titanic.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 96,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\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",
       "    <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>330877</td>\n",
       "      <td>8.4583</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Q</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>male</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>S</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>male</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>S</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>female</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>S</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>female</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>C</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",
       "6                   0       3   \n",
       "7                   0       1   \n",
       "8                   0       3   \n",
       "9                   1       3   \n",
       "10                  1       2   \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",
       "6                                             Moran, Mr. James    male   NaN   \n",
       "7                                      McCarthy, Mr. Timothy J    male  54.0   \n",
       "8                               Palsson, Master. Gosta Leonard    male   2.0   \n",
       "9            Johnson, Mrs. Oscar W (Elisabeth Vilhelmina Berg)  female  27.0   \n",
       "10                         Nasser, Mrs. Nicholas (Adele Achem)  female  14.0   \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  \n",
       "6                0      0            330877   8.4583   NaN        Q  \n",
       "7                0      0             17463  51.8625   E46        S  \n",
       "8                3      1            349909  21.0750   NaN        S  \n",
       "9                0      2            347742  11.1333   NaN        S  \n",
       "10               1      0            237736  30.0708   NaN        C  "
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<div>\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>count</th>\n",
       "      <td>891.000000</td>\n",
       "      <td>891.000000</td>\n",
       "      <td>714.000000</td>\n",
       "      <td>891.000000</td>\n",
       "      <td>891.000000</td>\n",
       "      <td>891.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>0.383838</td>\n",
       "      <td>2.308642</td>\n",
       "      <td>29.699118</td>\n",
       "      <td>0.523008</td>\n",
       "      <td>0.381594</td>\n",
       "      <td>32.204208</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>std</th>\n",
       "      <td>0.486592</td>\n",
       "      <td>0.836071</td>\n",
       "      <td>14.526497</td>\n",
       "      <td>1.102743</td>\n",
       "      <td>0.806057</td>\n",
       "      <td>49.693429</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.420000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25%</th>\n",
       "      <td>0.000000</td>\n",
       "      <td>2.000000</td>\n",
       "      <td>20.125000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>7.910400</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50%</th>\n",
       "      <td>0.000000</td>\n",
       "      <td>3.000000</td>\n",
       "      <td>28.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>14.454200</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75%</th>\n",
       "      <td>1.000000</td>\n",
       "      <td>3.000000</td>\n",
       "      <td>38.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>31.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>max</th>\n",
       "      <td>1.000000</td>\n",
       "      <td>3.000000</td>\n",
       "      <td>80.000000</td>\n",
       "      <td>8.000000</td>\n",
       "      <td>6.000000</td>\n",
       "      <td>512.329200</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "         survived      pclass         age       sibsp       parch        fare\n",
       "count  891.000000  891.000000  714.000000  891.000000  891.000000  891.000000\n",
       "mean     0.383838    2.308642   29.699118    0.523008    0.381594   32.204208\n",
       "std      0.486592    0.836071   14.526497    1.102743    0.806057   49.693429\n",
       "min      0.000000    1.000000    0.420000    0.000000    0.000000    0.000000\n",
       "25%      0.000000    2.000000   20.125000    0.000000    0.000000    7.910400\n",
       "50%      0.000000    3.000000   28.000000    0.000000    0.000000   14.454200\n",
       "75%      1.000000    3.000000   38.000000    1.000000    0.000000   31.000000\n",
       "max      1.000000    3.000000   80.000000    8.000000    6.000000  512.329200"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Int64Index: 891 entries, 1 to 891\n",
      "Data columns (total 11 columns):\n",
      "survived    891 non-null int64\n",
      "pclass      891 non-null int64\n",
      "name        891 non-null object\n",
      "sex         891 non-null object\n",
      "age         714 non-null float64\n",
      "sibsp       891 non-null int64\n",
      "parch       891 non-null int64\n",
      "ticket      891 non-null object\n",
      "fare        891 non-null float64\n",
      "cabin       204 non-null object\n",
      "embarked    889 non-null object\n",
      "dtypes: float64(2), int64(4), object(5)\n",
      "memory usage: 83.5+ KB\n"
     ]
    }
   ],
   "source": [
    "\"\"\"\n",
    "data: https://www.kaggle.com/c/titanic\n",
    "\n",
    "ref:\n",
    "\n",
    "http://ahmedbesbes.com/how-to-score-08134-in-titanic-kaggle-challenge.html\n",
    "\n",
    "\"\"\"\n",
    "\n",
    "\n",
    "import pandas as pd\n",
    "import numpy as np\n",
    "\n",
    "from IPython.core.display import display\n",
    "\n",
    "%matplotlib inline\n",
    "\n",
    "data = pd.read_csv('train.csv',header=0)\n",
    "data.columns = data.columns.str.lower()\n",
    "data.set_index('passengerid',inplace=True)\n",
    "\n",
    "display(data.head(10))\n",
    "display(data.describe())\n",
    "\n",
    "data.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 97,
   "metadata": {},
   "outputs": [
    {
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Ym2++Wa+88soFX1u4cGGHdRaLRbNnz+7usgAA6BadhlYmMAcAAAAABEqn97Qy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G63ty0AAAAAAN3VraL1ySeflN1uV0NDg371q18pMTGxw+eGYcgwjB5d2OVyyeVySZLy8vI6FLo9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x56iMWLF9d8rUVERAQAm81GcHCwsR0cHIzNZqtS5ty5c6SmpjJmzBheffVVdu7c+VtXU0RE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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0xb07abe0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "%matplotlib inline\n",
    "import math\n",
    "\n",
    "\n",
    "import matplotlib\n",
    "import matplotlib.pyplot as plt\n",
    "\n",
    "matplotlib.style.use('ggplot')\n",
    "\n",
    "ncols=2\n",
    "plot_columns=list(data.columns)\n",
    "plot_columns.remove('name')\n",
    "plot_columns.remove('ticket')\n",
    "fig, axes = plt.subplots(nrows=math.ceil(len(plot_columns)/ncols), ncols=ncols,figsize=(16,24))\n",
    "\n",
    "\n",
    "for i,column in enumerate(plot_columns):\n",
    "    a=data[column].value_counts().sort_index().plot.bar(ax=axes[i//2][i%2],title=column)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 98,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "image/png": 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kQYMGacOGDSooKFBNTU2Ajw4AgL6lX79+evnll/XOO+/o5ptv1pw5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\n+v8A7A1qnoZXPPwAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x108e8b70>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, axes = plt.subplots(nrows=math.ceil(len(plot_columns)/ncols), ncols=ncols,figsize=(16,24))\n",
    "\n",
    "\n",
    "def round_data(df):\n",
    "    round_columns=['age','fare']\n",
    "    for col in round_columns:\n",
    "        df[col]=df[col].round()\n",
    "    return df\n",
    "\n",
    "def convert_to_str(df):\n",
    "    str_col=['cabin']\n",
    "    for col in str_col:\n",
    "        df[col]=[str(i) for i in df[col]]\n",
    "    return df\n",
    "\n",
    "def convert_sex_to_int(df):\n",
    "    df['sex']=[0 if i=='male' else 1 for i in df['sex']]\n",
    "    return df\n",
    "\n",
    "data.pipe(round_data).pipe(convert_to_str).pipe(convert_sex_to_int)\n",
    "\n",
    "    \n",
    "for i,column in enumerate(plot_columns):\n",
    "    data[column].value_counts().sort_index().plot.bar(ax=axes[i//2][i%2],title=column)\n",
    "    "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 99,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<matplotlib.figure.Figure at 0x1236c160>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<matplotlib.figure.Figure at 0xa098908>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<matplotlib.figure.Figure at 0xd906240>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<matplotlib.figure.Figure at 0xcb99cc0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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uMTGR9xM4B8Hy9ycpKaldy7VZ9Pv27dOOHTtUXFyspqYmNTQ0aPXq1aqvr1dLS4ucTqc8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\nRK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x11720c50>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "def draw_chart(col):\n",
    "    survived= data[data['survived']==1][col].value_counts()\n",
    "    dead=data[data['survived']==0][col].value_counts()\n",
    "    df=pd.DataFrame([survived,dead])\n",
    "    df.index=['survived','dead']\n",
    "    df.plot.bar(stacked=True,title=col)\n",
    "draw_chart('sex')\n",
    "draw_chart('pclass')\n",
    "draw_chart('sibsp')\n",
    "draw_chart('parch')\n",
    "draw_chart('embarked')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 100,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.legend.Legend at 0x111e1d30>"
      ]
     },
     "execution_count": 100,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<matplotlib.figure.Figure at 0x9a14cf8>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "col='age'\n",
    "survived_age= data[data['survived']==1][col].dropna()\n",
    "dead_age=data[data['survived']==0][col].dropna()\n",
    "plt.hist([survived_age,dead_age], stacked=True,bins = 40,label = ['survived','dead'])\n",
    "plt.legend()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 101,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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0ohviET11eNZOh7QXvV6PefPmWdw2ZcoU6PV6jBgxol2zEFmDRU90mz799NPrbnviiSdU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\nT0QkORY9EZHk/j+bMiBtKv9SngAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0xa983390>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "def parse_cabin(df):\n",
    "    df['cabin_parsed']=[i[0] if i!='nan' else 'nan' for i in df['cabin']]\n",
    "    df.drop('cabin',axis=1,inplace=True)\n",
    "    return df\n",
    "\n",
    "data.pipe(parse_cabin)\n",
    "draw_chart('cabin_parsed')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 102,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.legend.Legend at 0xd964518>"
      ]
     },
     "execution_count": 102,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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FMtfKZbaVy2wrV3+c7ZgxY/Zqu/063WLixIlZuXJlkmTlypWZNGlS5+OrVq1K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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x11b24a90>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(12,8))\n",
    "col='fare'\n",
    "survived_age= data[data['survived']==1][col].dropna()\n",
    "dead_age=data[data['survived']==0][col].dropna()\n",
    "plt.hist([survived_age,dead_age], stacked=True,bins = 40,label = ['survived','dead'])\n",
    "plt.legend()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 103,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "24.6673553719 00\n",
      "24.0463917526 10\n",
      "22.1724137931 01\n",
      "23.2166666667 11\n",
      "15.306122449 12\n",
      "13.1612903226 02\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<div>\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>embarked</th>\n",
       "      <th>cabin_parsed</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>22.000000</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>A/5 21171</td>\n",
       "      <td>7.0</td>\n",
       "      <td>S</td>\n",
       "      <td>nan</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>38.000000</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>PC 17599</td>\n",
       "      <td>71.0</td>\n",
       "      <td>C</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>1</td>\n",
       "      <td>26.000000</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>STON/O2. 3101282</td>\n",
       "      <td>8.0</td>\n",
       "      <td>S</td>\n",
       "      <td>nan</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>35.000000</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>113803</td>\n",
       "      <td>53.0</td>\n",
       "      <td>S</td>\n",
       "      <td>C</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>35.000000</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>373450</td>\n",
       "      <td>8.0</td>\n",
       "      <td>S</td>\n",
       "      <td>nan</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>24.667355</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>330877</td>\n",
       "      <td>8.0</td>\n",
       "      <td>Q</td>\n",
       "      <td>nan</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>54.000000</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>17463</td>\n",
       "      <td>52.0</td>\n",
       "      <td>S</td>\n",
       "      <td>E</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>2.000000</td>\n",
       "      <td>3</td>\n",
       "      <td>1</td>\n",
       "      <td>349909</td>\n",
       "      <td>21.0</td>\n",
       "      <td>S</td>\n",
       "      <td>nan</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>27.000000</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>347742</td>\n",
       "      <td>11.0</td>\n",
       "      <td>S</td>\n",
       "      <td>nan</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>14.000000</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>237736</td>\n",
       "      <td>30.0</td>\n",
       "      <td>C</td>\n",
       "      <td>nan</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>4.000000</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>PP 9549</td>\n",
       "      <td>17.0</td>\n",
       "      <td>S</td>\n",
       "      <td>G</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>58.000000</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>113783</td>\n",
       "      <td>27.0</td>\n",
       "      <td>S</td>\n",
       "      <td>C</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>20.000000</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>A/5. 2151</td>\n",
       "      <td>8.0</td>\n",
       "      <td>S</td>\n",
       "      <td>nan</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>39.000000</td>\n",
       "      <td>1</td>\n",
       "      <td>5</td>\n",
       "      <td>347082</td>\n",
       "      <td>31.0</td>\n",
       "      <td>S</td>\n",
       "      <td>nan</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>14.000000</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>350406</td>\n",
       "      <td>8.0</td>\n",
       "      <td>S</td>\n",
       "      <td>nan</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>55.000000</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>248706</td>\n",
       "      <td>16.0</td>\n",
       "      <td>S</td>\n",
       "      <td>nan</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>2.000000</td>\n",
