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+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Exercício Semana 12 - Igea Martins (feito com Marianna Carvalho)\n",
+    "# Introdução\n",
+    "\n",
+    "O dataset 'titanic.csv' foi retirado do Kaggle e apresenta dados simples sobre os passageiros do Titanic. É uma coleção que contém informações sobre passageiros a bordo do famoso navio Titanic. Inclui variáveis como idade, classe social, sexo e sobrevivência, permitindo análises exploratórias e modelagem preditiva. "
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>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",
+       "      <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": [
+       "     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": 2,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "#Dataframe original\n",
+    "\n",
+    "import pandas as pd\n",
+    "import matplotlib.pyplot as plt\n",
+    "\n",
+    "df = pd.read_csv(\"titanic.csv\")\n",
+    "df"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# Processamento"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "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>25%</th>\n",
+       "      <th>50%</th>\n",
+       "      <th>75%</th>\n",
+       "      <th>max</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>PassengerId</th>\n",
+       "      <td>891.0</td>\n",
+       "      <td>446.000000</td>\n",
+       "      <td>257.353842</td>\n",
+       "      <td>1.00</td>\n",
+       "      <td>223.5000</td>\n",
+       "      <td>446.0000</td>\n",
+       "      <td>668.5</td>\n",
+       "      <td>891.0000</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>Survived</th>\n",
+       "      <td>891.0</td>\n",
+       "      <td>0.383838</td>\n",
+       "      <td>0.486592</td>\n",
+       "      <td>0.00</td>\n",
+       "      <td>0.0000</td>\n",
+       "      <td>0.0000</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>1.0000</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>Pclass</th>\n",
+       "      <td>891.0</td>\n",
+       "      <td>2.308642</td>\n",
+       "      <td>0.836071</td>\n",
+       "      <td>1.00</td>\n",
+       "      <td>2.0000</td>\n",
+       "      <td>3.0000</td>\n",
+       "      <td>3.0</td>\n",
+       "      <td>3.0000</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>Age</th>\n",
+       "      <td>714.0</td>\n",
+       "      <td>29.699118</td>\n",
+       "      <td>14.526497</td>\n",
+       "      <td>0.42</td>\n",
+       "      <td>20.1250</td>\n",
+       "      <td>28.0000</td>\n",
+       "      <td>38.0</td>\n",
+       "      <td>80.0000</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>SibSp</th>\n",
+       "      <td>891.0</td>\n",
+       "      <td>0.523008</td>\n",
+       "      <td>1.102743</td>\n",
+       "      <td>0.00</td>\n",
+       "      <td>0.0000</td>\n",
+       "      <td>0.0000</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>8.0000</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>Parch</th>\n",
+       "      <td>891.0</td>\n",
+       "      <td>0.381594</td>\n",
+       "      <td>0.806057</td>\n",
+       "      <td>0.00</td>\n",
+       "      <td>0.0000</td>\n",
+       "      <td>0.0000</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>6.0000</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>Fare</th>\n",
+       "      <td>891.0</td>\n",
+       "      <td>32.204208</td>\n",
+       "      <td>49.693429</td>\n",
+       "      <td>0.00</td>\n",
+       "      <td>7.9104</td>\n",
+       "      <td>14.4542</td>\n",
+       "      <td>31.0</td>\n",
+       "      <td>512.3292</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "             count        mean         std   min       25%       50%    75%  \\\n",
+       "PassengerId  891.0  446.000000  257.353842  1.00  223.5000  446.0000  668.5   \n",
+       "Survived     891.0    0.383838    0.486592  0.00    0.0000    0.0000    1.0   \n",
+       "Pclass       891.0    2.308642    0.836071  1.00    2.0000    3.0000    3.0   \n",
+       "Age          714.0   29.699118   14.526497  0.42   20.1250   28.0000   38.0   \n",
+       "SibSp        891.0    0.523008    1.102743  0.00    0.0000    0.0000    1.0   \n",
+       "Parch        891.0    0.381594    0.806057  0.00    0.0000    0.0000    0.0   \n",
