Data set description + Data processing .ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "be9a65f1",
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import numpy as np\n",
    "import random as rnd\n",
    "\n",
    "import matplotlib.pyplot as plt\n",
    "import seaborn as sns\n",
    "\n",
    "%matplotlib inline"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "e730bc8a",
   "metadata": {},
   "outputs": [],
   "source": [
    "titanic = pd.read_csv('./Data/train.csv')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "1eecf4bb",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>PassengerId</th>\n",
       "      <th>Survived</th>\n",
       "      <th>Pclass</th>\n",
       "      <th>Name</th>\n",
       "      <th>Sex</th>\n",
       "      <th>Age</th>\n",
       "      <th>SibSp</th>\n",
       "      <th>Parch</th>\n",
       "      <th>Ticket</th>\n",
       "      <th>Fare</th>\n",
       "      <th>Cabin</th>\n",
       "      <th>Embarked</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>Braund, Mr. Owen Harris</td>\n",
       "      <td>male</td>\n",
       "      <td>22.0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>A/5 21171</td>\n",
       "      <td>7.2500</td>\n",
       "      <td>NaN</td>\n",
       "      <td>S</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>Cumings, Mrs. John Bradley (Florence Briggs Th...</td>\n",
       "      <td>female</td>\n",
       "      <td>38.0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>PC 17599</td>\n",
       "      <td>71.2833</td>\n",
       "      <td>C85</td>\n",
       "      <td>C</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>3</td>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "      <td>Heikkinen, Miss. Laina</td>\n",
       "      <td>female</td>\n",
       "      <td>26.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>STON/O2. 3101282</td>\n",
       "      <td>7.9250</td>\n",
       "      <td>NaN</td>\n",
       "      <td>S</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>4</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>Futrelle, Mrs. Jacques Heath (Lily May Peel)</td>\n",
       "      <td>female</td>\n",
       "      <td>35.0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>113803</td>\n",
       "      <td>53.1000</td>\n",
       "      <td>C123</td>\n",
       "      <td>S</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>5</td>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>Allen, Mr. William Henry</td>\n",
       "      <td>male</td>\n",
       "      <td>35.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>373450</td>\n",
       "      <td>8.0500</td>\n",
       "      <td>NaN</td>\n",
       "      <td>S</td>\n",
       "    </tr>\n",
       "    <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",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>886</th>\n",
       "      <td>887</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>Montvila, Rev. Juozas</td>\n",
       "      <td>male</td>\n",
       "      <td>27.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>211536</td>\n",
       "      <td>13.0000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>S</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>887</th>\n",
       "      <td>888</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>Graham, Miss. Margaret Edith</td>\n",
       "      <td>female</td>\n",
       "      <td>19.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>112053</td>\n",
       "      <td>30.0000</td>\n",
       "      <td>B42</td>\n",
       "      <td>S</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>888</th>\n",
       "      <td>889</td>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>Johnston, Miss. Catherine Helen \"Carrie\"</td>\n",
       "      <td>female</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>W./C. 6607</td>\n",
       "      <td>23.4500</td>\n",
       "      <td>NaN</td>\n",
       "      <td>S</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>889</th>\n",
       "      <td>890</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>Behr, Mr. Karl Howell</td>\n",
       "      <td>male</td>\n",
       "      <td>26.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>111369</td>\n",
       "      <td>30.0000</td>\n",
       "      <td>C148</td>\n",
       "      <td>C</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>890</th>\n",
       "      <td>891</td>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>Dooley, Mr. Patrick</td>\n",
       "      <td>male</td>\n",
       "      <td>32.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>370376</td>\n",
       "      <td>7.7500</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Q</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>891 rows × 12 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "     PassengerId  Survived  Pclass  \\\n",
       "0              1         0       3   \n",
       "1              2         1       1   \n",
       "2              3         1       3   \n",
       "3              4         1       1   \n",
       "4              5         0       3   \n",
       "..           ...       ...     ...   \n",
       "886          887         0       2   \n",
       "887          888         1       1   \n",
       "888          889         0       3   \n",
       "889          890         1       1   \n",
       "890          891         0       3   \n",
       "\n",
       "                                                  Name     Sex   Age  SibSp  \\\n",
       "0                              Braund, Mr. Owen Harris    male  22.0      1   \n",
       "1    Cumings, Mrs. John Bradley (Florence Briggs Th...  female  38.0      1   \n",
       "2                               Heikkinen, Miss. Laina  female  26.0      0   \n",
       "3         Futrelle, Mrs. Jacques Heath (Lily May Peel)  female  35.0      1   \n",
       "4                             Allen, Mr. William Henry    male  35.0      0   \n",
       "..                                                 ...     ...   ...    ...   \n",
       "886                              Montvila, Rev. Juozas    male  27.0      0   \n",
       "887                       Graham, Miss. Margaret Edith  female  19.0      0   \n",
       "888           Johnston, Miss. Catherine Helen \"Carrie\"  female   NaN      1   \n",
       "889                              Behr, Mr. Karl Howell    male  26.0      0   \n",
       "890                                Dooley, Mr. Patrick    male  32.0      0   \n",
       "\n",
       "     Parch            Ticket     Fare Cabin Embarked  \n",
       "0        0         A/5 21171   7.2500   NaN        S  \n",
       "1        0          PC 17599  71.2833   C85        C  \n",
       "2        0  STON/O2. 3101282   7.9250   NaN        S  \n",
       "3        0            113803  53.1000  C123        S  \n",
       "4        0            373450   8.0500   NaN        S  \n",
       "..     ...               ...      ...   ...      ...  \n",
       "886      0            211536  13.0000   NaN        S  \n",
       "887      0            112053  30.0000   B42        S  \n",
