From 329b857552f8cbb75eddbf1ccd07be0d6ba54d2e Mon Sep 17 00:00:00 2001
From: danisnegrao <danisnegrao@gmail.com>
Date: Wed, 25 Oct 2023 20:29:00 -0300
Subject: [PATCH] Atividade Semana12 Dani_negrao

---
 exercicios/para-casa/Ex_dani2_S12.ipynb   |  740 ++++
 exercicios/para-casa/covidsp.csv          |  405 ++
 exercicios/para-sala/Ex_dani1_sem12.ipynb | 4811 +++++++++++++++++++++
 exercicios/para-sala/titanic.csv          |  892 ++++
 material/aula_s12.ipynb                   |  699 ++-
 5 files changed, 7355 insertions(+), 192 deletions(-)
 create mode 100644 exercicios/para-casa/Ex_dani2_S12.ipynb
 create mode 100644 exercicios/para-casa/covidsp.csv
 create mode 100644 exercicios/para-sala/Ex_dani1_sem12.ipynb
 create mode 100644 exercicios/para-sala/titanic.csv

diff --git a/exercicios/para-casa/Ex_dani2_S12.ipynb b/exercicios/para-casa/Ex_dani2_S12.ipynb
new file mode 100644
index 0000000..ee555d3
--- /dev/null
+++ b/exercicios/para-casa/Ex_dani2_S12.ipynb
@@ -0,0 +1,740 @@
+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 95,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import pandas as pd\n",
+    "import numpy as np\n",
+    "import matplotlib.pyplot as plt"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Este banco de dados se refere ao controle da COVID-19 no estado de São Paulo durante Março de 2020 a Abril de 2021. Ele inclui informações vitais, tais como:\n",
+    "\n",
+    "1. **Data do Boletim:** A data em que os dados foram registrados.\n",
+    "2. **Número de Casos Suspeitos:** Total de casos suspeitos de COVID-19.\n",
+    "3. **Número de Casos Confirmados:** Total de casos confirmados de COVID-19.\n",
+    "4. **Mortes pelo SIVEP-Gripe:** Dados de mortalidade fornecidos pelo Sistema de Vigilância Epidemiológica da Gripe (SIVEP-Gripe).\n",
+    "5. **Mortes pelo SIM:** Dados de mortalidade fornecidos pelo Sistema de Informação sobre Mortalidade (SIM) do Ministério da Saúde.\n",
+    "6. **Percentual de UTI Utilizada em Hospitais Públicos:** A porcentagem de leitos de UTI ocupados nos hospitais públicos.\n",
+    "7. **Estimativa de Casos Recuperados:** Número estimado de casos que resultaram em recuperação.\n",
+    "8. **Cidade ou Local dos Dados:** O nome da cidade ou local a que os dados se referem.\n",
+    "\n",
+    "Essas informações essenciais fornecem uma visão abrangente da situação da COVID-19 no estado de São Paulo durante o ano de 2020."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 96,
+   "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>Date</th>\n",
+       "      <th>Suspects</th>\n",
+       "      <th>ConfirmedCases</th>\n",
+       "      <th>DeathsSivep</th>\n",
+       "      <th>DeathsProAim</th>\n",
+       "      <th>CtiUsage</th>\n",
+       "      <th>Recovered</th>\n",
+       "      <th>Location</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>2020-03-23</td>\n",
+       "      <td>4743</td>\n",
+       "      <td>477</td>\n",
+       "      <td>30</td>\n",
+       "      <td>30</td>\n",
+       "      <td>67</td>\n",
+       "      <td>0</td>\n",
+       "      <td>sao paulo</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>2020-03-24</td>\n",
+       "      <td>4572</td>\n",
+       "      <td>484</td>\n",
+       "      <td>36</td>\n",
+       "      <td>36</td>\n",
+       "      <td>67</td>\n",
+       "      <td>0</td>\n",
+       "      <td>sao paulo</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>2020-03-25</td>\n",
+       "      <td>4300</td>\n",
+       "      <td>537</td>\n",
+       "      <td>41</td>\n",
+       "      <td>41</td>\n",
+       "      <td>67</td>\n",
+       "      <td>0</td>\n",
+       "      <td>sao paulo</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>2020-03-26</td>\n",
+       "      <td>4621</td>\n",
+       "      <td>565</td>\n",
+       "      <td>50</td>\n",
+       "      <td>50</td>\n",
+       "      <td>67</td>\n",
+       "      <td>0</td>\n",
+       "      <td>sao paulo</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>2020-03-27</td>\n",
+       "      <td>4621</td>\n",
+       "      <td>572</td>\n",
+       "      <td>62</td>\n",
+       "      <td>62</td>\n",
+       "      <td>67</td>\n",
+       "      <td>0</td>\n",
+       "      <td>sao paulo</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>...</th>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>399</th>\n",
+       "      <td>2021-04-26</td>\n",
+       "      <td>0</td>\n",
+       "      <td>799094</td>\n",
+       "      <td>26600</td>\n",
+       "      <td>26600</td>\n",
+       "      <td>81</td>\n",
+       "      <td>742116</td>\n",
+       "      <td>sao paulo</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>400</th>\n",
+       "      <td>2021-04-27</td>\n",
+       "      <td>0</td>\n",
+       "      <td>803849</td>\n",
+       "      <td>26844</td>\n",
+       "      <td>26844</td>\n",
+       "      <td>79</td>\n",
+       "      <td>744410</td>\n",
+       "      <td>sao paulo</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>401</th>\n",
+       "      <td>2021-04-28</td>\n",
+       "      <td>0</td>\n",
+       "      <td>808863</td>\n",
+       "      <td>27027</td>\n",
+       "      <td>27027</td>\n",
+       "      <td>80</td>\n",
+       "      <td>746368</td>\n",
+       "      <td>sao paulo</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>402</th>\n",
+       "      <td>2021-04-29</td>\n",
+       "      <td>0</td>\n",
+       "      <td>840834</td>\n",
+       "      <td>27194</td>\n",
+       "      <td>27194</td>\n",
+       "      <td>80</td>\n",
+       "      <td>746855</td>\n",
+       "      <td>sao paulo</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>403</th>\n",
+       "      <td>2021-04-30</td>\n",
+       "      <td>0</td>\n",
+       "      <td>844334</td>\n",
+       "      <td>27329</td>\n",
+       "      <td>27329</td>\n",
+       "      <td>77</td>\n",
+       "      <td>751622</td>\n",
+       "      <td>sao paulo</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "<p>404 rows × 8 columns</p>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "           Date  Suspects  ConfirmedCases  DeathsSivep  DeathsProAim  \\\n",
+       "0    2020-03-23      4743             477           30            30   \n",
+       "1    2020-03-24      4572             484           36            36   \n",
+       "2    2020-03-25      4300             537           41            41   \n",
+       "3    2020-03-26      4621             565           50            50   \n",
+       "4    2020-03-27      4621             572           62            62   \n",
+       "..          ...       ...             ...          ...           ...   \n",
+       "399  2021-04-26         0          799094        26600         26600   \n",
+       "400  2021-04-27         0          803849        26844         26844   \n",
+       "401  2021-04-28         0          808863        27027         27027   \n",
+       "402  2021-04-29         0          840834        27194         27194   \n",
+       "403  2021-04-30         0          844334        27329         27329   \n",
+       "\n",
+       "     CtiUsage  Recovered   Location  \n",
+       "0          67          0  sao paulo  \n",
+       "1          67          0  sao paulo  \n",
+       "2          67          0  sao paulo  \n",
+       "3          67          0  sao paulo  \n",
+       "4          67          0  sao paulo  \n",
+       "..        ...        ...        ...  \n",
+       "399        81     742116  sao paulo  \n",
+       "400        79     744410  sao paulo  \n",
+       "401        80     746368  sao paulo  \n",
+       "402        80     746855  sao paulo  \n",
+       "403        77     751622  sao paulo  \n",
+       "\n",
+       "[404 rows x 8 columns]"
+      ]
+     },
+     "execution_count": 96,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "df_dan_cd = pd.read_csv(\"covidsp.csv\")\n",
+    "df_dan_cd"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 97,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "Index(['Date', 'Suspects', 'ConfirmedCases', 'DeathsSivep', 'DeathsProAim',\n",
+       "       'CtiUsage', 'Recovered', 'Location'],\n",
+       "      dtype='object')"
+      ]
+     },
+     "execution_count": 97,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "df_dan_cd.columns"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 98,
+   "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>Data</th>\n",
+       "      <th>Suspeitos</th>\n",
+       "      <th>CasosConfirmados</th>\n",
+       "      <th>MortesSivep</th>\n",
+       "      <th>MortesSIM</th>\n",
+       "      <th>UTI</th>\n",
+       "      <th>Recuperados</th>\n",
+       "      <th>Localizacao</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>2020-03-23</td>\n",
+       "      <td>4743</td>\n",
+       "      <td>477</td>\n",
+       "      <td>30</td>\n",
+       "      <td>30</td>\n",
+       "      <td>67</td>\n",
+       "      <td>0</td>\n",
+       "      <td>sao paulo</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>2020-03-24</td>\n",
+       "      <td>4572</td>\n",
+       "      <td>484</td>\n",
+       "      <td>36</td>\n",
+       "      <td>36</td>\n",
+       "      <td>67</td>\n",
+       "      <td>0</td>\n",
+       "      <td>sao paulo</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>2020-03-25</td>\n",
+       "      <td>4300</td>\n",
+       "      <td>537</td>\n",
+       "      <td>41</td>\n",
+       "      <td>41</td>\n",
+       "      <td>67</td>\n",
+       "      <td>0</td>\n",
+       "      <td>sao paulo</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>2020-03-26</td>\n",
+       "      <td>4621</td>\n",
+       "      <td>565</td>\n",
+       "      <td>50</td>\n",
+       "      <td>50</td>\n",
+       "      <td>67</td>\n",
+       "      <td>0</td>\n",
+       "      <td>sao paulo</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>2020-03-27</td>\n",
+       "      <td>4621</td>\n",
+       "      <td>572</td>\n",
+       "      <td>62</td>\n",
+       "      <td>62</td>\n",
+       "      <td>67</td>\n",
+       "      <td>0</td>\n",
+       "      <td>sao paulo</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>...</th>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>399</th>\n",
+       "      <td>2021-04-26</td>\n",
+       "      <td>0</td>\n",
+       "      <td>799094</td>\n",
+       "      <td>26600</td>\n",
+       "      <td>26600</td>\n",
+       "      <td>81</td>\n",
+       "      <td>742116</td>\n",
+       "      <td>sao paulo</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>400</th>\n",
+       "      <td>2021-04-27</td>\n",
+       "      <td>0</td>\n",
+       "      <td>803849</td>\n",
+       "      <td>26844</td>\n",
+       "      <td>26844</td>\n",
+       "      <td>79</td>\n",
+       "      <td>744410</td>\n",
+       "      <td>sao paulo</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>401</th>\n",
+       "      <td>2021-04-28</td>\n",
+       "      <td>0</td>\n",
+       "      <td>808863</td>\n",
+       "      <td>27027</td>\n",
+       "      <td>27027</td>\n",
+       "      <td>80</td>\n",
+       "      <td>746368</td>\n",
+       "      <td>sao paulo</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>402</th>\n",
+       "      <td>2021-04-29</td>\n",
+       "      <td>0</td>\n",
+       "      <td>840834</td>\n",
+       "      <td>27194</td>\n",
+       "      <td>27194</td>\n",
+       "      <td>80</td>\n",
+       "      <td>746855</td>\n",
+       "      <td>sao paulo</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>403</th>\n",
+       "      <td>2021-04-30</td>\n",
+       "      <td>0</td>\n",
+       "      <td>844334</td>\n",
+       "      <td>27329</td>\n",
+       "      <td>27329</td>\n",
+       "      <td>77</td>\n",
+       "      <td>751622</td>\n",
+       "      <td>sao paulo</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "<p>404 rows × 8 columns</p>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "           Data  Suspeitos  CasosConfirmados  MortesSivep  MortesSIM  UTI  \\\n",
+       "0    2020-03-23       4743               477           30         30   67   \n",
+       "1    2020-03-24       4572               484           36         36   67   \n",
+       "2    2020-03-25       4300               537           41         41   67   \n",
+       "3    2020-03-26       4621               565           50         50   67   \n",
+       "4    2020-03-27       4621               572           62         62   67   \n",
+       "..          ...        ...               ...          ...        ...  ...   \n",
+       "399  2021-04-26          0            799094        26600      26600   81   \n",
+       "400  2021-04-27          0            803849        26844      26844   79   \n",
+       "401  2021-04-28          0            808863        27027      27027   80   \n",
+       "402  2021-04-29          0            840834        27194      27194   80   \n",
+       "403  2021-04-30          0            844334        27329      27329   77   \n",
+       "\n",
+       "     Recuperados Localizacao  \n",
+       "0              0   sao paulo  \n",
+       "1              0   sao paulo  \n",
+       "2              0   sao paulo  \n",
+       "3              0   sao paulo  \n",
+       "4              0   sao paulo  \n",
+       "..           ...         ...  \n",
+       "399       742116   sao paulo  \n",
+       "400       744410   sao paulo  \n",
+       "401       746368   sao paulo  \n",
+       "402       746855   sao paulo  \n",
+       "403       751622   sao paulo  \n",
+       "\n",
+       "[404 rows x 8 columns]"
+      ]
+     },
+     "execution_count": 98,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "traducao = {\n",
+    "    'Date': 'Data',\n",
+    "    'Suspects': 'Suspeitos',\n",
+    "    'ConfirmedCases': 'CasosConfirmados',\n",
+    "    'DeathsSivep': 'MortesSivep',\n",
+    "    'DeathsProAim': 'MortesSIM',\n",
+    "    'CtiUsage': 'UTI',\n",
+    "    'Recovered': 'Recuperados',\n",
+    "    'Location': 'Localizacao'\n",
+    "}\n",
+    "\n",
+    "# Renomeando as colunas\n",
+    "df_dan_cd.rename(columns=traducao, inplace=True)\n",
+    "df_dan_cd"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 99,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "False"
+      ]
+     },
+     "execution_count": 99,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "df_dan_cd.isnull().values.any()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 100,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "142122270"
+      ]
+     },
+     "execution_count": 100,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "#Determinando o total de casos confirmados durante o periodo analisado\n",
+    "\n",
+    "casos_confirmados = df_dan_cd['CasosConfirmados'].values\n",
+    "\n",
+    "soma_casos_confirmados = np.sum(casos_confirmados)\n",
+    "\n",
+    "soma_casos_confirmados\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 101,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "142720302"
+      ]
+     },
+     "execution_count": 101,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "#Determinando o total de casos Suspeitos durante o periodo analisado\n",
+    "\n",
+    "casos_suspeitos = df_dan_cd['Suspeitos'].values\n",
+    "\n",
+    "soma_casos_suspeitos = np.sum(casos_suspeitos)\n",
+    "\n",
+    "soma_casos_suspeitos"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 120,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 640x480 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "\n",
+    "categorias = ['Casos Suspeitos', 'Casos Confirmados']\n",
+    "\n",
+    "valores = [soma_casos_suspeitos, soma_casos_confirmados]\n",
+    "\n",
+    "plt.bar(categorias, valores, color=['limegreen', 'blue'], edgecolor=['black'])\n",
+    "\n",
+    "plt.xlabel('Tipo de Casos')\n",
+    "plt.ylabel('Número de Casos')\n",
+    "\n",
+    "for i in range(len(categorias)):\n",
+    "    plt.text(i, valores[i] + 20, str(valores[i]), ha='center')\n",
+    "\n",
+    "plt.title('Total de Casos Suspeitos e Confirmados')\n",
+    "\n",
+    "plt.show()\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 103,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 700x300 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "#Frenquencia de utilização de UTI por semana\n",
+    "numeros_de_uti = df_dan_cd['UTI'].values\n",
+    "plt.figure(figsize=(7, 3))\n",
+    "plt.hist(numeros_de_uti, bins=100, edgecolor='black', color='blue')\n",
+    "plt.xlabel('Percentual')\n",
+    "plt.ylabel('Frequência')\n",
+    "plt.title('Percentual de Uso da UTI em Rede Pública')\n",
+    "\n",
+    "\n",
+    "plt.show()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 105,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "4918732"
+      ]
+     },
+     "execution_count": 105,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "#Soma de mortes confirmadas pelo Sistema de Vigilância Epidemiológica da Gripe (SIVEP-Gripe)\n",
+    "Mortes_Sivep = df_dan_cd['MortesSivep'].values\n",
+    "\n",
+    "soma_mortesSivep = np.sum(Mortes_Sivep)\n",
+    "\n",
+    "soma_mortesSivep"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 106,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "4912005"
+      ]
+     },
+     "execution_count": 106,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "#Soma de mortes confirmadas pelo Sistema de Informação sobre Mortalidade (SIM)\n",
+    "Mortes_Sim = df_dan_cd['MortesSIM'].values\n",
+    "\n",
+    "soma_mortesSim = np.sum(Mortes_Sim)\n",
+    "\n",
+    "soma_mortesSim"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 127,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "O total de mortes confirmadas pela categoria foi de 9830737\n",
+      "A diferença de mortes confirmadas por categoria foi de 6727\n"
+     ]
+    }
+   ],
+   "source": [
+    "#Total e diferença de mortes Confirmadas pelas Categorias\n",
+    "Total_de_mortes = soma_mortesSim + soma_mortesSivep\n",
+    "print(f'O total de mortes confirmadas pela categoria foi de {Total_de_mortes}')\n",
+    "diferenca_pela_categotia = np.subtract(soma_mortesSivep, soma_mortesSim)\n",
+    "print(f'A diferença de mortes confirmadas por categoria foi de {diferenca_pela_categotia}')\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 140,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 600x600 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "\n",
+    "\n",
+    "#Cidade onde aconteceu a coleta de dados\n",
+    "\n",
+    "contagem_cidades = df_dan_cd['Localizacao'].value_counts()\n",
+    "\n",
+    "\n",
+    "plt.figure(figsize=(6, 6))\n",
+    "plt.pie(contagem_cidades, labels=contagem_cidades.index, autopct='%1.1f%%', startangle=140)\n",
+    "plt.title('Distribuição das Cidades na Coluna \"localizacao\"')\n",
+    "plt.show()\n",
+    "\n"
+   ]
+  }
+ ],
+ "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": "3.11.4"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 2
+}
diff --git a/exercicios/para-casa/covidsp.csv b/exercicios/para-casa/covidsp.csv
new file mode 100644
index 0000000..18cb3d3
--- /dev/null
+++ b/exercicios/para-casa/covidsp.csv
@@ -0,0 +1,405 @@
+Date,Suspects,ConfirmedCases,DeathsSivep,DeathsProAim,CtiUsage,Recovered,Location
+2020-03-23,4743,477,30,30,67,0,sao paulo
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diff --git a/exercicios/para-sala/Ex_dani1_sem12.ipynb b/exercicios/para-sala/Ex_dani1_sem12.ipynb
new file mode 100644
index 0000000..794957e
--- /dev/null
+++ b/exercicios/para-sala/Ex_dani1_sem12.ipynb
@@ -0,0 +1,4811 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 62,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import pandas as pd\n",
+    "\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 63,
+   "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>PassengerId</th>\n",
+       "      <th>Survived</th>\n",
+       "      <th>Pclass</th>\n",
+       "      <th>Name</th>\n",
+       "      <th>Sex</th>\n",
+       "      <th>Age</th>\n",
+       "      <th>SibSp</th>\n",
+       "      <th>Parch</th>\n",
+       "      <th>Ticket</th>\n",
+       "      <th>Fare</th>\n",
+       "      <th>Cabin</th>\n",
+       "      <th>Embarked</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>1</td>\n",
+       "      <td>0</td>\n",
+       "      <td>3</td>\n",
+       "      <td>Braund, Mr. Owen Harris</td>\n",
+       "      <td>male</td>\n",
+       "      <td>22.0</td>\n",
+       "      <td>1</td>\n",
+       "      <td>0</td>\n",
+       "      <td>A/5 21171</td>\n",
+       "      <td>7.2500</td>\n",
+       "      <td>NaN</td>\n",
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+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>2</td>\n",
+       "      <td>1</td>\n",
+       "      <td>1</td>\n",
+       "      <td>Cumings, Mrs. John Bradley (Florence Briggs Th...</td>\n",
+       "      <td>female</td>\n",
+       "      <td>38.0</td>\n",
+       "      <td>1</td>\n",
+       "      <td>0</td>\n",
+       "      <td>PC 17599</td>\n",
+       "      <td>71.2833</td>\n",
+       "      <td>C85</td>\n",
+       "      <td>C</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>3</td>\n",
+       "      <td>1</td>\n",
+       "      <td>3</td>\n",
+       "      <td>Heikkinen, Miss. Laina</td>\n",
+       "      <td>female</td>\n",
+       "      <td>26.0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>STON/O2. 3101282</td>\n",
+       "      <td>7.9250</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>S</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>4</td>\n",
+       "      <td>1</td>\n",
+       "      <td>1</td>\n",
+       "      <td>Futrelle, Mrs. Jacques Heath (Lily May Peel)</td>\n",
+       "      <td>female</td>\n",
+       "      <td>35.0</td>\n",
+       "      <td>1</td>\n",
+       "      <td>0</td>\n",
+       "      <td>113803</td>\n",
+       "      <td>53.1000</td>\n",
+       "      <td>C123</td>\n",
+       "      <td>S</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>5</td>\n",
+       "      <td>0</td>\n",
+       "      <td>3</td>\n",
+       "      <td>Allen, Mr. William Henry</td>\n",
+       "      <td>male</td>\n",
+       "      <td>35.0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>373450</td>\n",
+       "      <td>8.0500</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>S</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>...</th>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
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+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>886</th>\n",
+       "      <td>887</td>\n",
+       "      <td>0</td>\n",
+       "      <td>2</td>\n",
+       "      <td>Montvila, Rev. Juozas</td>\n",
+       "      <td>male</td>\n",
+       "      <td>27.0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>211536</td>\n",
+       "      <td>13.0000</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>S</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>887</th>\n",
+       "      <td>888</td>\n",
+       "      <td>1</td>\n",
+       "      <td>1</td>\n",
+       "      <td>Graham, Miss. Margaret Edith</td>\n",
+       "      <td>female</td>\n",
+       "      <td>19.0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>112053</td>\n",
+       "      <td>30.0000</td>\n",
+       "      <td>B42</td>\n",
+       "      <td>S</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>888</th>\n",
+       "      <td>889</td>\n",
+       "      <td>0</td>\n",
+       "      <td>3</td>\n",
+       "      <td>Johnston, Miss. Catherine Helen \"Carrie\"</td>\n",
+       "      <td>female</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>1</td>\n",
+       "      <td>2</td>\n",
+       "      <td>W./C. 6607</td>\n",
+       "      <td>23.4500</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>S</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>889</th>\n",
+       "      <td>890</td>\n",
+       "      <td>1</td>\n",
+       "      <td>1</td>\n",
+       "      <td>Behr, Mr. Karl Howell</td>\n",
+       "      <td>male</td>\n",
+       "      <td>26.0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>111369</td>\n",
+       "      <td>30.0000</td>\n",
+       "      <td>C148</td>\n",
+       "      <td>C</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>890</th>\n",
+       "      <td>891</td>\n",
+       "      <td>0</td>\n",
+       "      <td>3</td>\n",
+       "      <td>Dooley, Mr. Patrick</td>\n",
+       "      <td>male</td>\n",
+       "      <td>32.0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>370376</td>\n",
+       "      <td>7.7500</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>Q</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "<p>891 rows × 12 columns</p>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "     PassengerId  Survived  Pclass  \\\n",
+       "0              1         0       3   \n",
+       "1              2         1       1   \n",
+       "2              3         1       3   \n",
+       "3              4         1       1   \n",
+       "4              5         0       3   \n",
+       "..           ...       ...     ...   \n",
+       "886          887         0       2   \n",
+       "887          888         1       1   \n",
+       "888          889         0       3   \n",
+       "889          890         1       1   \n",
+       "890          891         0       3   \n",
+       "\n",
+       "                                                  Name     Sex   Age  SibSp  \\\n",
+       "0                              Braund, Mr. Owen Harris    male  22.0      1   \n",
+       "1    Cumings, Mrs. John Bradley (Florence Briggs Th...  female  38.0      1   \n",
+       "2                               Heikkinen, Miss. Laina  female  26.0      0   \n",
+       "3         Futrelle, Mrs. Jacques Heath (Lily May Peel)  female  35.0      1   \n",
+       "4                             Allen, Mr. William Henry    male  35.0      0   \n",
+       "..                                                 ...     ...   ...    ...   \n",
+       "886                              Montvila, Rev. Juozas    male  27.0      0   \n",
+       "887                       Graham, Miss. Margaret Edith  female  19.0      0   \n",
+       "888           Johnston, Miss. Catherine Helen \"Carrie\"  female   NaN      1   \n",
+       "889                              Behr, Mr. Karl Howell    male  26.0      0   \n",
+       "890                                Dooley, Mr. Patrick    male  32.0      0   \n",
+       "\n",
+       "     Parch            Ticket     Fare Cabin Embarked  \n",
+       "0        0         A/5 21171   7.2500   NaN        S  \n",
+       "1        0          PC 17599  71.2833   C85        C  \n",
+       "2        0  STON/O2. 3101282   7.9250   NaN        S  \n",
+       "3        0            113803  53.1000  C123        S  \n",
+       "4        0            373450   8.0500   NaN        S  \n",
+       "..     ...               ...      ...   ...      ...  \n",
+       "886      0            211536  13.0000   NaN        S  \n",
+       "887      0            112053  30.0000   B42        S  \n",
+       "888      2        W./C. 6607  23.4500   NaN        S  \n",
+       "889      0            111369  30.0000  C148        C  \n",
+       "890      0            370376   7.7500   NaN        Q  \n",
+       "\n",
+       "[891 rows x 12 columns]"
+      ]
+     },
+     "execution_count": 63,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "# carregando o dataset \n",
+    "df_dani = pd.read_csv(\"titanic.csv\")\n",
+    "df_dani"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 64,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "Index(['PassengerId', 'Survived', 'Pclass', 'Name', 'Sex', 'Age', 'SibSp',\n",
+       "       'Parch', 'Ticket', 'Fare', 'Cabin', 'Embarked'],\n",
+       "      dtype='object')"
+      ]
+     },
+     "execution_count": 64,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "df_dani.columns\n",
+    "\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 65,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Index(['IdPassageiro', 'Sobreviveu', 'Classe', 'Nome', 'Sexo', 'Idade',\n",
+      "       'IrmaosConjuge', 'PaisFilhos', 'Bilhete', 'Tarifa', 'Cabine',\n",
+      "       'Embarque'],\n",
+      "      dtype='object')\n"
+     ]
+    }
+   ],
+   "source": [
+    "\n",
+    "traducoes = {\n",
+    "    'PassengerId': 'IdPassageiro',\n",
+    "    'Survived': 'Sobreviveu',\n",
+    "    'Pclass': 'Classe',\n",
+    "    'Name': 'Nome',\n",
+    "    'Sex': 'Sexo',\n",
+    "    'Age': 'Idade',\n",
+    "    'SibSp': 'IrmaosConjuge',\n",
+    "    'Parch': 'PaisFilhos',\n",
+    "    'Ticket': 'Bilhete',\n",
+    "    'Fare': 'Tarifa',\n",
+    "    'Cabin': 'Cabine',\n",
+    "    'Embarked': 'Embarque'\n",
+    "}\n",
+    "\n",
+    "# Renomeie as colunas usando o dicionário de tradução\n",
+    "df_dani.rename(columns=traducoes, inplace=True)\n",
+    "\n",
+    "# Agora as colunas estão traduzidas para português\n",
+    "print(df_dani.columns)\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 66,
+   "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>IdPassageiro</th>\n",
+       "      <th>Sobreviveu</th>\n",
+       "      <th>Classe</th>\n",
+       "      <th>Nome</th>\n",
+       "      <th>Sexo</th>\n",
+       "      <th>Idade</th>\n",
+       "      <th>IrmaosConjuge</th>\n",
+       "      <th>PaisFilhos</th>\n",
+       "      <th>Bilhete</th>\n",
+       "      <th>Tarifa</th>\n",
+       "      <th>Cabine</th>\n",
+       "      <th>Embarque</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>1</td>\n",
+       "      <td>0</td>\n",
+       "      <td>3</td>\n",
+       "      <td>Braund, Mr. Owen Harris</td>\n",
+       "      <td>male</td>\n",
+       "      <td>22.0</td>\n",
+       "      <td>1</td>\n",
+       "      <td>0</td>\n",
+       "      <td>A/5 21171</td>\n",
+       "      <td>7.2500</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>S</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>2</td>\n",
+       "      <td>1</td>\n",
+       "      <td>1</td>\n",
+       "      <td>Cumings, Mrs. John Bradley (Florence Briggs Th...</td>\n",
+       "      <td>female</td>\n",
+       "      <td>38.0</td>\n",
+       "      <td>1</td>\n",
+       "      <td>0</td>\n",
+       "      <td>PC 17599</td>\n",
+       "      <td>71.2833</td>\n",
+       "      <td>C85</td>\n",
+       "      <td>C</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>3</td>\n",
+       "      <td>1</td>\n",
+       "      <td>3</td>\n",
+       "      <td>Heikkinen, Miss. Laina</td>\n",
+       "      <td>female</td>\n",
+       "      <td>26.0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>STON/O2. 3101282</td>\n",
+       "      <td>7.9250</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>S</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>4</td>\n",
+       "      <td>1</td>\n",
+       "      <td>1</td>\n",
+       "      <td>Futrelle, Mrs. Jacques Heath (Lily May Peel)</td>\n",
+       "      <td>female</td>\n",
+       "      <td>35.0</td>\n",
+       "      <td>1</td>\n",
+       "      <td>0</td>\n",
+       "      <td>113803</td>\n",
+       "      <td>53.1000</td>\n",
+       "      <td>C123</td>\n",
+       "      <td>S</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>5</td>\n",
+       "      <td>0</td>\n",
+       "      <td>3</td>\n",
+       "      <td>Allen, Mr. William Henry</td>\n",
+       "      <td>male</td>\n",
+       "      <td>35.0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>373450</td>\n",
+       "      <td>8.0500</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>S</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>...</th>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>886</th>\n",
+       "      <td>887</td>\n",
+       "      <td>0</td>\n",
+       "      <td>2</td>\n",
+       "      <td>Montvila, Rev. Juozas</td>\n",
+       "      <td>male</td>\n",
+       "      <td>27.0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>211536</td>\n",
+       "      <td>13.0000</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>S</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>887</th>\n",
+       "      <td>888</td>\n",
+       "      <td>1</td>\n",
+       "      <td>1</td>\n",
+       "      <td>Graham, Miss. Margaret Edith</td>\n",
+       "      <td>female</td>\n",
+       "      <td>19.0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>112053</td>\n",
+       "      <td>30.0000</td>\n",
+       "      <td>B42</td>\n",
+       "      <td>S</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>888</th>\n",
+       "      <td>889</td>\n",
+       "      <td>0</td>\n",
+       "      <td>3</td>\n",
+       "      <td>Johnston, Miss. Catherine Helen \"Carrie\"</td>\n",
