Car-Resale-Value.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Car Resale Value Prediction Model"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The dataset has been taken from Kaggle. This dataset contains Car resale prices all over the cities from India"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Data Description"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "- **full_name**: Name of the car along with model\n",
    "- **resale_price**: Resale price of the car (in Rs)\n",
    "- **registered_year**: Year the car was registered\n",
    "- **engine_capacity**: Engine Displacement of car (cc)\n",
    "- **insurance**: Type of insurance made available for the car (if any)\n",
    "- **transmission_type**: Transmission type of the car\n",
    "- **kms_driven**: Total kilometers the car was driven for\n",
    "- **owner_type**: Number of owners who previously owned the car\n",
    "- **fuel_type**: Type of fuel the car uses\n",
    "- **max_power**: Maximum power of the car (bhp)\n",
    "- **seats**: Number of seats the car has\n",
    "- **mileage**: Mileage of the car(kmpl)\n",
    "- **body_type**: Body configuration of the car\n",
    "- **city**: City in India the car is sold in"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Import Required Libraries"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import pandas as pd\n",
    "import seaborn as sns\n",
    "import matplotlib.pyplot as plt\n",
    "\n",
    "from sklearn.model_selection import train_test_split\n",
    "\n",
    "from sklearn.linear_model import LinearRegression\n",
    "from sklearn.ensemble import RandomForestRegressor\n",
    "import xgboost as xgb\n",
    "\n",
    "from sklearn.model_selection import cross_val_score\n",
    "\n",
    "import pickle\n",
    "\n",
    "import warnings\n",
    "warnings.filterwarnings('ignore')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Loading Data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "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>full_name</th>\n",
       "      <th>resale_price</th>\n",
       "      <th>registered_year</th>\n",
       "      <th>engine_capacity</th>\n",
       "      <th>insurance</th>\n",
       "      <th>transmission_type</th>\n",
       "      <th>kms_driven</th>\n",
       "      <th>owner_type</th>\n",
       "      <th>fuel_type</th>\n",
       "      <th>max_power</th>\n",
       "      <th>seats</th>\n",
       "      <th>mileage</th>\n",
       "      <th>body_type</th>\n",
       "      <th>city</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2017 Maruti Baleno 1.2 Alpha</td>\n",
       "      <td>₹ 5.45 Lakh</td>\n",
       "      <td>2017</td>\n",
       "      <td>1197 cc</td>\n",
       "      <td>Third Party insurance</td>\n",
       "      <td>Manual</td>\n",
       "      <td>40,000 Kms</td>\n",
       "      <td>First Owner</td>\n",
       "      <td>Petrol</td>\n",
       "      <td>83.1bhp</td>\n",
       "      <td>5.0</td>\n",
       "      <td>21.4 kmpl</td>\n",
       "      <td>Hatchback</td>\n",
       "      <td>Agra</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2018 Tata Hexa XTA</td>\n",
       "      <td>₹ 10 Lakh</td>\n",
       "      <td>2018</td>\n",
       "      <td>2179 cc</td>\n",
       "      <td>Third Party insurance</td>\n",
       "      <td>Automatic</td>\n",
       "      <td>70,000 Kms</td>\n",
       "      <td>First Owner</td>\n",
       "      <td>Diesel</td>\n",
       "      <td>153.86bhp</td>\n",
       "      <td>7.0</td>\n",
       "      <td>17.6 kmpl</td>\n",
       "      <td>MUV</td>\n",
       "      <td>Agra</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2015 Maruti Swift Dzire VXI</td>\n",
       "      <td>₹ 4.50 Lakh</td>\n",
       "      <td>2015</td>\n",
       "      <td>1197 cc</td>\n",
       "      <td>Third Party insurance</td>\n",
       "      <td>Manual</td>\n",
       "      <td>70,000 Kms</td>\n",
       "      <td>Second Owner</td>\n",
       "      <td>Petrol</td>\n",
       "      <td>83.14bhp</td>\n",
       "      <td>5.0</td>\n",
       "      <td>20.85 kmpl</td>\n",
       "      <td>Sedan</td>\n",
       "      <td>Agra</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2015 Maruti Swift Dzire VXI</td>\n",
       "      <td>₹ 4.50 Lakh</td>\n",
       "      <td>2015</td>\n",
       "      <td>1197 cc</td>\n",
       "      <td>Third Party insurance</td>\n",
       "      <td>Manual</td>\n",
       "      <td>70,000 Kms</td>\n",
       "      <td>Second Owner</td>\n",
       "      <td>Petrol</td>\n",
       "      <td>83.14bhp</td>\n",
       "      <td>5.0</td>\n",
       "      <td>20.85 kmpl</td>\n",
       "      <td>Sedan</td>\n",
       "      <td>Agra</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2009 Hyundai i10 Magna 1.1</td>\n",
       "      <td>₹ 1.60 Lakh</td>\n",
       "      <td>2009</td>\n",
       "      <td>1086 cc</td>\n",
       "      <td>Third Party insurance</td>\n",
       "      <td>Manual</td>\n",
       "      <td>80,000 Kms</td>\n",
       "      <td>First Owner</td>\n",
       "      <td>Petrol</td>\n",
       "      <td>68.05bhp</td>\n",
       "      <td>5.0</td>\n",
       "      <td>19.81 kmpl</td>\n",
       "      <td>Hatchback</td>\n",
       "      <td>Agra</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                      full_name resale_price registered_year engine_capacity  \\\n",
       "0  2017 Maruti Baleno 1.2 Alpha  ₹ 5.45 Lakh            2017         1197 cc   \n",
       "1            2018 Tata Hexa XTA    ₹ 10 Lakh            2018         2179 cc   \n",
       "2   2015 Maruti Swift Dzire VXI  ₹ 4.50 Lakh            2015         1197 cc   \n",
       "3   2015 Maruti Swift Dzire VXI  ₹ 4.50 Lakh            2015         1197 cc   \n",
       "4    2009 Hyundai i10 Magna 1.1  ₹ 1.60 Lakh            2009         1086 cc   \n",
       "\n",
       "               insurance transmission_type  kms_driven    owner_type  \\\n",
       "0  Third Party insurance            Manual  40,000 Kms   First Owner   \n",
       "1  Third Party insurance         Automatic  70,000 Kms   First Owner   \n",
       "2  Third Party insurance            Manual  70,000 Kms  Second Owner   \n",
       "3  Third Party insurance            Manual  70,000 Kms  Second Owner   \n",
       "4  Third Party insurance            Manual  80,000 Kms   First Owner   \n",
       "\n",
       "  fuel_type  max_power  seats     mileage  body_type  city  \n",
       "0    Petrol    83.1bhp    5.0   21.4 kmpl  Hatchback  Agra  \n",
       "1    Diesel  153.86bhp    7.0   17.6 kmpl        MUV  Agra  \n",
       "2    Petrol   83.14bhp    5.0  20.85 kmpl      Sedan  Agra  \n",
       "3    Petrol   83.14bhp    5.0  20.85 kmpl      Sedan  Agra  \n",
       "4    Petrol   68.05bhp    5.0  19.81 kmpl  Hatchback  Agra  "
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df = pd.read_csv('car_resale_prices.csv' , index_col=0)\n",
    "df.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Shape of Dataframe"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(17446, 14)"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.shape"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Null Values"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "full_name              0\n",
       "resale_price           0\n",
       "registered_year       69\n",
       "engine_capacity       14\n",
       "insurance              7\n",
       "transmission_type      0\n",
       "kms_driven             3\n",
       "owner_type            45\n",
       "fuel_type              0\n",
       "max_power            102\n",
       "seats                 10\n",
       "mileage              508\n",
       "body_type              0\n",
       "city                   0\n",
       "dtype: int64"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.isnull().sum()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Description of Dataframe"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Index: 17446 entries, 0 to 17445\n",
      "Data columns (total 14 columns):\n",
      " #   Column             Non-Null Count  Dtype  \n",
      "---  ------             --------------  -----  \n",
      " 0   full_name          17446 non-null  object \n",
      " 1   resale_price       17446 non-null  object \n",
      " 2   registered_year    17377 non-null  object \n",
      " 3   engine_capacity    17432 non-null  object \n",
      " 4   insurance          17439 non-null  object \n",
      " 5   transmission_type  17446 non-null  object \n",
      " 6   kms_driven         17443 non-null  object \n",
      " 7   owner_type         17401 non-null  object \n",
      " 8   fuel_type          17446 non-null  object \n",
      " 9   max_power          17344 non-null  object \n",
      " 10  seats              17436 non-null  float64\n",
      " 11  mileage            16938 non-null  object \n",
      " 12  body_type          17446 non-null  object \n",
      " 13  city               17446 non-null  object \n",
      "dtypes: float64(1), object(13)\n",
      "memory usage: 2.0+ MB\n"
     ]
    }
   ],
   "source": [
    "df.info()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## EDA"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Data Cleaning "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Converting resale_price, engine_capacity, kms_driven, max_power and mileage into float datatype"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "df['resale_price'] = df['resale_price'].str.replace('₹ ', '').str.replace(',', '')\n",
    "\n",
    "def convert_price(value):\n",
    "    if 'Lakh' in value:\n",
    "        value = value.replace(' Lakh', '')\n",
    "        return float(value) * 100000  \n",
    "    elif 'Crore' in value:\n",
    "        value = value.replace(' Crore', '')\n",
    "        return float(value) * 10000000  \n",
    "    else:\n",
    "        return float(value)\n",
    "\n",
    "df['resale_price'] = df['resale_price'].apply(convert_price)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "df['engine_capacity'] = df['engine_capacity'].str.replace(' cc', '').astype(float)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [],
   "source": [
    "df['kms_driven'] = df['kms_driven'].str.replace(',','').str.replace(' Kms', '').astype(float)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [],
   "source": [
    "df = df[~df['max_power'].str.contains('at', case=False, na=False)]\n",
    "\n",
    "df['max_power'] = df['max_power'].str.extract(r'(\\d+\\.?\\d*)', expand=False).astype(float)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [],
   "source": [
    "df = df[~df['mileage'].str.contains(' km/kg', case=False, na=False)]\n",
    "df['mileage'] = df['mileage'].str.replace('kmpl', '').astype(float)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "body_type\n",
       "Hatchback        7121\n",
       "Sedan            4663\n",
       "SUV              4397\n",
       "MUV               727\n",
       "Minivans           47\n",
       "Maruti             15\n",
       "Pickup             13\n",
       "Coupe              10\n",
       "Tata                7\n",
       "Mercedes-Benz       6\n",
       "Jaguar              3\n",
       "Wagon               3\n",
       "Chevrolet           3\n",
       "Mahindra            3\n",
       "Convertibles        2\n",
       "Toyota              2\n",
       "Cars                2\n",
       "BMW                 2\n",
       "Honda               2\n",
       "Datsun              2\n",
       "Audi                1\n",
       "Porsche             1\n",
       "Volvo               1\n",
       "Hyundai             1\n",
       "Skoda               1\n",
       "Isuzu               1\n",
       "Name: count, dtype: int64"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df['body_type'].value_counts()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Body type contains unnecessary values like(cars,Honada,Maruti etc.) so we will drop them."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array(['Hatchback', 'MUV', 'Sedan', 'Minivans', 'SUV', 'Coupe', 'Pickup',\n",
       "       'Convertibles', 'Wagon'], dtype=object)"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df = df[~df['body_type'].isin(['Maruti', 'Tata','Mercedes-Benz','Chevrolet','Mahindra','Jaguar','BMW','Honda','Toyota','Cars','Datsun','Skoda','Audi','Hyundai','Volvo','Porsche','Isuzu'])]\n",
    "df['body_type'].unique()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array(['Third Party', 'Comprehensive', 'Zero Dep', 'Not Available', nan],\n",
       "      dtype=object)"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df = df[~df['insurance'].isin(['1','2'])]\n",
    "df['insurance'] = df['insurance'].str.replace('Third Party insurance', 'Third Party')\n",
    "df['insurance'].unique()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "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>resale_price</th>\n",
       "      <th>registered_year</th>\n",
       "      <th>engine_capacity</th>\n",
       "      <th>insurance</th>\n",
       "      <th>transmission_type</th>\n",
       "      <th>kms_driven</th>\n",
       "      <th>owner_type</th>\n",
       "      <th>fuel_type</th>\n",
       "      <th>max_power</th>\n",
       "      <th>seats</th>\n",
       "      <th>mileage</th>\n",
       "      <th>body_type</th>\n",
       "      <th>city</th>\n",
       "      <th>Company</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>16309</th>\n",
       "      <td>11200000.0</td>\n",
       "      <td>2020</td>\n",
       "      <td>2925.0</td>\n",
       "      <td>Comprehensive</td>\n",
       "      <td>Automatic</td>\n",
       "      <td>33000.0</td>\n",
       "      <td>First Owner</td>\n",
       "      <td>Diesel</td>\n",
       "      <td>325.86</td>\n",
       "      <td>7.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>SUV</td>\n",
       "      <td>Bangalore</td>\n",
       "      <td>Mercedes-Benz</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2259</th>\n",
       "      <td>1425000.0</td>\n",
       "      <td>2019</td>\n",
       "      <td>1353.0</td>\n",
       "      <td>Comprehensive</td>\n",
       "      <td>Manual</td>\n",
       "      <td>16858.0</td>\n",
       "      <td>First Owner</td>\n",
       "      <td>Petrol</td>\n",
       "      <td>138.08</td>\n",
       "      <td>5.0</td>\n",
       "      <td>16.50</td>\n",
       "      <td>SUV</td>\n",
       "      <td>Jaipur</td>\n",
       "      <td>Kia</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2222</th>\n",
       "      <td>575000.0</td>\n",
       "      <td>2017</td>\n",
       "      <td>1396.0</td>\n",
       "      <td>Comprehensive</td>\n",
       "      <td>Manual</td>\n",
       "      <td>81000.0</td>\n",
       "      <td>First Owner</td>\n",
       "      <td>Diesel</td>\n",
       "      <td>88.73</td>\n",
       "      <td>5.0</td>\n",
       "      <td>22.54</td>\n",
       "      <td>Hatchback</td>\n",
       "      <td>Jaipur</td>\n",
       "      <td>Hyundai</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5847</th>\n",
       "      <td>640000.0</td>\n",
       "      <td>2019</td>\n",
       "      <td>1199.0</td>\n",
       "      <td>Comprehensive</td>\n",
       "      <td>Manual</td>\n",
       "      <td>22421.0</td>\n",
       "      <td>First Owner</td>\n",
       "      <td>Petrol</td>\n",
       "      <td>88.76</td>\n",
       "      <td>5.0</td>\n",
       "      <td>19.50</td>\n",
       "      <td>Sedan</td>\n",
       "      <td>Chennai</td>\n",
       "      <td>Honda</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4572</th>\n",
       "      <td>784000.0</td>\n",
       "      <td>2019</td>\n",
       "      <td>1462.0</td>\n",
       "      <td>Third Party</td>\n",
       "      <td>Automatic</td>\n",
       "      <td>57033.0</td>\n",
       "      <td>First Owner</td>\n",
       "      <td>Petrol</td>\n",
       "      <td>103.25</td>\n",
       "      <td>5.0</td>\n",
       "      <td>20.28</td>\n",
       "      <td>Sedan</td>\n",
       "      <td>Ahmedabad</td>\n",
       "      <td>Maruti</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "       resale_price  registered_year  engine_capacity      insurance  \\\n",
       "16309    11200000.0             2020           2925.0  Comprehensive   \n",
       "2259      1425000.0             2019           1353.0  Comprehensive   \n",
       "2222       575000.0             2017           1396.0  Comprehensive   \n",
       "5847       640000.0             2019           1199.0  Comprehensive   \n",
       "4572       784000.0             2019           1462.0    Third Party   \n",
       "\n",
       "      transmission_type  kms_driven   owner_type fuel_type  max_power  seats  \\\n",
       "16309         Automatic     33000.0  First Owner    Diesel     325.86    7.0   \n",
       "2259             Manual     16858.0  First Owner    Petrol     138.08    5.0   \n",
       "2222             Manual     81000.0  First Owner    Diesel      88.73    5.0   \n",
       "5847             Manual     22421.0  First Owner    Petrol      88.76    5.0   \n",
       "4572          Automatic     57033.0  First Owner    Petrol     103.25    5.0   \n",
       "\n",
       "       mileage  body_type       city        Company  \n",
       "16309      NaN        SUV  Bangalore  Mercedes-Benz  \n",
       "2259     16.50        SUV     Jaipur            Kia  \n",
       "2222     22.54  Hatchback     Jaipur        Hyundai  \n",
       "5847     19.50      Sedan    Chennai          Honda  \n",
       "4572     20.28      Sedan  Ahmedabad         Maruti  "
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df[\"Company\"] = df[\"full_name\"].apply(lambda x : x.split()[1])\n",
    "df[\"registered_year\"] = df[\"full_name\"].apply(lambda x : x.split()[0]).astype(int)\n",
    "df = df.drop('full_name',axis = 1)\n",
    "df.sample(5)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Handle Missing Values"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "resale_price           0\n",
       "registered_year        0\n",
       "engine_capacity       14\n",
       "insurance            630\n",
       "transmission_type      0\n",
       "kms_driven             3\n",
       "owner_type            43\n",
       "fuel_type              0\n",
       "max_power            101\n",
       "seats                 10\n",
       "mileage              499\n",
       "body_type              0\n",
       "city                   0\n",
       "Company                0\n",
       "dtype: int64"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.replace(\"Not Available\", np.nan, inplace=True)\n",
    "df.isnull().sum()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [],
   "source": [
    "df['kms_driven'].fillna(df['kms_driven'].median(), inplace=True)\n",
    "df['engine_capacity'].fillna(df['engine_capacity'].median(), inplace=True)\n",
    "df['max_power'].fillna(df['max_power'].mean(), inplace=True)\n",
    "df.dropna(subset=['insurance','seats','mileage','owner_type'], inplace=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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vE1y9ehXFixfPcjwtLQ0pKSlaD2/Dy8sL77zzDho2bIgCBQogZ86cNg+jXLt2DVu3bsXWrVthb2+PJk2a4OTJkyhdujRmzJihSwYzvU9FixbF8ePHsxzfvHkzSpUqpWsWAEhOTsabb76p+7jZefvtt7F06VLrvy0WC9LS0jB16lTUrl1b1yzOzs64d+9eluNRUVHInTu3rlkAoH379rh48SIGDRqE6tWro2LFiggODrb+r566d++Odu3aoWzZsrBYLKhXrx4A4ODBgyhZsqSuWQBz/XwDwMWLF7N9T5ydnZGYmKh7ngxm+Cw2LIsmFSOTSpUqybJly0TEtgF+8cUX8tZbb2k9vGklJyfLqlWrpGnTpuLo6CiVK1eW7777Tu7evWt9zZo1a3Rr7WZ6n+bPny9+fn7y888/i7u7u6xYsULGjx9v/W+9ffzxxzJ27Fjdx83OyZMnJU+ePNKoUSNxcnKSd999V0qVKiV58+a1/pWul5CQEGnVqpUkJydLjhw5JDo6Wi5duiTBwcHW0+J6iomJeeZDbytXrpTp06dbLxeIiCxevNiQSxlm+vkWST8zkPF1yJxn9uzZEhwcrGsWM30WG5lF8zKwbt06yZkzp0yePFnc3Nzkyy+/lJ49e4qTk5Ns2bJF6+FNy8fHR7y9vaVfv35y7NixbF9z584d8ff31yWP2d6n5cuXS/HixcVisYjFYhE/Pz9ZsGCB7jlERAYNGiReXl5So0YNGTBggISGhto89BYfHy/jx4+Xtm3bSuPGjWXEiBHy999/G5KjXr164uXlJfb29lKoUCFxdHSUGjVqSEJCgu55zGTJkiXy8OHDLMcfPXokS5Ys0T2P2X6+zVT4zfRZbGQWzcuAiMiePXukXr16kjt3bnF1dZXq1atLWFiYHkNnsXLlSmnbtq28/vrrEhwcbPPQ09KlS+XBgwe6jvk8ZnqfMiQmJsr169cNzVCrVq2nPmrXrm1oNjPYu3evfPPNNzJlyhTZunWroVmWLl0qb775puTPn996NmDGjBm6/zVuZ2eX7fftP//8I3Z2drpmyWC2n2+zFH4zfRYbmUWXMmAWs2bNkhw5csiAAQPEyclJ+vTpI/Xq1ZOcOXPKZ599pmuW7t27y71797IcT0hIkO7du+uaxayuX78ue/bskT179siNGzeMjmMat2/fli+//FJ69OghPXr0kK+++kpu3bpldCzDmWmGusViyfZ79vjx4+Lt7a1rFrMzuvDzszid5mXg0KFDcuDAgSzHDxw4IIcPH9Z6eBtBQUHy008/iYjtdaqRI0dK//79dc3ytL8cbt68Kfb29rpmETHX+3Tv3j3p3Lmz2NvbW/9qcHBwkE6dOkl8fLyuWTI7d+6cbN68WZKSkkREJC0tTfcMu3fvFk9PTylUqJD1LpjChQuLp6en7N69W/c827Ztk6ZNm0pAQIAEBARI06ZNDTs7YIYZ6hUrVpTg4GCxs7OTcuXK2Zx5LF++vHh4eEjbtm11yfIyMEPhN9NncUJCgnz++efyxhtvSLFixaRo0aI2Dy05/PdTEm31798fH3/8MV5//XWb41evXsWUKVNw8OBBrSNYxcbGWmeFu7q64v79+wCA999/H9WqVcPXX3+teYZ79+5B0ksY7t+/DxcXF+tzqamp2LRpE/LkyaN5jieZ6X3q2bMnjh07ho0bN+KNN94AAPzxxx8YPHgw+vTpg59//lm3LED6qn/t2rXDzp07YbFYcO7cOQQEBCAkJATe3t6YNm2abln69++P9957D9999x3s7e0BpH/f9OvXD/3798fJkyd1y/Ltt99i8ODBePfddzF48GAAwIEDB9CkSRPMmDED/fv31y0LYI4Z6q1atQIAHD9+HA0bNkSOHDmszzk5OcHf3x/vvPOOLlky8/b2hsViyXLcYrHAxcUFxYsXR7du3dC9e3dd8ty/fx/9+vXDihUrkJaWBgCwt7fHe++9h2+++UaXu7vM+Fncs2dP7N69G++//z7y58+f7XumGU2rhoi4u7tbG3pm0dHRkiNHDq2Ht1G0aFE5evSoiIhUrlxZ5s6dKyIiYWFhup26s1gsYmdn99SHvb29jB8/XpcsmZnpfXJzc5O9e/dmOb5nzx5xc3PTNYuIyPvvvy8NGzaUy5cv2/zFuXnzZildurSuWVxcXOTMmTNZjp85c0b3NRj8/Pxkzpw5WY5//fXXUqBAAV2ziJhrhvrixYtNcx1aRGT69Oni4+MjnTt3ltmzZ8vs2bOlc+fO4uvrKxMmTJCePXuKs7OzfP/997rkadeunQQGBsrmzZvl7t27cvfuXdm8ebMEBQXJe++9p0sGM34W58yZU/bt26frmBk0PzPg7OyM69evIyAgwOb4tWvX4OCg+fA26tSpg99++w3BwcHo3r07QkNDsWrVKhw5cgRt2rTRJcPOnTshIqhTpw5Wr16NXLlyWZ9zcnJCkSJFUKBAAV2yZGam98nHxyfbvwxy5swJb29vXbMAwJYtWxAWFoaCBQvaHA8MDLQuo6qXSpUq4fTp0wgKCrI5fvr0aevyt3qJj49Ho0aNshxv0KABhg8frmsWABgyZAj69++Phw8fQkRw6NAhrFixApMmTcKCBQt0zdK1a1ddx3ueffv2Yfz48ejbt6/N8Xnz5mHLli1YvXo1ypcvj9mzZ6NXr16a59mwYQPCwsLw1ltvWY81bNgQ8+fPz/Z7Sgtm/Cz29va2yaErrdtG+/btpWbNmjbXeu/cuSM1a9bU/dpZamqqzVLEK1askIEDB8rs2bPl0aNHumaJiYkx5Jrz05jpfZo3b57Uq1dPrl27Zj127do1adCggfVsjp7MtOrfzz//LIULF5Yvv/xS9u7dK3v37pUvv/xS/P395eeff9Z1xb0OHTrI1KlTsxz/8ssvdfvr7klmmaH++PFj+fLLL6Vq1aqSN29e8fb2tnnozd3dXc6dO5fl+Llz56zLWJ8/f163M2+FChWSyMjILMdPnDghfn5+umTIYKbP4mXLlsm7774riYmJuo9tEdF279OrV6+iRo0auHXrlvV63vHjx5E3b15s3boVhQoV0nJ4U4mMjETZsmVhZ2eHyMjIZ762fPnyOqVKZ6b3KTg4GOfPn8ejR49QuHBhAOnzPZydnREYGGjz2qNHj2qep0mTJqhcuTLGjRsHDw8PREZGokiRImjfvj3S0tKwatUqzTNksLN79qKhFosFIgKLxWLd4Ekr48ePx1dffYXq1atb53YcOHAA4eHhGDp0KDw9Pa2vHTRokKZZnpSUlISEhARD5t8AwKhRo7BgwQIMHToUn3/+OUaMGIGYmBisW7cOo0aN0v3rUbhwYYSGhiI0NNTm+IwZMzBjxgzExsYiMjISDRo0QFxcnOZ5vv/+e6xcuRLLli1Dvnz5AABxcXHo2rUr2rRpgz59+mg6vlk/i4ODg3HhwgWICPz9/eHo6GjzvJafd5qXAQBITEzEjz/+iBMnTsDV1RXly5dHhw4dsvwf1cPevXsxb948XLhwAatWrYKfnx+WLVuGokWL2pyy0oKdnR3i4uKQJ08e2NnZWT+4n6THB3l2zPI+ffHFFy/82tGjR2uYJN2ff/6JunXrolKlStixYwdatGiBU6dO4fbt2wgPD0exYsU0z5Dh31yWKFKkiIZJ0peNfhEWi8W6S56WFi1ahNq1a79wLi0VK1YMs2fPRtOmTeHh4YHjx49bjx04cAA//fSTrnnmz5+PDz74AE2aNMFrr70GADh8+DA2bdqEuXPnIiQkBNOmTcOhQ4fwyy+/aJ7H6MJv1s/i5332afl5p0sZMIvVq1fj/fffR6dOnbBs2TL89ddfCAgIwNdff41NmzZh06ZNmo5/6dIlFC5cGBaL5bkf6lp/kNO/c/fuXXz99dc4ceIEEhISUKlSJfTv3x/58+fXNUdiYiLc3d11HfNlERgYiOjoaPj5+aFmzZqoWbMmatWqle2a/Fpzd3fH6dOnUbhwYeTPnx8bN25EpUqVEB0djeDgYNy9e1f3TOHh4fj6669x9uxZAEBQUBAGDhxoyL4bRhd+fhZnpUkZ+O2339C4cWM4Ojrit99+e+ZrW7Ro8V8P/1TBwcEIDQ1Fly5d4OHhgRMnTiAgIADHjh1D48aNdTk9Zmbnzp3Dzp07cePGDevtPhlGjRqlW46uXbsiJCQENWrU0G3Ml0WOHDnQrl079OjRQ/MzWc+zc+dO3TdHep6rV69i165d2LNnD3bv3o1z584hf/78qFWrFpYvX65bjqCgICxduhSvv/463nrrLTRr1gyffPIJfvnlFwwcOBA3btzQLQs926RJk5A3b1706NHD5viiRYtw8+ZNQybDGkKTiQgWi3URh4yJPNk99F6W09XVVS5evCgiWfeC13vL1YkTJ8rChQuzHF+4cKFMnjxZ1ywiIt9//73Y29tL3rx5pUKFClKxYkXrQ+/bslq2bCmOjo5SvHhxmTBhgly5ckXX8Z9UrFgxGT16tGHbmGa2du1a69cnMDBQJk2aJFevXjUki5OTkwQEBMi4ceMkNjbWkAxPk5iYKJs3b5auXbuKg4OD7ovHDB8+XCZMmCAi6ZM+HRwcpHjx4uLk5CTDhw/XNcuTHjx4YL2dL+Ohty5duhiySFZ2ihQpIuHh4VmOHzhwQLe9YTIYOfFUqeWIixYtal0dLXMZWLJkiZQqVUrXLGb6BhRJ33/diBLyNDdu3JBp06ZJ+fLlxcHBQRo1aiQrV66U5ORk3bNMnz5dqlSpIhaLRapUqSIzZ860udPBCBlfn3LlyomDg4M0bdpUVq9ebXO3jNZu3rwp06dPlwoVKoiDg4M0aNBAfvnlF93vzMkQFhYmn376qbzxxhvi4uIiwcHB8uGHH8q6devk9u3bhmTKsH//fpk2bZr89ttvhoyfmJgo/fv3l9y5c2d7T73ezFT4nZ2dJTo6OstxI/5IHDlypOTPn1+++uorcXFxkXHjxklISIj4+PjIrFmzNB1b0zKQnJwsderUMcVfVCLpf42XLl1aDhw4IB4eHrJ3715Zvny55M6dW2bPnq1rFjN9A4qIeHh4ZLvokBlERETIgAEDxMXFRXx9feXDDz805Hvq7NmzMmrUKAkMDBQHBwepX7++ITvQPWn27Nni7OwsFotFcufOLSNHjtT91qSM98jHx0d8fHxk4MCBcvz4cV0zWCwWyZMnj0yZMkXu3Lmj69hm169fPylVqpSsWrVKXF1dZdGiRTJu3DgpWLCgLF++3JBMZin8xYsXt27vnNnSpUs1XwL4SQEBAbJhwwYRSf+DNWNb8lmzZkmHDh00HVvzMwO+vr6mKQNpaWnWbTIzLlW4uLjI559/rnsWM30Dioj06NFDvvvuO93HfZ6///5bJk+eLEFBQeLu7i5dunSRunXrioODg0yfPt2wXH/88YdUrFjRsB3o4uLiZMqUKVKqVClxc3OTTp06yY4dO2Tp0qVSpkwZqV+/vu6Zrl69KqNHjxZnZ2dxd3cXe3t7eeutt+TPP//UZfwZM2ZI69atxcfHRwoUKCAdOnSQefPmydmzZ3UZ/0lm2UFRJP2+/p07d4pIevHPWHNg6dKl0rhxY93zPMnIwj9lyhTx8fGRRYsWSUxMjMTExMjChQvFx8dHJk6cqEuGDG5ubnLp0iUREcmXL59ERESISPofiZ6enpqOrXkZ+PDDDw2/RvakR48eyalTp+TgwYNy//59QzKY6RtQJP2sia+vr3Tt2lW++uormTVrls1DT8nJybJq1Spp2rSpODo6SuXKleW7776zuba5Zs0a8fLy0jWXiMjBgwdl8ODBki9fPnFzc9N9cZ3Vq1dLs2bNxNHRUSpUqCBz5szJ8lfw+fPnxdHRUZc8ycnJsnLlSmncuLE4ODhItWrVZP78+ZKQkCAXL16UTp066X4JTkQkMjJS5syZI61btxZHR0fdF7Ix0w6KIumLDmX8kvHz85ODBw+KSPpy4xmLDhnF6MKflpYmH3/8sbi4uFgvm7i5uckXX3yh+dhPKlGihHXDuOrVq8ukSZNEJH3eSe7cuTUdW/MyMGDAAPH09JTKlStL7969JTQ01Oahp0WLFll3nDOamb4BRUT8/f2f+tD7TIWPj494e3tLv3795NixY9m+5s6dO7rNrXjy8kCDBg1kyZIlhhRJT09P6d27txw6dOipr0lKSpIxY8ZoniXjskCuXLlk8ODBcvLkySyvuXbtmlgsFs2zZEhLS5OIiAiZNm2aNGvWTLy8vMTe3l4qVqyoWwYRc+ygmFm5cuVk165dIiJSt25dGTp0qIikn37WuyiJmLPw379/Xw4dOiQnT56Uhw8f6jZuZkZOPNV8nYFn3XpksViwY8cOLYe3kTdvXjx48ABt27ZFSEiIIffXPikhIQGnT5+Gq6srAgMD4ezsbHQkwy1btgxt27a12UXMSHZ2dqhatSo6duyI9u3bI2/evIZlSUpKgpubm2HjZ1a3bl307NkTbdq0eer37ePHjxEeHo6aNWtqnqd58+YIDw/HvXv3UKFCBdSqVQs1a9ZEjRo14OXlpfn4mbm6uuLMmTMoUqSIzW3M586dQ/ny5fHgwQNd88yYMQP29vYYNGgQtm3bhubNm0NEkJKSgunTp1t3ndSLr68v0tLS0KFDB/Tq1QsVK1bM8pr4+HgEBwfj4sWLumYzkz/++AN//PEHAgMD0bx5c20H07RqmExKSoqsWbNGWrRoIY6OjhIUFCSTJ082fGY42erevbvcu3cvy/GEhATp3r277nnMMudF5Ol7r//zzz+6z1/YvXt3tncvpKSkGHLb2EcffSS///67zf4aRjHTDorZiYmJkdWrV+uyh0V2li5daqpdHUmHMwOZXb58GQBMsR/B9evXsXz5cixZsgRnzpxBo0aNEBISgubNmz93/ff/ypEjR/Drr78iNjYWycnJNs+tWbNGlwyZXblyBb/99lu2eaZPn65bDnt7e1y7di3LuvL//PMP8uXLh8ePH+uWxWwyL6Oa2d9//41ixYrp+hfn096nW7duIU+ePIYsqW0WCxYswJgxYzBt2jSEhIRgwYIFuHDhgnUHxfbt2xuW7eHDh4afdevRowdmzZoFDw8Pm+OJiYkYOHAgFi1aZFAy4509exZz5szB6dOnAQClSpXCwIEDs+xU+p/Tum2kpKTI559/Lp6entZr456enjJixAhD7hnP7MCBA9K7d29xdnYWf39/yZkzp/j7+1tn3WppxYoV4ujoKM2aNRMnJydp1qyZlChRQnLmzCndunXTfPwnbdu2Tdzc3KRs2bLi4OAgFStWFC8vL8mZM6fUrl1blwx3796V+Ph4sVgscv78eZtFUW7fvi1LliyR/Pnz65LF29tbbt68KSIiXl5eWRb/0HsHuoyJnHZ2djJhwgSbyZ3Tp0+XVq1a6X5d3GKxyI0bN7IcP3v2rHh4eOiaJcOuXbukWbNmUqxYMSlWrJg0b95c9uzZY0iWJ3dQLFiwoCE7KIqkL2YzduxYKVCggNjb21vPVHz++eeGZHraGa6bN2/qvkCUmaxatco6ETdjXt0bb7whDg4OsmrVKk3H1nyj+oEDB2LNmjWYOnWqdWezP/74A2PGjMGtW7fw3XffaR3BxvXr17Fs2TL88MMPiI6ORqtWrbBhwwbUq1cPiYmJGDt2LLp27ar5PvUTJ07EjBkz0L9/f3h4eGDWrFkoWrQo+vTpo/t69wDw6aef4qOPPsIXX3wBDw8PrF69Gnny5EGnTp1021/cy8sLFosFFosFJUqUyPK8xWL5V2ua/7+YMWOG9a+WmTNn6jLms8yYMQMAICKYO3cu7O3trc85OTnB398fc+fO1SVLmzZtAKS/H926dbOZL5CamorIyEhD5uMsX74c3bt3R5s2bay7AoaHh6Nu3bpYvHgxOnbsqFuWBw8eoHXr1ujUqROSkpLw559/Ijw8HAULFtQtQ2YTJkzAkiVLMHXqVPTq1ct6vGzZspg5cyZCQkJ0yXHv3j1I+sR13L9/3+YMRWpqKjZt2mTYTpNm8PHHH+PTTz/F2LFjbY6PHj0aH3/8Md555x3tBte0akj67OdNmzZlOb5x40bN75t8UsYtWWXKlJEZM2bIrVu3srzm+vXrusx+dnNzsy6NnCtXLuve3n/99Zfky5dP8/GflHmBCy8vL+u94cePH5ciRYrokmHXrl2yc+dOsVgssmbNGtm1a5f1sX//fkOW3U1JSZElS5ZIXFyc7mNnp1atWoavptetWzfp1q2bWCwWee+996z/7tatm/Tu3VsmTpxoPauip5IlS2Z7K9q0adOkZMmSumapX7++dd2OO3fuSN68eaVgwYLi4uIi3377ra5ZRNKX1N62bZuI2M5hOH36tK4z9jOWoX/aw97eXsaPH69bHrNxdXW1rgGRWVRUlLi6umo6tuZnBpydneHv75/leNGiReHk5KT18Dby5MmD3bt3W89QZCd37ty6zF719vbG/fv3AQB+fn74888/Ua5cOcTHxyMpKUnz8Z/k7u5unSeQP39+XLhwAWXKlAGQfq1eDxkzzi9evGjdUexZ+vXrh7Fjx8LX11ezTA4ODujbt6/1+p3Rdu7c+UKv8/T0xPHjxxEQEPCfZ/jhhx8AAP7+/vjoo4+eu4tieHg4qlSpovmdMtHR0dnOuG7RogU+++wzTcd+0tGjR61nc1atWoW8efPi2LFjWL16NUaNGoUPPvhA1zxXr17NdvfGtLQ0pKSk6JZj586dEBHUqVMHq1evRq5cuazPOTk5oUiRIihQoIBuecymVq1a2Lt3b5b3at++fXj77bc1HVvzMjBgwACMGzcOP/zwg/XD4NGjR5gwYQIGDBig9fA2Fi5c+NzXWCwWNGvWDJs2bdJ0omONGjWwdetWlCtXDm3btsXgwYOxY8cObN26FXXr1tVs3KepVq0a9u3bh1KlSqFJkyYYOnQoTp48iTVr1qBatWq6ZnnRLUOXL1+Ojz76SNMyAACvvfYajh079lJtZSo6zAt+0a1lGzdurFkxyaxQoULYvn17lg/Sbdu26T5pOSkpyXqZacuWLWjTpg3s7OxQrVo1zS9BZqd06dLYu3dvlu/hVatWITg4WLccZiz8ZtKiRQsMHz4cERER1s/dAwcOYOXKlfjiiy9sdgH+r3f81bwMHDt2DNu3b0fBggVRoUIFAMCJEyeQnJyMunXrWq8/AsbMoM9OTEyM5m3566+/xsOHDwEAI0aMgKOjI/bv34933nkHn3/+uaZjZ2f69OlISEgAkL7XeEJCAn755RcEBgbqeifBv6HHLzwg/QNp6NChuHLlCipXrpzlL+Hy5cvrkuNlpdf7NHToUAwaNAjHjx+3zlkIDw/H4sWLMWvWLF0yZChevDjWrVuH1q1bIywsDKGhoQCAGzduwNPTU9csQPoW5F27dsXVq1eRlpaGNWvW4OzZs1i6dCk2bNigex6zFX6z6NevHwDg22+/xbfffpvtc0D6H63/9d06mt9a2L179xd+bcbpR6NlXiREBampqQgPD0f58uV1X5zl/4Ve71N2t5paLBaIiCY/lP8FM30P65ll7dq1mDZtms1tWcOGDUPLli01HzuzVatWoWPHjkhNTUXdunWxZcsWAMCkSZOwZ88e/O9//9M1DwDs3bsXY8eOxYkTJ5CQkIBKlSph1KhRaNCgge5ZXpSZvo9fdbquM/Asel1XfBF6fQOmpqZi7dq11g+u0qVLo2XLlnBw0PyETRYuLi44ffo0ihYtqvvY/1d6vU/PO61rxssHZvoQNVMWPcXFxeHatWuoUKGCtVAeOnQInp6eKFmypMHpXg6qfu8YQf/fOk+h13VFszh16hRatGiBuLg462ISU6ZMQe7cufH777+jbNmyuuYpW7YsoqOjX6oyoBcz/rJ/nuddi32VHTlyxKZgV65c2ZAc+fLlQ758+WyOvfbaa4ZkoZfH4cOHsXPnTty4cQNpaWk2z2l5ydY0ZcAkJyh007NnT5QpUwZHjhyBt7c3AODOnTvo1q0bevfujf379+uaZ/z48fjoo48wbty4bK+LG3Gd00iZJ+o8z389kee/YKafJ72KyZUrV9ChQweEh4dbL3fFx8fjzTffxM8//2zYPf5G8fb2fuGv/e3btzVOQy9i4sSJ+PzzzxEUFIS8efPavH9a/xyZpgyo5vjx4zZFAEj/4Z0wYQKqVq2qe54mTZoASP/FlvmbzszXxTt37qxZSWnVqpXNvzPmCGT+dwa9vjYpKSkoWbIkNmzYgFKlSj3ztf/73//g5+enS67n0auY9OzZEykpKTh9+rT1bNvZs2fRvXt39OzZE5s3b9Ylh1mYYbEs+ndmzZqFRYsWoVu3brqPzTKQjXnz5mm+M12JEiVw/fp16738GW7cuJHt/cBae9H71/USHx+PQ4cOZXuqrEuXLgCg6eqVmcfctm0bhg8fjokTJ9qsovn5559j4sSJmmV4kqOjo/UOlOd56623NE7z4jLW09Da7t27sX//fps13IOCgjBnzhzN79E2o65duxod4f+ZloXfjOzs7FC9enVDxjbNBEKtJorMnj37hV+bsYSpHjZt2oSPP/4YY8aMsbmfdOzYsZg8ebLNh7lKPwwA8Pvvv6NTp05ISEiAp6dnllNlep/SLFu2LObOnZvlF+zevXvRu3dvXRckmjhxIqKiorBgwQJDJpoGBwe/8OnKo0ePapzGVokSJbB8+fIs1+UPHTqEjh074vz587rmMdq9e/esnx337t175mv1/ozx9/dHjx490K1bNxQuXFjXsc1s6tSp+Pvvvw05q2OaMqDVimlPToi7efMmkpKSbK4purm5IU+ePIiOjv5Px36WzLerZXy4ZrwVmf+t1yn6PXv2PPP5GjVqaJ4hQ4kSJdCkSRNMnDgRbm5uuo37NK6urjh8+HCWSZ2RkZF4/fXXdd0psHXr1ti+fTty5MiBcuXKZZnbofVaHf9mb4gXXZTov7J+/XpMnDgR33zzDapUqQIgfTLhwIEDMXz48CyXfl51mXeVtLOzy7bEGXUZcObMmVi8eDH+/PNP1K5dGyEhIWjdurUp7iYzUlpaGpo2bYqoqCiULl0ajo6ONs9r+fNtmjKgxy0kP/30E7799lssXLjQ5ppir1690KdPH3Tq1EmzsZ+0e/fuF35txqpdWnravfQZ9PywcHd3x8mTJ01zZ0mNGjXg4uKCZcuWWS8fXb9+HV26dMHDhw//1Xv5/+p563aYZa0OI3h7eyMpKQmPHz+2njXJ+O8nS5MKE+Z2796N6tWrw8HB4bnfo3p8xmTn6NGjWLx4MVasWIHU1FR07NgRPXr0QKVKlQzJY7QBAwZgwYIFqF27dpYJhIC2P9+6lIHHjx9j165duHDhAjp27AgPDw/8/fff8PT0RI4cObQe3qpYsWLZLr8ZERGBd999V5c9Cczq7t27Nv9OSUnBsWPHMHLkSEyYMEHXJZLbtGmD9u3bo127drqN+Sznz59H69atERUVZV3W9vLlywgMDMS6desMmeNhFvHx8Vi1ahUuXLiAYcOGIVeuXDh69Cjy5s2r+wTGJUuWvPBrX4Xr6f/Ww4cPERkZme08HKPviElJScG3336L4cOHIyUlBeXKlcOgQYPQvXt3pW6T9fDwwM8//4ymTZvqPrbmFx0vXbqERo0aITY2Fo8ePUL9+vXh4eGBKVOm4NGjR7ptuwoA165dw+PHj7McT01NxfXr13XLkVlSUhJiY2OtmwRl0HuJ25w5c2Y5Vr9+fTg5OWHIkCGIiIjQLUvTpk0xbNgw/PXXXyhXrlyWU2V6f3AVL14ckZGR2Lp1K86cOQMgfWW7evXqGfJBZZZyHRkZiXr16iFnzpyIiYlBr169kCtXLqxZswaxsbFYunSpblmAF/8FP3nyZMTHx79Uq23+v9q8eTO6dOmS7aZjRt4tlJKSgrVr1+KHH37A1q1bUa1aNYSEhODKlSv47LPPsG3bNvz000+GZDNCrly5UKxYMWMG13RPRBFp2bKldO7cWR49emSzdebOnTulePHiWg9vo1mzZhIcHCwRERHWY0eOHJFKlSpJ8+bNdc1y48YNadq06VO38jSL06dPi7u7u65jWiyWpz7M9LV5UtmyZSU2NlbTMWJiYqRkyZLi5uYm9vb21p+nQYMGSZ8+fTQd+0l169aVYcOGiYjttrjh4eG6bXv9f+Hh4WHNqorixYtLv379TLMVd0REhAwYMEB8fHwkd+7cMnToUDl9+rTNa06ePCkuLi4GJTTGokWLpF27dpKYmKj72JqfGdi7dy/279+fZbtif39/XL16VevhbSxatAhdu3ZFlSpVrH9tPn78GA0bNsSCBQt0zfLhhx8iPj4eBw8eRK1atbB27Vpcv34d48ePx7Rp03TNAqT/lZeZiODatWuYPHkyKlasqGuWJ09hviz02OBq8ODBqFKlCk6cOAEfHx/r8datW6NXr16ajv2kw4cPY968eVmO+/n5IS4uTtcs/4aYY5qUrq5fv44hQ4Zofsv0i6patSrq16+P7777Dq1atcpy9g9In/zdvn17A9IZZ/bs2bhw4QLy5s0Lf3//LF8XLe/Q0bwMpKWlZXsK6sqVK9YtPvWSO3dubNq0CVFRUdbTvSVLlkSJEiV0zQEAO3bswPr161GlShXY2dmhSJEiqF+/Pjw9PTFp0iTdrxlVrFgxy8I6QPrWxosWLdI1Cz2dmcq1s7NztresRUVFIXfu3LpmoWd79913sWvXLuNOQT8hOjr6uct8u7u7Kzch1sg7XjQvAw0aNMDMmTPx/fffA0i/PpWQkIDRo0dbV73Tm7+/P0QExYoVM+RebQBITExEnjx5AKTPgr558yZKlCiBcuXK6X5/NoAskyft7OyQO3duuLi46J4FSJ8J/dVXX9msMT9s2DAlF4/JzEzlukWLFhg7dix+/fVXAOk/27GxsRg+fDjeeecdXbPQs3399ddo27Yt9u7dm+08HD3XWAFezv0+9KD37biZaf6bcNq0aWjYsCFKly6Nhw8fomPHjjh37hx8fX2xYsUKrYe3kZSUhIEDB1pnHUdFRSEgIAADBw6En58fPvnkE92yBAUF4ezZs/D390eFChUwb948+Pv7Y+7cucifP79uOTJk98MZHx9vSBlYvnw5unfvjjZt2lg/pMLDw1G3bl0sXrwYHTt21D2TWZipXE+bNg3vvvsu8uTJgwcPHqBmzZqIi4vDG2+8gQkTJuiahZ5txYoV2LJlC1xcXLBr164sC3npUQa4V8KLi4iIsP4hVKZMmSx3wGlCj4kJKSkpsmzZMhk2bJh88MEHMn/+fElKStJjaBuDBg2SypUry969e8Xd3d06iWjdunVSsWJFXbMsW7ZMfvjhBxFJn8To6+srdnZ24uLiIj///LOuWUREJk+ebDNu27ZtxWKxSIECBeT48eO6ZilZsqRMnz49y/Fp06ZJyZIldc3yb2SeRKeVy5cvS+nSpaVUqVLi4OAg1apVEx8fHwkKCpLr169rOvbT7N27V7755huZMmWKbN261ZAM/4Ye75PZ5M2bVyZMmCCpqamGZVi8eLH1MW3aNPH29pb27dvLrFmzZNasWdK+fXvx9vbO9mdfFdevX5fatWuLxWIRb29v8fb2FovFInXq1JEbN25oOrYuZcAsChcuLH/88YeI2H4gnDt3Tjw8PIyMJomJiRIRESE3b940ZHx/f38JDw8XEZEtW7aIl5eXhIWFSUhIiNSvX1/XLE5OTnLu3Lksx8+dOyfOzs66Zvk39PolY5Zy/bJq3Lix/P3330bH0JW3t7ecP3/e6BhWbdq0kTlz5mQ5PmfOHGnZsqX+gUyiXbt2UqVKFfnrr7+sx06dOiVVqlSR9u3bazq2JpcJzLr9682bN63X6TNLTEw0fGELNzc3Q1fdiouLsy6os2HDBrRr1w4NGjSAv78/Xn/9dV2zFCpUCNu3b8+ymM+2bdusGY2W3X3qemxwBQAODg7o3Lmz5uM8z9ixY5/5/KhRo3RKkm7x4sXZ7vb2+PFjjBw5EpMmTQKQvi+Iarp27YpffvkFn332mdFRAABhYWGYMmVKluONGjXS9XKt2WzevBnbtm2z2ZW0dOnS+Oabb9CgQQNNx9akDLzojEi9F7uoUqUKNm7ciIEDB1rHB4AFCxZYd6PTyzvvvIPXXnsNw4cPtzk+depUHD58GCtXrtQ1j7e3Ny5fvoxChQph8+bNGD9+PID027D0XpBk6NChGDRoEI4fP44333wTQPqcgcWLF2PWrFm6ZgGAKVOmwN/fH++99x4AoF27dli9ejXy5cuHTZs2oUKFCgCg21yGc+fOYefOndmuJKfnL+C1a9fa/DslJQUXL16Eg4MDihUrpnsZGDRoEDZu3Ijvv//eujX42bNn0bFjR9y6dctaBlSUmpqKqVOnIiwsDOXLl88ygXD69Om65vHx8cH69esxdOhQm+Pr16+3uWVWNWlpadneZuno6Kj9Ldeanncwmb1790qOHDmkb9++4uLiIoMHD5b69euLu7u7HDlyRNcsvr6+EhkZmeV4ZGSk5MmTR9csIiL9+/eXIkWKSL169cTHx0fu378vIiIrVqyQ4OBg3fOsWbNGqlevLrly5ZJcuXJJ9erVZd26dbrnEDHXJZTvv/9e7O3tJW/evFKhQgWpWLGi9WHE+/Sku3fvSuvWrWXp0qW6j33+/HmpVq2a+Pn5yZYtW+Trr78WNzc36dixo8THx+uex0xq1ar11Eft2rV1z/PDDz+Ivb29NGvWTMaNGyfjxo2TZs2aiYODg3UulYpatGghNWrUkKtXr1qPXblyRWrWrCmtWrXSdGylyoCIyIULF6Rnz55StWpVKVWqlHTq1CnbX8pac3FxkTNnzmQ5fvr0aUNW3UpOTpYvv/xSBg0aJEePHrUenz59usyfP1/3PGbi4uJiXVlw0KBB0rt3bxEROXv2rHh5eemapXDhwjJ58mRdx/y3IiMjDVuBMDU1VQYOHCh2dnbi6OgoP/30kyE56PkOHDggHTt2lODgYAkODpaOHTvKgQMHjI5lqNjYWKlYsaI4OjpKQECABAQEiKOjowQHB8vly5c1HVuXjYoSExOxe/fubNfg1+v+1pSUFPTp0wcjR47Msq2xEV577TU0a9Ysy6nUMWPG4Pfff9d1LwB6tgIFCmDVqlV48803ERQUhPHjx6Nt27Y4e/Ysqlat+ty94v9LWm31/V/at28fmjdvjjt37ug+9u+//46QkBCUKFECUVFRKF++PJYuXYoCBQronoXo/0JEsG3btiz7oGhN83UGjh07hiZNmiApKQmJiYnIlSsX/vnnH7i5uSFPnjy6lQFHR0esXr0aI0eO1GW85xk5ciTatGmDCxcuoE6dOgCA7du3Y8WKFbrPF8hg5LXoXLlyISoqCr6+vs+9H1nve5DbtGmDjh07IjAwELdu3ULjxo0BpH9v671jYdu2bbFlyxb07dtX13GzM3v2bJt/y/9vCetly5ZZv0Z66tOnD5YsWYIJEyZgyJAhuH79Onr06IFy5crhu+++M80umJQuNTUV69ats7mfvkWLFrC3tzc4mf527NiBAQMG4MCBA/D09ET9+vVRv359AOk7ypYpUwZz587VdNE1zc8M1KpVCyVKlMDcuXORM2dOnDhxAo6OjujcuTMGDx6MNm3aaDm8ja5du6JixYoIDQ3Vbcxn2bhxIyZOnIjjx4/D1dUV5cuXx+jRow3ZW3z+/Pn44IMP4Ovri3z58mVZlETrVRGXLFmC9u3bw9nZGYsXL35mGdB7+9mUlBTMmjULly9fRrdu3awLgMyYMQMeHh7o2bOnblkmTZqE6dOno2nTpoasJBcZGYmyZcvCzs4uyxm2jFUr69Spg08//VT3FRHLli2LH3/80TqhM8M333yD4cOHIyEhQdc89HTnz59H06ZNceXKFQQFBQFIn+xZqFAhbNy40TTLJuulRYsWqF279lN/N82ePRs7d+7MMmn3v6R5GfDy8sLBgwcRFBQELy8v/PHHHyhVqhQOHjyIrl27Wk+F6CFjE6C6deuicuXKcHd3t3le7yU5X8SKFSvQokWLLFn/a0WKFEG/fv2y3N1A5vKsS1wWiwXR0dGajm9vb49r164hT548KFq0KA4fPgxfX19Nx3xRjx49grOzc7bPnT171vpLh4zXpEkTiAh+/PFH5MqVCwBw69YtdO7cGXZ2dti4caPBCfVVpEgRbN682eaWwszOnDmDBg0aIDY2VrMMmpeB3LlzY//+/QgMDESJEiUwZ84cNGzYEGfOnEHlypWRmJio5fA2jP4g/b/Q6xqxma5FHz16FI6OjihXrhyA9NuNfvjhB5QuXRpjxozJskmPHv7++2/s27cv20soZiyRWvHx8cGmTZvw+uuvw97eHnFxcdyUiP41d3d3HDhwwPoznuHEiROoXr26cmdxXFxc8Oeffz71suP58+dRrlw5PHjwQLMMms8ZCA4OxuHDhxEYGIiaNWti1KhR+Oeff7Bs2TKULVtW6+FtPLkZz8tAh/mdAMx1LbpPnz745JNPUK5cOURHR+O9995DmzZtsHLlSiQlJWHmzJm65lm8eDH69OkDJycn+Pj4GLKue4bo6GhDC9s777yDmjVrWvfPqFKlylOv8RpRrletWoVff/0128nKRmwARtlzdnbG/fv3sxxPSEgwpOwbzc/P75llIDIyUvM9azQvAxMnTrS+6RMmTECXLl3wwQcfIDAw0LCtcZOTk3Hx4kVDdy00m+LFi2PkyJHWtm7krmZRUVGoWLEiAGDlypWoWbMmfvrpJ4SHh6N9+/a6l4GRI0di1KhR+PTTT2FnZ6fr2E8qXrw4ChYsiJo1a6JWrVqoWbOmrpMYv//+e7Rp0wbnz5/HoEGD0KtXL93nBjzN7NmzMWLECHTr1g3r169H9+7dceHCBRw+fBj9+/c3Oh5l0qxZM/Tu3RsLFy7Ea6+9BgA4ePAg+vbtq+uqtGbRpEkTjBw5Eo0aNcqyOdyDBw8wevRoNGvWTNsQmt64aDKJiYnSo0cPsbe3F3t7e+s68gMGDJBJkyYZnC57eq137+/v/9RH0aJFNR8/Mw8PD4mKihIRkXr16snMmTNFROTSpUuGrMGQK1cu06zrfuXKFVm+fLn06tVLSpQoIRaLRfz8/KRjx466rwfRrVs3uXfvnq5jPktQUJB1XYHMPzcjR46U/v37GxmNnnDnzh1p0aKFWCwWcXJyEicnJ7FYLNKqVSslF4iKi4uTAgUKSKFChWTKlCmybt06WbdunUyePFkKFSokBQoUkLi4OE0zaF4GkpKSJDEx0frvmJgYmTFjhoSFhWk9dBZm2rXwRam4w1rt2rWlS5cusnTpUnF0dLRuWrRr1y5DFrMZNmyYactiVFSUdO3aVRwcHMTOzs7oOIZydXWVmJgYERHJnTu3dbfNqKgoyZUrl5HR6CnOnTsn69evl/Xr12e7OZlKYmJipHHjxmJnZycWi0UsFovY2dlJ48aNJTo6WvPxNT9H3rJlS7Rp0wZ9+/ZFfHw8XnvtNTg5OeGff/7B9OnT8cEHH2gdwWrdunX45ZdfUK1aNZvrvmXKlMGFCxd0y2EWQ4YMwbhx4+Du7o4hQ4Y89XUWiwXTpk3TLdfMmTPRqVMnrFu3DiNGjLCeBs9Y+EdvkyZNQrNmzbB58+ZsL6Houa57UlIS9u3bh127dmHXrl04duwYSpYsiQEDBqBWrVq65TCjfPny4fbt2yhSpAgKFy6MAwcOoEKFCrh48aJuc2/oxS1cuBAzZszAuXPnAACBgYH48MMPdb1V10yKFCmCTZs24c6dOzh//jxEBIGBgdZ9NrSmeRk4evQoZsyYASD9wzxfvnw4duwYVq9ejVGjRulaBsy8a+HTFClSJNuNK/4Lx44dQ0pKivW/n0bvr0358uVx8uTJLMe//PJLQxYkmTRpEsLCwqy3pj05gVBPXl5e8Pb2RqdOnfDJJ5/g7bff1u3Dwuzq1KmD3377DcHBwejevTtCQ0OxatUqHDlyRNf1TOj5Ro0ahenTp2PgwIHWTeL++OMPhIaGIjY29rk7Yr7KvL29UbVqVf0H1vrUg6urq1y6dElERNq2bStjxowRkfQ1mF1dXbUe3sbbb78ts2fPFpH00+8Zp14GDBggDRs21DWLSPp1s/nz58snn3wit27dEhGRiIgIuXLliu5ZzCQ2NtZmHe6DBw/K4MGDZd68eYbk8fLyMs3mKS1bthQfHx/Jnz+/dOjQQebNmydnz541OpYppKamSkpKivXfP//8swwcOFBmz54tycnJBiajJ/n6+ma7b8RPP/0kPj4+BiQizc8MFC9eHOvWrUPr1q0RFhZmXWHpxo0b8PT01Hp4GxMnTkTjxo3x119/4fHjx5g1axb++usv7N+/H7t379Y1S2RkJOrVq4ecOXMiJiYGvXr1Qq5cubBmzRrExsZi6dKluuYxk44dO6J37954//33ERcXh/r166NMmTL48ccfERcXp/vWuM7OzqhevbquYz7NunXrAKR//+zevRtbtmzByJEj4eDggFq1auHHH380NqCB7OzskJycjKNHj+LGjRtwdXW1rum+efNmNG/e3OCElCElJQVVqlTJcrxy5cp4/PixAYlI8zMDK1euFEdHR7Gzs5N69epZj0+cOFEaNWqk9fBZnD9/3hS7FtatW1eGDRsmIraTBMPDww3b8c0svLy8rDs6zpo1S958800REQkLC9P9zgaR9O/VgQMH6j7us6SlpUlERIR89dVX0rRpU3FwcBB7e3ujYxnqf//7n/j6+lonX2V+qD650mwGDBggoaGhWY4PHTpU+vXrZ0Ai0mXXwri4OFy7dg0VKlSw3qd96NAheHp6omTJkloPb0o5c+bE0aNHUaxYMXh4eODEiRMICAjApUuXEBQUhIcPHxod0TA5cuTAn3/+CX9/f7Ro0QLVq1fH8OHDERsbi6CgIE1X4cpO69atsWPHDvj4+KBMmTJZ5nCsWbNGtyzTp0/Hrl27sG/fPty7dw8VKlSwrjmg+vyBwMBANGjQAKNGjULevHmNjkNPyDxJ+fHjx1i8eDEKFy6MatWqAUhfZyA2NhZdunTBnDlzjIqpLF1W3MmXLx8SEhKwdetW1KhRA66urqhataruk68yr6ue2a1bt5AnTx6kpqbqlsXZ2TnbrW+joqKUX941Y4eupk2bYuvWrRg3bhyA9CWBfXx8dM/j5eX11Aloen8Pr1ixAjVr1kTv3r3x9ttvI2fOnLqOb2bXr1/HkCFDWARM6slJypUrVwYA651cvr6+8PX1xalTp3TPRjqUgVu3bqFdu3bYuXMnLBYLzp07h4CAAISEhMDb21vXW9aedhLk0aNHui+B2aJFC4wdOxa//vorgPRfKrGxsRg+fDjeeecdXbOYzZQpU9C6dWt8+eWX6Nq1q3UXut9++826WpmeGjRogA4dOmT73LBhw3TNcvjwYcTHx2PhwoXW+QNlypRBjx49lC8G7777Lnbt2qXcjncvi507dxodgZ5B88sEXbp0wY0bN7BgwQKUKlXKejo8LCwMQ4YM0aUFZuy7HhoainHjxiFHjhzW51JTU7Fnzx7ExMQ88/a6/9rdu3fx7rvv4siRI7h//z4KFCiAuLg4vPHGG9i0aZPmuxSaXWpqKu7du2dz2jsmJgZubm7Z3h6qJS8vL6xYsQKNGze2OT5kyBCsWLEC165d0y1LREQEGjZsCBcXF2sxOnz4MB48eIAtW7agUqVKumUxm6SkJLRt2xa5c+c2fEltopeN5mUgX758CAsLQ4UKFWyujUdHR6N8+fK67E6VsVvhpUuXULBgQZt71Z2cnODv74+xY8fi9ddf1zzLk/bt24fIyEgkJCSgUqVK1tnPZB4bN25Ep06dsGHDBrz11lsAgIEDB2L16tXYsWOHrvNe3n77bRQvXhzz58+37qvx+PFj9OzZE9HR0dizZ49uWcxm4cKF6Nu3L1xcXLLdUMqMu5ISmYXmZcDDwwNHjx5FYGCgTRk4cuQIGjZsiFu3bmk5vI3atWtjzZo1Sk+yMqtKlSph+/bt8Pb2RnBw8DOvxRux+9xPP/2EAQMGYOvWrVi4cCHWr1+PnTt3okSJErrmcHV1ta46mNlff/2FKlWqICkpSdc8ZpIvXz4MGjQIn3zyieEbShG9bDSfM/D2229j6dKl1klgFosFaWlpmDp1KmrXrq318DaevGaVmpqKkydPokiRIoYUhO3bt2P79u24ceMG0tLSbJ4zakdHo7Rs2RLOzs4AgFatWhkbJhsdO3ZEfHw8qlevjty5c2P37t267haYwdPTE7GxsVnKwOXLl02ze6BRkpOT8d5777EIEP0faH5m4NSpU6hTpw4qVaqEHTt2oEWLFjh16hRu376N8PBwXSf7fPjhhyhXrhxCQkKQmpqKGjVq4I8//oCbmxs2bNig69ruX3zxBcaOHYsqVaogf/78Wf4SXrt2rW5ZKKun7dWwcuVKVKpUyeb7Vs+9CQYNGoS1a9fiq6++su7TEB4ejmHDhuGdd97RfXtnMwkNDUXu3Lnx2WefGR2F6KWj6ZmBlJQUDBo0CL///ju2bt0KDw8PJCQkoE2bNujfvz/y58+v5fBZrFy5Ep07dwYA/P7774iJicGZM2ewbNkyjBgxAuHh4bplmTt3LhYvXoz3339ftzFfRgkJCVnOmuixcuXTJpMWL14c9+7dsz6v962FX331FSwWC7p06WJdqc3R0REffPABJk+erGsWs0lNTcXUqVMRFhaG8uXLG7qhFNHLRvMzA7lz58b+/fsRGBio5TAvxMXFBefPn0fBggXRu3dvuLm5YebMmbh48SIqVKiQ7X3/WvHx8cGhQ4d4G1Q2Ll68iAEDBmDXrl02iy+JCCwWi67rQZhVUlKS9f7sYsWKwc3NzeBExnvWZUeLxYIdO3bomIbo5aL5nIHOnTtj4cKFpvirJW/evPjrr7+QP39+bN68Gd999x2A9A9WvXfD69mzJ3766SeMHDlS13FfBp07d4aIYNGiRcibN69pd5Q0kpubG8qVK2d0DFPhfexE/3eal4HHjx9j0aJF2LZtGypXrpzl/nk9T911794d7dq1s16jz7iN7+DBg7ovi/zw4UN8//332LZtG09pPuHEiROIiIiwbhlMRETa0rwM/Pnnn9aFUKKiomye0/svvjFjxqBs2bK4fPky2rZta529bm9vj08++UTXLJGRkahYsSKA9K9RZqr/JVy1alVcvnyZZYCISCe6bFRE9G9cuHABffv2RefOnVG2bNksZ03Kly9vUDIioleTLhsVGWn27Nno3bs3XFxcrMsSPw2XKzWHmzdv4sKFC+jevbv1mMVi4QRCIiKNvPJnBooWLYojR47Ax8fHuixxdvRYrrRNmzZYvHgxPD09n7oLXgY9t8U1m9KlS6NUqVL4+OOPs51AWKRIEYOSERG9ml75MwMXL17M9r+NkDNnTusvNtV3mHuWS5cu4bfffjNkhT8iIhW98mcG6OXTvHlzdOvWTfmtnImI9PLKnxnI7GlLzFosFri4uKB48eJo2bIlcuXKpXMyyqx58+YIDQ3FyZMns92KtkWLFgYlIyJ6NSl1ZqB27do4evQoUlNTrbetRUVFwd7eHiVLlsTZs2dhsViwb98+lC5dWtMsT9uZL3Mx6datm+6bOZnBszaa4QRCIqL/nlLbe7Vs2RL16tXD33//jYiICERERODKlSuoX78+OnTogKtXr6JGjRoIDQ3VPEujRo0QHR0Nd3d31K5dG7Vr10aOHDlw4cIFVK1aFdeuXUO9evWwfv16zbOYTVpa2lMfLAJERP89pc4M+Pn5YevWrVn+6j916hQaNGiAq1ev4ujRo2jQoAH++ecfTbP06tULhQsXzrIc8fjx43Hp0iXMnz8fo0ePxsaNG3HkyBFNs7wM4uPj4eXlZXQMIqJXklJnBu7evYsbN25kOX7z5k3rJkVeXl5ITk7WPMuvv/6KDh06ZDnevn17/PrrrwCADh064OzZs5pnMZspU6bgl19+sf67bdu2yJUrF/z8/HDixAkDkxERvZqUKgMtW7ZEjx49sHbtWly5cgVXrlzB2rVrERISglatWgEADh06hBIlSmiexcXFBfv3789yfP/+/XBxcQGQfro8479VMnfuXBQqVAgAsHXrVmzbtg2bN29G48aNMWzYMIPTERG9epS6m2DevHkIDQ1F+/btrXvBOzg4oGvXrpgxYwYAoGTJkliwYIHmWQYOHIi+ffsiIiICVatWBQAcPnwYCxYswGeffQYACAsLs+5foJK4uDhrGdiwYQPatWuHBg0awN/fH6+//rrB6YiIXj1KzRnIkJCQYF1tMCAgADly5DAkx48//oivv/7aeikgKCgIAwcORMeOHQEADx48sN5doJICBQpg1apVePPNNxEUFITx48ejbdu2OHv2LKpWrWq9pENERP8Npc4MZIiLi8O1a9dQo0YNuLq6Wte811unTp3QqVOnpz7v6uqqYxrzaNOmDTp27IjAwEDcunULjRs3BgAcO3aMqxISEWlAqTJw69YttGvXDjt37oTFYsG5c+cQEBCAkJAQeHt7Y9q0abpnSk5Oxo0bN5CWlmZzvHDhwrpnMYsZM2bA398fly9fxtSpU61nbq5du4Z+/foZnI6I6NWj1GWCLl264MaNG1iwYAFKlSqFEydOICAgAGFhYRgyZAhOnTqlW5Zz586hR48eWSYRcmc+IiLSm1JnBrZs2YKwsDAULFjQ5nhgYCAuXbqka5Zu3brBwcEBGzZsQP78+Q25TGFm586dw86dO7M9azJq1CiDUhERvZqUKgOJiYlwc3PLcvz27dtwdnbWNcvx48cRERGBkiVL6jruy2D+/Pn44IMP4Ovri3z58tkUJYvFwjJARPQfU6oMvP3221i6dCnGjRsHIP0XS1paGqZOnar7HgClS5fWfJXDl9X48eMxYcIEDB8+3OgoRERKUGrOwKlTp1CnTh1UqlQJO3bsQIsWLXDq1Cncvn0b4eHhKFasmG5ZduzYgc8//xwTJ07Mdmc+T09P3bKYjaenJ44fP46AgACjoxARKUGZMpCSkoJGjRph0qRJ2Lp1K06cOIGEhARUqlQJ/fv3R/78+XXNk3lnvsynwTmBEAgJCUHVqlXRt29fo6MQESlBmcsEjo6OiIyMhLe3N0aMGGF0HOzcudPoCKZVvHhxjBw5EgcOHMj2rMmgQYMMSkZE9GpS5swAAISGhsLZ2RmTJ082OgoAYO/evZg3bx4uXLiAVatWwc/PD8uWLUPRokXx1ltvGR3PMEWLFn3qcxaLxbp6JBER/TeUOTMAAI8fP8aiRYuwbds2VK5cGe7u7jbPT58+Xbcsq1evxvvvv49OnTrh2LFjePToEYD0nRUnTpyITZs26ZbFbC5evGh0BCIipSh1ZuBZdwxYLBbs2LFDtyzBwcEIDQ1Fly5d4OHhYV0A6dixY2jcuDHi4uJ0y0JERGpT6syAma7Tnz17FjVq1MhyPGfOnIiPj9c/kMlcuXIFv/32G2JjY5GcnGzznJ5ncIiIVKBUGTCTfPny4fz58/D397c5vm/fPuVvqdu+fTtatGiBgIAAnDlzBmXLlkVMTAxEBJUqVTI6HhHRK8fu+S8hLfTq1QuDBw/GwYMHYbFY8Pfff+PHH3/ERx99hA8++MDoeIb69NNP8dFHH+HkyZNwcXHB6tWrcfnyZdSsWRNt27Y1Oh4R0StHqTkDZiIimDhxIiZNmoSkpCQAgLOzMz766CPrComq8vDwwPHjx1GsWDF4e3tj3759KFOmDE6cOIGWLVsiJibG6IhERK8UXiYwiMViwYgRIzBs2DCcP38eCQkJKF26tHW7XpW5u7tb5wnkz58fFy5cQJkyZQCASzgTEWmAZcBgTk5OKF26tNExTKVatWrYt28fSpUqhSZNmmDo0KE4efIk1qxZg2rVqhkdj4jolcPLBGQ60dHRSEhIQPny5ZGYmIihQ4di//79CAwMxPTp01GkSBGjIxIRvVJYBshUUlNTER4ejvLly8PLy8voOERESmAZINNxcXHB6dOnn7ksMRER/Xd4ayGZTtmyZbn/ABGRjnhmgExn8+bN+PTTTzFu3Lhs95Dw9PQ0KBkR0auJZYBMx87u/3/CymKxWP9bRGCxWJCammpELCKiVxZvLSTT+eGHH1CoUCHY29vbHE9LS0NsbKxBqYiIXl08M0CmY29vj2vXriFPnjw2x2/duoU8efLwzAAR0X+MEwjJdDIuBzwpISEBLi4uBiQiInq18TIBmcaQIUMApM8TGDlyJNzc3KzPpaam4uDBg6hYsaJB6YiIXl0sA2Qax44dA5B+ZuDkyZNwcnKyPufk5IQKFSrgo48+MioeEdEri3MGyHS6d++OWbNm8RZCIiKdsAwQEREpjhMIiYiIFMcyQEREpDiWASIiIsWxDBARESmOZYCIiEhxLANERESKYxkgIiJS3P8HonzZL7zaI/YAAAAASUVORK5CYII=",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Checking Null Values\n",
    "sns.heatmap(df.isnull(),cbar=False,yticklabels=False)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "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>resale_price</th>\n",
       "      <th>registered_year</th>\n",
       "      <th>engine_capacity</th>\n",
       "      <th>insurance</th>\n",
       "      <th>transmission_type</th>\n",
       "      <th>kms_driven</th>\n",
       "      <th>owner_type</th>\n",
       "      <th>fuel_type</th>\n",
       "      <th>max_power</th>\n",
       "      <th>seats</th>\n",
       "      <th>mileage</th>\n",
       "      <th>body_type</th>\n",
       "      <th>city</th>\n",
       "      <th>Company</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>10052</th>\n",
       "      <td>385000.0</td>\n",
       "      <td>2017</td>\n",
       "      <td>998.0</td>\n",
       "      <td>Comprehensive</td>\n",
       "      <td>Manual</td>\n",
       "      <td>69359.0</td>\n",
       "      <td>First Owner</td>\n",
       "      <td>Petrol</td>\n",
       "      <td>67.04</td>\n",
       "      <td>5.0</td>\n",
       "      <td>23.10</td>\n",
       "      <td>Hatchback</td>\n",
       "      <td>Gurgaon</td>\n",
       "      <td>Maruti</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7873</th>\n",
       "      <td>543000.0</td>\n",
       "      <td>2018</td>\n",
       "      <td>1197.0</td>\n",
       "      <td>Third Party</td>\n",
       "      <td>Manual</td>\n",
       "      <td>38953.0</td>\n",
       "      <td>Second Owner</td>\n",
       "      <td>Petrol</td>\n",
       "      <td>81.86</td>\n",
       "      <td>5.0</td>\n",
       "      <td>18.90</td>\n",
       "      <td>Hatchback</td>\n",
       "      <td>Hyderabad</td>\n",
       "      <td>Hyundai</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7940</th>\n",
       "      <td>640000.0</td>\n",
       "      <td>2020</td>\n",
       "      <td>999.0</td>\n",
       "      <td>Third Party</td>\n",
       "      <td>Manual</td>\n",
       "      <td>30000.0</td>\n",
       "      <td>First Owner</td>\n",
       "      <td>Petrol</td>\n",
       "      <td>71.01</td>\n",
       "      <td>7.0</td>\n",
       "      <td>20.00</td>\n",
       "      <td>MUV</td>\n",
       "      <td>Hyderabad</td>\n",
       "      <td>Renault</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1639</th>\n",
       "      <td>364000.0</td>\n",
       "      <td>2012</td>\n",
       "      <td>1461.0</td>\n",
       "      <td>Third Party</td>\n",
       "      <td>Manual</td>\n",
       "      <td>121243.0</td>\n",
       "      <td>Second Owner</td>\n",
       "      <td>Diesel</td>\n",
       "      <td>108.45</td>\n",
       "      <td>5.0</td>\n",
       "      <td>19.01</td>\n",
       "      <td>SUV</td>\n",
       "      <td>Jaipur</td>\n",
       "      <td>Renault</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15214</th>\n",
       "      <td>590000.0</td>\n",
       "      <td>2019</td>\n",
       "      <td>1186.0</td>\n",
       "      <td>Third Party</td>\n",
       "      <td>Manual</td>\n",
       "      <td>110000.0</td>\n",
       "      <td>First Owner</td>\n",
       "      <td>Diesel</td>\n",
       "      <td>73.97</td>\n",
       "      <td>5.0</td>\n",
       "      <td>24.00</td>\n",
       "      <td>Hatchback</td>\n",
       "      <td>Delhi</td>\n",
       "      <td>Hyundai</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "       resale_price  registered_year  engine_capacity      insurance  \\\n",
       "10052      385000.0             2017            998.0  Comprehensive   \n",
       "7873       543000.0             2018           1197.0    Third Party   \n",
       "7940       640000.0             2020            999.0    Third Party   \n",
       "1639       364000.0             2012           1461.0    Third Party   \n",
       "15214      590000.0             2019           1186.0    Third Party   \n",
       "\n",
       "      transmission_type  kms_driven    owner_type fuel_type  max_power  seats  \\\n",
       "10052            Manual     69359.0   First Owner    Petrol      67.04    5.0   \n",
       "7873             Manual     38953.0  Second Owner    Petrol      81.86    5.0   \n",
       "7940             Manual     30000.0   First Owner    Petrol      71.01    7.0   \n",
       "1639             Manual    121243.0  Second Owner    Diesel     108.45    5.0   \n",
       "15214            Manual    110000.0   First Owner    Diesel      73.97    5.0   \n",
       "\n",
       "       mileage  body_type       city  Company  \n",
       "10052    23.10  Hatchback    Gurgaon   Maruti  \n",
       "7873     18.90  Hatchback  Hyderabad  Hyundai  \n",
       "7940     20.00        MUV  Hyderabad  Renault  \n",
       "1639     19.01        SUV     Jaipur  Renault  \n",
       "15214    24.00  Hatchback      Delhi  Hyundai  "
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.sample(5)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Data Visualization"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Seperating Numerical and Categorical features\n",
    "categorical = ['insurance','transmission_type','owner_type','fuel_type','body_type','city','Company']\n",
    "numerical = df.drop(categorical,axis=1)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Numerical Features"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.histplot(x=df['registered_year'],color='Crimson')\n",
    "plt.title('Number of Cars Registered Over the Years')\n",
    "plt.xlabel('Registered_Year')\n",
    "plt.ylabel('Count')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "People in India started buying cars in early 2000s and the number of cars registered each year continued to rise, reaching its peak around 2015-2019. There is a decline around 2020, one of the reason for this could be pandemic.  "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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0xHq0lilTpkCtVuOhhx6q8y2+po3HW++rr74aaWlpuOOOO+qspOz3+3HZZZdBCBEVLALhHp8BAwZg0aJFWLRoETIzM3HKKadEHtdoNPjLX/6CJUuWYOPGjU2u15HUzCBqagBQ2wUXXABZlutdiE+SpOO69tChQ9GtWzc8+eSTcLvddR6v3XaNRlPn5/Vf//pXnWnrDZFluc7wVVpaGrKysiK/F0THo0P33BxJQUEB5s+fj4KCAmRlZQEID0F88cUXmD9/Ph599FHs3LkTe/bsweLFi/HGG29AlmXceuutOP/887F8+fIYt4Ca2x133IGpU6diwYIFuOaaa/Diiy9izJgxGDBgAK666ip07doVxcXFWLVqFfbt24fffvsNANC3b1+MHTsWQ4cORVJSElavXh2ZAguEvymfcsopeOKJJxAKhZCdnY2vvvoqssbMkdjtdrz00kv461//ihNOOAEXXnghUlNTUVBQgM8++wyjR4/GCy+80KKvy+G6d++Oe+65Bw8//DBOPvlknHfeeTAYDPj111+RlZWFOXPmHHe9k5OT8d5772Hy5Mk44YQTcOWVV6Jv374oKirCggULsH37djz33HMYNWpUnXOnTZuG+++/H0ajEVdccUWdpOfHHnsM33zzDYYPH46rrroKffv2RUVFBdauXYuvv/76mL+8mEwm9O3bF4sWLULPnj2RlJSE/v37o3///o2+xqmnnoqrr74ac+bMwfr16zFhwgTodDps27YNixcvxnPPPYfzzz//mOqnVqvx6quvYtKkSejXrx8uu+wyZGdnY//+/fjmm29gt9vxySefAAj3nL355ptwOBzo27cvVq1aha+//rrO0gENcblc6NSpE84//3wMGjQIVqsVX3/9NX799deo3iCiYxazeVpxBoD44IMPIvc//fRTAUBYLJaom1arFRdccIEQQoirrrpKABD5+fmR89asWSMAiC1btrR2E6gZNLRCsRBCyLIsunXrJrp16xaZ1rpjxw4xY8YMkZGRIXQ6ncjOzhZ//vOfxXvvvRc575///KcYNmyYSEhIECaTSfTu3Vs88sgjIhgMRsrs27dPnHvuuSIhIUE4HA4xdepUceDAgTpThxtaofibb74REydOFA6HQxiNRtGtWzdx6aWXitWrVx+xvQ2tUHy4munepaWlDT52uNdee00MGTJEGAwGkZiYKE499VSxdOnSZql3jV27domrrrpK5ObmCp1OJ1JSUsTZZ58tvv/++wbP2bZtmwAgAIgffvih3jLFxcXi+uuvFzk5OUKn04mMjAxx2mmniXnz5kXVvTGvXW0rV64UQ4cOFXq9Puq9bWiF4oZe23nz5omhQ4cKk8kkbDabGDBggLjzzjvFgQMHGl2XvLy8epcoWLdunTjvvPNEcnKyMBgMIi8vT1xwwQVi2bJlkTKVlZXisssuEykpKcJqtYqJEyeKLVu2iLy8PDFz5sxIuYZ+nwKBgLjjjjvEoEGDhM1mExaLRQwaNKjVVkmm9k8lxBFW4upAVCpV1GypRYsW4eKLL8amTZvqJPpZrVZkZGRg9uzZdbrVfT4fzGYzvvrqq8gCbURERNR6OCzVgCFDhkCWZZSUlESW3j/c6NGjIUkSduzYEUnG27p1KwAgLy+v1epKREREh3Tonhu3243t27cDCAczTz/9NMaNG4ekpCTk5ubikksuwY8//oinnnoKQ4YMQWlpKZYtW4aBAwdi8uTJUBQFJ510EqxWK5599lkoioLrr78edru9zh46RERE1Do6dHCzYsUKjBs3rs7xmTNnYsGCBQiFQvjnP/+JN954A/v370dKSgpGjBiBBx98EAMGDAAAHDhwADfeeCO++uorWCwWTJo0CU899RSSkpJauzlERESEDh7cEBERUfvDdW6IiIioXWFwQ0RERO1Kh5stpSgKDhw4AJvN1izLoRMREVHLE0LA5XIhKyurzuKbh+twwc2BAweQk5MT62oQERHRMdi7dy86dep0xDIxDW5eeuklvPTSS9i9ezcAoF+/frj//vuPuGna4sWLcd9992H37t3o0aMHHn/8cZx55pmNfk6bzQYg/OLY7fbjqj8RERG1jurqauTk5EQ+x48kpsFNp06d8Nhjj6FHjx4QQuD111/HOeecg3Xr1qFfv351yq9cuRLTp0/HnDlz8Oc//xnvvPMOpkyZgrVr1zZ6f5aaoSi73c7ghoiIqI1pTEpJ3E0FT0pKwty5c3HFFVfUeWzatGnweDz49NNPI8dGjBiBwYMH4+WXX27U9aurq+FwOOB0OhncEBERtRFN+fyOm9lSsixj4cKF8Hg8GDlyZL1lVq1ahfHjx0cdmzhxIlatWtXgdQOBAKqrq6NuRERE1H7FPLjZsGEDrFYrDAYDrrnmGnzwwQfo27dvvWWLioqQnp4edSw9PR1FRUUNXn/OnDlwOByRG5OJiYiI2reYBze9evXC+vXr8fPPP+Paa6/FzJkzsXnz5ma7/qxZs+B0OiO3vXv3Ntu1iYiIKP7EfCq4Xq9H9+7dAQBDhw7Fr7/+iueeew6vvPJKnbIZGRkoLi6OOlZcXIyMjIwGr28wGGAwGJq30kRERBS3Yt5zczhFURAIBOp9bOTIkVi2bFnUsaVLlzaYo0NEREQdT0x7bmbNmoVJkyYhNzcXLpcL77zzDlasWIEvv/wSADBjxgxkZ2djzpw5AICbb74Zp556Kp566ilMnjwZCxcuxOrVqzFv3rxYNoOIiIjiSEyDm5KSEsyYMQOFhYVwOBwYOHAgvvzyS5x++ukAgIKCgqgllkeNGoV33nkH9957L/7xj3+gR48e+PDDDxu9xg0RERG1f3G3zk1L4zo3REREbU+bXOeGiIiIqDkwuCEiIqJ2hcENERERtSsMboiIiKhdYXBDREREzeZAlQ++oBzTOjC4ISIiomYhhECpKwBPUIppPRjcEBERUbOQFQFZif0KMwxuiIiIqFlIioASB8vnMbghIiKiZiErAhJ7boiIiKi9kBQBhcENERERtRcyh6WIiIioPZEUhQnFRERE1H4oCiCz54aIiIjaC0lRoCixrgWDGyIiImomnC1FRERE7UpQioNuGzC4ISIiomYSkGK7p1QNBjdERETULIIye26IiIioHQlKsc+3ARjcEBERUTOIl00zAQY3RERE1AwkRYmL1YkBBjdERETUDNhzQ0RERO2KpIi4WJ0YYHBDREREzUBRBJT4mAnO4IaIiIiOn6QIKEKBWhXrmjC4ISIiomYgKwIqVRxENmBwQ0RERM1AUgQEmHNDRERE7YQsC0Cw54aIiIjaiaAsQ81hKSIiImovgpKAOk6iijipBhEREbVlIVmBhj03RERE1F4EZQWaeJgHDgY3REREdJwURUCSBHNuiIiIqH0Ib73AnhsiIiJqJxQR3jSTwQ0RERG1CzWbZjK4ISIionZBlgUUBcy5ISIiovZBUhQo7LkhIiKi9kJW4mVXqTAGN0RERHRcJCWeQhsGN0RERHScZEUAcdR3w+CGiIiIjoskK1AhPvJtAAY3REREdJyCcbSvFMDghoiIiI5TQFKgjpOZUgCDGyIiIjpOQYk9N0RERNROCCEQkgV7boiIiKh9kONs6wWAwQ0REREdB0kRkBUOS0XMmTMHJ510Emw2G9LS0jBlyhTk5+cf8ZwFCxZApVJF3YxGYyvVmIiIiGqTFQGhgD03Nb799ltcf/31+Omnn7B06VKEQiFMmDABHo/niOfZ7XYUFhZGbnv27GmlGhMREVFtkiIgxdmwlDaWT/7FF19E3V+wYAHS0tKwZs0anHLKKQ2ep1KpkJGR0dLVIyIioqOQFQFFEYij2Ca+cm6cTicAICkp6Yjl3G438vLykJOTg3POOQebNm1qsGwgEEB1dXXUjYiIiJqHpCgQCHc8xIu4CW4URcEtt9yC0aNHo3///g2W69WrF1577TV89NFHeOutt6AoCkaNGoV9+/bVW37OnDlwOByRW05OTks1gYiIqMNRlFjXoC6VECIudrq69tpr8fnnn+OHH35Ap06dGn1eKBRCnz59MH36dDz88MN1Hg8EAggEApH71dXVyMnJgdPphN1ub5a6ExERdVT7Kr3YtL8aWQkmAECh04cT8hKRYjU06/NUV1fD4XA06vM7pjk3NW644QZ8+umn+O6775oU2ACATqfDkCFDsH379nofNxgMMBia9wUmIiKiMFkRiKM9MwHEeFhKCIEbbrgBH3zwAZYvX44uXbo0+RqyLGPDhg3IzMxsgRoSERHRkQQlBeo4yrcBYtxzc/311+Odd97BRx99BJvNhqKiIgCAw+GAyRTu3poxYways7MxZ84cAMBDDz2EESNGoHv37qiqqsLcuXOxZ88eXHnllTFrBxERUUcVkOS4WsAPiHFw89JLLwEAxo4dG3V8/vz5uPTSSwEABQUFUKsPdTBVVlbiqquuQlFRERITEzF06FCsXLkSffv2ba1qExER0UFBWYmrNW6AOEoobi1NSUgiIiKiI/tpZzkkWcBh0gGIj4TiuJkKTkRERG1LzQJ+8TYsxeCGiIiIjomkKJCFgDrOook4qw4RERG1FbIiICsi7mZLMbghIiKiYyIpAnKcbZoJMLghIiKiY6QoAooMBjdERETUPkiKgCLibxE/BjdERER0TGRFxNVu4DUY3BAREdExkRQBgfhbLo/BDRERER0TWRaAYM8NERERtRNBWY67fBuAwQ0REREdo6AUfwv4AQxuiIiI6BiFZCXutl4AGNwQERHRMYrHHcEBBjdERER0DBRFQJLib+sFgMENERERHYPw1gvsuSEiIqJ2QhHhTTMZ3BAREVG7EK+bZgIMboiIiOgYyLKAooA5N0RERNQ+SIoChT03RERE1F7ISjzuKhXG4IaIiIiaTFLiNbRhcENERETHQFYEcFjfTaUniB+2lWFdQWVsKnUQgxsiIiJqMklWoEJ0vs22Ejfe+GkP5n6ZH6NahTG4ISIioiYL1rOvVHG1HwCQnWCKRZUiGNwQERFRkwUkBerDZkqVuMLBTSaDGyIiImprglJ9PTcBAEBWgjEWVYpgcENERERNIoRASBZ1em6KD/bcZDnYc0NERERtiNzA1gs1OTdZHJYiIiKitkRSBBRFRA1LuQMSPAEZAIeliIiIqI2Ra4KbWj03JQd7bawGLcx6bayqBoDBDRERETWRpAhIQqD2qFSxK5xMnGzVx6hWhzC4ISIioiY5Us9NitUQq2pFMLghIiKiJqnZNFNVK+emJpk42cKeGyIiImpj5Ho2zSw5OCzFnhsiIiJqcyRFOWxXqVo9N8y5ISIioramZliqhhAisjoxe26IiIiozQlKCtS18m1cfgm+UHiNG+bcEBERUZsTkOSoBfxq8m0SzTrotbEPLWJfAyIiImpTQnL0NPCafJs0W2xXJq7B4IaIiIiaJCgp9QY36fbY59sADG6IiIioCWRFQD5sX6ma1YnT7ey5ISIiojZGUhTIQkBdK4Io4bAUERERtVU1PTfqelYn5rAUERERtTmyIiCLQwnFQggOSxEREVHbJSsCioxIcFPlCyEohVcsTrWx54aIiIjaGEkREDg0LFVycGXiJIseOk18hBXxUQsiIiJqE8KbZh7afOFQvk18DEkBMQ5u5syZg5NOOgk2mw1paWmYMmUK8vPzj3re4sWL0bt3bxiNRgwYMAD/+9//WqG2REREJB22r1Sx6+BMqThJJgZiHNx8++23uP766/HTTz9h6dKlCIVCmDBhAjweT4PnrFy5EtOnT8cVV1yBdevWYcqUKZgyZQo2btzYijUnIiLqmGRZAKL2TKn4SiYGAJUQQhy9WOsoLS1FWloavv32W5xyyin1lpk2bRo8Hg8+/fTTyLERI0Zg8ODBePnll4/6HNXV1XA4HHA6nbDb7c1WdyIioo5gR4kbO0s9yHCEg5n7P9qIdXurcNOfuuP0vhkodPpwQl5is+8O3pTP77jKuXE6nQCApKSkBsusWrUK48ePjzo2ceJErFq1qt7ygUAA1dXVUTciIiI6NkFZiV7AL86mgQNxFNwoioJbbrkFo0ePRv/+/RssV1RUhPT09Khj6enpKCoqqrf8nDlz4HA4IrecnJxmrTcREVFHEpSUyNYLihCHNs1kcFPX9ddfj40bN2LhwoXNet1Zs2bB6XRGbnv37m3W6xMREXUk4Z6bcHBT6QlCUgTUKiC1mYehjoc21hUAgBtuuAGffvopvvvuO3Tq1OmIZTMyMlBcXBx1rLi4GBkZGfWWNxgMMBji5wUnIiJqqxRFQJIObZpZszJxitUQtUt4rMW050YIgRtuuAEffPABli9fji5duhz1nJEjR2LZsmVRx5YuXYqRI0e2VDWJiIgIgCwEZKFEApmSOFzjBohxz83111+Pd955Bx999BFsNlskb8bhcMBkMgEAZsyYgezsbMyZMwcAcPPNN+PUU0/FU089hcmTJ2PhwoVYvXo15s2bF7N2EBERdQQ1m2YatAd7biK7gcfXCElMe25eeuklOJ1OjB07FpmZmZHbokWLImUKCgpQWFgYuT9q1Ci88847mDdvHgYNGoT33nsPH3744RGTkImIiOj4SYqAUmvTzHjbMLNGTHtuGrPEzooVK+ocmzp1KqZOndoCNSIiIqKGyLKArCCyr9ShrRfYc0NERERtkKQoUT03JXG4OjHA4IaIiIgaSa61r5SsCJS6w8FNmo3BDREREbVBcq10knJPALIioFWrkGTRx7BWdTG4ISIiokaRZAEc7Lup2TAz1RZfa9wADG6IiIiokSRZgQrxvcYNwOCGiIiIGikoH9pXKl7XuAEY3BAREVEjBaRD+0rF6xo3AIMbIiIiaqTaO4Kz54aIiIjaNCEEQrKI9NyUHOy5yWDPDREREbVFsiIgH1zAT5IVlNesccPghoiIiNoiSRFQFAGNSoUydxCKAPQaNRLNulhXrQ4GN0RERHRUck1wo1ah2BXOt0m1GaBSxdcaNwCDGyIiImoESRGQhIBaVXvDzPgbkgIY3BAREVEjKLV6bg5tmBl/M6UABjdERETUCNLBTTNVKlWtaeDtrOcmGAwiPz8fkiQ1Z32IiIgoDsnKoU0zDy3g1056brxeL6644gqYzWb069cPBQUFAIAbb7wRjz32WLNXkIiIiGJPUhTUpA63u5ybWbNm4bfffsOKFStgNB5q1Pjx47Fo0aJmrRwRERHFB/ngsFRIVlDhCQKI3+BG29QTPvzwQyxatAgjRoyImv7Vr18/7Nixo1krR0RERPEhKClQqw4lExu0atiNTQ4jWkWTe25KS0uRlpZW57jH44nLue5ERER0/Gp2BK9Z4ybdbozbz/0mBzcnnngiPvvss8j9moa9+uqrGDlyZPPVjIiIiOJGUFLCC/jF8YaZNZrcn/Too49i0qRJ2Lx5MyRJwnPPPYfNmzdj5cqV+Pbbb1uijkRERBRjNcFNzbBUPG6YWaPJPTdjxozB+vXrIUkSBgwYgK+++gppaWlYtWoVhg4d2hJ1JCIiohiSFQH54L5SNcNSaXE6DRw4hp4bAOjWrRv+85//NHddiIiIKA5JigJZCOg1tVcnbkc9N//73//w5Zdf1jn+5Zdf4vPPP2+WShEREVH8UJRw7426DaxODBxDcHP33XdDluU6x4UQuPvuu5ulUkRERBQ/anpuJFlBlS8EoP6cG1kRUEEFTYxnUTV5WGrbtm3o27dvneO9e/fG9u3bm6VSREREFD9kRUCRgbJAePE+s14Di0FTp5wvJMOkV8Ncz2Otqck9Nw6HAzt37qxzfPv27bBYLM1SKSIiIoof4U0zBcpch/Jt6lvjxheU4TDrYNC2seDmnHPOwS233BK1GvH27dvx97//HWeffXazVo6IiIhiL7xppjjqGjdBRUaiWd+KNatfk4ObJ554AhaLBb1790aXLl3QpUsX9OnTB8nJyXjyySdboo5EREQUQ9LBfaWKXQ3PlJJkBVq1GjaDrpVrV1eTc24cDgdWrlyJpUuX4rfffoPJZMLAgQNxyimntET9iIiIKMZkWQBChZLIbuB1e268QRlmXf25OK3tmNa5UalUmDBhAiZMmNDc9SEiIqI4E5KVg9PAG+658YVkdEo0Qatp8qBQs2tUcPP888/jb3/7G4xGI55//vkjlr3pppuapWJEREQUH4KyArUah1YnrmeNG1lR4DDHfkgKaGRw88wzz+Diiy+G0WjEM88802A5lUrF4IaIiKidCUoKgpICl18CUHdYKigp0GvVsBqOaUCo2TWqFrt27ar3/0RERNT+BWUFFZ7wGjc2gxZmfXT44A1KMOm1sOjjI7hp0sBYKBRCt27d8Mcff7RUfYiIiCiOKIqAJAmUu8PBTX35Nn5JRopVD7U6tisT12hScKPT6eD3+1uqLkRERBRnZCEgCwXlnnAy8eG7gQshoAjAboyPfBvgGNa5uf766/H4449DkqSWqA8RERHFEVkRkBWBsgZ6bgKSAqNWDasxPoakgGOYCv7rr79i2bJl+OqrrzBgwIA6Wy68//77zVY5IiIiii1JEVCEQKn74DTww1Yn9gZlWAxamHSxX9+mRpODm4SEBPzlL39piboQERFRnJFlAVkBShpY4yYgychLNtW711SsNDm4mT9/fkvUg4iIiOKQpCiQFYHSmjVuagU3ihAAAGsc5dsATci5URQFjz/+OEaPHo2TTjoJd999N3w+X0vWjYiIiGJMVgQ8QQmeoAwgetNMf0iGSa+Jm/VtajQ6uHnkkUfwj3/8A1arFdnZ2Xjuuedw/fXXt2TdiIiIKMZkIVB+cI2bBJMOxlq5Nd6gDLsx+lg8aHRw88Ybb+Df//43vvzyS3z44Yf45JNP8Pbbb0NRlJasHxEREcWQJAuUuWs2zIzOtwnKCpIs+lhU64gaHdwUFBTgzDPPjNwfP348VCoVDhw40CIVIyIiotiTZAUV7hCA6DVuZEVAo1LBFkdTwGs0OriRJAlGY3TEptPpEAqFmr1SREREFB+CsnJodeJaG2b6guF8G0uc5dsATZgtJYTApZdeCoOhViKR349rrrkmaq0brnNDRETUPkiyAqcvhApvOLip3XPjDUrIcBih0zR5PeAW1+jgZubMmXWOXXLJJc1aGSIiIoofFZ4gqryhyKaZtXtuJCGQGIf5NkATgpuWWN/mu+++w9y5c7FmzRoUFhbigw8+wJQpUxosv2LFCowbN67O8cLCQmRkZDR7/YiIiDoqRREodPqhVgElruiE4pCsQKtRxdWWC7XFtC/J4/Fg0KBBePHFF5t0Xn5+PgoLCyO3tLS0FqohERFRx1TlC6HUFYBGpYY/FJ4ZnXpwjRtvUIZFr4VFH5/BTUxrNWnSJEyaNKnJ56WlpSEhIaH5K0REREQAgCKnDwICFd7wxKEkix56bbhPxB+SkWszQ6OOny0Xaou/LKBGGDx4MDIzM3H66afjxx9/PGLZQCCA6urqqBsRERE1rNofQkl1AA6jHiWuuhtmykLAYY6vLRdqa1PBTWZmJl5++WUsWbIES5YsQU5ODsaOHYu1a9c2eM6cOXPgcDgit5ycnFasMRERUdtT7PTDL4WnehdXR+fb+EMyDBp13G25UFv81qwevXr1Qq9evSL3R40ahR07duCZZ57Bm2++We85s2bNwm233Ra5X11dzQCHiIioAd6ghEKnHw5TeCZUTXBTs2GmLyTDYtTCrI+vLRdqO6aemzfffBOjR49GVlYW9uzZAwB49tln8dFHHzVr5Rpj2LBh2L59e4OPGwwG2O32qBsRERHVr9QVgDcowXIweCmuPjgsdXCNG19IRrJFD5UqPvNtgGMIbl566SXcdtttOPPMM1FVVQVZDu8SmpCQgGeffba563dU69evR2ZmZqs/LxERUXsTkGTsr/TBatBFgpfINHCbEYoQUAGwGeM33wY4huDmX//6F/7zn//gnnvugUZzqEvqxBNPxIYNG5p0LbfbjfXr12P9+vUAgF27dmH9+vUoKCgAEB5SmjFjRqR8Te/Q9u3bsXHjRtxyyy1Yvnw5dycnIiJqBmXuIFyBUGS/KCEESiI9N8Zwvo1OHZf7SdXW5Nrt2rULQ4YMqXPcYDDA4/E06VqrV6+OWpSvJjdm5syZWLBgAQoLCyOBDgAEg0H8/e9/x/79+2E2mzFw4EB8/fXX9S7sR0RERI0nyQr2V3ph1GqhPthrU+kNISgrUKuAFKseTl8IDrMORl385tsAxxDcdOnSBevXr0deXl7U8S+++AJ9+vRp0rXGjh0LIUSDjy9YsCDq/p133ok777yzSc9BRERER1ez1UJarS0WVuSXAACyE0zQatQISApSrIaGLhE3mhzc3Hbbbbj++uvh9/shhMAvv/yC//73v5gzZw5effXVlqgjERERtSBFEThQ5YNGrYoszOcNSnhv7T4AwHlDOkFWBNQqVVzuAn64JtfwyiuvhMlkwr333guv14uLLroIWVlZeO6553DhhRe2RB2JiIioBVX5QihzB5FUayPMj9YfgMsvITvBhHG90+ALyTDp43t9mxrHVMOLL74YF198MbxeL9xuN/d2IiIiasMKq8JbLeg04XlG1b4QPli3HwBw8fBcaNQqeIMS0uyGyBYM8ey4wi+z2Qyz2dxcdSEiIqJW5vSFUOLyI8F0qNfm/XX74AvJ6JJiwejuKQCAkKIgyRL/+TZAI4ObIUOGNHqxniNthUBERETxpaTaj6CsRGZAVXiC+OT3QgDAJcPzoFapEJIVaNVqWON0F/DDNaqWU6ZMaeFqEBERUWur2WrBbjzUa7N49V4EJQW90m04qXMiAMAXlGHWaWAxxPcU8BqNCm5mz57d0vUgIiKiVlZS7Yc3JCH7YIpJSbUfX2wqAgD8dWReZNTGG5KRkxieDt4WtI1aEhERUbMKSDL2V/lh1R/aSuG/vxZAUgQGdnJgUKeEyHFFUZBg1tdzlfjU5MEzWZbxzDPP4N1330VBQQGCwWDU4xUVFc1WOSIiIjo6IUSTN7Iscwfh8oeQ6TABAPZVerF8S3jRvr+OOLRQb0CSodeq28yQFHAMPTcPPvggnn76aUybNg1OpxO33XYbzjvvPKjVajzwwAMtUEUiIiJqyN4KD1bvqcTuMjcqPUFIsnLUc2q2WjDpDm218M4vBVAEMKxzEnpn2CNlfUEZJr0WljaSTAwcQ8/N22+/jf/85z+YPHkyHnjgAUyfPh3dunXDwIED8dNPP+Gmm25qiXoSERHRYZzeEHaWeSBJAhWeADQqNSx6LVJseiSY9bCbtDBo6/a4HL7Vwq4yN77fVgYAuGREblRZX0hGZoIRanXTeoZiqcnBTVFREQYMGAAAsFqtcDqdAIA///nPuO+++5q3dkRERFSvkKxgZ5kbQUlBhj08tCTJCjxBGbvKPAA8MOs1SLLokWQxwG7SwqzXQlEE9h+21cKbP+0BAJzcIwVdUqyR5/CHZKjVKiS2oXwb4BiCm06dOqGwsBC5ubno1q0bvvrqK5xwwgn49ddfYTC0jcV9iIiI2rp9FV6UVPuRfjCwAQCtRg2HSQ2HSQdFCHiDMg5U+bG30gujVoMEsx42oxbltbZa2FJUjV93V0KtAi4adqjXRgiBck8QnZPNUdsytAVNzrk599xzsWzZMgDAjTfeiPvuuw89evTAjBkzcPnllzd7BYmIiChauTuA3eUeOEz6SO/L4dQqFawGLdLtRmTaTTDptKjwBLGt2A21CpGtFmp6bf7UOw2dEg/tOlDtl2A1apGbbG5ysnKsNbnn5rHHHov8f9q0acjNzcWqVavQo0cPnHXWWc1aOSIiIooWkGTsLPNAUdDoHbpVKhVMeg1M+uj8m9/2VeH3fU5o1SpMP+lQr40kK3AHJPTPtsPchhKJaxx3jUeOHImRI0c2R12IiIjoCIQQ2FPmRbk7EJnCfTzXenNVuNfmjH4ZSLMbI49VeINItxuQUetYW9LkYanXX38dn332WeT+nXfeiYSEBIwaNQp79uxp1soRERHRIaXuAAoqvEgyGyJTuI/Vr7srkF/sgl6rxgUn5kSO+4IyVCogL9nSZlYkPlyTa/3oo4/CZApHi6tWrcILL7yAJ554AikpKbj11lubvYJEREQUDjp2lnqgVavqDC81lSJEJNfmrIGZSDyYMCyEQIU3gE4JbS+JuLYmD0vt3bsX3bt3BwB8+OGHOP/88/G3v/0No0ePxtixY5u7fkRERB2eogjsKnOjyhtCliN6qGhnqRu7yjzommpBTqK5Ub0tP24vw+5yL8x6Dc4b0ilyvMoXgt2oQ06S+Qhnx78mBzdWqxXl5eXIzc3FV199hdtuuw0AYDQa4fP5mr2CREREHV2xy499lT6kWPVRM5f2lHtw1/u/wx8Kr0qs16jRNdWC7mlW9EizoUeaFdmJpqghLFkRePvnAgDAlMHZsJvCe0uFZAW+oIQBnRKOu2co1poc3Jx++um48sorMWTIEGzduhVnnnkmAGDTpk3o3Llzc9ePiIioQ3MHJOwo9cCo00StNuzyh/DPz/6AP6QgxWqANyjBG5SxpciFLUUuAIUAAJNOg26pFvRIDwc7pa4A9lf5YDNqcc7grMj1KjxBZDhMSG+jScS1NTm4efHFF3Hvvfdi7969WLJkCZKTkwEAa9aswfTp05u9gkRERB2VrAjsLHXD45eQlWCKOj73y3wUVfuRZjPgmQsGw2rUorDKj20lLmwrcWNbiRs7St3whWRsPFCNjQeqo659/gmdItO8vUEJWrUKecnmBtfNaUtUQggR60q0purqajgcDjidTtjt9qOfQEREFCN7K7zYXFiNVKshsugeACxYuQtL1u6HQavG3PMHRm2ZUJusCOyt8GJ7iRtbS1zYXhLOz8l0GPH0BYNh1GmgCIFCpw/d06zonmZrraY1WVM+v49pnZvvv/8er7zyCnbu3InFixcjOzsbb775Jrp06YIxY8YcU6WJiIjoEKcvhJ1lblj12qjA5vttpViydj8A4ObTejQY2ACARq1C5xQLOqdYML5vOoDwAn0atSqSu1PlDSHBrI9anbita/JU8CVLlmDixIkwmUxYu3YtAoEAAMDpdOLRRx9t9goSERF1NCFZwa7S8KaYNQm/QHj37meXbQMA/OWETji5R2qTr63VqCOBTUhWEJBkdE62wKhr20nEtTU5uPnnP/+Jl19+Gf/5z3+g0x16wUePHo21a9c2a+WIiIg6on0VXhRV+5FqPZTc6/SFE4iDkoITchPw1xF5x/08Ze4AMhxGpNna18bXTQ5u8vPzccopp9Q57nA4UFVV1Rx1IiIi6rAqPUHsLvcgodammLIi8MSXW1DiCiDTYcQdE3ofd+KvOyDBoFUjL9kCdTtIIq6tycFNRkYGtm/fXuf4Dz/8gK5duzZLpYiIiDoiWREoqPBCPmxTzPk/7sLv+5ww6tS458w+sBqPb2tIRQg4fSHkJpnhqDXs1V40Obi56qqrcPPNN+Pnn3+GSqXCgQMH8Pbbb+P222/Htdde2xJ1JCIi6hBKXH4UOX1RWx8s31KCj347AAC4dXxP5CVbos4JSgqqvEG4AxL8IRmycvRJ0JWeIJIsOmQlHt/mm/GqyaHf3XffDUVRcNppp8Hr9eKUU06BwWDA7bffjhtvvLEl6khERNTu+UMy9pR7YdQdmh21vcSNF78Jj5ZMOykHo7qlRJ0TkGSUuQNIMOshKQKBoAxJFpAVBUB4qEmjVkGrVkGrUUOnOZhIrAh0TrZELQrYnhzzOjfBYBDbt2+H2+1G3759YbVa4fP5Iptqxiuuc0NERPFoV6kb+cVuZDqMUKtUqPIGceu7v6HMHcBJnRNx7+S+Udso1AQ2nZPDqw8LIRCSBYKyglDNTRLwhST4ggp8IRmSokCSFaTajOiXZY/ayiHetfg6NwCg1+vRt29fAEAgEMDTTz+NJ554AkVFRcd6SSIiog7J5Q+hoNILh1EHtUoFSVbw2BdbUOYOIDvBhL+f3isqsAlKSiSw6Z5mPZhcrIJWA5hQf2+MEDWBj4C+1nTw9qjROTeBQACzZs3CiSeeiFGjRuHDDz8EAMyfPx9dunTBM888g1tvvbWl6klERNQuCRFeRdgfVCKJwv/3wy5sOlANk06Deyb3iUouDkoKSt1+5CWb0T3N2qhdwAFApVLBoNXAatBCr21yym2b0uiem/vvvx+vvPIKxo8fj5UrV2Lq1Km47LLL8NNPP+Hpp5/G1KlTodG0z7E7IiKillLmDuJAlR/J1nAS8dd/FOPTDeFNL2+f0BM5tVYODskKSlzhwKZHmq3RgU1H0+jgZvHixXjjjTdw9tlnY+PGjRg4cCAkScJvv/3Wrru2iIiIWookKyio8EClAgxaDYqq/Xjlux0AgIuG5WJYl+RI2XBgE0BOkhk90hnYHEmjX5l9+/Zh6NChAID+/fvDYDDg1ltvZWBDRER0jIqq/Sh1BZFsMUAIgX8t3wZ/SEG/LDumnZQTKVfTY9Mp0YSe6baovaaorka/OrIsQ68/NO9eq9XCam14sy4iIiJqmC8Ynvpt0WugUavwxaYi/L7PCb1WjZv+1COSQCwdDGyyEsKBTXvPl2kOjR6WEkLg0ksvhcEQ3n/C7/fjmmuugcUSvZjQ+++/37w1JCIiaof2VXrh8oeQ5TChpNqP+T/uBgDMHJmHrITwsiqSrKD4YGDTK4OBTWM1OriZOXNm1P1LLrmk2StDRETUETi9Ieyv9CHRHB4R+dc32+ELyeibacefB2YBCG/FUOzyI9MRDmza64J7LaHRwc38+fNbsh5EREQdgqII7KnwIKQoSNYb8OWmIqzfWwW9Ro2bTwsPR8mKQJHTh8wEBjbHgv1bRERErajUHUCR049kiwGlrgD+74ddAIC/jggPR8mKQFG1HxkOI3pl2GDUMbBpKgY3RERErSQoKdhT7oFeo4ZWrcILB4ejemfYcNag8HBUicuPVJsevTPtDGyOEYMbIiKiVlLo9KHCE0SCWY9lf5RgbUEldBoVbjqtBzRqFSq9QZj1GvRIZ4/N8WBwQ0RE1ArcAQkFFV7YDDpUeYN49YedAIBLhuchJ9EMX1BGQFLQPc0Gu1EX49q2bQxuiIiIWlh4/ygPPAEJNqMWL3yzHZ6gjF7pNpwzOBuyIlDhDaJzshnpdkOsq9vmMbghIiJqYRWeIPZXhZOIv8kvweo9ldCqDw1Hlbj8SLcbkJds4cr/zYDBDRERUQsKSgoKKryAADwBCfO+Dw9HXTQ8F7lJZlR6wnk23dKsXKSvmcT0Vfzuu+9w1llnISsrCyqVCh9++OFRz1mxYgVOOOEEGAwGdO/eHQsWLGjxehIRETVVSFZwoMqHtQWVKHL6kWTW4d8rdsATkNE9zYrzhnQK59nIzLNpbjENbjweDwYNGoQXX3yxUeV37dqFyZMnY9y4cVi/fj1uueUWXHnllfjyyy9buKZERESNI8kKipx+rCuoxO/7nAiGFGQlmPDjjnL8srsCWrUKt5zWAwCYZ9NCGr1CcUuYNGkSJk2a1OjyL7/8Mrp06YKnnnoKANCnTx/88MMPeOaZZzBx4sSWqiYREdFRyYpAuTuAggovyt0BGLQaZNiN4SneniDmfRcejrpwWC7yki0odPqYZ9NC2tTg3qpVqzB+/PioYxMnTsSqVatiVCMiIuroFEWgxOXH7/uqsH5vFVx+Cel2E5KtBmjUKggh8O9vt8MVkNA11YK/DMlmnk0Li2nPTVMVFRUhPT096lh6ejqqq6vh8/lgMpnqnBMIBBAIBCL3q6urW7yeRETU/gkhUO4JYn+lDyWuANQqINVqgFZzKFgJyQreX7cfP+2sgEatwi2n9URIFgjKCvpnOJhn00LaVHBzLObMmYMHH3ww1tUgIqJ2pNITxN5KL0qqw1+eky166GoFNUIIrNpZjgUrd6PQ6QcATDsxB7lJZhQ6feieZmWeTQtqU8FNRkYGiouLo44VFxfDbrfX22sDALNmzcJtt90WuV9dXY2cnJwWrScREbVf1f4QNh5wIhBSkGjW1xlWyi9y4bUfd2FzYXikIMGsw8XD8jChXzqKq/3IdBiZZ9PC2lRwM3LkSPzvf/+LOrZ06VKMHDmywXMMBgMMBkbHRETUPA5U+uALysh0RH+pLqr2481Vu/HdtjIAgF6rxrlDsnHekGyY9Vrm2bSimAY3brcb27dvj9zftWsX1q9fj6SkJOTm5mLWrFnYv38/3njjDQDANddcgxdeeAF33nknLr/8cixfvhzvvvsuPvvss1g1gYiIOhCnL4Qipx8O06FcGbdfwrtr9uKT3w5AUgRUAE7rk4ZLhuch2Rr+cu0LypE8GxvzbFpcTIOb1atXY9y4cZH7NcNHM2fOxIIFC1BYWIiCgoLI4126dMFnn32GW2+9Fc899xw6deqEV199ldPAiYioVRRW+RCQFCRbDQjJCj7fWIiFv+yFKyABAAZ1cuDy0V3QNdUaOSckK6jwBtAtlXk2rUUlhBCxrkRrqq6uhsPhgNPphN1uj3V1iIiojXD6Qli3pxJGnRq/7XNGJQvnJJlx+ejOGJqbGMmlEUKgyhuCXwoPYfXOtEUlHVPTNOXzu03l3BAREcXKgSovApKCH3eU4z8H94dKMOtwyfA8jO+TDo36UIKwLyijwhtAgkmPHhlWpNuMUKuZQNxaGNwQEREdRU2ujV6jxn9/CadLnDUwE5eMyINZf+ijVFYEytwBqNRA1xQrcpPNMOo0sap2h8XghoiI6CgOVHkRlAS+/qMI7oCEnCQzrhjTNaq3xukLwRMMIdVqROcUC5Is+hjWuGNjcENERHQETm+41wYAPvrtAABgxoi8SGATkGSUewIw67Xom2lHpsMUtUoxtT4GN0REREew3+lFUBb4cP1+BCUFvTNsGN4lCYoQqPQEEVIEchLNyE22wGrgx2o84LtARETUAKc3hGKnH4GgjK82h1fInzmyM7xBGVW+EBLMOvRNsSDVZuCKw3GEwQ0REVEDanpt3lu7H7IiMDQvEV1TLXD5JfRIs6JTkgkGLROG4w2DGyIionrU9No4vSF8t60UAPDX4bmo9AbRLdWKbmnWo1yBYoXBDRERUT32V4V7bRat3gsAOKVHKpKtBqjVKnRKNMe4dnQkTOcmIiI6jNMbQlG1H4VVPqzZUwmNWoXpw3LgCcrISzbDpOdQVDxjzw0REVEtQohwr42k4L+/hHttJvRNh16rRoJZhwy7McY1pKNhzw0REVEtTl+412