       "      <td>4</td>\n",
       "      <td>1</td>\n",
       "      <td>382652</td>\n",
       "      <td>29.0</td>\n",
       "      <td>Q</td>\n",
       "      <td>nan</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>24.667355</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>244373</td>\n",
       "      <td>13.0</td>\n",
       "      <td>S</td>\n",
       "      <td>nan</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>31.000000</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>345763</td>\n",
       "      <td>18.0</td>\n",
       "      <td>S</td>\n",
       "      <td>nan</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>24.046392</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2649</td>\n",
       "      <td>7.0</td>\n",
       "      <td>C</td>\n",
       "      <td>nan</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>35.000000</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>239865</td>\n",
       "      <td>26.0</td>\n",
       "      <td>S</td>\n",
       "      <td>nan</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>34.000000</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>248698</td>\n",
       "      <td>13.0</td>\n",
       "      <td>S</td>\n",
       "      <td>D</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>15.000000</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>330923</td>\n",
       "      <td>8.0</td>\n",
       "      <td>Q</td>\n",
       "      <td>nan</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>28.000000</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>113788</td>\n",
       "      <td>36.0</td>\n",
       "      <td>S</td>\n",
       "      <td>A</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>8.000000</td>\n",
       "      <td>3</td>\n",
       "      <td>1</td>\n",
       "      <td>349909</td>\n",
       "      <td>21.0</td>\n",
       "      <td>S</td>\n",
       "      <td>nan</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>38.000000</td>\n",
       "      <td>1</td>\n",
       "      <td>5</td>\n",
       "      <td>347077</td>\n",
       "      <td>31.0</td>\n",
       "      <td>S</td>\n",
       "      <td>nan</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>24.667355</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2631</td>\n",
       "      <td>7.0</td>\n",
       "      <td>C</td>\n",
       "      <td>nan</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>19.000000</td>\n",
       "      <td>3</td>\n",
       "      <td>2</td>\n",
       "      <td>19950</td>\n",
       "      <td>263.0</td>\n",
       "      <td>S</td>\n",
       "      <td>C</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>24.046392</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>330959</td>\n",
       "      <td>8.0</td>\n",
       "      <td>Q</td>\n",
       "      <td>nan</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>24.667355</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>349216</td>\n",
       "      <td>8.0</td>\n",
       "      <td>S</td>\n",
       "      <td>nan</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>21.000000</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>28134</td>\n",
       "      <td>12.0</td>\n",
       "      <td>S</td>\n",
       "      <td>nan</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>48.000000</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>17466</td>\n",
       "      <td>26.0</td>\n",
       "      <td>S</td>\n",
       "      <td>D</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>15.306122</td>\n",
       "      <td>8</td>\n",
       "      <td>2</td>\n",
       "      <td>CA. 2343</td>\n",
       "      <td>70.0</td>\n",
       "      <td>S</td>\n",
       "      <td>nan</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>24.000000</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>233866</td>\n",
       "      <td>13.0</td>\n",
       "      <td>S</td>\n",
       "      <td>nan</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>42.000000</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>236852</td>\n",
       "      <td>13.0</td>\n",
       "      <td>S</td>\n",
       "      <td>nan</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>27.000000</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>SC/PARIS 2149</td>\n",
       "      <td>14.0</td>\n",
       "      <td>C</td>\n",
       "      <td>nan</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>31.000000</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>PC 17590</td>\n",
       "      <td>50.0</td>\n",
       "      <td>S</td>\n",
       "      <td>A</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>24.667355</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>345777</td>\n",
       "      <td>10.0</td>\n",
       "      <td>S</td>\n",
       "      <td>nan</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>4.000000</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>347742</td>\n",
       "      <td>11.0</td>\n",
       "      <td>S</td>\n",
       "      <td>nan</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>26.000000</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>349248</td>\n",
       "      <td>8.0</td>\n",
       "      <td>S</td>\n",
       "      <td>nan</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>47.000000</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>11751</td>\n",
       "      <td>53.0</td>\n",
       "      <td>S</td>\n",
       "      <td>D</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>33.000000</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>695</td>\n",
       "      <td>5.0</td>\n",
       "      <td>S</td>\n",
       "      <td>B</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>47.000000</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>345765</td>\n",
       "      <td>9.0</td>\n",
       "      <td>S</td>\n",
       "      <td>nan</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>28.000000</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>P/PP 3381</td>\n",
       "      <td>24.0</td>\n",
       "      <td>C</td>\n",
       "      <td>nan</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>15.000000</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2667</td>\n",
       "      <td>7.0</td>\n",
       "      <td>C</td>\n",
       "      <td>nan</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>20.000000</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>7534</td>\n",
       "      <td>10.0</td>\n",
       "      <td>S</td>\n",
       "      <td>nan</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>19.000000</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>349212</td>\n",
       "      <td>8.0</td>\n",
       "      <td>S</td>\n",
       "      <td>nan</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>24.667355</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>349217</td>\n",
       "      <td>8.0</td>\n",
       "      <td>S</td>\n",
       "      <td>nan</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>56.000000</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>11767</td>\n",
       "      <td>83.0</td>\n",
       "      <td>C</td>\n",
       "      <td>C</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>25.000000</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>230433</td>\n",
       "      <td>26.0</td>\n",
       "      <td>S</td>\n",
       "      <td>nan</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>33.000000</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>349257</td>\n",
       "      <td>8.0</td>\n",
       "      <td>S</td>\n",
       "      <td>nan</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>22.000000</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>7552</td>\n",
       "      <td>11.0</td>\n",
       "      <td>S</td>\n",
       "      <td>nan</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>28.000000</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>C.A./SOTON 34068</td>\n",
       "      <td>10.0</td>\n",
       "      <td>S</td>\n",
       "      <td>nan</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>25.000000</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>SOTON/OQ 392076</td>\n",
       "      <td>7.0</td>\n",
       "      <td>S</td>\n",
       "      <td>nan</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>39.000000</td>\n",
       "      <td>0</td>\n",
       "      <td>5</td>\n",
       "      <td>382652</td>\n",
       "      <td>29.0</td>\n",
       "      <td>Q</td>\n",
       "      <td>nan</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>27.000000</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>211536</td>\n",
       "      <td>13.0</td>\n",
       "      <td>S</td>\n",
       "      <td>nan</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>19.000000</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>112053</td>\n",
       "      <td>30.0</td>\n",
       "      <td>S</td>\n",
       "      <td>B</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>15.306122</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>W./C. 6607</td>\n",
       "      <td>23.0</td>\n",
       "      <td>S</td>\n",
       "      <td>nan</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>26.000000</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>111369</td>\n",
       "      <td>30.0</td>\n",
       "      <td>C</td>\n",
       "      <td>C</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>32.000000</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>370376</td>\n",
       "      <td>8.0</td>\n",
       "      <td>Q</td>\n",
       "      <td>nan</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  \\\n",
       "passengerid                                                           \n",
       "1                                      Braund, Mr. Owen Harris    0   \n",
       "2            Cumings, Mrs. John Bradley (Florence Briggs Th...    1   \n",
       "3                                       Heikkinen, Miss. Laina    1   \n",
       "4                 Futrelle, Mrs. Jacques Heath (Lily May Peel)    1   \n",
       "5                                     Allen, Mr. William Henry    0   \n",
       "6                                             Moran, Mr. James    0   \n",
       "7                                      McCarthy, Mr. Timothy J    0   \n",
       "8                               Palsson, Master. Gosta Leonard    0   \n",
       "9            Johnson, Mrs. Oscar W (Elisabeth Vilhelmina Berg)    1   \n",
       "10                         Nasser, Mrs. Nicholas (Adele Achem)    1   \n",
       "11                             Sandstrom, Miss. Marguerite Rut    1   \n",
       "12                                    Bonnell, Miss. Elizabeth    1   \n",
       "13                              Saundercock, Mr. William Henry    0   \n",
       "14                                 Andersson, Mr. Anders Johan    0   \n",
       "15                        Vestrom, Miss. Hulda Amanda Adolfina    1   \n",
       "16                            Hewlett, Mrs. (Mary D Kingcome)     1   \n",
       "17                                        Rice, Master. Eugene    0   \n",
       "18                                Williams, Mr. Charles Eugene    0   \n",
       "19           Vander Planke, Mrs. Julius (Emelia Maria Vande...    1   \n",
       "20                                     Masselmani, Mrs. Fatima    1   \n",
       "21                                        Fynney, Mr. Joseph J    0   \n",
       "22                                       Beesley, Mr. Lawrence    0   \n",
       "23                                 McGowan, Miss. Anna \"Annie\"    1   \n",
       "24                                Sloper, Mr. William Thompson    0   \n",
       "25                               Palsson, Miss. Torborg Danira    1   \n",
       "26           Asplund, Mrs. Carl Oscar (Selma Augusta Emilia...    1   \n",
       "27                                     Emir, Mr. Farred Chehab    0   \n",
       "28                              Fortune, Mr. Charles Alexander    0   \n",
       "29                               O'Dwyer, Miss. Ellen \"Nellie\"    1   \n",
       "30                                         Todoroff, Mr. Lalio    0   \n",
       "...                                                        ...  ...   \n",
       "862                                Giles, Mr. Frederick Edward    0   \n",
       "863          Swift, Mrs. Frederick Joel (Margaret Welles Ba...    1   \n",
       "864                          Sage, Miss. Dorothy Edith \"Dolly\"    1   \n",
       "865                                     Gill, Mr. John William    0   \n",
       "866                                   Bystrom, Mrs. (Karolina)    1   \n",
       "867                               Duran y More, Miss. Asuncion    1   \n",
       "868                       Roebling, Mr. Washington Augustus II    0   \n",
       "869                                van Melkebeke, Mr. Philemon    0   \n",
       "870                            Johnson, Master. Harold Theodor    0   \n",
       "871                                          Balkic, Mr. Cerin    0   \n",
       "872           Beckwith, Mrs. Richard Leonard (Sallie Monypeny)    1   \n",
       "873                                   Carlsson, Mr. Frans Olof    0   \n",
       "874                                Vander Cruyssen, Mr. Victor    0   \n",
       "875                      Abelson, Mrs. Samuel (Hannah Wizosky)    1   \n",
       "876                           Najib, Miss. Adele Kiamie \"Jane\"    1   \n",
       "877                              Gustafsson, Mr. Alfred Ossian    0   \n",
       "878                                       Petroff, Mr. Nedelio    0   \n",
       "879                                         Laleff, Mr. Kristo    0   \n",
       "880              Potter, Mrs. Thomas Jr (Lily Alexenia Wilson)    1   \n",
       "881               Shelley, Mrs. William (Imanita Parrish Hall)    1   \n",
       "882                                         Markun, Mr. Johann    0   \n",
       "883                               Dahlberg, Miss. Gerda Ulrika    1   \n",
       "884                              Banfield, Mr. Frederick James    0   \n",
       "885                                     Sutehall, Mr. Henry Jr    0   \n",
       "886                       Rice, Mrs. William (Margaret Norton)    1   \n",
       "887                                      Montvila, Rev. Juozas    0   \n",
       "888                               Graham, Miss. Margaret Edith    1   \n",
       "889                   Johnston, Miss. Catherine Helen \"Carrie\"    1   \n",
       "890                                      Behr, Mr. Karl Howell    0   \n",
       "891                                        Dooley, Mr. Patrick    0   \n",
       "\n",
       "                   age  sibsp  parch            ticket   fare embarked  \\\n",
       "passengerid                                                              \n",
       "1            22.000000      1      0         A/5 21171    7.0        S   \n",
       "2            38.000000      1      0          PC 17599   71.0        C   \n",
       "3            26.000000      0      0  STON/O2. 3101282    8.0        S   \n",
       "4            35.000000      1      0            113803   53.0        S   \n",
       "5            35.000000      0      0            373450    8.0        S   \n",
       "6            24.667355      0      0            330877    8.0        Q   \n",
       "7            54.000000      0      0             17463   52.0        S   \n",
       "8             2.000000      3      1            349909   21.0        S   \n",
       "9            27.000000      0      2            347742   11.0        S   \n",
       "10           14.000000      1      0            237736   30.0        C   \n",