+       "      <td>female</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>1</td>\n",
+       "      <td>2</td>\n",
+       "      <td>W./C. 6607</td>\n",
+       "      <td>23.4500</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>S</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>889</th>\n",
+       "      <td>890</td>\n",
+       "      <td>1</td>\n",
+       "      <td>1</td>\n",
+       "      <td>Behr, Mr. Karl Howell</td>\n",
+       "      <td>male</td>\n",
+       "      <td>26.0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>111369</td>\n",
+       "      <td>30.0000</td>\n",
+       "      <td>C148</td>\n",
+       "      <td>C</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>890</th>\n",
+       "      <td>891</td>\n",
+       "      <td>0</td>\n",
+       "      <td>3</td>\n",
+       "      <td>Dooley, Mr. Patrick</td>\n",
+       "      <td>male</td>\n",
+       "      <td>32.0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>370376</td>\n",
+       "      <td>7.7500</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>Q</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "<p>891 rows × 12 columns</p>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "     IdPassageiro  Sobreviveu  Classe  \\\n",
+       "0               1           0       3   \n",
+       "1               2           1       1   \n",
+       "2               3           1       3   \n",
+       "3               4           1       1   \n",
+       "4               5           0       3   \n",
+       "..            ...         ...     ...   \n",
+       "886           887           0       2   \n",
+       "887           888           1       1   \n",
+       "888           889           0       3   \n",
+       "889           890           1       1   \n",
+       "890           891           0       3   \n",
+       "\n",
+       "                                                  Nome    Sexo  Idade  \\\n",
+       "0                              Braund, Mr. Owen Harris    male   22.0   \n",
+       "1    Cumings, Mrs. John Bradley (Florence Briggs Th...  female   38.0   \n",
+       "2                               Heikkinen, Miss. Laina  female   26.0   \n",
+       "3         Futrelle, Mrs. Jacques Heath (Lily May Peel)  female   35.0   \n",
+       "4                             Allen, Mr. William Henry    male   35.0   \n",
+       "..                                                 ...     ...    ...   \n",
+       "886                              Montvila, Rev. Juozas    male   27.0   \n",
+       "887                       Graham, Miss. Margaret Edith  female   19.0   \n",
+       "888           Johnston, Miss. Catherine Helen \"Carrie\"  female    NaN   \n",
+       "889                              Behr, Mr. Karl Howell    male   26.0   \n",
+       "890                                Dooley, Mr. Patrick    male   32.0   \n",
+       "\n",
+       "     IrmaosConjuge  PaisFilhos           Bilhete   Tarifa Cabine Embarque  \n",
+       "0                1           0         A/5 21171   7.2500    NaN        S  \n",
+       "1                1           0          PC 17599  71.2833    C85        C  \n",
+       "2                0           0  STON/O2. 3101282   7.9250    NaN        S  \n",
+       "3                1           0            113803  53.1000   C123        S  \n",
+       "4                0           0            373450   8.0500    NaN        S  \n",
+       "..             ...         ...               ...      ...    ...      ...  \n",
+       "886              0           0            211536  13.0000    NaN        S  \n",
+       "887              0           0            112053  30.0000    B42        S  \n",
+       "888              1           2        W./C. 6607  23.4500    NaN        S  \n",
+       "889              0           0            111369  30.0000   C148        C  \n",
+       "890              0           0            370376   7.7500    NaN        Q  \n",
+       "\n",
+       "[891 rows x 12 columns]"
+      ]
+     },
+     "execution_count": 66,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "df_dani"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 67,
+   "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>IdPassageiro</th>\n",
+       "      <th>Sobreviveu</th>\n",
+       "      <th>Classe</th>\n",
+       "      <th>Nome</th>\n",
+       "      <th>Sexo</th>\n",
+       "      <th>Idade</th>\n",
+       "      <th>IrmaosConjuge</th>\n",
+       "      <th>PaisFilhos</th>\n",
+       "      <th>Bilhete</th>\n",
+       "      <th>Tarifa</th>\n",
+       "      <th>Cabine</th>\n",
+       "      <th>Embarque</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>7</th>\n",
+       "      <td>8</td>\n",
+       "      <td>0</td>\n",
+       "      <td>3</td>\n",
+       "      <td>Palsson, Master. Gosta Leonard</td>\n",
+       "      <td>male</td>\n",
+       "      <td>2.0</td>\n",
+       "      <td>3</td>\n",
+       "      <td>1</td>\n",
+       "      <td>349909</td>\n",
+       "      <td>21.0750</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>S</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>9</th>\n",
+       "      <td>10</td>\n",
+       "      <td>1</td>\n",
+       "      <td>2</td>\n",
+       "      <td>Nasser, Mrs. Nicholas (Adele Achem)</td>\n",
+       "      <td>female</td>\n",
+       "      <td>14.0</td>\n",
+       "      <td>1</td>\n",
+       "      <td>0</td>\n",
+       "      <td>237736</td>\n",
+       "      <td>30.0708</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>C</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>10</th>\n",
+       "      <td>11</td>\n",
+       "      <td>1</td>\n",
+       "      <td>3</td>\n",
+       "      <td>Sandstrom, Miss. Marguerite Rut</td>\n",
+       "      <td>female</td>\n",
+       "      <td>4.0</td>\n",
+       "      <td>1</td>\n",
+       "      <td>1</td>\n",
+       "      <td>PP 9549</td>\n",
+       "      <td>16.7000</td>\n",
+       "      <td>G6</td>\n",
+       "      <td>S</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>14</th>\n",
+       "      <td>15</td>\n",
+       "      <td>0</td>\n",
+       "      <td>3</td>\n",
+       "      <td>Vestrom, Miss. Hulda Amanda Adolfina</td>\n",
+       "      <td>female</td>\n",
+       "      <td>14.0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>350406</td>\n",
+       "      <td>7.8542</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>S</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>16</th>\n",
+       "      <td>17</td>\n",
+       "      <td>0</td>\n",
+       "      <td>3</td>\n",
+       "      <td>Rice, Master. Eugene</td>\n",
+       "      <td>male</td>\n",
+       "      <td>2.0</td>\n",
+       "      <td>4</td>\n",
+       "      <td>1</td>\n",
+       "      <td>382652</td>\n",
+       "      <td>29.1250</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>Q</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>...</th>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>850</th>\n",
+       "      <td>851</td>\n",
+       "      <td>0</td>\n",
+       "      <td>3</td>\n",
+       "      <td>Andersson, Master. Sigvard Harald Elias</td>\n",
+       "      <td>male</td>\n",
+       "      <td>4.0</td>\n",
+       "      <td>4</td>\n",
+       "      <td>2</td>\n",
+       "      <td>347082</td>\n",
+       "      <td>31.2750</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>S</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>852</th>\n",
+       "      <td>853</td>\n",
+       "      <td>0</td>\n",
+       "      <td>3</td>\n",
+       "      <td>Boulos, Miss. Nourelain</td>\n",
+       "      <td>female</td>\n",
+       "      <td>9.0</td>\n",
+       "      <td>1</td>\n",
+       "      <td>1</td>\n",
+       "      <td>2678</td>\n",
+       "      <td>15.2458</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>C</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>853</th>\n",
+       "      <td>854</td>\n",
+       "      <td>1</td>\n",
+       "      <td>1</td>\n",
+       "      <td>Lines, Miss. Mary Conover</td>\n",
+       "      <td>female</td>\n",
+       "      <td>16.0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>1</td>\n",
+       "      <td>PC 17592</td>\n",
+       "      <td>39.4000</td>\n",
+       "      <td>D28</td>\n",
+       "      <td>S</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>869</th>\n",
+       "      <td>870</td>\n",
+       "      <td>1</td>\n",
+       "      <td>3</td>\n",
+       "      <td>Johnson, Master. Harold Theodor</td>\n",
+       "      <td>male</td>\n",
+       "      <td>4.0</td>\n",
+       "      <td>1</td>\n",
+       "      <td>1</td>\n",
+       "      <td>347742</td>\n",
+       "      <td>11.1333</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>S</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>875</th>\n",
+       "      <td>876</td>\n",
+       "      <td>1</td>\n",
+       "      <td>3</td>\n",
+       "      <td>Najib, Miss. Adele Kiamie \"Jane\"</td>\n",
+       "      <td>female</td>\n",
+       "      <td>15.0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>2667</td>\n",
+       "      <td>7.2250</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>C</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "<p>113 rows × 12 columns</p>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "     IdPassageiro  Sobreviveu  Classe  \\\n",
+       "7               8           0       3   \n",
+       "9              10           1       2   \n",
+       "10             11           1       3   \n",
+       "14             15           0       3   \n",
+       "16             17           0       3   \n",
+       "..            ...         ...     ...   \n",
+       "850           851           0       3   \n",
+       "852           853           0       3   \n",
+       "853           854           1       1   \n",
+       "869           870           1       3   \n",
+       "875           876           1       3   \n",
+       "\n",
+       "                                        Nome    Sexo  Idade  IrmaosConjuge  \\\n",
+       "7             Palsson, Master. Gosta Leonard    male    2.0              3   \n",
+       "9        Nasser, Mrs. Nicholas (Adele Achem)  female   14.0              1   \n",
+       "10           Sandstrom, Miss. Marguerite Rut  female    4.0              1   \n",
+       "14      Vestrom, Miss. Hulda Amanda Adolfina  female   14.0              0   \n",
+       "16                      Rice, Master. Eugene    male    2.0              4   \n",
+       "..                                       ...     ...    ...            ...   \n",
+       "850  Andersson, Master. Sigvard Harald Elias    male    4.0              4   \n",
+       "852                  Boulos, Miss. Nourelain  female    9.0              1   \n",
+       "853                Lines, Miss. Mary Conover  female   16.0              0   \n",
+       "869          Johnson, Master. Harold Theodor    male    4.0              1   \n",
+       "875         Najib, Miss. Adele Kiamie \"Jane\"  female   15.0              0   \n",
+       "\n",
+       "     PaisFilhos   Bilhete   Tarifa Cabine Embarque  \n",
+       "7             1    349909  21.0750    NaN        S  \n",
+       "9             0    237736  30.0708    NaN        C  \n",
+       "10            1   PP 9549  16.7000     G6        S  \n",
+       "14            0    350406   7.8542    NaN        S  \n",
+       "16            1    382652  29.1250    NaN        Q  \n",
+       "..          ...       ...      ...    ...      ...  \n",
+       "850           2    347082  31.2750    NaN        S  \n",
+       "852           1      2678  15.2458    NaN        C  \n",
+       "853           1  PC 17592  39.4000    D28        S  \n",
+       "869           1    347742  11.1333    NaN        S  \n",
+       "875           0      2667   7.2250    NaN        C  \n",
+       "\n",
+       "[113 rows x 12 columns]"
+      ]
+     },
+     "execution_count": 67,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "#Filtrar quantos passageiros tinham menos de 18 anos\n",
+    "df_dani[(df_dani['Idade'] < 18)]\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 68,
+   "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>IdPassageiro</th>\n",
+       "      <th>Sobreviveu</th>\n",
+       "      <th>Classe</th>\n",
+       "      <th>Nome</th>\n",
+       "      <th>Sexo</th>\n",
+       "      <th>Idade</th>\n",
+       "      <th>IrmaosConjuge</th>\n",
+       "      <th>PaisFilhos</th>\n",
+       "      <th>Bilhete</th>\n",
+       "      <th>Tarifa</th>\n",
+       "      <th>Cabine</th>\n",
+       "      <th>Embarque</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>10</td>\n",
+       "      <td>1</td>\n",
+       "      <td>2</td>\n",
+       "      <td>Nasser, Mrs. Nicholas (Adele Achem)</td>\n",
+       "      <td>female</td>\n",
+       "      <td>14.0</td>\n",
+       "      <td>1</td>\n",
+       "      <td>0</td>\n",
+       "      <td>237736</td>\n",
+       "      <td>30.0708</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>C</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>15</td>\n",
+       "      <td>0</td>\n",
+       "      <td>3</td>\n",
+       "      <td>Vestrom, Miss. Hulda Amanda Adolfina</td>\n",
+       "      <td>female</td>\n",
+       "      <td>14.0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>350406</td>\n",
+       "      <td>7.8542</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>S</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>23</td>\n",
+       "      <td>1</td>\n",
+       "      <td>3</td>\n",
+       "      <td>McGowan, Miss. Anna \"Annie\"</td>\n",
+       "      <td>female</td>\n",
+       "      <td>15.0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>330923</td>\n",
+       "      <td>8.0292</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>Q</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>39</td>\n",
+       "      <td>0</td>\n",
+       "      <td>3</td>\n",
+       "      <td>Vander Planke, Miss. Augusta Maria</td>\n",
+       "      <td>female</td>\n",
+       "      <td>18.0</td>\n",
+       "      <td>2</td>\n",
+       "      <td>0</td>\n",
+       "      <td>345764</td>\n",
+       "      <td>18.0000</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>S</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>40</td>\n",
+       "      <td>1</td>\n",
+       "      <td>3</td>\n",
+       "      <td>Nicola-Yarred, Miss. Jamila</td>\n",
+       "      <td>female</td>\n",
+       "      <td>14.0</td>\n",
+       "      <td>1</td>\n",
+       "      <td>0</td>\n",
+       "      <td>2651</td>\n",
+       "      <td>11.2417</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>C</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>5</th>\n",
+       "      <td>50</td>\n",
+       "      <td>0</td>\n",
+       "      <td>3</td>\n",
+       "      <td>Arnold-Franchi, Mrs. Josef (Josefine Franchi)</td>\n",
+       "      <td>female</td>\n",
+       "      <td>18.0</td>\n",
+       "      <td>1</td>\n",
+       "      <td>0</td>\n",
+       "      <td>349237</td>\n",
+       "      <td>17.8000</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>S</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>6</th>\n",
+       "      <td>69</td>\n",
+       "      <td>1</td>\n",
+       "      <td>3</td>\n",
+       "      <td>Andersson, Miss. Erna Alexandra</td>\n",
+       "      <td>female</td>\n",
+       "      <td>17.0</td>\n",
+       "      <td>4</td>\n",
+       "      <td>2</td>\n",
+       "      <td>3101281</td>\n",
+       "      <td>7.9250</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>S</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>7</th>\n",
+       "      <td>72</td>\n",
+       "      <td>0</td>\n",
+       "      <td>3</td>\n",
+       "      <td>Goodwin, Miss. Lillian Amy</td>\n",
+       "      <td>female</td>\n",
+       "      <td>16.0</td>\n",
+       "      <td>5</td>\n",
+       "      <td>2</td>\n",
+       "      <td>CA 2144</td>\n",
+       "      <td>46.9000</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>S</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>8</th>\n",
+       "      <td>85</td>\n",
+       "      <td>1</td>\n",
+       "      <td>2</td>\n",
+       "      <td>Ilett, Miss. Bertha</td>\n",
+       "      <td>female</td>\n",
+       "      <td>17.0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>SO/C 14885</td>\n",
+       "      <td>10.5000</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>S</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>9</th>\n",
+       "      <td>112</td>\n",
+       "      <td>0</td>\n",
+       "      <td>3</td>\n",
+       "      <td>Zabour, Miss. Hileni</td>\n",
+       "      <td>female</td>\n",
+       "      <td>14.5</td>\n",
+       "      <td>1</td>\n",
+       "      <td>0</td>\n",
+       "      <td>2665</td>\n",
+       "      <td>14.4542</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>C</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>10</th>\n",
+       "      <td>115</td>\n",
+       "      <td>0</td>\n",
+       "      <td>3</td>\n",
+       "      <td>Attalah, Miss. Malake</td>\n",
+       "      <td>female</td>\n",
+       "      <td>17.0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>2627</td>\n",
+       "      <td>14.4583</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>C</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>11</th>\n",
+       "      <td>157</td>\n",
+       "      <td>1</td>\n",
+       "      <td>3</td>\n",
+       "      <td>Gilnagh, Miss. Katherine \"Katie\"</td>\n",
+       "      <td>female</td>\n",
+       "      <td>16.0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>35851</td>\n",
+       "      <td>7.7333</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>Q</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>12</th>\n",
+       "      <td>209</td>\n",
+       "      <td>1</td>\n",
+       "      <td>3</td>\n",
+       "      <td>Carr, Miss. Helen \"Ellen\"</td>\n",
+       "      <td>female</td>\n",
+       "      <td>16.0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>367231</td>\n",
+       "      <td>7.7500</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>Q</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>13</th>\n",
+       "      <td>308</td>\n",
+       "      <td>1</td>\n",
+       "      <td>1</td>\n",
+       "      <td>Penasco y Castellana, Mrs. Victor de Satode (M...</td>\n",
+       "      <td>female</td>\n",
+       "      <td>17.0</td>\n",
+       "      <td>1</td>\n",
+       "      <td>0</td>\n",
+       "      <td>PC 17758</td>\n",
+       "      <td>108.9000</td>\n",
+       "      <td>C65</td>\n",
+       "      <td>C</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>14</th>\n",
+       "      <td>312</td>\n",
+       "      <td>1</td>\n",
+       "      <td>1</td>\n",
+       "      <td>Ryerson, Miss. Emily Borie</td>\n",
+       "      <td>female</td>\n",
+       "      <td>18.0</td>\n",
+       "      <td>2</td>\n",
+       "      <td>2</td>\n",
+       "      <td>PC 17608</td>\n",
+       "      <td>262.3750</td>\n",
+       "      <td>B57 B59 B63 B66</td>\n",
+       "      <td>C</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>15</th>\n",
+       "      <td>330</td>\n",
+       "      <td>1</td>\n",
+       "      <td>1</td>\n",
+       "      <td>Hippach, Miss. Jean Gertrude</td>\n",
+       "      <td>female</td>\n",
+       "      <td>16.0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>1</td>\n",
+       "      <td>111361</td>\n",
+       "      <td>57.9792</td>\n",
+       "      <td>B18</td>\n",
+       "      <td>C</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>16</th>\n",
+       "      <td>390</td>\n",
+       "      <td>1</td>\n",
+       "      <td>2</td>\n",
+       "      <td>Lehmann, Miss. Bertha</td>\n",
+       "      <td>female</td>\n",
+       "      <td>17.0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>SC 1748</td>\n",
+       "      <td>12.0000</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>C</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>17</th>\n",
+       "      <td>418</td>\n",
+       "      <td>1</td>\n",
+       "      <td>2</td>\n",
+       "      <td>Silven, Miss. Lyyli Karoliina</td>\n",
+       "      <td>female</td>\n",
+       "      <td>18.0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>2</td>\n",
+       "      <td>250652</td>\n",
+       "      <td>13.0000</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>S</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>18</th>\n",
+       "      <td>436</td>\n",
+       "      <td>1</td>\n",
+       "      <td>1</td>\n",
+       "      <td>Carter, Miss. Lucile Polk</td>\n",
+       "      <td>female</td>\n",
+       "      <td>14.0</td>\n",
+       "      <td>1</td>\n",
+       "      <td>2</td>\n",
+       "      <td>113760</td>\n",
+       "      <td>120.0000</td>\n",
+       "      <td>B96 B98</td>\n",
+       "      <td>S</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>19</th>\n",
+       "      <td>447</td>\n",
+       "      <td>1</td>\n",
+       "      <td>2</td>\n",
+       "      <td>Mellinger, Miss. Madeleine Violet</td>\n",
+       "      <td>female</td>\n",
+       "      <td>13.0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>1</td>\n",
+       "      <td>250644</td>\n",
+       "      <td>19.5000</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>S</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>20</th>\n",
+       "      <td>505</td>\n",
+       "      <td>1</td>\n",
+       "      <td>1</td>\n",
+       "      <td>Maioni, Miss. Roberta</td>\n",
+       "      <td>female</td>\n",
+       "      <td>16.0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>110152</td>\n",
+       "      <td>86.5000</td>\n",
+       "      <td>B79</td>\n",
+       "      <td>S</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>21</th>\n",
+       "      <td>586</td>\n",
+       "      <td>1</td>\n",
+       "      <td>1</td>\n",
+       "      <td>Taussig, Miss. Ruth</td>\n",
+       "      <td>female</td>\n",
+       "      <td>18.0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>2</td>\n",
+       "      <td>110413</td>\n",
+       "      <td>79.6500</td>\n",
+       "      <td>E68</td>\n",
+       "      <td>S</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>22</th>\n",
+       "      <td>652</td>\n",
+       "      <td>1</td>\n",
+       "      <td>2</td>\n",
+       "      <td>Doling, Miss. Elsie</td>\n",
+       "      <td>female</td>\n",
+       "      <td>18.0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>1</td>\n",
+       "      <td>231919</td>\n",
+       "      <td>23.0000</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>S</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>23</th>\n",
+       "      <td>655</td>\n",
+       "      <td>0</td>\n",
+       "      <td>3</td>\n",
+       "      <td>Hegarty, Miss. Hanora \"Nora\"</td>\n",
+       "      <td>female</td>\n",
+       "      <td>18.0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>365226</td>\n",
+       "      <td>6.7500</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>Q</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>24</th>\n",
+       "      <td>678</td>\n",
+       "      <td>1</td>\n",
+       "      <td>3</td>\n",
+       "      <td>Turja, Miss. Anna Sofia</td>\n",
+       "      <td>female</td>\n",
+       "      <td>18.0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>4138</td>\n",
+       "      <td>9.8417</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>S</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>25</th>\n",
+       "      <td>690</td>\n",
+       "      <td>1</td>\n",
+       "      <td>1</td>\n",
+       "      <td>Madill, Miss. Georgette Alexandra</td>\n",
+       "      <td>female</td>\n",
+       "      <td>15.0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>1</td>\n",
+       "      <td>24160</td>\n",
+       "      <td>211.3375</td>\n",
+       "      <td>B5</td>\n",
+       "      <td>S</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>26</th>\n",
+       "      <td>701</td>\n",
+       "      <td>1</td>\n",
+       "      <td>1</td>\n",
+       "      <td>Astor, Mrs. John Jacob (Madeleine Talmadge Force)</td>\n",
+       "      <td>female</td>\n",
+       "      <td>18.0</td>\n",
+       "      <td>1</td>\n",
+       "      <td>0</td>\n",
+       "      <td>PC 17757</td>\n",
+       "      <td>227.5250</td>\n",
+       "      <td>C62 C64</td>\n",
+       "      <td>C</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>27</th>\n",
+       "      <td>703</td>\n",
+       "      <td>0</td>\n",
+       "      <td>3</td>\n",
+       "      <td>Barbara, Miss. Saiide</td>\n",
+       "      <td>female</td>\n",
+       "      <td>18.0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>1</td>\n",
+       "      <td>2691</td>\n",
+       "      <td>14.4542</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>C</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>28</th>\n",
+       "      <td>781</td>\n",
+       "      <td>1</td>\n",
+       "      <td>3</td>\n",
+       "      <td>Ayoub, Miss. Banoura</td>\n",
+       "      <td>female</td>\n",
+       "      <td>13.0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>2687</td>\n",
+       "      <td>7.2292</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>C</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>29</th>\n",
+       "      <td>782</td>\n",
+       "      <td>1</td>\n",
+       "      <td>1</td>\n",
+       "      <td>Dick, Mrs. Albert Adrian (Vera Gillespie)</td>\n",
+       "      <td>female</td>\n",
+       "      <td>17.0</td>\n",
+       "      <td>1</td>\n",
+       "      <td>0</td>\n",
+       "      <td>17474</td>\n",
+       "      <td>57.0000</td>\n",
+       "      <td>B20</td>\n",
+       "      <td>S</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>30</th>\n",
+       "      <td>787</td>\n",
+       "      <td>1</td>\n",
+       "      <td>3</td>\n",
+       "      <td>Sjoblom, Miss. Anna Sofia</td>\n",
+       "      <td>female</td>\n",
+       "      <td>18.0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>3101265</td>\n",
+       "      <td>7.4958</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>S</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>31</th>\n",
+       "      <td>808</td>\n",
+       "      <td>0</td>\n",
+       "      <td>3</td>\n",
+       "      <td>Pettersson, Miss. Ellen Natalia</td>\n",
+       "      <td>female</td>\n",
+       "      <td>18.0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>347087</td>\n",
+       "      <td>7.7750</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>S</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>32</th>\n",
+       "      <td>831</td>\n",
+       "      <td>1</td>\n",
+       "      <td>3</td>\n",
+       "      <td>Yasbeck, Mrs. Antoni (Selini Alexander)</td>\n",
+       "      <td>female</td>\n",
+       "      <td>15.0</td>\n",
+       "      <td>1</td>\n",
+       "      <td>0</td>\n",
+       "      <td>2659</td>\n",
+       "      <td>14.4542</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>C</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>33</th>\n",
+       "      <td>854</td>\n",
+       "      <td>1</td>\n",
+       "      <td>1</td>\n",
+       "      <td>Lines, Miss. Mary Conover</td>\n",
+       "      <td>female</td>\n",
+       "      <td>16.0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>1</td>\n",
+       "      <td>PC 17592</td>\n",
+       "      <td>39.4000</td>\n",
+       "      <td>D28</td>\n",
+       "      <td>S</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>34</th>\n",
+       "      <td>856</td>\n",
+       "      <td>1</td>\n",
+       "      <td>3</td>\n",
+       "      <td>Aks, Mrs. Sam (Leah Rosen)</td>\n",
+       "      <td>female</td>\n",
+       "      <td>18.0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>1</td>\n",
+       "      <td>392091</td>\n",
+       "      <td>9.3500</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>S</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>35</th>\n",
+       "      <td>876</td>\n",
+       "      <td>1</td>\n",
+       "      <td>3</td>\n",
+       "      <td>Najib, Miss. Adele Kiamie \"Jane\"</td>\n",
+       "      <td>female</td>\n",
+       "      <td>15.0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>2667</td>\n",
+       "      <td>7.2250</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>C</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "    IdPassageiro  Sobreviveu  Classe  \\\n",
+       "0             10           1       2   \n",
+       "1             15           0       3   \n",
+       "2             23           1       3   \n",
+       "3             39           0       3   \n",
+       "4             40           1       3   \n",
+       "5             50           0       3   \n",
+       "6             69           1       3   \n",
+       "7             72           0       3   \n",
+       "8             85           1       2   \n",
+       "9            112           0       3   \n",
+       "10           115           0       3   \n",
+       "11           157           1       3   \n",
+       "12           209           1       3   \n",
+       "13           308           1       1   \n",
+       "14           312           1       1   \n",
+       "15           330           1       1   \n",
+       "16           390           1       2   \n",
+       "17           418           1       2   \n",
+       "18           436           1       1   \n",
+       "19           447           1       2   \n",
+       "20           505           1       1   \n",
+       "21           586           1       1   \n",
+       "22           652           1       2   \n",
+       "23           655           0       3   \n",
+       "24           678           1       3   \n",
+       "25           690           1       1   \n",
+       "26           701           1       1   \n",
+       "27           703           0       3   \n",
+       "28           781           1       3   \n",
+       "29           782           1       1   \n",
+       "30           787           1       3   \n",
+       "31           808           0       3   \n",
+       "32           831           1       3   \n",
+       "33           854           1       1   \n",
+       "34           856           1       3   \n",
+       "35           876           1       3   \n",
+       "\n",
+       "                                                 Nome    Sexo  Idade  \\\n",
+       "0                 Nasser, Mrs. Nicholas (Adele Achem)  female   14.0   \n",
+       "1                Vestrom, Miss. Hulda Amanda Adolfina  female   14.0   \n",
+       "2                         McGowan, Miss. Anna \"Annie\"  female   15.0   \n",
+       "3                  Vander Planke, Miss. Augusta Maria  female   18.0   \n",
+       "4                         Nicola-Yarred, Miss. Jamila  female   14.0   \n",
+       "5       Arnold-Franchi, Mrs. Josef (Josefine Franchi)  female   18.0   \n",
+       "6                     Andersson, Miss. Erna Alexandra  female   17.0   \n",
+       "7                          Goodwin, Miss. Lillian Amy  female   16.0   \n",
+       "8                                 Ilett, Miss. Bertha  female   17.0   \n",
+       "9                                Zabour, Miss. Hileni  female   14.5   \n",
+       "10                              Attalah, Miss. Malake  female   17.0   \n",
+       "11                   Gilnagh, Miss. Katherine \"Katie\"  female   16.0   \n",
+       "12                          Carr, Miss. Helen \"Ellen\"  female   16.0   \n",
+       "13  Penasco y Castellana, Mrs. Victor de Satode (M...  female   17.0   \n",
+       "14                         Ryerson, Miss. Emily Borie  female   18.0   \n",
+       "15                       Hippach, Miss. Jean Gertrude  female   16.0   \n",
+       "16                              Lehmann, Miss. Bertha  female   17.0   \n",
+       "17                      Silven, Miss. Lyyli Karoliina  female   18.0   \n",
+       "18                          Carter, Miss. Lucile Polk  female   14.0   \n",
+       "19                  Mellinger, Miss. Madeleine Violet  female   13.0   \n",
+       "20                              Maioni, Miss. Roberta  female   16.0   \n",
+       "21                                Taussig, Miss. Ruth  female   18.0   \n",
+       "22                                Doling, Miss. Elsie  female   18.0   \n",
+       "23                       Hegarty, Miss. Hanora \"Nora\"  female   18.0   \n",
+       "24                            Turja, Miss. Anna Sofia  female   18.0   \n",
