Pandas.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'/home/luiz/GitHub/data_science'"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import pandas as pd\n",
    "import matplotlib.pyplot as plt\n",
    "import os\n",
    "os.getcwd()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "scrolled": false
   },
   "outputs": [],
   "source": [
    "data = pd.read_csv(r'titanic/train.csv')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>PassengerId</th>\n",
       "      <th>Survived</th>\n",
       "      <th>Pclass</th>\n",
       "      <th>Name</th>\n",
       "      <th>Sex</th>\n",
       "      <th>Age</th>\n",
       "      <th>SibSp</th>\n",
       "      <th>Parch</th>\n",
       "      <th>Ticket</th>\n",
       "      <th>Fare</th>\n",
       "      <th>Cabin</th>\n",
       "      <th>Embarked</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>Braund, Mr. Owen Harris</td>\n",
       "      <td>male</td>\n",
       "      <td>22.0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>A/5 21171</td>\n",
       "      <td>7.2500</td>\n",
       "      <td>NaN</td>\n",
       "      <td>S</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>Cumings, Mrs. John Bradley (Florence Briggs Th...</td>\n",
       "      <td>female</td>\n",
       "      <td>38.0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>PC 17599</td>\n",
       "      <td>71.2833</td>\n",
       "      <td>C85</td>\n",
       "      <td>C</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>3</td>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "      <td>Heikkinen, Miss. Laina</td>\n",
       "      <td>female</td>\n",
       "      <td>26.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>STON/O2. 3101282</td>\n",
       "      <td>7.9250</td>\n",
       "      <td>NaN</td>\n",
       "      <td>S</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>4</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>Futrelle, Mrs. Jacques Heath (Lily May Peel)</td>\n",
       "      <td>female</td>\n",
       "      <td>35.0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>113803</td>\n",
       "      <td>53.1000</td>\n",
       "      <td>C123</td>\n",
       "      <td>S</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>5</td>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>Allen, Mr. William Henry</td>\n",
       "      <td>male</td>\n",
       "      <td>35.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>373450</td>\n",
       "      <td>8.0500</td>\n",
       "      <td>NaN</td>\n",
       "      <td>S</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   PassengerId  Survived  Pclass  \\\n",
       "0            1         0       3   \n",
       "1            2         1       1   \n",
       "2            3         1       3   \n",
       "3            4         1       1   \n",
       "4            5         0       3   \n",
       "\n",
       "                                                Name     Sex   Age  SibSp  \\\n",
       "0                            Braund, Mr. Owen Harris    male  22.0      1   \n",
       "1  Cumings, Mrs. John Bradley (Florence Briggs Th...  female  38.0      1   \n",
       "2                             Heikkinen, Miss. Laina  female  26.0      0   \n",
       "3       Futrelle, Mrs. Jacques Heath (Lily May Peel)  female  35.0      1   \n",
       "4                           Allen, Mr. William Henry    male  35.0      0   \n",
       "\n",
       "   Parch            Ticket     Fare Cabin Embarked  \n",
       "0      0         A/5 21171   7.2500   NaN        S  \n",
       "1      0          PC 17599  71.2833   C85        C  \n",
       "2      0  STON/O2. 3101282   7.9250   NaN        S  \n",
       "3      0            113803  53.1000  C123        S  \n",
       "4      0            373450   8.0500   NaN        S  "
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 891 entries, 0 to 890\n",
      "Data columns (total 12 columns):\n",
      "PassengerId    891 non-null int64\n",
      "Survived       891 non-null int64\n",
      "Pclass         891 non-null int64\n",
      "Name           891 non-null object\n",
      "Sex            891 non-null object\n",
      "Age            714 non-null float64\n",
      "SibSp          891 non-null int64\n",
      "Parch          891 non-null int64\n",
      "Ticket         891 non-null object\n",
      "Fare           891 non-null float64\n",
      "Cabin          204 non-null object\n",
      "Embarked       889 non-null object\n",
      "dtypes: float64(2), int64(5), object(5)\n",
      "memory usage: 83.6+ KB\n"
     ]
    }
   ],
   "source": [
    "data.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>PassengerId</th>\n",
       "      <th>Survived</th>\n",
       "      <th>Pclass</th>\n",
       "      <th>Age</th>\n",
       "      <th>SibSp</th>\n",
       "      <th>Parch</th>\n",
       "      <th>Fare</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>891.000000</td>\n",
       "      <td>891.000000</td>\n",
       "      <td>891.000000</td>\n",
       "      <td>714.000000</td>\n",
       "      <td>891.000000</td>\n",
       "      <td>891.000000</td>\n",
       "      <td>891.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>446.000000</td>\n",
       "      <td>0.383838</td>\n",
       "      <td>2.308642</td>\n",
       "      <td>29.699118</td>\n",
       "      <td>0.523008</td>\n",
       "      <td>0.381594</td>\n",
       "      <td>32.204208</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>std</th>\n",
       "      <td>257.353842</td>\n",
       "      <td>0.486592</td>\n",
       "      <td>0.836071</td>\n",
       "      <td>14.526497</td>\n",
       "      <td>1.102743</td>\n",
       "      <td>0.806057</td>\n",
       "      <td>49.693429</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.420000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25%</th>\n",
       "      <td>223.500000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>2.000000</td>\n",
       "      <td>20.125000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>7.910400</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50%</th>\n",
       "      <td>446.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>3.000000</td>\n",
       "      <td>28.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>14.454200</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75%</th>\n",
       "      <td>668.500000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>3.000000</td>\n",
       "      <td>38.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>31.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>max</th>\n",
       "      <td>891.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>3.000000</td>\n",
       "      <td>80.000000</td>\n",
       "      <td>8.000000</td>\n",
       "      <td>6.000000</td>\n",
       "      <td>512.329200</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "       PassengerId    Survived      Pclass         Age       SibSp  \\\n",
       "count   891.000000  891.000000  891.000000  714.000000  891.000000   \n",
       "mean    446.000000    0.383838    2.308642   29.699118    0.523008   \n",
       "std     257.353842    0.486592    0.836071   14.526497    1.102743   \n",
       "min       1.000000    0.000000    1.000000    0.420000    0.000000   \n",
       "25%     223.500000    0.000000    2.000000   20.125000    0.000000   \n",
       "50%     446.000000    0.000000    3.000000   28.000000    0.000000   \n",
       "75%     668.500000    1.000000    3.000000   38.000000    1.000000   \n",
       "max     891.000000    1.000000    3.000000   80.000000    8.000000   \n",
       "\n",
       "            Parch        Fare  \n",
       "count  891.000000  891.000000  \n",
       "mean     0.381594   32.204208  \n",
       "std      0.806057   49.693429  \n",
       "min      0.000000    0.000000  \n",
       "25%      0.000000    7.910400  \n",
       "50%      0.000000   14.454200  \n",
       "75%      0.000000   31.000000  \n",
       "max      6.000000  512.329200  "
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data.describe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Name</th>\n",
       "      <th>Sex</th>\n",
       "      <th>Ticket</th>\n",
       "      <th>Cabin</th>\n",
       "      <th>Embarked</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>891</td>\n",
       "      <td>891</td>\n",
       "      <td>891</td>\n",
       "      <td>204</td>\n",
       "      <td>889</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>unique</th>\n",
       "      <td>891</td>\n",
       "      <td>2</td>\n",
       "      <td>681</td>\n",
       "      <td>147</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>top</th>\n",
       "      <td>Harper, Mrs. Henry Sleeper (Myna Haxtun)</td>\n",
       "      <td>male</td>\n",
       "      <td>1601</td>\n",
       "      <td>G6</td>\n",
       "      <td>S</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>freq</th>\n",
       "      <td>1</td>\n",
       "      <td>577</td>\n",
       "      <td>7</td>\n",
       "      <td>4</td>\n",
       "      <td>644</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                            Name   Sex Ticket Cabin Embarked\n",
       "count                                        891   891    891   204      889\n",
       "unique                                       891     2    681   147        3\n",
       "top     Harper, Mrs. Henry Sleeper (Myna Haxtun)  male   1601    G6        S\n",
       "freq                                           1   577      7     4      644"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data.describe(include='O')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [],
   "source": [
    "data.rename(\n",
    "    {\n",
    "        'PassengerId': 'IdPassageiro',\n",
    "        'Survived': 'Sobreviveu',\n",
    "        'Pclass': 'Classe',\n",
    "        'Name': 'Nome',\n",
    "        'Sex': 'Sexo',\n",
    "        'Age': 'Idade',\n",
    "        'Embarked': 'Embarcou'\n",
    "    },\n",
    "        axis=1, inplace=True\n",
    "    )"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>IdPassageiro</th>\n",
       "      <th>Sobreviveu</th>\n",
       "      <th>Classe</th>\n",
       "      <th>Nome</th>\n",
       "      <th>Sexo</th>\n",
       "      <th>Idade</th>\n",
       "      <th>SibSp</th>\n",
       "      <th>Parch</th>\n",
       "      <th>Ticket</th>\n",
       "      <th>Fare</th>\n",
       "      <th>Cabin</th>\n",
       "      <th>Embarcou</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>Braund, Mr. Owen Harris</td>\n",
       "      <td>male</td>\n",
       "      <td>22.0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>A/5 21171</td>\n",
       "      <td>7.2500</td>\n",
       "      <td>NaN</td>\n",
       "      <td>S</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>Cumings, Mrs. John Bradley (Florence Briggs Th...</td>\n",
       "      <td>female</td>\n",
       "      <td>38.0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>PC 17599</td>\n",
       "      <td>71.2833</td>\n",
       "      <td>C85</td>\n",