       "888      2        W./C. 6607  23.4500   NaN        S  \n",
       "889      0            111369  30.0000  C148        C  \n",
       "890      0            370376   7.7500   NaN        Q  \n",
       "\n",
       "[891 rows x 12 columns]"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "titanic"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "35801722",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array(['PassengerId', 'Survived', 'Pclass', 'Name', 'Sex', 'Age', 'SibSp',\n",
       "       'Parch', 'Ticket', 'Fare', 'Cabin', 'Embarked'], dtype=object)"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "titanic.columns.values"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "82603f21",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>PassengerId</th>\n",
       "      <th>Survived</th>\n",
       "      <th>Pclass</th>\n",
       "      <th>Age</th>\n",
       "      <th>SibSp</th>\n",
       "      <th>Parch</th>\n",
       "      <th>Fare</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>891.000000</td>\n",
       "      <td>891.000000</td>\n",
       "      <td>891.000000</td>\n",
       "      <td>714.000000</td>\n",
       "      <td>891.000000</td>\n",
       "      <td>891.000000</td>\n",
       "      <td>891.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>446.000000</td>\n",
       "      <td>0.383838</td>\n",
       "      <td>2.308642</td>\n",
       "      <td>29.699118</td>\n",
       "      <td>0.523008</td>\n",
       "      <td>0.381594</td>\n",
       "      <td>32.204208</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>std</th>\n",
       "      <td>257.353842</td>\n",
       "      <td>0.486592</td>\n",
       "      <td>0.836071</td>\n",
       "      <td>14.526497</td>\n",
       "      <td>1.102743</td>\n",
       "      <td>0.806057</td>\n",
       "      <td>49.693429</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.420000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25%</th>\n",
       "      <td>223.500000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>2.000000</td>\n",
       "      <td>20.125000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>7.910400</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50%</th>\n",
       "      <td>446.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>3.000000</td>\n",
       "      <td>28.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>14.454200</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75%</th>\n",
       "      <td>668.500000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>3.000000</td>\n",
       "      <td>38.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>31.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>max</th>\n",
       "      <td>891.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>3.000000</td>\n",
       "      <td>80.000000</td>\n",
       "      <td>8.000000</td>\n",
       "      <td>6.000000</td>\n",
       "      <td>512.329200</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "       PassengerId    Survived      Pclass         Age       SibSp  \\\n",
       "count   891.000000  891.000000  891.000000  714.000000  891.000000   \n",
       "mean    446.000000    0.383838    2.308642   29.699118    0.523008   \n",
       "std     257.353842    0.486592    0.836071   14.526497    1.102743   \n",
       "min       1.000000    0.000000    1.000000    0.420000    0.000000   \n",
       "25%     223.500000    0.000000    2.000000   20.125000    0.000000   \n",
       "50%     446.000000    0.000000    3.000000   28.000000    0.000000   \n",
       "75%     668.500000    1.000000    3.000000   38.000000    1.000000   \n",
       "max     891.000000    1.000000    3.000000   80.000000    8.000000   \n",
       "\n",
       "            Parch        Fare  \n",
       "count  891.000000  891.000000  \n",
       "mean     0.381594   32.204208  \n",
       "std      0.806057   49.693429  \n",
       "min      0.000000    0.000000  \n",
       "25%      0.000000    7.910400  \n",
       "50%      0.000000   14.454200  \n",
       "75%      0.000000   31.000000  \n",
       "max      6.000000  512.329200  "
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "titanic.describe()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "007214fd",
   "metadata": {},
   "source": [
    "# Understanding each column\n",
    "PassengerId - Unique ID for each passenger  <br>\n",
    "Survived - Survival (0 = No; 1 = Yes)   <br>\n",
    "Pclass - Passenger Class (1 = 1st; 2 = 2nd; 3 = 3rd)   <br>\n",
    "Name - Passenger Name   <br>\n",
    "Sex - Passenger Sex   <br>\n",
    "Age - Passenger Age   <br>\n",
    "SibSp - Number of Siblings/Spouses Aboard   <br>\n",
    "Parch - Number of Parents/Children Aboard   <br>\n",
    "ticket - Ticket Number   <br>\n",
    "Fare - Passenger Fare   <br>\n",
    "Cabin - Cabin number    <br>\n",
    "embarked - Port of Embarkation (C = Cherbourg; Q = Queenstown; S = Southampton)   <br>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "16619738",
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 891 entries, 0 to 890\n",
      "Data columns (total 12 columns):\n",
      " #   Column       Non-Null Count  Dtype  \n",
      "---  ------       --------------  -----  \n",
      " 0   PassengerId  891 non-null    int64  \n",
      " 1   Survived     891 non-null    int64  \n",
      " 2   Pclass       891 non-null    int64  \n",
      " 3   Name         891 non-null    object \n",
      " 4   Sex          891 non-null    object \n",
      " 5   Age          714 non-null    float64\n",
      " 6   SibSp        891 non-null    int64  \n",
      " 7   Parch        891 non-null    int64  \n",
      " 8   Ticket       891 non-null    object \n",
      " 9   Fare         891 non-null    float64\n",
      " 10  Cabin        204 non-null    object \n",
      " 11  Embarked     889 non-null    object \n",
      "dtypes: float64(2), int64(5), object(5)\n",
      "memory usage: 83.7+ KB\n"
     ]
    }
   ],
   "source": [
    "titanic.info()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "7f80652c",
   "metadata": {},
   "source": [
    "# Filling null data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "ab35c2b4",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th># of Null</th>\n",
       "      <th>Percentage</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>Cabin</th>\n",
       "      <td>687</td>\n",
       "      <td>0.771</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Age</th>\n",
       "      <td>177</td>\n",
       "      <td>0.199</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Embarked</th>\n",
       "      <td>2</td>\n",
       "      <td>0.002</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>PassengerId</th>\n",
       "      <td>0</td>\n",
       "      <td>0.000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Survived</th>\n",
       "      <td>0</td>\n",
       "      <td>0.000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Pclass</th>\n",
       "      <td>0</td>\n",
       "      <td>0.000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Name</th>\n",
