titanic_video6_final.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Populating the interactive namespace from numpy and matplotlib\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/Users/mario/anaconda3/lib/python3.7/site-packages/IPython/core/magics/pylab.py:160: UserWarning: pylab import has clobbered these variables: ['test']\n",
      "`%matplotlib` prevents importing * from pylab and numpy\n",
      "  \"\\n`%matplotlib` prevents importing * from pylab and numpy\"\n"
     ]
    }
   ],
   "source": [
    "import pandas as pd\n",
    "import numpy as np\n",
    "%matplotlib inline\n",
    "%pylab inline\n",
    "from sklearn.model_selection import RepeatedKFold\n",
    "from sklearn.ensemble import RandomForestClassifier"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [],
   "source": [
    "def transformar_sexo(valor):\n",
    "    if valor == 'female':\n",
    "        return 1\n",
    "    else:\n",
    "        return 0"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [],
   "source": [
    "train = pd.read_csv(\"train.csv\")\n",
    "test = pd.read_csv(\"test.csv\")\n",
    "\n",
    "train['Sex_binario'] = train['Sex'].map(transformar_sexo)\n",
    "test['Sex_binario'] = test['Sex'].map(transformar_sexo)\n",
    "\n",
    "variaveis = ['Sex_binario', 'Age', 'Pclass', 'SibSp', 'Parch', 'Fare']\n",
    "\n",
    "X = train[variaveis].fillna(-1)\n",
    "y = train['Survived']"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "modelo anterior = 0.8041457147175896"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
     "data": {
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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",
       "      <th>Sex_binario</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",
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       "      <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",
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       "      <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",
       "      <td>1</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",
       "      <td>1</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",
       "      <td>0</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  Sex_binario  \n",
       "0      0         A/5 21171   7.2500   NaN        S            0  \n",
       "1      0          PC 17599  71.2833   C85        C            1  \n",
       "2      0  STON/O2. 3101282   7.9250   NaN        S            1  \n",
       "3      0            113803  53.1000  C123        S            1  \n",
       "4      0            373450   8.0500   NaN        S            0  "
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "train.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Análise erro"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Treino: 445\n",
      "Valid: 446\n",
      "Acc: 0.7869955156950673\n",
      "\n",
      "Treino: 446\n",
      "Valid: 445\n",
      "Acc: 0.7797752808988764\n",
      "\n",
      "Treino: 445\n",
      "Valid: 446\n",
      "Acc: 0.827354260089686\n",
      "\n",
      "Treino: 446\n",
      "Valid: 445\n",
      "Acc: 0.8179775280898877\n",
      "\n",
      "Treino: 445\n",
      "Valid: 446\n",
      "Acc: 0.7847533632286996\n",
      "\n",
      "Treino: 446\n",
      "Valid: 445\n",
      "Acc: 0.7842696629213484\n",
      "\n",
      "Treino: 445\n",
      "Valid: 446\n",
      "Acc: 0.8161434977578476\n",
      "\n",
      "Treino: 446\n",
      "Valid: 445\n",
      "Acc: 0.7842696629213484\n",
      "\n",
      "Treino: 445\n",
      "Valid: 446\n",
      "Acc: 0.8004484304932735\n",
      "\n",
      "Treino: 446\n",
      "Valid: 445\n",
      "Acc: 0.8\n",
      "\n",
      "Treino: 445\n",
      "Valid: 446\n",
      "Acc: 0.8183856502242153\n",
      "\n",
      "Treino: 446\n",
      "Valid: 445\n",
      "Acc: 0.802247191011236\n",
      "\n",
      "Treino: 445\n",
      "Valid: 446\n",
      "Acc: 0.8116591928251121\n",
      "\n",
      "Treino: 446\n",
      "Valid: 445\n",
      "Acc: 0.8067415730337079\n",
      "\n",
      "Treino: 445\n",
      "Valid: 446\n",
      "Acc: 0.820627802690583\n",
      "\n",
      "Treino: 446\n",
      "Valid: 445\n",
      "Acc: 0.7887640449438202\n",
      "\n",
      "Treino: 445\n",
      "Valid: 446\n",
      "Acc: 0.8385650224215246\n",
      "\n",
      "Treino: 446\n",
      "Valid: 445\n",
      "Acc: 0.8044943820224719\n",
      "\n",
      "Treino: 445\n",
      "Valid: 446\n",
      "Acc: 0.7982062780269058\n",
      "\n",
      "Treino: 446\n",
      "Valid: 445\n",
      "Acc: 0.8112359550561797\n",
      "\n"
     ]
    }
   ],
   "source": [
    "resultados = []\n",
    "kf = RepeatedKFold(n_splits=2, n_repeats=10, random_state=10)\n",
    "\n",
    "for linhas_treino, linhas_valid in kf.split(X):\n",
    "    print(\"Treino:\", linhas_treino.shape[0])\n",
    "    print(\"Valid:\", linhas_valid.shape[0])\n",
    "\n",
    "    X_treino, X_valid = X.iloc[linhas_treino], X.iloc[linhas_valid]\n",
    "    y_treino, y_valid = y.iloc[linhas_treino], y.iloc[linhas_valid]\n",
    "\n",
    "    modelo = RandomForestClassifier(n_estimators=100, n_jobs=-1, random_state=0)\n",
    "    modelo.fit(X_treino, y_treino)\n",
    "\n",
    "    p = modelo.predict(X_valid)\n",
    "\n",
    "    acc = np.mean(y_valid == p)\n",
    "    resultados.append(acc)\n",
    "    print(\"Acc:\", acc)\n",
    "    print()\n",
    "    #print(X_treino.head())\n",
    "    #print()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "  <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",
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       "      <td>1</td>\n",
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       "      <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",
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       "      <td>1</td>\n",
       "      <td>0</td>\n",
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       "      <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",
       "      <td>1</td>\n",
       "      <td>1</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",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
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      "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  Sex_binario  p  \n",
       "0      0         A/5 21171   7.2500   NaN        S            0  0  \n",
       "1      0          PC 17599  71.2833   C85        C            1  1  \n",
       "2      0  STON/O2. 3101282   7.9250   NaN        S            1  0  \n",
       "3      0            113803  53.1000  C123        S            1  1  \n",
       "4      0            373450   8.0500   NaN        S            0  0  "
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "X_valid_check = train.iloc[linhas_valid].copy()\n",
    "X_valid_check['p'] = p\n",
    "X_valid_check.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(445, 14)"
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     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
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   "source": [
    "X_valid_check.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [
    {
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       "      <th>2</th>\n",
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       "      <td>Heikkinen, Miss. Laina</td>\n",
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       "      <td>Beesley, Mr. Lawrence</td>\n",
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       "      <td>3</td>\n",
       "      <td>McGowan, Miss. Anna \"Annie\"</td>\n",
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       "      <td>0</td>\n",
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       "      <th>23</th>\n",
       "      <td>24</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",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>26</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",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    PassengerId  Pclass                                               Name  \\\n",
       "2             3       3                             Heikkinen, Miss. Laina   \n",
       "21           22       2                              Beesley, Mr. Lawrence   \n",
       "22           23       3                        McGowan, Miss. Anna \"Annie\"   \n",
       "23           24       1                       Sloper, Mr. William Thompson   \n",
       "25           26       3  Asplund, Mrs. Carl Oscar (Selma Augusta Emilia...   \n",
       "\n",
       "       Sex   Age  SibSp  Parch            Ticket     Fare Cabin Embarked  \\\n",
       "2   female  26.0      0      0  STON/O2. 3101282   7.9250   NaN        S   \n",
       "21    male  34.0      0      0            248698  13.0000   D56        S   \n",
       "22  female  15.0      0      0            330923   8.0292   NaN        Q   \n",
       "23    male  28.0      0      0            113788  35.5000    A6        S   \n",
