 titanic data analysis project.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 4,
   "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>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",
       "  </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",
       "\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",
       "   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  "
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# to collect the data sets these are good websites.\n",
    "#www.data.gov\n",
    "#aws/publuc/data\n",
    "#google/public/data\n",
    "\n",
    "import pandas as pd\n",
    "from pandas import DataFrame,Series\n",
    "\n",
    "data1 = pd.read_csv('desktop/data1/train.csv')\n",
    "data1.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "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",
      "PassengerId    891 non-null int64\n",
      "Survived       891 non-null int64\n",
      "Pclass         891 non-null int64\n",
      "Name           891 non-null object\n",
      "Sex            891 non-null object\n",
      "Age            714 non-null float64\n",
      "SibSp          891 non-null int64\n",
      "Parch          891 non-null int64\n",
      "Ticket         891 non-null object\n",
      "Fare           891 non-null float64\n",
      "Cabin          204 non-null object\n",
      "Embarked       889 non-null object\n",
      "dtypes: float64(2), int64(5), object(5)\n",
      "memory usage: 83.6+ KB\n"
     ]
    }
   ],
   "source": [
    "data1.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [],
   "source": [
    "\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "import seaborn as sns\n",
    "%matplotlib inline\n",
    "sns.set(style=\"darkgrid\")\n",
    "\n",
    "\n",
    "\n",
    "# Who are the passenger in titanic?"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<seaborn.axisgrid.FacetGrid at 0x11c6d50f0>"
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 360x360 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.catplot(x='Sex', kind='count',data=data1)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<seaborn.axisgrid.FacetGrid at 0x11c6cdc88>"
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 405.725x360 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.catplot('Sex',hue='Pclass',kind = 'count',data=data1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [],
   "source": [
    "# i want male,female,child \n",
    "def female_male_sex(passenger):\n",
    "    Age,Sex = passenger\n",
    "    if Age < 16:\n",
    "        return 'child'\n",
    "    else:\n",
    "        return Sex"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [],
   "source": [
    "data1['person'] = data1[['Age','Sex']].apply(female_male_sex,axis =1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "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>Cabin</th>\n",
       "      <th>Embarked</th>\n",
       "      <th>person</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",
       "      <td>male</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",
       "      <td>female</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",
       "      <td>female</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",
       "      <td>female</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",
       "      <td>male</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>NaN</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>330877</td>\n",
       "      <td>8.4583</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Q</td>\n",
       "      <td>male</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>54.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>17463</td>\n",
       "      <td>51.8625</td>\n",
       "      <td>E46</td>\n",
       "      <td>S</td>\n",
       "      <td>male</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>2.0</td>\n",
       "      <td>3</td>\n",
       "      <td>1</td>\n",
       "      <td>349909</td>\n",
       "      <td>21.0750</td>\n",
       "      <td>NaN</td>\n",
       "      <td>S</td>\n",
       "      <td>child</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>27.0</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>347742</td>\n",
       "      <td>11.1333</td>\n",
       "      <td>NaN</td>\n",
       "      <td>S</td>\n",
       "      <td>female</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>14.0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>237736</td>\n",
       "      <td>30.0708</td>\n",
       "      <td>NaN</td>\n",
       "      <td>C</td>\n",
       "      <td>child</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  22.0      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",
       "5                                   Moran, Mr. James    male   NaN      0   \n",
       "6                            McCarthy, Mr. Timothy J    male  54.0      0   \n",
       "7                     Palsson, Master. Gosta Leonard    male   2.0      3   \n",
       "8  Johnson, Mrs. Oscar W (Elisabeth Vilhelmina Berg)  female  27.0      0   \n",
       "9                Nasser, Mrs. Nicholas (Adele Achem)  female  14.0      1   \n",
       "\n",
       "   Parch            Ticket     Fare Cabin Embarked  person  \n",
       "0      0         A/5 21171   7.2500   NaN        S    male  \n",
       "1      0          PC 17599  71.2833   C85        C  female  \n",
       "2      0  STON/O2. 3101282   7.9250   NaN        S  female  \n",
       "3      0            113803  53.1000  C123        S  female  \n",
       "4      0            373450   8.0500   NaN        S    male  \n",
       "5      0            330877   8.4583   NaN        Q    male  \n",
       "6      0             17463  51.8625   E46        S    male  \n",
       "7      1            349909  21.0750   NaN        S   child  \n",
       "8      2            347742  11.1333   NaN        S  female  \n",
       "9      0            237736  30.0708   NaN        C   child  "
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data1[0:10]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<seaborn.axisgrid.FacetGrid at 0x11cb5ecf8>"
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432.85x360 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# 1.\n",
    "\n",
    "sns.catplot('Pclass',data=data1,kind='count',hue='person')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x11cd757f0>"
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAXkAAAEBCAYAAACdctWRAAAABHNCSVQICAgIfAhkiAAAAAlwSFlzAAALEgAACxIB0t1+/AAAADl0RVh0U29mdHdhcmUAbWF0cGxvdGxpYiB2ZXJzaW9uIDIuMi4yLCBodHRwOi8vbWF0cGxvdGxpYi5vcmcvhp/UCwAAFi9JREFUeJzt3X9s1PUdx/HX9acoJY7ubiWkYZmauJAJhA28jbTpMkvLcStpmq1grJFsk0Xb2SxzrHa4uDlKZWkkTrM/kMVNo7DBgAariygR2skgG40b24hSfigrZxFLbXt3vfvuD8dJS+F+9H5879Pn4y/vet+7F/f93ov6vi+fr8OyLEsAACPlZDoAACB1KHkAMBglDwAGo+QBwGCUPAAYjJIHAINR8gBgMEoeAAxGyQOAwSh5ADAYJQ8ABqPkAcBglDwAGCwvUy/84YcfKxyObwHM4uKZGhgYSlGixJErPnbNJdk3G7niY9dcUuLZcnIc+sxnbop7u4yVfDhsxV3yl7ezI3LFx665JPtmI1d87JpLSm82xjUAYDBKHgAMRskDgMEoeQAwGCUPAAaj5AHAYJQ8ABgsY+fJI/2KZs3QDYWf7vJR/5guDY5kMBGAVIup5O+55x5duHBBeXmfPPyxxx7T6dOn9cwzz2hsbEz33nuv7r777pQGxdTdUJgn7w93R27v/VWNLmUwD4DUi1rylmWpr69Pr7/+eqTk+/v71dzcrJ07d6qgoED19fVaunSpbr311pQHBgDELmrJv/vuu5KktWvX6uLFi/rWt76lm266SXfeeaduvvlmSdLy5cvV1dWlBx98MLVpAQBxiVryg4ODcrvd+ulPf6pgMKiGhgZVV1fL6XRGHuNyudTb2xvXCxcXz4w/rSSnsyih7VItW3NlKrdd3y/JvtnIFR+75pLSmy1qyS9atEiLFi2K3K6rq9PGjRv1/e9/P3KfZVlyOBxxvfDAwFDci/Q4nUXy+ew3Rc6WXJMdWJnIbdf3S7JvNnLFx665pMSz5eQ4EvrlOOoplEeOHFFPT0/ktmVZmjt3rnw+X+Q+n88nl8sV94sDAFIraslfunRJ7e3t8vv9Ghoa0q5du/TEE0+op6dHFy5c0MjIiF599VWVlZWlIy8AIA5RxzUVFRU6duyYVq1apXA4rDVr1mjx4sVqbm5WQ0ODgsGg6urqdMcdd6QjLwAgDjGdJ//QQw/poYceGnef1+uV1+tNSSgAQHKwrAEAGIySBwCDUfIAYDBKHgAMRskDgMEoeQAwGCUPAAaj5AHAYJQ8ABiMkgcAg1HyAGAwSh4ADEbJA4DBKHkAMBglDwAGo+QBwGCUPAAYjJIHAINR8gBgsJiu8QokUyAYktNZNO6+Uf+YLg2OZCgRYC5KHmlXkJ8r7w93j7tv769qdClDeQCTMa4BAINR8gBgMEoeAAxGyQOAwSh5ADAYJQ8ABqPkAcBglDwAGIySBwCDUfIAYLCYS37Tpk1av369JOn48eOqra3V8uXL9cgjj2hsbCxlAQEAiYup5Ht6erRr167I7R/96EfasGGDXnnlFVmWpe3bt6csIAAgcVFL/uLFi+ro6NC6deskSe+9955GR0e1cOFCSVJtba26urpSmxIAkJCoJb9hwwY1Nzdr1qxZkqTz58/L6XRGfu50OtXf35+6hACAhF13qeEdO3Zozpw5crvd2rlzpyQpHA7L4XBEHmNZ1rjbsSounhn3NpKuWofcLrI1l51y2yWLXXJMRK742DWXlN5s1y35ffv2yefzqaamRh999JGGh4flcDjk8/kij/nggw/kcrnifuGBgSGFw1Zc2zidRfL57LfqeLbkmuzAykTuax3gdngPs2Vf2gW54pdotpwcR0K/HF+35Ldt2xb57507d+rw4cPauHGjVq5cqaNHj2rx4sXavXu3ysrK4n5hAEDqJXRlqM2bN6u1tVVDQ0OaP3++Ghoakp0LAJAEMZd8bW2tamtrJUm33367/vCHP6QsFAAgOfgXrwBgMEoeAAxGyQOAwSh5ADAYJQ8ABqPkAcBglDwAGIySBwCDUfIAYDBKHgAMRskDgMEoeQAwGCUPAAaj5AHAYJQ8ABiMkgcAg1HyAGAwSh4ADEbJA4DBKHkAMBglDwAGo+QBwGCUPAAYjJIHAINR8gBgMEoeAAxGyQOAwSh5ADAYJQ8ABqPkAcBglDwAGCwv0wFgH0WzZuiGwvGHxKh/TJcGRzKUCMBUxVTyTz75pF555RU5HA7V1dXpvvvuU3d3tzZu3Ci/36/q6mo1NzenOitS7IbCPHl/uHvcfXt/VaNLGcoDYOqilvzhw4f1l7/8RXv27NHY2JhWrFght9utlpYW/e53v9OcOXN0//3368CBAyovL09HZgBAjKLO5JcsWaLnnntOeXl5GhgYUCgU0uDgoObNm6fS0lLl5eXJ6/Wqq6srHXkBAHGIaVyTn5+vLVu26Nlnn1VVVZXOnz8vp9MZ+bnL5VJ/f39cL1xcPDO+pP/ndBYltF2qZWuuWHKn689ml/fQLjkmIld87JpLSm+2mL94bWpq0ne/+12tW7dOfX19cjgckZ9ZljXudiwGBoYUDltxbeN0Fsnns9+EOFtyTXZgRfv5xMckK1c6XicR2bIv7YJc8Us0W06OI6FfjqOOa9555x0dP35ckjRjxgxVVlbqrbfeks/nizzG5/PJ5XLF/eIAgNSKWvJnz55Va2urAoGAAoGAXnvtNdXX1+vkyZM6deqUQqGQOjs7VVZWlo68AIA4RB3XlJeXq7e3V6tWrVJubq4qKyvl8Xg0e/ZsNTY2yu/3q7y8XFVVVenICwCIQ0wz+cbGRjU2No67z+12a8+ePSkJBQBIDpY1AACDUfIAYDBKHgAMRskDgMEoeQAwGCUPAAaj5AHAYFw0BEk38eIjXHgEyBxKHkk38eIjXHgEyBzGNQBgMEoeAAzGuCZLMfcGEAtKPksx9wYQC8Y1AGAwSh4ADMa4xhCBYGjctVNH/WMZTGNffJeB6YaSN0RBfu5VM3pcje8yMN0wrgEAg1HyAGAwxjW4rslm/cywgexByeO6Jpv1M8MGsgfjGgAwGCUPAAZjXANjcA48cDVKHsbgHHjgaoxrAMBglDwAGIySBwCDUfIAYDBKHgAMRskDgMFiKvmnnnpKHo9HHo9H7e3tkqTu7m55vV5VVlaqo6MjpSEBAImJWvLd3d06ePCgdu3apT/96U/6xz/+oc7OTrW0tOjpp5/Wvn379Pbbb+vAgQPpyAsAiEPUknc6nVq/fr0KCgqUn5+vW265RX19fZo3b55KS0uVl5cnr9errq6udOQFAMQhasnfdtttWrhwoSSpr69PL7/8shwOh5xOZ+QxLpdL/f39qUsJAEhIzMsanDhxQvfff78efvhh5ebmqq+vL/Izy7LkcDjieuHi4plxPf6yK9c2t5NszZVI7ni3mbgmfTKzJOM5Jz4mW/dlppArfunMFlPJHz16VE1NTWppaZHH49Hhw4fl8/kiP/f5fHK5XHG98MDAkMJhK65tnM4i+Xz2W40kE7liPUiuzDXZNtF+Hu05Y8kW6/Vnp/oeRvvzxfIYjrH4kCt+iWbLyXEk9Mtx1HHNuXPn9MADD2jz5s3yeDySpAULFujkyZM6deqUQqGQOjs7VVZWFveLAwBSK+pv8lu3bpXf71dbW1vkvvr6erW1tamxsVF+v1/l5eWqqqpKaVAAQPyilnxra6taW1sn/dmePXuSHggAkDz8i1cAMBglDwAGo+QBwGBc/g9xmXjOuz8QUmFBbtKfN5brs068piuAq/EJQVwmO+f9ytuX70vG80Y7k3iya7oCGI9xDQAYjJIHAIMxrrGhibPmWObTpklkRg/gapS8DU02a7bnKhypk8iMHsDVGNcAgMEoeQAwGOMaQwWCIRXk59p6Te14xLomPYDxKHlDTZxpS9l9Hrlpfx4gXRjXAIDBKHkAMBjjmmmMOTdgPkp+Gov12qsAshfjGgAwGCUPAAbLunHNZGuIs64J7Ib1h2AXWVfyE9d1kVjXBPbD+kOwC8Y1AGAwSh4ADEbJA4DBsm4mPx3xj5ZSZ+J7GwiGrnoMX6Iim1HyWYDFuVInln8QxpeoyGaMawDAYJQ8ABiMcQ2QBpN9r8JsH+lAyQNpcK3vVZjtI9UY1wCAwSh5ADBYzCU/NDSklStX6uzZs5Kk7u5ueb1eVVZWqqOjI2UBAQCJi6nkjx07ptWrV6uvr0+SNDo6qpaWFj399NPat2+f3n77bR04cCCVOQEACYip5Ldv365HH31ULpdLktTb26t58+aptLRUeXl58nq96urqSmlQAED8Yjq75vHHHx93+/z583I6nZHbLpdL/f39yU0GAJiyhE6hDIfDcjgckduWZY27HYvi4pmJvPSkJlt/pCA/95q3r3XfVLC2jD0lsl9i2SZZ+/t6zzPxGHU6i5J+3CaDXY99u+aS0pstoZIvKSmRz+eL3Pb5fJFRTqwGBoYUDltxbXOtN2ay9Ud8vk/PQHY6iyY9R/nKx0yF01mUtOe6/HxIjon7JZb3NpZtou3vWPfh9Z4n1cdtMiT72E8Wu+aSEs+Wk+NI6JfjhE6hXLBggU6ePKlTp04pFAqps7NTZWVliTwVACCFEvpNvrCwUG1tbWpsbJTf71d5ebmqqqqSnQ0AMEVxlfz+/fsj/+12u7Vnz56kBwKy0WQXmI9m4ndJrGWDVGDtGiAJJltzPprJvkuy5xQZ2YxlDQDAYJQ8ABiMcU0cknGtT64Xam8mXk+XY256o+TjkIxrfXK9UHsz8Xq6HHPTG+MaADAYJQ8ABpu24xrOUUY2SsZxy7E/vUzbkuccZWSjZBy3HPvTC+MaADAYJQ8ABjNyXJNN5zpnU9Zsk23vbSJ5ma8jGiNLfrKZo12ZeF62XWTbe5vIcct8HdEwrgEAg1HyAGAwI8c1QCpl26w/Eax3Yw5KHohTts36E8F6N+ZgXAMABqPkAcBgjGuuIZFrdk62DbNMmOjKY/3y9xMTj/WJnwd/IKTCgtxxz8PnI/Uo+WuYOJOUos9dr7UNs0yYJpZjfbK5Pp+P9GNcAwAGo+QBwGCMa/5vOpz7DKSSndbeYU2fT1Hy/5dN690AdmSntXdY0+dTjGsAwGCUPAAYjHHNFFw592Oej2wVyyw927+zms4zekp+CpjjwwSxrMWT7cf6dJ7RM64BAINR8gBgMMY1KZbts0xkl2w/3jI5O0/FGvqTrWcVCIam9JzxmlLJ7927V88884zGxsZ077336u67705WLmNk+ywT2SXb17rP5Ow8FWvoJ7IGVrIlXPL9/f3q6OjQzp07VVBQoPr6ei1dulS33nprMvMBAKYg4ZLv7u7WnXfeqZtvvlmStHz5cnV1denBBx+MafucHEeiLy3XZ2ZEvS/a7Wzfxk5Z2MZeWUzbJtGuSOR5k/Xa13vORJ830SwOy7KsRDb8zW9+o+HhYTU3N0uSduzYod7eXv385z9PKAgAIPkSPrsmHA7L4fj0bxbLssbdBgBkXsIlX1JSIp/PF7nt8/nkcrmSEgoAkBwJl/xXv/pV9fT06MKFCxoZGdGrr76qsrKyZGYDAExRwl+8fu5zn1Nzc7MaGhoUDAZVV1enO+64I5nZAABTlPAXrwAA+2NZAwAwGCUPAAaj5AHAYJQ8ABgsK0p+7969WrFihSorK/X8889nOo6Ghoa0cuVKnT17VtInSzx4vV5VVlaqo6MjI5meeuopeTweeTwetbe32yaXJD355JNasWKFPB6Ptm3bZqtskrRp0yatX79eknT8+HHV1tZq+fLleuSRRzQ2Npb2PPfcc488Ho9qampUU1OjY8eO2eIzsH//ftXW1qq6ulq/+MUvJNljP+7YsSPyXtXU1Gjx4sV67LHHbJFt9+7dkc/lpk2bJGXgGLNs7r///a9VUVFhffjhh9bHH39seb1e68SJExnL8/e//91auXKlNX/+fOvMmTPWyMiIVV5ebp0+fdoKBoPW2rVrrTfeeCOtmQ4dOmR9+9vftvx+vxUIBKyGhgZr7969Gc9lWZb11ltvWfX19VYwGLRGRkasiooK6/jx47bIZlmW1d3dbS1dutT68Y9/bFmWZXk8Hutvf/ubZVmW9ZOf/MR6/vnn05onHA5by5Yts4LBYOQ+O3wGTp8+bS1btsw6d+6cFQgErNWrV1tvvPGGbfbjZf/5z3+su+66y3r//fcznm14eNj6yle+Yg0MDFjBYNCqq6uzDh06lPZjzPa/yV+5ENqNN94YWQgtU7Zv365HH3008q97e3t7NW/ePJWWliovL09erzft+ZxOp9avX6+CggLl5+frlltuUV9fX8ZzSdKSJUv03HPPKS8vTwMDAwqFQhocHLRFtosXL6qjo0Pr1q2TJL333nsaHR3VwoULJUm1tbVpz/Xuu+9KktauXatvfvOb+v3vf2+Lz8Cf//xnrVixQiUlJcrPz1dHR4dmzJhhi/14pZ/97Gdqbm7WmTNnMp4tFAopHA5rZGREY2NjGhsbU15eXtqPMduX/Pnz5+V0OiO3XS6X+vv7M5bn8ccf15e//OXIbTvku+222yIHTV9fn15++WU5HI6M57osPz9fW7ZskcfjkdvttsV7JkkbNmxQc3OzZs2aJenqfel0OtOea3BwUG63W7/+9a/129/+Vi+++KLef//9jL9fp06dUigU0rp161RTU6MXXnjBNvvxsu7ubo2Ojqq6utoW2WbOnKkf/OAHqq6uVnl5uebOnav8/Py0H2O2L3m7L4Rmp3wnTpzQ2rVr9fDDD6u0tNQ2uSSpqalJPT09OnfunPr6+jKebceOHZozZ47cbnfkPjvsy0WLFqm9vV1FRUWaPXu26urqtGXLloznCoVC6unp0S9/+Uu99NJL6u3t1ZkzZzKe60ovvvii7rvvPkn22Jf/+te/9Mc//lGvv/663nzzTeXk5OjQoUNpz2X7y/+VlJToyJEjkdt2WwjNLgu1HT16VE1NTWppaZHH49Hhw4dtkeudd95RIBDQF7/4Rc2YMUOVlZXq6upSbm5uRrPt27dPPp9PNTU1+uijjzQ8PCyHwzHuPfvggw/SnuvIkSMKBoORv3wsy9LcuXMzvi8/+9nPyu12a/bs2ZKkb3zjG7bYj5cFAgH99a9/VVtbmyR7fC4PHjwot9ut4uJiSZ+MZrZu3Zr2Y8z2v8nbfSG0BQsW6OTJk5H/ne3s7Ex7vnPnzumBBx7Q5s2b5fF4bJNLks6ePavW1lYFAgEFAgG99tprqq+vz3i2bdu2qbOzU7t371ZTU5O+/vWva+PGjSosLNTRo0clfXJmRLpzXbp0Se3t7fL7/RoaGtKuXbv0xBNPZPwzUFFRoYMHD2pwcFChUEhvvvmmqqqqMr4fL/v3v/+tz3/+87rxxhsl2eP4v/3229Xd3a3h4WFZlqX9+/dryZIlaT/GbP+bvN0XQissLFRbW5saGxvl9/tVXl6uqqqqtGbYunWr/H5/5LcYSaqvr894LkkqLy9Xb2+vVq1apdzcXFVWVsrj8Wj27NkZzzaZzZs3q7W1VUNDQ5o/f74aGhrS+voVFRU6duyYVq1apXA4rDVr1mjx4sUZ/wwsWLBA3/nOd7RmzRoFg0F97Wtf0+rVq/WFL3zBFvvxzJkzKikpidy2w+dy2bJl+uc//6na2lrl5+frS1/6kr73ve/prrvuSusxxgJlAGAw249rAACJo+QBwGCUPAAYjJIHAINR8gBgMEoeAAxGyQOAwSh5ADDY/wATe0CAvLC8RQAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "data1['Age'].hist(bins=70)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "29.69911764705882"
      ]
     },
     "execution_count": 43,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data1['Age'].mean()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "male      537\n",
       "female    271\n",
       "child      83\n",
       "Name: person, dtype: int64"
      ]
     },
     "execution_count": 24,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data1['person'].value_counts()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<seaborn.axisgrid.FacetGrid at 0x11d229ba8>"
      ]
     },
     "execution_count": 25,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 936.85x216 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#multiple plots on one figer.\n",
    "\n",
    "# 2.\n",
    "\n",
    "fig = sns.FacetGrid(data1,hue='Sex',aspect=4)\n",
    "fig.map(sns.kdeplot,'Age',shade=True)\n",
    "\n",
    "oldest=data1['Age'].max()\n",
    "\n",
    "fig.set(xlim=(0,oldest))\n",
    "\n",
    "fig.add_legend()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<seaborn.axisgrid.FacetGrid at 0x11d06c320>"
      ]
     },
     "execution_count": 26,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 936.85x216 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig = sns.FacetGrid(data1,hue='person',aspect=4)\n",
    "fig.map(sns.kdeplot,'Age',shade=True)\n",
    "\n",
    "oldest=data1['Age'].max()\n",
    "\n",
    "fig.set(xlim=(0,oldest))\n",
    "\n",
    "fig.add_legend()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<seaborn.axisgrid.FacetGrid at 0x1a24202da0>"
      ]
     },
     "execution_count": 47,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 909.725x216 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig = sns.FacetGrid(data1,hue='Pclass',aspect=4)\n",
    "fig.map(sns.kdeplot,'Age',shade=True)\n",
    "\n",
    "oldest = data1['Age'].max()\n",
    "\n",
    "fig.set(xlim=(0,oldest))\n",
    "fig.add_legend()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 48,
   "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>Cabin</th>\n",
       "      <th>Embarked</th>\n",
       "      <th>person</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",
       "      <td>male</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",
       "      <td>female</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",
       "      <td>female</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",
       "      <td>female</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",
       "      <td>male</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",
       "\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",
       "   Parch            Ticket     Fare Cabin Embarked  person  \n",
       "0      0         A/5 21171   7.2500   NaN        S    male  \n",
       "1      0          PC 17599  71.2833   C85        C  female  \n",
       "2      0  STON/O2. 3101282   7.9250   NaN        S  female  \n",
       "3      0            113803  53.1000  C123        S  female  \n",
       "4      0            373450   8.0500   NaN        S    male  "
      ]
     },
     "execution_count": 48,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#. 3\n",
    "\n",
    "data1.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 49,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "1      C85\n",
       "3     C123\n",
       "6      E46\n",
       "10      G6\n",
       "11    C103\n",
       "Name: Cabin, dtype: object"
      ]
     },
     "execution_count": 49,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "deck = data1['Cabin'].dropna()\n",
    "deck.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 50,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<seaborn.axisgrid.FacetGrid at 0x1a240189e8>"
      ]
     },
     "execution_count": 50,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAWoAAAFcCAYAAADh+/RTAAAABHNCSVQICAgIfAhkiAAAAAlwSFlzAAALEgAACxIB0t1+/AAAADl0RVh0U29mdHdhcmUAbWF0cGxvdGxpYiB2ZXJzaW9uIDIuMi4yLCBodHRwOi8vbWF0cGxvdGxpYi5vcmcvhp/UCwAAGhhJREFUeJzt3X94zffdx/HXkQhVzVSbI7potlJ03LTrOrJdS2qMBGcEdxuNJu3GLR2xulqdpfGj2o5hsmkupqau1HZtY6JSl6Z60SoNVbWLYrtrCOLOiaMhR6ry45zv/YfbuR1RYvU955Pk+bgu1+V8c77n8z6aPn19c873OCzLsgQAMFarcA8AALg2Qg0AhiPUAGA4Qg0AhiPUAGA4Qg0AhiPUAGA4Qg0AhiPUAGA4Qg0AhiPUAGC4JhPq+vp6lZWVqb6+PtyjAEBINZlQu91uDRw4UG63O9yjAEBINZlQA0BLRagBwHCEGgAMR6gBwHC2hnrLli0aNWqUUlJS9NJLL0mSSkpK5HK5NHjwYOXl5dm5PAA0C7aF+sSJE5o1a5aWLFmioqIiHTx4UFu3blVOTo6WLFmijRs3av/+/dq6datdIwBAs2BbqN955x0NHTpUsbGxat26tfLy8nTLLbcoPj5eXbp0UWRkpFwul4qLi+0aAQCahUi7HvjYsWNq3bq1srKyVF5erocfflj33nuvYmJiAvdxOp2qqKhosK/X65XX6w3axuunAbRUtoXa5/Np9+7dWrVqldq1a6ennnpKbdu2lcPhCNzHsqyg25cUFBQoPz/frtEAoEmxLdR33nmnEhIS1LFjR0nSoEGDVFxcrIiIiMB9PB6PnE5ng30zMzOVmpoatM3tdis9Pd2ucQHAWLadox4wYIC2b98ur9crn8+nbdu2KTk5WUePHtWxY8fk8/m0YcMGJSYmNtg3OjpacXFxQb9iY2PtGhUAjGbbEXXfvn01fvx4PfbYY6qrq9P3v/99jR07Vvfcc4+ys7NVU1OjpKQkJScn2zUCADQLDsuyrHAP0RhlZWUaOHCgNm/erLi4uHCPAwAh06TfmVhTW9si1wbQsth26iMU2kRF6T9SUsKy9idvvRWWdQG0PE36iBoAWgJCDQCGI9QAYDhCDQCGI9QAYDhCDQCGI9QAYDhCDQCGI9QAYDhCDQCGI9QAYDhCDQCGI9QAYDhCDQCGI9QAYDhCDQCGI9QAYDhCDQCGI9QAYDhCDQCGI9QAYDhCDQCGI9QAYDhCDQCGI9QAYDhCDQCGI9QAYDhCDQCGI9QAYDhCDQCGI9QAYDhCDQCGI9QAYDhCDQCGI9QAYDhCDQCGI9QAYLhIOx/88ccfV2VlpSIjLy4zZ84cHT9+XEuXLlV9fb0yMzOVnp5u5wgA0OTZFmrLslRaWqp33303EOqKigpNnTpVhYWFioqKUlpamvr166du3brZNQYANHm2hfrIkSOSpJ/85Cc6e/asHnnkEd16663q37+/OnToIEkaMmSIiouLNXnyZLvGAIAmz7ZQe71eJSQkaMaMGaqrq1NGRoZSUlIUExMTuI/T6dS+ffuuuq/X6w3a5na77RoVAIxmW6gfeOABPfDAA4HbY8aM0dy5c/XUU08FtlmWJYfD0WDfgoIC5efn2zUaADQptoV69+7dqqurU0JCgqSLUf76178uj8cTuI/H45HT6Wywb2ZmplJTU4O2ud1ufvAIoEWy7eV5586d0/z581VTU6Pq6mqtW7dOCxYs0I4dO1RZWakvvvhCmzZtUmJiYoN9o6OjFRcXF/QrNjbWrlEBwGi2HVEPGDBAe/fu1ciRI+X3+/XYY4/pwQcf1NSpU5WRkaG6ujqNGTNGffr0sWsEAGgWHJZlWeEeojHKyso0cOBAbd68WXFxcYHt/5GSEpZ5PnnrrbCsC6Dl4Z2JAGA4Qg0AhiPUAGA4Qg0AhiPUAGA4Qg0AhiPUAGA4Qg0AhiPUAGA4Qg00QRfqfS1y7ZbK1o/iAmCPtpERip3zeljWds/MCMu6LRlH1ABgOEINAIYj1ABgOEINAIYj1ABgOEINAIYj1ABgOEINAIYj1ABgOEINAIYj1ABgOEINAIYj1ABgOEINAIYj1ABgOEINAIYj1ABgOEINAIYj1ABgOEINAIYj1ABgOEINAIYj1ABgOEINAIYj1ABgOEINAIYj1ABgOEINAIazPdS//vWvNX36dEnSP/7xD40aNUpDhgzR888/r/r6eruXB4Amz9ZQ79ixQ+vWrQvcnjZtmmbOnKm3335blmVp9erVdi4PAM2CbaE+e/as8vLylJWVJUk6efKkLly4oPvvv1+SNGrUKBUXF191X6/Xq7KysqBfbrfbrlEBwGiRdj3wzJkzNXXqVJWXl0uSTp06pZiYmMDXY2JiVFFRcdV9CwoKlJ+fb9doANCk2BLqNWvWqHPnzkpISFBhYaEkye/3y+FwBO5jWVbQ7ctlZmYqNTU1aJvb7VZ6erod4wKA0WwJ9caNG+XxeDRixAhVVVXp/Pnzcjgc8ng8gfucPn1aTqfzqvtHR0crOjrajtEAoMmxJdQrV64M/L6wsFC7du3S3LlzNXz4cH388cd68MEHtX79eiUmJtqxPAA0K7ado76ahQsXKjc3V9XV1erVq5cyMjJCuTwANEm2h3rUqFEaNWqUJKlnz57629/+ZveSANCs8M5EADAcoQYAwxFqADAcoQYAwxFqADAcoQYAwxFqADAcoQYAwxFqADAcoQYAwxFqADAcoQYAwxFqADAcoQYAwxFqADAcoQYAwxFqADAcoQYAwxFqADAcoQYAwxFqADAcoQYAwxFqADAcoQYAwzUq1BUVFQ22/etf/7rpwwAAGrpmqM+ePauzZ89qwoQJqqqqCtw+ffq0Jk+eHKoZAaBFi7zWF5955hl98MEHkqR+/fr9/06RkRoyZIi9kwEAJF0n1CtWrJAk/fKXv9TcuXNDMhBapgv19Wobec1vx2a1LnAjGvUdOnfuXJ08eVJVVVWyLCuwvVevXrYNhpalbWSk7lqwIOTr/s+0aSFfE7hRjQr14sWLtWLFCt1xxx2BbQ6HQ5s3b7ZtMADARY0K9RtvvKFNmzapU6dOds8DALhCo16e17lzZyINAGHSqCPqhIQEzZ8/XwMHDlTbtm0D2zlHfXU1tbVqExXV4tYGYI9GhbqwsFCSVFxcHNjGOeov1yYqSj0yM8Oy9n8XFIRlXQD2aVSot2zZYvccAIAv0ahQr1y58qrbn3zyyZs6DACgoUaF+tNPPw38vra2Vh999JESEhJsGwoA8P8a/YaXy1VUVOj555+3ZSAAQLB/6zKnnTp10smTJ697v9/97ncaOnSohg0bFjh9UlJSIpfLpcGDBysvL+/fWR4AWpQbPkdtWZb2798f9C7Fq9m1a5d27typoqIi1dfXa+jQoUpISFBOTo5WrVqlzp07a+LEidq6dauSkpK+2rMAgGbshs9RSxffAPPcc89dc5/vfve7ev311xUZGamKigr5fD55vV7Fx8erS5cukiSXy6Xi4mJCDQDXcEPnqE+ePKn6+nrFx8c36sFbt26txYsX67XXXlNycrJOnTqlmJiYwNedTudVP5TA6/XK6/UGbXO73Y1aEwCam0aF+tixY/rZz36mU6dOye/36/bbb9eyZcvUtWvX6+47ZcoUTZgwQVlZWSotLZXD4Qh8zbKsoNuXFBQUKD8//waeBgA0X40K9Zw5czR+/HilpqZKktauXasXXnhBr7/++pfuc/jwYdXW1uq+++7TLbfcosGDB6u4uFgRERGB+3g8Hjmdzgb7ZmZmBta6xO12Kz09vVFPCgCak0a96uOzzz4LCufo0aN15syZa+5TVlam3Nxc1dbWqra2Vps3b1ZaWpqOHj2qY8eOyefzacOGDUpMTGywb3R0tOLi4oJ+xcbG3uBTA4DmoVFH1D6fT2fPnlWHDh0kSZWVldfdJykpSfv27dPIkSMVERGhwYMHa9iwYerYsaOys7NVU1OjpKQkJScnf7VnAADNXKNCPW7cOD366KNKSUmRw+HQxo0bldmIiw5lZ2crOzs7aFtCQoKKior+vWkBoAVq1KmPSy+fq6ur0+HDh1VRUaEf/ehHtg4GALioUUfU06dPV3p6ujIyMlRTU6M///nPysnJ0fLly+2eDwBavEYdUZ85c0YZGRmSpDZt2uiJJ56Qx+OxdTAAwEWNCrXP5wt6Y8rp06eDPo0cAGCfRp36eOKJJzRy5Ej94Ac/kMPhUElJyXXfQg4AuDkaFeoxY8aod+/e2rlzpyIiIvTTn/5U3bt3t3s2AIAaGWpJ6tmzp3r27GnnLACAq/i3rkcNAAgdQg0AhiPUAGA4Qg0AhiPUAGA4Qg0AhiPUAGA4Qg0AhiPUAGA4Qg0AhiPUAGA4Qg0AhiPUAGA4Qg0AhiPUAGA4Qg0AhiPUAGA4Qg0AhiPUAGA4Qg0AhiPUAGA4Qg0AhiPUAGA4Qg0AhiPUAGA4Qg0AhiPUAGA4Qg0AhiPUAGA4Qg0AhiPUAGA4Qg0AhrM11Pn5+Ro2bJiGDRum+fPnS5JKSkrkcrk0ePBg5eXl2bk8ADQLtoW6pKRE27dv17p16/TGG2/owIED2rBhg3JycrRkyRJt3LhR+/fv19atW+0aAQCahUi7HjgmJkbTp09XVFSUJKlr164qLS1VfHy8unTpIklyuVwqLi5WUlJS0L5er1derzdom9vttmtUADCabaG+9957A78vLS3VW2+9pXHjxikmJiaw3el0qqKiosG+BQUFys/Pt2s0AGhSbAv1JYcOHdLEiRP13HPPKSIiQqWlpYGvWZYlh8PRYJ/MzEylpqYGbXO73UpPT7d7XAAwjq2h/vjjjzVlyhTl5ORo2LBh2rVrlzweT+DrHo9HTqezwX7R0dGKjo62czQAaDJs+2FieXm5Jk2apIULF2rYsGGSpL59++ro0aM6duyYfD6fNmzYoMTERLtGAIBmwbYj6hUrVqimpkbz5s0LbEtLS9O8efOUnZ2tmpoaJSUlKTk52a4RAKBZsC3Uubm5ys3NverXioqK7FoWAJod3pkIAIYj1ABgOEINAIYj1ABgOEINAIYj1ABgOEINAIYj1ABgOEINAIYj1ABgOEINAIYj1ABgOEINAIYj1ABgOEINAIYj1ABgOEINAIYj1ABgOEINXMOF+voWuTbMYttnJgLNQdvISHXKezUsa1dM/a+wrAvzcEQNAIYj1ABgOEINAIYj1ABgOEINAIYj1ABgOEINAIYj1ABuqgt1vha1bijwhhcAN1Xb1hHqPG1NyNctX/CfIV8zVDiiBgDDEWoAMByhBgDDEWoAMByhBgDDEWoAMByhBgDDEWoAMByhBgDD2R7q6upqDR8+XGVlZZKkkpISuVwuDR48WHl5eXYvDwBNnq2h3rt3r8aOHavS0lJJ0oULF5STk6MlS5Zo48aN2r9/v7Zu3WrnCADQ5Nka6tWrV2vWrFlyOp2SpH379ik+Pl5dunRRZGSkXC6XiouL7RwBAJo8Wy/K9PLLLwfdPnXqlGJiYgK3nU6nKioqGuzn9Xrl9XqDtrndbnuGBADDhfTqeX6/Xw6HI3Dbsqyg25cUFBQoPz8/lKMBgLFCGurY2Fh5PJ7AbY/HEzgtcrnMzEylpqYGbXO73UpPT7d9RgAwTUhD3bdvXx09elTHjh1TXFycNmzYoNGjRze4X3R0tKKjo0M5GgAYK6ShbtOmjebNm6fs7GzV1NQoKSlJycnJoRwBAJqckIR6y5Ytgd8nJCSoqKgoFMsCQLPAOxMBwHCEGgAMR6gBwHCEGgAMR6gBwHCEGgAMR6gBwHCEGgAMR6gBwHCEGgAMR6gBwHCEGgAMR6gBwHCEGgAMR6gBwHCEGgAMR6gBwHCEGgAMR6gBwHCEGgAMR6gBwHCEGgAMR6gBwHCEugW5UFfXItcGmrrIcA+A0GnburW+MW1aWNYuXbAgLOsCzQFH1ABgOEINAIYj1ABgOEINAIYj1ABgOEINAIYj1ABgOEINAIYj1ABgOEINAIYj1ABgOEINAIYj1ABgOEINoEW4UOdrsuuG5TKnb775ppYuXar6+nplZmYqPT09HGMAaEHato7QXVlvhnzd//m96ys/RshDXVFRoby8PBUWFioqKkppaWnq16+funXrFupRAKBJCHmoS0pK1L9/f3Xo0EGSNGTIEBUXF2vy5MmB+3i9Xnm93qD9Tp48KUlyu91B260wfXJIWVnZte9w4UJoBrnCdec6fz40g1zhunNJcpw7F4JJgjVmrlbeqhBM0tD1ZnNUnw3RJMEa9d/y/JkQTBKsUXN9URmCSYJdba7Y2FhFRjY+vw7LsqybOdT1LFu2TOfPn9fUqVMlSWvWrNG+ffv04osvBu7zyiuvKD8/P5RjAUDIbN68WXFxcY2+f8iPqP1+vxwOR+C2ZVlBtyUpMzNTqampQdtqa2t14sQJfeMb31BERMRXmsHtdis9PV1/+tOfFBsb+5Ue62YydS7J3NmY68aZOltLmutGHyfkoY6NjdXu3bsDtz0ej5xOZ9B9oqOjFR0d3WDfe+6556bPciN/q4WKqXNJ5s7GXDfO1NmYq6GQvzzve9/7nnbs2KHKykp98cUX2rRpkxITE0M9BgA0GSE/ou7UqZOmTp2qjIwM1dXVacyYMerTp0+oxwCAJiMsr6N2uVxyub76awsBoCWImD179uxwDxEObdq0Ub9+/dSmTZtwjxLE1Lkkc2djrhtn6mzMdXUhf3keAODGcK0PADAcoQYAw4Xlh4nhVF1drd/85jf66KOPFBERoejoaE2fPl29evUK61xlZWVKTk5W165dg7Y/8sgjYb1oVX19vZYvX66ioiI5HA75fD6lpqZq4sSJDd6oFEpX/nlduHBB3/72t/XMM8/ozjvvDNtcl/v000/lcrm0ePFiDRkyJNzj6MMPP1RWVpbuvvtuWZaluro6paWlKTMzM6xzfdn3/u9//3t17tw5TFNJL7zwgvbs2aO6ujodP348MF9GRoZGjx4d2mGsFsTn81lpaWlWXl6eVVdXZ1mWZe3YscNKSEiwKisrwzrbiRMnrAEDBoR1hqvJzc21srKyrKqqKsuyLOvcuXNWRkaG9cc//jGsc1355+X3+62FCxdaY8eODeNUwX71q19ZU6ZMsZ588slwj2JZlmXt3LnTGjduXOD2uXPnrMTEROvQoUNhnMrc7/1LTJivRZ36+PDDD1VeXq4pU6YELojSv39/zZ07V36/P8zTmcftdquoqEjz5s0LvFO0ffv2mjlzpjFHrZc4HA5lZ2fr0KFD+uc//xnucVRXV6c333xTTz/9tA4cOKDjx4+He6QGampqFBERodtuuy3co+A6WtSpj4MHD6pnz55q1Sr476ekpKQwTRTs1KlTGjFiRNC2+fPnq0ePHmGZZ9++feratau+9rWvBW3v2rVrg3+mmiAqKkrx8fE6cuSIevbsGdZZtm7dqrvuukvf/OY3NWjQIP31r3/VtGnTwjqTJO3fv18jRoyQ3+/X8ePHlZKS0uASDuFw5fe+y+XS+PHjwziRWVpUqFu1amXc6zMv53Q6tX79+nCPEeTy89DFxcVaunSp/H6/oqKitHbt2jBOdnUOh0Nt27YN9xhau3athg8fLkkaOnSonn32Wf385z9XVFRUWOfq3bu3Vq1aJeniz2vGjx+vV199VRMnTgzrXCZ+75ukRZ366N27tw4ePCjripeOL1q0SDt37gzTVObq3bu3Dh8+rOrqaklScnKy1q9fr6VLl+rMmdBfb/h6amtrdfTo0bB/CMVnn32mbdu26bXXXtMPf/hD5ebmyuv16p133gnrXFdq3769UlJStGfPnnCPgutoUaH+zne+ozvuuEP5+fny+S5+jtm2bdtUWFgY9v+5TXTXXXfpxz/+sX7xi18EPsihvr5e7733XoPTR+Hm9/v1yiuvqG/fvrr77rvDOsv69evVv39/vf/++9qyZYveffddZWVl6S9/+UtY57qSz+fTrl279K1vfSvco+A6WtSpD4fDoSVLlmju3LkaPny4IiMjdfvtt+vVV1814odjVztH/dBDDyk3NzdME0mzZ8/WypUrlZGRIZ/Pp88//1z9+vXT8uXLwzbTJZf/efn9ft13331atGhRmKeS1q1bF/hgjEvS09P1hz/8QYcPHw7r+f1L56gdDofq6+vVo0cPTZgwIWzzoHF4CzkAGM6sf78CABog1ABgOEINAIYj1ABgOEINAIYj1GiWfD6fVq5cqVGjRmnEiBEaOnSoFixYoNra2mvu16NHD1VWVjbYvnnzZr300kt2jQtcEy/PQ7M0Y8YMVVVV6eWXX9Ztt92m8+fP69lnn9Wtt96qBQsWfOl+PXr00I4dO9SxY8cQTgtcG6FGs1NWVqbhw4dr+/btat++fWC7x+PRnj171L17d82ZM0eff/65PB6Pevbsqd/+9rdq06aNevTooUcffVSffPKJ/H6/nn76aQ0YMECFhYV6++23tWzZMj3++OO6//77tWfPHpWXlyshIUEvvviice/WRPPBdxaanQMHDqhbt25BkZakmJgYDRkyRKtXr9bIkSO1evVqbdq0SWVlZXrvvfcC94uLi9O6deu0YMECTZ8+/aqnQo4fP65Vq1apqKhI77//vnbt2mX300IL1qLeQo6WoVWrVte8vvi0adP0wQcfaPny5SotLdWpU6d0/vz5wNfHjh0rSerevbu6du2qv//97w0eY8CAAWrVqpXat2+v+Ph4VVVV3fwnAvwfQo1mp0+fPjpy5Iiqq6uDjqorKio0Y8YMtWvXTj6fTykpKXr44YdVXl4edEXFy09h+P3+wIdMXO7yS6k6HI4GV2QEbiZOfaDZ6dSpk1wul3JycgKXaK2urtbs2bPVoUMHbd++XZMmTdLQoUMlSXv37g1cTVG6eFElSYFPZunbt2/onwRwGY6o0SzNmjVLS5YsUVpamiIiIlRbW6tBgwYpOztba9as0aRJk9SuXTu1b99eDz30UNBHZZ04cUIjR46Uw+HQokWL1KFDhzA+E4BXfQCA8Tj1AQCGI9QAYDhCDQCGI9QAYDhCDQCGI9QAYDhCDQCGI9QAYLj/BTWPwMwQbdHMAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<Figure size 360x360 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "levels =[]\n",
    "\n",
    "for level in deck:\n",
    "    levels.append(level[0])\n",
    "\n",
    "cob = DataFrame(levels)\n",
    "cob.columns = ['Cabin']\n",
    "\n",
    "sns.catplot('Cabin',data=cob,palette = 'winter_d',kind = 'count')\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 51,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<seaborn.axisgrid.FacetGrid at 0x1a2440ec18>"
      ]
     },
     "execution_count": 51,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 360x360 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "\n",
    "\n",
    "cob = cob[cob.Cabin !='T']\n",
    "sns.catplot('Cabin',data=cob,palette='summer_d',kind = 'count')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 52,
   "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>Cabin</th>\n",
       "      <th>Embarked</th>\n",
       "      <th>person</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",
       "      <td>male</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",
       "      <td>female</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",
       "      <td>female</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",
       "      <td>female</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",
       "      <td>male</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",
       "\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",
       "   Parch            Ticket     Fare Cabin Embarked  person  \n",
       "0      0         A/5 21171   7.2500   NaN        S    male  \n",
       "1      0          PC 17599  71.2833   C85        C  female  \n",
       "2      0  STON/O2. 3101282   7.9250   NaN        S  female  \n",
       "3      0            113803  53.1000  C123        S  female  \n",
       "4      0            373450   8.0500   NaN        S    male  "
      ]
     },
     "execution_count": 52,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# .4\n",
    "\n",
    "data1.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 53,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<seaborn.axisgrid.FacetGrid at 0x1a243fb048>"
      ]
     },
     "execution_count": 53,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 405.725x360 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.catplot('Embarked',hue='Pclass',data=data1,kind='count')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 54,
   "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>Cabin</th>\n",
       "      <th>Embarked</th>\n",
       "      <th>person</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",
       "      <td>male</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",
       "      <td>female</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",
       "      <td>female</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",
       "      <td>female</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",
       "      <td>male</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",
       "\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",
       "   Parch            Ticket     Fare Cabin Embarked  person  \n",
       "0      0         A/5 21171   7.2500   NaN        S    male  \n",
       "1      0          PC 17599  71.2833   C85        C  female  \n",
       "2      0  STON/O2. 3101282   7.9250   NaN        S  female  \n",
       "3      0            113803  53.1000  C123        S  female  \n",
       "4      0            373450   8.0500   NaN        S    male  "
      ]
     },
     "execution_count": 54,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# 5. who was alone and who was family?\n",
    "\n",
    "data1.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 55,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0    1\n",
       "1    1\n",
       "2    0\n",
       "3    1\n",
       "4    0\n",
       "Name: Alone, dtype: int64"
      ]
     },
