TradingBotModelAccuracy.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 44,
   "id": "53bf0f58-2f51-4512-a986-9b4319d13721",
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import numpy as np \n",
    "from sklearn.linear_model import LinearRegression,Lasso,Ridge,ElasticNet\n",
    "from sklearn import tree\n",
    "from sklearn.ensemble import RandomForestClassifier,RandomForestRegressor\n",
    "from sklearn.tree import DecisionTreeRegressor\n",
    "from sklearn.metrics import accuracy_score,classification_report,mean_squared_error,mean_absolute_error,r2_score\n",
    "import seaborn as sns\n",
    "import matplotlib.pyplot as plt\n",
    "from sklearn.model_selection import train_test_split\n",
    "from sklearn.preprocessing import LabelEncoder"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "id": "c318862e-9826-4b33-b4b2-ab5c55914030",
   "metadata": {},
   "outputs": [],
   "source": [
    "lr=LinearRegression()\n",
    "decision_tree=DecisionTreeRegressor()\n",
    "random_forest=RandomForestRegressor()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "8a7739d2-c7ad-448c-872b-dd42ed9251a7",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Time</th>\n",
       "      <th>Open</th>\n",
       "      <th>High</th>\n",
       "      <th>Low</th>\n",
       "      <th>Close</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2018-08-23 09:16:00</td>\n",
       "      <td>1964.62</td>\n",
       "      <td>1965.36</td>\n",
       "      <td>1954.67</td>\n",
       "      <td>1954.87</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2018-08-23 09:17:00</td>\n",
       "      <td>1954.87</td>\n",
       "      <td>1959.74</td>\n",
       "      <td>1954.87</td>\n",
       "      <td>1958.15</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2018-08-23 09:18:00</td>\n",
       "      <td>1958.10</td>\n",
       "      <td>1958.30</td>\n",
       "      <td>1953.77</td>\n",
       "      <td>1953.77</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2018-08-23 09:19:00</td>\n",
       "      <td>1953.92</td>\n",
       "      <td>1955.46</td>\n",
       "      <td>1952.63</td>\n",
       "      <td>1953.18</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2018-08-23 09:20:00</td>\n",
       "      <td>1953.18</td>\n",
       "      <td>1954.67</td>\n",
       "      <td>1952.08</td>\n",
       "      <td>1952.68</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>196849</th>\n",
       "      <td>2020-10-12 15:26:00</td>\n",
       "      <td>612.85</td>\n",
       "      <td>613.00</td>\n",
       "      <td>612.30</td>\n",
       "      <td>612.35</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>196850</th>\n",
       "      <td>2020-10-12 15:27:00</td>\n",
       "      <td>612.35</td>\n",
       "      <td>612.50</td>\n",
       "      <td>612.30</td>\n",
       "      <td>612.40</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>196851</th>\n",
       "      <td>2020-10-12 15:28:00</td>\n",
       "      <td>612.40</td>\n",
       "      <td>612.50</td>\n",
       "      <td>612.00</td>\n",
       "      <td>612.35</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>196852</th>\n",
       "      <td>2020-10-12 15:29:00</td>\n",
       "      <td>612.45</td>\n",
       "      <td>612.50</td>\n",
       "      <td>612.00</td>\n",
       "      <td>612.45</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>196853</th>\n",
       "      <td>2020-10-12 15:30:00</td>\n",
       "      <td>612.50</td>\n",
       "      <td>613.90</td>\n",
       "      <td>612.30</td>\n",
       "      <td>613.70</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>196854 rows × 5 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                       Time     Open     High      Low    Close\n",
       "0       2018-08-23 09:16:00  1964.62  1965.36  1954.67  1954.87\n",
       "1       2018-08-23 09:17:00  1954.87  1959.74  1954.87  1958.15\n",
       "2       2018-08-23 09:18:00  1958.10  1958.30  1953.77  1953.77\n",
       "3       2018-08-23 09:19:00  1953.92  1955.46  1952.63  1953.18\n",
       "4       2018-08-23 09:20:00  1953.18  1954.67  1952.08  1952.68\n",
       "...                     ...      ...      ...      ...      ...\n",
       "196849  2020-10-12 15:26:00   612.85   613.00   612.30   612.35\n",
       "196850  2020-10-12 15:27:00   612.35   612.50   612.30   612.40\n",
       "196851  2020-10-12 15:28:00   612.40   612.50   612.00   612.35\n",
       "196852  2020-10-12 15:29:00   612.45   612.50   612.00   612.45\n",
       "196853  2020-10-12 15:30:00   612.50   613.90   612.30   613.70\n",
       "\n",
       "[196854 rows x 5 columns]"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "file_path = 'data/Bank Dataset/INDUSINDBK.csv'\n",
    "data = pd.read_csv(file_path)\n",
    "data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "60fdf207-8ac5-4451-b5e2-4ad19036a562",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Open</th>\n",
       "      <th>High</th>\n",
       "      <th>Low</th>\n",
       "      <th>Close</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>196854.000000</td>\n",
       "      <td>196854.000000</td>\n",
       "      <td>196854.000000</td>\n",
       "      <td>196854.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>1214.432744</td>\n",
       "      <td>1215.296450</td>\n",
       "      <td>1213.533731</td>\n",
       "      <td>1214.415382</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>std</th>\n",
       "      <td>469.019512</td>\n",
       "      <td>469.115518</td>\n",
       "      <td>468.913732</td>\n",
       "      <td>469.010740</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>235.550000</td>\n",
       "      <td>235.550000</td>\n",
       "      <td>235.550000</td>\n",
       "      <td>235.550000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25%</th>\n",
       "      <td>618.762500</td>\n",
       "      <td>619.300000</td>\n",
       "      <td>618.250000</td>\n",
       "      <td>618.800000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50%</th>\n",
       "      <td>1415.600000</td>\n",
       "      <td>1416.560000</td>\n",
       "      <td>1414.570000</td>\n",
       "      <td>1415.570000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75%</th>\n",
       "      <td>1529.660000</td>\n",
       "      <td>1530.610000</td>\n",
       "      <td>1528.600000</td>\n",
       "      <td>1529.650000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>max</th>\n",
       "      <td>1964.620000</td>\n",
       "      <td>1965.360000</td>\n",
       "      <td>1956.660000</td>\n",
       "      <td>1958.150000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                Open           High            Low          Close\n",
       "count  196854.000000  196854.000000  196854.000000  196854.000000\n",
       "mean     1214.432744    1215.296450    1213.533731    1214.415382\n",
       "std       469.019512     469.115518     468.913732     469.010740\n",
       "min       235.550000     235.550000     235.550000     235.550000\n",
       "25%       618.762500     619.300000     618.250000     618.800000\n",
       "50%      1415.600000    1416.560000    1414.570000    1415.570000\n",
       "75%      1529.660000    1530.610000    1528.600000    1529.650000\n",
       "max      1964.620000    1965.360000    1956.660000    1958.150000"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data.describe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "754c8e48-bff0-496a-896f-f689f433fa56",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 196854 entries, 0 to 196853\n",
      "Data columns (total 5 columns):\n",
      " #   Column  Non-Null Count   Dtype  \n",
      "---  ------  --------------   -----  \n",
      " 0   Time    196854 non-null  object \n",
      " 1   Open    196854 non-null  float64\n",
      " 2   High    196854 non-null  float64\n",
      " 3   Low     196854 non-null  float64\n",
      " 4   Close   196854 non-null  float64\n",
      "dtypes: float64(4), object(1)\n",
      "memory usage: 7.5+ MB\n"
     ]
    }
   ],
   "source": [
    "data.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "763a9b3d-cea9-4782-b705-066049c4e179",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(196854, 5)"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "2dfb139c-30ad-4f5c-a3eb-8203a107dc89",
   "metadata": {},
   "outputs": [],
   "source": [
    "data['Date'] = pd.to_datetime(data['Time']).dt.date\n",
    "data['Time'] = pd.to_datetime(data['Time']).dt.time"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "7153a629-b601-4b2a-91de-a7b8042a91a4",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Time</th>\n",
       "      <th>Open</th>\n",
       "      <th>High</th>\n",
       "      <th>Low</th>\n",
       "      <th>Close</th>\n",
       "      <th>Date</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>09:16:00</td>\n",
       "      <td>1964.62</td>\n",
       "      <td>1965.36</td>\n",
       "      <td>1954.67</td>\n",
       "      <td>1954.87</td>\n",
       "      <td>2018-08-23</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>09:17:00</td>\n",
       "      <td>1954.87</td>\n",
       "      <td>1959.74</td>\n",
       "      <td>1954.87</td>\n",
       "      <td>1958.15</td>\n",
       "      <td>2018-08-23</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>09:18:00</td>\n",
       "      <td>1958.10</td>\n",
       "      <td>1958.30</td>\n",
       "      <td>1953.77</td>\n",
       "      <td>1953.77</td>\n",
       "      <td>2018-08-23</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>09:19:00</td>\n",
       "      <td>1953.92</td>\n",
       "      <td>1955.46</td>\n",
       "      <td>1952.63</td>\n",
       "      <td>1953.18</td>\n",
       "      <td>2018-08-23</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>09:20:00</td>\n",
       "      <td>1953.18</td>\n",
       "      <td>1954.67</td>\n",
       "      <td>1952.08</td>\n",
       "      <td>1952.68</td>\n",
       "      <td>2018-08-23</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>196849</th>\n",
       "      <td>15:26:00</td>\n",
       "      <td>612.85</td>\n",
       "      <td>613.00</td>\n",
       "      <td>612.30</td>\n",
       "      <td>612.35</td>\n",
       "      <td>2020-10-12</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>196850</th>\n",
       "      <td>15:27:00</td>\n",
       "      <td>612.35</td>\n",
       "      <td>612.50</td>\n",
       "      <td>612.30</td>\n",
       "      <td>612.40</td>\n",
       "      <td>2020-10-12</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>196851</th>\n",
       "      <td>15:28:00</td>\n",
       "      <td>612.40</td>\n",
       "      <td>612.50</td>\n",
       "      <td>612.00</td>\n",
       "      <td>612.35</td>\n",
       "      <td>2020-10-12</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>196852</th>\n",
       "      <td>15:29:00</td>\n",
       "      <td>612.45</td>\n",
       "      <td>612.50</td>\n",
       "      <td>612.00</td>\n",
       "      <td>612.45</td>\n",
       "      <td>2020-10-12</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>196853</th>\n",
       "      <td>15:30:00</td>\n",
       "      <td>612.50</td>\n",
       "      <td>613.90</td>\n",
       "      <td>612.30</td>\n",
       "      <td>613.70</td>\n",
       "      <td>2020-10-12</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>196854 rows × 6 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "            Time     Open     High      Low    Close        Date\n",
       "0       09:16:00  1964.62  1965.36  1954.67  1954.87  2018-08-23\n",
       "1       09:17:00  1954.87  1959.74  1954.87  1958.15  2018-08-23\n",
       "2       09:18:00  1958.10  1958.30  1953.77  1953.77  2018-08-23\n",
       "3       09:19:00  1953.92  1955.46  1952.63  1953.18  2018-08-23\n",
       "4       09:20:00  1953.18  1954.67  1952.08  1952.68  2018-08-23\n",
       "...          ...      ...      ...      ...      ...         ...\n",
       "196849  15:26:00   612.85   613.00   612.30   612.35  2020-10-12\n",
       "196850  15:27:00   612.35   612.50   612.30   612.40  2020-10-12\n",
       "196851  15:28:00   612.40   612.50   612.00   612.35  2020-10-12\n",
       "196852  15:29:00   612.45   612.50   612.00   612.45  2020-10-12\n",
       "196853  15:30:00   612.50   613.90   612.30   613.70  2020-10-12\n",
       "\n",
       "[196854 rows x 6 columns]"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "0ae1aa33-d0e1-4f33-9f79-c84593ebc785",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1000x700 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "data['Open'].plot(figsize=(10,7))\n",
    "plt.title(\"Stock Price\",fontsize=17)\n",
    "plt.xlabel('Time',fontsize=14)\n",
    "plt.ylabel('Price',fontsize=14)\n",
