car_price_prediction.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "83ed1c95",
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "from sklearn.model_selection import train_test_split\n",
    "from sklearn.linear_model import LinearRegression\n",
    "import matplotlib.pyplot as plt\n",
    "from sklearn.metrics import r2_score\n",
    "from sklearn import metrics\n",
    "import numpy as np\n",
    "from sklearn.metrics import mean_squared_error, mean_absolute_error"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "6b8b0248",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>name</th>\n",
       "      <th>year</th>\n",
       "      <th>selling_price</th>\n",
       "      <th>km_driven</th>\n",
       "      <th>fuel</th>\n",
       "      <th>seller_type</th>\n",
       "      <th>transmission</th>\n",
       "      <th>owner</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Maruti 800 AC</td>\n",
       "      <td>2007</td>\n",
       "      <td>60000</td>\n",
       "      <td>70000</td>\n",
       "      <td>Petrol</td>\n",
       "      <td>Individual</td>\n",
       "      <td>Manual</td>\n",
       "      <td>First Owner</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Maruti Wagon R LXI Minor</td>\n",
       "      <td>2007</td>\n",
       "      <td>135000</td>\n",
       "      <td>50000</td>\n",
       "      <td>Petrol</td>\n",
       "      <td>Individual</td>\n",
       "      <td>Manual</td>\n",
       "      <td>First Owner</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Hyundai Verna 1.6 SX</td>\n",
       "      <td>2012</td>\n",
       "      <td>600000</td>\n",
       "      <td>100000</td>\n",
       "      <td>Diesel</td>\n",
       "      <td>Individual</td>\n",
       "      <td>Manual</td>\n",
       "      <td>First Owner</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Datsun RediGO T Option</td>\n",
       "      <td>2017</td>\n",
       "      <td>250000</td>\n",
       "      <td>46000</td>\n",
       "      <td>Petrol</td>\n",
       "      <td>Individual</td>\n",
       "      <td>Manual</td>\n",
       "      <td>First Owner</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Honda Amaze VX i-DTEC</td>\n",
       "      <td>2014</td>\n",
       "      <td>450000</td>\n",
       "      <td>141000</td>\n",
       "      <td>Diesel</td>\n",
       "      <td>Individual</td>\n",
       "      <td>Manual</td>\n",
       "      <td>Second Owner</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                       name  year  selling_price  km_driven    fuel  \\\n",
       "0             Maruti 800 AC  2007          60000      70000  Petrol   \n",
       "1  Maruti Wagon R LXI Minor  2007         135000      50000  Petrol   \n",
       "2      Hyundai Verna 1.6 SX  2012         600000     100000  Diesel   \n",
       "3    Datsun RediGO T Option  2017         250000      46000  Petrol   \n",
       "4     Honda Amaze VX i-DTEC  2014         450000     141000  Diesel   \n",
       "\n",
       "  seller_type transmission         owner  \n",
       "0  Individual       Manual   First Owner  \n",
       "1  Individual       Manual   First Owner  \n",
       "2  Individual       Manual   First Owner  \n",
       "3  Individual       Manual   First Owner  \n",
       "4  Individual       Manual  Second Owner  "
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dataset=pd.read_csv(\"car_details.csv\")\n",
    "dataset.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "5b7eb1f2",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(4340, 8)"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dataset.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "a17128f2",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "name             0\n",
       "year             0\n",
       "selling_price    0\n",
       "km_driven        0\n",
       "fuel             0\n",
       "seller_type      0\n",
       "transmission     0\n",
       "owner            0\n",
       "dtype: int64"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dataset.isnull().sum()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "d463c269",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 4340 entries, 0 to 4339\n",
      "Data columns (total 8 columns):\n",
      " #   Column         Non-Null Count  Dtype \n",
      "---  ------         --------------  ----- \n",
      " 0   name           4340 non-null   object\n",
      " 1   year           4340 non-null   int64 \n",
      " 2   selling_price  4340 non-null   int64 \n",
      " 3   km_driven      4340 non-null   int64 \n",
      " 4   fuel           4340 non-null   object\n",
      " 5   seller_type    4340 non-null   object\n",
      " 6   transmission   4340 non-null   object\n",
      " 7   owner          4340 non-null   object\n",
      "dtypes: int64(3), object(5)\n",
      "memory usage: 271.4+ KB\n"
     ]
    }
   ],
   "source": [
    "dataset.info()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "de4feb62",
   "metadata": {},
   "source": [
    "# Performing Data Analysis\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "f60e1838",
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>name</th>\n",
       "      <th>year</th>\n",
       "      <th>selling_price</th>\n",
       "      <th>km_driven</th>\n",
       "      <th>fuel</th>\n",
       "      <th>seller_type</th>\n",
       "      <th>transmission</th>\n",
       "      <th>owner</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Maruti 800 AC</td>\n",
       "      <td>2007</td>\n",
       "      <td>60000</td>\n",
       "      <td>70000</td>\n",
       "      <td>Petrol</td>\n",
       "      <td>Individual</td>\n",
       "      <td>Manual</td>\n",
       "      <td>First Owner</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Maruti Wagon R LXI Minor</td>\n",
       "      <td>2007</td>\n",
       "      <td>135000</td>\n",
       "      <td>50000</td>\n",
       "      <td>Petrol</td>\n",
       "      <td>Individual</td>\n",
       "      <td>Manual</td>\n",
       "      <td>First Owner</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Hyundai Verna 1.6 SX</td>\n",
       "      <td>2012</td>\n",
       "      <td>600000</td>\n",
       "      <td>100000</td>\n",
       "      <td>Diesel</td>\n",
       "      <td>Individual</td>\n",
       "      <td>Manual</td>\n",
       "      <td>First Owner</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Datsun RediGO T Option</td>\n",
       "      <td>2017</td>\n",
       "      <td>250000</td>\n",
       "      <td>46000</td>\n",
       "      <td>Petrol</td>\n",
       "      <td>Individual</td>\n",
       "      <td>Manual</td>\n",
       "      <td>First Owner</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Honda Amaze VX i-DTEC</td>\n",
       "      <td>2014</td>\n",
       "      <td>450000</td>\n",
       "      <td>141000</td>\n",
       "      <td>Diesel</td>\n",
       "      <td>Individual</td>\n",
       "      <td>Manual</td>\n",
       "      <td>Second Owner</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                       name  year  selling_price  km_driven    fuel  \\\n",
       "0             Maruti 800 AC  2007          60000      70000  Petrol   \n",
       "1  Maruti Wagon R LXI Minor  2007         135000      50000  Petrol   \n",
       "2      Hyundai Verna 1.6 SX  2012         600000     100000  Diesel   \n",
       "3    Datsun RediGO T Option  2017         250000      46000  Petrol   \n",
       "4     Honda Amaze VX i-DTEC  2014         450000     141000  Diesel   \n",
       "\n",
       "  seller_type transmission         owner  \n",
       "0  Individual       Manual   First Owner  \n",
       "1  Individual       Manual   First Owner  \n",
       "2  Individual       Manual   First Owner  \n",
       "3  Individual       Manual   First Owner  \n",
       "4  Individual       Manual  Second Owner  "
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "numerical_feature=[feature for feature in dataset.columns if dataset[feature].dtypes != 'o']\n",
    "dataset[numerical_feature].head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "e3639938",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Index(['name', 'year', 'selling_price', 'km_driven', 'fuel', 'seller_type',\n",
       "       'transmission', 'owner'],\n",
       "      dtype='object')"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dataset[numerical_feature].columns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "739ad9df",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([2007, 2012, 2017, 2014, 2016, 2015, 2018, 2019, 2013, 2011, 2010,\n",
       "       2009, 2006, 1996, 2005, 2008, 2004, 1998, 2003, 2002, 2020, 2000,\n",
       "       1999, 2001, 1995, 1997, 1992], dtype=int64)"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dataset['year'].unique()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "c1ea1e3c",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0.5, 1.0, 'year sold vs selling_price')"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAlYAAAHFCAYAAAAwv7dvAAAAOXRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjcuMiwgaHR0cHM6Ly9tYXRwbG90bGliLm9yZy8pXeV/AAAACXBIWXMAAA9hAAAPYQGoP6dpAAB3c0lEQVR4nO3deVxU9f4/8NewDfsIIgwjirhruKXmlmIqLqHWrW5dNdK2e7PULO2afbtptmBl1k0zW2562+TWT23RItyXBEWUBHFfQFkEWWYAWWfevz+IkyOICAPD4Ov5eMwjOec957zneHLefM7nvI9KRARERERE1GB21k6AiIiIqKVgYUVERERkISysiIiIiCyEhRURERGRhbCwIiIiIrIQFlZEREREFsLCioiIiMhCWFgRERERWQgLKyIiIiILYWFFRDZBpVJh8eLFN4xbu3YtVCoVzp8/3+g5NZUZM2agQ4cOZss6dOiAGTNmKD+fP38eKpUKa9eubdLcGsvixYuhUqmsnQbRTXOwdgJERNRw/v7+iImJQadOnaydikU88cQTGD9+vLXTILppLKyIqN6MRiMqKiqgVqutncotT61WY/DgwdZOo8GuXLkCV1dXBAQEICAgwNrpEN00XgoksiF79uyBSqXCunXrqq374osvoFKpEBcXpyw7ePAgJk+eDG9vbzg7O6Nfv3749ttvzd6XnZ2Np59+Gj179oS7uzt8fX0xatQo7Nmzxyyu6lLT22+/jddffx1BQUFQq9XYsWPHdfP97rvvMGjQIGg0Gri6uqJjx4547LHHzGJSU1Px8MMPw9fXF2q1Gj169MC7774Lk8l0w+MRGxuLYcOGwdnZGTqdDgsXLkR5efkN3/f+++9DpVLh9OnT1dYtWLAATk5OuHz5MgDg8OHDmDhxopKfTqdDWFgYLl68WOs+6vI+EcGqVavQt29fuLi4wMvLCw888ADOnj17w89wrZouBVZdTjt69CimTJkCjUYDPz8/PPbYY9Dr9Wbvz8/Px+OPPw5vb2+4u7sjLCwMZ8+erfMl2GvzePvtt/HGG2+gffv2cHZ2xoABA7Bt2zaz2Kr8Dh06hAceeABeXl7KiNv1LgV+8803GDJkCNzd3eHu7o6+ffviP//5j1nM1q1bMXr0aHh6esLV1RXDhg2rtm+ixsLCisiGDB8+HP369cOHH35Ybd3KlSsxcOBADBw4EACwY8cODBs2DPn5+Vi9ejV++OEH9O3bFw899JDZl29ubi4AYNGiRdi8eTPWrFmDjh07YuTIkdi5c2e1/XzwwQfYvn07li1bhl9++QXdu3evMdeYmBg89NBD6NixIyIjI7F582a88sorqKioUGKys7MxdOhQREdH47XXXsOPP/6IMWPGYP78+Zg1a1atxyI5ORmjR49Gfn4+1q5di9WrV+Pw4cN4/fXXb3QY8fDDD8PJyanafCSj0YivvvoKkyZNgo+PD4qKihAaGopLly7hww8/xJYtW/D++++jffv2KCgouO726/q+f/zjH5g7dy7GjBmD77//HqtWrcLRo0cxdOhQXLp06Yafo67uv/9+dO3aFevXr8eLL76Ib775Bs8995yy3mQyYdKkSfjmm2+wYMECbNy4EYMGDWrQpbiVK1ciKioK77//Pr766ivY2dlhwoQJiImJqRZ73333oXPnzvjuu++wevXq627zlVdewbRp06DT6bB27Vps3LgR06dPR0pKihLz1VdfYezYsfD09MR///tffPvtt/D29sa4ceNYXFHTECKyKWvWrBEAcvjwYWXZgQMHBID897//VZZ1795d+vXrJ+Xl5Wbvnzhxovj7+4vRaKxx+xUVFVJeXi6jR4+Wv/zlL8ryc+fOCQDp1KmTlJWV3TDPZcuWCQDJz8+/bsyLL74oAGT//v1my2fOnCkqlUpOnDihLAMgixYtUn5+6KGHxMXFRTIzM81y7969uwCQc+fO1ZrffffdJwEBAWbH4eeffxYA8tNPP4mIyMGDBwWAfP/99zf8vFery/tiYmIEgLz77rtmyy9cuCAuLi7yz3/+U1k2ffp0CQwMNIsLDAyU6dOnKz9X/f2sWbNGWbZo0SIBIG+//bbZe59++mlxdnYWk8kkIiKbN28WAPLRRx+ZxUVERFQ77jdSlYdOp5Pi4mJlucFgEG9vbxkzZky1/F555ZVq26laV+Xs2bNib28v06ZNu+6+i4qKxNvbWyZNmmS23Gg0Sp8+feSOO+6o8+cgqi+OWBHZmClTpsDX19ds1GrFihVo06YNHnroIQDA6dOncfz4cUybNg0AUFFRobzuvvtuZGRk4MSJE8r7V69ejdtvvx3Ozs5wcHCAo6Mjtm3bhmPHjlXb/+TJk+Ho6HjDPKtGzh588EF8++23SEtLqxazfft29OzZE3fccYfZ8hkzZkBEsH379utuf8eOHRg9ejT8/PyUZfb29soxuJFHH30UFy9exNatW5Vla9asgVarxYQJEwAAnTt3hpeXFxYsWIDVq1cjOTm5Ttuuy/s2bdoElUqFhx9+2OzvR6vVok+fPjWOFtbX5MmTzX7u3bs3SkpKkJWVBQDYtWsXgMq/q6tNmTKl3vu877774OzsrPzs4eGBSZMmYffu3TAajWax999//w23t2XLFhiNRjzzzDPXjdm3bx9yc3Mxffp0s2NqMpkwfvx4xMXFoaioqN6fiaguWFgR2Ri1Wo1//OMf+Oabb5Cfn4/s7Gx8++23eOKJJ5RJ5FWXkebPnw9HR0ez19NPPw0Ayhyi5cuXY+bMmRg0aBDWr1+P2NhYxMXFYfz48SguLq62f39//zrlOWLECHz//feoqKjAI488goCAAAQHB5vND8vJyalxezqdTll/PTk5OdBqtdWW17SsJhMmTIC/vz/WrFkDAMjLy8OPP/6IRx55BPb29gAAjUaDXbt2oW/fvnjppZdw2223QafTYdGiRbXO5arL+y5dugQRgZ+fX7W/o9jYWOXvxxJat25t9nPVeVL195uTkwMHBwd4e3ubxV1dtN6s6/3dlJWVobCw0Gx5Xc6p7OxsAKh1QnvVef/AAw9UO6ZvvfUWRES59E3UWHhXIJENmjlzJpYuXYrPP/8cJSUlqKiowFNPPaWs9/HxAQAsXLgQ9913X43b6NatG4DKOSkjR47ERx99ZLb+enOIbqa30D333IN77rkHpaWliI2NRUREBKZOnYoOHTpgyJAhaN26NTIyMqq9Lz093exz1KR169bIzMystrymZTWxt7dHeHg4PvjgA+Tn5+Obb75BaWkpHn30UbO4Xr16ITIyEiKCI0eOYO3atViyZAlcXFzw4osvXnf7N3qfj48PVCoV9uzZU+NdlU15p2Xr1q1RUVGB3Nxcs+KqrseyJtf7u3FycoK7u7vZ8rqcU23atAEAXLx4Ee3atasxpup8WbFixXXvkGxIsUhUFxyxIrJB/v7++Otf/4pVq1Zh9erVmDRpEtq3b6+s79atG7p06YLff/8dAwYMqPHl4eEBoPJL7dov8SNHjtQ4ybi+1Go1QkJC8NZbbwGovGMOAEaPHo3k5GQcOnTILL7qDse77rrrutu86667sG3bNrNJ3kajEf/73//qnNejjz6KkpISrFu3DmvXrsWQIUOuOxlfpVKhT58+eO+999CqVatqOV/P9d43ceJEiAjS0tJq/Pvp1atXnT9HQ4WEhABAtWMXGRlZ721u2LABJSUlys8FBQX46aefMHz4cGVE8GaMHTsW9vb21X4BuNqwYcPQqlUrJCcnX/e8d3JyqtfnIaorjlgR2ahnn30WgwYNAgDlctbVPv74Y0yYMAHjxo3DjBkz0LZtW+Tm5uLYsWM4dOgQvvvuOwCVX/CvvfYaFi1ahJCQEJw4cQJLlixBUFCQ2R18N+uVV17BxYsXMXr0aAQEBCA/Px///ve/4ejoqHyRP/fcc/jiiy8QFhaGJUuWIDAwEJs3b8aqVaswc+ZMdO3a9brbf/nll/Hjjz9i1KhReOWVV+Dq6ooPP/zwpubQdO/eHUOGDEFERAQuXLiATz75xGz9pk2bsGrVKtx7773o2LEjRAQbNmxAfn4+QkNDr7vdurxv2LBh+Pvf/45HH30UBw8exIgRI+Dm5oaMjAzs3bsXvXr1wsyZM+v8WRpi/PjxGDZsGObNmweDwYD+/fsjJiYGX3zxBQDAzu7mfwe3t7dHaGgonn/+eZhMJrz11lswGAx49dVX65Vjhw4d8NJLL+G1115DcXGx0j4iOTkZly9fxquvvgp3d3esWLEC06dPR25uLh544AH4+voiOzsbv//+O7Kzs2stzIgswnrz5omooTp06CA9evS47vrff/9dHnzwQfH19RVHR0fRarUyatQoWb16tRJTWloq8+fPl7Zt24qzs7Pcfvvt8v3331e7E63qbq933nmnTrlt2rRJJkyYIG3bthUnJyfx9fWVu+++W/bs2WMWl5KSIlOnTpXWrVuLo6OjdOvWTd55551qdy2ihrvTfvvtNxk8eLCo1WrRarXywgsvyCeffFKnuwKrVMW7uLiIXq83W3f8+HGZMmWKdOrUSVxcXESj0cgdd9wha9eurXWbN/O+zz//XAYNGiRubm7i4uIinTp1kkceeUQOHjyoxDT0rsDs7Gyz91bdWXr1McrNzZVHH31UWrVqJa6urhIaGiqxsbECQP7973/X+nmvVpXHW2+9Ja+++qoEBASIk5OT9OvXT3799Vez2Ovld/W6a33xxRcycOBAcXZ2Fnd3d+nXr5/ZZxYR2bVrl4SFhYm3t7c4OjpK27ZtJSwsTL777rs6fw6i+lKJiFippiOiBjhy5Aj69OmDDz/8UJmQTmRJ33zzDaZNm4bffvsNQ4cOrdN7zp8/j6CgILzzzjuYP39+I2dI1PzwUiCRjTlz5gxSUlLw0ksvwd/f3+xBvET1tW7dOqSlpaFXr16ws7NDbGws3nnnHYwYMaLORRURsbAisjmvvfYavvzyS/To0QPfffcdXF1drZ0StQAeHh6IjIzE66+/jqKiIqVov7qT/Y3m3NVnLhZRS8NLgUREdENVl/hqs2jRopt6riBRS8QRKyIiuiGdTmf2gO/rxRDd6jhiRURERGQhvCBOREREZCG8FNjETCYT0tPT4eHhcVOPBiEiIiLrEREUFBRAp9PVeqMGC6smlp6eft3nXBEREVHzduHChVofBs7CqolVPZ/twoUL8PT0tHI2REREVBcGgwHt2rVTvsevh4VVE6u6/Ofp6cnCioiIyMbcaBoPJ68TERERWQgLKyIiIiILYWFFREREZCEsrIiIiIgshIUVERERkYWwsCIiIiKyEBZWRERERBbCwoqIiIjIQlhYEREREVkICysiIiIiC7FqYdWhQweoVKpqr2eeeQZA5ZOkFy9eDJ1OBxcXF4wcORJHjx4120ZpaSlmz54NHx8fuLm5YfLkybh48aJZTF5eHsLDw6HRaKDRaBAeHo78/HyzmNTUVEyaNAlubm7w8fHBnDlzUFZWZhaTmJiIkJAQuLi4oG3btliyZAlExPIHhoiIiGySVQuruLg4ZGRkKK8tW7YAAP76178CAN5++20sX74cK1euRFxcHLRaLUJDQ1FQUKBsY+7cudi4cSMiIyOxd+9eFBYWYuLEiTAajUrM1KlTkZCQgKioKERFRSEhIQHh4eHKeqPRiLCwMBQVFWHv3r2IjIzE+vXrMW/ePCXGYDAgNDQUOp0OcXFxWLFiBZYtW4bly5c39mEiIiIiWyHNyLPPPiudOnUSk8kkJpNJtFqtLF26VFlfUlIiGo1GVq9eLSIi+fn54ujoKJGRkUpMWlqa2NnZSVRUlIiIJCcnCwCJjY1VYmJiYgSAHD9+XEREfv75Z7Gzs5O0tDQlZt26daJWq0Wv14uIyKpVq0Sj0UhJSYkSExERITqdTkwmU50/o16vFwDKdomIiFqKsgqjlFUYrZ1Go6jr93ezmWNVVlaGr776Co899hhUKhXOnTuHzMxMjB07VolRq9UICQnBvn37AADx8fEoLy83i9HpdAgODlZiYmJioNFoMGjQICVm8ODB0Gg0ZjHBwcHQ6XRKzLhx41BaWor4+HglJiQkBGq12iwmPT0d58+fv+7nKi0thcFgMHsRERG1NIaSctz51nZMWrEXhpJya6djNc2msPr++++Rn5+PGTNmAAAyMzMBAH5+fmZxfn5+yrrMzEw4OTnBy8ur1hhfX99q+/P19TWLuXY/Xl5ecHJyqjWm6ueqmJpEREQoc7s0Gg3atWt3/YNARERko7Yfy8IlQymOZxZg/re/37JzkJtNYfWf//wHEyZMMBs1AgCVSmX2s4hUW3ata2NqirdETNVJU1s+CxcuhF6vV14XLlyoNXciIiJbFJ2cedWfL2H1rrNWzMZ6mkVhlZKSgq1bt+KJJ55Qlmm1WgDVR4OysrKUkSKtVouysjLk5eXVGnPp0qVq+8zOzjaLuXY/eXl5KC8vrzUmKysLQPVRtaup1Wp4enqavYiIiFqSknIjdp7IBgBMHdQeAPDOr8ex7/Rla6ZlFc2isFqzZg18fX0RFhamLAsKCoJWq1XuFAQq52Ht2rULQ4cOBQD0798fjo6OZjEZGRlISkpSYoYMGQK9Xo8DBw4oMfv374derzeLSUpKQkZGhhITHR0NtVqN/v37KzG7d+82a8EQHR0NnU6HDh06WPBoEBER2ZZ9Zy7jSpkR/hpnvHFvMB7oHwCTALPXHUaGvtja6TUpqxdWJpMJa9aswfTp0+Hg4KAsV6lUmDt3Lt58801s3LgRSUlJmDFjBlxdXTF16lQAgEajweOPP4558+Zh27ZtOHz4MB5++GH06tULY8aMAQD06NED48ePx5NPPonY2FjExsbiySefxMSJE9GtWzcAwNixY9GzZ0+Eh4fj8OHD2LZtG+bPn48nn3xSGWGaOnUq1Go1ZsyYgaSkJGzcuBFvvvkmnn/++RtemiQiImrJtiRXXhkK7ekHlUqF1+8NRk9/T+QUlWHmV4dQWmG8wRZakEa/P/EGfv31VwEgJ06cqLbOZDLJokWLRKvVilqtlhEjRkhiYqJZTHFxscyaNUu8vb3FxcVFJk6cKKmpqWYxOTk5Mm3aNPHw8BAPDw+ZNm2a5OXlmcWkpKRIWFiYuLi4iLe3t8yaNcustYKIyJEjR2T48OGiVqtFq9XK4sWLb6rVggjbLRARUctSYTRJ/9eiJXDBJtlzMltZnnK5SHotipLABZvk5Y2JtWzBNtT1+1slcotO27cSg8EAjUYDvV7P+VZERGTz4lNycf9HMfBwdsChf4XC0f7Pi2Hbj1/CY2sPAgDee6gP/tIvwFppNlhdv7+tfimQiIiIbFf00crLgKO6+5oVVZXL/DBnVGcAwMINiTiW0fJ7ObKwIiIionoREUT/Mb9qbE9tjTHPjumKEV3boKTchKe+ioe+uGU3D2VhRURERPVyJrsQ5y4XwcneDiHd2tQYY2+nwr8f6ou2rVyQknMF8779HSZTy52FxMKKiIiI6uXXPy4DDuvcGu5qh+vGebk54aOHb4eTvR22HruEj3adaaoUmxwLKyIiIqqXaKXNQs2XAa/WO6AVltxzGwDg3egT2HuqZTYPZWFFREREN+2SoQS/X8iHSgWM6Vn9mbw1+dsd7fHggMrmoXMiDyM9v+U1D2VhRURERDetqilov3at4OvhXOf3LbknGLfpPJFbVIaZX7e85qEsrIiIiOimKXcD3nbjy4BXc3a0x+qH+0Pj4ojfL+RjyU/JFsnn3OUifLTzDKZ/fgBGK06Ov/5MMyIiIqIaGErKEXOmco5UaE+/m35/O29XvP+3vnhsbRy+3p+K29t74f7+N9c8VERwPLMAvyRl4tekTJy4VKCsi0/Jwx1B3jedlyWwsCIiIqKbsutENsqNgk5t3NCpjXu9tnFXN188O7oL3t96Ci9tTER3fw/cptPU+h6TSZBwMR+/JmUi6mgmUnKuKOsc7FQY2tkH42/Tootv/XKyBBZWREREdFPqexnwWnNGdUHChXzsPJGNmV8dwk+z7oTG1dEspsJowoHzufg1KRO/Hr2ETEOJsk7tYIeQrm0wPliL0d39qr3XGlhYERERUZ2VVhix43gWAGBsPS4DXs3OToX3H+qLiSv2IjX3Cp7/NgGfPjIA5SYTfjt9GVFJmdiSfAl5V/7s1u6udsDoHr4Yf5sWId3awNWpeZUyzSsbIiIiatZiz+aisLQCvh5q9Alo1eDttXJ1wuqH++O+j/Zh2/Es/PXjGJzILEBhaYUS4+3mhNAefhgfrMXQzq2hdrBv8H4bCwsrIiIiqrMtyZkAgDE9/WBnp7LINoPbavD6PcH45/ojiE/JAwBoPZ0xPliLcbdpMbCDFxzsbaORAQsrIiIiqhOTSZT+VQ29DHitBwe2Q6nRhEx9Mcb08EOfgFYWK9yaEgsrIiIiqpMjaXpcMpTCXe2AIZ1aW3z74YMDLb7NpmYb42pERERkddFHKy8DhnRr06znOVkTCysiIiKqk8a6DNiSsLAiIiKiGzqbXYhTWYVwtFfhru51e+jyrYiFFREREd1Q1WjV4I6t4els/UaczRULKyIiIrqhaF4GrBMWVkRERFSr7IJSHEqt7C81hoVVrVhYERERUa22HbsEEaBPgAb+Ghdrp9OssbAiIiKiWlnqocu3AhZWREREdF1FpRXYe/oyACCUlwFviIUVERERXdfuk9koqzChQ2tXdPF1t3Y6zR4LKyIiIrquqy8DqlS29+y+psbCioiIiGpUbjRh2zG2WbgZLKyIiIioRgfO5cJQUoHWbk7o197L2unYBBZWREREVKOqbutjevjB3o6XAeuChRURERFVIyKIPpoJABh7Gy8D1hULKyIiIqrmaLoB6foSuDrZY1hnH2unYzNYWBEREVE1VaNVI7q0gbOjvZWzsR0srIiIiKiaP9ss8DLgzWBhRURERGZSc67geGYB7O1UGNXd19rp2BQWVkRERGQmOrnyMuCgIG+0cnWycja2hYUVERERmam6DMhnA948FlZERESkyC0qw8HzuQBYWNUHCysiIiJSbDt2CSYBbtN5IsDL1drp2BwWVkRERKRQ7gbsqbVyJrbJ6oVVWloaHn74YbRu3Rqurq7o27cv4uPjlfUigsWLF0On08HFxQUjR47E0aNHzbZRWlqK2bNnw8fHB25ubpg8eTIuXrxoFpOXl4fw8HBoNBpoNBqEh4cjPz/fLCY1NRWTJk2Cm5sbfHx8MGfOHJSVlZnFJCYmIiQkBC4uLmjbti2WLFkCEbHsQSEiIrKC4jIj9pzKBsDLgPVl1cIqLy8Pw4YNg6OjI3755RckJyfj3XffRatWrZSYt99+G8uXL8fKlSsRFxcHrVaL0NBQFBQUKDFz587Fxo0bERkZib1796KwsBATJ06E0WhUYqZOnYqEhARERUUhKioKCQkJCA8PV9YbjUaEhYWhqKgIe/fuRWRkJNavX4958+YpMQaDAaGhodDpdIiLi8OKFSuwbNkyLF++vHEPFBERURPYfSobJeUmBHi5oIe/h7XTsU1iRQsWLJA777zzuutNJpNotVpZunSpsqykpEQ0Go2sXr1aRETy8/PF0dFRIiMjlZi0tDSxs7OTqKgoERFJTk4WABIbG6vExMTECAA5fvy4iIj8/PPPYmdnJ2lpaUrMunXrRK1Wi16vFxGRVatWiUajkZKSEiUmIiJCdDqdmEymOn1mvV4vAJRtEhERNRfzvk2QwAWb5NUfj1o7lWanrt/fVh2x+vHHHzFgwAD89a9/ha+vL/r164dPP/1UWX/u3DlkZmZi7NixyjK1Wo2QkBDs27cPABAfH4/y8nKzGJ1Oh+DgYCUmJiYGGo0GgwYNUmIGDx4MjUZjFhMcHAydTqfEjBs3DqWlpcqlyZiYGISEhECtVpvFpKen4/z58xY8MkRERE2rwmjCtmPstt5QVi2szp49i48++ghdunTBr7/+iqeeegpz5szBF198AQDIzKxsUObnZ/4X7Ofnp6zLzMyEk5MTvLy8ao3x9a3eOdbX19cs5tr9eHl5wcnJqdaYqp+rYq5VWloKg8Fg9iIiImpudp/KRt6VcrRydcSAQK8bv4Fq5GDNnZtMJgwYMABvvvkmAKBfv344evQoPvroIzzyyCNKnEqlMnufiFRbdq1rY2qKt0SM/DFx/Xr5RERE4NVXX601VyIiImsSEXy44wwA4MEB7eBgb/V722yWVY+cv78/evbsabasR48eSE1NBQBotZW3el47GpSVlaWMFGm1WpSVlSEvL6/WmEuXLlXbf3Z2tlnMtfvJy8tDeXl5rTFZWVkAqo+qVVm4cCH0er3yunDhQo1xRERE1hJ7NhfxKXlwcrDDE3cGWTsdm2bVwmrYsGE4ceKE2bKTJ08iMDAQABAUFAStVostW7Yo68vKyrBr1y4MHToUANC/f384OjqaxWRkZCApKUmJGTJkCPR6PQ4cOKDE7N+/H3q93iwmKSkJGRkZSkx0dDTUajX69++vxOzevdusBUN0dDR0Oh06dOhQ42dUq9Xw9PQ0exERETUnH+44DQB4aEA7+Ho6WzkbG9fo0+hrceDAAXFwcJA33nhDTp06JV9//bW4urrKV199pcQsXbpUNBqNbNiwQRITE2XKlCni7+8vBoNBiXnqqackICBAtm7dKocOHZJRo0ZJnz59pKKiQokZP3689O7dW2JiYiQmJkZ69eolEydOVNZXVFRIcHCwjB49Wg4dOiRbt26VgIAAmTVrlhKTn58vfn5+MmXKFElMTJQNGzaIp6enLFu2rM6fmXcFEhFRc3I4NU8CF2ySjgs3S2pOkbXTabbq+v1t1cJKROSnn36S4OBgUavV0r17d/nkk0/M1ptMJlm0aJFotVpRq9UyYsQISUxMNIspLi6WWbNmibe3t7i4uMjEiRMlNTXVLCYnJ0emTZsmHh4e4uHhIdOmTZO8vDyzmJSUFAkLCxMXFxfx9vaWWbNmmbVWEBE5cuSIDB8+XNRqtWi1Wlm8eHGdWy2IsLAiIqLm5Yn/xknggk3y/P8SrJ1Ks1bX72+VCNuGNyWDwQCNRgO9Xs/LgkREZFXHMw0Y//4eqFTAludC0NnX3dopNVt1/f7mtH8iIqJb1Ec7K+8EnBCsZVFlISysiIiIbkHnLxfhp9/TAQBPj+xs5WxaDhZWREREt6DVu87AJMBd3doguK3G2um0GCysiIiIbjHp+cVYf+giAGDWKI5WWRILKyIiolvMp3vOotwoGBTkjf6B3tZOp0VhYUVERHQLuVxYinUHKp9wwtEqy2NhRUREdAv5fO85lJSb0CdAgzs7+1g7nRaHhRUREdEtQl9cji9jUgAAT9/VGSqVysoZtTwsrIiIiG4RX8acR0FpBbr6uSO0h5+102mRWFgRERHdAq6UVeA/e88BAJ65qzPs7Dha1RhYWBEREd0Cvtmfirwr5Wjv7YqwXv7WTqfFYmFFRETUwpVWGPHpnrMAgJkjO8HBnl//jYVHloiIqIVbH5+GS4ZSaD2dcd/tba2dTovGwoqIiKgFqzCasHpX5cOWnxzREWoHeytn1LKxsCIiImrBfjqSjtTcK/B2c8KUO9pZO50Wj4UVERFRC2UyCVbtqBytevzOILg6OVg5o5aPhRUREVELFZ18CaeyCuGhdkD4kEBrp3NLYGFFRETUAokIPtxxGgDwyNBAeDo7WjmjWwMLKyIiohZoz6nLSEzTw8XRHo8NC7J2OrcMFlZEREQt0Mo/Rqum3NEerd3VVs7m1sHCioiIqIWJO5+LA+dy4WivwpMjOFrVlFhYERERtTArt1eOVj3QPwD+GhcrZ3NrYWFFRETUgiSl6bHrZDbsVMBTIZ2snc4th4UVERFRC1J1J+CkPjoEtnazcja3HhZWRERELcTprAJEHc0EADw9srOVs7k1sbAiIiJqIVbtPAMRYGxPP3TTelg7nVsSCysiIqIW4ELuFfyQkA4AeOYujlZZCwsrIiKiFuDf207BaBIM7+KDPu1aWTudWxYLKyIiIht3OqsQGw5dBAA8H9rVytnc2lhYERER2bj3t56ESYAxPXzRr72XtdO5pbGwIiIismHJ6QZsOpIBAHg+tJuVsyEWVkRERDZs+ZYTAICJvf3RU+dp5WyIhRUREZGNOpSah63HsmCnAp7j3KpmgYUVERGRjXo3unK06v7bA9CpjbuVsyGAhRUREZFN2nfmMn47nQNHexXmjO5i7XToDyysiIiIbIyIYNmvlaNVU+5oj3berlbOiKqwsCIiIrIxO05k4VBqPpwd7TCLXdabFRZWRERENsRkEiz79SQAYPqQDvD1dLZyRnQ1FlZEREQ2JOpoJpIzDHBXO+CpkE7WToeuwcKKiIjIRhhNguVbKkerHrszCF5uTlbOiK7FwoqIiMhGfH84DaezCqFxccQTw4OsnQ7VwKqF1eLFi6FSqcxeWq1WWS8iWLx4MXQ6HVxcXDBy5EgcPXrUbBulpaWYPXs2fHx84ObmhsmTJ+PixYtmMXl5eQgPD4dGo4FGo0F4eDjy8/PNYlJTUzFp0iS4ubnBx8cHc+bMQVlZmVlMYmIiQkJC4OLigrZt22LJkiUQEcseFCIiohqUVZjw/rbK0aqnQjrB09nRyhlRTaw+YnXbbbchIyNDeSUmJirr3n77bSxfvhwrV65EXFwctFotQkNDUVBQoMTMnTsXGzduRGRkJPbu3YvCwkJMnDgRRqNRiZk6dSoSEhIQFRWFqKgoJCQkIDw8XFlvNBoRFhaGoqIi7N27F5GRkVi/fj3mzZunxBgMBoSGhkKn0yEuLg4rVqzAsmXLsHz58kY+QkRERMC3By/gQm4xfNzVmD400Nrp0PWIFS1atEj69OlT4zqTySRarVaWLl2qLCspKRGNRiOrV68WEZH8/HxxdHSUyMhIJSYtLU3s7OwkKipKRESSk5MFgMTGxioxMTExAkCOHz8uIiI///yz2NnZSVpamhKzbt06UavVotfrRURk1apVotFopKSkRImJiIgQnU4nJpOpzp9Zr9cLAGW7REREN1JcViF3vLFFAhdskjV7z1o7nVtSXb+/rT5iderUKeh0OgQFBeFvf/sbzp49CwA4d+4cMjMzMXbsWCVWrVYjJCQE+/btAwDEx8ejvLzcLEan0yE4OFiJiYmJgUajwaBBg5SYwYMHQ6PRmMUEBwdDp9MpMePGjUNpaSni4+OVmJCQEKjVarOY9PR0nD9//rqfr7S0FAaDwexFRER0M76KTcElQynatnLBlEHtrZ0O1cKqhdWgQYPwxRdf4Ndff8Wnn36KzMxMDB06FDk5OcjMzAQA+Pn5mb3Hz89PWZeZmQknJyd4eXnVGuPr61tt376+vmYx1+7Hy8sLTk5OtcZU/VwVU5OIiAhlbpdGo0G7du1qPyhERERXKSytwKqdZwAAc0Z3htrB3soZUW2sWlhNmDAB999/P3r16oUxY8Zg8+bNAID//ve/SoxKpTJ7j4hUW3ata2NqirdEjPwxcb22fBYuXAi9Xq+8Lly4UGvuREREV1uz9xxyi8oQ5OOG+28PsHY6dANWvxR4NTc3N/Tq1QunTp1S7g68djQoKytLGSnSarUoKytDXl5erTGXLl2qtq/s7GyzmGv3k5eXh/Ly8lpjsrKyAFQfVbuaWq2Gp6en2YuIiKgu9FfK8cmeyikyc8d0gYN9s/rapho0q7+h0tJSHDt2DP7+/ggKCoJWq8WWLVuU9WVlZdi1axeGDh0KAOjfvz8cHR3NYjIyMpCUlKTEDBkyBHq9HgcOHFBi9u/fD71ebxaTlJSEjIwMJSY6OhpqtRr9+/dXYnbv3m3WgiE6Oho6nQ4dOnSw/MEgIqJb3id7zqCgpALdtR6Y1Ft34zeQ9TX+PPrrmzdvnuzcuVPOnj0rsbGxMnHiRPHw8JDz58+LiMjSpUtFo9HIhg0bJDExUaZMmSL+/v5iMBiUbTz11FMSEBAgW7dulUOHDsmoUaOkT58+UlFRocSMHz9eevfuLTExMRITEyO9evWSiRMnKusrKiokODhYRo8eLYcOHZKtW7dKQECAzJo1S4nJz88XPz8/mTJliiQmJsqGDRvE09NTli1bdlOfmXcFEhFRXWQXlEiPf/0igQs2ya9JGdZO55ZX1+9vqxZWDz30kPj7+4ujo6PodDq577775OjRo8p6k8kkixYtEq1WK2q1WkaMGCGJiYlm2yguLpZZs2aJt7e3uLi4yMSJEyU1NdUsJicnR6ZNmyYeHh7i4eEh06ZNk7