Oktoberfest/Oktoberfest dataset.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "d8136383",
   "metadata": {},
   "outputs": [],
   "source": [
    "import opendatasets as od"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "99e30f40",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Downloading oktoberfest.zip to .\\oktoberfest\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "100%|█████████████████████████████████████████████████████████████████████████████████| 871/871 [00:00<00:00, 9.69kB/s]"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\n"
     ]
    }
   ],
   "source": [
    "od.download(\"https://www.kaggle.com/datasets/lucafrance/oktoberfest\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "daad8ca1",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "    }\n",
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>year</th>\n",
       "      <th>duration</th>\n",
       "      <th>guests_total</th>\n",
       "      <th>guests_daily</th>\n",
       "      <th>beer_price</th>\n",
       "      <th>beer_consumption</th>\n",
       "      <th>roast_chicken_price</th>\n",
       "      <th>roast_chicken_consumption</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1985</td>\n",
       "      <td>16</td>\n",
       "      <td>7.1</td>\n",
       "      <td>444</td>\n",
       "      <td>3.20</td>\n",
       "      <td>54541</td>\n",
       "      <td>4.77</td>\n",
       "      <td>629520</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1986</td>\n",
       "      <td>16</td>\n",
       "      <td>6.7</td>\n",
       "      <td>419</td>\n",
       "      <td>3.30</td>\n",
       "      <td>53807</td>\n",
       "      <td>3.92</td>\n",
       "      <td>698137</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>1987</td>\n",
       "      <td>16</td>\n",
       "      <td>6.5</td>\n",
       "      <td>406</td>\n",
       "      <td>3.37</td>\n",
       "      <td>51842</td>\n",
       "      <td>3.98</td>\n",
       "      <td>732859</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>1988</td>\n",
       "      <td>16</td>\n",
       "      <td>5.7</td>\n",
       "      <td>356</td>\n",
       "      <td>3.45</td>\n",
       "      <td>50951</td>\n",
       "      <td>4.19</td>\n",
       "      <td>720139</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>1989</td>\n",
       "      <td>16</td>\n",
       "      <td>6.2</td>\n",
       "      <td>388</td>\n",
       "      <td>3.60</td>\n",
       "      <td>51241</td>\n",
       "      <td>4.22</td>\n",
       "      <td>775674</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   year  duration  guests_total  guests_daily  beer_price  beer_consumption  \\\n",
       "0  1985        16           7.1           444        3.20             54541   \n",
       "1  1986        16           6.7           419        3.30             53807   \n",
       "2  1987        16           6.5           406        3.37             51842   \n",
       "3  1988        16           5.7           356        3.45             50951   \n",
       "4  1989        16           6.2           388        3.60             51241   \n",
       "\n",
       "   roast_chicken_price  roast_chicken_consumption  \n",
       "0                 4.77                     629520  \n",
       "1                 3.92                     698137  \n",
       "2                 3.98                     732859  \n",
       "3                 4.19                     720139  \n",
       "4                 4.22                     775674  "
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import pandas as pd\n",
    "import numpy as np\n",
    "\n",
    "data = pd.read_csv(\"oktoberfest.csv\")\n",
    "data.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "760d9d75",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>year</th>\n",
       "      <th>duration</th>\n",
       "      <th>guests_total</th>\n",
       "      <th>guests_daily</th>\n",
       "      <th>beer_price</th>\n",
       "      <th>beer_consumption</th>\n",
       "      <th>roast_chicken_price</th>\n",
       "      <th>roast_chicken_consumption</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>30</th>\n",
       "      <td>2015</td>\n",
       "      <td>16</td>\n",
       "      <td>5.9</td>\n",
       "      <td>369</td>\n",
       "      <td>10.27</td>\n",
       "      <td>75134</td>\n",
       "      <td>10.75</td>\n",
       "      <td>503510</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>31</th>\n",
       "      <td>2016</td>\n",
       "      <td>17</td>\n",
       "      <td>5.6</td>\n",
       "      <td>329</td>\n",
       "      <td>10.57</td>\n",
       "      <td>66231</td>\n",
       "      <td>11.00</td>\n",
       "      <td>366876</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>32</th>\n",
       "      <td>2017</td>\n",
       "      <td>18</td>\n",
       "      <td>6.2</td>\n",
       "      <td>344</td>\n",
       "      <td>10.87</td>\n",
       "      <td>77836</td>\n",
       "      <td>11.41</td>\n",
       "      <td>466747</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>33</th>\n",
       "      <td>2018</td>\n",
       "      <td>16</td>\n",
       "      <td>6.3</td>\n",
       "      <td>394</td>\n",
       "      <td>11.30</td>\n",
       "      <td>78705</td>\n",
       "      <td>11.67</td>\n",
       "      <td>436492</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>34</th>\n",
       "      <td>2019</td>\n",
       "      <td>16</td>\n",
       "      <td>6.3</td>\n",
       "      <td>394</td>\n",
       "      <td>11.71</td>\n",
       "      <td>78502</td>\n",
       "      <td>12.15</td>\n",
       "      <td>434998</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    year  duration  guests_total  guests_daily  beer_price  beer_consumption  \\\n",
       "30  2015        16           5.9           369       10.27             75134   \n",
       "31  2016        17           5.6           329       10.57             66231   \n",
       "32  2017        18           6.2           344       10.87             77836   \n",
       "33  2018        16           6.3           394       11.30             78705   \n",
       "34  2019        16           6.3           394       11.71             78502   \n",
       "\n",
       "    roast_chicken_price  roast_chicken_consumption  \n",
       "30                10.75                     503510  \n",
       "31                11.00                     366876  \n",
       "32                11.41                     466747  \n",
       "33                11.67                     436492  \n",
       "34                12.15                     434998  "
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data.tail()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "0db5ca77",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 35 entries, 0 to 34\n",
      "Data columns (total 8 columns):\n",
      " #   Column                     Non-Null Count  Dtype  \n",
      "---  ------                     --------------  -----  \n",
      " 0   year                       35 non-null     int64  \n",
      " 1   duration                   35 non-null     int64  \n",
      " 2   guests_total               35 non-null     float64\n",
      " 3   guests_daily               35 non-null     int64  \n",
      " 4   beer_price                 35 non-null     float64\n",
      " 5   beer_consumption           35 non-null     int64  \n",
      " 6   roast_chicken_price        35 non-null     float64\n",
      " 7   roast_chicken_consumption  35 non-null     int64  \n",
      "dtypes: float64(3), int64(5)\n",
      "memory usage: 2.3 KB\n"
     ]
    }
   ],
   "source": [
    "data.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "e6095d5a",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data.duplicated().sum()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "15923155",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "year                         0\n",
       "duration                     0\n",
       "guests_total                 0\n",
       "guests_daily                 0\n",
       "beer_price                   0\n",
       "beer_consumption             0\n",
       "roast_chicken_price          0\n",
       "roast_chicken_consumption    0\n",
       "dtype: int64"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data.isnull().sum()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "bf1de97a",
   "metadata": {},
   "source": [
    "### Investigating the beer and chicken consumption over the years:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "bdf84923",
   "metadata": {},
   "outputs": [],
   "source": [
    "years = data.groupby('year')[['beer_consumption','roast_chicken_consumption']].sum().reset_index()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "dda0263d",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>year</th>\n",
       "      <th>beer_consumption</th>\n",
       "      <th>roast_chicken_consumption</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1985</td>\n",
       "      <td>54541</td>\n",