    "plt.grid(which=\"major\",color=\"k\",linestyle=\"-\",linewidth=0.5)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "d4491791-7f75-4fa2-a044-a7a950c0f797",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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m+eefx8aNG/Hbb79hz549uHXrFsaNGyecr6iowKhRo1BaWoqDBw/i+++/x+rVqzFv3jyhTXJyMkaNGoUBAwYgMTERzz33HB5//HFs3brVru+XiIiIiIhqHk9Hd0Ddli1bRPurV69GeHg4jh07hr59+yIvLw/fffcd1q5di4EDBwIAVq1ahVatWuHQoUPo0aMHtm3bhnPnzmHHjh2IiIhAhw4d8Pbbb+OVV17B/Pnz4e3tja+++gqxsbH44IMPAACtWrXC/v378dFHH2HYsGEa/SopKUFJSYmwL5PJbPgUiIiIiIjInTldIKYuLy8PABAaGgoAOHbsGMrKyjB48GChTcuWLdGwYUPEx8ejR48eiI+PR9u2bRERESG0GTZsGJ5++mmcPXsWHTt2RHx8vOgayjbPPfec1n4sXrwYCxYs0Dg+ceJEeHl5Wfo2rSIhIQFjxoxxdDfcGp+xffA52x6fsX3wOdsen7Ht8RnbB5+z7dnyGZeVlZn8GqcOxORyOZ577jn06tUL99xzDwAgPT0d3t7eCAkJEbWNiIhAenq60EY1CFOeV57T10Ymk+Hu3bvw8/MTnZs7dy7mzJkj7MtkMkRHR2PdunUICgqy/M1awZgxY7BhwwZHd8Ot8RnbB5+z7fEZ2wefs+3xGdsen7F98Dnbni2fsUwmQ3BwsEmvcepAbNasWThz5gz279/v6K7Ax8cHPj4+ju4GERERERG5AadL1qE0e/Zs/PPPP9i1axcaNGggHI+MjERpaSlyc3NF7TMyMhAZGSm0Uc+iqNw31CYoKEhjNIyIiIiIiMianC4QUygUmD17Nv766y/8999/iI2NFZ3v3LkzvLy8sHPnTuFYUlISUlNTERcXBwCIi4vD6dOnkZmZKbTZvn07goKC0Lp1a6GN6jWUbZTXICIiIiIishWnm5o4a9YsrF27Fn///TcCAwOFNV3BwcHw8/NDcHAwZsyYgTlz5iA0NBRBQUF45plnEBcXhx49egAAhg4ditatW+Phhx/G0qVLkZ6ejjfeeAOzZs0Sphc+9dRT+Oyzz/Dyyy/jsccew3///Ydff/0VmzZtcth7JyIiIiKimsHpRsS+/PJL5OXloX///qhXr57wZ926dUKbjz76CPfeey/Gjx+Pvn37IjIyEn/++adw3sPDA//88w88PDwQFxeHhx56CI888ggWLlwotImNjcWmTZuwfft2tG/fHh988AFWrFihNXU9ERERERGRNTndiJhCoTDYxtfXF59//jk+//xznW0aNWqEzZs3671O//79ceLECZP7SEREREREZAmnGxEjIiIiIiJyd043Ikam23DyFr7YdRl3Ino4uitERERERGQEjoi5AdndMlxIz0epl3MUliYiIiIiIv0YiLkBb4/Kv0ZZYAwAIFNWjHs/3YctZ9Id2CsiIiIiItKFgZgb+PvkzcoNiQQA0G3RTpy5KcNTPx1zYK+IiIiIiEgXBmJu4MDlLGF748lbonOZsmJ7d4eIiIiIiAxgIOYGhreJFLaf+Vmcjn/4x/vs3R0iIiIiIjKAgZgb+GRyR53nsgtL7dgTIiIiIiIyBgMxN+Dtyb9GIiIiIiJXwk/wbuLqopGO7gIRERERERmJgZibkEolWo/7evGvmIiIiIjI2fBTuptqE1VZ3Lm4TO7gnhARERERkToGYm6qa0yosJ1fXObAnhARERERkToGYm7qTkGJsJ1VwMyJRERERETOhIGYmwoP9BW2b+bedWBPiIiIiIhIHQMxN+J7946wfeJ6jrD9Q3yKA3pDRERERES6MBBzIyH5V4XtsAAfYfueqGBHdIeIiIiIiHRgIOZG6t45IWy/eW8reFaltG9TvzKD4vIdF7H43/MO6RsREREREVXzdHQHyHokAJIXj0RxmRx+3h4olysAAI+tPorPpnTE8h2XAADD20SiY8PaDuwpEREREVHNxhExNyORSODn7aFxfPba6tGy59Yl2rFHRERERESkjoFYDXQtq8jRXSAiIiIiqtEYiNVQ5RVyR3eBiIiIiKjGYiDmxpaOb6fz3KoDKfbrCBERERERiTAQc2MTukbrPPfuZmZPJCIiIiJyFAZiREREREREdsZAzM2FBnhb9HpZcRn+PH4D+cVlVuoRERERERGxjpibyy4s1Xo8MsgXAJCeV4zkO4W4nJmPwa0jUC/YT9Suw4JtkCsAbw8pLr47wub9JSIiIiKqCRiIubkO0SFIvJ6rcXxMhyjI5Qr0WLxTOPbZrss4/NpgAIBcrsCRlGxU1YRGKbMsEhERERFZDacmurnpPWNE+zP7NgYAFJdVoLi8QnQuQ1YibK88kIyJ3xwSnb+dXwIiIiIiIrIcAzE39/62JNF+sJ8XgMpArLRc9yjXO5s0syp2fXeHdTtHRERERFRDMRBzc+GBPqJ9H8/Kv/LiMjme+fmEI7pERERERFTjMRBzcy8OayHa9/XyAFA5Irbv0h2drxvaOsKm/SIiIiIiqskYiLm5uMZhwnbvpnWEQGzbuQy9r6sX7Kv1uFyZvYOIiIiIiMzGrIluTiKRIHnxSNzIuYsGtf2w6XSaUa/bcjZd6/HNZ9Jwb7soa3aRiIiIiKjG4YhYDSCRSBAd6g+JRIKikgrDL4A4g6Kqf89oD9CIiIiIiMh4HBGrYeQK/VMLY17dhKf7N9F5vlGov7W7RERERERU43BErIY5eSNX41jXmNqi/S93XxHt921eV9j+Qu0cERERERGZjoFYDTO0daTGMV3TEJXmj25tq+4QEREREdVIDMRqGE8PicaxR+Ia6Wz/xqhWaFy3llCP7J76QTbrGxERERFRTcFArIZpHx2icWx8pwY62/dqWgcAUFGVtv7MTZlN+kVEREREVJMwEKthgny90D02VHRMojlIJiguq8yyGKmjrhgREREREZmOgVgNNPwe8ToxH08PnW1jwgIAAFO6NxSOlVXIbdMxIivIlBWj79Jd+HzXZUd3hYiIiEgnBmI10JDWEaJ9Xy/dPwa1A7wBAMev5QrHdpzLsEm/iKzhk/8uITW7CMu2Jjm6K0REREQ6MRCrgRrUFtcCk+ibm1jlYka+sF1cblxRaCJHKCvXXyuPiIiIyBkwEKuhlLXBzi8cblT7BrX9hG3OTKSa4NOdl9Bv2S7cztdf3oGIiIjIHJ6O7gA5xg+PdYNCoTBqNAwAokOrR9Eq5IzEyHlduV2gcezMzTz4e3ugcd1aRl/ng+0XAQDvb03Cew+0s1r/iIiIiACOiNVoqkHYWwaKNquOiJXLOfWLnNfRazmi/cz8Ytz76X4M/GAPFArjfnYLSsqF7XVHr1u1f0REREQAAzGq8mivWFxdNBIpS0ZpPV8/pDoQ25B4y17dIjLJzwmpGscOX80Wtncn3TbqOjmFpVbrExEREZE2DMRIIJXqnqaoWkfscHK2znZEjjT3z9Max+Qqo2CPrj5i1HXSZcXC9rS4RpZ3jIiIiEgNAzHSqU4tb2E7NMBbT0si53W31PQsn2/9fVbY7hITqqclERERkXkYiJGGz6d0QmydAPz3Yn/hWG1/cSB2PbvIzr0iMk+RGYHYuTSZsJ3JrIlERERkAwzESMOodvWw68X+CPL1Eo75enmI2hSWlqu/jMihVGvdKc1ZlyhKvKH0S0Iqhi/fi/S8Yo1z6mr5eBhsQ0RERGQqBmJkFmawJ2cz9KO9Gsf+PHET/5zSTC7z6p+ncSE9H8/+csLgdVk3j4iIiGyBgRgZbe3j3YVtuZFpwIkcLU1t1KtMJbJKMCLxTCqn4RIREZENMBAjo/l4Vf+4MA4jV5FfLJ6aaGpq+q/2XMHlTM0i0URERESWYCBGZlGAkRi5JllxmcmvGfzhHhv0hIiIiGoyBmJkFhZ1Jlf127EbwnZ0qB/2X7qDIiafISIiIjtjIEZmWbE/2dFdIDLL13uuCtvXs+/ioe8Oo/W8rVBwvi0RERHZEQMxMoHE0R0g0ikq2BcA8HjvWLNeP2vtcQBAhZwBGREREdme0wVie/fuxejRoxEVFQWJRIL169eLzkskEq1/li1bJrSJiYnROL9kyRLRdU6dOoU+ffrA19cX0dHRWLp0qT3enkuTMA4jJ6YMn8Z2qI+UJaNMfv3m0+kAgGPXcqzYKyIiIiLtnC4QKywsRPv27fH5559rPZ+Wlib6s3LlSkgkEowfP17UbuHChaJ2zzzzjHBOJpNh6NChaNSoEY4dO4Zly5Zh/vz5+Oabb2z63lydlJEYOTHlzEJLf0yPpBhOaU9ERERkKU9Hd0DdiBEjMGLECJ3nIyMjRft///03BgwYgMaNG4uOBwYGarRVWrNmDUpLS7Fy5Up4e3ujTZs2SExMxIcffoiZM2da/ibclJRxGDkxa2TyvJZViGVbk6zQGyIiIiL9nG5EzBQZGRnYtGkTZsyYoXFuyZIlCAsLQ8eOHbFs2TKUl1dnRYuPj0ffvn3h7e0tHBs2bBiSkpKQk6N9WlJJSQlkMpnoT00j4RoxcnOHr3I0jIiIiOzD6UbETPH9998jMDAQ48aNEx1/9tln0alTJ4SGhuLgwYOYO3cu0tLS8OGHHwIA0tPTERsrXtAfEREhnKtdu7bGvRYvXowFCxZoHJ84cSK8vLys9ZYskpCQgDFjxtjs+kW+dYDG1VNAbXkvZ2XrZ0yVzHnOWc0eArwC8Pxzz8GvJAto/aTJ95235j/At47Wc+72986fZfvgc7Y9PmPb4zO2Dz5n27PlMy4rM71OqUsHYitXrsTUqVPh6+srOj5nzhxhu127dvD29saTTz6JxYsXw8fHx6x7zZ07V3RdmUyG6OhorFu3DkFBQea9ASsbM2YMNmzYYLPrn7mZh3s/3S/s2/JezsrWz5gqmfOcu767A7fzS/Dxxx+jdVQQYl7dZPJ9i3UEYYD7/bzzZ9k++Jxtj8/Y9viM7YPP2fZs+YxlMhmCg4NNeo3LTk3ct28fkpKS8Pjjjxts2717d5SXlyMlJQVA5TqzjIwMURvlvq51ZT4+PggKChL9qWmYrIOcmaFkHYdfGyRse3nwZ5mIiIgcy2UDse+++w6dO3dG+/btDbZNTEyEVCpFeHg4ACAuLg579+4VDSFu374dLVq00DotkSpJXfanhWqGykhMGYg9O7Cp6GxEUPXIedv6pn1jRURERGRtTvfRuqCgAImJiUhMTAQAJCcnIzExEampqUIbmUyG3377TetoWHx8PJYvX46TJ0/i6tWrWLNmDZ5//nk89NBDQpA1ZcoUeHt7Y8aMGTh79izWrVuHjz/+WDT1kDQxWQc5M4Va0sTJ3RvqbFtuRNHmBzs3sLRLRERERDo53Rqxo0ePYsCAAcK+MjiaNm0aVq9eDQD45ZdfoFAoMHnyZI3X+/j44JdffsH8+fNRUlKC2NhYPP/886IgKzg4GNu2bcOsWbPQuXNn1KlTB/PmzWPqegNU09fzQyo5G2VopfzCoF6wn862ZRWGA7FlD7bHb8duWKNrRERERBqcLhDr378/FOpfbauZOXOmzqCpU6dOOHTokMH7tGvXDvv27TOrjzVVuMrULiMGFIisatWBZCzYeA6hAd5YNb0r2keHQKFQQFI1F1H5e8OYpYzlFXJbdpWIiIjIIKebmkjOK9jPC+M61QcAg8EykbUt2HgOAJBdWIqxnx9AzKubEDt3M/KLK9d6Vo+IVXtrdGsAwEvDWoiupTo1sU4t4zKpyvntAxEREVkRAzEySet6ldkijVljQ2QPygBNSXVE7NFesTj6xmDMGiBO3KFQKLBxdm8MbBmONY9317hmbX/N2oDjvzponQ4TERERgYEYmUhWXA4AOJyc5eCeEFXanXQbgGqyDvHcRG0jXtGh/mjbIBgrp3dFi8hA7Ht5ACZ1jRbOb3u+HwCgW0yocOxEai4A4OCVO7jv8wM4czPPem+CiIiIahwGYmSST3ZeAgBkyEpQUTUqJpcr8Mb601h3JFXfS4nMllVQovPcnapzeXcNV7Rf+0R3DGkdgaUPtBMdjw71x5Lx7RA/dyDOLhiGuoGVwduK6V00rjHl28NIvJ6LR1cfMeUtEBEREYk4XbIOcm4dokOQeD0XANDktc34eFIHXM8uwk+HKoOwiV11pwwnMseFdBmGL9efWKewpFzYLimv0NmuZ5M66Nmkjs7z6pkWg3zFUxRv5BQJ27fzdQeHRERERIYwECOTdI2pLQRiAPB/vySKzufdLUOwn+b6GiJz/XzY8EhrmUoWxAobrl98Tu3nnYiIiMhcnJpIJvk54bre8w+tOGynnlBNse/SHYNtlu+4JGwrE8rYwtFrOTa7NhEREdUsDMTIJAUqU8C0Oc0EBmRlxqSXX30wRdj2kBpRSMxKWMaBiIiIzMVAjIicWvfGoRrH/vxfT53tJcZUdDZBvWBfnedi525GWt5dq96PiIiIagYGYkTk1D7977Jo/4upndCpYW2tba0cgwEAhraO0Hv+mbUnrH9TIiIicnsMxMgkj/aKMdjmpEoyD0NkxWUY/OEevL81yfxOUY0R5OuJkW3rAQAa1w3QOG+LmYKJN/RPt72RwxExIiIiMh0DMTLJnCHNDbZZ/O95o6+3+kAKLmcW4LNdlw03phrv1Pxhwvb6Wb3sck9DXyw80LmBXfpBRERE7oWBGJnEz8vDYJtAX+PT15+7JbOkO1SDqdf4spUn+zXWe75ZRC279IOIiIjcCwMxMomnh+Efmdr+xn9ATjRhGiPVPPnFZY7uAh6Ji9F73p5ZGomIiMh9MBAjq6vlY3wgVlJeYcOekKt78sdjju4C6of46T0vtUWGECIiInJ7DMTIYi8NayHaN2WqVnGZXNhmTSZSd/BKlqO7YBDDMCIiIjIHAzGyyJv3tsb/+jdBn2Z1hGPNTQjEfLyqfwQr5M4ViOXdLcPYz/bj271XHd0VgvbU9Gse744O0SF274sqR/7UXs8uwq9HrqOsQm64MRERETkVBmJkkQEt6kIikeDbR7qY9fr/9W8ibJc7WSD23b6rOHkjD+9uNj4LJNnOxtm9NY71alrHLtkTVX9O1ckdNJKrUCjQZ+kuvPzHKaw6kOyQPhAREZH5GIiRRTyllT9Cvl4eaBjqb7B92/lbMfrT/QCAsgo5SlSmJjpbIPbT4VRHd4FU3FM/WOe5t0a3BmC4+LK5Xh7eUuc5R/3YTlt1RNj+Zi8DMSIiIlfj6egOkOvx9/ZAUWllkg0Pj+r5YoZyFhy7lo384nKcvpmH0nI5Jn4TjxOpucL5ciebXpVdWCpsp+XdRVpesQN7UzM1DPVHanaRwXbT4mLQpVEomkfaPpV82/rBOH2zusizo9Y27r14W9guLCl3SB+IiIjIfBwRI5Opjjp4akndfTu/FEu3XEBqlvgDdHlF9QfWW7l3RUEYAFzKLLBuR60obvF/GPfFQdwJvcfRXalRejUNAwC8OFR/IXGpVIK2DYLh42m4zp2l7LUeq6CkHFduG/dvIrZOgI17Q0RERNbGQIxM9sLQ6iyJqqm7lSMXT/10DF/svoK+y3aJXhdWy1vY3nkhU+O6p2/kaRxzNrcibb8eiaqVlFcGPV5G1K+zl44NQ3DxnRFCkhBbrRG7562tGPTBHuxO0vy3ou5cGgujExERuRrn+XRDLsPfu3rUQaGSM87Q51HldEYAWHP4msb5L3ZfsbxzViK34sKfX49cx7M/n0BpuXNNvXQFZVWjqM4UiNWp5QNvTymC/Crr5dl6ZuJ0lbVgRERE5D64RoxM5qnyodiUYrb7Lt0Rtq/eLtQ4f6egBAqFAhInKJD70HeHrXatl/84BQDwkErw0cQOVrtuTVBWFbx6ezpPIHaqauRW+VPqZDlmiIiIyEU4z6cbchnBfl6Y2r0hJnWNRp1aPka/Tna3zGAbZ/lQq6+QsLnJGf46cdPc7tRYpVXrsbydaERsTPsoAIByeSQLkRMREZE5OCJGZnn3/rYmv+ZrIwojJ17PQedGoeZ0yW5WHUjBY71jjWrLbHaWySmqzFzp5en4UdJfZvbA0ZRs3N+xPgAII7fWjsPuFJSglg9/NRMREbk75/mamdxSQnI2nv7pGNLy7iLA23BGuzfWn7VDryyz8J9zRrW7kVOENm9ttXFv3Jsys2ZZueNHnXo0DsPsgc0grRoKE0bEYL2+3cq9iy7v7ED7Bdusdk0iIiJyTvzalWxqwtfxAIDb+SUoVEnWoct5J8n+Nr1nDFYfTLHoGq/9dcY6namhKlTmqV69o7mm0PEqIzFrTqfdU1UbrEQtsUtRaTn8vfnrmoiIyJ1wRIzs4ui1HEd3wSz3tqtn9mtVC+4qWTMbo7tTrdflBPlbNFSvEbPeNXWlwm89byvS8u5a70ZERETkcAzEiLRIzysGAEQG+Zr0ujM38/DQisN4c7320bArtwtQwHVjRlFdXze2Q5QDe6KdMji0Zh0xfYF63OL/8Pmuy8J+WIC3zrZERETk/BiIEWmx5Ww6AOD34zeEjH1dY2obfN29n+7H/st38OMhzTppADDko73o9PZ263XUjamWO2gZGeTAnminLN1gzTHOfANB+rKtScJ2VmGpsB0VbNoXBkREROR4DMTIapY90M7RXbCKeJXU9X2a1cWp+UNxdsEw1Pa3zggECzsbJ8jPuddEKUfENiTeRF6R4dIMxiivMBzWfb3nCqe4EhERuQEGYmQ1Q9tEWuU6eUbUG7Olyd8eEra3nkmHr5cHAnw8RSnF913SXP9lCtaeMiw0wPgadY6gTF9/JCUH7RdaJ8thhREB1uJ/L+BSZoHoGH+aiIiIXA8DMbKaIF/rjGCcupFrletYQ6lKwohaKu/v4e8SLLquelY80lQhr3xGjcL8HdwT7WyRPyQzv8SodsOW7xXtp1WtaSQiIiLXwUCMrEYikWBq94YWX8fSIMeaRrevThIRYMUiu+kmfHA+d0uGWWuPI7kqhfu2s+mYsy4RRaXunfTj5d9PAQDuGlH2wBGkNkjlaElmxKT0fCv2hIiIiGyNgRhZ1cvDWjq6C1bVuWGIsG3ubMIO0SEaxx5eeVjjWHmFHBfSZbieXSQ6fv8XB7DpVBpmrD4CAJj54zH8eeImvtl71bwOuYgrtysDT2NHiezNFin1Tc3Sqerl309asSdERERkawzEyKqC/b0wqWu0o7thNfVC/IRtD7V/LZczjRuBWD+rl8ax69nikY/b+SVo+vq/GL58H/os3SUKxpTTGNWLGh9z0dps7uLvxFtWv6bEguju4bgYYfvYtRzM+/sMSyWQzZRVyHEpI5/rXYmILMBAjKxuyXjLsyd+ufuKFXpiucGtIoTtgS0jROeyCkrVm+v05r2tdZ77cvcVdH13h+hYn6W7cCJVM9DacLL6w79qendyPGtkTiyv0Fw7aGwNNR/P6l/n4788iB/ir+GR7zRHXoms4dmfT2DIR3ux7sh1R3eFiMhlMRAjpzC4Vbho/70tFxzUEzEPafUIRedGtVH3TqKwrz56oS/j3aM9Y7Qer5ArdL7X+784qHHs2Z9PCNut6jlfba2arLjc8rVsZWqBWN/mdfHqiJaICPLB84Ob633tp/9d0jh2PDXX4j4RafPvmcpai1/ucY4vzXTR9uUGEZGzYCBGDrXluT54JK4Rlj3Q3tFdAQDkFlWPcr0xqpXG+cjM6hGGYD8v0bnE65ojWG/fdw8AQCqVYOtzfUXnSsvl6P/+LrP72lFl/Ro53q1c8xNtKJWrBfPz7m2FesF+ODR3EP5vcDON9gNbVn+BcTGjMqV9cZlzJjch96Fax85Zk+kAwLFr2Wjx5hZ8s9e5g0UiqrkYiJFdNQwVpyJvGRmEhWPvQe0A6xRLtlTi9Vxhe4yWKWESVE8BUx8B+2pPdfKMN0a1whdTO+EhlSySLSID8fGkDsL+JzsvaawVM4XUFvnTnVC7BsGO7oJRLqvV9jKHekHnmLAAALrXjr3/oOYXGOrTetVH2Ygs9ZDKlNfM/BJ8fzDFcZ3R49U/TqNCrsCizc4xw4KISB0DMbKrDJlz1zuavuqIsC3X8flVmTxj5YFk0fHt5zKE7bEd6mNk23oaH6DbRFVPJ0xIzjbYn9+O6l5/IbFJJSvnoBqOWKMkgj1sU/n7N5d60OSpniFGTWiAN2Kq6qz1a14Xz/58Ah/vFE9RXHPomsX9IlJ18EqWaP+tDWcd1BMiItfGQIxs4uXhLYTtXk3DAFSm+35PJZHHb0/F2b1fpogM1p9K/PdjN3SuP/Dz9tB63Mez+nhCiuFA7KWqWlra7Lt02+DrXdWd0LbCdrfYMAf2xHh+Xtr/zk2hPjVR3bODqqcnfvtIFwBAXJPK57Pn4m1RMheltzedt7hfREp3CpyznAQRkSuyXoVaIhUbVFJ7vzysJVpOD4S3hxQSiQSHrmahfXQIusaEOrCHmvQl29DlrQ1n8e79bTWO6/pQbs1MzylZRYYbuahi3+rgKz2vGLF1AhzYG+1mD2iKz3ZdFvY3nLyFJ/o0RlsLplKW6xqGrfK//k2QU1iKoW0i0KdZXQCG1+iY83NNpEt2ofHZYomISD+OiJFNNAqrXgvWPjoEPp4ewjS9JePbYXI355tudteMJAdrDqfitb9OQ6FQoG/zusJxDx0LuOoG+pjdP20e//6I4UYuSCKvrn9VVOqctbBeGNocR98YLDo2+rP9Fl2zrEJ/0OTr5YG377tHCMIAYL0N6pkR6aLrdxsREZmOgRjZxIAW4YYbqVFOYbSXneczcODyHSEDmLnZv9YeTsWCjeew92LlVMGXhrXQ2VbXlEUAGNWunsn33nE+0+TXuAL/4uppl22inDNZh0QiQZ1a1g2sVae6qq4nJHIWeXe118uTO+HIq/P1iIhIjIEY2YTUjG9Nv5vWFS0jA23QG01/HLuBGd8fxdQVh/Hg1/EAgF8SUs2+3mqVrGGqhXVNERnkK6z7qekUKr+aFDXo45TqiNj6Wb0c2BMi7ULUynYonbmVZ+eeEBG5PgZiZBMeOtJt6+Pr5YG3RrcBADQLr2XtLom88NtJYfvYtRzM/OEoPth+0ajXnl0wTO/5T3ZqFtY1hrenFJ4enPYDAHJp9Yc9J/yiXS9LCsiqZk30MpAx0RndLa3Anou3UWKF4tau7kK6DKsPJCM3MNbRXbGqdUe0Z3Id89kBpxwVIyJyZq73X3pyCeYGFMrX2TvBgHrq8Zgwfx0tgQAf/TluZMXmrWm6ersAretxOhoA5AQ3Fbad/cPd0/2biPZ3nDc/jb2rJ9Z47a/TmLYyAXPWnTTc2I3J5QoMX74P8zeeQ2r0UFzMyHd0l6zm673V9RKTF48Unfti92X15hZbse8qHv7usMmFykvL5Vap7UdEZEsMxMgmpGaMiAHVC8HLDGSPU6VQKJCaVQSFFVMSrpzeVe/5J/s21nnuucHNdJ4DoDPY+nRyJ0QE+WLrc31x8NWBhjtpQ78euY64xTuR46AMaWVe1SOizlLsW5cJXaJF+6/8cdrsaxlKX2+Kh3pUJsQZ016zMLkt3Mgpwl8nbgIANp1Os8s9ncnt/BIs/vc8ku8U4uodcQBwPk3moF7ZlnqdxPe3XcSZm9adovjOpvPYd+kO/jh+w6TXfbP3iuFGREQOxkCMbKJ/i7oI8PZAzyamJeDwrArEKgxkj1P19d6r6LtsF5b8e8Gke+nTuK7+qZH9VDIkqvu/QfoDsb9na679SVkyCt5Va8taRAYiKsQPax/vbkRPgdwi6wdLL/9xCml5xei55D+rX9sYYTmVta+6xYSiloERSEeLCBIn7NCVzMAYpeXmT2tUFxlUWQfPX0+CGGvq/d4uu9zHGRWWlKPruzvw9Z6rGP/lQZxWC0aS7xQ6qGe2p56w5t5PLcscqsvrf50xqf0fx2/apB9ERNbEQIxsItDXCyfmDcUaI4MJJeVI2q28YqNHuJQBmOqUGVvz1pOQQ/1bYnXGrv3p2bSOxjF/bw8ceX0wPpzQXjhmyQd/Q8xJ6W8qbX/Pcmll8NWxUYjN728pf29P7H1pgLDf2IKaZ9acmqj8ObRm7TrS7vdj1aM12YWlUF8muHyHeetGXYEtCzybOh1RlTsHv0TkPhiIkc14e0oNBiXqUrOrixR/sM245BmqjE2U0KeZZpCj9NtTcQZfry8Qs6VzC4ejbqAPxnVqIBxLSnfd9Scxr25C7NzN+OnQNdzOr/5AdyesHQDgSqZrfJhqqLKm8P6O9c2+TpkFiT50sUXWydyiUmw+ncakHDo4+7pGc6RmFeHtf84J+/VD/HS2NbcUiLo5vyaK9gtKqtffXsrIx6w1x91q/R0R1TwMxMipdImpLWx/r5IS3ljGjuCU65n6aEzCDE+p9n86DUN1J/kwx1P9qhNB6Jry+P62JKve0xHeWH8GIz/Zp3HcksQX9qYM7r/YfcXsD4fmBGLavuuY3C1aOG6LEbGHvjuM/605jve3uv7PnjWoJydKlxWL9vUFLa7ivi8O4Lv9ycL+1w931tnWkt9JCoVCGBnefDpddO70jcopn7suZGLIR3ux6XQaHvwq3ux7ERE5GgMxcio+ntXrWWb0MT3tc5mRa8vK9SQDMWZNja51WfrWjplDNSPfrAFNtbYpLLHtqIStRtzUpySqjoi5oqu3K0fv7pZVYOhHe826hjnJOkL9NZOZRAX7CdN8bTE4c+ZmZfIJrsOp5KX2xYz6lzmBvs69ztEY2WqJe1KyKn/eT741VKOtasBmqti5m9Hktc34eo9msg3l7+ZHVx8RjtlyajYRka0xECOnEqxSLFR9Ebgx9K0rKywpF84fScnR2c6Y6ZSxdbWvA3p5eAuDrzVFsJ8XfpzRDetm9tA5HTLEv/qZvfbXaTz90zGzMkjeKSjBnHWJSEjOFh0ftty8oMIQbamlF/97XrQf19i0ZC+OdDP3rsXXKDJjSleolqyS03rFQPlTbMuC2Oofzmuq2wbWSfl42Sdhij31qPq3GayjwLM5VH9vLdaSfKnEislsiIicAQMxclrvbDpnuJEaXd/+p9wpRJu3tiJ27mbRN6jjOtbHyuldTL5PbS2jEEBlkhJr69OsLrrrCUjO3qocnThzMw9rD6fi3zPpeG5dImJe3YQL6canzX77n3P488RNTPhac6qPtrV3JeUV2HjyltkfxlVHP5W+3iNOuPKUWo0u0qT+syiRAEG+XtVTFq0chxmT2VFaw+qS1w0Uf2n0+A9HRfsnr+fasTf2Yc4XZYYYGhV/dFWCxhdF2hSVliPIDUYhicj9MRAjp1VcJsf5NBkmfB2PIymG/+MLaP/2f8PJW+j//m5hPy3vrkr7ykDHVD6eUrRrEIwmOkbGDPFQ+aTao3GoWddQp5o2+u/EWwCA4cs1113pom8KYtPX/8WqA+LpRo9/fxTP/HwCnd7ebmJPK5XqWA+lWofIlQuyXldJPGNLQX7iD5xzR7QEAEiqxsSsPR6mbVqv+gisXAHIimvOlLEAb8Mf+l29WLc+I9tGah2ZNdXxVN0zFQCgsLRC6xdFqj7cfhGt521FgErZi64qa4+JiJwJAzFyao9/fxQJydl48Kt446bbaWny7M8nRPuqwcnMvo2F2mWmkEgkWP+/Xtj2fD/hWJdGxv/H/r4O1Zn1Dl01LsjU5+DlOxZf44KBtWALNp5DhVwhjCjuu1R9zz0Xb2PWmuPIMiGVta4pj6oBpbWCVEfos3SX0Vk8LRFRVS9Mya9qGlx1sg7rBgDbz2kmUNE2ZexShusG0aYy5leIem0xV/bBg+1F+59P6YQjrw+2+LohOmYaGCuvqAyf7KwsFZCWV50wxZqF0omIrImBGDmdKd0bAgCm94wRrbuJnbtZo636B/9LmQU4cPkODl3NMqoGTat6QaI1YRu0FFvWRSqViEa27qkfbPRrrbGW7KVh1dfYc+m2RdcyNg35g18dRPsF2zRGe6atTMCm02no/M4Oo+9pzAhB03D9hbWdyYW3h2scm7X2uM3vO6lrQ9G+8udZqCNm5fv93y+Jov2tZ9O1Jmfw8qg58xONqdKR4sJ1rVq++a9of1S7eqJ9iUT8u9BcYRaOqj288rDW4/qy5BIROZLTBWJ79+7F6NGjERUVVTnqsH696Pz06dMhkUhEf4YPF38Ays7OxtSpUxEUFISQkBDMmDEDBQXib2dPnTqFPn36wNfXF9HR0Vi6dKmt3xoZKaRq8bcxH25WHUgR7U9dcRhTVxzGpG8OoeWbW3DUyCmNKUtGIWXJKLRrEGJib6uZ8kFEdRRj63N9zbrfvVUfhvy9PXDtju5pcMaMiIz59IBR9zyemgsA+FNPtjxjPnAWqtQD0kfbOjJn5aslIYOuMgfWFFZL/OFVGeAqfxptPRjw5I/HsExLGvtn1Eai3Zvhf/vf2LHgvLUVl4lHPLX9rKvT93vnVu5drNh3VdTm4OU7ojqSqu6pr7+kSJlHZXmAUze0jzq687RQInJtTreatbCwEO3bt8djjz2GcePGaW0zfPhwrFq1Stj38REvGp46dSrS0tKwfft2lJWV4dFHH8XMmTOxdu1aAIBMJsPQoUMxePBgfPXVVzh9+jQee+wxhISEYObMmbZ7c2QUZUCzO8nwKE+SgXpN724+r/e8NZn6jfDp+UORW1SGaDNrjynvVyFX6K0/tWJfMp7o2xhA5cjXrdxixNYRr20z9BzVnU/TnQTknU3nsWKa/gQo+9RG8A68OhC9lvxnUh9cQYPaxtWP+vXIddzIMW9NmXryDOU0LFtMTdx0Ks3ottey7LNGzhkYM6I8s+rfoKtTzdKqT35JOYLUkhfJisvQa/F/yK/6Imb7uQxM7tYQz61L1Hut76Z1RfdFO3WeP9/iEb1FpPWVKyEiciSnGxEbMWIE3nnnHdx///062/j4+CAyMlL4U7t29dqc8+fPY8uWLVixYgW6d++O3r1749NPP8Uvv/yCW7cqExisWbMGpaWlWLlyJdq0aYNJkybh2WefxYcffmjz90eGKesfJRsxsmJo+mF6XrHe89YkNWYIT0Wgr5fZQRggDsRy9dTSeXfzeZRVyHH6Rh4eWnEYA97fjV1JmWbfF9AfuBlThPmpn6qn7L02sqVbFLzV5msjR0Fe/uMUPvnvsln3iAwWrxHLqcpiae2kiXlFZWZNtSwpr0CBkSOgrsqYL2F8vZzuP7c6bTh5C1vOaA+6Vz/aTefrFo5tI2zvu6i5bnVdwnUhCAOAw8nZWoMw1ef51/96IiLIF2+MaqW3z/q+yOAaMSJyVq7zXwYVu3fvRnh4OFq0aIGnn34aWVlZwrn4+HiEhISgS5fqb+QHDx4MqVSKw4cPC2369u0Lb+/qKT3Dhg1DUlIScnK0Z20qKSmBTCYT/SHbMGVkqWVkoN7zaXoCsTZR+qe7mMreKbuFQEyhQI6OAtNKzV7/F6M/2y/UT3vyx2MW3duYINlYM3pXjhSopwAn46hPE4u/Wvn7UFj7aKXPoKdu5pr1uu6LduKet7a6dTCmbwqtf1HlFxPGFpt3tLy7ZXj25xN46qfjWr/o6hAdovO1w++JFLa1jQbnG/kzUCFXIOmd4Uh6Zzg6Nqz8otXQ74cFG3WXO1EWWycicjZONzXRkOHDh2PcuHGIjY3FlStX8Nprr2HEiBGIj4+Hh4cH0tPTER4eLnqNp6cnQkNDkZ6eDgBIT09HbGysqE1ERIRwTnWETWnx4sVYsGCBxvGJEyfCy8v6taPMkZCQgDFjxji6GxbLDOsARHTXek79/eUFxgDRw8y6T9K1NJOfl9Zn3PpJAMDvv/2G/V8cMasv5ij38AVaTINCIf6g0Trpe2TU6YSssLY6X1taLhfehwIQ3oM6ibwMfsVZKPKP1HpeF4PPVeV+9983FgAQCeC2Wj9c7udZy3McPWYsJIaiIS2vM+m9q7xe9t83GPPvEtyp3Rqo1wf7D+zHmHXzNV5i6u+L3MBYIHqo8X1C5XvIrerb6OnPIrDwhkmvdxX6fg8VyHIh9Y/A0vc/wLd5l+zbMTOUefgBLR4BAIybMBl3fcOARvcCABqnbMCYMV/rv0DV3/dTby5D3ezTolO3IuKAsHZG9ePBceJZMZlh7YGIHsK+391M3PWr/m/9fgOZY13ud4mTcZfPF86Oz9n2bPmMy8pML9vicoHYpEmThO22bduiXbt2aNKkCXbv3o1BgwbZ7L5z587FnDlzhH2ZTIbo6GisW7cOQUHWHVkx15gxY7BhwwZHd8NiX+6+gve2XNB6Tv39bTubjplmju4smhSHCV0nmPQabc845tVNAICJEyfghaFvmtUXc+QVlaH9wm0axzf/9SuKSsvRet5Wva//a/3f8JBKcOpGLsZ8pj1ZR/LS+wBUv0djNArzN/hzqHo91bYKhULIjjmpazSWLHGtn2dtz+nX3/+En7fuERPV96zKlH/Lyvt2jw3FuiWrAQA/HrqGN9efQYt2XfHDx7M0Rs5M/X1x+kYeRn+233BDFb/+8RdavrkFALBw4QKzava5gmPXsjH+y8r6Vt9N64IO0SGYv/EcJnWNxtQVlW1Cut2PDc/0dmAvjaP6e+XbVd/j4e8OA1Vf9Kz49AM0rqs/k6nyZzEtsifiV78rOvf2P+e0ZtjURv1ns/+yXYDKukPVIMyc65Fp3OXzhbPjc7Y9Wz5jmUyG4GDjM2gDLjo1UVXjxo1Rp04dXL5cub4iMjISmZni9S/l5eXIzs5GZGSk0CYjQ7yORbmvbKPOx8cHQUFBoj9kf+rZryyZ+t9ezxQbc0hMXCNmKQ896cH9jSgwu+FkZeZDfYvcTaFMyV9cVoE7BSVCkoiyCjkOXrmD4rIKKBQKXFJZX/bRRHE9IolEgsOvDUKDm7uxZLxx35w7k/fV6isBugtXK1lz+UqbqOr/ACifc0JKthAMWaLCjKQfN3Kqy0/kF7vv1ERV/ZrXRVgtH3w6uSN6Na0jHHeZOmIqv1YuZxbgf/2bCvuWpqi3pK7ek/2aiPaXjNM94q8uyNflvnMmohrC5QOxGzduICsrC/XqVabyjouLQ25uLo4dqx4l+e+//yCXy9G9e3ehzd69e0VDiNu3b0eLFi20Tksk+6rQk+FKPTvgrgvGJ53oFiMuDmztOkfhdl7jZKj303vG6D3//LqTACrroSk1VEke8mgv/a9XSl48EilLRmFIq8rpvRmyEnR5ZwfmbzgLoLKg9pRvD6Plm1sw7suDolTnLSI0v9CICPJFaJ5mOnRX8EDnBvh7lrgWXfsF23Dsmva1p4B1M7qpfk7WV2LAHPr+Xeqimk3QldO3GysmzB+eHtr/s+qKCWnCArxFvyclRqTpV3U5U5zUx9ikGW+Nbq1xbGKXaNG+rrqNEUGav4etXNOciMhqnC4QKygoQGJiIhITEwEAycnJSExMRGpqKgoKCvDSSy/h0KFDSElJwc6dOzF27Fg0bdoUw4ZVzs9v1aoVhg8fjieeeAIJCQk4cOAAZs+ejUmTJiEqKgoAMGXKFHh7e2PGjBk4e/Ys1q1bh48//lg09ZAcR7WIs7rLmeJ6cOuOXjf6umueEK8789LxgclUn0/phMndojGxa7Thxlbk46m///PHtNF7Hqj8oPzgV/HCvqfKh64BLaqn/swe0BS6KEcC76ot7P8+/hrKK+T490y6cOxEai62nasejY4KEWf8cwfto0M0PjSO//KgzvbWrHGkOihr7eQY5hTFHfVJ9VTGxOu5QkbHmiQoPwUA8FCPRo7tiBnUM17qG4XXZvCHe0X7nRtVf9G56dneeHFoc62ve7RXrMYxqdponK5ArGtMKN5/sD0GtgzHtucrazSaM5pLRGQPTheIHT16FB07dkTHjh0BAHPmzEHHjh0xb948eHh44NSpUxgzZgyaN2+OGTNmoHPnzti3b5+oltiaNWvQsmVLDBo0CCNHjkTv3r3xzTffCOeDg4Oxbds2JCcno3PnznjhhRcwb9481hBzEj8n6A6udBX8NIaXhxQ9GlePiqnXuDHXqHb1sHhcO6sFdsbS9s17ypJRJl1jtVpBbNWkH94qgV64lm+Z1TWP0MxgaWidWoi/t97zrsqYIFjJGoHY0NaVo5FTupv+Yf/f02kadd202X7OcFkCQwzVi3JHssAYAMBXe644tiNGUp11UFahwCqV3xFRwZZ9cfLH8cpkLc3Ca6FNVDA6RFcHZj/O6IaYMH/8NEN7oiYAuPzuCIxsG2kwlf0DnRtg5fSu8KtaF8k4jIicldNNnO7fv7/eAqRbt+r/YAcAoaGhQvFmXdq1a4d9+/aZ3D9yrG/3XcXItpXTUM35APvzEz3wd+It+HhKEWxkYVJ35u+j+1eAamA5pn0U5v19Vu+11JNBAIbXR7krfck51FljZuLXD3fG3bIKo9YGqsqQFePpNZW1wQwF8aojmxFBPsiQlZjczz0XDQd87ipPT60/Z/LHserMlqXlctEsBHPWwSoUCuF1By5Xlla4VHXNXk3DMLFLNGLqBKBPs7rY/dIAvdfy9JDii6mdjb63srtyRmJE5KScbkSMSJ8Tqbm4VTV1sajU9KlXEokE93WsjxFVwVxNt+1sus5zqlMfQ/y9hTUuF94ejjlDtE8pItNZ40OiRCLRCMJ6qySK0EW1/pzcwBcb3WKrR5MPvzZYa5u5I1riyX6NDd63JvEpqVwfOKZ9lIN7YpxTKklFdhpRnF2dehIN5ZcxZ7QkK5FIJHjvgXZ4un8TjXPmUg0WpVXbjMOIyFkxECOXo2sk7L4OrvFBx1a0ZexTenZgU7z/YHs80LmB6Pi+S7pr71xVK9p84NWBSFkyCr5eHpjZtzGa1A3A/R3rW9Zpsla9ZQ2vq03fUk2coeSpsu7G0DqaHVVTE1UTumgzd4T+aWM1Ta3CWwCAmDoBDu6JccrKq4doVX8HfDK5o1Gv36EWvCmzsi78p7rg8rhO1vm9oS2JY6nKz7kyEOOIGBE5KwZi5HSa1NX/gUU5UnP6hvgbVvXpYOrZ69zdeC0fbj6e1AGDW0Xgib6N8UDnBnqDNXX3ROku0eDr5YEdc/rho4kdzOkqqTiRqjujoiUig8TreVTX/ylJVUYPDE31za9K2qBvnWbTcP01pmqmqufqRMHAhXQZrmVp/jwAwK6k6ky0iddzhW1jR/TaNwgR7RdVBWKq5Qs+MOH3kD47X+ivcWzr2epAUMqpiUTk5BiIkdN5sq94mso4tVEX5X9Sc4rEay78vMRTsyItXFjuCj6e1AEAMKV7Q63rN8Z2qI8V07og0IjEJGcXDMOHE6o/IMWE6Q+Itd3vyqKRRn9z/tKwFka1c1XPDW5mVLvzaTKb3F89y5y2rIeqdaH+75cTJl1/eJvqmot/PN0Tb49tg4EtTSuyawuW1KqyJWvWi7NEVkEJhi/fh37Ldms9X6byc2JO7bf71H5fb62a/qz6c26tmouxBkYZJcKImFVuR0RkdU6XrINI/QPktnMZGNWuHjadSgOg+9tNP2/x9wq13TQjn6qxHepjbAfTpvk8O7ApPvnvssbxAB9PjOvUAHFNwuDtIdX4ezCGh1SCjLxig+0S5w1x24yJSs8Nbo7eTevgAZXyANqEB9nmCwNPtb+/1OwitG0gTvmtmphh69kMlFXIsfZwKgpLy0WFfLWpHVD999e5UW1RanJbKq+Q66zVteHkLTz78wk0qRugdbTEIap+XylsNgnVNOpTjlXpS5RlrGi1qasLNp7Tmo7eWqQS3YGW6j8B1aQhRETOgiNi5PR8vTzw+ZROwn5WQWWCgcZqUxjVv7319pQKHw6TF4+0cS9dx/MGEm3UC/ZDWC3zi1Or/71o4+5BmFKJynqbhORsrW1CbfQsPNQCsRQtU9HUA/Jmr/+LtzacxdItSXhj/WmUVvVf27RFfR/alen0re1aViFavLkFS/69oHHubmkFnv25clTvyu1Cg8lHrGnPxcq1lilZmtM2lX8Ljh6VUSgUGPzhHlHdQHV79awZdVZvjNIs/qykOvXW0c+fiEgbBmLkdNS/s3yyrzgLW62qlOvqI2OqUxGVSST+eLonUpaM4jehKrQ9iz+e7mm166sHAMrr/zKzBwDgnvq61565G9Xi5BO+1vwArFAoMGvtcZvcW/3vwZgsiqp+OpSKlQeSAQD5xZqp1x/vU/nvUj0BDAB8MbUTlo5vZ9L9jPHS76dQIVdorcmVVShOp7/qYIrV76/LJzsv6TlbNSLm4EDgWlaRKBU9ACHQVvo78abN+9FdJfumNYTV0v1FhjgQYyRGRM6HgRg5vQi1tV7KlNuq39IPbxOJBrWrp8RM7tbQPp1zEy0iNYsxm6uOymha8uKRSF48Ep0b1UaPxmG4umgk/nmmj9Xu5ewe6KQZpFzPLhKK5ibfKRSNmlmTh1rAbc4H0QOX7yC3qFQ00jOle+W/rabhtXDh7eFaE8B4ekgxoWs0jrw+GM8O1D/F0RS6RhUB8YduANh06pbV7msZZSDm2EDAy1PzP/fqI523802vDafN9J4xon3VItGH9fwdmkN97eO+l6trkUlU3jIDMSJyRgzEyOnVCRB/47nqQAoA8YeIT6d0REuVYMJZF+w7K/X1RJa4p34w5t3bGise6QKJRCKu62PF+7gC9fd74PId9Fm6C1NXHAYgToxg63tvPJkmCgYUGmPPmvZduoMOC7fjvs8PCMdeHFqdZEVbEW9VdQN9MGeofZKyJKutfTqemmuX+xqkEP2fw2j72z5xXZyxMzTAOtNk549pI9p/8sdjVrmuNo3CxGvSVNeoqQbnjMOIyBkxECOn16qeeCqbMvuWMg5rGOoPLw8pmkdUB2J1A81f41QTeelIfmCux3rHYrCN1gm5sjWHrwGoHtmxZwKHlQeS8efxm8gqqBz1yKxjXHZLdcqpwebStXZLLldgwlfxePz7o2ZdVzXVujORVP0d23PNmjba1vn9U5UASanMRl9g/XehOiV+bX/DGVxN0SUmFLVzKtcMzhogzrir+l0ER8SIyBkxECOnozrD6L4OUaLsbABwqWqdg/LbfdX/2K6a3hWLx7VFswjrTbWrCbSt6yLrWPt4d2H75HVx7Tt7fzZ84beT6PzODmQVlCAjvKtZ1/DWMsXNkGcHVafyz66aWqzu6p1CJKRkY8f5DK0j2urHVu5PxqLN54Xg4dDVLNF5f2/9o3X2o1D5X8fRFoisPZwq2i8s0Sz6DVg32dFf/7N+fcfotD1IWTIKLw1rKTrOZB1E5OwYiJFTWz5J97f2p6oKOt8pqP5gN6BlONeHkVNRHdFVTd6x7kiqzdaHGfLcukS73u//VAKxVVUJQNSpfhmgXiMQAIrVntXCf87hm71X8dwviQCAYD/xSIuhGlP25ugRGUMFu4HKzJNKu1/sDwDCFGNribHj34tqt415/0RE9sZAjFzWwn/OAQAKSkwvOlrT/a9/E8ONyCp0jSDN33AO3+2vDkpsEThceHu41uP71NKUJ7w+CBtn97b6/ZVUg6zfjt7Q2mb+hrPCdtd3d2DjyVu4U1CdPEJXILPpdOX0ukyZONHEqHb1zO6vNUmUdcQcHAfoen6qAUpRWfXv0pg6AUhZMsrsKcaNnSAQVn3LlzLyHdcRIiIdGIiR0+EXl7b38vCWhhuRVXh6aB9NuFtWgY0nqzP79WwSZvV7G0qmoRQe6KtR7NlWMvNLMH1VAvLuVo96lZbLsefibVG7Z34+gfu/qE4SUmEgsUlCijgbX4C3ZWvZrM3RWRN1Lf+6W1Y9ClakY2qiORrXrWW1a5nLR+VLEFeskUZE7o+BGDkdZRFmsq3BrZhMwx7U08iLzqmMFKmnX3dGE7tEW+U6u5Nuo/2CbUICi3c2ndPa7np29VTOjm9vN+kezjMVzTnWiOl6Hul5xcJ2Yan1Zhc81jtG45h6WntbU51S+bWW2nNERI7GQIycTmydAGx/vi+OvznE0V1xa1891An+3h6cpmhj+tbXxDWuHgVzhnwphv7N7VTJfmcNk789BAD4If6a3naGMg6qrm1Scp5ArJKj14jtPJ+h9bhqUeciLc/RXD2baBYQH+rATKqOWo9JRKQPAzFySs0iAvXWtLFVmuWaxNNDinMLh3Oaoo15SCVoExWk9ZyXyrRFayZEMFdogDdSloxCuI7yD32aaX64tsTh5GyjpuxNqgrYdDmXlqdx7MytPMiKNZN+mMOSuoTOskbsg+0XtR5XnTqrLaC1Jl8HZ7K8nMl1YkTkXBiIkUv6Zu9VR3eByGhrVFLYq/KQVv8Kvp1fnWzCnjFZk7qaSRWahmtf3+Nt5XpzABA7d7Pe8wqFQqi7pkuuliyLfyfeQrv52yzqGwAcvpqFpq//K0omYprKCGzN4VQcT80x0NZ+IoIqg23VEbFyG48iOrqkwEMrEhx6fyIidQzEyCUt25rk6C4QGc1TSwDTIiIQ/ZpXjzAps/8BgKcd5yl2iw3VOObIKWTq/jh+02CbGSpFoEMMFAxWKBT49eh1JKUbNzoy8ZvK0bjVB1NwwkAgpUz5rsu4Lw4adU9bmzuiJTyrvgRQBl+pWUU2v6+fkcljrGn2gKbCdrqsWE9LIiL7YyBGRGRjvlpS2JfJ5YgI8gUAjamLZQYyBJoiTM8UXwB4oHMDjWMDWoZrbatwQMqJF387aVJ79dGxzPzqD98KhQK/HLmOl38/hWHL9wrHCo0sgXG/jkBKOdKjLeGKuYWzbenJfk2EabHKaZf/XdC+hswSifPEaw79HDAi9sLQ5qL9XB0FxYmIHIGBGBGRjWkbEVNd5+ijo9aYNRx+bZDe850aamYpbRQmnq44sm0kAODRXrHW65id/KSSCOSFX09i7p+nhf0KuQJvrD+DNm9txbFr2ke71APZmFc3aaxrU+46wTI/oyl/JpVBv7en9YOkEH/xs3PEiJj62su/ThgeYSUishcGYkREDlCuZ9RrZt/GVruPtiBQadaAJjqThNQL9hW2P5/SCafmD0WretqTjhhjWlwjs1+rZE76/ByVEbI/1T6E5xaVYs3hVADA8h3ak1loe88/HhJneVSOFDprIHY9W3PaoXL6a7m88guBAB/bBEnvP9he2PZ3gtpuCzZqL5VAROQIDMTI5a2c3sXRXSAymfr0w9+fihO2X7VTJkt9tcumdGsIoHINmUQiQZCv/rVXhlgjY57UjLVz6kGTqgojUhl6aLnn13vEyYLkwoiYc0Ri7RdsQ8yrm4S0/x9pCTIvVK2Ryy+unJaZYaP1U2PaRyEq2Bcj20ZqfZZERDUZAzFyee0bhDi6C0QmU45EKHWJCcWZBcNwZdFIswIOfdpHh2g9ri8Qe7p/E/w0oztWTrfOGicfI6a+9WismThElTFJTD5QGYExxJhaY9mFmmuKbubeFR9QBmJG39l2MvOLkXe3chTwUHIWAOByZoHO9v9bcxxFpeVYtPmCTfrj7SnFwbmD8MXUzja5PhGRK2MgRi6P37KSK9I2NbGWj6dNfp5/fyoOax7vjjHto0THk+8U6nyNp4cUvZvVQS0f60wnM2Yd3BujWus9b8yzGd+5gSgTpL6U6RdUMifuu3RHaxttgRggDm5Kq9b76Qts7SVTVl0G4dwtGQDg1A3NOmuqWs/bKtpvGRlo/Y45ieYR2kszEBE5AgMxcnm2rn1DZE3Kul32LEru5SFFr6Z18Mnkjvjrfz2F4ylZugMxawtQCYhWPKJ9OrGhQEb9/KSu2teM/fpkHJ7sV7nOrkhPkeLfj93Qez8AaKKjptrgD/cAgChxR2GpcdkXbWnPxdvC9qGrWaL6dMba8lxfa3bJqTQM1aybR0TkKAzEyOU5IhMXkal6NQ0DADzZtwmAyi8QbuRUTnGzYrZ6g2LrVH8QtUWBZl2GtIkUtiNVEoEojbjH8BoiTw/x+VkqNaLUqa/jUs90CACbTqVpHFO3VyWwUZdfXCaMhgHapzqGZZtbCNo8qjUW9126o/V912R3yxwfLBMRKTEQI5cXYKWpU0S2tPrRbtj70gAMriqWXCFXYOE/lRncTl7PtVs/VFOKH9WRst0Wgnyr/536qn15MrhVOJY+0A6G4sKSMvHolvq0SW010ZRkxYY/gKvXE7tToH806WJGvqgwdD0tAWZojv2y9CnXhimVlMs1Eoi0tiDzpatSzbZ54HIWg1MichoMxMhlqK9vIXIlXh5SNAzzFwrp1jSBvl74aGJ7LJ/YAUF+4gBqxbSuCPT1Mjg1MauwFD8/0QPD20Ti0NxB8FJZd9YsvBaWPdBO2FcPyoxJzKG+lqrLOzv0tn/6p+Oi7JfaRvQUEvv9ZzZHy3o29SLcHRqG2Kk3zuO9B9rhqX5NhP2ScvtNCyYi0oeBGLmMqBA/R3eByGJedpwO6Gzu79gA93WsD0+p9mdgKBA7eSMXcU3C8NXDnREZ7CvKolgvxE80+tOkrnhtlzGB2Eu/n9R7/t377xHt3y2rgFxldEVr/+0YiGlb86c++NMw1F/vNU68OcSaXXIaqklbDlzWnpiFiMjeau4nAnI5T/SJRX0GY+Ti7Lkuy9WYmjFSNahtpBZg5N4Vjw4ZE4gp1+xp81CPhhjcKkJ0LMDbEwEqRYq19V+i0J0sxNquZWkWblZPCvNorxi916gd4K33vKtSXV844/ujKHKCxCpERPxEQC4jrJYP9r8yQHRsYMtwB/WGyDzWrhHminSllDeU/f16tjhQUg18BrXS/btAoVBYnKXyrdFtEBHkizlDmgvHZMVlCPGvLnStbbTTtzjLovsCwNXbBXhkZQKOpGTrbbcrKVPjWKLK+sNV07sK9dye7NvY4n65kl0XxM9mT5LuJCxERPbCQIxcikQiwa4X+wv77RoEO64zRFbyw2PdHN0Fu1JP1qEktyBWkqvNwRvfqXqNWIVcYVGZi6bhtYQg69lBzYTjRaUVwgosbx110iSAKFgzx+AP92Dvxdt48Kt45BZpr2sGALu1BBfHqhKyeHtKMUDli6vRWtbcTu3e0KJ+OrOTauv/ruqpoUdEZC8MxMjlhAf6CNunDRQqJXIFfZvXdXQXnIJqYgl/bw8kvD5IdH7t4911vlZ93ZlqBsNyuQIVKlHePfVNyxzYNSZU5zllBj59A52TuloW4KjGkJO+OWTSa1cdSAGg2b86tXw02r57f1tTu+YyStUSdJy9xf92EJHjMRAjl6M6119fsVYici2qAccrw1siPFCcDr5n0zoar3l2YFMMbhWBXmrnVAOzpPR8jPx4v7C/clpXk/r1UA/dgZRyIE4C3ZHYw3GNTLqfPhfS83Wud9M15RMAisvEgUhksC8+nNDeav1ydn2aiX8+Np9Ox6GrWSi3Y2F1IiJ1DMTI5XipfMAqt2QuE5GD6BvZqSmUo12zVYoye6gsElMfwdFWowsA5gxtgRXTumgkyvD1qv49MfbzA6LCy7rW6TWpGyDaD6yqU6avaPwP8SkA9K9vU74vTyutD2zy2mZsO5uucVw5bTIiSHO0S5txnRoINbbm3dvaKn1zVtr+Did9cwhNX/8XgOaImbGuZxfhqIG1e0REujAQI5ej+iGKKe3JFUWrZPhbOr6dnpa29fLwFg67d3igL1KWjMKLw6r7EB1a/e9ZPVh6UE+xZm3UCxmr0pUmXz3lfVnVFz36Sg58uy9Z7zUrz1X+vzmr1P45dUvr8Zk/HtM49t/5yoQUrUwo2rxkfFsceHUgHusda0bvXIe+NYK7LmSi+Rv/YsJX8SZft8/SXXjgq3hRYW8iImMxECOXpu+baiJnFa4yYqFeeNgeDr82CNE3duCJPs6VOU81eFJ+bt4wuxeeGdgU/1MZObNUbR3JM5T3vJxZgJhXNwnT+Yyp/aZvrEv5vtQTihhj9toTRrdNqBqZ0Za0QxeJRFIjyoLoy5r56OojACqf34yqbVOdvsk1Z0RkOk/DTYiclxmfa4gczsfTA6fmD4VUInFIOvuIIF/Ull1x7uLSVf+42zUIQbsGIVa9tEQiQceGITiRmis6nlNUikxZMe7//IDouOq6VN0X1Xe/yv9XKICLGfloHhFoYo9N16tpGA5ctjx1vrswNgjeeUGzBIAut/NLhO30PN016IiIdHHi/woTGWbON8xEziDI1wu1fPhdmC62/pe9+lHNkgHHruWg26KdyC8RF/s1Zm2X/qmJ1edmrz1uQi/N17iOeJrl8okd7HJfZ/XW6DYI8fdC15jaets93MP4xCpjP6tOAHPlNtPhE5HpGIiRS2MYRuSe5BbU/VL6e1YvneeC/bzw7MDK6Y6G1lQZEzDn3S3TeU41jruYUWDwWtbw2shWov0BLXQXvK4JmkcE4vgbQwz+XZvy5Z7qurODV+6Y3TciqrkYiJFLM/TtJhG5JivEYWgfHaL3/PNDmuPQ3EF4sq/+tXKeFk7h1Jfa3hLXsgpx5mYenvvlBNLzikXn/NRS2Uv4X3tIpRKNws7qyiuM/8HLVJmaqF4egIjIGJwXQy5p87N9cPRaNh7sHO3orhCRDdhj2rFEIkFksK/e1PNfTu2kcezgqwPRc8l/xt/HQBCUfKcQtf29EOLvLTquMPAM+i3bLWyvT9SeXVHJ25nXA9rRJ5M6iJ6bujIzS6LoGxElItKFv5nJJbWOCsIjcTEOSXRARO7l3C2ZznMj2tbTOBYV4ocLbw83+vr61o99vusyBry/Gx0Wbtc4p6twszkYiFVqFBaAk/OGIumd4Vg3s4fG+UNXjE9wMmdIc2t2jYhqIP5mJiIip9MlJtRu97pTUGrya3y9PNBQpR6cuSngl21N0nlOX+0rU/FLq2rB/l7w8fRA98Zh2PvSAFGNultqUzz18fdm+RQisgwDMSIichqH5g7C70/FoYOB9V3OQDWt/c1c49OXbzmTblQ71RGxHXP6Gd+xKqoFskm7hmH+WPZgezQK8zfcWI22QLmgpNwqiWaIqGZgIEZERE4jMtjXrqNhlff0MdxIC2PS2gOaWRe3nEnT2u5OQYlov6i0QthuGOqPv/7XE32a1TG6f99N62p025ouurYZgZhakejLmQW4562tmLLikLW6RURujoEYERHVaBU68jP836Bmel/nKa3+T2idWt56WgKBKsGYrsQaXd7ZIdr/OSFV2PaQStCxYW38OKO7cCw61E9vMNg8IhBrH+9u1mhaTbP/cnX6+bwi4xJvlKllWBz84R4AwKGr2dbrGBG5NQZiRERUo1VoyZS3/fm+eN5AMoZzadVJPurU0j+q9tqoVhrHDl7WX3vqeGqOsO2hJeC6k1+qdXrcRxPbC9s9m9ZB0/BaGm1It/e36V63p0pfMhVdo55ERKoYiBERUY12b7soAEDjugE4+OpAnJw3FM0iAk26xsWMfL3ntX1oP3VTf00rD3159QHU9vfSelw1iQgZ5+2xbYTtTaeNC6L0pbqf8+tJi/tERO6PgRgREdUY/72gOU2vfXQI9r40AJuf7YOoED8E6whw9DGUn0G9Jpis2PD0t4x87Rn8ZlYVoK7QUWfM14vZ/Ez1UI9GwnZ2oXFZNCv0FH9WXd9HRKQLAzEiIqoxAn11jCKF+ds0gFH/yN5u/jaUlOkvHnzmpvb6ZsqBsgxZidbzdQ1MkyRNEokE/VvUBQAMaR1hsH1xWQVKys0r/kxEpORpuAkREZF7cFRhY20pzct0ZQmB5giaquTbhXrvFR7ka3zHSDCwZTh2J92GoVyYeXfL0H7BNrv0iYjcG0fEiIjIbb2hliTDw8MxhY21hVW+Xrr/E/zaX6d1ntt2LkPr8eTFI5GyZJSpXaMqwX6Vo6XbzmXonJ74/tYkBmFEZDUMxIiIyG093qexaN/H03r/2XuoR0Oj22oL//45pT0pRIVcgZ8TrpvUl2UPtIPEQHIP0k8ZiAHAm3+f0drms12Xjb7er0dN+zskopqHgRgREbm1wa2q1/x4WXFq4oIx91j0+gvp2jMt3sgpMvlaD3aJtqgvBIT4V9eC23QqDbuTMi263su/n7K0S0Tk5hiIERGRW+vdNMwm1/WQSjCmfZRRbY0ZrWrXIBgA0G/Zbku6RWZSHREDgOmrjqC0XI6T13ORVaA9MQoA1AvmmjwiMg+TdRARkVvrEhNqs2svfaAdOjYMwYAW4RZfKzxQ+wf63k3riPa/eqgTnvrpuMX3I7EgX82PRA9/dxiHk7MBANue76v1dVO6NcQH2y/atG9E5J4YiBERkVu7p34wfprRHfVCrD9y4evlgUd7xRpsZ9zyLQVSszSnJX4+pZNov19zy4M+0lRbZWqikjIIA4C1h1O1vu6D7Rfh7SFFqZ4smERE2jAQIyIit9e7WR3DjWwor8hwAWeFAui7bJfo2JVFI+EhFUdxft7iemfvP9je8g4SpFL90fLqgyk6z51bOAzn0/Ix+rP9Vu4VEbkzp1sjtnfvXowePRpRUVGQSCRYv369cK6srAyvvPIK2rZti4CAAERFReGRRx7BrVu3RNeIiYmBRCIR/VmyZImozalTp9CnTx/4+voiOjoaS5cutcfbIyKiGmj/5TsG2+y8oJkcQj0IU2oaXkvYfqBzA/M7RiLfPtLF5NecWzgMnh5StK1a46cqR0cafCIiwAkDscLCQrRv3x6ff/65xrmioiIcP34cb775Jo4fP44///wTSUlJGDNmjEbbhQsXIi0tTfjzzDPPCOdkMhmGDh2KRo0a4dixY1i2bBnmz5+Pb775xqbvjYiIaqaWkYFWvd7G2b3h4ynFm/e2tup1a7ohrSMMN6py/M0hSFkyCv7euicX7b5oWeZFInJvTjc1ccSIERgxYoTWc8HBwdi+fbvo2GeffYZu3bohNTUVDRtW13QJDAxEZGSk1uusWbMGpaWlWLlyJby9vdGmTRskJibiww8/xMyZM633ZoiIiABEBvtZ9Xp+3h5Iekf7fyvJ9pLeGQ4fTw+N47MHNMXeS7dx6kYeAOD5dSdxf0eOWBKRdk43ImaqvLw8SCQShISEiI4vWbIEYWFh6NixI5YtW4by8nLhXHx8PPr27Qtv7+qFucOGDUNSUhJycnK03qekpAQymUz0h4iIyBgKKBzdBbIibUEYALw4rAU2zO4t7LfTMl2RiEjJ6UbETFFcXIxXXnkFkydPRlBQkHD82WefRadOnRAaGoqDBw9i7ty5SEtLw4cffggASE9PR2ysOMtVRESEcK527doa91q8eDEWLFigcXzixInw8vLSOO4ICQkJWqdpkvXwGdsHn7Pt8Rnbh/I5Z4Z1ACK6m/Ta5ld+xZgxX9umY27E6j/LrZ802MTQ/TybPYRyrwDcProFY8a4/hp0/r6wDz5n27PlMy4rM5yUSZ3LBmJlZWWYMGECFAoFvvzyS9G5OXPmCNvt2rWDt7c3nnzySSxevBg+Pj5m3W/u3Lmi68pkMkRHR2PdunWiINCRxowZgw0bNji6G26Nz9g++Jxtj8/YPpTP+bP/LuH9babVmtr22/c26pV7sfbPcsyrmwy2MXS/l38/iV+P3kB4l+H4e/Y71uqaw/D3hX3wOdueLZ+xTCZDcLBpo+AuOTVRGYRdu3YN27dvNxgIde/eHeXl5UhJSQEAREZGIiMjQ9RGua9rXZmPjw+CgoJEf4iIiIwh58xEl7F4XFu957vFGi4QnlBVf+xk1VoxIiJtXC4QUwZhly5dwo4dOxAWFmbwNYmJiZBKpQgPryyCGRcXh71794qGELdv344WLVponZZIRERkiSndGxpupGJ0+ygb9YQMmdytIZIXj9R5/tmBzQxeIy2v2JpdIiI35XRTEwsKCnD58mVhPzk5GYmJiQgNDUW9evXwwAMP4Pjx4/jnn39QUVGB9PR0AEBoaCi8vb0RHx+Pw4cPY8CAAQgMDER8fDyef/55PPTQQ0KQNWXKFCxYsAAzZszAK6+8gjNnzuDjjz/GRx995JD3TERE7q1OLeOnxT/YuQGWsUizQ0kkEgR4e6CwtELjXK+mhr8ALimX26JbRORmnC4QO3r0KAYMGCDsK9dlTZs2DfPnzxfmdXbo0EH0ul27dqF///7w8fHBL7/8gvnz56OkpASxsbF4/vnnReu7goODsW3bNsyaNQudO3dGnTp1MG/ePKauJyIiu2vfIFg0hW1QK+NrWZHtTOsZgy92X9E4LpFoL7JNRGQqpwvE+vfvD4VC92R6fecAoFOnTjh06JDB+7Rr1w779u0zuX9ERETm6NU0DAcuZ4mO/fNMb+w8nykKxHKLSu3dNdKib/O6WgMxY/RpVgf7Lt0BAOQXlyHQ1zmyKxORc3G5NWJERESu6NtHumDtE93xeO/q8in31A/G0DbiEbBsBmJOoUfjMHw3rQv+e6Gfya99e+w9wvbnu8wL5ojI/TndiBgREZE78vf2RM8mdSCBBCv2JwvHW9UTZ+FtXKeWvbtGOpg7TbRcJU3mgBZ1rdUdInIzDMSIiIjsqEfjUDzaKwaN6wRoPR8eZF69S3IedQOr/w7XJ95E98aGE3wQUc3DqYlERER2JJFI8NboNng4Lkbr+Q4NQuzaHzJsSGvTRsaC/arXhP2ccB2XMvKt3SUicgMMxIiIiJyIVMqsfM7G28Oyj0tDPtorbBeXaabEJ6KaiYEYERERkR6eHtYJjr8/mIKWb27B9nMZVrkeEbk2BmJEREREevRsYp01Xm9tOAsAePbnE1a5HhG5NibrICIiItLjwc7R8PXyQKeGta1yvXK53CrXISLXxhExIiIiJzF3REtHd4G0kEolGNuhPqJD/Y1+zcl5Q0X7BSXlwnZZhQJylRT3RFQzMRAjIiJysAOvDsQHD7bHYyrFnsm1eXmK15UVqgRiAND4tc0oLefIGFFNxkCMiIjIweqH+GF85wbwsjA7HzkP9UyLJWWaQdfUFYfs1R0ickL8jU9ERERkZR5qZQgSUrI12hxJybFXd4jICTEQIyIiIrIyiUQciJ26kYvGdQI02u29eNteXSIiJ8NAjIiIiMjGfjx0Dd6emh+7HlmZ4IDeEJEzYCBGREREZGMKReUfIiIlBmJERERENvBorxjRflJGvmM6QkROySoFndPT0/Hnn3/iwoULKCoqwooVKwAAt2/fRnJyMtq2bQs/Pz9r3IqIiIjIJbw1ug1kd8vxx/Ebju4KETkhiwOxL774Ai+88AJKSkoAVC5OVQZimZmZiIuLw1dffYUnnnjC0lsRERERuZQGtflFNBFpZ9HUxI0bN2L27Nlo27YtNmzYgKefflp0vk2bNmjXrh3Wr19vyW2IiIiIXJJULXsiALxz3z1YMq6tsM/CzkQ1k0WB2LJly9CwYUPs2rUL9957L8LDwzXatG3bFufOnbPkNkREREQuSaoZhyH5TiH6t6j+zDTj+yN27BEROQuLArHExESMGjUKAQGadTGU6tevj4yMDEtuQ0REROSSpFoisTq1fET7+y7dgVzOlIpENY1FgZhcLoeXl5feNpmZmfDx8dHbhoiIiMgdaZuamJpdBPXDG07eslOPiMhZWBSItWjRAvv27dN5vry8HHv37kXbtm11tiEiIiJyV9qmJmpzODnbth0hIqdjUSA2depUnDhxAgsWLNA4V1FRgRdffBFXr17FI488YsltiIiIiFySthGx0nI5fL08RMd+TkiFQqGArLjMXl0jIgezKH39M888g40bN2LhwoVYs2YNfH19AQATJkzA0aNHkZKSgqFDh2LGjBlW6SwRERGRK9ESh+F6dhGC/TSXdsz++QQ2nUrDP8/0xj31g+3QOyJyJItGxLy8vLB161a8+uqryMrKwpkzZ6BQKPD7778jOzsbr7zyCjZs2ACJtt9CRERERG5O22egRePu0dp206k0AMCKfVdt2icicg4WF3T29vbGu+++i3feeQdJSUnIzs5GUFAQWrVqBQ8PD8MXICIiInJTm0+naRxrGh6o9zVlFcygSFQTWByIKUkkErRs2dJalyMiIiJyeceu5Zj8ml1JmTboCRE5G4umJp47dw6ffPIJbt++rfV8ZmYmPvnkE5w/f96S2xARERG5hQa1/YTtI68PFrZ7NgkTtotKK+zaJyJyDIsCsSVLluC9995DWFiY1vNhYWFYtmwZli5dasltiIiIiFzS7AFNRfs3cu4K23UDfTB/dGsAwMErWaJ2E76Ox9+JN23fQSJyGIsCsX379mHQoEGQSrVfxsPDA4MGDcLevXstuQ0RERGRS0qXFYv2nx/cXLR/QC0AU0pIzsb//ZJoq24RkROwKBBLT09HdHS03jb169dHWprmQlUiIiIid/fMwOoRsfBAHzw7SDxCdn/H+npfr1AwcQeRu7IoWUdAQAAyM/UvKM3MzBTqixERERHVJI3CArD7xf7w9/FAeKDpn4cq5Ap4erAMEJE7smhErFOnTli/fj1yc3O1ns/JycFff/2FTp06WXIbIiIiIpcVUydAZxB2K/eu1uNK5XKOiBG5K4sCsVmzZiErKwsDBgzQWAe2Z88eDBgwADk5OZg9e7ZFnSQiIiJyRw920b/Eo4KBGJHbsigQGzt2LJ5//nmcPHkSAwYMgL+/Pxo3bgx/f38MHDgQp06dwosvvoj77rvPSt0lIiIich/Bfl5Y+0R3neev3C6wY2+IyJ4sCsQA4IMPPsCGDRswbNgwBAQE4MaNG6hVqxZGjBiBTZs24b333rNGP4mIiIjcUpt6wTrPjfnsAHZdYIFnIndkUbIOpXvvvRf33nuvNS5FREREVKNIDHwt/uvR6xjQMtw+nSEiu7F4RIyIiIiIbOdyJqcnErkjBmJEREREDhTk64Vxnerjvg5RWs9fyixAfnGZnXtFRLZmUiAmlUrh6emJixcvCvseHh4G/3h6WmUGJBEREZFb+nBCByyf1FHn+bbzt9mxN0RkDyZFSH379oVEIoG/v79on4iIiIiIiIxnUiC2e/duvftEREREZL4Qfy/kFnEaIlFNYNEasb179yIxMdFKXSEiIiKq2dY+3sPRXSAiO7EoEBswYAC++eYba/WFiIiIqEZrHRWElCWjMOKeSNHxbrGhDuoREdmKRYFYeHg4fH19rdUXIiIiIgIQVstbtB/s5+WgnhCRrVgUiA0ZMgS7d++GQqGwVn+IiIiIarwQP3Egxo9aRO7HokBsyZIlyMrKwsyZM5GdnW2tPhERERHVaG0bBDu6C0RkYxYV+HrooYcQEhKClStX4qeffkJsbCwiIiI0UtpLJBLs3LnToo4SERER1RRxTcLUjnBIjMjdWBSIqaavLykpwYULF3DhwgWNdqw1RkRERGS8IF8vTO7WED8npALg1EQid2TR1ES5XG7Un4qKCmv1l4iIiKhGWDyuLd4b39bR3SAiGzErEIuPj8fAgQMRGBiI4OBgDBkyBAkJCdbuGxERERGBExOJ3JHJUxNPnz6NQYMGobi4WDi2c+dOHDx4EAkJCWjTpo1VO0hERERUU0nA5R1E7srkEbElS5aguLgYr7/+OtLT05Geno4333wTd+/exXvvvWeLPhIRERHVaHdLKyCXc1yMyJ2YHIjt27cPvXv3xttvv43w8HCEh4djwYIF6NOnD/bs2WOLPhIRERHVTFUDYvFXszDuy4OO7QsRWZXJgVhGRgZ69Oihcbx79+7IyMiwSqeIiIiISCzxeq6ju0BEVmRyIFZWVoZatWppHA8ICEBZWZlVOkVERERE4AoxIjdmUfp6IiIiIrId1mIlcl9mFXT+6aefcOjQIdGxy5cvAwBGjhyp0V4ikWDTpk3m3IqIiIiIiMjtmBWIXb58WQi81G3ZskXjGL/NISIiIjIdP0ERuS+TpyYmJyeb/Ofq1atGX3/v3r0YPXo0oqKiIJFIsH79etF5hUKBefPmoV69evDz88PgwYNx6dIlUZvs7GxMnToVQUFBCAkJwYwZM1BQUCBqc+rUKfTp0we+vr6Ijo7G0qVLTX0UREREREREZjF5RKxRo0a26IegsLAQ7du3x2OPPYZx48ZpnF+6dCk++eQTfP/994iNjcWbb76JYcOG4dy5c/D19QUATJ06FWlpadi+fTvKysrw6KOPYubMmVi7di0AQCaTYejQoRg8eDC++uornD59Go899hhCQkIwc+ZMm74/IiIiImOpTyoqq5DDy4NL/IncgVlTE21pxIgRGDFihNZzCoUCy5cvxxtvvIGxY8cCAH744QdERERg/fr1mDRpEs6fP48tW7bgyJEj6NKlCwDg008/xciRI/H+++8jKioKa9asQWlpKVauXAlvb2+0adMGiYmJ+PDDDxmIERERkdOSK1jUmchduNRXKsnJyUhPT8fgwYOFY8HBwejevTvi4+MBAPHx8QgJCRGCMAAYPHgwpFIpDh8+LLTp27cvvL29hTbDhg1DUlIScnJytN67pKQEMplM9IeIiIjIlq5n3xXtMw4jch9ONyKmT3p6OgAgIiJCdDwiIkI4l56ejvDwcNF5T09PhIaGitrExsZqXEN5rnbt2hr3Xrx4MRYsWKBxfOLEifDy8jLzHVlXQkICxowZ4+huuDU+Y/vgc7Y9PmP74HO2PXd/xjci+wChrYX9Bx54EFJFuV374O7P2FnwOdueLZ+xOfWUXSoQc6S5c+dizpw5wr5MJkN0dDTWrVuHoKAgB/as2pgxY7BhwwZHd8Ot8RnbB5+z7fEZ2wefs+25+zOev+EsVh9MEfbX/forAnzs+/HN3Z+xs+Bztj1bPmOZTIbg4GCTXuNSUxMjIyMBABkZGaLjGRkZwrnIyEhkZmaKzpeXlyM7O1vURts1VO+hzsfHB0FBQaI/RERERLbk7Sn+qMaZiUTuw6UCsdjYWERGRmLnzp3CMZlMhsOHDyMuLg4AEBcXh9zcXBw7dkxo899//0Eul6N79+5Cm71794qGELdv344WLVponZZIRERE5AieUnHaRCbrIHIfTheIFRQUIDExEYmJiQAqE3QkJiYiNTUVEokEzz33HN555x1s2LABp0+fxiOPPIKoqCjcd999AIBWrVph+PDheOKJJ5CQkIADBw5g9uzZmDRpEqKiogAAU6ZMgbe3N2bMmIGzZ89i3bp1+Pjjj0VTD4mIiIgcTa4WdzEOI3IfTrdG7OjRoxgwYICwrwyOpk2bhtWrV+Pll19GYWEhZs6cidzcXPTu3RtbtmwRaogBwJo1azB79mwMGjQIUqkU48ePxyeffCKcDw4OxrZt2zBr1ix07twZderUwbx585i6noiIiJyKQi3yUt8nItfldIFY//799f6SkUgkWLhwIRYuXKizTWhoqFC8WZd27dph3759ZveTiIiIyNYq5OqBmIM6QkRW53RTE4mIiIiokvrURK4RI3IfDMSIiIiInJR64MUwjMh9MBAjIiIiclLqgRhHxIjcBwMxIiIiIidVUiYXH2AcRuQ2GIgREREROal1R6+L9tXXjBGR62IgRkREROSkpveMEe3vuZjpmI4QkdUxECMiIiJyUq+OaIlZA5oI+6/8cdqBvSEia2IgRkREROSkfL088NKwlo7uBhHZAAMxIiIiIiIiO2MgRkREREREZGcMxIiIiIiIiOyMgRgREREREZGdMRAjIiIiciGrDiQ7ugtEZAUMxIiIiIic3LMDmwrbCzaec2BPiMhaGIgRERERObn7OzVwdBeIyMoYiBERERE5OS8PiaO7QERWxkCMiIiIyMl5SBmIEbkbBmJERERETs5DwkCMyN0wECMiIiJyclKOiBG5HQZiRERERE6OI2JE7oeBGBEREZGTkzIQI3I7DMSIiIiInFyZXO7oLhCRlTEQIyIiInJyXh78yEbkbvivmoiIiMjJBfl6ivZLyzlCRuTqGIgREREROTmJ2hqxR1cnOKgnRGQtDMSIiIiIXMyBy1mO7gIRWYiBGBEREZEL+Ot/PYXt//Vv4sCeEJE1MBAjIiIicgHtG4QI2w1D/R3XESKyCgZiRERERC5AKpVgxD2RAIDSCibrIHJ1DMSIiIiIXISPZ+VHN2ZNJHJ9DMSIiIiIXISsuBwAkJSe7+CeEJGlGIgRERERuYj/LmQCAH47dsPBPSEiSzEQIyIiIiIisjMGYkREREQu4uXhLQAAA1rUdXBPiMhSDMSIiIiIXESQrxcAwNuTH+GIXB3/FRMRERG5CImk8v8VCsf2g4gsx0CMiIiIiIjIzhiIEREREbkICSqHxDggRuT6GIgRERERuQjl1ES5XIEf41NwIV3m2A4Rkdk8Hd0BIiIiIjLNzguZ2FlVUyxlySgH94aIzMERMSIiIiIXcfV2gaO7QERWwkCMiIiIyEXcLatwdBeIyEoYiBERERG5iLulckd3gYishIEYERERkYtQsIAYkdtgIEZERETkIgJ8mGeNyF0wECMiIiJyEbfzSzSOFZSUO6AnRGQpBmJERERELmLL2XSNY7uq0tgTkWthIEZERETkwqTKKs9E5FIYiBERERG5iD7N6mgckzIOI3JJDMSIiIiIXIS3h+ZHNwlHxIhcEgMxIiIiIhdRWqFZR4xxGJFrYiBGRERE5CKGtYnUOMY1YkSuiYEYERERkYuY3K2hxjGuESNyTQzEiIiIiFyEh1SCDx5sLzrGETEi18RAjIiIiMiFDG4dIT7AOIzIJTEQIyIiInIhnmpzETkiRuSaGIgRERERuRAPtUDMg4EYkUtiIEZERETkwhiHEbkmBmJERERELoxTE4lcEwMxIiIiIhfG9PVErsklA7GYmBhIJBKNP7NmzQIA9O/fX+PcU089JbpGamoqRo0aBX9/f4SHh+Oll15CeXm5I94OERERkdkkHBEjckmeju6AOY4cOYKKigph/8yZMxgyZAgefPBB4dgTTzyBhQsXCvv+/v7CdkVFBUaNGoXIyEgcPHgQaWlpeOSRR+Dl5YVFixbZ500QERERmUE97mIcRuSaXDIQq1u3rmh/yZIlaNKkCfr16ycc8/f3R2RkpNbXb9u2DefOncOOHTsQERGBDh064O2338Yrr7yC+fPnw9vbW+M1JSUlKCkpEfZlMpmV3g0RERGR+RQKR/eAiMwhUShc+59vaWkpoqKiMGfOHLz22msAKqcmnj17FgqFApGRkRg9ejTefPNNYVRs3rx52LBhAxITE4XrJCcno3Hjxjh+/Dg6duyocZ/58+djwYIFGseHDx8OLy8v27w5EyUkJKBbt26O7oZb4zO2Dz5n2+Mztg8+Z9uric9YLpHiTKsnhP3GKRtQqyjNZveric/YEficbc+Wz7isrAxbtmxBXl4egoKCjHqNS46IqVq/fj1yc3Mxffp04diUKVPQqFEjREVF4dSpU3jllVeQlJSEP//8EwCQnp6OiAhxVXrlfnp6utb7zJ07F3PmzBH2ZTIZoqOjsW7dOqMftq2NGTMGGzZscHQ33BqfsX3wOdsen7F98DnbXk18xqXlcjR/419hf9GiRejROMxm96uJz9gR+Jxtz5bPWCaTITg42KTXuHwg9t1332HEiBGIiooSjs2cOVPYbtu2LerVq4dBgwbhypUraNKkiVn38fHxgY+Pj8X9JSIiIrIm157bRFRzuWTWRKVr165hx44dePzxx/W26969OwDg8uXLAIDIyEhkZGSI2ij3da0rIyIiInJGCjASI3JFLh2IrVq1CuHh4Rg1apTedsq1YPXq1QMAxMXF4fTp08jMzBTabN++HUFBQWjdurXN+ktERERkbVdvFzq6C0RkBpcNxORyOVatWoVp06bB07N6huWVK1fw9ttv49ixY0hJScGGDRvwyCOPoG/fvmjXrh0AYOjQoWjdujUefvhhnDx5Elu3bsUbb7yBWbNmcfohEREROTX1dPVf7bnimI4QkUVcdo3Yjh07kJqaiscee0x03NvbGzt27MDy5ctRWFiI6OhojB8/Hm+88YbQxsPDA//88w+efvppxMXFISAgANOmTRPVHSMiIiJyBXI5pyYSuSKXDcSGDh0KbZn3o6OjsWfPHoOvb9SoETZv3myLrhERERHZTU5RmaO7QERmcNmpiUREREQE3C2rcHQXiMgMDMSIiIiIXIjEcBMicgEMxIiIiIiISMOCjWfx5W4mg7EVBmJERERELu5OQYmju0Bu5lJGPlYdSMF7Wy44uitui4EYERERkQuRqOevB/DwdwkO6Am5s6JSrj20NQZiRERERC7ufJrM0V0gIhMxECMiIiIiIhHVgVdtJaPIcgzEiIiIiIhIRKKSn5NxmG0wECMiIiJyIUxfT/YmZyRmEwzEiIiIiIhIRDQ10XHdcGsMxIiIiIiISCeOiNkGAzEiIiIiItKJcZhtMBAjIiIiciFayogRWZ2HtPoHraxC7sCeuC8GYkREREREJOLtWR0mFJcxELMFBmJEREREbuB6dpGju0BuRHU64sWMfMd1xI0xECMiIiJyIRIdcxP7LN1l556Qe6uOxG7m3HVgP9wXAzEiIiIiIhJRHRH7bNdlZBWUOK4zboqBGBERERERichVArHU7CK8u+m84zrjphiIERERERGRiEKtjHNaXrGDeuK+GIgREREREZGIeu0wuUKBH+NTcDmzwDEdckOeju4AEREREVlucreGju4CuZH84nLR/uHkbBxOzgYAJC8eqTNpDBmPI2JERERELmp6zxhhO9CX36+T9fxvzTGd57aeTbdjT9wXAzEiIiIiFzWmQxRm9I4FAJRVsOguWc+dglKd55766ThGf7ofd0sr9F7jz+M38NOha9bumttgIEZERETkwsqrArBVB1Ic2xFyGzdyDBcHP30zD3+euKHzvFyuwJxfT+KN9WeQbqVEHz8euoaYVze5TfFyBmJERERELuz3Y7o/DBOZ45KRCTnU15GpKlUZoS0q1d3OFG+uPwOgsnj5qRu5UKhnFHExDMSIiIiIXFihgelhRKYKC/A2ql1Jme7psBfS84Xt5TsumdWPrWfTMefXRNwtrdCYejvmswMY9cl+s67rLLiqk4iIiIiIBMYm47hTUAIAuJV7Fz2X/AegOqNikErymA0nb2FK94bo0TjMpH48+WNlwpA/j9/Uev5cmgwKhcJlMzhyRIyIiIjIhfl5eTi6C+RmPt91xah2P1Yl4njqp+oMi2M/PwAAyL1bJmo76ZtDiHl1k5V6WK3IhUeEGYgRERERubCwWsZNIyOyhbIKOU7dyBP2T93IQ8yrmzDui4Na289YfcSq9+///m6rXs+eGIgRERERuTAXnZVFLsJQfbpmr/9r0vV2XsiEXG69JBu380tcNmkHAzEiIiIiFyYBIzGynfGdGlj9mufSZFa93op9yVa9nr0wECMiIiJyYaojYtmFuovwEpnD27M6XFg/qxeC/bwsvubm02kWXyM61E/Y7tQoxOLrOQIDMSIiIiIXJQFwLau6uG3i9RzHdYbcgvo0v5iwAGG7fYNgbH++L3o1NT774Z//64mUJaPw3vi2wrEvdhuXDESb8wuHI2XJKOx9aQCm94zBnCHN0blRqNnXcyQGYkRERERuwkWXypATqVBbvxXgU52VUyKRIDzIFz/N6I6WkYFGXa9Tw9pV17G8atY3D3eGn7eH0Jf5Y9rg2UHNLL6uozAQIyIiInJhvl78OEfWU64WiHlINdcgSiQS/PW/Xlpf/3CPRhjdPgodG4bgj6fjhONtooIt7tvQNpEWX8OZsKAzERERkQtrFBqApIx8ABwRI8up1uX655neaBjmD28PKdo2EAdSft4eWDKuLV7987RwrE4tH7x93z1arxtbJwAvDWuBZVuTAACFJeV6R8nS84pF+6+NbGnye3F2/AqFiIiIyEWF+Hvjqf6NHd0NciMl5dWBWJuoIAT5euH0gqH47ck4jbaTujUU7R99Y7Deaw9TGdG6W6a/EPO2c+mi/YEtI/S2d0UcESMiIiJyMZ9P6YTswhLE1gkQHeeAGFlq8Ad7hG1JVUpOH08PXc0F9UP8DLZpGl5L2DZUS0x1QmSdWj6i17oLBmJERERELmZUu3rCtuoSHlctbEvOo7BU/0iVut+fisPqgyl4897WRrX38pCgrEKBCgM/qxKVugw75vQ1qU+ugoEYERERkQuTqnxgZRhG9tYlJhRdYoxPH+8hrQzEyiv0/7QG+laHKSH+3mb3z5lxjRgRERGRC5OqDImVlssd2BMCgKT0fLy5/gwyZcWGGzuxx3rF2uS6xWWVP6OXbxfobVcv2PBUR1fHQIyIiIjIhalOTTx5Pddh/aBKw5bvxY+HrqHbop0uOVW0Y8MQAECPxrYtkvzY6iN6z5fLKwO2Zm64NkyJgRgRERGRC5OopDX49eh1B/aE1J1Py3d0F0ymHFX19rRtmGAoRlUWlvb0cN9wxX3fGREREVENoFBZGaaa4IAc78dD1yy+hkKhEIISe1Cmlfd2cABUWFLZj7ul5Q7thy0xECMiIiJyYWXl1R/SOzeq7cCekLqfE1ItvsbD3yWg37JdovpetnT1diEA07MnWqq0XI4OC7fhw22VBZ+f+ukYACAlq8iu/bAnBmJERERELqy0ovoD838XMh3YE9Jmy5k0i16///Id3Mi5ixZvbLH5yNiKfVeF7fziMpveCwC+3H1F2B735QHkFpXhk/8uI8PFE50Yi4EYERERkQsrYaZEp/bUT8eRlnfXKtfadjbdKtfR5Z1N54Xtfs3r2vReAPDelgvC9pmbMmH7cHK2ze/tDBiIEREREbmwAO/qekvPDmrmwJ5QcZn26Xxxi/+zSgbFF387afE1dFHvX1gtH5vdS5umKtkRr2e773REVQzEiIiIiFxYTJ0AYTu2jr8De+L8EpKzcehqls2uX1hi28QStly3pazv5Shj2kcJ2zdzq0cQJ3Rp4Iju2AUDMSIiIiIXp5xGVsFZijrdLa3AhK/jMembQ7hro4BG3zTRAisEaarBijVdyypEq3lbhP0/nu5pk/sAQJCvp9bjO1XWN4b4eQnb741vZ7O+OBoDMSIiIiIX51FV1VnuggWE7SWnqFTYLrVRxFqkJ8BrO38b5GrJNv46cQPHruUYff0AHw+z+6ZPv2W7Rfudqoo628K/z/XVely1GPkXKkk83LkkAwMxIiIiIhdXFYdpfNBXtTspEx9tv6i3jTtbtLk6EcXK/ck2uYfqSNu6mT00zndfvFPYTryei+fXncT4Lw9i6opDUP1bKS6r0Pr39HOCfQp22zL4qR/iJ9pPz9OdIbFhqHtPtWUgRkREROTilB+c9cVY01cdwcc7L+HfM7bNvOes/jlVnUb+452XsP1chtXvUaRSfLh9dIjGedVpedeyCoXtA5ezUOoVBADIKSxFq3lbMOmbQwA0Cyt/uvOSNbvscD1UglN19ixk7QgMxIiIiIhcnIfE+KmJ1kql7uqe+OEoSvWs6Sotl+Pg5Ts6MyFqc1elrZeH5sfs2QObCtueUvH5Uu9AAJVrpRQKICFFewr3D7ZfNKoveXfLcPhqlkY2RIVCgZQ7hQ4NcpZP7GBUO9WkHe6IgRgRERGRi1N+pucaMdNk5uueFvfupnOYsuIwXv79lNHXy7tbXQRZKgH+eaY3Hu8dKxx7ft1JfL7rMsor5PghPkX02uRG9yI9rxg+ntUfz2XFZWavZ2u/YBsmfnMIsXM3i45/vfcq+r+/G01e26w1EL2/Y32z7mcK9aQjJ1KNXyfnThiIEREREbk4qXJEzM2nclkiwFsz0UV5he7n9X38NQDAhpO3jL7HuiPVa7gkEgnuqR+MN+5tjQEtqosjL9uahCnfHtZatLjH4p3wVgnE2s3fpvU+Ma9u0luXbHdSpmj/8e+PQFZcGSQu+be6iPKjqxOQU1gqavvhhPY6r2stUql4DZopCUvcCQMxIiIiIhcnNWKNmJI7Z6HTp3+LcJvf43Z+idbjx1NzRfu6ph0CwMc7jFsDdjmzQOe56auOiPZ3nM9Eu/nbNIK3A5ez0PHt7cL+wVcHOuTnw1ZZLJ0dAzEiIiIiFydkTTRiamLNDMO0p34vl1s3AOivMvKlSnXKoiHn0mRGtfPUsgZt1Cf7EPPqJp2v+XzXZb3XjFLLaGhLX0ztJGwv3ZIkbK+a3hUAML5TAxx/c4jd+uMIDMSIiIiIXNzZW5Uf3lNUMvHpUkMHxLSOFg7+cC8StEwR/NDIhBjqvt1nm7T4ZxYMQ4Pa4iCpTG0UadvZdOHnQJf3t5n3vmxhxD2RWo8PaBmOlCWj8MGE9ggN8LZzr+zL5QKx+fPnQyKRiP60bNlSOF9cXIxZs2YhLCwMtWrVwvjx45GRIU5PmpqailGjRsHf3x/h4eF46aWXUF5uebVzIiIiIke4VDVN7adDqQbb1tA4TOdo4cRv4gEAKXcK8crvp5BypxCfmJgiXqFQ4Ng13dMN1VPQm6qWjyc2zu6N+aNbC8euZRWJ2sz88ZjW1/7wWDej7vHJ5I7md9AMNXWKrCqXC8QAoE2bNkhLSxP+7N+/Xzj3/PPPY+PGjfjtt9+wZ88e3Lp1C+PGjRPOV1RUYNSoUSgtLcXBgwfx/fffY/Xq1Zg3b54j3goRERGRxUL8vQAAg1rafh2Uq9I1a1N5vP/7u7Hu6HX0f3+3RpuNWhJ2nL6Rh27v7sB3+5OxaPN5jP8yXue9E9/SPcUuefFIHJo7SG/fAaB2gDem96rOwPjED0fx3pYLuHpb91qxq4tGom9z7dMlVT3VrwnubVvPYDuyLk/DTZyPp6cnIiM1hzPz8vLw3XffYe3atRg4cCAAYNWqVWjVqhUOHTqEHj16YNu2bTh37hx27NiBiIgIdOjQAW+//TZeeeUVzJ8/H97e7j0ESkRERO5nVNt6WHM4Fe0ahBhsW1NHIvStn9t36bbe1z7z8wnc266e6Nl9vPMiMvNL8PY/5zTat64XJNr399b+kTtlySgAQGSwL1pd/BGBw/5P61RJXb7cfQVf7r6CPS/11ziXOG+IRnZCbfd2Jp9Nse+onKO55IjYpUuXEBUVhcaNG2Pq1KlITa0chj927BjKysowePBgoW3Lli3RsGFDxMdXfksRHx+Ptm3bIiIiQmgzbNgwyGQynD17Vuc9S0pKIJPJRH+IiIiInIHUhILONZW+jJIPf5dg8PVxi//DLZUCw7cLSnW2XT6pg8axP57uicGtdI9YepUX4dcn4zSOv3v/PQb71m/ZbtF+ypJRCPHXPrjw7//1wZVFIw1e0xH6NDU8eudOJAp9RQic0L///ouCggK0aNECaWlpWLBgAW7evIkzZ85g48aNePTRR1FSIk4d2q1bNwwYMADvvfceZs6ciWvXrmHr1q3C+aKiIgQEBGDz5s0YMWKE1vvOnz8fCxYs0Dg+fPhweHl5WfdNmikhIQHduhk3D5jMw2dsH3zOtsdnbB98zrbHZ1zpZmQvZIXeg/DbxxB5+6jWNqdaPwkAiErbjzo5ur98Vucuz/ha/cHIC25i0TVqFd5E7LV/IEH189Sm3bmvtR6XSzxwptXjWtspn3Ny9HDkBzbSeR0FgNN67i2Rl6Pthe9Exwr8o5BVuxWib+2BVOE8eRHu+oTiUpMHhf2257626RpGW/4sl5WVYcuWLcjLy0NQUJDhF8AFpyaqBkrt2rVD9+7d0ahRI/z666/w87Ndys25c+dizpw5wr5MJkN0dDTWrVtn9MO2tTFjxmDDhg2O7oZb4zO2Dz5n2+Mztg8+Z9vjM640f8NZrD6YggkTJuLFYdrXvSvTms+cOVO01sgQc57x5cx83M4vRVyTMJNeZ0v/W3MMm0+nW3SNgoD6ON36SYxpH4VTego963peCoUCsXM3AwDWPtEdPZtUTw9UPmeFQoF0WTHqBfsB0D59UF+K+uSlYwGM1XH2/3S+zlFU38tGG/9btuXvC5lMhuDgYJNe45JTE1WFhISgefPmuHz5MiIjI1FaWorc3FxRm4yMDGFNWWRkpEYWReW+tnVnSj4+PggKChL9ISIiInIGzjQ1ccW+qxj84V5M/vYQDly+4+juCCqMqXZtpA16grBW9XR/RpRIJJjavSGGto5AXGPtQapEIqkKwkynTNpCrsHlA7GCggJcuXIF9erVQ+fOneHl5YWdO3cK55OSkpCamoq4uMo5t3FxcTh9+jQyMzOFNtu3b0dQUBBat26tcX0iIiIiZ6fMyVBhRCBmy1DtzM08vLPpvLA/dcVhG97NeAcu38HWsxmGG6ppGl7LpPaTu0Xj3//ro7fNu/e3xTePdLFJ0pT4Vw1nXyTn4XKB2Isvvog9e/YgJSUFBw8exP333w8PDw9MnjwZwcHBmDFjBubMmYNdu3bh2LFjePTRRxEXF4cePXoAAIYOHYrWrVvj4YcfxsmTJ7F161a88cYbmDVrFnx8fBz87oiIiIhMp/xMX1ZuuzArPa8YZ2/l6W0z8wft69P0seZIlS6qAWHb+sFYPrGDwdc82a8xPEwMlh7sEm1q18zSv0V1Uouri0bii6mdcPi1QfDz9rDL/a1p7ojKesArHuni4J7Yn8utEbtx4wYmT56MrKws1K1bF71798ahQ4dQt27lD+RHH30EqVSK8ePHo6SkBMOGDcMXX3whvN7DwwP//PMPnn76acTFxSEgIADTpk3DwoULHfWWiIiIiCxSVFoBAFh5IBmTukXj0/8u4/8GNdM6omPu7MUeiytnHO1+sT9i6gRobXMrr1jvNSrkCuy6kIkODUNQp5YPEpKz8fB3h/HGva3xcI9G5nXMgOvZ4sLHp2/m4b6O9dG4bgDGfHZA5+vmjmiF0zfyAAMDaSfnDcWupEwE+HiiU8Pa1uiyQV891BkJydnoFhsKqVSCkS5cA+zJfk3wSFyMSwaRlnK5QOyXX37Re97X1xeff/45Pv/8c51tGjVqhM2bN1u7a0REREQOcS6tuqzOhK/jkVtUhsNXs5Dw+mA9rzKeatHgnxNSMXdkK7Ous+bwNcz7+yzqBfsifu4g/N8vJ1BSLseb68/YLBDrs3SXaH9ClwYAoFFz7fBrg9B90U7Rsdb1gnDwSpbe6wf7e+G+jvUt76gJfL08jCrU7CpqYhAGuODURCIiIiISUx3lyi0qAwBk5peonK9ukF2ou/6VNkW+dTDwgz3CfvxV/YGJuoMqCTs2n04DAKTlFUOhUMBDT8FhW1kwRntdroggXywd3w4AMLFqimHvZnX0XmtGb+OzTxKpYyBGRERE5OIMzTZUXYb12a7LJl1bFhgj2j91Iw9yE9Z17VcJxA5dzRa2/++XRHjaOBDLUQs65wxprnf0ZULXaFxZNBLvPVAZkKm/Sw+pBINbRSA0oLJY8utmjgwSAS44NZGIiIiI1BhY+GVJWnuJQq5x7K8TNzG+cwPRsdSsIo12AHBeZdqkKvUU8HK5AlIrB2Zf7BYHnbWNSO+uOkrnJa0es+jcqDb+eLqn9TpHNR5HxIiIiIhcnKEBKmsHYuoBDgD0XbZL4xgAdIutrpc1qGW4zvs0fs266/dPpObg233JomMNw7QnGdEVoPVsEoYx7aPwyvCWDMLI6jgiRkREROTiFAYmJ1pS57nYRzMTYH5xudGvb1s/WNjeeSFTT0vr2p10W+NYn6biNV/3dYjC+sRb+HxKJ63XkEol+GRyR5v0j4gjYkREREQurrzCdlMTPSvuahxTTQSiS8vIQAD6g8QgX+uNCSgUCmTIilFYUhkkfh+fotFGferjRxM74MSbQ9Czqf6kHES2wBExIiIiIhdXUq45fVDVW3+fNfvatQrTcCesvehYzyZhOlpXk1YVQ9Y3bdKatZwXbDyH1QdTAADzR7cWskcq7ZjTT+M1EokEtasSbxDZG0fEiIiIiFxc8p1Cved/O3ZDtJ9bZDiFvUKhQH5xGSQKzWmInRsZLlysTHqhL8NiQYnxUxwNUQZhADB/4zmN89qKWxM5EgMxIiIiohrm2LUcrceLSqsDo5d+P4W287chO6SlcCw80AeAcWvOlLMATZkWqbBkMZua4W0irXYtIltgIEZERERUw2gbpFq48Rxaz9uKIymVtb5+rxpFywtuKrQZ1a5e1ev1B0xH3xgMSdXUxN+O3kD8lSxcSNeexl5VmYG1bqaoWxU0AkDCa4Osdl0ia2EgRkRERFTDaAukVh6oTPW+bEuSztdJUBlcGQqX6tTyEaYmbjmbjsnfHsLw5fsM9mvL2XSDbYxVUfUenxvcDOFBvla7LpG1MBAjIiIiqmH0TQHUN9qlnG5oytREUzz78wnTX6SDcm2ah8S6RaKJrIWBGBEREVENoy/LYoURUVZxWQUAIDO/WGebIyna16EBwMm3huo8d+DyHYP3V6ctIUiGrLJvHh4MxMg5MRAjIiIiqmH+75dEnef0xWE/xF8DUJmh8LHVR9Dt3Z1Y8u8FURvVAs66BPt56Tw3dcVhIYgyVmp2kcaxXVUFnTkiRs6KgRgRERERCRKv5wojXqpeGtYCpRXVI2n/XcgEAHy154qoXVSIaeuxloxri63P9RUd675op0nX+OXIdZ3nrudoBmlEzoCBGBEREVENtKoqOYc2s9ce1zg2a0BTjGpbz+B1vT09AAAtIwO1nq/tXzkalrJkFFKWjMKkbg3RQkdbY6kHg6p+OpRq0bWJbIWBGBEREZEbCvL11Ht+gZaix0o7zmdqPe7jpf2j4/cqxZS9lNkS1Ua5lHa/OEBvv0z146Fres9/MbWTVe9HZC0MxIiIiIjckPUqcgG/PhkHAGhSt5bW829tOCtse3lUf7zcMLuXqN0fT8ch2F/7+rCri0YK2+M61TeqX3dLK/Dm+jN624w0YhSPyBEYiBERERG5IWXSDW0ZBU0RlX4A3WJDAQAPdW9ksL2XZ3VyjHYNQrD7xf6ifV2kUgneGt0aAFCqJ6ujklyuQP/3d4mO7Xmpv2j/40kdDF6HyFH0j1kTERERkUtS1gozJh29PkH5KcJ2LQPTHYHqos9KMXUC8NOM7gj09RSNlmnj7Vl5Xl96fQD47L9LWLE/GblFZaLjAT7i/o3tYNzIGpEjMBAjIiIicnGeUgnK1Ua+lLsVFo6IeZcVCNseRlRpntK9ocax3s3qGHUvn6pEH4ZGxN7fdlHj2Hvj26JOLR+cnDcUB6/cwcBW4Ubdk8hRODWRiIiIyMWphlpNw2tVHasaEbMwEDOVrmyJxvARRsQ00+fr075BMCZ2rQwAg/29MKJtPSGoI3JWDMSIiIiIXJxCZfrhs4OaAageEVMfKVNqFq498YalJBYUUFZOTTx0Nduk1528kWf2PYkchYEYERERkYtTjbW6NKoNoDo40zXN71JmAf44dkPvdZPeGa5xTF+ctWOO9pT1xrqUkW/R64lcCQMxIiIiIhf3/WPd4OslxUcT20NaFSmVVVQGYkWl5Tpf98JvJ3H1dgHir2RpPe8l1fyo+P2j3YTt9tEhonN1a/ma2nWRuCZhwvYH25IsuhaRs2MgRkREROTi+jWvi7MLhuP+jg1wt6x6fVV2YakwWhbooz1H2+38EvyckKr1nFRLco4+zer8f3v3Hh1Vee9//DOBTEggkwAhNwjhKl4IKIgxRZFfyY+LtGC1R6pU1FpAGn5qsZiD1aLWChWPepa1HJdLiF0qXlYFK1IryEXFiMIiAgZyJOWmkmDVJGBAEvL9/WGzzZA7ZvZMJu/XWllr5nmemfnu7zyM++ve+9nK6B2nC9O7a9WvfuDX19g9wlqq7n3KHlu/Vx/sb9kpinv/MOl7fS4QDKyaCAAAEAZqVzSsuzjHN9WnnOcNFVXStwt9/G8rTgn0eDx69f9dcuaBNiHa67/Axn/8T772L57c7Os6N7MsPhCKmLUAAABhpG69ZfbdtWKNLT3/+dFvtKfEvxDzdo7QAz/JaNHn3fCDfmcUZ0O8LSio3F4FEggUjogBAACEkbo3TT5ZXePc0LmxW4Ct2v5pvbYVMy/WyH8v+tGce6acp9vHn6VujZz62BotWXHxpa2HvvfnAKGAI2IAAABhJCXuuwUz4qIjVfPvRRMjGilyyo9X1Ws7eqJ+W1Niu0R+r2Xr69p+9//1e376yo5rdpU4j7MG9NTG34xtk88F3EYhBgAAEEbqFlwmqcY5IubRzy/uW298967eem0XD+hZr80tsV38j6zd/tKHqqlzOuLeOtez/c/PR6pfQlfXYgPaEoUYAABAGPH4XSNmdQox6fdThyqzfw+/8WsLS/2eF943QV0i/RfNcFND17INuHON89gX/d3KjKcXbUB7QiEGAAAQRuqeIvjO3n85y9dHRHjk8XgU26XpJeZjvMEtbjwej342Kq1e++7DFZKkHw9PddoaWwkSaA8oxAAAAMLUrc8X6Otvvr2hc+0pi12jGj/aVbfICabFVw2r1zbpv9/W7sMVWvKPb2/0nBr3/W4eDQQbhRgAAEAYu2XFdknfnfKXGh/t1392cqzz+L/+Y7h7gZ2BSf/9tvP4s/ITQYwE+P4oxAAAAMLYF1+flPTdtWOn36ur9h5igxO7yds5dHYN/3TtBcEOAQio0PnXBgAAgIBrrNhqbHn7YPnRsFStmzdGkzNSGuzfec94lyMC2haFGAAAQAfwz8+/luS/qmJdIVaHSZIGJcbqF5f0a7CvuUVHgFBHIQYAANABnJPia7K/rW7I3NaG94mv1/buf/7Q/UCANkYhBgAA0AHUXhrmUcMFV6iuBN/5tGvaLhmUUG/BEaA9ohADAADoAGqvAWvswFeoXSPWmFvGDQ52CECboBADAAAIM/+4bUy9ttpTDy87q1eDrwnlOuzhq79bVv+i/j2CGAnQdoJ763QAAAC0ufSeMfXavqk6Jenba8XWzbtMf3x9j9YWljr9Oz4pdy2+1rpyRB9dOrhXkzejBtobjogBAACEmYaObtXeL0ySBiV209LpI1yM6PvrFRulGC/HEBA+KMQAAADCTGMLctR1+iIYANzFv0AAAIAw09LrvfYvnhzYQAA0ikIMAAAgzLSXFRCBjoxCDAAAIMy05p5gH/w2WwMSuuqlm7MCFxCAerjiEQAAIMx4WnFErFdslNb/ZmzgggHQII6IAQAAAIDLKMQAAAA6gD7do4MdAoA6KMQAAAA6gE3z/0+wQwBQB4UYAABAB9CpNSt4AAg4CjEAAAAAcBmFGAAAAAC4jEIMAAAgzL15+2XBDgHAaSjEAAAAwtiNo/tpYK9uwQ4DwGkoxAAAAMKYWbAjANAQCjEAAIAwVnGiKtghAGgAhRgAAEAY83Zidw8IRe3uX+aiRYs0atQoxcbGKjExUVdccYWKior8xowdO1Yej8fv7+abb/Ybc/DgQU2ePFkxMTFKTEzU/PnzVV1d7eamAAAABBynJgKhqXOwA2itTZs2KScnR6NGjVJ1dbXuvPNOjR8/XoWFherataszbubMmbrvvvuc5zExMc7jU6dOafLkyUpOTta7776rw4cPa8aMGYqMjNQDDzzg6vYAAAAEUg2VGBCS2l0h9vrrr/s9z8vLU2JiorZt26YxY8Y47TExMUpOTm7wPd544w0VFhZq3bp1SkpK0vnnn6/f//73ys3N1T333COv1xvQbQAAAHBLDXUYEJLa3amJpysvL5ck9ejRw6/92WefVUJCgoYOHaoFCxaosrLS6cvPz1dGRoaSkpKctgkTJqiiokIfffRRg5/zzTffqKKiwu8PAAAg1BlHxICQ1O6OiNVVU1Oj2267TaNHj9bQoUOd9muvvVbp6elKTU3Vjh07lJubq6KiIr388suSpJKSEr8iTJLzvKSkpMHPWrRoke6999567dOmTVNkZGRbbdL38v7772vKlCnBDiOskWN3kOfAI8fuIM+BR46bcO5sSdL6jRs15dnfnfHbkGN3kOfAC2SOq6pavzppuy7EcnJytGvXLr3zzjt+7bNmzXIeZ2RkKCUlRePGjVNxcbEGDhx4Rp+1YMECzZs3z3leUVGhtLQ0vfDCC/L5fGe2AW1sypQp+tvf/hbsMMIaOXYHeQ48cuwO8hx45Lhx/f7zNUnSpWMu02PX3HbG70OO3UGeAy+QOa6oqFBcXFyrXtNuT02cO3euVq9erQ0bNqhPnz5Njs3MzJQk7d27V5KUnJys0tJSvzG1zxu7riwqKko+n8/vDwAAINSxWAcQmtpdIWZmmjt3rlauXKn169erf//+zb6moKBAkpSSkiJJysrK0s6dO3XkyBFnzNq1a+Xz+XTuuecGJG4AAIBgqGG1DiAktbtTE3NycvTcc8/plVdeUWxsrHNNV1xcnKKjo1VcXKznnntOl19+uXr27KkdO3bo17/+tcaMGaNhw4ZJksaPH69zzz1X1113nR588EGVlJTorrvuUk5OjqKiooK5eQAAAG1ieFq8PjxUpqtHpQU7FAANaHeF2NKlSyV9e9PmupYvX64bbrhBXq9X69at06OPPqqvv/5aaWlpuuqqq3TXXXc5Yzt16qTVq1drzpw5ysrKUteuXXX99df73XcMAACgPXtx9sX69KvjGtCrW7BDAdCAdleINbcEa1pamjZt2tTs+6Snp2vNmjVtFRYAAEBIierciSIMCGHt7hoxAAAAAGjvKMQAAAAAwGUUYgAAAADgMgoxAAAAAHAZhRgAAAAAuIxCDAAAAABcRiEGAAAAAC6jEAMAAAAAl1GIAQAAAIDLKMQAAAAAwGUUYgAAAADgMgoxAAAAAHAZhRgAAAAAuIxCDAAAAABcRiEGAAAAAC6jEAMAAAAAl1GIAQAAAIDLKMQAAAAAwGUUYgAAAADgMgoxAAAAAHAZhRgAAAAAuKxzsANor8xMklRRURHkSL5TVVUVUvGEI3LsDvIceOTYHeQ58Mhx4JFjd5DnwAtkjmvft7ZGaAmPtWY0HJ988onS0tKCHQYAAACAEHHo0CH16dOnRWMpxM5QTU2NPvvsM8XGxsrj8QQ7HFVUVCgtLU2HDh2Sz+cLdjhhiRy7gzwHHjl2B3kOPHIceOTYHeQ58AKdYzPT0aNHlZqaqoiIll39xamJZygiIqLF1a6bfD4f/4ADjBy7gzwHHjl2B3kOPHIceOTYHeQ58AKZ47i4uFaNZ7EOAAAAAHAZhRgAAAAAuIxCLExERUVp4cKFioqKCnYoYYscu4M8Bx45dgd5DjxyHHjk2B3kOfBCMccs1gEAAAAALuOIGAAAAAC4jEIMAAAAAFxGIQYAAAAALqMQAwAAAACXUYiFgccff1z9+vVTly5dlJmZqffffz/YIYWERYsWadSoUYqNjVViYqKuuOIKFRUV+Y0ZO3asPB6P39/NN9/sN+bgwYOaPHmyYmJilJiYqPnz56u6utpvzMaNGzVixAhFRUVp0KBBysvLqxdPuH5P99xzT70cnn322U7/iRMnlJOTo549e6pbt2666qqrVFpa6vce5Lhp/fr1q5djj8ejnJwcSczjM/XWW2/pxz/+sVJTU+XxeLRq1Sq/fjPT7373O6WkpCg6OlrZ2dn6+OOP/cZ8+eWXmj59unw+n+Lj43XTTTfp2LFjfmN27NihSy+9VF26dFFaWpoefPDBerG89NJLOvvss9WlSxdlZGRozZo1rY4lFDWV46qqKuXm5iojI0Ndu3ZVamqqZsyYoc8++8zvPRqa/4sXL/Yb05FzLDU/l2+44YZ6OZw4caLfGOZy05rLcUO/0R6PR0uWLHHGMJeb1pL9tlDap2hJLM0ytGvPP/+8eb1eW7ZsmX300Uc2c+ZMi4+Pt9LS0mCHFnQTJkyw5cuX265du6ygoMAuv/xy69u3rx07dswZc9lll9nMmTPt8OHDzl95ebnTX11dbUOHDrXs7Gzbvn27rVmzxhISEmzBggXOmH/+858WExNj8+bNs8LCQnvsscesU6dO9vrrrztjwvl7WrhwoZ133nl+Ofz888+d/ptvvtnS0tLszTfftK1bt9rFF19sP/jBD5x+cty8I0eO+OV37dq1Jsk2bNhgZszjM7VmzRr77W9/ay+//LJJspUrV/r1L1682OLi4mzVqlX24Ycf2pQpU6x///52/PhxZ8zEiRNt+PDh9t5779nbb79tgwYNsmuuucbpLy8vt6SkJJs+fbrt2rXLVqxYYdHR0fbEE084YzZv3mydOnWyBx980AoLC+2uu+6yyMhI27lzZ6tiCUVN5bisrMyys7PthRdesD179lh+fr5ddNFFNnLkSL/3SE9Pt/vuu89vftf9He/oOTZrfi5ff/31NnHiRL8cfvnll35jmMtNay7HdXN7+PBhW7ZsmXk8HisuLnbGMJeb1pL9tlDap2gulpagEGvnLrroIsvJyXGenzp1ylJTU23RokVBjCo0HTlyxCTZpk2bnLbLLrvMbr311kZfs2bNGouIiLCSkhKnbenSpebz+eybb74xM7M77rjDzjvvPL/XTZs2zSZMmOA8D+fvaeHChTZ8+PAG+8rKyiwyMtJeeuklp2337t0myfLz882MHJ+JW2+91QYOHGg1NTVmxjxuC6fvWNXU1FhycrItWbLEaSsrK7OoqChbsWKFmZkVFhaaJPvggw+cMX//+9/N4/HYp59+amZmf/7zn6179+5Ons3McnNzbciQIc7zq6++2iZPnuwXT2Zmps2ePbvFsbQHDe28nu799983SXbgwAGnLT093R555JFGX0OO/TVWiE2dOrXR1zCXW6clc3nq1Kn2wx/+0K+Nudw6p++3hdI+RUtiaQlOTWzHTp48qW3btik7O9tpi4iIUHZ2tvLz84MYWWgqLy+XJPXo0cOv/dlnn1VCQoKGDh2qBQsWqLKy0unLz89XRkaGkpKSnLYJEyaooqJCH330kTOm7ndQO6b2O+gI39PHH3+s1NRUDRgwQNOnT9fBgwclSdu2bVNVVZXftp999tnq27evs+3kuHVOnjypZ555Rr/4xS/k8XicduZx29q3b59KSkr8tjcuLk6ZmZl+czc+Pl4XXnihMyY7O1sRERHasmWLM2bMmDHyer3OmAkTJqioqEhfffWVM6ap3LcklnBRXl4uj8ej+Ph4v/bFixerZ8+euuCCC7RkyRK/04zIccts3LhRiYmJGjJkiObMmaMvvvjC6WMut63S0lK99tpruummm+r1MZdb7vT9tlDap2hJLC3RucUjEXL+9a9/6dSpU36TTZKSkpK0Z8+eIEUVmmpqanTbbbdp9OjRGjp0qNN+7bXXKj09XampqdqxY4dyc3NVVFSkl19+WZJUUlLSYH5r+5oaU1FRoePHj+urr74K6+8pMzNTeXl5GjJkiA4fPqx7771Xl156qXbt2qWSkhJ5vd56O1VJSUnN5q+2r6kxHSXHda1atUplZWW64YYbnDbmcdurzUtD21s3Z4mJiX79nTt3Vo8ePfzG9O/fv9571PZ179690dzXfY/mYgkHJ06cUG5urq655hr5fD6n/ZZbbtGIESPUo0cPvfvuu1qwYIEOHz6shx9+WBI5bomJEyfqyiuvVP/+/VVcXKw777xTkyZNUn5+vjp16sRcbmNPP/20YmNjdeWVV/q1M5dbrqH9tlDap2hJLC1BIYYOIScnR7t27dI777zj1z5r1izncUZGhlJSUjRu3DgVFxdr4MCBbofZLk2aNMl5PGzYMGVmZio9PV0vvviioqOjgxhZeHrqqac0adIkpaamOm3MY7R3VVVVuvrqq2VmWrp0qV/fvHnznMfDhg2T1+vV7NmztWjRIkVFRbkdarv0s5/9zHmckZGhYcOGaeDAgdq4caPGjRsXxMjC07JlyzR9+nR16dLFr5253HKN7beFG05NbMcSEhLUqVOneiu0lJaWKjk5OUhRhZ65c+dq9erV2rBhg/r06dPk2MzMTEnS3r17JUnJyckN5re2r6kxPp9P0dHRHe57io+P11lnnaW9e/cqOTlZJ0+eVFlZmd+YuttOjlvuwIEDWrdunX75y182OY55/P3VblNT25ucnKwjR4749VdXV+vLL79sk/ldt7+5WNqz2iLswIEDWrt2rd/RsIZkZmaqurpa+/fvl0SOz8SAAQOUkJDg9xvBXG4bb7/9toqKipr9nZaYy41pbL8tlPYpWhJLS1CItWNer1cjR47Um2++6bTV1NTozTffVFZWVhAjCw1mprlz52rlypVav359vcP9DSkoKJAkpaSkSJKysrK0c+dOv/9A1e4onHvuuc6Yut9B7Zja76CjfU/Hjh1TcXGxUlJSNHLkSEVGRvpte1FRkQ4ePOhsOzluueXLlysxMVGTJ09uchzz+Pvr37+/kpOT/ba3oqJCW7Zs8Zu7ZWVl2rZtmzNm/fr1qqmpcYrhrKwsvfXWW6qqqnLGrF27VkOGDFH37t2dMU3lviWxtFe1RdjHH3+sdevWqWfPns2+pqCgQBEREc6pdOS49T755BN98cUXfr8RzOW28dRTT2nkyJEaPnx4s2OZy/6a228LpX2KlsTS0o1GO/b8889bVFSU5eXlWWFhoc2aNcvi4+P9VovpqObMmWNxcXG2ceNGv6ViKysrzcxs7969dt9999nWrVtt37599sorr9iAAQNszJgxznvULoM6fvx4KygosNdff9169erV4DKo8+fPt927d9vjjz/e4DKo4fo93X777bZx40bbt2+fbd682bKzsy0hIcGOHDliZt8u79q3b19bv369bd261bKysiwrK8t5PTlumVOnTlnfvn0tNzfXr515fOaOHj1q27dvt+3bt5ske/jhh2379u3Oin2LFy+2+Ph4e+WVV2zHjh02derUBpevv+CCC2zLli32zjvv2ODBg/2W/C4rK7OkpCS77rrrbNeuXfb8889bTExMveWoO3fubA899JDt3r3bFi5c2OBy1M3FEoqayvHJkydtypQp1qdPHysoKPD7na5d3ezdd9+1Rx55xAoKCqy4uNieeeYZ69Wrl82YMcP5jI6eY7Om83z06FH7zW9+Y/n5+bZv3z5bt26djRgxwgYPHmwnTpxw3oO53LTmfi/Mvl1+PiYmxpYuXVrv9czl5jW332YWWvsUzcXSEhRiYeCxxx6zvn37mtfrtYsuusjee++9YIcUEiQ1+Ld8+XIzMzt48KCNGTPGevToYVFRUTZo0CCbP3++3/2XzMz2799vkyZNsujoaEtISLDbb7/dqqqq/MZs2LDBzj//fPN6vTZgwADnM+oK1+9p2rRplpKSYl6v13r37m3Tpk2zvXv3Ov3Hjx+3X/3qV9a9e3eLiYmxn/zkJ3b48GG/9yDHzfvHP/5hkqyoqMivnXl85jZs2NDgb8T1119vZt8uA3333XdbUlKSRUVF2bhx4+rl/4svvrBrrrnGunXrZj6fz2688UY7evSo35gPP/zQLrnkEouKirLevXvb4sWL68Xy4osv2llnnWVer9fOO+88e+211/z6WxJLKGoqx/v27Wv0d7r2Hnnbtm2zzMxMi4uLsy5dutg555xjDzzwgF8BYdaxc2zWdJ4rKytt/Pjx1qtXL4uMjLT09HSbOXNmvf+BwlxuWnO/F2ZmTzzxhEVHR1tZWVm91zOXm9fcfptZaO1TtCSW5nj+veEAAAAAAJdwjRgAAAAAuIxCDAAAAABcRiEGAAAAAC6jEAMAAAAAl1GIAQAAAIDLKMQAAAAAwGUUYgAAAADgMgoxAAAAAHAZhRgAAA0YO3asPB5PsMMAAISpzsEOAACAQGttQWVmAYoEAIBvUYgBAMLewoUL67U9+uijKi8vb7BPkv7yl7+osrIy0KEBADooj/G//QAAHVC/fv104MABjn4BAIKCa8QAAGhAQ9eI5eXlyePxKC8vT6+++qoyMzMVExOj3r176+6771ZNTY0k6emnn9bw4cMVHR2tvn37asmSJQ1+hplp2bJlGj16tHw+n2JiYnThhRdq2bJlAd8+AEBwcWoiAACttHLlSr3xxhu64oorNHr0aL322mu6//77ZWaKi4vT/fffr6lTp2rs2LH661//qjvuuENJSUmaMWOG8x5mpunTp2vFihUaPHiwrr32Wnm9Xq1du1Y33XSTCgsL9dBDDwVxKwEAgcSpiQCADqm5UxPHjh2rTZs2+fXn5eXpxhtvVGRkpDZv3qxRo0ZJko4ePapBgwbp2LFj8vl82rx5swYMGCBJOnTokAYNGqQhQ4Zox44dzns9+eSTmjVrlm688UY98cQTioyMlCSdPHlSP/3pT/Xqq69q69atGjlyZKBSAAAIIk5NBACglX7+8587RZgkxcbG6kc/+pEqKys1Z84cpwiTpLS0NF1yySUqLCxUdXW10/6nP/1JXbt21eOPP+4UYZLk9Xr1hz/8QZK0YsUKF7YGABAMnJoIAEArnX/++fXaUlJSmuw7deqUSktL1bt3b1VWVmrnzp1KTU3VH//4x3rjq6qqJEl79uxp07gBAKGDQgwAgFby+Xz12jp37txsX22B9dVXX8nM9Omnn+ree+9t9HO+/vrrtggXABCCKMQAAHBZbbE2cuRIbd26NcjRAACCgWvEAABwWWxsrM455xzt3r1bZWVlwQ4HABAEFGIAAATBLbfcosrKSs2cObPBUxD37dun/fv3ux8YAMAVnJoIAEAQzJ49W++9956efvppbd68WdnZ2UpNTVVpaan27NmjLVu26LnnnlO/fv2CHSoAIAAoxAAACAKPx6O8vDxdfvnlevLJJ7V69WodO3ZMiYmJGjx4sB566CFlZ2cHO0wAQIBwQ2cAAAAAcBnXiAEAAACAyyjEAAAAAMBlFGIAAAAA4DIKMQAAAABwGYUYAAAAALiMQgwAAAAAXEYhBgAAAAAuoxADAAAAAJdRiAEAAACAyyjEAAAAAMBlFGIAAAAA4DIKMQAAAABw2f8H8+29oSGot9gAAAAASUVORK5CYII=",
      "text/plain": [
       "<Figure size 1000x700 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "data['High'].plot(figsize=(10,7))\n",
    "plt.title(\"Stock Price\",fontsize=17)\n",
    "plt.xlabel('Time',fontsize=14)\n",
    "plt.ylabel('Price',fontsize=14)\n",
    "plt.grid(which=\"major\",color=\"k\",linestyle=\"-\",linewidth=0.5)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "6d38335f-2897-42cc-ba68-12012370041b",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1000x700 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "data['Close'].plot(figsize=(10,7))\n",
    "plt.title(\"Stock Price\",fontsize=17)\n",
    "plt.xlabel('Time',fontsize=14)\n",
    "plt.ylabel('Price',fontsize=14)\n",
    "plt.grid(which=\"major\",color=\"k\",linestyle=\"-\",linewidth=0.5)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "81e44bc8-f531-4e32-bbf2-5ab0913db52a",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Axes: >"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "data['Open'].hist()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "63fa77ad-19b7-472a-ab2a-0127e20bda79",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Axes: >"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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TtXTpUnXq1EkvvfSS3O5/f/46atQoffbZZ5oxY4a8Xq/69++v/Pz8al9uBgAA8Asq9PzhD3+ocX1kZKRyc3OVm5t7xZquXbte9VvzQ4YM0Z49e2qsycrKUlZWVo01AAAAfvztLQAAYARCDwAAMAKhBwAAGIHQAwAAjEDoAQAARiD0AAAAIxB6AACAEQg9AADACIQeAABgBEIPAAAwAqEHAAAYgdADAACMQOgBAABGIPQAAAAjEHoAAIARCD0AAMAIhB4AAGAEQg8AADACoQcAABiB0AMAAIxA6AEAAEYg9AAAACMQegAAgBEIPQAAwAiEHgAAYARCDwAAMAKhBwAAGIHQAwAAjEDoAQAARiD0AAAAIxB6AACAEQg9AADACIQeAABgBEIPAAAwAqEHAAAYgdADAACMQOgBAABGIPQAAAAjEHoAAIARCD0AAMAIhB4AAGAEQg8AADACoQcAABjhukLP/PnzFRISokmTJtnLzp8/r8zMTLVv316tWrXSyJEjVVJSErDdkSNHlJ6erujoaMXGxmrKlCm6cOFCQM3mzZs1YMAAORwOde/eXStWrKg2fm5urrp166bIyEilpKRo586d13M6AACgGat16Nm1a5d+/etfq2/fvgHLJ0+erDfffFOrV6/Wli1bdPToUT344IP2+srKSqWnp6uiokLbtm3TK6+8ohUrVmjGjBl2zeHDh5Wenq67775bxcXFmjRpkh577DFt2LDBrlm1apWys7M1c+ZMvffee+rXr5/cbreOHz9e21MCAADNWIvabHTmzBmNHTtWv/3tb/XTn/7UXn7q1Cm9/PLLWrlype655x5J0vLly9WrVy9t375dgwcP1saNG3XgwAG99dZbiouLU//+/TV37lxNmzZNs2bNUkREhPLy8pSYmKiFCxdKknr16qV3331XixcvltvtliQtWrRIEyZM0Lhx4yRJeXl5WrdunZYtW6ann376upoCADdKt6fX3ehDAJqtWoWezMxMpaenKzU1NSD0FBUVyefzKTU11V7Ws2dPdenSRR6PR4MHD5bH41GfPn0UFxdn17jdbk2cOFH79+/XbbfdJo/HE7APf43/Y7SKigoVFRUpJyfHXh8aGqrU1FR5PJ4rHnd5ebnKy8vt+2VlZZIkn88nn89Xm1ZcE/++63OMxo4e0AOJHvjV1AdHmNXQh3NDOEKtgP82tMYwB3k81L4Hte1Z0KHnD3/4g9577z3t2rWr2jqv16uIiAjFxMQELI+Li5PX67VrLg08/vX+dTXVlJWV6YsvvtDJkydVWVl52ZqDBw9e8djnzZun2bNnV1u+ceNGRUdHX3G7ulJQUFDvYzR29IAeSPTA73J9WDDoBhzIDTR3YNUNGXf9+vU3ZNzL4fEQfA/OnTtXq3GCCj2ffvqpnnrqKRUUFCgyMrJWA95IOTk5ys7Otu+XlZWpc+fOSktLk9PprLdxfT6fCgoKNHToUIWHh9fbOI0ZPaAHEj3wq6kPvWdtuMJWzYsj1NLcgVX6ye5QlVeFNPj4+2a5G3zML+PxUPse+D+pCVZQoaeoqEjHjx/XgAED7GWVlZXaunWrnn/+eW3YsEEVFRUqLS0NeLenpKRE8fHxkqT4+PhqV1n5r+66tObLV3yVlJTI6XQqKipKYWFhCgsLu2yNfx+X43A45HA4qi0PDw9vkAnXUOM0ZvSAHkj0wO9yfSivbPgAcCOVV4XckHNuTPOPx0PwPahtv4K6euvee+/V3r17VVxcbN8GDhyosWPH2j+Hh4ersLDQ3ubQoUM6cuSIXC6XJMnlcmnv3r0BV1kVFBTI6XQqKSnJrrl0H/4a/z4iIiKUnJwcUFNVVaXCwkK7BgAA4FJBvdPTunVr9e7dO2BZy5Yt1b59e3v5+PHjlZ2drXbt2snpdOrJJ5+Uy+XS4MGDJUlpaWlKSkrSww8/rAULFsjr9Wr69OnKzMy034V54okn9Pzzz2vq1Kl69NFHtWnTJr3++utat+7fVzVkZ2crIyNDAwcO1KBBg7RkyRKdPXvWvpoLAADgUrW6eqsmixcvVmhoqEaOHKny8nK53W698MIL9vqwsDCtXbtWEydOlMvlUsuWLZWRkaE5c+bYNYmJiVq3bp0mT56spUuXqlOnTnrppZfsy9UladSoUfrss880Y8YMeb1e9e/fX/n5+dW+3AwAACDVQejZvHlzwP3IyEjl5uYqNzf3itt07dr1qt+cHzJkiPbs2VNjTVZWlrKysq75WAEAgLn421sAAMAIhB4AAGAEQg8AADACoQcAABiB0AMAAIxA6AEAAEYg9AAAACMQegAAgBEIPQAAwAiEHgAAYARCDwAAMAKhBwAAGIHQAwAAjEDoAQAARiD0AAAAIxB6AACAEQg9AADACC1u9AGg8ej29Lp627cjzNKCQVLvWRtUXhlSZ/v9ZH56ne0LANC88U4PAAAwAqEHAAAYgdADAACMQOgBAABGIPQAAAAjEHoAAIARCD0AAMAIhB4AAGAEQg8AADACoQcAABiB0AMAAIxA6AEAAEYg9AAAACMQegAAgBEIPQAAwAiEHgAAYARCDwAAMAKhBwAAGIHQAwAAjEDoAQAARiD0AAAAIxB6AACAEQg9AADACIQeAABgBEIPAAAwQlCh58UXX1Tfvn3ldDrldDrlcrn0l7/8xV5//vx5ZWZmqn379mrVqpVGjhypkpKSgH0cOXJE6enpio6OVmxsrKZMmaILFy4E1GzevFkDBgyQw+FQ9+7dtWLFimrHkpubq27duikyMlIpKSnauXNnMKcCAAAME1To6dSpk+bPn6+ioiLt3r1b99xzj+6//37t379fkjR58mS9+eabWr16tbZs2aKjR4/qwQcftLevrKxUenq6KioqtG3bNr3yyitasWKFZsyYYdccPnxY6enpuvvuu1VcXKxJkybpscce04YNG+yaVatWKTs7WzNnztR7772nfv36ye126/jx49fbDwAA0EwFFXq+/e1v67777tMtt9yir33ta/rZz36mVq1aafv27Tp16pRefvllLVq0SPfcc4+Sk5O1fPlybdu2Tdu3b5ckbdy4UQcOHNCrr76q/v37a/jw4Zo7d65yc3NVUVEhScrLy1NiYqIWLlyoXr16KSsrS9/97ne1ePFi+zgWLVqkCRMmaNy4cUpKSlJeXp6io6O1bNmyOmwNAABoTlrUdsPKykqtXr1aZ8+elcvlUlFRkXw+n1JTU+2anj17qkuXLvJ4PBo8eLA8Ho/69OmjuLg4u8btdmvixInav3+/brvtNnk8noB9+GsmTZokSaqoqFBRUZFycnLs9aGhoUpNTZXH46nxmMvLy1VeXm7fLysrkyT5fD75fL7atuKq/PuuzzHqgiPMqr99h1oB/60rjb2nl2oq86A+0YOLaupDfT4OG5P6ek64Vo1hDvJ4qH0PatuzoEPP3r175XK5dP78ebVq1UpvvPGGkpKSVFxcrIiICMXExATUx8XFyev1SpK8Xm9A4PGv96+rqaasrExffPGFTp48qcrKysvWHDx4sMZjnzdvnmbPnl1t+caNGxUdHX31k79OBQUF9T7G9VgwqP7HmDuwqk73t379+jrdX0No7POgIdCDiy7Xh4Z4HDYmdf2ccK0a03MHj4fge3Du3LlajRN06OnRo4eKi4t16tQp/c///I8yMjK0ZcuWWg3e0HJycpSdnW3fLysrU+fOnZWWlian01lv4/p8PhUUFGjo0KEKDw+vt3GuV+9ZG65eVEuOUEtzB1bpJ7tDVV4VUmf73TfLXWf7qm9NZR7UJ3pwUU19qM/HYWNSX88J16oxPHfweKh9D/yf1AQr6NATERGh7t27S5KSk5O1a9cuLV26VKNGjVJFRYVKS0sD3u0pKSlRfHy8JCk+Pr7aVVb+q7surfnyFV8lJSVyOp2KiopSWFiYwsLCLlvj38eVOBwOORyOasvDw8MbZMI11Di1VV5Z/0885VUhdTpOY+7nlTT2edAQ6MFFl+tDQzwOG5O6fk64Vo1p/vF4CL4Hte3Xdf+enqqqKpWXlys5OVnh4eEqLCy01x06dEhHjhyRy+WSJLlcLu3duzfgKquCggI5nU4lJSXZNZfuw1/j30dERISSk5MDaqqqqlRYWGjXAAAAfFlQ7/Tk5ORo+PDh6tKli06fPq2VK1dq8+bN2rBhg9q0aaPx48crOztb7dq1k9Pp1JNPPimXy6XBgwdLktLS0pSUlKSHH35YCxYskNfr1fTp05WZmWm/A/PEE0/o+eef19SpU/Xoo49q06ZNev3117Vu3Tr7OLKzs5WRkaGBAwdq0KBBWrJkic6ePatx48bVYWsAAEBzElToOX78uB555BEdO3ZMbdq0Ud++fbVhwwYNHTpUkrR48WKFhoZq5MiRKi8vl9vt1gsvvGBvHxYWprVr12rixIlyuVxq2bKlMjIyNGfOHLsmMTFR69at0+TJk7V06VJ16tRJL730ktzuf3/+OmrUKH322WeaMWOGvF6v+vfvr/z8/GpfbgYAAPALKvS8/PLLNa6PjIxUbm6ucnNzr1jTtWvXq35rfsiQIdqzZ0+NNVlZWcrKyqqxBgAAwI+/vQUAAIxA6AEAAEYg9AAAACMQegAAgBEIPQAAwAiEHgAAYARCDwAAMAKhBwAAGIHQAwAAjEDoAQAARiD0AAAAIxB6AACAEQg9AADACIQeAABgBEIPAAAwAqEHAAAYgdADAACMQOgBAABGIPQAAAAjEHoAAIARCD0AAMAIhB4AAGAEQg8AADACoQcAABiB0AMAAIxA6AEAAEYg9AAAACMQegAAgBEIPQAAwAiEHgAAYARCDwAAMAKhBwAAGIHQAwAAjEDoAQAARiD0AAAAIxB6AACAEQg9AADACIQeAABgBEIPAAAwAqEHAAAYgdADAACMQOgBAABGIPQAAAAjBBV65s2bp69//etq3bq1YmNjNWLECB06dCig5vz588rMzFT79u3VqlUrjRw5UiUlJQE1R44cUXp6uqKjoxUbG6spU6bowoULATWbN2/WgAED5HA41L17d61YsaLa8eTm5qpbt26KjIxUSkqKdu7cGczpAAAAgwQVerZs2aLMzExt375dBQUF8vl8SktL09mzZ+2ayZMn680339Tq1au1ZcsWHT16VA8++KC9vrKyUunp6aqoqNC2bdv0yiuvaMWKFZoxY4Zdc/jwYaWnp+vuu+9WcXGxJk2apMcee0wbNmywa1atWqXs7GzNnDlT7733nvr16ye3263jx49fTz8AAEAz1SKY4vz8/ID7K1asUGxsrIqKinTXXXfp1KlTevnll7Vy5Urdc889kqTly5erV69e2r59uwYPHqyNGzfqwIEDeuuttxQXF6f+/ftr7ty5mjZtmmbNmqWIiAjl5eUpMTFRCxculCT16tVL7777rhYvXiy32y1JWrRokSZMmKBx48ZJkvLy8rRu3TotW7ZMTz/99HU3BgAANC/X9Z2eU6dOSZLatWsnSSoqKpLP51Nqaqpd07NnT3Xp0kUej0eS5PF41KdPH8XFxdk1brdbZWVl2r9/v11z6T78Nf59VFRUqKioKKAmNDRUqampdg0AAMClgnqn51JVVVWaNGmSbr/9dvXu3VuS5PV6FRERoZiYmIDauLg4eb1eu+bSwONf719XU01ZWZm++OILnTx5UpWVlZetOXjw4BWPuby8XOXl5fb9srIySZLP55PP57vWUw+af9/1OUZdcIRZ9bfvUCvgv3Wlsff0Uk1lHtQnenBRTX2oz8dhY1JfzwnXqjHMQR4Pte9BbXtW69CTmZmpffv26d13363tLhrcvHnzNHv27GrLN27cqOjo6Hofv6CgoN7HuB4LBtX/GHMHVtXp/tavX1+n+2sIjX0eNAR6cNHl+tAQj8PGpK6fE65VY3ru4PEQfA/OnTtXq3FqFXqysrK0du1abd26VZ06dbKXx8fHq6KiQqWlpQHv9pSUlCg+Pt6u+fJVVv6ruy6t+fIVXyUlJXI6nYqKilJYWJjCwsIuW+Pfx+Xk5OQoOzvbvl9WVqbOnTsrLS1NTqcziA4Ex+fzqaCgQEOHDlV4eHi9jXO9es/acPWiWnKEWpo7sEo/2R2q8qqQOtvvvlnuOttXfWsq86A+0YOLaupDfT4OG5P6ek64Vo3huYPHQ+174P+kJlhBhR7LsvTkk0/qjTfe0ObNm5WYmBiwPjk5WeHh4SosLNTIkSMlSYcOHdKRI0fkcrkkSS6XSz/72c90/PhxxcbGSrqY8JxOp5KSkuyaL6fwgoICex8RERFKTk5WYWGhRowYIenix22FhYXKysq64vE7HA45HI5qy8PDwxtkwjXUOLVVXln/TzzlVSF1Ok5j7ueVNPZ50BDowUWX60NDPA4bk7p+TrhWjWn+8XgIvge17VdQoSczM1MrV67Un/70J7Vu3dr+Dk6bNm0UFRWlNm3aaPz48crOzla7du3kdDr15JNPyuVyafDgwZKktLQ0JSUl6eGHH9aCBQvk9Xo1ffp0ZWZm2oHkiSee0PPPP6+pU6fq0Ucf1aZNm/T6669r3bp19rFkZ2crIyNDAwcO1KBBg7RkyRKdPXvWvpoLAADgUkGFnhdffFGSNGTIkIDly5cv1/e//31J0uLFixUaGqqRI0eqvLxcbrdbL7zwgl0bFhamtWvXauLEiXK5XGrZsqUyMjI0Z84cuyYxMVHr1q3T5MmTtXTpUnXq1EkvvfSSfbm6JI0aNUqfffaZZsyYIa/Xq/79+ys/P7/al5sBAACkWny8dTWRkZHKzc1Vbm7uFWu6du161S+RDRkyRHv27KmxJisrq8aPswAAAPz421sAAMAIhB4AAGAEQg8AADACoQcAABiB0AMAAIxA6AEAAEYg9AAAACMQegAAgBFq/VfWAQBoqro9ve7qRfXMEWZpwaCLf2T2Wv7+2Cfz0xvgqJo33ukBAABGIPQAAAAjEHoAAIARCD0AAMAIhB4AAGAEQg8AADACoQcAABiB0AMAAIxA6AEAAEYg9AAAACMQegAAgBEIPQAAwAiEHgAAYARCDwAAMAKhBwAAGIHQAwAAjEDoAQAARiD0AAAAIxB6AACAEQg9AADACIQeAABgBEIPAAAwAqEHAAAYgdADAACMQOgBAABGIPQAAAAjEHoAAIARCD0AAMAIhB4AAGAEQg8AADACoQcAABiB0AMAAIxA6AEAAEYg9AAAACMQegAAgBGCDj1bt27Vt7/9bSUkJCgkJERr1qwJWG9ZlmbMmKGOHTsqKipKqamp+vDDDwNqTpw4obFjx8rpdComJkbjx4/XmTNnAmref/993XnnnYqMjFTnzp21YMGCaseyevVq9ezZU5GRkerTp4/Wr18f7OkAAABDBB16zp49q379+ik3N/ey6xcsWKDnnntOeXl52rFjh1q2bCm3263z58/bNWPHjtX+/ftVUFCgtWvXauvWrXr88cft9WVlZUpLS1PXrl1VVFSkZ599VrNmzdJvfvMbu2bbtm0aM2aMxo8frz179mjEiBEaMWKE9u3bF+wpAQAAA7QIdoPhw4dr+PDhl11nWZaWLFmi6dOn6/7775ck/e53v1NcXJzWrFmj0aNH64MPPlB+fr527dqlgQMHSpJ+9atf6b777tMvf/lLJSQk6LXXXlNFRYWWLVumiIgI3XrrrSouLtaiRYvscLR06VINGzZMU6ZMkSTNnTtXBQUFev7555WXl1erZgAAgOYr6NBTk8OHD8vr9So1NdVe1qZNG6WkpMjj8Wj06NHyeDyKiYmxA48kpaamKjQ0VDt27NADDzwgj8eju+66SxEREXaN2+3WL37xC508eVJt27aVx+NRdnZ2wPhut7vax22XKi8vV3l5uX2/rKxMkuTz+eTz+a739K/Iv+/6HKMuOMKs+tt3qBXw37rS2Ht6qaYyD+oTPbiopj7U5+OwMamv54SmJNgeNMfHTW2fE2rbizoNPV6vV5IUFxcXsDwuLs5e5/V6FRsbG3gQLVqoXbt2ATWJiYnV9uFf17ZtW3m93hrHuZx58+Zp9uzZ1ZZv3LhR0dHR13KK16WgoKDex7geCwbV/xhzB1bV6f6a4ve4Gvs8aAj04KLL9aEhHoeNSV0/JzRF19qDpvh8d62CfU44d+5crcap09DT2OXk5AS8O1RWVqbOnTsrLS1NTqez3sb1+XwqKCjQ0KFDFR4eXm/jXK/eszbU274doZbmDqzST3aHqrwqpN7Gacz8PWjs86A+NZXHQn2rqQ/1+ThsTHhOCL4H+2a5G+CoGlZtnxP8n9QEq05DT3x8vCSppKREHTt2tJeXlJSof//+ds3x48cDtrtw4YJOnDhhbx8fH6+SkpKAGv/9q9X411+Ow+GQw+Gotjw8PLxBnoAbapzaKq+s/yee8qqQBhmnMWvs86AhNFQPuj29rt7HqA1HmKUFg6TbfrbpMo8Hsx4fPCdcew+a8/NGsM8Jte1Fnf6ensTERMXHx6uwsNBeVlZWph07dsjlckmSXC6XSktLVVRUZNds2rRJVVVVSklJsWu2bt0a8JldQUGBevToobZt29o1l47jr/GPAwAAcKmgQ8+ZM2dUXFys4uJiSRe/vFxcXKwjR44oJCREkyZN0k9/+lP9+c9/1t69e/XII48oISFBI0aMkCT16tVLw4YN04QJE7Rz50799a9/VVZWlkaPHq2EhARJ0ve+9z1FRERo/Pjx2r9/v1atWqWlS5cGfDT11FNPKT8/XwsXLtTBgwc1a9Ys7d69W1lZWdffFQAA0OwE/fHW7t27dffdd9v3/UEkIyNDK1as0NSpU3X27Fk9/vjjKi0t1R133KH8/HxFRkba27z22mvKysrSvffeq9DQUI0cOVLPPfecvb5NmzbauHGjMjMzlZycrA4dOmjGjBkBv8vnG9/4hlauXKnp06frmWee0S233KI1a9aod+/etWoEAABo3oIOPUOGDJFlXfnyupCQEM2ZM0dz5sy5Yk27du20cuXKGsfp27ev3nnnnRprHnroIT300EM1HzAAAID421sAAMAQRl2y3pAuvWrEf6VG71kbjL9KAQCAG4V3egAAgBEIPQAAwAiEHgAAYAS+0wMAQBPQWH/DeE0+mZ9+ow8hAO/0AAAAIxB6AACAEQg9AADACIQeAABgBEIPAAAwAqEHAAAYgdADAACMQOgBAABGIPQAAAAjEHoAAIARCD0AAMAIhB4AAGAEQg8AADACoQcAABiB0AMAAIxA6AEAAEYg9AAAACMQegAAgBEIPQAAwAiEHgAAYARCDwAAMAKhBwAAGIHQAwAAjEDoAQAARiD0AAAAIxB6AACAEQg9AADACIQeAABgBEIPAAAwAqEHAAAYgdADAACM0OJGHwCApqHb0+uuex+OMEsLBkm9Z21QeWVIHRwVAFw73ukBAABGIPQAAAAjEHoAAIAR+E4P0MD4PgsA3Bi80wMAAIzQ5ENPbm6uunXrpsjISKWkpGjnzp03+pAAAEAj1KRDz6pVq5Sdna2ZM2fqvffeU79+/eR2u3X8+PEbfWgAAKCRadKhZ9GiRZowYYLGjRunpKQk5eXlKTo6WsuWLbvRhwYAABqZJvtF5oqKChUVFSknJ8deFhoaqtTUVHk8nstuU15ervLycvv+qVOnJEknTpyQz+er0+NrceHsv3+usnTuXJVa+EJVWWXmF1jpAT2Q6IEffaAHkhk9+Pzzz2tc7/P5dO7cOX3++ecKDw+/5v2ePn1akmRZVnAHZDVR//rXvyxJ1rZt2wKWT5kyxRo0aNBlt5k5c6YliRs3bty4cePWDG6ffvppUNmhyb7TUxs5OTnKzs6271dVVenEiRNq3769QkLqL2WXlZWpc+fO+vTTT+V0OuttnMaMHtADiR740Qd6INEDqfY9sCxLp0+fVkJCQlDjNdnQ06FDB4WFhamkpCRgeUlJieLj4y+7jcPhkMPhCFgWExNTX4dYjdPpNHZi+9EDeiDRAz/6QA8keiDVrgdt2rQJepwm+0XmiIgIJScnq7Cw0F5WVVWlwsJCuVyuG3hkAACgMWqy7/RIUnZ2tjIyMjRw4EANGjRIS5Ys0dmzZzVu3LgbfWgAAKCRadKhZ9SoUfrss880Y8YMeb1e9e/fX/n5+YqLi7vRhxbA4XBo5syZ1T5aMwk9oAcSPfCjD/RAogdSw/cgxLKCvd4LAACg6Wmy3+kBAAAIBqEHAAAYgdADAACMQOgBAABGIPTU0rx58/T1r39drVu3VmxsrEaMGKFDhw4F1AwZMkQhISEBtyeeeCKg5siRI0pPT1d0dLRiY2M1ZcoUXbhwoSFPpdZmzZpV7fx69uxprz9//rwyMzPVvn17tWrVSiNHjqz2yySb8vlLUrdu3ar1ICQkRJmZmZKa5xzYunWrvv3tbyshIUEhISFas2ZNwHrLsjRjxgx17NhRUVFRSk1N1YcffhhQc+LECY0dO1ZOp1MxMTEaP368zpw5E1Dz/vvv684771RkZKQ6d+6sBQsW1PepBaWmPvh8Pk2bNk19+vRRy5YtlZCQoEceeURHjx4N2Mfl5s/8+fMDahpzH642F77//e9XO79hw4YF1DT1uXC1Hlzu+SEkJETPPvusXdPU58G1vB7W1evB5s2bNWDAADkcDnXv3l0rVqwI7mBr9YevYLndbmv58uXWvn37rOLiYuu+++6zunTpYp05c8au+eY3v2lNmDDBOnbsmH07deqUvf7ChQtW7969rdTUVGvPnj3W+vXrrQ4dOlg5OTk34pSCNnPmTOvWW28NOL/PPvvMXv/EE09YnTt3tgoLC63du3dbgwcPtr7xjW/Y65v6+VuWZR0/fjzg/AsKCixJ1ttvv21ZVvOcA+vXr7f++7//2/rjH/9oSbLeeOONgPXz58+32rRpY61Zs8b629/+Zn3nO9+xEhMTrS+++MKuGTZsmNWvXz9r+/bt1jvvvGN1797dGjNmjL3+1KlTVlxcnDV27Fhr37591u9//3srKirK+vWvf91Qp3lVNfWhtLTUSk1NtVatWmUdPHjQ8ng81qBBg6zk5OSAfXTt2tWaM2dOwPy49DmksffhanMhIyPDGjZsWMD5nThxIqCmqc+Fq/Xg0nM/duyYtWzZMiskJMT6+OOP7ZqmPg+u5fWwLl4P/v73v1vR0dFWdna2deDAAetXv/qVFRYWZuXn51/zsRJ66sjx48ctSdaWLVvsZd/85jetp5566orbrF+/3goNDbW8Xq+97MUXX7ScTqdVXl5en4dbJ2bOnGn169fvsutKS0ut8PBwa/Xq1fayDz74wJJkeTwey7Ka/vlfzlNPPWV99atftaqqqizLav5z4MtP8lVVVVZ8fLz17LPP2stKS0sth8Nh/f73v7csy7IOHDhgSbJ27dpl1/zlL3+xQkJCrH/961+WZVnWCy+8YLVt2zagB9OmTbN69OhRz2dUO5d7sfuynTt3WpKsf/zjH/ayrl27WosXL77iNk2pD1cKPffff/8Vt2luc+Fa5sH9999v3XPPPQHLmtM8sKzqr4d19XowdepU69Zbbw0Ya9SoUZbb7b7mY+PjrTpy6tQpSVK7du0Clr/22mvq0KGDevfurZycHJ07d85e5/F41KdPn4Bfpuh2u1VWVqb9+/c3zIFfpw8//FAJCQm6+eabNXbsWB05ckSSVFRUJJ/Pp9TUVLu2Z8+e6tKlizwej6Tmcf6Xqqio0KuvvqpHH3004A/YNvc5cKnDhw/L6/UG/Lu3adNGKSkpAf/uMTExGjhwoF2Tmpqq0NBQ7dixw6656667FBERYde43W4dOnRIJ0+ebKCzqVunTp1SSEhItb/3N3/+fLVv31633Xabnn322YC385tDHzZv3qzY2Fj16NFDEydO1Oeff26vM20ulJSUaN26dRo/fny1dc1pHnz59bCuXg88Hk/APvw1/n1ciyb9G5kbi6qqKk2aNEm33367evfubS//3ve+p65duyohIUHvv/++pk2bpkOHDumPf/yjJMnr9Vb77dH++16vt+FOoJZSUlK0YsUK9ejRQ8eOHdPs2bN15513at++ffJ6vYqIiKj2BB8XF2efW1M//y9bs2aNSktL9f3vf99e1tznwJf5j/ly53Tpv3tsbGzA+hYtWqhdu3YBNYmJidX24V/Xtm3bejn++nL+/HlNmzZNY8aMCfijij/84Q81YMAAtWvXTtu2bVNOTo6OHTumRYsWSWr6fRg2bJgefPBBJSYm6uOPP9Yzzzyj4cOHy+PxKCwszLi58Morr6h169Z68MEHA5Y3p3lwudfDuno9uFJNWVmZvvjiC0VFRV31+Ag9dSAzM1P79u3Tu+++G7D88ccft3/u06ePOnbsqHvvvVcff/yxvvrVrzb0Yda54cOH2z/37dtXKSkp6tq1q15//fVrmnzNzcsvv6zhw4crISHBXtbc5wCuzufz6T/+4z9kWZZefPHFgHXZ2dn2z3379lVERIT+67/+S/PmzWsWf5pg9OjR9s99+vRR37599dWvflWbN2/WvffeewOP7MZYtmyZxo4dq8jIyIDlzWkeXOn1sLHg463rlJWVpbVr1+rtt99Wp06daqxNSUmRJH300UeSpPj4+GrfXvffj4+Pr4ejrV8xMTH62te+po8++kjx8fGqqKhQaWlpQE1JSYl9bs3p/P/xj3/orbfe0mOPPVZjXXOfA/5jvtw5Xfrvfvz48YD1Fy5c0IkTJ5rd3PAHnn/84x8qKCgIeJfnclJSUnThwgV98sknkppPH/xuvvlmdejQIWD+mzIX3nnnHR06dOiqzxFS050HV3o9rKvXgyvVOJ3Oa/4fbUJPLVmWpaysLL3xxhvatGlTtbceL6e4uFiS1LFjR0mSy+XS3r17Ax70/ifGpKSkejnu+nTmzBl9/PHH6tixo5KTkxUeHq7CwkJ7/aFDh3TkyBG5XC5Jzev8ly9frtjYWKWnp9dY19znQGJiouLj4wP+3cvKyrRjx46Af/fS0lIVFRXZNZs2bVJVVZUdCl0ul7Zu3Sqfz2fXFBQUqEePHo3qrfya+APPhx9+qLfeekvt27e/6jbFxcUKDQ21P/JpDn241D//+U99/vnnAfPfhLkgXXwnODk5Wf369btqbVObB1d7Payr1wOXyxWwD3+Nfx/XerCohYkTJ1pt2rSxNm/eHHCZ4blz5yzLsqyPPvrImjNnjrV7927r8OHD1p/+9Cfr5ptvtu666y57H/5L9NLS0qzi4mIrPz/fuummmxr15cqX+tGPfmRt3rzZOnz4sPXXv/7VSk1NtTp06GAdP37csqyLlyh26dLF2rRpk7V7927L5XJZLpfL3r6pn79fZWWl1aVLF2vatGkBy5vrHDh9+rS1Z88ea8+ePZYka9GiRdaePXvsq5Lmz59vxcTEWH/605+s999/37r//vsve8n6bbfdZu3YscN69913rVtuuSXgMuXS0lIrLi7Oevjhh619+/ZZf/jDH6zo6OhGc4muZdXch4qKCus73/mO1alTJ6u4uDjgOcJ/Jcq2bdusxYsXW8XFxdbHH39svfrqq9ZNN91kPfLII/YYjb0PNfXg9OnT1o9//GPL4/FYhw8ftt566y1rwIAB1i233GKdP3/e3kdTnwtXezxY1sVLzqOjo60XX3yx2vbNYR5c7fXQsurm9cB/yfqUKVOsDz74wMrNzeWS9YYi6bK35cuXW5ZlWUeOHLHuuusuq127dpbD4bC6d+9uTZkyJeB3tFiWZX3yySfW8OHDraioKKtDhw7Wj370I8vn892AMwreqFGjrI4dO1oRERHWV77yFWvUqFHWRx99ZK//4osvrB/84AdW27ZtrejoaOuBBx6wjh07FrCPpnz+fhs2bLAkWYcOHQpY3lznwNtvv33ZuZ+RkWFZ1sXL1n/yk59YcXFxlsPhsO69995qvfn888+tMWPGWK1atbKcTqc1btw46/Tp0wE1f/vb36w77rjDcjgc1le+8hVr/vz5DXWK16SmPhw+fPiKzxH+3+FUVFRkpaSkWG3atLEiIyOtXr16WT//+c8DAoFlNe4+1NSDc+fOWWlpadZNN91khYeHW127drUmTJgQcEmyZTX9uXC1x4NlWdavf/1rKyoqyiotLa22fXOYB1d7PbSsuns9ePvtt63+/ftbERER1s033xwwxrUI+f8HDAAA0KzxnR4AAGAEQg8AADACoQcAABiB0AMAAIxA6AEAAEYg9AAAACMQegAAgBEIPQAAwAiEHgAAYARCDwAAMAKhBwAAGIHQAwAAjPD/ALEGC9rv38HxAAAAAElFTkSuQmCC",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "data['High'].hist()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "id": "1a9c8c2c-25be-42de-8125-4e321f0b8588",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Axes: >"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1200x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# data[['Open','Close']].plot(marker='o', figsize=(10, 6), title=\"Open and Close Prices\")\n",
    "fig, ax = plt.subplots(figsize=(12, 6))\n",
    "data['Open'].plot(ax=ax, linestyle='-', linewidth=2, color='blue', alpha=0.7, label='Open')\n",
    "data['Close'].plot(ax=ax, linestyle='--', linewidth=2, color='orange', alpha=0.7, label='Close')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "id": "8ab15e6e-a163-4ed2-9baf-9c70a9d419f2",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Axes: >"
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1200x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# data[['High','Low']].plot(marker='o', figsize=(10, 6), title=\"High and Low Prices\")\n",
    "fig, ax = plt.subplots(figsize=(12, 6))\n",
    "data['High'].plot(ax=ax, linestyle='-', linewidth=2, color='blue', alpha=0.7, label='High')\n",
    "data['Low'].plot(ax=ax, linestyle='--', linewidth=2, color='orange', alpha=0.7, label='Low')"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "b5a33d09-264b-43ab-b48d-65cef730947a",
   "metadata": {},
   "source": [
    "**Split the dataset into X and y.**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "id": "18a25d2b-a55b-48a6-9ee9-bc6b3725f3b9",
   "metadata": {},
   "outputs": [],
   "source": [
    "X=data[['High','Low','Open']].values  #Independent variables\n",
    "y=data['Close'].values   #Dependent variables"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "02cb80e8-238e-424f-86f6-f4fd9dfe3ae0",
   "metadata": {},
   "source": [
    "**Splitting the model into testing and training.**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "id": "128bb120-b4fa-495e-9c98-ca7b880c4556",
   "metadata": {},
   "outputs": [],
   "source": [
    "X_train,X_test,y_train,y_test=train_test_split(X,y,test_size=0.3,random_state=0)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "id": "8badc1c0-a4e4-48a9-be2a-96a1b7060d74",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "((137797, 3), (59057, 3), (137797,), (59057,))"
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "X_train.shape, X_test.shape, y_train.shape, y_test.shape"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "9ecb8559-3df4-4f58-9183-7f4cae6b564f",