       "      <td>C</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>3</td>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "      <td>Heikkinen, Miss. Laina</td>\n",
       "      <td>female</td>\n",
       "      <td>26.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>STON/O2. 3101282</td>\n",
       "      <td>7.9250</td>\n",
       "      <td>NaN</td>\n",
       "      <td>S</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>4</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>Futrelle, Mrs. Jacques Heath (Lily May Peel)</td>\n",
       "      <td>female</td>\n",
       "      <td>35.0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>113803</td>\n",
       "      <td>53.1000</td>\n",
       "      <td>C123</td>\n",
       "      <td>S</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>5</td>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>Allen, Mr. William Henry</td>\n",
       "      <td>male</td>\n",
       "      <td>35.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>373450</td>\n",
       "      <td>8.0500</td>\n",
       "      <td>NaN</td>\n",
       "      <td>S</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   IdPassageiro  Sobreviveu  Classe  \\\n",
       "0             1           0       3   \n",
       "1             2           1       1   \n",
       "2             3           1       3   \n",
       "3             4           1       1   \n",
       "4             5           0       3   \n",
       "\n",
       "                                                Nome    Sexo  Idade  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 Embarcou  \n",
       "0      0         A/5 21171   7.2500   NaN        S  \n",
       "1      0          PC 17599  71.2833   C85        C  \n",
       "2      0  STON/O2. 3101282   7.9250   NaN        S  \n",
       "3      0            113803  53.1000  C123        S  \n",
       "4      0            373450   8.0500   NaN        S  "
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Index(['IdPassageiro', 'Sobreviveu', 'Classe', 'Nome', 'Sexo', 'Idade',\n",
       "       'SibSp', 'Parch', 'Ticket', 'Fare', 'Cabin', 'Embarcou'],\n",
       "      dtype='object')"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data.columns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [],
   "source": [
    "data.columns = ['IdPassageiro', 'Sobreviveu',\n",
    "                'Classe', 'Nome', 'Sexo',\n",
    "                'Idade', 'IrmaosConjuge',\n",
    "                'PaisFilhos', 'Bilhete',\n",
    "                'Tarifa', 'Cabine', 'Embarque']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Nome</th>\n",
       "      <th>Sexo</th>\n",
       "      <th>Idade</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Braund, Mr. Owen Harris</td>\n",
       "      <td>male</td>\n",
       "      <td>22.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Cumings, Mrs. John Bradley (Florence Briggs Th...</td>\n",
       "      <td>female</td>\n",
       "      <td>38.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Heikkinen, Miss. Laina</td>\n",
       "      <td>female</td>\n",
       "      <td>26.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Futrelle, Mrs. Jacques Heath (Lily May Peel)</td>\n",
       "      <td>female</td>\n",
       "      <td>35.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Allen, Mr. William Henry</td>\n",
       "      <td>male</td>\n",
       "      <td>35.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                                Nome    Sexo  Idade\n",
       "0                            Braund, Mr. Owen Harris    male   22.0\n",
       "1  Cumings, Mrs. John Bradley (Florence Briggs Th...  female   38.0\n",
       "2                             Heikkinen, Miss. Laina  female   26.0\n",
       "3       Futrelle, Mrs. Jacques Heath (Lily May Peel)  female   35.0\n",
       "4                           Allen, Mr. William Henry    male   35.0"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data[['Nome', 'Sexo', 'Idade']].head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Nome</th>\n",
       "      <th>Sexo</th>\n",
       "      <th>Idade</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Braund, Mr. Owen Harris</td>\n",
       "      <td>male</td>\n",
       "      <td>22.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Cumings, Mrs. John Bradley (Florence Briggs Th...</td>\n",
       "      <td>female</td>\n",
       "      <td>38.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Heikkinen, Miss. Laina</td>\n",
       "      <td>female</td>\n",
       "      <td>26.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Futrelle, Mrs. Jacques Heath (Lily May Peel)</td>\n",
       "      <td>female</td>\n",
       "      <td>35.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Allen, Mr. William Henry</td>\n",
       "      <td>male</td>\n",
       "      <td>35.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                                Nome    Sexo  Idade\n",
       "0                            Braund, Mr. Owen Harris    male   22.0\n",
       "1  Cumings, Mrs. John Bradley (Florence Briggs Th...  female   38.0\n",
       "2                             Heikkinen, Miss. Laina  female   26.0\n",
       "3       Futrelle, Mrs. Jacques Heath (Lily May Peel)  female   35.0\n",
       "4                           Allen, Mr. William Henry    male   35.0"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "interesse = ['Nome', 'Sexo', 'Idade']\n",
    "data[interesse].head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "29.69911764705882"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    ", "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "28.0"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data['Idade'].median() #mediana"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0    24.0\n",
       "dtype: float64"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data['Idade'].mode() #valor que mais se repete"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "803"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data['Idade'].idxmin() #indice da ocorrencia min."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "IdPassageiro                                      631\n",
       "Sobreviveu                                          1\n",
       "Classe                                              1\n",
       "Nome             Barkworth, Mr. Algernon Henry Wilson\n",
       "Sexo                                             male\n",
       "Idade                                              80\n",
       "IrmaosConjuge                                       0\n",
       "PaisFilhos                                          0\n",
       "Bilhete                                         27042\n",
       "Tarifa                                             30\n",
       "Cabine                                            A23\n",
       "Embarque                                            S\n",
       "Name: 630, dtype: object"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data.iloc[630] #localiza pelo indi"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>IdPassageiro</th>\n",
       "      <th>Sobreviveu</th>\n",
       "      <th>Classe</th>\n",
       "      <th>Nome</th>\n",
       "      <th>Sexo</th>\n",
       "      <th>Idade</th>\n",
       "      <th>IrmaosConjuge</th>\n",
       "      <th>PaisFilhos</th>\n",
       "      <th>Bilhete</th>\n",
       "      <th>Tarifa</th>\n",
       "      <th>Cabine</th>\n",
       "      <th>Embarque</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>630</th>\n",
       "      <td>631</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>Barkworth, Mr. Algernon Henry Wilson</td>\n",
       "      <td>male</td>\n",
       "      <td>80.00</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>27042</td>\n",
       "      <td>30.0000</td>\n",
       "      <td>A23</td>\n",
       "      <td>S</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>803</th>\n",
       "      <td>804</td>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "      <td>Thomas, Master. Assad Alexander</td>\n",
       "      <td>male</td>\n",
       "      <td>0.42</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>2625</td>\n",
       "      <td>8.5167</td>\n",
       "      <td>NaN</td>\n",
       "      <td>C</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "     IdPassageiro  Sobreviveu  Classe                                  Nome  \\\n",
       "630           631           1       1  Barkworth, Mr. Algernon Henry Wilson   \n",
       "803           804           1       3       Thomas, Master. Assad Alexander   \n",
       "\n",
       "     Sexo  Idade  IrmaosConjuge  PaisFilhos Bilhete   Tarifa Cabine Embarque  \n",
       "630  male  80.00              0           0   27042  30.0000    A23        S  \n",
       "803  male   0.42              0           1    2625   8.5167    NaN        C  "
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data.iloc[[630, 803]]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>IdPassageiro</th>\n",
       "      <th>Sobreviveu</th>\n",
       "      <th>Classe</th>\n",
       "      <th>Nome</th>\n",
       "      <th>Sexo</th>\n",
       "      <th>Idade</th>\n",
       "      <th>IrmaosConjuge</th>\n",
       "      <th>PaisFilhos</th>\n",
       "      <th>Bilhete</th>\n",
       "      <th>Tarifa</th>\n",
       "      <th>Cabine</th>\n",
       "      <th>Embarque</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>630</th>\n",
       "      <td>631</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>Barkworth, Mr. Algernon Henry Wilson</td>\n",
       "      <td>male</td>\n",
       "      <td>80.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>27042</td>\n",
       "      <td>30.0000</td>\n",
       "      <td>A23</td>\n",
       "      <td>S</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>631</th>\n",
       "      <td>632</td>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>Lundahl, Mr. Johan Svensson</td>\n",
       "      <td>male</td>\n",
       "      <td>51.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>347743</td>\n",
       "      <td>7.0542</td>\n",
       "      <td>NaN</td>\n",
       "      <td>S</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>632</th>\n",
       "      <td>633</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>Stahelin-Maeglin, Dr. Max</td>\n",
       "      <td>male</td>\n",
       "      <td>32.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>13214</td>\n",
       "      <td>30.5000</td>\n",
       "      <td>B50</td>\n",
       "      <td>C</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>633</th>\n",
       "      <td>634</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>Parr, Mr. William Henry Marsh</td>\n",
       "      <td>male</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>112052</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>S</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>634</th>\n",
       "      <td>635</td>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>Skoog, Miss. Mabel</td>\n",
       "      <td>female</td>\n",
       "      <td>9.0</td>\n",
       "      <td>3</td>\n",
       "      <td>2</td>\n",
