Data Analysis (Pandas CaseStudy 2).ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "2f604eb5",
   "metadata": {},
   "source": [
    "# Analysis on a Restaurant Data "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "fc846923",
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import seaborn as sb"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "82ee5e07",
   "metadata": {},
   "outputs": [],
   "source": [
    "dataset = pd.read_csv(\"tips.csv\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "1ef18448",
   "metadata": {},
   "source": [
    "# to get the starting top 5"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "fd2ea97e",
   "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>total_bill</th>\n",
       "      <th>tip</th>\n",
       "      <th>sex</th>\n",
       "      <th>smoker</th>\n",
       "      <th>day</th>\n",
       "      <th>time</th>\n",
       "      <th>size</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>16.99</td>\n",
       "      <td>1.01</td>\n",
       "      <td>Female</td>\n",
       "      <td>No</td>\n",
       "      <td>Sun</td>\n",
       "      <td>Dinner</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>10.34</td>\n",
       "      <td>1.66</td>\n",
       "      <td>Male</td>\n",
       "      <td>No</td>\n",
       "      <td>Sun</td>\n",
       "      <td>Dinner</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>21.01</td>\n",
       "      <td>3.50</td>\n",
       "      <td>Male</td>\n",
       "      <td>No</td>\n",
       "      <td>Sun</td>\n",
       "      <td>Dinner</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>23.68</td>\n",
       "      <td>3.31</td>\n",
       "      <td>Male</td>\n",
       "      <td>No</td>\n",
       "      <td>Sun</td>\n",
       "      <td>Dinner</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>24.59</td>\n",
       "      <td>3.61</td>\n",
       "      <td>Female</td>\n",
       "      <td>No</td>\n",
       "      <td>Sun</td>\n",
       "      <td>Dinner</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   total_bill   tip     sex smoker  day    time  size\n",
       "0       16.99  1.01  Female     No  Sun  Dinner     2\n",
       "1       10.34  1.66    Male     No  Sun  Dinner     3\n",
       "2       21.01  3.50    Male     No  Sun  Dinner     3\n",
       "3       23.68  3.31    Male     No  Sun  Dinner     2\n",
       "4       24.59  3.61  Female     No  Sun  Dinner     4"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dataset.head() "
   ]
  },
  {
   "cell_type": "markdown",
   "id": "21d44be9",
   "metadata": {},
   "source": [
    "# To get the last 5"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "882881ed",
   "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>total_bill</th>\n",
       "      <th>tip</th>\n",
       "      <th>sex</th>\n",
       "      <th>smoker</th>\n",
       "      <th>day</th>\n",
       "      <th>time</th>\n",
       "      <th>size</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>239</th>\n",
       "      <td>29.03</td>\n",
       "      <td>5.92</td>\n",
       "      <td>Male</td>\n",
       "      <td>No</td>\n",
       "      <td>Sat</td>\n",
       "      <td>Dinner</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>240</th>\n",
       "      <td>27.18</td>\n",
       "      <td>2.00</td>\n",
       "      <td>Female</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Sat</td>\n",
       "      <td>Dinner</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>241</th>\n",
       "      <td>22.67</td>\n",
       "      <td>2.00</td>\n",
       "      <td>Male</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Sat</td>\n",
       "      <td>Dinner</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>242</th>\n",
       "      <td>17.82</td>\n",
       "      <td>1.75</td>\n",
       "      <td>Male</td>\n",
       "      <td>No</td>\n",
       "      <td>Sat</td>\n",
       "      <td>Dinner</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>243</th>\n",
       "      <td>18.78</td>\n",
       "      <td>3.00</td>\n",
       "      <td>Female</td>\n",
       "      <td>No</td>\n",
       "      <td>Thur</td>\n",
       "      <td>Dinner</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "     total_bill   tip     sex smoker   day    time  size\n",
       "239       29.03  5.92    Male     No   Sat  Dinner     3\n",
       "240       27.18  2.00  Female    Yes   Sat  Dinner     2\n",
       "241       22.67  2.00    Male    Yes   Sat  Dinner     2\n",
       "242       17.82  1.75    Male     No   Sat  Dinner     2\n",
       "243       18.78  3.00  Female     No  Thur  Dinner     2"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dataset.tail()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "4b39b0e7",
   "metadata": {},
   "source": [
    "# To get the unique value of all these attributes[day, time, size] in the dataset "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "73d12468",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array(['Sun', 'Sat', 'Thur', 'Fri'], dtype=object)"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dataset['day'].unique()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "c3714bb5",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array(['Dinner', 'Lunch'], dtype=object)"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dataset['time'].unique()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "c0215446",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([2, 3, 4, 1, 6, 5], dtype=int64)"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dataset['size'].unique()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "ee0a6a8a",
   "metadata": {},
   "source": [
    "# To get the total no. of Dinner & Lunch"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "01a27e35",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Dinner    176\n",
       "Lunch      68\n",
       "Name: time, dtype: int64"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dataset['time'].value_counts()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "id": "31b00371",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\91986\\anaconda3\\lib\\site-packages\\seaborn\\_decorators.py:36: FutureWarning: Pass the following variable as a keyword arg: x. From version 0.12, the only valid positional argument will be `data`, and passing other arguments without an explicit keyword will result in an error or misinterpretation.\n",