     "execution_count": 55,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data1['Alone']=data1.SibSp + data1.Parch\n",
    "data1['Alone'].head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 56,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/Users/altaf/anaconda3/lib/python3.6/site-packages/pandas/core/indexing.py:189: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame\n",
      "\n",
      "See the caveats in the documentation: http://pandas.pydata.org/pandas-docs/stable/indexing.html#indexing-view-versus-copy\n",
      "  self._setitem_with_indexer(indexer, value)\n"
     ]
    },
    {
     "data": {
      "text/html": [
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       "<style scoped>\n",
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       "\n",
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>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",
       "      <th>person</th>\n",
       "      <th>Alone</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",
       "      <td>male</td>\n",
       "      <td>With Family</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",
       "      <td>female</td>\n",
       "      <td>With Family</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",
       "      <td>female</td>\n",
       "      <td>Alone</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",
       "      <td>female</td>\n",
       "      <td>With Family</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",
       "      <td>male</td>\n",
       "      <td>Alone</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",
       "\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",
       "   Parch            Ticket     Fare Cabin Embarked  person        Alone  \n",
       "0      0         A/5 21171   7.2500   NaN        S    male  With Family  \n",
       "1      0          PC 17599  71.2833   C85        C  female  With Family  \n",
       "2      0  STON/O2. 3101282   7.9250   NaN        S  female        Alone  \n",
       "3      0            113803  53.1000  C123        S  female  With Family  \n",
       "4      0            373450   8.0500   NaN        S    male        Alone  "
      ]
     },
     "execution_count": 56,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data1['Alone'].loc[data1['Alone'] > 0] = 'With Family'\n",
    "data1['Alone'].loc[data1['Alone'] == 0] = 'Alone'\n",
    "data1.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 57,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<seaborn.axisgrid.FacetGrid at 0x1a233db8d0>"
      ]
     },
     "execution_count": 57,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 360x360 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.catplot('Alone',data=data1,palette = 'Blues',kind = 'count')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 58,
   "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>Cabin</th>\n",
       "      <th>Embarked</th>\n",
       "      <th>person</th>\n",
       "      <th>Alone</th>\n",
       "      <th>Survivor</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",
       "      <td>male</td>\n",
       "      <td>With Family</td>\n",
       "      <td>No</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",
       "      <td>female</td>\n",
       "      <td>With Family</td>\n",
       "      <td>Yes</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",
       "      <td>female</td>\n",
       "      <td>Alone</td>\n",
       "      <td>Yes</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",
       "      <td>female</td>\n",
       "      <td>With Family</td>\n",
       "      <td>Yes</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",
       "      <td>male</td>\n",
       "      <td>Alone</td>\n",
       "      <td>No</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",
       "\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",
       "   Parch            Ticket     Fare Cabin Embarked  person        Alone  \\\n",
       "0      0         A/5 21171   7.2500   NaN        S    male  With Family   \n",
       "1      0          PC 17599  71.2833   C85        C  female  With Family   \n",
       "2      0  STON/O2. 3101282   7.9250   NaN        S  female        Alone   \n",
       "3      0            113803  53.1000  C123        S  female  With Family   \n",
       "4      0            373450   8.0500   NaN        S    male        Alone   \n",
       "\n",
       "  Survivor  \n",
       "0       No  \n",
       "1      Yes  \n",
       "2      Yes  \n",
       "3      Yes  \n",
       "4       No  "
      ]
     },
     "execution_count": 58,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 360x360 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "data1['Survivor'] = data1.Survived.map({0:'No',1:'Yes'})\n",
    "\n",
    "\n",
    "sns.catplot('Survivor',data=data1,palette='cool',kind ='count')\n",
    "\n",
    "data1.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 62,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/Users/altaf/anaconda3/lib/python3.6/site-packages/seaborn/categorical.py:3666: UserWarning: The `factorplot` function has been renamed to `catplot`. The original name will be removed in a future release. Please update your code. Note that the default `kind` in `factorplot` (`'point'`) has changed `'strip'` in `catplot`.\n",
      "  warnings.warn(msg)\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "<seaborn.axisgrid.FacetGrid at 0x1a2489a668>"
      ]
     },
     "execution_count": 62,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432.85x360 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.factorplot('Pclass','Survived',hue = 'person',data=data1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 63,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<seaborn.axisgrid.FacetGrid at 0x1a24a756d8>"
      ]
     },
     "execution_count": 63,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 360x360 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.lmplot('Age','Survived',data=data1,) #linear plot"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 65,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<seaborn.axisgrid.FacetGrid at 0x1a24c10a90>"
      ]
     },
     "execution_count": 65,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 405.725x360 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.lmplot('Age','Survived',hue = 'Pclass',data=data1,palette='cool')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 67,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<seaborn.axisgrid.FacetGrid at 0x1a24fc14a8>"
      ]
     },
     "execution_count": 67,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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sMXfpHh5+cRUrNh0hbqRupZKmVyfghWMpO6YgCM1DBImTqFjxDoeev43KL9/DiDVsT+vGMGrmKWJBSDKfIqJqtXMNoYh20hVHbqeVay4+h8fvHsP4oR2RZYkKv8prH+7gsZdXs35nEcZpAuWOg+W8MGcjOw+Wn/p1meAPxSitiohtUgWhDRFB4iR0fymmGiG48WMK//0E4b3rm61nkZinCCJHqpBo2BfqnvxKZs1eQUUg0RupCKjMmr2CPafYPzvda+fmSX35zV2jGdk/DwkoKg/z0ntb+e0/17Jtf9lJX/v7y/ezbX8Zi5bvr1f71Fhim1SxVFYQ2gYRJE4i69Lvk37B9aBYMcJVlH/8T0oXvoBWfqTZ2qCrUQjVv0BgRNWYPWfjCQX4VC3O7DkbT1uqIzvdyfen9ueh20cyuFc2AF8XBXhhzkaeeWMDe+sINNFY/Lif9VGzTWpVUG3yooSCIDSOCBInIVtsZIy9lrwbHsLRfRAA6pE9FM39HZUr52GoqU9Kq0tc0xMFArUwpxt+WrejGOMkjzEwWbejqF7n7Jjt4QfXDuJ/bh1O364ZAOwtqOTpN9Yze+5G8osCDXoNdanZJrWsKtqkpUMEQWgcsbrpNCy+LNpNupNo/g4ql7+NXlVMcPOnhPesI23UNFy9R9RuxGOzKnhciXpJmm4ktTNdXUzDRA/5sThimA4f5klie0lFGE2re3hK0wxKKsINOm/3Dmnce9Mwdh4s573P93HwqJ+t+8rYuq+M4f1ymHpBzwa/lm+L6XHKqiJ4xe53gtAqiSBRT47O/cidMYvA5k8JrF+CEQlQ8enrhHasJH3c9djadUKRZdwOGbfDimGYaLqOppvEtDi6YTY6aOjRKEpcR3al17lMNjvDhdUq1xkorFaZ7AxXUuft2y2T/+mawaY9pSxYto8jpSHW7Shmw84SnPbGL2s1qne/U2MGaR4bFlFVVhBaDfFpbABJseIbehm5Nz6Es+dQAGKF+yl+5/dUfDEHQ/3mSl2WJew2Kx6Xjcw0J1lpDnxuK06bgtKIvLK4pp90mezwfjnIJ0nGk5EY3i836fNKksSQ3tk8dNtIvj/lXNqlOTBMk1A0Mc9RGVAbvcQ1UVU2TDgqJrUFobUQQSIJFk8GWZfeRrspP8aSkQemSWjbFxS+9TihHaswzROv5BVZxmm34vPYaZfuJMNrw+O0YLPINHTb6Nplslr4uOc67VZ+PGMI9m8lrdmtCj+eMSQlGdWyLDFyQHsevWs0N0/qU5tJHYxoPPS3lSxYto9INPlyHHEjsSJLVJUVhNZBBIlGcHTqQ+51s0gbPR3J6sCIBqn4/E2K332WWPHXJ3+iJGGzWnA7bWT4HLRLc5DmtuKyW1Dk+m1JVFPOQ4r6j9ufolfndH73k3FkeBPF+zK8dn73k3H06px+skMlxaLIjB/aibwsV81LQo3F+WDlQR762wo+Wn2oURPSoqqsILQOIkg0kqQoeAdPIO/Gh3D1Gg6AVnyI4nlPU/H5W8Qjp9/HQZZlHPZEjaN26S7Sffb69TJM0CNhpHAlEt98ITtsFtxOK5BImEtlTaYT2l7dwPZZbq4Y0w27VSEU1Zn36V5+/fdVLPuqIOkeQU1V2XJ/FE0XK6AEoSWIIJEiijuNzIkzyZ72/7BmdgBMQjtWUvTvxwluW47ZgDIXNotS28vI9Dnwuq3YrcpJA4YeU6s3Mmq5q25ZlrhqfE8ev2cME4Z3xqJIVAVV3lyyi0de+pLVW48mlRNhAhFVp6Qygj+oEhd5FYLQrESQSDF7+3PIue4XpI29FsnmxFDDVH7xH4rnPY1adKDBx7MoMi67lXSvnXZpTtLcVhzWxOT3sTEjkU9RgaxHm6zseH343DZmXNKbx+4aw9hBHZAkKK2M8Mqi7Tzxymo27SlJKnPdNCEQ0SitEBPbgtCcRJBoApKs4B14UWIIqs9IALTSfErefZbyT98gHkkuGU2WJRx2K2ne6slvn722lyFL1ftThKqQYk2zVWlDZKY5+O4V/XjkjlGc1zcHgCMlIf76zmZ+/9o6dh06da2nk9ENk4qASmllRAxBCUIzEHkSTUhx+ci8+Du4+42lcvlctNJ8wru+JHJgE2nnX4m7/zgkOck8A0nCalGwWhRc9kTCnabHiekGMTUERuv4As3LcnPn1QOZVOhn/rJEnacDR/w899ZX9O2awbQLe9K9Q1qDj6tqcUoqI7jtVtwuq8itEIQm0iJBYuHChfz1r39F13VmzpzJLbfcUnvfjh07mDVrVu3v5eXlpKWlsWjRIt59912eeeYZsrKyALjooou47777mr39DWXP607ONfcT2rGSqjULMdUwlSveJrQzkYhnb39Oo88hyRI2mwVbddJyzXemRGLlUVPUJqyr2qzTbq3zsV3yfPxkxhD25Fcw//N97C2oYuehCnb+ax2De2Vz1fgedMz2NOj8ppnYryKsargcVtzO1ASLjbuLee/zfUy/8BwG985u9PEEoS1r9iBRVFTEc889x7x587DZbNx4442MHDmSc85JfFH269eP+fPnAxCJRLj++ut59NFHAdi6dSuzZs1iypQpzd3sRpNkGU//cTh7DMG/ZhGhHSvRyo5QMv+PuHqdT9qoaSjuhl9Rn/R81T8VDNq5TOKKg1jMIBrTiRtmkkXIv7Env/K4YoI11WZ/PGPIKZfb9uqcwc9vOY+t+8tY8Pk+8ouDbNpTwuY9JYzon8eUC3qQne5sUFsMM5GnEY4mgoXHaUVpRLB466NdbD9QTkTVRZAQznrN3kdfuXIlo0aNIj09HZfLxaRJk1i8eHGdj/373//O+eefz/DhiaWlW7Zs4d1332Xq1Kncf//9VFVVnfAcv99PQUHBcf8KCwub9DU1hOL0kHHhjeRc83OsOV0BCO9ZS+G/nyCw6RPMeKqHiUyIBLBqYXweK7lZbtqlO/G5rNgsJ18xdSqNrTYrSRIDe7bjl98fwR3TBpCb6cIEVm8r5NEXV/HWRzupCjZ846WaYFFSGSYQjiVdYTZSvTd3ROzRLQjN35MoLi4mO/ubq7OcnBw2b958wuMCgQBz5sxh4cKFtbdlZ2dz2223MWzYMJ599lkee+wxnnnmmeOe9+qrrzJ79uymewEpYsvpSs70nxHeuZqq1QswokGqVr1LaOcq0sddj6Nj75Sez1BDmIaGxZ2GzWrFZlXwuhO7xsU0nahqoOp6vYal6lNtdtzgjqc9jiwlSoUM7ZPNl1sKWbRiPxV+lc83HGbl5qNMGN6Zy0Z2rc35qK+4kdjgKBLV8bqtJx0CEwTh9Jo9SBiGUVs1FRKZw1Idl7MLFizgkksuqZ1/APjzn/9c+9933HEHl1566QnPmzlzJtOnTz/utsLCwuPmPVoLSZJx9xuNs/sgqta+T2j7cvSKQkoXvoCz51DSRk/H4slI2flMLYbuL0NxpSHbE0M6VouM1WLD7YS4YRKN6ahqHFXTOdmFeKqrzSqyzNjBHRjRP5dlXx1m8aqDBMIaS748xLKvDnPpyC5MGN65wUmBWtyg3K9it+p4nVbsdrFOQxAaqtk/NXl5eaxbt67295KSEnJyck543Mcff8zdd99d+3sgEOCdd97he9/7HpAILopy4sogn8+Hz+dLfcObkOxwk3HBDNz9RlP5xVxiRQeI7PuK6KFteM+bhHfQxUhKaq6GTcNAD1Yi6zEUlxdJ+mbEUZEl3A5rbRXbmBZHjcVPmMdoqmqzVovCxPO7MHZQB5auy+e/aw4RUXUWLNvPp+vyuXxMdy4Y0hGrpWGjpKoWJ6bFE70nESwEoUGafU5izJgxrFq1ivLyciKRCB999BHjx48/7jGmabJt2zaGDh1ae5vL5eLll19m06ZNALz++ut19iTaMlu7zmRffR8ZF38H2enF1GP4Vy+kaM5viebvSOGZTIxoCN1fjhmvOzEtkZNhIc1rJyfTRWaaA58rkZMx4txcHJa6l+42ttosgMNu4cqx3XninrFcOrILVotMIKwx5+PdPPLiKlZsOkK8ARnskMjcVrU4Zf4opRWJmlDNtR2tILRlzR4kcnNzue+++7j11lu5+uqrmTJlCoMGDeLOO+9ky5YtQGLZq9VqxW631z5PURSef/55Hn30US6//HK2bdvGAw880NzNb3KSJOHuM5K8G3+NZ+BFIMnoVcWUvv8XSpe8hB5ILgmtLqaeGH4y1Ohp2+SwWfC6E0l83dqn8eD3R9CtvRdLdd1zSUpttVkAj9PKtRf34vG7xzB+aEdkWaLcH+W1D3fw2MurWb+zCKOBX/QmoOpxyv0qJRURQpGYCBaCcAqSeRZ8QgoKCpg4cSJLly6lU6dO9X6eGdfQKks53bahTUkrP0LFF3OJHd0LgGSx4h16Gd7BE5EsJx+C+vnLWzlYHKFbjpNn7hhwmrNIyA539fBT/Zc7RVSdH/7+E0orI7RLd/DYXWNQZKnJ/m+VVIRZtPwAa7YV1p6jc66Xqy/sybndMxvU9mNZFRmvO1EIUZIkfvrMpxw44qd7Bx9/+vnFqXsBQkqJv1PzEGmqrZw1swPZV/2UzIkzkV0+TF3Dv/Z9Cuf8L5FDW1N0FhMjGkT3l2Hq9a+L5LRb8LoSgcrrstE510tmmiORp9AE76zsDBffn9qfh24fyeBe7QDILwrwwpyNPPPGBvYWVCZ13JoJ7uLyMIGQ2iSJh4LQVokg0QZIkoSr1/DEENTgiSDLxP2llH34d0o//Dt6VUlKzmPqMfRAKfFo8rWfHDYLaR47ORlu0r127EnmYpxKx2wPP7h2ML/47nD6dE2s/tpbUMnTr69n9tyN5BclVxtLN0z8YQ29urS5YZpiKEo464llHm2IbHOQPvpq3H1HUbn8bdTDu4ge2kphwU68Qy7BO+RSZKutUecwDZN4yI+paShuX9K1peRjVkrFtDgRVSeiaqRys7keHdO476Zh7DxYznuf7+PgUT9b95WxdV8Zw/vlMPWCnuRmJrfSCiAeNykuD+NyWHA5GpfFLQhtlQgSbZA1I492U35EZP9Gqla9SzxYQWD9YsK71pA+9hoc3QY1+hxGLIJpxLF40hq9/NZmVRLLT102IjGdcERH0+Mpm7vo2y2T/+mawaY9pSxYto8jpSHW7Shmw84SRg9qz5Vju5Ppc9TrWN+uRxWIxNANk2BEw+O04nLaUOSWLMYuCM1LBIk2SpIkXD2H4uhyLoGv/ktg41LiwXLKlryMvXM/0s1BgP20xzmVxOqn8urku/p9yZ7Ksb0LVYsTjVb3LlIQLSRJYkjvbAad04412wtZ9MV+SquirNh0hNVbC7lwWEcmj+6G13Xyntbp6lH5w4kA4nJYcaWomKAgtHbiXd7GyVY7aSOmkDvjlzg6nwuAmr+DW+NzmeLcgKWRu9WZRhw9WIEeqsI0UzdWZLcq1TkYx8xdpOC4siwxakB7Hr1rNDdd1gef24YeN1i6Np+H/raSBcv2EYmeWJOpvvWo4tWbHxVXhCmrjBKKxGrnMAThTCR6EmcIa3oOWVfcQ/TQVipXvA2Bci51bmVU/ADhvSbOnkOTXiJak3xnamqiV2FrXA/lWN/uXUSqexeN3aXUoshcOKwTowe259P1BSz58iDhqM4HKw/y+YYCJo3uxkXDOmGzJuZcGlqPyjQhqulENZCkGBZZxm5VcDgs2K1J7hEiCK2Q6EmcQSRJwtltIHk3/IpV0nlopoyXEOUfv0Lpotlo5UcbdXwzrqMHytGDVZhNsKmR3aqQXtO78NiwKnKjexc2q8KkUV154p4xXDGmG3arQiiqM+/Tvfz67yv5fEMB8bjRqHpUpplYRhuMapRVRiipiBAIqURVXayOEto80ZM4A0kWG18qw/lvRRduydhAT/MQ6uHdFL39WzwDLsQ3/HJkW8P2bPiGmagoq6sorqapkaXIEm6nDbfTRjSmE4nqRGMnLzhYHy6HlavG9+Si8zqzeNVBln1VQFUwxlsf7eK/a76md5d0LBYJXT/xJA2pR2UCMT1OTI8DGrIEdqsFu03GYbeKSW+hzRE9iVORFRSnpzqzue19uMsMLwuUyWRdfg8WXzYYBsHNn1L47ycI717bqKvcRK+iArOBNZQaymGzkOFzkJPhwue2YWnkl6zPbWPGJb32r+PXAAAgAElEQVR57K4xjBnUHkmC0soIKzcfJV5HgIDG1aMyTIjEdCqDMYrLQ1QF1BPmPQShNRM9iVOQJBnF5UXBi6lrGLFoYmloPE5LlupoKGfX/jg69Saw6RMCG5ZghP2Uf/IvbDtWkD7uemxZp9/7oW7mN3tpN/GwiqLIeF023A4rYVVLLKNtxIRxZpqDW684l8tGdmXBF/vZsLO4zr9oKutRGdXbrYaiWmJvcoeCw2YR+RdCqybenfUkWawoLi/W9BwsaVkoLh+S1UbK04mbiKRY8Q2bRO4ND+HsMQSA2NF9FL/9eyqXv42hNmwPiG8zjXijj1EfsizhcdrIznCS4bUndtdrxPHystzcdfVAHvze+fTvkXXcfRZF4ofXDTrldqzJqBmSqgzGKKoIU14VTUzWN3a2/hQ27i7m0ZdWsWl3arLzhbPHWdWT0I3UbEcpW2xgsaE4PZhxHUNTMWNRDD3W5FfUjWXxZpJ12e1E83dSuWIuemUxwa2fE967nrRR03D1GXHcHhP1ZpqJfSpi0UShwBTtf3EykiQl8hUcVlRVJxjVUWN60v27Lnk+fjJjCHvyK3hhzkZimoEeN3nura8Y0jubqy7oQYdsT0pfAyTeLpGYTiSmI0tq7fyF3WZJaR6G2LdbSNZZFSQqowECahC3zYWczBdhHSTFgqJYwOFOXE3XBAxNbdUBw9G5L7nX/5Lg5s/wr/8QIxqk4rM3CO1YQfq4GdiyO9frOE6bctxPIxbF1FVkpw/F4W6y9h/Lbrdgt1uIqjqBsFY9aZycXp0zyE53crgkhNUio+kGG3eXsGl3CSP65zH1gh60S0920v/UjNqAkVhWa7MoOO2pGZIS+3YLyTqrhpsM0yAQC1EWrkDV1ZQfX5IVFLsLizcTa3oOiicd2eZotUNSkmLBO/QS8m78Nc5zhgEQKzpI8Tt/oGLZfzCiodMeY8YFHRnaM40ZFxyTQ2CYxENViaWyKUzAOx2H3UJ2hpMsnwOnzZL0//aafJKcDCd3TBtAbqYLE1i9rZBHXlzFWx/toiqY+vfPsUwzkchXMyRVWhkhEIoRVRO7BApCczmrehI1NEOnPFKJy+rEa/Mgy6mPlTUBA7sr0cOIRTDUaHUp7tb1IVc86WRd8n2i/cZRuXwuesVRQtuXE9n/Fb4RU3H3G33SIahB3X0M6l73UlhDDWHGYygOT+2e2s3BYbfgsFvQ9DjhiE44yeQ8SUqsahraJ5svtxSyaPl+KgIqn28oYOXmI0wY3pnLRnXF7WjaobWagFGzKkqWEqu+nHYLdpvSiCRJQTi9szJIQOJrOqRFiOoqXpsHp9XRZB82SVZQHB4UhwdDj2HG1OpVUq2r6+/o2Ivc6/6H4LZl+Nd9gBENUbns34R2rCRj3PXYcrs1+JimrqEHK5CiIRSnN6XZ2qdjtSikeRU8LiuBsEZY1ZIaAVRkmbGDOzCify6fbzjM4lUHCUY0lnx5iGVfHebSkV2YMLxzynbkOx3DhLCqE1Z1LNXbzNptCnarCBhC6p21QaJG3DSoVP2E9Shemxu7pXGltk+nZtJbdnpqg4WhRVvN/IWkKHgHXYzrnPOo+vI9wrvXopV8TfG7z+DqO5q0kVNRnN4GHzexV0V59Q54nuQmx5OkKDLpXjtOh4VAKJZ0noLVonDJiC6MG9yBpevy+e+aQ0RUnQXL9vPpunwuH9OdC4Z0xGppvtdWU6E2FNFQ5MQ2s3abInoYQsqc9UGiRiweozyi4bQ68NjcWJLcR6G+JElCsjuQ7Y7q4agopqa2mglvxeUjc8KtuPuNpXL5XLSyw4R3riKyfyNpI6bgPnccUoOH6RI74JlaFMXlS8zXNCO7VcGe7iSiagRCWtJ5Fg67hSvHdufCYZ1Y8uVBPltfQCCsMefj3Xy85mumjOvOyAF5KE0wjHkyJtUBI6oRjGooMjht1tqAIQjJOqsmrk/HxCSsRSgNlRNQQxjNNOmaGI5yt8oJb3v7nuRc+wDp465HsjkxYxEql8+l+J0/oB7dn9Qxa7K19UBFiwy5Oe1W2qU78bmsNCaB2+O0cu3FvXj87jGMH9oRWZYo90f51wc7ePwfq1m/swijhQJ+3Egk7pX5oxSXh4nX1GNv+esPoY0RQaIOBgaBWJCycDmRWLRZz/3tFVIWTyay3Z30DnGpapNnwHjybvo17r6jAdDKCiiZ/xzln7xGPOxP4qgmRiyC7i8hHgk2eyE8WZbwuu1kZ7jwOKyNisfpXjs3T+rLb+4cxYj+eUhAYVmYl97bym//uZZt+8tatNCfbpi1wUqLG6LEudAgIkicgmbEqVCrKAtXENNjzX5+SVaQ7Q4snjQsNQHD5myxHobi9JJx0c3kTP851uwuAIR3r6Hw348T2PxZUpVhTcMkHvaj+8sSQ23NzKLIpHntZKc7ayeeuxr53O1ZShejoEHHys5wcdvU/jx020gG92oHwNdFAV6Ys5Fn39zA3oLKlLc/GVGtupZURZiSigj+YKJibVNmfAttl5iTqAc1HiMW0XBbHbhtbpQWuKo/bg4jrhGPRjBjIcyTfLBVRzG23rtQo31S3hZbbjdypv+c0M5V+FcvwFDDVK18h9DOxCooe4deDT5mzS54LTGxDYlJ6aw0hYiqMcZYRyfbUXyGAVzb4GN1zPHwg2sHs/9wFfM/38euryvYk1/J06+vZ2DPLK4a35POuQ2f/E810zymYm3kmIq1dgWHVRE1pQRABIl6MzEJahHCmorb5sJtc6Ysa7uhJMWKxW3FdLox1AiGGj5hbD+UvhPFUUYoagITUt8GWcZz7licPYbgX7OI0PYV6OVHKVnwJ5znnEf6qKtRPA2teXTMxLbTl5ItUxvKabfikDUwwC41ble/Hh3TuPemoew8VMF7n+/j0FE/W/aVsWVfGcP75TL1gh7kZtavBHlzMI4pESJJpDTjW2i7RJBooJr5iogewWv14GzmFTrHkqpLmcsON2YsQjwark3WM+VE0Kj52VQUh5uM8Tfg7jeGyuVziBUdJLJ3PdFDW/GdNxnPwIuQlIa9zcy4jh4sR445E72KJq4D9W0ZXgdUQYbPgd2moMaSL/MhSRL9umXSt2sGG3eXsOCL/RwtDbFuRxEbdhYzelB7rhzbnUxfy72P6nJsAl9NiRCHXcFutTTrEl+h5YkgkSS9er4iokfx2N3YmvmL7FiJoSgXst2FoakYzTzZDmDL7kz21fcR3rWGqi/nY0SDVH05n9DOL0kfdx2OTn0bfEwjFsHUo8h2D7LD1WyT9067hRjgsltol+YkFNUIhGKNKochSRJD++QwuFc2a7YVsnD5fsqqoqzYdITVWwu5cFhHJo/uhtfVtHk6yfh2wLDIcm3yns2qIIuNlM5oIkg0UjSuooZjeGxO3DZ3iw1B1ZCtdmSrnWM3SZJkuck3B4LE/hvuvqNwdh+Ef+0HBLctQ68sonTRn3H2GELa6OlYvJkNOqZpmMQjAYxYBNmRCITNPV/hdlhx2CwEQzFCSWZt15BliVED2zP83FyWbzrCBysO4A/FWLo2n+WbjnDJ+V245PwuOB2t86NZs1WrFjEIRo7fec9mVbBaRE7GmaZ1vhPbGBOTQCxMRFfx2bw4rM1XeuL0JCzpOZixGIYWxdSiTR4wZLuL9HHX4eo3msov5hAr3E9k/0aiX2/HO+wyvIMnNHgIyYzrxEN+jGi4RYKFIkukVWdt+xuRtV3DoshcNKwTYwa259P1+Sz58hDhqM77Kw7w2fp8Jo3uxkXDOmGztu4v3eMr1yJ6GWcgESRSSDfilEcrceh2vDY31hYcgjqWJMnfrIwyjWMChlodMJpm6aMtqyPZ0+4lsmcdlV++hxH241+ziPDO1aSNuxZnl/4NPuZxwcLuSgxDNWOwsFkVstIctUNQjV01arMqTBrVjQuGdOS/a77mk7X5hKI68z7dy9K1+Vw5thtjB3VoExPHdfUyHDZL7VyGCBhtkwgSTSCqq6h6DLfNicfqbpIqs8k6PmCYmHoMU4s12baskiTh6n0+jm4D8K/7kOCWz9H9JZR98Dcc3QaSPuYaLL52DT6uGdeJh/0YajhROLAZq8xKUmJ3PLtVoTIQa9T+FTVcDivTxvfk4vM6sXjVIZZ9VUBVUOXNJbv47+qvmXJBD84/Nxe5FWTh19exhQgVScVht+K0KdhEXak2pfV8e51hTEyCsTAl4TJCsXCLZtyejCRJyFb7N9uy+jKRHe4G1WSKFuyk9P2/Ei3YdcrHyTYn6WOuIff6WbV5FNGDWyj8z//iX/cBZpLJiomVUBUtkoyXyK1w4HU2LmP7WD63nRmX9Oaxu8YwZlB7JAlKKiO8snAbT/7fGjbtKWmV76XTiZsQimqUVpcJ8QdVojG9Tb6Ws02LBImFCxdyxRVXcNlll/HGG2+ccP/s2bO5+OKLmTZtGtOmTat9zI4dO7jmmmuYNGkSv/rVr9D11lVquy5x06BKDVAWqURtgazthpCtdizuRHa34klP7OF9mh2k/es+JJq/Hf+6D+p1Dmtme9pN/QmZl3wfxZ0OcQ3/ug8p/M//Ejm4JekvDUNT0f3liXpQeuPyGxpCliV8Hjvt0pzYUzh/kJnm4NYrzuWRO0YxrE8OAIdLgvz1nc38/rV17DpUnrJzNTfdMAlENMqrohSWhao3VFKJqBqaLkqFtDbNPtxUVFTEc889x7x587DZbNx4442MHDmSc845p/YxW7du5dlnn2Xo0KHHPfeBBx7giSeeYMiQITz44IPMmTOHm2++ublfQlJqqsy6qqvMtkTWdn1Jkoxid6HYXafd/8Ksvno3G3AVL0kSrnOG4ejan8CGJQQ2fUI8UEbZ4hdxdDmXtDHXYk3PSaLlZm3pdcXhQXa6m22+omauIhiOEYg0bgXUsfKy3Nw1fSBfF/qZv2w/2/aXceCIn+fe+op+3TKZdmFPurWve9On1s7kxA2VJAkUScJmVbBZxYqp1qDZexIrV65k1KhRpKen43K5mDRpEosXLz7uMVu3buXvf/87U6dO5bHHHkNVVQ4fPkw0GmXIkCEAXHPNNSc873Tm71jC15WHU/ZaGsrEJKRFKA2XE1RDbaKrLVtsKC4vlrRsLN6aYoOpGVuRrXbSRl5F7oxfYq/Oo4h+vZ2iOU9RtWZR8sNHZmLZrF5ViqE2X86IJCWKBmZ5HVhSPEnbJc/HT2YM4ec3D6NnpzQAdhws57evruVv8zZzpDSY0vO1FNNM9DTCaqK+VEllhOLyEFXBRE9DbN3a/Jq9J1FcXEx2dnbt7zk5OWzevLn291AoRL9+/XjggQfo2rUrs2bN4i9/+QsXXXTRcc/Lzs6mqKjohOP7/X78/uOrkhYWFgKwqXA7O1YeoEtaRy7oNoKhef2xNDAbOBXipoE/FiSiR/HaPK1syWzdJElCsjmQbQ5M05soB1KPPbDrw5qeS7srf0j04GYqV7xDPFhBYMMSwrvXkDZ6Os4eQ5Ka6Pwmc9uB4vQiWZpntZndbiHLIlMZUBu9VPbbenXJ4P5bzmPr/jIWfL6P/OIgG3eXsGlPCSP75zFlXA/apTffJH5TS6yYMtEiGkRAktTa7O82cI11RjjlN+SECRNO+eFcunRpg09oGMZxxzRN87jf3W43L730Uu3vt912Gw8++CDjx48/5fNqvPrqq8yePbvOc+d42lFJiK+rDvPGpneZv2MJozoPY2yX4WQ4G1pnqPE0Q6c8WolTd+C1uVMasGrmnptiYZUkySgON7LdBSkaNpMkCWf3wdg79SOw8b8ENn5MPFhB+X//D3vHPqSPuw5rRl5SxzZiUQxNRba7UZzNU3bdoshkpTnwh2IEI6mdI5EkiYE929G/RxYbdhazYNk+iisifLm1kLXbixg3pCNXjOlGmidx8RFREzvXAYQiGhFVw2lvHcuzG+rY4amaUudxwySq6mI3viZyym+lP/3pTwC8+eabWK1WbrjhBhRFYd68eWhacm/8vLw81q1bV/t7SUkJOTnfjD8fOXKElStXct111wGJYGCxWMjLy6OkpKT2caWlpcc9r8bMmTOZPn36cbcVFhZyyy23cM/w7xByxvji0Bo2F+4gGAvz8b7lLN23goG5fRjXdQS9sro3+xstokerl8y68NhcKTl/utdBcSTxs6lIkvTNmL+sIFvtGFqMxiyjla020s6/EnfvEVSunEf00FbUw7somvtbPIMuxjdsUnI72pnVxQNjYWS7G9nurLOmlKFGiEcCAIlMbzWS9PJaSZJI89ixWGT8QbXRORXfJksSw/vlMrRPNqu2HOX95QeoCKh8vqGAVVuOcPF5nTmnUzovz99a26OpCKjMmr2CH88YQq/OzX9h1BQMw6TMH0WRa7K/E8l8bSG3pC04ZZAYMGAAAHv27GHu3Lm1t//yl7+s/RJvqDFjxvDCCy9QXl6O0+nko48+4vHHH6+93+Fw8Ic//IGRI0fSqVMn3njjDS699FI6duyI3W5n/fr1nHfeecyfP5/x48efcHyfz4fPd5KJPEmiZ2ZXemZ2pSrqZ+XX61mVvx6/GmRz0U42F+0k19OOcV1GcH6nwTgszTcMVFM4UI3H8Nnc2Bq517bTboFI9c9mIEkyFl8Wpq4RVyOYsXCjMrstadm0u/xuIoe2Joag/KUEN35MePda0sdMx9lzWHJDUIZBPBIgHg0i25zV/xJ/52j+Do7++0nM6tpX8UA5h/50J+1v/BWOzv2Sfi1uhxWrIqckU7suiiwzbnBHRvbP4/MNh1m86iDBiMaSLw+xhEMnPF7V4syes5Hf/WRc7R4aZ4K48U1ehiSBTVES5UJslpSuPDvb1CvU+v1+ysu/WXJXVFREMJjcRFlubi733Xcft956K1dffTVTpkxh0KBB3HnnnWzZsoXMzEwee+wxfvCDHzB58mRM0+T73/8+AE8//TRPPfUUkydPJhwOc+uttybVBoA0h4/Le1/Mwxffy61DrqVHRmITnaJgKe9s/4BHlj7D29vepzBYcpojpVYsHqMsUolfDWA0Q72lVJMsVixuX2IZrTutwRVgv83ZdQB5Mx7Ed/6VoFgxwlWUf/xPShe+gFZ+JPkDmyaGGkYPlKNVFqP5yyic/6fqfI2aS34TMxbh6L+fxIhFGvU6bFaFdulO0r12muoC12pRuGREF564ZwxTL+hxymqtBibrdpw4p3emME1Q9Tj+sEZZZYSishCVgerJb7EjX4PU6xM8c+ZMpk6dyrhx4zBNkxUrVvDAAw8kfdKpU6cyderU4247dh5i0qRJTJo06YTn9e3bl7fffjvp89bFIlsY1mEgwzoMpMB/lOWH1rL+8GbUeIzlh9ay/NBaemd1Z1zXEfTP6d0sS1drEvGiutri5ciTdey8RaKMeSjp/AXJYsV33mRcvc5PDEEd3Ix6ZA9Fc3+HZ8B4fMOvaETGtYkZ1wlt+QKMOBZfO3R/CRwboE2D4PYV+IZckuQ5vuF2WHFYFfyhGBFVb5KCKA67hSvHdicQUvlsQ92r+TTNoKQi3ARnb31MEium9KhGKJqYL2pN+3i0dvUKEjfffDPDhg1j1apVANxxxx307t27SRvWEjr52nPjwKu4qu+lrM7/iuVfr6UsXMHusgPsLjtAhiONMV2GM7rzMDx2d5O3p7YceTyKz+ZpkZVYjVVTxlyyOTFjUeLRYNLBwuLLot3kO4nm76By+Vz0qhKCWz4jvHc9aaOm4eo9Iun5HM1fjBEow0D6ZntYSQbTxNRUtIrCpI5bF0WRyfA5cKgagZCG1kRXth1zvFitMppW9/HDUf2kC0DOaGJZVIPUu+N78OBBKisrueGGG9i9e3dTtqnFuaxOLu4xhl9d+BPuGn4z52YnykhURKt4f/dSHvn0WV7fNI9DlQ3bAzlZUV2lNFxBoI3kVtRFkiRkuxOLrx0WT3qjlqM6Ovcjd8Yv8Y2cimSxYUQCVHz6OiXznydWmtzfxOrLBosVMMGs/lKVwJKeg+xOT3pl1ak47VayM5z43Daaovbd8H45yKfImP9i4xGeenUt2/aXtdn3VVu2evVqhg8fXltZYurUqbz55pt1PvaFF17g9ddfb+YWJtQrSLz44ou89dZbLF68GFVVmT17Nn/+85+bum0tTpZkzs3pzV3n38KvLvwJF3YbhdPiIG7EWXd4M8+tfJlnV7zImoKNaPGmLQVRM7FdFi5HPU2SWUSLElQTOQxBNUREa/5NiE4mESxcWNOysXgyq0t/JHEcxYpv6GXk3vgQzp6JzPxY4X6K3/k9FV/MwVAbNpTiOmdYoudwLMMgHihHsrtw9Tq/Sb5IJUnC67KRmebEmuLJCqfdyo9nDDlh0tZqkWsT8r4uDPDCnI08++YG9hZUpvT8wumNGTOG+fPnM3/+fN5++21eeeWV2ryu1qJe78r333+fl156CafTSUZGBnPmzGHRokVN3bZWJdudxfRzJ/ObiT/jhoFT6eDNBeDrqiO8ufk9Hv30ORbt+piKSNN+0GLVuRWVET96HWUydpbs5e4Fsyivbkd5pJK7F8xiZ8neJm1XMmS7A6uvHRZPRtIT3BZPBlmX3ka7KT/GkpEHpklo2xcUvvU4oZ2rMM36DeVINgc5V/4AvpXYaMoyWeNnYERD6FUl6CF/k9SGslsVstKduFK8Gq1X53R+95NxZHgTryvDa+cPP72AB74znF98dzh9umQAsCe/kqdfX8+f526koCiQ0jYI9WO32+nXrx8bNmzg9ttvZ+rUqcycOZPKyuO/U/7whz9www03MGHCBH73u98BsG3bNq677jqmTJnC/fffj6ZpHD58mJtuuompU6dy9913n5BkXF/1ChIWiwWb7ZsrPp/Ph8XS9sbHU8Gm2Bjd+TweGHcPPx11G0Pb90eWZELVORePffpH/rH+3+wq3ddkXXgTCOsRSsLl+NUAcSOxrDKiRfnfZbOJ6ipm9ZSoiUlUVxO3p7hHUVdOQTJkuxNLWjaK29egCrTHcnTqQ+51s0gbfTWS1Y4RDVLx2ZsUv/ssseKv63UMW15POt76RKLwIKC40+l46xPY8noCiQxuIxpEqypFD5SnvOSHIktk+Byke+0pHX5y2Cy4nYnhPbfTWrvstUfHNO69aSg/vWEIXavrP23ZV8YTr6zh5flbKSo/Oya2W4vCwkK2b9/O8uXLufDCC1m4cCETJ05k3rx5tY/Zt28ffr+f//znPyxZsoQPP/yQ8vJyXnvtNX72s5+xaNEiOnToQH5+PvPmzeOaa65h4cKFjB49Oulpgnp907dv357PPvsMSZKIxWL84x//oGPHjkmd8EwhSRI9MrvQI7MLVdEAq/LXs/LrdfjVIFuKdrKlaCc57nZc0PV8zu84GIc19SuUalZBRbQobquL9Yc3nzSPzTRNVuavZ0KPsSk5d6pzCiRJShTlszmJR4IY0TANTcqTFAXv4Im4zhlO1ZfvEd6zDq34EMXznsbdbwy+EVNQnJ5TH8PqQHa4iYcqE2XT6/y7mYks7lgUKWpLtNueur+v22HFZkmsgIrGmrbSsSRJnNs9i37dMtm0p5T5y/ZxtDTEuh1FbNhZzJhB7blibHcyfW1vhV1bsHLlSqZNm5aoOOB08uCDD/Lss89y7733AtQu83/hhRcA6NmzJzNnzuS1115jz549+P1+IpEIY8aM4Re/+AWXXXYZV155JT169GDEiBHcd999bNiwgcmTJzN8+PCk2livy7Zf//rXvPLKK+zatYshQ4awbNkyHn744aROeCZKc3iZ3OsiHrn4PmYOva4256I4VMo72z/kkU+ebdKci5paUIeqjuBzeOtMAlTjMQoDxSk5n6FGqgNEhFTnFEiykihX7kt+vkJxp5E5cSbZV/0/rJkdAJPQjhUU/ftxgtuWp3T7VlOPoQcTuRbxSBDTSE2ynNWSKOuR7mmaSe1vkySJIb2z+fVtI/nelHPJSnNgmCbLNx3h4b+vYu7S3QTCrbvUfVtUMyfx3nvv8dZbbzFhwgQU5ZvyIpFIhKNHj9Y+ftOmTfzsZz/D6/Xy3e9+l86dO2OaJldddRVvvfUWnTp14pe//CUff/wxI0eO5L333mPgwIE8//zz/Otf/0qqjfXqSbhcLl599VUikQjxeByP59RXY2crRVYY2n4AQ9sP4LC/kOWH1rDuWzkXvbK6c0ET5Vy4bU6CahiPzY0W14gfMx5vV2zkeZMpv32i4PYV36wA+rYU5RTIVnti5VIsghEJ1lmm/HTsHc4h57pfENz2Bf61H2CoYSq/+A+hHStJv+B67LndG9XGY9XslBePBJCtiUKIks3e6FLlbqcNm1WhKtg02drfJssSowa0Z3i/XJZvOsIHKw7gD8VYujaf5ZuOcMn5XbhkRJdmy+Q/Gw0dOpSPPvqIW265hbfffpvCwkIcjkRPbv369UyYMIGrr76a7du3s3//fkzT5N577+U73/kOt912G6qqsmfPHjZs2ECfPn24+eab8Xg8rFmzJqn21OsvPXHiRC666CJmzJiRdJflbNPRl8cNA69ianXOxYqv11IarmBP2QH2lB0g3eFjbJfhjOo8DK89NUF3WPsBvLtjMaXhcO3SR1mSMcxEUcUxnc9LyXm0iqMn3T8ilTkFkiSh2F3INgdGNIQRDTW4FyDJCt6BF+HqOYyq1QsI71qNVppPybvP4uozirRRV6E4vSlpL5DI5I5FMGIRJFlJ7MNtczRqyW/NDniB6mKBzbFY1aLIXDSsE6MHtOfT9fl89OUhwqrO+ysO8NmGAiaN6spFwzphE+UuUu6nP/0ps2bNYs6cOWRnZ/Pss8/y6quvAnD55Zfzox/9iKVLl+Lz+Rg4cCBHjhzh9ttv5+GHH0aSJLKzs/nd735HIBDg/vvv55///Ccej4ennnoqqfZIZj1mVwOBAIsWLWLevHkEAgGuv/56pk+fTmZmZlInbW4FBQVMnDiRtxbMIa9D6te714dhGuwq3ccXB17NY0QAACAASURBVNewo2RP7Qc90fvozwVdR9A1vVOjz7O//BB/W/s6seoluRZJIdeTzT3nf4c+2T0bfXwA/1cfU/bf/6szUEhWO1mX3ZaS7ORvM404RjSMoQYxk6yWpxYeoHL5HLTqfArJ5kwUFOw/rrY6bNHc36KVHcaa1ZHc62c1vuGSlOhdON3IjazJFVE1qoIqDc2/e+L/VlNQHKRTjoeHbhvZ4POGoxr/XfM1S9d+Taw6OS/NY+fKsd0YO6hDixTTS/Y1WWSJ3KymT4Y9U9TrL+v1ernpppuYO3cuzz//PEuWLOHCCy9s6radUWRJpl92r+qci59yUffRJ+RcPJOCnIsemV15fML9pDsSq1U8djf/b9Rt5Hqz61wymwzPuWNPzCmoIcmJ+5uAJCvVGyDlIDvc32RGN4A9rzs51zzw/9k77/g47jL/v79TdrapWs1V7r3JRe5Oj0N6QgKG3BHgEkqA3MEFfuEIl3BcgOOAwCVALpA7wtGSENJ74iTusdx7t2VbVrPa9p3Zmfn9sdLasiWrrYrjeb9eftma3Z35bqKdZ7/P83w+D9lLPoFotgxpXPNXap77MfHKXmoTbt5dJJrqSAQbsPTud0V5NJVBWV5cXZzWVmwd54v+dxlhdU9s6HWr3LR0DP/+pYVcNnsYiixoCsX505v7eOg369mwqwrLEeR9JJEfeuihhzrzxF27dvHEE0/ws5/9jOLiYu677z5GjUpfTrc3CQQC/P73v+e2T92OP6P/6ylel4eJ+WNZOrKUQd4cGmJNBOMhAvEgO6r3svbYRiJGjHxfLp5udEUpssKGE1sJ6mFyPdksHTUfw0oQNeLYWKiS2iMrBqGoeEZMIrRnHZgteXKBcHkYvPw7qLmDu33uTl1fSEguN5LqTtpmdDH4CSFwFRTjm7gAW49hnDqBFQ0S2fchiaZazHATViyE7M3EP2VxWtdum4lUOgrbRshyl+sWsiTwaAqWZXfa0sO/8feMkU+SbQfInd39XZ7mUpg6Jo95U4uIxROcqA0RjiXYsr+Wrftryc7QKMxNj919R6zcUkEgrJPpc7G0pPO7cEkI/N6e7eguJjpVk7jhhhuIRqPceuutPPfccxQWFvb2ui4KXLKL+cNnMW9YCUcajrO6fANbq3YTNqK8e3g1Kw6vYUrheJYUlzJ+0Ogef/CSqu0I0UQcv+rD6+r+BDP38EkU/+NvOP7f/4gZqEPOzGX4F3+B1INzdhWhqCgZOVhxLdlZ1MVgIXv85FyyHN+kBTSsfhajppzIgY3QXM/pTauKlkK3FQsiFDeSS0OoWqcHIknNmgo1qhMI6x3aEbnQW/3dUwZlefjMdZO5en4xL608zOZ9NVTUhvj1c9sZNSSTmy8Zw4TiCyMd7XB+OhUk7r//fhYt6p0UgkNrzcVNZ2kudlbvY2f1Pgp8g1hcXEppGjQXCcukMR5oHp/a/dkVksuD7M5IBgl3Rp8GiFbr0LwIVcMMB7rVfusqKKbglm8Q2fshTR++hBVL2uAnmmqIVezHPbT3zCxtK9k6bOnR07ULzZuacdERfo8LRZJoDMW6XKdIB0WDfHzhlmmUVwV4aeVhdh2u48jJAI/8eQuTRuZy8yVjUkI9hwuT8waJ3/zmN9x9992sWLGC995775zHH3jggV5b2MVKi+biqjFL2F69h9XlZRyqL6cmXMffdr/Oq/veZe7QGSwuntvjlta4qaNHDXyqG7/Lj9Qbs077CCHJp3cVkWCX9QpCSPgmLcAzajpVf/4+VjwMZoJTLz+KZ0wJWQtuQfHn9NLqm0l1RsUQioqkJVNqHVmWuDWFQbKHhkC83fRTuQdezc5iWiMM74WlFxdl8rVPzOTAsQZeWHmIQyea2HO0nj1H6ykZn88NS0czJK//U70OXee8v30ZGcnWwJycXv5wOJzDmZqLk4EqVpWXselks+biWBmrj6VHc2FjEzKiRBNxMlz+HqWgBgI93VVIbh+yPxsrHkYoLuyETvTQFmLlu8iYvYyM6Zf3eJBSx9jYCR0zoWOKIJLiQrjcSe1IO9dWlaT3U1MoTjR+btptfa5EhUcjJNn0Zk5g3Igc7rtjNjsP1fHCB4eoqA0l6xUHapk3ZTDXLx5FXvaF/Tt2sXHe3/bly5cDkJeXx/XXX3/Bi+h8qhdNdqGbRsrb6EJgSGYRn5x2AzdMvJINJ7ayuryMU5H6VpqLljkX3dVcmLaVSkH5XT60HrZq9ietdxWBbius5cw8MmZcTtP6F7GiQQIfvkxk74dkL76tR+NMu4RtYxlxMOKYQiCpGpLLg3C5z6lRyZIgJ0NDlQXBSGs9hS61/rs3EUIwbWweU8YMYtOeal5adZjahijrd1ZStruKxTOHcu3CkWT5+248sEOSUCjE8uXLefzxxxk2rHPF/k59Jfrwww/5+c9/zuWXX87tt99OSUlJjxbaX/hcHgZ5c7AsC9000C2deCJOwrIuiKDhVT1cOmoBS0fOa6W5aIwFeG3/Ct48+AElRVNYPLK020XXZApKxyW78Koe3Ip2wQ6lkTQvQlFJhJqax5J2DSEEvgnz8IycTmDja4R2riTRVMOpV3+FZ9QMshbeipLRh8VZ+wzPKElGuDzJlNQZAV0IQYZPQ1Gkbukp0okkBHMnFzFrQgHrdlby6uojNATjfLD5BGu3n+TyOcO5en4xPnfXhYbRuEE4mmwVD0cNonEDj9Z9weJAIRIzWLX1JJWnQgzO87Nk5hC83fjv0xbbtm3jgQce4OjRo116XaeCxCOPPEJTUxOvvPIKDz/8MLFYjNtvv50777yzO2vtdyRJwi1puNFAyyBhJpqDhoGeiGPa9oAOGi2ai0n54zgVqWdN+UY+PLGZiBFj48ntbDy5HVVK/q/tTrCwSQaLuJkMFhkX8M5CyCpKZi5mJNgt00BIutRmL/p4sgtq1bPolQeJHtlG7PhuMkquJmPGFT1SVHcH2zKxYyGsWDhZv3A1d0jJyXV4NBVFlmkKxfvEzuN8yLLE4hlDmTeliA82V/DGuqOEogZvri9n5ZYKrp5XzGVzhqXcaTviwPFGHntma+p9NQTj3P/YGr76iZmMG57di++kd9l1uI7v/XY9lm0T1000l8yTL+3kwbvmM2X0oB6f/5lnnuHBBx/kW9/6Vpde1+nNZ1ZWFp/85Cf54he/iNfrbTWT+kJHkRW8Lg/Z7kwK/PkM8uaQpWXgVdwoQkKcZ7pXf5PnzeWmSVfz0OXfYPm0GxmamVSUG1YyL10VquWlvW9TF2no1vl1U6c+2khTLJCyJL/QEEJKmgb6sxA9cMtTc4eQf+O95F75WSRvFnbCIFD2KlXP/IBo+c40rrgrNNcvIoGkhXmgDjMewbbMlElgpndgfMNWFZkrS0fw719ayA2LR+F2yUTjCV5ceYjvPr6W9zYex0icf+sTjRutAkQLccPksWe29rprbm8RiRl877fricYTxPXke4vrJtF4InW8pzz88MPdslXqVOjevXs3zz33HG+88QaTJ0/mrrvu4vLLL+/yxS4UXLKKSz79wTJMg4RpYtgGumlgmIkBt9M4U3NxtPE4T5T9iWgiho3NisNreO/wGqYUTGBx8VzG541G6oKAy8YmbESJGnF8Li8+1XNBdkJJmhchqyQiTdhG9/QCQgi8Y2fjHjGFwKY3CO14DzNwirrX/xt38VSyF96KkpWf5pV3kjPqF5YkmvUXbvzegZX7d2sK1y0ezSWzh/PmuqO8v/kEwYjB0+/s5+0Nx7h+8SjmTx2M1EZA37inBqudz56FzcY91SyeceGNMVi19WS7inXLtlm1Nbnj6g86FSTuuecebrvtNp599lmGDBnS22sacKiyiiqreEjqE1pqGoalY5gJdCs5UH4gBA4hBKNyRpDjySIaTOogJCHRFA+ys2YfO2uSmotFxXMpHTqzS4rulhGqUSOCr4divP4iKcAbhBUPY0WDbXpAiebpdEJt/+YqudxkL7gZ38T5NK5+lnjFfmLlO6k6sZeMmVeSMfMqpG5anaeDM/UX3R3k1Nv4PSofv3wcl88dzmtrjrJm+0nqAzF+/9oe3vqwnBuXjKFkQn6rmlhtQwTDaHu3YRgWtQ0X5qCkylOh1A7ibOK6SeWpUB+v6DSdChKzZ8/mq1/9am+v5YKhVU2DZN4/YSVIWCYJK4FhJUiYxoCobWRofv550RfYUb2XVeUbUpqL53e/cYbmopTBXdBcJGyLJj1IJBHB6uR40IFEasCRmtRUnO2llDnnWkLbVuCf0fFuWc0pIu/6rxI9vJWmdc9jhhoIbnqDyL4NZC+6FffI6f1e+D+7uytTihNOSFiy2qFSuy/IyXBzxzUTuWreCF5edZiNu6upqovwxAs7GFGUwU1LxzB5VG7S4TTHi6pKbQYKVZXIz/H2wzvoOYPz/Gguuc1AoblkBvejxqRTQeLAgQPYtt3vv+wDFSFEardxJgkzkSoAxxN6vwUMWZKZOXgKMwdP4WSgOjnn4uR2dNNgzbGNrDm2kbG5I1lSXMrUwgmd1lwYlpmaWWFxAQYLWUXJyMWKR1rZeriHTcA9bELnzyME3jEluEdMJrj5LYLbVmCG6ql787dowyeRveg21Oz0zPJIBxpxhG0SitjYqhtb0QC53/fBBTle/uHGqSxrtvrYfvAUx6qCPPrMVsYNz+bmS8YwZ1IBf333QJuvlxDMmXRhWgYtmTmEJ19qu64lCcGSmf2XQutUkMjPz+e6665jxowZ+HynLXYdxfX5UWQFRVbw4cWyLOIJnbgZJ5bQsdvNrPYuQzIL+cS0G7i+WXOxpryM2kg9B+uPcrD+aLc1F6ZlcSrSgF/14j5PmmYgkhLghRqTOf3unkfVyJp3A94J82ha8xyx47uJH99D9TM/IGPG5WTMWoY0QP7buFSZTMkiEA5iWiFkl4ZQ3diyC7ufGzWGFWRwz20zOFzRxAsfHGT/sUYOHG/kP/+wiWljBvGJq8bzzNv7WxWvNVXmq5+Y2ekOqYGG163y4F3zz+lukoTgwbvmp3XI04oVK7r0/E5duaSk5ILVRgwUJEnC43LjwY1t28mWW9PAsAz0hNHn38Rbay4Os7p8A7tr9rfSXMwsmpyac9GZXaRu6tSbOi7DdcEFCyHJyBm5iGgIMxqiO62yLajZBQy69kvEynfSuOavmMF6glveJrK/jKwFt+AZUzIgduWKLJHtdxOM6MRiUYhHkRUl6cGlaNiS0q/pqNFDs/j6p2ax52g9L648THllgB2H6thxqI6SCfkcOtFIIGyQk6Hx4N3zL9gA0cKU0YN46sFlrNpacYZOYmi/TwHs1NWdekR6EUKgKa6U9sCymwvhzX/ifagIT2ouxjIpfyx1kQZWl5fx4YktRIwom07uYNPJHQzLHMyS4lJKhkxt1fXVHhdqsBBCIHszELKKGWns0SxsIQSekdNwD5tAYMs7BLe+jRlupP6d/0XbsyaZguplS/XOIEmCLJ8LRTIIxxKYRgKMIEKEkFUXwuXBljXsfgpqQggmjxrEpJG5bN1fy0urDlN5KsyWfafnxWsu+YIPEC14NKXfupjao9NW4W3x8ssvp3UxFyuSkHArGm4leTM9HTQSGJaOnkj0SXpqkDeHmyZdzcfGX8aWkztZVb6BE4FKTgQq+fOOF3lx71vMHz6LRSPmMMib9PM64JZZNTiLpbLMlLPO1xIstOZgoV0gwULS3AhlEIlw91tlWxCKi6y51+KbUErj2r8RO7qDeMV+qv/6I/zTLiVz9seQXD1z9e0McnM7qdyWTkQIfF4XcrOdh2U3N2PocdDjSLKEpHlAcWNLar+kSYUQlEwoYMa4fDbsquLl1Yepa0o2HFTVRfjruwe4ZkGxMyeiF+hUkPjud7+b+rdhGLz66qsMH94bXpIOcHbQ8LVOT5l6p3YaLQGn5e+u4JJV5g0voXTYTMobT7CqfANbK3cRMaIpzcXkguSci3dyvByNRtG9vnOCRAstxXvNcOG7QHYWyaL2oOaZD91Tap+JkplH3jVfIFq+K5mCCpwitG0FkQMbyZ5/M55xc3o1BdUSG86nJXRrKrIsEQzrGObp92uZFlYkDCKCJCX9o1A0bFmBPk5JSZJg/rTBzJlcyAO/XkNjKBnE3yk7xuptFVwxdwRXlo7o9xTNR4lO/ZcsLS1t9fPChQtZvnw5X/7yl3tlUQ6taZ2e8qV0GjEzTsyIt1nPuGbcpbx3ZC2XjVrYo+uOzBnOyJzh3DxpGeuOb2LNsY00xYLsqtnPrpr9yCLZCRXthJI5ZfWhK3hUDx7V3SVRX18jhEDxZWEpKmakqdtztc/EUzwF97DxBLetILj5TaxIgPoVv8e1Zy05i29HHdS/OiRVkcnO0GgK66lZ1ilsG8u0scwoEEUIgaQoSJqnzzukFFnC73XRGEpOpkskLCLxBK+uOcL7m09wzfxiLpk1DJfaPXdkh9N0K9w2NDRQU1OT7rU4dJKUTkPVsLRk15RuJs0KTTuZlhqfN5rxeaPTds0Mzc/VYy/hitGL2VG9l9XlZRysP4ppJztMqkOneGbnKywpnsvgjPO3IepWAj0eJKSH8aoePKoHpZtW531BSqkd7p5R4NkIWSVz1jK84+bStO55ooe3olcepPqv/4F/yhIy516LpPVfv78kSeT4NUIRg/B57CBs28Y0DDAMhCQlaxiqG1tR6cuAkelz8Y1Pz+KtD4+xYuMxwlGD5947yLsbj3PdolEsnDYYWR64X0YGOt2qSZw8eZJPfvKT3b7oyy+/zK9//WsSiQR33nknd9xxR6vH33nnHR599FFs22bYsGH88Ic/JCsri+eff56f/vSnDBqUNLu69NJL+frXv97tdXwUkISER3XjUZNdU0khX4KE1dI9Zaa1CH6m5qIyWM2j639HxIhiY7P22EbWNmsuFhfPZVrhxPNqLkzbIqiHCekRPIqGR3HjUlwDovPnbITSbBQYDiYHEqUBJSOXQVf/A7Hje2lc8yyJxhpCOz8gcmgzWfNuxDuhtMvzr9OGEPh9LmRFEGquU5wP27JIxGMQj50VMFyA1OsBw+tWufmSMVw+Zxivrz3Kqq0VNAbj/PGNvby1vpwbloxmzuRCpAH4uzXQ6TBI2LbN/fffj6qqBINB9u7dy5VXXsmECZ0XG51JdXU1jzzyCH/7299wuVwsX76cefPmMXbsWCDpd/7QQw+lZmn/4he/4NFHH+WBBx5g586d3H///Vx//fXduvZHHSHEGb5TScuMFkFfsmtKx7LTVwAfnFFItjuTiBElU8tAk9VWmossdwYLh89hwYhZZGoZ7Z7HxiaSiBFJxFAkGY/iGZD+UEJIKP4sTFnGjATpaZ2iBffwiRTe/m1C298nsOl1rGiQhvf/SHjPWrIX344rv//qfx5NRZYEwbBOB957Kc4JGH2owcj0aXzyqglcWTqCV1cfYd3OSmobo/zPy7t4c305Ny0dTcn4fvLW6mcee+wxXn/9dQAuueSSTrvBnvdTePDgQa644gp0XWf69On85Cc/4ZVXXuGuu+5izZo13Vro2rVrmT9/PtnZ2Xi9XpYtW8Ybb7yRetwwDB588EEKC5MpiwkTJlBZWQnAjh07eP7557nhhhu47777aGpq6tYaLiYUWcHn8pLtyaLAl8cgTw5Zrgw8ipbWeoDf5eXbl3yVL839O6YUjEcATbEgrx94j++teIT/2/ocRxqOd2hdnrBMgnqImnAdgXgwqVQfCN4RZyB7/Cj+nB45yp6NkBUySq6kaPl38YydBYBefYSa5/6ThpVPY8XSs3vpDi5VITvTjUvt+u+LbVkkYlESwQbsYC2SHkSydEQv7y0GZXn4zHWTefCu+cyakFS7V9SG+NVz2/nR/22kIRDr4Az9gxWPEtjyDnUr/o/Alnew4l2frtgWa9euZfXq1Tz//PO88MIL7Nq1i7fffrtTrz3vTuLHP/4x//RP/8Rll13Gc889B8Crr75KdXU1X//611m0qOuDEGtqasjPPx3JCwoK2L59e+rnnJwcrrrqKgBisRhPPPEEf//3fw8kld+f//znmTVrFj/72c/4t3/7N37605+2On8gECAQCLQ6VlVV1eV1fhQRQuBSXLgUFz682LadHDJk6sQSccweDl+ShMTE/LFMbNZcrDm2kfXHN5+luShicXEps4ZMO6/mwsIipEcIEzmj28s9YOZaSJobIeeRCDdiJ4y0nVf2ZzPoys8Rm7SYxtXPkmioJLx7NdHDW8gsvQHfpAX9koKSJYlsn0YwohNtx4iuI87skpIVGUl1N3dJ9Z6HVNEgH1+4ZRrlVQFe/OAQu4/Uc+hEE+9tOsGtl43tnYt2k9jxPVT+5WGwLWwjjlA16t75HYOXf6fHkxDz8/O5//77cbmSn58xY8Zw8uTJTr32vEGisrKSG2+8EUhOp7viiiuQJInBgwcTCnXPldCyrFY55/Y8oYLBIF/5yleYOHEit9xyCwC//OUvU4/fddddqWByJk899RSPPfZYt9Z2sSGESLXaZmoZ6KaRKoJ3ZsRr3IgTMZLfdCJGlLgRT2khBnlzuHHiVVwz7tKzNBdV/GXHS7y0923mDy9h0Yi5Kc1FW9gkaxdhI0rEiKJKCh6luTOqn9NRSUfZXMxw0zkmgT3FPXQchbf9P0K7VhLY+BpWLEzjyr8Qbu6CchWOTOv1OoOQBJl+DTmWnArX7Ru7bTeL9kIIEU52SLncILt6LWAUF2Vy7ydL2H+sgcMVTVw9f2AJ1qx4lMq/PIx9xlx2u9kipvIvD1P8j79JKuG7ybhx41L/Pnr0KK+//jp//vOfO/Xa837KzvwQbtmyhblz56Z+jse753FTVFREbe1ptWRtbS0FBa3Nz2pqavj0pz/NhAkTePjhh4Fk0Pjd736Xeo5t28jyuUXRO++8k3fffbfVnz/+8Y/dWuvFhktWydB8DPLmUOAbRI47C5/qwSUp5wxeOlxfzndX/ITGWHLX1hgL8N0VP+Fwffk555w3vIR/XvQF/mnBPzB7yDRkITVrLtby7+//gt9s/BN7ag926Chrk+yMatKDqXSUYabvW3wL26v28MOVj7Gjem+HzxWSjOzPQfZkQJrz7UKWyZh+GUXLv4t3fPKzZ9Qeo+b5n1L//p8wo8G0Xq+z+Nwq2T4X6WgYaumQSoSDmMF6CNUjJSII26Q3aszjR+Rw/aJR+D0DYxBTC6Hda6C933/bSj6eBg4cOMDnP/95vvWtbzFy5MhOvea8O4msrCz27t1LKBSitrY2FSQ2b96cqhl0lYULF/Loo49SX1+Px+Phrbfe4vvf/37qcdM0+dKXvsTHPvYx7rnnntRxr9fLb3/7W0pKSpgxYwZ/+MMf2txJZGZmkpmZ2a21OZxGlmQ8kpyaN2FaZmqn0RQP8puNf0Y/6watmwaPl/2B719+3znq6nM1F5tZc6ysleYi35ubnHMxbCZe9fzfmlLpKD2KJqu4FTduRUvL7uKvu15l76lDRI0Y0wondvj803Yectr0FGciezPJvfwz+CYtonH1sxh1FUT2riN6eCtZpdfjm7y4z2dGuFwK2bJEIBzHSKTn/SYDhg6GjpAEkuJCcrW41PZ+h1R/YjRUpnYOZ2MbcYyGnqfMN23axL333su//Mu/cN1113X6decNEt/4xjf47Gc/SygU4r777sPr9fLkk0/y+OOPt0r9dIXCwkK+/vWv85nPfAbDMLjtttuYPn06d999N/feey9VVVXs3r0b0zR58803AZg6dSoPP/wwP//5z3nooYeIxWKMHDmSH//4x91ag0PXOTNobKvazSBPDtFEjPpoY6u0lG3DlqpdzB8+q91zJTUXS7li9CJ2Vu9jVfkGDtYfpTZSzwt73uS1/SuYM2Q6i4tLGZJ5/i8jNjYxUydm6khxCa+q4VY9nfKYao9oIt7q784iaV6QFcxQY8p2PJ1og8dQ8PFvEt69hqYNr2DrURpXP0t4zzqyF9+ONjh9upjO0GIQGOpBnaI9bMvGbLYFad1Sq/W7S21voOYMRqham4FCqBpqTlGPzl9ZWclXvvIVHnnkERYsWNCl1543SMycOZOVK1cSi8VS385LSkp49tlnO71VaYsbbrjhHO1Fy8zsadOmsXdv29v8OXPm8Pzzz3f7ug7p4XigkhPBSjRFQxIC07aRhYRbcRMz45wK13XqPLIkM2PwZGYMnkxlsIZV5RvYWLEN3TRYe3wTa49vYkxuMUuKSzvUXEDz7sKIEjZiqLKCW9Zwq+4+FepJiguROahX6hSQTG/5py7FM6aEpg9fJrJ3HUbdCWpffATv+FKy5t+E7G29k7b1GLZtARK2bWHrMUSa/KKk5jqFGjc6pafoDme21EqylLQF6cJExQsB/+RF1L3zu7YfFBL+yV1vEjqTJ598kng8zo9+9KPUseXLl/OpT32qw9d2qJNwuVypijjArFntf0N0uDgY7M9Hk13Ez/imbdk2iiRT5M5ndG4xipBS6u9OnTOjgE9MvZ4bJlzJhorknIuacB2H6ss5VF9OlpaRnHPRgeYCkruLFq+roB7GJatocrKrqyc7jM7SUqdIh+14e8ieDHIv/TS+SQtpXP0MRu1xIvs3ED26ncw51+GfugQhyehVh6h59ddQ5AUksEwq/u8BCq77Mq6iMWlbj0dTURWJYNhA76ygohtYppW0BYlHIbVbs5v/XLg7DEnzMHj5d87pbkJIDF7+nR4VrSE5+6e7838cFyyHLrNwxBye2vrXVsdsbJriQeKmzuIRc3Gr7uSNusUypJP25x7VzSUj57O0eB776w6zqnwDu6r30xRPai7eOvgBM4oms2RkKSOzh3eozraxU55RQhcoUnLH0xI0eotUnUJRMcNN2FZ60zEtaIUjKbjlPsJ71xHY8DJWLEzT2ucI711L9rybOPXO/4IRB86w+TDi1Lz6a4Z+5t8RafxGrsgyORkSoahBJJbo3RrCmSc3TUS4Lvle2l8fbwAAIABJREFUFDe23L9zMLqLe/gkiv/xN4R2r8FoqELNKcI/eVGPA0RPcYKEQ5fxqG7+ZelX+cHKx1JjWQVJE8J/WfpV3M03ntPqbx8JyyRuxImaMQzT6PAGIoRgQt4YJuSNoS7SwNpmzUXYiLK5ciebK3cyNLOIJcWlzBoyFZfc8Q3fxsawTAw9TIgwsiTjll24ZA2tl+xAJJcbIStJPUUPbcfbQ0jJdIRn9EwCG14hvHsNifpKTr3+OO22CNkWkYOb8U3qvgFk24sR+L0uVCVpO2720SyttltqtQsuYEguD5kzr+zvZbRiYPkeOFwwTMwfyxM3/ohcTzYAuZ5snrjxR0zMb1ugpEgyPs1LnjeXXE82HsV9Tlttewzy5nDDxKt46PJv8KnpNzE8Mzmsp6JZc/HQip/x4p63OBWp7/T6bZLq7pARpT7WSE34FE2xAPEejC9tDyErKBmDkNx+ejMlIrt95Cz9JAUfvw9XwcjkwfbukAkDI1Db9mNpQHOp5GS60frYhbV1S20dhOqQjDCSbdAbab+LAWcn4dBt3Kobv+ajLtqAX/OldhAdoSkamqKRMBNEE3HiiRiG1XF6QpVV5g0roXToTMqbKlh19EO2Vu0mYsR478ha3j+ylkn541gyspQJeWO6ZDvSItgLG1ESVjLXbdsWpmV2WDDvDEnb8UwsxdXjqXcd4cofQf4tX6fhvT8R2f9h209SVNTM3vUwkiWJ7AyNSNwg3EtF7fPRyqVWCCRZRrg0JFXDtj39Z554geEECYd+Q5EVMmSFDM1HPBEnYsSIJeId1i6EEIzMHsbImcO4Ob6M9cc3s+bYRhpjAXbXHmB37QHyvLks7qTm4kziRpywHgEgEA9xoukkGZofV5oK3+mcenc+hJDIWXwbkcNboE17c4F3bN80oXg1FZciEQjradNUdBXbtjETCUgkQAqTUHWEoiG5NISqIQawVX1/44RShwGBpmjkeLLI8+bgUz2dTkVlaH6uGruU7176j3xu1icYN2gUAKeaNRcPrfgZT+94mZOBjsVIbanIv/Puf7K79gABPURdpJ6a8CkaYwHCegS9m+aDLVPvJM3X5dd26TouNwXX3wNtTQK0LYI7PsDuBcV6WyiyTI7fjcc1MG7GtmVh6VESoUaMxhoSwXrMWLhX9C0XOs5OwmFAocoqWbKKV/UQMaJEjFinuqJkSWZG0WRmFE2mKljD6vIyNlRsRTcN1h3fxLpmzcXi4rlML5x0TgopbsR5vOwPHarIE5ZJwkr66wiSpoaa7EJtbrNV5M59pIQQSdtxRcGMBNqvHfQQV9EYhn7m3+Gd/2i+sITkycCKBglseIXI3g/JWvxxPCPaGz6bPtLm/ZRubDupadFjmEIgFBVJdSOpGkIZWPYdPeEXv/gFb775JkIIbrvtNj73uc916nVOkHDoEZ7mGdqebszSPh/dDRYARRkF3Db1Oq6fcAUbKraxunzDOZqLBSNms2D4bLLcSc3F5sqd7d602lORt5gPRhIxSMQQiFSw0GS1Uy22stuHkJVkm2wvfYsVqjuVfxeSTNGnvktg4+uEdnxAIlBL3WuP4x45jeyFt6Jk5vXKGs7E51ZRJAiE+75O0SG2jW3omIaOiUAoCrLb12eTAqNGjLXHNlIZqmWwP5+FI+akrHF6woYNG1i/fj0vvfQSiUSCa6+9lksuuYTRoztW6TtBwqFH3D71el7Z9w7XT+idtr2WYOFTvUQTyWBhdmAE2IJbdbN05DyWFJeyv+4wq8vL2Fm9j6Z4kDcOvM9bB1cmNRfFpdSE6zCstlMvhmV0SkWeFPEldSEhQBYSmqLhkl1osqtdXylJ1ZIq7VAjVi90V51zPZeH7IW34pu4gMbVzxI/eYDY0R1UHd9LxswrySy5EtHLluyaSyVbkgiGdQxzoEWKFmzshIGVMJDS+x2oTfbWHuQHKx9LWfhrsountv6Vf1n61Xa7BjtLaWkpv//971EUherqakzTxOvtXOBzgoRDj5hWOLFTJng9JVnkzsDn8hE3dMKJKIapd2pvcabmoj7ayJryspTmYkvlTrZU7iTbnYks5NTM7jNRJZU836AurdcGErZForljqkVH4m7WZJyd7hKSjJyRC5Fg84Ch3r9xqrmDybvha0QPbaZp3QuY4UaCm14nsn8D2Ys+jrt4aq+OklUVmewMjaawjm70kaBigBI1Yvxg5WPEznAxiJvJhoMfrHyMJ278Uae7B9tDVVX+67/+i//5n//hmmuu6bRJq1O4drigkISEx+Umz5tDricHr9L5Ijck9RwtmotPT7+Z4VlDgGSRuq0AAUk9WklRz3L2NjaxRJzGeICacB31kQaC8XCryXstbbKyP6t9EVw3iCbiWM3XsGy7lXGhEALv2NkULn+AjJKrQJIxg3XUvfEEda8/TqKp97QUkBxHkOPX8GoX9/fVtcc2ttsEYds2a49vSst17r33XtatW0dlZSXPPPNMp15zcf+fcbig0RQXmuLCZ3oIG1GiXahbqLJK6bCZlA6bSXnjCVaVb2DzyZ3nzLRQJJkvzrnjHOvznnCmc60g2a6qySouyYWqqKguD0KSk26yPbTz2Nd4jP/c8mf8tgkoJGyTr636Od8s+RQTskekniepGlnzbsQ7YR6Nq/9K/MReYsd2U3XiB2TMvIKMkquSxnq9gRBk+FxIsiAc6ViN/1GkMlSb2jmcTdzUqQrW9Oj8hw4dQtd1Jk2ahMfj4eqrr2bfvn2deq2zk3C44FFllWx3ZpfbZ1sozh7G3824le9d/g2uGXtJq9cnLJM/73iJ94+sS03hSyc2YNkW0UScJj2YarNtSkSJud3EJYHZbHzSVbV2NBHnP7f8mdhZN5+YqSePt6GfULMLybvuHgYtuwvZnwNWguDmN6l++mEih7b06rxxn1sly6+SxtHhFwwtppltockuijIK2nyss5w4cYIHHngAXdfRdZ13332X2bNnd+q1TpBw+MigyipZZwQLqYu/3hman2vGX0aRP6lEbvGDatFcPPjuT/nLjpeo6ITmoru0dExFE3GCiRgByabOCFMba6AuHqQpESNmmyT3O+e/m66v3n3eFMb66l1tPiaEwDNqBoWffICM2dc0z8hooP7t/+HUK79MywCc9tBcKtkZGqp8cUWKhSPmtFv/EUKwcHjnbujtcckll3DppZdy88038/GPf5ySkpJODx5y0k0OHzlaOqL8LpOIESNiRDrdEQWkPqx53hw+M/PjrC4vo6xiG3FTZ/3xzaw/vpnROSNYXFzKjKJzNRfpREgyeDOxIiF0PYqeiBNBIEkSLllFlVUUIaMKGVkSrfQW1ZF64u10bMUtg+oOvK4k1UXW3OvwjS+lcc1zxI7tIl6xj+pnf4h/2mVkzr4maaSXZi7GgvaZpplndjcJIVqZZvaEr33ta3zta1/r8uucIOHwkUWWZDI0Hz6Xh4geJdzFYAGtNRdlFdtYVV5GTfgUhxuOcbjhGJmanwXDZ7NwxGyy3L0zNlcIgezLQMgSZjQC2FiWScwyiRkxQCSL3pKCqii4JAVFKAz1F5Cp+ggmIuecU5NUCr25nbq+kpVP3rVfIlq+k8Y1z2EGThHa9i6RAxvJXnAznrGz094FJUkS2T6NYC9MvRuotJhmrj2+iapgDUUZBSwcPjstAaInOEHC4SOPJCT8mg+vy0O4eS62RdeChVt1s2TkPBYXl3Kg7giryjews3ofgXiINw9+wNuHVjGjaBJLiksZlTOid2zH3T6QFKxo8CyDQBvbtjFMHcPUiZAMLMUZhXhdXjyaFyt+OkWkyioSEvMLu9ax5SmeinvoBILb3iWw+S2sSBP17z6Ftmct2YtvQ80dkp432kxKoR3VCUd7eT7FAMGturl8dM+m0KUbJ0g4XDRIQiJD8+NR3IT0CNFEtMs3HiEE4/NGMz5vNA3RRtYc28i645sJ6xG2VO5iS+UuhmQUNs+5mIaWZlGa5NIQsowZCWIn2vddsm0bVcjcOmoRv939KpnN71QgyHfn8NlJ1yJkmeRQU0FndRlCUcmcfQ3ecXNpXPs3Yke3Ez95gOpn/wP/tEvInP0xJC29Q3J8HheSlJxPMWCsPC4inMK1w0WHIitkezLJ9WTjkrrvzZPjyeb6CVfy0GVf544ZtzAiaygAJ4PVPL3zZR5a8TNe2PMmtZ2c+d1ZhKwg+7M6dTMelTGEf53zWeRmWw5JCO6ZchM5qpf6SBO1kQbq40GCpk7cMrE62UWlZA4i75q7ybvuHpSsfLAtQtvfo+ov3ye878O0d0F5NJVsnwvZuWP1Oc5OwuGipcUyI6JHCRnhLtcrWlBllblDZzB36AzKG0+wuryMzZU7iSZivH9kHe8fWcek/LEsKS5lYv7YLs25aA8hpNR41GT6qf2bsiarqWtKzZqMJDaWbRNPxJvnlScL4imzQiGhSjKSEO0aELqHT6LwE98muP09gpvexIoGaXjvD4T3rCV78e248ob1+L224HIpZMuCQGggW3l89HCChMNFjRACn+bFo7oJG1EiRgR3s1mhuxumhcXZwyjOHsZNE69m3fHNrDlWRmMswJ7ag+ypPUieN4dFI+Yyb3hJl+ZctIfkciMkBTMawE701CAwWRCPWybxMwvispJ0upWUNruohKySWXI13nFzaVr3PNFDW9CrDlPz3I/xTV5MVun1aTPIU+TTnU8OfYMTJBwcSHbTZGg+fKqHWyYv4/X973PpqAXdPp9f83HV2CVcPnohu2r2s7p8A/vrjnAq0sCLe9/itf0rmD10OkuKSxmaWdSjtQtFQfZnY0VCScvrtNFcEE/oGAmd1l1UanMXlYQiZASg+HMYdNXniU3eR+Pqv5JoqCK8axXRQ1uSau6J89IyDa7FyuNiFN31B06QcHA4A0mSmDdsFrOHzCCihwl3weqjLWRJZnrRJKYXTaIqVMua8jI2nNjahuZiLtOLJqFI3ftICiEh+zKTRe3mNtn003YXlRASqqSgyCqqJKMMGU/Bbd8mvPN9Ahtfx4qFaPjgT4T2rCFn8SdwFYzo8EodIgSSEyX6BCdIODi0gSLJZLozcStugnq4XV+drlDkz+fjU67luglXsLFiG6vKN1AdSq/mItkmK3dYp0gXtm1j280pqmbjQCGStQ1lYin+0dPRP3yF+MFNGDXl1PztJ/gmLSSz9Hpkjz8ta5BlgSoLp07RSzhBwsHhPLgUF4MUF1E9RsgIYfTQcA+StY7FxaUsGjGXA3VHWF1exo7qva00F9ObNReju6G5kFxuEBJWJHCWnqJvsG0b0zQxMUESsOBG5DEzsDa8ht1QRXjPGiKHt5A17wZ8Exci2pmz0VkEkJ3hJhjRiV0kwru+xAkSDg6dwONyo6nNnVB6pMtivLY4n+Zia+UutlbuYnBGAUuKS5k9ZHqXNBeS6kL4szEj6Sho9xQbCkYgrr0b9pVhb3sPOx6hceXTBHatxr/443gHj0URUrfHuEqSIMuvoUR1wrGEo6dII06QcHDoJC3KbY/qJqSHuzRStSNaNBfLxl7ClspdrC4v41hTBZXBGp7Z+Qov7X2becNKWFw8l/xODkASsoLsy8KKBNOyxp4iJBkxaT72yKnYW97BPrQVq66CwIv/RXBMCcqcZWj+nKQnlZBTBfGu1Fd8HheqKhMa0BPvLiycIOHg0EVkSSbLnYknjfWKFs6cc3GssYJV5RvYUrmTWCLOB0fX88HR9V3SXAhJRvJlpW196UB4/IiFN2OPm4214VWor8I+tAXj2G4SMy8nMn4OkqykNBsuyYUiSahCaVb/nv/m71JksjPchKMGkXh/76IufJwg4eDQTVrqFRE9SlAPdVuM1x4jsodyR/Yt3DTpatYf38Ka8jIaYk0pzcUgbw6LR8yldNhMfK72dQhCiOZJdwPrm7XIH470sS9gH9yEveVd0GPYZa9jH9wMc6/FLizGNE1ixE53Uclq805DOe+7kaTkICNVEQSjBv1QmvnI4AQJB4ce4nV5cCsaISNMWI+mLQXVgt/l48oxi1Oai1VHN7C/7jB1Z2ouhkxjcXEpw7IGd3g+IYk+6XzqDEKSEOPnYo+YjL11BfaBTdBQjfXW/yJGTUfMugrhzWjdRdUs9Es0NxGY2EStBIqQUYTUKkXl1lQURXJU2j3ACRIODmlAkiQytQw8ipuwHu2WeWCH1xAS0wonMq1wItWhU6w5VsaHJ7YQT+isP7GF9Se2MCpneGrORZuaCyGQvFnJFllz4HQCCbcPMf8G7LGzsDa8BnUV2Ee2Y5/Yi5h+KWLivORsjWZiZpxIIgZIhPQIVaFaPIqWbL0VCqqsosrJuoYsK2RnyATCceLGwHnPFwr9Ypf18ssvc+2113L11Vfzxz/+8ZzH9+zZw6233sqyZcv4zne+Q6K5O+PkyZPccccdXHPNNXz5y18mHA739dIdHM6LKqsp88D2xlGmg0J/HrdO/hjfu/yfuW3KtalpekcajvN/W5/jeyse4bX9K2iMBc55raS6kH3ZCKX75oa9hcgbivSxf0DMvxE0Lxg69qa3sF55HLvyMABHgif5/sanaNKTn/8mPcz3Nz7F4UAFppnUa4TiIRoiTZyKNFIba6AxEUb2gOqWsKSW9JsjxusMfR4kqqureeSRR/jTn/7ECy+8wNNPP83BgwdbPeeb3/wm//qv/8qbb76Jbds888wzAHzve9/j05/+NG+88QZTp07lV7/6VV8v38GhU2iKxiBvDjlaFkovTq5r0Vz8vyX38JV5dzK9cCICQVAP89bBlfzbe4/wu83PED9rXyNkGdmXidTPA23aQggJadwspJu+ihg/N3lDb6rFeuf3GB88zTPbXkK3jFRaz8ZGtwx+u/tV4mZr+3TbtpKBw4gRioeI2xGidoiaaCMNRpiwaTS734ITNNqmz4PE2rVrmT9/PtnZ2Xi9XpYtW8Ybb7yReryiooJYLMbMmTMBuPXWW3njjTcwDIOysjKWLVvW6vjZBAIBTpw40epPVVXvzeR1cDgfHpebPE8uPtWD6MWbkBCCcYNG8fnZy/nXy/6Jq8Yswe/yYtk2W6t