ZnqQf5xS4YtGqcNyQbQgB5yRauYdMG8B0iIiI6SAiBA1U+BEMK/vtruNfm7EFZkIVAVoIRyVx1uE3gsBQREdFBNb02G/Y7sbfCC6tBi4l9M6DTqZCTZOZaNm0Ee26IiIhwqNfGF5Tx7pp9AIC/nJANSQjkJZlhM+piXENqLPbcEBER4VCvza+7K1HqCiDZoseY7qmwmbTITDDFunrUBOy5ISKiDk8Igf2VPrj9Et5fG+61ueDEHAgIdE62cBXiNobBDRERdXhV3hCKXH58v60M1X4J2QkmDM5JQLrdiFSbIdbVoyZicENERB1aSFawv8qHKk8Qn/5eCAC44MRO0GlVyE0yQ6NmEnFbw5wbIiLqsNwBCTtK3Ch0+rB8Syl8IRndUy3omWZFpwQzEjn1u01icENERB1SSbUf20rccPslqATw5aYiAMD5Q3NgM+vRKYlJxG0Vh6WIiKhDkWQFO0rc+H2/EyFJQabDiEVr9kFSBAZ2cqBLqhl5SWaY9fz+31bxnSMiog7DE5Cwo9SNA1U+JJr1MOu1WL27At9sKQEAnDMoC8kWAzIc3D+qLWNwQ0REHUKpK4AdJW44/UGk2YxQAViwcheWrN0PABjdPRm5yRbkJpuh4/5RbRqDGyIiatdkRWBvhQc7yzxQQYVMuwnFrgCe/DIf+cUuAMDkAZmYNCADmQ4jUq2c+t3WMbghIqJ2yxeUsaPUjX2VPjhMOlgNWvywvQz/Wr4N3qAMi0GDm//UAwM6JSAoychN5v5R7QGDGyIiapfK3QFsK3Gj0htEus0IWRF44ZvtkVlRfTJsuH1CLyRa9Ch2+dEzzQY7949qFxjcEBFRuyIrAvsqvdhZ6oYQKmQ7TCio8OKJL/NRUOGFCsDUE3Nw0bBc+IIySlwB5CSaOfW7HWFwQ0RE7YY3KGFHiQf7q3xwGHWwGDT4anMx5n2/E0FJQaJZh7+f3gsDOzlQ5g5CpRLok2lDp0SuRNyeMLghIqI2TwiBUncAO0s8qPKFZ0MFJQVPfJmPH7aXAQBOyE3ALeN7wmrQ4oDThwSzHt3TrEhhAnG7w+CGiIjatJCsYE+5B7vLvdCqVMhymLCtxI0nvtyC4uoANGoVZozIw5Qh2fAeHIbqlGhGt1QrTHru9t0eMbghIqI2q9ofwo4SN4qr/Ug062HUafDh+v14fdUeyIpAms2AOyf2Rs90K8o9QQgI9M6wIifJwmGodozBDRERtTmKIlBU7ceOUjd8QRkZdhPcAQlzv9yM1XsqAQCju6fghnHdYdCqOQzVwTC4ISKiNsUfkrGrzI29FT6YdBpkOkzYdMCJuV/mo9wThE6jwlUnd8UZ/TIODkP5kZVgQvc0K/eL6iD4LhPRcSko9yLVZmDuArWKCk8QO0rdKHcHkGI1QKtWY9HqvXjn5z1QBJCdYMJdZ/RC52RLrWEoG4ehOhgGN0R0zAKSjKJqHww6NYMbalE1a9fsKvVAVgQyHSY4vSE8/fUfWL+3CgAwrlcqrj21O7QaVXgYyqRHtzQrUm0chupoGNwQ0THzhxS4AhK8ASnWVaF2LGoLBaMOVqMW6/dW4aml+ajyhmDQqnHtqd1wWp90VPtCqPCG0CnRjK6pFg5DdVB814nomPlDMgIhGU4fgxtqGZWeILaVuFDhCSHNZoBapcJbP+3Bu6v3QgDISzLjrjN6IyvBhKJqH/RaNfplOZCVYOIwVAfG4IaIjpk/JCMoCbiDEkKyAp1GHesqUTshhECh049tJS6EJIFMhxEVniCe/Cofmw5UAwAm9svAVSd3gawIFFX7kG43omuKFQ4z94fq6BjcENExc/pCMOs1CEgyfCGZwQ01i5CsYHeZB7vLPTDptEiy6/Dr7go88/VWuPwSTDoNbhjXHWN6pKDcHYRQCfRIsyE32cyfQQLA4IaIjpGiCHj8Mix6LdxBCf6gzB2V6bh5AhK2l7hR6PQh2WKASgW88u0OfLqhEADQLdWCOyf2RpJFj0KuXUMNYHBDRMfEL8kIyOHgBsHwhoVEx6PMHcD2YjecvhDSbUYUVHjx5Ff52FvpAwCcPSgLM0fmwROUUeULIi/ZjC4pVhh1nKlH0RjcENEx8YeUg7ssq2HQqJlUTMdMOTjNe0epG4AK6XYDPlp/AG/+tAeSIpBo1uGW03piQCcHSl0BWIxa9M92IMNuhErFpGGqi8ENER0Tf0iGAKBWqWDQauAOSJBkBVrmPFATBCQZO0vdKCj3wmbUwR9ScP9Hm/D7ficAYETXJNwwrgfUKqDEFUBWghFdU62wGvjxRQ3jTwcRHRNvUIIa4W/NBp0aVb4gfCEZNgY31EjV/hC2FbtQ6gqvNvzLrgq8uGI7PAEZBq0aV53cFaf1TkOZJwC9Ro2+mTZkJ5o5xZuOisENER2Tan8Iem04kNFp1AjJIhzcMKmYGqHE5cfWYjd8QQl2ow7//mYHlueXAAB6pFlx+4ResBt1KHb5kWE3oguneFMTMLghoiYLyQq8QSUS3AAABOAPKrGrFLUZRU4/thRVAwKo8IRw74cbUVwdgFoFTB2ag6lDO6HKF0JAltEn047sBBOHO6lJGNwQUZP5QjICkoxEkz5yTK8ND03lwhzDmlG8O1DlQ35RNQSALzcVY/HqvVAEkGYz4O8TeiE3yYwyTwDpdiO6pFiQYNYf9ZpEh4uLUPjFF19E586dYTQaMXz4cPzyyy8Nll2wYAFUKlXUzWg0tmJticgfkiHJImrBNINWDbdfgqyIGNaM4tm+Si/+KKpGUBJ48sutWPRrOLD5U680PDttMJItegRCMnpn2NA/28HAho5ZzHtuFi1ahNtuuw0vv/wyhg8fjmeffRYTJ05Efn4+0tLS6j3HbrcjPz8/cp9TAYlaVyCkAIgOYgxaDar94aRizmSh2oQQ2FvhxdZiN4KSgrlf5WNXmQcWvQbXj+uOE3ITUeULItVmQLdUK4MaOm4x77l5+umncdVVV+Gyyy5D37598fLLL8NsNuO1115r8ByVSoWMjIzILT09vRVrTEQufwhadfSfD51GhaCkwBeUY1QrikdCCBRUeJFf7IY/KOOR//2BXWUeJJh1eOTcAeiZboMvJKFXug0DOyUwsKFmEdPgJhgMYs2aNRg/fnzkmFqtxvjx47Fq1aoGz3O73cjLy0NOTg7OOeccbNq0qcGygUAA1dXVUTciOnZCCFT7JRi00avCqlQqCISHrIiA8OJ8u8s8yC9ywe2X8NBnm7G/yodUmwEPnNUXRp0aiRYdBuckokuqlftCUbOJ6U9SWVkZZFmu0/OSnp6OoqKies/p1asXXnvtNXz00Ud46623oCgKRo0ahX379tVbfs6cOXA4HJFbTk5Os7eDqCMJSAoCkgx9PR9EOo0aTl8wBrWieKMoAjvL3NhWEt5O4aFPN4UX4XMYcf/kvrAYtOieZsWA7AQkWthbQ82rzYXJI0eOxIwZMzB48GCceuqpeP/995GamopXXnml3vKzZs2C0+mM3Pbu3dvKNSZqX/whGSFJRE8DP8io1cDlk6EwqbhDkxWBHaVubC9xo8wVxEOfbEalN4TOyWbcO7kvTHoNeqXb0C3VWu/PEdHximnWX0pKCjQaDYqLi6OOFxcXIyMjo1HX0Ol0GDJkCLZv317v4waDAQYDd4slai7+kAJFiHpXiTXowjOmfCEZFiYVd0iSrGBHqQe7yjwodgbw2Bdb4AvJ6JVuw83je8CoU6NXhh1ZDu4LRS0npiGzXq/H0KFDsWzZssgxRVGwbNkyjBw5slHXkGUZGzZsQGZmZktVk4hqOdLu33qNGgFZgY95Nx2SJCvYVuLCrjI3Cso9eOR/f8AXkjEg24FbxveAWa9B30wHshNMDGyoRcX8q9Vtt92GmTNn4sQTT8SwYcPw7LPPwuPx4LLLLgMAzJgxA9nZ2ZgzZw4A4KGHHsKIESPQvXt3VFVVYe7cudizZw+uvPLKWDaDqMOo9kn15tsAB5OKBThjqgMKSDJ2lLhRUOHF9hIPnv16KyRF4MS8RFw5pivMBg16Z9qQZuO6ZNTyYh7cTJs2DaWlpbj//vtRVFSEwYMH44svvogkGRcUFEBda8ppZWUlrrrqKhQVFSExMRFDhw7FypUr0bdv31g1gajDkGQFnmDdmVK16dQquPyhVqwVxZI/JKPUFcC+Si+qfCFs3l+NF1dshyKAMd2T8dcRebAYteiTYUOylSkC1DpUQogOlflXXV0Nh8MBp9MJu90e6+oQtSnugIRfd5XDbtQ3mAjq9IWg1agwrHMS1Ny9ud3yBWWUuPzYW+mD2y/Botfg+21lmPf9TgDA+D5pmDq0ExwmPXpn2rh+DR23pnx+x7znhojaDn9IRlAW0GkaDloMWjU8QQl+SYZZzz8x7Y0nIKG42o8DVT64AxKsBh1SrXos/HUvFq8JL8nx54GZmDwgE4kWPXpn2mHnTvHUyviXhyjG3AEJ1b4QshJMsa7KUdUs0HekZFC9Vo1Kb3ilYgY37YfLHzoY1PjhDUqwG3XIcpiwubAaL3yzHfsqfQCAC07shHG9UpFqM6BPpp2z5igm+FNHFGPegIQDVT6kWA1xv+aHJyBBc5RZLmqVCooQnDHVTjh9IRQ7/Sh0+uALKXCYdMhOMMPtl/DiN9vx5ebwUh4JJh0uH90FPdOtyHAY0SvDDpO+4dwsopbE4IYoDniDMtwBCUna+M1LqNl2oTEBmFathsvf8JRxin/+kIxdZW4UOwMIyDISTHokWQwQQuD7baWY9/1OVHnDieOn903HJcNz4QvJyEowoWe6DUYdAxuKHQY3RHHAF5Th9ktIiuNl6IOyAn9IhqERwY1Bq4bTF4IQguuZtEFBSUF+kQuFVT4kWQxI1odnORVX+/HStzuwZk8lACA7wYQbxnVHbpIZrkAIuUlmdE+zxX0PJLV/DG6I4oAsBMo8fuQkxe/iZv6QgoCkwNqIPBqDVgNfSII/pHBooo0Jb53gQqHTj3S7EVqNGrIi8PFv+/H2zwUISAq0ahUuODEH5w7JhtMXgqQo6JdlR1aCud6Vq4laG4Mbojjh8oW3LYjXJFx/SIasKNA2Yudmg06NKl94pWIGN22HEAK7ytzYU+5DqtUArUaN7SVu/OubbdhZ6gEA9Muy4/px3ZFiMaDcE0SqTY9uqVZO9aa4Ep9/RYk6GLVKBb+kwO2X4jq4gWjct3K1SgUFTCpua/ZVerGz1INEsw6yIvDq9zvxye8HoAjAatDistGdcVrvNDh9Eqr9IXRLtSAv2cJhKIo78flXlKiDUakAtSo8MyXNHp/L0zt9oSZ9iGlUarj9IQDxP8Wdwvk0W0vcsBq0CEoKZn+yKdJbc0qPVFx5chdYDVoUu/ywGXTok+lAqs0Qt8Oo1LExuCGKEyadFuWeILoq9e+4HUuKIuDxyw3uKVUfJhW3HRWeIPKLXNCp1PAFZdz30UYccPqRYNLhlvE9MTQvES5/CCWuALISTOiWauX6NRTX+NNJFCfMeg0qfUG4AxIcpvha0dUvyQjIMixNGDIzaNXwhWQEJIXTgltASFZwoMoHm1GHRLPumANIlz+ErUUuhGQFgZCC+z/eiDJ3EGk2Ax4+pz/S7UYUV/uh1ajQN9OG7EQmDVP8Y3BDFCd0GjUkScRncBNSEJQUJJqb0nOjQbVPgi8oM7hpZrIisL3Ehd1lXuh1amQ5jOiUaIatidsc+IIy8otcqPaH4PKH8MAnm+HyS8hJNOHhc/rDYtCiqDq8wGS3VCsS43ipAqLaGNwQxRGtRoUKTwDZcbYVgz8kQyCcKNxYGvWhlYoTW65qHY6iCOwsdaOgwos0mxGKECio8KLEFUBuohmZCaZGBZNBScHWYhdK3QGUuQJ49H9b4AvJ6JFmxeyz+kERAlW+ELqmWJGXYj7iTvBE8YbBDVEcMeu1cHpDCEhyXH2YeIMS1Gj6UIRapYInwJWKm4sQAnvKPdhZ6kaS5dB2HVmO8HYI+cUuFFX7kZtsQbrN0OC0fVkR2F7qwgGnD3vKvHhqaT5CssDATg7MmtQbnoAMg06N/tl2ZNiNzJmiNofBDVEcMek0KHWH4PZLMFjjJ7hp6kypGgatGlW+UAvUqGPaV+nF9lI3Esz6Or0zVqMWFoMGVb4QNuxzosimR06SGSkWA9S1cmRq1rIpKPdi8/5qvLhiOxQBjOiahJv/1BNOXxApVgN6pNngMMfX8ChRYzG4IYojGrUKQoSTPJOthlhXB0B4+MIXlI8tuNGFZ9/4Q8y7OV6FTh/yi92w6LUNroWkUqmQaNbDbhSo8ARR4XEi3W5AXpIlEqjsrQivZfPTjgosWLUbAHBa7zRcNroLqg9uodA11cr3i9o0BjdEccao1aDUHURecnxMoQ7PlFKQeAyLCxq0Grj8EoOb41Ti8iO/0AWjVtOopGGNWoVUmwFBSUGR049ydwDZCWaYDRpsLXHhi41FeH/dfgDAOYOycM7gLARlGb3SrchJsnA2FLV5DG6I4oxJr4HHL8ETlGGNg7VE/CEZkiygqyd/Y2+lFw9/uhln9s/ElCHZdR7XqFWQDyYVJ7RCXdujCk8QWwpdABA1i67cHcDnm4qgUamQYtUjxWpAis2AVKshEkjqtWpkOkzwBiXsLPNArQLeXb0XX/9RAgC4eFguTu6ZAqNOg+7pVqTZ4nMBSaKmiv1fTiKKYtRpUOENwO2X4iK4CYQUAKLexxb9uheFTj/e/GkPTu6RUu9QmloFJhUfI6cvhD8KqxGSlajAY+2eSjy1NB/V/vpfV6tBi1SbIRL0pFoNSLbq8evuSvywvQwqAFeM6YITOychw25A93RbXPysETUX/jQTxSG1So0qbxAZjth/k3b5Q9Cq6/balLsD+GF7GQAgKCt4b80+XH1qtzrl9BoNqrxMKm4qd0DCH4XV8AVlpB/ckkNWBN7+eQ8Wr9kHAOiSYkHPNCtK3QGUuoMocwXgC8lwByS4AxJ2lXnqXFejVuHqU7picE4COidb0DmFe0NR+8PghigOmXUaVHiCkOTG7cLdUoQQqPZL9U5L/9/GIsiKQLJFj3JPEF9sKsK5J2TXGdo4tFJxfE1vb2lBSUGZOwABwKrXwmzQ1Du0Vx9fUMaWwmo4fSFkHgxsyt0BzP0qH5sOVAMAzhyQiStGd6kTmHgCEsrcgXDA4wqg7GDQU+YOIKQomNg3A4NzE9A9zYoshylqJhVRe8HghigOmfUalHvCWzEkmGO3KmxAUhCQZJi02sOOy/h8YyEA4G+ndMWnvxdiw34n3l29DzeM6x5V1qBVw+2R4A8qHSK4CckKSlwB7K3wosobhAoqaNQqGPUaOExaJJj0sBrCwU59r4c/JCO/qBpl7gAyHSaoVKqoYSiTToMb/9QdJ/dIrff5LQYtLAYt8pItUIRASFYQksL/ekISEs169Ey3IYmrDVM7xuCGqBUJIVDtk8Krwh687Sr1oNwTxHlDsiOzo7QaNSRFgcsf2+DGH5IRkgQcxujegRX5pXD5JaTZDBjeJRkOkw53v78BX/9RjPOHdkJGrZ3NtRo1ZEWBLyTDgfa7bkpIVlDqCqCgwgunLwiTVotMhwlqlQqSrMAfUlBaHcT+Sh80KjWMejXsRh0SzXpYDBpYDFqoVSpsPbgQX4bdBCGAN37aHRmG6ppqwV0TeyOr1grWQgiEZIGgrBwMZBRIioBKBaiggk6jgk6rhtmgQWZCeJsGk779B5nUsTG4ITpOihJepr7s4DL24cAlGLlfVut+uTuIoKzUe51Esx5/6p0WuW/QhoemcpLMrdWUOvwhBbKI3qVcCIGPfzsAADhrYBY0ahX6ZTkwJCcB6/ZWYdGvBbj5tJ5R11GpVPAG22dSsSQrKHWHe2oqPCGYdBqk20xRr5lWo4ZVo4bVGP6TKysC/pCMSk8QhU4f1CoVDDo1DNpwflKazYgqb/CIw1BuvwRnIAh1JIDRwKTXINVmgEWvhUGnhl6jhl6rhkGrjunwJlFrY3BDVA9ZESj3BFDmCkZ6WMoPBiiR4OVg4FLuCUJW6p9N1BCbQYuUg7NZfCEZG/dX4+2fwzOOavIyzHoNnL5QTNeI8QalOpsu/LbPiYIKL0w6DU7vmx45fvHwPKzbW4XlW0owdWhOVO+CXqOGs52tVCzJCsrcQeyt9KLCE4RBo0aG3dioNWI0alVk+AgAFBEOdgKSgjSbAb/vc+LpBoahApKMcncQRr0avdJscJj1MGjDQUxjc3qI2jsGN9RhhGQlOkBx1ephqbkdDGYqvEGIpsUrSDDrwmuN1Kw5YjVETcdNrvVY7WCloNyDs174ESWuAL7YWISzBmUBCE8Jd/pCcPmlmAU31T4J+sM+MD9aH1787bQ+aZEPZwDolWHDiXmJWL2nEv/9pQB/n9Ar8phBp4EnICEoKW1+Zo6sCJQd7Kkpdwdg0GqQbmtcUNMQtUoFs14LgzZ6NlTtYShZCa86rAiBnCQTcpKavgs4UUfB4IbatIAkR/Wi1AwBlR52v8wdaPJ0ZJUKSDLXLI52KGCJBDAHF0xLsRqQZNEf84e2UafBnwdm4u2fC7Bo9V6c1icNZn04/0IAqPaFkGpr/a0YJFmBJxg9U2p/pQ+r91RChfCQ1OEuHp6H1Xsq8e3WUlxwYk5kSM2gVaPCK8EXOrZtHGJJUQT8kgx/KJw3VOT0odwdhE6jRrrd1OigRggBb1BGtT+Eap8Elz8U+X/43xC2l7qxozQ8fbv2MJTTF4I7EEKK1YC8ZAtSrPq4WL2aKF4xuKG44w1KKHMFo5Jua3pUag8VlboDcDWwiFlDNGoVkiz6SICSenBV19q9LTXBTJJZ32p5CqO7p2D5lhIUOv34+LcDuPCkXADhKeFl7gC6pFhafcquX1IQlGTYjYcSmj/5PZxrc2LnxKhhpxrd06wY0TUJP+2swDu/FOCuM3oDAHQHk4r9ITlqld14EzgYxARC4X+d/iDcPhkBWUZQUqBAQK/WINXa8I7bTl8IW4tdyC92YVuxG2XuwMFARmrU8GXtYSh/SMa+Ki9sBi36ZdmR4TBx6ImoERjcUIsTQsAdkOok2ZY2kHTrDcpNur5Oo4ruUYkELIcHMAYkmHRxua6HRq3CX0fk4Ykv8/H+2v2Y1D8TDpMOZr0WTn8QnqDU6kMQ/pCMoCyg04RfL3dAwrItxQCAcwbV3WqhxkXD8vDTzgr8sL0MF5R50CXFcvARFbxxtFKxEAKugASXX4I3IEXym/ySEg5CRDgoM2jVsOi1SDSroT6styQoKdhZ6kZ+sQtbi13YWuxGUbX/iM9r1IVnSdmNOthNWtiNOtiMWthNOjhMOgzNS0SSWY/iaj9UaqBLsgU5SeaoIUAiOjL+ttAxqW9K8+E5LKW1hosCUv0zhBpi0Kpr7ZWjrzMcFMlpsRpgN2nbRRf96O4p6Lp2H3aWevDemr24YkxX6LVqhORwcBiL4AZA5LVdurkI/pCCvCQzBnZyNHhelxQLxnRPwQ/by/DfXwrwjzP7AAAMGnWD2wW0ppCsoNITRFF1eEPJgKxAo1LDcHBmUbJZ22CvTHG1H5sOOJFf7MbWYhd2l3kg1dMb0ynRhJ7pNvRMtyE7wQRHJIjRHXFYTojwzLsSdwBpNgNyk8xIsnAIiqipGNxQhKIIVHqD0QFKPUm35e7gEac0N8Si10QCk2TLoSAltZ7eFquhfQQsTaFWqTBzRGfM/mQTPttQiLMGZSHNZoRWpUKFO4hMR91hoJbkCUjQHHwPZEXg09/Di/adPTjrqO/N9GG5+HF7GVbtLMf2Eje6p1lh0GrgDkgIyUpMhlbcAQnl7gAKnX5U+0LQqFSwm3RIOUKythACBRVerNxRjp92lmNnPdsZOEw69Ey3otfBYKZHE/dpCskKfEE5vKaQImAzatE/24F0W8NDX0R0ZAxu2jlJVlDhDUZNaY4MAR22JkvFsUxpNmojSbVHSrpNtuph1vPH7WiG5CZgQLYDG/Y7sfCXvbjptB4w67Wo9IVadaZRzbYLNc/3085ylLgCsBu1OLVn/Svj1pabZMapPVOxYmsp3v55D2af1Q8GnRpVviB8IbnVghv5YMBeUu1HqSsAnyTDotMi7QizmxQhsLXIhVU7y7FqZzkKnYeGmdQqoGe6Db3SbeiVEQ5m0myGRgfiQggEpHDukT+kQBEKtFo1zFotMhONcJjCuV5cZI/o+PDTpplUeYOY+2U+uqRY0DXVgi4pVnRKbJnkv6CkoNwT7kGJxZTmml6WZIs+ZlOU2yuVSoUZI/Nwx3u/Y9mWYpw7JBtZCSaUugJwByQkaVtnteKgHP4ANhwMbmoW7ZvUP7PRWyhceFIuvttWitV7KpFf5EKvDBuCkoA/KMPewkNsvqCMck+4l6bKG4IK4UA8yVL/rDNJVrBhvxOrdpbj550VqPAGI4/pNCoMyUnEyK7JOKlLUqMSooUQEACEOJSk7JfCw3wGjRomvQYZDiNsRh3MBg0seu1xTSUnomgMbprJ9hI33v65IOqYVq1CbpIZXVIs4Vtq+N+uKVak26O/7flDclSPStS05sOSbpu6GJpKhfAwUD1JtzXDQzW9L8lWPWdjxFjvDHtkxtGbP+3BP87sA0UIuP1Sq+0H5A8qCIQUWPVabCt2YXNhNbRqFSb1z2j0NbITTRjXKw3LtpTg7Z/34KFz+kMFwBdqWsJ4Uzh9IRQ7/Sh2+eEJSDDptEix1D/rTREC6wqq8O3WEvyyuwKewKF6mfUanJiXhJHdknFCbgLMei1CsgKnL4QDVT5AJQCoAIT/rfkfhABU4fs1ycc6rQpWoxa5ZhMsRi0sei1MOk1cJrYTtRcMbppJitWAa0/thvxiFw5U+bC73AN/SMHOMk+94/QmnQa5SWYEZQVlrgBcTZxFolGrDgUstlqzguoZHkqy6PmtsI25ZHgeftlVgVU7y7G12IVkix6lbj9ykkytkovkl2TIIrwj+ccHp3+P6ZGCZGvT1tu58KRcrNhainV7q7DpgBPpdiOqvCHkJTdvfV3+EA5U+VFY5UNAUmA36ZDlqP+18odkfJNfgo9/O4B9lb7I8QSTDsO7JGFEt2QM6pQQCfL9IRnFB2dAJVv1SLYYoFIBavWhIEalCn+JUKsOP6aCQatmDydRK2Nw00w6p1hw16TekfuKIlBU7ceug8HNrlIPdpW5savMg72VPvhCMvKLXVHX0GvUSLbq6/SutKUpzdQ88pItkV6P11fuxj1n9oHbH14ErzVyl8IzpVQodwfww7YyAMDZ9SzadzQZDiPG907Dl5uL8c7PBbh7Um94AhIkWWmWZFlPQMKBKh8OVIV/pxLN+gYDsHJ3AJ9tKMQXG4siXyZMOg1O65OGMd1T0DvDHvkSIA72lDn9QRi0amQ4jMh0GJFo1vP3jqgNYHDTQtRqFbISTMhKMGF095Sox0Kygr0VXuyp8MKsOziDyNJ+pjRT87hoWC6+3VqK3/c7saXYhQyHEW6/1CrBjdMXgl6jxucbiyApAn0y7eiRbjuma11wUg6WbSnB7/ud2FbiRrrdgHV7q5BmM8BhCk+PbmrPojcoobDKj/1VPniDMhJMugbzabYWu/Dxbwfww/aySMJ8ut2AswdlYXyf9KjXU1YEqv0heIMyLAYNuqdZkWY3tniOEBE1LwY3MaDTqNE11YquqdZYV4XiWJrdiDMHZOLj3w7gzVV7cMcZPeH0hZBmN7bo8yqKgMcvAwL4fGN4+vc5g5rea1MjzWbExH4Z+GxDIRb+uhcPn90P3oCMP9wuaNXhfJR0mwEOsx52Y8NrzADhHqUipw/7Kn1wByQ4jHpkJ9TNQ5IVgZ92luOj3w7gj8LqyPH+WXacPTgbwzonRQVUNfk0QVmBw6RDlxQLUqwGzloiaqMY3BDFsQtOzMHSzcXYXurGxv3VcJj06KqIFs2h8kvh7QZ+3l2Oar+EVJsBI7oeX5LM1KGd8NXmIvxRWI1NhdU4ITcRiQgHFZ6AhG0lbqiggsWgQarNgESLHvZaC975QzJKqv0oqPTB7Q/BZqg/p6bcHcD328rwye8HUOIKAAgn9p/cIwVnD8pG97ToLxTeYHiFYiGAJKsO2QlmJtUTtQMMbojimMOkw7lDsvHOLwV4b80+9O9kD/dYtOD+TDV7K32+oQgA8OcBmccdTCVbDZjUP9wL9fbPezAkJwEqlQo6jRoJZj0SEO5tcQck7CrzYFeZB2ZDeKaTWa/F/iovnL4QrLWCmpAc3vpgS1E1thS5sKXIhTJ3IPKcdqMWk/pn4swBmVGzzIKSApc/BL+kwKRjPg1Re8TghijOnTM4C5/+fgCFTj++yy9D/6yEFg5uZGwpcmFPhRdGnRoT+jZ++veRnD+0E77YVIStxW7M+XwLMhxGJJp1SDTrkWjWI+Hg/zPsRigivFbNvkofJEWBRa+FXqPGxv3OSDCzo9SNkBy9iJNaBXRNteKMfhkY2ys1siaPrAi4/CF4gjJ0WhUSTDp0t4cDGu7ZRNT+8LeaKM6Z9VpMOykH//l+Fz77vRBThmQhu54duZuLJyBh+ZYSAMBpvdNhNTb8ZyIoKaj2h6DTqGHRa46YL5No1uOsgVlYsnYfVu0sb7CcVq2Cw6SLBDw6jRrbStxRvTI17EYtemXY0DvDjt4ZNvRIs0XyZGrWBnIFQlCpAJtRh95JJiSaDbAZteylIWrHGNwQtQGT+mfiw/UHUOoKYMma/RjYKaHRKwU31fYSN37f5wQAnNXA9G9fUIbTH4RKFV5vKSApKPcEISkKzDotrEZtvXkrFw/PRdcUC0rdAVR5g6j0hlB58N8qTxCugARJESj3BFHuCUadq1YBnZMtUcFMpsMYybsRQkAR4Twat1+CJAQseg06J1uQbNXDYdJxryaiDoLBDVEboNOocfGwXDy7bBs+/u0Arj61K7qktMxsu09/L4QAcGJeIrITo3uIPIGDa79oNMhOMCHTYUKCWXdw2EeC0xdEiSuASl8QIUmBUauBxaCNLGKn06hxyhH2pgrJCqq8oUObtHqC8AYkdEo0Iy/ZDINWAwXi4MLA4bWkgPBdNVRQqQGdWoU0hwFpNiMcJh0X0CPqgBjcEMUBIRDZy6mhtY7G9krDknX7sbfCixeWb8e1Y7tBEeFzFSGgCAFx+H0c3KwxpMAdkOAJSvAEZHgCUvgWDP/fHZDgDcpwBySsL6gCAJx9cPq3EOHAxRUIwaTXoGtKeO2X2nk/Wo0KiRY9Ei165CZZ4ApIqPaFUOLyw+WTUOENQqdWw2LQwKTTQACQZIGQrBy8CUiKgpoMmmSbHhkOI3QaNUw6DXRaFbTqcAKyVq2GShVepVutUkGtBjSqmv+roNOouEkrUQenEqKp2yq2bdXV1XA4HHA6nbDb7bGuDhGcvhDyi1zwBiUEDq4MXLNkv1GniZqp9NPOcjzyvz9avE65SWY8N20wXIHwqsgWgxbZDiPS7MYmJeAKEZ4BVe2XUOYKD0X5Q/LBmVLhYEWnCQc9Fr0WBp0Geq06fNOojxjsEVHH0pTPb369IYoxh0mHE/MS4QvJ8AZleAIhVHpDcAckuN0SJKFApwoHO0NyEjCscxI2F1ZDp1FBpVJBfXAPo5o9jSL3VYf2ODJo1TDrtbAatJFAwmI4eNNrDv4//G9JdQA2oxbFrgASzOEF7VJthmMa3lGpVLAZw6sQZyeYwvkwAQla9aEApmYtGyKi5hIXwc2LL76IuXPnoqioCIMGDcK//vUvDBs2rMHyixcvxn333Yfdu3ejR48eePzxx3HmmWe2Yo2JmpdarYoEG6k2AzoDCEgyvAEZ3pAMpy8Ip0dCdSCES0d3RrdUC3pltEzP4+YDTniCMjolmpBsMTRr8GHWazlkREQtLuZfmRYtWoTbbrsNs2fPxtq1azFo0CBMnDgRJSUl9ZZfuXIlpk+fjiuuuALr1q3DlClTMGXKFGzcuLGVa07UsgxaDRItemQnmNA304FhXZNwUuckDM1LRIa95aaC90i34YTcRGQ6TOxVIaI2KeY5N8OHD8dJJ52EF154AQCgKApycnJw44034u67765Tftq0afB4PPj0008jx0aMGIHBgwfj5ZdfPurzMeeGiIio7WnK53dMv5YFg0GsWbMG48ePjxxTq9UYP348Vq1aVe85q1atiioPABMnTmywPBEREXUsMR38LisrgyzLSE9Pjzqenp6OLVu21HtOUVFRveWLiorqLR8IBBAIHFrZtLq6ut5yRERE1D60+wH1OXPmwOFwRG45OTmxrhIRERG1oJgGNykpKdBoNCguLo46XlxcjIyM+jfry8jIaFL5WbNmwel0Rm579+5tnsoTERFRXIppcKPX6zF06FAsW7YsckxRFCxbtgwjR46s95yRI0dGlQeApUuXNljeYDDAbrdH3YiIiKj9ivmCE7fddhtmzpyJE088EcOGDcOzzz4Lj8eDyy67DAAwY8YMZGdnY86cOQCAm2++GaeeeiqeeuopTJ48GQsXLsTq1asxb968WDaDiIiI4kTMg5tp06ahtLQU999/P4qKijB48GB88cUXkaThgoICqNWHOphGjRqFd955B/feey/+8Y9/oEePHvjwww/Rv3//WDWBiIiI4kjM17lpbVznhoiIqO1pM+vcEBERETU3BjdERETUrjC4ISIionaFwQ0RERG1KwxuiIiIqF1hcENERETtSszXuWltNTPfuYEmERFR21Hzud2YFWw6XHDjcrkAgBtoEhERtUEulwsOh+OIZTrcIn6KouDAgQOw2WxQqVTNeu3q6mrk5ORg79697X6BQLa1/epI7WVb26+O1N6O0lYhBFwuF7KysqJ2LqhPh+u5UavV6NSpU4s+R0faoJNtbb86UnvZ1varI7W3I7T1aD02NZhQTERERO0KgxsiIiJqVxjcNCODwYDZs2fDYDDEuiotjm1tvzpSe9nW9qsjtbcjtbWxOlxCMREREbVv7LkhIiKidoXBDREREbUrDG6IiIioXWFwQ0RERO0Kg5vDfPfddzjrrLOQlZUFlUqFDz/8MOrx4uJiXHrppcjKyoLZbMYZZ5yBbdu2RZUpKirCX//6V2RkZMBiseCEE07AkiVLosp07twZKpUq6vbYY4+1dPOiNEdbd+zYgXPPPRepqamw2+244IILUFxcHFWmoqICF198Mex2OxISEnDFFVfA7Xa3dPOitFZb4+F9nTNnDk466STYbDakpaVhypQpyM/Pjyrj9/tx/fXXIzk5GVarFX/5y1/qtKWgoACTJ0+G2WxGWloa7rjjDkiSFFVmxYoVOOGEE2AwGNC9e3csWLCgpZtXR2u1d8WKFXXeW5VKhaKiolZpJ9B8bb3pppswdOhQGAwGDB48uN7n+v3333HyySfDaDQiJycHTzzxREs1q16t1dbdu3fX+77+9NNPLdm8Opqjvb/99humT5+OnJwcmEwm9OnTB88991yd54qH39uWxuDmMB6PB4MGDcKLL75Y5zEhBKZMmYKdO3fio48+wrp165CXl4fx48fD4/FEys2YMQP5+fn4+OOPsWHDBpx33nm44IILsG7duqjrPfTQQygsLIzcbrzxxhZvX23H21aPx4MJEyZApVJh+fLl+PHHHxEMBnHWWWdBUZTItS6++GJs2rQJS5cuxaefforvvvsOf/vb31qtnTV1bY22ArF/X7/99ltcf/31+Omnn7B06VKEQiFMmDAh6mf01ltvxSeffILFixfj22+/xYEDB3DeeedFHpdlGZMnT0YwGMTKlSvx+uuvY8GCBbj//vsjZXbt2oXJkydj3LhxWL9+PW655RZceeWV+PLLL9tle2vk5+dHvb9paWmt0k6gedpa4/LLL8e0adPqfZ7q6mpMmDABeXl5WLNmDebOnYsHHngA8+bNa7G2Ha612lrj66+/jnpfhw4d2uxtOpLmaO+aNWuQlpaGt956C5s2bcI999yDWbNm4YUXXoiUiZff2xYnqEEAxAcffBC5n5+fLwCIjRs3Ro7JsixSU1PFf/7zn8gxi8Ui3njjjahrJSUlRZXJy8sTzzzzTIvVvamOpa1ffvmlUKvVwul0RspUVVUJlUolli5dKoQQYvPmzQKA+PXXXyNlPv/8c6FSqcT+/ftbuFX1a6m2ChF/76sQQpSUlAgA4ttvvxVChOut0+nE4sWLI2X++OMPAUCsWrVKCCHE//73P6FWq0VRUVGkzEsvvSTsdrsIBAJCCCHuvPNO0a9fv6jnmjZtmpg4cWJLN+mIWqq933zzjQAgKisrW68xR3Esba1t9uzZYtCgQXWO//vf/xaJiYmRtgshxF133SV69erV/I1opJZq665duwQAsW7dupaq+jE53vbWuO6668S4ceMi9+P197a5seemCQKBAADAaDRGjqnVahgMBvzwww+RY6NGjcKiRYtQUVEBRVGwcOFC+P1+jB07Nup6jz32GJKTkzFkyBDMnTu3Tpd/LDWmrYFAACqVKmrhKKPRCLVaHSmzatUqJCQk4MQTT4yUGT9+PNRqNX7++efWaMpRNVdba8Tb++p0OgEASUlJAMLf7kKhEMaPHx8p07t3b+Tm5mLVqlUAwu/bgAEDkJ6eHikzceJEVFdXY9OmTZEyta9RU6bmGrHSUu2tMXjwYGRmZuL000/Hjz/+2NLNOaJjaWtjrFq1Cqeccgr0en3k2MSJE5Gfn4/Kyspmqn3TtFRba5x99tlIS0vDmDFj8PHHHzdPpY9Dc7XX6XRGrgHE7+9tc2Nw0wQ1P0izZs1CZWUlgsEgHn/8cezbtw+FhYWRcu+++y5CoRCSk5NhMBhw9dVX44MPPkD37t0jZW666SYsXLgQ33zzDa6++mo8+uijuPPOO2PRrHo1pq0jRoyAxWLBXXfdBa/XC4/Hg9tvvx2yLEfKFBUV1em212q1SEpKatVchSNprrYC8fe+KoqCW265BaNHj0b//v0BhN8TvV6PhISEqLLp6emR96SoqCjqg77m8ZrHjlSmuroaPp+vJZpzVC3Z3szMTLz88stYsmQJlixZgpycHIwdOxZr165t4VbV71jb2hiNeT1aU0u21Wq14qmnnsLixYvx2WefYcyYMZgyZUpMA5zmau/KlSuxaNGiqDSAePy9bQkdblfw46HT6fD+++/jiiuuQFJSEjQaDcaPH49JkyZB1Fro+b777kNVVRW+/vprpKSk4MMPP8QFF1yA77//HgMGDAAA3HbbbZHyAwcOhF6vx9VXX405c+bExRLajWlramoqFi9ejGuvvRbPP/881Go1pk+fjhNOOOGo29HHk+Zsa7y9r9dffz02btxYp3epvWrJ9vbq1Qu9evWK3B81ahR27NiBZ555Bm+++WazP9/RdKT3tiXbmpKSEvV7e9JJJ+HAgQOYO3cuzj777GZ/vsZojvZu3LgR55xzDmbPno0JEyY0Y+3aBgY3TTR06FCsX78eTqcTwWAQqampGD58eGTYZceOHXjhhRewceNG9OvXDwAwaNAgfP/993jxxRfx8ssv13vd4cOHQ5Ik7N69O+oPaCwdra0AMGHCBOzYsQNlZWXQarVISEhARkYGunbtCgDIyMhASUlJ1HUlSUJFRQUyMjJatT1H0hxtrU8s39cbbrghksDdqVOnyPGMjAwEg0FUVVVFfQssLi6OvCcZGRn45Zdfoq5XMyujdpnDZ6YUFxfDbrfDZDK1RJOOqKXbW59hw4bFJLg4nrY2RkPvbc1jraml21qf4cOHY+nSpcd1jWPVHO3dvHkzTjvtNPztb3/DvffeG/VYvP3etpS28/U6zjgcDqSmpmLbtm1YvXo1zjnnHACA1+sFgDo9FxqNps6smtrWr18PtVrdqjMvGquhttaWkpKChIQELF++HCUlJZFvPCNHjkRVVRXWrFkTKbt8+XIoioLhw4e3Whsa63jaWp9YvK9CCNxwww344IMPsHz5cnTp0iXq8aFDh0Kn02HZsmWRY/n5+SgoKMDIkSMBhN+3DRs2RAWmS5cuhd1uR9++fSNlal+jpkzNNVpLa7W3PuvXr0dmZmYzt6hhzdHWxhg5ciS+++47hEKhyLGlS5eiV69eSExMPP6GNEJrtbU+rf2+As3X3k2bNmHcuHGYOXMmHnnkkTrPEy+/ty0udrnM8cnlcol169aJdevWCQDi6aefFuvWrRN79uwRQgjx7rvvim+++Ubs2LFDfPjhhyIvL0+cd955kfODwaDo3r27OPnkk8XPP/8stm/fLp588kmhUqnEZ599JoQQYuXKleKZZ54R69evFzt27BBvvfWWSE1NFTNmzGhTbRVCiNdee02sWrVKbN++Xbz55psiKSlJ3HbbbVFlzjjjDDFkyBDx888/ix9++EH06NFDTJ8+vdXaKUTrtDVe3tdrr71WOBwOsWLFClFYWBi5eb3eSJlrrrlG5ObmiuXLl4vVq1eLkSNHipEjR0YelyRJ9O/fX0yYMEGsX79efPHFFyI1NVXMmjUrUmbnzp3CbDaLO+64Q/zxxx/ixRdfFBqNRnzxxRftsr3PPPOM+PDDD8W2bdvEhg0bxM033yzUarX4+uuv21RbhRBi27ZtYt26deLqq68WPXv2jPxu1MyOqqqqEunp6eKvf/2r2Lhxo1i4cKEwm83ilVdeaXdtXbBggXjnnXfEH3/8If744w/xyCOPCLVaLV577bVWa2tztXfDhg0iNTVVXHLJJVHXKCkpiZSJl9/blsbg5jA10z0Pv82cOVMIIcRzzz0nOnXqJHQ6ncjNzRX33ntv1HRJIYTYunWrOO+880RaWpowm81i4MCBUVPD16xZI4YPHy4cDocwGo2iT58+4tFHHxV+v781m9osbb3rrrtEenq60Ol0okePHuKpp54SiqJElSkvLxfTp08XVqtV2O12cdlllwmXy9VazRRCtE5b4+V9ra+dAMT8+fMjZXw+n7juuutEYmKiMJvN4txzzxWFhYVR19m9e7eYNGmSMJlMIiUlRfz9738XoVAoqsw333wjBg8eLPR6vejatWvUc7SW1mrv448/Lrp16yaMRqNISkoSY8eOFcuXL2+tZgohmq+tp556ar3X2bVrV6TMb7/9JsaMGSMMBoPIzs4Wjz32WCu1Mqy12rpgwQLRp08fYTabhd1uF8OGDYuabt1amqO9s2fPrvcaeXl5Uc8VD7+3LU0lRK1MWCIiIqI2jjk3RERE1K4wuCEiIqJ2hcENERERtSsMboiIiKhdYXBDRERE7QqDGyIiImpXGNwQERFRu8Lghoha3IIFC+rsZhzP2lp9iSgagxuiDuzSSy+FSqWCSqWCTqdDly5dcOedd8Lv9zfr80ybNg1bt25tVNl4Dyy2bt0Ks9mMd955J+q4oigYNWoUzj///BjVjIhqcFdwog7ujDPOwPz58xEKhbBmzRrMnDkTKpUKjz/+eLM9h8lkavUdh2VZhkqlqrOJ7fHq2bMnHnvsMdx4440YN25cZIPFp556Cjt37sTHH3/crM8HAMFgEHq9vtmvS9ReseeGqIMzGAzIyMhATk4OpkyZgvHjx2Pp0qWRxxVFwZw5c9ClSxeYTCYMGjQI7733XtQ1Pv74Y/To0QNGoxHjxo3D66+/DpVKhaqqKgB1e2N+++03jBs3DjabDXa7HUOHDsXq1auxYsUKXHbZZXA6nZEepQceeAAAEAgEcPvttyM7OxsWiwXDhw/HihUrIteseY6PP/4Yffv2hcFgQEFBwVHPqzk3NzcXZrMZ5557LsrLy4/4mt14440YNGgQrrrqKgDAli1bcP/992PevHlISUnBq6++ij59+sBoNKJ3797497//HXX+XXfdhZ49e8JsNqNr16647777onbgfuCBBzB48GC8+uqr6NKlC4xG4xHrQ0SHifXmVkQUOzNnzhTnnHNO5P6GDRtERkaGGD58eOTYP//5T9G7d2/xxRdfiB07doj58+cLg8EgVqxYIYQI7zKs0+nE7bffLrZs2SL++9//iuzsbAFAVFZWCiGEmD9/vnA4HJFr9uvXT1xyySXijz/+EFu3bhXvvvuuWL9+vQgEAuLZZ58Vdrs9sqNxzSarV155pRg1apT47rvvxPbt28XcuXOFwWAQW7dujTyHTqcTo0aNEj/++KPYsmWL8Hg8Rz3vp59+Emq1Wjz++OMiPz9fPPfccyIhISGqvvXZvXu3sNvtYt68eWL48OHi0ksvFUII8dZbb4nMzEyxZMkSsXPnTrFkyRKRlJQkFixYEDn34YcfFj/++KPYtWuX+Pjjj0V6erp4/PHHI4/Pnj1bWCwWccYZZ4i1a9eK3377rWlvLFEHx+CGqAObOXOm0Gg0wmKxCIPBIAAItVot3nvvPSGEEH6/X5jNZrFy5cqo86644goxffp0IUR4t/T+/ftHPX7PPfccMbix2WxRH/a1HV5WCCH27NkjNBqN2L9/f9Tx0047TcyaNStyHgCxfv36Jp03ffp0ceaZZ0Y9Pm3atKMGN0II8dprrwm1Wi1yc3OF0+kUQgjRrVs38c4770SVe/jhh8XIkSMbvM7cuXPF0KFDI/dnz54tdDqdKCkpOWodiKgu5twQdXDjxo3DSy+9BI/Hg2eeeQZarRZ/+ctfAADbt2+H1+vF6aefHnVOMBjEkCFDAAD5+fk46aSToh4fNmzYEZ/ztttuw5VXXok333wT48ePx9SpU9GtW7cGy2/YsAGyLKNnz55RxwOBAJKTkyP39Xo9Bg4c2KTz/vjjD5x77rlRj48cORJffPHFEdsAAJdddhnuu+8+3HjjjbDb7fB4PNixYweuuOKKyJAVAEiSBIfDEbm/aNEiPP/889ixYwfcbjckSYLdbo+6dl5eHlJTU49aByKqi8ENUQdnsVjQvXt3AMBrr72GQYMG4f/+7/9wxRVXwO12AwA+++wzZGdnR51nMBiO+TkfeOABXHTRRfjss8/w+eefY/bs2Vi4cGGdIKOG2+2GRqPBmjVroNFooh6zWq2R/5tMJqhUqiafdzy0Wi20Wm3k+QDgP//5D4YPHx5Vrub5V61ahYsvvhgPPvggJk6cCIfDgYULF+Kpp56KKm+xWJqlfkQdEYMbIopQq9X4xz/+gdtuuw0XXXRRVGLuqaeeWu85vXr1wv/+97+oY7/++utRn6tnz57o2bMnbr31VkyfPh3z58/HueeeC71eD1mWo8oOGTIEsiyjpKQEJ598cqPb05jz+vTpg59//jnq2E8//dTo56gtPT0dWVlZ2LlzJy6++OJ6y6xcuRJ5eXm45557Isf27NlzTM9HRPXjbCkiijJ16lRoNBq8+OKLsNlsuP3223Hrrbfi9ddfx44dO7B27Vr861//wuuvvw4AuPrqq7Flyxbcdddd2Lp1K959910sWLAAAKJ6UWr4fD7ccMMNWLFiBfbs2YMff/wRv/76K/r06QMA6Ny5M9xuN5YtW4aysjJ4vV707NkTF198MWbMmIH3338fu3btwi+//II5c+bgs88+a7AtjTnvpptuwhdffIEnn3wS27ZtwwsvvNCoIamGPPjgg5gzZw6ef/55bN26FRs2bMD8+fPx9NNPAwB69OiBgoICLFy4EDt27MDzzz+PDz744Jifj4jqEeukHyKKncNnS9WYM2eOSE1NFW63WyiKIp599lnRq1cvodPpRGpqqpg4caL49ttvI+U/+ugj0b17d2EwGMTYsWPFSy+9JAAIn88nhIhOEg4EAuLCCy8UOTk5Qq/Xi6ysLHHDDTdEygohxDXXXCOSk5MFADF79mwhhBDBYFDcf//9onPnzkKn04nMzExx7rnnit9//73Oc9R2tPOEEOL//u//RKdOnYTJZBJnnXWWePLJJxuVUCyEEHl5eeKZZ56JOvb222+LwYMHC71eLxITE8Upp5wi3n///cjjd9xxh0hOThZWq1VMmzZNPPPMM1HPN3v2bDFo0KBGPT8R1aUSQohYB1hE1L488sgjePnll7F3795YV4WIOiDm3BDRcfv3v/+Nk046CcnJyfjxxx8xd+5c3HDDDbGuFhF1UAxuiOi4bdu2Df/85z9RUVGB3Nxc/P3vf8esWbNiXS0i6qA4LEVERETtCmdLERERUbvC4IaIiIjaFQY3RERE1K4wuCEiIqJ2hcENERERtSsMboiIiKhdYXBDRERE7QqDGyIiImpXGNwQERFRu/L/EntZuXLAbkMAAAAASUVORK5CYII=",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.lineplot(x=df['registered_year'], y=df['resale_price'])\n",
    "plt.title('Resale Price Over the Years')\n",
    "plt.xlabel('Registered Year')\n",
    "plt.ylabel('Resale Price')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The cars registered way back in 2000s have leass resale value then the cars bought in recent years which is quite predictible."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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VRYquLlL17C/k6pAtR5ccmcF1Una23bEBAAAAQBLlEhB33HFry8yqGkV+WabaRb8ptrr4jx1Oh9y7rL/TW7cOMlxt9z9NjoBfvr37yLf3+qLpl2UK/7JMsfxiRVcVybmqSFWHnq/VA/ZQ0jGHyj9ysFzZGXbHBgAAANCGtd2f4ADsFFY4oshvKxX+6TdFlq2WzD8u73N1qrvTm3vXznL4vDambJ4cAb98+/SVb5++MssrFf51uUI/LZGjqEQ1n32jms++0Zqr7pfvwP5KOuYQ+UcOkSsr3e7YAAAAANoYyiUAcWdFojJWFCq09BuFl6yQItH6fc7sDHl67yJPr64sVr0dHMlJ8u3TV+U9Oyhp9GFKmPeDKt+Yq9oFP6nm069V8+nXWnPVpIZFU2aa3bEBAAAAtAGUSwDiwrIs1X71gyr+N0tVr8+Sq6Rc4fX7HCkBefrsIk/vXeTMSLUzZqvgaJ+p1AtOVuoFJyuyokChtz5Q5ZtzVbtwkWo+WaiaTxZqzZX3K+GgPesunRsxSM52FE0AAAAAmgblEoAdEv5lqSpeeV+Vr85SdEVB/XYrwStf713k6d1NzvbtZBiGjSlbL3en9kodf4pSx5+iyPJ8Vb71gUJvzFXtNz+r+qMFqv5ogYJX3Le+aDpE/hGDKfgAAAAAxBXlEoDtFs0vVsWrs1T5v1kK/7C4frvhT5B/5BBFh+6jigU/KDGF2TI7k7tzrtImnKq0CacqsixflW/NrSuavv1F1R/OV/WH8xW8/D4lDNpLSUcfIv/IwXKmx3fxeQAAAABtD+USgG0SK61Q6K25qnjlfdXM+1ay1i/M7XYpcegBChw3TInDB8qR6FNRUZH09U/2Bm7j3F1ylXbhGKVdOEaRpatV+eZcVb45V+HvflX1B1+p+oOvFLz8XiUM3ltJRx8ia79edkcGAAAA0EJRLgFtmGmZCgaDW9xv1dQq9uECRd7+WLGPvpaifyzM7dinj9wjB8l12AEyUgMKSQpVlEkVZQoGg3Ja1hbHxc7l7pqntItPU9rFpyny+6q6oumNuQr/sFjVc79U9dwvpUSfjAN3l/ZkJhMAAACA7UO5BLRhJaGQqh+eKldm9ib7jBWFcs76SkY4Ur/NykiR2b2jzB4dpKRE1RYFpalvbfLepcUFyvUnS8mpTRkfjeDepYPSLhmrtEvGKvzbSoXenKuK/72vyC/L5Jr1parKqpQweG8ZDofdUQEAAAC0EJRLQBuXnpikrEDD2SqRFQWqfO8LKRqTIzlJnt7r7/S2jbe2X1NZ0RRREWeebh3lufR0pV54qlZeM0mRp95Q7Vc/KFa0Rv6jDpEj0Wd3RAAAAAAtAL+aBtBANL9Yla/OkqIxubt1VPK5o5UweO9tLpbQ8hgul7yXjVX0sP0kt0vRFYUqf/ZNRQu2fMkkAAAAAGxAuQSgXrRorSpfeV+KROXq1F7+ow+W4eQ/E22F1a2Dkk87So60ZFkVIVX89x3Vfver3bEAAAAANHP81AhAkhRbW6rKV96TVRuWMy9LSX8bKsPFlbNtjbNdqpLHHiV3905SzFTVzE8VmvmprGjM7mgAAAAAmil+cgSgWGmFKl6eKauqRs7sDAVGHybD47Y7FjZja3f4a6yN7/BneD3yH3uoaj7/TjWfLFT4u18VC5Yo6ehD5EhOivtnAwAAAGjZKJeANs4I1ajyzU9lVVbJ0S5VSccfLsPrsTsWtuCv7vC3I/58hz/DMJQwYA+5ctopNP0DxQrWqPy5t+Q/6mC5O7WP62cDAAAAaNkol4A2zFETVtKs+TLLQ3KkBhQ4YTh3CGsBNneHvx21pTv8ubvmKTD2aIXemKNYcYkqX56phCH7yLtPXxmGEdcMAAAAAFom1lwC2iizulbpsxbIWR6SI9mvwElHyJGUaHcsNEPO1IACp46Up083ybJU/cFXCk3/UFY4Ync0AAAAAM0A5RLQBlnhiCr/957cpZUyfR4lnTictXTwlwy3S4kjBilh6P6Sw1Dk56Uqf366YuvK7I4GAAAAwGaUS0AbY0Wiqvzf+4oVrJHpcaty2D5ypsX3Eiu0ToZhyLdXHwVOOlKGP0HmmlJVPDdd4d9W2h0NAAAAgI0ol4A2xIrGVPnGHEVXFUket9YO3UtmWsDuWGhhXB2ylXz60XLmZsmqDSv06ixVf/q1rPV3mwMAAADQtlAuAW2EZZoKTf9A0aWrJbdLgdGHKZqRbHcstFCOpEQFTj5C3j17SZJqPvtGla/OkllTa3MyAAAAADsb5RLQBliWpap3PlZk8QrJ6VDSsUPl6hDfW9mj7TGcTiUOG6DEIw+SXE5Ff1+liufeUrS4xO5oAAAAAHYiyiWglbMsS1Xvz1N40e+Sw5D/6EPk7pJrdyy0It7deihw6kg5UpJkllao4oW36/6+AQAAAGgTKJeAVsxaf9v48Le/SJL8IwfL072TzanQGrmyMxQYe5RcXXKlSFSh6R+qas6XkmnaHQ0AAABAE6NcAlqxms++Ue38HyVJiUcMlKfXLjYnQmvmSPApafRh8u2/uySpdsGPSp+1UEY16zABAAAArRnlEtBK1Xz5vWo++0aSlDB0f3n77WpvILQJhsOhhMF7y3/MoZLHLW/xOgXemadofrHd0QAAAAA0EcoloBWq+XqRqj+cL0lKGLy3fHv1sTkR2hrPrp2VfNooRZP9clTVquK/76r2m59lWZbd0QAAAADEGeUS0MrU/rBY1bM+lyT5Dti9/hIlYGdzZqRqzZH7KdwpSzJNVb0/T1UzP5UVjdodDQAAAEAcUS4BrUj4l2WqmvGpJMm7V2/5DtrL5kRo6yy3S1WD+yth8N6SYSj8/WJV/PddmeWVdkcDAAAAECeUS0ArEfltpULTP5AsS55+PZRw6P4yDMPuWIBkGPLtv7uSjj9Mhs+rWOEalT/7piLL8+1OBgAAACAOKJeAViCyPF+Vb8yVTEvuXl2VePiBFEtodtxd8hQ4/Sg5szNkVdeqctp7qvnye9ZhAgAAAFo4yiWghYuuLlbla7OlWEzu7h3lHzFYhoN/tdE8OVMCCpwyQp7dukuWpeoP5yv05geywhG7owEAAABoJH4CBVqwaNFaVf7vfSkSlatzrvxHHSzDyb/WaN4Mt0uJRxykxGEDJIdDkV+XqXzqdMVKyuyOBgAAAKAR+CkUaKFia0tVOW2mrNqwXHnZSjr2UBkul92xgG1iGIa8e/ZS4OQjZPgTZK4tVflzbym8eLnd0QAAAABsJ8oloAWKrStXxUszZFXXypnTTkmjh8nwuO2OBWw3V162kk8/Wq4O2VI4otDrc1T9yUJZpml3NAAAAADbiHIJaGHM8kpVvjxTVqhajnapdXfg8nrsjgU0miMpUUknHiHvXr0lSTXzvlXlq7NkVtfanAwAAADAtrC9XFq9erVOO+00ZWRkKCEhQf369dP8+fPr91uWpeuvv17t27dXQkKChg0bpsWLFzcYo6SkRGPGjFFycrJSU1N1zjnnqLKycmefCtDkzFC1Kl6eKbO8Uo60ZAVOGC5Hgs/uWMAOM5wOJQ49QIkjBksup6JLV6viuTcVLVprdzQAAAAAW2FrubRu3ToNHDhQbrdb7777rn766Sfde++9SktLqz/mrrvu0oMPPqjJkyfriy++kN/v1/Dhw1VTU1N/zJgxY/Tjjz/q/fff1/Tp0/XRRx/p/PPPt+OUgCZj1IZV+fJMmevK5UhOUuDE4XIkJdodC4grb99uCowZJUdKksyySlW88LZqf/zN7lgAAAAA/oKtq//eeeed6tixo6ZMmVK/rWvXrvXPLcvSpEmTdO211+qYY46RJD377LPKzs7W66+/rpNPPlmLFi3SjBkz9NVXX2mfffaRJD300EMaMWKE7rnnHuXm5u7ckwKagBGOyj97gWJry2X4E5R04nA5kpPsjgU0CVdWugJjj1bo7Q8VXbpaVe98pFhhUAkH78fdEAEAAIBmyNbv0t98803ts88+OuGEE5SVlaU999xTTz75ZP3+pUuXqrCwUMOGDavflpKSov3331/z5s2TJM2bN0+pqan1xZIkDRs2TA6HQ1988cVmP7e2tlbl5eUNHkBzZUWiSvvga7nWlstI8Cpw4nA505LtjgU0KUeCV0nHDZNvwB6SpNqFi1T50gyZlVU2JwMAAADwZ7aWS7///rsee+wx9ejRQzNnztQFF1ygiy66SM8884wkqbCwUJKUnZ3d4H3Z2dn1+woLC5WVldVgv8vlUnp6ev0xf3b77bcrJSWl/tGxY8d4nxoQF1Y0psrXZ8tbXCrL7VLSCYfL2S5t628EWgHD4VDCQXvJ/7ehkset6OoilT/7pqKri+yOBgAAAGAjtpZLpmlqr7320m233aY999xT559/vs477zxNnjy5ST/36quvVllZWf1j5cqVTfp5QGNYMVOhtz5QdFm+TKdDlYfuJVd2O7tjATudp3snJY89So6MVFmhalW8OEOOH36TZVl2RwMAAAAgm8ul9u3bq0+fPg229e7dWytWrJAk5eTkSJKKihr+lrqoqKh+X05OjoqLixvsj0ajKikpqT/mz7xer5KTkxs8gObEMk1VvfuxIktWSE6n1h3cX7EsZiyh7XKmpyj5tFFy9+wimaacn3yr2msfkVlda3c0AAAAoM2ztVwaOHCgfvnllwbbfv31V3Xu3FlS3eLeOTk5mj17dv3+8vJyffHFFxowYIAkacCAASotLdWCBQvqj5kzZ45M09T++++/E84CiC/LslT1/jyFF/0uOQz5jzlE4fYZdscCbGd43PIfdbAShuwjy5Cib3yg1SMvUGRFgd3RAAAAgDbN1nLp0ksv1eeff67bbrtNS5Ys0QsvvKAnnnhC48ePlyQZhqFLLrlEt9xyi9588019//33Ov3005Wbm6tjjz1WUt1MpyOOOELnnXeevvzyS3366aeaMGGCTj75ZO4UhxbHsixVz/1S4e9+lQxD/pFD5OnGmmDABoZhyLdfP8VGHSSlJSv8/WKtGnauqj74yu5oAAAAQJtla7m077776rXXXtN///tf7bbbbrr55ps1adIkjRkzpv6YK664QhdeeKHOP/987bvvvqqsrNSMGTPk8/nqj3n++efVq1cvDR06VCNGjNBBBx2kJ554wo5TAnZIzadfq3bBT5KkxCMGytOrq82JgObJystS4st3ytu/l8x15So46Z9a98BU1mECAAAAbOCyO8CoUaM0atSoLe43DEMTJ07UxIkTt3hMenq6XnjhhaaIB+w0NV98p5p530qSEoYeIO9uPWxOBDRvjvaZyn7rYa256n5VPP+2Sm55XLVfL1LWQ/+SI+C3Ox4AAADQZtg6cwlAnZqFi1T9Ud26YQmD95Fvr942JwJaBofPq6xJVynz3sslt0uhtz/SquHjFF683O5oAAAAQJtBuQTYrPaHxaqe/bkkyTdgD/n272dzIqDlST79aOW99bCc7TMVWbxcqw47T5Vvf2R3LAAAAKBNsP2yOMAOpmkqGAzGfdxgMCjndqz5Ev55qapmfCpJ8u7dR76Be8Y9E9AamdZm/h3u0E7e/96umn/eJ3P+Tyo68xqVnPM3eS46WYbTuc1jZ2ZmyuHgdy8AAADAtqJcQpsUDAa15M7HleEPxHXcpcUFyvUnS8mpWz02/NtKhd7+ULIseXbfVQmH7CfDMOKaB2itSkIhVT88Va7M7E137rmrHOGwnN8tUeQ/r6l25qeKDdtX8nm3Ou7aUIV05ThlZ29mXAAAAACbRbmENivDH1BWICWuY66prNim4yLL8xV6Y65kWvL03kWJhw2gWAK2U3pi0pb/HR4+SOFOeQrN/FSOVcVyvfqh/MceIld2u50bEgAAAGgDmPcP7GTR1UWqfG22FIvJ3b2TEo8cJINLcIC48/TeRcljRsqRGpBZXqmKF95R7Q+L7Y4FAAAAtDr8RAvsRNGiNar83ywpEpWrS678Rx0sw8m/hkBTcWamKzD2KLl36SBFY6p69xNVvT9PVixmdzQAAACg1eCnWmAnia1Zp8pp78mqDcvVIVtJxw6V4dr2RYYBNI7D55X/uGHyHdhfklT7zc+qePFdmZVV9gYDAAAAWgnKJWAniK0rV8XLM2VV18qZ005Jxw2T4WbJM2BnMQxDCQP3lP+4YTK8HsXygyp/5k1FC+J/10gAAACgraFcApqYWV6pypdnyApVy9kuTUnHHy7D67E7FtAmebp1VGDsUXK0S5VVVa2Kl2YosqLA7lgAAABAi0a5BDQhs7JKFS/PlFkekiMtWUknDpcjYeu3QwfQdJxpyUoeM0quTu2lSFSVr7yv8JIVdscCAAAAWizKJaCJmNU1qpg2U+a6cjlSkhQ46Qg5/Al2xwIgyfC4lTR6mNzdO0mxmEKvz1H4p9/sjgUAAAC0SJRLQBOwasOqnPaezDWlMvwJSjphuBwBv92xAGzEcLnkP/oQefp0kyxLobc/kuPH3+2OBQAAALQ4lEtAvEWiqvzfLMWK1spI8Cpw4hFypiXbnQrAZhhOhxJHDJJ3z16SJOfH3yj879dsTgUAAAC0LJRLQDzFYvJ/+I2iq4tkeD1KOmG4nO1S7U4F4C8YhqGEoQfId8DukqTwpOe1duJkWZZlczIAAACgZaBcAuLEiplK+/h7uQvWSm6XkkYfJld2ht2xAGwDwzCUMGhvxQ7YTZJU+tDzWnP5vbJiMZuTAQAAAM0f5RIQB5ZpKvTux/KtCspyOpR03DC58rLsjgVgO5n9d5X3xnGSYaj8mTdU/H+3yIpE7Y4FAAAANGuUS8AOsixLVe99psii32U5DIWG9Je7U3u7YwFoJPfxhyn78Rskl1OVr85S4Rn/kllda3csAAAAoNmiXAJ2gGVZqp7zhcLfL5YMQ6UD+ymal2l3LAA7KOlvQ5Xz7O0yfB5VvT9PBSf/U2ZFyO5YAAAAQLPksjsA0JLVfLJQtQsXSZISjzhIBRk+JdicCUDjmZapYDBY92L3XeSbfK2qx9+ums++0fKjxith8jUyGnn3x8zMTDkc/E4HAAAArQ/lEtBI1Z9/p5rPv5MkJQ4bIO9u3aWCVTanArAjSkIhVT88Va7M7D82HnGAXG9/KvPH31R59MWKjjxIStq+GnltqEK6cpyys7O3fjAAAADQwlAuAY1Qs/An1Xy8QJKUMGQfeffsZXMiAPGSnpikrEDKHxsCKYqdmqqKl2dK6yrkfetjJZ0wXM5GzmACAAAAWhvm5wPbqfb7X1U9+wtJkm9Af/n262dzIgBNzZmRqsCpI+RIDcgsq1TFf99RLLjO7lgAAABAs0C5BGyH8KLfVTXjU0mSd5++8g3sb28gADuNMyWgwCkj5GyXJitUrYoX31G0IGh3LAAAAMB2lEvANgovWaHQOx9Jkjx79FTCwfvKMAybUwHYmRxJiUo6+Ug522fKqgmr4qUZiqwosDsWAAAAYCvKJWAbRJbnK/TmXMm05OnTTYmHDaBYAtooR4JXgROHy9WpvRSJqvKV9xVessLuWAAAAIBtKJeArTArqxSa/qEUM+Xu0UmJRx5EsQS0cYbHraTRw+Tu3kmKxRR6fY5qf/zN7lgAAACALSiXgL9gWZZCMz6RVVUjZ7s0+UcNkeHgXxsAkuFyyX/MIfL07SZZlqre+Ug1Xy+yOxYAAACw0/FTMvAXahf+pOjS1ZLLKf9RQ2S4XHZHAtCMGA6HEo8cJO9evSVJ1bM+V/Xn38myLJuTAQAAADsP5RKwBdHiElV/OF+SlDBkXznbpdmcCEBzZBiGEg7dX74Be0iSaj5eoOqP5lMwAQAAoM2gXAI2w4pE/1hnqVtHeffsZXckAM2YYRhKOGgvJRy8rySp9ssfVPXeZ7JM0+ZkAAAAQNOjXAI2o/rDr2SuLZWRmKDE4QNZwBvANvHtu5sShw+UDEPh735V6O2PZMVidscCAAAAmhQLyAB/Ev5tpWq//lmS5B8xSA5/gs2JALQk3t13leF1KzT9I0V+XqrKcEQ6ZC+7YwEAAABNhplLwEbMyipVvfuxJMm7dx+5u+bZnAhAS+Tp2VVJxw2VXE5Ff18l5zufyaqssjsWAAAA0CQol4D1LMtS6N1PZFXXypmZpoTBe9sdCUAL5u7aQYEThksetxwFa1R99o2KrS21OxYAAAAQd5RLwHq1C35SdNlqyeWUf9TBMlxcNQpgx7g6ZCtw8hGyfB6ZP/2u1UdPULQgaHcsAAAAIK4olwBJ0eISVX80X5KUcPC+crZLtTcQgFbDld1O0WOGyMjOUOTX5Vo9arwiv6+yOxYAAAAQN40ql3bZZRetXbt2k+2lpaXaZZdddjgUsDNZkahC0z+UYqbc3TrK27+X3ZEAtDZpASU8d4vcu3RQdEWBVh81XrU//WZ3KgAAACAuGlUuLVu2TLHN3Fq5trZWq1ev3uFQwM5U/cFXMteWyvAnKPGIg2QYht2RALRCjtxM5b71iDx9uylWXKL8Yy5Uzfwf7Y4FAAAA7LDtWlTmzTffrH8+c+ZMpaSk1L+OxWKaPXu2unTpErdwgGmaCgbjvz5JMBiU07IUXrJCtd/8LEnyHzlIjkRf3D8LADZwZaUr9/WHVHDqFar96gflj75UOc/dpsTB+9gdDQAAAGi07SqXjj32WEmSYRg644wzGuxzu93q0qWL7r333riFA4LBoJbc+bgy/IG4jru0uEB5hlfeGfMkSd69+8rdNS+unwEAm+NMDSj35XtVeOY1qv5wvgpOuUI5/75J/iMH2R0NAAAAaJTtKpdM05Qkde3aVV999ZXatWvXJKGAjWX4A8oKpGz9wO2wpqJciXO+llVdK2dmuhIG7x3X8QHgrziSEtX++TtVNO4mhd7+SIVnXaesB69S4MQj7I4GAAAAbLdGrbm0dOlSiiW0aP6fV8hdsFZyOeUfNUSGy2l3JABtjOH1KPvfNylw0hFSLKbi8beq7N//szsWAAAAsN22a+bSxmbPnq3Zs2eruLi4fkbTBk899dQOBwOaSrRorQJfL5YkJR68n5ztUu0NBKDNMlwuZT54tRzJSSp78hWtuXqSzPKQUi8dy80FAAAA0GI0qly66aabNHHiRO2zzz5q37493wCjxbAiUYXe/lCGaSnSIVOe/j3tjgSgjTMcDmXcepEcqQGtu3uKSm5/UrHyCmXc8H/8/xUAAAAtQqPKpcmTJ+vpp5/W2LFj450HaFLVH3wlc22ZYj6Pqgbsxg9uAJoFwzCUfsXZciT7tfa6h1X2yIsyyyqVec8/ZTi5bBcAAADNW6PWXAqHwzrwwAPjnQVoUuElK1T7zc+SpNKBu8nyeWxOBAANpf79JGVOukpyOFQxdbqKxk2UFY7YHQsAAAD4S40ql84991y98MIL8c4CNBmzskpVMz6RJHn36atw+wybEwHA5iWPGansJ2+U3C6F3pijwtP/JbOqxu5YAAAAwBY16rK4mpoaPfHEE5o1a5Z23313ud3uBvvvu+++uIQD4sGyLIXe+VhWda2cWelKGLS3FCywOxYAbFHS0YfIkZSowjOvUdXsz1Vw0j+V8/wdciYn2R0NAAAA2ESjyqXvvvtO/fv3lyT98MMPDfaxhg2am9r5Pyq6PF9yOeUfNUSGi/VLADR/iYfur/bT7lPhqVeq5vNvlX/sRcp9+V4526XZHQ0AAABooFHl0ty5c+OdA2gS0aK1qv54gSQp8ZD95MxItTcQAGyHhP13V+7rDyr/xMsU/n6xVh99oXJfuU+u3Cy7owEAAAD1GrXmEtASWJGoQtM/lGKm3N07ybNHT7sjAcB28/broby3HpErL0uRxcu1etR4hX9baXcsAAAAoF6jZi4dcsghf3n525w5cxodCIiXqrlfyiwpk+FPUOLwgVyyCaDF8nTvpNzpj6pg9CWK/L5K+UdNUPtp98rbt7vd0QAAAIDGzVzq37+/9thjj/pHnz59FA6HtXDhQvXr1y/eGYHtFl68XOFvf5Ek+UcMkiPRZ3MiANgx7g7Zyn3rEXn6dlcsWKL8Yy5Uzfwf7Y4FAAAANG7m0v3337/Z7TfeeKMqKyt3KBCwo8zKKlXN/FSS5N2nr9xd8mxOBADx4cpKV+4bD6rwlCtU89UPyh99qXKevU2JQ/axOxoAAADasLiuuXTaaafpqaeeiueQwHaxLEuhdz6WVV0rZ1a6EgbtbXckAIgrZ0pA7afdp4SD95VVVa2CU69Q5dsf2R0LAAAAbVhcy6V58+bJ5+PyI9indv6Pii7Pl1xO+UcNkeFy2h0JAOLO4U9Q+6l3yD9qiBSOqOic61Xx0gy7YwEAAKCNatRlcccdd1yD15ZlqaCgQPPnz9d1110Xl2DA9ooWrVX1RwskSYmH7CdnRqq9gQCgCRlej7KfvFHBS+9SxYvvqnjCrTLLK5Vy3vF2RwMAAEAb06hyKSUlpcFrh8Ohnj17auLEiTr88MPjEgzYHlYkqtD0DyXTlLt7J3n26Gl3JABocobLpcwHrpIjOUllT0zTmn89ILM8pNTLTucOmQAAANhpGlUuTZkyJd45gB1SNfdLmSVlMvwJShw+kB+qALQZhsOhjFsulCM1oHV3PaWSO/6tWHmlMm78P/5bCAAAgJ2iUeXSBgsWLNCiRYskSX379tWee+4Zl1DA9ggvXq7wt79IkvwjBsuRyLpfANoWwzCUfvlZciQnae21D6rs0RdlllUo897LZThZew4AAABNq1HlUnFxsU4++WR98MEHSk1NlSSVlpbqkEMO0YsvvqjMzMx4ZgS2yKysUtXMTyVJ3n13k7tLrs2JAMA+qeNOkCPZr+Ald6ri+bdlVlQp+7HrZHjcdkcDAABAK9aou8VdeOGFqqio0I8//qiSkhKVlJTohx9+UHl5uS666KJ4ZwQ2y7Ishd7+SFZ1rZxZ6UoYtJfdkQDAdsmnjFD2fyZKbpdCb85VwdirZVbV2B0LAAAArVijyqUZM2bo0UcfVe/eveu39enTR4888ojefffduIUD/krtVz8ouqJAcjnlHzWESz8AYL2kUUPU/vk7ZST6VD3nCxWc+A/FyivtjgUAAIBWqlHlkmmacrs3nWLvdrtlmuYOhwK2Jlq0RtUfL5QkJR66v5wZqfYGAoBmJvGQ/ZQ77T45kpNU88V3yj/2IkWD6+yOBQAAgFaoUeXSoYceqosvvlj5+fn121avXq1LL71UQ4cOjVs4YHOscESh6R9Jpil3j07y7L6r3ZEAoFny7ddPuW88JGdmmsLfL1b+0RMUXV1kdywAAAC0Mo0qlx5++GGVl5erS5cu6tatm7p166auXbuqvLxcDz30ULwzAg1Uzf1SZkmZjKREJQ4fyK22AeAveHfrrty3HpYrL0uRJSu06oi/q3b9HTYBAACAeGjU3eI6duyohQsXatasWfr5558lSb1799awYcPiGg74s/CvyxX+7ldJkn/EIDkSfDYnAoDmz9Otk/LeflT5J1+uyM9LtfroCcp69DoljRxsdzQAAAC0AttVLs2ZM0cTJkzQ559/ruTkZB122GE67LDDJEllZWXq27evJk+erEGDBjVJWLRtZkVIVTM/lSR5991N7s65NicCgG1jWqaCwWCTjJ2ZmSmHY+sTkV152cp7+1EVnXuDqud+qaKzrlXkunFKnXAqM0ABAACwQ7arXJo0aZLOO+88JScnb7IvJSVF48aN03333Ue5hLizLEuhdz6WVVMrZ3aGEgbtZXckANhmJaGQqh+eKldmdlzHXRuqkK4cp+zsbRvXmZyk9i/cqTXXPKTyp15VycTJiixZqcy7/yHDs+mNOgAAAIBtsV3l0rfffqs777xzi/sPP/xw3XPPPTscCviz2q9+UHRFgeR2yT9qiAyn0+5IALBd0hOTlBVIsTuGDJdLmXdeKk/3jlpz7UOqeOFtRVYUKOepm+VM2/SXRwAAAMDWbNeC3kVFRXK7t/ybTZfL1WTT/tGGBdep+uOFkupure1Mt/+HMwBo6VLOO145U++QkZSomk8WavWRf1f4t5V2xwIAAEALtF3lUl5enn744Yct7v/uu+/Uvn37HQ4FbGBV1cg16yvJNOXu0Ume3Xe1OxIAtBr+wwYo7+1H5eqQrchvK7X6iHGq/vRru2MBAACghdmucmnEiBG67rrrVFNTs8m+6upq3XDDDRo1alTcwgG1dz0to6xSRlKiEocPZNFZAIgzb59uypvxuLx795FZWqH8Ey5T+Qtv2x0LAAAALch2lUvXXnutSkpKtOuuu+quu+7SG2+8oTfeeEN33nmnevbsqZKSEl1zzTWNCnLHHXfIMAxdcskl9dtqamo0fvx4ZWRkKCkpSaNHj1ZRUVGD961YsUIjR45UYmKisrKydPnllysajTYqA5qXyrc/UvSVWbIk+UcMkiPBZ3ckAGiVXNkZyn3tQfmPOVSKRBW8+A6tnThZlmnaHQ0AAAAtwHYt6J2dna3PPvtMF1xwga6++mpZliVJMgxDw4cP1yOPPLLNd6zZ2FdffaXHH39cu+++e4Ptl156qd5++21NmzZNKSkpmjBhgo477jh9+mnd7ehjsZhGjhypnJwcffbZZyooKNDpp58ut9ut2267bbtzoPmIFgQVvLRu8Xiz/65yd861OREAND+mZcZ3rcOb/y53Tpoij/9PpQ89r8jvq5T16LVyJFLuAwAAYMu2q1ySpM6dO+udd97RunXrtGTJElmWpR49eigtLa1RASorKzVmzBg9+eSTuuWWW+q3l5WV6T//+Y9eeOEFHXrooZKkKVOmqHfv3vr88891wAEH6L333tNPP/2kWbNmKTs7W/3799fNN9+sK6+8UjfeeKM8Hk+jMsFelmmqePwtMteVy9FnF0X27WN3JABolkpCIVU/PFWuzO3/xc4WGVJoYF+lfvmLQm9/qPyjC5Uz9Q65ctrF7zMAAADQqmzXZXEbS0tL07777qv99tuv0cWSJI0fP14jR47UsGHDGmxfsGCBIpFIg+29evVSp06dNG/ePEnSvHnz1K9fvwazpYYPH67y8nL9+OOPW/zM2tpalZeXN3ig+Sh95L+q/nihjESffHdeLDkb/dcUAFq99MQkZQVS4vrw9+uphP/cIEd6imq//UWrho9T7feL7T5VAAAANFO2/tT+4osvauHChbr99ts32VdYWCiPx6PU1NQG27Ozs1VYWFh/zJ8vw9vwesMxm3P77bcrJSWl/tGxY8cdPBPES+23v6jkticlSe1uuUiOrnk2JwKAtsm5V291mPG43D06K5ZfrNWjxis081O7YwEAAKAZsq1cWrlypS6++GI9//zz8vl27loOV199tcrKyuofK1eu3Kmfj80zQ9UqGneTFI3JP3KIAqdx50EAsJO7a57y3n1MCUP2kVVVrcKxV6v0sRfr11wEAAAAJBvLpQULFqi4uFh77bWXXC6XXC6XPvzwQz344INyuVzKzs5WOBxWaWlpg/cVFRUpJydHkpSTk7PJ3eM2vN5wzOZ4vV4lJyc3eMB+a659UJHfVsrZPlOZ918hwzDsjgQAbZ4zJaD2/71byWccI1mW1l7/iNb88x5ZEe7MCgAAgDq2lUtDhw7V999/r2+++ab+sc8++2jMmDH1z91ut2bPnl3/nl9++UUrVqzQgAEDJEkDBgzQ999/r+Li4vpj3n//fSUnJ6tPHxaBbkkq3/pAFVOnS4ah7EevlTONwg8AmgvD7VK7u/+hjJsnSIah8mffVMHJ/1SstMLuaAAAAGgGtvtucfESCAS02267Ndjm9/uVkZFRv/2cc87RZZddpvT0dCUnJ+vCCy/UgAEDdMABB0iSDj/8cPXp00djx47VXXfdpcLCQl177bUaP368vF7vTj8nNE40v1jBy+6SJKVOOFUJB+1lcyIAwJ8ZhqHUv58kd9cOKjr/JlV/tECrR1yg9s/fKTfr4wEAALRptpVL2+L++++Xw+HQ6NGjVVtbq+HDh+vRRx+t3+90OjV9+nRdcMEFGjBggPx+v8444wxNnDjRxtRtk2maCgaD2/0+KxZTzXk3yyytkKPPLoqcParBpY7BYFBO1vYAgGbDP3yg8qY/ooLTrlJk8XKtOmKccp6+VQkD9rA7GgAAAGzSrMqlDz74oMFrn8+nRx55RI888sgW39O5c2e98847TZwMWxMMBrXkzseV4Q9s1/scX/8i55c/ynI5Vbt7N9U+Pq3B/qXFBcr1J0vJqXFMCwDYEd5+PdRh5uMqHHu1ar/5WfnHX6qs+69Q4MQj7I4GAAAAGzSrcgktW4Y/oKxAyjYfHy1co4qvfpIk+YceIG/HDpscs6aS9TwAoDly5bRT7hsPqfj/blHo7Q9VPP5WhZesVPpV58hw2LakIwAAAGzAd3+whRWOKDT9Q8m05N61szz9etgdCQCwnRyJPmU/NVGpF58mSSq9/1kVnX+TzOpam5MBAABgZ6Jcgi2q5nwhc125jECiEg8fKMMw7I4EAGgEw+FQxrXjlPng1ZLbpdAbc5R/7IWKFq21OxoAAAB2Esol7HThX5Yp/P1iSZJ/xGA5ErizHwC0dMmnjFDutPvkSEtW7cJFWn3EONX+uMTuWAAAANgJKJewU5nllaqa+akkybd/P7k7tbc5EQAgXhIG7qm8dyfL3a2joquKtHrk/yn0/jy7YwEAAKCJUS5hp7FMU6F3PpZVG5Yzp518A/e0OxIAIM483Toq793J8h20l6xQtQpPu0qlT7wiy7LsjgYAAIAmQrmEnabmyx8UXVkouV3yjxosw+m0OxIAoAk405KV+9I9CowZKZmm1l7zgNZceb+saNTuaAAAAGgClEvYKaIFQdV8ulCSlDj0ADnTUmxOBABoSobHrcz7r1T6DRdIhqHyKa+p4NQrFSuvtDsaAAAA4oxyCU3OCkcUmv6hZFpy9+wiz27d7Y4EANgJDMNQ2oRTlfP0LTISfaqe+6VWj7hAkeX5dkcDAABAHFEuoclVzf5CZmmFjIBfiYcfKMMw7I4EANiJ/CMGK+/Nh+XMaafIL8u06ohxqvnye7tjAQAAIE4ol9Ckwr8sVfiHxZIk/8jBcvi8NicCANjBu0dPdXjvCXn69ZC5plT5x12iiv+9b3csAAAAxAHlEpqMWV6pqpmfSZJ8B+wud8ccmxMBAOzkap+pvLcekX/EIFm1YRX/faJK7nqKO8kBAAC0cJRLaBKWaSr09keyasNytm8n34F72h0JANAMOPwJyp5yi1InnCJJWnf3FBX/faLMmlqbkwEAAKCxKJfQJGq+/F7RVUWS2yX/yCEynPxVAwDUMRwOZdzwf8q87wrJ5VTlq7OUf9wligbX2R0NAAAAjcBP/Ii7aEFQNZ9+LUlKHHaAnGnJNicCADRHyWOPUvuX75UjJUm1X/2g1UeMU/jnpXbHAgAAwHaiXEJcWeGIQtM/lExL7p5d5Onb3e5IAIBmLHHQ3sqb8bhcXfIUXVGg1SMuUNWcL+yOBQAAgO3gsjsAWpeq2Z/LLK2QEfAr8fADZRiG3ZEAANvJtEwFg8EmGTszM1MOR8PfbXm6d1KHmY+r8MxrVDPvWxWceqXa3XaxUs7+W5NkAAAAQHxRLiFujCWrFP5hiWQY8o8cLIfPa3ckAEAjlIRCqn54qlyZ2XEdd22oQrpynLKzNx3XmZ6i3Gn3KfiPu1Xx0gytufI+RRYvV8bNE2S4+HYFAACgOeO7NcSFWRCU86O6dZZ8+/eTu2OOzYkAADsiPTFJWYGUnfqZhtejzIf+JXePziq55XGV/ft/iixdrewnb5Qj4N+pWQAAALDtWHMJO8yKxVRz1YMywhE522fKd+CedkcCALRQhmEo7eLTlP3UzTISvKqa/blWj/w/RVYW2h0NAAAAW0C5hB1W+sDzMhcskuV2yT9ysAwnf60AADsm6aiDlfvGQ3JmpSu86HetHj5ONQt+tDsWAAAANoMWADukZsGPKrnrKUlS7KA95ExLtjkRAKC18O3ZWx3ee0Kevt0VC5Yo/9iLVPn6HLtjAQAA4E8ol9BoZmWViv4+UYrF5DriQFm7drI7EgCglXHlZStv+iNKPPxAWTVhFZ13g9bd+4wsy7I7GgAAANajXEKjrbnqfkWX5cvVIVve68dJhmF3JABAK+RISlTOs7cp5e8nSpJK7vi3isffIqs2bHMyAAAASJRLaKTK12ar4qUZksOhrEevk5HMXXwAAE3HcDrV7uYL1e7uf0hOpyqnvaf84y5RbM06u6MBAAC0eZRL2G6RlYUK/vMeSVLaJWOVMGAPmxMBANqKlDOPVfsX75YjOUk1X36vVUf+XeFfl9kdCwAAoE2jXMJ2scIRFf99oszySnn37qO0f55pdyQAQBuTePC+ynv3Mbk6t1d0Wb5WH3mBqj6cb3csAACANotyCdvMsiwFr7xPNV9+LyMpUdmPXS/D7bI7FgCgDfLs2kUdZjwu3379ZJZXquCkf6rsmTfsjgUAANAmUS5hm5U98Yoqpk6XHA5lP3Gj3F3z7I4EAGjDnO3SlPvqJCWdcLgUi2nNP+/RmusekhWL2R0NAACgTaFcwjapmv2F1l7/sCQp48YL5D9sgM2JAACQDK9HWY9cq7SrzpEklU1+WYVnXCOzssrmZAAAAG0H1zRhq8K/LlPReTdIpqnAKSOU8veT7I4EAGiBTMtUMBhskrEzLz1dnl06qvjC21Q181OtHjVe7Z+/Q6687Cb5PAAAAPyBcgl/KVZSpoIxV8msCMm3/+7KvPsfMgzD7lgAgBaoJBRS9cNT5cqMb+GzNlQhXTlO2X8bKlfHHBWefrXCPy7RquHjlDP1Dvn694rr5wEAAKAhyiVskRWJqujc6xVdtlqujjnKnnKLDK/H7lgAgBYsPTFJWYGUJhvft09f5c14XIWnXaXwot+Vf/QEZT34LyUde2iTfSYAAEBbx5pL2KI11zyg6o8XyvAnKGfqHXJlptkdCQCArXJ3aq+8tx9V4tADZFXXqui8G1Q07ibF1pbaHQ0AAKBVolzCZpX951WVT3ldMgxlT75e3j7d7I4EAMA2cwT8ypl6u1IvPk1yOFT56iytOGisKl+fI8uy7I4HAADQqlAuYRNVH3ylNdc8KElKv3ac/EccZHMiAAC2n+FyKePaccqbMVme3rvIXFNaN4vprGsVLVxjdzwAAIBWg3IJDYR/W6Gic6+XYjElnThcqReeanckAAB2iG/P3uow699Ku/wsyeVU6O2PtHLQ6ap4aQazmAAAAOKABb1RL1ZaocIxV8ksq5R3n77KvPdy7gwHAGj2TMtUMBjc+oFnjFTCAX1Ve92jMn/6XcUTbtXal96R9/pxcrRvt9m3ZGZmyuHgd3EAAAB/hXIJkiQrGlXReTco8ttKufKylPPMbXL4vHbHAgBgq0pCIVU/PFWuzOxte8NBu8sRSJBj/iLFPv5aoRETFBvQT1bvLtJGv1RZG6qQrhyn7OxtHBcAAKCNolyCJGntdQ+r+oOvZCT6lPPcHXJlpdsdCQCAbZaemKSsQMq2v2Hwfor13VWhGZ8olh+U66Ov5VpWqMThA+VMDTRdUAAAgFaIed5Q2TNvqOzf/5MkZT1yrbz9eticCACApufMSFXglBFKOGQ/yeVUdEWByp9+XTULfmItJgAAgO3AzKU2rvqThVpz1f2SpPSrz1PSqCE2JwIAYOcxHA759ukrd7eOqpr5qaIrC1U95wuFf1kqDdrD7ngAAAAtAjOX2rDI76tUePZ1UjSmpOOGKfXSsXZHAgDAFs60ZCWddIQSDxsguV2KrS6Wa9pshf/zmqxo1O54AAAAzRrlUhsVK69UwdirZK4rl3fP3sqcdBV3hgMAtGmGYcjbv5dSzv6bXF3yZMRMhe9/XquP+Ltqf/rN7ngAAADNFuVSG2TFYio+/yZFfl0uZ/tM5Tx7mxwJ3BkOAABJciQnKen4wxQ9ZG8p2a/ab3/RqmHnquTuKbLCEbvjAQAANDuUS23Q2hsfVdXsz2UkeNX+udvlymlndyQAAJoVwzBk9eysxDcmKfHIg6RIVOvuekqrDj9Ptd/+Ync8AACAZoVyqY0pnzpdZZNfliRlPXSNvHv0tDkRAADNlyMzTTnP3KbsJ26UIyNF4R9/06rh47T2lsdl1tTaHQ8AAKBZoFxqQ6o/+0bBK+6VJKVdfpaSjjnE5kQAADR/hmEo6W9D1emT55R07KFSLKbSB6Zq1aHnqOarH+yOBwAAYDvKpTYisjxfhWdfK0Wi8h99iNL+eabdkQAAaFGc7dKU/eRNyn76Vjmz0hVZvFyrR/6f1lz7oMxQtd3xAAAAbEO51AaYlVUqHHu1zLVl8uy+q7Ie+pcMB3/0AAA0RtLIwer4yXMKnHSEZFkqe3yaVh58pqo/WWh3NAAAAFvQMLRyViymonE3KbzodzmzM9T+udvlSPTZHQsAgBbNmZasrIevUc5/75YrL0vRZfnK/9vFCl5+j8yKkN3xAAAAdirKpVau5NYnVPXeZzK8HuU8e5tcuVl2RwIAoNXwDztAHT9+VslnHiNJKn/6Da0cdLqqZn9hczIAAICdh3KpFSt/8V2VPvSCJCnzgavk26uPzYkAAGh9HAG/Mu/+p3Jfe0CuLrmKri5Wwcn/VPGFtylWWmF3PAAAgCZHudRK1Xz5vYL/uFuSlHrp6QqMPszmRAAAtG4JB+2ljh88rZRxJ0iGoYoX39XKgacp9O7HdkcDAABoUpRLrVBkZaEKz7xGCkfkHzlY6VedY3ckAADaBIc/Qe1uuUh50x+Ru3snxYpLVHj6v1R0/o2KrVlndzwAAIAmQbnUytTdGe4qxYLr5OnbXVkPX8Od4QAA2Ml8+/VTh7lPKfWiMZLDocrXZmvFQWNV+dpsWZZldzwAAIC4onVoRSzTVPH4WxT+8Tc5M9OUM/UOOZIS7Y4FAECb5PB5lXHd35U383F5+uwic22Zis6/UUVnXqNo4Rq74wEAAMQN5VIrUnL7vxV652PJ41bOM7fJ3SHb7kgAALR5vv691OH9fyvt8rMkl1Ohdz7WyoPGqvzFd5nFBAAAWgXKpVai4n/vq3TSc5KkrPuvkG/f3WxOBAAANjA8bqVfcbY6zPq3vHv0lFlWqeCFt6ng5MsVWVVkdzwAAIAdQrnUCtQs+FHBi++QJKVeOEaBE4+wOREAANgcb9/uypsxWenX/V2G16PqOV9o5aDTVfbMG7JM0+54AAAAjUK51MJFVxep8PR/yaoNK3H4QKVfc57dkQAAwF8wXC6lXTRGHeY+Je++u8mqrNKaf96j/NGXKrJ0td3xAAAAthvlUgtmhqpVMPZqxYpL5Om9i7InXy/D6bQ7FgAA2AaeHp2V99bDyrjlIhkJXtV8slArDz5TpY9PkxWL2R0PAABgm7nsDoDGsUxTxRfepvD3i+XISOHOcAAAxJlpmQoGg00ydmZmphwOhwynU6njTpD/8ANVfOmdqvn0a6299kGF3pijzAeukqdH5yb5fAAAgHiiXGqh1t3ztEJvfSC5XcqZcqvcndrbHQkAgFalJBRS9cNT5cqM791X14YqpCvHKTv7j3HdXfOU++oklT/3ltbe+KhqvvpBqw45W2lXnK3U/ztJhotv2QAAQPPFdyotUOXrc7Tu7imSpMy7/6mEAXvYnAgAgNYpPTFJWYGUnfJZhsOhlDOOUeLQAxS87C5Vz/1SJTdPVujNucp88Gp5+3TbKTkAAAC2F2sutTA13/ys4gtvlSSlXHCSkseMtDkRAACIJ3eHbLV/6R5lPvQvOVKSVPvtL1o17FyV3D1FVjhidzwAAIBNUC61INHCNSoce7WsmrAShx6gjBsusDsSAABoAoZhKPnkI9Xxk+eUeORBUiSqdXc9pVWHnavab3+xOx4AAEADlEsthFldq8LT/6VY4Rq5d+2srCdu4M5wAAC0cq6cdsp55jZlP3GjHBkpCv/0u1YNH6e1EyfLrKm1Ox4AAIAkyqUWwbIsBS++XbVfL5IjLVntp94pZ3KS3bEAAMBOYBiGkv42VJ0+eU5JfxsqxWIqfeh5rTrkbNV8+b3d8QAAACiXWoLS+55V5WuzJZdTOVNukbtrnt2RAADATuZsl6bsJ25UzjO3ypmVrsiSFVo9arzWXPOgzFC13fEAAEAbRrnUzFW+9YFK7vi3JCnzzsuUMHBPewMBAABb+UcMVsdPpypw8pGSZansiWlaefCZqv5kod3RAABAG0W51IzVfveriiesvzPceccr+fSjbU4EAACaA2dqQFkP/UvtX7xHrrwsRZflK/9vFyt4+T0yK0J2xwMAAG2My+4A2Lxo0VoVjL1aVlWNEg7eVxkTx8dlXNM0FQwG4zLWxoLBoJyWFfdxAQDAliUO3V8dP35Wayc+pvKn31D502+o6v15anfXP5R42AAZhmF3RAAA0AZQLjVDZk2tCs+8RrH8Yrm7dVT2v2+S4YrPH1UwGNSSOx9Xhj8Ql/E2WFpcoFx/spScGtdxAQDAX3ME/Mq8+59KOuZQFV96p6LL8lU45kp5+/dSygUnKemog2W4+ZYPAAA0HVsvi7v99tu17777KhAIKCsrS8cee6x++eWXBsfU1NRo/PjxysjIUFJSkkaPHq2ioqIGx6xYsUIjR45UYmKisrKydPnllysaje7MU4kby7IUvOwu1c7/UY6UJOU8f4ecKfEtgjL8AWUFUuL6SEvk7nUAANgp4aC91PGDp5VywUkyfB7VfvOzisfdpBX7nqTSR/6rWFmF3REBAEArZWu59OGHH2r8+PH6/PPP9f777ysSiejwww9XKPTHWgGXXnqp3nrrLU2bNk0ffvih8vPzddxxx9Xvj8ViGjlypMLhsD777DM988wzevrpp3X99dfbcUo7rPTB51U57T3J6VT2f26Wp1snuyMBAIAWwuFPULuJE9T561eUduXZcmamKbq6WGtvfFTL9xitNdc8qMjyfLtjAgCAVsbWOdIzZsxo8Prpp59WVlaWFixYoMGDB6usrEz/+c9/9MILL+jQQw+VJE2ZMkW9e/fW559/rgMOOEDvvfeefvrpJ82aNUvZ2dnq37+/br75Zl155ZW68cYb5fF47Di1Rgm9+7FKbn1CktTutouVOGQfmxMBAICWyNkuTen/PEupE05V5Svvq3TyS4r8skxlT0xT2b//J//IwUq94CT59t3N7qgAAKAVaFZ3iysrK5MkpaenS5IWLFigSCSiYcOG1R/Tq1cvderUSfPmzZMkzZs3T/369VN2dnb9McOHD1d5ebl+/PHHzX5ObW2tysvLGzzsVvvjEhX9/WbJspR81rFKOftvdkcCAAAtnMPnVfJpo9Tx42fV/qV7lHDwvpJpKvTWB1o94gKtOvLvqnxzrqwWupwAAABoHppNuWSapi655BINHDhQu+1W91u0wsJCeTwepaamNjg2OztbhYWF9cdsXCxt2L9h3+bcfvvtSklJqX907NgxzmezfaLBdSoce7WsqmolDNpL7W692NY8AACgdTEMQ4mH7q/cafepw4dPK3DKCMnjVu38H1V0zvVasf+pKp38sszKKrujAgCAFqjZlEvjx4/XDz/8oBdffLHJP+vqq69WWVlZ/WPlypVN/plbYtWGVXTmNYquLJS7awdl/+dm7ugCAACajLdPN2U9eLU6L5ymtMvOkCM9RdEVBVp73UNavvtxWnPjI4qsKtr6QAAAAOs1ixZjwoQJmj59uj766CN16NChfntOTo7C4bBKS0sbzF4qKipSTk5O/TFffvllg/E23E1uwzF/5vV65fV643wW28+yLAX/eY9qvvxejuT1d4ZLS7Y7FgAAaEKmZSoYDDbJ2JmZmXI4tu13h67sDKVffa5SLz5NFdNmqmzyy4osWaGyR15U2eRpSjrmEKVccJJ8/Xs1SVYAANB62FouWZalCy+8UK+99po++OADde3atcH+vffeW263W7Nnz9bo0aMlSb/88otWrFihAQMGSJIGDBigW2+9VcXFxcrKypIkvf/++0pOTlafPn127gltp7LHXlLFi+9KDoeyn7xRnh6d7Y4EAACaWEkopOqHp8qVmb31g7fD2lCFdOW4TZYL2BpHok8pZxyj5LFHqWrWPJU+9rJqPlmoyldnqfLVWfIdsIdSLzhRicMHynA645oZAAC0DraWS+PHj9cLL7ygN954Q4FAoH6NpJSUFCUkJCglJUXnnHOOLrvsMqWnpys5OVkXXnihBgwYoAMOOECSdPjhh6tPnz4aO3as7rrrLhUWFuraa6/V+PHjm8XspC0JvfeZ1t74qCQpY+IEJR66v82JAADAzpKemKSsQIrdMRowHA75Dx8o/+EDVfvdryp9/GVVvjpLNZ9/q8LPv5W7aweljDtBgZOPlMOfYHdcAADQjNi65tJjjz2msrIyHXzwwWrfvn3946WXXqo/5v7779eoUaM0evRoDR48WDk5OXr11Vfr9zudTk2fPl1Op1MDBgzQaaedptNPP10TJ06045S2SfjnpSoad5NkWQqMPUop5x9vdyQAAIB63t13VfYj16rzwmlKvWiMHClJiixdpTVX3a/l/Udr7S2PK1q4xu6YAACgmbD9srit8fl8euSRR/TII49s8ZjOnTvrnXfeiWe0JhNbW6qC066UVVkl34H9lXnHpTIMw+5YAAAAm3C1z1TGdX9X2qWnq+KlGSqd/LKiy1ar9IGpKn30RSX9bahS/36SvP162B0VAADYqNncLa4tsMIRFZ51raLLC+Tqkqucp26W4XHbHQsAAOAvOZISlXLOcer0+fPKeeZW+Q7YQ4pEVfnyTK069GzlH3exQu99Jss07Y4KAABs0CzuFtcWWJal4JX3qWbetzKSEtX+uTvkzEi1OxYAAMA2M5xO+UcMln/EYNV8vUhlj72kyjc/UPXHC1X98UK5u3dSyt9PVODEI+RIaL5rXwIAgPiiXNpJyp54RRVTp0uGoezHb5CnV9etvwkAAGAbmZapYDDYJGNnZmbK4Wg44d23Z2/5nrhR6dcXqezfr6ji2bcUWbJCa/55j0puf1IpZx6r5LP+Jld2RpNkAgAAzQfl0k5QNecLrb3+YUlSxo3/J//hB9qcCAAAtDYloZCqH54qV2Z2XMddG6qQrhyn7OzNj+vukK12N45X+j/PUvnU6Sp7YpqiKwu17t5ntO6hFxQYfZhSLjhJ3t67xDUXAABoPiiXmlh48XIVnXejZJoKnDJCKRecZHckAADQSqUnJikrkGLLZzuSEpX69xOVcu5xCr3zsUofe0m1839UxX/fUcV/31HCwfsq9YKTlHDIftzMBACAVoYFvZtQbF25CsdcJbO8Ur79d1fm3f/gmykAANCqGS6Xko4+RB3enay8dx6T/6iDJYdD1R98pYKT/qmVg89Q+fNvy6yptTsqAACIE8qlJmJFoio65zpFlq6Sq2OOsqfcIsPrsTsWAADATuPbdzflPHWzOn35X6Wcf4IMf4IiPy9V8JI7tGKvE1Ry79OKrVlnd0wAALCDKJeayJprHlD1xwtlJCYo57nb5cpMszsSAACALdydc9Xu1ovU+dv/KePG/5MzN0ux4Dqtu+M/Wr7n8Qr+426FFy+3OyYAAGgkyqUmUPbUayqf8vr6O8NdL2/f7nZHAgAAsJ0zJaDU8aeo8/yXlPX4DfLu0VNWTVjlz76plQeepoJTr1DVxwtkWZbdUQEAwHagXIqzqg/na82/HpAkpV9zvvxHHGRzIgAAgObFcLsUOG6Y8t5/UrlvPiz/iEGSYajq/XkqOO4SrTrkbFW8NENWOGJ3VAAAsA0ol+Io/NsKFZ1znRSLKenE4Uq9aIzdkQAAAJotwzCUMGAP5TxzmzrOe17JZx8nI9Gn8I9LVDzhVi3f6wStm/ScYuvK7Y4KAAD+AuVSnMRKK+ruDFdWKe8+fZV57+XcGQ4AAGAbebp1VOadl6rzN/9T+rXj5Mxpp1jRWpXc+oSW9x+t4BX3KfzbSrtjAgCAzaBcigMrGlXReTco8ttKufKylPP0rXL4vHbHAgAAaHGcaclKu/g0dV7wsrIeuUaevt1lVdWofMprWjlgjApOv1rVn33DukwAADQjLrsDtAZrr39E1R98JSPRp5xnb5crO8PuSAAAAC2a4XErcOIRSjphuKo/Waiyx15S1fvzVPXuJ6p69xN5+/dSygUnKemog2W4//iW1jRNBYPBJsmUmZkph4PfzQIA8GeUSzuo/Nk3VfbkK5KkrEeulXf3XeMyblN9YxQMBuXkN30AAKCFMAxDiYP2VuKgvRVevFxlj09TxUvvqvabn1U87iatvekxpZw3Wsljj5IzJaBgMKgldz6uDH8grjnWhiqkK8cpOzs7ruMCANAaUC7tgOpPv1bwyvskSelXnaukUUPiNnZTfWO0tLhAuf5kKTk1ruMCAIDWybSaz0wgT4/Oyrznn0q/6hyVPfOGyv/zqmL5xSq56TGtu/tpJQzaS9H+uyqj1lRmdjLrXwIAsJNQLu0AZ3aG3J3ay7tHT6Vednrcx8/wB5QVSInrmGsqK+I6HgAAaN1KQiFVPzxVrsz4ztjZkZlAznZpSv/HmUodf4oq/zdLpZNfUuTnpaqa+ak081O5JZUl+uTq1F7uTu3l6pwrR0oSZRMAAE2EcmkHeLp3Ut7MJ2R4PXyzAgAAWq30xKS4/8IrHhw+r5LHjFTg1BGq/fYXVX+0QGWz5yn65Q9SVY0iPy9V5OeldccmJ8nVuX194eRISrQ5PQAArQfl0g5ypsb3sjUAAABsH8Mw5OvfS77+vRQ+aZjWPfCc0irCii4vUHRFgaIFxTLLKxX+frHC3y+WJDkyUuTulCtXp/ZydcrhTr8AAOwAyiUAAAC0Lk6n3B1z5O6YI2lPWeGIoquLFFlfNsWK1spcW6batWWq/XqRZBhyZmfI1SmnrnDKy5Lhcdt9FgAAtBiUSwAAAGjVDI9b7q4d5O7aQZJkVtcourJQ0eUFiqwokFlSpljhGsUK16j2yx8kh0Ou3My6S+g658rZvp3NZwAAQPNGuQQAAIA2xZHgk2fXLvLs2kWSZFaEFFlRqOiKfEWWF8iqCCm6qkjRVUWq+ewbye2SMydD4US/akcMkWe37jKcTlvPAQCA5oRyCQAAAG2aI+CXt283eft2k2VZMksrFF1RoMjyfEVXFMiqrpVjZZHC9z2nVfc9J0dqQAkD91LCoL2UMHhvubt34uYuAIA2jXIJAAAAWM8wDDnTkuVMS5Z3j56yLEux4DqV/vq7PB6PzAWLZJZWKPT2hwq9/aEkyZnTrq5oGrS3EgbtLXeHbJvPAgCAnYtyCQAAANgCwzDkykqXmeBUwoRTlZWRodpvflH1RwtU/ckC1Xz5g2KFa1Q57T1VTntPkuTu2uGPsumgPeVsl2bzWQAA0LQolwAAALDTmZapYDAY93GDwaCclhX3cTcwXC759ukr3z59lXbZ6TKra1Uz/4f1ZdNC1X79syJLVymydJXKn31TkuTp200JB9VdQpcwoL8cAX+T5QMAwA6USwAAANjpSkIhVT88Va7M+F5CtrS4QLn+ZCk5Na7jbokjwavEQXsrcdDekqRYeaVqPv+2vmwK//hb/aPs8WmS0ynvnr3qyybfvrvJ4fPulKwAADQVyiUAAADYIj0xSVmBlLiOuaayIq7jbS9ncpL8hw+U//CBkqRocJ1qPv1a1R8vUPXHCxVZukq1839U7fwfVTrpORlej3z77aaEg/ZWwuC95e3fU4aLb9EBAC0L/+cCAAAAmogrM01Jxx6qpGMPlSRFVhaq+pOFdWXTRwsUK1qr6o8XqvrjhdLtT0r+BDn36SPn/rvJuX8/OXp0kuFwNOqzMzMz5Wjke3c202yayyQlvg4btKSvA4CWh3IJAAAA2EncHXPkPmWEkk8ZIcuyVPj51yq85TElBctl5AdlhKoV+3CBYh8ukCRZPq+svHYy87Jk5WVKyX7JMLb6OWtDFdKV45Sd3TLuXBcMBrXkzseV4Q/EdVy+DnVa2tcBQMtDuQQAAADYwDAMOXbJU8JefZQRSJFlmooFSxRdXqDIigJFVxXJqKmV8dtqOX5bLUlyJPvl6tRerk65cnduL0dSos1nET8Z/kDcL5Nsifg6AGiJKJcAAACAZsBwOOTKbidXdjv59usnKxZTrGCNIsvzFV1RoGh+UGZ5SOEflij8w5K69yT65EgJyJkakCM1WY7UJDlTkyWXJasJ75oHAMDGKJcAAACAZshwOuXqkC1Xh2xp4J6ywhFFVxcrsiJf0RWFihWukVVVo1hVjWIFDdfpcUsKvTJHK7vkydU5V+4uuXJ3yZO7S55cXXLl7pgjw+O258QAAK0O5RIAAADQAhget9xd8+TumidJssIRxdaVyyytkFlaoVjp+udlFYqVV8qorlV40e8KL/p908EcDrnysuTukitXlzy5O28on3Ll6ponZ3LSTj47AEBLRrkEAAAAtECGxy1XdoaUnbHJvuLSdUr521ClVNQqsixfkWWrFVm2WtHl+Yosy5dVVaPoykJFVxZKHy/c5P2O9JT1hdP68qnLH+WTM6ddo+9gBwBonSiXAAAAgNbG6ZCjU3slbubuYJZlKVZcUlc2bSie1pdO0WWrFQuuk1lSptqSMtV+vWiT9xs+j1yd2teVTZ03Kp+65sndqb0Mr2dnnCEAoBmhXAIAAADaEMMw5MrOqJv1tP/um+w3K6vqZjstryub6mY91ZVQ0ZVFsmrCivy6XJFfl29ucDnbZzaY6VS/zlOXPDnTknfCGWJnMU1TwWBw6wc2QmZmphzMkANaDMolAAAAoJUxrR38oT8zIGX2lPbpKUlyrn9Y0ZjSak3FVhT8candsj+eW6FqxfKLFcsvVs1n32wyrCMlqa5s2niR8a55MpM8ksnd7VqaYDCoJXc+rgx/IK7jrg1VSFeOU/ZmZt4BaJ4olwAAAIBWpiQUUvXDU+XKjO8P52tDFep+5ThlH7yvpH0b7LMsS7E1pXWznZavv9xu6R+zn2LFJTLLKlX77S+q/faXTcZ2ORwqS0mSIzUgZ2qyHKmB9c8DcqQEZLj50aU5yvAHlBVIsTsGAJvxX2gAAACgFUpPTNqpP/QbhiFXZppcmWny7bvbJvvNULUiKwr+uNRu6UaX3q0olBGNylxXLnNduaJaven4SYlypgRkJPvlSPDKSPDJ8HnlSNz4uU9GgleGix9zAGBn4r+6AAAAAJqcw58gb+9d5O29yyb7CvPzVXrnU0qLSmZphWKlFTJLK2SWlitWWiGFI7IqqxStrNJmeqdNuV1yJHjl8rhV/d1vKsrJlDM9RY6MFDnTUho+z0iRIz1FDp83/icNAG0E5RIAAAAAWxlOp5TslzuQInVuuM+yLFk1tevLpgqZlVWyqmtlVtfIqq6VVV0js6ZWVlXdc1mWFInKjERlSIqtKVXltmRI9NWVTul15dOGxxYLqbQUORIopNo6FjUH6lAuAQAAANgmO7xQ+BYEg0E5rc0v6G0YhowEnxwJPql95l+OY1mWFI7IrKorntaVlMh/0F5KilmKrS2Tua5csbVlipWUKrauXObaMsVKyqRYTFZVjaJVNdKqom3OvcVCanPPKaRaJRY1x86woyVmRUVFHNNsHuUSAAAAgG3SVAuFLy0uUK4/WUpO3aFxDMOQvB45vR4pTbICHrmPOVipf/EDumVZMitC64umUsVKymWW/On52jLF1tUVUeb654rGv5AKuw0ZS1YpkhaSkbB+DSmfl8XMmzkWNUdT29ESs7K2Js6JNsV/pQAAAABss6ZYKHxNZdP/Vn1LDMOQMzlJzuQkubvmbdN7GhRS6+rKJ7PkT883emx4vS2FlEva9DI+l1OG1yPD4677p9cjw+uW4Vn/zw3b6ve7G7xWJFo3qwtAi7UjJabP7Ylzmk1RLgEAAADAdrAsS2uqQ1KiS0rMkPIyNjnGUN0PW66N3qPKKlmllbJKy2Wtq5BVWtHgeW3RGhmLV8oVidavJyXTqiulotWyQtWNyuuWFHrmbS0N+OVI9ssRSFr/zy28Tk6qe77x62S/HEmJMlgDCMBmUC4BAAAAwHaI+zo7TkkZAS2OVSq3897qmpMraaM1pKprZYUjsmrD6x/rn2+8LRyRGuxb/zwcqVvkPBqTua5c5rryHYpqJCXWl00xr1vOkjJV+hM3M2tq41lVG2ZZrX/udMbhi4bGYAFyNBXKJQAAAADYTk2xzs6fLw9ssIZUI1mWpWDJWqWcOkoZvgSZ5aH1j0qZlaGGrytCMitCiq1/bVVUKVZRKbM8JIUjdeNVVilWWaVYft34DkmR7Q3lcjYsn/5UTDlkKvzMWypvn/3HrKn6mVV1s6qMRF/d1wfbhQXI0VQolwAAAACglTIMQ/K45cjJkGcHfvA3a2plVlT9UUKVV2rdynxVvj5HAYdz87OpaiN/zKCqDUuRaN1gGy7zq9r8ZX5OSeEFP+sv59c4nXIEEv+4hK+xl/m1wVlULECOpkC5BAAAAAD4Sw6fVw6fV8pMq99WUVQk6+ff5NvGosIyzY3Kp82XUQqHFaqolLdrnjzhWF2htX72VF2xVSWZphSLySytkFm6Y4vBG/6EP8qmwEazo/6irHJumD0V8NdddgiAcgkAAAAA0PQMh0OGzyv5vH95XEVFmXwTTt3sJVaWZckKVdfPnqqfTVUeqiuhNn5dXimzsu51rDykyLoyqbJaVmXVH5f5haoVC1UrVtD4dYhcTodKt+tufpvul9vFZX5o0SiXAAAAAAAtgmEYdYuKJyVK7TO3+X1FRUVasfFaQ7FYXcEUjkrhiIxwpP51g+e1ESmyhX3rL/MzYqasqhpZVTU7cmJ15ZOvrnxyuhwq+/431bRLkxHwS4FEGcl+GUmJda+T/TICdc+NQKK0jZf4BYNBOS2r8TmBLaBcAgAAAAC0evFea8gyTf28YrkSoqY6JKfVry+lButNbe4SwIb7ZFmSZdVfHijVLZSu/DWKbk8et0vyuiWPW5bH/cfz9f+Ux611tVVKCQQUyc6pmzXl88jwermLH3YY5RIAAAAAANvJcDhked2yfA65stIbNYZlWVIk+qe1p8JaWVgobySmDG+CrNqwzJpwg/1WbVjW+m2KxuryRKLrF02v1pYusMtd/89KfbvpTrerwewpw+uR4fPK8LjlaLBto+frHxsyoO2iXAIAAAAAwAYb7uZneNxSUmL99hqfZBgO+XJy/+LddaxYbP3sqNr6wql+tlRNbYPX5WVlckWi8pj64y5+GxYlj0RlRaKyQpu/i99fcUuqfOZtVacG6hZET0lavzB63XPnn17/sT1Qfwc/w5/AulMtGOXSDjJNU8Fg4xd/2xKuhQUAAAAAbI3hdMpIdEqJvq0eu7xglRIMh7puVFpZpvlHGfWnWVHbuk2SFIkqFlynWHBd407E6dyolPKvL6QCddtS1t+xLzlQt/3PZVVKkhxJiTIcjm36qKb6OV6SMjMz5djGHK0J5dIOCgaDWrLxwnBxsrS4QLn+ZCk5Na7jAgAAAACwgeFwyEjwSgl/fRe/LbEsS8GStUo5ZYTS3T6ZZZV1d/Mrq5BZVqlYeWXdtk3+GVKsvO4YRWNSLCazpExmSVkjT8SQI+BvMDPKkZIkRyDpj0Jq/b4KM6r8t+cqkJIseT3r16RySTtYCq0NVUhXjtvsnQ5bO8qlOIj3wnCStKayIq7jAQAAAAAQbxsu7XO0z5S3EaWKZVmyqmrqSqf1xVPsz2XUn7dv2Lf+tVUbliyrft+22OwqWW5X/ZpSjg0LnW9unanNrDtl+Dzbfe6tCeUSAAAAsBWmxVIIANAUDMOQ4U+Qw58gtc9s1BhmTa3M8tD60qmifmaUWV6p2J9em2UVqlmzTrHl+XJEYnXFVGT9ffk2rDtVUSWzETlcLqdC/5urFanJ9bOknBvNoNp49pQjKbFuplXAL0fgj+eGu2XWNC0zNQAAALATlYRCqn54qlyZ8b3UgaUQALQGTVXAS9u2hpHD55XD55W28a59RUVFWvfwC/VXIFkxc7vWmNr4Ydb8sSi6EY3JCq5TpLHrTkkyfJ66oinJL2N96RTxOOVcVaQqv79uAXhv3SLwhsfzx3OvZ/22uudyOXfqAumUSwAAAMA2SE9MYimEFoYZZ8DO0VQF/M5aw8hwOmQk+rZpUfTNsUxTVjiiNWvXKvm4YUpzedfPmtp4namKjWZTVcqqrKpbm6oiJLOySlZVTd1YNWHFasKbLIzukFS7XSdlrC+ePKp0Nuq0tgvlEgAAAIBWiRlndVpaydYUeSkEm15TFPAtheFwyPB5pWS/nL26KqExa09FozIrq/8onCpCMiuqZFWEVJpfoKqZn8lvOOvu7BcOywpHNnmucOSPu/dZVt1Mq5qwYmY0zme8KcolAAAAAK0WM85aXsnWFHlbWiGItsdwueRMDciZuumd6ENFRTILg0rYhv+WWZZVt3bU+qLJCkdkVVRI//m8KWLXo1wCAAAAgFaupZVs8c7b0gpBoLE23L3P8LilpERJkistqck/l3IJAAAAAAA0Oy3tks62jHIJAAAAAAA0Oy3tks62jHIJAAAAAAA0Sy3tks62inIJAAAAAABgB7Xly/golwAAAAAAAHZQW76Mj3IJAAAAAAAgDtrqZXwOuwMAAAAAAACg5aJcAgAAAAAAQKNRLgEAAAAAAKDRKJcAAAAAAADQaK2mXHrkkUfUpUsX+Xw+7b///vryyy/tjgQAAAAAANDqtYpy6aWXXtJll12mG264QQsXLtQee+yh4cOHq7i42O5oAAAAAAAArVqrKJfuu+8+nXfeeTrrrLPUp08fTZ48WYmJ/9/enQdFdaV/A/+2YDeICiI7IqugUcElAXHFEcFlVMxEwVJkVKISjRowW6UEGaNiJCEzicEYEcMYYdyZqHGFxomDGhFKUCSKRDQjKCYgi6J2n/ePvPQvHfaWtf1+qrqkz33u6XPox9O3Hu693Q07duxo76EREREREREREWk13fYewPN68uQJMjIy8P7776vaunTpAm9vb6Snp9e5T3V1Naqrq1XPy8rKAAAPHz5s9uuXl5ej8Jf7qKh+3Ox9G/Jz6QPIJF0gdHXYL/tlv63Yb2caK/tlv+yX/bJf9st+2S/77Th9sl/221n6ralXCCFaclhqOn1xqaSkBAqFAubm5mrt5ubmuHbtWp37bNy4EZGRkbXabWxsWmWMRERERERERETt6cGDBzA0NGyVvjt9cUkT77//PkJDQ1XPS0tLYWtri8LCwlb7RVPn9PDhQ9jY2OD27dvo2bNnew+HOhjmBzWE+UH1YW5QQ5gfVB/mBjWE+UENKSsrQ9++fWFsbNxqr9Hpi0smJibQ0dFBcXGxWntxcTEsLCzq3Ecmk0Emk9VqNzQ05H9EqlPPnj2ZG1Qv5gc1hPlB9WFuUEOYH1Qf5gY1hPlBDenSpfVuu93pb+gtlUoxfPhwnD59WtWmVCpx+vRpeHp6tuPIiIiIiIiIiIi0X6c/cwkAQkNDERQUhJdffhnu7u749NNPUVlZiQULFrT30IiIiIiIiIiItJpWFJf8/f1x//59hIeHo6ioCEOGDMGxY8dq3eS7PjKZDBEREXVeKkcvNuYGNYT5QQ1hflB9mBvUEOYH1Ye5QQ1hflBD2iI/JKI1v4uOiIiIiIiIiIi0Wqe/5xIREREREREREbUfFpeIiIiIiIiIiEhjLC4REREREREREZHGWFwiIiIiIiIiIiKNaWVxacuWLbCzs4Oenh48PDxw4cKFBuP37t2L/v37Q09PD4MHD8bRo0fVtgshEB4eDktLS+jr68Pb2xvXr19vzSlQK2pOfnz11VcYM2YMevXqhV69esHb27tW/F//+ldIJBK1x6RJk1p7GtQKmpMbO3furPW+6+npqcVw7dAuzckPLy+vWvkhkUgwdepUVQzXDu1w5swZTJs2DVZWVpBIJDh06FCj+8jlcgwbNgwymQxOTk7YuXNnrZjmHstQx9Tc/Dhw4AAmTpwIU1NT9OzZE56enjh+/LhazNq1a2utHf3792/FWVBraW5+yOXyOj9bioqK1OK4fnR+zc2Nuo4pJBIJBg4cqIrh2qEdNm7ciFdeeQU9evSAmZkZ/Pz8kJeX1+h+bVHz0Lri0r/+9S+EhoYiIiICly5dgpubG3x9fXHv3r064//73/9izpw5WLRoETIzM+Hn5wc/Pz/k5OSoYj766CP84x//wNatW3H+/HkYGBjA19cXjx8/bqtpUQtpbn7I5XLMmTMHqampSE9Ph42NDXx8fPDzzz+rxU2aNAl3795VPRITE9tiOtSCmpsbANCzZ0+19/3WrVtq27l2aI/m5seBAwfUciMnJwc6OjqYNWuWWhzXjs6vsrISbm5u2LJlS5PiCwoKMHXqVIwfPx5ZWVlYtWoVgoOD1QoImqxH1DE1Nz/OnDmDiRMn4ujRo8jIyMD48eMxbdo0ZGZmqsUNHDhQbe34/vvvW2P41Mqamx818vLy1N5/MzMz1TauH9qhubnx97//XS0nbt++DWNj41rHHVw7Or+0tDQsW7YM586dw8mTJ/H06VP4+PigsrKy3n3arOYhtIy7u7tYtmyZ6rlCoRBWVlZi48aNdcbPnj1bTJ06Va3Nw8NDLFmyRAghhFKpFBYWFmLz5s2q7aWlpUImk4nExMRWmAG1pubmxx89e/ZM9OjRQ3z99deqtqCgIDFjxoyWHiq1sebmRnx8vDA0NKy3P64d2uV5146YmBjRo0cPUVFRoWrj2qF9AIiDBw82GPPOO++IgQMHqrX5+/sLX19f1fPnzTfqmJqSH3V56aWXRGRkpOp5RESEcHNza7mBUYfQlPxITU0VAMSvv/5abwzXD+2jydpx8OBBIZFIxE8//aRq49qhne7duycAiLS0tHpj2qrmoVVnLj158gQZGRnw9vZWtXXp0gXe3t5IT0+vc5/09HS1eADw9fVVxRcUFKCoqEgtxtDQEB4eHvX2SR2TJvnxR1VVVXj69CmMjY3V2uVyOczMzODi4oKQkBA8ePCgRcdOrUvT3KioqICtrS1sbGwwY8YMXLlyRbWNa4f2aIm1Iy4uDgEBATAwMFBr59rx4mnsuKMl8o20h1KpRHl5ea3jjuvXr8PKygoODg6YO3cuCgsL22mE1B6GDBkCS0tLTJw4EWfPnlW1c/2gGnFxcfD29oatra1aO9cO7VNWVgYAtT4nfq+tah5aVVwqKSmBQqGAubm5Wru5uXmta5FrFBUVNRhf829z+qSOSZP8+KN3330XVlZWav/xJk2ahISEBJw+fRqbNm1CWloaJk+eDIVC0aLjp9ajSW64uLhgx44dSE5Oxq5du6BUKjFy5EjcuXMHANcObfK8a8eFCxeQk5OD4OBgtXauHS+m+o47Hj58iEePHrXIZxVpj+joaFRUVGD27NmqNg8PD+zcuRPHjh1DbGwsCgoKMGbMGJSXl7fjSKktWFpaYuvWrdi/fz/2798PGxsbeHl54dKlSwBa5liXOr///e9/+O6772odd3Dt0D5KpRKrVq3CqFGjMGjQoHrj2qrmodvkSKIXXFRUFJKSkiCXy9Vu3BwQEKD6efDgwXB1dYWjoyPkcjkmTJjQHkOlNuDp6QlPT0/V85EjR2LAgAH48ssvsW7dunYcGXU0cXFxGDx4MNzd3dXauXYQUUN2796NyMhIJCcnq91TZ/LkyaqfXV1d4eHhAVtbW+zZsweLFi1qj6FSG3FxcYGLi4vq+ciRI5Gfn4+YmBj885//bMeRUUfy9ddfw8jICH5+fmrtXDu0z7Jly5CTk9Nh7p2lVWcumZiYQEdHB8XFxWrtxcXFsLCwqHMfCwuLBuNr/m1On9QxaZIfNaKjoxEVFYUTJ07A1dW1wVgHBweYmJjgxo0bzz1mahvPkxs1unbtiqFDh6red64d2uN58qOyshJJSUlNOmjj2vFiqO+4o2fPntDX12+R9Yg6v6SkJAQHB2PPnj21LmX4IyMjIzg7O3PteEG5u7ur3nuuHySEwI4dOxAYGAipVNpgLNeOzm358uU4fPgwUlNT0adPnwZj26rmoVXFJalUiuHDh+P06dOqNqVSidOnT6udYfB7np6eavEAcPLkSVW8vb09LCws1GIePnyI8+fP19sndUya5Afw253z161bh2PHjuHll19u9HXu3LmDBw8ewNLSskXGTa1P09z4PYVCgezsbNX7zrVDezxPfuzduxfV1dWYN29eo6/DtePF0NhxR0usR9S5JSYmYsGCBUhMTMTUqVMbja+oqEB+fj7XjhdUVlaW6r3n+kFpaWm4ceNGk/6oxbWjcxJCYPny5Th48CBSUlJgb2/f6D5tVvNo1q3IO4GkpCQhk8nEzp07xdWrV8XixYuFkZGRKCoqEkIIERgYKN577z1V/NmzZ4Wurq6Ijo4Wubm5IiIiQnTt2lVkZ2erYqKiooSRkZFITk4Wly9fFjNmzBD29vbi0aNHbT4/ej7NzY+oqCghlUrFvn37xN27d1WP8vJyIYQQ5eXlYvXq1SI9PV0UFBSIU6dOiWHDhol+/fqJx48ft8scSTPNzY3IyEhx/PhxkZ+fLzIyMkRAQIDQ09MTV65cUcVw7dAezc2PGqNHjxb+/v612rl2aI/y8nKRmZkpMjMzBQDxySefiMzMTHHr1i0hhBDvvfeeCAwMVMXfvHlTdOvWTbz99tsiNzdXbNmyRejo6Ihjx46pYhrLN+o8mpsf33zzjdDV1RVbtmxRO+4oLS1VxYSFhQm5XC4KCgrE2bNnhbe3tzAxMRH37t1r8/nR82lufsTExIhDhw6J69evi+zsbLFy5UrRpUsXcerUKVUM1w/t0NzcqDFv3jzh4eFRZ59cO7RDSEiIMDQ0FHK5XO1zoqqqShXTXjUPrSsuCSHEZ599Jvr27SukUqlwd3cX586dU20bN26cCAoKUovfs2ePcHZ2FlKpVAwcOFAcOXJEbbtSqRRr1qwR5ubmQiaTiQkTJoi8vLy2mAq1gubkh62trQBQ6xERESGEEKKqqkr4+PgIU1NT0bVrV2Fraytef/11foB3Us3JjVWrVqlizc3NxZQpU8SlS5fU+uPaoV2a+9ly7do1AUCcOHGiVl9cO7RHzVeD//FRkw9BQUFi3LhxtfYZMmSIkEqlwsHBQcTHx9fqt6F8o86jufkxbty4BuOFEMLf319YWloKqVQqrK2thb+/v7hx40bbToxaRHPzY9OmTcLR0VHo6ekJY2Nj4eXlJVJSUmr1y/Wj89Pks6W0tFTo6+uLbdu21dkn1w7tUFdeAFA7lmivmofk/w+QiIiIiIiIiIio2bTqnktERERERERERNS2WFwiIiIiIiIiIiKNsbhEREREREREREQaY3GJiIiIiIiIiIg0xuISERERERERERFpjMUlIiIiIiIiIiLSGItLRERERERERESkMRaXiIiIiIiIiIjayZkzZzBt2jRYWVlBIpHg0KFDze5DCIHo6Gg4OztDJpPB2toa69evb/nB1oPFJSIiIqIWYmdnBy8vr/YeRr06+viIiIheRJWVlXBzc8OWLVs07mPlypXYvn07oqOjce3aNfz73/+Gu7t7C46yYSwuERERUYcll8shkUjUHt27d8ewYcMQExODZ8+etfcQ24SdnZ3a70AqlcLOzg7BwcG4fft2ew+PiIiInsPkyZPx4YcfYubMmXVur66uxurVq2FtbQ0DAwN4eHhALpertufm5iI2NhbJycmYPn067O3tMXz4cEycOLGNZgDottkrEREREWlozpw5mDJlCoQQKCoqQkJCAkJDQ5Gbm4tt27a19/DaRJ8+fbBx40YAQHl5OeRyOXbs2IGjR4/i8uXLMDExabSPvLw8SCSS1h4qERERtaDly5fj6tWrSEpKgpWVFQ4ePIhJkyYhOzsb/fr1w7fffgsHBwccPnwYkyZNghAC3t7e+Oijj2BsbNwmY2RxiYiIiDq8YcOGYd68earnb7zxBvr374/t27dj/fr1MDU1bcfRtQ1DQ0O130FISAjMzMzw+eefIz4+Hm+//Xad+z19+hQKhQJ6enqQyWRtNVwiIiJqAYWFhYiPj0dhYSGsrKwAAKtXr8axY8cQHx+PDRs24ObNm7h16xb27t2LhIQEKBQKvPXWW3jttdeQkpLSJuPkZXFERETU6RgYGGDEiBEQQiA/P19t2927dxESEoK+fftCKpXCysoKixcvxr1799TifvnlF7z11ltwdHSEnp4eevfujeHDh2Pz5s1qcV988QV8fHxgbW0NqVQKS0tLzJs3Dz/99FOTx3vx4kXMnDkTJiYmkMlkcHFxwfr165/7sj5fX18AwI0bNwAAa9euhUQiwZUrVxAaGoo+ffpAT08P586dA1D/PZcyMzMxa9YsmJubQyaTwcbGBnPmzKn1uz116hR8fHxgZGQEPT09uLq6YuvWrc81ByIiIqpfdnY2FAoFnJ2d0b17d9UjLS1N9TmtVCpRXV2NhIQEjBkzBl5eXoiLi0Nqairy8vLaZJw8c4mIiIg6pZoDqt+f7l1YWAhPT088efIEixYtgqOjI27cuIHY2Fikpqbi4sWLMDQ0BADMmjULZ86cwdKlS+Hq6opHjx4hNzcXcrlc7Syg6OhojBgxAitWrICxsTFycnKwfft2pKSkIDs7G717925wnEeOHMGrr74KJycnhIWFwdjYGOnp6QgPD0dWVhb27t2r8e/g+vXrAFDrkri5c+dCX18fYWFhkEgksLS0rLePw4cP4y9/+QsMDAwQHBwMJycnFBUV4fjx48jJyYGjoyMAYNu2bVi6dClGjBiBDz74AAYGBjh58iRCQkKQn59fqyhHREREz6+iogI6OjrIyMiAjo6O2rbu3bsDACwtLaGrqwtnZ2fVtgEDBgD47djIxcWl1cfJ4hIRERF1eFVVVSgpKVHdc2nr1q3IzMyEu7u72oHUm2++iadPnyIzMxN9+vRRtc+aNQsjRoxATEwM1q5di7KyMqSkpCAkJASfffZZg6+dnZ0NAwMDtbbp06fD29sbcXFxeOedd+rd9/Hjx1i0aBE8PDyQkpICXd3fDr2WLFkCNzc3hIaGQi6XN+kb3BQKBUpKSgD83z2XIiMjoaurizlz5qjFGhkZ4dSpU6rXq09VVRUWLFgAQ0NDZGZmwtraWrUtPDwcSqUSwG9ng61YsQIBAQHYvXu3KuaNN97AypUr8cknnyAkJAQODg6NzoOIiIiabujQoVAoFLh37x7GjBlTZ8yoUaPw7Nkz5Ofnq/4o9OOPPwIAbG1t22ScvCyOiIiIOryIiAiYmprCzMwMrq6u+OKLL/Dqq68iOTlZFVNWVobDhw9j+vTp0NPTQ0lJiephZ2cHJycnnDhxAgCgr68PmUyG8+fPN3p5W01hSalUoqysDCUlJXBzc4OhoSHOnz/f4L4nT55EcXExFixYgNLSUrUxTZkyBQBUY2rMtWvXYGpqClNTUzg4OGDhwoUwMTFBcnIyBg0apBa7atWqRgtLAHD8+HGUlJQgLCxMrbBUo0uX3w4V9+3bh+rqaixatEhtDiUlJZg2bRqUSiVOnTrVpHkQERGRuoqKCmRlZSErKwsAUFBQgKysLBQWFsLZ2Rlz587F/PnzceDAARQUFODChQvYuHEjjhw5AgDw9vbGsGHDsHDhQmRmZiIjIwNLlizBxIkT1f4I15p45hIRERF1eIsXL8asWbPw9OlTZGdnY9OmTbhz5w709PRUMXl5eVAqlYiLi0NcXFyd/dScWSOVSvHpp59i5cqVsLe3x0svvYQ//elP8PPzw4QJE9T2SUlJwd/+9jecP38ejx8/Vtv266+/Njju3NxcAMDChQvrjSkuLm6wjxp2dnb46quvVOO3srKCk5NTnbFNPZCsuaxu6NChDcbVzMPb27vemKbOg4iIiNRdvHgR48ePVz0PDQ0FAAQFBWHnzp2Ij4/Hhx9+iLCwMPz8888wMTHBiBEj8Oc//xnAb38M+vbbb/Hmm29i7NixMDAwwOTJk/Hxxx+32RxYXCIiIqIOr1+/fqrCxuTJkzF69GiMHj0aS5cuRVJSEgBACAEAmDdvHoKCgursR19fX/Xz0qVLMWPGDBw5cgRpaWnYt28fPv/8c/j7+6v6/OGHH+Dj4wMnJydERUXB3t4e+vr6kEgkCAgIUF02Vp+aMW3evBlDhgypM6bmm18aY2Bg0GBx5/e6devWpLimqplHQkJCvfdv4iVxREREmvHy8lJ91tala9euiIyMRGRkZL0xVlZW2L9/f2sMr0lYXCIiIqJOZ+TIkQgMDERCQgJWrFiBkSNHwsnJCRKJBE+ePGlyEcbS0hLBwcEIDg6GQqFAYGAgEhMTERYWhldeeQW7d++GQqHAd999B3t7e9V+lZWVjZ61BPxWFAOaVxhqSzVnOGVlZcHHx6feuJp5mJiYdMh5EBERUfviPZeIiIioU1qzZg10dHQQHh4OAOjduzemTJmCAwcO4Ny5c7XihRC4f/8+gN9uZF1VVaW2XUdHB66urgCAX375RdVWs+/vbdiwodGzlgDA19cXZmZmiIqKUvX5e48ePUJ5eXmj/bQWHx8fmJiY4OOPP8bdu3drba+Z9+zZsyGTyRAREYFHjx7ViisrK0N1dXWrj5eIiIg6Jp65RERERJ2Sk5MTAgIC8M033+A///kPxowZg9jYWIwePRpjx47F/PnzMXToUCiVSty8eRPJycmYP38+1q5dix9//BHjxo3DzJkzMWjQIPTq1Qu5ubmIjY2Fvb296ttYZs6ciZiYGEyZMgWLFy+GVCrFyZMncfnyZZiYmDQ6RgMDAyQkJMDPzw8uLi5YuHAhnJycUFpaimvXruHAgQM4ePBgk74trjV069YNcXFxeO211zBo0CAEBwfDyckJ9+/fx/HjxxEaGooZM2agT58+iI2NRXBwMAYMGIDAwEDY2tri/v37yM7OxqFDh3D16lXY2dm1yzyIiIiofbG4RERERJ3WBx98gMTERISHhyM1NRU2NjbIyMjApk2bkJycjF27dkFPTw82NjaYNm0aZs+eDQCwsbHBwoULkZqaikOHDqG6uhrW1tZ4/fXX8e6776ruWTRq1Cjs378f69atw5o1a6Cvrw9vb2+kpaVh7NixTRqjr68vfvjhB0RFRWHXrl24f/8+evXqBUdHR4SGhqrOlmov06dPx/fff48NGzYgLi4O5eXlMDc3x5gxYzB48GBV3IIFC+Ds7Izo6Gh8+eWXKC0thYmJCVxcXLBu3TpYWFi04yyIiIioPUlEQ3eNIiIiIiIiIiIiagDvuURERERERERERBpjcYmIiIiIiIiIiDTG4hIREREREREREWmMxSUiIiIiIiIiItIYi0tERERERERERKQxFpeIiIiIiIiIiEhjLC4REREREREREZHGWFwiIiIiIiIiIiKNsbhEREREREREREQaY3GJiIiIiIiIiIg0xuISERERERERERFpjMUlIiIiIiIiIiLS2P8De2EVifpZytwAAAAASUVORK5CYII=",
      "text/plain": [
       "<Figure size 1400x500 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(14,5))\n",
    "sns.histplot(x=df['resale_price'],kde=True,color='Crimson')\n",
    "plt.xlabel('Resale Price',fontsize=13)\n",
    "plt.xlim(0,2e6)\n",
    "plt.title('Distribution of Resale Price')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0.5, 1.0, 'Correlational Heatmap')"
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.heatmap(numerical.corr(),annot=True) \n",
    "plt.title('Correlational Heatmap')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Categorical Features"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "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": 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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 features in categorical:\n",
    "    sns.countplot(df[features],palette='inferno')\n",
    "    plt.xlabel('count')\n",
    "    plt.ylabel(features)\n",