      "  warnings.warn(\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:xlabel='time', ylabel='count'>"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "sb.countplot(\"time\",hue=\"time\", data=dataset)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "id": "975a5319",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "time\n",
       "Dinner    10.0\n",
       "Lunch      6.7\n",
       "Name: tip, dtype: float64"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dataset.groupby(['time'])['tip'].max() "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "id": "fc424076",
   "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>sex</th>\n",
       "      <th>Female</th>\n",
       "      <th>Male</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>smoker</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>No</th>\n",
       "      <td>5.2</td>\n",
       "      <td>9.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Yes</th>\n",
       "      <td>6.5</td>\n",
       "      <td>10.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "sex     Female  Male\n",
       "smoker              \n",
       "No         5.2   9.0\n",
       "Yes        6.5  10.0"
      ]
     },
     "execution_count": 26,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dataset.groupby(['smoker','sex'])['tip'].max().unstack()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "aea19cc2",
   "metadata": {},
   "source": [
    "# to get the tip as a percentage created a variable & i have store in it"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "id": "3af3720b",
   "metadata": {},
   "outputs": [],
   "source": [
    "dataset['tip_percent'] = dataset.tip / dataset.total_bill"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "id": "204ccb22",
   "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>total_bill</th>\n",
       "      <th>tip</th>\n",
       "      <th>sex</th>\n",
       "      <th>smoker</th>\n",
       "      <th>day</th>\n",
       "      <th>time</th>\n",
       "      <th>size</th>\n",
       "      <th>tip_percent</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>16.99</td>\n",
       "      <td>1.01</td>\n",
       "      <td>Female</td>\n",
       "      <td>No</td>\n",
       "      <td>Sun</td>\n",
       "      <td>Dinner</td>\n",
       "      <td>2</td>\n",
       "      <td>0.059447</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>10.34</td>\n",
       "      <td>1.66</td>\n",
       "      <td>Male</td>\n",
       "      <td>No</td>\n",
       "      <td>Sun</td>\n",
       "      <td>Dinner</td>\n",
       "      <td>3</td>\n",
       "      <td>0.160542</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>21.01</td>\n",
       "      <td>3.50</td>\n",
       "      <td>Male</td>\n",
       "      <td>No</td>\n",
       "      <td>Sun</td>\n",
       "      <td>Dinner</td>\n",
       "      <td>3</td>\n",
       "      <td>0.166587</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>23.68</td>\n",
       "      <td>3.31</td>\n",
       "      <td>Male</td>\n",
       "      <td>No</td>\n",
       "      <td>Sun</td>\n",
       "      <td>Dinner</td>\n",
       "      <td>2</td>\n",
       "      <td>0.139780</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>24.59</td>\n",
       "      <td>3.61</td>\n",
       "      <td>Female</td>\n",
       "      <td>No</td>\n",
       "      <td>Sun</td>\n",
       "      <td>Dinner</td>\n",
       "      <td>4</td>\n",
       "      <td>0.146808</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   total_bill   tip     sex smoker  day    time  size  tip_percent\n",
       "0       16.99  1.01  Female     No  Sun  Dinner     2     0.059447\n",
       "1       10.34  1.66    Male     No  Sun  Dinner     3     0.160542\n",
       "2       21.01  3.50    Male     No  Sun  Dinner     3     0.166587\n",
       "3       23.68  3.31    Male     No  Sun  Dinner     2     0.139780\n",
       "4       24.59  3.61  Female     No  Sun  Dinner     4     0.146808"
      ]
     },
     "execution_count": 28,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dataset.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "98cce7ac",
   "metadata": {},
   "source": [
    "# Visualizing the total_bill with the tip and analysing it"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "id": "ffa41c0b",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:xlabel='total_bill', ylabel='tip'>"
      ]
     },
     "execution_count": 31,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "dataset.plot.scatter(x=\"total_bill\", y=\"tip\") # Through this i can make out that the \n",
    "                                             #one who has more of total_bill that person has given more of tips"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "ae165c8a",
   "metadata": {},
   "source": [
    "# compare between male and female"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "id": "fce85578",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:xlabel='total_bill', ylabel='tip'>"
      ]
     },
     "execution_count": 37,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "sb.scatterplot(x=\"total_bill\", y=\"tip\", data=dataset, hue=\"sex\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "d44b6b3c",
   "metadata": {},
   "source": [
    "# now let's compare with time like when people are more in a restaurant"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "id": "875f34d4",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:xlabel='total_bill', ylabel='tip'>"
      ]
     },
     "execution_count": 36,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "sb.scatterplot(x= \"total_bill\", y= \"tip\", data=dataset,hue=\"day\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "1b31290a",
   "metadata": {},
   "source": [
    "# Created 2 separate scatterplot to its more easy to analysis"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "id": "203669c0",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<seaborn.axisgrid.FacetGrid at 0x203f10126a0>"
      ]
     },