       "11            4.000000      1      1           PP 9549   17.0        S   \n",
       "12           58.000000      0      0            113783   27.0        S   \n",
       "13           20.000000      0      0         A/5. 2151    8.0        S   \n",
       "14           39.000000      1      5            347082   31.0        S   \n",
       "15           14.000000      0      0            350406    8.0        S   \n",
       "16           55.000000      0      0            248706   16.0        S   \n",
       "17            2.000000      4      1            382652   29.0        Q   \n",
       "18           24.667355      0      0            244373   13.0        S   \n",
       "19           31.000000      1      0            345763   18.0        S   \n",
       "20           24.046392      0      0              2649    7.0        C   \n",
       "21           35.000000      0      0            239865   26.0        S   \n",
       "22           34.000000      0      0            248698   13.0        S   \n",
       "23           15.000000      0      0            330923    8.0        Q   \n",
       "24           28.000000      0      0            113788   36.0        S   \n",
       "25            8.000000      3      1            349909   21.0        S   \n",
       "26           38.000000      1      5            347077   31.0        S   \n",
       "27           24.667355      0      0              2631    7.0        C   \n",
       "28           19.000000      3      2             19950  263.0        S   \n",
       "29           24.046392      0      0            330959    8.0        Q   \n",
       "30           24.667355      0      0            349216    8.0        S   \n",
       "...                ...    ...    ...               ...    ...      ...   \n",
       "862          21.000000      1      0             28134   12.0        S   \n",
       "863          48.000000      0      0             17466   26.0        S   \n",
       "864          15.306122      8      2          CA. 2343   70.0        S   \n",
       "865          24.000000      0      0            233866   13.0        S   \n",
       "866          42.000000      0      0            236852   13.0        S   \n",
       "867          27.000000      1      0     SC/PARIS 2149   14.0        C   \n",
       "868          31.000000      0      0          PC 17590   50.0        S   \n",
       "869          24.667355      0      0            345777   10.0        S   \n",
       "870           4.000000      1      1            347742   11.0        S   \n",
       "871          26.000000      0      0            349248    8.0        S   \n",
       "872          47.000000      1      1             11751   53.0        S   \n",
       "873          33.000000      0      0               695    5.0        S   \n",
       "874          47.000000      0      0            345765    9.0        S   \n",
       "875          28.000000      1      0         P/PP 3381   24.0        C   \n",
       "876          15.000000      0      0              2667    7.0        C   \n",
       "877          20.000000      0      0              7534   10.0        S   \n",
       "878          19.000000      0      0            349212    8.0        S   \n",
       "879          24.667355      0      0            349217    8.0        S   \n",
       "880          56.000000      0      1             11767   83.0        C   \n",
       "881          25.000000      0      1            230433   26.0        S   \n",
       "882          33.000000      0      0            349257    8.0        S   \n",
       "883          22.000000      0      0              7552   11.0        S   \n",
       "884          28.000000      0      0  C.A./SOTON 34068   10.0        S   \n",
       "885          25.000000      0      0   SOTON/OQ 392076    7.0        S   \n",
       "886          39.000000      0      5            382652   29.0        Q   \n",
       "887          27.000000      0      0            211536   13.0        S   \n",
       "888          19.000000      0      0            112053   30.0        S   \n",
       "889          15.306122      1      2        W./C. 6607   23.0        S   \n",
       "890          26.000000      0      0            111369   30.0        C   \n",
       "891          32.000000      0      0            370376    8.0        Q   \n",
       "\n",
       "            cabin_parsed  \n",
       "passengerid               \n",
       "1                    nan  \n",
       "2                      C  \n",
       "3                    nan  \n",
       "4                      C  \n",
       "5                    nan  \n",
       "6                    nan  \n",
       "7                      E  \n",
       "8                    nan  \n",
       "9                    nan  \n",
       "10                   nan  \n",
       "11                     G  \n",
       "12                     C  \n",
       "13                   nan  \n",
       "14                   nan  \n",
       "15                   nan  \n",
       "16                   nan  \n",
       "17                   nan  \n",
       "18                   nan  \n",
       "19                   nan  \n",
       "20                   nan  \n",
       "21                   nan  \n",
       "22                     D  \n",
       "23                   nan  \n",
       "24                     A  \n",
       "25                   nan  \n",
       "26                   nan  \n",
       "27                   nan  \n",
       "28                     C  \n",
       "29                   nan  \n",
       "30                   nan  \n",
       "...                  ...  \n",
       "862                  nan  \n",
       "863                    D  \n",
       "864                  nan  \n",
       "865                  nan  \n",
       "866                  nan  \n",
       "867                  nan  \n",
       "868                    A  \n",
       "869                  nan  \n",
       "870                  nan  \n",
       "871                  nan  \n",
       "872                    D  \n",
       "873                    B  \n",
       "874                  nan  \n",
       "875                  nan  \n",
       "876                  nan  \n",
       "877                  nan  \n",
       "878                  nan  \n",
       "879                  nan  \n",
       "880                    C  \n",
       "881                  nan  \n",
       "882                  nan  \n",
       "883                  nan  \n",
       "884                  nan  \n",
       "885                  nan  \n",
       "886                  nan  \n",
       "887                  nan  \n",
       "888                    B  \n",
       "889                  nan  \n",
       "890                    C  \n",
       "891                  nan  \n",
       "\n",
       "[891 rows x 11 columns]"
      ]
     },
     "execution_count": 103,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# deal with missing data\n",
    "from sklearn.preprocessing import Imputer\n",
    "\n",
    "\n",
    "cached_mean_age={}\n",
    "\n",
    "\n",
    "def generate_key(i):\n",
    "    return str(i['sex'])+str(i['parch'])\n",
    "\n",
    "def impute_age(df):\n",
    "    new_age=[]\n",
    "    df['age'].fillna(-1,inplace=True)\n",
    "    for _,i in df.iterrows():\n",
    "        if i['age']!=-1:\n",
    "            new_age.append(i['age'])\n",
    "        else:\n",
    "            if generate_key(i) in cached_mean_age:\n",
    "                new_age.append(cached_mean_age[generate_key(i)])\n",
    "            else:\n",
    "                mean_age=data[(data['sex']==i['sex']) & (data['parch']==i['parch'])]['age'].dropna().mean()\n",
    "                if pd.isnull(mean_age):\n",
    "                    mean_age=data['age'].dropna().mean()\n",
    "                print(mean_age,generate_key(i))\n",
    "                cached_mean_age[generate_key(i)]=mean_age\n",
    "                new_age.append(mean_age)\n",
    "            \n",
    "    df['age']=new_age\n",
    "    return df\n",
    "\n",
    "def impute_embarked(df):\n",
    "    df['embarked'].fillna('S',inplace=True)\n",
    "    return df\n",
    "\n",
    "data.pipe(impute_age)\n",
    "data.pipe(impute_embarked)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 104,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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yKqJ2mzZtQnBwMCorK5GUlAQ/Pz+MGjVK7Vj9CoteAC0tLQgNDe2wjB/GkqOo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\nEtz/AaCkZ3DqUuVdAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0xd09bcc0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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UqcP58+dZu3YtAKmpuf9Y5s2bx/fff4+3t7dzmysp0YuI4d3xl4aE\nV7wFgJp16nH+7Gn8/AM4dvgg4x4ZBOTeZSokLKzQfaanpZGedpG7InJH6x3vu5/J40YVuF/Lli0J\nCAgAoHbt2pw5c4bKlfMWXNu8eTO7d++mU6dOAFy+fJnQ0FDatWvHyZMnee6552jbti3R0dEA1K1b\nl8cee4yOHTvSsaPrSy8r0YuI4Xl5eTl/tlo9sNvtOBwOqtWoxVtLP73uvtVq1OLgvj3cHdms0K9n\ntVrJyckBcpP0H8Xi4eGBzWbLt7/D4aB3795MnDgx33Pffvst69evZ8mSJXz55ZfMmDGDDz74gK1b\nt/LNN98wa9Ys1q1bh6en69Kz5uhFxFB8y5UjM7Pg20VVvf12UlOS2fPTTgBs2dkcO3wwX7sBQ4bz\n1oxpJCUmAHDlShafLnsfP39//AMC+WlHHADffLmSuyL+CsCtt97Kzz/nFk3797//Xai4y5QpQ3Z2\nNpA76l+1ahWJiYkApKSkcPr0aZKTk8nJyaFz58489dRT7N69m5ycHM6ePUuLFi147rnnuHjxIhkZ\nLrxdFhrRi4jBBJYP4i93NWbQ/fcS2TKaplGtr9muTBkvpkyfy+xpL5KRnobdbqNX/0HcXrN2nnZN\nW7UmOSmRcUMfwoEDCxbuvb8XABNfeo0ZL/6dy5cvU6nKrUx48VUAhg8fzvDhw1m+fDktW7YsVNz9\n+/cnJiaGBg0aMHfuXMaPH0+/fv1wOBx4enry8ssv4+Pjw9ixY53fFiZOnIjdbmfUqFGkpaXhcDgY\nOnQogYGBN/nbuzaL4+rpazc7e/asu0MokH3ofe4OwVSs73zh7hBMo9uy/S7ra1jDQOrcUr7ghiZW\nM6Ssu0PIJzMzE19f3zzbKlWqVKh9NaIXMYEV68e7rK9LFR+hnF/tghuaWUgtd0fgUpqjFxExOSV6\nERGTU6IXkbyMcdpOfufPnE5VoheRPCznT2Oz57g7DPkNm82Gh8fNp2udjBWRPLw3/ocsIKtiFbBY\n3B2OW3iEVy64UTFxOBx4eHjg4+Nz030USaL/8ccfWbx4MTk5ObRt25bu3bsXxcuISBGwOBz4bPjK\n3WG4lbVtZ3eH4FIuT/Q5OTksWrSI5557jpCQECZOnEhERARVqlRx9UuJyH/NaxDj7hBMxZjFhm+e\nyxP94cOHqVixIhUq5JYEbd68OXFxcaZI9PowuZbZPkwiRuXyRJ+cnExISIjzcUhICIcOHXL1y4jI\nb6wJae/uEEzFbIMQt52MjY2NJTY2FoBp06YV+lJed5o2bVrBjUTcIO4p439+xH1cvrwyODiYpKQk\n5+OkpCSCg4PztYuJiWHatGlKnkVgwoQJ7g5B5Jr0t+keLk/0NWrU4Ny5c8THx2Oz2diyZQsRERGu\nfhkRESkkl0/dWK1WHn74YV5++WVycnK45557uPXWW139MiIiUkhFMkd/9913c/fddxdF11IIMTFa\nHSTGpL9N9zBMPXoRESkaqnUjImJySvQiIianRC8iYnKqXikiRSI9Pf26z/v5+RVTJKKTsSXYQw89\nhOU6ZWTff//9YoxGJK+RI0disVhwOBwkJibi5+eHw+EgIyOD0NBQ5s2b5+4QSw0lehP4+OOPKV++\nPFFRUTgcDjZv3sylS5fo1q2bu0MTYeHChURERDiXXO/atYvdu3fz0EMPuTmy0kNz9Cbw008/0aFD\nB8qWLYuvry/t27dn27Zt7g5LBIAjR47kua6mUaNG7Nu3z40RlT5K9Cbg4eHBpk2byMnJIScnh02b\nNv2p246JuFJAQADLly8nPj6e+Ph4VqxYgb+/v7vDKlU0dWMC8fHxLFmyhAMHDgBQp04dBg0aRHh4\nuJsjE8k9KfvJJ5/wyy+/AFC3bl169+6tk7HFSIleRMTktLzSBM6ePcu7775Lamoq06dP58SJE2zf\nvp2ePXu6OzQRLl68yOeff87p06e5cuWKc/vkyZPdGFXpoolcE1iwYAEPPvggVqsVgNtuu40tW7a4\nOSqRXLNnz6Zy5crEx8fTu3dvwsLCqFGjhrvDKlWU6E3gypUr1KxZM882nYwVo0hLS6NNmzZYrVbq\n1avHiBEjdHvRYqapGxPw9/fn/Pnzzountm7dSlBQkJujEsnl6ZmbZoKCgti5cydBQUEkJye7OarS\nRSdjTeDXX39l4cKFHDhwgHLlyhEeHs7o0aMJCwtzd2gi7Nixg7p165KYmMjixYvJzMykd+/euvNc\nMVKiN4GcnBw8PDy4fPkyDoeDsmXLujskETEQTeSawMiRI1mwYAGHDh3Cx8fH3eGI5HH27FleeOEF\nxo0bB8CJEydYvny5m6MqXZToTWDWrFk0aNCAr7/+mscee4xFixaxf/9+d4clAmhVmBEo0ZuAt7c3\nzZs358knn+TVV1/l0qVLWqMshqFVYe6nVTcmsW/fPrZs2cKPP/5I9erVeeKJJ9wdkgigVWFGoJOx\nJjBy5EiqVatGs2bNiIiI0Dy9GIpWhbmfEr0JZGZm4uvr6+4wRPJYtWpVnsdXrlwhJyfHORDp0qWL\nO8IqlTR1U4J9/vnndOvWjY8++uiazz/88MPFHJHI/1y6dAnIXXVz5MgR57r5TZs2UbduXXeGVuoo\n0ZdglStXBqB69epujkQkv969ewPw0ksv8eqrrzqv7+jduzczZsxwZ2iljhJ9CXZ1hFS1alUlezGs\nxMREZxkEyC2JkJCQ4MaISh8lehP48MMPuXDhApGRkTRv3pyqVau6OyQRp6ioKJ555hmaNGkCQFxc\nHNHR0W6OqnTRyViTuHDhAlu2bOH7778nMzOT5s2bqx69GMbRo0edF/HVrVuX22+/3c0RlS5K9CZz\n8uRJPv/8c7Zs2cI///lPd4cjIgagRG8Cp0+fZsuWLWzbtg1/f3+aN29OZGQkgYGB7g5NRAxAid4E\nnn32WVq0aEHTpk0JDg52dzgiYjA6GVvC5eTkUKFCBTp16uTuUETEoFRZqITz8PAgLS0Nm83m7lBE\nxKA0dWMCCxcu5NixYzRu3DhPnRtdYi4ioKkbUwgKCiIoKAiHw+G87FxE5CqN6EVETE4jehOYMmXK\nNbfr5iMiAkr0pjBw4EDnz1euXGHbtm3O27aJiCjRm8DvC5rdcccdGs2LiJMSvQmkp6c7f87JyeHo\n0aNcuHDBjRGJiJEo0ZvA008/jcViweFw4OnpSVhYGI8++qi7wxIRg1CiN4H+/ftz11134evry6ef\nfsqxY8fw8vJyd1giYhC6MtYEVqxYga+vL/v372f37t20bt2ad999191hiYhBKNGbgIdH7tu4c+dO\n2rVrR5MmTVQSQUSclOhNIDg4mIULF7JlyxYaNWpEdnY2ug5ORK7SlbEmkJWVxY8//kjVqlW55ZZb\nSElJ4eTJkzRs2NDdoYmIASjRi4iYnKZuRERMToleRMTklOhFRExOiV5ExOSU6EVETO7/AXteQnVJ\nuuCKAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0xd09b668>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "all_title=''\n",
    "\n",
    "def add_title(df):\n",
    "    titles=[]\n",
    "    for i in df['name']:\n",
    "        title=i.split(',')[1].split('.')[0].strip()\n",
    "        if all_title:\n",
    "            if title not in all_title:\n",
    "                title='Unknown'\n",
    "        titles.append(title)\n",
    "    df['title']=titles\n",
    "    df.drop('name',axis=1,inplace=True)\n",
    "    return df\n",
    "\n",
    "data.pipe(add_title)\n",
    "all_title=set(list(data['title'].unique()))\n",
    "\n",
    "def add_family(df):\n",
    "    df['family']=df['sibsp']+df['parch']\n",
    "    return df\n",
    "\n",
    "data.pipe(add_family)\n",
    "\n",
    "draw_chart('family')\n",
    "draw_chart('title')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 105,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "37.0 14\n",
      "28.5116331857 09\n",
      "28.5116331857 19\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>survived</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>family</th>\n",
       "      <th>cabin_parsed_A</th>\n",
       "      <th>cabin_parsed_B</th>\n",
       "      <th>...</th>\n",
       "      <th>title_Rev</th>\n",
       "      <th>title_Sir</th>\n",
       "      <th>title_Unknown</th>\n",
       "      <th>title_the Countess</th>\n",
       "      <th>embarked_C</th>\n",
       "      <th>embarked_Q</th>\n",
       "      <th>embarked_S</th>\n",
       "      <th>pclass_1</th>\n",
       "      <th>pclass_2</th>\n",
       "      <th>pclass_3</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",
       "      <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>0</td>\n",
       "      <td>22.000000</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>A/5 21171</td>\n",
       "      <td>7.0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>38.000000</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>PC 17599</td>\n",
       "      <td>71.0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>26.000000</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>STON/O2. 3101282</td>\n",
       "      <td>8.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>35.000000</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>113803</td>\n",
       "      <td>53.0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>35.000000</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>373450</td>\n",
       "      <td>8.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>24.667355</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>330877</td>\n",
       "      <td>8.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>54.000000</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>17463</td>\n",
       "      <td>52.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2.000000</td>\n",
       "      <td>3</td>\n",
       "      <td>1</td>\n",
       "      <td>349909</td>\n",
       "      <td>21.0</td>\n",
       "      <td>4</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>27.000000</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>347742</td>\n",
       "      <td>11.0</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>14.000000</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>237736</td>\n",
       "      <td>30.0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>4.000000</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>PP 9549</td>\n",
       "      <td>17.0</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>58.000000</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>113783</td>\n",