+       "Fare         891.0   32.204208   49.693429  0.00    7.9104   14.4542   31.0   \n",
+       "\n",
+       "                  max  \n",
+       "PassengerId  891.0000  \n",
+       "Survived       1.0000  \n",
+       "Pclass         3.0000  \n",
+       "Age           80.0000  \n",
+       "SibSp          8.0000  \n",
+       "Parch          6.0000  \n",
+       "Fare         512.3292  "
+      ]
+     },
+     "execution_count": 3,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "df.describe().T"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# Visualização"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### Qual foi a média de idade dos passageiros em relação ao seu sexo:\n",
+    "Pelos dados abaixo podemos ver como a maioria das mulheres passageiras eram mais novas (média de 27 anos) do que os homens (média de 30 anos) sobreviventes no navio. "
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
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+       "\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>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>803</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",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>755</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>644</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>469</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>78</th>\n",
+       "      <td>79</td>\n",
+       "      <td>1</td>\n",
+       "      <td>2</td>\n",
+       "      <td>Caldwell, Master. Alden Gates</td>\n",
+       "      <td>male</td>\n",
+       "      <td>0.83</td>\n",
+       "      <td>0</td>\n",
+       "      <td>2</td>\n",
+       "      <td>248738</td>\n",
+       "      <td>29.0000</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>859</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>863</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>868</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>878</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>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",
+       "  </tbody>\n",
+       "</table>\n",
+       "<p>891 rows × 12 columns</p>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "     PassengerId  Survived  Pclass                                      Name  \\\n",
+       "803          804         1       3           Thomas, Master. Assad Alexander   \n",
+       "755          756         1       2                 Hamalainen, Master. Viljo   \n",
+       "644          645         1       3                    Baclini, Miss. Eugenie   \n",
+       "469          470         1       3             Baclini, Miss. Helene Barbara   \n",
+       "78            79         1       2             Caldwell, Master. Alden Gates   \n",
+       "..           ...       ...     ...                                       ...   \n",
+       "859          860         0       3                          Razi, Mr. Raihed   \n",
+       "863          864         0       3         Sage, Miss. Dorothy Edith \"Dolly\"   \n",
+       "868          869         0       3               van Melkebeke, Mr. Philemon   \n",
+       "878          879         0       3                        Laleff, Mr. Kristo   \n",
+       "888          889         0       3  Johnston, Miss. Catherine Helen \"Carrie\"   \n",
+       "\n",
+       "        Sex   Age  SibSp  Parch      Ticket     Fare Cabin Embarked  \n",
+       "803    male  0.42      0      1        2625   8.5167   NaN        C  \n",
+       "755    male  0.67      1      1      250649  14.5000   NaN        S  \n",
+       "644  female  0.75      2      1        2666  19.2583   NaN        C  \n",
+       "469  female  0.75      2      1        2666  19.2583   NaN        C  \n",
+       "78     male  0.83      0      2      248738  29.0000   NaN        S  \n",
+       "..      ...   ...    ...    ...         ...      ...   ...      ...  \n",
+       "859    male   NaN      0      0        2629   7.2292   NaN        C  \n",
+       "863  female   NaN      8      2    CA. 2343  69.5500   NaN        S  \n",
+       "868    male   NaN      0      0      345777   9.5000   NaN        S  \n",
+       "878    male   NaN      0      0      349217   7.8958   NaN        S  \n",
+       "888  female   NaN      1      2  W./C. 6607  23.4500   NaN        S  \n",
+       "\n",
+       "[891 rows x 12 columns]"
+      ]
+     },
