gabrielle_oficina4.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Oficina Aula 4.1"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Aluna: Gabrielle F Campos"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Olá, estudante!\n",
    "\n",
    "Nesta oficina, você continuará a analisar o conjunto de dados dos passageiros do Titanic. Esse conjunto de dados é bastante famoso em ciência de dados, sendo disponibilizado diretamente pela biblioteca seaborn sem a necessidade de baixar os dados para a sua máquina. Portanto, crie um Jupyter Notebook, para responder às questões."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "1 - Importe as bibliotecas pandas, matplotlib e seaborn e use a palavra mágica inline, para exibir as visualizações no notebook. Depois, carregue os dados em um DataFrame. Os dados podem ser carregados pelo seaborn, utilizando a função load_dataset(‘titanic’);"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import matplotlib.pyplot as plt\n",
    "import seaborn as sns\n",
    "%matplotlib inline\n",
    "sns.set(style=\"darkgrid\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "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>survived</th>\n",
       "      <th>pclass</th>\n",
       "      <th>sex</th>\n",
       "      <th>age</th>\n",
       "      <th>sibsp</th>\n",
       "      <th>parch</th>\n",
       "      <th>fare</th>\n",
       "      <th>embarked</th>\n",
       "      <th>class</th>\n",
       "      <th>who</th>\n",
       "      <th>adult_male</th>\n",
       "      <th>deck</th>\n",
       "      <th>embark_town</th>\n",
       "      <th>alive</th>\n",
       "      <th>alone</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>male</td>\n",
       "      <td>22.0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>7.2500</td>\n",
       "      <td>S</td>\n",
       "      <td>Third</td>\n",
       "      <td>man</td>\n",
       "      <td>True</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Southampton</td>\n",
       "      <td>no</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>female</td>\n",
       "      <td>38.0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>71.2833</td>\n",
       "      <td>C</td>\n",
       "      <td>First</td>\n",
       "      <td>woman</td>\n",
       "      <td>False</td>\n",
       "      <td>C</td>\n",
       "      <td>Cherbourg</td>\n",
       "      <td>yes</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "      <td>female</td>\n",
       "      <td>26.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>7.9250</td>\n",
       "      <td>S</td>\n",
       "      <td>Third</td>\n",
       "      <td>woman</td>\n",
       "      <td>False</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Southampton</td>\n",
       "      <td>yes</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>female</td>\n",
       "      <td>35.0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>53.1000</td>\n",
       "      <td>S</td>\n",
       "      <td>First</td>\n",
       "      <td>woman</td>\n",
       "      <td>False</td>\n",
       "      <td>C</td>\n",
       "      <td>Southampton</td>\n",
       "      <td>yes</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>male</td>\n",
       "      <td>35.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>8.0500</td>\n",
       "      <td>S</td>\n",
       "      <td>Third</td>\n",
       "      <td>man</td>\n",
       "      <td>True</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Southampton</td>\n",
       "      <td>no</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   survived  pclass     sex   age  sibsp  parch     fare embarked  class  \\\n",
       "0         0       3    male  22.0      1      0   7.2500        S  Third   \n",
       "1         1       1  female  38.0      1      0  71.2833        C  First   \n",
       "2         1       3  female  26.0      0      0   7.9250        S  Third   \n",
       "3         1       1  female  35.0      1      0  53.1000        S  First   \n",
       "4         0       3    male  35.0      0      0   8.0500        S  Third   \n",
       "\n",
       "     who  adult_male deck  embark_town alive  alone  \n",
       "0    man        True  NaN  Southampton    no  False  \n",
       "1  woman       False    C    Cherbourg   yes  False  \n",