       "25  female  38.0      1      5            347077  31.3875   NaN        S   \n",
       "\n",
       "    Sex_binario  p  Survived  \n",
       "2             1  0         1  \n",
       "21            0  0         1  \n",
       "22            1  0         1  \n",
       "23            0  0         1  \n",
       "25            1  0         1  "
      ]
     },
     "execution_count": 24,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "erros = X_valid_check[X_valid_check['Survived'] != X_valid_check['p']]\n",
    "erros = erros[['PassengerId', 'Pclass', 'Name', 'Sex', 'Age', 'SibSp',\n",
    "       'Parch', 'Ticket', 'Fare', 'Cabin', 'Embarked', 'Sex_binario', 'p', 'Survived']]\n",
    "erros.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [],
   "source": [
    "mulheres = erros[erros['Sex'] == 'female']\n",
    "homens = erros[erros['Sex'] == 'male']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "      <th></th>\n",
       "      <th>PassengerId</th>\n",
       "      <th>Pclass</th>\n",
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       "    <tr>\n",
       "      <th>888</th>\n",
       "      <td>889</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",
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       "      <th>501</th>\n",
       "      <td>502</td>\n",
       "      <td>3</td>\n",
       "      <td>Canavan, Miss. Mary</td>\n",
       "      <td>female</td>\n",
       "      <td>21.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>364846</td>\n",
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       "      <td>1</td>\n",
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       "      <th>498</th>\n",
       "      <td>499</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",
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       "      <th>882</th>\n",
       "      <td>883</td>\n",
       "      <td>3</td>\n",
       "      <td>Dahlberg, Miss. Gerda Ulrika</td>\n",
       "      <td>female</td>\n",
       "      <td>22.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>7552</td>\n",
       "      <td>10.5167</td>\n",
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       "      <th>474</th>\n",
       "      <td>475</td>\n",
       "      <td>3</td>\n",
       "      <td>Strandberg, Miss. Ida Sofia</td>\n",
       "      <td>female</td>\n",
       "      <td>22.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>7553</td>\n",
       "      <td>9.8375</td>\n",
       "      <td>NaN</td>\n",
       "      <td>S</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>419</th>\n",
       "      <td>420</td>\n",
       "      <td>3</td>\n",
       "      <td>Van Impe, Miss. Catharina</td>\n",
       "      <td>female</td>\n",
       "      <td>10.0</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>345773</td>\n",
       "      <td>24.1500</td>\n",
       "      <td>NaN</td>\n",
       "      <td>S</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
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       "    <tr>\n",
       "      <th>357</th>\n",
       "      <td>358</td>\n",
       "      <td>2</td>\n",
       "      <td>Funk, Miss. Annie Clemmer</td>\n",
       "      <td>female</td>\n",
       "      <td>38.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>237671</td>\n",
       "      <td>13.0000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>S</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>254</th>\n",
       "      <td>255</td>\n",
       "      <td>3</td>\n",
       "      <td>Rosblom, Mrs. Viktor (Helena Wilhelmina)</td>\n",
       "      <td>female</td>\n",
       "      <td>41.0</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>370129</td>\n",
       "      <td>20.2125</td>\n",
       "      <td>NaN</td>\n",
       "      <td>S</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>503</th>\n",
       "      <td>504</td>\n",
       "      <td>3</td>\n",
       "      <td>Laitinen, Miss. Kristina Sofia</td>\n",
       "      <td>female</td>\n",
       "      <td>37.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>4135</td>\n",
       "      <td>9.5875</td>\n",
       "      <td>NaN</td>\n",
       "      <td>S</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>654</th>\n",
       "      <td>655</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",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>772</th>\n",
       "      <td>773</td>\n",
       "      <td>2</td>\n",
       "      <td>Mack, Mrs. (Mary)</td>\n",
       "      <td>female</td>\n",
       "      <td>57.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>S.O./P.P. 3</td>\n",
       "      <td>10.5000</td>\n",
       "      <td>E77</td>\n",
       "      <td>S</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>177</th>\n",
       "      <td>178</td>\n",
       "      <td>1</td>\n",
       "      <td>Isham, Miss. Ann Elizabeth</td>\n",
       "      <td>female</td>\n",
       "      <td>50.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>PC 17595</td>\n",
       "      <td>28.7125</td>\n",
       "      <td>C49</td>\n",
       "      <td>C</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>852</th>\n",
       "      <td>853</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",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>854</th>\n",
       "      <td>855</td>\n",
       "      <td>2</td>\n",
       "      <td>Carter, Mrs. Ernest Courtenay (Lilian Hughes)</td>\n",
       "      <td>female</td>\n",
       "      <td>44.0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>244252</td>\n",
       "      <td>26.0000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>S</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>593</th>\n",
       "      <td>594</td>\n",
       "      <td>3</td>\n",
       "      <td>Bourke, Miss. Mary</td>\n",
       "      <td>female</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>364848</td>\n",
       "      <td>7.7500</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Q</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>830</th>\n",
       "      <td>831</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",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>855</th>\n",
       "      <td>856</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",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>866</th>\n",
       "      <td>867</td>\n",
       "      <td>2</td>\n",
       "      <td>Duran y More, Miss. Asuncion</td>\n",
       "      <td>female</td>\n",
       "      <td>27.0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>SC/PARIS 2149</td>\n",
       "      <td>13.8583</td>\n",
       "      <td>NaN</td>\n",
       "      <td>C</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>677</th>\n",
       "      <td>678</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",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>3</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",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>216</th>\n",
       "      <td>217</td>\n",
       "      <td>3</td>\n",
       "      <td>Honkanen, Miss. Eliina</td>\n",
       "      <td>female</td>\n",
       "      <td>27.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>STON/O2. 3101283</td>\n",
       "      <td>7.9250</td>\n",
       "      <td>NaN</td>\n",
       "      <td>S</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>192</th>\n",
       "      <td>193</td>\n",
       "      <td>3</td>\n",
       "      <td>Andersen-Jensen, Miss. Carla Christine Nielsine</td>\n",
       "      <td>female</td>\n",
       "      <td>19.0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>350046</td>\n",
       "      <td>7.8542</td>\n",
       "      <td>NaN</td>\n",
       "      <td>S</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>142</th>\n",
       "      <td>143</td>\n",
       "      <td>3</td>\n",
       "      <td>Hakkarainen, Mrs. Pekka Pietari (Elin Matilda ...</td>\n",
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       "      <td>24.0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>STON/O2. 3101279</td>\n",
       "      <td>15.8500</td>\n",
       "      <td>NaN</td>\n",
       "      <td>S</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>85</th>\n",
       "      <td>86</td>\n",
       "      <td>3</td>\n",
       "      <td>Backstrom, Mrs. Karl Alfred (Maria Mathilda Gu...</td>\n",
       "      <td>female</td>\n",
       "      <td>33.0</td>\n",
       "      <td>3</td>\n",
       "      <td>0</td>\n",
       "      <td>3101278</td>\n",
       "      <td>15.8500</td>\n",
       "      <td>NaN</td>\n",
       "      <td>S</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>44</th>\n",
       "      <td>45</td>\n",
       "      <td>3</td>\n",
       "      <td>Devaney, Miss. Margaret Delia</td>\n",
       "      <td>female</td>\n",
       "      <td>19.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>330958</td>\n",
