Titanic.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Questions about Titanic dataset\n",
    "\n",
    "Highlights: \n",
    "\n",
    "* On April 15, 1912, the Titanic sank after colliding with an iceberg, killing 1502 out of 2224 passengers and crew. Translated 32% survival rate.\n",
    "* One of the reasons that the shipwreck led to such loss of life was that there were not enough lifeboats for the passengers and crew.\n",
    "* Although there was some element of luck involved in surviving the sinking, some groups of people were more likely to survive than others."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 82,
   "metadata": {
    "collapsed": false,
    "scrolled": true
   },
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import seaborn as sns\n",
    "import matplotlib.pyplot as plt\n",
    "%matplotlib inline\n",
    "\n",
    "def plot_correlation_map( df ):\n",
    "    corr = data.corr()\n",
    "    _ , ax = plt.subplots( figsize =( 12 , 10 ) )\n",
    "    cmap = sns.diverging_palette( 220 , 10 , as_cmap = True )\n",
    "    _ = sns.heatmap(\n",
    "        corr, \n",
    "        cmap = cmap,\n",
    "        square=True, \n",
    "        cbar_kws={ 'shrink' : .9 }, \n",
    "        ax=ax, \n",
    "        annot = True, \n",
    "        annot_kws = { 'fontsize' : 12 }\n",
    "    )\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Dataset"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 83,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\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</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>A/5 21171</td>\n",
       "      <td>7.2500</td>\n",
       "      <td></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</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</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>STON/O2. 3101282</td>\n",
       "      <td>7.9250</td>\n",
       "      <td></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</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</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>373450</td>\n",
       "      <td>8.0500</td>\n",
       "      <td></td>\n",
       "      <td>S</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>6</td>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>Moran, Mr. James</td>\n",
       "      <td>male</td>\n",
       "      <td></td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>330877</td>\n",
       "      <td>8.4583</td>\n",
       "      <td></td>\n",
       "      <td>Q</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>7</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>McCarthy, Mr. Timothy J</td>\n",
       "      <td>male</td>\n",
       "      <td>54</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>7</th>\n",
       "      <td>8</td>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>Palsson, Master. Gosta Leonard</td>\n",
       "      <td>male</td>\n",
       "      <td>2</td>\n",
       "      <td>3</td>\n",
       "      <td>1</td>\n",
       "      <td>349909</td>\n",
       "      <td>21.0750</td>\n",
       "      <td></td>\n",
       "      <td>S</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>9</td>\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</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>347742</td>\n",
       "      <td>11.1333</td>\n",
       "      <td></td>\n",
       "      <td>S</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>10</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>Nasser, Mrs. Nicholas (Adele Achem)</td>\n",
       "      <td>female</td>\n",
       "      <td>14</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>237736</td>\n",
       "      <td>30.0708</td>\n",
       "      <td></td>\n",
       "      <td>C</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>11</td>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "      <td>Sandstrom, Miss. Marguerite Rut</td>\n",
       "      <td>female</td>\n",
       "      <td>4</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>PP 9549</td>\n",
       "      <td>16.7000</td>\n",
       "      <td>G6</td>\n",
       "      <td>S</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>12</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>Bonnell, Miss. Elizabeth</td>\n",
       "      <td>female</td>\n",
       "      <td>58</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>113783</td>\n",
       "      <td>26.5500</td>\n",
       "      <td>C103</td>\n",
       "      <td>S</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>13</td>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>Saundercock, Mr. William Henry</td>\n",
       "      <td>male</td>\n",
       "      <td>20</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>A/5. 2151</td>\n",
       "      <td>8.0500</td>\n",
       "      <td></td>\n",
       "      <td>S</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>14</td>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>Andersson, Mr. Anders Johan</td>\n",
       "      <td>male</td>\n",
       "      <td>39</td>\n",
       "      <td>1</td>\n",
       "      <td>5</td>\n",
       "      <td>347082</td>\n",
       "      <td>31.2750</td>\n",
       "      <td></td>\n",
       "      <td>S</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>15</td>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>Vestrom, Miss. Hulda Amanda Adolfina</td>\n",
       "      <td>female</td>\n",
       "      <td>14</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>350406</td>\n",
       "      <td>7.8542</td>\n",
       "      <td></td>\n",
       "      <td>S</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>16</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>Hewlett, Mrs. (Mary D Kingcome)</td>\n",
       "      <td>female</td>\n",
       "      <td>55</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>248706</td>\n",
       "      <td>16.0000</td>\n",
       "      <td></td>\n",
       "      <td>S</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>17</td>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>Rice, Master. Eugene</td>\n",
       "      <td>male</td>\n",
       "      <td>2</td>\n",
       "      <td>4</td>\n",
       "      <td>1</td>\n",
       "      <td>382652</td>\n",
       "      <td>29.1250</td>\n",
       "      <td></td>\n",
       "      <td>Q</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>18</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>Williams, Mr. Charles Eugene</td>\n",
       "      <td>male</td>\n",
       "      <td></td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>244373</td>\n",
       "      <td>13.0000</td>\n",
       "      <td></td>\n",
       "      <td>S</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>19</td>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>Vander Planke, Mrs. Julius (Emelia Maria Vande...</td>\n",
       "      <td>female</td>\n",
       "      <td>31</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>345763</td>\n",
       "      <td>18.0000</td>\n",
       "      <td></td>\n",
       "      <td>S</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>20</td>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "      <td>Masselmani, Mrs. Fatima</td>\n",
       "      <td>female</td>\n",
       "      <td></td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2649</td>\n",
       "      <td>7.2250</td>\n",
       "      <td></td>\n",
       "      <td>C</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    PassengerId  Survived  Pclass  \\\n",
       "0             1         0       3   \n",
       "1             2         1       1   \n",
       "2             3         1       3   \n",
       "3             4         1       1   \n",
       "4             5         0       3   \n",
       "5             6         0       3   \n",
       "6             7         0       1   \n",
       "7             8         0       3   \n",
       "8             9         1       3   \n",
       "9            10         1       2   \n",
       "10           11         1       3   \n",
       "11           12         1       1   \n",
       "12           13         0       3   \n",
       "13           14         0       3   \n",
       "14           15         0       3   \n",
       "15           16         1       2   \n",
       "16           17         0       3   \n",
       "17           18         1       2   \n",
       "18           19         0       3   \n",
       "19           20         1       3   \n",
       "\n",
       "                                                 Name     Sex Age  SibSp  \\\n",
       "0                             Braund, Mr. Owen Harris    male  22      1   \n",
       "1   Cumings, Mrs. John Bradley (Florence Briggs Th...  female  38      1   \n",
       "2                              Heikkinen, Miss. Laina  female  26      0   \n",
       "3        Futrelle, Mrs. Jacques Heath (Lily May Peel)  female  35      1   \n",
       "4                            Allen, Mr. William Henry    male  35      0   \n",
       "5                                    Moran, Mr. James    male          0   \n",
       "6                             McCarthy, Mr. Timothy J    male  54      0   \n",
       "7                      Palsson, Master. Gosta Leonard    male   2      3   \n",
       "8   Johnson, Mrs. Oscar W (Elisabeth Vilhelmina Berg)  female  27      0   \n",
       "9                 Nasser, Mrs. Nicholas (Adele Achem)  female  14      1   \n",
       "10                    Sandstrom, Miss. Marguerite Rut  female   4      1   \n",
       "11                           Bonnell, Miss. Elizabeth  female  58      0   \n",
       "12                     Saundercock, Mr. William Henry    male  20      0   \n",
       "13                        Andersson, Mr. Anders Johan    male  39      1   \n",
       "14               Vestrom, Miss. Hulda Amanda Adolfina  female  14      0   \n",
       "15                   Hewlett, Mrs. (Mary D Kingcome)   female  55      0   \n",
       "16                               Rice, Master. Eugene    male   2      4   \n",
       "17                       Williams, Mr. Charles Eugene    male          0   \n",
       "18  Vander Planke, Mrs. Julius (Emelia Maria Vande...  female  31      1   \n",
       "19                            Masselmani, Mrs. Fatima  female          0   \n",
       "\n",
       "    Parch            Ticket     Fare Cabin Embarked  \n",
       "0       0         A/5 21171   7.2500              S  \n",
       "1       0          PC 17599  71.2833   C85        C  \n",
       "2       0  STON/O2. 3101282   7.9250              S  \n",
       "3       0            113803  53.1000  C123        S  \n",
       "4       0            373450   8.0500              S  \n",
       "5       0            330877   8.4583              Q  \n",
       "6       0             17463  51.8625   E46        S  \n",
       "7       1            349909  21.0750              S  \n",
       "8       2            347742  11.1333              S  \n",
       "9       0            237736  30.0708              C  \n",
       "10      1           PP 9549  16.7000    G6        S  \n",
       "11      0            113783  26.5500  C103        S  \n",
       "12      0         A/5. 2151   8.0500              S  \n",
       "13      5            347082  31.2750              S  \n",
       "14      0            350406   7.8542              S  \n",
       "15      0            248706  16.0000              S  \n",
       "16      1            382652  29.1250              Q  \n",
       "17      0            244373  13.0000              S  \n",
       "18      0            345763  18.0000              S  \n",
       "19      0              2649   7.2250              C  "
      ]
     },
     "execution_count": 83,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data = pd.read_csv('titanic.csv', na_filter=False)\n",
    "\n",
    "data.head(20)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Variable descriptions\n",
    "\n",
    "* __Survived__: Survival (0 = No; 1 = Yes).\n",
    "* __pclass__: Passenger Class (1 = 1st; 2 = 2nd; 3 = 3rd).\n",
    "* __name__: Name.\n",
    "* __sex__: Sex.\n",
    "* __age__: Age.\n",
    "* __sibsp__: Number of Siblings/Spouses Aboard.\n",
    "* __parch__: Number of Parents/Children Aboard.\n",
    "* __ticket__: Ticket Number.\n",
    "* __fare__: Passenger Fare.\n",
    "* __cabin__: Cabin.\n",
    "* __embarked__: Port of Embarkation (C = Cherbourg; Q = Queenstown; S = Southampton)."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Questions\n",
    "\n",
    "## __1.- Which features are available in the dataset?__"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 84,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "['PassengerId' 'Survived' 'Pclass' 'Name' 'Sex' 'Age' 'SibSp' 'Parch'\n",
      " 'Ticket' 'Fare' 'Cabin' 'Embarked']\n"
     ]
    }
   ],
   "source": [
    "print(data.columns.values)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## __2.- Which features are categorical or numerical?__\n",
    "\n",
    "\n",
    "* Categorical: Survived, Pclass, Sex, Embarked.\n",
    "* Numerical: PassengerId, Age, SibSp, Parch, Fare."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 85,
   "metadata": {
    "collapsed": false,
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\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>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",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>446.000000</td>\n",
       "      <td>0.383838</td>\n",
       "      <td>2.308642</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>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>0.000000</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>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>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>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>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       SibSp       Parch        Fare\n",
       "count   891.000000  891.000000  891.000000  891.000000  891.000000  891.000000\n",
       "mean    446.000000    0.383838    2.308642    0.523008    0.381594   32.204208\n",
       "std     257.353842    0.486592    0.836071    1.102743    0.806057   49.693429\n",
       "min       1.000000    0.000000    1.000000    0.000000    0.000000    0.000000\n",
       "25%     223.500000    0.000000    2.000000    0.000000    0.000000    7.910400\n",
       "50%     446.000000    0.000000    3.000000    0.000000    0.000000   14.454200\n",
       "75%     668.500000    1.000000    3.000000    1.000000    0.000000   31.000000\n",
       "max     891.000000    1.000000    3.000000    8.000000    6.000000  512.329200"
      ]
     },