       "      <td>347088</td>\n",
       "      <td>27.9000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>S</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "     IdPassageiro  Sobreviveu  Classe                                  Nome  \\\n",
       "630           631           1       1  Barkworth, Mr. Algernon Henry Wilson   \n",
       "631           632           0       3           Lundahl, Mr. Johan Svensson   \n",
       "632           633           1       1             Stahelin-Maeglin, Dr. Max   \n",
       "633           634           0       1         Parr, Mr. William Henry Marsh   \n",
       "634           635           0       3                    Skoog, Miss. Mabel   \n",
       "\n",
       "       Sexo  Idade  IrmaosConjuge  PaisFilhos Bilhete   Tarifa Cabine Embarque  \n",
       "630    male   80.0              0           0   27042  30.0000    A23        S  \n",
       "631    male   51.0              0           0  347743   7.0542    NaN        S  \n",
       "632    male   32.0              0           0   13214  30.5000    B50        C  \n",
       "633    male    NaN              0           0  112052   0.0000    NaN        S  \n",
       "634  female    9.0              3           2  347088  27.9000    NaN        S  "
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data.iloc[630:635]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Nome</th>\n",
       "      <th>Sexo</th>\n",
       "      <th>Idade</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>630</th>\n",
       "      <td>Barkworth, Mr. Algernon Henry Wilson</td>\n",
       "      <td>male</td>\n",
       "      <td>80.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>631</th>\n",
       "      <td>Lundahl, Mr. Johan Svensson</td>\n",
       "      <td>male</td>\n",
       "      <td>51.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>632</th>\n",
       "      <td>Stahelin-Maeglin, Dr. Max</td>\n",
       "      <td>male</td>\n",
       "      <td>32.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>633</th>\n",
       "      <td>Parr, Mr. William Henry Marsh</td>\n",
       "      <td>male</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>634</th>\n",
       "      <td>Skoog, Miss. Mabel</td>\n",
       "      <td>female</td>\n",
       "      <td>9.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                     Nome    Sexo  Idade\n",
       "630  Barkworth, Mr. Algernon Henry Wilson    male   80.0\n",
       "631           Lundahl, Mr. Johan Svensson    male   51.0\n",
       "632             Stahelin-Maeglin, Dr. Max    male   32.0\n",
       "633         Parr, Mr. William Henry Marsh    male    NaN\n",
       "634                    Skoog, Miss. Mabel  female    9.0"
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data[interesse].iloc[630:635]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "342"
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len(data[interesse].loc[data['Sobreviveu']==1])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [],
   "source": [
    "infos1 = data[['Nome', 'Sexo', 'Idade']].loc[~(data['Sobreviveu']==1) & (data['Idade']<16)]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "34\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "                                        Nome    Sexo  Idade\n",
      "7             Palsson, Master. Gosta Leonard    male    2.0\n",
      "14      Vestrom, Miss. Hulda Amanda Adolfina  female   14.0\n",
      "16                      Rice, Master. Eugene    male    2.0\n",
      "24             Palsson, Miss. Torborg Danira  female    8.0\n",
      "50                Panula, Master. Juha Niilo    male    7.0\n",
      "59        Goodwin, Master. William Frederick    male   11.0\n",
      "63                     Skoog, Master. Harald    male    4.0\n",
      "111                     Zabour, Miss. Hileni  female   14.5\n",
      "119        Andersson, Miss. Ellis Anna Maria  female    2.0\n",
      "147         Ford, Miss. Robina Maggie \"Ruby\"  female    9.0\n",
      "164             Panula, Master. Eino Viljami    male    1.0\n",
      "171                     Rice, Master. Arthur    male    4.0\n",
      "182    Asplund, Master. Clarence Gustaf Hugo    male    9.0\n",
      "205               Strom, Miss. Telma Matilda  female    2.0\n",
      "278                       Rice, Master. Eric    male    7.0\n",
      "297             Allison, Miss. Helen Loraine  female    2.0\n",
      "352                       Elias, Mr. Tannous    male   15.0\n",
      "374               Palsson, Miss. Stina Viola  female    3.0\n",
      "386          Goodwin, Master. Sidney Leonard    male    1.0\n",
      "419                Van Impe, Miss. Catharina  female   10.0\n",
      "480           Goodwin, Master. Harold Victor    male    9.0\n",
      "541     Andersson, Miss. Ingeborg Constanzia  female    9.0\n",
      "542        Andersson, Miss. Sigrid Elisabeth  female   11.0\n",
      "634                       Skoog, Miss. Mabel  female    9.0\n",
      "642            Skoog, Miss. Margit Elizabeth  female    2.0\n",
      "683              Goodwin, Mr. Charles Edward    male   14.0\n",
      "686                 Panula, Mr. Jaako Arnold    male   14.0\n",
      "731                 Hassan, Mr. Houssein G N    male   11.0\n",
      "787                Rice, Master. George Hugh    male    8.0\n",
      "813       Andersson, Miss. Ebba Iris Alfrida  female    6.0\n",
      "819             Skoog, Master. Karl Thorsten    male   10.0\n",
      "824             Panula, Master. Urho Abraham    male    2.0\n",
      "850  Andersson, Master. Sigvard Harald Elias    male    4.0\n",
      "852                  Boulos, Miss. Nourelain  female    9.0\n"
     ]
    }
   ],
   "source": [
    "print(len(infos1))\n",
    "print(type(infos1))\n",
    "print(infos1[:])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [],
   "source": [
    "data['Sexo'].replace({'male': 'homem', 'female':'mulher'}, inplace=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>IdPassageiro</th>\n",
       "      <th>Sobreviveu</th>\n",
       "      <th>Classe</th>\n",
       "      <th>Nome</th>\n",
       "      <th>Idade</th>\n",
       "      <th>IrmaosConjuge</th>\n",
       "      <th>PaisFilhos</th>\n",
       "      <th>Bilhete</th>\n",
       "      <th>Tarifa</th>\n",
       "      <th>Cabine</th>\n",
       "      <th>Embarque</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Sexo</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>homem</th>\n",
       "      <td>577</td>\n",
       "      <td>577</td>\n",
       "      <td>577</td>\n",
       "      <td>577</td>\n",
       "      <td>453</td>\n",
       "      <td>577</td>\n",
       "      <td>577</td>\n",
       "      <td>577</td>\n",
       "      <td>577</td>\n",
       "      <td>107</td>\n",
       "      <td>577</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mulher</th>\n",
       "      <td>314</td>\n",
       "      <td>314</td>\n",
       "      <td>314</td>\n",
       "      <td>314</td>\n",
       "      <td>261</td>\n",
       "      <td>314</td>\n",
       "      <td>314</td>\n",
       "      <td>314</td>\n",
       "      <td>314</td>\n",
       "      <td>97</td>\n",
       "      <td>312</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "        IdPassageiro  Sobreviveu  Classe  Nome  Idade  IrmaosConjuge  \\\n",
       "Sexo                                                                   \n",
       "homem            577         577     577   577    453            577   \n",
       "mulher           314         314     314   314    261            314   \n",
       "\n",
       "        PaisFilhos  Bilhete  Tarifa  Cabine  Embarque  \n",
       "Sexo                                                   \n",
       "homem          577      577     577     107       577  \n",
       "mulher         314      314     314      97       312  "
      ]
     },
     "execution_count": 27,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data.groupby('Sexo').count()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>IdPassageiro</th>\n",
       "      <th>Sobreviveu</th>\n",
       "      <th>Classe</th>\n",
       "      <th>Idade</th>\n",
       "      <th>IrmaosConjuge</th>\n",
       "      <th>PaisFilhos</th>\n",
       "      <th>Tarifa</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Sexo</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>homem</th>\n",
       "      <td>454.147314</td>\n",
       "      <td>0.188908</td>\n",
       "      <td>2.389948</td>\n",
       "      <td>30.726645</td>\n",
       "      <td>0.429809</td>\n",
       "      <td>0.235702</td>\n",
       "      <td>25.523893</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mulher</th>\n",
       "      <td>431.028662</td>\n",
       "      <td>0.742038</td>\n",
       "      <td>2.159236</td>\n",
       "      <td>27.915709</td>\n",
       "      <td>0.694268</td>\n",
       "      <td>0.649682</td>\n",
       "      <td>44.479818</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "        IdPassageiro  Sobreviveu    Classe      Idade  IrmaosConjuge  \\\n",
       "Sexo                                                                   \n",
       "homem     454.147314    0.188908  2.389948  30.726645       0.429809   \n",
       "mulher    431.028662    0.742038  2.159236  27.915709       0.694268   \n",
       "\n",
       "        PaisFilhos     Tarifa  \n",
       "Sexo                           \n",
       "homem     0.235702  25.523893  \n",
       "mulher    0.649682  44.479818  "
      ]
     },
     "execution_count": 28,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data.groupby('Sexo').mean()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>IdPassageiro</th>\n",
       "      <th>Classe</th>\n",
       "      <th>Idade</th>\n",
       "      <th>IrmaosConjuge</th>\n",
       "      <th>PaisFilhos</th>\n",
       "      <th>Tarifa</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Sobreviveu</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>447.016393</td>\n",
       "      <td>2.531876</td>\n",
       "      <td>30.626179</td>\n",
       "      <td>0.553734</td>\n",
       "      <td>0.329690</td>\n",
       "      <td>22.117887</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>444.368421</td>\n",
       "      <td>1.950292</td>\n",
       "      <td>28.343690</td>\n",
       "      <td>0.473684</td>\n",
       "      <td>0.464912</td>\n",
       "      <td>48.395408</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "            IdPassageiro    Classe      Idade  IrmaosConjuge  PaisFilhos  \\\n",
       "Sobreviveu                                                                 \n",
       "0             447.016393  2.531876  30.626179       0.553734    0.329690   \n",
       "1             444.368421  1.950292  28.343690       0.473684    0.464912   \n",
       "\n",
       "               Tarifa  \n",
       "Sobreviveu             \n",
       "0           22.117887  \n",
       "1           48.395408  "
      ]
     },
     "execution_count": 29,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data.groupby('Sobreviveu').mean()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>IdPassageiro</th>\n",