       "      <td>7.8792</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Q</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>26</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",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>23</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",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>233</th>\n",
       "      <td>234</td>\n",
       "      <td>3</td>\n",
       "      <td>Asplund, Miss. Lillian Gertrud</td>\n",
       "      <td>female</td>\n",
       "      <td>5.0</td>\n",
       "      <td>4</td>\n",
       "      <td>2</td>\n",
       "      <td>347077</td>\n",
       "      <td>31.3875</td>\n",
       "      <td>NaN</td>\n",
       "      <td>S</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>479</th>\n",
       "      <td>480</td>\n",
       "      <td>3</td>\n",
       "      <td>Hirvonen, Miss. Hildur E</td>\n",
       "      <td>female</td>\n",
       "      <td>2.0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>3101298</td>\n",
       "      <td>12.2875</td>\n",
       "      <td>NaN</td>\n",
       "      <td>S</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "     PassengerId  Pclass                                               Name  \\\n",
       "888          889       3           Johnston, Miss. Catherine Helen \"Carrie\"   \n",
       "501          502       3                                Canavan, Miss. Mary   \n",
       "498          499       1    Allison, Mrs. Hudson J C (Bessie Waldo Daniels)   \n",
       "882          883       3                       Dahlberg, Miss. Gerda Ulrika   \n",
       "474          475       3                        Strandberg, Miss. Ida Sofia   \n",
       "419          420       3                          Van Impe, Miss. Catharina   \n",
       "357          358       2                          Funk, Miss. Annie Clemmer   \n",
       "254          255       3           Rosblom, Mrs. Viktor (Helena Wilhelmina)   \n",
       "503          504       3                     Laitinen, Miss. Kristina Sofia   \n",
       "654          655       3                       Hegarty, Miss. Hanora \"Nora\"   \n",
       "772          773       2                                  Mack, Mrs. (Mary)   \n",
       "177          178       1                         Isham, Miss. Ann Elizabeth   \n",
       "852          853       3                            Boulos, Miss. Nourelain   \n",
       "854          855       2      Carter, Mrs. Ernest Courtenay (Lilian Hughes)   \n",
       "593          594       3                                 Bourke, Miss. Mary   \n",
       "830          831       3            Yasbeck, Mrs. Antoni (Selini Alexander)   \n",
       "855          856       3                         Aks, Mrs. Sam (Leah Rosen)   \n",
       "866          867       2                       Duran y More, Miss. Asuncion   \n",
       "677          678       3                            Turja, Miss. Anna Sofia   \n",
       "2              3       3                             Heikkinen, Miss. Laina   \n",
       "216          217       3                             Honkanen, Miss. Eliina   \n",
       "192          193       3    Andersen-Jensen, Miss. Carla Christine Nielsine   \n",
       "142          143       3  Hakkarainen, Mrs. Pekka Pietari (Elin Matilda ...   \n",
       "85            86       3  Backstrom, Mrs. Karl Alfred (Maria Mathilda Gu...   \n",
       "44            45       3                      Devaney, Miss. Margaret Delia   \n",
       "25            26       3  Asplund, Mrs. Carl Oscar (Selma Augusta Emilia...   \n",
       "22            23       3                        McGowan, Miss. Anna \"Annie\"   \n",
       "233          234       3                     Asplund, Miss. Lillian Gertrud   \n",
       "479          480       3                           Hirvonen, Miss. Hildur E   \n",
       "\n",
       "        Sex   Age  SibSp  Parch            Ticket      Fare    Cabin Embarked  \\\n",
       "888  female   NaN      1      2        W./C. 6607   23.4500      NaN        S   \n",
       "501  female  21.0      0      0            364846    7.7500      NaN        Q   \n",
       "498  female  25.0      1      2            113781  151.5500  C22 C26        S   \n",
       "882  female  22.0      0      0              7552   10.5167      NaN        S   \n",
       "474  female  22.0      0      0              7553    9.8375      NaN        S   \n",
       "419  female  10.0      0      2            345773   24.1500      NaN        S   \n",
       "357  female  38.0      0      0            237671   13.0000      NaN        S   \n",
       "254  female  41.0      0      2            370129   20.2125      NaN        S   \n",
       "503  female  37.0      0      0              4135    9.5875      NaN        S   \n",
       "654  female  18.0      0      0            365226    6.7500      NaN        Q   \n",
       "772  female  57.0      0      0       S.O./P.P. 3   10.5000      E77        S   \n",
       "177  female  50.0      0      0          PC 17595   28.7125      C49        C   \n",
       "852  female   9.0      1      1              2678   15.2458      NaN        C   \n",
       "854  female  44.0      1      0            244252   26.0000      NaN        S   \n",
       "593  female   NaN      0      2            364848    7.7500      NaN        Q   \n",
       "830  female  15.0      1      0              2659   14.4542      NaN        C   \n",
       "855  female  18.0      0      1            392091    9.3500      NaN        S   \n",
       "866  female  27.0      1      0     SC/PARIS 2149   13.8583      NaN        C   \n",
       "677  female  18.0      0      0              4138    9.8417      NaN        S   \n",
       "2    female  26.0      0      0  STON/O2. 3101282    7.9250      NaN        S   \n",
       "216  female  27.0      0      0  STON/O2. 3101283    7.9250      NaN        S   \n",
       "192  female  19.0      1      0            350046    7.8542      NaN        S   \n",
       "142  female  24.0      1      0  STON/O2. 3101279   15.8500      NaN        S   \n",
       "85   female  33.0      3      0           3101278   15.8500      NaN        S   \n",
       "44   female  19.0      0      0            330958    7.8792      NaN        Q   \n",
       "25   female  38.0      1      5            347077   31.3875      NaN        S   \n",
       "22   female  15.0      0      0            330923    8.0292      NaN        Q   \n",
       "233  female   5.0      4      2            347077   31.3875      NaN        S   \n",
       "479  female   2.0      0      1           3101298   12.2875      NaN        S   \n",
       "\n",
       "     Sex_binario  p  Survived  \n",
       "888            1  1         0  \n",
       "501            1  1         0  \n",
       "498            1  1         0  \n",
       "882            1  1         0  \n",
       "474            1  1         0  \n",
       "419            1  1         0  \n",
       "357            1  1         0  \n",
       "254            1  1         0  \n",
       "503            1  1         0  \n",
       "654            1  1         0  \n",
       "772            1  1         0  \n",
       "177            1  1         0  \n",
       "852            1  1         0  \n",
       "854            1  1         0  \n",
       "593            1  1         0  \n",
       "830            1  0         1  \n",
       "855            1  0         1  \n",
       "866            1  0         1  \n",
       "677            1  0         1  \n",
       "2              1  0         1  \n",
       "216            1  0         1  \n",
       "192            1  0         1  \n",
       "142            1  0         1  \n",
       "85             1  0         1  \n",
       "44             1  0         1  \n",
       "25             1  0         1  \n",
       "22             1  0         1  \n",
       "233            1  0         1  \n",
       "479            1  0         1  "
      ]
     },
     "execution_count": 26,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "mulheres.sort_values(\"Survived\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>PassengerId</th>\n",
       "      <th>Pclass</th>\n",
       "      <th>Name</th>\n",
       "      <th>Sex</th>\n",
       "      <th>Age</th>\n",
       "      <th>SibSp</th>\n",
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       "      <th>Embarked</th>\n",
       "      <th>Sex_binario</th>\n",
       "      <th>p</th>\n",
       "      <th>Survived</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>238</th>\n",
       "      <td>239</td>\n",
       "      <td>2</td>\n",
       "      <td>Pengelly, Mr. Frederick William</td>\n",
       "      <td>male</td>\n",
       "      <td>19.00</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>28665</td>\n",
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       "      <th>442</th>\n",
       "      <td>443</td>\n",
       "      <td>3</td>\n",