     "execution_count": 85,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data.describe()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## __3.- Which features are mixed data types?__\n",
    "\n",
    "* Ticket, Cabin."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## __4.- Which features may contain errors or typos?__\n",
    "\n",
    "__What can we do with in those cases?__\n",
    "\n",
    "\n",
    "## __5.- Which features contain blank, null or empty values?__\n",
    "\n",
    "__What can we do with in those cases?__\n",
    "\n",
    "## __6.- What do you think are the most important reasons passangers survived the Titanic sinking?__\n",
    "\n",
    "__Who has not seen the Titanic film?__\n",
    " "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 86,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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2JiIiIiK/n7U2H+h90stbTnh/AgVDB38Xb2/htxQwxpgY4ODxa+AiIiIiQSlIFtz2qm5q\njHnAGHMvBdfCfzXGDPBtWCIiIiLib95eYO8LLAS6UTD7+c8+i0hEREQkwDlCHD5/BAJvE8WjhT8z\nrbXH8H5so4iIiIhUUF7f65mCSSz/NMa8RMFq3yIiIiLBSWMU/8da2wO43Fo7F5hgrX3Mt2GJiIiI\niL95O5nlj8D1xphOwDeF6/SIiIiIBKeQEN8/AoC3UbwCbAX+AVzHqev2iIiIiEgl4+0YxSPAXsBl\nrd1jjHH7MCYRERGRgOYIkIqfr3nbywzgc2CmMeYJCu4ZKCIiIiKVmLcVxa5AE2vtZmPMxcAkH8Yk\nIiIiEtiCZNazt4liQ+AvxpguFNx4uh7Qy2dRiYiIiIjfeXvpOanw5/XABcB5vglHREREpAJwOHz/\nCADeVhSzrLWvGmOaWWsfNsYs92ajuPkf/o7QxBt7buvi7xAqvdRxo/0dQlC47oJ6/g6h0qt+OMPf\nIVR6uTt2+TuE4HB9G39HEDS8TRTdxpg4INIYUwOI8GFMIiIiIoFNs54LGGOigCHAHcB7FNzOb7GP\n4xIRERERPyuxomiM6QP0B1zAk9baz4FPyyMwERERkUDlCJAxhL5WWkXxfsAA1wJ9fR+OiIiIiASK\n0sYo5lhrc4F0Y0zV8ghIREREJOAFSUXR28ksULB+ooiIiIiEBEdaVFqieJExJomCJPH47wBYa+/3\naWQiIiIi4lelJYpdT/h9gi8DEREREakwHMGxPE6JiaK1dml5BSIiIiIigaUsYxRFREREBHAEyRjF\n4KibioiIiEiZqaIoIiIiUla6hZ+IiIiIBDNVFEVERETKKkgW3FZFUUREREQ8UkVRREREpIwcqiiK\niIiISDBTRVFERESkrDTrWURERESCmSqKIiIiImWlMYoiIiIiEsxUURQREREpK1UURURERCSYqaIo\nIiIiUkYOzXoWERERkWCmiqKIiIhIWQXJGEUliiIiIiJlFRIciaIuPYuIiIiIR6ooioiIiJRVkFx6\nVkVRRERERDxSRVFERESkjLQ8joiIiIgENVUURURERMrKERy1tuDopYiIiIiUmSqKIiIiImWldRRF\nREREJJipoigiIiJSRg6toygiIiIiwaxSVxRXrFhBYmIiubm5NGvWjEGDBhEREeF1u7y8PEaOHMnK\nlSvJy8ujW7dudOnSBYBly5YxePBg4uLiij5n0qRJ1KhRo9z6V1HFPtefY9t/5tD0D/0dSoW06bs1\nzEmaRp7TRb3GjbnvsX9QPTz8lHbL5s/l6wXzweGgdmwc9/buQ2R0zWJt3k4YTvS5tejSs3d5hR+w\nfu/5Iisri6FDh7Jjxw7cbje333473bt3B3S+OG7pqlW8OXkyTmcuzS+8kKEDnibipGNwujZ5eXm8\nMmY0a39IAeCGa65mQK/eOBwONmzZwuvjxnI0J4f8/Hwevude/nzLLf7oYkBZ/sN6xsyehdPpolmD\nhrzY4+9EnHNOsTafrfyaaZ/Px+FwUL1qVZ65vxutzr8AgJlLFvPx8qXkOHNp2fh8Xur+d6qGhfmj\nK4FJs54rtoMHDzJkyBBGjBjB7NmzqV+/PomJiWVqN3v2bHbu3MkHH3zAtGnTmD59Ohs3bgQgJSWF\nbt26kZSUVPQItpN+WYU1bkj9Ua8TcfON/g6lwso6fJikcaN5eMCzPD96POfFxvHp+++e0m5X6ja+\nnPMxTw0bwbP/SSSmbj3mzXi/WJvFnyST+uPm8go9oJ2N88X48eOJjY1l5syZTJs2jeTkZFJSCpIa\nnS/gwKFDDEoYwZuDBzP33Wk0qFuPkZMned1mzsKF7Ni1i48mTyZ50iTWpqSwYNlS3G43/xwymCce\n6k7yxEmMf/U1EiaM5+dffvFHNwPGwcwMBk+dzBuPP8lHw1+nfkwMYz6cWazNjj27GTXrAxL/OYAZ\ng1+m5586M2DsaAAWf7eWGUsWMr7/M3w4dDjHcp28v/ALf3RF/KzSJoqrVq2iVatWNGrUCIAuXbow\nf/583G631+2+/PJLOnfuTGhoKFFRUXTo0IH58+cDBSf+tWvX0q1bN3r27Mm6devKt4MVUM07O5Mx\nbwFZS5b5O5QKa0vK9zRq0ow6desBcF2H2/hu+dJT/q4bNmnKC6MncE6NGjhzczl8YD/hkZFF72/d\nmMKP36/jug63lmv8gepsnC8GDBhA3759AUhPTyc3N7eoIqnzBXyzdi0XGUPjBg0AuKdzZz5bvLjY\nMS6pTV5+Pkdzcsh1OnEWPqqFVSXX6eSxB//GtVdeCUBcTAw1o6LZm5ZW/p0MICs3beSi8y+kUWxB\nFfvu9jczf/XKYse7amgogx56mJiaBVcaWp1/AemHD+N0ufjsm695sMOtREdEEBISwvN/e4jbr23r\nl74ErBCH7x8BoNIminv37iU2NrboeZ06dcjOziY7O9vrdie/Fxsby759+wCIjo7m7rvv5r///S99\n+vTh6aefZu/evT7uVcWWNnIsmV8s9ncYFdrB9HRq1q5d9LzmebXJOXqEY0ePntK2SmgoKd+u4qXe\nPUjdvIlr2v8RgMMH9pM8dRIP9u1PSJDcgqo0Z+N84XA4CA0NZdCgQdxzzz1ceeWVNG7cGND5AmBP\n2j7iYuoUPY+NiSErO5vsI0e8anNHx45ERUbyh3u60u7uLjSqX592bdtSrWpV7urUqWibWXPnciTn\nKJe2alU+HQtQew8cILZWraLndc6tRdbRo2Tn5BS9Vq92DDdc1hoAt9vNvz9I4qbWlxMWGsrPe/dw\nIDOTJ0a+QdeXnmfCJx8TGR5cVXApUOK/EsaYG0/3KK8Az1R+fr7H16tUqeJ1u5OrCUDRP6wJCQm0\nb98egNatW3PppZeyevXq3xOySKncbs9/r6e75+ilV7dh+JT3ubXrfUwY9hIup5N330zgzu49iT63\nlsdtgtHZOF8c9/LLL7No0SIyMjKYPHkyoPMFQH7+qedToNiXlZLajJ82jXOjo1n6YTKLZ3zA4YxM\n3plZ/FLq5OlJjH33HRKHvUL1atXOXvAVUL6Hf78Aqng4Vxw9dox/jR/Lrn37eLH7wwC48vJYvWkj\nr/d+gvcHDSEjO4vE2RpXXozD4ftHAChtMstjhT+bAFWBNcDlQBbQzndhnZkJEyawbFnBZc3s7Gya\nNGlS9F5aWhpRUVGcc9JA3ri4uKJxhye3i4uLIz09vei9ffv2UadOHTIzM5k1axY9evQomh7vdrsJ\nDa3Uc4PET+bNeJ+Na78FIOfoEeo2alz03uED+wmvEUG16tWLbZO2+zcyDh2iScuCqkqb9n9k5sTx\n7Ezdyv59+/j43SkAZBw6SH5+Pk6nk/see7KcehQYzvb5YuXKlTRt2pSYmBjCw8Pp2LEjS5Ys0fmi\nUN06ddiw5cei5/vS04iKjCT8hGNcUptFK5bzXJ8nCQsLIywsjL906MCCZcvo3rUrubm5PD/idVJ/\n/pn3xyRS/4RJQ8EqrlYtNv6UWvR838GDRIXX4JyTEujd+/fz1OiRXFC3HhOfHkj1qlUBiKlZk/ZX\nXFk0+aVTm7ZMmvNJ+XVAAkaJFUVr7X3W2vuANCDeWvsIcA2QU9J2/tK7d++igeJTp05l48aN7Ny5\nE4Dk5GRuuummU7Zp06bNadvdeOONfPrpp7hcLjIzM1mwYAHt2rUjPDycWbNmsWTJEgC2bNnCpk2b\naNtW4zfk7Ot07wM888YonnljFP8cnsCOrZZ9u38D4OsF87n4qmtO2Sbj0EHefTOBrIwMANauWErd\nRo24sEUrhkyYUvR513W4lSvaXh90SSKc/fPFwoULmThxIm63m9zcXBYuXEh8fLzOF4Xaxsfzw+Yf\niyaZfDBnDjefdAxKatOyWTM+X/oVAE6Xiy9XfsNlrVoC0G/oELKOHOG/o8coSSx07UWXsOGnVHbu\n3QNA8tIl3HT55cXaHM7K4pERw7n5iit5rffjRUkiwB/jr2Lh2jXk5Obidrv56vt1tLrggnLtQ6Bz\nhDh8/ggEDk+XV09mjFkHXG2tdRljqgErrbVXlLZdZmZm6R/uQytWrGDs2LE4nU4aNGjAkCFDiI6O\nZvPmzQwbNoykpKQS27lcLkaNGsXq1atxOp3ceeedPPjggwBs3ryZhIQEsrOzCQ0NpV+/fsTHx5d7\nH/fc1qXc9/l7VbTlcVLHjfZ3CMVsWreWuUnTyHO5OC82jm59/kmNyEh2pm5lxvhEnnljFAArvpjH\n8i/mUSWkClG1anH333txXmzxf0Tnz0wiOyMjIJbHue6Cen7d/+89X2RmZjJ8+HBSU1NxOBy0a9eO\nXr16ERISEjDni+qHM8p9nydatrpw6RuXi4Z16/HqwIHs2r2bl/79BskTJ522TXRUFIcOH2Z44hh+\n3LqVkJAQrrniCp7u/Rgbtmzhb33/wfkNGlDthGpZv0ce5bqrrir3Pubu2FXu+zydFSk/MCZ5Fs48\nFw1i6vDy3x/l1/Q0hr4zhRmDX2by3E+Z8PFsmjZoWGy7CQP+RWR4OJPnfMKCNd+Sn59Pi8aNef5v\nPU5ZXsdfalzfxu9ZVNrIsT7PcWL++YTf++ltovgE8A9gI3AR8Lq1dmpp2/k7UQwGFTFRrGgCLVGs\nrPydKAYDfyeKwSCQEsXKLCASxTfH+z5RfOoxv/fTq0Ey1tqxxphZFIxV3GqtTS9tGxERERGp2Lxa\nG8MYcxGQDEwCehpj/uTTqEREREQCWZDMevZ2EbXRQA8KJrW8DQz2VUAiIiIiAU8Lbhdnrd0GuK21\naUCm70ISERERkUDg7UJeB4wxvYAaxph7gUM+jElEREQkoJ3uRgeVjbe9/DtwAZAOxBc+FxEREZFK\nzNuK4hBgkrV2sy+DEREREakQHMFRUfQ2UVwBjDDGRAJTgQ+stUd9F5aIiIiI+JtX6bC1Ntla+yfg\nXuBWYLdPoxIREREJZEEy69mriqIxphHwEHAXsA64zZdBiYiIiIj/eXvpORmYDNxordU9oERERCSo\nOQJkQWxfK/HSszGmQeGv3YAvgThjTHNjTHOfRyYiIiIiflVaRbFf4WPCSa+7gZt9EpGIiIhIoAuS\nimKJiaK1tl/hr6OAT621+b4PSUREREQCgbeLAP0B+MEY84ox5gJfBiQiIiIS8EJCfP8IAN4uj/Mk\ncCWwHhhrjFnk06hERERExO+8nfUMcDXQEYgFPvRNOCIiIiIVgMYo/o8xZjPwAzDZWtvTtyGJiIiI\nSCDwtqI41Vqb4NNIRERERCoIraNY3G3GmCo+jUREREREAoq3FcUY4DdjzHYK1lB0W2vb+i4sERER\nkQAWILOSfc3bRPFPPo1CRERERAKOt4niQx5eG3o2AxERERGpMIJkjKK3ieLewp8O4Aq8H9soIiIi\nUvno0vP/WGvfOvG5MWa+b8IRERERkUDh7TqKzU94Wg9o7JtwRERERAKfI0SXnk/0FgWznWsB+4F+\nPotIRERERAJCiYmiMeYK4G3gGgpmPk8AwoGqvg9NREREJEAFyWSW0kZiJgAPWWtzgWHArUA88C9f\nByYiIiIi/lXapecq1toUY0w9oIa1dh2AMSbf96GJiIiIBCiHf2c9G2NCgHHAZcAxoKe1dpuHdhOB\nA9bagWeyn9J66Sz8eSuwqHCHYUDkmexMRERERM6KO4Dq1tprgYHAv09uYIzpBVzye3ZSWkVxkTHm\na6Ah0NkY0wRIBD74PTsVERERqcgCYNbz9cDnANbaVcaY+BPfNMa0pWCOyVtAizPdSYkVRWvt60BP\noI21dn3hyxOtta+e6Q5FRERE5HeLAg6f8DzPGBMKYIypC7wE9Pm9Oyl1eRxr7Y8n/J4KpP7enYqI\niIhUaP6f9ZxB8aGAIdZaV+HvdwO1gXlAHBBujNlirX2nrDvxdh1FEREREQkcXwN/BmYaY9oAG46/\nYa0dDYwGMMZ0B1qcSZIIShRFREREys7Ps56Bj4BbjDHfAA6ghzHmfiDCWjvxbO1EiaKIiIhIBWOt\nzQd6n/TyFg/t3vk9+1GiKCIiIlJW/p/1XC78XjcVERERkcCkiqKIiIhIGTn8P+u5XKiiKCIiIiIe\nqaJYwaWOG+3vECq9Jo//w98hBIXqM6b4O4RKLyc6yt8hVHpTMp2lN5Lfra+/AwCNURQRERGR4KaK\nooiIiEiDnUwhAAAgAElEQVRZhQRHrU2JooiIiEhZ+X/B7XIRHL0UERERkTJTRVFERESkjLQ8joiI\niIgENVUURURERMpKy+OIiIiISDBTRVFERESkrDRGUURERESCmSqKIiIiImWldRRFREREJJipoigi\nIiJSRg7NehYRERGRYKaKooiIiEhZadaziIiIiAQzVRRFREREyiokOGptwdFLERERESkzVRRFRERE\nysihMYoiIiIiEsxUURQREREpK41RFBEREZFgpoqiiIiISFkFyRhFJYoiIiIiZaVb+ImIiIhIMFNF\nUURERKSMHI7gqLUFRy9FREREpMxUURQREREpqyCZzKKKooiIiIh4pIqiiIiISFlp1rOIiIiIBDNV\nFEVERETKSrOeRURERCSYqaIoIiIiUkYOjVEUERERkWCmiqKIiIhIWWkdRREREREJZqooioiIiJRV\nkFQUK3WiuGLFChITE8nNzaVZs2YMGjSIiIgIr9tlZWUxdOhQduzYgdvt5vbbb6d79+4ALFu2jMGD\nBxMXF1f0OZMmTaJGjRrl1b2AtOm7NcxJmkae00W9xo2577F/UD08/JR2y+bP5esF88HhoHZsHPf2\n7kNkdM1ibd5OGE70ubXo0rN3eYVfacQ+159j23/m0PQP/R1KhbB01SrenDwZpzOX5hdeyNABTxNx\n0v/Lp2uTl5fHK2NGs/aHFABuuOZqBvTqjcPh4Nvvv+eNiW/hcrmoXq0az/bpwyUtWvqjiwHBm3Ny\naW327NlDjx49mD59OjVrFpwzfvrpJ1555RWOHj0KwJNPPsm1115bfh0LYDs2pbBqbjL5Lhfn1WtA\n+/u6U7X6Oae0+/rjD0hd/x3Vwgv+7mvWiaVj94Jz75Tnn6JG9LlFbS+/uSPN49uUTwfE7yrtpeeD\nBw8yZMgQRowYwezZs6lfvz6JiYllajd+/HhiY2OZOXMm06ZNIzk5mZSUgn8MUlJS6NatG0lJSUWP\nYE8Ssw4fJmncaB4e8CzPjx7PebFxfPr+u6e025W6jS/nfMxTw0bw7H8Sialbj3kz3i/WZvEnyaT+\nuLm8Qq80who3pP6o14m4+UZ/h1JhHDh0iEEJI3hz8GDmvjuNBnXrMXLyJK/bzFm4kB27dvHR5Mkk\nT5rE2pQUFixbitPpZMCwlxnSrz+zJ03m0Qe68eyrr/qjiwHBm3NyaW3mzp3LI488QlpaWrHtXnvt\nNTp37kxSUhIvvvgiAwcOxOVylUu/AtnRrEy+nD6VWx9+nPuff4Wo82JYOSfZY9s921O55aFHueeZ\nl7jnmZeKksSDe/dQLbxG0ev3PPOSksRCjpAQnz8CQWBE4QOrVq2iVatWNGrUCIAuXbowf/583G63\n1+0GDBhA3759AUhPTyc3N7fom21KSgpr166lW7du9OzZk3Xr1pVj7wLTlpTvadSkGXXq1gPgug63\n8d3ypacc84ZNmvLC6AmcU6MGztxcDh/YT3hkZNH7Wzem8OP367iuw63lGn9lUPPOzmTMW0DWkmX+\nDqXC+GbtWi4yhsYNGgBwT+fOfLZ4cbG/25La5OXnczQnh1ynE2fho1pYVcLCwlj8wUxaNmuG2+3m\nl927iY6K8ksfA4E35+SS2qSlpbF06VJGjRp1ymfn5+eTmZkJwJEjR6hWrVo59Cjw7dqyiZhG51Mz\nJhaAi65rx9bvVp9yTs5zOUn/dSfrv/yCD0YM5vMp48g8uB+APTu24XA4+DgxgRmvv8Saz+eQn59f\n7n0R/6m0l5737t1LbGxs0fM6deqQnZ1NdnZ2scsYpbULDQ1l0KBBLF68mHbt2tG4cWMAoqOj6dSp\nE+3bt2f9+vX079+fpKSkYp8VbA6mp1Ozdu2i5zXPq03O0SMcO3r0lMvPVUJDSfl2FTMmjCE0NIzb\n7nkAgMMH9pM8dRKPvTCEbxZ+Xq7xVwZpI8cCEH5laz9HUnHsSdtHXEydouexMTFkZWeTfeRI0eXn\nktrc0bEjC5Yt5Q/3dMWVl0fb+HjatW0LQFhoKOkHDtC1dy8OZmTwxguDyrdzAcSbc3JJbWJiYkhI\nSPD42f/617/o3bs3SUlJHDhwgOHDhxMaWmn/efNa1qEDRNSsVfQ8oua55OYcxXksp9jl5+zDh6jf\nrAVtbr+LmnViWf/lF8yfnMjdA17EnZ9PQ9OKtn+5G1euk88mjaJq9epc1u4Wf3QpsARIxc/XvO6l\nMSbEGFPFGHODMaaqL4M6G073jadKlSplbvfyyy+zaNEiMjIymDx5MgAJCQm0b98egNatW3PppZey\nevXqsxF6heV2ez6WpyufX3p1G4ZPeZ9bu97HhGEv4XI6effNBO7s3pPoc2t53EbkbMvPd3t8PeSE\nv9uS2oyfNo1zo6NZ+mEyi2d8wOGMTN6ZObOoTe1atVgycxbvjx7DoIQR7Ni16+x2oILw5lzr7Xn7\nRMeOHePZZ59l8ODBzJs3j0mTJjF8+HD27Nnz+wKuBE6uHB7nOOnWc1HnxfCnXk9xbmwcDoeD1u07\ncjg9jcwD6bS69kZuuOt+qoSGUS08nMvadWD7hu/LI3wJEF595TLGvAn8CDQGrgD2Ag/5MK4zMmHC\nBJYtK7jklp2dTZMmTYreS0tLIyoqinPOKT6INy4ujo0bN3pst3LlSpo2bUpMTAzh4eF07NiRJUuW\nkJmZyaxZs+jRoweOwllPbrc7KL/BzpvxPhvXfgtAztEj1G3UuOi9wwf2E14jgmrVqxfbJm33b2Qc\nOkSTlq0AaNP+j8ycOJ6dqVvZv28fH787BYCMQwfJz8/H6XRy32NPllOPJNjUrVOHDVt+LHq+Lz2N\nqMhIwk84V5TUZtGK5TzX50nCwsIICwvjLx06sGDZMu7q1InV67/nj9ffAECr5s1p3qQJW7dv5/yG\nDcuvgwGipHNtWdqcLDU1lZycHG64oeA4X3LJJVx44YVs3Lix2GTDYPHtvI/ZvvEHAJzHjlKrboOi\n97IPH6JaeDhhJ12aT/9tF/t//QVz1YkTgNyEVKmCXbOS8+o3oHa9wr9Zd8HrQtDMeva2oniVtfYt\n4Fpr7a1Ag9I28Ifjlx6SkpKYOnUqGzduZOfOnQAkJydz0003nbJNmzZtTttu4cKFTJw4EbfbTW5u\nLgsXLiQ+Pp7w8HBmzZrFkiVLANiyZQubNm2ibeHlpmDS6d4HeOaNUTzzxij+OTyBHVst+3b/BsDX\nC+Zz8VXXnLJNxqGDvPtmAlkZGQCsXbGUuo0acWGLVgyZMKXo867rcCtXtL1eSaL4VNv4eH7Y/CM/\n//ILAB/MmcPNJ/2/XFKbls2a8fnSrwBwulx8ufIbLmvVkipVqvBiQgLrChOfbTu2s33nTi5pGZyz\nnks615alzckaNmxIVlYWP/xQkBz98ssv7NixgxYtWvigF4Hv6k53FE06ufOp59i7I5VDaXsB2Pj1\nV1xw8anDUhyOEFbMnk7G/oJJQpu+/orz6jUgomYtDuz+lTXzPiE/Px9Xbi4bli+h6eVXlWufxL8c\npytNn8gYswp4AugD9AJWWGuvLm27zMzM0j/ch1asWMHYsWNxOp00aNCAIUOGEB0dzebNmxk2bBhJ\nSUkltsvMzGT48OGkpqbicDho164dvXr1IiQkhM2bN5OQkEB2djahoaH069eP+Pj4cu/j19t/K/d9\nlmTTurXMTZpGnsvFebFxdOvzT2pERrIzdSszxifyzBsFA9FXfDGP5V/Mo0pIFaJq1eLuv/fivNji\n3/7nz0wiOyPD78vjNHn8H37d/5moiMvjnD9jit/2vWx14dI3LhcN69bj1YED2bV7Ny/9+w2SJ046\nbZvoqCgOHT7M8MQx/Lh1KyEhIVxzxRU83fsxwkJDWfPDD7zx1gRcLhdVw8J4qmdPrrn8Cr/1Myfa\nv5NpPJ1rf/31V6/OxyeKj49n0aJFRcvjrF27ltGjR3Ps2DFCQ0N55JFHaNeuXXl3D4ApK9b7Zb+n\n8/PmFFbNnU2ey0V07Tr84YGHqV4jgn07d/DljHe555mXALBrV/L9ovnk5+cTUfNc2t/Xnchzz8OZ\ne4zlHyax9+efyM/Lo0nreK65/a9FV9P8pe9tN/i9nHd0wyaf5zjnXHKR3/vpbaL4OAWXmh8GHgE2\nWGvfLm07fyeKwSDQEsXKqCImihWRPxPFYOHvRDEYBFqiWFkFQqKYs/FHn+c41S9u6fd+ejWozlo7\nDhgHYIz5t7U2OEdji4iIiAQRbyezPA0cAmoCPYwxn1tr+/k0MhEREZFApcksxdwFvAvcZq1tBVzu\nu5BEREREJBB4u55LHhBHwbI4AKdfq0BERESksgsJjoqit4niV4WPbsaYkcBnvgpIRERERAKDt5NZ\nngeeBzDGrLHWOn0alYiIiEggC5Ixit5OZulMwTqKYYDDGFPbWnuJTyMTEREREb/y9tLzMAoW2u4N\nfAn80WcRiYiIiAS4k++ZXVl528vd1tqVANbadwjQW/iJiIiIyNnjbUXxmDHmRiDMGNMRqO3DmERE\nREQCW5DMeva2ovgYBeMThwGPFv4UERERkUqsxIqiMab5CU+P37bvOUD3cBYREZHgFRIcYxRLu/T8\n1gm/uwEH/0sSb/ZJRCIiIiISEEpMFK217QGMMdWBltba740xd6AFt0VERCSIOYJkHUVv66b/BVoX\n/t6cgvs+i4iIiEgl5m2iWN9aOxXAWjsCqOu7kEREREQCXEiI7x8BwNso3McnthhjmgBVfBeSiIiI\niASCUtdRNMZEAQOBD4wxscBvFNylRURERCQ4BckYxdKWx+kD9AdcwJPW2s/LJSoRERER8bvSKor3\nAwaIAt4DlCiKiIiIqKIIQI61NhdIN8ZULY+ARERERAKdQ7fwO0VwHBERERERAUqvKF5kjEmiIEk8\n/jsA1tr7fRqZiIiISKByBMbyNb5WWqLY9YTfJ/gyEBEREREJLKXdwm9peQUiIiIiUmEEyWSW4Kib\nioiIiEiZlbrgtoiIiIicRLOeRURERCSYqaIoIiIiUkaOIJn1HBy9FBEREZEyU0VRREREpKw0RlFE\nREREgpkqiiIiIiJldLR6NZ/vI9LneyidKooiIiIi4pESRRERERHxSImiiIiIiHikRFFEREREPFKi\nKCIiIiIeadaziIiISAVjjAkBxgGXAceAntbabSe8/2fgRcAFTLHWTjqT/aiiKCIiIlLx3AFUt9Ze\nCwwE/n38DWNMGDAS6ADcBDxqjIk9k50oURQRERGpeK4HPgew1q4C4k94ryWwzVp70FqbC6wAbjyT\nnfj00nOOQ1e2fe26C+r5O4RKr/qMKf4OISjsuPdhf4dQ6dV+vKe/Q6j0el12ib9DkOARBRw+4Xme\nMSbUWuvy8F4mEH0mO1FFUURERKTiyaD4zVtCCpNET+9FAofOZCdKFEVEREQqnq+BTgDGmDbAhhPe\n+xFoZoypZYypSsFl55VnshNdGxYRERGpeD4CbjHGfAM4gB7GmPuBCGvtRGNMP+ALCoqCU6y1v57J\nTpQoioiIiFQw1tp8oPdJL2854f05wJzfux9dehYRERERj5QoioiIiIhHShRFRERExCMliiIiIiLi\nkRJFEREREfFIs55FREREyshZJczfIZQLVRRFRERExCNVFEVERETKyO32dwTlQxVFEREREfFIFUUR\nERGRMsoPkpKiKooiIiIi4pEqiiIiIiJl5FZFUURERESCmSqKIiIiImWkiqKIiIiIBDVVFEVERETK\nKFhmPStRFBERESmjIMkTdelZRERERDxTRVFERESkjDSZRURERESCmiqKIiIiImWUjyqKIiIiIhLE\nVFEUERERKSONURQRERGRoKaKooiIiEgZBcuC26ooioiIiIhHqiiKiIiIlFF+viqKIiIiIhLEVFEU\nERERKaMgGaKoiqKIiIiIeKaKooiIiEgZaR1FEREREQlqqiiKiIiIlJHu9SwiIiIiQU0VRREREZEy\nCpYxipU6Ufxm+TLeShxDrjOXJk2b8eyLg6kREVGmdn/6Q3tq14kpanv/gw/RodPtbP8plRHDXubo\n0SM4HA569+nLNW3bllvfAsmKFStITEwkNzeXZs2aMWjQICI8HOfTtcvKymLo0KHs2LEDt9vN7bff\nTvfu3QFYtmwZgwcPJi4uruhzJk2aRI0aNcqre363dNUq3pw8Gaczl+YXXsjQAU8TcVL/T9cmLy+P\nV8aMZu0PKQDccM3VDOjVG4fDwbfff88bE9/C5XJRvVo1nu3Th0tatPRHFyus2Of6c2z7zxya/qG/\nQ6lwvv4/y7jFC3Dm5dE0NpbnO/+VGtWqe2y7dMtmhnyUzJJnBxV7fe/hQ/R8+y3e692HmuHBc07w\n1rK1axn9/jRynU6aNz6fwU88SUR4+Cnt3G43LyaOpmnDRjx0x1+LXv9g/jxmL1rIsdxcWjZpwpAn\nnqRqWFh5dkECQKW99Hzw4AGGD3mJYQlvMH32J9Rr0IDxY0aVqd3OHTuIiIrknekzix4dOt0OwL9f\nG87tf7mDd6bP5NkXh/DiwGdwuVzl2sdAcPDgQYYMGcKIESOYPXs29evXJzExsUztxo8fT2xsLDNn\nzmTatGkkJyeTklKQ2KSkpNCtWzeSkpKKHsGUJB44dIhBCSN4c/Bg5r47jQZ16zFy8iSv28xZuJAd\nu3bx0eTJJE+axNqUFBYsW4rT6WTAsJcZ0q8/sydN5tEHuvHsq6/6o4sVUljjhtQf9ToRN9/o71Aq\npIPZ2Qz7ZDavdr2PmX2eol7NWoxdtMBj25370xmz4PNTqjfzfvieXlMnk5aZWR4hVzgHDh/mxcTR\n/PvpgXyaOJ76sXGMem/aKe1++mUXj7w0iAVfryj2+qJVK5k+7zMmDh7K7FFjOJaby3tzPimv8CsE\nt9vt80cgqLSJ4pqVK2nZ6iIaNmoMwF+73M3C+fNPOfAltduQsp4qIVV48tGePHTP3Uyd+BZ5eXkA\n5Oflk5mRAcCRI9lUrVa1HHsXOFatWkWrVq1o1KgRAF26dGG+h+NcUrsBAwbQt29fANLT08nNzS2q\nSKakpLB27Vq6detGz549WbduXTn2zv++WbuWi4yhcYMGANzTuTOfLV5c7PiW1CYvP5+jOTnkOp04\nCx/VwqoSFhbG4g9m0rJZM9xuN7/s3k10VJRf+lgR1byzMxnzFpC1ZJm/Q6mQVqdupWX9+jQ6rzYA\nd151NV9s+OGU80aOM5fBH33IPzreVuz1tMwMlm75kZEP/K3cYq5oVq7/noubNqVxvXoAdL31VuYt\nX3rKMZ4xfx5/ufkPdLju+mKvz/3qS/7W+S9ER0YSEhLCC70e4083tS+3+CVweH3p2RgTAsQA+6y1\ngZHmlmDv3r3UOeFyZUydWLKzsziSnV3s8nNJ7fJceVx1TRsef+qfHDuWwzN9n6RGRA263t+NfgOf\npW+vR5mZ9F8OHjjAkFdfJzS0Ul/J92jv3r3ExsYWPa9Tpw7Z2dlkZ2cXu/xcWrvQ0FAGDRrE4sWL\nadeuHY0bFyTu0dHRdOrUifbt27N+/Xr69+9PUlJSsc+qzPak7SMupk7R