       "      <td>629520</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1986</td>\n",
       "      <td>53807</td>\n",
       "      <td>698137</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>1987</td>\n",
       "      <td>51842</td>\n",
       "      <td>732859</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>1988</td>\n",
       "      <td>50951</td>\n",
       "      <td>720139</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>1989</td>\n",
       "      <td>51241</td>\n",
       "      <td>775674</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   year  beer_consumption  roast_chicken_consumption\n",
       "0  1985             54541                     629520\n",
       "1  1986             53807                     698137\n",
       "2  1987             51842                     732859\n",
       "3  1988             50951                     720139\n",
       "4  1989             51241                     775674"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "years.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "cc133c8b",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>year</th>\n",
       "      <th>beer_consumption</th>\n",
       "      <th>roast_chicken_consumption</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1985</td>\n",
       "      <td>-0.761963</td>\n",
       "      <td>0.472739</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1986</td>\n",
       "      <td>-0.834763</td>\n",
       "      <td>1.035905</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>1987</td>\n",
       "      <td>-1.029658</td>\n",
       "      <td>1.320881</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>1988</td>\n",
       "      <td>-1.118030</td>\n",
       "      <td>1.216483</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>1989</td>\n",
       "      <td>-1.089267</td>\n",
       "      <td>1.672280</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   year  beer_consumption  roast_chicken_consumption\n",
       "0  1985         -0.761963                   0.472739\n",
       "1  1986         -0.834763                   1.035905\n",
       "2  1987         -1.029658                   1.320881\n",
       "3  1988         -1.118030                   1.216483\n",
       "4  1989         -1.089267                   1.672280"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from sklearn.preprocessing import StandardScaler\n",
    "\n",
    "scaler = StandardScaler()\n",
    "\n",
    "years[['beer_consumption', 'roast_chicken_consumption']] = scaler.fit_transform(years[['beer_consumption', \n",
    "                                                                                       'roast_chicken_consumption']])\n",
    "years.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "a1b1da65",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.legend.Legend at 0x20637479f70>"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 600x400 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "import seaborn as sns\n",
    "\n",
    "plt.figure(figsize=(6,4))\n",
    "\n",
    "sns.lineplot(years, x='year', y='beer_consumption', label='Beer Consumption', marker='o')\n",
    "sns.lineplot(years, x='year', y='roast_chicken_consumption', label='Chicken Consumption', marker='o')\n",
    "\n",
    "plt.title(\"Beer and Roast Chicken consumption at Oktoberfest over the years:\")\n",
    "plt.xlabel(\"Year\")\n",
    "plt.ylabel(\"Consumption\")\n",
    "plt.grid(True)\n",
    "plt.legend()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "5d58408c",
   "metadata": {},
   "source": [
    "### Investigating the beer and chicken prices over the years:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "057abe5a",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.legend.Legend at 0x2063d9cc070>"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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U1j//lDK+1q2trdWZM2cy1LVp06aqatWq6ZZldd+LFi1SgDp8+HCG/abJ7vl59913M31PDB06VGk0GlMdjh49qgD1yy+/pCtXr149Vbt2bdPjL774QllZWal9+/alK5cW+6pVq0zLAOXm5mb6THucqlWrZvqZnNXP+/j4eOXp6ak6d+6crpxer1fVq1dX9erVe+TxL1y4oKysrNR3331nWpaYmKi8vLzS/XM2ZMgQ5ezsbHrtpJkwYYICHvoPY9pn/SeffKK8vLwyfH5m9ppK2+eDCdSDWrRooaytrR9Z5kEWeRlo1qxZ7Nu3j3379rF69WoGDhzIa6+9xpQpU0xlVq5cibu7O507dyY1NdX0U6NGDfz8/EzNmWvXriU1NZUBAwakK2dvb0/Tpk0z7aX+zDPPZCnO1NRUPv/8c6pUqYKtrS02NjbY2tpy7tw5Tp06laF8ly5d0j0OCQkB4MqVKwDs2rWLpKSkDNePn3rqKUqVKpWlmABWrVqFVqtFq9VSqlQpfv31VyZPnkzHjh1NZTZt2oSTkxM9e/ZMt21aE+1/myEPHTpEly5d8PLywtraGq1Wy4ABA9Dr9Zw9exaAcuXK4eHhwTvvvMO0adM4efJkluPNbZk9z0lJSYSHhz90m9WrV1OhQgVatWr12P0fPHiQBg0a4Ovry7///pvu3KxcuRKNRkO/fv3Svd78/PyoXr16htebn58f9erVyxBv2mvicVq2bJnucoa1tTXPPfcc58+fz3CJISuv6507dxITE8OwYcPQaDSZljl//jynT582vU7/W88OHToQGhpqau6uV68eq1ev5t1332XLli0kJiZmqV4A06ZNo1atWtjb22NjY4NWq2Xjxo2Zvrdyk7rX5P1g/deuXUvjxo1p0qQJ69evz3Jn1M2bNwNkuPxRr149KleunKHJ38XFJcNruG/fvhgMBrZt2wZk/fMvTUhICBUqVMhSvFndd40aNbC1teWVV15h5syZGS5z5sSmTZuoUqVKhvfEoEGDUEqxadMmAIKDg6lduzbTp083lTl16hR79+5Nd8lh5cqVVKtWjRo1aqSrS9u2bdNd9krTokULPDw8nrge8PjP+507dxIREcHAgQPTxWYwGGjXrh379u3LcKnqv8qUKUOnTp2YOnWq6TU7d+5c7t69y/Dhw03lVq5cSfPmzSlevHi647Rv3x6ArVu3mspu2rSJVq1a4ebmZvqs/+ijj7h7926Gz8/MXlN169YFoFevXixcuJAbN25kGvvGjRszXIJ6HItMVipXrkydOnWoU6cO7dq14+eff6ZNmza8/fbbpmGBt27dIioqytSX5b8/YWFhpuGraf006tatm6HcggULMgxzdXR0zPIokTFjxvDhhx/SrVs3VqxYwZ49e9i3bx/Vq1fP9EPZy8sr3WM7OzsAU9m7d+8Cxi+wB2W27GGefvpp9u3bx+7du/nzzz8JCgpi+PDh7Nixw1Tm7t27+Pn5ZfhA9vHxwcbGxhTL1atXady4MTdu3OD7779n+/bt7Nu3jx9//DFd7G5ubmzdupUaNWrw3nvvUbVqVYoXL87HH3/8yGv/j1KyZEkALl26lK3tHvc8Z+b27duUKFEiS/tfv349t27d4qWXXsow6uPWrVsopfD19c3wetu9e3eG19uDsabFm9Uv9Ue9VtLOYZqsjPhJ65PwqOci7T315ptvZqjjsGHDAEz1/OGHH3jnnXdYtmwZzZs3x9PTk27dunHu3LlHxjFx4kSGDh1K/fr1Wbx4Mbt372bfvn20a9cuWwnPg0qWLMnt27cf+SWQ1n8nMDAw3fJly5aRmJjI0KFDTa+prEg7D5k9/8WLF89wnjLrS/PgOc3q51+a7Iz2yuq+y5Yty4YNG/Dx8eG1116jbNmylC1blu+//z7Lx3rQ3bt3H/o8pa1PM3jwYHbt2mXqUzZ9+nTs7Ozo06dPurocPXo0Qz1cXFxQSj3R8/Q4j/scSnsf9ezZM0N8X331FUopIiIiHnmMUaNGce7cOdavXw8Y+xc2bNiQWrVqmcrcunWLFStWZDhG1apVgfvv1b1799KmTRsAfv31V/7991/27dvH+++/ny7uNJk9V02aNGHZsmWmBoISJUpQrVq1x/ZRywqLHA2UmZCQENauXcvZs2epV68e3t7eeHl5sWbNmkzLu7i4AODt7Q3AokWLstQ68bD/JjMze/ZsBgwYwOeff55u+Z07d3I0dDHtxR0WFpZhXVhYWIYOXA/j5uZmGk1Vv3596tevT/Xq1Rk2bBiHDx/GysoKLy8v9uzZg1IqXZ3Dw8NJTU01PW/Lli0jPj6eJUuWpHv+Dh8+nOG4wcHBzJ8/H6UUR48eZcaMGXzyySc4ODjkaGRF27Zt+eWXX1i2bFmej8woVqzYQzs7Puitt97iwoULpta6AQMGmNZ5e3uj0WjYvn17pl9o2fmSy4qHvVYg44dlVl7baR0iH/VcpL02xo4dS48ePTItU7FiRQCcnJwYP34848eP59atW6ZWls6dOz+y4/Ls2bNp1qwZP/30U7rlsbGxj63Do7Ru3Zp169axYsUKevfunWG9Uorly5fj6elJ7dq106377rvvWLBgAe3bt2fp0qWmD/bHSTsPoaGhGZLAmzdvmp7PNA92hIeM5zSrn39psvO5lp19N27cmMaNG6PX69m/fz+TJ0/m9ddfx9fXN9Pn93G8vLwIDQ3NsPzmzZum2NL06dOHMWPGMGPGDD777DP+/PNPunXrlq5lxNvbGwcHB/7444+H1vW/svM8Pam0Y0+ePDnd6M3/yixx/a8WLVpQrVo1pkyZgrOzMwcPHmT27NkZjhMSEsJnn32W6T7SEsH58+ej1WpZuXIl9vb2pvUPmxfrYc9V165d6dq1K8nJyezevZsvvviCvn37EhQURMOGDR9Zn0cpMMlK2pdj2odpp06dmD9/Pnq9nvr16z90u7Zt22JjY8OFCxeyfHknqzQaTYYvn3/++YcbN25Qrly5bO+vQYMG2NvbM2fOnHSx7ty5kytXrmQ5WXlQ+fLlefvttxk/fjwLFiygT58+tGzZkoULF7Js2TK6d+9uKjtr1iwA0yiotBfkf+uplOLXX3996PE0Gg3Vq1fnu+++Y8aMGekmbstOq0HXrl0JDg7miy++oFOnTpmOCEprmn/S4eXt27fno48+YtOmTbRo0eKRZa2srPj5559xdnZm0KBBxMfHM3ToUMD4uvzyyy+5ceMGvXr1eqKYsmLjxo3cunXL9KGm1+tZsGABZcuWzXJL0X899dRTuLm5MW3aNHr37p3pB1LFihUpX748R44cyZCoP4qvry+DBg3iyJEjTJo06ZHTAmT23jp69Ci7du1K1+KRlVaz/3rppZf45ptvGDt2LC1atMDHxyfd+q+//prTp0/z5ZdfZhh9aG9vz5IlS+jXrx9dunRhwYIFdO3a9bGxpL2eZs+ebWomB9i3bx+nTp0y/eeaJjY2luXLl6e7jJA270uTJk2ArH/+5URO9m1tbU39+vWpVKkSc+bM4eDBg/Tu3Tvb56dly5Z88cUXHDx4MF3rwKxZs9BoNDRv3ty0zMPDg27dujFr1iwaNmxIWFhYhlEnnTp14vPPP8fLy4vSpUtnKYasys5nWWYaNWqEu7s7J0+eTHfZJrtGjhzJq6++SnR0NL6+vjz77LPp1nfq1IlVq1ZRtmzZR17i0mg02NjYYG1tbVqWmJjIn3/+maO47OzsaNq0Ke7u7qxdu5ZDhw4VvmTl+PHjputZd+/eZcmSJaxfv57u3bubXnC9e/dmzpw5dOjQgVGjRlGvXj20Wi3Xr19n8+bNdO3ale7duxMUFMQnn3zC+++/z8WLF01ztty6dYu9e/ea/vPLiU6dOjFjxgwqVapESEgIBw4c4JtvvsnRlwQY33xvvvkm//vf/3jppZd49tlnuXbtGuPGjcvWZaDMvPnmm0ybNo3x48fTq1cvBgwYwI8//sjAgQO5fPkywcHB7Nixg88//5wOHTqY+m60bt0aW1tb+vTpw9tvv01SUhI//fQTkZGR6fa/cuVKpk6dSrdu3ShTpgxKKZYsWUJUVBStW7c2lQsODmbLli2sWLECf39/XFxcTP+FP8ja2tr0H2zDhg0ZOnQozZs3x8nJiStXrrBo0SJWrFiRIZaceP31101fPu+++y716tUjMTGRrVu30qlTp3Qfkmm+/fZbXFxcGDZsGHFxcbz11ls0atSIV155hRdeeIH9+/fTpEkTnJycCA0NZceOHQQHB5sSm9zg7e1NixYt+PDDD3FycmLq1KmcPn06w/DlrHJ2dubbb7/lpZdeolWrVrz88sv4+vpy/vx5jhw5Yuo39vPPP9O+fXvatm3LoEGDCAgIICIiglOnTnHw4EH++usvwNiy16lTJ0JCQvDw8ODUqVP8+eefNGzY8JEJZqdOnfj000/5+OOPadq0KWfOnOGTTz6hdOnS6a51u7i4UKpUKf7++29atmyJp6cn3t7eD03s3d3dWbJkCZ06daJ27dq89dZbVK9enZiYGBYsWMCcOXN47rnnTMOQH6TVapk3bx4vvfQSPXv2ZNasWabLDsHBwQB8//33DBw4EK1WS8WKFalYsSKvvPIKkydPxsrKivbt23P58mU+/PBDAgMDGT16dLpjeHl5MXToUK5evUqFChVYtWoVv/76K0OHDjVdGs3q519OZHXf06ZNY9OmTXTs2JGSJUuSlJRkasFI+/zI7vkZPXo0s2bNomPHjnzyySeUKlWKf/75h6lTpzJ06NAMfSQGDx7MggULGD58OCVKlMjQ5+z1119n8eLFNGnShNGjRxMSEoLBYODq1ausW7eON954I8fJXlpL8oIFCyhTpgz29vam10BWODs7M3nyZAYOHEhERAQ9e/bEx8eH27dvc+TIEW7fvp2hZTEz/fr1Y+zYsWzbto0PPvgAW1vbdOs/+eQT1q9fz1NPPcXIkSOpWLEiSUlJXL58mVWrVjFt2jRKlChBx44dmThxIn379uWVV17h7t27TJgwIVutwR999BHXr1+nZcuWlChRgqioKL7//nu0Wi1NmzY1lWvZsiVbt27NXr+VbHXHzWOZjQZyc3NTNWrUUBMnTswwKkSn06kJEyao6tWrK3t7e+Xs7KwqVaqkhgwZos6dO5eu7LJly1Tz5s2Vq6ursrOzU6VKlVI9e/ZMNzxs4MCBysnJKcvxRkZGqhdffFH5+PgoR0dH9fTTT6vt27erpk2bpusl/uDQxzRpo0v+O9TTYDCoL774QgUGBipbW1sVEhKiVqxYkWGfD5PZ0OU0P/74Y7phsXfv3lWvvvqq8vf3VzY2NqpUqVJq7NixGZ7nFStWmJ7jgIAA9dZbb6nVq1crwDSM9PTp06pPnz6qbNmyysHBQbm5ual69eqpGTNmpNvX4cOHVaNGjZSjo2OWRzhFRUWpTz/9VNWqVUs5OzsrrVarSpYsqfr166f+/fdfU7m00UD/HQqqVMYRL2nP04OjkiIjI9WoUaNUyZIllVarVT4+Pqpjx46mYegPDl1OkzYK5KOPPjIt++OPP1T9+vWVk5OTcnBwUGXLllUDBgxIN8Q5s5EYShlfh6VKlXrs88K94axTp05VZcuWVVqtVlWqVEnNmTMn0/o/OCLiYc+NUkqtWrVKNW3aVDk5OSlHR0dVpUoV9dVXX6Urc+TIEdWrVy/l4+OjtFqt8vPzUy1atFDTpk0zlXn33XdVnTp1lIeHh7Kzs1NlypRRo0ePNg2rfJjk5GT15ptvqoCAAGVvb69q1aqlli1blulzs2HDBlWzZk1lZ2engCyNNrt69ap67bXXVJkyZZStra1yc3NTTZo0UbNnz84wCiqz96/BYDBNqfDrr7+alo8dO1YVL15cWVlZpXt/6PV69dVXX6kKFSoorVarvL29Vb9+/dS1a9fSHSvtNbFlyxZVp04dZWdnp/z9/dV7772XYeRVVj//HvWZ8LDXYFb2vWvXLtW9e3dVqlQpZWdnp7y8vFTTpk3V8uXL0+0ru+fnypUrqm/fvsrLy0tptVpVsWJF9c0335hGmP2XXq9XgYGBClDvv/9+pvuLi4tTH3zwgapYsaLpXAcHB6vRo0enG0mX9n7KqsuXL6s2bdooFxcXBZhel9n5vFfKOAVGx44dlaenp9JqtSogIEB17Ngxw/aPMmjQIGVjY6OuX7+e6frbt2+rkSNHqtKlSyutVqs8PT1V7dq11fvvv59uGP8ff/yhKlasaHqvfvHFF+r333/P9PMzs9fUypUrVfv27VVAQICytbVVPj4+qkOHDmr79u3pyuVk6LJGKQu4YYwQIts0Gk2GUXJCiKIlJSWFoKAgnn766QyTMhYmFnkZSAghhBAPd/v2bc6cOcP06dO5detWob49BEiyIoQQQhQ4//zzDy+88AL+/v5MnTo1XYfkwkguAwkhhBDColnkpHBCCCGEEGkkWRFCCCGERZNkRQghhBAWrdB3sDUYDNy8eRMXF5d8nUpZCCGEKOiUUsTGxlK8eHGsrMzXvlHok5WbN29muCGZEEIIIbLu2rVrOZ6dPTcU+mQl7aZb165dy/LdlB9Hp9Oxbt062rRpk+H+IYWZ1Lto1RuKbt2l3lLvoiAr9Y6JiSEwMDDDzTHzW6FPVtIu/bi6uuZqsuLo6Iirq2uRe2FLvYtOvaHo1l3qLfUuCrJTb3N3o5AOtkIIIYSwaJKsCCGEEMKiSbIihBBCCItW6PusZIVSitTUVPR6fZbK63Q6bGxsSEpKyvI2hYHU21hva2trbGxszH4NVwghiooin6ykpKQQGhpKQkJClrdRSuHn58e1a9eK1BeW1Pt+vR0dHfH398fW1tbM0QkhROFXpJMVg8HApUuXsLa2pnjx4tja2mbpS9hgMBAXF4ezs7NZJ8nJb1JvZzQaDSkpKdy+fZtLly5Rvnz5IvVcCCGEORTpZCUlJQWDwUBgYCCOjo5Z3s5gMJCSkoK9vX2R+qKSehvr7eDggFar5cqVK6blQggh8k7R+cZ5hKL0xStyh7xmhBAi/8gnrhBCCCEsmiQrQgghRGFwYCaEHTd3FHlCkhVhVhqNhmXLlpk7DCGEKNjOroUVo+D3NhBxydzR5DpJVgqgQYMGodFoTD9eXl60a9eOo0ePmi2moKAgUzyOjo5Uq1aNn3/++bHbhYaG0r59+3yIUAghCqnwU7DoRUBBcE/wCDJ3RLnOrMnKtm3b6Ny5M8WLF8/wH7ZOp+Odd94hODgYJycnihcvzoABA7h586b5ArYg7dq1IzQ0lNDQUDZu3IiNjQ2dOnXK8+PqdLqHrvvkk08IDQ3l6NGjdOvWjVdffZUFCxZkWjYlJQUAPz8/7Ozs8iRWIYQo9BIiYF5vSImFUo2gwwQohPNgmTVZiY+Pp3r16kyZMiXDuoSEBA4ePMiHH37IwYMHWbJkCWfPnqVLly55GpNSioSU1Mf+JKbos1Quqz9KqWzFaWdnh5+fH35+ftSoUYN33nmHa9eucfv2bVOZGzdu8Nxzz+Hh4YGXlxddu3bl8uXL6fYzffp0KleujL29PZUqVWLq1KmmdZcvX0aj0bBw4UKaNWuGo6MjCxcufGhMLi4u+Pn5Ua5cOf73v/9Rvnx5UwLarFkzhg8fzpgxY/D29qZ169ZAxstA169fp3fv3nh6euLk5ESdOnXYs2ePaf2KFSuoXbs29vb2lClThvHjx5Oampqt504IIQoFvQ4WDoDIy+BeEnr9CTaFc6JKs86z0r59+4deAnBzc2P9+vXplk2ePJl69epx9epVSpYsmel2ycnJJCcnmx7HxMQAxhaBB1sFdDodSikMBgMGgwGAhJRUqo1Lf9z8cHxcaxxts3Y6lFKmuAHi4uKYPXs25cqVw8PDA4PBQEJCAs2bN+fpp59my5Yt2NjY8Nlnn9GuXTsOHz6Mra0tv/76K+PHj+eHH36gZs2aHDp0iCFDhuDg4MDAgQNN+3/nnXf45ptv+O2339I9Z5nF9d/l9vb2prlsAGbOnMmrr77K9u3b05VNe/7j4uJo2rQpAQEBLFu2DD8/Pw4ePEhqaioGg4G1a9fSr18/Jk2aROPGjblw4QKvvvoqSik++uijJ3r+H/d8P1g/g8GAUgqdToe1tXWeHdvc0t4zj2pRK4yk3lJvi6cUVqvfxPrydpStE6nPzgFbV8hGHbJSb0t5TgrUpHDR0dFoNBrc3d0fWuaLL75g/PjxGZavW7cuw8RvNjY2+Pn5ERcXZ7oskZhinnvexMbEkmqbtS89nU7HP//8g6urK2BsofLz82P+/PnExcUBMHv2bAC+/fZb06y8kyZNIigoiFWrVtGiRQs+/fRTPvnkE1q1agVAq1atGDp0KD/99BPdu3c37WvIkCGmMgCxsbEZYjIYDCQlJRETE0NqaioLFy7k2LFjDBw40LSsdOnSvP/++6Zt0hLJxMREYmJimDFjBrdv32bDhg14eHgAxstdaWU//fRTRo0aRffu3QHw9vbm3XffZdy4cbz++utZeu6exH/rnZKSQmJiItu2bSsSLTsP/uNQVEi9i5aCVO/StzcQcn0WCg17SrzCrf2XgJx1rH1UvbNzK5q8VGCSlaSkJN5991369u1r+pLOzNixYxkzZozpcUxMDIGBgbRp0ybDdklJSVy7dg1nZ2fTLKQuSnF8XOtHxqKUIi42DmcX51y7R46D1jrL+9JqtTRr1sx0ySYiIoKffvqJXr16sXv3bkqVKsXJkye5ePEigYGB6bZNSkoiNDSU5ORkbty4wciRI9N90aempuLm5oarqyvOzs4ANGrUCFdXV5RSxMbG4uLikiFWKysrxo0bx2effUZycjK2tra8+eabjBo1CisrK2xsbKhXr16m587BwQFXV1fOnDlDzZo1KVWqVKb1PnLkCIcOHWLixImmZXq9nqSkJGxsbLI1C3F2ZFbvpKQkHBwcaNKkSaGewVan07F+/Xpat26NVqs1dzj5Ruot9bZkmktbsT48BwBDiw+p3XBkjvaTlXqn/VNpbgUiWdHpdPTu3RuDwZCuT0Vm7OzsMu2wqdVqM5wMvV6PRqPBysoq3Yykzo9p1jcYDOiTrXGy05plJlONRoOzszMVKlQwLatbty5ubm78/vvv/O9//0MpRe3atZkzZ06G7YsVK0ZSUhIAv/76K/Xr10+33traOt1z4uLigpWVlekSSNpz9qC33nqLQYMGmW7y92BC87B7CqUdKy3ZeNhzajAYGD9+PD169MiwztHRMc/ORWb1trKyQqPRZPq6KoyKSj0fJPUuWgpEve9egCWDQekhpDfWjcdg/YT/ND+q3pbyfFh8sqLT6ejVqxeXLl1i06ZNj2xVKcrSvkgTExMBqFWrFgsWLMDHxyfT58zNzY2AgAAuXrzI888/nysxeHt7U65cuRxvHxISwm+//UZERASenp4Z1teqVYszZ8480TGEEKLASoyCuc9BUjSUqAudvy+UI38yY9HzrKQlKufOnWPDhg14eXmZOySLkZycTFhYGGFhYZw6dYoRI0YQFxdH586dAXj++efx9vama9eubN++nUuXLrF161ZGjRrF9evXARg3bhxffPEF33//PWfPnuXYsWNMnz493WWW/NSnTx/8/Pzo1q0b//77LxcvXmTx4sXs2rULgI8++ohZs2Yxbtw4Tpw4walTp1iwYAEffPCBWeIVQoh8o0+FRYPh7jlwDYDn5oC28F6CfpBZk5W4uDgOHz7M4cOHAbh06RKHDx/m6tWrpKam0rNnT/bv38+cOXPQ6/WmL+e0zrBF2Zo1a/D398ff35/69euzb98+/vrrL5o1awYYL4ts27aNkiVL0qNHDypXrszgwYNJTEw0tbS89NJL/Pbbb8yYMYPg4GCaNm3KjBkzKF26tFnqZGtry7p16/Dx8aFDhw4EBwfz5ZdfmkbbtG3blpUrV7J+/Xrq1q1LgwYNmDhx4kP7uAghRKGx/kO4sBG0jtBnHrj4mjuifGXWy0D79++nefPmpsdpHWMHDhzIuHHjWL58OQA1atRIt93mzZtNX8pF0YwZM5gxY8Zjy/n5+TFz5sxHlunbty99+/bNdF1QUFCW5395cP6WB23ZsiXT5Q/uv1SpUixatOih+2nbti1t27bNUkxCCFEoHJgJu+/11+z2E/hXN288ZmDWZKVZs2aP/DLM7kRpQgghRKFy+V/45w3j383eg6rdzBqOuVh0nxUhhBCiyIq8DAv7g0EHVbtD07cfWtRgULy39BgL913Lv/jykSQrQgghhKVJjoV5fSDhrvGyT9epDx35o5Ri/IoTzN1zlbFLj3H1rmVM5JabJFkRQgghLMmVXfBzUwg/Cc6+0Hse2GY+6aVSis9XnWLmritoNPD1MyGU9MqbCTLNyeLnWRFCCCGKhOQ42Dge9v4KKHDxh95zwS3goZtMXH+WX7cbp9n/vHswz9QukU/B5i9JVoQQQghzu7AJlo+C6KvGx7UGQOtPwcH9oZtM3niOyZvOAzC+S1X61Mv8Br+FgSQrQgghhLkkRsG69+GQ8eazuJeEzj9A2eaP3OyXbRf4dv1ZAN7vUJmBTwXlbZxmJsmKEEIIYQ6nV8HK0RAXBmig3ivQ8iOwc37kZjN3XubzVacBeLNNBV5uUiYfgjUvSVaEEEKI/BR/B1a/DccXGx97lYMuU6BUw8duOnfPVT5efgKAES3KMbxF+byM1GLIaKBCTKPRsGzZsoeu37JlCxqNhqioqCztr0WLFowdOzZ3gstj48aNyzDzsRBCmJVScGwR/FjPmKhorKDR6/DqjiwlKosOXOf9ZccAeKVJGca0rpDHAVsOSVYKqLCwMEaMGEGZMmWws7MjMDCQzp07s3Hjxizv46mnniI0NBQ3N7c8jPTJzJgxA41GY/rx9/c33YX7Ud58881sPRdCCJGnYkJh/vOw+EXj3Ck+VeGljdB6PGgdHrv58iM3eXvREZSCgQ1LMbZ9JTRF5I7LIJeBCqTLly/TqFEj3N3d+frrrwkJCUGn07F27Vpee+01Tp8+naX92Nra4ufnl8fRPjlXV1fOnDmDUorTp08zZMgQunTpwuHDh003OUyjlEKv1+Ps7Iyz86Ov+wohRL64fRZmdIT4cLDSQpM34ekxYGObpc3XHA9j9ILDGBT0qRfIx52rFqlEBaRlJSOlICX+8T+6hKyVy+pPNu6DNGzYMDQaDXv37qVnz55UqFCBqlWrMmbMGHbv3p2u7J07d+jevTuOjo6UL1/edHNIyPwy0L///kvTpk1xdHTEw8ODtm3bEhkZmWkca9aswc3NjVmzZgFw48YNnnvuOTw8PPDy8qJr167pbnA4aNAgunXrxoQJE/D398fLy4vXXnsNnU73yPpqNBr8/Pzw9/enefPmfPzxxxw/fpzz58+b6rB27Vrq1KmDnZ0d27dvz/Qy0B9//EHVqlWxs7PD39+f4cOHm9ZFR0fzyiuv4OPjg6urKy1atODIkSOPjEsIIR7r7gWY2dmYqPhUhSFbodm7WU5UNp2+xYh5B9EbFD1qBvBZt2CsrIpWogLSspKRLgE+L/7IIlaAe24f972bYOv02GIRERGsWbOGzz77DCenjOXd3dNHNn78eL7++mu++eYbJk+ezPPPP8+VK1fw9PTMsO3hw4dp2bIlgwcP5ocffsDGxobNmzej1+szlJ0/fz6vvPIKf/75J127diUhIYHmzZvTuHFjtm3bho2NDf/73/9o164dR48exdbW+MbcvHkz/v7+bN68mfPnz/Pcc89Ro0YNXn755Sw+UeDgYGwy/W+S8/bbbzNhwgTKlCmDu7s7W7duTbfNTz/9xJgxY/jyyy9p37490dHR/Pvvv4CxNaZjx454enqyatUq3Nzc+Pnnn2nZsiVnz57N8JwKIUSWRF6BmV2Mo318qsKgleCY8bP3Ybafu82rsw+i0ys6hfjzdc+QIpmogCQrBc758+dRSlGpUqUslR80aBB9+vQB4PPPP2fy5Mns3buXdu3aZSj79ddfU6dOHaZOnWpaVrVq1QzlfvrpJ95//33+/vtvmjc3zgUwf/58rKys+O2330zNk9OnT8fd3Z0tW7bQpk0bADw8PJgyZQrW1tZUqlSJjh07snHjxiwnK9evX+ebb76hRIkSVKhQgTt37gDwySef0Lp164du97///Y833niDUaNGmZbVrVsXMCZQx44dIzw8HDs7OwAmTJjAsmXLWLRoES+99FKWYhNCCJPoG8YWlZjr4F0BBizLVqKy5+JdXp61n5RUA22r+vLdczWwsS66F0MkWXmQ1tHYyvEIBoOBmNhYXF1csLLKpRePNmv3clD3Lhdl9XplSEiI6W8nJydcXFwIDw/PtOzhw4d59tlnH7m/5cuX8/vvv7Njxw7q1atnWn7gwAHOnz+Pi4tLuvJJSUlcuHDB9Lhq1arp+pn4+/tz7NixRx4zOjoaZ2dnlFIkJCRQq1YtlixZYmqtAahTp85Dtw8PD+fmzZu0bNky0/UHDhwgLi4OLy+vdMsTExPTxS6EEFkSG2ZMVKKugEdpGLAcnH2yvPnxG9G8OHM/SToDLSr5MLlPLbRFOFEBSVYy0mgefznGYACt3lgut5KVLCpfvjwajYZTp07RrVu3x5bXarXpHms0GgwGQ6Zl0y6vPEpwcDDHjh1j+vTp1K1b15Q0GQwGateuzZw5czJsU6xYsRzFk8bFxYWDBw9iZWWFr69vppe/MluW5nH1MhgM+Pv7s2XLlgzr5BKQECJb4u/ArK4QcQHcSsLAFeDqn+XNL96OY+Afe4lLTqV+aU+mPl8LW5uinaiAdLAtcDw9PWnbti0//vgj8fHxGdZndc6UzISEhDx2uG/p0qXZuHEjf//9NyNGjDAtr1WrFufOncPHx4dy5cql+3nSodFWVlaUK1eOMmXKPDIpeRgXFxeCgoIeWrdatWoRFhaGjY1Nhti9vb2fKHYhRBGSEGFMVG6fBpfiMHA5uAdmefPQ6ET6/76Xu/EpVAtw5beBdbDXWj9+wyJAkpUCaOrUqej1eurVq8fixYs5d+4cp06d4ocffqBhw8dPLPQwY8eOZd++fQwbNoyjR49y+vRpfvrpJ1O/kDQVKlRg8+bNLF68mNdffx2A559/Hm9vb7p27cr27du5dOkSW7duZdSoUVy/fv1Jqpsrxo0bx7fffssPP/zAuXPnOHjwIJMnTwagVatWNGzYkG7durF27VouX77Mzp07+eCDD9i/f7+ZIxdCFAhJ0fBnd7h1HJx8jC0qnqWzvHlkfAoDft/LjahEyng7MeOFerjYax+/YREhyUoBVLp0aQ4ePEjz5s154403qFatGq1bt2bjxo389NNPOd5vhQoVWLduHUeOHKFevXo0bNiQv//+GxubjFcLK1asyKZNm5g3bx5vvPEGjo6ObNu2jZIlS9KjRw8qV67M4MGDSUxMxNXV9UmqmysGDhzIpEmTmDp1KlWrVqVTp06cO3cOMF6KWrVqFU2aNGHw4MFUqFCB3r17c/nyZXx9fc0cuRDC4iXHwuyeEHoYHL2MLSre5bK8eVxyKoNm7ONceBz+bvbMerEe3s52eRdvAaRRKhsTfBRAMTExuLm5ER0dneFLMykpiUuXLlG6dGns7e2zvE+DwUBMTAyurq6518G2AJB63693Tl87BY1Op2PVqlV06NAhQ3+jwkzqbUH1jrwC1/ZCtR5glTeXRJ6o3ikJMKcnXPkX7N2Nw5P9grO8eXKqnhdn7GfH+Tt4OGr569WGlPNxefyGuSAr9X7Ud2h+kg62QgghLNdfg+DmQYi8BE3fNnc06emSYH4fY6Ji5wr9l2YrUdEbFKMXHGbH+Ts42loz/YV6+ZaoFDRF599jIYQQBUvoUWOiArD1awjP2q1E8kVqCizsDxe3gNYJ+i2GgFpZ3lwpxQfLjrHqWBi21lb8OqAONQLd8yzcgk6SFSGEEJbp0J/G3xorMOjg79fAkHFG7XyXmgKLXoBz68DGAZ5fCIH1Hr/df3y99gzz9l7DSgM/9KlBo3Iy8vBRJFkRQghheXRJcHSh8e/OPxgvs9zYD3ummTeuq3vg5yZweiVY20GfeRD0dLZ28cu2C/y0xTjh5Ofdg2lXLevzsBRVkqxwf1ZYIbJKXjNC5LHTKyEpClxLQI2+0OZT4/KNn0LExfyPJzEKVo6GP9rA7VPGUT995kLZ5tnazcJ91/h8lfFy1rvtK9G7Xsk8CLbwKdLJSlrv54SEBDNHIgqatNeMxYyYEKKwSbsEVKOvcRRQrYEQ1BhSE2H5yGzdqf6JKAUnlsKP9WD/H/di6gfD90O5Vtna1ZrjYby75CgAQ5qW4dWmZXM72kKrSI8Gsra2xt3d3XSvHEdHxyzdc8dgMJCSkkJSUlKRG8Jb1Out0WhISEggPDwcd3f3dPc5EkLkksgrxo6rADWfN/7WaKDLDzD1Kbi8HQ7OhNqD8jaOqKvwz5twbq3xsVc56DQJSjfO9q52XrjDyHmHMCh4rk4g77bL2s1ohVGRTlYA/Pz8AB56c7/MKKVITEzEwcEhyzcULAyk3vfr7e7ubnrtCCFy2eG5xt+lm4JH0P3