+     "execution_count": 4,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "df_ordenado = df.sort_values(by='Age', ascending=True)\n",
+    "df_ordenado"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 5,
+   "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>803</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",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>755</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>644</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>469</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>78</th>\n",
+       "      <td>79</td>\n",
+       "      <td>1</td>\n",
+       "      <td>2</td>\n",
+       "      <td>Caldwell, Master. Alden Gates</td>\n",
+       "      <td>male</td>\n",
+       "      <td>0.83</td>\n",
+       "      <td>0</td>\n",
+       "      <td>2</td>\n",
+       "      <td>248738</td>\n",
+       "      <td>29.0000</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>116</th>\n",
+       "      <td>117</td>\n",
+       "      <td>0</td>\n",
+       "      <td>3</td>\n",
+       "      <td>Connors, Mr. Patrick</td>\n",
+       "      <td>male</td>\n",
+       "      <td>70.50</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>370369</td>\n",
+       "      <td>7.7500</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>Q</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>493</th>\n",
+       "      <td>494</td>\n",
+       "      <td>0</td>\n",
+       "      <td>1</td>\n",
+       "      <td>Artagaveytia, Mr. Ramon</td>\n",
+       "      <td>male</td>\n",
+       "      <td>71.00</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>PC 17609</td>\n",
+       "      <td>49.5042</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>C</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>96</th>\n",
+       "      <td>97</td>\n",
+       "      <td>0</td>\n",
+       "      <td>1</td>\n",
+       "      <td>Goldschmidt, Mr. George B</td>\n",
+       "      <td>male</td>\n",
+       "      <td>71.00</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>PC 17754</td>\n",
+       "      <td>34.6542</td>\n",
+       "      <td>A5</td>\n",
+       "      <td>C</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>851</th>\n",
+       "      <td>852</td>\n",
+       "      <td>0</td>\n",
+       "      <td>3</td>\n",
+       "      <td>Svensson, Mr. Johan</td>\n",
+       "      <td>male</td>\n",
+       "      <td>74.00</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>347060</td>\n",
+       "      <td>7.7750</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>S</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>630</th>\n",
+       "      <td>631</td>\n",
+       "      <td>1</td>\n",
+       "      <td>1</td>\n",
+       "      <td>Barkworth, Mr. Algernon Henry Wilson</td>\n",
+       "      <td>male</td>\n",
+       "      <td>80.00</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>27042</td>\n",
+       "      <td>30.0000</td>\n",
+       "      <td>A23</td>\n",
+       "      <td>S</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "<p>714 rows × 12 columns</p>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "     PassengerId  Survived  Pclass                                  Name  \\\n",
+       "803          804         1       3       Thomas, Master. Assad Alexander   \n",
+       "755          756         1       2             Hamalainen, Master. Viljo   \n",
+       "644          645         1       3                Baclini, Miss. Eugenie   \n",
+       "469          470         1       3         Baclini, Miss. Helene Barbara   \n",
+       "78            79         1       2         Caldwell, Master. Alden Gates   \n",
+       "..           ...       ...     ...                                   ...   \n",
+       "116          117         0       3                  Connors, Mr. Patrick   \n",
+       "493          494         0       1               Artagaveytia, Mr. Ramon   \n",
+       "96            97         0       1             Goldschmidt, Mr. George B   \n",
+       "851          852         0       3                   Svensson, Mr. Johan   \n",
+       "630          631         1       1  Barkworth, Mr. Algernon Henry Wilson   \n",
+       "\n",
+       "        Sex    Age  SibSp  Parch    Ticket     Fare Cabin Embarked  \n",
+       "803    male   0.42      0      1      2625   8.5167   NaN        C  \n",
