covid19.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "international-leisure",
   "metadata": {},
   "source": [
    "# Covid-19 Analysis in Germany\n",
    "\n",
    "### Introductons\n",
    "The New `Coronavirus`, also known as `Covid-19` is an infectious disease caused by SARS-CoV-2. It is a new strain from the coronavirus family that has not been identified in humans before. Coronaviruses are a large group of viruses that infect animals. According to the US Centers for Disease and Control Prevention, they are referred to zoonotic which means in rare cases they can be transmitted from animals to humans. Coronaviruses are known to cause respiratory illnesses that range from mild illnesses like the common cold, to more severe and lethal diseases such as Severe Acute Respiratory syndrome (SARS) and Middle East Respiratory Syndrome (MERS).\n",
    "\n",
    "`Covid-19` can cause pneumonia-like symptoms. Those infected with the virus will encounter symptoms such as dry coughs, fever, lost sense of taste or/and smell, and breathing difficulties. However the symptoms can vary depending on the patient's immune system and their underlying health conditions. While some will experience common cold- like symptoms and recover in a matter of 2 weeks, other  extreme cases it may result in organ failure and death.\n",
    "\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "close-morocco",
   "metadata": {},
   "source": [
    "Though the past outbreak of the SARS virus is more deadly with 15% fatality rate, the new coronavirus is far more transmissible and has already claimed more lives. Since the outbreak was first detected in Wohan, China in December 2019.\n",
    "The outbreak was declared a global pandemic by the World Health Organization (WHO) in March 2020, affecting 219 countries and territories around the world. As a global problem with millions of people sick and a large number of new cases on a daily basis, it is realistic to encounter issues gathering such an enormous number of data, and even more so to get accurate data. It’s important to consider that many countries lack the medical supplies for a wide range of tests to achieve an accurate number of active cases. Not to mention all the people that were sick and did not get tested it is practically impossible to gather accurate data. \n",
    "\n",
    "In all of that uncertainty, to have a good look at the bigger picture you need to apply some analysis using statistical tools that are widely available these days to be used by any professionals in any field to help them to get an overview or insights from their data to be able to take decisions in the future with some level of efficiency and accuracy and minimize wrong decision as much as possible.\n",
    "\n",
    "Therefore, in this project I have taken the analysis approach to get some insights on the dataset that Robert Koch-Institut collected after almost one year from the first outbreak in Germany."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "ongoing-billion",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Starting by importing OS module to handle files on the operating system level\n",
    "import os "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "hungarian-sandwich",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['archive.zip', 'covid_de.csv']"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Checking my working folder\n",
    "os.listdir(\"./dataset/\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "attached-imperial",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['state,county,age_group,gender,date,cases,deaths,recovered\\n',\n",
       " 'Baden-Wuerttemberg,LK Alb-Donau-Kreis,00-04,F,2020-03-27,1,0,1\\n',\n",
       " 'Baden-Wuerttemberg,LK Alb-Donau-Kreis,00-04,F,2020-03-28,1,0,1\\n',\n",
       " 'Baden-Wuerttemberg,LK Alb-Donau-Kreis,00-04,F,2020-04-03,1,0,1\\n',\n",
       " 'Baden-Wuerttemberg,LK Alb-Donau-Kreis,00-04,F,2020-10-18,1,0,1\\n']"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Checking my dataset by opening the CSV\n",
    "show_file = []\n",
    "with open(\"./dataset/covid_de.csv\") as f:\n",
    "    show_file = f.readlines()\n",
    "show_file[0:5]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "confused-consultation",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 510109 entries, 0 to 510108\n",
      "Data columns (total 8 columns):\n",
      " #   Column     Non-Null Count   Dtype \n",
      "---  ------     --------------   ----- \n",
      " 0   state      510109 non-null  object\n",
      " 1   county     510109 non-null  object\n",
      " 2   age_group  507521 non-null  object\n",
      " 3   gender     498571 non-null  object\n",
      " 4   date       510109 non-null  object\n",
      " 5   cases      510109 non-null  int64 \n",
      " 6   deaths     510109 non-null  int64 \n",
      " 7   recovered  510109 non-null  int64 \n",
      "dtypes: int64(3), object(5)\n",
      "memory usage: 31.1+ MB\n",
      "None\n",
      "               cases         deaths      recovered\n",
      "count  510109.000000  510109.000000  510109.000000\n",
      "mean        4.355406       0.111972       3.793950\n",
      "std         6.665811       0.488713       6.364455\n",
      "min         0.000000       0.000000      -1.000000\n",
      "25%         1.000000       0.000000       1.000000\n",
      "50%         2.000000       0.000000       2.000000\n",
      "75%         5.000000       0.000000       4.000000\n",
      "max       206.000000      17.000000     206.000000\n"
     ]
    },
    {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>state</th>\n",
       "      <th>county</th>\n",
       "      <th>age_group</th>\n",
       "      <th>gender</th>\n",
       "      <th>date</th>\n",
       "      <th>cases</th>\n",
       "      <th>deaths</th>\n",
       "      <th>recovered</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Baden-Wuerttemberg</td>\n",
       "      <td>LK Alb-Donau-Kreis</td>\n",
       "      <td>00-04</td>\n",
       "      <td>F</td>\n",
       "      <td>2020-03-27</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Baden-Wuerttemberg</td>\n",
       "      <td>LK Alb-Donau-Kreis</td>\n",
       "      <td>00-04</td>\n",
       "      <td>F</td>\n",
       "      <td>2020-03-28</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Baden-Wuerttemberg</td>\n",
       "      <td>LK Alb-Donau-Kreis</td>\n",
       "      <td>00-04</td>\n",
       "      <td>F</td>\n",
       "      <td>2020-04-03</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Baden-Wuerttemberg</td>\n",
       "      <td>LK Alb-Donau-Kreis</td>\n",
       "      <td>00-04</td>\n",
       "      <td>F</td>\n",
       "      <td>2020-10-18</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Baden-Wuerttemberg</td>\n",
       "      <td>LK Alb-Donau-Kreis</td>\n",
       "      <td>00-04</td>\n",
       "      <td>F</td>\n",
       "      <td>2020-10-22</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                state              county age_group gender        date  cases  \\\n",
       "0  Baden-Wuerttemberg  LK Alb-Donau-Kreis     00-04      F  2020-03-27      1   \n",
       "1  Baden-Wuerttemberg  LK Alb-Donau-Kreis     00-04      F  2020-03-28      1   \n",
       "2  Baden-Wuerttemberg  LK Alb-Donau-Kreis     00-04      F  2020-04-03      1   \n",
       "3  Baden-Wuerttemberg  LK Alb-Donau-Kreis     00-04      F  2020-10-18      1   \n",
       "4  Baden-Wuerttemberg  LK Alb-Donau-Kreis     00-04      F  2020-10-22      1   \n",
       "\n",
       "   deaths  recovered  \n",
       "0       0          1  \n",
       "1       0          1  \n",
       "2       0          1  \n",
       "3       0          1  \n",
       "4       0          1  "
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Importing the most two poweful libraries to handle data Pandas and Numpy.\n",
    "import pandas as pd\n",
    "import numpy as np\n",
    "data_set = pd.read_csv(\"./dataset/covid_de.csv\")\n",
    "print(data_set.info())\n",
    "# Having a brief summary statistical look at the dataset.\n",
    "print(data_set.describe())\n",
    "# Having a brief look at the dataset after extracted to DataFrame object.\n",
    "data_set.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "stylish-cathedral",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "state            0\n",
       "county           0\n",
       "age_group     2588\n",
       "gender       11538\n",
       "date             0\n",
       "cases            0\n",
       "deaths           0\n",
       "recovered        0\n",
       "dtype: int64"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Checking if there is anull values in the dataset.\n",
    "data_set.isnull().sum()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "geological-indonesia",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "state        0\n",
       "county       0\n",
       "age_group    0\n",
       "gender       0\n",
       "date         0\n",
       "cases        0\n",
       "deaths       0\n",
       "recovered    0\n",
       "dtype: int64"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "\"\"\" After checking the null values in the dataset, I found out they are empty values which can't be \n",
    "    used, I have decided to discard them. \"\"\"\n",
    "data_set = data_set.dropna()\n",
    "data_set.isnull().sum()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "furnished-proxy",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Creating a generic function to extract categories from any dataframe.\n",
    "def num_of_categories(data_frame, column_name):\n",
    "    \"\"\"\" The function takes two arguments \"data_farme\" and \"column_name\" and it \n",
    "            returns a list of all the unique values in that column. \"\"\"\n",
    "    num_of_cat = set()\n",
    "    for num in data_frame[column_name]:\n",
    "        num_of_cat.add(str(num))\n",
    "    num_of_cat = list(num_of_cat)\n",
    "    num_of_cat.sort()\n",
    "    return num_of_cat"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "dried-princess",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['Baden-Wuerttemberg',\n",
       " 'Bayern',\n",
       " 'Berlin',\n",
       " 'Brandenburg',\n",
       " 'Bremen',\n",
       " 'Hamburg',\n",
       " 'Hessen',\n",
       " 'Mecklenburg-Vorpommern',\n",
       " 'Niedersachsen',\n",
       " 'Nordrhein-Westfalen',\n",
       " 'Rheinland-Pfalz',\n",
       " 'Saarland',\n",
       " 'Sachsen',\n",
       " 'Sachsen-Anhalt',\n",
       " 'Schleswig-Holstein',\n",
       " 'Thueringen']"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Extracting all the states names from the dataframe.\n",
    "num_of_states = num_of_categories(data_set, \"state\")\n",
    "num_of_states"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "racial-chest",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['00-04', '05-14', '15-34', '35-59', '60-79', '80-99']"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Extracting all the age-groups from the dataframe.\n",
    "num_of_age_group = num_of_categories(data_set, \"age_group\")\n",
    "num_of_age_group"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "minimal-suspect",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'Baden-Wuerttemberg': [4634, 15619, 88925, 112866, 44215, 26883],\n",
       " 'Bayern': [7911, 24415, 120784, 151402, 60289, 38296],\n",
       " 'Berlin': [2026, 7115, 39629, 43939, 16157, 10147],\n",
       " 'Brandenburg': [977, 2913, 13909, 28392, 12848, 9146],\n",
       " 'Bremen': [264, 933, 5787, 5932, 2023, 1049],\n",
       " 'Hamburg': [899, 2841, 16174, 16879, 5626, 3928],\n",
       " 'Hessen': [2753, 8814, 52821, 65187, 24846, 17415],\n",
       " 'Mecklenburg-Vorpommern': [300, 1139, 4325, 7668, 3824, 2678],\n",
       " 'Niedersachsen': [3150, 9333, 44797, 52109, 19842, 13473],\n",
       " 'Nordrhein-Westfalen': [9849, 30389, 152140, 184382, 67640, 41564],\n",
       " 'Rheinland-Pfalz': [1696, 5073, 27543, 33941, 14072, 10192],\n",
       " 'Saarland': [562, 1505, 7073, 9137, 4490, 3027],\n",
       " 'Sachsen': [1558, 6199, 36509, 71859, 36181, 27818],\n",
       " 'Sachsen-Anhalt': [730, 2308, 10671, 20031, 10211, 7612],\n",
       " 'Schleswig-Holstein': [765, 2142, 10766, 13199, 5280, 3964],\n",
       " 'Thueringen': [855, 2823, 13371, 26188, 13144, 9184]}"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Creating a generic function sum all the data for all the states in specific case in all age_group.\n",
    "def sum_cases(file_path, state, case_param, age):\n",
    "    \"\"\" The function takes four arguments \"file_path\" for the CSV that has the dataset,\n",
    "        \"state\" which a list of all the states, \"case_param\" which is the case you want \n",
    "        e.g.(\"deaths\") which also a column name and the \"age\" which is a list of all the\n",
    "        age groups in the dataset. It returns a dictionary of all the states as keys and \n",
    "        sum of all cases in all the age groups as a list of values. \"\"\"\n",
    "    \n",
    "    state_data = pd.read_csv(file_path)\n",
    "    states_dict = {}\n",
    "    for i in state:\n",
    "        states_dict[i] = []\n",
    "        for j in age:\n",
    "            states_dict[i].append(state_data[np.logical_and(state_data[\"state\"]==i,\n",
    "                                      state_data[\"age_group\"]==j)][case_param].sum())\n",
    "    return states_dict\n",
    "# Getting the sum of all the cases around Germany.\n",
    "states_all_cases = sum_cases(\"./dataset/covid_de.csv\", num_of_states, \"cases\", num_of_age_group)\n",
    "states_all_cases"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "sustained-bullet",
   "metadata": {},
   "outputs": [
    {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Baden-Wuerttemberg</th>\n",
       "      <th>Bayern</th>\n",
       "      <th>Berlin</th>\n",
       "      <th>Brandenburg</th>\n",
       "      <th>Bremen</th>\n",
       "      <th>Hamburg</th>\n",
       "      <th>Hessen</th>\n",
       "      <th>Mecklenburg-Vorpommern</th>\n",
       "      <th>Niedersachsen</th>\n",
       "      <th>Nordrhein-Westfalen</th>\n",
       "      <th>Rheinland-Pfalz</th>\n",
       "      <th>Saarland</th>\n",
       "      <th>Sachsen</th>\n",
       "      <th>Sachsen-Anhalt</th>\n",
       "      <th>Schleswig-Holstein</th>\n",
       "      <th>Thueringen</th>\n",
       "      <th>age_group</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>4634</td>\n",
       "      <td>7911</td>\n",
       "      <td>2026</td>\n",
       "      <td>977</td>\n",
       "      <td>264</td>\n",
       "      <td>899</td>\n",
       "      <td>2753</td>\n",
       "      <td>300</td>\n",
       "      <td>3150</td>\n",
       "      <td>9849</td>\n",
       "      <td>1696</td>\n",
       "      <td>562</td>\n",
       "      <td>1558</td>\n",
       "      <td>730</td>\n",
       "      <td>765</td>\n",
       "      <td>855</td>\n",
       "      <td>00-04</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>15619</td>\n",
       "      <td>24415</td>\n",
       "      <td>7115</td>\n",
       "      <td>2913</td>\n",
       "      <td>933</td>\n",
       "      <td>2841</td>\n",
       "      <td>8814</td>\n",
       "      <td>1139</td>\n",
       "      <td>9333</td>\n",
       "      <td>30389</td>\n",
       "      <td>5073</td>\n",
       "      <td>1505</td>\n",
       "      <td>6199</td>\n",
       "      <td>2308</td>\n",
       "      <td>2142</td>\n",
       "      <td>2823</td>\n",
       "      <td>05-14</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>88925</td>\n",
       "      <td>120784</td>\n",
       "      <td>39629</td>\n",
       "      <td>13909</td>\n",
       "      <td>5787</td>\n",
       "      <td>16174</td>\n",
       "      <td>52821</td>\n",
       "      <td>4325</td>\n",
       "      <td>44797</td>\n",
       "      <td>152140</td>\n",
       "      <td>27543</td>\n",
       "      <td>7073</td>\n",
       "      <td>36509</td>\n",
       "      <td>10671</td>\n",
       "      <td>10766</td>\n",
       "      <td>13371</td>\n",
       "      <td>15-34</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>112866</td>\n",
       "      <td>151402</td>\n",
       "      <td>43939</td>\n",
       "      <td>28392</td>\n",
       "      <td>5932</td>\n",
       "      <td>16879</td>\n",
       "      <td>65187</td>\n",
       "      <td>7668</td>\n",
       "      <td>52109</td>\n",
       "      <td>184382</td>\n",
       "      <td>33941</td>\n",
       "      <td>9137</td>\n",
       "      <td>71859</td>\n",
       "      <td>20031</td>\n",
       "      <td>13199</td>\n",
       "      <td>26188</td>\n",
       "      <td>35-59</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>44215</td>\n",
       "      <td>60289</td>\n",
       "      <td>16157</td>\n",
       "      <td>12848</td>\n",
       "      <td>2023</td>\n",
       "      <td>5626</td>\n",
       "      <td>24846</td>\n",
       "      <td>3824</td>\n",
       "      <td>19842</td>\n",
       "      <td>67640</td>\n",
       "      <td>14072</td>\n",
       "      <td>4490</td>\n",
       "      <td>36181</td>\n",