       "      <td>27.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>20.000000</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>A/5. 2151</td>\n",
       "      <td>8.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>39.000000</td>\n",
       "      <td>1</td>\n",
       "      <td>5</td>\n",
       "      <td>347082</td>\n",
       "      <td>31.0</td>\n",
       "      <td>6</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>14.000000</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>350406</td>\n",
       "      <td>8.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>55.000000</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>248706</td>\n",
       "      <td>16.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2.000000</td>\n",
       "      <td>4</td>\n",
       "      <td>1</td>\n",
       "      <td>382652</td>\n",
       "      <td>29.0</td>\n",
       "      <td>5</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>24.667355</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>244373</td>\n",
       "      <td>13.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>31.000000</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>345763</td>\n",
       "      <td>18.0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>24.046392</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2649</td>\n",
       "      <td>7.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>35.000000</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>239865</td>\n",
       "      <td>26.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>34.000000</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>248698</td>\n",
       "      <td>13.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>15.000000</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>330923</td>\n",
       "      <td>8.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>28.000000</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>113788</td>\n",
       "      <td>36.0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>8.000000</td>\n",
       "      <td>3</td>\n",
       "      <td>1</td>\n",
       "      <td>349909</td>\n",
       "      <td>21.0</td>\n",
       "      <td>4</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>38.000000</td>\n",
       "      <td>1</td>\n",
       "      <td>5</td>\n",
       "      <td>347077</td>\n",
       "      <td>31.0</td>\n",
       "      <td>6</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>24.667355</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2631</td>\n",
       "      <td>7.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>19.000000</td>\n",
       "      <td>3</td>\n",
       "      <td>2</td>\n",
       "      <td>19950</td>\n",
       "      <td>263.0</td>\n",
       "      <td>5</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>24.046392</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>330959</td>\n",
       "      <td>8.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>30</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>24.667355</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>349216</td>\n",
       "      <td>8.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <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",
       "      <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>0</td>\n",
       "      <td>21.000000</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>28134</td>\n",
       "      <td>12.0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>863</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>48.000000</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>17466</td>\n",
       "      <td>26.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>864</th>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>15.306122</td>\n",
       "      <td>8</td>\n",
       "      <td>2</td>\n",
       "      <td>CA. 2343</td>\n",
       "      <td>70.0</td>\n",
       "      <td>10</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>865</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>24.000000</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>233866</td>\n",
       "      <td>13.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>866</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>42.000000</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>236852</td>\n",
       "      <td>13.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>867</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>27.000000</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>SC/PARIS 2149</td>\n",
       "      <td>14.0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>868</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>31.000000</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>PC 17590</td>\n",
       "      <td>50.0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>869</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>24.667355</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>345777</td>\n",
       "      <td>10.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>870</th>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>4.000000</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>347742</td>\n",
       "      <td>11.0</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>871</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>26.000000</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>349248</td>\n",
       "      <td>8.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>872</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>47.000000</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>11751</td>\n",
       "      <td>53.0</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>873</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>33.000000</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>695</td>\n",
       "      <td>5.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>874</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>47.000000</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>345765</td>\n",
       "      <td>9.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>875</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>28.000000</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>P/PP 3381</td>\n",
       "      <td>24.0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>876</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>15.000000</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2667</td>\n",
       "      <td>7.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>877</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>20.000000</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>7534</td>\n",
       "      <td>10.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>878</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>19.000000</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>349212</td>\n",
       "      <td>8.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>879</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>24.667355</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>349217</td>\n",
       "      <td>8.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>880</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>56.000000</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>11767</td>\n",
       "      <td>83.0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>881</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>25.000000</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>230433</td>\n",
       "      <td>26.0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>882</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>33.000000</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>349257</td>\n",
       "      <td>8.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>883</th>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>22.000000</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>7552</td>\n",
       "      <td>11.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>884</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>28.000000</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>C.A./SOTON 34068</td>\n",
       "      <td>10.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>885</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>25.000000</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>SOTON/OQ 392076</td>\n",
       "      <td>7.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>886</th>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>39.000000</td>\n",
       "      <td>0</td>\n",
       "      <td>5</td>\n",
       "      <td>382652</td>\n",
       "      <td>29.0</td>\n",
       "      <td>5</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>887</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>27.000000</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>211536</td>\n",
       "      <td>13.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>888</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>19.000000</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>112053</td>\n",
       "      <td>30.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>889</th>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>15.306122</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>W./C. 6607</td>\n",
       "      <td>23.0</td>\n",
       "      <td>3</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>890</th>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>26.000000</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>111369</td>\n",
       "      <td>30.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>891</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>32.000000</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>370376</td>\n",
       "      <td>8.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>891 rows × 41 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "             survived  sex        age  sibsp  parch            ticket   fare  \\\n",
       "passengerid                                                                    \n",
       "1                   0    0  22.000000      1      0         A/5 21171    7.0   \n",
       "2                   1    1  38.000000      1      0          PC 17599   71.0   \n",
       "3                   1    1  26.000000      0      0  STON/O2. 3101282    8.0   \n",
       "4                   1    1  35.000000      1      0            113803   53.0   \n",
       "5                   0    0  35.000000      0      0            373450    8.0   \n",
       "6                   0    0  24.667355      0      0            330877    8.0   \n",
       "7                   0    0  54.000000      0      0             17463   52.0   \n",
       "8                   0    0   2.000000      3      1            349909   21.0   \n",
       "9                   1    1  27.000000      0      2            347742   11.0   \n",
       "10                  1    1  14.000000      1      0            237736   30.0   \n",
       "11                  1    1   4.000000      1      1           PP 9549   17.0   \n",
       "12                  1    1  58.000000      0      0            113783   27.0   \n",
       "13                  0    0  20.000000      0      0         A/5. 2151    8.0   \n",
       "14                  0    0  39.000000      1      5            347082   31.0   \n",
       "15                  0    1  14.000000      0      0            350406    8.0   \n",
       "16                  1    1  55.000000      0      0            248706   16.0   \n",
       "17                  0    0   2.000000      4      1            382652   29.0   \n",
       "18                  1    0  24.667355      0      0            244373   13.0   \n",
       "19                  0    1  31.000000      1      0            345763   18.0   \n",
       "20                  1    1  24.046392      0      0              2649    7.0   \n",
       "21                  0    0  35.000000      0      0            239865   26.0   \n",
       "22                  1    0  34.000000      0      0            248698   13.0   \n",
       "23                  1    1  15.000000      0      0            330923    8.0   \n",
       "24                  1    0  28.000000      0      0            113788   36.0   \n",
       "25                  0    1   8.000000      3      1            349909   21.0   \n",
       "26                  1    1  38.000000      1      5            347077   31.0   \n",
       "27                  0    0  24.667355      0      0              2631    7.0   \n",
       "28                  0    0  19.000000      3      2             19950  263.0   \n",
       "29                  1    1  24.046392      0      0            330959    8.0   \n",
       "30                  0    0  24.667355      0      0            349216    8.0   \n",
       "...               ...  ...        ...    ...    ...               ...    ...   \n",
       "862                 0    0  21.000000      1      0             28134   12.0   \n",
       "863                 1    1  48.000000      0      0             17466   26.0   \n",
       "864                 0    1  15.306122      8      2          CA. 2343   70.0   \n",
       "865                 0    0  24.000000      0      0            233866   13.0   \n",
       "866                 1    1  42.000000      0      0            236852   13.0   \n",
       "867                 1    1  27.000000      1      0     SC/PARIS 2149   14.0   \n",
       "868                 0    0  31.000000      0      0          PC 17590   50.0   \n",
       "869                 0    0  24.667355      0      0            345777   10.0   \n",
       "870                 1    0   4.000000      1      1            347742   11.0   \n",
       "871                 0    0  26.000000      0      0            349248    8.0   \n",
       "872                 1    1  47.000000      1      1             11751   53.0   \n",
       "873                 0    0  33.000000      0      0               695    5.0   \n",
       "874                 0    0  47.000000      0      0            345765    9.0   \n",
       "875                 1    1  28.000000      1      0         P/PP 3381   24.0   \n",
       "876                 1    1  15.000000      0      0              2667    7.0   \n",
       "877                 0    0  20.000000      0      0              7534   10.0   \n",
       "878                 0    0  19.000000      0      0            349212    8.0   \n",
       "879                 0    0  24.667355      0      0            349217    8.0   \n",
       "880                 1    1  56.000000      0      1             11767   83.0   \n",
       "881                 1    1  25.000000      0      1            230433   26.0   \n",
       "882                 0    0  33.000000      0      0            349257    8.0   \n",
       "883                 0    1  22.000000      0      0              7552   11.0   \n",
       "884                 0    0  28.000000      0      0  C.A./SOTON 34068   10.0   \n",
       "885                 0    0  25.000000      0      0   SOTON/OQ 392076    7.0   \n",
       "886                 0    1  39.000000      0      5            382652   29.0   \n",
       "887                 0    0  27.000000      0      0            211536   13.0   \n",
       "888                 1    1  19.000000      0      0            112053   30.0   \n",
       "889                 0    1  15.306122      1      2        W./C. 6607   23.0   \n",
       "890                 1    0  26.000000      0      0            111369   30.0   \n",
       "891                 0    0  32.000000      0      0            370376    8.0   \n",
       "\n",
       "             family  cabin_parsed_A  cabin_parsed_B    ...     title_Rev  \\\n",
       "passengerid                                            ...                 \n",