     "execution_count": 40,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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EBija5WRhH+M1M+I06UtExpbYcCfpfaTPTO2jTEQmNgUPIgMUEeLgv86dTkJESFfZZYsymZcRG7xKiYgMQHJ0GP93xXxc3eY3fPmMqUxPjQpirURkNNKEaZFBmJsZy/NfOoF9lU1EhDqYmhxJVJgmS4vI2HPC5ARevutECqubiY8IYUpyJK4QfUwQEX9qFUQGKTMunMy48GBXQ0RkUIwx5CVFkpcUGeyqiMgopmFLIiIiIiISEAUPIiIiIiISEAUPIiIiIiISEAUPIiIiIiISEAUPIiIiIiISEAUPIiIiIiISEAUPIiIiIiISkKCs82CMiQX+DswBLOBzlmV9FIy6iIiIyMTg9Vrsrmhkf1UTsS4n01KjiXFpYU+R/gjWInG/B16xLOtyY0wIoBW2REREZFi9v7uSWx5aTbvHC8BnlmTx3+fOIDY8JMg1Exk7RnzYkjEmGjgZuA/Asqx2y7JqR7oeIiIiMrp5vBbFNc2UN7QO+lgVDa18658buwIHgMc/KWTrwfpBH1tkIglGz0MeUAE8YIyZD6wBvmxZVlP3jYwxtwG3AWRnZ494JUVExgO1pTJWHaxt4aGPCnjwgwKiw5x85/wZnD07lYjQgX10aWh1c7CudxBS2dg22KqKTCjBmDDtABYBf7EsayHQBHyr50aWZd1jWVa+ZVn5SUlJI11HEZFxQW2pDIuWOmgsH9ZT/GtdMX97Zy9tbi8VjW189akNrC+sHfDxkqJCyc+J61WekxAxiFqKTDzBCB6KgCLLsj7ufP0MvmBCRERERjN3O+x6HR68AP52Erz3G6gvGfLT1Da388Sqwl7ln+yrHvAxo8Kc/PiSOcxOjwYgOszB765awIzUqAEfU2QiGvFhS5ZllRpjCo0x0y3L2gGcAWwd6XqIiIhIP5Wsg8euAMvyvV7xQzA2OPErQ3qaMKed3IRwDlQ3+5WnxYQN6rgz06J57JalHKxrJSrMQWac8rWI9Few1nm4E3jUGLMRWAD8b5DqISIiIoEqWnM4cDjkk79BY8WQnibMaefOM6YS6jj8MSUnIZwlk+IHfeyY8BBmpkUrcBAZoKCkarUsaz2QH4xzi4iIyAC5YnuXRSSDY3A9An3Jz4njuS8ez46yRsIcNuZkxJAVrw/8MnZ1rnN2jWVZdxtj0oE/WJZ1eZCr1W/BWudBRERExprMJRCdAfXFvtfGBmd8D8KGft6AMYZZ6THMSo8Z8mOLBEks8EXgbsuyDgJjLnAABQ8iIiLSTWuHm8rGdiJDHb0XT0ucAte/AMWrobUO0hf6vkQkED8HJhtj1gO7gJmWZc0xxtwIXALYgTnAr4EQ4DqgDTjfsqxqY8xk4M9AEtAM3GpZ1vaRvggFDyIiIgLA7vIGfvnqDl7fWsaU5Eh+ePFsluUlYIw5vFHiFN+XiPTXt4A5lmUtMMbkAi91e28OsBAIA3YD/21Z1kJjzG+B64HfAfcAX7Asa5cxZilwN3D6CNYfUPAgIiIiQGNrB999bjMrO9Oh7ixr5MYHVvHSnScyNWV0pjMtq2tlU3EdVY1t5CVFMjczmjCnPtrImPSWZVkNQIMxpg54sbN8EzDPGBMJHA883S2YDx35aip4EBEREeBgXWtX4HBIm9vL3orGURk8VDa08c1nNvDursqusl9dMY/LF2cFsVYiA9Z9qXNvt9defJ/XbUCtZVkLRrhevQSUqtUYs8gYc5cx5k5jjBZ0ExERGWfCQ+xEhfZ+phjtcgahNse2rbTeL3AA+NFLWymuaQlSjUSOqQEYUCRuWVY9sM8YcwWA8Zk/lJUL1DGDB2PM94CHgAQgEXjAGPPd4a6YiIiIjJzMuHD+30Wz/MrOnZPC9NToINXo6BpaO3qV1be4aenwBKE2IsdmWVYV8IExZjPwywEc4lrgZmPMBmAL8KmhrF+gAhm29BlgoWVZrQDGmJ8Da4GfDGfFREREZGRdNC+NyUkR7KtsIiEylDnp0cRHhBx7xyCYnBRFqMNGm9vbVXb6jCTSY4d+zQmRoWJZ1jV9lD0IPNjtdW5f71mWtQ84d3hreGyBBA8F+GZ+t3a+DgX2DFeFREREJDhcIQ4W58SzOGfwKzkPt2kpkTz0uSX8+KWt7C5v5MJ5adxx2hTCQzSdU2Q4BfIX1gZsMca8DljAWcD7xpg/AFiWddcw1k9ERESkF2MMy/ISeOzWpTS1eUiMDCHEYQ92tUTGvUCCh+c6vw55e3iqIiIiItI/Ma4QYlzBroXIxHHM4MGyrIdGoiIiIiIiIjK6HTF4MMY8ZVnWlcaYTfiGK/mxLGvesNZMRERERERGlaP1PHy5899twDe7lRvg/4atRiIiIiIiMiodMXiwLKuk89splmXt7/6eMWbGsNZKRERERGSCMcZ4gE2AE3DjW2vtd5ZleY0x+cD1wU5WdLRhS7cDXwTyjDEbu70VBXww3BUTkaHR0u5mzf5adpbWE+1yMjsjhplpo3PRJxERkQmuxbKsBQDGmGTgMSAG+L5lWauB1cN5cmOMw7Is99G2OdqwpceA/wA/A77VrbzBsqzqIaifyITT3O6mw+0lJnzkFl1av6+ExPJVLNn3GB57GPs6rmGf7XgmpcSOWB1EjsbjtSiobKKhzU1mrIvEqNBgV0kGqLa5nS0H6ymtbyUz1sXs9Ggiw5zBrpbIsMj91svXAP8LZAMHgO8U/PyCx4bq+JZllRtjbgNWGWN+AJwCfMOyrAs7X2cDeZ3//s6yrD8YY3LxfX5/HzgeKAY+ZVlWizFmMvBnIAloBm61LGu7MeZBoBpYiG8h6K8frV5HG7ZUB9ThW2FaRAbB7fHy8b5qfv/GLsobWrnxhElcMDeVpKjhXQm1rrmd1Oo1TFpxU1fZrN0vU3X5c5By6rCeWyQQTW1unl5dyM/+s502t5fcxHD+fM0iZqfHBLtq0k/N7W7+/NZu7n1vX1fZf50znVtPysPpsAWxZiJDrzNwuBcI7yzKAe7N/dbLDHEAsdcYYwOS+3h7BnAavlFBO4wxf+ksnwp8xrKsW40xTwGXAY8A9wBfsCxrlzFmKXA3cHrnPtOAMy3L8hyrTvprFhkBm4rruP7+T/ikoJqCqmZ+8MIWnl9/cNjPa7xuMnc84F9oeYnY89Kwn1skENtK6vnBi1tpc3sBKKhs5vsvbKGhtSPINZP+2l3e6Bc4APzm9Z3srWwa8nNZlkVrxzE/44gMp//lcOBwSHhn+VAzRyh/2bKsNsuyKoFyIKWzfJ9lWes7v18D5BpjIvH1RDxtjFkP/A1I63aspwMJHCCwReJEZJA2FNXh8fpnPL7v/X1csjCDxMjhG6IR7QrBY+89ZMDhHLlhUyJHU1jT3KtsdUENVY3tRGm4y5jS0Np7mLTba9HYdtTh0/22q6yBp1YX8tHeKs6bncpF89PJTogY0nOIBCC7n+UDYozJAzz4goOZPd5u6/a9h8Of63uWu/B1GNQemk/Rh4CjfPU8iIyAiBB7r7JYlxOnfZj/BO0OrGW3+5fZHNhnf2p4zysSoJTo3kP3pqVEEhOuwGGsyY4PJ7bH/1tmnIusuKFb/rm0roVbHlrFve/tY3NxPb98bSc/eGELjeqpkpF3oJ/l/WaMSQL+CvzJsqxea671h2VZ9cA+Y8wVncc2xpj5AzmWeh5kQmrt8LC6oIan1xQSHmLnskWZLMyOw27ro2ewrRH2fwjrH4OIRJh/NWQsBnOkXsTeFmXHkRQZSkXj4YcBXz9nOjGu4f+A5Mg9EW54EWvDk1iOUKrzLuUXK51M2rObc+ekkpcUOex1GDKWBUWrYcPj0FIDC6+F7OUQoqeOY9WstGhuOiGXBz4oACAy1MFPL5lL3AgmFRhPdpY18J9NJWwoquPCeWmcODWR5B5zqxpb3Xyyr5pn1hSSHB3GpQszmJ8VO+hzZ8WH88CNx/H9FzazsaieJbnxfO+iWST3ESAO1O7yRvZXt/iVvbmjgv1VzczO8M2TqWxo44M9lbyw/iCz0qO5cF4a01N7ZJir3A3bX/K17TPOhylnQkzmkNVzxLnboegTWPeI7/XCz0LmEnCMvr8jy7LYUFTHc2uLqGxs47LFWSydFE9E6Jj7SPod/Oc8gG8S8ncGeVxX57CiQ6laHwZ+M8hjHnIt8BdjzHc7j/8EsKG/BzGDDGRGRH5+vrV69bBmppIJ5p2d5dxw/6qu1w6b4cnPL2dxTlzvjbc+D09df/i1IxQ+9yqkL+zXOXeVNfDJvmqqm9tZOime+ZmxhDp790gMl/YOD79/cyd/fmtvV9mUpEgevWUpKTHDO3F7yBSvhfvPAU/74bKrH4MZFwSvTiMv8Ki1h9Halja2udld3kBdi5uc+HByExUMDkRRTTNX/u0jDta2dpXdfmoeXz9rOo5uvZwvbjjInY+v63od5rTxz9uPH7JJ6nUt7dQ1u4mPcA55pqWVe6u4+p6VfmXGwH/uOokZadF4vRZ/fns3v35tZ9f7iZEhPHP78eQeGtrUUAYPXwrlWw4fZN7VcOFvIaTnEPYxouB9eOhC3wMW8P1QbngJck8Mbr36sLm4jsv+8mHXPCeAu69dxPlz046y17AYcFt6yHBnWxqtxlyYJzJYHR4vf3/Xf1Kf22vx6pbS3sFDWwO8+yv/Mncb7Hu338HD1JQopqZEDaTKQ6Kgupm7397rV7a7opGd5Q1jJ3jY85Z/4ADw3m8h77Sxe9MXIkMdLMjqI3CXftle2uAXOADc914BV+VndwVk9S0d/OHNXX7btHZ4WVVQM2TBQ4wrhBjX8DzxnpocyeKcWNbsr+0quyo/i9xE39//wboW7n5rj98+lY3tbC+pPxw8VGz3DxwANj4Bx98FqbOHpd7Dbu3DhwMH8H2/5qFRGTx8tLfSL3AA+NObuzh5auKYS+vbGSiM+2ChJwUPMiF5++hxO2IvXF/lY6DHrqf+XN6oZXn7KPMAY+kiRIZJX01Vj0ILC29ff0ZjpCFIiAzlt1cu5L1dFawrrOXEKQksn5xAmLPz44x1hPb9KK+OXT4G9JUkp6/2chTo61fNa43pn/6EownTMuE47TZuPmmSX5ndZjhndmrvjUOj4KSv+ZfZQ2DSScNYw+GRk+Di0wsz/MomJUYwNXkMzXmYfBr0zB514lc150EEmJYaRUq0f/a2G4+fREa3CcsxrhC+dPoUv21CHTaOyx07PT/ZCeFcuyyHX10xn0sWZpISffj60mNd3H7KZL/t4yNCmNF9zkPiDEia4X/Q2Z+GeP/7wpiy6Ibe8/AW3RCcuhzDskkJhPRIFvKl06You9oYojkPMiG1drj5eF8Nj63cT3ionc8syWFRdqzfuOAubQ2+8aSrH4TIJFh0PWQe168J06NFcU0Lb+8o58WNB1mel8AF89KZMpaCB68XilfBmn9AcxXk3wQ5J0DoGLqGwRt3cx5k6OwobeD59cWsL6zlkgUZnDI9qVdGq4aWDj7aW8XjnxSSFhPKlflZLMgeO8HDsVQ0tPLuzkqeW1fMrPRoLl2Ywcy0nhOmd8GWf8G+d2DWp2DauRCbFZT6Dgl3OxSuhNUP+B7t538OspeN2gnT6wtreWJVIRUNbVyzJItleYlEho34YJixdxMfJRQ8iIiMLQoeREQGT8HDAGnYkoiIiIiIBEQTpkVERGTA6prbKappITzUTk58BLa+1suRIVHZ2MYHuyt5ccNBZqZFc+G8dKanBi+Lnww9Y0yjZVnDMhbXGPMDoNGyrF8da9ujUfAgMsHVNLXT4fEO6UJOIjIx7Cxr4JvPbGBDYR1hThvfPm8Gly/OGosLfo16Xq/Fox/v57ev+1LtvrGtnCdWFfLMF5aTk6CkETJyNGxJZIJq7XDz8sYSLv7z+5zzu3f581u7KK9vPfaOIiJAS7uHX72ygw2FdYBvvYjvv7CVzcV1Qa7Z+HSwtoW/vO2/hkVFQxvbSxqCVCPhBzHX8IOYAn4Q4+3895rhOI0x5m1jTH7n94nGmILO7280xjxrjHnFGLPLGPN/3fY51xiz1hizwRizotvhZnUeb68x5q6B1EfBg8gEte5ALXc8tpbC6hZqmjv45as7eWljSbCrJSJjRHVTOyt2lPcqP1DdHITajH8WR1h2SCskBIcvULgXyME3+ToHuHe4AoijWABcBcwFrjLGZBljkjrrdpllWfOBK7ptPwM4B1gCfN8Y0+8cuQoeRCaoj/ZW9Sp7ZOV+6lra+9haRMRfZJiDmX2Mt0+KCu1jaxmsjFgXnz85z68soecaFjKS/hcI71EW3lk+klZYllVnWVYrsBVfELMMeNeyrH0AlmVVd9v+Zcuy2izLqgTKgZT+nlCDEkUmqL5u8OmxYYQ67EGojYiMNTEuJ9+/eDY33P8Jze2+FY4/NT+dORkxQa7Z+GSzGa5bnkN2QgTPri1iTkYMly7MIDdR8x2CJLuf5YPh5vAD/54TFNu6fe/B99necORFu/vavl8UPIhMUMvzEkiJDqWs3teOOO2GO0+fSphTwYOIBOa43HheuvNE9lU2ERXmYFpqFLGu0bUwWWuHm4ZWN7HhITj7Wgh0DEmKCuPyxZlcvjgz2FUROIDvKX9f5UOtAFgMfAJcHsD2HwF/NsZMsixrnzEmvkfvw6AoeBCZoKYkR/H4rcvYVFxHS7uH2enRzE7XE0MR6Z+8pEjykkbnKu+bi+v4/Ru7WFdYwxkzUrj15ElMSVZqUxkS38E3r6D70KXmzvLBCDfGFHV7/RvgV8BTxpjrgDePdQDLsiqMMbcBzxpjbPiGJ501yHp10QrTIiJji1aYFglAUU0zl/z5AyobD8/jWpQdywM3HkdM+OjqHZGgGPyCJL7J0f+Lb6jSAeA7/KDusUEfd5RTz4OIiIiMO3srmvwCB4C1B2o5UN3MXAUPMhR8gcK4DxZ6GtuD/0RERET64ArpPX/LYTOa1yUySAoeREREZND2VzWxvrCW0rrRsdjktORIzp2d6lf2hVPyyNVqzCKDomFLclQt7R6qmtqICXMS5er3OiIiIjJKDFd77vFafLC7krseX0dtSwdJUaH86ZqFLJ2UMGTnGIiY8BB+ePEsLlmYzr7KZmakRrEgOxanQ89NRQZDwYMc0Y7Sen7xn+28s6uSeRkxfO+iWSzMjgt2tUREpJ+Gqz3fUdbAq5tL2VpSz+dOnMTaAzW8vaOCLz22jhe+dAJpMa4hqP3ApcS4ODfIdRAZbxR+S5+qm9q48/F1vLmjAo/XYl1hLTc88An7q5qCXTUREemH6qY27npi/ZC35wWVTXz23o/5zes7eWVzKb95fSczUqNIiQ6loqGtaw0ZERlfFDxInwqrW9hZ1uhXVt/ipqCqOUg1Ggc8HVCzH+oPBrsmIjKBFFW3sKO0wa+svsVNQeXggoctB+upaPQPEB775ADnz00jOsxBfIQyGomMRxq2JH2KCHXgtBs6PP7rgESFDcGvTNEa2PQUNJbD/M9AzvEQOjoXGBoytYXw4Z9gzX0QEgln/gjmXAqhWqxIRIZXeKiDELuNdo/XrzwqbHDzHjxeb68yt8cixG7jF5fPIzs+vI+9RGSsU8+D9Ck3IZxvnD3dr+yq/CymJg/yQ37JBnjwfPj4r7DlWXjsCtizYnDHHAs2PAGf/NXX+9BSAy/eCUVarEtEhl9uQjhfP3uaX9lV+VlMTRlcez4zLZrIUP8HSp87YRJXH5fJ2bNSj7CXiIx16nmQPjnsNq5dms38rFgOVDeTGh3G7IzoQT+pYt/74O6Rxu/dX8Hk08fvU/jmalj/SO/y/R/B5NNGvj4iMqF0teeZsRyoaSY1OpTZGTGDbs+npkTx+K1LeWTlfnaWNXLVcVmcMTOZpKiwIaq5iIxGCh7kiCLDnCzLS2BZ3lCm2+vdzY3XDZZveNTeika2dY7NnZkaRV7SOBjO5HRBwlSoKfAvj80KSnVEZHQqqWth68F6GlrdTE2JZGZqNDab6dcxmtrceLwW0T1SsUaGOVk2OYFlDG361LmZsfzs0zG4vV5CHFp8TWQiUPAgIyv3RLCHgKf9cNnJ34CwaLaW1HHtvR9T09wBQHxECI/espSZadFBquwQcbrglG/C/veho8VXljgNck4Ibr1EZNQ4WNPC7Y+uYUNRHeBbCfnBm5Zw4tTEgPZv6/Dw4Z4qfr9iFw2tbj5/Sh5nzUohLnz4Jy3bbIYQmwIHkYkiaMGDMcYOrAaKLcu6MFj1CBa3x0thTQteyyIzzkXoCDyx8XotCmuaafd4yYwNxxUShMY+bQHc+DKsfQgayiD/Jsg9CYDn1x3sChwAqpvaeXHDwREJHqqb2qloaCMm3EFq9DDkBM9aCresgPJt4HBB2jz1PIhMNO42qN1PSweU2lOIiXB1ZSTaWFzbFThEhTq4ZWE47tIttCbPJMzdAF4PxGaDs+8hQesKa/n60xv4/IIQ0sI6WLmzAKfNcOmizH5VsbC6mZYODxkxLiKGIkFGH9xN1RRWN+O1h5KZHD8i97/RqqG1g5K6VsJD7GTGaYK5jA3B7Hn4MrANGOOPlfuvsqGN+z/Yx73v7cXjtbj6uGzuOG0KGXHDt5BNfUs7T6wq4jev76C1w8t5c1L51rkzyEmMGLZz9skYyFri++phW0l9H2UNvcqG2saiWr7x9AZ2ljWSHBXKLy6bxynTkvo9XOCYUmb7vkRk4qktxHrn/zDrH8FlcxA1/ws8zLmcunA287NiqWnyPThJigzh4dOamfHxV6BlAVZjFqx50NdbO/dKOO27EJfd6/Cb9lfyzCmV5K38H2iu4ryU+Wzx/C/N7amEhxz7Vt/U5uaF9Qf56b+30djm5uSpiXz/4tlMHuKho5WFu7h/dSX3rq7B47W4anEad545g/TYiffBeVdZA995bjOrCqqJdjn4wUWzOX9uGmHOiRtMydgQlGxLxphM4ALg78E4f7B9uKeSu9/eQ4fHwmv58mK/trV0WM+5vrCO//33Nlo7fHMO/rO5lEc/OYDXax1jz5HT1xOySxamD+s5Kxp8i+EdWtOivKGNzz+8hj0VjcfYU0SkH7Y+j1n3D7C84Gknce0fOC9qL19+Yh3lDa1M68x89K2lTma8/QVoLIP0hZiP/+brsbAs2PgkbHq6z8OfnVRD3ltfhOYqAJxlG5iz5ruEdPR+KNOXzcV1fPu5TTS2uQF4d1clf1qxiza3ZwguvlN9CR/tLuXuj6u77n+Pry7hlY1FQ3eOMaK53c3//nsbqwqqAd+6G197akOfD9FERptgpWr9HfBf9Dl7dvxbsb28V9nz6w/S7hnCRrqHDYW1vcpe3HCQmub23hsHyUlTEvnG2dMID7ETHmLnv86dzolTAhvvO1CldS3s77HwXbvHy4FqLYYnIkOko9W3tk0PaeXvY7fZKKltZU5GDH++ZiF5jkroaIboDKja1ftYm56C1t49sinug77ApBtH6TocTWU0tnawYlsZdzy6lp++vJWNRbW99t/bx4Jx/9lSSlXjEN4jmqt4s7B38fMby2kfyiBlDKhsaOOtHRW9yvcNcuE+kZEw4sOWjDEXAuWWZa0xxpx6lO1uA24DyM7u3UU7ls3NiOH59f6rDC/MjiXEPnxdldkJvbuEZ6VFExE6eubMJ0aFcsdpU7h0YQYYQ3pMGMYM8dChHqJdTiJDHV1P2w5J0MqoMk6M57Z0zLCHQOZxvnVuuqmLmUHTng5iXE5CnXYumJdO24E8eAdfD0J0Ru9jpS/qc95DWGxK720jkiAshje2lfOVJ9d3FT/68QGeuf14ZnWbT5YYGdpr9+kpUb3WcRgUp4vZ8dU816N4YWYUTvvEWnYqItRBTkJ4r4dXCRG9/x9ERptg/LWeAFxsjCkAngBON8b0SoJvWdY9lmXlW5aVn5SUNNJ1HFanz0hmcre5BklRoVyZP7yTZxfnxLE4J7brdVSog7vOmDrqxlYaY8iICycj1jXsgQNATkIEP7lkDt1P9cVTJzM1ZZyuOSETznhuS8cMmw0W3+j7MN+pI34aH5mFfPOcGeR0e7gTmjoDTv0OtDf5ehKSZhw+Tng8LPsC2PtYnyFlNuTf3O2cdrjo99Q7Evn9Cv8ejOZ2D+v21/iVzcuM5rQZh+sX5rTxPxfM7JXydVDiJnH61FgmJxz+gJwUGcpVx2WPSHs/miREhvLTS+YQ0i1ounBeGrMzJtw0UBmDjGUFb8x7Z8/DN46VbSk/P99avXp8rcZ7sLaFHaUNeCyL6SlRZMUP/2Sx8oZWdpQ00NLhYUpy5PhYQ2EItLs97Cxr5EB1M8nRocxIiSJysIvhiQyfAX/KGo9t6ZhSXYCnbCutHhulrjxawlKYlhLZe32EtgZfZraGEl+GpcYK33o4yTMgPu/Ix2+phbKt0Fzh2y5pJrVtXj715w96PeH+8admc93yXL+yqsY2tpc20NjqZnJyBFOSh+EhSkcrB8vK2FHRisfmZHp6AllJMUN/njHAsix2ljWyt7KRWJeTGalRxKnnYSRNrIh1CCl4EBEZWxQ8TAAldS00tHaQHu0icpBP/59ZU8g3nt7Y9TrUYePZ249ndsbE/NAu0knBwwAFdcC7ZVlvA28Hsw4y8Wwrqef1raUU17Zw7uw0jsuNJ3KY8pmLiPRHW4eHV7eU8X+vbqeysY1PLcjgmiXZzM+KHfAxz56Vwl8/u5jHP9lPWoyLq5dkK3AQkQHTJyaZUHaXN3D1PSupa/HlVH9yVRG/uXI+n+7nQkoiIoE6UNXE5oP1tHR4mJ4Sxez06COO8V+zv4a7nljX9frJVYXYgJToUFJjBrYWULQrhHPnpHLO7JQJN7dARIaeggeZUDYW1XUFDof8+rWdnDItiYQ+so2IiAzGvopGbnjgEw5UtwAQYrfxyC1LWDIpoc/ttxzsnef/lS2lXHlc1oCDh0MUOAxcdVMba/bXsqGwlinJkSyZFE967PAt7Coymil4kAnF7ek9x6fd48UbxLk/IjJ+rdpf0xU4gK+9+d0bu7jvhlhcIb2z3cVF9J7fkBoThss5sVKZjiYdbi/3vrePv7y9p6vsxCkJ/P7qhXroJBOSWiOZEJrb3Xy8t4rYcCdhPW7Cd5w6maSo3nnTRUQGq6y+tVfZgepmWjr6XhRtcU4ck5MOp/K22wy3nZxHbrf03iOtqd3NpqI6VhVUU9HQ+3rGu4LqJu55d69f2fu7q9hV3hikGokEl3oeZEJ4cUMJ//3PjSRGhvDNc6bzyb5qyuvb+OyyHE6dodz3IjI88nPiepV9Zkk28UdYiHJSYiT3XLeY9YW1NLZ5mJQYwdyMaMKcwbldVzS08qvXdvLkKt/S0HmJ4fzls/lMT504a+G0u714vL17p9uOEACKjHfqeZBxr6immZ++vBWAysZ2fvzSNoprW/juBbO4bHGmVvQUkWGzICuWP1y9gNToMFxOO188dTKXLuxj5ehuJidHcdniLG44PpeTpyUFNff/ugO1XYEDwN7KZu55dw/t7onzwTknPpwTJvvPUUmKDGVystZKkolJPQ8SMMuy2FfZRHl9K1FhDuLbDxLdepCw6ETsydMpazHsrWgi1GFjclIkMeH9z01eVt/adYwpyZFDsrppm9tLfavbr2xzcT3lE7D7XURGlivEwcULMjh+ciLtHi+p0WHYbAOfuOz1WmwqrmNdYS2hDsOi7Pg+ewFaO9zsKW+itqWDzNgwGts91DS1kxUfTk6CbwhUh8fL3opGKhraSI1xkZcY0atuO0obeh17T0UjjW1u4nsubjdOtbm9nDEzhdSYMD7eV82M1CjOmZ1K9ARdTPRAdTOF1c3EuJxMTorAFaKPkhON/sfHo8YKKHgPdr0OqXNh6tmQOGXQh31rRzlffXI9Xz97OvlmO2lv3watdWAMOy5/k9termV/58TAc2en8v2LZ5HWj+wgO0obuO0fq7qOcd7cVL5/4WxSY/znI+wsa2DFtnL2VTZy1qwUluQmHDVQSY9xcc6sFF7dWtZVFuqw6amRiIyYxKih6T1Ys7+Ga/6+ko7O5A/RLgdP3racmWnRXds0tHRw7/t7+eObu8nPiWNWejT/+Gg/lgVRoQ7uvT6fxblxPLu2mP95bhNur0Wow8Yfrl7AOXPS/M7XPTDJindx3bJc9lU28ue3dnPenDQWZsdhH0QwNBbsqWjiRy9tJS8xgsU5cRRUNvHNZzYyPTWKeZmxwa7eiFpdUM3ND63uylp4x6mT+fwpeUS7+h6GJ+OThi2NNx43fPI3eOYm2PAYvPptePxqqCse1GGLa1r42lMbOGNmCs015cxY+S1f4AC4k+bywPqmrg/94EstuGpfdcDH7/B4uf/9vX7H+M+mUlYX+B+joKqJz973Mb94ZTtPrS7i1n+s4V/rj35trhA73zp/BtcsySYq1MGCrBgevnkJ01ImzphdERn7Otxe/vbunq7AAaC+xc3bOyr8tttW2sAfVuzGsuDkaUk89KEvcABoaHPzzX9uYHd5I9/pDBzA93T9609vpKCqye9YC7NjuTI/C4Ablufyi1e28/gnhdz3fgFX3bOSdQdqhvGKR4dDGW73Vjbx/PqDbCiqC26FgqSmuZ3/+ddmv3Tnf357D1tLevdOyfim4GG8qS2AD37vX1a1C8q3DuqwVU1t1DZ3kB7rIsXZhK12X9d7TUkL+LDY3WufrSW985UfSWObmw/2VPUq39bjGFsO1lNe3+ZX9uvXd1BS18LRTEqM5Iefms3rXzuFh29eesQc6yIy/pXXt3Kgunnkx+13tELJRl+vcPk28Pbv/G7LorSP7E09MyCVdmsP29zeXtsXVrdQ3djWaxJwY5ubqsZ2v7KkqDC+d9EsXvvqSWwurvfbx+O1eHJ1IUfT2uHmoz2V/P6NnTy6cj97xmCGoslJkeTn+k98P2tmMnlBzIAVDHXNHX0OYyut0xDgiUbDlsYbrxe8vT/I4+noXdYPSVGhJEWGcqCqGVd0BO7EmTgqtwEQWfoxZ2RfyQM9Ohr6050bHebk9OnJ/GPlfr/yuZkxfq/dnt43wg63hbePTBg9Oe22XkOgRGTiaOvwsGJ7OT94YQtVTe1cujCDO0+f0jUHYFh1tMKaB3y9wZYFdidcdj/MujjgQ7icdm48fhLfeHqDX/kZM1P8XuclR3Lq9CRW7q0irI95CZOTIkiKCiXEbqO9W5sa7XKQ3MfwqshQB9NSovsMtprbjh4Avbm9gi8+urbrdWpMKI/fupxJY+iDd3xECL++Yj5vbCvnw92VnDo9idNmJBM5weY8xEWEMD8zplfPS0acFsubaNTzMN7E5cDC6/3LIpIgeeagDpsW4+IPn1nAh3sqiYxLYttxP4WoVADstXu5dn408zMPj7n9zJKsXk9qjsZuM1x/fC5zMw4f45ol2SzukeZwZlo0kaH+Me/nT8nr19wKEZmYthys54uPrqW8wffU/Zk1Rfzt3b109PFQYshV7jgcOIDvgc7zd0B1Qb8Oc/qMJH5yyWwy41xMTYnkL59dxKLsWMCXUvS9XRX87N/bqWlq545Tp3Cwtpk7Tp1MiN13u0+KCuWXV8xncnIUv71qPuGdC9VFhzn449ULyYoPP+K5r16a3btsSdYRt69uauPn/9nuV1Za18amMTjsJychgptPnMR9Nx7HdctzyYw78s9pvIpxOfnJJXNI63wI57AZvn3+DL/5NjIxGGsMrKybn59vrV69OtjVGDvqimDbi7DxScjIh8U3QuqcITl0UU0z5fWtRIQ6iO6oILq1lLCYBOwJU6hp9bK/qokQh53cxHDCB5CBoaapnYKqJkIddiYlhveZxWFjUS0Pr9zPztIGrl6SxRkzUkiOVo+CTBgDnp060dvSJz85wH8/u8mvzOW0s+Lrp5AeO8wPIHa9Do9e3rv8lhWQmd/vw1U3tWG3GWK6TVRdta+KK+9ZSffb+q+umMeJUxNoaPFQ19JBRpyr62GLZVkUVDVR1dhOSnSYX+DQ3O5m3YFa3t5RTkp0GCdNSyInPpyP91bx9/f2gYFbTprE0kkJhDn7zrpUVt/Kub97l5pm/57vX1w2l6uO6x2IyNhQVtdKYY0v21JuYgRO+5h9Dj2+Z/oPIw1bGo9iMmHZ7bD4JnCEHp7tNQQy48K7PXGJBiZ3vRcXAXEuh28itX1gQWlcRAhxR1g86ZB5mbH84tMxuL1eLKC1feLkGxeRgYvtIytbVryLiJARSDkak+kbqtR9CGlEEkT5shtVNrax9WA9VU1t5CZEMCstmtAjfCgHiO9j7Yc3tpXT83ngIyv3c+G8dFKjex/LGMOkxEgmJfY+/lvby7njsXWHz/f2Hp76/DJOmZ7M8ZN9OzgdR//QmBwVyudOnMSvX9vZVea0G2bpSfWYlhITRoqGAE9oCh7GM+cQ/HF7PVC5CxpKfDe5xKlgO8INrXI3rL4fdvwbspfD8V+ClNmDr0MfbDbD1qJ67n57DzvKGrh8USafXpRBxgTsShaRwMzNjGVRdixrD9QCvmEX/++CWcSEDzzNZEltCwVVTYSHOJicFHHkcfCJ03xzHJ6/A9rqITIZLn8AYjKoaWrjhy9u5cUNB7s2/91VC7jkGIvJ9ZQR6yI5KpTyhsNJJSLDnPQ3k2ptczu/fHWHX1l1UzvrC2uZkhx1zKDhEGMMV+Zn4nLaeXjlfjJiXdx1xlRmp8cce2cRGbUUPMiReT2w5Tn41+3gaQd7CFzyF5j9abD1uHm01PpuioUrfa9r9sG+d+Hm1yCmfzfAQOwqa+Cav39Mc2evw69f30lpfSs/uGh2wDc2EZlY0mNd/PnaRWw9WE9DawdTkqMGNV5768E6Pvfg6q4MSFfmZ/LNc6aTFNXHgxub3Tc5OnUeNFf6HsZ0to3bSxv8AgeA77+whfzcuGOOrXd7vLR2eFhfWMvW0nrOnJlCVryLv76zl/rWDr5wymRC+rmYm9tjdbWt3fWVuelYUqJd3HJSHlcsziTEYcc1Er08fbAsiw6vlxD7xFjYTmQ4KXiQI6vaA89/0Rc4gO/f5+/w3fySpvlvW733cOBwSH2RL03sMAQPO8sae93cnlhVyG0n541M5hQRGZPSYlxDkmChtcPN717f5Zc69anVRZw9O5UzZ4bR5vawr7KJlnYP2fHhJER2DjOKz/V9dVPb0jsbXl1LR58f4A9pbnezck8VD68s4JIFmXywp4o9FY2s2V9DRIidn182l9RoF/OzYvt9bYlRodx2ch4/eXlbV5nTbpiXMfAeg8H07gzWluI6Hv34ANtK6rk8P5MzZ6aQonlyIgOm4EGOrLEM3P5rKuBuhaay3sGDvXNuRc8Bt46hWVW1p9A+ehfCnXYcPXtEBqmxtYN1B2pZvb+ajLhwlk6KV3AiItS1uPm4oPdCmPurmqhuauOv7+zl7+/txWvBzLQofn/1wiMuTJmXGNErbepxufFdWW36snJvFbf8YzU/v2wuK7aX8dHeamanRfM/F8zk16/toLKxnYvmD/zBzSULM4gIdfCPjwpIj3XxhZMnD3q4UVOrm6qmNmJczhELJvaUN/KZv6+kvsWXwnxdYS3FNS18/ezp435lbJHhouBBjiw6DZzh0NF8uCwkomuCn5+EybDk8/DxXw+XTT0HEmcMS9VmpUczNTmSXd0WHPrmudOHPN/0v9Yf5Lv/2tz1enpKJA/cuIT0QZyntcNNYXULGMiJD+/3kAIRCb7YcCcnT03kxY0lfuV5iZGsL6zjnnf3dpVtK2ngL2/t5heXz+vz731qchT33ZjP/zy3icTIMI6fHM8lCzOIOsL8CbfHy4MfFHDhvHT+8dF+Nhf7FtN8u6GCLSX1XLs0h/YBDDHqLjEylM8syebi+ek47IbQQbZT20rq+dFLW/hoTzXTU6P4yafmcNyk+EEdMxDbS+u7AodD7nt/H59Zkk20y8HKPdU8v76Y3MQILpyXzqx0TeYWORYFD3Jk8ZPhsr/Dc5+HtgYIjaLxgrt5dV8oGXVVzM2IIeLQmgvOMDjp65B7EhSvhpQ5vknT4YGv9dAf6bEu/n5DPh/vrWZ/dTNLcuO7cp0PleKaFv7vFf8c5TvKGtlWWj/g4KG4poXfvrGTf64twmYM1y3N4fbTJqsLXWQMKKxupri2hfiIECYlRvCl06eyvayBXWWNGAO3nDiJ+VkxPLOmqNe+7+yqpLa5g+Q+sh7ZbIYTpyTyy8vnc/8H+3hzewXpsS5iXM4+508Y4/swn5sYzgs95kpUNLQREWpnad7QfDCPCB38x4SqxjbufHwtu8ubANhR2sBND67ixTtPHPbF4ux99EY7bAaHDV7eWMJ3njv8cOiRj/fzzy8cz9Qj9BCJiI+ChwmsoqGVhlY3yVGhfWcIMQZmXAC3vUtbXQkflDr47xcbqGjYCMD/XjqHa5bmHN4+MhlmXuj7GgE5CRHDOoTI7fXS1MeY45aOgaeGfW1radcHC49l8eBHBczLiuHTizIHfEwRGX4r91Rx2yOrqW9x47QbvnfRLK5YnMUTty5jf1UzrhA7kxIjCHPaye2jXcrPiSPadeRb7taSeq6//5OuScnfeW4z9a1uvnDK5F7b2m2Gm07IZeW+KmwGvD1Giy7IimVeRuygrncoFde2dAUOhzS2udlf1TTswcPMtChSY0IprTs8BPeuM6Zit9n47Ru7/Latb3Gz5WCdggeRY1DwMAF5vRbv7a7kt69t54xZqUSHOciOD6e6qZ24iBAWJduIrdvhm/AcmwOpc/ikOorPvfAJ1y7NJjkqFLvNEB8Rwr/WFeFyOpiZHk12twWGPF6L7SX17CpvJCrMwZyMGFKiwyiuaWbrwXpaOrxMT41keuro7SJOj3Fx1XFZPPbxga6y8BA70wd4Y/F4LV7cUNKr/I2tZQoeREax8vpWvvXsRq5fnoujc5x8aV0bu8obmJsRe3gyNFDX3EGIw8YPLppFtMtJW4eXN7aV8pUzpxLmPErwcLC+Vzajv72zh/mZMb52JzXatxhbRwuUbmJZ417mZSaSd2EWX3mxkMTIEK5fnkuYw0a728veikaKq+uprm9kcjTMiPMSkjyt71TbtYVQstE3py1lFiTPHJofXKfIUAehDluv64t2HX5oVdvczpaD9ZTXt5KdEM7MtGg8HoutJfUU17aQEetidnr0kVPhHkFOQgQPf24pK7aVs6OsgXNmp7J0UjwdXi/enlEX4BnBdXOrGtvY0rm2x6SECGakRrG3soldZY1EhjmYlRZN2lEWL9xf1cS2kno8XosZqdFMTo4cucrLhKbgYQLaVd7IFx9Zw9fPns5v39jBl8+Yxq3/WIPba7E8O5y/ZL0Ja/5weIczf4hJvpLrl+ewuqCGrSX1fPeCmXzj6Y00tvnGkmbGhvHg55YwJdn3wfqjPZXc+MAq3J2Nc35OHD++ZDZffmI9O8t88xRCHTYevWUp+bnDP+51IJwOG188dTLJUaH8c20RU5Mj+dJpUwf8VMpuMyyZFMfaAzV+5Quyh2dol4gMjcrGNq7Mz+Lv7++jusmXfS4hIoRlPcbsN7W5+eNbu3wrMHe69aQ8zpmdeswHJSF9JIFwOe1UNLTxyb5qTpqayDmzU2Hj0/DindiASODihdcx5db/4kCzk68+ub7rA/rkpAhOn5HCve/txRi4+9wYzmv5ACad7H+Sqj3w6JVQvdv32hkO178AWcf174d0FLkJEXz7vBn84MWtXWXXLs1mapLvw25jq5vfvbGLBz8s6Hr/+xfNwmtZ/PilwxmfvnbWND5/ct5RF8/ry9SUqD7b7TtPn+JXp4gQO3NGaM5DTVM7P3pxK893Djtz2g1//MxC7np8fdfE+XmZMdx97aI+0/XuLGvguvs+pqze16MS7XLw2C1LmTOKepxk/FJC/Alof1UTp0xP4slVhZw+I4XHPj7Q9SH/5hkdxHYPHADe/DHzwypJjAxla0k9s9OjWVVQ3RU4ABTVtvLOzgoA6prb+dFLW7uOCbB6fw2bi+q7Agfw5Qz//YpdtAznCtGNFVC2FRrLB7R7Zlw4XzlzGi/ccSJ/uXYxi3IG90H/04syyew2X2JaSiRnzkwe1DFFZHglRYVRUNXUFTgAVDW1897uSr/t9lQ0+gUOAA9+uI+i2hYKKv2H7fQ0Jz2axEj/DERXLclm88E6Xttayq7yRhpLdsOr3/LbxrbuYSaHNfDox/v9nuzvqWgi1GkjxG7DsuB777VStnczNPfIEFXw3uHAAXwJMt77de9Me4NgsxmuyM/i6c8v5zdXzueRm5fyjbOnE9XZ87CrvMEvcAD4+X+2U9XY7lf2uzd2sreykaFy8YJ0/nD1Ao6fnMC1S7N5/LZlI9Ybvr20vitwADh9RjJ/fHO3X8atjUV1bCys63P/17eWdQUO4Bty9djHhVg9Mx6KDAP1PExAMeFOUqPDeHdnJadOT+KV2tKu9yK8fTTMXjdRNBMZ6ntykxIdRlFNS6/N9lT4bo5N7R4OVDf3er+vXOZ7K5pobncHvHBQW4eH+lY3ceFOHPZjxL4HPoZ/fcG3BkVsLlzyZ8g9MaDz9BQXMTRpBaelRPHU55d3TbCclhpJavTQZogSkaGVFBVKSW1rr/Lu2d7AtzZDTx0eC8uChtbe73WXnRDBnadP5UB1M9VN7UxPieKNbWXER4QQHxFKm9uLt60R2nsHIc3tbvZV9C6va+7AFWKnvcVLRWMbTSYM2pshvFuPSe2BXvtRucM3PGoIU21HhDo4blJ8nxmW6vv4ubW5vb1SqXotemVOGoz4iFAuXpDBRfPTMWZk07b2/F1JiQ5j5d7eqX8rm/oO4naX975Xbyup10J4MiLU8zABTU+JIiLEzukzkvlgTyWnzzj85HtXeyK4ejxdj86A2BzmZvpyfK89UMMJUxJ7Hff06b7jJEWF8umFvcfwT07uPTHuivxM4gP8YL65uI67Hl/HBX94jx++uIU9FUd5AlVbCE9e4wscAGoL4IlroHrfkfcZIemxLk6ZnsTJ05IUOIiMEZcu6r1mwiUL0v1eZ8eHEx3m/0wuM86F2+Ml4xgrRTvtNkIdNp5ZU8Sqgmp+/sp2Vu+vYXZGDDXN7USE2HHE5/gW6fTb0UV8VCSXL+7d5qbGhHV9SD0tL5JUZytEpvhvlHNC78osvA5csUet71DKToggoscDpEkJ4b0CrqSoUL+5dUNlpAMHgNzECJz2w+f9cE8VZ8/q3Qs94wg9IWfPTulVdkV+pgIHGREKHiag2PAQPndiHp9dls3kpEimJEdy1sxkbAbu3+qh5pJHsVLn+jbOyIerHoXoNOZmxPCHqxfgsBnqmtu5blkOoQ4bUaEOvn/RLI7rnLvgtNu47eQ8Ll2Yjs34Gvw/X7OQxdlx/OKyecSGO3HYDDcdn8Mtsw1m+79h+7+hZv8R61xY3cwN93/Cq1vLKG9o4+GVB/jOs5to6OOJFQB1hdDkP6SA1rq+n7KJiBzDydOS+NpZ03A57bicdr55znRO7PEQJSchgvtvPI7pKb6x/PMyY7jrjKlcND+dpKhjP8U/fUYyNyzP8aVbDbFz84mTqGps45tnT+f0mSmExyTCpX+FSaf4dkiYCtc8jUmczJX5WVy3LBuHzRAX7uRHF89mY1EtxsBZU6L47nGG8FnngKPHhOPM4+DC3/keGtmdsPR2mHvFUPzIAjYpMYIHbjqOaZ0/tyW58fz52kVcujCDuRm+D8/zM2P4+/WLjzqBeCyZlhzFAzceR3a873oyYl1ctzyXK/MzsdsMiZEh/O6qBczL7Dt4WJ6XwP+cP7NrMvqXTp/CGTN7BxQiw8GMhfFx+fn51urVq4NdjXGpze2htK61KxOGy2knOToMmmugpQbCE8Dlv6poWX0rrR0ekqNCqWxqx24M6X006IeO3XXMTiV1LXR4LDLb92F7+FPQ5JsrQXQGfPZZSO69sNzbO8q58YFVvcpfvuvEvlc9Ld8GfzsJPN2CC2ODz78HqXMC/OmIjEoDfkyqtnRwLMuiuNY3ZDMj1nXEJ9a1ze2UN7ThtBkSo0KPuNhbX7xei4O1LZ3ZgLwYYyM1JozwkG49Gm0NvvlcYTEQkdBV3OHxUlLXSojdt09lQxtNTQ0kh7Tjik44+jCkumLwdkB0JtiDM6K5pqmd+pYOEiJDurIq1bW0U9vUQWyEkxjXyKxKPZKqGttobHWTGB1KRIiDdreHkrpWwpz2gNb/Ka5twfJapMe6sGnF7P7SD2yANOdhvPF6fU/dLS/EZB3zJhDqsPe9VkJ43BEXeOveoGWFHPn4Rzp2WkxnoPHaE4cDB4D6Ytj2Qp/Bg6uP7BoOmyHkSPMeEqbA2T+F//zX4bIzvu97UiciMgDGmD4z3/QUGx5CbPjAPujabIbMYw3NCY3yffXgtNv8hvUkRoWSGECPBwAxvYdljbS4iJBe88tiXCHjMmg4JCEy1C/Vb8iR7slHkDFOemJkbFHwMJ40VcKaB+G9X4HXA0u/AMu+CNFpwa5Zb5aFVby2V9jvPbi+z7F0U1OiOG1GEm9tPxxs3HHaFHKPtMCQ3QmLroeMxVBX5OvVSJ4FzqGbACgi41tJXQvl9W3ER4SQNcRj7S3LYt2BWp5afYCy+jauWZrN8ryEfq9jICIy0hQ8jCcF78ObPz78+sM/QHwe5N8UvDodiTG0zLyc8P3v+xXXTbqAvvo74iNC+N9L57L2QC0FFY3MSo9hQXYszqNlXHK6IDPf9yUi0g8f7ankrsfXU9HYRozLya+vmM/pM5KHbGjI5uI6PnPvyq70qm/tqOCPV87hokU5Q3J8EZHhognT48n2l3uXrX/Uf9z/KPKRbRHVC77g6yVwhFK56C4eq5h0xJSGaTEuLpibxh2nT+W0GcnEDXBYgIjI0RTXtPDFR9dS0ehLk1nX0sEdj61l3zHWauiPlbvLe624/Kd3Cmho6p0GW0RkNFHPw3iSMhs2+b5ty1hGQ+IiYuKTcdpG539ziTeWX+07lxuXnIfXMty/xcv0tDDCHEo1JyLBU1rfSk2z/0OMNreX4toWJidHDsk5jLf3QxKDRVVlCR6TOeA5EyIiw210fqqcgPZXNbGqoJrC6hYW58SyMCuua/XNgE0/D9Y+xLaF3+MvexNYubWdU6fGc2t5I1NTek+uC7YTpiTywPv7+O+3fE/zIkMd/PqqPJwOdYiJSPDEhztxOe20dHi6yg6lnR4qy7LCurLcHXLnQicfbj+IKbPzmSUaviQio5NStY4CJbUtfO7B1Wwrre8q+9GnZnP98tx+H6u0rJTL7t9Ccd3h1VBnpkXxyM1L/TI6jBbFNS1sK6mn3eNlekrUkD3VExnHlKp1mFmWxQsbDvK1pzbg8VoYAz+4aDafWZJFyBD1jFp1B9mwfSfP7bNT0Wrj8kntTHVW8Jn3EgDDC186gfiI0dFml9a3UNXYTlJkqF/a7WHRUAZlm33paBOnQfJMCMIibjIh6BdrgNTzMApsK6n3CxwAfvnKDs6YkXzMVUlpLPetouwIg4Sp7Gt0cLC+lfTOlUWb2j1sK2lgf3XzqAweMuJcZMQp1ZyIjB7GGM6fm8b01CgO1raQEh3GlKTIIQscAExMOgumtjHFuZaOuhKKrVR+sS2JoppmchPCsY2SD8zv76rga09toLyhjfSYMH5z1QKW5SUce8eBqD8Iz90O+972vXaE+tb+yT1xeM4nIgOi4GEUaO3w9ipr7vDQ7rFo6/CwrrCWd3ZWEBfu5KSpScxM61xxsnwbPHUDVO7wvV58E+Hzvss3zp7O3opGEiJDCXHY+Ns7ewY2j6ByF+x6Dar2QMYiSJoBafN9E5xFRqHimhY+2VfFpuJ6FuXEclxufEALLcnE5vFabC6uZUdpAxuL6shLiuTU6UnMSI1mRurhFX6La5r5aHc5W4trWJxsWBLXRFJqJsQNbIhRISm82rSQx9YksK+qCctqBuArZ05jd1kjb+4oJ8bl5OSpScxM73ul4eFUUNnE5x9eQ1O7b/jWwbpWbn9kDS/eeWJA613028F1hwMHAHcbvPoduP7FXouVikjwKHgYBaalRhIeYqe5/fD42ssXZZARG8YHu6u46cHDKytHh+3mqS8sZ0aiCz74w+HAAWDHv9kUfwe/fHVnV1FmnIuff3oeeUn9bOir98HDn4a6A77Xq++Dk79Jh7sDZ+7yAV3nsZTW+3Kqx4UPfU51Gf/qmtv53gubWbGtHID7P4Cr8rP4wcWzcYVoEr4c2ebiWl7dUsbdb+/pKnvwQxeP3rKsqy2qamzjm89s5MM9VQDcD9y4IJpv7/wdoWd8GyKT+33eXeUN/GHFLm4/dTKF1S3UNLczPzOWtNhQLv/bR13b/elNX7vf9eBohBTXtnQFDofUNHdwsLZleIKHpsreZZW7oL1RwYPIKKKZqaPAlOQoHr1lKafPSCIzzsVdp0/hS6dPpcNj8bs3dvptW9/q5uO91dBaA3vf9HuvZNbN/PKNfX5lRTUthDlthDn7GSeWbjocOByy+j5sJetpb2/r37ECsGpfNRf/8QMu/tMHXPCH93h1cwke7+ifjyOjx+6Kpq7A4ZAnVxeyt7IxSDWSsWLLwXoeWbnfr+xAtW8+1iG7yxu7AodD/rGhnn2RC6Fi+4DO67TbqG9184tXdrBiexm7yhv5zRs72FzsP4y1oc3NR3urjnCU4ZMQEYK9x7oWoQ4b8RHDlAkqcWrvsjmfhoj+B2YiMnwUPIwSC7PjuPvaxbzwpRP56lnTyIoPx+310tDq7rVtc7sbwmJh0ql+5R5HOK0dnl7bewcyKd7T3rusvRksLxUNQ5uHvKSuhS8+tpbyBl9QUt/q5kuPr2NvhT70SeA63L2H/wG4PX2XiwB4vRZuj9Xn8NH2br877X38HnktcOMAdx/tZQCmp0Qxu3M4Ull9G7vLG7n5xDxW7ukdKDS19b4XDLe8pAj+5/yZXa8PTRyflDhMiS3SFsAlfwFX51KhMy6CE74KDg2VFRlNNGxpFAlz2glzHh5eEeMK4baT8/jWs5u6ymwGlk5KAEcInPBlKPrEN2EaSLPVccPybO55r6Br+/AQO9NSBtDVnTwLnOHQ0Xy4bN5VFNsy6fAM7RCQsvo2Khr8ezM6PBZFNS2jMsWsjE55SRHkJUawt9tCXouyY8lNiAhirWS0s9kMk5MiuXhBOs+sKeoqjwixM71b+zMlKZKM2DCKaw9nsjshJ4Kc+hWQ9NUBnTs5Ooy7r13E+7sq2VpSzwlTEpmdHs3KvVW83q0XzWbg+MnDNEn5KEIcdj6zNIv83DhK61pJj3UxNTmyV2/E0J0wHBZcA7kngbsVojMhRAk1REYbBQ+j3DmzU7HbDPd/sI+EiFC+eNpk5mV2jv1MmQU3/Qeq94DDhT1xKje1OkiKDuPJVUVMTYrktlPymJ46gA/gKbNov/Y5HB/+HlvNXqxp51KTsowPajP59BDPR4gLdxIV6qCh25M1YyB5CHOqy/iXHB3GX69bzCMf7eeDPZWcMTOZq4/LJkaLbUlP7jZoKPU9IIlMYn52LF4sEiJCWLG9nMmJEXz+lDy/hxdpsS7uv3EJD32wh48LajknL4Qrc1qISv8cxGYNuCo5CRHkJERQUNnI397Zyw9f3ML1y3P42aVz+cfKAqalRHLdslxSgzTx3+V0MC8zlnmZI3jSQfw8RWT4aZ2HMaKpzY3DZgh1BvbUv6G1g1CHbdCpBVsObsNeux9TvYfm8AysnOXEJqQM6ph9+femEu56fB3uzpzq3zl/Jtcty/HriREJhMdr0dzmJiLUgW24npAGl9Z5GIyqPfD2z2DzPyEmC87/JUw+A+wOmtvdtHV4iAx1HnGxSrfHS0u7m0jTinGGg33wz+Cqm9q49u8fs62koatsanIEf/nsYl7ZXMbdb+/GbgxfPnMqly3KJG645hyITCzj8gYxEtTzMEZEhPbvvyoqbAjGiFbuwvXIBdDsG38bA3DeLyDhC4M/dg9nz0rh5btOorimmaSoUKamRClwkAGx20z/V2eXiaGjFd78MWx5zve6dj88fjXc8iZkLCQ8xEF4yNHbWofdRpQrBAjsA3y720NNcwdRYUc+9v6qZr/AAaC4tpWP91bzq9cOZ9T7ycvbSIsJ44J56Uc9p9drUdnYRpjTTrT+FkRkiCl4GAcqGlpZXVDDqoIaZmdEs2xS/LEXlzuCHaX1vL+7ksrGdu5M3kh4c4+Je2//HGZ+CqLThqDmhznsNqanRg1siJWISCAaSmDrv/zLQiKgpXpYTre7vJG/vrOH17eWMS8jhm+cM535WbG9tgtz2jEGug8EmJsRwwsbDvba9uWNJUcNHoprmnn04wM8saqQ9JgwvnXeDJZPThy+eQoiMuEoeBjj2twe7n57Dw98UNBVdsLkBP54zaIjptOrbmrj/V1VPLOmkGkpUVy6KIPZ6THsKmvg6ntWUtPcAcDlZzczuefOXjeg7DUiMgaFREBUmm8lY4BF10N4AnzwOyj82JcWNGnGkJyqrqWDb/1zI6v31wDw3u5KNhTX8uIdJ5KT6D+Jf1JiODcuz+WBDwu6yuZmxNDu8fLxPv/AZmrKkTMdebwWD35YwL3v+VJ2Vze1c8MDq3jui8czLzP26BWuLYSmCt96FTEjOcFBRMYaBQ9jXEFlEw91u+EAfLCnit1lDSzJ6zs7xzNrivnff28D4N1dlTy1ppBnbz+etQdqugIHgG1WDpNDo6GtW87xk74B0RlDfh0iIsMuMhnO/xU8eS1kLIb2Jlj7D997+96FjU/BjS9DzODbuKKa5q7A4ZD6Fjd7K5t6BQ9hTgd3nDaFE6Yksq2knqkpkSzKjqOisY1/rS+mvsWXTCIhIoTz5h6517esvpVHVvqvz+PxWuwsazh68LB7BTx7q2+IakQiXHovTDm9fxcsIhOGgocxrsNj0ddaan3lJAcoqW3hjyt2+ZXVt7jZVtJAS4885995r53Us//BouoXsVVs9z2lm3zGkNVdRGTETTnLN8ehqRIev8r/vZp9UL5tSIIHl9NOiN3Wqy0OD+17LldiVChnzkrhzFmHE1IkR4fx3O0nsLWkHpsxzEqPZlLikVMPhzlsJESGUFTjvxZPxNHmcVTthaeu963iDL6fy9M3wOffhfhJx7hKEZmIFDyMcTkJ4Zw4JZH3d1d2laXHhjE56Qhd28aXBrUvC7JicNgM7s5opL7VzWZrGvkX/ga8HrBpArOIjHGOEMhYBBU7+n5/AFMDDta2sLm4joZWN1OTI5mVHk12fDhfOXMq//fq4fOcNSuZacn9W2BtcnIkkwPcJz4ylP93wSw+/8iarrKpyZHMyYg58k71xYcDh0Pa6n3lCh5EpA8KHsa4qDAnP75kDs+sLuSVLaUsmRTPDctzSYvte2GdtBgXd50xlZ+8vK2rLMblZFZaNLmJETxyy1L+8vZuSuvauPGEXM6a2fkUTIGDiIwncbmw+CZYfV+3sjxImnnEXfpysLaF2x9Zw4aiOsC3oNv9Nx7HqdOT+eyybPJz4ympayHcaWdeVgxxEcO7fs2p05P45xeWs/lgPfERIczPiiXraGvzRCSC3Qmew0NWsYdARNKw1vNoSupa2FvRhNNuY0py5BHn74lIcGidh9HC0w5eL1gevLYwWjyWf3pWdztYXnB2WyjIsnxjdkMisBrKaGhpIdwViSMkDML6yFrk