y8PLOYlJQUCQsLExcXF/H29pZZs2aZtVYQETly5IgMHz5c1Gq1aLVaWbx48U21WhBhYUVERHXz6o9HJXDBJpm8cu9Nf9eQ5dX1+1slwtbhTclgMECj0UCv13O+FRER1ShDX4yQd3airMKELx+/A8O7tLF2Sre8un5/N6s5VkRERAR8sO00yipMGBTkjTs7+1g7HboJLKyIiIiakZScInx3sLI1zwvjut2wxRA1LyysiIiImpH3t55ChUkwslsbDOjgbe106CaxsCIiImomTl4qwPcJaQCA+WO7WTkbqg8WVkRERM3Ee1tOQgSYEKxFcFuNtdOhemBhRURE1AwkXtTjl6RMqFTAc6FdrZ0O1RMLKyIiIisTEby2ORkAcG/ftujq52HljKi+WFgRERFZ2c+JmThwLhfOjnZ4YRznVtkyFlZERERWVFJuxJs/HwMAzAzpDF0rFytnRA3BwoqIiMiKPt19Fmn5xdBpnPH3ER2tnQ41EAsrIiIiK8nQF2PVzjMAgIV394CLk72VM6KGYmFFRERkJW/9chzF5UYM7OCFib39rZ0OWQALKyIiIiuIT8nD9wnpUKmARZNu46NrWggWVkRERE3MZBIs+ekoAODB/u3YDLQFYWFFRETUxDYcTsPvF/VwVztgPtsrtCgsrIiIiJpQYWkF3oo6DgCYPaoz2niorZwRWRILKyIioia0asdpZBeUokNrV8wY1sHa6ZCF1buw2rNnDx5++GEMGTIEaWmVT+L+8ssvsXfvXoslR0RE1JKk5lzBZ3vOAQBeDusJtQPbK7Q09Sqs1q9fj3HjxsHFxQWHDx9GaWkpAKCgoABvvvmmRRMkIiJqKd74ORllRhOGd/HB6B6+1k6HGkG9CqvXX38dq1evxqeffgpHR0dl+dChQ3Ho0CGLJUdERNRS7Dt9Gb8evQR7OxX+NbEn2yu0UPUqrE6cOIERI0ZUW+7p6Yn8/PyG5kRERNSiVBhNWLIpGQAQPjgQXf08rJwRNZZ6FVb+/v44ffp0teV79+5Fx458zhEREdHV1sVdwPHMArRydcTcMV2snQ41onoVVv/4xz/w7LPPYv/+/VCpVEhPT8fXX3+N+fPn4+mnn7Z0jkRERDZLf6Ucy6NPAACeD+2KVq5OVs6IGpNDfd70z3/+E3q9HnfddRdKSkowYsQIqNVqzJ8/H7NmzbJ0jkRERDbr/W0nkXelHF393DH1jvbWTocamUpEpL5vvnLlCpKTk2EymdCzZ0+4u7tbMrcWyWAwQKPRQK/Xw9PT09rpEBFRIzp1qQDj/70HRpPgq8cH4c4uPtZOieqprt/f9Rqx0uv1MBqN8Pb2xoABA5Tlubm5cHBwYMFARES3PBHBkk3JMJoEoT39WFTdIuo1x+pvf/sbIiMjqy3/9ttv8be//a3BSREREdm67cezsOfUZTjZ2+H/7u5h7XSoidSrsNq/fz/uuuuuastHjhyJ/fv3NzgpIiIiW1ZWYcLrm48BAB67MwgdfNysnBE1lXoVVqWlpaioqKi2vLy8HMXFxQ1OioiIyJb9d995nLtcBB93NWaN6mztdKgJ1auwGjhwID755JNqy1evXo3+/fs3OCkiIiJbdbmwFB9sOwUA+Of4bnBX12s6M9moev1tv/HGGxgzZgx+//13jB49GgCwbds2xMXFITo62qIJEhER2ZJ3o0+goLQCvdpq8MDtAdZOh5pYvUashg0bhpiYGLRr1w7ffvstfvrpJ3Tu3BlHjhzB8OHDLZ0jERGRTUhK0yMy7gIAYNGknrCz4/MAbzX1Hp/s27cvvv76a0vmQkREZLNEBEt+SoYIMLmPDgM6eFs7JbKCOhdWBoNB6U9lMBhqjWUfKyIiutX8nJiJA+dz4exohxcndLd2OmQldS6svLy8kJGRAV9fX7Rq1QoqVfXhTRGBSqWC0Wi0aJJERETNWWmFEUujKtsr/GNEJ+hauVg5I7KWOhdW27dvh7d35bDmjh07Gi0hIiIiW/PFvhRcyC2Gn6ca/wjpaO10yIrqXFiFhIQAACoqKrBz50489thjaNeuXaMlRkREZAvyisqwYntle4V5Y7vB1YntFW5lN31XoIODA5YtW8bLfURERAA+2H4KhpIKdNd64H62V7jl1avdwujRo7Fz504Lp0JERGRbzl0uwpcxKQCAl8N6wp7tFW559RqvnDBhAhYuXIikpCT0798fbm7mz0CaPHmyRZIjIiJqzt765TgqTIKR3drgzi4+1k6HmgGViMjNvsnO7voDXbwrsHYGgwEajQZ6vZ5tKYiIbFjc+Vz8dXUM7FRA1NwR6OrnYe2UqBHV9fu7XpcCTSbTdV/1LaoiIiKgUqkwd+5cZZmIYPHixdDpdHBxccHIkSNx9OhRs/eVlpZi9uzZ8PHxgZubGyZPnoyLFy+axeTl5SE8PBwajQYajQbh4eHIz883i0lNTcWkSZPg5uYGHx8fzJkzB2VlZWYxiYmJCAkJgYuLC9q2bYslS5agHnUpERHZOJNJ8PrmyvYKDw1sz6KKFPUqrCwtLi4On3zyCXr37m22/O2338by5cuxcuVKxMXFQavVIjQ0FAUFBUrM3LlzsXHjRkRGRmLv3r0oLCzExIkTzQq8qVOnIiEhAVFRUYiKikJCQgLCw8OV9UajEWFhYSgqKsLevXsRGRmJ9evXY968eUqMwWBAaGgodDod4uLisGLFCixbtgzLly9vxCNDRETN0abEDPx+IR9uTvZ4LrSLtdOh5kTqaevWrRIWFiYdO3aUTp06SVhYmGzZsuWmt1NQUCBdunSRLVu2SEhIiDz77LMiImIymUSr1crSpUuV2JKSEtFoNLJ69WoREcnPzxdHR0eJjIxUYtLS0sTOzk6ioqJERCQ5OVkASGxsrBITExMjAOT48eMiIvLzzz+LnZ2dpKWlKTHr1q0TtVoter1eRERWrVolGo1GSkpKlJiIiAjR6XRiMpnq/Hn1er0AULZLRES2pbisQoZGbJPABZvkg60nrZ0ONZG6fn/Xa8Rq5cqVGD9+PDw8PPDss89izpw58PT0xN13342VK1fe1LaeeeYZhIWFYcyYMWbLz507h8zMTIwdO1ZZplarERISgn379gEA4uPjUV5ebhaj0+kQHBysxMTExECj0WDQoEFKzODBg6HRaMxigoODodPplJhx48ahtLQU8fHxSkxISAjUarVZTHp6Os6fP3/dz1daWgqDwWD2IiIi2/XffeeRll8MracznhjOZqBkrl53BUZEROC9997DrFmzlGVz5szBsGHD8MYbb5gtr01kZCQOHTqEuLi4ausyMzMBAH5+fmbL/fz8kJKSosQ4OTnBy8urWkzV+zMzM+Hr61tt+76+vmYx1+7Hy8sLTk5OZjEdOnSotp+qdUFBQTV+xoiICLz66qs1riMiItuSW1SGlTtOAwDmj+sGFyd7K2dEzU29RqwMBgPGjx9fbfnYsWPrPCJz4cIFPPvss/jqq6/g7Ox83bhrn0kofzyPsDbXxtT2XMOGxMgfE9dry2fhwoXQ6/XK68KFC7XmTkREzdcH206hoKQCPf098Zd+ba2dDjVD9SqsJk+ejI0bN1Zb/sMPP2DSpEl12kZ8fDyysrLQv39/ODg4wMHBAbt27cIHH3wABwcHs9Ggq2VlZSnrtFotysrKkJeXV2vMpUuXqu0/OzvbLOba/eTl5aG8vLzWmKysLADVR9Wuplar4enpafYiIiLbcza7EF/FVl4x+b+wHmwGSjWqV2HVo0cPvPHGGwgLC8Prr7+O119/HRMnTsQbb7yB2267DR988IHyup7Ro0cjMTERCQkJymvAgAGYNm0aEhIS0LFjR2i1WmzZskV5T1lZGXbt2oWhQ4cCAPr37w9HR0ezmIyMDCQlJSkxQ4YMgV6vx4EDB5SY/fv3Q6/Xm8UkJSUhIyNDiYmOjoZarUb//v2VmN27d5u1YIiOjoZOp6t2iZCIiFqepX80Ax3V3RfDOrMZKNWsXg1CrzefqNrGVSqcPXu2ztsdOXIk+vbti/fffx8A8NZbbyEiIgJr1qxBly5d8Oabb2Lnzp04ceIEPDwqe4bMnDkTmzZtwtq1a+Ht7Y358+cjJycH8fHxsLevvPY9YcIEpKen4+OPPwYA/P3vf0dgYCB++uknAJXtFvr27Qs/Pz+88847yM3NxYwZM3DvvfdixYoVAAC9Xo9u3bph1KhReOmll3Dq1CnMmDEDr7zyillbhhthg1AiItuz/2wOHvokFvZ2KkQ9Oxxd2LfqllPX7+96TV4/d+5cvRO7Gf/85z9RXFyMp59+Gnl5eRg0aBCio6OVogoA3nvvPTg4OODBBx9EcXExRo8ejbVr1ypFFQB8/fXXmDNnjnL34OTJk83uXrS3t8fmzZvx9NNPY9iwYXBxccHUqVOxbNkyJUaj0WDLli145plnMGDAAHh5eeH555/H888/3wRHgoiIrMVkErz5c2Uz0L8NbMeiimpVrxGruvL09FQu61EljlgREdmWHxLS8GxkAtyc7LHzhbvQxkN94zdRi9Ooj7Spq0as2YiIiBpdSbkRb0edAADMHNmJRRXdULN4pA0REVFztOa3ymag/hpnPH4nr77QjbGwIiIiqkFOYSlWVTUDHctmoFQ3LKyIiIhq8O9tp1BQWoHbdGwGSnXXqIXVjTqkExERNUdnsgvx9f5UAMD/3d0DdmwGSnXEyetERETXWPrLcRhNgtHdfTGUzUDpJjRqYfXLL7+gbVsOnxIRke2IPZuDLcmXYG+nwsK7u1s7HbIx9WoQer2mmCqVCs7OzujcuTPuuece3HnnnQ1KjoiIqCmZTII3Nlc2A51yRzt09mUzULo59SqsDh8+jEOHDsFoNKJbt24QEZw6dQr29vbo3r07Vq1ahXnz5mHv3r3o2bOnpXMmIiJqFD/8nobEND3c1Q6YO6artdMhG1SvS4H33HMPxowZg/T0dMTHx+PQoUNIS0tDaGgopkyZgrS0NIwYMQLPPfecpfMlIiJqFCXlRrxzVTNQH3c2A6WbV69H2rRt2xZbtmypNhp19OhRjB07FmlpaTh06BDGjh2Ly5cvWyzZloCPtCEiap5W7zqDpb8ch07jjO3zR8LZkX2r6E+N+kgbvV6PrKysasuzs7NhMBgAAK1atUJZWVl9Nk9ERNSkSiuM+M/ecwCA58d2Y1FF9VbvS4GPPfYYNm7ciIsXLyItLQ0bN27E448/jnvvvRcAcODAAXTtyuvTRETU/P30ewayC0qh9XTGPX111k6HbFi9Jq9//PHHeO655/C3v/0NFRUVlRtycMD06dPx3nvvAQC6d++Ozz77zHKZEhERNQIRwWd7zgIAZgzrAEd7PpSE6q9ec6yqFBYW4uzZsxARdOrUCe7u7pbMrUXiHCsioublt9OXMe2z/XB1skfMi6OhcXW0dkrUDNX1+7teI1ZV3N3d0bt374ZsgoiIyKqqRqseHNCORRU1WL0Kq6KiIixduhTbtm1DVlYWTCaT2fqzZ89aJDkiIqLGdDqrADtOZEOlAh4d1sHa6VALUK/C6oknnsCuXbsQHh4Of39/PmyZiIhs0n/2ngcAhPbwQ2BrN+smQy1CvQqrX375BZs3b8awYcMsnQ8REVGTyCksxYZDFwEATwzvaOVsqKWo160PXl5e8Pb2tnQuRERETebr/akorTChd4AGAzt4WTsdaiHqVVi99tpreOWVV3DlyhVL50NERNToSsqN+CLmPADg8TuDOKWFLKZelwLfffddnDlzBn5+fujQoQMcHc3vojh06JBFkiMiImoMP/6ejsuFZfDXOOPuXv7WTodakHoVVlXd1YmIiGyNiOA/eyofXzNjKBuCkmXVq7BatGiRpfMgIiJqEntPX8aJSwVwdbLH3+5ob+10qIVhmU5ERLeUz/4YrXpwQDtoXNgQlCyrziNW3t7eOHnyJHx8fODl5VXrRL/c3FyLJEdERGRJJy8VYNfJyoagjw0LsnY61ALVubB677334OHhAQB4//33GysfIiKiRvP53srRqnE9tWjf2tXK2VBLVOfCavr06TX+mYiIyBZcLizFhsNpAIAnhnO0ihpHnQsrg8FQ543W9tRnIiIia/g6NhVlFSb0adcK/QPZEJQaR50Lq1atWt2wgZqIQKVSwWg0NjgxIiIiSykpN+LL2PMAgCfYEJQaUZ0Lqx07djRmHkRERI3mx4TKhqBtW7lgQrDW2ulQC1bnwiokJKQx8yAiImoUIoLP9p4FUNkQ1IENQakR1bmwOnLkSJ032rt373olQ0REZGl7Tl3GyUuFcHOyx0N3tLN2OtTC1bmw6tu3L1QqFUSk1jjOsSIioubksz9aLDw4sB08ndkQlBpXnQurc+fONWYeREREFnciswC7T2bDTgU8OpQtFqjx1bmwCgwMbMw8iIiILE5pCHobG4JS06j3DL4vv/wSw4YNg06nQ0pKCoDKjuw//PCDxZIjIiKqr+yCUmxMYENQalr1Kqw++ugjPP/887j77ruRn5+vzKlq1aoVH3dDRETNwlexKSirMKFvu1a4vT0bglLTqFdhtWLFCnz66af4v//7P9jb2yvLBwwYgMTERIslR0REVB8l5UZ8FVt5NeWJ4WwISk2nXoXVuXPn0K9fv2rL1Wo1ioqKGpwUERFRQ3x/OA05RZUNQcffxoag1HTqVVgFBQUhISGh2vJffvkFPXv2rPN2PvroI/Tu3Ruenp7w9PTEkCFD8MsvvyjrRQSLFy+GTqeDi4sLRo4ciaNHj5pto7S0FLNnz4aPjw/c3NwwefJkXLx40SwmLy8P4eHh0Gg00Gg0CA8PR35+vllMamoqJk2aBDc3N/j4+GDOnDkoKyszi0lMTERISAhcXFzQtm1bLFmy5IbtJ4iIqGlVNgStnLT+6DA2BKWmVa+z7YUXXsAzzzyD//3vfxARHDhwAG+88QZeeuklvPDCC3XeTkBAAJYuXYqDBw/i4MGDGDVqFO655x6leHr77bexfPlyrFy5EnFxcdBqtQgNDUVBQYGyjblz52Ljxo2IjIzE3r17UVhYiIkTJ5r10po6dSoSEhIQFRWFqKgoJCQkIDw8XFlvNBoRFhaGoqIi7N27F5GRkVi/fj3mzZunxBgMBoSGhkKn0yEuLg4rVqzAsmXLsHz58vocQiIiaiS7TmbjdFYh3NUOeHAgG4JSE5N6+uSTT6R9+/aiUqlEpVJJu3bt5LPPPqvv5hReXl7y2WeficlkEq1WK0uXLlXWlZSUiEajkdWrV4uISH5+vjg6OkpkZKQSk5aWJnZ2dhIVFSUiIsnJyQJAYmNjlZiYmBgBIMePHxcRkZ9//lns7OwkLS1NiVm3bp2o1WrR6/UiIrJq1SrRaDRSUlKixERERIhOpxOTyVTnz6fX6wWAsl0iIrKshz+LlcAFm2TJT0etnQq1IHX9/q7XiFVxcTGmTZuGlJQUZGVlITY2Fs899xwCAgLqXeAZjUZERkaiqKgIQ4YMwblz55CZmYmxY8cqMWq1GiEhIdi3bx8AID4+HuXl5WYxOp0OwcHBSkxMTAw0Gg0GDRqkxAwePBgajcYsJjg4GDqdTokZN24cSktLER8fr8SEhIRArVabxaSnp+P8+fP1/txERGQ5xzMN2HPqMuxUlc8FJGpq9Sqs7rnnHnzxxRcAAAcHB0yePBnLly/Hvffei48++uimtpWYmAh3d3eo1Wo89dRT2LhxI3r27InMzEwAgJ+fn1m8n5+fsi4zMxNOTk7w8vKqNcbX17fafn19fc1irt2Pl5cXnJycao2p+rkqpialpaUwGAxmLyIiahz/2VM5t2pCsD/aebMhKDW9ehVWhw4dwvDhwwEA/+///T/4+fkhJSUFX3zxBT744IOb2la3bt2QkJCA2NhYzJw5E9OnT0dycrKy/tpbZEXkhrfNXhtTU7wlYuSPieu15RMREaFMmtdoNGjXjtf7iYgaQ1ZBCX5ISAcAPM6GoGQl9Sqsrly5Ag8PDwBAdHQ07rvvPtjZ2WHw4MFKF/a6cnJyQufOnTFgwABERESgT58++Pe//w2ttvL22GtHg7KyspSRIq1Wi7KyMuTl5dUac+nSpWr7zc7ONou5dj95eXkoLy+vNSYrKwtA9VG1qy1cuBB6vV55XbhwofYDQkRE9fJVTArKjCbc3p4NQcl66lVYde7cGd9//z0uXLiAX3/9VZnjlJWVBU9PzwYlJCIoLS1FUFAQtFottmzZoqwrKyvDrl27MHToUABA//794ejoaBaTkZGBpKQkJWbIkCHQ6/U4cOCAErN//37o9XqzmKSkJGRkZCgx0dHRUKvV6N+/vxKze/dusxYM0dHR0Ol06NChw3U/j1qtVtpJVL2IiMiy9FfKsWbfeQDAE8M7WjcZurXVZ2b8d999J46OjmJnZyehoaHK8jfffFPGjx9f5+0sXLhQdu/eLefOnZMjR47ISy+9JHZ2dhIdHS0iIkuXLhWNRiMbNmyQxMREmTJlivj7+4vBYFC28dRTT0lAQIBs3bpVDh06JKNGjZI+ffpIRUWFEjN+/Hjp3bu3xMTESExMjPTq1UsmTpyorK+oqJDg4GAZPXq0HDp0SLZu3SoBAQEya9YsJSY/P1/8/PxkypQpkpiYKBs2bBBPT09ZtmzZTR073hVIRGR5b/1yTAIXbJJx7+0So7Hud2oT1VVdv7/r3W4hIyNDDh06JEajUVm2f/9+OXbsWJ238dhjj0lgYKA4OTlJmzZtZPTo0UpRJSJiMplk0aJFotVqRa1Wy4gRIyQxMdFsG8XFxTJr1izx9vYWFxcXmThxoqSmpprF5OTkyLRp08TDw0M8PDxk2rRpkpeXZxaTkpIiYWFh4uLiIt7e3jJr1iyz1goiIkeOHJHhw4eLWq0WrVYrixcvvqlWCyIsrIiILC3LUCLdX/5FAhdskl+TMqydDrVQdf3+VomwdXhTMhgM0Gg00Ov1vCxIRGQBr/50FGt+O48+7Vrh+6eH8rmA1Cjq+v3NPv9ERGSz0vOL8XVsKgBg/tiuLKrI6lhYERGRzVqx/TTKjCbcEeSNOzv7WDsdIhZWRERkm1JyivDdwcoWNi+M68bRKmoWWFgREZFNen/rKVSYBCFd22BgB29rp0MEgIUVERHZoJOXCvB9QhoAYP7YblbOhuhPLKyIiMjmLI8+CRFg/G1a9ArQWDsdIgULKyIisimJF/WIOpoJlQp4fmxXa6dDZIaFFRER2ZRl0ScAAPf2bYuufh5WzobIHAsrIiKyGXHnc7HrZDYc7FSYO6aLtdMhqoaFFRER2QQRwTu/Vo5W/XVAOwS2drNyRkTVsbAiIiKbsOfUZRw4lwsnBzvMGd3Z2ukQ1YiFFRERNXsignf/mFv18KBA+GtcrJwRUc1YWBERUbO3JfkSfr+oh4ujPZ6+q5O10yG6LhZWRETUrJlMguVbTgIAHh3WAT7uaitnRHR9LKyIiKhZ++lIOo5nFsDD2QH/GMHRKmreWFgREVGzVWE04f2tpwAAfx/eERpXRytnRFQ7FlZERNRsrT90EecuF8HbzQmP3hlk7XSIboiFFRERNUulFUZ8sO00AODpkZ3grnawckZEN8bCioiImqV1+1ORll8MP081Hh4caO10iOqEhRURETU7V8oqsHLHGQDA7FFd4Oxob+WMiOqGhRURETU7/92XgsuFpWjn7YIHB7SzdjpEdcbCioiImhVDSTlW76ocrZo7uiucHPhVRbaDZysRETUr/9lzDvricnT2dce9/dpaOx2im8LCioiImo28ojL8Z+85AMDzoV1hb6eyckZEN4eFFRERNRurd51BYWkFevp7YvxtWmunQ3TTWFgREVGzkGUowX9jzgMA5o/rCjuOVpENYmFFRERWV1phxOubj6Gk3ITb27fCXd18rZ0SUb2wjS0REVnVwfO5WLD+CM5kFwEAXhjXHSoVR6vINrGwIiIiqygoKcfbUSfwZWwKAMDHXY3X770NQzq1tnJmRPXHwoqIiJrctmOX8PL3ScjQlwAAHhrQDi/d3QMaV0crZ0bUMCysiIioyWQXlOLVn45i05EMAEBga1dE/KUXhnb2sXJmRJbBwopahNIKI9b8dh53B/ujfWtXa6dDRNcQEfy/+It4ffMx6IvLYW+nwhPDgzB3dFe4OPE5gNRysLCiFuGr2FQs/eU44lPy8OkjA6ydDhFdJTXnCl7amIi9py8DAHr6e+LtB3ojuK3GypkRWR4LK2oRYs7kAADiU/IgIryjiKgZqDCasHbfebwbfRLF5UaoHezwXGhXPH5nEBzt2e2HWiYWVmTzTCZB3PlcAEBuURku5hWjnTcvBxJZU3K6AS9uOIIjF/UAgMEdvRFxX28E+bhZOTOixsXCimzeqaxC6IvLlZ8PX8hnYUVkJSXlRqzYfgof7zqLCpPAw9kBL4f1wIMD2nEkmW4JLKzI5h34Y7Sqyu8X8jG5j85K2RDdug6ez8U//98RnL1c2ehzQrAWr06+Db6ezlbOjKjpsLAim3fgXGVh1dHHDWcvFyHhQr51EyK6BcWdz8W0z/ajrMIEXw81ltwTjPHBfIgy3Xo4e5Bsmogg7o/C6vHhQQCApDQ9yo0ma6ZFdEs5nVWAJ/57EGUVJtzVrQ22PB/CoopuWSysyKZdyC1GpqEEjvYq/KVfW3g6O6C0woQTmQXWTo3olnDJUILpn8dBX1yOfu1bYdW0/tC4sHs63bpYWJFNq5pf1autBq5ODujTrhWAygnsRNS4DCXlmP75AaTlF6Ojjxv+M30gm33SLc+qhVVERAQGDhwIDw8P+Pr64t5778WJEyfMYkQEixcvhk6ng4uLC0aOHImjR4+axZSWlmL27Nnw8fGBm5sbJk+ejIsXL5rF5OXlITw8HBqNBhqNBuHh4cjPzzeLSU1NxaRJk+Dm5gYfHx/MmTMHZWVlZjGJiYkICQmBi4sL2rZtiyVLlkBELHdQ6KZUXQYcGOQNAOj7R2GVkJpvpYyIbg1lFSY89WU8jmcWwMddjf8+dge83ZysnRaR1Vm1sNq1axeeeeYZxMbGYsuWLaioqMDYsWNRVFSkxLz99ttYvnw5Vq5cibi4OGi1WoSGhqKg4M9LPXPnzsXGjRsRGRmJvXv3orCwEBMnToTRaFRipk6dioSEBERFRSEqKgoJCQkIDw9X1huNRoSFhaGoqAh79+5FZGQk1q9fj3nz5ikxBoMBoaGh0Ol0iIuLw4oVK7Bs2TIsX768kY8UXU/ViNWgawqr3y/mWykjopbPZBK88P9+x74zOXBzssfaRweyxQlRFWlGsrKyBIDs2rVLRERMJpNotVpZunSpElNSUiIajUZWr14tIiL5+fni6OgokZGRSkxaWprY2dlJVFSUiIgkJycLAImNjVViYmJiBIAcP35cRER+/vlnsbOzk7S0NCVm3bp1olarRa/Xi4jIqlWrRKPRSElJiRITEREhOp1OTCZTnT6jXq8XAMo2qf4uGYolcMEm6fDiJsm/UiYiItkFJcoyfXGZlTMkapne3JwsgQs2SaeFm2XXiSxrp0PUJOr6/d2s5ljp9ZUder29K0cfzp07h8zMTIwdO1aJUavVCAkJwb59+wAA8fHxKC8vN4vR6XQIDg5WYmJiYqDRaDBo0CAlZvDgwdBoNGYxwcHB0On+7H80btw4lJaWIj4+XokJCQmBWq02i0lPT8f58+dr/EylpaUwGAxmL7KMg+fzAADd/DyUybI+7moEeLlABEj8o+MzEVnO53vP4ePdZwEAb93fGyO6trFyRkTNS7MprEQEzz//PO68804EBwcDADIzMwEAfn5+ZrF+fn7KuszMTDg5OcHLy6vWGF9f32r79PX1NYu5dj9eXl5wcnKqNabq56qYa0VERCjzujQaDdq1a3eDI0F1VdW/quoyYBVlnhUnsBNZ1M+JGXhtczIA4IVx3XB//wArZ0TU/DSbwmrWrFk4cuQI1q1bV23dtY9BkDo8ZPfamJriLREjf0xcv14+CxcuhF6vV14XLlyoNW+quwPXTFyvUlVYHeYEdiKL2X82B3P/lwARIHxwIJ4e2cnaKRE1S82isJo9ezZ+/PFH7NixAwEBf/4GpNVWNpi7djQoKytLGSnSarUoKytDXl5erTGXLl2qtt/s7GyzmGv3k5eXh/Ly8lpjsrKyAFQfVauiVqvh6elp9qKGM5SU41hm5WXVOzpcf8RKeMcmUYOdvFSAJ7+obAA6tqcfFk++jc/9I7oOqxZWIoJZs2Zhw4YN2L59O4KCgszWBwUFQavVYsuWLcqysrIy7Nq1C0OHDgUA9O/fH46OjmYxGRkZSEpKUmKGDBkCvV6PAwcOKDH79++HXq83i0lKSkJGRoYSEx0dDbVajf79+ysxu3fvNmvBEB0dDZ1Ohw4dOljoqFBdxJ/PgwjQobVrteeQBbfVwN5OhcuFpUjXl1gpQ6KWIUNfjOmfH4ChpAL9A73wwZR+sLdjUUV0PVYtrJ555hl89dVX+Oabb+Dh4YHMzExkZmaiuLgYQOXltblz5+LNN9/Exo0bkZSUhBkzZsDV1RVTp04FAGg0Gjz++OOYN28etm3bhsOHD+Phhx9Gr169MGbMGABAjx49MH78eDz55JOIjY1FbGwsnnzySUycOBHdunUDAIwdOxY9e/ZEeHg4Dh8+jG3btmH+/Pl48sknlVGmqVOnQq1WY8aMGUhKSsLGjRvx5ptv4vnnn+dvb02sqs3CwGtGqwDA2dEe3bUeANjPiqgh9MXlmPF5HDL0JejUxg2fPTIAzo5sAEpUq0a+O7FWAGp8rVmzRokxmUyyaNEi0Wq1olarZcSIEZKYmGi2neLiYpk1a5Z4e3uLi4uLTJw4UVJTU81icnJyZNq0aeLh4SEeHh4ybdo0ycvLM4tJSUmRsLAwcXFxEW9vb5k1a5ZZawURkSNHjsjw4cNFrVaLVquVxYsX17nVggjbLVjK/at+k8AFm+TbuNQa17+04YgELtgkb2xObuLMiFqGkvIKeejjfRK4YJMMeH2LpOYUWTslIquq6/e3SoSTUJqSwWCARqOBXq/nfKt6Kik3otfiX1FuFOx6YSQCW7tVi/nu4AW88P+O4I4O3vj2qSFWyJLIdplMgjmRh7HpSAbc1Q743z8G4zadxtppEVlVXb+/m8XkdaKbkXAhH+VGga+HGu2v0+25agJ7YpoeFUZTE2ZHZPsifjmGTUcy4GCnwuqH+7OoIroJLKzI5lQ9H/COIO/rzm3r1MYdHmoHFJcbcfJSYVOmR2TTPttzFp/uOQcAeOevvXFnFx8rZ0RkW1hYkc2pmrh+R1D1ietV7OxU6N2u8rdsNgolqpuffk/H65uPAQBenNAdf+nHBqBEN4uFFdmUCqMJh1Iqe5bVdEfg1foEtAIA/M7CiuiGjlzMx7zvfgcAzBjaAf8Y0dHKGRHZJhZWZFOSMwwoKjPC09kB3fw8ao3lo22I6iavqAwzvzqEsgoTxvTwxb8m9mQLGaJ6YmFFNkV5jE0Hb9jdoElhVWF1MqsAhaUVjZ0akU0ymgTP/i8BafnFCGztincf7MsGoEQNwMKKbMr1ng9YE19PZ+g0zhABEi/qGzs1Ipv0760nsftkNpwd7bD64f7QuDhaOyUim8bCimyGiCCuDhPXr9a3fSsAvBxIVJNtxy7hg+2nAQAR9/VCD3/21iNqKBZWZDNOZxUi70o5nB3tEFzHvjqcwE5Us9ScK3jufwkAgEeGBPIOQCILYWFFNqOqzUK/dl5wcqjbqcsJ7ETVlZQb8dRX8TCUVKBf+1Z4OayntVMiajFYWJHNuLoxaF31CtDATgVkGkqQqS9prNSIbIaI4P82JiE5w4DWbk5YNe32Ov+iQkQ3xv+byGYcqEdh5erkgK5/tGXgqBUR8M2BVKw/dBF2KmDFlH7w17hYOyWiFoWFFdmEi3lXkK4vgYOdCv3+mJBeV/04gZ0IQOX/A6/+mAwAeGFcdwztzMfVEFkaCyuyCVWjVcFtNXB1crip91ZNYE+4kGfptIhsRm5RGZ7+Kh5lRhPG9vTDUyHsrE7UGFhYkU242TYLV6tquZB4UQ+jSSyZFpFNMJoEc9YdRrq+BEE+blj2YB92VidqJCysyCZc3XH9ZnXx9YCrkz2Kyow4nVVo6dSImr33tpzE3tOX4eJoj9UP94enM5uAEjUWFlbU7F0uLMWZ7CIAwMAOXjf9fns7FXq1rex7xX5WdKvZknwJK3dUNgFden8vdNPW/oxNImoYFlbU7B384zJgNz8PtHJ1qtc2qi4HHmZhRbeQ85eL8Py3CQCAGUM74J6+ba2bENEtgIUVNXsHzlVOOh8YdPOjVVX6sVEo3WKKyyqbgBaUVOD29q3w0t09rJ0S0S2BhRU1ewfO5wAA7ghqXe9t9PmjsDp5qQBXyioskRZRs1XZBDQRxzML4OPuhFXT+rMJKFET4f9p1KwVlJQjOd0AALijHhPXq/hrXODnqYbRJEhKM1gqPaJm6av9qdhwOA32diqsmHI7tBpna6dEdMtgYUXN2qHUfJgEaO/t2uAvB/azolvBodQ8LPnpKABgwfhuGNKp/iO9RHTzWFhRs3bgXOVlwPq0WbhW1QT23y/oG7wtoubocmEpnvn6EMqNggnBWjw5nE1AiZoaCytq1uL+mLh+RwMmrlfpywns1IJdzLuCp78+hAx9CTq2ccPbD/RmE1AiK7i5Z4MQNaGSciMSLuYDaNjE9Sq92mqgUgFp+cXIKiiBrwfnnZDtO5tdiI92nsHGw2moMAlcnSqbgHqwCSiRVbCwombryEU9yipM8HFXo0Nr1wZvz8PZEV183XHyUiF+v6BHaE8WVmS7jmUY8OGO0/g5MQNVT2oa1rk1/jmuO7r6sQkokbWwsKJm68/nA3pZ7JJG33atcPJSIRIu5CG0p59FtknUlBIu5GPl9tPYeuySsmxMD188fVdn3N6+4ZfMiahhWFhRs1X1fMCGtFm4Vp92rfDtwYucwE42RUSw/1wuPtxxGntOXQYAqFTA3b388czIzuip87RyhkRUhYUVNUtGkyA+parjuuUKq6oJ7L9fyIfJJLCz4+Rear5EBDtPZuPD7adx8I//H+ztVLi3b1vMHNkJnX3drZwhEV2LhRU1S8cyDCgsrYCH2gHdtZb7bbybnwecHe1QUFqBs5cL0dmXc1Go+TGZBNHJmVi547TS0NbJ3g4PDgzAP0Z0Qjvvhs85JKLGwcKKmqWqy4ADOnjB3oKjSg72dujVVoO483lIuKBnYUXNSoXRhE1HMvDhjtM4lVUIAHBxtMe0Qe3x5IiO8PPkDRdEzR0LK2qWqgorS14GrNK3Xas/Cqs8PNA/wOLbJ7pZIoJfkjLxdtRxnM+5AgDwUDtgxrAOeHRYELzdnKycIRHVFQsranZE5M87Ai04cb1KHzYKpWYk4UI+Xt+UrMyh8nZzwuN3BiF8SCA82YuKyOawsKJm5+zlIuQUlUHtYIdeARqLb79qAvvxjAKUlBvh7Ghv8X0Q3UhafjHejjqOHxLSAVRe8vv7iI74+4iOcFPzn2YiW8X/e6nZqboM2LddK6gdLF/0tG3lAh93NS4XluJouh79Ay0/KkZ0PQUl5fho5xn8Z+85lFaYoFIB998egPljuzX4QeNEZH0srKjZiavqX9UI86sAQKVSoW87DbYey0LCBRZW1DQqjCZ8e/Ailm85gcuFZQCAwR298XJYTwS3tfzILBFZBwsranb2N3JhBVSOhlUWVvmNtg+iKrtPZuONzcdw4lIBACDIxw0LJ3RHaE8/PiiZqIVhYUXNSnp+MdLyi2Fvp2rUx3P8OYE9r9H2QXTyUgHe2HwMu05mAwA0Lo6YO6YLpg0KhJODnZWzI6LGwMKKmpWquwFv03k26gTe3gGtAAAXcouRU1iK1u7qRtsX3XouF5bivS0nse5AKkwCONqr8MiQDpg9qjNaubJ1AlFLxsKKmpX9jfB8wJpoXBzRqY0bzmQX4feL+RjVnQ9kpoYrKTfi89/OYdWOMygsrQAAjL9NixcndEcHHzcrZ0dETYGFFTUrcY3YGPRafdq1wpnsIiSksrCihhER/HQkA2/9chxp+cUAgF5tNXg5rAcGdWxt5eyIqClZ9SL/7t27MWnSJOh0OqhUKnz//fdm60UEixcvhk6ng4uLC0aOHImjR4+axZSWlmL27Nnw8fGBm5sbJk+ejIsXL5rF5OXlITw8HBqNBhqNBuHh4cjPzzeLSU1NxaRJk+Dm5gYfHx/MmTMHZWVlZjGJiYkICQmBi4sL2rZtiyVLlkBELHY8bnW5RWXKYzwGNvKIFQD0q5pndVHf6Puixncx7wpWbj+FE5kFTbrf+JQ83PfRPsxZdxhp+cXw1zjjvYf64IdnhrGoIroFWbWwKioqQp8+fbBy5coa17/99ttYvnw5Vq5cibi4OGi1WoSGhqKg4M9/OOfOnYuNGzciMjISe/fuRWFhISZOnAij0ajETJ06FQkJCYiKikJUVBQSEhIQHh6urDcajQgLC0NRURH27t2LyMhIrF+/HvPmzVNiDAYDQkNDodPpEBcXhxUrVmDZsmVYvnx5IxyZW1PV/Kouvu5N8giPvu0qJ8f/fiGfBbKNO51VgPtW7cOy6JMY9/5u/P2LgzhyMb9R93kh9wpmfXMI93+0D4dT8+HqZI95oV2xfd5I/KVfAOws+IxLIrIh0kwAkI0bNyo/m0wm0Wq1snTpUmVZSUmJaDQaWb16tYiI5Ofni6Ojo0RGRioxaWlpYmdnJ1FRUSIikpycLAAkNjZWiYmJiREAcvz4cRER+fnnn8XOzk7S0tKUmHXr1olarRa9Xi8iIqtWrRKNRiMlJSVKTEREhOh0OjGZTHX+nHq9XgAo26U/vfbTUQlcsEkWbjjSJPsrLTdKl//7WQIXbJKz2YVNsk+yvKNperl9SbQELtgk/V+Llg4vbpLABZWvhz+Lldgzly26P31xmbz5c7J0eany3Onw4ib553e/yyV9sUX3Q0TNS12/v5vt/b7nzp1DZmYmxo4dqyxTq9UICQnBvn37AADx8fEoLy83i9HpdAgODlZiYmJioNFoMGjQICVm8ODB0Gg0ZjHBwcHQ6XRKzLhx41BaWor4+HglJiQkBGq12iwmPT0d58+fv+7nKC0thcFgMHtRzRrz+YA1cXKwQ7DOEwDbLtiqIxfzMeXTWOQUlSG4rSeinwvBludG4L5+bWFvp8KeU5fx0CexeHB1DHadzG7QyGSF0YQvY1Mw8p2d+HjXWZQZTRjWuTU2zx6Otx7oDV9Pdk0nIitfCqxNZmYmAMDPz3xSsZ+fn7IuMzMTTk5O8PLyqjXG19e32vZ9fX3NYq7dj5eXF5ycnGqNqfq5KqYmERERytwujUaDdu3a1f7Bb1FFpRVISq8sOhuzMei1lH5WqflNtk+yjIPnczHt0/3QF5ejX/tW+PqJwfB2c0JnXw8sf6gvdswbiamD2sPJ3g4Hzudi+ucHMHnlb4hKyoTJVPcCS0Sw43gWxv97D/71fRJyi8rQqY0bPp8xAF89Pgg9/yjOiYgAG7gr8NquxCJyw07F18bUFG+JmKrffmvLZ+HChXj++eeVnw0GA4urGsSn5MFoErRt5QJdK5cm229fTmC3SftOX8bj/z2I4nIjBgV54z8zBsL9mr5n7Vu74s2/9MKcUV3wye6z+OZAChLT9Hjqq3h09XPHM3d1RlgvfzjYX//3y+OZBryx+Rj2nLoMAPBydcRzoV0x5Y72cKzlfUR062q2hZVWqwVQORrk7++vLM/KylJGirRaLcrKypCXl2c2apWVlYWhQ4cqMZcuXaq2/ezsbLPt7N+/32x9Xl4eysvLzWKuHZnKysoCUH1U7Wpqtdrs8iGZyyksxX/2nsOXMSkAgEFNOFoFAP3+mMB+LN2A0gpjozz0mSxr54ks/OPLeJRWmDC8iw8+CR8AF6fr/71pNc54ZVJPPHNXJ3z+2zl8sS8FJy8V4tnIBCzfchIzQzrhvtsDzDqhZxWU4L0tJ/G/uAswCeBkb4dHh3XA03d1hsbFsSk+JhHZqGb7K1dQUBC0Wi22bNmiLCsrK8OuXbuUoql///5wdHQ0i8nIyEBSUpISM2TIEOj1ehw4cECJ2b9/P/R6vVlMUlISMjIylJjo6Gio1Wr0799fidm9e7dZC4bo6GjodDp06NDB8geghcvUl2DJT8kY9tZ2rNp5BgWlFejm54G5Y7o2aR7tvF3g7eaEMqMJyemc/9bc/Xo0E09+cRClFSaM6eGLTx+pvai6Wmt3NV4Y1x17XxyFeaFd4eXqiJScK3hxQyJGvrMDa387h/wrZVi5/RTuemcn1h2oLKrCevlj6/MhWHh3DxZVRHRDKmnIbM4GKiwsxOnTpwEA/fr1w/Lly3HXXXfB29sb7du3x1tvvYWIiAisWbMGXbp0wZtvvomdO3fixIkT8PDwAADMnDkTmzZtwtq1a+Ht7Y358+cjJycH8fHxsLev/Ad3woQJSE9Px8cffwwA+Pvf/47AwED89NNPACrbLfTt2xd+fn545513kJubixkzZuDee+/FihUrAAB6vR7dunXDqFGj8NJLL+HUqVOYMWMGXnnlFbO2DDdiMBig0Wig1+vh6Xnrzc1IzbmCj3adwfr4iygzmgAAfQI0eOauzhjTw88qt6g/uuYAdpzIxuJJPTFjWFCT75/q5qff0zH3fwkwmgRhvfzx3kN9G/S8vaLSCqw7kIpPdp9FVkEpAEClAqr+RezTrhX+FdYDA5roZgoiat7q/P3duDcn1m7Hjh0CoNpr+vTpIlLZcmHRokWi1WpFrVbLiBEjJDEx0WwbxcXFMmvWLPH29hYXFxeZOHGipKammsXk5OTItGnTxMPDQzw8PGTatGmSl5dnFpOSkiJhYWHi4uIi3t7eMmvWLLPWCiIiR44ckeHDh4tarRatViuLFy++qVYLIrduu4VTlwzyXORh6bhws3Ir/IOr98nuk1k3fQwt7f0tJyVwwSZ5dt0hq+ZB1/dtXKoE/dFG4bnIw1JeYbTYtovLKuTLmPMyNGKbBC7YJEMjtsn3hy+K0Wjd85KImpe6fn9bdcTqVnSrjVglpenx4Y7TiDqaqYwEhHRtg1mjOjdJd/W62HkiCzPWxCHIxw075o+0djp0jS9jU/Cv75MAAFPuaI837g1ulJHNcqMJRy7m4zadBs6OnGtHRObq+v3dbCevk22LT8nFyu2nseNEtrJs3G1+mHVXF/QK0Fgxs+qq7gw8d7kI+VfK0Mq18bu+U918tucsXt98DAAwY2gHLJrU84Z3BdeXo70d+gc2j2KfiGwXCyuyGBHBvjM5WLH9FGLPVjb7tFMBk/vo8PRdndHVz8PKGdaslasTgnzccO5yERIu5GNkt+p9z6jprdx+CsuiTwIAZo7shH+O69ZoRRURkaWwsKIGExFsO5aFlTtOI+FCPgDA0V6F+28PwFMhndDBx826CdZBnwANzl0uwu8X9Cys6iG7oBSbj6TjTHYRAlu7orOvOzr7ukOncbnpy3YigmXRJ/DhjjMAgOdDu2L2qM4sqojIJrCwonozmgQ/J2bgwx2ncTyz8sHYagc7TLmjPf4+omOTNvpsqL7tWuH7hHSsP3QRw7v64Pb2Xjd+0y2uoKQc0Ucv4Yff0/Hb6csw1tDN3MXRHp183dC5jbtSbHX2dUdga7caG2yKCF7ffAz/2XsOAPDS3d3x9xGdGv2zEBFZCievN7GWMHm93GjC94fT8NHOMzh7uQgA4K52wMODA/H4nUFo42F7DVEz9SUI+2APcooq+5RNuaMd/jmuO7zcON/qamUVJuw8kYUffk/H1uRLKK0wKev6tmuFQUHeuJB3BaezCnHuchHKjTX/8+JgpzIb2ers647ObTwQGZeKr/enAgBenXwbpg/t0BQfi4johur6/c3CqonZcmFVUm7Ed/EXsXrnGaTlFwMANC6OeGxYEGYM7QCNq203T8wpLMXSX47ju/iLACofX7JwQg880D/AKv21mguTSbD/XC5+/D0NPydmQl9crqzr2MYN9/Zti8l9dNUu+VYYTUjJrSyyTmcV4kxWIU5nV/63qMx43f2pVMDS+3rhoYHtG+0zERHdLBZWzZQtFlZFpRX4Zn8qPt3zZyNFH3c1nhwehGmDA6s9o83WxZ3Pxcsbk3DiUuXlzQGBXnjt3mD08LeNvy9LEBEkZxjwQ0I6fkxIR6ahRFnn56nG5D463NO3LW7Ted703CcRQYa+RCm4TmcX4vSlyv+KCBZPvg339G1r6Y9ERNQgLKyaKVsqrPTF5fhi33l8/ts55F2pHKVo28oF/wjpiAcHtGvRvX7KjSas/e083tt6ElfKjLC3U+HRoR0wN7Rriyskr5aacwU/JKThh9/TcTqrUFnu6eyAu3v5Y3JfHQYFtYZ9I43gSR0esk5EZA0srJopWyisrn4wckFpBQCgQ2tXPD2yM+7t17ZBjxGxNRn6Yry2KRk/J1Y+gNvPU41XJt6Gu3tpbb4AyL9ShqPpBhxN1//xX4NZMeXkYIcxPXxxT9+2GNmtDR9QTUS3NBZWzVRzLqwy9SX4ZPdZfHMgBSXllZOSu/l54JlRnRHWy7/RRilswc4TWVj041Gk5FwBAAzv4oMl9wQjyAZaSYgILhlKcTRdj6S0PwupqnlyV7NTAcM6++Cevm0x7jY/eDjb9rw5IiJLYWHVTDXHwqo5Phi5OSopN2L1rjNYtfMMyipMcLK3w1MjO+HpkZ1u+rJoaYUR5y4XKfOMTv0xubvMaILGxRGezo6V/3VxuOrPjso6TxcH5c8ezg5w+KN1gckkSMm9ohRPSWl6JKcblLsdr9Xe2xW36Tz/eGnQO0CD1u62d1cnEVFjY2HVTDWnwup0VgFW7TiDH35PV3oQ3RHkjdmjOuPOzj42f6mrsZy7XIRFPx7F7pOVj+sJbO2KxZNvw101NBYtKCk3m6R95o8/p+ZeQQ1tn+rNXe0AT2cHGEoqUPjH5dur2amAzr7uuE2nUYqonjpPaFw4IkVEVBcsrJqp5lBY2cKDkZs7EcEvSZlY8lOycsfchGAthnZq/eedblmFuGQove42PJ0dzPs4+brD1ckB+uJyGIrLYSip+PPPxeUwlJT/8fMfy0vKcaWGtgVODnboofVAT6WI8kR3rSdcnDhHioiovlhYNVPWLKxs6cHItqKwtAL/3noSn/92vsbO4wDg66G+phFm5X/beKgbPCpYVmFCQcmfRZiLoz06tqm5qzkREdUfC6tmqqkLq6oHI6/cfhoxZ3MA2MaDkW3N8UwDVmw7jeJyI7r4uqPTH0VUpzbuvNxGRNQC1PX7u+U25LnFtYQHI9uS7lpPfDjtdmunQUREVsbCqoUxmgS/JGVg5XbbfzAyERGRrWFh1UIoD0bedQZnsysfjOzmZI/wIR1s9sHIREREtoaFVQtwpawC49/fg9TcyuaVLenByERERLaEhVUL4OrkgOC2nrhSZmyxD0YmIiKyBfz2bSEWT74Nns6OLfrByERERM0dC6sWwtfD2dopEBER3fLYRZCIiIjIQlhYEREREVkICysiIiIiC2FhRURERGQhLKyIiIiILISFFREREZGFsLAiIiIishAWVkREREQWwsKKiIiIyEJYWBERERFZCAsrIiIiIgthYUVERERkISysiIiIiCzEwdoJ3GpEBABgMBisnAkRERHVVdX3dtX3+PWwsGpiBQUFAIB27dpZORMiIiK6WQUFBdBoNNddr5IblV5kUSaTCenp6fDw8IBKpbJ2Os2KwWBAu3btcOHCBXh6elo7HZvD49dwPIYNw+PXcDyGDdOYx09EUFBQAJ1OBzu768+k4ohVE7Ozs0NAQIC102jWPD09+Q9KA/D4NRyPYcPw+DUcj2HDNNbxq22kqgonrxMRERFZCAsrIiIiIgthYUXNhlqtxqJFi6BWq62dik3i8Ws4HsOG4fFrOB7DhmkOx4+T14mIiIgshCNWRERERBbCwoqIiIjIQlhYEREREVkICysiIiIiC2FhRRaze/duTJo0CTqdDiqVCt9//73Z+kuXLmHGjBnQ6XRwdXXF+PHjcerUKbOYM2fO4C9/+QvatGkDT09PPPjgg7h06ZJZTIcOHaBSqcxeL774YmN/vEYXERGBgQMHwsPDA76+vrj33ntx4sQJsxgRweLFi6HT6eDi4oKRI0fi6NGjZjGlpaWYPXs2fHx84ObmhsmTJ+PixYtmMXl5eQgPD4dGo4FGo0F4eDjy8/Mb+yM2uqY8hi3xPLTU8fvkk08wcuRIeHp6QqVS1Xhu8Rxs+DHkOVjz8cvNzcXs2bPRrVs3uLq6on379pgzZw70er3ZdhrrHGRhRRZTVFSEPn36YOXKldXWiQjuvfdenD17Fj/88AMOHz6MwMBAjBkzBkVFRcr7x44dC5VKhe3bt+O3335DWVkZJk2aBJPJZLa9JUuWICMjQ3m9/PLLTfIZG9OuXbvwzDPPIDY2Flu2bEFFRQXGjh2rHB8AePvtt7F8+XKsXLkScXFx0Gq1CA0NVZ5BCQBz587Fxo0bERkZib1796KwsBATJ06E0WhUYqZOnYqEhARERUUhKioKCQkJCA8Pb9LP2xia8hgCLe88tNTxu3LlCsaPH4+XXnrpuvviOdjwYwjwHKzp+KWnpyM9PR3Lli1DYmIi1q5di6ioKDz++ONm+2q0c1CIGgEA2bhxo/LziRMnBIAkJSUpyyoqKsTb21s+/fRTERH59ddfxc7OTvR6vRKTm5srAGTLli3KssDAQHnvvfca/TNYW1ZWlgCQXbt2iYiIyWQSrVYrS5cuVWJKSkpEo9HI6tWrRUQkPz9fHB0dJTIyUolJS0sTOzs7iYqKEhGR5ORkASCxsbFKTExMjACQ48ePN8VHazKNdQxFbo3zsD7H72o7duwQAJKXl2e2nOdgw4+hCM/BKrUdvyrffvutODk5SXl5uYg07jnIEStqEqWlpQAAZ2dnZZm9vT2cnJywd+9eJUalUpk1dnN2doadnZ0SU+Wtt95C69at0bdvX7zxxhsoKytrgk/RtKqGrb29vQEA586dQ2ZmJsaOHavEqNVqhISEYN++fQCA+Ph4lJeXm8XodDoEBwcrMTExMdBoNBg0aJASM3jwYGg0GiWmpWisY1ilpZ+H9Tl+dcFzsOHHsArPwbodP71eD09PTzg4VD4iuTHPQT6EmZpE9+7dERgYiIULF+Ljjz+Gm5sbli9fjszMTGRkZACoPKnd3NywYMECvPnmmxARLFiwACaTSYkBgGeffRa33347vLy8cODAASxcuBDnzp3DZ599Zq2PZ3Eigueffx533nkngoODAQCZmZkAAD8/P7NYPz8/pKSkKDFOTk7w8vKqFlP1/szMTPj6+lbbp6+vrxLTEjTmMQRa/nlY3+NXFzwHG34MAZ6DV6vt+OXk5OC1117DP/7xD2VZY56DLKyoSTg6OmL9+vV4/PHH4e3tDXt7e4wZMwYTJkxQYtq0aYPvvvsOM2fOxAcffAA7OztMmTIFt99+O+zt7ZW45557Tvlz79694eXlhQceeED5za0lmDVrFo4cOVJtpA4AVCqV2c8iUm3Zta6NqSm+LtuxJY19DFv6eWjp43ejbdR3O81ZYx9DnoN/ut7xMxgMCAsLQ8+ePbFo0aJat1Hbdm4GLwVSk+nfvz8SEhKQn5+PjIwMREVFIScnB0FBQUrM2LFjcebMGWRlZeHy5cv48ssvkZaWZhZzrcGDBwMATp8+3eifoSnMnj0bP/74I3bs2IGAgABluVarBYBqv01lZWUpv71ptVqUlZUhLy+v1phr77QEgOzs7Gq/Bdqqxj6GNWlJ52FDjl9d8Bxs+DGsCc9B8+NXUFCA8ePHw93dHRs3boSjo6PZdhrrHGRhRU1Oo9GgTZs2OHXqFA4ePIh77rmnWoyPjw9atWqF7du3IysrC5MnT77u9g4fPgwA8Pf3b7Scm4KIYNasWdiwYQO2b99erZgMCgqCVqvFli1blGVlZWXYtWsXhg4dCqCyeHV0dDSLycjIQFJSkhIzZMgQ6PV6HDhwQInZv38/9Hq9EmOrmuoY1qQlnIeWOH51wXOw4cewJjwH/zx+BoMBY8eOhZOTE3788Uez+b1AI5+DDZr6TnSVgoICOXz4sBw+fFgAyPLly+Xw4cOSkpIiIpV3ZezYsUPOnDkj33//vQQGBsp9991nto3PP/9cYmJi5PTp0/Lll1+Kt7e3PP/888r6ffv2Kds9e/as/O9//xOdTieTJ09u0s/aGGbOnCkajUZ27twpGRkZyuvKlStKzNKlS0Wj0ciGDRskMTFRpkyZIv7+/mIwGJSYp556SgICAmTr1q1y6NAhGTVqlPTp00cqKiqUmPHjx0vv3r0lJiZGYmJipFevXjJx4sQm/byNoamOYUs9Dy11/DIyMuTw4cPy6aefCgDZvXu3HD58WHJycpQYnoMNO4Y8B69//AwGgwwaNEh69eolp0+fNttOU/w7yMKKLKbqtuBrX9OnTxcRkX//+98SEBAgjo6O0r59e3n55ZeltLTUbBsLFiwQPz8/cXR0lC5dusi7774rJpNJWR8fHy+DBg0SjUYjzs7O0q1bN1m0aJEUFRU15UdtFDUdOwCyZs0aJcZkMsmiRYtEq9WKWq2WESNGSGJiotl2iouLZdasWeLt7S0uLi4yceJESU1NNYvJycmRadOmiYeHh3h4eMi0adNqvJ3b1jTVMWyp56Gljt+iRYtuuB2egw07hjwHr3/8rvddBEDOnTunxDXWOaj644MQERERUQNxjhURERGRhbCwIiIiIrIQFlZEREREFsLCioiIiMhCWFgRERERWQgLKyIiIiILYWFFREREZCEsrIiImrEZM2bg3nvvrTVm5MiRmDt3bpPkQ0S1Y2FFREREZCEsrIiILMBoNMJkMlk7DSKyMhZWRNSifPHFF2jdujVKS0vNlt9///145JFHlJ9/+ukn9O/fH87OzujYsSNeffVVVFRUKOuXL1+OXr16wc3NDe3atcPTTz+NwsJCZf3atWvRqlUrbNq0CT179oRarUZKSkq1fPLy8jBt2jS0adMGLi4u6NKlC9asWaOsT0xMxKhRo+Di4oLWrVvj73//u9l+rlVUVIRHHnkE7u7u8Pf3x7vvvluv40REjYOFFRG1KH/9619hNBrx448/KssuX76MTZs24dFHHwUA/Prrr3j44YcxZ84cJCcn4+OPP8batWvxxhtvKO+xs7PDBx98gKSkJPz3v//F9u3b8c9//tNsX1euXEFERAQ+++wzHD16FL6+vtXy+de//oXk5GT88ssvOHbsGD766CP4+Pgo7x8/fjy8vLwQFxeH7777Dlu3bsWsWbOu+/leeOEF7NixAxs3bkR0dDR27tyJ+Pj4Bh0zIrKgBj/GmYiomZk5c6ZMmDBB+fn999+Xjh07islkEhGR4cOHy5tvvmn2ni+//FL8/f2vu81vv/1WWrdurfy8Zs0aASAJCQm15jJp0iR59NFHa1z3ySefiJeXlxQWFirLNm/eLHZ2dpKZmSkiItOnT5d77rlHREQKCgrEyclJIiMjlficnBxxcXGRZ599ttY8iKhpOFi7sCMisrQnn3wSAwcORFpaGtq2bYs1a9ZgxowZUKlUAID4+HjExcWZjVAZjUaUlJTgypUrcHV1xY4dO/Dmm28iOTkZBoMBFRUVKCkpQVFREdzc3AAATk5O6N27d625zJw5E/fffz8OHTqEsWPH4t5778XQoUMBAMeOHUOfPn2U7QHAsGHDYDKZcOLECfj5+Zlt68yZMygrK8OQIUOUZd7e3ujWrVvDDhgRWQwvBRJRi9OvXz/06dMHX3zxBQ4dOoTExETMmDFDWW8ymfDqq68iISFBeSUmJuLUqVNwdnZGSkoK7r77bgQHB2P9+vWIj4/Hhx9+CAAoLy9XtuPi4qIUa9czYcIEpKSkYO7cuUhPT8fo0aMxf/58AICIXPf9NS0XkZs9FETUxFhYEVGL9MQTT2DNmjX4/PPPMWbMGLRr105Zd/vtt+PEiRPo3LlztZednR0OHjyIiooKvPvuuxg8eDC6du2K9PT0eufSpk0bzJgxA1999RXef/99fPLJJwCAnj17IiEhAUVFRUrsb7/9Bjs7O3Tt2rXadjp37gxHR0fExsYqy/Ly8nDy5Ml650ZElsXCiohapGnTpiEtLQ2ffvopHnvsMbN1r7zyCr744gssXrwYR48exbFjx/C///0PL7/8MgCgU6dOqKiowIoVK3D27Fl8+eWXWL16db3yeOWVV/DDDz/g9OnTOHr0KDZt2oQePXooOTo7O2P69OlISkrCjh07MHv2bISHh1e7DAgA7u7uePzxx/HCCy9g27ZtSEpKwowZM2Bnx3/KiZoL/t9IRC2Sp6cn7r//fri7u1frXD5u3Dhs2rQJW7ZswcCBAzF48GAsX74cgYGBAIC+ffti+fLleOuttxAcHIyvv/4aERER9crDyckJCxcuRO/evTFixAjY29sjMjISAODq6opff/0Vubm5GDhwIB544AGMHj0aK1euvO723nnnHYwYMQKTJ0/GmDFjcOedd6J///71yo2ILE8lvGhPRC1UaGgoevTogQ8++MDaqRDRLYKFFRG1OLm5uYiOjsa0adOQnJzMu+aIqMmw3QIRtTi333478vLy8NZbb7GoIqImxRErIiIiIgvh5HUiIiIiC2FhRURERGQhLKyIiIiILISFFREREZGFsLAiIiIishAWVkREREQWwsKKiIiIyEJYWBERERFZCAsrIiIiIgv5/w2JavdLJx38AAAAAElFTkSuQmCC",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "dataset.groupby('year')['selling_price'].median().plot()\n",
    "plt.xlabel('year sold')\n",
    "plt.ylabel('selling_price')\n",
    "plt.title('year sold vs selling_price')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "ebde18ac",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0.5, 1.0, 'year sold vs selling_price')"
      ]
     },
     "execution_count": 10,
     "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": [
    "plt.scatter(dataset['year'],dataset['selling_price'])\n",
    "plt.xlabel('year sold')\n",
    "plt.ylabel('selling_price')\n",
    "plt.title('year sold vs selling_price')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "06dcaeb1",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['fuel', 'seller_type', 'transmission', 'owner']"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "discrete_features=[feature for feature in numerical_feature if (len(dataset[feature].unique())<25 and feature not in dataset['year'] )]\n",
    "discrete_features"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "328c7ca5",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "for feature in discrete_features:\n",
    "    data=dataset.copy()\n",
    "    dataset.groupby(feature)['selling_price'].median().plot.bar()\n",
    "    plt.xlabel(feature)\n",
    "    plt.ylabel('selling_price')\n",
    "    plt.title(feature)\n",
    "    plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "e5185740",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['name', 'selling_price', 'km_driven']"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "continous_features=[feature for feature in numerical_feature if feature not in discrete_features+['year'] ]\n",
    "continous_features"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "bdd7a3e7",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "for feature in continous_features:\n",
    "    data=dataset.copy()\n",
    "    dataset[feature].hist(bins=25)\n",
    "    plt.xlabel(feature)\n",
    "    plt.ylabel('count')\n",
    "    plt.title(feature)\n",
    "    plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "e31e6eda",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 4340 entries, 0 to 4339\n",
      "Data columns (total 3 columns):\n",
      " #   Column         Non-Null Count  Dtype \n",
      "---  ------         --------------  ----- \n",
      " 0   name           4340 non-null   object\n",
      " 1   selling_price  4340 non-null   int64 \n",
      " 2   km_driven      4340 non-null   int64 \n",
      "dtypes: int64(2), object(1)\n",
      "memory usage: 101.8+ KB\n"
     ]
    }
   ],
   "source": [
    "dataset[continous_features].info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "b666108f",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "40bf9887",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAioAAAHFCAYAAADcytJ5AAAAOXRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjcuMiwgaHR0cHM6Ly9tYXRwbG90bGliLm9yZy8pXeV/AAAACXBIWXMAAA9hAAAPYQGoP6dpAABSCklEQVR4nO3deViU5f4/8Pczw44wCoaAC6DlgrigZqGiZmquWZ1OaWqaZWmamvXNrFNqHSU7LdavorKy1FxOx9zKcMk9MUskJTRNEU0hRGSJnZn79wfMxDAz8MwwwzwD79d1cV3NM/c8z+fWaj7cy+eWhBACRERERAqkcnYARERERJYwUSEiIiLFYqJCREREisVEhYiIiBSLiQoREREpFhMVIiIiUiwmKkRERKRYTFSIiIhIsZioEBERkWIxUSFqghYvXgxJkpCdne3sUExcvHgRkiTh888/l9V+6tSpCA8Pd2hMROQ8TFSIyKW99NJL2Lx5s7PDICIHcXN2AEREtigqKoKPjw86dOjg7FCIyIE4okJEAIAzZ86gffv2uO2225CVlYXBgwcjKioKiYmJ6NevH7y9vREeHo5Vq1YBAL799lv06tULPj4+6NatGxISEqx+5tWrV/HAAw/Az88PGo0GDz74IDIzM03aTZ06Fc2aNcOpU6cwfPhw+Pn54c477zS8V33qJzo6GrGxsSb30Gq1aN26Ne677z7DtbKyMvz73/9G586d4enpiZtuugmPPPIIrl27ZvTZ8PBwjBkzBgkJCejVqxe8vb3RuXNnfPbZZ1b3mYisw0SFiHDgwAH069cP3bt3x759+xAUFAQAyMzMxCOPPILHHnsMW7duRbdu3TBt2jS88sorWLhwIZ577jls2rQJzZo1wz333IOrV6/KfmZxcTGGDh2KXbt2IS4uDl999RWCg4Px4IMPmm1fVlaGu+++G0OGDMHWrVuxZMkSs+0eeeQRHD58GOfOnTO6vmvXLly9ehWPPPIIAECn02HcuHF47bXX8NBDD+Hbb7/Fa6+9ht27d2Pw4MEoLi42+vwvv/yCZ555Bk8//TS2bt2K7t2749FHH8XBgwdl95mIbCCIqMlZtGiRACCuXbsm1qxZIzw8PMScOXOEVqs1tBk0aJAAIH7++WfDtevXrwu1Wi28vb3FlStXDNeTk5MFAPHuu+/KjiE+Pl4AEFu3bjW6Pn36dAFArFq1ynBtypQpAoD47LPPTO4zZcoUERYWZnidnZ0tPDw8xAsvvGDU7oEHHhCtWrUS5eXlQggh1q9fLwCITZs2GbX76aefBADxwQcfGK6FhYUJLy8vkZ6ebrhWXFwsAgICxBNPPCG7z0RkvUYzonLw4EGMHTsWoaGhkCQJW7ZssfoeQgi88cYb6NixIzw9PdG2bVssW7bM/sESKcTSpUsxdepUvPbaa3jnnXegUhn/LyEkJAS9e/c2vA4ICEBQUBB69uyJ0NBQw/UuXboAANLT02U/e9++ffDz88Pdd99tdP2hhx6y+Jl//OMfdd43MDAQY8eOxRdffAGdTgcAuHHjBrZu3YqHH34Ybm6VS/O++eYbNG/eHGPHjkVFRYXhp2fPnggODsb+/fuN7tuzZ0+0a9fO8NrLywsdO3a0qs9EZL1Gk6gUFhaiR48eeO+992y+x9y5c/HJJ5/gjTfewJkzZ7B9+3b07dvXjlESKcvatWvRunVrjB8/3uz7AQEBJtc8PDxMrnt4eAAASkpKZD/7+vXraNWqlcn14OBgs+19fHzg7+8v697Tpk3DlStXsHv3bgDA+vXrUVpaiqlTpxra/Pnnn8jNzYWHhwfc3d2NfjIzM022bgcGBpo8x9PT02SKiIjsq9Hs+hk5ciRGjhxp8f2ysjL861//wpdffonc3FxERUVh+fLlGDx4MADg9OnTiI+PR0pKCjp16tRAURM5V0JCAh588EHExsbi+++/R1hYWIM9OzAwEMeOHTO5bm4xLQBIkiT73nfddRdCQ0OxatUq3HXXXVi1ahVuu+02REZGGtq0bNkSgYGBFhcB+/n5yX4eETlOoxlRqcsjjzyCH374ARs2bMDJkyfxz3/+EyNGjDAsuNu+fTvat2+Pb775BhEREQgPD8djjz2GnJwcJ0dO5DhhYWE4dOgQPD09ERsba7IA1ZHuuOMOFBQUYNu2bUbX161bV+97q9VqTJ48GVu2bMGhQ4fw888/Y9q0aUZtxowZg+vXr0Or1aJPnz4mP/yFhUgZmkSicv78eaxfvx5fffUVYmNj0aFDBzz77LMYMGCAYavlhQsXkJ6ejq+++gqrV6/G559/juPHj+P+++93cvREjhUSEoIDBw7gpptuwsCBA5GSktIgz3344YfRsWNHPPzww3j//fexa9cuzJs3Dzt37rTL/adNm4bS0lI89NBD8Pb2NtlNNH78eIwcORKjRo3CK6+8goSEBHz//ff44osvMHXqVBaRI1KIRjP1U5ukpCQIIdCxY0ej66WlpYZ5Z51Oh9LSUqxevdrQ7tNPP0Xv3r3x22+/8bcratRatmyJvXv3YvTo0Rg0aJDdkoXa+Pj4YO/evZg7dy6ef/55SJKE4cOHY8OGDejXr1+979+xY0f069cPR44cwcSJE6HRaIzeV6vV2LZtG9555x2sWbMGcXFxcHNzQ5s2bTBo0CB069at3jEQUf1JQgjh7CDsTZIkbN68Gffccw8AYOPGjZg4cSJ+/fVXqNVqo7bNmjVDcHAwFi1ahGXLlqG8vNzwXnFxMXx8fLBr1y4MGzasIbtAREREaCIjKtHR0dBqtcjKyjJbsRIA+vfvj4qKCpw/f95Qkvvs2bMA0KALDImIiOhvjWZE5a+//sLvv/8OoDIxeeutt3DHHXcgICAA7dq1w6RJk/DDDz/gzTffRHR0NLKzs7F3715069YNo0aNgk6nw6233opmzZphxYoV0Ol0mDVrFvz9/bFr1y4n947ItVRUVNT6vkqlMqnZQkRkTqP5P8XPP/+M6OhoREdHAwDmz5+P6OhovPzyywCAVatW4eGHH8YzzzyDTp064e6778aPP/6Itm3bAqj8H+f27dvRsmVLDBw4EKNHj0aXLl2wYcMGp/WJyBVdvHjRpC5JzZ9XXnnF2WESkYtoNCMqRKQMZWVlOHnyZK1tQkNDjSrbEhFZwkSFiIiIFKvRTP0QERFR4+PSu350Oh2uXr0KPz8/q8prExERkfMIIVBQUIDQ0NA6F9a7dKJy9epVw2JYIiIici2XL19GmzZtam3j0omK/tCwy5cvyz5VlYiIiJwrPz8fbdu2lXX4p0snKvrpHn9/fyYqRERELkbOsg0upiUiIiLFYqJCREREisVEhYiIiBSLiQoREREpFhMVIiIiUiwmKkRERKRYTFSIiIhIsZioEBERkWIxUSEiIiLFcunKtM6g1QkcS8tBVkEJgvy80DciAGoVD0QkIiJyBCYqVkhIycCS7anIyCsxXAvReGHR2EiMiApxYmRERESNE6d+ZEpIycDMtUlGSQoAZOaVYObaJCSkZDgpMiIiosaLiYoMWp3Aku2pEGbe019bsj0VWp25FkRERGQrJioyHEvLMRlJqU4AyMgrwbG0nIYLioiIqAlgoiJDVoHlJMWWdkRERCQPExUZgvy87NqOiIiI5GGiIkPfiACEaLxgaROyhMrdP30jAhoyLCIiokaPiYoMapWERWMjAcAkWdG/XjQ2kvVUiIiI7IyJikwjokIQP6kXgjXG0zvBGi/ET+rFOipEREQOwIJvVhgRFYJhkcGsTEtERNRAmKhYSa2SENMh0NlhEBERNQmc+iEiIiLFYqJCREREisVEhYiIiBSLiQoREREpFhMVIiIiUiwmKkRERKRYTFSIiIhIsZioEBERkWIxUSEiIiLFYqJCREREisVEhYiIiBSLiQoREREpFhMVIiIiUiwmKkRERKRYTFSIiIhIsZioEBERkWK5OTsApdPqBI6l5SCroARBfl7oGxEAtUpydlhERERNAhOVWiSkZGDJ9lRk5JUYroVovLBobCRGRIU4MTIiIqKmgVM/FiSkZGDm2iSjJAUAMvNKMHNtEhJSMpwUGRERUdPBRMUMrU5gyfZUCDPv6a8t2Z4Krc5cCyIiIrIXJipmHEvLMRlJqU4AyMgrwbG0nIYLioiIqAliomJGVoHlJMWWdkRERGQbJipmBPl52bUdERER2capiUpFRQX+9a9/ISIiAt7e3mjfvj1eeeUV6HQ6Z4aFvhEBCNF4wdImZAmVu3/6RgQ0ZFhERERNjlMTleXLl+PDDz/Ee++9h9OnT+P111/Hf/7zH/y///f/nBkW1CoJi8ZGAoBJsqJ/vWhsJOupEBEROZhTE5XExESMGzcOo0ePRnh4OO6//34MHz4cP//8szPDAgCMiApB/KReCNYYT+8Ea7wQP6kX66gQERE1AKcWfBswYAA+/PBDnD17Fh07dsQvv/yCw4cPY8WKFWbbl5aWorS01PA6Pz/fofGNiArBsMhgVqYlIiJyEqcmKgsWLEBeXh46d+4MtVoNrVaLpUuXYsKECWbbx8XFYcmSJQ0ao1olIaZDYIM+k4iIiCo5depn48aNWLt2LdatW4ekpCR88cUXeOONN/DFF1+Ybb9w4ULk5eUZfi5fvtzAERMREVFDkoQQTiuv2rZtWzz//POYNWuW4dq///1vrF27FmfOnKnz8/n5+dBoNMjLy4O/v78jQyUiIiI7seb726kjKkVFRVCpjENQq9VO355MREREyuDUNSpjx47F0qVL0a5dO3Tt2hUnTpzAW2+9hWnTpjkzLCIiIlIIp079FBQU4KWXXsLmzZuRlZWF0NBQTJgwAS+//DI8PDzq/DynfoiIiFyPNd/fTk1U6ouJChERketxmTUqRERERLVhokJERESKxUSFiIiIFIuJChERESkWExUiIiJSLCYqREREpFhMVIiIiEixmKgQERGRYjFRISIiIsViokJERESKxUSFiIiIFIuJChERESkWExUiIiJSLCYqREREpFhMVIiIiEixmKgQERGRYjFRISIiIsViokJERESKxUSFiIiIFIuJChERESkWExUiIiJSLCYqREREpFhMVIiIiEixmKgQERGRYjFRISIiIsViokJERESKxUSFiIiIFIuJChERESkWExUiIiJSLCYqREREpFhMVIiIiEixmKgQERGRYjFRISIiIsViokJERESKxUSFiIiIFIuJChERESkWExUiIiJSLCYqREREpFhMVIiIiEixmKgQERGRYjFRISIiIsViokJERESKxUSFiIiIFIuJChERESkWExUiIiJSLCYqREREpFhMVIiIiEixmKgQERGRYjFRISIiIsViokJERESKxUSFiIiIFIuJChERESkWExUiIiJSLCYqREREpFhMVIiIiEixmKgQERGRYjFRISIiIsViokJERESKxUSFiIiIFIuJChERESkWExUiIiJSLCYqREREpFhMVIiIiEixmKgQERGRYjk9Ubly5QomTZqEwMBA+Pj4oGfPnjh+/LizwyIiIiIFcHPmw2/cuIH+/fvjjjvuwHfffYegoCCcP38ezZs3d2ZYREREpBBOTVSWL1+Otm3bYtWqVYZr4eHhzguIiIiIFMWpUz/btm1Dnz598M9//hNBQUGIjo7GypUrnRkSERERKYhTE5ULFy4gPj4et9xyC3bu3IkZM2Zgzpw5WL16tdn2paWlyM/PN/ohIiKixksSQghnPdzDwwN9+vTBkSNHDNfmzJmDn376CYmJiSbtFy9ejCVLlphcz8vLg7+/v0NjJSIiIvvIz8+HRqOR9f3t1BGVkJAQREZGGl3r0qULLl26ZLb9woULkZeXZ/i5fPlyQ4RJRERETuLUxbT9+/fHb7/9ZnTt7NmzCAsLM9ve09MTnp6eDREaERERKYBTR1SefvppHD16FMuWLcPvv/+OdevW4eOPP8asWbOcGRYREREphFMTlVtvvRWbN2/G+vXrERUVhVdffRUrVqzAxIkTnRkWERERKYRTF9PWlzWLcYiIiEgZXGYxLREREVFtmKgQERGRYjFRISIiIsViokJERESKxUSFiIiIFIuJChERESkWExUiIiJSLKeW0Kf60+oEjqXlIKugBEF+XugbEQC1SnJ2WERERHbBRMWFJaRkYMn2VGTklRiuhWi8sGhsJEZEhTgxMiIiIvvg1I+LSkjJwMy1SUZJCgBk5pVg5tokJKRkOCkyIiIi+2Gi4oK0OoEl21Nh7uwD/bUl21Oh1bns6QhEREQAmKi4pGNpOSYjKdUJABl5JTiWltNwQRERETkAExUXlFVgOUmxpR0REZFSMVFxQUF+XnZtR0REpFRMVFxQ34gAhGi8YGkTsoTK3T99IwIaMiwiIiK7Y6LigtQqCYvGRgKASbKif71obCTrqRARkcuzKVHJzc3FJ598goULFyInp3LBZlJSEq5cuWLX4MiyEVEhiJ/UC8Ea4+mdYI0X4if1Yh0VIiJqFKwu+Hby5EkMHToUGo0GFy9exPTp0xEQEIDNmzcjPT0dq1evdkScZMaIqBAMiwxmZVoiImq0rB5RmT9/PqZOnYpz587By+vv3+ZHjhyJgwcP2jU4qptaJSGmQyDG9WyNmA6BTFKIiKhRsTpR+emnn/DEE0+YXG/dujUyMzPtEhQRERERYEOi4uXlhfz8fJPrv/32G2666Sa7BEVEREQE2JCojBs3Dq+88grKy8sBAJIk4dKlS3j++efxj3/8w+4BEhERUdNldaLyxhtv4Nq1awgKCkJxcTEGDRqEm2++GX5+fli6dKkjYiQiIqImyupdP/7+/jh8+DD27t2LpKQk6HQ69OrVC0OHDnVEfERERNSESUIIlz1iNz8/HxqNBnl5efD393d2OERERCSDNd/fVk/9zJkzB++++67J9ffeew/z5s2z9nZEREREFlmdqGzatAn9+/c3ud6vXz/873//s0tQRERERIANicr169eh0WhMrvv7+yM7O9suQREREREBNiQqN998MxISEkyuf/fdd2jfvr1dgnJ1aVmF6PTiDoQ//y06vbgDaVmFzg6JiIjIJVm962f+/PmYPXs2rl27hiFDhgAAvv/+e7z55ptYsWKFveNzOe0XfgtdteXJpVqBO97aD5UEXIgb7bzAiIiIXJBNu37i4+OxdOlSXL16FQAQHh6OxYsX4+GHH7Z7gLVR2q6fmklKTUxWiIiIrPv+tnpEBQBmzpyJmTNn4tq1a/D29kazZs1sCrQxScsqrDVJAQCdqGwXEeTbMEERERG5OKvXqFR30003MUmpMuKdA3ZtR0RERDJHVHr16oXvv/8eLVq0QHR0NCRJstg2KSnJbsG5klKtvBk0ue2IiIhIZqIybtw4eHp6AgDuueceR8ajWFqdwLG0HGTmFSOnsAwBzTwR7O+FvhEBUKskeKolWUmIp9pykkdERETGrFpMq9VqcfjwYXTv3h0tWrRwZFyyNNRi2oSUDCzZnoqMvBKT90I0Xlg0NhKdgvxxx1v767zXvvmDuUaFiIiaNIeV0Fer1bjrrruQm5tbn/hcSkJKBmauTTKbpABARl4JZq5Nwm9Z+VDVMViiksAkhYiIyApWL6bt1q0bLly44IhYFEerE1iyPRVyhpyWbE/FuaWjLCYr3JpMRERkPasTlaVLl+LZZ5/FN998g4yMDOTn5xv9NBZancDnP6RZHEmpTqByZOVYWg4uxI3GvvmDDWtRPNUS9s0fzCSFiIjIBlYXfFOp/s5tqu/+EUJAkiRotVr7RVcHR61RqW1NSm3eGd8T43q2tlscREREjZFDC77t27fP5sBcgX5Nii2biIP8vOweDxERUVNmdaIyaNAgR8ShCNasSalOAhCsqdyqTERERPZjUwn9Gzdu4NNPP8Xp06chSRK6dOmCRx55BAEBrv1FfSwtx+rpHr1FYyOhrmvbDxEREVnF6sW0Bw4cQHh4ON59913cuHEDOTk5ePfddxEREYEDB1y7PHxWgfVJSojGC/GTemFEVIgDIiIiImrarB5RmTVrFh588EHEx8dDrVYDqCwE9+STT2LWrFlISUmxe5ANRe4ak8m3t0OvsACjyrRERERkf1YnKufPn8emTZsMSQpQWQhu/vz5WL16tV2Da2h9IwIQovFCZl6JxXUqPh5qtAvwxehuIfBwq9eZjnajL++fVVCCID8mT0RE1HhYnaj06tULp0+fRqdOnYyunz59Gj179rRXXE6hVklYNDYSM9cmQQLMJitFZVos3XEacd+dxvTYCCwcFdnQYRoxt5VaX9af01FEROTqrK6jsnHjRjz33HN46qmncPvttwMAjh49ivfffx+vvfYaunTpYmjbvXt3+0ZbgxLqqDwx0HnJiqWt1PqxFK6dISIiJbLm+7teBd/M3lCSGqz4myMPJdTqBI78no2HPztW63ZllQSceXVkg08DaXUCA5bvtZhM6bdMH14whNNARESkKA4t+JaWlmZzYK5ErZJw9s+COmuq6ASwJvEiHo1t3yBx6dW1lbp6Wf+YDoFG75VV6LAm8SLSc4oQFuCDyTHhillvQ0REVJ3ViUpYWJgj4lCk9Jwiu7azJ7lbqWu2i9uRipWH0qCrloEt3aGM9TZEREQ12VTwrakIC/Cxazt7kruVunq7uB2p+Oig6YiYTsBwnckKEREpCcf7azE5Jhx1Le9QSZXtGpp+K7Wl8CRU7v7Rl/Uvq9Bh5aHap+1WHkpDWYXOvoESERHVAxOVWni4qTA9NqLWNtNjI5yyvkO/lRqASbKif129rP+axItG0z3m6NfbEBERKQUTlTosHBWJJwZGmIysqCTnbk0GgBFRIYif1AvBGuNpoGAzZf2VvN6GiIjIEqvXqFy+fBmSJKFNmzYAgGPHjmHdunWIjIzE448/bvcAlWDhqEg8M7yzInfKjIgKwbDI4Dor0yp5vQ0REZElVtdRiY2NxeOPP47JkycjMzMTnTp1QteuXXH27FnMmTMHL7/8sqNiNeHIOiqNTVmFDp1f+q7W6R9n1YQhIqKmxZrvb6u/kVJSUtC3b18AwH//+19ERUXhyJEjWLduHT7//HObAibHU/J6GyIiIkus/lYqLy+Hp6cnAGDPnj24++67AQCdO3dGRkaGfaMju1o4KhLDIoPMvjcsMohbk4mISHGsTlS6du2KDz/8EIcOHcLu3bsxYsQIAMDVq1cRGBhYx6fJmRJSMrAnNcvkugRgT2oWElKYaBIRkbJYnagsX74cH330EQYPHowJEyagR48eAIBt27YZpoRIebQ6gSXbU80eCaC/tmR7KrR17WEmIiJqQFbv+hk8eDCys7ORn5+PFi1aGK4//vjj8PHhjhGlqs/ZQERERM5i08pJIQSOHz+Ojz76CAUFBQAADw8PJioKZuvZQERERM5k9YhKeno6RowYgUuXLqG0tBTDhg2Dn58fXn/9dZSUlODDDz90RJxUT7acDURERORsVo+ozJ07F3369MGNGzfg7e1tuH7vvffi+++/t2twjZ1WJ5B4/jq2Jl9B4vnrda4PKavQ4dNDF/Dy1hR8euiCVefyWHs2EBERkRJYPaJy+PBh/PDDD/Dw8DC6HhYWhitXrtgcSFxcHF544QXMnTsXK1assPk+riIhJQNLtqcarRsJ0Xhh0dhIo9L3enE7UrHyUJpRwbalO05jeqy8Mv76s4Fmrk2CBBgtqjV3NhAREZESWD2iotPpoNVqTa7/8ccf8PPzsymIn376CR9//DG6d+9u0+ddTUJKBmauTTJZ3JqZV4KZa5NMtgnH7UjFRwfTTKrK6gTw0cE0xO1IlfVca84GIiIiUgKrE5Vhw4YZjXhIkoS//voLixYtwqhRo6wO4K+//sLEiROxcuVKo11EjZW124TLKnRYeSit1nuuPJQmexpoRFQIDi8YgvXTb8c743ti/fTbcXjBECYpRESkSFYnKm+//TYOHDiAyMhIlJSU4KGHHkJ4eDiuXLmC5cuXWx3ArFmzMHr0aAwdOrTOtqWlpcjPzzf6UQJr1o5Ys00YANYkXqz1fB6gcmRlTeJF2fGqVRJiOgRiXM/WiOkQyOkeIiJSLKvXqISGhiI5ORnr169HUlISdDodHn30UUycONFoca0cGzZsQFJSEn766SdZ7ePi4rBkyRJrQ3Yoa9eOWLtNOD2nSFZ7ue2IiIhcidWJCgB4e3tj2rRpmDZtms0Pvnz5MubOnYtdu3bBy0veltiFCxdi/vz5htf5+flo27atzTHUl37tSE36tSMATJIVa7cJhwXIq00jtx0REZErkYQQddZM37Ztm+wb6g8prMuWLVtw7733Qq1WG65ptVpIkgSVSoXS0lKj98yx5phoeyur0KHzS9/VOi2jkoAzr440OpFYqxMYsHwvMvNKzK5TkVC5uPXwgiFQqySbn0NERKRU1nx/yxpRueeee2Q9WJIkszuCzLnzzjtx6tQpo2uPPPIIOnfujAULFtSZpDS0tKxCjHjnAEq1Ap5qCY/1by977cijse0N16zdJuzhpsL02AizIzd602MjmKQQEVGjJCtR0enkFxaTy8/PD1FRUUbXfH19ERgYaHLd2dov/NYoKSnVCrx/8Lysz5pbO6LfJlyzjkqwhToq+umjmmthVBJk11EhIiJyRTatUWlKaiYp1rK0dmREVAiGRQbjWFoOsgpKEORXWRXW0g6chaMi8czwzliTeBHpOUUIC/DB5JhwjqQQEVGjZlOiUlhYiAMHDuDSpUsoKyszem/OnDk2B7N//36bP+sIaVmF9UpSVBIwOSbc4vv6bcJyebipjKaRiIiIGjurE5UTJ05g1KhRKCoqQmFhIQICApCdnQ0fHx8EBQXVK1FRmhHvHKjX57l2hIiIqH6s/hZ9+umnMXbsWOTk5MDb2xtHjx5Feno6evfujTfeeMMRMTpNqda24RSVBDwxkGtHiIiI6svqEZXk5GR89NFHUKvVUKvVKC0tRfv27fH6669jypQpuO+++xwRp1N4qiVZyYq7BDw/qgvXjhAREdmZ1YmKu7s7JKlywWerVq1w6dIldOnSBRqNBpcuXbJ7gM6UMHcQ7nhrf53tdj09GBFBvg6Ph4iIqKmxOlGJjo7Gzz//jI4dO+KOO+7Ayy+/jOzsbKxZswbdunVzRIxOExHkC5WEOoutMUkhIiJyDKvnJ5YtW4aQkMo6H6+++ioCAwMxc+ZMZGVl4eOPP7Z7gM52IW40LJ3Zp5Iq3yciIiLHkFVCX6kasoR+zcq0CXMHcSSFiIjIBnYvoV9dcXExhBDw8aksZJaeno7NmzcjMjISw4cPty1iFxAR5Ivflo6y+nNanZBV1E1uOyIioqbE6kRl3LhxuO+++zBjxgzk5uaib9++8PDwQHZ2Nt566y3MnDnTEXG6pISUDJMy+SFmyuTLbUdERNTUWL1GJSkpCbGxsQCA//3vfwgODkZ6ejpWr16Nd9991+4BuqqElAzMXJtklHwAQGZeCWauTUJCSoZV7YiIiJoiqxOVoqIi+Pn5AQB27dqF++67DyqVCrfffjvS09PtHqAr0uoElmxPhbnFP/prS7anoqxCJ6udtj51/ImIiFyY1YnKzTffjC1btuDy5cvYuXOnYV1KVlaWwxe0uopjaTkmIyTVCQAZeSVYk3hRVrtjaTn2D5KIiMgFWJ2ovPzyy3j22WcRHh6O2267DTExMQAqR1eio6PtHqAryiqwnHxUl55TZNf7ERERNTZWL6a9//77MWDAAGRkZKBHjx6G63feeSfuvfdeuwbnqoL8vGS1Cwvwsev9iIiIGhubDqQJDg5GdHQ0VKq/P963b1907tzZboG5sr4RAQjReMHS5mIJlbt6JseEy2rXNyLAMYESEREpHE/OcwC1SsKisZUnJ9dMQvSvF42NhIebSlY71lMhIqKmiomKjbQ6gcTz17E1+QoSz1832ZkzIioE8ZN6IVhjPG0TrPFC/KRehvooctsRERE1RSyhbwNrCrSxMi0REZExa76/mahYSV+gzdIf2gcPReOuqJB6JR1MWoiIqDFz6Fk/TVlthdz0Zq07AY1PCnKLyg3XrCmHz3L6REREf+MaFSvUVcgNqCzSVj1JAeSXw2c5fSIiImNMVKxga+E1OeXw5ZbdZzl9IiJqSpio1KLmzp6Wvp4236uucvhyy+6znD4RETUlXKNigbm1IsH+Xmju424ytWMNS6MyckdrWE6fiIiaEiYqZlja2fNnfkmtC2nlsFQOX26ZfJbTJyKipoRTPzXUtVZEAtDCx91i2fva1FYOX27ZfZbTJyKipoSJSg1y1orcKCpH7C0trb733T1CLNZDkVt2n/VUiIioKWGiUoPcNSC2TAFt+yWj1l07LKdPRERkjGtUapC7BiQ80AeHzll3b/2unZgOgRbbjIgKwbDIYFamJSIiAhMVE/q1Ipl55hfOSqgc4XhhVCS+/PESrC1rImfERq2Sak1miIiImgpO/dQgd62It4ca02MjrL7/zxdz8PLWFHx66ALKKnT1C5aIiKiR46GEFsg9cyduRypWHkqzemQFAFQSMD02AgtHRdojZCIiIpfA05PtRO4pxmUVOqxJvIhD565h/9lsq5/zxEAmK0RE1HQwUXEicyMxdVFJwJlXR8LDjTNxRETU+Fnz/c3FtDJZGl2peX1YZLDRrp2fL+ZgzdFLtd5bJ4CHViZiZFQIJseEM2EhIiKqwkRFBnOjJD4eavRo3RwXsv/CnwWlhus117EcT78h6xk/p+fi5/RcLN1xmutWiIiIqvBX9zroz/2pOZVTVKZFYtp1oyQFADLzSjBzbRISUjIAAGEBPlY9TyeAjw6mIW5Hav0CJyIiagSYqNSirEKHFzanWFWFVlT9PL0xGf/afArlWtu2IK88lMbty0RE1ORx6seChJQMvLD5FHIKy236fHG5Dmt/rH1tSm10Apj15XGM6h6KYH9WpyUioqaJiYoZ+ukeZ2+H2n06C7tPZwEAgv29sPjuSJ73Q0RETQqnfmrQ6gSWbE91epJSU2Z+CWZUW/tCRETUFDBRqeFYWo5VNVAa2sKvT5mcwKzVCSSev46tyVeQeP56rSc0ExERuRJO/dQg59BAZ7pRVI6jF66j/80tAcgv9U9EROSKOKJSQ5Cfl7NDqFPi+esALG+drrlFmoiIyFUxUamhb0QAQjReJicn18ZD3dC7cUSta2n015ZsT+U0EBERuTQmKjWoVRIWjbWuKuzdPUKtSmzqS+Ptgbd3n611LY0AkJFXgmNpOQ0XGBERkZ0xUTFjRFQI4if1go+7WlZ7H083xE/qhRCN46eNJAlYuuM03tv3u6z2Sl9zQ0REVBsuprVgRFQILucUY+mO03W2DQvwwYioEMNhhFdvFGHl4TScySywe1zWnnXtCmtuiIiILOGISi2m9AtHXcVgVRIwOSYcQOW0UUyHQNzTq43dRzJsKUqrkoDeYS3sGgcREVFDYqJSCw83FabHRtTaZnpsBDzcjP8Yj164bnPp/epeGt0F74zviZdGd4Eta2J1Qv7pzURERErERKUOC0dF4omBESYjGioJeGJgBBaOMl54m5CSgVlfJtnl2S39PDGuZ2u09PO0+R5co0JERK6Ma1RkWDgqEs8M74w1iReRnlOEsAAfTI4JNxlJsfcZQfr1JfVZZ+LsNSpancCxtBxkFZQgyI+HKxIRkXWYqMjk4abCo7HtLb5v7zOCQjSVX+rA37VdMvNKZN9fAhBc7R7OwKq5RERUX5z6sRN7nhEkAVg0NtIw8lC9toucsQh9m+r3aGismktERPbARMVOrF0LYil/CNF4IX5SL5MRB31tl+AatVpa+LijuY+70bVgC/doKKyaS0RE9sKpHzuxdi2I/jv6kf7haNPcGwG+HgjWeNe6hqN6rZbqaz4AKGodSF2jS9Wr5sZ0CGy4wIiIyOUwUbGT3mEtEODrbtW2ZAlAQkomDi8YIjux0NdqqUlJX/hyR5e4I4mIiOrCqR87SEjJwKD/7LO6dkpjPY9H7uiSs3ckERGR8nFEpZ7ssSU5M79xjSzUtUtJCTuSiIjINXBEpR7stSX51W9+bVS7YGrbpaSEHUlEROQ6mKjUg722JOcUljtsy65WJ5B4/jq2Jl9B4vnrDbbTxtIuJWfvSCIiItfCqZ96sPdi0CXbUzEsMthuIw3OLrhmaZcSR1KIiEguJir1YM/FoHVt2S2r0NVZwr86S2tn9AXXGmpUw9IuJSIiIjmYqNSD3EWjb9zfA9/9moG1Ry/VeU9zozRxO1Kx8lCa0QnKS3ecxvRY00MRgboLrkmw/+gNERGRI3CNig306z6+OXkV429tB6D2RaP9b2mJ0d1CZd275ijN0m9T8dFB4yQFqCwY99HBNMTtSDW5hzUF12zhiHUvzlpLQ0REyubUEZW4uDh8/fXXOHPmDLy9vdGvXz8sX74cnTp1cmZYtTK37qOZpxt0QqCoTGu4pvFxxyP9IjAsMhiAbVt2v0m+ipWH0mqNZ+WhNDwzvLPRNJAjC645Yt2Ls9fSEBGRcjl1ROXAgQOYNWsWjh49it27d6OiogLDhw9HYWGhM8OyyNJBe3+VVhiSFP1ISm5ROd7ecxYDlu9FQkqG1Vt2E1IyMHvDiTpj0glgTeJFo2vWFFyzZiTDEQcN8vBCIiKqjVNHVBISEoxer1q1CkFBQTh+/DgGDhzopKjMk1szpa7Fq/GTepmMHgTXGD3QP0uu9Jwio9dyR29uFJZiwPK9skYyHLHuhWtpiIioLopaTJuXlwcACAgwX7G0tLQUpaWlhtf5+fkNEhdge82Uml+4crbsWvussAAfo9f60ZuZa5MgwTh50j+ld1gLPLnOdMTG0q4gRxw0yMMLiYioLopZTCuEwPz58zFgwABERUWZbRMXFweNRmP4adu2bYPFV5+aKTUXr+q37I7r2RoxHQJNRguseZZKAibHhJtct1RwrbmPOzTe7vjmpPkpFX1Ss2R7qtE0kCPWvfDwQiIiqotiRlRmz56NkydP4vDhwxbbLFy4EPPnzze8zs/Pd2iyotUJw8hHdkFp3R+og9wvXGvqs0yPjbBYT6Xm6M3F7EK8vedcnfc0N5LhiIMGeXghERHVRRGJylNPPYVt27bh4MGDaNOmjcV2np6e8PT0bJCYzO1EUUkw2SZsDUtfuDWLuT10Wxh8PNRGu4jMsVRHpTr96I1WJzBg+V6r4q2eWPWNCECwvycy880nbPp1L73DWiDx/HVZlWh5eCEREdXFqYmKEAJPPfUUNm/ejP379yMiIsKZ4RhYqupqa5JS2xeuuWJur357us57vjc+GmN6yqvNAti2xuZi9t+LdHenZqKkQme2nT4NubtHCAb9Z5/sbcZy1tLw8EIioqbNqYnKrFmzsG7dOmzduhV+fn7IzMwEAGg0Gnh7ezslJnudiFydgPkv3LgdlcXcrCVJwPCoYKs+szs10+rnvL3nLPKKy6Dx9sCKPWct/plofNzxYJ82+PhgmtUl++XuhCIioqZJEkI4rQSoJJn/TXnVqlWYOnVqnZ/Pz8+HRqNBXl4e/P397RJT4vnrmLDyqF3updfCxx0//2uYUaJSVqFD55e+s3mU5qXRXfBobHtZbbU6gVuX7kFOYZltD6uDr4cafl5udU4LHV4wxOLoSPX1QDy8kIiocbPm+9vpUz9K44gdJjeKyk222K5JvFiv9S7pOUWyv9yPpeU4LEkBgMIyLQprWU8jZ5sxDy8kIiJzFLGYVkkctcPkam6x0euaRdqsVVRaIbtYm1K29yolDiIich2KqaOiFH0jAtDcx93u902+fMPoddsWPhZa1k2SgP8lXZFddl4p23uVEgcREbkOJipO0vGmZjZ/1ttdbfa6pWJtlVuLnZckSKgc7eE2YyIishYTlRqOpeUgt6jc7vctKKnAD+ey8cPv2diafAWbf7li9T1UEjCme0it9VVqVsEFKtd/TOjbzpaw643bjImIqD64RqUGR62j2JJ8FVuSr9r8+RdGdsbU/hH4LiXDYvn76iZ+chQ6AbirgO/mDEJ4S9unmqwR4OuOnMK/Ez1uMyYiovpgolLDxexCZ4dgllolwcNNJXudh37mp1wHDF1xQPZzIgJ9kHbd9oW+L43pimB/L24zJiIiu2CiUo1WJ7D+2CVnh2GWfpeQvuy8LSc5AzCpAFudr4cae54ZjN2pmSYF2GqOlFgS7O/FbcZERGQ3TFSqOZaWY7FombOFBVRO3ahVEu7uEWJTRVugMkmxlKy8+UAPqFWSyWGGQX6VZ/jULI9fHc/lISIiR+Bi2mqUWudDJQGTY8IBVI76bPul7jUqtd0rWGM8fRSi8cKHNUrc6wuwjevZGjEdAuHhpsKisZGQ8PcCWT0umCUiIkfhiEo1Sq3zMT02Ah5ulTmlLYcLVqcTwOEFQ2wqV89zeYiIqKExUalGv/4jM6/ErocS1sfgji0xuFMraHUCapVU71Efd1X9ytWbmxbiglkiInIUJirVqFUSFo2NxMy1SbUuOm1I+89mY//ZbEN5/PqO+nw3Z5DstlqdwNEL15F4/joAgZj2LXF7h0Cey0NERA3Gqacn15cjTk8GgISUDJPpDSWQALz/UDRe/fa0TaM+EoC010bLapuQkoHnvz5lUvyuubcbXvtHd07zEBGRzaz5/uZiWjOGdG6Faf0j0KONxmThqDMJAK9+exovjY606fMtfN2x42TdRecSUjIwY22S2Qq9ucUVmGHmPCEiIiJHYKJSQ9yOVHR+6Tss3XEav/yRp4jpn+oy8kqQeCEbgzq2hJe7dWlUTmE5nlx3AnE7Ui220eoEFm+z/L7egk0njc4TIiIicgQmKtXE7UjFRwfToPTv3zVHL2H/2WyUlNsW6EcH07DDQhn+yloydU955RVX4Oj56zY9n4iISC4mKlXKKnRYeci2Imqu6KWtKWZHRKzZVZR4IdueIdmdVieQeP46tiZfQeL56xwBIiJyQdz1U2VN4kXFj6TY0/XCMhxLyzHZvWPdriIlreAxZm5BdAjrvRARuRyOqFTRn6XTlJgbPekbEYAAXw9Zn4/pEIjiMi1e2nIKkz/9ES9tOYXiMq29w7TajpOVi4Fr