       "      <td>Petterson, Mr. Johan Emil</td>\n",
       "      <td>male</td>\n",
       "      <td>25.00</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>347076</td>\n",
       "      <td>7.7750</td>\n",
       "      <td>NaN</td>\n",
       "      <td>S</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
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       "    <tr>\n",
       "      <th>422</th>\n",
       "      <td>423</td>\n",
       "      <td>3</td>\n",
       "      <td>Zimmerman, Mr. Leo</td>\n",
       "      <td>male</td>\n",
       "      <td>29.00</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>315082</td>\n",
       "      <td>7.8750</td>\n",
       "      <td>NaN</td>\n",
       "      <td>S</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>373</th>\n",
       "      <td>374</td>\n",
       "      <td>1</td>\n",
       "      <td>Ringhini, Mr. Sante</td>\n",
       "      <td>male</td>\n",
       "      <td>22.00</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>PC 17760</td>\n",
       "      <td>135.6333</td>\n",
       "      <td>NaN</td>\n",
       "      <td>C</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>371</th>\n",
       "      <td>372</td>\n",
       "      <td>3</td>\n",
       "      <td>Wiklund, Mr. Jakob Alfred</td>\n",
       "      <td>male</td>\n",
       "      <td>18.00</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>3101267</td>\n",
       "      <td>6.4958</td>\n",
       "      <td>NaN</td>\n",
       "      <td>S</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>698</th>\n",
       "      <td>699</td>\n",
       "      <td>1</td>\n",
       "      <td>Thayer, Mr. John Borland</td>\n",
       "      <td>male</td>\n",
       "      <td>49.00</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>17421</td>\n",
       "      <td>110.8833</td>\n",
       "      <td>C68</td>\n",
       "      <td>C</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>262</th>\n",
       "      <td>263</td>\n",
       "      <td>1</td>\n",
       "      <td>Taussig, Mr. Emil</td>\n",
       "      <td>male</td>\n",
       "      <td>52.00</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>110413</td>\n",
       "      <td>79.6500</td>\n",
       "      <td>E67</td>\n",
       "      <td>S</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>231</th>\n",
       "      <td>232</td>\n",
       "      <td>3</td>\n",
       "      <td>Larsson, Mr. Bengt Edvin</td>\n",
       "      <td>male</td>\n",
       "      <td>29.00</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>347067</td>\n",
       "      <td>7.7750</td>\n",
       "      <td>NaN</td>\n",
       "      <td>S</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>214</th>\n",
       "      <td>215</td>\n",
       "      <td>3</td>\n",
       "      <td>Kiernan, Mr. Philip</td>\n",
       "      <td>male</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>367229</td>\n",
       "      <td>7.7500</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Q</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
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       "    <tr>\n",
       "      <th>721</th>\n",
       "      <td>722</td>\n",
       "      <td>3</td>\n",
       "      <td>Jensen, Mr. Svend Lauritz</td>\n",
       "      <td>male</td>\n",
       "      <td>17.00</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>350048</td>\n",
       "      <td>7.0542</td>\n",
       "      <td>NaN</td>\n",
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       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
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       "    <tr>\n",
       "      <th>169</th>\n",
       "      <td>170</td>\n",
       "      <td>3</td>\n",
       "      <td>Ling, Mr. Lee</td>\n",
       "      <td>male</td>\n",
       "      <td>28.00</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1601</td>\n",
       "      <td>56.4958</td>\n",
       "      <td>NaN</td>\n",
       "      <td>S</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>544</th>\n",
       "      <td>545</td>\n",
       "      <td>1</td>\n",
       "      <td>Douglas, Mr. Walter Donald</td>\n",
       "      <td>male</td>\n",
       "      <td>50.00</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>PC 17761</td>\n",
       "      <td>106.4250</td>\n",
       "      <td>C86</td>\n",
       "      <td>C</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>783</th>\n",
       "      <td>784</td>\n",
       "      <td>3</td>\n",
       "      <td>Johnston, Mr. Andrew G</td>\n",
       "      <td>male</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",
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       "    <tr>\n",
       "      <th>139</th>\n",
       "      <td>140</td>\n",
       "      <td>1</td>\n",
       "      <td>Giglio, Mr. Victor</td>\n",
       "      <td>male</td>\n",
       "      <td>24.00</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>PC 17593</td>\n",
       "      <td>79.2000</td>\n",
       "      <td>B86</td>\n",
       "      <td>C</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>122</th>\n",
       "      <td>123</td>\n",
       "      <td>2</td>\n",
       "      <td>Nasser, Mr. Nicholas</td>\n",
       "      <td>male</td>\n",
       "      <td>32.50</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",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>118</th>\n",
       "      <td>119</td>\n",
       "      <td>1</td>\n",
       "      <td>Baxter, Mr. Quigg Edmond</td>\n",
       "      <td>male</td>\n",
       "      <td>24.00</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>PC 17558</td>\n",
       "      <td>247.5208</td>\n",
       "      <td>B58 B60</td>\n",
       "      <td>C</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>102</th>\n",
       "      <td>103</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",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>48</th>\n",
       "      <td>49</td>\n",
       "      <td>3</td>\n",
       "      <td>Samaan, Mr. Youssef</td>\n",
       "      <td>male</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>2662</td>\n",
       "      <td>21.6792</td>\n",
       "      <td>NaN</td>\n",
       "      <td>C</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>28</td>\n",
       "      <td>1</td>\n",
       "      <td>Fortune, Mr. Charles Alexander</td>\n",
       "      <td>male</td>\n",
       "      <td>19.00</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",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>34</th>\n",
       "      <td>35</td>\n",
       "      <td>1</td>\n",
       "      <td>Meyer, Mr. Edgar Joseph</td>\n",
       "      <td>male</td>\n",
       "      <td>28.00</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>PC 17604</td>\n",
       "      <td>82.1708</td>\n",
       "      <td>NaN</td>\n",
       "      <td>C</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>579</th>\n",
       "      <td>580</td>\n",
       "      <td>3</td>\n",
       "      <td>Jussila, Mr. Eiriik</td>\n",
       "      <td>male</td>\n",
       "      <td>32.00</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>STON/O 2. 3101286</td>\n",
       "      <td>7.9250</td>\n",
       "      <td>NaN</td>\n",
       "      <td>S</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>621</th>\n",
       "      <td>622</td>\n",
       "      <td>1</td>\n",
       "      <td>Kimball, Mr. Edwin Nelson Jr</td>\n",
       "      <td>male</td>\n",
       "      <td>42.00</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>11753</td>\n",
       "      <td>52.5542</td>\n",
       "      <td>D19</td>\n",
       "      <td>S</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>803</th>\n",
       "      <td>804</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",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>622</th>\n",
       "      <td>623</td>\n",
       "      <td>3</td>\n",
       "      <td>Nakid, Mr. Sahid</td>\n",
       "      <td>male</td>\n",
       "      <td>20.00</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>2653</td>\n",
       "      <td>15.7417</td>\n",
       "      <td>NaN</td>\n",
       "      <td>C</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>630</th>\n",
       "      <td>631</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",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>643</th>\n",
       "      <td>644</td>\n",
       "      <td>3</td>\n",
       "      <td>Foo, Mr. Choong</td>\n",
       "      <td>male</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1601</td>\n",
       "      <td>56.4958</td>\n",
       "      <td>NaN</td>\n",
       "      <td>S</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>744</th>\n",
       "      <td>745</td>\n",
       "      <td>3</td>\n",
       "      <td>Stranden, Mr. Juho</td>\n",
       "      <td>male</td>\n",
       "      <td>31.00</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>STON/O 2. 3101288</td>\n",