+       "25                  Madill, Miss. Georgette Alexandra  female   15.0   \n",
+       "26  Astor, Mrs. John Jacob (Madeleine Talmadge Force)  female   18.0   \n",
+       "27                              Barbara, Miss. Saiide  female   18.0   \n",
+       "28                               Ayoub, Miss. Banoura  female   13.0   \n",
+       "29          Dick, Mrs. Albert Adrian (Vera Gillespie)  female   17.0   \n",
+       "30                          Sjoblom, Miss. Anna Sofia  female   18.0   \n",
+       "31                    Pettersson, Miss. Ellen Natalia  female   18.0   \n",
+       "32            Yasbeck, Mrs. Antoni (Selini Alexander)  female   15.0   \n",
+       "33                          Lines, Miss. Mary Conover  female   16.0   \n",
+       "34                         Aks, Mrs. Sam (Leah Rosen)  female   18.0   \n",
+       "35                   Najib, Miss. Adele Kiamie \"Jane\"  female   15.0   \n",
+       "\n",
+       "    IrmaosConjuge  PaisFilhos     Bilhete    Tarifa           Cabine Embarque  \n",
+       "0               1           0      237736   30.0708              NaN        C  \n",
+       "1               0           0      350406    7.8542              NaN        S  \n",
+       "2               0           0      330923    8.0292              NaN        Q  \n",
+       "3               2           0      345764   18.0000              NaN        S  \n",
+       "4               1           0        2651   11.2417              NaN        C  \n",
+       "5               1           0      349237   17.8000              NaN        S  \n",
+       "6               4           2     3101281    7.9250              NaN        S  \n",
+       "7               5           2     CA 2144   46.9000              NaN        S  \n",
+       "8               0           0  SO/C 14885   10.5000              NaN        S  \n",
+       "9               1           0        2665   14.4542              NaN        C  \n",
+       "10              0           0        2627   14.4583              NaN        C  \n",
+       "11              0           0       35851    7.7333              NaN        Q  \n",
+       "12              0           0      367231    7.7500              NaN        Q  \n",
+       "13              1           0    PC 17758  108.9000              C65        C  \n",
+       "14              2           2    PC 17608  262.3750  B57 B59 B63 B66        C  \n",
+       "15              0           1      111361   57.9792              B18        C  \n",
+       "16              0           0     SC 1748   12.0000              NaN        C  \n",
+       "17              0           2      250652   13.0000              NaN        S  \n",
+       "18              1           2      113760  120.0000          B96 B98        S  \n",
+       "19              0           1      250644   19.5000              NaN        S  \n",
+       "20              0           0      110152   86.5000              B79        S  \n",
+       "21              0           2      110413   79.6500              E68        S  \n",
+       "22              0           1      231919   23.0000              NaN        S  \n",
+       "23              0           0      365226    6.7500              NaN        Q  \n",
+       "24              0           0        4138    9.8417              NaN        S  \n",
+       "25              0           1       24160  211.3375               B5        S  \n",
+       "26              1           0    PC 17757  227.5250          C62 C64        C  \n",
+       "27              0           1        2691   14.4542              NaN        C  \n",
+       "28              0           0        2687    7.2292              NaN        C  \n",
+       "29              1           0       17474   57.0000              B20        S  \n",
+       "30              0           0     3101265    7.4958              NaN        S  \n",
+       "31              0           0      347087    7.7750              NaN        S  \n",
+       "32              1           0        2659   14.4542              NaN        C  \n",
+       "33              0           1    PC 17592   39.4000              D28        S  \n",
+       "34              0           1      392091    9.3500              NaN        S  \n",
+       "35              0           0        2667    7.2250              NaN        C  "
+      ]
+     },
+     "execution_count": 68,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "#Determinar quantos adolescentes eram meninas \n",
+    "df_dani_meninasadolescente = df_dani[(df_dani['Idade'] >= 12) & (df_dani['Idade'] <= 18 ) & (df_dani['Sexo'] == 'female')]\n",
+    "df_dani_meninasadolescente.reset_index(drop=True)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 69,
+   "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>IdPassageiro</th>\n",
+       "      <th>Sobreviveu</th>\n",
+       "      <th>Classe</th>\n",
+       "      <th>Nome</th>\n",
+       "      <th>Sexo</th>\n",
+       "      <th>Idade</th>\n",
+       "      <th>IrmaosConjuge</th>\n",
+       "      <th>PaisFilhos</th>\n",
+       "      <th>Bilhete</th>\n",
+       "      <th>Tarifa</th>\n",
+       "      <th>Cabine</th>\n",
+       "      <th>Embarque</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>25</td>\n",
+       "      <td>0</td>\n",
+       "      <td>3</td>\n",
+       "      <td>Palsson, Miss. Torborg Danira</td>\n",
+       "      <td>female</td>\n",
+       "      <td>8.0</td>\n",
+       "      <td>3</td>\n",
+       "      <td>1</td>\n",
+       "      <td>349909</td>\n",
+       "      <td>21.0750</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>S</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>95</td>\n",
+       "      <td>0</td>\n",
+       "      <td>3</td>\n",
+       "      <td>Coxon, Mr. Daniel</td>\n",
+       "      <td>male</td>\n",
+       "      <td>59.0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>364500</td>\n",
+       "      <td>7.2500</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>S</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>499</td>\n",
+       "      <td>0</td>\n",
+       "      <td>1</td>\n",
+       "      <td>Allison, Mrs. Hudson J C (Bessie Waldo Daniels)</td>\n",
+       "      <td>female</td>\n",
+       "      <td>25.0</td>\n",
+       "      <td>1</td>\n",
+       "      <td>2</td>\n",
+       "      <td>113781</td>\n",
+       "      <td>151.5500</td>\n",
+       "      <td>C22 C26</td>\n",
+       "      <td>S</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>608</td>\n",
+       "      <td>1</td>\n",
+       "      <td>1</td>\n",
+       "      <td>Daniel, Mr. Robert Williams</td>\n",
+       "      <td>male</td>\n",
+       "      <td>27.0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>113804</td>\n",
+       "      <td>30.5000</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>S</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>749</td>\n",
+       "      <td>0</td>\n",
+       "      <td>1</td>\n",
+       "      <td>Marvin, Mr. Daniel Warner</td>\n",
+       "      <td>male</td>\n",
+       "      <td>19.0</td>\n",
+       "      <td>1</td>\n",
+       "      <td>0</td>\n",
+       "      <td>113773</td>\n",
+       "      <td>53.1000</td>\n",
+       "      <td>D30</td>\n",
+       "      <td>S</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>5</th>\n",
+       "      <td>769</td>\n",
+       "      <td>0</td>\n",
+       "      <td>3</td>\n",
+       "      <td>Moran, Mr. Daniel J</td>\n",
+       "      <td>male</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>1</td>\n",
+       "      <td>0</td>\n",
+       "      <td>371110</td>\n",
+       "      <td>24.1500</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>Q</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>6</th>\n",
+       "      <td>770</td>\n",
+       "      <td>0</td>\n",
+       "      <td>3</td>\n",
+       "      <td>Gronnestad, Mr. Daniel Danielsen</td>\n",
+       "      <td>male</td>\n",
+       "      <td>32.0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>8471</td>\n",
+       "      <td>8.3625</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>S</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "   IdPassageiro  Sobreviveu  Classe  \\\n",
+       "0            25           0       3   \n",
+       "1            95           0       3   \n",
+       "2           499           0       1   \n",
+       "3           608           1       1   \n",
+       "4           749           0       1   \n",
+       "5           769           0       3   \n",
+       "6           770           0       3   \n",
+       "\n",
+       "                                              Nome    Sexo  Idade  \\\n",
+       "0                    Palsson, Miss. Torborg Danira  female    8.0   \n",
+       "1                                Coxon, Mr. Daniel    male   59.0   \n",
+       "2  Allison, Mrs. Hudson J C (Bessie Waldo Daniels)  female   25.0   \n",
+       "3                      Daniel, Mr. Robert Williams    male   27.0   \n",
+       "4                        Marvin, Mr. Daniel Warner    male   19.0   \n",
+       "5                              Moran, Mr. Daniel J    male    NaN   \n",
+       "6                 Gronnestad, Mr. Daniel Danielsen    male   32.0   \n",
+       "\n",
+       "   IrmaosConjuge  PaisFilhos Bilhete    Tarifa   Cabine Embarque  \n",
+       "0              3           1  349909   21.0750      NaN        S  \n",
+       "1              0           0  364500    7.2500      NaN        S  \n",
+       "2              1           2  113781  151.5500  C22 C26        S  \n",
+       "3              0           0  113804   30.5000      NaN        S  \n",
+       "4              1           0  113773   53.1000      D30        S  \n",
+       "5              1           0  371110   24.1500      NaN        Q  \n",
+       "6              0           0    8471    8.3625      NaN        S  "
+      ]
+     },
+     "execution_count": 69,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "#Passeigeiro com nome que tenha Dani\n",
+    "df_danistr = df_dani[df_dani['Nome'].str.contains('Dani')]\n",
+    "df_danistr.reset_index(drop=True)\n",
+    "\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 70,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
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+       "\n",
+       "    .dataframe tbody tr th {\n",
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+       "\n",
+       "    .dataframe thead th {\n",
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+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>IdPassageiro</th>\n",
+       "      <th>Sobreviveu</th>\n",
+       "      <th>Classe</th>\n",
+       "      <th>Nome</th>\n",
+       "      <th>Sexo</th>\n",
+       "      <th>Idade</th>\n",
+       "      <th>IrmaosConjuge</th>\n",
+       "      <th>PaisFilhos</th>\n",
+       "      <th>Bilhete</th>\n",
+       "      <th>Tarifa</th>\n",
+       "      <th>Cabine</th>\n",
+       "      <th>Embarque</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>1</td>\n",
+       "      <td>0</td>\n",
+       "      <td>3</td>\n",
+       "      <td>Braund, Mr. Owen Harris</td>\n",
+       "      <td>male</td>\n",
+       "      <td>22.0</td>\n",
+       "      <td>1</td>\n",
+       "      <td>0</td>\n",
+       "      <td>A/5 21171</td>\n",
+       "      <td>7.2500</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>S</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>3</td>\n",
+       "      <td>1</td>\n",
+       "      <td>3</td>\n",
+       "      <td>Heikkinen, Miss. Laina</td>\n",
+       "      <td>female</td>\n",
+       "      <td>26.0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>STON/O2. 3101282</td>\n",
+       "      <td>7.9250</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>S</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>5</td>\n",
+       "      <td>0</td>\n",
+       "      <td>3</td>\n",
+       "      <td>Allen, Mr. William Henry</td>\n",
+       "      <td>male</td>\n",
+       "      <td>35.0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>373450</td>\n",
+       "      <td>8.0500</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>S</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>6</td>\n",
+       "      <td>0</td>\n",
+       "      <td>3</td>\n",
+       "      <td>Moran, Mr. James</td>\n",
+       "      <td>male</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>330877</td>\n",
+       "      <td>8.4583</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>Q</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>8</td>\n",
+       "      <td>0</td>\n",
+       "      <td>3</td>\n",
+       "      <td>Palsson, Master. Gosta Leonard</td>\n",
+       "      <td>male</td>\n",
+       "      <td>2.0</td>\n",
+       "      <td>3</td>\n",
+       "      <td>1</td>\n",
+       "      <td>349909</td>\n",
+       "      <td>21.0750</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>S</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>...</th>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>670</th>\n",
+       "      <td>885</td>\n",
+       "      <td>0</td>\n",
+       "      <td>3</td>\n",
+       "      <td>Sutehall, Mr. Henry Jr</td>\n",
+       "      <td>male</td>\n",
+       "      <td>25.0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>SOTON/OQ 392076</td>\n",
+       "      <td>7.0500</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>S</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>671</th>\n",
+       "      <td>886</td>\n",
+       "      <td>0</td>\n",
+       "      <td>3</td>\n",
+       "      <td>Rice, Mrs. William (Margaret Norton)</td>\n",
+       "      <td>female</td>\n",
+       "      <td>39.0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>5</td>\n",
+       "      <td>382652</td>\n",
+       "      <td>29.1250</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>Q</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>672</th>\n",
+       "      <td>887</td>\n",
+       "      <td>0</td>\n",
+       "      <td>2</td>\n",
+       "      <td>Montvila, Rev. Juozas</td>\n",
+       "      <td>male</td>\n",
+       "      <td>27.0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>211536</td>\n",
+       "      <td>13.0000</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>S</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>673</th>\n",
+       "      <td>889</td>\n",
+       "      <td>0</td>\n",
+       "      <td>3</td>\n",
+       "      <td>Johnston, Miss. Catherine Helen \"Carrie\"</td>\n",
+       "      <td>female</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>1</td>\n",
+       "      <td>2</td>\n",
+       "      <td>W./C. 6607</td>\n",
+       "      <td>23.4500</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>S</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>674</th>\n",
+       "      <td>891</td>\n",
+       "      <td>0</td>\n",
+       "      <td>3</td>\n",
+       "      <td>Dooley, Mr. Patrick</td>\n",
+       "      <td>male</td>\n",
+       "      <td>32.0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>370376</td>\n",
+       "      <td>7.7500</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>Q</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "<p>675 rows × 12 columns</p>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "     IdPassageiro  Sobreviveu  Classe  \\\n",
+       "0               1           0       3   \n",
+       "1               3           1       3   \n",
+       "2               5           0       3   \n",
+       "3               6           0       3   \n",
+       "4               8           0       3   \n",
+       "..            ...         ...     ...   \n",
+       "670           885           0       3   \n",
+       "671           886           0       3   \n",
+       "672           887           0       2   \n",
+       "673           889           0       3   \n",
+       "674           891           0       3   \n",
+       "\n",
+       "                                         Nome    Sexo  Idade  IrmaosConjuge  \\\n",
+       "0                     Braund, Mr. Owen Harris    male   22.0              1   \n",
+       "1                      Heikkinen, Miss. Laina  female   26.0              0   \n",
+       "2                    Allen, Mr. William Henry    male   35.0              0   \n",
+       "3                            Moran, Mr. James    male    NaN              0   \n",
+       "4              Palsson, Master. Gosta Leonard    male    2.0              3   \n",
+       "..                                        ...     ...    ...            ...   \n",
+       "670                    Sutehall, Mr. Henry Jr    male   25.0              0   \n",
+       "671      Rice, Mrs. William (Margaret Norton)  female   39.0              0   \n",
+       "672                     Montvila, Rev. Juozas    male   27.0              0   \n",
+       "673  Johnston, Miss. Catherine Helen \"Carrie\"  female    NaN              1   \n",
+       "674                       Dooley, Mr. Patrick    male   32.0              0   \n",
+       "\n",
+       "     PaisFilhos           Bilhete   Tarifa Cabine Embarque  \n",
+       "0             0         A/5 21171   7.2500    NaN        S  \n",
+       "1             0  STON/O2. 3101282   7.9250    NaN        S  \n",
+       "2             0            373450   8.0500    NaN        S  \n",
+       "3             0            330877   8.4583    NaN        Q  \n",
+       "4             1            349909  21.0750    NaN        S  \n",
+       "..          ...               ...      ...    ...      ...  \n",
+       "670           0   SOTON/OQ 392076   7.0500    NaN        S  \n",
+       "671           5            382652  29.1250    NaN        Q  \n",
+       "672           0            211536  13.0000    NaN        S  \n",
+       "673           2        W./C. 6607  23.4500    NaN        S  \n",
+       "674           0            370376   7.7500    NaN        Q  \n",
+       "\n",
+       "[675 rows x 12 columns]"
+      ]
+     },
+     "execution_count": 70,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "# Filtrando passageiros da segunda e terceira classe\n",
+    "df_daniclass = df_dani.query(\"Classe in (2, 3)\")\n",
+    "df_daniclass.reset_index(drop=True)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 71,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
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+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
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+       "\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>IdPassageiro</th>\n",
+       "      <th>Sobreviveu</th>\n",
+       "      <th>Classe</th>\n",
+       "      <th>Nome</th>\n",
+       "      <th>Sexo</th>\n",
+       "      <th>Idade</th>\n",
+       "      <th>IrmaosConjuge</th>\n",
+       "      <th>PaisFilhos</th>\n",
+       "      <th>Bilhete</th>\n",
+       "      <th>Tarifa</th>\n",
+       "      <th>Cabine</th>\n",
+       "      <th>Embarque</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>1</td>\n",
+       "      <td>0</td>\n",
+       "      <td>3</td>\n",
+       "      <td>Braund, Mr. Owen Harris</td>\n",
+       "      <td>male</td>\n",
+       "      <td>22.0</td>\n",
+       "      <td>1</td>\n",
+       "      <td>0</td>\n",
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+       "      <td>7.2500</td>\n",
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+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>2</td>\n",
+       "      <td>1</td>\n",
+       "      <td>1</td>\n",
+       "      <td>Cumings, Mrs. John Bradley (Florence Briggs Th...</td>\n",
+       "      <td>female</td>\n",
+       "      <td>38.0</td>\n",
+       "      <td>1</td>\n",
+       "      <td>0</td>\n",
+       "      <td>PC 17599</td>\n",
+       "      <td>71.2833</td>\n",
+       "      <td>C85</td>\n",
+       "      <td>C</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>3</td>\n",
+       "      <td>1</td>\n",
+       "      <td>3</td>\n",
+       "      <td>Heikkinen, Miss. Laina</td>\n",
+       "      <td>female</td>\n",
+       "      <td>26.0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>STON/O2. 3101282</td>\n",
+       "      <td>7.9250</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>S</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>4</td>\n",
+       "      <td>1</td>\n",
+       "      <td>1</td>\n",
+       "      <td>Futrelle, Mrs. Jacques Heath (Lily May Peel)</td>\n",
+       "      <td>female</td>\n",
+       "      <td>35.0</td>\n",
+       "      <td>1</td>\n",
+       "      <td>0</td>\n",
+       "      <td>113803</td>\n",
+       "      <td>53.1000</td>\n",
+       "      <td>C123</td>\n",
+       "      <td>S</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>5</td>\n",
+       "      <td>0</td>\n",
+       "      <td>3</td>\n",
+       "      <td>Allen, Mr. William Henry</td>\n",
+       "      <td>male</td>\n",
+       "      <td>35.0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>373450</td>\n",
+       "      <td>8.0500</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>S</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>5</th>\n",
+       "      <td>6</td>\n",
+       "      <td>0</td>\n",
+       "      <td>3</td>\n",
+       "      <td>Moran, Mr. James</td>\n",
+       "      <td>male</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>330877</td>\n",
+       "      <td>8.4583</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>Q</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>6</th>\n",
+       "      <td>7</td>\n",
+       "      <td>0</td>\n",
+       "      <td>1</td>\n",
+       "      <td>McCarthy, Mr. Timothy J</td>\n",
+       "      <td>male</td>\n",
+       "      <td>54.0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>17463</td>\n",
+       "      <td>51.8625</td>\n",
+       "      <td>E46</td>\n",
+       "      <td>S</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>7</th>\n",
+       "      <td>8</td>\n",
+       "      <td>0</td>\n",
+       "      <td>3</td>\n",
+       "      <td>Palsson, Master. Gosta Leonard</td>\n",
+       "      <td>male</td>\n",
+       "      <td>2.0</td>\n",
+       "      <td>3</td>\n",
+       "      <td>1</td>\n",
+       "      <td>349909</td>\n",
+       "      <td>21.0750</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>S</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>8</th>\n",
+       "      <td>9</td>\n",
+       "      <td>1</td>\n",
+       "      <td>3</td>\n",
+       "      <td>Johnson, Mrs. Oscar W (Elisabeth Vilhelmina Berg)</td>\n",
+       "      <td>female</td>\n",
+       "      <td>27.0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>2</td>\n",
+       "      <td>347742</td>\n",
+       "      <td>11.1333</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>S</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>9</th>\n",
+       "      <td>10</td>\n",
+       "      <td>1</td>\n",
+       "      <td>2</td>\n",
+       "      <td>Nasser, Mrs. Nicholas (Adele Achem)</td>\n",
+       "      <td>female</td>\n",
+       "      <td>14.0</td>\n",
+       "      <td>1</td>\n",
+       "      <td>0</td>\n",
+       "      <td>237736</td>\n",
+       "      <td>30.0708</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>C</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>10</th>\n",
+       "      <td>11</td>\n",
+       "      <td>1</td>\n",
+       "      <td>3</td>\n",
+       "      <td>Sandstrom, Miss. Marguerite Rut</td>\n",
+       "      <td>female</td>\n",
+       "      <td>4.0</td>\n",
+       "      <td>1</td>\n",
+       "      <td>1</td>\n",
+       "      <td>PP 9549</td>\n",
+       "      <td>16.7000</td>\n",
+       "      <td>G6</td>\n",
+       "      <td>S</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>11</th>\n",
+       "      <td>12</td>\n",
+       "      <td>1</td>\n",
+       "      <td>1</td>\n",
+       "      <td>Bonnell, Miss. Elizabeth</td>\n",
+       "      <td>female</td>\n",
+       "      <td>58.0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>113783</td>\n",
+       "      <td>26.5500</td>\n",
+       "      <td>C103</td>\n",
+       "      <td>S</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>12</th>\n",
+       "      <td>13</td>\n",
+       "      <td>0</td>\n",
+       "      <td>3</td>\n",
+       "      <td>Saundercock, Mr. William Henry</td>\n",
+       "      <td>male</td>\n",
+       "      <td>20.0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>A/5. 2151</td>\n",
+       "      <td>8.0500</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>S</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>13</th>\n",
+       "      <td>14</td>\n",
+       "      <td>0</td>\n",
+       "      <td>3</td>\n",
+       "      <td>Andersson, Mr. Anders Johan</td>\n",
+       "      <td>male</td>\n",
+       "      <td>39.0</td>\n",
+       "      <td>1</td>\n",
+       "      <td>5</td>\n",
+       "      <td>347082</td>\n",
+       "      <td>31.2750</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>S</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>14</th>\n",
+       "      <td>15</td>\n",
+       "      <td>0</td>\n",
+       "      <td>3</td>\n",
+       "      <td>Vestrom, Miss. Hulda Amanda Adolfina</td>\n",
+       "      <td>female</td>\n",
+       "      <td>14.0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>350406</td>\n",
+       "      <td>7.8542</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>S</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>15</th>\n",
+       "      <td>16</td>\n",
+       "      <td>1</td>\n",
+       "      <td>2</td>\n",
+       "      <td>Hewlett, Mrs. (Mary D Kingcome)</td>\n",
+       "      <td>female</td>\n",
+       "      <td>55.0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>248706</td>\n",
+       "      <td>16.0000</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>S</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>16</th>\n",
+       "      <td>17</td>\n",
+       "      <td>0</td>\n",
+       "      <td>3</td>\n",
+       "      <td>Rice, Master. Eugene</td>\n",
+       "      <td>male</td>\n",
+       "      <td>2.0</td>\n",
+       "      <td>4</td>\n",
+       "      <td>1</td>\n",
+       "      <td>382652</td>\n",
+       "      <td>29.1250</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>Q</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>17</th>\n",
+       "      <td>18</td>\n",
+       "      <td>1</td>\n",
+       "      <td>2</td>\n",
+       "      <td>Williams, Mr. Charles Eugene</td>\n",
+       "      <td>male</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>244373</td>\n",
+       "      <td>13.0000</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>S</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>18</th>\n",
+       "      <td>19</td>\n",
+       "      <td>0</td>\n",
+       "      <td>3</td>\n",
+       "      <td>Vander Planke, Mrs. Julius (Emelia Maria Vande...</td>\n",
+       "      <td>female</td>\n",
+       "      <td>31.0</td>\n",
+       "      <td>1</td>\n",
+       "      <td>0</td>\n",
+       "      <td>345763</td>\n",
+       "      <td>18.0000</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>S</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>19</th>\n",
+       "      <td>20</td>\n",
+       "      <td>1</td>\n",
+       "      <td>3</td>\n",
+       "      <td>Masselmani, Mrs. Fatima</td>\n",
+       "      <td>female</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>2649</td>\n",
+       "      <td>7.2250</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>C</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>20</th>\n",
+       "      <td>21</td>\n",
+       "      <td>0</td>\n",
+       "      <td>2</td>\n",
+       "      <td>Fynney, Mr. Joseph J</td>\n",
+       "      <td>male</td>\n",
+       "      <td>35.0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>239865</td>\n",
+       "      <td>26.0000</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>S</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>21</th>\n",
+       "      <td>22</td>\n",
+       "      <td>1</td>\n",
+       "      <td>2</td>\n",
+       "      <td>Beesley, Mr. Lawrence</td>\n",
+       "      <td>male</td>\n",
+       "      <td>34.0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>248698</td>\n",
+       "      <td>13.0000</td>\n",
+       "      <td>D56</td>\n",
+       "      <td>S</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>22</th>\n",
+       "      <td>23</td>\n",
+       "      <td>1</td>\n",
+       "      <td>3</td>\n",
+       "      <td>McGowan, Miss. Anna \"Annie\"</td>\n",
+       "      <td>female</td>\n",
+       "      <td>15.0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>330923</td>\n",
+       "      <td>8.0292</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>Q</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>23</th>\n",
+       "      <td>24</td>\n",
+       "      <td>1</td>\n",
+       "      <td>1</td>\n",
+       "      <td>Sloper, Mr. William Thompson</td>\n",
+       "      <td>male</td>\n",
+       "      <td>28.0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>113788</td>\n",
+       "      <td>35.5000</td>\n",
+       "      <td>A6</td>\n",
+       "      <td>S</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>24</th>\n",
+       "      <td>25</td>\n",
+       "      <td>0</td>\n",
+       "      <td>3</td>\n",
+       "      <td>Palsson, Miss. Torborg Danira</td>\n",
+       "      <td>female</td>\n",
+       "      <td>8.0</td>\n",
+       "      <td>3</td>\n",
+       "      <td>1</td>\n",
+       "      <td>349909</td>\n",
+       "      <td>21.0750</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>S</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>25</th>\n",
+       "      <td>26</td>\n",
+       "      <td>1</td>\n",
+       "      <td>3</td>\n",
+       "      <td>Asplund, Mrs. Carl Oscar (Selma Augusta Emilia...</td>\n",
+       "      <td>female</td>\n",
+       "      <td>38.0</td>\n",
+       "      <td>1</td>\n",
+       "      <td>5</td>\n",
+       "      <td>347077</td>\n",
+       "      <td>31.3875</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>S</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>26</th>\n",
+       "      <td>27</td>\n",
+       "      <td>0</td>\n",
+       "      <td>3</td>\n",
+       "      <td>Emir, Mr. Farred Chehab</td>\n",
+       "      <td>male</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>2631</td>\n",
+       "      <td>7.2250</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>C</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>27</th>\n",
+       "      <td>28</td>\n",
+       "      <td>0</td>\n",
+       "      <td>1</td>\n",
+       "      <td>Fortune, Mr. Charles Alexander</td>\n",
+       "      <td>male</td>\n",
+       "      <td>19.0</td>\n",
+       "      <td>3</td>\n",
+       "      <td>2</td>\n",
+       "      <td>19950</td>\n",
+       "      <td>263.0000</td>\n",
+       "      <td>C23 C25 C27</td>\n",
+       "      <td>S</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>28</th>\n",
+       "      <td>29</td>\n",
+       "      <td>1</td>\n",
+       "      <td>3</td>\n",
+       "      <td>O'Dwyer, Miss. Ellen \"Nellie\"</td>\n",
+       "      <td>female</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>330959</td>\n",
+       "      <td>7.8792</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>Q</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>29</th>\n",
+       "      <td>30</td>\n",
+       "      <td>0</td>\n",
+       "      <td>3</td>\n",
+       "      <td>Todoroff, Mr. Lalio</td>\n",
+       "      <td>male</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>349216</td>\n",
+       "      <td>7.8958</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>S</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "    IdPassageiro  Sobreviveu  Classe  \\\n",
+       "0              1           0       3   \n",
+       "1              2           1       1   \n",
+       "2              3           1       3   \n",
+       "3              4           1       1   \n",
+       "4              5           0       3   \n",
+       "5              6           0       3   \n",
+       "6              7           0       1   \n",
+       "7              8           0       3   \n",
+       "8              9           1       3   \n",
+       "9             10           1       2   \n",
+       "10            11           1       3   \n",
+       "11            12           1       1   \n",
+       "12            13           0       3   \n",
+       "13            14           0       3   \n",
+       "14            15           0       3   \n",
+       "15            16           1       2   \n",