7trKzCvBTC4EJiJyKRxRqdK2hbezQ2hw5kZP1CoJ/x4XhSfXJdX62RY+7lj1wwVM/OSa4dqhc5XrZ4ZFBmHlw7fWOz6tTlhdWG7HyauYvf6E2ff05xwt2Z6KYZHBLFJHROQCmKhU6RxsvzosriCkxgGCNZOC6bERta7ZaRvgjT2nr5l9b3dqFqav/qleyYotUzcJKRl4cp35JEVPoHLnlLlpLyIiUh4mKlWy/1LmqcmOIMH4AEFLScH02HD87/gV3KhWTyVE44XnR3bG3A3JtT5jd2oWisu08PZQWx1fQkoGZq5NMtkarp+6ia9xgCJQmWgt2V73tmo9pR5ASURExpioVMkpLHN2CA0iROOFl0Z3gcbbA1uTr+BidiHe3nPOpF1GXgk+OXQR/298NP4sKEF6ThHCAnwwOSYcr37zq6xnLduRilfv6WZVfPqEw9y65tqmbqw9rFGpB1ASEZExJipVApp5OjsEh2ru4473J/RCXnE5Xv1W3vEAAsCcjSeMdkN9cjgNGm95/9qkZRdafM/S+pO6Eg5LUzfWjJDUnPYiIiLlYqJSJcivcScquUXl+DHtOt7d+7tVn6u5ZTszrwQZefI+6+1uftqntvUnpRU6WfeumZhYM0JSfdqLiIiUjYlKFZ228RdRsTZJMceaP6W7ugabXKtt/cmMtUm4v1cbWfeumZj0jQhAiMar1sMaVRLw3gTT9S31YcvOJCIiko+JSpUfL7IcvL3lFZdja/IVwxc4gFrXnwDA/5L+qPO+wf6eJlM3apWERWMjMXNtEiSYT6jemxCNUd3tl6SwqBwRkeMxUanSlKrSNgSVVHnSs16Ixgvjb21n1YJXS0oqdNidmmmSDIyICkH8pF4NkjzYsjOJiIisJwkhXPYrOj8/HxqNBnl5efD3r18dlI8PnMey787YKTKqydIoh633AmAxGXD0dIxWJzBg+V6LSZcEIFjjhcMLhnAaiIjIDGu+vzmiUiW3Wq0Qsj97ZsN1VZhVqySHFnOzdWcSERFZj2f9VLmaV+zsEMgK1ZOBhiZ3KzSLyhER1R9HVKqENmcBsIZkr6kga5MBe0wLyd0KzaJyRET1x0SlSv8ON+GD/RecHUaT8PTQW7Dhp8t2WVhrTTJgr106dW2F1q9RYVE5IqL6Y6JS5VZ+qTic/gu8T1gA2rTwQfLlGwCA4jKdrG3JNTX3cYdOJ6DViTpHRSzt0smoqt/yaP9wDI0MNiQXtY261LYVWt+KReWIiOyDu36q/HAuGxM//dFOkZElzX3czS5cbubphr9KK2y6Z12jInXt0qkZH2C8uNrS/VlHhYjINtZ8fzNRqbL8u9OIP8CpH0fReKmRV6J16DM+eCgao7qHmlxPPH8dE1Yetfm+tW2HZmVaIiLrcXuyDU7+IfMAG7JJQaljkxQAmL3+BN6DZFJ9tr67b/SZ/IubUzCkcyt4uP29Wc7RW6GJiJo6bk+uUlLu+C/SpqwhKv/qBPDkuiTsOJmBxPPXsTX5ChLPX0dLX/scOHm9sAy3x+1BQkqGXe5HRER144hKFU83Dtc3FrPXJxklRsH+Xmju4468ovJ6b4nOKSy3qUQ+p4hIScoqdFiTeBHpOUUIC/DB5Jhwo5FCIiVhomLAL43GoubozZ/5f28jtkf9FgHghc2nUFyuQ7B/3UkHF92SksTtSMXKQ2lG/50s3XEa02MjsHBUpPMCI7KAKXQVbw/mbEri626/fzX1Jfdb+Lijlb99poFyCsvx9MZkTFh5FAOW77U4HaTfFl1zx5H+8EJOI1FDituRio8Oppkk8zoBfHQwDXE7Up0TGFEtmKhUkSSX3fzUKBWW6+x6PwHgRlE53nygJ8Z0t+8ohqWkQ6sTWLI91ewIjv7aku2p0PLobmoAZRU6rDyUVmublYfSUFZh3//2iOqLiUqVIH+WO28KMnOLseOUfUcxLCUd1hxeSORoaxIv1rmoXScq2xEpCROVKmEBPs4OgRrAicu5snYgeVs59WQu6eDhhaQk6TlFdm1H1FCYqFQRHO10KT4eakMVWWv8mS8vKWh/k6/V9waMkw4eXkhKIveXMf7SRkrDRKXK8apzZ8g1FJdpkVtUjvt7tcHgji1lf66oTF69nF+vFti0lqV60qE/vNDSfiAJlbt/eHghNYTJMeGoa0e8SqpsR6QkTFSqFDVA5VSyH/3szf+S/sD+s9myP9etjX+d/7PW23cmS/Z9zSUd+sML9e/XbA/w8EJqOB5uKkyPjai1zfTYCNZTIcXhv5FVWvp6ODsEagCxNwfV+T9rvUKZoy961ZMOrU4g8fx1lFboMG/oLSbbooM1XlYXjSOqr4WjIvHEwAiTZF0lAU8MZB0VUiYWD6kSGuDt7BDIwZr7uOP2DoHof0tLnMv6C3vPXLPLfYP9PbH47q6GpMNcgbdgfy88PbQjwlv6uExlWmdU02UFX8dbOCoSzwzvzMq05DKYqFQJ8LFPITBSrnYB3oYvvemxHeySqDw9tCNmD7nZcF99gbeaG4v+zC/Bij1nET+pl0scYuiMarqs4NtwPNxUeDS2vbPDIJKFKXSVMl2ps0MgBzv5Rz7+KqkAAPQOa1HvQxPeGx+NuUNvMZrucWaBN/10k/4wRlufY6maboYDq+mygi8RWcIRlSpvJlxwdgjUAG5duhtvP9gTGm+Pep/582eN+ifWFHiz96iKvUYjaku2gMo+LPz6FIZFBtttSqauBE9CZYJnz2cSkevgiEoVllFpGorLdZi5Ngm7fs2s973Sc4pQVqHDp4cu4OWtKdj40yVZn/vh92yrRz1qGy2x52hEXckWUHkUwXt7z8m+Z32fyQq+RE0bR1SqqMBkpakQAD4/crHe9zn7ZwE6v/SdrEq31b2373fDP8sZ9ahttGRYZLBdRyPkVsld9cNFzB5yi11GOFjBl4hqwxGVKo8PCHd2CNSA6jvtIwE4eiHH6iSlprpGPeoaLXlv7+92HY2QWyU3t7jcbiMcrOBLpEz2WvdWXxxRqVKk5Qm2JJ+9/m2pbdRDzuLcVT/UfhquntzRiL4RAWju7Y7c4nK73VPOM0M0XsjMKzHbVwmVdWdYwZeo4ShpFx5HVKrwfAuSQwJws43nAFliadRDznoROQkFIH80Qq2SMLVfuKy2LZvZZ0s/K/gSKYvSduExUany4K3tnB0CuQAB4PdrhbLaDo8Mwjvje2L2HR1kta85QmGPEQtbzhO6NVxmWzsOQo6ICkH8pF4I1hgnVKzgS9SwnF1mwRxO/VSRu2ODSK5W/l4Y0z0Ux9Jy8N6+83W2P/fnX0g8f91QjbW+azJsHY3ILpRXU0huO7lGRIVgWGQwK9MSOZEzyyxYwkSlSnpOkbNDoEZmzdFL2HM6Cy+Njqx1DYbee/t+x3v7fjfa0RPg64GcwjJZz/PzckNBVUE7oHI0wpb5ZGcublWrJJeo3EvUWClxFx4TlSpco0KOkJlXglnrkvD4wAh8fDANEuqeMdHPA8dP6oV7eobisx8uynrWPT1DMapbaL1HI7i4lajpUuIuPK5RqTI5JhwSR5jJzvRf9Nt+ycD7D0WbrMGo7TNLtqfizs6tZD8rPNAXMR0CMa5na8R0CLR5yoSLW4maLv0vKpb+67Zl3Vt9MVGp4uGmwpBONzk7DGqE9HO6LXw9cXjBEKyffnudC2z1n4EEtPKTt7tmckx4vWPV4+JWoqZJib+ocOqnmsdiO+B7O5yoS2ROVkGJYQ2G3Pnd7L9K8dLoSMzecMLB0Zni4laipkn/i0rNOiq2rnurL6cnKh988AH+85//ICMjA127dsWKFSsQGxvrlFj6RgQgqJk7sv6SV5uCyBrV53StmQdOuZIrq+0XR9IwfaC8rdBycXErUdOkpF9UnDr1s3HjRsybNw8vvvgiTpw4gdjYWIwcORKXLjlnq7BaJaFziMYpzybl0v9n2dzH3ebP15zTtWYe+KeLN2Q9R247IiI59L+o1HfdW305NVF566238Oijj+Kxxx5Dly5dsGLFCrRt2xbx8fFOi4mF9Knmf4rBGi98OKkXjv9rGNZPvx2P9AuTvfDa0pyuNfPAvh5qWc+S246IyJU4beqnrKwMx48fx/PPP290ffjw4Thy5IiTogLCA31wyH4n2JMLeXJQB/S/pSVuDQ/A8fQbZoc7YzoEIqZDIG4ND8ST65LqvGdtc7py54Hv69UGm5Ov1vms+3q1kdtVIiKX4bREJTs7G1qtFq1aGW+/bNWqFTIzM81+prS0FKWlf1fDzM/Pt3tcL4yKxJqjrFLb1DwxMALPjexseF3XuoxR3UPwocpMkuHviQl92yG8pa+sOV0588D9bm4JXw81Csu0Fu/j66lGv5tbyukqEZFLcfpiWqnGGLoQwuSaXlxcHJYsWeLQeLw91BgWGYTdqVkOfQ7V35juIRgVFYwn18nbEdOrXXOcuJRrNL2nkoDpsRFYOCrS6ufba7FZXQtW1SoJbz7QAzPWWh7BefOfPbgbh4gaJUkI4ZRlGWVlZfDx8cFXX32Fe++913B97ty5SE5OxoEDB0w+Y25EpW3btsjLy4O/v79d45u++icmK3ZSsxqrSgLu7BKElCv5RqMRLXzcIYRAbvHfZeB9PFQoLteh+r+lNZOLhJQMLN6Wisx881t+g/09sfjurhgRFYKyCh3WJF5Eek4RwgJ8MDkmHB5urlFOyFw/nXXsOhFRfeTn50Oj0cj6/nZaogIAt912G3r37o0PPvjAcC0yMhLjxo1DXFxcnZ+3pqO2KC7T4h/xPyA1o8DougQguq0GF7KLkFuszK3MbioJFWZOt/RyV6GkXGdyvYWXG9RqCYVlWvh6qDFrSHss+/Y3mGkKNwkY37cdJElCuwAfdG7lh31ns7Al+arRuTT6L9EhnVuZTQ60OmEyGgHA5JpWJ+pMLqrfq6WvJyBV1iBpbLU/zP2ZNZa+EVHT4TKJysaNGzF58mR8+OGHiImJwccff4yVK1fi119/RVhYWJ2fd3Siomfpt/DqXxoXs4uw/tglo992m/u4Y1LfdsgtLkd6ThHatvBGUakWu1L/RFH53+sNgpq5o5mXO4rLdQjVeOGzqX3h4abCsh2puHi9COGBPnhhVCQ83FQ4fPYaPj50AVfzihGq8cJj/dpD5SZhy4krKCzT4tbwFpjSLwJqlYQj57Kx6cQfKCrT4tbwAEzpVxl3XlE5pn1+DFfzSgzP01jYenstvxT3fnAYOYXlCPB1x+YnB+Amf/OVUvklSkREcrhMogJUFnx7/fXXkZGRgaioKLz99tsYOHCgrM82VKIil9wvan6hExFRU+ZSiUp9KC1RISIiorpZ8/3tGqsIiYiIqEliokJERESKxUSFiIiIFIuJChERESkWExUiIiJSLCYqREREpFhMVIiIiEixmKgQERGRYjFRISIiIsVyc3YA9aEvqpufn+/kSIiIiEgu/fe2nOL4Lp2oFBRUnmrctm1bJ0dCRERE1iooKIBGo6m1jUuf9aPT6XD16lX4+flBkux7qF9+fj7atm2Ly5cvN8pzhNg/19WY+wawf66O/XNtDdU/IQQKCgoQGhoKlar2VSguPaKiUqnQpk0bhz7D39+/Uf7LqMf+ua7G3DeA/XN17J9ra4j+1TWSosfFtERERKRYTFSIiIhIsZioWODp6YlFixbB09PT2aE4BPvnuhpz3wD2z9Wxf65Nif1z6cW0RERE1LhxRIWIiIgUi4kKERERKRYTFSIiIlIsJipERESkWExUzPjggw8QEREBLy8v9O7dG4cOHWrwGA4ePIixY8ciNDQUkiRhy5YtRu8LIbB48WKEhobC29sbgwcPxq+//mrUprS0FE899RRatmwJX19f3H333fjjjz+M2ty4cQOTJ0+GRqOBRqPB5MmTkZuba9Tm0qVLGDt2LHx9fdGyZUvMmTMHZWVlRm1OnTqFQYMGwdvbG61bt8Yrr7xi8QyHuLg43HrrrfDz80NQUBDuuece/Pbbb42mf/Hx8ejevbuhYFJMTAy+++67RtG3muLi4iBJEubNm9do+rd48WJIkmT0Exwc3Gj6d+XKFUyaNAmBgYHw8fFBz549cfz48UbTv/DwcJO/P0mSMGvWLJfvX0VFBf71r38hIiIC3t7eaN++PV555RXodDpDG1fun0WCjGzYsEG4u7uLlStXitTUVDF37lzh6+sr0tPTGzSOHTt2iBdffFFs2rRJABCbN282ev+1114Tfn5+YtOmTeLUqVPiwQcfFCEhISI/P9/QZsaMGaJ169Zi9+7dIikpSdxxxx2iR48eoqKiwtBmxIgRIioqShw5ckQcOXJEREVFiTFjxhjer6ioEFFRUeKOO+4QSUlJYvfu3SI0NFTMnj3b0CYvL0+0atVKjB8/Xpw6dUps2rRJ+Pn5iTfeeMNs3+666y6xatUqkZKSIpKTk8Xo0aNFu3btxF9//dUo+rdt2zbx7bffit9++0389ttv4oUXXhDu7u4iJSXF5ftW3bFjx0R4eLjo3r27mDt3bqP4uxNCiEWLFomuXbuKjIwMw09WVlaj6F9OTo4ICwsTU6dOFT/++KNIS0sTe/bsEb///nuj6J8QQmRlZRn93e3evVsAEPv27XP5/v373/8WgYGB4ptvvhFpaWniq6++Es2aNRMrVqxoNH9/5jBRqaFv375ixowZRtc6d+4snn/+eSdFJEwSFZ1OJ4KDg8Vrr71muFZSUiI0Go348MMPhRBC5ObmCnd3d7FhwwZDmytXrgiVSiUSEhKEEEKkpqYKAOLo0aOGNomJiQKAOHPmjBCiMmFSqVTiypUrhjbr168Xnp6eIi8vTwghxAcffCA0Go0oKSkxtImLixOhoaFCp9PV2b+srCwBQBw4cKBR9k8IIVq0aCE++eSTRtO3goICccstt4jdu3eLQYMGGRKVxtC/RYsWiR49eph9z9X7t2DBAjFgwACzfWsM/TNn7ty5okOHDkKn07l8/0aPHi2mTZtmdO2+++4TkyZNEkI0zr8/IYTg1E81ZWVlOH78OIYPH250ffjw4Thy5IiTojKVlpaGzMxMozg9PT0xaNAgQ5zHjx9HeXm5UZvQ0FBERUUZ2iQmJkKj0eC2224ztLn99tuh0WiM2kRFRSE0NNTQ5q677kJpaalhuDgxMRGDBg0yKhB011134erVq7h48WKd/cnLywMABAQENLr+abVabNiwAYWFhYiJiWk0fZs1axZGjx6NoUOHGl1vLP07d+4cQkNDERERgfHjx+PChQuNon/btm1Dnz598M9//hNBQUGIjo7GypUrDe+7ev9qKisrw9q1azFt2jRIkuTy/RswYAC+//57nD17FgDwyy+/4PDhwxg1ahSAxvf3p8dEpZrs7GxotVq0atXK6HqrVq2QmZnppKhM6WOpLc7MzEx4eHigRYsWtbYJCgoyuX9QUJBRm5rPadGiBTw8PGpto39d15+bEALz58/HgAEDEBUV1Wj6d+rUKTRr1gyenp6YMWMGNm/ejMjIyEbRtw0bNiApKQlxcXEm7zWG/t12221YvXo1du7ciZUrVyIzMxP9+vXD9evXXb5/Fy5cQHx8PG655Rbs3LkTM2bMwJw5c7B69Wqjz7hq/2rasmULcnNzMXXq1EbRvwULFmDChAno3Lkz3N3dER0djXnz5mHChAmNon+WuPTpyY4iSZLRayGEyTUlsCXOmm3MtbdHG1G1WKqueGbPno2TJ0/i8OHDJu+5cv86deqE5ORk5ObmYtOmTZgyZQoOHDhQ6/1coW+XL1/G3LlzsWvXLnh5eVmM1VX7BwAjR440/HO3bt0QExODDh064IsvvsDtt99u8Z6u0D+dToc+ffpg2bJlAIDo6Gj8+uuviI+Px8MPP1zrPV2hfzV9+umnGDlypNFv/Zbu6Qr927hxI9auXYt169aha9euSE5Oxrx58xAaGoopU6a4fP8s4YhKNS1btoRarTbJ9LKyskyyQmfS70CoLc7g4GCUlZXhxo0btbb5888/Te5/7do1ozY1n3Pjxg2Ul5fX2iYrKwuAaWZf3VNPPYVt27Zh3759aNOmTaPqn4eHB26++Wb06dMHcXFx6NGjB9555x2X79vx48eRlZWF3r17w83NDW5ubjhw4ADeffdduLm5WfxtyVX6Z46vry+6deuGc+fOufzfX0hICCIjI42udenSBZcuXTLcz5X7V116ejr27NmDxx57zHDN1fv3f//3f3j++ecxfvx4dOvWDZMnT8bTTz9tGN109f5ZwkSlGg8PD/Tu3Ru7d+82ur57927069fPSVGZioiIQHBwsFGcZWVlOHDggCHO3r17w93d3ahNRkYGUlJSDG1iYmKQl5eHY8eOGdr8+OOPyMvLM2qTkpKCjIwMQ5tdu3bB09MTvXv3NrQ5ePCg0ba0Xbt2ITQ0FOHh4SbxCyEwe/ZsfP3119i7dy8iIiIaVf/MEUKgtLTU5ft255134tSpU0hOTjb89OnTBxMnTkRycjLat2/v0v0zp7S0FKdPn0ZISIjL//3179/fpBTA2bNnERYWBqBx/be3atUqBAUFYfTo0YZrrt6/oqIiqFTGX9tqtdqwPdnV+2eR7GW3TYR+e/Knn34qUlNTxbx584Svr6+4ePFig8ZRUFAgTpw4IU6cOCEAiLfeekucOHHCsE36tddeExqNRnz99dfi1KlTYsKECWa3oLVp00bs2bNHJCUliSFDhpjdgta9e3eRmJgoEhMTRbdu3cxuQbvzzjtFUlKS2LNnj2jTpo3RFrTc3FzRqlUrMWHCBHHq1Cnx9ddfC39/f4tb0GbOnCk0Go3Yv3+/0TbCoqIiQxtX7t/ChQvFwYMHRVpamjh58qR44YUXhEqlErt27XL5vplTfddPY+jfM888I/bv3y8uXLggjh49KsaMGSP8/PwM/w9w5f4dO3ZMuLm5iaVLl4pz586JL7/8Uvj4+Ii1a9c2mr8/IYTQarWiXbt2YsGCBSbvuXL/pkyZIlq3bm3Ynvz111+Lli1biueee65R9M8SJipmvP/++yIsLEx4eHiIXr16GbbNNqR9+/YJACY/U6ZMEUJUbkNbtGiRCA4OFp6enmLgwIHi1KlTRvcoLi4Ws2fPFgEBAcLb21uMGTNGXLp0yajN9evXxcSJE4Wfn5/w8/MTEydOFDdu3DBqk56eLkaPHi28vb1FQECAmD17ttF2MyGEOHnypIiNjRWenp4iODhYLF682OL2M3P9AiBWrVplaOPK/Zs2bZrh35+bbrpJ3HnnnYYkxdX7Zk7NRMXV+6evO+Hu7i5CQ0PFfffdJ3799ddG07/t27eLqKgo4enpKTp37iw+/vhjo/ddvX9CCLFz504BQPz2228m77ly//Lz88XcuXNFu3bthJeXl2jfvr148cUXRWlpaaPonyWSENaWiCMiIiJqGFyjQkRERIrFRIWIiIgUi4kKERERKRYTFSIiIlIsJipERESkWExUiIiISLGYqBAREZFiMVEhIiODBw/GvHnznPb8ixcvQpIkJCcn19pu8eLF6NmzZ4PERETOw0SFiFzSs88+i++//97ZYRCRg7k5OwAiImsIIaDVatGsWTM0a9bM2eEQkYNxRIWIapWQkACNRoPVq1dj6tSpuOeee7Bs2TK0atUKzZs3x5IlS1BRUYH/+7//Q0BAANq0aYPPPvtM9v2PHTuG6OhoeHl5oU+fPjhx4oTR+/v374ckSdi5cyf69OkDT09PHDp0yGjqZ+fOnfDy8kJubq7RZ+fMmYNBgwYZXh85cgQDBw6Et7c32rZtizlz5qCwsNDwfnh4OJYtW4Zp06bBz88P7dq1w8cff2z9HxoR2Q0TFSKyaMOGDXjggQewevVqPPzwwwCAvXv34urVqzh48CDeeustLF68GGPGjEGLFi3w448/YsaMGZgxYwYuX75c5/0LCwsxZswYdOrUCcePH8fixYvx7LPPmm373HPPIS4uDqdPn0b37t2N3hs6dCiaN2+OTZs2Ga5ptVr897//xcSJEwEAp06dwl133YX77rsPJ0+exMaNG3H48GHMnj3b6F5vvvmmIWF68sknMXPmTJw5c8aqPzcisiOrjjAkokZPfxry+++/LzQajdi7d6/hvSlTpoiwsDCh1WoN1zp16iRiY2MNrysqKoSvr69Yv359nc/66KOPREBAgCgsLDRci4+PFwDEiRMnhBB/nyS+ZcsWo88uWrRI9OjRw/B6zpw5YsiQIYbXO3fuFB4eHiInJ0cIIcTkyZPF448/bnSPQ4cOCZVKJYqLi4UQQoSFhYlJkyYZ3tfpdCIoKEjEx8fX2RcicgyuUSEiE5s2bcKff/6Jw4cPo2/fvkbvde3aFSrV34OxrVq1QlRUlOG1Wq1GYGAgsrKy6nzO6dOn0aNHD/j4+BiuxcTEmG3bp0+fWu81ceJExMTE4OrVqwgNDcWXX36JUaNGoUWLFgCA48eP4/fff8eXX35p+IwQAjqdDmlpaejSpQsAGI3WSJKE4OBgWX0hIsfg1A8RmejZsyduuukmrFq1CkIIo/fc3d2NXkuSZPaaTqer8zk1710bX1/fWt/v27cvOnTogA0bNqC4uBibN2/GpEmTDO/rdDo88cQTSE5ONvz88ssvOHfuHDp06GBoZ2tfiMgxOKJCRCY6dOiAN998E4MHD4ZarcZ7773nkOdERkZizZo1KC4uhre3NwDg6NGjNt/voYcewpdffok2bdpApVJh9OjRhvd69eqFX3/9FTfffHO94yaihsMRFSIyq2PHjti3bx82bdrksAJwDz30EFQqFR599FGkpqZix44deOONN2y+38SJE5GUlISlS5fi/vvvh5eXl+G9BQsWIDExEbNmzUJycjLOnTuHbdu24amnnrJHV4jIQTiiQkQWderUCXv37jWMrNhbs2bNsH37dsyYMQPR0dGIjIzE8uXL8Y9//MOm+91yyy249dZb8dNPP2HFihVG73Xv3h0HDhzAiy++iNjYWAgh0KFDBzz44IN26AkROYokrJkkJiIiImpAnPohIiIixWKiQkQOs2zZMkOp+5o/I0eOdHZ4ROQCOPVDRA6Tk5ODnJwcs+95e3ujdevWDRwREbkaJipERESkWJz6ISIiIsViokJERESKxUSFiIiIFIuJChERESkWExUiIiJSLCYqREREpFhMVIiIiEixmKgQERGRYv1/O/jSaTtLyYEAAAAASUVORK5CYII=",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.scatter(dataset['km_driven'],dataset['selling_price'])\n",
    "plt.xlabel('km_driven')\n",
    "plt.ylabel('sales price')\n",
    "plt.title('km_driven')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "0de7d6fb",
   "metadata": {},
   "outputs": [],
   "source": [
    "continous_features.remove(\"name\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "id": "fe3b4ee2",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "for feature in continous_features:\n",
    "    data=dataset.copy()\n",
    "    if 0 in data[feature].unique():\n",
    "        pass\n",
    "    else:\n",
    "        data[feature]=np.log(data[feature])\n",
    "        data['selling_price']=np.log(data['selling_price'])\n",
    "        plt.scatter(data[feature],data['selling_price'])\n",
    "        plt.xlabel(feature)\n",
    "        plt.ylabel('sales price')\n",
    "        plt.title(feature)\n",
    "        plt.show()\n",
    "        "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "id": "896cbf46",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAjMAAAGxCAYAAACXwjeMAAAAOXRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjcuMiwgaHR0cHM6Ly9tYXRwbG90bGliLm9yZy8pXeV/AAAACXBIWXMAAA9hAAAPYQGoP6dpAAA5p0lEQVR4nO3dfVhUdeL//9cIOAiCioSAophUZCHajTdpAmtiuKLkWplbS5vbtu36M+9L3VK3lDQ1d3XTzfrUftxqa11ky3STNQW0sBQpyTJvoDR10TRHQWEc5vdHX+bTBCiMwOHA83FdXnDe5z3DC65rmlfnvOcci9PpdAoAAMCkWhkdAAAA4EpQZgAAgKlRZgAAgKlRZgAAgKlRZgAAgKlRZgAAgKlRZgAAgKlRZgAAgKlRZgAAgKlRZgBckVdffVUWi0VFRUWusQcffFCRkZFu8yIjI/Xggw82araGsnXrVlksFm3dutXoKAAkeRsdAEDLsG7dOgUGBhodo17cdNNN+vDDD9WzZ0+jowAQZQZAI+nTp4/REa6Y3W6XxWJRYGCg+vfvb3QcAP8Pp5mAFurEiRP69a9/rYiICFmtVl111VUaOHCg/vOf/7jm/Oc//9GQIUMUGBgoPz8/DRw4UJs3b/bo5/34NFPlqZo33nhDs2fPVnh4uAIDA3XHHXdo3759bo91Op1asGCBunXrJl9fX91yyy3KzMxUfHy84uPj65xjxIgRWrdunXr16iVfX19dffXV+tOf/uQ2rzLfmjVrNHXqVHXu3FlWq1UHDhyo8TTTjh07lJycrI4dO8rX11c9evTQpEmT3Obs379f48aNU0hIiKxWq66//nr9+c9/rtPvAMAdR2aAFuqBBx5QXl6e5s+fr2uvvVbfffed8vLy9O2330qS/va3v+kXv/iFRo0apb/+9a/y8fHRX/7yFw0bNkzvvfeehgwZUi85Zs2apYEDB+qll16SzWbT448/ruTkZH3++efy8vKSJM2ePVtpaWn69a9/rdGjR+vw4cP61a9+JbvdrmuvvbbOPzM/P1+TJk3S3LlzFRoaqtdee02PPfaYysvLNW3aNLe5M2fO1IABA7Rq1Sq1atVKISEhOn78eJXnfO+995ScnKzrr79eS5cuVdeuXVVUVKRNmza55uzdu1e33XabunbtqiVLlig0NFTvvfeeJk6cqJMnT2rOnDl1/l0ASHICaJHatm3rnDRpUrX7SkpKnEFBQc7k5GS3cYfD4YyNjXX27dvXNfbKK684JTkLCwtdY6mpqc5u3bq5PbZbt27O1NRU1/aWLVuckpzDhw93m/fWW285JTk//PBDp9PpdJ46dcpptVqd9957r9u8Dz/80CnJGRcXV8vf+P9yWCwWZ35+vtv40KFDnYGBgc6SkhK3fIMHD67yHJX7tmzZ4hrr0aOHs0ePHs7z58/X+LOHDRvm7NKli/PMmTNu4xMmTHD6+vo6T506VaffBcD3OM0EtFB9+/bVq6++qmeeeUa5ubmy2+2ufR988IFOnTql1NRUXbx40fWvoqJCd955pz7++GOVlJTUS46RI0e6bffq1UuS9NVXX0mScnNzVVZWpnvuucdtXv/+/at8Yqq2brjhBsXGxrqNjRs3TjabTXl5eW7jP/vZzy77fF9++aUOHjyo8ePHy9fXt9o5Fy5c0ObNm3XXXXfJz8/P7e86fPhwXbhwQbm5uR79PkBLR5kBWqg333xTqampeumllzRgwAAFBQXpF7/4hY4fP67//ve/kqQxY8bIx8fH7d/ChQvldDp16tSpesnRsWNHt22r1SpJOn/+vCS5Tnt16tSpymOrG6uN0NDQGscqf16lsLCwyz7fiRMnJEldunSpcc63336rixcvavny5VX+psOHD5cknTx5sta/A4D/w5oZoIUKDg7WsmXLtGzZMn399dd6++239cQTT6i4uFiTJ0+WJC1fvrzGT+14WiTqqrLsVBasHzp+/LhHR2eqW/NSOfbjcmWxWC77fFdddZUk6ciRIzXO6dChg7y8vPTAAw/od7/7XbVzunfvftmfBaAqygwAde3aVRMmTNDmzZu1fft2DRw4UO3bt9fevXs1YcIEQ7P169dPVqtVb775pkaPHu0az83N1VdffeVRmfnss8/0ySefuJ1qev311xUQEKCbbrqpzs937bXXqkePHvqf//kfTZkyxXV06Yf8/PyUkJCg3bt3q1evXmrdunWdfw6A6lFmgBbozJkzSkhI0Lhx4xQdHa2AgAB9/PHH+ve//63Ro0erbdu2Wr58uVJTU3Xq1CmNGTNGISEhOnHihD755BOdOHFCK1eubJSsQUFBmjJlitLS0tShQwfdddddOnLkiObNm6ewsDC1alX3s+Xh4eEaOXKk5s6dq7CwMP3tb39TZmamFi5cKD8/P49y/vnPf1ZycrL69++vyZMnq2vXrvr666/13nvv6bXXXpMk/fGPf9SgQYN0++2369FHH1VkZKTOnj2rAwcO6J133tH777/v0c8GWjrKDNAC+fr6ql+/flqzZo2Kiopkt9vVtWtXPf7445oxY4Yk6f7771fXrl21aNEiPfLIIzp79qxCQkLUu3fvRr8twfz58+Xv769Vq1bplVdeUXR0tFauXKnZs2erffv2dX6+3r1765e//KXmzJmj/fv3Kzw8XEuXLnWdXvPEsGHDlJ2drT/84Q+aOHGiLly4oC5durgtcO7Zs6fy8vL09NNP6/e//72Ki4vVvn17XXPNNa51MwDqzuJ0Op1GhwCAuiosLFR0dLTmzJmjWbNm1fpxkZGRuvHGG7V+/foGTAegMXFkBkCT98knn+iNN97QbbfdpsDAQO3bt0+LFi1SYGCgxo8fb3Q8AAajzABo8vz9/bVz5069/PLL+u6779SuXTvFx8dr/vz5rk9VORwOXepAs8VicV1RGEDzwmkmAM1CZGSk60J71YmLi6tyLyUAzQNHZgA0C++8847Kyspq3B8QENCIaQA0Jo7MAAAAU+N2BgAAwNSa/WmmiooKHT16VAEBAbW6LDkAADCe0+nU2bNnFR4eftmLYzb7MnP06FFFREQYHQMAAHjg8OHDl7yJq9QCykzlor/Dhw8rMDDQ4DQA6pPdbtemTZuUmJgoHx8fo+MAqEc2m00RERG1Wrzf7MtM5amlwMBAygzQzNjtdvn5+SkwMJAyAzRTtVkiwgJgAABgapQZAABgapQZAABgapQZAABgapQZAABgapQZAABgapQZAABgapQZAABgapQZAKbkcDiUlZWl7OxsZWVlyeFwGB0JgEEoMwBMJz09XVFRURo6dKiWLl2qoUOHKioqSunp6UZHA2AAQ8tMdna2kpOTFR4eLovFooyMjCpzPv/8c40cOVLt2rVTQECA+vfvr6+//rrxwwJoEtLT0zVmzBjFxMQoJydHb7zxhnJychQTE6MxY8ZQaIAWyNAyU1JSotjYWK1YsaLa/QcPHtSgQYMUHR2trVu36pNPPtGTTz4pX1/fRk4KoClwOByaOnWqRowYoYyMDPXr109t2rRRv379lJGRoREjRmjatGmccgJaGENvNJmUlKSkpKQa98+ePVvDhw/XokWLXGNXX331JZ+zrKxMZWVlrm2bzSbp+xvS2e32K0wMwEhZWVkqKirSmjVr5HA4XK/pyq/Tp0/X4MGDtWXLFsXFxRkZFcAVqst7dpO9a3ZFRYXeffddzZgxQ8OGDdPu3bvVvXt3zZw5UykpKTU+Li0tTfPmzasyvmnTJvn5+TVgYgANLTs7W5J05MgRFRcXa+/evTp9+rT27Nmjnj17qry8XJK0ceNGlZSUGBkVwBUqLS2t9dwmW2aKi4t17tw5Pfvss3rmmWe0cOFC/fvf/9bo0aMv+X9dM2fO1JQpU1zbNptNERERSkxMVGBgYGPFB9AA/P39tXTpUh04cEAvv/yyioqKXPsiIyM1fvx4Sd8f9eXIDGBulWdWasPidDqdDZil1iwWi9atW+c66nL06FF17txZ9913n15//XXXvJEjR8rf319vvPFGrZ7XZrOpXbt2OnPmDGUGMDmHw6Hw8HAVFxdrxIgRevzxx3XkyBF16dJFCxcu1Pr16xUSEqKjR4/Ky8vL6LgArkBd3r+b7Eezg4OD5e3trZ49e7qNX3/99XyaCWjBfvj/X5XfN5H/JwNgkCZbZlq3bq1bb71V+/btcxv/8ssv1a1bN4NSATBSTk6OTpw4obS0NBUUFGjw4MG67777NHjwYH322WdasGCBiouLlZOTY3RUAI3I0DUz586d04EDB1zbhYWFys/PV1BQkLp27arp06fr3nvv1eDBg5WQkKB///vfeuedd7R161bjQgMwzLFjxyRJEyZM0PTp07VlyxZt3LhRSUlJSkhIUGlpqWbNmuWaB6BlMLTM7Ny5UwkJCa7tyoW7qampevXVV3XXXXdp1apVSktL08SJE3Xdddfpn//8pwYNGmRUZAAGCgsLkyQVFBSof//+iouLU0lJieLi4uTl5aWCggK3eQBahiazALihsAAYaD4cDoeioqIUExOjjIwMORwObdiwQcOHD5eXl5dSUlJUUFCg/fv3swAYMLlmsQAYAH7My8tLS5Ys0fr165WSkqLc3FydP39eubm5SklJ0fr167V48WKKDNDCNNnrzABAdUaPHq21a9dq6tSpGjx4sGu8e/fuWrt2rUaPHm1gOgBG4DQTAFNyOBxVFgBzRAZoPury/s2RGQCm5OXlVWUBMICWiTUzAADA1CgzAADA1CgzAADA1CgzAADA1CgzAADA1CgzAADA1CgzAADA1CgzAADA1CgzAADA1CgzAADA1CgzAEzJ4XAoKytL2dnZysrKksPhMDoSAINQZgCYTnp6uqKiojR06FAtXbpUQ4cOVVRUlNLT042OBsAAlBkAppKenq4xY8YoJiZGOTk5euONN5STk6OYmBiNGTOGQgO0QBan0+k0OkRDqsstxAE0bQ6HQ1FRUYqJiVFGRoYcDoc2bNig4cOHy8vLSykpKSooKND+/fu5izZgcnV5/+bIDADTyMnJUVFRkWbNmqVWrdz/89WqVSvNnDlThYWFysnJMSghACNQZgCYxrFjxyRJN954Y7X7K8cr5wFoGbyNDgAAtRUWFiZJKigoUKdOndSzZ09duHBBvr6+2rt3r44fP+42D0DLwJoZAKZRuWamqKioxjndu3dnzQzQDLBmBkCz5OXlpa+++uqSc4qKiigyQAtDmQFgGoWFhao8mFzdAmBJcjqdKiwsbPRsAIxDmQFgGtHR0a7vO3fu7Lbvh9s/nAeg+WMBMADTKC8vd30fExOjm2++WQcPHlSPHj1UXl6uw4cPV5kHoPmjzAAwDS8vL9c9mDZs2OAa37NnT5V5AFoOTjMBMI2xY8fW6zwAzQNlBoBpJCQkuG1brVbdfffdslqtl5wHoHmjzAAwjX/9619u22VlZfrHP/6hsrKyS84D0LxRZgCYxr59+yRJ/v7+1e6vHK+cB6BlYAEwANNo3bq1JKmkpERXXXWVAgICdPr0aXXo0EFnz57ViRMn3OYBaBk4MgPANMaNG+f6/sSJEzp06JBOnz6tQ4cOuYrMj+cBaP44MgPANG655Ra37cqjMz88KlPdPADNG2UGgGkcPXrUbfvEiRNuJaameQCaN04zATCNjIyMep0HoHmgzAAwjbNnz7ptW61WRUdHV7nOzI/nAWjeKDMATOPUqVOu7xMTE5WZmak5c+YoMzNTiYmJ1c4D0PyxZgaAaXz66aeu7/ft26fBgwe7tiMjI6udB6D5o8wAMI3Km0xK0pEjRxQbG6vy8nK1bt1aBQUF1c4D0PxRZgCYhtVqdd26wOFw6JNPPqlxHoCWgzIDwDQ+//xzXX311ZIki8WiqKgo174DBw7I6XS65gFoOSgzAEyjc+fOru+dTqf2799/2XkAmj8+zQTANF544QVJ3x+VqU7leOU8AC2DoWUmOztbycnJCg8Pl8ViqXKhqwcffFAWi8XtX//+/Y0JC8BwBw8elCStXr1anTp1ctvXqVMnvfjii27zALQMhpaZkpISxcbGasWKFTXOufPOO3Xs2DHXvw0bNjRiQgBNSY8ePSRJv/rVr/Tf//7Xbd9///tfPfzww27zALQMhq6ZSUpKUlJS0iXnWK1WhYaGNlIiAE3ZI488osmTJ9dqHoCWo8kvAN66datCQkLUvn17xcXFaf78+QoJCalxfllZmeujm5Jks9kkSXa7XXa7vcHzAmg4mzdvrvW8YcOGNXAaAA2pLu/ZTbrMJCUl6e6771a3bt1UWFioJ598Uj/5yU+0a9euGq8jkZaWpnnz5lUZ37Rpk/z8/Bo6MoAG9OSTT9Zq3qxZs7hwHmBypaWltZ5rcVZemMFgFotF69atU0pKSo1zjh07pm7duunvf/+7Ro8eXe2c6o7MRERE6OTJkwoMDKzv2AAaUXh4uE6ePKmrrrpKBw8e1MqVK5WVlaW4uDg9+uij6tGjh06cOKHg4GAdPXrU6LgAroDNZlNwcLDOnDlz2ffvJn1k5sfCwsLUrVu3Gq8tIX2/xqa6ozY+Pj7y8fFpyHgAGkmrVq3k7++vyZMn67rrrtPw4cPl5eXl9pFtXu+AudXlNWyq68x8++23Onz4sMLCwoyOAsAAMTExkr7/5FJycrJyc3N1/vx55ebmKjk5WcXFxW7zALQMhh6ZOXfunA4cOODaLiwsVH5+voKCghQUFKS5c+fqZz/7mcLCwlRUVKRZs2YpODhYd911l4GpARhl+vTp2rJliyRpw4YNNV6qYfr06Y0ZC4DBDC0zO3fuVEJCgmt7ypQpkqTU1FStXLlSe/bs0f/+7//qu+++U1hYmBISEvTmm28qICDAqMgA6kFpaam++OKLOj8uODjY7WaT1fH19VVwcLDy8vI8yhYdHc2HBQCTaTILgBuKzWZTu3btarWACEDjyMvL080332x0jGrt2rVLN910k9ExgBavLu/fploADKB5iI6O1q5duzx+/Pvvv6/Fixe7XQU4NDRUU6dO1U9+8pMrzgbAXDgyA8CUHA6HXvnHes18fbvSxg3UL+8eIS8vL6NjAagnHJkB0Ox5eXnplgGD5J/vrVsG9KfIAC2YqT6aDQAA8GOUGQAAYGqUGQAAYGqUGQAAYGqUGQAAYGqUGQAAYGqUGQAAYGqUGQAAYGqUGQAAYGqUGQAAYGqUGQAAYGqUGQAAYGqUGQAAYGqUGQAAYGqUGQAAYGqUGQAAYGqUGQAAYGqUGQAAYGqUGQAAYGqUGQAAYGqUGQAAYGqUGQAAYGqUGQAAYGqUGQAAYGqUGQAAYGqUGQAAYGqUGQAAYGqUGQAAYGqUGQAAYGqUGQAAYGqUGQAAYGqUGQAAYGqUGQAAYGqUGQAAYGqUGQAAYGqUGQAAYGqUGQAAYGqUGQAAYGqUGQAAYGqUGQAAYGqUGQAAYGqGlpns7GwlJycrPDxcFotFGRkZNc595JFHZLFYtGzZskbLBwAAmj5Dy0xJSYliY2O1YsWKS87LyMjQjh07FB4e3kjJAACAWXgb+cOTkpKUlJR0yTnffPONJkyYoPfee08//elPGykZAAAwC0PLzOVUVFTogQce0PTp03XDDTfU6jFlZWUqKytzbdtsNkmS3W6X3W5vkJwAjHHx4kXXV17fQPNSl9d0ky4zCxculLe3tyZOnFjrx6SlpWnevHlVxjdt2iQ/P7/6jAfAYIfPSZK3cnNz9U2B0WkA1KfS0tJaz22yZWbXrl364x//qLy8PFksllo/bubMmZoyZYpr22azKSIiQomJiQoMDGyIqAAM8snXp6Q9O9W/f3/Fdg0yOg6AelR5ZqU2mmyZycnJUXFxsbp27eoaczgcmjp1qpYtW6aioqJqH2e1WmW1WquM+/j4yMfHp6HiAjCAt7e36yuvb6B5qctrusmWmQceeEB33HGH29iwYcP0wAMP6Je//KVBqQAAQFNjaJk5d+6cDhw44NouLCxUfn6+goKC1LVrV3Xs2NFtvo+Pj0JDQ3Xdddc1dlQAANBEGVpmdu7cqYSEBNd25VqX1NRUvfrqqwalAgAAZmJomYmPj5fT6az1/JrWyQAAgJaLezMBAABTo8wAAABTo8wAAABTo8wAAABTo8wAAABTo8wAAABTo8wAAABTo8wAAABTo8wAAABTo8wAAABT87jM5OTk6P7779eAAQP0zTffSJLWrFmjbdu21Vs4AACAy/GozPzzn//UsGHD1KZNG+3evVtlZWWSpLNnz2rBggX1GhAAAOBSPCozzzzzjFatWqXVq1fLx8fHNX7bbbcpLy+v3sIBAABcjkdlZt++fRo8eHCV8cDAQH333XdXmgkAAKDWPCozYWFhOnDgQJXxbdu26eqrr77iUAAAALXlUZl55JFH9Nhjj2nHjh2yWCw6evSoXnvtNU2bNk2//e1v6zsjAABAjbw9edCMGTN05swZJSQk6MKFCxo8eLCsVqumTZumCRMm1HdGAACAGnlUZiRp/vz5mj17tvbu3auKigr17NlTbdu2rc9sAAAAl+VRmTlz5owcDoeCgoJ0yy23uMZPnTolb29vBQYG1ltAAACAS/FozczYsWP197//vcr4W2+9pbFjx15xKAAAgNryqMzs2LFDCQkJVcbj4+O1Y8eOKw4FAABQWx6VmbKyMl28eLHKuN1u1/nz5684FAAAQG15VGZuvfVWvfjii1XGV61apZtvvvmKQwEAANSWRwuA58+frzvuuEOffPKJhgwZIknavHmzPv74Y23atKleAwIAAFyKR0dmBg4cqA8//FARERF666239M477ygqKkqffvqpbr/99vrOCAAAUCOPrzPTu3dvvfbaa/WZBQAAoM5qXWZsNpvr+jE2m+2Sc7nODAAAaCy1LjMdOnTQsWPHFBISovbt28tisVSZ43Q6ZbFY5HA46jUkAABATWpdZt5//30FBQVJkrZs2dJggQAAAOqi1mUmLi5OknTx4kVt3bpVDz30kCIiIhosGAAAQG3UeQGwt7e3Fi9erNTU1IbIA6AJKzxZopKyqhfMNMrBEyWur97eHn+eod75W73VPdjf6BhAi+HRq3/IkCHaunWrHnzwwXqOA6CpKjxZooTFW42OUa2pa/cYHaGKLdPiKTRAI/GozCQlJWnmzJkqKCjQzTffLH9/9xfsyJEj6yUcgKaj8ojMsnt7KyqkrcFpvldyvkzrt36oEfED5N/GanQcSdKB4nOa9GZ+kzqCBTR3HpWZRx99VJK0dOnSKvv4NBPQvEWFtNWNndsZHUPS9/eDO36VdFO3DvLx8TE6DgCDeFRmKioq6jsHAACARzy6nQEAAEBT4XGZ2bx5s0aMGKEePXooKipKI0aM0H/+85/6zAYAAHBZHpWZFStW6M4771RAQIAee+wxTZw4UYGBgRo+fLhWrFhR3xkBAABq5NGambS0ND3//POaMGGCa2zixIkaOHCg5s+f7zYOAADQkDw6MmOz2XTnnXdWGU9MTLzsTSgBAADqk0dlZuTIkVq3bl2V8X/9619KTk6+4lAAAAC15dFppuuvv17z58/X1q1bNWDAAElSbm6utm/frqlTp+pPf/qTa+7EiRPrJykAAEA1PCozL7/8sjp06KC9e/dq7969rvH27dvr5Zdfdm1bLBbKDAAAaFAelZnCwsL6zgEAAOCRBr1oXmBgoA4dOlTj/uzsbCUnJys8PFwWi0UZGRlu++fOnavo6Gj5+/urQ4cOuuOOO7Rjx46GjAwAAEymQcuM0+m85P6SkhLFxsbWeG2aa6+9VitWrNCePXu0bds2RUZGKjExUSdOnGiIuAAAwIQ8Os1UX5KSkpSUlFTj/nHjxrltL126VC+//LI+/fRTDRkypKHjAQAAEzC0zNRFeXm5XnzxRbVr106xsbE1zisrK1NZWZlru/K6N3a7XXa7vcFzAs3VxYsXXV+bymupMkdTySM1zb8TYEZ1ef00+TKzfv16jR07VqWlpQoLC1NmZqaCg4NrnJ+WlqZ58+ZVGd+0aZP8/PwaMirQrB0+J0ne2rZtm75qa3Qad5mZmUZHcGnKfyfATEpLS2s91+K83MKWKxAYGKj8/HxdffXVlw9isWjdunVKSUlxGy8pKdGxY8d08uRJrV69Wu+//7527NihkJCQap+nuiMzEREROnnypAIDA6/o9wFass+O2pSyMlcZj/bXDeFN47Vkt9uVmZmpoUOHysfHx+g4kprm3wkwI5vNpuDgYJ05c+ay798NemSmPnqSv7+/oqKiFBUVpf79++uaa67Ryy+/rJkzZ1Y732q1ymq1Vhn38fFpMv+xA8zI29vb9bWpvZaa0uu7Kf+dADOpy+unQT/NtHHjRnXu3Llen9PpdLodeQEAAC2bR0dmpkyZUu24xWKRr6+voqKiNGrUKA0aNOiSz3Pu3DkdOHDAtV1YWKj8/HwFBQWpY8eOmj9/vkaOHKmwsDB9++23euGFF3TkyBHdfffdnsQGAADNkEdlZvfu3crLy5PD4dB1110np9Op/fv3y8vLS9HR0XrhhRc0depUbdu2TT179qzxeXbu3KmEhATXdmVJSk1N1apVq/TFF1/or3/9q06ePKmOHTvq1ltvVU5Ojm644QZPYgMAgGbIozIzatQoBQUF6ZVXXnEtyrHZbBo/frwGDRqkhx9+WOPGjdPkyZP13nvv1fg88fHxl1xXk56e7kk8AADQgni0Zua5557T008/7ba6ODAwUHPnztWiRYvk5+enp556Srt27aq3oAAAANXxqMycOXNGxcXFVcZPnDjhukhd+/btVV5efmXpAAAALsOjMjNq1Cg99NBDWrdunY4cOaJvvvlG69at0/jx413Xifnoo4907bXX1mdWAACAKjxaM/OXv/xFkydP1tixY12X7vb29lZqaqqef/55SVJ0dLReeuml+ksKAABQDY/KTNu2bbV69Wo9//zzOnTokJxOp3r06KG2bf/v2t29e/eur4wAAAA1uqIrALdt21a9evWqrywAmrAyxwW18v1GhbZ9auXbNG46dPHiRR29eFSfn/rcdeVdoxXazqmV7zcqc1yQ1M7oOECL4NGrv6SkRM8++6w2b96s4uJiVVRUuO0/dOhQvYQD0HQcLflK/t2Xa9ZHRiep6oV/v2B0BDf+3aWjJb11szoZHQVoETwqM7/61a+UlZWlBx54QGFhYbJYLPWdC0ATE+7fTSWF/5/+eG9v9QhpOkdmtm/broGDBjaZIzMHi8/psTfzFZ7QzegoQIvh0at/48aNevfddzVw4MD6zgOgibJ6+ariQmd1D7xOPTs2jdMndrtdhd6Fuj7o+iZzU8eKC2dUceGErF6+RkcBWgyPPprdoUMHBQUF1XcWAACAOvOozDz99NN66qmnVFpaWt95AAAA6sSj00xLlizRwYMH1alTJ0VGRlY5vJuXl1cv4QAAAC7HozJTeZVfAAAAo3lUZubMmVPfOQAAADzi0ZoZAACApqLWR2aCgoL05ZdfKjg4WB06dLjktWVOnTpVL+EAAAAup9Zl5vnnn1dAQIAkadmyZQ2VBwAAoE5qXWZSU1Or/R4AAMBItS4zNput1k8aGBjoURgAAIC6qnWZad++/WXvweR0OmWxWORwOK44GAAAQG3Uusxs2bKlIXMAAAB4pNZlJi4uriFzAAAAeKTWZebTTz+t9ZP26tXLozAAAAB1Vesy07t3b1ksFjmdzkvOY80MAABoTLUuM4WFhQ2ZAwAAwCO1LjPdunVryBwAAAAe8fjeTGvWrNHAgQMVHh6ur776StL3Vwb+17/+VW/hAAAALsejMrNy5UpNmTJFw4cP13fffedaI9O+fXtudQAAABqVR2Vm+fLlWr16tWbPni0vLy/X+C233KI9e/bUWzgAAIDL8ajMFBYWqk+fPlXGrVarSkpKrjgUAABAbXlUZrp37678/Pwq4xs3blTPnj2vNBMAAECt1frTTD80ffp0/e53v9OFCxfkdDr10Ucf6Y033lBaWppeeuml+s4IAABQI4/KzC9/+UtdvHhRM2bMUGlpqcaNG6cuXbroj3/8o8aOHVvfGQEAAGrkUZk5f/68fv7zn+vhhx/WyZMndejQIW3fvl1dunSp73wAmojz9u8/tVjwzRmDk/yfkvNl2nlCCv3qtPzbWI2OI0k6UHzO6AhAi+NRmRk1apRGjx6t3/zmN/L29tbIkSPl4+OjkydPaunSpXr00UfrOycAgx38f2/ST6Q3tU8semvNgY+NDlGFv9Wj/7wC8IBHr7a8vDw9//zzkqS1a9eqU6dO2r17t/75z3/qqaeeoswAzVDiDaGSpB4hbdXGx+sysxvHvmNnNHXtHi0ZE6PrwtoZHcfF3+qt7sH+RscAWgyPykxpaakCAgIkSZs2bdLo0aPVqlUr9e/f33U1YADNS5B/a43t29XoGG4uXrwoSepxlb9u7Nx0ygyAxuXRR7OjoqKUkZGhw4cP67333lNiYqIkqbi4WIGBgfUaEAAA4FI8KjNPPfWUpk2bpsjISPXr108DBgyQ9P1RmuoupgcAANBQPDrNNGbMGA0aNEjHjh1TbGysa3zIkCG666676i0cAADA5Xi83D40NFShoaFuY3379r3iQAAAAHXh0WkmAACApoIyAwAATI0yAwAATM3QMpOdna3k5GSFh4fLYrEoIyPDtc9ut+vxxx9XTEyM/P39FR4erl/84hc6evSocYEBAECTY2iZKSkpUWxsrFasWFFlX2lpqfLy8vTkk08qLy9P6enp+vLLLzVy5EgDkgIAgKbK0JuHJCUlKSkpqdp97dq1U2ZmptvY8uXL1bdvX3399dfq2rVpXYkUAAAYw1R3Qjtz5owsFovat29f45yysjKVlZW5tm02m6TvT1vZ7faGjgigEVXezuDixYu8voFmpi6vadOUmQsXLuiJJ57QuHHjLnnLhLS0NM2bN6/K+KZNm+Tn59eQEQE0ssPnJMlbubm5+qbA6DQA6lNpaWmt55qizNjtdo0dO1YVFRV64YUXLjl35syZmjJlimvbZrMpIiJCiYmJ3DcKaGY++fqUtGen+vfvr9iuQUbHAVCPKs+s1EaTLzN2u1333HOPCgsL9f7771+2kFitVlmt1irjPj4+8vHxaaiYAAzg7e3t+srrG2he6vKabtJlprLI7N+/X1u2bFHHjh2NjgQAAJoYQ8vMuXPndODAAdd2YWGh8vPzFRQUpPDwcI0ZM0Z5eXlav369HA6Hjh8/LkkKCgpS69atjYoNAACaEEPLzM6dO5WQkODarlzrkpqaqrlz5+rtt9+WJPXu3dvtcVu2bFF8fHxjxQQAAE2YoWUmPj5eTqezxv2X2gcAACBxbyYAAGBylBkAAGBqlBkAAGBqlBkAAGBqlBkAAGBqlBkAAGBqlBkAAGBqlBkAAGBqlBkAAGBqlBkAAGBqlBkAAGBqlBkAAGBqlBkAAGBqlBkAAGBqlBkAAGBqlBkAAGBqlBkAAGBqlBkAAGBqlBkAAGBqlBkAAGBqlBkAAGBqlBkAAGBqlBkAAGBqlBkAAGBqlBkAAGBqlBkAAGBqlBkAAGBqlBkAAGBqlBkAAGBqlBkAAGBqlBkAAGBqlBkAAGBqlBkAAGBqlBkAAGBqlBkAAGBqlBkAAGBqlBkAAGBqlBkAAGBqlBkAAGBqlBkAAGBqlBkAAGBqlBkAAGBqlBkAAGBqlBkAAGBqhpaZ7OxsJScnKzw8XBaLRRkZGW7709PTNWzYMAUHB8tisSg/P9+QnAAAoOkytMyUlJQoNjZWK1asqHH/wIED9eyzzzZyMgAAYBbeRv7wpKQkJSUl1bj/gQcekCQVFRU1UiIAAGA2hpaZhlBWVqaysjLXts1mkyTZ7XbZ7XajYgFoABcvXnR95fUNNC91eU03uzKTlpamefPmVRnftGmT/Pz8DEgEoKEcPidJ3srNzdU3BUanAVCfSktLaz232ZWZmTNnasqUKa5tm82miIgIJSYmKjAw0MBkAOrbJ1+fkvbsVP/+/RXbNcjoOADqUeWZldpodmXGarXKarVWGffx8ZGPj48BiQA0FG9vb9dXXt9A81KX1zTXmQEAAKZm6JGZc+fO6cCBA67twsJC5efnKygoSF27dtWpU6f09ddf6+jRo5Kkffv2SZJCQ0MVGhpqSGYAANC0GHpkZufOnerTp4/69OkjSZoyZYr69Omjp556SpL09ttvq0+fPvrpT38qSRo7dqz69OmjVatWGZYZAAA0LYYemYmPj5fT6axx/4MPPqgHH3yw8QIBAADTYc0MAAAwNcoMAAAwNcoMAAAwNcoMAAAwNcoMAAAwNcoMAAAwNcoMAAAwNcoMAFMqLy/Xay+v1KnMVXrt5ZUqLy83OhIAg1BmAJjOjBkz5O/vr8VPP6mzeeu1+Okn5e/vrxkzZhgdDYABmt1dswE0bzNmzNBzzz2nTp066deTntD/HOmoh7p8qxeXPavnnntOkrRo0SKDUwJoTBbnpe4n0AzYbDa1a9dOZ86cUWBgoNFxAEgqLS3VF198UefHlZeXa9CgQWrXrp1ee+01/eqRR/XN8WJ1Dg3RS39ZqZ///Oc6c+aMtm3bptatW3uULTo6Wn5+fh49FkD9qcv7N2UGQKPLy8vTzTffbHSMau3atUs33XST0TGAFq8u79+cZgLQ6KKjo7Vr1646P27hwoV66623XNs9e96gG/sOUsFH27R372eu8XvuuUePP/64x9kAmAtlBkCj8/Pz8+joR69evVxl5uzZs7JardqwYYOGv7hcZWVlCggIcM3j6ArQcvBpJgCm8frrr0uSfHx85OPjo6ysLGVnZysrK0s+Pj7y9vZ2mwegZeDIDADTOH78uCTJbrfLz89PFRUVkqSlS5eqVatWru3KeQBaBo7MADCN8PBw1/c//uzCD7d/OA9A80eZAWAa77//vuv74uJiLV68WMOHD9fixYtVXFxc7TwAzR+nmQCYxmef/d8nlq666ioFBwcrMDBQH330kaZNm+Y2Lz4+3oCEAIxAmQFgGseOHZP0/QJgu92ukydP6uTJk679leOV8wC0DJQZAKYRFhYm6fsFwN7e3mrXrp3Onz+vNm3a6MyZM7Lb7W7zALQMrJkBYBq33HKLJMlisejs2bM6duyYXn/9dR07dkxnz56VxWJxmwegZaDMADCNJ554QtL3n1y65557lJubq/Pnzys3N1f33HOP6xNNlfMAtAyUGQCmsX//fknSn//8Z+3Zs0eDBw/Wfffdp8GDB6ugoEDLly93mwegZaDMADCNa665RpJ0+PBhHThwQJmZmZoyZYoyMzO1f/9+HT582G0egJaBu2YDMI3z58/Lz89PrVu3dq2R2bBhg4YPHy6n06mAgACVl5ertLRUbdq0MTougCtQl/dvjswAMI02bdpo1KhRKi8vV0BAgO6//35lZGTo/vvvdxWZUaNGUWSAFoYjMwBMp2/fvvr444+rjN9666366KOPDEgEoL7V5f2b68wAMJX09HTt3LlTw4cPV+vWrXXw4EH16NFD5eXl2rhxo9LT0zV69GijYwJoRByZAWAaDodDUVFRiomJUUZGhhwOh2vNjJeXl1JSUlRQUKD9+/fLy8vL6LgArgBrZgA0Szk5OSoqKtKsWbPUqpX7f75atWqlmTNnqrCwUDk5OQYlBGAEygwA06i859KNN95Y7f7Kce7NBLQslBkAplF5z6WCgoJq91eOc28moGWhzAAwjdtvv12RkZFasGCBKioq3PZVVFQoLS1N3bt31+23325QQgBGoMwAMA0vLy8tWbJE69evV0pKitu9mVJSUrR+/XotXryYxb9AC8NHswGYyujRo7V27VpNnTpVgwcPdo13795da9eu5WPZQAvER7MBmJLD4dCWLVu0ceNGJSUlKSEhgSMyQDPCRfMANHteXl6Ki4tTSUmJ4uLiKDJAC8aaGQAAYGqUGQAAYGqUGQAAYGqUGQAAYGqUGQAAYGqUGQCm5HA4lJWVpezsbGVlZcnhcBgdCYBBDC0z2dnZSk5OVnh4uCwWizIyMtz2O51OzZ07V+Hh4WrTpo3i4+P12WefGRMWQJORnp6uqKgoDR06VEuXLtXQoUMVFRWl9PR0o6MBMIChZaakpESxsbFasWJFtfsXLVqkpUuXasWKFfr4448VGhqqoUOH6uzZs42cFEBTkZ6erjFjxigmJkY5OTl64403lJOTo5iYGI0ZM4ZCA7RATeYKwBaLRevWrVNKSoqk74/KhIeHa9KkSXr88cclSWVlZerUqZMWLlyoRx55pFbPyxWAgebD4XAoKipKMTExysjIkMPh0IYNGzR8+HB5eXkpJSVFBQUF2r9/PxfRA0yuWVwBuLCwUMePH1diYqJrzGq1Ki4uTh988EGNZaasrExlZWWubZvNJkmy2+2y2+0NGxpAg8rKylJRUZHWrFkjh8Phek1Xfp0+fboGDx6sLVu2KC4uzsioAK5QXd6zm2yZOX78uCSpU6dObuOdOnXSV199VePj0tLSNG/evCrjmzZtkp+fX/2GBNCosrOzJUlHjhxRcXGx9u7dq9OnT2vPnj3q2bOnysvLJUkbN25USUmJkVEBXKHS0tJaz22yZaaSxWJx23Y6nVXGfmjmzJmaMmWKa9tmsykiIkKJiYmcZgJMzt/fX0uXLtXBgwf10ksvqaioyLUvMjJS48ePlyQlJSVxZAYwucozK7XRZMtMaGiopO+P0ISFhbnGi4uLqxyt+SGr1Sqr1Vpl3MfHRz4+PvUfFECjSUhI0FVXXaXf//73GjFihNasWaMjR46oS5cuWrhwoZ588kmFhIRwB22gGajLe3aTvc5M9+7dFRoaqszMTNdYeXm5srKydNtttxmYDICRfnhktvLzC03kcwwADGLokZlz587pwIEDru3CwkLl5+crKChIXbt21aRJk7RgwQJdc801uuaaa7RgwQL5+flp3LhxBqYGYJScnBwVFxcrLS1Nf/nLXzR48GDXvu7du2vBggWaNWuWcnJyFB8fb1xQAI3K0DKzc+dOJSQkuLYr17qkpqbq1Vdf1YwZM3T+/Hn99re/1enTp9WvXz9t2rRJAQEBRkUGYKBjx45JkiZMmKDp06dry5Yt2rhxo5KSkpSQkKDS0lLNmjXLNQ9Ay2BomYmPj7/k4WGLxaK5c+dq7ty5jRcKQJNVuX6uoKBA/fv3V1xcnEpKShQXFycvLy8VFBS4zQPQMjTZNTMA8GO33367IiMjtWDBAlVUVLjtq6ioUFpamrp3767bb7/doIQAjECZAWAaXl5eWrJkidavX6+UlBTl5ubq/Pnzys3NVUpKitavX6/FixfzSSaghWmyH80GgOqMHj1aa9eu1dSpU6ssAF67dq1Gjx5tYDoARmgy92ZqKNybCWieHA5HlQXAHJEBmo9mcW8mALgULy+vKguAAbRMrJkBAACmRpkBAACmRpkBAACmRpkBAACmRpkBAACmRpkBAACmRpkBAACmRpkBAACmRpkBAACm1uyvAFx5twabzWZwEgD1zW63q7S0VDabTT4+PkbHAVCPKt+3a3PXpWZfZs6ePStJioiIMDgJAACoq7Nnz6pdu3aXnNPsbzRZUVGho0ePKiAgQBaLxeg4AOqRzWZTRESEDh8+zI1kgWbG6XTq7NmzCg8PV6tWl14V0+zLDIDmqy531QXQfLEAGAAAmBplBgAAmBplBoBpWa1WzZkzR1ar1egoAAzEmhkAAGBqHJkBAACmRpkBAACmRpkBAACmRpkBAACmRpkBUO+KiopksViUn58vSdq6dassFou+++47SdKrr76q9u3bG5avLn6cHUDTQ5kB0Ojuvfdeffnll0bHqJXbbrtNx44du+y9YQAYp9nfaBJA09OmTRu1adPG6BiXZbfb1bp1a4WGhhodBcAlcGQGQI3Wrl2rmJgYtWnTRh07dtQdd9yhkpISSdIrr7yi66+/Xr6+voqOjtYLL7xQ6+f98WmmuXPnqnfv3lqzZo0iIyPVrl07jR071nXXe+n7O+f+/Oc/l7+/v8LCwvT8888rPj5ekyZNqtXPjIyM1NNPP61x48apbdu2Cg8P1/Lly93mWCwWrVq1SqNGjZK/v7+eeeaZak8zbd++XXFxcfLz81OHDh00bNgwnT59WtL3N8dbtGiRrr76arVp00axsbFau3Ztrf82AOqOMgOgWseOHdN9992nhx56SJ9//rm2bt2q0aNHy+l0avXq1Zo9e7bmz5+vzz//XAsWLNCTTz6pv/71rx7/vIMHDyojI0Pr16/X+vXrlZWVpWeffda1f8qUKdq+fbvefvttZWZmKicnR3l5eXX6Gc8995x69eqlvLw8zZw5U5MnT1ZmZqbbnDlz5mjUqFHas2ePHnrooSrPkZ+fryFDhuiGG27Qhx9+qG3btik5OVkOh0OS9Pvf/16vvPKKVq5cqc8++0yTJ0/W/fffr6ysLA/+KgBqxQkA1di1a5dTkrOoqKjKvoiICOfrr7/uNvb00087BwwY4HQ6nc7CwkKnJOfu3budTqfTuWXLFqck5+nTp51Op9P5yiuvONu1a+d67Jw5c5x+fn5Om83mGps+fbqzX79+TqfT6bTZbE4fHx/nP/7xD9f+7777zunn5+d87LHHavX7dOvWzXnnnXe6jd17773OpKQk17Yk56RJk9zm/Dj7fffd5xw4cGC1P+PcuXNOX19f5wcffOA2Pn78eOd9991Xq5wA6o41MwCqFRsbqyFDhigmJkbDhg1TYmKixowZo4sXL+rw4cMaP368Hn74Ydf8ixcvXtEi2cjISAUEBLi2w8LCVFxcLEk6dOiQ7Ha7+vbt69rfrl07XXfddXX6GQMGDKiyvWzZMrexW2655ZLPkZ+fr7vvvrvafXv37tWFCxc0dOhQt/Hy8nL16dOnTlkB1B5lBkC1vLy8lJmZqQ8++ECbNm3S8uXLNXv2bL3zzjuSpNWrV6tfv35VHuMpHx8ft22LxaKKigpJ369DqRz7IWc93Frux8/p7+9/yfmXWrhcmffdd99V586d3fZxM0yg4bBmBkCNLBaLBg4cqHnz5mn37t1q3bq1tm/frs6dO+vQoUOKiopy+9e9e/cGydGjRw/5+Pjoo48+co3ZbDbt37+/Ts+Tm5tbZTs6OrpOz9GrVy9t3ry52n09e/aU1WrV119/XeVvExERUaefA6D2ODIDoFo7duzQ5s2blZiYqJCQEO3YsUMnTpzQ9ddfr7lz52rixIkKDAxUUlKSysrKtHPnTp0+fVpTpkyp9ywBAQFKTU3V9OnTFRQUpJCQEM2ZM0etWrWqcmTlUrZv365FixYpJSVFmZmZ+sc//qF33323TllmzpypmJgY/fa3v9VvfvMbtW7dWlu2bNHdd9+t4OBgTZs2TZMnT1ZFRYUGDRokm82mDz74QG3btlVqampdf3UAtUCZAVCtwMBAZWdna9myZbLZbOrWrZuWLFmipKQkSZKfn5+ee+45zZgxQ/7+/oqJian1x6Q9sXTpUv3mN7/RiBEjFBgYqBkzZujw4cPy9fWt9XNMnTpVu3bt0rx58xQQEKAlS5Zo2LBhdcpx7bXXatOmTZo1a5b69u2rNm3aqF+/frrvvvskSU8//bRCQkKUlpamQ4cOqX379rrppps0a9asOv0cALVncdbHSWcAaGQlJSXq3LmzlixZovHjx192fmRkpCZNmtSghQuAMTgyA8AUdu/erS+++EJ9+/bVmTNn9Ic//EGSNGrUKIOTATAaZQaAaSxevFj79u1T69atdfPNNysnJ0fBwcHKyclxnf6qzrlz5xoxJYDGxmkmAKZ3/vx5ffPNNzXuj4qKasQ0ABobZQYAAJga15kBAACmRpkBAACmRpkBAACmRpkBAACmRpkBAACmRpkBAACmRpkBAACm9v8DMKpcLVR9ymsAAAAASUVORK5CYII=",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "for feature in continous_features:\n",
    "    data=dataset.copy()\n",
    "    if 0 in data[feature].unique():\n",
    "        pass\n",
    "    else:\n",
    "        data[feature]=np.log(data[feature])\n",
    "        data.boxplot(column=feature)\n",
    "        plt.ylabel(feature)\n",
    "        plt.title(feature)\n",
    "        plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "id": "aa49bbfe",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['name', 'fuel', 'seller_type', 'transmission', 'owner']"
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "categorical_features=[feature for feature in dataset.columns if dataset[feature].dtypes == 'O']\n",
    "categorical_features"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "id": "efe41ee5",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>name</th>\n",
       "      <th>fuel</th>\n",
       "      <th>seller_type</th>\n",
       "      <th>transmission</th>\n",
       "      <th>owner</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Maruti 800 AC</td>\n",
       "      <td>Petrol</td>\n",
       "      <td>Individual</td>\n",
       "      <td>Manual</td>\n",
       "      <td>First Owner</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Maruti Wagon R LXI Minor</td>\n",
       "      <td>Petrol</td>\n",
       "      <td>Individual</td>\n",
       "      <td>Manual</td>\n",
       "      <td>First Owner</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Hyundai Verna 1.6 SX</td>\n",
       "      <td>Diesel</td>\n",
       "      <td>Individual</td>\n",
       "      <td>Manual</td>\n",
       "      <td>First Owner</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Datsun RediGO T Option</td>\n",
       "      <td>Petrol</td>\n",
       "      <td>Individual</td>\n",
       "      <td>Manual</td>\n",
       "      <td>First Owner</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Honda Amaze VX i-DTEC</td>\n",
       "      <td>Diesel</td>\n",
       "      <td>Individual</td>\n",
       "      <td>Manual</td>\n",
       "      <td>Second Owner</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>4335</th>\n",
       "      <td>Hyundai i20 Magna 1.4 CRDi (Diesel)</td>\n",
       "      <td>Diesel</td>\n",
       "      <td>Individual</td>\n",
       "      <td>Manual</td>\n",
       "      <td>Second Owner</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4336</th>\n",
       "      <td>Hyundai i20 Magna 1.4 CRDi</td>\n",
       "      <td>Diesel</td>\n",
       "      <td>Individual</td>\n",
       "      <td>Manual</td>\n",
       "      <td>Second Owner</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4337</th>\n",
       "      <td>Maruti 800 AC BSIII</td>\n",
       "      <td>Petrol</td>\n",
       "      <td>Individual</td>\n",
       "      <td>Manual</td>\n",
       "      <td>Second Owner</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4338</th>\n",
       "      <td>Hyundai Creta 1.6 CRDi SX Option</td>\n",
       "      <td>Diesel</td>\n",
       "      <td>Individual</td>\n",
       "      <td>Manual</td>\n",
       "      <td>First Owner</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4339</th>\n",
       "      <td>Renault KWID RXT</td>\n",
       "      <td>Petrol</td>\n",
       "      <td>Individual</td>\n",
       "      <td>Manual</td>\n",
       "      <td>First Owner</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>4340 rows × 5 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                                     name    fuel seller_type transmission  \\\n",
       "0                           Maruti 800 AC  Petrol  Individual       Manual   \n",
       "1                Maruti Wagon R LXI Minor  Petrol  Individual       Manual   \n",
       "2                    Hyundai Verna 1.6 SX  Diesel  Individual       Manual   \n",
       "3                  Datsun RediGO T Option  Petrol  Individual       Manual   \n",
       "4                   Honda Amaze VX i-DTEC  Diesel  Individual       Manual   \n",
       "...                                   ...     ...         ...          ...   \n",
       "4335  Hyundai i20 Magna 1.4 CRDi (Diesel)  Diesel  Individual       Manual   \n",
       "4336           Hyundai i20 Magna 1.4 CRDi  Diesel  Individual       Manual   \n",
       "4337                  Maruti 800 AC BSIII  Petrol  Individual       Manual   \n",
       "4338     Hyundai Creta 1.6 CRDi SX Option  Diesel  Individual       Manual   \n",
       "4339                     Renault KWID RXT  Petrol  Individual       Manual   \n",
       "\n",
       "             owner  \n",
       "0      First Owner  \n",
       "1      First Owner  \n",
       "2      First Owner  \n",
       "3      First Owner  \n",
       "4     Second Owner  \n",
       "...            ...  \n",
       "4335  Second Owner  \n",
       "4336  Second Owner  \n",
       "4337  Second Owner  \n",
       "4338   First Owner  \n",
       "4339   First Owner  \n",
       "\n",
       "[4340 rows x 5 columns]"
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dataset[categorical_features]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "id": "3e3ebba0",
   "metadata": {},
   "outputs": [],
   "source": [
    "#categorical_features.remove(\"name\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "id": "8298e437",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "name   1491\n",
      "fuel   5\n",
      "seller_type   3\n",
      "transmission   2\n",
      "owner   5\n"
     ]
    }
   ],
   "source": [
    "for feature in categorical_features:\n",
    "    print(feature,' ',len(dataset[feature].unique()))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "id": "69d8687f",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAlYAAAJUCAYAAADXbWgUAAAAOXRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjcuMiwgaHR0cHM6Ly9tYXRwbG90bGliLm9yZy8pXeV/AAAACXBIWXMAAA9hAAAPYQGoP6dpAABbL0lEQVR4nO3deVhV5eL+/3uDiIC4RREQ9ThkmQSWijml4KxpapOWyokytaNpHvQ4fBosyzFTS3/Hcjg5p6eMJstQFJQU9eOM85gjaolgioz794cf97cdTtGSxXa/X9fFdcVaD+ybvcJ986y1n2Wx2Ww2AQAA4C9zMzsAAADAvYJiBQAAYBCKFQAAgEEoVgAAAAahWAEAABiEYgUAAGAQihUAAIBBKFYAAAAGoVgBAAAYhGIFAABgEIoVAACAQShWAOBEbDabMjMzzY4B4CYoVgBcTlJSklq1aiVfX195e3urSZMmWr58uSQpIyNDJUqU0Pvvv28f/8svv8jNzU1Wq1W5ubn27YMGDVKFChV0/V72kZGRCg0N1ebNm9WsWTN5e3urRo0aGj9+vPLz8x0yZGRkaOjQoapevbpKliypSpUqafDgwbp8+bLDOIvFoldffVUff/yxateuLU9PT82bN+9uPTUA/iKKFQCXkpiYqJYtWyo9PV1z5szRZ599Jl9fXz3xxBNaunSpypQpowYNGmjVqlX2r4mPj5enp6cuXbqkTZs22bevWrVKLVu2lMVisW9LTU1Vz5491atXL33zzTfq0KGDRo4cqYULF9rHXLlyRREREZo3b54GDRqkH374QcOHD9fcuXPVuXNne1G77quvvtKMGTP01ltv6ccff1SzZs3u4jME4C+xAYALadSokS0gIMB26dIl+7bc3FxbaGiorXLlyrb8/HzbG2+8YfPy8rJdvXrVZrPZbC+//LKtffv2tjp16tjeeecdm81ms506dcomyTZz5kz794mIiLBJsm3cuNHhMUNCQmzt2rWzfz5u3Dibm5ubbfPmzQ7jvvjiC5sk2/fff2/fJslmtVptFy5cMO5JAHDXMGMFwGVcvnxZGzdu1DPPPKPSpUvbt7u7uysqKkonT57U/v371apVK2VmZmr9+vWSrs1MtWnTRq1bt9bKlSvt2ySpdevWDo8RFBSkRx991GFbnTp19PPPP9s//+677xQaGqpHHnlEubm59o927drJYrEoISHB4etbtmwpPz8/w54HAHdPCbMDAEBRSUtLk81mU8WKFQvsCw4OliT9+uuvatKkiby9vbVq1SpVqVJFx44dU5s2bXTy5ElNmzZNv/32m1atWqUaNWqoevXqDt+nfPnyBb63p6enwwXnZ8+e1aFDh+Th4XHDnL/88ovD5zfKC6B4olgBcBl+fn5yc3PTmTNnCuw7ffq0JMnf318lS5bUY489plWrVqly5coKCgpSWFiYatSoIUlKSEhQfHy8OnXqVKgc/v7+8vLy0n/+85+b7v+931/DBaB4o1gBcBk+Pj5q2LChvvzyS02aNEleXl6SpPz8fC1cuFCVK1fWAw88IOnaKb6RI0fK19fXfrrPx8dHjRo10rRp03T69OkCpwHvVKdOnTR27FiVL1++wIwXAOfGNVYAXMq4ceP066+/qkWLFvriiy/0zTff6PHHH1dKSoomTZpknx1q1aqV8vLyFB8frzZt2ti/vnXr1oqLi5PFYlHLli0LlWHw4MGqVauWmjdvrsmTJ2vVqlWKi4vT7Nmz1a1bN23cuNGQnxVA0aNYAXApERERWr16tXx8fBQdHa3nnntO6enp+uabb9S9e3f7uLp169pPyf1+Zur6f9etW/eG11PdCR8fH61bt07R0dGaOXOmOnbsqG7duumjjz5S5cqVVa1atcL/gABMZbHZ/rBgCgAAAAqFGSsAAACDUKwAAAAMQrECAAAwCMUKAADAIBQrAAAAg1CsAAAADMLK60UsPz9fp0+flq+vL7epAADASdhsNl26dEnBwcFyc7v5vBTFqoidPn1aVapUMTsGAAAohBMnTqhy5co33U+xKmK+vr6Srh2YMmXKmJwGAADciYyMDFWpUsX+On4zFKsidv30X5kyZShWAAA4mdtdxsPF6wAAAAahWAEAABiEYgUAAGAQihUAAIBBKFYAAAAGoVgBAAAYhGIFAABgEIoVAACAQShWAAAABqFYAQAAGIRiBQAAYBCKFQAAgEEoVgAAAAahWAEAABikhNkBAACup9qI5WZHMMSx8R3NjoBihhkrAAAAg1CsAAAADEKxAgAAMAjFCgAAwCAUKwAAAINQrAAAAAxCsQIAADAIxQoAAMAgFCsAAACDUKwAAAAMQrECAAAwCMUKAADAIBQrAAAAg1CsAAAADEKxAgAAMAjFCgAAwCAUKwAAAINQrAAAAAxCsQIAADAIxQoAAMAgFCsAAACDUKwAAAAMQrECAAAwCMUKAADAIBQrAAAAg1CsAAAADEKxAgAAMAjFCgAAwCAUKwAAAINQrAAAAAxCsQIAADAIxQoAAMAgFCsAAACDmFqscnNz9cYbb6h69ery8vJSjRo1NHr0aOXn59vH2Gw2vf322woODpaXl5ciIyO1e/duh++TlZWlgQMHyt/fXz4+PurcubNOnjzpMCYtLU1RUVGyWq2yWq2KiorSxYsXHcYcP35cTzzxhHx8fOTv769BgwYpOzvbYcyuXbsUEREhLy8vVapUSaNHj5bNZjP2iQEAAE7J1GI1YcIEffzxx5o+fbr27t2riRMn6v3339e0adPsYyZOnKjJkydr+vTp2rx5s4KCgtSmTRtdunTJPmbw4MGKjY3VkiVLlJSUpN9++02dOnVSXl6efUyPHj20fft2rVixQitWrND27dsVFRVl35+Xl6eOHTvq8uXLSkpK0pIlS7Rs2TINGTLEPiYjI0Nt2rRRcHCwNm/erGnTpmnSpEmaPHnyXX6mAACAM7DYTJxu6dSpkwIDAzVnzhz7tqefflre3t5asGCBbDabgoODNXjwYA0fPlzStdmpwMBATZgwQf369VN6eroqVKigBQsWqHv37pKk06dPq0qVKvr+++/Vrl077d27VyEhIUpOTlbDhg0lScnJyWrcuLH27dunWrVq6YcfflCnTp104sQJBQcHS5KWLFmi6OhonTt3TmXKlNGMGTM0cuRInT17Vp6enpKk8ePHa9q0aTp58qQsFsttf+aMjAxZrValp6erTJkyhj6fAOAsqo1YbnYEQxwb39HsCCgid/r6beqM1WOPPab4+HgdOHBAkrRjxw4lJSXp8ccflyQdPXpUqampatu2rf1rPD09FRERofXr10uStmzZopycHIcxwcHBCg0NtY/ZsGGDrFarvVRJUqNGjWS1Wh3GhIaG2kuVJLVr105ZWVnasmWLfUxERIS9VF0fc/r0aR07duyGP2NWVpYyMjIcPgAAwL2phJkPPnz4cKWnp+vBBx+Uu7u78vLyNGbMGD3//POSpNTUVElSYGCgw9cFBgbq559/to8pWbKk/Pz8Coy5/vWpqakKCAgo8PgBAQEOY/74OH5+fipZsqTDmGrVqhV4nOv7qlevXuAxxo0bp3feeef2TwYAAHB6ps5YLV26VAsXLtTixYu1detWzZs3T5MmTdK8efMcxv3xFJvNZrvtabc/jrnReCPGXD+TerM8I0eOVHp6uv3jxIkTt8wNAACcl6kzVv/61780YsQIPffcc5KksLAw/fzzzxo3bpxeeOEFBQUFSbo2G1SxYkX71507d84+UxQUFKTs7GylpaU5zFqdO3dOTZo0sY85e/Zsgcc/f/68w/fZuHGjw/60tDTl5OQ4jLk+e/X7x5EKzqpd5+np6XDqEAAA3LtMnbG6cuWK3NwcI7i7u9uXW6hevbqCgoK0cuVK+/7s7GwlJibaS1P9+vXl4eHhMObMmTNKSUmxj2ncuLHS09O1adMm+5iNGzcqPT3dYUxKSorOnDljHxMXFydPT0/Vr1/fPmbt2rUOSzDExcUpODi4wClCAADgekwtVk888YTGjBmj5cuX69ixY4qNjdXkyZP15JNPSrp2em3w4MEaO3asYmNjlZKSoujoaHl7e6tHjx6SJKvVqt69e2vIkCGKj4/Xtm3b1KtXL4WFhal169aSpNq1a6t9+/bq06ePkpOTlZycrD59+qhTp06qVauWJKlt27YKCQlRVFSUtm3bpvj4eA0dOlR9+vSxX/3fo0cPeXp6Kjo6WikpKYqNjdXYsWMVExNzR+8IBAAA9zZTTwVOmzZNb775pvr3769z584pODhY/fr101tvvWUfM2zYMGVmZqp///5KS0tTw4YNFRcXJ19fX/uYKVOmqESJEurWrZsyMzPVqlUrzZ07V+7u7vYxixYt0qBBg+zvHuzcubOmT59u3+/u7q7ly5erf//+atq0qby8vNSjRw9NmjTJPsZqtWrlypUaMGCAwsPD5efnp5iYGMXExNzNpwkAADgJU9exckWsYwUArGMF5+MU61gBAADcSyhWAAAABqFYAQAAGIRiBQAAYBCKFQAAgEEoVgAAAAahWAEAABiEYgUAAGAQihUAAIBBKFYAAAAGoVgBAAAYhGIFAABgEIoVAACAQShWAAAABqFYAQAAGIRiBQAAYBCKFQAAgEEoVgAAAAahWAEAABiEYgUAAGAQihUAAIBBKFYAAAAGoVgBAAAYhGIFAABgEIoVAACAQShWAAAABqFYAQAAGIRiBQAAYBCKFQAAgEEoVgAAAAahWAEAABiEYgUAAGAQihUAAIBBKFYAAAAGoVgBAAAYhGIFAABgEIoVAACAQShWAAAABqFYAQAAGIRiBQAAYBCKFQAAgEEoVgAAAAahWAEAABiEYgUAAGAQihUAAIBBKFYAAAAGoVgBAAAYhGIFAABgEIoVAACAQShWAAAABqFYAQAAGIRiBQAAYBCKFQAAgEEoVgAAAAahWAEAABiEYgUAAGAQihUAAIBBKFYAAAAGoVgBAAAYhGIFAABgEIoVAACAQShWAAAABqFYAQAAGIRiBQAAYBCKFQAAgEEoVgAAAAahWAEAABjE9GJ16tQp9erVS+XLl5e3t7ceeeQRbdmyxb7fZrPp7bffVnBwsLy8vBQZGandu3c7fI+srCwNHDhQ/v7+8vHxUefOnXXy5EmHMWlpaYqKipLVapXValVUVJQuXrzoMOb48eN64okn5OPjI39/fw0aNEjZ2dkOY3bt2qWIiAh5eXmpUqVKGj16tGw2m7FPCgAAcEqmFqu0tDQ1bdpUHh4e+uGHH7Rnzx598MEHKlu2rH3MxIkTNXnyZE2fPl2bN29WUFCQ2rRpo0uXLtnHDB48WLGxsVqyZImSkpL022+/qVOnTsrLy7OP6dGjh7Zv364VK1ZoxYoV2r59u6Kiouz78/Ly1LFjR12+fFlJSUlasmSJli1bpiFDhtjHZGRkqE2bNgoODtbmzZs1bdo0TZo0SZMnT767TxQAAHAKFpuJ0y0jRozQTz/9pHXr1t1wv81mU3BwsAYPHqzhw4dLujY7FRgYqAkTJqhfv35KT09XhQoVtGDBAnXv3l2SdPr0aVWpUkXff/+92rVrp7179yokJETJyclq2LChJCk5OVmNGzfWvn37VKtWLf3www/q1KmTTpw4oeDgYEnSkiVLFB0drXPnzqlMmTKaMWOGRo4cqbNnz8rT01OSNH78eE2bNk0nT56UxWK57c+ckZEhq9Wq9PR0lSlT5i8/hwDgjKqNWG52BEMcG9/R7AgoInf6+m3qjNU333yj8PBwPfvsswoICFDdunU1a9Ys+/6jR48qNTVVbdu2tW/z9PRURESE1q9fL0nasmWLcnJyHMYEBwcrNDTUPmbDhg2yWq32UiVJjRo1ktVqdRgTGhpqL1WS1K5dO2VlZdlPTW7YsEERERH2UnV9zOnTp3Xs2LEb/oxZWVnKyMhw+AAAAPcmU4vVkSNHNGPGDN1///368ccf9corr2jQoEGaP3++JCk1NVWSFBgY6PB1gYGB9n2pqakqWbKk/Pz8bjkmICCgwOMHBAQ4jPnj4/j5+alkyZK3HHP98+tj/mjcuHH267qsVquqVKlym2cFAAA4K1OLVX5+vurVq6exY8eqbt266tevn/r06aMZM2Y4jPvjKTabzXbb025/HHOj8UaMuX4m9WZ5Ro4cqfT0dPvHiRMnbpkbAAA4L1OLVcWKFRUSEuKwrXbt2jp+/LgkKSgoSFLB2aBz587ZZ4qCgoKUnZ2ttLS0W445e/Zsgcc/f/68w5g/Pk5aWppycnJuOebcuXOSCs6qXefp6akyZco4fAAAgHuTqcWqadOm2r9/v8O2AwcOqGrVqpKk6tWrKygoSCtXrrTvz87OVmJiopo0aSJJql+/vjw8PBzGnDlzRikpKfYxjRs3Vnp6ujZt2mQfs3HjRqWnpzuMSUlJ0ZkzZ+xj4uLi5Onpqfr169vHrF271mEJhri4OAUHB6tatWpGPCUAAMCJmVqs/vnPfyo5OVljx47VoUOHtHjxYs2cOVMDBgyQdO302uDBgzV27FjFxsYqJSVF0dHR8vb2Vo8ePSRJVqtVvXv31pAhQxQfH69t27apV69eCgsLU+vWrSVdmwVr3769+vTpo+TkZCUnJ6tPnz7q1KmTatWqJUlq27atQkJCFBUVpW3btik+Pl5Dhw5Vnz597LNMPXr0kKenp6Kjo5WSkqLY2FiNHTtWMTExd/SOQAAAcG8rYeaDN2jQQLGxsRo5cqRGjx6t6tWra+rUqerZs6d9zLBhw5SZman+/fsrLS1NDRs2VFxcnHx9fe1jpkyZohIlSqhbt27KzMxUq1atNHfuXLm7u9vHLFq0SIMGDbK/e7Bz586aPn26fb+7u7uWL1+u/v37q2nTpvLy8lKPHj00adIk+xir1aqVK1dqwIABCg8Pl5+fn2JiYhQTE3M3nyYAAOAkTF3HyhWxjhUAsI4VnI9TrGMFAABwL6FYAQAAGIRiBQAAYBCKFQAAgEEKXazWrVunXr16qXHjxjp16pQkacGCBUpKSjIsHAAAgDMpVLFatmyZ2rVrJy8vL23btk1ZWVmSpEuXLmns2LGGBgQAAHAWhSpW7733nj7++GPNmjVLHh4e9u1NmjTR1q1bDQsHAADgTApVrPbv36/mzZsX2F6mTBldvHjxr2YCAABwSoUqVhUrVtShQ4cKbE9KSlKNGjX+cigAAABnVKhi1a9fP7322mvauHGjLBaLTp8+rUWLFmno0KHq37+/0RkBAACcQqHuFThs2DClp6erRYsWunr1qpo3by5PT08NHTpUr776qtEZAQAAnEKhb8I8ZswYvf7669qzZ4/y8/MVEhKi0qVLG5kNAADAqRSqWKWnpysvL0/lypVTeHi4ffuFCxdUokQJbi4MAABcUqGusXruuee0ZMmSAtv/+9//6rnnnvvLoQAAAJxRoYrVxo0b1aJFiwLbIyMjtXHjxr8cCgAAwBkVqlhlZWUpNze3wPacnBxlZmb+5VAAAADOqFDFqkGDBpo5c2aB7R9//LHq16//l0MBAAA4o0JdvD5mzBi1bt1aO3bsUKtWrSRJ8fHx2rx5s+Li4gwNCAAA4CwKNWPVtGlTbdiwQVWqVNF///tfffvtt6pZs6Z27typZs2aGZ0RAADAKRR6HatHHnlEixYtMjILAACAU7vjYpWRkWFfnyojI+OWY1nHCgAAuKI7LlZ+fn46c+aMAgICVLZsWVkslgJjbDabLBaL8vLyDA0JAADgDO64WK1evVrlypWTJK1Zs+auBQIAAHBWd1ysIiIiJEm5ublKSEjQSy+9pCpVqty1YAAAAM7mT78rsESJEpo0aRKn+wAAAP6gUMsttGrVSgkJCQZHAQAAcG6FWm6hQ4cOGjlypFJSUlS/fn35+Pg47O/cubMh4QAAAJxJoYrVP/7xD0nS5MmTC+zjXYEAAMBVFapY5efnG50DAADA6RXqGisAAAAUVOhiFR8fr06dOum+++5TzZo11alTJ61atcrIbAAAAE6lUMVq+vTpat++vXx9ffXaa69p0KBBKlOmjB5//HFNnz7d6IwAAABOoVDXWI0bN05TpkzRq6++at82aNAgNW3aVGPGjHHYDgAA4CoKNWOVkZGh9u3bF9jetm3b296gGQAA4F5VqGLVuXNnxcbGFtj+9ddf64knnvjLoQAAAJxRoU4F1q5dW2PGjFFCQoIaN24sSUpOTtZPP/2kIUOG6KOPPrKPHTRokDFJAQAAijmLzWaz/dkvql69+p19c4tFR44c+dOh7mUZGRmyWq1KT09XmTJlzI4DAKaoNmK52REMcWx8R7MjoIjc6et3oWasjh49WuhgAAAA96q7ukBomTJlmLECAAAu464Wq0KcZQQAAHBa3NIGAADAIBQrAAAAg1CsAAAADHJXi5XFYrmb3x4AAKBY4eJ1AAAAg9zVYvXDDz+oUqVKd/MhAAAAio1CLRAaExNzw+0Wi0WlSpVSzZo11aVLFz322GN/KRwAAIAzKVSx2rZtm7Zu3aq8vDzVqlVLNptNBw8elLu7ux588EH9+9//1pAhQ5SUlKSQkBCjMwMAABRLhToV2KVLF7Vu3VqnT5/Wli1btHXrVp06dUpt2rTR888/r1OnTql58+b65z//aXReAACAYqtQN2GuVKmSVq5cWWA2avfu3Wrbtq1OnTqlrVu3qm3btvrll18MC3sv4CbMAMBNmOF87vT1u1AzVunp6Tp37lyB7efPn1dGRoYkqWzZssrOzi7MtwcAAHBKhT4V+NJLLyk2NlYnT57UqVOnFBsbq969e6tr166SpE2bNumBBx4wMisAAECxVqiL1z/55BP985//1HPPPafc3Nxr36hECb3wwguaMmWKJOnBBx/U7NmzjUuKO8YUOwAA5ihUsSpdurRmzZqlKVOm6MiRI7LZbLrvvvtUunRp+5hHHnnEqIwAAABOoVDF6rrSpUurTp06RmUBAABwaoUqVpcvX9b48eMVHx+vc+fOKT8/32H/kSNHDAkHAADgTApVrF5++WUlJiYqKipKFStW5GbLAAAAKmSx+uGHH7R8+XI1bdrU6DwAAABOq1DLLfj5+alcuXJGZwEAAHBqhSpW7777rt566y1duXLF6DwAAABOq1CnAj/44AMdPnxYgYGBqlatmjw8PBz2b9261ZBwAAAAzqRQxer66uoAAAD4fwpVrEaNGmV0DgAAAKdXqGusAAAAUNAdz1iVK1dOBw4ckL+/v/z8/G65dtWFCxcMCQcAAOBM7rhYTZkyRb6+vpKkqVOn3q08AAAATuuOi9ULL7xww/8GAADANXdcrDIyMu74m5YpU6ZQYQAAAJzZHV+8XrZsWfn5+d3y4/qYwhg3bpwsFosGDx5s32az2fT2228rODhYXl5eioyM1O7dux2+LisrSwMHDpS/v798fHzUuXNnnTx50mFMWlqaoqKiZLVaZbVaFRUVpYsXLzqMOX78uJ544gn5+PjI399fgwYNUnZ2tsOYXbt2KSIiQl5eXqpUqZJGjx4tm81WqJ8XAADce+54xmrNmjV3LcTmzZs1c+ZM1alTx2H7xIkTNXnyZM2dO1cPPPCA3nvvPbVp00b79++3X+81ePBgffvtt1qyZInKly+vIUOGqFOnTtqyZYvc3d0lST169NDJkye1YsUKSVLfvn0VFRWlb7/9VpKUl5enjh07qkKFCkpKStKvv/6qF154QTabTdOmTZN0bcauTZs2atGihTZv3qwDBw4oOjpaPj4+GjJkyF17bgAAgPO442IVERFxVwL89ttv6tmzp2bNmqX33nvPvt1ms2nq1Kl6/fXX9dRTT0mS5s2bp8DAQC1evFj9+vVTenq65syZowULFqh169aSpIULF6pKlSpatWqV2rVrp71792rFihVKTk5Ww4YNJUmzZs1S48aNtX//ftWqVUtxcXHas2ePTpw4oeDgYEnXVpePjo7WmDFjVKZMGS1atEhXr17V3Llz5enpqdDQUB04cECTJ09WTEzMLd8lCQAAXMMdnwrcuXPnHX/8GQMGDFDHjh3txei6o0ePKjU1VW3btrVv8/T0VEREhNavXy9J2rJli3JychzGBAcHKzQ01D5mw4YNslqt9lIlSY0aNZLVanUYExoaai9VktSuXTtlZWVpy5Yt9jERERHy9PR0GHP69GkdO3bspj9fVlaWMjIyHD4AAMC96Y5nrB555BFZLJbbXlNksViUl5d3R99zyZIl2rp1qzZv3lxgX2pqqiQpMDDQYXtgYKB+/vln+5iSJUsWuK4rMDDQ/vWpqakKCAgo8P0DAgIcxvzxcfz8/FSyZEmHMdWqVSvwONf3Va9e/YY/47hx4/TOO+/ccB8AALi33HGxOnr0qKEPfOLECb322muKi4tTqVKlbjruj6fYbDbbbU+7/XHMjcYbMeZ6ybxVnpEjRyomJsb+eUZGhqpUqXLL/AAAwDndcbGqWrWqoQ+8ZcsWnTt3TvXr17dvy8vL09q1azV9+nTt379f0rXZoIoVK9rHnDt3zj5TFBQUpOzsbKWlpTnMWp07d05NmjSxjzl79myBxz9//rzD99m4caPD/rS0NOXk5DiMuT579fvHkQrOqv2ep6enw+lDAABw7yr0vQIXLFigpk2bKjg42H5qburUqfr666/v6OtbtWqlXbt2afv27faP8PBw9ezZU9u3b1eNGjUUFBSklStX2r8mOztbiYmJ9tJUv359eXh4OIw5c+aMUlJS7GMaN26s9PR0bdq0yT5m48aNSk9PdxiTkpKiM2fO2MfExcXJ09PTXvwaN26stWvXOizBEBcXp+Dg4AKnCAEAgGsqVLGaMWOGYmJi9Pjjj+vixYv2a6rKli17x7e78fX1VWhoqMOHj4+Pypcvr9DQUPuaVmPHjlVsbKxSUlIUHR0tb29v9ejRQ5JktVrVu3dvDRkyRPHx8dq2bZt69eqlsLAw+8XwtWvXVvv27dWnTx8lJycrOTlZffr0UadOnVSrVi1JUtu2bRUSEqKoqCht27ZN8fHxGjp0qPr06WNf7LRHjx7y9PRUdHS0UlJSFBsbq7Fjx/KOQAAAYFeoYjVt2jTNmjVLr7/+un2tKEkKDw/Xrl27DAs3bNgwDR48WP3791d4eLhOnTqluLg4+xpW0rV7GHbt2lXdunVT06ZN5e3trW+//dYh16JFixQWFqa2bduqbdu2qlOnjhYsWGDf7+7uruXLl6tUqVJq2rSpunXrpq5du2rSpEn2MVarVStXrtTJkycVHh6u/v37KyYmxuH6KQAA4NostkIsHe7l5aV9+/apatWq8vX11Y4dO1SjRg0dPHhQderUUWZm5t3Iek/IyMiQ1WpVenr6Xbv1T7URy+/K9y1qx8Z3NDsCgLuEf6fgbO709btQM1bVq1fX9u3bC2z/4YcfFBISUphvCQAA4PTu+F2Bv/evf/1LAwYM0NWrV2Wz2bRp0yZ99tlnGjdunGbPnm10RgAAAKdQqGL14osvKjc3V8OGDdOVK1fUo0cPVa5cWR9++KGee+45ozMCAAA4hUIVq8zMTPXs2VN9+vTRL7/8oiNHjuinn35S5cqVjc4HAADgNAp1jVWXLl00f/58SVKJEiXUuXNnTZ48WV27dtWMGTMMDQgAAOAsClWstm7dqmbNmkmSvvjiC/v9++bPn6+PPvrI0IAAAADOolDF6sqVK/a1pOLi4vTUU0/Jzc1NjRo1sq/CDgAA4GoKVaxq1qypr776SidOnNCPP/6otm3bSrp277y7tTYTAABAcVeoYvXWW29p6NChqlatmho2bKjGjRtLujZ7VbduXUMDAgAAOItCvSvwmWee0WOPPaYzZ87o4Ycftm9v1aqVnnzyScPCAQAAOJNCFStJCgoKUlBQkMO2Rx999C8HAgAAcFaFOhUIAACAgihWAAAABqFYAQAAGIRiBQAAYBCKFQAAgEEoVgAAAAahWAEAABiEYgUAAGAQihUAAIBBKFYAAAAGoVgBAAAYhGIFAABgEIoVAACAQShWAAAABqFYAQAAGIRiBQAAYBCKFQAAgEEoVgAAAAahWAEAABiEYgUAAGAQihUAAIBBKFYAAAAGoVgBAAAYhGIFAABgEIoVAACAQShWAAAABqFYAQAAGIRiBQAAYBCKFQAAgEEoVgAAAAahWAEAABiEYgUAAGAQihUAAIBBKFYAAAAGoVgBAAAYhGIFAABgEIoVAACAQShWAAAABqFYAQAAGIRiBQAAYBCKFQAAgEFKmB0AAIpKtRHLzY7wlx0b39HsCABugRkrAAAAg1CsAAAADEKxAgAAMAjFCgAAwCAUKwAAAINQrAAAAAxCsQIAADAIxQoAAMAgFCsAAACDUKwAAAAMQrECAAAwCMUKAADAIBQrAAAAg1CsAAAADEKxAgAAMIipxWrcuHFq0KCBfH19FRAQoK5du2r//v0OY2w2m95++20FBwfLy8tLkZGR2r17t8OYrKwsDRw4UP7+/vLx8VHnzp118uRJhzFpaWmKioqS1WqV1WpVVFSULl686DDm+PHjeuKJJ+Tj4yN/f38NGjRI2dnZDmN27dqliIgIeXl5qVKlSho9erRsNptxTwoAAHBapharxMREDRgwQMnJyVq5cqVyc3PVtm1bXb582T5m4sSJmjx5sqZPn67NmzcrKChIbdq00aVLl+xjBg8erNjYWC1ZskRJSUn67bff1KlTJ+Xl5dnH9OjRQ9u3b9eKFSu0YsUKbd++XVFRUfb9eXl56tixoy5fvqykpCQtWbJEy5Yt05AhQ+xjMjIy1KZNGwUHB2vz5s2aNm2aJk2apMmTJ9/lZwoAADiDEmY++IoVKxw+//TTTxUQEKAtW7aoefPmstlsmjp1ql5//XU99dRTkqR58+YpMDBQixcvVr9+/ZSenq45c+ZowYIFat26tSRp4cKFqlKlilatWqV27dpp7969WrFihZKTk9WwYUNJ0qxZs9S4cWPt379ftWrVUlxcnPbs2aMTJ04oODhYkvTBBx8oOjpaY8aMUZkyZbRo0SJdvXpVc+fOlaenp0JDQ3XgwAFNnjxZMTExslgsRfjsAQCA4qZYXWOVnp4uSSpXrpwk6ejRo0pNTVXbtm3tYzw9PRUREaH169dLkrZs2aKcnByHMcHBwQoNDbWP2bBhg6xWq71USVKjRo1ktVodxoSGhtpLlSS1a9dOWVlZ2rJli31MRESEPD09HcacPn1ax44du+HPlJWVpYyMDIcPAABwbyo2xcpmsykmJkaPPfaYQkNDJUmpqamSpMDAQIexgYGB9n2pqakqWbKk/Pz8bjkmICCgwGMGBAQ4jPnj4/j5+alkyZK3HHP98+tj/mjcuHH267qsVquqVKlym2cCAAA4q2JTrF599VXt3LlTn332WYF9fzzFZrPZbnva7Y9jbjTeiDHXL1y/WZ6RI0cqPT3d/nHixIlb5gYAAM6rWBSrgQMH6ptvvtGaNWtUuXJl+/agoCBJBWeDzp07Z58pCgoKUnZ2ttLS0m455uzZswUe9/z58w5j/vg4aWlpysnJueWYc+fOSSo4q3adp6enypQp4/ABAADuTaZevG6z2TRw4EDFxsYqISFB1atXd9hfvXp1BQUFaeXKlapbt64kKTs7W4mJiZowYYIkqX79+vLw8NDKlSvVrVs3SdKZM2eUkpKiiRMnSpIaN26s9PR0bdq0SY8++qgkaePGjUpPT1eTJk3sY8aMGaMzZ86oYsWKkqS4uDh5enqqfv369jH/8z//o+zsbJUsWdI+Jjg4WNWqVbuLzxQAAHdHtRHLzY5giGPjO5odQZLJM1YDBgzQwoULtXjxYvn6+io1NVWpqanKzMyUdO302uDBgzV27FjFxsYqJSVF0dHR8vb2Vo8ePSRJVqtVvXv31pAhQxQfH69t27apV69eCgsLs79LsHbt2mrfvr369Omj5ORkJScnq0+fPurUqZNq1aolSWrbtq1CQkIUFRWlbdu2KT4+XkOHDlWfPn3ss0w9evSQp6enoqOjlZKSotjYWI0dO5Z3BAIAAEkmz1jNmDFDkhQZGemw/dNPP1V0dLQkadiwYcrMzFT//v2Vlpamhg0bKi4uTr6+vvbxU6ZMUYkSJdStWzdlZmaqVatWmjt3rtzd3e1jFi1apEGDBtnfPdi5c2dNnz7dvt/d3V3Lly9X//791bRpU3l5ealHjx6aNGmSfYzVatXKlSs1YMAAhYeHy8/PTzExMYqJiTH6qQEAAE7IYmPZ8CKVkZEhq9Wq9PT0u3a9FdO6wI3dC78b98rvxb1wLKR743hwLO7Mnb5+F4uL1wEAAO4FFCsAAACDUKwAAAAMQrECAAAwCMUKAADAIBQrAAAAg1CsAAAADEKxAgAAMAjFCgAAwCAUKwAAAINQrAAAAAxCsQIAADAIxQoAAMAgFCsAAACDUKwAAAAMQrECAAAwCMUKAADAIBQrAAAAg1CsAAAADEKxAgAAMEgJswMA97pqI5abHeEvOza+o9kRAMApMGMFAABgEIoVAACAQShWAAAABqFYAQAAGIRiBQAAYBCKFQAAgEEoVgAAAAahWAEAABiEYgUAAGAQihUAAIBBKFYAAAAGoVgBAAAYhGIFAABgEIoVAACAQShWAAAABqFYAQAAGIRiBQAAYBCKFQAAgEEoVgAAAAahWAEAABiEYgUAAGAQihUAAIBBKFYAAAAGoVgBAAAYhGIFAABgEIoVAACAQShWAAAABqFYAQAAGIRiBQAAYBCKFQAAgEEoVgAAAAahWAEAABiEYgUAAGAQihUAAIBBKFYAAAAGoVgBAAAYhGIFAABgEIoVAACAQShWAAAABqFYAQAAGIRiBQAAYBCKFQAAgEEoVgAAAAahWAEAABiEYgUAAGAQihUAAIBBKFaF8O9//1vVq1dXqVKlVL9+fa1bt87sSAAAoBigWP1JS5cu1eDBg/X6669r27ZtatasmTp06KDjx4+bHQ0AAJiMYvUnTZ48Wb1799bLL7+s2rVra+rUqapSpYpmzJhhdjQAAGCyEmYHcCbZ2dnasmWLRowY4bC9bdu2Wr9+/Q2/JisrS1lZWfbP09PTJUkZGRl3LWd+1pW79r2L0t18jorSvXA8OBbFB8eieLkXjgfH4s99f5vNdstxFKs/4ZdfflFeXp4CAwMdtgcGBio1NfWGXzNu3Di98847BbZXqVLlrmS8l1inmp0A13Esig+ORfHC8Sg+iupYXLp0SVar9ab7KVaFYLFYHD632WwFtl03cuRIxcTE2D/Pz8/XhQsXVL58+Zt+TXGXkZGhKlWq6MSJEypTpozZcVwax6J44XgUHxyL4uNeORY2m02XLl1ScHDwLcdRrP4Ef39/ubu7F5idOnfuXIFZrOs8PT3l6enpsK1s2bJ3K2KRKlOmjFP/ktxLOBbFC8ej+OBYFB/3wrG41UzVdVy8/ieULFlS9evX18qVKx22r1y5Uk2aNDEpFQAAKC6YsfqTYmJiFBUVpfDwcDVu3FgzZ87U8ePH9corr5gdDQAAmIxi9Sd1795dv/76q0aPHq0zZ84oNDRU33//vapWrWp2tCLj6empUaNGFTjFiaLHsSheOB7FB8ei+HC1Y2Gx3e59gwAAALgjXGMFAABgEIoVAACAQShWAAAABqFYAQAAGIRiBTiJ3NxcvfPOOzpx4oTZUSApJydHL774oo4cOWJ2FJeXm5urefPm3fTWYig6eXl5SkxMVFpamtlRTEOxwi3l5OSoRo0a2rNnj9lRXF6JEiX0/vvvKy8vz+wokOTh4aHY2FizY0DXfjf+8Y9/ONzwHuZwd3dXu3btdPHiRbOjmIZihVvy8PBQVlaW097X8F7TunVrJSQkmB0D/+fJJ5/UV199ZXYMSGrYsKG2b99udgxICgsLc+mZXBYIxW0NHDhQEyZM0OzZs1WiBP/LmKlDhw4aOXKkUlJSVL9+ffn4+Djs79y5s0nJXFPNmjX17rvvav369Tc8HoMGDTIpmevp37+/YmJidOLEiRseizp16piUzPWMGTNGQ4cO1bvvvnvDY+Hs9wu8HRYIxW09+eSTio+PV+nSpRUWFlbgl+TLL780KZnrcXO7+SSzxWLhNGERq169+k33WSwWl/6rvajd6HfDYrHIZrPxu1HEfn8sfn+2w1WOBdMPuK2yZcvq6aefNjsGJOXn55sdAb9z9OhRsyPg/3Asio81a9aYHcFUzFgBTurq1asqVaqU2TEgKTs7W0ePHtV9993H6XLAxXHxOu5Ibm6uVq1apU8++USXLl2SJJ0+fVq//fabyclcS15ent59911VqlRJpUuXtp9qevPNNzVnzhyT07meK1euqHfv3vL29tZDDz2k48ePS7p2bdX48eNNTuea9uzZoxUrVuibb75x+EDRWrdunXr16qUmTZro1KlTkqQFCxYoKSnJ5GR3H8UKt/Xzzz8rLCxMXbp00YABA3T+/HlJ0sSJEzV06FCT07mWMWPGaO7cuZo4caJKlixp3x4WFqbZs2ebmMw1jRw5Ujt27FBCQoLD7GHr1q21dOlSE5O5niNHjujhhx9WaGioOnbsqK5du6pr16568skn9eSTT5odz6UsW7ZM7dq1k5eXl7Zu3WpfBuPSpUsaO3asyenuPooVbuu1115TeHi40tLS5OXlZd9+/aJ2FJ358+dr5syZ6tmzp9zd3e3b69Spo3379pmYzDV99dVXmj59uh577DGHi3RDQkJ0+PBhE5O5ntdee03Vq1fX2bNn5e3trd27d2vt2rUKDw9niZIi9t577+njjz/WrFmz5OHhYd/epEkTbd261cRkRYOLAXBbSUlJ+umnnxxmSCSpatWq9ileFI1Tp06pZs2aBbbn5+crJyfHhESu7fz58woICCiw/fLly6z9VsQ2bNig1atXq0KFCnJzc5Obm5see+wxjRs3ToMGDdK2bdvMjugy9u/fr+bNmxfYXqZMGZdYOJQZK9xWfn7+Dd8ee/LkSfn6+pqQyHU99NBDWrduXYHtn3/+uerWrWtCItfWoEEDLV++3P759TI1a9YsNW7c2KxYLikvL0+lS5eWJPn7++v06dOSrv0BuH//fjOjuZyKFSvq0KFDBbYnJSWpRo0aJiQqWsxY4bbatGmjqVOnaubMmZKuvXj89ttvGjVqlB5//HGT07mWUaNGKSoqSqdOnVJ+fr6+/PJL7d+/X/Pnz9d3331ndjyXM27cOLVv31579uxRbm6uPvzwQ+3evVsbNmxQYmKi2fFcSmhoqHbu3KkaNWqoYcOG9usQZ86c6RIv5sVJv3799Nprr+k///mPLBaLTp8+rQ0bNmjo0KF66623zI5317HcAm7r9OnTatGihdzd3XXw4EGFh4fr4MGD8vf319q1a294KgR3z48//qixY8dqy5Ytys/PV7169fTWW2+pbdu2ZkdzSbt27dKkSZMcjsfw4cMVFhZmdjSX8uOPP+ry5ct66qmndOTIEXXq1En79u1T+fLltXTpUrVs2dLsiC7l9ddf15QpU3T16lVJkqenp3019nsdxQp3JDMzU5999pm2bt1qf/Ho2bOnw8XsAFCcXLhwQX5+flzvZpIrV65oz549ys/PV0hIiP1U7b2OYgU4oezsbJ07d67ASux/+9vfTErkuvLz83Xo0KEbHo8bXcALY+Xl5Wn37t26//77C/yhd+XKFR06dEihoaG3vB0UYCSKFe7IgQMHlJCQcMMXD1c4Z15cHDx4UC+99JLWr1/vsN1V7sFV3CQnJ6tHjx76+eef9cd/SjkeRWPu3LmaPn26Nm7c6LAEiXStdDVs2FCDBw9Wr169TEroei5fvqzx48crPj7+hq8Z9/o9NLl4Hbc1a9Ys/eMf/5C/v7+CgoIcptUtFgvFqghFR0erRIkS+u6771SxYkVOcZjslVdeUXh4uJYvX87xMMmcOXM0dOjQAqVKktzd3TVs2DBNnz6dYlWEXn75ZSUmJioqKsolfy+YscJtVa1aVf3799fw4cPNjuLyfHx8tGXLFj344INmR4GuHY8dO3bccG0xFI2AgABt2rRJ1apVu+H+o0eP6tFHH7XfMQJ3X9myZbV8+XI1bdrU7Cim4KQzbistLU3PPvus2TGgayt6//LLL2bHwP9p2LDhDdfrQdG5fPmyMjIybrr/0qVLunLlShEmgp+fn8qVK2d2DNNQrHBbzz77rOLi4syOAUkTJkzQsGHDlJCQoF9//VUZGRkOHyhaAwcO1JAhQzR37lxt2bJFO3fudPjA3Xf//fcXuObw95KSknT//fcXYSK8++67euutt1y20HIqELc1btw4TZ48WR07dlRYWJjDvZ8kadCgQSYlcz3X39n0x2sWuHjdHDd6p5nFYuF4FKGJEydq4sSJWr16terUqeOwb8eOHWrVqpWGDRumYcOGmZTQ9dStW1eHDx+WzWZTtWrVCrxm3Ov3C6RY4baqV69+030Wi+Wef4dHcZKQkHDLC0EjIiKKMA1+/vnnW+6vWrVqESVxXTk5OWrbtq2SkpLUunVrPfjgg7JYLNq7d69WrVqlpk2bauXKlQVe3HH3vPPOO7fcP2rUqCJKYg6KFQDAqeXk5GjKlClavHixDh48KJvNpgceeEA9evTQ4MGDC9xAHribKFa4rYMHD3KNQjHRtGlTRUREKDIyUk2bNpWPj4/ZkVxacHCwIiMjFRkZqYiICNWqVcvsSIDpXn/9dfu/Ud7e3mbHKXIUK9yWm5ubKlasqIiICPuLOi8g5hg3bpwSExO1fv16Xb16VfXr17cfk8cee8xlbhlRXHz22WdKTExUQkKCDhw4oMDAQPvxiIiIUO3atc2OCBS59u3ba/369crKylK9evXsvw+u8m8UxQq3dfbsWa1evfqmLyCvvPKK2RFdTl5enjZv3qyEhAQlJCRo9erVslgsysrKMjuayzp79qzWrFmj7777TkuXLlV+fj4Xr8Nl5eXladOmTfbXjQ0bNigzM1P16tVTcnKy2fHuKooV/rRDhw7pvffe06JFi3jxMMm+ffvs/2AlJiYqOztbzZo1U2xsrNnRXM5vv/2mpKQk+/HYtm2bQkJCFBERoSlTppgdDzDV/v37lZCQoFWrVumrr75S2bJl7/nFWilWuK3rLxzXX8S3b9+u2rVr26d3u3TpYnZEl9G9e3etXbtW+fn5at68uZo3b66IiIgCbzNH0WjYsKF27typ0NBQRUZGqnnz5mrWrJnKli1rdjTANDNmzFBiYqISExOVl5enZs2a2c9wuMK/VRQr3JaHh4fKlSunqKgotWjRQo899pisVqvZsVySm5ub/P39FR0drRYtWqhZs2Yucc1CcVWuXDlZLBa1bt3afhE711WZKzs7W0ePHtV9992nEiW4Ha4Z3NzcVKFCBQ0ZMkSvvPKKypQpY3akIsXK67itjh07Ki8vTwsWLND8+fO1ePFi7d271+xYLunChQuaPXu2cnNz9cYbb8jf318NGzbU8OHD9cMPP5gdz+VcuHBBa9asUdOmTbVq1SpFREQoKChI3bt318cff2x2PJdy5coV9e7dW97e3nrooYd0/PhxSdcWMB4/frzJ6VzLl19+qZ49e2rJkiUKCAhw+Dfqt99+MzveXceMFe7Yzp077dO769atk8ViUWRkpJYsWWJ2NJd1+PBhvffee1q4cCHXuxUDW7Zs0fTp0zkeJnjttdf0008/aerUqWrfvr127typGjVq6JtvvtGoUaO0bds2syO6pPT0dK1bt05ffPGFFi9e7BJvsmGeFHesTp06ysvLU05OjrKysrRixQp9+eWXZsdyKRcuXLBfJJ2QkKDdu3erXLly6tKli1q0aGF2PJezbds2+7FYt26dLl26pIcfflivvfYax6OIffXVV1q6dKkaNWrkcHeCkJAQHT582MRkrumP/1alpKSofPnyLnF3CIoVbmvKlCkOLxyPPPKIIiIi1K9fPzVv3tzseC6lQoUK8vf3V7NmzdSnTx9FRkYqNDTU7Fguq0GDBnrkkUcUGRmpPn36qHnz5i53PUlxcf78eQUEBBTYfvny5VveBgrGq1Onjvbs2aNy5cqpefPmLvdvFcUKt7Vo0SJeOIqJHTt2uMw/Ts7gwoUL/D4UEw0aNNDy5cs1cOBASf/vRuWzZs1S48aNzYzmcvr27etSReqPuMYKcDI7d+7UgQMHZLFYdP/997vE25eLq8zMTK1cudLheLRp00ZeXl5mR3M569evV/v27dWzZ0/NnTtX/fr10+7du7VhwwYlJiaqfv36Zkd0Ob/88ossFovKly9vdpQiRbHCbW3evFmfffaZw4vH888/rwYNGpgdzaVs2rRJvXv31p49e3T919Ziseihhx7SnDlzOB5F7JtvvtHLL7+sX375xWG7v7+/5syZoyeeeMKkZK5r165dmjRpkrZs2aL8/HzVq1dPw4cPV1hYmNnRXMbFixf1+uuva+nSpUpLS5Mk+fn56bnnntN7773nEmu8UaxwS8OGDdOkSZNUunRp1ahRQzabTUeOHNGVK1c0dOhQTZgwweyILmHPnj1q2LChateurX/+85+qXbu2bDab9u7dqylTpmj//v1KTk5WSEiI2VFdwvr16xUZGanOnTtryJAh9rWr9uzZow8++EDfffedEhISOAUFl3LhwgU1btxYp06dUs+ePR3+nVq8eLGqVKmi9evXy8/Pz+yodxXFCjc1b948vfLKK3r//ffVr18/eXh4SJJycnI0Y8YMDR8+XJ988on+/ve/m5z03vfss88qLy9Py5YtK3Ahrs1m01NPPSUPDw/997//NSmha3n88cdVpUoVffLJJzfc369fP504cULff/99ESdzXS1atFCvXr30zDPPsICxSQYPHqz4+HitWrVKgYGBDvtSU1PVtm1btWrV6t6/1ZMNuIkGDRrYJk+efNP9H3zwga1BgwZFmMh1+fv72zZv3nzT/Zs2bbL5+/sXYSLXVrZsWdvOnTtvun/Hjh22smXLFmEiDBw40BYUFGQrVaqU7amnnrLFxsbasrKyzI7lUqpWrWpbsWLFTff/8MMPtqpVqxZdIJOw8jpuavfu3be8D2DXrl21e/fuIkzkui5dulTgL8DfCwoK0qVLl4owkWu7evXqLd8NaLVa7/lFEIubjz76SKdOndLXX38tX19fvfDCCwoKClLfvn2VmJhodjyXcObMGT300EM33R8aGqrU1NQiTGQOihVuyt3dXdnZ2Tfdn5OTI3d39yJM5LqqVaumTZs23XT/xo0bVbVq1SJM5NoeeOABrV69+qb74+PjVbNmzSJMBOnaPeratm2ruXPn6uzZs/rkk0+0adMmtWzZ0uxoLsHf31/Hjh276f6jR4+6xDsEKVa4qfr162vRokU33b9gwQLVq1evCBO5ru7duysmJkYpKSkF9u3atUtDhw7Vc889Z0Iy1xQdHa2hQ4fe8Bqq5cuXa9iwYXrxxRdNSAbp2vU8H3/8sSZMmKCdO3cqPDzc7EguoX379nr99ddv+Ad5VlaW3nzzTbVv396EZEWLi9dxU9999526du2qmJgYDRkyxH4qKjU1VR988IGmTp2q2NhYderUyeSk976rV6+qVatW2rhxo9q0aePwLrRVq1bp0Ucf1erVq1WqVCmTk7qG/Px8de/eXcuWLVOtWrUcjsfBgwfVtWtXff7553Jz42/XopKRkaFly5Zp8eLFSkhIUI0aNdSjRw/17NmT2cMicvLkSYWHh8vT01MDBgzQgw8+KOna78W///1vZWVl6X//939VpUoVk5PeXRQr3NK0adM0dOhQ5ebm2t9pk56eLnd3d02cOFGDBw82N6ALyc7O1pQpU+xriknXTkk999xz+uc//ylPT0+TE7qepUuX3vB4MHtY9Ly8vOTn56du3bqpZ8+erOtmkqNHj6p///6Ki4tzWG+vTZs2mj59ukuUXIoVbuvkyZP6/PPPdfDgQUnXXjyefvrpe/6vDgDOIy4uTq1bt2aWsJhIS0uzv2bUrFlT5cqVMzlR0aFYAQAAGISbMAMAnFK9evUUHx8vPz8/1a1bt8Diub+3devWIkwGV0axAgA4pS5dutivLezatau5YYD/w6lAAIBTy8vLU1JSkurUqXPP34cOxR9X+QFOKDs7W/v371dubq7ZUQDTubu7q127drp48aLZUQBOBeL2atSooc2bNxdYMffixYuqV6+ejhw5YlIy13PlyhUNHDhQ8+bNkyQdOHBANWrU0KBBgxQcHKwRI0aYnPDe99RTT93x2C+//PIuJsHvhYWF6ciRI6pevbrZUVzSN998c8djO3fufBeTmI9ihds6duyY8vLyCmzPysrSqVOnTEjkukaOHKkdO3YoISHBYQXj1q1ba9SoURSrInB9PTdJstlsio2NldVqta/uvWXLFl28ePFPFTD8dWPGjNHQoUP17rvvqn79+vLx8XHYf6t7O+Kv++M1bhaLRb+/0uj3byy40evJvYRihZv6/V8gP/74o8MLSl5enuLj41WtWjUTkrmur776SkuXLlWjRo0c/qEKCQnR4cOHTUzmOj799FP7fw8fPlzdunXTxx9/bL9vZl5envr3788LeRG7/odG586dHX43bDabLBbLPf9ibrb8/Hz7f69atUrDhw/X2LFj1bhxY1ksFq1fv15vvPGGxo4da2LKosHF67ip6wvt/fEvD0ny8PBQtWrV9MEHH3BLmyLk7e2tlJQU1ahRQ76+vtqxY4dq1KihHTt2qHnz5kpPTzc7okupUKGCkpKSVKtWLYft+/fvV5MmTfTrr7+alMz1JCYm3nJ/REREESVBaGioPv74Yz322GMO29etW6e+fftq7969JiUrGsxY4aau/wVSvXp1bd68Wf7+/iYnQoMGDbR8+XINHDhQ0v+bXp81a5YaN25sZjSXlJubq7179xYoVnv37nX4Cx53H8Wp+Dh8+LDDGY7rrFarjh07VvSBihjFCrd19OjRAtsuXryosmXLFn0YFzdu3Di1b99ee/bsUW5urj788EPt3r1bGzZsuO1f7DDeiy++qJdeekmHDh1So0aNJEnJyckaP368XnzxRZPTuZaDBw/q66+/1rFjx2SxWFSjRg116dJFNWrUMDuay2nQoIEGDx6shQsXqmLFipKk1NRUDRkyRI8++qjJ6YqADbiN8ePH25YsWWL//JlnnrFZLBZbcHCwbfv27SYmc007d+60/f3vf7c99NBDttq1a9t69uxp27lzp9mxXFJeXp5twoQJtuDgYJvFYrH/XkyYMMGWm5trdjyXMXbsWFuJEiVsbm5utqCgIFtgYKDNzc3N5uHhYXv//ffNjudyDhw4YAsNDbV5eHjY7rvvPtt9991n8/DwsD300EO2gwcPmh3vruMaK9xWjRo1tHDhQjVp0kQrV65Ut27dtHTpUv33v//V8ePHFRcXZ3ZEwHQZGRmSePdZUVuzZo1at26tN998U6+99pp9gdALFy5o6tSpGjt2rFavXq3mzZubnNS15Ofna9WqVdq3b59sNptCQkLUunXrW9526F5BscJteXl56cCBA6pSpYpee+01Xb16VZ988okOHDighg0bKi0tzeyILqNFixbq1auXnnnmmRtewwC4mu7du6ts2bL65JNPbri/b9++unTpkj777LMiTuaacnNzVapUKW3fvl2hoaFmxzEFK6/jtvz8/HTixAlJ0ooVK9S6dWtJ197GzFuYi1ZYWJjeeOMNBQUF6emnn9ZXX32l7Oxss2O5rLNnzyoqKkrBwcEqUaKE3N3dHT5w923atElRUVE33R8VFaXk5OQiTOTaSpQooapVq7r0awMzVritV199Vd99953uv/9+bdu2TceOHVPp0qW1dOlSTZgwgbvGF7HrU+yLFy9WbGys3N3d9cwzz6hnz568M6qIdejQQcePH9err76qihUrFjjN0aVLF5OSuQ5vb28dOHBAlStXvuH+kydP6v7771dmZmYRJ3Ndn376qT7//HMtXLhQ5cqVMztOkaNY4bZycnL00Ucf6fjx44qOjlbdunUlSVOnTlXp0qX18ssvm5zQdV29elXffvutxowZo127drn0X4lm8PX11bp16/TII4+YHcVlubm5KTU1VQEBATfcf/bsWQUHB/O7UYTq1q2rQ4cOKScnR1WrVi2wCv69/sc4yy3glnJyctS3b1+9+eabBd62PHjwYHNCQdK1ty8vWbJECxcu1M6dO9WgQQOzI7mcKlWqFFg8F0Vv9uzZKl269A33Xbp0qYjT4I+3t3E1zFjhtsqWLautW7eyHkwxkJGRoWXLlmnx4sVKSEhQjRo11KNHD/Xs2VM1a9Y0O57LiYuL0wcffKBPPvmE2zuZpFq1anf0TrMbrccH3A0UK9zWiy++qLCwMMXExJgdxeV5eXnJz89P3bp1U8+ePZmlMpmfn5+uXLmi3NxceXt7y8PDw2H/hQsXTEoGwCycCsRt1axZU++++67Wr19/w7vGDxo0yKRkrufrr79W69at7fdxhLmmTp1qdgSgWChXrpwOHDggf39/+fn53XIW8V7/g4MZK9xW9erVb7rPYrHoyJEjRZgGknT+/Hnt379fFotFDzzwgCpUqGB2JAAubN68eXruuefk6empefPm3XLsCy+8UESpzEGxApzIlStX9Oqrr2r+/Pn2m/y6u7vr73//u6ZNmyZvb2+TE7qevLw8ffXVV9q7d68sFotCQkLUuXNn1rECXBTFCnAi/fr106pVqzR9+nQ1bdpUkpSUlKRBgwapTZs2mjFjhskJXcuhQ4f0+OOP69SpU6pVq5ZsNpv9LgXLly/XfffdZ3ZEwBT5+fk6dOiQzp07Z/8j8Lp7/fZCFCvcUExMjN599135+Pjc9qL1yZMnF1Eq+Pv764svvlBkZKTD9jVr1qhbt246f/68OcFc1OOPPy6bzaZFixbZF0L89ddf1atXL7m5uWn58uUmJwSKXnJysnr06KGff/65wHIkFovlnl9TjIvXcUPbtm1TTk6O/b9vxhVuqFmcXLlyRYGBgQW2BwQE6MqVKyYkcm2JiYlKTk52WF26fPnyGj9+vH1GEUXD3d1dZ86cKbBQ6K+//qqAgIB7/sW8OHnllVcUHh6u5cuX3/COBPc6ihVuaM2aNTpy5IisVqvWrFljdhz8n8aNG2vUqFGaP3++SpUqJUnKzMzUO++8o8aNG5uczvV4enrecAHK3377TSVLljQhkeu62cmXrKwsjkURO3jwoL744guXXVuPYoWbuv/++x3+Auzevbs++uijG86YoGh8+OGHat++vSpXrqyHH35YFotF27dvV6lSpfTjjz+aHc/ldOrUSX379tWcOXP06KOPSpI2btyoV155RZ07dzY5nWv46KOPJF2bPf/jCux5eXlau3atHnzwQbPiuaSGDRvq0KFDLlusuMYKN/XHe3D5+vpqx44drMBusszMTC1cuFD79u2TzWZTSEiIevbsKS8vL7OjuZyLFy/qhRde0LfffmtfHDQ3N1edO3fW3LlzZbVaTU5477u+HMzPP/+sypUrO7wbs2TJkqpWrZpGjx6thg0bmhXRJezcudP+34cPH9Ybb7yhf/3rXwoLCyuwcG6dOnWKOl6RoljhpihWwJ05dOiQ9u7day+6rvqXuplatGihL7/8Un5+fmZHcUlubm6yWCw3PSV7fR8Xr8OlWSyWAhcdutpFiMXR/v37NW3aNPu6SQ8++KBeffVVTneYqGbNmpQpk/3xWtC8vDzt2rVLVatWpWwVAe7F+P8wY4WbcnNzU4cOHeTp6SlJ+vbbb9WyZcsCt7T58ssvzYjnkr744gs9//zzCg8Pt1+snpycrM2bN2vx4sV69tlnTU7oWp555hmFh4drxIgRDtvff/99bdq0SZ9//rlJyVzP4MGDFRYWpt69eysvL0/NmzfXhg0b5O3tre+++67AEiUw3ksvvaQPP/xQvr6+ZkcxFcUKN/Xiiy/e0bhPP/30LifBdTVq1FCvXr00evRoh+2jRo3SggULuL1QEatQoYJWr16tsLAwh+27du1S69atdfbsWZOSuZ5KlSrp66+/Vnh4uL766isNGDBAa9as0fz587VmzRr99NNPZke8591syQtXQ7ECnIi3t7d27txZ4LTTwYMH9fDDD7OWVRHz8vLS9u3bVatWLYft+/btU926dZWZmWlSMtdTqlQpHTp0SJUrV1bfvn3l7e2tqVOn6ujRo3r44YeVkZFhdsR73h+vy3VVbmYHAHDnIiMjtW7dugLbk5KS1KxZMxMSubbQ0FAtXbq0wPYlS5YoJCTEhESuKzAwUHv27FFeXp5WrFih1q1bS7q2qC73bSw6XIfLxetAsffNN9/Y/7tz584aPny4tmzZokaNGkm6do3V559/rnfeecesiC7rzTff1NNPP63Dhw+rZcuWkqT4+Hh99tlnXF9VxF588UV169bNvtJ3mzZtJF1bV4w3dhSdBx544Lbl6sKFC0WUxhycCgSKOTe3O5tYdoW3MRdHy5cv19ixY7V9+3Z5eXmpTp06GjVqlCIiIsyO5nK++OILnThxQs8++6wqV64sSZo3b57Kli2rLl26mJzu3ufm5qapU6fedv22F154oYgSmYNiBQC4p1y9etV+yycUHa6xuoZrrIB7wK+//qqpU6eaHcMlXbx4UbNnz9b//M//2E9xbN26VadOnTI5mWvJy8vTu+++q0qVKql06dL2d8i++eabmjNnjsnpXAPXV11DsQKclM1m048//qhu3bopODhYY8aMMTuSy9m5c6ceeOABTZgwQe+//74uXrwoSYqNjdXIkSPNDedixowZo7lz52rixIkON10OCwvT7NmzTUzmOjgBdg3FCnAyx44d01tvvaWqVavq8ccfV6lSpbR8+XKlpqaaHc3lxMTEKDo6WgcPHnQ49dShQwetXbvWxGSuZ/78+Zo5c6Z69uzp8C7AOnXqaN++fSYmcx35+fkufxpQolgBTiErK0ufffaZWrVqpdq1ayslJUWTJ0+Wm5ubRowYodatW/OWchNs3rxZ/fr1K7C9UqVKFN0idurUqRveVig/P185OTkmJIKrYrkFwAlUqlRJISEh6tWrl7744gv7vc+ef/55k5O5tlKlSt1w4cn9+/erQoUKJiRyXQ899JDWrVunqlWrOmz//PPPVbduXZNSwRVRrAAnkJeXZ78pNjNTxUeXLl00evRo/fe//5V07eLd48ePa8SIEXr66adNTucart+fbtSoUYqKitKpU6eUn5+vL7/8Uvv379f8+fP13XffmR0TLoRTgYATOHPmjPr27avPPvtMQUFBevrppxUbG8u7cEw2adIknT9/XgEBAcrMzFRERIRq1qwpX19f3kxQRObNm6fMzEw98cQTWrp0qb7//ntZLBa99dZb2rt3r7799lv7YqFAUWAdK8DJHD58WJ9++qnmzZunU6dO6fnnn1d0dLRatmzJbJZJVq9era1btyo/P1/16tWz304Fdx9rJ6G4oVgBTio/P18//vij5syZo2+//Va+vr765ZdfzI4FFCk3NzedPXuWa9pQbFCsgHvA+fPntWDBAsXExJgdxSVs3LhRFy5cUIcOHezb5s+fr1GjRuny5cvq2rWrpk2bJk9PTxNTugY3NzdZrVaXvz8dig+KFQD8SR06dFBkZKSGDx8uSdq1a5fq1aun6Oho1a5dW++//7769eunt99+29ygLoD706G4oVgBwJ9UsWJFffvttwoPD5ckvf7660pMTFRSUpKka2/xHzVqlPbs2WNmTJfANVYobnhXIAD8SWlpaQoMDLR/npiYqPbt29s/b9CggU6cOGFGNJfDO2NR3FCsAOBPCgwM1NGjRyVJ2dnZ2rp1qxo3bmzff+nSJXl4eJgVz6Vw0gXFDcUKuEccPnzY7Aguo3379hoxYoTWrVunkSNHytvbW82aNbPv37lzp+677z4TE7oO7k+H4oZiBTihMmXKqGPHjlq2bJkkKSkpyWHGBHfXe++9J3d3d0VERGjWrFmaNWuWSpYsad//n//8R23btjUxIQCzcPE64IS++OIL7d69W59++qnKlSunffv2qVevXpo5c6bZ0VxKenq6SpcuXWBh1gsXLqh06dIOZQuAa6BYAU7g119/lc1mk7+/v8P2OXPmqG/fvvLx8dG+ffsUHBxsUkIAgMSpQMAp/P3vf9f333/vsO27777TwIED9emnn+rJJ5/UqFGjTEoHALiOGSvACZQvX17Jycm6//77JUnr1q3TE088of/85z966qmntGnTJnXp0kVnzpwxOSkAuLYSZgcAcHu5ubnKzMyUJG3btk3PPfecli5dqnbt2kmSypYtq99++83MiAAAUawAp9CoUSP17t1b7dq107///W+98cYb9lIlSUuWLFHt2rVNTAgAkChWgFP497//rT59+mjjxo0aPXq0RowYofPnz+uRRx7R2rVrNXPmTC1dutTsmADg8rjGCnBCq1ev1siRI7Vz505VqlRJw4YNU9++fc2OBQAuj2IFAABgEJZbAAAAMAjFCgAAwCAUKwAAAINQrAAAAAxCsQIAADAI61gBTiY+Pl7x8fE6d+6c8vPzHfb95z//MSkVAECiWAFO5Z133tHo0aMVHh6uihUrymKxmB0JAPA7rGMFOJGKFStq4sSJioqKMjsKAOAGuMYKcCLZ2dlq0qSJ2TEAADdBsQKcyMsvv6zFixebHQMAcBOcCgSKuZiYGPt/5+fna968eapTp47q1KkjDw8Ph7GTJ08u6ngAgN+hWAHFXIsWLe547Jo1a+5iEgDA7VCsAAAADMI1VoATeemll3Tp0qUC2y9fvqyXXnrJhEQAgN9jxgpwIu7u7jpz5owCAgIctv/yyy8KCgpSbm6uSckAABILhAJOISMjQzabTTabTZcuXVKpUqXs+/Ly8vT9998XKFsAgKJHsQKcQNmyZWWxWGSxWPTAAw8U2G+xWPTOO++YkAwA8HucCgScQGJiomw2m1q2bKlly5apXLly9n0lS5ZU1apVFRwcbGJCAIDEjBXgFCIiIpSbm6u///3vCg8PV5UqVcyOBAC4Ad4VCDiJEiVKaNmyZcrLyzM7CgDgJihWgBNp1aqVEhISzI4BALgJTgUCTqRDhw4aOXKkUlJSVL9+ffn4+Djs79y5s0nJAAASF68DTsXN7eaTzBaLhdOEAGAyihUAAIBBuMYKAADAIFxjBTiR0aNH33L/W2+9VURJAAA3wqlAwInUrVvX4fOcnBwdPXpUJUqU0H333aetW7ealAwAIDFjBTiVbdu2FdiWkZGh6OhoPfnkkyYkAgD8HjNWwD0gJSVFnTp10rFjx8yOAgAujYvXgXvAxYsXlZ6ebnYMAHB5nAoEnMhHH33k8LnNZtOZM2e0YMECtW/f3qRUAIDrOBUIOJHq1as7fO7m5qYKFSqoZcuWGjlypHx9fU1KBgCQKFYAAACG4RorwEmdPHlSp06dMjsGAOB3KFaAE8nPz9fo0aNltVpVtWpV/e1vf1PZsmX17rvvKj8/3+x4AODyuHgdcCKvv/665syZo/Hjx6tp06ay2Wz66aef9Pbbb+vq1asaM2aM2REBwKVxjRXgRIKDg/Xxxx+rc+fODtu//vpr9e/fn1ODAGAyTgUCTuTChQt68MEHC2x/8MEHdeHCBRMSAQB+j2IFOJGHH35Y06dPL7B9+vTpevjhh01IBAD4PU4FAk4kMTFRHTt21N/+9jc1btxYFotF69ev14kTJ/T999+rWbNmZkcEAJdGsQKczOnTp/X//X//n/bt2yebzaaQkBD1799fwcHBZkcDAJdHsQKcwJEjR1S9enVZLBazowAAboFrrAAncP/99+v8+fP2z7t3766zZ8+amAgAcCMUK8AJ/HFi+fvvv9fly5dNSgMAuBmKFQAAgEEoVoATsFgsBa6v4norACh+uKUN4ARsNpuio6Pl6ekpSbp69apeeeUV+fj4OIz78ssvzYgHAPg/FCvACbzwwgsOn/fq1cukJACAW2G5BQAAAINwjRUAAIBBKFYAAAAGoVgBAAAYhGIFAABgEIoVAACAQShWAAAABqFYAQAAGIRiBQDFWHZ2ttkRAPwJFCsALi0rK0uDBg1SQECASpUqpccee0ybN2+WJNWvX18ffPCBfWzXrl1VokQJZWRkSJJSU1NlsVi0f/9+SVK1atU0duxYvfTSS/L19dXf/vY3zZw50+HxTp06pe7du8vPz0/ly5dXly5ddOzYMfv+6Ohode3aVePGjVNwcLAeeOCBu/wMADASxQqASxs2bJiWLVumefPmaevWrapZs6batWunCxcuKDIyUgkJCZKu3a9x3bp18vPzU1JSkiRpzZo1CgoKUq1atezf74MPPlB4eLi2bdum/v376x//+If27dsnSbpy5YpatGih0qVLa+3atUpKSlLp0qXVvn17h5mp+Ph47d27VytXrtR3331XdE8GgL+MYgXAZV2+fFkzZszQ+++/rw4dOigkJESzZs2Sl5eX5syZo8jISK1bt075+fnauXOn3N3dFRUVZS9bCQkJioiIcPiejz/+uPr376+aNWtq+PDh8vf3t49fsmSJ3NzcNHv2bIWFhal27dr69NNPdfz4cfsYSfLx8dHs2bP10EMPKTQ0tIieDQBGoFgBcFmHDx9WTk6OmjZtat/m4eGhRx99VHv37lXz5s116dIlbdu2TYmJiYqIiFCLFi2UmJgo6cbFqk6dOvb/tlgsCgoK0rlz5yRJW7Zs0aFDh+Tr66vSpUurdOnSKleunK5evarDhw/bvy4sLEwlS5a8mz86gLukhNkBAMAs1+9Bb7FYCmy3WCyyWq165JFHlJCQoPXr16tly5Zq1qyZtm/froMHD+rAgQOKjIx0+FoPDw+Hzy0Wi/Lz8yVJ+fn5ql+/vhYtWlQgS4UKFez/7ePjY8SPB8AEzFgBcFk1a9ZUyZIl7ddMSVJOTo7+93//V7Vr15YkRUZGas2aNVq7dq0iIyNVtmxZhYSE6L333lNAQIB93J2oV6+eDh48qICAANWsWdPhw2q1Gv7zASh6FCsALsvHx0f/+Mc/9K9//UsrVqzQnj171KdPH125ckW9e/eWdK1YrVixQhaLRSEhIfZtixYtKnAa8HZ69uwpf39/denSRevWrdPRo0eVmJio1157TSdPnjT85wNQ9ChWAFza+PHj9fTTTysqKkr16tXToUOH9OOPP8rPz0+S1Lx5c0lSRESE/ZRhRESE8vLy/nSx8vb21tq1a/W3v/1NTz31lGrXrq2XXnpJmZmZKlOmjLE/GABTWGzXLzIAAADAX8KMFQAAgEEoVgAAAAahWAEAABiEYgUAAGAQihUAAIBBKFYAAAAGoVgBAAAYhGIFAABgEIoVAACAQShWAAAABqFYAQAAGOT/B/Yp0Ic8b2BIAAAAAElFTkSuQmCC",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "for feature in categorical_features:\n",
    "    data=dataset.copy()\n",
    "    dataset.groupby(feature)['selling_price'].median().plot.bar()\n",
    "    plt.xlabel(feature)\n",
    "    plt.ylabel('selling_price')\n",
    "    plt.title(feature)\n",
    "    plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "id": "41ab46b9",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>name</th>\n",
       "      <th>year</th>\n",
       "      <th>selling_price</th>\n",
       "      <th>km_driven</th>\n",
       "      <th>fuel</th>\n",
       "      <th>seller_type</th>\n",
       "      <th>transmission</th>\n",