       "      <td>7.9250</td>\n",
       "      <td>NaN</td>\n",
       "      <td>S</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>751</th>\n",
       "      <td>752</td>\n",
       "      <td>3</td>\n",
       "      <td>Moor, Master. Meier</td>\n",
       "      <td>male</td>\n",
       "      <td>6.00</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>392096</td>\n",
       "      <td>12.4750</td>\n",
       "      <td>E121</td>\n",
       "      <td>S</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>673</th>\n",
       "      <td>674</td>\n",
       "      <td>2</td>\n",
       "      <td>Wilhelms, Mr. Charles</td>\n",
       "      <td>male</td>\n",
       "      <td>31.00</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>244270</td>\n",
       "      <td>13.0000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>S</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>690</th>\n",
       "      <td>691</td>\n",
       "      <td>1</td>\n",
       "      <td>Dick, Mr. Albert Adrian</td>\n",
       "      <td>male</td>\n",
       "      <td>31.00</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",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>762</th>\n",
       "      <td>763</td>\n",
       "      <td>3</td>\n",
       "      <td>Barah, Mr. Hanna Assi</td>\n",
       "      <td>male</td>\n",
       "      <td>20.00</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2663</td>\n",
       "      <td>7.2292</td>\n",
       "      <td>NaN</td>\n",
       "      <td>C</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>707</th>\n",
       "      <td>708</td>\n",
       "      <td>1</td>\n",
       "      <td>Calderhead, Mr. Edward Pennington</td>\n",
       "      <td>male</td>\n",
       "      <td>42.00</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>PC 17476</td>\n",
       "      <td>26.2875</td>\n",
       "      <td>E24</td>\n",
       "      <td>S</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>569</th>\n",
       "      <td>570</td>\n",
       "      <td>3</td>\n",
       "      <td>Jonsson, Mr. Carl</td>\n",
       "      <td>male</td>\n",
       "      <td>32.00</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>350417</td>\n",
       "      <td>7.8542</td>\n",
       "      <td>NaN</td>\n",
       "      <td>S</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>647</th>\n",
       "      <td>648</td>\n",
       "      <td>1</td>\n",
       "      <td>Simonius-Blumer, Col. Oberst Alfons</td>\n",
       "      <td>male</td>\n",
       "      <td>56.00</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>13213</td>\n",
       "      <td>35.5000</td>\n",
       "      <td>A26</td>\n",
       "      <td>C</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>22</td>\n",
       "      <td>2</td>\n",
       "      <td>Beesley, Mr. Lawrence</td>\n",
       "      <td>male</td>\n",
       "      <td>34.00</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",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>414</th>\n",
       "      <td>415</td>\n",
       "      <td>3</td>\n",
       "      <td>Sundman, Mr. Johan Julian</td>\n",
       "      <td>male</td>\n",
       "      <td>44.00</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>STON/O 2. 3101269</td>\n",
       "      <td>7.9250</td>\n",
       "      <td>NaN</td>\n",
       "      <td>S</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>489</th>\n",
       "      <td>490</td>\n",
       "      <td>3</td>\n",
       "      <td>Coutts, Master. Eden Leslie \"Neville\"</td>\n",
       "      <td>male</td>\n",
       "      <td>9.00</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>C.A. 37671</td>\n",
       "      <td>15.9000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>S</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>24</td>\n",
       "      <td>1</td>\n",
       "      <td>Sloper, Mr. William Thompson</td>\n",
       "      <td>male</td>\n",
       "      <td>28.00</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",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>36</th>\n",
       "      <td>37</td>\n",
       "      <td>3</td>\n",
       "      <td>Mamee, Mr. Hanna</td>\n",
       "      <td>male</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2677</td>\n",
       "      <td>7.2292</td>\n",
       "      <td>NaN</td>\n",
       "      <td>C</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>55</th>\n",
       "      <td>56</td>\n",
       "      <td>1</td>\n",
       "      <td>Woolner, Mr. Hugh</td>\n",
       "      <td>male</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>19947</td>\n",
       "      <td>35.5000</td>\n",
       "      <td>C52</td>\n",
       "      <td>S</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>146</th>\n",
       "      <td>147</td>\n",
       "      <td>3</td>\n",
       "      <td>Andersson, Mr. August Edvard (\"Wennerstrom\")</td>\n",
       "      <td>male</td>\n",
       "      <td>27.00</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>350043</td>\n",
       "      <td>7.7958</td>\n",
       "      <td>NaN</td>\n",
       "      <td>S</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>165</th>\n",
       "      <td>166</td>\n",
       "      <td>3</td>\n",
       "      <td>Goldsmith, Master. Frank John William \"Frankie\"</td>\n",
       "      <td>male</td>\n",
       "      <td>9.00</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>363291</td>\n",
       "      <td>20.5250</td>\n",
       "      <td>NaN</td>\n",
       "      <td>S</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>187</th>\n",
       "      <td>188</td>\n",
       "      <td>1</td>\n",
       "      <td>Romaine, Mr. Charles Hallace (\"Mr C Rolmane\")</td>\n",
       "      <td>male</td>\n",
       "      <td>45.00</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>111428</td>\n",
       "      <td>26.5500</td>\n",
       "      <td>NaN</td>\n",
       "      <td>S</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>248</th>\n",
       "      <td>249</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",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>553</th>\n",
       "      <td>554</td>\n",
       "      <td>3</td>\n",
       "      <td>Leeni, Mr. Fahim (\"Philip Zenni\")</td>\n",
       "      <td>male</td>\n",
       "      <td>22.00</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2620</td>\n",
       "      <td>7.2250</td>\n",
       "      <td>NaN</td>\n",
       "      <td>C</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>271</th>\n",
       "      <td>272</td>\n",
       "      <td>3</td>\n",
       "      <td>Tornquist, Mr. William Henry</td>\n",
       "      <td>male</td>\n",
       "      <td>25.00</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>LINE</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>S</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>338</th>\n",
       "      <td>339</td>\n",
       "      <td>3</td>\n",
       "      <td>Dahl, Mr. Karl Edwart</td>\n",
       "      <td>male</td>\n",
       "      <td>45.00</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>7598</td>\n",
       "      <td>8.0500</td>\n",
       "      <td>NaN</td>\n",
       "      <td>S</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>391</th>\n",
       "      <td>392</td>\n",
       "      <td>3</td>\n",
       "      <td>Jansson, Mr. Carl Olof</td>\n",
       "      <td>male</td>\n",
       "      <td>21.00</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>350034</td>\n",
       "      <td>7.7958</td>\n",
       "      <td>NaN</td>\n",
       "      <td>S</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>400</th>\n",
       "      <td>401</td>\n",
       "      <td>3</td>\n",
       "      <td>Niskanen, Mr. Juha</td>\n",
       "      <td>male</td>\n",
       "      <td>39.00</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>STON/O 2. 3101289</td>\n",
       "      <td>7.9250</td>\n",
       "      <td>NaN</td>\n",
       "      <td>S</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>804</th>\n",
       "      <td>805</td>\n",
       "      <td>3</td>\n",
       "      <td>Hedman, Mr. Oskar Arvid</td>\n",
       "      <td>male</td>\n",
       "      <td>27.00</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>347089</td>\n",
       "      <td>6.9750</td>\n",
       "      <td>NaN</td>\n",
       "      <td>S</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>429</th>\n",
       "      <td>430</td>\n",
       "      <td>3</td>\n",
       "      <td>Pickard, Mr. Berk (Berk Trembisky)</td>\n",
       "      <td>male</td>\n",
       "      <td>32.00</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>SOTON/O.Q. 392078</td>\n",
       "      <td>8.0500</td>\n",
       "      <td>E10</td>\n",
       "      <td>S</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>444</th>\n",
       "      <td>445</td>\n",
       "      <td>3</td>\n",
       "      <td>Johannesen-Bratthammer, Mr. Bernt</td>\n",
