{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Ejercicio misceláneo: Análisis exploratorio y Feature Engineering"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 76,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import numpy as np\n",
    "import os\n",
    "from scipy import stats"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "scrolled": true
   },
   "outputs": [],
   "source": [
    "ruta_archivo = os.path.join(\"titanic\", \"train.csv\")\n",
    "df = pd.read_csv(os.path.join(\"titanic\", \"train.csv\"), index_col='PassengerId')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>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",
       "    <tr>\n",
       "      <th>PassengerId</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
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       "      <th>1</th>\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>2</th>\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",
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       "    <tr>\n",
       "      <th>3</th>\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",
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       "      <td>S</td>\n",
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       "    <tr>\n",
       "      <th>4</th>\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",
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       "      <td>53.1000</td>\n",
       "      <td>C123</td>\n",
       "      <td>S</td>\n",
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       "    <tr>\n",
       "      <th>5</th>\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": [
       "             Survived  Pclass  \\\n",
       "PassengerId                     \n",
       "1                   0       3   \n",
       "2                   1       1   \n",
       "3                   1       3   \n",
       "4                   1       1   \n",
       "5                   0       3   \n",
       "\n",
       "                                                          Name     Sex   Age  \\\n",
       "PassengerId                                                                    \n",
       "1                                      Braund, Mr. Owen Harris    male  22.0   \n",
       "2            Cumings, Mrs. John Bradley (Florence Briggs Th...  female  38.0   \n",
       "3                                       Heikkinen, Miss. Laina  female  26.0   \n",
       "4                 Futrelle, Mrs. Jacques Heath (Lily May Peel)  female  35.0   \n",
       "5                                     Allen, Mr. William Henry    male  35.0   \n",
       "\n",
       "             SibSp  Parch            Ticket     Fare Cabin Embarked  \n",
       "PassengerId                                                          \n",
       "1                1      0         A/5 21171   7.2500   NaN        S  \n",
       "2                1      0          PC 17599  71.2833   C85        C  \n",
       "3                0      0  STON/O2. 3101282   7.9250   NaN        S  \n",
       "4                1      0            113803  53.1000  C123        S  \n",
       "5                0      0            373450   8.0500   NaN        S  "
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 1. Elimine las variables/columnas 'Ticket' y 'Cabin'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "      <td>Heikkinen, Miss. Laina</td>\n",
       "      <td>female</td>\n",
       "      <td>26.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
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       "      <td>S</td>\n",
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       "    <tr>\n",
       "      <th>4</th>\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",
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       "      <th>5</th>\n",
       "      <td>0</td>\n",
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       "      <td>male</td>\n",
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      "text/plain": [
       "             Survived  Pclass  \\\n",
       "PassengerId                     \n",
       "1                   0       3   \n",
       "2                   1       1   \n",
       "3                   1       3   \n",
       "4                   1       1   \n",
       "5                   0       3   \n",
       "\n",
       "                                                          Name     Sex   Age  \\\n",
       "PassengerId                                                                    \n",
       "1                                      Braund, Mr. Owen Harris    male  22.0   \n",
       "2            Cumings, Mrs. John Bradley (Florence Briggs Th...  female  38.0   \n",
       "3                                       Heikkinen, Miss. Laina  female  26.0   \n",
       "4                 Futrelle, Mrs. Jacques Heath (Lily May Peel)  female  35.0   \n",
       "5                                     Allen, Mr. William Henry    male  35.0   \n",
       "\n",
       "             SibSp  Parch     Fare Embarked  \n",
       "PassengerId                                  \n",
       "1                1      0   7.2500        S  \n",
       "2                1      0  71.2833        C  \n",
       "3                0      0   7.9250        S  \n",
       "4                1      0  53.1000        S  \n",
       "5                0      0   8.0500        S  "
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.drop(columns=['Cabin'], inplace=True)\n",
    "df.drop(columns=['Ticket'], inplace=True)\n",
    "df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "      <td>892.000000</td>\n",
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       "      <td>Jonsson, Mr. Carl</td>\n",
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       "      <td>NaN</td>\n",
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       "      <th>50%</th>\n",
       "      <td>0.000000</td>\n",
       "      <td>3.000000</td>\n",
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       "      <td>NaN</td>\n",
       "      <td>28.000000</td>\n",
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       "      <td>0.000000</td>\n",
       "      <td>14.454200</td>\n",
       "      <td>NaN</td>\n",
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       "      <th>75%</th>\n",
       "      <td>1.000000</td>\n",
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       "      <td>NaN</td>\n",
       "      <td>38.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>31.000000</td>\n",
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       "      <th>max</th>\n",
       "      <td>1.000000</td>\n",
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       "      <td>NaN</td>\n",
       "      <td>80.000000</td>\n",
       "      <td>8.000000</td>\n",
       "      <td>6.000000</td>\n",
       "      <td>512.329200</td>\n",
       "      <td>NaN</td>\n",
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      ],
      "text/plain": [
       "          Survived      Pclass               Name   Sex         Age  \\\n",
       "count   892.000000  892.000000                892   892  715.000000   \n",
       "unique         NaN         NaN                892     2         NaN   \n",
       "top            NaN         NaN  Jonsson, Mr. Carl  male         NaN   \n",
       "freq           NaN         NaN                  1   578         NaN   \n",
       "mean      0.383408    2.309417                NaN   NaN   29.742196   \n",
       "std       0.486489    0.835923                NaN   NaN   14.561951   \n",
       "min       0.000000    1.000000                NaN   NaN    0.420000   \n",
       "25%       0.000000    2.000000                NaN   NaN   20.250000   \n",
       "50%       0.000000    3.000000                NaN   NaN   28.000000   \n",
       "75%       1.000000    3.000000                NaN   NaN   38.000000   \n",
       "max       1.000000    3.000000                NaN   NaN   80.000000   \n",
       "\n",
       "             SibSp       Parch        Fare Embarked  \n",
       "count   892.000000  892.000000  891.000000      890  \n",
       "unique         NaN         NaN         NaN        3  \n",