lnmWg5Yew9j1Y9yGUaw1uAbl/fH2qsW/M5s9BFw9WWmg8Bp4eA9rszauklGLBvmt8vPwEKXoD7ar68Vn3akXqMzQ3FPlkRaPR4O/vj4+PDzqdLkvb6HQ6tm3bRpMmTYrUZQCpt7HeWq1WWlSEyCsGPRy+d0PUmv0zrq//qvGyzPV98M8Y6DPf2OqSW24eghWjIPSI8XHJhsbWFJ/st4TEJ6fywbLjLD10A4BWlX34vk8NbIr4HZRzosgnK2msra2z/AVkbW1Namoq9vb2RepLW+pdtOothFlc3ALR18DeDSp3yrjeyhq6TIGfG8PZNXBsEYQ8+8SHtdYnYbX+fdj3KyiD8fitP4GaAyAHl73P3opl6OwDXLgdj7WVhjfbVGRIkzJYWUmLSk5IsiKEEMJypHWsDe4FWofMy/hUgiZvwebPYPXbUKYZOBfL8SE159bR4tRYrHV3jQuqPQNtvwCXnN0bbNGB63yw7BhJOgO+rnZM7lOLeqU9cxyfkGRFCCGEpUiIgNP/GP+ulckloP96ejSc/Nt4l+M170DPP7J/vPi7sOZdbI4txAZQbiXRdPoOymdvlE+axBQ9H/19nL8OGO8037i8N989V0NuSpgL5MKZEEIIy3B0IehTwC8E/Ks/uqy1FrpOAY01HF8Mp1dl/ThKwfElxuHIxxaiNFac92lP6ivbc5yonA+Po9uP//LXgetYaeCN1hWY+YLcPTm3SLIihBDC/JS6fwkos461mSleE54aYfx75WjjxG2PExsGC/oZp8tPuAPFKqMfuIYTAX3A1ilHof99+AZdpuzgzK1YvJ3tmP1SfUa0LC/9U3KRJCtCCCHM7+Yh4yUda7vsdZht9q5x/pO4MFj3wcPLKQWH5hhbU06vBCsbaPoODNmKysYNCP8rSadn7JJjjJp/mIQUPQ3LeLFq1NM8VVbu85PbpM+KEEII80trVancGRw8sr6d1gG6TIbp7Y37qPZMxinwo64ZhyNf2Gh87F8duv4IfsHGx1mctuK/Lt2JZ9icg5wKjUGjgRHNyzGqVQWspTUlT0jLihBCCPNKSTAOQYbHd6zNTKmnoO7Lxr9XjITkOOPfBgPs+w2mNjAmKtZ20PJjeGnT/UQlB/45GkrnyTs4FRqDl5MtM1+ox5g2FSVRyUPSsiKEEMK8Tq2A5BhwLwlBTXK2j1YfG+ddiboKm/4H9V423kPoyg7j+sD6xvlZilXIcZjJqXo+++cUs3ZdAaBukAeT+9TCzy17s9qK7JNkRQghhHmZblrYL0cTsAFg5wKdv4fZPYxT5R+YDqlJoHU0tqbUe9k4oVwOXb2bwGtzD3LsRjQAQ5uV5Y3WFWQ22nwiyYoQQgjzibhovDEhGuMdlp9EuZZQ43njdP2pSVC6CXT+ATxLP9Fu1xwP461FR4hNSsXdUct3vWrQvJLPk8UqskWSFSGEEOZz6N59gMq2APfAJ99fuy+MrSx+Icbk5wnuG5SSauDL1af5499LANQq6c7kvrUIcH/IzLoiz0iyIoQQwjwM+vt3WM5Jx9rM2LtB+6+eeDfXIxMYPvcQh69FAfBy49K83a4SWrnsYxaSrAghhDCP8xsh9iY4eELFDuaOxmTjqVuMWXiE6EQdrvY2fNurBq2r5Ow+QSJ3SLIihBDCPA7NMv4OeQ5szD8tvU5vYML6U/y87SIA1Uu4MaVvLQI9Hc0cmZBkRQghRP6Luw1nVhv/zq1LQE8gKhn6/7GfA1ejABj0VBDvdaiMrY1c9rEEkqwIIYTIf0cXgCEVitcC36pmDWXbuTt8fdSa+NQoXOxs+LpnCO2D/c0ak0hPkhUhhBD5K91NC/uZLYyUVAMT1p3hl20XAQ1V/F34qV9tSnnl7IaGIu9IsiKEECJ/Xd8Pt0+DjQME9zRLCJfvxDNy/iGOXjdO8tbY18BPL9fD2VFmo7VEkqwIIYTIX2kda6t0NQ41zmfLDt3g/aXHiE/R4+ag5YtuVdFd3o+dNucz3Iq8JcmKEEKI/JMSD8eXGP/O54618cmpfPT3CRYfvA5AvSBPJvWuQTEnG1ZdztdQRDZJsiKEECL/nFgGKXHgWQZKNcq3wx6/Ec3IeYe4eCceKw2MbFme4c3LYWNthU6ny7c4RM6YdUzWtm3b6Ny5M8WLF0ej0bBs2bJ065VSjBs3juLFi+Pg4ECzZs04ceKEeYIVQgjx5Ew3LXz+iabCzyqlFL/vuESPqTu5eCcefzd75r3cgNdbyU0ICxKznqn4+HiqV6/OlClTMl3/9ddfM3HiRKZMmcK+ffvw8/OjdevWxMbG5nOkQgghnkj8XVg+Aq7uAo3Vk9+0MAvuxiXz4sz9fLryJCl6A62r+LJqZGPql/HK82OL3GXWy0Dt27enffv2ma5TSjFp0iTef/99evToAcDMmTPx9fVl7ty5DBkyJD9DFUIIkRMGAxycCRvHQ2KkcdnTY8C1eJ4eduf5O7y+4DDhscnY2ljxYcfK9GtQCk0+tOaI3GexfVYuXbpEWFgYbdq0MS2zs7OjadOm7Ny586HJSnJyMsnJyabHMTExAOh0uly7Lpm2n6J2nVPqXbTqDUW37lLv3Km35uYhrNa8jVXoIQCUT1X07b5CBTaAPHpuE1P0TN16kZ+3X0IpKFvMiUm9Qqjk50Jqamqm28j5fni9LeU50SillLmDANBoNCxdupRu3boBsHPnTho1asSNGzcoXvx+Bv7KK69w5coV1q5dm+l+xo0bx/jx4zMsnzt3Lo6Ocn8HIYTIa9rUOCqHLiLozmY0KHRW9pz2f4ZLxVqhNHkzPDhFD//e0rDxphWxOmPrSUMfA92DDNjJiOQcS0hIoG/fvkRHR+Pq6mq2OCy2ZSXNg012SqlHNuONHTuWMWPGmB7HxMQQGBhImzZtcu2J1ul0rF+/ntatW6PVanNlnwWB1Lto1RuKbt2l3jmstzKgOTof603j0STcBcBQ9RloOZ5KLn5UyuV4AZJ0eubvv84v2y5xOy4FgBLu9rzdtgLtq/llaR9yvh9e77SrE+ZmscmKn5/xRRYWFoa///17NISHh+Pr+/BbddvZ2WFnl/HunVqtNtdfhHmxz4JA6l30FNW6S72zIfQorHoTru0xPi5WCTpMwKp04zwZyZGk0zN/71WmbrlAeKzx0n+AuwMjWpTjmdol0OZgpI+c78zXWQKLTVZKly6Nn58f69evp2bNmgCkpKSwdetWvvrqKzNHJ4QQAoCkaNj8Oez9BZQBtE7Q7F1oMBSsc/+LLkmnZ8G+a0zdcp5bMfeTlNeal6Nn7RJyl+RCyqzJSlxcHOfPnzc9vnTpEocPH8bT05OSJUvy+uuv8/nnn1O+fHnKly/P559/jqOjI3375v2QNyGEEI9gMBjvnLz+I4gPNy6r2h3afAZuAbl+uORUPQv3XePHzRcIi0kCoLibPa+1KMeztQMlSSnkzJqs7N+/n+bNm5sep/U1GThwIDNmzODtt98mMTGRYcOGERkZSf369Vm3bh0uLi7mClkIIcT1/bD6bbhxwPjYqxx0+AbKtsj1Q6WkGli4/xpTN5/nZrQxSfF3s2dY83L0qlMCOxvpPVsUmDVZadasGY8ajKTRaBg3bhzjxo3Lv6CEEEJkLiYUNoyDo/ONj22docmb0GAY2GTsK/ikohJSeGHGPg5djQLA19WO15qX47m6gZKkFDEW22dFCCGEhdAlwe4fYdu3oIs3LqvRD1p+BC4PH/DwJMJjkuj/+17O3IrFzUHL6Fbl6V2vJPZyZ+QiSZIVIYQQmVMKTq+Ete9D1BXjshL1oP2XEFA7zw579W4C/X7fw9WIBHxc7PjzxfpU9JPL/0WZJCtCCCEyunUC1rwLl7YZH7v4Q+tPIPjZPL0B4ZmwWPr/vofw2GRKejoy56X6BHrKhJ5FnSQrQgghTLSpsViteQcOTjcORba2g0YjodHrYOecp8c+dDWSQdP3EZ2oo6KvC3++WA8fV/s8PaYoGCRZEUIIAYDm0J+0OvkB1vp7/VKqdDW2pngE5fmxd5y7wyt/7ichRU/Nku5MH1QXd0fbPD+uKBgkWRFCCAE7p2Cz7n3AeMNBTfuvoHTjfDn0muOhjJx3mBS9gcblvZnWrzZOdvL1JO6TV4MQQhR1+6fDvUTljF9XyrzwM1o7h3w59ML913h38VEMCtpX82NS7xoyLFlkIMmKEEIUZccWwcrRAOgbjuR0Ym3KWOXPV8Nv2y/yv39OAdCrTgk+7x6MTQ7u6SMKP3lVCCFEUXV6FSx5BVBQ9yUMzT/M05E+aZRSfLvujClReblxab56JkQSFfFQ0rIihBBF0cUt8NcgUHoI6Q3tvwG9Ps8PazAoxq04waxdxnlb3mpbkWHNyqLJhyRJFFySrAghRFFzdQ/M6wP6ZKjUCbr+CFZWeZ6sJKfqeXvRUf4+fBONBj7pWo3+DUrl6TFF4SDJihBCFCWhR2HOs6BLMN54sOcfYJ33XwW3YpJ4dfYBDl2NwsZKw7e9qtO1Ru7fnVkUTpKsCCFEUXH7LPzZHZKjoWRDeG52ntyA8EEHrkTy6uwD3I5NxtXehil9a9GkQrE8P64oPCRZEUKIoiDyMszqCgl3wL869F0Atk55ftj5e6/y4d/H0ekVFXyd+aV/HYK88/64onCRZEUIIQq7mFBjohJ7E4pVgn5Lwd4tTw+Zkmrg05Un+XO3sSNtu6p+TOhVHWeZ7E3kgLxqhBCiMIu/C392M7aseARB/2Xg5JWnh7wdm8xrcw6y93IEGg2MaVWB15qXw8pKRvyInJFkRQghCqukaJjdA26fBpfiMOBvcPXP00MevR7FkD8PEBqdhIudDd89V4NWVXzz9Jii8JNkRQghCqOIS7BsKIQeBkcvY6KSxzckXHLwOmOXHCM51UCZYk780r8O5Xzy9k7NomiQZEUIIQoDgx6u74ezq+HMamNrCoCdG/RfCsUq5NmhU/UGvlh9mt93XAKgZSUfvutdA1d7bZ4dUxQtkqwIIURBlRwHFzYZk5NzayHh7v11Gmso9RS0/sQ4+iePRMSnMHzuQXZeMB57ZItyvN6qgvRPEblKkhUhhChIoq7B2TXGBOXydtCn3F9n5wblW0PF9lCuJTh45GkoJ25GM+TPA1yPTMTR1pqJvarTrlre9okRRZMkK0IIYemSYmD/H8Y7JN86ln6dR2mo2AEqtjNO9Gad95delFLM3XuV8StOkpJqoKSnI78OqENFP5c8P7YomiRZEUIISxV/F/ZMg70/G0f2AGisILA+VGhnbEHxrpAvd0o2hZScyntLj/H34ZuAsX/Kt72q4+5om28xiKInR8mKXq9nxowZbNy4kfDwcAwGQ7r1mzZtypXghBCiSIq5CTunwIHpxnv4gDEpaTjceOPBPJ4n5WFOh8UwbM5BLt6Ox9pKw9ttK/Jy4zLSP0XkuRwlK6NGjWLGjBl07NiRatWqya29hRAiN0Rcgn8nweG59/ui+FeHxm9Apc7GOyObycL91/jo7+Mk6Qz4udozpW9N6gR5mi0eUbTkKFmZP38+CxcupEOHDrkdjxBCFD3hp2D7RDi+CNS9luqST0GTN6Bsy3y9zPOghJRUPlx2gsUHrwPQpEIxvutVHS/nvL8BohBpcpSs2NraUq5cudyORQghipYbB4xJyumV95eVa2VsSSn1lPniuud8eCxDZx/kXHgcVhp4o01FhjYtK5d9RL7LUbLyxhtv8P333zNlyhS5BCSEENkVcxP+Hg4XNt5boIEqXeDpMVC8hjkjM1l66DrvLTlOok5PMRc7fuhdk4ZlzdNXRogcJSs7duxg8+bNrF69mqpVq6LVph8qt2TJklwJTgghCp27F2BWN4i+apy4LeQ5eHp0ns4wmx0penh/2QkWHrgBQKNyXkx6ribFXOSyjzCfHCUr7u7udO/ePbdjEUKIwi3sGPzZA+LDwbMsPP8XeJU1d1Qml+7E891xa24m3ECjgVEtyzOiRXms5bKPMLMcJSvTp0/P7TiEEKJwu7ob5vSC5GjwC4Z+S8G5mLmjAsBgUMzcdZmv15wmUafBy8mWH/rUpFE5b3OHJgTwhJPC3b59mzNnzqDRaKhQoQLFilnGG08IISzK+Q0wvx+kJhpnme0zHxzczR0VAOfD43hn8VEOXIkEoLyrgRmvNiTAU+6WLCxHjpKV+Ph4RowYwaxZs0wTwllbWzNgwAAmT56Mo6NjrgYphBAF1vElsOQVMOigXGvoNQtszf8Zmao38Mv2i0zacI6UVAPOdja81aY8rreP4SP9U4SFydEMQ2PGjGHr1q2sWLGCqKgooqKi+Pvvv9m6dStvvPFGbscohBAF04EZsGiwMVGp2gN6z7WIROXkzRi6Tf2Xr9ecISXVQLOKxVg3ugl96wUi3VOEJcpRy8rixYtZtGgRzZo1My3r0KEDDg4O9OrVi59++im34hNCiIJpxyTY8LHx7zqDocMEsLI2a0jJqXp+3HSeqVsukGpQuDlo+ahTFXrUCkCj0aDT6cwanxAPk6NkJSEhAV9f3wzLfXx8SEhIeOKghBCiwFIKNowzTpsPxrlTWn5k1lloAQ5fi+LtRUc4eysOgLZVffm0WzV8XOzNGpcQWZGjZKVhw4Z8/PHHzJo1C3t74ws9MTGR8ePH07Bhw1wNUAghCgyDHv4ZY7z8A9D6E2g0yqwhJabo+W7DWX7bfhGDAm9nW8Z3qUaHYD+Z1FMUGDlKVr7//nvatWtHiRIlqF69OhqNhsOHD2Nvb8/atWtzO0YhhLB8qSmw9BU4sRQ0VtBpEtQeaNaQ9ly8yzuLj3L5rrHFu3vNAD7qVAUPJ1uzxiVEduUoWalWrRrnzp1j9uzZnD59GqUUvXv35vnnn8fBwSG3YxRCCMuWkgAL+xuHKFtp4ZnfoGo3s4WTpNPz9Zoz/PHvJQD8XO35rHs1WlbOePleiIIgx/OsODg48PLLL+dmLEIIUbCEn4bDc+DoAoi7BVpHeG42lGtptpBOhcbw+vzDnLkVC0DvuoG817Eyrvbax2wphOXKcrKyfPly2rdvj1arZfny5Y8s26VLlycOTAghLFJiFBxfbExSbhy4v9zZzziHSsn6ZgnLYFD88e8l43BkvQFvZ1u+7hlCi0rSmiIKviwnK926dSMsLAwfHx+6dev20HIajQa9Xp8bsQkhhGUw6OHiFmOCcmol6JONy61soHxbqNEXyrcBG/P0BQmNTuTNv47w7/m7ALSq7MOXz4Tg7SyTu4nCIcvJStpMtQ/+LYQQhVbEBTi+EI7Mh5gb95f7VIWaz0NwL7Pf3+efo6G8t/QY0Yk67LVWfNipCn3rlZSRPqJQyVGflVmzZvHcc89hZ5c+a09JSWH+/PkMGDAgV4ITQoh8lRwL4aewun6Qp8/+hvbQufvrHDwg+FljK4p/DbPPmxKbpGPc8pMsPngdgJASbnz3XA3KFpN7+ojCJ0fJygsvvEC7du3w8fFJtzw2NpYXXnhBkhUhhGXTp8Ld8xB+Am6dhFsnjH9HXQXAGvAClMYKTblWUON5qNgebCzjssr+yxGMXniYaxGJWGlgWLNyjGpVHq11ju6gIoTFy1GyopTKtInx+vXruLm5PXFQQgiRa1Li4couuHUcwk8ak5M7Z0Cfknl5F38MxSpzKqkYFXp+gNazZP7G+wg6vYEfNp7jx83nMSgo4eHAd8/VoG6Qp7lDEyJPZStZqVmzJhqNBo1GQ8uWLbGxub+5Xq/n0qVLtGvXLteDFEKIbNHr4MImOPYXnP4HdJncBsTWGXyqgG8VYx8U3yrGx46e6HU6zq9aRQUX//yP/SEu3Ynn9fmHOHI9GoAetQIY36UqLjIkWRQB2UpW0kYBHT58mLZt2+LsfP/aqK2tLUFBQTzzzDO5GqAQQmSJwQDX9hgTlBNLITHi/jr3khBQJ31i4lYSrArGZZMTN6N5/rc9RCXocHPQ8ln3anQKKW7usITIN9lKVj7+2HgH0aCgIJ577jnTfYGEEMJswo4bE5TjiyH62v3lTj5Q7Rljp9iAWmbvEJtTJ2/GmBKV6oHuTOtXC383mSlcFC056rMycKDxfhf79+/n1KlTaDQaKleuTO3atXM1OCGEyFTkFTi+CI4tMvZDSWPrAlW6QHBPCGoC1jmepNsinAqN4fnfdhOVoKNGoDuzXqwnM9GKIilH7+QbN27Qu3dv/v33X9zd3QGIioriqaeeYt68eQQGBuZmjEKIgiIhAu5eAFtHY58QOxfj7+xMlpaabJy6PjYMYkPv/Q67/zjmprGDbBprW6jQ1tiCUr4NaAtHq8PpMGOLSuS9FhVJVERRluOhyzqdjlOnTlGxYkUAzpw5w+DBg3nxxRdZt25drgYphLBwSsGh2bBmLKTEZlxvbXsveXE2tn7YOt3729mYXMTfuZ+M/LevyUNpoHQTY4JSuTM4uOd2jczqTFgsfX/dQ0R8CtVLuDFrsCQqomjLUbKyfft2du7caUpUACpWrMjkyZNp1KhRrgWXmprKuHHjmDNnDmFhYfj7+zNo0CA++OADrApIxzghCr3YMFgxCs6uMT52KmZMXlLiIDXJuEyfYkxCspSIANZ24OILLv7g4mf87fyfxz5VjOsLobO3Yun7624i4lMIKeHGrBfr4+YgiYoo2nKUrJQsWRKdTpdheWpqKgEBAU8cVJqvvvqKadOmMXPmTKpWrcr+/ft54YUXcHNzY9SoUbl2HCFEDh1fDP+8AYmRxtaT5u/DUyPAytq4Xq8zJi0p8ZAcZ/w7Ofbe73uPdYng5J0+GXHwKLAdYp/EuXuJyt34FKoFuPLnYElUhIAcJitff/01I0aM4Mcff6R27dpoNBr279/PqFGjmDBhQq4Ft2vXLrp27UrHjh0B4yikefPmsX///lw7hhAiB+Lvwj9j4OQy42O/EOj+s3FI8H9Za42Jh4NHvodY0Jy7FUufX3dzJy6FqsVdmf1ifdwcJVERAnKYrAwaNIiEhATq169vmhguNTUVGxsbBg8ezODBg01lIyKy2Oybiaeffppp06Zx9uxZKlSowJEjR9ixYweTJk166DbJyckkJyebHsfExACg0+kybQ3KibT95Nb+Cgqpd9GqN2Red83Z1VivGoMm/jZKY43h6TEYGo0xJiaF5DnK73N+4XY8/f7Yx524FCr7uTBjYG2ctJp8f80V1de61Pvh9baU50SjlFLZ3WjmzJlZLps2zDknlFK89957fPXVV1hbW6PX6/nss88YO3bsQ7cZN24c48ePz7B87ty5ODo65jgWIYo6m9R4gm/MoWTEDgBi7AM4WOoVoh1Lmzmygu1WIkw5YU2MTkOAo+K1KnqcpEFFWIiEhAT69u1LdHQ0rq6uZosjR8lKfpk/fz5vvfUW33zzDVWrVuXw4cO8/vrrTJw48aFJUGYtK4GBgdy5cyfXnmidTsf69etp3bo1Wm3R+VSRehetesP9urctb4vd6jFoYm+i0GBoOBxDk3fApnBODJlf5/zivRaV23EpVPJ1ZuYLdfB0ysYw71xWVF/rUu+H1zsmJgZvb2+zJytPNGNSeHg44eHhGAyGdMtDQkKeKKg0b731Fu+++y69e/cGIDg4mCtXrvDFF188NFmxs7PDzi7jnVG1Wm2uvwjzYp8FgdS7CEmJI+TaDOwPbTI+9iyDpttPWJdsgLV5I8sXeXnOL96Oo//0/cZExc+FuS83MGui8l9F8rWO1Pth6yxBjpKVAwcOMHDgQE6dOsWDDTMajQa9Xp8rwSUkJGQYomxtbZ0hORJC5IH4O9j81orSkZeMj+u9Aq3GGedIEU/kyt14+vy6m/DYZCr6ujDnpfoWk6gIYYlyPClchQoV+P333/H19UWTR0MMO3fuzGeffUbJkiWpWrUqhw4dYuLEiek68Aoh8sixv9BEXiJR64H22d+xqdDS3BEVCuExSfT/fS+3YpKp4OvMnJfr4+WcsTVYCHFfjpKVS5cusWTJEsqVK5fb8aQzefJkPvzwQ4YNG0Z4eDjFixdnyJAhfPTRR3l6XCEEcPs0AFc9G1OmdBMzB1M4RCfoGPDHXq5GJFDKy5HZL9XHWxIVIR4rR8lKy5YtOXLkSJ4nKy4uLkyaNOmRQ5WFEHnk9lkAYu2LmzmQwiEhJZXBM/dxOiwWHxc7Zr9YHx+XwtlBWYjclqNk5bfffmPgwIEcP36catWqZeiA06VLl1wJTghhRvdaVuIkWXliKakGhs4+yIErkbja2zDrxXoEespUCkJkVY6SlZ07d7Jjxw5Wr16dYV1udrAVQphJ/B1IjEChIc7e39zRFGgGg+KNv46w9extHLTWTH+hHpX8zDcEVIiCKEd3Axw5ciT9+/cnNDQUg8GQ7kcSFSEKgdtnjL/dAtFbSZ+KnFJK8fHyE6w4chOttYaf+tWidim59YAQ2ZWjZOXu3buMHj0aX9/CeddTIYq8O8ZkRXlXMHMgBdt3G87x5+4raDQwsVcNmlX0MXdIQhRIOUpWevTowebNm3M7FiGEpbjXuVaSlZyb/u8lfth4DoBPulajc3Xp+yNETuWoz0qFChUYO3YsO3bsIDg4OEMH25EjR+ZKcEIIM7nXuVZ5V4CbZo6lAFp66DrjV5wE4I3WFejfoJSZIxKiYMvxaCBnZ2e2bt3K1q1b063TaDSSrAhR0N0xtqzgXQFu3jFvLAXMxlO3ePOvowAMblSa4S3ydooHIYqCHE8KJ4QopJJjIeYGAMqrAiDJSlbtuXiXYXMOojcoetQK4IOOlfNshm8hipIc9VkRQhRiaa0qTj7g4G7WUAqSEzejeWnmfpJTDbSq7MNXz4RgZSWJihC5IUctK4+7N88ff/yRo2CEEBbgXudailU0bxwFyKU78Qz8Yy+xyanUK+3JlL610FrL/4JC5JYcJSuRkZHpHut0Oo4fP05UVBQtWrTIlcCEEGZyr3OtJCuPp5RiycEbjFtxgtikVKoWd+W3gXWw11qbOzQhCpUcJStLly7NsMxgMDBs2DDKlCnzxEEJIczI1LlWkpVHuR2bzHtLj7H+5C0Aqge68/vAOrjaax+zpRAiu3KtndLKyorRo0fz3Xff5dYuhRDmkDZ7bTGZY+VhVh0Lpc13W1l/8hZaaw1vta3I4lcbyh2UhcgjOWpZeZgLFy6Qmpqam7sUQuSn1GSIvDfaT1pWMohKSOGjv0+w/Ihx8pnK/q58+2x1qhSXe/0IkZdylKyMGTMm3WOlFKGhofzzzz8MHDgwVwITQpjB3QugDGDnBi5+IP98mGw6fYt3Fx8jPDYZaysNw5qVZUSL8tjaSEdaIfJajpKVQ4cOpXtsZWVFsWLF+Pbbbx87UkgIYcHu/OcSkMwPAkBsko7/rTzFgv3XAChbzIlve9WgRqC7eQMTogjJUbIi9wUSopBK668il4AA2HXxLmOXnuRGVCIaDbzYqDRvtq0oo32EyGc5SlYSExNRSuHo6AjAlStXWLp0KVWqVKFNmza5GqAQIh9J51oAElJSWXTJiu27DgBQ0tORCc9Wp15pTzNHJkTRlKNkpWvXrvTo0YNXX32VqKgo6tWrh62tLXfu3GHixIkMHTo0t+MUQuSHIjxsWSnFiZsxrDkextJD17kRZeyL0q9BSca2r4yTXa6ORxBCZEOO3n0HDx40DVFetGgRfn5+HDp0iMWLF/PRRx9JsiJEQWTQw51zxr+LSMuKUooj16NZfTyU1cfCuBqRYFrnbquY2Kc2LSr7mzFCIQTkMFlJSEjAxcUFgHXr1tGjRw+srKxo0KABV65cydUAhRD5JOoK6JPBxh7cS5k7mjxjMCgOXo1k9fEw1hwP40ZUommdvdaKZhV8aFOlGKlXDtG4nLcZIxVCpMlRslKuXDmWLVtG9+7dWbt2LaNHjwYgPDwcV1eZb0CIAimtv4pXebAqXB1I9QbFvssRrD4WypoTYdyKSTatc7S1pkUlHzoE+9OsYjEcbW3Q6XSsun7oEXsUQuSnHCUrH330EX379mX06NG0bNmShg0bAsZWlpo1a+ZqgEKIfFIIO9caDIrpOy/z05bz3IlLMS13sbOhVRVf2lfzo0mFYjK6RwgLl6NkpWfPnjz99NOEhoZSvXp10/KWLVvSvXv3XAtOCJGPClnn2qt3E3hz0RH2XooAwM1BS5sqvrQP9qNROW/sbCRBEaKgyHH3dj8/P/z8/NItq1ev3hMHJIQwk0LSsqKUYs6eq3y+6hQJKXocba15r0NlnqsbiNZaZpsVoiDKUbISHx/Pl19+ycaNGwkPD8dgMKRbf/HixVwJTgiRT5S637JSrJJ5Y3kCodGJvL3oKNvP3QGgXmlPJvSsTkkvRzNHJoR4EjlKVl566SW2bt1K//798ff3RyPTcgtRsMWGQXIMaKzBs6y5o8k2pRRLDt5g3IoTxCalYmdjxdvtKvHCU0FYWcnnkxAFXY6SldWrV/PPP//QqFGj3I5HCGEOt08bf3uWBhtb88aSTbdjk3lv6THWn7wFQPVAd759tjrlfJzNHJkQIrfkKFnx8PDA01OmnRai0CignWtXHQvl/aXHiEzQobXW8HqrCgxpUgYb6ZsiRKGSo3f0p59+ykcffURCQsLjCwshLF8B61wblZDCyHmHGDbnIJEJOir7u/L3a0/zWvNykqgIUQjlqGXl22+/5cKFC/j6+hIUFIRWq023/uDBg7kSnBAin5ipZSUhJZWNp8JJTNFneZv4lFSmbrnA7dhkrK00DGtWlhEtymNrI0mKEIVVjpKVbt265XIYQgizMrWs5F+ycuRaFK8vOMylO/E52r5sMSe+7VWDGoHuuRuYEMLi5ChZ+fjjj3M7DiGEuSREQHy48W/vvL8MlKo38NOWC3y/8RypBoWPix3VAtyytY/gADeGNisrM88KUUQ80T3PDxw4wKlTp9BoNFSpUkWm2heiIEq7BORaAuzydgTNtYgERi84zP4rkQB0DPHns27VcHcsWCOQhBD5K0fJSnh4OL1792bLli24u7ujlCI6OprmzZszf/58ihUrlttxCiHySj50rlVKsfjgDcYtP0FccirOdjZ80rUq3WsGyDxNQojHylGPtBEjRhATE8OJEyeIiIggMjKS48ePExMTw8iRI3M7RiFEXsrjzrVRCSkMn3uIN/86QlxyKnWDPFg9qjE9apWQREUIkSU5allZs2YNGzZsoHLlyqZlVapU4ccff6RNmza5FpwQIh/kYefaHefu8MZfh7kVk4yNlYbRrSvwatOyWMusskKIbMhRsmIwGDIMVwbQarUZ7hMkhLBweZCsJOn0TFh7ht92XAKgjLcTk3rXIKSEe64dQwhRdOToMlCLFi0YNWoUN2/eNC27ceMGo0ePpmXLlrkWnBAij6XEQ/RV49+5dBnodFgM3X7815SoPF+/JCtHPi2JihAix3LUsjJlyhS6du1KUFAQgYGBaDQarl69SnBwMLNnz87tGIUQeeXOOeNvRy9w8srxbpRSnLgZw+rjofy6/RIpqQa8nGz56pkQWlXxzaVghRBFVY6SlcDAQA4ePMj69es5ffo0SimqVKlCq1atcjs+IUReeoLOtUk6Pbsu3mXjqVtsOhXOzegk07oWlXz46pkQirnY5VakQogiLFvJyqZNmxg+fDi7d+/G1dWV1q1b07p1awCio6OpWrUq06ZNo3HjxnkSrBAil2Vz2PKduGQ2nQ5n46lbbD93h4T/TJPvoLXm6fLedK5enM4h/jLSRwiRa7KVrEyaNImXX34ZV1fXDOvc3NwYMmQIEydOlGRFiILiTlqyUinT1UopbibAtK0X2XT2DoevRaHU/fW+rna0rOxL68q+NCzrJTPKCiHyRLaSlSNHjvDVV189dH2bNm2YMGHCEwclhMgnaS0rmUyzf+5WLEP+PMDFOzbAedPyagGutKzkS+sqvlQt7iotKEKIPJetZOXWrVuZDlk27czGhtu3bz9xUEKIfKDXQcRF498PDFtO0ul5be5BLt6Jx0ajaFS+GK2r+NGysg/+bg5mCFYIUZRlK1kJCAjg2LFjlCtXLtP1R48exd/fP1cCE0LksYiLYEgFW2dwDUi36n//nOTsrTi8nW0ZVTGB3t1qPfIfFSGEyEvZmmelQ4cOfPTRRyQlJWVYl5iYyMcff0ynTp1yLTghRB4yXQIqD/+5lLP2RBizdxvnXvn6mWq4yj0GhRBmlq2WlQ8++IAlS5ZQoUIFhg8fTsWKFdFoNJw6dYoff/wRvV7P+++/n1exCiFyU1rn2v8MWw6NTuSdxUcBeLlxaRqX82bVWXMEJ4QQ92UrWfH19WXnzp0MHTqUsWPHou4NC9BoNLRt25apU6fi6ysTQAlRIDwwzb7eoBi94DBRCTqqBbjyVttKoPSP2IEQQuSPbE8KV6pUKVatWkVkZCTnz59HKUX58uXx8PDIi/iEEHnlgWRl2tYL7L4YgaOtNT/0romtjRU6nSQrQgjzy9EMtgAeHh7UrVs3N2MRQuQXg+H+VPveFTl4NZKJ643Xe8Z1qUqZYs5mDE4IIdLL0Y0M89ONGzfo168fXl5eODo6UqNGDQ4cOGDusIQo2KKvQWoiWNsS4xjAqPmH0BsUnUL8ebZ2CXNHJ4QQ6eS4ZSU/REZG0qhRI5o3b87q1avx8fHhwoULuLu7mzs0IQq2e/cEUp5l+XD5aa5FJBLg7sBn3YNlkjchhMWx6GTlq6++IjAwkOnTp5uWBQUFmS8gIQqLe/1VbtiU5O/DN7G20vBDnxq4OchcKkIIy2PRycry5ctp27Ytzz77LFu3biUgIIBhw4bx8ssvP3Sb5ORkkpOTTY9jYmIA0Ol06HS6XIkrbT+5tb+CQupdeOptfeskVsDym8a+KcOblSGkuEuGOhbGumeF1FvqXRRkpd6W8pxolPrvbcksi729PQBjxozh2WefZe/evbz++uv8/PPPDBgwINNtxo0bx/jx4zMsnzt3Lo6OjnkarxAFRaMzn+KdcI4RKcM56dSQ4VX1WMnVHyHEAxISEujbty/R0dGZ3sQ4v1h0smJra0udOnXYuXOnadnIkSPZt28fu3btynSbzFpWAgMDuXPnTq490TqdjvXr19O6desiNQW51LuQ1FspUr8qg4M+lmf5mm+H98XfzT7TooWu7lkk9ZZ6FwVZqXdMTAze3t5mT1Ys+jKQv78/VapUSbescuXKLF68+KHb2NnZYWdnl2G5VqvN9RdhXuyzIJB6F2x7jp6mvj4Wg9Lwco82lPR2eew2haXu2SX1Llqk3pmvswQWPXS5UaNGnDlzJt2ys2fPUqpUKTNFJETBdjcumT/+XgNApJ0/baqXNnNEQgjxeBadrIwePZrdu3fz+eefc/78eebOncsvv/zCa6+9Zu7QhChwlFK8tegoxZIuA+BeMti8AQkhRBZZdLJSt25dli5dyrx586hWrRqffvopkyZN4vnnnzd3aEIUKEk6Pd+uO8um0+FUtLoJgLVPxcdsJYQQlsGi+6wAdOrUiU6dOpk7DCEKpORUPQv3XePHzRcIi0kCoGWxKIjAdE8gIYSwdBafrAghsi85Vc/C/deZuvk8odHGJMXfzZ6RLcvjv/2qsZC3JCtCiIJBkhUhCpGUVAN/HbjGj5vOc/NekuLnas+w5mV5rm4gdqlxsCrUWLhYBTNGKoQQWSfJihCFQEqqgcUHrzNl03luRCUC4Otqx7Bm5XiubiD2WmtjwVDjPYFw8Qd7NzNFK4QQ2SPJihAFmE5vYPGB60zZfJ7rkcYkpZiLHcOalaVPvZL3k5Q0d+5NBeAtrSpCiIJDkhUhCqCElFSWH77Jj1vOcy3CmKR4O9sxtFlZnq+fSZKS5t4NDKVzrRCiIJFkRYgCQinF/iuR/LX/Gv8cDSU+RQ+At7MtrzYty/P1S+Fg+5AkJc2de5eBpGVFCFGASLIixKMoheb6XsqHrUBzKhWCngJX/3wN4WZUIksOXmfRgetcvptgWl7Ky5F+9UvRr0EWkpQ00rIihCiAJFkRIjMxN+HIPDg8F5u756kCsOQv4zq3khBYDwLrG3/7VgPr3H0rJen0rD0RxqID19lx/g5ptxt1tLWmY7A/z9YJpG6QBxpNNm6VrEuEqCvGv2XYshCiAJFkRYg0uiQ48w8cmgMXN4MyAKC0joQ5VsbPPgVN+AmIvmr8Ob7IuJ3WEQJq30te6kOJOuDome3DK6U4fC2Kvw5cZ8WRm8QmpZrW1S/tybN1AmlfzQ8nuxy+be+eN9bJ3h2cfXK2DyGEMANJVkTRphTcPGhMUI4vgqTo++tKPgU1+pJaoSN7N26nQ4cOaA1JcOMAXNsL1/bAtX2QHA2Xtxt/0nhXhIBa4FMFfKuAT1Vw8YNMWkJS9Qb+OnCd33dc4nx4nGl5gLsDz9QuQc9aJSjp5fjkdf3vJaDstMgIIYSZSbIiiqa4cDi6wJik3D51f7lrCajRB6r3Aa+yxmU63f31di5QppnxB8BgMA4HvrbnfgJz97xx2Z30dwzHwcOYtPhWAZ8qGHyqsibcg2+23ODSnXgA7LVWdKjmT8/aJWhQxgsrq1xMKqRzrRCigJJkRRQdKfFwZjUc+wvOrQdlHE2DjT1U7gw1+kLppmCVxc6qAFZW4FPZ+FN7kHFZ/F24vhfCjsGtExB+0pjAJEbClR3GH4x3Ee0AVDMU46J9KdyDQqhUoRL2Hnqw10NsEjj7grU2Z/VNjoXYMIgNhdhbcH6Dcbl0rhVCFDCSrIjCTa+DC5uMCcrpf0B3fzQNJeoaE5SqPcDBPfeO6eQFFdsbf9LoEuH2GS6d3MfxQ7twizlLRatr+GqiKGl1m5Lchsv74fKDO9OAk7fxEpKLvzF5cfG/99jPuF9TQhJ2/++4W5AS9+DOjHyr5l5dhRAiH0iyIgofg8F4OebYX3BiKSRG3F/nURqCnzX+5OO9cU7d0TFhnY6Np4sDz2BrY8XAeqUYVs8Dj7jzxhaYu+f+k3CEQVwYGFIh/rbxJ+xY9g9s53ovwbmX7PhWhdLNcrl2QgiRtyRZEYWDUsYv/GN/wfHFEH3t/jqnYlDtGWOCElA7XzuXXrkbz8T1Z1l+5CZKgbWVhl51ShjvfuzmYCxUzB9KN864scEACXeNSUuG1pN7yYzW0ZiIpGtx8b+/zM453+oqhBB5RZIVUbBFXoZji4w//+0oa+ti7IcS8iwENcn1eVAeJyw6iSmbzzF/7zVSDcZJUjqG+PNG6wqUKZbFBMLKCpyLGX/8gvMwWiGEsGySrIiCJ+42nFxmbEW5tuf+cmtbKN/G2IJSoS1oHfIlHINBcf52HAeuRHLgSiQHr0Ry8d7oHoCmFYrxVtuKVAuQuxwLIUROSLIiCobkWDi9Co4thAub74/kQQNBT0NIL2NLioNHnocSl5zKkWtR95OTq5HpJnBLUzfIgzfaVKRBGa88j0kIIQozSVaE5UpNMQ63PfaXcchxauL9dcVrGltQqvbI83v1JOn07L+tYe+KUxy6Fs3psBjuXdkxcdBaUz3QjdqlPKhdyoOagR54ONnmaVxCCFFUSLIiLIvBAFd33hvJswySou6v8yx7byRPT/Auny/h7LscwVt/HeHyXWvgfqfdAHcHU2JSu5QHlfxcsLG2ypeYhBCiqJFkRViOyCuw6AXjdPZpnP3ujeTpaWxNyaeRPPHJqXy95jSzdl9BKXDVKp6pG0Td0l7UKumBn5t9vsQhhBBCkhVhKU7/A8uGGu/NY+sMVbsZW1GCGmdvRtlcsP3cbcYuOcb1SONlp561AqhtfYWe7Sui1eZwNlkhhBA5JsmKMC+9DjaMg11TjI9L1IWe08E9MN9DiU7U8dk/J1m4/zpgvNTz5TPBNAhyZ9WqK/kejxBCCCNJVoT5RF0zXva5vs/4uMFr0Goc2OR/x9T1J2/xwbJj3IpJBmBgw1K83a4STnY26P57I0MhhBD5TpIVYR5n18LSIcab+9m5QbepULlTvodxNy6Z8StOsvzITQBKezvx1TMh1Cvtme+xCCGEyJwkKyJ/6VNh06fw7yTj4+I14dkZ4BGUr2EopVh5NJSPl58gIj4FKw283KQMo1tVwF6bv31khBBCPJokKyL/xNyERYPh6i7j43pDoM2nYGOXr2Hcikniw2XHWXfyFgAVfV34umcI1QPd8zUOIYQQWSPJisgf5zfCkpeNN+azdYGuk6Fq93wN4eLtOH7fcYlFB66TnGrAxkrDa83L8VrzctjayBwpQghhqSRZEXnLoIctX8C2CYAy3pDv2ZngVTZfDq+U4sCVSH7ZdpH1p26h7s08W7OkO593D6ayv2u+xCGEECLnJFkReSf+Dvw1CC5vNz6uMxjafgHavJ9QTW9QrDsRxi/bL3LoapRpectKPrzcpAz1S3uiyacJ5oQQQjwZSVaySyk0V3dR7fpsUO3NHY3lun0W5j4LkZeNk7x1/t44C20eS0hJZdGB6/y2/RJXIxIAsLW2oketAF5qXJpyPi55HoMQQojcJclKdiVFYT2vF2VTE0m9vA0qtDJ3RJbn0jZY0M84G617Kei