+       "16            17           0       3   \n",
+       "17            18           1       2   \n",
+       "18            19           0       3   \n",
+       "19            20           1       3   \n",
+       "20            21           0       2   \n",
+       "21            22           1       2   \n",
+       "22            23           1       3   \n",
+       "23            24           1       1   \n",
+       "24            25           0       3   \n",
+       "25            26           1       3   \n",
+       "26            27           0       3   \n",
+       "27            28           0       1   \n",
+       "28            29           1       3   \n",
+       "29            30           0       3   \n",
+       "\n",
+       "                                                 Nome    Sexo  Idade  \\\n",
+       "0                             Braund, Mr. Owen Harris    male   22.0   \n",
+       "1   Cumings, Mrs. John Bradley (Florence Briggs Th...  female   38.0   \n",
+       "2                              Heikkinen, Miss. Laina  female   26.0   \n",
+       "3        Futrelle, Mrs. Jacques Heath (Lily May Peel)  female   35.0   \n",
+       "4                            Allen, Mr. William Henry    male   35.0   \n",
+       "5                                    Moran, Mr. James    male    NaN   \n",
+       "6                             McCarthy, Mr. Timothy J    male   54.0   \n",
+       "7                      Palsson, Master. Gosta Leonard    male    2.0   \n",
+       "8   Johnson, Mrs. Oscar W (Elisabeth Vilhelmina Berg)  female   27.0   \n",
+       "9                 Nasser, Mrs. Nicholas (Adele Achem)  female   14.0   \n",
+       "10                    Sandstrom, Miss. Marguerite Rut  female    4.0   \n",
+       "11                           Bonnell, Miss. Elizabeth  female   58.0   \n",
+       "12                     Saundercock, Mr. William Henry    male   20.0   \n",
+       "13                        Andersson, Mr. Anders Johan    male   39.0   \n",
+       "14               Vestrom, Miss. Hulda Amanda Adolfina  female   14.0   \n",
+       "15                   Hewlett, Mrs. (Mary D Kingcome)   female   55.0   \n",
+       "16                               Rice, Master. Eugene    male    2.0   \n",
+       "17                       Williams, Mr. Charles Eugene    male    NaN   \n",
+       "18  Vander Planke, Mrs. Julius (Emelia Maria Vande...  female   31.0   \n",
+       "19                            Masselmani, Mrs. Fatima  female    NaN   \n",
+       "20                               Fynney, Mr. Joseph J    male   35.0   \n",
+       "21                              Beesley, Mr. Lawrence    male   34.0   \n",
+       "22                        McGowan, Miss. Anna \"Annie\"  female   15.0   \n",
+       "23                       Sloper, Mr. William Thompson    male   28.0   \n",
+       "24                      Palsson, Miss. Torborg Danira  female    8.0   \n",
+       "25  Asplund, Mrs. Carl Oscar (Selma Augusta Emilia...  female   38.0   \n",
+       "26                            Emir, Mr. Farred Chehab    male    NaN   \n",
+       "27                     Fortune, Mr. Charles Alexander    male   19.0   \n",
+       "28                      O'Dwyer, Miss. Ellen \"Nellie\"  female    NaN   \n",
+       "29                                Todoroff, Mr. Lalio    male    NaN   \n",
+       "\n",
+       "    IrmaosConjuge  PaisFilhos           Bilhete    Tarifa       Cabine  \\\n",
+       "0               1           0         A/5 21171    7.2500          NaN   \n",
+       "1               1           0          PC 17599   71.2833          C85   \n",
+       "2               0           0  STON/O2. 3101282    7.9250          NaN   \n",
+       "3               1           0            113803   53.1000         C123   \n",
+       "4               0           0            373450    8.0500          NaN   \n",
+       "5               0           0            330877    8.4583          NaN   \n",
+       "6               0           0             17463   51.8625          E46   \n",
+       "7               3           1            349909   21.0750          NaN   \n",
+       "8               0           2            347742   11.1333          NaN   \n",
+       "9               1           0            237736   30.0708          NaN   \n",
+       "10              1           1           PP 9549   16.7000           G6   \n",
+       "11              0           0            113783   26.5500         C103   \n",
+       "12              0           0         A/5. 2151    8.0500          NaN   \n",
+       "13              1           5            347082   31.2750          NaN   \n",
+       "14              0           0            350406    7.8542          NaN   \n",
+       "15              0           0            248706   16.0000          NaN   \n",
+       "16              4           1            382652   29.1250          NaN   \n",
+       "17              0           0            244373   13.0000          NaN   \n",
+       "18              1           0            345763   18.0000          NaN   \n",
+       "19              0           0              2649    7.2250          NaN   \n",
+       "20              0           0            239865   26.0000          NaN   \n",
+       "21              0           0            248698   13.0000          D56   \n",
+       "22              0           0            330923    8.0292          NaN   \n",
+       "23              0           0            113788   35.5000           A6   \n",
+       "24              3           1            349909   21.0750          NaN   \n",
+       "25              1           5            347077   31.3875          NaN   \n",
+       "26              0           0              2631    7.2250          NaN   \n",
+       "27              3           2             19950  263.0000  C23 C25 C27   \n",
+       "28              0           0            330959    7.8792          NaN   \n",
+       "29              0           0            349216    7.8958          NaN   \n",
+       "\n",
+       "   Embarque  \n",
+       "0         S  \n",
+       "1         C  \n",
+       "2         S  \n",
+       "3         S  \n",
+       "4         S  \n",
+       "5         Q  \n",
+       "6         S  \n",
+       "7         S  \n",
+       "8         S  \n",
+       "9         C  \n",
+       "10        S  \n",
+       "11        S  \n",
+       "12        S  \n",
+       "13        S  \n",
+       "14        S  \n",
+       "15        S  \n",
+       "16        Q  \n",
+       "17        S  \n",
+       "18        S  \n",
+       "19        C  \n",
+       "20        S  \n",
+       "21        S  \n",
+       "22        Q  \n",
+       "23        S  \n",
+       "24        S  \n",
+       "25        S  \n",
+       "26        C  \n",
+       "27        S  \n",
+       "28        Q  \n",
+       "29        S  "
+      ]
+     },
+     "execution_count": 71,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "df_dani[:30]"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 72,
+   "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>IdPassageiro</th>\n",
+       "      <th>Sobreviveu</th>\n",
+       "      <th>Classe</th>\n",
+       "      <th>Nome</th>\n",
+       "      <th>Sexo</th>\n",
+       "      <th>Idade</th>\n",
+       "      <th>IrmaosConjuge</th>\n",
+       "      <th>PaisFilhos</th>\n",
+       "      <th>Bilhete</th>\n",
+       "      <th>Tarifa</th>\n",
+       "      <th>Cabine</th>\n",
+       "      <th>Embarque</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>2</td>\n",
+       "      <td>1</td>\n",
+       "      <td>1</td>\n",
+       "      <td>Cumings, Mrs. John Bradley (Florence Briggs Th...</td>\n",
+       "      <td>female</td>\n",
+       "      <td>38.0</td>\n",
+       "      <td>1</td>\n",
+       "      <td>0</td>\n",
+       "      <td>PC 17599</td>\n",
+       "      <td>71.2833</td>\n",
+       "      <td>C85</td>\n",
+       "      <td>C</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>3</td>\n",
+       "      <td>1</td>\n",
+       "      <td>3</td>\n",
+       "      <td>Heikkinen, Miss. Laina</td>\n",
+       "      <td>female</td>\n",
+       "      <td>26.0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>STON/O2. 3101282</td>\n",
+       "      <td>7.9250</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>S</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>4</td>\n",
+       "      <td>1</td>\n",
+       "      <td>1</td>\n",
+       "      <td>Futrelle, Mrs. Jacques Heath (Lily May Peel)</td>\n",
+       "      <td>female</td>\n",
+       "      <td>35.0</td>\n",
+       "      <td>1</td>\n",
+       "      <td>0</td>\n",
+       "      <td>113803</td>\n",
+       "      <td>53.1000</td>\n",
+       "      <td>C123</td>\n",
+       "      <td>S</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>9</td>\n",
+       "      <td>1</td>\n",
+       "      <td>3</td>\n",
+       "      <td>Johnson, Mrs. Oscar W (Elisabeth Vilhelmina Berg)</td>\n",
+       "      <td>female</td>\n",
+       "      <td>27.0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>2</td>\n",
+       "      <td>347742</td>\n",
+       "      <td>11.1333</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>S</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>10</td>\n",
+       "      <td>1</td>\n",
+       "      <td>2</td>\n",
+       "      <td>Nasser, Mrs. Nicholas (Adele Achem)</td>\n",
+       "      <td>female</td>\n",
+       "      <td>14.0</td>\n",
+       "      <td>1</td>\n",
+       "      <td>0</td>\n",
+       "      <td>237736</td>\n",
+       "      <td>30.0708</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>C</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>...</th>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>337</th>\n",
+       "      <td>876</td>\n",
+       "      <td>1</td>\n",
+       "      <td>3</td>\n",
+       "      <td>Najib, Miss. Adele Kiamie \"Jane\"</td>\n",
+       "      <td>female</td>\n",
+       "      <td>15.0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>2667</td>\n",
+       "      <td>7.2250</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>C</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>338</th>\n",
+       "      <td>880</td>\n",
+       "      <td>1</td>\n",
+       "      <td>1</td>\n",
+       "      <td>Potter, Mrs. Thomas Jr (Lily Alexenia Wilson)</td>\n",
+       "      <td>female</td>\n",
+       "      <td>56.0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>1</td>\n",
+       "      <td>11767</td>\n",
+       "      <td>83.1583</td>\n",
+       "      <td>C50</td>\n",
+       "      <td>C</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>339</th>\n",
+       "      <td>881</td>\n",
+       "      <td>1</td>\n",
+       "      <td>2</td>\n",
+       "      <td>Shelley, Mrs. William (Imanita Parrish Hall)</td>\n",
+       "      <td>female</td>\n",
+       "      <td>25.0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>1</td>\n",
+       "      <td>230433</td>\n",
+       "      <td>26.0000</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>S</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>340</th>\n",
+       "      <td>888</td>\n",
+       "      <td>1</td>\n",
+       "      <td>1</td>\n",
+       "      <td>Graham, Miss. Margaret Edith</td>\n",
+       "      <td>female</td>\n",
+       "      <td>19.0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>112053</td>\n",
+       "      <td>30.0000</td>\n",
+       "      <td>B42</td>\n",
+       "      <td>S</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>341</th>\n",
+       "      <td>890</td>\n",
+       "      <td>1</td>\n",
+       "      <td>1</td>\n",
+       "      <td>Behr, Mr. Karl Howell</td>\n",
+       "      <td>male</td>\n",
+       "      <td>26.0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>111369</td>\n",
+       "      <td>30.0000</td>\n",
+       "      <td>C148</td>\n",
+       "      <td>C</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "<p>342 rows × 12 columns</p>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "     IdPassageiro  Sobreviveu  Classe  \\\n",
+       "0               2           1       1   \n",
+       "1               3           1       3   \n",
+       "2               4           1       1   \n",
+       "3               9           1       3   \n",
+       "4              10           1       2   \n",
+       "..            ...         ...     ...   \n",
+       "337           876           1       3   \n",
+       "338           880           1       1   \n",
+       "339           881           1       2   \n",
+       "340           888           1       1   \n",
+       "341           890           1       1   \n",
+       "\n",
+       "                                                  Nome    Sexo  Idade  \\\n",
+       "0    Cumings, Mrs. John Bradley (Florence Briggs Th...  female   38.0   \n",
+       "1                               Heikkinen, Miss. Laina  female   26.0   \n",
+       "2         Futrelle, Mrs. Jacques Heath (Lily May Peel)  female   35.0   \n",
+       "3    Johnson, Mrs. Oscar W (Elisabeth Vilhelmina Berg)  female   27.0   \n",
+       "4                  Nasser, Mrs. Nicholas (Adele Achem)  female   14.0   \n",
+       "..                                                 ...     ...    ...   \n",
+       "337                   Najib, Miss. Adele Kiamie \"Jane\"  female   15.0   \n",
+       "338      Potter, Mrs. Thomas Jr (Lily Alexenia Wilson)  female   56.0   \n",
+       "339       Shelley, Mrs. William (Imanita Parrish Hall)  female   25.0   \n",
+       "340                       Graham, Miss. Margaret Edith  female   19.0   \n",
+       "341                              Behr, Mr. Karl Howell    male   26.0   \n",
+       "\n",
+       "     IrmaosConjuge  PaisFilhos           Bilhete   Tarifa Cabine Embarque  \n",
+       "0                1           0          PC 17599  71.2833    C85        C  \n",
+       "1                0           0  STON/O2. 3101282   7.9250    NaN        S  \n",
+       "2                1           0            113803  53.1000   C123        S  \n",
+       "3                0           2            347742  11.1333    NaN        S  \n",
+       "4                1           0            237736  30.0708    NaN        C  \n",
+       "..             ...         ...               ...      ...    ...      ...  \n",
+       "337              0           0              2667   7.2250    NaN        C  \n",
+       "338              0           1             11767  83.1583    C50        C  \n",
+       "339              0           1            230433  26.0000    NaN        S  \n",
+       "340              0           0            112053  30.0000    B42        S  \n",
+       "341              0           0            111369  30.0000   C148        C  \n",
+       "\n",
+       "[342 rows x 12 columns]"
+      ]
+     },
+     "execution_count": 72,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "#determinar quantos passageiros sobreviveu\n",
+    "df_danilocv = df_dani.loc[df_dani[\"Sobreviveu\"] == 1]\n",
+    "df_danilocv.reset_index(drop=True)\n",
+    "\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 73,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
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+       "\n",
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+       "\n",
+       "    .dataframe thead th {\n",
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+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>IdPassageiro</th>\n",
+       "      <th>Sobreviveu</th>\n",
+       "      <th>Classe</th>\n",
+       "      <th>Nome</th>\n",
+       "      <th>Sexo</th>\n",
+       "      <th>Idade</th>\n",
+       "      <th>IrmaosConjuge</th>\n",
+       "      <th>PaisFilhos</th>\n",
+       "      <th>Bilhete</th>\n",
+       "      <th>Tarifa</th>\n",
+       "      <th>Cabine</th>\n",
+       "      <th>Embarque</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>804</td>\n",
+       "      <td>1</td>\n",
+       "      <td>3</td>\n",
+       "      <td>Thomas, Master. Assad Alexander</td>\n",
+       "      <td>male</td>\n",
+       "      <td>0.42</td>\n",
+       "      <td>0</td>\n",
+       "      <td>1</td>\n",
+       "      <td>2625</td>\n",
+       "      <td>8.5167</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>C</td>\n",
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+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>756</td>\n",
+       "      <td>1</td>\n",
+       "      <td>2</td>\n",
+       "      <td>Hamalainen, Master. Viljo</td>\n",
+       "      <td>male</td>\n",
+       "      <td>0.67</td>\n",
+       "      <td>1</td>\n",
+       "      <td>1</td>\n",
+       "      <td>250649</td>\n",
+       "      <td>14.5000</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>S</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>645</td>\n",
+       "      <td>1</td>\n",
+       "      <td>3</td>\n",
+       "      <td>Baclini, Miss. Eugenie</td>\n",
+       "      <td>female</td>\n",
+       "      <td>0.75</td>\n",
+       "      <td>2</td>\n",
+       "      <td>1</td>\n",
+       "      <td>2666</td>\n",
+       "      <td>19.2583</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>C</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>470</td>\n",
+       "      <td>1</td>\n",
+       "      <td>3</td>\n",
+       "      <td>Baclini, Miss. Helene Barbara</td>\n",
+       "      <td>female</td>\n",
+       "      <td>0.75</td>\n",
+       "      <td>2</td>\n",
+       "      <td>1</td>\n",
+       "      <td>2666</td>\n",
+       "      <td>19.2583</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>C</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>832</td>\n",
+       "      <td>1</td>\n",
+       "      <td>2</td>\n",
+       "      <td>Richards, Master. George Sibley</td>\n",
+       "      <td>male</td>\n",
+       "      <td>0.83</td>\n",
+       "      <td>1</td>\n",
+       "      <td>1</td>\n",
+       "      <td>29106</td>\n",
+       "      <td>18.7500</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>S</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>...</th>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>337</th>\n",
+       "      <td>728</td>\n",
+       "      <td>1</td>\n",
+       "      <td>3</td>\n",
+       "      <td>Mannion, Miss. Margareth</td>\n",
+       "      <td>female</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>36866</td>\n",
+       "      <td>7.7375</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>Q</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>338</th>\n",
+       "      <td>741</td>\n",
+       "      <td>1</td>\n",
+       "      <td>1</td>\n",
+       "      <td>Hawksford, Mr. Walter James</td>\n",
+       "      <td>male</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>16988</td>\n",
+       "      <td>30.0000</td>\n",
+       "      <td>D45</td>\n",
+       "      <td>S</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>339</th>\n",
+       "      <td>829</td>\n",
+       "      <td>1</td>\n",
+       "      <td>3</td>\n",
+       "      <td>McCormack, Mr. Thomas Joseph</td>\n",
+       "      <td>male</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>367228</td>\n",
+       "      <td>7.7500</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>Q</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>340</th>\n",
+       "      <td>840</td>\n",
+       "      <td>1</td>\n",
+       "      <td>1</td>\n",
+       "      <td>Marechal, Mr. Pierre</td>\n",
+       "      <td>male</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>11774</td>\n",
+       "      <td>29.7000</td>\n",
+       "      <td>C47</td>\n",
+       "      <td>C</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>341</th>\n",
+       "      <td>850</td>\n",
+       "      <td>1</td>\n",
+       "      <td>1</td>\n",
+       "      <td>Goldenberg, Mrs. Samuel L (Edwiga Grabowska)</td>\n",
+       "      <td>female</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>1</td>\n",
+       "      <td>0</td>\n",
+       "      <td>17453</td>\n",
+       "      <td>89.1042</td>\n",
+       "      <td>C92</td>\n",
+       "      <td>C</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "<p>342 rows × 12 columns</p>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "     IdPassageiro  Sobreviveu  Classe  \\\n",
+       "0             804           1       3   \n",
+       "1             756           1       2   \n",
+       "2             645           1       3   \n",
+       "3             470           1       3   \n",
+       "4             832           1       2   \n",
+       "..            ...         ...     ...   \n",
+       "337           728           1       3   \n",
+       "338           741           1       1   \n",
+       "339           829           1       3   \n",
+       "340           840           1       1   \n",
+       "341           850           1       1   \n",
+       "\n",
+       "                                             Nome    Sexo  Idade  \\\n",
+       "0                 Thomas, Master. Assad Alexander    male   0.42   \n",
+       "1                       Hamalainen, Master. Viljo    male   0.67   \n",
+       "2                          Baclini, Miss. Eugenie  female   0.75   \n",
+       "3                   Baclini, Miss. Helene Barbara  female   0.75   \n",
+       "4                 Richards, Master. George Sibley    male   0.83   \n",
+       "..                                            ...     ...    ...   \n",
+       "337                      Mannion, Miss. Margareth  female    NaN   \n",
+       "338                   Hawksford, Mr. Walter James    male    NaN   \n",
+       "339                  McCormack, Mr. Thomas Joseph    male    NaN   \n",
+       "340                          Marechal, Mr. Pierre    male    NaN   \n",
+       "341  Goldenberg, Mrs. Samuel L (Edwiga Grabowska)  female    NaN   \n",
+       "\n",
+       "     IrmaosConjuge  PaisFilhos Bilhete   Tarifa Cabine Embarque  \n",
+       "0                0           1    2625   8.5167    NaN        C  \n",
+       "1                1           1  250649  14.5000    NaN        S  \n",
+       "2                2           1    2666  19.2583    NaN        C  \n",
+       "3                2           1    2666  19.2583    NaN        C  \n",
+       "4                1           1   29106  18.7500    NaN        S  \n",
+       "..             ...         ...     ...      ...    ...      ...  \n",
+       "337              0           0   36866   7.7375    NaN        Q  \n",
+       "338              0           0   16988  30.0000    D45        S  \n",
+       "339              0           0  367228   7.7500    NaN        Q  \n",
+       "340              0           0   11774  29.7000    C47        C  \n",
+       "341              1           0   17453  89.1042    C92        C  \n",
+       "\n",
+       "[342 rows x 12 columns]"
+      ]
+     },
+     "execution_count": 73,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "nome_da_coluna = 'Idade'\n",
+    "df_danilocv = df_danilocv.sort_values(by=nome_da_coluna)\n",
+    "df_danilocv.reset_index(drop=True)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 74,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
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+       "\n",
+       "    .dataframe tbody tr th {\n",
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+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
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+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>IdPassageiro</th>\n",
+       "      <th>Sobreviveu</th>\n",
+       "      <th>Classe</th>\n",
+       "      <th>Nome</th>\n",
+       "      <th>Sexo</th>\n",
+       "      <th>Idade</th>\n",
+       "      <th>IrmaosConjuge</th>\n",
+       "      <th>PaisFilhos</th>\n",
+       "      <th>Bilhete</th>\n",
+       "      <th>Tarifa</th>\n",
+       "      <th>Cabine</th>\n",
+       "      <th>Embarque</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>1</td>\n",
+       "      <td>0</td>\n",
+       "      <td>3</td>\n",
+       "      <td>Braund, Mr. Owen Harris</td>\n",
+       "      <td>male</td>\n",
+       "      <td>22.0</td>\n",
+       "      <td>1</td>\n",
+       "      <td>0</td>\n",
+       "      <td>A/5 21171</td>\n",
+       "      <td>7.2500</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>S</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>5</td>\n",
+       "      <td>0</td>\n",
+       "      <td>3</td>\n",
+       "      <td>Allen, Mr. William Henry</td>\n",
+       "      <td>male</td>\n",
+       "      <td>35.0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>373450</td>\n",
+       "      <td>8.0500</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>S</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>6</td>\n",
+       "      <td>0</td>\n",
+       "      <td>3</td>\n",
+       "      <td>Moran, Mr. James</td>\n",
+       "      <td>male</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>330877</td>\n",
+       "      <td>8.4583</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>Q</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>7</td>\n",
+       "      <td>0</td>\n",
+       "      <td>1</td>\n",
+       "      <td>McCarthy, Mr. Timothy J</td>\n",
+       "      <td>male</td>\n",
+       "      <td>54.0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>17463</td>\n",
+       "      <td>51.8625</td>\n",
+       "      <td>E46</td>\n",
+       "      <td>S</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>8</td>\n",
+       "      <td>0</td>\n",
+       "      <td>3</td>\n",
+       "      <td>Palsson, Master. Gosta Leonard</td>\n",
+       "      <td>male</td>\n",
+       "      <td>2.0</td>\n",
+       "      <td>3</td>\n",
+       "      <td>1</td>\n",
+       "      <td>349909</td>\n",
+       "      <td>21.0750</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>S</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>...</th>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
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+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>544</th>\n",
+       "      <td>885</td>\n",
+       "      <td>0</td>\n",
+       "      <td>3</td>\n",
+       "      <td>Sutehall, Mr. Henry Jr</td>\n",
+       "      <td>male</td>\n",
+       "      <td>25.0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>SOTON/OQ 392076</td>\n",
+       "      <td>7.0500</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>S</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>545</th>\n",
+       "      <td>886</td>\n",
+       "      <td>0</td>\n",
+       "      <td>3</td>\n",
+       "      <td>Rice, Mrs. William (Margaret Norton)</td>\n",
+       "      <td>female</td>\n",
+       "      <td>39.0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>5</td>\n",
+       "      <td>382652</td>\n",
+       "      <td>29.1250</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>Q</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>546</th>\n",
+       "      <td>887</td>\n",
+       "      <td>0</td>\n",
+       "      <td>2</td>\n",
+       "      <td>Montvila, Rev. Juozas</td>\n",
+       "      <td>male</td>\n",
+       "      <td>27.0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>211536</td>\n",
+       "      <td>13.0000</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>S</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>547</th>\n",
+       "      <td>889</td>\n",
+       "      <td>0</td>\n",
+       "      <td>3</td>\n",
+       "      <td>Johnston, Miss. Catherine Helen \"Carrie\"</td>\n",
+       "      <td>female</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>1</td>\n",
+       "      <td>2</td>\n",
+       "      <td>W./C. 6607</td>\n",
+       "      <td>23.4500</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>S</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>548</th>\n",
+       "      <td>891</td>\n",
+       "      <td>0</td>\n",
+       "      <td>3</td>\n",
+       "      <td>Dooley, Mr. Patrick</td>\n",
+       "      <td>male</td>\n",
+       "      <td>32.0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>370376</td>\n",
+       "      <td>7.7500</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>Q</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "<p>549 rows × 12 columns</p>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "     IdPassageiro  Sobreviveu  Classe  \\\n",
+       "0               1           0       3   \n",
+       "1               5           0       3   \n",
+       "2               6           0       3   \n",
+       "3               7           0       1   \n",
+       "4               8           0       3   \n",
+       "..            ...         ...     ...   \n",
+       "544           885           0       3   \n",
+       "545           886           0       3   \n",
+       "546           887           0       2   \n",
+       "547           889           0       3   \n",
+       "548           891           0       3   \n",
+       "\n",
+       "                                         Nome    Sexo  Idade  IrmaosConjuge  \\\n",
+       "0                     Braund, Mr. Owen Harris    male   22.0              1   \n",
+       "1                    Allen, Mr. William Henry    male   35.0              0   \n",
+       "2                            Moran, Mr. James    male    NaN              0   \n",
+       "3                     McCarthy, Mr. Timothy J    male   54.0              0   \n",
+       "4              Palsson, Master. Gosta Leonard    male    2.0              3   \n",
+       "..                                        ...     ...    ...            ...   \n",
+       "544                    Sutehall, Mr. Henry Jr    male   25.0              0   \n",
+       "545      Rice, Mrs. William (Margaret Norton)  female   39.0              0   \n",
+       "546                     Montvila, Rev. Juozas    male   27.0              0   \n",
+       "547  Johnston, Miss. Catherine Helen \"Carrie\"  female    NaN              1   \n",
+       "548                       Dooley, Mr. Patrick    male   32.0              0   \n",
+       "\n",
+       "     PaisFilhos          Bilhete   Tarifa Cabine Embarque  \n",
+       "0             0        A/5 21171   7.2500    NaN        S  \n",
+       "1             0           373450   8.0500    NaN        S  \n",
+       "2             0           330877   8.4583    NaN        Q  \n",
+       "3             0            17463  51.8625    E46        S  \n",
+       "4             1           349909  21.0750    NaN        S  \n",
+       "..          ...              ...      ...    ...      ...  \n",
+       "544           0  SOTON/OQ 392076   7.0500    NaN        S  \n",
+       "545           5           382652  29.1250    NaN        Q  \n",
+       "546           0           211536  13.0000    NaN        S  \n",
+       "547           2       W./C. 6607  23.4500    NaN        S  \n",
+       "548           0           370376   7.7500    NaN        Q  \n",
+       "\n",
+       "[549 rows x 12 columns]"
+      ]
+     },
+     "execution_count": 74,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "df_danilocm = df_dani.loc[df_dani[\"Sobreviveu\"] == 0]\n",
+    "df_danilocm.reset_index(drop=True)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 75,
+   "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>IdPassageiro</th>\n",
+       "      <th>Sobreviveu</th>\n",
+       "      <th>Classe</th>\n",
+       "      <th>Nome</th>\n",
+       "      <th>Sexo</th>\n",
+       "      <th>Idade</th>\n",
+       "      <th>IrmaosConjuge</th>\n",
+       "      <th>PaisFilhos</th>\n",
+       "      <th>Bilhete</th>\n",
+       "      <th>Tarifa</th>\n",
+       "      <th>Cabine</th>\n",
+       "      <th>Embarque</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>165</td>\n",
+       "      <td>0</td>\n",
+       "      <td>3</td>\n",
+       "      <td>Panula, Master. Eino Viljami</td>\n",
+       "      <td>male</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>4</td>\n",
+       "      <td>1</td>\n",
+       "      <td>3101295</td>\n",
+       "      <td>39.6875</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>S</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>387</td>\n",
+       "      <td>0</td>\n",
+       "      <td>3</td>\n",
+       "      <td>Goodwin, Master. Sidney Leonard</td>\n",
+       "      <td>male</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>5</td>\n",
+       "      <td>2</td>\n",
+       "      <td>CA 2144</td>\n",
+       "      <td>46.9000</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>S</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>643</td>\n",