       "top            NaN         NaN         NaN        S  \n",
       "freq           NaN         NaN         NaN      645  \n",
       "mean      0.522422    0.381166   32.204208      NaN  \n",
       "std       1.102264    0.805706   49.693429      NaN  \n",
       "min       0.000000    0.000000    0.000000      NaN  \n",
       "25%       0.000000    0.000000    7.910400      NaN  \n",
       "50%       0.000000    0.000000   14.454200      NaN  \n",
       "75%       1.000000    0.000000   31.000000      NaN  \n",
       "max       8.000000    6.000000  512.329200      NaN  "
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.describe(include='all')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 2. Encuentre los mejores valores para completar la variable 'Embarked' para los  pasajeros con datos faltantes"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 93,
   "metadata": {},
   "outputs": [
    {
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       "      <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",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "Empty DataFrame\n",
       "Columns: [Survived, Pclass, Name, Sex, Age, SibSp, Parch, Fare, Embarked, Title, IsMother]\n",
       "Index: []"
      ]
     },
     "execution_count": 93,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df[df.Embarked.isnull()]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "S    645\n",
       "C    168\n",
       "Q     77\n",
       "Name: Embarked, dtype: int64"
      ]
     },
     "execution_count": 46,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#Tome en cuenta que simplemente emplear el valor que más aparece casi nunca es la mejor alternativa\n",
    "#Para obtener mejores resultados deberá apoyarse en los resultados de un análisis exploratorio de datos\n",
    "#aplicado a las variable(s) que puedan estar relacionadas con 'Embarked'\n",
    "df['Embarked'].value_counts()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 91,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Pclass  Sex   \n",
       "1       female    S\n",
       "        male      S\n",
       "2       female    S\n",
       "        male      S\n",
       "3       female    S\n",
       "        male      S\n",
       "Name: Embarked, dtype: object"
      ]
     },
     "execution_count": 91,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Obtenemos el puerto más común según la clase y el sexo\n",
    "df.groupby(['Pclass', 'Sex'])['Embarked'].agg(pd.Series.mode)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 92,
   "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>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>Fare</th>\n",
       "      <th>Embarked</th>\n",
       "      <th>Title</th>\n",
       "      <th>IsMother</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>PassengerId</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",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "Empty DataFrame\n",
       "Columns: [Survived, Pclass, Name, Sex, Age, SibSp, Parch, Fare, Embarked, Title, IsMother]\n",
       "Index: []"
      ]
     },
     "execution_count": 92,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Como podemos observar, todos los valores que se obtuvieron en la celda de arriba pertenecen al puerto 'S'\n",
    "# Entonces, reemplazaremos los valores NaN por el puerto 'S'\n",
    "df['Embarked'].fillna('S', inplace=True)\n",
    "df[df.Embarked.isnull()]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 3. Complete el código de la siguiente función para extraer el título de cada pasajero"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [],
   "source": [
    "def extractTitle(name):\n",
    "    title_mapping = {'mr' : 'Mr', \n",
    "               'mrs' : 'Mrs', \n",
    "               'miss' : 'Miss', \n",
    "               'master' : 'Master',\n",
    "               'don' : 'Sir',\n",
    "               'rev' : 'Sir',\n",
    "               'dr' : 'Officer',\n",
    "               'mme' : 'Mrs',\n",
    "               'ms' : 'Mrs',\n",
    "               'major' : 'Officer',\n",
    "               'lady' : 'Lady',\n",
    "               'sir' : 'Sir',\n",
    "               'mlle' : 'Miss',\n",
    "               'col' : 'Officer',\n",
    "               'capt' : 'Officer',\n",
    "               'the countess' : 'Lady',\n",
    "               'jonkheer' : 'Sir',\n",
    "               'dona' : 'Lady'\n",
    "                 }\n",
    "    title = name.split(', ')[1].split('.')[0].lower()\n",
    "    return title_mapping[title]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></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>Fare</th>\n",
       "      <th>Embarked</th>\n",
       "      <th>Title</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>PassengerId</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>1</th>\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>7.2500</td>\n",
       "      <td>S</td>\n",
       "      <td>Mr</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\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>71.2833</td>\n",
       "      <td>C</td>\n",
       "      <td>Mrs</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\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>7.9250</td>\n",
       "      <td>S</td>\n",
       "      <td>Miss</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\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>53.1000</td>\n",
       "      <td>S</td>\n",
       "      <td>Mrs</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\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>8.0500</td>\n",
       "      <td>S</td>\n",
       "      <td>Mr</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "             Survived  Pclass  \\\n",
       "PassengerId                     \n",
       "1                   0       3   \n",
       "2                   1       1   \n",
       "3                   1       3   \n",
       "4                   1       1   \n",
       "5                   0       3   \n",
       "\n",
       "                                                          Name     Sex   Age  \\\n",
       "PassengerId                                                                    \n",
       "1                                      Braund, Mr. Owen Harris    male  22.0   \n",
       "2            Cumings, Mrs. John Bradley (Florence Briggs Th...  female  38.0   \n",
       "3                                       Heikkinen, Miss. Laina  female  26.0   \n",
       "4                 Futrelle, Mrs. Jacques Heath (Lily May Peel)  female  35.0   \n",
       "5                                     Allen, Mr. William Henry    male  35.0   \n",
       "\n",
       "             SibSp  Parch     Fare Embarked Title  \n",
       "PassengerId                                        \n",
       "1                1      0   7.2500        S    Mr  \n",
       "2                1      0  71.2833        C   Mrs  \n",
       "3                0      0   7.9250        S  Miss  \n",
       "4                1      0  53.1000        S   Mrs  \n",
       "5                0      0   8.0500        S    Mr  "
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df['Title'] =  df['Name'].map(lambda name : extractTitle(name))\n",
    "df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
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       "\n",
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       "\n",
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>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>Fare</th>\n",
       "      <th>Embarked</th>\n",
       "      <th>Title</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>892.000000</td>\n",
       "      <td>892.000000</td>\n",
       "      <td>892</td>\n",
       "      <td>892</td>\n",
       "      <td>715.000000</td>\n",
       "      <td>892.000000</td>\n",
       "      <td>892.000000</td>\n",
       "      <td>891.000000</td>\n",
       "      <td>890</td>\n",
       "      <td>892</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>unique</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>892</td>\n",