7EHwq5ekhb8cmM2vXZf7cfYWoBOO8KO6OWvo3KEX/hqXwcZHp8YUQoqCSZCW7HDww1OyP9b5fsNr5vSQrDzo0B1aMBEMqlKgHfeaBk3eeHe5OXDIT1p5hycEbpOgNAJT0dOSlxqXpWbsEjrbyEhdCiIJOPslzwFB/KJp9v2F1eRvcOAgBtcwdkvkZDLD5f7D9W+Pjqj2g20952j9lx7k7jF54mNuxxllna5Z0Z0iTMrSu4oe1lfRHEUKIwkKSlZxwC+SGR0MCI/81Tm7Wa5a5IzIvXSIsGwYnlhgfN34Tmr8PVnkzHFinNzBx/Vmmbb2AUlDB15nPugdTN0hmnRVCiMJIkpUcOufb0ZisnFwOd86Ddzlzh2Qecbdhfh/j/X2stNDlB6jRN88Ody0igRHzDnH4WhQAfeuX5MOOVXCwlVlnhRCisJKZsHIo1qEEhnJtAAU7fzB3OOZx+wz81tKYqNi7Q/+leZqorDhykw7fb+fwtShc7W346flafN49WBIVIYQo5CRZeQKGp0YZ/zgyD2JCzRtMfru4BX5rDVFXwKM0vLQBSjfOk0MlpKTyzqKjjJh3iNjkVGqX8mDVqMa0D/bPk+MJIYSwLJKsPAEVWB9KNgR9Cuyeau5w8o3m0J8w+xlIjobABvDSRvAunyfHOnkzhs6Td7Bg/zU0GhjRohwLXmlACQ/HPDmeEEIIyyPJypNq9Lrx9/7pkBhlzkjynjJQ5cYCbFaNNg5NDn4WBvwNTl65fyilmLnzMt2m/suF2/H4utox56X6vNGmIjbW8rIVQoiiRD71n1T5NuBTBVJiYf/v5o4m70RcwnpeL8qH/2N83PQd6PFrngxNjoxP4ZU/D/Dx8hOkpBpoWcmH1aOa8FTZvJuvRQghhOWSZOVJWVndb13Z/ZNxGG9hotfBju9gakOsLm1Br9GS2mUqNH8P8uDeOtvP3abDD9tZf/IWttZWfNy5Cr8NrIOnk22uH0sIIUTBIEOXc0O1HrDpU4i+BofnQt0XzR1R7ri+H1aMglvHATAENWazQ2eaBvfK9UMduRbFN2vPsOP8HQDKeDvxQ5+aVAtwy/VjCSGEKFgkWckN1lp4agSsfts4jLnWQLAuwE9tUgxs/AT2/QYocPCEtp+jr/IM8atX5+qhzofHMmHtWdacCANAa63h+fqleKttRZzsCvBzKIQQItfIt0Fuqdkftn5lvMvwyWX5cofhPHFqBax6C2LvDcWu3hfa/M/YiVany7XD3IhKZNL6syw+eB2DMl5R6l4zgNGtKhDoKSN9hBBC3CfJSm6xdYR6Q2DL58Yp+Ks9kyd9OvJM9HVY9TacudeB1rMMdJoEZZrm6mHuxCXz4+bzzNl91XTjwdZVfHmzTUUq+rnk6rGEEEIUDpKs5KZ6L8O/30PYMbiwEcoVgDsyG/Sw91djn5uUOLCyMXYYbvImaB1y7TCxSTp+3X6J37dfJD5FD0CDMp683a4StUp65NpxhBBCFD6SrOQmR0+oPQh2/wg7JllmsqIUJMdCYgREXoEN4+DmQeO6wPrQ+XvwqZxrh0vS6flz1xWmbjlPZILxMlJwgBtvta1I4/LeaApS65MQQgizkGQltzUcBnt/hsvbjaNpStTJn+PqEuHyDogLh4S7xmQkIeLe35HGv9OWGR7oe2LnBq3HQa1BuXqn5PPhcQz8Yy83oozDucsUc+LNNhVpX81PkhQhhBBZJslKbnMrASHPweE5xvlJes/J2+PpU+HwbNjyFcTezPp2Nvbg6AVBjaH1eHDxy9WwwqKTGPD7Hm5GJ+HvZs/rrcrzTK0SMvusEEKIbJNkJS80GmVMVk7/A7fPQrEKuX8MgwFOLoVNn0HEBeMyF3/jbLqOXsZLUg6ext+mv/+z3DbvRtxEJ+gY+MdebkYnUcbbiUVDn5JJ3YQQQuSYJCt5oVhFqNjROLJm5/fQ9cfc27dScH4jbBwPYUeNyxy9oPGbUGdwnkx/nx1JOj0vzdrHmVux+LjYMXNwPUlUhBBCPJEC1Sb/xRdfoNFoeP31180dyuM9Pdr4+8gCiL6RO/u8ugdmdIQ5zxgTFVsXaPYejDpi7Ctj5kQlVW9g5LxD7LsciYudDTMH15M5U4QQQjyxAtOysm/fPn755RdCQkLMHUrWBNaFUk/DlR2weyq0/Szn+7p1AjZ+CmfvzR5rbWccJv30mDy543FOKKX48O8TrDt5C1sbK34dWIfK/q7mDksIIUQhUCBaVuLi4nj++ef59ddf8fAoQHNyPP268feBGcZRONkVcQkWvww/NTImKhorqDUARh40Jj8WkqgATNpwjnl7r6LRwPfP1aBBGcuJTQghRMFWIFpWXnvtNTp27EirVq343//+98iyycnJJCcnmx7HxMQAoNPp0OXSdPFp+3ns/ko1xcanKprwE+j3/ILh6TceXjY5Fs3d8xBxHs3dC2junEFzdjUaQyoAhspd0Td9F7zKpwWRG1XJlofVe+7ea3y/8RwAH3eqTKtK3rn2XFuCLJ/vQqio1l3qLfUuCrJSb0t5TjRKKWXuIB5l/vz5fPbZZ+zbtw97e3uaNWtGjRo1mDRpUqblx40bx/jx4zMsnzt3Lo6O+d9/IiBiF3Wu/ESyjQsbqkzATheFc3IYzklhOCeH3vs7FPvU6Ey3v+USzKniPYl2LJ3PkWfNkbsapp+1QqGhbYCBDiUN5g5JCCFELklISKBv375ER0fj6mq+S/sWnaxcu3aNOnXqsG7dOqpXrw7w2GQls5aVwMBA7ty5k2tPtE6nY/369bRu3RqtVvvowoZUbH6qjybqCgoNGh7+dCsnH5RnGfAqh/IqhypRH1Wibq7EnBserPfeyxG8MPMgKakGnqsTwKddqhTKyd6ydb4LmaJad6m31LsoyEq9Y2Ji8Pb2NnuyYtGXgQ4cOEB4eDi1a9c2LdPr9Wzbto0pU6aQnJyMtbV1um3s7Oyws7PLsC+tVpvrL8Ks7VMLTd6C5cONiYqNA3iVA+9yxt9e5Y1/e5ZF4+BOQfiq12q1XLibyKtzDpOSaqB1FV8+6x5S6Cd8y4vXUEFRVOsu9S5apN6Zr7MEFp2stGzZkmPHjqVb9sILL1CpUiXeeeedDImKxarZDwJqg70ruBTP1SntzeFGVCID/9hLbFIqdYM8mNynZqFPVIQQQpiPRScrLi4uVKtWLd0yJycnvLy8Miy3aBoN+FYxdxS5Ik4Hg2ce4FZMMhV8nfltQF3stQUkaRRCCFEgWXSyIixLQkoqv5y25kpcAsXd7Jk5uB5ujpbRRCiEEKLwKnDJypYtW8wdQpETGZ/Cgv3XmLXzMjfjNLg7aJn1Yj383RzMHZoQQogioMAlKyL/nLwZw8ydl1l2+AbJqcYhyc5axS/9alLOx8XM0QkhhCgqJFkR6aTqDaw/eYsZOy+z59L9WXerFnelf/1AbG4eoWZJd/MFKIQQosiRZEUAEBGfwvx9V5m96wo3o5MAsLbS0K6aHy88FUTtUh6kpqayKuyImSMVQghR1EiyUsSduBnNzJ2X+fvwTdOlHi8nW/rUK8nzDUpKvxQhhBBmJ8lKERSXnMqqY6Es3HeN/VciTcurBbgy6KnSdArxl+HIQgghLIYkK0WEwaDYcymCRQeus/p4KAkpegBs0i71NAqiVkmPQjldvhBCiIJNkpVC7lpEAksO3mDRwWtci0g0LS/j7UTPOiV4plYJfF3tzRihEEII8WiSrBRCiSl61pwI5a/919l54a5pubOdDZ2r+9OzdglpRRFCCFFgSLJSSOgNikNXI1l04Dorj4YSl5xqWteonBc9a5egXVV/HGylL4oQQoiCRZKVAkhvUFy8HcfR69Ecu2H8OXkzhkSd3lSmpKcjPWuXoEetAEp4OJoxWiGEEOLJSLJi4fQGxaU7cRy7Ec3R69EcvxHNiZsxpg6y/+VsZ0O7an70rF2CekGeWFnJZR4hhBAFnyQrFiQ+OZWzt2I5ExbL6bBYTt6M4cTNaOIzSUwcba2pVtyNagFuhJQw/i7j7SQJihBCiEJHkhUzSNUbuHw3gTNhsZwJi+F0WCxnbsVyNSIBpTKWd9BaU7W4K8El3Ai+l5yU9nbGWhITIYQQRYAkK3ksVW/gxM0Y9l2O4GRoDGfCYjkXHkfKvdliH+TtbEclPxcq+rlQ2d+VkBJulC0miYkQQoiiS5KVXKY3KE7cjGb3xbvsvhjBvksRxP5nZE4aB601FfxcqORrTEzSEhQvZzszRC2EEEJYLklWnpDeoDgVGsPui3fZdeEuezNJTlzsbahf2pPgAHdTYlLS01H6lwghhBBZIMlKNhkMipOhMWy+qWH5nEPsuxxJTNIDyYmdDfVKe9KwrBcNynhR2d9VLuMIIYQQOSTJSjbplaLPb/tISLEGbgPGIcP1SnvSoIwnDcp4UbW4myQnQgghRC6RZCWbtNZWNCnvzZUboXSqV5Gny/tQtbgrNtZW5g5NCCGEKJQkWcmByb2rs2rVDTo0Lo1WqzV3OEIIIUShJs0BQgghhLBokqwIIYQQwqJJsiKEEEIIiybJihBCCCEsmiQrQgghhLBokqwIIYQQwqJJsiKEEEIIiybJihBCCCEsmiQrQgghhLBokqwIIYQQwqJJsiKEEEIIi1bo7w2klAIgJiYm1/ap0+lISEggJiamSN0bSOpdtOoNRbfuUm+pd1GQlXqnfXemfZeaS6FPVmJjYwEIDAw0cyRCCCFEwRQbG4ubm5vZjq9R5k6X8pjBYODmzZu4uLig0WhyZZ8xMTEEBgZy7do1XF1dc2WfBYHUu2jVG4pu3aXeUu+iICv1VkoRGxtL8eLFsbIyX8+RQt+yYmVlRYkSJfJk366urkXqhZ1G6l30FNW6S72LFql35szZopJGOtgKIYQQwqJJsiKEEEIIiybJSg7Y2dnx8ccfY2dnZ+5Q8pXUu2jVG4pu3aXeUu+ioCDVu9B3sBVCCCFEwSYtK0IIIYSwaJKsCCGEEMKiSbIihBBCCIsmyYoQQgghLFqRTVa2bdtG586dKV68OBqNhmXLlqVbf+vWLQYNGkTx4sVxdHSkXbt2nDt3Ll2ZsLAw+vfvj5+fH05OTtSqVYtFixalKxMUFIRGo0n38+677+Z19R4qN+p94cIFunfvTrFixXB1daVXr17cunUrXZnIyEj69++Pm5sbbm5u9O/fn6ioqDyu3cPlV70t7Xx/8cUX1K1bFxcXF3x8fOjWrRtnzpxJV0Ypxbhx4yhevDgODg40a9aMEydOpCuTnJzMiBEj8Pb2xsnJiS5dunD9+vV0ZSzpnOdnvS3pnOdWvX/55ReaNWuGq6srGo0m0/NYGM93VuptSecbcqfuERERjBgxgooVK+Lo6EjJkiUZOXIk0dHR6fZjznNeZJOV+Ph4qlevzpQpUzKsU0rRrVs3Ll68yN9//82hQ4coVaoUrVq1Ij4+3lSuf//+nDlzhuXLl3Ps2DF69OjBc889x6FDh9Lt75NPPiE0NNT088EHH+R5/R7mSesdHx9PmzZt0Gg0bNq0iX///ZeUlBQ6d+6MwWAw7atv374cPnyYNWvWsGbNGg4fPkz//v3zrZ4Pyq96g2Wd761bt/Laa6+xe/du1q9fT2pqKm3atEn3Ov7666+ZOHEiU6ZMYd++ffj5+dG6dWvTfbUAXn/9dZYuXcr8+fPZsWMHcXFxdOrUCb1ebypjSec8P+sNlnPOc6veCQkJtGvXjvfee++hxyqM5zsr9QbLOd+QO3W/efMmN2/eZMKECRw7dowZM2awZs0aXnzxxXTHMus5V0IBaunSpabHZ86cUYA6fvy4aVlqaqry9PRUv/76q2mZk5OTmjVrVrp9eXp6qt9++830uFSpUuq7777Ls9ifRE7qvXbtWmVlZaWio6NNZSIiIhSg1q9fr5RS6uTJkwpQu3fvNpXZtWuXAtTp06fzuFaPl1f1Vsqyz7dSSoWHhytAbd26VSmllMFgUH5+furLL780lUlKSlJubm5q2rRpSimloqKilFarVfPnzzeVuXHjhrKyslJr1qxRSln+Oc+reitl2ec8J/X+r82bNytARUZGplteGM/3fz2s3kpZ9vlW6snrnmbhwoXK1tZW6XQ6pZT5z3mRbVl5lOTkZADs7e1Ny6ytrbG1tWXHjh2mZU8//TQLFiwgIiICg8HA/PnzSU5OplmzZun299VXX+Hl5UWNGjX47LPPSElJyZd6ZFdW6p2cnIxGo0k3iZC9vT1WVlamMrt27cLNzY369eubyjRo0AA3Nzd27tyZH1XJltyqdxpLPt9pzbqenp4AXLp0ibCwMNq0aWMqY2dnR9OmTU3n6sCBA+h0unRlihcvTrVq1UxlLP2c51W901jqOc9JvbOiMJ7v7LDU8w25V/fo6GhcXV2xsTHeQtDc51ySlUxUqlSJUqVKMXbsWCIjI0lJSeHLL78kLCyM0NBQU7kFCxaQmpqKl5cXdnZ2DBkyhKVLl1K2bFlTmVGjRjF//nw2b97M8OHDmTRpEsOGDTNHtR4rK/Vu0KABTk5OvPPOOyQkJBAfH89bb72FwWAwlQkLC8PHxyfD/n18fAgLC8vXOmVFbtUbLPt8K6UYM2YMTz/9NNWqVQMwnQ9fX990ZX19fU3rwsLCsLW1xcPD45FlLPWc52W9wXLPeU7rnRWF8XxnlaWeb8i9ut+9e5dPP/2UIUOGmJaZ+5wX+rsu54RWq2Xx4sW8+OKLeHp6Ym1tTatWrWjfvn26ch988AGRkZFs2LABb29vli1bxrPPPsv27dsJDg4GYPTo0abyISEheHh40LNnT1NmbkmyUu9ixYrx119/MXToUH744QesrKzo06cPtWrVwtra2lROo9Fk2L9SKtPl5pab9bbk8z18+HCOHj2aoSUIMp6vrJyrB8tY6jnP63pb6jnP7Xo/bh853U9uy+t6W+r5htype0xMDB07dqRKlSp8/PHHj9zHo/aT2yRZeYjatWtz+PBhoqOjSUlJoVixYtSvX586deoAxpEhU6ZM4fjx41StWhWA6tWrs337dn788UemTZuW6X4bNGgAwPnz583+ws7M4+oN0KZNGy5cuMCdO3ewsbHB3d0dPz8/SpcuDYCfn1+GUTIAt2/fzpDdW4rcqHdmLOV8jxgxguXLl7Nt2zZKlChhWu7n5wcY/2vy9/c3LQ8PDzedKz8/P1JSUoiMjEzXyhAeHs5TTz1lKmOJ5zyv650ZSzjnT1LvrCiM5zunLOF8Q+7UPTY2lnbt2uHs7MzSpUvRarXp9mPOcy6XgR7Dzc2NYsWKce7cOfbv30/Xrl0BY69xACur9E+htbV1htEh/5U2Uui/LxpL9LB6/5e3tzfu7u5s2rSJ8PBwunTpAkDDhg2Jjo5m7969prJ79uwhOjr6kR/yluBJ6p0Zc59vpRTDhw9nyZIlbNq0KUNiVbp0afz8/Fi/fr1pWUpKClu3bjWdq9q1a6PVatOVCQ0N5fjx46YylnbO86vemTHnOc+NemdFYTzfOVUY3uNgbFFp06YNtra2LF++PF0fPrCAc57nXXgtVGxsrDp06JA6dOiQAtTEiRPVoUOH1JUrV5RSxp7QmzdvVhcuXFDLli1TpUqVUj169DBtn5KSosqVK6caN26s9uzZo86fP68mTJigNBqN+ueff5RSSu3cudO034sXL6oFCxao4sWLqy5dupilzko9eb2VUuqPP/5Qu3btUufPn1d//vmn8vT0VGPGjElXpl27diokJETt2rVL7dq1SwUHB6tOnTrlWz0flB/1tsTzPXToUOXm5qa2bNmiQkNDTT8JCQmmMl9++aVyc3NTS5YsUceOHVN9+vRR/v7+KiYmxlTm1VdfVSVKlFAbNmxQBw8eVC1atFDVq1dXqamppjKWdM7zq96Wds5zq96hoaHq0KFD6tdff1WA2rZtmzp06JC6e/euqUxhPN+Pq/f/27uDkKi2OI7jvxmUsdKmEsYaGtGgMrgGhugmIygQRCFtlWKCkpsCKYLZRLNwJSI0m0BbuHEhkvtqYZtamAwFLqLQZpBW2YgIIlrOv8V7b3jz7NFmnDmv9/3A3cz9z5nz5zCXH3PvYVxbb7P89L6xsWHNzc1WX19vS0tLOeO48h3/34aVv7am/fPo6+szM7N4PG4nT5600tJSq66utgcPHtj29nbOGB8/frSuri4LhUJ28OBBO3/+fM5W5kQiYc3NzRYMBq2srMzOnj1rsVjMNjc3C9lqjnz0HY1GraqqykpLS+306dM2NjZmmUwmpyadTltPT49VVFRYRUWF9fT0/HQbYKEUom8X1/tnPUuyycnJbE0mk7FYLGbHjx+3QCBgly5dssXFxZxxtra27M6dO3bs2DE7cOCAtbe328rKSk6NS2teqL5dW/N89R2LxX45zu+43r/q27X1NstP7/92fZRkyWQyW1fMNff92SwAAICTeGYFAAA4jbACAACcRlgBAABOI6wAAACnEVYAAIDTCCsAAMBphBUAAOA0wgoAAHAaYQUAADiNsAIgL8xMV69eVWtr655zjx8/VjAY1MrKShFmBuC/jrACIC98Pp8mJyc1Pz+v8fHx7OvJZFLRaFTxeFzV1dV5/cxv377ldTwAbiKsAMibSCSieDyu+/fvK5lMysw0MDCgK1euqKmpSW1tbSovL1dVVZV6e3v19evX7HufPXumixcv6siRI6qsrFR7e7uWl5ez51OplHw+n2ZmZnT58mWVlZVpamqqGG0CKDD+yBBA3l27dk3r6+u6fv26hoeHtbCwoMbGRt26dUs3b97U1taWotGovn//rrm5OUnS7OysfD6f6uvrtbm5qYcPHyqVSundu3fy+/1KpVKqra1VTU2NxsbG1NDQoEAgoHA4XORuAew3wgqAvPvy5Ys8z1M6ndbTp0/19u1bzc/P6/nz59maz58/KxKJ6MOHDzpz5syeMVZXVxUKhbS4uCjP87Jh5dGjRxoaGipkOwCKjNtAAPIuFAppcHBQ586dU2dnpxKJhF6+fKny8vLsUVdXJ0nZWz3Ly8vq7u7WqVOndPjwYdXW1krSnodyGxsbC9sMgKIrKfYEAPyeSkpKVFLyxyUmk8moo6NDIyMje+pOnDghSero6FAkEtGTJ08UDoeVyWTkeZ52dnZy6g8dOrT/kwfgFMIKgH134cIFzc7OqqamJhtg/i6dTuv9+/caHx9XS0uLJOnVq1eFniYAR3EbCMC+u337ttbW1nTjxg29efNGnz590osXL9Tf36/d3V0dPXpUlZWVmpiY0NLSkubm5nTv3r1iTxuAIwgrAPZdOBzW69evtbu7q9bWVnmep6GhIQWDQfn9fvn9fk1PTyuRSMjzPN29e1ejo6PFnjYAR7AbCAAAOI1fVgAAgNMIKwAAwGmEFQAA4DTCCgAAcBphBQAAOI2wAgAAnEZYAQAATiOsAAAApxFWAACA0wgrAADAaYQVAADgtB9DziFy/zmv3QAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<Figure size 600x400 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(6,4))\n",