       "      <td>10211</td>\n",
       "      <td>5280</td>\n",
       "      <td>13144</td>\n",
       "      <td>60-79</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>26883</td>\n",
       "      <td>38296</td>\n",
       "      <td>10147</td>\n",
       "      <td>9146</td>\n",
       "      <td>1049</td>\n",
       "      <td>3928</td>\n",
       "      <td>17415</td>\n",
       "      <td>2678</td>\n",
       "      <td>13473</td>\n",
       "      <td>41564</td>\n",
       "      <td>10192</td>\n",
       "      <td>3027</td>\n",
       "      <td>27818</td>\n",
       "      <td>7612</td>\n",
       "      <td>3964</td>\n",
       "      <td>9184</td>\n",
       "      <td>80-99</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   Baden-Wuerttemberg  Bayern  Berlin  Brandenburg  Bremen  Hamburg  Hessen  \\\n",
       "0                4634    7911    2026          977     264      899    2753   \n",
       "1               15619   24415    7115         2913     933     2841    8814   \n",
       "2               88925  120784   39629        13909    5787    16174   52821   \n",
       "3              112866  151402   43939        28392    5932    16879   65187   \n",
       "4               44215   60289   16157        12848    2023     5626   24846   \n",
       "5               26883   38296   10147         9146    1049     3928   17415   \n",
       "\n",
       "   Mecklenburg-Vorpommern  Niedersachsen  Nordrhein-Westfalen  \\\n",
       "0                     300           3150                 9849   \n",
       "1                    1139           9333                30389   \n",
       "2                    4325          44797               152140   \n",
       "3                    7668          52109               184382   \n",
       "4                    3824          19842                67640   \n",
       "5                    2678          13473                41564   \n",
       "\n",
       "   Rheinland-Pfalz  Saarland  Sachsen  Sachsen-Anhalt  Schleswig-Holstein  \\\n",
       "0             1696       562     1558             730                 765   \n",
       "1             5073      1505     6199            2308                2142   \n",
       "2            27543      7073    36509           10671               10766   \n",
       "3            33941      9137    71859           20031               13199   \n",
       "4            14072      4490    36181           10211                5280   \n",
       "5            10192      3027    27818            7612                3964   \n",
       "\n",
       "   Thueringen age_group  \n",
       "0         855     00-04  \n",
       "1        2823     05-14  \n",
       "2       13371     15-34  \n",
       "3       26188     35-59  \n",
       "4       13144     60-79  \n",
       "5        9184     80-99  "
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Extract the sum of all the cases into a dataframe.\n",
    "states_all_cases_frame = pd.DataFrame(states_all_cases)\n",
    "# Adding a new column to the dataframe to display all the age groups.\n",
    "states_all_cases_frame[\"age_group\"] = num_of_age_group\n",
    "states_all_cases_frame"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "certified-warning",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Baden-Wuerttemberg</th>\n",
       "      <th>Bayern</th>\n",
       "      <th>Berlin</th>\n",
       "      <th>Brandenburg</th>\n",
       "      <th>Bremen</th>\n",
       "      <th>Hamburg</th>\n",
       "      <th>Hessen</th>\n",
       "      <th>Mecklenburg-Vorpommern</th>\n",
       "      <th>Niedersachsen</th>\n",
       "      <th>Nordrhein-Westfalen</th>\n",
       "      <th>Rheinland-Pfalz</th>\n",
       "      <th>Saarland</th>\n",
       "      <th>Sachsen</th>\n",
       "      <th>Sachsen-Anhalt</th>\n",
       "      <th>Schleswig-Holstein</th>\n",
       "      <th>Thueringen</th>\n",
       "      <th>age_group</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>3</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
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       "      <td>3</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>00-04</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>05-14</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>9</td>\n",
       "      <td>13</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>11</td>\n",
       "      <td>0</td>\n",
       "      <td>7</td>\n",
       "      <td>13</td>\n",
       "      <td>6</td>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>4</td>\n",
       "      <td>15-34</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>218</td>\n",
       "      <td>295</td>\n",
       "      <td>84</td>\n",
       "      <td>64</td>\n",
       "      <td>16</td>\n",
       "      <td>47</td>\n",
       "      <td>154</td>\n",
       "      <td>8</td>\n",
       "      <td>118</td>\n",
       "      <td>455</td>\n",
       "      <td>76</td>\n",
       "      <td>31</td>\n",
       "      <td>137</td>\n",
       "      <td>44</td>\n",
       "      <td>33</td>\n",
       "      <td>50</td>\n",
       "      <td>35-59</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>1808</td>\n",
       "      <td>2721</td>\n",
       "      <td>676</td>\n",
       "      <td>579</td>\n",
       "      <td>82</td>\n",
       "      <td>311</td>\n",
       "      <td>1299</td>\n",
       "      <td>121</td>\n",
       "      <td>869</td>\n",
       "      <td>3043</td>\n",
       "      <td>674</td>\n",
       "      <td>184</td>\n",
       "      <td>1572</td>\n",
       "      <td>477</td>\n",
       "      <td>230</td>\n",
       "      <td>572</td>\n",
       "      <td>60-79</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>5025</td>\n",
       "      <td>7360</td>\n",
       "      <td>1509</td>\n",
       "      <td>1645</td>\n",
       "      <td>169</td>\n",
       "      <td>711</td>\n",
       "      <td>3377</td>\n",
       "      <td>322</td>\n",
       "      <td>2291</td>\n",
       "      <td>7299</td>\n",
       "      <td>1768</td>\n",
       "      <td>521</td>\n",
       "      <td>4576</td>\n",
       "      <td>1191</td>\n",
       "      <td>623</td>\n",
       "      <td>1568</td>\n",
       "      <td>80-99</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   Baden-Wuerttemberg  Bayern  Berlin  Brandenburg  Bremen  Hamburg  Hessen  \\\n",
       "0                   3       1       0            0       0        1       0   \n",
       "1                   0       1       0            0       1        0       0   \n",
       "2                   9      13       1            0       0        3      11   \n",
       "3                 218     295      84           64      16       47     154   \n",
       "4                1808    2721     676          579      82      311    1299   \n",
       "5                5025    7360    1509         1645     169      711    3377   \n",
       "\n",
       "   Mecklenburg-Vorpommern  Niedersachsen  Nordrhein-Westfalen  \\\n",
       "0                       0              0                    3   \n",
       "1                       0              0                    2   \n",
       "2                       0              7                   13   \n",
       "3                       8            118                  455   \n",
       "4                     121            869                 3043   \n",
       "5                     322           2291                 7299   \n",
       "\n",
       "   Rheinland-Pfalz  Saarland  Sachsen  Sachsen-Anhalt  Schleswig-Holstein  \\\n",
       "0                1         0        0               0                   0   \n",
       "1                0         0        0               0                   0   \n",
       "2                6         1        3               0                   0   \n",
       "3               76        31      137              44                  33   \n",
       "4              674       184     1572             477                 230   \n",
       "5             1768       521     4576            1191                 623   \n",
       "\n",
       "   Thueringen age_group  \n",
       "0           0     00-04  \n",
       "1           0     05-14  \n",
       "2           4     15-34  \n",
       "3          50     35-59  \n",
       "4         572     60-79  \n",
       "5        1568     80-99  "
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Getting the sum of all the daeth cases around Germany.\n",
    "states_death_cases_age = sum_cases(\"./dataset/covid_de.csv\", num_of_states, \"deaths\", num_of_age_group)\n",
    "# Extract the sum of the death cases into a dataframe.\n",
    "states_death_cases_age_frame = pd.DataFrame(states_death_cases_age)\n",
    "# Adding a new column to the dataframe to display all the age groups.\n",
    "states_death_cases_age_frame[\"age_group\"]= num_of_age_group\n",
    "states_death_cases_age_frame"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "experienced-roller",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
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       "\n",
       "    .dataframe tbody tr th {\n",
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       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Baden-Wuerttemberg</th>\n",
       "      <th>Bayern</th>\n",
       "      <th>Berlin</th>\n",
       "      <th>Brandenburg</th>\n",
       "      <th>Bremen</th>\n",
       "      <th>Hamburg</th>\n",
       "      <th>Hessen</th>\n",
       "      <th>Mecklenburg-Vorpommern</th>\n",
       "      <th>Niedersachsen</th>\n",
       "      <th>Nordrhein-Westfalen</th>\n",
       "      <th>Rheinland-Pfalz</th>\n",
       "      <th>Saarland</th>\n",
       "      <th>Sachsen</th>\n",
       "      <th>Sachsen-Anhalt</th>\n",
       "      <th>Schleswig-Holstein</th>\n",
       "      <th>Thueringen</th>\n",
       "      <th>age_group</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>4223</td>\n",
       "      <td>7209</td>\n",
       "      <td>1853</td>\n",
       "      <td>790</td>\n",
       "      <td>237</td>\n",
       "      <td>764</td>\n",
       "      <td>2471</td>\n",
       "      <td>254</td>\n",
       "      <td>2840</td>\n",
       "      <td>9009</td>\n",
       "      <td>1505</td>\n",
       "      <td>517</td>\n",
       "      <td>1340</td>\n",
       "      <td>592</td>\n",
       "      <td>652</td>\n",
       "      <td>745</td>\n",
       "      <td>00-04</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>14538</td>\n",
       "      <td>22699</td>\n",
       "      <td>6699</td>\n",
       "      <td>2575</td>\n",
       "      <td>850</td>\n",
       "      <td>2566</td>\n",
       "      <td>8129</td>\n",
       "      <td>1002</td>\n",
       "      <td>8593</td>\n",
       "      <td>28387</td>\n",
       "      <td>4581</td>\n",
       "      <td>1383</td>\n",
       "      <td>5649</td>\n",
       "      <td>1934</td>\n",
       "      <td>1881</td>\n",
       "      <td>2602</td>\n",
       "      <td>05-14</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>82141</td>\n",
       "      <td>111117</td>\n",
       "      <td>36764</td>\n",
       "      <td>12200</td>\n",
       "      <td>5254</td>\n",
       "      <td>14284</td>\n",
       "      <td>48117</td>\n",
       "      <td>3790</td>\n",
       "      <td>41544</td>\n",
       "      <td>139366</td>\n",
       "      <td>24547</td>\n",
       "      <td>6483</td>\n",
       "      <td>31849</td>\n",
       "      <td>8713</td>\n",
       "      <td>9400</td>\n",
       "      <td>12024</td>\n",
       "      <td>15-34</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>103379</td>\n",
       "      <td>138376</td>\n",
       "      <td>40120</td>\n",
       "      <td>24726</td>\n",
       "      <td>5343</td>\n",
       "      <td>14734</td>\n",
       "      <td>58692</td>\n",
       "      <td>6577</td>\n",
       "      <td>47814</td>\n",
       "      <td>167601</td>\n",
       "      <td>29813</td>\n",
       "      <td>8266</td>\n",
       "      <td>62764</td>\n",
       "      <td>15723</td>\n",
       "      <td>11364</td>\n",
       "      <td>23203</td>\n",
       "      <td>35-59</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>38357</td>\n",
       "      <td>51825</td>\n",
       "      <td>13537</td>\n",
       "      <td>10246</td>\n",
       "      <td>1677</td>\n",
       "      <td>4483</td>\n",
       "      <td>20520</td>\n",
       "      <td>3058</td>\n",
       "      <td>16879</td>\n",
       "      <td>57136</td>\n",
       "      <td>11440</td>\n",
       "      <td>3844</td>\n",
       "      <td>29567</td>\n",
       "      <td>7258</td>\n",
       "      <td>4064</td>\n",
       "      <td>10911</td>\n",
       "      <td>60-79</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>18733</td>\n",
       "      <td>26659</td>\n",
       "      <td>6998</td>\n",
       "      <td>5786</td>\n",
       "      <td>671</td>\n",
       "      <td>2587</td>\n",
       "      <td>11382</td>\n",
       "      <td>1742</td>\n",
       "      <td>9126</td>\n",
       "      <td>28216</td>\n",
       "      <td>6546</td>\n",
       "      <td>2146</td>\n",
       "      <td>18729</td>\n",
       "      <td>4229</td>\n",
       "      <td>2201</td>\n",
       "      <td>6245</td>\n",
       "      <td>80-99</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   Baden-Wuerttemberg  Bayern  Berlin  Brandenburg  Bremen  Hamburg  Hessen  \\\n",
       "0                4223    7209    1853          790     237      764    2471   \n",
       "1               14538   22699    6699         2575     850     2566    8129   \n",
       "2               82141  111117   36764        12200    5254    14284   48117   \n",
       "3              103379  138376   40120        24726    5343    14734   58692   \n",
       "4               38357   51825   13537        10246    1677     4483   20520   \n",
       "5               18733   26659    6998         5786     671     2587   11382   \n",
       "\n",
       "   Mecklenburg-Vorpommern  Niedersachsen  Nordrhein-Westfalen  \\\n",
       "0                     254           2840                 9009   \n",
       "1                    1002           8593                28387   \n",
       "2                    3790          41544               139366   \n",
       "3                    6577          47814               167601   \n",
       "4                    3058          16879                57136   \n",
       "5                    1742           9126                28216   \n",
       "\n",
       "   Rheinland-Pfalz  Saarland  Sachsen  Sachsen-Anhalt  Schleswig-Holstein  \\\n",
       "0             1505       517     1340             592                 652   \n",
       "1             4581      1383     5649            1934                1881   \n",
       "2            24547      6483    31849            8713                9400   \n",
       "3            29813      8266    62764           15723               11364   \n",
       "4            11440      3844    29567            7258                4064   \n",
       "5             6546      2146    18729            4229                2201   \n",
       "\n",
       "   Thueringen age_group  \n",
       "0         745     00-04  \n",
       "1        2602     05-14  \n",
       "2       12024     15-34  \n",
       "3       23203     35-59  \n",
       "4       10911     60-79  \n",
       "5        6245     80-99  "
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Getting the sum of all the recovery cases around Germany.\n",
    "states_recovered_cases_age = sum_cases(\"./dataset/covid_de.csv\", num_of_states, \"recovered\", num_of_age_group)\n",
    "# Extract the sum of all the recovered cases into a dataframe.\n",
    "states_recovered_cases_age_frame = pd.DataFrame(states_recovered_cases_age)\n",
    "# Adding a new column to the dataframe to display all the age groups.\n",
    "states_recovered_cases_age_frame[\"age_group\"]= num_of_age_group\n",
    "states_recovered_cases_age_frame"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "expired-coupon",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 648x360 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "\"\"\" Here we come to the visualization part \"one chart is better than a thousand word\" they say.\n",
    "    I have started with importing two of the most powerful visualization tools to apply which are \n",
    "    matplotlib and seaborn. \"\"\"\n",
    "import matplotlib\n",
    "import matplotlib.pyplot as plt\n",
    "import seaborn as sns\n",
    "# Getting the style of the charts ready.\n",
    "%matplotlib inline\n",
    "sns.set_style(\"darkgrid\")\n",
    "matplotlib.rcParams['font.size'] = 14\n",
    "matplotlib.rcParams['figure.figsize'] = (9, 5)\n",
    "# Displayed below all the death cases across age groups in Bayern as an example.\n",
    "plt.bar(states_death_cases_age_frame[\"age_group\"],states_death_cases_age_frame[\"Bayern\"])\n",
    "plt.title(\"Bayern Death Cases\")\n",
    "plt.xlabel(\"Age Group\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "vital-rider",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 648x360 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Displayed below all the recovered cases across age groups in Bayern as an example.\n",