       "      <td>0</td>\n",
       "      <td>0.000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Sex</th>\n",
       "      <td>0</td>\n",
       "      <td>0.000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>SibSp</th>\n",
       "      <td>0</td>\n",
       "      <td>0.000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Parch</th>\n",
       "      <td>0</td>\n",
       "      <td>0.000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Ticket</th>\n",
       "      <td>0</td>\n",
       "      <td>0.000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Fare</th>\n",
       "      <td>0</td>\n",
       "      <td>0.000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "             # of Null  Percentage\n",
       "Cabin              687       0.771\n",
       "Age                177       0.199\n",
       "Embarked             2       0.002\n",
       "PassengerId          0       0.000\n",
       "Survived             0       0.000\n",
       "Pclass               0       0.000\n",
       "Name                 0       0.000\n",
       "Sex                  0       0.000\n",
       "SibSp                0       0.000\n",
       "Parch                0       0.000\n",
       "Ticket               0       0.000\n",
       "Fare                 0       0.000"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Finding missing data\n",
    "miss_total = titanic.isnull().sum().sort_values(ascending=False)\n",
    "percentage = miss_total/891 \n",
    "percent_2 = (round(percentage, 3)).sort_values(ascending=False)\n",
    "miss_total = pd.concat([miss_total, percent_2], axis=1, keys=['# of Null', 'Percentage'])\n",
    "miss_total"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "44b9813f",
   "metadata": {},
   "outputs": [],
   "source": [
    "# drop Cabin column since it has huge amount of missing data, and it does not affect suvival (TODO: discuss this? Is there more about this attribute?)\n",
    "titanic = titanic.drop(['Cabin'], axis=1)\n",
    "# titanic.Cabin.unique()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "f1f05ec6",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>PassengerId</th>\n",
       "      <th>Survived</th>\n",
       "      <th>Pclass</th>\n",
       "      <th>Name</th>\n",
       "      <th>Sex</th>\n",
       "      <th>Age</th>\n",
       "      <th>SibSp</th>\n",
       "      <th>Parch</th>\n",
       "      <th>Ticket</th>\n",
       "      <th>Fare</th>\n",
       "      <th>Embarked</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>Braund, Mr. Owen Harris</td>\n",
       "      <td>male</td>\n",
       "      <td>22.0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>A/5 21171</td>\n",
       "      <td>7.2500</td>\n",
       "      <td>S</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>Cumings, Mrs. John Bradley (Florence Briggs Th...</td>\n",
       "      <td>female</td>\n",
       "      <td>38.0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>PC 17599</td>\n",
       "      <td>71.2833</td>\n",
       "      <td>C</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>3</td>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "      <td>Heikkinen, Miss. Laina</td>\n",
       "      <td>female</td>\n",
       "      <td>26.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>STON/O2. 3101282</td>\n",
       "      <td>7.9250</td>\n",
       "      <td>S</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>4</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>Futrelle, Mrs. Jacques Heath (Lily May Peel)</td>\n",
       "      <td>female</td>\n",
       "      <td>35.0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>113803</td>\n",
       "      <td>53.1000</td>\n",
       "      <td>S</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>5</td>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>Allen, Mr. William Henry</td>\n",
       "      <td>male</td>\n",
       "      <td>35.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>373450</td>\n",
       "      <td>8.0500</td>\n",
       "      <td>S</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>886</th>\n",
       "      <td>887</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>Montvila, Rev. Juozas</td>\n",
       "      <td>male</td>\n",
       "      <td>27.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>211536</td>\n",
       "      <td>13.0000</td>\n",
       "      <td>S</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>887</th>\n",
       "      <td>888</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>Graham, Miss. Margaret Edith</td>\n",
       "      <td>female</td>\n",
       "      <td>19.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>112053</td>\n",
       "      <td>30.0000</td>\n",
       "      <td>S</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>888</th>\n",
       "      <td>889</td>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>Johnston, Miss. Catherine Helen \"Carrie\"</td>\n",
       "      <td>female</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>W./C. 6607</td>\n",
       "      <td>23.4500</td>\n",
       "      <td>S</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>889</th>\n",
       "      <td>890</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>Behr, Mr. Karl Howell</td>\n",
       "      <td>male</td>\n",
       "      <td>26.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>111369</td>\n",
       "      <td>30.0000</td>\n",
       "      <td>C</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>890</th>\n",
       "      <td>891</td>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>Dooley, Mr. Patrick</td>\n",
       "      <td>male</td>\n",
       "      <td>32.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>370376</td>\n",
       "      <td>7.7500</td>\n",
       "      <td>Q</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>891 rows × 11 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "     PassengerId  Survived  Pclass  \\\n",
       "0              1         0       3   \n",
       "1              2         1       1   \n",
       "2              3         1       3   \n",
       "3              4         1       1   \n",
       "4              5         0       3   \n",
       "..           ...       ...     ...   \n",
       "886          887         0       2   \n",
       "887          888         1       1   \n",
       "888          889         0       3   \n",
       "889          890         1       1   \n",
       "890          891         0       3   \n",
       "\n",
       "                                                  Name     Sex   Age  SibSp  \\\n",
       "0                              Braund, Mr. Owen Harris    male  22.0      1   \n",
       "1    Cumings, Mrs. John Bradley (Florence Briggs Th...  female  38.0      1   \n",
       "2                               Heikkinen, Miss. Laina  female  26.0      0   \n",
       "3         Futrelle, Mrs. Jacques Heath (Lily May Peel)  female  35.0      1   \n",
       "4                             Allen, Mr. William Henry    male  35.0      0   \n",