       "      <td>male</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>65306</td>\n",
       "      <td>8.1125</td>\n",
       "      <td>NaN</td>\n",
       "      <td>S</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>449</th>\n",
       "      <td>450</td>\n",
       "      <td>1</td>\n",
       "      <td>Peuchen, Major. Arthur Godfrey</td>\n",
       "      <td>male</td>\n",
       "      <td>52.00</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>113786</td>\n",
       "      <td>30.5000</td>\n",
       "      <td>C104</td>\n",
       "      <td>S</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>283</th>\n",
       "      <td>284</td>\n",
       "      <td>3</td>\n",
       "      <td>Dorking, Mr. Edward Arthur</td>\n",
       "      <td>male</td>\n",
       "      <td>19.00</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>A/5. 10482</td>\n",
       "      <td>8.0500</td>\n",
       "      <td>NaN</td>\n",
       "      <td>S</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>821</th>\n",
       "      <td>822</td>\n",
       "      <td>3</td>\n",
       "      <td>Lulic, Mr. Nikola</td>\n",
       "      <td>male</td>\n",
       "      <td>27.00</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>315098</td>\n",
       "      <td>8.6625</td>\n",
       "      <td>NaN</td>\n",
       "      <td>S</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "     PassengerId  Pclass                                             Name  \\\n",
       "238          239       2                  Pengelly, Mr. Frederick William   \n",
       "442          443       3                        Petterson, Mr. Johan Emil   \n",
       "422          423       3                               Zimmerman, Mr. Leo   \n",
       "373          374       1                              Ringhini, Mr. Sante   \n",
       "371          372       3                        Wiklund, Mr. Jakob Alfred   \n",
       "698          699       1                         Thayer, Mr. John Borland   \n",
       "262          263       1                                Taussig, Mr. Emil   \n",
       "231          232       3                         Larsson, Mr. Bengt Edvin   \n",
       "214          215       3                              Kiernan, Mr. Philip   \n",
       "721          722       3                        Jensen, Mr. Svend Lauritz   \n",
       "169          170       3                                    Ling, Mr. Lee   \n",
       "544          545       1                       Douglas, Mr. Walter Donald   \n",
       "783          784       3                           Johnston, Mr. Andrew G   \n",
       "139          140       1                               Giglio, Mr. Victor   \n",
       "122          123       2                             Nasser, Mr. Nicholas   \n",
       "118          119       1                         Baxter, Mr. Quigg Edmond   \n",
       "102          103       1                        White, Mr. Richard Frasar   \n",
       "48            49       3                              Samaan, Mr. Youssef   \n",
       "27            28       1                   Fortune, Mr. Charles Alexander   \n",
       "34            35       1                          Meyer, Mr. Edgar Joseph   \n",
       "579          580       3                              Jussila, Mr. Eiriik   \n",
       "621          622       1                     Kimball, Mr. Edwin Nelson Jr   \n",
       "803          804       3                  Thomas, Master. Assad Alexander   \n",
       "622          623       3                                 Nakid, Mr. Sahid   \n",
       "630          631       1             Barkworth, Mr. Algernon Henry Wilson   \n",
       "643          644       3                                  Foo, Mr. Choong   \n",
       "744          745       3                               Stranden, Mr. Juho   \n",
       "751          752       3                              Moor, Master. Meier   \n",
       "673          674       2                            Wilhelms, Mr. Charles   \n",
       "690          691       1                          Dick, Mr. Albert Adrian   \n",
       "762          763       3                            Barah, Mr. Hanna Assi   \n",
       "707          708       1                Calderhead, Mr. Edward Pennington   \n",
       "569          570       3                                Jonsson, Mr. Carl   \n",
       "647          648       1              Simonius-Blumer, Col. Oberst Alfons   \n",
       "21            22       2                            Beesley, Mr. Lawrence   \n",
       "414          415       3                        Sundman, Mr. Johan Julian   \n",
       "489          490       3            Coutts, Master. Eden Leslie \"Neville\"   \n",
       "23            24       1                     Sloper, Mr. William Thompson   \n",
       "36            37       3                                 Mamee, Mr. Hanna   \n",
       "55            56       1                                Woolner, Mr. Hugh   \n",
       "146          147       3     Andersson, Mr. August Edvard (\"Wennerstrom\")   \n",
       "165          166       3  Goldsmith, Master. Frank John William \"Frankie\"   \n",
       "187          188       1    Romaine, Mr. Charles Hallace (\"Mr C Rolmane\")   \n",
       "248          249       1                    Beckwith, Mr. Richard Leonard   \n",
       "553          554       3                Leeni, Mr. Fahim (\"Philip Zenni\")   \n",
       "271          272       3                     Tornquist, Mr. William Henry   \n",
       "338          339       3                            Dahl, Mr. Karl Edwart   \n",
       "391          392       3                           Jansson, Mr. Carl Olof   \n",
       "400          401       3                               Niskanen, Mr. Juha   \n",
       "804          805       3                          Hedman, Mr. Oskar Arvid   \n",
       "429          430       3               Pickard, Mr. Berk (Berk Trembisky)   \n",
       "444          445       3                Johannesen-Bratthammer, Mr. Bernt   \n",
       "449          450       1                   Peuchen, Major. Arthur Godfrey   \n",
       "283          284       3                       Dorking, Mr. Edward Arthur   \n",
       "821          822       3                                Lulic, Mr. Nikola   \n",
       "\n",
       "      Sex    Age  SibSp  Parch             Ticket      Fare        Cabin  \\\n",
       "238  male  19.00      0      0              28665   10.5000          NaN   \n",
       "442  male  25.00      1      0             347076    7.7750          NaN   \n",
       "422  male  29.00      0      0             315082    7.8750          NaN   \n",
       "373  male  22.00      0      0           PC 17760  135.6333          NaN   \n",
       "371  male  18.00      1      0            3101267    6.4958          NaN   \n",
       "698  male  49.00      1      1              17421  110.8833          C68   \n",
       "262  male  52.00      1      1             110413   79.6500          E67   \n",
       "231  male  29.00      0      0             347067    7.7750          NaN   \n",
       "214  male    NaN      1      0             367229    7.7500          NaN   \n",
       "721  male  17.00      1      0             350048    7.0542          NaN   \n",
       "169  male  28.00      0      0               1601   56.4958          NaN   \n",
       "544  male  50.00      1      0           PC 17761  106.4250          C86   \n",
       "783  male    NaN      1      2         W./C. 6607   23.4500          NaN   \n",
       "139  male  24.00      0      0           PC 17593   79.2000          B86   \n",
       "122  male  32.50      1      0             237736   30.0708          NaN   \n",
       "118  male  24.00      0      1           PC 17558  247.5208      B58 B60   \n",
       "102  male  21.00      0      1              35281   77.2875          D26   \n",
       "48   male    NaN      2      0               2662   21.6792          NaN   \n",
       "27   male  19.00      3      2              19950  263.0000  C23 C25 C27   \n",
       "34   male  28.00      1      0           PC 17604   82.1708          NaN   \n",
       "579  male  32.00      0      0  STON/O 2. 3101286    7.9250          NaN   \n",
       "621  male  42.00      1      0              11753   52.5542          D19   \n",
       "803  male   0.42      0      1               2625    8.5167          NaN   \n",
       "622  male  20.00      1      1               2653   15.7417          NaN   \n",
       "630  male  80.00      0      0              27042   30.0000          A23   \n",
       "643  male    NaN      0      0               1601   56.4958          NaN   \n",
       "744  male  31.00      0      0  STON/O 2. 3101288    7.9250          NaN   \n",
       "751  male   6.00      0      1             392096   12.4750         E121   \n",
       "673  male  31.00      0      0             244270   13.0000          NaN   \n",