       "      <td>2</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3</td>\n",
       "      <td>7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>top</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Simmons, Mr. John</td>\n",
       "      <td>male</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>S</td>\n",
       "      <td>Mr</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>freq</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1</td>\n",
       "      <td>578</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>645</td>\n",
       "      <td>518</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>0.383408</td>\n",
       "      <td>2.309417</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>29.742196</td>\n",
       "      <td>0.522422</td>\n",
       "      <td>0.381166</td>\n",
       "      <td>32.204208</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>std</th>\n",
       "      <td>0.486489</td>\n",
       "      <td>0.835923</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>14.561951</td>\n",
       "      <td>1.102264</td>\n",
       "      <td>0.805706</td>\n",
       "      <td>49.693429</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.420000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25%</th>\n",
       "      <td>0.000000</td>\n",
       "      <td>2.000000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>20.250000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>7.910400</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50%</th>\n",
       "      <td>0.000000</td>\n",
       "      <td>3.000000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>28.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>14.454200</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75%</th>\n",
       "      <td>1.000000</td>\n",
       "      <td>3.000000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>38.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>31.000000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>max</th>\n",
       "      <td>1.000000</td>\n",
       "      <td>3.000000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>80.000000</td>\n",
       "      <td>8.000000</td>\n",
       "      <td>6.000000</td>\n",
       "      <td>512.329200</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "          Survived      Pclass               Name   Sex         Age  \\\n",
       "count   892.000000  892.000000                892   892  715.000000   \n",
       "unique         NaN         NaN                892     2         NaN   \n",
       "top            NaN         NaN  Simmons, Mr. John  male         NaN   \n",
       "freq           NaN         NaN                  1   578         NaN   \n",
       "mean      0.383408    2.309417                NaN   NaN   29.742196   \n",
       "std       0.486489    0.835923                NaN   NaN   14.561951   \n",
       "min       0.000000    1.000000                NaN   NaN    0.420000   \n",
       "25%       0.000000    2.000000                NaN   NaN   20.250000   \n",
       "50%       0.000000    3.000000                NaN   NaN   28.000000   \n",
       "75%       1.000000    3.000000                NaN   NaN   38.000000   \n",
       "max       1.000000    3.000000                NaN   NaN   80.000000   \n",
       "\n",
       "             SibSp       Parch        Fare Embarked Title  \n",
       "count   892.000000  892.000000  891.000000      890   892  \n",
       "unique         NaN         NaN         NaN        3     7  \n",
       "top            NaN         NaN         NaN        S    Mr  \n",
       "freq           NaN         NaN         NaN      645   518  \n",
       "mean      0.522422    0.381166   32.204208      NaN   NaN  \n",
       "std       1.102264    0.805706   49.693429      NaN   NaN  \n",
       "min       0.000000    0.000000    0.000000      NaN   NaN  \n",
       "25%       0.000000    0.000000    7.910400      NaN   NaN  \n",
       "50%       0.000000    0.000000   14.454200      NaN   NaN  \n",
       "75%       1.000000    0.000000   31.000000      NaN   NaN  \n",
       "max       8.000000    6.000000  512.329200      NaN   NaN  "
      ]
     },
     "execution_count": 24,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.describe(include='all')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 4. Encuentre los mejores valores para completar la variable 'Age' para los pasajeros con datos faltantes"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Tome en cuenta que simplemente emplear el valor de tendencia central (mediana) de todo el conjunto casi nunca es la mejor alternativa\n",
    "Para obtener mejores resultados deberá apoyarse en los resultados de un análisis exploratorio de datos\n",
    "aplicado a las variable(s) que puedan estar relacionadas con 'Age'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
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       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>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>Fare</th>\n",
       "      <th>Embarked</th>\n",
       "      <th>Title</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>PassengerId</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>6</th>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>Moran, Mr. James</td>\n",
       "      <td>male</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>8.4583</td>\n",
       "      <td>Q</td>\n",
       "      <td>Mr</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>Williams, Mr. Charles Eugene</td>\n",
       "      <td>male</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>13.0000</td>\n",
       "      <td>S</td>\n",
       "      <td>Mr</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "      <td>Masselmani, Mrs. Fatima</td>\n",
       "      <td>female</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>7.2250</td>\n",
       "      <td>C</td>\n",
       "      <td>Mrs</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>Emir, Mr. Farred Chehab</td>\n",
       "      <td>male</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>7.2250</td>\n",
       "      <td>C</td>\n",
       "      <td>Mr</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29</th>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "      <td>O'Dwyer, Miss. Ellen \"Nellie\"</td>\n",
       "      <td>female</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>7.8792</td>\n",
       "      <td>Q</td>\n",
       "      <td>Miss</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "             Survived  Pclass                           Name     Sex  Age  \\\n",
       "PassengerId                                                                 \n",
       "6                   0       3               Moran, Mr. James    male  NaN   \n",
       "18                  1       2   Williams, Mr. Charles Eugene    male  NaN   \n",
       "20                  1       3        Masselmani, Mrs. Fatima  female  NaN   \n",
       "27                  0       3        Emir, Mr. Farred Chehab    male  NaN   \n",
       "29                  1       3  O'Dwyer, Miss. Ellen \"Nellie\"  female  NaN   \n",
       "\n",
       "             SibSp  Parch     Fare Embarked Title  \n",
       "PassengerId                                        \n",
       "6                0      0   8.4583        Q    Mr  \n",
       "18               0      0  13.0000        S    Mr  \n",
       "20               0      0   7.2250        C   Mrs  \n",
       "27               0      0   7.2250        C    Mr  \n",
       "29               0      0   7.8792        Q  Miss  "
      ]
     },
     "execution_count": 40,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df[df['Age'].isnull()].head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(177, 10)"
      ]
     },
     "execution_count": 41,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df[df['Age'].isnull()].shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "28.0"
      ]
     },
     "execution_count": 26,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df['Age'].median()"
   ]
  },
  {
   "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",