+       "755    male   0.67      1      1    250649  14.5000   NaN        S  \n",
+       "644  female   0.75      2      1      2666  19.2583   NaN        C  \n",
+       "469  female   0.75      2      1      2666  19.2583   NaN        C  \n",
+       "78     male   0.83      0      2    248738  29.0000   NaN        S  \n",
+       "..      ...    ...    ...    ...       ...      ...   ...      ...  \n",
+       "116    male  70.50      0      0    370369   7.7500   NaN        Q  \n",
+       "493    male  71.00      0      0  PC 17609  49.5042   NaN        C  \n",
+       "96     male  71.00      0      0  PC 17754  34.6542    A5        C  \n",
+       "851    male  74.00      0      0    347060   7.7750   NaN        S  \n",
+       "630    male  80.00      0      0     27042  30.0000   A23        S  \n",
+       "\n",
+       "[714 rows x 12 columns]"
+      ]
+     },
+     "execution_count": 5,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "df_ordenado_sem_nan = df_ordenado.dropna(subset=['Age'])\n",
+    "df_ordenado_sem_nan "
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 6,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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+feXh4aF//OMfio2NtdVSEp4OHTpkOwIl/T4VPjs7u8o1o+Yw9RwO5ePjowULFmj69Onq379/uf3uvvtuFRUVKSEhodSy3377zTZFNiYmRvXq1VNycrLd/yiTkpIuWkvJ/0zPX88YU2rKcXni4uK0ZcsWff3117a2kydPljoaFRsbq4YNG2rWrFk6d+5cqe1U9t4gbm5uio2N1cqVK5WRkWFrT0tL0yeffFKqr2Q/xpycHC1atMiuX2Vex7vvvlubN28utS/p9yMqv/32W7m119Z+yhp3YWGhXn75Zbt+HTt2VEREhJKSkkpNuy5Zt1mzZrr66qv15ptv2vXZu3evPv30U8XFxZVbR4nKjDsuLk5ff/21Nm/ebGvLy8vTq6++qhYtWlzwFNWAAQPk6uqqGTNmlDp6VbLfmJgYeXh4aO7cuXa1vP7668rJyVG/fv0uOp5LERcXp8zMTLv/7Pz2229KTk6Wj4+PevXqVe66mZmZ2r9/f6n2wsJCrVu3zu5UU2U+PyNHjlRxcbFef/11vfrqq3J3d9eIESNsr0/Je/zH9+uFF16QpBp/zVAFDrlSCH9a51+gfCFlTT1/8MEHjSRz8803mxdffNHMmzfPjBs3zoSEhNjNTJo2bZrdlN4RI0ZUaOp5YWGhiYyMNIGBgebpp582ycnJpnfv3qZDhw4VmlXy008/mcaNG1do6vnSpUuNq6uradu2rZk5c6Z55ZVXzGOPPWauvvpqM3r06Avup6zZWLt27TJeXl4mLCzMzJ4928ycObPMqefffvut8fDwMO3atTPz5s0zs2fPNpGRkbYxnl9jRV/HvLw807FjR+Pu7m4eeOABs2DBAvPcc8+ZYcOGmQYNGpiTJ09ecDy1sZ+srCzTqFEjEx4ebp5//nnzwgsvmGuuucY27vMvUl+zZo2pV6+eCQ8PN9OnTzevvPKKmTBhgunbt6+tT8nU89atW5s5c+aYGTNm2G478P3339v6lVygXFZtFR13ydRzPz8/Ex8fb1588UVz9dVXGxcXlwpNPY+Pj7dNPX/uuedMcnKyGTp0qJk6dWqpOvv27WvmzZtnHn744XKnnv/xQmRjyv73aowxki76eS6Zeu7h4WEeeeQRk5ycbJv1dbGp59u2bTMuLi6mT58+ZtasWeaNN94ws2fPtr2v58+gqujn54033jCSzOLFi23rllzIXnLbAGP+O/X87rvvNvPnz7c9Z+q5cyLsoFZdStgxxphXX33VdOrUyXh7extfX1/Trl07M3nyZPPTTz/Z+hQVFZmnnnrKNGvWzHh7e5vevXubvXv3mvDw8IvOxtq/f7+JiYkxPj4+JjAw0IwcOdLs2rWrQmHHmN/vd9OrVy/j5eVlLrvsMpOQkGBef/31UkGiZP+xsbHGz8/PeHl5mcjISDN8+HCzffv2C+6jrLBjjDEpKSmmU6dOxsPDw1x++eVm4cKFtl9i51u1apVp37698fLyMi1atDDPPPOM7Qf8+TVW9HU05vep0NOmTTMtW7Y0Hh4eJjAw0PbL9fxflmWprf18+eWXpnv37sbb29uEhISYyZMn26ZH/3FG3qZNm8yNN95ofH19TYMGDUz79u1NcnKyXZ/PPvvM9OjRw3h7e5uGDRua/v37l5qdc6GwU5lxHz582Nx5553G39/feHl5ma5du5oPP/zwguM93xtvvGGuueYa4+npaRo1amR69epl1q5da9dn3rx5pnXr1qZevXomKCjI/O1vfys1/b4mwo4xxhw/ftzcd999JjAw0BbGK/LvLTc317z00ksmNjbWNG/e3NSrV8/4+vqa6Oho89prr5WaNXaxz8/Ro0eNn5+f6d+/f6l93X777aZBgwa2MHvu3Dnz1FNPmYiICFOvXj0TGhpqpk2bZruNAZyLizG1ePUYAABALeOaHQAAYGmEHQAAYGmEHQAAYGmEHQAAYGmEHQAAYGmEHQAAYGl8XYR+/86dn376Sb6+vnzXCQAAdYQxRqdPn1ZISEipL5M9H2FH0k8//VTqG3sBAEDdcPToUTVv3rzc5YQdSb6+vpJ+f7EaNmzo4GoAAEBF5ObmKjQ01PZ7vDyEHcl26qphw4aEHQAA6piLXYLCBcoAAMDSHBp2Nm7cqP79+yskJEQuLi5auXKlbdm5c+c0ZcoUtWvXTg0aNFBISIiGDh2qn376yW4bp06d0uDBg9WwYUP5+/trxIgROnPmTC2PBAAAOCuHhp28vDx16NBB8+fPL7UsPz9fqampio+PV2pqqlasWKEDBw7o1ltvtes3ePBg7du3T2vXrtWHH36ojRs3atSoUbU1BAAA4OSc5lvPXVxc9N5772nAgAHl9tm2bZu6du2qI0eOKCwsTGlpaWrTpo22bdumzp07S5LWrFmjuLg4/fDDDwoJCanQvnNzc+Xn56ecnByu2QEAoI6o6O/vOnXNTk5OjlxcXOTv7y9J2rx5s/z9/W1BR5JiYmLk6uqqrVu3OqhKAADgTOrMbKyzZ89qypQp+utf/2pLb5mZmWratKldP3d3dwUEBCgzM7PcbRUUFKigoMD2PDc3t2aKBgAADlcnjuycO3dOd999t4wxWrBgwSVvLzExUX5+frYHNxQEAMC6nD7slASdI0eOaO3atXbn5IKDg3XixAm7/r/99ptOnTql4ODgcrc5bdo05eTk2B5Hjx6tsfoBAIBjOfVprJKgc+jQIa1fv16NGze2Wx4dHa3s7Gzt2LFDnTp1kiR9/vnnKi4uVrdu3crdrqenpzw9PWu0dgAA4BwcGnbOnDmj7777zvY8PT1dO3fuVEBAgJo1a6Y777xTqamp+vDDD1VUVGS7DicgIEAeHh6KiorSTTfdpJEjR2rhwoU6d+6cxowZo0GDBlV4JhYAALA2h04937Bhg66//vpS7cOGDdP06dMVERFR5nrr169X7969Jf1+U8ExY8bogw8+kKurqwYOHKi5c+fKx8enwnUw9RwAgLqnor+/neY+O45E2AEAoO6x5H12AAAAKouwAwAALM2pZ2MBVpaRkaGsrCxHl1FpgYGBCgsLc3QZAFBhhB3AATIyMhQVFaX8/HxHl1Jp9evXV1paGoEHQJ1B2AEcICsrS/n5+VqyZImioqIcXU6FpaWlaciQIcrKyiLsAKgzCDuAA0VFRaljx46OLgMALI0LlAEAgKURdgAAgKURdgAAgKURdgAAgKURdgAAgKURdgAAgKURdgAAgKURdgAAgKURdgAAgKURdgAAgKURdgAAgKURdgAAgKURdgAAgKURdgAAgKURdgAAgKURdgAAgKURdgAAgKURdgAAgKURdgAAgKURdgAAgKW5O7oAoDpkZGQoKyvL0WVUWFpamqNLAIA/DcIO6ryMjAxFRUUpPz/f0aVU2rFjxxxdAgBYHmEHdV5WVpby8/O1ZMkSRUVFObqcClm9erXi4+OVnZ3t6FIAwPIIO7CMqKgodezY0dFlVAinsQCg9nCBMgAAsDTCDgAAsDTCDgAAsDTCDgAAsDTCDgAAsDTCDgAAsDTCDgAAsDTCDgAAsDTCDgAAsDTCDgAAsDTCDgAAsDTCDgAAsDTCDgAAsDTCDgAAsDTCDgAAsDTCDgAAsDTCDgAAsDTCDgAAsDTCDgAAsDTCDgAAsDSHhp2NGzeqf//+CgkJkYuLi1auXGm33BijJ554Qs2aNZO3t7diYmJ06NAhuz6nTp3S4MGD1bBhQ/n7+2vEiBE6c+ZMLY4CAAA4M4eGnby8PHXo0EHz588vc/mzzz6ruXPnauHChdq6dasaNGig2NhYnT171tZn8ODB2rdvn9auXasPP/xQGzdu1KhRo2prCAAAwMm5O3LnN998s26++eYylxljlJSUpMcff1y33XabJOmtt95SUFCQVq5cqUGDBiktLU1r1qzRtm3b1LlzZ0lScnKy4uLi9NxzzykkJKTWxgIAAJyT016zk56erszMTMXExNja/Pz81K1bN23evFmStHnzZvn7+9uCjiTFxMTI1dVVW7duLXfbBQUFys3NtXsAAABrctqwk5mZKUkKCgqyaw8KCrIty8zMVNOmTe2Wu7u7KyAgwNanLImJifLz87M9QkNDq7l6AADgLJw27NSkadOmKScnx/Y4evSoo0sCAAA1xGnDTnBwsCTp+PHjdu3Hjx+3LQsODtaJEyfslv/22286deqUrU9ZPD091bBhQ7sHAACwJqcNOxEREQoODta6detsbbm5udq6dauio6MlSdHR0crOztaOHTtsfT7//HMVFxerW7dutV4zAABwPg6djXXmzBl99913tufp6enauXOnAgICFBYWpvHjx2vmzJm64oorFBERofj4eIWEhGjAgAGSpKioKN10000aOXKkFi5cqHPnzmnMmDEaNGgQM7EAAIAkB4ed7du36/rrr7c9nzhxoiRp2LBhWrx4sSZPnqy8vDyNGjVK2dnZuu6667RmzRp5eXnZ1lm6dKnGjBmjPn36yNXVVQMHDtTcuXNrfSwAAMA5OTTs9O7dW8aYcpe7uLhoxowZmjFjRrl9AgICtGzZspooDwAAWIDTXrMDAABQHQg7AADA0gg7AADA0gg7AADA0gg7AADA0gg7AADA0gg7AADA0gg7AADA0gg7AADA0gg7AADA0gg7AADA0gg7AADA0gg7AADA0gg7AADA0gg7AADA0gg7AADA0gg7AADA0gg7AADA0gg7AADA0gg7AADA0gg7AADA0gg7AADA0gg7AADA0gg7AADA0gg7AADA0gg7AADA0gg7AADA0gg7AADA0gg7AADA0gg7AADA0gg7AADA0gg7AADA0gg7AADA0gg7AADA0gg7AADA0gg7AADA0gg7AADA0gg7AADA0gg7AADA0gg7AADA0gg7AADA0gg7AADA0gg7AADA0gg7AADA0gg7AADA0gg7AADA0gg7AADA0gg7AADA0gg7AADA0pw67BQVFSk+Pl4RERHy9vZWZGSkEhISZIyx9THG6IknnlCzZs3k7e2tmJgYHTp0yIFVAwAAZ+LUYeeZZ57RggULNG/ePKWlpemZZ57Rs88+q+TkZFufZ599VnPnztXChQu1detWNWjQQLGxsTp79qwDKwcAAM7C3dEFXMhXX32l2267Tf369ZMktWjRQv/617/09ddfS/r9qE5SUpIef/xx3XbbbZKkt956S0FBQVq5cqUGDRrksNoBAIBzcOojO9dee63WrVungwcPSpJ27dqlTZs26eabb5YkpaenKzMzUzExMbZ1/Pz81K1bN23evLnc7RYUFCg3N9fuAQAArMmpj+xMnTpVubm5at26tdzc3FRUVKSnn35agwcPliRlZmZKkoKCguzWCwoKsi0rS2Jiop566qmaKxwAADgNpz6y8/bbb2vp0qVatmyZUlNT9eabb+q5557Tm2++eUnbnTZtmnJycmyPo0ePVlPFAADA2Tj1kZ1JkyZp6tSptmtv2rVrpyNHjigxMVHDhg1TcHCwJOn48eNq1qyZbb3jx4/r6quvLne7np6e8vT0rNHaAQCAc3DqIzv5+flydbUv0c3NTcXFxZKkiIgIBQcHa926dbblubm52rp1q6Kjo2u1VgAA4Jyc+shO//799fTTTyssLExXXXWVvvnmG73wwgu6//77JUkuLi4aP368Zs6cqSuuuEIRERGKj49XSEiIBgwY4NjiAQCAU3DqsJOcnKz4+Hj9/e9/14kTJxQSEqIHH3xQTzzxhK3P5MmTlZeXp1GjRik7O1vXXXed1qxZIy8vLwdWDgAAnIVThx1fX18lJSUpKSmp3D4uLi6aMWOGZsyYUXuFAQCAOsOpr9kBAAC4VIQdAABgaYQdAABgaYQdAABgaYQdAABgaYQdAABgaYQdAABgaYQdAABgaYQdAABgaYQdAABgaU79dREAnFNaWpqjS6iUwMBAhYWFOboMAA5C2AFQYceOHZMkDRkyxMGVVE79+vWVlpZG4AH+pAg7ACosOztbkpSQkKC4uDjHFlNBaWlpGjJkiLKysgg7wJ8UYQdApUVERKhjx46OLgMAKoQLlAEAgKURdgAAgKURdgAAgKURdgAAgKURdgAAgKURdgAAgKURdgAAgKURdgAAgKURdgAAgKURdgAAgKURdgAAgKURdgAAgKURdgAAgKURdgAAgKURdgAAgKURdgAAgKURdgAAgKURdgAAgKURdgAAgKURdgAAgKURdgAAgKW5V3XFoqIirVy5UmlpaZKkq666Srfeeqvc3NyqrTgAAIBLVaWw891336lfv3764YcfdOWVV0qSEhMTFRoaqo8++kiRkZHVWiQAAEBVVek01tixY3X55Zfr6NGjSk1NVWpqqjIyMhQREaGxY8dWd40AAABVVqUjOykpKdqyZYsCAgJsbY0bN9bs2bPVo0ePaisOAADgUlXpyI6np6dOnz5dqv3MmTPy8PC45KIAAACqS5XCzi233KJRo0Zp69atMsbIGKMtW7booYce0q233lrdNQIAAFRZlcLO3LlzFRkZqejoaHl5ecnLy0s9evRQy5YtlZSUVM0lAgAAVF2Vrtnx9/fX+++/r++++8429TwqKkotW7as1uIAAAAuVZWO7Kxfv16S1LJlS/Xv31/9+/e3BZ1XXnml+qoDAAC4RFUKOzfddJMmTZqkc+fO2dqysrLUv39/TZ06tdqKAwAAuFRVPrLz3nvvqUuXLtq/f78++ugjtW3bVrm5udq5c2c1lwgAAFB1VQo71157rXbu3Km2bduqY8eOuv322zVhwgRt2LBB4eHh1V0jAABAlVX5i0APHjyo7du3q3nz5nJ3d9eBAweUn59fnbUBAABcsiqFndmzZys6Olo33nij9u7dq6+//lrffPON2rdvr82bN1d3jQAAAFVWpbDz0ksvaeXKlUpOTpaXl5fatm2rr7/+WnfccYd69+5drQX++OOPGjJkiBo3bixvb2+1a9dO27dvty03xuiJJ55Qs2bN5O3trZiYGB06dKhaawAAAHVXlcLOnj17dPPNN9u11atXT3PmzNGnn35aLYVJ0i+//KIePXqoXr16+vjjj7V//349//zzatSoka3Ps88+q7lz52rhwoXaunWrGjRooNjYWJ09e7ba6gAAAHVXlW4qGBgYqOzsbL377rs6fPiwJk2apICAAKWmplbrjQWfeeYZhYaGatGiRba2iIgI29+NMUpKStLjjz+u2267TZL01ltvKSgoSCtXrtSgQYOqrRYAAFA3VenIzu7du9WqVSs988wzeu6555SdnS1JWrFihaZNm1Ztxa1atUqdO3fWXXfdpaZNm+qaa67Ra6+9Zluenp6uzMxMxcTE2Nr8/PzUrVu3C147VFBQoNzcXLsHAACwpiqFnQkTJmj48OE6dOiQvLy8bO1xcXHauHFjtRX3/fffa8GCBbriiiv0ySef6G9/+5vGjh2rN998U5KUmZkpSQoKCrJbLygoyLasLImJifLz87M9QkNDq61mAADgXKoUdrZv364HH3ywVPtll112wZBRWcXFxerYsaNmzZqla665RqNGjdLIkSO1cOHCS9rutGnTlJOTY3scPXq0mioGAADOpkphx9PTs8xTPwcPHlSTJk0uuagSzZo1U5s2bezaoqKilJGRIUkKDg6WJB0/ftyuz/Hjx23LyuLp6amGDRvaPQAAgDVVKezceuutmjFjhu27sVxcXJSRkaEpU6Zo4MCB1VZcjx49dODAAbu2gwcP2u7SHBERoeDgYK1bt862PDc3V1u3blV0dHS11QEAAOquKoWd559/XmfOnFHTpk3166+/qlevXoqMjJSPj4+efvrpaituwoQJ2rJli2bNmqXvvvtOy5Yt06uvvqrRo0dL+j1kjR8/XjNnztSqVau0Z88eDR06VCEhIRowYEC11QEAAOquKk099/Pz09q1a7Vp0ybt3r1bZ86cUadOndSnT59qLa5Lly567733NG3aNM2YMUMRERFKSkrS4MGDbX0mT56svLw8jRo1StnZ2bruuuu0Zs0auwunAQDAn1elws7mzZv1888/65ZbbpEkXXfddTp8+LCeffZZ5efna8CAAUpOTpanp2e1FXjLLbfY9lcWFxcXzZgxQzNmzKi2fQIAAOuo1GmsGTNmaN++fbbne/bs0ciRI3XjjTdq6tSp+uCDD5SYmFjtRQIAAFRVpcLOzp077U5VLV++XF27dtVrr72miRMnau7cuXr77bervUgAAICqqlTY+eWXX+xu4JeSkmL3HVldunThnjUAAMCpVCrsBAUFKT09XZJUWFio1NRUde/e3bb89OnTqlevXvVWCAAAcAkqFXbi4uI0depUffHFF5o2bZrq16+vnj172pbv3r1bkZGR1V4kAABAVVVqNlZCQoLuuOMO9erVSz4+PnrzzTfl4eFhW/7GG2+ob9++1V4kAABAVVUq7AQGBmrjxo3KycmRj4+P3Nzc7Ja/88478vHxqdYCAQAALkWVbypYloCAgEsqBgAAoLpV6esiAAAA6grCDgAAsDTCDgAAsDTCDgAAsDTCDgAAsDTCDgAAsDTCDgAAsDTCDgAAsDTCDgAAsDTCDgAAsDTCDgAAsDTCDgAAsDTCDgAAsDTCDgAAsDTCDgAAsDTCDgAAsDTCDgAAsDTCDgAAsDTCDgAAsDTCDgAAsDTCDgAAsDTCDgAAsDTCDgAAsDR3RxcAOJOMjAxlZWXV+H7S09Ntf6amppbZJzAwUGFhYTVeCwBYHWEH+D8ZGRmKiopSfn5+re0zPj5e8fHxZS6rX7++0tLSCDwAcIkIO8D/ycrKUn5+vpYsWaKoqKga3dfq1asVHx+vhIQExcXFlVqelpamIUOGKCsri7ADAJeIsAP8QVRUlDp27Fij+0hLS5MkRURE1Pi+8LuS17yu4DQmUH0IOwAs7dixY5KkIUOGOLiSyuE0JlB9CDsALC07O1uSyj1l6Iw4jQlUL8IOgD8FThkCf17cZwcAAFgaYQcAAFgap7EAJ+YsM4iYGQSgLiPsAE7I2WYQlcwMAoC6iLADOCFnmkF0/swgAKiLCDuAE2MGEQBcOi5QBgAAlkbYAQAAlkbYAQAAlkbYAQAAlkbYAQAAllanZmPNnj1b06ZN07hx45SUlCRJOnv2rB555BEtX75cBQUFio2N1csvv6ygoCDHFosKy8jIuKRpzSX3f7nU+8BwHxkAsKY6E3a2bdumV155Re3bt7drnzBhgj766CO988478vPz05gxY3THHXfoyy+/dFClqIyMjAxFRUUpPz//krdVXTfgK7mhHwDAGupE2Dlz5owGDx6s1157TTNnzrS15+Tk6PXXX9eyZct0ww03SJIWLVqkqKgobdmyRd27d3dUyaigrKws5efna8mSJYqKiqrSNkpuencp25Ck1atXKz4+3nZDPwCANdSJsDN69Gj169dPMTExdmFnx44dOnfunGJiYmxtrVu3VlhYmDZv3lxu2CkoKFBBQYHteW5ubs0VjwqJioq65JvnXeo2OI0FANbk9GFn+fLlSk1N1bZt20oty8zMlIeHh/z9/e3ag4KClJmZWe42ExMT9dRTT1V3qQAAwAk59Wyso0ePaty4cVq6dKm8vLyqbbvTpk1TTk6O7XH06NFq2zYAAHAuTh12duzYoRMnTqhjx45yd3eXu7u7UlJSNHfuXLm7uysoKEiFhYWlrrE4fvy4goODy92up6enGjZsaPcAAADW5NSnsfr06aM9e/bYtd13331q3bq1pkyZotDQUNWrV0/r1q3TwIEDJUkHDhxQRkaGoqOjHVEyAABwMk4ddnx9fdW2bVu7tgYNGqhx48a29hEjRmjixIkKCAhQw4YN9fDDDys6OpqZWAAAQJKTh52KePHFF+Xq6qqBAwfa3VQQAABAqoNhZ8OGDXbPvby8NH/+fM2fP98xBQEAAKfm1BcoAwAAXCrCDgAAsDTCDgAAsDTCDgAAsDTCDgAAsDTCDgAAsDTCDgAAsLQ6d58dAI6Rlpam9PR0SVJ6erpSU1MdVktgYKDCwsIctn8AdQthB8AFHTt2TJI0ZMgQW1t8fLzi4+MdVZLq16+vtLQ0Ag+ACiHsALig7OxsSVJCQoKk34NOQkKC4uLiHFJPWlqahgwZoqysLMIOgAoh7ACokIiICLu/d+zY0YHVAEDFcYEyAACwNMIOAACwNMIOAACwNMIOAACwNMIOAACwNMIOAACwNMIOAACwNMIOAACwNMIOAACwNMIOAACwNMIOAACwNMIOAACwNMIOAACwNMIOAACwNHdHFwAAKFtaWpqjS6iUwMBAhYWFOboMoBTCDgA4mWPHjkmShgwZ4uBKKqd+/fpKS0sj8MDpEHYAwMlkZ2dLkhISEhQXF+fYYiooLS1NQ4YMUVZWFmEHToewU8MyMjKUlZXl6DIqhUPRgHOIiIhQx44dHV0GUOcRdmpQRkaGoqKilJ+f7+hSKoVD0QAAKyHs1KCsrCzl5+dryZIlioqKcnQ5FcKhaACA1RB2akFUVBSHogEAcBDuswMAACyNsAMAACyNsAMAACyNsAMAACyNsAMAACyNsAMAACyNsAMAACyNsAMAACyNsAMAACyNOygDqJPS0tIq1C89Pd32Z2pqarXXwRfnAs6PsAOgTjl27JgkaciQIZVaLz4+XvHx8dVeD1+cCzg/wg6AOiU7O1uSlJCQoLi4uIv2X716teLj4yvcvzL44lygbiDs1JKMjAxlZWU5ugxJFTvsXtFTBJeqZD+Xsr/aqhXOJSIiokJfsFvy+ahofwDWQ9ipBceOHVPPnj2Vn5/v6FIkXfiwe1VPEVyq6thfSe0AAJyPsFMLsrOzlZ+fryVLligqKsqhtVzssHtlTxFUVz2X8tqUnKYoqR0AgPMRdmpRVFRUnTmMXtuH/C/lteE0FgDgQrjPDgAAsDSnDjuJiYnq0qWLfH191bRpUw0YMEAHDhyw63P27FmNHj1ajRs3lo+PjwYOHKjjx487qGIAAOBsnDrspKSkaPTo0dqyZYvWrl2rc+fOqW/fvsrLy7P1mTBhgj744AO98847SklJ0U8//aQ77rjDgVUDAABn4tTX7KxZs8bu+eLFi9W0aVPt2LFDf/nLX5STk6PXX39dy5Yt0w033CBJWrRokaKiorRlyxZ1797dEWUDAAAn4tRHdv4oJydHkhQQECBJ2rFjh86dO6eYmBhbn9atWyssLEybN292SI0AAMC5OPWRnfMVFxdr/Pjx6tGjh9q2bStJyszMlIeHh/z9/e36BgUFKTMzs9xtFRQUqKCgwPY8Nze3RmoGAACOV2eO7IwePVp79+7V8uXLL3lbiYmJ8vPzsz1CQ0OroUIAAOCM6kTYGTNmjD788EOtX79ezZs3t7UHBwersLCw1M3kjh8/ruDg4HK3N23aNOXk5NgeR48eranSAQCAgzn1aSxjjB5++GG999572rBhgyIiIuyWd+rUSfXq1dO6des0cOBASdKBAweUkZGh6Ojocrfr6ekpT0/PGq0dwJ9Hdd/YMj093fZnampqhderyPfeAX9GTh12Ro8erWXLlun999+Xr6+v7TocPz8/eXt7y8/PTyNGjNDEiRMVEBCghg0b6uGHH1Z0dDQzsQDUuJr+Lrn4+HjFx8dXuP+FvvcO+DNz6rCzYMECSVLv3r3t2hctWqThw4dLkl588UW5urpq4MCBKigoUGxsrF5++eVarhTAn1FNfZdcyfe9VWa7F/veO+DPzKnDjjHmon28vLw0f/58zZ8/vxYqAoDSqvu75EpOi9X2d9QBVlUnLlAGAACoKsIOAACwNMIOAACwNMIOAACwNMIOAACwNKeejQUAqFuq+waLNY0bMf45EHYAAJespm+wWFO4EeOfA2EHAHDJauoGizWJGzH+eRB2AADVhhshwhlxgTIAALA0wg4AALA0wg4AALA0wg4AALA0wg4AALA0wg4AALA0wg4AALA0wg4AALA0wg4AALA0wg4AALA0wg4AALA0vhvrTyotLa3M