Titanic-Udacity_SuzanaMota.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Entendendo o Titanic\n",
    "\n",
    "O naufrágio do RMS Titanic foi um dos maiores e mais lembrados naufrágios da história. Em 15 de abril de 1912, durante sua viagem inaugural, o Titanic afundou depois de colidir com um iceberg, matando 1502 de 2224 passageiros e tripulantes. Esta tragédia chocou a comunidade internacional e levou a melhorias nas normas de segurança para os navios.\n",
    "\n",
    "Uma das razões pelas quais o naufrágio causou tantas mortes, foi a ausência de botes salva-vidas suficientes para os passageiros e a tripulação. Embora houvesse algum elemento de sorte envolvido na sobrevivência do naufrágio, alguns grupos de pessoas tinham maior probabilidade de sobreviver do que outros, como mulheres, crianças e a classe alta.\n",
    "\n",
    "![Image of Yaktocat](https://github.com/suzanasvm/TitanicUdacity/blob/master/titanic.jpg?raw=true)\n",
    "\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Etapa 1:\n",
    "## Importando bibliotecas "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 180,
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import pandas as pd\n",
    "import matplotlib.pyplot as plt"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Etapa 2:\n",
    "## Lendo arquivo CSV"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 181,
   "metadata": {},
   "outputs": [],
   "source": [
    "titanic = pd.read_csv('titanic-data-6.csv')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Exibindo alguns registros"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 182,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "<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",
       "  </tbody>\n",
       "</table>\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",
       "                                                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",
       "   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  "
      ]
     },
     "execution_count": 182,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "titanic.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Observando variáveis disponíveis:\n",
    "\n",
    "Survived (Sobreviveu): 0 = Não, 1 = Sim <br>\n",
    "Pclass (Classe): Classe de ingresso 1 = 1º, 2 = 2º, 3 = 3º<br>\n",
    "Sex (Sexo): Sexo do passageiro<br>\n",
    "Age (Idade): Idade em anos<br>\n",
    "Sibsp: Quantidade de irmãos / cônjuges a bordo do Titanic<br>\n",
    "Parch: Quantidade de pais / crianças a bordo do Titanic<br>\n",
    "Ticket (Bilhete): Número do bilhete de embarque<br>\n",
    "Fare (Tarifa): Tarifa paga pelo Passageiro<br>\n",
    "Cabin (Cabine): Número de cabine<br>\n",
    "Embarked (Embarque): Porto de Embarque (C = Cherbourg, Q = Queenstown, S = Southampton)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Etapa 3:\n",
    "## Limpando dados\n",
    "Excluindo colunas que não serão utilizadas: Ticket, Pclass, Cabin, Fare, PassengerID, SibSp"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 183,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Survived</th>\n",
       "      <th>Name</th>\n",
       "      <th>Sex</th>\n",
       "      <th>Age</th>\n",
       "      <th>Parch</th>\n",
       "      <th>Embarked</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0</td>\n",
       "      <td>Braund, Mr. Owen Harris</td>\n",
       "      <td>male</td>\n",
       "      <td>22.0</td>\n",
       "      <td>0</td>\n",
       "      <td>S</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\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>0</td>\n",
       "      <td>C</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>1</td>\n",
