEbigIhERESkWR4RkYmxsjIyMjBLbb926BWNjYxk6IiIiUh4GIZk8aSAuLy8PJiYmldwNERGRMnGydCVbvnw5gIdXia1fvx61a9eW9hUWFuLAgQN49dVX5WqPiIhIUThHqJI5OTkBAK5cuYJGjRrpnQYzMTGBo6Mj5syZAw8PD7laJCIiUgwGIZl06dIFP//8M6ysrORuhYiISLEYhIiIiEixOEeoEgUFBeHLL7+Eubk5goKCyqxdsmRJJXVFRESkXAxClSg+Ph4FBQXSfz8J7zVGRERUOXhqjIiIiBSL6wgRERGRYvHUmExycnKwYMECREVFISMjA0VFRXr7L126JFNnREREysEgJJMPP/wQ+/fvh5+fHxo0aMB5QURERDLgHCGZ1KlTB2FhYejYsaPcrRARESkW5wjJxMrKCnXr1pW7DSIiIkVjEJLJl19+iZkzZ+LevXtyt0JERKRYPDUmk1atWuHixYsQQsDR0RE1a9bU23/8+HGZOiMiIlIOTpaWSf/+/TlBmoiISGYcESIiIiLF4hyhSmZkZARjY+MSDysrK7Rv3x4///yz3C0SEREpBk+NVbLQ0NBSt2dlZeHo0aMYNmwYNm3ahPfff7+SOyMiIlIenhqrYr799lts3rwZR44ckbsVIiKiao+nxqoYHx8fnD9/Xu42iIiIFIFBqIrJzc1FrVq15G6DiIhIERiEqph169ahVatWcrdBRESkCJwsXcmCgoJK3a7T6XDs2DFcvHgRBw8erOSuiIiIlImTpStZly5dSt1uaWmJV199FYGBgXBwcKjkroiIiJSJQYiIiIgUi3OEiIiISLEYhIiIiEixGISIiIhIsRiEiIiISLEYhIio0jk6OmLZsmVyt/FUycnJUKlUSEhIqNTP3bdvH1QqFbKysl7K+/v7+2PAgAEv5b2JDA2DEBE9t4oGhtjYWHz00UcvvA9nZ2eYmJjg2rVrL/y9Z8+eDZVKVeYjOTn5hXxWhw4dkJaWBo1GAwAIDg5GnTp1Xsh7A8A333yD4ODgF/Z+RIaMQYiIKk1+fj4AoH79+jAzM3uh7x0dHY379+/j/ffffym/5KdMmYK0tDTp0ahRI8yZM0dvm729fbnfr6Cg4InbTUxMYGdnB5VK9aLaBwAUFhaiqKgIGo3mhQYrIkPGIERUDRQVFeHrr79Gs2bNoFar0bhxY8ydOxcAcOrUKXTt2hWmpqaoV68ePvroI9y9e1d6befOnTFx4kS99xswYAD8/f2l546Ojpg3bx5GjhwJCwsLNG7cGGvXrpX2Ozk5AQBatWoFlUqFzp07A/j/T8HMnz8fWq0WzZs3l97v0VNjOp0OH330EWxsbGBpaYmuXbvixIkT0v4TJ06gS5cusLCwgKWlJdq0aYNjx47p9bxhwwb4+vrCz88P3333HR5fIu1pxwAAR48eRatWrVCrVi20bdsW8fHx0r7atWvDzs5OehgbG8PCwkJ6bmpqio8//viJxzB79my8/vrr+O6779CkSROo1WoIIaBSqbB69Wr0798f5ubm+Oqrr/ROje3btw8jRoyATqeTRp5mz54NAMjMzMQHH3wAKysrmJmZoVevXrhw4YL0mcUjSb///jtcXV2hVqtx5cqVEqfGhBBYuHAhmjRpAlNTU7Rs2RI7duyQ9mdmZmLo0KGoX78+TE1N8corr2Djxo0gqg4YhIiqgWnTpuHrr7/GjBkzcObMGfzwww+wtbXFvXv30LNnT1hZWSE2NhY//fQT9uzZg3HjxlX4MxYvXiyFg8DAQHz88cc4e/YsgIcBAgD27NmDtLQ0/Pzzz9LroqKikJSUhMjISPz+++8l3lcIgd69eyM9PR27d+9GXFwcWrdujW7duuH27dsAgKFDh6JRo0aIjY1FXFwcPv/8c9SsWVN6jzt37uCnn37CsGHD0L17d+Tk5GDfvn0VOoacnBz06dMHzs7OiIuLw+zZszFlypRyfW3KcwwA8L///Q/bt2/Hzp079U4jzpo1C/3798epU6cwcuRIvffu0KEDli1bBktLS2nkqbgvf39/HDt2DL/99hsOHz4MIQTefvttvdGme/fuYf78+Vi/fj1Onz4NGxubEv3/5z//wcaNG7Fq1SqcPn0akyZNwrBhw7B//34AkL6v/vjjDyQlJWHVqlWwtrYu19eGqMoTRGTQsrOzhVqtFuvWrSuxb+3atcLKykrcvXtX2hYWFiaMjIxEenq6EEIILy8v8cknn+i9rn///mL48OHScwcHBzFs2DDpeVFRkbCxsRGrVq0SQghx+fJlAUDEx8frvc/w4cOFra2tyMvL09vu4OAgli5dKoQQIioqSlhaWor79+/r1TRt2lSsWbNGCCGEhYWFCA4OfuLXYO3ateL111+Xnn/yySdi6NChJT6zrGNYs2aNqFu3rsjJyZFqVq1aVepxPcsxzJo1S9SsWVNkZGTo1QAQEydO1Nv2119/CQAiMzNTCCHExo0bhUaj0as5f/68ACD+/vtvads///wjTE1Nxfbt26XXARAJCQl6rx0+fLjo37+/EEKIu3fvilq1aolDhw7p1YwaNUoMGTJECCFE3759xYgRI0p8DYiqA950lcjAJSUlIS8vD926dSt1X8uWLWFubi5t69ixI4qKinDu3DnY2tqW+3NatGgh/bdKpYKdnR0yMjKe+jp3d3eYmJg8cX9cXBzu3r2LevXq6W3Pzc3FxYsXATy8WfGHH36ILVu2wNvbG++//z6aNm0q1W7YsAHDhg2Tng8bNgydOnVCVlaW3lyYso6h+Gv16NwlT0/Ppx5feY8BABwcHFC/fv0Sr2/btm25PudRSUlJqFGjBjw8PKRt9erVg7OzM5KSkqRtJiYmesf9uDNnzuD+/fvo3r273vb8/Hy0atUKAPDxxx/j3XffxfHjx+Hj44MBAwagQ4cOFe6ZqCpiECIycKampk/cJ/7fHJTSFG83MjIqMZ+mtIm8j56KKn59UVHRU/t7NISVpqioCA0aNCj1VFZxiJk9ezZ8fX0RFhaGP/74A7NmzUJISAjeeecdnDlzBkeOHEFsbCw+++wz6bWFhYX48ccf8fHHH5frGB7/GlREeY4BePLX4mlfo9I8qd/H/5+bmpqWOem6+PjDwsLQsGFDvX1qtRoA0KtXL1y5cgVhYWHYs2cPunXrhrFjx2LRokUV7puoquEcISID98orr8DU1BRRUVEl9rm6uiIhIQE5OTnStr///htGRkbSxOX69esjLS1N2l9YWIjExMQK9VA84lNYWFjh/lu3bo309HTUqFEDzZo103s8Og+lefPmmDRpEiIiIjBw4EBpsu6GDRvQqVMnnDhxAgkJCdJj6tSp2LBhQ7n7cHV1xYkTJ5Cbmytti4mJeaHH8KxMTExKfG1dXV3x4MEDHDlyRNp269YtnD9/Hi4uLuV+7+JJ1CkpKSV6f/QquPr168Pf3x/ff/89li1bVmKiOZGhYhAiMnC1atXCZ599hqlTp2Lz5s24ePEiYmJisGHDBgwdOhS1atXC8OHDkZiYiL/++gvjx4+Hn5+fdFqsa9euCAsLQ1hYGM6ePYvAwMAKL+RnY2MDU1NThIeH48aNG9DpdOV+rbe3Nzw9PTFgwAD8+eefSE5OxqFDh/Cf//wHx44dQ25uLsaNG4d9+/bhypUr+PvvvxEbGwsXFxcUFBRgy5YtGDJkCNzc3PQeH374IeLi4vSu3CqLr68vjIyMMGrUKJw5cwa7d+8u94jH047heTk6OuLu3buIiorCP//8g3v37uGVV15B//79ERAQgOjoaJw4cQLDhg1Dw4YN0b9//3K/t4WFBaZMmYJJkyZh06ZNuHjxIuLj4/Htt99i06ZNAICZM2fi119/xf/+9z+cPn0av//+e4XCFlFVxiBEVA3MmDEDkydPxsyZM+Hi4oLBgwcjIyMDZmZm+PPPP3H79m20a9cO7733Hrp164aVK1dKrx05ciSGDx+ODz74AF5eXnByckKXLl0q9Pk1atTA8uXLsWbNGmi12gr9IlapVNi9ezc6deqEkSNHonnz5vjXv/6F5ORk2NrawtjYGLdu3cIHH3yA5s2bY9CgQejVqxe++OIL/Pbbb7h16xbeeeedEu/7yiuvwN3dvdyjQrVr18auXbtw5swZtGrVCtOnT8fXX3/9Qo7heXXo0AFjxozB4MGDUb9+fSxcuBAAsHHjRrRp0wZ9+vSBp6cnhBDYvXt3iVOAT/Pll19i5syZmD9/PlxcXNCjRw/s2rVLWhbBxMQE06ZNQ4sWLdCpUycYGxsjJCTkuY+LqCpQiec5MU5ERERkwDgiRERERIrFIERERESKxSBEREREisUgRERERIrFIERERESKxSBEREREisUgRERERIrFIERERESKxSBEREREisUgRERERIrFIERERESK9f8BZAKSsD5nY24AAAAASUVORK5CYII=\n",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sum_death_by_country = df.groupby('countriesAndTerritories')['deaths'].sum()\n",
    "sum_death_by_country.nlargest(10).plot.bar()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "ab2aa7ba",
   "metadata": {},
   "source": [
    "# Explanation:\n",
    "The data above illustrates the top ten nations that experienced the highest amount of deaths due to COVID-19 per 50,000 deaths. The top 3 being the United States Brazil and India, the data can be used to see the countries protocols towards COVID-19 to lower cases and deaths."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "2e8fafe4",
   "metadata": {},
   "source": [
    "# Conclusion:\n",
    "The data was able to answer the questions countries who were the most and least affected by the COVID-19 pandemic. The data will also help provide and set example on what countries did to cause the specific amount of cases and deaths in their countries so to avoid repeat mistakes in future pandemics."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "57ba3a69",
   "metadata": {},
   "source": [
    "# Limitations: \n",
    "Although the data is helpful and can help prevent the same mistakes made for future pandemics, many of these countries are restricted to their laws and cutural opinions on confronting these issues so many of these countries might continue their same protcols used during COVID-19."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "eaf5a99e",
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "conda_python3",
   "language": "python",
   "name": "conda_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": "3.10.8"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}