89iYGLKys8k+cqTo8nNJ\nbe7o2JEFy5byh3u64srLo218PO0Kh0iEhYaSfuAAXXv34mBGBm+8UPyynpxe2sixAIRf2drPkVRM\n+zIOExsVXfS8TlQU2ceOcST3WLHLz6/N/YS/XnkVTWPjim0fExnF6/fcX27xVkR79qcTW7t20fPY\n82qTdeQI2UePFrv8/NwjvQD4dkNKse1//u1XDjRtxmNDB5N28ABXtGzFU3/rXi6xVxRBcqtn7yqK\nxpg7gZ+Az4GtxphbfBrVWeB253t8PaRKFa/bdb7zLp565l9UrVqVyMgo7nngQZZ9+SXHjh3jpYH/\n4rnBQ/lo/gISJ08h4ZVh7N2z56z3I9Dl53s+flVOOs7etHv55ZdZtGgRGRkZTJ48GYCEhATaty/4\nFtu6dWsuvfRSVq9efTZCrxBOd9P5kJAQr9qMnzaNc6OjWfphMotnfMDhjEzemTmzqE3tWrVYMnMW\n748ew6CEEezYtevsdkDEg/zTXFILcfzv7/rDNaupEhLCny+/srzCqlTcXpw7SuLKy2NlynoSBjzD\n9BH/5nBWFonv//dshljh6dJzcYOAq621lwPXAa/4LqQzN3n8OLrf15Xu93VlzscfsT89vei99LR9\nREZFcc455xTbJjau7mnbff7ZXLZt/b+i99xuN1VCQ9meuo2cnByuu7FgfNLFl1zK+U0uZPPGDT7u\nYWCYMGEC999/P/fffz+ffPIJ6Sccv7S0NKI8HOe4uLjTtlu5ciVpaWkAhIeH07FjR7Zs2UJmZiZT\npkwp9j+L2+0Oqspt3Tp1SD+wv+j5vvQ0oiIjCT/h+JbUZtGK5dx5622EhYURGRHBXzp04Nv168nM\nymLRiuVF27Rq3pzmTZqwdfv28umYBLXY6JqkZ/1vbGFaRgZR1c/hnKr/G8Izb/06fvz1Vx6ckEi/\n96dxzOXkwQmJpGVm+CPkCicuJob0gweLnu/bv5+oiAjCq3ueMHSymHNrcfM1bYgIDycsLIzbb2zH\nD/+3xVfhSgDzNlHcb63dB2Ct3QsE5P+pPR97vGjSycR33mPThhR27fwZgI8//JAbbmp3yjZXt7n2\ntO1+St3G2+PHkZeXx7GcHJJnzuAPt3SgfsOGZGdlsuGH9QD8umsXP2/fTnPTolz66W+9e/cumlgy\ndepUNm7cyM6dOwFITk7mpptuOmWbNm3anLbdwoULmThxIm63m9zcXBYuXEh8fDzh4eHMmjWLJUuW\nALBlyxY2bdpE2yCaXd42Pp4fNv/Iz7/8AsAHc+Zw80n9L6lNy2bN+HzpVwA4XS6+XPkNl7VqSZUq\nVXgxIYF1GzcCsG3Hdrbv3MklLTXrWXzvmiZN2fjLLnbuL/jy+NHaNdzQovj5c8ojj5H0+D94r3cf\n/vPA36gWGsZ7vfsQE6mxtN649rLWpPyf5efffgNg1oLPaXfV1V5v/8dr27Lwm2/IOXYMt9vNl9+u\n4qKmzXwVboUULBVFhzeBGGM+AsKBpUA8EAd8BWCtfe5026VlHfVrL1euWM6ExDG4nE7qN2jAC0OH\nERUdzZbNm3jt5SG8M31mie1yjh7lPyNeY/OGDbhcTtr/8RYefeJJHA4H69asYdzokeQeyyU0NJTu\njzzKje1vLvc+Vnf7f6b1ihUrGDt2LE6nkwYNGjBkyBCio6PZvHkzw4YNIykpqcR2mZmZDB8+nNTU\nVBwOB+3ataNXr16EhISwefNmEhISyM7OJjQ0lH79+hEfH1+u/at+2L/fi5atLlz6xuWiYd16vDpw\nILt27+alf79B8sRJp20THRXFocOHGZ44hh+3biUkJIRrrriCp3s/RlhoKGt++IE33pqAy+WialgY\nT/XsyTWXX+G3fu6492G/7ftMVbTlcWo/3tPfIRT5Zqtl3OKFOPPyaHBuLV786138dvAgwz/9iPd6\n9ynW9rdDB3lg3Bi+fO7FUz6nzZAX+PzpZwNmeZxzLrvE3yEUWf7dWkb/9z2cLhcN4uJ45R9P8cve\nPQwZN5aZ/3mzWNtBY0YVWx4nLy+PSR/O4ouvl5OXn0/LC5swqPfjHpfX8YfqF7Vw+DuGjb/s9XmO\nc3GDWL/309tE8aHTvWetffd07/k7UQwGgZAoVnb+ThSDRUVMFCuaQEoUK6tAShQrs0BIFFN27fF5\njnNpwzi/97PUwV7GmMuste8aY6oCjwDHgCnWWs+zE0RERESkUihxjKIxph8w0RgTCiQAtwCXACPL\nITYRERGRgJTvdvv8EQhKqyjeDbQF3MD9QDNr7SFjzDc+j0xERERE/Kq0Wc+Z1to8oDXwk7X2UOHr\nfr9mLiIiIuIvwTLrubRE0W2MaQ50Bz4FMMY0AzSDQkRERKSSK+3S8wvAe8Ae4DljzE3Afym4JC0i\nIiISlAJlDKGvlZgoWmvXANccf26MWQlcaK11+jowEREREfEvb+/1HG+M+Y6C+z0vNcZooSgREREJ\nWm637x+BwNtb+I0GHrTWNgB6AeN8F5KIiIiIBAJvE8Wj1trNANbaDUCu70ISERERCWzBMuu5xDGK\nxphHC391GmPGAcuAqwHd00xERESkkitt1nPdwp8rC38a4DCw3mcRiYiIiAQ4zXou8La19pfCtRRF\nREREJIiUlij2K3y8RcFt/GoBeRRUFW/2bWgiIiIigSlQxhD6WmmTWf5rjPke6AgkAvWASOBNXwcm\nIiIiIv5VWqKYADxkrc0FhgG3AvHAv3wdmIiIiEigCpZ1FEu79FzFWptijKkH1LDWrgMwxgRI+CIi\nIiLlL1gms5RWUTx+q75bgUUAxpgwIMKXQYmIyP+3d9/xUVTrH8c/CYROqCkCIoJ4KGIB9QKKIHav\ngnpRFBsIKHb0IkWkilQVEFQU7BqKgqI0QZpUlasoRc+9gBRBIKEmgZCy+/tjlpiETdj1x2Y32e/7\n9doXs7NnJs8ZJrPPPnPORkQk+E5XUfzGGLMKOBtoZ4yphzNWcXrAIxMREREJUZrMAlhrRwHdgObW\n2pPfnfi2tXZEwCMTERERkaA6XUURa+2vOZa3AlsDGpGIiIhIiNMYRREREREJa6etKIqIiIhIbqoo\nioiIiEhYU0VRRERExE+a9SwiIiIiYU0VRRERERE/qaIoIiIiImFNFUURERERP7nCo6CoiqKIiIiI\neKeKooiIiIifNEZRRERERMKaKooiIiIiflJFUURERETCmiqKIiIiIn5yoYqiiIiIiIQxVRRFRERE\n/BQuYxSVKIqIiIj4SV+4LSIiIiJhTRVFERERET+5wqSkqIqiiIiIiHgV0IpiGXdmIHcvQJkjR4Md\nQrGXVik62CGEheqPdQt2CMVe0htTgh1CsVdz7IhghyCFJFwms6iiKCIiIiJeaYyiiIiIiJ9UURQR\nERGRsKaKooiIiIifQvFP+BljygIfA7FAMvCgtTbRS7tIYC4w21o7qaB9qqIoIiIiUjw8Cmyw1rYC\nPgdnELIAACAASURBVAReyKfdMKCKLztUoigiIiLiJ7fbHfDH33AlsMCzPB+4Nm8DY0wHwJWjXYF0\n61lERESkiDHGdAWeybN6H3DEs5wMVMqzzQVAJ6ADMNCXn6NEUURERMRPwZ70bK19B3gn5zpjzCyg\noudpReBwns0eAGoCS4A6QLoxZru1Nt/qohJFERERkeJhFXAz8D1wE7Ai54vW2t4nl40xg4G9BSWJ\noERRRERExG+uYJcUvXsT+MAYsxJIx7nNjDHmWWCLtfZLf3eoRFFERESkGLDWHgPu9LL+VS/rBvuy\nTyWKIiIiIn7SX2YRERERkbCmiqKIiIiIn1RRFBEREZGwpoqiiIiIiJ9CdNbzGadEUURERMRP4ZIo\n6taziIiIiHiliqKIiIiInzSZRURERETCmiqKIiIiIn5yhUdBURVFEREREfFOFUURERERP2mMooiI\niIiENVUURURERPykiqKIiIiIhDVVFEVERET8pL/MIiIiIiJhTRVFERERET+FSUFRFUURERER8U4V\nRRERERE/adaziIiIiIQ1VRRFRERE/KRZzyIiIiIS1lRRFBEREfGTxiiKiIiISFhTRVFERETETxqj\nKCIiIiJhrdhVFFeuXMnEiRNJT0+nfv36DBgwgAoVKvjcLisri7Fjx7JmzRqysrK477776NChQ65t\nZ8+ezbJlyxg7diwA77//PgsXLsx+/dChQxw7dozly5cHtrMhYPnatYybMoWMjHTOr1uXob2eo0L5\n8j61ycrK4qUJr7Hu518AaPWPy+n1SA8iIiLY8NtvjHrjdY6npeFyuXio493cet11wehi0PlyTp+u\nzd69e+nSpQtTp06lcuXKAGzbto2XXnqJ48ePA/Dkk0/SokWLwutYCFv1X8sbixeSkZXFeXFx9G93\nO+VLl/Hadvlvmxny+UyW9BuQa/2+I4fp9s5bfNTjCSqXK+91Wzm9uOf/zYnfd3B46mfBDqXIWfHT\nj0yYMY30jEzq167NoG4PU6FcuVxt5q5cwQfz5hBBBGVKl6L3/Q/SuG490tLTGfn+u2zatg2X20WT\neufRt/NDlClVKki9CT2qKBZBhw4dYsiQIYwePZpZs2ZRs2ZNJk6c6Fe7WbNmsXPnTqZPn86HH37I\n1KlT2bhxIwBHjhxh+PDhjBkzJtcg1s6dO5OQkEBCQgJvvfUWZcuWZfjw4YXT6SA6ePgwA8aMZtzg\nwcz54ENqnVWDsVMm+9zmq0WL2L5rF59PmcLMyZNZ98svLPx2OW63m2eGDObxBzsz8+3JvDliJGMm\nvcmOP/4IRjeDypdz+nRt5syZQ/fu3UlMTMy13ciRI2nXrh0JCQkMHDiQvn37kpmZWSj9CmWHUlMZ\nNnsWI+66hxlP9KRG5aq8/s1Cr213HkhiwsIFpwxqn/fzTzzy3hQSk5MLI+RiKeqcs6k5fhQV2l4V\n7FCKpINHjzJo8luMefoZvnj5VWrFxvLa9Km52mzfs4dxUxN4/bm+TB8+km7tb6fXeKcA8s7sz8l0\nuZg+fCQzRowmLT2dd7+cHYyuhCy32x3wRygoVoni2rVradSoEbVr1wagQ4cOzJ8//5SDXVC7pUuX\n0q5dO0qWLEl0dDTXX3898+fPB2DRokVUr16dnj175hvDuHHjaNmyJVdccUWAehk6Vq9bR2NjOKdW\nLQA6tmvH3MWLcx3vgtpkuVwcT0sjPSODDM+jdFQp0jMyePT+B2jRrBkA8TExVI6uxL48iU448OWc\nLqhNYmIiy5cvZ/z48afs2+VykexJZI4dO0bp0qULoUeh77ut/6NhzZrUrlYdgDsuu5yvN/x8ynUk\nLSOdwZ9/xlM33JRrfWLyUZb/9itj732g0GIujirf0Y6j8xaSsuTbYIdSJK3d8AuNz63LOfFnAXDn\nNdcxf/WqXOdxqagoBnbrTkyVKgA0PrcuSYcPk5GZSdMGDene/nYiIyMpERlJgzp1+DMp/K7BUsxu\nPe/bt4+4uLjs57GxsaSmppKamprrNlxB7fK+FhcXx5YtWwCyb0F/9dVXXn/+1q1bWbZsGbNnh8en\nrr2J+4mPic1+HhcTQ0pqKqnHjmXffi6ozW033MDCb5dzTce7yMzKouWll9KmZUsA/nXzzdnbfDpn\nDsfSjnNho0aF1LPQ4cs5XVCbmJgYxowZ43Xfffr0oUePHiQkJHDw4EGGDx9OyZLF6pLwt+w/eoS4\n6ErZz2Ojo0k9cYJj6Sdy3X4eOWc2tze7jPPi4nNtH1MxmlEdOxVavMVV4tjXASjX7OIgR1I07T1w\ngLhq1bKfx1atSsrx46QeP559+7lGTAw1YmIApzr2yicf0bppM6JKlqRFkwuzt92TlMgnC+YzoGv3\nwu1EiAuRgl/A+fSuYIypA3QAsgc3WGuHBiimv83lcnldX6JECZ/beSv1Rkb6VnidNm0ad911l9cx\nkcWRy+X9tyTn8SqozZsffkiVSpVY/tlM0k6c4KmBA3l/xgw633VXdrspUxP4eNYsJo0cRZkwrHj5\nck77et7ndOLECfr168fgwYNp1aoVGzZs4JlnnqFRo0bEx8fnu104yG/cUWTEX+f1Zz98R4nISG69\npBl7Dh8qrNBEfJbfbcsSXt7PjqelMfDtSew7cIDXe/fN9drm37fx73Gvcvd1N3DVJU0DEquENl9v\nPU8FygP7cjxCwqRJk+jUqROdOnVi9uzZJCUlZb+WmJhIdHQ0ZcuWzbVNfHx8vu3yvrZ//35iY2M5\nnaysLJYsWcKtt956BnpVNJwVG0vSwQPZz/cnJRJdsSLlchzvgtp8s3IFd9x4E1FRUVSsUIH211/P\n9+vXA5Cens5zw15k3pIlfDJhIg3q1Su8joWQgs5Vf9rktXXrVtLS0mjVqhUATZo0oW7dutnjccNZ\nXKXKJKX8NbYw8ehRosuUpWyOQfzz1v/Ir7t3c/+kiTz7yYecyMzg/kkTSUw+GoyQRU4RX60aSYcP\nZz/ff+gg0eXLU7ZM7klZfyYl8eDQQURGRvJ2/wFUzDEZccGa1Tw6cjhPdbyHru1vK7TYiwqX2x3w\nRyjwNVE8Zq0dYq196+QjoFH54eSts4SEBN577z02btzIzp07AZg5cyatW7c+ZZvmzZvn2+6qq67i\nyy+/JDMzk+TkZBYuXEibNm1OG8eWLVuoWLEiNWrUOHOdC3EtL72Unzf/mj3JZPpXX9HWc+vYlzYN\n69dnwfJlAGRkZrJ0zWouatQQgGeHDiHl2DE+fm0CNcO4wlXQuepPm7zOPvtsUlJS+PnnnwH4448/\n2L59Ow0aNAhAL4qWf9Q7j41/7GLnASf5/nzdD7TKc1ze7f4oCY89xUc9nuDVex+gdMkoPurxBDEV\no4MRssgpWjS5kA1b/seOvX8C8Nnib2jT9NJcbY6kpNDtpaFcc+lljHriqVwzmhd9/x2jP/qAN/r0\n46aWxX/MveSvwFvPxpjzPYv7jDGdgP8AbgBr7X8DHJvfqlatysCBA+nTpw8ZGRnUqlWLIUOGALB5\n82aGDRtGQkJCge06dOjA7t276dSpExkZGdxxxx0080yqKMiuXbvCKkkEqFalCsN6P8czQwaTkZnJ\n2WfVYETfvmy0lkGvvMzMtyfn2wagz6OPMXziBG7t/CCRkZH8o2lTHrr7Hn7cuJFla9ZQp1Yt7n/6\nqeyf92z3h7nissuC1d2gyO9c9fV8zk/FihV5+eWXeeWVVzhx4gQlS5bk+eefp5Zn0lE4q1q+AgPa\n38Hzn04jIyuLWlWqMvD2f/Hrnt0M//JzPurxRLBDFDmtqpUqMfjhHjz32jgyMzOpFRvHiz0eY9O2\nrQydMpnpw0fy6eJF7