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       "\n",
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       "\n",
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       "        text-align: right;\n",
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>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>Survived</th>\n",
       "      <td>1.000000</td>\n",
       "      <td>-0.338965</td>\n",
       "      <td>-0.079388</td>\n",
       "      <td>-0.034886</td>\n",
       "      <td>0.082010</td>\n",
       "      <td>0.257307</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Pclass</th>\n",
       "      <td>-0.338965</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>-0.365161</td>\n",
       "      <td>0.082599</td>\n",
       "      <td>0.017994</td>\n",
       "      <td>-0.549500</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Age</th>\n",
       "      <td>-0.079388</td>\n",
       "      <td>-0.365161</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>-0.308847</td>\n",
       "      <td>-0.189989</td>\n",
       "      <td>0.096067</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>SibSp</th>\n",
       "      <td>-0.034886</td>\n",
       "      <td>0.082599</td>\n",
       "      <td>-0.308847</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.414985</td>\n",
       "      <td>0.159651</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Parch</th>\n",
       "      <td>0.082010</td>\n",
       "      <td>0.017994</td>\n",
       "      <td>-0.189989</td>\n",
       "      <td>0.414985</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.216225</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Fare</th>\n",
       "      <td>0.257307</td>\n",
       "      <td>-0.549500</td>\n",
       "      <td>0.096067</td>\n",
       "      <td>0.159651</td>\n",
       "      <td>0.216225</td>\n",
       "      <td>1.000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "          Survived    Pclass       Age     SibSp     Parch      Fare\n",
       "Survived  1.000000 -0.338965 -0.079388 -0.034886  0.082010  0.257307\n",
       "Pclass   -0.338965  1.000000 -0.365161  0.082599  0.017994 -0.549500\n",
       "Age      -0.079388 -0.365161  1.000000 -0.308847 -0.189989  0.096067\n",
       "SibSp    -0.034886  0.082599 -0.308847  1.000000  0.414985  0.159651\n",
       "Parch     0.082010  0.017994 -0.189989  0.414985  1.000000  0.216225\n",
       "Fare      0.257307 -0.549500  0.096067  0.159651  0.216225  1.000000"
      ]
     },
     "execution_count": 28,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.corr()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Según la matriz de correlación, *Age* tiene la correlación más alta con *Pclass*. Entonces, agruparemos los datos según este parámetro. También los agruparemos según el sexo, o sea, que los datos estarán agrupados por clase y por sexo. Porque las edades de las personas pueden variar según su sexo."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {},
   "outputs": [],
   "source": [
    "pasajeros_por_clase_y_sexo = df.groupby(['Pclass', 'Sex'])\n",
    "mediana_age_pasajeros = pasajeros_por_clase_y_sexo['Age'].transform('median')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
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       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
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       "\n",
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Survived</th>\n",
       "      <th>Pclass</th>\n",
       "      <th>Name</th>\n",
       "      <th>Sex</th>\n",
       "      <th>Age</th>\n",
       "      <th>SibSp</th>\n",
       "      <th>Parch</th>\n",
       "      <th>Fare</th>\n",
       "      <th>Embarked</th>\n",
       "      <th>Title</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>PassengerId</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",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "Empty DataFrame\n",
       "Columns: [Survived, Pclass, Name, Sex, Age, SibSp, Parch, Fare, Embarked, Title]\n",
       "Index: []"
      ]
     },
     "execution_count": 30,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Reemplazar los datos nulos de Age\n",
    "df['Age'].fillna(mediana_age_pasajeros, inplace=True)\n",
    "\n",
    "df[df['Age'].isnull()].head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 5. Cree una nueva variable 'IsMother' (1=es madre, 0=no es madre) \n",
    "\n",
    "#### Responda la siguiente pregunta sustentando su respuesta con los resultados de un análisis exploratorio de datos.\n",
    "#### Las madres tuvieron mayor probabilidad de sobrevivir al accidente del Titanic?"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Elegimos a las madres como las mujeres que están casadas y que viajen al menos con un Parch(parientes que sean padres o hijos).\n",
    "\n",
    "No incluímos a las mujeres con el título de Miss, para evitar incluir a las mujeres que no son madres pero que \n",
    "viajan con sus papás.\n",
    "\n",
    "Hay que tener en cuenta que en esa época no habían muchas madres solteras (por el machismo), así que no se\n",
    "pierde mucha información en caso de que una mujer sea madre y no esté casada."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "      <th></th>\n",
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       "      <th>Pclass</th>\n",
       "      <th>Name</th>\n",
       "      <th>Sex</th>\n",
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       "      <th>IsMother</th>\n",
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       "    <tr>\n",
       "      <th>PassengerId</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>888</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>Graham, Miss. Margaret Edith</td>\n",
       "      <td>female</td>\n",
       "      <td>19.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>30.00</td>\n",
       "      <td>S</td>\n",
       "      <td>Miss</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>889</th>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>Johnston, Miss. Catherine Helen \"Carrie\"</td>\n",
       "      <td>female</td>\n",
       "      <td>21.5</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>23.45</td>\n",
       "      <td>S</td>\n",
       "      <td>Miss</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>890</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>Behr, Mr. Karl Howell</td>\n",
       "      <td>male</td>\n",
       "      <td>26.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>30.00</td>\n",
       "      <td>C</td>\n",
       "      <td>Mr</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>891</th>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>Dooley, Mr. Patrick</td>\n",
       "      <td>male</td>\n",
       "      <td>32.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>7.75</td>\n",
       "      <td>Q</td>\n",
       "      <td>Mr</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1044</th>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>Storey, Mr. Thomas</td>\n",
       "      <td>male</td>\n",
       "      <td>60.5</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>S</td>\n",
       "      <td>Mr</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "             Survived  Pclass                                      Name  \\\n",
       "PassengerId                                                               \n",
       "888                 1       1              Graham, Miss. Margaret Edith   \n",
       "889                 0       3  Johnston, Miss. Catherine Helen \"Carrie\"   \n",
       "890                 1       1                     Behr, Mr. Karl Howell   \n",
       "891                 0       3                       Dooley, Mr. Patrick   \n",
       "1044                0       3                        Storey, Mr. Thomas   \n",
       "\n",
       "                Sex   Age  SibSp  Parch   Fare Embarked Title  IsMother  \n",
       "PassengerId                                                              \n",
       "888          female  19.0      0      0  30.00        S  Miss         0  \n",
       "889          female  21.5      1      2  23.45        S  Miss         0  \n",