7gDLTW27Yc/BSp5cX0V8ZAgXz09nVvrhJ1Ptbg8dHi8RoU5aOzzYDINeL2K8aG53E+qwK3OJBNP4XuehoxWMzddD0IeA/ga9Ht8KxSHHWF28/iDsfgO2Pg9Zy2DWp2iNnexr83DT3GFhcziwedoJcTio7zA4bQZXZ9vc1uFh7YEarrvvk641ar62NIozEyqYGufAEZMOjeXQ1oAVkUhLaj6ERh41HWy724NlEfCaPod+HpWNbVQ2tpEUFUpyVD8WlPN0wJbnad7yEmGVW7BV74aL/gDzP+O3hsWB6iY2FNbyn02lnDQ1ieOnJJAzDKu37yit55aHVlPYOfTqpKmJ/PzTc/vMIOj2eOnwWricdprb3YTYbTjsfa/PIdIH3cgHaMR7HowxWcA/gFR8aXvusSzr9yNdj1HD3Q77P/Rl+2hvpG3hTTxbN4OHNjZx3pxULpmfRk7dJ/DBH3w3w+O/BHmnQn0JrHsYDq6DBZ/FrPsH0dPPgx3/8WVEWnyTb35CVLIvKClcCR/8ERpLiJ1zOYtrClicEAfzr4YE/y7tEIedlg4PL24o5r739xEbHsJtJ+Vx3KR4nBO0YT5Y28K/N5Xw7NpiZqdHc8PxuUcfCiAi/dNS65u4u/JucMXBCXdB9nLfU3EO/w3+c20Rc9Jjjvw3WLoZVt0HRZ/AnMtgzmUc8CZSUt9KQkQokxIjugIPb2QaVVOvJHzWNXgtL2/vrGTlW2v47BwXb+5rprjRy1fyDpK48V48NifVs27hHwezOGteNvWtHfz9vX3YbYb/OncGz60r4qopXq4p+B9C1m/01SU0Cs7/NXzyN3Yc/2v+8epe1hU3cv7cNC5ZkOHXI9Da4WHl3irueXcvHR4vt56UxwlTEo+4xk9xTTMvbijh+Q3FzEmPYXZ6NL94ZQex4U5+e+UClk3uO2FGT/tr2nm2bB6vliVzfG40V1+cxLSMpK7Aoba5nde3lvGPj/YTG+7k1OlJ/Omt3byxrYyrj8tiUW4cCUPUm+LxWjy8cn9X4ADw3q5KVu6t4rLF/sHDugM13PveXvZXNXPx/HSqGtupbGzjphNymXuszFIiMigj3vNgjEkD0izLWmuMiQLWAJdYlrX1SPuMiadlA1XwATx0gV+C792n3c0Fr8fT5vZy5vQEfu/4IxF7Xjq8zw0vwyv/DWWbfdmPVv4ZTv0OvP7//I996d98wUHxWrjvrM40q51O+jqsvh9S5sJVj4DL/yb8r3XFfOXJ9V2vbQae+vxy8nPjh/Lqx4R2t4cfv7SVh7tlMYlxOfnXHSccdfKiyDAZnz0PG5/yZfw5xNjgplcgeykdbi8/emlLr7/B5754PHnd53fV7Pe1dY1lXUXuWZdxV/PN/Ht7LaEOGz+9dC4Xz0+nvKGVRz8+wJOrCsmIDeP2U6fw8/9s496znPxhPby6q4GXz21i+pu3+FVz85kP8557Fr94xX/OxHcvmMnpbSvIe/8b/teVdyoV067m/BVJVDS0dRVfOC+NX14+H1eIr4fhw92VXPP3j/12vf+GfE6fmUJPbW4P331uM0+vKeoqi48I4ar8LP7yzh5iXE5euvPEow9XAhpaO/jio2t5b9fhOXM58S6e/PxyUmN8Q1+f+OQA33p2U9f7Dpvh62dP4xev7OArZ04lLjyEG47PPep5AtXQ0sEld3/Ingr/ORg3nZDL9y+a3fV6W0k9l979Aa3dknzcdEIur20po76lg+fuOIEp/ZxbIhOSeh4GaMQfI1uWVWJZ1trO7xuAbcDEzf2549/+KwMBuTsf5KRJvmFHb+yoYn/6ef77lG3yBQ7g+9WPSoPSjb2PveYhaG/25S/vHjgAbP4nTD0bCt6F6r1+bzW1ubnnPf8yrwXv7aro9+WNB8W1rTz2SaFfWV1LBztKG46wh4j0S1sjfPhH/zLLC3tWAFBVU8WFsQW8cWYpT57r5cy8cOpaOthZ1uNvsGKHX+AA4Nj2LOdl+j60t7m9/Pc/N7K/qokHPtjHX97eQ3VTO5uK67nr8XXccdpUvB2tvLyjnoVZMUza+1ivqk4q+Td7K5t6le8ubyS2tbj3tVXvpTYsyy9wAHhpYwmFNc1dr59b13vff3y0H28f6fQKq1v459oiv7LqpnZCHL5bel1LBwfrWnrt19P+qia/wAFgf3ULeyp811fb3M5f39nj977ba1HZ2E5kqAPLgr++s4eqRv9rG6jIMAfnzO4dLOXn+D+02lZS7xc4APxzbRFnzUqhoc3d+/dCRIZUUCdMG2NygYXAx328dxtwG0B2dvbIVmwk9TEm1+uMpKXNd8OwGbDj8d+gsxvft0HnRDdHH2NcQyJ8E50dfUyedrp88yzAb1wrgN0YIkJ6j7d1OSfm/Hq7Aafd4OlxE3fa9dBCRr8x0ZYae9/zE5zh0NFG0pYHSH37pwBMASYt/jpVrSf2HkbZvW3sduwO6/DfqsdrUdPczqMf+6+H4PZatHa4MU4bDpuhzePF7Yyk58wLjzMS4+79t28zBnfGcdCzYyfvNGoaW3tt77AZ7N1S30WG9W5fI8McfWbHc9gMDlvvNLCHtnXaDfHhx55k7LDZeq1sDeDsHNZlN4bwPu4FTrthcXYcWw7WER4ydHPAjDFckZ/FugM1fLS3GmPgs0uzOW5SXI/z937u6XLaaXd7O69LbbPIcAraAHZjTCTwT+ArlmXV93zfsqx7LMvKtywrPykpeFkfht20c/0/+BvD7qmf46MC34/k+qWZ5BY83e19G6TOh2nn+17v+DfMvBASp4Ej1H+7/M/5yrKXQliPscHzroKdr8LC6yDefx3psBA7d5w2xa8sPMTOSdMSB325Y1FmXDh3nT7VrywvMYIZaX1MShcZZcZEWxri8g3B9CuLgMmnQdUu7O/8zO+t5LW/5WsLTe+/weSZkLbAr6h6/m080G1QrM1AZKijz3H6tS1u3PYwbl4UzcaienbnfsbXlh5iD2FH4lnMTIui++fTELuN3MQIvrcmnJLlP4CQSN9+My+C0Chyq95lTor/A56bT5pEdsLhYUUXz0/3eyBhtxmuX56D6SN6yIoP54un+rfbk5MiqGpsxxj4/kWzAxpSmZsYzmeO8w8ol+XFM6VzFesol5OvnDnN7/3oMAczU6OZmhrJG9vK+dpZ04gNIFAJ1KTECP52XT4vfukE/nPXSXz3glm9JoDPTo8mMdL/nFcfl81/NpeQFediZlr0kNVHRHoLSrYlY4wTeAl41bKs3xxr+1E9Tnew2pvgwErY+xZ0tNI26QxWNObyfmE7y6cksXRSPMkNW2DHK+Bugxnn+1ZGbSiFgvd8Q5LyzoCoFGipgQMfQkezb0hSzkm+mzL4JhHufBUaS32TECt3QXwe5J4I0b1XLG3r8LC+sJbXt5YR7XJy+ozkCT1BuKapnVUF1byzs4JpKZGcNDXJf6y1yMgZn3MeOtqgeJXvgUhYLEw9B9Ln++aFPXh+r82br3mB8Gmn9D5O9V7Y87ZvKGfeqex0zeOSB3fS3O7BaTf86FNzuGxRBiu2l3P7I2u7dpuaHMnPPj2Xj3aXc362h+1VbnZUefjspHpiC9/Ea7NzMPlUXqtJZ2leIh7L4o1tZdhthoTIUP769h7KG9rIjAvj+ydFcerkGJzuFtjzBlbVHgpmfYEVZeHsLG/m5KlJLJucQGLk4QDG67XYWFzLim3luD0WZ8xMZkFW7BGzB1U1tbFqXzXv7qpkRmoUc9JjqGxsIy3GxbSUyICzNZXVt/Lx3ipW7q1mXmYMJ0xJ7DGR282a/bWs2FZGQmQoSyfFs6O0gV3ljZw5M5lFOXFHzR41XHaWNvD2znIOVDezdFICRTXNhDntnDwt6cjrHIn4UxfVAAVjwrQBHgKqLcv6SiD7jOob3mDtfA0euwIiU3xP2oyBS/4KWUuOvW/5Dtj4JGx9FjLy4cSvQsrsY+8nImPZ+AwejqSuCO49zZfy9JCIJLj1LYjNOubulmVRUNVESV0riZG+bEtOu422Dg8bi+rYWnJ4PYTsY0wwPpLtJfU8+GEBn+yr5rw5qVyRn0WukimIjHYKHgYoGIPYTwCuAzYZY9Z3ln3Hsqx/B6EuweVxw8d/8X3ffZLfxqeOHTw0VcGzN0NpZxaM6n1w4GO4+VWITh+e+oqIjLSYTLj6cXjpq77ehNR5cOFvewcOR1gfwhhDeoyL0ro27ntvLy6ng4sWpLMwK5bjJsVz3KTBZ5CbkRbNTy6ZQ3O7h6gwR59DjY6lrcPDjtIGDtQ0kxQZysy0KKJdWhxNREafEQ8eLMt6H0V7PsaAvY/82EdYHMlPzd7DgcMhdQegao+CBxEZXzLz4YYXobkKXPEQ3m0CbWs97HkTPvozhEbhXn4nu8Lm0o6DvMQIosKcfLyvmuvv/6Rrl0c/2c+Tty1nUU5cHycbGIfdRrRrYNMILcvipY0lfP3pDV1lN584ia+eOa3PidQiIsE0MVf8Gi1sdlh2O37pNGwOOmZ86tj7OsLoMw2H0+VbFK58u2+eRNFqaFPaOhEZ41yxkDDZP3AAX+Dw9A2+ReH2rMDx6KW07PuET/3pA7759AbK6lq4733/1NMdHotXtpSOXN2P4UB1M997frNf2X3v72NXudpuERl9FDwEW/ZyuOEl3ItupH7+raw+7TFueMXNJ/uqjrxPRzNEZ8CyO/3L51zuy7q0ZwX87SR4/Cr4+xnw7q98T+dERMaTjlb46E/+ZZZFTuU7ZMS6eGVLGeuLaunokdIUwN1H2VA4UN3MxqJayht6p2c9kvoWN03tnl7lNU3tQ1k1EZEhof7QYHOEUJGQz1fKHRRWt5BTHc7SyXF8tKeaGJeT6andUs51tPoyLL37K1+WpuV3wPX/ggOrIHkGZC7xlb/wpcNrOAB88DuYfh5kLxvpqxMRGT7G5kuL2oPHEd6V8/+ljSV87oQ8PtxT3fW+zcB5c3pnmRsMt8fLa1vL+NY/N1Lf6iY9Jow/XbMooKFR6bFhTE6K6FqcDSDUYTvmCtEiIsGgnodRoKimhQ92V7EgK5bwEDu/fWMXv31jJzc/tJptJd16DIpWwaOXQ+FK3yrT//oCNFfDqf8Fsy6G6FRfutaGPrrj+yoTERnLHCFwwpf9h3A6wtgZczwVnaseZ8S6yE108cCNx3HqtCTOm5PKY7cuY0F27LGP39YAhZ/A1hehZCO4j9wTsLu8kTsfX0d9qxuAg3Wt3Pn4Osrrj90DkRAZyu+vXsicdN/DorSYMO69Pp8pyUo5KiKjj3oeRoHoMCehDhuTkyP57es7u8qLalq4++3d/OqK+YQ67LD95d47r/wLTL8AnJ2L6ESlQvJsKN9yeBtjIH7SMF+FiEgQ5JyA5/qX8Wx9iSYTRknyqez35JAVv5f0GBetHV7AcNqMZE6ZloQxBJYNqa0JPvgjvPsL32tjg0/fA3Ov6HPzoprmXqvQF9e2UFLXSnJ0WJ/7dDcnI4ZHb1lKeUMbMS5nQPuIiASDgofh1FQF7Y0QmeybyHwEuYkRfP+iWWwv7T05buWeauqrK0mKtIOrj+5vVzyYbosBhcfDp/4Mz9wENfsgNArO/zUkzRyKK5owvF6LkroW7DYbqTG6iYuMWo4QXmvM46ebz6LN7aWioRG7bSu/u2oBL20socPj7Rr+Y+tcFrqsvgW3xyIpMpTyxjZCHDZcDjs1LR3EhzuJDHNC5Y7DgQOA5YWXvuZbU6ePhzEJ3RZ8c9oNZ81KYUZqFLZ+9O/HhIcQc7TVmptroK0eIhJ96wKJiASBgofh4PXCvnfg5a/7UqrOuBhO/y4kTetzc7vNcMnCDFZsK+cfH+33e++kSRHEPH8dNBbDRb/33TDaO8fFGhscfyc4nP4HzFgIN78O9cUQFqNeh34qq2/h0ZUHuOe9vYQ57Xzz7OlcND+daJfz2DuLyNCrPwhlW6CjBZJnQuLUrrdaOjz87d09FNW0dJV5vBar9lVzxeIMUmNcHKhqJjshnA63l5c3lvDzV7bT3O7h6iXZWJaXqclRPLOmiA1FdSzJjed7F81iTvdF6Q5pq4eW2j6rmBAZwg3Lc3hufTFfPXMaT60u5N+bSvlwTxXfu2g2s9Ki+9wvYAUfwMvfgMptMOVsOOuHvp+FiMgIU/AwHMq3+laN9nT4Xm973pch6cqHjvi0KDzEwfIMJzcsjOUf62uxLJiaFM4XsosIWfGxb6Nnb4XPPAUH1/puopNPg/RFfdchMsn3Jf326uYy/vDmbgBaO7z8z782kxYbxukzUoJcM5FxrqOFjuoD7G0Kpc4TSlZSLGnecnjqOijtXAMhNAqufx4yFlPT1M7eikacfTzeX5AVy0d7q3jww/1YlsUVizO5dGEG//3s4fVxHvqwgC+fMYWHPixgd+dk5U8KqrntH6t58/oswuwh/sknYnN9me76EONyUtvSwc8unce3n93YNfdh5d5q7nxsLU99frlf70S/VOyARy/ztfsAu16Fpgq47jlfClsRkRGkCdPDoWrX4cDhkN2vQ13xUXdLbN7Ltxp/zktn1fHPK5J4YuoKpr31hcMbNFf7FoI74S449b99q1DbFf8NpeZ2N0+sKuxV/vb2iiDURmQCaaqiadWj3L+qgvP/vpUr71vLxX/6gHXlHVCx7fB2bQ3w3m9pa2nmT2/t5up7V3LmLP/APjrMQbvHy33vF+DxWngteHJ1ER8X+LLYdffvTaVMSYnyKztY18oOTxpc9QhEdD6ESZgCl98PUcl9Vj/GFcJnlmSzs6y+K3A4ZE9FE4Xdekb6rXrP4cChq5Jroa5o4McUERkgffIcDmExvcvC4yHkGGn3wqJwFX/A7MJ3YcE1sP9D8Lp7bBM7ZNUcdm0NvvkYx7ruUSTEbmNyUgRbS/zXxchJGDvXIDImlaxje3sSP3u/rquoorGNb/+niMdnXkPc5gcPb1u2iaqaWu57fx8AL2w4yHfOn8mGwlqSo0O5Oj+bP7y5q9cp3tlRyez0aD7cc3gdnez4cMrr2/y2sxkIdTog+xy47R1fFruoVN9cg6NYOim+c9L0br/yELuNiBB73zsFoq92PyRiTLWtIjJ+qOdhOKTMgWnn+Jed90uIyTz6fvFT4dTv+L7f+jwcd4tvXsMhWcsgbf7Q1nU4NNfAhifh/vPgkU/D7hVHTXE4mjjsNm4+KY/wbjf61JhQTp6mIWAiw6pqD8UdvVOTbi9rojp2jn/h3Csp6zicyKCwppnHPznA7opGPrUgg+lpUczP6v0QZ3FOLG734cXYXE47Z81KYXKS/3DSL58xlUmJnWUxGZA655iBA/iyOM3PjOW6ZTl+5d84Z/rh4w1E8kyYd5V/2dk/hTjNZxORkWcsyzr2VkGWn59vrV69OtjV6J+GMijZAC1VED8FUuceTqd6NK31ULoRag9AXC7YHFC919ebkTYfotOHveqDtvEp3/yMQ4yBG/4NuccHr079tKO0gR2l9TjsNmanR5OToMwmMmoEkGe0b6O6Ld35GqsOtnLFK/5P6CcnRfD0uR7in7/ON3Rn7pVw2ncotSVz+V8/4tOLMmhq81BW38qc9GjOm5tGTkIEeysaufUfq7sWXkuPDePBG5cQ5rSx5WA97R4v6bFhlDe0ExPmwO21qGxsJyM2jNnpMYNKkFDT1M6Wg3WU1reRFedidkYMkaGD7OhvrPDdGxrLID4PUuep50FkcAbclk50Ch5kaLU3wwPnQcl6//ITvuLLDiIigzU+g4emChrX/pP7q+fw25V1WBbEhjv5+/X55OfE+R6oeNohNhscvonHGwpr+eKjaymuPTwf4EcXz+a65TkYYyipbWFneSNer8XUlEgy4/RhW0S6KHgYIM15GE41BXBgJdQWQmY+ZCyGsEGm6xvtbEdYj6KveSAiIodEJBG59LN8vqqQM2dnUOcJITMprmuNBuJyeu1SVt/aFTgclxvHadOT2V3RyBOfFJIRF8b6A7XMzohhYXYs8REDzHQkIiJ+FDwMl7piePI6XzfzIef/GpbcErw6jQRHKJz4Vd86F5bXVxYSCVPODG69RGT0C4kkNG0mswLc3N25onNSVCjL8hL4v1d3dL03OSmCE6cmcfNDq/nCKXl87axphDgGMWlZREQATZgePmWb/QMHgBU/9PVCjHc5x8NN/4FTvgVn/dj3fdq8YNdKRMaZGalRRIc5uHBeWq8FNvdUNBEf7pu3cO97+9hX2RyMKsoo1uHxsqusgU/2VVE8mFS6IhOMeh6GS8+c3ADtjf4LDo1XdidkL/N9iYgMk7ykSB69dRnbS+p5uG1/r/c9nXP6PF6L9m5ZlkRaO9w8uaqQn7y8jQ6PRUJECH+7bjH5ufHBrprIqKeeh+GSPAOcPSbnzf/MsdO1DkJRTTObimopq28dtnOIiIwmczNiuGh+Olcdl+VXHua0Ye9ceTo/J45srdUi3WwvaeT7L2ylw+MLMKua2vnGMxuobGw7xp4iop6H4ZI0A65/Ad75hW911HlXwaIburKEDCWv1+LN7eV845kN1DZ3kBodxu+vXsDSvIQhP5eIyGgT5rRz+6mTSYwM5Zk1RUxKjODTizL4+3t7uX5ZDjccn0uMKyTY1ZRRpHuGrkMKKpupamwnMVKT60WORsHDcMo6Dq58GDqaIDzBt97BMNhT2cgdj62lze2boFxa38qXHlvH8186gfRY17CcU0RkNMmMC+crZ07l+uU5hIc4sNnglGlJxLicOOzqZBd/6bG9113KjHMRHzHw9T1EJopx26JWNLSy7kANu8sb8Xj7v5bFoYlU6w/UUNlw5G7Moppm1u6v5kBVU98bhLh8K5MOU+AAcLCmpStwOKSisW3Ihy+1uz2sL6zhn2uKeHN7mYZHicioYowhITIUV4idUIedhMjQgAMHr9dib0Uj6w7UqG2bAKalRPHt82Zg67w1R4c5+NUV80mKCmAxV5EJblz2PGwqquP2R9dQVNNCiN3Gd86fwZXHZREeEtjlNra6eeTj/fz6tR10eCwmJYbz52sXMyvNf42Gd3dWcOfj66hr6SAq1MFvrlrAGTOSsdlGdt2RxMhQjIHu6/1FhNiJCx/abvo3t5dz+6Nru85z4pREfn3lfFKi1diKyNjV2uHhuXXF/OCFLbS5vaRGh/HX6xaxIKuPNWtkXIgIdXDj8bmcPC2J6qZ2suJcZCdEBLtaImPCuOt5qGvp4LvPb6KoM+1au8fLD17cyvaShoCPseVgHT//z/auiVT7Kpv5yUtbaWpzd21zoLqZLz22lrqWDgAa2tzc+fhaCo7UAzGMpiRH8t0LZnZ1bththp99ei45QzhBsLyhle89v8UvQHl/dyVbD9YP2TlERIJhZ1kD3352k9/Qz288vYHqJk2eHc9CnXZmpkVzwpREBQ4i/TDueh6qG9vYUFjXq/xAdTOLcgJ7ilRY0zsf+Id7qqhuaici1PcjK6tvob7V7bdNa4eXg7Ut5CVFDqDmAxfqtHPt0hyWTIqnvL6NjFgXk5MjMUM4VKql3UNFH1ko6juDJxGRsaqojxz/u8ubqGxo18rUIiI9jLueh5hwJ5OTej9BSIsJfGhNah/DcOZlRhPtOjyRKiEiFJfTf7VSp92QHKQhPGFOO3MzYjljZgoz0qJxDvEEwZToUM6bk+pXZrcZJiePbKAkIjLU+hp6mR4TRmy4Js+KiPQ07oKH+IhQfvbpuUSGHu5U+fzJecxMiwr4GLPTY7hheU7X62iXgx9eNIeYbsFDbkIEv7hsLk677+m+3Wb4ySVzmJQ4Prs+w5wOvnnOdD61IB2bgex4F/fdkM+M1MB/riIio9H01Ci+fMbUrtfhIXb+74r5QXsYJCIymhnL6n8mopGWn59vrV69ul/7FFQ2caC6mdhwJ1OSIgkP7d8IrcZWN7srGqhvcZObEN7neEi3x8ueikZK61pJiQ4jLymSEMe4i8f8tLk9lNe3ERFiJ165sEWCYcDjEQfSlk4ULe1udpc3+ibPxoczKTFiSId+isiooz/wARp3cx4OyU2MIHcQvQCRYY5jZtpw2G1MT41memr0UbcbT0IddrLitVKriIwvrhAHczNjg10NEZFRb3w/JhcRERERkSGj4EFERERERAKi4EFERERERAKi4EFERERERAKi4EFERERERAKi4EFERERERAKi4EFERERERAKi4EFERERERAKi4EFERERERAJiLMsKdh2OyRhTAewPdj1GQCJQGexKjLCJeM2g655ohvK6Ky3LOncgO06QtlS/YxOLrnviGOprHnBbOtGNieBhojDGrLYsKz/Y9RhJE/GaQdcd7HqMtIl63cEwUX/Wuu6JZSJe90S85tFKw5ZERERERCQgCh5ERERERCQgCh5Gl3uCXYEgmIjXDLruiWaiXncwTNSfta57YpmI1z0Rr3lU0pwHEREREREJiHoeREREREQkIAoeREREREQkIAoegsAYc78xptwYs7lbWbwx5nVjzK7Of+OCWcfhYIzJMsa8ZYzZZozZYoz5cmf5uL12Y0yYMeYTY8yGzmv+YWf5uL3m7owxdmPMOmPMS52vx/11G2MKjDGbjDHrjTGrO8vG/XUHw0RsSydiOwpqS9WWqi0dTRQ8BMeDQM+FSb4FrLAsayqwovP1eOMGvm5Z1kxgGXCHMWYW4/va24DTLcuaDywAzjXGLGN8X3N3Xwa2dXs9Ua77NMuyFnTLST5RrnukPcjEa0snYjsKakvVlvpMlOse1RQ8BIFlWe8C1T2KPwU81Pn9Q8AlI1mnkWBZVollWWs7v2/A1xBmMI6v3fJp7Hzp7PyyGMfXfIgxJhO4APh7t+Jxf91HMFGve1hNxLZ0IrajoLYUtaWHTNTrHlUUPIweKZZllYDv5gAkB7k+w8oYkwssBD5mnF97Z3fzeqAceN2yrHF/zZ1+B/wX4O1WNhGu2wJeM8asMcbc1lk2Ea57tJgwP+uJ1I6C2lLUlsLEuO5RzxHsCsjEY4yJBP4JfMWyrHpjTLCrNKwsy/IAC4wxscBzxpg5Qa7SsDPGXAiUW5a1xhhzapCrM9JOsCzroDEmGXjdGLM92BWS8WeitaOgtlRtqdrS0UI9D6NHmTEmDaDz3/Ig12dYGGOc+G54j1qW9Wxn8YS4dsuyaoG38Y3RHu/XfAJwsTGmAHgCON0Y8wjj/7qxLOtg57/lwHPAEibAdY8i4/5nPZHbUVBbqrZ0fF/3WKDgYfR4Abih8/sbgOeDWJdhYXyPxu4DtlmW9Ztub43bazfGJHU+JcMY4wLOBLYzjq8ZwLKsb1uWlWlZVi5wNfCmZVmfZZxftzEmwhgTdeh74GxgM+P8ukeZcf2znojtKKgtVVuqtnQ00QrTQWCMeRw4FUgEyoDvA/8CngKygQPAFZZl9ZwIOKYZY04E3gM2cXjs5nfwjdcdl9dujJmHb1KXHV+w/pRlWT8yxiQwTq+5p86u9m9YlnXheL9uY0wevidk4BsW+phlWT8d79cdLBOxLZ2I7SioLQW1pWpLRw8FDyIiIiIiEhANWxIRERERkYAoeBARERERkYAoeBARERERkYAoeBARERERkYAoeBARERERkYAoeBARERERkYAoeJBxyRgTa4z54jG2yTXGXBPAsXKNMZuP8v6Nxpg/HeG9D3sewxhzqjHmpWOdV0Qk2NSWikhPCh5kvIoFjnrDA3KBY97wBsOyrOOH8/giIsMsFrWlItKNggcZr34OTDbGrDfG/LLza7MxZpMx5qpu25zUuc1XO59ovWeMWdv51Z+bVZYx5hVjzA5jzPcPFRpjGofyokRERpjaUhHx4wh2BUSGybeAOZZlLTDGXAZ8AZgPJAKrjDHvdm7zDcuyLgQwxoQDZ1mW1WqMmQo8DuQHeL4lwBygufP4L1uWtXpoL0lEZMSpLRURPwoeZCI4EXjcsiwPUGaMeQc4DqjvsZ0T+JMxZgHgAab14xyvW5ZVBWCMebbznLrhich4orZURBQ8yIRgAtzuq0AZvqdqNqC1H+ewjvFaRGSsU1sqIprzIONWAxDV+f27wFXGGLsxJgk4GfikxzYAMUCJZVle4DrA3o/znWWMiTfGuIBLgA8GWX8RkdFAbamI+FHPg4xLlmVVGWM+6Ezp9x9gI7AB31Os/7Isq9QYUwW4jTEbgAeBu4F/GmOuAN4CmvpxyveBh4EpwGMaoysi44HaUhHpyViWegRFREREROTYNGxJREREREQComFLIgEyxpwD/KJH8T7Lsi4NRn1ERMYitaUiY5uGLYmIiIiISEA0bElERERERAKi4EFERERERAKi4EFERERERAKi4EFERERERALy/wEZji6rSnsbHwAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<Figure size 789.625x360 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "sb.relplot(x=\"total_bill\", y=\"tip\", col=\"sex\", hue=\"time\" , data=dataset)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "47715bdc",
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3 (ipykernel)",
   "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": "3.9.12"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}