       "2  woman       False  NaN  Southampton   yes   True  \n",
       "3  woman       False    C  Southampton   yes  False  \n",
       "4    man        True  NaN  Southampton    no   True  "
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "titanic = sns.load_dataset(\"titanic\")\n",
    "titanic.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "2 - Crie uma visualização que mostre a distribuição do valor da passagem (“fare”), de acordo com a cidade na qual o passageiro embarcou (\"embark_town\"). Você pode escolher a técnica que julgar mais adequada;"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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WmzZtwrRp0xAWFgZXV1ckJSWVu5/JZELr1q3xww8/mB9LS0szJz6VOW5F592t9fr06YP33nvP4vl5eXlh9+7dlT4/b3+fVSpVhZ/fW88bOzs7i+dy6/tX1vfqje+177//Hg4ODgBKboC4/VI01SzelUmVFhcXhw8//BCzZs2yKD937hxCQ0PRunVrzJkzB4899hhOnz4NoOTLpTIJD3Dz1/LZs2eRkJCALl26wN3dHRcvXoROp4PBYMCuXbus9vPz84MkSTh06BAAICYmBo8//jjOnDkDd3d3/Otf/0L//v3NSZnJZMKAAQOwefNm86/5DRs2oEePHlZfmgMGDMC2bdug0+mg0+nMd6U6OTmhS5cu2LhxI4CSsT7btm1D3759reKzs7PDmDFjsHDhQgwfPhwODg7Iy8vD6dOn8dxzz2H48OFITU1FQkKCeQzWrcf/7rvvYDAYIMsyNm7ciH79+lX4Wg4YMAA//vgjZFlGbm4ufv/9dwBAfHw8CgoK8PTTT2Pw4MGIjo6GXq+3Ou4NN+6Qu3btGg4dOoTg4GAcOnQIgwYNwtSpU9GpUyfs2bMHJpMJQEliFhsbi4kTJ+KNN95AXl4eMjIyyiz/448/MHfuXPOv8VOnTsFkMqFbt27mXk4A2LVrF/Ly8iBJEvr3749ffvkF6enpAIDvvvsOjz76aIWvSVmCg4MRHh6OvLw8yLJsccNL//79sXHjRvNr9Morr5h7UG71xx9/4NFHH8X48ePh4eGByMhImEwmODk5oWPHjubXMSUlBVOmTIGzszNUKhV+++03ACVJwq5du0o9fyqK75tvvoEQAnq9Hps2bSq1jT59+mDr1q2QZRl6vR5PPfUUjh49Wun9K6us97Oy8dzQo0cPXLp0yfz+3+gBv3GMCRMm4KGHHkKrVq2wd+9emEwmuLm5oWPHjubk6+zZs7hw4QIAIDAwEPHx8eZjxMbGYsSIEUhLS7OIq7zjVva869OnDw4dOoTLly8DACIiIjB27FhotdqqvJTYu3cvcnNzYTKZsGnTJgQHB1fp8xsSEoLw8HDk5uZClmWLu13d3NzMd6inpaXhyJEjAEq+1wIDA/Hll18CKOkRnDJlivn7g2oHe8yoTFqtFuPGjQNQ0lthZ2eHZ555xnzJ8Ib27dtj1KhRmDRpEhwdHWFvb4/FixcDKBlA/s4775Ta03W7xMREjB8/HpIk4Z133oGrqyv69euHHj16YNSoUfD09ESvXr1w/vx5i/00Gg3Wrl2L1157DbNmzULnzp2xbt06+Pv7my8hSpKEnj17wt3dHfHx8XjwwQeRkpKChx56CLIso0WLFli9erVVTJMnT0ZCQgJCQ0OtBl6vXr0aS5cuxZYtW6DX6xEWFoaJEyeW+tweeughfPPNN3jttdcAAM7Ozpg9ezYmTJgAR0dHNG7cGN26dUN8fDx8fHzM+/3f//0f3nrrLYwfPx5GoxGdO3fGK6+8UuFrOX/+fLz66qsYNWoU3N3dzb2c7dq1Q0hICEaNGgWNRmO+bBMfHw9fX1+rdpKSkjBx4kRotVosXrwYfn5+mDx5Mp599lmEhYXBaDSiX79++O233yDLMp577jm8+eabeO+99yBJEubNmwdvb+8yyxcsWIC5c+fC0dERTk5O6NGjBxISEuDq6op33nkHL774IhQKBTp16gSVSgUHBwf0798fTzzxBGbNmgVJkuDk5IR169ZZ9UBV1sCBA3H+/HlMmjQJzs7OaN++Pa5fvw4A+Ne//oW33noLEyZMgMlkQkBAQKnTpcydOxerVq3C+++/D7VajW7dupkvXf3nP//B66+/jg0bNkCSJCxfvhxNmzbFhx9+iGXLlmHt2rUwmUyYO3cuevfubTW9Q3nxLV68GMuWLUNYWBgMBgMGDBhQ6kDtefPmYfny5Rg3bhxMJhNGjx6N4cOHo0ePHpXav7LKej8rG8/evXsBAO7u7li9ejWee+45qNVq9OjRw7zvrFmzsGTJEvz4448ASpKuGwnYO++8g5deegnff/89fH194efnZ25vzZo1WLVqFXQ6HYQQWLVqFby9vS3iKu+4lT3v2rRpg6VLl+KZZ54x95r+97//NV/ur6wbP3Tz8vIQFBSE2bNnQ61Wl/n5vf1HZa9evTBz5kxMnToVdnZ25kucQMmQiOeeew4jRoyAt7c3evfubX5s9erVeOONNxAWFga9Xo/Q0FCMHTu2SrHT3ZFEWdcwiO4x8fHxWL58OWbPnl3m2CuqvMGDB+P999/HAw88UOvHLigowIcffoj58+fDwcEBZ8+exZw5c3Dw4ME7TsCI6rPw8HBs3LjRPD6RbBd7zOi+sXTpUiQmJqKwsLCuQ6G75OTkBLVajQcffBAqlQoqlcrc20ZEdD9jjxkRERGRjeDgfyIiIiIbwcSMiIiIyEYwMSMiIiKyEffN4P/r1wshyxwuR0RERLZLoZDg5lb29Cn3TWImy4KJGREREd3TeCmTiIiIyEYwMSMiIiKyEUzMiIiIiGwEEzMiIiIiG8HEjIiIiMhGMDEjIiIishFMzIiIiIhsxH0zjxkRUXURshGGM7/DlHYRysatoe40DJKi7K9LY2IMDBciITk0hKbzSCicPGC4fATGuKNQNPSEussoKOwb1uIzIKJ7FRMzIqLb6CK/heGvvQAAY9wxyLlpsB/wWKl1jYmnUfzruwBKJrg2Xj0BTbex0B348mad5LNoMPH1mg6biO4DvJRJRHQbw4VDt21Hll33YiRuJGUAIAqyYDizx6KOnBkPU3ZStcZIRPcnJmZERLeRHJwttx2dy6hpXbekvsttBQpI9k7VEhsR3d+YmBER3cau92RA+fdID4WqZLsMms4jITX0NG+r2wXDrs8Ui4RNEzgGCkfXmgqXiO4jkhDivlj5OyurgIuYE1G1kYvzIGfEQdGoJRS394DdRpiMMKVegOTQEEp3n5Iyow6mlAtQNPSEwrVJbYRMRPcAhUKCh0fZPeg1mpjNmDED2dnZUKlKfnkuXboUhYWFWLFiBXQ6HUaNGoUFCxYAAGJjY/Hyyy+jsLAQ3bt3x+uvv27erzKYmBEREZGtqygxq7G7MoUQuHr1Kvbt22dOsLRaLUaOHIkNGzagadOmmDNnDiIiIjBw4EA8//zzWLZsGQIDA7Fo0SJs2rQJU6dOranwiIiIiGxOjY0xu3LlCgBg1qxZGDt2LL755hvExMSgRYsW8PHxgUqlQlhYGMLDw5GcnAytVovAwEAAwMSJExEeHl5ToRERERHZpBrrMcvLy0OfPn3wyiuvwGAwYObMmXj88cfh6XlzkKyXlxfS0tKQnp5uUe7p6Ym0tLQqHa+8bkEiIiKie0GNJWZdu3ZF165dzdsPPvgg1qxZg6CgIHOZEAKSJEGWZUiSZFVeFRxjRkRERLauojFmNXYp89ixYzh8+LB5WwiB5s2bIyMjw1yWkZEBLy8vNGnSxKI8MzMTXl5eNRUaERERkU2qscQsPz8fq1atgk6nQ0FBAbZu3YpnnnkGcXFxiI+Ph8lkwo4dOxAcHIzmzZvDzs4Ox48fBwBs374dwcHBNRUaERERkU2qsUuZgwYNwqlTpzB+/HjIsoypU6eia9euWLlyJebPnw+dToeBAwdi5MiRAIDVq1dj8eLFKCgoQMeOHTFz5syaCo2IiIjIJnGCWSIiIqJaUmdjzIiIiIioapiYEREREdkIJmZERERENoKJGREREZGNYGJGREREZCOYmBERERHZCCZmRERERDaCiRkRERGRjWBiRkRERGQjmJgRERER2QgmZkREREQ2gokZERERkY1gYkZERERkI5iYEREREdkIJmZERERENoKJGREREZGNYGJGREREZCOYmBERERHZCCZmRERERDaCiRkRERGRjWBiRkRERGQjmJgRERER2QgmZkREREQ2gokZERERkY1gYkZERERkI5iYEREREdkIJmZERERENoKJGREREZGNYGJGREREZCOYmBERERHZCCZmRERERDaCiRkRERGRjWBiRkRERGQjmJgRERER2QgmZkREREQ2gokZERERkY1gYkZERERkI5iYEREREdkIJmZERERENqLGE7O33noLCxcuBABERkYiLCwMw4cPx7vvvmuuExsbi4kTJ2LEiBF4+eWXYTQaazosIiIiIptTo4nZ4cOHsXXrVgCAVqvFokWL8OGHH2Lnzp04c+YMIiIiAADPP/88lixZgl27dkEIgU2bNtVkWEREREQ2qcYSs5ycHLz77rt48sknAQAxMTFo0aIFfHx8oFKpEBYWhvDwcCQnJ0Or1SIwMBAAMHHiRISHh9dUWEREREQ2S1VTDS9ZsgQLFixASkoKACA9PR2enp7mx728vJCWlmZV7unpibS0tCofz8PD6e6DJiIiIqpDNZKY/fDDD2jatCn69OmDLVu2AABkWYYkSeY6QghIklRmeVVlZRVAlsXdB09ERERUQxQKqdzOpBpJzHbu3ImMjAyMGzcOubm5KCoqQnJyMpRKpblORkYGvLy80KRJE2RkZJjLMzMz4eXlVRNhEREREdm0GknMvvzyS/O/t2zZgiNHjuD111/H8OHDER8fD29vb+zYsQOTJk1C8+bNYWdnh+PHjyMoKAjbt29HcHBwTYRFREREZNNqbIzZ7ezs7LBy5UrMnz8fOp0OAwcOxMiRIwEAq1evxuLFi1FQUICOHTti5syZtRUWERERkc2QhBD3xcAsjjEjIiIiW1fRGDPO/E9ERERkI5iYEREREdkIJmZERERENoKJGREREZGNYGJGREREZCOYmBERERHZCCZmRERERDaCiRkRERGRjWBiRkRERGQjmJgRERER2QgmZkREREQ2gokZERERkY1gYkZERERkI5iYEREREdkIJmZERERENoKJGREREZGNYGJGREREZCOYmBERERHZCCZmRERERDaCiRkRERGRjWBiRkRERGQjmJgRERER2QgmZkREREQ2gokZERERkY1gYkZERERkI5iYEREREdkIJmZERERENoKJGREREZGNYGJGREREZCOYmBERERHZCCZmRERERDaCiRkRERGRjWBiRkRERGQjmJgRERER2QgmZkREREQ2gokZERERkY1gYkZERERkI5iYEREREdkIJmZERERENqJGE7P3338fo0ePxpgxY/Dll18CACIjIxEWFobhw4fj3XffNdeNjY3FxIkTMWLECLz88sswGo01GRoRERGRzamxxOzIkSOIiorCTz/9hM2bN2PDhg04d+4cFi1ahA8//BA7d+7EmTNnEBERAQB4/vnnsWTJEuzatQtCCGzatKmmQiMiIiKySTWWmPXs2RNff/01VCoVsrKyYDKZkJeXhxYtWsDHxwcqlQphYWEIDw9HcnIytFotAgMDAQATJ05EeHh4TYVGREREZJNUNdm4Wq3GmjVr8MUXX2DkyJFIT0+Hp6en+XEvLy+kpaVZlXt6eiItLa1Kx/LwcKq2uImIiIjqQo0mZgDw1FNP4YknnsCTTz6Jq1evQpIk82NCCEiSBFmWSy2viqysAsiyqLa4iYiIiKqbQiGV25lUY5cyL1++jNjYWACAg4MDhg8fjujoaGRkZJjrZGRkwMvLC02aNLEoz8zMhJeXV02FRkRERGSTaiwxS0pKwuLFi6HX66HX6/H7779j8uTJiIuLQ3x8PEwmE3bs2IHg4GA0b94cdnZ2OH78OABg+/btCA4OrqnQiIiIiGxSjV3KHDhwIGJiYjB+/HgolUoMHz4cY8aMgbu7O+bPnw+dToeBAwdi5MiRAIDVq1dj8eLFKCgoQMeOHTFz5syaCo2IiIjIJklCiPtiYBbHmBEREZGtq7MxZkRERERUNUzMiIiIiGwEEzMiIiIiG8HEjIiIiMhGMDEjIiIishFMzIiIiIhsBBMzIiIiIhvBxIyIiIjIRlQqMdNqtTh//jyEECguLq7pmIiIiIjqpQoTsz///BNDhw7FnDlzkJaWhpCQEJw4caI2YqMacD7hOn4/noSUrMI72l8WAjGXM7H3RBKycrUV1i/WGfH78SR8uTMWkWdSYTTJd3RcorogjHrIBVlV3k8uyoHQ80csEVVdhUsyTZ06FUuXLsVzzz2Hbdu2ISIiAmvWrMHmzZtrK8ZK4ZJMFdsccRm/HI4HACgkCf83vhOC2nlWqY1PfjqLqL/SAAAalQLPTemKNs1dSq2bX6THa18exfV8nbmsVZOGeHlmdygU0h0+C6LaYbhyBNqD6wFdIRQevnAY8W8onDzK3UcYdSje8yFMCacApQqarmNh121sLUVMRPeCu16SSavVok2bNubtgQMHwmQyVU90VGu0eiN2HUk0b8tC4JfDV6vURtr1InNSBgB6o4xd0Qll1o88k2qRlAFAXGo+zl7NrtJxiWqbMOqgjfgS0JX0LMtZCdAd+bHC/Qxn95YkZQBgMkJ/bAtM2Uk1GSoR3WcqTMxUKhVyc3MhSSU9HFeuXKnxoKj6yTKsehSrelnRaLLukTSU00ZZ7RuNvJxJtk0UXgcMlpci5evJFe5nun7NqkwupYyIqCwVJmZPPvkkpk+fjtTUVDzzzDOYMmUK/u///q82YqNq5GivQr8HmliUDe3uU6U2mjdqgA4t3czbCknCkCDvMuv36dgEDnYqizJPVwd08iv/chBRXZOcG0PhYvl5Ufl2qXA/lW/n2wo0UDZrX52hEdF9rsIxZgaDAdeuXcOhQ4cgyzL69OmD1q1b11Z8lcYxZhWTZYHo2DQkZRSgUysPBLRwq3in2xiMJhw6k4qsXC2C2nmiZRPncutn52mx60gCkjIK4e/jgqHdfdDAXn2nT4Go1si5qdBF/wA5NwWqFl2h6T4BkkJV4X76s7/DcC4Ckl0DaILGQ9W0XS1ES0T3iorGmFWYmI0bNw7bt2+v9sCqGxMzIiIisnV3PfjfwcEBqamp1RoUEREREVmrsF++uLgYQ4YMQZMmTeDo6Ggu//nnn2s0MCKi2mS48Ad0x7YCRj3UHYfALmh8qfXkwuvQHvgSppRzUHq2gn3wP6zGoxER3akKL2UeOXKk1PKePXvWSEB3ipcyiehOma4no+iHxQBufofYD50LtV8Pq7pF4e/enBIDgMLTDw0mLKmNMInoPlDRpcwKe8x69uyJnJwcFBcXQwgBk8mEhISy564iIrrXmFIv4takrKTsQqmJmSn1gsW2nHEFwmSEpKz4xgAioopU+E3y/vvv45NPPgEAKJVKGAwGtGnThpcyiei+ofSyvtNc6eVXZl1T0hnztsKjBZMyIqo2FQ7+3759O/bt24cRI0bgt99+w4oVKyxWAiAiutcpPXxg128GJPuGgEoDdeeRULXuXWpd+wGPQfn3FBgKz1awHzS7NkMlovtchT/z3N3d4eXlBT8/P5w7dw7jx4/Hp59+WhuxERHVGk3HIdB0HAIhhHmlk9IoGjaCY9hLFdYjIroTlVqSKSEhAX5+fjh27BiMRiN0Ol1FuxER3ZMqm2wxKSOimlBmYvbee+8BAIKDg/HKK68gJCQEv/32G0JCQtCrV6/aio+IiIio3ihzuoyhQ4di48aNeOKJJ7B+/XpIkoTi4mJkZ2ejadOmcHd3r+1Yy8XpMoiIiMjW3fF0Gf369UNISAgAoG/fvubxFDf+GxsbW+3BEhHVFrk4D6bUi1B6+AAATFmJkJy9IPLSofRsCYWTB+SCLJgyrkLZuDUUjq51GzAR1QsVTjA7bdo0bNy4sbbiuWPsMSOiyjImnUHxrjWASV96BUkBdbv+MJz/AxAyoFDBYehcqFp2rd1Aiei+c9eLmN8rmJgRUWUVbn0dckZcBbUk3DrprMK1GRo8/GaNxkVE97+7nvmfqCJCCBw9l46rKfnw93VFYJtGdR0SUbmEtqAytW7bJ79mgiEiukWF02UQVeR/ey/ho+1nEX4kAWt+jMGv0fF1HRJRudTt+ldYR3JpfNs+A2oqHCIiM/aY0V0xyTL2nUy2KNtzLAmjerWoo4iIKqbpOhaKBu4wJp+Fws0bgIApOwmSUg2YjFB6+UEVEAxj7AGYMq5A2bQ91O2D6zpsIqoHmJjRXZEgQaVUwGCUzWVqFTtiybZJkgR1uwEV9oJpHhheSxEREZXgX1C6KwqFhLC+Lc3bEmCxTURERJXHHjMql1ZvxOGzaSgoNqBXgBe83BwBAEnpBTh+IQMezvYYEuQNfx9XxKXkoZ2vKzyc7bHvRBIKtEb06tAYXq4OdfwsiGqGEALGy1EwpVyAsnEbqNr2gSTx9y4R3TlOl0FlkmWBpV8dRUJ6yR1sdmolXp4RhPwiPd7ZdAqmv1/vTn7ueObhQAAlY86WfnUMibfuMzMI3p5l3xpMdK/SHfkR+j93mLfVnUfCvvfkOoyIiGxdRdNl8KcdlSk2/ro5KQMAncGEfX8mY8/xJHNSBgBnrmQjObOwZJ+r181J2Y19Ik5eq72giWqRPnafxbbhr31l1CQiqhwmZlQmhWRdppQkKCTrB27UlUrZSVFaQ0T3AUltf9u2XR1FQkT3CyZmVKZ2LdzQprmLedvBToVB3ZpjeE8fqJQ3T50gf0809WgAAAjwdUPrZs7mxxz/3ofofmTXfSJg/qEiQdNjUp3GQ0T3vhodY7Zu3Tr8+uuvAICBAwfihRdeQGRkJFasWAGdTodRo0ZhwYIFAIDY2Fi8/PLLKCwsRPfu3fH6669Dpar8vQkcY1YzDEYZx8+no6DYgO7tveDqVNIjkJ5TjD8vZMDDxQFd2zay6BUzGE04dj4DRVojgtp5mvchuh/JOakwpV2Ewqs1lG7N6jocIrJxdbZWZmRkJNasWYOvv/4akiTh8ccfx0MPPYTVq1djw4YNaNq0KebMmYOZM2di4MCBCA0NxbJlyxAYGIhFixahU6dOmDp1aqWPx8SMiIiIbF2dDf739PTEwoULodFooFar0bp1a1y9ehUtWrSAj48PVCoVwsLCEB4ejuTkZGi1WgQGBgIAJk6ciPDw8JoKjYiIiMgm1dg8Zm3btjX/++rVq/j1118xffp0eHp6msu9vLyQlpaG9PR0i3JPT0+kpaVV6XjlZZ9ERERE94Ian2D24sWLmDNnDl544QUolUpcvXrV/JgQApIkQZZlSLfc6XejvCp4KZOIiIhsXZ3OY3b8+HE89thjePbZZzFhwgQ0adIEGRkZ5sczMjLg5eVlVZ6ZmQkvL6+aDI2IiIjI5tRYYpaSkoK5c+di9erVGDNmDACgS5cuiIuLQ3x8PEwmE3bs2IHg4GA0b94cdnZ2OH78OABg+/btCA4OrqnQiIiIiGxSjd2VuWzZMmzevBm+vr7mssmTJ6Nly5bm6TIGDhyIl156CZIk4dy5c1i8eDEKCgrQsWNHrFixAhqNptLH46VMIiIisnV1Nl1GbWNiRkRERLaOa2USERER3SOYmBERERHZCCZmRERERDaCiRkRERGRjWBiRkRERGQjmJgRERER2QgmZkREREQ2gokZERERkY1gYlZPFWoN0OlNdR0Gcgt0nBiYiIjob6q6DoBql9Ek44udsYj+Kw0qpQKje7fAuP6taj2O1OwifLDlNJIzC+HW0A5PhHZA+xZutR4HERGRLWGPWT3zx+kURJ1NgxCAwShj+x9xiEvJq/U4Nu6+gOTMQgDA9XwdvtgZC/n+WB2MiIjojjExq2eS0wutypLSC2o9jqQMy2Nm5mpt4tIqERFRXWJiVs908nO32FYqJATUwSXETq0s42jdzBkOdryyTkRE9Rv/EtYzXdo0wozh/th7Mhl2aiXG9muJRq4OtR7H1KH+UCkV+OtqNnwbN8SUIW1rPQYiIiJbIwlxfwzsycoq4N19NiA5owAHY1KgUSsQEtgc7s72AABZCBw6nYKzcdnQ6k1o1qgBQgKbwcvNsY4jJiIiqj0KhQQPD6cyH2diVg8YTTL2HEvC5Wu5aNvcBYODvKFS3t1V7D8vZuLHiMswGGUMCfJGyyYNER6dgJgrmZDlkjouThosf7wXHO3V+HbPBew5lmTRhqOdCm883gtuDe3uKhYiIqJ7RUWJGS9l1gMbd19AxJ/XAADHz2cgPacY04e3u+P24lLysGZzjHn7+98vQpKA21P83AI9Tl7MRN9OTXDg7+PfqkhnxJHYNIzo6XvHsRAREd1POPi/Hog8k2qxfei27aracyzRqqysflcHOxUkSYK9Rlnm40T3IiEETOmXYcq5BlNmPExZCXUdEhHdB/hXsR5wdtQgK09r3nZx1NxVex5/jxurSJvmLujc2gMAMCHYD+vDz1s87u3phJ4BXncVC1FdELpCFP2yCnJmvEW50qczHEb8G5Ki9B8iREQVYWJWDzwyuA0++fksjCYBlVKBhwe3uav2RvTyRcSpa8gvMgAAlAqgkasD0rKLAQAtmzTEuP6t8ICfBxQKCQAwMLA5/H1ccTEpF7Isw8XJDg/4edz1WDeiuqD/a59VUgYApsQYGK8eh9qvZx1ERUT3AyZm9UD39l5o6+OK+NQ8tGziDOcGd9dj1sBejXfn9UfU2VQU6YwY0KUZ1EoFLiblQKNWolVT51L3a+rRAE09GtzVsYlsgSjMLvuxguu1GAkR3W94VyYRURUZU86j+OeVAG77zlFq0ODh5VA09KyTuIjI9nG6DCKiGmBMjIEhNgLCZACEgGTXAJoHhkPp5VfXoRGRDeN0GVQlRlPJJGQ3xn4JIaA3yrBTV20wc/r1Inz2SywuJ+XCr7kzHh/TAY3dOZks2SZhMsBw8TBMyWehaNQSmoCBkDTln6+KRi0hTLthSjwDhXtz2HWfYE7KTNnJ0EZ8BjnjKpRN28F+0BNQOHnUxlMhonsce8zI7KdDcfg1KgGyEBjSzRtd2zbCFztjkXa9GG29XTBnbEfzTP4VWfnNcVxIyjVvt/F2waLpQTUVOtEdE0JG4bY3IDLizGVSAzc0eHAZJLuyx0QW7/0IxktRN/dp6IkGk9+CJClQuHkJ5Fumz1D6dIbjqGdq5gkQ0T2loh4z3hJHAIDzCdex7WAcdAYTDEYZ4UcSsHbLaaRdL7nT8mJSLr7bc7HS7V2+lmexfSU5r4yaRHXLdO2cRVIGAKLwOgwXD5e/X9ply33yMyCK8yCMeoukrKTupeoJlojue0zMCAAQn5pvVVZQbLDYvlpKnbK09XYpd5vIZgi5jHJTubspm7S12JZcGkNycIGk0kDh2eq2uv53FSIR1R9MzAgA0M7XDdJtZbdPJBvQwq3S7c0aE4CAFm5QqxQIaOGGf44JqIYoiaqfslkAJLfmFmWSfUOo2vQpdz/7PlOhahkEKDVQePrBYehcSFLJp8hh0JySZEyphtLnAdgPeLTG4iei+wvHmJHZodMp2BF5FSZZYHgPH3Rs5Y5vfruAxPQCdPJzx/Rh/nC0V9d1mETVThi00J/9HaZr56Bs5At1p+FQOLKXl4iqH6fLICIiIrIRnC6DqoXRJOPEhQzkFujRzd8THi43L3MWFBtw9Fw68gv1kCQJLZo44QE/D0iSVO5+REREZIk9ZlQpb393ErHxJUvN2KmVeGl6N/g2bojcQj1e//IIcgr0FvVDujbHzBHtLPfTKLFoehB8vMr+pUBERHQ/43QZdNcuX8s1J1cAoDOYsOdYEgAg8nSKVVIGAAf+vIbTlzMt99ObsOdYYs0HTEREdI9iYkYVKq1PVf67UC6jw1VAwFTKLARl1Se6l8i5aTBlJ5f8Oy8dpuwki8eFrhCm9CslyzUREVUBx5hRhVo3c0ab5i64lFwyk79apcCQIG8AQN9OTfHb0UTkF1n+AerbsQm6tPFA6+bOuPz35LJqlQKDu3nXbvBEZRDGkp5eSaWp/D5ChnbfJ+YZ/yUHF4jiks+Fsml7OIxaAOPVE9Du/wKQDYB9QziOehZKz5bVHj8R3Z84xowqRW8wIeqvNOQW6NAjoDGa3LLuZU6BDlFn05BToINCAlo2dUb3dl5QKCToDCZEl7EfUV3RHd0MfcwuQMhQdxgMuz5TIIpyIDk0hKS4+XtV6IsBIZuXZjImxqD413fKbFfdfSIMx7dZTlqr0qDBg8ugcPaqqadDRPcQTpdBRHQLY/JfKP5llUWZ5NQIoiATkoMz7AfOgso3ENqo72E4sxsQAmr//rAb8BgM5/ZD98fXZbYtuTaDyLlmVa70fgCOo5+t9udCRPceDv4nIrqFnBVvVSYKMkv+W5wH7f7PYUiIgSEmHJBNgJBhOH8AxitHoPLtApR16VOSylzeyZR8Brrj23Gf/A4mohrEMWZEVK8om3UAIAEo48YVbT7k9MtW5XJ2EtRtesMx9EXoT/0KYTJA1bwTTKnnIUwGaDoMgfFaLAwxv5bSqID++FYoGnpA7d+/ep8QEd1XarTHrKCgAKGhoUhK+ntqhchIhIWFYfjw4Xj33XfN9WJjYzFx4kSMGDECL7/8MoxGY02GRUT1mLJRC9gPegIKt2aQXJr8najdpHDzhqp1T0Cy/HpU+jxQ8l+v1nAYNg+OIxdA88Aw879Vvp1h132C1X63Mib/Vf1PiIjuKzWWmJ06dQpTpkzB1atXAQBarRaLFi3Chx9+iJ07d+LMmTOIiIgAADz//PNYsmQJdu3aBSEENm3aVFNhERFB3bYvGjz0JpweWQmHkU9D3WkYJOfGULXoCocRT0Hp1hz2Q+dC4ekHhYcv7EOegKppuwrblVQaKJu0LfNxZaMW1fk0iOg+VGOJ2aZNm/Dqq6/Cy6vkTqSYmBi0aNECPj4+UKlUCAsLQ3h4OJKTk6HVahEYGAgAmDhxIsLDw2sqLCIiC5JKA/u+0+A0+S04jPi3+e5JdasgNJiwBA0mLYXav1+l27Mf8BgUHr4lbTu4AGp7QFJA1aYP1B2G1MhzIKL7R42NMVu+fLnFdnp6Ojw9Pc3bXl5eSEtLsyr39PREWlpaTYVFRFSjFK5N0WDSUgh9MSSNA4RsAmRTleZLI6L6q9YG/8uyDEmSzNtCCEiSVGZ5VZV36ylZMplk/HIoDmeuZMHf1w3jgv2gVimt6ukMJmyPuIxLSTno0qYRRvZtBaWi6u8NUf3UsK4DIKJ7UK0lZk2aNEFGRoZ5OyMjA15eXlblmZmZ5sufVcF5zCrv+98v4rejJWtWHj6dgovx2Xg8tINVvY+2n8GR2HRzvYSUPDwY0rpWYyWqTsbUizAlnYbC3QeqVkGQ/h6oLxflwHgxEpCUUPn3hcKeSRUR1YyK5jGrtcSsS5cuiIuLQ3x8PLy9vbFjxw5MmjQJzZs3h52dHY4fP46goCBs374dwcHBtRVWvZOeU4w9xy3X9Yv+Kw3/GN0eSsXNIYd6gwlHz6Vb1Nt9LBG7jiSgkasDpg/zR8dW7rUSM1F1MFz4A9r9n5m31R0Gw77/TMhFOSjc9BKgLwYA6GLC4fTQMvNs/5UhTAYYLhyCnJMCVYuuUDVrX+3xE1XW7wkH8Fv8PpiEjCE+wRjV6s7HNsZknMXmiz8jR5+H7o0DMbndRKgVnGmrJtXaBLN2dnZYuXIl5s+fj9GjR8PPzw8jR44EAKxevRorVqzAyJEjUVRUhJkzZ9ZWWPXOVztjrXoWnRzVUNx2+VilVKCBvdqizGCUYZIF0rKLsG7LaZy+nIW4lFycjcuGsbQVy2+RnFGAmMtZ0BtM1fNEiKpIH2N5U5EhNgJCXwztvk/NSRkAoOg6DFeOVqlt7e8fQXfwKxhO70LxjpUw/L2WJlFtu5xzFVsu7UCBoRDFxmLsiNuFs1nn7qitQkMRvjj7LTK12TDKRkSlHMPvCRHVHDHdrsbT3r1795r/3adPH/z0009Wddq3b48ff/yxpkMhAJf+XlD8Vo8MbmM1rk+hkPDI4Db46tdzMMmiZFLzW/I5ncGEd384Zd72cnXAS9O7wcXJzqr97/ZcxO5jJZdOXRposHBaNzTmmplU26TbxlFKEiBJMKVdsq5azlxkt5MLr8N49bhFmf7sHqjb9L6jMInuRlye9coWcbnx6OhR9V7c5IJrMMgGi7IrudbtU/Vif2Q9Eht/HUqFBOMtnVatmjZE7w5NrOoajCb0DPBCh5buSEwvwJm4LOw5lmRV74Ybl0gnDbQcg5aRU4w9fydlAJBbqMcvh+Mxa0zA3T8hokoSRj0Urk0slmNSdxoKSW0PSeMIYdTdrCxJUPn1KLstfTEMl6NhSv4LktoOqrb9SiaVvXU5JiGgjfgCwqSHOmBQpeZAI6oOfi4tK1VWGd5OzaBRqKG/JTlrfYdtUeUxMasncgp0eHfTnzCaLC9jBvl7WtXdtPcS9hxPgiQBQ4O88dCgNmjn64oirRHRf6XBVMZNFnmFeottIQTyiwxWC9/kFelBVJu0B76E8XK0eVvZMgj2vScDAOy6T4D2wJe4sUSTpufDkDQOpbZjuHoC2r0fAcab57DhylFA4wDoCksKJAXk7ETzsk7Gy0fhOOEVKBu1rP4nRnQbP5cWeLDtWOyK3wshBIb4BKODx539MHBUO+KfnaaXjDHT5aJHk64Y7Msx4DWNiVk9ERt/3SopA4Aj59Jx+VoeOrR0w6Cu3jh9JQvhRxLMj/8anYD2LdzwgJ8HHg/tgOE9fPD6l0etki1JAoLaeSIxvQCeLvb4ZvcFRP+VBreGdnB3tkN23s0eif4PNK2pp0lkJhflwJR6EbJeC+OlwxaPma7dXBpJCBmKRiUTwmoCQ6Euo7dMCAHdoQ0WSRkAwKC9raJsWUeYYLgUzcSMas0gn/4Y5FM9a7J2ahSATo14haM2MTGrJ5p5lH6HWUJaARLSCnDyYiZiLmejTXPnUurk4wE/DwDAD/sulbr0s18zZ/x321noDCY42KlQrCtZ7zQzVwu1SoEAX1dcTSuASwM1NGrrOdOIqpM+NgK6P9ZbXl60qKCFXJwHU+Jp6A5+ZS7WHfoGKt8upU4GK4pyIAqv31E8ckYc5KJcKBxd7mh/Iqo/au2uTKpbzT0boKJ5e09fyYK/j6tVeUCLm9NiXE3LL3Xfy8l50P19x+WNpOwGg1FGbEIOinVGpGYXY+3mGGTmFJsfI6pOclEOdH98VXZSBgAQ0B7aaDVoXxTnlnozgOl6Mgp/XFxqSwp3nwpjMqWcQ9H2NyzHshERlYI9ZvWEQpKgVimgN5SfCMVevY4m7g5IzS6GUiFhZC9f+DW72Yvm19QFp69k3VUsJlngxIUMnI7Lxtm4bHi62uOxke0R0JLzotHdM16OtryFuAymK9FQ+nS2LJQkKJytx10aYsJvjiH7m7JlEDRdRkHOSYMu4tMKjyfyM2FMPA11q+4V1iWi+os9ZvWEQiFhcDfvCuv9FHkVqdklvVkmWSDqbBoKivXILSj5pf9EWAf4eFrPWFzVhZr+t+8SzsZlAwAycrT4+KezFc6FRlQpavvK11VpoGjUouTfCiU0QRMgOXlYVRO3jyMDYNdlFFSN20DpUcrnSlP60AGpKrERUb3ExKweeXhQGwzq2tw8mWyPAC80cS/97rMbsvK0WLD2EBasO4S1m2Ngp1ZgfHAr2N02TuxG/0QDh8p1wt7eoZFXZEBWnvUfP6KqUjZpByhvGSNWzizlKq/WaDDxdTg+tBx2Ax+H4fwBFHz2OIp//y+E4eZlR3XAINw6FkDh0QIKr5KpYZSNWkDZouvNRtX2aDB+MRzCFkFydL0ZV7MAKJtbL31GRHQrSYhK9PnfA7hWZuVdTMrB738vy9TQUY3fjydXet/JQ9pgR2Q8CooNZdZp7O6ItOyiKsXk4WyPt57sAwUXSae7VPzbGhivnrhZoFABsvG2WhJUrYJgP2g2JJUGQl+Mgo0LLO6w1ASGwq7ng+ZtU9olGC5HQ3J0gyZgoMWSTUIImK7FQhTnQuXT2fyYMGhhTDgFSeMAZfNOkBT8LUxU39nMWplkG0rmMzsFrb5koH5V06D41IJykzIACPB1haerPeKu5cGvmQsc7JSIuZxlPubtfBo7YdaoACZlVC1MaZctC25PyuwbosGDyyzukJSvJ1tNe2FKt2xH2bgNlI3blHpMSZKgKqU3TFLbQ9WiK0RRDiq8+4aICEzM6p0/L2VaJEgCgEZd8U0BN/QM8EJSRgES0wvKrNOrQ2O083WzKHvxo8hSE7MhQd6YNsy/csETVYKyaTsYrxwxbyvcmkHh0gTG+JNQODeG3YDHrKatULj7ABpHQH+zp1fZpPTzUggZ8vVkKBq4Qxj1MF4+AsnOEarWPSGpLJckM1w9AW3E54CuEJJLEziO+DcUrpzHj4jKxsSsnnEtZS3LIUHeCI9KsJqfrEXjhmjn64qEtHwU60wI6doMXdo0QnPPBtiw6zwuJuVCCEChKBkz5uKkwdi+raySMgDILbCe7f9f4zuge3vr5aCI7oZdv+mAyQBj8l9QNmoBuwGPQenWDEIIqzVhb5DUdnAYNg+6w99Czs+CunUPKFt2hSk7CUr3m4P75bx0FO38D0ReGqBUlxSaSnqQFWf3wHH8EkiKkvGXQjZCd+BL892cIjcV2qjv4ThyQQ0+eyK61zExq2c6+3mga9tGOHkxEwDQupkzwvq2xOEzqci5LXla8HAXODewnmizkYsDFjwcWKXj+jVzxrmEHPO2g52SSRnVCIWDMxxG/Nu8LUxGCNlkTphuZ7qeDOOlKEh2TnAMewlQ20O7ex2Kt7wGAFB6d4LDiKchKVUoPrSxJCkDzAnZDXJmPEzJZ6H6ewoOoS2A0FrO+yfnpFTTsySi+xUTs3pk99FEHDqTAoNRhlqlgMEoo6GjGqcuZSK30LpHKz4tDy2aOMPZ0To5O3jqGvadTIa9RomeAY0RdTYVqdeL4de0If