       "890            male  26.0      0      0  30.00        C    Mr         0  \n",
       "891            male  32.0      0      0   7.75        Q    Mr         0  \n",
       "1044           male  60.5      0      0    NaN        S    Mr         0  "
      ]
     },
     "execution_count": 40,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "def es_mujer_y_no_soltera_y_viaja_con_hijos(fila):\n",
    "    return (fila['Parch'] > 0) & (fila['Sex'] == 'female') & (fila['Title'] != 'Miss')\n",
    "\n",
    "def es_madre(fila):\n",
    "    if es_mujer_y_no_soltera_y_viaja_con_hijos(fila):\n",
    "        return 1\n",
    "    return 0\n",
    "\n",
    "df['IsMother'] = df.apply(es_madre, axis=1)\n",
    "df.tail()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "      <th>9</th>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "      <td>Johnson, Mrs. Oscar W (Elisabeth Vilhelmina Berg)</td>\n",
       "      <td>female</td>\n",
       "      <td>27.0</td>\n",
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       "      <td>Asplund, Mrs. Carl Oscar (Selma Augusta Emilia...</td>\n",
       "      <td>female</td>\n",
       "      <td>38.0</td>\n",
       "      <td>1</td>\n",
       "      <td>5</td>\n",
       "      <td>31.3875</td>\n",
       "      <td>S</td>\n",
       "      <td>Mrs</td>\n",
       "      <td>1</td>\n",
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       "      <th>99</th>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>Doling, Mrs. John T (Ada Julia Bone)</td>\n",
       "      <td>female</td>\n",
       "      <td>34.0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>23.0000</td>\n",
       "      <td>S</td>\n",
       "      <td>Mrs</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>141</th>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>Boulos, Mrs. Joseph (Sultana)</td>\n",
       "      <td>female</td>\n",
       "      <td>21.5</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>15.2458</td>\n",
       "      <td>C</td>\n",
       "      <td>Mrs</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>167</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>Chibnall, Mrs. (Edith Martha Bowerman)</td>\n",
       "      <td>female</td>\n",
       "      <td>35.0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>55.0000</td>\n",
       "      <td>S</td>\n",
       "      <td>Mrs</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>168</th>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>Skoog, Mrs. William (Anna Bernhardina Karlsson)</td>\n",
       "      <td>female</td>\n",
       "      <td>45.0</td>\n",
       "      <td>1</td>\n",
       "      <td>4</td>\n",
       "      <td>27.9000</td>\n",
       "      <td>S</td>\n",
       "      <td>Mrs</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>248</th>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>Hamalainen, Mrs. William (Anna)</td>\n",
       "      <td>female</td>\n",
       "      <td>24.0</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>14.5000</td>\n",
       "      <td>S</td>\n",
       "      <td>Mrs</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>252</th>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>Strom, Mrs. Wilhelm (Elna Matilda Persson)</td>\n",
       "      <td>female</td>\n",
       "      <td>29.0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>10.4625</td>\n",
       "      <td>S</td>\n",
       "      <td>Mrs</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>255</th>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>Rosblom, Mrs. Viktor (Helena Wilhelmina)</td>\n",
       "      <td>female</td>\n",
       "      <td>41.0</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>20.2125</td>\n",
       "      <td>S</td>\n",
       "      <td>Mrs</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>256</th>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "      <td>Touma, Mrs. Darwis (Hanne Youssef Razi)</td>\n",
       "      <td>female</td>\n",
       "      <td>29.0</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>15.2458</td>\n",
       "      <td>C</td>\n",
       "      <td>Mrs</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>260</th>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>Parrish, Mrs. (Lutie Davis)</td>\n",
       "      <td>female</td>\n",
       "      <td>50.0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>26.0000</td>\n",
       "      <td>S</td>\n",
       "      <td>Mrs</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>269</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>Graham, Mrs. William Thompson (Edith Junkins)</td>\n",
       "      <td>female</td>\n",
       "      <td>58.0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>153.4625</td>\n",
       "      <td>S</td>\n",
       "      <td>Mrs</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>273</th>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>Mellinger, Mrs. (Elizabeth Anne Maidment)</td>\n",
       "      <td>female</td>\n",
       "      <td>41.0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>19.5000</td>\n",
       "      <td>S</td>\n",
       "      <td>Mrs</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>280</th>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "      <td>Abbott, Mrs. Stanton (Rosa Hunt)</td>\n",
       "      <td>female</td>\n",
       "      <td>35.0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>20.2500</td>\n",
       "      <td>S</td>\n",
       "      <td>Mrs</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>300</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>Baxter, Mrs. James (Helene DeLaudeniere Chaput)</td>\n",
       "      <td>female</td>\n",
       "      <td>50.0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>247.5208</td>\n",
       "      <td>C</td>\n",
       "      <td>Mrs</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>313</th>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>Lahtinen, Mrs. William (Anna Sylfven)</td>\n",
       "      <td>female</td>\n",
       "      <td>26.0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>26.0000</td>\n",
       "      <td>S</td>\n",
       "      <td>Mrs</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>320</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>Spedden, Mrs. Frederic Oakley (Margaretta Corn...</td>\n",
       "      <td>female</td>\n",
       "      <td>40.0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>134.5000</td>\n",
       "      <td>C</td>\n",
       "      <td>Mrs</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>324</th>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>Caldwell, Mrs. Albert Francis (Sylvia Mae Harb...</td>\n",
       "      <td>female</td>\n",
       "      <td>22.0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>29.0000</td>\n",
       "      <td>S</td>\n",
       "      <td>Mrs</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>329</th>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "      <td>Goldsmith, Mrs. Frank John (Emily Alice Brown)</td>\n",
       "      <td>female</td>\n",
       "      <td>31.0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>20.5250</td>\n",
       "      <td>S</td>\n",
       "      <td>Mrs</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>363</th>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>Barbara, Mrs. (Catherine David)</td>\n",
       "      <td>female</td>\n",
       "      <td>45.0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>14.4542</td>\n",
       "      <td>C</td>\n",
       "      <td>Mrs</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>395</th>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "      <td>Sandstrom, Mrs. Hjalmar (Agnes Charlotta Bengt...</td>\n",
       "      <td>female</td>\n",
       "      <td>24.0</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>16.7000</td>\n",
       "      <td>S</td>\n",
       "      <td>Mrs</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>417</th>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>Drew, Mrs. James Vivian (Lulu Thorne Christian)</td>\n",
       "      <td>female</td>\n",