       "      <td>Heikkinen, Miss. Laina</td>\n",
       "      <td>female</td>\n",
       "      <td>26.0</td>\n",
       "      <td>0</td>\n",
       "      <td>S</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\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>0</td>\n",
       "      <td>S</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>0</td>\n",
       "      <td>Allen, Mr. William Henry</td>\n",
       "      <td>male</td>\n",
       "      <td>35.0</td>\n",
       "      <td>0</td>\n",
       "      <td>S</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
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      ],
      "text/plain": [
       "   Survived                                               Name     Sex   Age  \\\n",
       "0         0                            Braund, Mr. Owen Harris    male  22.0   \n",
       "1         1  Cumings, Mrs. John Bradley (Florence Briggs Th...  female  38.0   \n",
       "2         1                             Heikkinen, Miss. Laina  female  26.0   \n",
       "3         1       Futrelle, Mrs. Jacques Heath (Lily May Peel)  female  35.0   \n",
       "4         0                           Allen, Mr. William Henry    male  35.0   \n",
       "\n",
       "   Parch Embarked  \n",
       "0      0        S  \n",
       "1      0        C  \n",
       "2      0        S  \n",
       "3      0        S  \n",
       "4      0        S  "
      ]
     },
     "execution_count": 183,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "def limpa(coluna,valor):\n",
    "    titanic[coluna].fillna(valor,inplace=True)\n",
    "    return titanic.head(6)\n",
    "    \n",
    "    \n",
    "def remove(colunas):\n",
    "    for i in range(0, len(colunas)):\n",
    "        titanic.drop([colunas[i]],axis = 1, inplace = True)\n",
    "    return titanic.head()\n",
    "\n",
    "colunas = ['Pclass','Fare','Ticket','Cabin','PassengerId','SibSp']\n",
    "remove(colunas)\n",
    "\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Funções para filtro de dados:\n",
    "\n",
    "Remove coluna: Retira as colunas indicadas na passagem de parametros\n",
    "\n",
    "Limpa Coluna e Valores: Recebe a coluna desejada e o valor a ser filtrado e remove os itens com estas características."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 184,
   "metadata": {},
   "outputs": [],
   "source": [
    "titanic_idade = titanic.copy()\n",
    "titanic_idade.drop(titanic[titanic['Age'].isnull() == True].index ,inplace=True)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Etapa 4:\n",
    "### Fazendo perguntas"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Pergunta 1: Qual a porcentagem dos passageiros sobreviventes?"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 185,
   "metadata": {},
   "outputs": [],
   "source": [
    "titanic['Not Survived'] = titanic['Survived'].map({0:1,1:0})"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 186,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Sobreviventes     : 342\n",
      "Não Sobreviventes : 549\n"
     ]
    }
   ],
   "source": [
    "print('Sobreviventes     :', titanic['Survived'].value_counts()[1])\n",
    "print('Não Sobreviventes :', titanic['Survived'].value_counts()[0])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 187,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0,0.5,'')"
      ]
     },