45JgAO9mocjU1HfGo+2rdww5ShbfGf7/9EXpEBkgS4NbTH29+fRF6BHh1aumPiQD+rOz2J7oYQMnSR38Jwbj+gUMOuWxg0XUZb1DFlXkXR9uXmJEv/115ouk+AMf7kzTpJZ2C8HA0hSZATT1V0UPM/FY6uUHi2gpwRZy5T+Qbe9fMiovsb78qsJyLPpOCzHbGVrq9SSlBIEvRGGV1ae+DJcZ1gpylJnGIuZ+G9H8r+A+XSQI2gdl7Ye+Lm3Z6+jZ2QkFb2uLRBXZtjxog7W2iXqDSGS4eh3fuxRZnjhFeh9Gxl3tYe/AqG2P0WdRTuPpCzEy3KNEHjoT+103qdzFv38/CF44RXLXrm5IJs6I78ADk7CSqfB6AJGl/qck9EVH/wrkwCAByNTa9S/ZIFz0sS3VOXs7D4s2ioVRJaN3fBsXMZ5e6bW2jAvpOWU3CUl5SVHCMTM8DEjKqPKeNqKWVxFomZeZzYLeTsRMspNhTKkn1KScrUXcdCoXEA7Byhbt3b6nKpwskdDoPn3NXzIKL6hYlZPVCkNVqM77oTNyZ/vbEqQEWq2g/btIxF1onulGRfygoVt0z4CgCajkNhOPu71bqa9iFPwBh3FBAC6geGQ9m4LWDnBOhu+YFh5wS7wDGQ1NY31BAR3SkmZvXAn5cyzAuM26KGDmpMGdK2rsOg+4ju2FboT2y3KtfuXgdp2HyoWpbM1K9waQy7PlOgi9xorqNs4g91m15Qt+llLtOf+tUiKZOcveA47hUmZURU7ZiY1QMOmtp/m50c1Pj3g52xMyrefAdoWRZO64qmjdhjRtVDyEboY8LLehC6U7+YEzMA0HQaBsnJHca4E1C4eEHTaZjVbro/d1gWGHRQODSszrCJiAAwMasXHmjtgYaOauQXlT9jf2kauzlAFgIZOVVbx7Kg2AC9UUaPAK9yE7O23s5o2qjsQZBEVSZgdWnS8nHrx9Qtg6BuGVT5fcprn4joLnDhtnpApVSgsVv5i5WXJTNXi3+MCsA/RrfHqF6+Vks4adQKPPNwF/Tu2Nh635xidG/nhQ4trSecveFfEx64o7iIyiIpVVC17lXWo9B0Hlml9uSi3JKVAW6h7jyq1Lqm1IvQHvgC2qj/QS7IqtJxiIgA9pjVGz3aN8al5Lwq72eSBT7+6SwWPNwZ5xNy4OKksZyIVgBrN59GAwfLU0mpkHA1LR9tfVzx3OSuuJqahz3HkhB5JtVcx9/HFS4NOEaHqpf+9G4YLxy6WaBUw673ZIjiPKh8u0Dp5Vfu/sJkhOHMbzClXYaisR8M5w5C5N48bzU9HoRdoOV8aHJBFnRR38N45ai5zHg5Gg0eWWG1TBMRUXk4j1k9IYTAD/suIfxIYrn1urfzxF9Xr6NIZ7nws4NGieJb1rps5GyHzDyd1f7ODdQo0hr/nm4DsNco8ewjgcjMLYZOLyMpswAJaQXw9myAsf1blTp5LdGdknNSUbhpoVW5Xe9HoCmll8uUnQzTtb+g8PCFqmnJdC3aA1/CcC6izGOo/HrCYei/zNvCZEThpoUQ+daX7O2Hzy//EikR1Tucx4wAAJIkoVBrrLBe2vVieLrZIz715h1oKqVkkZQBQLGu9LbyCi3HsWn1Jrz5zXGL6TNG9vRFv85N4WjH04+ql+7kz6WWS3Y3vwRNWQkQxXmQi/Og2/+peW4XTbdxsOs+AYaLkeUeQxgtf5CYUi+UmpTdflwiosrgX8Z6pPTlmy0lpltPBHuj9+tWVemcvL1PNvxIAsKPJMDZUY3/G9+p1EXPie6EKfmMdaFTI/OYM23E5zCcP1hSrlBanJz6U79CEzgGkqOLZaKlsgNuScZMCadgvBYLVbMAAIDk6FJqLKoWXc29cERElcXB//WA0STjtyMJSMoof/b9qpDLuALu7mwH38aV6yXIKzLgq/Bz1RYTkdWvAEkBx4dXALIJ+uS/biZlACDfNrefMAEQsOs9uSRp+3t/hVtzq8Poor6HPmYXhK4QSrfmUHcYfPOQ9g1hN+RfcBjxb8hFOTAm/Am5uOrjO4mofuIYs3pgffg5RPx5zaq8vY8rziflVHmW/orc6JmrbLOfvTAICkVl+vOIyqf7cwf0R340byuad4Kcet68SHl51B0Gw77/TOhO/AT9sS2VOp7k0gQNJi2FpNLAmHoBuj82QM5OhGTnBFXbPjD8tbckAVSq4DBkrsX8aUR3ShYyolKO4VJOHFo6+6Bfs15Q/v1jotioRURSJDKKMtHZsyO6eHYst60iQxH2Jx1ClvY6unl1RmuXVth47gck5CejjUtLTG43EepSli6jO8cxZmRxJ+St4lLzqj0pAyqfkN1w+Vou2nq7Vn8gVO/YBYZC6e4DU8p5oIEr9JHfVnpfY2YC5MLr0N8+mWw5RG4qjEmnoW4ZBOOlaPPi50JXAMOZ3TcrmozQRf+PiRlVi5+v7MJv8fsAANGpx5FckIIp7ScBAD6O+QoXc64AAKJSj2FGwMPo3bR7mW2tO/U54vNKztuolGNw1jghT19ydSWzOAsphWl4ocdTNfl06Da8lFkPNHQs/deOzmAbk2R+8ctfdR0C3UdUvl1g1+thSFLVvt5E+iVoIzcCxqpNxCwpSn7f3kjKysLLmVRdIq8dsdiOSjkGWcjIKMoyJ2U37E08iBxdbqntJBekmJOyG24kZTfE5ychqzi7zFgKDIW4knsV+kr0SlPlsMesHngwpDU++cl2k5+061qcT7jOmwCoWikbtazyPqa0S4DGAdAXlV5BUgBqe/PjCi8/KL07QZgMUHi1hin1wi11lX+PWyuh9u9X5XiISuOodkCBodC87aBygAQJ9io7KCQF5FtWpkguSMErkSswuuVQjGo11KIdB5U9JEgQFVzneCN6Naa3fwgqpRr7E/+ASqHCMN8QnEiPwaFrURB/tzUv8HG0dPat1udaHzExqwd6BjTGl7/EwlDK3ZW24sSFTCZmVOeUXq0hTAbIiTHWD0oS7PpMhbpNbxjijkHSOELp0wnaiM9hvBRdkrRZENB0Gwf5ejKUTdtZ3CBAdDfG+Y3C52c3QhYyJEgY13oUJElCQ40ThvoONF/mvEEWMnZe3YM+zXrA1e7mXcTu9m4I8e6HfUl/AAAaqBzR0tkXZ7Mtb8oyyEZ8f2Ebio3F5rJz2RctErpioxY/XvgZz3WfWxNPuV5hYlYPKCQJ3fy9EB2bVtehlGlA5yZ1HQLdR4RRB93Rcgbw2zsD2jxAqb55Y4BSDWEyQs5OLqNRAcOlSGg6DYUmIATG+JMo+mExROHfl3nE7Xd5yjClX4b94DlQ2HPBc6o+gV4PYKnzQsTlJcC3oTcaObibHxvXehS6Nw7E+r++R3JBirlcFjJydLkWiRkAPOg/Fj2bdkN28XW0c28DB5UDLly/hI9ivoLOdHOVl1uTMgCl9rJlFJe9LjJVHseY1RO5hdaz9NuKXgFe8PbiHy6qHnJ+JrR/bIDpmvXle6lhI9gPn4+GM9eg4eyvoPx7LjIAgMkAOfEUUFjOGpd6bckx8tJR/Nu6m0lZGUxJZ6A78OUdPQ+i8rjZu6KbV2eLpAwAtEYdmjh6YZB3f4vyRvbuaOzoBQAwySbkaPMgCxmykOHp0AiBXg/AQVWyprK/WxsMaN7HYv9mDSr+8dzBg/P2VQdOl1FPLPz4MNKvF1dcsQ6M698K4/q3qusw6B4nZBOKd6+DKf5k2ZVuzEtm3xCSkGFKqdo8eorWfQF94d+XOiv/fSM1cIem8whoHhhRpeMRVZbWqMPXf32PmMy/0EDtiPGtR+NwyjFczo2DBAkqhRJG2YTmTk1xrSAVMmQooICDyh6FxiK0cW2FWR2nw8Wu5EeySTZhb+JBnMu+iOZOTXEu+yKSC2/2wPVuEoSs4uu4mFtys0Ebl1Z4quts87QdVLaKpstgYlYP5BfpsWDtH1Warb82ebra460n+9Z1GHSPM1w6DO3ej6ulLalhI4iC69aXJ++Sw+jnofIuf14pojux48pv+PXqHvO2AhLkKk5e5OfSEnYKDWTIGOs3Ei1dSgby/3Q5HLvi91rUDW01HKNaDUVmcTY0SjWcNbzqUVkVJWa8lFkPXE3Nt9mkDAAycrScMoPumpybXm1tifzMKiVlCk+/StWrag8dUWUl5luOjaxqUgYAV3KvIvb6BZy/fglvH1+HxLwkAMDl3DirupdySsoaObgzKatmHPxfDxw8ZT3rv605EpuOWWM61HUYdA9TtQiE/vjW2j+wUg1VhyHQR1jOH6XuPAqGmF8tyhSevGRP1ccgG3Eq/TSiUo7jal6CxWNKKGDC3c1V+eGpL+Hp4I4io9bqsaDGXQAAKYVp+OlyOIqMxejk0R4h3v24UsBdYmJWD/wVV85gZhthNNrGZLd071I2agG73lOgi/oeVV9/4i6YDNBHfArJpQlEQSZgMgKQIPRFUHUZDWNMOCBkQGUHScGLFFQ98vT5WBn9HnIN+aU+frdJGQDkGfKRV0b76UWZ2HZpJ3Yn7DeXXcq5gqSCa/hHx6l3fez6jN8S9UCR3vaTHtuPkO4Fms4joOn1SJ0cW+Sm/p2UAYCA8VwE5LRLJUkZABh1KN73KYRRX2YbRJV1ICmyzKSsNuxJiMCehAir8uNpp2DgKgB3hYkZEd1X5OyEiivVEjknxbJAVwhRYPs92GT7Cg1lrE5RS8Tf/7udnVLDOzPvkk0lZj///DNGjx6N4cOHY+PGjXUdzn2jmYdjXYdQIQ9nu7oOge4TquZ1eNfjbbP/K5tazuskNWwEyblxbUZE96meTYLq9Pi+Tt7wdPCwKh/fegwUVVynlizZzBiztLQ0vPvuu9iyZQs0Gg0mT56MXr16oU2bNnUd2j1v2RO98f4Pf+LU5fInw6xLbb1d6zoEuk+o/ftBLrwOw9ndEPriktn9dcWo8gVzB2co3JpDzowH9CVzACqb+kPRpC0Mp3+7ZbFzASg1sOs3DZLGEfqTP0EYDdB0Ggp1u2DoHFxgjD8JhUtj2PWdynFmVC1aufji6W5z8GnMNyg0Flo8poIKDTSOKDIWwSAbzeVKKOBi54IGf6+1maPLg4CAQlLAVeMMo2xCgbEQspChkdQwCINFn5haUsFJ7YQAD39MahsGvazHDxe240puPBqqnfBIuwlo5cK1Mu+WzcxjtnXrVhw9ehRvvvkmAOCDDz6AEALz5s2r1P6cx+zOGYwy/oi5hg2/Xai48m2GBnnjkSFtoFQosPXAFew9kQS9UYahioP51SoFPn4upMrHJ6osIRthSr0IycEFSrdmFo8Zrp6Advc683gwdadhsO87rS7CJKoyrVEHpUIJtcK6ryVfXwCFpEADtfWVE73JgAJDAdzty16n2CAbS22X7lxF85jZzKudnp4OT09P87aXlxdiYkpZSLgM5T1JqtiIhvbYuOdilZNbT48GaNK4ZO212ZO6YPakLlj9zXFEnEyqUjtqlQKenpwLh2pY456ll3sOhL6lH4qu/AmNpw8c/QJrNSyiu1P2d6dnOY+VcK/gcaptNpOYybIMSZLM20IIi+2KsMfs7g3r7o1dRxKtyiUAAS3c8Ff8dYtye40CAzo1RkaG5Z1BgwKb4shfKSjWVX6CztG9fK3aIapdroBfCAwACnkuElENuWd6zJo0aYJjx46ZtzMyMuDl5VWHEdU/jwxuiyB/T5y8mAm3hnZo1dQZ17IK0bqZC5o1aoCzV7Px86E4FGmN6NLGA2F9W0Gjtr77xrdxQ6yY0wdnrmRBpVQgNbsIJlmgmYcj0rKLYW+nQte2jXA+IQcXk3IwsEsz+DV3qYNnTEREZFtsZoxZWloapkyZgh9//BEODg6YPHky3njjDXTu3LlS+7PHjIiIiGzdPdNj1rhxYyxYsAAzZ86EwWDAgw8+WOmkjIiIiOh+YDM9ZneLPWZERERk6yrqMeOEOkREREQ2gokZERERkY1gYkZERERkI5iYEREREdkIJmZERERENsJmpsu4WwpF5VcJICIiIqoLFeUr9810GURERET3Ol7KJCIiIrIRTMyIiIiIbAQTMyIiIiIbwcSMiIiIyEYwMSMiIiKyEUzMiIiIiGwEEzMiIiIiG8HEjIiIiMhGMDEjIiIishFMzIiIiIhsBBOze1h4eDgmTpyIsWPHIiwsDJ999tkdtbNv3z58+eWXAIC1a9di7dq11RlmudasWYNjx47V2vHo/lFQUIDXX38doaGhGDduHGbMmIGzZ88iOjoaM2bMuON273Z/ortRVFSEFStWYMSIERg7diymTZuGqKioOo2J39O1675ZxLy+SUtLw1tvvYUtW7bAzc0NhYWFmDFjBlq1aoUhQ4ZUqa0zZ87UUJQVO3r0KHr16lVnx6d7kyzLeOKJJ9CrVy9s27YNKpUKUVFReOKJJ/Dqq6/WdXhEd0QIgblz58LPzw87duyAWq3GX3/9hTlz5uDdd99F9+7d6yQufk/XLiZm96jr16/DYDBAq9UCABo0aICVK1fCzs4Of/75J5YvXw6dTgc3NzcsXboULVq0wIwZMzBv3jz06tULSUlJmDlzJj755BN8//33AIBmzZoBAGJiYjB58mSkpaVh4sSJmD9/PgoKCrBo0SKkpaUhPT0dffr0wfLly3HkyBF89NFHUKvVSEpKwuDBg+Ho6Ig9e/YAAD755BM0atQIffr0wbBhw3Dy5Ek0aNAAq1evxrFjx3DmzBksXrwY69atg0ajwZIlS5CTkwNHR0e8/PLL6Ny5MxYuXAgnJyecPXsWaWlpmDt3LiZNmlQ3LzzZhOjoaKSkpOCpp56CQlHS8d+7d2+sWLEChYWFyM7OxhNPPIGEhAS0atUKa9asgUajwbZt27B+/XrIsoyOHTvi1VdfhZ2dHXr37o1OnTohIyMDL7zwAq5fv45//vOfSE9PR+fOnfHqq69Co9Fg3759eO+99yDLMnx8fLB06VI0atQIgwcPxtdffw1vb29ER0dj3bp12LBhA2bMmAEXFxdcvHgR7733HuLi4rBmzRo4OjoiICAAJpMJK1eurONXk2zF8ePHERcXh08++QRqtRoA0KFDBzz55JP44IMPYDQarb7D9+7di8zMTCxZsgSpqamQJAnPPvss+vbti8LCQixduhQXL16EyWTCE088gdDQUGzZsgUHDx5Ebm4uEhMT0a9fP7z22mtITU3Fc889h6KiIigUCixevBhXr16t8HtaoVDg9ddfxw8//ICioiL07NkTGzduRJcuXbBkyRL06dMHERER/B6vLEH3rCVLlogOHTqISZMmiVWrVonY2Fih0+nEoEGDxKlTp4QQQuzcuVNMnDhRCCHE9OnTRVRUlBBCiMTERDFo0CAhhBBr1qwRa9asMf97woQJQqfTiaysLNGlSxeRn58vfv75Z/Hhhx8KIYTQ6XRi6NCh4vTp0yIqKkp07dpVXLt2TRQVFYnAwEDx3XffCSGEWLhwofjqq6+EEEL4+/uLLVu2CCGE+Prrr8WcOXOsYpo0aZLYtWuXEEKIkydPipCQEKHT6cSLL74o5s6dK2RZFufOnRM9e/as2ReWbN5nn31mPoduFxUVJQIDA0VCQoIwmUxi0qRJYt++feLChQtiypQpQqvVCiGEWL16tfjggw+EECXn543zMCoqSnTp0kXExcUJWZbFv//9b/HVV1+JzMxM0b9/f5GYmCiEEOLTTz8V8+fPF0IIMWjQIHN5VFSUmD59uhCi5Py+8dnKysoS/fr1E6mpqcJkMom5c+eKF198sYZeIboXffHFF+LJJ5+0Kr9w4YLo2rVrmd/hTz/9tNizZ48QQoi0tDQxZMgQkZ+fL95++22xfv16IYQQ+fn5YsyYMSIhIUFs3rxZDBw4UOTn54uioiIRHBwszp07J9auXSs+/fRTIYQQERER4rPPPhNCVO57Ojg4WOTl5YmIiAjRp08f8cknnwghhBg2bJjIz8/n93gVsMfsHvb666/jX//6F/744w/88ccfePjhhzF79mw4Ozujc+fOAIBRo0ZhyZIlyM/Pr3S7AwYMgEajgbu7O9zc3JCbm4vQ0FDExMTgq6++wpUrV5CTk4OioiIAgL+/P5o2bQoAcHNzQ58+fQCU9MDl5eUBAOzs7DB+/HgAwIQJE/DOO+9YHLOwsBAJCQkYPnw4ACAwMBAuLi64cuUKAKBfv36QJAn+/v7Iycm5sxeM7hsKhQJ2dnZlPt6+fXv4+PgAAFq3bo3r168jKSkJ8fHxePjhhwEABoMBHTp0MO/TpUsX87+7d++Oli1bAgDCwsKwZcsW+Pr6onPnzvD29gYAPPLII/jkk08qjPXGZ/HYsWPo2rUrGjduDAAYP368uWeZCCi5lClJklW5VquFEKLM/SIjI3HlyhWsWbMGAGA0GpGYmIjIyEhotVps3rwZQMn4tYsXLwIAunbtCicnJwCAj48PcnNz0adPH8yfPx+xsbEYOHAgpk+fbnGc8r6n+/bti+joaJw4cQKPPvoojh49ikGDBqFp06bm4/B7vHKYmN2j9u/fj6KiIowePRqTJk3CpEmTsGnTJvz8889WdYUQMJlM5n8DJR/csqhUN08LSZIghMCGDRuwa9cuPPzww+jbty8uXLhgbutGl/sNSqXSqk2FQmH+wpFl2apOaV86t8Z9449waV9aVP906tQJ3377rdUfsnfeeQd9+/Yt9Rw2mUwYNWoUFi9eDKDkj8yN8wsA7O3tzf++dX8hBFQqFWRZtohBCGHxOSrrs3