+       "      <td>0</td>\n",
+       "      <td>3</td>\n",
+       "      <td>Skoog, Miss. Margit Elizabeth</td>\n",
+       "      <td>female</td>\n",
+       "      <td>2.0</td>\n",
+       "      <td>3</td>\n",
+       "      <td>2</td>\n",
+       "      <td>347088</td>\n",
+       "      <td>27.9000</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>S</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>206</td>\n",
+       "      <td>0</td>\n",
+       "      <td>3</td>\n",
+       "      <td>Strom, Miss. Telma Matilda</td>\n",
+       "      <td>female</td>\n",
+       "      <td>2.0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>1</td>\n",
+       "      <td>347054</td>\n",
+       "      <td>10.4625</td>\n",
+       "      <td>G6</td>\n",
+       "      <td>S</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>298</td>\n",
+       "      <td>0</td>\n",
+       "      <td>1</td>\n",
+       "      <td>Allison, Miss. Helen Loraine</td>\n",
+       "      <td>female</td>\n",
+       "      <td>2.0</td>\n",
+       "      <td>1</td>\n",
+       "      <td>2</td>\n",
+       "      <td>113781</td>\n",
+       "      <td>151.5500</td>\n",
+       "      <td>C22 C26</td>\n",
+       "      <td>S</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>...</th>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>544</th>\n",
+       "      <td>860</td>\n",
+       "      <td>0</td>\n",
+       "      <td>3</td>\n",
+       "      <td>Razi, Mr. Raihed</td>\n",
+       "      <td>male</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>2629</td>\n",
+       "      <td>7.2292</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>C</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>545</th>\n",
+       "      <td>864</td>\n",
+       "      <td>0</td>\n",
+       "      <td>3</td>\n",
+       "      <td>Sage, Miss. Dorothy Edith \"Dolly\"</td>\n",
+       "      <td>female</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>8</td>\n",
+       "      <td>2</td>\n",
+       "      <td>CA. 2343</td>\n",
+       "      <td>69.5500</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>S</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>546</th>\n",
+       "      <td>869</td>\n",
+       "      <td>0</td>\n",
+       "      <td>3</td>\n",
+       "      <td>van Melkebeke, Mr. Philemon</td>\n",
+       "      <td>male</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>345777</td>\n",
+       "      <td>9.5000</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>S</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>547</th>\n",
+       "      <td>879</td>\n",
+       "      <td>0</td>\n",
+       "      <td>3</td>\n",
+       "      <td>Laleff, Mr. Kristo</td>\n",
+       "      <td>male</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>349217</td>\n",
+       "      <td>7.8958</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>S</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>548</th>\n",
+       "      <td>889</td>\n",
+       "      <td>0</td>\n",
+       "      <td>3</td>\n",
+       "      <td>Johnston, Miss. Catherine Helen \"Carrie\"</td>\n",
+       "      <td>female</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>1</td>\n",
+       "      <td>2</td>\n",
+       "      <td>W./C. 6607</td>\n",
+       "      <td>23.4500</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>S</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "<p>549 rows × 12 columns</p>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "     IdPassageiro  Sobreviveu  Classe  \\\n",
+       "0             165           0       3   \n",
+       "1             387           0       3   \n",
+       "2             643           0       3   \n",
+       "3             206           0       3   \n",
+       "4             298           0       1   \n",
+       "..            ...         ...     ...   \n",
+       "544           860           0       3   \n",
+       "545           864           0       3   \n",
+       "546           869           0       3   \n",
+       "547           879           0       3   \n",
+       "548           889           0       3   \n",
+       "\n",
+       "                                         Nome    Sexo  Idade  IrmaosConjuge  \\\n",
+       "0                Panula, Master. Eino Viljami    male    1.0              4   \n",
+       "1             Goodwin, Master. Sidney Leonard    male    1.0              5   \n",
+       "2               Skoog, Miss. Margit Elizabeth  female    2.0              3   \n",
+       "3                  Strom, Miss. Telma Matilda  female    2.0              0   \n",
+       "4                Allison, Miss. Helen Loraine  female    2.0              1   \n",
+       "..                                        ...     ...    ...            ...   \n",
+       "544                          Razi, Mr. Raihed    male    NaN              0   \n",
+       "545         Sage, Miss. Dorothy Edith \"Dolly\"  female    NaN              8   \n",
+       "546               van Melkebeke, Mr. Philemon    male    NaN              0   \n",
+       "547                        Laleff, Mr. Kristo    male    NaN              0   \n",
+       "548  Johnston, Miss. Catherine Helen \"Carrie\"  female    NaN              1   \n",
+       "\n",
+       "     PaisFilhos     Bilhete    Tarifa   Cabine Embarque  \n",
+       "0             1     3101295   39.6875      NaN        S  \n",
+       "1             2     CA 2144   46.9000      NaN        S  \n",
+       "2             2      347088   27.9000      NaN        S  \n",
+       "3             1      347054   10.4625       G6        S  \n",
+       "4             2      113781  151.5500  C22 C26        S  \n",
+       "..          ...         ...       ...      ...      ...  \n",
+       "544           0        2629    7.2292      NaN        C  \n",
+       "545           2    CA. 2343   69.5500      NaN        S  \n",
+       "546           0      345777    9.5000      NaN        S  \n",
+       "547           0      349217    7.8958      NaN        S  \n",
+       "548           2  W./C. 6607   23.4500      NaN        S  \n",
+       "\n",
+       "[549 rows x 12 columns]"
+      ]
+     },
+     "execution_count": 75,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "nome_da_coluna = 'Idade'\n",
+    "df_danilocm = df_danilocm.sort_values(by=nome_da_coluna)\n",
+    "df_danilocm.reset_index(drop=True)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 76,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "<pandas.core.groupby.generic.DataFrameGroupBy object at 0x0000012120F6A050>"
+      ]
+     },
+     "execution_count": 76,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "#Agrupar passageiros por Classe\n",
+    "dado_agrupados = df_dani.groupby('Classe')\n",
+    "dado_agrupados"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 77,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "Classe\n",
+       "1    216\n",
+       "2    184\n",
+       "3    491\n",
+       "Name: IdPassageiro, dtype: int64"
+      ]
+     },
+     "execution_count": 77,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "#contagem de Passageiros por classe\n",
+    "contagem_de_passegeiros = dado_agrupados['IdPassageiro'].count()\n",
+    "contagem_de_passegeiros"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 78,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "Classe\n",
+       "3    491\n",
+       "1    216\n",
+       "2    184\n",
+       "Name: count, dtype: int64"
+      ]
+     },
+     "execution_count": 78,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "#Função value counts\n",
+    "df_dani['Classe'].value_counts()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 79,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "Classe\n",
+       "1    38.233441\n",
+       "2    29.877630\n",
+       "3    25.140620\n",
+       "Name: Idade, dtype: float64"
+      ]
+     },
+     "execution_count": 79,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "#Media de Idade de passageiros por classe\n",
+    "media_idade = dado_agrupados['Idade'].mean()\n",
+    "media_idade"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 80,
+   "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>count</th>\n",
+       "      <th>mean</th>\n",
+       "      <th>std</th>\n",
+       "      <th>min</th>\n",
+       "      <th>50%</th>\n",
+       "      <th>100%</th>\n",
+       "      <th>max</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>Idade</th>\n",
+       "      <td>714.0</td>\n",
+       "      <td>29.699118</td>\n",
+       "      <td>14.526497</td>\n",
+       "      <td>0.42</td>\n",
+       "      <td>28.0</td>\n",
+       "      <td>80.0</td>\n",
+       "      <td>80.0</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "       count       mean        std   min   50%  100%   max\n",
+       "Idade  714.0  29.699118  14.526497  0.42  28.0  80.0  80.0"
+      ]
+     },
+     "execution_count": 80,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "df_dani[['Idade']].describe(percentiles=[1]).T"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 81,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Este é o valor máximo Classe\n",
+      "1    512.3292\n",
+      "2     73.5000\n",
+      "3     69.5500\n",
+      "Name: Tarifa, dtype: float64\n",
+      "este o valor mínimoClasse\n",
+      "1    0.0\n",
+      "2    0.0\n",
+      "3    0.0\n",
+      "Name: Tarifa, dtype: float64\n"
+     ]
+    }
+   ],
+   "source": [
+    "#Obter o valor máximo e mínimo pago por passageiros em cada classe\n",
+    "valor_max = dado_agrupados['Tarifa'].max()\n",
+    "valor_min = dado_agrupados['Tarifa'].min()\n",
+    "print(f'Este é o valor máximo {valor_max}')\n",
+    "print(f'este o valor mínimo{valor_min}')"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 82,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "<pandas.core.groupby.generic.DataFrameGroupBy object at 0x0000012122F79010>"
+      ]
+     },
+     "execution_count": 82,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "#Agrupar passageiros por Sexo\n",
+    "dado_agrup_sex = df_dani.groupby('Sexo')\n",
+    "dado_agrup_sex"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 83,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "Sexo\n",
+       "female    314\n",
+       "male      577\n",
+       "Name: IdPassageiro, dtype: int64"
+      ]
+     },
+     "execution_count": 83,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "#contagem de Passageiros por Sexo\n",
+    "contagem_de_passegeirosx = dado_agrup_sex['IdPassageiro'].count()\n",
+    "contagem_de_passegeirosx"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 84,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "Sexo\n",
+       "female    27.915709\n",
+       "male      30.726645\n",
+       "Name: Idade, dtype: float64"
+      ]
+     },
+     "execution_count": 84,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "#Media de Idade de passageiros por Sexo\n",
+    "media_idadesx = dado_agrup_sex['Idade'].mean()\n",
+    "media_idadesx"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 85,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Este é o valor máximo Sexo\n",
+      "female    512.3292\n",
+      "male      512.3292\n",
+      "Name: Tarifa, dtype: float64\n",
+      "este o valor mínimoSexo\n",
+      "female    6.75\n",
+      "male      0.00\n",
+      "Name: Tarifa, dtype: float64\n"
+     ]
+    }
+   ],
+   "source": [
+    "#Obter o valor máximo e mínimo pago por passageiros em cada classe\n",
+    "valor_maxsx = dado_agrup_sex['Tarifa'].max()\n",
+    "valor_minsx = dado_agrup_sex['Tarifa'].min()\n",
+    "print(f'Este é o valor máximo {valor_maxsx}')\n",
+    "print(f'este o valor mínimo{valor_minsx}')"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 93,
+   "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 tr th {\n",
+       "        text-align: left;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead tr:last-of-type th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th colspan=\"4\" halign=\"left\">Tarifa</th>\n",
+       "      <th colspan=\"4\" halign=\"left\">Idade</th>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th>count</th>\n",
+       "      <th>mean</th>\n",
+       "      <th>min</th>\n",
+       "      <th>max</th>\n",
+       "      <th>count</th>\n",
+       "      <th>mean</th>\n",
+       "      <th>min</th>\n",
+       "      <th>max</th>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>Sexo</th>\n",
+       "      <th>Embarque</th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th rowspan=\"3\" valign=\"top\">female</th>\n",
+       "      <th>C</th>\n",
+       "      <td>73</td>\n",
+       "      <td>75.169805</td>\n",
+       "      <td>7.2250</td>\n",
+       "      <td>512.3292</td>\n",
+       "      <td>61</td>\n",
+       "      <td>28.344262</td>\n",
+       "      <td>0.75</td>\n",
+       "      <td>60.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>Q</th>\n",
+       "      <td>36</td>\n",
+       "      <td>12.634958</td>\n",
+       "      <td>6.7500</td>\n",
+       "      <td>90.0000</td>\n",
+       "      <td>12</td>\n",
+       "      <td>24.291667</td>\n",
+       "      <td>15.00</td>\n",
+       "      <td>39.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>S</th>\n",
+       "      <td>203</td>\n",
+       "      <td>38.740929</td>\n",
+       "      <td>7.2500</td>\n",
+       "      <td>263.0000</td>\n",
+       "      <td>186</td>\n",
+       "      <td>27.771505</td>\n",
+       "      <td>1.00</td>\n",
+       "      <td>63.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th rowspan=\"3\" valign=\"top\">male</th>\n",
+       "      <th>C</th>\n",
+       "      <td>95</td>\n",
+       "      <td>48.262109</td>\n",
+       "      <td>4.0125</td>\n",
+       "      <td>512.3292</td>\n",
+       "      <td>69</td>\n",
+       "      <td>32.998841</td>\n",
+       "      <td>0.42</td>\n",
+       "      <td>71.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>Q</th>\n",
+       "      <td>41</td>\n",
+       "      <td>13.838922</td>\n",
+       "      <td>6.7500</td>\n",
+       "      <td>90.0000</td>\n",
+       "      <td>16</td>\n",
+       "      <td>30.937500</td>\n",
+       "      <td>2.00</td>\n",
+       "      <td>70.5</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>S</th>\n",
+       "      <td>441</td>\n",
+       "      <td>21.711996</td>\n",
+       "      <td>0.0000</td>\n",
+       "      <td>263.0000</td>\n",
+       "      <td>368</td>\n",
+       "      <td>30.291440</td>\n",
+       "      <td>0.67</td>\n",
+       "      <td>80.0</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "                Tarifa                              Idade                    \\\n",
+       "                 count       mean     min       max count       mean    min   \n",
+       "Sexo   Embarque                                                               \n",
+       "female C            73  75.169805  7.2250  512.3292    61  28.344262   0.75   \n",
+       "       Q            36  12.634958  6.7500   90.0000    12  24.291667  15.00   \n",
+       "       S           203  38.740929  7.2500  263.0000   186  27.771505   1.00   \n",
+       "male   C            95  48.262109  4.0125  512.3292    69  32.998841   0.42   \n",
+       "       Q            41  13.838922  6.7500   90.0000    16  30.937500   2.00   \n",
+       "       S           441  21.711996  0.0000  263.0000   368  30.291440   0.67   \n",
+       "\n",
+       "                       \n",
+       "                  max  \n",
+       "Sexo   Embarque        \n",
+       "female C         60.0  \n",
+       "       Q         39.0  \n",
+       "       S         63.0  \n",
+       "male   C         71.0  \n",
+       "       Q         70.5  \n",
+       "       S         80.0  "
+      ]
+     },
+     "execution_count": 93,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "#Determinar valor máximo e mínimo pelo sexo\n",
+    "\n",
+    "df_dani.groupby(['Sexo','Embarque']).agg({'Tarifa':['count','mean','min','max'],\n",
+    " 'Idade':['count','mean','min','max']})\n"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Aula da Biblioteca Matplotlib"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 94,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "Matplotlib is building the font cache; this may take a moment.\n"
+     ]
+    }
+   ],
+   "source": [
+    "import matplotlib.pyplot as plt"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 99,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 640x480 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "fig, ax = plt.subplots()\n",
+    "ax.plot([1,2,3,4], [2,4,6,8]);"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 106,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": "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",
+      "text/plain": [
+       "<Figure size 640x480 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "#Pandas\n",
+    "contagem_de_passegeiros.plot(kind='barh');"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 108,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 640x480 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "df_dani['Idade'].plot(kind='hist');"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 132,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 640x480 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "# título, legendas (Y e X)\n",
+    "contagem_passageirosx = df_dani['Sexo'].value_counts()\n",
+    "contagem_passageirosx.plot(kind='bar', color= 'green',edgecolor='yellow', hatch='-');\n",
+    "#df['Idade'].plot.hist(bins=10, edgecolor='black')\n",
+    "plt.xlabel('Gênero dos Passageiros')\n",
+    "plt.ylabel('Quantidade')\n",
+    "plt.title('Número de Passageiros por Gênero');"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 137,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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CQoLdsHbTpk3JycmpkPf8v/p++OEHzGYza9eutRsRqOmtFUdq+iEM0Lp1aw4cOICiKHbloqOj7fLt37+fmJgYli9fzoQJE9Tj5w+Nt27dGjj7V/65zq+zXbt2bN68meuuu87pL4RLdZ764KhPMTExeHh4qIHZ6tWrmThxIm+88Yaap7i42OE158i5v7/yJ43AdkssPj6eq666Sj1WPhJzft3nX8vlE2x9fHwYNGhQjdrhyPn9VxSFo0eP0rVrV7u2R0dH27W9/Fh5+sXSunVrrFYrsbGxdhP/T548SU5OTo3P7+j/0xYtWuDh4VHhGgY4cuQIWq1WHSFs164d+fn5Nfpdu7m5ccstt3DLLbdgtVqZNm0aH330Ec8//3yFESpR/2TOjqgXTz31FB4eHjz44INkZmbapWVlZfF///d/+Pj42C3z365dO3Jzc+1GhFJTUys8qVH+1/75tyEczQWpqfI1RGryxTd8+HBOnDjB6tWr1WPlj9lX105FUSo8vhoUFES3bt1Yvny53e2UTZs2VVhp+o477sBisfDyyy9XaFdZWVmV7b9U56kPO3futLsNl5SUxJo1axgyZIj6Puh0ugojQu+9916F0ZbK9OjRgxYtWvDhhx9SUlKiHv/0008r/D7Kg5hzH3+3WCwVrpHu3bvTrl07Xn/9dfLz8yuc89SpUzVq24oVK+xuG69evZrU1FSGDRumtt3f358PP/zQ7lHvn3/+mcOHDzNixIganae2hg8fDqA+7VTuzTffBKjx+T09PSv8rnU6HUOGDGHNmjV2j/qfPHmSVatW0a9fP3x8fADbdb1z5042bNhQoe6cnBx1Ltj5n1larVYNHCtb+kDULxnZEfWiffv2rFixgrvvvpsrr7yywgrK2dnZfPnll3b35u+66y5mzJjB6NGjeeSRRygsLGTRokV06NDB7otsyJAh6l9dDz74IPn5+XzyySf4+/uTmppaq/Z269YNnU7HggULyM3NxWg0quv4nG/KlCksXLiQCRMmEBUVRVBQEJ999lmFx3M7duxIu3bteOqpp0hJScHHx4dvv/3W4Vyh+fPnM2LECPr168d9991HVlYW7733HldccYXdl+CAAQN48MEHmT9/Pnv37mXIkCEYDAZiY2P55ptveOedd+wmTtfXecqtXr3a4W2YwYMHExAQUG35murSpQuRkZF2j54DzJ07V81z880389lnn+Hr60vnzp3ZuXMnmzdvtpv7UxWDwcC///1vHnzwQW688UbuvPNO4uPjWbZsWYU5O1dccQV9+vRh5syZZGVl0axZM7788ssKE6u1Wi2LFy9m2LBhXHHFFUyePJng4GBSUlL49ddf8fHx4Ycffqi2bc2aNaNfv35MnjyZkydP8vbbb9O+fXumTJmitn3BggVMnjyZAQMGcPfdd6uPnrdp04bHH3+8Rr+D2rrqqquYOHEiH3/8MTk5OQwYMID//e9/LF++nFGjRnHDDTfUqJ7u3buzefNm3nzzTVq2bElYWBi9e/fm3//+N5s2baJfv35MmzYNvV7PRx99hNls5rXXXlPLP/3006xdu5abb75ZXX6ioKCA/fv3s3r1ahISEmjevDkPPPAAWVlZ3HjjjYSEhHD8+HHee+89unXrVumSFKKe1dNTYEIoiqIo+/fvV+655x4lMDBQ0Wq1CqCYTCbl4MGDDvNv3LhR6dKli+Lm5qZEREQon3/+ucNHz9euXat07dpVMZlMSps2bZQFCxYoS5curfC4b+vWrZURI0ZUOM/5j5MriqJ88sknStu2bRWdTmf3eLCjvMePH1duvfVWxcPDQ2nevLny6KOPqo9ln/vo+aFDh5RBgwYpXl5eSvPmzZUpU6Yo//zzjwIoy5Yts6vz22+/VTp16qQYjUalc+fOyn//+99KH8f/+OOPle7duyvu7u6Kt7e3cuWVVyrPPPOMcuLECYe/10t9nqoePT/3d1T+6PQ333xjV778cea///7bYb2nTp1SjwHK9OnTlc8//1wJDw9XjEajcvXVV1dYRiA7O1uZPHmy0rx5c8XLy0uJjIxUjhw5orRu3drucebKzl3ugw8+UMLCwhSj0aj06NFD2bp1q8NrJC4uThk0aJBiNBqVgIAAZdasWcqmTZscLnGwZ88eZcyYMYqfn59iNBqV1q1bK3fccYfyyy+/VPl7Lv/9ffHFF8rMmTMVf39/xd3dXRkxYoTd0gblvvrqK+Xqq69WjEaj0qxZM2XcuHFKcnKyXZ6JEycqnp6eVZ73XNX9vsqVlpYqc+fOVcLCwhSDwaCEhoYqM2fOVIqLi+3yVfb/rKIoypEjR5Trr79ecXd3VwC792337t1KZGSk4uXlpXh4eCg33HCDsmPHjgp1nD59Wpk5c6bSvn17xc3NTWnevLly7bXXKq+//rq6/MHq1auVIUOGKP7+/oqbm5vSqlUr5cEHH1RSU1Nr/HsRl5ZGUS7yLEwhnLBixQomTZrE+PHj7VYxFqIxK189uS53vK+J3377jRtuuIFvvvmmRiNtQrgquY0lGpQJEyaQmprKs88+S0hICPPmzavvJgkhhGjkJNgRDc6MGTOYMWNGfTdDCCGEi5CnsYQQQgjh0mTOjhBCCCFcmozsCCGEEMKlSbAjhBBCCJcmE5Sx7Ydy4sQJvL29ndoWQAghhBD1R1EUTp8+TcuWLavcr02CHeDEiRMVdk8WQgghROOQlJRESEhIpekS7ADe3t6A7ZdVvkeKEEIIIRq2vLw8QkND1e/xykiww9mdcn18fCTYEUIIIRqZ6qagyARlIYQQQrg0CXaEEEII4dIk2BFCCCGES5NgRwghhBAuTYIdIYQQQrg0CXaEEEII4dIk2BFCCCGES5NgRwghhBAuTYIdIYQQQrg0CXaEEEII4dIk2BFCCCGES5NgRwghhBAuTYIdIYQQQrg0CXaEEEII4dL09d0AUXOJiZCRUd+tcA3Nm0OrVvXdCiGEEJeCBDuNRGIiRHRQKDZr6rspLsFkVIiO0UjAI4QQlwEJdhqJjAwqBDrhIUV8OSe+2rKfrvfj/e/8sSr25TUahYdHpzNxaGa1ddz5UhhHk90dpq2dF0tw89IqyyefMjDyuXCHafXRj2KzhowMGd0RQojLgQQ7jYxWo6hf9knpRrq1L0Rbzcyrd771R6tVsFo06LQKABar7XVugY5rOhRWWd5qhaSTRvXfOq2CxXo24NBqqLaOExm+dv8+t4766ocQQojLg0xQbmR6d84HbKMZxSVaEtLcqi2z96gHZRbbWx3RqpiIVsUAlFm07D3qUW35+FQj5lItGo0twBjSMw8vdwvaMwHHgXjHIz7nKs+j1Sp4e1gY3COv3voBSrV5hRBCuA4JdhqZhY8mseeTgwztZQsWDiZUHWhYLBCTZKJ1gJmVs4+xf+lB9i89yMrZx2gdYCYm2YjFUvU5DyaYABjaK4+9iw+ybkEsiV/v45m70jAarDUOdkxuVmbcncbxr/bx82ux9daPa7vkV9teIYQQrkOjKMpl/2duXl4evr6+5Obm4uPjU9/NcWj3bujeHaI+PqTertm2z4uCYi2RZwIGR9Kz9Xz3RxPuG56JQW//VpeWaVi6zo/R/XPwb1pWaR0b/ueDl7uV666sGCSkZhr47o8mTBt1qsr2f/B9C8b0zybQr+J5LnU/3I1Wuk/tTFQUXHNNlc0WQgjRgNX0+1uCHRpvsCNqZ3eMhwQ7QgjhAmr6/S23sYQQQgjh0iTYEUIIIYRLk2BHCCGEEC5Ngh0Xkn1ah2ZgD1ZtblbrOlZtboZmYA+yT+tqXUePqZ3o+WCnWpdvKP0QQgjhGiTYcSG/RNkmZ838JLjWdcz4KASALbu9a1X+dKGWqBhPdkV7kl9Yu8urIfRDCCGE65Bgx0UoCsxbGQhAUrobR5OdXyk4NtlISoYBgHkrg6jNc3qL1viffb22hdPlG0o/hBBCuA4JdlxAzmkdy9f7sSfWE7BtxTB7STDJ6Qas1urLW62QnG5g9pJgdRuG3TGeLF/vR04NbwOZSzQcjDfx6qpA9dirq4I4GG/CXFKzzUsbQj+EEEK4Hllnh8a3zk639oXM/CSY3/Z6E5NkIifftsXZ+XtWARgNVsKCzHQJK+Kt6UmE+Ns27ExKN/D4wlAOJrifs43CWefW1cSrjA6hxQzsdpr5U1LUPay++6MJi9a04FCCO6lZBqxWDRqNgnJm767y11qtQku/Ujq1LuKhkacY3T8HsAUn9dGPjq2KWLGhhayzI4QQjZyss+PCtFqYPDSThDSjGiAAFQIEAHOplugkE0N75akBAkCofylDe+URnWSqECCcX1dOvp6ENCP3Dcuw26xzeO9cTG4KKRluWM/kV87Zkbz8tdWqIfmUG+5GK8N759Z7P0Zel1MhnxBCCNclwU4j1bF1MdvfO0KQXwl6neN7PBqNgkajsHxmPPePyKiQ/sDNGXz6bIKazxG9zkqQXwnb3ztCRCuzXZrRTWH13DjGXJ9dafnydoy9PovVc49hdLPPVx/9aBNY6jCPEEII1yTBTiPWPsTM9oVHaOLleAdMRdGwfGY89w7JqrSOCZGZLJ8Zbzcic66m3hZ2LDxC+xCzw3Q3g8JXc+IY1S+n0nOM6pfDl3OOVdjTqiH1QwghhOuSYKeRCwsqwcu98tm7V7UrqraOrm0rz+PlbqVNUEmV5fV66Ny6CIO+YjsMeitXtClCr3dQ8BwNoR9CCCFcU70HOykpKYwfPx4/Pz/c3d258sor2bVrl5quKApz5swhKCgId3d3Bg0aRGxsrF0dWVlZjBs3Dh8fH5o0acL9999Pfn7FHbpdUZFZQ2K6GwDaM08gnXs76EC8e7V1nJunvGz500zHT7pRbK7+aaoD8e6UWTRqO8rbUmbR1KgNDaUfQgghXE+9BjvZ2dlcd911GAwGfv75Zw4dOsQbb7xB06ZN1TyvvfYa7777Lh9++CF//fUXnp6eREZGUlxcrOYZN24cBw8eZNOmTfz4449s3bqVqVOn1keXLrkjiSZ1cnD7YDNLZ8TbTcB1NkgY1S+HpTPiaRdsu91jtWo4kmiqto49Rz1QFA0eJgsvTDzBCxNP4GGyoCga9sR6NJp+CCGEcD3V3Fy4uBYsWEBoaCjLli1Tj4WFhamvFUXh7bffZvbs2YwcORKAFStWEBAQwPfff89dd93F4cOHWb9+PX///Tc9evQA4L333mP48OG8/vrrtGzZ8tJ26hI7EO9Om0AzcyefYNygTHQ6mDwsk6joNGYtDq5xkBDZM5dXHkihe0QhABOGZLJysx8vLGvJgXh3uoVXfouooEhLRq6ep+5M49l7UvHztc29mTbyFAu+COSDNS0oLNbiYar8NlVD6IcQQgjXVK/r7HTu3JnIyEiSk5P5/fffCQ4OZtq0aUyZMgWAY8eO0a5dO/bs2UO3bt3UcgMGDKBbt2688847LF26lCeffJLs7Gw1vaysDJPJxDfffMPo0aOrbUdjW2fnmg6F6vGjyUZaBZTgZnD8Nh5KMNG5TbHDtJrkMZfYHhsvHyFxJDdfR36RluAWjp9ySjllwMvdim8lE5Dh0vZjd4wH3ad2lnV2hBCikWsU6+wcO3aMRYsWER4ezoYNG3jooYd45JFHWL58OQBpaWkABAQE2JULCAhQ09LS0vD397dL1+v1NGvWTM1zPrPZTF5ent1PY9U+xFxpgABUGyBUl8foplQZ6AD4elkqDXQAgluUVhnoQMPohxBCCNdUr7exrFYrPXr0YN68eQBcffXVHDhwgA8//JCJEydetPPOnz+fuXPnXrT6hRBCCNFw1OvITlBQEJ07d7Y71qlTJxITEwEIDLTts3Ty5Em7PCdPnlTTAgMDSU9Pt0svKysjKytLzXO+mTNnkpubq/4kJSXVSX+EEEII0fDUa7Bz3XXXER0dbXcsJiaG1q1bA7bJyoGBgfzyyy9qel5eHn/99Rd9+/YFoG/fvuTk5BAVFaXm2bJlC1arld69ezs8r9FoxMfHx+6nsThdeGFvWbFZc8GPYOfm6y5oJ3FFsdVxIeqiH0IIIS4P9RrsPP744/z555/MmzePo0ePsmrVKj7++GOmT58OgEaj4bHHHuPf//43a9euZf/+/UyYMIGWLVsyatQowDYSNHToUKZMmcL//vc/tm/fzr/+9S/uuusul3wSa+BjHTl2wq3W5d0ju+Me2b3W5eNSjDS5+WrufSWs+syVGP9KGE1uvrpe+yGEEOLyUa/BTs+ePfnuu+/44osv6NKlCy+//DJvv/0248aNU/M888wzPPzww0ydOpWePXuSn5/P+vXrMZnOrpmycuVKOnbsyE033cTw4cPp168fH3/8cX106ZJY/XuzWpWLSTKqr2OTjVXkrOrctjWQNkX51Gp0R1Fg0y6fM3XVXz+EEEJcPur10fOGojE9eg7Q1LuMpK/34VnF9gqOTJrfhs83+QFw75BMlj2b4FT5giItoXd0Jfu0bV77T6/GMrxPbjWl7P2005ebZ4YD9deP7fs96fdwJ3n0XAghGrmafn/X69NYonZy8nVMerUNQ3rmER5sJjykmJbNS9GcN4UlN19HbLKR2BQT0YkmPtvkp65SvGKjH60DSohoVUyHkGLCQ4rx8bQPOhQFTmQYiE02EZtiZOPfPuScmWuj0yo8/n4o0UkmwoNt5cOCKq6TU1KqIT7V7UwdJj5c2wKdVsFi1dRbP77a0hQhhBCXDxnZofGN7IBtg83SsrN3Ie+4IYsvnj+G9syhr7Y05a6X2qnpep0Vq6JRgwStVkGrUSiz2ApoNApfzjnGHTfYFme0WuHul9vy9a9nbzWdf87z6wxpUcKO9w8T6m9bcycp3UDfaZ1IyXBzeM766odeZ6XMopWRHSGEaOQaxaKCovbODRBGXpfNZ7Pi1QAB4M4bs1nyTDwajYLmTDBQHiCAba+oMotWTV/yTIIaIABotbBiZjy3Xnf22LnnBNQ6dVqFgKal/PJmtBroAIT62475Ny1Fp1XUc9Z3P85vgxBCCNcmn/qNmEajcPvALL6Ze8zh6sP3Dc9kxcx4Na+j8mALBiYPy6yQbnRTWD33GLcNyHJYHmyjJAHNStm+8AgdQiuuUBzRysyOhUcIaFZqt4t5Q+uHEEII1yXBTiMWEVrMqtnHMOgr/wIfPySLWeNSK01/bnwq44dkVZpu0Ct88fwxOoQ43oqhzKLl5wWxVW7F0C7YzM8LYisdUWkI/RBCCOG6JNhpxDJy9ehrMMU8r1CHXlcxkNDrFPIKq1/cT6+3navS+guqryO3ijwNpR9CCCFckwQ7jYxWo6DV2r7wM3INZORU/+W9L86D0jItep1Vndui19kmBu+Lc6+2/KkcPZl5Btv5tQq6M+cvb8eB+OrrKM9TXkanrd9+CCGEuHxIsNPIbHkzmlnjUnE32nYRP5hgqqYE7D8TaIzok8v+pQfZv/QgI86sj7P/WPVBwsEz5d2NFp4bn0rGmr18/WIcbQJtt66cCXbCAs18/WIcGWv21ls/jIaqd2AXQgjhWmRMv5Hx9rTy8v0neHhMOvM+D+JoiokB3fIrzZ+erefq9oXMm5JCr04F6vHvX4njr0OezFocTHq2Hv+mZZXWcTTFyGO3nWTmuFQ13+0DsxndL5vlG5rz+z9e1bY7r0DHkmfimTAkU71lVV/9GNEnh8FPRVTbZiGEEK5B1tmhca2zE/XxIa7pUKget1hAV8V0lerS66KOxnaO3TEedJ/aWdbZEUKIRk7W2blMVBcAVJdeF3W4yjmEEEK4Jgl2hBBCCOHSJNgRQgghhEuTYMeFKAo8tzi4Ro9xVyYjR89zi4MvqB0/7PDlxx2+tS7fUPohhBDCNUiw40K27fdi3udB9JnWsdZ19J7WkXmfB7FtX/VPWDmiKHDrrHBumRVObae+N4R+CCGEcB0S7LiQxT81ByAty0B+ofNvbX6hlrQsg11dzvpp59kRnXV/1m50pyH0QwghhOuQYMdFHE028vkmPwAKzVoWrW3hdB0frPGnyGy7JD7b5EdcitGp8ooCc5a1RHdmleU5y1o6PbrTEPohhBDCtciigo2Q1Qo//+VLTLKJ2GQj0Ukm/jnqjlajYEWDomh4bnEwX//ajE6tiwgPMRMeXMyN15xWF91Lz9azZbc3sSm2Og4fd+efOHcURQPYtqXo/VBHrmpfRERoMeEhZjqEFDOsdy7aMyHyP0fd+fuIp9qOA/HuHE05uxLy7hhPIu7twhVtitTyPTsWcFX7onrth1Z2PhdCiMuKBDuNkFYLKRkGnng/tNI8pWVadkV7EhXjgaJouOXaHEb3z1HTfT0trPrFjx92NEGjUdTgoFyZRUtmnpYtuw1s2e2DRqPw0ZPH1UAHwM2g8PzSlqRluTmsAyA22cTRFCOKoiGwWQm/vhVT7/2YNb7y3dOFEEK4HrmN1UhNvSWDpTPi1Q0xqzK6fzar58ZhdDubz+imsHpuHKP7Z1dZtrz+pc8kMOXmDLu0Tq2L2fpuNIHNStTNQR3RaRUCm5Ww9d1oOrYurvd+jDknWBJCCOH6JNhpxCYPy+SzWfGVpms0CncMzOarF47hZqgYSLgZFL564Ri3D8yuMtD4bFY8k4ZlOkwLDzGzfeERApqWOQx4dFqFgKZl7Hj/COEh5gbbDyGEEK5Lgp1GbtzgLK5sW+QwTVE0zJ+ajEFfeQBg0CvMn5Ls8BYUQNe2RYwbnFVlG9q2LOHhMemO2wA8MjadsKCSKutoCP0QQgjhmiTYaeSsVohOPDsp+PzRlUMJ7tXWcX6ec+uITjJhtVbfjkPHTeqoSvnTWGCbIHwowVRVUaDh9EMIIYTrkWCnkYtPNWIu1aqBxpCeeXi5W9Ce+aI/EF99kFCeR6tV8PawMLhHHmC7fVRcoiUhza3aOvYe9aDMYrucIloVE9HKNjenzKJl71GPRtMPIYQQrkeCnUbu4JlRk6G98ti7+CDrFsSS+PU+nrkrDaPBWuMgweRmZcbdaRz/ah8/vxbLnk8OMrRX3plzVF2HxQIxSSZaB5hZOfsY+5ceZP/Sg6ycfYzWAWZiko1YLA2/H0IIIVyTPHreyBkNCtveO8J1V+arx5p6W5g/NYVHxqbz3R9Nqq3j2i75vP5QEoF+ZeqxbuFFrFsQy7Z9XhQUVx0TZ+bpeftfidw3PNNuXs09g7K4fWA2S9f5kZmnV9fGaaj9EEII4Zo0ilLbHYxcR15eHr6+vuTm5uLj41PfzXFo927o3h2iPj7ENR0K67s5jdruGA+6T+1MVBRcc019t0YIIURt1fT7W/7UFUIIIYRLk2BHCCGEEC5Ngh0hhBBCuDQJdhqZ7lM7k31aV+vyPaZ2oueDnWpdPvu0Ds3AHqza3KzWdaza3AzNwB712g8hhBCXDwl2GqEtu71rVe50oZaoGE92RXuSX1i7t/6XKNsEsJmfBNeqPMCMj0KA+u2HEEKIy4d8UzRC81YGUZtn6Bat8T/7em0Lp8srCsxbGQhAUrobR5ONTtcRm2wkJcMA1G8/hBBCXD4k2GmEdsd4sny9Hzk1vA1kLtFwMN7Eq6sC1WOvrgriYLwJc4njvaTOl3Nax/L1fuyJ9QRsWzHMXhJMcrqhRtswWK2QnG5g9pJgdRuH+urHDzt8a5RXCCGEa5B1dmhc6+yALdCwWG1f7k28yugQWszAbqeZPyUF7Znw9bs/mrBoTQsOJbiTmmXAatWg0SjqRpnlr7VahZZ+pXRqXcRDI08xun8OYAtOZn4SzG97vYlJMpGTr69w7nJGg5WwIDNdwop4a3oSIf6lACSlG3h8YSgHE9zV7SDOVZ/9AGSdHSGEaORknR0Xdm6wkZOvJyHNyH3DMtQAAWB471xMbgopGW5Yz+Q/d0fw8tdWq4bkU264G60M752rpmu1MHloJglpRrsA4fxAB8BcqiU6ycTQXnlqoAMQ6l/K0F55RCeZKgQ69d0PIYQQlw8Jdhoxvc5KkF8J2987QkQrs12a0U1h9dw4xlyfrW6u6YhGozD2+ixWzz2G0c0+X8fWxWx/7whBfiXodY7vVWk0ChqNwvKZ8dw/IqNC+gM3Z/DpswlqvobaDyGEEK5Lgp1GrKm3hR0Lj9A+xOww3c2g8NWcOEb1y6m0jlH9cvhyzjG7Pa3O1T7EzPaFR2ji5XgnT0XRsHxmPPcOyar0HBMiM1k+M95uRKah9UMIIYTrkmCnEfNyt9ImqKTKPHo9dG5dhEFfcUTDoLdyRZsi9NXc3QkLKsHLvfIRkavaFVXb1q5tK8/TUPohhBDCNUmw0wiVP810/KQbxebqn0I6EO9OmcWWT6tV0J4pX2bRcCDevdryRWYNieluannA7nZQTeo4N0952frshxBCiMuHBDuNzAsTU2gXbLvdY7VqOJJoqrbMnqMeKIoGD5OFFyae4IWJJ/AwWVAUDXtiPaotfyTRpE4Obh9sZumMeEZel6OmOxvsjOqXw9IZ8fXaDyGEEJcPeTylkbn1ulyen5DKys1+vLCsJQfi3ekWXvktooIiLRm5ep66M41n70nFz9c2Z2XayFMs+CKQD9a0oLBYi4ep8ts7B+LdaRNoZu7kE4wblIlOB5OHZRIVncasxcE1DnYie+byygMpdI8oBGDCkMx66cfkYRm8sKz2K0ALIYRoXGSdHRrXOjtRHx/img62YMFcYnvcunyExJHcfB35RVqCW5Q6TE85ZcDL3YpvFRN3jyYbaRVQgpvB8aVyKMFE5zbFVba/qjyXuh8H4t3pPrWzrLMjhBCNXE2/v50e2SkqKkJRFDw8bLcNjh8/znfffUfnzp0ZMmRI7VssnGZ0U6oMEAB8vSxVBgCVBQ/nquwpqXLVBTrV5Wko/RBCCOGanJ6zM3LkSFasWAFATk4OvXv35o033mDkyJEsWrTIqbpefPFFNBqN3U/Hjh3V9OLiYqZPn46fnx9eXl6MHTuWkydP2tWRmJjIiBEj8PDwwN/fn6effpqysjJnuyWEEEIIF+V0sLN792769+8PwOrVqwkICOD48eOsWLGCd9991+kGXHHFFaSmpqo/27ZtU9Mef/xxfvjhB7755ht+//13Tpw4wZgxY9R0i8XCiBEjKCkpYceOHSxfvpxPP/2UOXPmON0OIYQQQrgmp29jFRYW4u3tDcDGjRsZM2YMWq2WPn36cPz4cecboNcTGBhY4Xhubi5Llixh1apV3HjjjQAsW7aMTp068eeff9KnTx82btzIoUOH2Lx5MwEBAXTr1o2XX36ZGTNm8OKLL+Lmdvk9Zpybr8PH04Kmlg8dKQrkFeiqvGVUnfLHyE3G2k8Hawj9EEII4RqcHtlp374933//PUlJSWzYsEGdp5Oenl6ryb2xsbG0bNmStm3bMm7cOBITEwGIioqitLSUQYMGqXk7duxIq1at2LlzJwA7d+7kyiuvJCAgQM0TGRlJXl4eBw8edLotjV1cipEmN1/Nva+E1bqO8a+E0eTmqzl2ovaBontkd9wju9e6fEPphxBCCNfgdLAzZ84cnnrqKdq0aUOvXr3o27cvYBvlufrqq52qq3fv3nz66aesX7+eRYsWER8fT//+/Tl9+jRpaWm4ubnRpEkTuzIBAQGkpaUBkJaWZhfolKeXp1XGbDaTl5dn9+MKVv/eFIBNUT7U5hk7RYFNu3zO1NWsVm2ISTKqr2OTjVXkrFxD6IcQQgjX4XSwc9ttt5GYmMiuXbvYsGGDevymm27irbfecqquYcOGcfvtt9O1a1ciIyNZt24dOTk5fP311842yynz58/H19dX/QkNDb2o57sUCoq0LPjCdjswPdvAz3/5Ol3Huj99OZVjAODVVYEUFDm/5uS8z4PQaRV0WoV5nwc5Xb6h9EMIIYTrqNWigoGBgQQGBpKcnAxASEgIvXr1uuDGNGnShA4dOnD06FEGDx5MSUkJOTk5dqM7J0+eVOf4BAYG8r///c+ujvKntRzNAyo3c+ZMnnjiCfXfeXl5jS7gURQ4kWEgNtlEbIqRjX/7kJOvA2zbMDz+fijRSSbCg4sJDykmLKjiOjklpRriU93O1GHiw7Ut0GkVLFYNOfk6Jr3ahiE98wgPNhMeUkzL5qUV5tDk5uuITTYSm2IiOtHEZ5v81FWKV2z0o3VACRGtiukQYmuHj6f9on/10Q9ZWUoIIS4zipMsFosyd+5cxcfHR9FqtYpWq1V8fX2Vl156SbFYLM5WZ+f06dNK06ZNlXfeeUfJyclRDAaDsnr1ajX9yJEjCqDs3LlTURRFWbdunaLVapWTJ0+qeT766CPFx8dHKS4urvF5c3NzFUDJzc29oPZfTFFRigKKEvXxQcWy5W/ljhsyFVuoYPsx6C12/9brLIpWa1X/HdLCrCR+vVdRfvtbUX77W0n8eq8S3Nyspmu1VkWvs1RZ5x03ZCqWLX+rdXw552iV5zy/To3Gqnz1wlG1fH31Y3CPHNvvMqq+31UhhBAXoqbf306P7z/33HMsXLiQV199lT179rBnzx7mzZvHe++9x/PPP+9UXU899RS///47CQkJ7Nixg9GjR6PT6bj77rvx9fXl/vvv54knnuDXX38lKiqKyZMn07dvX/r06QPAkCFD6Ny5M/feey///PMPGzZsYPbs2UyfPh2jsXbzRRoDrRZWzIzn1uuy1WOlZfZvZZlFi9WqQadVCGhayi9vRhPqf3bhvVB/2zH/pqXotApWq4Yyi30d59Y58rpsPpsVj/acLHfemM2SZ+LRaBQ0GkU9Z7nyOsvTlzyTwB03nG1zffXj5ftSHP9ihRBCuCSng53ly5ezePFiHnroIbp27UrXrl2ZNm0an3zyCZ9++qlTdSUnJ3P33XcTERHBHXfcgZ+fH3/++SctWrQA4K233uLmm29m7NixXH/99QQGBvLf//5XLa/T6fjxxx/R6XT07duX8ePHM2HCBF566SVnu9XoGN0UVs89xm0DstBoHN+X0eusBDQrZfvCI3QIrbh6cEQrMzsWHiGgWandLubn0mgUbh+YxTdzjzncLuK+4ZmsmBmv5nVUHmxBzeRhmQ2iHwbZEU4IIS4rTu+NZTKZ2LdvHx06dLA7Hh0dTbdu3Sgqqnwzx4aqse6NBVBWBl0mX0F0kuPNOP9ZcpCu7ap+T/bFuXPV/Vc4TOvYqoj9Sw+iryZAmL24JfNWBqEo9pN6NBqF58an8vL9J6osfyn7sTvGQ/bGEkIIF1DT72+nR3auuuoqFi5cWOH4woULueqqq5ytTlwgvR4yciuPRPIKdNXWkVtFnoxcfbWBDkBeoQ69rmLcrNcp5BVW34aG0g8hhBCux+mP/9dee40RI0awefNmdY2dnTt3kpSUxLp16+q8gaJqp3L0ZObZHrPWahU0gMWqQXtm/sqBeHf6dc2vso4D8e5q+fL5MQq2OTcZuQYycvQ0b1L1fmP74jwoLdOi11mxnJm3o9MqlJZp2RfneLSmIfZDCCGE63F6ZGfAgAHExMQwevRocnJyyMnJYcyYMURHR6t7ZolL5+CZL3h3o4XnxqeSsWYvX78YR5tA29yW8gCgKuV5wgLNfP1iHBlr9jJrXCruRttWCwcTTNXWsf9MHSP65LJ/6UH2Lz3IiD65trRj1behofRDCCGE63FqZKe0tJShQ4fy4Ycf8sorr1ysNgknHE0x8thtJ5k5LhX/prZRi9sHZjO6XzbLNzTn93+8qq0jr0DHkmfimTAkU73V8/L9J3h4TDrzPg/iaIqJAd0qH1VJz9ZzdftC5k1JoVenAvX496/E8dchT2YtDiY9W6+2r6H2QwghhGtyeoJyixYt2LFjB+Hh4RerTZdcY56gbLGArorpLNWl10Udje0cMkFZCCFcw0WboDx+/HiWLFlyQY0Tdae6AKC69Lqow1XOIYQQwjU5PUG5rKyMpUuXsnnzZrp3746np6dd+ptvvllnjRNCCCGEuFBOBzsHDhzgmjNj/zExMXZpmvM3ThJCCCGEqGdOBzu//vrrxWiHqKH3v2vBkhnHa13+hx2+aICbr82tVXlFgdlLgnn8tpO1fow7I0fPW6sDeOWB2m/bcKH9EEIIcflwes6OqF9Lf27Btn3VP5nkiKLArbPCuWVWeK13/t6234t5nwfRZ1rH2lUA9J7WkXmfB9VrP4QQQlw+ajSyM2bMGD799FN8fHwYM2ZMlXnP3btKXByLf2pe7QJ7jvy001d9ve5PX0b0dX5UZPFPzQFIyzKQX6jFy8PxXlSVyS/UkpZlUOuqr34IIYS4fNRoZMfX11edj+Pr61vlj7j4PtvkR1yKc7u6KwrMWdYSnVZBp1WYs6yl06MiR5ONfL7JD4BCs5ZFa1s4VwHwwRp/isy2y66++pF00uBcASGEEI2a0+vsuKLGtM4O2HYB9/W0cFX7IiJCiwkPMdMhpJhhvXPRnglf/znqzt9HPIlJNhGbbORAvDtHU+xXEA4PKeaKNkVq+Z4dC7iqvW2zTasVfv7LVy0fnWTin6Pu5BboKLPYTmLQW7mqXRGdWtvqCA8u5sZrTquLAqZn69my25vYFFsdh4+780+cO6Vl2nrtR1S0O7kFBllnRwghGrmafn/XamvEsrIyfvvtN+Li4rjnnnvw9vbmxIkT+Pj44OVVu3kYoubKLFoy87Rs2W1gy24fNBqFj548rgYIAG4GheeXtiQtyw2NRqmwGzlAbLKJoylGFEVDYLMSfn3r7NN1Wi2kZBh44v3QSttRWqZlV7QnUTEeKIqGW67NYXT/HDXd19PCql/8+GFHE4dtaCj9EEII4dqcnqB8/PhxrrzySkaOHMn06dM5deoUAAsWLOCpp56q8waKymk0ChqNwtJnEphyc4ZdWqfWxWx9N5rAZiXotJUP3um0CoHNStj6bjQdWxfbpU29JYOlM+LV81RldP9sVs+Nw+h2Np/RTWH13DhG989uNP0QQgjhepwOdh599FF69OhBdnY27u5nN2ccPXo0v/zyS502TlTvs1nxTBqW6TAtPMTM9oVHCGha5jBQ0GkVApqWseP9I4SHmB3WMXlYJp/Niq/