{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 52,
   "id": "524e29b0-cb0a-4d3b-b383-b0e5b8803515",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Requirement already satisfied: scikit-learn in c:\\users\\hirsi\\appdata\\local\\programs\\python\\python313\\lib\\site-packages (1.7.0)\n",
      "Requirement already satisfied: numpy>=1.22.0 in c:\\users\\hirsi\\appdata\\local\\programs\\python\\python313\\lib\\site-packages (from scikit-learn) (2.3.0)\n",
      "Requirement already satisfied: scipy>=1.8.0 in c:\\users\\hirsi\\appdata\\local\\programs\\python\\python313\\lib\\site-packages (from scikit-learn) (1.15.3)\n",
      "Requirement already satisfied: joblib>=1.2.0 in c:\\users\\hirsi\\appdata\\local\\programs\\python\\python313\\lib\\site-packages (from scikit-learn) (1.5.1)\n",
      "Requirement already satisfied: threadpoolctl>=3.1.0 in c:\\users\\hirsi\\appdata\\local\\programs\\python\\python313\\lib\\site-packages (from scikit-learn) (3.6.0)\n"
     ]
    }
   ],
   "source": [
    "!pip install scikit-learn\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "id": "e2e3adc0-fe10-48d5-bb0d-f2e1cd0960f0",
   "metadata": {},
   "outputs": [],
   "source": [
    "# import required libararies\n",
    "import pandas as pd\n",
    "import numpy as np\n",
    "import seaborn as sns\n",
    "import matplotlib.pyplot as plt"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "647a412d-6735-46df-a2f9-a93c0ac55190",
   "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>Id</th>\n",
       "      <th>MSSubClass</th>\n",
       "      <th>MSZoning</th>\n",
       "      <th>LotFrontage</th>\n",
       "      <th>LotArea</th>\n",
       "      <th>Street</th>\n",
       "      <th>Alley</th>\n",
       "      <th>LotShape</th>\n",
       "      <th>LandContour</th>\n",
       "      <th>Utilities</th>\n",
       "      <th>...</th>\n",
       "      <th>PoolArea</th>\n",
       "      <th>PoolQC</th>\n",
       "      <th>Fence</th>\n",
       "      <th>MiscFeature</th>\n",
       "      <th>MiscVal</th>\n",
       "      <th>MoSold</th>\n",
       "      <th>YrSold</th>\n",
       "      <th>SaleType</th>\n",
       "      <th>SaleCondition</th>\n",
       "      <th>SalePrice</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1</td>\n",
       "      <td>60</td>\n",
       "      <td>RL</td>\n",
       "      <td>65.0</td>\n",
       "      <td>8450</td>\n",
       "      <td>Pave</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Reg</td>\n",
       "      <td>Lvl</td>\n",
       "      <td>AllPub</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>2008</td>\n",
       "      <td>WD</td>\n",
       "      <td>Normal</td>\n",
       "      <td>208500</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2</td>\n",
       "      <td>20</td>\n",
       "      <td>RL</td>\n",
       "      <td>80.0</td>\n",
       "      <td>9600</td>\n",
       "      <td>Pave</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Reg</td>\n",
       "      <td>Lvl</td>\n",
       "      <td>AllPub</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "      <td>5</td>\n",
       "      <td>2007</td>\n",
       "      <td>WD</td>\n",
       "      <td>Normal</td>\n",
       "      <td>181500</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>3</td>\n",
       "      <td>60</td>\n",
       "      <td>RL</td>\n",
       "      <td>68.0</td>\n",
       "      <td>11250</td>\n",
       "      <td>Pave</td>\n",
       "      <td>NaN</td>\n",
       "      <td>IR1</td>\n",
       "      <td>Lvl</td>\n",
       "      <td>AllPub</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "      <td>9</td>\n",
       "      <td>2008</td>\n",
       "      <td>WD</td>\n",
       "      <td>Normal</td>\n",
       "      <td>223500</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>4</td>\n",
       "      <td>70</td>\n",
       "      <td>RL</td>\n",
       "      <td>60.0</td>\n",
       "      <td>9550</td>\n",
       "      <td>Pave</td>\n",
       "      <td>NaN</td>\n",
       "      <td>IR1</td>\n",
       "      <td>Lvl</td>\n",
       "      <td>AllPub</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>2006</td>\n",
       "      <td>WD</td>\n",
       "      <td>Abnorml</td>\n",
       "      <td>140000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>5</td>\n",
       "      <td>60</td>\n",
       "      <td>RL</td>\n",
       "      <td>84.0</td>\n",
       "      <td>14260</td>\n",
       "      <td>Pave</td>\n",
       "      <td>NaN</td>\n",
       "      <td>IR1</td>\n",
       "      <td>Lvl</td>\n",
       "      <td>AllPub</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "      <td>12</td>\n",