     "execution_count": 187,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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FpYiISBpZQRcgIt0zf9p0A4qA4pRbId7nOPzGiCmJqw67OAtI+Lc40AjU+rf11bNmJoKoXWSgU1iKZID506bnApOBSUCZ/7fj/wlAKRBlO3uDWrJy3gI+vp3ZuPLKqno2h2ctsAZYCHwILAA+rJ41s2lnl0dksFFYivSz+dOmlwMf63SbAoR3ZrqNyURJmlEMKPFvu3YxjiuvrFqJF54fAu8DrwKvVs+a2bIz9YkMZApLkT40f9r0HOAA4HDgCOAgvN2nva416Qp7YTIGjPdvFSmPt5dXVr0BvAS8CLxYPWvm8l6Yn8iAYM65oGsQGTTmT5uehReKn/L/HgDk9Me8nxg5bc0Nh14wuj/m5VuOF5xPAv+onjVzTT/OW6RfqWUpspPmT5teAhwHnOCcO9bM0u0OHSwmAKf5N1deWfUy8HfgsepZM98JtDKRXqaWpcgOmD9t+hi8kDjJOXe4mQW+4RlAy3J7qvGDE5its3BloFNYinSTf8bqic65s4FjzGynTsjpbRkWlqlWAXcDd1TPmrkg6GJEdoTCUiSN+dOmHwKc45w73cz65OSc3pDBYZnqOeAO4KHqWTMbgy5GpLsC33Ukkon8VuSXks59O2S2J4CZBVzVoHC4f7uhvLLqQeAP1bNmvhxwTSJpKSxFUsyfNn2Mc+7SJFwSNisNKSD7ShS4ALigvLLqeeCa6lkznwi4JpEuKSxFgPnTpu+dcO7KEJxmZtkZdTBy8DsMeLy8supNYBbwF50QJJlGYSlD2vxp0/dud+6nWfC5sPazBm0f4AFgYXll1S+Bu6tnzWwLuCYRQFcdkSFq/rTpu785dfdHnXNvZZudYArKTDIFuBVYXF5Z9fXyyipt1EvgFJYypMyfNn3C61N3v985915OKKSQzGzjgBuBd8orq2YGXYwMbQpLGRLmT5ue88puU3+ScG5hXih0hpnpvT9wTAP+UV5Z9a/yyqo9gy5GhiZ9YcigN2e3qV9oSSarC8Ph74fN+qWfVukTRwNvlVdW/b68smpk0MXI0KKwlEHrtam77/7yblNfKA6HH8oNhcYEXY/0ijBwMbCgvLLq8vLKKp24LP1CYSmDzvxp08PPT9nt2hyzedFw+JCg65E+UQz8GnipvLJqr6CLkcFPYSmDyt93mbx/QyKxYHhW1nfCGdZ3q/SJ/YHXyiurflheWZUddDEyeCksZVD4U1lZ6F+Td71+l0jkpaJweJeg65F+FQGuBubqBCDpKwpLGfAe22XyPpMjOQsmRSLfVGtySJuB18r8bnlllb7bpFfpDSUDVkU0ao+U71JZHom8XBIOTw66HskIOcCvgKfKK6tGBV2MDB4KSxmQrhg1uuS7I0f+d1pu7s+zzXSsSjqrwGtlHhh0ITI4KCxlwLlh/ISDTygqmj85knNk0LVIRpsAPFteWXVx0IXIwKewlAGjIhq1uyZNuuLwgoLZw7Oy9LtJ6Y4I8Pvyyqo7yyurcoMuRgYuhaUMCBXRaO5XS4c/cEBe/i9yQyH1wiM9dS7wQnllVXnAdcgApbCUjHdyScm4bw4f8fw+eXmnqd9z2Qn7Aq+WV1YdHnQhMvAoLCWjfXX48H0uLh3+4rTc3P2CrkUGheHAk+WVVScEXYgMLApLyVjfGzXq+C8PK/3PpEikLOhaZFDJBf5aXll1XtCFyMChsJSMUxGNWuWo0V89rbjkzyOyskqDrkcGpTBwR3ll1feCLkQGBoWlZJSKaDR737y8ylNLSn5TGA4XBF2PDHq/LK+s+lV5ZZUOhst2KSwlY1REozkzcvN++qWSYT/ID4Xygq5HhozvAneWV1ZlBV2IZC6FpWSEimg0d7+8vGu+PGzYZXmhkH4PJ/3tHOBu9SkrXdEbQwJXEY3m7Z+X98uzSoZ9Xb+hlACdCdwUdBGSmRSWEqiKaDR/r5zca84sGXZRTigUCboeGfIuKq+s+kXQRUjmUVhKYCqi0YKy7OyrzykddqGCUjLIFeWVVVcFXYRkFoWlBKIiGs0ZFc664qLhIy4sCOmsV8k4PyuvrLo06CIkcygspd9VRKNZ0VDo4q8NH/61knC4JOh6RLpwY3ll1ZeDLkIyg8JS+lVFNGoRs7MuGT7ie6Ozs0cGXY/IdhhexwVHBl2IBE9hKf2mIho14MRzhg27siwSGR90PSLdkAU8VF5ZpS4XhziFpfSnTx4XjX5vRl7+tKALEemBEcAj5ZVV+UEXIsFRWEq/qIhGp+2Vk/vd46NFBwZdi8gOmAHcHnQREhyFpfS5imh05Mhw1pXnlpYeETYLB12PyA46o7yy6oqgi5BgKCylT1VEo7nZZt/82vDhx+SHQtGg6xHZST8vr6w6JugipP8pLKXPVESjIeDss0uGnTQmO3ts0PWI9IIQ8IBO+Bl6FJbSlz5zUH7+afvm5e0VdCEivagEuEuX9RpaFJbSJyqi0Sml4fB5pxWXHGSm7xQZdI4Evh10EdJ/FJbS6yqi0ULgaxeWDj8gNxRSV3YyWF1TXlm1Z9BFSP9QWEqv8jse+NLMaNH+ZZHI5KDrEelDOcA95ZVV2UEXIn1PYSm9bf9xWVlHHx2N6veUMhTMAH4YdBHS9xSW0msqotHhwHnnDCv9eLaZLrklQ0VleWXVQUEXIX1LYSm9wv+ZyDlHFhROnhiJ7Bp0PSL9KAzcqd2xg5vCUnrLfnlm+322qEhb2DIUTQO+HnQR0ncUlrLT/LNfzzl7WOlu+aFQUdD1iATkh+WVVaOCLkL6hsJSesOJ03Jyxu+dm7tf0IWIBKgY+FnQRUjfUFjKTqmIRicDR51RUrJvyEzvJxnqzi+vrNo36CKk9+nLTXZYRTSaBZx7REFB6ais7ElB1yOSAULADUEXIb1PYSk742CDsmOjRQcEXYhIBjm0vLLqzKCLkN6lsJQdUhGN5gGnfTZaNLwkHB4ddD0iGeYX5ZVVOUEXIb1HYSk7qiLbLHpEYeGhQRcikoEmAOcFXYT0HoWl9FhFNFoEnHhKUfH4glCoJOh6RDLUleWVVVlBzdzMrjazpwKY7zwzO72/59vXFJayI46JmEUOyM9XBwQiXSsHztqZCZjZZDN7yMxWm9lGM1tmZo9YBncn6Zzb0zn3YH/Nz8ycmR3W1/NRWEqPVESjI4BjPxctGpkbChUGXY9Ihvuf8sqqnfmefRxYBewORIGDgX8BvX6RWDNTd33bobCUnjoGcGpVinTLVOC0HXmimQ3HC8mbnXP1zrPcOXezc67VH+drZvaBmdWb2RwzO3zrydh1ZlZrZsvNrDJlwJFmFjezL5vZImC9/3i+mV1rZovNbL2Z/dPMpvjDPmtma1OD1cwK/VbvEf79ajM7y///VTO7rFNBPzKz/6bcP8nMXjOzDWY238y+lDLsXDNbaGbf9OuvM7NbzCzsD3/LH/VJv4bb0i2DP/wMf14xM1tjZnelez0UltJtFdFoMVBxdGG0KBoODw+6HpEB4qryyqoetwSdc7XAPOA2MzvbzPYws03TMbMvAj8BzgaGA38A/mlmZSmTOQJYA4wFTgQu95/XIQwch3epsY6z2m/D6+v2IGAMMBf4hx+QTwBxYGbKNE4FVgPPbWMx7iDlRCe//rOBO/37RwG3A98CSoFzgN92BK+vzK9tV2B/f35n+Ovo4/44RzvnCp1zF6RbBjPLB+4BLnXORYHJfg3bpbCUnjgcsMMKCg4OuhCRAWRv4IQdfO6RwNN4YfImsMbM/s8PnfOAW5xzc51zcefc7cDbQOpvPFcBv3DOtTnnXgNuZeuzdCv9lmuTmY0Avghc4pxb45xrA36EF7YHOucSeEGTOo3zgDudc24b9d8PTDOzGf79CrxQfNi/fxlwvXPuOedc0jn3MnAvXqB2aAZ+4Jxrdc4tBP4DfKKrFZZuGfzR2v26Sp1zjc65