       "      <th>Sobreviveu</th>\n",
       "      <th>Idade</th>\n",
       "      <th>IrmaosConjuge</th>\n",
       "      <th>PaisFilhos</th>\n",
       "      <th>Tarifa</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Classe</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>461.597222</td>\n",
       "      <td>0.629630</td>\n",
       "      <td>38.233441</td>\n",
       "      <td>0.416667</td>\n",
       "      <td>0.356481</td>\n",
       "      <td>84.154687</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>445.956522</td>\n",
       "      <td>0.472826</td>\n",
       "      <td>29.877630</td>\n",
       "      <td>0.402174</td>\n",
       "      <td>0.380435</td>\n",
       "      <td>20.662183</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>439.154786</td>\n",
       "      <td>0.242363</td>\n",
       "      <td>25.140620</td>\n",
       "      <td>0.615071</td>\n",
       "      <td>0.393075</td>\n",
       "      <td>13.675550</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "        IdPassageiro  Sobreviveu      Idade  IrmaosConjuge  PaisFilhos  \\\n",
       "Classe                                                                   \n",
       "1         461.597222    0.629630  38.233441       0.416667    0.356481   \n",
       "2         445.956522    0.472826  29.877630       0.402174    0.380435   \n",
       "3         439.154786    0.242363  25.140620       0.615071    0.393075   \n",
       "\n",
       "           Tarifa  \n",
       "Classe             \n",
       "1       84.154687  \n",
       "2       20.662183  \n",
       "3       13.675550  "
      ]
     },
     "execution_count": 30,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data.groupby('Classe').mean()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th>IdPassageiro</th>\n",
       "      <th>Sobreviveu</th>\n",
       "      <th>Idade</th>\n",
       "      <th>IrmaosConjuge</th>\n",
       "      <th>PaisFilhos</th>\n",
       "      <th>Tarifa</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Sexo</th>\n",
       "      <th>Classe</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th rowspan=\"3\" valign=\"top\">homem</th>\n",
       "      <th>1</th>\n",
       "      <td>455.729508</td>\n",
       "      <td>0.368852</td>\n",
       "      <td>41.281386</td>\n",
       "      <td>0.311475</td>\n",
       "      <td>0.278689</td>\n",
       "      <td>67.226127</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>447.962963</td>\n",
       "      <td>0.157407</td>\n",
       "      <td>30.740707</td>\n",
       "      <td>0.342593</td>\n",
       "      <td>0.222222</td>\n",
       "      <td>19.741782</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>455.515850</td>\n",
       "      <td>0.135447</td>\n",
       "      <td>26.507589</td>\n",
       "      <td>0.498559</td>\n",
       "      <td>0.224784</td>\n",
       "      <td>12.661633</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"3\" valign=\"top\">mulher</th>\n",
       "      <th>1</th>\n",
       "      <td>469.212766</td>\n",
       "      <td>0.968085</td>\n",
       "      <td>34.611765</td>\n",
       "      <td>0.553191</td>\n",
       "      <td>0.457447</td>\n",
       "      <td>106.125798</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>443.105263</td>\n",
       "      <td>0.921053</td>\n",
       "      <td>28.722973</td>\n",
       "      <td>0.486842</td>\n",
       "      <td>0.605263</td>\n",
       "      <td>21.970121</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>399.729167</td>\n",
       "      <td>0.500000</td>\n",
       "      <td>21.750000</td>\n",
       "      <td>0.895833</td>\n",
       "      <td>0.798611</td>\n",
       "      <td>16.118810</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "               IdPassageiro  Sobreviveu      Idade  IrmaosConjuge  PaisFilhos  \\\n",
       "Sexo   Classe                                                                   \n",
       "homem  1         455.729508    0.368852  41.281386       0.311475    0.278689   \n",
       "       2         447.962963    0.157407  30.740707       0.342593    0.222222   \n",
       "       3         455.515850    0.135447  26.507589       0.498559    0.224784   \n",
       "mulher 1         469.212766    0.968085  34.611765       0.553191    0.457447   \n",
       "       2         443.105263    0.921053  28.722973       0.486842    0.605263   \n",
       "       3         399.729167    0.500000  21.750000       0.895833    0.798611   \n",
       "\n",
       "                   Tarifa  \n",
       "Sexo   Classe              \n",
       "homem  1        67.226127  \n",
       "       2        19.741782  \n",
       "       3        12.661633  \n",
       "mulher 1       106.125798  \n",
       "       2        21.970121  \n",
       "       3        16.118810  "
      ]
     },
     "execution_count": 31,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data.groupby(['Sexo', 'Classe']).mean()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th>Sexo</th>\n",
       "      <th>homem</th>\n",
       "      <th>mulher</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Sobreviveu</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>468</td>\n",
       "      <td>81</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>109</td>\n",
       "      <td>233</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "Sexo        homem  mulher\n",
       "Sobreviveu               \n",
       "0             468      81\n",
       "1             109     233"
      ]
     },
     "execution_count": 32,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pd.crosstab(data['Sobreviveu'],data['Sexo'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<style  type=\"text/css\" >\n",
       "    #T_37257b94_3eb4_11ea_9892_fcaa14f4f223row0_col0 {\n",
       "            background-color:  #2258a5;\n",
       "        }    #T_37257b94_3eb4_11ea_9892_fcaa14f4f223row0_col1 {\n",
       "            background-color:  #ffffd9;\n",
       "        }    #T_37257b94_3eb4_11ea_9892_fcaa14f4f223row0_col2 {\n",
       "            background-color:  #7ecdbb;\n",
       "        }    #T_37257b94_3eb4_11ea_9892_fcaa14f4f223row1_col0 {\n",
       "            background-color:  #ffffd9;\n",
       "        }    #T_37257b94_3eb4_11ea_9892_fcaa14f4f223row1_col1 {\n",
       "            background-color:  #1e85ba;\n",
       "        }    #T_37257b94_3eb4_11ea_9892_fcaa14f4f223row1_col2 {\n",
       "            background-color:  #ffffd9;\n",
       "        }    #T_37257b94_3eb4_11ea_9892_fcaa14f4f223row2_col0 {\n",
       "            background-color:  #081d58;\n",
       "        }    #T_37257b94_3eb4_11ea_9892_fcaa14f4f223row2_col1 {\n",
       "            background-color:  #081d58;\n",
       "        }    #T_37257b94_3eb4_11ea_9892_fcaa14f4f223row2_col2 {\n",
       "            background-color:  #081d58;\n",
       "        }</style>  \n",
       "<table id=\"T_37257b94_3eb4_11ea_9892_fcaa14f4f223\" > \n",
       "<thead>    <tr> \n",
       "        <th class=\"index_name level0\" >Sexo</th> \n",
       "        <th class=\"col_heading level0 col0\" >homem</th> \n",
       "        <th class=\"col_heading level0 col1\" >mulher</th> \n",
       "        <th class=\"col_heading level0 col2\" >Total</th> \n",
       "    </tr>    <tr> \n",
       "        <th class=\"index_name level0\" >Sobreviveu</th> \n",
       "        <th class=\"blank\" ></th> \n",
       "        <th class=\"blank\" ></th> \n",
       "        <th class=\"blank\" ></th> \n",
       "    </tr></thead> \n",
       "<tbody>    <tr> \n",
       "        <th id=\"T_37257b94_3eb4_11ea_9892_fcaa14f4f223level0_row0\" class=\"row_heading level0 row0\" >0</th> \n",
       "        <td id=\"T_37257b94_3eb4_11ea_9892_fcaa14f4f223row0_col0\" class=\"data row0 col0\" >468</td> \n",
       "        <td id=\"T_37257b94_3eb4_11ea_9892_fcaa14f4f223row0_col1\" class=\"data row0 col1\" >81</td> \n",
       "        <td id=\"T_37257b94_3eb4_11ea_9892_fcaa14f4f223row0_col2\" class=\"data row0 col2\" >549</td> \n",
       "    </tr>    <tr> \n",
       "        <th id=\"T_37257b94_3eb4_11ea_9892_fcaa14f4f223level0_row1\" class=\"row_heading level0 row1\" >1</th> \n",
       "        <td id=\"T_37257b94_3eb4_11ea_9892_fcaa14f4f223row1_col0\" class=\"data row1 col0\" >109</td> \n",
       "        <td id=\"T_37257b94_3eb4_11ea_9892_fcaa14f4f223row1_col1\" class=\"data row1 col1\" >233</td> \n",
       "        <td id=\"T_37257b94_3eb4_11ea_9892_fcaa14f4f223row1_col2\" class=\"data row1 col2\" >342</td> \n",
       "    </tr>    <tr> \n",
       "        <th id=\"T_37257b94_3eb4_11ea_9892_fcaa14f4f223level0_row2\" class=\"row_heading level0 row2\" >Total</th> \n",
       "        <td id=\"T_37257b94_3eb4_11ea_9892_fcaa14f4f223row2_col0\" class=\"data row2 col0\" >577</td> \n",
       "        <td id=\"T_37257b94_3eb4_11ea_9892_fcaa14f4f223row2_col1\" class=\"data row2 col1\" >314</td> \n",
       "        <td id=\"T_37257b94_3eb4_11ea_9892_fcaa14f4f223row2_col2\" class=\"data row2 col2\" >891</td> \n",
       "    </tr></tbody> \n",
       "</table> "
      ],
      "text/plain": [
       "<pandas.io.formats.style.Styler at 0x7fe5cf8e7710>"
      ]
     },
     "execution_count": 33,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pd.crosstab(data['Sobreviveu'],\n",
    "            data['Sexo'],\n",
    "            margins=True, \n",
    "            margins_name='Total').style.background_gradient(cmap='YlGnBu')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Idade</th>\n",
       "      <th>Sexo</th>\n",
       "      <th>Classe</th>\n",
       "      <th>Sobreviveu</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>803</th>\n",
       "      <td>0.42</td>\n",
       "      <td>homem</td>\n",
       "      <td>3</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>755</th>\n",
       "      <td>0.67</td>\n",
       "      <td>homem</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>644</th>\n",
       "      <td>0.75</td>\n",
       "      <td>mulher</td>\n",
       "      <td>3</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>469</th>\n",
       "      <td>0.75</td>\n",
       "      <td>mulher</td>\n",
       "      <td>3</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>78</th>\n",
       "      <td>0.83</td>\n",
       "      <td>homem</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>831</th>\n",
       "      <td>0.83</td>\n",
       "      <td>homem</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>305</th>\n",
       "      <td>0.92</td>\n",
       "      <td>homem</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>827</th>\n",
       "      <td>1.00</td>\n",
       "      <td>homem</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>381</th>\n",
       "      <td>1.00</td>\n",
       "      <td>mulher</td>\n",
       "      <td>3</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>164</th>\n",
       "      <td>1.00</td>\n",
       "      <td>homem</td>\n",
       "      <td>3</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>183</th>\n",
       "      <td>1.00</td>\n",
       "      <td>homem</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>386</th>\n",