WjXYVCYdUG0a06d+6M9evXw2AwQK1WIzs7G25ubjh16hQ6duwIoPTzTJZlrF+/Hq6urgCA9PR0eHh4QJZlvP322+Z9MzMz4eLigp9//tnih82Nz0hQUBB++eUX7N+/Hzt37sTWrVvNN4bdeuxb3fhshYSE4PDhwzhz5gw+++wz/O9//8O+ffswaNAgc11+j1cO78q8R9nb2+M///kPkpKSAJR8OGJjYxEYGIicnBzExMQAAHbu3IlmzZrB1dUVbm5uuHTpEgBY/FJXKpXlJmoAcOjQITzyyCMYO3YsdDodzp07V6U/MsXFxdi7dy8AYMuWLQgODjYf22QywcnJCd7e3vjtt98AAH/++ScyMzPRtm3bSh+D6o/u3bvDw8MD69atMydXBw8exJYtW5CdnV3qPr169cLu3buRlZUFIQRee+01rF+/vtS6x48fx7Vr1yDLMrZt24a+ffuiS5cuOHXqlPkz97///c88IPrWz9bvv/9eapvdunXD6dOnkZ6eDiEEdu7cyT9QZCEoKAitW7fGW2+9BYPBgK1bt2LKlCn48MMPMXfu3DK/w3v37o1vv/0WAHDp0iWEhYWhuLgYvXv3xnfffQegJFkbO3YsUlJSyjz+qlWr8NNPP2HChAlYsmQJ/vrrLwCV+57u168f/vjjDygUCjRs2BABAQH4+uuvERISUhMv1X2NPWb3qN69e2PevHl48sknYTAYAJRcgpw/fz4GDx6MN954A8XFxXBxccG7774LAHj88cexcOFCbN682eLOzR49euDFF19Eo0aNyjzeo48+itdeew2ffPIJnJyc0LVrVyQlJcHX17fSMYeHh+Pdd9+Fl5cX3nrrLXPMr776Kt566y28/fbbeO2117B27Vqo1WqsXbsWGo3mTl4eus9JkoQPP/wQK1asQGhoKFQqFdzc3PDJJ5+Uedm+ffv2mDdvHh599FHIsoyAgADMnj271Lpt2rTBokWLkJGRgd69e+PBBx+EUqnE0qVLMW/ePBgMBjRr1gzLly8HADz11FN44403sG7dOvTv37/UNt3d3bF48WLMmjULGo0G3t7ecHZ2rp4XhO4LkiThgw8+wH/+8x+MGTMGarUazs7O8PX1xYEDB/DPf/4TL730ktV3+OLFi7FkyRKEhYUBKEmwnJycMG/ePLz22msIDQ2FyWTC888/D19f3zKnvpgxYwaeffZZbNmyBUqlskrf0xqNBk2aNMEDDzwAoORv1KVLl8xDAqjyJFHehWuiatKuXTucP3++rsMgqjPXr1/Hhg0bMG/ePCgUCixbtsx8tzRReWRZRkREBEJCQtjLWg+wx4yIqBa4uroiLy8PoaGhUCqV6Nixo/lGBKLyKBQKi7FadH9jjxkRERGRjeDgfyIiIiIbwcSMiIiIyEYwMSMiIiKyEUzMiOi+snbtWixduvSu2oiOjkZoaGiV9omJicGSJUvu6rhEREzMiIiqwaVLl5CWllbXYRDRPY6JGRHZnL179+Khhx7C+PHjMXnyZJw8eRJr167F888/j5kzZ2LUqFF47rnn8MMPP2DatGkYOHAgduzYYd7/8uXLmDZtGkJDQ/H888+joKAAALBv3z5MnjwZEydOREhICN577z0AJT1kY8eOxeTJkxEWFga9Xm9u69ixYwgJCcGJEyfKjDclJQVr1qzBsWPH8NJLLwEoWRkgNDQUY8eOxaxZsxAXF2deg/CGf/7zn3jxxRcBAHq9Hr169UJ+fj4eeOABrF27FpMnT8bgwYPNs7oTUT1Qe+ulExFVLC4uToSGhors7GwhhBAXLlwQ/fr1EytXrhSDBg0SeXl5ori4WPTo0UOsWLFCCCHE7t27xfDhw4UQQqxZs0aEhISIrKwsIcuyePbZZ8WqVauELMti+vTpIi4uTgghRGpqqggICBBZWVkiKipKtG/fXiQlJQkhhIiKihJjxowRhw8fFkOHDhWxsbEVxr1582Yxe/ZsIYQQkZGRYujQoSIrK8v82KhRo4Qsy2Lw4MHi/Pnzori4WISEhIjg4GAhhBD79+8Xjz/+uBBCCH9/f7FhwwYhhBCnT58WnTp1ElqttjpeXiKycZxglohsyqFDh5Ceno7HHnvMXCZJEhISEtC3b180bNgQAODl5YUBAwYAAHx9fZGTk2OuP2zYMLi7uwMAJk2ahFWrVkGSJHz00UfYv38/duzYgcuXL0MIgeLiYgBA06ZN0bx5c3MbqampePLJJzFlyhS0b9++Ss/h4MGDGD16tDmGiRMnYvny5UhKSsKwYcNw4MABtG3bFr1798b58+dx8eJF/P777xg+fLi5jRtL7nTs2BF6vR5FRUUWC08T0f2JlzKJyKbIsow+ffpg+/bt5v9v2rQJbdu2tVo7VaUq/belUqm0aE+lUqGoqAgTJkzA2bNn0aFDB7zwwgtQqVQQf8+x7ejoaNXGF198ga1bt+LUqVNVfg63E0LAaDRi6NChiIiIwKFDh9CvXz/07dsXf/zxBw4cOIChQ4ea699Iwm4swSM4FzhRvcDEjIhsSp8+fXDo0CFcvnwZABAREYGxY8dCp9NVuo29e/ciNzcXJpMJmzZtQnBwMOLj41FQUICnn34agwcPRnR0NPR6falJFAB4enqiW7duePHFF/HCCy+Ye9bKolQqYTQaAZQs+rxz505kZ2cDADZv3gxXV1e0aNEC3bp1Q2JiIvbv34++ffuiX79+WL9+PVq2bAk3N7dKP0ciuj/xUiYR2ZQ2bdpg6dKleOaZZyCEgEqlwn//+18cPny40slZ69atMWfOHOTl5SEoKAizZ8+GWq1GSEgIRo0aBY1GA39/f7Rp0wbx8fFWPXG3mjBhAnbt2oWVK1fi9ddfL7NeYGAgPvjgA8ybNw/r1q3DY489hkcffRSyLMPd3R0ff/wxFIqS38LBwcE4ffo03N3dERQUhNzcXIvLmERUf3GtTCIiIiIbwR4zIqJKuHLlChYsWFDqY61atTJPvUFEdDfYY0ZERERkIzj4n4iIiMhGMDEjIiIishFMzIiIiIhsBBMzIiIiIhvBxIyIiIjIRvw/T/VK+tBunh0AAAAASUVORK5CYII=\n",
      "text/plain": [
       "<Figure size 720x360 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(10,5))\n",
    "plt.title('Distribuição do valor da passagem de acordo com a cidade de embarque')\n",
    "sns.stripplot(x=\"embark_town\", y=\"fare\", data=titanic)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "3 - Crie uma visualização que mostre as distribuições do valor da passagem, de acordo com a cidade de embarque, sexo e se o passageiro sobreviveu ou não. Você pode escolher a técnica que julgar mais adequada. Que diferença você consegue notar nas distribuições dos passageiros que sobreviveram em relação aos que não sobreviveram?"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<seaborn.axisgrid.FacetGrid at 0x2600a331940>"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 792.85x360 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.catplot(x=\"embark_town\", y=\"fare\", hue = 'sex', col = 'survived', kind = 'violin', split = True, data=titanic)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Resposta: A proporção de passageiros que sobreviveram e que embarcaram na cidade de Cherbourg é maior nesta vizualização."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "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": 4
}