Kaggle_Titanic.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 79,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "import pandas as pd"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 80,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\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>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",
       "      <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>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",
       "    </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>STON/O2. 3101282</td>\n",
       "      <td>7.9250</td>\n",
       "      <td>NaN</td>\n",
       "      <td>S</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>113803</td>\n",
       "      <td>53.1000</td>\n",
       "      <td>C123</td>\n",
       "      <td>S</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>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": 80,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "plain_data = pd.read_csv('./titanic_data/train.csv', index_col=0)\n",
    "plain_data.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 119,
   "metadata": {},
   "outputs": [],
   "source": [
    "y = plain_data['Survived']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 83,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Index([u'Survived', u'Pclass', u'Name', u'Sex', u'Age', u'SibSp', u'Parch',\n",
       "       u'Ticket', u'Fare', u'Cabin', u'Embarked'],\n",
       "      dtype='object')"
      ]
     },
     "execution_count": 83,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "plain_data.columns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 84,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
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       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\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>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",
       "      <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>0</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>0.0</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>1</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>1.0</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>1</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>0.0</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>1</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>0.0</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>0</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>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>Moran, Mr. James</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>330877</td>\n",
       "      <td>8.4583</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>McCarthy, Mr. Timothy J</td>\n",
       "      <td>0</td>\n",
       "      <td>54.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>17463</td>\n",
       "      <td>51.8625</td>\n",
       "      <td>E46</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>Palsson, Master. Gosta Leonard</td>\n",
       "      <td>0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>3</td>\n",
       "      <td>1</td>\n",
       "      <td>349909</td>\n",
       "      <td>21.0750</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "      <td>Johnson, Mrs. Oscar W (Elisabeth Vilhelmina Berg)</td>\n",
       "      <td>1</td>\n",
       "      <td>27.0</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>347742</td>\n",
       "      <td>11.1333</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>Nasser, Mrs. Nicholas (Adele Achem)</td>\n",
       "      <td>1</td>\n",
       "      <td>14.0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>237736</td>\n",
       "      <td>30.0708</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "      <td>Sandstrom, Miss. Marguerite Rut</td>\n",
       "      <td>1</td>\n",
       "      <td>4.0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>PP 9549</td>\n",
       "      <td>16.7000</td>\n",
       "      <td>G6</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>Bonnell, Miss. Elizabeth</td>\n",
       "      <td>1</td>\n",
       "      <td>58.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>113783</td>\n",
       "      <td>26.5500</td>\n",
       "      <td>C103</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>Saundercock, Mr. William Henry</td>\n",
       "      <td>0</td>\n",
       "      <td>20.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>A/5. 2151</td>\n",
       "      <td>8.0500</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>Andersson, Mr. Anders Johan</td>\n",
       "      <td>0</td>\n",
       "      <td>39.0</td>\n",
       "      <td>1</td>\n",
       "      <td>5</td>\n",
       "      <td>347082</td>\n",
       "      <td>31.2750</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>Vestrom, Miss. Hulda Amanda Adolfina</td>\n",
       "      <td>1</td>\n",
       "      <td>14.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>350406</td>\n",
       "      <td>7.8542</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>Hewlett, Mrs. (Mary D Kingcome)</td>\n",
       "      <td>1</td>\n",
       "      <td>55.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>248706</td>\n",
       "      <td>16.0000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>Rice, Master. Eugene</td>\n",
       "      <td>0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>4</td>\n",
       "      <td>1</td>\n",
       "      <td>382652</td>\n",
       "      <td>29.1250</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</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>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>244373</td>\n",
       "      <td>13.0000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>Vander Planke, Mrs. Julius (Emelia Maria Vande...</td>\n",
       "      <td>1</td>\n",
       "      <td>31.0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>345763</td>\n",
       "      <td>18.0000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.0</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>1</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2649</td>\n",