       "      <td>1.00</td>\n",
       "      <td>homem</td>\n",
       "      <td>3</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>172</th>\n",
       "      <td>1.00</td>\n",
       "      <td>mulher</td>\n",
       "      <td>3</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>788</th>\n",
       "      <td>1.00</td>\n",
       "      <td>homem</td>\n",
       "      <td>3</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>642</th>\n",
       "      <td>2.00</td>\n",
       "      <td>mulher</td>\n",
       "      <td>3</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>2.00</td>\n",
       "      <td>homem</td>\n",
       "      <td>3</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>530</th>\n",
       "      <td>2.00</td>\n",
       "      <td>mulher</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>297</th>\n",
       "      <td>2.00</td>\n",
       "      <td>mulher</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>824</th>\n",
       "      <td>2.00</td>\n",
       "      <td>homem</td>\n",
       "      <td>3</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>205</th>\n",
       "      <td>2.00</td>\n",
       "      <td>mulher</td>\n",
       "      <td>3</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>119</th>\n",
       "      <td>2.00</td>\n",
       "      <td>mulher</td>\n",
       "      <td>3</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>340</th>\n",
       "      <td>2.00</td>\n",
       "      <td>homem</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>479</th>\n",
       "      <td>2.00</td>\n",
       "      <td>mulher</td>\n",
       "      <td>3</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>2.00</td>\n",
       "      <td>homem</td>\n",
       "      <td>3</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>348</th>\n",
       "      <td>3.00</td>\n",
       "      <td>homem</td>\n",
       "      <td>3</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>407</th>\n",
       "      <td>3.00</td>\n",
       "      <td>homem</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>374</th>\n",
       "      <td>3.00</td>\n",
       "      <td>mulher</td>\n",
       "      <td>3</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>261</th>\n",
       "      <td>3.00</td>\n",
       "      <td>homem</td>\n",
       "      <td>3</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>43</th>\n",
       "      <td>3.00</td>\n",
       "      <td>mulher</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>193</th>\n",
       "      <td>3.00</td>\n",
       "      <td>homem</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>718</th>\n",
       "      <td>NaN</td>\n",
       "      <td>homem</td>\n",
       "      <td>3</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>727</th>\n",
       "      <td>NaN</td>\n",
       "      <td>mulher</td>\n",
       "      <td>3</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>732</th>\n",
       "      <td>NaN</td>\n",
       "      <td>homem</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>738</th>\n",
       "      <td>NaN</td>\n",
       "      <td>homem</td>\n",
       "      <td>3</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>739</th>\n",
       "      <td>NaN</td>\n",
       "      <td>homem</td>\n",
       "      <td>3</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>740</th>\n",
       "      <td>NaN</td>\n",
       "      <td>homem</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>760</th>\n",
       "      <td>NaN</td>\n",
       "      <td>homem</td>\n",
       "      <td>3</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>766</th>\n",
       "      <td>NaN</td>\n",
       "      <td>homem</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>768</th>\n",
       "      <td>NaN</td>\n",
       "      <td>homem</td>\n",
       "      <td>3</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>773</th>\n",
       "      <td>NaN</td>\n",
       "      <td>homem</td>\n",
       "      <td>3</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>776</th>\n",
       "      <td>NaN</td>\n",
       "      <td>homem</td>\n",
       "      <td>3</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>778</th>\n",
       "      <td>NaN</td>\n",
       "      <td>homem</td>\n",
       "      <td>3</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>783</th>\n",
       "      <td>NaN</td>\n",
       "      <td>homem</td>\n",
       "      <td>3</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>790</th>\n",
       "      <td>NaN</td>\n",
       "      <td>homem</td>\n",
       "      <td>3</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>792</th>\n",
       "      <td>NaN</td>\n",
       "      <td>mulher</td>\n",
       "      <td>3</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>793</th>\n",
       "      <td>NaN</td>\n",
       "      <td>homem</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>815</th>\n",
       "      <td>NaN</td>\n",
       "      <td>homem</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>825</th>\n",
       "      <td>NaN</td>\n",
       "      <td>homem</td>\n",
       "      <td>3</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>826</th>\n",
       "      <td>NaN</td>\n",
       "      <td>homem</td>\n",
       "      <td>3</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>828</th>\n",
       "      <td>NaN</td>\n",
       "      <td>homem</td>\n",
       "      <td>3</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>832</th>\n",
       "      <td>NaN</td>\n",
       "      <td>homem</td>\n",
       "      <td>3</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>837</th>\n",
       "      <td>NaN</td>\n",
       "      <td>homem</td>\n",
       "      <td>3</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>839</th>\n",
       "      <td>NaN</td>\n",
       "      <td>homem</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>846</th>\n",
       "      <td>NaN</td>\n",
       "      <td>homem</td>\n",
       "      <td>3</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>849</th>\n",
       "      <td>NaN</td>\n",
       "      <td>mulher</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>859</th>\n",
       "      <td>NaN</td>\n",
       "      <td>homem</td>\n",
       "      <td>3</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>863</th>\n",
       "      <td>NaN</td>\n",
       "      <td>mulher</td>\n",
       "      <td>3</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>868</th>\n",
       "      <td>NaN</td>\n",
       "      <td>homem</td>\n",
       "      <td>3</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>878</th>\n",
       "      <td>NaN</td>\n",
       "      <td>homem</td>\n",
       "      <td>3</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>888</th>\n",
       "      <td>NaN</td>\n",
       "      <td>mulher</td>\n",
       "      <td>3</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>891 rows × 4 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "     Idade    Sexo  Classe  Sobreviveu\n",
       "803   0.42   homem       3           1\n",
       "755   0.67   homem       2           1\n",
       "644   0.75  mulher       3           1\n",
       "469   0.75  mulher       3           1\n",
       "78    0.83   homem       2           1\n",
       "831   0.83   homem       2           1\n",
       "305   0.92   homem       1           1\n",
       "827   1.00   homem       2           1\n",
       "381   1.00  mulher       3           1\n",
       "164   1.00   homem       3           0\n",
       "183   1.00   homem       2           1\n",
       "386   1.00   homem       3           0\n",
       "172   1.00  mulher       3           1\n",
       "788   1.00   homem       3           1\n",
       "642   2.00  mulher       3           0\n",
       "7     2.00   homem       3           0\n",
       "530   2.00  mulher       2           1\n",
       "297   2.00  mulher       1           0\n",
       "824   2.00   homem       3           0\n",
       "205   2.00  mulher       3           0\n",
       "119   2.00  mulher       3           0\n",
       "340   2.00   homem       2           1\n",
       "479   2.00  mulher       3           1\n",
       "16    2.00   homem       3           0\n",
       "348   3.00   homem       3           1\n",
       "407   3.00   homem       2           1\n",
       "374   3.00  mulher       3           0\n",
       "261   3.00   homem       3           1\n",
       "43    3.00  mulher       2           1\n",
       "193   3.00   homem       2           1\n",
       "..     ...     ...     ...         ...\n",
       "718    NaN   homem       3           0\n",
       "727    NaN  mulher       3           1\n",
       "732    NaN   homem       2           0\n",
       "738    NaN   homem       3           0\n",
       "739    NaN   homem       3           0\n",
       "740    NaN   homem       1           1\n",
       "760    NaN   homem       3           0\n",
       "766    NaN   homem       1           0\n",
       "768    NaN   homem       3           0\n",
       "773    NaN   homem       3           0\n",
       "776    NaN   homem       3           0\n",
       "778    NaN   homem       3           0\n",
       "783    NaN   homem       3           0\n",
       "790    NaN   homem       3           0\n",
       "792    NaN  mulher       3           0\n",
       "793    NaN   homem       1           0\n",
       "815    NaN   homem       1           0\n",
       "825    NaN   homem       3           0\n",
       "826    NaN   homem       3           0\n",
       "828    NaN   homem       3           1\n",
       "832    NaN   homem       3           0\n",
       "837    NaN   homem       3           0\n",
       "839    NaN   homem       1           1\n",
       "846    NaN   homem       3           0\n",
       "849    NaN  mulher       1           1\n",
       "859    NaN   homem       3           0\n",
       "863    NaN  mulher       3           0\n",
       "868    NaN   homem       3           0\n",
       "878    NaN   homem       3           0\n",
       "888    NaN  mulher       3           0\n",
       "\n",
       "[891 rows x 4 columns]"
      ]
     },
     "execution_count": 34,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data[['Idade','Sexo','Classe','Sobreviveu']].sort_values('Idade', ascending=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "IdPassageiro       0\n",
       "Sobreviveu         0\n",
       "Classe             0\n",
       "Nome               0\n",
       "Sexo               0\n",
       "Idade            177\n",
       "IrmaosConjuge      0\n",
       "PaisFilhos         0\n",
       "Bilhete            0\n",
       "Tarifa             0\n",
       "Cabine           687\n",
       "Embarque           2\n",
       "dtype: int64"
      ]
     },
     "execution_count": 35,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data.isnull().sum()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>IdPassageiro</th>\n",
       "      <th>Sobreviveu</th>\n",
       "      <th>Classe</th>\n",
       "      <th>Nome</th>\n",
       "      <th>Sexo</th>\n",