9vT0dNufqampDqsDAIDqQtj5kzl27JgkaciQIRfsFx8fr/j4+NooSdJ/6wIAoLoRdv5ksrOzJUkJCQmKi4srtXz16tWKj48vd3l1K9lfSV0AAFQ3ws6fVEREhDp27FiqveS0UnnLqxunsQAANY0LlAEAgKURdgAAgKVxGgsALMRRp4bLmskZGBiosLAwh9RTGXXtdHpdeV2dCWEHACygojMta9r5Mznr16+vtLQ0p/3F7CyvWWU5++vqjAg7AGABF5tpWdP+OJMzLS1NQ4YMUVZWltP+Unb0a1YVdeF1dUaEHQCwkNqaSflH5c3kdJZTRBc69eOo1wy1h7ADAKh2znaKiFM/f26EHQBAtXOmU0Sc+gFhBwBQYzhFBGfAfXYAAIClEXYAAIClEXYAAIClEXYAAIClEXYAAIClEXYAAIClEXYAAIClEXYAAIClEXYAAIClEXYAAIClEXYAAIClEXYAAIClEXYAAIClEXYAAICluTu6AAAAUDlpaWmOLqFSAgMDFRYW5rD9E3YAAKgjjh07JkkaMmSIgyupnPr16ystLc1hgccyYWf+/PmaM2eOMjMz1aFDByUnJ6tr166OLgsAgGqTnZ0tSUpISFBcXJxji6mgtLQ0DRkyRFlZWYSdS/Hvf/9bEydO1MKFC9WtWzclJSUpNjZWBw4cUNOmTR1dHgAA1SoiIkIdO3Z0dBl1hiUuUH7hhRc0cuRI3XfffWrTpo0WLlyo+vXr64033nB0aQAAwMHqfNgpLCzUjh07FBMTY2tzdXVVTEyMNm/e7MDKAACAM6jzp7GysrJUVFSkoKAgu/agoCB9++23Za5TUFCggoIC2/OcnBxJUm5ubrXWdubMGUn/vWp+xYoV2rFjR7Xuo7K2bt0qSVq/fr3y8/Mrvby266mtbVTndqpjX7X9PlzI+bWUcGRdlX1tavK1rKltV2W7jv7M/HH/jq7nfEeOHJEk7dixw/ZzWfrvz+a0tDRt3LjRIbVVVl2s+cCBA5J+/51Y3b9nS7ZnjLlwR1PH/fjjj0aS+eqrr+zaJ02aZLp27VrmOk8++aSRxIMHDx48ePCwwOPo0aMXzAp1/shOYGCg3NzcdPz4cbv248ePKzg4uMx1pk2bpokTJ9qeFxcX69SpU2rcuLFcXFwuuabc3FyFhobq6NGjatiw4SVvz9lYfXwSY7QCq49PYoxWYPXxSTU7RmOMTp8+rZCQkAv2q/Nhx8PDQ506ddK6des0YMAASb+Hl3Xr1mnMmDFlruPp6SlPT0+7Nn9//2qvrWHDhpb98ErWH5/EGK3A6uOTGKMVWH18Us2N0c/P76J96nzYkaSJEydq2LBh6ty5s7p27aqkpCTl5eXpvvvuc3RpAADAwSwRdu655x6dPHlSTzzxhDIzM3X11VdrzZo1pS5aBgAAfz6WCDuSNGbMmHJPW9U2T09PPfnkk6VOlVmF1ccnMUYrsPr4JMZoBVYfn+QcY3Qx5mLztQAAAOquOn9TQQAAgAsh7AAAAEsj7AAAAEsj7AAAAEsj7FSz+fPnq0WLFvLy8lK3bt309ddfO7qkKtu4caP69++vkJAQubi4aOXKlXbLjTF64okn1KxZM3l7eysmJkaHDh1yTLFVkJiYqC5dusjX11dNmzbVgAEDbN/hUuLs2bMaPXq0GjduLB8fHw0cOLDU3bqd2YIFC9S+fXvbzbyio6P18ccf25bX9fH90ezZs+Xi4qLx48fb2ur6GKdPny4XFxe7R+vWrW3L6/r4Svz4448aMmSIGjduLG9vb7Vr107bt2+3La/rP29atGhR6n10cXHR6NGjJdX997GoqEjx8fGKiIiQt7e3IiMjlZCQYPedVQ59Dy/926lQYvny5cbDw8O88cYbZt++fWbkyJHG39/fHD9+3NGlVcnq1avNY489ZlasWGEkmffee89u+ezZs42fn59ZuXKl2bVrl7n11ltNRESE+fXXXx1TcCXFxsaaRYsWmb1795qdO3eauLg4ExYWZs6cOWPr89BDD5nQ0FCzbt06s337dtO9e3dz7bXXOrDqylm1apX56KOPzMGDB82BAwfMo48+aurVq2f27t1rjKn74zvf119/bVq0aGHat29vxo0bZ2uv62N88sknzVVXXWWOHTtme5w8edK2vK6PzxhjTp06ZcLDw83w4cPN1q1bzffff28++eQT891339n61PWfNydOnLB7D9euXWskmfXr1xtj6v77+PTTT5vGjRubDz/80KSnp5t33nnH+Pj4mJdeesnWx5HvIWGnGnXt2tWMHj3a9ryoqMiEhISYxMREB1ZVPf4YdoqLi01wcLCZM2eOrS07O9t4enqaf/3rXw6o8NKdOHHCSDIpKSnGmN/HU69ePfPOO+/Y+qSlpRlJZvPmzY4q85I1atTI/O///q+lxnf69GlzxRVXmLVr15pevXrZwo4Vxvjkk0+aDh06lLnMCuMzxpgpU6aY6667rtzlVvx5M27cOBMZGWmKi4st8T7269fP3H///XZtd9xxhxk8eLAxxvHvIaexqklhYaF27NihmJgYW5urq6tiYmK0efNmB1ZWM9LT05WZmWk3Xj8/P3Xr1q3OjjcnJ0eSFBAQIEnasWOHzp07ZzfG1q1bKywsrE6OsaioSMuXL1deXp6io6MtNb7Ro0erX79+dmORrPMeHjp0SCEhIbr88ss1ePBgZWRkSLLO+FatWqXOnTvrrrvuUtOmTXXNNdfotddesy232s+bwsJCLVmyRPfff79cXFws8T5ee+21WrdunQ4ePChJ2rVrlzZt2qSbb75ZkuPfQ8vcQdnRsrKyVFRUVOorKoKCgvTtt986qKqak5mZKUlljrdkWV1SXFys8ePHq0ePHmrbtq2k38fo4eFR6kti69oY9+zZo+joaJ09e1Y+Pj5677331KZNG+3cudMS41u+fLlSU1O1bdu2Usus8B5269ZNixcv1pVXXqljx47pqaeeUs+ePbV3715LjE+Svv/+ey1YsEATJ07Uo48+qm3btmns2LHy8PDQsGHDLPfzZuXKlcrOztbw4cMlWeNzOnXqVOXm5qp169Zyc3NTUVGRnn76aQ0ePFiS439nEHYA/X5kYO/evdq0aZOjS6l2V155pXbu3KmcnBy9++67GjZsmFJSUhxdVrU4evSoxo0bp7Vr18rLy8vR5dSIkv8ZS1L79u3VrVs3hYeH6+2335a3t7cDK6s+xcXF6ty5s2bNmiVJuuaaa7R3714tXLhQw4YNc3B11e/111/XzTffrJCQEEeXUm3efvttLV26VMuWLdNVV12lnTt3avz48QoJCXGK95DTWNUkMDBQbm5upa6eP378uIKDgx1UVc0pGZMVxjtmzBh9+OGHWr9+vZo3b25rDw4OVmFhobKzs+3617Uxenh4qGXLlurUqZMSExPVoUMHvfTSS5YY344dO3TixAl17NhR7u7ucnd3V0pKiubOnSt3d3cFBQXV+TH+kb+/v1q1aqXvvvvOEu+hJDVr1kxt2rSxa4uKirKdrrPSz5sjR47os88+0wMPPGBrs8L7OGnSJE2dOlWDBg1Su3bt9D//8z+aMGGCEhMTJTn+PSTsVBMPDw916tRJ69ats7UVFxdr3bp1io6OdmBlNSMiIkLBwcF2483NzdXWrVvrzHiNMRozZozee+89ff7554qIiLBb3qlTJ9WrV89ujAcOHFBGRkadGWNZiouLVVBQYInx9enTR3v27NHOnTttj86dO2vw4MG2v9f1Mf7RmTNndPjwYTVr1swS76Ek9ejRo9RtHw4ePKjw8HBJ1vh5U2LRokVq2rSp+vXrZ2uzwvuYn58vV1f7SOHm5qbi4mJJTvAe1vgl0H8iy5cvN56enmbx4sVm//79ZtSoUcbf399kZmY6urQqOX36tPnmm2/MN998YySZF154wXzzzTfmyJEjxpjfpxH6+/ub999/3+zevdvcdtttdWoq6N/+9jfj5+dnNmzYYDclND8/39bnoYceMmFhYebzzz8327dvN9HR0SY6OtqBVVfO1KlTTUpKiklPTze7d+82U6dONS4uLubTTz81xtT98ZXl/NlYxtT9MT7yyCNmw4YNJj093Xz55ZcmJibGBAYGmhMnThhj6v74jPn9tgHu7u7m6aefNocOHTJLly419evXN0uWLLH1qes/b4z5fYZuWFiYmTJlSqlldf19HDZsmLnssstsU89XrFhhAgMDzeTJk219HPkeEnaqWXJysgkLCzMeHh6ma9euZsuWLY4uqcrWr19vJJV6DBs2zBjz+1TC+Ph4ExQUZDw9PU2fPn3MgQMHHFt0JZQ1Nklm0aJFtj6//vqr+fvf/24aNWpk6tevb26//XZz7NgxxxVdSffff78JDw83Hh4epkmTJqZPnz62oGNM3R9fWf4Ydur