       "      <td>7.2250</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>Fynney, Mr. Joseph J</td>\n",
       "      <td>0</td>\n",
       "      <td>35.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>239865</td>\n",
       "      <td>26.0000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>Beesley, Mr. Lawrence</td>\n",
       "      <td>0</td>\n",
       "      <td>34.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>248698</td>\n",
       "      <td>13.0000</td>\n",
       "      <td>D56</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "      <td>McGowan, Miss. Anna \"Annie\"</td>\n",
       "      <td>1</td>\n",
       "      <td>15.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>330923</td>\n",
       "      <td>8.0292</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>Sloper, Mr. William Thompson</td>\n",
       "      <td>0</td>\n",
       "      <td>28.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>113788</td>\n",
       "      <td>35.5000</td>\n",
       "      <td>A6</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>Palsson, Miss. Torborg Danira</td>\n",
       "      <td>1</td>\n",
       "      <td>8.0</td>\n",
       "      <td>3</td>\n",
       "      <td>1</td>\n",
       "      <td>349909</td>\n",
       "      <td>21.0750</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "      <td>Asplund, Mrs. Carl Oscar (Selma Augusta Emilia...</td>\n",
       "      <td>1</td>\n",
       "      <td>38.0</td>\n",
       "      <td>1</td>\n",
       "      <td>5</td>\n",
       "      <td>347077</td>\n",
       "      <td>31.3875</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.0</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>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2631</td>\n",
       "      <td>7.2250</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28</th>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>Fortune, Mr. Charles Alexander</td>\n",
       "      <td>0</td>\n",
       "      <td>19.0</td>\n",
       "      <td>3</td>\n",
       "      <td>2</td>\n",
       "      <td>19950</td>\n",
       "      <td>263.0000</td>\n",
       "      <td>C23 C25 C27</td>\n",
       "      <td>0.0</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>1</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>330959</td>\n",
       "      <td>7.8792</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>30</th>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>Todoroff, Mr. Lalio</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>349216</td>\n",
       "      <td>7.8958</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>862</th>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>Giles, Mr. Frederick Edward</td>\n",
       "      <td>0</td>\n",
       "      <td>21.0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>28134</td>\n",
       "      <td>11.5000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>863</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>Swift, Mrs. Frederick Joel (Margaret Welles Ba...</td>\n",
       "      <td>1</td>\n",
       "      <td>48.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>17466</td>\n",
       "      <td>25.9292</td>\n",
       "      <td>D17</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>864</th>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>Sage, Miss. Dorothy Edith \"Dolly\"</td>\n",
       "      <td>1</td>\n",
       "      <td>NaN</td>\n",
       "      <td>8</td>\n",
       "      <td>2</td>\n",
       "      <td>CA. 2343</td>\n",
       "      <td>69.5500</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>865</th>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>Gill, Mr. John William</td>\n",
       "      <td>0</td>\n",
       "      <td>24.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>233866</td>\n",
       "      <td>13.0000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>866</th>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>Bystrom, Mrs. (Karolina)</td>\n",
       "      <td>1</td>\n",
       "      <td>42.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>236852</td>\n",
       "      <td>13.0000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>867</th>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>Duran y More, Miss. Asuncion</td>\n",
       "      <td>1</td>\n",
       "      <td>27.0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>SC/PARIS 2149</td>\n",
       "      <td>13.8583</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>868</th>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>Roebling, Mr. Washington Augustus II</td>\n",
       "      <td>0</td>\n",
       "      <td>31.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>PC 17590</td>\n",
       "      <td>50.4958</td>\n",
       "      <td>A24</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>869</th>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>van Melkebeke, Mr. Philemon</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>345777</td>\n",
       "      <td>9.5000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>870</th>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "      <td>Johnson, Master. Harold Theodor</td>\n",
       "      <td>0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>347742</td>\n",
       "      <td>11.1333</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>871</th>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>Balkic, Mr. Cerin</td>\n",
       "      <td>0</td>\n",
       "      <td>26.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>349248</td>\n",
       "      <td>7.8958</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.0</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>1</td>\n",
       "      <td>47.0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>11751</td>\n",
       "      <td>52.5542</td>\n",
       "      <td>D35</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>873</th>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>Carlsson, Mr. Frans Olof</td>\n",
