Final_Project.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "4b7be680",
   "metadata": {},
   "source": [
    "# Analysis of COVID-19 Data from Brazil"
   ]
  },
  {
   "attachments": {
    "brazilian-flag-graphic.png": {
     "image/png": 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"
    }
   },
   "cell_type": "markdown",
   "id": "58c57e0a",
   "metadata": {},
   "source": [
    "![brazilian-flag-graphic.png](attachment:brazilian-flag-graphic.png)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "dbd7dbe2",
   "metadata": {},
   "source": [
    "COVID-19 Background: Coronavirus disease (COVID-19) is an infectious disease caused by the SARS-CoV-2 virus.Most people infected with the virus will experience mild to moderate respiratory illness and recover without requiring special treatment. However, some will become seriously ill and require medical attention. Older people and those with underlying medical conditions like cardiovascular disease, diabetes, chronic respiratory disease, or cancer are more likely to develop serious illness. Anyone can get sick with COVID-19 and become seriously ill or die at any age. \n",
    "\n",
    "Data Source:[World Heath Organization](https://www.who.int/health-topics/coronavirus#tab=tab_1)\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "1db39c96",
   "metadata": {},
   "source": [
    "# Import Data from S3 Bucket"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "e40559e8",
   "metadata": {},
   "outputs": [],
   "source": [
    "%matplotlib inline\n",
    "import pandas as pd"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "id": "44ade7d1",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Looking in indexes: https://pypi.org/simple, https://pip.repos.neuron.amazonaws.com\n",
      "Collecting xlrd\n",
      "  Downloading xlrd-2.0.1-py2.py3-none-any.whl (96 kB)\n",
      "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m96.5/96.5 kB\u001b[0m \u001b[31m1.2 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0mta \u001b[36m0:00:01\u001b[0m\n",
      "\u001b[?25hInstalling collected packages: xlrd\n",
      "Successfully installed xlrd-2.0.1\n"
     ]
    }
   ],
   "source": [
    "!pip install xlrd"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "id": "1d11580f",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>dateRep</th>\n",
       "      <th>day</th>\n",
       "      <th>month</th>\n",
       "      <th>year</th>\n",
       "      <th>cases</th>\n",
       "      <th>deaths</th>\n",
       "      <th>countriesAndTerritories</th>\n",
       "      <th>geoId</th>\n",
       "      <th>countryterritoryCode</th>\n",
       "      <th>popData2019</th>\n",
       "      <th>continentExp</th>\n",
       "      <th>Cumulative_number_for_14_days_of_COVID-19_cases_per_100000</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>14/12/2020</td>\n",
       "      <td>14</td>\n",
       "      <td>12</td>\n",
       "      <td>2020</td>\n",
       "      <td>746</td>\n",
       "      <td>6</td>\n",
       "      <td>Afghanistan</td>\n",
       "      <td>AF</td>\n",
       "      <td>AFG</td>\n",
       "      <td>38041757.0</td>\n",
       "      <td>Asia</td>\n",
       "      <td>9.013779</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>13/12/2020</td>\n",
       "      <td>13</td>\n",
       "      <td>12</td>\n",
       "      <td>2020</td>\n",
       "      <td>298</td>\n",
       "      <td>9</td>\n",
       "      <td>Afghanistan</td>\n",
       "      <td>AF</td>\n",
       "      <td>AFG</td>\n",
       "      <td>38041757.0</td>\n",
       "      <td>Asia</td>\n",
       "      <td>7.052776</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2020-12-12 00:00:00</td>\n",
       "      <td>12</td>\n",
       "      <td>12</td>\n",
       "      <td>2020</td>\n",
       "      <td>113</td>\n",
       "      <td>11</td>\n",
       "      <td>Afghanistan</td>\n",
       "      <td>AF</td>\n",
       "      <td>AFG</td>\n",
       "      <td>38041757.0</td>\n",
       "      <td>Asia</td>\n",
       "      <td>6.868768</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2020-11-12 00:00:00</td>\n",
       "      <td>11</td>\n",
       "      <td>12</td>\n",
       "      <td>2020</td>\n",
       "      <td>63</td>\n",
       "      <td>10</td>\n",
       "      <td>Afghanistan</td>\n",
       "      <td>AF</td>\n",
       "      <td>AFG</td>\n",
       "      <td>38041757.0</td>\n",
       "      <td>Asia</td>\n",
       "      <td>7.134266</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2020-10-12 00:00:00</td>\n",
       "      <td>10</td>\n",
       "      <td>12</td>\n",
       "      <td>2020</td>\n",
       "      <td>202</td>\n",
       "      <td>16</td>\n",
       "      <td>Afghanistan</td>\n",
       "      <td>AF</td>\n",
       "      <td>AFG</td>\n",
       "      <td>38041757.0</td>\n",
       "      <td>Asia</td>\n",
       "      <td>6.968658</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "               dateRep  day  month  year  cases  deaths  \\\n",
       "0           14/12/2020   14     12  2020    746       6   \n",
       "1           13/12/2020   13     12  2020    298       9   \n",
       "2  2020-12-12 00:00:00   12     12  2020    113      11   \n",
       "3  2020-11-12 00:00:00   11     12  2020     63      10   \n",
       "4  2020-10-12 00:00:00   10     12  2020    202      16   \n",
       "\n",
       "  countriesAndTerritories geoId countryterritoryCode  popData2019  \\\n",
       "0             Afghanistan    AF                  AFG   38041757.0   \n",
       "1             Afghanistan    AF                  AFG   38041757.0   \n",
       "2             Afghanistan    AF                  AFG   38041757.0   \n",
       "3             Afghanistan    AF                  AFG   38041757.0   \n",
       "4             Afghanistan    AF                  AFG   38041757.0   \n",
       "\n",
       "  continentExp  Cumulative_number_for_14_days_of_COVID-19_cases_per_100000  \n",
       "0         Asia                                           9.013779           \n",
       "1         Asia                                           7.052776           \n",
       "2         Asia                                           6.868768           \n",
       "3         Asia                                           7.134266           \n",
       "4         Asia                                           6.968658           "
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df = pandas.read_excel('s3://patterson-241-2023-python/covid_data (2).xls')\n",
    "df.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "cb6bd4bb",
   "metadata": {},
   "source": [
    "# Brazil Data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "id": "11b419de",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>dateRep</th>\n",
       "      <th>day</th>\n",
       "      <th>month</th>\n",
       "      <th>year</th>\n",
       "      <th>cases</th>\n",
       "      <th>deaths</th>\n",
       "      <th>countriesAndTerritories</th>\n",
       "      <th>geoId</th>\n",
       "      <th>countryterritoryCode</th>\n",
       "      <th>popData2019</th>\n",
       "      <th>continentExp</th>\n",
       "      <th>Cumulative_number_for_14_days_of_COVID-19_cases_per_100000</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>7991</th>\n",
       "      <td>14/12/2020</td>\n",
       "      <td>14</td>\n",
       "      <td>12</td>\n",
       "      <td>2020</td>\n",
       "      <td>21825</td>\n",
       "      <td>279</td>\n",
       "      <td>Brazil</td>\n",
       "      <td>BR</td>\n",
       "      <td>BRA</td>\n",
       "      <td>211049519.0</td>\n",
       "      <td>America</td>\n",
       "      <td>278.234228</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7992</th>\n",
       "      <td>13/12/2020</td>\n",
       "      <td>13</td>\n",
       "      <td>12</td>\n",
       "      <td>2020</td>\n",
       "      <td>43900</td>\n",
       "      <td>686</td>\n",
       "      <td>Brazil</td>\n",
       "      <td>BR</td>\n",
       "      <td>BRA</td>\n",