       "690  male  31.00      1      0              17474   57.0000          B20   \n",
       "762  male  20.00      0      0               2663    7.2292          NaN   \n",
       "707  male  42.00      0      0           PC 17476   26.2875          E24   \n",
       "569  male  32.00      0      0             350417    7.8542          NaN   \n",
       "647  male  56.00      0      0              13213   35.5000          A26   \n",
       "21   male  34.00      0      0             248698   13.0000          D56   \n",
       "414  male  44.00      0      0  STON/O 2. 3101269    7.9250          NaN   \n",
       "489  male   9.00      1      1         C.A. 37671   15.9000          NaN   \n",
       "23   male  28.00      0      0             113788   35.5000           A6   \n",
       "36   male    NaN      0      0               2677    7.2292          NaN   \n",
       "55   male    NaN      0      0              19947   35.5000          C52   \n",
       "146  male  27.00      0      0             350043    7.7958          NaN   \n",
       "165  male   9.00      0      2             363291   20.5250          NaN   \n",
       "187  male  45.00      0      0             111428   26.5500          NaN   \n",
       "248  male  37.00      1      1              11751   52.5542          D35   \n",
       "553  male  22.00      0      0               2620    7.2250          NaN   \n",
       "271  male  25.00      0      0               LINE    0.0000          NaN   \n",
       "338  male  45.00      0      0               7598    8.0500          NaN   \n",
       "391  male  21.00      0      0             350034    7.7958          NaN   \n",
       "400  male  39.00      0      0  STON/O 2. 3101289    7.9250          NaN   \n",
       "804  male  27.00      0      0             347089    6.9750          NaN   \n",
       "429  male  32.00      0      0  SOTON/O.Q. 392078    8.0500          E10   \n",
       "444  male    NaN      0      0              65306    8.1125          NaN   \n",
       "449  male  52.00      0      0             113786   30.5000         C104   \n",
       "283  male  19.00      0      0         A/5. 10482    8.0500          NaN   \n",
       "821  male  27.00      0      0             315098    8.6625          NaN   \n",
       "\n",
       "    Embarked  Sex_binario  p  Survived  \n",
       "238        S            0  1         0  \n",
       "442        S            0  1         0  \n",
       "422        S            0  1         0  \n",
       "373        C            0  1         0  \n",
       "371        S            0  1         0  \n",
       "698        C            0  1         0  \n",
       "262        S            0  1         0  \n",
       "231        S            0  1         0  \n",
       "214        Q            0  1         0  \n",
       "721        S            0  1         0  \n",
       "169        S            0  1         0  \n",
       "544        C            0  1         0  \n",
       "783        S            0  1         0  \n",
       "139        C            0  1         0  \n",
       "122        C            0  1         0  \n",
       "118        C            0  1         0  \n",
       "102        S            0  1         0  \n",
       "48         C            0  1         0  \n",
       "27         S            0  1         0  \n",
       "34         C            0  1         0  \n",
       "579        S            0  0         1  \n",
       "621        S            0  0         1  \n",
       "803        C            0  0         1  \n",
       "622        C            0  0         1  \n",
       "630        S            0  0         1  \n",
       "643        S            0  0         1  \n",
       "744        S            0  0         1  \n",
       "751        S            0  0         1  \n",
       "673        S            0  0         1  \n",
       "690        S            0  0         1  \n",
       "762        C            0  0         1  \n",
       "707        S            0  0         1  \n",
       "569        S            0  0         1  \n",
       "647        C            0  0         1  \n",
       "21         S            0  0         1  \n",
       "414        S            0  0         1  \n",
       "489        S            0  0         1  \n",
       "23         S            0  0         1  \n",
       "36         C            0  0         1  \n",
       "55         S            0  0         1  \n",
       "146        S            0  0         1  \n",
       "165        S            0  0         1  \n",
       "187        S            0  0         1  \n",
       "248        S            0  0         1  \n",
       "553        C            0  0         1  \n",
       "271        S            0  0         1  \n",
       "338        S            0  0         1  \n",
       "391        S            0  0         1  \n",
       "400        S            0  0         1  \n",
       "804        S            0  0         1  \n",
       "429        S            0  0         1  \n",
       "444        S            0  0         1  \n",
       "449        S            0  0         1  \n",
       "283        S            0  0         1  \n",
       "821        S            0  0         1  "
      ]
     },
     "execution_count": 27,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "homens.sort_values(\"Survived\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Novas variaveis"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [],
   "source": [
    "train['Embarked_S'] = (train['Embarked'] == 'S').astype(int)\n",
    "train['Embarked_C'] = (train['Embarked'] == 'C').astype(int)\n",
    "#train['Embarked_Q'] = (train['Embarked'] == 'Q').astype(int)\n",
    "\n",
    "train['Cabine_nula'] = train['Cabin'].isnull().astype(int)\n",
    "\n",
    "train['Nome_contem_Miss'] = train['Name'].str.contains(\"Miss\").astype(int)\n",
    "train['Nome_contem_Mrs'] = train['Name'].str.contains(\"Mrs\").astype(int)\n",
    "\n",
    "train['Nome_contem_Master'] = train['Name'].str.contains(\"Master\").astype(int)\n",
    "train['Nome_contem_Col'] = train['Name'].str.contains(\"Col\").astype(int)\n",
    "train['Nome_contem_Major'] = train['Name'].str.contains(\"Major\").astype(int)\n",
    "train['Nome_contem_Mr'] = train['Name'].str.contains(\"Mr\").astype(int)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['Sex_binario', 'Age', 'Pclass', 'SibSp', 'Parch', 'Fare']"
      ]
     },
     "execution_count": 29,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "variaveis"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "metadata": {},
   "outputs": [],
   "source": [
    "variaveis = ['Sex_binario', 'Age', 'Pclass', 'SibSp', 'Parch', 'Fare', 'Embarked_S', 'Embarked_C', 'Cabine_nula',\n",
    "             'Nome_contem_Miss', 'Nome_contem_Mrs',\n",
    "             'Nome_contem_Master', 'Nome_contem_Col', 'Nome_contem_Major', 'Nome_contem_Mr']\n",
    "\n",
    "X = train[variaveis].fillna(-1)\n",
    "y = train['Survived']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 54,
   "metadata": {},
   "outputs": [],
   "source": [
    "from sklearn.linear_model import LogisticRegression"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 55,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Treino: 445\n",
      "Valid: 446\n",
      "Acc: 0.8251121076233184\n",
      "\n",
      "Treino: 446\n",
      "Valid: 445\n",
      "Acc: 0.8044943820224719\n",
      "\n",
      "Treino: 445\n",
      "Valid: 446\n",
      "Acc: 0.8139013452914798\n",
      "\n",
      "Treino: 446\n",
      "Valid: 445\n",
      "Acc: 0.802247191011236\n",
      "\n",
      "Treino: 445\n",
      "Valid: 446\n",
      "Acc: 0.8139013452914798\n",
      "\n",
      "Treino: 446\n",
      "Valid: 445\n",
      "Acc: 0.8179775280898877\n",
      "\n",
      "Treino: 445\n",
      "Valid: 446\n",
      "Acc: 0.8161434977578476\n",
      "\n",
      "Treino: 446\n",
      "Valid: 445\n",
      "Acc: 0.8179775280898877\n",
      "\n",
      "Treino: 445\n",
      "Valid: 446\n",
      "Acc: 0.820627802690583\n",
      "\n",
      "Treino: 446\n",
      "Valid: 445\n",
      "Acc: 0.8089887640449438\n",
      "\n",
      "Treino: 445\n",
      "Valid: 446\n",
      "Acc: 0.827354260089686\n",
      "\n",
      "Treino: 446\n",
      "Valid: 445\n",
      "Acc: 0.8179775280898877\n",
      "\n",
      "Treino: 445\n",
      "Valid: 446\n",
      "Acc: 0.8430493273542601\n",
      "\n",
      "Treino: 446\n",
      "Valid: 445\n",
      "Acc: 0.8067415730337079\n",
      "\n",
      "Treino: 445\n",
      "Valid: 446\n",
      "Acc: 0.8094170403587444\n",
      "\n",
      "Treino: 446\n",
      "Valid: 445\n",
      "Acc: 0.8134831460674158\n",
      "\n",
      "Treino: 445\n",
      "Valid: 446\n",
      "Acc: 0.8452914798206278\n",
      "\n",
      "Treino: 446\n",
      "Valid: 445\n",
      "Acc: 0.8179775280898877\n",
      "\n",
      "Treino: 445\n",
      "Valid: 446\n",