    "\n",
    "sns.lineplot(data, x=data['year'], y=data['beer_price'], label='Beer Price')\n",
    "sns.lineplot(data, x=data['year'], y=data['roast_chicken_price'], label='Chicken Price')\n",
    "\n",
    "plt.title(\"Beer and Roast Chicken prices at Oktoberfest over the years:\")\n",
    "plt.xlabel(\"Year\")\n",
    "plt.ylabel(\"Consumption\")\n",
    "plt.grid(True)\n",
    "plt.legend()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "c4031709",
   "metadata": {},
   "source": [
    "### Investigating the liters of beers consumed per person yearly:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "4fc39cb2",
   "metadata": {},
   "outputs": [],
   "source": [
    "data_mod = data.copy()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "4f05a3bb",
   "metadata": {},
   "outputs": [],
   "source": [
    "data_mod['beer_in_liters'] = data_mod['beer_consumption'] * 100 # Converting hectoliters to liters\n",
    "data_mod['pop'] = data['guests_total'] *1000000 # COnverting the population in millions"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "2827f0aa",
   "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>year</th>\n",
       "      <th>duration</th>\n",
       "      <th>guests_total</th>\n",
       "      <th>guests_daily</th>\n",
       "      <th>beer_price</th>\n",
       "      <th>beer_consumption</th>\n",
       "      <th>roast_chicken_price</th>\n",
       "      <th>roast_chicken_consumption</th>\n",
       "      <th>beer_in_liters</th>\n",
       "      <th>pop</th>\n",
       "      <th>beer_per_person</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1985</td>\n",
       "      <td>16</td>\n",
       "      <td>7.1</td>\n",
       "      <td>444</td>\n",
       "      <td>3.20</td>\n",
       "      <td>54541</td>\n",
       "      <td>4.77</td>\n",
       "      <td>629520</td>\n",
       "      <td>5454100</td>\n",
       "      <td>7100000.0</td>\n",
       "      <td>0.768183</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1986</td>\n",
       "      <td>16</td>\n",
       "      <td>6.7</td>\n",
       "      <td>419</td>\n",
       "      <td>3.30</td>\n",
       "      <td>53807</td>\n",
       "      <td>3.92</td>\n",
       "      <td>698137</td>\n",
       "      <td>5380700</td>\n",
       "      <td>6700000.0</td>\n",
       "      <td>0.803090</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>1987</td>\n",
       "      <td>16</td>\n",
       "      <td>6.5</td>\n",
       "      <td>406</td>\n",
       "      <td>3.37</td>\n",
       "      <td>51842</td>\n",
       "      <td>3.98</td>\n",
       "      <td>732859</td>\n",
       "      <td>5184200</td>\n",
       "      <td>6500000.0</td>\n",
       "      <td>0.797569</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>1988</td>\n",
       "      <td>16</td>\n",
       "      <td>5.7</td>\n",
       "      <td>356</td>\n",
       "      <td>3.45</td>\n",
       "      <td>50951</td>\n",
       "      <td>4.19</td>\n",
       "      <td>720139</td>\n",
       "      <td>5095100</td>\n",
       "      <td>5700000.0</td>\n",
       "      <td>0.893877</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>1989</td>\n",
       "      <td>16</td>\n",
       "      <td>6.2</td>\n",
       "      <td>388</td>\n",
       "      <td>3.60</td>\n",
       "      <td>51241</td>\n",
       "      <td>4.22</td>\n",
       "      <td>775674</td>\n",
       "      <td>5124100</td>\n",
       "      <td>6200000.0</td>\n",
       "      <td>0.826468</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   year  duration  guests_total  guests_daily  beer_price  beer_consumption  \\\n",
       "0  1985        16           7.1           444        3.20             54541   \n",
       "1  1986        16           6.7           419        3.30             53807   \n",
       "2  1987        16           6.5           406        3.37             51842   \n",
       "3  1988        16           5.7           356        3.45             50951   \n",
       "4  1989        16           6.2           388        3.60             51241   \n",
       "\n",
       "   roast_chicken_price  roast_chicken_consumption  beer_in_liters        pop  \\\n",
       "0                 4.77                     629520         5454100  7100000.0   \n",
       "1                 3.92                     698137         5380700  6700000.0   \n",
       "2                 3.98                     732859         5184200  6500000.0   \n",
       "3                 4.19                     720139         5095100  5700000.0   \n",
       "4                 4.22                     775674         5124100  6200000.0   \n",
       "\n",
       "   beer_per_person  \n",
       "0         0.768183  \n",
       "1         0.803090  \n",
       "2         0.797569  \n",
       "3         0.893877  \n",
       "4         0.826468  "
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data_mod['beer_per_person'] = data_mod['beer_in_liters'] / data_mod['pop']\n",
    "data_mod.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "b5bb34b8",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 600x400 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(6,4))\n",
    "\n",
    "sns.lineplot(data_mod, x=data_mod['year'], y=data_mod['beer_per_person'], marker='o')\n",
    "\n",
    "plt.title(\"Average beer consumed per person over the years:\")\n",
    "plt.xlabel(\"Year\")\n",
    "plt.ylabel(\"Consumption\")\n",
    "plt.grid(True)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "16e9417b",
   "metadata": {},
   "source": [
    "### Investigating the total money spent on food:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "c1f335d1",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 600x400 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "data_mod['total_money_spent'] = data_mod['beer_consumption'] * data_mod['beer_price'] + data_mod['roast_chicken_consumption'] * data_mod['roast_chicken_price']\n",
    "\n",
    "yearly_spending = data_mod.groupby('year')['total_money_spent'].sum().reset_index()\n",
    "\n",
    "plt.figure(figsize=(6, 4))\n",
    "\n",
    "sns.lineplot(yearly_spending, x='year', y='total_money_spent', label='Total Spending', marker='o')\n",
    "plt.title('Yearly Total Money Spent at Oktoberfest')\n",
    "plt.xlabel('Year')\n",
    "plt.ylabel('Total Money Spent')\n",
    "plt.legend()\n",
    "plt.grid(True)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "7181bcdb",
   "metadata": {},
   "source": [
    "### Investigating the correlation of beer and chicken consumption with their respective prices:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "id": "fe4d350e",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Index(['year', 'duration', 'guests_total', 'guests_daily', 'beer_price',\n",
       "       'beer_consumption', 'roast_chicken_price', 'roast_chicken_consumption'],\n",
       "      dtype='object')"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data.columns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "id": "7f549f00",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0.5, 1.0, 'Correlation Plot of Beer and Chicken Consumption with Prices')"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 600x400 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "correlations = data[['beer_consumption', 'beer_price', 'roast_chicken_consumption', 'roast_chicken_price']].corr()\n",
    "\n",
    "plt.figure(figsize=(6,4))\n",
    "sns.heatmap(correlations, annot=True, linewidths=.5)\n",
    "plt.title('Correlation Plot of Beer and Chicken Consumption with Prices')"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "d370cb04",
   "metadata": {},
   "source": [
    "### Developing a linear regression model to:\n",
    "- Predict how many visitors are expected to come to for the year 2023\n",
    "- Predict how much beer will be consumed in 2023\n",
    "- Predict how much roast chickens will be eaten in 2023\n",
    "- Calculating the price elasticity of beer and chicken"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "0d435302",
   "metadata": {},
   "source": [
    "#### 1. Predicting the number of guests expected to visit in the year 2023"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "id": "ca9eb9b3",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Predicted number of visitors in 2023: 6.01M\n",
      "Mean Squared Error (MSE): 0.20\n",
      "R-squared (R2): -0.09\n"
     ]
    }
   ],
   "source": [
    "import warnings\n",
    "warnings.filterwarnings(\"ignore\")\n",
    "from sklearn.model_selection import train_test_split\n",
    "from sklearn.linear_model import LinearRegression\n",
    "from sklearn.metrics import mean_squared_error, r2_score\n",
    "\n",
    "# data.head()\n",
    "\n",
    "X = data[[\"year\"]]\n",