    "    plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Below graphs show the Variation in Resale Price due to different types of insurance,Companies,Transmission and many other features"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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qNDRU7733nn39tdPMy5cvV2xsrDw8PLRs2TJJ0sKFC1W3bl15eHioTp06mjNnTp5jy8jIUOvWrVWpUiXde++92rZtm8P6LVu2KCYmRp6engoKCtKgQYN0+fJl+/qQkBBNmjRJTz31lHx8fHT33XfrzTfftK+/cuWKEhISFBAQIA8PDwUHB2vy5MkOx3ft9HSzZs3yPIj9xx9/VMWKFfXFF19IkrKyspSYmKgaNWrIy8tLTZo00aZNm4x/hgAA4PbgVGhMT0/XE088IUlydXXVr7/+Km9vb7388st65ZVXCtTHzz//rHXr1ik+Pl5eXl551t9xxx3Kzc3Vww8/rJ9//lmbN2/W+vXrlZGRoUcffdSh7eHDh/XJJ59o3bp1evfdd7Vo0SJ16tRJJ06c0ObNm/XKK6/opZde0ldffeWwXVJSkrp166bdu3crLi5O//jHP5Senu7Q5oUXXtBzzz2n9PR0tWvXTsuWLdPo0aM1ceJEpaena9KkSUpKStJbb73lsN2oUaOUmJio1NRURURE6LHHHlN2dra93vbt26tbt27as2ePli9fri1btighIcGhj+nTpys6Olq7du3SwIEDNWDAAO3fv1+SNGvWLK1atUr//ve/tX//fi1btkwhISHXHeu4uDilpKTojzfKL1++XIGBgYqJiZEkJSQkaNu2bUpJSdGePXvUvXt3tW/fXgcPHszvj1BZWVm6cOGCwwsAAJRPToVGLy8v+3WMAQEBOnz4sH3dmTNnCtTHoUOHZFmW6tSpk2+bDRs2aO/evXrnnXfUuHFjNWnSREuXLtXmzZv19ddf29vl5uZq8eLFqlevnjp37qzWrVtr//79mjlzpmrXrq0nn3xStWvX1saNGx367969u/r27auIiAiNHz9e0dHRev311x3aDB48WI888ohq1qypgIAAjRkzRtOnT7cve+SRRzRkyBDNnz/fYbvExER16tRJERERGjdunI4ePapDhw5JkiZPnqy4uDgNHjxY4eHhatasmWbNmqWlS5fqt99+s/fRsWNHDRw4UGFhYRoxYoSqVKliP4Zjx44pPDxcLVq0UHBwsFq0aKHHHnvsuuPYo0cPff/999qyZYt92TvvvKPHHntMNptNx44dU3JyslasWKGYmBjVqlVLiYmJatGihZKTk/P985k8ebL8/Pzsr6CgoHzbAgCAss2p0PjAAw/YA0jHjh31/PPPa+LEiXrqqaf0wAMPFKiPgjweMj09XUFBQQ5hpF69errjjjscZgRDQkLk4+Njf1+9enXVq1dPFSpUcFh2+vRph/6bNm2a5/2fZxqjo6PtP1++fFmHDx9Wnz595O3tbX9NmDDBIThLUoMGDew/BwQESJJ9/7t379aSJUsc+mjXrp1yc3MdHmf0xz5sNpv8/f3tffTu3VupqamqXbu2Bg0adMNv6Klataratm1rP72emZmpbdu2KS4uTpK0d+9e5eTkKCIiwqGmzZs35zmuPxo5cqTOnz9vfx0/fjzftgAAoGxz6kaYGTNm6NKlS5KkcePG6dKlS1q+fLnCw8MLfOd0eHi4bDZbkdzs8uebU2w223WX5ebmFrrvP546v3bMCxYsUJMmTRzaubi45FuTzWaTJPv+L126pKeffvq635xz9913X7ePPx9Do0aNlJmZqU8++USff/65evTooTZt2jhcl/lHcXFxGjRokF5//XW98847ioyMVGRkpL0eFxcX7dy5M89xeHt7X7c/SXJ3d5e7u3u+6wEAQPlR6NCYk5OjEydO2GfBvLy8NG/evELvuHLlymrXrp1mz56tQYMG5bmu8dy5c6pbt66OHz+u48eP22cb09LSdO7cOdWrV6/Q+/yz7du326/NvPY+Kioq3/bVq1dXYGCgMjIy7LN0zmjUqJHS0tIUFhbmdB+S5Ovrq0cffVSPPvqo/v73v6t9+/b6+eefVbly5TxtH374YfXv31/r1q3TO++843DcUVFRysnJ0enTp+3XOAIAAPxRoUOji4uL2rZtq/T0dN1xxx03tfPZs2erefPmuv/++/Xyyy+rQYMGys7O1vr16zV37lylpaUpMjJScXFxmjlzprKzszVw4EDFxsY6nDZ21ooVKxQdHa0WLVpo2bJl2rFjhxYtWnTDbcaNG6dBgwbJz89P7du3V1ZWlr755hudPXtWQ4cOLdB+R4wYoQceeEAJCQnq27evvLy8lJaWpvXr1+uNN94oUB8zZsxQQECAoqKiVKFCBa1YsUL+/v75/pl4eXmpa9euSkpKUnp6usP1jxEREYqLi9MTTzyh6dOnKyoqSj/++KM2bNigBg0aqFOnTgWqCQAAlF9OXdNYv379Ivl+6dDQUH377bdq3bq1nn/+edWvX18PPfSQNmzYoLlz58pms+mjjz7SnXfeqZYtW6pNmzYKDQ3V8uXLb3rf0u8BMCUlRQ0aNNDSpUv17rvvGmcw+/btq4ULFyo5OVmRkZGKjY3VkiVLbvh93H/WoEEDbd68WQcOHFBMTIyioqI0evRoBQYGFrgPHx8fTZ06VdHR0brvvvt05MgRrV271uE6zj+Li4vT7t27FRMT43AaXJKSk5P1xBNP6Pnnn1ft2rXVtWtXff3113naAQCA25PNKsgdKX+ybt06jRw5UuPHj1fjxo3znFq+0ZddlxY2m00ffPCBunbtWtKllBvXvvD8yY1Py83braTLAQCg3JgXPeuW9X3t8/v8+fM3zHBO3QjTsWNHSVKXLl3sN3lIv98RbbPZlJOT40y3AAAAKKWcCo1/ft4hAAAAyjenQmNsbGxR11HsnDgrDwAAcNtyKjRe+77i/LRs2dKpYgAAAFA6ORUaW7VqlWfZH69t5JpGAACA8sWpR+6cPXvW4XX69GmtW7dO99133w2/zg4AAABlk1MzjX5+fnmWPfTQQ3Jzc9PQoUO1c+fOmy4MAAAApYdTM435qV69uvbv31+UXQIAAKAUcGqmcc+ePQ7vLcvSyZMnNWXKFDVs2LAo6gIAAEAp4lRobNiwoWw2W57H1jzwwANavHhxkRQGAACA0sOp0JiZmenwvkKFCqpatao8PDyKpCgAAACULk6FxuDg4DzLzp07R2gEAAAop5y6EeaVV17R8uXL7e979OihypUrq0aNGtq9e3eRFQcAAIDSwanQOG/ePAUFBUmS1q9fr/Xr12vdunXq0KGDhg0bVqQFAgAAoOQ5dXr61KlT9tC4evVq9ejRQ23btlVISIiaNGlSpAUCAACg5Dk103jnnXfq+PHjkqR169apTZs2kn5/9A5fIQgAAFD+ODXT+Mgjj6hnz54KDw/XTz/9pA4dOkiSdu3apbCwsCItEAAAACXPqdD42muvKSQkRMePH9fUqVPl7e0tSTp58qQGDhxYpAUCAACg5DkVGitWrKjExMQ8y4cMGXLTBQEAAKD0cSo0StLBgwe1ceNGnT59Wrm5uQ7rRo8efdOFAQAAoPRwKjQuWLBAAwYMUJUqVeTv7y+bzWZfZ7PZCI0AAADljFOhccKECZo4caJGjBhR1PUAAACgFHLqkTtnz55V9+7di7oWAAAAlFJOhcbu3bvrs88+K+paAAAAUEo5dXo6LCxMSUlJ2r59uyIjI1WxYkWH9YMGDSqS4gAAAFA62CzLsgq7Uc2aNfPv0GZTRkbGTRWFsunChQvy8/PTkxuflpu3W0mXAwBAuTEvetYt6/va5/f58+fl6+ubbzunZhozMzOdLgwAAABlT4FD49ChQzV+/Hh5eXlp6NCh+baz2WyaPn16kRQHAACA0qHAoXHXrl26evWq/ef8/PGZjQAAACgfChwaN27ceN2fAQAAUP459cgdAAAA3F4IjQAAADAiNAIAAMCI0AgAAAAjQiMAAACMCI0AAAAwIjQCAADAiNAIAAAAI0IjAAAAjAiNAAAAMCI0AgAAwIjQCAAAACPXki4A5c/MRlPl6+tb0mUAAIAixEwjAAAAjAiNAAAAMCI0AgAAwIjQCAAAACNCIwAAAIwIjQAAADAiNAIAAMCI0AgAAAAjQiMAAACMCI0AAAAwIjQCAADAiNAIAAAAI0IjAAAAjAiNAAAAMCI0AgAAwIjQCAAAACNCIwAAAIwIjQAAADAiNAIAAMCI0AgAAAAjQiMAAACMCI0AAAAwIjQCAADAiNAIAAAAI9eSLgDlz/DB38rNzbukywAA3EKz5kWXdAkoZsw0AgAAwIjQCAAAACNCIwAAAIwIjQAAADAiNAIAAMCI0AgAAAAjQiMAAACMCI0AAAAwIjQCAADAiNAIAAAAI0IjAAAAjAiNAAAAMCI0AgAAwIjQCAAAACNCIwAAAIwIjQAAADAiNAIAAMCI0AgAAAAjQiMAAACMCI0AAAAwIjQCAADAiNAIAAAAI0IjAAAAjAiNAAAAMCI0AgAAwIjQCAAAACNCIwAAAIwIjQAAADAiNAIAAMCI0AgAAAAjQiMAAACMCI0AAAAwIjQCAADAiNAIAAAAI0IjAAAAjAiNAAAAMCI0AgAAwIjQCAAAACNCIwAAAIwIjQAAADAiNAIAAMCI0AgAAAAjQiMAAACMCI0AAAAwIjQCAADAiNBYAJs2bZLNZsv31bp16xKtqUKFCvLz81NUVJSGDx+ukydPFns9AACgfCM0FkCzZs108uTJPK/58+fLZrNp4MCBTvd95cqVm6pt//79+v777/X1119rxIgR+vzzz1W/fn3t3bv3pvoFAAD4I0JjAbi5ucnf39/hdfbsWSUmJurFF19U9+7d7W3/+9//qkOHDvL29lb16tX1+OOP68yZM/b1rVq1UkJCggYPHqwqVaqoXbt2kqTNmzfr/vvvl7u7uwICAvTCCy8oOzvbWFu1atXk7++viIgI/eMf/9DWrVtVtWpVDRgwwKHdwoULVbduXXl4eKhOnTqaM2eOfd2RI0dks9mUkpKiZs2aycPDQ/Xr19fmzZtvuO+srCxduHDB4QUAAMonQqMTzp07p4cfflitWrXS+PHjHZb/9a9/VVRUlL755hutW7dOP/zwg3r06OGw/VtvvSU3Nzdt3bpV8+bN03fffaeOHTvqvvvu0+7duzV37lwtWrRIEyZMKHRtnp6eeuaZZ7R161adPn1akrRs2TKNHj1aEydOVHp6uiZNmqSkpCS99dZbDtsOGzZMzz//vHbt2qWmTZuqc+fO+umnn/Ld1+TJk+Xn52d/BQUFFbpeAABQNriWdAFlTW5urnr27ClXV1ctW7ZMNpvNvu6NN95QVFSUJk2aZF+2ePFiBQUF6cCBA4qIiJAkhYeHa+rUqfY2o0aNUlBQkN544w3ZbDbVqVNH33//vUaMGKHRo0erQoXCZfs6depI+n0GsVq1ahozZoymT5+uRx55RJJUs2ZNpaWlaf78+erVq5d9u4SEBHXr1k2SNHfuXK1bt06LFi3S8OHDr7ufkSNHaujQofb3Fy5cIDgCAFBOERoL6cUXX9S2bdu0Y8cO+fj4OKzbvXu3Nm7cKG9v7zzbHT582B4aGzdu7LAuPT1dTZs2dQigzZs316VLl3TixAndfffdharRsixJks1m0+XLl3X48GH16dNH/fr1s7fJzs6Wn5+fw3ZNmza1/+zq6qro6Gilp6fnux93d3e5u7sXqjYAAFA2ERoLISUlRdOmTdOaNWsUHh6eZ/2lS5fUuXNnvfLKK3nWBQQE2H/28vK6pXVeC3ohISG6dOmSJGnBggVq0qSJQzsXF5dbWgcAACg/CI0FlJqaqj59+mjKlCn2m1f+rFGjRlq5cqVCQkLk6lrwoa1bt65Wrlwpy7Lss41bt26Vj4+P7rrrrkLV+euvv+rNN99Uy5YtVbVqVUlSYGCgMjIyFBcXd8Ntt2/frpYtW0r6fSZy586dSkhIKNT+AQBA+cSNMAVw5swZde3aVa1atdI///lPnTp1yuH1448/SpLi4+P1888/67HHHtPXX3+tw4cP69NPP9WTTz6pnJycfPsfOHCgjh8/rmeffVb79u3TRx99pDFjxmjo0KHG6xlPnz6tU6dO6eDBg0pJSVHz5s115swZzZ07195m3Lhxmjx5smbNmqUDBw5o7969Sk5O1owZMxz6mj17tj744APt27dP8fHxOnv2rJ566qmbGDkAAFBeMNNYAGvWrNHRo0d19OhRh9PM1wQHB+vIkSMKDAzU1q1bNWLECLVt21ZZWVkKDg5W+/btbxj+atSoobVr12rYsGG69957VblyZfXp00cvvfSSsbbatWvLZrPJ29tboaGhatu2rYYOHSp/f397m759+6pSpUp69dVXNWzYMHl5eSkyMlKDBw926GvKlCmaMmWKUlNTFRYWplWrVqlKlSoFHygAAFBu2axrd03gtnXkyBHVrFlTu3btUsOGDZ3u58KFC/Lz89PTT26Um1vem4EAAOXHrHnRJV0Cisi1z+/z58/L19c333acngYAAIARoREAAABGXNMIhYSEiKsUAADAjTDTCAAAACNCIwAAAIwIjQAAADAiNAIAAMCI0AgAAAAjQiMAAACMCI0AAAAwIjQCAADAiNAIAAAAI0IjAAAAjAiNAAAAMCI0AgAAwIjQCAAAACNCIwAAAIwIjQAAADAiNAIAAMCI0AgAAAAjQiMAAACMCI0AAAAwIjQCAADAiNAIAAAAI0IjAAAAjAiNAAAAMCI0AgAAwIjQCAAAACNCIwAAAIwIjQAAADAiNAIAAMCI0AgAAAAjQiMAAACMCI0AAAAwIjQCAADAiNAIAAAAI0IjAAAAjAiNAAAAMCI0AgAAwIjQCAAAACNCIwAAAIxcS7oAlD9TZzaSr69vSZcBAACKEDONAAAAMCI0AgAAwIjQCAAAACNCIwAAAIwIjQAAADAiNAIAAMCI0AgAAAAjQiMAAACMCI0AAAAwIjQCAADAiNAIAAAAI757GkXGsixJ0oULF0q4EgAAUFDXPrevfY7nh9CIIvPTTz9JkoKCgkq4EgAAUFgXL16Un59fvusJjSgylStXliQdO3bshr90uDkXLlxQUFCQjh8/Ll9f35Iup1xjrIsPY108GOfiU5bG2rIsXbx4UYGBgTdsR2hEkalQ4fdLZP38/Er9X5DywNfXl3EuJox18WGsiwfjXHzKylgXZLKHG2EAAABgRGgEAACAEaERRcbd3V1jxoyRu7t7SZdSrjHOxYexLj6MdfFgnItPeRxrm2W6vxoAAAC3PWYaAQAAYERoBAAAgBGhEQAAAEaERgAAABgRGlEos2fPVkhIiDw8PNSkSRPt2LHjhu1XrFihOnXqyMPDQ5GRkVq7dm0xVVq2FWacFyxYoJiYGN15552688471aZNG+OfC/5/hf2dviYlJUU2m01du3a9tQWWE4Ud53Pnzik+Pl4BAQFyd3dXREQE/34UUGHHeubMmapdu7Y8PT0VFBSkIUOG6LfffiumasumL774Qp07d1ZgYKBsNps+/PBD4zabNm1So0aN5O7urrCwMC1ZsuSW11nkLKCAUlJSLDc3N2vx4sXW//t//8/q16+fdccdd1g//PDDddtv3brVcnFxsaZOnWqlpaVZL730klWxYkVr7969xVx52VLYce7Zs6c1e/Zsa9euXVZ6errVu3dvy8/Pzzpx4kQxV172FHasr8nMzLRq1KhhxcTEWA8//HDxFFuGFXacs7KyrOjoaKtjx47Wli1brMzMTGvTpk1WampqMVde9hR2rJctW2a5u7tby5YtszIzM61PP/3UCggIsIYMGVLMlZcta9eutUaNGmW9//77liTrgw8+uGH7jIwMq1KlStbQoUOttLQ06/XXX7dcXFysdevWFU/BRYTQiAK7//77rfj4ePv7nJwcKzAw0Jo8efJ12/fo0cPq1KmTw7ImTZpYTz/99C2ts6wr7Dj/WXZ2tuXj42O99dZbt6rEcsOZsc7OzraaNWtmLVy40OrVqxehsQAKO85z5861QkNDrStXrhRXieVGYcc6Pj7e+utf/+qwbOjQoVbz5s1vaZ3lSUFC4/Dhw6177rnHYdmjjz5qtWvX7hZWVvQ4PY0CuXLlinbu3Kk2bdrYl1WoUEFt2rTRtm3brrvNtm3bHNpLUrt27fJtD+fG+c9++eUXXb16VZUrV75VZZYLzo71yy+/rGrVqqlPnz7FUWaZ58w4r1q1Sk2bNlV8fLyqV6+u+vXra9KkScrJySmussskZ8a6WbNm2rlzp/0UdkZGhtauXauOHTsWS823i/Lyeeha0gWgbDhz5oxycnJUvXp1h+XVq1fXvn37rrvNqVOnrtv+1KlTt6zOss6Zcf6zESNGKDAwMM8/UHDkzFhv2bJFixYtUmpqajFUWD44M84ZGRn6v//7P8XFxWnt2rU6dOiQBg4cqKtXr2rMmDHFUXaZ5MxY9+zZU2fOnFGLFi1kWZays7P1zDPP6MUXXyyOkm8b+X0eXrhwQb/++qs8PT1LqLLCYaYRKEemTJmilJQUffDBB/Lw8CjpcsqVixcv6vHHH9eCBQtUpUqVki6nXMvNzVW1atX05ptvqnHjxnr00Uc1atQozZs3r6RLK3c2bdqkSZMmac6cOfr222/1/vvva82aNRo/fnxJl4ZSiJlGFEiVKlXk4uKiH374wWH5Dz/8IH9//+tu4+/vX6j2cG6cr5k2bZqmTJmizz//XA0aNLiVZZYLhR3rw4cP68iRI+rcubN9WW5uriTJ1dVV+/fvV61atW5t0WWQM7/TAQEBqlixolxcXOzL6tatq1OnTunKlStyc3O7pTWXVc6MdVJSkh5//HH17dtXkhQZGanLly+rf//+GjVqlCpUYG6pKOT3eejr61tmZhklZhpRQG5ubmrcuLE2bNhgX5abm6sNGzaoadOm192madOmDu0laf369fm2h3PjLElTp07V+PHjtW7dOkVHRxdHqWVeYce6Tp062rt3r1JTU+2vLl26qHXr1kpNTVVQUFBxll9mOPM73bx5cx06dMgeyiXpwIEDCggIIDDegDNj/csvv+QJhtfCumVZt67Y20y5+Tws6TtxUHakpKRY7u7u1pIlS6y0tDSrf//+1h133GGdOnXKsizLevzxx60XXnjB3n7r1q2Wq6urNW3aNCs9Pd0aM2YMj9wpgMKO85QpUyw3Nzfrvffes06ePGl/Xbx4saQOocwo7Fj/GXdPF0xhx/nYsWOWj4+PlZCQYO3fv99avXq1Va1aNWvChAkldQhlRmHHesyYMZaPj4/17rvvWhkZGdZnn31m1apVy+rRo0dJHUKZcPHiRWvXrl3Wrl27LEnWjBkzrF27dllHjx61LMuyXnjhBevxxx+3t7/2yJ1hw4ZZ6enp1uzZs3nkDsq/119/3br77rstNzc36/7777e2b99uXxcbG2v16tXLof2///1vKyIiwnJzc7Puuecea82aNcVccdlUmHEODg62JOV5jRkzpvgLL4MK+zv9R4TGgivsOH/55ZdWkyZNLHd3dys0NNSaOHGilZ2dXcxVl02FGeurV69aY8eOtWrVqmV5eHhYQUFB1sCBA62zZ88Wf+FlyMaNG6/77+61se3Vq5cVGxubZ5uGDRtabm5uVmhoqJWcnFzsdd8sm2Ux/wwAAIAb45pGAAAAGBEaAQAAYERoBAAAgBGhEQAAAEaERgAAABgRGgEAAGBEaAQAAIARoREAAKAU++KLL9S5c2cFBgbKZrPpww8/LHQflmVp2rRpioiIkLu7u2rUqKGJEycWqg9CIwBAkjR27Fg1bNiwRPYdEhKimTNnlsi+gdLu8uXLuvfeezV79myn+3juuee0cOFCTZs2Tfv27dOqVat0//33F6oPQiMAlAK9e/eWzWaTzWZTxYoVVbNmTQ0fPly//fZbSZdWKH88Djc3N4WFhenll19Wdnb2Dbf7+uuv1b9//2KqEihbOnTooAkTJuh//ud/rrs+KytLiYmJqlGjhry8vNSkSRNt2rTJvj49PV1z587VRx99pC5duqhmzZpq3LixHnrooULVQWgEgFKiffv2OnnypDIyMvTaa69p/vz5GjNmTEmXVWjXjuPgwYN6/vnnNXbsWL366qvXbXvlyhVJUtWqVVWpUqXiLBMoNxISErRt2zalpKRoz5496t69u9q3b6+DBw9Kkj7++GOFhoZq9erVqlmzpkJCQtS3b1/9/PPPhdoPoREASgl3d3f5+/srKChIXbt2VZs2bbR+/Xr7+tzcXE2ePFk1a9aUp6en7r33Xr333nv29WfPnlVcXJyqVq0qT09PhYeHKzk52b5+xIgRioiIUKVKlRQaGqqkpCRdvXr1hjUtXLhQdevWlYeHh+rUqaM5c+YU+DiCg4M1YMAAtWnTRqtWrZL0+0xk165dNXHiRAUGBqp27dqS8p6ePnfunJ5++mlVr15dHh4eql+/vlavXm1fv2XLFsXExMjT01NBQUEaNGiQLl++bKwNKG+OHTum5ORkrVixQjExMapVq5YSExPVokUL+9//jIwMHT16VCtWrNDSpUu1ZMkS7dy5U3//+98LtS/XW3EAAICb89///ldffvmlgoOD7csmT56st99+W/PmzVN4eLi++OIL/fOf/1TVqlUVGxurpKQkpaWl6ZNPPlGVKlV06NAh/frrr/btfXx8tGTJEgUGBmrv3r3q16+ffHx8NHz48OvWsGzZMo0ePVpvvPGGoqKitGvXLvXr109eXl7q1atXgY/F09NTP/30k/39hg0b5Ovr6xCI/yg3N1cdOnTQxYsX9fbbb6tWrVpKS0uTi4uLJOnw4cNq3769JkyYoMWLF+vHH39UQkKCEhISHEIycDvYu3evcnJyFBER4bA8KytLf/nLXyT9/ncqKytLS5cutbdbtGiRGjdurP3799v/82ZCaASAUmL16tXy9vZWdna2srKyVKFCBb3xxhuSfv8AmDRpkj7//HM1bdpUkhQaGqotW7Zo/vz5io2N1bFjxxQVFaXo6GhJv8/e/dFLL71k/zkkJESJiYlKSUnJNzSOGTNG06dP1yOPPCJJqlmzptLS0jR//vwChUbLsrRhwwZ9+umnevbZZ+3Lvby8tHDhQrm5uV13u88//1w7duxQenq6/QMuNDTUvn7y5MmKi4vT4MGDJUnh4eGaNWuWYmNjNXfuXHl4eBhrA8qLS5cuycXFRTt37rT/x+oab29vSVJAQIBcXV0dgmXdunUl/T5TSWgEgDKmdevWmjt3ri5fvqzXXntNrq6u6tatmyTp0KFD+uWXX/JcuH7lyhVFRUVJkgYMGKBu3brp22+/Vdu2bdW1a1c1a9bM3nb58uWaNWuWDh8+rEuXLik7O1u+vr7XreXy5cs6fPiw+vTpo379+tmXZ2dny8/P74bHcS38Xr16Vbm5uerZs6fGjh1rXx8ZGZlvYJSk1NRU3XXXXXlmTq7ZvXu39uzZo2XLltmXWZal3NxcZWZm2j8MgdtBVFSUcnJydPr0acXExFy3TfPmzZWdna3Dhw+rVq1akqQDBw5IksPZDBNCIwCUEl5eXgoLC5MkLV68WPfee68WLVqkPn366NKlS5KkNWvWqEaNGg7bubu7S/r9DsujR49q7dq1Wr9+vR588EHFx8dr2rRp2rZtm+Li4jRu3Di1a9dOfn5+SklJ0fTp069by7X9LViwQE2aNHFY9+fZjD+7Fn7d3NwUGBgoV1fHjxovL68bbu/p6XnD9ZcuXdLTTz+tQYMG5Vl3991333BboCy6dOmSDh06ZH+fmZmp1NRUVa5cWREREYqLi9MTTzyh6dOnKyoqSj/++KM2bNigBg0aqFOnTmrTpo0aNWqkp556SjNnzlRubq7i4+P10EMP5fufs+shNAJAKVShQgW9+OKLGjp0qHr27Kl69erJ3d1dx44dU2xsbL7bVa1aVb169VKvXr0UExOjYcOGadq0afbrI0eNGmVve/To0Xz7qV69ugIDA5WRkaG4uLhC1f7H8OuMBg0a6MSJEzpw4MB1P9AaNWqktLS0m9oHUJZ88803at26tf390KFDJUm9evXSkiVLlJycrAkTJuj555/Xd999pypVquiBBx7Q3/72N0m//3vy8ccf69lnn1XLli3l5eWlDh065PufxvwQGgGglOrevbuGDRum2bNnKzExUYmJiRoyZIhyc3PVokULnT9/Xlu3bpWvr6969eql0aNHq3HjxrrnnnuUlZWl1atX20/VhoeH69ixY0pJSdF9992nNWvW6IMPPrjh/seNG6dBgwbJz89P7du3V1ZWlr755hudPXvW/qF1K8TGxqply5bq1q2bZsyYobCwMO3bt082m03t27fXiBEj9MADDyghIUF9+/aVl5eX0tLStH79evs1oEB50qpVK1mWle/6ihUraty4cRo3bly+bQIDA7Vy5cqbqoNH7gBAKeXq6qqEhARNnTpVly9f1vjx45WUlKTJkyerbt26at++vdasWaOaNWtKktzc3DRy5Eg1aNBALVu2lIuLi1JSUiRJXbp00ZAhQ5SQkKCGDRvqyy+/VFJS0g3337dvXy1cuFDJycmKjIxUbGyslixZYt/frbRy5Urdd999euyxx1SvXj0NHz5cOTk5kn6fidy8ebMOHDigmJgYRUVFafTo0QoMDLzldQG3M5t1o+gKAAAAiJlGAAAAFAChEQAAAEaERgAAABgRGgEAAGBEaAQAAIARoREAAABGhEYAAAAYERoBAABgRGgEAACAEaERAAAARoRGAAAAGP1/KyxWvJ62tLAAAAAASUVORK5CYII=",
      "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": 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lOXfu3L3+OgAAwH2KhyzyqXz58urUqZM6deqkSZMmafDgwZo8ebJGjBih6tWrKzExMccxbm5uee5/wIABunz5subMmaOaNWvKwcFBrVu31o0bN6zalStXzmrdZDIpOzv7rv06ODhYzSwCAADjYgbvHtWvX1/p6ekKDAzUr7/+qrJly8rHx8dqqVq1qiTJ399fu3btsjp+586dVuvbt2/XyJEj1aVLFzVo0EAODg76/fffi+18AABAyccMXh5dvnxZffr0UWRkpBo3bixnZ2ft3btXM2bMUM+ePdWxY0e1bt1avXr10owZM+Tn56fz589rw4YNeuyxxxQUFKRRo0YpIiJCQUFBatOmjZYtW6Yff/xR3t7elnF8fX21dOlSBQUFKSUlRf/4xz9UoUIFG545AAAoaQh4eeTk5KSWLVtq1qxZOnXqlDIzM+Xp6akhQ4bopZdekslk0hdffKGXX35ZAwcO1KVLl1StWjW1a9dODz74oCTpySef1KlTpzR+/Hhdv35dvXv31vDhw7Vx40bLOB988IGGDh2qwMBAeXp6avr06Ro3bpytThsAAJRAPEVbSt1+CoenaAEAKDl4ihYAAKCUIuABAAAYDAEPAADAYAh4AAAABkPAAwAAMBgCHgAAgMEQ8AAAAAyGgAcAAGAwBDwAAACD4avKSrknA2fn+iZsAABQ8jCDBwAAYDAEPAAAAIMh4AEAABgMAQ8AAMBgCHgAAAAGQ8ADAAAwGAIeAACAwfAevFJu9P7xsneyL5K+FwTNLZJ+AQBA7pjBAwAAMBgCHgAAgMEQ8AAAAAyGgAcAAGAwBDwAAACDIeABAAAYDAEPAADAYAh4AAAABkPAAwAAMBgCHgAAgMEQ8AAAAAyGgPc/2rdvr9GjR+e5/ZkzZ2QymXTgwIEiqwkAACA/SkXAi4iIkMlk0rBhw3Lsi4qKkslkUkREhCRp9erVmjZtWp779vT01IULF9SwYcPCKhcAAOCelIqAJ90KYitWrNC1a9cs265fv67ly5fLy8vLsq1y5cpydnbOc792dnaqVq2aypYtW6j1AgAAFFSpCXiBgYHy9PTU6tWrLdtWr14tLy8vBQQEWLb97yXaWrVqafr06YqMjJSzs7O8vLy0cOFCy/7/vkSbnZ2thx56SPPnz7ca+/vvv1eZMmV09uxZSdLMmTPVqFEjOTo6ytPTUyNGjFBaWpqlfVxcnNzc3LRx40b5+/vLyclJYWFhunDhgqVNYmKiWrRoIUdHR7m5ualNmzaW/gEAQOlWagKeJEVGRio2NtayvnjxYg0cOPAvj3v77bcVFBSk77//XiNGjNDw4cN1/PjxHO3KlCmjvn37avny5Vbbly1bpjZt2qhmzZqWdnPnztWPP/6oJUuW6JtvvtH48eOtjvnzzz/11ltvaenSpfr222+VlJSkcePGSZJu3rypXr16KTg4WIcOHdKOHTs0dOhQmUymu55DRkaGUlJSrBYAAGBMpSrg9evXT9u2bdPZs2d19uxZbd++Xf369fvL47p06aIRI0bIx8dHL7zwgqpWraqEhIQ7tg0PD9f27duVlJQkScrOztaKFSsUHh5uaTN69GiFhISoVq1aevTRR/Xaa6/pk08+seonMzNTCxYsUFBQkAIDAxUdHa34+HhJUkpKipKTk9WtWzfVqVNH/v7+GjBggNWl5v8VExMjV1dXy+Lp6fmX5w0AAEqmUhXw3N3d1bVrV8XFxSk2NlZdu3ZV1apV//K4xo0bW342mUyqVq2aLl68eMe2TZs2lb+/v2UWb8uWLbp48aL69OljabN582Z16NBBNWrUkLOzs5555hldvnxZf/75p6VNxYoVVadOHct69erVLWNWrlxZERERCg0NVffu3TVnzhyry7d3MmHCBCUnJ1uWc+fO/eV5AwCAkqlUBTzp1mXauLg4LVmyRJGRkXk6ply5clbrJpNJ2dnZd20fHh5uCXjLly9XWFiYqlSpIunWPXvdunVT48aNtWrVKu3bt0/z5s2TJN24cSPXMc1ms2U9NjZWO3bs0MMPP6yVK1fKz89PO3fuvGtNDg4OcnFxsVoAAIAxlbqAFxYWphs3bigzM1OhoaFFMsbTTz+tH374Qfv27dNnn31mdXl23759ys7O1ttvv61WrVrJz89P58+fL9A4AQEBmjBhgr777js1bNgwx71/AACgdCp17/aws7PT0aNHLT8XhVq1aunhhx/WoEGDlJWVpR49elj2+fj4KDMzU++88466d++u7du3a8GCBfnq//Tp01q4cKF69OghDw8PHT9+XCdOnFD//v0L+1QAAEAJVOpm8CQVyyXK8PBwHTx4UI899pgqVKhg2d6kSRPNnDlT//znP9WwYUMtW7ZMMTEx+eq7YsWKOnbsmHr37i0/Pz8NHTpUUVFRevbZZwv7NAAAQAlkMv/3jV0oNVJSUuTq6qqBCc/K3sm+SMZYEDS3SPoFAKC0uv35nZycnOtkVamcwQMAADAyAh4AAIDBFDjgLV26VG3atJGHh4flK7Jmz56ttWvXFlpxAAAAyL8CBbz58+drzJgx6tKli65evaqsrCxJkpubm2bPnl2Y9QEAACCfChTw3nnnHb3//vt6+eWXrV41EhQUpMOHDxdacQAAAMi/AgW806dPKyAgIMd2BwcHpaen33NRAAAAKLgCBbzatWvrwIEDObZ/9dVX8vf3v9eaAAAAcA8K9E0WY8aMUVRUlK5fvy6z2azdu3fr448/VkxMjBYtWlTYNQIAACAfChTwBg8erAoVKmjixIn6888/9fTTT8vDw0Nz5szRU089Vdg1AgAAIB/u+Zss/vzzT6WlpemBBx4orJpQDPL6JmwAAHD/yOvnd4Fm8G67ePGijh8/LkkymUxyd3e/l+4AAABQCAr0kEVqaqqeeeYZeXh4KDg4WMHBwfLw8FC/fv2UnJxc2DUCAAAgHwoU8AYPHqxdu3Zpw4YNunr1qq5evar169dr7969evbZZwu7RgAAAORDge7Bc3R01MaNG/XII49Ybd+6davCwsJ4F14JwD14AACUPHn9/C7QDF6VKlXk6uqaY7urq6sqVapUkC4BAABQSAoU8CZOnKgxY8bo119/tWz79ddf9Y9//EOTJk0qtOIAAACQfwW6RBsQEKCTJ08qIyNDXl5ekqSkpCQ5ODjI19fXqu3+/fsLp1IUKi7RAgBQ8hTpa1J69epV0Lpwnxm9f4PsnSraugxDWhDU09YlAABKqQIFvMmTJxd2HQAAACgkBboHb8CAAfr2228LuxYAAAAUggIFvOTkZHXs2FG+vr6aPn26fvnll8KuCwAAAAVUoIC3Zs0a/fLLLxo+fLhWrlypWrVqqXPnzvrss8+UmZlZ2DUCAAAgHwoU8CTJ3d1dY8aM0cGDB7Vr1y75+PhYvr7s+eef14kTJwqzTgAAAORRgQPebRcuXNCmTZu0adMm2dnZqUuXLjp8+LDq16+vWbNmFUaNAAAAyIcCBbzMzEytWrVK3bp1U82aNfXpp59q9OjROn/+vJYsWaLNmzfrk08+0auvvlrY9QIAAOAvFOg1KdWrV1d2drb69u2r3bt3q2nTpjnahISEyM3N7R7LAwAAQH4VKODNmjVLffr0Ufny5e/axs3NTadPny5wYQAAACiYAl2iTUhIuOPTsunp6YqMjLznogAAAFBwBQp4S5Ys0bVr13Jsv3btmj788MN7LgoAAAAFl69LtCkpKTKbzTKbzUpNTbW6RJuVlaUvvvhCDzzwQKEXCQAAgLzL1wyem5ubKleuLJPJJD8/P1WqVMmyVK1aVZGRkYqKiiqqWku0S5cuafjw4fLy8pKDg4OqVaum0NBQbd++XZJkMpm0Zs2aHMdFRESoV69ekqRGjRpp2LBhd+x/6dKlcnBw0O+//15UpwAAAEqIfM3gJSQkyGw269FHH9WqVatUuXJlyz57e3vVrFlTHh4ehV6kEfTu3Vs3btzQkiVL5O3trd9++03x8fG6fPlynvsYNGiQpkyZolmzZqlChQpW+2JjY9WjRw9VrVq1sEsHAAAlTL4CXnBwsCTp9OnT8vLykslkyrX9iBEj9Oqrr5b60HH16lVt3bpViYmJlt9hzZo11aJFi3z1069fP73wwgtatWqV+vXrZ9l++vRpJSYm6osvvijUugEAQMlUoIcsatas+ZfhTpI++ugjpaSkFGQIQ3FycpKTk5PWrFmjjIyMAvdTtWpV9ezZU4sXL7baHhcXp4ceekh/+9vf7npsRkaGUlJSrBYAAGBM9/xVZbkxm81F2X2JUbZsWcXFxWnJkiVyc3NTmzZt9NJLL+nQoUP57mvQoEFKTEy0vGPQbDZryZIlGjBggMqUufsfZ0xMjFxdXS2Lp6dngc8HAADc34o04OH/6927t86fP69169YpLCxMiYmJCgwMVFxcXL766dSpkx566CHFxsZKkuLj45WUlKSBAwfmetyECROUnJxsWc6dO1fQUwEAAPc5Al4xKl++vDp16qRJkybpu+++U0REhCZPnixJcnZ2VnJyco5jrl69KldXV8t6mTJlFBERoSVLlig7O1uxsbEKCQmRt7d3rmM7ODjIxcXFagEAAMZEwLOh+vXrKz09XZJUt25d7du3z2p/VlaWDh48KD8/P6vtAwcO1Llz57R69Wp9/vnnGjRoULHVDAAA7n8F+i5a5M/ly5fVp08fRUZGqnHjxnJ2dtbevXs1Y8YM9ezZU5I0ZswYDRo0SPXq1VOnTp2Unp6ud955R1euXNHgwYOt+qtdu7YeffRRDR06VA4ODnr88cdtcVoAAOA+VaQBr1+/flwK1K2naFu2bKlZs2bp1KlTyszMlKenp4YMGaKXXnpJktS3b1+ZzWbNnDlTL774oipWrKhmzZrp22+/1YMPPpijz0GDBik+Pl4jRoyw+kYRAAAAk7kAj7rWqlVLkZGRioiIkJeXV1HUhSKWkpIiV1dXDUxYLnunirYux5AWBPW0dQkAAIO5/fmdnJyc6yRage7BGz16tFavXi1vb2916tRJK1asuKf3uwEAAKDwFDjgHThwQLt375a/v7+ee+45Va9eXdHR0dq/f39h1wgAAIB8uKenaAMDAzV37lydP39ekydP1qJFi9S8eXM1bdpUixcv5kXHAAAANnBPD1lkZmbq888/V2xsrDZt2qRWrVpp0KBB+s9//qOXXnpJmzdv1vLlywurVgAAAORBgQLe/v37FRsbq48//lhlypRR//79NWvWLNWrV8/S5rHHHlPz5s0LrVAAAADkTYECXvPmzdWpUyfNnz9fvXr1Urly5XK0qV27tp566ql7LhAAAAD5U6CA9/PPP6tmzZq5tnF0dLR8XyoAAACKT4EesvircAcAAADbyfMMXqVKlWQymfLU9o8//ihwQQAAALg3eQ54s2fPtvx8+fJlvfbaawoNDVXr1q0lSTt27NDGjRs1adKkQi8SRWd2YFe+Tg4AAIMp0FeV9e7dWyEhIYqOjrba/u6772rz5s1as2ZNYdWHIpLXrzoBAAD3jyL9qrKNGzcqLCwsx/awsDBt3ry5IF0CAACgkBQo4FWpUkVr167NsX3t2rWqUqXKPRcFAACAgivQa1KmTp2qwYMHKzExUS1btpQk7dq1S1999ZXef//9Qi0QAAAA+VOggBcRESF/f3/NnTtXq1evliT5+/tr27ZtlsAHAAAA2yjQQxYo+XjIAgCAkievn98FmsGTpKysLK1Zs0ZHjx6VJDVo0EA9evSQnZ1dQbsEAABAIShQwDt58qS6du2q//znP6pbt64kKSYmRp6entqwYYPq1KlTqEUCAAAg7wp0ibZLly4ym81atmyZKleuLOnWy4/79eunMmXKaMOGDYVeKArX7SnegQsTZF/RydblAABgGAvCg4qs7yK9RLtlyxbt3LnTEu6kW69OeeONN9SmTZuCdAkAAIBCUqD34Dk4OCg1NTXH9rS0NNnb299zUQAAACi4AgW8bt26aejQodq1a5fMZrPMZrN27typYcOGqUePHoVdIwAAAPKhQAFv7ty5qlOnjlq3bq3y5curfPnyevjhh+Xj46M5c+YUdo0AAADIhwLdg+fm5qa1a9fq5MmTOnLkiCSpfv368vHxKdTiAAAAkH8Ffg/eBx98oFmzZunEiROSJF9fX40ePVqDBw8utOIAAACQfwUKeK+88opmzpyp5557Tq1bt5Yk7dixQ88//7ySkpL06quvFmqRAAAAyLsCBbz58+fr/fffV9++fS3bevToocaNG+u5554j4AEAANhQgR6yyMzMVFBQzpf4NWvWTDdv3rznogAAAFBwBQp4zzzzjObPn59j+8KFCxUeHn7PRQEAAKDg8nyJdsyYMZafTSaTFi1apK+//lqtWrWSJO3atUtJSUnq379/4VcJAACAPMtzwPv++++t1ps1ayZJOnXqlCSpatWqqlq1qn788cdCLO/+8uuvv+r111/Xhg0b9Msvv+iBBx5Q06ZNNXr0aHXo0MHW5QEAAEjKR8BLSEgoyjrue2fOnFGbNm3k5uamN998U40aNVJmZqY2btyoqKgoHTt2zNYlAgAASCrgPXil0YgRI2QymbR792717t1bfn5+atCggcaMGaOdO3dKkpKSktSzZ085OTnJxcVFTzzxhH777TdLHxEREerVq5dVv6NHj1b79u0t6+3bt1d0dLSio6Pl6uqqqlWratKkSTKbzZY2GRkZGjdunGrUqCFHR0e1bNlSiYmJRXn6AACgBCHg5cEff/yhr776SlFRUXJ0dMyx383NTdnZ2erZs6f++OMPbdmyRZs2bdLPP/+sJ598Mt/jLVmyRGXLltXu3bs1Z84czZw5U4sWLbLsj46O1o4dO7RixQodOnRIffr0UVhYmOWl03eSkZGhlJQUqwUAABhTgb/JojQ5efKkzGaz6tWrd9c28fHxOnz4sE6fPi1PT09J0ocffqgGDRpoz549at68eZ7H8/T01KxZs2QymVS3bl0dPnxYs2bN0pAhQ5SUlKTY2FglJSXJw8NDkjRu3Dh99dVXio2N1fTp0+/YZ0xMjKZOnZqPswYAACUVM3h58N+XR+/m6NGj8vT0tIQ76db387q5ueno0aP5Gq9Vq1YymUyW9datW+vEiRPKysrS4cOHlZWVJT8/Pzk5OVmWLVu2WB54uZMJEyYoOTnZspw7dy5fNQEAgJKDGbw88PX1lclkuucHKcqUKZMjLGZmZuarj7S0NNnZ2Wnfvn2ys7Oz2ufk5HTX4xwcHOTg4JCvsQAAQMnEDF4eVK5cWaGhoZo3b57S09Nz7L969ar8/f117tw5q5mxI0eO6OrVq6pfv74kyd3dXRcuXLA69sCBAzn627Vrl9X6zp075evrKzs7OwUEBCgrK0sXL16Uj4+P1VKtWrVCOFsAAFDSEfDyaN68ecrKylKLFi20atUqnThxQkePHtXcuXPVunVrdezYUY0aNVJ4eLj279+v3bt3q3///goODrZ8rdujjz6qvXv36sMPP9SJEyc0efJk/fDDDznGSkpK0pgxY3T8+HF9/PHHeueddzRq1ChJkp+fn8LDw9W/f3+tXr1ap0+f1u7duxUTE6MNGzYU6+8EAADcnwh4eeTt7a39+/crJCREY8eOVcOGDdWpUyfFx8dr/vz5MplMWrt2rSpVqqR27dqpY8eO8vb21sqVKy19hIaGatKkSRo/fryaN2+u1NTUO37zR//+/XXt2jW1aNFCUVFRGjVqlIYOHWrZHxsbq/79+2vs2LGqW7euevXqpT179sjLy6tYfhcAAOD+ZjLn5QkCFJv27duradOmmj17dpGOk5KSIldXVw1cmCD7ine/dw8AAOTPgvCgIuv79ud3cnKyXFxc7tqOGTwAAACDIeABAAAYDK9Juc/wlWMAAOBeMYMHAABgMAQ8AAAAgyHgAQAAGAwBDwAAwGAIeAAAAAZDwAMAADAYXpNSys1+MjDXN2EDAICShxk8AAAAgyHgAQAAGAwBDwAAwGAIeAAAAAZDwAMAADAYAh4AAIDBEPAAAAAMhoAHAABgMLzouJQbP3q/7O2dbF1GiTV3QZCtSwAAIAdm8AAAAAyGgAcAAGAwBDwAAACDIeABAAAYDAEPAADAYAh4AAAABkPAAwAAMBgCHgAAgMEQ8AAAAAyGgAcAAGAwBLx7FBERoV69euWp7ZkzZ2QymXTgwIEirQkAAJRuBLw8iIiIkMlkkslkkr29vXx8fPTqq6/q5s2bmjNnjuLi4mxdIgAAgEVZWxdQUoSFhSk2NlYZGRn64osvFBUVpXLlymnChAm2Lg0AAMAKM3h55ODgoGrVqqlmzZoaPny4OnbsqHXr1uW4RJudna0ZM2bIx8dHDg4O8vLy0uuvv37HPrOyshQZGal69eopKSlJU6ZMUdOmTa3azJ49W7Vq1bKs3x5v6tSpcnd3l4uLi4YNG6YbN24UwVkDAICSiBm8AqpQoYIuX76cY/uECRP0/vvva9asWXrkkUd04cIFHTt2LEe7jIwM9e3bV2fOnNHWrVvl7u6e57Hj4+NVvnx5JSYm6syZMxo4cKCqVKly1yB5e7yMjAzLekpKSp7HAwAAJQszePlkNpu1efNmbdy4UY8++qjVvtTUVM2ZM0czZszQgAEDVKdOHT3yyCMaPHiwVbu0tDR17dpVly5dUkJCQr7CnSTZ29tr8eLFatCggbp27apXX31Vc+fOVXZ29l2PiYmJkaurq2Xx9PTM15gAAKDkIODl0fr16+Xk5KTy5curc+fOevLJJzVlyhSrNkePHlVGRoY6dOiQa199+/ZVenq6vv76a7m6uua7liZNmqhixYqW9datWystLU3nzp276zETJkxQcnKyZcmtLQAAKNkIeHkUEhKiAwcO6MSJE7p27ZqWLFkiR0dHqzYVKlTIU19dunTRoUOHtGPHDqvtZcqUkdlsttqWmZl5b4X/Pw4ODnJxcbFaAACAMRHw8sjR0VE+Pj7y8vJS2bJ3vnXR19dXFSpUUHx8fK59DR8+XG+88YZ69OihLVu2WLa7u7vr119/tQp5d3pn3sGDB3Xt2jXL+s6dO+Xk5MRlVwAAIImHLApV+fLl9cILL2j8+PGyt7dXmzZtdOnSJf34448aNGiQVdvnnntOWVlZ6tatm7788ks98sgjat++vS5duqQZM2bo73//u7766it9+eWXOWbbbty4oUGDBmnixIk6c+aMJk+erOjoaJUpQ14HAAAEvEI3adIklS1bVq+88orOnz+v6tWra9iwYXdsO3r0aGVnZ6tLly766quv9PDDD+tf//qXpk+frmnTpql3794aN26cFi5caHVchw4d5Ovrq3bt2lmexv3f+wEBAEDpZTL/701fuK9FRETo6tWrWrNmzT31k5KSIldXVz07MEH29k6FU1wpNHdBkK1LAACUIrc/v5OTk3O9n55regAAAAZDwAMAADAY7sErYeLi4mxdAgAAuM8xgwcAAGAwBDwAAACDIeABAAAYDAEPAADAYAh4AAAABkPAAwAAMBhek1LKzZgdmOubsAEAQMnDDB4AAIDBEPAAAAAMhoAHAABgMAQ8AAAAgyHgAQAAGAwBDwAAwGAIeAAAAAZDwAMAADAYXnRcym0YvV8V7Z1sXQZgWD0XBNm6BAClEDN4AAAABkPAAwAAMBgCHgAAgMEQ8AAAAAyGgAcAAGAwBDwAAACDIeABAAAYDAEPAADAYAh4AAAABkPAAwAAMBgCHgAAgMEQ8IpA+/btNXr0aMt6rVq1NHv27FyPMZlMWrNmTZHWBQAASgebB7xff/1Vzz33nLy9veXg4CBPT091795d8fHxti7tLyUmJspkMunq1atW21evXq1p06bZpigAAFDqlbXl4GfOnFGbNm3k5uamN998U40aNVJmZqY2btyoqKgoHTt2zJbl5SozM/Ou+ypXrlyMlQAAAFiz6QzeiBEjZDKZtHv3bvXu3Vt+fn5q0KCBxowZo507d0qSkpKS1LNnTzk5OcnFxUVPPPGEfvvtN0sfU6ZMUdOmTbV06VLVqlVLrq6ueuqpp5SamipJWrhwoTw8PJSdnW01ds+ePRUZGWlZX7t2rQIDA1W+fHl5e3tr6tSpunnzpmW/yWTS/Pnz1aNHDzk6OmrIkCEKCQmRJFWqVEkmk0kRERGScl6ilaTU1FT17dtXjo6OqlGjhubNm5fr7+bcuXN64okn5ObmpsqVK6tnz546c+aMZX9iYqJatGghR0dHubm5qU2bNjp79uxd+8vIyFBKSorVAgAAjMlmAe+PP/7QV199paioKDk6OubY7+bmpuzsbPXs2VN//PGHtmzZok2bNunnn3/Wk08+adX21KlTWrNmjdavX6/169dry5YteuONNyRJffr00eXLl5WQkJBj7PDwcEnS1q1b1b9/f40aNUpHjhzRe++9p7i4OL3++utW40yZMkWPPfaYDh8+rKlTp2rVqlWSpOPHj+vChQuaM2fOXc/3zTffVJMmTfT999/rxRdf1KhRo7Rp06Y7ts3MzFRoaKicnZ21detWbd++XU5OTgoLC9ONGzd08+ZN9erVS8HBwTp06JB27NihoUOHymQy3XX8mJgYubq6WhZPT8+7tgUAACWbzS7Rnjx5UmazWfXq1btrm/j4eB0+fFinT5+2BJIPP/xQDRo00J49e9S8eXNJUnZ2tuLi4uTs7CxJeuaZZxQfH6/XX39dlSpVUufOnbV8+XJ16NBBkvTZZ5+patWqlhm4qVOn6sUXX9SAAQMkSd7e3po2bZrGjx+vyZMnW+p5+umnNXDgQMv66dOnJUkPPPCA3Nzccj3fNm3a6MUXX5Qk+fn5afv27Zo1a5Y6deqUo+3KlSuVnZ2tRYsWWUJbbGys3NzclJiYqKCgICUnJ6tbt26qU6eOJMnf3z/X8SdMmKAxY8ZY1lNSUgh5AAAYlM1m8Mxm81+2OXr0qDw9Pa2CSP369eXm5qajR49attWqVcsS7iSpevXqunjxomU9PDxcq1atUkZGhiRp2bJleuqpp1SmzK3TP3jwoF599VU5OTlZliFDhujChQv6888/Lf0EBQUV+Hxbt26dY/2/z+G/HTx4UCdPnpSzs7OlnsqVK+v69es6deqUKleurIiICIWGhqp79+6aM2eOLly4kOv4Dg4OcnFxsVoAAIAx2WwGz9fXVyaTqVAepChXrpzVuslksrrnrnv37jKbzdqwYYOaN2+urVu3atasWZb9aWlpmjp1qh5//PEcfZcvX97y850uJReFtLQ0NWvWTMuWLcuxz93dXdKtGb2RI0fqq6++0sqVKzVx4kRt2rRJrVq1KpYaAQDA/ctmAa9y5coKDQ3VvHnzNHLkyBzh6erVq/L399e5c+d07tw5yyzekSNHdPXqVdWvXz/PY5UvX16PP/64li1bppMnT6pu3boKDAy07A8MDNTx48fl4+OTr3Owt7eXJGVlZf1l29sPjfz3+t0uqwYGBmrlypV64IEHcp1pCwgIUEBAgCZMmKDWrVtr+fLlBDwAAGDbp2jnzZunrKwstWjRQqtWrdKJEyd09OhRzZ07V61bt1bHjh3VqFEjhYeHa//+/dq9e7f69++v4ODgfF8uDQ8P14YNG7R48WLLwxW3vfLKK/rwww81depU/fjjjzp69KhWrFihiRMn5tpnzZo1ZTKZtH79el26dElpaWl3bbt9+3bNmDFDP/30k+bNm6dPP/1Uo0aNumutVatWVc+ePbV161adPn1aiYmJGjlypP7zn//o9OnTmjBhgnbs2KGzZ8/q66+/1okTJ/7yPjwAAFA62DTgeXt7a//+/QoJCdHYsWPVsGFDderUSfHx8Zo/f75MJpPWrl2rSpUqqV27durYsaO8vb21cuXKfI/16KOPqnLlyjp+/Liefvppq32hoaFav369vv76azVv3lytWrXSrFmzVLNmzVz7rFGjhuUBjQcffFDR0dF3bTt27Fjt3btXAQEBeu211zRz5kyFhobesW3FihX17bffysvLS48//rj8/f01aNAgXb9+XS4uLqpYsaKOHTtmebXM0KFDFRUVpWeffTbfvxcAAGA8JnNennaA4aSkpMjV1VXLByaoor2TrcsBDKvngoI/nAUA/+v253dycnKut3HZ/KvKAAAAULgIeAAAAAZDwAMAADAYAh4AAIDBEPAAAAAMhoAHAABgMAQ8AAAAgyHgAQAAGAwBDwAAwGDK2roA2FbX2YG5vgkbAACUPMzgAQAAGAwBDwAAwGAIeAAAAAZDwAMAADAYAh4AAIDBEPAAAAAMhoAHAABgMLwHr5TbP3qlnOwr2roMoEQIWhBu6xIAIE+YwQMAADAYAh4AAIDBEPAAAAAMhoAHAABgMAQ8AAAAgyHgAQAAGAwBDwAAwGAIeAAAAAZDwAMAADAYAh4AAIDBEPAAAAAMhoAHAABgMAS8u1iwYIGcnZ118+ZNy7a0tDSVK1dO7du3t2qbmJgok8mkU6dOFXOVAAAAORHw7iIkJERpaWnau3evZdvWrVtVrVo17dq1S9evX7dsT0hIkJeXl+rUqWOLUgEAAKwQ8O6ibt26ql69uhITEy3bEhMT1bNnT9WuXVs7d+602h4SEqKlS5cqKChIzs7Oqlatmp5++mldvHjRqt9169bJ19dX5cuXV0hIiJYsWSKTyaSrV69a2qxatUoNGjSQg4ODatWqpbffftuqj1q1amn69OmKjIyUs7OzvLy8tHDhwlzPJyMjQykpKVYLAAAwJgJeLkJCQpSQkGBZT0hIUPv27RUcHGzZfu3aNe3atUshISHKzMzUtGnTdPDgQa1Zs0ZnzpxRRESE5fjTp0/r73//u3r16qWDBw/q2Wef1csvv2w15r59+/TEE0/oqaee0uHDhzVlyhRNmjRJcXFxVu3efvttBQUF6fvvv9eIESM0fPhwHT9+/K7nEhMTI1dXV8vi6el5778gAABwXzKZzWazrYu4Xy1atEijR4/W1atXde3aNVWuXFnnz5/X5s2btWDBAm3ZskXffPONOnTooLNnz8rLy8vq+L1796p58+ZKTU2Vk5OTXnzxRW3YsEGHDx+2tJk4caJef/11XblyRW5ubgoPD9elS5f09ddfW9qMHz9eGzZs0I8//ijp1gxe27ZttXTpUkmS2WxWtWrVNHXqVA0bNuyO55KRkaGMjAzLekpKijw9PZUwcKGc7CsW2u8MMLKgBeG2LgFAKZeSkiJXV1clJyfLxcXlru2YwctF+/btlZ6erj179mjr1q3y8/OTu7u7goODLffhJSYmytvbW15eXtq3b5+6d+8uLy8vOTs7Kzg4WJKUlJQkSTp+/LiaN29uNUaLFi2s1o8ePao2bdpYbWvTpo1OnDihrKwsy7bGjRtbfjaZTKpWrVqOy8H/zcHBQS4uLlYLAAAwprK2LuB+5uPjo4ceekgJCQm6cuWKJbB5eHjI09NT3333nRISEvToo48qPT1doaGhCg0N1bJly+Tu7q6kpCSFhobqxo0bhV5buXLlrNZNJpOys7MLfRwAAFDyMIP3F0JCQpSYmKjExESr16O0a9dOX375pXbv3q2QkBAdO3ZMly9f1htvvKG2bduqXr16OWbU6tata/VUriTt2bPHat3f31/bt2+32rZ9+3b5+fnJzs6ucE8OAAAYEgHvL4SEhGjbtm06cOCAZQZPkoKDg/Xee+/pxo0bCgkJkZeXl+zt7fXOO+/o559/1rp16zRt2jSrvp599lkdO3ZML7zwgn766Sd98sknlocnTCaTJGns2LGKj4/XtGnT9NNPP2nJkiV69913NW7cuGI7ZwAAULIR8P5CSEiIrl27Jh8fHz344IOW7cHBwUpNTbW8TsXd3V1xcXH69NNPVb9+fb3xxht66623rPqqXbu2PvvsM61evVqNGzfW/PnzLU/ROjg4SJICAwP1ySefaMWKFWrYsKFeeeUVvfrqq1ZP4wIAAOSGp2ht7PXXX9eCBQt07ty5Yh339lM4PEUL5B1P0QKwtbw+RctDFsXsX//6l5o3b64qVapo+/btevPNNxUdHW3rsgAAgIEQ8IrZiRMn9Nprr+mPP/6Ql5eXxo4dqwkTJti6LAAAYCAEvGI2a9YszZo1y9ZlAAAAA+MhCwAAAIMh4AEAABgMAQ8AAMBgCHgAAAAGQ8ADAAAwGAIeAACAwfCalFIucPaTub4JGwAAlDzM4AEAABgMAQ8AAMBguERbSpnNZkm3vrQYAACUDLc/t29/jt8NAa+Uunz5siTJ09PTxpUAAID8Sk1Nlaur6133E/BKqcqVK0uSkpKScv0PxGhSUlLk6empc+fOlbqHS0rruXPepeu8pdJ77qX1vKXSde5ms1mpqany8PDItR0Br5QqU+bW7Zeurq6G/8twJy4uLqXyvKXSe+6cd+lTWs+9tJ63VHrOPS8TMzxkAQAAYDAEPAAAAIMh4JVSDg4Omjx5shwcHGxdSrEqrectld5z57xL13lLpffcS+t5S6X73O/GZP6r52wBAABQojCDBwAAYDAEPAAAAIMh4AEAABgMAQ8AAMBgCHil0Lx581SrVi2VL19eLVu21O7du21dUpH79ttv1b17d3l4eMhkMmnNmjW2LqlYxMTEqHnz5nJ2dtYDDzygXr166fjx47Yuq1jMnz9fjRs3trz4tHXr1vryyy9tXVaxe+ONN2QymTR69Ghbl1LkpkyZIpPJZLXUq1fP1mUVi19++UX9+vVTlSpVVKFCBTVq1Eh79+61dVlFqlatWjn+vE0mk6Kiomxd2n2BgFfKrFy5UmPGjNHkyZO1f/9+NWnSRKGhobp48aKtSytS6enpatKkiebNm2frUorVli1bFBUVpZ07d2rTpk3KzMzU3/72N6Wnp9u6tCL30EMP6Y033tC+ffu0d+9ePfroo+rZs6d+/PFHW5dWbPbs2aP33ntPjRs3tnUpxaZBgwa6cOGCZdm2bZutSypyV65cUZs2bVSuXDl9+eWXOnLkiN5++21VqlTJ1qUVqT179lj9WW/atEmS1KdPHxtXdp8wo1Rp0aKFOSoqyrKelZVl9vDwMMfExNiwquIlyfz555/bugybuHjxolmSecuWLbYuxSYqVapkXrRoka3LKBapqalmX19f86ZNm8zBwcHmUaNG2bqkIjd58mRzkyZNbF1GsXvhhRfMjzzyiK3LsLlRo0aZ69SpY87OzrZ1KfcFZvBKkRs3bmjfvn3q2LGjZVuZMmXUsWNH7dixw4aVobgkJydLkipXrmzjSopXVlaWVqxYofT0dLVu3drW5RSLqKgode3a1erve2lw4sQJeXh4yNvbW+Hh4UpKSrJ1SUVu3bp1CgoKUp8+ffTAAw8oICBA77//vq3LKlY3btzQRx99pMjISJlMJluXc18g4JUiv//+u7KysvTggw9abX/wwQf166+/2qgqFJfs7GyNHj1abdq0UcOGDW1dTrE4fPiwnJyc5ODgoGHDhunzzz9X/fr1bV1WkVuxYoX279+vmJgYW5dSrFq2bKm4uDh99dVXmj9/vk6fPq22bdsqNTXV1qUVqZ9//lnz58+Xr6+vNm7cqOHDh2vkyJFasmSJrUsrNmvWrNHVq1cVERFh61LuG2VtXQCA4hEVFaUffvihVNyTdFvdunV14MABJScn67PPPtOAAQO0ZcsWQ4e8c+fOadSoUdq0aZPKly9v63KKVefOnS0/N27cWC1btlTNmjX1ySefaNCgQTasrGhlZ2crKChI06dPlyQFBATohx9+0IIFCzRgwAAbV1c8PvjgA3Xu3FkeHh62LuW+wQxeKVK1alXZ2dnpt99+s9r+22+/qVq1ajaqCsUhOjpa69evV0JCgh566CFbl1Ns7O3t5ePjo2bNmikmJkZNmjTRnDlzbF1Wkdq3b58uXryowMBAlS1bVmXLltWWLVs0d+5clS1bVllZWbYusdi4ubnJz89PJ0+etHUpRap69eo5/tHi7+9fKi5PS9LZs2e1efNmDR482Nal3FcIeKWIvb29mjVrpvj4eMu27OxsxcfHl5r7kkobs9ms6Ohoff755/rmm29Uu3ZtW5dkU9nZ2crIyLB1GUWqQ4cOOnz4sA4cOGBZgoKCFB4ergMHDsjOzs7WJRabtLQ0nTp1StWrV7d1KUWqTZs2OV5/9NNPP6lmzZo2qqh4xcbG6oEHHlDXrl1tXcp9hUu0pcyYMWM0YMAABQUFqUWLFpo9e7bS09M1cOBAW5dWpNLS0qz+FX/69GkdOHBAlStXlpeXlw0rK1pRUVFavny51q5dK2dnZ8u9lq6urqpQoYKNqytaEyZMUOfOneXl5aXU1FQtX75ciYmJ2rhxo61LK1LOzs457rF0dHRUlSpVDH/v5bhx49S9e3fVrFlT58+f1+TJk2VnZ6e+ffvaurQi9fzzz+vhhx/W9OnT9cQTT2j37t1auHChFi5caOvSilx2drZiY2M1YMAAlS1LpLFi68d4Ufzeeecds5eXl9ne3t7cokUL886dO21dUpFLSEgwS8qxDBgwwNalFak7nbMkc2xsrK1LK3KRkZHmmjVrmu3t7c3u7u7mDh06mL/++mtbl2UTpeU1KU8++aS5evXqZnt7e3ONGjXMTz75pPnkyZO2LqtY/Pvf/zY3bNjQ7ODgYK5Xr5554cKFti6pWGzcuNEsyXz8+HFbl3LfMZnNZrNtoiUAAACKAvfgAQAAGAwBDwAAwGAIeAAAAAZDwAMAADAYAh4AAIDBEPAAAAAMhoAHAABgMAQ8AACAQvLtt9+qe/fu8vDwkMlk0po1a/Ldh9ls1ltvvSU/Pz85ODioRo0aev311/PVBwEPAEqgKVOmqGnTpjYZu1atWpo9e7ZNxgbud+np6WrSpInmzZtX4D5GjRqlRYsW6a233tKxY8e0bt06tWjRIl99EPAAIJ8iIiJkMplkMplUrlw51a5dW+PHj9f169dtXVq+/Pd52Nvby8fHR6+++qpu3ryZ63F79uzR0KFDi6lKoGTp3LmzXnvtNT322GN33J+RkaFx48apRo0acnR0VMuWLZWYmGjZf/ToUc2fP19r165Vjx49VLt2bTVr1kydOnXKVx0EPAAogLCwMF24cEE///yzZs2apffee0+TJ0+2dVn5dvs8Tpw4obFjx2rKlCl6880379j2xo0bkiR3d3dVrFixOMsEDCM6Olo7duzQihUrdOjQIfXp00dhYWE6ceKEJOnf//63vL29tX79etWuXVu1atXS4MGD9ccff+RrHAIeABSAg4ODqlWrJk9PT/Xq1UsdO3bUpk2bLPuzs7MVExOj2rVrq0KFCmrSpIk+++wzy/4rV64oPDxc7u7uqlChgnx9fRUbG2vZ/8ILL8jPz08VK1aUt7e3Jk2apMzMzFxrWrRokfz9/VW+fHnVq1dP//rXv/J8HjVr1tTw4cPVsWNHrVu3TtKtGb5evXrp9ddfl4eHh+rWrSsp5yXaq1ev6tlnn9WDDz6o8uXLq2HDhlq/fr1l/7Zt29S2bVtVqFBBnp6eGjlypNLT0/+yNsBokpKSFBsbq08//VRt27ZVnTp1NG7cOD3yyCOWv/8///yzzp49q08//VQffvih4uLitG/fPv3973/P11hli+IEAKA0+eGHH/Tdd9+pZs2alm0xMTH66KOPtGDBAvn6+urbb79Vv3795O7uruDgYE2aNElHjhzRl19+qapVq+rkyZO6du2a5XhnZ2fFxcXJw8NDhw8f1pAhQ+Ts7Kzx48ffsYZly5bplVde0bvvvquAgAB9//33GjJkiBwdHTVgwIA8n0uFChV0+fJly3p8fLxcXFyswut/y87OVufOnZWamqqPPvpIderU0ZEjR2RnZydJOnXqlMLCwvTaa69p8eLFunTpkqKjoxUdHW0VaIHS4PDhw8rKypKfn5/V9oyMDFWpUkXSrb9TGRkZ+vDDDy3tPvjgAzVr1kzHjx+3/EPrrxDwAKAA1q9fLycnJ928eVMZGRkqU6aM3n33XUm3/mc9ffp0bd68Wa1bt5YkeXt7a9u2bXrvvfcUHByspKQkBQQEKCgoSNKtWbH/NnHiRMvPtWrV0rhx47RixYq7BrzJkyfr7bff1uOPPy5Jql27to4cOaL33nsvTwHPbDYrPj5eGzdu1HPPPWfZ7ujoqEWLFsne3v6Ox23evFm7d+/W0aNHLR9G3t7elv0xMTEKDw/X6NGjJUm+vr6aO3eugoODNX/+fJUvX/4vawOMIi0tTXZ2dtq3b5/lH0G3OTk5SZKqV6+usmXLWoVAf39/SbdmAAl4AFCEQkJCNH/+fKWnp2vWrFkqW7asevfuLUk6efKk/vzzzxw3Rd+4cUMBAQGSpOHDh6t3797av3+//va3v6lXr156+OGHLW1XrlypuXPn6tSpU0pLS9PNmzfl4uJyx1rS09N16tQpDRo0SEOGDLFsv3nzplxdXXM9j9tBNTMzU9nZ2Xr66ac1ZcoUy/5GjRrdNdxJ0oEDB/TQQw/lmJG47eDBgzp06JCWLVtm2WY2m5Wdna3Tp09bPriA0iAgIEBZWVm6ePGi2rZte8c2bdq00c2bN3Xq1CnVqVNHkvTTTz9JktVVgr9CwAOAAnB0dJSPj48kafHixWrSpIk++OADDRo0SGlpaZKkDRs2qEaNGlbHOTg4SLr1pN3Zs2f1xRdfaNOmTerQoYOioqL01ltvaceOHQoPD9fUqVMVGhoqV1dXrVixQm+//fYda7k93vvvv6+WLVta7fvfWYL/dTuo2tvby8PDQ2XLWn8sODo65np8hQoVct2flpamZ599ViNHjsyxz8vLK9djgZIoLS1NJ0+etKyfPn1aBw4cUOXKleXn56fw8HD1799fb7/9tgICAnTp0iXFx8ercePG6tq1qzp27KjAwEBFRkZq9uzZys7OVlRUlDp16nTXf0jdCQEPAO5RmTJl9NJLL2nMmDF6+umnVb9+fTk4OCgpKUnBwcF3Pc7d3V0DBgzQgAED1LZtW/3jH//QW2+9Zbmf7+WXX7a0PXv27F37efDBB+Xh4aGff/5Z4eHh+ar9v4NqQTRu3Fj/+c9/9NNPP93xwycwMFBHjhy5pzGAkmTv3r0KCQmxrI8ZM0aSNGDAAMXFxSk2Nlavvfaaxo4dq19++UVVq1ZVq1at1K1bN0m3/n/y73//W88995zatWsnR0dHde7c+a7/wLsbAh4AFII+ffroH//4h+bNm6dx48Zp3Lhxev7555Wdna1HHnlEycnJ2r59u1xcXDRgwAC98soratasmRo0aKCMjAytX7/ecrnS19dXSUlJWrFihZo3b64NGzbo888/z3X8qVOnauTIkXJ1dVVYWJgyMjK0d+9eXblyxfIBUxSCg4PVrl079e7dWzNnzpSPj4+OHTsmk8mksLAwvfDCC2rVqpWio6M1ePBgOTo66siRI9q0aZPlnkXASNq3by+z2XzX/eXKldPUqVM1derUu7bx8PDQqlWr7qkOXpMCAIWgbNmyio6O1owZM5Senq5p06Zp0qRJiomJkb+/v8LCwrRhwwbVrl1bkmRvb68JEyaocePGateunezs7LRixQpJUo8ePfT8888rOjpaTZs21XfffadJkyblOv7gwYO1aNEixcbGqlGjRgoODlZcXJxlvKK0atUqNW/eXH379lX9+vU1fvx4ZWVlSbo1w7dlyxb99NNPatu2rQICAvTKK6/Iw8OjyOsCSjOTObeYCQAAgBKHGTwAAACDIeABAAAYDAEPAADAYAh4AAAABkPAAwAAMBgCHgAAgMEQ8AAAAAyGgAcAAGAwBDwAAACDIeABAAAYDAEPAADAYP4PSwzfXYIDTkMAAAAASUVORK5CYII=",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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pKZydnbFmzRro6urC0dER3bt3x4ULFxATE1PupVciIiKqf2R9+TU7O7tUYGvTpg0aNGiADz/8EJMnT8aZM2cQFRWl1mbevHl49dVX0bp1a7z99tsoKirCwYMHMXPmTLV2Xbt2xcGDB9GnTx/o6OggJCSkQnX16tUL7du3R2BgIFauXImioiKMHz8eXl5ecHd3l9p5e3tj9erVePPNNwEADRs2hJOTE3bu3Im1a9dW+nwQERGRfMl6pC4uLg6urq5q08KFC/Hll1/i4MGDaN++Pb7++utSPzfi7e2N3bt3Y//+/XBxcUHPnj2RkJDw1H288sorOHDgAD766COsXr26QnUJgoDvvvsOL730Erp3745evXrBxsYGO3fuVGvn5eWF4uJitXvnvL29Sy0jIiIiEsT/3mBGsqRSqaBUKnEsdjiMjPQ0XQ4RvUDunTdougQiqqIn39/Z2dkwMTEpt62sR+qIiIiI6guGOiIiIiIZYKgjIiIikgGGOiIiIiIZkPVPmlBpbu4rn3mjJREREdU9HKkjIiIikgGGOiIiIiIZYKgjIiIikgGGOiIiIiIZ4IMS9cyO8yEw4BsliIhIBoLd+baUf+NIHREREZEMMNQRERERyQBDHREREZEMMNQRERERyQBDHREREZEMMNQRERERyQBDXS0QFhYGFxcXaT44OBgBAQHlbmNtbY2VK1fWaF1ERERUdzDUPYfg4GAIggBBEKCrq4umTZuid+/e2Lx5M0pKSmp032fPnsWYMWNqdB9ERERUdzDUPSdfX1/cvn0baWlpOHToEHr06IH3338f/fr1Q1FRUY3t18zMDA0aNKix/omIiKhuYah7TgqFAubm5mjWrBnc3Nzw4Ycf4rvvvsOhQ4cQFRUFAMjKysKoUaNgZmYGExMT9OzZExcvXnxm3xEREbCwsECjRo0wYcIEFBYWSut4+ZWIiIj+jaGuBvTs2RMdOnTAt99+CwB46623cPfuXRw6dAjnzp2Dm5sbXn31VTx48KDMPo4dO4bU1FQcO3YMW7duRVRUlBQSKyI/Px8qlUptIiIiIvliqKshjo6OSEtLw4kTJ5CQkIDdu3fD3d0ddnZ2iIiIgKmpKfbs2VPm9i+99BLWrFkDR0dH9OvXD3379kVsbGyF9x8eHg6lUilNVlZW1XFYREREVEsx1NUQURQhCAIuXryI3NxcNGrUCEZGRtJ048YNpKamlrl927Ztoa2tLc1bWFjg7t27Fd5/aGgosrOzpSkjI+O5joeIiIhqNx1NFyBXycnJaNWqFXJzc2FhYYG4uLhSbUxNTcvcXldXV21eEIRKPVGrUCigUCgq3J6IiIjqNoa6GvC///0Ply5dwpQpU9C8eXNkZmZCR0cH1tbWmi6NiIiIZIqh7jnl5+cjMzMTxcXFuHPnDg4fPozw8HD069cP7777LrS0tODh4YGAgAAsXboU9vb2uHXrFg4cOIABAwbA3d1d04dAREREMsBQ95wOHz4MCwsL6Ojo4KWXXkKHDh2watUqBAUFQUvr8S2LBw8exOzZszF8+HD89ddfMDc3R/fu3dG0aVMNV09ERERyIYiiKGq6CKp5KpUKSqUS644Nh4GRnqbLISIiem7B7hs0XUKNe/L9nZ2dDRMTk3Lb8ulXIiIiIhlgqCMiIiKSAYY6IiIiIhlgqCMiIiKSAT79Ws8Euq185o2WREREVPdwpI6IiIhIBhjqiIiIiGSAoY6IiIhIBhjqiIiIiGSAoY6IiIhIBvj0az0Tej4ECr4mjIie06f14PVMRHUNR+qIiIiIZIChjoiIiEgGGOqIiIiIZIChjoiIiEgGGOqIiIiIZKDOhTpBELBv3z6N7Nva2horV6584bWkpaVBEAQkJSXV+L6IiIiobqp1oS4zMxOTJk2CjY0NFAoFrKys4O/vj9jYWE2XVsrt27fRp08fTZdBREREVLt+py4tLQ2enp4wNTXFsmXL0L59exQWFuLIkSOYMGECrly5oukS1Zibm9f4PgoKCmp8H0RERFT31aqRuvHjx0MQBCQkJGDgwIGwt7dH27ZtMXXqVJw+fVpqd+/ePQwYMAANGjSAnZ0d9u/fL60rLi7GyJEj0apVKxgYGMDBwQGfffaZ2n6Cg4MREBCAiIgIWFhYoFGjRpgwYQIKCwulNnfv3oW/vz8MDAzQqlUr7Nixo1S9/738evLkSbi4uEBfXx/u7u7Yt2+f2mXTytS2aNEiWFpawsHBQVp3/fp19OjRAw0aNECHDh1w6tSpKp1nIiIikp9aM1L34MEDHD58GIsWLYKhoWGp9aamptLn+fPnY+nSpVi2bBlWr16NwMBA3Lx5Ew0bNkRJSQmaN2+O3bt3o1GjRjh58iTGjBkDCwsLDBo0SOrj2LFjsLCwwLFjx3Dt2jUMHjwYLi4uGD16NIDH4erWrVs4duwYdHV1MXnyZNy9e7fM+lUqFfz9/eHn54evvvoKN2/eREhIiFqbitYWGxsLExMTHD16VG372bNnIyIiAnZ2dpg9ezaGDBmCa9euQUen9H/G/Px85Ofnq9VHRERE8lVrQt21a9cgiiIcHR2f2TY4OBhDhgwBACxevBirVq1CQkICfH19oauri/nz50ttW7VqhVOnTmHXrl1qwemll17CmjVroK2tDUdHR/Tt2xexsbEYPXo0rl69ikOHDiEhIQGdOnUCAERGRsLJyanMmr766isIgoAvvvgC+vr6aNOmDf78808pJAKocG2GhobYtGkT9PQev84rLS0NADBt2jT07dsXwONg27ZtW1y7du2p5yw8PFxtX0RERCRvtebyqyiKFW7r7OwsfTY0NISJiYnaKNratWvRsWNHmJmZwcjICBs3bkR6erpaH23btoW2trY0b2FhIfWRnJwMHR0ddOzYUVrv6OioNlr4XykpKXB2doa+vr60rHPnzqXaVaS29u3bS4GurOO2sLAAgDJHD0NDQ5GdnS1NGRkZZdZOREREdV+tCXV2dnYQBKFCD0Po6uqqzQuCgJKSEgBAdHQ0pk2bhpEjR+KHH35AUlIShg8fXuqBg/L6qCkVre1pl58B9ZoFQQCAMmtWKBQwMTFRm4iIiEi+ak2oa9iwIXx8fLB27Vrk5eWVWp+VlVWhfuLj49G1a1eMHz8erq6usLW1RWpqaqVqcXR0RFFREc6dOyctS0lJKbcGBwcHXLp0Se0+trNnz1Z7bURERERPU2tCHfD40mRxcTE6d+6Mb775Br///juSk5OxatUqeHh4VKgPOzs7JCYm4siRI7h69SrmzJlTKlw9i4ODA3x9fTF27FicOXMG586dw6hRo2BgYFDmNkOHDkVJSQnGjBmD5ORkHDlyBBEREQD+b1StOmojIiIieppaFepsbGxw/vx59OjRAx988AHatWuH3r17IzY2FuvXr69QH2PHjsUbb7yBwYMHo0uXLrh//z7Gjx9f6Vq2bNkCS0tLeHl54Y033sCYMWPQpEmTMtubmJjg+++/R1JSElxcXDB79mzMnTsXAKT77KqrNiIiIqL/EsTKPKFAlbJjxw4MHz4c2dnZ5Y7yvQgqlQpKpRLjjw2Hwqj0QxhERJXxqfsGTZdAVC88+f7Ozs5+5v3xteYnTeRg27ZtsLGxQbNmzXDx4kXMnDkTgwYN0nigIyIiIvljqKtGmZmZmDt3LjIzM2FhYYG33noLixYt0nRZREREVA8w1FWjGTNmYMaMGZoug4iIiOqhWvWgBBERERFVDUfq6plwt5X8IWIiIiIZ4kgdERERkQww1BERERHJAEMdERERkQww1BERERHJAEMdERERkQzw6dd6JuT8augZ6Wu6DCIioqfa4P6BpkuoszhSR0RERCQDDHVEREREMsBQR0RERCQDDHVEREREMsBQR0RERCQDDHVEREREMsBQV4Pi4uIgCAKysrI0XQoRERHJXJ0LdcHBwRAEQZoaNWoEX19f/PLLL5oujYiIiEhj6lyoAwBfX1/cvn0bt2/fRmxsLHR0dNCvXz9Nl1UjCgoKNF0CERER1QF1MtQpFAqYm5vD3NwcLi4umDVrFjIyMvDXX38BAGbOnAl7e3s0aNAANjY2mDNnDgoLC6Xtw8LC4OLigu3bt8Pa2hpKpRJvv/02cnJypDY5OTkIDAyEoaEhLCwssGLFCnh7eyMkJERqs337dri7u8PY2Bjm5uYYOnQo7t69W27t33zzDdq2bQuFQgFra2ssX75cbb21tTUWLlyId999FyYmJhgzZgwA4MSJE+jWrRsMDAxgZWWFyZMnIy8vr8z95OfnQ6VSqU1EREQkX3Uy1P1bbm4uvvzyS9ja2qJRo0YAAGNjY0RFReHy5cv47LPP8MUXX2DFihVq26WmpmLfvn2IiYlBTEwMjh8/jiVLlkjrp06divj4eOzfvx9Hjx7Fzz//jPPnz6v1UVhYiIULF+LixYvYt28f0tLSEBwcXGat586dw6BBg/D222/j0qVLCAsLw5w5cxAVFaXWLiIiAh06dMCFCxcwZ84cpKamwtfXFwMHDsQvv/yCnTt34sSJE5g4cWKZ+woPD4dSqZQmKyurCp5RIiIiqosEURRFTRdRGcHBwfjyyy+hr//4/aV5eXmwsLBATEwM3NzcnrpNREQEoqOjkZiYCODxSN2yZcuQmZkJY2NjAMCMGTPw008/4fTp08jJyUGjRo3w1Vdf4c033wQAZGdnw9LSEqNHj8bKlSufup/ExER06tQJOTk5MDIyQlxcHHr06IGHDx/C1NQUgYGB+Ouvv/DDDz9I28yYMQMHDhzAb7/9BuDxSJ2rqyv27t0rtRk1ahS0tbXx+eefS8tOnDgBLy8v5OXlSefi3/Lz85Gfny/Nq1QqWFlZYfixj/nuVyIiqrX47ld1KpUKSqUS2dnZMDExKbdtnRyp69GjB5KSkpCUlISEhAT4+PigT58+uHnzJgBg586d8PT0hLm5OYyMjPDRRx8hPT1drQ9ra2sp0AGAhYWFdOn0+vXrKCwsROfOnaX1SqUSDg4Oan2cO3cO/v7+aNGiBYyNjeHl5QUApfb1RHJyMjw9PdWWeXp64vfff0dxcbG0zN3dXa3NxYsXERUVBSMjI2ny8fFBSUkJbty48dR9KRQKmJiYqE1EREQkXzqaLqAqDA0NYWtrK81v2rQJSqUSX3zxBfr27YvAwEDMnz8fPj4+UCqViI6OLnXvmq6urtq8IAgoKSmpcA15eXnw8fGBj48PduzYATMzM6Snp8PHx+e5H24wNDRUm8/NzcXYsWMxefLkUm1btGjxXPsiIiIieaiToe6/BEGAlpYW/vnnH5w8eRItW7bE7NmzpfVPRvAqysbGBrq6ujh79qwUmrKzs3H16lV0794dAHDlyhXcv38fS5Yske5Xe3J5tyxOTk6Ij49XWxYfHw97e3toa2uXuZ2bmxsuX76sFmSJiIiI/q1Ohrr8/HxkZmYCAB4+fIg1a9YgNzcX/v7+UKlUSE9PR3R0NDp16oQDBw6o3Z9WEcbGxggKCsL06dPRsGFDNGnSBPPmzYOWlhYEQQDweIRMT08Pq1evxnvvvYdff/0VCxcuLLffDz74AJ06dcLChQsxePBgnDp1CmvWrMG6devK3W7mzJl4+eWXMXHiRIwaNQqGhoa4fPkyjh49ijVr1lTq2IiIiEie6uQ9dYcPH4aFhQUsLCzQpUsXnD17Frt374a3tzdef/11TJkyBRMnToSLiwtOnjyJOXPmVHofn376KTw8PNCvXz/06tULnp6ecHJykh5KMDMzQ1RUFHbv3o02bdpgyZIliIiIKLdPNzc37Nq1C9HR0WjXrh3mzp2LBQsWlPvELAA4Ozvj+PHjuHr1Krp16wZXV1fMnTsXlpaWlT4uIiIikqc69/SrpuTl5aFZs2ZYvnw5Ro4cqelyKu3J0zN8+pWIiGozPv2qrjJPv9bJy68vwoULF3DlyhV07twZ2dnZWLBgAQCgf//+Gq6MiIiIqDSGunJEREQgJSUFenp66NixI37++Wc0btxY02URERERlcJQVwZXV1ecO3dO02UQERERVUidfFCCiIiIiNRxpK6eWek2iW+XICIikiGO1BERERHJAEMdERERkQww1BERERHJAEMdERERkQww1BERERHJAJ9+rWdCzv8PekaGmi6DiKhW2uDeW9MlEFVZlUbqgoKC8NNPP1V3LURERERURVUKddnZ2ejVqxfs7OywePFi/Pnnn9VdFxERERFVQpVC3b59+/Dnn39i3Lhx2LlzJ6ytrdGnTx/s2bMHhYWF1V0jERERET1DlR+UMDMzw9SpU3Hx4kWcOXMGtra2GDZsGCwtLTFlyhT8/vvv1VknEREREZXjuZ9+vX37No4ePYqjR49CW1sbfn5+uHTpEtq0aYMVK1ZUR41ERERE9AxVCnWFhYX45ptv0K9fP7Rs2RK7d+9GSEgIbt26ha1bt+LHH3/Erl27sGDBguqut85IS0uDIAhISkrSdClERERUD1TpJ00sLCxQUlKCIUOGICEhAS4uLqXa9OjRA6amps9ZXu0SHByMrKws7Nu375ltrayscPv2bTRu3LjmCyMiIqJ6r0qhbsWKFXjrrbegr69fZhtTU1PcuHGjyoXVddra2jA3N6/x/RQUFEBPT6/G90NERES1W5Uuvx47duypT7nm5eVhxIgRz11UXXD48GG88sorMDU1RaNGjdCvXz+kpqZK6/97+TUuLg6CIODAgQNwdnaGvr4+Xn75Zfz666/SNmFhYaVGPVeuXAlra2tpPjg4GAEBAVi0aBEsLS3h4OBQk4dJREREdUSVQt3WrVvxzz//lFr+zz//YNu2bc9dVF2Ql5eHqVOnIjExEbGxsdDS0sKAAQNQUlJS7nbTp0/H8uXLcfbsWZiZmcHf37/SPwMTGxuLlJQUHD16FDExMU9tk5+fD5VKpTYRERGRfFXq8qtKpYIoihBFETk5OWqXX4uLi3Hw4EE0adKk2ousjQYOHKg2v3nzZpiZmeHy5cto165dmdvNmzcPvXs/fg3N1q1b0bx5c+zduxeDBg2q8L4NDQ2xadOmci+7hoeHY/78+RXuk4iIiOq2SoU6U1NTCIIAQRBgb29far0gCPUmSPz++++YO3cuzpw5g3v37kkjdOnp6eWGOg8PD+lzw4YN4eDggOTk5Ertu3379s+8jy40NBRTp06V5lUqFaysrCq1HyIiIqo7KhXqjh07BlEU0bNnT3zzzTdo2LChtE5PTw8tW7aEpaVltRdZG/n7+6Nly5b44osvYGlpiZKSErRr1w4FBQVV7lNLSwuiKKote9qlWUNDw2f2pVAooFAoqlwLERER1S2VCnVeXl4AgBs3bqBFixYQBKFGiqrt7t+/j5SUFHzxxRfo1q0bAODEiRMV2vb06dNo0aIFAODhw4e4evUqnJycADx+S0dmZiZEUZTOLX/njoiIiCqiwqHul19+Qbt27aClpYXs7GxcunSpzLbOzs7VUlxt9dJLL6FRo0bYuHEjLCwskJ6ejlmzZlVo2wULFqBRo0Zo2rQpZs+ejcaNGyMgIAAA4O3tjb/++gtLly7Fm2++icOHD+PQoUMwMTGpwaMhIiIiOahwqHNxcUFmZiaaNGkCFxcXCIJQ6lIh8Pi+uuLi4motsrYoKSmBjo4OtLS0EB0djcmTJ6Ndu3ZwcHDAqlWr4O3t/cw+lixZgvfffx+///47XFxc8P3330v3xzk5OWHdunVYvHgxFi5ciIEDB2LatGnYuHFjDR8ZERER1XWC+LRk9hQ3b96ULrnevHmz3LYtW7asluJqG19fX9ja2mLNmjWV3jYuLg49evTAw4cPNfKmDZVKBaVSieHH9kLP6Nn35BER1Ucb3HtrugQiNU++v7Ozs5955a7Cv1PXsmVL6T6vr776CrGxsWjZsqXaFBsbi+jo6OervhZ6+PAhYmJiEBcXh169emm6HCIiIqJSqvTjw59//jkcHR1LLW/bti02bNjw3EXVNiNGjMB7772HDz74AP3799d0OURERESlVOndr5mZmbCwsCi13MzMDLdv337uomqbvXv3Pncf3t7eT70HkYiIiKg6VGmkzsrKCvHx8aWWx8fH15vfqSMiIiKqTao0Ujd69GiEhISgsLAQPXv2BPD4faQzZszABx98UK0FUvVa6daTP5FCREQkQ1UKddOnT8f9+/cxfvx46Q0K+vr6mDlzJkJDQ6u1QCIiIiJ6tgr/pMnT5ObmIjk5GQYGBrCzs+NrqWqxyjwSTURERLVDZb6/qzRS94SRkRE6der0PF0QERERUTWo0oMSRERERFS7MNQRERERycBzXX6luifk+/PQa2Ck6TKIiOqlDQPcNV0CyRhH6oiIiIhkgKGOiIiISAYY6oiIiIhkgKGOiIiISAYY6oiIiIhkgKGOiIiISAYY6p6TIAjYt28fACAtLQ2CICApKUmjNREREVH9U+9DXXBwMAICAtSW7dmzB/r6+li+fHmtqIeIiIjoWfjjw/+xadMmTJgwARs2bMDw4cM1XQ4RERFRhdT7kbp/W7p0KSZNmoTo6Ggp0K1fvx6tW7eGnp4eHBwcsH379gr3V1xcjBEjRsDR0RHp6ekoLi7GyJEj0apVKxgYGMDBwQGfffaZ1D4sLAxbt27Fd999B0EQIAgC4uLiAAAzZ86Evb09GjRoABsbG8yZMweFhYVl7js/Px8qlUptIiIiIvniSN3/N3PmTKxbtw4xMTF49dVXAQB79+7F+++/j5UrV6JXr16IiYnB8OHD0bx5c/To0aPc/vLz8zFkyBCkpaXh559/hpmZGQoLC9G8eXPs3r0bjRo1wsmTJzFmzBhYWFhg0KBBmDZtGpKTk6FSqbBlyxYAQMOGDQEAxsbGiIqKgqWlJS5duoTRo0fD2NgYM2bMeOr+w8PDMX/+/Go8Q0RERFSbCaIoipouQpOCg4Px9ddfo6CgALGxsejZs6e0ztPTE23btsXGjRulZYMGDUJeXh4OHDgA4PGDEnv37kVAQADS0tLQqlUr/PzzzwgLC0N+fj5iYmKgVCrL3P/EiRORmZmJPXv2SPVkZWVJD1+UJSIiAtHR0UhMTHzq+vz8fOTn50vzKpUKVlZWGP7lMb77lYhIQ/juV6oslUoFpVKJ7OxsmJiYlNuWl18BODs7w9raGvPmzUNubq60PDk5GZ6enmptPT09kZycXG5/Q4YMQV5eHn744YdSgW7t2rXo2LEjzMzMYGRkhI0bNyI9Pf2ZNe7cuROenp4wNzeHkZERPvroo3K3UygUMDExUZuIiIhIvhjqADRr1gxxcXH4888/4evri5ycnOfqz8/PD7/88gtOnTqltjw6OhrTpk3DyJEj8cMPPyApKQnDhw9HQUFBuf2dOnUKgYGB8PPzQ0xMDC5cuIDZs2c/czsiIiKqPxjq/r+WLVvi+PHjyMzMlIKdk5MT4uPj1drFx8ejTZs25fY1btw4LFmyBK+//jqOHz+utm3Xrl0xfvx4uLq6wtbWFqmpqWrb6unpobi4WG3ZyZMn0bJlS8yePRvu7u6ws7PDzZs3n/OIiYiISE74oMS/WFlZIS4uDj169ICPjw/ee+89jBo1Cq6urujVqxe+//57fPvtt/jxxx+f2dekSZNQXFyMfv364dChQ3jllVdgZ2eHbdu24ciRI2jVqhW2b9+Os2fPolWrVtJ21tbWOHLkCFJSUtCoUSMolUrY2dkhPT0d0dHR6NSpEw4cOIC9e/fW5KkgIiKiOoYjdf/RvHlzxMXF4d69e1i/fj2WLVuGiIgItG3bFp9//jm2bNkCb2/vCvUVEhKC+fPnw8/PDydPnsTYsWPxxhtvYPDgwejSpQvu37+P8ePHq20zevRoODg4wN3dHWZmZoiPj8frr7+OKVOmYOLEiXBxccHJkycxZ86cGjh6IiIiqqvq/dOv9cWTp2f49CsRkebw6VeqLD79SkRERFTPMNQRERERyQBDHREREZEMMNQRERERyQB/0qSeWenvxrdLEBERyRBH6oiIiIhkgKGOiIiISAYY6oiIiIhkgKGOiIiISAb4oEQ9ExJ+Hnr6fKMEEREAbJjHNzyQfHCkjoiIiEgGGOqIiIiIZIChjoiIiEgGGOqIiIiIZIChjoiIiEgGGOqIiIiIZKBWh7q4uDgIgoCsrCxNlwIACAsLg4uLS6W2EQQB+/btqxW1EBERkXzVilB36tQpaGtro2/fvpouhYiIiKhOqhWhLjIyEpMmTcJPP/2EW7duabocIiIiojpH46EuNzcXO3fuxLhx49C3b19ERUWVanPu3Dm4u7ujQYMG6Nq1K1JSUqR1Ty5Dbt68GS1atICRkRHGjx+P4uJiLF26FObm5mjSpAkWLVqk1mdWVhZGjRoFMzMzmJiYoGfPnrh48aJamyVLlqBp06YwNjbGyJEj8ejRI7X1Z8+eRe/evdG4cWMolUp4eXnh/Pnzpeq/ffs2+vTpAwMDA9jY2GDPnj1q62fOnAl7e3s0aNAANjY2mDNnDgoLCytVCxEREdVvGg91u3btgqOjIxwcHPDOO+9g8+bNEEVRrc3s2bOxfPlyJCYmQkdHByNGjFBbn5qaikOHDuHw4cP4+uuvERkZib59++KPP/7A8ePH8cknn+Cjjz7CmTNnpG3eeust3L17F4cOHcK5c+fg5uaGV199FQ8ePJDqCgsLw+LFi5GYmAgLCwusW7dObb85OTkICgrCiRMncPr0adjZ2cHPzw85OTlq7ebMmYOBAwfi4sWLCAwMxNtvv43k5GRpvbGxMaKionD58mV89tln+OKLL7BixQq1c/SsWv4rPz8fKpVKbSIiIiL5EsT/JqgXzNPTE4MGDcL777+PoqIiWFhYYPfu3fD29kZcXBx69OiBH3/8Ea+++ioA4ODBg+jbty/++ecf6OvrIywsDMuWLUNmZiaMjY0BAL6+vkhJSUFqaiq0tB7nVkdHRwQHB2PWrFk4ceIE+vbti7t370KhUEi12NraYsaMGRgzZgy6du0KV1dXrF27Vlr/8ssv49GjR0hKSnrqsZSUlMDU1BRfffUV+vXrB+DxgxLvvfce1q9fr9aPm5tbmcEsIiIC0dHRSExMBIAq1RIWFob58+eXWj581jG++5WI6P/ju1+ptlOpVFAqlcjOzoaJiUm5bTU6UpeSkoKEhAQMGTIEAKCjo4PBgwcjMjJSrZ2zs7P02cLCAgBw9+5daZm1tbUU6ACgadOmaNOmjRTonix7ss3FixeRm5uLRo0awcjISJpu3LiB1NRUAEBycjK6dOmiVoeHh4fa/J07dzB69GjY2dlBqVTCxMQEubm5SE9PL3c7Dw8PtZG6nTt3wtPTE+bm5jAyMsJHH32k1kdFavmv0NBQZGdnS1NGRka57YmIiKhu09HkziMjI1FUVARLS0tpmSiKUCgUWLNmjbRMV1dX+iwIAoDHo2JPW/+kzdOWPdkmNzcXFhYWiIuLK1WTqalphesPCgrC/fv38dlnn6Fly5ZQKBTw8PBAQUFBhfs4deoUAgMDMX/+fPj4+ECpVCI6OhrLly+vcB9Po1Ao1EYhiYiISN40NlJXVFSEbdu2Yfny5UhKSpKmixcvwtLSEl9//XWN7dvNzQ2ZmZnQ0dGBra2t2tS4cWMAgJOTk9o9eABw+vRptfn4+HhMnjwZfn5+aNu2LRQKBe7du1dqf//d7vTp03BycgIAnDx5Ei1btsTs2bPh7u4OOzs73Lx5U619RWohIiKi+k1jI3UxMTF4+PAhRo4cCaVSqbZu4MCBiIyMxLJly2pk37169YKHhwcCAgKwdOlS2Nvb49atWzhw4AAGDBgAd3d3vP/++wgODoa7uzs8PT2xY8cO/Pbbb7CxsZH6sbOzw/bt2+Hu7g6VSoXp06fDwMCg1P52794Nd3d3vPLKK9ixYwcSEhKkS8x2dnZIT09HdHQ0OnXqhAMHDmDv3r1q21ekFiIiIqrfNDZSFxkZiV69epUKdMDjUJeYmIhffvmlRvYtCAIOHjyI7t27Y/jw4bC3t8fbb7+NmzdvomnTpgCAwYMHY86cOZgxYwY6duyImzdvYty4caWO4eHDh3Bzc8OwYcMwefJkNGnSpNT+5s+fj+joaDg7O2Pbtm34+uuv0aZNGwDA66+/jilTpmDixIlwcXHByZMnMWfOHLXtK1ILERER1W8af/qVXownT8/w6Vciov/Dp1+ptqszT78SERERUfVgqCMiIiKSAYY6IiIiIhlgqCMiIiKSAY3++DC9eCtD3Z55oyURERHVPRypIyIiIpIBhjoiIiIiGWCoIyIiIpIBhjoiIiIiGWCoIyIiIpIBPv1azywKOQ+FHl8TRkREtd+CDXyNW2VwpI6IiIhIBhjqiIiIiGSAoY6IiIhIBhjqiIiIiGSAoY6IiIhIBhjqiIiIiGSAoe5fBEHAvn37NF1GhQQHByMgIEDTZRAREVEtUa9CXWZmJiZNmgQbGxsoFApYWVnB398fsbGxmi6t0j777DNERUVpugwiIiKqJerNjw+npaXB09MTpqamWLZsGdq3b4/CwkIcOXIEEyZMwJUrVzRdYqUolUpNl0BERES1SL0ZqRs/fjwEQUBCQgIGDhwIe3t7tG3bFlOnTsXp06eldvfu3cOAAQPQoEED2NnZYf/+/Wr9/Prrr+jTpw+MjIzQtGlTDBs2DPfu3ZPWe3t7Y/LkyZgxYwYaNmwIc3NzhIWFqfUhCAI2bdpU5n6Ki4sxcuRItGrVCgYGBnBwcMBnn32m1sezLr/m5+dDpVKpTURERCRf9SLUPXjwAIcPH8aECRNgaGhYar2pqan0ef78+Rg0aBB++eUX+Pn5ITAwEA8ePAAAZGVloWfPnnB1dUViYiIOHz6MO3fuYNCgQWr9bd26FYaGhjhz5gyWLl2KBQsW4OjRo2ptyttPSUkJmjdvjt27d+Py5cuYO3cuPvzwQ+zatavCxxweHg6lUilNVlZWFd6WiIiI6p56EequXbsGURTh6Oj4zLbBwcEYMmQIbG1tsXjxYuTm5iIhIQEAsGbNGri6umLx4sVwdHSEq6srNm/ejGPHjuHq1atSH87Ozpg3bx7s7Ozw7rvvwt3dvdR9e+XtR1dXF/Pnz4e7uztatWqFwMBADB8+vFKhLjQ0FNnZ2dKUkZFR4W2JiIio7qkX99SJoljhts7OztJnQ0NDmJiY4O7duwCAixcv4tixYzAyMiq1XWpqKuzt7Uv1AQAWFhZSHxXZDwCsXbsWmzdvRnp6Ov755x8UFBTAxcWlwsehUCigUCgq3J6IiIjqtnoR6uzs7CAIQoUehtDV1VWbFwQBJSUlAIDc3Fz4+/vjk08+KbWdhYVFhfqoSJvo6GhMmzYNy5cvh4eHB4yNjbFs2TKcOXPmmfUTERFR/VQvQl3Dhg3h4+ODtWvXYvLkyaXuq8vKylK7r64sbm5u+Oabb2BtbQ0dnZo7dfHx8ejatSvGjx8vLUtNTa2x/REREVHdVy/uqQMeX84sLi5G586d8c033+D3339HcnIyVq1aBQ8Pjwr1MWHCBDx48ABDhgzB2bNnkZqaiiNHjmD48OEoLi6utlrt7OyQmJiII0eO4OrVq5gzZw7Onj1bbf0TERGR/NSbUGdjY4Pz58+jR48e+OCDD9CuXTv07t0bsbGxWL9+fYX6sLS0RHx8PIqLi/Haa6+hffv2CAkJgampKbS0qu9Ujh07Fm+88QYGDx6MLl264P79+2qjdkRERET/JYiVeYqA6iyVSgWlUokZw49BoVf6QQ8iIqLaZsEGd02XoHFPvr+zs7NhYmJSbtt6M1JHREREJGcMdUREREQywFBHREREJAMMdUREREQyUC9+p47+z+yVbs+80ZKIiIjqHo7UEREREckAQx0RERGRDDDUEREREckAQx0RERGRDPBBiXpmb8h5NOAbJYiIKu0tvt2AajmO1BERERHJAEMdERERkQww1BERERHJAEMdERERkQww1BERERHJAEMdERERkQww1BERERHJAENdNQgODoYgCBAEAXp6erC1tcWCBQtQVFSk6dKIiIionuCPD1cTX19fbNmyBfn5+Th48CAmTJgAXV1dhIaGaro0IiIiqgc4UldNFAoFzM3N0bJlS4wbNw69evXC/v374e3tjZCQELW2AQEBCA4Oluatra2xePFijBgxAsbGxmjRogU2btyotk1GRgYGDRoEU1NTNGzYEP3790daWlrNHxgRERHVCQx1NcTAwAAFBQUVbr98+XK4u7vjwoULGD9+PMaNG4eUlBQAQGFhIXx8fGBsbIyff/4Z8fHxMDIygq+vb5n7yM/Ph0qlUpuIiIhIvhjqqpkoivjxxx9x5MgR9OzZs8Lb+fn5Yfz48bC1tcXMmTPRuHFjHDt2DACwc+dOlJSUYNOmTWjfvj2cnJywZcsWpKenIy4u7qn9hYeHQ6lUSpOVlVV1HB4RERHVUgx11SQmJgZGRkbQ19dHnz59MHjwYISFhVV4e2dnZ+mzIAgwNzfH3bt3AQAXL17EtWvXYGxsDCMjIxgZGaFhw4Z49OgRUlNTn9pfaGgosrOzpSkjI+O5jo+IiIhqNz4oUU169OiB9evXQ09PD5aWltDReXxqtbS0IIqiWtvCwsJS2+vq6qrNC4KAkpISAEBubi46duyIHTt2lNrOzMzsqfUoFAooFIoqHQsRERHVPQx11cTQ0BC2trallpuZmeH27dvSfHFxMX799Vf06NGjwn27ublh586daNKkCUxMTKqlXiIiIpIXXn6tYT179sSBAwdw4MABXLlyBePGjUNWVlal+ggMDETjxo3Rv39//Pzzz7hx4wbi4uIwefJk/PHHHzVTOBEREdUpDHU1bMSIEQgKCsK7774LLy8v2NjYVGqUDgAaNGiAn376CS1atMAbb7wBJycnjBw5Eo8ePeLIHREREQEABPG/N3yRLKlUKiiVSkQNP4YGekaaLoeIqM55a4O7pkugeujJ93d2dvYzB3I4UkdEREQkAwx1RERERDLAUEdEREQkAwx1RERERDLA36mrZwasdOMTs0RERDLEkToiIiIiGWCoIyIiIpIBhjoiIiIiGWCoIyIiIpIBhjoiIiIiGeDTr/XM+ZDjMNIz1HQZREREsuK+oaemS+BIHREREZEcMNQRERERyQBDHREREZEMMNQRERERyQBDHREREZEMMNS9YGFhYXBxcXnufgRBwL59+567HyIiIpKHehXqgoODIQgC3nvvvVLrJkyYAEEQEBwc/OILq4Lbt2+jT58+mi6DiIiIaol6FeoAwMrKCtHR0fjnn3+kZY8ePcJXX32FFi1aaLCyyjE3N4dCodB0GURERFRL1LtQ5+bmBisrK3z77bfSsm+//RYtWrSAq6urtMza2horV65U29bFxQVhYWHSvCAI+Pzzz9GvXz80aNAATk5OOHXqFK5duwZvb28YGhqia9euSE1NLVXH559/DisrKzRo0ACDBg1Cdna2tO7s2bPo3bs3GjduDKVSCS8vL5w/f15te15+JSIion+rd6EOAEaMGIEtW7ZI85s3b8bw4cOr1NfChQvx7rvvIikpCY6Ojhg6dCjGjh2L0NBQJCYmQhRFTJw4UW2ba9euYdeuXfj+++9x+PBhXLhwAePHj5fW5+TkICgoCCdOnMDp06dhZ2cHPz8/5OTkVLiu/Px8qFQqtYmIiIjkq16GunfeeQcnTpzAzZs3cfPmTcTHx+Odd96pUl/Dhw/HoEGDYG9vj5kzZyItLQ2BgYHw8fGBk5MT3n//fcTFxalt8+jRI2zbtg0uLi7o3r07Vq9ejejoaGRmZgIAevbsiXfeeQeOjo5wcnLCxo0b8ffff+P48eMVris8PBxKpVKarKysqnR8REREVDfUy1BnZmaGvn37IioqClu2bEHfvn3RuHHjKvXl7OwsfW7atCkAoH379mrLHj16pDZS1qJFCzRr1kya9/DwQElJCVJSUgAAd+7cwejRo2FnZwelUgkTExPk5uYiPT29wnWFhoYiOztbmjIyMqp0fERERFQ36Gi6AE0ZMWKEdFl07dq1pdZraWlBFEW1ZYWFhaXa6erqSp8FQShzWUlJSYVrCwoKwv379/HZZ5+hZcuWUCgU8PDwQEFBQYX7UCgUfJCCiIioHqm3oc7X1xcFBQUQBAE+Pj6l1puZmeH27dvSvEqlwo0bN6pl3+np6bh16xYsLS0BAKdPn4aWlhYcHBwAAPHx8Vi3bh38/PwAABkZGbh371617JuIiIjkqd6GOm1tbSQnJ0uf/6tnz56IioqCv78/TE1NMXfu3Ke2qwp9fX0EBQUhIiICKpUKkydPxqBBg2Bubg4AsLOzw/bt2+Hu7g6VSoXp06fDwMCgWvZNRERE8lQv76l7wsTEBCYmJk9dFxoaCi8vL/Tr1w99+/ZFQEAAWrduXS37tbW1xRtvvAE/Pz+89tprcHZ2xrp166T1kZGRePjwIdzc3DBs2DBMnjwZTZo0qZZ9ExERkTwJ4n9vHCNZUqlUUCqVODZ8P4z0DDVdDhERkay4b+hZI/0++f7Ozs4ucyDqiXo9UkdEREQkFwx1RERERDLAUEdEREQkAwx1RERERDJQb3/SpL5yW+n1zBstiYiIqO7hSB0RERGRDDDUEREREckAQx0RERGRDDDUEREREckAQx0RERGRDPDp13rmfMg6GOnpa7oMIiKqJPcNIZougWo5jtQRERERyQBDHREREZEMMNQRERERyQBDHREREZEMMNQRERERyQBDHREREZEM1LtQl5aWBkEQkJSUVOP7ioqKgqmpaY30bW1tjZUrV9ZI30RERFT31NpQFxwcjICAgFLL4+LiIAgCsrKyXnhNRERERLVVrQ11tVlBQYGmSyAiIiJSU2dDXV5eHkxMTLBnzx615fv27YOhoSFycnIAAAkJCXB1dYW+vj7c3d1x4cKFUn39+uuv6NOnD4yMjNC0aVMMGzYM9+7dk9Z7e3tj4sSJCAkJQePGjeHj4wMA+PTTT9G+fXsYGhrCysoK48ePR25ubqn+9+3bBzs7O+jr68PHxwcZGRnSutTUVPTv3x9NmzaFkZEROnXqhB9//FFt+7t378Lf3x8GBgZo1aoVduzYUfUTR0RERLJUZ0OdoaEh3n77bWzZskVt+ZYtW/Dmm2/C2NgYubm56NevH9q0aYNz584hLCwM06ZNU2uflZWFnj17wtXVFYmJiTh8+DDu3LmDQYMGqbXbunUr9PT0EB8fjw0bNgAAtLS0sGrVKvz222/YunUr/ve//2HGjBlq2/39999YtGgRtm3bhvj4eGRlZeHtt9+W1ufm5sLPzw+xsbG4cOECfH194e/vj/T0dKlNcHAwMjIycOzYMezZswfr1q3D3bt3yz0/+fn5UKlUahMRERHJV61+92tMTAyMjIzUlhUXF0ufR40aha5du+L27duwsLDA3bt3cfDgQWmk66uvvkJJSQkiIyOhr6+Ptm3b4o8//sC4ceOkPtasWQNXV1csXrxYWrZ582ZYWVnh6tWrsLe3BwDY2dlh6dKlarWEhIRIn62trfHxxx/jvffew7p166TlhYWFWLNmDbp06QLgcTh0cnJCQkICOnfujA4dOqBDhw5S+4ULF2Lv3r3Yv38/Jk6ciKtXr+LQoUNISEhAp06dAACRkZFwcnIq99yFh4dj/vz55bYhIiIi+ajVI3U9evRAUlKS2rRp0yZpfefOndG2bVts3boVAPDll1+iZcuW6N69OwAgOTkZzs7O0Nf/vxfYe3h4qO3j4sWLOHbsGIyMjKTJ0dERwONLo0907NixVH0//vgjXn31VTRr1gzGxsYYNmwY7t+/j7///ltqo6OjI4UxAHB0dISpqSmSk5MBPB6pmzZtGpycnGBqagojIyMkJydLI3XJycnQ0dFR2/+TPsoTGhqK7Oxsafr3JV8iIiKSn1o9UmdoaAhbW1u1ZX/88Yfa/KhRo7B27VrMmjULW7ZswfDhwyEIQoX3kZubC39/f3zyySel1llYWKjV8m9paWno168fxo0bh0WLFqFhw4Y4ceIERo4ciYKCAjRo0KBC+582bRqOHj2KiIgI2NrawsDAAG+++eZzP4yhUCigUCieqw8iIiKqO2r1SF1FvPPOO7h58yZWrVqFy5cvIygoSFrn5OSEX375BY8ePZKWnT59Wm17Nzc3/Pbbb7C2toatra3a9N8g92/nzp1DSUkJli9fjpdffhn29va4detWqXZFRUVITEyU5lNSUpCVlSVdPo2Pj0dwcDAGDBiA9u3bw9zcHGlpaVJ7R0dHFBUV4dy5c6X6ICIiInqizoe6l156CW+88QamT5+O1157Dc2bN5fWDR06FIIgYPTo0bh8+TIOHjyIiIgIte0nTJiABw8eYMiQITh79ixSU1Nx5MgRDB8+XO3+vf+ytbVFYWEhVq9ejevXr2P79u3SAxT/pquri0mTJuHMmTM4d+4cgoOD8fLLL6Nz584AHt+r9+233yIpKQkXL17E0KFDUVJSIm3v4OAAX19fjB07Vupj1KhRMDAweN5TR0RERDJS50MdAOmS54gRI9SWGxkZ4fvvv8elS5fg6uqK2bNnl7rMamlpifj4eBQXF+O1115D+/btERISAlNTU2hplX16OnTogE8//RSffPIJ2rVrhx07diA8PLxUuwYNGmDmzJkYOnQoPD09YWRkhJ07d0rrP/30U7z00kvo2rUr/P394ePjAzc3N7U+tmzZAktLS3h5eeGNN97AmDFj0KRJk6qcKiIiIpIpQRRFUdNFPK/t27djypQpuHXrFvT09DRdTq2kUqmgVCpxbHg4jPT0n70BERHVKu4bQjRdAmnAk+/v7OxsmJiYlNu2Vj8o8Sx///03bt++jSVLlmDs2LEMdERERFRv1enLr0uXLoWjoyPMzc0RGhqq6XKIiIiINKZOh7qwsDAUFhYiNja21I8UExEREdUndTrUEREREdFjdfqeOqo8t5Xjn3mjJREREdU9HKkjIiIikgGO1NUTT365RqVSabgSIiIiqqgn39sV+QU6hrp64v79+wAAKysrDVdCRERElZWTkwOlUlluG4a6eqJhw4YAgPT09Gf+oaDnp1KpYGVlhYyMDN7DWMN4rl8cnusXh+f6xant51oUReTk5MDS0vKZbRnq6oknrzxTKpW18g+tXJmYmPB8vyA81y8Oz/WLw3P94tTmc13RwRg+KEFEREQkAwx1RERERDLAUFdPKBQKzJs3DwqFQtOl1As83y8Oz/WLw3P94vBcvzhyOteCWJFnZImIiIioVuNIHREREZEMMNQRERERyQBDHREREZEMMNQRERERyQBDnYysXbsW1tbW0NfXR5cuXZCQkFBu+927d8PR0RH6+vpo3749Dh48+IIqrfsqc66/+OILdOvWDS+99BJeeukl9OrV65n/bUhdZf9sPxEdHQ1BEBAQEFCzBcpIZc91VlYWJkyYAAsLCygUCtjb2/Pvkgqq7LleuXIlHBwcYGBgACsrK0yZMgWPHj16QdXWTT/99BP8/f1haWkJQRCwb9++Z24TFxcHNzc3KBQK2NraIioqqsbrrDYiyUJ0dLSop6cnbt68Wfztt9/E0aNHi6ampuKdO3ee2j4+Pl7U1tYWly5dKl6+fFn86KOPRF1dXfHSpUsvuPK6p7LneujQoeLatWvFCxcuiMnJyWJwcLCoVCrFP/744wVXXjdV9nw/cePGDbFZs2Zit27dxP79+7+YYuu4yp7r/Px80d3dXfTz8xNPnDgh3rhxQ4yLixOTkpJecOV1T2XP9Y4dO0SFQiHu2LFDvHHjhnjkyBHRwsJCnDJlyguuvG45ePCgOHv2bPHbb78VAYh79+4tt/3169fFBg0aiFOnThUvX74srl69WtTW1hYPHz78Ygp+Tgx1MtG5c2dxwoQJ0nxxcbFoaWkphoeHP7X9oEGDxL59+6ot69Klizh27NgarVMOKnuu/6uoqEg0NjYWt27dWlMlykpVzndRUZHYtWtXcdOmTWJQUBBDXQVV9lyvX79etLGxEQsKCl5UibJR2XM9YcIEsWfPnmrLpk6dKnp6etZonXJSkVA3Y8YMsW3btmrLBg8eLPr4+NRgZdWHl19loKCgAOfOnUOvXr2kZVpaWujVqxdOnTr11G1OnTql1h4AfHx8ymxPj1XlXP/X33//jcLCQjRs2LCmypSNqp7vBQsWoEmTJhg5cuSLKFMWqnKu9+/fDw8PD0yYMAFNmzZFu3btsHjxYhQXF7+osuukqpzrrl274ty5c9Il2uvXr+PgwYPw8/N7ITXXF3X9u1FH0wXQ87t37x6Ki4vRtGlTteVNmzbFlStXnrpNZmbmU9tnZmbWWJ1yUJVz/V8zZ86EpaVlqb84qLSqnO8TJ04gMjISSUlJL6BC+ajKub5+/Tr+97//ITAwEAcPHsS1a9cwfvx4FBYWYt68eS+i7DqpKud66NChuHfvHl555RWIooiioiK89957+PDDD19EyfVGWd+NKpUK//zzDwwMDDRUWcVwpI7oBVqyZAmio6Oxd+9e6Ovra7oc2cnJycGwYcPwxRdfoHHjxpouR/ZKSkrQpEkTbNy4ER07dsTgwYMxe/ZsbNiwQdOlyU5cXBwWL16MdevW4fz58/j2229x4MABLFy4UNOlUS3CkToZaNy4MbS1tXHnzh215Xfu3IG5uflTtzE3N69Ue3qsKuf6iYiICCxZsgQ//vgjnJ2da7JM2ajs+U5NTUVaWhr8/f2lZSUlJQAAHR0dpKSkoHXr1jVbdB1VlT/bFhYW0NXVhba2trTMyckJmZmZKCgogJ6eXo3WXFdV5VzPmTMHw4YNw6hRowAA7du3R15eHsaMGYPZs2dDS4tjNNWhrO9GExOTWj9KB3CkThb09PTQsWNHxMbGSstKSkoQGxsLDw+Pp27j4eGh1h4Ajh49WmZ7eqwq5xoAli5dioULF+Lw4cNwd3d/EaXKQmXPt6OjIy5duoSkpCRpev3119GjRw8kJSXBysrqRZZfp1Tlz7anpyeuXbsmBWcAuHr1KiwsLBjoylGVc/3333+XCm5PwrTIV7hXmzr/3ajpJzWoekRHR4sKhUKMiooSL1++LI4ZM0Y0NTUVMzMzRVEUxWHDhomzZs2S2sfHx4s6OjpiRESEmJycLM6bN48/aVJBlT3XS5YsEfX09MQ9e/aIt2/flqacnBxNHUKdUtnz/V98+rXiKnuu09PTRWNjY3HixIliSkqKGBMTIzZp0kT8+OOPNXUIdUZlz/W8efNEY2Nj8euvvxavX78u/vDDD2Lr1q3FQYMGaeoQ6oScnBzxwoUL4oULF0QA4qeffipeuHBBvHnzpiiKojhr1ixx2LBhUvsnP2kyffp0MTk5WVy7di1/0oQ0Y/Xq1WKLFi1EPT09sXPnzuLp06eldV5eXmJQUJBa+127don29vainp6e2LZtW/HAgQMvuOK6qzLnumXLliKAUtO8efNefOF1VGX/bP8bQ13lVPZcnzx5UuzSpYuoUChEGxsbcdGiRWJRUdELrrpuqsy5LiwsFMPCwsTWrVuL+vr6opWVlTh+/Hjx4cOHL77wOuTYsWNP/fv3ybkNCgoSvby8Sm3j4uIi6unpiTY2NuKWLVteeN1VJYgix22JiIiI6jreU0dEREQkAwx1RERERDLAUEdEREQkAwx1RERERDLAUEdEREQkAwx1RERERDLAUEdEREQkAwx1RERERM/hp59+gr+/PywtLSEIAvbt21fpPkRRREREBOzt7aFQKNCsWTMsWrSoUn0w1BER1QFhYWFwcXHRyL6tra2xcuVKjeybqC7Iy8tDhw4dsHbt2ir38f7772PTpk2IiIjAlStXsH//fnTu3LlSfTDUERE9Q3BwMARBgCAI0NXVRatWrTBjxgw8evRI06VVyr+PQ09PD7a2tliwYAGKiorK3e7s2bMYM2bMC6qSqO7p06cPPv74YwwYMOCp6/Pz8zFt2jQ0a9YMhoaG6NKlC+Li4qT1ycnJWL9+Pb777ju8/vrraNWqFTp27IjevXtXqg6GOiKiCvD19cXt27dx/fp1rFixAp9//jnmzZun6bIq7clx/P777/jggw8QFhaGZcuWPbVtQUEBAMDMzAwNGjR4kWUSycrEiRNx6tQpREdH45dffsFbb70FX19f/P777wCA77//HjY2NoiJiUGrVq1gbW2NUaNG4cGDB5XaD0MdEVEFKBQKmJubw8rKCgEBAejVqxeOHj0qrS8pKUF4eDhatWoFAwMDdOjQAXv27JHWP3z4EIGBgTAzM4OBgQHs7OywZcsWaf3MmTNhb2+PBg0awMbGBnPmzEFhYWG5NW3atAlOTk7Q19eHo6Mj1q1bV+HjaNmyJcaNG4devXph//79AB6P5AUEBGDRokWwtLSEg4MDgNKXX7OysjB27Fg0bdoU+vr6aNeuHWJiYqT1J06cQLdu3WBgYAArKytMnjwZeXl5z6yNSI7S09OxZcsW7N69G926dUPr1q0xbdo0vPLKK9LfAdevX8fNmzexe/dubNu2DVFRUTh37hzefPPNSu1LpyYOgIhIzn799VecPHkSLVu2lJaFh4fjyy+/xIYNG2BnZ4effvoJ77zzDszMzODl5YU5c+bg8uXLOHToEBo3boxr167hn3/+kbY3NjZGVFQULC0tcenSJYwePRrGxsaYMWPGU2vYsWMH5s6dizVr1sDV1RUXLlzA6NGjYWhoiKCgoAofi4GBAe7fvy/Nx8bGwsTERC2w/ltJSQn69OmDnJwcfPnll2jdujUuX74MbW1tAEBqaip8fX3x8ccfY/Pmzfjrr78wceJETJw4US3EEtUXly5dQnFxMezt7dWW5+fno1GjRgAe/3+Vn5+Pbdu2Se0iIyPRsWNHpKSkSP/AehaGOiKiCoiJiYGRkRGKioqQn58PLS0trFmzBsDjv5wXL16MH3/8ER4eHgAAGxsbnDhxAp9//jm8vLyQnp4OV1dXuLu7A3g8+vVvH330kfTZ2toa06ZNQ3R0dJmhbt68eVi+fDneeOMNAECrVq1w+fJlfP755xUKdaIoIjY2FkeOHMGkSZOk5YaGhti0aRP09PSeut2PP/6IhIQEJCcnS18+NjY20vrw8HAEBgYiJCQEAGBnZ4dVq1bBy8sL69evh76+/jNrI5KT3NxcaGtr49y5c9I/fp4wMjICAFhYWEBHR0ct+Dk5OQF4PNLHUEdEVI169OiB9evXIy8vDytWrICOjg4GDhwIALh27Rr+/vvvUjc1FxQUwNXVFQAwbtw4DBw4EOfPn8drr72GgIAAdO3aVWq7c+dOrFq1CqmpqcjNzUVRURFMTEyeWkteXh5SU1MxcuRIjB49WlpeVFQEpVJZ7nE8CaeFhYUoKSnB0KFDERYWJq1v3759mYEOAJKSktC8efNSow5PXLx4Eb/88gt27NghLRNFESUlJbhx44b0RUVUX7i6uqK4uBh3795Ft27dntrG09MTRUVFSE1NRevWrQEAV69eBQC1KwLPwlBHRFQBhoaGsLW1BQBs3rwZHTp0QGRkJEaOHInc3FwAwIEDB9CsWTO17RQKBYDHT8fdvHkTBw8exNGjR/Hqq69iwoQJiIiIwKlTpxAYGIj58+fDx8cHSqUS0dHRWL58+VNrebK/L774Al26dFFb99+RgP96Ek719PRgaWkJHR31rwFDQ8NytzcwMCh3fW5uLsaOHYvJkyeXWteiRYtytyWqq3Jzc3Ht2jVp/saNG0hKSkLDhg1hb2+PwMBAvPvuu1i+fDlcXV3x119/ITY2Fs7Ozujbty969eoFNzc3jBgxAitXrkRJSQkmTJiA3r17l/kPqKdhqCMiqiQtLS18+OGHmDp1KoYOHYo2bdpAoVAgPT0dXl5eZW5nZmaGoKAgBAUFoVu3bpg+fToiIiKk+/Nmz54ttb1582aZ/TRt2hSWlpa4fv06AgMDK1X7v8NpVTg7O+OPP/7A1atXn/pl4+bmhsuXLz/XPojqmsTERPTo0UOanzp1KgAgKCgIUVFR2LJlCz7++GN88MEH+PPPP9G4cWO8/PLL6NevH4DHf6d8//33mDRpErp37w5DQ0P06dOnzH/YlYWhjoioCt566y1Mnz4da9euxbRp0zBt2jRMmTIFJSUleOWVV5CdnY34+HiYmJggKCgIc+fORceOHdG2bVvk5+cjJiZGuhRpZ2eH9PR0REdHo1OnTjhw4AD27t1b7v7nz5+PyZMnQ6lUwtfXF/n5+UhMTMTDhw+lL5Sa4OXlhe7du2PgwIH49NNPYWtriytXrkAQBPj6+mLmzJl4+eWXMXHiRIwaNQqGhoa4fPkyjh49Kt2DSCQ33t7eEEWxzPW6urqYP38+5s+fX2YbS0tLfPPNN89VB3/ShIioCnR0dDBx4kQsXboUeXl5WLhwIebMmYPw8HA4OTnB19cXBw4cQKtWrQAAenp6CA0NhbOzM7p37w5tbW1ER0cDAF5//XVMmTIFEydOhIuLC06ePIk5c+aUu/9Ro0Zh06ZN2LJlC9q3bw8vLy9ERUVJ+6tJ33zzDTp16oQhQ4agTZs2mDFjBoqLiwE8Hsk7fvw4rl69im7dusHV1RVz586FpaVljddFVN8JYnnRkoiIiIjqBI7UEREREckAQx0RERGRDDDUEREREckAQx0RERGRDDDUEREREckAQx0RERGRDDDUEREREckAQx0RERGRDDDUEREREckAQx0RERGRDDDUEREREcnA/wNS4BgDf6mn3AAAAABJRU5ErkJggg==",
      "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 features in categorical:\n",
    "    sns.barplot(x=df['resale_price'],y=df[features],palette='hls',errorbar=None)\n",
    "    plt.xlabel('Resale Price')\n",
    "    plt.ylabel(features)\n",
    "    plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 500x300 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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mZ2cjNzcXERERSpuHhwdCQ0ORnp4OAEhPT4enpydCQkKUmIiICDg5OSEjI0OJefjhhy2eIBAdHY0DBw7gwoULt1H2iRxDWVkZJk2ahMcffxyrVq1CaGgoXF1dERoailWrVuHxxx/H5MmTefqUqBJW3Yd45MgRLF68GBMnTsTLL7+MnTt3Yty4cdBoNBg8eDByc3MBAL6+vhbv8/X1Vfpyc3Ph4+NjmUStWqhbt65FTFBQUIUxyvuuPUVbzmg0wmg0Kq8NBgOAK/dhmUwma3aT6J6VmpqKo0eP4ssvv0RZWZnyvV/+3ylTpuDhhx/G5s2bER4ebstUiaqFNb//rSqIZrMZISEhePvttwEADzzwAPbs2YMlS5Zg8ODB1mV5l82ePbvSZ8Rt2LABOp3OBhkRVb8tW7YAAP766y+cO3dOaU9OTgYAFBcXAwDWrVuHS5cuVX+CRNWsqKioyrFWFUR/f3+0bNnSou2+++7DihUrAAB+fn4AgLy8PPj7+ysxeXl5aNeunRJz+vRpizFKS0tx/vx55f1+fn7Iy8uziCl/XR5zvWnTpmHixInK6/LleqKiorhSDTmM2rVr47333kPDhg0RGhoKk8mE5ORkREZGQq1WY/v27QCAHj168AiRHEL52cKqsKogdu7cGQcOHLBo+/PPP9GoUSMAQFBQEPz8/LBx40alABoMBmRkZGD06NEAgLCwMOTn5yMzMxMdOnQAAGzatAlmsxmhoaFKzCuvvAKTyaQsN5WcnIzg4OBKT5cCgFarhVarrdCuVqu5ZBU5jG7duqFx48aYO3cuVq1apbSr1Wo4Oztj3rx5CAoKQrdu3eDs7Gy7RImqiVW//62ZrbNjxw6pVauWzJo1Sw4ePCjLli0TnU4n//vf/5SYOXPmiKenp3z//ffy+++/S+/evSUoKEiKi4uVmMcee0weeOABycjIkJ9//lmaN28u/fv3V/rz8/PF19dXnn32WdmzZ498/fXXotPp5KOPPqpyrpxlSo7q2lmmW7ZskeXLl8uWLVs4y5QckjW1wKqCKCKyevVqad26tWi1WmnRooUsXbrUot9sNstrr70mvr6+otVqpXv37nLgwAGLmHPnzkn//v3Fzc1N9Hq9DB06VAoLCy1ifvvtN+nSpYtotVpp0KCBzJkzx6o8WRDJka1YsUIaN24sAJSvoKAgFkNyONbUApWIyN9wlGpzBoMBHh4eKCgo4DVEckhlZWXYvHkz1q1bhx49evA0KTkka2qB3T7+icjROTs7Izw8HJcuXUJ4eDiLIdEtcHFvIiIisCASEREBYEEkIiICwIJIREQEgAWRiIgIAAsiERERABZEIrtVXFyMcePGYcaMGRg3bpyysDcRVY435hPZodjYWHz//fcV2nv37m2xximRvbOmFvAIkcjOlBdDjUaDuLg4LF68GHFxcdBoNPj+++8RGxtr6xSJaiQeIRLZkeLiYuh0Omg0GhQWFkKlUiEpKQk9e/aEiMDd3R0lJSUoKiqCq6urrdMl+tvxCJHIQU2ZMgUAMHHiRGg0Gos+jUaD8ePHW8QR0VUsiER25ODBgwCAESNGVNo/fPhwizgiuooFkciONG/eHADw3//+t9L+Tz75xCKOiK7iNUQiO8JriESWeA2RyEG5urqid+/eKCkpgbu7O15++WWcOHECL7/8slIMe/fuzWJIVAkeIRLZId6HSHQFjxCJHNyqVatQVFSEUaNGoV27dhg1ahSKiopYDIluopatEyCiv4erqysWLlyoXENUq9W2TomoRuMRIhEREVgQiYiIALAgEhERAWBBJCIiAsCCSEREBMDKgjhjxgyoVCqLrxYtWij9ly9fxpgxY+Dl5QU3Nzf07dsXeXl5FmPk5OQgJiYGOp0OPj4+mDJlCkpLSy1iUlJS0L59e2i1WjRr1gzx8fG3v4dEDurixYvo27cvXnzxRfTt2xcXL160dUpENZrVt120atUKP/3009UBal0dYsKECVi7di0SEhLg4eGBF154AX369MHWrVsBAGVlZYiJiYGfnx+2bduGU6dOYdCgQVCr1Xj77bcBANnZ2YiJicGoUaOwbNkybNy4ESNGjIC/vz+io6PvdH+JHEKnTp2wc+dO5fWxY8fg7u6Ojh07YseOHTbMjKgGEyu8/vrrcv/991fal5+fL2q1WhISEpS2/fv3CwBJT08XEZGkpCRxcnKS3NxcJWbx4sWi1+vFaDSKiEhcXJy0atXKYux+/fpJdHS0NalKQUGBAJCCggKr3kd0r+vYsaMAuOFXx44dbZ0iUbWxphZYfQ3x4MGDqF+/Ppo0aYKBAwciJycHAJCZmQmTyYSIiAgltkWLFggMDER6ejoAID09HW3atIGvr68SEx0dDYPBgL179yox145RHlM+BhHd2MWLF5Ujwx49eiAtLQ3Lly9HWloaevToAQDYuXMnT58SVcKqU6ahoaGIj49HcHAwTp06hZkzZ6Jr167Ys2cPcnNzodFo4OnpafEeX19f5ObmAgByc3MtimF5f3nfzWIMBgOKi4tvuCix0WiE0WhUXhsMBgCAyWSCyWSyZjeJ7lkDBgwAADRo0AArV65EWVkZzp07h/bt22PlypVo0qQJTp48iQEDBmDFihU2zpbo72fN73+rCmL5X5gA0LZtW4SGhqJRo0b49ttvbb56/uzZszFz5swK7Rs2bIBOp7NBRkTVLyMjAwDw5JNPYv369Up7cnIyAKBv3754//33kZGRgaSkJJvkSFSdioqKqhx7R2uZenp64h//+AcOHTqEyMhIlJSUID8/3+IoMS8vD35+fgAAPz+/Chf0y2ehXhtz/czUvLw86PX6mxbdadOmYeLEicprg8GAgIAAREVF8WkX5DAaNmyI06dPIzc3FxEREfjwww+RmpqK8PBwjBkzBsuWLVPievbsaeNsif5+5WcLq+ROLlYWFhZKnTp1ZMGCBcqkmsTERKX/jz/+qHRSTV5enhLz0UcfiV6vl8uXL4vIlUk1rVu3tthO//79OamGqApWr16tTJ5xdna2mExz7evVq1fbOlWiamFNLbCqIE6aNElSUlIkOztbtm7dKhEREVKvXj05ffq0iIiMGjVKAgMDZdOmTbJr1y4JCwuTsLAw5f2lpaXSunVriYqKkqysLFm/fr14e3vLtGnTlJgjR46ITqeTKVOmyP79++XDDz8UZ2dnWb9+vTWpsiCSQyotLRUnJyel8HXq1Elef/116dSpk9Lm5OQkpaWltk6VqFr8bQWxX79+4u/vLxqNRho0aCD9+vWTQ4cOKf3FxcXy/PPPS506dUSn08kTTzwhp06dshjj6NGj0qNHD3F1dZV69erJpEmTxGQyWcRs3rxZ2rVrJxqNRpo0aSKfffaZNWmKCAsiOSaj0WhRECv7cnJyUm5zIrJ31tQClYjIHZ+krYGseUoykb2YP38+JkyYgNGjR2P16tX466+/lL6AgADExMRgyZIl+M9//oPx48fbLlGiamJNLeBapkR25PDhwwCA6dOn4/Dhw3jnnXfQs2dPvPPOOzh06BBee+01izgiuuqOZpkSUc3StGlTAMAbb7yBdevW4ejRowCApKQkfPDBB3jssccs4ojoKp4yJbIjJSUlcHV1hdlsRkxMDF566SX89ddfaNiwIebMmYO1a9fCyckJxcXF0Gg0tk6X6G/HU6ZEDsrZ2Rlubm4AgF27dmH37t0oLi7G7t27sWvXLgCAm5sbnJ2dbZkmUY3EU6ZEdiQtLQ0GgwEDBw7EN998g+eff17pq1WrFgYMGICvvvoKaWlpeOSRR2yXKFENxCNEIjty6tQpAMCSJUtw6dIli0k1ly5dwpIlSyziiOgqHiES2RF/f38AwJ49e/Dggw9i3LhxaNasGXr27Am1Wo3MzEyLOCK6ikeIRHaka9euaNy4Md5++22YzWaLPrPZjNmzZyMoKAhdu3a1UYZENRcLIpEdcXZ2xrvvvos1a9YgNjYW27dvR3FxMbZv347Y2FisWbMG77zzDifVEFWCp0yJ7EyfPn2QmJiISZMm4eGHH1bag4KCkJiYiD59+tgwO6Kai/chEtmpkpISvP/++9i0aRMeffRRjB07lvceksPhfYhEDu67775D8+bNMXnyZCQlJWHy5Mlo3rw5vvvuO1unRlRjsSAS2ZnvvvsOffv2RU5OjkV7Tk4O+vbty6JIdAM8ZUpkR8rKyuDu7q4szTZ+/HgEBQUhOzsb8+fPV5Z2Kyws5MQacgg8ZUrkoDZs2IDi4mKo1WoUFhbirbfegr+/P9566y0UFhZCrVajuLgYGzZssHWqRDUOCyKRHXnvvfcAoNIJNBqNBmPGjLGII6KrWBCJ7Eh+fj4AICwsrNL+0NBQizgiuooFkciOhISEAABeeumlSleqefXVVy3iiOgqFkQiO1J+KvTw4cPo1auXxUo1vXr1wuHDhy3iiOgqrlRDZEdcXV3Ru3dvfP/990hKSkJSUlKFmN69e8PV1dUG2RHVbLztgsgOeXp6oqCgoEK7h4cHrx+SQ+FtF0QOrFOnTigoKIBKpULz5s3xj3/8A82bN4dKpUJBQQE6depk6xSJaiSeMiWyIxcvXsTOnTuhUqlQVFQEZ2dnJCUloWfPnigrK4NOp8POnTtx8eJFuLm52TpdohqFR4hEduTZZ58FADzzzDNwcXGx6HNxccGAAQMs4ojoqjsqiHPmzIFKpcL48eOVtsuXL2PMmDHw8vKCm5sb+vbti7y8PIv35eTkICYmBjqdDj4+PpgyZQpKS0stYlJSUtC+fXtotVo0a9YM8fHxd5IqkUMon0U6efLkSvsnTpxoEUdEV912Qdy5cyc++ugjtG3b1qJ9woQJWL16NRISEpCamoqTJ09aPH+trKwMMTExKCkpwbZt2/D5558jPj4e06dPV2Kys7MRExODbt26ISsrC+PHj8eIESPw448/3m66RA6hadOmAIB33nmn0v7y2y3K44joGnIbCgsLpXnz5pKcnCzh4eHy4osviohIfn6+qNVqSUhIUGL3798vACQ9PV1ERJKSksTJyUlyc3OVmMWLF4terxej0SgiInFxcdKqVSuLbfbr10+io6OrnGNBQYEAkIKCgtvZRaJ7UmFhoQAQlUolxcXFUlJSIqtWrZKSkhIpLi4WlUolAKSwsNDWqRJVC2tqwW0dIY4ZMwYxMTGIiIiwaM/MzITJZLJob9GiBQIDA5Geng4ASE9PR5s2beDr66vEREdHw2AwYO/evUrM9WNHR0crYxBR5dzc3NCxY0eICHQ6HYYMGYLDhw9jyJAh0Ol0EBF07NiRE2qIKmH1LNOvv/4av/zyC3bu3FmhLzc3FxqNBp6enhbtvr6+yM3NVWKuLYbl/eV9N4sxGAwoLi6u9KZio9EIo9GovDYYDAAAk8kEk8lk5V4S3bu2bt2Khx56CLt27cJXX32Fr776SukLCQnB1q1b+TNBDsOa73WrCuLx48fx4osvIjk5ucIMNlubPXs2Zs6cWaF9w4YN0Ol0NsiIyHZeffVVFBUVYf78+cjLy4Ovry/Gjx8PnU5X6eo1RPaqqKioyrFWFcTMzEycPn0a7du3V9rKysqwZcsWfPDBB/jxxx9RUlKC/Px8i6PEvLw8+Pn5AQD8/PywY8cOi3HLZ6FeG3P9zNS8vDzo9fobLjk1bdo0ZQYdcOUIMSAgAFFRUVyphhxW7969kZycjMjISKjValunQ1Ttys8WVoVVBbF79+7YvXu3RdvQoUPRokULTJ06FQEBAVCr1di4cSP69u0LADhw4ABycnKUx9GEhYVh1qxZOH36NHx8fAAAycnJ0Ov1aNmypRJz/V+xycnJN3ykDQBotVpotdoK7Wq1mr8IyOHx54AclTXf91YVRHd3d7Ru3dqirXbt2vDy8lLahw8fjokTJ6Ju3brQ6/UYO3YswsLC8OCDDwIAoqKi0LJlSzz77LOYO3cucnNz8eqrr2LMmDFKQRs1ahQ++OADxMXFYdiwYdi0aRO+/fZbrF271pp0iYiIquyuL932n//8B05OTujbty+MRiOio6OxaNEipd/Z2Rlr1qzB6NGjERYWhtq1a2Pw4MF44403lJigoCCsXbsWEyZMwIIFC9CwYUP897//RXR09N1Ol4iICACfdkFk10wmk7KWKU+ZkiPi0y6IiIisxIJIREQEPv6JyG6VlJTg/fffx6ZNm3Do0CGMHTsWGo3G1mkR1Vg8QiSyQ3FxcdDpdJg8eTKSkpIwefJk6HQ6xMXF2To1ohqLBZHIzsTFxWHevHm4fr6ciGDevHksikQ3wFmmRHakpKQErq6uMJvNiImJwUsvvYS//voLDRs2xJw5c7B27Vo4OTmhuLiYp0/JIXCWKZGDev/992E2m9G2bVskJiYiIyMDX375JTIyMpCYmIi2bdvCbDbj/ffft3WqRDUOCyKRHfn5558BXHkAsJubm8U1RDc3N+XBwOVxRHQVCyKRHSl/zuHKlSsrvYa4cuVKizgiuooFkciO9O/fX/n3Y489hrS0NCxfvhxpaWl47LHHKo0joitYEInsyL59+5R/79q1C7t370ZxcTF2796NXbt2VRpHRFfwxnwiO7J161bl32fOnMHzzz+vvFapVBZxkydPrtbciGo6HiES2RF3d3cAVx7DFhgYaNHXqFEjDBs2zCKOiK7iESKRHXn22Wfx5Zdf4rvvvsOpU6eQlpaGdevWoUePHujatSv8/f2VOCKyxCNEIjvy6KOPwsPDAxcuXEBgYCAOHjyI1q1b4+DBgwgMDMSFCxfg4eGBRx991NapEtU4PEIksiPOzs749NNP0bdv3xteQ/z000/h7OxsqxSJaiweIRLZmT59+mDFihWVXkNcsWIF+vTpY6PMiGo2HiES2aE+ffrAbDbjqaeeUtrmzZvHYkh0EyyIRHbo2lssypUXRztdz5/ojvGUKZGdub4YtmjR4qb9RHQFCyKRHSlfqxQAMjIyUFJSgjlz5qCkpAQZGRmVxhHRFSyIRHbk2muEnTp1sui79jWvJRJVxIJIZIe6du1aaXtoaGg1Z0J072BBJLJDaWlplbZfe9qUiCxZVRAXL16Mtm3bQq/XQ6/XIywsDOvWrVP6L1++jDFjxsDLywtubm7o27cv8vLyLMbIyclBTEwMdDodfHx8MGXKFJSWllrEpKSkoH379tBqtWjWrBni4+Nvfw+JHMh3332n/FulUkGj0SA2NhYajcZiMs21cUR0hVUFsWHDhpgzZw4yMzOxa9cuPProo+jduzf27t0LAJgwYQJWr16NhIQEpKam4uTJkxbXKsrKyhATE4OSkhJs27YNn3/+OeLj4zF9+nQlJjs7GzExMejWrRuysrIwfvx4jBgxAj/++ONd2mUi+/XEE0/c1TgihyJ3qE6dOvLf//5X8vPzRa1WS0JCgtK3f/9+ASDp6ekiIpKUlCROTk6Sm5urxCxevFj0er0YjUYREYmLi5NWrVpZbKNfv34SHR1tVV4FBQUCQAoKCm5314juSQBu+UXkKKypBbd9DbGsrAxff/01Ll26hLCwMGRmZsJkMiEiIkKJadGiBQIDA5Geng4ASE9PR5s2beDr66vEREdHw2AwKEeZ6enpFmOUx5SPQUQ3VtV7DHkvIlFFVq9Us3v3boSFheHy5ctwc3PDypUr0bJlS2RlZUGj0cDT09Mi3tfXF7m5uQCA3Nxci2JY3l/ed7MYg8GA4uJiuLq6VpqX0WiE0WhUXhsMBgCAyWSCyWSydjeJ7B5/LsgRWPN9bnVBDA4ORlZWFgoKCpCYmIjBgwcjNTXV2mHuutmzZ2PmzJkV2jds2ACdTmeDjIhsS61WIzg4GCIClUqFAwcOWPxySEpKsmF2RNWjqKioyrFWF0SNRoNmzZoBADp06ICdO3diwYIF6NevH0pKSpCfn29xlJiXlwc/Pz8AgJ+fH3bs2GExXvks1Gtjrp+ZmpeXB71ef8OjQwCYNm0aJk6cqLw2GAwICAhAVFQU9Hq9tbtJdM8zmUzYs2fPDft79uxZjdkQ2Ub52cKquOPFvc1mM4xGIzp06AC1Wo2NGzeib9++AIADBw4gJycHYWFhAICwsDDMmjULp0+fho+PDwAgOTkZer0eLVu2VGKu/8s1OTlZGeNGtFottFpthXa1Wg21Wn2nu0l0T4qLi0NQUBCys7Mxd+5ciz7+XJAjsOr73JrZOi+99JKkpqZKdna2/P777/LSSy+JSqWSDRs2iIjIqFGjJDAwUDZt2iS7du2SsLAwCQsLU95fWloqrVu3lqioKMnKypL169eLt7e3TJs2TYk5cuSI6HQ6mTJliuzfv18+/PBDcXZ2lvXr11uTKmeZkkNCFWaYgjNNyYFYUwus+qkYNmyYNGrUSDQajXh7e0v37t2VYigiUlxcLM8//7zUqVNHdDqdPPHEE3Lq1CmLMY4ePSo9evQQV1dXqVevnkyaNElMJpNFzObNm6Vdu3ai0WikSZMm8tlnn1mTpoiwIJJjCgkJqVIxDAkJsXWqRNXCmlqgErHPh6MZDAZ4eHigoKCA1xDJYURGRuKnn366ZVxERASSk5OrISMi27KmFrAgEtkRa+4vtNMffSIL1tQCLu5NREQEFkQiIiIALIhEREQA7sJ9iERUcwUEBECr1cJoNOL48eO2ToeoRmNBJLJjLIJEVcdTpkR25PrF9e80jsiRsCAS2ZGqLlPFZduIKmJBJLIjVX2yC58AQ1QRCyKRHTl27NhdjSNyJCyIREREYEEkIiICwIJIREQEgAWRiIgIAAsiERERABZEIiIiACyIREREAFgQiYiIALAgEtmVV1999a7GETkSlYiIrZP4OxgMBnh4eKCgoAB6vd7W6RBVi7KyMtSqdeuH2JSWlsLZ2bkaMiKyLWtqAY8QiexIVYqhNXFEjoQFkYiICCyIRHarYcOGKCkpwapVq1BSUoKGDRvaOiWiGo0FkchOXf9ECz7hgujmrCqIs2fPRseOHeHu7g4fHx/ExsbiwIEDFjGXL1/GmDFj4OXlBTc3N/Tt2xd5eXkWMTk5OYiJiYFOp4OPjw+mTJmC0tJSi5iUlBS0b98eWq0WzZo1Q3x8/O3tIZGDcnZ2hkajQWxsLDQaDSfREN2CVQUxNTUVY8aMwfbt25GcnAyTyYSoqChcunRJiZkwYQJWr16NhIQEpKam4uTJk+jTp4/SX1ZWhpiYGJSUlGDbtm34/PPPER8fj+nTpysx2dnZiImJQbdu3ZCVlYXx48djxIgR+PHHH+/CLhMREVVC7sDp06cFgKSmpoqISH5+vqjVaklISFBi9u/fLwAkPT1dRESSkpLEyclJcnNzlZjFixeLXq8Xo9EoIiJxcXHSqlUri23169dPoqOjq5xbQUGBAJCCgoLb3j+iew2AKn8ROQJrasEdXUMsKCgAANStWxcAkJmZCZPJhIiICCWmRYsWCAwMRHp6OgAgPT0dbdq0ga+vrxITHR0Ng8GAvXv3KjHXjlEeUz4GERHR3XbbNyOZzWaMHz8enTt3RuvWrQEAubm50Gg08PT0tIj19fVFbm6uEnNtMSzvL++7WYzBYEBxcTFcXV0r5GM0GmE0GpXXBoMBAGAymWAymW53N4nsFn8uyBFY831+2wVxzJgx2LNnD37++efbHeKumj17NmbOnFmhfcOGDdDpdDbIiKhmS0pKsnUKRH+7oqKiKsfeVkF84YUXsGbNGmzZssXi3iY/Pz+UlJQgPz/f4igxLy8Pfn5+SsyOHTssxiufhXptzPUzU/Py8qDX6ys9OgSAadOmYeLEicprg8GAgIAAREVFcek2ckglJSUwmUxITk5GZGQk1Go1NBqN0t+zZ08bZkdUPcrPFlaFVQVRRDB27FisXLkSKSkpCAoKsujv0KED1Go1Nm7ciL59+wIADhw4gJycHISFhQEAwsLCMGvWLJw+fRo+Pj4AgOTkZOj1erRs2VKJuf6v1+TkZGWMymi1Wmi12grtarUaarXamt0kqlGKiorwxx9/WP0+jUaD1J+3Ydvuw6hTzwfhXR6y6N+9e/ctx2jRogXPsNA9zarf/9bM1hk9erR4eHhISkqKnDp1SvkqKipSYkaNGiWBgYGyadMm2bVrl4SFhUlYWJjSX1paKq1bt5aoqCjJysqS9evXi7e3t0ybNk2JOXLkiOh0OpkyZYrs379fPvzwQ3F2dpb169dXOVfOMiV7kZmZadXs0bv5lZmZaevdJ7oj1tQCq552oVKpKm3/7LPPMGTIEABXbsyfNGkSli9fDqPRiOjoaCxatEg5HQpcWTFj9OjRSElJQe3atTF48GDMmTPHYsHhlJQUTJgwAfv27UPDhg3x2muvKduoCj7tguyFtUeIHTp0uGVMZmZmlcbiESLd66ypBXz8E5EdutEfr8CVSx9EjoKPfyJycDcqeiyGRDfGgkhkp0QEvx49i0ZT1+DXo2dZDIlugQWRiIgILIhEREQAWBCJiIgAsCASEREBYEEkIiICwIJIREQEgAWRiIgIAAsiERERgDt4HiIRWS/77CVcMpZW2/YOn7mk/PfatYL/brW1tRBUr3a1bY/obmBBJKom2Wcvods7KTbZ9qTEWz/q6W7bPPkRFkW6p7AgElWT8iPD+f3aoZmPW/Vss9iINSnpePyRMNR2rfi80L/DodMXMf6brGo9Eia6G1gQiapZMx83tG7gUS3bMplMyPUG2jeqwwdlE90CJ9UQERGBBZGIiAgACyIREREAFkQiIiIALIhEREQAOMuUqFqpahmQbTgAJ5fque2itLQUJ0tPYv/5/dV2Y3624SJUtQzVsi2iu4kFkagaqT0z8PKOt6t9u4vWL6rW7ak9uwPoWa3bJLpTLIhE1aTYVAZTfihGd/y/arsxv9hYgrRdu9E1pA1ctZpq2ebx80WYd/BUtWyL6G5iQSSqJodPX4SU6rFgXTGA4mrcciBWHyqoxu0BgB61tfz1QvcWfscSVZOoVn4AgKY+bnBVO1fLNg+cKsCkxN1498k2CPavntVxAC7uTfcosVJqaqo8/vjj4u/vLwBk5cqVFv1ms1lee+018fPzExcXF+nevbv8+eefFjHnzp2TAQMGiLu7u3h4eMiwYcOksLDQIua3336TLl26iFarlYYNG8q///1vq/IsKCgQAFJQUGDtLhLZjV+PnpVGU9fIr0fP2joVIpuwphZYfdvFpUuXcP/99+PDDz+stH/u3LlYuHAhlixZgoyMDNSuXRvR0dG4fPmyEjNw4EDs3bsXycnJWLNmDbZs2YLnnntO6TcYDIiKikKjRo2QmZmJefPmYcaMGVi6dKm16RIREVXNnVReXHeEaDabxc/PT+bNm6e05efni1arleXLl4uIyL59+wSA7Ny5U4lZt26dqFQqOXHihIiILFq0SOrUqSNGo1GJmTp1qgQHB1c5Nx4hEvEIkehvPUK8mezsbOTm5iIiIkJp8/DwQGhoKNLT0wEA6enp8PT0REhIiBITEREBJycnZGRkKDEPP/wwNJqrs+Kio6Nx4MABXLhw4W6mTEREBOAuT6rJzc0FAPj6+lq0+/r6Kn25ubnw8fGxTKJWLdStW9ciJigoqMIY5X116tSpsG2j0Qij0ai8Nhiu3BhsMplgMpnuZLeI7lmlpaXKf/lzQI7Imu97u5llOnv2bMycObNC+4YNG6DT6WyQEZHtHb8IALWwfft2nNhj62yIql9RUVGVY+9qQfTzuzKtPC8vD/7+/kp7Xl4e2rVrp8ScPn3a4n2lpaU4f/688n4/Pz/k5eVZxJS/Lo+53rRp0zBx4kTltcFgQEBAAKKioqDX6+9sx4juUb/lnAd278KDDz6I+wPr2jodompXfrawKu5qQQwKCoKfnx82btyoFECDwYCMjAyMHj0aABAWFob8/HxkZmaiQ4cOAIBNmzbBbDYjNDRUiXnllVdgMpmUp3wnJycjODi40tOlAKDVaqHVaiu0q9VqPimcHFb5+qW1atXizwE5JGu+762eVHPx4kVkZWUhKysLwJWJNFlZWcjJyYFKpcL48ePx1ltv4YcffsDu3bsxaNAg1K9fH7GxsQCA++67D4899hhGjhyJHTt2YOvWrXjhhRfwz3/+E/Xr1wcADBgwABqNBsOHD8fevXvxzTffYMGCBRZHgERERHeVtVNYN2/eLAAqfA0ePFhErt6Y7+vrK1qtVrp37y4HDhywGOPcuXPSv39/cXNzE71eL0OHDr3pjfkNGjSQOXPmWJUnb7sg4m0XRNbUApWIiA3r8d/GYDDAw8MDBQUFvIZIDivr2DnELt6OVaMfRLtGXrZOh6jaWVML7GaWKZG9Kioqwh9//HFb7z1wKh/G3EPYv8cV5nOeVr+/RYsWnKVNDoMFkaiG++OPP5QJaLdrwOe3977MzEy0b9/+jrZNdK9gQSSq4Vq0aIHMzEyr35eYmIjZs2crr6dNm4Ynn3zS6m0TOQpeQySyQyqV6oZ9dvojT1Qpa2rBXV3LlIhs7/pieP1SiTcrlkSOjAWRyI58/PHHyr/XrVuHkpISLF26FCUlJVi3bl2lcUR0BU+ZEtmRa4/+RAQmkwlJSUno2bMn1Gp1hX4ie8dTpkQOrlmzZpW2N2rUqJozIbp3sCAS2aFDhw5V2n7s2LFqzoTo3sGCSGRHli5dqvx7/fr1Fn3Xvr42joiu4DVEIjtz/SzSunXr4vz58xZtdvpjT1QBryESObDrix2LIVHVsCAS2SERqXBadOnSpSyGRDfBU6ZEduz62y6IHA1PmRIREVmJBZGIiAgsiERERABYEImIiACwIBIREQFgQSQiIgLAgkhERASABZHIbhUXF2PcuHGYMWMGxo0bh+LiYlunRFSj8cZ8IjsUGxuL77//vkJ77969sWrVqupPiMhGeGM+kQMrL4YajQZxcXFYvHgx4uLioNFo8P333yM2NtbWKRLVSDW6IH744Ydo3LgxXFxcEBoaih07dtg6JaIarbi4WCmG+fn5iIyMxMGDBxEZGYn8/HylKPL0KVFFNbYgfvPNN5g4cSJef/11/PLLL7j//vsRHR2N06dP2zo1ohprypQpAICYmBi0bNkSkZGReO+99xAZGYmWLVuiZ8+eFnFEdFWNLYjvvfceRo4ciaFDh6Jly5ZYsmQJdDodPv30U1unRlRjHTx4EACwcuVKtGnTBmlpaVi+fDnS0tLQpk0b5fpheRwRXVUjC2JJSQkyMzMRERGhtDk5OSEiIgLp6ek2zIyoZmvSpAkAoGnTpli1ahVCQ0Ph6uqK0NBQrFq1Sukv/y8RXVXL1glU5uzZsygrK4Ovr69Fu6+vL/74449K32M0GmE0GpXXBoMBwJXH35hMpr8vWaIapGfPnliyZAlycnJQXFwMlUoF4MrPQUlJCY4fP67E8eeCHIE13+c1siDejtmzZ2PmzJkV2jds2ACdTmeDjIiq35YtWwBc+SXg6emJXr16ISIiAs888wxWr16N0tJSAEBKSgrMZrMtUyWqFkVFRVWOrZH3IZaUlECn0yExMdFiivjgwYORn59f6f1VlR0hBgQE4OzZs7wPkRxGamoqIiMj0aVLF/z8888V+jt37oytW7ciOTkZ4eHhNsiQqHoZDAbUq1evSvch1sgjRI1Ggw4dOmDjxo1KQTSbzdi4cSNeeOGFSt+j1Wqh1WortKvVaj4pnBxGt27d0LhxY9SpUwcXL17E5MmTsX37djz44IN455130L9/fwQFBaFbt25wdna2dbpEfztrfv/XyIIIABMnTsTgwYMREhKCTp06Yf78+bh06RKGDh1q69SIaixnZ2e8++67ePLJJ9G/f39MmTIF4eHhaNCgAfr37481a9YgMTGRxZCoEjW2IPbr1w9nzpzB9OnTkZubi3bt2mH9+vUVJtoQkaU+ffogMTERkyZNwsMPP6y0BwUFITExEX369LFhdkQ1V428hng3cC1TcnRlZWXYvHkz1q1bhx49evA0KTkka2pBjT1CJKI74+zsjPDwcFy6dAnh4eEshkS3UCNvzCciIqpuLIhERESw41Om5ZdGy1esIXJEJpMJRUVFMBgMvP2IHFJ5DajKdBm7LYiFhYUAgICAABtnQkREtlZYWAgPD4+bxtjtLFOz2YyTJ0/C3d1dWc+RyNGUr9h0/PhxzrYmhyQiKCwsRP369eHkdPOrhHZbEImItx8RWYOTaoiIiMCCSEREBIAFkciuabVavP7665UufE9ElngNkYiICDxCJCIiAsCCSEREBIAFkYiICAALIlG1GTJkCGJjY22dRo1y9OhRqFQqZGVl2ToVIk6qIaouBQUFEBF4enraOpUao6ysDGfOnEG9evVQq1YtpKSkoFu3brhw4QI/J6p2druWKVFNc6t1FB2Rs7Mz/Pz8bJ0GEQCeMiUCcGXt29mzZyMoKAiurq64//77kZiYCABISUmBSqXCxo0bERISAp1Oh4ceeggHDhywGOOtt96Cj48P3N3dMWLECLz00kto166d0n/9KdNHHnkE48aNQ1xcHOrWrQs/Pz/MmDHDYsz8/HyMGDEC3t7e0Ov1ePTRR/Hbb79Veb9Wr16Njh07wsXFBfXq1cMTTzyh9H355ZcICQmBu7s7/Pz8MGDAAJw+fVrpL9/vtWvXom3btnBxccGDDz6IPXv2KDHnzp1D//790aBBA+h0OrRp0wbLly+v8NnOnTsXzZo1g1arRWBgIGbNmgXA8pTp0aNH0a1bNwBAnTp1oFKpMGTIEHzxxRfw8vKC0Wi0GDc2NhbPPvtslT8LolsSIpK33npLWrRoIevXr5fDhw/LZ599JlqtVlJSUmTz5s0CQEJDQyUlJUX27t0rXbt2lYceekh5///+9z9xcXGRTz/9VA4cOCAzZ84UvV4v999/vxIzePBg6d27t/I6PDxc9Hq9zJgxQ/7880/5/PPPRaVSyYYNG5SYiIgI6dWrl+zcuVP+/PNPmTRpknh5ecm5c+duuU9r1qwRZ2dnmT59uuzbt0+ysrLk7bffVvo/+eQTSUpKksOHD0t6erqEhYVJjx49lP7y/b7vvvtkw4YN8vvvv8vjjz8ujRs3lpKSEhER+euvv2TevHny66+/yuHDh2XhwoXi7OwsGRkZyjhxcXFSp04diY+Pl0OHDklaWpp8/PHHIiKSnZ0tAOTXX3+V0tJSWbFihQCQAwcOyKlTpyQ/P1+KiorEw8NDvv32W2XMvLw8qVWrlmzatKkK/3eJqoYFkRze5cuXRafTybZt2yzahw8fLv3791cKw08//aT0rV27VgBIcXGxiIiEhobKmDFjLN7fuXPnWxbELl26WLynY8eOMnXqVBERSUtLE71eL5cvX7aIadq0qXz00Ue33K+wsDAZOHDgLePK7dy5UwBIYWGhiFwtiF9//bUSc+7cOXF1dZVvvvnmhuPExMTIpEmTRETEYDCIVqtVCuD1ri2I127zwoULFnGjR4+2KNbvvvuuNGnSRMxmc5X3j+hWeMqUHN6hQ4dQVFSEyMhIuLm5KV9ffPEFDh8+rMS1bdtW+be/vz8AKKcYDxw4gE6dOlmMe/3rylw7Zvm45WP+9ttvuHjxIry8vCzyys7OtsjrRrKystC9e/cb9mdmZqJXr14IDAyEu7s7wsPDAQA5OTkWcWFhYcq/69ati+DgYOzfvx/AlUkxb775Jtq0aYO6devCzc0NP/74ozLG/v37YTQab5pHVYwcORIbNmzAiRMnAADx8fEYMmQIH+1GdxUn1ZDDu3jxIgBg7dq1aNCggUWfVqtVis+1T5wv/0VsNpvvaNvXP8VepVIpY168eBH+/v5ISUmp8L6qzMB0dXW9Yd+lS5cQHR2N6OhoLFu2DN7e3sjJyUF0dDRKSkqqnP+8efOwYMECzJ8/H23atEHt2rUxfvx4ZYyb5WCNBx54APfffz+++OILREVFYe/evVi7du1dGZuoHAsiObyWLVtCq9UiJydHOUq6VlWOxoKDg7Fz504MGjRIadu5c+cd5dW+fXvk5uaiVq1aaNy4sdXvb9u2LTZu3IihQ4dW6Pvjjz9w7tw5zJkzBwEBAQCAXbt2VTrO9u3bERgYCAC4cOEC/vzzT9x3330AgK1bt6J379545plnAFz5A+HPP/9Ey5YtAQDNmzeHq6srNm7ciBEjRtwyZ41GA+DKkef1RowYgfnz5+PEiROIiIhQ8ia6W1gQyeG5u7tj8uTJmDBhAsxmM7p06YKCggJs3boVer0ejRo1uuUYY8eOxciRIxESEoKHHnoI33zzDX7//Xc0adLktvOKiIhAWFgYYmNjMXfuXPzjH//AyZMnsXbtWjzxxBMICQm56ftff/11dO/eHU2bNsU///lPlJaWIikpCVOnTkVgYCA0Gg3ef/99jBo1Cnv27MGbb75Z6ThvvPEGvLy84Ovri1deeQX16tVTZss2b94ciYmJ2LZtG+rUqYP33nsPeXl5SkF0cXHB1KlTERcXB41Gg86dO+PMmTPYu3cvhg8fXmFbjRo1gkqlwpo1a9CzZ0+4urrCzc0NADBgwABMnjwZH3/8Mb744ovb/lyJbsjWFzGJagKz2Szz58+X4OBgUavV4u3tLdHR0ZKamlrpRI9ff/1VAEh2drbS9sYbb0i9evXEzc1Nhg0bJuPGjZMHH3xQ6a9sUs2LL75okUfv3r1l8ODBymuDwSBjx46V+vXri1qtloCAABk4cKDk5ORUab9WrFgh7dq1E41GI/Xq1ZM+ffoofV999ZU0btxYtFqthIWFyQ8//FDpBJfVq1dLq1atRKPRSKdOneS3335Txjh37pz07t1b3NzcxMfHR1599VUZNGiQxX6WlZXJW2+9JY0aNRK1Wi2BgYHKbNfrJ9WUf45+fn6iUqksPgsRkWeffVbq1q1bYaIR0d3AlWqI/iaRkZHw8/PDl19+aetUbktNXDWme/fuaNWqFRYuXGjrVMgO8ZQp0V1QVFSEJUuWIDo6Gs7Ozli+fDl++uknJCcn2zo1u3DhwgWkpKQgJSUFixYtsnU6ZKdYEInuApVKhaSkJMyaNQuXL19GcHAwVqxYgYiIiL9tm61atcKxY8cq7fvoo48wcODAv23b1e2BBx7AhQsX8O9//xvBwcG2TofsFE+ZEt2jjh07BpPJVGmfr68v3N3dqzkjonsbCyIRERG4uDcREREAFkQiIiIALIhEREQAWBCJiIgAsCASEREBYEEkIiICwIJIREQEgAWRiIgIAPD/AJNjBkifIZqzAAAAAElFTkSuQmCC",