       "      <th>Idade</th>\n",
       "      <th>IrmaosConjuge</th>\n",
       "      <th>PaisFilhos</th>\n",
       "      <th>Bilhete</th>\n",
       "      <th>Tarifa</th>\n",
       "      <th>Cabine</th>\n",
       "      <th>Embarque</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>61</th>\n",
       "      <td>62</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>Icard, Miss. Amelie</td>\n",
       "      <td>mulher</td>\n",
       "      <td>38.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>113572</td>\n",
       "      <td>80.0</td>\n",
       "      <td>B28</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>829</th>\n",
       "      <td>830</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>Stone, Mrs. George Nelson (Martha Evelyn)</td>\n",
       "      <td>mulher</td>\n",
       "      <td>62.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>113572</td>\n",
       "      <td>80.0</td>\n",
       "      <td>B28</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "     IdPassageiro  Sobreviveu  Classe  \\\n",
       "61             62           1       1   \n",
       "829           830           1       1   \n",
       "\n",
       "                                          Nome    Sexo  Idade  IrmaosConjuge  \\\n",
       "61                         Icard, Miss. Amelie  mulher   38.0              0   \n",
       "829  Stone, Mrs. George Nelson (Martha Evelyn)  mulher   62.0              0   \n",
       "\n",
       "     PaisFilhos Bilhete  Tarifa Cabine Embarque  \n",
       "61            0  113572    80.0    B28      NaN  \n",
       "829           0  113572    80.0    B28      NaN  "
      ]
     },
     "execution_count": 36,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data.loc[data['Embarque'].isnull()]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array(['S', 'C', 'Q', nan], dtype=object)"
      ]
     },
     "execution_count": 37,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data['Embarque'].unique()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0    S\n",
       "dtype: object"
      ]
     },
     "execution_count": 38,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data['Embarque'].mode()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "metadata": {},
   "outputs": [],
   "source": [
    "data['Embarque'].fillna('S',inplace=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "metadata": {},
   "outputs": [],
   "source": [
    "data['Embarque'].at[61] = 'C'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'C'"
      ]
     },
     "execution_count": 41,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data['Embarque'].loc[61]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "metadata": {},
   "outputs": [],
   "source": [
    "data.drop('Cabine',axis=1, inplace=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0       484.0\n",
       "1      1444.0\n",
       "2       676.0\n",
       "3      1225.0\n",
       "4      1225.0\n",
       "5         NaN\n",
       "6      2916.0\n",
       "7         4.0\n",
       "8       729.0\n",
       "9       196.0\n",
       "10       16.0\n",
       "11     3364.0\n",
       "12      400.0\n",
       "13     1521.0\n",
       "14      196.0\n",
       "15     3025.0\n",
       "16        4.0\n",
       "17        NaN\n",
       "18      961.0\n",
       "19        NaN\n",
       "20     1225.0\n",
       "21     1156.0\n",
       "22      225.0\n",
       "23      784.0\n",
       "24       64.0\n",
       "25     1444.0\n",
       "26        NaN\n",
       "27      361.0\n",
       "28        NaN\n",
       "29        NaN\n",
       "        ...  \n",
       "861     441.0\n",
       "862    2304.0\n",
       "863       NaN\n",
       "864     576.0\n",
       "865    1764.0\n",
       "866     729.0\n",
       "867     961.0\n",
       "868       NaN\n",
       "869      16.0\n",
       "870     676.0\n",
       "871    2209.0\n",
       "872    1089.0\n",
       "873    2209.0\n",
       "874     784.0\n",
       "875     225.0\n",
       "876     400.0\n",
       "877     361.0\n",
       "878       NaN\n",
       "879    3136.0\n",
       "880     625.0\n",
       "881    1089.0\n",
       "882     484.0\n",
       "883     784.0\n",
       "884     625.0\n",
       "885    1521.0\n",
       "886     729.0\n",
       "887     361.0\n",
       "888       NaN\n",
       "889     676.0\n",
       "890    1024.0\n",
       "Name: Idade, Length: 891, dtype: float64"
      ]
     },
     "execution_count": 43,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data['Idade'].apply(lambda x: x**2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "metadata": {},
   "outputs": [],
   "source": [
    "#Funçao para remover ultimo digito da coluna Bilhete\n",
    "data['Bilhete'] = data['Bilhete'].apply(lambda x: x[:-1])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "metadata": {
    "scrolled": true
   },
   "outputs": [],
   "source": [
    "#Transformando sexo em bool com variavel dummy\n",
    "data = pd.get_dummies(data,columns=['Sexo'], drop_first=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "metadata": {},
   "outputs": [],
   "source": [
    "embarque = pd.get_dummies(data,columns=['Embarque'], drop_first=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Embarque_Q</th>\n",
       "      <th>Embarque_S</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   Embarque_Q  Embarque_S\n",
       "0           0           1\n",
       "1           0           0\n",
       "2           0           1\n",
       "3           0           1\n",
       "4           0           1"
      ]
     },
     "execution_count": 47,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "embarque[['Embarque_Q','Embarque_S']].head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 48,
   "metadata": {},
   "outputs": [],
   "source": [
    "embarque = pd.get_dummies(data['Embarque'], drop_first=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 49,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Q</th>\n",
       "      <th>S</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   Q  S\n",
       "0  0  1\n",
       "1  0  0\n",
       "2  0  1\n",
       "3  0  1\n",
       "4  0  1"
      ]
     },
     "execution_count": 49,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "embarque.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 50,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "((891, 11), (891, 2))"
      ]
     },
     "execution_count": 50,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data.shape, embarque.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 51,
   "metadata": {},
   "outputs": [],
   "source": [
    "data = pd.concat([data,embarque],axis=1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 52,
   "metadata": {},
   "outputs": [],
   "source": [
    "data.drop(columns='Embarque', axis=1, inplace=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 53,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>IdPassageiro</th>\n",
       "      <th>Sobreviveu</th>\n",
       "      <th>Classe</th>\n",
       "      <th>Nome</th>\n",
       "      <th>Idade</th>\n",
       "      <th>IrmaosConjuge</th>\n",
       "      <th>PaisFilhos</th>\n",
       "      <th>Bilhete</th>\n",
       "      <th>Tarifa</th>\n",
       "      <th>Sexo_mulher</th>\n",
       "      <th>Q</th>\n",
       "      <th>S</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>22.0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>A/5 2117</td>\n",
       "      <td>7.2500</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>Cumings, Mrs. John Bradley (Florence Briggs Th...</td>\n",
       "      <td>38.0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>PC 1759</td>\n",
       "      <td>71.2833</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>3</td>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "      <td>Heikkinen, Miss. Laina</td>\n",
       "      <td>26.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>STON/O2. 310128</td>\n",
       "      <td>7.9250</td>\n",
       "      <td>1</td>\n",
       "      <td>0</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>35.0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>11380</td>\n",
       "      <td>53.1000</td>\n",
       "      <td>1</td>\n",
       "      <td>0</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>35.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>37345</td>\n",
       "      <td>8.0500</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   IdPassageiro  Sobreviveu  Classe  \\\n",
       "0             1           0       3   \n",
       "1             2           1       1   \n",
       "2             3           1       3   \n",
       "3             4           1       1   \n",
       "4             5           0       3   \n",
       "\n",
       "                                                Nome  Idade  IrmaosConjuge  \\\n",
       "0                            Braund, Mr. Owen Harris   22.0              1   \n",
       "1  Cumings, Mrs. John Bradley (Florence Briggs Th...   38.0              1   \n",
       "2                             Heikkinen, Miss. Laina   26.0              0   \n",
       "3       Futrelle, Mrs. Jacques Heath (Lily May Peel)   35.0              1   \n",
       "4                           Allen, Mr. William Henry   35.0              0   \n",
       "\n",
       "   PaisFilhos          Bilhete   Tarifa  Sexo_mulher  Q  S  \n",
       "0           0         A/5 2117   7.2500            0  0  1  \n",
       "1           0          PC 1759  71.2833            1  0  0  \n",
       "2           0  STON/O2. 310128   7.9250            1  0  1  \n",
       "3           0            11380  53.1000            1  0  1  \n",
       "4           0            37345   8.0500            0  0  1  "
      ]
     },
     "execution_count": 53,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 54,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0                              Braund, Mr. Owen Harris\n",
       "1    Cumings, Mrs. John Bradley (Florence Briggs Th...\n",
       "2                               Heikkinen, Miss. Laina\n",
       "3         Futrelle, Mrs. Jacques Heath (Lily May Peel)\n",
       "4                             Allen, Mr. William Henry\n",
       "Name: Nome, dtype: object"
      ]
     },
     "execution_count": 54,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data['Nome'].head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 61,
   "metadata": {},
   "outputs": [],
   "source": [
    "data['Titulo'] = data['Nome'].str.extract('(\\w+)\\.')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 63,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>IdPassageiro</th>\n",
       "      <th>Sobreviveu</th>\n",
       "      <th>Classe</th>\n",
       "      <th>Nome</th>\n",
       "      <th>Idade</th>\n",
       "      <th>IrmaosConjuge</th>\n",
       "      <th>PaisFilhos</th>\n",
       "      <th>Bilhete</th>\n",
       "      <th>Tarifa</th>\n",
       "      <th>Sexo_mulher</th>\n",
       "      <th>Q</th>\n",
       "      <th>S</th>\n",
       "      <th>Titulo</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>22.0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>A/5 2117</td>\n",