       "..                                                 ...     ...   ...    ...   \n",
       "886                              Montvila, Rev. Juozas    male  27.0      0   \n",
       "887                       Graham, Miss. Margaret Edith  female  19.0      0   \n",
       "888           Johnston, Miss. Catherine Helen \"Carrie\"  female   NaN      1   \n",
       "889                              Behr, Mr. Karl Howell    male  26.0      0   \n",
       "890                                Dooley, Mr. Patrick    male  32.0      0   \n",
       "\n",
       "     Parch            Ticket     Fare Embarked  \n",
       "0        0         A/5 21171   7.2500        S  \n",
       "1        0          PC 17599  71.2833        C  \n",
       "2        0  STON/O2. 3101282   7.9250        S  \n",
       "3        0            113803  53.1000        S  \n",
       "4        0            373450   8.0500        S  \n",
       "..     ...               ...      ...      ...  \n",
       "886      0            211536  13.0000        S  \n",
       "887      0            112053  30.0000        S  \n",
       "888      2        W./C. 6607  23.4500        S  \n",
       "889      0            111369  30.0000        C  \n",
       "890      0            370376   7.7500        Q  \n",
       "\n",
       "[891 rows x 11 columns]"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "titanic"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "3e3e9e3e",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "titanic['Age'].plot.hist(grid=True, bins=20, rwidth=0.9,\n",
    "                   color='#607c8e')\n",
    "plt.title('Age disdribution before filling missing values')\n",
    "plt.xlabel('Age')\n",
    "plt.ylabel('Frequency')\n",
    "plt.grid(axis='y', alpha=0.75)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "593c0eca",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "29.69911764705882"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "titanic['Age'].mean()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "407c2214",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Embarked       2\n",
       "PassengerId    0\n",
       "Survived       0\n",
       "Pclass         0\n",
       "Name           0\n",
       "Sex            0\n",
       "Age            0\n",
       "SibSp          0\n",
       "Parch          0\n",
       "Ticket         0\n",
       "Fare           0\n",
       "dtype: int64"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Replace missing age by average(Age)\n",
    "titanic['Age']=titanic['Age'].fillna(titanic['Age'].mean())\n",
    "miss_total = titanic.isnull().sum().sort_values(ascending=False)\n",
    "miss_total"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "51b8887c",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "titanic['Age'].plot.hist(grid=True, bins=20, rwidth=0.9,\n",
    "                   color='#607c8e')\n",
    "plt.title('Age disdribution after filling missing values')\n",
    "plt.xlabel('Age')\n",
    "plt.ylabel('Frequency')\n",
    "plt.grid(axis='y', alpha=0.75)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "ed42c7bb",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "count     889\n",
       "unique      3\n",
       "top         S\n",
       "freq      644\n",
       "Name: Embarked, dtype: object"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Finally, the two missing value of embarked \n",
    "titanic['Embarked'].describe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "b349b12b",
   "metadata": {},
   "outputs": [],
   "source": [
    "# replace missing value with the most frequent one: S\n",
    "titanic['Embarked'] = titanic['Embarked'].fillna('S')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "faafbeef",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "PassengerId    0\n",
       "Survived       0\n",
       "Pclass         0\n",
       "Name           0\n",
       "Sex            0\n",
       "Age            0\n",
       "SibSp          0\n",
       "Parch          0\n",
       "Ticket         0\n",
       "Fare           0\n",
       "Embarked       0\n",
       "dtype: int64"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Now no missing values!\n",
    "miss_total = titanic.isnull().sum().sort_values(ascending=False)\n",
    "miss_total"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "c36cd56a",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>PassengerId</th>\n",
       "      <th>Survived</th>\n",
       "      <th>Pclass</th>\n",
       "      <th>Name</th>\n",
       "      <th>Sex</th>\n",
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       "      <td>Braund, Mr. Owen Harris</td>\n",
       "      <td>male</td>\n",
       "      <td>22.000000</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>A/5 21171</td>\n",
       "      <td>7.2500</td>\n",
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       "      <td>Cumings, Mrs. John Bradley (Florence Briggs Th...</td>\n",
       "      <td>female</td>\n",
       "      <td>38.000000</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>PC 17599</td>\n",
       "      <td>71.2833</td>\n",
       "      <td>C</td>\n",
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       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>3</td>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "      <td>Heikkinen, Miss. Laina</td>\n",
       "      <td>female</td>\n",
       "      <td>26.000000</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>STON/O2. 3101282</td>\n",
       "      <td>7.9250</td>\n",
       "      <td>S</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>4</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>Futrelle, Mrs. Jacques Heath (Lily May Peel)</td>\n",
       "      <td>female</td>\n",
       "      <td>35.000000</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>113803</td>\n",
       "      <td>53.1000</td>\n",
       "      <td>S</td>\n",
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       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>5</td>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>Allen, Mr. William Henry</td>\n",
       "      <td>male</td>\n",
       "      <td>35.000000</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>373450</td>\n",
       "      <td>8.0500</td>\n",
       "      <td>S</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>886</th>\n",
       "      <td>887</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>Montvila, Rev. Juozas</td>\n",
       "      <td>male</td>\n",
       "      <td>27.000000</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>211536</td>\n",
       "      <td>13.0000</td>\n",
       "      <td>S</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>887</th>\n",
       "      <td>888</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>Graham, Miss. Margaret Edith</td>\n",
       "      <td>female</td>\n",
       "      <td>19.000000</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>112053</td>\n",
       "      <td>30.0000</td>\n",
       "      <td>S</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>888</th>\n",