      "Acc: 0.8295964125560538\n",
      "\n",
      "Treino: 446\n",
      "Valid: 445\n",
      "Acc: 0.8292134831460675\n",
      "\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/Users/mario/anaconda3/lib/python3.7/site-packages/sklearn/linear_model/logistic.py:433: FutureWarning: Default solver will be changed to 'lbfgs' in 0.22. Specify a solver to silence this warning.\n",
      "  FutureWarning)\n",
      "/Users/mario/anaconda3/lib/python3.7/site-packages/sklearn/linear_model/logistic.py:433: FutureWarning: Default solver will be changed to 'lbfgs' in 0.22. Specify a solver to silence this warning.\n",
      "  FutureWarning)\n",
      "/Users/mario/anaconda3/lib/python3.7/site-packages/sklearn/linear_model/logistic.py:433: FutureWarning: Default solver will be changed to 'lbfgs' in 0.22. Specify a solver to silence this warning.\n",
      "  FutureWarning)\n",
      "/Users/mario/anaconda3/lib/python3.7/site-packages/sklearn/linear_model/logistic.py:433: FutureWarning: Default solver will be changed to 'lbfgs' in 0.22. Specify a solver to silence this warning.\n",
      "  FutureWarning)\n",
      "/Users/mario/anaconda3/lib/python3.7/site-packages/sklearn/linear_model/logistic.py:433: FutureWarning: Default solver will be changed to 'lbfgs' in 0.22. Specify a solver to silence this warning.\n",
      "  FutureWarning)\n",
      "/Users/mario/anaconda3/lib/python3.7/site-packages/sklearn/linear_model/logistic.py:433: FutureWarning: Default solver will be changed to 'lbfgs' in 0.22. Specify a solver to silence this warning.\n",
      "  FutureWarning)\n",
      "/Users/mario/anaconda3/lib/python3.7/site-packages/sklearn/linear_model/logistic.py:433: FutureWarning: Default solver will be changed to 'lbfgs' in 0.22. Specify a solver to silence this warning.\n",
      "  FutureWarning)\n",
      "/Users/mario/anaconda3/lib/python3.7/site-packages/sklearn/linear_model/logistic.py:433: FutureWarning: Default solver will be changed to 'lbfgs' in 0.22. Specify a solver to silence this warning.\n",
      "  FutureWarning)\n",
      "/Users/mario/anaconda3/lib/python3.7/site-packages/sklearn/linear_model/logistic.py:433: FutureWarning: Default solver will be changed to 'lbfgs' in 0.22. Specify a solver to silence this warning.\n",
      "  FutureWarning)\n",
      "/Users/mario/anaconda3/lib/python3.7/site-packages/sklearn/linear_model/logistic.py:433: FutureWarning: Default solver will be changed to 'lbfgs' in 0.22. Specify a solver to silence this warning.\n",
      "  FutureWarning)\n",
      "/Users/mario/anaconda3/lib/python3.7/site-packages/sklearn/linear_model/logistic.py:433: FutureWarning: Default solver will be changed to 'lbfgs' in 0.22. Specify a solver to silence this warning.\n",
      "  FutureWarning)\n",
      "/Users/mario/anaconda3/lib/python3.7/site-packages/sklearn/linear_model/logistic.py:433: FutureWarning: Default solver will be changed to 'lbfgs' in 0.22. Specify a solver to silence this warning.\n",
      "  FutureWarning)\n",
      "/Users/mario/anaconda3/lib/python3.7/site-packages/sklearn/linear_model/logistic.py:433: FutureWarning: Default solver will be changed to 'lbfgs' in 0.22. Specify a solver to silence this warning.\n",
      "  FutureWarning)\n",
      "/Users/mario/anaconda3/lib/python3.7/site-packages/sklearn/linear_model/logistic.py:433: FutureWarning: Default solver will be changed to 'lbfgs' in 0.22. Specify a solver to silence this warning.\n",
      "  FutureWarning)\n",
      "/Users/mario/anaconda3/lib/python3.7/site-packages/sklearn/linear_model/logistic.py:433: FutureWarning: Default solver will be changed to 'lbfgs' in 0.22. Specify a solver to silence this warning.\n",
      "  FutureWarning)\n",
      "/Users/mario/anaconda3/lib/python3.7/site-packages/sklearn/linear_model/logistic.py:433: FutureWarning: Default solver will be changed to 'lbfgs' in 0.22. Specify a solver to silence this warning.\n",
      "  FutureWarning)\n",
      "/Users/mario/anaconda3/lib/python3.7/site-packages/sklearn/linear_model/logistic.py:433: FutureWarning: Default solver will be changed to 'lbfgs' in 0.22. Specify a solver to silence this warning.\n",
      "  FutureWarning)\n",
      "/Users/mario/anaconda3/lib/python3.7/site-packages/sklearn/linear_model/logistic.py:433: FutureWarning: Default solver will be changed to 'lbfgs' in 0.22. Specify a solver to silence this warning.\n",
      "  FutureWarning)\n",
      "/Users/mario/anaconda3/lib/python3.7/site-packages/sklearn/linear_model/logistic.py:433: FutureWarning: Default solver will be changed to 'lbfgs' in 0.22. Specify a solver to silence this warning.\n",
      "  FutureWarning)\n",
      "/Users/mario/anaconda3/lib/python3.7/site-packages/sklearn/linear_model/logistic.py:433: FutureWarning: Default solver will be changed to 'lbfgs' in 0.22. Specify a solver to silence this warning.\n",
      "  FutureWarning)\n"
     ]
    }
   ],
   "source": [
    "resultados2 = []\n",
    "kf = RepeatedKFold(n_splits=2, n_repeats=10, random_state=10)\n",
    "\n",
    "for linhas_treino, linhas_valid in kf.split(X):\n",
    "    print(\"Treino:\", linhas_treino.shape[0])\n",
    "    print(\"Valid:\", linhas_valid.shape[0])\n",
    "\n",
    "    X_treino, X_valid = X.iloc[linhas_treino], X.iloc[linhas_valid]\n",
    "    y_treino, y_valid = y.iloc[linhas_treino], y.iloc[linhas_valid]\n",
    "\n",
    "    #modelo = RandomForestClassifier(n_estimators=100, n_jobs=-1, random_state=0)\n",
    "    modelo = LogisticRegression()\n",
    "    \n",
    "    modelo.fit(X_treino, y_treino)\n",
    "\n",
    "    p = modelo.predict(X_valid)\n",
    "\n",
    "    acc = np.mean(y_valid == p)\n",
    "    resultados2.append(acc)\n",
    "    print(\"Acc:\", acc)\n",
    "    print()\n",
    "    #print(X_treino.head())\n",
    "    #print()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 56,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "((array([2., 3., 3., 5., 1., 2., 2., 0., 0., 2.]),\n",
       "  array([0.80224719, 0.80655162, 0.81085605, 0.81516048, 0.81946491,\n",
       "         0.82376934, 0.82807376, 0.83237819, 0.83668262, 0.84098705,\n",
       "         0.84529148]),\n",
       "  <a list of 10 Patch objects>),\n",
       " (array([4., 2., 0., 4., 2., 2., 4., 0., 1., 1.]),\n",
       "  array([0.77977528, 0.78565426, 0.79153323, 0.7974122 , 0.80329118,\n",
       "         0.80917015, 0.81504913, 0.8209281 , 0.82680707, 0.83268605,\n",
       "         0.83856502]),\n",
       "  <a list of 10 Patch objects>))"
      ]
     },
     "execution_count": 56,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "pylab.hist(resultados2), pylab.hist(resultados,alpha=0.8)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "modelo anterior = 0.8041457147175896"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 57,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.8190736635259735"
      ]
     },
     "execution_count": 57,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "np.mean(resultados2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 58,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/Users/mario/anaconda3/lib/python3.7/site-packages/sklearn/linear_model/logistic.py:433: FutureWarning: Default solver will be changed to 'lbfgs' in 0.22. Specify a solver to silence this warning.\n",
      "  FutureWarning)\n"
     ]
    }
   ],
   "source": [
    "test['Embarked_S'] = (test['Embarked'] == 'S').astype(int)\n",
    "test['Embarked_C'] = (test['Embarked'] == 'C').astype(int)\n",
    "#test['Embarked_Q'] = (test['Embarked'] == 'Q').astype(int)\n",
    "\n",
    "test['Cabine_nula'] = (test['Cabin'].isnull()).astype(int)\n",
    "\n",
    "test['Nome_contem_Miss'] = test['Name'].str.contains(\"Miss\").astype(int)\n",
    "test['Nome_contem_Mrs'] = test['Name'].str.contains(\"Mrs\").astype(int)\n",
    "\n",
    "test['Nome_contem_Master'] = test['Name'].str.contains(\"Master\").astype(int)\n",
    "test['Nome_contem_Col'] = test['Name'].str.contains(\"Col\").astype(int)\n",
    "test['Nome_contem_Major'] = test['Name'].str.contains(\"Major\").astype(int)\n",
    "test['Nome_contem_Mr'] = test['Name'].str.contains(\"Mr\").astype(int)\n",
    "\n",
    "modelo = LogisticRegression()\n",
    "modelo.fit(X, y)\n",
    "\n",
    "p = modelo.predict(test[variaveis].fillna(-1))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Criar submission"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 59,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(418,)"
      ]
     },
     "execution_count": 59,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "sub = pd.Series(p, index=test['PassengerId'], name='Survived')\n",
    "sub.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 60,
   "metadata": {},
   "outputs": [],
   "source": [
    "sub.to_csv(\"modelo_video6_lr.csv\", header=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
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  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
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