       "      <td>2008</td>\n",
       "      <td>WD</td>\n",
       "      <td>Normal</td>\n",
       "      <td>250000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 81 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "   Id  MSSubClass MSZoning  LotFrontage  LotArea Street Alley LotShape  \\\n",
       "0   1          60       RL         65.0     8450   Pave   NaN      Reg   \n",
       "1   2          20       RL         80.0     9600   Pave   NaN      Reg   \n",
       "2   3          60       RL         68.0    11250   Pave   NaN      IR1   \n",
       "3   4          70       RL         60.0     9550   Pave   NaN      IR1   \n",
       "4   5          60       RL         84.0    14260   Pave   NaN      IR1   \n",
       "\n",
       "  LandContour Utilities  ... PoolArea PoolQC Fence MiscFeature MiscVal MoSold  \\\n",
       "0         Lvl    AllPub  ...        0    NaN   NaN         NaN       0      2   \n",
       "1         Lvl    AllPub  ...        0    NaN   NaN         NaN       0      5   \n",
       "2         Lvl    AllPub  ...        0    NaN   NaN         NaN       0      9   \n",
       "3         Lvl    AllPub  ...        0    NaN   NaN         NaN       0      2   \n",
       "4         Lvl    AllPub  ...        0    NaN   NaN         NaN       0     12   \n",
       "\n",
       "  YrSold  SaleType  SaleCondition  SalePrice  \n",
       "0   2008        WD         Normal     208500  \n",
       "1   2007        WD         Normal     181500  \n",
       "2   2008        WD         Normal     223500  \n",
       "3   2006        WD        Abnorml     140000  \n",
       "4   2008        WD         Normal     250000  \n",
       "\n",
       "[5 rows x 81 columns]"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# load the data and show the first 5 row\n",
    "df = pd.read_csv(\"data/train.csv\")\n",
    "df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "f9a58f39-79e1-4f2d-a745-21f7e3b1a495",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Shape (1460, 81)\n",
      "columns Index(['Id', 'MSSubClass', 'MSZoning', 'LotFrontage', 'LotArea', 'Street',\n",
      "       'Alley', 'LotShape', 'LandContour', 'Utilities', 'LotConfig',\n",
      "       'LandSlope', 'Neighborhood', 'Condition1', 'Condition2', 'BldgType',\n",
      "       'HouseStyle', 'OverallQual', 'OverallCond', 'YearBuilt', 'YearRemodAdd',\n",
      "       'RoofStyle', 'RoofMatl', 'Exterior1st', 'Exterior2nd', 'MasVnrType',\n",
      "       'MasVnrArea', 'ExterQual', 'ExterCond', 'Foundation', 'BsmtQual',\n",
      "       'BsmtCond', 'BsmtExposure', 'BsmtFinType1', 'BsmtFinSF1',\n",
      "       'BsmtFinType2', 'BsmtFinSF2', 'BsmtUnfSF', 'TotalBsmtSF', 'Heating',\n",
      "       'HeatingQC', 'CentralAir', 'Electrical', '1stFlrSF', '2ndFlrSF',\n",
      "       'LowQualFinSF', 'GrLivArea', 'BsmtFullBath', 'BsmtHalfBath', 'FullBath',\n",
      "       'HalfBath', 'BedroomAbvGr', 'KitchenAbvGr', 'KitchenQual',\n",
      "       'TotRmsAbvGrd', 'Functional', 'Fireplaces', 'FireplaceQu', 'GarageType',\n",
      "       'GarageYrBlt', 'GarageFinish', 'GarageCars', 'GarageArea', 'GarageQual',\n",
      "       'GarageCond', 'PavedDrive', 'WoodDeckSF', 'OpenPorchSF',\n",
      "       'EnclosedPorch', '3SsnPorch', 'ScreenPorch', 'PoolArea', 'PoolQC',\n",
      "       'Fence', 'MiscFeature', 'MiscVal', 'MoSold', 'YrSold', 'SaleType',\n",
      "       'SaleCondition', 'SalePrice'],\n",
      "      dtype='object')\n",
      "data types Id                 int64\n",
      "MSSubClass         int64\n",
      "MSZoning          object\n",
      "LotFrontage      float64\n",
      "LotArea            int64\n",
      "                  ...   \n",
      "MoSold             int64\n",
      "YrSold             int64\n",
      "SaleType          object\n",
      "SaleCondition     object\n",
      "SalePrice          int64\n",
      "Length: 81, dtype: object\n"
     ]
    }
   ],
   "source": [
    "# explore the data properts\n",
    "print(\"Shape\",df.shape)\n",
    "print(\"columns\", df.columns)\n",
    "print(\"data types\" , df.dtypes)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "62f92336-2d2a-4528-955a-4576bf2d9e34",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "PoolQC          1453\n",
      "MiscFeature     1406\n",
      "Alley           1369\n",
      "Fence           1179\n",
      "MasVnrType       872\n",
      "FireplaceQu      690\n",
      "LotFrontage      259\n",
      "GarageQual        81\n",
      "GarageFinish      81\n",
      "GarageType        81\n",
      "dtype: int64\n"
     ]
    }
   ],
   "source": [
    "# check missing values\n",