       "      <td>889</td>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>Johnston, Miss. Catherine Helen \"Carrie\"</td>\n",
       "      <td>female</td>\n",
       "      <td>29.699118</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>W./C. 6607</td>\n",
       "      <td>23.4500</td>\n",
       "      <td>S</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>889</th>\n",
       "      <td>890</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>Behr, Mr. Karl Howell</td>\n",
       "      <td>male</td>\n",
       "      <td>26.000000</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>111369</td>\n",
       "      <td>30.0000</td>\n",
       "      <td>C</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>890</th>\n",
       "      <td>891</td>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>Dooley, Mr. Patrick</td>\n",
       "      <td>male</td>\n",
       "      <td>32.000000</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>370376</td>\n",
       "      <td>7.7500</td>\n",
       "      <td>Q</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>891 rows × 11 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "     PassengerId  Survived  Pclass  \\\n",
       "0              1         0       3   \n",
       "1              2         1       1   \n",
       "2              3         1       3   \n",
       "3              4         1       1   \n",
       "4              5         0       3   \n",
       "..           ...       ...     ...   \n",
       "886          887         0       2   \n",
       "887          888         1       1   \n",
       "888          889         0       3   \n",
       "889          890         1       1   \n",
       "890          891         0       3   \n",
       "\n",
       "                                                  Name     Sex        Age  \\\n",
       "0                              Braund, Mr. Owen Harris    male  22.000000   \n",
       "1    Cumings, Mrs. John Bradley (Florence Briggs Th...  female  38.000000   \n",
       "2                               Heikkinen, Miss. Laina  female  26.000000   \n",
       "3         Futrelle, Mrs. Jacques Heath (Lily May Peel)  female  35.000000   \n",
       "4                             Allen, Mr. William Henry    male  35.000000   \n",
       "..                                                 ...     ...        ...   \n",
       "886                              Montvila, Rev. Juozas    male  27.000000   \n",
       "887                       Graham, Miss. Margaret Edith  female  19.000000   \n",
       "888           Johnston, Miss. Catherine Helen \"Carrie\"  female  29.699118   \n",
       "889                              Behr, Mr. Karl Howell    male  26.000000   \n",
       "890                                Dooley, Mr. Patrick    male  32.000000   \n",
       "\n",
       "     SibSp  Parch            Ticket     Fare Embarked  \n",
       "0        1      0         A/5 21171   7.2500        S  \n",
       "1        1      0          PC 17599  71.2833        C  \n",
       "2        0      0  STON/O2. 3101282   7.9250        S  \n",
       "3        1      0            113803  53.1000        S  \n",
       "4        0      0            373450   8.0500        S  \n",
       "..     ...    ...               ...      ...      ...  \n",
       "886      0      0            211536  13.0000        S  \n",
       "887      0      0            112053  30.0000        S  \n",
       "888      1      2        W./C. 6607  23.4500        S  \n",
       "889      0      0            111369  30.0000        C  \n",
       "890      0      0            370376   7.7500        Q  \n",
       "\n",
       "[891 rows x 11 columns]"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "titanic"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "b9f29b4e",
   "metadata": {},
   "source": [
    "# Encoding"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "id": "3a49c033",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>PassengerId</th>\n",
       "      <th>Survived</th>\n",
       "      <th>Pclass</th>\n",
       "      <th>Name</th>\n",
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       "      <td>Cumings, Mrs. John Bradley (Florence Briggs Th...</td>\n",
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       "      <td>38.000000</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>PC 17599</td>\n",
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       "      <th>2</th>\n",
       "      <td>3</td>\n",
       "      <td>1</td>\n",
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       "      <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>7.9250</td>\n",
       "      <td>S</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>4</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>Futrelle, Mrs. Jacques Heath (Lily May Peel)</td>\n",
       "      <td>1</td>\n",
       "      <td>35.000000</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>113803</td>\n",
       "      <td>53.1000</td>\n",
       "      <td>S</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>5</td>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>Allen, Mr. William Henry</td>\n",
       "      <td>0</td>\n",
       "      <td>35.000000</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>373450</td>\n",
       "      <td>8.0500</td>\n",
       "      <td>S</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>886</th>\n",
       "      <td>887</td>\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>13.0000</td>\n",
       "      <td>S</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>887</th>\n",
       "      <td>888</td>\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>30.0000</td>\n",
       "      <td>S</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>888</th>\n",
       "      <td>889</td>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>Johnston, Miss. Catherine Helen \"Carrie\"</td>\n",
       "      <td>1</td>\n",
       "      <td>29.699118</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>W./C. 6607</td>\n",
       "      <td>23.4500</td>\n",
       "      <td>S</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>889</th>\n",
       "      <td>890</td>\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>30.0000</td>\n",
       "      <td>C</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>890</th>\n",
       "      <td>891</td>\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>7.7500</td>\n",
       "      <td>Q</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>891 rows × 11 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "     PassengerId  Survived  Pclass  \\\n",
       "0              1         0       3   \n",
       "1              2         1       1   \n",
       "2              3         1       3   \n",
       "3              4         1       1   \n",
       "4              5         0       3   \n",
       "..           ...       ...     ...   \n",
       "886          887         0       2   \n",
       "887          888         1       1   \n",
       "888          889         0       3   \n",
       "889          890         1       1   \n",