       "      <td>34.0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>32.5000</td>\n",
       "      <td>S</td>\n",
       "      <td>Mrs</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>424</th>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>Danbom, Mrs. Ernst Gilbert (Anna Sigrid Maria ...</td>\n",
       "      <td>female</td>\n",
       "      <td>28.0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>14.4000</td>\n",
       "      <td>S</td>\n",
       "      <td>Mrs</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>438</th>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>Richards, Mrs. Sidney (Emily Hocking)</td>\n",
       "      <td>female</td>\n",
       "      <td>24.0</td>\n",
       "      <td>2</td>\n",
       "      <td>3</td>\n",
       "      <td>18.7500</td>\n",
       "      <td>S</td>\n",
       "      <td>Mrs</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>441</th>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>Hart, Mrs. Benjamin (Esther Ada Bloomfield)</td>\n",
       "      <td>female</td>\n",
       "      <td>45.0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>26.2500</td>\n",
       "      <td>S</td>\n",
       "      <td>Mrs</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>473</th>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>West, Mrs. Edwy Arthur (Ada Mary Worth)</td>\n",
       "      <td>female</td>\n",
       "      <td>33.0</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>27.7500</td>\n",
       "      <td>S</td>\n",
       "      <td>Mrs</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>499</th>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>Allison, Mrs. Hudson J C (Bessie Waldo Daniels)</td>\n",
       "      <td>female</td>\n",
       "      <td>25.0</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>151.5500</td>\n",
       "      <td>S</td>\n",
       "      <td>Mrs</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>507</th>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>Quick, Mrs. Frederick Charles (Jane Richards)</td>\n",
       "      <td>female</td>\n",
       "      <td>33.0</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>26.0000</td>\n",
       "      <td>S</td>\n",
       "      <td>Mrs</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>524</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>Hippach, Mrs. Louis Albert (Ida Sophia Fischer)</td>\n",
       "      <td>female</td>\n",
       "      <td>44.0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>57.9792</td>\n",
       "      <td>C</td>\n",
       "      <td>Mrs</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>534</th>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "      <td>Peter, Mrs. Catherine (Catherine Rizk)</td>\n",
       "      <td>female</td>\n",
       "      <td>21.5</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>22.3583</td>\n",
       "      <td>C</td>\n",
       "      <td>Mrs</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>559</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>Taussig, Mrs. Emil (Tillie Mandelbaum)</td>\n",
       "      <td>female</td>\n",
       "      <td>39.0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>79.6500</td>\n",
       "      <td>S</td>\n",
       "      <td>Mrs</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>568</th>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>Palsson, Mrs. Nils (Alma Cornelia Berglund)</td>\n",
       "      <td>female</td>\n",
       "      <td>29.0</td>\n",
       "      <td>0</td>\n",
       "      <td>4</td>\n",
       "      <td>21.0750</td>\n",
       "      <td>S</td>\n",
       "      <td>Mrs</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>582</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>Thayer, Mrs. John Borland (Marian Longstreth M...</td>\n",
       "      <td>female</td>\n",
       "      <td>39.0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>110.8833</td>\n",
       "      <td>C</td>\n",
       "      <td>Mrs</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>601</th>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>Jacobsohn, Mrs. Sidney Samuel (Amy Frances Chr...</td>\n",
       "      <td>female</td>\n",
       "      <td>24.0</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>27.0000</td>\n",
       "      <td>S</td>\n",
       "      <td>Mrs</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>609</th>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>Laroche, Mrs. Joseph (Juliette Marie Louise La...</td>\n",
       "      <td>female</td>\n",
       "      <td>22.0</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>41.5792</td>\n",
       "      <td>C</td>\n",
       "      <td>Mrs</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>611</th>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>Andersson, Mrs. Anders Johan (Alfrida Konstant...</td>\n",
       "      <td>female</td>\n",
       "      <td>39.0</td>\n",
       "      <td>1</td>\n",
       "      <td>5</td>\n",
       "      <td>31.2750</td>\n",
       "      <td>S</td>\n",
       "      <td>Mrs</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>639</th>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>Panula, Mrs. Juha (Maria Emilia Ojala)</td>\n",
       "      <td>female</td>\n",
       "      <td>41.0</td>\n",
       "      <td>0</td>\n",
       "      <td>5</td>\n",
       "      <td>39.6875</td>\n",
       "      <td>S</td>\n",
       "      <td>Mrs</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>658</th>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>Bourke, Mrs. John (Catherine)</td>\n",
       "      <td>female</td>\n",
       "      <td>32.0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>15.5000</td>\n",
       "      <td>Q</td>\n",
       "      <td>Mrs</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>671</th>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>Brown, Mrs. Thomas William Solomon (Elizabeth ...</td>\n",
       "      <td>female</td>\n",
       "      <td>40.0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>39.0000</td>\n",
       "      <td>S</td>\n",
       "      <td>Mrs</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>679</th>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>Goodwin, Mrs. Frederick (Augusta Tyler)</td>\n",
       "      <td>female</td>\n",
       "      <td>43.0</td>\n",
       "      <td>1</td>\n",
       "      <td>6</td>\n",
       "      <td>46.9000</td>\n",
       "      <td>S</td>\n",
       "      <td>Mrs</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>737</th>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>Ford, Mrs. Edward (Margaret Ann Watson)</td>\n",
       "      <td>female</td>\n",
       "      <td>48.0</td>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "      <td>34.3750</td>\n",
       "      <td>S</td>\n",
       "      <td>Mrs</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>755</th>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>Herman, Mrs. Samuel (Jane Laver)</td>\n",
       "      <td>female</td>\n",
       "      <td>48.0</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>65.0000</td>\n",
       "      <td>S</td>\n",
       "      <td>Mrs</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>764</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>Carter, Mrs. William Ernest (Lucile Polk)</td>\n",
       "      <td>female</td>\n",
       "      <td>36.0</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>120.0000</td>\n",
       "      <td>S</td>\n",
       "      <td>Mrs</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>775</th>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>Hocking, Mrs. Elizabeth (Eliza Needs)</td>\n",
       "      <td>female</td>\n",
       "      <td>54.0</td>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "      <td>23.0000</td>\n",
       "      <td>S</td>\n",
       "      <td>Mrs</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>780</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>Robert, Mrs. Edward Scott (Elisabeth Walton Mc...</td>\n",
       "      <td>female</td>\n",
       "      <td>43.0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>211.3375</td>\n",
