Saudi Arabian GP 2023.ipynb

{
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       "<div>\n",
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>position</th>\n",
       "      <th>driver</th>\n",
       "      <th>driverid</th>\n",
       "      <th>constructor</th>\n",
       "      <th>constructorid</th>\n",
       "      <th>laps</th>\n",
       "      <th>time</th>\n",
       "      <th>points</th>\n",
       "      <th>grid</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1.0</td>\n",
       "      <td>Sergio Pérez</td>\n",
       "      <td>81.5</td>\n",
       "      <td>Red Bull</td>\n",
       "      <td>9.0</td>\n",
       "      <td>50</td>\n",
       "      <td>1:21:14.894</td>\n",
       "      <td>25</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2.0</td>\n",
       "      <td>Max Verstappen</td>\n",
       "      <td>50.0</td>\n",
       "      <td>Red Bull</td>\n",
       "      <td>9.0</td>\n",
       "      <td>50</td>\n",
       "      <td>5.355</td>\n",
       "      <td>19</td>\n",
       "      <td>15</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>3.0</td>\n",
       "      <td>Fernando Alonso</td>\n",
       "      <td>4.0</td>\n",
       "      <td>Aston Martin</td>\n",
       "      <td>11.7</td>\n",
       "      <td>50</td>\n",
       "      <td>20.728</td>\n",
       "      <td>15</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>4.0</td>\n",
       "      <td>George Russell</td>\n",
       "      <td>84.7</td>\n",
       "      <td>Mercedes</td>\n",
       "      <td>13.1</td>\n",
       "      <td>50</td>\n",
       "      <td>25.866</td>\n",
       "      <td>12</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>5.0</td>\n",
       "      <td>Lewis Hamilton</td>\n",
       "      <td>1.0</td>\n",
       "      <td>Mercedes</td>\n",
       "      <td>13.1</td>\n",
       "      <td>50</td>\n",
       "      <td>31.065</td>\n",
       "      <td>10</td>\n",
       "      <td>8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>6.0</td>\n",
       "      <td>Carlos Sainz</td>\n",
       "      <td>83.2</td>\n",
       "      <td>Ferrari</td>\n",
       "      <td>6.0</td>\n",
       "      <td>50</td>\n",
       "      <td>35.876</td>\n",
       "      <td>8</td>\n",
       "      <td>5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>7.0</td>\n",
       "      <td>Charles Leclerc</td>\n",
       "      <td>84.4</td>\n",
       "      <td>Ferrari</td>\n",
       "      <td>6.0</td>\n",
       "      <td>50</td>\n",
       "      <td>43.162</td>\n",
       "      <td>6</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>8.0</td>\n",
       "      <td>Esteban Ocon</td>\n",
       "      <td>83.9</td>\n",
       "      <td>Alpine F1 Team</td>\n",
       "      <td>21.4</td>\n",
       "      <td>50</td>\n",
       "      <td>52.832</td>\n",
       "      <td>4</td>\n",
       "      <td>7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>9.0</td>\n",
       "      <td>Pierre Gasly</td>\n",
       "      <td>84.2</td>\n",
       "      <td>Alpine F1 Team</td>\n",
       "      <td>21.4</td>\n",
       "      <td>50</td>\n",
       "      <td>54.747</td>\n",
       "      <td>2</td>\n",
       "      <td>10</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>10.0</td>\n",
       "      <td>Kevin Magnussen</td>\n",
       "      <td>76.0</td>\n",
       "      <td>Haas F1 Team</td>\n",
       "      <td>21.0</td>\n",
       "      <td>50</td>\n",
       "      <td>+1:04.826</td>\n",
       "      <td>1</td>\n",
       "      <td>13</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>11.0</td>\n",
       "      <td>Yuki Tsunoda</td>\n",
       "      <td>85.2</td>\n",
       "      <td>AlphaTauri</td>\n",
       "      <td>21.3</td>\n",
       "      <td>50</td>\n",
       "      <td>+1:07.494</td>\n",
       "      <td>0</td>\n",
       "      <td>16</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>12.0</td>\n",
       "      <td>Nico Hülkenberg</td>\n",
       "      <td>27.0</td>\n",
       "      <td>Haas F1 Team</td>\n",
       "      <td>21.0</td>\n",
       "      <td>50</td>\n",
       "      <td>+1:10.588</td>\n",
       "      <td>0</td>\n",
       "      <td>11</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>13.0</td>\n",
       "      <td>Guanyu Zhou</td>\n",
       "      <td>24.0</td>\n",
       "      <td>Alfa Romeo</td>\n",
       "      <td>51.0</td>\n",
       "      <td>50</td>\n",
       "      <td>+1:16.060</td>\n",
       "      <td>0</td>\n",
       "      <td>12</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>14.0</td>\n",
       "      <td>Nyck de Vries</td>\n",
       "      <td>21.0</td>\n",
       "      <td>AlphaTauri</td>\n",
       "      <td>21.3</td>\n",
       "      <td>50</td>\n",
       "      <td>+1:17.478</td>\n",
       "      <td>0</td>\n",
       "      <td>18</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>15.0</td>\n",
       "      <td>Oscar Piastri</td>\n",
       "      <td>85.7</td>\n",
       "      <td>McLaren</td>\n",
       "      <td>1.0</td>\n",
       "      <td>50</td>\n",
       "      <td>+1:25.021</td>\n",
       "      <td>0</td>\n",
       "      <td>9</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>16.0</td>\n",
       "      <td>Logan Sargeant</td>\n",
       "      <td>85.8</td>\n",
       "      <td>Williams</td>\n",
       "      <td>3.0</td>\n",
       "      <td>50</td>\n",
       "      <td>+1:26.293</td>\n",