    "plt.bar(states_recovered_cases_age_frame[\"age_group\"],states_recovered_cases_age_frame[\"Bayern\"])\n",
    "plt.title(\"Bayern Recovered Cases\")\n",
    "plt.xlabel(\"Age Group\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "quick-costa",
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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bY+vWrbCysuLxO04IPwQMnfxHCCGEEBlFa3QIIYQQIrMo0SGEEEKIzKJEhxBCCCEyixIdQgghhMgsSnQIIYQQIrOqtb381KlTWLRokdi13r17Izg4GK9fv4a3tzfu3r2LZs2awcPDQ+xAvZiYGKxatQovX75Ex44dsXLlSrRs2ZJtDw0Nxc6dO/Hx40f88ssv8Pb2hqqqKoCSAmS+vr44f/48lJSUMHnyZEyfPp39t1XF/pri4mKIRNLfbCYvL5B4PygmxaxN8SgmxaSYFLM6FBXlv9pWrUTn6dOn6Nu3L1skCwCUlZXBMAxcXFygp6eHiIgIXL58Ga6urjh9+jR0dXWRnp6OWbNmwcXFBT179sTWrVvh4uKCU6dOQU5ODlFRUdi4cSPWrl0LTU1NeHp6wt/fHytWrAAArF27FnFxcdi7dy/evHkDNzc3aGtrY+DAgVXGroxIxCA7+9sPC+SaurqqxPtBMSlmbYpHMSkmxaSY1aGhUf+rbdWaukpJSUH79u2hoaHB/mnQoAFiYmLw/PlzrFixAm3btoWzszPMzMwQEREBADh8+DD09fUxffp0tG3bFn5+fkhPT0dMTAyAkkPqJkyYgN69e8PY2BjLly9HZGQkPn36hLy8PBw+fBheXl4wMjJCnz59MG3aNLaaa1WxCSGEEEKqleg8ffoUrVu3Lnc9Pj4eHTp0QL169dhr5ubm7Dkv8fHxsLS0ZNtUVFRgaGiIuLg4iEQiJCYmirWbmppCJBLh0aNHSEpKglAoFDsPx9zcHImJiSgqKqoyNiGEEEJIlYmOUChEWloa/vrrL/Tr1w99+vTBunXrIBQKkZmZWe4E48aNG+PNmzcA8NX2jIwM5OTkoKCgQKxdQUEB6urqePPmDTIzM6GmpgZlZWW2vUmTJigsLMSHDx+qjE0IIYQQUuUandTUVBQVFUFVVRWbN2/Gy5cvsWrVKnz69AkFBQVQVFQUe7ySkhIKCwsBlBwWWHpWS9l2oVCIz58/s19X1F5UVFRhG1CSfOXn51cauzLy8gKoq6tW+Ti+ycvLSbwfFJNi1qZ4FJNiUkyK+b2qTHTatWuHmJgY9jRifX19MAyDhQsXYuTIkcjNzRV7vFAoRJ06dQCULFgWCoXl2tXV1dmRmora69SpA4FAUGEbUDIFpqysXGnsytBiZIpJMWtHPIpJMSkmxayO716MXJrklNLT00NhYSE0NTWRmZkp1vbu3TtoaGgAALS0tL7aXprsvHv3jm0rKipCdnY2NDU1oaWlhZycHLFkJzMzE0pKSlBTU6v0uQkhhBBCgGokOlFRUejcubNYwvHw4UM0aNAApqamSEpKQl7e/2VzsbGxMDU1BQCYmJjg7t27bFt+fj4ePnwIU1NTyMnJwdjYGLGxsWz7vXv3IC8vDwMDAxgYGEBRURFxcXFiz21oaAgFBQWYmJhUGpsQQgghpMpEx9LSEgzDYOnSpXj+/DmuXLmCtWvXYurUqbCysoK2tjY8PDyQnJyMkJAQxMfHY+TIkQAABwcHxMfHY9u2bXj69CmWLFkCbW1t2NjYAADGjRuHPXv2ICoqComJifDx8YGDgwPq1q0LFRUVDB06FD4+PkhISMClS5ewZ88eODo6AkCVsQkhhBBCqkx0GjZsiN27d+P169cYPnw4vL29MWbMGMyYMQPy8vIIDg7Ghw8fMHz4cJw4cQJbtmyBjo4OAEBHRwdBQUE4ceIEHBwc8O7dOwQHB0NOriTswIEDMWvWLCxfvhxTpkyBkZERPDw82Nienp4wNjbGpEmTsGzZMsyePRsDBgwAgCpjE0IIIYQIGIaRfu1mCSssFNWIxVM/ysIxiik7MX+E10gxKSbFrNkxK/Ldi5EJIYQQQmqjap11RQgh5NvVa6ACFeXq32Yr+1T6pfyCIuTm5P+XbhHyQ6FEhxBCeKKirIBWHmd4ee4X/gORW/XDCPnh0dQVIYQQQmQWJTqEEEIIkVmU6BBCCCFEZlGiQwghhBCZRYkOIYQQQmQWJTqEEEIIkVmU6BBCCCFEZlGiQwghhBCZRYkOIYQQQmQWJTqEEEIIkVmU6BBCCCFEZlGiQwghhBCZRYkOIYQQQmQWJTqEEEIIkVmU6BBCCCFEZlGiQwghhBCZRYkOIYQQQmQWJTqEEEIIkVmU6BBCCCFEZlGiQwghhBCZRYkOIYQQQmQWJTqEEEIIkVmU6BBCCCFEZlGiQwghhBCZRYkOIYQQQmQWJTqEEEIIkVmU6BBCCCFEZlGiQwghhBCZRYkOIYQQQmQWJTqEEEIIkVmU6BBCCCFEZlGiQwghhBCZRYkOIYQQQmQWJTqEEEIIkVmU6BBCCCFEZlGiQwghhBCZRYkOIYQQQmQWJTqEEEIIkVnflOgsWbIEEydOZL9+/fo1nJycYGpqCjs7O1y9elXs8TExMRg8eDBMTEwwceJEpKamirWHhoaiW7duMDMzg6enJ/Ly8tg2oVAIb29vWFpaokuXLti5c6fYv60qNiGEEEJItROd6OhoREREsF8zDAMXFxeoq6sjIiICw4YNg6urK9LS0gAA6enpmDVrFoYMGYKjR4+iSZMmcHFxQXFxMQAgKioKGzduxLJly3DgwAEkJibC39+fff61a9ciLi4Oe/fuhY+PD7Zt24YzZ85UKzYhhBBCCFDNRCcvLw/e3t74+eef2WsxMTF4/vw5VqxYgbZt28LZ2RlmZmZsMnT48GHo6+tj+vTpaNu2Lfz8/JCeno6YmBgAwP79+zFhwgT07t0bxsbGWL58OSIjI/Hp0yfk5eXh8OHD8PLygpGREfr06YNp06bh4MGD1YpNCCGEEAJUM9EJDAyElZUVrKys2Gvx8fHo0KED6tWrx14zNzfHvXv32HZLS0u2TUVFBYaGhoiLi4NIJEJiYqJYu6mpKUQiER49eoSkpCQIhUKYm5uLPXdiYiKKioqqjE0IIYQQAgAKVT0gLi4O58+fx+nTp7Fnzx72emZmJjQ1NcUe27hxY7x586bS9oyMDOTk5KCgoECsXUFBAerq6njz5g0UFRWhpqYGZWVltr1JkyYoLCzEhw8fqoz9I6nXQAUqylX+N4rR0Khf7cfmFxQhNyf/W7tFCCGE1AiVvkMKhUIsWbIEXl5eUFNTE2vLz8+HoqKi2DUlJSUUFhay7UpKSuXahUIhPn/+zH5dUXtRUVGFbaV9qip2VeTlBVBXV63WY/kkLy/33f1QVJRHK48zHPWovBf+A6HwnX3k4nVSzJoR80d4jdKK+V98bx9/lO8txZStmN+q0kRn69ataNmyJezs7Mq1KSsrIzc3V+yaUChEnTp12HahUFiuXV1dnR2pqai9Tp06EAgEFbYBJVNgVcWuikjEIDs7r+oH8kxdXfW7+/EtozP/1ff2kYvXSTFrRswf4TVyGZPv30/63aSYP2LMilT2u1ZponPq1ClkZmbCzMwMAFBYWAiRSAQzMzPMmDEDSUlJYo9/9+4dNDQ0AABaWlrIzMws196uXTs22Xn37h1++uknAEBRURGys7OhqakJOTk55OTkQCgUsiM5mZmZUFJSgpqaGrS0tCqNTQghhBACVLEYOTQ0FKdPn8bx48dx/PhxjBw5EkZGRjh+/DhMTEyQlJQkVvsmNjYWpqamAAATExPcvXuXbcvPz8fDhw9hamoKOTk5GBsbIzY2lm2/d+8e5OXlYWBgAAMDAygqKiIuLk7suQ0NDaGgoFBlbEIIIYQQoIpEp3nz5mjZsiX7p0GDBqhTpw5atmwJKysraGtrw8PDA8nJyQgJCUF8fDxGjhwJAHBwcEB8fDy2bduGp0+fYsmSJdDW1oaNjQ0AYNy4cdizZw+ioqKQmJgIHx8fODg4oG7dulBRUcHQoUPh4+ODhIQEXLp0CXv27IGjoyMAVBmbEEIIIQT4jiMg5OXlERwcjA8fPmD48OE4ceIEtmzZAh0dHQCAjo4OgoKCcOLECTg4OODdu3cIDg6GnFxJyIEDB2LWrFlYvnw5pkyZAiMjI3h4eLDP7+npCWNjY0yaNAnLli3D7NmzMWDAgGrFJoQQQggBAAHDMIy0OyFphYWiGrF4iqvFyHzvusrM/Phdz/GjLJD7EWL+CK+Ry5h8/n7S7ybF/FFjVqSyxch0qCchhBBCZBYlOoQQQgiRWZToEEIIIURmUaJDCCGEEJlFiQ4hhBBCZBYlOoQQQgiRWZToEEIIIURmUaJDCCGEEJlFiQ4hhBBCZBYlOoQQQgiRWZToEEIIIURmUaJDCCGEEJlFiQ4hhBBCZBYlOoQQQgiRWZToEEIIIURmUaJDCCGEEJlFiQ4hhBBCZBYlOoQQQgiRWZToEEIIIURmUaJDCCGEEJlFiQ4hhBBCZBYlOoQQQgiRWZToEEIIIURmUaJDCCGEEJlFiQ4hhBBCZBYlOoQQQgiRWZToEEIIIURmUaJDCCGEEJlFiQ4hhBBCZBYlOoQQQgiRWZToEEIIIURmUaJDCCGEEJlFiQ4hhBBCZBYlOoQQQgiRWZToEEIIIURmUaJDCCGEEJlFiQ4hhBBCZBYlOoQQQgiRWZToEEIIIURmUaJDCCGEEJlFiQ4hhBBCZBYlOoQQQgiRWdVKdFJSUjB58mSYmZmhZ8+e2LVrF9v2+vVrODk5wdTUFHZ2drh69arYv42JicHgwYNhYmKCiRMnIjU1Vaw9NDQU3bp1g5mZGTw9PZGXl8e2CYVCeHt7w9LSEl26dMHOnTvF/m1VsQkhhBDyY6sy0SksLMT06dPRrFkzHD9+HEuXLkVwcDBOnjwJhmHg4uICdXV1REREYNiwYXB1dUVaWhoAID09HbNmzcKQIUNw9OhRNGnSBC4uLiguLgYAREVFYePGjVi2bBkOHDiAxMRE+Pv7s7HXrl2LuLg47N27Fz4+Pti2bRvOnDkDAFXGJoQQQgipMtHJyMhAx44dsWzZMrRs2RI9e/ZE586dcfv2bcTExOD58+dYsWIF2rZtC2dnZ5iZmSEiIgIAcPjwYejr62P69Olo27Yt/Pz8kJ6ejpiYGADA/v37MWHCBPTu3RvGxsZYvnw5IiMj8enTJ+Tl5eHw4cPw8vKCkZER+vTpg2nTpuHgwYMAUGVsQgghhJAqEx0dHR1s3LgRderUAcMwiI2Nxe3bt2FjY4P4+Hh06NAB9erVYx9vbm6Oe/fuAQDi4+NhaWnJtqmoqMDQ0BBxcXEQiURITEwUazc1NYVIJMKjR4+QlJQEoVAIc3NzsedOTExEUVFRlbEJIYQQQr5pMXK3bt0wbtw4mJmZoX///sjMzISmpqbYYxo3bow3b94AwFfbMzIykJOTg4KCArF2BQUFqKur482bN8jMzISamhqUlZXZ9iZNmqCwsBAfPnyoMjYhhBBCiMK3PDg4OBhv377F8uXLsXr1auTn50NRUVHsMUpKSigsLAQA5OfnQ0lJqVy7UCjE58+f2a8rai8qKqqwDShZpFxV7MrIywugrq5ajVfML3l5uRrRj6p8bx+l8ToppmzE+5Fi/hf0u0kxf8SY3+qbEh1jY2MAwOfPn+Hu7g4HBwfk5uaKPUYoFKJOnToAAGVlZQiFwnLt6urq7EhNRe116tSBQCCosA0omQJTVlauNHZlRCIG2dl5VT6Ob+rqqt/dDw2N+hz15uu+t49cvE6KWTNi/givkcuYfP9+0u8mxfwRY1akst+1ai1GvnTpktg1PT09FBYWQkNDA5mZmWJt7969g4aGBgBAS0vrq+2lyc67d+/YtqKiImRnZ0NTUxNaWlrIyckRS3YyMzOhpKQENTW1Sp+bEEIIIQSoxohOSkoK5syZg7///huNGzcGADx48ACNGjWCubk5du/ejby8PKiqlgxdxcbGwtTUFABgYmKCO3fusM+Vn5+Phw8fYtasWZCTk4OxsTFiY2PRuXNnAMC9e/cgLy8PAwMDyMnJQVFREXFxcbC2tmaf29DQEAoKCjAxMcGOHTu+Glta6jVQgYpy9QfKvuUTX35BEXJz8v9LtwghhJAfUpXvyJaWltDT04OHhwc8PDzw8uVLrF+/HjNnzoSVlRW0tbXh4eGBOXPm4K+//kJ8fDxWrVoFAHBwcMDu3buxbds29O3bF8HBwdDW1oaNjQ0AYNy4cfjtt9/Qvn17NGvWDD4+PnBwcEDdunUBAEOHDoWPjw/8/f2RmZmJPXv2wNfXFwCqjC0tKsoKaOVxhpfnfuE/ELlVP4wQQggh/1+VU1eKiorYsWMH5OXlMXLkSCxduhSTJk2Co6Mj5OXlERwcjA8fPmD48OE4ceIEtmzZAh0dHQAlW9ODgoJw4sQJODg44N27dwgODoacXEnYgQMHYtasWVi+fDmmTJkCIyMjeHh4sLE9PT1hbGyMSZMmYdmyZZg9ezYGDBgAAFXGJoQQQgip1hyLtrY2tm/fXmFby5Yt2SJ+FenevTu6d+/+1XZnZ2c4OztX2KaiooI1a9ZgzZo1/yk2IYQQQn5sdKgnIYQQQmQWJTqEEEIIkVmU6BBCCCFEZlGiQwghhBCZRYkOIYQQQmQWJTqEEEIIkVmU6BBCCCFEZlGiQwghhBCZRYkOIYQQQmQWJTqEEEIIkVmU6BBCCCFEZlGiQwghhBCZRYkOIYQQQmQWJTqEEEIIkVmU6BBCCCFEZlGiQwghhBCZRYkOIYQQQmQWJTqEEEIIkVmU6BBCCCFEZlGiQwghhBCZRYkOIYQQQmQWJTqEEEIIkVmU6BBCCCFEZlGiQwghhBCZRYkOIYQQQmQWJTqEEEIIkVmU6BBCCCFEZlGiQwghhBCZRYkOIYQQQmQWJTqEEEIIkVmU6BBCCCFEZlGiQwghhBCZRYkOIYQQQmQWJTqEEEIIkVmU6BBCCCFEZlGiQwghhBCZRYkOIYQQQmQWJTqEEEIIkVmU6BBCCCFEZlGiQwghhBCZRYkOIYQQQmRWtRKdly9fYubMmbC0tES3bt3g7++PgoICAMDr16/h5OQEU1NT2NnZ4erVq2L/NiYmBoMHD4aJiQkmTpyI1NRUsfbQ0FB069YNZmZm8PT0RF5eHtsmFArh7e0NS0tLdOnSBTt37hT7t1XFJoQQQsiPrcpERygUYubMmVBSUkJ4eDjWrVuHixcvIjAwEAzDwMXFBerq6oiIiMCwYcPg6uqKtLQ0AEB6ejpmzZqFIUOG4OjRo2jSpAlcXFxQXFwMAIiKisLGjRuxbNkyHDhwAImJifD392djr127FnFxcdi7dy98fHywbds2nDlzBgCqjE0IIYQQUmWik5CQgJcvX2L16tXQ09ODlZUV5s6di1OnTiEmJgbPnz/HihUr0LZtWzg7O8PMzAwREREAgMOHD0NfXx/Tp09H27Zt4efnh/T0dMTExAAA9u/fjwkTJqB3794wNjbG8uXLERkZiU+fPiEvLw+HDx+Gl5cXjIyM0KdPH0ybNg0HDx4EgCpjE0IIIYRUmei0adMGISEhqFu3LntNIBBAKBQiPj4eHTp0QL169dg2c3Nz3Lt3DwAQHx8PS0tLtk1FRQWGhoaIi4uDSCRCYmKiWLupqSlEIhEePXqEpKQkCIVCmJubiz13YmIiioqKqoxNCCGEEKJQ1QMaNWqEzp07s18XFxfj4MGDMDc3R2ZmJjQ1NcUe37hxY7x58wYAvtqekZGBnJwcFBQUiLUrKChAXV0db968gaKiItTU1KCsrMy2N2nSBIWFhfjw4UOVsQkhhBBCqkx0vrR69Wo8evQIERER2Lt3LxQVFcXalZSUUFhYCADIz8+HkpJSuXahUIjPnz+zX1fUXlRUVGEbULJuKD8/v9LYlZGXF0BdXbUar7bmkUa/vzemvLycxPtNMWUj3o8U87+g302K+SPG/FbVTnQYhsGqVavw+++/Y9OmTWjXrh2UlZWRm5sr9jihUIg6deoAAJSVlSEUCsu1q6ursyM1FbXXqVOHnR77sg0omQKrKnZlRCIG2dl5VT7uv9DQqM/L85b6st98x6so5rdSV1fl7ftNMSUb80d4jVzGlPT94FvV5u8txfxxY1akst+1am0vLy4uhpeXF8LDwxEYGIg+ffoAALS0tJCZmSn22Hfv3kFDQ6PK9tJk5927d2xbUVERsrOzoampCS0tLeTk5IglO5mZmVBSUoKamlqVsQkhhBBCqpXo+Pv749SpUwgKCkK/fv3Y6yYmJkhKShKrfRMbGwtTU1O2/e7du2xbfn4+Hj58CFNTU8jJycHY2BixsbFs+7179yAvLw8DAwMYGBhAUVERcXFxYs9taGgIBQWFKmMTQgghhFSZ6Ny7dw/79++Hq6srjIyMkJmZyf6xsrKCtrY2PDw8kJycjJCQEMTHx2PkyJEAAAcHB8THx2Pbtm14+vQplixZAm1tbdjY2AAAxo0bhz179iAqKgqJiYnw8fGBg4MD6tatCxUVFQwdOhQ+Pj5ISEjApUuXsGfPHjg6OgJAlbEJIYQQQqpco3PhwgUAwPr167F+/XqxtgcPHiA4OBhLlizB8OHD0aJFC2zZsgU6OjoAAB0dHQQFBWH16tXYvn07TExMEBwcDDm5kvxq4MCBeP36NZYvXw6hUIi+ffvCw8ODfX5PT08sX74ckyZNQt26dTF79mwMGDAAACAvL19pbEIIIYQQAcMwjLQ7IWmFhSJeFyO38jjDy3O/8B+IzMyPEov3tZjf6kdZIPcjxPwRXiOXMSV9P/hWtfl7SzF/3JgV+e7FyIQQQgghtRElOoQQQgiRWZToEEIIIURmfXNlZEIIIUSa6jVQgYryt719Vbd4Y35BEXJz8v9Lt0gNRYkOIYSQWkVFWYHXRd65VT+M1CI0dUUIIYQQmUWJDiGEEEJkFiU6hBBCCJFZtEaHkB/cty7s/JYTuWlhJyFE2ijRIeQHRws7CSGyjKauCCGEECKzKNEhhBBCiMyiRIcQQgghMosSHUIIIYTILEp0CCGEECKzKNEhhBBCiMyiRIcQQgghMosSHUIIIYTILEp0CCGEECKzKNEhhBBCiMyiRIcQQgghMosSHUIIIYTILEp0CCGEECKz6PRyQsgPoV4DFagoV/+Wp6FRv9qPzS8oQm5O/n/pFiGEZ5ToEEJ+CCrKCmjlcYaX537hPxC5vDwzIeR70dQVIYQQQmQWJTqEEEIIkVmU6BBCCCFEZlGiQwghhBCZRYkOIYQQQmQWJTqEEEIIkVmU6BBCCCFEZlGiQwghhBCZRYkOIYQQQmQWJTqEEEIIkVmU6BBCCCFEZtFZV+SbfevhiED1D0ikwxEJIYRwiRId8s3ocERCCCG1BU1dEUIIIURmUaJDCCGEEJlFiQ4hhBBCZNY3JTpCoRCDBg3CP//8w157/fo1nJycYGpqCjs7O1y9elXs38TExGDw4MEwMTHBxIkTkZqaKtYeGhqKbt26wczMDJ6ensjLyxOL5+3tDUtLS3Tp0gU7d+4U+7dVxSaEEELIj63aiU5BQQEWLFiA5ORk9hrDMHBxcYG6ujoiIiIwbNgwuLq6Ii0tDQCQnp6OWbNmYciQITh69CiaNGkCFxcXFBcXAwCioqKwceNGLFu2DAcOHEBiYiL8/f3Z51+7di3i4uKwd+9e+Pj4YNu2bThz5ky1YhNCCCGEVCvRefr0KUaNGoWXL1+KXY+JicHz58+xYsUKtG3bFs7OzjAzM0NERAQA4PDhw9DX18f06dPRtm1b+Pn5IT09HTExMQCA/fv3Y8KECejduzeMjY2xfPlyREZG4tOnT8jLy8Phw4fh5eUFIyMj9OnTB9OmTcPBgwerFZsQQgghpFqJzp07d9ClSxf88ccfYtfj4+PRoUMH1KtXj71mbm6Oe/fuse2WlpZsm4qKCgwNDREXFweRSITExESxdlNTU4hEIjx69AhJSUkQCoUwNzcXe+7ExEQUFRVVGZsQQgghpFp1dMaMGVPh9czMTGhqaopda9y4Md68eVNpe0ZGBnJyclBQUCDWrqCgAHV1dbx58waKiopQU1ODsrIy296kSRMUFhbiw4cPVcYmhBBCCPmugoH5+flQVFQUu6akpITCwkK2XUlJqVy7UCjE58+f2a8rai8qKqqwDShZpFxV7MrIywugrq5ajVdY80ij35KOyUU8eXk5iff7R4n5rb63f7XhNQK183eTfmYrRvegmh3zW31XoqOsrIzcXPE6tkKhEHXq1GHbhUJhuXZ1dXV2pKai9jp16kAgEFTYBpRMgVUVuzIiEYPs7LwqH/dfVPeog//qy37zHU8aMbn4v1FXV+Xt/1jWYtb0/0+uvq/SeJ0/yvdW0jFr+vcVqL3f29oQsyKV/Ux8Vx0dLS0tZGZmil179+4dNDQ0qmwvTXbevXvHthUVFSE7OxuamprQ0tJCTk6OWLKTmZkJJSUlqKmpVRmbEEIIIeS7Eh0TExMkJSWJ1b6JjY2Fqakp23737l22LT8/Hw8fPoSpqSnk5ORgbGyM2NhYtv3evXuQl5eHgYEBDAwMoKioiLi4OLHnNjQ0hIKCQpWxCSGEEEK+a+rKysoK2tra8PDwwJw5c/DXX38hPj4eq1atAgA4ODhg9+7d2LZtG/r27Yvg4GBoa2vDxsYGADBu3Dj89ttvaN++PZo1awYfHx84ODigbt26AIChQ4fCx8cH/v7+yMzMxJ49e+Dr61ut2IQQ8qOp10AFKsrfdlv/lmmg/IIi5Obkf2u3CJGq70p05OXlERwcjCVLlmD48OFo0aIFtmzZAh0dHQCAjo4OgoKCsHr1amzfvh0mJiYIDg6GnFzJQNLAgQPx+vVrLF++HEKhEH379oWHhwf7/J6enli+fDkmTZqEunXrYvbs2RgwYEC1YhNCyI9GRVkBrTzO8Pb8L/wHIrfqhxFSo3xzovP48WOxr1u2bMkW8atI9+7d0b1796+2Ozs7w9nZucI2FRUVrFmzBmvWrKmwvarYhBBCCPmx0aGehBBCCJFZlOgQQgghRGZRokMIIYQQmUWJDiGEEEJkFiU6hBBCCJFZlOgQQgghRGZRokMIIYQQmUWJDiGEEEJkFiU6hBBCCJFZlOgQQgghRGZ911lXhEgKn4cV0kGFhBAiuyjRIbUCn4cV0kGFhBAiuyjRIYQQQggA2Rw9p0SHEEIIIQBkc/ScFiMTQgghRGZRokMIIYQQmUWJDiGEEEJkFiU6hBBCCJFZlOgQQgghRGbRritCCCGkCrK47fpHQYkOIYQQUgVZ3Hb9o6CpK0IIIYTILBrRIaQGoeFxQgjhFiU6hNQgNDxOCCHcoqkrQgghhMgsSnQIIYQQIrMo0SGEEEKIzKI1OoQQQkgNRJsTuEGJDiGEEFID0eYEbtDUFSGEEEJkFiU6hBBCCJFZlOgQQgghRGZRokMIIYQQmUWLkQkhhPxntDOI1HSU6BBCCPnPaGcQqelo6ooQQgghMotGdAghEvet0x3VneoAaLqDECKOEh1CiMTRdAchRFIo0SHkK2iRJSGE1H6U6BDyFTTqQAghtR8tRiaEEEKIzKr1iY5QKIS3tzcsLS3RpUsX7Ny5U9pdIoQQQkgNUeunrtauXYu4uDjs3bsXb968gZubG7S1tTFw4EBpd40QQgghUlarR3Ty8vJw+PBheHl5wcjICH369MG0adNw8OBBaXeNEEIIITVArU50kpKSIBQKYW5uzl4zNzdHYmIiioqKpNgzQgghhNQEtTrRyczMhJqaGpSVldlrTZo0QWFhIT58+CDFnhFCCCGkJhAwDMNIuxP/1fHjx7F+/Xr8/fff7LW0tDT06dMHly5dgo6OjhR7RwghhBBpq9UjOsrKyhAKhWLXSr9WUVGRRpcIIYQQUoPU6kRHS0sLOTk5YslOZmYmlJSUoKamJsWeEUIIIaQmqNWJjoGBARQVFREXF8dei42NhaGhIRQUav3OeUIIIYR8p1qd6KioqGDo0KHw8fFBQkICLl26hD179sDR0VHaXSOEEEJIDVCrFyMDQH5+PpYvX46oqCjUrVsXTk5OcHJykna3CCGEEFID1PpEhxBCCCHka2r11BUhhBBCSGUo0SGEEEKIzKJEhxBCCCEyi/ZgS9Dt27crvC4QCKCoqAgNDQ1oa2tzHjcnJwdPnjxBUVERvlySZWNjw3k8Qr5XSkoK7t+/X+HP7IgRI6TUK1JbSPrnZ8uWLZg6dWq5QrW5ubnYunUr3N3dOY8J0O9JddFiZAnq168fXr16heLiYqipqYFhGOTk5EAgEEBeXh5FRUUwMTFBUFAQNDU1OYkZGRkJHx8ffP78uVybQCDAo0ePOIlTVnZ2Nnbv3s0ervrlj1hYWBjnMSdOnAiBQFDuetkk0s7ODt26deMspjRe5/Hjx7/apqSkBA0NDZiYmEBJSYnTuJK8oYaEhCAwMBANGjRA3bp1xdoEAgEuXbrEabxSDMMgIyMDhYWF5dp0dXV5iVk29pffVzk57gfc79y5AzMzM8jLy4tdz8vLw549e/Drr79yEqdXr14V/j5WhOv/T0n9/Dx9+hSZmZkAACcnJ2zatAn169cv95j169fj3r17nMQsSxq/J9K453GBEh0J2rZtG65cuQJ/f3+0bt0aQMnZXF5eXujRoweGDx+OZcuWAQA2b97MScz+/fvD1tYW8+bNQ7169Th5zqrMmjULCQkJGDx4cIUxubqZlrV582aEhISgf//+MDU1BcMwePDgAc6cOQN7e3soKyvj5MmT8PT0hIODAycxpfE6HR0dcefOHSgrK6N169ZgGAapqanIz8+Hjo4OsrOzUb9+fezcuRN6enqcxJT0DbVXr14YPXo0ZsyYwenzVubq1avw9vZm37hKMQzD2weC+/fvw9fXF/fv30dxcXG5dj5i6uvrw8zMDBs3boSWlhZ7/d27d7C1teUs5pEjR9i/v3r1CqGhoRg9ejSMjY2hoKCABw8eIDw8HBMnTuT890RSPz83b97EpEmTKn2MqqoqJk+eDFdXV87jS+P3RBr3PE4wRGKsra2ZR48elbv+6NEjxtrammEYhnn69CljYWHBWUxTU1Pm+fPnnD1fdZibmzO3b9+WaMwxY8YwBw8eLHf98OHDzLhx4xiGYZgLFy4w/fv35yymNF6nr68vM3PmTObff/9lr338+JFxdXVl/P39maKiImbFihWMk5MTZzF79uzJbN++nbPnq4q5ubnEf2YHDRrEuLq6MklJScyrV6/K/eHDiBEjmPHjxzOXLl1ibt68We4PH9q3b8/MmjWL6dSpE/P333+z1zMzMxl9fX1eYjo4ODBnz54td/3PP/9kBg0axHk8afz89OzZk3n//r1EY0rjdUrjnscFWowsYR8+fKjwmkgkYr+u7pBvdfTq1QuXL1/m7Pmqo1GjRlBWVpZozIcPH6Jz587lrltYWCAxMREAYGRkhPT0dM5iSuN1Hj9+HIsWLUKDBg3Ya/Xq1YOrqyuOHDkCeXl5ODo64u7du5zFzMnJQf/+/Tl7vqrY29sjPDy83LA4n9LS0jB37ly0b98ezZs3L/eHD8nJyVi6dCl69eoFKyurcn/4IBAI4OvrC1dXV8yePRubNm1iR634kpKSgp9++qncdR0dHbx69YrzeNL4+bl8+TIaNWoksXiAdF6nNO55XKDFyBI0YsQIuLu7w9XVFcbGxmAYBvfv38eWLVswbNgwZGVlISAggNObXKNGjRAYGIgzZ86gRYsWUFRUFGtfu3YtZ7FKLVq0CD4+PpgzZw50dHTKrRfhY72Dvr4+QkND8dtvv7FrGxiGQVhYGNq2bQsASExMRNOmTTmLKY3XqaqqiuTk5HLTUikpKWz8vLw81KlTh7OYpTdUd3d3Xt8QS2VlZSEqKgqnTp1C8+bNy/3M8rEOwMLCAgkJCWjTpg3nz/01+vr6ePXqVYVJAF9K3xTHjh0LQ0NDzJs3D3FxceyUOR/Mzc3h5+eHlStXolmzZgCAFy9eYMWKFbC1teU8nqR+frp3717t34crV65wErMsafyeSOOexwVaoyNBDMNg+/bt+P333/H27VsAgKamJiZMmICpU6fin3/+wR9//IGlS5dythjZ09Oz0vbVq1dzEqcsfX19sa9LbwYMz+sdpk+fDhUVFRgYGIBhGCQlJSE/Px/bt29HUVERJk+ejGXLlnG2eFYar3Pfvn3YvHkzHB0dYWRkBKDktYeFhWHq1KkYOnQoXF1d0aZNG/j7+3MSc8GCBYiKioKamppEbqhbtmyptJ2PdQDBwcHYuXMnbG1tK/xAMHfuXM5jhoWFYevWrRg6dCh0dXXLxeRj14y+vj5u3LiBxo0bAyh5s1y0aBEeP36M9+/f8/Iz+/btW7i6uiI+Ph716tUDwzD49OkTrK2tsWnTJqipqXEaT1I/P5GRkdV+7LBhwziJWZY0fk+kcc/jAiU6EhQREYFevXqhUaNGyMrKgoKCQrlV+lzbsmULhg8fzsu29a95/fp1pe18TAUUFxcjLy8PZ86cwZMnTyAvL4927dph4MCBUFVVxatXr5Cbm1vuF/V7SON1AsDJkydx6NAhPH78GAoKCmjbti0mTpyIAQMG4Pbt27h48SLmzp0LVVVVTuJJ+oa6ZMkSODs7o2XLlpw+b2UmTpz41TaBQIADBw5wHrNXr16VxuRj14ynpyeWLFkitpCUYRhs2rQJJ0+e5HWaOzk5GSkpKQCAdu3acbZYvjJFRUWQl5eXyEjk1wiFQs53QUqLtO5534sSHQmysLBAREQEWrVqJdGYx48fh46ODq9xiouL2SmjinaQlMXHttlBgwZh3bp1nCYy1RUbG4sXL16gf//++N///odWrVrxdmOTRuJaliTeOKysrHDs2DHef2aJ5DAS3rofFhaGffv2IT09HefOnUNISAgaNmyIefPm8XL/efv2LbZv347k5GT2/scwDIRCIZ4/f47Y2FhO4ri5uWHp0qWoV68e3NzcKn0sH8sSSknynscFWqMjQZ07d0ZkZCRmzJjB2aftqtjb22PLli2YPn06tLW1yy0k4+qX3tDQENevX0fjxo3RoUOHSt8I+Rje/Pfff8vVBuHb+/fvMWPGDDx9+hRCoRBWVlYIDAzEkydPsGfPHl5GJPbt2wd7e3vOn7cqknzjKJ1idHR0RPPmzcv9zPK1DiApKQkHDx5Eamoq1q1bhz///BMtWrTgtPbSl969e4cjR44gNTUVixcvxs2bN6Gnp4f27dtzFqO6a0kEAgH++usvzuKWkvTW/b179+LAgQOYO3culi9fDgDo0qULfH19AZRMxXLNy8sLr169Qr9+/bBnzx5MmTIFL1++xJ9//gkvLy/O4pS9x0n6fgdI557HBRrRkaDRo0cjPj4eAoEA6urq5W7gfCxY6969OzIyMr56o+PqJnPr1i38/PPPUFBQwM2bNyu9sfKxoyQgIAAnT57E4MGDK3xz5GO9w7x588AwDNasWQMbGxucPHkSDRs2hJubGwoLC7Fz507OY/r6+uLTp0+8J65lffnGcerUKTx48AC+vr5wcHDg/I1DGusA/v77b8yZMwd2dnY4c+YMzpw5g8jISISEhGD16tUYPHgw5zETExMxefJkGBoa4u7duzh37hx27dqFyMhIBAcHo2vXrpzEkfZaksGDB6NNmzZwcXGpsPYK19Md/fv3x2+//QZbW1uYmZnh5MmT0NXVxY0bN+Dp6Ylr165xGg8AzMzMsGfPHpiZmcHBwQFeXl4wNzdHSEgIbt68id27d3MeUxqkcc/jAo3oSNCYMWMwZswYicYMCAiQSJyyyYu1tbVEYpZ17tw5KCoq4vz58+XaBAIBL4lOdHQ0wsLCxHY41atXDwsXLsSoUaM4jwcAFy9eREZGBk6cOFFhOx9JQHh4OLtDxsfHBwDwyy+/oH79+vD09OQ80eGr8nFlAgMD4enpidGjR7M/Q66urtDQ0EBwcDAviY6/vz+cnZ0xY8YMmJmZAQB8fHygoaGB9evXc5boVDd5EQqFnMT7UlpaGjZt2iSxHW1v3rypcHlA06ZNkZOTw0tMhmHYAoxt27bFw4cPYW5uDjs7O16TnCtXrmD//v1ITU1FaGgojhw5gmbNmmH06NG8xJPGPY8LlOhIUOkNp7i4GK9fv0azZs1QXFzM69xmaQKSkZGB58+fw9TUFLm5uWjSpAmncaS91VLStYKAktGT/Pz8ctczMzN5qzUhqcS1LEm/cZR+wpfkOoBnz55VWIepS5cuvOxMBEpqP1X03Pb29rx9MpbUWpKyJL1139TUFEePHsW8efPYa8XFxdi1axc6duzIS0xDQ0McP34cLi4uMDAwwPXr1zFx4kSkpaXxEg8ATpw4gVWrVrF1s4qLi6GhoQF/f3/k5+dj8uTJnMeUxj2PC5ToSFBRURHWr1+PgwcPQiQS4cKFC1i3bh0UFBTg6+vLy7qdT58+wdPTE1FRUZCTk8OFCxfg5+eHrKwsbN26ld1m+r3K3lSkITo6utJ2Pg4vHTRoEFauXAkfHx8IBALk5ubixo0bWLFiBQYMGMB5PICfab+qSPqNQxrrAHR0dHDv3r1y638uX77M25qgxo0bIyUlBS1atBC7Hhsby1l5iS9Jai1JWT///DN8fHxw+fJliWzd/+233zB9+nRcuXIFQqEQy5Ytw4sXL1BQUMDb6MqiRYswc+ZMqKioYOjQodi1axfs7OyQkZHB25q6Xbt2wcfHR2zUaPz48WjcuDHWrl3LS6IjjXseF2iNjgStX78eV65cwdKlS+Hs7IyTJ08iIyMD3t7esLS0xIoVKziPuXTpUjx//hz+/v4YNGgQTp48ieLiYri7u6NZs2YIDAzkPKaTkxOWLFkike2jpb6220pZWRlNmzbFhQsXOI8pFAqxYcMGhIWFsbtJ5OXlMXLkSHh6evLyCaeqkTM+RsuSk5Mxffp0qKurIzk5GdbW1mJvHFzvdJPGOoCLFy/Czc0NI0aMQHh4OJycnJCWloYLFy4gICAAdnZ2nMf8448/EBQUhOnTpyMwMBAeHh5IT0/HgQMHsGjRIowfP57