       "      <td>S</td>\n",
       "      <td>Mrs</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>800</th>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>Van Impe, Mrs. Jean Baptiste (Rosalie Paula Go...</td>\n",
       "      <td>female</td>\n",
       "      <td>30.0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>24.1500</td>\n",
       "      <td>S</td>\n",
       "      <td>Mrs</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>802</th>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>Collyer, Mrs. Harvey (Charlotte Annie Tate)</td>\n",
       "      <td>female</td>\n",
       "      <td>31.0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>26.2500</td>\n",
       "      <td>S</td>\n",
       "      <td>Mrs</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>821</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>Hays, Mrs. Charles Melville (Clara Jennings Gr...</td>\n",
       "      <td>female</td>\n",
       "      <td>52.0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>93.5000</td>\n",
       "      <td>S</td>\n",
       "      <td>Mrs</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>824</th>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "      <td>Moor, Mrs. (Beila)</td>\n",
       "      <td>female</td>\n",
       "      <td>27.0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>12.4750</td>\n",
       "      <td>S</td>\n",
       "      <td>Mrs</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>856</th>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "      <td>Aks, Mrs. Sam (Leah Rosen)</td>\n",
       "      <td>female</td>\n",
       "      <td>18.0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>9.3500</td>\n",
       "      <td>S</td>\n",
       "      <td>Mrs</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>857</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>Wick, Mrs. George Dennick (Mary Hitchcock)</td>\n",
       "      <td>female</td>\n",
       "      <td>45.0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>164.8667</td>\n",
       "      <td>S</td>\n",
       "      <td>Mrs</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>859</th>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "      <td>Baclini, Mrs. Solomon (Latifa Qurban)</td>\n",
       "      <td>female</td>\n",
       "      <td>24.0</td>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>19.2583</td>\n",
       "      <td>C</td>\n",
       "      <td>Mrs</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>872</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>Beckwith, Mrs. Richard Leonard (Sallie Monypeny)</td>\n",
       "      <td>female</td>\n",
       "      <td>47.0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>52.5542</td>\n",
       "      <td>S</td>\n",
       "      <td>Mrs</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>880</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>Potter, Mrs. Thomas Jr (Lily Alexenia Wilson)</td>\n",
       "      <td>female</td>\n",
       "      <td>56.0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>83.1583</td>\n",
       "      <td>C</td>\n",
       "      <td>Mrs</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>881</th>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>Shelley, Mrs. William (Imanita Parrish Hall)</td>\n",
       "      <td>female</td>\n",
       "      <td>25.0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>26.0000</td>\n",
       "      <td>S</td>\n",
       "      <td>Mrs</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>886</th>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>Rice, Mrs. William (Margaret Norton)</td>\n",
       "      <td>female</td>\n",
       "      <td>39.0</td>\n",
       "      <td>0</td>\n",
       "      <td>5</td>\n",
       "      <td>29.1250</td>\n",
       "      <td>Q</td>\n",
       "      <td>Mrs</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "             Survived  Pclass  \\\n",
       "PassengerId                     \n",
       "9                   1       3   \n",
       "26                  1       3   \n",
       "99                  1       2   \n",
       "141                 0       3   \n",
       "167                 1       1   \n",
       "168                 0       3   \n",
       "248                 1       2   \n",
       "252                 0       3   \n",
       "255                 0       3   \n",
       "256                 1       3   \n",
       "260                 1       2   \n",
       "269                 1       1   \n",
       "273                 1       2   \n",
       "280                 1       3   \n",
       "300                 1       1   \n",
       "313                 0       2   \n",
       "320                 1       1   \n",
       "324                 1       2   \n",
       "329                 1       3   \n",
       "363                 0       3   \n",
       "395                 1       3   \n",
       "417                 1       2   \n",
       "424                 0       3   \n",
       "438                 1       2   \n",
       "441                 1       2   \n",
       "473                 1       2   \n",
       "499                 0       1   \n",
       "507                 1       2   \n",
       "524                 1       1   \n",
       "534                 1       3   \n",
       "559                 1       1   \n",
       "568                 0       3   \n",
       "582                 1       1   \n",
       "601                 1       2   \n",
       "609                 1       2   \n",
       "611                 0       3   \n",
       "639                 0       3   \n",
       "658                 0       3   \n",
       "671                 1       2   \n",
       "679                 0       3   \n",
       "737                 0       3   \n",
       "755                 1       2   \n",
       "764                 1       1   \n",
       "775                 1       2   \n",
       "780                 1       1   \n",
       "800                 0       3   \n",
       "802                 1       2   \n",
       "821                 1       1   \n",
       "824                 1       3   \n",
       "856                 1       3   \n",
       "857                 1       1   \n",
       "859                 1       3   \n",
       "872                 1       1   \n",
       "880                 1       1   \n",
       "881                 1       2   \n",
       "886                 0       3   \n",
       "\n",
       "                                                          Name     Sex   Age  \\\n",
       "PassengerId                                                                    \n",
       "9            Johnson, Mrs. Oscar W (Elisabeth Vilhelmina Berg)  female  27.0   \n",
       "26           Asplund, Mrs. Carl Oscar (Selma Augusta Emilia...  female  38.0   \n",
       "99                        Doling, Mrs. John T (Ada Julia Bone)  female  34.0   \n",
       "141                              Boulos, Mrs. Joseph (Sultana)  female  21.5   \n",
       "167                     Chibnall, Mrs. (Edith Martha Bowerman)  female  35.0   \n",
       "168            Skoog, Mrs. William (Anna Bernhardina Karlsson)  female  45.0   \n",
       "248                            Hamalainen, Mrs. William (Anna)  female  24.0   \n",
       "252                 Strom, Mrs. Wilhelm (Elna Matilda Persson)  female  29.0   \n",
       "255                   Rosblom, Mrs. Viktor (Helena Wilhelmina)  female  41.0   \n",
       "256                    Touma, Mrs. Darwis (Hanne Youssef Razi)  female  29.0   \n",
       "260                                Parrish, Mrs. (Lutie Davis)  female  50.0   \n",
       "269              Graham, Mrs. William Thompson (Edith Junkins)  female  58.0   \n",
       "273                  Mellinger, Mrs. (Elizabeth Anne Maidment)  female  41.0   \n",
       "280                           Abbott, Mrs. Stanton (Rosa Hunt)  female  35.0   \n",
       "300            Baxter, Mrs. James (Helene DeLaudeniere Chaput)  female  50.0   \n",
       "313                      Lahtinen, Mrs. William (Anna Sylfven)  female  26.0   \n",