       "1                 1               0               0    ...             0   \n",
       "2                 1               0               0    ...             0   \n",
       "3                 0               0               0    ...             0   \n",
       "4                 1               0               0    ...             0   \n",
       "5                 0               0               0    ...             0   \n",
       "6                 0               0               0    ...             0   \n",
       "7                 0               0               0    ...             0   \n",
       "8                 4               0               0    ...             0   \n",
       "9                 2               0               0    ...             0   \n",
       "10                1               0               0    ...             0   \n",
       "11                2               0               0    ...             0   \n",
       "12                0               0               0    ...             0   \n",
       "13                0               0               0    ...             0   \n",
       "14                6               0               0    ...             0   \n",
       "15                0               0               0    ...             0   \n",
       "16                0               0               0    ...             0   \n",
       "17                5               0               0    ...             0   \n",
       "18                0               0               0    ...             0   \n",
       "19                1               0               0    ...             0   \n",
       "20                0               0               0    ...             0   \n",
       "21                0               0               0    ...             0   \n",
       "22                0               0               0    ...             0   \n",
       "23                0               0               0    ...             0   \n",
       "24                0               1               0    ...             0   \n",
       "25                4               0               0    ...             0   \n",
       "26                6               0               0    ...             0   \n",
       "27                0               0               0    ...             0   \n",
       "28                5               0               0    ...             0   \n",
       "29                0               0               0    ...             0   \n",
       "30                0               0               0    ...             0   \n",
       "...             ...             ...             ...    ...           ...   \n",
       "862               1               0               0    ...             0   \n",
       "863               0               0               0    ...             0   \n",
       "864              10               0               0    ...             0   \n",
       "865               0               0               0    ...             0   \n",
       "866               0               0               0    ...             0   \n",
       "867               1               0               0    ...             0   \n",
       "868               0               1               0    ...             0   \n",
       "869               0               0               0    ...             0   \n",
       "870               2               0               0    ...             0   \n",
       "871               0               0               0    ...             0   \n",
       "872               2               0               0    ...             0   \n",
       "873               0               0               1    ...             0   \n",
       "874               0               0               0    ...             0   \n",
       "875               1               0               0    ...             0   \n",
       "876               0               0               0    ...             0   \n",
       "877               0               0               0    ...             0   \n",
       "878               0               0               0    ...             0   \n",
       "879               0               0               0    ...             0   \n",
       "880               1               0               0    ...             0   \n",
       "881               1               0               0    ...             0   \n",
       "882               0               0               0    ...             0   \n",
       "883               0               0               0    ...             0   \n",
       "884               0               0               0    ...             0   \n",
       "885               0               0               0    ...             0   \n",
       "886               5               0               0    ...             0   \n",
       "887               0               0               0    ...             1   \n",
       "888               0               0               1    ...             0   \n",
       "889               3               0               0    ...             0   \n",
       "890               0               0               0    ...             0   \n",
       "891               0               0               0    ...             0   \n",
       "\n",
       "             title_Sir  title_Unknown  title_the Countess  embarked_C  \\\n",
       "passengerid                                                             \n",
       "1                    0              0                   0           0   \n",
       "2                    0              0                   0           1   \n",
       "3                    0              0                   0           0   \n",
       "4                    0              0                   0           0   \n",
       "5                    0              0                   0           0   \n",
       "6                    0              0                   0           0   \n",
       "7                    0              0                   0           0   \n",
       "8                    0              0                   0           0   \n",
       "9                    0              0                   0           0   \n",
       "10                   0              0                   0           1   \n",
       "11                   0              0                   0           0   \n",
       "12                   0              0                   0           0   \n",
       "13                   0              0                   0           0   \n",
       "14                   0              0                   0           0   \n",
       "15                   0              0                   0           0   \n",
       "16                   0              0                   0           0   \n",
       "17                   0              0                   0           0   \n",
       "18                   0              0                   0           0   \n",
       "19                   0              0                   0           0   \n",
       "20                   0              0                   0           1   \n",
       "21                   0              0                   0           0   \n",
       "22                   0              0                   0           0   \n",
       "23                   0              0                   0           0   \n",
       "24                   0              0                   0           0   \n",
       "25                   0              0                   0           0   \n",
       "26                   0              0                   0           0   \n",
       "27                   0              0                   0           1   \n",
       "28                   0              0                   0           0   \n",
       "29                   0              0                   0           0   \n",
       "30                   0              0                   0           0   \n",
       "...                ...            ...                 ...         ...   \n",
       "862                  0              0                   0           0   \n",
       "863                  0              0                   0           0   \n",
       "864                  0              0                   0           0   \n",
       "865                  0              0                   0           0   \n",
       "866                  0              0                   0           0   \n",
       "867                  0              0                   0           1   \n",
       "868                  0              0                   0           0   \n",
       "869                  0              0                   0           0   \n",
       "870                  0              0                   0           0   \n",
       "871                  0              0                   0           0   \n",
       "872                  0              0                   0           0   \n",
       "873                  0              0                   0           0   \n",
       "874                  0              0                   0           0   \n",
       "875                  0              0                   0           1   \n",
       "876                  0              0                   0           1   \n",
       "877                  0              0                   0           0   \n",
       "878                  0              0                   0           0   \n",
       "879                  0              0                   0           0   \n",
       "880                  0              0                   0           1   \n",
       "881                  0              0                   0           0   \n",
       "882                  0              0                   0           0   \n",
       "883                  0              0                   0           0   \n",
       "884                  0              0                   0           0   \n",
       "885                  0              0                   0           0   \n",
       "886                  0              0                   0           0   \n",
       "887                  0              0                   0           0   \n",
       "888                  0              0                   0           0   \n",
       "889                  0              0                   0           0   \n",
       "890                  0              0                   0           1   \n",
       "891                  0              0                   0           0   \n",
       "\n",
       "             embarked_Q  embarked_S  pclass_1  pclass_2  pclass_3  \n",
       "passengerid                                                        \n",
       "1                     0           1         0         0         1  \n",
       "2                     0           0         1         0         0  \n",
       "3                     0           1         0         0         1  \n",
       "4                     0           1         1         0         0  \n",
       "5                     0           1         0         0         1  \n",
       "6                     1           0         0         0         1  \n",
       "7                     0           1         1         0         0  \n",
       "8                     0           1         0         0         1  \n",
       "9                     0           1         0         0         1  \n",
       "10                    0           0         0         1         0  \n",
       "11                    0           1         0         0         1  \n",
       "12                    0           1         1         0         0  \n",
       "13                    0           1         0         0         1  \n",
       "14                    0           1         0         0         1  \n",
       "15                    0           1         0         0         1  \n",
       "16                    0           1         0         1         0  \n",
       "17                    1           0         0         0         1  \n",
       "18                    0           1         0         1         0  \n",
       "19                    0           1         0         0         1  \n",
       "20                    0           0         0         0         1  \n",
       "21                    0           1         0         1         0  \n",
       "22                    0           1         0         1         0  \n",
       "23                    1           0         0         0         1  \n",
       "24                    0           1         1         0         0  \n",
       "25                    0           1         0         0         1  \n",
       "26                    0           1         0         0         1  \n",
       "27                    0           0         0         0         1  \n",
       "28                    0           1         1         0         0  \n",
       "29                    1           0         0         0         1  \n",
       "30                    0           1         0         0         1  \n",
       "...                 ...         ...       ...       ...       ...  \n",
       "862                   0           1         0         1         0  \n",
       "863                   0           1         1         0         0  \n",
       "864                   0           1         0         0         1  \n",
       "865                   0           1         0         1         0  \n",
       "866                   0           1         0         1         0  \n",
       "867                   0           0         0         1         0  \n",
       "868                   0           1         1         0         0  \n",
       "869                   0           1         0         0         1  \n",
       "870                   0           1         0         0         1  \n",
       "871                   0           1         0         0         1  \n",
       "872                   0           1         1         0         0  \n",
       "873                   0           1         1         0         0  \n",
       "874                   0           1         0         0         1  \n",
       "875                   0           0         0         1         0  \n",
       "876                   0           0         0         0         1  \n",
       "877                   0           1         0         0         1  \n",
       "878                   0           1         0         0         1  \n",
       "879                   0           1         0         0         1  \n",
       "880                   0           0         1         0         0  \n",
       "881                   0           1         0         1         0  \n",
       "882                   0           1         0         0         1  \n",
       "883                   0           1         0         0         1  \n",
       "884                   0           1         0         1         0  \n",
       "885                   0           1         0         0         1  \n",
       "886                   1           0         0         0         1  \n",
       "887                   0           1         0         1         0  \n",
       "888                   0           1         1         0         0  \n",
       "889                   0           1         0         0         1  \n",
       "890                   0           0         1         0         0  \n",
       "891                   1           0         0         0         1  \n",
       "\n",
       "[891 rows x 41 columns]"
      ]
     },
     "execution_count": 105,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# dummy code cabin, title, embarked\n",
    "\n",