       "      <td>0</td>\n",
       "      <td>33.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>695</td>\n",
       "      <td>5.0000</td>\n",
       "      <td>B51 B53 B55</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>874</th>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>Vander Cruyssen, Mr. Victor</td>\n",
       "      <td>0</td>\n",
       "      <td>47.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>345765</td>\n",
       "      <td>9.0000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>875</th>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>Abelson, Mrs. Samuel (Hannah Wizosky)</td>\n",
       "      <td>1</td>\n",
       "      <td>28.0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>P/PP 3381</td>\n",
       "      <td>24.0000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>876</th>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "      <td>Najib, Miss. Adele Kiamie \"Jane\"</td>\n",
       "      <td>1</td>\n",
       "      <td>15.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2667</td>\n",
       "      <td>7.2250</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>877</th>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>Gustafsson, Mr. Alfred Ossian</td>\n",
       "      <td>0</td>\n",
       "      <td>20.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>7534</td>\n",
       "      <td>9.8458</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>878</th>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>Petroff, Mr. Nedelio</td>\n",
       "      <td>0</td>\n",
       "      <td>19.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>349212</td>\n",
       "      <td>7.8958</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>879</th>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>Laleff, Mr. Kristo</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>349217</td>\n",
       "      <td>7.8958</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.0</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>1</td>\n",
       "      <td>56.0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>11767</td>\n",
       "      <td>83.1583</td>\n",
       "      <td>C50</td>\n",
       "      <td>1.0</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>1</td>\n",
       "      <td>25.0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>230433</td>\n",
       "      <td>26.0000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>882</th>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>Markun, Mr. Johann</td>\n",
       "      <td>0</td>\n",
       "      <td>33.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>349257</td>\n",
       "      <td>7.8958</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>883</th>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>Dahlberg, Miss. Gerda Ulrika</td>\n",
       "      <td>1</td>\n",
       "      <td>22.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>7552</td>\n",
       "      <td>10.5167</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>884</th>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>Banfield, Mr. Frederick James</td>\n",
       "      <td>0</td>\n",
       "      <td>28.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>C.A./SOTON 34068</td>\n",
       "      <td>10.5000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>885</th>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>Sutehall, Mr. Henry Jr</td>\n",
       "      <td>0</td>\n",
       "      <td>25.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>SOTON/OQ 392076</td>\n",
       "      <td>7.0500</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.0</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>1</td>\n",
       "      <td>39.0</td>\n",
       "      <td>0</td>\n",
       "      <td>5</td>\n",
       "      <td>382652</td>\n",
       "      <td>29.1250</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>887</th>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>Montvila, Rev. Juozas</td>\n",
       "      <td>0</td>\n",
       "      <td>27.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>211536</td>\n",
       "      <td>13.0000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>888</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>Graham, Miss. Margaret Edith</td>\n",
       "      <td>1</td>\n",
       "      <td>19.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>112053</td>\n",
       "      <td>30.0000</td>\n",
       "      <td>B42</td>\n",
       "      <td>0.0</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>1</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>W./C. 6607</td>\n",
       "      <td>23.4500</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.0</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>0</td>\n",
       "      <td>26.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>111369</td>\n",
       "      <td>30.0000</td>\n",
       "      <td>C148</td>\n",
       "      <td>1.0</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>0</td>\n",
       "      <td>32.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>370376</td>\n",
       "      <td>7.7500</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>891 rows × 11 columns</p>\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",
       "6                   0       3   \n",
       "7                   0       1   \n",
       "8                   0       3   \n",
       "9                   1       3   \n",
       "10                  1       2   \n",
       "11                  1       3   \n",
       "12                  1       1   \n",
       "13                  0       3   \n",
       "14                  0       3   \n",
       "15                  0       3   \n",
       "16                  1       2   \n",
       "17                  0       3   \n",
       "18                  1       2   \n",
       "19                  0       3   \n",
       "20                  1       3   \n",
       "21                  0       2   \n",
       "22                  1       2   \n",