       "      <td>7.2500</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>Mr</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>Cumings, Mrs. John Bradley (Florence Briggs Th...</td>\n",
       "      <td>38.0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>PC 1759</td>\n",
       "      <td>71.2833</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>Mrs</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>3</td>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "      <td>Heikkinen, Miss. Laina</td>\n",
       "      <td>26.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>STON/O2. 310128</td>\n",
       "      <td>7.9250</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>Miss</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>35.0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>11380</td>\n",
       "      <td>53.1000</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>Mrs</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>35.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>37345</td>\n",
       "      <td>8.0500</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>Mr</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   IdPassageiro  Sobreviveu  Classe  \\\n",
       "0             1           0       3   \n",
       "1             2           1       1   \n",
       "2             3           1       3   \n",
       "3             4           1       1   \n",
       "4             5           0       3   \n",
       "\n",
       "                                                Nome  Idade  IrmaosConjuge  \\\n",
       "0                            Braund, Mr. Owen Harris   22.0              1   \n",
       "1  Cumings, Mrs. John Bradley (Florence Briggs Th...   38.0              1   \n",
       "2                             Heikkinen, Miss. Laina   26.0              0   \n",
       "3       Futrelle, Mrs. Jacques Heath (Lily May Peel)   35.0              1   \n",
       "4                           Allen, Mr. William Henry   35.0              0   \n",
       "\n",
       "   PaisFilhos          Bilhete   Tarifa  Sexo_mulher  Q  S Titulo  \n",
       "0           0         A/5 2117   7.2500            0  0  1     Mr  \n",
       "1           0          PC 1759  71.2833            1  0  0    Mrs  \n",
       "2           0  STON/O2. 310128   7.9250            1  0  1   Miss  \n",
       "3           0            11380  53.1000            1  0  1    Mrs  \n",
       "4           0            37345   8.0500            0  0  1     Mr  "
      ]
     },
     "execution_count": 63,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 66,
   "metadata": {},
   "outputs": [],
   "source": [
    "data['Sexo'] = data['Sexo_mulher'].map({0: 'homem', 1:'mulher'})"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 68,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th>Sexo</th>\n",
       "      <th>homem</th>\n",
       "      <th>mulher</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Titulo</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>Capt</th>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Col</th>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Countess</th>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Don</th>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Dr</th>\n",
       "      <td>6</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Jonkheer</th>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Lady</th>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Major</th>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Master</th>\n",
       "      <td>40</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Miss</th>\n",
       "      <td>0</td>\n",
       "      <td>182</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Mlle</th>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Mme</th>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Mr</th>\n",
       "      <td>517</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Mrs</th>\n",
       "      <td>0</td>\n",
       "      <td>125</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Ms</th>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Rev</th>\n",
       "      <td>6</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Sir</th>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "Sexo      homem  mulher\n",
       "Titulo                 \n",
       "Capt          1       0\n",
       "Col           2       0\n",
       "Countess      0       1\n",
       "Don           1       0\n",
       "Dr            6       1\n",
       "Jonkheer      1       0\n",
       "Lady          0       1\n",
       "Major         2       0\n",
       "Master       40       0\n",
       "Miss          0     182\n",
       "Mlle          0       2\n",
       "Mme           0       1\n",
       "Mr          517       0\n",
       "Mrs           0     125\n",
       "Ms            0       1\n",
       "Rev           6       0\n",
       "Sir           1       0"
      ]
     },
     "execution_count": 68,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pd.crosstab(data['Titulo'], data['Sexo'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 88,
   "metadata": {},
   "outputs": [],
   "source": [
    "#data['Titulo'] = data['Titulo'].apply(lambda x: x if x in ['Master', \\\n",
    "#                                                        'Miss', \\\n",
    "#                                                        'Mr', \\\n",
    "#                                                        'Mrs'] else 'Outros')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 94,
   "metadata": {},
   "outputs": [],
   "source": [
    "data['Titulo'] = data['Titulo'].apply(lambda x: 'Outros' if x not in ['Master', \\\n",
    "                                                        'Miss', \\\n",
    "                                                        'Mr', \\\n",
    "                                                        'Mrs'] else x)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 95,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th>Sexo</th>\n",
       "      <th>homem</th>\n",
       "      <th>mulher</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Titulo</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>Master</th>\n",
       "      <td>40</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Miss</th>\n",
       "      <td>0</td>\n",
       "      <td>182</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Mr</th>\n",
       "      <td>517</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Mrs</th>\n",
       "      <td>0</td>\n",
       "      <td>125</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Outros</th>\n",
       "      <td>20</td>\n",
       "      <td>7</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "Sexo    homem  mulher\n",
       "Titulo               \n",
       "Master     40       0\n",
       "Miss        0     182\n",
       "Mr        517       0\n",
       "Mrs         0     125\n",
       "Outros     20       7"
      ]
     },
     "execution_count": 95,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pd.crosstab(data['Titulo'], data['Sexo'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 91,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Titulo</th>\n",
       "      <th>Sexo</th>\n",
       "      <th>Idade</th>\n",
       "      <th>Classe</th>\n",
       "      <th>Sobreviveu</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>Master</td>\n",
       "      <td>homem</td>\n",
       "      <td>2.00</td>\n",
       "      <td>3</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>Master</td>\n",
       "      <td>homem</td>\n",
       "      <td>2.00</td>\n",
       "      <td>3</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50</th>\n",
       "      <td>Master</td>\n",
       "      <td>homem</td>\n",
       "      <td>7.00</td>\n",
       "      <td>3</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>59</th>\n",
       "      <td>Master</td>\n",
       "      <td>homem</td>\n",
       "      <td>11.00</td>\n",
       "      <td>3</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>63</th>\n",
       "      <td>Master</td>\n",
       "      <td>homem</td>\n",
       "      <td>4.00</td>\n",
       "      <td>3</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>65</th>\n",
       "      <td>Master</td>\n",
       "      <td>homem</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>78</th>\n",
       "      <td>Master</td>\n",
       "      <td>homem</td>\n",
       "      <td>0.83</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>125</th>\n",
       "      <td>Master</td>\n",
       "      <td>homem</td>\n",
       "      <td>12.00</td>\n",
       "      <td>3</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>159</th>\n",
       "      <td>Master</td>\n",
       "      <td>homem</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>164</th>\n",
       "      <td>Master</td>\n",
       "      <td>homem</td>\n",
       "      <td>1.00</td>\n",
       "      <td>3</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>165</th>\n",
       "      <td>Master</td>\n",
       "      <td>homem</td>\n",
       "      <td>9.00</td>\n",
       "      <td>3</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>171</th>\n",
       "      <td>Master</td>\n",
       "      <td>homem</td>\n",
       "      <td>4.00</td>\n",
       "      <td>3</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>176</th>\n",
       "      <td>Master</td>\n",
       "      <td>homem</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>182</th>\n",
       "      <td>Master</td>\n",
       "      <td>homem</td>\n",
       "      <td>9.00</td>\n",
       "      <td>3</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>183</th>\n",
       "      <td>Master</td>\n",
       "      <td>homem</td>\n",
       "      <td>1.00</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>193</th>\n",
       "      <td>Master</td>\n",
       "      <td>homem</td>\n",
       "      <td>3.00</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>261</th>\n",
       "      <td>Master</td>\n",
       "      <td>homem</td>\n",
       "      <td>3.00</td>\n",
       "      <td>3</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>278</th>\n",
       "      <td>Master</td>\n",
       "      <td>homem</td>\n",
       "      <td>7.00</td>\n",
       "      <td>3</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>305</th>\n",
       "      <td>Master</td>\n",
       "      <td>homem</td>\n",
       "      <td>0.92</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>340</th>\n",
       "      <td>Master</td>\n",
       "      <td>homem</td>\n",
       "      <td>2.00</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>348</th>\n",
       "      <td>Master</td>\n",
       "      <td>homem</td>\n",
       "      <td>3.00</td>\n",
       "      <td>3</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>386</th>\n",
       "      <td>Master</td>\n",
       "      <td>homem</td>\n",
       "      <td>1.00</td>\n",
       "      <td>3</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>407</th>\n",