bQX9FhSW0i3+7ypnHpCXnz0iK2tC0PWIDDDf3JEnOedqnHNXOef2BUqAK4Af4AXURGBRp6d85D/eYUmnEKvG+1lLhySwLOX+Lv7ft/3dohvwds9mp0z3TuA4MxtlZrsChwB3d1F/HfA3NofrecADzrmmlPld2TEvf37nAuNSJrPWD+kOjXjHb7uy3WXw5308cCzwkb8LOG0nEgpL6a4DgNwjCwtnpB1TRDqrKK+smrozE3DONTnn7sJrPe6DF3K7dBptMluGX1nqrlu8M3SXbznZLcJ0if93N+dcScot3zl3v/+E94HX8M70PRd4yjmXOs3O7gTO9Ft8n/fvp87v6k7zijrnjt/O9Drr3KLtzjI87Zw7ARgB/BS41w/+LiksJS2/D9gTS8PhjROzs6cHXY/IAGTART16gtkwM/u5me3lH2vLMrNTgL3wjg/eBVxkZgf4w87FC9H7UyYzFvie//wZwIV00QoEcM6tBe4DbjKz8X4dJWZ2spmlnv1+J3A+3u7SO9Isyr/xdqX+Ea+lOydl2G+Ab5nZ4WYWNrOIme1nZl3uZt2G1cBu3V0GMxttZqeYWbHfYt3gPzWx1ZRTKCylO/YAhh0bjU4J+2ehiUiPndvDLvDagFHAX/F2I64Dvg98wzn3kHPuPrxjcfcCtcAlwPHOueqUaTyHF5irgX8A1+MFyfZcCHwAPG1mMeAdvJNqUltwD+C1YguBR7c3MedcEi8oj6NTsDrnngS+CvwKqME7xnqdP93u+l/gxx1nynZjGULApUC1P+x3wDmd1ttWbNvHZEU2q4hGLwOmXjNm7CnqBzZzPTFy2pobDr1Ar09mO7161sw/B12E9JxalrJdFdFoKfDxffPyIgpKkZ2m/mIHKIWlpLMfwOEFBfsEXYjIIHB0eWXV+KCLkJ5TWEqXKqLREHBMFqzfJRLZK+h6RAaBEPCltGNJxlFYyvZMAYYfWlAwKmKh3KCLERkkTgq6AOk5haVsz0FA+8dz8/RzEZHec2B5ZdWooIuQnlFYyjb5v608yKCmLBLZPeh6RAaREPC5oIuQnlFYSld2AXL3z8sflRcKba9rKRHpuR3tK1YCorCUrswAEvvlaResSB/4THllVV7QRUj3KSxlK/5ZsIcAtWWRyE71Zyki25QPfCboIqT7soIuQDLSRKBoXFZWvCgcHhF0MTJ41T37Rxrfe4ZkcwOWFSF3wp4M+/QFZBWNwiUTbOgY3tpIVtEoig/9IgXTDks73ba1i1l197fJnbgno8/4Wcr87mHjG48Tyosy/PhvkTthDwBcIs7qe75D6bHfIGfMlK4m29tOAP7eXzOTnaOwlG3ZG3CfyM/vfEUDkV5VuGcFxQeeQiingGR7CxuevYeaR3/JmC9fS+z1KhrnzWb0GdeQVTqe5gVzWPfoL4iMLCN7+MQup+mSCWqfuJ7ciXts8Xjr6oU0zX+W8Rf9gZYlb7P+yZsYd/5vAah/6c/kls/oz6AE7zJRMkBoN6xsywygYXIkpzzoQmRwyx4+kVBOgXfHgVmI9vUrAIhvWEXOxL3JHj4BMyN/6sGE86K0rVuynSl6wRcZsxs5E/bc4vF43SoiY3cjlFtI3q6fIF63CoC2ddU0ffACJYelvaRhbxtXXllV1t8zlR2jsJQt+Bd53gVoGJuVVR5wOTIENL73NEuvO41l132Bhtceo9gPrcKPH0N7zRLaapbikgka338el0yQO7HrzqTa1lXT+O5/GHbk1l2wZo8so23VAhLNMZo+eoXskeV+K/RGSo+5BMuK9NkybsfBQcxUek67YaWzMsBNyM4ujIbDpUEXI4NfwR5HUrDHkSQ21rHx7SeJjPQaW1nFY8iZsCerbr8UzLCsbEbM/A7hgpJtTsclE9Q+/huGffpCQjn5Ww2PjJhE0QEns+aB/yWcV8Tw4y+j4ZVHyRm7G1nFY1j3yDUkmurJ22Vfig85vU+XOcXBeJe7kgynsJTOdgPcvnl55UEXIkNLuHAYhR8/hhW3XMD4r91J3X//QHz9SsZffDvhohG0rviAdY/8FIvkkrfLvls9v2Huw2QNG0f+lAO7nEd0xvFEZ3iHCtvrVtL4zr8Zc/b/o/afN5K36/4U7PUp1tx/FZGxU8nbZUafLWsKtSwHCO2Glc5mAA0TsyPjgi5Ehh6XTODaW0hsrKVt9UIK9voUWcWjMAuRO2E6uRP2pHnRa9t8bvPi12n+6BWW3XAmy279mL/YAAAgAElEQVQ4k4a5f6Vl2TyW3XAmiebYlvNxjtonbvBaoZE82tcuJmf8dCwUJmf8dNrWftQfiwuwj35vOTCoZSmb+Mcry4FlI7PCYwIuRwY555LEXq+iYNrhhAtKiDfUsP6pmwkXjyZ7+ERyxu9B47ynyZtyAFnREbSu/ICWpe8w7NMXbnN6I0/6H1y8fdP9hlceoW31AkZ87gpCuQVbjLvxzSfIKhmzqYWaVTKG5kWvES4aScvStyk+8At9t+Bbysa7DN7z/TVD2TEKS0k1FnCAKwkrLKXvNS96lfoXH8C1txDKKSBn0t6MPv2nWCjMsIrzqXv6Dlb/8XKSbc2E80soOuBkCvf6FADxhrWsvO0SRp16NbkT9yKcX7zFtEM5+Vg4m6yiLX8qHG9YR8OrjzL2y7/e9FjJkedR8/dr2fDCfeRPPYS8qQf1/cJvdjAKy4xnzrmga5AMURGNHgJcWJadveHKUaO/FXQ90jNPjJy25oZDLxgddB3SYw9Vz5p5WtBFyPbpmKWk2hVo3T0nV61Kkf6jLiUHAIWlpNoN2DghO1thKdJ/dg26AElPYSnAputXjgeaRmZljQy6HpEhpLC8smps0EXI9ikspUPHlduTRaGQOiMQ6V+7BV2AbJ/CUjqMAgygIBwaFnAtIkNNv/bgLj2nsJQOwwGKQ6GciIVygy5GZIhRyzLDKSylwwSgdWJ2pDjtmCLS2xSWGU5hKR3GAS2jsrKKgi5EZAiaHHQBsn0KS+kwAmgpzQorLEX6n06qy3AKS6EiGg0BJUBbYSi09bWNRKSv6aS6DKewFICo/9fl6uQekSBEyyur9H2cwfTiCEABXgfq5IRMYSnS/wxv745kKIWlAORs+sdCOdsbUUT6jHbFZjCFpQBsak1GTC1LkYCoZZnBFJYCXlgaQMRMLUuRYKhlmcEUlgLeblgDyDKLBFyLyFClDkEymMJSIKVlaf5fERHZTGEp4J0NmwRw/lmxItLvEkEXIF1TWAp4rUmF5AC3S2NNrkvE24KuQ3aYwjKDKSylg3a/DnDTmmqKvz73j7UumdSX7sCk1y2DKSwF1KocND679r2xZ77+0CrnnF7TgUdhmcEUlgJbhqW+ZAe4s5e/MuGYeY8vDboO6TGFZQZTWMoW4s7Fg65Bdt63F84u22/Bc9VB1yE9orDMYApL2UKbc81B1yC946fzHi3fdembS4KuQ7pNYZnBFJYC0Ir/Xmh1yZaAa5FedMNr95aNXrNgWdB1SLesD7oA6ZrCUgA2tSZbkk5hOYiEDG596Q/ji9YvWxl0LZLWmqALkK4pLAWgBb9TglansBxsIiRDtz1/08jc2Lq1QdciXUoAtUEXIV1TWAp4YekAmpJJHbMchKLJ9uxbn7mhKKupXrv6MtO66lkzk0EXIV1TWAp4YQlAo8Jy0BoZb8797TPXR6y1qSHoWmQr2gWb4RSWAinHLGsS8fogC5G+VdbaUHjtszcmaW9tCroW2YLCMsMpLAW8lqUBrGhvrwu4FuljezSuK/nB8zc3uUR7a9C1yCYKywynsBSAGF5Y2tK2toakukob9A6uXzbisjl317lkQr/tywwKywynsBRmx2JxoA7IiUOyxTkd0xoCjlv3/pizX3twlXNJbRwFb1HQBcj2KSylwxq8i0CzMZncEHAt0k/OXPH6hM++8w91WhC8eUEXINunsJQOq/DDsiGR0HHLIeTri56ddNAHs6uDrmOIU1hmOIWldFgJRABqEvGagGuRfvbD+VXlu1e/qn5kg7GmetZMdUiQ4RSW0mHTj9WXtrWvDrIQCcZv3nygbNyq93Vpr/6nVuUAoLCUDrX4vfi819qyKogCXmxs5Iwl1ez34QccsnABP17jZfb7LS18dfkyjli4gD0+eJ/Xmrr3E8F769Zz3KKP2O/DD/jURwt5uH7zodgH6uo4fOECPvXRQp6KxbZ43leXL9vqsaHi5jm3TyypXboi6DqGGIXlAJAVdAGSMdbg/3xkbTze1JxMxvJCoWh/zfzlpka+vXIFPx4zhoqCQhzwUVsbANlmHFUY5RvDR3D60u7tKby5tobH6hv41bhx7JGTS0MySV3Cu1RnTTzODbU1/LWsnJpEnK8uX05FYSFhM/5WX080FOIz0X5b9IySbc5uf/6m0WdVfHtNc9Ho0UHXM0QoLAcAtSwFgNmxWCteYOYBrE8k+nVX7HXr1nF6SQnHRIuIhELkhELskZsLwK45OZxaUsLeeXndmlZDIsGttbX8z+hR7JWbR8iMknCYXSI5AKxsb6csO5sx2dnslZtHGNiQSFATj3NLbQ3/O2poZ0S+i2fd9syNJdmNdTqO1j8UlgOAwlJSLQQKAdbG2/ttV2xTMsk7LS1EzDilejGHLFzAOUuX8G7LjnVT+1ZLMy3OsaytnaMWfcQRCxfw3ZUrqIl7LctJkQjL29tZ0d7O283NZJlRGg7zkzWruXTECEqztMOlNNGSc9MzN+SFWjaq+8O+lQDeDLoISU9hKak+xP/5yJK29n67/mFDIkES+Et9PdeMGcvTu07hkIICLl6+nIYd6GCmLu49598bYzwwqYx/7DKZFue4cpW3SCXhMD8YPYbLV67gl+vWcu3YcTy5MUa7cxxZUMhVq1by5aVLmLV2DfEh3JnRhLZY/q+f/S20tzQGXcsg9lb1rJkbgy5C0lNYSqrV+Ne1fK25aWl/9XpXEPLehicXFbN7bi4RM75aOpy4c7zR3PPWZcf0LiwdzvCsLIrCYS4dPoI5TU00Jb2rIB0VjfJgWTn3Tipj15wcrl9Xww9Hj+HW9bWMzc7mnkll1MYTPFI/tBtW05pqin/83M0txNWPbB95PugCpHsUlpJqFf57ojaRaK5PJvvluGU0HGZ8djZmWw/bxkNpTfOPdXb3ubPWruG80lJGZ2fzQWsrM/xjo/vl5zG/VdfC3r9h+fDLX7p9g0v6Z0hJb3ou6AKkexSWssnsWGwjXuuyAGB5e9vi/pr3GSUlPFJfz8LWVuLOccf69UTMmJGXh3OO1mSSVr9V2O7fT3TR8h2fnc0RBQX8YX0tGxIJGpMJbq6t4dCCAvJDW77ln924kTXxOKeWlAAwMTub5xsbiTvHC42NTMqO9O2CDxBH1S4c/ZVX7lvrXFIXKO4lztt182zQdUj3KCyls9eBEoAPW1ur+2um5w8r5fPFxZy3bCmHLlzAc42N3DJhItFwmJXxdmYs+JAZCz70xl2+jBkLPuSxhs27SPf78AP+nnJ/1thxDA9ncdSijzh20SJyQyFmjRm7xTwbkwl+uW4tPx49ZtNjXx0+nHktLRyycAEOOM0PUYFTV7017uS3Hl2hi9L0DjN7p3rWzLVB1yHdY3rjS6qKaHQv4NvAsuJQKOdnY8ZeGbJt7SCVoeqa3Y9d8tz0z5QFXccgcF31rJmXB12EdI9altJZNX7nBPXJZGtdItFvZ8XKwHDVB/8s23Px3Oqg6xgE/hN0AdJ9CkvZgn/ccjn+7y0XtbV9GGxFkomufeuh8okr56nj9R3knGsCZgddh3SfwlK25XWgGGBuU+P8gGuRDPW7uXdNKq2pXh50HQORmVVVz5rZvU6OJSMoLGVb3sN/b7zX2rquIZHQJbtkK9nm7LYXfj+2oH61rlLTc38OugDpGYWlbMsioAX/+paL2trUupRtynOJ8G3P3lgaaVyvDapu8nfBPh50HdIzCkvZyuxYLA7MBYYDvNLUpLCULpUkWiM3P319fqgltiH92KJdsAOTwlK68ir+JdzeaGle1ZhM6otQujS2vTH/hmduCFlbs/o5Te+hoAuQnlNYSlcWAHH8wFzY2vpusOVIptu1ua7omuduaiPepj4Cu+Dvgq0Kug7puV4LSzObaWbrzewSM/uOmZ3RW9PuYR1Xm9lTAcx3npmd3t/z7SuzY7E24DX8XbH/3bjxjWArkoFgn9iq0itfvK3BJeLtQdeSibQLduBKG5Zm9rSZOTM7otPjC83s3JSHPg0cDewFnAD8szcLzXTOuT2dcw/21/z81+SwPp7NHCAHYEFb6/qaeHxZH89PBoEj1y8adfEr965TP7LbdFvQBciO6W7Lsha41rbT7Zlz7nLn3KvOuUucc590zg2IY1xmlh10DRlsPt5ZsTkAbzY3vx5sOTJQnLT63XGnvvFX9SObwjn3IfDvoOuQHdPdsPwDMAH44rYGmlm+mf3VzFabWYOZvW5mR3Ua5xQze8vM6v2/J3c1MzMbZmYPmVmtP/67ZnZ4yvCvmdkH/rA5qcM2j2LX+c9fbmaVKQOONLO4mX3ZzBYB61OW4VozW+zvTv6nmU3xh33WzNamBquZFZrZxo4Wt5lVm9lZ/v+vmtllnQr6kZn9N+X+SWb2mpltMLP5ZvallGHn+i33b/r115nZLWYW9oe/5Y/6pF/DbemWwR9+hj+vmJmtMbO7unoNAGbHYu3Af4ERAP/aGJvX5pyOR0m3fGXpnImfmv8v9fLjM7PfVc+aqa2HAaq7YdkI/AC4xsxyupjOX4Hd8I5x3Q88bGYjAczsYOBPQKU//CrgfjM7sIv5fQ/IB8rwroDxebwu2DCzLwI/Ac72p/UH4J9mltqx8xHAGmAscCJwuf+8DmHgOGAGMNp/7DZgGnAQMAbvpxP/8APyCbyTXWamTONUvMtZbet6dHcA53Xc8VvkZwN3+vePAm4HvgWUAucAv+20q7vMr21XYH9/fmcAOOc+7o9ztHOu0Dl3QbplMLN84B7gUudcFJjs15DOHPyTfBqTyfaFra1vd+M5IgBc8eFTZR//6MXqoOsImnOuEbg76Dpkx/XkBJ87gRhwWecBzrmNzrl7nXMx51y7c+5XQBvelzx4wfGwc+4J51zcOVcFPAKc38W82vCCcHe8K6N86JxbnDKtW5xzc/1p3Q68DZyZ8vxVwC+cc23OudeAW0kJL1+lc67eOddkZiPwWs2XOOfWOOfagB/hhe2BzrkEXtCkTuM84E637f1M9wPTzGyGf78CLxQf9u9fBlzvnHvOOZd0zr0M3IsXqB2agR8451qdcwvxOl3+RBfri3TL4I/W7tdV6pxrdM5158KzK4DFwDCApzbGXtGuNemJWe/8tbx8+TtDvYV5T/WsmfXpR5NM1e2w9APjCuAqMxueOszM8szsRjNb5O+G3YD35TrSH2UiXq8wqT7yH9+WX+GFw93AOjO728w6WoDdmdaSTiFWjbcbuUMSSD1ZZRf/79v+btENeLtns1OmeydwnJmNMrNdgUPoYkvROVcH/I3N4Xoe8IB/2njH/K7smJc/v3OBcSmTWeuv8w6NQHRb8+vOMvjzPh44FvjI3wV8ZhfT2mR2LObwWtZFAO+3ttasiLd/kO55IqlufOWPk0as/WjIniBmZr8NugbZOT366Yhz7gngZbxdsqkuBz6Jd0ZssXOuBKjDu9QTeMG0S6fnTGbLwEqdT6Nz7n+dc3sBewLj8QK0u9Mq63QyUjn+btzNs9giTDu2endzzpWk3PKdc/f7T3gf76cUZ+EF21POue11In0ncKbf4vu8fz91fld3mlfUOXf8dqbXWefmXXeW4Wnn3Al4xyB/CtzrB3867+C1dHMAnoptfL4HdYqQZc7+8OKt4wrrVqwKupb+5px7pnrWzHlB1yE7Z0d+Z/k94KtsbjWC1+poxTtrNmJmP8A71tjhLuAUMzvGzMJmdhxbB8gmZvY5M5vun9CyEe+MzHjKtC4yswPMLMu8n6/sg7frs8NY4Hv+sboZwIVs53iBc24tcB9wk5mN92soMbOTzawwZdQ78XYdn413XHJ7/o0XMH/Ea+nOSRn2G+BbZna4vz4iZrafmXW5m3UbVuMdI+7WMpjZaPNOsir2W6wdZysntppyJ7NjsRa81uVogJebm5avi8eX9qBWEXJJhO947ncjcjbWrg26lv5kZtcFXYPsvB6HpXPuLeAB/N1yvv+H9+W7Em+XaBPers+O57yIdxLLtXgtzl8CZ3UKkFS7An8HGvzpNOOdHIRz7j68Y3H34oXzJcDxzrnqlOc/hxeYq4F/ANfjBcn2XAh8ADxtZjG81tSpbNmCewCvFVsIPLq9iTnnknhBeRydgtU59yTeBsevgBq8Y6zX+dPtrv8Fftxxpmw3liEEXApU+8N+B5zTab1tz7N4wZoF8GyjWpfSc9FkW/Ytz1wfDTc31AVdS39wycSb1bNmbve7QgYG08ka0l0V0egXgU/hnfTDz8eM/VpxODwq2KpkIFqcWxK79FOX4yL52zsOPxjMrJ41U1cYGQTUN6z0xH/wWpYhgBcaG58NthwZqHZp2RD9xbO/SxBvaw66lr7iEu2vKSgHD4WldNvsWGwt8CL+scuqWMO89fH4ymCrkoFq741rSq564daNLhFvC7qWvmDh7CuDrkF6j8JSeuqfeBeFDjngXxtj/d5pvQweh9dVj/z63D/WumQy7YlmA4lLtL9YPWvmf4KuQ3qPwlJ6ZHYstgx4Ca+HIJ5rbFy8qr19YbBVyUD22bXvjT3z9YdWddHBx4CkVuXgo7CUHfE3vC4DswD+1lD/1GD6opP+d/byVyYcM+/xQfFzJJdo/2/1rJk6W3yQUVhKj/nHLp/E+3kO77S0rFnU1qY+Y2WnfHvh7LJPLHhuQHeL51wybuHsS4KuQ3qfwlJ2VEfn8jkAD9Zv+E+71x+tyA77ybxHy6YsfWPABqZrb72+etZMdQc5CCksZYfMjsUa8DrDHw2wvL09Nrep8b/bf5ZIete/9qeyMWs+HHD9yCbbW1eHInnfD7oO6RsKS9kZTwP1+B28P7Bhw8v6KYnsrJDBLS/dNr5o/bKB9V5Kxi+qnjVT13sdpBSWssP8PmPvwuuY3ZLgHq6v/0dSJ/vIToqQDN32/E0jc2PrBkQ/ssnWxn8vve60x4KuQ/qOwlJ21tvAK/gn+7zR0rxqfmvr3GBLksEgmmzPvvWZG4qymurXB13L9rhEvNWyIp2vlyuDjMJSdop/vcuOK77kAPyxbv3spmRSF7qVnTYy3pz722euj1hrU0PQtXQl2d7y4yW/OmlF0HVI31JYyk6bHYvV4l2RZSxALJlse6S+/hH99lJ6Q1lrQ+G1z96YpL21Kf3Y/SvRsvH1cG7hz4OuQ/qewlJ6y7N4l1MbCfBCU+OSt1taXgi0Ihk09mhcV/KD529ucon21qBr6ZCMtzW59paTqmfN1EbhEKCwlF4xOxaLA7cDuXh9x3JH3frZOjtWesvB9ctGXDbn7jqXTGREP7LxulXfXP67cwbcT1xkxygspdf4/cbeB4wHaHcueXdd3cNx59qDrUwGi+PWvT/m7NceXOVcMtDWXLx+zaMrb7/k9iBrkP6lsJTeNht4CxgHsKCtdf0zjRufCLYkGUzOXPH6hM++84/AWnSJ5tjKRFP9F4OavwRDYSm9anYslgTuBNqBQoCH6+vfWNTaqr5jpdd8fdGzkw76YHZ1f8/XJeLxRGzdyavu/vagvWi1bJvCUnrd7FisDrgFGIX/Hvtdbc3fdfxSetMP51eV7179ar/2I9tet+rqlXd84+X+nKdkBoWl9InZsdjbeBeKngTQ7Fz8lvW1D7Ykk43BViaDyW/efKBs3Kr3++XSXm01Sx9bedvFP+uPeUnmUVhKX3oIeB//+OWy9vaGP9dveDDhXEaczSiDw81zbp9YUru0TzsFaK9b9X7DK4+c1pfzkMymsJQ+MzsWawduBhqBYQBzmpqWPasTfqQXZZuz25+/aXRew5o1fTH9RGPduqYPnj9m41tPZsxvPKX/KSylT82OxTYA1+Od7JMH8FB9/WvzWlrmBFqYDCr5Lp512zM3lmQ31tX25nSTrU2NTQtfPqHu6bv6ZVevZC6FpfS52bFYNXArXnd4YYCbamv+tbit9Z0g65LBpTTRknPTMzfkhVo29kq/xC4Rjzcvfv3i2idu0IadKCyl37wM/B3vhB9zwG9qav62sr19YbBlyWAyoS2Wf92zNxrtLTt1IplzSdey5M1Z6/7283t7qzYZ2BSW0i/8q5P8FXgeKAOvh5/ratb9uTYeXx5ocTKoTG2qLfrJc79vJb5j/cg6l3TNH716R+yNx3/Y27XJwKWwlH4zOxZL4F0s+i1gIkBjMtn+m5p19zUkEuuCrE0Gl080rCi9/KXbN7hkIt6T5znnXNOCOQ9vfOuflzYtmJvsq/pk4FFYSr9KOUN2Mf5PSmoTieYba2ruaUgkagItTgaVo2oXjv7KK/etdS7ZrdBzztH04YtVje88dUHTgrk681W2oLCUfjc7FmvGO0O2BhgNsCLeHvtNzbq76hOJtYEWJ4PKqaveGnfyW4+uSHdpVeccTQteerzx3f98uWnBXF24XLaisJRAzI7FYsCv8X6DORpgdTze+Ot1a++qS8RXB1qcDCoXVb8w8Yj3/9Nlt3jOOZoXzvln4ztPndW0YO6G/qxNBg6FpQRmdixWC8wCYviBWZNINF+7bt3dtfF4n/bIIkPLVR/8s2zPxXOrOz/uBeXcf298+99falowty6A0mSAsHS7J0T6WkU0Wgp8DygFVgEUhUKR74wc9aWRWVmTAi1OBpWvHnDekmXj9iwDcMlEonH+s483vf/ceU0L5vZqZwYy+CgsJSNURKMlwHfxrlSyEiDPLOuyESM/PykSmR5ocTJotDtz5x5+6YrakvGjYm8+/reWJW9d2rRgrk4sk7QUlpIxKqLRIuByYAKwHCAE9rXhI47eMzf3oECLk0FjtWU3nFYy7cHGmiVXKSiluxSWklEqotFC4FJgGrAUcACnF5fsf3hBwbEhMx1nlx22zFntFcn8Wz8k/POmBXNjQdcjA4fCUjJORTQaAc4FDgOWAAmATxYUTP58cclp2WY5AZYnA9Rr8eSG7ydyb1yblXtN04K5LUHXIwOLwlIyUkU0GgJOBk7EO4bZAjA1kjP8vNLS04rD4VFB1icDR9K55