    "csv1 = pd.read_csv('train.csv',header=0)\n",
    "csv1.columns = csv1.columns.str.lower()\n",
    "csv1.set_index('passengerid',inplace=True)\n",
    "\n",
    "csv2 = pd.read_csv('test.csv',header=0)\n",
    "csv2.columns = csv2.columns.str.lower()\n",
    "csv2.set_index('passengerid',inplace=True)\n",
    "all_csv = pd.concat([csv1.iloc[:,1:],csv2],axis=0,ignore_index=True)\n",
    "all_csv.pipe(round_data).pipe(convert_to_str).pipe(convert_sex_to_int).pipe(parse_cabin).pipe(add_title).pipe(impute_age)\n",
    "\n",
    "\n",
    "cached_col_candicates={}\n",
    "\n",
    "def convert_to_dummy(df):\n",
    "    columns=['cabin_parsed','title','embarked','pclass']\n",
    "    for col in columns:\n",
    "        \n",
    "        if col not in cached_col_candicates:\n",
    "            if col=='title':\n",
    "                cached_col_candicates[col]=pd.Series(data[col].unique()).append(pd.Series('Unknown'))\n",
    "            else:\n",
    "                cached_col_candicates[col]=pd.Series(data[col].unique())\n",
    "        dummy_code=pd.get_dummies(df[col].append(cached_col_candicates[col]),prefix=col).iloc[:-len(cached_col_candicates[col])]\n",
    "        for dummy_col in dummy_code:\n",
    "            df[dummy_col]=dummy_code[dummy_col]\n",
    "        df.drop(col,axis=1,inplace=True)\n",
    "    return df\n",
    "        \n",
    "data.pipe(convert_to_dummy)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 106,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Int64Index: 891 entries, 1 to 891\n",
      "Data columns (total 40 columns):\n",
      "survived              891 non-null int64\n",
      "sex                   891 non-null int64\n",
      "age                   891 non-null float64\n",
      "sibsp                 891 non-null int64\n",
      "parch                 891 non-null int64\n",
      "fare                  891 non-null float64\n",
      "family                891 non-null int64\n",
      "cabin_parsed_A        891 non-null uint8\n",
      "cabin_parsed_B        891 non-null uint8\n",
      "cabin_parsed_C        891 non-null uint8\n",
      "cabin_parsed_D        891 non-null uint8\n",
      "cabin_parsed_E        891 non-null uint8\n",
      "cabin_parsed_F        891 non-null uint8\n",
      "cabin_parsed_G        891 non-null uint8\n",
      "cabin_parsed_T        891 non-null uint8\n",
      "cabin_parsed_nan      891 non-null uint8\n",
      "title_Capt            891 non-null uint8\n",
      "title_Col             891 non-null uint8\n",
      "title_Don             891 non-null uint8\n",
      "title_Dr              891 non-null uint8\n",
      "title_Jonkheer        891 non-null uint8\n",
      "title_Lady            891 non-null uint8\n",
      "title_Major           891 non-null uint8\n",
      "title_Master          891 non-null uint8\n",
      "title_Miss            891 non-null uint8\n",
      "title_Mlle            891 non-null uint8\n",
      "title_Mme             891 non-null uint8\n",
      "title_Mr              891 non-null uint8\n",
      "title_Mrs             891 non-null uint8\n",
      "title_Ms              891 non-null uint8\n",
      "title_Rev             891 non-null uint8\n",
      "title_Sir             891 non-null uint8\n",
      "title_Unknown         891 non-null uint8\n",
      "title_the Countess    891 non-null uint8\n",
      "embarked_C            891 non-null uint8\n",
      "embarked_Q            891 non-null uint8\n",
      "embarked_S            891 non-null uint8\n",
      "pclass_1              891 non-null uint8\n",
      "pclass_2              891 non-null uint8\n",
      "pclass_3              891 non-null uint8\n",
      "dtypes: float64(2), int64(5), uint8(33)\n",
      "memory usage: 84.4 KB\n"
     ]
    }
   ],
   "source": [
    "# final data\n",
    "data.drop('ticket',axis=1,inplace=True)\n",
    "data.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 107,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(891, 10)"
      ]
     },
     "execution_count": 107,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
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      "text/plain": [
       "<matplotlib.figure.Figure at 0x120c4da0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import os\n",
    "\n",
    "from sklearn.feature_selection import SelectFromModel\n",
    "from sklearn.ensemble import RandomForestClassifier\n",
    "from sklearn.model_selection import cross_val_score,GridSearchCV\n",
    "from sklearn.externals import joblib\n",
    "\n",
    "select_model_filename= 'select_from.pkl'\n",
    "\n",
    "X=data.iloc[:,1:]\n",
    "y=data.iloc[:,0]\n",
    "\n",
    "clf = RandomForestClassifier(n_estimators=40,n_jobs=-1,random_state=1)\n",
    "clf=clf.fit(X, y)\n",
    "joblib.dump(clf,select_model_filename)\n",
    "\n",
    "    \n",
    "features = pd.DataFrame()\n",
    "features['feature'] = X.columns\n",
    "features['importance'] = clf.feature_importances_\n",
    "features.sort_values(by=['importance'], ascending=True, inplace=True)\n",
    "features.set_index('feature', inplace=True)\n",
    "features.plot(kind='barh', figsize=(20, 20))\n",
    "\n",
    "\n",
    "model = SelectFromModel(clf,'mean', prefit=True)\n",
    "train_reduced = model.transform(X)\n",
    "train_reduced.shape\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 108,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Best score: 0.8361391694725028\n",
      "Best parameters: {'max_depth': 8, 'max_features': 5, 'n_estimators': 40, 'n_jobs': -1, 'random_state': 1}\n"
     ]
    }
   ],
   "source": [
    "final_model_filename='final_model.pkl'\n",
    "\n",
    "random_forest=RandomForestClassifier()\n",
    "parameters = {'n_estimators':list(range(20,50,5)),'max_features':list(range(3,8)),'max_depth':list(range(4,16,2)),'n_jobs':[-1],'random_state':[1]}\n",
    "clf = GridSearchCV(random_forest, parameters,scoring='accuracy')\n",
    "\n",
    "clf.fit(train_reduced,y)\n",
    "joblib.dump(clf,final_model_filename)\n",
    "\n",
    "\n",
    "model=clf\n",
    "parameters=clf .best_params_\n",
    "\n",
    "print('Best score: {}'.format(clf.best_score_))\n",
    "print('Best parameters: {}'.format(clf.best_params_))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 109,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>sex</th>\n",
       "      <th>age</th>\n",
       "      <th>sibsp</th>\n",
       "      <th>parch</th>\n",
       "      <th>fare</th>\n",
       "      <th>family</th>\n",
       "      <th>cabin_parsed_A</th>\n",
       "      <th>cabin_parsed_B</th>\n",
       "      <th>cabin_parsed_C</th>\n",
       "      <th>cabin_parsed_D</th>\n",
       "      <th>...</th>\n",
       "      <th>title_Rev</th>\n",
       "      <th>title_Sir</th>\n",
       "      <th>title_Unknown</th>\n",
       "      <th>title_the Countess</th>\n",
       "      <th>embarked_C</th>\n",
       "      <th>embarked_Q</th>\n",
       "      <th>embarked_S</th>\n",
       "      <th>pclass_1</th>\n",
       "      <th>pclass_2</th>\n",
       "      <th>pclass_3</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",
       "      <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>892</th>\n",
       "      <td>0</td>\n",
       "      <td>34.000000</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>8.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
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       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>893</th>\n",
       "      <td>1</td>\n",
       "      <td>47.000000</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
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       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>894</th>\n",
       "      <td>0</td>\n",
       "      <td>62.000000</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>10.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>895</th>\n",
       "      <td>0</td>\n",
       "      <td>27.000000</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>9.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
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       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>896</th>\n",
       "      <td>1</td>\n",
       "      <td>22.000000</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>12.0</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>897</th>\n",
       "      <td>0</td>\n",
       "      <td>14.000000</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>9.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>898</th>\n",
       "      <td>1</td>\n",
       "      <td>30.000000</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>8.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>899</th>\n",
       "      <td>0</td>\n",
       "      <td>26.000000</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>29.0</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>900</th>\n",
       "      <td>1</td>\n",
       "      <td>18.000000</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>901</th>\n",
       "      <td>0</td>\n",
       "      <td>21.000000</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>24.0</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>902</th>\n",
       "      <td>0</td>\n",
       "      <td>24.667355</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>8.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>903</th>\n",
       "      <td>0</td>\n",
       "      <td>46.000000</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>26.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>904</th>\n",
       "      <td>1</td>\n",
       "      <td>23.000000</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>82.0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>905</th>\n",
       "      <td>0</td>\n",
       "      <td>63.000000</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>26.0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>906</th>\n",
       "      <td>1</td>\n",
       "      <td>47.000000</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>61.0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>907</th>\n",
       "      <td>1</td>\n",
       "      <td>24.000000</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>28.0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>908</th>\n",
       "      <td>0</td>\n",
       "      <td>35.000000</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>12.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>909</th>\n",
       "      <td>0</td>\n",
       "      <td>21.000000</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>910</th>\n",
       "      <td>1</td>\n",
       "      <td>27.000000</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>8.0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>911</th>\n",
       "      <td>1</td>\n",
       "      <td>45.000000</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>912</th>\n",
       "      <td>0</td>\n",
       "      <td>55.000000</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>59.0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>913</th>\n",
       "      <td>0</td>\n",
       "      <td>9.000000</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>3.0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>914</th>\n",
       "      <td>1</td>\n",
       "      <td>24.046392</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>32.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>915</th>\n",
       "      <td>0</td>\n",
       "      <td>21.000000</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>61.0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>916</th>\n",
       "      <td>1</td>\n",
       "      <td>48.000000</td>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "      <td>262.0</td>\n",
       "      <td>4</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>917</th>\n",
       "      <td>0</td>\n",
       "      <td>50.000000</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>14.0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>918</th>\n",
       "      <td>1</td>\n",
       "      <td>22.000000</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>62.0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>919</th>\n",
       "      <td>0</td>\n",
       "      <td>22.000000</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>920</th>\n",
       "      <td>0</td>\n",
       "      <td>41.000000</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>30.0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>921</th>\n",
       "      <td>0</td>\n",
       "      <td>24.667355</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>22.0</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <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",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1280</th>\n",
       "      <td>0</td>\n",
       "      <td>21.000000</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>8.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1281</th>\n",
       "      <td>0</td>\n",
       "      <td>6.000000</td>\n",
       "      <td>3</td>\n",
       "      <td>1</td>\n",
       "      <td>21.0</td>\n",
       "      <td>4</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1282</th>\n",
       "      <td>0</td>\n",
       "      <td>23.000000</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>94.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1283</th>\n",
       "      <td>1</td>\n",
       "      <td>51.000000</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>39.0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1284</th>\n",
       "      <td>0</td>\n",
       "      <td>13.000000</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>20.0</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1285</th>\n",
       "      <td>0</td>\n",
       "      <td>47.000000</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>10.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1286</th>\n",
       "      <td>0</td>\n",
       "      <td>29.000000</td>\n",
       "      <td>3</td>\n",
       "      <td>1</td>\n",
       "      <td>22.0</td>\n",
       "      <td>4</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1287</th>\n",
       "      <td>1</td>\n",
       "      <td>18.000000</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>60.0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1288</th>\n",
       "      <td>0</td>\n",
       "      <td>24.000000</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1289</th>\n",
       "      <td>1</td>\n",
       "      <td>48.000000</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>79.0</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1290</th>\n",
       "      <td>0</td>\n",
       "      <td>22.000000</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>8.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1291</th>\n",
       "      <td>0</td>\n",
       "      <td>31.000000</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>8.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1292</th>\n",
       "      <td>1</td>\n",
       "      <td>30.000000</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>165.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1293</th>\n",
       "      <td>0</td>\n",
       "      <td>38.000000</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>21.0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1294</th>\n",
       "      <td>1</td>\n",
       "      <td>22.000000</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>59.0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1295</th>\n",
       "      <td>0</td>\n",
       "      <td>17.000000</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>47.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1296</th>\n",
       "      <td>0</td>\n",
       "      <td>43.000000</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>28.0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1297</th>\n",