       "23                  1       3   \n",
       "24                  1       1   \n",
       "25                  0       3   \n",
       "26                  1       3   \n",
       "27                  0       3   \n",
       "28                  0       1   \n",
       "29                  1       3   \n",
       "30                  0       3   \n",
       "...               ...     ...   \n",
       "862                 0       2   \n",
       "863                 1       1   \n",
       "864                 0       3   \n",
       "865                 0       2   \n",
       "866                 1       2   \n",
       "867                 1       2   \n",
       "868                 0       1   \n",
       "869                 0       3   \n",
       "870                 1       3   \n",
       "871                 0       3   \n",
       "872                 1       1   \n",
       "873                 0       1   \n",
       "874                 0       3   \n",
       "875                 1       2   \n",
       "876                 1       3   \n",
       "877                 0       3   \n",
       "878                 0       3   \n",
       "879                 0       3   \n",
       "880                 1       1   \n",
       "881                 1       2   \n",
       "882                 0       3   \n",
       "883                 0       3   \n",
       "884                 0       2   \n",
       "885                 0       3   \n",
       "886                 0       3   \n",
       "887                 0       2   \n",
       "888                 1       1   \n",
       "889                 0       3   \n",
       "890                 1       1   \n",
       "891                 0       3   \n",
       "\n",
       "                                                          Name  Sex   Age  \\\n",
       "PassengerId                                                                 \n",
       "1                                      Braund, Mr. Owen Harris    0  22.0   \n",
       "2            Cumings, Mrs. John Bradley (Florence Briggs Th...    1  38.0   \n",
       "3                                       Heikkinen, Miss. Laina    1  26.0   \n",
       "4                 Futrelle, Mrs. Jacques Heath (Lily May Peel)    1  35.0   \n",
       "5                                     Allen, Mr. William Henry    0  35.0   \n",
       "6                                             Moran, Mr. James    0   NaN   \n",
       "7                                      McCarthy, Mr. Timothy J    0  54.0   \n",
       "8                               Palsson, Master. Gosta Leonard    0   2.0   \n",
       "9            Johnson, Mrs. Oscar W (Elisabeth Vilhelmina Berg)    1  27.0   \n",
       "10                         Nasser, Mrs. Nicholas (Adele Achem)    1  14.0   \n",
       "11                             Sandstrom, Miss. Marguerite Rut    1   4.0   \n",
       "12                                    Bonnell, Miss. Elizabeth    1  58.0   \n",
       "13                              Saundercock, Mr. William Henry    0  20.0   \n",
       "14                                 Andersson, Mr. Anders Johan    0  39.0   \n",
       "15                        Vestrom, Miss. Hulda Amanda Adolfina    1  14.0   \n",
       "16                            Hewlett, Mrs. (Mary D Kingcome)     1  55.0   \n",
       "17                                        Rice, Master. Eugene    0   2.0   \n",
       "18                                Williams, Mr. Charles Eugene    0   NaN   \n",
       "19           Vander Planke, Mrs. Julius (Emelia Maria Vande...    1  31.0   \n",
       "20                                     Masselmani, Mrs. Fatima    1   NaN   \n",
       "21                                        Fynney, Mr. Joseph J    0  35.0   \n",
       "22                                       Beesley, Mr. Lawrence    0  34.0   \n",
       "23                                 McGowan, Miss. Anna \"Annie\"    1  15.0   \n",
       "24                                Sloper, Mr. William Thompson    0  28.0   \n",
       "25                               Palsson, Miss. Torborg Danira    1   8.0   \n",
       "26           Asplund, Mrs. Carl Oscar (Selma Augusta Emilia...    1  38.0   \n",
       "27                                     Emir, Mr. Farred Chehab    0   NaN   \n",
       "28                              Fortune, Mr. Charles Alexander    0  19.0   \n",
       "29                               O'Dwyer, Miss. Ellen \"Nellie\"    1   NaN   \n",
       "30                                         Todoroff, Mr. Lalio    0   NaN   \n",
       "...                                                        ...  ...   ...   \n",
       "862                                Giles, Mr. Frederick Edward    0  21.0   \n",
       "863          Swift, Mrs. Frederick Joel (Margaret Welles Ba...    1  48.0   \n",
       "864                          Sage, Miss. Dorothy Edith \"Dolly\"    1   NaN   \n",
       "865                                     Gill, Mr. John William    0  24.0   \n",
       "866                                   Bystrom, Mrs. (Karolina)    1  42.0   \n",
       "867                               Duran y More, Miss. Asuncion    1  27.0   \n",
       "868                       Roebling, Mr. Washington Augustus II    0  31.0   \n",
       "869                                van Melkebeke, Mr. Philemon    0   NaN   \n",
       "870                            Johnson, Master. Harold Theodor    0   4.0   \n",
       "871                                          Balkic, Mr. Cerin    0  26.0   \n",
       "872           Beckwith, Mrs. Richard Leonard (Sallie Monypeny)    1  47.0   \n",
       "873                                   Carlsson, Mr. Frans Olof    0  33.0   \n",
       "874                                Vander Cruyssen, Mr. Victor    0  47.0   \n",
       "875                      Abelson, Mrs. Samuel (Hannah Wizosky)    1  28.0   \n",
       "876                           Najib, Miss. Adele Kiamie \"Jane\"    1  15.0   \n",
       "877                              Gustafsson, Mr. Alfred Ossian    0  20.0   \n",