6GO+55x7TrFkz4+HhYS677DJzzz332N1/pq6Pr8QHH3xg2rZtazw9PU3r1q3Nq6++are8rv+8McaYTz75xEgqs+66/j7m5uaacePGmbCwMOPl5WUuv/xy89hjj5mCggJbH0e+hy7GnHd7QwAAAIvhmh0AAGBphB0AAGBphB0AAGBphB0AAGBphB0AAGBphB0AAGBphB0AAGBphB0AdVbv3r01fvz4S9rGhg0b5OLiUup7iQBYB2EHgNMaPny4BgwY4OgyANRxhB0AAGBphB0AdUJeXp6GDh0qHx8fNWvWTM8//3ypPv/85z/VuXNn+fr6Kjg4WPfee69OnDhh12f16tVq1aqVvL29df311+s///lPqe1s2rRJPXv2lLe3t0JDQzV27Fjl5eXV1NAA1DDCDoA6YdKkSUpJSdH777+vTz/9VBs2bFBqaqpdn3PnzikhIUG7du3SypUr9Z///EfDhw+3LT969KjuuOMO9e/fXzt37tQDDzygqVOn2m3j8OHDuummmzRw4EDt3r1b//73v7Vp0yaNGTOmNoYJoAbwRaAAnNbw4cOVnZ2tJUuWqHHjxlqyZInuuusuSdKpU6fUvHlzjRo1SklJSWWuv337dnXp0kWnT5+Wj4+PHn30Ub3//vvat2+frc/UqVP1zDPP6JdffpG/v78eeOABubm56ZVXXrH12bRpk3r16qW8vDx5eXnV6JgBVD+O7ABweocPH1ZhYaG6detmawsICNCVV15p12/Hjh3q37+/wsLC5Ovrq169ekmSMjIyJElpaWl225Ck6Ohou+e7du3S4sWL5ePjY3vExsaquLhY6enpNTE8ADXM3dEFAEB1yMvLU2xsrGJjY7V06VI1adJEGRkZio2NVWFhYYW3c+bMGT344IMaO3ZsqWVhYWHVWTKAWkLYAeD0IiMjVa9ePW3dutUWOH755RcdPHjQdvTm22+/1c8//6zZs2crNDRU0u+nsc4XFRWlVatW2bVt2bLF7nnHjh21f/9+tWzZsqaGA6CWcRoLgNPz8fHRiBEjNGnSJH3++efau3evhg8fLlfX//4ICwsLk4eHh5KTk/X9999r1apVSkhIsNvOQw89pEOHDmnSpEk6cOCAli1bpsWLF9v1mTJlir766iuNGTNGO3fu1KFDh/T+++9zgTJQhxF2ANQJc+bMUc+ePdW/f3/FxMTouuuuU6dOnWzLmzRposWLF+udd95RmzZtNHv2bD333HN22wgLC9P/+3//TytXrlSHDh20cOFCzZo1y65P+/btlZKSooMHD6pnz5665ppr9MQTTygkJKRWxgmg+jEbCwAAWBpHdgAAgKURdgAAgKURdgAAgKURdgAAgKURdgAAgKURdgAAgKURdgAAgKURdgAAgKURdgAAgKURdgAAgKURdgAAgKURdgAAgKX9f4296NzYHxhGAAAAAElFTkSuQmCC",
+      "text/plain": [
+       "<Figure size 640x480 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "variacao_idade = df_ordenado_sem_nan.groupby('Sex')['Age']\n",
+    "variacao_idade.plot.hist(fill=False)\n",
+    "\n",
+    "plt.xlabel('Idade')\n",
+    "plt.ylabel('Sexo')\n",
+    "plt.title('Média de Idade de acordo com o Sexo')\n",
+    "\n",
+    "plt.show()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### Qual foi a média de idade dos sobreviventes em relação ao seu sexo:\n",
+    "Pelos dados abaixo podemos ver como a maioria das mulheres sobreviventes eram mais velhas (média 28 anos) do que os homens (média 27 anos) sobreviventes no navio. Muito embora a maioria das passageiras mulheres fossem mais novas do que os passageiros homens."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 7,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "(342, 12)"
+      ]
+     },
+     "execution_count": 7,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "df_filtrado1 = df[df['Survived'] == True]\n",
+    "df_filtrado1.shape"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 8,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "Sex\n",
+       "female    28.847716\n",
+       "male      27.276022\n",
+       "Name: Age, dtype: float64"
+      ]
+     },
+     "execution_count": 8,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "media_idade_genero = df_filtrado1.groupby('Sex')['Age'].mean()\n",
+    "media_idade_genero"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 9,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 640x480 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "media_idade_genero = df_filtrado1.groupby('Sex')['Age'].mean()\n",
+    "media_idade_genero.plot.bar()\n",
+    "\n",
+    "plt.xlabel('Sexo')\n",
+    "plt.ylabel('Idade')\n",
+    "plt.title('Média de Idade de acordo com o Sexo')\n",
+    "\n",
+    "plt.show()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### Qual foi a média de sobreviventes por Porto de Embarque:\n",
+    " - C: Cherbourg\n",
+    " - Q: Queenstown\n",
+    " - S: Southampton\n",
+    "\n",
+    " Pelos dados abaixo podemos ver como a maioria dos sobreviventes embarcaram no porto de Cherbourg."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 10,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 640x480 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "taxa_sob_porto = df.groupby('Embarked')['Survived'].mean()\n",
+    "taxa_sob_porto.plot.bar()\n",
+    "\n",
+    "plt.xlabel('Embarcados')\n",
+    "plt.ylabel('Sobreviventes')\n",
+    "plt.title('Taxa de Sobrevivência por Porto')\n",
+    "\n",
+    "plt.show()"
+   ]
+  }
+ ],
+ "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/titanic.csv b/exercicios/para-casa/titanic.csv
new file mode 100644
index 0000000..5cc466e
--- /dev/null
+++ b/exercicios/para-casa/titanic.csv
@@ -0,0 +1,892 @@
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