       "      <td>0</td>\n",
       "      <td>20</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>17.0</td>\n",
       "      <td>Lando Norris</td>\n",
       "      <td>84.6</td>\n",
       "      <td>McLaren</td>\n",
       "      <td>1.0</td>\n",
       "      <td>50</td>\n",
       "      <td>+1:26.445</td>\n",
       "      <td>0</td>\n",
       "      <td>19</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>18.0</td>\n",
       "      <td>Valtteri Bottas</td>\n",
       "      <td>77.0</td>\n",
       "      <td>Alfa Romeo</td>\n",
       "      <td>51.0</td>\n",
       "      <td>49</td>\n",
       "      <td>+1 Lap</td>\n",
       "      <td>0</td>\n",
       "      <td>14</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>NaN</td>\n",
       "      <td>Alexander Albon</td>\n",
       "      <td>23.0</td>\n",
       "      <td>Williams</td>\n",
       "      <td>3.0</td>\n",
       "      <td>27</td>\n",
       "      <td>Brakes</td>\n",
       "      <td>0</td>\n",
       "      <td>17</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>NaN</td>\n",
       "      <td>Lance Stroll</td>\n",
       "      <td>84.0</td>\n",
       "      <td>Aston Martin</td>\n",
       "      <td>11.7</td>\n",
       "      <td>16</td>\n",
       "      <td>Engine</td>\n",
       "      <td>0</td>\n",
       "      <td>6</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    position           driver  driverid     constructor  constructorid  laps  \\\n",
       "0        1.0     Sergio Pérez      81.5        Red Bull            9.0    50   \n",
       "1        2.0   Max Verstappen      50.0        Red Bull            9.0    50   \n",
       "2        3.0  Fernando Alonso       4.0    Aston Martin           11.7    50   \n",
       "3        4.0   George Russell      84.7        Mercedes           13.1    50   \n",
       "4        5.0   Lewis Hamilton       1.0        Mercedes           13.1    50   \n",
       "5        6.0     Carlos Sainz      83.2         Ferrari            6.0    50   \n",
       "6        7.0  Charles Leclerc      84.4         Ferrari            6.0    50   \n",
       "7        8.0     Esteban Ocon      83.9  Alpine F1 Team           21.4    50   \n",
       "8        9.0     Pierre Gasly      84.2  Alpine F1 Team           21.4    50   \n",
       "9       10.0  Kevin Magnussen      76.0    Haas F1 Team           21.0    50   \n",
       "10      11.0     Yuki Tsunoda      85.2      AlphaTauri           21.3    50   \n",
       "11      12.0  Nico Hülkenberg      27.0    Haas F1 Team           21.0    50   \n",
       "12      13.0      Guanyu Zhou      24.0      Alfa Romeo           51.0    50   \n",
       "13      14.0    Nyck de Vries      21.0      AlphaTauri           21.3    50   \n",
       "14      15.0    Oscar Piastri      85.7         McLaren            1.0    50   \n",
       "15      16.0   Logan Sargeant      85.8        Williams            3.0    50   \n",
       "16      17.0     Lando Norris      84.6         McLaren            1.0    50   \n",
       "17      18.0  Valtteri Bottas      77.0      Alfa Romeo           51.0    49   \n",
       "18       NaN  Alexander Albon      23.0        Williams            3.0    27   \n",
       "19       NaN     Lance Stroll      84.0    Aston Martin           11.7    16   \n",
       "\n",
       "           time  points  grid  \n",
       "0   1:21:14.894      25     1  \n",
       "1         5.355      19    15  \n",
       "2        20.728      15     3  \n",
       "3        25.866      12     4  \n",
       "4        31.065      10     8  \n",
       "5        35.876       8     5  \n",
       "6        43.162       6     2  \n",
       "7        52.832       4     7  \n",
       "8        54.747       2    10  \n",
       "9     +1:04.826       1    13  \n",
       "10    +1:07.494       0    16  \n",
       "11    +1:10.588       0    11  \n",
       "12    +1:16.060       0    12  \n",
       "13    +1:17.478       0    18  \n",
       "14    +1:25.021       0     9  \n",
       "15    +1:26.293       0    20  \n",
       "16    +1:26.445       0    19  \n",
       "17       +1 Lap       0    14  \n",
       "18       Brakes       0    17  \n",
       "19       Engine       0     6  "
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Libraries, Read Out Dataset\n",
    "\n",
    "import matplotlib.pyplot as plt\n",
    "import seaborn as sns\n",
    "import pandas as pd\n",
    "import numpy as np\n",
    "%matplotlib inline\n",
    "dataset = pd.read_csv('Saudi Arabian GP 2023.csv')\n",
    "dataset.head(20)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [],
   "source": [
    "# X = Drivers ID, y = Final Position, Z = Constructors ID, H = Grid\n",
    "\n",
    "X = dataset.iloc[:-2, 2:-6].values\n",
    "y = dataset.iloc[:-2, :-8].values\n",
    "Z = dataset.iloc[:-2, 4:-4].values\n",
    "H = dataset.iloc[:-2, 8:].values"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [
    {
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      ],
      "text/plain": [
       "LinearRegression()"
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Machine Learning Regression Grid vs Final Position\n",
    "\n",
    "from sklearn.linear_model import LinearRegression\n",
    "regressor = LinearRegression()\n",
    "regressor.fit(H, y)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0, 0.5, 'Position')"
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
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      "text/plain": [