    "print(df.isnull().sum().sort_values(ascending=False).head(10))\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "1dbdffef-fd10-48ba-aa2d-8723ad5fac64",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Visualize Key Features"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "id": "72be7ce9-3e37-41b5-ab7d-17cd799ad6a3",
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAjsAAAHHCAYAAABZbpmkAAAAOnRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjEwLjMsIGh0dHBzOi8vbWF0cGxvdGxpYi5vcmcvZiW1igAAAAlwSFlzAAAPYQAAD2EBqD+naQAAXJNJREFUeJzt3QecU1X2B/CTMr33AjPMDL0NIE0QBQVpig3r4oqKYIFVwb+6rAVBV1xRdEUsuypYsK/SRFA6yoD03gaGYZje+2Qmyft/zs0kJsN0ZvKSl9/383mkvUnuS0Jycu6596okSZIIAAAAQKHUcjcAAAAAoD0h2AEAAABFQ7ADAAAAioZgBwAAABQNwQ4AAAAoGoIdAAAAUDQEOwAAAKBoCHYAAABA0RDsAAAAgKIh2AGQ2UsvvUQqlcoujzVq1CixmW3dulU89vfff2+Xx7///vspLi6OHFlZWRk99NBDFBkZKZ6bJ5980m6PbX49+NRRLF++XLTp/PnzcjcFoNUQ7AC0wxeDefP09KTo6GgaN24cvfPOO1RaWtomj5ORkSGCpIMHD5KjceS2Ncerr74qXsdHH32UPv/8c/rrX//a4L7V1dX073//mwYMGED+/v4UGBhIvXv3phkzZtDJkydJbhygWL8fNRoNxcbG0q233uq0rw9Aa2hb9VcA0KgFCxZQfHw81dTUUFZWlvilzhmCxYsX0+rVqykxMdGy7/PPP09///vfWxxQzJ8/X2RJ+vfv3+y/++WXX6i9Nda2//73v2Q0GsmRbd68ma688kqaN29ek/tOnjyZfv75Z7rnnnto+vTp4vXmIGft2rU0fPhw6tGjBzkCbt/EiRPJYDDQiRMn6P333xft3rVrV5PvHw727r77bvLw8LBbewHaGoIdgHYwYcIEGjRokOXy3LlzxZfojTfeSDfddJP4wvHy8hK3abVasbWniooK8vb2Jnd3d5KTm5sbObqcnBzq1atXk/vt2bNHBDX//Oc/6R//+IfNbe+++y4VFRWRo7jiiivo3nvvtVy+6qqrxPuQg54PP/yw3r8pLy8nHx8fkQ3iDcCZoRsLwE6uu+46euGFFyg1NZW++OKLRmt2fv31VxoxYoToFvH19aXu3btbvlA5SzR48GBx/oEHHrB0UXDXC+OanD59+tC+ffvommuuEUGO+W/r1uyY8S9+3ofrVPgLjr8I09LSbPbhTA3X3NRlfZ9Nta2+mh3+Un3qqacoJiZGZA/4WN944w2SJMlmP76fWbNm0cqVK8Xx8b7cZbR+/fpmBzHTpk2jiIgI0b3Yr18/+vTTTy+pl0lJSaGffvrJ0vaGalXOnj1rCRzq4uAgJCTEcplf88cee0wcGwe5fNsdd9zR7DqY3bt30/jx4ykgIEC8niNHjqTff/+dLue9yPhYrbtft23bJtoZHh5OHTt2tLmtbls5M8Tt8PPzE114/Lp/+eWX7dpugNZCZgfAjrhLgIMK7k7ibo/6HDt2TGSAuKuLu8P4Sz05OdnyJdGzZ09x/YsvvihqQ66++mpxPXebmOXn54vsEnc/8C96/oJvDGcn+Avt2WefFUHB22+/TWPGjBF1HeYMVHM0p23WOKDhwGrLli0iEOEulQ0bNtDTTz9N6enp9NZbb9ns/9tvv9EPP/wgvpD5S5broLgr6cKFCzbBRV2VlZUiIOPnkQMm7mL87rvvRPDFGZgnnnhCtJ1rdGbPni2+6DkAY2FhYfXeZ6dOncTpihUrRMDTWHaOs0A7d+4UrwffNwcOnFXhNh0/flwEAg3hjCC/lgMHDhRda2q1mpYtWyYClh07dtCQIUOopcyBWt3njJ9XPl5+/TgIbQgHQA8++KAINjlryUH5gQMHROD5l7/8pd3aDdBqEgC0mWXLlnE6QtqzZ0+D+wQEBEgDBgywXJ43b574G7O33npLXM7NzW3wPvj+eR9+vLpGjhwpbvvggw/qvY03sy1btoh9O3ToIJWUlFiu//bbb8X1//73vy3XderUSZo6dWqT99lY2/jv+X7MVq5cKfZ95ZVXbPa7/fbbJZVKJSUnJ1uu4/3c3d1trjt06JC4fsmSJVJj3n77bbHfF198YbmuurpaGjZsmOTr62tz7Ny+G264QWqK0Wi0PNcRERHSPffcIy1dulRKTU29ZN+KiopLrktKShJ/+9lnn13yevCp+TG6du0qjRs3Tpy3vr/4+Hjp+uuvb7SNKSkp4v7mz58v3k9ZWVnS1q1bxfuPr//f//5n874dMWKEpNfrbe7DfBvfFysqKpL8/PykoUOHSpWVlZc8J23RboC2hm4sADvjbqnGRmXxr2S2atWqVhfzcjaIu5Ga67777hOZErPbb7+doqKiaN26ddSe+P65y+fxxx+3uZ6zKhzfcFeJNc42de7c2XKZs1/chXLu3LkmH4e76LhQ17p+iB+Xh5pz901LcSaMs1CvvPIKBQUF0VdffUUzZ84UGZ+77rrLpmbHOjvGRcyceevSpYt4rffv39/gY3Bm7cyZMyJbwn+Tl5cnNs66jB49mrZv396s9whnVjhjw88BZ5M4s/Ovf/2LbrvtNpv9ONvYVH0Od7Hy+5eL6rk7sO5z0pbtBmgr6MYCsDP+cuWaiIbwF+VHH30k5nrhLxT+cuAvJQ5AuCugOTp06NCiYuSuXbte8qXFX8btPbcK17Lw0HzrQItxl5L5dms8bLouDjQKCwubfBw+xrrPX0OP05Kg8rnnnhNbZmamCJp4KPq3334rgilzbRZ3oy1cuFB043D3nHU9UnFxcYP3zwEDmzp1aoP78N/zc9AY7lLkGiE+fvPw+PpGV3H3XnO7wLhuqr3bDdBWEOwA2NHFixfFhzwHEg3hLAD/8uU6Fi6U5TqIb775RtQ6cK1Pc0bGtKTOprkamviQi5vtNVqnocepW8wsB86EcU0O1xBxMMEBD9e2cC3P3/72NxHo8PQDw4YNEwW7/Hzy/o1lOMy3LVq0qMEh4pwpbAoHepwVs9f7pq3aDdBWEOwA2BEXwDKeZLAx/AucMzq88dw8PNEdZw84AOIvrbaecdn8S9w6eOBiXuv5gPhXeH3DqTkrkpCQYLnckrZxl8/GjRtFt4h1dsc8IZ+5CPhy8f0cPnxYfAlbZ3fa+nEYZ3T4eePnlLtuuOuIZ6jmLMebb75p2a+qqqrJ4enmLjvuqmtOsGIP5jYdPXq0waDdEdsNrg01OwB2wqNTXn75ZdFVMGXKlAb3KygouOQ6869jnU4nTnl4OGuruVw+++wzmzoi/nLmbhkeTWP9BcaT0PGswWY8z0zdIeotaZt5ojuel8Yaj8LioMn68S8HPw5P7sgZMjO9Xk9LliwRGQYeEt1SHMzwKLC6+LiTkpJEcGgeycUZqbrZJ35sPvbG8Egmft55KD53f9aVm5tL9jZ27FgRmHK3HAds1szH6IjtBteGzA5AO+DCWs4a8Bdqdna2CHS4sJMzCDyDct3CTms8dJu7sW644QaxPw8Ff++998SQZZ57h/EXCddefPDBB+KLhwOMoUOHNqvmoj7BwcHivrmomdvLQ8/5V7v18HiuIeIgiOdNufPOO0XtBtekWBcMt7RtkyZNomuvvVZkrbg+iOe+4a46Ls7mLp+6991aXLPCk+fxUHOef4jn+uFj4eH8fKx1a4aa49ChQ6IAlwMyHmLPzyHX4/DcPTyLNN+vuduNpxLgrB53X/GEhRwMcUarseHyjLNQXL/Fj8FdY/z6cD0WPw5n+ThzsmbNGrInfkwORvn9wHPr8HPAgR0/Hzx5JR+/I7YbXFybj+8CcGHmYbrmjYdKR0ZGiqG2PIzbeohzQ0PPN23aJN18881SdHS0+Hs+5WHNp0+ftvm7VatWSb169ZK0Wq3NUG8eDt27d+9629fQ0POvvvpKmjt3rhQeHi55eXmJodf1DaF+8803xTB1Dw8P6aqrrpL27t17yX021ra6Q89ZaWmpNHv2bHGcbm5uYsjyokWLbIYsM76fmTNnXtKmhobE15WdnS098MADUmhoqHhe+/btW+/w+OYOPef7e+2118SxR0VFiWMNCgqSrrvuOun777+32bewsNDy2DzUnYdknzx58pK21x16bnbgwAHptttuk0JCQsRzz3935513ivdKc4ae8/PZ2ikT6g49N1u9erU0fPhw8X7x9/eXhgwZIt5HbdFugLam4n/kDrgAAAAA2gtqdgAAAEDREOwAAACAoiHYAQAAAEVDsAMAAACKhmAHAAAAFA3BDgAAACgaJhWsXceFJwHjicXaehp+AAAAaB88ew7P/s4LCje2UDKCHSIR6MTExMjdDAAAAGgFXraGZ5lvCIIdIstU8fxk8TTmAAAA4PhKSkpEsqKpJV8Q7Fit0syBDoIdAAAA59JUCQoKlAEAAEDREOwAAACAoiHYAQAAAEVDsAMAAACKhmAHAAAAFA3BDgAAACgagh0AAABQNAQ7AAAAoGgIdgAAAEDREOwAAACAoiHYAQAAAEVDsAMAAACKhmAHAAAAFA3BDgAAACiarMHO9u3badKkSRQdHS2WZ1+5cqXN7XxdfduiRYss+8TFxV1y+2uvvSbD0QAAAIAj0sr54OXl5dSvXz968MEH6bbbbrvk9szMTJvLP//8M02bNo0mT55sc/2CBQto+vTplst+fn7t2Gow69WnL2VkZDS5Hwezx48esUubAAAAHCrYmTBhgtgaEhkZaXN51apVdO2111JCQoLN9Rzc1N0X2h8HOvO+SWpyv/l3DbNLewAAAJy6Zic7O5t++uknkdmpi7utQkJCaMCAAaKLS6/Xy9JGAAAAcDyyZnZa4tNPPxUZnLrdXY8//jhdccUVFBwcTDt37qS5c+eK7q/Fixc3eF86nU5sZiUlJe3adgAAAJCP0wQ7n3zyCU2ZMoU8PT1trp8zZ47lfGJiIrm7u9PDDz9MCxcuJA8Pj3rvi2+bP39+u7cZAAAA5OcU3Vg7duygU6dO0UMPPdTkvkOHDhXdWOfPn29wH87+FBcXW7a0tLQ2bjEAAAA4CqfI7Hz88cc0cOBAMXKrKQcPHiS1Wk3h4eEN7sMZn4ayPgAAAKAssgY7ZWVllJycbLmckpIighWuv4mNjbXU03z33Xf05ptvXvL3SUlJtHv3bjFCi+t5+PLs2bPp3nvvpaCgILseCwAAADgmWYOdvXv3ikClbv3N1KlTafny5eL8119/TZIk0T333HPJ33N2hm9/6aWXRMFxfHy8CHas63gAAADAtakkjiRcHGePAgICRP2Ov7+/3M1xGoHBIc2eZ6eoIN8ubQIAANdR0szvb6coUAYAAABoLQQ7AAAAoGhOMRoLnBsXonOXV2OwfhYAALQXBDvQ7oxGY5O1PVg/CwAA2gu6sQAAAEDREOwAAACAoiHYAQAAAEVDsAMAAACKhmAHAAAAFA3BDgAAACgagh0AAABQNAQ7AAAAoGgIdgAAAEDREOwAAACAoiHYAQAAAEVDsAMAAACKhmAHAAAAFA3BDgAAACgagh0AAABQNAQ7AAAAoGgIdgAAAEDREOwAAACAoiHYAQAAAEVDsAMAAACKhmAHAAAAFA3BDgAAACgagh0AAABQNAQ7AAAAoGgIdgAAAEDREOwAAACAoiHYAQAAAEVDsAMAAACKhmAHAAAAFA3BDgAAACgagh0AAABQNAQ70P40WjIYJblbAQAALkordwNA2bJLqqjDwx/Re1uTKcTXg2KDvenKhGDSqhFnAwCAfSDYgXaTUVRJqw5mkMY7kDixk1uqE1tFtZ6u7xlBKpVK7iYCAIALwM9raBd5ZTpaeTCdqg1Gqko7SvcOjaXreoQTxzcnMktp34VCuZsIAAAuQtZgZ/v27TRp0iSKjo4Wv/JXrlxpc/v9998vrrfexo8fb7NPQUEBTZkyhfz9/SkwMJCmTZtGZWVldj4SqGt3SgHVGCTqEOhFuf9bILqw+nYIoJFdw8TtvyfnU2p+udzNBAAAFyBrsFNeXk79+vWjpUuXNrgPBzeZmZmW7auvvrK5nQOdY8eO0a+//kpr164VAdSMGTPs0HpoSHFlDZ3NMQWcI7uFkaSvttyW2DGA+kT7WwIeSULhMgAAKLhmZ8KECWJrjIeHB0VGRtZ724kTJ2j9+vW0Z88eGjRokLhuyZIlNHHiRHrjjTdExgjs7+CFIuIQhouRw/w8bG7j7NzwLqF0KruUcst0dC6vnDqH+crWVgAAUD6Hr9nZunUrhYeHU/fu3enRRx+l/Px8y21JSUmi68oc6LAxY8aQWq2m3bt3N3ifOp2OSkpKbDZoG1U1BjqWWSzOXxEbWO8+Xm4a6h9jum3XOWR3AADAhYMd7sL67LPPaNOmTfSvf/2Ltm3bJjJBBoNB3J6VlSUCIWtarZaCg4PFbQ1ZuHAhBQQEWLaYmJh2PxZXcTS9WNTqhPi6i8xOQ66IDSJ3jZryyqrpbC5qdwAAwEWHnt99992W83379qXExETq3LmzyPaMHj261fc7d+5cmjNnjuUyZ3YQ8LSN07W1Ov07BjY6tNyzNrvzx/kC2peKkVkAAOCimZ26EhISKDQ0lJKTk8VlruXJycmx2Uev14sRWg3V+ZjrgHj0lvUGl69cpxfz6LD4UJ8m9+8XE0BqFVFWSRWpgzraoYUAAOCKnCrYuXjxoqjZiYqKEpeHDRtGRUVFtG/fPss+mzdvJqPRSEOHDpWxpa4pNb9CnIb7eZCPR9NJQ293rSUo8ugxst3bBwAArknWbiyeD8ecpWEpKSl08OBBUXPD2/z582ny5MkiS3P27Fl65plnqEuXLjRu3Dixf8+ePUVdz/Tp0+mDDz6gmpoamjVrluj+wkgs+ztfO29OXEjTWR2zPtEBombHretVpNMbyEOraccWAgCAK5I1s7N3714aMGCA2BjX0fD5F198kTQaDR0+fJhuuukm6tatm5gscODAgbRjxw7RDWW2YsUK6tGjh6jh4SHnI0aMoP/85z8yHpVrMholulBgyuzEhTZcmFxXbIg3+XpoSe3pS78cy27HFgIAgKuSNbMzatSoRocdb9iwocn74AzQl19+2cYtg5bKLKkind5Inlo1Rfh7Nvvv1CoV9YryF4XK3+xJo0n9kJEDAAAXrtkBx2Ve+oEzNRzAtETv2hmVf0vOo8ziynZpHwAAuC4EO9AmztcWJ8e3oF7HzN/LjfRZp8X5dUcanh8JAACgNRDswGXjwmLzkPOYRiYSbEz1WdOM1z8dzmjTtgEAADj0pILgHHJKTIGOv6e2WUPO61OTsodUI/5K+y8UUXpRpVgtva5effpSRkbjwRCPwjt+9Eir2gAAAMqEYAcuG08KyFpSmFyXVFFEg+OC6Y+UAlp3OJOmX5NwyT4c6Mz7JqnR+5l/17BWtwEAAJQJ3Vhw2bJrg53IgNYHO2xSommyyLXoygIAgDaEYAcuC08dkFV8+ZkdNr5PlFg+4tDFYkqrnbMHAADgciHYgctSptNTebWBeLQ5LxNxOcL8PGhofIg4v+EYRmUBAEDbQLADbVKvE+rjQW6ay387Xd8rQpxuPIHZlAEAoG0g2IHLkl1sGokVEXB5WR2zMT1Nwc6e84VUVFHdJvcJAACuDcEOtElmJ/Iy63XMeAbm7hF+ZDBKtPVUbpvcJwAAuDYEO9B6KhXllLZtsMPG9AoXp7+iKwsAANoAgh1oNXVgNNUYJHLTqCjIx73N7tfclbXtVC5V641tdr8AAOCaEOxAq2mCY8VpqK9Hixf/bEy/joHiPnmk1+6U/Da7XwAAcE0IdqDVNMEdxSkHJm1JrVbRmJ6mrqyNx9GVBQAAlwfBDlx2sBPShl1YdbuyNp7IERMXAgAAtBaCHXC4zA4b0TWUPN3UYlHQE5mlbX7/AADgOhDsQKuUVtWQ2i9MnA/xbfvMjqebhq7uarr/X9GVBQAAlwHBDrTK6ewycerjoRGBSXu43tKVhWAHAABaD8EOtMrp7FLLMhHt5doe4WLNrSPpxZRZXNlujwMAAMqGYAda5VRWabt1YVkvDDogJlCc33Qip90eBwAAlA3BDlxmsNN+mR02BguDAgDAZUKwAy3GQ8FP1XZjtcewc2uje5iCnaSz+UQat3Z9LAAAUCYEO9BieWXVVFBeTZLR2O7BTrcIX4oK8CSd3kjaqB7t+lgAAKBMCHag1V1YxpJs0mra9y2kUqloZDfTEHS3mMR2fSwAAFAmBDvQYuYuLEPhRbs83qjupmBHG9PXLo8HAADKgmAHWuxsrmmOHWNhhl0eb3iXUNKoVaQJjKbiyhq7PCYAACgHgh1osXO1wY6hONMuj+fv6UYDY4PE+dT8crs8JgAAKAeCHWixc7mmgMNYlGW3xxxZ25WVml9ht8cEAABlQLADLVKm01NOqU6cNxbbMdipLVJOK6wggxGroAMAQPMh2IEWSanN6oT6upNUbb8sS68ofzJWFFGNQaKMIiwdAQAAzYdgB1rkXJ6pXich1Neuj6tWq0h/8ag4n1qAriwAAGg+BDvQImdrMzsJYT52f+yatMPi9DyKlAEAoAUQ7ECrRmLJEeyYMzv5ZdVUVqW3++MDAIBzQrADLZKSZ8qqxNu5G4tJujKK9PcU51MLkN0BAIDm0TZzPwCxAKg52GnrzE5ZWRkFBoc0uk9paRl1CvGmrJIqMQS9d3RAm7YBAACUCcEONBsHGRXVBtKqVRQb7N2m9200GmneN0mN7vPUhN4i2NmdUkAXCirIaJRE4TIAAEBj0I0FLZ5MkAMdt3ZeALQhEf6e5KlVi1XQOfgCAABoCoIdcIriZDO16s+sEmd3AAAAHDrY2b59O02aNImio6NJpVLRypUrLbfV1NTQs88+S3379iUfHx+xz3333UcZGbaLT8bFxYm/td5ee+01GY7GdYadx4fKF+ywmNpgJw3BDgAAOHqwU15eTv369aOlS5decltFRQXt37+fXnjhBXH6ww8/0KlTp+imm266ZN8FCxZQZmamZfvb3/5mpyNwLX8WJ9t/JFZ9wQ53Y1XrjbK2BQAAHJ+sBcoTJkwQW30CAgLo119/tbnu3XffpSFDhtCFCxcoNjbWcr2fnx9FRka2e3tdnXnF8bgQeTM7AV5uYiuurKH0okrZM00AAODYnKpmp7i4WHRTBQYG2lzP3VYhISE0YMAAWrRoEen1jU84p9