      "text/plain": [
       "<Figure size 500x300 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 500x300 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 500x300 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 500x300 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 500x300 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Ouliers Visualization\n",
    "for feature in numerical:\n",
    "    if feature != 'resale_price':\n",
    "        plt.figure(figsize=(5,3))\n",
    "        df.boxplot(column=feature)\n",
    "        # plt.ylabel(feature)\n",
    "        plt.title(feature)\n",
    "        plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Applying One-Hot-Encoding"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(15814, 78)"
      ]
     },
     "execution_count": 27,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df=pd.get_dummies(df,columns=categorical,dtype=int)\n",
    "df.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "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>resale_price</th>\n",
       "      <th>registered_year</th>\n",
       "      <th>engine_capacity</th>\n",
       "      <th>kms_driven</th>\n",
       "      <th>max_power</th>\n",
       "      <th>seats</th>\n",
       "      <th>mileage</th>\n",
       "      <th>insurance_Comprehensive</th>\n",
       "      <th>insurance_Third Party</th>\n",
       "      <th>insurance_Zero Dep</th>\n",
       "      <th>...</th>\n",
       "      <th>Company_Mitsubishi</th>\n",
       "      <th>Company_Nissan</th>\n",
       "      <th>Company_OpelCorsa</th>\n",
       "      <th>Company_Porsche</th>\n",
       "      <th>Company_Renault</th>\n",
       "      <th>Company_Skoda</th>\n",
       "      <th>Company_Tata</th>\n",
       "      <th>Company_Toyota</th>\n",
       "      <th>Company_Volkswagen</th>\n",
       "      <th>Company_Volvo</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>3814</th>\n",
       "      <td>391000.0</td>\n",
       "      <td>2014</td>\n",
       "      <td>1198.0</td>\n",
       "      <td>75029.0</td>\n",
       "      <td>86.80</td>\n",
       "      <td>5.0</td>\n",
       "      <td>19.40</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16276</th>\n",
       "      <td>330000.0</td>\n",
       "      <td>2012</td>\n",
       "      <td>1248.0</td>\n",
       "      <td>41000.0</td>\n",
       "      <td>75.00</td>\n",
       "      <td>5.0</td>\n",
       "      <td>20.30</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12834</th>\n",
       "      <td>581000.0</td>\n",
       "      <td>2018</td>\n",
       "      <td>1197.0</td>\n",
       "      <td>26000.0</td>\n",
       "      <td>81.80</td>\n",
       "      <td>5.0</td>\n",
       "      <td>21.21</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3808</th>\n",
       "      <td>354000.0</td>\n",
       "      <td>2014</td>\n",
       "      <td>998.0</td>\n",
       "      <td>66783.0</td>\n",
       "      <td>67.04</td>\n",
       "      <td>5.0</td>\n",
       "      <td>20.51</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6769</th>\n",
       "      <td>1365000.0</td>\n",
       "      <td>2019</td>\n",
       "      <td>1999.0</td>\n",
       "      <td>64882.0</td>\n",
       "      <td>149.92</td>\n",
       "      <td>5.0</td>\n",
       "      <td>14.62</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 78 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "       resale_price  registered_year  engine_capacity  kms_driven  max_power  \\\n",
       "3814       391000.0             2014           1198.0     75029.0      86.80   \n",
       "16276      330000.0             2012           1248.0     41000.0      75.00   \n",
       "12834      581000.0             2018           1197.0     26000.0      81.80   \n",
       "3808       354000.0             2014            998.0     66783.0      67.04   \n",
       "6769      1365000.0             2019           1999.0     64882.0     149.92   \n",
       "\n",
       "       seats  mileage  insurance_Comprehensive  insurance_Third Party  \\\n",
       "3814     5.0    19.40                        0                      1   \n",
       "16276    5.0    20.30                        1                      0   \n",
       "12834    5.0    21.21                        0                      1   \n",
       "3808     5.0    20.51                        1                      0   \n",
       "6769     5.0    14.62                        1                      0   \n",
       "\n",
       "       insurance_Zero Dep  ...  Company_Mitsubishi  Company_Nissan  \\\n",
       "3814                    0  ...                   0               0   \n",
       "16276                   0  ...                   0               0   \n",
       "12834                   0  ...                   0               0   \n",
       "3808                    0  ...                   0               0   \n",
       "6769                    0  ...                   0               0   \n",
       "\n",
       "       Company_OpelCorsa  Company_Porsche  Company_Renault  Company_Skoda  \\\n",
       "3814                   0                0                0              0   \n",
       "16276                  0                0                0              0   \n",
       "12834                  0                0                0              0   \n",
       "3808                   0                0                0              0   \n",
       "6769                   0                0                0              0   \n",
       "\n",
       "       Company_Tata  Company_Toyota  Company_Volkswagen  Company_Volvo  \n",
       "3814              0               0                   0              0  \n",
       "16276             0               0                   0              0  \n",
       "12834             0               0                   0              0  \n",
       "3808              0               0                   0              0  \n",
       "6769              0               0                   0              0  \n",
       "\n",
       "[5 rows x 78 columns]"
      ]
     },
     "execution_count": 28,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.sample(5)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Spliting the Data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {},
   "outputs": [],
   "source": [
    "X = df.drop('resale_price',axis=1)\n",
    "Y = df['resale_price']\n",
    "\n",
    "X_train,X_test,Y_train,Y_test = train_test_split(X, Y, test_size = 0.2, random_state = 100)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "X_train: (12651, 77)\n",
      "X_test: (3163, 77)\n",
      "Y_train: (12651,)\n",
      "Y_test: (3163,)\n"
     ]
    }
   ],
   "source": [
    "print(\"X_train:\", X_train.shape)\n",
    "print(\"X_test:\",X_test.shape)\n",
    "print(\"Y_train:\",Y_train.shape) \n",
    "print(\"Y_test:\",Y_test.shape)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Training Models"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Linear Regression"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<style>#sk-container-id-1 {\n",
       "  /* Definition of color scheme common for light and dark mode */\n",
       "  --sklearn-color-text: black;\n",
       "  --sklearn-color-line: gray;\n",
       "  /* Definition of color scheme for unfitted estimators */\n",
       "  --sklearn-color-unfitted-level-0: #fff5e6;\n",
       "  --sklearn-color-unfitted-level-1: #f6e4d2;\n",
       "  --sklearn-color-unfitted-level-2: #ffe0b3;\n",
       "  --sklearn-color-unfitted-level-3: chocolate;\n",
       "  /* Definition of color scheme for fitted estimators */\n",
       "  --sklearn-color-fitted-level-0: #f0f8ff;\n",
       "  --sklearn-color-fitted-level-1: #d4ebff;\n",
       "  --sklearn-color-fitted-level-2: #b3dbfd;\n",
       "  --sklearn-color-fitted-level-3: cornflowerblue;\n",
       "\n",
       "  /* Specific color for light theme */\n",
       "  --sklearn-color-text-on-default-background: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, black)));\n",
       "  --sklearn-color-background: var(--sg-background-color, var(--theme-background, var(--jp-layout-color0, white)));\n",
       "  --sklearn-color-border-box: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, black)));\n",
       "  --sklearn-color-icon: #696969;\n",
       "\n",
       "  @media (prefers-color-scheme: dark) {\n",
       "    /* Redefinition of color scheme for dark theme */\n",
       "    --sklearn-color-text-on-default-background: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, white)));\n",
       "    --sklearn-color-background: var(--sg-background-color, var(--theme-background, var(--jp-layout-color0, #111)));\n",
       "    --sklearn-color-border-box: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, white)));\n",
       "    --sklearn-color-icon: #878787;\n",
       "  }\n",
       "}\n",
       "\n",
       "#sk-container-id-1 {\n",
       "  color: var(--sklearn-color-text);\n",
       "}\n",
       "\n",
       "#sk-container-id-1 pre {\n",
       "  padding: 0;\n",
       "}\n",
       "\n",
       "#sk-container-id-1 input.sk-hidden--visually {\n",
       "  border: 0;\n",
       "  clip: rect(1px 1px 1px 1px);\n",
       "  clip: rect(1px, 1px, 1px, 1px);\n",
       "  height: 1px;\n",
       "  margin: -1px;\n",
       "  overflow: hidden;\n",
       "  padding: 0;\n",
       "  position: absolute;\n",
       "  width: 1px;\n",
       "}\n",
       "\n",
       "#sk-container-id-1 div.sk-dashed-wrapped {\n",
       "  border: 1px dashed var(--sklearn-color-line);\n",
       "  margin: 0 0.4em 0.5em 0.4em;\n",
       "  box-sizing: border-box;\n",
       "  padding-bottom: 0.4em;\n",
       "  background-color: var(--sklearn-color-background);\n",
       "}\n",
       "\n",
       "#sk-container-id-1 div.sk-container {\n",
       "  /* jupyter's `normalize.less` sets `[hidden] { display: none; }`\n",
       "     but bootstrap.min.css set `[hidden] { display: none !important; }`\n",
       "     so we also need the `!important` here to be able to override the\n",
       "     default hidden behavior on the sphinx rendered scikit-learn.org.\n",
       "     See: https://github.com/scikit-learn/scikit-learn/issues/21755 */\n",
       "  display: inline-block !important;\n",
       "  position: relative;\n",
       "}\n",
       "\n",
       "#sk-container-id-1 div.sk-text-repr-fallback {\n",
       "  display: none;\n",
       "}\n",
       "\n",
       "div.sk-parallel-item,\n",
       "div.sk-serial,\n",
       "div.sk-item {\n",
       "  /* draw centered vertical line to link estimators */\n",
       "  background-image: linear-gradient(var(--sklearn-color-text-on-default-background), var(--sklearn-color-text-on-default-background));\n",
       "  background-size: 2px 100%;\n",
       "  background-repeat: no-repeat;\n",
       "  background-position: center center;\n",
       "}\n",
       "\n",
       "/* Parallel-specific style estimator block */\n",
       "\n",
       "#sk-container-id-1 div.sk-parallel-item::after {\n",
       "  content: \"\";\n",
       "  width: 100%;\n",
       "  border-bottom: 2px solid var(--sklearn-color-text-on-default-background);\n",
       "  flex-grow: 1;\n",
       "}\n",
       "\n",
       "#sk-container-id-1 div.sk-parallel {\n",
       "  display: flex;\n",
       "  align-items: stretch;\n",
       "  justify-content: center;\n",
       "  background-color: var(--sklearn-color-background);\n",
       "  position: relative;\n",
       "}\n",
       "\n",
       "#sk-container-id-1 div.sk-parallel-item {\n",
       "  display: flex;\n",
       "  flex-direction: column;\n",
       "}\n",
       "\n",
       "#sk-container-id-1 div.sk-parallel-item:first-child::after {\n",
       "  align-self: flex-end;\n",
       "  width: 50%;\n",
       "}\n",
       "\n",
       "#sk-container-id-1 div.sk-parallel-item:last-child::after {\n",
       "  align-self: flex-start;\n",
       "  width: 50%;\n",
       "}\n",
       "\n",
       "#sk-container-id-1 div.sk-parallel-item:only-child::after {\n",
       "  width: 0;\n",
       "}\n",
       "\n",
       "/* Serial-specific style estimator block */\n",
       "\n",
       "#sk-container-id-1 div.sk-serial {\n",
       "  display: flex;\n",
       "  flex-direction: column;\n",
       "  align-items: center;\n",
       "  background-color: var(--sklearn-color-background);\n",
       "  padding-right: 1em;\n",
       "  padding-left: 1em;\n",
       "}\n",
       "\n",
       "\n",
       "/* Toggleable style: style used for estimator/Pipeline/ColumnTransformer box that is\n",
       "clickable and can be expanded/collapsed.\n",
       "- Pipeline and ColumnTransformer use this feature and define the default style\n",
       "- Estimators will overwrite some part of the style using the `sk-estimator` class\n",
       "*/\n",
       "\n",
       "/* Pipeline and ColumnTransformer style (default) */\n",
       "\n",
       "#sk-container-id-1 div.sk-toggleable {\n",
       "  /* Default theme specific background. It is overwritten whether we have a\n",
       "  specific estimator or a Pipeline/ColumnTransformer */\n",
       "  background-color: var(--sklearn-color-background);\n",
       "}\n",
       "\n",
       "/* Toggleable label */\n",
       "#sk-container-id-1 label.sk-toggleable__label {\n",
       "  cursor: pointer;\n",
       "  display: block;\n",
       "  width: 100%;\n",
       "  margin-bottom: 0;\n",
       "  padding: 0.5em;\n",
       "  box-sizing: border-box;\n",
       "  text-align: center;\n",
       "}\n",
       "\n",
       "#sk-container-id-1 label.sk-toggleable__label-arrow:before {\n",
       "  /* Arrow on the left of the label */\n",
       "  content: \"▸\";\n",
       "  float: left;\n",
       "  margin-right: 0.25em;\n",
       "  color: var(--sklearn-color-icon);\n",
       "}\n",
       "\n",
       "#sk-container-id-1 label.sk-toggleable__label-arrow:hover:before {\n",
       "  color: var(--sklearn-color-text);\n",
       "}\n",
       "\n",
       "/* Toggleable content - dropdown */\n",
       "\n",
       "#sk-container-id-1 div.sk-toggleable__content {\n",
       "  max-height: 0;\n",
       "  max-width: 0;\n",
       "  overflow: hidden;\n",
       "  text-align: left;\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-unfitted-level-0);\n",
       "}\n",
       "\n",
       "#sk-container-id-1 div.sk-toggleable__content.fitted {\n",
       "  /* fitted */\n",
       "  background-color: var(--sklearn-color-fitted-level-0);\n",
       "}\n",
       "\n",
       "#sk-container-id-1 div.sk-toggleable__content pre {\n",
       "  margin: 0.2em;\n",
       "  border-radius: 0.25em;\n",
       "  color: var(--sklearn-color-text);\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-unfitted-level-0);\n",
       "}\n",
       "\n",
       "#sk-container-id-1 div.sk-toggleable__content.fitted pre {\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-fitted-level-0);\n",
       "}\n",
       "\n",
       "#sk-container-id-1 input.sk-toggleable__control:checked~div.sk-toggleable__content {\n",
       "  /* Expand drop-down */\n",
       "  max-height: 200px;\n",
       "  max-width: 100%;\n",
       "  overflow: auto;\n",
       "}\n",
       "\n",
       "#sk-container-id-1 input.sk-toggleable__control:checked~label.sk-toggleable__label-arrow:before {\n",
       "  content: \"▾\";\n",
       "}\n",
       "\n",
       "/* Pipeline/ColumnTransformer-specific style */\n",
       "\n",
       "#sk-container-id-1 div.sk-label input.sk-toggleable__control:checked~label.sk-toggleable__label {\n",
       "  color: var(--sklearn-color-text);\n",
       "  background-color: var(--sklearn-color-unfitted-level-2);\n",
       "}\n",
       "\n",
       "#sk-container-id-1 div.sk-label.fitted input.sk-toggleable__control:checked~label.sk-toggleable__label {\n",
       "  background-color: var(--sklearn-color-fitted-level-2);\n",
       "}\n",
       "\n",
       "/* Estimator-specific style */\n",
       "\n",
       "/* Colorize estimator box */\n",
       "#sk-container-id-1 div.sk-estimator input.sk-toggleable__control:checked~label.sk-toggleable__label {\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-unfitted-level-2);\n",
       "}\n",
       "\n",
       "#sk-container-id-1 div.sk-estimator.fitted input.sk-toggleable__control:checked~label.sk-toggleable__label {\n",
       "  /* fitted */\n",
       "  background-color: var(--sklearn-color-fitted-level-2);\n",
       "}\n",
       "\n",
       "#sk-container-id-1 div.sk-label label.sk-toggleable__label,\n",
       "#sk-container-id-1 div.sk-label label {\n",
       "  /* The background is the default theme color */\n",
       "  color: var(--sklearn-color-text-on-default-background);\n",
       "}\n",
       "\n",
       "/* On hover, darken the color of the background */\n",
       "#sk-container-id-1 div.sk-label:hover label.sk-toggleable__label {\n",
       "  color: var(--sklearn-color-text);\n",
       "  background-color: var(--sklearn-color-unfitted-level-2);\n",
       "}\n",
       "\n",
       "/* Label box, darken color on hover, fitted */\n",
       "#sk-container-id-1 div.sk-label.fitted:hover label.sk-toggleable__label.fitted {\n",
       "  color: var(--sklearn-color-text);\n",
       "  background-color: var(--sklearn-color-fitted-level-2);\n",
       "}\n",
       "\n",
       "/* Estimator label */\n",
       "\n",
       "#sk-container-id-1 div.sk-label label {\n",
       "  font-family: monospace;\n",
       "  font-weight: bold;\n",
       "  display: inline-block;\n",
       "  line-height: 1.2em;\n",
       "}\n",
       "\n",
       "#sk-container-id-1 div.sk-label-container {\n",
       "  text-align: center;\n",
       "}\n",
       "\n",
       "/* Estimator-specific */\n",
       "#sk-container-id-1 div.sk-estimator {\n",
       "  font-family: monospace;\n",
       "  border: 1px dotted var(--sklearn-color-border-box);\n",
       "  border-radius: 0.25em;\n",
       "  box-sizing: border-box;\n",
       "  margin-bottom: 0.5em;\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-unfitted-level-0);\n",
       "}\n",
       "\n",
       "#sk-container-id-1 div.sk-estimator.fitted {\n",
       "  /* fitted */\n",
       "  background-color: var(--sklearn-color-fitted-level-0);\n",
       "}\n",
       "\n",
       "/* on hover */\n",
       "#sk-container-id-1 div.sk-estimator:hover {\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-unfitted-level-2);\n",
       "}\n",
       "\n",
       "#sk-container-id-1 div.sk-estimator.fitted:hover {\n",
       "  /* fitted */\n",
       "  background-color: var(--sklearn-color-fitted-level-2);\n",
       "}\n",
       "\n",
       "/* Specification for estimator info (e.g. \"i\" and \"?\") */\n",
       "\n",
       "/* Common style for \"i\" and \"?\" */\n",
       "\n",
       ".sk-estimator-doc-link,\n",
       "a:link.sk-estimator-doc-link,\n",
       "a:visited.sk-estimator-doc-link {\n",
       "  float: right;\n",
       "  font-size: smaller;\n",
       "  line-height: 1em;\n",
       "  font-family: monospace;\n",
       "  background-color: var(--sklearn-color-background);\n",
       "  border-radius: 1em;\n",
       "  height: 1em;\n",
       "  width: 1em;\n",
       "  text-decoration: none !important;\n",
       "  margin-left: 1ex;\n",
       "  /* unfitted */\n",
       "  border: var(--sklearn-color-unfitted-level-1) 1pt solid;\n",
       "  color: var(--sklearn-color-unfitted-level-1);\n",
       "}\n",
       "\n",
       ".sk-estimator-doc-link.fitted,\n",
       "a:link.sk-estimator-doc-link.fitted,\n",
       "a:visited.sk-estimator-doc-link.fitted {\n",
       "  /* fitted */\n",
       "  border: var(--sklearn-color-fitted-level-1) 1pt solid;\n",
       "  color: var(--sklearn-color-fitted-level-1);\n",
       "}\n",
       "\n",
       "/* On hover */\n",
       "div.sk-estimator:hover .sk-estimator-doc-link:hover,\n",
       ".sk-estimator-doc-link:hover,\n",
       "div.sk-label-container:hover .sk-estimator-doc-link:hover,\n",
       ".sk-estimator-doc-link:hover {\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-unfitted-level-3);\n",
       "  color: var(--sklearn-color-background);\n",
       "  text-decoration: none;\n",
       "}\n",
       "\n",
       "div.sk-estimator.fitted:hover .sk-estimator-doc-link.fitted:hover,\n",
       ".sk-estimator-doc-link.fitted:hover,\n",
       "div.sk-label-container:hover .sk-estimator-doc-link.fitted:hover,\n",
       ".sk-estimator-doc-link.fitted:hover {\n",
       "  /* fitted */\n",
       "  background-color: var(--sklearn-color-fitted-level-3);\n",
       "  color: var(--sklearn-color-background);\n",
       "  text-decoration: none;\n",
       "}\n",
       "\n",
       "/* Span, style for the box shown on hovering the info icon */\n",
       ".sk-estimator-doc-link span {\n",
       "  display: none;\n",
       "  z-index: 9999;\n",
       "  position: relative;\n",
       "  font-weight: normal;\n",
       "  right: .2ex;\n",
       "  padding: .5ex;\n",
       "  margin: .5ex;\n",
       "  width: min-content;\n",
       "  min-width: 20ex;\n",
       "  max-width: 50ex;\n",
       "  color: var(--sklearn-color-text);\n",
       "  box-shadow: 2pt 2pt 4pt #999;\n",
       "  /* unfitted */\n",
       "  background: var(--sklearn-color-unfitted-level-0);\n",
       "  border: .5pt solid var(--sklearn-color-unfitted-level-3);\n",
       "}\n",
       "\n",
       ".sk-estimator-doc-link.fitted span {\n",
       "  /* fitted */\n",
       "  background: var(--sklearn-color-fitted-level-0);\n",
       "  border: var(--sklearn-color-fitted-level-3);\n",
       "}\n",
       "\n",
       ".sk-estimator-doc-link:hover span {\n",
       "  display: block;\n",
       "}\n",
       "\n",
       "/* \"?\"-specific style due to the `<a>` HTML tag */\n",
       "\n",
       "#sk-container-id-1 a.estimator_doc_link {\n",
       "  float: right;\n",
       "  font-size: 1rem;\n",
       "  line-height: 1em;\n",
       "  font-family: monospace;\n",
       "  background-color: var(--sklearn-color-background);\n",
       "  border-radius: 1rem;\n",
       "  height: 1rem;\n",
       "  width: 1rem;\n",
       "  text-decoration: none;\n",
       "  /* unfitted */\n",
       "  color: var(--sklearn-color-unfitted-level-1);\n",
       "  border: var(--sklearn-color-unfitted-level-1) 1pt solid;\n",
       "}\n",
       "\n",
       "#sk-container-id-1 a.estimator_doc_link.fitted {\n",
       "  /* fitted */\n",
       "  border: var(--sklearn-color-fitted-level-1) 1pt solid;\n",
       "  color: var(--sklearn-color-fitted-level-1);\n",
       "}\n",
       "\n",
       "/* On hover */\n",
       "#sk-container-id-1 a.estimator_doc_link:hover {\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-unfitted-level-3);\n",
       "  color: var(--sklearn-color-background);\n",
       "  text-decoration: none;\n",
       "}\n",
       "\n",
       "#sk-container-id-1 a.estimator_doc_link.fitted:hover {\n",
       "  /* fitted */\n",
       "  background-color: var(--sklearn-color-fitted-level-3);\n",
       "}\n",
       "</style><div id=\"sk-container-id-1\" class=\"sk-top-container\"><div class=\"sk-text-repr-fallback\"><pre>LinearRegression()</pre><b>In a Jupyter environment, please rerun this cell to show the HTML representation or trust the notebook. <br />On GitHub, the HTML representation is unable to render, please try loading this page with nbviewer.org.</b></div><div class=\"sk-container\" hidden><div class=\"sk-item\"><div class=\"sk-estimator fitted 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 fitted sk-toggleable__label-arrow fitted\">&nbsp;&nbsp;LinearRegression<a class=\"sk-estimator-doc-link fitted\" rel=\"noreferrer\" target=\"_blank\" href=\"https://scikit-learn.org/1.5/modules/generated/sklearn.linear_model.LinearRegression.html\">?<span>Documentation for LinearRegression</span></a><span class=\"sk-estimator-doc-link fitted\">i<span>Fitted</span></span></label><div class=\"sk-toggleable__content fitted\"><pre>LinearRegression()</pre></div> </div></div></div></div>"
      ],
      "text/plain": [
       "LinearRegression()"
      ]
     },
     "execution_count": 31,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Training The Linear Regression Model\n",
    "model1 = LinearRegression()\n",
    "model1.fit(X_train, Y_train)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Making Prediction For Test Dataset\n",
    "Y_pred = model1.predict(X_test)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "0.6892398009560106\n"
     ]
    }
   ],
   "source": [
    "# Predicting Accuracy of Model\n",
    "print(model1.score(X_test,Y_test))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[0.75201074 0.70173496 0.72728641 0.68696209 0.72842624]\n"
     ]
    }
   ],
   "source": [
    "CV1 = cross_val_score(model1,X_train,Y_train,cv=5)\n",
    "print(CV1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Visualization of performance\n",
    "sns.lineplot(Y_test, label='Actual')\n",
    "sns.lineplot(Y_pred, label='Predicted')\n",
    "plt.xlim(0,3200)\n",
    "plt.legend()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### XGBoost"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<style>#sk-container-id-2 {\n",
       "  /* Definition of color scheme common for light and dark mode */\n",
       "  --sklearn-color-text: black;\n",
       "  --sklearn-color-line: gray;\n",
       "  /* Definition of color scheme for unfitted estimators */\n",
       "  --sklearn-color-unfitted-level-0: #fff5e6;\n",
       "  --sklearn-color-unfitted-level-1: #f6e4d2;\n",
       "  --sklearn-color-unfitted-level-2: #ffe0b3;\n",
       "  --sklearn-color-unfitted-level-3: chocolate;\n",
       "  /* Definition of color scheme for fitted estimators */\n",
       "  --sklearn-color-fitted-level-0: #f0f8ff;\n",
       "  --sklearn-color-fitted-level-1: #d4ebff;\n",
       "  --sklearn-color-fitted-level-2: #b3dbfd;\n",
       "  --sklearn-color-fitted-level-3: cornflowerblue;\n",
       "\n",
       "  /* Specific color for light theme */\n",
       "  --sklearn-color-text-on-default-background: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, black)));\n",
       "  --sklearn-color-background: var(--sg-background-color, var(--theme-background, var(--jp-layout-color0, white)));\n",
       "  --sklearn-color-border-box: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, black)));\n",
       "  --sklearn-color-icon: #696969;\n",
       "\n",
       "  @media (prefers-color-scheme: dark) {\n",
       "    /* Redefinition of color scheme for dark theme */\n",
       "    --sklearn-color-text-on-default-background: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, white)));\n",
       "    --sklearn-color-background: var(--sg-background-color, var(--theme-background, var(--jp-layout-color0, #111)));\n",
       "    --sklearn-color-border-box: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, white)));\n",
       "    --sklearn-color-icon: #878787;\n",
       "  }\n",
       "}\n",
       "\n",
       "#sk-container-id-2 {\n",
       "  color: var(--sklearn-color-text);\n",
       "}\n",
       "\n",
       "#sk-container-id-2 pre {\n",
       "  padding: 0;\n",
       "}\n",
       "\n",
       "#sk-container-id-2 input.sk-hidden--visually {\n",
       "  border: 0;\n",
       "  clip: rect(1px 1px 1px 1px);\n",
       "  clip: rect(1px, 1px, 1px, 1px);\n",
       "  height: 1px;\n",
       "  margin: -1px;\n",
       "  overflow: hidden;\n",
       "  padding: 0;\n",
       "  position: absolute;\n",
       "  width: 1px;\n",
       "}\n",
       "\n",
       "#sk-container-id-2 div.sk-dashed-wrapped {\n",
       "  border: 1px dashed var(--sklearn-color-line);\n",
       "  margin: 0 0.4em 0.5em 0.4em;\n",
       "  box-sizing: border-box;\n",
       "  padding-bottom: 0.4em;\n",
       "  background-color: var(--sklearn-color-background);\n",
       "}\n",
       "\n",
       "#sk-container-id-2 div.sk-container {\n",
       "  /* jupyter's `normalize.less` sets `[hidden] { display: none; }`\n",
       "     but bootstrap.min.css set `[hidden] { display: none !important; }`\n",
       "     so we also need the `!important` here to be able to override the\n",
       "     default hidden behavior on the sphinx rendered scikit-learn.org.\n",
       "     See: https://github.com/scikit-learn/scikit-learn/issues/21755 */\n",
       "  display: inline-block !important;\n",
       "  position: relative;\n",
       "}\n",
       "\n",
       "#sk-container-id-2 div.sk-text-repr-fallback {\n",
       "  display: none;\n",
       "}\n",
       "\n",
       "div.sk-parallel-item,\n",
       "div.sk-serial,\n",
       "div.sk-item {\n",
       "  /* draw centered vertical line to link estimators */\n",
       "  background-image: linear-gradient(var(--sklearn-color-text-on-default-background), var(--sklearn-color-text-on-default-background));\n",
       "  background-size: 2px 100%;\n",
       "  background-repeat: no-repeat;\n",