zmNJYSyKNrfsFBQU4deoUUlJSIBKJ0Lp1awwZMqTcWW1c+vTpE/Lz89GkSRNkZGTg4sWLUFdXh52dHS9r50xMTHD69Gno6uqKrUVKTU3F4MGDkZCQwHlMadzzOMH7IROE1bNnT+bOnTsMw5ScQfXy5UuGYRjm7t27TKdOnXiJ2aVLF+bBgwflYj569IixtLTkJWanTp2YFy9e8PLc1VVUVMQ8e/aMcXJyYo4cOcJrrPz8fObJkyfMo0ePmNzcXF5jHTt2TOzP4cOHmfXr1zNdu3ZlIiIieIv7+fNn5siRI4y/vz+zatUq5tChQ7y9VisrKyY5OZlhGPGf2adPnzI///wzLzEZpuR3YvHixczw4cMZe3t7Zt68ecy9e/d4i8cwDHPp0iVm3LhxjLW1NWNhYcGMHDmSOXPmDG/xTExMmNevXzMMwzBubm7MgQMHGIZhmJcvXzJWVla8xZUGkUjEMAzDZGRkMGfPnpXYPam4uJgRiURif/gwYsQIJjQ0lGEY8d+T9evXMyNGjOAlZilJ3vO4QFNXEpSVlVXhVJGKigo+f/7MS8zPnz+XGyoGSjJzhqfBvDFjxsDV1RWjR49G8+bNy62r4GMa6Uvy8vJo3bo1PDw8MG3aNF4WIwMlox3Pnj1jF3ImJyezbXwsYP3awlIzMzOEhIRwdjL7l5SVlTF8+HDIycnh7du3iI2Nxbt373j5hCytdQD6+vpitUc+fPiAhg0b8hYPKCkaWFnhQK5JYy0JULLD7OnTp+yZfsz/Xxf06NEjrFy5ktNY9+7dw9y5c7FmzRq0bdsWI0aMQG5uLoRCIQIDA9G3b19O4wElmwC8vb3x+PFjFBUVVdjONXd3d8yYMQPR0dEoLCxEcHAwnj9/jqSkJGzfvp3zeABw+/btctcePnwIgUAARUVFaGhoSK3GV2Uo0ZEgGxsb7Ny5U+wX++PHj9iwYQM6derES8zevXtj/fr1YjfwFy9ewNfXFz169OAl5rZt2wCgwqk4SZcJf/v2LT5+/MjLcwcGBmLHjh2oX79+hW/AfCQ6X9OmTRs8ePCAl+eW9BuHNNYBvHv3DqtXr8a0adOgp6eH6dOn49atW2jWrBl27NiBdu3acRJn06ZN1X4sH8dOSGMtyebNmxEcHIwmTZrg/fv30NLSwrt37yASidCvXz/O4/n7+6N3794wNjZGaGgoFBQUEB0djZMnT2LTpk28JDqenp5QV1fHxo0bea92X8rCwgIXLlxAWFgY5OXlkZOTAwsLC2zYsIG3ZGPJkiV49eoViouLoaamBoZhkJOTA4FAAHl5eRQVFcHExARBQUG8rTP7L2iNjgRlZGRg9uzZePXqFXJyctCqVSukp6dDV1cX27Zt46V8dm5uLjw9PXHx4kUwDANVVVXk5+eja9euCAgIgLq6OucxpaGiKqG5ubm4fv06Bg0aBD8/P85jWllZYcGCBRItGVDRoutPnz5h7969+Pz5M44ePcp5zDFjxqBDhw5YuHAhQkNDcfjwYZw7dw4nT57E/v37cfr0aU7jSWMdwJw5c/DhwwesXbsW//zzD9asWYMdO3bg5MmTeP78OWfrSCpbr1IWl2tX/v77b1hbW7Mjq5JeS9K1a1fMmTMHo0ePRq9evbB//36oqalh/vz5aN++fZUVfr9Vx44dce7cOTRv3hyjRo2CiYkJlixZgtevX8POzo6XtSsdO3bEqVOnJFowb8uWLZg6dSpUVFTErufm5mLr1q1wd3fnPOa2bdtw5coV+Pv7o3Xr1gBKygd4eXmhR48eGD58OHtA7ObNmzmP/19RoiMF0dHRePbsGYqKitC6dWt07dqVlxtMWWlpaUhJSWFj8r1QuKCgABcuXEBqaiomTpyIpKQk6OnpQUNDg5d4FR1eqqioCGNjY9jb2/OyLblnz54ICQnh7NN+dVS08Lf0dXp7e8PAwIDzmNJ44wBKpl3T0tIgEomgq6vL60JSc3NzHD58GHp6enB2doaamhoCAgKQlpaGwYMH4969e7zF5puZmRnOnj2LZs2aoXfv3jh69KhEP+AYGRkhKioK2tramD17Nvr16wd7e3vcv38frq6unJeG6NatGzZs2ICmTZuib9++2LVrF7p06YILFy5g7dq1vNRpGjduHKZOnYrevXtz/txlPX36lK0w7eTkhE2bNpUbQXr69CnWr1/Py89sp06dsG/fvnL3oaSkJEyePBkxMTFISUnBmDFjKpzmkhaaupICDQ0N5OTkQFFRES1atOA1yRkyZAgGDx6MgQMH8jZV9aXU1FRMnjwZ8vLyePPmDYYOHYrw8HBER0dj9+7d7KnbXOKr1kll3NzcsGLFCri6uqJZs2bl/h/5GD5OSkri/Dmroq6ujvT0dDAMg8TERHZK5f79+7wlrpJe+6SgoACGYZCXl4ebN29i1apVAMDbOqRSkli70qhRI3h7e8PIyAivX7/G9u3by40ClOJjuqxp06ZIS0uDtrY29PT08PDhQ9jb26Nu3brIysriPJ6DgwNmz54NRUVFtG/fHjY2NggLC0NAQACnZTAiIiLYv5uYmMDDwwNjxoyBrq5uuXsBV2sE379/jylTprBfu7q6lnuMqqoqnJycOIlXkQ8fPlR4rfRnGIBUD1GtCCU6EvT+/XvMmTMHd+/eZec3P378iJ49e8LPz4+XT1ljx47F+fPnsXHjRhgbG2PQoEGws7PjrH5ORVauXInevXtjyZIl+PnnnwEAGzZswPLly+Hn54dDhw7xEjc6Ohrh4eF49uwZFBUV0aZNGzg5OaFDhw68xBOJRLh//z4cHR3FrjM8HlUAlNSw+fvvv5GSkgJFRUW0bduW1wXeknrjKCWNtU82NjZYsmQJVFVVoaysjJ49e+Kff/6Br68vb5/SJbV2ZevWrQgKCsLdu3chEAhw7969Cjco8PXmNGrUKMyfPx+rV69Gnz59MGnSJDRu3BgxMTG8HMI7d+5cdOjQAa9fv8aQIUMgJycHHR0dBAYGomfPnpzFCQ4OFvu6fv36OHPmTLnHcVmZ3dramv2w06tXL0RERKBRo0acPHd1jBgxAu7u7nB1dYWxsTEYhsH9+/exZcsWDBs2DFlZWQgICJBKva9KSWOr149q2rRpzKRJk5hXr16x154/f86MHTuWmTNnDq+xMzMzmdDQUGbChAmMsbEx4+TkxBw9epT5+PEj57HMzc2ZZ8+eMQwjvu0xNTWVMTU15TwewzDMkSNHGCMjI8bDw4MJDQ1l9u/fzyxcuJAxMjJiTp8+zUvMLl26ML6+vszjx4+Z1NTUcn/48OLFC6ZXr16MmZkZM2zYMGbo0KGMqakpY29vz6SlpfESk2EYJioqitm7dy/z/v17hmEY5sqVK8zly5d5iWVpacn8/vvvvDz313z8+JHx9fVlZs2axcTFxTEMwzD79u1j/P39mfz8fF5idunShQkPD2cYpqT0xMuXL5l///2XcXJyYtasWcNLzJ49ezIfPnzg5bkrc+LECebmzZsMwzDM4cOHmeHDhzNOTk5MSkqKxPsia0q3r799+5b3bfTFxcVMcHAwY2try7Rv355p3749Y2try+zYsYMpKipirl27xsyePZvJyMjgrQ//BSU6EtSxY0e2PkhZjx49YkxMTCTSh+TkZGbdunVMx44dGWNjY8bExIRxc3Pj9AfT1taWvamVTXT+/PNPplu3bpzF+TJmZGRkueu///4707NnT15iWlpasq9NUkaPHs0sXLhQrHbFv//+y8yePZuZPHkyr7G/vKE+f/6clzg9evRgnjx5wstz1ySGhoZsTRsXFxfm+PHjDMMwTGJiIuc/sx8/fmQuXrzIXLt2jZcPNzXJq1evGFdXV6Zfv35Mjx49mO7du4v94cu///7L3L59m4mOjmb++ecf9k90dDQv8eLi4phu3box0dHRTGZmJtO1a1fGzMyMMTQ0ZKKioniJWdaHDx+YnJwc3uNwgaauJEhPTw9PnjxB27Ztxa6/fPmStzLzQMnitPPnz+PcuXNITU1F586dsWLFCvTt2xdZWVnw8fHBzJkzcezYMU7ijRkzBkuXLsWiRYsAACkpKYiOjsbGjRsxduxYTmJ86dOnTzA2Ni533dzcnJd1AAAwdepUBAcHY+nSpV9d88C10vORyq4badCgAebPn4/hw4fzEvPL7eUODg68bi+XxtonoVCII0eO4PHjxygoKChXY6pseQauSGrtyr179zBjxgz8+++/AErW7AQGBvJ6+O637KTi+nvr5uaGjx8/Yvz48RLb6h0ZGQkfH58K66HxNY395TZ6RUVF3rfRAyX38/v376OoqKjc7wlf9cq+FyU6PCu7YM3KygpLlizB/fv3YWRkBDk5OTx58gQHDhzA1KlTeYk/cOBA9jDP8ePHw87OTqwImqqqKoYPH46lS5dyFtPFxQX169fHypUrkZ+fj5kzZ6Jx48aYMmUKb69z4sSJCAgIwJo1a6CmpgYAyM/PR1BQEG/bv69evYrExEScOnUK6urqUFAQ/3Xi4zgGU1NTREdHs1s7S8XGxvKy4wqQfF0Saax98vb2RlRUFLp06SKxN0dJrV1Zu3YtOnfujCVLlkBOTg4BAQFYunQpL8eilJKXl+ftuauSmJiIo0ePSnQ35Pbt2zFixAjMmzcP9erVk0jMhw8fYv369ahbty4uX76M3r17Q1lZGZ07d4avry8vMUNCQrBhwwaoqamVW6TP5VokrtH2cp5Vt+qpQCDgZdtjSEgIBg0aVOmn4Pz8fAgEAtSpU4fz+Hl5eRCJRLy8eZQ994lhGGRkZEBJSQk6OjqQk5PDq1evIBQKYWBgwEt9mcjIyErbv1bF+FuVLTKXkZGBEydOsIlHabJ89uxZODo6YvHixZzELEvS28u7du2KX375BaNGjarwZ/LLQzC5YGZmhuDgYIlU7S7r5MmTaNq0KaysrHDkyBGEh4dDXV0dS5Ys4ey0bzMzMxw/fpyt8ZKdnY1OnTrh5s2b7IcCPm3ZsgXDhw+XWMVce3t7LFmyRKILYs3MzBAZGYlWrVpJLKY0ttH36tULo0ePxowZMzh/bj7RiA7PuK4R8a2cnZ1RWFiI169fo7i4GMD/bWF9+PAhhgwZwuu0S2ZmJg4fPozi4mL88ssvMDEx4ey5pX1iemkiU1xcjNevX6NZs2YoLi7mvGbPnTt3xL7++eefkZWVhWvXrrHXTE1NkZiYyGncUpLeXi4UCjFp0iRep3O/1KBBA962ypfVq1cv/P7779DS0ipX8G3kyJEYOXIk5zHz8/PFRhnU1dVRp04dfPz4USKJzr59+zB06FBeY5QtpNmvXz+4ublh5syZFW715iOZ7dWrFy5fvszrtu4vSXo3JADk5OSgf//+vDw3n2hER8K+rA9SSiAQYNCgQZzH+/PPP/Hbb78hJyenXJuWlhZn0yt5eXnw9/fH2bNnAZR8qho/fjxGjx6Nxo0bg2EYpKWlISgoiPeiWpJSVFSE9evX4+DBgxCJRLhw4QLWrVsHBQUF+Pr6QlVVVdpd5MSmTZtw6NAhKCoqokmTJjh27Bh+//139oY6efJkTuPt2LEDL1684H3tU2niD5ScJH7+/HksW7YMurq65aZeuKp19fPPP8PT0xPW1tbo378//vjjj6+ep8VVoqevr48bN26IlZQoe9o133x9ffHp0ydMnz4d2tra5UoGcPG9re5UH19Tn6tWrUJ4eDh++ukntGjRotz2fT7WeAEl9/fSbfSNGjXC1atXUVxczOk2+rJ8fX2hqKgId3f3GlcrpzKU6EhQVfVBrl+/znnMX375BVZWVpg8eTLGjh2LkJAQZGdnw9fXF7NmzeLsEMjStUeOjo5o1KgRQkND2cWVpVWLN27ciJiYGISHh3MSs6zs7Gzs3r0biYmJFS6SCwsL4zzm+vXrceXKFSxduhTOzs44efIkMjIy4O3tDUtLywrP+uLClStXvpos8zWkLMkb6rhx45CYmAiGYXhd+6Svry92sy5dA1QRrt4ct2/fjo0bN4pNuX75d67XIhkYGODatWtsosMwDCwtLREZGVku0eGjeGn37t2RkZHB+/dWmiqqzF6WNAqa8mHBggWIioqCmpoamjdvXi6h4+M+ywVKdCRIGmcjGRkZ4ezZs2jRogWmTp2KsWPHok+fPrh+/Tr8/f05O6eoU6dOCAkJQceOHQGUVMrs3LkzIiIi2ErIr169wqBBg3gpTT5r1iwkJCRg8ODBFS4G/PXXXzmP2atXLwQEBMDc3FzsE3JcXBxcXFwqPJfqe3l6euLUqVPQ09Mrt35FIBDwkkSWysjIYBe25+bmokmTJrzEkdTap1u3blX7sVyu98jJycHHjx/Ru3dvHDly5KsF37g6++7LhA74elLHR9JR1feZ67U0xcXF2LlzJzQ0NNidiJMnT4atrS2cnJwkOhIhEolw/fp1dO/enZPnK7susSp8bIbYsmVLpe183Ge5QGt0JKhu3bowNzeXaMwGDRogPz8fANC6dWs8evQIffr0QevWrfHq1SvO4mRnZ6Np06bs140aNYKKiorYGoA6deqgoKCAs5hl3b59G9u3b4eFhQUvz1+RrKysCitMq6ioVLjNlAsXLlzAxo0b0adPH16evyKfPn2Cp6cnoqKiICcnhwsXLsDPzw9ZWVnYunUr51W2uUpkqvLlG+zdu3dRXFzM/gwFBQWhW7dunK4rA0p+Jxs0aIDVq1ejdevW5RLzvLw8HD16tNoHgFaFq8NB/6vKEpk3b95wHs/f3x8XL16Ej48Pe23gwIHYtm0bcnJyMH/+fM5jfunJkyeIjIzEqVOn8P79e84SSGmvS6ypiUxVKNGRIGnUB+nZsyd8fHzg4+MDa2trrFmzBt27d8eFCxegpaXFaSxpbilt1KgRL6daV8bGxgY7d+4UO5Po48eP2LBhAzp16sRLTC0tLc7/36qyZs0aZGVl4dKlS+w6Mg8PD7i7u2PlypUIDAzkNN6zZ8+wceNGPH/+vNz0HABetkUfPXoUPj4+cHd3ZxOd//3vf3B0dMTq1asxYMAATuK8f/8eeXl5AAAvLy/o6emVW6Pz6NEjBAQEcJbofC3RePPmDTQ1NXk/UDglJQVr165FcnJyuQ0R2dnZnI8inTlzBlu3boWpqSl7beTIkWjdujXmzZvHW6KTlZWF06dPIzIyEo8ePYKCggL69+/Pae2wij4E5ObmIjU1FSKRCC1btuR8gbmbmxuWLl2KevXqVVkfia+1SN+LEh0JkkZ9EC8vL6xevRoPHjyAvb09Lly4gNGjR0NVVRUBAQGcxoqNjRXbRs4wDOLi4tiRo4oWRHNl0aJF8PHxwZw5c6Cjo1Nu5xMfiy6XLVuG2bNnw8bGBgUFBZgxYwbS09Ohq6uLbdu2cR4PAJu0TpgwocJk2dLSkvOYly9fRkhIiNhUSsuWLbF8+fJyP8tcWLhwIeTk5ODg4MBLyYOKbN++HatXr8bAgQPZa6tXr0aXLl2wefNmzhKdO3fuYO7cuexanNGjR4u1l64kkMSo1oABA3DixAneFyR7e3ujuLgYM2bMgJ+fH9zc3PD69WscOnSIl7UrBQUFFX7oqVevHj59+sRprKKiIly5cgWRkZG4du0aioqKYGJiAoFAgLCwMHYqnw9CoRBr1qzBH3/8AZFIBIZhoKCggIEDB8LX15ez3Z9lP8BK88Ps96BER4L8/f3h4ODw1fogfKhbt67YiMO6deuwfPly1KlTp9wiz+9V0Um6X34C4Gt+vDR26WLcLxd48pFEKisrIyIiAtHR0Xj27BmKiorQunVrdO3albdPyQ8ePMCjR4/g4eFRro2v1/n58+cKD4EUCoXlFn1z4fnz54iIiChXQZxPmZmZMDQ0LHfdyMgI6enpnMXp378/Ll++jOLiYvTp0weHDx8WW6MjEAigqqrKywG/X5LU8sz79+/jjz/+gIGBAY4fP442bdpg/PjxaN26NQ4fPsz51vPu3bvD19cXa9asYZO4tLQ0rF69Gra2tpzFWblyJc6cOYNPnz7B0tISnp6e6Nu3LzQ0NGBoaMj7rss1a9bg2rVr2LZtG8zMzFBcXIy4uDisWrUKgYGBcHd35yRO2WS0efPmEq2JxBVKdCRIGvVBykpNTeWtpk3pibrSwkdxrKrY29uzReYkVWhu27ZtmD9/PsaOHSuxZLl3795Yv3692LD0ixcv4Ovrix49enAez9bWFnFxcRJNdIyNjbF//34sXbpULBkPCwvj/ITt0jeJL39nhEIhkpKSylW9ru0UFBTYkd42bdrg0aNHsLGxQefOnbFmzRrO43l7e2P27Nno27cvGzc3Nxc2NjacVoA/ePAgWrZsicWLF6NHjx4SPUUcKJmi27x5s9jUZPfu3VGnTh0sWLCAs0SnLEnUROIDJToSJKmzkapT02b//v0yVdOmdFolNjYWL168QP/+/fG///0PrVq14ryAXyllZeUK15DwSUlJCb179y5Xfp1P3t7ebO0XhmFgb2+PvLw82NrawsvLi/N4np6eGDZsGE6ePInmzZuXGwXkY7rD09MTU6ZMwdWrV9mjNJKSkpCXl4cdO3ZwHg8oSRY9PDzg5uaGn376CWPGjMHTp09Rt25d7Nixg/eF9UOGDJHIz5G5uTl2794NNzc3GBkZ4dSpU5g8eTLi4+N5WVenrq6OsLAwJCcnIyUlBYqKimjVqhX09PQ4jRMeHo7Tp09jw4YN+O2332BsbIw+ffpI7J7KMEyFNZjU1dXZdWBcs7e3x5YtW3iticQH2l4uQZKqDyLtmjbS8P79e8yYMQNPnz6FUChkdwY9efIEe/bsYcvfc8nX1xfHjh1Dt27d0Lx583K/9KUVhLl07NgxREVFwc3NDTo6OuV+hvi80aSlpSElJQUikQitW7fm7IiCL02bNg2JiYmwtrau8I2Q67VlpbKysnD27Fn2zbFly5YYMmQIb2cXOTk5oV69eli+fDlOnTqFHTt2IDIyEhEREfjrr7/EzsmrzVJSUuDi4oJRo0Zh7NixcHBwQEZGBj5//ozZs2dj9uzZnMcsLCzE27dvv1oNnkvFxcWIjo7G6dOncfHiReTm5gIo+WDr6OgITU1NTuOVmjt3Lj5//ox169axI1c5OTlYvHgxBAIBtm/fznnM2loTiRIdCZJUfRBp17SRhnnz5oFhGKxZswY2NjY4efIkGjZsCDc3NxQWFmLnzp2cx6xsV4xAIOBlW2/37t3x/v17iESiCtu5utFUVHvla7i+uZmYmODQoUMVrpmRhjdv3oiVTuCKqakpTp06BV1dXTg6OqJly5bw9fXF69evMWDAAMTHx3MSp1evXtX+v+RzCjg/Px8qKirIy8vDrVu3oK6uLrYziitRUVHw9vbmvRp8RYRCIa5cuYIzZ87g6tWrKCoqQteuXXlJOjIyMuDo6Ii3b9+y57+9fPkSrVq1wtatW3lZRyPpmkhcoakrCZLU2UjSrmkjDdHR0QgLCxNbt1KvXj0sXLgQo0aN4iVmaGgoL89bGb5GM760d+9esa8ZhsGsWbPg4+PD+/b2du3a8bpDryKS3gINAKqqqsjJycGHDx9w9+5ddgfbixcvOF2MPGvWLPbvr169QmhoKEaPHg1jY2MoKCjgwYMHCA8P52w7e0UKCwvx4cMH9nvbpk0bCIVCnDx5kvMRlg0bNqB///5frQbPJyUlJfTr1w/9+vXDp0+f8Oeff+LMmTO8xNLS0sLp06dx7do1PHv2DMrKytDT00Pnzp152/RRmshIqngoVyjRkSBJno1UW7cB/ldycnJsYcSyMjMzJVJfp3Sht0gkgp2dHedF5kpJqvhaRYur5eTkYG5uzvti+lGjRmHx4sUYNmwYdHR0yv0sjxgxgvOYkt4CDQB9+/bF/PnzoaysDE1NTXTr1g1nz57FqlWrODuaBYDYQaEjRozAqlWrYGdnx17r168fjI2NsWnTJl4KwlU1wsJ1ovPq1SuEhISgRYsWMDIyQmZmJvr06QN5eXl25yufli9fDldXVzRq1AhDhw7ldfGuoqIievfuLbF1QZIuHsoVSnQkaNOmTbh+/Tr27NkDZ2dnACXTH97e3vD39+f0bCRp1rSRhkGDBmHlypXw8fGBQCBAbm4ubty4gRUrVnBWAwWo3kLvAwcO8LbQWxojD5K2fft2KCkpVfhJWCAQ8JLoSHoLNFCSXB08eBCvX7/GhAkToKSkBKFQiFmzZmH8+PGcxwNKfn5++umnctd1dHQ4rZRelqRHWCRVDf5rTp48ialTp/KyC0va05CSLh7KFUp0JOjMmTPs2UilLCws4OfnBxcXF04THWnWtJGGxYsXY8OGDRg5ciQKCwsxbNgwyMvLY+TIkVi8eDFncVatWoX79+/D09OTXeg9btw4DB8+XGyh986dO3lJdKQx8iBply9flnhMSW+BLo05efJkdiq7qKgIAwYM4G2XIFCyA8rPzw8rV65Es2bNAJRMla1YsYLTGjNlSXqEpWw1eCsrK6xdu5a3avAV4XPZa0WJoa+vL3799dcKd2BxTdLFQ7lCiY4ESepsJGnXtJEGJSUleHh4YN68eUhLS4NIJIKuri7n22cvXbokttDbxMQEnTt3xuDBg9nHjBgxAvv27eM0bilpjDxIw5s3bxAaGoqUlBQUFxejTZs2GDlyJOdbhEtJegs0ULJuZcOGDRKZyi7l5+cHV1dX9OrVC/Xq1QPDMPj06ROsra3h6+vLeTxA8iMsX1aD//PPP3mrBi9pZachS/n5+cHOzk4i9dkkXTyUK5ToSJA0zkaSZbdv3660/eHDh+zfuToaQdoLvSU18lDR1ubi4mKcO3eu3JA811NJt27dgrOzM/T19WFqagqRSIS7d+/i0KFD2Lt3Ly8H43p4eMDFxQWHDh3C2LFjceDAAVhYWLBboPmwefNmXL9+Hbt372YrevM1lV1KU1MT4eHhbI0ZoGTxN18JJCDZEZaEhATo6+uz99jLly9DTU0Nv/76K0aMGCGREZ2zZ89K/Dw6SZF08VCu0PZyCcrIyMDs2bPx6tUr5OTkoFWrVkhPT4eOjg62bdsGHR0daXexVilbsbbskQ/KysqQl5dHXl4e5OXlUbdu3Sq3RX5LzBs3boiNzJmZmeHkyZPsJ6p3797B1taWl/Uy06dPh46ODtzc3HD8+HGcOnUKBw8exPnz57Fq1SrcuHGDkzi9evWq1uMEAgHnawEcHBzQpUsXLFiwQOz6+vXrcfv2bV5rP0lqCzRQ8j0uncou+zMUFxcHFxcXREdH8xKXYRhkZGSgsLCwXBsfowKfPn3C6tWrYWFhAXt7e7i5ueH06dPsCEt1f9Yq8+HDB0ybNg2PHj3C6dOnoaenh927d2PdunUwNDRE/fr1kZSUhLCwMN7qP6WkpOD+/fsoKioqN7rBx7qyUl/ef/iUm5sLT09PXLx4EQzDQFVVFfn5+ejatSsCAgIkcnTJf0EjOhKkpaUl8bORZNmDBw/Yvx87dgxHjx6Fr68v2rVrB6BkJ5S3tzd69uzJaVxpLvSubOTBxcWFszjSWCdT6unTp9iwYUO56w4ODrzUJir1/PlzdpvsvXv3cPXqVRgZGfGW6EhqKrusq1evwtvbG5mZmWLX+ToTTlIjLBs3boSSkhKioqKgq6uLjx8/YvPmzejcuTN2794NAAgMDMT69euxdetWTmKWFRISgsDAQDRo0KDcdDlfC+iloV69eggKCmKLh5a+h/E5IsgFSnQkyNHREVu3bi13NtKHDx8wffp0HD16VIq9q33KbjsODAzEnj172CQHKFkk99tvv2HixImYMmUKZ3GludBbT08PFy5cwOfPn1GnTh0cPXoUt27dQsOGDXnb0i5pOjo6iI+PL1fN+t69e7xtXz127Bi8vb2xZ88eqKmpYebMmTA3N8eFCxeQnp7Oy7ZraUxlr1u3DmZmZnBxceGt4jNQvRGWgwcPcjbCcuXKFQQGBrKjGn///TcKCgrETofv27cvfv/99++OVZHw8HDMmzePnYLkS0WjfF9+0CrFx/l7aWlp7N/LJjel16V1jmNVKNHh2dWrV9nqw7dv38bWrVvLnXP18uVLiWx7lHUZGRnlDmB89uwZp7tYpLHQW5pViqVh6tSpWLZsGZ4+fcou+o6Pj0dYWBgWLlzIS8wdO3Zg5cqVsLa2xurVq9G2bVvs3bsXMTExcHd35yXRWbZsGWbPng0bGxsUFBRgxowZSE9Ph66uLrZt28Z5PKDkDWnTpk28Td+UkvQIS1ZWllgl4OjoaCgoKKBz587sNXV1dd7OpsvJyUH//v15ee6yvvaBraIPWnzcC/r27VvhvUggEEBOTg7379/nPCYXKNHhWeknGYZhwDAM7t27J7ZqXSAQQFVVlbctrD+KcePGwc3NDY6Ojmjfvj0AIDExEQcPHqxwBKY2kWaVYmkYPnw4gJLToffv3486deqgdevW8Pf3R79+/XiJmZ6ezo6i/PXXX2wROx0dHfz777+8xJTGVLaFhQUSEhJ4T3QkPcLSrFkzvHjxgq02f+3aNZiZmYmNWt25c4eXYxGAknpa4eHhcHd357Vsh7R31H65Hk8kEuHly5fYsmULZs6cKaVeVY0SHZ7p6Oiw6wo8PT2xZMkSXoeMf1S//vorNDQ0cOTIEezatQtAyW6SpUuXwt7eXsq9+z7SrFIsLcOHD2cTHknQ1dXFjRs3oKmpiZcvX7I1kEq38HPF2toaVlZW7J/27duXm8rm088//wwfHx9cvnwZLVq0KLdVmKuDaCU9wjJ06FD4+flhzpw5iImJQUZGBjw8PNj2hIQEbNiwgbfjYLKyshAVFYVTp06hefPm5b6vYWFhvMQtdfr0afTq1YuXkgRlla2fU6pFixZQV1fHwoULa+zOK0p0JOjWrVsoKioqdz0jIwNDhw7lbZfFj2L06NFinxhJ7XXt2jUcPnwYKSkpkJOTQ/v27TF+/HhetpYDwJw5c7Bo0SKIRCIMHjwYBgYG8Pf3xx9//IEtW7ZwFmfhwoWIj49HeHg4/Pz8oKamBktLS7HEh0/R0dEwMjJCVlYWsrKyxNq4HImQ9AjLjBkz8PHjR3h7e0MgEMDV1ZU95mLVqlUIDQ1Fz5492Yr0XGvTpo1URzSWLl0KExMT3hOdrykuLkZGRoZUYlcHbS/n2dmzZ9nTck+dOoV+/fqVK0D2v//9D6mpqfj777+l0EPZ8ffffyMxMbHC7Z1cfVKtKSS5pVTS/vjjD/j6+mLQoEEwMjKCSCTC/fv3cf78eaxbt46XtRDJyclo3LgxMjIyYGBgAKBkfVeDBg14O7AwNzcXcXFxiI+Px71795CYmAiBQABLS0tYW1tjwoQJvMSVhODgYJw7d44dYTl06BACAwPZ5CMhIQG//vorRo0axcv6p7IeP34MkUiEDh068BqnVFFREeTl5SVaeV5S94NNmzaVu5abm4tTp07B3Nyclx1tXKARHZ516tSJTWAYhoGcnFy5Qwr19fXh7u4uje7JDD8/Pxw8eBD6+voVbu8ktcf27duxYsWKclNXlpaW7LlJXHN0dMTOnTthZGTEXuN7HUu9evVga2sLW1tbfPjwAbGxsbhw4QIuXbqEixcv8pboJCYm4unTpxCJRAD+76y0R48eie0A+x7SHmEpi+9RslJhYWHYt28f0tPTce7cOYSEhKBhw4aYN2+ezJQPuXPnjtjXAoEAioqKGDNmDKc7W7lGiQ7PGjVqxJ5B9OzZM6xatUpqw4uy7OzZs/D19eX9ZGJpkGaVYmnIyclhd1uVZWFhwdt5Xk2bNkVGRoZYosOnrKws3Lx5EzExMYiJiUFqaipatmwJKysrrFy5stJT6r/H5s2bERwcjCZNmuD9+/fQ0tLCu3fvIBKJOF3oLS8vD3d39wo/wI0YMQLDhg2T2AiLJOzduxcHDhzA3LlzsXz5cgBAly5d2GM1vix+ybUVK1ZI5OTw0NBQ3mPwgaauJMjKygoHDx6s8PRg8n1sbGxw6NAhtG7dWtpd4Zw0qxRLQ2BgIB4+fIg1a9awidynT5+wdOlS6OjoYP78+ZzH9PDwwKlTp2BgYIDmzZuXm14uW/L+e6xevRoxMTFITk6Grq4urKys2AXKmpqanMSoTNeuXTFnzhyMHj0avXr1wv79+6Gmpob58+ejffv25bYpk+rp378/fvvtN9ja2opNI924cQOenp64du0a5zH/97//VXi9dJSlYcOG5WYPuJCcnIzHjx+joKBAohWgvweN6EiQvr4+7ty5Q4kODyZMmIAtW7ZgxYoVnB/kKW3SrFIsDTExMXjw4AF69OgBXV1dyMvLIy0tDfn5+dDS0sKJEyfYx5auf/teAoGA3VLOp/3790NLSwvu7u4YPHhwuRE5vmVnZ7OnlBsYGODu3buwt7fH/Pnz4erqSonOf/TmzRu0atWq3PWmTZvyVim9b9++KC4uZr8urW5dSkFBAX369IGvry9nO313796NgIAANGjQoNxz1uQK0JToSFDdunXh6+uLoKCgCj818r0FUZbduHEDCQkJOHfuHBo2bFhueydXb4iEf2PGjJF4TL6mxL4UEhKCmJgYnDx5EgEBAWjdujWsra1hbW0NS0tL3s8Katq0KdLS0qCtrQ09PT08fPgQ9vb2qFu3brldWKT6TE1NcfToUcybN4+9VlxcjF27dlU4DcsFHx8f7Nq1C7/99ht7TEliYiL8/PwwePBgdOrUCQEBAfD39+ds7dXu3bvh6emJSZMmcfJ8kkJTVxJU1TZVvncfyLLIyMhK24cNGyahnpDv5eTkhCVLlkj8/JwrV65g//79SE1NRWhoKI4cOYJmzZrxVrIgJycHt27dYtfqpKSk4KeffmITHy4Ou/xSSEgI9u3bh9WrV6Nhw4aYNGkSZs2ahZiYGOTn5/N2RIKsS05OxvTp06Guro7k5GRYW1vjxYsXKCgowO7du8tVbOdC9+7dERgYiJ9//lns+r179zB37lxcvXoVDx8+hJOTE2JiYjiJaWFhgcjIyFq325NGdCSobCIjjS2IsqyyRIavsu+EH48ePYKCgmRvTSdOnMCqVavg6OiIu3fvori4GBoaGvD390d+fj4mT57MecwGDRqgT58+6NOnDwDg4cOH+P3333H48GEcOHCAlxL+zs7OaNq0KVRUVNCxY0d4eXkhPDwc6urqWLVqFefxfhTt2rXDhQsXcOrUKaSkpEAkEqFv374YMmQIb1Ppnz59qvD3RCAQ4OPHjwBKdvZVdEr9fzV06FCEhobCy8uLs+eUBBrRkbAfYQuiNLx9+xbbt29HcnIyO29dum32+fPniI2NlXIPSXVt2rQJly9fxujRo9G8efNyZ5XxUUV48ODBcHFxgZ2dndhi0vPnz2Pt2rWcr5PKzc1FYmIi4uPjkZCQgISEBPz7778wNDSEhYUFLC0t0b17d05jEv4VFxdDTk4Ob9++RWxsLDp06FDucFquLFmyBHFxcfD29oaRkREYhsGDBw/g5+cHAwMD+Pj4YOXKlfjf//5X7hiZbzF+/Hj274WFhUhISICGhgaaN29ebrFzTV1+QSM6EiTtLYiyzMvLC69evUK/fv2wZ88eTJkyBS9fvsSff/5Z6z59/OhKD7RcsWJFuTa+Dit8+fJlhVvLDQwM8O7dO87ieHh4ID4+HqmpqVBSUoKJiQksLS0xceJEmJmZoU6dOpzFKvUtC4y52l32oymdLlqzZg3atm2LESNGIDc3F0KhEIGBgejbty/nMZcuXQpfX184OzuzFfcVFBQwfPhwuLu748aNG3j48CHWrVv3XXHS09MxYMAA9mezW7du3913SaNER4LCw8OxYsUK2NrawsfHBwDwyy+/oH79+vD09KRE5zvExsZiz549MDMzw40bN9CjRw+Ym5sjJCQEf/31V62uMvujkcbBhT/99BOuXr1a7ufk6NGjnBac+/DhA4YNGwZLS0sYGxtLZIqOjy3GRJy/vz969+4NY2NjhIaGQkFBAdHR0Th58iQ2bdrES6KjrKyMlStXwsvLC8+ePYOCggJatGjB1mkrOy36PdLT0zFlyhSJ1OnhCyU6EiSNLYg/CoZh2JO827Zti4cPH8Lc3Bx2dnbYvXu3lHtHvlVeXh6OHz+OZ8+eQSQSoU2bNhg4cCBv27Hd3d0xY8YMREdHo7CwEMHBwXj+/DmSkpKwfft2zuKEhIR89fqYMWPQoEEDzmKVktSOsh/Zw4cPsX79etStWxeXL19G7969oaysjM6dO7Mj9lyIjo6GpaUlm0h9qezOOa6meGVhdQslOhIkjS2IPwpDQ0McP34cLi4uMDAwwPXr1zFx4kSkpaVJu2vkGyUlJWHatGlQVFRkz7q6fPkytm7dioMHD6Jt27acx7SwsMD58+dx6NAhyMvLIycnBxYWFtiwYQNnB09WZvv27bCzs+Ml0fnS186EKz2qgXw7dXV1pKeng2EYJCYmsmfr3b9/HxoaGpzFmTJlCm7cuIHGjRtXeuQC11O8tX3TDC1GlqCvbUEUCoXYtWsXL1sQfxRxcXGYOXMmZs6ciaFDh2Lw4MGoX78+MjIyYG9vj2XLlkm7i6SaJk6cCB0dHfj6+rJTO0VFRfD29sabN2++a2FlTSWpQxmrOhPuwIEDvMaXVZs2bcKhQ4egqKiIJk2a4NixY/j9998REBCAefPm8bJrT1L09fWrnejwsX6OC5ToSFhBQQFOnjzJDsm3bt2a1y2IP4rs7GwoKioiPz8fTZo0QUZGBi5evAh1dXXY2dnRjrZaxMTEBJGRkeUO1Xz27BkcHBwQFxfHSZyJEydW+wbOdwIgqUSna9eumD9/vkyeCSdtf/75J16/fo0hQ4agUaNGuHr1KoqLi9GzZ09e4vXv3x/du3eHra0trK2ty+1O5Iq+vj42btwINTW1Kh/Lx45ILtDUlYQpKytj5MiR0u6GzLG3t0dwcDAMDQ0BAFpaWmLbIkntoampiZcvX5ZLdF68eMFZKXsAMDc3Z/+enZ2NI0eOoHfv3jAyMoKioiIePnyICxcuSOTnaOfOnewaMz6JRKJyBeYIN75ccMx3eYAFCxYgOjoavr6+ePv2LSwsLNCtWzfY2tpyeuafQCCApaUlLUYm1dO9e/dKP0HSMQX/nbKyMhUGlBGjR4/Gb7/9hjlz5rBr1+Lj47FlyxZOj4cou1autBrzuHHjxB5jbW1d4enxXMnJycGTJ09QVFRUrtYTH5+OZflMOGl6/fo11q5di6SkJAiFwnILePm4t/fv3x/9+/cHALx69Qr//PMPrly5An9/f2hra+PixYucxJGFSR9KdCSo7I0VKFl3kJaWhsjIyHJt5NvY2trCyckJ3bp1q/AcsdLFgaTmmzp1KvLz87Fhwwb8+++/AAANDQ1MnTqVt7UOd+/ehbe3d7nrZmZmnJ0T9KXIyEj4+Pjg8+fP5dr4qhdEZ8Lxw83NDR