       "878                                       Petroff, Mr. Nedelio    0  19.0   \n",
       "879                                         Laleff, Mr. Kristo    0   NaN   \n",
       "880              Potter, Mrs. Thomas Jr (Lily Alexenia Wilson)    1  56.0   \n",
       "881               Shelley, Mrs. William (Imanita Parrish Hall)    1  25.0   \n",
       "882                                         Markun, Mr. Johann    0  33.0   \n",
       "883                               Dahlberg, Miss. Gerda Ulrika    1  22.0   \n",
       "884                              Banfield, Mr. Frederick James    0  28.0   \n",
       "885                                     Sutehall, Mr. Henry Jr    0  25.0   \n",
       "886                       Rice, Mrs. William (Margaret Norton)    1  39.0   \n",
       "887                                      Montvila, Rev. Juozas    0  27.0   \n",
       "888                               Graham, Miss. Margaret Edith    1  19.0   \n",
       "889                   Johnston, Miss. Catherine Helen \"Carrie\"    1   NaN   \n",
       "890                                      Behr, Mr. Karl Howell    0  26.0   \n",
       "891                                        Dooley, Mr. Patrick    0  32.0   \n",
       "\n",
       "             SibSp  Parch            Ticket      Fare        Cabin  Embarked  \n",
       "PassengerId                                                                   \n",
       "1                1      0         A/5 21171    7.2500          NaN       0.0  \n",
       "2                1      0          PC 17599   71.2833          C85       1.0  \n",
       "3                0      0  STON/O2. 3101282    7.9250          NaN       0.0  \n",
       "4                1      0            113803   53.1000         C123       0.0  \n",
       "5                0      0            373450    8.0500          NaN       0.0  \n",
       "6                0      0            330877    8.4583          NaN       2.0  \n",
       "7                0      0             17463   51.8625          E46       0.0  \n",
       "8                3      1            349909   21.0750          NaN       0.0  \n",
       "9                0      2            347742   11.1333          NaN       0.0  \n",
       "10               1      0            237736   30.0708          NaN       1.0  \n",
       "11               1      1           PP 9549   16.7000           G6       0.0  \n",
       "12               0      0            113783   26.5500         C103       0.0  \n",
       "13               0      0         A/5. 2151    8.0500          NaN       0.0  \n",
       "14               1      5            347082   31.2750          NaN       0.0  \n",
       "15               0      0            350406    7.8542          NaN       0.0  \n",
       "16               0      0            248706   16.0000          NaN       0.0  \n",
       "17               4      1            382652   29.1250          NaN       2.0  \n",
       "18               0      0            244373   13.0000          NaN       0.0  \n",
       "19               1      0            345763   18.0000          NaN       0.0  \n",
       "20               0      0              2649    7.2250          NaN       1.0  \n",
       "21               0      0            239865   26.0000          NaN       0.0  \n",
       "22               0      0            248698   13.0000          D56       0.0  \n",
       "23               0      0            330923    8.0292          NaN       2.0  \n",
       "24               0      0            113788   35.5000           A6       0.0  \n",
       "25               3      1            349909   21.0750          NaN       0.0  \n",
       "26               1      5            347077   31.3875          NaN       0.0  \n",
       "27               0      0              2631    7.2250          NaN       1.0  \n",
       "28               3      2             19950  263.0000  C23 C25 C27       0.0  \n",
       "29               0      0            330959    7.8792          NaN       2.0  \n",
       "30               0      0            349216    7.8958          NaN       0.0  \n",
       "...            ...    ...               ...       ...          ...       ...  \n",
       "862              1      0             28134   11.5000          NaN       0.0  \n",
       "863              0      0             17466   25.9292          D17       0.0  \n",
       "864              8      2          CA. 2343   69.5500          NaN       0.0  \n",
       "865              0      0            233866   13.0000          NaN       0.0  \n",
       "866              0      0            236852   13.0000          NaN       0.0  \n",
       "867              1      0     SC/PARIS 2149   13.8583          NaN       1.0  \n",
       "868              0      0          PC 17590   50.4958          A24       0.0  \n",
       "869              0      0            345777    9.5000          NaN       0.0  \n",
       "870              1      1            347742   11.1333          NaN       0.0  \n",
       "871              0      0            349248    7.8958          NaN       0.0  \n",
       "872              1      1             11751   52.5542          D35       0.0  \n",
       "873              0      0               695    5.0000  B51 B53 B55       0.0  \n",
       "874              0      0            345765    9.0000          NaN       0.0  \n",
       "875              1      0         P/PP 3381   24.0000          NaN       1.0  \n",
       "876              0      0              2667    7.2250          NaN       1.0  \n",
       "877              0      0              7534    9.8458          NaN       0.0  \n",
       "878              0      0            349212    7.8958          NaN       0.0  \n",
       "879              0      0            349217    7.8958          NaN       0.0  \n",
       "880              0      1             11767   83.1583          C50       1.0  \n",
       "881              0      1            230433   26.0000          NaN       0.0  \n",