    "y = data[\"guests_total\"]\n",
    "\n",
    "X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.2, random_state=42)\n",
    "\n",
    "model = LinearRegression()\n",
    "model.fit(X_train, y_train)\n",
    "\n",
    "y_pred = model.predict(X_test)\n",
    "\n",
    "year_2023 = np.array([[2023]])\n",
    "visitors_2023 = model.predict(year_2023)\n",
    "\n",
    "print(f\"Predicted number of visitors in 2023: {visitors_2023[0]:.2f}M\")\n",
    "\n",
    "mse = mean_squared_error(y_test, y_pred)\n",
    "r2 = r2_score(y_test, y_pred)\n",
    "\n",
    "print(f\"Mean Squared Error (MSE): {mse:.2f}\")\n",
    "print(f\"R-squared (R2): {r2:.2f}\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "e01a273a",
   "metadata": {},
   "source": [
    "From the obtained evaluation metrics it can is evident that, with low MSE value, on average, the predicted value is close to the actual values. However the negative R2 score indicates that the modelis performing poorly and is failing to capture the variance and the underlying patterns"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "6967c54a",
   "metadata": {},
   "source": [
    "#### 2. Predicting the quantity of beer consumption that is expected in the year 2023"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "id": "54c621e0",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "For the number of visitors in 2023, 6.01M guests, the predicted average amount of beer consumption in 2023: 79739.89hL\n",
      "Root Mean Squared Error (RMSE): 4333.33hL\n",
      "R-squared (R2): 0.86\n"
     ]
    }
   ],
   "source": [
    "X = data[['year', 'guests_total']]\n",
    "y = data[['beer_consumption']]\n",
    "\n",
    "X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.3, random_state=30)\n",
    "\n",
    "model2 = LinearRegression()\n",
    "model2.fit(X_train, y_train)\n",
    "\n",
    "y_pred2 = model2.predict(X_test)\n",
    "\n",
    "y_2023 = np.array([[2023, 6.01]])\n",
    "consumption_2023 = model2.predict(y_2023)\n",
    "predicted = consumption_2023[0][0]\n",
    "\n",
    "print(f\"For the number of visitors in 2023, {visitors_2023[0]:.2f}M guests, the predicted average amount of beer consumption in 2023: {predicted:.2f}hL\")\n",
    "\n",
    "rmse = mean_squared_error(y_test, y_pred2, squared=False)\n",
    "r2_2 = r2_score(y_test, y_pred2)\n",
    "\n",
    "print(f\"Root Mean Squared Error (RMSE): {rmse:.2f}hL\")\n",
    "print(f\"R-squared (R2): {r2_2:.2f}\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "57a3ee35",
   "metadata": {},
   "source": [
    "I calculated the RMSE instead of MSE here because, the unit of the targer variable is $hL$ and calculating the MSE would give a value in $hL^{2}$. The RMSE value indicates that the predicted value is off by 4333.33hL, which can be considered as relatively low and the higher R2 value indicates that the chosen features explains the variance of the model"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "a9396a05",
   "metadata": {},
   "source": [
    "#### 3. Predicting the quantity of roast chicken consumption that is expected in the year 2023"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "id": "6f4b368f",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "For the number of visitors in 2023, 6.01M guests, the predicted average amount of chicken consumption in 2023: 365285.71kg\n",
      "Root Mean Squared Error (RMSE): 37257.34kg\n",
      "R-squared (R2): 0.68\n"
     ]
    }
   ],
   "source": [
    "X = data[['year', 'guests_total']]\n",
    "y = data[['roast_chicken_consumption']]\n",
    "\n",
    "X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.2, random_state=27)\n",
    "\n",
    "model3 = LinearRegression()\n",
    "model3.fit(X_train, y_train)\n",
    "\n",
    "y_pred3 = model3.predict(X_test)\n",
    "\n",
    "y_2023 = np.array([[2023, 6.01]])\n",
    "chicken_2023 = model3.predict(y_2023)\n",
    "chicken_predicted = chicken_2023[0][0]\n",
    "\n",
    "print(f\"For the number of visitors in 2023, {visitors_2023[0]:.2f}M guests, the predicted average amount of chicken consumption in 2023: {chicken_predicted:.2f}kg\")\n",
    "\n",
    "rmse = mean_squared_error(y_test, y_pred3, squared=False)\n",
    "r2_2 = r2_score(y_test, y_pred3)\n",
    "\n",
    "print(f\"Root Mean Squared Error (RMSE): {rmse:.2f}kg\")\n",
    "print(f\"R-squared (R2): {r2_2:.2f}\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "29d268bb",
   "metadata": {},
   "source": [
    "The RMSE is calculated here again for the same reason that was used in predicting the beer consumption. The R2 score indicates, the features selected for the model relatively explains the variance, but not too efficient"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "ce0fd18b",
   "metadata": {},
   "source": [
    "#### Calculating the price elasticity of beer and chicken and inferring what it means for the year 2023"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "id": "8c417d13",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Beer Price Elasticity: 0.58\n"
     ]
    }
   ],
   "source": [
    "X_beer = data[['beer_price']]\n",
    "y_beer = data[['beer_consumption']]\n",
    "\n",
    "X_beer_train, X_beer_test, y_beer_train, y_beer_test = train_test_split(X_beer, y_beer, test_size=0.2, random_state=32)\n",
    "\n",
    "beer_model = LinearRegression()\n",
    "beer_model.fit(X_beer_train, y_beer_train)\n",
    "\n",
    "beer_score = beer_model.score(X_beer_test, y_beer_test)\n",
    "# beer_score\n",
    "\n",
    "beer_price_coefficient = beer_model.coef_[0]\n",
    "# beer_price_coefficient\n",
    "\n",
    "current_beer_price = 13.75\n",
    "beer_elasticity = beer_price_coefficient * (current_beer_price / beer_model.predict([[current_beer_price]])[0])\n",
    "print(f\"Beer Price Elasticity: {beer_elasticity[0]:.2f}\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "484c7af9",
   "metadata": {},
   "source": [
    "The beer price elasticity value indicates that the change of prices are inelastic, meaning, consumers dont really care much about the change in price of the beer and continue to buy it. This inelastic demand would result beneficial to the totl revenue collection since the quality demand doesnt strongly respond to price changes\n",
    "\n",
    "Current price source: https://www.statista.com/statistics/1333495/beer-prices-development-oktoberfest-munich/#:~:text=Beer%20prices%20at%20the%20Oktoberfest%202002-2023&text=In%202023%2C%20beer%20at%20the,(COVID-19)%20pandemic."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "id": "35fbcb53",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Chicken Price Elasticity: -1.12\n"
     ]
    }
   ],
   "source": [
    "X_chicken = data[['roast_chicken_price']]\n",
    "y_chicken = data[['roast_chicken_consumption']]\n",
    "\n",
    "X_chicken_train, X_chicken_test, y_chicken_train, y_chicken_test = train_test_split(X_chicken, y_chicken, test_size=0.2, random_state=46)\n",
    "\n",
    "chicken_model = LinearRegression()\n",
    "chicken_model.fit(X_chicken_train, y_chicken_train)\n",
    "\n",
    "chicken_score = chicken_model.score(X_chicken_test, y_chicken_test)\n",
    "\n",
    "chicken_price_coefficient = chicken_model.coef_[0]\n",
    "current_chicken_price = 12 \n",
    "chicken_elasticity = chicken_price_coefficient * (current_chicken_price / chicken_model.predict([[current_chicken_price]])[0])\n",
    "print(f\"Chicken Price Elasticity: {chicken_elasticity[0]:.2f}\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "360a5207",
   "metadata": {},
   "source": [
    "SInce the value is greater than 1, it is regarded as a elastic demand, that is, the change is price of roasted chicken does affect the sales. The negative symbol indicates that the price and quantity demanded move in opposite directions. When the price of the chicken goes up by 1 euro, the sales is likely to go down by 1.12%\n",
    "\n",
    "Roasted chicken current price source: https://tischreservierung-oktoberfest.de/en/blog/what-you-need-to-know-for-the-oktoberfest-2023/#:~:text=The%20beer%20price%20will%20be,cost%20you%20about%2012%20Euro"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "b99287ee",
   "metadata": {},
   "source": [
    "### Reference and documentation"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "b892b978",
   "metadata": {},
   "source": [
    "- [Dataset](https://www.kaggle.com/datasets/lucafrance/oktoberfest)\n",
    "- [Understanding the dataset](https://www.researchgate.net/publication/337904317_Oktoberfest_Food_Dataset)\n",
    "- Lot of refernces from StackOverflow in regard to the linear regression model and choosing rmse or mse metric for evaluation metric\n",
    "- [Price Elasticity: What it is & Ways to calculate it](https://www.questionpro.com/blog/price-elasticity/)\n",
    "- [Using Machine Learning to Estimate Price Elasticity](https://thedatageneralist.com/using-machine-learning-to-estimate-price-elasticity/)\n",
    "- [Price Elasticity](https://www.kaggle.com/code/pratx557/price-elasticity)\n",
    "- ChatGPT to explain code snippets from refernce materials"
   ]
  }
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