0/BqNwh0Ds/nqhWO4GSqew82g8NULx7h9YHaVgUZ990MIIYTrcjrY+eOPP5g9ezZubm52x9u0aUNKSu3XTRHO69q2iHGDs6rM07ZlCQ+PSXeYpgCPjE0nLKikyjrGDc7iyrZFjutQNMyfmoxBX3kgY9ArzJ+S7PAWFDSMfgghhHBdTgc7VqsVi8VS4XhycjLe3t510ihROe05oyPRSSasNXjy+9BxkzqqUv4UU3ldhxJMVRUFbJN8oxPP5jt/dOVQgvv5RSq24bw859ZRX/0QQghxeXA62BkyZAhvv/22+m+NRkN+fj4vvPACw4cPr8u2CQd6d7atS6PRKBSXaElIc6umBOw96qE+QRXRqpiIVrY5LWUWLXuPelRbPj7ViLlUqwYaQ3rm4eVuQXsm2DgQX32wU55Hq1Xw9rAwuEdevfXDNhYkhBDicuF0sPPGG2+wfft2OnfuTHFxMffcc496C2vBggUXo43iHAsfTWLPJwcZ2ssWLBysZlTFYoGYJBOtA8ysnH2M/UsPsn/pQVbOPkbrADMxyUYcDNTZOXhm1GRorzz2Lj7IugWxJH69j2fuSsNosNY42DG5WZlxdxrHv9rHz6/F1ls/ru3i/EKGQgghGq9arbNTVlbGl19+yb59+8jPz+eaa65h3LhxdhOWG5PGtM5O1MeHuKZDIQDb9nlRUKwl8kzA4Eh6tp7v/mjCfcMzK8yrKS3TsHSdH6P756hr4ziy4X8+eLlbue7KikFCaqaB7/5owrRRp6ps/wfft2BM/2wC/Sqe51L3w91opfvUzrLOjhBCNHI1/f6WRQVpvMGOqJ3dMR4S7AghhAu4aIsKrl271uFxjUaDyWSiffv2hIWFOVutEEIIIcRF4XSwM2rUKDQaDecPCJUf02g09OvXj++//56mTZvWWUOFEEIIIWrD6QnKmzZtomfPnmzatInc3Fxyc3PZtGkTvXv35scff2Tr1q1kZmbKaspCCCGEaBBqtYLym2++yU033YS3tzfe3t7cdNNN/Oc//+Hpp5/muuuu4+2332bTpk0Xo72iCtmndWgG9mDV5ma1rmPV5mZoBvYg+7Su1nX0mNqJng92qnX5htIPIYQQrsHpYCcuLs7hJCAfHx+OHTsGQHh4OBkZGRXyiIvrlyjb+zLzk+Ba1zHjoxAAtuyu3QKRpwu1RMV4sivak/xCpy8voGH0QwghhOtw+tuoe/fuPP300+oGoACnTp3imWeeoWfPngDExsYSGiq7TF9KigLzVgYCkJTuxtFko9N1xCYbSckwADBvZRC1eU5v0Rr/s6/XtnC6fEPphxBCCNfhdLCzZMkS4uPjCQkJoX379rRv356QkBASEhJYvHgxAPn5+cyePbvOGyscyzmtY/l6P/bEegK2rRRmLwkmOd1Qo20YrFZITjcwe0mwugXD7hhPlq/3I6eGt4HMJRoOxpt4dVWgeuzVVUEcjDdhLnG8J1ZD7IcQQgjXU6t1dqxWKxs3biQmJgaAiIgIBg8ejFZbu9sW9a2xrbPTrX0hMz8J5re93sQkmcjJtz1Up9MqWKz2gYXRYCUsyEyXsCLemp5EiH8pAEnpBh5fGMrBBPdztlE469y6mniV0SG0mIHdTjN/Sgrlb/N3fzRh0ZoWHEpwJzXLgNWqQaNR1A0/y19rtQot/Urp1LqIh0aeYnT/HMAWnNRHPzq2KmLFhhayzo4QQjRyNf3+rlV0otVqGTp0KI888giPPPIIkZGRjTbQaYy0Wpg8NJOENKMaIAAVAgQAc6mW6CQTQ3vlqQECQKh/KUN75RGdZKoQIJxfV06+noQ0I/cNy+Dct3l471xMbgopGW5Yz+Q/d2fz8tdWq4bkU264G60M751b7/0YeV1OhXxCCCFcl9Pr7AAUFBTw+++/k5iYSElJiV3aI488UicNE1Xr2LqY7e8d4fpHIziVo1c3yDxX+cady2fGc++QrArpD9ycgZtBYdKrbQD7QKWcXmelRZMytr4TTfsQs12a0U1h9dw47n65Ld/90cRh+fJ2jOmfzRdz4its9VAf/cgrlFtaQghxOXE62NmzZw/Dhw+nsLCQgoICmjVrRkZGBh4eHvj7+0uwcwm1DzGzfeERev1fJzJyKwYJiqJhxaxjDgOEchMiM9FoFCbMa+swvam3hR0Lj9AmqMRhuptB4as5cdwxtx3f/eF4EclR/XL4cs4x9JVcbZe6H7tjqt8hXQghhOtw+t7T448/zi233EJ2djbu7u78+eefHD9+nO7du/P6669fjDaKKoQFleDlXvns3avaFVVbR9e2lefxcrdWGuiU0+uhc+siDPqK7TDorVzRpqjSQKdcQ+iHEEII1+R0sLN3716efPJJtFotOp0Os9lMaGgor732GrNmzboYbRRVKDJrSEx3A0B75gkkve5s0HAgvvqd6M/NU162/Gmm4yfdKDZX/zTVgXh3yiwatR3lbSmzaGrUhobSDyGEEK7H6WDHYDCok5H9/f1JTEwEwNfXl6SkpLptnajWkUSTOjm4fbCZpTPi7SbgOhskjOqXw9IZ8bQLts3PsVo1HEk0VVvHnqMeKIoGD5OFFyae4IWJJ/AwWVAUDXtiq79t1FD6IYQQwvU4PWfn6quv5u+//yY8PJwBAwYwZ84cMjIy+Oyzz+jSpcvFaKOowoF4d9oEmpk7+QTjBmWi08HkYZlERacxa3FwjYOEyJ65vPJACt0jCgGYMCSTlZv9eGFZSw7Eu9MtvPJbRAVFWjJy9Tx1ZxrP3pOKn68FgGkjT7Hgi0A+WNOCwmItHqbKb1M1hH4IIYRwTU6vs7Nr1y5Onz7NDTfcQHp6OhMmTGDHjh2Eh4ezdOlSrrrqqovV1oumsa2zc02HQvX40WQjrQJKcDM4fhsPJZjo3Ka4yrqrymMusT02Xj5C4khuvo78Ii3BLUodpqecMuDlbsXXy1JpHZeyH7tjPOg+tbOssyOEEI1cTb+/nR7Z6dGjh/ra39+f9evX166Fok6c/zj4+aoLEKrLY3RTqgx0AHy9LFUGMpUFQedqCP0QQgjhmpyes1NUVERh4dmRhePHj/P222+zcePGOm2YEEIIIURdcDrYGTlyJCtWrAAgJyeHXr168cYbbzBy5EgWLVpU5w0UQgghhLgQTgc7u3fvpn///gCsXr2awMBAjh8/zooVK3j33XfrvIHC3unCC9uWo9isueBHsHPzdRe0k7ii2Oq4EHXRDyGEEJcHp785CwsL8fb2BmDjxo2MGTMGrVZLnz59OH78eJ03UNgb+FhHjp1wq3V598juuEd2r3X5uBQjTW6+mntfCat1HeNfCaPJzVfXaz+EEEJcPpwOdtq3b8/3339PUlISGzZsYMiQIQCkp6c32CeZXM3q35vVqlxMklF9HZtsrCJnVee2bQmxKcqnVqM7igKbdvmcqav++iGEEOLy4XSwM2fOHJ566inatGlD79696du3L2Ab5bn66qtr3ZBXX30VjUbDY489ph4rLi5m+vTp+Pn54eXlxdixYzl58qRducTEREaMGKHuzfX0009TVlZW63Y0Bq+uCqSgyPnbWfM+D0KnVdBpFeZ9HuR0+YIiLQu+CAQgPdvAz3/5Ol3Huj99OZVjAOqvH0Vy+0sIIS4rTj96ftttt9GvXz9SU1Pt1tS56aabGD16dK0a8ffff/PRRx/RtWtXu+OPP/44P/30E9988w2+vr7861//YsyYMWzfvh0Ai8XCiBEjCAwMZMeOHaSmpjJhwgQMBgPz5s2rVVsag5x8HZNebcOQnnmEB5sJDymmZfNSNOd9h+fm64hNNhKbYiI60cRnm/zUVYpXbPSjdUAJEa2K6RBSTHhIMT6e9ov+KQqcyDAQm2wiNsXIxr99yDkz10anVXj8/VCik0yEB9vKhwVVXCenpFRDfKrbmTpMfLi2BTqtgsWqqbd+fLXF8YalQgghXJRygXJzc5XvvvtOOXToUK3Knz59WgkPD1c2bdqkDBgwQHn00UcVRVGUnJwcxWAwKN98842a9/Dhwwqg7Ny5U1EURVm3bp2i1WqVtLQ0Nc+iRYsUHx8fxWw2O9UHQMnNza1VHy6FqChFsX1t234Meovdv++4IVOxbPlbUX6z/Xw556hdul5nUbRaq/pvrdaq6HVn69BorMpXLxxVy1u2/K3ccUNmlec8v86QFmYl8eu9ah2JX+9VgpubKz1nffWjPH9UVH2/q0IIIS5ETb+/nb6HcMcdd7Bw4ULAtuZOjx49uOOOO+jatSvffvut08HW9OnTGTFiBIMGDbI7HhUVRWlpqd3xjh070qpVK3bu3AnAzp07ufLKKwkICFDzREZGkpeXx8GDBys9p9lsJi8vz+6nsSktO/vWjbwum89mxaM9592888ZsljwTj0ajoNEolFm06mgI2PaKKrNo1fQlzyRwxw3ZarpWCytmxnPrdWePnXtOQK1Tp1UIaFrKL29GE+p/dgHBUH/bMf+mpei0inrO+u7H+W0QQgjh2pz+1N+6dav66Pl3332Hoijk5OTw7rvv8u9//9upur788kt2797N/PnzK6SlpaXh5uZGkyZN7I4HBASQlpam5jk30ClPL0+rzPz58/H19VV/QkNDnWp3Q6HRKNw+MItv5h5zuM3CfcMzWTEzXs3rqDzYgoHJwzIrpBvdFFbPPcZtA7Iclgfb7uIBzUrZvvAIHUIrrlAc0crMjoVHCGhWareLeUPrhxBCCNfldLCTm5tLs2a2p2jWr1/P2LFj8fDwYMSIEcTGxta4nqSkJB599FFWrlyJyXRpd6OeOXMmubm56k9j3a09IrSYVbOPYdBX/gU+fkgWs8alVpr+3PhUxg/JqjTdoFf44vljdAhxvBVDmUXLzwtiq9yKoV2wmZ8XxFY6otIQ+iGEEMJ1OR3shIaGsnPnTgoKCli/fr366Hl2drZTQUtUVBTp6elcc8016PV69Ho9v//+O++++y56vZ6AgABKSkrIycmxK3fy5EkCA21PBAUGBlZ4Oqv83+V5HDEajfj4+Nj9NEYZuXr0NZhinleoQ6+rGEjodQp5hdUv7qfX285Vaf0F1deRW0WehtIPIYQQrsnpYOexxx5j3LhxhISE0LJlSwYOHAjYbm9deeWVNa7npptuYv/+/ezdu1f96dGjB+PGjVNfGwwGfvnlF7VMdHQ0iYmJ6uPuffv2Zf/+/aSnp6t5Nm3ahI+PD507d3a2a42CVqOg1dq+8DNyDWTkVP/lvS/Og9IyLXqdVZ3botdZKS3Tsi/Ovdryp3L0ZObZHhfXnnnku/w1wIH46usoz1NeRqet334IIYS4fDgd7EybNo0///yTpUuXsm3bNrRnZpO2bdvWqTk73t7edOnSxe7H09MTPz8/unTpgq+vL/fffz9PPPEEv/76K1FRUUyePJm+ffvSp08fAIYMGULnzp259957+eeff9iwYQOzZ89m+vTpGI2uudjcljejmTUuFXejbZfxgwnVj6btPxNojOiTy/6lB9m/9CAj+uTa0o5VHyQcPFPe3WjhufGpZKzZy9cvxtEm0HbryplgJyzQzNcvxpGxZm+99cNoqHyHdiGEEK6nVmP63bt3p3t3+6X6R4wYUScNOtdbb72FVqtl7NixmM1mIiMj+eCDD9R0nU7Hjz/+yEMPPUTfvn3x9PRk4sSJvPTSS3XelobC29PKy/ef4OEx6cz7PIijKSYGdMuvNH96tp6r2xcyb0oKvToVqMe/fyWOvw55MmtxMOnZevybVr4Q49EUI4/ddpKZ41LVfLcPzGZ0v2yWb2jO7/94VdvuvAIdS56JZ8KQTPWWVX31Y0SfHAY/FVFtm4UQQrgGjaI4v+h/cnIya9euJTExkZKSEru0N998s84ad6nk5eXh6+tLbm5ug52/s3s3dO8OUR8f4poOhepxiwV0VUxXqS69LupobOfYHeNB96mdiYqCa66puk4hhBANV02/v50e2fnll1+49dZbadu2LUeOHKFLly4kJCSgKArXyDfHJVddAFBdel3U4SrnEEII4ZqcnrMzc+ZMnnrqKfbv34/JZOLbb78lKSmJAQMGcPvtt1+MNgohhBBC1JrTwc7hw4eZMGECAHq9nqKiIry8vHjppZdYsGBBnTdQCCGEEOJCOB3seHp6qvN0goKCiIuLU9MyMjLqrmXCaYoCzy0OrtFj3JXJyNHz3OLgC2rHDzt8+XGH8zuil2so/RBCCOEanP426dOnD9u2baNTp04MHz6cJ598kv379/Pf//5XfSRc1I9t+72Y93kQX21pytFVB2pVR+9pHTl2wsSwXrn061r501GVURS4dVY4ANZfd1XYwbwmGkI/hBBCuA6nR3befPNNevfuDcDcuXO56aab+Oqrr2jTpg1Lliyp8waKmlv8U3MA0rIM5Bc6v9llfqGWtCyDXV3O+mnn2RGddX/WbnSnIfRDCCGE63D6m6Rt27Z07doVsN3S+vDDD9m3bx/ffvstrVu3rvMGipo5mmzk801+ABSatSxa28LpOj5Y40+R2XZJfLbJj7gU5xZmVBSYs6wlujOrLM9Z1hJnFzZoCP0QQgjhWmo9KWLXrl0cPnwYgM6dO1dYZFBcPFYr/PyXLzHJJmKTjUQnmfjnqDtajYIVDYqi4bnFwXz9azM6tS4iPMRMeHAxN15zWl10Lz1bz5bd3sSm2Oo4fNydf+LcURTbfSetRqH3Qx25qn0REaHFhIeY6RBSzLDeuZxZNJt/jrrz9xFPtR0H4t05mnJ2JeTdMZ5E3NuFK9oUqeV7dizgqvZF9doPrex8LoQQlxWng53k5GTuvvtutm/fTpMmTQDIycnh2muv5csvvyQkJKSu2yjOo9VCSoaBJ94PrTRPaZmWXdGeRMV4oCgabrk2h9H9c9R0X08Lq37x44cdTdBoFDU4KFdm0ZKZp2XLbgNbdvug0Sh89ORxNdABcDMoPL+0JWlZbg7rAIhNNnE0xYiiaAhsVsKvb8XUez9mja9893QhhBCux+nbWA888AClpaUcPnyYrKwssrKyOHz4MFarlQceeOBitFE4MPWWDJbOiFc3xKzK6P7ZrJ4bh9HtbD6jm8LquXGM7p9dZdny+pc+k8CUm+2ftuvUupit70YT2KxE3RzUEZ1WIbBZCVvfjaZj6+J678eYc4IlIYQQrs/pYOf3339n0aJFRESc3VsoIiKC9957j61bt9Zp40TVJg/L5LNZ8ZWmazQKdwzM5qsXjuFmqBhIuBkUvnrhGLcPzK4y0PhsVjyThmU6TAsPMbN94RECmpY5DHh0WoWApmXseP8I4SHmBtsPIYQQrsvpYCc0NJTS0tIKxy0WCy1btqyTRomaGzc4iyvbFjlMUxQN86cmY9BXHgAY9ArzpyQ7vAUF0LVtEeMGZ1XZhrYtS3h4TLrjNgCPjE0nLKjEYXq5htAPIYQQrsnpYOc///kPDz/8MLt27VKP7dq1i0cffZTXX3+9Thsnqme1QnTi2UnB54+uHEpwr7aO8/OcW0d0kgmrtfp2HDpuUkdVyp/GAtsE4UMJpqqKAg2nH0IIIVyP08HOpEmT2Lt3L71798ZoNGI0Gunduze7d+/mvvvuo1mzZuqPuPjiU42YS7VqoDGkZx5e7ha0Z77oD8RXHySU59FqFbw9LAzukQfYbh8Vl2hJSHOrto69Rz0os9gup4hWxUS0ss3NKbNo2XvUo9H0QwghhOtx+mmst99++yI0Q9TWwTOjJkN75TF/SjJXtS8i+7SO174I5K1vAmocJJjcrDx++0meviuNpt4W9sa6M2txCD//5cvBBHfatqz8NpTFAjFJJloHmJk3JYW7brTdLvpySzNmfRJMTLIRi6XqXccbQj+EEEK4Jo2iOLvsm+vJy8vD19eX3NxcfHx86rs5Du3eDd27Q9THh7imQ6F6fMP/fPByt3LdlRW3REjNNPDdH02YNupUlXV/8H0LxvTPJtCvrELatn1eFBRrieyVV2n59Gw93/3RhPuGZ1aYV1NapmHpOj9G989R18Zx5FL2Y3eMB92ndiYqCq65psoqhRBCNGA1/f6WYIfGHewI50mwI4QQrqGm39/ObzwkhBBCCNGISLAjhBBCCJcmwY4QQgghXFqtg52jR4+yYcMGiopsC8HJ1J9Lo/vUzmSfruKxpmr0mNqJng92qnX57NM6NAN7sGpz7ZcWWLW5GZqBPeq1H0IIIS4fTgc7mZmZDBo0iA4dOjB8+HBSU22bKt5///08+eSTdd5AUdGW3d61Kne6UEtUjCe7oj3JL6xdnPtLlG0C2MxPgmtVHmDGR7bNYuuzH0IIIS4fTn9TPP744+j1ehITE/HwOLtY3J133sn69evrtHHCsXkrg6jNQNqiNf5nX69t4XR5RYF5KwMBSEp342iy0ek6YpONpGQYgPrthxBCiMuH08HOxo0bWbBgASEhIXbHw8PDOX78eJ01TFRud4wny9f7kVPD20DmEg0H4028uipQPfbqqiAOxpswlzjeS+p8Oad1LF/vx55YT8C2FcPsJcEkpxtqtA2D1QrJ6QZmLwlWt3Gor378sMO3RnmFEEK4BqfX2fH29mb37t2Eh4fj7e3NP//8Q9u2bdm1axeRkZFkZja+XaUb0zo7YAs0LFbbl3sTrzI6hBYzsNtp5k9JQXsmfP3ujyYsWtOCQwnupGYZsFo1aDSKulFm+WutVqGlXymdWhfx0MhTjO6fA9iCk5mfBPPbXm9ikkzk5OsrnLuc0WAlLMhMl7Ai3pqeRIi/baPYpHQDjy8M5WCCu7odxLnqsx+ArLMjhBCN3EVbZ6d///6sWLFC/bdGo8FqtfLaa69xww031K61winnBhs5+XoS0ozcNyxDDRAAhvfOxeSmkJLhhvVM/nN3BC9/bbVqSD7lhrvRyvDeuWq6VguTh2aSkGa0CxDOD3QAzKVaopNMDO2VpwY6AKH+pQztlUd0kqlCoFPf/RBCCHH5cDrYee211/j4448ZNmwYJSUlPPPMM3Tp0oWtW7eyYMGCi9FGUQm9zkqQXwnb3ztCRCuzXZrRTWH13DjGXJ+tbq7piEajMPb6LFbPPYbRzT5fx9bFbH/vCEF+Jeh1ju9VaTQKGo3C8pnx3D8io0L6Azdn8OmzCWq+htoPIYQQrsvpYKdLly7ExMTQr18/Ro4cSUFBAWPGjGHPnj20a9fuYrRRVKKpt4UdC4/QPsTsMN3NoPDVnDhG9cuptI5R/XL4cs6xCntalWsfYmb7wiM08bI4TFcUDctnxnPvkKxKzzEhMpPlM+PtRmQaWj+EEEK4rlqN6/v6+vLcc8/VdVuEk7zcrbQJqnoXb70eOrcu4sedvpSW2ce2Br2VK9oUoa/mKggLKsHL3UpGruP0q9oVVdvWrm0rz9NQ+iGEEMI11SjY2bdvX40r7Nq1a60bI2qmfGLv8ZNuFJs1mIxVzzE/EO9OmcU2qqI98ySU1aqhzKLhQLx7tecrMmtITHdTy1utGvQ6K2UWrVp/12oCnnPPU162PvshhBDi8lGjYKdbt25oNBoURUGjOXdyqO0L59xjFovcJriYXpiYwhdb/IhJMmG1ajiSaKJbeNWBxp6jHiiKBg+ThRl3pwGw4ItACot17In1qLIswJFEkzo5uH2wmWfvSeWnnb58u9W2inJNAo1z84zql8PwPrm8uiqo3vohhBDi8lGjYCc+Pl59vWfPHp566imefvpp+vbtC8DOnTt54403eO211y5OK4Xq1utyeX5CKis3+/HCspYciHevMkgoKNKSkavnqTvTePaeVPx8bcHotJGnWPBFIB+saUFhsRYPU+UTdw/Eu9Mm0MzcyScYNygTnQ4mD8skKjqNWYuDaxzsRPbM5ZUHUugeUQjAhCGZ9dKPycMyeGFZ7VeAFkII0bg4vc5Or169ePHFFxk+fLjd8XXr1vH8888TFRVVpw28FBrTOjtRHx/img62YMFcYnvcul2w44m9ALn5OvKLtAS3KHWYnnLKgJe7Fd8qJu4eTTbSKqAEN4PjS+VQgonObYqrbH9VeS51Pw7Eu9N9amdZZ0cIIRq5mn5/Oz1Bef/+/YSFhVU4HhYWxqFDh5ytTlwAo5tSZYAA4OtlqTIAqCx4OFdlT0mVqy7QqS5PQ+mHEEII1+T0o+edOnVi/vz5lJScfXqmpKSE+fPn06mT7EIthBBCiIbF6ZGdDz/8kFtuuYWQkBD1yat9+/ah0Wj44Ycf6ryBQgghhBAXwulgp1evXhw7doyVK1dy5MgRwLbj+T333IOnp2edN1A4Jzdfh4+nBU0tHzpSFMgr0FV5y6g6xWbbyat7lLwqDaEfQgghXEOtFhX09PRk6tSpdd0WcYHiUoy0H3cl4wZl8vns+OoLODD+lTBWbfYjbtU+2raseqG/yrhH2nYsVX7bVavyDaUfQgghXIPTc3ZEw7X696YAbIrywbln7GwUBTbt8jlTV7NatSEmyai+jk02VpGzcg2hH0IIIVyHBDsuoqBIy4IvAgFIzzbw81++Ttex7k9fTuUYAHh1VSAFRc5fHvM+D0KnVdBpFeZ9HuR0+YbSDyGEEK6jVrexRP1TFDiRYSA22URsipGNf/uQk68DbNtJPP5+KNFJJsKDiwkPKSYsqOI6OSWlGuJT3c7UYeLDtS3ULRxy8nVMerUNQ3rmER5sJjykmJbNSyvMocnN1xGbbCQ2xUR0oonPNvmpqxSv2OhH64ASIloV0yHE1g4fT/tF/+qjH7UZLRJCCNF4Ob2ooCtqbIsKdmtfyN0vt+XrX8/eojHorXYbZOp1VqyKRg08QlqUsOP9w4T629ajSUo30HdaJ1Iyzu55pdUo6n5Xjuq844Ysvnj+GNozh77a0pS7Xjq70/355zy/To1G4cs5x7jjhmwArFbqpR+De+SyaZevLCoohBCNXE2/v2s1vp+Tk8PixYuZOXMmWVlZAOzevZuUlJTatVY4RauFFTPjufW6bPXY+TuBl1m0WK0adFqFgKal/PJmtBogAIT62475Ny1Fd2Zzz3MDhPPrHHldNp/NilcDHYA7b8xmyTPxaDQKmjMBxrl7T5XXWZ6+5JkENdCpz368fJ9cp0IIcTlxOtjZt28fHTp0YMGCBbz++uvk5OQA8N///peZM2c6VdeiRYvo2rUrPj4++Pj40LdvX37++Wc1vbi4mOnTp+Pn54eXlxdjx47l5MmTdnUkJiYyYsQIPDw88Pf35+mnn6asrMzZbjU6RjeF1XOPcduALDQax4Nzep2VgGalbF94hA6hFVcPjmhlZsfCIwQ0K0Wvc7ynlEajcPvALL6Ze8zhdhH3Dc9kxcx4Na+j8mALaiYPy2wQ/TDIzVshhLisOB3sPPHEE0yaNInY2FhMJpN6fPjw4WzdutWpukJCQnj11VeJiopi165d3HjjjYwcOZKDBw8C8Pjjj/PDDz/wzTff8Pvvv3PixAnGjBmjlrdYLIwYMYKSkhJ27NjB8uXL+fTTT5kzZ46z3WqUDHqFL54/RocQx1sxlFm0/LwgtsqtGNoFm/l5QWyF0ZByEaHFrJp9DIO+8rud44dkMWtcaqXpz41PZfyQrErTG0o/hBBCuCan/8b9+++/+eijjyocDw4OJi0tzam6brnlFrt/v/LKKyxatIg///yTkJAQlixZwqpVq7jxxhsBWLZsGZ06deLPP/+kT58+bNy4kUOHDrF582YCAgLo1q0bL7/8MjNmzODFF1/Ezc3N2e41Ono9ZORW/jbmFeiqrSO3ijwZuXr0NbhK8gp16HUKpWX2M5j1OoW8wurb0FD6IYQQwvU4PbJjNBrJy8urcDwmJoYWLVrUuiEWi4Uvv/ySgoIC+vbtS1RUFKWlpQwaNEjN07FjR1q1asXOnTsB2LlzJ1deeSUBAQFqnsjISPLy8tTRIVd3KkdPZp7tMWvtmUe+y18DHIh3r7aO8jzlZXRaRX2dkWsgI6f6KGFfnAelZVr0Oqs6R0evs00M3hdXfRsaSj+EEEK4HqeDnVtvvZWXXnqJ0lLbJFGNRkNiYiIzZsxg7NixTjdg//79eHl5YTQa+b//+z++++47OnfuTFpaGm5ubjRp0sQuf0BAgDqClJaWZhfolKeXp1XGbDaTl5dn99NYHTzzBe9utPDc+FQy1uzl6xfjaBNou+XjTJAQFmjm6xfjyFizl1njUnE32rZaOJhgqqo4APvP1DGiTy77lx5k/9KDjOiTa0s7Vn0bGko/hBBCuB6n/9R94403uO222/D396eoqIgBAwaQlpZG3759eeWVV5xuQEREBHv37iU3N5fVq1czceJEfv/9d6frccb8+fOZO3fuRT3HpXI0xchjt51k5rhU/JvaJmbfPjCb0f2yWb6hOb//41VtHXkFOpY8E8+EIZnqrZ6X7z/Bw2PSmfd5EEdTTAzoll9p+fRsPVe3L2TelBR6dSpQj3//Shx/HfJk1uJg0rP1avsaaj+EEEK4plqvs7Nt2zb27dtHfn4+11xzjd3tpgsxaNAg2rVrx5133slNN91Edna23ehO69ateeyxx3j88ceZM2cOa9euZe/evWp6fHw8bdu2Zffu3Vx99dUOz2E2mzGbz052zcvLIzQ0tNGss3NNh0L1uMUCuiqms1SXXhd1NLZz7I7xoPvUzrLOjhBCNHI1XWen1pMY+vXrR79+/WpbvFJWqxWz2Uz37t0xGAz88ssv6u2x6OhoEhMT6du3L4A6mpSeno6/vz8AmzZtwsfHh86dO1d6DqPRiNFYu32bGprqAoDq0uuiDlc5hxBCCNdUo2Dn3XffrXGFjzzySI3zzpw5k2HDhtGqVStOnz7NqlWr+O2339iwYQO+vr7cf//9PPHEEzRr1gwfHx8efvhh+vbtS58+fQAYMmQInTt35t577+W1114jLS2N2bNnM336dJcJZoQQQghxYWoU7Lz11lt2/z516hSFhYXq7aWcnBx1UT9ngp309HQmTJhAamoqvr6+dO3alQ0bNjB48GD1vFqtlrFjx2I2m4mMjOSDDz5Qy+t0On788Uceeugh+vbti6enJxMnTuSll16qcRuEEEII4dqcnrOzatUqPvjgA5YsWUJERARgu700ZcoUHnzwQcaNG3dRGnoxNaa9se4bdoolM47Xup4fdviiAW6+NrdW5RUFZi8J5vHbTtK8Se1Wqs7I0fPW6gBeeaD22zZcSD9kzo4QQriGmn5/Ox3stGvXjtWrV1eY/BsVFcVtt91GfHx87VpcjxpTsAPwx7tH6NfV+aeKFAW0N/QAwPrrrgo7mNfEH/u8uP6RjrRrWczRVQecrwBod08Xjp0w1Vs/JNgRQgjXcNE2Ak1NTXW495TFYqmwb5W4OBb/1LxW5X7a6au+XvenbxU5qz93WpaB/ELn95HNL9SSlmWwq8tZddEPIYQQlw+nv61uuukmHnzwQXbv3q0ei4qK4qGHHqqzx89F1T7b5EdcinMTsBUF5ixrie7M6sRzlrXE2UUHjiYb+XyTHwCFZi2L1jq/YvYHa/wpMtsuu/rqR9JJg3MFhBBCNGpO38Y6deoUEydOZP369RgMti+NsrIyIiMj+fTTT9VHwBuTxnYbS6+z4utp4ar2RUSEFhMeYqZDSDHDeueiPRO+/nPUnb+PeBKTbCI22ciBeHeOptivIBweUswVbYrU8j07FnBV+yIArFb4+S9ftXx0kol/jrqTW6BTN9s06K1c1a6ITq1tdYQHF3PjNafVRQHTs/Vs2e1NbIqtjsPH3fknzp3SMm299iMq2p3cAoPcxhJCiEbuoq2z06JFC9atW0dMTAxHjhwBbHtWdejQofatFU4ps2jJzNOyZbeBLbt90GgUPnryuBogALgZFJ5f2pK0LDc0GgVFqTixJTbZxNEUI4qiIbBZCb++FaOmabWQkmHgifdDK21HaZmWXdGeRMV4oCgabrk2h9H9c9R0X08Lq37x44cdTRy2oaH0QwghhGur9QrKrqSxjeyU02hsb93SZxKYNCyzQpnYZCPXPxJBRq5eHY05n15npblvGVvfjSY8xFwhfdnPftz/WhsAh4FGeTtG9cvhyznHcDPYX04lpRrueqkt329rUmX5+uiHjOwIIUTjdlFXUE5OTmbt2rUkJiZSUlJil/bmm2/WpkpRS5/Nimfc4CyHaeEhZrYvPML1j3QkLcuAxWofbOi0CgFNy/jjvSOEBZU4rGPysEzc9Ar3zgtzmK7RKNwxMJvPnovHoK8YN7sZFL564RjjXwnjm9+aVhrw1Hc/hBBCuC6nJyj/8ssvREREsGjRIt544w1+/fVXli1bxtKlS+32qBIXX9e2RZUGCOXatizh4THpDtMU4JGx6ZUGCOXGDc7iyrZFjutQNMyfmuww0Cln0CvMn5JcaaDTEPohhBDCdTkd7MycOZOnnnqK/fv3YzKZ+Pbbb0lKSmLAgAHcfvvtF6ON4hxazdmgIjrJhNVafZlDx03qraLyp5jK6zqUYKqqKGCb5BudeDZfeXm1/gT36ttwXp5z66ivfgghhLg8OB3sHD58mAkTJgCg1+spKirCy8uLl156iQULFtR5A4W93p1ti/BpNArFJVoS0tyqLbP3qIc61yWiVTERrYoB2wThvUc9qi0fn2rEXKpVA40hPfPwcregPRNsHIivPtgpz6PVKnh7WBjcI6/e+mEbCxJCCHG5cDrY8fT0VOfpBAUFERcXp6ZlZGTUXcuEQwsfTWLPJwcZ2ssWLBysZlTFYoGYJBOtA8ysnH2M/UsPsn/pQVbOPkbrADMxyUYslqrPefDMqMnQXnnsXXyQdQtiSfx6H8/clYbRYK1xsGNyszLj7jSOf7WPn1+Lrbd+XNvF+VWbhRBCNF5OT1Du06cP27Zto1OnTgwfPpwnn3yS/fv389///lfdjVxcXN3Ci1i3IJZt+7woKK46Xs3M0/P2vxK5b3im3byaewZlcfvAbJau8yMzT6+ujeOI0aCw7b0jXHfl2SChqbeF+VNTeGRsOt/90aTaNl/bJZ/XH0oi0O/seeqrH+5GK92ndq62zUIIIVyD04+eHzt2jPz8fLp27UpBQQFPPvkkO3bsIDw8nDfffJPWrVtfrLZeNI3p0fOojw9xTYfC+m5OoyZ7YwkhhGu4aI+et23bVn3t6enJhx9+WLsWCiGEEEJcAs7v5CiEEEII0YjUaGSnadOmaDSO10g5X1ZW1eulCCGEEEJcSjUa2Xn77bd56623eOutt5g9ezYAkZGRvPjii7z44otERkYC8Pzzz1+8lopqZZ/WoRnYg1Wbm9W6jlWbm6EZ2IPs07pa19Fjaid6Ptip1uUbSj+EEEK4hhqN7EycOFF9PXbsWF566SX+9a9/qcceeeQRFi5cyObNm3n88cfrvpWiRn6Jsk3OmvlJMPcMqt0I24yPQgDYstubsQNynC5/ulBLVIwnAPmFWrw8arBa4HkaQj+EEEK4Dqfn7GzYsIGhQ4dWOD506FA2b95cJ40SzlMUmLcyEICkdDeOJhudriM22UhKhgGAeSuDqM0WsYvW+J99vbaF0+UbSj+EEEK4DqeDHT8/P9asWVPh+Jo1a/Dz86uTRgnn5JzWsXy9H3tibSMqOq3C7CXBJKcbarQNg9UKyekGZi8JVrdg2B3jyfL1fuTU8DaQuUTDwXgTr64KVI+9uiqIg/EmzCU1m+/VEPohhBDC9Ti9zs6nn37KAw88wLBhw+jduzcAf/31F+vXr+eTTz5h0qRJF6OdF1VjW2enW/tCZn4SzG97vYlJMpGTb7sbqdMqFXYENxqshAWZ6RJWxFvTkwjxLwUgKd3A4wtDOZjgfs42CmedW1cTrzI6hBYzsNtp5k9JQXsm63d/NGHRmhYcSnAnNcuA1apBo1HUDT/LX2u1Ci39SunUuoiHRp5idP8cwBac1Ec/OrYqYsWGFrLOjhBCNHI1/f52emRn0qRJbN++HR8fH/773//y3//+Fx8fH7Zt29YoA53GSKuFyUMzSUgzqgECUCFAADCXaolOMjG0V54aIACE+pcytFce0UmmCgHC+XXl5OtJSDNy37AMNdABGN47F5ObQkqGG9Yz+c/d2bz8tdWqIfmUG+5GK8N759Z7P0Zel1MhnxBCCNfl9KKCAL1792blypV13RbhhI6ti9n+3hGufzSCUzl6dYPMc5Vv3Ll8Zjz3Dqk40feBmzNwMyhMerUNYB+olNPrrLRoUsbWd6JpH2K2SzO6KayeG8fdL7fluz+aOCxf3o4x/bP5Yk683VYP9dWPvEK5pSWEEJeTGo3s5OXl2b2u6kdcOu1DzGxfeIQmXo53wFQUTaUBQrkJkZksnxlfaaDS1NvCjoVHKgQ65dwMCl/NiWNUv5xKzzGqXw5fzjlWIdBpSP0QQgjhumq8qGBqair+/v40adLE4QKDiqKg0WiwVLf1tKhTYUEleLlbych1nH5Vu6Jq6+jatvI8Xu5W2gSVVFler4fOrYv4cacvpWX28bNBb+WKNkXoq7nSGkI/hBBCuKYaBTtbtmyhWTPbAm+//vrrRW2QcE6RWUNiuhsAWq2C1apBr7Oqt4MOxLvTtZpA4UC8u/q6vGz5xN7jJ90oNmswGauex34g3p0yi0ZtB9jm6pRZNHb1N/R+CCGEcD01CnYGDBigvg4LCyM0NLTC6I6iKCQlJdVt60S1jiSa1MnB7YPNPHtPKj/t9OXbrbbgtCaBxrl5RvXLYXifXF5dFURMkq3uI4kmuoVXHWjsOeqBomjwMFmYcXcaAAu+CKSwWMeeWI9G0w8hhBCux+kJymFhYeotrXNlZWURFhYmt7EusQPx7rQJNDN38gnGDcpEp4PJwzKJik5j1uLgGgcJkT1zeeWBFLpHFAIwYUgmKzf78cKylhyId68ySCgo0pKRq+epO9N49p5U/Hxt18C0kadY8EUgH6xpQWGxFg9T5YvlNIR+CCGEcE1Or7Oj1Wo5efIkLVrYr457/PhxOnfuTEFBQZ028FJobOvsXNOhUD1+NNlIq4AS3AyO38ZDCSY6tymusu6q8phLbI+NtwuufGJvbr6O/CItwS1KHaannDLg5W7Ft5IJyHBp+7E7xoPuUzvLOjtCCNHI1fT7u8YjO0888QQAGo2G559/Hg+Ps7cmLBYLf/31F926dat9i0WtVPd0UXUBQnV5jG5KlYEOgK+XpcpAprIg6FwNoR9CCCFcU42DnT179gC2uTn79+/Hzc1NTXNzc+Oqq67iqaeeqvsWCiGEEEJcgBoHO+VPYU2ePJl33nmnwd7uEUIIIYQ4l9PbRSxbtkwCnXp0utDpt8xOsVlDsblmG3NWJjdfd0E7iSuKrY4LURf9EEIIcXlw+puzoKCA559/nmuvvZb27dvTtm1bux9xcQ18rCPHTrhVn7ES7pHdcY/sXuvycSlGmtx8Nfe+ElbrOsa/EkaTm6+u134IIYS4fDj96PkDDzzA77//zr333ktQUJDD1ZTFxbX692Y8c2YtG2fEJBnV17HJRsJrsXXC6t+bArApygdFAWfffkWBTbt8ztRVf/0QQghx+XA62Pn555/56aefuO666y5Ge0QNvLoqkOmj0vF0r3zdGkfmfR6E7szqxvM+D2LZswlOlS8o0rLgi0AA0rMN/PyXL8P7VLK/QyXW/enLqRwDUH/9KJLbX0IIcVlxOthp2rSpunWEqB85+TomvdqGIT3zCA82Ex5STMvmpRVGWXLzdcQmG4lNMRGdaOKzTX7qKsUrNvrROqCEiFbFdAgpJjykGB9P+6BDUeBEhoHYZBOxKUY2/u1Dzpm5NjqtwuPvhxKdZCI82FY+LKjiOjklpRriU93O1GHiw7Ut1C0c6qsfX21peqFvgRBCiEbE6UUFP//8c9asWcPy5cvt1tppzBrTooLlDHqr3aabd9yQxRfPH0N75tBXW5py10vt1HS9zopV0ahBglaroNUo6t5TGo3Cl3OOcccN2QBYrXD3y235+tezge355zy/zpAWJex4/zCh/rZ1dZLSDfSd1omUDDeH56yvfpTvmyWLCgohRONW54sKlnvjjTeIi4sjICCANm3aYDAY7NJ3797tfGuF084NEEZel81ns+LVAAHgzhuzKSiO54H/tAGwCzDAtkmnFQ0ajS3WXfJMghogAGi1sGJmPMUlGtZub1rhnOfWqdMqNPct45c3o9VAByDUv5Rf3ozm+kc7kpmrx3LmnPXdj/PrEEII4dqcDnZGjRp1EZohakOjUbhtQDYrZ8dj0FccoLtveCZueoUJ88PQaBQURVOhPNiCgfFDsiqUN7oprJ57jHteDuPbrU0rlAfbKIl/0zK2vhPtcIXiiFZmdiw8wvWPRpCerXcYaDSEfgghhHBdTt/GckWN8TYWQMdWRexfehB9NSHr7MUtmbcyyGGQ8Nz4VF6+/0SV5cvKoMvkK4hOcrwZ5z9LDtK1XdUbbO6Lc+eq+69wmFZf/ZDbWEII0bjV9PtbxvMbsYxcfbUBAkBeoQ69rmJMq9cp5BVWv7ifXm87V6X1F1RfR24VeRpKP4QQQrgmp4Mdi8XC66+/Tq9evQgMDKRZs2Z2P+Li0moUtGceu87INZCRU/2X9744D0rLtOh1VjQaBY1GQa+zTQzeF+d4tOZcp3L0ZObZ5mZptYr62Hd5Ow7EV19HeZ7yMjpt/fZDCCHE5cPpYGfu3Lm8+eab3HnnneTm5vLEE08wZswYtFotL7744kVoojjXljejmTUuFXejbZfxgwmmasvsPxNojOiTy/6lB9m/9CAjzqyPs/9Y9UHCwTPl3Y0WnhufSsaavXz9YhxtAm1zdJwJdsICzXz9YhwZa/bWWz+Mhsp3aBdCCOF6nA52Vq5cySeffMKTTz6JXq/n7rvvZvHixcyZM4c///zTqbrmz59Pz5498fb2xt/fn1GjRhEdHW2Xp7i4mOnTp+Pn54eXlxdjx47l5MmTdnkSExMZMWIEHh4e+Pv78/TTT1NWVuZs1xoFb08rL99/goQv9/Po2JMcTak6SEjP1nN1+0L+WnSY71+J44qwYq4IK+b7V+L484PDXNW+iPTsqkdVjqYYeey2kyR8uZ+X7jtBE28Ltw/MJnrFARY/nUBeDfbryivQseSZeI6sOMDtA7Np4m2pt378OP9ote0VQgjhOpyeoOzp6cnhw4dp1aoVQUFB/PTTT1xzzTUcO3aMq6++mtzcmq+oO3ToUO666y569uxJWVkZs2bN4sCBAxw6dAhPT08AHnroIX766Sc+/fRTfH19+de//oVWq2X79u2A7bZat27dCAwM5D//+Q+pqalMmDCBKVOmMG/evBq1ozFNUI76+BDXdChUj1ssoKtiukp16XVRR2M7x+4YD7pP7SwTlIUQopG7aOvshISEkJqaSqtWrWjXrh0bN27kmmuu4e+//8ZoNFZfwTnWr19v9+9PP/0Uf39/oqKiuP7668nNzWXJkiWsWrWKG2+8EbDtut6pUyf+/PNP+vTpw8aNGzl06BCbN28mICCAbt268fLLLzNjxgxefPFF3Nxqv9lkY1BdAFBdel3U4SrnEEII4Zqcvo01evRofvnlFwAefvhhnn/+ecLDw5kwYQL33XffBTWmfFSofKJzVFQUpaWlDBo0SM3TsWNHWrVqxc6dOwHYuXMnV155JQEBAWqeyMhI8vLyOHjw4AW1RwghhBCNn9MjO6+++qr6+s4771QDj/DwcG655ZZaN8RqtfLYY49x3XXX0aVLFwDS0tJwc3OjSZMmdnkDAgJIS0tT85wb6JSnl6c5YjabMZvPLoCXl5dX63YLIYQQomG74HV2+vbtyxNPPHFBgQ7A9OnTOXDgAF9++eWFNqla8+fPx9fXV/0JDQ296Oe8FBQFnlscXKPHuCuTkaPnucXBF9SOH3b48uMO31qXbyj9EEII4Rqc/jZZsWJFlekTJkxwuhH/+te/+PHHH9m6dSshISHq8cDAQEpKSsjJybEb3Tl58iSBgYFqnv/973929ZU/rVWe53wzZ87kiSeeUP+dl5fnEgHPtv1ezPs8iK+2NOXoqgO1qqP3tI4cO2FiWK9c+nXNd7q8osCts8IBsP66q8IO5jXREPohhBDCdTgd7Dz66KN2/y4tLaWwsBA3Nzc8PDycCnYUReHhhx/mu+++47fffiMsLMwuvXv37hgMBn755RfGjh0LQHR0NImJifTt2xewjSy98sorpKen4+/vD8CmTZvw8fGhc+fODs9rNBqdnkzdGCz+qTkAaVkG8gu1eHlYnSqfX6glLcug1lWbIOGnnWdHdNb96cuIvjV/Oq9cQ+iHEEII1+H0bazs7Gy7n/z8fKKjo+nXrx9ffPGFU3VNnz6dzz//nFWrVuHt7U1aWhppaWkUFdn2WfL19eX+++/niSee4NdffyUqKorJkyfTt29f+vTpA8CQIUPo3Lkz9957L//88w8bNmxg9uzZTJ8+3SUDmsocTTby+SY/AArNWhatbeF0HR+s8afIbLskPtvkR1yKc78/RYE5y1qiO7PK8pxlLXF257WG0A8hhBCupc42At21axfjx4/nyJEjNT95Jfc4li1bxqRJkwDbooJPPvkkX3zxBWazmcjISD744AO7W1THjx/noYce4rfffsPT05OJEyfy6quvoq/Jhks0vnV2urUv5Oe/fIlJNhGbbCQ6ycQ/R93JLdCpu4ob9FaualdEp9ZFhIeYCQ8u5sZrTuPf1LbYYnq2ni27vYlNsdVx+Lg7/8S5U1pmK6/XWfH1tHBV+yIiQosJDzHTIaSYYb1z0Z4Jkf856s7fRzzVdhyId6+wOGB4SDFXtClSy/fsWMBV7W3BrNVKvfRDq1F4bGErWWdHCCEauYu2zk6lFen1nDhR9a7T56tJnGUymXj//fd5//33K83TunVr1q1b59S5GzOtFlIyDDzxfuXzjErLtOyK9iQqxgNF0XDLtTmM7p+jpvt6Wlj1ix8/7GiCRqNU2Em8zKIlM0/Llt0Gtuz2QaNR+OjJ42qgA+BmUHh+aUvSstwc1gEQm2ziaIoRRdEQ2KyEX9+Kqfd+zBqfWun5hBBCuB6ng521a9fa/VtRFFJTU1m4cCHXXXddnTVMVG3qLRkY9Ar3v9YGwGGgUW50/2y+nHMMN8PZ4NLoprB6bhx3vdSW77c1qbSsRmMrs/SZBCYNy7RL69S6mK3vRnP9IxFk5Oopszhug06r0Ny3lK3vRhMeYrZLq49+dG1XxCuftaw0rxBCCNfidLAzatQou39rNBpatGjBjTfeyBtvvFFX7RI1MHlYJm56hXvnhTlM12gU7hiYzWfPxWPQVxxFczMofPXCMca/EsY3vzWtNND4bFY84wZnOUwLDzGzfeERrn+kI2lZBixW+zp0WoWApmX88d4RwoJKGkQ/dsd4OEwXQgjhmpyeoGy1Wu1+LBYLaWlprFq1iqCgoIvRRlGFcYOzuLJtkcM0RdEwf2qywwChnEGvMH9KcqUBQte2RZUGOuXatizh4THpjtsAPDI2vdJAp1xD6IcQQgjXVOtFBTMyMmTl4QbAaoXoxLOTgnVa+4DgUIJ7tXWcn+fcOqKTTFhr8OT3oeMm9VZR+dNYAFqNwqGEqnc0h4bTDyGEEK7HqWAnJyeH6dOn07x5cwICAmjatCmBgYHMnDmTwsLC6isQdS4+1Yi5VKsGGkN65uHlbkF75ov+QHz1QUJ5Hq1WwdvDwuAetiBWo1EoLtGSkFb9Zqp7j3qoT1BFtComolUxYJsgvPdo9beNGko/hBBCuJ4az9nJysqib9++pKSkMG7cODp16gTAoUOHeO+999i0aRPbtm1j3759/PnnnzzyyCMXrdHirINnRk2G9spj/pRkrmpfRPZpHa99Echb3wTUOEgwuVl5/PaTPH1XGk29LeyNdWfW4hB+/suXgwnutG1Z+W0oiwVikky0DjAzb0oKd91ou1305ZZmzPokmJhkIxZL1buON4R+CCGEcE01DnZeeukl3NzciIuLq7Dx5ksvvcSQIUO499572bhxI++++26dN1Q4ZjQobHvvCNddeXaV4KbeFuZPTeGRsel890eTauu4tks+rz+URKBfmXqsW3gR6xbEsm2fFwXFVQ8AZubpeftfidw3PNNuXs09g7K4fWA2S9f5kZmnV9fGaaj9EEII4ZpqvKhgmzZt+Oijj4iMjHSYvn79eoYPH84LL7zACy+8UKeNvNga26KC13SQW4YXYneMB92ndpZFBYUQopGr6fd3jf/UTU1N5Yorrqg0vUuXLmi12kYX6AghhBDCtdU42GnevDkJCQmVpsfHx6sbcQohhBBCNBQ1nrMTGRnJc889x6ZNm3Bzs3+qxWw28/zzzzN06NA6b6AQouFKTISMjPpuhWto3hxatarvVgjhmpyaoNyjRw/Cw8OZPn06HTt2RFEUDh8+zAcffIDZbGbFihUXs60C6D61M1k/7KGpt6VW5XtM7YRGA39/dLhW5bNP62h2y9WsnH2MewbVbpG+VZubMe7fbeu1H+LCJSZCp04KhYWVb/Ehas7DQ+HwYY0EPEJcBDUOdkJCQti5cyfTpk1j5syZ6iaeGo2GwYMHs3DhQlrJ/6WXxJbd3owdkON0udOFWqJiPAHIL9Ti5eH8Knu/RNkmgM38JLjWwc6Mj0KA+u2HuHAZGVBYqOGTp+OZ8h/bVh9/vHsYD1ONnnmws3mXNzM+DiWwWQk/vXq0Vu0Z9kw46TkGXnswiZu6n3a6fEGxhusfsS2pcan7cfi4ifGvtCUjQ0Z3hLgYnNobKywsjJ9//pns7GxiY2MBaN++Pc2aNbsojROOzVsZxJjrc9A4+Qf1ojVn51QtWtuCp+866VR5RYF5KwMBSEp342iykfbnbexZndhkIykZBqB++yHqzv64s4tG7jzkVav344H/tAbgZLYBHw9Lra6rU7m2j7Mvf23GU3eddPq6eu2LQPV1ffVDCHFx1GrhkaZNm9KrVy969eolgU492B3jyfL1fuScrmKVvnOYSzQcjDfx6qqzH+avrgriYLwJc0nNvhFyTutYvt6PPbG2ERWdVmH2kmCS0w012obBaoXkdAOzlwSr2zjUVz9+2OFbo7yiZpat91NfX87X1YX2Qwhx8dR4nR1X1pjW2QHbB2n57uJNvMroEFrMwG6nmT8lBe2Z8PW7P5qwaE0LDiW4k5plwGrVoNEo6kaZ5a+1WoWWfqV0al3EQyNPMbp/DmD78J35STC/7fUmJslETr6+wrnLGQ1WwoLMdAkr4q3pSYT4lwKQlG7g8YWhHExwV7eDOFd99gOQdXYu0NlrUgHkurqQfsSdMFJappVrUggn1fk6O6LhOPfDNCdfT0KakfuGZagf5ADDe+diclNIyXDDeib/uTuCl7+2WjUkn3LD3WhleO9cNV2rhclDM0lIM9oFCOd/kAOYS7VEJ5kY2itP/SAHCPUvZWivPKKTTBW+kOq7H6IuyXV1of0oLZOPYiEuJvk/rBHT66wE+ZWw/b0jRLSynxtgdFNYPTeOMddnq5trOqLRKIy9PovVc49hdLPP17F1MdvfO0KQXwl6neNxdo1GQaNRWD4znvtHVHwG+YGbM/j02QQ1X0Pth6hbcl051w/b6JgQ4mKRYKcRa+ptYcfCI5VOgnQzKHw1J45R/XIqrWNUvxy+nHPMbk+rc7UPMbN94RGaeDl+RFxRNCyfGc+9Qyp/MmtCZCbLZ8bb/eXc0Poh6pZcV87146X7UipNF0JcOAl2GjEvdyttgqrexVuvh86tizDoK/7ladBbuaJNEfpq7u6EBZXg5V75iMhV7YqqbWvXtpXnaSj9EHVDrit7NelHeLA8tSXExSTBTiNU/tTJ8ZNuFJurf1rkQLw7ZRZbPq1WQXumfJlFw4F492rLF5k1JKa7qeUBu2H7mtRxbp7ysvXZD1G35Lq6sH4cTTFWm0cIUXsS7DQyL0xMod2ZvwKtVg1HEk3Vltlz1ANF0eBhsvDCxBO8MPEEHiYLiqJhT6xHteWPJJrUSZztg80snRHPyOty1HRnv5RG9cth6Yz4eu2HqDsmN7muLrQfcSck2BHiYpLHUxqZW6/L5fkJqazc7McLy1pyIN6dbuGVD5MXFGnJyNXz1J1pPHtPKn6+trkF00aeYsEXgXywpgWFxVo8TJUPwx+Id6dNoJm5k08wblAmOh1MHpZJVHQasxYH1/hLKbJnLq88kEL3iEIAJgzJrJd+TB6WwQvLgqtts6iZn16N5cZr8oHL+7q6kH7EpVQflAkhak/W2aFxrbMT9fEhrulg+1A3l9gei21Xxf3+3Hwd+UVagluUOkxPOWXAy92KbxUTd48mG2kVUIKbwfGlcijBROc2xVW2v6o8l7ofB+Ld6T61s6xpcoEcXZPlLsfr6kL6sfq3Jtz+Ynu5JoVwUk2/v2VkpxEzuilVfpAD+HpZqvygruxD/lzVLXlf3Qd5dXkaSj9E3ZHr6qya9KNty6onUgshLozM2RFCCCGES5NgRwghhBAuTYIdF5Obr7ugXb0VxVbHhSg2a2r0yG9VGkI/RN2R6+qsuuiHEMI5Euy4kLgUI01uvpp7XwmrdR3jXwmjyc1Xc+xE7dejcY/sjntk91qXbyj9EHVHrquzLrQfQgjnSbDjQlb/3hSATVE+tfrrVVFg0y6fM3U1q1UbYpLOrhcSm1y7tUMaQj9E3ZHr6qy66IcQwnkS7LiIgiItC74IBCA928DPf/k6Xce6P305lWMA4NVVgRQUOX95zPs8CJ1WQadVmPd5kNPlG0o/RN2R6+qsC+2HEKJ25NHzRkpR4ESGgdhkE7EpRjb+7UPOmbkEOq3C4++HEp1kIjy4mPCQYsKCKq4DUlKqIT7V7UwdJj5c2wKdVsFi1ZCTr2PSq20Y0jOP8GAz4SHFtGxeiua8qQa5+Tpik43EppiITjTx2SY/dTXZFRv9aB1QQkSrYjqE2Nrh42m/OFt99ENWlrq4Ltfr6kL6YZUt24S4qGRRQRrfooLd2hdy98tt+frXs0PpBr2V0rKzf2nqdVasikb9YA1pUcKO9w8T6m9bNyQp3UDfaZ1IyTi7p49Wo1Bm0VZa5x03ZPHF88fQnjn01Zam3PVSu0rPeX6dGo3Cl3OOcccN2QBYrdRLPwb3yGXTLl9ZwO0ClV+TP70aw/A+ecDlfV1daD8AuSaFcFJNv79lfL8R0mphxcx4br0uWz127ocuQJlFi9WqQadVCGhayi9vRqsf5ACh/rZj/k1L0WkVrFaN3Yfu+XWOvC6bz2bFqx/kAHfemM2SZ+LRaBQ0Zz60z917qrzO8vQlzySoX0j12Y+X70tx/IsVtRLYrEx9fTlfVxfSD7js/+YU4qKSYKeRMroprJ57jNsGZJ35sKxIr7MS0KyU7QuP0CG04iqvEa3M7Fh4hIBmpXa7NJ9Lo1G4fWAW38w95nA5/PuGZ7JiZrya11F5sH35TB6W2SD6YZCbtxfV5XpdXUg/JAAX4uKSYKcRM+gVvnj+GB1CHC9HX2bR8vOC2CqXzG8XbObnBbEV/motFxFazKrZxzDoK//Lc/yQLGaNS600/bnxqYwfklVpekPph6g7cl2dVZN+lN8GFEJcHBLsNHJ6PWTkVj5UkVdQ/QJouVXkycjVo6/BSEheoQ69ruIHvl6nkFdYfRsaSj9E3ZHr6pzzXGA/hBAXRoKdRu5Ujp7MPNvjsNozj7SWvwY4EO9ebR3lecrL6LSK+joj10BGTvWf5vviPCgt06LXWdU5CnqdbQLnvrjq29BQ+iHqjlxXddcPIcSFkWCnkTt45oPY3WjhufGpZKzZy9cvxtEm0DY078yHeVigma9fjCNjzV5mjUvF3WjbDfpggqnaOvafqWNEn1z2Lz3I/qUHGdEn15Z2rPo2NJR+iLoj11Xd9UMIcWHkT91G7miKkcduO8nMcan4N7U9FXP7wGxG98tm+Ybm/P6PV7V15BXoWPJMPBOGZKpD8i/ff4KHx6Qz7/MgjqaYGNAtv9Ly6dl6rm5fyLwpKfTqVKAe//6VOP465MmsxcGkZ+vV9jXUfoi6JddVzfuRlSe3soS4mGSdHRrfOjvXdChUj1ssoKvic7K69Lqoo7GdY3eMB92ndpY1TS5QZddkuYb0njf0c/x92INeD8k1KYSzZJ2dy0R1H6LVpddFHa5yDlG3GsN73ljOIYS4MBLsCCGEEMKlSbAjhBBCCJdWr8HO1q1bueWWW2jZsiUajYbvv//eLl1RFObMmUNQUBDu7u4MGjSI2NhYuzxZWVmMGzcOHx8fmjRpwv33309+vutOQn3/uxYXVP6HHb78uMP5HZ/LKQo8tzj4gh7jzsjR89zi4FqXhwvvh6hbcl3Z1EU/hBB1r16DnYKCAq666iref/99h+mvvfYa7777Lh9++CF//fUXnp6eREZGUlx8dkXUcePGcfDgQTZt2sSPP/7I1q1bmTp16qXqwiW39OcWbNtX/RMkjigK3DornFtmhdd65+9t+72Y93kQfaZ1rF0FQO9pHZn3eVC99kPUHbmuzqqLfggh6l69BjvDhg3j3//+N6NHj66QpigKb7/9NrNnz2bkyJF07dqVFStWcOLECXUE6PDhw6xfv57FixfTu3dv+vXrx3vvvceXX37JiRMnLnFvLp3FPzWvVbmfdp79i3Xdn7X767X83GlZBvILnb988gu1pGUZ7OpyVl30Q9SdP84JLi736+pC+yGEuDga7P+N8fHxpKWlMWjQIPWYr68vvXv3ZufOnQDs3LmTJk2a0KNHDzXPoEGD0Gq1/PXXX5XWbTabycvLs/tpTD7b5EdcitGpMooCc5a1RHdmFdk5y1o6/dfr0WQjn2/yA6DQrGXRWudvqX2wxp8is+2yq69+JJ00OFdAVOnDtS3kuqJu+iGEuDga7I3ltLQ0AAICAuyOBwQEqGlpaWn4+/vbpev1epo1a6bmcWT+/PnMnTu3jlt86Wg1Cr0f6shV7YuICC0mPMRMh5BihvXORXsmfP3nqDt/H/EkJtlEbLKRA/HuHE05u9Lr7hhPIu7twhVtitTyPTsWcFX7IgCsVvj5L1+1fHSSiX+OuqPVKFjRoCganlsczNe/NqNTa1sd4cHF3HjNaXXxtvRsPVt2exObYqvj8HF3/olzR1E09dqPqGhZsbYuRSed/X1eztfVhfTjz0MeF/19EuJy1mCDnYtp5syZPPHEE+q/8/LyCA0NrccWOafMoiUzT8uW3Qa27PZBo1H46Mnj6gc5gJtB4fmlLUnLckOjUdQvgnPFJps4mmJEUTQENivh17di1DStFlIyDDzxfuW/l9IyLbuiPYmK8UBRNNxybQ6j++eo6b6eFlb94scPO5o4bEND6YeoW3JdOd8PkMlnQlxMDfY2VmBgIAAnT560O37y5Ek1LTAwkPT0dLv0srIysrKy1DyOGI1GfHx87H4ao/INBZc+k8CUmzPs0jq1Lmbru9EENitRNz90RKdVCGxWwtZ3o+nYutgubeotGSydEa+epyqj+2ezem4cRrez+YxuCqvnxjG6f3aj6YeoG3Jd1V0/hBAX7v/bu/Owpq78f+Dv7AlEVpVdpIqAtXXX2mq1ioCOftXOtHZK3Wpx2opd+HWsW0HtYuvMOI6jXdTBpUVH2+lia7VVtI5bHZe6IYJAEEQQkH0LkJzfH5ELkYQAuZLt83qePA/c5dzzufnc5OTec8+12sZOUFAQvL29kZyczE2rqKjAmTNnMGrUKADAqFGjUFZWhvPnz3PLHDlyBFqtFiNHjuzyOlvC58tUmDvprsF5wf5qnNx4HV7ujQY/0EVCBi/3RpzadB3B/mqDZcybdBefL1MZ3b5AwPDsuFLsSciCVNJ6G1IJw56ELDwzrrTNLwRLx0H4Q3nV8TgmDrOtfoOE2BqLNnaqqqpw8eJFXLx4EYCuU/LFixeRk5MDgUCAN954A++99x727duHK1euYPbs2fD19cX06dMBAGFhYYiKikJMTAz+97//4eTJk4iNjcVzzz0HX19fywXWRR59qBbRE0vaXOYh33oserrQ4DwG4LXfFyLIp77NMqInluCRh2oNl8EEWLPgFiRi4184EjHDmphbBi8VANYRB+EP5VWLMtoZR+wMw3UghPDDoo2dc+fOYfDgwRg8eDAAIC4uDoMHD0Z8fDwAYPHixVi0aBEWLFiA4cOHo6qqCgcPHoRc3tyRMCkpCaGhoZgwYQImT56M0aNHY/PmzRaJpysIW/yKTcuVQ6s1vc61m3Lu12/T3SZNZV3Llre1KgBdZ8y0nObl7v8VfC3bdIff+5dpWYal4iD8obwyL46s2x27e4wQ0jEWbeyMGzcOjLFWr+3btwMABAIBVq9ejYKCAtTV1eHw4cPo16+fXhkeHh7YtWsXKisrUV5ejsTERCiVnRtUzBaM7K8bHVogYKirFyK7QGpynYsZTmjU6N7qkF51COml63vQqBHiYobpu0BU+TKoG4TcF0LE8AooFRoI732oX1WZ/jBvWkYoZOjmpOFO21siDuoMyj/KK/PiyKTGDiEPlNX22SGGbXw9F79tSUHUCN2HeoqJX40aDZCeK0eglxpJK7JwJTEFVxJTkLQiC4FeaqTfkkGjaXubKfd+3UaNqMDFrSn48aMbyNl7GYufK4BMom33l5JcqsXbfyzAzT2XcWDtDYvF8fgA+32ciCW8N/8W5ZWZcXR0XCBCSMcIGKMB9ysqKuDq6ory8nKrvTPrwgVg6FDg/OZrGNKvBgBw4rIS1XVCRI4w3rmxsFSMb4674cXJd1v1G2hoFCDxR0/MGFPGjf1hyE//c4FSocUTj7RuJOTfleCb4254dXpRm/X/+NseeHpMKbw9W2+nq+NQyLQYuqA/zp8Hhgxps9qkDYZyEnDcvDInjiWb/fDRLh/KSUI6qL3f39TYge02dkjnXEh3osYODygn+UM5SUjntPf7my5jEUIIIcSuUWOHEEIIIXbNIR8XQQghxH7l5ADFxaaXI23r3h3o1cvSteAHNXbsSGmlCB5TByNpRRaeD297MDVjdh32QPR7D6Hk+9/g3s3EbShGDFsQBoEAOPtZaqfWt5Y4CH8or5qZGwdpW04OEBbGUFNjeLBJ0n5OTgypqQK7aPBQY8eOJJ/Xdc5ausWv0x/mb3/mDwA4cqEbfj+2rMPrV9YIcT7dGQBQVSOE0qkdo7rdxxriIPyivNLhIw7StuJioKZGgC+WZyHsvueZ3a+6ToAnXwsDABzfkAonecfv1zl8rhve3hwAb4967P8wo1N1nrQ4GIVlEqz9Uy4mDK3s8PoPIo7Um3K88P5DKC62j7M71NixE4wBHyTpHn6aWyhFxi0Z+hp5no8xN27JkFcsAQB8kOSDp58sg6CDP44++a5n89/7euDPz91pY+nWrCUOwh/Kq2bmxkHaLyywzuRdgmt3Nz8w+vQ1Zafy6qW/BAIA7pRK4OKk6VReFZXrvor/fdQDbz13p8N59SDiMNVQtDXUQdkOlFWKsOOgJ367ofvFKBIyrPiXH24VSto1XL5WC9wqlGDFv/y4oe4vpDtjx0FPlFWK2lUHdb0AKSo5PtzVfNB9uMsHKSo51PXtO3KtIQ7CH8orfuMg/KG8Mh3HnRL7OhdC4+zA9sbZGdS3Bku3+OGXi92QnitHWZUuKUVCBo1WP8FlEi2CfNQYEFSLvy/MhX/PBgBAbqEEb24MQEq2osVjFJq1LMtN2Yh+AXUYN6gSa2LyILy36DfH3fDJdz1wLVuB/BIJtFoBBALGPZix6W+hkMHXswFhgbV4ZVoRZowpA6A72C0RR2ivWuz8qQeNaWKmppz88cN0THpMN3CfI+eVOXF0d2lEYZmEcpIHTXk5O7II296+6dB5ZW4cAKw+J2mcHTsmFALzou4iu0DGJSoAg4mqbhAiLVeOqBEV3AEHAAE9GxA1ogJpufJWB9z9ZZVViZFdIMOLk4q5Aw4AJo8sh1zKkFcshfbe8i2fQN30t1YrwK0iKRQyLSaPLLd4HNOeKGu1HOk8L4/m0YUdOa/MiaOwTNJqG8Q8054oc/i8MjcOe0KNHRsVGliHk/+8Dh/PeohFhs+ZCgQMAgHDjqUqzP9d6/swX5pSjO1LsrnlDBGLtPDxrMfJf15HSC/9a9EyKcNXqzLx9JOlRtdvqsfvnyzBV6uyIJPqL2eJOHp7NxhchvDDUfPKnDjGDy43Op90zv3HuSPmlTlx2NsDk6mxY8P6+qtxcuN1uCkN3wLLmAA7lqowK8L4nSezI+9ix1KV3i+Dlty7aXBq43Wjne6kEoY98ZmYPrrM6Damjy7Dv+OzWj17yJriIPyivOpYHGsW5BmdT/jjaHllThyAfZ3pocaOjQvyqYdSYbw33MA+tSbLePQh48soFVr09qlvc32xGOgfWAuJuHU9JGItHu5dC7GJvm7WEAfhF+WVTrvioP7zXcah8srMOOwJNXZsXK1agJxCKQBAeK9Hf8vTkldVCpNltFymad2muwNu3pGiTm26hX9VpUCjRsDVo6kujRpBu+pgLXEQ/lBe8RcH4RflVfvisCfU2LFx13PkXCe1vn5qJL6t0uuA29GDbvroMiS+rUIfP93pU61WgOs5cpNl/JbhBMYEcJJrkDDnNhLm3IaTXAPGBPjthpPNxEH4Q3nFXxyEX5RX7YvDntjXjfQO6KpKgd7eaqyadxvR4XchEgHzJt3F+bQCLNvq1+6DLnJ4Od5/KQ9DQ3SDcM2OuIukw55I2OaLqyoFBgUbP+VaXStEcbkYb80swJLn8+HpqrsG/Oq0Iny02xsff9cDNXVCOMmN/2KwhjgIvyiv2h9HLZ117DKOlFfmxBH7jwD8eq2byThsBY2zA9sbZ6flqKAZt2To5VUPqcTw23gtW47+vdseCbOtZdT1utsXm35xGFJeJUJVrRB+PQzf5ZRXJIFSoYWr0Y5wXRvHhXQnDF3Q3+rHj7B2xnKyiaPllTHtiSMjT4Zxb4RSTvLAVF46Ul6ZE4etfE629/ubzuzYOFN3F5k64EwtI5OyNg84AHBVato8oIwdjC1ZQxyEX5RXOu2J404pjbPTVRwpr0xxpLtTqc8OIYQQQuwaNXYIIYQQYteosWNjKmvMe8vq1AKzb8EurxLBnJ5ejOnKMAcfcRD+UF41MzcOwi/KKx0+4rBl1NixMePeCEXWbWmn11dEDoUicmin18/Mk8FtymDMej+o02W88H4Q3KYMtmgchF+UVzp8xEH4Q3nVjI84bBk1dmzQV8c8OrVeeq6M+/vGLVkbS7a1bXcAwKHzLp36lcEYcOicy72yLBcH4c/NO82dax09r8yNg/CL8kqHjzhsHTV2bNCHu7xRXdvxt+6DL3wgEjKIhAwffOHT4fWra4X4aLc3AKCwVIIDZ1w7XMaPv7qi6N4Tni0VB41pwq/EH7tTXoGfOAh/atUCyqt7+IjD1tGt5zaorEqEuR/2RsTwCgT7qRHsXwff7g0Q3PcdXl4lwo1bMtzIkyMtR47PD3lyo2Xu/NkTgV71COlVh37+dQj2r4OLs/7gU4wBt4sluHFLjht5Mvx81gVl9675ioQMb24KQFquHMF+uvWDfFqP11DfIIAqX3qvDDk+3dcDIiGDRiuwWBx7jrib+xaQFvb/6sY90NCR88qcOP57SWnem0BaSdjm6/B5ZU4c5vYPtTY0qCBsa1DBJhKxFg2Nzcn47FMl2P1OFoT3Ju054o7nVvfh5otFWmiZgDvohEIGoYChUaNbQSBg+Hd8Fp59qhQAoNUCf3z3Iew92nzK8/5t3l+mf496nNqUioCeuvEdcgslGPVqGPKKpQa3aak4xCItGjVCqx8sy9o15aRAwLjGjiPnlblxAKCc5EFTXjYd500cNa/MjcPac7K939/21XRzIC0TddoTpfh8mYpLVACYOb4U/1qsgkDAILiX6E0HB6B79kqjRsjN/9fibO6AAwChENi5VIX/e6J5WsttAuDKFAkZvNwbkLwujTvgACCgp25aT/cGiISM26al47i/DsQ8TQ0dwLHzypw4hAKH/83Ju/tzwhHzypw44mfnGdyvtoo+9W2YQMDwzLgSfLkqy+Bw3y9OvoudS1XcsobWB3QH17xJd1vNl0kZvlqVhT+MLTG4PqD7leHl0YCTG6+jX0Dr0ThDeqlxauN1eHk0GH2arjXEQfhDedXxODxcGw2uT/jlaHllThzTRpcbXM9WUWPHhoUE1GHXiixIxMa/wF+IKMGy6Hyj85e/kI8XIkqMzpeIGXa/k4V+/oaHNm/UCHHgoxttDm3ex0+NAx/dMHpGxRriIPyivNJpbxwbX8sxOp/wx9Hyytw47Ak1dmxYcbkY4nZ0Ma+oEUEsap3QYhFDRY3pQabEYt22jJZfbbqM8jaWsZY4CD8or+4rvx1xVDrg3TGW4kh5xUcc9oKOMBsjFDAIhboDqLhcguIy09l6OdMJDY1CiEVa7lqxWKTroHY5U2Fy/aIyMe5W6G5bFN67hbLpbwC4qjJdRtMyTeuIhJaNg/BHJKS8MjeOzDy5yWVIxzl6XvERh72gxo6NObIuDcui86GQ6Z52m5Jt+kPyyr2E/91j5biSmIIriSn43WO667FXskwfMCn31lfINFj+Qj6Kv7uIvSsz0dtbdwq1IwddkLcae1dmovi7ixaLQyYx/qRg0nGjH6mivDIzjszbNDgm32QSyis+4rAXjtOssxPdnLV4d/5tLHq6EB984YOMPDnGDqoyunxhqRiD+9bgg5g8jAir5qZ/+34mzlxzxrKtfigsFaOnu/EOkhl5MrzxhztYGp3PLffMuFLMGF2KHT91x7F2jBFSUS3CvxarMDviLnfq1FJx/O6xMkx8K8RknUn7rFt4Cw8H6foWOHJemRNHFV3G4t0PazIQPqwSgOPmlblx2BMaZwe2Nc7O+c3XMKRfDTddowFEbVy6NTWfjzJsbRsX0p0wdEF/qx8/wtoZy8km1vSeW/s2zqY6YcQrlJN8MDcv27OMreSVOWXYyuckjbPjIEwlu6n5fJRhL9sg/LKF99xWtkH4YyvvuTVsw55QY4cQQgghdo0aO4QQQgixa9TYsSOMAcu3+pl1O2FxmRjLt/qZVY/vT7nih1Odf+KztcRB+EN51czcOAi/KK90+IjDmtlnVA7qxBUlPvjCB3uOuCNj19VOlTHy1VBk3ZZj0ohyjH604730GQP+b1kwAEB79FyrJ+m2hzXEQfhFeaXDRxyEP5RXzfiIw5rRmR07snV/dwBAQYkEVTUdf2uraoQoKJHoldVR+083/7L48dfO/cqwhjgIfyivmvERB+EP5VUzc+OwdvYXkYPKuCXDF4c8AQA1aiE+2dejw2V8/F1P1Kp1KfH5IU9k5nVsoDPGgPhtvhDdG+0zfpsvOjqwgTXEQfhFeaXDRxyEP5RXzfiIw9rZzTg7mzZtwl/+8hcUFBRg4MCB+Oc//4kRI0a0a11bG2dnUN8aHDjjivRbcty4JUNarhyXMhQorxZxD32TiLUY2KcWYYG1CPZXI9ivDuOHVHKDUxWWinHkQjfcyNOVkXpTgUuZCjQ06tYXi7RwddZgYN9ahATUIdhfjX7+dZg0shzCe03kSxkKnL3uzNXjqkqBjPuGvQ/2r8PDvWu59YeHVmNg31oAgFYLi8QhFDC8sbGX1Y8fYe2acvLQX9O4wdscOa/MicPFSYOdP3ennORBU16uj83BoqcLHTqvzImjr58aqTcVVp+T7f3+tos+O3v27EFcXBw+/fRTjBw5EuvXr0dkZCTS0tLQs2dPS1ePd0IhkFcsQdymAKPLNDQKcS7NGefTncCYAFMfL8OMMWXcfFdnDXYle+L7U24QCBgY07/I26gR4m6FEEcuSHDkggsEAobP/t9N7oADAKmE4Z1EXxSUSA2WAQA3bsmRkScDYwJ4e9Tj6N/TLR7HsheMP42YdJxS0fz4DUfOK3PjIPwqKhdTXpkRR+pN04+jsCV2cRlr3bp1iImJwbx589C/f398+umncHJyQmJioqWr9sAsmFqMxLdV3APm2jJjTCm+WpUJmbR5OZmU4atVmZgxprTNdZvKT1ycjZgpxXrzwgLr8N8NafD2qOceUmeISMjg7VGP/25IQ2hgncXjeLrFhw8xn7TFs1UdOa/MicPTpaHN7ZCOu/84d8S84iMOe2HzjZ36+nqcP38e4eHh3DShUIjw8HCcPn3agjV78OZNuovPl6mMzhcIGJ4dV4o9CVmQSlontFTCsCchC8+MK20z4T9fpsLcSXcNzgv2V+Pkxuvwcm80eOCJhAxe7o04tek6gv3VVhsH4Q/lVcfj2LYk22j5hD+OllfmxAHYVyPI5i9jFRcXQ6PRwMvLS2+6l5cXrl+/bnAdtVoNtbo5AcrLdU+iraioeHAVNVPVvbsRz6c3oKpWy00P6FmMIB9nZN1ufcqRMWDGmJs4ndL2U75njL6JvUcNp0KQTy0Cehbjv5faKqEOU0blYPP3PQDon1LVaBmmjCpCbmEdcguNl9CVcaTlNgCoQFUVYMVvudUzlpNNHC2vzImjoKQGlJP8MJWXjpRX5sTRxNpzsul722T3Y2bj8vLyGAB26tQpvel//vOf2YgRIwyuk5CQwKBrttKLXvSiF73oRS8bf+Xm5rbZVrD5Mzvdu3eHSCTCnTt39KbfuXMH3t7eBtdZunQp4uLiuP+1Wi1KSkrg6ekJAY3y1WkVFRUICAhAbm6u1d7VRhwP5SWxNpST/GGMobKyEr6+vm0uZ/ONHalUiqFDhyI5ORnTp08HoGu8JCcnIzY21uA6MpkMMpn+WAZubm4PuKaOw8XFhQ5gYnUoL4m1oZzkh6urq8llbL6xAwBxcXGYM2cOhg0bhhEjRmD9+vWorq7GvHnzLF01QgghhFiYXTR2Zs6ciaKiIsTHx6OgoACDBg3CwYMHW3VaJoQQQojjsYvGDgDExsYavWxFuoZMJkNCQkKrS4SEWBLlJbE2lJNdz24eF0EIIYQQYojNDypICCGEENIWauwQQgghxK5RY4cQQgghdo0aO4QQQgixa9TYIZ1y+vRp/PDDD3rTdu7ciaCgIPTs2RMLFizQe/4YIQ/akSNH0L9/f4PPuCsvL8fDDz+M48ePW6BmhDQrLi626ucw2itq7JBOWb16NVJSUrj/r1y5gvnz5yM8PBxLlizB999/jzVr1liwhsTRrF+/HjExMQZHpHV1dcWf/vQnrFu3zgI1I46urKwMCxcuRPfu3eHl5QV3d3d4e3tj6dKlqKmpsXT1HALdek46xcfHB99//z2GDRsGAFi+fDmOHTuGEydOAAC+/PJLJCQk4Nq1a5asJnEggYGBOHjwIMLCwgzOv379OiIiIpCTk9PFNSOOrKSkBKNGjUJeXh6io6O5/Lx27Rp27dqF0NBQnDhxApcvX8avv/6K1157zcI1tk92M6gg6VqlpaV6I1QfO3YMkyZN4v4fPnw4cnNzLVE14qDu3LkDiURidL5YLEZRUVEX1ogQ3VlwqVSKzMzMVqP6r169GhEREZg1axZ+/vlnbNiwwUK1tH90GYt0ipeXF1QqFQCgvr4eFy5cwGOPPcbNr6ysbPOLhxC++fn54erVq0bnX758GT4+Pl1YI0KAb7/9Fn/9618NPr7I29sba9euxX/+8x/uGY/kwaDGDumUyZMnY8mSJTh+/DiWLl0KJycnjBkzhpt/+fJl9OnTx4I1JI5m8uTJeOedd1BXV9dqXm1tLRISEjBlyhQL1Iw4svz8fDz88MNG5w8YMABCoRAJCQldWCvHQ5exSKe8++67ePrppzF27FgolUrs2LEDUqmUm5+YmIiIiAgL1pA4mhUrVuDrr79Gv379EBsbi5CQEAC6vjqbNm2CRqPB8uXLLVxL4mi6d++O7Oxs+Pv7G5yvUqnQs2fPLq6V46EOysQs5eXlUCqVEIlEetNLSkqgVCr1GkCEPGg3b97EK6+8gp9++glNH20CgQCRkZHYtGkTgoKCLFxD4mhefPFFZGZm4tChQ60+D9VqNSIjI/HQQw8hMTHRQjV0DNTYIYTYndLSUmRkZIAxhuDgYLi7u1u6SsRB3bp1C8OGDYNMJsPChQsRGhoKxhhSU1Px8ccfQ61W4+zZs+jVq5elq2rXqLFDCCGEPEAqlQqvvvoqfv75Z70zjhMnTsTGjRvRt29fC9fQ/lFjhxBCCOkCpaWluHHjBgCgb9++8PDwsHCNHAc1dgghhBBi1+jWc0IIIYTYNWrsEEIIIcSuUWOHEEIIIXaNGjuEkHYrKytDaGgoRowYgdzcXAwYMACNjY1dWoe5c+di+vTpXbrN9rLmuhHiyKixQ4gNmzt3LgQCAQQCAaRSKfr27YvVq1eb3QAx9qV9/PhxTJgwAbGxsRg/fjwiIiIgFtveQOzjxo3j9lvL18svv2zpqhFCHgDb+5QihOiJiorCtm3boFar8eOPP2LhwoWQSCRYunRph8vSaDQQCARG50+dOhVTp04FAMyePbvTdbYGMTExWL16td40JycnC9WmbQ0NDfRgXULMQGd2CLFxMpkM3t7eCAwMxCuvvILw8HDs27cPgG5cj9mzZ8Pd3R1OTk6YNGkSN84HAGzfvh1ubm7Yt28f+vfvD5lMhhdffBE7duzAd999x53x+OWXXwAAV65cwfjx46FQKODp6YkFCxagqqpKrz5bt25FWFgY5HI5QkND8fHHH3Pz6uvrERsbCx8fH8jlcgQGBmLNmjVGY9NoNIiLi4Obmxs8PT2xePFi3D9ahlarxZo1axAUFASFQoGBAwfiq6++MrnfnJyc4O3trfdycXEBAGRnZ0MgEGDv3r0YM2YMFAoFhg8fjvT0dJw9exbDhg2DUqnEpEmTUFRU1KrsVatWoUePHnBxccHLL7+M+vp6bt7BgwcxevRoLqYpU6YgMzOTm9+07T179mDs2LGQy+VISkoyuC/mzJmjdwaud+/eWL9+vV5dBg0ahJUrV3L/l5WV4aWXXuLqN378eFy6dMnk/iLEllFjhxA7o1AouC/XuXPn4ty5c9i3bx9Onz4NxhgmT56MhoYGbvmamhp89NFH2Lp1K1JSUrBhwwY8++yziIqKQn5+PvLz8/H444+juroakZGRcHd3x9mzZ/Hll1/i8OHDiI2N5cpKSkpCfHw83n//faSmpuKDDz7AO++8gx07dgAANmzYgH379mHv3r1IS0tDUlISevfubTSWv/3tb9i+fTsSExNx4sQJlJSU4JtvvtFbZs2aNdi5cyc+/fRTpKSk4M0338QLL7yAY8eOmb0vExISsGLFCly4cAFisRjPP/88Fi9ejH/84x84fvw4MjIyEB8fr7dOcnIyUlNT8csvv2D37t34+uuvsWrVKm5+dXU14uLicO7cOSQnJ0MoFGLGjBnQarV65SxZsgSvv/46UlNTERkZ2a590R7PPPMMCgsLceDAAZw/fx5DhgzBhAkTUFJS0rmdRIgtYIQQmzVnzhw2bdo0xhhjWq2WHTp0iMlkMvbWW2+x9PR0BoCdPHmSW764uJgpFAq2d+9exhhj27ZtYwDYxYsXjZbbZPPmzczd3Z1VVVVx0/bv38+EQiErKChgjDHWp08ftmvXLr313n33XTZq1CjGGGOLFi1i48ePZ1qttl3x+fj4sLVr13L/NzQ0MH9/f65udXV1zMnJiZ06dUpvvfnz57M//vGPRssdO3Ysk0gkzNnZWe/1xRdfMMYYU6lUDADbunUrt87u3bsZAJacnMxNW7NmDQsJCeH+nzNnDvPw8GDV1dXctE8++YQplUqm0WgM1qWoqIgBYFeuXNHb9vr16zu0LxhjLDAwkP3973/XW2/gwIEsISGBMcbY8ePHmYuLC6urq9Nbpk+fPuyzzz4ztrsIsXnUZ4cQG/fDDz9AqVSioaEBWq0Wzz//PFauXInk5GSIxWKMHDmSW9bT0xMhISFITU3lpkmlUjz66KMmt5OamoqBAwfC2dmZm/bEE09Aq9UiLS0NSqUSmZmZmD9/PmJiYrhlGhsb4erqCkB3pmnixIkICQlBVFQUpkyZgoiICIPbKy8vR35+vl79xWIxhg0bxl3KysjIQE1NDSZOnKi3bn19PQYPHtxmPNHR0Vi+fLneNC8vL73/W+6XpnmPPPKI3rTCwkK9dQYOHKjX92fUqFGoqqpCbm4uAgMDcePGDcTHx+PMmTMoLi7mzujk5ORgwIAB3HrDhg3r0L5oj0uXLqGqqgqenp5602tra/UupRFib6ixQ4iNe+qpp/DJJ59AKpXC19e3w3dHKRSKNjslt1dT350tW7bofSkDgEgkAgAMGTIEKpUKBw4cwOHDh/Hss88iPDy8XX1s2trm/v374efnpzdPJpO1ua6rq6vJBzC27BTctI/un3b/5SdTpk6disDAQGzZsgW+vr7QarUYMGCAXr8eAHqNyvYSCoWtGj8tL1lWVVXBx8eH64PVkpubW4e3R4itoMYOITbO2dnZ4Jd2WFgYGhsbcebMGTz++OMAgLt37yItLQ39+/dvs0ypVAqNRtOqvO3bt6O6upr7Ij558iSEQiFCQkLg5eUFX19fZGVlITo62mjZLi4umDlzJmbOnIk//OEPiIqKQklJSauHIrq6usLHxwdnzpzBk08+CUB3lqipnwkArlN1Tk4Oxo4da2JPdY1Lly6htrYWCoUCAPDrr79CqVQiICCA2/9btmzBmDFjAAAnTpwwWWZ79gUA9OjRA/n5+dz/FRUVUKlU3P9DhgxBQUEBxGJxm32lCLE31NghxE4FBwdj2rRpiImJwWeffYZu3bphyZIl8PPzw7Rp09pct3fv3vjpp5+QlpYGT09PuLq6Ijo6GgkJCZgzZw5WrlyJoqIiLFq0CLNmzeIu8axatQqvvfYaXF1dERUVBbVajXPnzqG0tBRxcXFYt24dfHx8MHjwYAiFQnz55Zfw9vY2elbh9ddfx4cffojg4GCEhoZi3bp1KCsr4+Z369YNb731Ft58801otVqMHj0a5eXlOHnyJFxcXDBnzhyjMdbU1KCgoEBvmkwmg7u7e/t2sBH19fWYP38+VqxYgezsbCQkJCA2NhZCoRDu7u7w9PTE5s2b4ePjg5ycHCxZsqRd5ZraFwAwfvx4bN++HVOnToWbmxvi4+O5s2oAEB4ejlGjRmH69OlYu3Yt+vXrh9u3b2P//v2YMWOG3qUzQuyKhfsMEULMYKgjcUslJSVs1qxZzNXVlSkUChYZGcnS09O5+du2bWOurq6t1issLGQTJ05kSqWSAWBHjx5ljDF2+fJl9tRTTzG5XM48PDxYTEwMq6ys1Fs3KSmJDRo0iEmlUubu7s6efPJJ9vXXXzPGdJ2cBw0axJydnZmLiwubMGECu3DhgtH6NzQ0sNdff525uLgwNzc3FhcXx2bPnq0Xs1arZevXr2chISFMIpGwHj16sMjISHbs2DGj5Y4dO5YBaPWKjIxkjDV3Ev7tt9+4dY4ePcoAsNLSUqP7r+n9iI+PZ56enkypVLKYmBi9DsGHDh1iYWFhTCaTsUcffZT98ssvDAD75ptvjG67vfuivLyczZw5k7m4uLCAgAC2fft2vQ7KjDFWUVHBFi1axHx9fZlEImEBAQEsOjqa5eTkGN1fhNg6AWMd6N1GCCHEasydOxdlZWX49ttvLV0VQqwajbNDCCGEELtGjR1CCCGE2DW6jEUIIYQQu0ZndgghhBBi16ixQwghhBC7Ro0dQgghhNg1auwQQgghxK5RY4cQQgghdo0aO4QQQgixa9TYIYQQQohdo8YOIYQQQuwaNXYIIYQQYtf+P+yOgHkmK2qlAAAAAElFTkSuQmCC",
+      "text/plain": [
+       "<Figure size 640x480 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "# título, legendas (Y e X)\n",
+    "contagem_portoes = df_dani['Embarque'].value_counts()\n",
+    "contagem_portoes.plot(kind='bar', color= 'pink',edgecolor='blue', hatch='*');\n",
+    "#df['Idade'].plot.hist(bins=10, edgecolor='black')\n",
+    "plt.xlabel('Portões de Embarque')\n",
+    "plt.ylabel('Quantidade de passageiros')\n",
+    "plt.title('Quantidade de Embarque por Portões');"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 144,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 640x480 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "# título, legendas (Y e X)\n",
+    "contagem_P = df_dani['Sobreviveu'].value_counts()\n",
+    "contagem_P.plot(kind='barh', color= 'black',edgecolor='white', hatch='*');\n",
+    "#df['Idade'].plot.hist(bins=10, edgecolor='black')\n",
+    "plt.ylabel('Mortos (0)   Vivos (1)')\n",
+    "plt.xlabel('Quantidade de passageiros')\n",
+    "plt.title('Sobreviventes');"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 158,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 640x480 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "# título, legendas (Y e X)\n",
+    "df_dani['Idade'].plot.hist(bins=70, edgecolor= 'black', color='blue')\n",
+    "#contagem_id.plot(kind='scater', color= 'black',edgecolor='white', hatch='*');\n",
+    "#df['Idade'].plot.hist(bins=10, edgecolor='black')\n",
+    "plt.ylabel('Quantidade de passageiros')\n",
+    "plt.xlabel('Idade')\n",
+    "plt.title('Histórico de Idade');"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 159,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import numpy as np\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 166,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "array([ 0, 10, 20, 30, 40, 50])"
+      ]
+     },
+     "execution_count": 166,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "array_precos = np.array([12, 22, 32, 42, 52, 62])\n",
+    "array_promocional = array_precos -2 * 6\n",
+    "array_promocional"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 174,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "[100 200 300]\n",
+      "Séries\n",
+      "0    100\n",
+      "1    200\n",
+      "2    300\n",
+      "dtype: int32\n"
+     ]
+    }
+   ],
+   "source": [
+    "precos = np.array([100, 200, 300])\n",
+    "print(precos)\n",
+    "\n",
+    "print('Séries')\n",
+    "precos_series = pd.Series(precos)\n",
+    "print(precos_series)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 175,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "Bala         100\n",
+       "Chocolate    200\n",
+       "Bolo         300\n",
+       "dtype: int32"
+      ]
+     },
+     "execution_count": 175,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "produtos_em_series = pd.Series(precos, index=['Bala', 'Chocolate', 'Bolo'])\n",
+    "produtos_em_series"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 176,
+   "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>A</th>\n",
+       "      <th>B</th>\n",
+       "      <th>C</th>\n",
+       "      <th>D</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>1</td>\n",
+       "      <td>2</td>\n",
+       "      <td>3</td>\n",
+       "      <td>4</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>5</td>\n",
+       "      <td>6</td>\n",
+       "      <td>7</td>\n",
+       "      <td>8</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "   A  B  C  D\n",
+       "0  1  2  3  4\n",
+       "1  5  6  7  8"
+      ]
+     },
+     "execution_count": 176,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "#Criando dataframes Pandas com arrays Numpy:\n",
+    "lista_1 = [[1, 2, 3, 4], [5, 6, 7, 8]]\n",
+    "array_1 = np.array(lista_1)\n",
+    "df = pd.DataFrame(array_1, columns=['A', 'B', 'C', 'D'])\n",
+    "df"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 178,
+   "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>A</th>\n",
+       "      <th>B</th>\n",
+       "      <th>C</th>\n",
+       "      <th>D</th>\n",
+       "      <th>E</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>1</td>\n",
+       "      <td>2</td>\n",
+       "      <td>3</td>\n",
+       "      <td>4</td>\n",
+       "      <td>9</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>5</td>\n",
+       "      <td>6</td>\n",
+       "      <td>7</td>\n",
+       "      <td>8</td>\n",
+       "      <td>10</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "   A  B  C  D   E\n",
+       "0  1  2  3  4   9\n",
+       "1  5  6  7  8  10"
+      ]
+     },
+     "execution_count": 178,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "df['E']=[9, 10]\n",
+    "df"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 181,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "0      1\n",
+       "1      4\n",
+       "2      9\n",
+       "3     16\n",
+       "4     25\n",
+       "5     36\n",
+       "6     49\n",
+       "7     64\n",
+       "8     81\n",
+       "9    100\n",
+       "dtype: int32"
+      ]
+     },
+     "execution_count": 181,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "lista_2 = [1, 2, 3, 4, 5, 6, 7, 8, 9, 10]\n",
+    "array_2 = np.array(lista_2)\n",
+    "\n",
+    " \n",
+    "#Cálculo Matemático\n",
+    "#Determinando a sequência de quadrados perfeitos\n",
+    "raiz = pd.Series(array_2)\n",
+    "\n",
+    "raiz_de = np.square(raiz)\n",
+    "raiz_de"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 184,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "[28  7 36 19  6 30 30 15 13 19 28 32 25 31 47 27 31 38 48  9 37 20 28 36\n",
+      " 49 39  9 17 26 12 33 29 17 12 38 15 14 23 14  6 23 18 18 34  6 12 41 43\n",
+      " 24 45 38 16 15 22 42 39 28 17 27 23  9 18 16 40 40 35 20 40 13 31 26 41\n",
+      " 44  6 43 22 47 43 12 11 14 47 47 41  7 46 19 31 13 47 47 19 22 15  9 12\n",
+      " 39 22 43 16 40 39 43 18 21 44 19 11 22 12 41 28 36 23 34 17 37 27 41 45\n",
+      " 18 21 13 22 35 21 25 49 15 37 43 13 24 28 34 26 21 49 46 25 30 32 27  8\n",
+      " 13 13 42 16 45 25  8 37 25 16  7 44 36  5 36 33 22 37 37 27 38 43 41 13\n",
+      "  8 39 18  7 35 47 30 10 18 18 45 48  7 34 31 28 48 48 29 45 25  5 36 13\n",
+      " 14 36 36 48 14 33 16 28  9 32  5 26  7 31 37 22 28  6 24 17  9 41 36 33\n",
+      " 10  7 26 36 26 12 30 31 10 42 31 44 30 38 10  8  9 42 34 28  5 21 25  8\n",
+      " 25  7 31 27 35 28 47 27 26 13 20 10 28 34 21 11 25 41 10 21 18 40 21 26\n",
+      " 24 27 20 37 13 28 19 35  9 30 12 14 21 11 13 33 34 13 22 30 28 14 10 32\n",
+      "  5 14 10 33 35 39 47  7 15 27 41 43 17  6 27  5 11 11 40 30 16 33  7  6\n",
+      " 33  6 29 13 12 29 25 14 47  5 41 28 17 26 14  7 13 22 14  7  9 39 30 11\n",
+      " 16 44 47 44 14 38 48 49 14 19 34 33 46 31 33 28 42 28 41 31 37 49 19 24\n",
+      " 31 40 32 47 25 33  7 31 33 17 26  7 29 45 34 14 10 32 32 17 10 29 11 11\n",
+      " 22 36 23 37  6 47 32 39 48 12 28  9 29 20 11 14 38 25 11 32 34  8 32 42\n",
+      "  5  7 14 26 10 14 22 19  7 11 45 34 17 40 25 23 15 26 12 36 31 43 36 19\n",
+      "  6 29 24  5 20 25 23 11 22 23 48 34 41 46 31 14  7  5 41 14 14 32 10 12\n",
+      " 38 12 36 19 29 41 46 21 17  7 35 37 15 32 25 25 17 39 18 10 38 46  8 20\n",
+      " 35 38 45 18 41 26 10 31 49 38 35 27 48  9 41 32 22 28 46 36]\n"
+     ]
+    }
+   ],
+   "source": [
+    "array_dan500 = np.random.randint(5, 50, 500)\n",
+    "print(array_dan500)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 191,
+   "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>Coluna500</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>28</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>7</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>36</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>19</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>6</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>...</th>\n",
+       "      <td>...</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>495</th>\n",
+       "      <td>32</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>496</th>\n",
+       "      <td>22</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>497</th>\n",
+       "      <td>28</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>498</th>\n",
+       "      <td>46</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>499</th>\n",
+       "      <td>36</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "<p>500 rows × 1 columns</p>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "     Coluna500\n",
+       "0           28\n",
+       "1            7\n",
+       "2           36\n",
+       "3           19\n",
+       "4            6\n",
+       "..         ...\n",
+       "495         32\n",
+       "496         22\n",
+       "497         28\n",
+       "498         46\n",
+       "499         36\n",
+       "\n",
+       "[500 rows x 1 columns]"
+      ]
+     },
+     "execution_count": 191,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "df_500 = pd.DataFrame({'Coluna500': array_dan500})\n",
+    "df_500\n"
+   ]
+  }
+ ],
+ "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": "3.11.4"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 2
+}
diff --git a/exercicios/para-sala/titanic.csv b/exercicios/para-sala/titanic.csv
new file mode 100644
index 0000000..5cc466e
--- /dev/null
+++ b/exercicios/para-sala/titanic.csv
@@ -0,0 +1,892 @@
+PassengerId,Survived,Pclass,Name,Sex,Age,SibSp,Parch,Ticket,Fare,Cabin,Embarked
+1,0,3,"Braund, Mr. Owen Harris",male,22,1,0,A/5 21171,7.25,,S
+2,1,1,"Cumings, Mrs. John Bradley (Florence Briggs Thayer)",female,38,1,0,PC 17599,71.2833,C85,C
+3,1,3,"Heikkinen, Miss. Laina",female,26,0,0,STON/O2. 3101282,7.925,,S
+4,1,1,"Futrelle, Mrs. Jacques Heath (Lily May Peel)",female,35,1,0,113803,53.1,C123,S
+5,0,3,"Allen, Mr. William Henry",male,35,0,0,373450,8.05,,S
+6,0,3,"Moran, Mr. James",male,,0,0,330877,8.4583,,Q
+7,0,1,"McCarthy, Mr. Timothy J",male,54,0,0,17463,51.8625,E46,S
+8,0,3,"Palsson, Master. Gosta Leonard",male,2,3,1,349909,21.075,,S
+9,1,3,"Johnson, Mrs. Oscar W (Elisabeth Vilhelmina Berg)",female,27,0,2,347742,11.1333,,S
+10,1,2,"Nasser, Mrs. Nicholas (Adele Achem)",female,14,1,0,237736,30.0708,,C
+11,1,3,"Sandstrom, Miss. Marguerite Rut",female,4,1,1,PP 9549,16.7,G6,S
+12,1,1,"Bonnell, Miss. Elizabeth",female,58,0,0,113783,26.55,C103,S
+13,0,3,"Saundercock, Mr. William Henry",male,20,0,0,A/5. 2151,8.05,,S
+14,0,3,"Andersson, Mr. Anders Johan",male,39,1,5,347082,31.275,,S
+15,0,3,"Vestrom, Miss. Hulda Amanda Adolfina",female,14,0,0,350406,7.8542,,S
+16,1,2,"Hewlett, Mrs. (Mary D Kingcome) ",female,55,0,0,248706,16,,S
+17,0,3,"Rice, Master. Eugene",male,2,4,1,382652,29.125,,Q
+18,1,2,"Williams, Mr. Charles Eugene",male,,0,0,244373,13,,S
+19,0,3,"Vander Planke, Mrs. Julius (Emelia Maria Vandemoortele)",female,31,1,0,345763,18,,S
+20,1,3,"Masselmani, Mrs. Fatima",female,,0,0,2649,7.225,,C
+21,0,2,"Fynney, Mr. Joseph J",male,35,0,0,239865,26,,S
+22,1,2,"Beesley, Mr. Lawrence",male,34,0,0,248698,13,D56,S
+23,1,3,"McGowan, Miss. Anna ""Annie""",female,15,0,0,330923,8.0292,,Q
+24,1,1,"Sloper, Mr. William Thompson",male,28,0,0,113788,35.5,A6,S
+25,0,3,"Palsson, Miss. Torborg Danira",female,8,3,1,349909,21.075,,S
+26,1,3,"Asplund, Mrs. Carl Oscar (Selma Augusta Emilia Johansson)",female,38,1,5,347077,31.3875,,S
+27,0,3,"Emir, Mr. Farred Chehab",male,,0,0,2631,7.225,,C
+28,0,1,"Fortune, Mr. Charles Alexander",male,19,3,2,19950,263,C23 C25 C27,S
+29,1,3,"O'Dwyer, Miss. Ellen ""Nellie""",female,,0,0,330959,7.8792,,Q
+30,0,3,"Todoroff, Mr. Lalio",male,,0,0,349216,7.8958,,S
+31,0,1,"Uruchurtu, Don. Manuel E",male,40,0,0,PC 17601,27.7208,,C
+32,1,1,"Spencer, Mrs. William Augustus (Marie Eugenie)",female,,1,0,PC 17569,146.5208,B78,C
+33,1,3,"Glynn, Miss. Mary Agatha",female,,0,0,335677,7.75,,Q
+34,0,2,"Wheadon, Mr. Edward H",male,66,0,0,C.A. 24579,10.5,,S
+35,0,1,"Meyer, Mr. Edgar Joseph",male,28,1,0,PC 17604,82.1708,,C
+36,0,1,"Holverson, Mr. Alexander Oskar",male,42,1,0,113789,52,,S
+37,1,3,"Mamee, Mr. Hanna",male,,0,0,2677,7.2292,,C
+38,0,3,"Cann, Mr. Ernest Charles",male,21,0,0,A./5. 2152,8.05,,S
+39,0,3,"Vander Planke, Miss. Augusta Maria",female,18,2,0,345764,18,,S
+40,1,3,"Nicola-Yarred, Miss. Jamila",female,14,1,0,2651,11.2417,,C
+41,0,3,"Ahlin, Mrs. Johan (Johanna Persdotter Larsson)",female,40,1,0,7546,9.475,,S
+42,0,2,"Turpin, Mrs. William John Robert (Dorothy Ann Wonnacott)",female,27,1,0,11668,21,,S
+43,0,3,"Kraeff, Mr. Theodor",male,,0,0,349253,7.8958,,C
+44,1,2,"Laroche, Miss. Simonne Marie Anne Andree",female,3,1,2,SC/Paris 2123,41.5792,,C
+45,1,3,"Devaney, Miss. Margaret Delia",female,19,0,0,330958,7.8792,,Q
+46,0,3,"Rogers, Mr. William John",male,,0,0,S.C./A.4. 23567,8.05,,S
+47,0,3,"Lennon, Mr. Denis",male,,1,0,370371,15.5,,Q
+48,1,3,"O'Driscoll, Miss. Bridget",female,,0,0,14311,7.75,,Q
+49,0,3,"Samaan, Mr. Youssef",male,,2,0,2662,21.6792,,C
+50,0,3,"Arnold-Franchi, Mrs. Josef (Josefine Franchi)",female,18,1,0,349237,17.8,,S
+51,0,3,"Panula, Master. Juha Niilo",male,7,4,1,3101295,39.6875,,S
+52,0,3,"Nosworthy, Mr. Richard Cater",male,21,0,0,A/4. 39886,7.8,,S
+53,1,1,"Harper, Mrs. Henry Sleeper (Myna Haxtun)",female,49,1,0,PC 17572,76.7292,D33,C
+54,1,2,"Faunthorpe, Mrs. Lizzie (Elizabeth Anne Wilkinson)",female,29,1,0,2926,26,,S
+55,0,1,"Ostby, Mr. Engelhart Cornelius",male,65,0,1,113509,61.9792,B30,C
+56,1,1,"Woolner, Mr. Hugh",male,,0,0,19947,35.5,C52,S
+57,1,2,"Rugg, Miss. Emily",female,21,0,0,C.A. 31026,10.5,,S
+58,0,3,"Novel, Mr. Mansouer",male,28.5,0,0,2697,7.2292,,C
+59,1,2,"West, Miss. Constance Mirium",female,5,1,2,C.A. 34651,27.75,,S
+60,0,3,"Goodwin, Master. William Frederick",male,11,5,2,CA 2144,46.9,,S
+61,0,3,"Sirayanian, Mr. Orsen",male,22,0,0,2669,7.2292,,C
+62,1,1,"Icard, Miss. Amelie",female,38,0,0,113572,80,B28,
+63,0,1,"Harris, Mr. Henry Birkhardt",male,45,1,0,36973,83.475,C83,S
+64,0,3,"Skoog, Master. Harald",male,4,3,2,347088,27.9,,S
+65,0,1,"Stewart, Mr. Albert A",male,,0,0,PC 17605,27.7208,,C
+66,1,3,"Moubarek, Master. Gerios",male,,1,1,2661,15.2458,,C
+67,1,2,"Nye, Mrs. (Elizabeth Ramell)",female,29,0,0,C.A. 29395,10.5,F33,S
+68,0,3,"Crease, Mr. Ernest James",male,19,0,0,S.P. 3464,8.1583,,S
+69,1,3,"Andersson, Miss. Erna Alexandra",female,17,4,2,3101281,7.925,,S
+70,0,3,"Kink, Mr. Vincenz",male,26,2,0,315151,8.6625,,S
+71,0,2,"Jenkin, Mr. Stephen Curnow",male,32,0,0,C.A. 33111,10.5,,S
+72,0,3,"Goodwin, Miss. Lillian Amy",female,16,5,2,CA 2144,46.9,,S
+73,0,2,"Hood, Mr. Ambrose Jr",male,21,0,0,S.O.C. 14879,73.5,,S
+74,0,3,"Chronopoulos, Mr. Apostolos",male,26,1,0,2680,14.4542,,C
+75,1,3,"Bing, Mr. Lee",male,32,0,0,1601,56.4958,,S
+76,0,3,"Moen, Mr. Sigurd Hansen",male,25,0,0,348123,7.65,F G73,S
+77,0,3,"Staneff, Mr. Ivan",male,,0,0,349208,7.8958,,S
+78,0,3,"Moutal, Mr. Rahamin Haim",male,,0,0,374746,8.05,,S
+79,1,2,"Caldwell, Master. Alden Gates",male,0.83,0,2,248738,29,,S
+80,1,3,"Dowdell, Miss. Elizabeth",female,30,0,0,364516,12.475,,S
+81,0,3,"Waelens, Mr. Achille",male,22,0,0,345767,9,,S
+82,1,3,"Sheerlinck, Mr. Jan Baptist",male,29,0,0,345779,9.5,,S
+83,1,3,"McDermott, Miss. Brigdet Delia",female,,0,0,330932,7.7875,,Q
+84,0,1,"Carrau, Mr. Francisco M",male,28,0,0,113059,47.1,,S
+85,1,2,"Ilett, Miss. Bertha",female,17,0,0,SO/C 14885,10.5,,S
+86,1,3,"Backstrom, Mrs. Karl Alfred (Maria Mathilda Gustafsson)",female,33,3,0,3101278,15.85,,S
+87,0,3,"Ford, Mr. William Neal",male,16,1,3,W./C. 6608,34.375,,S
+88,0,3,"Slocovski, Mr. Selman Francis",male,,0,0,SOTON/OQ 392086,8.05,,S
+89,1,1,"Fortune, Miss. Mabel Helen",female,23,3,2,19950,263,C23 C25 C27,S
+90,0,3,"Celotti, Mr. Francesco",male,24,0,0,343275,8.05,,S
+91,0,3,"Christmann, Mr. Emil",male,29,0,0,343276,8.05,,S
+92,0,3,"Andreasson, Mr. Paul Edvin",male,20,0,0,347466,7.8542,,S
+93,0,1,"Chaffee, Mr. Herbert Fuller",male,46,1,0,W.E.P. 5734,61.175,E31,S
+94,0,3,"Dean, Mr. Bertram Frank",male,26,1,2,C.A. 2315,20.575,,S
+95,0,3,"Coxon, Mr. Daniel",male,59,0,0,364500,7.25,,S
+96,0,3,"Shorney, Mr. Charles Joseph",male,,0,0,374910,8.05,,S
+97,0,1,"Goldschmidt, Mr. George B",male,71,0,0,PC 17754,34.6542,A5,C
+98,1,1,"Greenfield, Mr. William Bertram",male,23,0,1,PC 17759,63.3583,D10 D12,C
+99,1,2,"Doling, Mrs. John T (Ada Julia Bone)",female,34,0,1,231919,23,,S
+100,0,2,"Kantor, Mr. Sinai",male,34,1,0,244367,26,,S
+101,0,3,"Petranec, Miss. Matilda",female,28,0,0,349245,7.8958,,S
+102,0,3,"Petroff, Mr. Pastcho (""Pentcho"")",male,,0,0,349215,7.8958,,S
+103,0,1,"White, Mr. Richard Frasar",male,21,0,1,35281,77.2875,D26,S
+104,0,3,"Johansson, Mr. Gustaf Joel",male,33,0,0,7540,8.6542,,S
+105,0,3,"Gustafsson, Mr. Anders Vilhelm",male,37,2,0,3101276,7.925,,S
+106,0,3,"Mionoff, Mr. Stoytcho",male,28,0,0,349207,7.8958,,S
+107,1,3,"Salkjelsvik, Miss. Anna Kristine",female,21,0,0,343120,7.65,,S
+108,1,3,"Moss, Mr. Albert Johan",male,,0,0,312991,7.775,,S
+109,0,3,"Rekic, Mr. Tido",male,38,0,0,349249,7.8958,,S
+110,1,3,"Moran, Miss. Bertha",female,,1,0,371110,24.15,,Q
+111,0,1,"Porter, Mr. Walter Chamberlain",male,47,0,0,110465,52,C110,S
+112,0,3,"Zabour, Miss. Hileni",female,14.5,1,0,2665,14.4542,,C
+113,0,3,"Barton, Mr. David John",male,22,0,0,324669,8.05,,S
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+777,0,3,"Tobin, Mr. Roger",male,,0,0,383121,7.75,F38,Q
+778,1,3,"Emanuel, Miss. Virginia Ethel",female,5,0,0,364516,12.475,,S
+779,0,3,"Kilgannon, Mr. Thomas J",male,,0,0,36865,7.7375,,Q
+780,1,1,"Robert, Mrs. Edward Scott (Elisabeth Walton McMillan)",female,43,0,1,24160,211.3375,B3,S
+781,1,3,"Ayoub, Miss. Banoura",female,13,0,0,2687,7.2292,,C
+782,1,1,"Dick, Mrs. Albert Adrian (Vera Gillespie)",female,17,1,0,17474,57,B20,S
+783,0,1,"Long, Mr. Milton Clyde",male,29,0,0,113501,30,D6,S
+784,0,3,"Johnston, Mr. Andrew G",male,,1,2,W./C. 6607,23.45,,S
+785,0,3,"Ali, Mr. William",male,25,0,0,SOTON/O.Q. 3101312,7.05,,S
+786,0,3,"Harmer, Mr. Abraham (David Lishin)",male,25,0,0,374887,7.25,,S
+787,1,3,"Sjoblom, Miss. Anna Sofia",female,18,0,0,3101265,7.4958,,S
+788,0,3,"Rice, Master. George Hugh",male,8,4,1,382652,29.125,,Q
+789,1,3,"Dean, Master. Bertram Vere",male,1,1,2,C.A. 2315,20.575,,S
+790,0,1,"Guggenheim, Mr. Benjamin",male,46,0,0,PC 17593,79.2,B82 B84,C
+791,0,3,"Keane, Mr. Andrew ""Andy""",male,,0,0,12460,7.75,,Q
+792,0,2,"Gaskell, Mr. Alfred",male,16,0,0,239865,26,,S
+793,0,3,"Sage, Miss. Stella Anna",female,,8,2,CA. 2343,69.55,,S
+794,0,1,"Hoyt, Mr. William Fisher",male,,0,0,PC 17600,30.6958,,C
+795,0,3,"Dantcheff, Mr. Ristiu",male,25,0,0,349203,7.8958,,S
+796,0,2,"Otter, Mr. Richard",male,39,0,0,28213,13,,S
+797,1,1,"Leader, Dr. Alice (Farnham)",female,49,0,0,17465,25.9292,D17,S
+798,1,3,"Osman, Mrs. Mara",female,31,0,0,349244,8.6833,,S
+799,0,3,"Ibrahim Shawah, Mr. Yousseff",male,30,0,0,2685,7.2292,,C
+800,0,3,"Van Impe, Mrs. Jean Baptiste (Rosalie Paula Govaert)",female,30,1,1,345773,24.15,,S
+801,0,2,"Ponesell, Mr. Martin",male,34,0,0,250647,13,,S
+802,1,2,"Collyer, Mrs. Harvey (Charlotte Annie Tate)",female,31,1,1,C.A. 31921,26.25,,S
+803,1,1,"Carter, Master. William Thornton II",male,11,1,2,113760,120,B96 B98,S
+804,1,3,"Thomas, Master. Assad Alexander",male,0.42,0,1,2625,8.5167,,C
+805,1,3,"Hedman, Mr. Oskar Arvid",male,27,0,0,347089,6.975,,S
+806,0,3,"Johansson, Mr. Karl Johan",male,31,0,0,347063,7.775,,S
+807,0,1,"Andrews, Mr. Thomas Jr",male,39,0,0,112050,0,A36,S
+808,0,3,"Pettersson, Miss. Ellen Natalia",female,18,0,0,347087,7.775,,S
+809,0,2,"Meyer, Mr. August",male,39,0,0,248723,13,,S
+810,1,1,"Chambers, Mrs. Norman Campbell (Bertha Griggs)",female,33,1,0,113806,53.1,E8,S
+811,0,3,"Alexander, Mr. William",male,26,0,0,3474,7.8875,,S
+812,0,3,"Lester, Mr. James",male,39,0,0,A/4 48871,24.15,,S
+813,0,2,"Slemen, Mr. Richard James",male,35,0,0,28206,10.5,,S
+814,0,3,"Andersson, Miss. Ebba Iris Alfrida",female,6,4,2,347082,31.275,,S
+815,0,3,"Tomlin, Mr. Ernest Portage",male,30.5,0,0,364499,8.05,,S
+816,0,1,"Fry, Mr. Richard",male,,0,0,112058,0,B102,S
+817,0,3,"Heininen, Miss. Wendla Maria",female,23,0,0,STON/O2. 3101290,7.925,,S
+818,0,2,"Mallet, Mr. Albert",male,31,1,1,S.C./PARIS 2079,37.0042,,C
+819,0,3,"Holm, Mr. John Fredrik Alexander",male,43,0,0,C 7075,6.45,,S
+820,0,3,"Skoog, Master. Karl Thorsten",male,10,3,2,347088,27.9,,S
+821,1,1,"Hays, Mrs. Charles Melville (Clara Jennings Gregg)",female,52,1,1,12749,93.5,B69,S
+822,1,3,"Lulic, Mr. Nikola",male,27,0,0,315098,8.6625,,S
+823,0,1,"Reuchlin, Jonkheer. John George",male,38,0,0,19972,0,,S
+824,1,3,"Moor, Mrs. (Beila)",female,27,0,1,392096,12.475,E121,S
+825,0,3,"Panula, Master. Urho Abraham",male,2,4,1,3101295,39.6875,,S
+826,0,3,"Flynn, Mr. John",male,,0,0,368323,6.95,,Q
+827,0,3,"Lam, Mr. Len",male,,0,0,1601,56.4958,,S
+828,1,2,"Mallet, Master. Andre",male,1,0,2,S.C./PARIS 2079,37.0042,,C
+829,1,3,"McCormack, Mr. Thomas Joseph",male,,0,0,367228,7.75,,Q
+830,1,1,"Stone, Mrs. George Nelson (Martha Evelyn)",female,62,0,0,113572,80,B28,
+831,1,3,"Yasbeck, Mrs. Antoni (Selini Alexander)",female,15,1,0,2659,14.4542,,C
+832,1,2,"Richards, Master. George Sibley",male,0.83,1,1,29106,18.75,,S
+833,0,3,"Saad, Mr. Amin",male,,0,0,2671,7.2292,,C
+834,0,3,"Augustsson, Mr. Albert",male,23,0,0,347468,7.8542,,S
+835,0,3,"Allum, Mr. Owen George",male,18,0,0,2223,8.3,,S
+836,1,1,"Compton, Miss. Sara Rebecca",female,39,1,1,PC 17756,83.1583,E49,C
+837,0,3,"Pasic, Mr. Jakob",male,21,0,0,315097,8.6625,,S
+838,0,3,"Sirota, Mr. Maurice",male,,0,0,392092,8.05,,S
+839,1,3,"Chip, Mr. Chang",male,32,0,0,1601,56.4958,,S
+840,1,1,"Marechal, Mr. Pierre",male,,0,0,11774,29.7,C47,C
+841,0,3,"Alhomaki, Mr. Ilmari Rudolf",male,20,0,0,SOTON/O2 3101287,7.925,,S
+842,0,2,"Mudd, Mr. Thomas Charles",male,16,0,0,S.O./P.P. 3,10.5,,S
+843,1,1,"Serepeca, Miss. Augusta",female,30,0,0,113798,31,,C
+844,0,3,"Lemberopolous, Mr. Peter L",male,34.5,0,0,2683,6.4375,,C
+845,0,3,"Culumovic, Mr. Jeso",male,17,0,0,315090,8.6625,,S
+846,0,3,"Abbing, Mr. Anthony",male,42,0,0,C.A. 5547,7.55,,S
+847,0,3,"Sage, Mr. Douglas Bullen",male,,8,2,CA. 2343,69.55,,S
+848,0,3,"Markoff, Mr. Marin",male,35,0,0,349213,7.8958,,C
+849,0,2,"Harper, Rev. John",male,28,0,1,248727,33,,S
+850,1,1,"Goldenberg, Mrs. Samuel L (Edwiga Grabowska)",female,,1,0,17453,89.1042,C92,C
+851,0,3,"Andersson, Master. Sigvard Harald Elias",male,4,4,2,347082,31.275,,S
+852,0,3,"Svensson, Mr. Johan",male,74,0,0,347060,7.775,,S
+853,0,3,"Boulos, Miss. Nourelain",female,9,1,1,2678,15.2458,,C
+854,1,1,"Lines, Miss. Mary Conover",female,16,0,1,PC 17592,39.4,D28,S
+855,0,2,"Carter, Mrs. Ernest Courtenay (Lilian Hughes)",female,44,1,0,244252,26,,S
+856,1,3,"Aks, Mrs. Sam (Leah Rosen)",female,18,0,1,392091,9.35,,S
+857,1,1,"Wick, Mrs. George Dennick (Mary Hitchcock)",female,45,1,1,36928,164.8667,,S
+858,1,1,"Daly, Mr. Peter Denis ",male,51,0,0,113055,26.55,E17,S
+859,1,3,"Baclini, Mrs. Solomon (Latifa Qurban)",female,24,0,3,2666,19.2583,,C
+860,0,3,"Razi, Mr. Raihed",male,,0,0,2629,7.2292,,C
+861,0,3,"Hansen, Mr. Claus Peter",male,41,2,0,350026,14.1083,,S
+862,0,2,"Giles, Mr. Frederick Edward",male,21,1,0,28134,11.5,,S
+863,1,1,"Swift, Mrs. Frederick Joel (Margaret Welles Barron)",female,48,0,0,17466,25.9292,D17,S
+864,0,3,"Sage, Miss. Dorothy Edith ""Dolly""",female,,8,2,CA. 2343,69.55,,S
+865,0,2,"Gill, Mr. John William",male,24,0,0,233866,13,,S
+866,1,2,"Bystrom, Mrs. (Karolina)",female,42,0,0,236852,13,,S
+867,1,2,"Duran y More, Miss. Asuncion",female,27,1,0,SC/PARIS 2149,13.8583,,C
+868,0,1,"Roebling, Mr. Washington Augustus II",male,31,0,0,PC 17590,50.4958,A24,S
+869,0,3,"van Melkebeke, Mr. Philemon",male,,0,0,345777,9.5,,S
+870,1,3,"Johnson, Master. Harold Theodor",male,4,1,1,347742,11.1333,,S
+871,0,3,"Balkic, Mr. Cerin",male,26,0,0,349248,7.8958,,S
+872,1,1,"Beckwith, Mrs. Richard Leonard (Sallie Monypeny)",female,47,1,1,11751,52.5542,D35,S
+873,0,1,"Carlsson, Mr. Frans Olof",male,33,0,0,695,5,B51 B53 B55,S
+874,0,3,"Vander Cruyssen, Mr. Victor",male,47,0,0,345765,9,,S
+875,1,2,"Abelson, Mrs. Samuel (Hannah Wizosky)",female,28,1,0,P/PP 3381,24,,C
+876,1,3,"Najib, Miss. Adele Kiamie ""Jane""",female,15,0,0,2667,7.225,,C
+877,0,3,"Gustafsson, Mr. Alfred Ossian",male,20,0,0,7534,9.8458,,S
+878,0,3,"Petroff, Mr. Nedelio",male,19,0,0,349212,7.8958,,S
+879,0,3,"Laleff, Mr. Kristo",male,,0,0,349217,7.8958,,S
+880,1,1,"Potter, Mrs. Thomas Jr (Lily Alexenia Wilson)",female,56,0,1,11767,83.1583,C50,C
+881,1,2,"Shelley, Mrs. William (Imanita Parrish Hall)",female,25,0,1,230433,26,,S
+882,0,3,"Markun, Mr. Johann",male,33,0,0,349257,7.8958,,S
+883,0,3,"Dahlberg, Miss. Gerda Ulrika",female,22,0,0,7552,10.5167,,S
+884,0,2,"Banfield, Mr. Frederick James",male,28,0,0,C.A./SOTON 34068,10.5,,S
+885,0,3,"Sutehall, Mr. Henry Jr",male,25,0,0,SOTON/OQ 392076,7.05,,S
+886,0,3,"Rice, Mrs. William (Margaret Norton)",female,39,0,5,382652,29.125,,Q
+887,0,2,"Montvila, Rev. Juozas",male,27,0,0,211536,13,,S
+888,1,1,"Graham, Miss. Margaret Edith",female,19,0,0,112053,30,B42,S
+889,0,3,"Johnston, Miss. Catherine Helen ""Carrie""",female,,1,2,W./C. 6607,23.45,,S
+890,1,1,"Behr, Mr. Karl Howell",male,26,0,0,111369,30,C148,C
+891,0,3,"Dooley, Mr. Patrick",male,32,0,0,370376,7.75,,Q
diff --git a/material/aula_s12.ipynb b/material/aula_s12.ipynb
index 6a3a013..4f2b9d2 100644
--- a/material/aula_s12.ipynb
+++ b/material/aula_s12.ipynb
@@ -114,7 +114,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 1,
+   "execution_count": 9,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -124,7 +124,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 2,
+   "execution_count": 10,
    "metadata": {
     "id": "_eorJ3GNS_mm",
     "outputId": "14f2b233-cc14-4f8a-a041-98b4cb90d2cc"
@@ -379,7 +379,7 @@
        "[891 rows x 12 columns]"
       ]
      },
-     "execution_count": 2,
+     "execution_count": 10,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -401,7 +401,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 3,
+   "execution_count": 11,
    "metadata": {
     "id": "ZuehjTU7S_mt",
     "outputId": "6ce66e1f-01d4-4889-f97f-50d5edae71e6"
@@ -424,7 +424,7 @@
        " 'PortoEmbarcacao']"
       ]
      },
-     "execution_count": 3,
+     "execution_count": 11,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -456,7 +456,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 4,
+   "execution_count": 12,
    "metadata": {
     "id": "h6tvl5HPS_mw",
     "outputId": "4639f186-8484-4780-f4dc-0a29f3cc759e"
@@ -724,7 +724,7 @@
        "[891 rows x 12 columns]"
       ]
      },
-     "execution_count": 4,
+     "execution_count": 12,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -753,7 +753,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 5,