E1KYsm6dSxZty5727f69WfC9Gm43W6G5vgmi4vPP59+nR8KRndCUqjMSg60\niII6aoxZms9Lbmtt29PtPDk5OTyOYhCVOaJbXYGWVklVosKQ+dWCYIdQ7CW9MSXYIRR7NceOCHYI\nYaHcZU0jgh3DuHnfBjzH6XnzVUHvZ4EVRWvt1QDGmDJAQ2vtT8aY24C5hRGciIiISCgKl4qir2MU\nPwZOfkfB+cAHgQlHREREREKFr4liTWvtewDW2tHAWYELSURERCS0adZzbu6TE1uMMfWA/L+gTURE\nRESKBV//DENPYLoxJg7YAzwSuJBEREREQlto1PsCz9dE8Spr7SUBjUREREREQoqvt55vNsbodrOI\niIgI4TNG0deKYgywxxjzO0611W2tbXmabURERESkCPM1UbwloFGIiIiIFCHh8j2KviaKUcCdnn8j\ngBpoQouIiIhIseZropgAfA5ciTPruULAIhIREREJcS5XeFQUfZ3MkmKtHQH8Ya3tDMQFLiQRERER\nCQW+VhTdxph4oKIxpjyqKIqIiEgY0xhFD2NMNDAEuA34CNjm+VdEREQkLIXK19cEWoGJojHmCeDf\nQCbwpLV2AfBlYQQmIiIiIsF1uopiJ8AA0ThVxAUBj0hEREQkxIVHPfH0k1nSrLXp1tokoFRhBCQi\nIiIiocHXySzgfH+iiIiISNjTZBZHY2NMAk6SeHIZAGttp4BGJiIiIiJBdbpE8a4cy5MCGYiIiIhI\nUaFZz4C1dnlhBSIiIiIiocWfMYoiIiIiQviMUfT1T/iJiIiISJhRRVFERETET+EyRlEVRRERERHx\nShVFERERET+FSUFRFUURERER8U4VRRERERE/adaziIiIiIQ1VRRFRERE/KRZzyIiIiIS1lRRFBER\nEfGTKooiIiIiEtZUURQRERHxU7jMelaiKCIiIuKncEkUdetZRERERLxSRVFERETET67wKCiqoigi\nIiIi3qmiKCIiIuInjVEUERERkbCmiqKIiIiIn8KloqhEsYhL374r2CEUe+8mZwQ7hLDwyEVNgh1C\nsVdz7Ihgh1Ds7X6mX7BDCAv1V34d7BDChhJFERERET/pT/iJiIiISFhTRVFERETET+EyRlEVRRER\nERHxShVFERERET/pL7OIiIiISFhTRVFERETETy63K9ghFApVFEVERETEK1UURURERPwUJpOeVVEU\nEREREe9UURQRERHxk75HUURERETCmiqKIiIiIn4Kxb/1bIwpC3wMxALJwIPW2sQ8bf4NdAJcwHBr\n7ecF7VMVRRERERE/ud3ugD/+hkeBDdbaVsCHwAs5XzTGVAaeBloA1wPjTrdDJYoiIiIixcOVwALP\n8nzg2jyvpwI7gPKex2m/DFK3nkVERET8FOzJLMaYrsAzeVbvA454lpOBSl423QVsBkoAI073c5Qo\nioiIiBQx1tp3gHdyrjPGzAIqep5WBA7n2ewm4CzgXM/zr40xq6y13+f3c3TrWURERMRPLnfgH3/D\nKuBmz/JNwIo8rx8CjgMnrLVpOIlk5YJ2qIqiiIiISPHwJvCBMWYlkI4zuxljzLPAFmvtl8aYa4G1\nxhgXsBJYVNAOlSiKiIiI+CnYYxS9sdYeA+70sv7VHMuDgEG+7lO3nkVERETEK1UURURERPzkIvQq\nioGgiqKIiIiIeKWKooiIiIifQnGMYiCooigiIiIiXqmiKCIiIuIn19/8osOiRhVFEREREfFKFUUR\nERERP2mMooiIiIiENVUURURERPwUJkMUVVEUEREREe9UURQRERHxk8YoioiIiEhYU0VRRERExE9u\n/a1nEREREQlnqiiKiIiI+MkVJmMUlSiKiIiI+EmTWUREREQkrBXbiuLKlSuZOHEi6enp1K9fnwED\nBlChQgW/2uzdu5cuXbowdepUKleuDMC6desYP348mZmZlC5dml69enHBBRcUat9C1Yqf1zNh1qdk\nZGRSv9bZDOzSlQply+ZqM3fNKj5cMJ+IiAjKlCpF70730ajOuQDMWLKYL1YsJy0jnYbn1GFQ566U\niooKRldC2vZNv7B2zkxcmZlUq1GLq+/pTKkyZU9pt+qL6Wxd/x9KlysPQOXYOG7o3AOAd/v3pHyl\nKtltL2l7A+df2rxwOlAEfLtuHa998iHpGRmcf04dBj/+JBXKlTulndvtZuDE1zjv7No8eNvt2eun\nz5/HrG8WcSI9nYb16jHk8Sd1Luex4qcfmTBjGukZmdSvXZtB3R4+5RjPXbmCD+bNIYIIypQuRe/7\nH6Rx3Xqkpacz8v132bRtGy63iyb1zqNv54coU6pUkHpTtMU9/29O/L6Dw1M/C3YoRYq+cLsIO3To\nEEOGDGH06NHMmjWLmjVrMnHiRL/azJkzh+7du5OYmJi9LiMjg379+tG/f3+mTp1K165dGThwYKH1\nK5QdSj7K4Pem8PJjT/L58FHUjIlhwmczcrXZvvdPxn86nYnP9GLa4Bfpdks7er3+GgCL/7OOaUsW\n8ea/e/PZ0OGcSM/gk0VfB6MrIe14SjJLp77HjQ89Rqf+LxFdLYY1X8302nbv71u57sGH6dh7EB17\nD8pOEg/t20vpcuWz13fsPUhJYg4Hjxxh4MTXeOW5vnw58U1qxsUz/qMPT2m37Y9ddB80gIWrVuZa\n/83aNUydN5e3Bw9l1vgJnEhP56OvZhdW+EXCwaNHGTT5LcY8/QxfvPwqtWJjeW361Fxttu/Zw7ip\nCbz+XF+mDx9Jt/a302v8WADemf05mS4X04ePZMaI0aSlp/PulzrG/oo652xqjh9FhbZXBTsUCWHF\nMlFcu3YtjRo1onbt2gB06NCB+fPn5xpPUFCbxMREli9fzvjx43PtNyoqivnz59OgQQPcbje7d+/O\nrjSGuzWbNtK4Tl1qx8UDcOfVbZn/3Zpcx7xUyZIMePAhYjzHrFGdc0k6coSMzEzmrl7F/dffSKUK\nFYiMjKT/Aw/yzxYtg9KXULbrt03E1K5D5Zg4ABpf0Yb//ee7U8bKZGVmkLR7J+uXfs300YNZ8O4b\nJB86AMDe7VuIiIjgi4ljmDZqED8s+AqXy1XofQlVa9b/xAXnncc5NWoAcNeNNzJvxfJTjvG0+fNo\n3/Yarr/iylzr5yxbygPt2lOpYkUiIyN54ZFHuaX11YUWf1GwdsMvND63LufEnwXAnddcx/zVq3Jf\nL6KiGNitOzFVnMp343PrknT4MBmZmTRt0JDu7W8nMjKSEpGRNKhThz+TEr3+LMlf5TvacXTeQlKW\nfBvsUIokt9sd8Eco8PnWszEmGqgDbLXWpgYsojNg3759xMXFZT+PjY0lNTWV1NTU7FvLBbWJiYlh\nzJgxXvddsmRJDhw4wH333cfhw4cZMWJEYDtTROw7eJC4qlWzn8dWqUrK8eOkpqVl336uUT2GGtVj\nAOcX7JXpCbS++BKiSpZkx769NE6uy+NjXybx8CEuqW/oeWfHoPQllKUcPkiFyn8d5wqVq5CedpyM\nE2m5bj+nHjlMzfoNaP7Pf1E5No71S79m/pSJ3NlrIG6Xi7NNI1q2v5PM9AzmTh5PqTJluKjNdcHo\nUsjZeyCJuOrVs5/HVatOyrFjpB4/nuvW6PPdHwHg+w2/5Np+x57dHDyvPo8OHUzioYM0bdiIng90\nLpTYi4q9Bw4QV61a9vPYqp7rRY5jXCMmhhoxOa4Xn3xE66bNiCpZkhZNLszedk9SIp8smM+Art0L\ntxPFQOLY1wEo1+ziIEciocyniqIxpgOwHPgEeNYY80JAo/p/yq86UqJECb/a5KdatWrMnz+f9957\njyFDhrBjx46/F2gxkt/XBJSIPPUUO37iBH3efJ1d+/czsPNDAGRmZfHdpo2M6vE4nwwYwtHUFCbO\n0niZvPL7hBkRkfs4R1eL4ZZHelIlLp6IiAguvvoGjiQlknwwiUYtrqLVvzpRomQUpcuV46I21/P7\nhp8KI/wiwZ3PwKNIL+eyN5lZWaz5ZT1jevVm6uhXOJKSwsRPPj6TIRZ5+Z3HXq8XaWn0njCeXfv2\nMajbw7le2/z7Nrq+OIS7r7uBqy5pGpBYRfITLhVFX289PwM0B5KAYcDtBTcPrvj4eJKSkrKfJyYm\nEh0dTdkcEyt8aZNXSkoKS5cuzX7eoEED6tevz5YtW85wD4qe+KpVSTpyOPv5/kOHiC5XnrKlS+dq\n9+eBA3Qe/iKRkZG8/VxfKnomWsRUrszVTZtRoWxZokqW5ObmLdmwVccV4Pt5XzB99BCmjx7Cr2tX\ncOzokezXUo8cpnS5ckTlOc5Je3Zhf1iTZ09uIkuUwP6whqQ9u3KsdtaLIz4mhqRDh7Kf7z9wgOgK\nFShXpoxP28dUqUrbfzSnQrlyREVF8c+r2vDzf38LVLhFUny1aiQdznm9OEh0+fKUzXOM/0xK4sGh\ng5zrRf8BVCxfPvu1BWtW8+jI4TzV8R66tr+t0GIXCTe+JopZ1toTgNta6wZC+tZz8+bN2bhxIzt3\n7gRg5syZtG7d2u82eUVGRjJ06FDWr18PwNatW9mxY4dmPQMtGjdhw7at7Ny3F4CZy5fQ+pJLcrU5\nkpJC99HDadu0GSN7PJZrhuK1l17GonU/kJaejtvtZtlPP9Lo3HMLtQ+h6vKbb8uedHJHz+fZt30r\nhxP3AbBx1TLOveDU20YREZGsnDWVoweccVubVi2jWo1aVKhclYN/7uaHebNxuVxkpqezYcUSzrvk\nskLtUyhrcdHF/PJfy449ewD4dOEC2lx2uc/bX9uiJYtWrybtxAncbjdLv19L4/PqByrcIqlFkwvZ\nsOV/7Nj7JwCfLf6GNk0vzdXmSEoK3V4ayjWXXsaoJ57Kdb1Y9P13jP7oA97o04+bWl5RqLGLnORy\nuwP+CAW+jlFcaYxJAGoZYyYBPwQwpv+3qlWrMnDgQPr06UNGRga1atViyJAhbN68mWHDhpGQkJBv\nm4KUK1eOl19+mVdffZXMzEyioqIYNmxYrrGO4apqdDSDu3TjuTcmkpGVSa2YWF7s+jCbt//O0Pff\nZdrgF/l02RL2HjjA0p9+ZOlPP2ZvO6lXH+68+hqOpKRw79BBuFwuGpxzDv07dglij0JTuYrRtO3U\nha/fe5OszEwqVY/lmnud2/f7d25n6bQP6Nh7ENXOqsmV/7qHeZMn4HK5qFC5Ctc94Ny2u/TGW1nx\nWQLTRw3ClZVFvYsvpWHzVsHsVkipVrkyQ594il5jRpGRmUmt+Hheeqonm7b8jyFvvM6MV8cVuH3H\nG2/iaEoK9zz3LFkuFw3r1mOAZ4iFOKpWqsTgh3vw3GvjyMzMpFZsHC/2eIxN27YydMpkpg8fyaeL\nF7E3KYkl69axZN267G3f6tefCdOn4Xa7GTplcvb6i88/n346ziJnXIQv98CNMZWAFkAT4Ddr7Ve+\n7Dw5OTk00uFiLPLnTcEOodibkpwR7BDCwiO1Y4IdQrHnOnYs2CEUe7uf6RfsEMJC/ZVfRwQ7hltG\nTQ54jjOnT/eg99PXiuJca+2VwIJABiMiIiIiocPXRPGgMeZpwAIuAGvtwoBFJSIiIhLCQmVWcqD5\nmigeAC72PADcgBJFERERkWLMp0TRWptrVoEx5qzAhCMiIiIS+sKkoOhbomiMGQo8CpQCygH/BRoH\nMC4RERERCTJfv0exHVAL5y+zNAR2BywiERERkRAXLt+j6Gui+KfnC7crWmu34FQWRURERKQY83Uy\nyx/GmIeAVGPMCKByAGMSERERCWnhMuu5wIqiMeYFz+IjwK/Ac8AeoFOA4xIRERGRIDtdRbEtMMxa\n6zLGvGStbQtMKIS4REREREJWqIwhDLTTJYoR+SyLiIiIhC3dena481kWERERkWLudBXFZsaY1TjV\nxEY5lt3W2pYBj05EREQkBIVJQfG0ieKFhRKFiIiIiIScAhNFa+2OwgpEREREpKgIl8ksvn7htoiI\niIiEGV+/cFtEREREPDTrWURERETCmiqKIiIiIn5aNviJsPh+aVUURURERMQrJYoiIiIi4pUSRRER\nERHxSomiiIiIiHilRFFEREREvFKiKCIiIiJeKVEUEREREa+UKIqIiIiIV0oURURERMQrJYoiIiIi\n4pUSRRERERHxSomiiIiIiHilRFFEREREvFKiKCIiIiJeKVEUEREREa+UKIqIiIiIV0oURURERMQr\nJYoiIiIi4pUSRRERERHxSomiiIiIiHilRFFEREREvFKiKCIiIiJeRbjd7mDHICIiIiIhSBVFERER\nEfFKiaKIiIiIeKVEUURERES8UqIoIiIiIl4pURQRERERr5QoioiIiIhXJYMdwOkYY9oAM4DNgBso\nC3xirZ0QzLh8ZYzZa62Nz7PuRuBua23n4ET19xhj+gLXAlGAC+hlrf3P39zXOOBVa+3Ov7n9NGCS\ntXbZ39m+qPDn/DfGLAN6WGt/K8wYixNv5zhwP/Aq8BCw11o7Kc82lwPDcD54VwRmWGtfKcy4i5Iz\nfU3XeV8wY0wd4Bfgxxyrl1hrhwYnIilqQj5R9Fhirb0bwBhTGrDGmI+stYeDHFfYMMY0AtoBV1hr\n3caYi4EPgIv+zv6stT3PZHzFnM7/QpDfOW6tvcjzen6bTgQesNb+ZoyJAlYbY5ZYa38qlMCLJp3T\nhWuztbZNsIOQoqmoJIo5VQSygIuMMYNwPsVXADoBO3E+qVYCygH9rbULjTHvAefhfHIdb639yBjT\nGnjJs6+twCPAvcDNnm3rAaOste97KgavA8nAfiDNWtvZGPOk5+e6gWnW2teMMe8D1TyPf54M2hjT\nEHgXSPU8DgXo+ATKEaA28JAxZoG1dr0x5vKcn+aNMT2AeOB94CvgADAP6AI08rz5TgQWA08DPYCP\ngQ7W2u3GmA5AK2Ag8A7OMQR4ylq7wRjzONAN+BOILZReh56c5/9InPN/N865C4AxphbwJlAGOAt4\nwVr7hTHmJeBqnN/7mdbaUcaYx4AHcapnP1hrnyrU3oSWAs9xT5vbjTF34VwjnrLWfg/sA57wXGfW\n4ySa6caYzsBtOP9n1YGh1tqZhdulIqGga3o6ua8ly4FxnHreDzLGxAHlgXustdsKtQdFjDGmBPAW\ncDbONeJLa+0LXt6/euNck0vg3AH6NDgRSzAVlTGKbY0xy4wxS4BPgCeBxsB9nk9Js4A7cZK7ltSZ\nfwAABUFJREFU6sCtwD1ASWNMReAq4A7gRiDLGBMBTAbusNa2xrngdPb8rErW2ltwKgt9PesmAZ2t\ntW1xksqT1YeOwJU4v0i3mb9KDkustS2ttTmTwTHAQGvttcDqM3ZkCom1djeeaguwxhjzG3BLAZvE\nA9dba0fj3PZo5akcXI1z4T/pHeABz3IXnP+X54HF1tqrgYeBNz1vAk8DzYH2QKkz1bciwNv5Px54\nyFr7D2Au0DBH+wbAK9ba63CO3+Oe9ffivPm2Ak5WbroAT1hrWwC/GmOK4ofHM8LHc/x3z3WgK851\nAZzjug8nOd8PvOI518FJXK4DrgdeDefjm4ev13TIfS15C+/n/VzP/8t8oEPhdaPIaOQ53ss8H3ya\nA2uttTcAl/PXByHwvH952pxrrb0S57rd3xhTubADl+ArKhet7NsUJxlj2gOvGWNSgJrAKmvtJmPM\nW8BUnDFGr1lrk40xPYG3gWicClYMzqeoGZ7criywCNiCUxEA2IVTkQGoYa3d5FleAdwNXACcg1Md\nA6gC1PcsWy99OB/43rO8itxv7CHPGHMecNRa+5Dn+aU4F+U/czSLyLH8u7U23bM8GadqFY/zyTUz\nx228BGCFMWYKEG2t3WiMaYLzRtLR06YqzoeATdbaE56ff/JYhgNv5/+71tpfAay173jWnXz5T+AF\nY0xXnGp3lGf9vcBInP+H+Z51XYBexphzgTXk/j8MKz6e498CeK418caYMkBTa+2LwIvGmKrAezgJ\nejKw3FrrAvYZYw7hXHty7i9c+XRN97yU81oSn895f3Ks9F6c81tyy3Xr2RgTDTxgjLkaOAqUztH2\n5PtXE6CZJ7EE5zpSh7/eIyVMFJWKojeTgS6eCSF7gAhPglHRWvtPnMRkgjHmLKCZtfZ2nFL6aJxq\nyh9Ae88vz0vAEs9+vf3x612eCiI4n7LA+WXaBFzt2cf7OJUzcG7j5bUZaOFZvszfzoaAC4GJxpiT\nlbz/4hzHAzhJN0DTHO1zHoPFwCU4kwGm5NyptfYIzkV+LM4bLMBvwFjPcb0LJ7n/H9DYGFPWc9vk\nkjPTrSJrjzGmPoAxpo8x5vYcr70IfGitvR9YivO7URqnQnMPTnWgszHmHKA7ztCB1jjHtGVhdiLE\n5HeOZ+VoczmA51qzE+c8/9gYcz6AtfYgsAM44WnfzNM+DueD6v4A96EoO+Wa7lmf81qS33nv7bot\n+esMHLbW3gu8ApTz3GmDv473b8BSz3W4Lc6wrq2FHKeEgKKcKH6MU4lahTPGpQZOMtHGGPMt8CnO\nWLe9QLwxZjVO1fBlz6fTp4G5nvWPARsL+FmPAe8aY77BeaPIsNb+jJMArTTGrMOpJu4uYB//xqny\nLAb+8Xc7HSzW2lk41dQfPMf8a+A5nFvqbxhjvsYZx+JtWzfwGVDKWuvtQjMZuAmY7nn+EnCX55Ps\nAmCjtTYRpxq2GqfKk3qGulZUPYJzTi7HSfDm5XjtU+Blz+/BdUB1TyX2ILAWJ3lciJPobMD5PVqC\nk8R8V3hdCC0FnONHcjQ713OsJgGPeK4ld+H8X3xnjFmLk+C862kf7/mdnws8Zq3NmXRKbt6u6XkV\ndN6L7xYDN3quEW/ivHfmPd5fASnGmBU4H+bd1trkwg1TQkGE260PYqfjmUQxw1qbaIwZBqTrqwVE\npCCeySwNrLV9T9dWRCRUFZUxisG2D1joGTtzBOe2toiIiEixpoqiiIiIiHhVlMcoioiIiEgAKVEU\nEREREa+UKIqIiIiIV0oURURERMQrJYoiIiIi4pUSRRERERHx6v8Ab4niX4aCGgwAAAAASUVORK5C\nYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x113df9d50>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plot_correlation_map(data)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 87,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x11437b190>"
      ]
     },
     "execution_count": 87,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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GlyDpd2DPQJJkGEiSDANJEoaBJAnDQJKEYSBJwjCQJGEYSJIwDCRJeAeyJL1hON/9b89A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\nRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x11435c510>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.countplot(data['Pclass'], hue=data['Survived'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 88,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x113f14550>"
      ]
     },
     "execution_count": 88,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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JUu/RXXoGY4ABmXkkcBlwQ4PrkaRepbuEwd8APwfIzPnAoY0tR5J6l6ZSqdToGoiI24Cf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\nQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x1144b0050>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.countplot(data['Sex'], hue=data['Survived'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 89,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x11437b050>"
      ]
     },
     "execution_count": 89,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<matplotlib.figure.Figure at 0x1138af150>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.countplot('Embarked', hue='Survived', data=data)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## __7.- How can we use the feature name?__"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 90,
   "metadata": {
    "collapsed": false,
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\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</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>A/5 21171</td>\n",
       "      <td>7.2500</td>\n",
       "      <td></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</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</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>STON/O2. 3101282</td>\n",
       "      <td>7.9250</td>\n",
       "      <td></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</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</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>373450</td>\n",
       "      <td>8.0500</td>\n",
       "      <td></td>\n",
       "      <td>S</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>6</td>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>Moran, Mr. James</td>\n",
       "      <td>male</td>\n",
       "      <td></td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>330877</td>\n",
       "      <td>8.4583</td>\n",
       "      <td></td>\n",
       "      <td>Q</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>7</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>McCarthy, Mr. Timothy J</td>\n",
       "      <td>male</td>\n",
       "      <td>54</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>7</th>\n",
       "      <td>8</td>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>Palsson, Master. Gosta Leonard</td>\n",
       "      <td>male</td>\n",
       "      <td>2</td>\n",
       "      <td>3</td>\n",
       "      <td>1</td>\n",
       "      <td>349909</td>\n",
       "      <td>21.0750</td>\n",
       "      <td></td>\n",
       "      <td>S</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>9</td>\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</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>347742</td>\n",
       "      <td>11.1333</td>\n",
       "      <td></td>\n",
       "      <td>S</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>10</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>Nasser, Mrs. Nicholas (Adele Achem)</td>\n",
       "      <td>female</td>\n",
       "      <td>14</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>237736</td>\n",
       "      <td>30.0708</td>\n",
       "      <td></td>\n",
       "      <td>C</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   PassengerId  Survived  Pclass  \\\n",
       "0            1         0       3   \n",
       "1            2         1       1   \n",
       "2            3         1       3   \n",
       "3            4         1       1   \n",
       "4            5         0       3   \n",
       "5            6         0       3   \n",
       "6            7         0       1   \n",
       "7            8         0       3   \n",
       "8            9         1       3   \n",
       "9           10         1       2   \n",
       "\n",
       "                                                Name     Sex Age  SibSp  \\\n",
       "0                            Braund, Mr. Owen Harris    male  22      1   \n",
       "1  Cumings, Mrs. John Bradley (Florence Briggs Th...  female  38      1   \n",
       "2                             Heikkinen, Miss. Laina  female  26      0   \n",
       "3       Futrelle, Mrs. Jacques Heath (Lily May Peel)  female  35      1   \n",
       "4                           Allen, Mr. William Henry    male  35      0   \n",
       "5                                   Moran, Mr. James    male          0   \n",
       "6                            McCarthy, Mr. Timothy J    male  54      0   \n",
       "7                     Palsson, Master. Gosta Leonard    male   2      3   \n",
       "8  Johnson, Mrs. Oscar W (Elisabeth Vilhelmina Berg)  female  27      0   \n",
       "9                Nasser, Mrs. Nicholas (Adele Achem)  female  14      1   \n",