PpqKSkxGaDxukNRrpYaFqTikdEyS0myEucoisLAAAUM/S8qqpK1PDcc8895O/vb7n+8ccfpyuuuIKCg4Np586dNHfuXNGVtXjx4gbva+HChTR//nw7tdw59erT16Y+Su0XRv73vEmSvpp6JcTwrDti3hs5u7KOZpTQhUIEOwAAoIBgh4uV77zzTjGp3fvvv29z25w5cyznExMTyd3dnR5++GER0Hh4eNR7fxwQWf8dZ3ZiYvgLHMw40LGe94a7sFYezKAQf1968pudlnlv5BIT5G1ZOqJcpycfD6d4KwMAgAzUzhLopKamihoe66xOfYYOHSq6sc6fP9/gPhwE8f1Yb9A4ro9hAd5u5Ai83DUU5msKZs3dawAAAE4X7JgDnTNnztDGjRtFXU5TDh48SGq1msLDw+3SRpcLdrwcI9hhMcGmuh3MtwMAAI2RNffP6yElJydbLqekpIhghetvoqKi6PbbbxfDzteuXUsGg4GysrLEfnw7d1clJSXR7t276dprrxUjsvjy7Nmz6d5776WgoCAZj0x5iipMwU6gAwU7HYO8af+FIjEiCwAAwCGDnb1794pAxcxcRzN16lR66aWXaPXq1eJy//79bf5uy5YtNGrUKNEd9fXXX4t9eYRVfHy8CHas63FAmd1YLDrQk1S1bSutqiE/T8dpGwAAOA5Zgx0OWLjouCGN3cZ4FNauXbvaoWVQ93UwBzuOlNnx0Goo3N+Dskt0lF5YST2iHKdtAADgOBy6ZgccQ3m1gfRGiVQqcrjsScdA06isi+jKAgCABiDYgSYV19br+Hu6kUbNHUeOo0Pt5IIYkQUAAA1BsANNKqqsdriRWA3V7QAAANSFYAeccth53bodxnU7AAAAdSHYgWZ3YwU60Egsa6jbAQCAxiDYgSYVOXBmh6FuBwAAGoNgB5rkiMPO69btmNup8sLSHwAAYAvBDjSqqsZAOr1RnPd30GCH63ZCfN3FeW1EN7mbAwAADgbBDjQrq+PtriE3jeO+XaIDTF1ZmsiucjcFAAAcjON+e4FDKHHweh2z6ABTV5Y2AsEOAADYQrADjSqp0jt0F5ZZVGBtZic0TnS9AQAAmCHYgebNseNgy0TU5e+pJR93Dak0WjqUViR3cwAAwIEg2IFmdWP5e8m6ZmyTVCqVJbuzN7VQ7uYAAIADQbADTjt7ckN1O3vPF8jdFAAAcCAIdqBBkiRRqblmx8G7sZg5s7MvtZCMRknu5gAAgINAsAMNKtPpySBJxAud+3o6djcWC/P1IKlGJ4qqk3PL5G4OAAA4CAQ70KCSSlNWx8/TjdQqXlvcsWnUKtLnnhXn955H3Q4AAJgg2IEGFVc5R3GyNUPWGXG6NxV1OwAAYIJgB5x+2Lk1ffYZS90OAAAAQ7ADzRh27jzBjiE7mbjHLTW/gnJLdXI3BwAAHACCHXD6pSKsSdUV1C3cT5zfh64sAABAsAPNq9lxnmCHDYwLEqcoUgYAAIZgB+qncaNyncHpanbYoE61wQ7qdgAAAMEONETtGypO3TVq8nRzrrfJoE7B4vRYRjEWBQUAAAQ7UD+1f5hl2DmvO+VMYoK9KMzPg2oMEhYFBQAABDtQP7VfmNMVJ5txcGbuytp3AV1ZAACuDsEONBrsOMOaWPUZEBsoTg9eQGYHAMDVIdiBJrqxnDXYMWV2DqQViQVNAQDAdSHYgXqp/cKdthuL9YkOIK1aJSYWTC+qlLs5AAAgIwQ7UC+Nn2k0lr8TrHZeHy93DfWM8hfnD6JIGQDApSHYgUsUV9SQysPHqbuxrOt2DqBuBwDApSHYgUtcKKgQp97uGnLTqBUQ7GBEFgCAK3PebzJoN2mFFU5dr2PWP8ZUpHw0o4R0ekwuCADgqhDsQIOZHWfuwmJxId4U6O1G1Xojncgslbs5AAAgEwQ7cIm02mDH2dbEqm9ywQEx6MoCAHB1CHbgEmmFlZalIpydZb4dFCkDALgsBDvQcGbHybuxbGZSxvBzAACX5fw/3aFNGYwSpZszO07YjVVWVkaBwSF/XuHmRQH3vy/qkIKi40iqKqXo6Gg6fvSInM0EAAA7QrADNrJLqqjaYCTJqCdfJ5xQ0Gg00rxvkmyu+3xXKhWUV9O9b/xACWG+NP+uYbK1DwAAnKQbKyEhgfLz8y+5vqioSNzWXNu3b6dJkyaJX9pcTLpy5Uqb23lNoxdffJGioqLIy8uLxowZQ2fOnLHZp6CggKZMmUL+/v4UGBhI06ZNE7/u4fK6sIyl+aRWqUgJIv09xWlWSZXcTQEAAGcJds6fP08Gw6Xzluh0OkpPT2/2/ZSXl1O/fv1o6dKl9d7++uuv0zvvvEMffPAB7d69m3x8fGjcuHFUVfXnlxYHOseOHaNff/2V1q5dKwKoGTNmtOawwKo42ViaQ0oRGWAKdjKLEewAALiiFvVTrF692nJ+w4YNFBAQYLnMwc+mTZsoLi6u2fc3YcIEsdWHszpvv/02Pf/883TzzTeL6z777DOKiIgQGaC7776bTpw4QevXr6c9e/bQoEGDxD5LliyhiRMn0htvvCEyRtC6OXaMpbmkFObMDnfRGbECOgCAy2lRsHPLLbeIU+5ymjp1qs1tbm5uItB5880326RhKSkplJWVJbquzDi4Gjp0KCUlJYlgh0+568oc6DDeX61Wi0zQrbfeWu99cwaKN7OSkpI2abMSXDQHOyV5pBQhvu7kplFRjUEStTsAAOBatC0t/mTx8fEimxIaaloZuz1woMM4k2ONL5tv49Pw8HCb27VaLQUHB1v2qc/ChQtp/vz57dJu5WR2lNONxbVHEf6edLGwkrLQlQUA4HLUrc26tGeg097mzp1LxcXFli0tLU3uJjnculhK6sZiKFIGAHBdrR5bzPU5vOXk5FgyPmaffPLJZTcsMjJSnGZnZ4vRWGZ8uX///pZ9+PGt6fV6MULL/Pf18fDwEBvYqqoxUHaJqXvPWKKsYCeqtkgZmR0AANfTqswOdwGNHTtWBDt5eXlUWFhos7UF7irjgIUfw7q2hmtxhg0zzZPCpzzcfd++fZZ9Nm/eLIIvru2BluFuHubroSVJp6zh+9yNxfK5ZsfNS+7mAACAo2d2eCj48uXL6a9//etlPTjPh5OcnGzTPXbw4EFRcxMbG0tPPvkkvfLKK9S1a1cR/LzwwgtihJW5ULpnz540fvx4mj59umhTTU0NzZo1SxQvYyRW67uwOgZ50UVSFh8PLfl7aqmkSk/a8ObPBQUAAC4a7FRXV9Pw4cMv+8H37t1L1157reXynDlzxCmP9OJg6plnnhFz8fC8OZzBGTFihBhq7ulp+pXOVqxYIQKc0aNHi1FYkydPFnPzQOsnFIwN9qZdpDw8305JVRlpwjvL3RQAAHD0YOehhx6iL7/8UmRaLseoUaPEfDoN4SHuCxYsEFtDOAvEbYG2C3Zigr1JibhI+XR2GWnDu8jdFAAAcPRgh2cw/s9//kMbN26kxMREMceOtcWLF7dV+8CO0goqLZkdJYoKMNXqaMITRJDNwTQAAChfq4Kdw4cPW0ZEHT161OY2fIE4/xw7McHKLOAN9XMnDb8/vfzFsXYK8ZG7SQAA4KjBzpYtW9q+JSArznRYurGClJnZ0arVFObnIebaOXChCMEOAICLaNXQc1Ce4soaKtXpxfmOCg12rBcFPXChbaZIAAAAhWZ2eARVY91VPNcNOGe9Dmc+vNw1pFQ8ueDBNKIDaUVyNwUAAOykVcGOuV7HjOe34flxuH6n7gKh4Fxz7Ci1OLnushHHM0rEjNGebsoN7AAA4DKCnbfeeqve61966SUxUSA4cXFykDKLk838PLVkrCgivXcgHU0vpkFxwXI3CQAAnKlm5957722TdbHA/pQ+x44Zd78acs6K81ykDAAAytemwU5SUpLN7MbgPNJq18VSerDD9NmmYOcg6nYAAFxCq7qxbrvttkuGLWdmZorlHy53VmWQx4X8ckUPO7dmyDGtx4YRWQAArqFVwU5AQIDNZV6Tqnv37mJZB14NHZyL3mC0rHjeKUT5wY4+N4XUKqKM4irKKq6yDEcHAABlalWws2zZsrZvCcgms7iK9EaJ3LVqy2glRdPrqHukP53ILKGDaYU0PiBK7hYBAICjBTtm+/btoxMnTojzvXv3pgEDBrRVu8COUvP/HIml5pSHCxgQGyiCHS5SHt8HwQ4AgJK1KtjJycmhu+++m7Zu3UqBgYHiuqKiIjHZ4Ndff01hYWFt3U5oR6kFpnodV1o+YUBMIH25+wJGZAEAuIBWjcb629/+RqWlpXTs2DEqKCgQG08oWFJSQo8//njbtxLsMseO0icUrJvZYYfTi6jGYJS7OQAA4GiZnfXr19PGjRupZ8+elut69epFS5cuRYGyE7pQ243lCsXJZgmhvmKCwdIqPZ3KKqU+HWyL7gEAwMUzO0ajkdzc3C65nq/j28A5a3ZcKdjh2qT+MabsDoagAwAoW6uCneuuu46eeOIJysjIsFyXnp5Os2fPptGjR7dl+6Cd8RxJf3ZjuU7NDhvYKUic7jmPYAcAQMlaFey8++67oj4nLi6OOnfuLLb4+Hhx3ZIlS9q+ldBuCsqrqUynJ17EvqPC18Wqa0jtulh7zheIoA8AAJSpVTU7MTExtH//flG3c/LkSXEd1++MGTOmrdsH7Sy1NqvD8+u42grgA2KDSKtWiXmGeFJFV1gqAwDAFbUos7N582ZRiMwZHF5Q8frrrxcjs3gbPHiwmGtnx44d7ddaaLfiZFcaiWXm5a6xFCZzdgcAAJSpRcHO22+/TdOnTyd/f/96l5B4+OGHafHixW3ZPmhnrlicbG1I/J9dWQAAoEwtCnYOHTpE48ePb/B2HnbOsyqD83DFCQWtDa6t2/kjBcEOAIBStSjYyc7OrnfIuZlWq6Xc3Ny2aBfYiSt3Y7FBtSOyzuaWU36ZTu7mAACA3MFOhw4dxEzJDTl8+DBFRWGdIWcsUHbVbqwgH3fqFuErzmMIOgCAMrUo2Jk4cSK98MILVFVVdcltlZWVNG/ePLrxxhvbsn3Qjiqq9ZRbaspmdHKxOXasoSsLAEDZWjT0/Pnnn6cffviBunXrRrNmzaLu3buL63n4OS8VYTAY6LnnnmuvtkIbM08mGODlRgHeDXdPukKR8ordF2h3Sr7cTQEAALmDnYiICNq5cyc9+uijNHfuXMtEbDwMfdy4cSLg4X3AObjimlj1GZYQIk6PZ5ZQUUU1BXq7y90kAACQc1LBTp060bp166iwsJCSk5NFwNO1a1cKCjIVeoLzcMXVzusT7u9JXcJ9KTmnjHadK6DxfSLlbhIAAMg9gzLj4IYnEgTnn2PH1YMdNrxziAh2ks7mIdgBAFCYVq2NBcrg6iOx6gY77PezqNsBAFAaBDsu7EJ+uUuudl6fofEhYjFUzu7klFw62hAAAJwXgh0XpTcYxeKXDJkd03w7vaJMy6AknUN2BwBASRDsuChe6VtvlMhdqxYrngPRVV1CxenOZAQ7AABKgmDHxYuTY4K8SK1Wyd0chzDMUreTJ3dTAACgDSHYcVGuvgBofYbEBZObRiW691LyTM8PAAA4PwQ7LsrVFwCtj4+HlgZ1Mi0dsfVUjtzNAQCANoJgx8W7sVCcbGtU9zBxuvVUrtxNAQAAVwl24uLixHIUdbeZM2eK20eNGnXJbY888ojczXZ4mGOnfqO6h4vTXefyqarGIHdzAABAzhmU7WXPnj1igVGzo0eP0vXXX0933HGH5brp06fTggULLJe9vfEF3hhe4uPPOXbwXFnrFuFLUQGeYrQaD0G/tjb4AQAA5+XwmZ2wsDCKjIy0bGvXrqXOnTvTyJEjbYIb6338/U3zpUD9CsqrqbzaICbR6xiEYMcaZwbNXVnb0JUFAKAIDh/sWKuurqYvvviCHnzwQfGlZLZixQoKDQ2lPn36iNXYKypMXTTQeBcWz6/j6aaRuzkOZ2Q3UzZn22kEOwAASuDw3VjWVq5cSUVFRXT//fdbrvvLX/4iVmKPjo6mw4cP07PPPkunTp2iH374ocH70el0YjMrKSkhV5KKLqxGXdUlhLRqlRh+fj6vnOJCMTwfAMCZOVWw8/HHH9OECRNEYGM2Y8YMy/m+fftSVFQUjR49ms6ePSu6u+qzcOFCmj9/PrmqlDxTZichDF/i9fHzdKMh8cG082w+bTyRTQ9dnSB3kwAAwBW6sVJTU2njxo300EMPNbrf0KFDxWlycnKD+3BXV3FxsWVLS0sjV2KeMC8eGYsGje0VIU43HMuSuykAAOAqwc6yZcsoPDycbrjhhkb3O3jwoDjlDE9DPDw8RBGz9eZKUvLKxGkcZk9u0NjekeJ0b2oh5Zb+2eUJAADOxymCHaPRKIKdqVOnklb7Z88bd1W9/PLLtG/fPjp//jytXr2a7rvvPrrmmmsoMTFR1jY78rDz8+jGalJ0oBcldgwgSSLRlQUAAM7LKYId7r66cOGCGIVlzd3dXdw2duxY6tGjBz311FM0efJkWrNmjWxtdXS5ZToq0+mJ1/6MQYFyo8bVZnfQlQUA4NycokCZgxnOSNQVExND27Ztk6VNzsqc1ekQ5EUeWgw7b8y43hG0aMMp+j05j0qqasjf003uJgEAgFIzO9D29Trxob5yN8XhdQn3E119NQaJtpzEwqAAAM4KwY6LDjuPx5pYzTK+tivrp8OZcjcFAABaCcGOy2Z2UJzcHDf1j7asgl5cWSN3cwAAoBUQ7LhozQ5mBW6eHpH+1D3Cj6oNRtpwFIXKAADOCMGOCzEaJUqpXSoiwYVrdsrKyigwOKTJrVefvjbZnVWH0mVuOQAAKHY0FrSNjOJKqtYbyU2jouhAT3JVPG/TvG+Smtxv/l3DxOlN/aLFqCxePiKnpIrC/V33uQMAcEbI7LhgFxYvAKrV4KVvLp6PaGCnIDHB4BoUKgMAOB1847kQDDtvvZtru7J+PHDR5nru6mpudxgAAMgD3ViuOOw8FMPOW+rGxGh6ee1xOppeQsczSqhXtGk9tYyMjCa7xMzdYQAAIA9kdhSmsUzDh1+tFPt8uvQNuZvpdIJ93On62pXQv92bJndzAACgBZDZUZjGMg3Lfk+hkio95Z8/Yfd2KcGdg2Jo3ZEs+vFAOv19Qg/ydMNyGwAAzgDBjovQG4wi0GGl6cki09OY0lJTfQ/86equYRQd4EkZxVX06/FsmtTPVMcDAACODcGOiyisMM3+66lVk768iOb9fKzR/Z+a0NtOLXMeGrWKbh/Ykd7ZnCy6shDsAAA4BwQ7LqKwolqcBvm4y90Up5t80JraL5T871lM20/nUHCnnsiAAQA4AQQ7LqKwvDbY8Uawc7mTD648mE6p+RU08pmPaNUTo2RpGwAANB9GY7mIAktmx03upji9/h0DxemxzBJSuWE2ZQAAR4dgx8VqdoKR2blsnUK8KdDLTSy94dMLmR0AAEeHYMcFSJL0ZzcWanYum0qlon4xpuyO3xU3iOcXAAAcF4IdF1Cm05PeKJFaReTviW6sttAzyk8sqOoWEkNphZVyNwcAABqBYMcFFNRmdQK83MTwabh8HloN9YoyLRlxKK1I7uYAAEAjEOy4Ur0OurDaVL/aQuVzeeVUXGl6jgEAwPEg2HEBGHbePrj+qTLlgDh/+CKyOwAAjgrBjksNO0ew09ZKD6wVp8cySqjGYJS7OQAAUA8EOy6V2UFxclurOrdf1ELp9EY6kVkid3MAAKAeCHYUrqrGQOXVBnEeNTvtQaJ+HQPEuQNpRWTEMHQAAIeDYMdFRmL5emjFCCJoe72jA8hDq6aiiho6l1sud3MAAKAOBDsuEuyEIKvTbty1akqsze7sSy3EJIMAAA4GwY7C5dcGO+jCav9h6DyHUVZJFWUUVcndHAAAsIJgx0UyO8G+CHbak4+HlnpG+onz+y4Uyt0cAACwgmBH4dCNZT9XdAoSpyl55ZRfppO7OQAAUAvBjoLpagxiXSyGbqz2x5M2dg7zEeeR3QEAcBwIdlxgMkGMxLKfQZ2CxemprFIqrcISEgAAjgDBjoLll6E42d4iAzypQ6AXGSWig1ggFADAISDYcYXiZAQ7djWwtnbnaHqJ6EoEAAB5IdhRMBQnyyMuxFs859UGIx26WCx3cwAAXB6CHQXDHDvyUKlUNCjOlN0RXVlaPP8AAHJCsKNQOv2fI7GQ2bG/buF+YoHQyhoDefS4Vu7mAAC4NAQ7Ci9OFiOx3DASy97UapWldscjcYIIPgEAQB4IdhQe7IRg5mTZ9IzyIx8PDal9g+nH/elyNwcAwGU5dLDz0ksvifoH661Hjx6W26uqqmjmzJkUEhJCvr6+NHnyZMrOzpa1zY4ir3YG31BfD7mb4rK0ajVdEWvK7ry/7SzpDUa5mwQA4JIcOthhvXv3pszMTMv222+/WW6bPXs2rVmzhr777jvatm0bZWRk0G233SZrex1FXrk52EFmR059OwSQsaqUUvMr6KcjmXI3BwDAJWnJwWm1WoqMjLzk+uLiYvr444/pyy+/pOuuu05ct2zZMurZsyft2rWLrrzySnJVkiRRnrkbyweZHTm5adSkO7KBvAbfTu9tOUuTEqNFPQ8AANiPw2d2zpw5Q9HR0ZSQkEBTpkyhCxcuiOv37dtHNTU1NGbMGMu+3MUVGxtLSUlJjd6nTqejkpISm01JeBRWtd5I/J2KYefyqz62URSKn8oupU0nc+RuDgCAy3HoYGfo0KG0fPlyWr9+Pb3//vuUkpJCV199NZWWllJWVha5u7tTYGCgzd9ERESI2xqzcOFCCggIsGwxMTGkJOasDi9MqUEWQXZSdQXde2UncX7J5jMi8wYAAPbj0MHOhAkT6I477qDExEQaN24crVu3joqKiujbb7+9rPudO3eu6AYzb2lpaaTE4mSMxHIcD10dT15uGjp8sZi2nEJ2BwDAnhw62KmLszjdunWj5ORkUcdTXV0tgh9rPBqrvhofax4eHuTv72+zKQlGYjkefi3uG2bK7ry9EdkdAAB7cqpgp6ysjM6ePUtRUVE0cOBAcnNzo02bNlluP3XqlKjpGTZsGLky8xw7CHYcy4xrEizZnc2o3QEAsBuHDnb+7//+TwwpP3/+PO3cuZNuvfVW0mg0dM8994ham2nTptGcOXNoy5YtomD5gQceEIGOK4/EIrWWCivMwQ66sRxJCGd3hiO7AwBgbw499PzixYsisMnPz6ewsDAaMWKEGFbO59lbb71FarVaTCbII6y4rue9994jV6YOjCKjROSuVYsRQOBYZlydQJ8npdKR9GLadCKHxvSKkLtJAACK59Dfhl9//XWjt3t6etLSpUvFBiaaYNPIslAfdzHjNDhgdmdYHH2w7Sy9vek0je4ZjtcJAMCVu7Gg5TShpm6SMD/U6zhy7Y63u4aOppfQxhOo3QEAaG8IdhRGE4Jgx9HxRI9Th8eJ829vPI3aHQCAdoZgR