       "      <td>0</td>\n",
       "      <td>20.000000</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>14.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1298</th>\n",
       "      <td>0</td>\n",
       "      <td>23.000000</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>10.0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1299</th>\n",
       "      <td>0</td>\n",
       "      <td>50.000000</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>212.0</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1300</th>\n",
       "      <td>1</td>\n",
       "      <td>24.046392</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>8.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1301</th>\n",
       "      <td>1</td>\n",
       "      <td>3.000000</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>14.0</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1302</th>\n",
       "      <td>1</td>\n",
       "      <td>24.046392</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>8.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1303</th>\n",
       "      <td>1</td>\n",
       "      <td>37.000000</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>90.0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1304</th>\n",
       "      <td>1</td>\n",
       "      <td>28.000000</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>8.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1305</th>\n",
       "      <td>0</td>\n",
       "      <td>24.667355</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>8.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1306</th>\n",
       "      <td>1</td>\n",
       "      <td>39.000000</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>109.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1307</th>\n",
       "      <td>0</td>\n",
       "      <td>38.000000</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1308</th>\n",
       "      <td>0</td>\n",
       "      <td>24.667355</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>8.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1309</th>\n",
       "      <td>0</td>\n",
       "      <td>22.172414</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>22.0</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>418 rows × 39 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "             sex        age  sibsp  parch   fare  family  cabin_parsed_A  \\\n",
       "passengerid                                                                \n",
       "892            0  34.000000      0      0    8.0       0               0   \n",
       "893            1  47.000000      1      0    7.0       1               0   \n",
       "894            0  62.000000      0      0   10.0       0               0   \n",
       "895            0  27.000000      0      0    9.0       0               0   \n",
       "896            1  22.000000      1      1   12.0       2               0   \n",
       "897            0  14.000000      0      0    9.0       0               0   \n",
       "898            1  30.000000      0      0    8.0       0               0   \n",
       "899            0  26.000000      1      1   29.0       2               0   \n",
       "900            1  18.000000      0      0    7.0       0               0   \n",
       "901            0  21.000000      2      0   24.0       2               0   \n",
       "902            0  24.667355      0      0    8.0       0               0   \n",
       "903            0  46.000000      0      0   26.0       0               0   \n",
       "904            1  23.000000      1      0   82.0       1               0   \n",
       "905            0  63.000000      1      0   26.0       1               0   \n",
       "906            1  47.000000      1      0   61.0       1               0   \n",
       "907            1  24.000000      1      0   28.0       1               0   \n",
       "908            0  35.000000      0      0   12.0       0               0   \n",
       "909            0  21.000000      0      0    7.0       0               0   \n",
       "910            1  27.000000      1      0    8.0       1               0   \n",
       "911            1  45.000000      0      0    7.0       0               0   \n",
       "912            0  55.000000      1      0   59.0       1               0   \n",
       "913            0   9.000000      0      1    3.0       1               0   \n",
       "914            1  24.046392      0      0   32.0       0               0   \n",
       "915            0  21.000000      0      1   61.0       1               0   \n",
       "916            1  48.000000      1      3  262.0       4               0   \n",
       "917            0  50.000000      1      0   14.0       1               0   \n",
       "918            1  22.000000      0      1   62.0       1               0   \n",
       "919            0  22.000000      0      0    7.0       0               0   \n",
       "920            0  41.000000      0      0   30.0       0               1   \n",
       "921            0  24.667355      2      0   22.0       2               0   \n",
       "...          ...        ...    ...    ...    ...     ...             ...   \n",
       "1280           0  21.000000      0      0    8.0       0               0   \n",
       "1281           0   6.000000      3      1   21.0       4               0   \n",
       "1282           0  23.000000      0      0   94.0       0               0   \n",
       "1283           1  51.000000      0      1   39.0       1               0   \n",
       "1284           0  13.000000      0      2   20.0       2               0   \n",
       "1285           0  47.000000      0      0   10.0       0               0   \n",
       "1286           0  29.000000      3      1   22.0       4               0   \n",
       "1287           1  18.000000      1      0   60.0       1               0   \n",
       "1288           0  24.000000      0      0    7.0       0               0   \n",
       "1289           1  48.000000      1      1   79.0       2               0   \n",
       "1290           0  22.000000      0      0    8.0       0               0   \n",
       "1291           0  31.000000      0      0    8.0       0               0   \n",
       "1292           1  30.000000      0      0  165.0       0               0   \n",
       "1293           0  38.000000      1      0   21.0       1               0   \n",
       "1294           1  22.000000      0      1   59.0       1               0   \n",
       "1295           0  17.000000      0      0   47.0       0               0   \n",
       "1296           0  43.000000      1      0   28.0       1               0   \n",
       "1297           0  20.000000      0      0   14.0       0               0   \n",
       "1298           0  23.000000      1      0   10.0       1               0   \n",
       "1299           0  50.000000      1      1  212.0       2               0   \n",
       "1300           1  24.046392      0      0    8.0       0               0   \n",
       "1301           1   3.000000      1      1   14.0       2               0   \n",
       "1302           1  24.046392      0      0    8.0       0               0   \n",
       "1303           1  37.000000      1      0   90.0       1               0   \n",
       "1304           1  28.000000      0      0    8.0       0               0   \n",
       "1305           0  24.667355      0      0    8.0       0               0   \n",
       "1306           1  39.000000      0      0  109.0       0               0   \n",
       "1307           0  38.000000      0      0    7.0       0               0   \n",
       "1308           0  24.667355      0      0    8.0       0               0   \n",
       "1309           0  22.172414      1      1   22.0       2               0   \n",
       "\n",
       "             cabin_parsed_B  cabin_parsed_C  cabin_parsed_D    ...     \\\n",
       "passengerid                                                    ...      \n",
       "892                       0               0               0    ...      \n",
       "893                       0               0               0    ...      \n",
       "894                       0               0               0    ...      \n",
       "895                       0               0               0    ...      \n",
       "896                       0               0               0    ...      \n",
       "897                       0               0               0    ...      \n",
       "898                       0               0               0    ...      \n",
       "899                       0               0               0    ...      \n",
       "900                       0               0               0    ...      \n",
       "901                       0               0               0    ...      \n",
       "902                       0               0               0    ...      \n",
       "903                       0               0               0    ...      \n",
       "904                       1               0               0    ...      \n",
       "905                       0               0               0    ...      \n",
       "906                       0               0               0    ...      \n",
       "907                       0               0               0    ...      \n",
       "908                       0               0               0    ...      \n",
       "909                       0               0               0    ...      \n",
       "910                       0               0               0    ...      \n",
       "911                       0               0               0    ...      \n",
       "912                       0               0               0    ...      \n",
       "913                       0               0               0    ...      \n",
       "914                       0               0               0    ...      \n",
       "915                       0               0               0    ...      \n",
       "916                       1               0               0    ...      \n",
       "917                       0               0               0    ...      \n",
       "918                       1               0               0    ...      \n",
       "919                       0               0               0    ...      \n",
       "920                       0               0               0    ...      \n",
       "921                       0               0               0    ...      \n",
       "...                     ...             ...             ...    ...      \n",
       "1280                      0               0               0    ...      \n",
       "1281                      0               0               0    ...      \n",
       "1282                      1               0               0    ...      \n",
       "1283                      0               0               1    ...      \n",
       "1284                      0               0               0    ...      \n",
       "1285                      0               0               0    ...      \n",
       "1286                      0               0               0    ...      \n",
       "1287                      0               1               0    ...      \n",
       "1288                      0               0               0    ...      \n",
       "1289                      1               0               0    ...      \n",
       "1290                      0               0               0    ...      \n",
       "1291                      0               0               0    ...      \n",
       "1292                      0               1               0    ...      \n",
       "1293                      0               0               0    ...      \n",
       "1294                      0               0               0    ...      \n",
       "1295                      0               0               0    ...      \n",
       "1296                      0               0               1    ...      \n",
       "1297                      0               0               1    ...      \n",
       "1298                      0               0               0    ...      \n",
       "1299                      0               1               0    ...      \n",
       "1300                      0               0               0    ...      \n",
       "1301                      0               0               0    ...      \n",
       "1302                      0               0               0    ...      \n",
       "1303                      0               1               0    ...      \n",
       "1304                      0               0               0    ...      \n",
       "1305                      0               0               0    ...      \n",
       "1306                      0               1               0    ...      \n",
       "1307                      0               0               0    ...      \n",
       "1308                      0               0               0    ...      \n",
       "1309                      0               0               0    ...      \n",
       "\n",
       "             title_Rev  title_Sir  title_Unknown  title_the Countess  \\\n",
       "passengerid                                                            \n",
       "892                  0          0              0                   0   \n",
       "893                  0          0              0                   0   \n",
       "894                  0          0              0                   0   \n",
       "895                  0          0              0                   0   \n",
       "896                  0          0              0                   0   \n",
       "897                  0          0              0                   0   \n",
       "898                  0          0              0                   0   \n",
       "899                  0          0              0                   0   \n",
       "900                  0          0              0                   0   \n",
       "901                  0          0              0                   0   \n",
       "902                  0          0              0                   0   \n",
       "903                  0          0              0                   0   \n",
       "904                  0          0              0                   0   \n",
       "905                  0          0              0                   0   \n",
       "906                  0          0              0                   0   \n",
       "907                  0          0              0                   0   \n",
       "908                  0          0              0                   0   \n",
       "909                  0          0              0                   0   \n",
       "910                  0          0              0                   0   \n",
       "911                  0          0              0                   0   \n",
       "912                  0          0              0                   0   \n",
       "913                  0          0              0                   0   \n",
       "914                  0          0              0                   0   \n",
       "915                  0          0              0                   0   \n",
       "916                  0          0              0                   0   \n",
       "917                  0          0              0                   0   \n",
       "918                  0          0              0                   0   \n",
       "919                  0          0              0                   0   \n",
       "920                  0          0              0                   0   \n",
       "921                  0          0              0                   0   \n",