       "      <th>owner</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Maruti 800 AC</td>\n",
       "      <td>2007</td>\n",
       "      <td>60000</td>\n",
       "      <td>70000</td>\n",
       "      <td>Petrol</td>\n",
       "      <td>Individual</td>\n",
       "      <td>Manual</td>\n",
       "      <td>First Owner</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Maruti Wagon R LXI Minor</td>\n",
       "      <td>2007</td>\n",
       "      <td>135000</td>\n",
       "      <td>50000</td>\n",
       "      <td>Petrol</td>\n",
       "      <td>Individual</td>\n",
       "      <td>Manual</td>\n",
       "      <td>First Owner</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Hyundai Verna 1.6 SX</td>\n",
       "      <td>2012</td>\n",
       "      <td>600000</td>\n",
       "      <td>100000</td>\n",
       "      <td>Diesel</td>\n",
       "      <td>Individual</td>\n",
       "      <td>Manual</td>\n",
       "      <td>First Owner</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Datsun RediGO T Option</td>\n",
       "      <td>2017</td>\n",
       "      <td>250000</td>\n",
       "      <td>46000</td>\n",
       "      <td>Petrol</td>\n",
       "      <td>Individual</td>\n",
       "      <td>Manual</td>\n",
       "      <td>First Owner</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Honda Amaze VX i-DTEC</td>\n",
       "      <td>2014</td>\n",
       "      <td>450000</td>\n",
       "      <td>141000</td>\n",
       "      <td>Diesel</td>\n",
       "      <td>Individual</td>\n",
       "      <td>Manual</td>\n",
       "      <td>Second Owner</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                       name  year  selling_price  km_driven    fuel  \\\n",
       "0             Maruti 800 AC  2007          60000      70000  Petrol   \n",
       "1  Maruti Wagon R LXI Minor  2007         135000      50000  Petrol   \n",
       "2      Hyundai Verna 1.6 SX  2012         600000     100000  Diesel   \n",
       "3    Datsun RediGO T Option  2017         250000      46000  Petrol   \n",
       "4     Honda Amaze VX i-DTEC  2014         450000     141000  Diesel   \n",
       "\n",
       "  seller_type transmission         owner  \n",
       "0  Individual       Manual   First Owner  \n",
       "1  Individual       Manual   First Owner  \n",
       "2  Individual       Manual   First Owner  \n",
       "3  Individual       Manual   First Owner  \n",
       "4  Individual       Manual  Second Owner  "
      ]
     },
     "execution_count": 25,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dataset.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "id": "ba637320",
   "metadata": {},
   "outputs": [],
   "source": [
    "dataset.drop(columns=['name'],inplace=True)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "f0488d56",
   "metadata": {},
   "source": [
    "# Handling Temporial Data(year)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "id": "e881244c",
   "metadata": {},
   "outputs": [],
   "source": [
    "dataset['present_year']=2020\n",
    "dataset['new_year']=dataset['present_year']-dataset['year']\n",
    "dataset=dataset.drop(columns=['year','present_year'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "id": "34f3bf90",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>selling_price</th>\n",
       "      <th>km_driven</th>\n",
       "      <th>fuel</th>\n",
       "      <th>seller_type</th>\n",
       "      <th>transmission</th>\n",
       "      <th>owner</th>\n",
       "      <th>new_year</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>60000</td>\n",
       "      <td>70000</td>\n",
       "      <td>Petrol</td>\n",
       "      <td>Individual</td>\n",
       "      <td>Manual</td>\n",
       "      <td>First Owner</td>\n",
       "      <td>13</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>135000</td>\n",
       "      <td>50000</td>\n",
       "      <td>Petrol</td>\n",
       "      <td>Individual</td>\n",
       "      <td>Manual</td>\n",
       "      <td>First Owner</td>\n",
       "      <td>13</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>600000</td>\n",
       "      <td>100000</td>\n",
       "      <td>Diesel</td>\n",
       "      <td>Individual</td>\n",
       "      <td>Manual</td>\n",
       "      <td>First Owner</td>\n",
       "      <td>8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>250000</td>\n",
       "      <td>46000</td>\n",
       "      <td>Petrol</td>\n",
       "      <td>Individual</td>\n",
       "      <td>Manual</td>\n",
       "      <td>First Owner</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>450000</td>\n",
       "      <td>141000</td>\n",
       "      <td>Diesel</td>\n",
       "      <td>Individual</td>\n",
       "      <td>Manual</td>\n",
       "      <td>Second Owner</td>\n",
       "      <td>6</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   selling_price  km_driven    fuel seller_type transmission         owner  \\\n",
       "0          60000      70000  Petrol  Individual       Manual   First Owner   \n",
       "1         135000      50000  Petrol  Individual       Manual   First Owner   \n",
       "2         600000     100000  Diesel  Individual       Manual   First Owner   \n",
       "3         250000      46000  Petrol  Individual       Manual   First Owner   \n",
       "4         450000     141000  Diesel  Individual       Manual  Second Owner   \n",
       "\n",
       "   new_year  \n",
       "0        13  \n",
       "1        13  \n",
       "2         8  \n",
       "3         3  \n",
       "4         6  "
      ]
     },
     "execution_count": 28,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dataset.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "064d6479",
   "metadata": {},
   "source": [
    "# Scaling Numerical Features"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "id": "4be1e31c",
   "metadata": {},
   "outputs": [],
   "source": [
    "num_features=['selling_price','km_driven']\n",
    "\n",
    "for feature in num_features:\n",
    "    dataset[feature]=np.log(dataset[feature])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "id": "a604f22e",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>selling_price</th>\n",
       "      <th>km_driven</th>\n",
       "      <th>fuel</th>\n",
       "      <th>seller_type</th>\n",
       "      <th>transmission</th>\n",
       "      <th>owner</th>\n",
       "      <th>new_year</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>11.002100</td>\n",
       "      <td>11.156251</td>\n",
       "      <td>Petrol</td>\n",
       "      <td>Individual</td>\n",
       "      <td>Manual</td>\n",
       "      <td>First Owner</td>\n",
       "      <td>13</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>11.813030</td>\n",
       "      <td>10.819778</td>\n",
       "      <td>Petrol</td>\n",
       "      <td>Individual</td>\n",
       "      <td>Manual</td>\n",
       "      <td>First Owner</td>\n",
       "      <td>13</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>13.304685</td>\n",
       "      <td>11.512925</td>\n",
       "      <td>Diesel</td>\n",
       "      <td>Individual</td>\n",
       "      <td>Manual</td>\n",
       "      <td>First Owner</td>\n",
       "      <td>8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>12.429216</td>\n",
       "      <td>10.736397</td>\n",
       "      <td>Petrol</td>\n",
       "      <td>Individual</td>\n",
       "      <td>Manual</td>\n",
       "      <td>First Owner</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>13.017003</td>\n",
       "      <td>11.856515</td>\n",
       "      <td>Diesel</td>\n",
       "      <td>Individual</td>\n",
       "      <td>Manual</td>\n",
       "      <td>Second Owner</td>\n",
       "      <td>6</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   selling_price  km_driven    fuel seller_type transmission         owner  \\\n",
       "0      11.002100  11.156251  Petrol  Individual       Manual   First Owner   \n",
       "1      11.813030  10.819778  Petrol  Individual       Manual   First Owner   \n",
       "2      13.304685  11.512925  Diesel  Individual       Manual   First Owner   \n",
       "3      12.429216  10.736397  Petrol  Individual       Manual   First Owner   \n",
       "4      13.017003  11.856515  Diesel  Individual       Manual  Second Owner   \n",
       "\n",
       "   new_year  \n",
       "0        13  \n",
       "1        13  \n",
       "2         8  \n",
       "3         3  \n",
       "4         6  "
      ]
     },
     "execution_count": 30,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dataset.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "74afa0ad",
   "metadata": {},
   "source": [
    "# Scaling categorical Features"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "id": "f7f9f1e1",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['fuel', 'seller_type', 'transmission', 'owner']"
      ]
     },
     "execution_count": 31,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "categorical_features=[feature for feature in dataset.columns if dataset[feature].dtype=='O']\n",
    "categorical_features"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "id": "87978a07",
   "metadata": {},
   "outputs": [],
   "source": [
    "for feature in categorical_features:\n",
    "    temp=dataset.groupby(feature)['selling_price'].count()/len(dataset)\n",
    "    temp_df=temp[temp>0.01].index\n",
    "    dataset[feature]=np.where(dataset[feature].isin(temp_df),dataset[feature],'Rare_var')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "id": "315e2da6",
   "metadata": {},
   "outputs": [],
   "source": [
    "for feature in categorical_features:\n",
    "    labels_ordered=dataset.groupby([feature])['selling_price'].mean().sort_values().index\n",
    "    labels_ordered={k:i for i,k in enumerate(labels_ordered,0)}\n",
    "    dataset[feature]=dataset[feature].map(labels_ordered)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "id": "850ff990",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "6"
      ]
     },
     "execution_count": 34,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "scaling_feature=[feature for feature in dataset.columns if feature not in ['selling_price'] ]\n",
    "len(scaling_feature)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "id": "fa9cf6aa",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['km_driven', 'fuel', 'seller_type', 'transmission', 'owner', 'new_year']"
      ]
     },
     "execution_count": 35,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "scaling_feature"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "id": "7d14075f",
   "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>MinMaxScaler()</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\">MinMaxScaler</label><div class=\"sk-toggleable__content\"><pre>MinMaxScaler()</pre></div></div></div></div></div>"
      ],
      "text/plain": [
       "MinMaxScaler()"
      ]
     },
     "execution_count": 36,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "feature_scale=[feature for feature in dataset.columns if feature not in ['selling_price']]\n",
    "\n",
    "from sklearn.preprocessing import MinMaxScaler\n",
    "scaler=MinMaxScaler()\n",
    "scaler.fit(dataset[feature_scale])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "id": "0385823e",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[0.82027744, 0.5       , 0.        , 0.        , 0.75      ,\n",
       "        0.46428571],\n",
       "       [0.79553789, 0.5       , 0.        , 0.        , 0.75      ,\n",
       "        0.46428571],\n",
       "       [0.84650242, 1.        , 0.        , 0.        , 0.75      ,\n",
       "        0.28571429],\n",
       "       ...,\n",
       "       [0.8328023 , 0.5       , 0.        , 0.        , 0.5       ,\n",
       "        0.39285714],\n",
       "       [0.83875565, 1.        , 0.        , 0.        , 0.75      ,\n",
       "        0.14285714],\n",
       "       [0.77913098, 0.5       , 0.        , 0.        , 0.75      ,\n",
       "        0.14285714]])"
      ]
     },
     "execution_count": 37,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "scaler.transform(dataset[feature_scale])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "id": "58f505b9",
   "metadata": {},
   "outputs": [],
   "source": [
    "data = pd.concat([dataset[['selling_price']].reset_index(drop=True),\n",
    "                    pd.DataFrame(scaler.transform(dataset[feature_scale]), columns=feature_scale)],\n",
    "                    axis=1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "id": "238d7d51",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>selling_price</th>\n",
       "      <th>km_driven</th>\n",
       "      <th>fuel</th>\n",
       "      <th>seller_type</th>\n",
       "      <th>transmission</th>\n",
       "      <th>owner</th>\n",
       "      <th>new_year</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>11.002100</td>\n",
       "      <td>0.820277</td>\n",
       "      <td>0.5</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.75</td>\n",
       "      <td>0.464286</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>11.813030</td>\n",
       "      <td>0.795538</td>\n",
       "      <td>0.5</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.75</td>\n",
       "      <td>0.464286</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>13.304685</td>\n",
       "      <td>0.846502</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.75</td>\n",
       "      <td>0.285714</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>12.429216</td>\n",
       "      <td>0.789407</td>\n",
       "      <td>0.5</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.75</td>\n",
       "      <td>0.107143</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>13.017003</td>\n",
       "      <td>0.871765</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.50</td>\n",
       "      <td>0.214286</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   selling_price  km_driven  fuel  seller_type  transmission  owner  new_year\n",
       "0      11.002100   0.820277   0.5          0.0           0.0   0.75  0.464286\n",
       "1      11.813030   0.795538   0.5          0.0           0.0   0.75  0.464286\n",
       "2      13.304685   0.846502   1.0          0.0           0.0   0.75  0.285714\n",
       "3      12.429216   0.789407   0.5          0.0           0.0   0.75  0.107143\n",
       "4      13.017003   0.871765   1.0          0.0           0.0   0.50  0.214286"
      ]
     },
     "execution_count": 39,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "4615debf",
   "metadata": {},
   "source": [
    "# Preparing Data For Test And Train\n",
    "### Here Using \"data\" for Train And Test Data We Got 68.23% for Linear Regression and 75.05% Using Random Forest Regressor\n",
    "### Here Using \"dataset\" for Train And Test Data We Got 68.25% for Linear Regression and 90.11% Using Random Forest Regressor"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "id": "f1d1ebbc",
   "metadata": {},
   "outputs": [],
   "source": [
    "y=dataset[['selling_price']].copy()\n",
    "x=dataset.drop(['selling_price'],axis=1).copy()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "id": "51a4977c",
   "metadata": {},
   "outputs": [],
   "source": [
    "x_train,x_test,y_train,y_test=train_test_split(x,y,test_size=0.30,random_state=0) # random_state=0"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "id": "27a42d59",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "((3038, 6), (1302, 6))"
      ]
     },
     "execution_count": 42,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "x_train.shape,x_test.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "id": "a3357b41",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "((3038, 1), (1302, 1))"
      ]
     },
     "execution_count": 43,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "y_train.shape,y_test.shape"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "2a21033d",
   "metadata": {},
   "source": [
    "# Using Lasso Technique To Select Best Features"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "id": "9ac3d957",
   "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>SelectFromModel(estimator=Lasso(alpha=0.005, random_state=0))</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 sk-dashed-wrapped\"><div class=\"sk-label-container\"><div class=\"sk-label sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-2\" type=\"checkbox\" ><label for=\"sk-estimator-id-2\" class=\"sk-toggleable__label sk-toggleable__label-arrow\">SelectFromModel</label><div class=\"sk-toggleable__content\"><pre>SelectFromModel(estimator=Lasso(alpha=0.005, random_state=0))</pre></div></div></div><div class=\"sk-parallel\"><div class=\"sk-parallel-item\"><div class=\"sk-item\"><div class=\"sk-label-container\"><div class=\"sk-label sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-3\" type=\"checkbox\" ><label for=\"sk-estimator-id-3\" class=\"sk-toggleable__label sk-toggleable__label-arrow\">estimator: Lasso</label><div class=\"sk-toggleable__content\"><pre>Lasso(alpha=0.005, random_state=0)</pre></div></div></div><div class=\"sk-serial\"><div class=\"sk-item\"><div class=\"sk-estimator sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-4\" type=\"checkbox\" ><label for=\"sk-estimator-id-4\" class=\"sk-toggleable__label sk-toggleable__label-arrow\">Lasso</label><div class=\"sk-toggleable__content\"><pre>Lasso(alpha=0.005, random_state=0)</pre></div></div></div></div></div></div></div></div></div></div>"
      ],
      "text/plain": [
       "SelectFromModel(estimator=Lasso(alpha=0.005, random_state=0))"
      ]
     },
     "execution_count": 44,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from sklearn.linear_model import Lasso\n",
    "from sklearn.feature_selection import SelectFromModel\n",
    "feature_sel_model = SelectFromModel(Lasso(alpha=0.005, random_state=0)) # remember to set the seed, the random state in this function\n",
    "feature_sel_model.fit(x_train, y_train)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "id": "ab02a2ea",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([ True,  True,  True,  True,  True,  True])"
      ]
     },
     "execution_count": 45,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "feature_sel_model.get_support()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "id": "0d723669",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "total features: 6\n",
      "selected features: 6\n"
     ]
    }
   ],
   "source": [
    "selected_feat = x_train.columns[(feature_sel_model.get_support())]\n",
    "print('total features: {}'.format((x_train.shape[1])))\n",
    "print('selected features: {}'.format(len(selected_feat)))\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "id": "fa2faf5f",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Index(['km_driven', 'fuel', 'seller_type', 'transmission', 'owner',\n",
       "       'new_year'],\n",
       "      dtype='object')"
      ]
     },
     "execution_count": 47,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "selected_feat"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 48,
   "id": "bd94f8dc",
   "metadata": {},
   "outputs": [],
   "source": [
    "x_train=x_train[selected_feat]\n",
    "x_test=x_test[selected_feat]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 49,
   "id": "f5e8201a",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>km_driven</th>\n",
       "      <th>fuel</th>\n",
       "      <th>seller_type</th>\n",
       "      <th>transmission</th>\n",
       "      <th>owner</th>\n",
       "      <th>new_year</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>330</th>\n",
       "      <td>11.695247</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>12</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3022</th>\n",
       "      <td>10.799576</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2497</th>\n",
       "      <td>11.289782</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>16</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2078</th>\n",
       "      <td>10.986292</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1837</th>\n",
       "      <td>10.870471</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "      km_driven  fuel  seller_type  transmission  owner  new_year\n",
       "330   11.695247     2            0             0      1        12\n",
       "3022  10.799576     1            0             0      3         5\n",
       "2497  11.289782     1            0             0      3        16\n",
       "2078  10.986292     1            1             0      3         6\n",
       "1837  10.870471     2            0             0      3         4"
      ]
     },
     "execution_count": 49,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "x_train.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "646c6398",
   "metadata": {},
   "source": [
    "# Using Linear Regression"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 50,
   "id": "730ecdd6",
   "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>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-5\" type=\"checkbox\" checked><label for=\"sk-estimator-id-5\" 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": 50,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "model=LinearRegression()\n",
    "model.fit(x_train,y_train)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 51,
   "id": "4cc2100c",
   "metadata": {},
   "outputs": [],
   "source": [
    "y_pred= model.predict(x_test)  \n",
    "x_pred= model.predict(x_train)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 52,
   "id": "4e269ff0",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Mean Absolute Error: 0.3635704312096986\n",
      "Mean Square Error: 0.22243254724822314\n",
      "Root Mean Square Error: 0.47162755140918466\n"
     ]
    }
   ],
   "source": [
    "mae = metrics.mean_absolute_error(y_test, y_pred)\n",
    "mse = metrics.mean_squared_error(y_test, y_pred)\n",
    "r2 = np.sqrt(metrics.mean_squared_error(y_test, y_pred))\n",
    "\n",
    "print('Mean Absolute Error:', mae)\n",
    "print('Mean Square Error:', mse)\n",
    "print('Root Mean Square Error:', r2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 53,
   "id": "35923c03",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.6825567982283098"
      ]
     },
     "execution_count": 53,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "r2_score(y_train, x_pred)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 54,
   "id": "383d16d4",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<table class=\"simpletable\">\n",
       "<caption>OLS Regression Results</caption>\n",
       "<tr>\n",
       "  <th>Dep. Variable:</th>      <td>selling_price</td>  <th>  R-squared (uncentered):</th>      <td>   0.994</td> \n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Model:</th>                   <td>OLS</td>       <th>  Adj. R-squared (uncentered):</th> <td>   0.994</td> \n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Method:</th>             <td>Least Squares</td>  <th>  F-statistic:       </th>          <td>8.215e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Date:</th>             <td>Sun, 17 Mar 2024</td> <th>  Prob (F-statistic):</th>           <td>  0.00</td>  \n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Time:</th>                 <td>18:39:51</td>     <th>  Log-Likelihood:    </th>          <td> -4308.1</td> \n",