0H4SxOZHecw/eoE8nHX0LGMElp/tPFJMAEA4PIg2FGQi4WVpPbwEctEYE0sx8/uTBsRL84v2nAKK6IDALQjBDsKwlkCxoEOlolwfNOvSRBBz7m8cvp270W5mwMAoFgIdhTkeEaxOEUXlnPw83SjWdd2sdTuVFYb5G4SAIAiIdhRYGYHwY7zmHJlLHUM8qKcUh198nuK3M0BAFAkBDsKgmDH+XhoNfTU2G7iPM+9U1humv0aAADaDoIdhcgv01FWSRVJkpHCsCaWU7m5XwfqEelHpVV6em9rstzNAQBQHAQ7CnE805TVMRbniKUiwHmo1Sp6dkIPcf7TpFRKL6qUu0kAAIqCb0WFdWEZ8lPlbgq0wqhuYTQ0Ppiq9UZ685dTcjcHAEBREOwoxNF000gsBDvOidfHmjuxpzj/w/50OnLR9HoCAMDlQ7CjEIdrvxwNuRjR46z6xwTSLf2jxfn5a45hGQkAAFdY9Ryah0fwXCioEOcR7DinXn36UkZGBql8gsj/rtdpb2ohhQ+eSDXn/rDsEx0dTcePHpG1nQAAzgjBjgIcru3CigvxpoPVpqAHnAsHOvO+SRLnd53Lp90pBRR545N035WdSKsxJWDn3zVM5lYCADgndGMpwOG0InGa2DFQ7qZAGxjYKYh8PbRiKPr+C6bXFgAAWg/BjgIcqq3X6ReDYEcJ3DRquqpLiDi/N7WAynR6uZsEAODU0I2lAIcvmn799+sYIHdToB5lZWUUGGwKXhpSWlpmc7l7hB8dSisWE0XuPJtHY3tFtnMrAQCUC8GOk8sqrhLrKvEq572jEew4IqPRaKnHachTE3pfMhR9ZLcw+mZvGp3ILKXEDsjaAQC0FrqxnNyh2qxO13Bf8nLXyN0caEORAZ7UM9JPnN9yKocjILmbBADglBDsKKYLC7/8leiqLqHkrlGL7J1795FyNwcAwCkh2FHIZIKJMejCUiIfDy1dmRAsznsOuROrogMAtAKCHSdmNEp0qHbYOTI7ysWvbYivO6k9fen1DVg3CwCgpRDsOLGzuWVUUqUnLzcNda+t7QBlrop+bbdwcf7rPRcsAS4AADQPgh0nti+1UJz2iwkQc7OAcnUI8qLqM78TL5f14qqjIqsHAADNg29IBQQ7POMuKF/lrq/Jz0MrJpHkIekAANA8CHac2L4LCHZciVRZTE9e302cf339SRQrAwA0E4IdJ1VQXk3ncsvF+QExCHZcZSbmp24eQoaCNCqsqKFe98wVMzPX3XgFdQAA+BNmUHZSB2qzOp3DfCjIx13u5oC9ZmL++ndKL6yk7/dfJI9e19HUqVMpwt/TZj+sjg4AYAuZHSeFeh3XLlbubjWzspGrlgEAoEEIdpwUgh3XdnXtzMrZJTrLxJIAAFA/BDtOqMZgtKyJhWDHdWdWvqqLaSV1XhW9pKpG7iYBADgsBDtO6FhGCVXVGCnAy40SQn3lbg7IpG+HAIoK8KQag0RbTuaQhO4sAIB6IdhxQrvO5YvTIfHBYnZdcE0qlYrG9IwgjUpF5/Mr6HR2mdxNAgBwSAh2nDjYuTLB1I0BrivYx50Gx5u6MredzqXKaoPcTQIAcDgIdpyM3mCkPSkF4rx5NWxwbYM6BVOIjztV1hhox5lcuZsDAOBwEOw4maMZJVRebRD1Oj0j/eVuDjgAjdrUncVOZJWStiMmFQQAsIZgx8kknTV1YQ1FvQ5YiQzwpP4xgeK898hpVFSBpSQAAMwQ7DgZ1OtAQ4Z3DqEgbzdS+wTTP348gtFZAADOEOwsXLiQBg8eTH5+fhQeHk633HILnTp1ymafUaNGiVEp1tsjjzxCSp1fZ+95c70Ogh2w5aZR07jekSQZ9bTuSBZ9v+/iZd0fr7FV39pbWIcLAJyNQ6+NtW3bNpo5c6YIePR6Pf3jH/+gsWPH0vHjx8nHx8ey3/Tp02nBggWWy97e3qRER9OLRb1OoLcb9ahdLgDAGq+TVbX3B/Iacie9uOoYJXYMtCwt0VIZGRk075ukRvfBOlwA4AwcOthZv369zeXly5eLDM++ffvommuusQluIiMjSel21tbrDIlDvQ40THfoJxo75THacSaPHvliH62adRX5e7rJ3SwAANk4dDdWXcXFpjWAgoNth1yvWLGCQkNDqU+fPjR37lyqqKho9H50Oh2VlJTYbM6A51FhV3cLk7sp4Mgkif599wDqEOhFKXnl9NS3h8hoRP0OALgupwl2jEYjPfnkk3TVVVeJoMbsL3/5C33xxRe0ZcsWEeh8/vnndO+99zZZCxQQEGDZYmJiyNHx2kf7axf/HNkVwQ40Pdng+/deIRYL/fV4Nr3y0wkULAOAy3LobixrXLtz9OhR+u2332yunzFjhuV83759KSoqikaPHk1nz56lzp0713tfHBTNmTPHcpkzO44e8OxMzie9UaKEUB+KDVFmTRK0La7XWXRHIj3x9UH65PcUigzwoBnX1P9/AgBAyZwiszNr1ixau3atyN507Nix0X2HDh0qTpOTkxvcx8PDg/z9/W02Z+nCugZdWNACN/fvQM9N7CnOv7ruJK3YnSp3kwAA7M6hgx1Ou3Og8+OPP9LmzZspPj6+yb85ePCgOOUMj1Lw87C9NtgZ2R3BDrTM9GsSaMY1CeL8cz8epf9uPyd3kwAA7Err6F1XX375Ja1atUrMtZOVlSWu5zobLy8v0VXFt0+cOJFCQkLo8OHDNHv2bDFSKzExkZQiOaeM0osqyV2rpivjMb8OtNzcCT1Iq1bRe1vP0j/XnaC8Mh09Pa47aTUO/XsHAKBNOPQn3fvvvy9GYPHEgZypMW/ffPONuN3d3Z02btwo5t7p0aMHPfXUUzR58mRas2YNKYm5C4uXiPBy18jdHHBCPNnmM+N7iACHfbj9HN2/bA8VlGNZCQBQPofO7DQ1eoSLinniQaXbfDJHnI5EvQ5cppnXdqFOId70zPeH6bfkPJr47x208La+dG2PcLmbBgDgmpkdICosr6bdKaYlIswrWwNcjhsTo+nHx64SI/uySqrogeV7aM63B0XXFgCAEiHYcXAbT2STwSiJ5SHiQv9cIgPgcvASEj89fjU9NCKeVCqiH/an07WLtori5Wq9Ue7mAQC0KQQ7Dm7DMVNR9oQ+yhldBo6B67+ev7EX/e/R4ZTYMYBKdXpRvDz+7e20pbbrFABACRDsOLAynZ62n8kT58f3Uf7aXyCPK2KDaOVjV9HrtydSqK8HncsrF11bPuOfQgEzACgCgh0HtvVUjuhSiA/1oW4RvnI3BxSMF5a9c1AMbfm/kfTwyARy06jILbafmISQ53jS1RjkbiIAQKsh2HFg64+aurDG9Y4UQ4cB2pufpxvNndCTfpk9kmrO7ydeP/RAWhF9mpRKR9KLsb4WADglBDsOqqJab6mbQBcW2BtnE8t/eZtu6R9Nwd7uVFljEFMgrDyYQWVVermbBwCgnHl2XL0wubzaQLHB3tSvY4DczQEnUlZWRoHBjc+0HR0dTcePHmnyvjqF+NBfhnrToYtFlHQ2ny4UVNAXu1Pp+l4R1DkMXasA4BwQ7DgoHgrMbruiA7qwoEWMRiPN+yap0X3m3zWs2fenUatEEXNciI8IwnNKdbT2cCYNjgviqZnboMUAAO0LwY4DyiyuFLPbsslXNL7KO0B7ZX9KS8tsLgf7uIsiZn5vHkwroj3nC8ln3BwxatDXAx8lAOC48AnlgH48kE5cBzokPphigr3lbg64aPbnqQm9683y8LIlkf6eYsJLiu1Hd32YRMvuH0zh/p7t2GIAgNZDgbKD4dEu/9t3UZyffEUHuZsD0OAMzJx1NFaW0LGMErr1vZ10OrtU7mYBANQLwY6D2X+hiM7mlpOnm5om9sWsyeC4IgM8qWzlfLHGVnpRJU1+fyftPGvqfgUAcCQIdhzM8p3nxekNfaPFnCcAjsxYmiuWmxjYKYhKq/Q09ZM/aNVBU3E9AICjQLDjQLKKq+jnI5ni/ANXxcndHIBmCfJxpxUPDaWJfSOpxiDRE18fpI92nJO7WQAAFgh2HMjnu86T3iiJwuQ+HTC3DjgPTzcNLbnnCrp/uClIf+WnE/TK2uNk5CmYAQBkhmDHQVTVGOjL3RfE+QeR1QEnxCO15k3qRXMn9BCXP/othZ785iDp9FhXCwDkhaHnDjTcvLCihjoEetH1vepfHqJXn76UkZHRorlRAOSYr8ety3DyHvUQrT6UQWs3/0Z73ppBIb4esrQRAADBjgPglc3f3ZxsqdXhX8j14UCnNXOjAMgxX09qfjmtO5JF1SEJdNO7v9N/7htIvaPRPQsA9oduLAfwzd40MXQ33M+D7r2yk9zNAWgTvK7WnYM6kqE4S7y/b3tvJ32+KxUrpwOA3SHYcYBanXc3nxHnZ13XRRR6AigFd12V/fgSjeoeRjq9kV5YeZSmf7ZXjDwEALAXdGPJ7ItdqZRdoiNjaR49PmkoPW7UN7gv6nHAGUnVFfTJ1MG0bOd5+tfPJ2njiRzaeXYrPT66q+i29dA2P8BvTt1ac1d0BwDXgWBHRnllOnpnkymrc/3gXtTnlh2N7o96HHBWarWKpo2Ip+GdQ+i5H4+ImcJf+/kkLfs9RVx/95BY8m/GJJrNqVtryYruAOAa0I0lo1fXnaCSKj3p885Tryh/uZsD0O56RvnT948Mpzfv6CcWE+Ws5qvrTtKgVzbSw5/vpZUH0imjqFLuZgKAwiCzI5Oks/n0w/50