       "...                ...        ...            ...                 ...   \n",
       "1280                 0          0              0                   0   \n",
       "1281                 0          0              0                   0   \n",
       "1282                 0          0              0                   0   \n",
       "1283                 0          0              0                   0   \n",
       "1284                 0          0              0                   0   \n",
       "1285                 0          0              0                   0   \n",
       "1286                 0          0              0                   0   \n",
       "1287                 0          0              0                   0   \n",
       "1288                 0          0              0                   0   \n",
       "1289                 0          0              0                   0   \n",
       "1290                 0          0              0                   0   \n",
       "1291                 0          0              0                   0   \n",
       "1292                 0          0              0                   0   \n",
       "1293                 0          0              0                   0   \n",
       "1294                 0          0              0                   0   \n",
       "1295                 0          0              0                   0   \n",
       "1296                 0          0              0                   0   \n",
       "1297                 0          0              0                   0   \n",
       "1298                 0          0              0                   0   \n",
       "1299                 0          0              0                   0   \n",
       "1300                 0          0              0                   0   \n",
       "1301                 0          0              0                   0   \n",
       "1302                 0          0              0                   0   \n",
       "1303                 0          0              0                   0   \n",
       "1304                 0          0              0                   0   \n",
       "1305                 0          0              0                   0   \n",
       "1306                 0          0              1                   0   \n",
       "1307                 0          0              0                   0   \n",
       "1308                 0          0              0                   0   \n",
       "1309                 0          0              0                   0   \n",
       "\n",
       "             embarked_C  embarked_Q  embarked_S  pclass_1  pclass_2  pclass_3  \n",
       "passengerid                                                                    \n",
       "892                   0           1           0         0         0         1  \n",
       "893                   0           0           1         0         0         1  \n",
       "894                   0           1           0         0         1         0  \n",
       "895                   0           0           1         0         0         1  \n",
       "896                   0           0           1         0         0         1  \n",
       "897                   0           0           1         0         0         1  \n",
       "898                   0           1           0         0         0         1  \n",
       "899                   0           0           1         0         1         0  \n",
       "900                   1           0           0         0         0         1  \n",
       "901                   0           0           1         0         0         1  \n",
       "902                   0           0           1         0         0         1  \n",
       "903                   0           0           1         1         0         0  \n",
       "904                   0           0           1         1         0         0  \n",
       "905                   0           0           1         0         1         0  \n",
       "906                   0           0           1         1         0         0  \n",
       "907                   1           0           0         0         1         0  \n",
       "908                   0           1           0         0         1         0  \n",
       "909                   1           0           0         0         0         1  \n",
       "910                   0           0           1         0         0         1  \n",
       "911                   1           0           0         0         0         1  \n",
       "912                   1           0           0         1         0         0  \n",
       "913                   0           0           1         0         0         1  \n",
       "914                   0           0           1         1         0         0  \n",
       "915                   1           0           0         1         0         0  \n",
       "916                   1           0           0         1         0         0  \n",
       "917                   0           0           1         0         0         1  \n",
       "918                   1           0           0         1         0         0  \n",
       "919                   1           0           0         0         0         1  \n",
       "920                   0           0           1         1         0         0  \n",
       "921                   1           0           0         0         0         1  \n",
       "...                 ...         ...         ...       ...       ...       ...  \n",
       "1280                  0           1           0         0         0         1  \n",
       "1281                  0           0           1         0         0         1  \n",
       "1282                  0           0           1         1         0         0  \n",
       "1283                  0           0           1         1         0         0  \n",
       "1284                  0           0           1         0         0         1  \n",
       "1285                  0           0           1         0         1         0  \n",
       "1286                  0           0           1         0         0         1  \n",
       "1287                  0           0           1         1         0         0  \n",
       "1288                  0           1           0         0         0         1  \n",
       "1289                  1           0           0         1         0         0  \n",
       "1290                  0           0           1         0         0         1  \n",
       "1291                  0           1           0         0         0         1  \n",
       "1292                  0           0           1         1         0         0  \n",
       "1293                  0           0           1         0         1         0  \n",
       "1294                  1           0           0         1         0         0  \n",
       "1295                  0           0           1         1         0         0  \n",
       "1296                  1           0           0         1         0         0  \n",
       "1297                  1           0           0         0         1         0  \n",
       "1298                  0           0           1         0         1         0  \n",
       "1299                  1           0           0         1         0         0  \n",
       "1300                  0           1           0         0         0         1  \n",
       "1301                  0           0           1         0         0         1  \n",
       "1302                  0           1           0         0         0         1  \n",
       "1303                  0           1           0         1         0         0  \n",
       "1304                  0           0           1         0         0         1  \n",
       "1305                  0           0           1         0         0         1  \n",
       "1306                  1           0           0         1         0         0  \n",
       "1307                  0           0           1         0         0         1  \n",
       "1308                  0           0           1         0         0         1  \n",
       "1309                  1           0           0         0         0         1  \n",
       "\n",
       "[418 rows x 39 columns]"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "test = pd.read_csv('test.csv',header=0)\n",
    "test.columns = test.columns.str.lower()\n",
    "test.set_index('passengerid',inplace=True)\n",
    "\n",
    "\n",
    "test.pipe(round_data).pipe(convert_to_str).pipe(convert_sex_to_int).pipe(parse_cabin).pipe(impute_age).pipe(impute_embarked).pipe(add_title).pipe(add_family).pipe(convert_to_dummy)\n",
    "test.drop('ticket',axis=1,inplace=True)\n",
    "\n",
    "display(test)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 110,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Int64Index: 418 entries, 892 to 1309\n",
      "Data columns (total 39 columns):\n",
      "sex                   418 non-null int64\n",
      "age                   418 non-null float64\n",
      "sibsp                 418 non-null int64\n",
      "parch                 418 non-null int64\n",
      "fare                  418 non-null float64\n",
      "family                418 non-null int64\n",
      "cabin_parsed_A        418 non-null uint8\n",
      "cabin_parsed_B        418 non-null uint8\n",
      "cabin_parsed_C        418 non-null uint8\n",
      "cabin_parsed_D        418 non-null uint8\n",
      "cabin_parsed_E        418 non-null uint8\n",
      "cabin_parsed_F        418 non-null uint8\n",
      "cabin_parsed_G        418 non-null uint8\n",
      "cabin_parsed_T        418 non-null uint8\n",
      "cabin_parsed_nan      418 non-null uint8\n",
      "title_Capt            418 non-null uint8\n",
      "title_Col             418 non-null uint8\n",
      "title_Don             418 non-null uint8\n",
      "title_Dr              418 non-null uint8\n",
      "title_Jonkheer        418 non-null uint8\n",
      "title_Lady            418 non-null uint8\n",
      "title_Major           418 non-null uint8\n",
      "title_Master          418 non-null uint8\n",
      "title_Miss            418 non-null uint8\n",
      "title_Mlle            418 non-null uint8\n",
      "title_Mme             418 non-null uint8\n",
      "title_Mr              418 non-null uint8\n",
      "title_Mrs             418 non-null uint8\n",
      "title_Ms              418 non-null uint8\n",
      "title_Rev             418 non-null uint8\n",
      "title_Sir             418 non-null uint8\n",
      "title_Unknown         418 non-null uint8\n",
      "title_the Countess    418 non-null uint8\n",
      "embarked_C            418 non-null uint8\n",
      "embarked_Q            418 non-null uint8\n",
      "embarked_S            418 non-null uint8\n",
      "pclass_1              418 non-null uint8\n",
      "pclass_2              418 non-null uint8\n",
      "pclass_3              418 non-null uint8\n",
      "dtypes: float64(2), int64(4), uint8(33)\n",
      "memory usage: 36.3 KB\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Int64Index: 891 entries, 1 to 891\n",
      "Data columns (total 40 columns):\n",
      "survived              891 non-null int64\n",
      "sex                   891 non-null int64\n",
      "age                   891 non-null float64\n",
      "sibsp                 891 non-null int64\n",
      "parch                 891 non-null int64\n",
      "fare                  891 non-null float64\n",
      "family                891 non-null int64\n",
      "cabin_parsed_A        891 non-null uint8\n",
      "cabin_parsed_B        891 non-null uint8\n",
      "cabin_parsed_C        891 non-null uint8\n",
      "cabin_parsed_D        891 non-null uint8\n",
      "cabin_parsed_E        891 non-null uint8\n",
      "cabin_parsed_F        891 non-null uint8\n",
      "cabin_parsed_G        891 non-null uint8\n",
      "cabin_parsed_T        891 non-null uint8\n",
      "cabin_parsed_nan      891 non-null uint8\n",
      "title_Capt            891 non-null uint8\n",
      "title_Col             891 non-null uint8\n",
      "title_Don             891 non-null uint8\n",
      "title_Dr              891 non-null uint8\n",
      "title_Jonkheer        891 non-null uint8\n",
      "title_Lady            891 non-null uint8\n",
      "title_Major           891 non-null uint8\n",
      "title_Master          891 non-null uint8\n",
      "title_Miss            891 non-null uint8\n",
      "title_Mlle            891 non-null uint8\n",
      "title_Mme             891 non-null uint8\n",
      "title_Mr              891 non-null uint8\n",
      "title_Mrs             891 non-null uint8\n",
      "title_Ms              891 non-null uint8\n",
      "title_Rev             891 non-null uint8\n",
      "title_Sir             891 non-null uint8\n",
      "title_Unknown         891 non-null uint8\n",
      "title_the Countess    891 non-null uint8\n",
      "embarked_C            891 non-null uint8\n",
      "embarked_Q            891 non-null uint8\n",
      "embarked_S            891 non-null uint8\n",
      "pclass_1              891 non-null uint8\n",
      "pclass_2              891 non-null uint8\n",
      "pclass_3              891 non-null uint8\n",
      "dtypes: float64(2), int64(5), uint8(33)\n",
      "memory usage: 84.4 KB\n"
     ]
    }
   ],
   "source": [
    "def impute_fare(df):\n",
    "    df['fare'].fillna(-1,inplace=True)\n",
    "    return Imputer(missing_values=-1,strategy=\"median\",axis=0)\n",
    "\n",
    "test.pipe(impute_fare)\n",
    "\n",
    "    \n",
    "test.info()\n",
    "data.info()\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 111,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "(418, 10)\n",
      "[0 0 0 0 1 0 0 0 1 0 0 0 1 0 1 1 0 0 0 0 0 1 1 0 1 0 1 0 1 0 0 0 1 1 1 0 1\n",
      " 0 0 0 0 0 0 1 1 0 0 0 1 1 0 0 1 1 0 0 0 0 0 1 0 0 0 1 1 1 1 0 0 1 1 0 0 1\n",
      " 1 0 0 1 0 1 1 0 0 0 0 0 1 1 1 1 1 0 1 0 0 0 1 0 1 0 1 0 0 0 1 0 0 0 0 0 0\n",
      " 1 1 1 1 0 0 1 0 1 1 0 1 0 0 1 0 1 0 0 0 1 0 0 0 0 0 0 1 0 0 1 0 0 0 0 0 0\n",
      " 0 0 1 0 0 1 0 0 1 1 1 1 1 1 1 0 0 1 0 0 1 0 0 0 0 0 0 1 1 0 1 1 0 0 1 0 1\n",
      " 0 1 0 0 0 0 0 1 0 1 0 1 1 0 1 1 1 1 1 0 0 0 0 1 0 0 0 0 1 0 0 1 0 1 0 1 0\n",
      " 1 0 1 1 0 1 0 0 0 1 0 0 1 0 0 0 1 1 1 1 0 0 1 0 1 0 1 1 1 0 1 0 0 0 0 0 1\n",
      " 0 0 0 1 1 0 0 0 0 1 0 0 0 1 1 0 1 0 0 0 0 0 1 1 0 1 0 0 0 0 0 0 0 0 1 0 0\n",
      " 1 0 0 0 0 0 0 0 1 1 1 1 0 0 0 0 0 0 1 1 0 0 0 0 0 0 0 0 1 0 1 0 0 0 1 0 0\n",
      " 1 0 0 0 0 0 1 0 0 0 1 1 1 0 1 0 1 1 0 0 0 1 0 1 0 0 0 0 1 1 0 1 0 0 0 1 0\n",
      " 0 1 0 0 1 1 0 0 0 0 0 0 1 1 0 1 0 0 0 0 0 1 1 0 0 1 0 1 0 0 1 0 1 0 0 0 0\n",
      " 0 1 1 1 1 0 0 1 0 0 1]\n"
     ]
    }
   ],
   "source": [
    "select_model=joblib.load(select_model_filename)\n",
    "model = SelectFromModel(select_model,'mean', prefit=True)\n",
    "test_reduced = model.transform(test)\n",
    "test_reduced.shape\n",
    "print(test_reduced.shape)\n",
    "\n",
    "final_model=joblib.load(final_model_filename)\n",
    "predict_y=final_model.predict(test_reduced)\n",
    "print(predict_y)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 112,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "result=pd.DataFrame()\n",
    "result['PassengerId']=test.index\n",
    "result['Survived']=predict_y\n",
    "\n",
    "result.to_csv('result.csv',index=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 113,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "2017-07-24 12:04:50.043929\n"
     ]
    }
   ],
   "source": [
    "import datetime\n",
    "print(datetime.datetime.now())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  }
 ],
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