DONG994qL7+V8Bf/J6kRHpEYSkZqyIaNeBg4EKgDmgAyDfLunj4iJlTcnL2CbI+yXzNyWTjnzbUPfd6c/MvgGf8PopFekxhKRmvIhqdCnwDiOD/tATg5KLifSoKC4/PMssOrDjJWKva21fdsr72n2vj8V/NjsXmB12PDGwKSxkQ/N9iXsTmE38SAHvl5I46a9iwU4vC4RFB1ieZwznnXmlunndP3foHE/B7v/MLkZ2isJQBoyIazQZO8G9r8brKIxoKRc4vLT16aiRnPzMLskQJ2MZEYsMD9Rvmvt7cfDfe8cn2oGuSwUFhKQNORTT6MeBr/t01HY8fUVAw+YSi4hPyQ6HiYCqTIM1raZ53V13dy43J5E3Aazo+Kb1JYSkDUkU0OhJvt+wUvLNl28DrJu/80tKjp+bk7hdkfdJ/mpLJ2F/qN8yZ09T0PPCH2bHYqrRPEukhhaUMWBXRaBZwFPAFoBVv1yygVuZQ4Jxz81tb37u7bv0bsWTyfuDJ2bFYjy72LNJdCksZ8Cqi0fHAV4BdgRX4rcyCUCj7zJKSwz6Wm3dI2CwryBqld9XG4ysf3LDh9XdbW97Ea00uDbomGdwUljIopLQyT8XrwGBTK3NyJFJyenHJMRMjkWlB1Se9ozWZbJrduPHlxxoaFgOPAY/PjsXagq5LBj+FpQwqFdHoBOBsYHdgHbCxY9gnCwomHxctOk4/Mxl4kt4u17furVv/fn0y+Q5wr1qT0p8UljLo+F3l7QecBUTxOjJoB8iC0CnFJfsdkJ9/eF4oFA2wTOkG5xzV7W3z/rKh/v3F7W0rgXuBV2fHYsmga5OhRWEpg1ZFNJoHHAN8DogDq/GvYpJnlnVycfF+n8jLPyw3FCoMsEzpwrK2tvf/2lD/9getrY3AE3i7XBuDrkuGJoWlDHoV0eho4DS81mYTKccz882yPl9csv++eXmH5oZCBUHVKJutam//6G8N9W+809LSCLwJPDQ7FlsRdF0ytCksZUjwO2WfDHwe2BOv9591HcMLQqHsk4qK9/t4Xu4BhaHwsIDKHLKSziWr29vefaIh9t681pY2YB7wMLBInQtIJlBYypDih+YU4BRgOhADajqGh8A+UxidenBB/kGjs7LLg6ly6GhzyZb5La2vPtpQ/+HqeDwMLAQeAj5USEomUVjKkOSH5lS80NyNzZ0abDpxZO/c3NFHFUYP3CUS2Vu/0+xd9YnEujebm199rKF+ZbNzYWAR8AgwTyEpmUhhKUOaH5q7AJ8BDvQfXosXngCUhsO5nymM7rVXbu7HRmRlTQygzEGhLZls/qit7d3nGxvffaOlOQmEgDnAv4FqhaRkMoWliM+/DNhhwLFAHrABqE8dZ0okUnpkYeHHpubkfEzHNtNLOpdcFY9/9EZz05tPbdy4qs25Irwelp7EuxhzTZpJiGQEhaVIJxXRaA6wL15oTsLbNVsDNKeOd1B+/sQZeXnTyrMju0fD4eH9X2lmijvXvqq9/aP3W1s/eK5x45KaRKIACAPVwFPAG7NjsaZAixTpIYWlSBf8XbRj8X5y8mmgGK9VtA7vd5ub7BbJKT0wP3/3KTmRqSPCWZNCZqF+LzhALclk47L29g/eaWn+4PnGxiUtzg0DIng9KP0XeBlYpV2tMlApLEW6oSIaDeN11H4IcDCQhdfirMXri3aT0nA496D8/Mm7RnLKxmVnlxeFQqMG20Wp25xrWRdvX1rd1r743Zbm6rdbWjY4KMVbL+3Aa8DzeGe16kogMuApLEV6qCIajeAF58fwgrPIH1QPNOD3EtRheDict09e3oRdIzkTx2ZnTRwWDo+JWCi3X4veCUnnkrFksqY2EV+9rK19+XutLUvntbSsTUIhUAIYXgvyRbxOBBapc3MZbBSWIjvB31U7HpiG1+osZ3NY1uOFyFb9mE7Izo7uFskZPSE7e9SorKxRpVnh0UWh8Iggf6LinHPNzsViiUTtukR89ar2+JpFba1r5re2rmtzLonXz24RXkssM28AAAJDSURBVDgasBRv9+o8YJn6a5XBTGEp0osqotECvJOCdgP2Acr8QYb3c5RGvC73tgoWA0ZlZRWMz84uHhXOKirNChcXh8NFRaFwcV4oVJht5GRjOdlmOVlmOWGzcHdqijvX1uZcS7tzLW3+rTmZbGpIJurXxxMb1sbjG1bF2+uXtrfXt3uhGALy8VqOOSm1LgXeBj7E+6mH+mmVIUNhKdKH/DNrx/u3XfG63BvfabQWvCBtwTve160PZcQsXBQKRbL8k4mcd3POgcO5JLiGRKItvo1g7pgEkOvfcvDyumPeK4CP/NtqYPnsWKxlWxMRGQoUliL9zL9Q9XBgFN7ZtmXAaP+xYjbl3qbdnYYXeHEgkfI3lXX6PyvlFvKf71KGG95u4nV4YbjK/7saWKeTckS2pLAUySB+kEbxQrMYr3OEHKAAb7dox988tmwJupT/43jHSmP+bSNeq7UFbzdwPVA/OxZr7/slEhkcFJYiIiJpDKkfTouIiOwIhaWIiEgaCksREZE0FJYiIiJpKCxFRETSUFiKiIikobAUERFJQ2EpIiKShsJSREQkDYWliIhIGgpLERGRNBSWIiIiaSgsRURE0lBYioiIpKGwFBERSUNhKSIikobCUkREJA2FpYiISBoKSxERkTQUliIiImkoLEVERNJQWIqIiKShsBQREUlDYSkiIpKGwlJERCQNhaWIiEgaCksREZE0FJYiIiJpKCxFRETSUFiKiIikobAUERFJQ2EpIiKShsJSREQkDYWliIhIGv8fxWkG26lh0bIAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<Figure size 360x360 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "titanic['Survived'].value_counts().plot.pie(colors=('tab:red', 'tab:blue'), \n",
    "                                       title='Qual a porcentagem dos passageiros sobreviventes?', \n",
    "                                       fontsize=13, shadow=True, startangle=90,autopct='%1.1f%%',\n",
    "                                       labels=('Não sobreviventes','Sobreviventes'),\n",
    "                                       figsize=(5,5)).set_ylabel('')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Podemos observar que na totalidade, apenas 38,4% dos passageiros do Titanic sobreviveram ao naufrágio, tratando de números absolutos, foram 342 sobreviventes e 61,6% das pessoas não resistiram, totalizando 549 pessoas."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Pergunta 2: Qual a faixa etária dos passageiros do Titanic? "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 188,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0,0.5,'Frequência')"