       "<Figure size 1500x1000 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Saudi Arabian GP 23 Driver Position\n",
    "\n",
    "plt.figure(figsize=(15,10))\n",
    "plt.grid(color = 'green', linestyle = '--', linewidth = 0.5)\n",
    "plt.scatter(X, y, color = 'blue')\n",
    "plt.title('Saudi Arabian GP 23 Driver Position')\n",
    "plt.xlabel('Driver ID')\n",
    "plt.ylabel('Position')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0, 0.5, 'Position')"
      ]
     },
     "execution_count": 24,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<Figure size 1500x1000 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Saudi Arabian GP 23 Constructor Position\n",
    "\n",
    "plt.figure(figsize=(15,10))\n",
    "plt.grid(color = 'green', linestyle = '--', linewidth = 0.5)\n",
    "plt.scatter(Z, y, color = 'blue')\n",
    "plt.title('Saudi Arabian GP 23 Constructor Positions')\n",
    "plt.xlabel('Constructor ID')\n",
    "plt.ylabel('Position')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0, 0.5, 'Drivers')"
      ]
     },
     "execution_count": 25,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<Figure size 1500x1000 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Saudi Arabian GP 23 Driver Points\n",
    "\n",
    "f, ax = plt.subplots(figsize = (15, 10))\n",
    "sns.barplot(x='points', y='driver', data=dataset)\n",
    "plt.title('Saudi Arabian GP 23 Driver Points')\n",
    "plt.xlabel('GP Points')\n",
    "plt.ylabel('Drivers')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0, 0.5, 'Constructors')"
      ]
     },
     "execution_count": 26,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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YESNG5Mwzz8zjjz+eGTNmLPC1AcCSJJQEAJYKG2ywQU466aT84x//yLvvvptjjjkmb775Zs4777wkyRdffJHNN988TzzxRM4888yMGjUqTz31VG6++eYkX23FXliffPJJll9++Tna27RpU+vruP/++/PGG2/kF7/4RSorKzNx4sRMnDgxv/zlLzNlypRcd911c5wzt6dhX3jhhTnssMOy0UYb5aabbsrjjz+ep556Kj179pzrtc6t5jZt2mT69On54osv5lprVVVVtttuu9x888058cQTc9999+XJJ5/M448/nmTun+myyy5b4/3sLbjz+/xn30/xmyFNs2bN8tRTT+Wpp57KgAED5nruqquumqeeeipPP/10XnzxxUycODHXXHNNKioq5jnfNw0cODBnnnlmzjrrrBxxxBHz7NetW7dsvPHG2XffffPAAw+kVCrllFNOme/Ys6/tjTfeWKBaPvnkk7n+vNu1a1d9/Ou+7fOuqKjIgw8+mPXWWy+nnHJK1l577bRr1y4DBgxYqHBrUZ7I/tFHH6Vu3bq1/r1Z2M9kYWvdbLPNqr9DY8aMycSJEzNkyJA0aNAgn332WUql0kLN/02NGzeu8T8Ekq9+TlOnTl2g+m644YYccMABufLKK9O9e/css8wy+fWvfz3Xe9sCwPeJe0oCAEud+vXrZ8CAAbnooovy4osvJvkq7Hv33XczatSoGvdlnDhx4hznN2zYcK4PX/nmw1uWXXbZPPnkk3P0W5QwYOjQoUm+ChUvvPDCuR4/5JBDarTN7QE611xzTbbccstcdtllNdpn3yfwm+ZW8/vvv58GDRrUWAH2dS+++GKef/75jBgxIgcccEB1+7hx4+bav7bWX3/9tGzZMrfeemv++Mc/VrfXrVs3G2ywQXUtczP7oT21NXDgwJx++uk5/fTTvzVg/LpmzZpljTXWyKuvvjrffttvv31OOeWU3HLLLenZs+e3jrvsssvmvffem6P93XffTZK0atVqgWucbZ111sn111+fUqmU//73vxkxYkT+8Ic/pFGjRvN8sNA3ze072LBhw+qHtXzdN3+PWrdunVmzZuX999+vVbi5sJ/JwjxwKvkquJ3Xd6hly5apU6fOYv+ZLIxWrVrl4osvzsUXX5zx48fn3//+d04++eR8+OGHufPOO7/TuQFgUVgpCQD8oM0tDEj+39bh2auVZgcRs1eKzXbFFVfMcW7Hjh3z6quv1ghUPvnkkzz66KM1+vXo0SOff/559ROCZ/v73/++kFfxlc8++yz/+te/summm+aBBx6Y47XvvvvmqaeemmcA93VlZWVzXOt///vfObb3znbzzTfXWJn1+eef59Zbb83mm2+eunXrznOOZME+00XRoEGDnHDCCXnxxRdz7rnnLtax5+eMM87I6aefnt///vfzXIk5Lx9//HFeeOGFdOrUab79unXrlh122CFDhw6d58OWnn766YwfPz5JsvXWW1cH7F939dVXp3Hjxtl4440Xqs6vKysry09+8pNcdNFFadGiRZ599tnqY+Xl5Qu9mrhjx4758MMP88EHH1S3TZ8+PXfddVeNfjvssEOSzBGgf9O8ath6660zZsyYGvUmX30mZWVl6dGjx0LVvTCaNGmSjTbaKDfffHON2qqqqnLNNddkxRVXzOqrr77I8yzIiuLkq5W3RxxxRLbddts5Pg8A+L6xUhIA+EHbfvvts+KKK6ZXr15ZY401UlVVldGjR2fQoEFp2rRpjj766CTJJptskpYtW+bQQw/NgAEDUr9+/Vx77bV5/vnn5xhz//33zxVXXJH99tsvBx98cD755JOcd955czxx+Ne//nUuuuii/PrXv85ZZ52V1VZbLbfffvscocuCuvbaazN16tQcddRRczwdO/lqRdi1116boUOH5qKLLprvWDvvvHPOOOOMDBgwIFtssUVeeeWV/OEPf8jKK6+cmTNnztG/bt262XbbbXPsscemqqoq5557biorKzNw4MB5zrHGGmtk1VVXzcknn5xSqZRlllkmt956a+65556FvvZvc9JJJ+Xll1/OySefnIceeih77bVXOnbsmGnTpuX111/PlVdembp166Zx48aLZb5Bgwalf//+6dmzZ3baaafqLemzzQ7/Jk2alG233Tb77LNPVltttTRq1CivvvpqBg8enGnTpi1QmHn11VenZ8+e2WGHHdKnT5/ssMMOadmyZd57773ceuutue666/LMM89kpZVWyoABAzJy5Mj06NEj/fv3zzLLLJNrr702t912W84777yF2paeJCNHjsyll16aXXfdNausskpKpVJuvvnmTJw4sfqepslXqylHjRqVW2+9NW3btk2zZs3SuXPn+Y691157pX///tl7771zwgknZOrUqRkyZMgc9yjdfPPNs//+++fMM8/MBx98kJ133jnl5eV57rnn0rhx4xx55JHVNVx//fW54YYbssoqq6Rhw4ZZZ511cswxx+Tqq6/OTjvtlD/84Q/p0KFDbrvttlx66aU57LDDFksoOD9nn312tt122/To0SPHH398GjRokEsvvTQvvvhirrvuuoVemTk3zZo1S4cOHfJ///d/2XrrrbPMMsukVatWadmyZXr06JF99tkna6yxRvUtDe68887svvvui+HqAOA7tAQfsgMAsMhuuOGG0j777FNabbXVSk2bNi3Vr1+/tNJKK5X233//OZ5+/Oijj5a6d+9eaty4cal169algw46qPTss8/O8aTsUqlUuuqqq0prrrlmqWHDhqW11lqrdMMNN8z1acJvv/12aY899ig1bdq01KxZs9Iee+xRevTRR2v19O311luvtNxyy5WmTZs2zz4bb7xxqVWrVqVp06ZVP833H//4xxz9pk2bVjr++ONLK6ywQqlhw4albt26lW655ZY5rmH2E4nPPffc0sCBA0srrrhiqUGDBqWuXbuW7rrrrhpjzu3p22PGjCltu+22pWbNmpVatmxZ+sUvflEaP378HE8Knn39H3300beOOT///ve/S7169Sotv/zypXr16pWaNWtWWm+99UrHHXfcHE+wnv307drYYostqp+kPbfXbFOnTi0ddNBBpTXXXLPUtGnTUr169Uorrrhiab/99iu99NJLCzzfl19+WRoyZEipe/fupebNm5fq1atXateuXWn33Xcv3XbbbTX6vvDCC6VevXqVKioqSg0aNCj95Cc/meP7O6/vxuyf9+z+L7/8culXv/pVadVVVy01atSoVFFRUdpwww1LI0aMqHHe6NGjS5tuummpcePGpSTVT8Ge/fN76qmn5npdt99+e2m99dYrNWrUqLTKKquULrnkkrn+LsyaNat00UUXlbp06VJq0KBBqaKiotS9e/fSrbfeWt3nzTffLG233XalZs2alZLU+B6/9dZbpX322ae07LLLlurXr1/q3Llz6fzzzy/NmjVrjms///zz5/lz+KYOHTqUdtppp2/t9/DDD5e22mqrUpMmTUqNGjUqbbzxxjVqL5Xm/fTtJk2azDHe3D6je++9t9S1a9fqp7wfcMABpalTp5YOPfTQ0rrrrltq3rx5qVGjRqXOnTuXBgwYUJo8efICXycALAllpVKpVFQACgAAAADgnpIAAAAAQKGEkgAAAABAoYSSAAAAAEChhJIAAAAAQKGEkgAAAABAoYSSAAAAAECh6i3pAvhhq6qqyrvvvptmzZqlrKxsSZcDAAAAwBJUKpXy+eefp127dqlTZ97rIYWSLJJ333037du3X9JlAAAAAPA9MmHChKy44orzPC6UZJE0a9YsyVdftObNmy/hagAAAABYkiorK9O+ffvqzGhehJIsktlbtps3by6UBAAAACBJvvU2fx50AwAAAAAUSigJAAAAABRKKAkAAAAAFEooCQAAAAAUyoNuWCx+9vvrUre80ZIuAwAAAL53njn/10u6BPjesVISAAAAACiUUBIAAAAAKJRQEgAAAAAolFASAAAAACiUUBIAAAAAKJRQEgAAAAAolFASAAAAACiUUBIAAAAAKJRQEgAAAAAolFASAAAAACiUUBIAAAAAKJRQEgAAAAAolFASAAAAACiUUBIAAAAAKJRQEgAAAAAolFASAAAAACiUUBIAAAAAKJRQEgAAAAAolFASAAAAACiUUBIAAAAAKJRQEgAAAAAolFASAAAAACiUUBIAAAAAKJRQEgAAAAAolFASAAAAACiUUPJ76M0330xZWVlGjx79nc91+umnZ7311qt+37t37+y6667f+bwAAAAA/HgJJRdB7969U1ZWlrKystSrVy8rrbRSDjvssHz22Wff+dxbbrll9dx16tTJ8ssvn1/84hd56623vvO5AQAAAGBRCCUXUc+ePfPee+/lzTffzJVXXplbb701hx9+eCFzH3zwwXnvvffyzjvv5P/+7/8yYcKE7LfffoXMDQAAAAC1VW9JF/BDV15enjZt2iRJVlxxxey1114ZMWJEjT7Dhw/PeeedlzfeeCMdO3bMUUcdVSO4fPLJJ3PIIYdk7Nix6dKlS0499dQFmrtx48bVc7dt2za/+93vcuihh1YfHzFiRPr27ZuJEydWt91yyy3ZbbfdUiqVannFAAAAzEvTV+5InRmTl3QZfM/ss8+dS7oEvodat26dwYMHL+kylhih5GL0+uuv584770z9+vWr2/76179mwIABueSSS9K1a9c899xzOfjgg9OkSZMccMABmTx5cnbeeedstdVWueaaa/LGG2/k6KOPXui5P/300/zjH//IRhtttDgvaQ7Tpk3LtGnTqt9XVlZ+p/MBAAD8kNSZMTl1pgslqemDD3wn4JuEkoto5MiRadq0aWbNmpWpU6cmSS688MLq42eccUYGDRqU3XffPUmy8sorZ8yYMbniiitywAEH5Nprr82sWbMybNiwNG7cOGuvvXbefvvtHHbYYd8696WXXporr7wypVIpU6ZMyeqrr5677rrru7nQ/9/ZZ5+dgQMHfqdzAAAAALB0E0ouoh49euSyyy7LlClTcuWVV+bVV1/NkUcemST56KOPMmHChBx44IE5+OCDq8+ZOXNmKioqkiRjx47NT37ykzRu3Lj6ePfu3Rdo7n333bd6q/cHH3yQP/7xj9luu+3yzDPPpFmzZovrEmvo169fjj322Or3lZWVad++/XcyFwAAwA9NVf0mS7oEvofatmy6pEvge6h169ZLuoQlSii5iJo0aZJOnTolSYYMGZIePXpk4MCBOeOMM1JVVZXkqy3c39xWXbdu3SRZpHs7VlRUVM/dqVOnDB06NG3bts0NN9yQgw46KHXq1Jlj/BkzZtR6vuSre2iWl5cv0hgAAABLqy8677CkS+B76IHzf72kS4DvHU/fXswGDBiQCy64IO+++26WX375rLDCCnn99dfTqVOnGq+VV145SbLWWmvl+eefz5dfflk9xuOPP16ruWcHnbPHat26dT7//PNMnvz/7l0xevToWl4ZAAAAACweQsnFbMstt8zaa6+dP/7xj0mS008/PWeffXYGDx6cV199NS+88EKGDx9efd/JffbZJ3Xq1MmBBx6YMWPG5Pbbb88FF1ywQHNNmTIl77//ft5///08//zzOfzww9OwYcNst912SZKNNtoojRs3zimnnJJx48bl73//+xxPBgcAAACAogklvwPHHnts/vrXv2bChAk56KCDcuWVV2bEiBFZZ511ssUWW2TEiBHVKyWbNm2aW2+9NWPGjEnXrl1z6qmn5txzz12gef7617+mbdu2adu2bXr06JGPPvoot99+ezp37pwkWWaZZXLNNdfk9ttvzzrrrJPrrrsup59++nd12QAAAACwQMpKi3JTQ370KisrU1FRkZ8ceXnqljda0uUAAADA984z7inJj8jsrGjSpElp3rz5PPtZKQkAAAAAFEooCQAAAAAUSigJAAAAABRKKAkAAAAAFEooCQAAAAAUSigJAAAAABRKKAkAAAAAFEooCQAAAAAUSigJAAAAABRKKAkAAAAAFEooCQAAAAAUSigJAAAAABRKKAkAAAAAFEooCQAAAAAUSigJAAAAABRKKAkAAAAAFEooCQAAAAAUSigJAAAAABRKKAkAAAAAFEooCQAAAAAUSigJAAAAABRKKAkAAAAAFEooCQAAAAAUSigJAAAAABSq3pIugKXDQ2f+Ks2bN1/SZQAAAADwA2ClJAAAAABQKKEkAAAAAFAooSQAAAAAUCihJAAAAABQKKEkAAAAAFAooSQAAAAAUCihJAAAAABQKKEkAAAAAFAooSQAAAAAUCihJAAAAABQKKEkAAAAAFAooSQAAAAAUCihJAAAAABQKKEkAAAAAFCoeku6AJYOE87ZOM0a1l3SZQB8r63U/4UlXQIAAMD3gpWSAAAAAEChhJIAAAAAQKGEkgAAAABAoYSSAAAAAEChhJIAAAAAQKGEkgAAAABAoYSSAAAAAEChhJIAAAAAQKGEkgAAAABAoYSSAAAAAEChhJIAAAAAQKGEkgAAAABAoYSSAAAAAEChhJIAAAAAQKGEkgAAAABAoYSSAAAAAEChhJIAAAAAQKGEkgAAAABAoYSSAAAAAEChhJIAAAAAQKGEkgAAAABAoYSSAAAAAEChhJIAAAAAQKGEkgAAAABAoYSSAAAAAEChhJI/Im+++WbKysoyevToJV0KAAAAAD9iS00o+eijj6Zu3brp2bPnQp1XdFDXsWPHlJWV5frrr5/j2Nprr52ysrKMGDFikefp3bt3dt111xpt7du3z3vvvZcuXbos8vgAAAAAUFtLTSg5bNiwHHnkkXnkkUcyfvz4JV3OfLVv3z7Dhw+v0fb444/n/fffT5MmTRZp7FmzZqWqqmqux+rWrZs2bdqkXr16izQHAAAAACyKpSKdmjx5cm688cY89dRTef/99zNixIj079+/+vhnn32WI444InfffXe++OKLrLjiijnllFPym9/8JiuvvHKSpGvXrkmSLbbYIqNGjUpVVVXOPPPM/OUvf8lHH32UNddcM+ecc071Ssw333wzK6+8cm666ab86U9/yhNPPJHVVlstl19+ebp37z7fevfdd99cdNFFmTBhQtq3b5/kq1B13333zdVXX12j74UXXpjhw4fn9ddfzzLLLJNevXrlvPPOS9OmTZMkI0aMSN++fXPNNdfkxBNPzKuvvlpjnLKysiTJAw88kI4dO2bllVfOc889l/XWWy+jRo1Kjx49cu+99+akk07KmDFjst5662X48OHp3LnzQv0Mfv/UMqlff6n4OgF8Z+rts8+SLgHgB6N169YZPHjwki4DAPiOLBUp0g033JDOnTunc+fO2W+//XLkkUfmtNNOqw7kTjvttIwZMyZ33HFHWrVqlXHjxuXLL79Mkjz55JPZcMMNc++992bttddOgwYNkiSDBw/OoEGDcsUVV6Rr164ZNmxYfv7zn+ell17KaqutVj33qaeemgsuuCCrrbZaTj311PzqV7/KuHHj5rsacfnll8/222+fq666Kr///e8zZcqU3HDDDXnwwQfnCCXr1KmTIUOGpGPHjnnjjTdy+OGH58QTT8yll15a3WfKlCk5++yzc+WVV2bZZZdNmzZtMnXq1FRWVlavyFxmmWXy7rvvzrWeU089NYMGDUrr1q1z6KGHpk+fPvnPf/4z177Tpk3LtGnTqt9XVlYmST6dXjf1qurO85oBSPLBB0u6AgAAgO+FpWL79tChQ7PffvslSXr27Jkvvvgi9913X/Xx8ePHp2vXrtlggw3SsWPHbLPNNunVq1eSr/4PbJLqMG+ZZZZJklxwwQU56aSTsvfee6dz584599xzs9566+Xiiy+uMffxxx+fnXbaKauvvnoGDhyYt956K+PGjfvWmvv06ZMRI0akVCrln//8Z1ZdddWst956c/Tr27dvevTokZVXXjlbbbVVzjjjjNx44401+syYMSOXXnppNtlkk3Tu3DkVFRVp1KhRysvL06ZNm7Rp06Y6bJ2bs846K1tssUXWWmutnHzyyXn00UczderUufY9++yzU1FRUf2avdITAAAAABbUD36l5CuvvJInn3wyN998c5KkXr162WuvvTJs2LBss802SZLDDjsse+yxR5599tlst9122XXXXbPJJpvMc8zKysq8++672XTTTWu0b7rppnn++edrtK277rrVf27btm2S5MMPP8waa6wx37p32mmnHHLIIXnooYcybNiw9OnTZ679Hnjggfzxj3/MmDFjUllZmZkzZ2bq1KmZPHly9f0nGzRoUKOOhTWva1hppZXm6NuvX78ce+yx1e8rKyvTvn37LNNgVurXL6t1DQA/BvVatFvSJQD8YMxePAAALJ1+8KHk0KFDM3PmzKywwgrVbaVSKfXr189nn32Wli1bZocddshbb72V2267Lffee2+23nrr/O53v8sFF1ww37Fnb//++rjfbKtfv/4c/ef1oJmvq1evXvbff/8MGDAgTzzxRP71r3/N0eett97KjjvumEMPPTRnnHFGlllmmTzyyCM58MADM2PGjOp+jRo1mqOuhbEw11BeXp7y8vI52s/86adp1tD2bYD5Wan/qCVdAgAAwPfCD3r79syZM3P11Vdn0KBBGT16dPXr+eefT4cOHXLttddW923dunV69+6da665JhdffHH+8pe/JEn1tuZZs2ZV923evHnatWuXRx55pMZ8jz76aNZcc83FVn+fPn3y4IMPZpdddknLli3nOP70009n5syZGTRoUDbeeOOsvvrq87wv5Dc1aNCgxjUBAAAAwPfFD3ql5MiRI/PZZ5/lwAMPTEVFRY1je+65Z4YOHZojjjgi/fv3z/rrr5+1114706ZNy8iRI6vDxeWWWy6NGjXKnXfemRVXXDENGzZMRUVFTjjhhAwYMKD6Xo/Dhw/P6NGjawSdi2rNNdfMxx9/nMaNG8/1+KqrrpqZM2fmT3/6U3r16pX//Oc/ufzyyxdo7I4dO+auu+7KK6+8kmWXXXaOzwcAAAAAlpQf9ErJoUOHZptttplr4LbHHntk9OjRefbZZ9OgQYP069cv6667bn72s5+lbt26uf7665N8tY16yJAhueKKK9KuXbvssssuSZKjjjoqxx13XI477riss846ufPOO/Pvf/+7xpO3F4dll102jRo1muux9dZbLxdeeGHOPffcdOnSJddee23OPvvsBRr34IMPTufOnbPBBhukdevW83yaNgAAAAAUraxUKpWWdBH8cFVWVqaioiIv9lvTPSUBvsVK/V9Y0