       "\n",
       "   Parch            Ticket     Fare Cabin Embarked  \n",
       "0      0         A/5 21171   7.2500              S  \n",
       "1      0          PC 17599  71.2833   C85        C  \n",
       "2      0  STON/O2. 3101282   7.9250              S  \n",
       "3      0            113803  53.1000  C123        S  \n",
       "4      0            373450   8.0500              S  \n",
       "5      0            330877   8.4583              Q  \n",
       "6      0             17463  51.8625   E46        S  \n",
       "7      1            349909  21.0750              S  \n",
       "8      2            347742  11.1333              S  \n",
       "9      0            237736  30.0708              C  "
      ]
     },
     "execution_count": 90,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data.head(10)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Tip: can we detect married passengers? \n",
    "\n",
    "Or can we use the title? Mr, Master, etc."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 8.- How can we use the features SibSp and Parch?"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 91,
   "metadata": {
    "collapsed": false,
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\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</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>A/5 21171</td>\n",
       "      <td>7.2500</td>\n",
       "      <td></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</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</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>STON/O2. 3101282</td>\n",
       "      <td>7.9250</td>\n",
       "      <td></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</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</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>373450</td>\n",
       "      <td>8.0500</td>\n",
       "      <td></td>\n",
       "      <td>S</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>6</td>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>Moran, Mr. James</td>\n",
       "      <td>male</td>\n",
       "      <td></td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>330877</td>\n",
       "      <td>8.4583</td>\n",
       "      <td></td>\n",
       "      <td>Q</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>7</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>McCarthy, Mr. Timothy J</td>\n",
       "      <td>male</td>\n",
       "      <td>54</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>7</th>\n",
       "      <td>8</td>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>Palsson, Master. Gosta Leonard</td>\n",
       "      <td>male</td>\n",
       "      <td>2</td>\n",
       "      <td>3</td>\n",
       "      <td>1</td>\n",
       "      <td>349909</td>\n",
       "      <td>21.0750</td>\n",
       "      <td></td>\n",
       "      <td>S</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>9</td>\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</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>347742</td>\n",
       "      <td>11.1333</td>\n",
       "      <td></td>\n",
       "      <td>S</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>10</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>Nasser, Mrs. Nicholas (Adele Achem)</td>\n",
       "      <td>female</td>\n",
       "      <td>14</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>237736</td>\n",
       "      <td>30.0708</td>\n",
       "      <td></td>\n",
       "      <td>C</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   PassengerId  Survived  Pclass  \\\n",
       "0            1         0       3   \n",
       "1            2         1       1   \n",
       "2            3         1       3   \n",
       "3            4         1       1   \n",
       "4            5         0       3   \n",
       "5            6         0       3   \n",
       "6            7         0       1   \n",
       "7            8         0       3   \n",
       "8            9         1       3   \n",
       "9           10         1       2   \n",
       "\n",
       "                                                Name     Sex Age  SibSp  \\\n",
       "0                            Braund, Mr. Owen Harris    male  22      1   \n",
       "1  Cumings, Mrs. John Bradley (Florence Briggs Th...  female  38      1   \n",
       "2                             Heikkinen, Miss. Laina  female  26      0   \n",
       "3       Futrelle, Mrs. Jacques Heath (Lily May Peel)  female  35      1   \n",
       "4                           Allen, Mr. William Henry    male  35      0   \n",
       "5                                   Moran, Mr. James    male          0   \n",
       "6                            McCarthy, Mr. Timothy J    male  54      0   \n",
       "7                     Palsson, Master. Gosta Leonard    male   2      3   \n",
       "8  Johnson, Mrs. Oscar W (Elisabeth Vilhelmina Berg)  female  27      0   \n",
       "9                Nasser, Mrs. Nicholas (Adele Achem)  female  14      1   \n",
       "\n",
       "   Parch            Ticket     Fare Cabin Embarked  \n",
       "0      0         A/5 21171   7.2500              S  \n",
       "1      0          PC 17599  71.2833   C85        C  \n",
       "2      0  STON/O2. 3101282   7.9250              S  \n",
       "3      0            113803  53.1000  C123        S  \n",
       "4      0            373450   8.0500              S  \n",
       "5      0            330877   8.4583              Q  \n",
       "6      0             17463  51.8625   E46        S  \n",
       "7      1            349909  21.0750              S  \n",
       "8      2            347742  11.1333              S  \n",
       "9      0            237736  30.0708              C  "
      ]
     },
     "execution_count": 91,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data.head(10)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Tip: can we use it to detect the size of the family? \n",
    "\n",
    "Can you suppose the probability of survival if: singleton, small family and large family?"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 92,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x113269610>"
      ]
     },
     "execution_count": 92,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<matplotlib.figure.Figure at 0x114346e50>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "data['Family']= data['Parch']+ data['SibSp']+1\n",
    "data.loc[data[\"Family\"] == 1, \"FamilySize\"] = 'singleton'\n",
    "data.loc[(data[\"Family\"] > 1)  &  (data[\"Family\"] < 5) , \"FamilySize\"] = 'small'\n",
    "data.loc[data[\"Family\"] >4, \"FamilySize\"] = 'large'\n",
    "sns.countplot(data['FamilySize'],hue=data['Survived'])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Source and more information at: \n",
    "* https://www.kaggle.com/c/titanic\n",
    "* https://www.kaggle.com/startupsci/titanic/titanic-data-science-solutions\n",
    "* https://www.kaggle.com/viczyf/titanic/titanic-random-forest-82-78"
   ]
  }
 ],
 "metadata": {
  "anaconda-cloud": {},
  "kernelspec": {
   "display_name": "Python [conda env:python2]",
   "language": "python",
   "name": "conda-env-python2-py"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 2
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython2",
   "version": "2.7.13"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 1
}