8/fsT48eNRv359icXNzc1FfHw8YmNjERsbi4SEBDRq1Igd2ebCsGHDyt1Paxtao1MD/PXXXwgJCaFzZr7DxIkTv9pGiyxrPgcHBwwZMgQDBgwQ26Xy/v17KCsrczplVZFx48ahRYsWWL58OVsY7ePHj/Dy8sLHjx+xb98+zmP2798ftra2mDdvHu+vrxSdCcePjh074ujRo2jXrp3EYtrb2yMlJQW6urowNTXFzz//DAsLC06nrWQFjejUAG3atMGDBw+k3Y1aLTQ0VNpdIN/BysoK+/fvx9q1a2FtbY0hQ4agX79+ElsXUFphtnPnzmjRogUYhsHLly+hra391do33+vt27eYMGGCxJIcgBIZvrRu3Vrip783b94cb968YY+dUFBQkPgZcbUFjehIUEUFnj59+oS9e/fi8+fPOHr0qBR6JXtSU1Nx+PBhiEQi2NnZwcTERNpdItUUFxeH8+fP48KFC8jOzkbPnj0xZMgQ2Nra8n4TFwqFiI6OxtOnTwGUHNTYuXNn3uIuXLgQhoaGcHJy4uX5S40fPx7btm1DgwYNMG7cuErXCdbUs4pqorL387t37+LIkSOYOXMmdHV1y+3y5HM30uPHj3H79m3cunULd+/eZRcPb9iwgbeYtQ2lfxJUUYEnRUVFGBsb87YOQJbl5eXB398fZ8+eBVAylDt+/HiMHj0ajRs3BsMwOHDgAIKCgtC7d28p95ZUh5mZGczMzODp6Yk7d+7g/PnzWLp0KQoLC/HLL79gyJAhvO0aUlJSQr169aCuro7+/fvjf//7H3tALB8aNWqEwMBAnDlzBi1atCi3Xoarc6dsbGzY5+7cuTMnz0kqvp+XnmFYFl/rrUq1b98eDMNAJBKhqKgIf//9NxISEniLVxvRiA7PPn78KNHFaT+SJUuW4P79+3B0dESjRo0QGhqKhw8fwt7eHp6engCAjRs3IiYmBuHh4VLuLfmvGIZBTEwMu6uFjzeN9+/fY8aMGXj69CkKCwtx/vx5+Pn54cmTJ9izZw8vJ1CX/ox+Dd9HNxQVFUFeXr7WV739UYWGhuLmzZu4ffs2hEIhrK2t0aVLF3Tt2pXW6XyBEh2edejQAfr6+rCysoK1tTUsLS0lOicvyzp16oSQkBB2C/KHDx/QuXNnREREsCdRv3r1CoMGDcK9e/ek2FPyX+Tm5uLSpUu4cOECoqOjoaOjg8GDB8PZ2ZnzWPPmzQPDMFizZg1sbGxw8uRJNGzYEG5ubigsLMTOnTs5jyktYWFh2LdvH9LT03Hu3DmEhISgYcOGmDdvHhXW/I+Ki4uxc+dOaGhoYPjw4QCAyZMns7tB+Ugm7e3t0bVrV3Tt2hXm5ua8FQyUBTR1xbOdO3ciPj4e9+7dQ2RkJHJzc9G+fXtYWVnBysoKlpaWNOLzH2VnZ6Np06bs140aNYKKiopYBc86deqgoKBAGt0j/0F2drZYctOkSRMMHDgQrq6uvB6REh0djbCwMHbHFQDUq1cPCxcuxKhRoziLs2nTJjg7O0NFRQWbNm366uP4Ondq7969OHDgAObOnctOs3Tp0oU9eHLBggWcx/wR+Pv74+LFi/Dx8WGvDRw4ENu2bUNOTg7mz5/PecwTJ04gNzcXioqKUFJSwpMnT3Dt2jUYGRmhU6dOnMerzSjR4VmXLl3QpUsX9utnz54hISEBcXFxCAoKwtOnT9GuXTtYW1vD3d1dij2tneTl5aXdBcKB8PBwREVF4datW6hbty769++PvXv3wsLCQiLx5eTkkJ+fX+56ZmYmpzVE7ty5gylTpkBFRQV37tz56uP4mk4KDw/HihUrYGtry74p//LLL6hfvz48PT0p0fmPzpw5g61bt8LU1JS9NnLkSLRu3Rrz5s3jJdG5cuUK5s+fj61bt0JXVxfjx49Ho0aNsGXLFnh4eHBaXLO2o0RHwtq0aYOWLVtCT08Pbdq0wb1793DlyhWkpqZSovMfxMbGio2IMQyDuLg4vHr1CkBJ5VlS8/n7+6NXr17YvHkzunXrJvFtsoMGDcLKlSvh4+MDgUCA3Nxc3LhxAytWrMCAAQM4i1O2DII0SiK8efMGrVq1Kne9adOm9LvyHQoKCipMiOvVq4dPnz7xEnPDhg2YMWMGbGxssHHjRjRp0gRnz57FpUuXsGbNGkp0yqBER0IePHiAmJgYxMTEsKXezczMYG1tjUmTJsHY2FjKPaydKhred3NzE/uaFlvWfDdu3KjwSILY2FgYGxvzvv5g8eLF2LBhA0aOHInCwkIMGzYM8vLyGDlyJBYvXsxb3KSkJBw8eBCpqalYt24d/vzzT7Ro0QLdunXjJZ6pqSmOHj0qVom9uLgYu3btYte6kW/XvXt3+Pr6Ys2aNezBrGlpaVi9ejVsbW15ifnixQvY29tDIBDg8uXL6NOnDwQCAQwMDPD27VteYtZWtBiZZ7/++iu7Kt7MzIxdlGxsbEzFnQipws8//4wTJ07wfqp3qc+fPyMtLQ0ikQi6urq8ngf1999/Y86cObCzs8OZM2dw5swZREZGIiQkBKtXr8bgwYM5j5mcnIzp06dDXV0dycnJsLa2xosXLyAUCrFr1y5e10HJsuzsbMyePVtshDk3Nxc2NjZYu3YtmjRpwnnMPn36YMmSJWjWrBmGDh2KsLAwmJub448//sD+/fvZshuEEh3e6evrQ1NTE+PHj0eXLl1gaGhIIwyEVJOZmRlOnjzJS6ITHR0NS0tLKCgoVFjMsyw+Cr4NHz4co0ePxujRo8Ve5++//44DBw7g3LlznMcESqZZTp48iWfPnkEkEqF169YYMmQIHfLJgeTkZKSkpEBRURGtWrWCnp4eb7HCwsKwevVqyMnJwdzcHHv37kVwcDCCg4Ph7++PQYMG8Ra7tqFEh2cpKSmIiYnBzZs3cevWLYhEIpibm6NTp06wtraGgYGBtLtISI3FZ6Kjr6+PGzduoHHjxpWOZPBV8M3U1BSnTp2Crq6u2Ot8+fIlBg0aREXfapnCwkK8ffuWLTLJMAyEQiEePnyIIUOG8BLz4cOH+N///oeuXbuiTp06uHfvHurUqUMjc1+guROe6enpQU9PD+PHjwcAPHr0CDdv3kRMTAy2bt0KOTk5WFpawtrautKDKQn5Ec2cOVOsXACXHjx4AIFAgOLiYqmcNaejo4N79+6VS+IuX77M21Td69ev2cKLQqEQX37OpdPL/5uoqCh4e3tXuKBbS0uLt0SnQ4cOyM/Px5kzZ9C/f3+oqqpWuNj8R0cjOlLy+fNnJCQk4NSpUzh9+jQ+f/7Ma5lwQog4fX39ak0jCwQCPHz4kPP4Fy9ehJubG0aMGIHw8HA4OTkhLS0NFy5cQEBAAOzs7DiPOX78eHz8+BEjRoyosH4XHfr53/zyyy+wsrLC5MmTMXbsWISEhCA7Oxu+vr6YNWsWHBwcOI/5/v17zJw5E8nJyRAKhbhw4QLv1bxrK0p0JIBhGDx58gQJCQnsn5SUFDRp0gTm5uawsLCApaUl2rZtK+2uEiJ1lSUgioqK0NDQgJ2dHebOnVvufKhvcevWra+2ZWRkYOPGjXj9+jUGDhyI9evX/+c4lUlKSsKePXuQkpLCrpeZPHkybwfRduzYEUePHkW7du14ef4flZGREc6ePYsWLVpg6tSpGDt2LPr06YPr16/D398fp0+f5jzmj1TN+3vR1BXPJkyYgAcPHuDz58/Q1dWFhYUFJk+eDAsLC4ntJCGkNlm+fDm2bNmCOXPmwNTUFAzD4P79+wgKCoKDgwN++uknbN26FQzDfNfWbysrq3LXiouLceDAAWzZsgUaGhrYu3cvrydP6+vrc3Z4Z3W0bt0aWVlZEov3o2jQoAFbcLJ169Z49OgR+vTpg9atW7M1vbgmqWresoASHZ61a9cO48aNg4WFBTQ1NaXdHUJqvN27d8PPz0+sloy+vj60tbWxfPlyREVFQUtLC3PmzOG0xk1cXBx8fHzw4sULzJw5E1OnTv2uEaOqCIVCHDlyBI8fP0ZBQUG59TJcJUBld5T169cPbm5umDlzJnR1dcudbcVnUifLevbsCR8fH/j4+MDKygpr165F9+7dceHCBWhpafESU1LVvGUBJTo8W7ZsWYXXly9fDldXVzRq1EjCPSKkZnv37l2Fbw6NGjViC6FpaGhwVnE2OzsbAQEBOHbsGHr06IGtW7eiefPmnDx3Zby9vREVFYUuXbrwet7dlClTyl0rPeeqLL52l/0IvLy8sHr1ajx48AD29vb4888/MXr0aKiqqiIgIICXmJKq5i0LaI2OlEi6EBohtcWvv/6KDx8+wN/fHy1atAAAvHz5EkuWLEHdunWxdetWBAUFITo6Gn/88cd3xTpy5AjWr1+PunXrwsvLC7179+biJVSLmZkZgoODJTaKkpubC3l5eaioqJRry8jIwNq1a3lbiyTLEhISoK+vz1bvvnz5Mv755x80bNgQI0aM4G1ERygUYsOGDQgLC0NhYSEAsNW8PT09aVSnDEp0pITP+iCE1GbZ2dmYP38+oqOjUb9+fTAMg0+fPqFr167w8/NDYmIivLy8EBwcjJ9//vk/xxkzZgzi4+Ohra2NKVOmiK11+NKIESP+c5yv6d69O3bv3s37JoSMjAy4u7vj5s2bAIBu3bph7dq1UFNTg0gkwt69e7Ft2zYoKCiwjyFV+/DhA6ZNm4ZHjx7h9OnT0NPTw+7du7Fu3ToYGhqifv36SEpKQlhYGNq0acNbPyRZzbu2okRHSijRIaRiycnJaNu2LVJTU/H48WPIy8ujbdu2bH2Qz58/Q1lZ+bsrjPfq1atajxMIBLh06dJ3xSpVWkwOAP744w+cP38ey5Ytg66uLuTl5cUe++X6mf/KxcUFycnJcHV1haKiIoKCgmBsbIx58+bBxcUFSUlJGDFiBObPn4+GDRtyEvNHsHTpUjx58gQBAQHQ1dXFx48f0bVrV1hYWGD37t0AgMDAQDx9+hRbt27lJGZVFbzLovVW/4cSHSlJT0+HlpYWZzczQmSFjY0Ndu7cCSMjI2l3hXNlt86X3nq/lrBxtV7G2toaGzduZN/4Xrx4AQcHB7Rs2RIikQgrV66kQ4X/g27duiEwMBDm5uYAgLNnz2LBggXYvHkz+vXrBwC4f/8+nJycKi1l8C2qW/GY1luJo8XIEpaSkoL79++jqKio3C4LPobHCaltmjZtioyMDJlMdA4cOMD+XSQSlRvF4UNOTo7YmUutWrVCYWEhmjdvjg0bNvC6s0yWZWVlQVtbm/06OjoaCgoK6Ny5M3tNXV0dQqGQs5hJSUmcPdePhBIdCQoJCUFgYCAaNGhQbh5VIBBQokMIgPbt28PV1RUGBgZo3rx5uUWVkqw7w7WytXsGDRqEdevW8X4uEcMw5RIqeXl5zJ49m5Kc79CsWTO8ePECzZo1Q3FxMa5duwYzMzPUq1ePfcydO3fEkiE+vH37FgUFBeWu07KI/0OJjgSFh4dj3rx5mDFjhrS7QkiNJRAIeDsbqCb5999/JTKi8zW0aPX7DB06FH5+fpgzZw5iYmKQkZEBDw8Ptj0hIQEbNmzgrXjf9evX4e7ujg8fPohNgzIMQ1NXX6BER4JycnLQv39/aXeDkBpt9erV0u6CRAwZMgROTk4YPHhwhSNXXI7wnj59WiyxKS4uxrlz58rV8aJR5eqbMWMGPn78CG9vbwgEAri6urLnk61atQqhoaHo2bMnnJ2deYnv6+sLGxsbTJs2jdc6TLKAFiNLkK+vLxQVFeHu7v7dO0YIkVWbNm2qtH3u3LkS6gm/Ktv1xeVOL2nsLvvRPX78GCKRCB06dOAtRseOHXHmzBmaoqoGGtGRoKysLERFReHUqVNo3rx5ufnxsLAwKfWMkJrjzp07Yl+LRCK8evUKOTk5MlXx9fLlyzIVh/yf9u3b8x6jU6dOuH37NiU61UCJjgS1adMGM2fOlHY3CKnRQkNDK7y+Zs0aFBUVSbg33Lp9+3a1H2tpacljT0htVHa0U0NDA8uWLcPff/+NFi1alCtVIisjn1ygqSspKSoqgry8PE1hEVJNaWlpGDZsWLkRn9rkyx1WpYtHlZWVIS8vj7y8PMjLy6Nu3bqc1V4hsmPixInVepxAIBArZfCjoxEdCQsLC8O+ffuQnp6Oc+fOISQkBA0bNsS8efOoeCAhlTh//nylxzTUBg8ePGD/fuzYMRw9ehS+vr5o164dACA1NRXe3t7o2bOntLpIarCKRjtLd1kBJRteGjRoIOlu1XiU6EjQ3r17ceDAAcydO5c9PbhLly7w9fUFACxYsECKvSOkZujevXu5kc5Pnz4hNzcX7u7uUuoVN8puJw8MDMSePXvYJAcAWrZsid9++w0TJ06s8NRxQkq9e/cO7u7uMDIywvz58wEAdnZ2MDIywurVq8vtqPuRUaIjQeHh4VixYgVsbW3h4+MDAPjll19Qv359eHp6UqJDCIB58+aJfS0QCKCoqAhjY2P2NHNZkZGRUW4669mzZ+xJ2IR8zdKlSwGIlwQICwuDr68vVq5ciQ0bNkirazUOJToS9ObNG/ZgwrKaNm2KnJwcyXeIkBpo2LBh7N+zsrKgqKgoVm1WVowbNw5ubm5wdHRkd+kkJibi4MGDcHV1lXLvSE138+ZNREREiO26atWqFby8vDBmzBgp9qzmoURHgkxNTXH06FGxT6zFxcXYtWsXOnbsKL2OEVKDFBcXIygoCOHh4cjOzgZQssPEyckJkydPlmrfuPTrr79CQ0MDR44cwa5duwAA7dq1w9KlS2Fvby/l3pGarm7dunj16hVat24tdj0jI4OO9vgC7bqSoOTkZEyfPh3q6upITk6GtbU1Xrx4AaFQiF27dvF+5g0htcGqVatw8eJFzJ07Fx06dEBxcTESEhKwefNmDBs2DAsXLpR2FzmxZcsWDB8+nPezkIhs2rx5MyIiIjB37lwYGhoCAB4+fIigoCAMGDAAixcvlnIPaw5KdCSsoKAAJ0+exLNnzyASidC6dWsMGTKEzp0h5P8zNzfHjh07YGFhIXb9n3/+wfz583Hz5k0p9YxbFhYWiIyMpIJv5D8pLi7G5s2bcfjwYWRlZQEAGjVqhIkTJ2L69OlSPUetpqGpKwlTVlbGyJEjpd0NQmqs+vXrQ0Gh/K2pbt26MjUkb29vj61bt2L69OnQ1tYud9YVlZsgX5OQkAB9fX3MmzcP8+bNw/Hjx3Hz5k3o6Ohg2LBhlOR8gUZ0eNarV69qFwWkc2bIjyotLY39+4ULF3DkyBF4eXnByMgIAoEAT548wapVqzBhwgSMHj1aij3lTvfu3ZGRkfHV+wOdPk2+9OHDB0ybNg2PHj3C6dOnoaenhz179iAgIABGRkaoV68ekpKScPDgQejp6Um7uzUGJTo8O3LkCPv3V69eITQ0FKNHj4axsTEUFBTw4MEDhIeHY+LEifj111+l2FNCpEdfX599wy97S/rymkAgkJkEoKrKx1ZWVhLqCaktli5diidPniAgIAC6urr4+PEjunbtCgsLC+zevRtASX2mp0+fYuvWrVLubc1BU1c8KztNNWLECKxatQp2dnbstX79+sHY2BibNm2iRIf8sH7E0czSRCYlJQUpKSnsmj3alEC+5sqVKwgMDGTXdf39998oKCgQG+Xs27cvfv/9d2l1sUaiREeCUlJS8NNPP5W7rqOjg1evXkmhR4TUDM2bN6/wOsMwkNVB53///Rfu7u64cuUK1NTUIBKJ8OnTJ1hYWCA4OBj169eXdhdJDZOVlSW2Sy86OhoKCgro3Lkze01dXR1CoVAa3auxaLWbBJmbm8PPzw/p6enstRcvXrDVkgkhJUXzRo8eDUNDQ3To0AGGhoZif2SFr68vMjMzce7cOdy8eRN37tzBqVOnkJ+fj9WrV0u7e6QGatasGV68eAGgZNfVtWvXYGZmJlZQ886dO1Sy4As0oiNBfn5+cHV1Ra9evVCvXj0wDINPnz7B2toaK1askHb3CKkRVqxYAWVlZQQFBclkReRSf/31F/bv3y9W8K1t27ZYunQppk+fLsWekZpq6NCh8PPzw5w5cxATE4OMjAx4eHiw7QkJCdiwYQNGjRolxV7WPJToSJCmpibCw8ORnJyMlJQUACWVUGl1PCH/Jzk5GYcPH65wmleWfO0kdoFAAJFIJOHekNpgxowZ+PjxI7y9vSEQCODq6squ+Vy1ahVCQ0PRs2dPODs7S7mnNQvtupKwwsJCvH37FsXFxQBK1iAIhUI8fPgQQ4YMkXLvCJG+MWPGwNnZGb169ZJ2V3jl7e2Nx48fY82aNeyozrNnz+Dh4YGWLVsiICBAyj0ktcnjx48hEonQoUMHaXelxqFER4KioqLg7e1d4QGeWlpauHLliuQ7RUgNExYWhq1bt2Lo0KHQ1dUtVySw7GnNtVlOTg5mz56N27dvs1N0ubm56NGjB9asWQM1NTUp95AQ2UCJjgT98ssvsLKywuTJkzF27FiEhIQgOzsbvr6+mDVrFhwcHKTdRUKkrrKRHIFAUKu3opeO5JZVOpVdp06d/9fevYU0GTdgAH+mZpYlMSGjVJghakli2ckkzA06IEhRKAhiyVDqYl2kEVpkBEkmaAqBUJFmhpqhdqCLzTDLJGUeYhvEItERkiwptQNu+y4+GkUJ67Pt/777nh94sXf/i+dGffifXsTExCA6OhoAb0Ym+le4R8eHJiYmUF9fj+joaCQmJuLDhw/QaDQIDAxERUUFiw4RAIPBIDqC12zYsMGjm9IVCgVMJpMPEhH5PxYdHwoLC8OXL18AACqVCmazGRqNBiqVivfoEP1kamoKra2tGBsbQ3FxMfr7+7F+/XrExcWJjrYoDQ0NC343OTmJ6upq2Gw2HDhwwIepiPwb50Z9aM+ePSgvL8ebN2+wfft2dHR0YGRkBHfu3EFERIToeESSMDo6ir1796Kvrw8PHjzA3Nwc+vv7ceTIEfT29oqOtyjbtm377SclJQUmkwnl5eUIDg7GzZs3UVVVJToqkd/gHh0fmp2dxaVLl5CSkoKsrCwUFxfj4cOHWL58OSorK/3+lAmRJ3Jzc7F7924UFhYiOTkZnZ2diIqKQl1dHfR6Pe7fvy864j9jNBpRXl6Od+/eoaioCAUFBX71hnYiKWDREWxmZgYhISEICuIqIhEAJCcno6OjA9HR0b8UnfHxcWRmZmJ4eFh0xEWbnp5GZWUl2tvbkZ6ejrKysgVfg0FEi8P/roKMjY2hpaUFTqcT+/btQ1JSkuhIRJIQHh4Oq9XqPn30w+DgIFavXi0o1b/T2tqKqqoqhIaGoq6uDmq1WnQkIr/GouNlc3NzqKiowKNHjwAAWVlZyM3NRXZ2NsLDw+FyuXDr1i3U1tbyDx4RAK1Wi7Nnz0Kr1cLlcuH58+d4//49GhoacOrUKdHxFiUnJwfDw8NYu3Ytjh49io8fP6Ktre2PY/3lviAi0bh05WWlpaV4/fo18vLyoFQq0djYCJPJhKysLJw5cwYAUF1djZcvX+Lu3buC0xJJg8FgwPXr12G1WuFwOKBSqZCfny/700ie7sOT+31BRFLCouNlO3bsQH19PTZt2gQAsNvtSE1NRVtbGxITEwH8936dzMxMDA0NCUxKRETkf7h05WXT09NYs2aN+7NSqcSyZct+ud49JCQE3759ExGPSBJqamo8HqvT6byYhIj8DYuODwQGBoqOQCRpAwMDHo3z5FZhIqKfsej4wODgIFauXOn+7HK5YDQa3bch/+kln0T/TxobGz0ax98VIvpb3KPjZfHx8R6NUygUMJvNXk5DJH2XL19GSUnJb8/b29tx5coVvHjxQkAqIpIrzuh4mcViER2BSFa6urrw+fNnXLhwAQqFAhaLBefPn4fZbMaxY8dExyMimeGMDhFJis1mg1arRWxsLCIiItDU1ISMjAycPn0akZGRouMRkcyw6BCR5ExPT6OoqAgjIyO8TJOIFoVFh4iE+9Px8q9fv6KpqQlxcXFIS0tzP+fxciL6G9yjQ0TCLXS8/Mc74H58z+PlRPS3OKNDRJLkcrncxebTp08ICwsTnIiI5ChAdAAiop9NTU2hoKAA1dXV7mf79+9HYWEh7Ha7uGBEJEssOkQkKefOnQPw69u7m5qaMD8/j4sXL4qKRUQyxaUrIpKULVu2oK2tDSqV6pfnVqsVOTk5ePXqlaBkRCRHnNEhIkkJDQ11vx7lZ5OTk1iyZImAREQkZzx1RUSScvjwYZSWlkKn02Hjxo0AAJPJhNraWhw8eFBwOiKSGy5dEZGkOJ1OXL16FS0tLe7Nx0qlEnl5edBqtQgMDBSckIjkhEWHiCTLbrcjODgYK1asEB2FiGSKe3SISHIsFgvKysqg0+kwOzuL27dvo6enR3QsIpIhFh0ikpRnz54hJycHDocDw8PD+P79O+x2O44fP46uri7R8YhIZrh0RUSScujQIWRnZyM7OxvJycno7OxEVFQUmpub0dDQgMePH4uOSEQywhkdIpKUt2/fIjU19bfnu3btgs1mE5CIiOSMRYeIJCUyMhJDQ0O/PTcYDIiKivJ9ICKSNd6jQ0SScvLkSZSUlGB0dBQOhwP37t3D+Pg4njx5gsrKStHxiEhmuEeHiCTHYrHgxo0bsFqtcDgcUKlUyM/PR1JSkuhoRCQzLDpERETkt7h0RUTC1dTUeDxWp9N5MQkR+RsWHSIS7tq1awgICEBCQgJCQ0Ox0ESzQqHwcTIikjsuXRGRcM3NzdDr9TAajdi6dSvUajXUajWUSqXoaEQkcyw6RCQZMzMz6OnpgV6vR29vL2JjY6HRaKDRaBAZGSk6HhHJEIsOEUnS/Pw8+vr6YDAY8PTpU6xatQoajQYnTpwQHY2IZIRFh4gky+l0YnBwEHq9Hq2trXA6nTAajaJjEZGMsOgQkaT8WL7q7u5GT08PgoKCkJ6ejoyMDKSlpWHp0qWiIxKRjLDoEJFwExMT6O7uhsFgwMDAANatW4eMjAyo1Wps3ryZp62I6H/GokNEwiUkJCAoKMh94iomJmbBsTt37vRhMiKSOxYdIhIuPj7eo3EKhQJms9nLaYjIn7DoEBERkd8KEB2AiIiIyFtYdIiIiMhvsegQERGR32LRISIiIr/FokNERER+6z9Qd5WtlC7smgAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<Figure size 648x360 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Displayed below all sum of all the cases across all Germany.\n",
    "plt.bar(num_of_states, states_all_cases_frame.iloc[:, :-1].apply(sum))\n",
    "plt.xticks(rotation=90)\n",
    "plt.title(\"Total Confirmed Cases\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "still-missouri",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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NgrOzMzIyMgAAWVlZmDNnDkaMGIEjR46gWbNmcHJyQnl5OQAgOjoagYGBWLFiBfbt24fExET4+fmxj7927VrcvXsXu3fvhqenJ7Zs2YJTp/iZK0IIIYQQ2fNFiczjx4/x888/4/nz52LHY2Nj8fTpU3h5eaFjx45wdHSEsbExDh8+DAA4ePAgdHV1MXPmTHTs2BE+Pj7IyspCbGwsAGDv3r2YNGkS+vfvDwMDA6xcuRJHjx5FYWEhioqKcPDgQSxduhT6+voYMGAAZsyYgfDwcI7/BIQQQgiRVV+UyNy+fRu9evXCH3/8IXY8ISEBXbt2hZqaGnvMxMQE8fHx7HkzMzP2nIqKCvT09HD37l2IRCIkJiaKnTcyMoJIJEJycjJSUlIgFAphYmIi9tiJiYkoKyv7pidLCCGEkLrli5Zfjxs3rtrjOTk5aN68udixpk2b4uXLl589n52djfz8fJSUlIidV1BQgLq6Ol6+fAlFRUU0atQIysrK7PlmzZqhtLQUb9++rfK4hBBCCPn+1KiOTHFxMRQVFcWOKSkpobS0lD2vpKRU5bxQKMT79+/Z29WdLysrq/Yc8GES8OfIywugrl7/658Qx+Tl5WpFO/5LTdsojedJMSmmLMX7VvTepJjfY8yvVaNERllZGQUF4uXUhEIh6tWrx57/OOkQCoVQV1dne1qqO1+vXj0IBIJqzwEfhqg+RyRikJdX9Nn7SIK6en1O2vE1lXq/RU3byNXzpJgUU9bi0XuTYlJMyfjce61GdWQ0NTWRk5Mjduz169fQ0ND4z/MVyczr16/Zc2VlZcjLy0Pz5s2hqamJ/Px8sWQmJycHSkpKaNSoUU2aTQghhJA6okaJjKGhIVJSUsRqv8TFxcHIyIg9f+fOHfZccXExkpKSYGRkBDk5ORgYGCAuLo49Hx8fD3l5eXTp0gVdunSBoqIi7t69K/bYenp6UFCgnRUIIYQQUsNExtzcHK1atYKrqytSU1MRGhqKhIQEjB07FgBgZ2eHhIQEbNmyBY8fP4a7uztatWoFS0tLAMCECROwa9cuREdHIzExEZ6enrCzs4OqqipUVFQwcuRIeHp64t69e7hw4QJ27dqFKVOm1PxZE0IIIaROqFHXhry8PEJCQuDu7o7Ro0ejTZs2CA4OhpaWFgBAS0sLQUFB8PX1xdatW2FoaIiQkBDIyX3In4YOHYoXL15g5cqVEAqFGDhwIFxdXdnHd3Nzw8qVK/HLL79AVVUVc+fOxZAhQ2rSZEIIIYTUIV+dyDx8+FDsdtu2bT9bpM7a2hrW1tafPO/o6AhHR8dqz6moqGDNmjVYs2bN1zaTEEIIId8B2jSSEEIIITKLEhlCCCGEyCxKZAghhBAisyiRIYQQQojMokSGEEIIITKLEhlCCCGEyCxKZAghhBAisyiRIYQQQojMokSGEEIIITKLEhlCCCGEyCxKZAghhBAisyiRIYQQQojMokSGEEIIITKLEhlCCCGEyCxKZAghhBAisyiRIYQQQojMokSGEEIIITKLEhlCCCGEyCxKZAghhBAisyiRIYQQQojMokSGEEIIITKLEhlCCCGEyCxKZAghhBAisyiRIYQQQojMokSGEEIIITKLEhlCCCGEyCxKZAghhBAisyiRIYQQQojMokSGEEIIITKLEhlCCCGEyCxKZAghhBAisyiRIYQQQojMokSGEEIIITKLEhlCCCGEyCxKZAghhBAisyiRIYQQQojM4iSR+ffff/Hbb7/B3NwcVlZWWLduHUQiEQDgxYsXcHBwgJGREWxsbHD58mWx342NjcXw4cNhaGiIyZMnIz09Xex8WFgY+vTpA2NjY7i5uaGoqIiLJhNCCCGkDuAkkfH09ER2djbCw8Ph7++Pv/76C7t37wbDMHBycoK6ujoOHz6MUaNGwdnZGRkZGQCArKwszJkzByNGjMCRI0fQrFkzODk5oby8HAAQHR2NwMBArFixAvv27UNiYiL8/Py4aDIhhBBC6gBOEpnLly/jl19+wQ8//IAePXpg2LBhiI2NRWxsLJ4+fQovLy907NgRjo6OMDY2xuHDhwEABw8ehK6uLmbOnImOHTvCx8cHWVlZiI2NBQDs3bsXkyZNQv/+/WFgYICVK1fi6NGjKCws5KLZhBBCCJFxnCQy6urqOH78OIqLi5GdnY2rV69CT08PCQkJ6Nq1K9TU1Nj7mpiYID4+HgCQkJAAMzMz9pyKigr09PRw9+5diEQiJCYmip03MjKCSCRCcnIyF80mhBBCiIzjJJFZsWIFbt68ie7du6NPnz5o1qwZ5s+fj5ycHDRv3lzsvk2bNsXLly8B4JPns7OzkZ+fj5KSErHzCgoKUFdXZ3+fEEIIId83BS4e5Pnz5+jatSvmzp2LgoICeHt7Y82aNSguLoaioqLYfZWUlFBaWgoAKC4uhpKSUpXzQqEQ79+/Z29Xd/5z5OUFUFevX9OnVWPy8nK1oh3/paZtlMbzpJgUU5bifSt6b1LM7zHm16pxIvP8+XP4+Pjg4sWLaNGiBQBAWVkZDg4OGDt2LAoKCsTuLxQKUa9ePfZ+HyclQqEQ6urqUFZWZm9/6vc/RSRikJcn/dVN6ur1OWmHhkYDDlrzaTVtI1fPk2JSTFmLR+9NikkxJeNz77UaDy3dv38fqqqqbBIDAPr6+hCJRNDQ0EBOTo7Y/V+/fg0NDQ0AgKam5ifPVyQzr1+/Zs+VlZUhLy+vynAUIYQQQr5PNU5kmjdvjvz8fGRlZbHH0tLSAADt27dHSkqKWO2XuLg4GBkZAQAMDQ1x584d9lxxcTGSkpJgZGQEOTk5GBgYIC4ujj0fHx8PeXl5dOnSpabNJoQQQkgdUONExsjICF26dIGbmxtSUlIQHx8PDw8P2NraYvDgwWjVqhVcXV2RmpqK0NBQJCQkYOzYsQAAOzs7JCQkYMuWLXj8+DHc3d3RqlUrWFpaAgAmTJiAXbt2ITo6GomJifD09ISdnR1UVVVr2mxCCCGE1AE1TmQUFBSwbds2NGrUCL/88gvmzZsHc3NzeHl5QV5eHiEhIXj79i1Gjx6NY8eOITg4GFpaWgAALS0tBAUF4dixY7Czs8Pr168REhICObkPzRo6dCjmzJmDlStXYtq0adDX14erq2tNm0wIIYSQOoKTVUuamprYuHFjtefatm2L8PDwT/6utbU1rK2tP3ne0dERjo6ONW4jIYQQQuoe2jSSEEIIITKLEhlCCCGEyCxKZAghhBAisyiRIYQQQojMokSGEEIIITKLEhlCCCGEyCxKZAghhBAisyiRIYQQQojMokSGEEIIITKLEhlCCCGEyCxKZAghhBAisyiRIYQQQojMokSGEEIIITKLEhlCCCGEyCxKZAghhBAisxSk3QBZo9ZQBSrKX/5n09Bo8MX3LS4pQ0F+8bc0ixBCCPkuUSLzlVSUFdDO9RQvj/3MbygKeHlkQgghpG6ioSVCCCGEyCxKZAghhBAisyiRIYQQQojMokSGEEIIITKLEhlCCCGEyCxKZAghhBAisyiRIYQQQojMokSGEEIIITKLEhlCCCGEyCxKZAghhBAisyiRIYQQQojMokSGEEIIITKLEhlCCCGEyCxKZAghhBAisyiRIYQQQojMokSGEEIIITKLEhlCCCGEyCwFaTeAEEII+ZhaQxWoKH/5R5SGRoMvvm9xSRkK8ou/pVmkFqJEhhBCSK2joqyAdq6neHnsZ35DUcDLIxNpqPHQUmlpKXx9fWFhYQELCwusWLECQqEQAPDixQs4ODjAyMgINjY2uHz5stjvxsbGYvjw4TA0NMTkyZORnp4udj4sLAx9+vSBsbEx3NzcUFRUVNPmEkIIIaQOqXEis3btWpw7dw4hISHYsmULrl69is2bN4NhGDg5OUFdXR2HDx/GqFGj4OzsjIyMDABAVlYW5syZgxEjRuDIkSNo1qwZnJycUF5eDgCIjo5GYGAgVqxYgX379iExMRF+fn41bS4hhBBC6pAaJTL5+fk4cOAAvL29YWJigu7du2PevHl48OABYmNj8fTpU3h5eaFjx45wdHSEsbExDh8+DAA4ePAgdHV1MXPmTHTs2BE+Pj7IyspCbGwsAGDv3r2YNGkS+vfvDwMDA6xcuRJHjx5FYWFhzZ81IYQQQuqEGiUycXFxqFevHnr27MkeGz16NHbs2IGEhAR07doVampq7DkTExPEx8cDABISEmBmZsaeU1FRgZ6eHu7evQuRSITExESx80ZGRhCJREhOTq5JkwkhhBBSh9QokXn+/Dlat26NkydPYujQoejbty/WrFkDoVCInJwcNG/eXOz+TZs2xcuXLwHgk+ezs7ORn5+PkpISsfMKCgpQV1dnf58QQgghpEarlgoLC5GZmYnw8HB4enqisLAQnp6eKCsrQ3FxMRQVFcXur6SkhNLSUgBAcXExlJSUqpwXCoV4//49e7u68/9FXl4AdfX6NXlqUiONdtc0pry8nMTbTTEppizF+1b03uQP/W1rb8yvVaNERkFBAQUFBfD390ebNm0AAEuWLMGSJUswatQoFBSIL3ATCoWoV68eAEBZWblKUiIUCqGurg5lZWX29qd+/3NEIgZ5efyscPqaWgXforp2SyPm11BXr8/b35tiUszaHI/em/zFpL/t9xuzOp97PdRoaKl58+ZQUFBgkxgA0NHRQUlJCTQ0NJCTkyN2/9evX0NDQwMAoKmp+cnzFcnM69ev2XNlZWXIy8urMhxFCCGEkO9XjRIZIyMjlJWV4eHDh+yxtLQ0qKqqwsjICCkpKWK1X+Li4mBkZAQAMDQ0xJ07d9hzxcXFSEpKgpGREeTk5GBgYIC4uDj2fHx8POTl5dGlS5eaNJkQQgghdUiNEpl27dqhf//+cHNzw/3793H79m2sW7cOP//8MywtLdGqVSu4uroiNTUVoaGhSEhIwNixYwEAdnZ2SEhIwJYtW/D48WO4u7ujVatWsLS0BABMmDABu3btQnR0NBITE+Hp6Qk7OzuoqqrW/FkTQgghpE6o8RYFa9euxerVq/HLL79AQUEBI0eOxOLFiyEvL4+QkBC4u7tj9OjRaNOmDYKDg6GlpQUA0NLSQlBQEHx9fbF161YYGhoiJCQEcnIfcquhQ4fixYsXWLlyJYRCIQYOHAhXV9eaNpcQQgghdUiNExk1NTX4+vrC19e3yrm2bdsiPDz8k79rbW0Na2vrT553dHSEo6NjTZtICCGEkDqqxlsUEEIIIYRICyUyhBBCCJFZlMgQQgghRGZRIkMIIYQQmUWJDCGEEEJkFiUyhBBCCJFZlMgQQgghRGZRIkMIIYQQmUWJDCGEEEJkFiUyhBBCCJFZlMgQQgghRGZRIkMIIYQQmUWJDCGEEEJkFiUyhBBCCJFZlMgQQgghRGZRIkMIIYQQmUWJDCGEEEJkFiUyhBBCCJFZlMgQQgghRGZRIkMIIYQQmUWJDCGEEEJkloK0G0AI4ZdaQxWoKH/dW11Do8EX3a+4pAwF+cXf0ixCCOEEJTKE1HEqygpo53qKl8d+5jcUBbw8MiGEfBkaWiKEEEKIzKJEhhBCCCEyixIZQgghhMgsSmQIIYQQIrMokSGEEEKIzKJEhhBCCCEyixIZQgghhMgsSmQIIYQQIrMokSGEEEKIzKJEhhBCCCEyixIZQgghhMgsSmQIIYQQIrMokSGEEEKIzOI0kXF3d8fkyZPZ2y9evICDgwOMjIxgY2ODy5cvi90/NjYWw4cPh6GhISZPnoz09HSx82FhYejTpw+MjY3h5uaGoqIiLptLCCGEEBnHWSITExODw4cPs7cZhoGTkxPU1dVx+PBhjBo1Cs7OzsjIyAAAZGVlYc6cORgxYgSOHDmCZs2awcnJCeXl5QCA6OhoBAYGYsWKFdi3bx8SExPh5+fHVXMJIYQQUgdwksgUFRXBw8MD3bt3Z4/Fxsbi6dOn8PLyQseOHeHo6AhjY2M22Tl48CB0dXUxc+ZMdOzYET4+PsjKykJsbCwAYO/evZg0aRL69+8PAwMDrFy5EkePHkVhYSEXTSaEEEJIHcBJIhMQEABzc3OYm5uzxxISEtC1a1eoqamxx0xMTBAfH8+eNzMzY8+pqKhAT08Pd+/ehUgkQmJioth5IyMjiEQiJCcnc9FkQgghhNQBNU5k7t69i7Nnz8LFxUXseE5ODpo3by52rGnTpnj58uVnz2dnZyM/Px8lJSVi5xUUFKCurs7+PiGEEEKIQk1+WSgUwt3dHUuXLkWjRo3EzhUXF0NRUVHsmJKSEkpLS9nzSkpKVc4LhUK8f/+evV3d+f8iLy+Aunr9r34+tYE02l3TmPLychJvN8WsPbhon6Sfpyz8XQF6b/KJ/ra1N+bXqlEis3nzZrRt2xY2NjZVzikrK6OgoEDsmFAoRL169djzHyclQqEQ6urqUFZWZm9/6vc/RyRikJfHzwonDY0GvDxuheraLY2YX0NdvT5vf2+KWfOYtf31A0j+b8tVvNr+t5XV1yxAf9vvOWZ1Pvd6qFEic+LECeTk5MDY2BgAUFpaCpFIBGNjY8yaNQspKSli93/9+jU0NDQAAJqamsjJyalyvlOnTmwy8/r1a/zwww8AgLKyMuTl5VUZjiKEEELI96tGiUxYWBjKysrY23v27MH9+/exbt06/PPPP9i2bRuKiopQv/6Hbqm4uDgYGRkBAAwNDXH79m32d4uLi5GUlIQ5c+ZATk4OBgYGiIuLQ8+ePQEA8fHxkJeXR5cuXWrSZEIIIYTUITVKZFq3bi12u2HDhqhXrx7atm0LLS0ttGrVCq6urpg/fz7+97//ISEhAatXrwYA2NnZYefOndiyZQsGDhyIkJAQtGrVCpaWlgCACRMmYNmyZejcuTNatmwJT09P2NnZQVVVtSZNJoQQQkgdwtsWBfLy8ggJCcHbt28xevRoHDt2DMHBwdDS0gIAaGlpISgoCMeOHYOdnR1ev36NkJAQyMl9aNLQoUMxZ84crFy5EtOmTYO+vj5cXV35ai4hhBBCZFCNemQ+tmjRIrHbbdu2RXh4+Cfvb21tDWtr60+ed3R0hKOjI2ftI4QQQkjdQptGEkIIIURmUSJDCCGEEJlFiQwhhBBCZBYlMoQQQgiRWZTIEEIIIURmUSJDCCGEEJlFiQwhhBBCZBYlMoQQQgiRWZTIEEIIIURmUSJDCCGEEJnF6RYFhBAiLWoNVaCi/OWXNA2NBl983+KSMhTkF39LswghPKNEhhBSJ6goK6Cd6yleHvuZ31AU8PLIhJCaoqElQgghhMgsSmQIIYQQIrMokSGEEEKIzKJEhhBCCCEyixIZQgghhMgsSmQIIYQQIrMokSGEEEKIzKJEhhBCCCEyixIZQgghhMgsSmQIIYQQIrMokSGEEEKIzKJEhhBCCCEyixIZQgghhMgsSmQIIYQQIrMokSGEEEKIzKJEhhBCCCEyS0HaDSCEEPLl1BqqQEX5yy/dGhoNvvi+xSVlKMgv/pZmESI1lMgQQogMUVFWQDvXU7w89jO/oSjg5ZEJ4Q8NLRFCCCFEZlEiQwghhBCZRYkMIYQQQmQWJTKEEEIIkVk02ZdUS9IrI742HhcxCSGEyD5KZEi1JL0ygs94n4pJCCFE9tU4kXn+/Dl8fHwQFxcHFRUVDBkyBIsWLYKysjJevHgBDw8P3LlzBy1btoSrqyusra3Z342NjcXq1avx/PlzdOvWDatWrULbtm3Z82FhYdi+fTvevXuHn376CR4eHqhfv35Nm0wIIYR8l/js/ZZWz3eNEhmhUIjZs2ejY8eOiIyMxJs3b7B06VIAgIuLC5ycnNChQwccPnwYFy9ehLOzM06ePAltbW1kZWVhzpw5cHJyQt++fbF582Y4OTnhxIkTkJOTQ3R0NAIDA7F27Vo0b94cbm5u8PPzg5eXFydPnBBCCPne1MU6RDWa7Hvv3j08f/4cvr6+6NChA8zNzbFgwQKcOHECsbGxePr0Kby8vNCxY0c4OjrC2NgYhw8fBgAcPHgQurq6mDlzJjp27AgfHx9kZWUhNjYWALB3715MmjQJ/fv3h4GBAVauXImjR4+isLCw5s+aEEIIIXVCjRKZ9u3bIzQ0FKqqquwxgUAAoVCIhIQEdO3aFWpqauw5ExMTxMfHAwASEhJgZmbGnlNRUYGenh7u3r0LkUiExMREsfNGRkYQiURITk6uSZMJIYQQUofUKJFp0qQJevbsyd4uLy9HeHg4TExMkJOTg+bNm4vdv2nTpnj58iUAfPJ8dnY28vPzUVJSInZeQUEB6urq7O8TQgghhHC6asnX1xfJyck4fPgwdu/eDUVFRbHzSkpKKC0tBQAUFxdDSUmpynmhUIj379+zt6s7/1/k5QVQV5fNScHSaDfF/DLy8nISb7c0Yn4tLtr3vTzP7yGmLPxfArL5PGXhbyuN9nGSyDAMg9WrV+PAgQPYuHEjOnXqBGVlZRQUiE/7EQqFqFevHgBAWVm5SlIiFAqhrq4OZWVl9vanfv9zRCIGeXlFNXlKn/Q1tUu+RXXt/h5i8h2vuphfS129Pm+vKz5jSuP187Vk9Xl+LzG/Blfvk+/leUo6Zm3/u37K59pd48q+5eXlWLp0KSIjIxEQEIABAwYAADQ1NZGTkyN239evX0NDQ+M/z1ckM69fv2bPlZWVIS8vr8pwFCGEEEK+XzVOZPz8/HDixAkEBQVh0KBB7HFDQ0OkpKSgqOj/srO4uDgYGRmx5+/cucOeKy4uRlJSEoyMjCAnJwcDAwPExcWx5+Pj4yEvL48uXbrUtMmEEEIIqSNqlMjEx8dj7969cHZ2hr6+PnJyctgfc3NztGrVCq6urkhNTUVoaCgSEhIwduxYAICdnR0SEhKwZcsWPH78GO7u7mjVqhUsLS0BABMmTMCuXbsQHR2NxMREeHp6ws7OTmyFFCGEEEK+bzWaIxMVFQUAWL9+PdavXy927sGDBwgJCYG7uztGjx6NNm3aIDg4GFpaWgAALS0tBAUFwdfXF1u3boWhoSFCQkIgJ/chtxo6dChevHiBlStXQigUYuDAgXB1da1JcwkhhBBSx9QokXFxcYGLi8snz7dt2xbh4eGfPG9tbS22ZcHHHB0d4ejoWJMmEkIIIf+JNq6VXbRpJCGEkO8ebVwru2o82ZcQQgghRFookSGEEEKIzKJEhhBCCCEyixIZQgghhMgsSmQIIYQQIrMokSGEEEKIzKJEhhBCCCEyixIZQgghhMgsSmQIIYQQIrMokSGEEEKIzKJEhhBCCCEyixIZQgghhMgsSmQIIYQQIrMokSGEEEKIzFKQdgMI+Z6oNVSBivLXve00NBp80f2KS8pQkF/8Lc0ihBCZRYkMIRKkoqyAdq6neHnsZ35DUcDLIxNCSO1FQ0uEEEIIkVmUyBBCCCFEZtHQEiGEECIFNGeOG5TIEEIIIVJAc+a4QUNLhBBCCJFZlMgQQgghRGbR0BIhhJDP+tq5HF86jwP4vuZyEH5QIkMIIeSzaC4Hqc1oaIkQQgghMosSGUIIIYTILEpkCCGEECKzKJEhhBBCiMyiRIYQQgghMotWLRFCOEel1wkhkkKJDCGEc7RclxAiKTS0RAghhBCZRYkMIYQQQmQWDS2R7xbN4yCEENlX6xMZoVAIb29vnD17FkpKSpg6dSpmzpwp7WaROoDmcRBCiOyr9YnM2rVrcffuXezevRsvX77EkiVL0KpVKwwdOlTaTSOEEEKIlNXqOTJFRUU4ePAgli5dCn19fQwYMAAzZsxAeHi4tJtGCCGEkFqgVicyKSkpEAqFMDExYY+ZmJggMTERZWVlUmwZIYQQQmqDWp3I5OTkoFGjRlBWVmaPNWvWDKWlpXj79q0UW0YIIYSQ2kDAMAwj7UZ8yl9//YX169fj6tWr7LGMjAwMGDAAFy5cgJaWlhRbRwghhBBpq9U9MsrKyhAKhWLHKm6rqKhIo0mEEEIIqUVqdSKjqamJ/Px8sWQmJycHSkpKaNSokRRbRgghhJDaoFYnMl26dIGioiLu3r3LHouLi4Oenh4UFGr9ynFCCCGE8KxWJzIqKioYOXIkPD09ce/ePVy4cAG7du3ClClTpN00QgghhNQCtXqyLwAUFxdj5cqViI6OhqqqKhwcHODg4CDtZhFCCCGkFqj1iQwhhBBCyKfU6qElQgghhJDPoUSGEEIIITKLEhlCCCGEyCxaw8yhW7duVXtcIBBAUVERGhoaaNWqFedx8/Pz8ejRI5SVleHjKU+WlpacxyOEC2lpabh//361r9sxY8ZIqVVEVkj69RMcHIzp06dXKcZaUFCAzZs3w8XFhfOY9B75MjTZl0ODBg1CZmYmysvL0ahRIzAMg/z8fAgEAsjLy6OsrAyGhoYICgpC8+bNOYl59OhReHp64v3791XOCQQCJCcncxKnsry8POzcuZPdvPPjl1BERATnMSdPngyBQFDleOUk0cbGBn369OEspjSe519//fXJc0pKStDQ0IChoSGUlJQ4jSvpC2ZoaCgCAgLQsGFDqKqqip0TCAS4cOEC5zEBgGEYZGdno7S0tMo5bW1tXmJWjv3x31ZOjttO8du3b8PY2Bjy8vJix4uKirBr1y7MmzePkzj9+vWr9v1YHT7+LyX1+nn8+DFycnIAAA4ODti4cSMaNGhQ5T7r169HfHw8JzErSOM9Io1rHhcokeHQli1bcOnSJfj5+UFHRwfAh72hli5dih9//BGjR4/GihUrAACbNm3iJObgwYNhZWWFhQsXQk1NjZPH/C9z5szBvXv3MHz48GpjcnWxrGzTpk0IDQ3F4MGDYWRkBIZh8ODBA5w6dQq2trZQVlbG8ePH4ebmBjs7O05iSuN5TpkyBbdv34aysjJ0dHTAMAzS09NRXFwMLS0t5OXloUGDBti+fTs6dOjASUxpXDD79esHe3t7zJo1i/PH/pTLly/Dw8OD/WCqwDAMb0n//fv34e3tjfv376O8vLzKea5j6urqwtjYGIGBgdDU1GSPv379GlZWVpzFO3ToEPvvzMxMhIWFwd7eHgYGBlBQUMCDBw8QGRmJyZMn8/I+kdTr58aNG/jll18+e5/69etj6tSpcHZ25jS2NN4j0rjmcYIhnLGwsGCSk5OrHE9OTmYsLCwYhmGYx48fM6amppzFNDIyYp4+fcrZ430JExMT5tatWxKNOW7cOCY8PLzK8YMHDzITJkxgGIZhoqKimMGDB3MWUxrP09vbm5k9ezbz77//ssfevXvHODs7M35+fkxZWRnj5eXFODg4cBazb9++zNatWzl7vC9hYmIi8dftsGHDGGdnZyYlJYXJzMys8sOHMWPGMBMnTmQuXLjA3Lhxo8oP1zp37szMmTOH6dGjB3P16lX2eE5ODqOrq8t5PIZhGDs7O+b06dNVjp87d44ZNmwYLzGl8frp27cv8+bNG4nFk8ZzlMY1jws02Zdjb9++rfaYSCRib39pl+yX6NevHy5evMjZ432JJk2aQFlZWaIxk5KS0LNnzyrHTU1NkZiYCADQ19dHVlYWZzGl8Tz/+usv/Pbbb2jYsCF7TE1NDc7Ozjh06BDk5eUxZcoU3Llzh7OY+fn5GDx4MGeP9yVsbW0RGRlZpeuaTxkZGViwYAE6d+6M1q1bV/nhQ2pqKpYvX45+/frB3Ny8yg/XBAIBvL294ezsjLlz52Ljxo1sjxNf0tLS8MMPP1Q5rqWlhczMTF5iSuP1c/HiRTRp0kRi8aTxHKVxzeMCTfbl0JgxY+Di4gJnZ2cYGBiAYRjcv38fwcHBGDVqFHJzc+Hv78/pBaxJkyYICAjAqVOn0KZNGygqKoqdX7t2LWexKvz222/w9PTE/PnzoaWlVWW+Bh9zDXR1dREWFoZly5ax8woYhkFERAQ6duwIAEhMTESLFi04iymN51m/fn2kpqZWGTZKS0tj4xcVFaFevXqcxay4YLq4uPD6gVdZbm4uoqOjceLECbRu3brK65aPsXhTU1Pcu3cP7du35/yxP0VXVxeZmZnVftDzoeJDb/z48dDT08PChQtx9+5ddkibDyYmJvDx8cGqVavQsmVLAMCzZ8/g5eUFKysrXmJK6vVjbW39xe+JS5cucRKzgjTeI9K45nGB5shwiGEYbN26FQcOHMCrV68AAM2bN8ekSZMwffp0/P333/jjjz+wfPlyzib7urm5ffa8r68vJ3Eq09XVFbtd8UZneJ5rMHPmTKioqKBLly5gGAYpKSkoLi7G1q1bUVZWhqlTp2LFihWcTU6VxvPcs2cPNm3ahClTpkBfXx/Ah+ceERGB6dOnY+TIkXB2dkb79u3h5+fHScxff/0V0dHRaNSokcQumMHBwZ89z8dYfEhICLZv3w4rK6tqk/4FCxZwHjMiIgKbN2/GyJEjoa2tXSUm1xOpdXV1cf36dTRt2hTAhw/D3377DQ8fPsSbN294ec2+evUKzs7OSEhIgJqaGhiGQWFhISwsLLBx40Y0atSI85iSev0cPXr0i+87atQoTmJWkMZ7RBrXPC5QIsOhw4cPo1+/fmjSpAlyc3OhoKBQZYY714KDgzF69GhelnV/yosXLz57no9u+vLychQVFeHUqVN49OgR5OXl0alTJwwdOhT169dHZmYmCgoKqrwRa0IazxMAjh8/jv379+Phw4dQUFBAx44dMXnyZAwZMgS3bt3C+fPnsWDBAtSvX5+TeNK4YLq7u8PR0RFt27bl/LE/ZfLkyZ88JxAIsG/fPs5j9uvX77MxuZ5I7ebmBnd3d7GJmgzDYOPGjTh+/Divw9CpqalIS0sDAHTq1Imzyej/paysDPLy8hLrTayOUCjkfCWhNEjrmldTlMhwyNTUFIcPH0a7du0kGvOvv/6ClpYWr3HKy8vZIZ3qVl9UxvWSUgAYNmwY1q1bx2mi8qXi4uLw7NkzDB48GP/88w/atWvH20VLGolpZZL6UDA3N8eff/7J++uWSAYjhWXtERER2LNnD7KysnDmzBmEhoaicePGWLhwIS/XoFevXmHr1q1ITU1lr4EMw0AoFOLp06eIi4urcYwlS5Zg+fLlUFNTw5IlSz57Xz6mDVSQ5DWPCzRHhkM9e/bE0aNHMWvWLM6+Lf8XW1tbBAcHY+bMmWjVqlWViVpcvaH19PRw7do1NG3aFF27dv3sBx0f3Y///vtvldoYfHvz5g1mzZqFx48fQygUwtzcHAEBAXj06BF27drFS2/Cnj17YGtry/nj/hdJfyhUDANOmTIFrVu3rvK65evDLyUlBeHh4UhPT8e6detw7tw5tGnThtP6Qx97/fo1Dh06hPT0dPz++++4ceMGOnTogM6dO3Py+F86j0MgEOB///sfJzErk8ay9t27d2Pfvn1YsGABVq5cCQDo1asXvL29AXwYLuXa0qVLkZmZiUGDBmHXrl2YNm0anj9/jnPnzmHp0qWcxKh8jZP09Q6QzjWPC9QjwyF7e3skJCRAIBBAXV29ysWZ68lgwIeLWHZ29icvZFxdRG7evInu3btDQUEBN27c+OyFk4/VGP7+/jh+/DiGDx9e7QcfH0XbFi5cCIZhsGbNGlhaWuL48eNo3LgxlixZgtLSUmzfvp3zmN7e3igsLOQ9Ma3s4w+FEydO4MGDB/D29oadnR0vHwrSGIu/evUq5s+fDxsbG5w6dQqnTp3C0aNHERoaCl9fXwwfPpzzmImJiZg6dSr09PRw584dnDlzBjt27MDRo0cREhKC3r171ziGNOdxAMDw4cPRvn17ODk5VVt7hI/hiMGDB2PZsmWwsrKCsbExjh8/Dm1tbVy/fh1ubm64cuUK5zGNjY2xa9cuGBsbw87ODkuXLoWJiQlCQ0Nx48YN7Ny5k/OYkiaNax4XqEeGQ+PGjcO4ceMkGtPf318icSonJxYWFhKJWdmZM2egqKiIs2fPVjknEAh4SWRiYmIQEREhtkJITU0Nixcvxs8//8x5PAA4f/48srOzcezYsWrP8/EBHxkZya4w8fT0BAD89NNPaNCgAdzc3HhJZPiq3Ps5AQEBcHNzg729Pfs6cnZ2hoaGBkJCQnhJZPz8/ODo6IhZs2bB2NgYAODp6QkNDQ2sX7+ek0TmS5MToVBY41jVycjIwMaNGyW6Guzly5fVDuG3aNEC+fn5vMRkGIYtMtixY0ckJSXBxMQENjY2vCUxly5dwt69e5Geno6wsDAcOnQILVu2hL29PS/xpHHN4wIlMhyquKCUl5fjxYsXaNmyJcrLy3kdW6xIMLKzs/H06VMYGRmhoKAAzZo14zSONJchApB4rRzgQ+9HcXFxleM5OTm81VqQVGJamTQ+FCq+pUtyLP7JkyfV1iLq1asXL6v7gA/1j6p7bFtbW16+3UpiHsfHpLGs3cjICEeOHMHChQvZY+Xl5dixYwe6devGS0w9PT389ddfcHJyQpcuXXDt2jVMnjwZGRkZvMQ7duwYVq9ezdaNKi8vh4aGBvz8/FBcXIypU6dyHlMa1zwuUCLDobKyMqxfvx7h4eEQiUSIiorCunXroKCgAG9vb17mzRQWFsLNzQ3R0dGQk5NDVFQUfHx8kJubi82bN7PLMGuq8gVDGmJiYj57no/NMYcNG4ZVq1bB09MTAoEABQUFuH79Ory8vDBkyBDO4wH8DMv9F2l8KEhjLF5LSwvx8fFV5t9cvHiRtzk5TZs2RVpaGtq0aSN2PC4ujrMSDJVJYh7Hx7p37w5PT09cvHhRYsvaly1bhpkzZ+LSpUsQCoVYsWIFnj17hpKSEt56R3777TfMnj0bKioqGDlyJHbs2AEbGxtkZ2fzMq9tx44d8PT0FOvxmThxIpo2bYq1a9fykshI45rHBZojw6H169fj0qVLWL58ORwdHXH8+HFkZ2fDw8MDZmZm8PLy4jzm8uXL8fTpU/j5+WHYsGE4fvw4ysvL4eLigpYtWyIgIIDzmA4ODnB3d5fY8kqg6pyKCsrKymjRogWioqI4jykUCrFhwwZERESwqzHk5eUxduxYuLm58fIN5b96vvjo7UpNTcXMmTOhrq6O1NRUWFhYiH0o8LFSTBpj8efPn8eSJUswZswYREZGwsHBARkZGYiKioK/vz9sbGw4j/nHH38gKCgIM2fOREBAAFxdXZGVlYV9+/bht99+w8SJEzmNJ415HNJY1g4AJSUlOHHiBNLS0iASiaCjo4MRI0ZU2S+MS4WFhSguLkazZs2QnZ2N8+fPQ11dHTY2NpzPXzM0NMTJkyehra0tNg8oPT0dw4cPx7179ziNB0jnmscJ3jdB+I707duXuX37NsMwH/ZAev78OcMwDHPnzh2mR48evMTs1asX8+DBgyoxk5OTGTMzM15i9ujRg3n27Bkvj/2lysrKmCdPnjAODg7MoUOHeI1VXFzMPHr0iElOTmYKCgp4jfXnn3+K/Rw8eJBZv34907t3b+bw4cO8xX3//j1z6NAhxs/Pj1m9ejWzf/9+Xp+rubk5k5qayjCM+Ov28ePHTPfu3XmLm5yczPz+++/M6NGjGVtbW2bhwoVMfHw8b/EYhmEuXLjATJgwgbGwsGBMTU2ZsWPHMqdOneIllqGhIfPixQuGYRhmyZIlzL59+xiGYZjnz58z5ubmvMSUJpFIxDAMw2RnZzOnT5+W2HWpvLycEYlEYj9cGzNmDBMWFsYwjPh7ZP369cyYMWM4j1eZJK95XKChJQ7l5uZWO5SjoqKC9+/f8xLz/fv3VbpygQ+ZNcNTZ9u4cePg7OwMe3t7tG7dusqcBj6GeT4mLy8PHR0duLq6YsaMGbxM9gU+9FY8efKEnSiZmprKnuNjcuinJm4aGxsjNDSUs529P6asrIzRo0dDTk4Or169QlxcHF6/fs3bt1tpjcXr6uqK1d94+/YtGjduzFs84ENRvM8VxuOSpOdxVEhMTMTjx4/ZPeWY/z8vJzk5GatWreI8Xnx8PBYsWIA1a9agY8eOGDNmDAoKCiAUChEQEICBAwdyHjM5ORkeHh54+PAhysrKqj3PJRcXF8yaNQsxMTEoLS1FSEgInj59ipSUFGzdupXTWBVu3bpV5VhSUhIEAgEUFRWhoaEhtRpXn0OJDIcsLS2xfft2sTfuu3fvsGHDBvTo0YOXmP3798f69evFLs7Pnj2Dt7c3fvzxR15ibtmyBQCqHSqTdBnrV69e4d27d7w8dkBAALZt24YGDRpU++HKRyLzKe3bt8eDBw94eWxpfChIYyz+9evX8PX1xYwZM9ChQwfMnDkTN2/eRMuWLbFt2zZ06tSJkzgbN2784vtyPX9E0vM4AGDTpk0ICQlBs2bN8ObNG2hqauL169cQiUQYNGgQLzH9/PzQv39/GBgYICwsDAoKCoiJicHx48exceNGXl6zbm5uUFdXR2BgIO8V24EPk6ijoqIQEREBeXl55Ofnw9TUFBs2bOAtmXB3d0dmZibKy8vRqFEjMAyD/Px8CAQCyMvLo6ysDIaGhggKCuJljte3ojkyHMrOzsbcuXORmZmJ/Px8tGvXDllZWdDW1saWLVt4qadQUFAANzc3nD9/HgzDoH79+iguLkbv3r3h7+8PdXV1zmNKQ3VVLgsKCnDt2jUMGzYMPj4+nMc0NzfHr7/+KtEl9dVNai4sLMTu3bvx/v17HDlyhPOY48aNQ9euXbF48WKEhYXh4MGDOHPmDI4fP469e/fi5MmTnMeUxlj8/Pnz8fbtW6xduxZ///031qxZg23btuH48eN4+vQpZ3M5PjdnpDKu5o9cvXoVFhYWbM+oJOdxAEDv3r0xf/582Nvbo1+/fti7dy8aNWqERYsWoXPnzv9ZofZbdOvWDWfOnEHr1q3x888/w9DQEO7u7njx4gVsbGx4mT/SrVs3nDhxQmJF4YKDgzF9+nSoqKiIHS8oKMDmzZvh4uLCecwtW7bg0qVL8PPzg46ODoAPy+uXLl2KH3/8EaNHj2Y3IN20aRPn8b8VJTI8iImJwZMnT1BWVgYdHR307t2blwtIZRkZGUhLS2Nj8j0Rt6SkBFFRUUhPT8fkyZORkpKCDh06QENDg5d41W2OqaioCAMDA9ja2vKyZLdv374IDQ3l7Jv6l6huYm3F8/Tw8ECXLl04jymND4UK79+/R0ZGBkQiEbS1tXmdqGliYoKDBw+iQ4cOcHR0RKNGjeDv74+MjAwMHz4c8fHxvMXmk7GxMU6fPo2WLVuif//+OHLkiES/wOjr6yM6OhqtWrXC3LlzMWjQINja2uL+/ftwdnbmpXRCnz59sGHDBrRo0QIDBw7Ejh070KtXL0RFRWHt2rW81CmaMGECpk+fjv79+3P+2BUeP37MVkh2cHDAxo0bq/T+PH78GOvXr+fl9dqjRw/s2bOnynUoJSUFU6dORWxsLNLS0jBu3Lhqh6GkhYaWeKChoYH8/HwoKiqiTZs2vCYxI0aMwPDhwzF06FDehpI+lp6ejqlTp0JeXh4vX77EyJEjERkZiZiYGOzcuZPdtZlLfNX5+JwlS5bAy8sLzs7OaNmyZZX/Rz66d1NSUjh/zP+irq6OrKwsMAyDxMREdrjj/v37vCWmgOTnHykoKIBhGBQVFeHGjRtYvXo1APA6Fwjgf/5IkyZN4OHhAX19fbx48QJbt26t8i2+Ah9LoVu0aIGMjAy0atUKHTp0QFJSEmxtbaGqqorc3FzO4wGAnZ0d5s6dC0VFRXTu3BmWlpaIiIiAv78/p6UiDh8+zP7b0NAQrq6uGDduHLS1tatcD7iYp/fmzRtMmzaNve3s7FzlPvXr14eDg0ONY33K27dvqz1W8foFINUNOqtDiQyH3rx5g/nz5+POnTvs+OK7d+/Qt29f+Pj48PItafz48Th79iwCAwNhYGCAYcOGwcbGhrP6MdVZtWoV+vfvD3d3d3Tv3h0AsGHDBqxcuRI+Pj7Yv38/L3FjYmIQGRmJJ0+eQFFREe3bt4eDgwO6du3KSzyRSIT79+9jypQpYscZnre0Ly8vx9WrV5GWlgZFRUV07NiR1wnUkvpQqEwa848sLS3h7u6O+vXrQ1lZGX379sXff/8Nb29v3r5lS2L+yObNmxEUFIQ7d+5AIBAgPj6+2gUAfH34/Pzzz1i0aBF8fX0xYMAA/PLLL2jatCliY2N52+R1wYIF6Nq1K168eIERI0ZATk4OWlpaCAgIQN++fTmLExISIna7QYMGOHXqVJX7cVVd3MLCgv0y069fPxw+fBhNmjSp8eN+qTFjxsDFxQXOzs4wMDAAwzC4f/8+goODMWrUKOTm5sLf318q9a4+SxpLpeqqGTNmML/88guTmZnJHnv69Ckzfvx4Zv78+bzGzsnJYcLCwphJkyYxBgYGjIODA3PkyBHm3bt3nMcyMTFhnjx5wjCM+LLA9PR0xsjIiPN4DMMwhw4dYvT19RlXV1cmLCyM2bt3L7N48WJGX1+fOXnyJC8xe/XqxXh7ezMPHz5k0tPTq/zw4dmzZ0y/fv0YY2NjZtSoUczIkSMZIyMjxtbWlsnIyOAlJsMwTHR0NLN7927mzZs3DMMwzKVLl5iLFy/yFs/MzIw5cOAAb49fnXfv3jHe3t7MnDlzmLt37zIMwzB79uxh/Pz8mOLiYl5i9urVi4mMjGQY5kN5hufPnzP//vsv4+DgwKxZs4bzeH379mXevn3L+eP+l2PHjjE3btxgGIZhDh48yIwePZpxcHBg0tLSJN6WuqZiaferV694X2JeXl7OhISEMFZWVkznzp2Zzp07M1ZWVsy2bduYsrIy5sqVK8zcuXOZ7Oxs3trwLSiR4VC3bt3Y2hiVJScnM4aGhhJpQ2pqKrNu3TqmW7dujIGBAWNoaMgsWbKE0xeelZUVe9GqnMicO3eO6dOnD2dxPo559OjRKscPHDjA9O3bl5eYZmZm7HOTFHt7e2bx4sVitRv+/fdfZu7cuczUqVN5jf3xBfPp06e8xfrxxx+ZR48e8fb4tYWenh5b18XJyYn566+/GIZhmMTERE5ft+/evWPOnz/PXLlyhZcvL7VNZmYm4+zszAwaNIj58ccfGWtra7Efvvz777/MrVu3mJiYGObvv/9mf2JiYjiPdffuXaZPnz5MTEwMk5OTw/Tu3ZsxNjZm9PT0mOjoaM7jfezt27dMfn4+73G4QENLHOrQoQMePXqEjh07ih1//vw5byXQgQ+Tv86ePYszZ84gPT0dPXv2hJeXFwYOHIjc3Fx4enpi9uzZ+PPPPzmJN27cOCxfvhy//fYbACAtLQ0xMTEIDAzE+PHjOYnxscLCQhgYGFQ5bmJiwts4/PTp0xESEoLly5d/cs4B1yr25qk8Z6Nhw4ZYtGgRRo8ezUvMj5df29nZ8b78Whrzj4RCIQ4dOoSHDx+ipKSkSp2lyiUMuCKJ+SPx8fGYNWsW/v33XwAf5swEBATwurnr16xE4uPvumTJErx79w4TJ06UyFJo4MMu456entXWBONjqPnjJeaKioq8LzEHPlzP79+/j7KysirvEb7qddUUJTI1VHkymLm5Odzd3XH//n3o6+tDTk4Ojx49wr59+zB9+nRe4g8dOpTdLHLixImwsbERK/BVv359jB49GsuXL+csppOTExo0aIBVq1ahuLgYs2fPRtOmTTFt2jTenufkyZPh7++PNWvWoFGjRgCA4uJiBAUF8bY8+vLly0hMTMSJEyegrq4OBQXxtwsf2wUYGRkhJiaGXfpYIS4ujpcVS4B0anJIY/6Rh4cHoqOj0atXL4l9+Eli/sjatWvRs2dPuLu7Q05ODv7+/li+fDkv23ZUkJeX5+2xv0RiYiKOHDki0RWFW7duxZgxY7Bw4UKoqanxHi8pKQnr16+HqqoqLl68iP79+0NZWRk9e/aEt7c3LzFDQ0OxYcMGNGrUqMoEeK7mAfGBll/X0JdW7BQIBLwsCQwNDcWwYcM++w22uLgYAoFAbGt2rhQVFUEkEvHywVB53yGGYZCdnQ0lJSVoaWlBTk4OmZmZEAqF6NKlCy/1VY4ePfrZ85+qwvu1KhdQy87OxrFjx9jEoiIZPn36NKZMmYLff/+dk5iVSWP5de/evfHTTz/h559/rvZ1+fEmi1wwNjZGSEiIRCpPV3b8+HG0aNEC5ubmOHToECIjI6Gurg53d3dOdow2NjbGX3/9xdY3ycvLQ48ePXDjxg026edTcHAwRo8eLdGKr7a2tnB3d5fopFNjY2McPXq02p3i+SCNJeb9+vWDvb09Zs2axflj84l6ZGqIjxoJX8PR0RGlpaV48eIFysvLAfzf8s6kpCSMGDGC12GRnJwcHDx4EOXl5fjpp59gaGjI2WNLe8ftikSlvLwcL168QMuWLVFeXs55zZrbt2+L3e7evTtyc3Nx5coV9piRkRESExM5jVtBGsuvhUIhfvnlF16HXD/WsGFDXpeTV+jXrx8OHDgATU3NKkXNxo4di7Fjx3Iar7i4WKyHQF1dHfXq1cO7d+8kksjs2bMHI0eO5D1O5WKRgwYNwpIlSzB79uxql0Lzkaz269cPFy9e5HXpc2XSWE2Yn5+PwYMH8/LYfKIeGY59XBujgkAgwLBhwziPd+7cOSxbtgz5+flVzmlqanI2/FFUVAQ/Pz+cPn0awIdvRBMnToS9vT2aNm0KhmGQkZGBoKAgXgtGSVJZWRnWr1+P8PBwiEQiREVFYd26dVBQUIC3tzfq168v7SZyYuPGjdi/fz8UFRXRrFkz/Pnnnzhw4AB7wZw6dSrnMbdt24Znz57xPv+oIrkHPuxEffbsWaxYsQLa2tpVhke4qvfUvXt3uLm5wcLCAoMHD8Yff/zxyf2cuEjkdHV1cf36dbGSC5V3S+abt7c3CgsLMXPmTLRq1arKcnqu/q5fOhTH19Dk6tWrERkZiR9++AFt2rSpssSdj7lA586dY5eYN2nSBJcvX0Z5eTmnS8wr8/b2hqKiIlxcXGpdrZjPoUSGQ/9VG+PatWucx/zpp59gbm6OqVOnYvz48QgNDUVeXh68vb0xZ84czjYZrJj7M2XKFDRp0gRhYWHsxMWKqruBgYGIjY1FZGQkJzEry8vLw86dO5GYmFjtJLSIiAjOY65fvx6XLl3C8uXL4ejoiOPHjyM7OxseHh4wMzOrdq8pLly6dOmTyTBfXb6SvmBOmDABiYmJYBiG1/lHurq6Yhfkijk41eHqw2/r1q0IDAwUGxb9+N9czgXq0qULrly5wiYyDMPAzMwMR48erZLI8FGc09raGtnZ2bz/XaWtuurilUmjaCfXfv31V0RHR6NRo0Zo3bp1lWSNj+ssFyiR4ZA09ubR19fH6dOn0aZNG0yfPh3jx4/HgAEDcO3aNfj5+XG2T06PHj0QGhqKbt26AfhQ6bFnz544fPgwW8k3MzMTw4YN46V09pw5c3Dv3j0MHz682ol28+bN4zxmv3794O/vDxMTE7FvuHfv3oWTk1O1+yLVlJubG06cOIEOHTpUmTsiEAh4SRIrZGdnsxPHCwoK0KxZM95iSWr+0c2bN7/4vlzOt8jPz8e7d+/Qv39/HDp06JNFzbjYf+3jZA34dMLGR1LxX39jPuaxlJeXY/v27dDQ0GBX802dOhVWVlZwcHCQaG+CSCTCtWvXYG1tXePHqjwv8L/wsdggODj4s+f5uM5ygebIcEhVVRUmJiYSjdmwYUMUFxcDAHR0dJCcnIwBAwZAR0cHmZmZnMXJy8tDixYt2NtNmjSBioqK2Bh8vXr1UFJSwlnMym7duoWtW7fC1NSUl8evTm5ubrUVklVUVKpdgsmFqKgoBAYGYsCAAbw8fnUKCwvh5uaG6OhoyMnJISoqCj4+PsjNzcXmzZt5qRLNVaLyXz7+EL1z5w7Ky8vZ11FQUBD69OnD6dwu4MP7smHDhvD19YWOjk6V5LuoqAhHjhz54g0mP4erzS6/1ecSlZcvX/IS08/PD+fPn4enpyd7bOjQodiyZQvy8/OxaNEiXuJW9ujRIxw9ehQnTpzAmzdvOEkSpT0vsLYmKv+FEhkOSaM2Rt++feHp6QlPT09YWFhgzZo1sLa2RlRUFDQ1NTmNJc0ll02aNOFlR+TPsbS0xPbt28X2w3n37h02bNiAHj168BJTU1OT8/+3/7JmzRrk5ubiwoUL7DwuV1dXuLi4YNWqVQgICOA85pMnTxAYGIinT59WGUIDwMvS4SNHjsDT0xMuLi5sIvPPP/9gypQp8PX1xZAhQziJ8+bNGxQVFQEAli5dig4dOlSZI5OcnAx/f39OEplPJRIvX75E8+bNed+wNi0tDWvXrkVqamqVBQd5eXm89AKdOnUKmzdvhpGREXts7Nix0NHRwcKFC3lLZHJzc3Hy5EkcPXoUycnJUFBQwODBgzmrn1Vdgl9QUID09HSIRCK0bduW8wncS5YswfLly6Gmpvaf9YH4mAfEBUpkOCSN2hhLly6Fr68vHjx4AFtbW0RFRcHe3h7169eHv78/p7Hi4uLEllkzDIO7d++yPT/VTTjmym+//QZPT0/Mnz8fWlpaVVYO8TGpccWKFZg7dy4sLS1RUlKCWbNmISsrC9ra2tiyZQvn8QCwSemkSZOqTYbNzMw4j3nx4kWEhoaKDXO0bdsWK1eurPJa5srixYshJycHOzs7XsoCVGfr1q3w9fXF0KFD2WO+vr7o1asXNm3axFkic/v2bSxYsICdC2Nvby92vmI0n+9eqSFDhuDYsWO8T/j18PBAeXk5Zs2aBR8fHyxZsgQvXrzA/v37eZs3UlJSUu0XGzU1NRQWFnIaq6ysDJcuXcLRo0dx5coVlJWVwdDQEAKBABEREexwO9eEQiHWrFmDP/74AyKRCAzDQEFBAUOHDoW3tzdnqycrf0GVdn2gb0WJDIf8/PxgZ2f3ydoYfFBVVRXrMVi3bh1WrlyJevXqVZlAWVPV7cT6cQbP19h0ReyKya4fT57kI0lUVlbG4cOHERMTgydPnqCsrAw6Ojro3bs3b99yHzx4gOTkZLi6ulY5x9fzfP/+fbWbDAqFwiqTqrny9OlTHD58uEoVbD7l5ORAT0+vynF9fX1kZWVxFmfw4MG4ePEiysvLMWDAABw8eFBsjoxAIED9+vV52US2MklNf7x//z7++OMPdOnSBX/99Rfat2+PiRMnQkdHBwcPHuRlaba1tTW8vb2xZs0aNlHLyMiAr68vrKysOIuzatUqnDp1CoWFhTAzM4ObmxsGDhwIDQ0N6Onp8bpycc2aNbhy5Qq2bNkCY2NjlJeX4+7du1i9ejUCAgLg4uLCSZzKyWbr1q0lXhOIC5TIcEgatTEqS09P562mS8WOrNLCR/Gn/2Jra8sWUJNUEbUtW7Zg0aJFGD9+vMSS4f79+2P9+vVi3cbPnj2Dt7c3fvzxR15iWllZ4e7duxJNZAwMDLB3714sX75cLOGOiIjgfJfmig+Cj983QqEQKSkpVSo3yzIFBQW2p7Z9+/ZITk6GpaUlevbsiTVr1vAS08PDA3PnzsXAgQPZ2AUFBbC0tOS0inl4eDjatm2L33//HT/++KNEd6I+deoUNm3aJDZ0aG1tjXr16uHXX3/lLJGpTFI1gbhGiQyHJLU3z5fUdNm7d2+dqulSMewRFxeHZ8+eYfDgwfjnn3/Qrl07zgvUVVBWVq52/gaflJSU0L9//yrlwfnk4eHB1j1hGAa2trYoKiqClZUVli5dyktMNzc3jBo1CsePH0fr1q2r9OTxMSTh5uaGadOm4fLly+x2DykpKSgqKsK2bds4jwd8SAhdXV2xZMkS/PDDDxg3bhweP34MVVVVbNu2jdfJ6yNGjJDI68jExAQ7d+7EkiVLoK+vjxMnTmDq1KlISEjgbV6buro6IiIikJqairS0NCgqKqJdu3bo0KEDp3EiIyNx8uRJbNiwAcuWLYOBgQEGDBggkesqwzDV1h9SV1dn52BxzdbWFsHBwbzXBOIaLb/mkKRqY0i7pos0vHnzBrNmzcLjx48hFArZlTWPHj3Crl272PLsXPL29saff/6JPn36oHXr1lXe1BUVcLn0559/Ijo6GkuWLIGWllaV1xCfF5KMjAykpaVBJBJBR0eHk/L5nzJjxgwkJibCwsKi2g87rud3VcjNzcXp06fZD7+2bdtixIgRvO2d4+DgADU1NaxcuRInTpzAtm3bcPToURw+fBj/+9//xPZqk1VpaWlwcnLCzz//jPHjx8POzg7Z2dl4//495s6di7lz5/ISt7S0FK9evfpkRXMulZeXIyYmBidPnsT58+dRUFAA4MOX1ylTpqB58+acxgM+XF/ev3+PdevWsb1O+fn5+P333yEQCLB161bOY8pqTSBKZDgkqdoY0q7pIg0LFy4EwzBYs2YNLC0tcfz4cTRu3BhLlixBaWkptm/fznnMz60oEQgEvCx7tba2xps3byASiao9z9WFpLraI5/Cx8XL0NAQ+/fvr3bOijS8fPlSrLwAV4yMjHDixAloa2tjypQpaNu2Lby9vfHixQsMGTIECQkJNY7Rr1+/L/6/5HOItri4GCoqKigqKsLNmzehrq4utqqIS9HR0fDw8OC9onl1hEIhLl26hFOnTuHy5csoKytD7969OU8ssrOzMWXKFLx69Yrde+z58+do164dNm/ezMs8FmnUBOICDS1xSFJ780i7pos0xMTEICIiQmzeiJqaGhYvXoyff/6Zl5hhYWG8PO7n8NUT8bHdu3eL3WYYBnPmzIGnp6dEln936tSJ11Vu1ZHGMuH69esjPz8fb9++xZ07d9hVYM+ePeNssu+cOXPYf2dmZiIsLAz29vYwMDCAgoICHjx4gMjISE6Wen9KaWkp3r59y/5d27dvD6FQiOPHj3PeOwIAGzZswODBgz9Z0ZxPSkpKGDRoEAYNGoTCwkKcO3cOp06d4jyOpqYmTp48iStXruDJkydQVlZGhw4d0LNnT94WVVQkKpIsjskFSmQ4JMm9eWR1mdy3kpOTYwv/VZaTkyOR+jIVE6lFIhFsbGw4L6BWQVLFxaqbvCwnJwcTExOJTFb/+eef8fvvv2PUqFHQ0tKq8noeM2YM5zGlsUx44MCBWLRoEZSVldG8eXP06dMHp0+fxurVqznbPqTyJpRjxozB6tWrYWNjwx4bNGgQDAwMsHHjRl4Knv1X7wgfiUxmZiZCQ0PRpk0b6OvrIycnBwMGDIC8vDy7epRPK1euhLOzM5o0aYKRI0fyNkFWUVER/fv3l9hcR2kUx+QCJTIc2rhxI65du4Zdu3bB0dERwIfhCQ8PD/j5+XG6N480a7pIw7Bhw7Bq1Sp4enpCIBCgoKAA169fh5eXF2f1P4Avm0i9b98+3iZSS6PXQBq2bt0KJSWlar/JCgQCXhIZaSwT9vDwQHh4OF68eIFJkyZBSUkJQqEQc+bMwcSJEzmPl5aWhh9++KHKcS0tLU4rfVcmjd4RSVU0/5Tjx49j+vTpnK9ikvYwoTSKY3KBEhkOnTp1it2bp4KpqSl8fHzg5OTEaSIjzZou0vD7779jw4YNGDt2LEpLSzFq1CjIy8tj7Nix+P333zmLs3r1aty/fx9ubm7sROoJEyZg9OjRYhOpt2/fzksiI41eA2m4ePGixGNKY5mwgoICpk6dyg43l5WVYciQIbyttDMxMYGPjw9WrVqFli1bAvgwjOXl5cVpfZXKpNE7Urmiubm5OdauXctbRfPq8DW1tLrEz9vbG/PmzfvkDupckkZxTC5QIsMhSe3NI+2aLtKgpKQEV1dXLFy4EBkZGRCJRNDW1uZ8eemFCxfEJlIbGhqiZ8+eGD58OHufMWPGYM+ePZzGrSCNXgNpefnyJcLCwpCWloby8nK0b98eY8eO5XwJbQVpLBMuLS3Fhg0bJDLcDAA+Pj5wdnZGv379oKamBoZhUFhYCAsLC3h7e3Maq4I0ekc+rmh+7tw53iqaS1LlYcIKPj4+sLGxkciQrzSKY3KBEhkOSWNvnrrs1q1bnz2flJTE/pur0v3SnkgtqV6D6pb9lpeX48yZM1W6y/kY5rl58yYcHR2hq6sLIyMjiEQi3LlzB/v378fu3bt52XzV1dUVTk5O2L9/P8aPH499+/bB1NSUXSbMh02bNuHatWvYuXMnW5War+FmAGjevDkiIyPZ+irAh4nVfCWHgOR7R+7duwddXV32Onvx4kU0atQI8+bNw5gxYyTSI3P69GmJ74kmCdIojskFWn7NoezsbMydOxeZmZnIz89Hu3btkJWVBS0tLWzZsgVaWlrSbqJMqVxttfKWBMrKypCXl0dRURHk5eWhqqr6n8sGvybm9evXxXrWjI2Ncfz4cfYb0evXr2FlZcXLfJWZM2dCS0sLS5YswV9//YUTJ04gPDwcZ8+exerVq3H9+nVO4vTr1++L7icQCHgZi7ezs0OvXr3w66+/ih1fv349bt26xWv9I0kuE+7Xrx873Fz5dXT37l04OTkhJiaG85gMwyA7OxulpaVVzvHxrb6wsBC+vr4wNTWFra0tlixZgpMnT7K9I1/6Wvsvb9++xYwZM5CcnIyTJ0+iQ4cO2LlzJ9atWwc9PT00aNAAKSkpiIiI4K0GUlpaGu7fv4+ysrIqPRR8JPxA1esPnwoKCuDm5obz58+DYRjUr18fxcXF6N27N/z9/XnfVuNbUY8MhzQ1NSW+N09d9uDBA/bff/75J44cOQJvb2906tQJwIeVRB4eHujbty+ncaU5kfpzvQZOTk6cxZHGHJXKHj9+jA0bNlQ5bmdnx0t9ngpPnz5ll5LGx8fj8uXL0NfX5y2RkdRwc4XLly/Dw8MDOTk5Ysf52pNMkr0jgYGBUFJSQnR0NLS1tfHu3Tts2rQJPXv2xM6dOwEAAQEBWL9+PTZv3sxZ3AqhoaEICAhAw4YNqwxp8zVBXdLU1NQQFBTEFses+Azjs0ePC5TIcGjKlCnYvHlzlb153r59i5kzZ+LIkSNSbJ3sqbwkNyAgALt27WKTGODDJLRly5Zh8uTJmDZtGmdxpTmRukOHDoiKisL79+9Rr149HDlyBDdv3kTjxo15W/ItDVpaWkhISKhSkTk+Pp63JZ5//vknPDw8sGvXLjRq1AizZ8+GiYkJoqKikJWVxcvSZEkPN69btw7GxsZwcnLirVox8GW9I+Hh4Zz2jly6dAkBAQFsz8TVq1dRUlIitrv4wIEDceDAAU7ifSwyMhILFy5khwj5UF0P3cdfpCrwsf9bRkYG++/KyUvFcWntI/hfKJGpocuXL7PVc2/duoXNmzdX2Wfp+fPnElkSWNdlZ2dX2dzvyZMnnK4AkcZEamlX2ZWG6dOnY8WKFXj8+DE7sTohIQERERFYvHgxLzG3bduGVatWwcLCAr6+vujYsSN2796N2NhYuLi48JLIrFixAnPnzoWlpSVKSkowa9YsZGVlQVtbG1u2bOE8XkZGBjZu3Mjr9hKAdHpHcnNzxarZxsTEQEFBAT179mSPqaur87Y/Wn5+PgYPHszLY1f41Bey6r5I8XEtGDhwYLXXIoFAADk5Ody/f5/zmFygRKaGKr6JMAwDhmEQHx8vNutbIBCgfv36vC3v/F5MmDABS5YswZQpU9C5c2cAQGJiIsLDw6vtQZEl0q6yKw2jR48G8GF34b1796JevXrQ0dGBn58fBg0axEvMrKwsthfkf//7H1uoTUtLC//++y8vMSU93Gxqaop79+7xnshIo3ekZcuWePbsGVsx/cqVKzA2Nhbrebp9+zYvpfuBDzWlIiMj4eLiwluPrLRXpH48H04kEuH58+cIDg7G7NmzpdSq/0aJTA1paWmxY/pubm5wd3fntUv3ezVv3jxoaGjg0KFD2LFjB4APqzGWL18OW1tbKbeuZqRdZVdaRo8ezSY0kqCtrY3r16+jefPmeP78OVsHqGKZO1csLCxgbm7O/nTu3LnKcDNfunfvDk9PT1y8eBFt2rSpspSWq41OpdE7MnLkSPj4+GD+/PmIjY1FdnY2XF1d2fP37t3Dhg0beNuyJDc3F9HR0Thx4gRat25d5W8bERHBS1wAOHnyJPr168f5cv2PVa4fU6FNmzZQV1fH4sWLa+3KJUpkOHTz5k2UlZVVOZ6dnY2RI0fyskLhe2Jvby/2jY/ItitXruDgwYNIS0uDnJwcOnfujIkTJ/Ky9BoA5s+fj99++w0ikQjDhw9Hly5d4Ofnhz/++APBwcGcxVm8eDESEhIQGRkJHx8fNGrUCGZmZmKJDV9iYmKgr6+P3Nxc5Obmip3jshdBGr0js2bNwrt37+Dh4QGBQABnZ2d2K4bVq1cjLCwMffv2Zauqc619+/ZS65VYvnw5DA0NeU9kPqW8vBzZ2dlSif0laPl1DZ0+fZrdafXEiRMYNGhQleJa//zzD9LT03H16lUptLDuuHr1KhITE6td+sjVN83aQpJLLqXhjz/+gLe3N4YNGwZ9fX2IRCLcv38fZ8+exbp163iZi5CamoqmTZsiOzsbXbp0AfBhjlXDhg152xSvoKAAd+/eRUJCAuLj45GYmAiBQAAzMzNYWFhg0qRJvMTlW0hICM6cOcP2juzfvx8BAQFsYnHv3j3MmzcPP//8My9zjz728OFDiEQidO3alfdYwId99eTl5SVWPV1S14ONGzdWOVZQUIATJ07AxMSEl9VgXKAemRrq0aMHm6AwDAM5ObkqG+Dp6urCxcVFGs2rM3x8fBAeHg5dXd1qlz4S2bJ161Z4eXlVGVoyMzNj9+7h2pQpU7B9+3bo6+uzx/ieS6KmpgYrKytYWVnh7du3iIuLQ1RUFC5cuIDz58/zksgkJibi8ePHEIlEAP5vr67k5GSx1VM1Ie3ekY/x2ctVWUREBPbs2YOsrCycOXMGoaGhaNy4MRYuXFgnSmzcvn1b7LZAIICioiLGjRvH6cpQrlEiU0NNmjRh98B58uQJVq9eLbXuv7rs9OnT8Pb25n1XW2mQdpVdacjPz2dXK1VmamrK255SLVq0QHZ2tlgiw6fc3FzcuHEDsbGxiI2NRXp6Otq2bQtzc3OsWrXqszudf6tNmzYhJCQEzZo1w5s3b6CpqYnXr19DJBJxOolaXl4eLi4u1X5BGzNmDEaNGiWx3hFJ2b17N/bt24cFCxZg5cqVAIBevXqxWz98XNyRS15eXhLZeTosLIz3GHygoSUOmZubIzw8vNrdZ0nNWFpaYv/+/dDR0ZF2Uzgn7Sq70hAQEICkpCSsWbOGTdYKCwuxfPlyaGlpYdGiRZzHdHV1xYkTJ9ClSxe0bt26yhBw5bLsNeHr64vY2FikpqZCW1sb5ubm7ATg5s2bcxLjU3r37o358+fD3t4e/fr1w969e9GoUSMsWrQInTt3rrKMl3y5wYMHY9myZbCyshIb6rl+/Trc3Nxw5coVTuP9888/1R6v6CVp3Lhxld5/LqSmpuLhw4coKSmRWPXimqIeGQ7p6uri9u3blMjwYNKkSQgODoaXlxfnG0VKm7Sr7EpDbGwsHjx4gB9//BHa2tqQl5dHRkYGiouLoampiWPHjrH3rZiDVlMCgYBdcs2nvXv3QlNTEy4uLhg+fHiVXjU+5eXlsbtcd+nSBXfu3IGtrS0WLVoEZ2dnSmRq4OXLl2jXrl2V4y1atOCl2vfAgQNRXl7O3q6ozlxBQUEBAwYMgLe3N2crZXfu3Al/f380bNiwymPW5urFlMhwSFVVFd7e3ggKCqr2Gx+fy/PquuvXr+PevXs4c+YMGjduXGXpI1cfdkQyxo0bJ/GYfA1ZfSw0NBSxsbE4fvw4/P39oaOjAwsLC1hYWMDMzIzX/WpatGiBjIwMtGrVCh06dEBSUhJsbW2hqqpaZRUT+TpGRkY4cuQIFi5cyB4rLy/Hjh07qh0mrSlPT0/s2LEDy5YtY7fQSExMhI+PD4YPH44ePXrA398ffn5+nM192rlzJ9zc3PDLL79w8niSQkNLHPqvJZySmL1fVx09evSz50eNGiWhlhAuODg4wN3dXeJ7uFy6dAl79+5Feno6wsLCcOjQIbRs2ZK3Zf35+fm4efMmO1cmLS0NP/zwA5vYcLWhYoXQ0FDs2bMHvr6+aNy4MX755RfMmTMHsbGxKC4u5q18//cgNTUVM2fOhLq6OlJTU2FhYYFnz56hpKQEO3furFJ1vKasra0REBCA7t27ix2Pj4/HggULcPnyZSQlJcHBwQGxsbGcxDQ1NcXRo0dlbrUk9chwqHKiIunleXXd5xIVvkqSE/4kJydDQUGyl59jx45h9erVmDJlCu7cuYPy8nJoaGjAz88PxcXFmDp1KucxGzZsiAEDBmDAgAEAgKSkJBw4cAAHDx7Evn37OC8z7+joiBYtWkBFRQXdunXD0qVLERkZCXV1daxevZrTWN+bTp06ISoqCidOnEBaWhpEIhEGDhyIESNG8DLcXVhYWO17RCAQ4N27dwA+rIqrbpfzbzVy5EiEhYVh6dKlnD2mJFCPDMfq+vI8aXn16hW2bt2K1NRUdty4Ylnp06dPERcXJ+UWkq+xceNGXLx4Efb29mjdunWV/bL4qII7fPhwODk5wcbGRmyy5tmzZ7F27VrO5yoVFBQgMTERCQkJuHfvHu7du4d///0Xenp6MDU1hZmZGaytrTmNSfhXXl4OOTk5vHr1CnFxcejatWuVzU+54O7ujrt378LDwwP6+vpgGAYPHjyAj48PunTpAk9PT6xatQr//PNPlW1OvsbEiRPZf5eWluLevXvQ0NBA69atq0wmrq3TI6hHhkPSXJ5X1y1duhSZmZkYNGgQdu3ahWnTpuH58+c4d+6czH17IGA3TPTy8qpyjq8N8Z4/f17t0usuXbrg9evXnMVxdXVFQkIC0tPToaSkBENDQ5iZmWHy5MkwNjZGvXr1OIsFVN1Q8HO4Wpn1PaoY0lmzZg06duyIMWPGoKCgAEKhEAEBARg4cCCn8ZYvXw5vb284OjqyFeMVFBQwevRouLi44Pr160hKSsK6detqFCcrKwtDhgxhX5d9+vSpcdsljRIZDkVGRsLLywtWVlbw9PQEAPz0009o0KAB3NzcKJGpgbi4OOzatQvGxsa4fv06fvzxR5iYmCA0NBT/+9//ZLZC6vdKGpvj/fDDD7h8+XKV18qRI0c4Laj29u1bjBo1CmZmZjAwMOB9CI2PJbikKj8/P/Tv3x8GBgYICwuDgoICYmJicPz4cWzcuJHzREZZWRmrVq3C0qVL8eTJEygoKKBNmzZsnbLKQ5Y1kZWVhWnTpkmkTg1fKJHhkKSX531PGIZhd4Lu2LEjkpKSYGJiAhsbG+zcuVPKrSPfoqioCH/99ReePHkCkUiE9u3bY+jQobwtV3ZxccGsWbMQExOD0tJShISE4OnTp0hJScHWrVs5ixMaGvrJ4+PGjUPDhg05iwVIbjXW9y4pKQnr16+HqqoqLl68iP79+0NZWRk9e/Zke91rKiYmBmZmZmyS9LHKK8+4Gn6tC7NLKJHhkKSX531P9PT08Ndff8HJyQldunTBtWvXMHnyZGRkZEi7aeQbpKSkYMaMGVBUVGT3Wrp48SI2b96M8PBwdOzYkfOYpqamOHv2LPbv3w95eXnk5+fD1NQUGzZs4HRzw0/ZunUrbGxsOE9kPvapPckqthIg30ZdXR1ZWVlgGAaJiYns/m7379+HhoYGJzGmTZuG69evo2nTpp/dEoDr4VdZX5RCk3059KnleUKhEDt27OB8ed735O7du5g9ezZmz56NkSNHYvjw4WjQoAGys7Nha2uLFStWSLuJ5CtMnjwZWlpa8Pb2ZodeysrK4OHhgZcvX9Zo8mJtJYmN//5rT7J9+/bxFruu27hxI/bv3w9FRUU0a9YMf/75Jw4cOAB/f38sXLiQl1VvkqCrq/vFiQwfc9e4QIkMx0pKSnD8+HG2u1xHR4e35Xnfk7y8PCgqKqK4uBjNmjVDdnY2zp8/D3V1ddjY2NCKMBljaGiIo0ePVtm08cmTJ7Czs8Pdu3c5iTN58uQvvkjz/SEviUSmd+/eWLRoUZ3ck6w2OHfuHF68eIERI0agSZMmuHz5MsrLy9G3b1/OYw0ePBjW1tawsrKChYVFlZV9XNHV1UVgYCAaNWr0n/flYzUhF2hoiWPKysoYO3astJtR59ja2iIkJAR6enoAAE1NTbFlg0S2NG/eHM+fP6+SyDx79oyzcusAYGJiwv47Ly8Phw4dQv/+/aGvrw9FRUUkJSUhKipKIq+l7du3s/O8+CISiaoUUCPc+XhCL5/L53/99VfExMTA29sbr169gqmpKfr06QMrKytO95wTCAQwMzOjyb7kA2tr689++6My+t9OWVmZCt/VIfb29li2bBnmz5/Pzh9LSEhAcHAwp9sXVJ6vVlFNeMKECWL3sbCwqHYHcq7k5+fj0aNHKCsrq1LviOtvuHV5TzJpe/HiBdauXYuUlBQIhcIqk2S5vr4PHjwYgwcPBgBkZmbi77//xqVLl+Dn54dWrVrh/PnznMSpC4MylMhwqPJFE/gw5p+RkYGjR49WOUe+jpWVFRwcHNCnT59q97GqmHhHZMP06dNRXFyMDRs24N9//wUAaGhoYPr06bzNNbhz5w48PDyqHDc2NuZsr5qPHT16FJ6ennj//n2Vc3zUy6E9yfizZMkSvHv3DhMnTkSDBg0kErOgoAAJCQmIi4tDXFwc7t27hyZNmrA901wYNWpUleuprKE5MhLwv//9D6GhobTPSQ1Mnjz5k+doEqNssLOzw4gRIzBkyBCxVR5v3ryBsrIyp0NK1ZkwYQLatGmDlStXssW/3r17h6VLl+Ldu3fYs2cP5zEHDx4MKysrLFy4kPfnB9CeZHzq1q0bjhw5gk6dOkkknq2tLdLS0qCtrQ0jIyN0794dpqamnA4r1RXUIyMB7du3x4MHD6TdDJkWFhYm7SaQGjI3N8fevXuxdu1aWFhYYMSIERg0aJDExuYrqqT27NkTbdq0AcMweP78OVq1avXJ2i819erVK0yaNEkiSQxAiQqfdHR0JLqDeOvWrfHy5Ut2SwQFBQWJ708mK6hHhkPVFTAqLCzE7t278f79exw5ckQKrap70tPTcfDgQYhEItjY2MDQ0FDaTSJf4e7duzh79iyioqKQl5eHvn37YsSIEbCysuL9Qi0UChETE4PHjx8D+LARYM+ePXmLu3jxYujp6cHBwYGXxwc+7JWzZcsWNGzYEBMmTPjsPL3auldObVX5mn7nzh0cOnQIs2fPhra2dpWVknyt6Hn48CFu3bqFmzdv4s6dO+zk3A0bNvASTxZReseh6goYKSoqwsDAgLcx+LqsqKgIfn5+OH36NIAPXa0TJ06Evb09mjZtCoZhsG/fPgQFBaF///5Sbi35UsbGxjA2Noabmxtu376Ns2fPYvny5SgtLcVPP/2EESNG8LbyRklJCWpqalBXV8fgwYPxzz//sJuQ8qFJkyYICAjAqVOn0KZNmypzVrjY+8jS0pJ93J49e9b48cj/qe6aXrGPXmV87Q8GAJ07dwbDMBCJRCgrK8PVq1dx7949XmLJKuqRqaF3795JbOLX98bd3R3379/HlClT0KRJE4SFhSEpKQm2trZwc3MDAAQGBiI2NhaRkZFSbi2pCYZhEBsby64K4eND4c2bN5g1axYeP36M0tJSnD17Fj4+Pnj06BF27drFyw7GFa/TT+Fze4GysjLIy8vLfNXW71VYWBhu3LiBW7duQSgUwsLCAr169ULv3r1pnsxHKJGpoa5du0JXVxfm5uawsLCAmZmZxMbD67oePXogNDSUXZ779u1b9OzZE4cPH2Z3Mc7MzMSwYcMQHx8vxZaSb1VQUIALFy4gKioKMTEx0NLSwvDhw+Ho6Mh5rIULF4JhGKxZswaWlpY4fvw4GjdujCVLlqC0tBTbt2/nPKY0REREYM+ePcjKysKZM2cQGhqKxo0bY+HChVQ4sgbKy8uxfft2aGhoYPTo0QCAqVOnsisquU4YbW1t0bt3b/Tu3RsmJia8FcSrC2hoqYa2b9+OhIQExMfH4+jRoygoKEDnzp1hbm4Oc3NzmJmZUY/NN8rLy0OLFi3Y202aNIGKiopYBcp69eqhpKREGs0j3ygvL08seWnWrBmGDh0KZ2dnXrfxiImJQUREBLtiCQDU1NSwePFi/Pzzz5zF2bhxIxwdHaGiooKNGzd+8n587H20e/du7Nu3DwsWLGCHQHr16sVuavjrr79yGu974ufnh/Pnz8PT05M9NnToUGzZsgX5+flYtGgRp/GOHTuGgoICKCoqQklJCY8ePcKVK1egr6+PHj16cBpL1lEiU0O9evVCr1692NtPnjzBvXv3cPfuXQQFBeHx48fo1KkTLCws4OLiIsWWyiZ5eXlpN4FwJDIyEtHR0bh58yZUVVUxePBg7N69G6amphKJLycnh+Li4irHc3JyOK2jcfv2bUybNg0qKiq4ffv2J+/Hx5BPZGQkvLy8YGVlxX7g/vTTT2jQoAHc3NwokamBU6dOYfPmzTAyMmKPjR07Fjo6Oli4cCHnicylS5ewaNEibN68Gdra2pg4cSKaNGmC4OBguLq6clo4UtZRIsOx9u3bo23btujQoQPat2+P+Ph4XLp0Cenp6ZTIfIO4uDixHi2GYXD37l1kZmYC+FA1lcgGPz8/9OvXD5s2bUKfPn0kvpR02LBhWLVqFTw9PSEQCFBQUIDr16/Dy8sLQ4YM4SxO5VIBki4b8PLlS7Rr167K8RYtWtB7pYZKSkqqTXjV1NRQWFjIebwNGzZg1qxZsLS0RGBgIJo1a4bTp0/jwoULWLNmDSUylVAiw5EHDx4gNjYWsbGxbBlyY2NjWFhY4JdffoGBgYGUWyibqut6X7JkidhtmswoG65fv15t2fy4uDgYGBjwPgfg999/x4YNGzB27FiUlpZi1KhRkJeXx9ixY/H777/zFjclJQXh4eFIT0/HunXrcO7cObRp0wZ9+vThPJaRkRGOHDkiVkm8vLwcO3bsYOeakW9jbW0Nb29vrFmzht34MyMjA76+vrCysuI83rNnz2BrawuBQICLFy9iwIABEAgE6NKlC169esV5PFlGk31raN68eeyscmNjY3bSr4GBARUvIuQLdO/eHceOHeN1V+jK3r9/j4yMDIhEImhra/O6J9HVq1cxf/582NjY4NSpUzh16hSOHj2K0NBQ+Pr6Yvjw4ZzGS01NxcyZM6Guro7U1FRYWFjg2bNnEAqF2LFjB69zkOq6vLw8zJ07V6yXuKCgAJaWlli7di2aNWvGabwBAwbA3d0dLVu2xMiRIxEREQETExP88ccf2Lt3L1uWglAiU2O6urpo3rw5Jk6ciF69ekFPT496CAj5CsbGxjh+/DgviUxMTAzMzMygoKBQbcHKyvgoaDZ69GjY29vD3t5e7HkeOHAA+/btw5kzZziPWVJSguPHj+PJkycQiUTQ0dHBiBEjaBNJjqSmpiItLQ2Kiopo164dOnTowEuciIgI+Pr6Qk5ODiYmJti9ezdCQkIQEhICPz8/DBs2jJe4sogSmRpKS0tDbGwsbty4gZs3b0IkEsHExAQ9evSAhYUFunTpIu0mElKr8ZnI6Orq4vr162jatOlneyP4KmhmZGSEEydOQFtbW+x5Pn/+HMOGDaPCZjKmtLQUr169YosoMgwDoVCIpKQkjBgxgvN4SUlJ+Oeff9C7d2/Uq1cP8fHxqFevHvWsfYTGPmqoQ4cO6NChAyZOnAgASE5Oxo0bNxAbG4vNmzdDTk4OZmZmsLCw+OzGh4R8r2bPni22pJ5LDx48gEAgQHl5uVT2O9PS0kJ8fHyVJO3ixYu8JG4vXrxgiwoKhUJ8/D2Vdr/+dtHR0fDw8Kh20rSmpiYviUzXrl1RXFyMU6dOYfDgwahfv361k7m/d9Qjw5P379/j3r17OHHiBE6ePIn379/zVsKaEFI9XV3dLxrqFQgESEpK4jz++fPnsWTJEowZMwaRkZFwcHBARkYGoqKi4O/vDxsbG07jTZw4Ee/evcOYMWOqrV9Fm0p+u59++gnm5uaYOnUqxo8fj9DQUOTl5cHb2xtz5syBnZ0dp/HevHmD2bNnIzU1FUKhEFFRUbxXopZVlMhwgGEYPHr0CPfu3WN/0tLS0KxZM5iYmMDU1BRmZmbo2LGjtJtKSK3wuQRDUVERGhoasLGxwYIFC6rsT/Q1bt68+clz2dnZCAwMxIsXLzB06FCsX7/+m+N8TkpKCnbt2oW0tDR2zsrUqVN52ey0W7duOHLkCDp16sT5Y3/v9PX1cfr0abRp0wbTp0/H+PHjMWDAAFy7dg1+fn44efIkp/G+l0rUXKChpRqaNGkSHjx4gPfv30NbWxumpqaYOnUqTE1NJbYKgxBZs3LlSgQHB2P+/PkwMjICwzC4f/8+goKCYGdnhx9++AGbN28GwzA1Whptbm5e5Vh5eTn27duH4OBgaGhoYPfu3bztXAx8SNq42BzyS+jo6CA3N1cisb43DRs2ZAsq6ujoIDk5GQMGDICOjg5b14pLkqpEXRdQIlNDnTp1woQJE2BqaormzZtLuzmEyISdO3fCx8dHrJaKrq4uWrVqhZUrVyI6OhqampqYP38+pzVe7t69C09PTzx79gyzZ8/G9OnTa9Tj81+EQiEOHTqEhw8foqSkpMqcFS4SnMqrsQYNGoQlS5Zg9uzZ0NbWrrK3Ep8JW13Xt29feHp6wtPTE+bm5li7di2sra0RFRUFTU1NzuNJqhJ1XUCJTA2tWLGi2uMrV66Es7MzmjRpIuEWEVL7vX79utqLf5MmTdhiXxoaGpxVTM3Ly4O/vz/+/PNP/Pjjj9i8eTNat27NyWN/joeHB6Kjo9GrVy/e9lybNm1alWMV+yxVxtfKrO/F0qVL4evriwcPHsDW1hbnzp2Dvb096tevD39/f87jSaoSdV1Ac2R4IukiX4TIknnz5uHt27fw8/NDmzZtAADPnz+Hu7s7VFVVsXnzZgQFBSEmJgZ//PFHjWIdOnQI69evh6qqKpYuXYr+/ftz8RS+iLGxMUJCQiTSE1JQUAB5eXmoqKhUOZednY21a9fyNg+orrt37x50dXXZ6tMXL17E33//jcaNG2PMmDG89MgIhUJs2LABERERKC0tBQC2ErWbmxv1ylRCiQxP+KyNQYisy8vLw6JFixATE4MGDRqAYRgUFhaid+/e8PHxQWJiIpYuXYqQkBB07979m+OMGzcOCQkJaNWqFaZNmyY23+BjY8aM+eY4n2JtbY2dO3fyOtE/OzsbLi4uuHHjBgCgT58+WLt2LRo1agSRSITdu3djy5YtUFBQYO9Dvszbt28xY8YMJCcn4+TJk+jQoQN27tyJdevWQU9PDw0aNEBKSgoiIiLQvn17XtogyUrUsooSGZ5QIkPIp6WmpqJjx45IT0/Hw4cPIS8vj44dO7I1Mt6/fw9lZeUaV8nu16/fF91PIBDgwoULNYpVoaJYGgD88ccfOHv2LFasWAFtbe0qu7l/PIflWzg5OSE1NRXOzs5QVFREUFAQDAwMsHDhQjg5OSElJQVjxozBokWL0Lhx4xrH+54sX74cjx49gr+/P7S1tfHu3Tv07t0bpqam2LlzJwAgICAAjx8/xubNm2sc77+qT1dG853+DyUyPMnKyoKmpiYnFypC6hpLS0ts374d+vr60m4K5yovLa+4vH4qIeNizoqFhQUCAwPZD7Znz57Bzs4Obdu2hUgkwqpVq2jT2m/Up08fBAQEwMTEBABw+vRp/Prrr9i0aRMGDRoEALh//z4cHBw+u9T/S31pxV6a7ySOJvtyLC0tDffv30dZWVmVFQp8dF0TIotatGiB7OzsOpnI7Nu3j/23SCSq0gvDtfz8fLH9ftq1a4fS0lK0bt0aGzZs4HVVVl2Xm5uLVq1asbdjYmKgoKCAnj17ssfU1dUhFAo5iZeSksLJ43xvKJHhUGhoKAICAtCwYcMq45gCgYASGUL+v86dO8PZ2RldunRB69atq0xclFTdFT5Url0zbNgwrFu3jte9cRiGqZIsycvLY+7cuZTE1FDLli3x7NkztGzZEuXl5bhy5QqMjY2hpqbG3uf27dtiyQ7XXr16hZKSkirHadrC/6FEhkORkZFYuHAhZs2aJe2mEFKrCQQCXvamqW3+/fdf3ntkPoUmhdbcyJEj4ePjg/nz5yM2NhbZ2dlwdXVlz9+7dw8bNmzgpUDdtWvX4OLigrdv34oNUTIMQ0NLH6FEhkP5+fkYPHiwtJtBSK3n6+sr7SZIxIgRI+Dg4IDhw4dX2/PEVS/tyZMnxRKX8vJynDlzpkodK+oV/jqzZs3Cu3fv4OHhAYFAAGdnZ3Z/rNWrVyMsLAx9+/aFo6Mj57G9vb1haWmJGTNm8FaDqK6gyb4c8vb2hqKiIlxcXGq82oKQumzjxo2fPb9gwQIJtYRfn1s1xdVKKWmszCLAw4cPIRKJ0LVrV14ev1u3bjh16hQNIX0B6pHhUG5uLqKjo3HixAm0bt26yvh0RESElFpGSO1y+/ZtsdsikQiZmZnIz8+vU1VLL168WCdikKo6d+7M6+P36NEDt27dokTmC1Aiw6H27dtj9uzZ0m4GIbVeWFhYtcfXrFmDsrIyCbeGW7du3fri+5qZmfHYEiJrKvdUamhoYMWKFbh69SratGlTpZRHXem15AINLfGkrKwM8vLyNMREyFfIyMjAqFGjqvTYyJKPVyhVTNBUVlaGvLw8ioqKIC8vD1VVVU5qj5C6Y/LkyV90P4FAILbM/3tHPTIci4iIwJ49e5CVlYUzZ84gNDQUjRs3xsKFC6k4HiH/4ezZs5/dRkAWPHjwgP33n3/+iSNHjsDb2xudOnUCAKSnp8PDwwN9+/aVVhNJLVVdT2XFKiXgw4KShg0bSrpZtR4lMhzavXs39u3bhwULFrC7z/bq1Qve3t4AgF9//VWKrSOk9rC2tq7SW1lYWIiCggK4uLhIqVXcqLzcOiAgALt27WKTGABo27Ytli1bhsmTJ1e7czUhwIcd4l1cXKCvr49FixYBAGxsbKCvrw9fX98qK9K+Z5TIcCgyMhJeXl6wsrKCp6cnAOCnn35CgwYN4ObmRokMIf/fwoULxW4LBAIoKirCwMCA3Q27rsjOzq4y3PTkyRN2J2VCqrN8+XIA4kvmIyIi4O3tjVWrVmHDhg3SalqtQ4kMh16+fMlueldZixYtkJ+fL/kGEVJLjRo1iv13bm4uFBUVxaql1hUTJkzAkiVLMGXKFHaVS2JiIsLDw+Hs7Czl1pHa7MaNGzh8+LDYqqV27dph6dKlGDdunBRbVvtQIsMhIyMjHDlyROzbZnl5OXbs2IFu3bpJr2GE1DLl5eUICgpCZGQk8vLyAHxYpeHg4ICpU6dKtW1cmjdvHjQ0NHDo0CHs2LEDANCpUycsX74ctra2Um4dqc1UVVWRmZkJHR0dsePZ2dm09cRHaNUSh1JTUzFz5kyoq6sjNTUVFhYWePbsGYRCIXbs2MHrfiuEyJLVq1fj/PnzWLBgAbp27Yry8nLcu3cPmzZtwqhRo7B48WJpN5ETwcHBGD16NK978ZC6adOmTTh8+DAWLFgAPT09AEBSUhKCgoIwZMgQ/P7771JuYe1BiQzHSkpKcPz4cTx58gQikQg6OjoYMWIE7XtCSCUmJibYtm0bTE1NxY7//fffWLRoEW7cuCGllnHL1NQUR48epaJm5KuVl5dj06ZNOHjwIHJzcwEATZo0weTJkzFz5kyp7eFVG9HQEseUlZUxduxYaTeDkFqtQYMGUFCoevlRVVWtU93mtra22Lx5M2bOnIlWrVpV2WuJSjKQ6ty7dw+6urpYuHAhFi5ciL/++gs3btyAlpYWRo0aRUnMR6hHpob69ev3xUXvaJ8T8j3LyMhg/x0VFYVDhw5h6dKl0NfXh0AgwKNHj7B69WpMmjQJ9vb2Umwpd6ytrZGdnf3JawTtYEwqe/v2LWbMmIHk5GScPHkSHTp0wK5du+Dv7w99fX2oqakhJSUF4eHh6NChg7SbW2tQIlNDhw4dYv+dmZmJsLAw2Nvbw8DAAAoKCnjw4AEiIyMxefJkzJs3T4otJUS6dHV12Q/0ypedj48JBII68wH/X5V7zc3NJdQSIguWL1+OR48ewd/fH9ra2nj37h169+4NU1NT7Ny5E8CH2kSPHz/G5s2bpdza2oOGlmqo8jDSmDFjsHr1anabdwAYNGgQDAwMsHHjRkpkyHfte+yRrEhU0tLSkJaWxs6bo4n/pDqXLl1CQEAAO6fq6tWrKCkpEeuhHDhwIA4cOCCtJtZKlMhwKC0tDT/88EOV41paWsjMzJRCiwipPVq3bl3tcYZhUFc7hv/991+4uLjg0qVLaNSoEUQiEQoLC2FqaoqQkBA0aNBA2k0ktUhubq7YCreYmBgoKCigZ8+e7DF1dXUIhUJpNK/WoplmHDIxMYGPjw+ysrLYY8+ePWOr/RJCPkhMTIS9vT309PTQtWtX6Onpif3UFd7e3sjJycGZM2dw48YN3L59GydOnEBxcTF8fX2l3TxSy7Rs2RLPnj0D8GHV0pUrV2BsbCxWLPL27du0nP8j1CPDIR8fHzg7O6Nfv35QU1MDwzAoLCyEhYUFvLy8pN08QmoNLy8vKCsrIygoqE5W9K3wv//9D3v37hUrataxY0csX74cM2fOlGLLSG00cuRI+Pj4YP78+YiNjUV2djZcXV3Z8/fu3cOGDRvw888/S7GVtQ8lMhxq3rw5IiMjkZqairS0NAAfqnjS7HJCxKWmpuLgwYPVDsXWJZ/ayVsgEEAkEkm4NaS2mzVrFt69ewcPDw8IBAI4Ozuzcy5Xr16NsLAw9O3bF46OjlJuae1Cq5Y4VlpailevXqG8vBzAh/F/oVCIpKQkjBgxQsqtI6R2GDduHBwdHdGvXz9pN4VXHh4eePjwIdasWcP2yjx58gSurq5o27Yt/P39pdxCIisePnwIkUiErl27SrsptQ4lMhyKjo6Gh4dHtRtEampq4tKlS5JvFCG1UEREBDZv3oyRI0dCW1u7ShG8yjv+yrL8/HzMnTsXt27dYofQCgoK8OOPP2LNmjVo1KiRlFtIiOyjRIZDP/30E8zNzTF16lSMHz8eoaGhyMvLg7e3N+bMmQM7OztpN5GQWuFzPTECgUCml2pX9MZWVjHcXK9ePbRv3x5t2rQBQJV9CeECzZHhUGZmJkJDQ9GmTRvo6+sjJycHAwYMgLy8PPz8/CiRIeT/u3jxorSbwJuuXbt+UbVvgUCApKQkCbSIkLqNEhkONWzYEMXFxQAAHR0dJCcnY8CAAdDR0aE6MoR85PXr1zh06BDS09Px+++/48aNG+jQoQM6d+4s7abVyL59+z55Ljs7G4GBgXjx4gWGDBkiwVYRUndRvyaH+vbtC09PT6SmpsLCwgLHjh3DvXv3sH//fmhqakq7eYTUGomJiRg8eDBiYmJw8uRJFBUV4caNGxg7diyuXbsm7ebViLm5eZUfU1NTJCUlwdPTE0pKSti9ezfWr18v7aYSUifQHBkOFRYWwtfXF6amprC1tcXvv/+OU6dOoX79+vD396/zKzQI+VITJ05Enz59MGvWLBgbG+P48ePQ1tZGcHAwLly4gKNHj0q7iZy5e/cuPD098ezZM8yePRvTp0+vUzt8EyJtlMjwrKCgAPXq1YOCAo3iEVLB2NgYx44dQ5s2bcQSmYyMDAwbNgwJCQnSbmKN5eXlwd/fH3/++Sd+/PFHLFu27JPbNBBCvh19uvIkPT0dBw8eRHl5OX766ScYGhpKu0mE1BpNmzZFWloau3qnQlxcHJo3by6lVnHn0KFDWL9+PVRVVREcHIz+/ftLu0mE1FmUyNRQUVER/Pz8cPr0aQCAra0tJk6cCHt7ezRt2hQMw2Dv3r0ICgqiixkh/9/MmTPh4eGBmTNngmEYXL9+HVlZWdi3bx9+++03aTevRsaNG4eEhAS0atUK06ZNQ25uLg4fPlztfetKvRxCpImGlmrI3d0d9+/fx5QpU9CkSROEhYUhKSkJtra2cHNzAwAEBgYiNjYWkZGRUm4tIbXHxYsXsXPnTqSlpUEkEkFHRwdTp06V+dU8XzoXTtbr5RBSW1AiU0M9evRAaGgounXrBgB4+/YtevbsicOHD0NfXx/Ah/oyw4YNQ3x8vBRbSgghhNQ9NLRUQ3l5eWjRogV7u0mTJlBRURErPV6vXj2UlJRIo3mE1BobN2784vsuWLCAx5YQQuoSSmQ4IC8vL+0mEFLr3b59+4vu9yVVcQkhpAIlMhyIi4tDgwYN2NsMw+Du3btsNd/qNpEk5HsTFhb2Rfej9wsh5GvQHJka0tXV/aL7CQQCJCcn89waQmTD2rVrsWTJkirH//zzT6xbtw5///23FFpFCJFF1CNTQykpKdJuAiEy58SJE3j37h28vLwgEAiQkpKClStXIjk5GQ4ODtJuHiFEhlCPDCFE4l68eIGZM2eiU6dO0NTUREREBPr16wcXFxdoaWlJu3mEEBlCiQwhRCry8vIwe/Zs3Lt3jwpGEkK+GSUyhBCJqG759fv37xEREYHOnTujd+/e7HFafk0I+VI0R4YQIhGfWn5dsQ9ZxXlafk0I+RrUI0MIkRqGYdjEJT8/Hw0bNpRyiwghskZO2g0ghHx/Xr9+jenTpyMwMJA9ZmNjg1mzZuHt27fSaxghROZQIkMIkbjly5cDEN/9OSIiAmVlZVi1apW0mkUIkUE0tEQIkTgTExMcPnwYOjo6YsfT0tIwbtw43Lp1S0otI4TIGuqRIYRInKqqKruFR2XZ2dlQVFSUQosIIbKKVi0RQiRuzJgxcHd3x4IFC6CnpwcASEpKQlBQEEaNGiXl1hFCZAkNLRFCJK68vBybNm3CwYMH2cm9TZo0wZQpUzBz5kzaUZ4Q8sUokSGESNXbt2+hpKQENTU1aTeFECKDaI4MIUQqUlJSsGzZMixYsACFhYUIDw/HlStXpN0sQoiMoUSGECJxV69exbhx4yASiZCQkAChUIi3b9/CyckJJ06ckHbzCCEyhIaWCCESN3r0aNjb28Pe3h7Gxsb4f+3csUrzUACG4S8l0KGLdG0zWCiYSSh0sHaQJBfi3kEnb8Kpk5tDlwzi4iIdkkoQXJQUOtTFLtU7cGyD0/8vIojgORx5nzGc4Rtfcpre3NwoCAKlaarJZKLb21vbEwE4gjcyAIxbrVYaDAafnh8eHurt7c3CIgCuImQAGNdutzWfzz89z/NcQRCYHwTAWfyPDADjTk9PdXZ2psVioe12q+vra63Xa02nU52fn9ueB8Ah/EYGgBXPz8+6vLzUy8uLttutdnd3dXx8rP39fdvTADiEkAEAAM7iagmAEePx+NtnT05OfnEJgL+EkAFgxMXFhWq1msIwVKPR0Fcvgz3PM7wMgMu4WgJgRJqmyrJMZVmq3+8rjmPFcaxms2l7GgCHETIAjHp/f1dRFMqyTPf39+p2u0qSREmSqN1u254HwDGEDABrNpuNHh4elOe57u7utLOzoyRJNBqNbE8D4AhCBoBVVVXp6elJWZbp6upKVVWpLEvbswA4gpABYNy/66XZbKaiKOT7vo6OjhRFkYbDoer1uu2JABxByAAw4vX1VbPZTHme6/HxUa1WS1EUKY5j9Xo9vlYC8COEDAAjwjCU7/v/v1jqdDpfnj04ODC4DIDLCBkARuzt7X3rnOd5Wi6Xv7wGwF9ByAAAAGfVbA8AAAD4KUIGAAA4i5ABAADOImQAAICzCBkAAOCsDx2CuF0uZmkeAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<Figure size 648x360 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Displayed below all sum of the death cases across all Germany.\n",
    "plt.bar(num_of_states, states_death_cases_age_frame.iloc[:, :-1].apply(sum))\n",
    "plt.xticks(rotation=90)\n",
    "plt.title(\"Total Death Cases\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "id": "selective-pollution",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 648x360 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Displayed below all sum of the recovered cases across all Germany.\n",
    "plt.bar(num_of_states, states_recovered_cases_age_frame.iloc[:, :-1].apply(sum))\n",
    "plt.xticks(rotation=90)\n",
    "plt.title(\"Total Recovered Cases\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "id": "dietary-baker",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Creating a generic function sum all the cases according to the age groups.\n",
    "def total_cases_to_age(df):\n",
    "    \"\"\" The function takes one argument \"df\" which is dataframe that has the cases\n",
    "        according to the age groups and it returns a list of the sum of all the cases \n",
    "        across all age groups. \"\"\"\n",
    "    new_list = []\n",
    "    for i in range(df.shape[0]):\n",
    "        new_list.append(df.iloc[i,:-1].sum())\n",
    "    return new_list"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "id": "european-marathon",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 648x360 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Displayed below all sum of all the cases in Germany across all age groups.\n",
    "total_cases = total_cases_to_age(states_all_cases_frame)\n",
    "plt.bar(num_of_age_group, total_cases)\n",
    "plt.title(\"Total Confirmed Cases to Age Group\")\n",
    "plt.xlabel(\"Age Group\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "id": "nuclear-leather",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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Di1wvXbokPae31gFuhpvb51tVVYVly5ZJYaIhs2bNQlFREZYsWdLgKcDr1683+Emq3/P29sbRo0elUA3cPPJ04MAB9O7dG61atULr1q0BQLrgGrj5/UgNnS4qKChATk6OdL+0tBRZWVl49tln7zkWIoBHZIgwe/ZsTJo0Cf/7v/+L0NBQ6PV6JCYmoqamBm+++aa0Xtu2bZGdnY2TJ0+iX79+eOqpp/DZZ5/hySefRNu2bXHs2DFs27YNAAw+Qnw/9Ho9Tp48Kd2vqKjAiRMnsH37dvj6+iIkJATAzWtR3nvvPURGRgIAhgwZgqqqKmzYsAH5+fmIiooCcPOamf3792Pbtm3o1q0bcnJysH79epiZmaGqqspgTqdOncJ3331ncC2GMWJiYvD666/jpZdewquvvgqVSoXq6mocOnQIX331FUaMGIGXX35ZGt+3336L+Ph4qNVq5OfnIzExETqdThpf3759IYTA9OnTMXnyZDg4OODbb7/F+fPnpSMwb775Jl5++WWEhYXh1VdfhZ2dHXbu3ImDBw9Kn6bx8/NDcnIy3nvvPYwePRr19fX47LPPYGtr2+i3Ordt2xY//fQTfvjhB/j6+t736+QWrVaLb7/9Fq+88kqDXwLYqVMn9O3bF3//+98xe/ZsTJw4Edu3b8ekSZPwxhtvALj5pXy1tbXS6S9XV1eMHj0aCxYsQGFhIZRKJQoKCrBq1So4Ojo2emrzVoBbvHgxMjMzMWbMGHTr1g01NTXIyMjArl27UFFRgalTpzb6PL/55ps4evQoQkJCMHXqVNjY2GDr1q0oLCzE+vXrAdw8auPl5YXt27fj6aefhpOTE1JTUxs8kmNmZoaZM2finXfegaWlJdauXYu2bdvitddea3QcRJKWucaYqGXc7RNC6enp4tVXXxV9+vQRXl5eYtq0aSInJ8dgnS1btoi+ffsKb29vUVNTI86dOydCQkKESqUSPj4+YsKECeLw4cPihRdekD7Fcr+fWnJ1dZVuPXv2FM8++6wYN26c2LZtm8EnW275+uuvRXBwsPDw8BA+Pj5iypQp4scff5TqV65cEe+9957w8fERKpVKjBgxQiQnJ4sFCxYIPz8/6ZM3J0+eFAMHDhSenp7ixIkT0qeWLl68aPB448ePlz4505jLly+LlStXiqCgIKFWq4W3t7d46aWXxO7duw0+DVNTUyNiYmKEv7+/6NOnj3j++efFqlWrxNq1a4W7u7u4fPmyEEKIH3/8UUyePFn4+voKDw8PMXLkSINP/whx8xM5U6dOFWq1WqhUKhEcHCwOHDhgsM6BAwfE2LFjpXVCQ0MNPg3VkK+//lr4+voKlUolCgsLhRD39zq5Zf369cLV1VVkZmbe9TFSUlKEq6ur2LFjhxBCiJ9//lm89tprok+fPsLPz0+sWbNGvPzyy2LatGnSNrW1tSIhIUEMHTpUuLu7iwEDBogPPvhAaLXaRudzS25urli0aJF4/vnnhVKpFCqVSowaNUp89NFHIj8/32Dd339S75azZ8+KyZMnC5VKJVQqlZg4caI4fvy4wToFBQViypQpQqlUCl9fX7Fo0SLxxRdf3PGppYEDB4rU1FQxYMAAoVarxcyZM0VBQcF9zYVICCHMhOCvohERtbRTp07h6tWrBt/4q9frMWjQIIwcORJz585twdE9HOHh4fj+++9x9OjRlh4KyRhPLRERPQYuXbqEd955B9OmTYOvry+qqqrw5ZdforKyEi+99FJLD4/oscUgQ0T0GPif//kfREVF4bPPPsPmzZthZWUFlUqF7du345lnnmnp4RE9tnhqiYiIiGSLH78mIiIi2WKQISIiItkyyWtk6uvrUVdnemfMLCzMTHJejwJ7Zzz2zjjsm/HYO+OZau+srO78LqZbTDLI1NUJlJdX3XtFmVEoWpnkvB4F9s547J1x2DfjsXfGM9XeOTnd+ZMct/DUEhEREckWgwwRERHJFoMMERERyRaDDBEREckWgwwRERHJVpOCTGRkJEJDQ6X7RUVFCAsLg0qlwvDhw3HkyBGD9dPT0zFy5EgolUqEhoYiPz/foL5161YEBARArVYjIiICVVX/f6W1TqfD/Pnz4e3tDX9/f2zYsMGY+REREZEJu+8g88MPPyA1NVW6L4TAzJkzoVAokJqaijFjxmDWrFkoLCwEABQXF2PGjBkYNWoUdu7cCUdHR8ycORP19fUAgLS0NKxcuRJRUVHYsmULNBoN4uLipP0vXboUmZmZSE5ORkxMDBISErB///4HNW8iIiIyAfcVZKqqqjB//nz07dtXWpaeno4LFy5g4cKF6N69O6ZOnQq1Wi2FnZSUFPTq1QtTpkxB9+7dsWTJEhQXFyM9PR0AsHnzZoSEhGDIkCHw9PREdHQ0du/ejevXr6OqqgopKSmYN28ePDw8EBgYiMmTJ2Pbtm0PoQVEREQkV/cVZFasWAEfHx/4+PhIy7Kzs9G7d2+0bt1aWubl5YWsrCyp7u3tLdXs7Ozg7u6OzMxM1NXVQaPRGNRVKhXq6upw7tw55OTkQKfTwcvLy2DfGo0GtbW1Rk+WiIiITMs9g0xmZia+/vprzJ0712C5VquFs7OzwbL27dujpKSk0XppaSkqKipQU1NjULe0tIRCoUBJSQm0Wi0cHBxgY2Mj1R0dHaHX63H58uWmz5KIiIhMUqM/UaDT6RAZGYl58+bBwcHBoFZdXQ0rKyuDZdbW1tDr9VLd2tr6jrpOp8ONGzek+w3Va2trG6zdGhMRERERcI8gs3btWnTu3BnDhw+/o2ZjY4PKykqDZTqdDra2tlL996FDp9NBoVBIR1oaqtva2sLMzKzBGnDzFNW9WFiYQaFodc/15MbCwtwk5/UosHfGY++Mw74ZT869qwNg28gPHD4Kjf0u0cN0Q1+Hlph5o0Fm79690Gq1UKvVAAC9Xo+6ujqo1WpMmzYNOTk5BuuXlZXByckJAODi4gKtVntHvUePHlKYKSsrg6urKwCgtrYW5eXlcHZ2hrm5OSoqKqDT6aQjMVqtFtbW1nccGWoIfzSSfo+9Mx57Zxz2zXhy7p2TUxt0Cf9jfsL2YlwQtNprD2XfRv9o5NatW7Fv3z7s2bMHe/bswbhx4+Dh4YE9e/ZAqVQiJyfH4LtfMjIyoFKpAABKpRKnTp2SatXV1Th79ixUKhXMzc3h6emJjIwMqZ6VlQULCwu4ubnBzc0NVlZWyMzMNNi3u7s7LC1N8ge7iYiIyAiNBpmnnnoKnTt3lm5t27aFra0tOnfuDB8fH3To0AHh4eE4f/48EhMTkZ2djXHjxgEAgoODkZ2djYSEBOTm5iIyMhIdOnSAn58fAGDChAlISkpCWloaNBoNYmJiEBwcDHt7e9jZ2WH06NGIiYnB6dOncejQISQlJWHixIkPvyNEREQkG0Yf3rCwsEB8fDwiIyMxduxYdOrUCWvWrEHHjh0BAB07dsTq1asRGxuLdevWQalUIj4+HubmN7NTUFAQioqKEB0dDZ1Oh6FDhyI8PFzaf0REBKKjo/Haa6/B3t4eb7zxBl544YVmTpeIiIhMiZkQQrT0IB40vb5OtudXGyPn88Ytjb0zHntnHPbNeHLuHa+RecyukSEiIiJ6nDHIEBERkWwxyBAREZFsMcgQERGRbDHIEBERkWwxyBAREZFsMcgQERGRbDHIEBERkWwxyBAREZFsMcgQERGRbDHIEBERkWwxyBAREZFsMcgQERGRbDHIEBERkWwxyBAREZFsMcgQERGRbDHIEBERkWwxyBAREZFsMcgQERGRbDHIEBERkWwxyBAREZFs3VeQycvLw+uvvw61Wo1BgwZh48aNUm3+/Pno2bOnwW3Tpk1SPT09HSNHjoRSqURoaCjy8/MN9r1161YEBARArVYjIiICVVVVUk2n02H+/Pnw9vaGv78/NmzY0MzpEhERkSm5Z5DR6/WYMmUK/vSnP2HPnj1YsGAB4uPj8dVXXwEAcnNzMWfOHBw7dky6vfzyywCA4uJizJgxA6NGjcLOnTvh6OiImTNnor6+HgCQlpaGlStXIioqClu2bIFGo0FcXJz02EuXLkVmZiaSk5MRExODhIQE7N+//2H0gYiIiGTonkGmtLQUffr0QVRUFDp37oxBgwahf//+OHHiBADgl19+gYeHB5ycnKSbnZ0dACAlJQW9evXClClT0L17dyxZsgTFxcVIT08HAGzevBkhISEYMmQIPD09ER0djd27d+P69euoqqpCSkoK5s2bBw8PDwQGBmLy5MnYtm3bQ2wHERERyck9g0zHjh2xcuVK2NraQgiBjIwMnDhxAn5+ftBqtSgvL8czzzzT4LbZ2dnw9vaW7tvZ2cHd3R2ZmZmoq6uDRqMxqKtUKtTV1eHcuXPIycmBTqeDl5eXVPfy8oJGo0FtbW1z5kxEREQmokkX+wYEBGDChAlQq9V4/vnnkZubC0tLS6xatQoDBw7EqFGjsGvXLml9rVYLZ2dng320b98epaWlqKioQE1NjUHd0tISCoUCJSUl0Gq1cHBwgI2NjVR3dHSEXq/H5cuXjZ0vERERmRDLpqwcHx+PS5cuITo6GrGxsdKRmF69eiE0NBTHjx/HggULYGdnh+HDh6O6uhrW1tYG+7C2toZOp8ONGzek+w3Va2trG6wBNy8CboyFhRkUilZNmZosWFiYm+S8HgX2znjsnXHYN+Oxd/LVEs9bk4KMp6cnAODGjRuYO3cuTp06haCgICgUCgA3A01+fj527NiB4cOHw8bG5o7QodPpoFAopCMtDdVtbW1hZmbWYA2AdA3O3dTVCZSXVzW6jhwpFK1Mcl6PAntnPPbOOOyb8eTcOyenNi09hBb1sJ63xvp6Xxf7Hjp0yGBZt27doNfrUVlZKYWYW7p27YrS0lIAgIuLC7RarUG9rKwMTk5OUpgpKyuTarW1tSgvL4ezszNcXFxQUVFhEGa0Wi2sra3h4OBwr2ETERHRH8A9g0xeXh7eeust/Pbbb9KyM2fOoF27dkhMTMS0adMM1j937hy6du0KAFAqlTh16pRUq66uxtmzZ6FSqWBubg5PT09kZGRI9aysLFhYWMDNzQ1ubm6wsrJCZmamVM/IyIC7uzssLZt0IImIiIhM1D2DjLe3N7p164bw8HDk5eXh3//+Nz755BNMnz4dgwcPxtGjR7FlyxYUFBRg+/bt2LNnDyZNmgQACA4ORnZ2NhISEpCbm4vIyEh06NABfn5+AIAJEyYgKSkJaWlp0Gg0iImJQXBwMOzt7WFnZ4fRo0cjJiYGp0+fxqFDh5CUlISJEyc+3I4QERGRbJgJIcS9Vvrvf/+LhQsX4vjx47C3t0dISAimTp0KMzMzHDhwAPHx8cjPz8fTTz+Nd955B8OGDZO2PXLkCGJjY1FcXAylUonFixejU6dOUj0xMRGbNm2CTqfD0KFDERUVBVtbWwA3j+BER0cjLS0N9vb2CAsLQ1hY2D0npdfXyfb8amPkfN64pbF3xmPvjMO+GU/OvXNyaoMu4X/ML269GBcErfbaQ9l3Y9fI3FeQkRsGGfo99s547J1x2Dfjybl3DDKPPsjwRyOJiIhIthhkiIiISLYYZIiIiEi2GGSIiIhIthhkiIiISLYYZIiIiEi2GGSIiIhIthhkiIiISLYYZIiIiEi2GGSIiIhIthhkiIiISLYYZIiIiEi2GGSIiIhIthhkiIiISLYYZIiIiEi2GGSIiIhIthhkiIiISLYYZIiIiEi2GGSIiIhIthhkiIiISLbuK8jk5eXh9ddfh1qtxqBBg7Bx40apVlRUhLCwMKhUKgwfPhxHjhwx2DY9PR0jR46EUqlEaGgo8vPzDepbt25FQEAA1Go1IiIiUFVVJdV0Oh3mz58Pb29v+Pv7Y8OGDc2ZKxEREZmYewYZvV6PKVOm4E9/+hP27NmDBQsWID4+Hl999RWEEJg5cyYUCgVSU1MxZswYzJo1C4WFhQCA4uJizJgxA6NGjcLOnTvh6OiImTNnor6+HgCQlpaGlStXIioqClu2bIFGo0FcXJz02EuXLkVmZiaSk5MRExODhIQE7N+//yG1goiIiOTmnkGmtLQUffr0QVRUFDp37oxBgwahf//+OHHiBNLT03HhwgUsXLgQ3bt3x9SpU6FWq5GamgoASElJQa9evTBlyhR0794dS5YsQXFxMdLT0wEAmzdvRkhICIYMGQJPT09ER0dj9+7duH79OqqqqpCSkoJ58+bBw8MDgYGBmDx5MrZt2/ZwO0JERESycc8g07FjR6xcuRK2trYQQiAjIwMnTpyAn58fsrOz0bt3b7Ru3Vpa38vLC1lZWQCA7OxseHt7SzU7Ozu4u7sjMzMTdXV10Gg0BnWVSoW6ujqcO3cOOTk50Ol08PLyMti3RqNBbW3tg5g7ERERyVyTLvYNCAjAhAkToFar8fzzz0Or1cLZ2dlgnfbt26OkpAQA7lovLS1FRUUFampqDOqWlpZQKBQoKSmBVquFg4MDbGxspLqjoyP0ej0uX77c5IkSERGR6bFsysrx8fG4dOkSoqOjERsbi+rqalhZWRmsY21tDb1eDwCorq6GtbX1HXWdTocbN25I9xuq19bWNlgDbl4E3BgLCzMoFK2aMjVZsLAwN8l5PQrsnfHYO+Owb8Zj7+SrJZ63JgUZT09PAMCNGzcwd+5cBAcHo7Ky0mAdnU4HW1tbAICNjc0doUOn00GhUEhHWhqq29rawszMrMEacPMUVWPq6gTKy6saXUeOFIpWJjmvR4G9Mx57Zxz2zXhy7p2TU5uWHkKLeljPW2N9va+LfQ8dOmSwrFu3btDr9XBycoJWqzWolZWVwcnJCQDg4uJy1/qtMFNWVibVamtrUV5eDmdnZ7i4uKCiosIgzGi1WlhbW8PBweFewyYiIqI/gHsGmby8PLz11lv47bffpGVnzpxBu3bt4OXlhZycHIPvfsnIyIBKpQIAKJVKnDp1SqpVV1fj7NmzUKlUMDc3h6enJzIyMqR6VlYWLCws4ObmBjc3N1hZWSEzM9Ng3+7u7rC0bNKBJCIiIjJR9wwy3t7e6NatG8LDw5GXl4d///vf+OSTTzB9+nT4+PigQ4cOCA8Px/nz55GYmIjs7GyMGzcOABAcHIzs7GwkJCQgNzcXkZGR6NChA/z8/AAAEyZMQFJSEtLS0qDRaBATE4Pg4GDY29vDzs4Oo0ePRkxMDE6fPo1Dhw4hKSkJEydOfLgdISIiItkwE0KIe6303//+FwsXLsTx48dhb2+PkJAQTJ06FWZmZsjPz0dkZCSys7PRqVMnREREYMCAAdK2R44cQWxsLIqLi6FUKrF48WJ06tRJqicmJmLTpk3Q6XQYOnQooqKipGtsqqurER0djbS0NNjb2yMsLAxhYWH3nJReXyfb86uNkfN545bG3hmPvTMO+2Y8OffOyakNuoT/Mb+49WJcELTaaw9l341dI3NfQUZuGGTo99g747F3xmHfjCfn3jHIPPogwx+NJCIiItlikCEiIiLZYpAhIiIi2WKQISIiItlikCEiIiLZYpAhIiIi2WKQISIiItlikCEiIiLZYpAhIiIi2WKQISIiItlikCEiIiLZYpAhIiIi2WKQISIiItlikCEiIiLZYpAhIiIi2WKQISIiItlikCEiIiLZYpAhIiIi2WKQISIiItlikCEiIiLZYpAhIiIi2bqvIFNQUIDp06fD29sbAQEBiIuLQ01NDQBg/vz56Nmzp8Ft06ZN0rbp6ekYOXIklEolQkNDkZ+fb7DvrVu3IiAgAGq1GhEREaiqqpJqOp0O8+fPh7e3N/z9/bFhw4YHMGUiIiIyFfcMMjqdDtOnT4e1tTU+//xzLFu2DP/617+wYsUKAEBubi7mzJmDY8eOSbeXX34ZAFBcXIwZM2Zg1KhR2LlzJxwdHTFz5kzU19cDANLS0rBy5UpERUVhy5Yt0Gg0iIuLkx576dKlyMzMRHJyMmJiYpCQkID9+/c/jD4QERGRDN0zyJw+fRoFBQWIjY1Ft27d4OPjg7fffht79+4FAPzyyy/w8PCAk5OTdLOzswMApKSkoFevXpgyZQq6d++OJUuWoLi4GOnp6QCAzZs3IyQkBEOGDIGnpyeio6Oxe/duXL9+HVVVVUhJScG8efPg4eGBwMBATJ48Gdu2bXuI7SAiIiI5uWeQ6dq1KxITE2Fvby8tMzMzg06ng1arRXl5OZ555pkGt83Ozoa3t7d0387ODu7u7sjMzERdXR00Go1BXaVSoa6uDufOnUNOTg50Oh28vLykupeXFzQaDWpra42aLBEREZmWewaZdu3aoX///tL9+vp6bNu2DV5eXsjNzYWlpSVWrVqFgQMHYtSoUdi1a5e0rlarhbOzs8H+2rdvj9LSUlRUVKCmpsagbmlpCYVCgZKSEmi1Wjg4OMDGxkaqOzo6Qq/X4/Lly82aNBEREZkGy6ZuEBsbi3PnziE1NRXHjx8HAPTq1QuhoaE4fvw4FixYADs7OwwfPhzV1dWwtrY22N7a2ho6nQ43btyQ7jdUr62tbbAG3LxupzEWFmZQKFo1dWqPPQsLc5Oc16PA3hmPvTMO+2Y89k6+WuJ5u+8gI4TAhx9+iB07dmDVqlXo0aMHunfvjqCgICgUCgA3A01+fj527NiB4cOHw8bG5o7QodPpoFAopCMtDdVtbW2l01e/rwGQrsG5m7o6gfLyqkbXkSOFopVJzutRYO+Mx94Zh30znpx75+TUpqWH0KIe1vPWWF/v6+PX9fX1mDdvHj7//HOsWLECgYGBAG5eK3MrxNzStWtXlJaWAgBcXFyg1WoN6mVlZXBycpLCTFlZmVSrra1FeXk5nJ2d4eLigoqKCoMwo9VqYW1tDQcHh/sZNhEREZm4+woycXFx2Lt3L1avXo1hw4YZLJ82bZrBuufOnUPXrl0BAEqlEqdOnZJq1dXVOHv2LFQqFczNzeHp6YmMjAypnpWVBQsLC7i5ucHNzQ1WVlbIzMyU6hkZGXB3d4elZZPPiBEREZEJumeQycrKwubNmzFr1ix4eHhAq9VKt8GDB+Po0aPYsmULCgoKsH37duzZsweTJk0CAAQHByM7OxsJCQnIzc1FZGQkOnToAD8/PwDAhAkTkJSUhLS0NGg0GsTExCA4OBj29vaws7PD6NGjERMTg9OnT+PQoUNISkrCxIkTH25HiIiISDbMhBCisRU++ugjJCUlNVg7c+YM0tLSEB8fj/z8fDz99NN45513DI7aHDlyBLGxsSguLoZSqcTixYvRqVMnqZ6YmIhNmzZBp9Nh6NChiIqKgq2tLYCbR3Cio6ORlpYGe3t7hIWFISws7J6T0uvrZHt+tTFyPm/c0tg747F3xmHfjCfn3jk5tUGX8D/mF7dejAuCVnvtoey7sWtk7hlk5IhBhn6PvTMee2cc9s14cu4dg8yjDzL80UgiIiKSLQYZIiIiki0GGSIiIpItBhkiIiKSLQYZIiIiki0GGSIiIpItBhkiIiKSLQYZIiIiki0GGSIiIpItBhkiIiKSLQYZIiIiki0GGSIiIpItBhkiIiKSLQYZIiIiki0GGSIiIpItBhkiIiKSLQYZIiIiki0GGSIiIpItBhkiIiKSLQYZIiIikq37CjIFBQWYPn06vL29ERAQgLi4ONTU1AAAioqKEBYWBpVKheHDh+PIkSMG26anp2PkyJFQKpUIDQ1Ffn6+QX3r1q0ICAiAWq1GREQEqqqqpJpOp8P8+fPh7e0Nf39/bNiwobnzJSIiIhNyzyCj0+kwffp0WFtb4/PPP8eyZcvwr3/9CytWrIAQAjNnzoRCoUBqairGjBmDWbNmobCwEABQXFyMGTNmYNSoUdi5cyccHR0xc+ZM1NfXAwDS0tKwcuVKREVFYcuWLdBoNIiLi5Mee+nSpcjMzERycjJiYmKQkJCA/fv3P6RWEBERkdzcM8icPn0aBQUFiI2NRbdu3eDj44O3334be/fuRXp6Oi5cuICFCxeie/fumDp1KtRqNVJTUwEAKSkp6NWrF6ZMmYLu3bt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\n",
      "text/plain": [
       "<Figure size 648x360 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Displayed below all sum of the death cases across all age groups.\n",
    "total_death_cases = total_cases_to_age(states_death_cases_age_frame)\n",
    "plt.bar(num_of_age_group, total_death_cases)\n",
    "plt.title(\"Total Death Cases to Age Group\")\n",
    "plt.xlabel(\"Age Group\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "id": "after-planet",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 648x360 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Displayed below all sum of the recovered cases across all age groups.\n",
    "total_recovered_cases = total_cases_to_age(states_recovered_cases_age_frame)\n",
    "plt.bar(num_of_age_group, total_recovered_cases)\n",
    "plt.title(\"Total Recovered Cases to Age Group\")\n",
    "plt.xlabel(\"Age Group\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "id": "moderate-seeker",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 648x360 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Creating a list to hold the sum of all the cases.\n",
    "all_cases_compared = [sum(total_cases), sum(total_recovered_cases), \n",
    "                      sum(total_cases) - (sum(total_recovered_cases) + sum(total_death_cases)),\n",
    "                      sum(total_death_cases)]\n",
    "# Displayed below a comparison between all the cases.\n",
    "labels = [\"Confirmed Cases\", \"Recovered Cases\", \"Active Cases\", \"Death Cases\", ]\n",
    "plt.bar(labels, all_cases_compared)\n",
    "# Assigning yticks to make the chart much more readable.\n",
    "plt.yticks((0 , 200000, 400000, 600000, 800000, 1000000, 1200000, 1400000, 1600000, 1800000, 2000000, 2200000, 2400000),\n",
    "           (\"0\", \"200k\", \"400k\", \"600k\",\"800k\", \"1m\", \"1.2m\", \"1.4m\", \"1.6m\", \"1.8m\", \"2m\", \"2.2m\", \"2.4m\"))\n",
    "# Another way of modifying the yticks.\n",
    "# plt.yticks(np.arange(0, 3000000, step=200000))\n",
    "plt.title(\"All Cases Comparison\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "controlled-equation",
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.8.5"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}