iUAAAB8p2ZnRZMmTUrz5s3n2e8HvVISAAAAAPjhEUoCAAAAAIUSSgIAAAAAhRJKAgAAAACFEkoCAAAAAIUSSgIAAAAAhRJKAgAAAACFEkoCAAAAAIUSSgIAAAAAhRJKAgAAAACFEkoCAAAAAIUSSgIAAAAAhRJKAgAAAACFEkoCAAAAAIUSSgIAAAAAhRJKAgAAAACFEkoCAAAAAIUSSgIAAAAAhRJKAgAAAACFEkoCAAAAAIUSSgIAAAAAhRJKAgAAAACFEkoCAAAAAIUSSgIAAAAAhaq3pAtg6dD+5MfTvHnzJV0GAAAAAD8AVkoCAAAAAIUSSgIAAAAAhRJKAgAAAACFEkoCAAAAAIUSSgIAAAAAhRJKAgAAAACFEkoCAAAAAIUSSgIAAAAAhRJKAgAAAACFEkoCAAAAAIUSSgIAAAAAhRJKAgAAAACFEkoCAAAAAIUSSgIAAAAAhaq3pAtg6bDt5dumXiNfJwD4PvjPkf9Z0iUAAMB8WSkJAAAAABRKKAkAAAAAFEooCQAAAAAUSigJAAAAABRKKAkAAAAAFEooCQAAAAAUSigJAAAAABRKKAkAAAAAFEooCQAAAAAUSigJAAAAABRKKAkAAAAAFEooCQAAAAAUSigJAAAAABRKKAkAAAAAFEooCQAAAAAUSigJAAAAABRKKAkAAAAAFEooCQAAAAAUSigJAAAAABRKKAkAAAAAFEooCQAAAAAUSigJAAAAABRKKAkAAAAAFEooCQAAAAAUSigJAAAAABRKKLmU6d27d3bdddclXQYAAAAAzJNQch569+6dsrKyHHrooXMcO/zww1NWVpbevXsXXxgAAAAA/MAJJeejffv2uf766/Pll19Wt02dOjXXXXddVlpppVqPWyqVMnPmzMVRIgAAAAD84NRb0gV8n3Xr1i2vv/56br755uy7775Jkptvvjnt27fPKqusUt2vVCrl/PPPz+WXX5733nsvq6++ek477bTsueeeSZJRo0alR48eufPOO3Pqqafmv//9b+66665sscUWOf/88/PXv/41EyZMyPLLL59DDjkkp556apLknXfeybHHHpu77747derUyWabbZbBgwenY8eOSZJZs2blhBNOyLBhw1K3bt0ceOCBKZVKNa7h22r77LPPcsQRR+Tuu+/OF198kRVXXDGnnHJKfvOb33zXHy8AfO81eKhByr4sW9JlLLR9HttnSZdQK61bt87gwYOXdBkAABRAKPktfvOb32T48OHVoeSwYcPSp0+fjBo1qrrP73//+9x888257LLLstpqq+Whhx7Kfvvtl9atW2eLLbao7nfiiSfmggsuyCqrrJIWLVqkX79++etf/5qLLroom222Wd577728/PLLSZIpU6akR48e2XzzzfPQQw+lXr16OfPMM9OzZ8/897//TYMGDTJo0KAMGzYsQ4cOzVprrZVBgwblX//6V7baaqsFru20007LmDFjcscdd6RVq1YZN25cjZWh3zRt2rRMmzat+n1lZeXi+qgB4Hun7MuyH2Qo+cGXHyzpEgAAYL7KSt9cWkeSr+4pOXHixFx55ZVZccUV8/LLL6esrCxrrLFGJkyYkIMOOigtWrTIn//857Rq1Sr3339/unfvXn3+QQcdlClTpuTvf/979UrJW265JbvsskuS5PPPP0/r1q1zySWX5KCDDppj/mHDhuW8887L2LFjU1b21X8MTZ8+PS1atMgtt9yS7bbbLu3atcvRRx+dk046KUkyc+bMrLzyyll//fVzyy23ZPLkyd9a289//vO0atUqw4YNW6DP5fTTT8/AgQPnaN/w3A1Tr5GMG4ClS/ld5T/IUPKHavnll8/f//73JV0GAACLoLKyMhUVFZk0aVKaN28+z35SpG/RqlWr7LTTTrnqqqtSKpWy0047pVWrVtXHx4wZk6lTp2bbbbetcd706dPTtWvXGm0bbLBB9Z/Hjh2badOmZeutt57rvM8880zGjRuXZs2a1WifOnVqXnvttUyaNCnvvfdejbCxXr162WCDDaq3cC9IbYcddlj22GOPPPvss9luu+2y6667ZpNNNpnn59GvX78ce+yx1e8rKyvTvn37efYHgB+yUqMf5v+7bdO8zZIuoVZat269pEsAAKAgQskF0KdPnxxxxBFJkj//+c81jlVVVSVJbrvttqywwgo1jpWXl9d436RJk+o/N2rUaL5zVlVVZf3118+11147x7EF/Qv7gtS2ww475K233sptt92We++9N1tvvXV+97vf5YILLpjrmOXl5XNcFwAsrab/bPqSLqFW/n6k1YYAAHy/CSUXQM+ePTN9+lf/UbL99tvXOLbWWmulvLw848ePr3H/yG+z2mqrpVGjRrnvvvvmun27W7duueGGG7LccsvNc6lr27Zt8/jjj+dnP/tZkq+2bz/zzDPp1q3bQtXWunXr9O7dO717987mm2+eE044YZ6hJAAAAAAsKqHkAqhbt27Gjh1b/eeva9asWY4//vgcc8wxqaqqymabbZbKyso8+uijadq0aQ444IC5jtmwYcOcdNJJOfHEE9OgQYNsuumm+eijj/LSSy/lwAMPzL777pvzzz8/u+yyS/7whz9kxRVXzPjx43PzzTfnhBNOyIorrpijjz4655xzTlZbbbWsueaaufDCCzNx4sSFqq1///5Zf/31s/baa2fatGkZOXJk1lxzze/sswQAAAAAoeQCmt+NOc8444wst9xyOfvss/P666+nRYsW6datW0455ZT5jnnaaaelXr166d+/f9599920bds2hx56aJKkcePGeeihh3LSSSdl9913z+eff54VVlghW2+9dXUtxx13XN5777307t07derUSZ8+fbLbbrtl0qRJC1xbgwYN0q9fv7z55ptp1KhRNt9881x//fWL+nEBAAAAwDx5+jaLZPYTlTx9GwC+P/5z5H+WdAkAAPxILejTt+sUWBMAAAAAgFASAAAAACiWUBIAAAAAKJRQEgAAAAAolFASAAAAACiUUBIAAAAAKJRQEgAAAAAolFASAAAAACiUUBIAAAAAKJRQEgAAAAAolFASAAAAACiUUBIAAAAAKJRQEgAAAAAolFASAAAAACiUUBIAAAAAKJRQEgAAAAAolFASAAAAACiUUBIAAAAAKJRQEgAAAAAolFASAAAAACiUUBIAAAAAKJRQEgAAAAAolFASAAAAACiUUBIAAAAAKFS9JV0AS4d7Dr0nzZs3X9JlAAAAAPADYKUkAAAAAFAooSQAAAAAUCihJAAAAABQKKEkAAAAAFAooSQAAAAAUCihJAAAAABQKKEkAAAAAFAooSQAAAAAUCihJAAAAABQKKEkAAAAAFAooSQAAAAAUCihJAAAAABQKKEkAAAAAFAooSQAAAAAUKh6S7oAlg6P9NwhTer5OgFLhy0eenBJlwAAALBUs1ISAAAAACiUUBIAAAAAKJRQEgAAAAAolFASAAAAACiUUBIAAAAAKJRQEgAAAAAolFASAAAAACiUUBIAAAAAKJRQEgAAAAAolFASAAAAACiUUBIAAAAAKJRQEgAAAAAolFASAAAAACiUUBIAAAAAKJRQEgAAAAAolFASAAAAACiUUBIAAAAAKJRQEgAAAAAolFASAAAAACiUUBIAAAAAKJRQEgAAAAAolFASAAAAACiUUBIAAAAAKJRQEgAAAAAolFASAAAAACiUUJIaRowYkRYtWizpMgAAAABYigklC9a7d++UlZXN8Ro3btySLi1Jstdee+XVV19d0mUAAAAAsBSrt6QL+DHq2bNnhg8fXqOtdevWCz3OjBkzUr9+/W9tW5jxGjVqlEaNGtXqfAAAAABYEELJJaC8vDxt2rSZo/3WW2/N6aefnpdeeint2rXLAQcckFNPPTX16n31YyorK8tll12WO+64I/fee2+OP/74lJWV5ZZbbslRRx2VM888M2+++WZmzZqVu+66K2eeeWZefPHF1K1bN927d8/gwYOz6qqrJknefPPNrLzyyrnhhhty6aWX5vHHH89ll12WsrKy9O3bNxMnTizyIwGWUsPr1k1l2ZKuYuFdsc8+S7qEhda6desMHjx4SZcBAACwQISS3xN33XVX9ttvvwwZMiSbb755Xnvttfz2t79NkgwYMKC634ABA3L22WfnoosuSt26dTN8+PCMGzcuN954Y2666abUrVs3STJ58uQce+yxWWeddTJ58uT0798/u+22W0aPHp06df7frv2TTjopgwYNyvDhw1NeXp677757vnVOmzYt06ZNq35fWVm5OD8GYClTWZZMKvvhpZKTPvhgSZcAAACwVBNKLgEjR45M06ZNq9/vsMMO+eCDD3LyySfngAMOSJKsssoqOeOMM3LiiSfWCCX32Wef9OnTp8Z406dPz9/+9rcaW8D32GOPGn2GDh2a5ZZbLmPGjEmXLl2q2/v27Zvdd999gWs/++yzM3DgwAXuDwAAAADfJJRcAnr06JHLLrus+n2TJk3SqVOnPPXUUznrrLOq22fNmpWpU6dmypQpady4cZJkgw02mGO8Dh06zHFPytdeey2nnXZaHn/88Xz88cepqqpKkowfP75GKDm38eanX79+OfbYY6vfV1ZWpn379gs1BvDj0byUJKUlXcZCaziXW2x839Xm3sQAAABLilByCZgdQn5dVVVVBg4cONdViw0bNqxx7tzG+6ZevXqlffv2+etf/5p27dqlqqoqXbp0yfTp07/13PkpLy9PeXn5Qp0D/Hj9ZtasJV1CrWzx978v6RIAAACWakLJ74lu3brllVdemSOsrI1PPvkkY8eOzRVXXJHNN988SfLII48s8rgAAAAAsDgIJb8n+vfvn5133jnt27fPL37xi9SpUyf//e9/88ILL+TMM89cqLFatmyZZZddNn/5y1/Stm3bjB8/PieffPJ3VDkAAAAALJw6396FImy//fYZOXJk7rnnnvz0pz/NxhtvnAsvvDAdOnRY6LHq1KmT66+/Ps8880y6dOmSY445Jueff/53UDUAAAAALLyyUqn0w3sCAd8blZWVqaioyG3dN0mTehbeAkuHLR56cEmXAAAA8IM0OyuaNGlSmjdvPs9+VkoCAAAAAIUSSgIAAAAAhRJKAgAAAACFEkoCAAAAAIUSSgIAAAAAhRJKAgAAAACFEkoCAAAAAIUSSgIAAAAAhRJKAgAAAACFEkoCAAAAAIUSSgIAAAAAhRJKAgAAAACFEkoCAAAAAIUSSgIAAAAAhRJKAgAAAACFEkoCAAAAAIUSSgIAAAAAhRJKAgAAAACFEkoCAAAAAIUSSgIAAAAAhRJKAgAAAACFEkoCAAAAAIUSSgIAAAAAhRJKAgAAAACFqrekC2DpsNmdd6R58+ZLugwAAAAAfgCslAQAAAAACiWUBAAAAAAKJZQEAAAAAAollAQAAAAACiWUBAAAAAAKJZQEAAAAAAollAQAAAAACiWUBAAAAAAKJZQEAAAAAAollAQAAAAACiWUBAAAAAAKJZQEAAAAAAollAQAAAAACiWUBAAAAAAKVW9JF8DS4YpT7kij8sZLugy+J44Y1GtJlwAAAAB8j1kpCQAAAAAUSigJAAAAABRKKAkAAAAAFEooCQAAAAAUSigJAAAAABRKKAkAAAAAFEooCQAAAAAUSigJAAAAABRKKAkAAAAAFEooCQAAAAAUSigJAAAAABRKKAkAAAAAFEooCQAAAAAUSigJAAAAABRKKAkAAAAAFEooCQAAAAAUSigJAAAAABRKKAkAAAAAFEooCQAAAAAUSigJAAAAABRKKAkAAAAAFEooCQAAAAAUSigJAAAAABRKKAkAAAAAFEooCQAAAAAU6nsfSo4aNSplZWWZOHHiAp9z+umnZ7311vvOagIAAAAAau97EUo++uijqVu3bnr27LlYxjv++ONz3333LZax5qdjx44pKyur8VpxxRWrj//lL3/JlltumebNmy9QsPrNsb756t2793d7QQAAAABQgO9FKDls2LAceeSReeSRRzJ+/PhFHq9p06ZZdtllF0Nl3+4Pf/hD3nvvverXc889V31sypQp6dmzZ0455ZQFGuvr41x88cVp3rx5jbbBgwd/V5cBAAAAAIWpV5uTrrrqqrRq1So77bRTkuTEE0/MX/7yl6y11lq57rrr0qFDhwUea/Lkybnxxhvz1FNP5f3338+IESPSv3//efYfMWJE+vbtmxEjRuTEE0/M+PHjs/nmm2fYsGFp3759kq+2b99yyy0ZPXp0kqR3796ZOHFiNttsswwaNCjTp0/P3nvvnYsvvjj169dPkkyfPj2///3vc+2112bixInp0qVLzj333Gy55Zbzrb9Zs2Zp06bNXI/17ds3yVdb0BfE18epqKhIWVlZjbZbb701p59+el566aW0a9cuBxxwQE499dTUq/fVj/HCCy/M8OHD8/rrr2eZZZZJr169ct5556Vp06Y1Prtrrrkmxx13XCZMmJAdd9wxV111Vf75z39mwIABmTRpUvbbb79cfPHFqVu37gLVzXfnwf/dmKnTP1/SZSy0R/e5bkmXsNBat24t+AcAAICC1CqU/OMf/5jLLrssSfLYY4/lkksuycUXX5yRI0fmmGOOyc0337zAY91www3p3LlzOnfunP322y9HHnlkTjvttJSVlc3znClTpuSss87KVVddlQYNGuTwww/P3nvvnf/85z/zPOeBBx5I27Zt88ADD2TcuHHZa6+9st566+Xggw9OkvzmN7/Jm2++meuvvz7t2rXLv/71r/Ts2TMvvPBCVltttQW+nu/KXXfdlf322y9DhgzJ5ptvntdeey2//e1vkyQDBgxIktSpUydDhgxJx44d88Ybb+Twww/PiSeemEsvvbR6nClTpmTIkCG5/vrr8/nnn2f33XfP7rvvnhYtWuT222/P66+/nj322CObbbZZ9tprrznqmDZtWqZNm1b9vrKy8ju+8h+3qdM/z5QZP7xQcsoHP7yaAQAAgOLUavv2hAkT0qlTpyTJLbfckj333DO//e1vc/bZZ+fhhx9eqLGGDh2a/fbbL0nSs2fPfPHFF996P8gZM2bkkksuSffu3bP++uvnqquuyqOPPponn3xynue0bNkyl1xySdZYY43svPPO2Wmnnarnee2113LdddflH//4RzbffPOsuuqqOf7447PZZptl+PDh863lpJNOStOmTatfQ4YMWajrX1BnnXVWTj755BxwwAFZZZVVsu222+aMM87IFVdcUd2nb9++6dGjR1ZeeeVstdVWOeOMM3LjjTfWGGfGjBm57LLL0rVr1/zsZz/LnnvumUceeSRDhw7NWmutlZ133jk9evTIAw88MNc6zj777FRUVFS/Zq9OBQAAAIAFVauVkk2bNs0nn3ySlVZaKXfffXeOOeaYJEnDhg3z5ZdfLvA4r7zySp588snqlZX16tXLXnvtlWHDhmWbbbaZd9H16mWDDTaofr/GGmukRYsWGTt2bDbccMO5nrP22mvX2I7ctm3bvPDCC0mSZ599NqVSKauvvnqNc6ZNm/at96Y84YQTajyAplWrVvPtX1vPPPNMnnrqqZx11lnVbbNmzcrUqVMzZcqUNG7cOA888ED++Mc/ZsyYMamsrMzMmTMzderUTJ48OU2aNEmSNG7cOKuuumr1GMsvv3w6duxYvcV7dtuHH3441zr69euXY489tvp9ZWWlYPI71LBBsyVdQq00W6bxki5hobVu3XpJlwAAAAA/GrUKJbfddtscdNBB6dq1a1599dXqe0u+9NJL6dix4wKPM3To0MycOTMrrLBCdVupVEr9+vXz2WefpWXLlvM8d27bu+e35Xv2vSO/3reqqipJUlVVlbp16+aZZ56Z4z6KXw/r5qZVq1bVq0a/S1VVVRk4cGB23333OY41bNgwb731VnbccccceuihOeOMM7LMMsvkkUceyYEHHpgZM2ZU953b5zC/z+abysvLU15evhiuiAWxxWq/XNIl1MoRg3ot6RIAAACA77FahZJ//vOfc9ppp2X8+PG56aabqlcTPvPMM/nVr361QGPMnDkzV199dQYNGpTtttuuxrE99tgj1157bY444oh5nvv0009Xr4p85ZVXMnHixKyxxhq1uZx07do1s2bNyocffpjNN9+8VmN817p165ZXXnllngHo008/nZkzZ2bQoEGpU+erXfnf3LoNAAAAAN8HCx1Kzpw5M4MHD86JJ544x7bdgQMHLvA4I0eOzGeffZYDDzwwFRUVNY7tueeeGTp06DxDyfr16+fII4/MkCFDUr9+/RxxxBHZeOON57l1+9usvvrq2XffffPrX/86gwYNSteuXfPxxx/n/vvvzzrrrJMdd9yxVuO+//77ef/99zNu3LgkyQsvvJBmzZplpZVWyjLLLLNQY/Xv3z8777xz2rdvn1/84hepU6dO/vvf/+aFF17ImWeemVVXXTUzZ87Mn/70p/Tq1Sv/+c9/cvnll9eqbgAAAAD4Li30g27q1auX888/P7NmzVqkiYcOHZptttlmjkAy+Wql5OjRo/Pss8/O9dzGjRvnpJNOyj777JPu3bunUaNGuf766xepnuHDh+fXv/51jjvuuHTu3Dk///nP88QTTyzS/RIvv/zydO3atfoJ3z/72c/StWvX/Pvf/17osbbffvuMHDky99xzT376059m4403zoUXXpgOHTokSdZbb71ceOGFOffcc9OlS5dce+21Ofvss2tdOwAAAAB8V8pKpVJpYU/adddds+uuu9Z4wEtRRowYkb59+2bixImFz82cKisrU1FRkfN+d30alf/wHm7Cd8M9JQEAAODHaXZWNGnSpDRv3nye/Wp1T8kddtgh/fr1y4svvpj111+/+snOs/385z+vzbAAAAAAwI9ArULJww47LEly4YUXznGsrKxskbd2AwAAAABLr4W+p2SSVFVVzfP1XQeSvXv3tnUbAAAAAH7AahVKAgAAAADUVq1DyQcffDC9evVKp06dstpqq+XnP/95Hn744cVZGwAAAACwFKpVKHnNNddkm222SePGjXPUUUfliCOOSKNGjbL11lvn73//++KuEQAAAABYitTqQTdnnXVWzjvvvBxzzDHVbUcffXQuvPDCnHHGGdlnn30WW4EAAAAAwNKlVislX3/99fTq1WuO9p///Od54403FrkoAAAAAGDpVatQsn379rnvvvvmaL/vvvvSvn37RS4KAAAAAFh61Wr79nHHHZejjjoqo0ePziabbJKysrI88sgjGTFiRAYPHry4awQAAAAAliK1CiUPO+ywtGnTJoMGDcqNN96YJFlzzTVzww03ZJdddlmsBQIAAAAAS5dahZJJsttuu2W33XZbnLUAAAAAAD8Ctbqn5CqrrJJPPvlkjvaJEydmlVVWWeSiAAAAAIClV61CyTfffDOzZs2ao33atGl55513FrkoAAAAAGDptVDbt//9739X//muu+5KRUVF9ftZs2blvvvuS8eOHRdbcQAAAADA0mehQsldd901SVJWVpYDDjigxrH69eunY8eOGTRo0GIrDgAAAABY+ixUKFlVVZUkWXnllfPUU0+lVatW30lRAAAAAMDSq1ZP337jjTcWdx0AAAAAwI9ErR50c9RRR2XIkCFztF9yySXp27fvotYEAAAAACzFahVK3nTTTdl0003naN9kk03yz3/+c5GLAgAAAACWXrUKJT/55JMaT96erXnz5vn4448XuSgAAAAAYOlVq1CyU6dOufPOO+dov+OOO7LKKqssclEAAAAAwNKrVg+6OfbYY3PEEUfko48+ylZbbZUkue+++zJo0KBcfPHFi7M+AAAAAGApU6tQsk+fPpk2bVrOOuusnHHGGUmSjh075rLLLsuvf/3rxVogAAAAALB0KSuVSqVFGeCjjz5Ko0aN0rRp08VVEz8glZWVqaioyKRJk9K8efMlXQ4AAAAAS9CCZkW1Win5da1bt17UIQAAAACAH5FahZIrr7xyysrK5nn89ddfr3VBAAAAAMDSrVahZN++fWu8nzFjRp577rnceeedOeGEExZHXQAAAADAUqpWoeTRRx891/Y///nPefrppxepIAAAAABg6VZncQ62ww475KabblqcQwIAAAAAS5nFGkr+85//zDLLLLM4hwQAAAAAljK12r7dtWvXGg+6KZVKef/99/PRRx/l0ksvXWzFAQAAAABLn1qFkrvuumuN93Xq1Enr1q2z5ZZbZo011lgcdQEAAAAAS6mFDiVnzpyZjh07Zvvtt0+bNm2+i5oAAAAAgKXYQt9Tsl69ejnssMMybdq076IeAAAAAGApV6sH3Wy00UZ57rnnFnctAAAAAMCPQK3uKXn44YfnuOOOy9tvv531118/TZo0qXF83XXXXSzFAQAAAABLn7JSqVRa2JPq1JlzgWVZWVlKpVLKysoya9asxVIc33+VlZWpqKjIpEmT0rx58yVdDgAAAABL0IJmRbVaKfnGG2/UujAAAAAA4MetVqHkW2+9lU022ST16tU8febMmXn00UfToUOHxVIcPxznH7x/Gtavv1jHPPWafy7W8QAAAAD4fqjVg2569OiRTz/9dI72SZMmpUePHotcFAAAAACw9KpVKDn73pHf9Mknn8zx0BsAAAAAgK9bqO3bu+++e5KvHmrTu3fvlJeXVx+bNWtW/vvf/2aTTTZZvBUCAAAAAEuVhQolKyoqkny1UrJZs2Zp1KhR9bEGDRpk4403zsEHH7x4KwQAAAAAlioLFUoOHz48SdKxY8ccf/zxtmoDAAAAAAutVveUPPHEE2vcU/Ktt97KxRdfnLvvvnuxFQYAAAAALJ1qFUrusssuufrqq5MkEydOzIYbbphBgwZll112yWWXXbZYCwQAAAAAli61CiWfffbZbL755kmSf/7zn2nTpk3eeuutXH311RkyZMhiLRAAAAAAWLrUKpScMmVKmjVrliS5++67s/vuu6dOnTrZeOON89Zbby3WAgEAAACApUutQslOnTrllltuyYQJE3LXXXdlu+22S5J8+OGHad68+WItEAAAAABYutQqlOzfv3+OP/74dOzYMRtttFG6d++e5KtVk127dl2sBQIAAAAAS5d6tTlpzz33zGabbZb33nsvP/nJT6rbt9566+y2226LrTgAAAAAYOlTq1AySdq0aZM2bdrUaNtwww0XuSAAAAAAYOlWq1By8uTJOeecc3Lfffflww8/TFVVVY3jr7/++mIpDgAAAABY+tQqlDzooIPy4IMPZv/990/btm1TVla2uOsCAAAAAJZStQol77jjjtx2223ZdNNNF3c9AAAAAMBSrlZP327ZsmWWWWaZxV0LAAAAAPAjUKtQ8owzzkj//v0zZcqUxV0PAAAAALCUq9X27UGDBuW1117L8ssvn44dO6Z+/fo1jj/77LOLpTgAAAAAYOlTq1By1113XcxlAAAAAAA/FrUKJQcMGLC46wAAAAAAfiRqFUrO9swzz2Ts2LEpKyvLWmutla5duy6uugAAAACApVStQskPP/wwe++9d0aNGpUWLVqkVCpl0qRJ6dGjR66//vq0bt16cdcJAAAAACwlavX07SOPPDKVlZV56aWX8umnn+azzz7Liy++mMrKyhx11FGLu0YAAAAAYClSq5WSd955Z+69996sueaa1W1rrbVW/vznP2e77bZbbMUBAAAAAEufWq2UrKqqSv369edor1+/fqqqqha5KAAAAABg6VWrUHKrrbbK0UcfnXfffbe67Z133skxxxyTrbfeerEV17t37+y6665ztI8aNSplZWWZOHHiYptrYZ1++ukpKyub43XvvfcmSV566aXsscce6dixY8rKynLxxRfPd7zevXvPdbyvvwAAAABgaVCrUPKSSy7J559/no4dO2bVVVdNp06dsvLKK+fzzz/Pn/70p8Vd4/fW2muvnffee6/G62c/+1mSZMqUKVlllVVyzjnnpE2bNt861uDBg2uMkyTDhw+fow0AAAAAfuhqdU/J9u3b59lnn80999yTl19+OaVSKWuttVa22WabxV3fAvnkk09yxBFH5OGHH86nn36aVVddNaecckp+9atfVfe58847c+aZZ+bFF19M3bp107179wwePDirrrpqkmT69Ok59thjc9NNN+Wzzz5LmzZtcsghh6Rfv37znLdevXrzDBx/+tOf5qc//WmS5OSTT/7Wa6ioqEhFRUWNthYtWlSP/84772SvvfbK3XffnTp16mSzzTbL4MGD07FjxyTJU089lVNOOSXPPfdcZsyYkfXWWy8XXXRRunXrVj1eWVlZLr/88tx66625//7706FDhwwbNiytW7fOQQcdlKeeeirrrrturrnmmurPZUE98VFl6ter1ddpnvbZZ5/FOt7XtW7dOoMHD/7OxgcAAABg3hYqRbr//vtzxBFH5PHHH0/z5s2z7bbbZtttt02STJo0KWuvvXYuv/zybL755t9JsfMyderUrL/++jnppJPSvHnz3Hbbbdl///2zyiqrZKONNkqSTJ48Occee2zWWWedTJ48Of37989uu+2W0aNHp06dOhkyZEj+/e9/58Ybb8xKK62UCRMmZMKECYVex7xMmTIlPXr0yOabb56HHnoo9erVy5lnnpmePXvmv//9bxo0aJDPP/88BxxwQIYMGZIkGTRoUHbcccf873//S7NmzarHOuOMM3LhhRfmwgsvzEknnZR99tknq6yySvr165eVVlopffr0yRFHHJE77rhjrrVMmzYt06ZNq35fWVn5VfusqswqW7z3E536wQeLdTwAAAAAvh8WKpS8+OKLc/DBB6d58+ZzHKuoqMghhxySCy+8cLGGkiNHjkzTpk1rtM2aNavG+xVWWCHHH3989fsjjzwyd955Z/7xj39Uh5J77LFHjXOGDh2a5ZZbLmPGjEmXLl0yfvz4rLbaatlss81SVlaWDh06fGttL7zwQo3a1lprrTz55JMLfY3f5vrrr0+dOnVy5ZVXVt9bcvjw4WnRokVGjRqV7bbbLltttVWNc6644oq0bNkyDz74YHbeeefq9t/85jf55S9/mSQ56aST0r1795x22mnZfvvtkyRHH310fvOb38yzlrPPPjsDBw5c3JcIAAAAwI/IQoWSzz//fM4999x5Ht9uu+1ywQUXLHJRX9ejR49cdtllNdqeeOKJ7LffftXvZ82alXPOOSc33HBD3nnnnerVfE2aNKnu89prr+W0007L448/no8//rj6KeHjx49Ply5d0rt372y77bbp3LlzevbsmZ133jnbbbfdfGvr3Llz/v3vf1e/Ly8vXxyXPIdnnnkm48aNq7HiMflqhehrr72WJPnwww/Tv3//3H///fnggw8ya9asTJkyJePHj69xzrrrrlv95+WXXz5Jss4669Romzp1aiorK+caPvfr1y/HHnts9fvKysq0b98+5XXrpH7dWt2idJ4qWrVerON9XevW393YAAAAAMzfQoWSH3zwQerXrz/vwerVy0cffbTIRX1dkyZN0qlTpxptb7/9do33gwYNykUXXZSLL74466yzTpo0aZK+fftm+vTp1X169eqV9u3b569//WvatWuXqqqqdOnSpbpPt27d8sYbb+SOO+7Ivffem1/+8pfZZptt8s9//nOetTVo0GCO2r4LVVVVWX/99XPttdfOcWx2uNa7d+989NFHufjii9OhQ4eUl5ene/fuNT6DJDV+frNXXc6tbXZo+03l5eVzDV83at08Defz3aiNU6/5+2IdDwAAAIDvh4UKJVdYYYW88MIL8wzi/vvf/6Zt27aLpbCF8fDDD2eXXXapXj1ZVVWV//3vf1lzzTWTfPUgnLFjx+aKK66o3lr+yCOPzDFO8+bNs9dee2WvvfbKnnvumZ49e+bTTz/NMsssU9zFzEW3bt1yww03ZLnllpvr6sXkq8/g0ksvzY477pgkmTBhQj7++OMiywQAAACABbJQ+2133HHH9O/fP1OnTp3j2JdffpkBAwbUuH9hUTp16pR77rknjz76aMaOHZtDDjkk77//fvXxli1bZtlll81f/vKXjBs3Lvfff3+NLchJctFFF+X666/Pyy+/nFdffTX/+Mc/0qZNm7Ro0aJWNU2fPj2jR4/O6NGjM3369LzzzjsZPXp0xo0bt9Bj7bvvvmnVqlV22WWXPPzww3njjTfy4IMP5uijj65eNdqpU6f87W9/y9ixY/PEE09k3333TaNGjWpVOwAAAAB8lxYqlPz973+fTz/9NKuvvnrOO++8/N///V/+/e9/59xzz03nzp3z6aef5tRTT/2uap2n0047Ld26dcv222+fLbfcMm3atMmuu+5afbxOnTq5/vrr88wzz6RLly455phjcv7559cYo2nTpjn33HOzwQYb5Kc//WnefPPN3H777alTp3b3SXz33XfTtWvXdO3aNe+9914uuOCCdO3aNQcddNBCj9W4ceM89NBDWWmllbL77rtnzTXXTJ8+ffLll19Wr5wcNmxYPvvss3Tt2jX7779/jjrqqCy33HK1qh0AAAAAvktlpVKptDAnvPXWWznssMNy1113ZfapZWVl2X777XPppZemY8eO30WdfE9VVlamoqIiv//lz7+De0rO+36eAAAAAHz/zM6KJk2aNM/bECYLeU/JJOnQoUNuv/32fPbZZxk3blxKpVJWW221tGzZcpEKBgAAAAB+HBY6lJytZcuW+elPf7o4awEAAAAAfgRqd8NEAAAAAIBaEkoCAAAAAIUSSgIAAAAAhRJKAgAAAACFEkoCAAAAAIUSSgIAAAAAhRJKAgAAAACFEkoCAAAAAIUSSgIAAAAAhRJKAgAAAACFEkoCAAAAAIUSSgIAAAAAhRJKAgAAAACFEkoCAAAAAIUSSgIAAAAAhRJKAgAAAACFEkoCAAAAAIUSSgIAAAAAhRJKAgAAAACFEkoCAAAAAIUSSgIAAAAAhRJKAgAAAACFKiuVSqUlXQQ/XJWVlamoqMikSZPSvHnzJV0OAAAAAEvQgmZFVkoCAAAAAIUSSgIAAAAAhRJKAgAAAACFEkoCAAAAAIUSSgIAAAAAhRJKAgAAAACFEkoCAAAAAIUSSgIAAAAAhRJKAgAAAACFEkoCAAAAAIUSSgIAAAAAhRJKAgAAAACFEkoCAAAAAIUSSgIAAAAAhRJKAgAAAACFEkoCAAAAAIUSSgIAAAAAhRJKAgAAAACFEkoCAAAAAIUSSgIAAAAAhRJKAgAAAACFEkoCAAAAAIUSSgIAAAAAhRJKAgAAAACFEkoCAAAAAIUSSgIAAAAAhRJKAgAAAACFEkoCAAAAAIUSSgIAAAAAhRJKAgAAAACFEkoCAAAAAIUSSgIAAAAAhRJKAgAAAACFEkoCAAAAAIUSSgIAAAAAhRJKAgAAAACFEkoCAAAAAIUSSgIAAAAAhRJKAgAAAACFEkoCAAAAAIUSSn6LUaNGpaysLBMnTlzgc04//fSst95631lN36XevXtn1113XdJlAAAAALAUE0r+/x599NHUrVs3PXv2XNKlZMSIESkrK5vva9SoUd/J3IMHD86IESO+k7EBAAAAIBFKVhs2bFiOPPLIPPLIIxk/fvwSrWWvvfbKe++9V/3q3r17Dj744Bptm2yyyWKdc9asWamqqkpFRUVatGixWMcGAAAAgK8TSiaZPHlybrzxxhx22GHZeeed57tScMSIEWnRokVuueWWrL766mnYsGG23XbbTJgwYY6+f/vb39KxY8dUVFRk7733zueff1597M4778xmm22WFi1aZNlll83OO++c1157LUnSqFGjtGnTpvrVoEGDNG7cuPr96NGjs9VWW8313GTuW85Hjx6dsrKyvPnmmzWuY+TIkVlrrbVSXl6et956y/ZtAAAAAL5zQskkN9xwQzp37pzOnTtnv/32y/Dhw1MqlebZf8qUKTnrrLNy1VVX5T//+U8qKyuz99571+jz2muv5ZZbbsnIkSMzcuTIPPjggznnnHOqj0+ePDnHHntsnnrqqdx3332pU6dOdtttt1RVVX1rvYty7jev4+yzz86VV16Zl156Kcstt9y3njNt2rRUVlbWeAEAAADAwqi3pAv4Phg6dGj222+/JEnPnj3zxRdf5L777ss222wz1/4zZszIJZdcko022ihJctVVV2XNNdfMk08+mQ033DBJUlVVlREjRqRZs2ZJkv333z/33XdfzjrrrCTJHnvsMUcNyy23XMaMGZMuXbrMt95FOfeb13HppZfmJz/5yQKfc/bZZ2fgwIEL3B8AAAAAvulHv1LylVdeyZNPPlm90rFevXrZa6+9MmzYsHmeU69evWywwQbV79dYY420aNEiY8eOrW7r2LFjdSCZJG3bts2HH35Y/f61117LPvvsk1VWWSXNmzfPyiuvnCQLdD/LRTn36xo0aJB11113oc7p169fJk2aVP2a27Z1AAAAAJifH/1KyaFDh2bmzJlZYYUVqttKpVLq16+fzz77bJ7nlZWVzbetfv36cxz7+vbqXr16pX379vnrX/+adu3apaqqKl26dMn06dO/teZvO