       "320          Spedden, Mrs. Frederic Oakley (Margaretta Corn...  female  40.0   \n",
       "324          Caldwell, Mrs. Albert Francis (Sylvia Mae Harb...  female  22.0   \n",
       "329             Goldsmith, Mrs. Frank John (Emily Alice Brown)  female  31.0   \n",
       "363                            Barbara, Mrs. (Catherine David)  female  45.0   \n",
       "395          Sandstrom, Mrs. Hjalmar (Agnes Charlotta Bengt...  female  24.0   \n",
       "417            Drew, Mrs. James Vivian (Lulu Thorne Christian)  female  34.0   \n",
       "424          Danbom, Mrs. Ernst Gilbert (Anna Sigrid Maria ...  female  28.0   \n",
       "438                      Richards, Mrs. Sidney (Emily Hocking)  female  24.0   \n",
       "441                Hart, Mrs. Benjamin (Esther Ada Bloomfield)  female  45.0   \n",
       "473                    West, Mrs. Edwy Arthur (Ada Mary Worth)  female  33.0   \n",
       "499            Allison, Mrs. Hudson J C (Bessie Waldo Daniels)  female  25.0   \n",
       "507              Quick, Mrs. Frederick Charles (Jane Richards)  female  33.0   \n",
       "524            Hippach, Mrs. Louis Albert (Ida Sophia Fischer)  female  44.0   \n",
       "534                     Peter, Mrs. Catherine (Catherine Rizk)  female  21.5   \n",
       "559                     Taussig, Mrs. Emil (Tillie Mandelbaum)  female  39.0   \n",
       "568                Palsson, Mrs. Nils (Alma Cornelia Berglund)  female  29.0   \n",
       "582          Thayer, Mrs. John Borland (Marian Longstreth M...  female  39.0   \n",
       "601          Jacobsohn, Mrs. Sidney Samuel (Amy Frances Chr...  female  24.0   \n",
       "609          Laroche, Mrs. Joseph (Juliette Marie Louise La...  female  22.0   \n",
       "611          Andersson, Mrs. Anders Johan (Alfrida Konstant...  female  39.0   \n",
       "639                     Panula, Mrs. Juha (Maria Emilia Ojala)  female  41.0   \n",
       "658                              Bourke, Mrs. John (Catherine)  female  32.0   \n",
       "671          Brown, Mrs. Thomas William Solomon (Elizabeth ...  female  40.0   \n",
       "679                    Goodwin, Mrs. Frederick (Augusta Tyler)  female  43.0   \n",
       "737                    Ford, Mrs. Edward (Margaret Ann Watson)  female  48.0   \n",
       "755                           Herman, Mrs. Samuel (Jane Laver)  female  48.0   \n",
       "764                  Carter, Mrs. William Ernest (Lucile Polk)  female  36.0   \n",
       "775                      Hocking, Mrs. Elizabeth (Eliza Needs)  female  54.0   \n",
       "780          Robert, Mrs. Edward Scott (Elisabeth Walton Mc...  female  43.0   \n",
       "800          Van Impe, Mrs. Jean Baptiste (Rosalie Paula Go...  female  30.0   \n",
       "802                Collyer, Mrs. Harvey (Charlotte Annie Tate)  female  31.0   \n",
       "821          Hays, Mrs. Charles Melville (Clara Jennings Gr...  female  52.0   \n",
       "824                                         Moor, Mrs. (Beila)  female  27.0   \n",
       "856                                 Aks, Mrs. Sam (Leah Rosen)  female  18.0   \n",
       "857                 Wick, Mrs. George Dennick (Mary Hitchcock)  female  45.0   \n",
       "859                      Baclini, Mrs. Solomon (Latifa Qurban)  female  24.0   \n",
       "872           Beckwith, Mrs. Richard Leonard (Sallie Monypeny)  female  47.0   \n",
       "880              Potter, Mrs. Thomas Jr (Lily Alexenia Wilson)  female  56.0   \n",
       "881               Shelley, Mrs. William (Imanita Parrish Hall)  female  25.0   \n",
       "886                       Rice, Mrs. William (Margaret Norton)  female  39.0   \n",
       "\n",
       "             SibSp  Parch      Fare Embarked Title  IsMother  \n",
       "PassengerId                                                   \n",
       "9                0      2   11.1333        S   Mrs         1  \n",
       "26               1      5   31.3875        S   Mrs         1  \n",
       "99               0      1   23.0000        S   Mrs         1  \n",
       "141              0      2   15.2458        C   Mrs         1  \n",
       "167              0      1   55.0000        S   Mrs         1  \n",
       "168              1      4   27.9000        S   Mrs         1  \n",
       "248              0      2   14.5000        S   Mrs         1  \n",
       "252              1      1   10.4625        S   Mrs         1  \n",
       "255              0      2   20.2125        S   Mrs         1  \n",
       "256              0      2   15.2458        C   Mrs         1  \n",
       "260              0      1   26.0000        S   Mrs         1  \n",
       "269              0      1  153.4625        S   Mrs         1  \n",
       "273              0      1   19.5000        S   Mrs         1  \n",
       "280              1      1   20.2500        S   Mrs         1  \n",
       "300              0      1  247.5208        C   Mrs         1  \n",
       "313              1      1   26.0000        S   Mrs         1  \n",
       "320              1      1  134.5000        C   Mrs         1  \n",
       "324              1      1   29.0000        S   Mrs         1  \n",
       "329              1      1   20.5250        S   Mrs         1  \n",
       "363              0      1   14.4542        C   Mrs         1  \n",
       "395              0      2   16.7000        S   Mrs         1  \n",
       "417              1      1   32.5000        S   Mrs         1  \n",
       "424              1      1   14.4000        S   Mrs         1  \n",
       "438              2      3   18.7500        S   Mrs         1  \n",
       "441              1      1   26.2500        S   Mrs         1  \n",
       "473              1      2   27.7500        S   Mrs         1  \n",
       "499              1      2  151.5500        S   Mrs         1  \n",
       "507              0      2   26.0000        S   Mrs         1  \n",
       "524              0      1   57.9792        C   Mrs         1  \n",
       "534              0      2   22.3583        C   Mrs         1  \n",
       "559              1      1   79.6500        S   Mrs         1  \n",
       "568              0      4   21.0750        S   Mrs         1  \n",
       "582              1      1  110.8833        C   Mrs         1  \n",
       "601              2      1   27.0000        S   Mrs         1  \n",
       "609              1      2   41.5792        C   Mrs         1  \n",
       "611              1      5   31.2750        S   Mrs         1  \n",
       "639              0      5   39.6875        S   Mrs         1  \n",
       "658              1      1   15.5000        Q   Mrs         1  \n",
       "671              1      1   39.0000        S   Mrs         1  \n",
       "679              1      6   46.9000        S   Mrs         1  \n",
       "737              1      3   34.3750        S   Mrs         1  \n",
       "755              1      2   65.0000        S   Mrs         1  \n",
       "764              1      2  120.0000        S   Mrs         1  \n",
       "775              1      3   23.0000        S   Mrs         1  \n",
       "780              0      1  211.3375        S   Mrs         1  \n",
       "800              1      1   24.1500        S   Mrs         1  \n",
       "802              1      1   26.2500        S   Mrs         1  \n",
       "821              1      1   93.5000        S   Mrs         1  \n",
       "824              0      1   12.4750        S   Mrs         1  \n",
       "856              0      1    9.3500        S   Mrs         1  \n",
       "857              1      1  164.8667        S   Mrs         1  \n",
       "859              0      3   19.2583        C   Mrs         1  \n",
       "872              1      1   52.5542        S   Mrs         1  \n",
       "880              0      1   83.1583        C   Mrs         1  \n",
       "881              0      1   26.0000        S   Mrs         1  \n",
       "886              0      5   29.1250        Q   Mrs         1  "
      ]
     },
     "execution_count": 41,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.loc[(df['IsMother'] == 1)]"
   ]
  }
 ],
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