+   "execution_count": 13,
    "metadata": {
     "id": "gZKfzWYAS_mx",
     "outputId": "cdc7a73b-0f3b-42ce-cdf2-f8322b15e686"
@@ -1021,7 +1021,7 @@
        "[891 rows x 12 columns]"
       ]
      },
-     "execution_count": 5,
+     "execution_count": 13,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -1033,7 +1033,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 6,
+   "execution_count": 15,
    "metadata": {},
    "outputs": [
     {
@@ -1073,79 +1073,79 @@
        "  </thead>\n",
        "  <tbody>\n",
        "    <tr>\n",
-       "      <th>1</th>\n",
-       "      <td>2</td>\n",
+       "      <th>7</th>\n",
+       "      <td>8</td>\n",
+       "      <td>0</td>\n",
+       "      <td>3</td>\n",
+       "      <td>Palsson, Master. Gosta Leonard</td>\n",
+       "      <td>male</td>\n",
+       "      <td>2.0</td>\n",
+       "      <td>3</td>\n",
        "      <td>1</td>\n",
+       "      <td>349909</td>\n",
+       "      <td>21.0750</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>S</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>9</th>\n",
+       "      <td>10</td>\n",
        "      <td>1</td>\n",
-       "      <td>Cumings, Mrs. John Bradley (Florence Briggs Th...</td>\n",
+       "      <td>2</td>\n",
+       "      <td>Nasser, Mrs. Nicholas (Adele Achem)</td>\n",
        "      <td>female</td>\n",
-       "      <td>38.0</td>\n",
+       "      <td>14.0</td>\n",
        "      <td>1</td>\n",
        "      <td>0</td>\n",
-       "      <td>PC 17599</td>\n",
-       "      <td>71.2833</td>\n",
-       "      <td>C85</td>\n",
+       "      <td>237736</td>\n",
+       "      <td>30.0708</td>\n",
+       "      <td>NaN</td>\n",
        "      <td>C</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>3</th>\n",
-       "      <td>4</td>\n",
-       "      <td>1</td>\n",
+       "      <th>10</th>\n",
+       "      <td>11</td>\n",
        "      <td>1</td>\n",
-       "      <td>Futrelle, Mrs. Jacques Heath (Lily May Peel)</td>\n",
+       "      <td>3</td>\n",
+       "      <td>Sandstrom, Miss. Marguerite Rut</td>\n",
        "      <td>female</td>\n",
-       "      <td>35.0</td>\n",
+       "      <td>4.0</td>\n",
        "      <td>1</td>\n",
-       "      <td>0</td>\n",
-       "      <td>113803</td>\n",
-       "      <td>53.1000</td>\n",
-       "      <td>C123</td>\n",
+       "      <td>1</td>\n",
+       "      <td>PP 9549</td>\n",
+       "      <td>16.7000</td>\n",
+       "      <td>G6</td>\n",
        "      <td>S</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>4</th>\n",
-       "      <td>5</td>\n",
+       "      <th>14</th>\n",
+       "      <td>15</td>\n",
        "      <td>0</td>\n",
        "      <td>3</td>\n",
-       "      <td>Allen, Mr. William Henry</td>\n",
-       "      <td>male</td>\n",
-       "      <td>35.0</td>\n",
+       "      <td>Vestrom, Miss. Hulda Amanda Adolfina</td>\n",
+       "      <td>female</td>\n",
+       "      <td>14.0</td>\n",
        "      <td>0</td>\n",
        "      <td>0</td>\n",
-       "      <td>373450</td>\n",
-       "      <td>8.0500</td>\n",
+       "      <td>350406</td>\n",
+       "      <td>7.8542</td>\n",
        "      <td>NaN</td>\n",
        "      <td>S</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>6</th>\n",
-       "      <td>7</td>\n",
+       "      <th>16</th>\n",
+       "      <td>17</td>\n",
        "      <td>0</td>\n",
-       "      <td>1</td>\n",
-       "      <td>McCarthy, Mr. Timothy J</td>\n",
+       "      <td>3</td>\n",
+       "      <td>Rice, Master. Eugene</td>\n",
        "      <td>male</td>\n",
-       "      <td>54.0</td>\n",
-       "      <td>0</td>\n",
-       "      <td>0</td>\n",
-       "      <td>17463</td>\n",
-       "      <td>51.8625</td>\n",
-       "      <td>E46</td>\n",
-       "      <td>S</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>11</th>\n",
-       "      <td>12</td>\n",
-       "      <td>1</td>\n",
+       "      <td>2.0</td>\n",
+       "      <td>4</td>\n",
        "      <td>1</td>\n",
-       "      <td>Bonnell, Miss. Elizabeth</td>\n",
-       "      <td>female</td>\n",
-       "      <td>58.0</td>\n",
-       "      <td>0</td>\n",
-       "      <td>0</td>\n",
-       "      <td>113783</td>\n",
-       "      <td>26.5500</td>\n",
-       "      <td>C103</td>\n",
-       "      <td>S</td>\n",
+       "      <td>382652</td>\n",
+       "      <td>29.1250</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>Q</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>...</th>\n",
@@ -1163,153 +1163,140 @@
        "      <td>...</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>873</th>\n",
-       "      <td>874</td>\n",
+       "      <th>850</th>\n",
+       "      <td>851</td>\n",
        "      <td>0</td>\n",
        "      <td>3</td>\n",
-       "      <td>Vander Cruyssen, Mr. Victor</td>\n",
+       "      <td>Andersson, Master. Sigvard Harald Elias</td>\n",
        "      <td>male</td>\n",
-       "      <td>47.0</td>\n",
-       "      <td>0</td>\n",
-       "      <td>0</td>\n",
-       "      <td>345765</td>\n",
-       "      <td>9.0000</td>\n",
+       "      <td>4.0</td>\n",
+       "      <td>4</td>\n",
+       "      <td>2</td>\n",
+       "      <td>347082</td>\n",
+       "      <td>31.2750</td>\n",
        "      <td>NaN</td>\n",
        "      <td>S</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>879</th>\n",
-       "      <td>880</td>\n",
+       "      <th>852</th>\n",
+       "      <td>853</td>\n",
+       "      <td>0</td>\n",
+       "      <td>3</td>\n",
+       "      <td>Boulos, Miss. Nourelain</td>\n",
+       "      <td>female</td>\n",
+       "      <td>9.0</td>\n",
        "      <td>1</td>\n",
        "      <td>1</td>\n",
-       "      <td>Potter, Mrs. Thomas Jr (Lily Alexenia Wilson)</td>\n",
+       "      <td>2678</td>\n",
+       "      <td>15.2458</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>C</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>853</th>\n",
+       "      <td>854</td>\n",
+       "      <td>1</td>\n",
+       "      <td>1</td>\n",
+       "      <td>Lines, Miss. Mary Conover</td>\n",
        "      <td>female</td>\n",
-       "      <td>56.0</td>\n",
+       "      <td>16.0</td>\n",
        "      <td>0</td>\n",
        "      <td>1</td>\n",
-       "      <td>11767</td>\n",
-       "      <td>83.1583</td>\n",
-       "      <td>C50</td>\n",
-       "      <td>C</td>\n",
+       "      <td>PC 17592</td>\n",
+       "      <td>39.4000</td>\n",
+       "      <td>D28</td>\n",
+       "      <td>S</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>881</th>\n",
-       "      <td>882</td>\n",
-       "      <td>0</td>\n",
+       "      <th>869</th>\n",
+       "      <td>870</td>\n",
+       "      <td>1</td>\n",
        "      <td>3</td>\n",
-       "      <td>Markun, Mr. Johann</td>\n",
+       "      <td>Johnson, Master. Harold Theodor</td>\n",
        "      <td>male</td>\n",
-       "      <td>33.0</td>\n",
-       "      <td>0</td>\n",
-       "      <td>0</td>\n",
-       "      <td>349257</td>\n",
-       "      <td>7.8958</td>\n",
+       "      <td>4.0</td>\n",
+       "      <td>1</td>\n",
+       "      <td>1</td>\n",
+       "      <td>347742</td>\n",
+       "      <td>11.1333</td>\n",
        "      <td>NaN</td>\n",
        "      <td>S</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>885</th>\n",
-       "      <td>886</td>\n",
-       "      <td>0</td>\n",
+       "      <th>875</th>\n",
+       "      <td>876</td>\n",
+       "      <td>1</td>\n",
        "      <td>3</td>\n",
-       "      <td>Rice, Mrs. William (Margaret Norton)</td>\n",
+       "      <td>Najib, Miss. Adele Kiamie \"Jane\"</td>\n",
        "      <td>female</td>\n",
-       "      <td>39.0</td>\n",
-       "      <td>0</td>\n",
-       "      <td>5</td>\n",
-       "      <td>382652</td>\n",
-       "      <td>29.1250</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>Q</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>890</th>\n",
-       "      <td>891</td>\n",
-       "      <td>0</td>\n",
-       "      <td>3</td>\n",
-       "      <td>Dooley, Mr. Patrick</td>\n",
-       "      <td>male</td>\n",
-       "      <td>32.0</td>\n",
+       "      <td>15.0</td>\n",
        "      <td>0</td>\n",
        "      <td>0</td>\n",
-       "      <td>370376</td>\n",
-       "      <td>7.7500</td>\n",
+       "      <td>2667</td>\n",
+       "      <td>7.2250</td>\n",
        "      <td>NaN</td>\n",
-       "      <td>Q</td>\n",
+       "      <td>C</td>\n",
        "    </tr>\n",
        "  </tbody>\n",
        "</table>\n",
-       "<p>305 rows × 12 columns</p>\n",
+       "<p>113 rows × 12 columns</p>\n",
        "</div>"
       ],
       "text/plain": [
        "     IdPassageiro  Sobreviveu  Classe  \\\n",
-       "1               2           1       1   \n",
-       "3               4           1       1   \n",
-       "4               5           0       3   \n",
-       "6               7           0       1   \n",
-       "11             12           1       1   \n",
+       "7               8           0       3   \n",
+       "9              10           1       2   \n",
+       "10             11           1       3   \n",
+       "14             15           0       3   \n",
+       "16             17           0       3   \n",
        "..            ...         ...     ...   \n",
-       "873           874           0       3   \n",
-       "879           880           1       1   \n",
-       "881           882           0       3   \n",
-       "885           886           0       3   \n",
-       "890           891           0       3   \n",
+       "850           851           0       3   \n",
+       "852           853           0       3   \n",
+       "853           854           1       1   \n",
+       "869           870           1       3   \n",
+       "875           876           1       3   \n",
        "\n",
-       "                                                  Nome    Sexo  Idade  \\\n",
-       "1    Cumings, Mrs. John Bradley (Florence Briggs Th...  female   38.0   \n",
-       "3         Futrelle, Mrs. Jacques Heath (Lily May Peel)  female   35.0   \n",
-       "4                             Allen, Mr. William Henry    male   35.0   \n",
-       "6                              McCarthy, Mr. Timothy J    male   54.0   \n",
-       "11                            Bonnell, Miss. Elizabeth  female   58.0   \n",
-       "..                                                 ...     ...    ...   \n",
-       "873                        Vander Cruyssen, Mr. Victor    male   47.0   \n",
-       "879      Potter, Mrs. Thomas Jr (Lily Alexenia Wilson)  female   56.0   \n",
-       "881                                 Markun, Mr. Johann    male   33.0   \n",
-       "885               Rice, Mrs. William (Margaret Norton)  female   39.0   \n",
-       "890                                Dooley, Mr. Patrick    male   32.0   \n",
+       "                                        Nome    Sexo  Idade  NumeroIrmaos  \\\n",
+       "7             Palsson, Master. Gosta Leonard    male    2.0             3   \n",
+       "9        Nasser, Mrs. Nicholas (Adele Achem)  female   14.0             1   \n",
+       "10           Sandstrom, Miss. Marguerite Rut  female    4.0             1   \n",
+       "14      Vestrom, Miss. Hulda Amanda Adolfina  female   14.0             0   \n",
+       "16                      Rice, Master. Eugene    male    2.0             4   \n",
+       "..                                       ...     ...    ...           ...   \n",
+       "850  Andersson, Master. Sigvard Harald Elias    male    4.0             4   \n",
+       "852                  Boulos, Miss. Nourelain  female    9.0             1   \n",
+       "853                Lines, Miss. Mary Conover  female   16.0             0   \n",
+       "869          Johnson, Master. Harold Theodor    male    4.0             1   \n",
+       "875         Najib, Miss. Adele Kiamie \"Jane\"  female   15.0             0   \n",
        "\n",
-       "     NumeroIrmaos  NumeroPais NumeroTicket  PrecoTicket NumeroCabine  \\\n",
-       "1               1           0     PC 17599      71.2833          C85   \n",
-       "3               1           0       113803      53.1000         C123   \n",
-       "4               0           0       373450       8.0500          NaN   \n",
-       "6               0           0        17463      51.8625          E46   \n",
-       "11              0           0       113783      26.5500         C103   \n",
-       "..            ...         ...          ...          ...          ...   \n",
-       "873             0           0       345765       9.0000          NaN   \n",
-       "879             0           1        11767      83.1583          C50   \n",
-       "881             0           0       349257       7.8958          NaN   \n",
-       "885             0           5       382652      29.1250          NaN   \n",
-       "890             0           0       370376       7.7500          NaN   \n",
-       "\n",
-       "    PortoEmbarcacao  \n",
-       "1                 C  \n",
-       "3                 S  \n",
-       "4                 S  \n",
-       "6                 S  \n",
-       "11                S  \n",
-       "..              ...  \n",
-       "873               S  \n",
-       "879               C  \n",
-       "881               S  \n",
-       "885               Q  \n",
-       "890               Q  \n",
+       "     NumeroPais NumeroTicket  PrecoTicket NumeroCabine PortoEmbarcacao  \n",
+       "7             1       349909      21.0750          NaN               S  \n",
+       "9             0       237736      30.0708          NaN               C  \n",
+       "10            1      PP 9549      16.7000           G6               S  \n",
+       "14            0       350406       7.8542          NaN               S  \n",
+       "16            1       382652      29.1250          NaN               Q  \n",
+       "..          ...          ...          ...          ...             ...  \n",
+       "850           2       347082      31.2750          NaN               S  \n",
+       "852           1         2678      15.2458          NaN               C  \n",
+       "853           1     PC 17592      39.4000          D28               S  \n",
+       "869           1       347742      11.1333          NaN               S  \n",
+       "875           0         2667       7.2250          NaN               C  \n",
        "\n",
-       "[305 rows x 12 columns]"
+       "[113 rows x 12 columns]"
       ]
      },
-     "execution_count": 6,
+     "execution_count": 15,
      "metadata": {},
      "output_type": "execute_result"
     }
    ],
    "source": [
-    "df[df['Idade'] > 30]"
+    "df[df['Idade'] < 18] "
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 7,
+   "execution_count": 28,
    "metadata": {
     "id": "xzHvkQRrS_mx",
     "outputId": "ca4d371d-386e-433d-e49b-6e5a6749f767"
@@ -1321,7 +1308,7 @@
        "(305, 12)"
       ]
      },
-     "execution_count": 7,
+     "execution_count": 28,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -1334,7 +1321,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 8,
+   "execution_count": 17,
    "metadata": {},
    "outputs": [
     {
@@ -1599,7 +1586,7 @@
        "[103 rows x 12 columns]"
       ]
      },
-     "execution_count": 8,
+     "execution_count": 17,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -1635,7 +1622,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 10,
+   "execution_count": 23,
    "metadata": {},
    "outputs": [
     {
@@ -1675,42 +1662,369 @@
        "  </thead>\n",
        "  <tbody>\n",
        "    <tr>\n",
-       "      <th>855</th>\n",
-       "      <td>856</td>\n",
+       "      <th>51</th>\n",
+       "      <td>52</td>\n",
+       "      <td>0</td>\n",
+       "      <td>3</td>\n",
+       "      <td>Nosworthy, Mr. Richard Cater</td>\n",
+       "      <td>male</td>\n",
+       "      <td>21.00</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>A/4. 39886</td>\n",
+       "      <td>7.8000</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>S</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>102</th>\n",
+       "      <td>103</td>\n",
+       "      <td>0</td>\n",
+       "      <td>1</td>\n",
+       "      <td>White, Mr. Richard Frasar</td>\n",
+       "      <td>male</td>\n",
+       "      <td>21.00</td>\n",
+       "      <td>0</td>\n",
+       "      <td>1</td>\n",
+       "      <td>35281</td>\n",
+       "      <td>77.2875</td>\n",
+       "      <td>D26</td>\n",
+       "      <td>S</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>135</th>\n",
+       "      <td>136</td>\n",
+       "      <td>0</td>\n",
+       "      <td>2</td>\n",
+       "      <td>Richard, Mr. Emile</td>\n",
+       "      <td>male</td>\n",
+       "      <td>23.00</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>SC/PARIS 2133</td>\n",
+       "      <td>15.0458</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>C</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>183</th>\n",
+       "      <td>184</td>\n",
+       "      <td>1</td>\n",
+       "      <td>2</td>\n",
+       "      <td>Becker, Master. Richard F</td>\n",
+       "      <td>male</td>\n",
+       "      <td>1.00</td>\n",
+       "      <td>2</td>\n",
+       "      <td>1</td>\n",
+       "      <td>230136</td>\n",
+       "      <td>39.0000</td>\n",
+       "      <td>F4</td>\n",
+       "      <td>S</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>248</th>\n",
+       "      <td>249</td>\n",
+       "      <td>1</td>\n",
+       "      <td>1</td>\n",
+       "      <td>Beckwith, Mr. Richard Leonard</td>\n",
+       "      <td>male</td>\n",
+       "      <td>37.00</td>\n",
+       "      <td>1</td>\n",
+       "      <td>1</td>\n",
+       "      <td>11751</td>\n",
+       "      <td>52.5542</td>\n",
+       "      <td>D35</td>\n",
+       "      <td>S</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>284</th>\n",
+       "      <td>285</td>\n",
+       "      <td>0</td>\n",
+       "      <td>1</td>\n",
+       "      <td>Smith, Mr. Richard William</td>\n",
+       "      <td>male</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>113056</td>\n",
+       "      <td>26.0000</td>\n",
+       "      <td>A19</td>\n",
+       "      <td>S</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>407</th>\n",
+       "      <td>408</td>\n",
        "      <td>1</td>\n",
+       "      <td>2</td>\n",
+       "      <td>Richards, Master. William Rowe</td>\n",
+       "      <td>male</td>\n",
+       "      <td>3.00</td>\n",
+       "      <td>1</td>\n",
+       "      <td>1</td>\n",
+       "      <td>29106</td>\n",
+       "      <td>18.7500</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>S</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>424</th>\n",
+       "      <td>425</td>\n",
+       "      <td>0</td>\n",
        "      <td>3</td>\n",
-       "      <td>Aks, Mrs. Sam (Leah Rosen)</td>\n",
+       "      <td>Rosblom, Mr. Viktor Richard</td>\n",
+       "      <td>male</td>\n",
+       "      <td>18.00</td>\n",
+       "      <td>1</td>\n",
+       "      <td>1</td>\n",
+       "      <td>370129</td>\n",
+       "      <td>20.2125</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>S</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>437</th>\n",
+       "      <td>438</td>\n",
+       "      <td>1</td>\n",
+       "      <td>2</td>\n",
+       "      <td>Richards, Mrs. Sidney (Emily Hocking)</td>\n",
        "      <td>female</td>\n",
-       "      <td>18.0</td>\n",
+       "      <td>24.00</td>\n",
+       "      <td>2</td>\n",
+       "      <td>3</td>\n",
+       "      <td>29106</td>\n",
+       "      <td>18.7500</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>S</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>477</th>\n",
+       "      <td>478</td>\n",
        "      <td>0</td>\n",
+       "      <td>3</td>\n",
+       "      <td>Braund, Mr. Lewis Richard</td>\n",
+       "      <td>male</td>\n",
+       "      <td>29.00</td>\n",
        "      <td>1</td>\n",
-       "      <td>392091</td>\n",
-       "      <td>9.35</td>\n",
+       "      <td>0</td>\n",
+       "      <td>3460</td>\n",
+       "      <td>7.0458</td>\n",
        "      <td>NaN</td>\n",
        "      <td>S</td>\n",
        "    </tr>\n",
+       "    <tr>\n",
+       "      <th>482</th>\n",
+       "      <td>483</td>\n",
+       "      <td>0</td>\n",
+       "      <td>3</td>\n",
+       "      <td>Rouse, Mr. Richard Henry</td>\n",
+       "      <td>male</td>\n",
+       "      <td>50.00</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>A/5 3594</td>\n",
+       "      <td>8.0500</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>S</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>506</th>\n",
+       "      <td>507</td>\n",
+       "      <td>1</td>\n",
+       "      <td>2</td>\n",
+       "      <td>Quick, Mrs. Frederick Charles (Jane Richards)</td>\n",
+       "      <td>female</td>\n",
+       "      <td>33.00</td>\n",
+       "      <td>0</td>\n",
+       "      <td>2</td>\n",
+       "      <td>26360</td>\n",
+       "      <td>26.0000</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>S</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>529</th>\n",
+       "      <td>530</td>\n",
+       "      <td>0</td>\n",
+       "      <td>2</td>\n",
+       "      <td>Hocking, Mr. Richard George</td>\n",
+       "      <td>male</td>\n",
+       "      <td>23.00</td>\n",
+       "      <td>2</td>\n",
+       "      <td>1</td>\n",
+       "      <td>29104</td>\n",
+       "      <td>11.5000</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>S</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>795</th>\n",
+       "      <td>796</td>\n",
+       "      <td>0</td>\n",
+       "      <td>2</td>\n",
+       "      <td>Otter, Mr. Richard</td>\n",
+       "      <td>male</td>\n",
+       "      <td>39.00</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>28213</td>\n",
+       "      <td>13.0000</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>S</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>812</th>\n",
+       "      <td>813</td>\n",
+       "      <td>0</td>\n",
+       "      <td>2</td>\n",
+       "      <td>Slemen, Mr. Richard James</td>\n",
+       "      <td>male</td>\n",
+       "      <td>35.00</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>28206</td>\n",
+       "      <td>10.5000</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>S</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>815</th>\n",
+       "      <td>816</td>\n",
+       "      <td>0</td>\n",
+       "      <td>1</td>\n",
+       "      <td>Fry, Mr. Richard</td>\n",
+       "      <td>male</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>112058</td>\n",
+       "      <td>0.0000</td>\n",
+       "      <td>B102</td>\n",
+       "      <td>S</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>831</th>\n",
+       "      <td>832</td>\n",
+       "      <td>1</td>\n",
+       "      <td>2</td>\n",
+       "      <td>Richards, Master. George Sibley</td>\n",
+       "      <td>male</td>\n",
+       "      <td>0.83</td>\n",
+       "      <td>1</td>\n",
+       "      <td>1</td>\n",
+       "      <td>29106</td>\n",
+       "      <td>18.7500</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>S</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>871</th>\n",
+       "      <td>872</td>\n",
+       "      <td>1</td>\n",
+       "      <td>1</td>\n",
+       "      <td>Beckwith, Mrs. Richard Leonard (Sallie Monypeny)</td>\n",
+       "      <td>female</td>\n",
+       "      <td>47.00</td>\n",
+       "      <td>1</td>\n",
+       "      <td>1</td>\n",
+       "      <td>11751</td>\n",
+       "      <td>52.5542</td>\n",
+       "      <td>D35</td>\n",
+       "      <td>S</td>\n",
+       "    </tr>\n",
        "  </tbody>\n",
        "</table>\n",
        "</div>"
       ],
       "text/plain": [
-       "     IdPassageiro  Sobreviveu  Classe                        Nome    Sexo  \\\n",
-       "855           856           1       3  Aks, Mrs. Sam (Leah Rosen)  female   \n",
+       "     IdPassageiro  Sobreviveu  Classe  \\\n",
+       "51             52           0       3   \n",
+       "102           103           0       1   \n",
+       "135           136           0       2   \n",
+       "183           184           1       2   \n",
+       "248           249           1       1   \n",
+       "284           285           0       1   \n",
+       "407           408           1       2   \n",
+       "424           425           0       3   \n",
+       "437           438           1       2   \n",
+       "477           478           0       3   \n",
+       "482           483           0       3   \n",
+       "506           507           1       2   \n",
+       "529           530           0       2   \n",
+       "795           796           0       2   \n",
+       "812           813           0       2   \n",
+       "815           816           0       1   \n",
+       "831           832           1       2   \n",
+       "871           872           1       1   \n",
+       "\n",
+       "                                                 Nome    Sexo  Idade  \\\n",
+       "51                       Nosworthy, Mr. Richard Cater    male  21.00   \n",
+       "102                         White, Mr. Richard Frasar    male  21.00   \n",
+       "135                                Richard, Mr. Emile    male  23.00   \n",
+       "183                         Becker, Master. Richard F    male   1.00   \n",
+       "248                     Beckwith, Mr. Richard Leonard    male  37.00   \n",
+       "284                        Smith, Mr. Richard William    male    NaN   \n",
+       "407                    Richards, Master. William Rowe    male   3.00   \n",
+       "424                       Rosblom, Mr. Viktor Richard    male  18.00   \n",
+       "437             Richards, Mrs. Sidney (Emily Hocking)  female  24.00   \n",
+       "477                         Braund, Mr. Lewis Richard    male  29.00   \n",
+       "482                          Rouse, Mr. Richard Henry    male  50.00   \n",
+       "506     Quick, Mrs. Frederick Charles (Jane Richards)  female  33.00   \n",
+       "529                       Hocking, Mr. Richard George    male  23.00   \n",
+       "795                                Otter, Mr. Richard    male  39.00   \n",
+       "812                         Slemen, Mr. Richard James    male  35.00   \n",
+       "815                                  Fry, Mr. Richard    male    NaN   \n",
+       "831                   Richards, Master. George Sibley    male   0.83   \n",
+       "871  Beckwith, Mrs. Richard Leonard (Sallie Monypeny)  female  47.00   \n",
        "\n",
-       "     Idade  NumeroIrmaos  NumeroPais NumeroTicket  PrecoTicket NumeroCabine  \\\n",
-       "855   18.0             0           1       392091         9.35          NaN   \n",
+       "     NumeroIrmaos  NumeroPais   NumeroTicket  PrecoTicket NumeroCabine  \\\n",
+       "51              0           0     A/4. 39886       7.8000          NaN   \n",
+       "102             0           1          35281      77.2875          D26   \n",
+       "135             0           0  SC/PARIS 2133      15.0458          NaN   \n",
+       "183             2           1         230136      39.0000           F4   \n",
+       "248             1           1          11751      52.5542          D35   \n",
+       "284             0           0         113056      26.0000          A19   \n",
+       "407             1           1          29106      18.7500          NaN   \n",
+       "424             1           1         370129      20.2125          NaN   \n",
+       "437             2           3          29106      18.7500          NaN   \n",
+       "477             1           0           3460       7.0458          NaN   \n",
+       "482             0           0       A/5 3594       8.0500          NaN   \n",
+       "506             0           2          26360      26.0000          NaN   \n",
+       "529             2           1          29104      11.5000          NaN   \n",
+       "795             0           0          28213      13.0000          NaN   \n",
+       "812             0           0          28206      10.5000          NaN   \n",
+       "815             0           0         112058       0.0000         B102   \n",
+       "831             1           1          29106      18.7500          NaN   \n",
+       "871             1           1          11751      52.5542          D35   \n",
        "\n",
        "    PortoEmbarcacao  \n",
-       "855               S  "
+       "51                S  \n",
+       "102               S  \n",
+       "135               C  \n",
+       "183               S  \n",
+       "248               S  \n",
+       "284               S  \n",
+       "407               S  \n",
+       "424               S  \n",
+       "437               S  \n",
+       "477               S  \n",
+       "482               S  \n",
+       "506               S  \n",
+       "529               S  \n",
+       "795               S  \n",
+       "812               S  \n",
+       "815               S  \n",
+       "831               S  \n",
+       "871               S  "
       ]
      },
-     "execution_count": 10,
+     "execution_count": 23,
      "metadata": {},
      "output_type": "execute_result"
     }
    ],
    "source": [
-    "df[df['Nome'].str.contains('Rose')]"
+    "df_oque_eu_quero = df[df['Nome'].str.contains('Richard')]\n",
+    "df_oque_eu_quero"
    ]
   },
   {
@@ -1861,7 +2175,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 14,
+   "execution_count": 34,
    "metadata": {
     "id": "W-Ktv45VS_mz",
     "outputId": "00f9464e-df1b-4cd2-c0b3-30eac23016f1"
@@ -1873,7 +2187,7 @@
        "(491, 12)"
       ]
      },
-     "execution_count": 14,
+     "execution_count": 34,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -2514,12 +2828,12 @@
    "source": [
     "### Exercício 04 parte 01\n",
     "\n",
-    "- Realizar filtro com apenas uma única condição;\n",
-    "- Realizar filtro com múltiplas condições;\n",
-    "- Selecionar entradas com string específica;\n",
-    "- Realizar uma consulta passageiros da segunda e terceira classe;\n",
-    "- Obter subamostra do dataset com 30 amostras utilizando o método de slicing;\n",
-    "- Utilizar a função loc para obter a idade e sobrevivência do passageiro;\n"
+    "- Realizar filtro com apenas uma única condição;✅\n",
+    "- Realizar filtro com múltiplas condições;✅\n",
+    "- Selecionar entradas com string específica;✅\n",
+    "- Realizar uma consulta passageiros da segunda e terceira classe;✅\n",
+    "- Obter subamostra do dataset com 30 amostras utilizando o método de slicing;✅\n",
+    "- Utilizar a função loc para obter a idade e sobrevivência do passageiro;✅\n"
    ]
   },
   {
@@ -2583,21 +2897,22 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 21,
+   "execution_count": 1,
    "metadata": {
     "id": "noSCxvLQS_m6",
     "outputId": "fd434c19-19d3-4395-a595-83703e140d1b"
    },
    "outputs": [
     {
-     "data": {
-      "text/plain": [
-       "<pandas.core.groupby.generic.DataFrameGroupBy object at 0x000002BED4E60F50>"
-      ]
-     },
-     "execution_count": 21,
-     "metadata": {},
-     "output_type": "execute_result"
+     "ename": "NameError",
+     "evalue": "name 'df' is not defined",
+     "output_type": "error",
+     "traceback": [
+      "\u001b[1;31m---------------------------------------------------------------------------\u001b[0m",
+      "\u001b[1;31mNameError\u001b[0m                                 Traceback (most recent call last)",
+      "\u001b[1;32mc:\\Users\\Dani Negrão\\estudos\\semana12\\on26-python-s12-pandas-numpy-II\\material\\aula_s12.ipynb Célula 35\u001b[0m line \u001b[0;36m2\n\u001b[0;32m      <a href='vscode-notebook-cell:/c%3A/Users/Dani%20Negr%C3%A3o/estudos/semana12/on26-python-s12-pandas-numpy-II/material/aula_s12.ipynb#X46sZmlsZQ%3D%3D?line=0'>1</a>\u001b[0m \u001b[39m# Agrupar passageiros por classe\u001b[39;00m\n\u001b[1;32m----> <a href='vscode-notebook-cell:/c%3A/Users/Dani%20Negr%C3%A3o/estudos/semana12/on26-python-s12-pandas-numpy-II/material/aula_s12.ipynb#X46sZmlsZQ%3D%3D?line=1'>2</a>\u001b[0m dado_agrupado \u001b[39m=\u001b[39m df\u001b[39m.\u001b[39mgroupby(\u001b[39m'\u001b[39m\u001b[39mClasse\u001b[39m\u001b[39m'\u001b[39m)\n\u001b[0;32m      <a href='vscode-notebook-cell:/c%3A/Users/Dani%20Negr%C3%A3o/estudos/semana12/on26-python-s12-pandas-numpy-II/material/aula_s12.ipynb#X46sZmlsZQ%3D%3D?line=2'>3</a>\u001b[0m dado_agrupado\n",
+      "\u001b[1;31mNameError\u001b[0m: name 'df' is not defined"
+     ]
     }
    ],
    "source": [