2U98cpyLCJp5IdmMlO58y0j7/IV0IzYs07zqka78A+cMBkI7t4WtHq7mkIYx8llbFtm22nTrQwVltVEXCNBPE9CiBWID66GnL9JCpE2+ZId4Lg6MuRPq8JlFTU0N+fn7q54KCArZv397u4/n5+VRXV9PQ0IDf70dRlFbHz+app57iscce68V34ODQNSRJIsudiVvRCOoR9DS2zLZFjieL6yZcwbKxl7C1ajeryj+kvLECgCYJHlzx01aaC9mbgZBkzGiYgdYBBSByByMt+xz24e3Eyl5DM3Q+VhdmtvYuf9UXcEBK7oYMO8GpWFM3rtDaMl0IgUAgywqqrKAlFLSEjiorabF5v9Do8yBhWVYrmwHbtlv93N7jZz8PaNOu4M477+SWW25pdayqqoo77rgjXW/BwaFbpGt+RWdRZIU5Q6czZ+h0Vm59iXcqthKW7Faai4l5Y1hSXMqkgnHIktRnnk9dRQgJMWYmuzWIbnmbeY1hCkSYezLfYYfLz2uGRsilkefuuSbEtm1sbKxm99sYNopkAwJVVpJmhpKCLMmozX9/lOnzIFFUVMTGjRtTP9fW1lJQUNDq8dra2tTPp06doqCggNzcXILBIKZpIsvyOa9rITMzk8zM3hlI7+DQU1rmV7hVjaAeJmqkvwuqLZbOvJGlM28kpIeTmotjZTREm9h76hB7Tx1ikCebRcVzmVs0FY9h9IvnU2eYOngy368o48MMjZtqg4yOGUzTQ0w8FmJlbgYzZo3qleu2VD9000A/o+4hEMiSlAocyT8yiqT0ypzz/qDP904LFy5k3bp11NfXE41Geeutt1i6dGnq8aFDh6JpGps2bQLgxRdfZOnSpaiqypw5c3jttdcAeOGFF1q9zsHhQkKWZLLdPR+h2lVaNBffvfQfuWv2cibkjQGgLtrIS3vf5t9WPsozR1dREWvoszV1Bbfs4q7J19Hg8fC/w/L4c2EmAVlCteGKuiDKa09gn9jXZ+uxsUlYJtFEnKAepiHWxKlIA2Ej0mdr6G2Ene5htJ3g5Zdf5r//+78xDIPbbruNu+++m7vvvpt7772XadOmsXfvXh544AFCoRBTpkzhhz/8IS6Xi4qKCu6//37q6uoYPHgwP/vZz8jK6nh7eeLECa644greffddhg1L3zhFB4d0YNs2IT1COE3GgV2lOnSK1eUbKKvYRqzZ7hugOHMwiwqmMG3QmF7t0OoOcdNg26kDnIo1UaB4mVFZibR3A7Sk8IaOR5p7DSIjt8fXkjQPsjejS6/J1Pz4Xb4eX3sg0C9Boq9xgoTDhUDCTBDQQ61u1H1JPBFnY8V2VpVvoCp0OuXrVz3ML5jC/MLJZGnpmQHRG9hNtUkhXtWR5AFJRkxZhJi6GNEFB92zcYKEEyQcHAYUUT1GQA/2emG7PWzb5mD9UVaXb2BH9V6s5luEhGBq7mgWFk1ldOaQAZlzt20bju3G2vgmRJqFhL4spDnXwPCJ3VqzEyScIOHgMOAwLZNwGsan9pTGaBNrj29i7bFNhPTTDgdFnlwWDp7GrLzxaPLAU27bho69cxX27rXQMihqyBikuR9DZOZ16VxOkHCChIPDgEU3DUJ6uN9SUC0kzARbKney+siHlAcrU8fdsos5+RNZWDSVfE92P66wbexAHVbZ63Cy2dVBkhCTFiKmLUWonUtBOUHCCRIODgOemBEnpIfQrf6fj1Bec4jV5WVsOXWAhH3aMG981nAWDZ7GxOwRA0p0Zts2nNiHVfYGhBuTB72ZiNlXI4qndJiCcoKEEyQcHC4IbNvuMyFeR1h6jGCglg+rdrOueicN8dPT73K0DBYWTmVuwSR8A8gbyk4Y2LvWYO9aDWZzsC0alUxBZZ+ruWrBCRJOkHBwuKCwLKvXZld0aR2GjhUNYiYM9jYcY03VDvY3HU89rgiZkrxxLCyaxjB//nnO1LfYwfpkYbtFTyGkpBX59EsQrnODmhMknCDh4HBBkjATBPUwsUSs30KFbZqYkQB2IqlCro02srZqJxtr9xI7w6Oq2F/IwqJpTB9Amgu7Yn8yBRWsTx7w+BGzrkaMmtYqBeUECSdIODhc0MSNpNpXt4yOn9wL2LaFFQ5hGbHTazINNtfuY03VTqqj9anjftXDvILJzC+cQvYA0FzYZgJ791rsHStPp6AKipFKr0XkFAJOkHCChIPDRwDbtokYUUJ6/9QrbNvGjkUwYxHOdJK1bZvDgZOsrdrJzvrDWJzWXEzJHcWiomkDQnNhhxuTKahje5IHhEBMKEXMuBQ5I9cJEv29iN7GCRIOFwv9Xa+w9BhmJAht3FYa4yHWV+/iw5rdhIxo6nihJ5dFRVOZlT+h3zUX9slDWGWvQaAuecDtQ55/A+r0rvnEOUHiAsMJEg4XG4ZpENIj/VKvsHQdKxpo10k2YZnsqDvEmqodlIdOz4RJai4msKBoKgWenL5a7jnYZgJ773rs7R9Ac63F9ZmHkM7TAXU2H6Ug0edW4Q4ODr2PKqvkeLKIG26CRu8POjoTyeVCyNnNBe1zdR2KJFOSP56S/PGcCNWytmoHW04dIGbqrK7aweqqHYzPGs7CoqlMyinuc82FkBXElMXYo6Zjb3sPEgbC1/M5FRcqzk7CweEjTn/VK2zLxIqEsIyO1eJhI0ZZzR7WtqG5WFA4ldJ+1Fw4hWsnSDg4XBT0R73Ctm2saAgrHu34yYBlW+xtPMaaynM1FzPzxrGoaCrD/J1P+6SDiz1IOOkmB4eLBEmSyNQy8CjuZn1F7/tBCSGSM7RlGTPS8QxtSUhMzhnJ5JyR1EYbWVe9k7KapOZiY+1eNtbuZYS/kIVFU5kxaOyA0Vx8lHF2Eg4OFylRI0ZQD5GwzI6fnAYsPd5c0O7aLUc3DTad2s/aqh1URU5rLnyKh/mFva+5cHYSDg4OFyUe1Y2muAjpfZOCklwaQsrBjDRhm50PTC5ZZUHhFOYXTOZIsJI1lTvYWX+YcCLKuxWbeK9iM5ObNRdjBoDm4qOGEyQcHC5iJJFMQblljYAe7vUuKKEoyP5srEgQy+jatYQQjM4cwujMITTFQ6yv3s36ml2EjCg76w+zs/4whZ4cFhZNY/YA0Fx8VHDSTQ4ODsBpl9mgHu71Wdu2bScDhR7r+MnnIWGZ7Kg/nNRcBKtSx92yi9n5E1iYBs2Fk25ycHBwIPlN3ad50VSNUDxMNBHttQSUEALZl5ksaEdbW3l0BUVKOs2W5I2jIlzL2qqdbK7dT8zUWVO1gzVVOxiXNYxFRdP6RXPxUcAJEg4ODq1QJJlsTyaehEZQ710hnuT2gSRjRYNdLmifzVBfPrePuYzrRixgQ+0e1lXtoj4e4EDTCQ40nWjWXExp1lx40vQOPvo4QcLBwaFNNEXDJbt6XYgnudwgpGSg6EJBuz28qptLh5SwdPAM9jUeY03VTvY1HqMhHuS1Y+t563gZM/PGsbBoKsP7WHNxIeIECQcHh3YRQuBzeXErGiE9TMSI9UoXlKS6EFJ2q9kUPT6nkJiUM5JJjuaiRziFawcHh04TT+gE46Fem13R1myKdKKbBptP7WdNG5qLeYWTWFA4hWytdZHaKVw7ODg4dBJNceGScwjrEUJ6JO1dUEJIyP5MRFQ+ZzZFOnDJKvMLpzCvWXOxtmoHO+qPEE5EWVGxmfcqtqTmXDiaiyROkHBwcOgSQgj8mg+3ohHUw0QT6f/WL3l8IKenoN0WrTQXepgPq3exvno3QSNyjuZiztAZfDT2BN3DSTc5ODj0iJgRJ6AHe8XewzJ0rEj7synSScIy2Vl/mLVVOzkSrEwd12QXpcNmsrh4LoX+/E6dy0k3OTg4ODTjVjVcskpIDxFOc2FbUl0If/uzKdKJIiWdZmfmjaMifCo15yJu6qwq38Cq8g3N9HE/AAAQ9ElEQVSMHzSaxcVzmVo44aLRXDg7CQcHh7QRT8QJxsNpL2x3ZTZFOokYMTY2HGJt5XbqIg2p4znuLBYVz2H+sFn4tXN3DB+lnYQTJBwcHNKKbduE9AjhNBe2uzqbIl1Imgfh8bG39iAryzewt/Zg6jFZkpk1eCpLiksZkT00dfyjFCScdJODg0NaEUKQofnwpLmwfXo2hYIZDUEffr+VhMTkgvFMLhhPbbiO1eVlbDixlWgiRlnFNsoqtjEiayhLRpYys2hyn62rL+jzncTJkyf55je/SV1dHaNGjeInP/kJPl/riFtTU8O3v/1tTp06hSRJfOtb32LBggUYhsG8efMYPnx46rl/+9vfkOXzi2CcnYSDQ/8RM+IE9RCGlb6aQnI2RbBPCtrt6STiCZ3NlTtYdXQDJ4PVqeN+l5f/uu7fnJ1Ed/ne977Hpz/9aa677jp++ctf8qtf/YpvfvObrZ7z4x//mMsvv5w77riDw4cP8/d///esXLmSffv2UVJSwpNPPtnXy3ZwcOgmblXDpaiE9WjaUlDJ2RRyl2dTpBNNcbFg+GzmD5vF4YZjrC7fwLaqPYT0SL+sp7fo0yBhGAZlZWX88pe/BODWW2/l7/7u784JEldddRXz588HoLi4mHg8TiQSYceOHdTX13PrrbeiKAr33XcfpaWlrV4bCAQIBAKtjlVVVeHg4NB/SEJKpaBCeiQtDrM9mU2RToQQjMktZkxuMU2xAGUV2/ptLb1BnwaJhoYG/H4/ipK8bH5+PtXV1ec8b9myZal/P/nkk0yaNImMjAyEEFxxxRV88Ytf5MCBA9x99928/PLL5Obmpp7/1FNP8dhjj/X+m3FwcOgyiqwkHWYNjUAaUlBCkpF8WRAJYel9W9Buiyx3JleOWdLfy0grvRYkXn/9dX74wx+2OlZcXHyOzP18svff/e53PP300/zhD38AYPny5anHJk+ezPTp09m8eTNXXnll6vidd97JLbfc0uo8VVVV3HHHHd1+Lw4ODulFU7X/3969xzR1vnEA//a0p6cttZQ7bF4yjQkZ21w20LERmW6Tm+gkZt4my4xZzIwY/9iG4Mwubl7CYH+Y/WHCdHGEbGPEDgNEJ2NBcBMNmZI5x8bUiSAduslFaWnP7w+E3/hBf8qt5fR8P4kJNKfyPrymj+973vM8CNXpJ+QUVH9viml3e1N0Y6JLeajdpCWJlJQUpKSkDHlt4Mazy+WCVquF3W5HePjIpXr37duH77//HkVFRYiMjAQAHDlyBE888QRmzpwJoP9InCgObVFosVhgsVgmISIimkiDp6BEw4Q0ORIMpru9KW5NSikPtfLqI4OiKCI2Nhbl5eUA+j/0Fy5cOOy6Q4cO4ccff0RxcfFgggCAixcv4tNPPwUANDc348KFC3jyySe9M3gimhQDTY6CjVbohfH1pRb0ErQBQdDo2N96onj9CGxLSwuys7PR0dGBqKgo5OfnIzAwEMXFxWhvb0dWVhbmz58Ps9k8ZEVw4MABBAQEICcnB83NzdBoNMjNzR28wf3/8AgskTIM9Nnuco6vyZEsu/uf0B5nD22ApcL5xDURTTkut2tCmhy5HXfGXUlW7UlCHRWqiEhRtIIWgYa7W1Ba/Zj/HkFvgBBgheYeD9ySZ0wSRDRlSTo9QoxWBErToB1j1VVBJ0JrtkIQpQkenTowSRDRlDbQZzvMFAKzaIQGo+8W1/88hQWCZJyEEfo3JgkiUgRBEGAxWBBitEIawxbUQIFArdEMjCHRqBWTBBEpil6nR4gpCFbJAp0w+nsNgsHU//CdwERxP5gkiEiRTHojQo3BMOtNo96CEvQGCKZAaAR+BN4Lf0NEpFiCIMAiTUOIKQgG7ehuTAuiHlqefLonJgkiUjy9VkSwyYogKXBUW1ADlWQ1Ip/Q9oRJgoj8hlFvQKgpGNNGsQWlEbTQBgRCEA2TPDplYpIgIr/S37tiGkJHsQWl0QgQAqZBkEyTPDrlYZIgIr8kjnILqv+IrBlaE4/I/pvX25cSEXmTUW+ApNOj09F1X7WgBMkEaIRx13zyF1xJEJHfEwThbi2owPsqR84jsv/FlQQRqYakk6DX6tHt6EHXPTriCaIeGrMVsg/7Z08FTBJEpCoajQZmKQAG0YDO3i7c7vPcc0Kj1UGjVffHJNdSRKRKOkGLIGMggg3WMZX3UAt1p0giUj2DKEGvE9Hl6Ea34/a4mhz5I64kiEj1BM1/y3uMpcKsP2OSICK6S68VETzOJkf+hr8FIqJ/GWhyFGoKhklnVP1jdUwSREQj0ApaWI0WBBusEAX13r5lkiAi+j8kUUKIKQjT9AFjap2qdEwSRET30F800DyqooH+gkmCiOg+DRQNtEoW1dzYVu9GGxHRGJn0Rkg6Pboc3ehx3vbrJyvUkQqJiCaYVtDeLRpova+igUrFlQQR0TgMFA3scvSg+x5FA5WISYKIaJw0Gg2mSQEw6PTodHT7ejgTikmCiGiCiHef2O5zu3w9lAnDexJERBPMn6rKMkkQEZFHXt9uunbtGt544w10dHTgoYceQl5eHgICAoZc09LSgqVLl2LmzJkAgNDQUBQWFsLhcCA3NxeNjY0wGAzIy8vDnDlzvB0CEZFqeH0l8e6772Lt2rWorKzEI488gk8++WTYNY2NjUhPT4fNZoPNZkNhYSEA4PDhwzAajaioqEBOTg62b9/u7eETEamKV5OE0+lEfX09kpKSAAAZGRmorKwcdt358+fx66+/Yvny5cjMzMTFixcBANXV1Vi2bBkAIC4uDjdu3MC1a9eGvPfWrVu4evXqkD9tbW2THBkRkX/y6nbTzZs3YTabodP1/9iwsDBcv3592HWSJGHZsmVYvXo1ampqsHnzZpSXl6O9vR1hYWGD14WFhaGtrQ0PPPDA4GufffYZ9u/fP/nBEBGpwKQliYqKCuzevXvIa7NmzYJGM7SK4v9+DwBbtmwZ/DoxMREfffQRmpubIcvykOtlWYYgDF0MvfLKK1ixYsWQ19ra2rBu3boxx0JEpFaTliRSUlKQkpIy5DWn04kFCxbA5XJBq9XCbrcjPDx82HsPHz6MpUuXIigoCEB/MtDpdIiIiEB7e/vgDe2//vpr2PstFgssFsskRUVEpC5evSchiiJiY2NRXl4OADhy5AgWLlw47Lr6+nqUlJQAAE6fPg23243Zs2cjMTERNpsNAHDmzBlIkjRkq4mIiCaWRpZlrxYwbGlpQXZ2Njo6OhAVFYX8/HwEBgaiuLgY7e3t2Lp1K65fv47s7GzY7XZIkoQPPvgA0dHR6O3txc6dO9HY2Ai9Xo9du3YhJibmnj/z6tWreO6553DixAlMnz7dC1ESEfkHrycJX2CSICIaG1XUbnK5+uuo8CgsEXlLZGTk4ElOJVN+BPfBbrcDAE84EZHX+MvOhSq2m+7cuYPGxkaEhYVBq/Vt4a2B47hFRUWIjIz06Vgmgr/FAzAmpZjqMXEloSAGgwGxsbG+HsYQkZGRfvG/jAH+Fg/AmJTCH2OaSlgFloiIPGKSICIij5gkiIjII+0777zzjq8HoTaSJGHBggWQJMnXQ5kQ/hYPwJiUwh9jmmpUcbqJiIjGhttNRETkEZMEERF5xCThRWVlZUhNTcWSJUtQVFTk6+GM2f79+5GWloa0tDTs27cPAFBXV4f09HQsWbIEBQUFPh7h2OzduxfZ2dkAgAsXLiAjIwNJSUnIzc1FX1+fj0c3OlVVVcjIyEBKSgp27doFQPlzZLPZBv/d7d27F4Dy50kRZPKKtrY2edGiRfLNmzfl7u5uOT09XW5qavL1sEattrZWXrVqldzb2ys7HA45MzNTLisrkxMTE+UrV67ITqdT3rBhg1xdXe3roY5KXV2dvGDBAvmtt96SZVmW09LS5IaGBlmWZXn79u1yUVGRL4c3KleuXJETEhLk1tZW2eFwyGvWrJGrq6sVPUc9PT1yXFyc3NHRITudTnnlypVybW2toudJKbiS8JK6ujo89dRTsFqtMJlMSEpKGrG/91QXFhaG7Oxs6PV6iKKIOXPm4NKlS5g1axZmzJgBnU6H9PR0RcX2999/o6CgAJs2bQLQX87+zp07ePzxxwF47sU+VR0/fhypqamIjIyEKIooKCiA0WhU9By5XC643W7cvn0bfX196Ovrg06nU/Q8KYUqynJMBf/bnzs8PBznzp3z4YjGZu7cuYNfX7p0CRUVFXj55ZeHxTZS7/KpaufOndi2bRtaW1sBDJ8rT73Yp6rLly9DFEVs2rQJra2tePbZZzF37lxFz5HZbMbWrVuRkpICo9GIuLg4iKKo6HlSCq4kvMTtdg/rzz1Sf2+laGpqwoYNG/Dmm29ixowZio3tq6++QlRUFOLj4wdfU/pcuVwunDp1Ch9++CG++OILnDt3Dn/++aeiY/rll1/w9ddf47vvvkNNTQ0EQUBtba2iY1IKriS8JDIyEmfOnBn83lN/byU4e/YssrKykJOTg7S0NJw+fXqwHDugrNjKy8tht9uxfPly/PPPP+jp6YFGoxkSz0i91Key0NBQxMfHIzg4GADw/PPPo7KyckgFZCXNEQCcPHkS8fHxCAkJAdC/tVRYWKjoeVIKriS85Omnn8apU6dw48YN3L59G8eOHRuxv/dU19rais2bNyMvLw9paWkAgHnz5uGPP/7A5cuX4XK5cPToUcXEdvDgQRw9ehQ2mw1ZWVlYvHgxdu/eDUmScPbsWQD9p2qUEg8ALFq0CCdPnsStW7fgcrlQU1OD5ORkxc4RAERHR6Ourg49PT2QZRlVVVWYP3++oudJKbiS8JKIiAhs27YNmZmZcDqdWLlyJR577DFfD2vUCgsL0dvbiz179gy+tnr1auzZswdbtmxBb28vEhMTkZyc7MNRjl9eXh527NiBrq4uxMTEIDMz09dDum/z5s3Dxo0bsXbtWjidTjzzzDNYs2YNZs+erdg5SkhIwM8//4yMjAyIoohHH30Ur732Gl544QXFzpNSsCwHERF5xO0mIiLyiEmCiIg8YpIgIiKPmCSIiMgjJgkiIvKISYJUz+l0IiEhARs3bvT1UIimHCYJUr3jx48jOjoajY2N+P333309HKIphc9JkOqtX78eqampaGpqQl9fH9577z0AwIEDB1BSUoKAgADExsbixIkTqKqqgsPhQF5eHurr6+FyufDwww9jx44dMJvNPo6EaOJxJUGq9ttvv6GhoQHJycl48cUXYbPZcPPmTdTU1KC0tBQlJSUoLS1Fd3f34HsOHDgArVaL0tJSfPPNNwgPD0deXp4PoyCaPCzLQapWXFyMRYsWISgoCEFBQZg+fTq+/PJL2O12JCcnw2KxAADWrVuHH374AQBQXV2Nzs5O1NXVAei/pzFQeI7I3zBJkGr19PTAZrNBr9dj8eLFAICuri58/vnnSEtLw793Yv9dQdXtdiMnJweJiYkAgO7ubvT29np38ERewu0mUq2ysjJYrVbU1NSgqqoKVVVV+Pbbb9HT04OYmBgcO3YMnZ2dAICSkpLB9yUkJKCoqAgOhwNutxtvv/028vPzfRUG0aRikiDVKi4uxquvvjpklWCxWLB+/XocOnQIL730ElatWoWMjAx0dnbCaDQCAF5//XU8+OCDWLFiBVJTUyHLMrKzs30VBtGk4ukmohGcP38eDQ0Ng6WnDx48iJ9++gkff/yxj0dG5F1MEkQj6OrqQk5ODpqbm6HRaBAVFYX3338fERERvh4akVcxSRARkUe8J0FERB4xSRARkUdMEkRE5BGTBBERecQkQUREHjFJEBGRR/8BXcIKD+ZA5E0AAAAASUVORK5CYII=\n",
      "text/plain": [
       "<Figure size 405.725x360 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "generation = [10,20,40,60,80]\n",
    "\n",
    "sns.lmplot('Age','Survived',hue='Pclass',data=data1,x_bins=generation)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 68,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<seaborn.axisgrid.FacetGrid at 0x1a2547f400>"
      ]
     },
     "execution_count": 68,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432.85x360 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.lmplot('Age','Survived',hue='Sex',data=data1,palette = 'summer',x_bins=generation)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.6.5"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}