       "  background-position: center center;\n",
       "}\n",
       "\n",
       "/* Parallel-specific style estimator block */\n",
       "\n",
       "#sk-container-id-2 div.sk-parallel-item::after {\n",
       "  content: \"\";\n",
       "  width: 100%;\n",
       "  border-bottom: 2px solid var(--sklearn-color-text-on-default-background);\n",
       "  flex-grow: 1;\n",
       "}\n",
       "\n",
       "#sk-container-id-2 div.sk-parallel {\n",
       "  display: flex;\n",
       "  align-items: stretch;\n",
       "  justify-content: center;\n",
       "  background-color: var(--sklearn-color-background);\n",
       "  position: relative;\n",
       "}\n",
       "\n",
       "#sk-container-id-2 div.sk-parallel-item {\n",
       "  display: flex;\n",
       "  flex-direction: column;\n",
       "}\n",
       "\n",
       "#sk-container-id-2 div.sk-parallel-item:first-child::after {\n",
       "  align-self: flex-end;\n",
       "  width: 50%;\n",
       "}\n",
       "\n",
       "#sk-container-id-2 div.sk-parallel-item:last-child::after {\n",
       "  align-self: flex-start;\n",
       "  width: 50%;\n",
       "}\n",
       "\n",
       "#sk-container-id-2 div.sk-parallel-item:only-child::after {\n",
       "  width: 0;\n",
       "}\n",
       "\n",
       "/* Serial-specific style estimator block */\n",
       "\n",
       "#sk-container-id-2 div.sk-serial {\n",
       "  display: flex;\n",
       "  flex-direction: column;\n",
       "  align-items: center;\n",
       "  background-color: var(--sklearn-color-background);\n",
       "  padding-right: 1em;\n",
       "  padding-left: 1em;\n",
       "}\n",
       "\n",
       "\n",
       "/* Toggleable style: style used for estimator/Pipeline/ColumnTransformer box that is\n",
       "clickable and can be expanded/collapsed.\n",
       "- Pipeline and ColumnTransformer use this feature and define the default style\n",
       "- Estimators will overwrite some part of the style using the `sk-estimator` class\n",
       "*/\n",
       "\n",
       "/* Pipeline and ColumnTransformer style (default) */\n",
       "\n",
       "#sk-container-id-2 div.sk-toggleable {\n",
       "  /* Default theme specific background. It is overwritten whether we have a\n",
       "  specific estimator or a Pipeline/ColumnTransformer */\n",
       "  background-color: var(--sklearn-color-background);\n",
       "}\n",
       "\n",
       "/* Toggleable label */\n",
       "#sk-container-id-2 label.sk-toggleable__label {\n",
       "  cursor: pointer;\n",
       "  display: block;\n",
       "  width: 100%;\n",
       "  margin-bottom: 0;\n",
       "  padding: 0.5em;\n",
       "  box-sizing: border-box;\n",
       "  text-align: center;\n",
       "}\n",
       "\n",
       "#sk-container-id-2 label.sk-toggleable__label-arrow:before {\n",
       "  /* Arrow on the left of the label */\n",
       "  content: \"▸\";\n",
       "  float: left;\n",
       "  margin-right: 0.25em;\n",
       "  color: var(--sklearn-color-icon);\n",
       "}\n",
       "\n",
       "#sk-container-id-2 label.sk-toggleable__label-arrow:hover:before {\n",
       "  color: var(--sklearn-color-text);\n",
       "}\n",
       "\n",
       "/* Toggleable content - dropdown */\n",
       "\n",
       "#sk-container-id-2 div.sk-toggleable__content {\n",
       "  max-height: 0;\n",
       "  max-width: 0;\n",
       "  overflow: hidden;\n",
       "  text-align: left;\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-unfitted-level-0);\n",
       "}\n",
       "\n",
       "#sk-container-id-2 div.sk-toggleable__content.fitted {\n",
       "  /* fitted */\n",
       "  background-color: var(--sklearn-color-fitted-level-0);\n",
       "}\n",
       "\n",
       "#sk-container-id-2 div.sk-toggleable__content pre {\n",
       "  margin: 0.2em;\n",
       "  border-radius: 0.25em;\n",
       "  color: var(--sklearn-color-text);\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-unfitted-level-0);\n",
       "}\n",
       "\n",
       "#sk-container-id-2 div.sk-toggleable__content.fitted pre {\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-fitted-level-0);\n",
       "}\n",
       "\n",
       "#sk-container-id-2 input.sk-toggleable__control:checked~div.sk-toggleable__content {\n",
       "  /* Expand drop-down */\n",
       "  max-height: 200px;\n",
       "  max-width: 100%;\n",
       "  overflow: auto;\n",
       "}\n",
       "\n",
       "#sk-container-id-2 input.sk-toggleable__control:checked~label.sk-toggleable__label-arrow:before {\n",
       "  content: \"▾\";\n",
       "}\n",
       "\n",
       "/* Pipeline/ColumnTransformer-specific style */\n",
       "\n",
       "#sk-container-id-2 div.sk-label input.sk-toggleable__control:checked~label.sk-toggleable__label {\n",
       "  color: var(--sklearn-color-text);\n",
       "  background-color: var(--sklearn-color-unfitted-level-2);\n",
       "}\n",
       "\n",
       "#sk-container-id-2 div.sk-label.fitted input.sk-toggleable__control:checked~label.sk-toggleable__label {\n",
       "  background-color: var(--sklearn-color-fitted-level-2);\n",
       "}\n",
       "\n",
       "/* Estimator-specific style */\n",
       "\n",
       "/* Colorize estimator box */\n",
       "#sk-container-id-2 div.sk-estimator input.sk-toggleable__control:checked~label.sk-toggleable__label {\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-unfitted-level-2);\n",
       "}\n",
       "\n",
       "#sk-container-id-2 div.sk-estimator.fitted input.sk-toggleable__control:checked~label.sk-toggleable__label {\n",
       "  /* fitted */\n",
       "  background-color: var(--sklearn-color-fitted-level-2);\n",
       "}\n",
       "\n",
       "#sk-container-id-2 div.sk-label label.sk-toggleable__label,\n",
       "#sk-container-id-2 div.sk-label label {\n",
       "  /* The background is the default theme color */\n",
       "  color: var(--sklearn-color-text-on-default-background);\n",
       "}\n",
       "\n",
       "/* On hover, darken the color of the background */\n",
       "#sk-container-id-2 div.sk-label:hover label.sk-toggleable__label {\n",
       "  color: var(--sklearn-color-text);\n",
       "  background-color: var(--sklearn-color-unfitted-level-2);\n",
       "}\n",
       "\n",
       "/* Label box, darken color on hover, fitted */\n",
       "#sk-container-id-2 div.sk-label.fitted:hover label.sk-toggleable__label.fitted {\n",
       "  color: var(--sklearn-color-text);\n",
       "  background-color: var(--sklearn-color-fitted-level-2);\n",
       "}\n",
       "\n",
       "/* Estimator label */\n",
       "\n",
       "#sk-container-id-2 div.sk-label label {\n",
       "  font-family: monospace;\n",
       "  font-weight: bold;\n",
       "  display: inline-block;\n",
       "  line-height: 1.2em;\n",
       "}\n",
       "\n",
       "#sk-container-id-2 div.sk-label-container {\n",
       "  text-align: center;\n",
       "}\n",
       "\n",
       "/* Estimator-specific */\n",
       "#sk-container-id-2 div.sk-estimator {\n",
       "  font-family: monospace;\n",
       "  border: 1px dotted var(--sklearn-color-border-box);\n",
       "  border-radius: 0.25em;\n",
       "  box-sizing: border-box;\n",
       "  margin-bottom: 0.5em;\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-unfitted-level-0);\n",
       "}\n",
       "\n",
       "#sk-container-id-2 div.sk-estimator.fitted {\n",
       "  /* fitted */\n",
       "  background-color: var(--sklearn-color-fitted-level-0);\n",
       "}\n",
       "\n",
       "/* on hover */\n",
       "#sk-container-id-2 div.sk-estimator:hover {\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-unfitted-level-2);\n",
       "}\n",
       "\n",
       "#sk-container-id-2 div.sk-estimator.fitted:hover {\n",
       "  /* fitted */\n",
       "  background-color: var(--sklearn-color-fitted-level-2);\n",
       "}\n",
       "\n",
       "/* Specification for estimator info (e.g. \"i\" and \"?\") */\n",
       "\n",
       "/* Common style for \"i\" and \"?\" */\n",
       "\n",
       ".sk-estimator-doc-link,\n",
       "a:link.sk-estimator-doc-link,\n",
       "a:visited.sk-estimator-doc-link {\n",
       "  float: right;\n",
       "  font-size: smaller;\n",
       "  line-height: 1em;\n",
       "  font-family: monospace;\n",
       "  background-color: var(--sklearn-color-background);\n",
       "  border-radius: 1em;\n",
       "  height: 1em;\n",
       "  width: 1em;\n",
       "  text-decoration: none !important;\n",
       "  margin-left: 1ex;\n",
       "  /* unfitted */\n",
       "  border: var(--sklearn-color-unfitted-level-1) 1pt solid;\n",
       "  color: var(--sklearn-color-unfitted-level-1);\n",
       "}\n",
       "\n",
       ".sk-estimator-doc-link.fitted,\n",
       "a:link.sk-estimator-doc-link.fitted,\n",
       "a:visited.sk-estimator-doc-link.fitted {\n",
       "  /* fitted */\n",
       "  border: var(--sklearn-color-fitted-level-1) 1pt solid;\n",
       "  color: var(--sklearn-color-fitted-level-1);\n",
       "}\n",
       "\n",
       "/* On hover */\n",
       "div.sk-estimator:hover .sk-estimator-doc-link:hover,\n",
       ".sk-estimator-doc-link:hover,\n",
       "div.sk-label-container:hover .sk-estimator-doc-link:hover,\n",
       ".sk-estimator-doc-link:hover {\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-unfitted-level-3);\n",
       "  color: var(--sklearn-color-background);\n",
       "  text-decoration: none;\n",
       "}\n",
       "\n",
       "div.sk-estimator.fitted:hover .sk-estimator-doc-link.fitted:hover,\n",
       ".sk-estimator-doc-link.fitted:hover,\n",
       "div.sk-label-container:hover .sk-estimator-doc-link.fitted:hover,\n",
       ".sk-estimator-doc-link.fitted:hover {\n",
       "  /* fitted */\n",
       "  background-color: var(--sklearn-color-fitted-level-3);\n",
       "  color: var(--sklearn-color-background);\n",
       "  text-decoration: none;\n",
       "}\n",
       "\n",
       "/* Span, style for the box shown on hovering the info icon */\n",
       ".sk-estimator-doc-link span {\n",
       "  display: none;\n",
       "  z-index: 9999;\n",
       "  position: relative;\n",
       "  font-weight: normal;\n",
       "  right: .2ex;\n",
       "  padding: .5ex;\n",
       "  margin: .5ex;\n",
       "  width: min-content;\n",
       "  min-width: 20ex;\n",
       "  max-width: 50ex;\n",
       "  color: var(--sklearn-color-text);\n",
       "  box-shadow: 2pt 2pt 4pt #999;\n",
       "  /* unfitted */\n",
       "  background: var(--sklearn-color-unfitted-level-0);\n",
       "  border: .5pt solid var(--sklearn-color-unfitted-level-3);\n",
       "}\n",
       "\n",
       ".sk-estimator-doc-link.fitted span {\n",
       "  /* fitted */\n",
       "  background: var(--sklearn-color-fitted-level-0);\n",
       "  border: var(--sklearn-color-fitted-level-3);\n",
       "}\n",
       "\n",
       ".sk-estimator-doc-link:hover span {\n",
       "  display: block;\n",
       "}\n",
       "\n",
       "/* \"?\"-specific style due to the `<a>` HTML tag */\n",
       "\n",
       "#sk-container-id-2 a.estimator_doc_link {\n",
       "  float: right;\n",
       "  font-size: 1rem;\n",
       "  line-height: 1em;\n",
       "  font-family: monospace;\n",
       "  background-color: var(--sklearn-color-background);\n",
       "  border-radius: 1rem;\n",
       "  height: 1rem;\n",
       "  width: 1rem;\n",
       "  text-decoration: none;\n",
       "  /* unfitted */\n",
       "  color: var(--sklearn-color-unfitted-level-1);\n",
       "  border: var(--sklearn-color-unfitted-level-1) 1pt solid;\n",
       "}\n",
       "\n",
       "#sk-container-id-2 a.estimator_doc_link.fitted {\n",
       "  /* fitted */\n",
       "  border: var(--sklearn-color-fitted-level-1) 1pt solid;\n",
       "  color: var(--sklearn-color-fitted-level-1);\n",
       "}\n",
       "\n",
       "/* On hover */\n",
       "#sk-container-id-2 a.estimator_doc_link:hover {\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-unfitted-level-3);\n",
       "  color: var(--sklearn-color-background);\n",
       "  text-decoration: none;\n",
       "}\n",
       "\n",
       "#sk-container-id-2 a.estimator_doc_link.fitted:hover {\n",
       "  /* fitted */\n",
       "  background-color: var(--sklearn-color-fitted-level-3);\n",
       "}\n",
       "</style><div id=\"sk-container-id-2\" 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=0.1, 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=100, n_jobs=None,\n",
       "             num_parallel_tree=None, random_state=42, ...)</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 fitted sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-2\" type=\"checkbox\" checked><label for=\"sk-estimator-id-2\" class=\"sk-toggleable__label fitted sk-toggleable__label-arrow fitted\">&nbsp;XGBRegressor<span class=\"sk-estimator-doc-link fitted\">i<span>Fitted</span></span></label><div class=\"sk-toggleable__content fitted\"><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=0.1, 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=100, n_jobs=None,\n",
       "             num_parallel_tree=None, random_state=42, ...)</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=0.1, 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=100, n_jobs=None,\n",
       "             num_parallel_tree=None, random_state=42, ...)"
      ]
     },
     "execution_count": 36,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "model2= xgb.XGBRegressor(n_estimators=100, learning_rate=0.1, random_state=42)\n",
    "model2.fit(X_train, Y_train)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {},
   "outputs": [],
   "source": [
    "Y_predt = model2.predict(X_test)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "0.9119535343358782\n"
     ]
    }
   ],
   "source": [
    "print(model2.score(X_test,Y_test))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[0.91615065 0.9303113  0.92667094 0.86802516 0.9339211 ]\n"
     ]
    }
   ],
   "source": [
    "CV2 = cross_val_score(model2,X_train,Y_train,cv=5)\n",
    "print(CV2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Visualization of performance\n",
    "sns.lineplot(Y_test, label='Actual')\n",
    "sns.lineplot(Y_predt, label='Predicted')\n",
    "plt.xlim(0,3000)\n",
    "plt.legend()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Random Forest"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<style>#sk-container-id-3 {\n",
       "  /* Definition of color scheme common for light and dark mode */\n",
       "  --sklearn-color-text: black;\n",
       "  --sklearn-color-line: gray;\n",
       "  /* Definition of color scheme for unfitted estimators */\n",
       "  --sklearn-color-unfitted-level-0: #fff5e6;\n",
       "  --sklearn-color-unfitted-level-1: #f6e4d2;\n",
       "  --sklearn-color-unfitted-level-2: #ffe0b3;\n",
       "  --sklearn-color-unfitted-level-3: chocolate;\n",
       "  /* Definition of color scheme for fitted estimators */\n",
       "  --sklearn-color-fitted-level-0: #f0f8ff;\n",
       "  --sklearn-color-fitted-level-1: #d4ebff;\n",
       "  --sklearn-color-fitted-level-2: #b3dbfd;\n",
       "  --sklearn-color-fitted-level-3: cornflowerblue;\n",
       "\n",
       "  /* Specific color for light theme */\n",
       "  --sklearn-color-text-on-default-background: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, black)));\n",
       "  --sklearn-color-background: var(--sg-background-color, var(--theme-background, var(--jp-layout-color0, white)));\n",
       "  --sklearn-color-border-box: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, black)));\n",
       "  --sklearn-color-icon: #696969;\n",
       "\n",
       "  @media (prefers-color-scheme: dark) {\n",
       "    /* Redefinition of color scheme for dark theme */\n",
       "    --sklearn-color-text-on-default-background: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, white)));\n",
       "    --sklearn-color-background: var(--sg-background-color, var(--theme-background, var(--jp-layout-color0, #111)));\n",
       "    --sklearn-color-border-box: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, white)));\n",
       "    --sklearn-color-icon: #878787;\n",
       "  }\n",
       "}\n",
       "\n",
       "#sk-container-id-3 {\n",
       "  color: var(--sklearn-color-text);\n",
       "}\n",
       "\n",
       "#sk-container-id-3 pre {\n",
       "  padding: 0;\n",
       "}\n",
       "\n",
       "#sk-container-id-3 input.sk-hidden--visually {\n",
       "  border: 0;\n",
       "  clip: rect(1px 1px 1px 1px);\n",
       "  clip: rect(1px, 1px, 1px, 1px);\n",
       "  height: 1px;\n",
       "  margin: -1px;\n",
       "  overflow: hidden;\n",
       "  padding: 0;\n",
       "  position: absolute;\n",
       "  width: 1px;\n",
       "}\n",
       "\n",
       "#sk-container-id-3 div.sk-dashed-wrapped {\n",
       "  border: 1px dashed var(--sklearn-color-line);\n",
       "  margin: 0 0.4em 0.5em 0.4em;\n",
       "  box-sizing: border-box;\n",
       "  padding-bottom: 0.4em;\n",
       "  background-color: var(--sklearn-color-background);\n",
       "}\n",
       "\n",
       "#sk-container-id-3 div.sk-container {\n",
       "  /* jupyter's `normalize.less` sets `[hidden] { display: none; }`\n",
       "     but bootstrap.min.css set `[hidden] { display: none !important; }`\n",
       "     so we also need the `!important` here to be able to override the\n",
       "     default hidden behavior on the sphinx rendered scikit-learn.org.\n",
       "     See: https://github.com/scikit-learn/scikit-learn/issues/21755 */\n",
       "  display: inline-block !important;\n",
       "  position: relative;\n",
       "}\n",
       "\n",
       "#sk-container-id-3 div.sk-text-repr-fallback {\n",
       "  display: none;\n",
       "}\n",
       "\n",
       "div.sk-parallel-item,\n",
       "div.sk-serial,\n",
       "div.sk-item {\n",
       "  /* draw centered vertical line to link estimators */\n",
       "  background-image: linear-gradient(var(--sklearn-color-text-on-default-background), var(--sklearn-color-text-on-default-background));\n",
       "  background-size: 2px 100%;\n",
       "  background-repeat: no-repeat;\n",
       "  background-position: center center;\n",
       "}\n",
       "\n",
       "/* Parallel-specific style estimator block */\n",
       "\n",
       "#sk-container-id-3 div.sk-parallel-item::after {\n",
       "  content: \"\";\n",
       "  width: 100%;\n",
       "  border-bottom: 2px solid var(--sklearn-color-text-on-default-background);\n",
       "  flex-grow: 1;\n",
       "}\n",
       "\n",
       "#sk-container-id-3 div.sk-parallel {\n",
       "  display: flex;\n",
       "  align-items: stretch;\n",
       "  justify-content: center;\n",
       "  background-color: var(--sklearn-color-background);\n",
       "  position: relative;\n",
       "}\n",
       "\n",
       "#sk-container-id-3 div.sk-parallel-item {\n",
       "  display: flex;\n",
       "  flex-direction: column;\n",
       "}\n",
       "\n",
       "#sk-container-id-3 div.sk-parallel-item:first-child::after {\n",
       "  align-self: flex-end;\n",
       "  width: 50%;\n",
       "}\n",
       "\n",
       "#sk-container-id-3 div.sk-parallel-item:last-child::after {\n",
       "  align-self: flex-start;\n",
       "  width: 50%;\n",
       "}\n",
       "\n",
       "#sk-container-id-3 div.sk-parallel-item:only-child::after {\n",
       "  width: 0;\n",
       "}\n",
       "\n",
       "/* Serial-specific style estimator block */\n",
       "\n",
       "#sk-container-id-3 div.sk-serial {\n",
       "  display: flex;\n",
       "  flex-direction: column;\n",
       "  align-items: center;\n",
       "  background-color: var(--sklearn-color-background);\n",
       "  padding-right: 1em;\n",
       "  padding-left: 1em;\n",
       "}\n",
       "\n",
       "\n",
       "/* Toggleable style: style used for estimator/Pipeline/ColumnTransformer box that is\n",
       "clickable and can be expanded/collapsed.\n",
       "- Pipeline and ColumnTransformer use this feature and define the default style\n",
       "- Estimators will overwrite some part of the style using the `sk-estimator` class\n",
       "*/\n",
       "\n",
       "/* Pipeline and ColumnTransformer style (default) */\n",
       "\n",
       "#sk-container-id-3 div.sk-toggleable {\n",
       "  /* Default theme specific background. It is overwritten whether we have a\n",
       "  specific estimator or a Pipeline/ColumnTransformer */\n",
       "  background-color: var(--sklearn-color-background);\n",
       "}\n",
       "\n",
       "/* Toggleable label */\n",
       "#sk-container-id-3 label.sk-toggleable__label {\n",
       "  cursor: pointer;\n",
       "  display: block;\n",
       "  width: 100%;\n",
       "  margin-bottom: 0;\n",
       "  padding: 0.5em;\n",
       "  box-sizing: border-box;\n",
       "  text-align: center;\n",
       "}\n",
       "\n",
       "#sk-container-id-3 label.sk-toggleable__label-arrow:before {\n",
       "  /* Arrow on the left of the label */\n",
       "  content: \"▸\";\n",
       "  float: left;\n",
       "  margin-right: 0.25em;\n",
       "  color: var(--sklearn-color-icon);\n",
       "}\n",
       "\n",
       "#sk-container-id-3 label.sk-toggleable__label-arrow:hover:before {\n",
       "  color: var(--sklearn-color-text);\n",
       "}\n",
       "\n",
       "/* Toggleable content - dropdown */\n",
       "\n",
       "#sk-container-id-3 div.sk-toggleable__content {\n",
       "  max-height: 0;\n",
       "  max-width: 0;\n",
       "  overflow: hidden;\n",
       "  text-align: left;\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-unfitted-level-0);\n",
       "}\n",
       "\n",
       "#sk-container-id-3 div.sk-toggleable__content.fitted {\n",
       "  /* fitted */\n",
       "  background-color: var(--sklearn-color-fitted-level-0);\n",
       "}\n",
       "\n",
       "#sk-container-id-3 div.sk-toggleable__content pre {\n",
       "  margin: 0.2em;\n",
       "  border-radius: 0.25em;\n",
       "  color: var(--sklearn-color-text);\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-unfitted-level-0);\n",
       "}\n",
       "\n",
       "#sk-container-id-3 div.sk-toggleable__content.fitted pre {\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-fitted-level-0);\n",
       "}\n",
       "\n",
       "#sk-container-id-3 input.sk-toggleable__control:checked~div.sk-toggleable__content {\n",
       "  /* Expand drop-down */\n",
       "  max-height: 200px;\n",
       "  max-width: 100%;\n",
       "  overflow: auto;\n",
       "}\n",
       "\n",
       "#sk-container-id-3 input.sk-toggleable__control:checked~label.sk-toggleable__label-arrow:before {\n",
       "  content: \"▾\";\n",
       "}\n",
       "\n",
       "/* Pipeline/ColumnTransformer-specific style */\n",
       "\n",
       "#sk-container-id-3 div.sk-label input.sk-toggleable__control:checked~label.sk-toggleable__label {\n",
       "  color: var(--sklearn-color-text);\n",
       "  background-color: var(--sklearn-color-unfitted-level-2);\n",
       "}\n",
       "\n",
       "#sk-container-id-3 div.sk-label.fitted input.sk-toggleable__control:checked~label.sk-toggleable__label {\n",
       "  background-color: var(--sklearn-color-fitted-level-2);\n",
       "}\n",
       "\n",
       "/* Estimator-specific style */\n",
       "\n",
       "/* Colorize estimator box */\n",
       "#sk-container-id-3 div.sk-estimator input.sk-toggleable__control:checked~label.sk-toggleable__label {\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-unfitted-level-2);\n",
       "}\n",
       "\n",
       "#sk-container-id-3 div.sk-estimator.fitted input.sk-toggleable__control:checked~label.sk-toggleable__label {\n",
       "  /* fitted */\n",
       "  background-color: var(--sklearn-color-fitted-level-2);\n",
       "}\n",
       "\n",
       "#sk-container-id-3 div.sk-label label.sk-toggleable__label,\n",
       "#sk-container-id-3 div.sk-label label {\n",
       "  /* The background is the default theme color */\n",
       "  color: var(--sklearn-color-text-on-default-background);\n",
       "}\n",
       "\n",
       "/* On hover, darken the color of the background */\n",
       "#sk-container-id-3 div.sk-label:hover label.sk-toggleable__label {\n",
       "  color: var(--sklearn-color-text);\n",
       "  background-color: var(--sklearn-color-unfitted-level-2);\n",
       "}\n",
       "\n",
       "/* Label box, darken color on hover, fitted */\n",
       "#sk-container-id-3 div.sk-label.fitted:hover label.sk-toggleable__label.fitted {\n",
       "  color: var(--sklearn-color-text);\n",
       "  background-color: var(--sklearn-color-fitted-level-2);\n",
       "}\n",
       "\n",
       "/* Estimator label */\n",
       "\n",
       "#sk-container-id-3 div.sk-label label {\n",
       "  font-family: monospace;\n",
       "  font-weight: bold;\n",
       "  display: inline-block;\n",
       "  line-height: 1.2em;\n",
       "}\n",
       "\n",
       "#sk-container-id-3 div.sk-label-container {\n",
       "  text-align: center;\n",
       "}\n",
       "\n",
       "/* Estimator-specific */\n",
       "#sk-container-id-3 div.sk-estimator {\n",
       "  font-family: monospace;\n",
       "  border: 1px dotted var(--sklearn-color-border-box);\n",
       "  border-radius: 0.25em;\n",
       "  box-sizing: border-box;\n",
       "  margin-bottom: 0.5em;\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-unfitted-level-0);\n",
       "}\n",
       "\n",
       "#sk-container-id-3 div.sk-estimator.fitted {\n",
       "  /* fitted */\n",
       "  background-color: var(--sklearn-color-fitted-level-0);\n",
       "}\n",
       "\n",
       "/* on hover */\n",
       "#sk-container-id-3 div.sk-estimator:hover {\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-unfitted-level-2);\n",
       "}\n",
       "\n",
       "#sk-container-id-3 div.sk-estimator.fitted:hover {\n",
       "  /* fitted */\n",
       "  background-color: var(--sklearn-color-fitted-level-2);\n",
       "}\n",
       "\n",
       "/* Specification for estimator info (e.g. \"i\" and \"?\") */\n",
       "\n",
       "/* Common style for \"i\" and \"?\" */\n",
       "\n",
       ".sk-estimator-doc-link,\n",
       "a:link.sk-estimator-doc-link,\n",
       "a:visited.sk-estimator-doc-link {\n",
       "  float: right;\n",
       "  font-size: smaller;\n",
       "  line-height: 1em;\n",
       "  font-family: monospace;\n",
       "  background-color: var(--sklearn-color-background);\n",
       "  border-radius: 1em;\n",
       "  height: 1em;\n",
       "  width: 1em;\n",
       "  text-decoration: none !important;\n",
       "  margin-left: 1ex;\n",
       "  /* unfitted */\n",
       "  border: var(--sklearn-color-unfitted-level-1) 1pt solid;\n",
       "  color: var(--sklearn-color-unfitted-level-1);\n",
       "}\n",
       "\n",
       ".sk-estimator-doc-link.fitted,\n",
       "a:link.sk-estimator-doc-link.fitted,\n",
       "a:visited.sk-estimator-doc-link.fitted {\n",
       "  /* fitted */\n",
       "  border: var(--sklearn-color-fitted-level-1) 1pt solid;\n",
       "  color: var(--sklearn-color-fitted-level-1);\n",
       "}\n",
       "\n",
       "/* On hover */\n",
       "div.sk-estimator:hover .sk-estimator-doc-link:hover,\n",
       ".sk-estimator-doc-link:hover,\n",
       "div.sk-label-container:hover .sk-estimator-doc-link:hover,\n",
       ".sk-estimator-doc-link:hover {\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-unfitted-level-3);\n",
       "  color: var(--sklearn-color-background);\n",
       "  text-decoration: none;\n",
       "}\n",
       "\n",
       "div.sk-estimator.fitted:hover .sk-estimator-doc-link.fitted:hover,\n",
       ".sk-estimator-doc-link.fitted:hover,\n",
       "div.sk-label-container:hover .sk-estimator-doc-link.fitted:hover,\n",
       ".sk-estimator-doc-link.fitted:hover {\n",
       "  /* fitted */\n",
       "  background-color: var(--sklearn-color-fitted-level-3);\n",
       "  color: var(--sklearn-color-background);\n",
       "  text-decoration: none;\n",
       "}\n",
       "\n",
       "/* Span, style for the box shown on hovering the info icon */\n",
       ".sk-estimator-doc-link span {\n",
       "  display: none;\n",
       "  z-index: 9999;\n",
       "  position: relative;\n",
       "  font-weight: normal;\n",
       "  right: .2ex;\n",
       "  padding: .5ex;\n",
       "  margin: .5ex;\n",
       "  width: min-content;\n",
       "  min-width: 20ex;\n",
       "  max-width: 50ex;\n",
       "  color: var(--sklearn-color-text);\n",
       "  box-shadow: 2pt 2pt 4pt #999;\n",
       "  /* unfitted */\n",
       "  background: var(--sklearn-color-unfitted-level-0);\n",
       "  border: .5pt solid var(--sklearn-color-unfitted-level-3);\n",
       "}\n",
       "\n",
       ".sk-estimator-doc-link.fitted span {\n",
       "  /* fitted */\n",
       "  background: var(--sklearn-color-fitted-level-0);\n",
       "  border: var(--sklearn-color-fitted-level-3);\n",
       "}\n",
       "\n",
       ".sk-estimator-doc-link:hover span {\n",
       "  display: block;\n",
       "}\n",
       "\n",
       "/* \"?\"-specific style due to the `<a>` HTML tag */\n",
       "\n",
       "#sk-container-id-3 a.estimator_doc_link {\n",
       "  float: right;\n",
       "  font-size: 1rem;\n",
       "  line-height: 1em;\n",
       "  font-family: monospace;\n",
       "  background-color: var(--sklearn-color-background);\n",
       "  border-radius: 1rem;\n",
       "  height: 1rem;\n",
       "  width: 1rem;\n",
       "  text-decoration: none;\n",
       "  /* unfitted */\n",
       "  color: var(--sklearn-color-unfitted-level-1);\n",
       "  border: var(--sklearn-color-unfitted-level-1) 1pt solid;\n",
       "}\n",
       "\n",
       "#sk-container-id-3 a.estimator_doc_link.fitted {\n",
       "  /* fitted */\n",
       "  border: var(--sklearn-color-fitted-level-1) 1pt solid;\n",
       "  color: var(--sklearn-color-fitted-level-1);\n",
       "}\n",
       "\n",
       "/* On hover */\n",
       "#sk-container-id-3 a.estimator_doc_link:hover {\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-unfitted-level-3);\n",
       "  color: var(--sklearn-color-background);\n",
       "  text-decoration: none;\n",
       "}\n",
       "\n",
       "#sk-container-id-3 a.estimator_doc_link.fitted:hover {\n",
       "  /* fitted */\n",
       "  background-color: var(--sklearn-color-fitted-level-3);\n",
       "}\n",
       "</style><div id=\"sk-container-id-3\" class=\"sk-top-container\"><div class=\"sk-text-repr-fallback\"><pre>RandomForestRegressor(random_state=42)</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 fitted sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-3\" type=\"checkbox\" checked><label for=\"sk-estimator-id-3\" class=\"sk-toggleable__label fitted sk-toggleable__label-arrow fitted\">&nbsp;&nbsp;RandomForestRegressor<a class=\"sk-estimator-doc-link fitted\" rel=\"noreferrer\" target=\"_blank\" href=\"https://scikit-learn.org/1.5/modules/generated/sklearn.ensemble.RandomForestRegressor.html\">?<span>Documentation for RandomForestRegressor</span></a><span class=\"sk-estimator-doc-link fitted\">i<span>Fitted</span></span></label><div class=\"sk-toggleable__content fitted\"><pre>RandomForestRegressor(random_state=42)</pre></div> </div></div></div></div>"
      ],
      "text/plain": [
       "RandomForestRegressor(random_state=42)"
      ]
     },
     "execution_count": 41,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "model3 = RandomForestRegressor(n_estimators=100, random_state=42)\n",
    "model3.fit(X_train, Y_train)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "metadata": {},
   "outputs": [],
   "source": [
    "Y_predict = model3.predict(X_test)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "0.9304791455918067\n"
     ]
    }
   ],
   "source": [
    "print(model3.score(X_test,Y_test))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[0.91885418 0.91909888 0.92889428 0.85952425 0.92611108]\n"
     ]
    }
   ],
   "source": [
    "CV3 = cross_val_score(model3,X_train,Y_train,cv=5)\n",
    "print(CV3)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Visualization of performance\n",
    "sns.lineplot(Y_test, label='Actual')\n",
    "sns.lineplot(Y_predict, label='Predicted')\n",
    "plt.xlim(0,3200)\n",
    "plt.legend()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Saving The Best Model"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "metadata": {},
   "outputs": [],
   "source": [
    "import gzip\n",
    "with gzip.open('car_resale_model.pkl.gz ', 'wb') as file:\n",
    "    pickle.dump(model3, file)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Conclusion"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "After Training and Evaluating all the models below are the results :\n",
    "- **Random Forest** and **XGBoost** significantly outperform **Linear Regression**\n",
    "- The small difference in accuracy between Random Forest and XGBoost suggests that both models are well-suited for this dataset, but Random Forest has a slight edge in performance.\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Thank You For Reading"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "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": "3.12.4"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}