       "      <td>Master</td>\n",
       "      <td>homem</td>\n",
       "      <td>3.00</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>445</th>\n",
       "      <td>Master</td>\n",
       "      <td>homem</td>\n",
       "      <td>4.00</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>480</th>\n",
       "      <td>Master</td>\n",
       "      <td>homem</td>\n",
       "      <td>9.00</td>\n",
       "      <td>3</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>489</th>\n",
       "      <td>Master</td>\n",
       "      <td>homem</td>\n",
       "      <td>9.00</td>\n",
       "      <td>3</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>549</th>\n",
       "      <td>Master</td>\n",
       "      <td>homem</td>\n",
       "      <td>8.00</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>709</th>\n",
       "      <td>Master</td>\n",
       "      <td>homem</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>751</th>\n",
       "      <td>Master</td>\n",
       "      <td>homem</td>\n",
       "      <td>6.00</td>\n",
       "      <td>3</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>755</th>\n",
       "      <td>Master</td>\n",
       "      <td>homem</td>\n",
       "      <td>0.67</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>787</th>\n",
       "      <td>Master</td>\n",
       "      <td>homem</td>\n",
       "      <td>8.00</td>\n",
       "      <td>3</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>788</th>\n",
       "      <td>Master</td>\n",
       "      <td>homem</td>\n",
       "      <td>1.00</td>\n",
       "      <td>3</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>802</th>\n",
       "      <td>Master</td>\n",
       "      <td>homem</td>\n",
       "      <td>11.00</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>803</th>\n",
       "      <td>Master</td>\n",
       "      <td>homem</td>\n",
       "      <td>0.42</td>\n",
       "      <td>3</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>819</th>\n",
       "      <td>Master</td>\n",
       "      <td>homem</td>\n",
       "      <td>10.00</td>\n",
       "      <td>3</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>824</th>\n",
       "      <td>Master</td>\n",
       "      <td>homem</td>\n",
       "      <td>2.00</td>\n",
       "      <td>3</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>827</th>\n",
       "      <td>Master</td>\n",
       "      <td>homem</td>\n",
       "      <td>1.00</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>831</th>\n",
       "      <td>Master</td>\n",
       "      <td>homem</td>\n",
       "      <td>0.83</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>850</th>\n",
       "      <td>Master</td>\n",
       "      <td>homem</td>\n",
       "      <td>4.00</td>\n",
       "      <td>3</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>869</th>\n",
       "      <td>Master</td>\n",
       "      <td>homem</td>\n",
       "      <td>4.00</td>\n",
       "      <td>3</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "     Titulo   Sexo  Idade  Classe  Sobreviveu\n",
       "7    Master  homem   2.00       3           0\n",
       "16   Master  homem   2.00       3           0\n",
       "50   Master  homem   7.00       3           0\n",
       "59   Master  homem  11.00       3           0\n",
       "63   Master  homem   4.00       3           0\n",
       "65   Master  homem    NaN       3           1\n",
       "78   Master  homem   0.83       2           1\n",
       "125  Master  homem  12.00       3           1\n",
       "159  Master  homem    NaN       3           0\n",
       "164  Master  homem   1.00       3           0\n",
       "165  Master  homem   9.00       3           1\n",
       "171  Master  homem   4.00       3           0\n",
       "176  Master  homem    NaN       3           0\n",
       "182  Master  homem   9.00       3           0\n",
       "183  Master  homem   1.00       2           1\n",
       "193  Master  homem   3.00       2           1\n",
       "261  Master  homem   3.00       3           1\n",
       "278  Master  homem   7.00       3           0\n",
       "305  Master  homem   0.92       1           1\n",
       "340  Master  homem   2.00       2           1\n",
       "348  Master  homem   3.00       3           1\n",
       "386  Master  homem   1.00       3           0\n",
       "407  Master  homem   3.00       2           1\n",
       "445  Master  homem   4.00       1           1\n",
       "480  Master  homem   9.00       3           0\n",
       "489  Master  homem   9.00       3           1\n",
       "549  Master  homem   8.00       2           1\n",
       "709  Master  homem    NaN       3           1\n",
       "751  Master  homem   6.00       3           1\n",
       "755  Master  homem   0.67       2           1\n",
       "787  Master  homem   8.00       3           0\n",
       "788  Master  homem   1.00       3           1\n",
       "802  Master  homem  11.00       1           1\n",
       "803  Master  homem   0.42       3           1\n",
       "819  Master  homem  10.00       3           0\n",
       "824  Master  homem   2.00       3           0\n",
       "827  Master  homem   1.00       2           1\n",
       "831  Master  homem   0.83       2           1\n",
       "850  Master  homem   4.00       3           0\n",
       "869  Master  homem   4.00       3           1"
      ]
     },
     "execution_count": 91,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data[['Titulo', 'Sexo', 'Idade', 'Classe', 'Sobreviveu']].loc[data['Titulo'] == 'Master']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 96,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Titulo        Master\n",
       "Sexo           homem\n",
       "Idade             12\n",
       "Classe             3\n",
       "Sobreviveu         1\n",
       "dtype: object"
      ]
     },
     "execution_count": 96,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data[['Titulo', 'Sexo', 'Idade', 'Classe', 'Sobreviveu']].loc[data['Titulo'] == 'Master'].max()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 113,
   "metadata": {},
   "outputs": [],
   "source": [
    "cabine = pd.read_csv(r'titanic/train.csv')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 114,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0     NaN\n",
       "1     C85\n",
       "2     NaN\n",
       "3    C123\n",
       "4     NaN\n",
       "Name: Cabin, dtype: object"
      ]
     },
     "execution_count": 114,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "cabine['Cabin'].head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 115,
   "metadata": {},
   "outputs": [],
   "source": [
    "for idx, _ in cabine[['Cabin']].dropna().iterrows():\n",
    "    cabine['Cabin'].at[idx] = cabine['Cabin'].at[idx][0]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 117,
   "metadata": {},
   "outputs": [],
   "source": [
    "cabine = cabine.dropna(subset=['Cabin'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 130,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th>Survived</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Cabin</th>\n",
       "      <th>Sex</th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th rowspan=\"2\" valign=\"top\">A</th>\n",
       "      <th>female</th>\n",
       "      <td>1.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>male</th>\n",
       "      <td>0.428571</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"2\" valign=\"top\">B</th>\n",
       "      <th>female</th>\n",
       "      <td>1.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>male</th>\n",
       "      <td>0.400000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"2\" valign=\"top\">C</th>\n",
       "      <th>female</th>\n",
       "      <td>0.888889</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>male</th>\n",
       "      <td>0.343750</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"2\" valign=\"top\">D</th>\n",
       "      <th>female</th>\n",
       "      <td>1.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>male</th>\n",
       "      <td>0.466667</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"2\" valign=\"top\">E</th>\n",
       "      <th>female</th>\n",
       "      <td>0.933333</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>male</th>\n",
       "      <td>0.588235</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"2\" valign=\"top\">F</th>\n",
       "      <th>female</th>\n",
       "      <td>1.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>male</th>\n",
       "      <td>0.375000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>G</th>\n",
       "      <th>female</th>\n",
       "      <td>0.500000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>T</th>\n",
       "      <th>male</th>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "              Survived\n",
       "Cabin Sex             \n",
       "A     female  1.000000\n",
       "      male    0.428571\n",
       "B     female  1.000000\n",
       "      male    0.400000\n",
       "C     female  0.888889\n",
       "      male    0.343750\n",
       "D     female  1.000000\n",
       "      male    0.466667\n",
       "E     female  0.933333\n",
       "      male    0.588235\n",
       "F     female  1.000000\n",
       "      male    0.375000\n",
       "G     female  0.500000\n",
       "T     male    0.000000"
      ]
     },
     "execution_count": 130,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "cabine[['Cabin', 'Survived', 'Sex']].groupby(['Cabin', 'Sex']).mean()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 131,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>PassengerId</th>\n",
       "      <th>Survived</th>\n",
       "      <th>Pclass</th>\n",
       "      <th>Name</th>\n",
       "      <th>Sex</th>\n",
       "      <th>Age</th>\n",
       "      <th>SibSp</th>\n",
       "      <th>Parch</th>\n",
       "      <th>Ticket</th>\n",
       "      <th>Fare</th>\n",
       "      <th>Cabin</th>\n",
       "      <th>Embarked</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>339</th>\n",
       "      <td>340</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>Blackwell, Mr. Stephen Weart</td>\n",
       "      <td>male</td>\n",
       "      <td>45.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>113784</td>\n",
       "      <td>35.5</td>\n",
       "      <td>T</td>\n",
       "      <td>S</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "     PassengerId  Survived  Pclass                          Name   Sex   Age  \\\n",
       "339          340         0       1  Blackwell, Mr. Stephen Weart  male  45.0   \n",
       "\n",
       "     SibSp  Parch  Ticket  Fare Cabin Embarked  \n",
       "339      0      0  113784  35.5     T        S  "
      ]
     },
     "execution_count": 131,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "cabine.loc[cabine['Cabin'] == 'T']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.7.4"
  },
  "widgets": {
   "application/vnd.jupyter.widget-state+json": {
    "state": {},
    "version_major": 2,
    "version_minor": 0
   }
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}