       "</tr>\n",
       "<tr>\n",
       "  <th>No. Observations:</th>      <td>  3038</td>      <th>  AIC:               </th>          <td>   8628.</td> \n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Df Residuals:</th>          <td>  3032</td>      <th>  BIC:               </th>          <td>   8664.</td> \n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Df Model:</th>              <td>     6</td>      <th>                     </th>              <td> </td>    \n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Covariance Type:</th>      <td>nonrobust</td>    <th>                     </th>              <td> </td>    \n",
       "</tr>\n",
       "</table>\n",
       "<table class=\"simpletable\">\n",
       "<tr>\n",
       "        <td></td>          <th>coef</th>     <th>std err</th>      <th>t</th>      <th>P>|t|</th>  <th>[0.025</th>    <th>0.975]</th>  \n",
       "</tr>\n",
       "<tr>\n",
       "  <th>km_driven</th>    <td>    1.0489</td> <td>    0.010</td> <td>  100.088</td> <td> 0.000</td> <td>    1.028</td> <td>    1.069</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>fuel</th>         <td>    0.3220</td> <td>    0.036</td> <td>    8.861</td> <td> 0.000</td> <td>    0.251</td> <td>    0.393</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>seller_type</th>  <td>    0.3321</td> <td>    0.039</td> <td>    8.512</td> <td> 0.000</td> <td>    0.256</td> <td>    0.409</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>transmission</th> <td>    0.9618</td> <td>    0.061</td> <td>   15.823</td> <td> 0.000</td> <td>    0.843</td> <td>    1.081</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>owner</th>        <td>    0.6553</td> <td>    0.027</td> <td>   24.541</td> <td> 0.000</td> <td>    0.603</td> <td>    0.708</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>new_year</th>     <td>   -0.1418</td> <td>    0.005</td> <td>  -25.917</td> <td> 0.000</td> <td>   -0.153</td> <td>   -0.131</td>\n",
       "</tr>\n",
       "</table>\n",
       "<table class=\"simpletable\">\n",
       "<tr>\n",
       "  <th>Omnibus:</th>       <td>1042.189</td> <th>  Durbin-Watson:     </th> <td>   1.977</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Prob(Omnibus):</th>  <td> 0.000</td>  <th>  Jarque-Bera (JB):  </th> <td>8495.596</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Skew:</th>           <td> 1.398</td>  <th>  Prob(JB):          </th> <td>    0.00</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Kurtosis:</th>       <td>10.700</td>  <th>  Cond. No.          </th> <td>    45.7</td>\n",
       "</tr>\n",
       "</table><br/><br/>Notes:<br/>[1] R² is computed without centering (uncentered) since the model does not contain a constant.<br/>[2] Standard Errors assume that the covariance matrix of the errors is correctly specified."
      ],
      "text/latex": [
       "\\begin{center}\n",
       "\\begin{tabular}{lclc}\n",
       "\\toprule\n",
       "\\textbf{Dep. Variable:}    &  selling\\_price  & \\textbf{  R-squared (uncentered):}      &     0.994   \\\\\n",
       "\\textbf{Model:}            &       OLS        & \\textbf{  Adj. R-squared (uncentered):} &     0.994   \\\\\n",
       "\\textbf{Method:}           &  Least Squares   & \\textbf{  F-statistic:       }          & 8.215e+04   \\\\\n",
       "\\textbf{Date:}             & Sun, 17 Mar 2024 & \\textbf{  Prob (F-statistic):}          &     0.00    \\\\\n",
       "\\textbf{Time:}             &     18:39:51     & \\textbf{  Log-Likelihood:    }          &   -4308.1   \\\\\n",
       "\\textbf{No. Observations:} &        3038      & \\textbf{  AIC:               }          &     8628.   \\\\\n",
       "\\textbf{Df Residuals:}     &        3032      & \\textbf{  BIC:               }          &     8664.   \\\\\n",
       "\\textbf{Df Model:}         &           6      & \\textbf{                     }          &             \\\\\n",
       "\\textbf{Covariance Type:}  &    nonrobust     & \\textbf{                     }          &             \\\\\n",
       "\\bottomrule\n",
       "\\end{tabular}\n",
       "\\begin{tabular}{lcccccc}\n",
       "                      & \\textbf{coef} & \\textbf{std err} & \\textbf{t} & \\textbf{P$> |$t$|$} & \\textbf{[0.025} & \\textbf{0.975]}  \\\\\n",
       "\\midrule\n",
       "\\textbf{km\\_driven}   &       1.0489  &        0.010     &   100.088  &         0.000        &        1.028    &        1.069     \\\\\n",
       "\\textbf{fuel}         &       0.3220  &        0.036     &     8.861  &         0.000        &        0.251    &        0.393     \\\\\n",
       "\\textbf{seller\\_type} &       0.3321  &        0.039     &     8.512  &         0.000        &        0.256    &        0.409     \\\\\n",
       "\\textbf{transmission} &       0.9618  &        0.061     &    15.823  &         0.000        &        0.843    &        1.081     \\\\\n",
       "\\textbf{owner}        &       0.6553  &        0.027     &    24.541  &         0.000        &        0.603    &        0.708     \\\\\n",
       "\\textbf{new\\_year}    &      -0.1418  &        0.005     &   -25.917  &         0.000        &       -0.153    &       -0.131     \\\\\n",
       "\\bottomrule\n",
       "\\end{tabular}\n",
       "\\begin{tabular}{lclc}\n",
       "\\textbf{Omnibus:}       & 1042.189 & \\textbf{  Durbin-Watson:     } &    1.977  \\\\\n",
       "\\textbf{Prob(Omnibus):} &   0.000  & \\textbf{  Jarque-Bera (JB):  } & 8495.596  \\\\\n",
       "\\textbf{Skew:}          &   1.398  & \\textbf{  Prob(JB):          } &     0.00  \\\\\n",
       "\\textbf{Kurtosis:}      &  10.700  & \\textbf{  Cond. No.          } &     45.7  \\\\\n",
       "\\bottomrule\n",
       "\\end{tabular}\n",
       "%\\caption{OLS Regression Results}\n",
       "\\end{center}\n",
       "\n",
       "Notes: \\newline\n",
       " [1] R² is computed without centering (uncentered) since the model does not contain a constant. \\newline\n",
       " [2] Standard Errors assume that the covariance matrix of the errors is correctly specified."
      ],
      "text/plain": [
       "<class 'statsmodels.iolib.summary.Summary'>\n",
       "\"\"\"\n",
       "                                 OLS Regression Results                                \n",
       "=======================================================================================\n",
       "Dep. Variable:          selling_price   R-squared (uncentered):                   0.994\n",
       "Model:                            OLS   Adj. R-squared (uncentered):              0.994\n",
       "Method:                 Least Squares   F-statistic:                          8.215e+04\n",
       "Date:                Sun, 17 Mar 2024   Prob (F-statistic):                        0.00\n",
       "Time:                        18:39:51   Log-Likelihood:                         -4308.1\n",
       "No. Observations:                3038   AIC:                                      8628.\n",
       "Df Residuals:                    3032   BIC:                                      8664.\n",
       "Df Model:                           6                                                  \n",
       "Covariance Type:            nonrobust                                                  \n",
       "================================================================================\n",
       "                   coef    std err          t      P>|t|      [0.025      0.975]\n",
       "--------------------------------------------------------------------------------\n",
       "km_driven        1.0489      0.010    100.088      0.000       1.028       1.069\n",
       "fuel             0.3220      0.036      8.861      0.000       0.251       0.393\n",
       "seller_type      0.3321      0.039      8.512      0.000       0.256       0.409\n",
       "transmission     0.9618      0.061     15.823      0.000       0.843       1.081\n",
       "owner            0.6553      0.027     24.541      0.000       0.603       0.708\n",
       "new_year        -0.1418      0.005    -25.917      0.000      -0.153      -0.131\n",
       "==============================================================================\n",
       "Omnibus:                     1042.189   Durbin-Watson:                   1.977\n",
       "Prob(Omnibus):                  0.000   Jarque-Bera (JB):             8495.596\n",
       "Skew:                           1.398   Prob(JB):                         0.00\n",
       "Kurtosis:                      10.700   Cond. No.                         45.7\n",
       "==============================================================================\n",
       "\n",
       "Notes:\n",
       "[1] R² is computed without centering (uncentered) since the model does not contain a constant.\n",
       "[2] Standard Errors assume that the covariance matrix of the errors is correctly specified.\n",
       "\"\"\""
      ]
     },
     "execution_count": 54,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import statsmodels.api as sm\n",
    "simple=sm.OLS(y_train,x_train.astype(float)).fit()\n",
    "simple.summary()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 55,
   "id": "1cd84acb",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.collections.PathCollection at 0x1cb2c910f90>"
      ]
     },
     "execution_count": 55,
     "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": [
    "plt.scatter(y_test,y_pred)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 56,
   "id": "63b264aa",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Prediction for test set: [[13.72994594]\n",
      " [13.84043799]\n",
      " [12.41801421]\n",
      " ...\n",
      " [11.83646842]\n",
      " [12.36637814]\n",
      " [12.59196263]]\n"
     ]
    }
   ],
   "source": [
    "print(\"Prediction for test set: {}\".format(y_pred))"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "b54e287d",
   "metadata": {},
   "source": [
    "# Using Random Forest Regressor"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 57,
   "id": "cb17a3d7",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\ProgramData\\anaconda3\\Lib\\site-packages\\sklearn\\base.py:1151: DataConversionWarning: A column-vector y was passed when a 1d array was expected. Please change the shape of y to (n_samples,), for example using ravel().\n",
      "  return fit_method(estimator, *args, **kwargs)\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<style>#sk-container-id-4 {color: black;}#sk-container-id-4 pre{padding: 0;}#sk-container-id-4 div.sk-toggleable {background-color: white;}#sk-container-id-4 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-4 label.sk-toggleable__label-arrow:before {content: \"▸\";float: left;margin-right: 0.25em;color: #696969;}#sk-container-id-4 label.sk-toggleable__label-arrow:hover:before {color: black;}#sk-container-id-4 div.sk-estimator:hover label.sk-toggleable__label-arrow:before {color: black;}#sk-container-id-4 div.sk-toggleable__content {max-height: 0;max-width: 0;overflow: hidden;text-align: left;background-color: #f0f8ff;}#sk-container-id-4 div.sk-toggleable__content pre {margin: 0.2em;color: black;border-radius: 0.25em;background-color: #f0f8ff;}#sk-container-id-4 input.sk-toggleable__control:checked~div.sk-toggleable__content {max-height: 200px;max-width: 100%;overflow: auto;}#sk-container-id-4 input.sk-toggleable__control:checked~label.sk-toggleable__label-arrow:before {content: \"▾\";}#sk-container-id-4 div.sk-estimator input.sk-toggleable__control:checked~label.sk-toggleable__label {background-color: #d4ebff;}#sk-container-id-4 div.sk-label input.sk-toggleable__control:checked~label.sk-toggleable__label {background-color: #d4ebff;}#sk-container-id-4 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-4 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-4 div.sk-estimator:hover {background-color: #d4ebff;}#sk-container-id-4 div.sk-parallel-item::after {content: \"\";width: 100%;border-bottom: 1px solid gray;flex-grow: 1;}#sk-container-id-4 div.sk-label:hover label.sk-toggleable__label {background-color: #d4ebff;}#sk-container-id-4 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-4 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-4 div.sk-item {position: relative;z-index: 1;}#sk-container-id-4 div.sk-parallel {display: flex;align-items: stretch;justify-content: center;background-color: white;position: relative;}#sk-container-id-4 div.sk-item::before, #sk-container-id-4 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-4 div.sk-parallel-item {display: flex;flex-direction: column;z-index: 1;position: relative;background-color: white;}#sk-container-id-4 div.sk-parallel-item:first-child::after {align-self: flex-end;width: 50%;}#sk-container-id-4 div.sk-parallel-item:last-child::after {align-self: flex-start;width: 50%;}#sk-container-id-4 div.sk-parallel-item:only-child::after {width: 0;}#sk-container-id-4 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-4 div.sk-label label {font-family: monospace;font-weight: bold;display: inline-block;line-height: 1.2em;}#sk-container-id-4 div.sk-label-container {text-align: center;}#sk-container-id-4 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-4 div.sk-text-repr-fallback {display: none;}</style><div id=\"sk-container-id-4\" 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-6\" type=\"checkbox\" checked><label for=\"sk-estimator-id-6\" 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": 57,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from sklearn.ensemble import RandomForestRegressor\n",
    "model2=RandomForestRegressor()\n",
    "model2.fit(x_train,y_train)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 58,
   "id": "d816adbe",
   "metadata": {},
   "outputs": [],
   "source": [
    "y_pred2= model2.predict(x_test)  \n",
    "x_pred2= model2.predict(x_train)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 59,
   "id": "4f47533c",
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Mean Absolute Error: 0.32778355979929774\n",
      "Mean Square Error: 0.21014257058602398\n",
      "Root Mean Square Error: 0.45841310036475175\n"
     ]
    }
   ],
   "source": [
    "mae = metrics.mean_absolute_error(y_test, y_pred2)\n",
    "mse = metrics.mean_squared_error(y_test, y_pred2)\n",
    "r2 = np.sqrt(metrics.mean_squared_error(y_test, y_pred2))\n",
    "\n",
    "print('Mean Absolute Error:', mae)\n",
    "print('Mean Square Error:', mse)\n",
    "print('Root Mean Square Error:', r2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 60,
   "id": "58734e74",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.9009513882630886"
      ]
     },
     "execution_count": 60,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "r2_score(y_train, x_pred2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 61,
   "id": "8ae6be15",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Prediction for test set: [13.38060842 14.27293541 12.23644898 ... 11.92340515 12.62055018\n",
      " 12.55491063]\n"
     ]
    }
   ],
   "source": [
    "print(\"Prediction for test set: {}\".format(y_pred2))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 62,
   "id": "f02b695a",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.collections.PathCollection at 0x1cb2f5932d0>"
      ]
     },
     "execution_count": 62,
     "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": [
    "plt.scatter(y_test,y_pred2)\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "22aa382e",
   "metadata": {},
   "source": [
    "# Using XGBoost Regressor"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 63,
   "id": "36f96b67",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<style>#sk-container-id-5 {color: black;}#sk-container-id-5 pre{padding: 0;}#sk-container-id-5 div.sk-toggleable {background-color: white;}#sk-container-id-5 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-5 label.sk-toggleable__label-arrow:before {content: \"▸\";float: left;margin-right: 0.25em;color: #696969;}#sk-container-id-5 label.sk-toggleable__label-arrow:hover:before {color: black;}#sk-container-id-5 div.sk-estimator:hover label.sk-toggleable__label-arrow:before {color: black;}#sk-container-id-5 div.sk-toggleable__content {max-height: 0;max-width: 0;overflow: hidden;text-align: left;background-color: #f0f8ff;}#sk-container-id-5 div.sk-toggleable__content pre {margin: 0.2em;color: black;border-radius: 0.25em;background-color: #f0f8ff;}#sk-container-id-5 input.sk-toggleable__control:checked~div.sk-toggleable__content {max-height: 200px;max-width: 100%;overflow: auto;}#sk-container-id-5 input.sk-toggleable__control:checked~label.sk-toggleable__label-arrow:before {content: \"▾\";}#sk-container-id-5 div.sk-estimator input.sk-toggleable__control:checked~label.sk-toggleable__label {background-color: #d4ebff;}#sk-container-id-5 div.sk-label input.sk-toggleable__control:checked~label.sk-toggleable__label {background-color: #d4ebff;}#sk-container-id-5 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-5 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-5 div.sk-estimator:hover {background-color: #d4ebff;}#sk-container-id-5 div.sk-parallel-item::after {content: \"\";width: 100%;border-bottom: 1px solid gray;flex-grow: 1;}#sk-container-id-5 div.sk-label:hover label.sk-toggleable__label {background-color: #d4ebff;}#sk-container-id-5 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-5 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-5 div.sk-item {position: relative;z-index: 1;}#sk-container-id-5 div.sk-parallel {display: flex;align-items: stretch;justify-content: center;background-color: white;position: relative;}#sk-container-id-5 div.sk-item::before, #sk-container-id-5 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-5 div.sk-parallel-item {display: flex;flex-direction: column;z-index: 1;position: relative;background-color: white;}#sk-container-id-5 div.sk-parallel-item:first-child::after {align-self: flex-end;width: 50%;}#sk-container-id-5 div.sk-parallel-item:last-child::after {align-self: flex-start;width: 50%;}#sk-container-id-5 div.sk-parallel-item:only-child::after {width: 0;}#sk-container-id-5 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-5 div.sk-label label {font-family: monospace;font-weight: bold;display: inline-block;line-height: 1.2em;}#sk-container-id-5 div.sk-label-container {text-align: center;}#sk-container-id-5 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-5 div.sk-text-repr-fallback {display: none;}</style><div id=\"sk-container-id-5\" class=\"sk-top-container\"><div class=\"sk-text-repr-fallback\"><pre>XGBRegressor(base_score=None, booster=None, callbacks=None,\n",
       "             colsample_bylevel=None, colsample_bynode=None,\n",
       "             colsample_bytree=None, device=None, early_stopping_rounds=None,\n",
       "             enable_categorical=False, eval_metric=None, feature_types=None,\n",
       "             gamma=None, grow_policy=None, importance_type=None,\n",
       "             interaction_constraints=None, learning_rate=None, max_bin=None,\n",
       "             max_cat_threshold=None, max_cat_to_onehot=None,\n",
       "             max_delta_step=None, max_depth=None, max_leaves=None,\n",
       "             min_child_weight=None, missing=nan, monotone_constraints=None,\n",
       "             multi_strategy=None, n_estimators=None, n_jobs=None,\n",
       "             num_parallel_tree=None, random_state=None, ...)</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-7\" type=\"checkbox\" checked><label for=\"sk-estimator-id-7\" class=\"sk-toggleable__label sk-toggleable__label-arrow\">XGBRegressor</label><div class=\"sk-toggleable__content\"><pre>XGBRegressor(base_score=None, booster=None, callbacks=None,\n",
       "             colsample_bylevel=None, colsample_bynode=None,\n",
       "             colsample_bytree=None, device=None, early_stopping_rounds=None,\n",
       "             enable_categorical=False, eval_metric=None, feature_types=None,\n",
       "             gamma=None, grow_policy=None, importance_type=None,\n",
       "             interaction_constraints=None, learning_rate=None, max_bin=None,\n",
       "             max_cat_threshold=None, max_cat_to_onehot=None,\n",
       "             max_delta_step=None, max_depth=None, max_leaves=None,\n",
       "             min_child_weight=None, missing=nan, monotone_constraints=None,\n",
       "             multi_strategy=None, n_estimators=None, n_jobs=None,\n",
       "             num_parallel_tree=None, random_state=None, ...)</pre></div></div></div></div></div>"
      ],
      "text/plain": [
       "XGBRegressor(base_score=None, booster=None, callbacks=None,\n",
       "             colsample_bylevel=None, colsample_bynode=None,\n",
       "             colsample_bytree=None, device=None, early_stopping_rounds=None,\n",
       "             enable_categorical=False, eval_metric=None, feature_types=None,\n",
       "             gamma=None, grow_policy=None, importance_type=None,\n",
       "             interaction_constraints=None, learning_rate=None, max_bin=None,\n",
       "             max_cat_threshold=None, max_cat_to_onehot=None,\n",
       "             max_delta_step=None, max_depth=None, max_leaves=None,\n",
       "             min_child_weight=None, missing=nan, monotone_constraints=None,\n",
       "             multi_strategy=None, n_estimators=None, n_jobs=None,\n",
       "             num_parallel_tree=None, random_state=None, ...)"
      ]
     },
     "execution_count": 63,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from xgboost import XGBRegressor\n",
    "model3=  XGBRegressor()\n",
    "model3.fit(x_train,y_train)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 64,
   "id": "52051215",
   "metadata": {},
   "outputs": [],
   "source": [
    "y_pred3= model3.predict(x_test)  \n",
    "x_pred3= model3.predict(x_train)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 65,
   "id": "a3cb228a",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Mean Absolute Error: 0.3320489622222549\n",
      "Mean Square Error: 0.20415125624172975\n",
      "Root Mean Square Error: 0.4518310040731266\n"
     ]
    }
   ],
   "source": [
    "mae = metrics.mean_absolute_error(y_test, y_pred3)\n",
    "mse = metrics.mean_squared_error(y_test, y_pred3)\n",
    "r2 = np.sqrt(metrics.mean_squared_error(y_test, y_pred3))\n",
    "\n",
    "print('Mean Absolute Error:', mae)\n",
    "print('Mean Square Error:', mse)\n",
    "print('Root Mean Square Error:', r2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 66,
   "id": "9281f512",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.8678628928407979"
      ]
     },
     "execution_count": 66,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "r2_score(y_train, x_pred3)"
   ]
  }
 ],
 "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": "3.11.7"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}