   "metadata": {},
   "source": [
    "**Training the model using Linear Regression**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "id": "06a9314d-2d22-4ee0-9af2-965b2be53c18",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<style>#sk-container-id-1 {color: black;}#sk-container-id-1 pre{padding: 0;}#sk-container-id-1 div.sk-toggleable {background-color: white;}#sk-container-id-1 label.sk-toggleable__label {cursor: pointer;display: block;width: 100%;margin-bottom: 0;padding: 0.3em;box-sizing: border-box;text-align: center;}#sk-container-id-1 label.sk-toggleable__label-arrow:before {content: \"▸\";float: left;margin-right: 0.25em;color: #696969;}#sk-container-id-1 label.sk-toggleable__label-arrow:hover:before {color: black;}#sk-container-id-1 div.sk-estimator:hover label.sk-toggleable__label-arrow:before {color: black;}#sk-container-id-1 div.sk-toggleable__content {max-height: 0;max-width: 0;overflow: hidden;text-align: left;background-color: #f0f8ff;}#sk-container-id-1 div.sk-toggleable__content pre {margin: 0.2em;color: black;border-radius: 0.25em;background-color: #f0f8ff;}#sk-container-id-1 input.sk-toggleable__control:checked~div.sk-toggleable__content {max-height: 200px;max-width: 100%;overflow: auto;}#sk-container-id-1 input.sk-toggleable__control:checked~label.sk-toggleable__label-arrow:before {content: \"▾\";}#sk-container-id-1 div.sk-estimator input.sk-toggleable__control:checked~label.sk-toggleable__label {background-color: #d4ebff;}#sk-container-id-1 div.sk-label input.sk-toggleable__control:checked~label.sk-toggleable__label {background-color: #d4ebff;}#sk-container-id-1 input.sk-hidden--visually {border: 0;clip: rect(1px 1px 1px 1px);clip: rect(1px, 1px, 1px, 1px);height: 1px;margin: -1px;overflow: hidden;padding: 0;position: absolute;width: 1px;}#sk-container-id-1 div.sk-estimator {font-family: monospace;background-color: #f0f8ff;border: 1px dotted black;border-radius: 0.25em;box-sizing: border-box;margin-bottom: 0.5em;}#sk-container-id-1 div.sk-estimator:hover {background-color: #d4ebff;}#sk-container-id-1 div.sk-parallel-item::after {content: \"\";width: 100%;border-bottom: 1px solid gray;flex-grow: 1;}#sk-container-id-1 div.sk-label:hover label.sk-toggleable__label {background-color: #d4ebff;}#sk-container-id-1 div.sk-serial::before {content: \"\";position: absolute;border-left: 1px solid gray;box-sizing: border-box;top: 0;bottom: 0;left: 50%;z-index: 0;}#sk-container-id-1 div.sk-serial {display: flex;flex-direction: column;align-items: center;background-color: white;padding-right: 0.2em;padding-left: 0.2em;position: relative;}#sk-container-id-1 div.sk-item {position: relative;z-index: 1;}#sk-container-id-1 div.sk-parallel {display: flex;align-items: stretch;justify-content: center;background-color: white;position: relative;}#sk-container-id-1 div.sk-item::before, #sk-container-id-1 div.sk-parallel-item::before {content: \"\";position: absolute;border-left: 1px solid gray;box-sizing: border-box;top: 0;bottom: 0;left: 50%;z-index: -1;}#sk-container-id-1 div.sk-parallel-item {display: flex;flex-direction: column;z-index: 1;position: relative;background-color: white;}#sk-container-id-1 div.sk-parallel-item:first-child::after {align-self: flex-end;width: 50%;}#sk-container-id-1 div.sk-parallel-item:last-child::after {align-self: flex-start;width: 50%;}#sk-container-id-1 div.sk-parallel-item:only-child::after {width: 0;}#sk-container-id-1 div.sk-dashed-wrapped {border: 1px dashed gray;margin: 0 0.4em 0.5em 0.4em;box-sizing: border-box;padding-bottom: 0.4em;background-color: white;}#sk-container-id-1 div.sk-label label {font-family: monospace;font-weight: bold;display: inline-block;line-height: 1.2em;}#sk-container-id-1 div.sk-label-container {text-align: center;}#sk-container-id-1 div.sk-container {/* jupyter's `normalize.less` sets `[hidden] { display: none; }` but bootstrap.min.css set `[hidden] { display: none !important; }` so we also need the `!important` here to be able to override the default hidden behavior on the sphinx rendered scikit-learn.org. See: https://github.com/scikit-learn/scikit-learn/issues/21755 */display: inline-block !important;position: relative;}#sk-container-id-1 div.sk-text-repr-fallback {display: none;}</style><div id=\"sk-container-id-1\" class=\"sk-top-container\"><div class=\"sk-text-repr-fallback\"><pre>LinearRegression()</pre><b>In a Jupyter environment, please rerun this cell to show the HTML representation or trust the notebook. <br />On GitHub, the HTML representation is unable to render, please try loading this page with nbviewer.org.</b></div><div class=\"sk-container\" hidden><div class=\"sk-item\"><div class=\"sk-estimator sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-1\" type=\"checkbox\" checked><label for=\"sk-estimator-id-1\" class=\"sk-toggleable__label sk-toggleable__label-arrow\">LinearRegression</label><div class=\"sk-toggleable__content\"><pre>LinearRegression()</pre></div></div></div></div></div>"
      ],
      "text/plain": [
       "LinearRegression()"
      ]
     },
     "execution_count": 24,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "lr.fit(X_train,y_train)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "id": "00b4ad18-555d-4e04-8c8a-6c93ca8e1668",
   "metadata": {},
   "outputs": [],
   "source": [
    "y_pred=lr.predict(X_test)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "id": "ce7b89a7-28ca-40ce-a5b1-d5335d0dff8b",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([ 481.28467646, 1519.81494305, 1336.66682538, ..., 1378.51824344,\n",
       "       1503.86545866, 1297.2613789 ])"
      ]
     },
     "execution_count": 26,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "y_pred"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "id": "41648887-cb3a-499b-89d9-84b6d422ed6f",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Model coefficients:  [ 0.74668629  0.73027289 -0.4769683 ]\n",
      "Model intercept:  0.004870247216103962\n"
     ]
    }
   ],
   "source": [
    "print(\"Model coefficients: \",lr.coef_)\n",
    "print(\"Model intercept: \",lr.intercept_)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "af83f041-b4c8-4823-b00c-3ebddcd1b551",
   "metadata": {},
   "source": [
    "**Prediction table of Actual and Predicted values**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "id": "4eef1129-f183-4749-97a8-c887a1700806",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "       Actual Price  Predicted Price\n",
      "0            481.30       481.284676\n",
      "1           1519.97      1519.814943\n",
      "2           1336.90      1336.666825\n",
      "3            505.05       505.027233\n",
      "4           1567.00      1566.573608\n",
      "...             ...              ...\n",
      "59052       1516.30      1516.149068\n",
      "59053       1450.98      1450.772768\n",
      "59054       1378.50      1378.518243\n",
      "59055       1503.65      1503.865459\n",
      "59056       1297.00      1297.261379\n",
      "\n",
      "[59057 rows x 2 columns]\n"
     ]
    }
   ],
   "source": [
    "dframe=pd.DataFrame(y_test,y_pred)\n",
    "dfr=pd.DataFrame({\"Actual Price\":y_test,\"Predicted Price\":y_pred})\n",
    "print(dfr)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "47fcdee6-3efa-4daf-89e2-10a1d1d518c0",
   "metadata": {},
   "source": [
    "**Normality of Residual**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "id": "1bbeaad5-b014-4b08-ae66-1c4736cb1ed7",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<seaborn.axisgrid.FacetGrid at 0x153c9b550>"
      ]
     },
     "execution_count": 32,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 500x500 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "residual=y_test-y_pred\n",
    "sns.displot(residual)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "6becb6b7-9edb-49e8-a9ab-e36de41bcec3",
   "metadata": {},
   "source": [
    "**Computing the accuracy of Linear Regression model**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 77,
   "id": "ddfe65bb-f9ab-43b5-a951-18a5c011064a",
   "metadata": {},
   "outputs": [],
   "source": [
    "R2_score=round(r2_score(y_test,y_pred),6)   #R2 score to get the accuracy of your model on a percentage scale\n",
    "MAE=round(mean_absolute_error(y_test,y_pred),3)\n",
    "MSE=round(mean_squared_error(y_test,y_pred),3)\n",
    "RMSE=round(np.sqrt(mean_squared_error(y_test,y_pred)),3)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 78,
   "id": "16498fa5-4045-412a-bf75-f45ecabee0bc",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Mean Absolute Error:  0.428\n",
      "Mean Squared Error:  0.435\n",
      "Root Mean Squared Error:  0.659\n",
      "R2 Score:  99.99980000000001 %\n"
     ]
    }
   ],
   "source": [
    "print(\"Mean Absolute Error: \",MAE)\n",
    "print(\"Mean Squared Error: \",MSE)\n",
    "print(\"Root Mean Squared Error: \",RMSE)\n",
    "print(\"R2 Score: \",R2_score*100,\"%\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "5ac1966e-4d6a-496a-85ad-0113ba2dab46",
   "metadata": {},
   "source": [
    "**Training the model using Decision Tree**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "id": "7d00db6e-7bcb-48de-8a8e-d17ff313f796",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<style>#sk-container-id-2 {color: black;}#sk-container-id-2 pre{padding: 0;}#sk-container-id-2 div.sk-toggleable {background-color: white;}#sk-container-id-2 label.sk-toggleable__label {cursor: pointer;display: block;width: 100%;margin-bottom: 0;padding: 0.3em;box-sizing: border-box;text-align: center;}#sk-container-id-2 label.sk-toggleable__label-arrow:before {content: \"▸\";float: left;margin-right: 0.25em;color: #696969;}#sk-container-id-2 label.sk-toggleable__label-arrow:hover:before {color: black;}#sk-container-id-2 div.sk-estimator:hover label.sk-toggleable__label-arrow:before {color: black;}#sk-container-id-2 div.sk-toggleable__content {max-height: 0;max-width: 0;overflow: hidden;text-align: left;background-color: #f0f8ff;}#sk-container-id-2 div.sk-toggleable__content pre {margin: 0.2em;color: black;border-radius: 0.25em;background-color: #f0f8ff;}#sk-container-id-2 input.sk-toggleable__control:checked~div.sk-toggleable__content {max-height: 200px;max-width: 100%;overflow: auto;}#sk-container-id-2 input.sk-toggleable__control:checked~label.sk-toggleable__label-arrow:before {content: \"▾\";}#sk-container-id-2 div.sk-estimator input.sk-toggleable__control:checked~label.sk-toggleable__label {background-color: #d4ebff;}#sk-container-id-2 div.sk-label input.sk-toggleable__control:checked~label.sk-toggleable__label {background-color: #d4ebff;}#sk-container-id-2 input.sk-hidden--visually {border: 0;clip: rect(1px 1px 1px 1px);clip: rect(1px, 1px, 1px, 1px);height: 1px;margin: -1px;overflow: hidden;padding: 0;position: absolute;width: 1px;}#sk-container-id-2 div.sk-estimator {font-family: monospace;background-color: #f0f8ff;border: 1px dotted black;border-radius: 0.25em;box-sizing: border-box;margin-bottom: 0.5em;}#sk-container-id-2 div.sk-estimator:hover {background-color: #d4ebff;}#sk-container-id-2 div.sk-parallel-item::after {content: \"\";width: 100%;border-bottom: 1px solid gray;flex-grow: 1;}#sk-container-id-2 div.sk-label:hover label.sk-toggleable__label {background-color: #d4ebff;}#sk-container-id-2 div.sk-serial::before {content: \"\";position: absolute;border-left: 1px solid gray;box-sizing: border-box;top: 0;bottom: 0;left: 50%;z-index: 0;}#sk-container-id-2 div.sk-serial {display: flex;flex-direction: column;align-items: center;background-color: white;padding-right: 0.2em;padding-left: 0.2em;position: relative;}#sk-container-id-2 div.sk-item {position: relative;z-index: 1;}#sk-container-id-2 div.sk-parallel {display: flex;align-items: stretch;justify-content: center;background-color: white;position: relative;}#sk-container-id-2 div.sk-item::before, #sk-container-id-2 div.sk-parallel-item::before {content: \"\";position: absolute;border-left: 1px solid gray;box-sizing: border-box;top: 0;bottom: 0;left: 50%;z-index: -1;}#sk-container-id-2 div.sk-parallel-item {display: flex;flex-direction: column;z-index: 1;position: relative;background-color: white;}#sk-container-id-2 div.sk-parallel-item:first-child::after {align-self: flex-end;width: 50%;}#sk-container-id-2 div.sk-parallel-item:last-child::after {align-self: flex-start;width: 50%;}#sk-container-id-2 div.sk-parallel-item:only-child::after {width: 0;}#sk-container-id-2 div.sk-dashed-wrapped {border: 1px dashed gray;margin: 0 0.4em 0.5em 0.4em;box-sizing: border-box;padding-bottom: 0.4em;background-color: white;}#sk-container-id-2 div.sk-label label {font-family: monospace;font-weight: bold;display: inline-block;line-height: 1.2em;}#sk-container-id-2 div.sk-label-container {text-align: center;}#sk-container-id-2 div.sk-container {/* jupyter's `normalize.less` sets `[hidden] { display: none; }` but bootstrap.min.css set `[hidden] { display: none !important; }` so we also need the `!important` here to be able to override the default hidden behavior on the sphinx rendered scikit-learn.org. See: https://github.com/scikit-learn/scikit-learn/issues/21755 */display: inline-block !important;position: relative;}#sk-container-id-2 div.sk-text-repr-fallback {display: none;}</style><div id=\"sk-container-id-2\" class=\"sk-top-container\"><div class=\"sk-text-repr-fallback\"><pre>DecisionTreeRegressor()</pre><b>In a Jupyter environment, please rerun this cell to show the HTML representation or trust the notebook. <br />On GitHub, the HTML representation is unable to render, please try loading this page with nbviewer.org.</b></div><div class=\"sk-container\" hidden><div class=\"sk-item\"><div class=\"sk-estimator sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-2\" type=\"checkbox\" checked><label for=\"sk-estimator-id-2\" class=\"sk-toggleable__label sk-toggleable__label-arrow\">DecisionTreeRegressor</label><div class=\"sk-toggleable__content\"><pre>DecisionTreeRegressor()</pre></div></div></div></div></div>"
      ],
      "text/plain": [
       "DecisionTreeRegressor()"
      ]
     },
     "execution_count": 47,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "decision_tree.fit(X_train,y_train)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 48,
   "id": "cc1ac799-6d91-4d32-9bf3-50ae9c2b588e",
   "metadata": {},
   "outputs": [],
   "source": [
    "y_pred2=decision_tree.predict(X_test)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 49,