       "890          891         0       3   \n",
       "\n",
       "                                                  Name Sex        Age  SibSp  \\\n",
       "0                              Braund, Mr. Owen Harris   0  22.000000      1   \n",
       "1    Cumings, Mrs. John Bradley (Florence Briggs Th...   1  38.000000      1   \n",
       "2                               Heikkinen, Miss. Laina   1  26.000000      0   \n",
       "3         Futrelle, Mrs. Jacques Heath (Lily May Peel)   1  35.000000      1   \n",
       "4                             Allen, Mr. William Henry   0  35.000000      0   \n",
       "..                                                 ...  ..        ...    ...   \n",
       "886                              Montvila, Rev. Juozas   0  27.000000      0   \n",
       "887                       Graham, Miss. Margaret Edith   1  19.000000      0   \n",
       "888           Johnston, Miss. Catherine Helen \"Carrie\"   1  29.699118      1   \n",
       "889                              Behr, Mr. Karl Howell   0  26.000000      0   \n",
       "890                                Dooley, Mr. Patrick   0  32.000000      0   \n",
       "\n",
       "     Parch            Ticket     Fare Embarked  \n",
       "0        0         A/5 21171   7.2500        S  \n",
       "1        0          PC 17599  71.2833        C  \n",
       "2        0  STON/O2. 3101282   7.9250        S  \n",
       "3        0            113803  53.1000        S  \n",
       "4        0            373450   8.0500        S  \n",
       "..     ...               ...      ...      ...  \n",
       "886      0            211536  13.0000        S  \n",
       "887      0            112053  30.0000        S  \n",
       "888      2        W./C. 6607  23.4500        S  \n",
       "889      0            111369  30.0000        C  \n",
       "890      0            370376   7.7500        Q  \n",
       "\n",
       "[891 rows x 11 columns]"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Male=0, Female=1\n",
    "titanic.loc[titanic['Sex']=='male','Sex']= 0\n",
    "titanic.loc[titanic['Sex']=='female','Sex']= 1\n",
    "titanic"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "id": "4206beb3",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "count          891\n",
       "unique         681\n",
       "top       CA. 2343\n",
       "freq             7\n",
       "Name: Ticket, dtype: object"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "titanic['Ticket'].describe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "id": "eac1258f",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Drop Ticket column\n",
    "titanic = titanic.drop(['Ticket'], axis=1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "id": "2b67850f",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
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       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>PassengerId</th>\n",
       "      <th>Survived</th>\n",
       "      <th>Pclass</th>\n",
       "      <th>Age</th>\n",
       "      <th>SibSp</th>\n",
       "      <th>Parch</th>\n",
       "      <th>Fare</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>891.000000</td>\n",
       "      <td>891.000000</td>\n",
       "      <td>891.000000</td>\n",
       "      <td>891.000000</td>\n",
       "      <td>891.000000</td>\n",
       "      <td>891.000000</td>\n",
       "      <td>891.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>446.000000</td>\n",
       "      <td>0.383838</td>\n",
       "      <td>2.308642</td>\n",
       "      <td>29.699118</td>\n",
       "      <td>0.523008</td>\n",
       "      <td>0.381594</td>\n",
       "      <td>32.204208</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>std</th>\n",
       "      <td>257.353842</td>\n",
       "      <td>0.486592</td>\n",
       "      <td>0.836071</td>\n",
       "      <td>13.002015</td>\n",
       "      <td>1.102743</td>\n",
       "      <td>0.806057</td>\n",
       "      <td>49.693429</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.420000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25%</th>\n",
       "      <td>223.500000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>2.000000</td>\n",
       "      <td>22.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>7.910400</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50%</th>\n",
       "      <td>446.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>3.000000</td>\n",
       "      <td>29.699118</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>14.454200</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75%</th>\n",
       "      <td>668.500000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>3.000000</td>\n",
       "      <td>35.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>31.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>max</th>\n",
       "      <td>891.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>3.000000</td>\n",
       "      <td>80.000000</td>\n",
       "      <td>8.000000</td>\n",
       "      <td>6.000000</td>\n",
       "      <td>512.329200</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "       PassengerId    Survived      Pclass         Age       SibSp  \\\n",
       "count   891.000000  891.000000  891.000000  891.000000  891.000000   \n",
       "mean    446.000000    0.383838    2.308642   29.699118    0.523008   \n",
       "std     257.353842    0.486592    0.836071   13.002015    1.102743   \n",
       "min       1.000000    0.000000    1.000000    0.420000    0.000000   \n",
       "25%     223.500000    0.000000    2.000000   22.000000    0.000000   \n",
       "50%     446.000000    0.000000    3.000000   29.699118    0.000000   \n",
       "75%     668.500000    1.000000    3.000000   35.000000    1.000000   \n",
       "max     891.000000    1.000000    3.000000   80.000000    8.000000   \n",
       "\n",
       "            Parch        Fare  \n",
       "count  891.000000  891.000000  \n",
       "mean     0.381594   32.204208  \n",
       "std      0.806057   49.693429  \n",
       "min      0.000000    0.000000  \n",
       "25%      0.000000    7.910400  \n",
       "50%      0.000000   14.454200  \n",
       "75%      0.000000   31.000000  \n",
       "max      6.000000  512.329200  "
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "titanic.describe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "id": "fb7e459b",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 891 entries, 0 to 890\n",
      "Data columns (total 10 columns):\n",
      " #   Column       Non-Null Count  Dtype  \n",
      "---  ------       --------------  -----  \n",
      " 0   PassengerId  891 non-null    int64  \n",
      " 1   Survived     891 non-null    int64  \n",
      " 2   Pclass       891 non-null    int64  \n",
      " 3   Name         891 non-null    object \n",
      " 4   Sex          891 non-null    object \n",
      " 5   Age          891 non-null    float64\n",
      " 6   SibSp        891 non-null    int64  \n",
      " 7   Parch        891 non-null    int64  \n",
      " 8   Fare         891 non-null    float64\n",