      ]
     },
     "execution_count": 188,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "text/plain": [
       "<Figure size 432x288 with 0 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure();\n",
    "titanic_idade.hist(column='Age', color=('blue'), alpha=0.8, bins=10, figsize=(10,4))\n",
    "plt.title('Faixa Etária dos Passageiros')\n",
    "plt.xlabel('Idade')\n",
    "plt.ylabel('Frequência')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Pelo histograma, concluimos que a maior parte dos passageiros girava na faixa etária de 20 a 40 anos, aproximadamente."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Pergunta 3: Os menores de idade, sobreviveram mais dos que os maiores de idade?\n",
    "\n",
    "Considerando a maior idade brasileira, de 18 anos, dividiu-se os dados em dois grupos: os de crianças com indivíduos menores de 18 anos e adultos com indivíduos maiores de 18 anos."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 189,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(Text(0,0.5,''), Text(0.5,0,''))"
      ]
     },
     "execution_count": 189,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x180 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "titanic_idade['Crianca_Adulto'] = 0\n",
    "titanic_idade.loc[titanic_idade[titanic_idade['Age'] < 18].index, 'Crianca_Adulto'] = 'Crianças'\n",
    "titanic_idade.loc[titanic_idade[titanic_idade['Age'] >= 18].index, 'Crianca_Adulto'] = 'Adulto'\n",
    "titanic_idade.groupby('Crianca_Adulto')[['Survived']].mean()\n",
    "\n",
    "titanic_idade.groupby('Crianca_Adulto')['Survived'].mean().plot.barh(title='4.3. Média de Sobrevivência', figsize=(10,2.5),\n",
    "                                                                color=('tab:green','tab:blue')).set_ylabel(''),plt.xlabel('')\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Conclusões\n",
    "\n",
    "Foi possível identificar neste trabalho de análise de dados exploratório, que algumas características foram primordiais para a sobrevivência dos indivíduos.\n",
    "\n",
    "Primeiro que apenas 38,4 % das pessoas sobreviveram ao Titanic, falando de números absolutos foram 342 pessoas que sobreviveram, em universo de 891 pessoas.\n",
    "\n",
    "Identificamos que as crianças foram protegidas e tiveram uma chance de sobrevivência muito superior aos adultos, na faixa de 0,56 de sobrevivência para as crianças e 0,37 para os adultos.\n",
    "\n",
    "Seria possível obter outros pontos de vista e insights interessantes, analisando dados como: sexo, classe, faixa etária, entre outras informações em trabalhos futuros.\n",
    "\n",
    "# Limitações\n",
    "\n",
    "Encontrou-se neste projeto, como um dos principais fatores limitantes a ausência de alguns valores relevantes, como por exemplo, a idades de alguns passageiros.\n",
    "\n",
    "Medida Tomada: Foram considerados apenas os valores que possuíam a informação de idade, excluíndo-se todos aqueles com idade nula. Uma outra medida que poderia ter sido adotada, seria a predição das idades dos passageiros.\n",
    "\n",
    "\n",
    "# Fontes Utilizadas\n",
    "\n",
    "- https://www.kaggle.com/c/titanic\n",
    "- https://canalhistoria.pt/blogue/10-coisas-que-nao-sabias-sobre-o-titanic/\n",
    "- https://paulovasconcellos.com.br/o-que-o-naufr%C3%A1gio-do-titanic-nos-ensina-at%C3%A9-hoje-data-science-project-2fea8ff1c9b5\n"
   ]
  }
 ],
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  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}