       "      <td>211049519.0</td>\n",
       "      <td>America</td>\n",
       "      <td>279.486541</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7993</th>\n",
       "      <td>2020-12-12 00:00:00</td>\n",
       "      <td>12</td>\n",
       "      <td>12</td>\n",
       "      <td>2020</td>\n",
       "      <td>54428</td>\n",
       "      <td>672</td>\n",
       "      <td>Brazil</td>\n",
       "      <td>BR</td>\n",
       "      <td>BRA</td>\n",
       "      <td>211049519.0</td>\n",
       "      <td>America</td>\n",
       "      <td>283.287544</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7994</th>\n",
       "      <td>2020-11-12 00:00:00</td>\n",
       "      <td>11</td>\n",
       "      <td>12</td>\n",
       "      <td>2020</td>\n",
       "      <td>53347</td>\n",
       "      <td>770</td>\n",
       "      <td>Brazil</td>\n",
       "      <td>BR</td>\n",
       "      <td>BRA</td>\n",
       "      <td>211049519.0</td>\n",
       "      <td>America</td>\n",
       "      <td>273.669896</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7995</th>\n",
       "      <td>2020-10-12 00:00:00</td>\n",
       "      <td>10</td>\n",
       "      <td>12</td>\n",
       "      <td>2020</td>\n",
       "      <td>53453</td>\n",
       "      <td>836</td>\n",
       "      <td>Brazil</td>\n",
       "      <td>BR</td>\n",
       "      <td>BRA</td>\n",
       "      <td>211049519.0</td>\n",
       "      <td>America</td>\n",
       "      <td>266.215248</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                  dateRep  day  month  year  cases  deaths  \\\n",
       "7991           14/12/2020   14     12  2020  21825     279   \n",
       "7992           13/12/2020   13     12  2020  43900     686   \n",
       "7993  2020-12-12 00:00:00   12     12  2020  54428     672   \n",
       "7994  2020-11-12 00:00:00   11     12  2020  53347     770   \n",
       "7995  2020-10-12 00:00:00   10     12  2020  53453     836   \n",
       "\n",
       "     countriesAndTerritories geoId countryterritoryCode  popData2019  \\\n",
       "7991                  Brazil    BR                  BRA  211049519.0   \n",
       "7992                  Brazil    BR                  BRA  211049519.0   \n",
       "7993                  Brazil    BR                  BRA  211049519.0   \n",
       "7994                  Brazil    BR                  BRA  211049519.0   \n",
       "7995                  Brazil    BR                  BRA  211049519.0   \n",
       "\n",
       "     continentExp  Cumulative_number_for_14_days_of_COVID-19_cases_per_100000  \n",
       "7991      America                                         278.234228           \n",
       "7992      America                                         279.486541           \n",
       "7993      America                                         283.287544           \n",
       "7994      America                                         273.669896           \n",
       "7995      America                                         266.215248           "
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "Brazil_data = df.loc[df['countriesAndTerritories'] == 'Brazil']\n",
    "Brazil_data.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "34ef8f0d",
   "metadata": {},
   "source": [
    "# Question 1: How many cases of COVID-19 total were in Brazil?"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "id": "4da2d7e8",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/tmp/ipykernel_7326/1378579182.py:1: FutureWarning: The default value of numeric_only in DataFrame.sum is deprecated. In a future version, it will default to False. In addition, specifying 'numeric_only=None' is deprecated. Select only valid columns or specify the value of numeric_only to silence this warning.\n",
      "  Brazil_data.sum()['cases']\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "6901952"
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "Brazil_data.sum()['cases']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "id": "4735cfc3",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot: xlabel='countriesAndTerritories'>"
      ]
     },
     "execution_count": 27,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sum_death_by_country = df.groupby('countriesAndTerritories')['deaths'].sum()\n",
    "sum_death_by_country.nlargest(10).plot.bar()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "9ebacda4",
   "metadata": {},
   "source": [
    "Brazil had a total of 6,901,952 COVID-19 cases in the year of 2020. This bar graph was added to show a comparison of Brazils total COVID-19 cases in comparison to other countries with high COVID-19 numbers as well.  Brazil had the second highest amount of cases following the United States in 2020. "
   ]
  },
  {
   "cell_type": "markdown",
   "id": "e2230829",
   "metadata": {},
   "source": [
    "# Question 2: What month was the COVID- 19 data the highest in Brazil?"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "id": "0f0ccd87",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/tmp/ipykernel_7326/1862868881.py:1: FutureWarning: The default value of numeric_only in DataFrameGroupBy.sum is deprecated. In a future version, numeric_only will default to False. Either specify numeric_only or select only columns which should be valid for the function.\n",
      "  sum_cases_per_day = Brazil_data.groupby('month').sum()['cases']\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "<AxesSubplot: xlabel='month'>"
      ]
     },
     "execution_count": 32,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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qa5syMBIuKgUy8y5zRDzJAssIEQnxRWYBas0S4jtpEddJKzqOQwn0dsPY3nUj4j/J4NERsn8sI0TU7swWCWt211+4yqMibaJhme8Ph4uRV1YpOA3RjbGMEFG7Sz9xEecuX4W3mxpjeoWKjuOQugV5YehtARwRT7LAMkJE7a7hwtWHEnVwd1UJTuO4fl8/Iv6LzAJcrqwRnIbo+lhGiKhdnbtchS3HSwAAjwwIF5zGsSV39kPPUG9U11qsBZDIHrGMEFG7WrsnH5IEDOzsh84BHUTHcWgKhQK/r7925F87z3JEPNktlhEiajc1JgvW7S0AADzGC1fbxai4EIT5uKO0osZ6DyAie8MyQkTt5sfDxSitqEGglwbDewSJjuMUXFRKTB0UCQD4OOMMR8STXbK5jKSnp2PMmDEIDQ2FQqHAhg0bbvqcrVu3IjExEW5uboiOjsaHH37YkqxEJHMN1y1M7BcOFxX/LdReJvYLh5ebGqcvVuK/9dfrENkTmz8NKisrER8fj0WLFjVr/9zcXIwaNQpDhgxBdnY2/vznP2PWrFn46quvbA5LRPJ18kI5dudegkqpwMP9dKLjOJUOGjUm9a+7WJgj4skeqW19wsiRIzFy5Mhm7//hhx8iPDwc77//PgAgJiYGmZmZePfdd/Hggw/a+u2JSKZW1w85u6t7IEK07oLTOJ+pA6OwLCMXu3MvYX/BFcTrfERHIrJq8+OkO3fuREpKSqNtd999NzIzM1FbW9vW356I7ECl0YSvss4B4H1oRAnWuuG+3nUD5j7miHiyM21eRoqLixEU1PhCtaCgIJhMJpSWljb5HKPRCIPB0OhBRPL13f5ClBtNiPDzwOAu/qLjOK0n64egpR4sQsGlKsFpiH7RLleQKRSKRl9LktTk9gYLFiyAVqu1PnQ6nl8mkitJkqwXrj7SPxxKZdN/76ntxYR4Y0hXf1gkYPl2jogn+9HmZSQ4OBjFxcWNtpWUlECtVsPPz6/J58ydOxd6vd76KCgoaOuYRNRGcgqu4HChAa5qJcYl8h8WojUMQVu3twD6Kp4qJ/vQ5mUkOTkZaWlpjbZt3rwZSUlJcHFxafI5Go0G3t7ejR5EJE+f7aq7cPXeuBB09HQVnIYGd/FH92AvVNWYsXoPR8STfbC5jFRUVCAnJwc5OTkA6pbu5uTkID+/7gNn7ty5mDx5snX/GTNmIC8vD3PmzMHRo0exfPlyLFu2DC+88ELr/AREZLeuVNVg04FCAMAjvHDVLvx6RPzK7WdhNHFEPIlncxnJzMxEQkICEhISAABz5sxBQkICXn31VQBAUVGRtZgAQFRUFFJTU/Hzzz+jd+/e+N///V988MEHXNZL5AS+zDoHo8mCmBBv9An3ER2H6t3bKxTB3m4oKTfiu5xC0XGIoJAaria1YwaDAVqtFnq9nqdsiGTCYpFw13tbkVtaifn3x1mHbpF9+GjraSz4/hi6BXXAj7Nvv+6CAqJb0dzf35zHTERtYsfpMuSWVqKDRo3f1c+3IPvxcP9wdNCoceJCBbaeuCg6Djk5lhEiahMNy3kf6BMGT43Nw56pjXm7uWBi37rVTRyCRqKxjBBRqyvWVyPt6AUAnLhqz6YOjoJKqcD2U2U4dF4vOg45MZYRImp1n+/Nh9kioV+kL7oFeYmOQ9cR5uOOMb1CAACf8OgICcQyQkStqtZswdo9dSvqHhnAi1bt3RP1I+I3HihC4ZWrgtOQs2IZIaJW9dPRC7hgMMLP0xX3xAaLjkM3ERumxaAufjBbJKzgiHgShGWEiFpVw8TV8X110KhVgtNQczTcQG/tngIYqjkintofywgRtZrc0kpsO1UKhQKY1I+naOTijm4BuC3ICxVGE9buzr/5E4haGcsIEbWa1fXLeYd2C4DO10NwGmouhUKBJ4ZEAQBWbD+LGpNFcCJyNiwjRNQqqmvNWJ91DgCX88rRfb1DEeilQbGh2no/IaL2wjJCRK1i04Ei6K/WIszHHUNvCxQdh2ykUaswZVAkAGBp+hnI4E4h5EBYRoioVTRMXJ3UPxwqJe9zIkeP9IuAh6sKx4rLse1Uqeg45ERYRojolh06r0dOwRW4qBSYUD9inORH6+Fi/d9vaTqHoFH7YRkholu2enfdUZF7YkPg30EjOA3dimmDoqBUABknS3G0yCA6DjkJlhEiuiWG6lpsyK674PHR/lzOK3c6Xw+MiqsbEc8b6FF7YRkholvyddY5XK01o1tQB/SL8hUdh1rB72+vG4L2XU4hznNEPLUDlhEiajFJkvBZ/ZCsR/pHQKHghauOoFcnHwyI9oXJIuEPn2WhqsYkOhI5OJYRImqx3bmXcKqkAu4uKtzfJ0x0HGpFbz3QC76erjhwTo9Za3NgtnCpL7UdlhEiarGG5bxjE0Lh7eYiOA21pkh/T3w8OQmuaiX+c/QC/nfTEdGRyIGxjBBRi1wsN+LHw8UA6k7RkONJjOiI9yf0BgCs3HEWy7bxrr7UNlhGiKhFvsgsQK1ZQm+dD2LDtKLjUBsZFReCP4/qDgB4899H8MOhYsGJyBGxjBCRzcwWCWvqL1zlfWgc35NDovHogHBIEjB7XTay8y+LjkQOhmWEiGz28/ESnL9yFVp3F9zbK0R0HGpjCoUCr4/piWG3BaC61oIn/pWJ/LIq0bHIgbCMEJHNGi5cHZ/UCW4uKsFpqD2oVUosmtQHPUO9UVZZgykr9+BKVY3oWOQgWEaIyCYFl6rw84mLAIBJvHDVqXhq1Fg+pS9CtG44c7EST32aBaPJLDoWOQCWESKyyZo9+ZAkYEhXf0T5e4qOQ+0syNsNK6b2hZdGjd25l/DilwcgSZxBQreGZYSIms1oMuOLvQUAuJzXmXUP9saSRxOhViqwIacQ/5d2QnQkkjmWESJqth8OFaOssgbB3m4YHhMoOg4JNLirP+bfHwcA+GDLKWtJJWoJlhEiarYvMut+4Uzsp4NaxY8PZze+rw7P3tkFAPDnbw4i4+RFwYlIrvhpQkTNcrHciJ2nywAADyR0EpyG7MWcEd3wu96hMFkkPP3ZPhwrNoiORDLEMkJEzfL9oSJYJCC+kxbhfh6i45CdUCgUeOehXugX5YtyownTVuzFBUO16FgkMywjRNQsm/YXAQDu7RUqOAnZG41ahaWPJSI6wBOF+mpMW7kXlUaT6FgkIywjRHRTxfpq7M27BAAYzYmr1AQfD1esnNIPfp6uOFxowLNrs2EyW0THIplgGSGim/r3wSJIUt1dXEN93EXHITsV7ueBTx5PgkatxJZjJXh942HOIKFmYRkhopvadKAQAHgfGrqphPCO+PvEBCgUwGe78vFJRq7oSCQDLCNEdEPnLlchO/8KFIq628kT3cw9scF4ZXQPAMBfU48i9WCR4ERk71hGiOiG/n2g7hdJv0hfBHm7CU5DcjFtUCSmDIwEAMxel4Os+muOiJrCMkJEN7SpvozcG89VNNR8CoUCf7m3B4bHBKLGZMGTq7JwtrRSdCyyUywjRHRdZ0srcfC8HkoFMDI2WHQckhmVUoEPHk5AXJgWlyprMHXlXlyurBEdi+wQywgRXde/68/1D+zsD/8OGsFpSI48XNVYNiUJYT7uyC2txO8/zUR1rVl0LLIzLCNEdF0b93MVDd26QC83rJjaF15uauw9exl//PIALBYu+aVfsIwQUZNOlVTgWHE51EoF7uEpGrpF3YK88NGjiVArFdi4vxDvbj4uOhLZEZYRImpSw2yRwV394ePhKjgNOYKBXfzx1oO9AACLfz6NtXvyBScie9GiMrJ48WJERUXBzc0NiYmJyMjIuOH+q1evRnx8PDw8PBASEoKpU6eirKysRYGJqO1JkvTLKhrei4Za0UOJnTB7eFcAwCsbDmHriYuCE5E9sLmMrFu3DrNnz8bLL7+M7OxsDBkyBCNHjkR+ftMNd9u2bZg8eTKmT5+Ow4cPY/369di7dy+eeOKJWw5PRG3j+IVynCqpgKtKiZSeQaLjkIN57q6ueKBPGMwWCU9/loUjhQbRkUgwm8vIe++9h+nTp+OJJ55ATEwM3n//feh0OixZsqTJ/Xft2oXIyEjMmjULUVFRGDx4MJ566ilkZmbecngiahsNd+i947YAeLu5CE5DjkahUOCtB3ohOdoPlTVmTFu5F0X6q6JjkUA2lZGamhpkZWUhJSWl0faUlBTs2LGjyecMHDgQ586dQ2pqKiRJwoULF/Dll19i9OjR1/0+RqMRBoOh0YOI2kfdKRquoqG25apW4sPHEtE1sAOKDdWYumIvyqtrRcdqdfqqWpy8UC46ht2zqYyUlpbCbDYjKKjxYdugoCAUFxc3+ZyBAwdi9erVmDBhAlxdXREcHAwfHx/84x//uO73WbBgAbRarfWh0+lsiUlEt+BwoQFny6rg5qLE8BieoqG2o3V3wfIpfeHfQYNjxeWYuSYbtWaL6Fi3zGKRsP1UKZ77PBt95/8HI/4vHZ/zYt0batEFrAqFotHXkiRds63BkSNHMGvWLLz66qvIysrCDz/8gNzcXMyYMeO6rz937lzo9Xrro6CgoCUxiagFNtYfFbmzeyA8NWrBacjR6Xw9sHxKEtxdVEg/cRGvfnsIkiTPGSSFV67ig59O4o53/4tHPtmNb3MKUWOqK1evbzzMIyQ3YNMnjb+/P1Qq1TVHQUpKSq45WtJgwYIFGDRoEP74xz8CAHr16gVPT08MGTIEb775JkJCrj0MrNFooNFw2iNRe5MkyXpjPK6iofbSq5MPPng4Ab//NBNr9xQg3NcTfxjaWXSsZjGazPjPkRKsyyxAxsmLaOhRXho17usdivFJOry7+TgyTpbi2bXZ2DBzENxcVGJD2yGbjoy4uroiMTERaWlpjbanpaVh4MCBTT6nqqoKSmXjb6NS1f0PIdf2S+Socgqu4Nzlq/BwVWHYbYGi45ATGdEjCK/d2wMA8PYPx6zTf+3V8eJyzNt4BAPm/4SZa/Yh/URdERkQ7Yv/mxCPPS8Px1/vj0O8zgcLx8fDz9MVx4rL8db3x0RHt0s2H4OdM2cOHnvsMSQlJSE5ORlLly5Ffn6+9bTL3Llzcf78eaxatQoAMGbMGDz55JNYsmQJ7r77bhQVFWH27Nno168fQkP5Ly8ie9IwW2R4TBDcXfmvN2pfUwZFIf/SVSzfnov/Wb8fwVo39I30FR3LylBdi437C/HF3gLsP6e3bg/y1uChxE4Yl6hDpL/nNc8L9HLDu+PjMXXFXqzccRZDuvrjLl6P1YjNZWTChAkoKyvDvHnzUFRUhNjYWKSmpiIiIgIAUFRU1GjmyJQpU1BeXo5Fixbhf/7nf+Dj44M777wTb7/9duv9FER0yyyWX5+i4SoaEuPl0TE4f6UKPx6+gCdXZeLrPwxEdEAHYXkkScKe3EtYl1mA1INFqK6tuwZErVRgeEwQJvTVYUhXf6hVNz7RMOy2QEwfHIVl23Lxxy8P4PvnhiDI2609fgRZUEgyOFdiMBig1Wqh1+vh7e0tOg6RQ9p79hLGfbgTXho1Mv8yHBo1j4yQGFdrzJj48S7sL7iCCD8PfP2HgfBr57tGXzBU48usc1ifWYCzZVXW7V0CO2BCkg739wmz+U7WRpMZDyzegcOFBgzq4odPp/WHUtn04g9H0dzf37xUnogAAJvqz9GP6BnEIkJCubuq8MnkJDywZDvyyqrw5KpMrHlyQJtf+FlrtmDLsRJ8sbcA/z1egoYbC3u6qjAmPhTj++qQoPO57urRm9GoVfjg4QTc+8E2bD9Vho/Sz8jmQt22xjJCRDBbJKQeqlslN4araMgOBHhpsGJKPzyweDv25V/BnC9ysOjhPm1yJOFUSQW+yCzA1/vOobSixrq9b2RHjEvSYXRcSKstc+8c0AFv3NcTf/rqABZuPo7kzn7orfNpldeWM5YRIsLu3DJcLDdC6+6CQV38RcchAlB3SmTp5CQ8tmw3Ug8W4+2OxzB3VEyrvHal0YRNBwrxReY5ZOVdtm7376DBg4lhGJ+kQ+c2ulZlXFInpJ+8iE0HijBrbTb+PWswvJz8tgssI0RkXUVzT89guKpbNAuRqE0MiPbD3x6Kx+x1Ofgo/Qw6+XrgsQERLXotSZKwL/8y1u0twKYDRaiqMQMAVEoFht0WiPFJnTCseyBcbnIx6q1SKBT46/1xyM6/gvxLVfjLhkN4f2JCm35Pe8cyQuTkTGYLfqg/RXNvPFfRkP0ZmxCGgktVWJh2Aq99ewidfNwxrHvz5+BcLDfi633n8EVmAU5frLRuj/b3xLgkHR7sE4bAdl7ZonV3wQcP98b4j3ZhQ04hbu8WgAf6dGrXDPaEZYTIye04XYZLlTXw83RFcrSf6DhETXrmzi7Iv1SF9VnnMHPNPnzxVDJiw7TX3d9ktmDriYtYt7cAW46VwFR/Naq7iwqje4VgfJIOfSM7tvhi1NaQGOGL2Xd1xcK0E/jLhkPoE96xyTklzoBlhMjJNdyh957Y4JvOSiASRaFQYP4DcSjSV2PbqVJMW7kX38wchDAf90b75ZZW4ovMAnyVdQ4l5Ubr9t46H0zoq8O9vULs6vqMp4d1wbZTpdidewmzPs/GlzMGOuWpUs4ZIXJiNSYLkt5Mg6HahLVPDkByZx4ZIftmqK7FuCU7cfxCOW4L8sL6PyRDrVTg+4PFWJdZgD25l6z7+nq64oGEMIzvq0O3IC+BqW+sSH8VI/+egStVtXjq9uhWu0jXHnDOCBHd1LZTF2GoNiHAS4N+UfYzdpvoerzdXLB8al/c/8/tOH6hHPf/czsuGIyoMJoAAEoFcHu3AExI0uGumCBZHGUI0brj7Qd74alPs/BR+hkM6uKP27sFiI7Vruz/fyUiajOb9tetohkdFwKVg0+CJMcR5uOO5VP6wsNVhdMXK1FhNCHc1wMvpHTD9pfuxMqp/TAyLkQWRaTB3T2D8eiAcADAnC/2o7TCeJNnOBYeGSFyUtW1Zmw+cgEA70VD8hMbpsWqaf3w74NFGNEjCAOi/GQ/Wv2V0T2wJ/cSTlyowAvr92P5431l/zM1l3xqIxG1qq0nLqLCaEKI1g19wjuKjkNks6RIX7w2picGdvZ3iF/abi4q/OPhPtColfj5+EWs2HFWdKR2wzJC5KQaBp2NjgtxiA9yIkdwW7AXXhlddwHr298fw6HzesGJ2gfLCJETulpjxk9H60/RxPNeNET25NEBERjRIwg1ZgtmfZ6NqhqT6EhtjmWEyAltOVaCqhozdL7uiO90/cFRRNT+FAoF3nmwF4K93XDmYiXe+O6I6EhtjmWEyAk1DDobHRcqdAIlETWto6cr/m9CbygUwLrMAuvfWUfFMkLkZCqMJmw5VgKAq2iI7FlyZz/MHNoFADD364MouFQlOFHbYRkhcjI/Hb0Ao8mCKH9P9AzlRGMie/bc8K7oE+6D8moTZq/LgclsER2pTbCMEDmZjfWDzu7tFcJTNER2zkWlxN8nJsBLo0ZW3mV88NNJ0ZHaBMsIkRPRX61F+omLAIB7e3EVDZEc6Hw9MP+BOADAov+ewq4zZYITtT6WESInknbkAmrMFnQN7IDbgu33xmFE1NiY+FCMS+wEiwQ8vy4HV6pqREdqVSwjRE6k4Yp8HhUhkp/X7+uJaH9PFOmr8eJXByBJkuhIrYZlhMhJXK6swbaTpQCAe+O5ioZIbjw1anzwcAJcVAr8ePgCVu/OFx2p1bCMEDmJHw8Xw2SREBPijc4BHUTHIaIWiA3T4sV7ugMA/nfTEZy4UC44UetgGSFyEg33ouFsESJ5mzYoCnd0C4DRZMGza7JRXWsWHemWsYwQOYHSCiN2nK47RTOG14sQyZpSqcC74+Lh30GD4xfKMT/1qOhIt4xlhMgJfH+oGBYJ6NVJi3A/D9FxiOgWBXhpsHB8PABg1c48bD5cLDjRrWEZIXICm/Y3rKLhKRoiR3FHtwA8OSQKAPCnrw6gWF8tOFHLsYwQObgLhmrsOXsJADCap2iIHMof7+6OuDAtrlTVYva6bJgt8lzuyzJC5OBSDxZBkoA+4T4I83EXHYeIWpGrWokPHk6Ah6sKu85cwodbT4uO1CIsI0QO7pdVNDwqQuSIovw9Me93sQCA99JOICvvsuBEtmMZIXJg569cRVbeZSgUwGheL0LksB7sE4b74kNhtkh47vNsGKprRUeyCcsIkQP7d/34976RvgjydhOchojaikKhwJv3x0Ln645zl6/i5W8OyWpcPMsIkQNrOEUzhkdFiByet5sL/j4xASqlAhv3F+LLrHOiIzUbywiRg8orq8SBc3ooFcA9sSwjRM6gT3hHzBnRDQDw2neHceZiheBEzcMyQuSgGo6KJHf2Q4CXRnAaImovM+7ojORoP1TVmDHr82wYTfY/Lp5lhMhBcRUNkXNSKRX4vwm90dHDBYfOG/Duj8dFR7oplhEiB3T6YgWOFhmgVipwT89g0XGIqJ0Fa93wzkN14+I/zsjFz8dLBCe6MZYRIge0aX/dUZFBXfzR0dNVcBoiEmFEjyBMTo4AALywfj8ulhsFJ7o+lhEiB7TpAO9FQ0TAn0fFoHuwF0oravA/6/fDYqfj4llGiBzM8eJynCypgKtKiRSeoiFyam4uKvzj4QRo1Eqkn7iI5dtzRUdqEssIkYNpOCpyezd/aN1dBKchItG6Bnnh1TE9AABv/3AMB8/pBSe6VovKyOLFixEVFQU3NzckJiYiIyPjhvsbjUa8/PLLiIiIgEajQefOnbF8+fIWBSai65MkiatoiOgak/qF456ewag1S5j1eTYqjSbRkRqxuYysW7cOs2fPxssvv4zs7GwMGTIEI0eORH5+/nWfM378ePz0009YtmwZjh8/jrVr16J79+63FJyIrnW40IDc0kpo1EoM7xEkOg4R2QmFQoG3HoxDiNYNuaWVeO27w6IjNaKQbBxe379/f/Tp0wdLliyxbouJicHYsWOxYMGCa/b/4YcfMHHiRJw5cwa+vr4tCmkwGKDVaqHX6+Ht7d2i1yByBm99fwwfbj2Ne3oG48PHEkXHISI7s/tMGR7+eBcsEvD3ib3xu95hbfr9mvv726YjIzU1NcjKykJKSkqj7SkpKdixY0eTz/nuu++QlJSEd955B2FhYejWrRteeOEFXL161ZZvTUQ3UXeKpn4VTTxX0RDRtfpH++GZO7sCAF755hAKLlUJTlRHbcvOpaWlMJvNCApqfPg3KCgIxcXFTT7nzJkz2LZtG9zc3PDNN9+gtLQUTz/9NC5dunTd60aMRiOMxl/WQxsMBltiEjml/ef0OHf5KtxdVLize6DoOERkp2bd2QU7TpUiM+8yZn2ejS+eSoaLSux6lhZ9d4VC0ehrSZKu2dbAYrFAoVBg9erV6NevH0aNGoX33nsPK1euvO7RkQULFkCr1VofOp2uJTGJnMqm/XVHRe6KCYSHq03/ziAiJ6JWKfH+xN7wclMjO/8K3v/PCdGRbCsj/v7+UKlU1xwFKSkpueZoSYOQkBCEhYVBq9Vat8XExECSJJw71/TtjefOnQu9Xm99FBQU2BKTyOlYLBL+fZCraIioeTp19MBbD/QCACz++TR2nC4VmsemMuLq6orExESkpaU12p6WloaBAwc2+ZxBgwahsLAQFRW/3Mb4xIkTUCqV6NSpU5PP0Wg08Pb2bvQgouvbl38ZRfpqdNCoMfS2ANFxiEgGRvcKwYQkHSQJeH5dDi5V1gjLYvNpmjlz5uCTTz7B8uXLcfToUTz//PPIz8/HjBkzANQd1Zg8ebJ1/0mTJsHPzw9Tp07FkSNHkJ6ejj/+8Y+YNm0a3N3dW+8nIXJiDbNFRvQIgpuLSnAaIpKL1+7rgegAT1wwGLF8m7jprDafWJ4wYQLKysowb948FBUVITY2FqmpqYiIqLsZT1FRUaOZIx06dEBaWhqeffZZJCUlwc/PD+PHj8ebb77Zej8FkRMzNzpFw1U0RNR8Hq5q/OPhBKQduYBnhnURlsPmOSMicM4I0fXtPF03N8DbTY3MV0bAVc27PBCRfWiTOSNEZH8aZovc3TOYRYSIZImfXEQyZjJb8MOhutVt98ZzFQ0RyRPLCJGM7TxThrLKGnT0cMHAzn6i4xARtQjLCJGMbdpfd+HqPbEhwicoEhG1FD+9iGSqxmTBD4frTtGM4SoaIpIxlhEimdp+qhT6q7Xw76BB/2ieoiEi+WIZIZKpjfWraEbFBUOlbPreUEREcsAyQiRD1bVmpB2+AID3oiEi+WMZIZKh9BMXUW40IdjbDUkRHUXHISK6JSwjRDLUcC+aUXEhUPIUDRHJHMsIkcxcrTHjP0frT9HEcxUNEckfywiRzPz3eAmqaswI83FHgs5HdBwiolvGMkIkMw33orm3VwgUCp6iISL5YxkhkpFKowlbjpUA4CoaInIcLCNEMvKfoxdQXWtBhJ8HYsOufztuIiI5YRkhkpGGVTQ8RUNEjoRlhEgmDNW12Hr8IgCeoiEix8IyQiQTaYcvoMZsQecAT3QP9hIdh4io1bCMEMnEL6toQnmKhogcCssIkQxcqapBxslSAMAYDjojIgfDMkIkAz8eLobJIqF7sBe6BPIUDRE5FpYRIhn49SoaIiJHwzJCZOfKKozYcboMAFfREJFjYhkhsnPfHyqG2SIhNswbkf6eouMQEbU6lhEiO/frVTRERI6IZYTIjpUYqrE79xIAYHQcrxchIsfEMkJkx1IPFkGSgN46H+h8PUTHISJqEywjRHaMq2iIyBmwjBDZqcIrV5GZdxkAMJplhIgcGMsIkZ1KPVh3VKRvZEeEaN0FpyEiajssI0R2aqP1FA1X0RCRY2MZIbJDBZeqsL/gCpQKYGRcsOg4RERtimWEyA41XLg6INoPgV5ugtMQEbUtlhEiO8RBZ0TkTFhGiOxMbmklDhcaoFIqcE8sT9EQkeNjGSGyM5v21x0VGdTFH76eroLTEBG1PZYRIjvDQWdE5GxYRojsyMkL5Th+oRwuKgXu7sFTNETkHFhGiOxIw2yR27sGQOvhIjgNEVH7YBkhshOSJP2yiiaep2iIyHmwjBDZiaNF5ThzsRKuaiWGxwSJjkNE1G5YRojsxMb6oyLDbguAlxtP0RCR82AZIbID1bVmrM8sAADcFx8mOA0RUftqURlZvHgxoqKi4ObmhsTERGRkZDTredu3b4darUbv3r1b8m2JHNZ3+wtRWlGDEK0bUnryFA0ROReby8i6deswe/ZsvPzyy8jOzsaQIUMwcuRI5Ofn3/B5er0ekydPxl133dXisESOSJIkLN+WCwB4fGAkXFQ8YElEzsXmT7333nsP06dPxxNPPIGYmBi8//770Ol0WLJkyQ2f99RTT2HSpElITk5ucVgiR7TzdBmOFZfD3UWFh/uGi45DRNTubCojNTU1yMrKQkpKSqPtKSkp2LFjx3Wft2LFCpw+fRqvvfZay1ISObBl9UdFHkrsxNkiROSU1LbsXFpaCrPZjKCgxue0g4KCUFxc3ORzTp48iZdeegkZGRlQq5v37YxGI4xGo/Vrg8FgS0wi2ThzsQI/HSsBAEwdFCk2DBGRIC06Oa1QKBp9LUnSNdsAwGw2Y9KkSXjjjTfQrVu3Zr/+ggULoNVqrQ+dTteSmER2b8X2swCAu7oHIjqgg9gwRESC2FRG/P39oVKprjkKUlJScs3REgAoLy9HZmYmnnnmGajVaqjVasybNw/79++HWq3Gli1bmvw+c+fOhV6vtz4KCgpsiUkkC/qqWnyZdQ4AMH1wlOA0RETi2HSaxtXVFYmJiUhLS8P9999v3Z6Wlobf/e531+zv7e2NgwcPNtq2ePFibNmyBV9++SWiopr+ANZoNNBoNLZEI5KdtXvzcbXWjO7BXkju7Cc6DhGRMDaVEQCYM2cOHnvsMSQlJSE5ORlLly5Ffn4+ZsyYAaDuqMb58+exatUqKJVKxMbGNnp+YGAg3NzcrtlO5ExqzRb8a8dZAMC0wVFNnuYkInIWNpeRCRMmoKysDPPmzUNRURFiY2ORmpqKiIgIAEBRUdFNZ44QObvvDxWjSF8N/w6uuC8+VHQcIiKhFJIkSaJD3IzBYIBWq4Ver4e3t7foOES3RJIkjF28A/sLrmD28K6YPbz5F3cTEclJc39/c9QjUTvbl38Z+wuuwFWtxKMDIkTHISISjmWEqJ0t33YWADC2dyj8O/BCbSIilhGidnTuchW+P1QEoO7CVSIiYhkhalf/2nEWFgkY1MUP3YN5/RMREcAyQtRuKowmfL6nboAfh5wREf2CZYSonazPLEC50YToAE8M7RYoOg4Rkd1gGSFqB2aLhJX1Q86mDoqCUskhZ0REDVhGiNrBT0cvIK+sClp3FzzYJ0x0HCIiu8IyQtQOlm3LBQA83C8cHq42Dz4mInJoLCNEbezQeT12516CWqnA4wM55IyI6LdYRoja2PL6oyKj4kIQonUXnIaIyP6wjBC1oRJDNTYeKATAIWdERNfDMkLUhj7dlYdas4TEiI7orfMRHYeIyC6xjBC1kepaM1bvzgfAIWdERDfCMkLURr7JPo9LlTUI83FHSo8g0XGIiOwWywhRG5AkyXrh6tRBkVCr+FeNiOh6+AlJ1AYyTpbiZEkFPF1VGN9XJzoOEZFdYxkhagMNQ87GJeng7eYiOA0RkX1jGSFqZadKyrH1xEUoFHWnaIiI6MZYRoha2bJtZwEAI2KCEOHnKTYMEZEMsIwQtaJLlTX4et85AFzOS0TUXCwjRK1o7Z58GE0WxIZ5o1+Ur+g4RESywDJC1EpqTBb8a8dZAMC0QVFQKBRiAxERyQTLCFEr+ffBQpSUGxHopcG9vUJFxyEikg2WEaJWIEmSdTnv5OQIuKr5V4uIqLn4iUnUCvbkXsKh8wZo1EpM6h8hOg4RkaywjBC1guXb646KPNCnE3w9XQWnISKSF5YRoluUX1aFzUcuAACmccgZEZHNWEaIbtGKHbmQJOD2bgHoGuQlOg4RkeywjBDdAkN1Lb7YWwCAQ86IiFqKZYToFnyxtwCVNWZ0DeyA27v6i45DRCRLLCNELWQyW7Bi+1kAwLTBHHJGRNRSLCNELZR25ALOX7mKjh4uuD8hTHQcIiLZYhkhaqGGIWeP9I+Am4tKcBoiIvliGSFqgf0FV5CZdxkuKgUmJ3PIGRHRrWAZIWqBhqMiY3qFItDbTXAaIiJ5YxkhslGR/ipSDxYBqLtwlYiIbg3LCJGNVu3Mg8kioX+UL2LDtKLjEBHJHssIkQ2qakxYszsfAI+KEBG1FpYRIht8te889FdrEe7rgeExQaLjEBE5BJYRomayWCSsqL9wdeqgSKiUHHJGRNQaWEaImmnriYs4U1oJL40a45J0ouMQETkMlhGiZmpYzjuxnw4dNGrBaYiIHEeLysjixYsRFRUFNzc3JCYmIiMj47r7fv311xgxYgQCAgLg7e2N5ORk/Pjjjy0OTCTCsWIDtp0qhVIBTE6OFB2HiMih2FxG1q1bh9mzZ+Pll19GdnY2hgwZgpEjRyI/P7/J/dPT0zFixAikpqYiKysLw4YNw5gxY5CdnX3L4Ynay/L6oyL3xAZD5+shOA0RkWNRSJIk2fKE/v37o0+fPliyZIl1W0xMDMaOHYsFCxY06zV69uyJCRMm4NVXX23W/gaDAVqtFnq9Ht7e3rbEJbplpRVGDHxrC2pMFnz1h2QkRviKjkREJAvN/f1t05GRmpoaZGVlISUlpdH2lJQU7Nixo1mvYbFYUF5eDl/f63+gG41GGAyGRg8iUVbvykeNyYJ4nQ/6hHcUHYeIyOHYVEZKS0thNpsRFNR4vkJQUBCKi4ub9RoLFy5EZWUlxo8ff919FixYAK1Wa33odFy5QGIYTWZ8uisPADB9cBQUCi7nJSJqbS26gPW3H8iSJDXrQ3rt2rV4/fXXsW7dOgQGBl53v7lz50Kv11sfBQUFLYlJdMu+yylEaYURIVo3jIwNFh2HiMgh2bQ+0d/fHyqV6pqjICUlJdccLfmtdevWYfr06Vi/fj2GDx9+w301Gg00Go0t0YhanSRJ1uW8k5Mj4aLiSngiorZg06erq6srEhMTkZaW1mh7WloaBg4ceN3nrV27FlOmTMGaNWswevToliUlamc7T5fhWHE53F1UmNQvXHQcIiKHZfPkpjlz5uCxxx5DUlISkpOTsXTpUuTn52PGjBkA6k6xnD9/HqtWrQJQV0QmT56Mv//97xgwYID1qIq7uzu0Wt7xlOzX8u11R0UeSuwErYeL4DRERI7L5jIyYcIElJWVYd68eSgqKkJsbCxSU1MREREBACgqKmo0c+Sjjz6CyWTCzJkzMXPmTOv2xx9/HCtXrrz1n4CoDeSWVuKnYyUA6u5DQ0REbcfmOSMicM4ItbdXvz2EVTvzcGf3QCyf0ld0HCIiWWqTOSNEzkBfVYv1mecA1C3nJSKitsUyQvQba/fm42qtGd2DvTCws5/oOEREDo9lhOhXas0W/GvHWQDANA45IyJqFywjRL/yw6FiFOmr4d/BFffFh4qOQ0TkFFhGiH6lYcjZowMi4OaiEpyGiMg5sIwQ1cvKu4ycgitwVSnxSP8I0XGIiJwGywhRveX1R0V+1zsUAV68HQERUXthGSECcO5yFb4/VAQAmD6Ey3mJiNoTywgRgFU782CRgEFd/NA9mIP1iIjaE8sIOb1Kowlr99TdwoBDzoiI2h/LCDm99ZkFKK82IdrfE0O7BYqOQ0TkdFhGyKmZLRJW1A85mzooEkolh5wREbU3lhFyaj8dvYC8sipo3V3wYGIn0XGIiJwSywg5teXb65bzPtwvHB6uasFpiIicE8sIOa3DhXrsOnMJKqUCjw/kkDMiIlFYRshpNYx+HxUXghCtu+A0RETOi2WEnFKJoRob9xcC4HJeIiLRWEbIKX26Kw+1ZgmJER3RW+cjOg4RkVNjGSGnU11rxurdHHJGRGQvWEbI6WzIPo9LlTUI83FHSo8g0XGIiJweywg5FUmSrMt5pwyMhFrFvwJERKLxk5icSsbJUpy4UAFPVxUm9NOJjkNERGAZISfTsJx3XJIO3m4ugtMQERHAMkJO5FRJObaeuAiFou4+NEREZB9YRshpLN9+FgAwIiYIEX6eYsMQEZEVywg5hcuVNfh63zkAwDQu5yUisiu8Mxg5vLyySrz9wzFU11rQM9Qb/aN8RUciIqJfYRkhh7Uv/zI+Tj+DHw4XQ5Lqtj0zrAsUCoXYYERE1AjLCDkUs0VC2pEL+DjjDLLyLlu339EtAE/dHo2BXfwFpiMioqawjJBDuFpjxpdZBVi2LRdny6oAAK4qJX7XOxRPDInGbcFeghMSEdH1sIyQrF0sN2LVzrP4bFceLlfVAgC07i54dEA4Hk+ORKC3m+CERER0MywjJEunSsrxSUYuvs4+jxqTBQCg83XHE4OjMS6pEzxc+X9tIiK54Cc2yYYkSdh15hI+zjiDLcdKrNt763zw+9ujcXfPYKiUvDiViEhuWEbI7tWaLUg9WISPM87g0HkDAEChAFJ6BOHJIdFIjOjIFTJERDLGMkJ2q7y6Fuv2FmD5tlwU6qsBAG4uSjyU2AnTB0cjyp9TVImIHAHLCNmdwitXsXLHWazdnY9yowkA4N/BFZOTI/HogAj4eroKTkhERK2JZYTsxuFCPT7JyMXG/YUwWeqmlHUO8MSTQ6IxNiEMbi4qwQmJiKgtsIyQUJIkYeuJi/g44wy2nyqzbh8Q7Ysnh0Rj2G2BUPKiVCIih8YyQkIYTWZ8m1OITzLO4MSFCgCASqnA6LgQPDkkGnGdtIITEhFRe2EZoXZ1paoGq3fnY+WOs7hYbgQAeLqq8HC/cEwZFIlOHT0EJyQiovbGMkLtIr+sCsu2ncEXmedwtdYMAAj2dsPUQZGY2C8cWncXwQmJiEgUlhFqU/vyL+OTjDP44VAx6q9JRUyIN35/exRGx4XCVa0UG5CIiIRr0W+CxYsXIyoqCm5ubkhMTERGRsYN99+6dSsSExPh5uaG6OhofPjhhy0KS/Jgtkj44VAxHlqyAw8s3oHUg3VF5I5uAVj9RH+kzhqM+xM6sYgQERGAFhwZWbduHWbPno3Fixdj0KBB+OijjzBy5EgcOXIE4eHh1+yfm5uLUaNG4cknn8Rnn32G7du34+mnn0ZAQAAefPDBVvkhyD5crTHjy33nsCzjjPXOuS4qBcb2DuOdc4mI6LoUkiRJtjyhf//+6NOnD5YsWWLdFhMTg7Fjx2LBggXX7P/iiy/iu+++w9GjR63bZsyYgf3792Pnzp3N+p4GgwFarRZ6vR7e3t62xKUWkiQJtWYJRpMZRpMFNSYLjCYLjCbzL/9da0GN2QxjrQVHigy8cy4RETXS3N/fNh0ZqampQVZWFl566aVG21NSUrBjx44mn7Nz506kpKQ02nb33Xdj2bJlqK2thYuLuAsXyyqM1osp7ZkkwVoEGhWDWjNqzHWloG67uX6/hn1+VRx+tc34q203eo2W0Pm6Y/qgKIxL0sFTw0uSiIjo5mz6bVFaWgqz2YygoKBG24OCglBcXNzkc4qLi5vc32QyobS0FCEhIdc8x2g0wmg0Wr82GAy2xGy2NzYewXf7C9vktR2Nq1oJjUoJjYsSGrWq7uv6h6taCa27Cx7o04l3ziUiIpu16J+uv71DqiRJN7xralP7N7W9wYIFC/DGG2+0JJpN1CoFNDK4iFKhwDUFoNHXLiq4WovCL3/eUBSu3V8JV5XqV/9d9xq/Lhcatcr6Z64qJaegEhFRm7GpjPj7+0OlUl1zFKSkpOSaox8NgoODm9xfrVbDz8+vyefMnTsXc+bMsX5tMBig0+lsidos743vjffG92711yUiIqLms+mwgKurKxITE5GWltZoe1paGgYOHNjkc5KTk6/Zf/PmzUhKSrru9SIajQbe3t6NHkREROSYbD5HMWfOHHzyySdYvnw5jh49iueffx75+fmYMWMGgLqjGpMnT7buP2PGDOTl5WHOnDk4evQoli9fjmXLluGFF15ovZ+CiIiIZMvma0YmTJiAsrIyzJs3D0VFRYiNjUVqaioiIiIAAEVFRcjPz7fuHxUVhdTUVDz//PP45z//idDQUHzwwQecMUJEREQAWjBnRATOGSEiIpKf5v7+tv+lJEREROTQWEaIiIhIKJYRIiIiEoplhIiIiIRiGSEiIiKhWEaIiIhIKJYRIiIiEoplhIiIiIRiGSEiIiKhWEaIiIhIKJvvTSNCw8R6g8EgOAkRERE1V8Pv7ZvdeUYWZaS8vBwAoNPpBCchIiIiW5WXl0Or1V73z2VxozyLxYLCwkJ4eXlBoVCIjtOuDAYDdDodCgoKeJPAW8D3sXXwfWwdfB9bB9/H1tGW76MkSSgvL0doaCiUyutfGSKLIyNKpRKdOnUSHUMob29v/mVrBXwfWwffx9bB97F18H1sHW31Pt7oiEgDXsBKREREQrGMEBERkVAsI3ZOo9Hgtddeg0ajER1F1vg+tg6+j62D72Pr4PvYOuzhfZTFBaxERETkuHhkhIiIiIRiGSEiIiKhWEaIiIhIKJYRO7VgwQL07dsXXl5eCAwMxNixY3H8+HHRsWRvwYIFUCgUmD17tugosnP+/Hk8+uij8PPzg4eHB3r37o2srCzRsWTFZDLhlVdeQVRUFNzd3REdHY158+bBYrGIjmbX0tPTMWbMGISGhkKhUGDDhg2N/lySJLz++usIDQ2Fu7s7hg4disOHD4sJa8du9D7W1tbixRdfRFxcHDw9PREaGorJkyejsLCwXbKxjNiprVu3YubMmdi1axfS0tJgMpmQkpKCyspK0dFka+/evVi6dCl69eolOorsXL58GYMGDYKLiwu+//57HDlyBAsXLoSPj4/oaLLy9ttv48MPP8SiRYtw9OhRvPPOO/jb3/6Gf/zjH6Kj2bXKykrEx8dj0aJFTf75O++8g/feew+LFi3C3r17ERwcjBEjRlhvJUJ1bvQ+VlVVYd++ffjLX/6Cffv24euvv8aJEydw3333tU84iWShpKREAiBt3bpVdBRZKi8vl7p27SqlpaVJd9xxh/Tcc8+JjiQrL774ojR48GDRMWRv9OjR0rRp0xpte+CBB6RHH31UUCL5ASB988031q8tFosUHBwsvfXWW9Zt1dXVklarlT788EMBCeXht+9jU/bs2SMBkPLy8to8D4+MyIRerwcA+Pr6Ck4iTzNnzsTo0aMxfPhw0VFk6bvvvkNSUhLGjRuHwMBAJCQk4OOPPxYdS3YGDx6Mn376CSdOnAAA7N+/H9u2bcOoUaMEJ5Ov3NxcFBcXIyUlxbpNo9HgjjvuwI4dOwQmkz+9Xg+FQtEuR0BlcW8aZydJEubMmYPBgwcjNjZWdBzZ+fzzz7Fv3z7s3btXdBTZOnPmDJYsWYI5c+bgz3/+M/bs2YNZs2ZBo9Fg8uTJouPJxosvvgi9Xo/u3btDpVLBbDbjr3/9Kx5++GHR0WSruLgYABAUFNRoe1BQEPLy8kREcgjV1dV46aWXMGnSpHa57w/LiAw888wzOHDgALZt2yY6iuwUFBTgueeew+bNm+Hm5iY6jmxZLBYkJSVh/vz5AICEhAQcPnwYS5YsYRmxwbp16/DZZ59hzZo16NmzJ3JycjB79myEhobi8ccfFx1P1n57R3dJkpzuLu+tpba2FhMnToTFYsHixYvb5XuyjNi5Z599Ft999x3S09Od/s7FLZGVlYWSkhIkJiZat5nNZqSnp2PRokUwGo1QqVQCE8pDSEgIevTo0WhbTEwMvvrqK0GJ5OmPf/wjXnrpJUycOBEAEBcXh7y8PCxYsIBlpIWCg4MB1B0hCQkJsW4vKSm55mgJ3VxtbS3Gjx+P3NxcbNmypd3uhsxrRuyUJEl45pln8PXXX2PLli2IiooSHUmW7rrrLhw8eBA5OTnWR1JSEh555BHk5OSwiDTToEGDrllafuLECURERAhKJE9VVVVQKht/7KpUKi7tvQVRUVEIDg5GWlqadVtNTQ22bt2KgQMHCkwmPw1F5OTJk/jPf/4DPz+/dvvePDJip2bOnIk1a9bg22+/hZeXl/W8qFarhbu7u+B08uHl5XXNdTaenp7w8/Pj9Tc2eP755zFw4EDMnz8f48ePx549e7B06VIsXbpUdDRZGTNmDP76178iPDwcPXv2RHZ2Nt577z1MmzZNdDS7VlFRgVOnTlm/zs3NRU5ODnx9fREeHo7Zs2dj/vz56Nq1K7p27Yr58+fDw8MDkyZNEpja/tzofQwNDcVDDz2Effv2YdOmTTCbzdbfO76+vnB1dW3bcG2+XodaBECTjxUrVoiOJntc2tsyGzdulGJjYyWNRiN1795dWrp0qehIsmMwGKTnnntOCg8Pl9zc3KTo6Gjp5ZdfloxGo+hodu2///1vk5+Hjz/+uCRJdct7X3vtNSk4OFjSaDTS7bffLh08eFBsaDt0o/cxNzf3ur93/vvf/7Z5Nt61l4iIiITiNSNEREQkFMsIERERCcUyQkREREKxjBAREZFQLCNEREQkFMsIERERCcUyQkREREKxjBAREZFQLCNEJFuvv/46evfuLToGEd0ilhEikgWFQoENGzaIjkFEbYBlhIiIiIRiGSEimwwdOhTPPvssZs+ejY4dOyIoKAhLly5FZWUlpk6dCi8vL3Tu3Bnff/+99Tlbt25Fv379oNFoEBISgpdeegkmk6nRa86aNQt/+tOf4Ovri+DgYLz++uvWP4+MjAQA3H///VAoFNavG3z66aeIjIyEVqvFxIkTUV5e3pZvARG1MpYRIrLZv/71L/j7+2PPnj149tln8Yc//AHjxo3DwIEDsW/fPtx999147LHHUFVVhfPnz2PUqFHo27cv9u/fjyVLlmDZsmV48803r3lNT09P7N69G++88w7mzZuHtLQ0AMDevXsBACtWrEBRUZH1awA4ffo0NmzYgE2bNmHTpk3YunUr3nrrrfZ7M4jolvGuvURkk6FDh8JsNiMjIwMAYDabodVq8cADD2DVqlUAgOLiYoSEhGDnzp3YuHEjvvrqKxw9ehQKhQIAsHjxYrz44ovQ6/VQKpXXvCYA9OvXD3feeae1WCgUCnzzzTcYO3asdZ/XX38df/vb31BcXAwvLy8AwJ/+9Cekp6dj165d7fF2EFEr4JERIrJZr169rP+tUqng5+eHuLg467agoCAAQElJCY4ePYrk5GRrEQGAQYMGoaKiAufOnWvyNQEgJCQEJSUlN80SGRlpLSK2PI+I7AfLCBHZzMXFpdHXCoWi0baG4mGxWCBJUqMiAgANB2R/vb2p17RYLC3K0pznEZH9YBkhojbVo0cP7NixA78+I7xjxw54eXkhLCys2a/j4uICs9ncFhGJSDCWESJqU08//TQKCgrw7LPP4tixY/j222/x2muvYc6cOVAqm/8RFBkZiZ9++gnFxcW4fPlyGyYmovbGMkJEbSosLAypqanYs2cP4uPjMWPGDEyfPh2vvPKKTa+zcOFCpKWlQafTISEhoY3SEpEIXE1DREREQvHICBEREQnFMkJERERCsYwQERGRUCwjREREJBTLCBEREQnFMkJERERCsYwQERGRUCwjREREJBTLCBEREQnFMkJERERCsYwQERGRUCwjREREJNT/AwA6LA1eYpghAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sum_cases_per_day = Brazil_data.groupby('month').sum()['cases']\n",
    "sum_cases_per_day.plot()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "258beced",
   "metadata": {},
   "source": [
    "This line graph is answering the question of what month was the COVID-19 data the highest in Brazil.  According to this it looks like in August the number of cases in Brazil was over 1.2 million.  June and July as well were extremely close to being the highest because they are also above 1.2 million cases.  There was a small spike that made August the month with the highest number of cases. This was suprising because we did not expect these numbers to be so high. There was a huge decrease after August up until December of 2020. This graph is showing just how quickly the number of COVID-19 cases in a country can change and drastically increase or decrease from month to month."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "ac7067c0",
   "metadata": {},
   "source": [
    "# Question 3: How many deaths total did Brazil have from COVID-19?"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "id": "4c93551e",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/tmp/ipykernel_7326/3093324216.py:1: FutureWarning: The default value of numeric_only in DataFrame.sum is deprecated. In a future version, it will default to False. In addition, specifying 'numeric_only=None' is deprecated. Select only valid columns or specify the value of numeric_only to silence this warning.\n",
      "  Brazil_data.sum()['deaths']\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "181402"
      ]
     },
     "execution_count": 31,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "Brazil_data.sum()['deaths']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "id": "9a48bd5a",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/tmp/ipykernel_7326/1880913069.py:1: FutureWarning: The default value of numeric_only in DataFrameGroupBy.sum is deprecated. In a future version, numeric_only will default to False. Either specify numeric_only or select only columns which should be valid for the function.\n",
      "  sum_deaths_per_day=Brazil_data.groupby('month').sum()['deaths']\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "<AxesSubplot: xlabel='month'>"
      ]
     },
     "execution_count": 30,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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HMqWOQyQ5Fh0ikoTZLDBv3WFUVZvRv11LPHEv17VqCG5qJ7wwpD2A2qM7ZQZeck7NG4sOEUlizf5M7DtXBBelAovHRfDqqgb0eO8gtGnpistlRnz8y1mp4xBJikWHiJpcdnEFFm87DgCYN6wjJx83MKVCjrlDOwIAPtpzFpfLDBInIpIOiw4RNSkhBOavP4Jyowm923jhyag2UkdySA+G+SMiUINyownLfz4jdRwiybDoEFGT+vZgNn45fRlqJzneejiCa700ErlchpeHdQIArNl3ARcKyyVORCQNFh0iajL5uir8c2vt3nhzojugbasWEidybP3a+eC+Dq1QbRJ4Z/spqeMQSYJFh4iahBACf9twBKVVNegW5IkpA9pKHalZeOnKXJ1Nh3KRkaOTOA1R02PRIaImsTE9BztOFEClkGPpIxFQ8JRVkwhrrcGY7rUrJL8Vf0LiNERNj0WHiBpdQWkVFmyqPWU16/526ODnfotnUEOa80BHKBUy/HL6Mn49c1nqOERNikWHiBrda98fha6yGl0DPPDswHukjtPsBLd0xcQ+IQCAxT+cgNncbHf+oWaIRYeIGtXWw3n4ISMfTnIZljwSAaWCXztSmDG4HdxUChzJ0WFbRp7UcYiaDL9xiKjRFJUb8Y/vMwAA0wbdg64BGokTNV8+LdR45r7ao2lLfzyJapNZ4kRETYNFh4gazeubj6Kw3IiOfu6YMbi91HGavb/+KRQ+LVS4UFiBuP3c8JOaBxYdImoUCccu4vv0XMhlwJJHIqBy4teN1NzUTph1f23h/M+OMyjnhp/UDPCbh4ganK6iGn/bcAQA8Mx996BbkKe0gcji8d7BCGnpistlBnySeE7qOESNjkWHiBrcP7ceQ0GpAW1buSF2CE9Z2RKVkxxzo2sXEfxg928o5Iaf5OBYdIioQe06WYDvUrIhkwFLH4mAs1IhdSS6xohwf4S19kC50YT3uOEnOTgWHSJqMKVV1Xhlfe0pq7/0C0VkiLfEiehGajf87AygdsPPrKIKiRMRNR4WHSJqMIt+OIFcXRWCvV0xd2gHqePQTQxo74M/tfe5suHnSanjEDUaFh0iahB7z1zGV/tqL1l+6+EIuKqcJE5EtzJvWCcAwMb0XBzN5Yaf5JhYdIjorlUYazBv/WEAwKS+wYi6p6XEieh2hLXWYFS32g0/l8TzqA45JhYdIrprS+JPIquoEq09XfDy8M5Sx6F6mBvdAU5yGXafuoS93PCTHBCLDhHdlQPni/B50nkAwMJx4Wih5ikrexLS0g0T+wQDABbHn4AQ3PCTHAuLDhHdsapqE+Z9dxhCAON7BWJgh1ZSR6I7MPP+9nBTKXA4W4dtR/KljkPUoFh0iOiOvZtwCmcvl8PXXY2/jegidRy6Qz4t1Pjrn9oCAN7ezg0/ybGw6BDRHUnPKsFHv5wFACx8KBwaF6XEiehuTL2vLVq6qXDucjm+PpAldRyiBsOiQ0T1Zqgx4cVvD8EsgLHdAzCki5/UkegutbDa8PM0Kozc8JMcA4sOEdXb8p/P4HRBGXxaqPDaqK5Sx6EG8sS9wQj2dsWlUgP+xw0/yUGw6BBRvWTk6LBi128AgH+OCYOXm0riRNRQVE5yzImuXdF61e6zKCo3SpyI6O6x6BDRbas2mfHSd4dhMgs8GK7F8HB/qSNRAxsVEYCuAR4oM9RgOTf8JAfAokNEt23Vrt9wLE8PL1clXh8dJnUcagRyuQwvD6/dGmJ1Mjf8JPvHokNEt+XUxVL89+fTAIAFo7uilbta4kTUWP7UvhX6t2sJo8mMdxNOSR2H6K6w6BDRLdWYzHjx20OoNgkM6eyL0Vf2RyLHVbfh54b0HBzL1UuchujOsegQ0S19kngOh7J1cHd2wr/GhkMmk0kdiRpZRKAnRkb4QwhgyY8npI5DdMdYdIjopn67VIZ3rpy++PvILtBqnCVORE1lbnRHOMll2HXyEpJ+K5Q6DtEdYdEhoj9kMgvM++4wjDVm/Km9Dx6NDJQ6EjWhNj5ueOJebvhJ9o1Fh4j+0BdJ53HwQjHcVAosfjiCp6yaoZn3t4OrSoFDWSWIz+CGn2R/WHSI6IYuFJZjSfxJAMD8BzujtaeLxIlICr7uzpYNP5f+eBI13PCT7AyLDhFdx2wWeHndEVRWm9C3rTcmXDl9Qc3T1D+FwttNhbOXy/HNwWyp4xDVS72KzqJFi9C7d2+4u7vD19cXY8eOxcmTJ63GPPXUU5DJZFa3vn37Wo0xGAyYOXMmfHx84ObmhtGjRyM72/pfnuLiYsTExECj0UCj0SAmJgYlJSVWYzIzMzFq1Ci4ubnBx8cHs2bNgtHIJcuJ7tbaA5lIOlsIF6UCbz0cAbmcp6yaM3dnJWYObgcA+PdPp7jhJ9mVehWd3bt3Y/r06UhOTkZCQgJqamoQHR2N8vJyq3HDhg1DXl6e5bZt2zarx2NjY7FhwwbExcUhMTERZWVlGDlyJEwmk2XMhAkTkJ6ejvj4eMTHxyM9PR0xMTGWx00mE0aMGIHy8nIkJiYiLi4O69atw5w5c+7kcyCiK3JKKrFoW+3lxC8O7YiQlm4SJyJbMKFPMIK8XVBQasCnv56XOg7R7RN3oaCgQAAQu3fvttw3efJkMWbMmD98TklJiVAqlSIuLs5yX05OjpDL5SI+Pl4IIcSxY8cEAJGcnGwZk5SUJACIEydOCCGE2LZtm5DL5SInJ8cyZu3atUKtVgudTndb+XU6nQBw2+OJHJ3ZbBYxn+wTIfO2iHErfhU1JrPUkciGbEjNFiHztoiwf8SLojKD1HGoGavP3++7mqOj0+kAAN7e3lb379q1C76+vujQoQOmTp2KgoICy2MpKSmorq5GdHS05b6AgACEhYVh7969AICkpCRoNBr06dPHMqZv377QaDRWY8LCwhAQ8PsKrUOHDoXBYEBKSsoN8xoMBuj1eqsbEf3uu5Rs7Dl1CSonOZY8EgEFT1nRVUZ3C0Bnfw+UGmrw/k5u+En24Y6LjhACs2fPxoABAxAW9vvmfsOHD8eaNWvw888/45133sGBAwcwePBgGAwGAEB+fj5UKhW8vLysXs/Pzw/5+fmWMb6+vtf9Tl9fX6sxfn5+Vo97eXlBpVJZxlxr0aJFljk/Go0GQUFBd/r2iRzORX0V/rnlGABg9gMdcE+rFhInIltz9YafXyRdQHYxN/wk23fHRWfGjBk4fPgw1q5da3X/Y489hhEjRiAsLAyjRo3CDz/8gFOnTmHr1q03fT0hhNUaHTdar+NOxlxt/vz50Ol0lltWVtZNMxE1F0II/G3DEeiratAtUIO/DgiVOhLZqPva+6DfPbUbfi7jhp9kB+6o6MycORObNm3Czp07ERh485VS/f39ERISgtOna3c91mq1MBqNKC4uthpXUFBgOUKj1Wpx8eLF617r0qVLVmOuPXJTXFyM6urq64701FGr1fDw8LC6ERGw6VAufjpeAKVChiWPdIOTgitP0I3JZLLfN/xMy8GJfE4BINtWr28zIQRmzJiB9evX4+eff0Zo6K3/q6+wsBBZWVnw9/cHAERGRkKpVCIhIcEyJi8vDxkZGejXrx8AICoqCjqdDvv377eM2bdvH3Q6ndWYjIwM5OXlWcZs374darUakZGR9XlbRM3apVIDXtt0FAAwc3B7dNS6S5yIbF23IE+MCL+y4Wf8yVs/gUhCMiFuf/OSadOm4auvvsL333+Pjh07Wu7XaDRwcXFBWVkZFixYgIcffhj+/v44f/48XnnlFWRmZuL48eNwd6/9An3++eexZcsWfPbZZ/D29sbcuXNRWFiIlJQUKBQKALVzfXJzc/HBBx8AAJ555hmEhIRg8+bNAGovL+/evTv8/PywdOlSFBUV4amnnsLYsWPx3nvv3db70ev10Gg00Ol0PLpDzdb0NanYeiQPnf09sGlGfyh5NIduw7nL5RiybDdMZoG4Z/qib9uWUkeiZqQ+f7/r9Y22cuVK6HQ6DBo0CP7+/pbb119/DQBQKBQ4cuQIxowZgw4dOmDy5Mno0KEDkpKSLCUHAN59912MHTsW48ePR//+/eHq6orNmzdbSg4ArFmzBuHh4YiOjkZ0dDQiIiLw5ZdfWh5XKBTYunUrnJ2d0b9/f4wfPx5jx47F22+/XZ+3RNSs/XAkD1uP5EEhl2HpIxEsOXTbQn3c8MS9tRd0LP6BG36S7arXER1HwyM61JwVlxvxwLu7cbnMiBl/boe5Qzve+klEVykorcLAJbtQWW3CqkmRGBamlToSNRONdkSHiBzHG1uO4XKZEe19W2Dm/e2kjkN2qHbDz9q5mkt+PMENP8kmsegQNUM7jl/EhrQcyGXAkkcioHZS3PpJRDfwzH1t4eWqxNlL5fg2hRt+ku1h0SFqZnSV1XhlwxEAwF//1BY9gr1u8QyiP+burMSMwe0B1G74WWk03eIZRE2LRYeomVm49Tgu6g0I9XHD7Ac6SB2HHMCkvsFo7emCi3oDPt17Tuo4RFZYdIiakT2nLuHrg1mQXTll5azkKSu6e2onBeYOrS3NK3f9huJyo8SJiH7HokPUTJQZajB/fe0pq8lRbdC7jfctnkF0+8Z0a1274WdVDVbs4oafZDtYdIiaicU/HEdOSSWCvF3wIi8lpwYml8vw0rDaf64+T7qAnJJKiRMR1WLRIWoGkn4rxOrkTADA4nERcFM7SZyIHNGgDq3Qt603jDVmvMsNP8lGsOgQObgKYw3mrTsMAHji3mD0b+cjcSJyVDKZDC8P7wwAWJeajZP5pRInImLRIXJ461KykVlUAX+NM155sJPUccjBdQ/yxPAwLYQAlv54Quo4RCw6RI5u37kiAMCEe4Ph7qyUOA01B3OHdoRCLsNPxwuw/8o/f0RSYdEhcnBpmSUAgJ4hXBiQmsY9rVrgsd51G34e54afJCkWHSIHdlFfhZySSshlQLcgT6njUDMSe397uCgVSM0swfZjF6WOQ80Yiw6RA0u9UAwA6ODnjha80oqakK+HM54e0AYAsPTHk9zwkyTDokPkwFIza4sOT1uRFJ4deA88XZU4U1CGdanc8JOkwaJD5MBS6+bncONOkoCHsxIz/twOAPBuwmlUVXPDT2p6LDpEDspYY8aRHB0AoGewp7RhqNma1DcErT1dkK+vwmd7z0sdh5ohFh0iB3U0VwdjjRlerkqE+rhJHYeaKWelArMfqN3wc8XOMyip4Iaf1LRYdIgcVN1pqx7BXpDJZNKGoWZtbI/W6KR1h76qBit3/SZ1HGpmWHSIHJRlIjJPW5HEFHIZ5g2rXZX7073nkcsNP6kJsegQOai0C3VFhxORSXqDOrbCvaG1G37++ydu+ElNh0WHyAHl66qQq6viQoFkM2o3/Kw9qvNdSjZOXeSGn9Q0WHSIHFDaldNWHbUecONCgWQjegZ7YVhXLcwC+NuGI1xEkJoEiw6RA+L8HLJVrzzYGS3UTjhwvhjLd56ROg41Ayw6RA6ICwWSrQpu6Yo3HwoDAPx3x2nubk6NjkWHyMFYLRTIrR/IBo3p3hoP9wyEWQCxcWlcW4caFYsOkYOpWyjQ202FNi1dpY5DdEOvj+mKUB835Oqq8PK6IxBCSB2JHBSLDpGDsSwUGOTJhQLJZrVQO+G/j/eAUiFD/NF8fLU/U+pI5KBYdIgcDHcsJ3sRHqjBS0NrLzl/Y/MxXnJOjYJFh8jB1C0U2INXXJEdmDIgFPd1aAVDjRmz1qZxh3NqcCw6RA7EaqHAQE+p4xDdklwuwzuPdoNPCxVO5Jdi4bbjUkciB8OiQ+RA6k5bdeJCgWRHWrmr8c747gCAL5IuYPvRfGkDkUNh0SFyIKl1+1uFeEobhKieBnZohWfuawsAeGndYeTpuPEnNQwWHSIH8vuKyJyITPZnbnRHhLfWoKSiGrFx6TCZeck53T0WHSIHYagxISNHD4BFh+yTykmO/z7RA64qBfadK8IKbhFBDYBFh8hBHM3Vw2iqXSgwhAsFkp0K9XHDP8fUbhHx7x2nkXKBW0TQ3WHRIXIQlvk5wVwokOzbuJ6tMbZ7AExmgVlr06GrrJY6EtkxFh0iB5FWtyIyT1uRnZPJZPjn2DAEe7sip6QSr6znFhF051h0iBwEJyKTI3F3VuK/T/SAk1yGrUfy8M3BLKkjkZ1i0SFyAHm6SuTpqqCQy9AtSCN1HKIG0T3IE3OHdgQALNh0DGcKuEUE1V+9is6iRYvQu3dvuLu7w9fXF2PHjsXJkyetxgghsGDBAgQEBMDFxQWDBg3C0aNHrcYYDAbMnDkTPj4+cHNzw+jRo5GdnW01pri4GDExMdBoNNBoNIiJiUFJSYnVmMzMTIwaNQpubm7w8fHBrFmzYDQa6/OWiBxC6oUSAEAnrTtcVVwokBzHM39qiwHtfFBZbcLMtencIoLqrV5FZ/fu3Zg+fTqSk5ORkJCAmpoaREdHo7y83DJmyZIlWLZsGZYvX44DBw5Aq9XigQceQGnp7008NjYWGzZsQFxcHBITE1FWVoaRI0fCZPr9H+AJEyYgPT0d8fHxiI+PR3p6OmJiYiyPm0wmjBgxAuXl5UhMTERcXBzWrVuHOXPm3M3nQWSXeNqKHJVcLsOy8d3g7abC8Tw9Fv9wQupIZG/EXSgoKBAAxO7du4UQQpjNZqHVasXixYstY6qqqoRGoxGrVq0SQghRUlIilEqliIuLs4zJyckRcrlcxMfHCyGEOHbsmAAgkpOTLWOSkpIEAHHixAkhhBDbtm0Tcrlc5OTkWMasXbtWqNVqodPpbiu/TqcTAG57PJGtGvt+ogiZt0WsT82SOgpRo/j5+EURMm+LCJm3Rfx0LF/qOCSx+vz9vqs5OjqdDgDg7e0NADh37hzy8/MRHR1tGaNWqzFw4EDs3bsXAJCSkoLq6mqrMQEBAQgLC7OMSUpKgkajQZ8+fSxj+vbtC41GYzUmLCwMAQEBljFDhw6FwWBASkrKDfMaDAbo9XqrG5G9M9SYcJQLBZKD+3MnXzzdPxQA8OJ3h3FRXyVxIrIXd1x0hBCYPXs2BgwYgLCw2sWd8vNrN2Lz8/OzGuvn52d5LD8/HyqVCl5eXjcd4+vre93v9PX1tRpz7e/x8vKCSqWyjLnWokWLLHN+NBoNgoKC6vu2iWxORk7tQoEt3VQI9uZCgeS45g3viC7+HigqN+L/vuYWEXR77rjozJgxA4cPH8batWuve+zaxcqEELdcwOzaMTcafydjrjZ//nzodDrLLSuLlyuS/Uu7Mj+nR7AXFwokh6Z2UuC9CT3golRg72+F+GDPb1JHIjtwR0Vn5syZ2LRpE3bu3InAwEDL/VqtFgCuO6JSUFBgOfqi1WphNBpRXFx80zEXL1687vdeunTJasy1v6e4uBjV1dXXHempo1ar4eHhYXUjsneWicjcsZyagXtatcDrY7oCAN7Zfsryzz/RH6lX0RFCYMaMGVi/fj1+/vlnhIaGWj0eGhoKrVaLhIQEy31GoxG7d+9Gv379AACRkZFQKpVWY/Ly8pCRkWEZExUVBZ1Oh/3791vG7Nu3DzqdzmpMRkYG8vLyLGO2b98OtVqNyMjI+rwtIrtWd2k55+dQc/FoZCBGRvjDZBZ4IS4N+ipuEUF/rF5FZ/r06Vi9ejW++uoruLu7Iz8/H/n5+aisrARQeyopNjYWCxcuxIYNG5CRkYGnnnoKrq6umDBhAgBAo9FgypQpmDNnDnbs2IG0tDRMmjQJ4eHhGDJkCACgc+fOGDZsGKZOnYrk5GQkJydj6tSpGDlyJDp2rF08Kjo6Gl26dEFMTAzS0tKwY8cOzJ07F1OnTuWRGmo2cksqka+vXSgwIpALBVLzIJPJ8OZD4Qj0ckFWUSVe3ZDBLSLoj9Xnci4AN7x9+umnljFms1m89tprQqvVCrVaLe677z5x5MgRq9eprKwUM2bMEN7e3sLFxUWMHDlSZGZmWo0pLCwUEydOFO7u7sLd3V1MnDhRFBcXW425cOGCGDFihHBxcRHe3t5ixowZoqqq6rbfDy8vJ3u3+VCOCJm3RYz47x6poxA1uYPni0Tb+VtFyLwt4tuDXFqhOanP32+ZEM23Buv1emg0Guh0Oh4FIrv0xuZj+N+v5/BkVAjeGBMmdRyiJvf+zjNY+uNJuKoU2DJzANq2aiF1JGoC9fn7zb2uiOxYquWKK09pgxBJ5LmB9yCqbUtUGE2YuTYNhhpuEUHWWHSI7FRVtQlHc2sX7eREZGquFHIZ3n2sO7xclTiaq8fS+JO3fhI1Kyw6RHbqaK4O1SbBhQKp2dNqnLH0kW4AgI8Tz2HnyQKJE5EtYdEhslN1l5VzoUAiYEgXP0yOCgEAzP3mEApKuUUE1WLRIbJTXCiQyNr8Bzujk9YdheVGzPnmEMzcIoLAokNkl4QQvxcdzs8hAgA4KxV474kecFbK8cvpy/g48azUkcgGsOgQ2aFcXRUu6g1cKJDoGu393PHaqNotIpbEn8ShrBJpA5HkWHSI7FDqhdqjOZ393eGqcpI4DZFtebx3EB4M16LGLDArLg1lhhqpI5GEWHSI7BBPWxH9MZlMhkUPRaC1pwsuFFbgHxszpI5EEmLRIbJDqZklAFh0iP6IxlWJ/zzeHXIZsD4tB+tTs6WORBJh0SGyM1XVJhzjQoFEt9SrjTdeuL8DAODvGzNw/nK5xIlICiw6RHYmI6d2oUCfFioEebtIHYfIps0Y3A73hnqj3GjCC3FpMNaYpY5ETYxFh8jO/L6/FRcKJLoVhVyGfz/WHRoXJQ5l6/BOAreIaG5YdIjsTN2KyDxtRXR7Ajxd8NbDEQCAD3afxZ5TlyRORE2JRYfIjlgvFOgpbRgiOzIsTItJfYMBALO/OYTLZQaJE1FTYdEhsiM5JZUoKDXASS5DRKCn1HGI7MqrI7qgg18LXC4zcIuIZoRFh8iOpF25rLyzvwdcVAppwxDZmdotInpC7STH7lOX8L9fz0kdiZoAiw6RHeFpK6K701HrjldHdgEAvBV/Ahk5OokTUWNj0SGyI5aFAkM4EZnoTk3qE4zoLn6oNgnMWpuGcm4R4dBYdIjsBBcKJGoYMpkMSx6JgL/GGWcvl2PBpqNSR6JGxKJDZCd+XyhQjUAvLhRIdDc8XVV497HaLSK+TcnG9+k5UkeiRsKiQ2Qnrp6fw4UCie5e37YtMWNwewDAqxsykFlYIXEiagwsOkR2wrJQIOfnEDWYWYPboVeIF0oNNZgVl4ZqE7eIcDQsOkR2wHqhQBYdoobipJDj3493h7uzE9KzSvBuwimpI1EDY9EhsgPWCwVqpI5D5FACvVyxeFztFhErd/+GvWcuS5yIGhKLDpEdqLusvEuAB5yVXCiQqKGNiPDHE/cGQQgg9ut0FJUbpY5EDYRFh8gOpF7gaSuixvaPkV3RzrcFCkoNePHbQxCCW0Q4AhYdIjuQdmV+Tg+uiEzUaFxUCvz38R5QOcmx40QB3oo/yf2wHACLDpGNq6o24WiuHgCP6BA1ti4BHvj7iM4AgFW7f8PULw5CX1UtcSq6Gyw6RDbuSI4ONWaBVu5cKJCoKcREtcHbj3azHNkZs/xXnL5YKnUsukMsOkQ27vf5OVwokKipPBIZiO+ei0KAxhnnLpdj7Pu/Ij4jT+pYdAdYdIhsHNfPIZJGRKAnNs8cgL5tvVFuNOG51alY+uMJmDhvx66w6BDZsNqFAksAcEVkIim0bKHG6il9MGVAKADg/Z2/4enPDkBXwXk79oJFh8iGZRdX4tKVhQLDW3OhQCIpOCnk+PvILvjP493hrJRj96lLGLU8ESfy9VJHo9vAokNkw+pOW3XlQoFEkhvTvTXWPd8PgV4uyCyqwEPv78WWw7lSx6JbYNEhsmFpV05b9eD8HCKb0DVAg80zBmBAOx9UVpsw46s0LNp2HDXcDNRmsegQ2TDLRGTOzyGyGV5uKnz2l954dmBbAMAHe87iqU8PoJjbRtgkFh0iG1VVbcIxy0KBntKGISIrTgo55g/vjOUTesBFqUDimcsYtTwRGTk6qaPRNVh0iGzU4ezahQJ93dVo7cmFAols0ciIAGyY3g8hLV2RXVyJh1fuxca0HKlj0VVYdIhs1NXr53ChQCLb1UnrgU3TB2BQx1Yw1JgR+3U63th8DNWct2MT6l109uzZg1GjRiEgIAAymQwbN260evypp56CTCazuvXt29dqjMFgwMyZM+Hj4wM3NzeMHj0a2dnZVmOKi4sRExMDjUYDjUaDmJgYlJSUWI3JzMzEqFGj4ObmBh8fH8yaNQtGI8+RkmOwrIgc4iltECK6JY2rEp9M7o0Zf24HAPjfr+cQ88k+XC4zSJyM6l10ysvL0a1bNyxfvvwPxwwbNgx5eXmW27Zt26wej42NxYYNGxAXF4fExESUlZVh5MiRMJlMljETJkxAeno64uPjER8fj/T0dMTExFgeN5lMGDFiBMrLy5GYmIi4uDisW7cOc+bMqe9bIrI5VgsF8oorIrugkMswd2hHrJoUCTeVAslnizD6vUQczi6ROlrzJu4CALFhwwar+yZPnizGjBnzh88pKSkRSqVSxMXFWe7LyckRcrlcxMfHCyGEOHbsmAAgkpOTLWOSkpIEAHHixAkhhBDbtm0Tcrlc5OTkWMasXbtWqNVqodPpbiu/TqcTAG57PFFTySwsFyHztoh2r2wVlcYaqeMQUT2dyteLPy/dKULmbRHt/7ZNfHMgU+pIDqU+f78bZY7Orl274Ovriw4dOmDq1KkoKCiwPJaSkoLq6mpER0db7gsICEBYWBj27t0LAEhKSoJGo0GfPn0sY/r27QuNRmM1JiwsDAEBAZYxQ4cOhcFgQEpKyg1zGQwG6PV6qxuRLaqbn9MlQMOFAonsUHs/d2yc0R9DOvvCWGPGi98dxj++z4CxhvN2mlqDF53hw4djzZo1+Pnnn/HOO+/gwIEDGDx4MAyG2vOU+fn5UKlU8PKyPhzv5+eH/Px8yxhfX9/rXtvX19dqjJ+fn9XjXl5eUKlUljHXWrRokWXOj0ajQVBQ0F2/X6LGcPWO5URknzyclfgwphdih7QHAHyRdAETP05GQWmVxMmalwYvOo899hhGjBiBsLAwjBo1Cj/88ANOnTqFrVu33vR5QgirK0tudJXJnYy52vz586HT6Sy3rKys231bRE2K83OIHINcLkPskA74+MlecFc74cD5Yox6L9Fy1JYaX6NfXu7v74+QkBCcPn0aAKDVamE0GlFcbP3/5IKCAssRGq1Wi4sXL173WpcuXbIac+2Rm+LiYlRXV193pKeOWq2Gh4eH1Y3I1lQaTTied2WhQK6ITOQQhnTxw/cz+qOdbwtc1Bvw+AfJiNufKXWsZqHRi05hYSGysrLg7+8PAIiMjIRSqURCQoJlTF5eHjIyMtCvXz8AQFRUFHQ6Hfbv328Zs2/fPuh0OqsxGRkZyMvLs4zZvn071Go1IiMjG/ttETWaw9klqDEL+HmoEaBxljoOETWQtq1aYOP0/hjWVQujyYyX1x/B/PVHYKgx3frJdMfqXXTKysqQnp6O9PR0AMC5c+eQnp6OzMxMlJWVYe7cuUhKSsL58+exa9cujBo1Cj4+PnjooYcAABqNBlOmTMGcOXOwY8cOpKWlYdKkSQgPD8eQIUMAAJ07d8awYcMwdepUJCcnIzk5GVOnTsXIkSPRsWNHAEB0dDS6dOmCmJgYpKWlYceOHZg7dy6mTp3KIzVk164+bcWFAokcSwu1E1ZO6okXh3aETAas3Z+Jxz9MxkU95+00lnoXnYMHD6JHjx7o0aMHAGD27Nno0aMH/vGPf0ChUODIkSMYM2YMOnTogMmTJ6NDhw5ISkqCu7u75TXeffddjB07FuPHj0f//v3h6uqKzZs3Q6H4/eqSNWvWIDw8HNHR0YiOjkZERAS+/PJLy+MKhQJbt26Fs7Mz+vfvj/Hjx2Ps2LF4++237+bzIJLc1SsiE5HjkclkmP7ndvjfU73h4eyEtMwSjHwvEQfPF0kdzSHJhBBC6hBS0ev10Gg00Ol0PApENkEIgd5v/oTLZUasez4KkSHeUkciokZ0obAcz36ZghP5pXCSy/DaqC6Y1DeER3NvoT5/v7nXFZENySqqxOUyI5QKGboGaKSOQ0SNLKSlG9ZP64cREf6oMQv8/fujeOm7w6iq5rydhsKiQ2RDuFAgUfPjqnLC8id6YP7wTpDLgG9TsvHYB0nILamUOppDYNEhsiG/z8/xlDYIETUpmUyGZwfegy+e7gNPVyUOZesw6r1EJJ8tlDqa3WPRIbIhnIhM1LwNaO+DzTMGoIu/BwrLjZj48T58+us5NOPptHeNRYfIRlQYa3A8rxQAFwokas6CvF2x7vl+GNs9ACazwOubj2HON4c4b+cOsegQ2YjD2TqYuFAgEQFwUSnw7mPd8Y+RXaCQy7A+LQcPr9yLrKIKqaPZHRYdIhtx9WkrXlpKRDKZDE8PCMXqKX3Q0k2Fo7l6jF6eiF/PXJY6ml1h0SGyEakXSgBwfg4RWYu6pyU2zRyA8NYaFFdUI+aTffhoz1nO27lNLDpENkAIgbS6IzohntKGISKb09rTBd8+F4VHIgNhFsCb245jVlw6Kow1UkezeSw6RDYgq6gSheVcKJCI/pizUoGlj0Tgn2O6wkkuw+ZDuXj2yxTUmMxSR7NpLDpENqBufk5XLhRIRDchk8kQE9UGa/7aBy5KBX45fRn/3HJM6lg2jUWHyAZw/Rwiqo8+bVvi3ce6AQA+T7qAL5POSxvIhrHoENmAVM7PIaJ6GhbmjxeHdgQALNh8DL+cviRxItvEokMkMauFAnlEh4jqYdqgezCuZ2uYzALT1qTiTEGZ1JFsDosOkcTqFgrUejgjwNNF6jhEZEdkMhkWjQtHrxAvlFbVYMrnB1BcbpQ6lk1h0SGSGE9bEdHdUDsp8EFMJAK9XHChsALPrU6BsYZXYtVh0SGSGBcKJKK71bKFGv97qjdaqJ2w71wR/r4xgwsKXsGiQyShqxcK7MGiQ0R3oYOfO96b0ANyGfD1wSx8/Ms5qSPZBBYdIgllFlWgsNwIlUKOsNYeUschIjv3546+eHVEFwDAwh+O46djFyVOJD0WHSIJWRYKbO0BtRMXCiSiu/eX/m0woU8whABeiEvD8Ty91JEkxaJDJCHOzyGihiaTyfD66K7o364lyo0m/PXzg7hUapA6lmRYdIgkxBWRiagxKBVyrJgQibY+bsgpqcQzXx5EVbVJ6liSYNEhkkiFsQYn8q8sFMhLy4mogWlclfjkqd7QuCiRllmCl7473CyvxGLRIZLIoazahQL9Nc7w13ChQCJqeKE+blg5qSec5DJsOpSL934+I3WkJseiQyQRnrYioqbQ7x4f/HNsGABgWcIpbDmcK3GipsWiQySR39fP8ZQ2CBE5vCfuDcaUAaEAgDnfHMKhrBJpAzUhFh0iCQghkJpZAgDoGcIjOkTU+F55sDMGd/KFocaMqV8cRJ6uUupITYJFh0gCFworUHRlocCuAVwokIgan0Iuw38e746Ofu4oKDXgr58fRIWxRupYjY5Fh0gCdfNzwrhQIBE1IXdnJT6e3Ast3VQ4mqtHbFw6zGbHvhKLRYdIApyITERSCfJ2xQcxkVAp5Nh+7CKWbj8pdaRGxaJDJAHLisicn0NEEujVxhtvPRIOAFi56zd8l5ItcaLGw6JD1MTKDTU4kV+79wyP6BCRVB7qEYjpf74HADB//WEcOF8kcaLGwaJD1MQOZZfALIAAjTO0Gmep4xBRMzbngY4YHqZFtUng2S9TkFlYIXWkBseiQ9TE0q5cVt6Dp62ISGJyuQzvjO+GsNYeKCo3YsrnB6CvqpY6VoNi0SFqYqkXOBGZiGyHq8oJHz/ZG34eapwuKMPMr9JQYzJLHavBsOgQNSEhBNKurEjakysiE5GN0Gqc8fGTveGslGP3qUv419bjUkdqMCw6RE3ofN1CgU5ydA3QSB2HiMgiPFCDZeO7AwA+23seq5MvSBuogbDoEDWhutNW4a01UDnxXz8isi0PhvtjbnQHAMBrm44i8fRliRPdPX7TEjWh3xcK9JQ2CBHRH5j+53Z4qEdrmMwC09ak4LdLZVJHuissOkRNyLKRJyciE5GNkslkWDQuHJEhXtBX1WDKZwdQXG6UOtYdq3fR2bNnD0aNGoWAgADIZDJs3LjR6nEhBBYsWICAgAC4uLhg0KBBOHr0qNUYg8GAmTNnwsfHB25ubhg9ejSys61XZSwuLkZMTAw0Gg00Gg1iYmJQUlJiNSYzMxOjRo2Cm5sbfHx8MGvWLBiN9vv/DHJsZYYanKxbKJCXlhORDXNWKvBBTCRae7rgfGEFnl+TAmONfV6JVe+iU15ejm7dumH58uU3fHzJkiVYtmwZli9fjgMHDkCr1eKBBx5AaWmpZUxsbCw2bNiAuLg4JCYmoqysDCNHjoTJZLKMmTBhAtLT0xEfH4/4+Hikp6cjJibG8rjJZMKIESNQXl6OxMRExMXFYd26dZgzZ0593xJRkzicVbtQYGtPF/h5cKFAIrJtPi3U+OSpXnBTKZB8tgj/+D4DQtjhBqDiLgAQGzZssPxsNpuFVqsVixcvttxXVVUlNBqNWLVqlRBCiJKSEqFUKkVcXJxlTE5OjpDL5SI+Pl4IIcSxY8cEAJGcnGwZk5SUJACIEydOCCGE2LZtm5DL5SInJ8cyZu3atUKtVgudTndb+XU6nQBw2+OJ7sZ7O06JkHlbxPQ1KVJHISK6bTuO54vQl7eIkHlbxEd7fpM6jhCifn+/G3SOzrlz55Cfn4/o6GjLfWq1GgMHDsTevXsBACkpKaiurrYaExAQgLCwMMuYpKQkaDQa9OnTxzKmb9++0Gg0VmPCwsIQEBBgGTN06FAYDAakpKTcMJ/BYIBer7e6ETUVzs8hIns0uJMfXnmwMwDgzW3H8fOJixInqp8GLTr5+fkAAD8/P6v7/fz8LI/l5+dDpVLBy8vrpmN8fX2ve31fX1+rMdf+Hi8vL6hUKsuYay1atMgy50ej0SAoKOgO3iVR/QkhkFZ3xRXn5xCRnZkyIBRP3BsEIYCZX6VZNia2B41y1ZVMJrP6WQhx3X3XunbMjcbfyZirzZ8/HzqdznLLysq6aSaihnLucjmKK6qhdpKji7+H1HGIiOpFJpPhjTFhiGrbEuVGE6Z8dhCXywxSx7otDVp0tFotAFx3RKWgoMBy9EWr1cJoNKK4uPimYy5evP7Q2KVLl6zGXPt7iouLUV1dfd2RnjpqtRoeHh5WN6KmUHfaigsFEpG9UirkWDmpJ0J93JBTUolnvjiIqmrTrZ8osQb9xg0NDYVWq0VCQoLlPqPRiN27d6Nfv34AgMjISCiVSqsxeXl5yMjIsIyJioqCTqfD/v37LWP27dsHnU5nNSYjIwN5eXmWMdu3b4darUZkZGRDvi2iu5bK01ZE5AA8XVX4ZHIveDg7ITWzBC+vO2zzV2I51fcJZWVlOHPmjOXnc+fOIT09Hd7e3ggODkZsbCwWLlyI9u3bo3379li4cCFcXV0xYcIEAIBGo8GUKVMwZ84ctGzZEt7e3pg7dy7Cw8MxZMgQAEDnzp0xbNgwTJ06FR988AEA4JlnnsHIkSPRsWNHAEB0dDS6dOmCmJgYLF26FEVFRZg7dy6mTp3KIzVkc37fsdxT2iBERHepbasWWDkpEk/+bz82pueinW8LzBjcXupYf6y+l3Tt3LlTALjuNnnyZCFE7SXmr732mtBqtUKtVov77rtPHDlyxOo1KisrxYwZM4S3t7dwcXERI0eOFJmZmVZjCgsLxcSJE4W7u7twd3cXEydOFMXFxVZjLly4IEaMGCFcXFyEt7e3mDFjhqiqqrrt98LLy6kplFZVWy7NvKirlDoOEVGDWJ18XoTMq/1u23o4t0l/d33+fsuEsPFjTo1Ir9dDo9FAp9PxKBA1ml/PXMbEj/ehtacLfn15sNRxiIgazOubj+LTX8/DWSnHN89GISLQs0l+b33+fnNWJFEjs5y24vwcInIwr47ogkEdW6Gq2oypXxxEvq5K6kjXYdEhamR1E5F7BHlKG4SIqIEp5DK890QPdPBrgYt6A/76xQFUGGukjmWFRYeoEQkhkJZVAoBHdIjIMbk7K/HJ5N7wdlMhI0eP2V8fgtlsO7NiWHSIGtG5y+Uo4UKBROTggrxd8WFMJFQKOeKP5uOdhJNSR7Jg0SFqRFwokIiai15tvLH44XAAwPs7f8P61GyJE9XiNy9RI+JCgUTUnIzrGYhpg+4BALy87ggOni+SOBGLDlGj4kKBRNTczI3uiGFdtTCazHj2yxRkFVVImodFh6iRlBlqcOpiKQCgZzCP6BBR8yCXy7DssW4Ia+2BwnIj/u/rdEm3iWDRIWokh7JKYBZAa08X+Ho4Sx2HiKjJuKqc8PGTvdG7jRcWjQuHTCaTLEu997oiotvDhQKJqDnTapzxzbNRkpYcgEd0iBqNZSIy5+cQUTMldckBWHSIGoXVQoGcn0NEJBkWHaJGcPaqhQI7c6FAIiLJsOgQNYK6+TkRgVwokIhISvwGJmoEdSsi87QVEZG0WHSIGkFa3Y7lLDpERJJi0SFqYKVV1ThZt1BgiKe0YYiImjkWHaIGdihLByGAQC8X+LpzoUAiIimx6BA1sN/Xz+FpKyIiqbHoEDUwLhRIRGQ7WHSIGpDZLJBWd8UVt34gIpIciw5RAzp7uRy6ymo4K7lQIBGRLWDRIWpAdaetIlp7Qqngv15ERFLjNzFRA7Ksn8PLyomIbAKLDlEDSr1QAoBXXBER2QoWHaIGoq+qxqmCKwsFsugQEdkEFh2iBnIoqwRCAEHeLmjlrpY6DhERgUWHqMHwtBURke1h0SFqIFwRmYjI9rDoEDWA2oUCWXSIiGwNiw5RAzh7uQz6qho4K+Xo5O8udRwiIrqCRYeoAdTNz4kI5EKBRES2hN/IRA2A83OIiGwTiw5RA+CO5UREtolFh+gu6auqcbqgDAB3LCcisjUsOkR3KT2zdqHAYG9X+LTgQoFERLaERYfoLvG0FRGR7WLRIbpLqZklAHjaiojIFrHoEN0FLhRIRGTbWHSI7sJvl8pQWlUDF6UCnbRcKJCIyNY0eNFZsGABZDKZ1U2r1VoeF0JgwYIFCAgIgIuLCwYNGoSjR49avYbBYMDMmTPh4+MDNzc3jB49GtnZ2VZjiouLERMTA41GA41Gg5iYGJSUlDT02yG6qc2H8wAAEYEaOHGhQCIim9Mo38xdu3ZFXl6e5XbkyBHLY0uWLMGyZcuwfPlyHDhwAFqtFg888ABKS0stY2JjY7FhwwbExcUhMTERZWVlGDlyJEwmk2XMhAkTkJ6ejvj4eMTHxyM9PR0xMTGN8XaIbijx9GUs//k0AGB8ryCJ0xAR0Y04NcqLOjlZHcWpI4TAv//9b/ztb3/DuHHjAACff/45/Pz88NVXX+HZZ5+FTqfDJ598gi+//BJDhgwBAKxevRpBQUH46aefMHToUBw/fhzx8fFITk5Gnz59AAAfffQRoqKicPLkSXTs2LEx3haRRU5JJWbFpcEsgPG9AjGuZ2upIxER0Q00yhGd06dPIyAgAKGhoXj88cdx9uxZAMC5c+eQn5+P6Ohoy1i1Wo2BAwdi7969AICUlBRUV1dbjQkICEBYWJhlTFJSEjQajaXkAEDfvn2h0WgsY27EYDBAr9db3Yjqy1BjwrTVKSgqNyKstQfeGBMGmUwmdSwiIrqBBi86ffr0wRdffIEff/wRH330EfLz89GvXz8UFhYiPz8fAODn52f1HD8/P8tj+fn5UKlU8PLyuukYX1/f6363r6+vZcyNLFq0yDKnR6PRICiIpxuo/l7ffAyHsnXwdFVi5cRIOCsVUkciIqI/0OBFZ/jw4Xj44YcRHh6OIUOGYOvWrQBqT1HVufa/foUQt/wv4mvH3Gj8rV5n/vz50Ol0lltWVtZtvSeiOt8ezMJX+zIhkwH/fqw7grxdpY5EREQ30eiXibi5uSE8PBynT5+2zNu59qhLQUGB5SiPVquF0WhEcXHxTcdcvHjxut916dKl644WXU2tVsPDw8PqRnS7MnJ0eHVjBgDg/4Z0wKCO1x9VJCIi29LoRcdgMOD48ePw9/dHaGgotFotEhISLI8bjUbs3r0b/fr1AwBERkZCqVRajcnLy0NGRoZlTFRUFHQ6Hfbv328Zs2/fPuh0OssYooZUUmHE82tSYKgxY3AnX8z4czupIxER0W1o8Kuu5s6di1GjRiE4OBgFBQX417/+Bb1ej8mTJ0MmkyE2NhYLFy5E+/bt0b59eyxcuBCurq6YMGECAECj0WDKlCmYM2cOWrZsCW9vb8ydO9dyKgwAOnfujGHDhmHq1Kn44IMPAADPPPMMRo4cySuuqMGZzQKxX6cjq6gSwd6ueHd8d8jlnHxMRGQPGrzoZGdn44knnsDly5fRqlUr9O3bF8nJyQgJCQEAvPTSS6isrMS0adNQXFyMPn36YPv27XB3/31V2XfffRdOTk4YP348Kisrcf/99+Ozzz6DQvH7pM81a9Zg1qxZlquzRo8ejeXLlzf02yHCf38+jV0nL0HtJMeqSZHQuCqljkRERLdJJoQQUoeQil6vh0ajgU6n43wduqGdJwrw9OcHIATwzqPd8HBkoNSRiIiavfr8/eaa9UR/ILOwAi/EpUEIYFLfYJYcIiI7xKJDdANV1SY8tzoF+qoadA/yxN9HdpE6EhER3QEWHaJrCCHwtw0ZOJanR0s3FVZO6gm1ExcFJCKyRyw6RNf4an8m1qVmQy4D3nuiB/w1LlJHIiKiO8SiQ3SV9KwSvL7pGADgpWGd0K+dj8SJiIjobrDoEF1RWGbAtNUpMJrMGNrVD8/e11bqSEREdJdYdIgAmMwCs+LSkKurQlsfN7z9aDfuSE5E5ABYdIgAvLP9JH49UwhXlQKrYiLh7sxFAYmIHAGLDjV7Px7Nx4pdvwEA3no4Ah383G/xDCIishcsOtSsnb1UhrnfHAIAPN0/FKO6BUiciIiIGhKLDjVbFcYaPLc6BaWGGvRu44X5D3aSOhIRETUwFh1qloQQeHndEZy6WIZW7mq8P6EnlAr+60BE5Gj4zU7N0md7z2PToVw4yWVYMbEnfD2cpY5ERESNgEWHmp0D54vw5tbjAIBXHuyM3m28JU5ERESNhUWHmpUCfRWmrUlFjVlgVLcA/KV/G6kjERFRI2LRoWaj2mTGjK/ScKnUgA5+LbB4XDgXBSQicnAsOtRsvPXDCew/X4QWaiesmhQJN7WT1JGIiKiRsehQs7DlcC4+TjwHAHj70W5o26qFxImIiKgpsOiQwzt9sRQvfXcYAPD8oHswLEwrcSIiImoqLDrk0EqrqvHs6hRUGE3od09LzHmgg9SRiIioCbHokMMSQuDFbw/j7KVy+Guc8d8nesCJiwISETUr/NYnh/XhnrOIP5oPpaJ2UUCfFmqpIxERURNj0SGHtPfMZbwVfwIA8NqorugR7CVxIiIikgKLDjmcPF0lZq5Ng1kAD/cMxMQ+wVJHIiIiibDokEMx1Jjw/OpUFJYb0cXfA28+FMZFAYmImjEWHXIo/9pyHOlZJfBwrl0U0FmpkDoSERFJiEWHHMb61Gx8mXwBAPCfx3sguKWrxImIiEhqLDrkEI7l6vHKhiMAgBfub48/d/KVOBEREdkCFh2ye7qKajy3OgVV1WYM6tgKL9zfXupIRERkI1h0yK6ZzQKzv0lHZlEFAr1c8O/HukMu5+RjIiKqxaJDdu39nWew40QBVE5yrJoUCU9XldSRiIjIhrDokN3afeoSlv10CgDwr7FhCGutkTgRERHZGhYdsktZRRV4IS4NQgBP3BuM8b2CpI5EREQ2iEWH7E5VtQnPr0lBSUU1ugVqsGB0F6kjERGRjWLRIbvz2vdHkZGjh5erEismRULtxEUBiYjoxlh0yK7E7c/E1wezIJcB7z3RE609XaSORERENoxFh+zG4ewS/OP7owCAOdEdMaC9j8SJiIjI1rHokF0oKjfi+dWpMJrMeKCLH54feI/UkYiIyA6w6JDNM5kFXohLQ05JJdq0dMU747txUUAiIrotLDpk8/790yn8cvoyXJQKrIqJhIezUupIRERkJ+y+6KxYsQKhoaFwdnZGZGQkfvnlF6kjUQP66dhFvPfzGQDA4ofD0UnrIXEiIiKyJ05SB7gbX3/9NWJjY7FixQr0798fH3zwAYYPH45jx44hODhY6njNlhACRpMZVUYzKqprUGk0obLahKpqEyqNZlRWX/nZaEKFsQaV1earHjdZPb7vXBEA4Kl+bTCme2uJ3xkREdkbmRBCSB3iTvXp0wc9e/bEypUrLfd17twZY8eOxaJFi275fL1eD41GA51OBw+PhjtSUGaoQUmFscFer7EIARhqrMtHpfFK4bi6dFxTPir/4PGri4q5Af+pigzxwtqpfaFysvsDkERE1ADq8/fbbo/oGI1GpKSk4OWXX7a6Pzo6Gnv37r3hcwwGAwwGg+VnvV7fKNk2pefilQ1HGuW17Y2TXAYXlQIuSoXl/zorr/q57rErP1seU8rhqnKCh4sTBnX0ZckhIqI7YrdF5/LlyzCZTPDz87O638/PD/n5+Td8zqJFi/D66683ejaFHFDbyR9m52tKhuvVZURVWzhclAo4qxRwVTrBRSW/5vEblxbnK/9bqbCPz4GIiByT3RadOjKZ9WXGQojr7qszf/58zJ492/KzXq9HUFDDbwb5WO9gPNabc4SIiIikZrdFx8fHBwqF4rqjNwUFBdcd5amjVquhVqubIh4RERHZALs9r6BSqRAZGYmEhASr+xMSEtCvXz+JUhEREZEtsdsjOgAwe/ZsxMTEoFevXoiKisKHH36IzMxMPPfcc1JHIyIiIhtg10XnscceQ2FhId544w3k5eUhLCwM27ZtQ0hIiNTRiIiIyAbY9To6d6ux1tEhIiKixlOfv992O0eHiIiI6FZYdIiIiMhhsegQERGRw2LRISIiIofFokNEREQOi0WHiIiIHBaLDhERETksFh0iIiJyWCw6RERE5LDseguIu1W3KLRer5c4CREREd2uur/bt7O5Q7MuOqWlpQCAoKAgiZMQERFRfZWWlkKj0dx0TLPe68psNiM3Nxfu7u6QyWRSx2lyer0eQUFByMrK4l5fd4GfY8Pg59gw+Dk2DH6ODaOxPkchBEpLSxEQEAC5/OazcJr1ER25XI7AwECpY0jOw8OD/yI3AH6ODYOfY8Pg59gw+Dk2jMb4HG91JKcOJyMTERGRw2LRISIiIofFotOMqdVqvPbaa1Cr1VJHsWv8HBsGP8eGwc+xYfBzbBi28Dk268nIRERE5Nh4RIeIiIgcFosOEREROSwWHSIiInJYLDpERETksFh0mplFixahd+/ecHd3h6+vL8aOHYuTJ09KHcvuLVq0CDKZDLGxsVJHsTs5OTmYNGkSWrZsCVdXV3Tv3h0pKSlSx7IrNTU1ePXVVxEaGgoXFxe0bdsWb7zxBsxms9TRbNqePXswatQoBAQEQCaTYePGjVaPCyGwYMECBAQEwMXFBYMGDcLRo0elCWvDbvY5VldXY968eQgPD4ebmxsCAgLw5JNPIjc3t8nyseg0M7t378b06dORnJyMhIQE1NTUIDo6GuXl5VJHs1sHDhzAhx9+iIiICKmj2J3i4mL0798fSqUSP/zwA44dO4Z33nkHnp6eUkezK2+99RZWrVqF5cuX4/jx41iyZAmWLl2K9957T+poNq28vBzdunXD8uXLb/j4kiVLsGzZMixfvhwHDhyAVqvFAw88YNknkWrd7HOsqKhAamoq/v73vyM1NRXr16/HqVOnMHr06KYLKKhZKygoEADE7t27pY5il0pLS0X79u1FQkKCGDhwoHjhhRekjmRX5s2bJwYMGCB1DLs3YsQI8fTTT1vdN27cODFp0iSJEtkfAGLDhg2Wn81ms9BqtWLx4sWW+6qqqoRGoxGrVq2SIKF9uPZzvJH9+/cLAOLChQtNkolHdJo5nU4HAPD29pY4iX2aPn06RowYgSFDhkgdxS5t2rQJvXr1wqOPPgpfX1/06NEDH330kdSx7M6AAQOwY8cOnDp1CgBw6NAhJCYm4sEHH5Q4mf06d+4c8vPzER0dbblPrVZj4MCB2Lt3r4TJ7J9Op4NMJmuyI7fNelPP5k4IgdmzZ2PAgAEICwuTOo7diYuLQ2pqKg4cOCB1FLt19uxZrFy5ErNnz8Yrr7yC/fv3Y9asWVCr1XjyySeljmc35s2bB51Oh06dOkGhUMBkMuHNN9/EE088IXU0u5Wfnw8A8PPzs7rfz88PFy5ckCKSQ6iqqsLLL7+MCRMmNNlmqSw6zdiMGTNw+PBhJCYmSh3F7mRlZeGFF17A9u3b4ezsLHUcu2U2m9GrVy8sXLgQANCjRw8cPXoUK1euZNGph6+//hqrV6/GV199ha5duyI9PR2xsbEICAjA5MmTpY5n12QymdXPQojr7qPbU11djccffxxmsxkrVqxost/LotNMzZw5E5s2bcKePXsQGBgodRy7k5KSgoKCAkRGRlruM5lM2LNnD5YvXw6DwQCFQiFhQvvg7++PLl26WN3XuXNnrFu3TqJE9unFF1/Eyy+/jMcffxwAEB4ejgsXLmDRokUsOndIq9UCqD2y4+/vb7m/oKDguqM8dGvV1dUYP348zp07h59//rnJjuYAvOqq2RFCYMaMGVi/fj1+/vlnhIaGSh3JLt1///04cuQI0tPTLbdevXph4sSJSE9PZ8m5Tf37979ueYNTp04hJCREokT2qaKiAnK59de5QqHg5eV3ITQ0FFqtFgkJCZb7jEYjdu/ejX79+kmYzP7UlZzTp0/jp59+QsuWLZv09/OITjMzffp0fPXVV/j+++/h7u5uOQ+t0Wjg4uIicTr74e7uft28Jjc3N7Rs2ZLznerh//7v/9CvXz8sXLgQ48ePx/79+/Hhhx/iww8/lDqaXRk1ahTefPNNBAcHo2vXrkhLS8OyZcvw9NNPSx3NppWVleHMmTOWn8+dO4f09HR4e3sjODgYsbGxWLhwIdq3b4/27dtj4cKFcHV1xYQJEyRMbXtu9jkGBATgkUceQWpqKrZs2QKTyWT5u+Pt7Q2VStX4AZvk2i6yGQBuePv000+ljmb3eHn5ndm8ebMICwsTarVadOrUSXz44YdSR7I7er1evPDCCyI4OFg4OzuLtm3bir/97W/CYDBIHc2m7dy584bfh5MnTxZC1F5i/tprrwmtVivUarW47777xJEjR6QNbYNu9jmeO3fuD//u7Ny5s0nyyYQQovHrFBEREVHT4xwdIiIiclgsOkREROSwWHSIiIjIYbHoEBERkcNi0SEiIiKHxaJDREREDotFh4iIiBwWiw4RERE5LBYdIqJrLFiwAN27d5c6BhE1ABYdImrWZDIZNm7cKHUMImokLDpERETksFh0iMgmDBo0CDNnzkRsbCy8vLzg5+eHDz/8EOXl5fjLX/4Cd3d33HPPPfjhhx8sz9m9ezfuvfdeqNVq+Pv74+WXX0ZNTY3Va86aNQsvvfQSvL29odVqsWDBAsvjbdq0AQA89NBDkMlklp/rfPnll2jTpg00Gg0ef/xxlJaWNuZHQESNgEWHiGzG559/Dh8fH+zfvx8zZ87E888/j0cffRT9+vVDamoqhg4dipiYGFRUVCAnJwcPPvggevfujUOHDmHlypX45JNP8K9//eu613Rzc8O+ffuwZMkSvPHGG0hISAAAHDhwAADw6aefIi8vz/IzAPz222/YuHEjtmzZgi1btmD37t1YvHhx030YRNQguHs5EdmEQYMGwWQy4ZdffgEAmEwmaDQajBs3Dl988QUAID8/H/7+/khKSsLmzZuxbt06HD9+HDKZDACwYsUKzJs3DzqdDnK5/LrXBIB7770XgwcPtpQWmUyGDRs2YOzYsZYxCxYswNKlS5Gfnw93d3cAwEsvvYQ9e/YgOTm5KT4OImogPKJDRDYjIiLC8r8VCgVatmyJ8PBwy31+fn4AgIKCAhw/fhxRUVGWkgMA/fv3R1lZGbKzs2/4mgDg7++PgoKCW2Zp06aNpeTU53lEZFtYdIjIZiiVSqufZTKZ1X11pcZsNkMIYVVyAKDuAPXV99/oNc1m8x1luZ3nEZFtYdEhIrvUpUsX7N27F1effd+7dy/c3d3RunXr234dpVIJk8nUGBGJyAaw6BCRXZo2bRqysrIwc+ZMnDhxAt9//z1ee+01zJ49G3L57X+1tWnTBjt27EB+fj6Ki4sbMTERSYFFh4jsUuvWrbFt2zbs378f3bp1w3PPPYcpU6bg1VdfrdfrvPPOO0hISEBQUBB69OjRSGmJSCq86oqIiIgcFo/oEBERkcNi0SEiIiKHxaJDREREDotFh4iIiBwWiw4RERE5LBYdIiIiclgsOkREROSwWHSIiIjIYbHoEBERkcNi0SEiIiKHxaJDREREDuv/AZa3Sdv8QoL9AAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sum_deaths_per_day=Brazil_data.groupby('month').sum()['deaths']\n",
    "\n",
    "sum_deaths_per_day.plot()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "2ce414d1",
   "metadata": {},
   "source": [
    "The sum of COVID-19 deaths in Brazil is 181,402 in 2020. This line graph is giving a vizualization of the deaths spread out by month.  We thought this would give a better undertsanding on how many deaths were in each month of 2020.  Just like the number of cases, the deaths also spiked around June through August and these months were much higher than months before and after.  June through August was when Brazil was hit the hardest with COVID-19 and it is important to recognize this when analyzing the data. "
   ]
  },
  {
   "cell_type": "markdown",
   "id": "a4033f9d",
   "metadata": {},
   "source": [
    "# Question 4: What was the number of cases compared with deaths in Brazil by COVID-19 over time?"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "id": "f30f5bc3",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot: xlabel='cases', ylabel='deaths'>"
      ]
     },
     "execution_count": 33,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 640x480 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "Brazil_data.plot.scatter(x='cases',y='deaths',c= 'month')"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "ffed0251",
   "metadata": {},
   "source": [
    "The scatterplot above is demonstrating the amount of deaths related to the number of COVID-19 cases in Brazil. The use of colors helps to determine whether the cases and deaths took place in earlier or later months.  The darker the dot the later the month in the year. The largest amount of deaths in Brazil happened mostly between the months of Febuary and August reaching up to around 1000 deaths with multiple dots clustered around the area.  The numbers start to decrease as it moves into September through December. This is a great representation of the relationship between the number of cases and the number of deaths in Brazil throughout the year of 2020."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "59f239b8",
   "metadata": {},
   "source": [
    "# Conclusions and Limitations"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "3812a5d5",
   "metadata": {},
   "source": [
    "In conclusion, Brazil was hit by COVID-19 pretty hard and they experienced the second highest amount of cases in the world below the United States. The months of June through August were when Brazil experienced the most cases and deaths from COVID-19. Comparing the data of cases and deaths through a scatter plot helped vizualize how the number of cases are comparing to the number of deaths through the months of 2020. Regarding limitations, we were limited to only having access to the COVID-19 data in 2020 so it isnt including years prior or after 2020. This leaves out the true number of deaths and cases that Brazil had all throughout COVID-19. There also could be potential gaps in the data that need to be recognized. Improvements could include adding data from more months throughout other years than just 2020. Looking more in depth into the effect that COVID-19 had on Brazil could improve this project as well. Also by having more skills in programming because we only really know the basics in programming. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "56d164fa",
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "conda_python3",
   "language": "python",
   "name": "conda_python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.10.8"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}