7dOnTrV1zHbjBkz5hinUaNGc72O+SkvL095eflCnQMAAAAAX/ejDiVnzpyZq6++OoMGDcp2221X49gee+yRa6+9dq7boWfOnJmnn366eqv2K6+8kokTJ2aNNdZYoHk/+eSTjB07NldccUU233zzJMkjjzyy2M5t3bp1kuS9995Ly5Ytk3z1oBsAAAAA+D74UYeSI0eOzGeffZYDDzwwFRUVNY7tueeeGTp0aC666KI5zqtfv36OPPLIDBkyJPXr188RRxyRjTfeuDqk/DYtW7bMsssum7/85S9p27Ztxo8fn5NPPnmxndupU6e0b98+p59+es4888z873//y6BBgxZofAAAAAD4rv2o7yk5dOjQbLPNNnMEkslXKyVHjx6dZ599do5jjRs3zkknnZR99tkn3bt3T6NGjXL99dcv8Lx16tTJ9ddfn2eeeSZdunTJMccck/PPP3+xnVu/fv1cd911efnll/OTn/wk5557bs4888wFrg8AAAAAvktlpa/feJBvNWLEiPTt2zcTJ05c0qV8L1RWVqaioiKTJk1K8+bNl3Q5AAAAACxBC5oV/ahXSgIAAAAAxRNKAgAAAACFEkoupN69e9u6DQAAAACLQCgJAAAAABRKKAkAAAAAFEooCQAAAAAUSigJAAAAABRKKAkAAAAAFEooCQAAAAAUSigJAAAAABRKKAkAAAAAFEooCQAAAAAUSigJAAAAABRKKAkAAAAAFEooCQAAAAAUSigJAAAAABRKKAkAAAAAFEooCQAAAAAUSigJAAAAABRKKAkAAAAAFEooCQAAAAAUSigJAAAAABRKKAkAAAAAFEooCQAAAAAUSigJAAAAABRKKAkAAAAAFEooCQAAAAAUSigJAAAAABRKKAkAAAAAFEooCQAAAAAUSigJAAAAABRKKAkAAAAAFEooCQAAAAAUSigJAAAAABRKKAkAAAAAFEooCQAAAAAUSigJAAAAABRKKAkAAAAAFEooCQAAAAAUSigJAAAAABRKKAkAAAAAFEooCQAAAAAUSigJAAAAABRKKAkAAAAAFEooCQAAAAAUSigJAAAAABRKKAkAAAAAFEooCQAAAAAUSigJAAAAABRKKAkAAAAAFEooCQAAAAAUSigJAAAAABRKKAkAAAAAFEooCQAAAAAUSigJAAAAABRKKAkAAAAAFEooCQAAAAAUSigJAAAAABRKKAkAAAAAFEooCQAAAAAUSigJAAAAABRKKAkAAAAAFEooCQAAAAAUSigJAAAAABRKKAkAAAAAFEoo+f8bNWpUysrKMnHixOq2W265JZ06dUrdunXTt2/fJVYbAAAAACxNflSh5KOPPpq6deumZ8+eC9T/kEMOyZ577pkJEybkjDPOqNWcs8PO2a9ll102W221Vf7zn//UajwAAAAA+KH7UYWSw4YNy5FHHplHHnkk48ePn2/fL774Ih9++GG23377tGvXLs2aNVukuV955ZW89957GTVqVFq3bp2ddtopH3744SKNCQAAAAA/RD+aUHLy5Mm58cYbc9hhh2XnnXfOiBEj5tl31KhR1SHkVlttlbKysowaNSqffPJJfvWrX2XFFVdM48aNs8466+S6665boPmXW265tGnTJuuss05+//vfZ9KkSXniiSeqjz/44IPZcMMNU15enrZt2+bkk0/OzJkzq49vueWWOfLII9O3b9+0bNkyyy+/fP7yl79k8uTJ+c1vfpNmzZpl1VVXzR133FFj3jFjxmTHHXdM06ZNs/zyy2f//ffPxx9/XH182rRpOeqoo7LccsulYcOG2WyzzfLUU08t0DUBAAAAQG38aELJG264IZ07d07nzp2z3377Zfjw4SmVSnPtu8kmm+SVV15Jktx000157733sskmm2Tq1KlZf/31M3LkyLz44ov57W9/m/33379GuPhtpkyZkuHDhydJ6tevnyR55513suOOO+anP/1pnn/++Vx22WUZOnRozjzzzBrnXnXVVWnVqlWefPLJHHnkkTnssMPyi1/8IptsskmeffbZbL/99tl///0zZcqUJMl7772XLbbYIuutt16efvrp3Hnnnfnggw/yy1/+snrME088MTfddFOuuuqqPPvss+nUqVO23377fPrpp3Otf9q0aamsrKzxAgAAAICFUVaaVzK3lNl0003zy1/+MkcffXRmzpyZtm3b5rrrrss222yT5KvVkT169Mhnn32WFi1aZOLEiWnZsmUeeOCBbLnllvMcd6eddsqaa66ZCy64YK7HZ4/bpEmTJF+FkqVSKeuvv34ee+yx1K9fP6eeempuuummjB07NmVlZUmSSy+9NCeddFImTZqUOnXqZMstt8ysWbPy8MMPJ0lmzZqVioqK7L777rn66quTJO+//37atm2bxx57LBtvvHH69++fJ554InfddVd1PW+//Xbat2+fV155JSussEJatmyZESNGZJ999kmSzJgxIx07dkzfvn1zwgknzHE9p59+egYOHDhH+6RJk9K8efNv+zEAAAAAsBSrrKxMRUXFt2ZFP4qVkq+88kqefPLJ7L333kmSevXqZa+99sqwYcMWapxZs2blrLPOyrrrrptll102TZs2zd133/2t96dMkocffjjPPvtsrrvuunTo0CEjRoyoXik5duzYdO/evTqQTL4KUb/44ou8/fbb1W3rrrtu9Z/r1q2bZZddNuuss0512/LLL58k1feqfOaZZ/LAAw+kadOm1a811lgjSfLaa6/ltddey4wZM7LppptWj1G/fv1suOGGGTt27Fyvo1+/fpk0aVL1a8KECd967QAAAADwdfWWdAFFGDp0aGbOnJkVVlihuq1UKqV+/fr57LPP0rJlywUaZ9CgQbnoooty8cUXZ5111kmTJk3St2/fTJ8+/VvPXXnlldOiRYusvvrqmTp1anbbbbe8+OKLKS8vT6lUqhFIzq4vSY322SHmbGVlZTXaZvetqqqq/mevXr1y7rnnzlFP27ZtM27cuDnmmD33N9tmKy8vT3l5+bdeLwAAAADMy1K/UnLmzJm5+uqrM2jQoIwePbr69fzzz6dDhw659tprF3ishx9+OLvsskv222+//OQnP8kqq6yS//3vfwtd0/7775+qqqpceumlSZK11lorjz76aI17XD766KNp1qxZjSB1YXXr1i0vvfRSOnbsmE6dOtV4NWnSJJ06dUqDBg3yyCOPVJ8zY8aMPP3001lzzTVrPS8AAAAAzM9SH0qOHDkyn332WQ488MB06dKlxmvPPffM0KFDF3isTp065Z577smjjz6asWPH5pBDDsn777+/0DXVqVMnffv2zTnnnJMpU6bk8MMPz4QJE3LkkUfm5Zdfzv/93/9lwIABOfbYY1OnTu1/RL/73e/y6aef5le/+lWefPLJvP7667n77rvTp0+fzJo1K02aNMlhhx2WE044IXfeeWfGjBmTgw8+OFOmTMmBBx5Y63kBAAAAYH6W+lBy6NCh2WabbVJRUTHHsT322COjR4/Os88+u0BjnXbaaenWrVu23377bLnllmnTpk123XXXWtXVp0+fzJgxI5dccklWWGGF3H777XnyySfzk5/8JIceemgOPPDA/P73v6/V2LO1a9cu//nPfzJr1qxsv/326dKlS44++uhUVFRUh53nnHNO9thjj+y///7p1q1bxo0bl7vuumuBt7QDAAAAwML60Tx9m+/Ggj5RCQAAAICln6dvAwAAAADfS0JJAAAAAKBQQkkAAAAAoFBCSQAAAACgUEJJAAAAAKBQQkkAAAAAoFBCSQAAAACgUEJJAAAAAKBQQkkAAAAAoFBCSQAAAACgUEJJAAAAAKBQQkkAAAAAoFBCSQAAAACgUEJJAAAAAKBQQkkAAAAAoFBCSQAAAACgUEJJAAAAAKBQQkkAAAAAoFBCSQAAAACgUEJJAAAAAKBQQkkAAAAAoFBCSQAAAACgUEJJAAAAAKBQQkkAAAAAoFBCSQAAAACgUEJJAAAAAKBQQkkAAAAAoFBCSQAAAACgUEJJAAAAAKBQQkkAAAAAoFBCSQAAAACgUEJJAAAAAKBQQkkAAAAAoFBCSQAAAACgUEJJAAAAAKBQQkkAAAAAoFBCSQAAAACgUEJJAAAAAKBQQkkAAAAAoFBCSQAAAACgUEJJAAAAAKBQQkkAAAAAoFBCSQAAAACgUEJJAAAAAKBQQkkAAAAAoFBCSQAAAACgUEJJAAAAAKBQQkkAAAAAoFBCSQAAAACgUEJJAAAAAKB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",
      "text/plain": [
       "<Figure size 1500x1000 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Saudi Arabian GP 23 Contructor Points\n",
    "\n",
    "f, ax = plt.subplots(figsize=(15,10))\n",
    "sns.barplot(x='points', y='constructor', data=dataset)\n",
    "plt.title('Saudi Arabian GP 23 Constructor Points')\n",
    "plt.xlabel('GP Points')\n",
    "plt.ylabel('Constructors')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0, 0.5, 'Finish Position')"
      ]
     },
     "execution_count": 27,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<Figure size 1500x1000 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Saudi Arabian GP 23 Grid VS Finish Points\n",
    "\n",
    "plt.figure(figsize=(15, 10))\n",
    "plt.grid(color = 'green', linestyle = '--', linewidth = 0.5)\n",
    "plt.scatter(H, y, color = 'red')\n",
    "plt.plot(H, regressor.predict(H), color = 'blue')\n",
    "plt.title('Grid VS Finish')\n",
    "plt.xlabel('Start Position')\n",
    "plt.ylabel('Finish Position')"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "base",
   "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": "3.11.3"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}