   "id": "64989419-c1f6-499d-b155-e054053207e6",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([ 481.75, 1519.82, 1336.  , ..., 1378.  , 1504.05, 1299.3 ])"
      ]
     },
     "execution_count": 49,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "y_pred2"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "931a5b29-c869-4dee-b3b7-ad6ec5d75cc6",
   "metadata": {},
   "source": [
    "**Prediction table of Actual and Predicted values (Decision Tree)**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 52,
   "id": "55e9af66-0b75-4512-9172-cdc43998ec89",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "       Actual Price  Predicted Price\n",
      "0            481.30           481.75\n",
      "1           1519.97          1519.82\n",
      "2           1336.90          1336.00\n",
      "3            505.05           505.10\n",
      "4           1567.00          1566.87\n",
      "...             ...              ...\n",
      "59052       1516.30          1516.00\n",
      "59053       1450.98          1451.23\n",
      "59054       1378.50          1378.00\n",
      "59055       1503.65          1504.05\n",
      "59056       1297.00          1299.30\n",
      "\n",
      "[59057 rows x 2 columns]\n"
     ]
    }
   ],
   "source": [
    "dframe2=pd.DataFrame(y_test,y_pred2)\n",
    "dfr2=pd.DataFrame({\"Actual Price\":y_test,\"Predicted Price\":y_pred2})\n",
    "print(dfr2)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "b1d00e3a-4304-4e58-9512-67f468d96a23",
   "metadata": {},
   "source": [
    "**Normality of Residual**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 53,
   "id": "7b221b8b-7852-4c50-9fdc-fe6b15ad5a22",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<seaborn.axisgrid.FacetGrid at 0x15781f890>"
      ]
     },
     "execution_count": 53,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 500x500 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "residual2=y_test-y_pred2\n",
    "sns.displot(residual2)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "64ddf3a5-9c5c-4e2a-a361-488cc32c32b5",
   "metadata": {},
   "source": [
    "**Computing the accuracy of Decision Tree model**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 79,
   "id": "3c957500-78eb-45a1-9b6d-c0a057250d6b",
   "metadata": {},
   "outputs": [],
   "source": [
    "R2_score2=round(r2_score(y_test,y_pred2),6)  #R2 score to get the accuracy of your model on a percentage scale\n",
    "MAE2=round(mean_absolute_error(y_test,y_pred2),3)\n",
    "MSE2=round(mean_squared_error(y_test,y_pred2),3)\n",
    "RMSE2=round(np.sqrt(mean_squared_error(y_test,y_pred2)),3)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 80,
   "id": "651fa001-8b38-4c02-8686-fbc24009a982",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Mean Absolute Error:  0.599\n",
      "Mean Squared Error:  1.034\n",
      "Root Mean Squared Error:  1.017\n",
      "R2 Score:  99.9995 %\n"
     ]
    }
   ],
   "source": [
    "print(\"Mean Absolute Error: \",MAE2)\n",
    "print(\"Mean Squared Error: \",MSE2)\n",
    "print(\"Root Mean Squared Error: \",RMSE2)\n",
    "print(\"R2 Score: \",R2_score2*100,\"%\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "8bf2b292-51fb-4d8c-9183-c84a5339df07",
   "metadata": {},
   "source": [
    "**Training the model using Random Forest**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 56,
   "id": "a10bea55-8475-4bf2-8c3e-3a2f1138fe9b",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<style>#sk-container-id-3 {color: black;}#sk-container-id-3 pre{padding: 0;}#sk-container-id-3 div.sk-toggleable {background-color: white;}#sk-container-id-3 label.sk-toggleable__label {cursor: pointer;display: block;width: 100%;margin-bottom: 0;padding: 0.3em;box-sizing: border-box;text-align: center;}#sk-container-id-3 label.sk-toggleable__label-arrow:before {content: \"▸\";float: left;margin-right: 0.25em;color: #696969;}#sk-container-id-3 label.sk-toggleable__label-arrow:hover:before {color: black;}#sk-container-id-3 div.sk-estimator:hover label.sk-toggleable__label-arrow:before {color: black;}#sk-container-id-3 div.sk-toggleable__content {max-height: 0;max-width: 0;overflow: hidden;text-align: left;background-color: #f0f8ff;}#sk-container-id-3 div.sk-toggleable__content pre {margin: 0.2em;color: black;border-radius: 0.25em;background-color: #f0f8ff;}#sk-container-id-3 input.sk-toggleable__control:checked~div.sk-toggleable__content {max-height: 200px;max-width: 100%;overflow: auto;}#sk-container-id-3 input.sk-toggleable__control:checked~label.sk-toggleable__label-arrow:before {content: \"▾\";}#sk-container-id-3 div.sk-estimator input.sk-toggleable__control:checked~label.sk-toggleable__label {background-color: #d4ebff;}#sk-container-id-3 div.sk-label input.sk-toggleable__control:checked~label.sk-toggleable__label {background-color: #d4ebff;}#sk-container-id-3 input.sk-hidden--visually {border: 0;clip: rect(1px 1px 1px 1px);clip: rect(1px, 1px, 1px, 1px);height: 1px;margin: -1px;overflow: hidden;padding: 0;position: absolute;width: 1px;}#sk-container-id-3 div.sk-estimator {font-family: monospace;background-color: #f0f8ff;border: 1px dotted black;border-radius: 0.25em;box-sizing: border-box;margin-bottom: 0.5em;}#sk-container-id-3 div.sk-estimator:hover {background-color: #d4ebff;}#sk-container-id-3 div.sk-parallel-item::after {content: \"\";width: 100%;border-bottom: 1px solid gray;flex-grow: 1;}#sk-container-id-3 div.sk-label:hover label.sk-toggleable__label {background-color: #d4ebff;}#sk-container-id-3 div.sk-serial::before {content: \"\";position: absolute;border-left: 1px solid gray;box-sizing: border-box;top: 0;bottom: 0;left: 50%;z-index: 0;}#sk-container-id-3 div.sk-serial {display: flex;flex-direction: column;align-items: center;background-color: white;padding-right: 0.2em;padding-left: 0.2em;position: relative;}#sk-container-id-3 div.sk-item {position: relative;z-index: 1;}#sk-container-id-3 div.sk-parallel {display: flex;align-items: stretch;justify-content: center;background-color: white;position: relative;}#sk-container-id-3 div.sk-item::before, #sk-container-id-3 div.sk-parallel-item::before {content: \"\";position: absolute;border-left: 1px solid gray;box-sizing: border-box;top: 0;bottom: 0;left: 50%;z-index: -1;}#sk-container-id-3 div.sk-parallel-item {display: flex;flex-direction: column;z-index: 1;position: relative;background-color: white;}#sk-container-id-3 div.sk-parallel-item:first-child::after {align-self: flex-end;width: 50%;}#sk-container-id-3 div.sk-parallel-item:last-child::after {align-self: flex-start;width: 50%;}#sk-container-id-3 div.sk-parallel-item:only-child::after {width: 0;}#sk-container-id-3 div.sk-dashed-wrapped {border: 1px dashed gray;margin: 0 0.4em 0.5em 0.4em;box-sizing: border-box;padding-bottom: 0.4em;background-color: white;}#sk-container-id-3 div.sk-label label {font-family: monospace;font-weight: bold;display: inline-block;line-height: 1.2em;}#sk-container-id-3 div.sk-label-container {text-align: center;}#sk-container-id-3 div.sk-container {/* jupyter's `normalize.less` sets `[hidden] { display: none; }` but bootstrap.min.css set `[hidden] { display: none !important; }` so we also need the `!important` here to be able to override the default hidden behavior on the sphinx rendered scikit-learn.org. See: https://github.com/scikit-learn/scikit-learn/issues/21755 */display: inline-block !important;position: relative;}#sk-container-id-3 div.sk-text-repr-fallback {display: none;}</style><div id=\"sk-container-id-3\" class=\"sk-top-container\"><div class=\"sk-text-repr-fallback\"><pre>RandomForestRegressor()</pre><b>In a Jupyter environment, please rerun this cell to show the HTML representation or trust the notebook. <br />On GitHub, the HTML representation is unable to render, please try loading this page with nbviewer.org.</b></div><div class=\"sk-container\" hidden><div class=\"sk-item\"><div class=\"sk-estimator sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-3\" type=\"checkbox\" checked><label for=\"sk-estimator-id-3\" class=\"sk-toggleable__label sk-toggleable__label-arrow\">RandomForestRegressor</label><div class=\"sk-toggleable__content\"><pre>RandomForestRegressor()</pre></div></div></div></div></div>"
      ],
      "text/plain": [
       "RandomForestRegressor()"
      ]
     },
     "execution_count": 56,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "random_forest.fit(X_train,y_train)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 57,
   "id": "a9ee2662-3dfe-488c-ac46-1ab63c1a9d0e",
   "metadata": {},
   "outputs": [],
   "source": [
    "y_pred3=random_forest.predict(X_test)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 58,
   "id": "6e870c21-169c-4507-91a9-8e053a8713ce",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([ 481.474  , 1519.88715, 1336.444  , ..., 1378.3515 , 1504.0976 ,\n",
       "       1297.3625 ])"
      ]
     },
     "execution_count": 58,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "y_pred3"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "3583003f-2ee5-480b-91ca-f48a6f3d391e",
   "metadata": {},
   "source": [
    "**Prediction of Actual and Predicted values (Random Forest)**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 59,
   "id": "f84321aa-99a8-414d-8888-0918c1141ba8",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "       Actual Price  Predicted Price\n",
      "0            481.30       481.474000\n",
      "1           1519.97      1519.887150\n",
      "2           1336.90      1336.444000\n",
      "3            505.05       505.005279\n",
      "4           1567.00      1566.529900\n",
      "...             ...              ...\n",
      "59052       1516.30      1516.063500\n",
      "59053       1450.98      1450.865100\n",
      "59054       1378.50      1378.351500\n",
      "59055       1503.65      1504.097600\n",
      "59056       1297.00      1297.362500\n",
      "\n",
      "[59057 rows x 2 columns]\n"
     ]
    }
   ],
   "source": [
    "dframe3=pd.DataFrame(y_test,y_pred2)\n",
    "dfr3=pd.DataFrame({\"Actual Price\":y_test,\"Predicted Price\":y_pred3})\n",
    "print(dfr3)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "558ef236-26ff-4058-bb40-874a3e0bc028",
   "metadata": {},
   "source": [
    "**Normality of Residual**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 60,
   "id": "6a087c8f-35a1-441e-904c-227af20e2d55",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<seaborn.axisgrid.FacetGrid at 0x158f11b10>"
      ]
     },
     "execution_count": 60,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 500x500 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "residual3=y_test-y_pred3\n",
    "sns.displot(residual3)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "e77da233-b8a8-4f19-8043-413be586ab6a",
   "metadata": {},
   "source": [
    "**Computing the accuracy of Random Forest model**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 81,
   "id": "02f57c0a-0423-4f20-93e2-f41c94eaaaa1",
   "metadata": {},
   "outputs": [],
   "source": [
    "R2_score3=round(r2_score(y_test,y_pred3),6)  #R2 score to get the accuracy of your model on a percentage scale\n",
    "MAE3=round(mean_absolute_error(y_test,y_pred3),3)\n",
    "MSE3=round(mean_squared_error(y_test,y_pred3),3)\n",
    "RMSE3=round(np.sqrt(mean_squared_error(y_test,y_pred3)),3)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 82,
   "id": "399d2699-58fb-4883-84e1-bffdf6bd8ca1",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "R2 Score:  99.9997\n",
      "Mean Absolute Error:  0.473\n",
      "Mean Squared Error:  0.621\n",
      "Root Mean Square Error:  0.788\n"
     ]
    }
   ],
   "source": [
    "print(\"R2 Score: \",R2_score3*100)\n",
    "print(\"Mean Absolute Error: \",MAE3)\n",
    "print(\"Mean Squared Error: \",MSE3)\n",
    "print(\"Root Mean Square Error: \",RMSE3)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 63,
   "id": "e83e1d03-1e2a-420e-897e-3abb61c3c6d4",
   "metadata": {},
   "outputs": [],
   "source": [
    "def mean_absolute_percentage_error(y_test, y_pred): \n",
    "    y_test, y_pred = np.array(y_test), np.array(y_pred)\n",
    "    return np.mean(np.abs((y_test - y_pred) / y_test)) * 100"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "33b5743f-1041-481e-b864-7c15c8bba09d",
   "metadata": {},
   "source": [
    "**Mean Absolute Percentage Error for Linear Regression Model**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 64,
   "id": "041863c8-685a-4a68-b08a-155e6288ddb5",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Mean Absolute Percentage Error for Linear Regression: 0.04 %\n"
     ]
    }
   ],
   "source": [
    "MAPE_LR=mean_absolute_percentage_error(y_test,y_pred)\n",
    "print('Mean Absolute Percentage Error for Linear Regression:', round(MAPE_LR, 2), '%')"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "ba5b47aa-6eff-4905-a2bf-cbfe5e89e600",
   "metadata": {},
   "source": [
    "**Mean Absolute Percentage Error for Decision Tree Model**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 65,
   "id": "4864b645-3606-4169-aae2-3c69036be723",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Mean Absolute Percentage Error for Decision Tree: 0.06 %\n"
     ]
    }
   ],
   "source": [
    "MAPE_Decison_Tree=mean_absolute_percentage_error(y_test,y_pred2)\n",
    "print('Mean Absolute Percentage Error for Decision Tree:', round(MAPE_Decison_Tree, 2), '%')"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "ec1d24ab-c3ca-468e-9dd0-5cc0823fc4e1",
   "metadata": {},
   "source": [
    "**Mean Absolute Percentage Error for Random Forest Model**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 66,
   "id": "615f3ac0-4c1c-4c81-a348-e5519c0be9b7",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Mean Absolute Percentage Error for Decision Tree: 0.05 %\n"
     ]
    }
   ],
   "source": [
    "MAPE_Random_Forest=mean_absolute_percentage_error(y_test,y_pred3)\n",
    "print('Mean Absolute Percentage Error for Decision Tree:', round(MAPE_Random_Forest, 2), '%')"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "34cd778f-8754-4360-a0e9-8ae52ee3d0a9",
   "metadata": {},
   "source": [
    "**From the above calculations we found that the Mean Absolute Error (MAE) of Linear Regression is lesser than Decision Tree and Random Forest Algorithms.**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "114cc889-50ab-4918-b671-ab107fb5e3fc",
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3 (ipykernel)",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.11.5"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}