       "882              0      0            349257    7.8958          NaN       0.0  \n",
       "883              0      0              7552   10.5167          NaN       0.0  \n",
       "884              0      0  C.A./SOTON 34068   10.5000          NaN       0.0  \n",
       "885              0      0   SOTON/OQ 392076    7.0500          NaN       0.0  \n",
       "886              0      5            382652   29.1250          NaN       2.0  \n",
       "887              0      0            211536   13.0000          NaN       0.0  \n",
       "888              0      0            112053   30.0000          B42       0.0  \n",
       "889              1      2        W./C. 6607   23.4500          NaN       0.0  \n",
       "890              0      0            111369   30.0000         C148       1.0  \n",
       "891              0      0            370376    7.7500          NaN       2.0  \n",
       "\n",
       "[891 rows x 11 columns]"
      ]
     },
     "execution_count": 84,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "temp = plain_data.copy(deep=True)\n",
    "temp['Sex'].fillna('male')\n",
    "temp['Embarked'].fillna('S')\n",
    "\n",
    "gender_dict = {'male':0, 'female':1}\n",
    "embarked_dict = {'S':0, 'C':1, 'Q':2}\n",
    "\n",
    "temp.replace(to_replace={'Sex':gender_dict}, inplace=True)\n",
    "temp.replace(to_replace={'Embarked':embarked_dict}, inplace=True)\n",
    "\n",
    "temp"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 92,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style>\n",
       "    .dataframe thead tr:only-child th {\n",
       "        text-align: right;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: left;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\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>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",
       "      <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>887</th>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>Montvila, Rev. Juozas</td>\n",
       "      <td>0</td>\n",
       "      <td>27.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>211536</td>\n",
       "      <td>13.00</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>888</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>Graham, Miss. Margaret Edith</td>\n",
       "      <td>1</td>\n",
       "      <td>19.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>112053</td>\n",
       "      <td>30.00</td>\n",
       "      <td>B42</td>\n",
       "      <td>0.0</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>1</td>\n",
       "      <td>28.0</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>W./C. 6607</td>\n",
       "      <td>23.45</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.0</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>0</td>\n",
       "      <td>26.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>111369</td>\n",
       "      <td>30.00</td>\n",
       "      <td>C148</td>\n",
       "      <td>1.0</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>0</td>\n",
       "      <td>32.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>370376</td>\n",
       "      <td>7.75</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "             Survived  Pclass                                      Name  Sex  \\\n",
       "PassengerId                                                                    \n",
       "887                 0       2                     Montvila, Rev. Juozas    0   \n",
       "888                 1       1              Graham, Miss. Margaret Edith    1   \n",
       "889                 0       3  Johnston, Miss. Catherine Helen \"Carrie\"    1   \n",
       "890                 1       1                     Behr, Mr. Karl Howell    0   \n",
       "891                 0       3                       Dooley, Mr. Patrick    0   \n",
       "\n",
       "              Age  SibSp  Parch      Ticket   Fare Cabin  Embarked  \n",
       "PassengerId                                                         \n",
       "887          27.0      0      0      211536  13.00   NaN       0.0  \n",
       "888          19.0      0      0      112053  30.00   B42       0.0  \n",
       "889          28.0      1      2  W./C. 6607  23.45   NaN       0.0  \n",
       "890          26.0      0      0      111369  30.00  C148       1.0  \n",
       "891          32.0      0      0      370376   7.75   NaN       2.0  "
      ]
     },
     "execution_count": 92,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "median_age = temp['Age'].median()\n",
    "median_fare = temp['Fare'].median()\n",
    "\n",
    "temp['Age'] = temp['Age'].fillna(median_age)\n",
    "temp['Fare'] = temp['Fare'].fillna(median_fare)\n",
    "temp.tail()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 189,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "(891, 4)\n",
      "(891,)\n"
     ]
    }
   ],
   "source": [
    "features_for_prediction = ['Age', 'Fare', 'Sex', 'Embarked']\n",
    "X = temp[features_for_prediction]\n",
    "print X.shape\n",
    "print y.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 279,
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "from sklearn.cross_validation import train_test_split\n",
    "\n",
    "X_train, X_test, y_train, y_test = train_test_split(X, y, random_state=4)\n",
    "\n",
    "embark_col=X_train['Embarked']\n",
    "embark_col.replace(to_replace=np.nan, value=0, inplace=True)\n",
    "X_train['Embarked'].update(embark_col)\n",
    "    \n",
    "X_train = np.array(X_train)\n",
    "X_test = np.array(X_test)\n",
    "y_train = np.array(y_train)\n",
    "y_test = np.array(y_test)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 280,
   "metadata": {},
   "outputs": [],
   "source": [
    "from sklearn.linear_model import LogisticRegression\n",
    "\n",
    "logreg = LogisticRegression()\n",
    "\n",
    "logreg.fit(X_train, y_train)\n",
    "\n",
    "y_pred = logreg.predict(X_test)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 281,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.80269058295964124"