      " 9   Embarked     891 non-null    object \n",
      "dtypes: float64(2), int64(5), object(3)\n",
      "memory usage: 69.7+ KB\n"
     ]
    }
   ],
   "source": [
    "titanic.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "id": "de9947b7",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
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       "    .dataframe tbody tr th {\n",
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>PassengerId</th>\n",
       "      <th>Survived</th>\n",
       "      <th>Pclass</th>\n",
       "      <th>Name</th>\n",
       "      <th>Sex</th>\n",
       "      <th>Age</th>\n",
       "      <th>SibSp</th>\n",
       "      <th>Parch</th>\n",
       "      <th>Fare</th>\n",
       "      <th>Embarked</th>\n",
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       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>Braund, Mr. Owen Harris</td>\n",
       "      <td>0</td>\n",
       "      <td>22.000000</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>7.2500</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>Cumings, Mrs. John Bradley (Florence Briggs Th...</td>\n",
       "      <td>1</td>\n",
       "      <td>38.000000</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>71.2833</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>3</td>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "      <td>Heikkinen, Miss. Laina</td>\n",
       "      <td>1</td>\n",
       "      <td>26.000000</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>7.9250</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>4</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>Futrelle, Mrs. Jacques Heath (Lily May Peel)</td>\n",
       "      <td>1</td>\n",
       "      <td>35.000000</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>53.1000</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>5</td>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>Allen, Mr. William Henry</td>\n",
       "      <td>0</td>\n",
       "      <td>35.000000</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>8.0500</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>886</th>\n",
       "      <td>887</td>\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>13.0000</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>887</th>\n",
       "      <td>888</td>\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>30.0000</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>888</th>\n",
       "      <td>889</td>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>Johnston, Miss. Catherine Helen \"Carrie\"</td>\n",
       "      <td>1</td>\n",
       "      <td>29.699118</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>23.4500</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>889</th>\n",
       "      <td>890</td>\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>30.0000</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>890</th>\n",
       "      <td>891</td>\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>7.7500</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>891 rows × 10 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "     PassengerId  Survived  Pclass  \\\n",
       "0              1         0       3   \n",
       "1              2         1       1   \n",
       "2              3         1       3   \n",
       "3              4         1       1   \n",
       "4              5         0       3   \n",
       "..           ...       ...     ...   \n",
       "886          887         0       2   \n",
       "887          888         1       1   \n",
       "888          889         0       3   \n",
       "889          890         1       1   \n",
       "890          891         0       3   \n",
       "\n",
       "                                                  Name Sex        Age  SibSp  \\\n",
       "0                              Braund, Mr. Owen Harris   0  22.000000      1   \n",
       "1    Cumings, Mrs. John Bradley (Florence Briggs Th...   1  38.000000      1   \n",
       "2                               Heikkinen, Miss. Laina   1  26.000000      0   \n",
       "3         Futrelle, Mrs. Jacques Heath (Lily May Peel)   1  35.000000      1   \n",
       "4                             Allen, Mr. William Henry   0  35.000000      0   \n",
       "..                                                 ...  ..        ...    ...   \n",
       "886                              Montvila, Rev. Juozas   0  27.000000      0   \n",
       "887                       Graham, Miss. Margaret Edith   1  19.000000      0   \n",
       "888           Johnston, Miss. Catherine Helen \"Carrie\"   1  29.699118      1   \n",
       "889                              Behr, Mr. Karl Howell   0  26.000000      0   \n",
       "890                                Dooley, Mr. Patrick   0  32.000000      0   \n",
       "\n",
       "     Parch     Fare Embarked  \n",
       "0        0   7.2500        0  \n",
       "1        0  71.2833        1  \n",
       "2        0   7.9250        0  \n",
       "3        0  53.1000        0  \n",
       "4        0   8.0500        0  \n",
       "..     ...      ...      ...  \n",
       "886      0  13.0000        0  \n",
       "887      0  30.0000        0  \n",
       "888      2  23.4500        0  \n",
       "889      0  30.0000        1  \n",
       "890      0   7.7500        2  \n",
       "\n",
       "[891 rows x 10 columns]"
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# encode the Embarked column\n",
    "titanic.loc[titanic['Embarked']=='S','Embarked']=0\n",
    "titanic.loc[titanic['Embarked']=='C','Embarked']=1\n",
    "titanic.loc[titanic['Embarked']=='Q','Embarked']=2\n",
    "titanic"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "id": "c8071522",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 891 entries, 0 to 890\n",
      "Data columns (total 10 columns):\n",
      " #   Column       Non-Null Count  Dtype  \n",
      "---  ------       --------------  -----  \n",
      " 0   PassengerId  891 non-null    int64  \n",
      " 1   Survived     891 non-null    int64  \n",
      " 2   Pclass       891 non-null    int64  \n",
      " 3   Name         891 non-null    object \n",
      " 4   Sex          891 non-null    object \n",
      " 5   Age          891 non-null    float64\n",
      " 6   SibSp        891 non-null    int64  \n",
      " 7   Parch        891 non-null    int64  \n",
      " 8   Fare         891 non-null    float64\n",
      " 9   Embarked     891 non-null    object \n",
      "dtypes: float64(2), int64(5), object(3)\n",
      "memory usage: 69.7+ KB\n"
     ]
    }
   ],
   "source": [
    "titanic.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "id": "bcd421d2",
   "metadata": {},
   "outputs": [],
   "source": [
    "# convert object types to int\n",
    "titanic['Sex'] = titanic['Sex'].astype(int)\n",
    "titanic['Embarked'] = titanic['Embarked'].astype(int)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "id": "3cfa3428",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 891 entries, 0 to 890\n",
      "Data columns (total 10 columns):\n",