      ]
     },
     "execution_count": 281,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from sklearn import metrics\n",
    "\n",
    "metrics.accuracy_score(y_test, y_pred)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 282,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "from sklearn.neighbors import KNeighborsClassifier\n",
    "\n",
    "k_range = range(1, 26)\n",
    "scores = []\n",
    "for k in k_range:\n",
    "    knn = KNeighborsClassifier(n_neighbors=k)\n",
    "    knn.fit(X_train, y_train)\n",
    "    y_pred = knn.predict(X_test)\n",
    "    scores.append(metrics.accuracy_score(y_test, y_pred))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 283,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.text.Text at 0x11867ca10>"
      ]
     },
     "execution_count": 283,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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zeGGR2XCs4qEjWJIZl2RzbuTiFEyl1JXWDaXUbqA5z05FMFOEoFuzK6UGQ1Hp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\nkEGcgiAIgpDh/wflm7HsuDb+zAAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x118667c50>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "\n",
    "%matplotlib inline\n",
    "\n",
    "plt.plot(k_range, scores)\n",
    "plt.xlabel('Value of K')\n",
    "plt.ylabel('Accuracy')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 289,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "(891, 7)\n",
      "(891,)\n"
     ]
    }
   ],
   "source": [
    "features_for_prediction = [\"Pclass\", \"Sex\", \"Age\", \"SibSp\", \"Parch\", \"Fare\", \"Embarked\"]\n",
    "X = temp[features_for_prediction]\n",
    "print X.shape\n",
    "print y.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 290,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "X_train, X_test, y_train, y_test = train_test_split(X, y, random_state=4)\n",
    "\n",
    "embark_col=X_train['Embarked']\n",
    "embark_col.replace(to_replace=np.nan, value=0, inplace=True)\n",
    "X_train['Embarked'].update(embark_col)\n",
    "    \n",
    "X_train = np.array(X_train)\n",
    "X_test = np.array(X_test)\n",
    "y_train = np.array(y_train)\n",
    "y_test = np.array(y_test)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 291,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "logreg = LogisticRegression()\n",
    "\n",
    "logreg.fit(X_train, y_train)\n",
    "\n",
    "y_pred = logreg.predict(X_test)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 292,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.7982062780269058"
      ]
     },
     "execution_count": 292,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "metrics.accuracy_score(y_test, y_pred)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 318,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(418, 7)"
      ]
     },
     "execution_count": 318,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "test_data = pd.read_csv('./titanic_data/test.csv')\n",
    "test_data['Sex']=test_data['Sex'].fillna('male')\n",
    "test_data['Embarked']=test_data['Embarked'].fillna('S')\n",
    "\n",
    "test_data.replace(to_replace={'Sex':gender_dict}, inplace=True)\n",
    "test_data.replace(to_replace={'Embarked':embarked_dict}, inplace=True)\n",
    "\n",
    "median_age = test_data['Age'].median()\n",
    "median_fare = test_data['Fare'].median()\n",
    "\n",
    "test_data['Age'] = test_data['Age'].fillna(median_age)\n",
    "test_data['Fare'] = test_data['Fare'].fillna(median_fare)\n",
    "test_data\n",
    "\n",
    "test_data_X = np.array(test_data[predictors])\n",
    "test_data_X.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 319,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(418,)"
      ]
     },
     "execution_count": 319,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "X = np.concatenate((X_train, X_test))\n",
    "y = np.concatenate((y_train, y_test))\n",
    "\n",
    "logreg = LogisticRegression()\n",
    "logreg.fit(X, y)\n",
    "result=logreg.predict(test_data_X)\n",
    "result.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 321,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style>\n",
       "    .dataframe thead tr:only-child th {\n",
       "        text-align: right;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: left;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\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",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>892</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>893</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>894</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>895</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>896</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>897</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>898</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>899</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>900</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>901</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>902</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>903</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>904</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>905</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>906</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>907</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>908</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>909</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>910</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>911</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>912</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>913</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>914</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>915</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>916</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>917</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>918</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>919</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28</th>\n",
       "      <td>920</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29</th>\n",
       "      <td>921</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>388</th>\n",
       "      <td>1280</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>389</th>\n",
       "      <td>1281</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>390</th>\n",
       "      <td>1282</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>391</th>\n",
       "      <td>1283</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>392</th>\n",
       "      <td>1284</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>393</th>\n",
       "      <td>1285</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>394</th>\n",
       "      <td>1286</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>395</th>\n",
       "      <td>1287</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>396</th>\n",
       "      <td>1288</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>397</th>\n",
       "      <td>1289</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>398</th>\n",
       "      <td>1290</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>399</th>\n",
       "      <td>1291</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>400</th>\n",
       "      <td>1292</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>401</th>\n",
       "      <td>1293</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>402</th>\n",
       "      <td>1294</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>403</th>\n",
       "      <td>1295</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>404</th>\n",
       "      <td>1296</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>405</th>\n",
       "      <td>1297</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>406</th>\n",
       "      <td>1298</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>407</th>\n",
       "      <td>1299</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>408</th>\n",
       "      <td>1300</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>409</th>\n",
       "      <td>1301</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>410</th>\n",
       "      <td>1302</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>411</th>\n",
       "      <td>1303</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>412</th>\n",
       "      <td>1304</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>413</th>\n",
       "      <td>1305</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>414</th>\n",
       "      <td>1306</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>415</th>\n",
       "      <td>1307</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>416</th>\n",
       "      <td>1308</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>417</th>\n",
       "      <td>1309</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>418 rows × 2 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "     PassengerId  Survived\n",
       "0            892         0\n",
       "1            893         0\n",
       "2            894         0\n",
       "3            895         0\n",
       "4            896         1\n",
       "5            897         0\n",
       "6            898         1\n",
       "7            899         0\n",
       "8            900         1\n",
       "9            901         0\n",
       "10           902         0\n",
       "11           903         0\n",
       "12           904         1\n",
       "13           905         0\n",
       "14           906         1\n",
       "15           907         1\n",
       "16           908         0\n",
       "17           909         0\n",
       "18           910         1\n",
       "19           911         1\n",
       "20           912         0\n",
       "21           913         0\n",
       "22           914         1\n",
       "23           915         1\n",
       "24           916         1\n",
       "25           917         0\n",
       "26           918         1\n",
       "27           919         0\n",
       "28           920         0\n",
       "29           921         0\n",
       "..           ...       ...\n",
       "388         1280         0\n",
       "389         1281         0\n",
       "390         1282         1\n",
       "391         1283         1\n",
       "392         1284         0\n",
       "393         1285         0\n",
       "394         1286         0\n",
       "395         1287         1\n",
       "396         1288         0\n",
       "397         1289         1\n",
       "398         1290         0\n",
       "399         1291         0\n",
       "400         1292         1\n",
       "401         1293         0\n",
       "402         1294         1\n",
       "403         1295         1\n",
       "404         1296         0\n",
       "405         1297         0\n",
       "406         1298         0\n",
       "407         1299         0\n",
       "408         1300         1\n",
       "409         1301         1\n",
       "410         1302         1\n",
       "411         1303         1\n",
       "412         1304         1\n",
       "413         1305         0\n",
       "414         1306         1\n",
       "415         1307         0\n",
       "416         1308         0\n",
       "417         1309         0\n",
       "\n",
       "[418 rows x 2 columns]"
      ]
     },
     "execution_count": 321,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "submission = pd.DataFrame({\n",
    "        \"PassengerId\": test_data[\"PassengerId\"],\n",
    "        \"Survived\": result\n",
    "    })\n",
    "submission"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 325,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "1.0"
      ]
     },
     "execution_count": 325,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "actual=pd.read_csv('./titanic_data/result.csv')\n",
    "metrics.accuracy_score(result, actual['Survived'])"
   ]
  }
 ],
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