      " #   Column       Non-Null Count  Dtype  \n",
      "---  ------       --------------  -----  \n",
      " 0   PassengerId  891 non-null    int64  \n",
      " 1   Survived     891 non-null    int64  \n",
      " 2   Pclass       891 non-null    int64  \n",
      " 3   Name         891 non-null    object \n",
      " 4   Sex          891 non-null    int32  \n",
      " 5   Age          891 non-null    float64\n",
      " 6   SibSp        891 non-null    int64  \n",
      " 7   Parch        891 non-null    int64  \n",
      " 8   Fare         891 non-null    float64\n",
      " 9   Embarked     891 non-null    int32  \n",
      "dtypes: float64(2), int32(2), int64(5), object(1)\n",
      "memory usage: 62.8+ KB\n"
     ]
    }
   ],
   "source": [
    "titanic.info()\n",
    "\n",
    "# writing processed data to disk\n",
    "\n",
    "# titanic.to_csv('preprocessed_titanic.csv')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "id": "15b09731",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.legend.Legend at 0x208ee161df0>"
      ]
     },
     "execution_count": 27,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 1152x432 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# TODO: Should use bar plot to visualize this\n",
    "plt.figure(figsize=(16, 6))\n",
    "for i in range(1,4):\n",
    "    Pclass_plot = titanic[titanic['Pclass']==i]\n",
    "    plt.plot(Pclass_plot['Pclass'], Pclass_plot['Survived'], linestyle='none', marker='o', label=i)\n",
    "plt.xlabel('Pclass')\n",
    "plt.ylabel('Survived')\n",
    "plt.legend()\n",
    "# plt.plot(X_plot[:, 0], X_plot[:, 1], linestyle='none', marker='o', label=target_name)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "id": "8e437806",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1152x1152 with 9 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "_ = titanic.hist(figsize=(16,16), grid=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "id": "2c15bfea",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>PassengerId</th>\n",
       "      <th>Survived</th>\n",
       "      <th>Pclass</th>\n",
       "      <th>Name</th>\n",
       "      <th>Sex</th>\n",
       "      <th>Age</th>\n",
       "      <th>SibSp</th>\n",
       "      <th>Parch</th>\n",
       "      <th>Fare</th>\n",
       "      <th>Embarked</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>Braund, Mr. Owen Harris</td>\n",
       "      <td>0</td>\n",
       "      <td>22.000000</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>7.2500</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>Cumings, Mrs. John Bradley (Florence Briggs Th...</td>\n",
       "      <td>1</td>\n",
       "      <td>38.000000</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>71.2833</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>3</td>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "      <td>Heikkinen, Miss. Laina</td>\n",
       "      <td>1</td>\n",
       "      <td>26.000000</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>7.9250</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>4</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>Futrelle, Mrs. Jacques Heath (Lily May Peel)</td>\n",
       "      <td>1</td>\n",
       "      <td>35.000000</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>53.1000</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>5</td>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>Allen, Mr. William Henry</td>\n",
       "      <td>0</td>\n",
       "      <td>35.000000</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>8.0500</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>886</th>\n",
       "      <td>887</td>\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>13.0000</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>887</th>\n",
       "      <td>888</td>\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>30.0000</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>888</th>\n",
       "      <td>889</td>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>Johnston, Miss. Catherine Helen \"Carrie\"</td>\n",
       "      <td>1</td>\n",
       "      <td>29.699118</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>23.4500</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>889</th>\n",
       "      <td>890</td>\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>30.0000</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>890</th>\n",
       "      <td>891</td>\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>7.7500</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>891 rows × 10 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "     PassengerId  Survived  Pclass  \\\n",
       "0              1         0       3   \n",
       "1              2         1       1   \n",
       "2              3         1       3   \n",
       "3              4         1       1   \n",
       "4              5         0       3   \n",
       "..           ...       ...     ...   \n",
       "886          887         0       2   \n",
       "887          888         1       1   \n",
       "888          889         0       3   \n",
       "889          890         1       1   \n",
       "890          891         0       3   \n",
       "\n",
       "                                                  Name  Sex        Age  SibSp  \\\n",
       "0                              Braund, Mr. Owen Harris    0  22.000000      1   \n",
       "1    Cumings, Mrs. John Bradley (Florence Briggs Th...    1  38.000000      1   \n",
       "2                               Heikkinen, Miss. Laina    1  26.000000      0   \n",
       "3         Futrelle, Mrs. Jacques Heath (Lily May Peel)    1  35.000000      1   \n",
       "4                             Allen, Mr. William Henry    0  35.000000      0   \n",
       "..                                                 ...  ...        ...    ...   \n",
       "886                              Montvila, Rev. Juozas    0  27.000000      0   \n",
       "887                       Graham, Miss. Margaret Edith    1  19.000000      0   \n",
       "888           Johnston, Miss. Catherine Helen \"Carrie\"    1  29.699118      1   \n",
       "889                              Behr, Mr. Karl Howell    0  26.000000      0   \n",
       "890                                Dooley, Mr. Patrick    0  32.000000      0   \n",
       "\n",
       "     Parch     Fare  Embarked  \n",
       "0        0   7.2500         0  \n",
       "1        0  71.2833         1  \n",
       "2        0   7.9250         0  \n",
       "3        0  53.1000         0  \n",
       "4        0   8.0500         0  \n",
       "..     ...      ...       ...  \n",
       "886      0  13.0000         0  \n",
       "887      0  30.0000         0  \n",
       "888      2  23.4500         0  \n",
       "889      0  30.0000         1  \n",
       "890      0   7.7500         2  \n",
       "\n",
       "[891 rows x 10 columns]"
      ]
     },
     "execution_count": 29,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "titanic"
   ]
  }
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