UqmIKncsJ/Vd18vdJAC7ZXkmD+xIk/pF08qD6WK25dPZZbThWLbYWFSAJ3UJ96XOYb7ifLi/B4X7eZI6MFrUuXlo1aTi/zwAAM2AYEcG/GH9/EpTTcGUobH07oeYWh9cj7tWTXcOiqE7BnakE5mltOZwBv2enCdWUc8srhLbjjO2C4v63/kafbj9nJiewdtdQz7uWvLx0FCgtzuF+rhTmB/P5YMgCABsIdiRwfw1x8XK5vzB/PTYHvSu3A0CkBFnaHpF+4uNlev0IuBJySujlLwKyi6popzSKsop0dGpC1mk9vQlg1ESC4/yZlJuuT//+5bStOV76Lqe4TSmZwRF+HvKdGQA4CgQ7NjZmkMZ9NUfF0T31Vt39qcAb6xsDtCSGcJfW3OIKqoNVF6tp3Kdgcp0eioor6b8Mh3llOpI7+lLm07miO25H49SYscAur5nBI3vE0ldI/zsdjwA4DgQ7NjR2dwymvuDqftq5qguNKJrqNxNAnAYzZ0hXKtRk78Xb5f+UOCMz8LHp9CCD76mjSey6WBaER2+WCy2N389LQqkb+oXTZP6RVHHIO92PBoAcCQIduyE0/BTP/lD/AodHBdET47pKneTABSHa3mKU47Qc5OHissqrwByi+1HbnGDSBvTh05klojtX+tP0qBOQXRT/2ia2DeKQrFuF4CiIdixAw5wHli2hy4WVlKnEG96/96B4tcpANhvvS4eGJCcU0anskoprbCc9qYWio1r6K7qEioyPuN6R5BfM+b7AQDngmCnnRVX1tCDy/eIgssQH3f69IEh+BUJLqWhldHtPUM4L8XSp0OA2BY8MJEWffWLWJWdu7i2n84V2z9+VNPoHuF0Q2IUjegSKkZ5AYDzQ7DTzjMk3/fxH3Q8s4T8PbX0yf2DKS7UR+5mATjMyuhyzRAuVRTSQ1cniC0lr5xWH8yg1YfSxSjJn49miU2tIurbMZCu7hJKV3cNpX4xgVi7DsBJIdhpJ4Xl1XTnh0l0LrecjBXFdPH712nkO2n17os1rwAcI9ukCYklty7DyC2mH1FwRzqUViS2d7ckk7tGLYbHD4gNpAGxQTQgJpA6BnlhckMAJ4Bgp50EeLnRwNggSj6XSvePHUhBk75tcF+seQXgeNmmBQ9OpP/8uIV+S84Tkx3mlVWL0V28Lfv9vNjHz1NLPSP9qWeUnxjpxVv3SD9kgAAcDIKddpwS/7XJifTRk7dS0C3r5W4OALRQaXYaTR/b33JZ7RdGmvAupI3oQhregmOotIroj/MFYjOTjEYyFmeSIf8CGQrSyFCYQaHuNXR052YMTACQCYKddh4GK1UWy90MAGiH7A/P6cOTGb7z0hwa+8hLlFuqE9mfyhoiTVAHsRGZVmCv4kkTX9xACWE+1Dncl7qG+4q1v7qG+1FcqDd5aJEJAmhPCHYAAFr5Y4aXfKk4vpWu7homrpMkicqrDZRXqqPcMh3ll1VTQUU15RSWUDV50MmsUrFZ45KfKH9Pyjp3nCrzLpKxJJeMpTm1p7k2P5iio6Pp+FHTxKQA4ILBztKlS2nRokWUlZVF/fr1oyVLltCQIUPkbhYAuBAuVvb10IrNeuTl/LuG05HkC3Qmp1TM9XMmu4ySc8soObuMSnV6yiiuIgpJII+QhEvuU6tWidmi/Ty0dHrnOnp742mxEnxkgBdFi1NPzA0E4ArBzjfffENz5syhDz74gIYOHUpvv/02jRs3jk6dOkXh4eFyNw8AXJ5EMcHeYruuR8Sf10qSyAClFVTS+Nv/SmOmPy/m5iqprKHiqhoqq9KTvra7jDePHqPo7Y1nLrl3Dq5MAZAnRQd4iVO+zIugBvu4U4ivO4X4eJCXu326y/QGI1XUGKhCZ6CKaj1NvOkWysnJqb21zug1o54kfQ1FhgbRvt2/k6dWI2oeQVnr2kXLnJVURLCzePFimj59Oj3wwAPiMgc9P/30E33yySf097//Xe7mAQA0mAkK9/MUW83ZJBoSH2xzu2l19xoqqdKLwGf1Z+/RgzNnU2ZxJWUVV1FGUaXpNp2eznDGKKfxaSy83TUi8An28RBzf3GQ5FObieJAyE2tIo1aTVoNn6rE4+v0Rqo2bwaD5TwvxmpekJWDGnHKl3V68Tc2Rs4m05r2DausrWti7lo1eWrVok08ss1DqxZ1TXw9n//zVGO5rKmdAkAiyXRqOqm99Odlqnu7ZT/TGT5ufiwPN9Njetae8uPw82d+vkynGvJ2N533cdcotgBdkkzvA35tefHdUl2NOOXL/N7L8+tKkxZ9RHqDREZJEs8pP59GyRTaqlUq2vbdf0XAzsG3HJw+2KmurqZ9+/bR3LlzLdep1WoaM2YMJSU1PZEZAIAjzCJd33xb/MXLszibZ3JetmMFvX9gle1OWg9S+wSR2jdEnBo8Asg9MIzUPiGk8vIntZe/OFVp3EwBSkGlyCTZg2Q0EOl1ZNTXkG+AbSBnZpAkMhgkcWpmDqg4kHMmHBj5mIMfq2DIFByZAiW+nfcTQaUILlWW4NJ02XR93embrJ6eP6+zhHIN78MBq94oUY3BSDUG06ne+rxREkupcNBiDlr5vDmwMZ/n/RriPXIa7TiT1+hz4zV4MhVVINhptby8PDIYDBQR8WdqmPHlkydP1vs3Op1ObGbFxaYCwJKSknaJiKvKyy57n7a8L3vu44htQrsdbx+lt5s/o5795NdG9/nH5CFtdj+v/u+PS9pYbTRSVbWBKmsMVFltoP99sJBefe11y5ccdztJtV+M/AXJX4b8pctZEzfOnmhMm5uWMx9q8uQsh5uWZs18lO6e/bLpNg1/cfOpujZLxF/aqnrbVNdrD46hk6eSSVdjoCq9UbSTz+v0BqqukUhnMIrswozHZtKNM/5BeqORDEYeNWdqr/VX8Y6Vn9JTs2eTqrbLrG7gwJdff2MRjZw8zXTZ5rkicd/8POxc9x0NHDuZDOKxTM8JB2EcLPDzWa2XSFddTSq16au0QkdUQUS5pFxe7n8GdCLT5a6lpN+2UK+BI0ijUZGan3UVWU75deFsz/7Na0hVM4RKSupk/S6T+Xub3+ONkpxceno6H6G0c+dOm+uffvppaciQIfX+zbx588TfYMOGDRs2bNjI6be0tLRGYwWnz+yEhoaSRqOh7Oxsm+v5cmRkZL1/w11eXNBsVlRURJ06daILFy5QQEAAuRKOimNiYigtLY38/ZvqVVcWVz12Vz1uVz52Vz1uhmNX9rFzRqe0tFQUQDfG6YMdd3d3GjhwIG3atIluueUWy2RgfHnWrFn1/o2Hh4fY6uJAR6lviKbwcePYXYurHrcrH7urHjfDsfuTUjUnSeH0wQ7jLM3UqVNp0KBBYm4dHnpeXl5uGZ0FAAAArksRwc5dd91Fubm59OKLL4pJBfv370/r16+/pGgZAAAAXI8igh3GXVYNdVs1hbu05s2bV2/XltLh2F3v2F31uF352F31uBmO3TWPvS4VVynL3QgAAACA9qLM6R4BAAAAaiHYAQAAAEVDsAMAAACKhmAHAAAAFA3BDhEtXbqU4uLiyNPTk4YOHUp//NH4Gi72tH37dpo0aZKYHZLXmFm5cqXN7VxfzkPuo6KiyMvLSyyAeubMGZt9CgoKaMqUKWJSqcDAQJo2bZpYmNDa4cOH6eqrrxbPAc+4+frrr1/Slu+++4569Ogh9unbty+tW7euxW1proULF9LgwYPJz8+PwsPDxYSRp06dstmnqqqKZs6cSSEhIeTr60uTJ0++ZCZtnhX7hhtuIG9vb3E/Tz/9NOn1tosLbt26la644goxYqFLly60fPnyFr9HmtOW5nr//fcpMTHRMhHYsGHD6Oeff1b8cdf12muviff8k08+qfhjf+mll8SxWm/8f03px22Wnp5O9957r7hP/uzgz5e9e/cq/nOOn+e6rztv/Py6wutuV5KL+/rrryV3d3fpk08+kY4dOyZNnz5dCgwMlLKzsyVHsG7dOum5556TfvjhB7H+x48//mhz+2uvvSYFBARIK1eulA4dOiTddNNNUnx8vFRZWWnZZ/z48VK/fv2kXbt2STt27JC6dOki3XPPPZbbi4uLpYiICGnKlCnS0aNHpa+++kry8vKSPvzwQ8s+v//+u6TRaKTXX39dOn78uPT8889Lbm5u0pEjR1rUluYaN26ctGzZMtGegwcPShMnTpRiY2OlsrIyyz6PPPKIFBMTI23atEnau3evdOWVV0rDhw+33K7X66U+ffpIY8aMkQ4cOCCey9DQUGnu3LmWfc6dOyd5e3tLc+bMEce1ZMkScZzr169v0Xukqba0xOrVq6WffvpJOn36tHTq1CnpH//4h3iu+blQ8nFb++OPP6S4uDgpMTFReuKJJ5r9eM567LxeX+/evaXMzEzLlpubq/jjZgUFBVKnTp2k+++/X9q9e7do54YNG6Tk5GTFf87l5OTYvOa//vqr+JzfsmWL4l93e3P5YIcXC505c6blssFgkKKjo6WFCxdKjqZusGM0GqXIyEhp0aJFluuKiookDw8P8R+Z8Zub/27Pnj2WfX7++WdJpVKJRVTZe++9JwUFBUk6nc6yz7PPPit1797dcvnOO++UbrjhBpv2DB06VHr44Yeb3ZbLwR8KfBzbtm2z3Dd/CH333XeWfU6cOCH2SUpKEpf5P75arZaysrIs+7z//vuSv7+/5VifeeYZ8SVj7a677hLBVnPfI81py+Xi1+ejjz5yieMuLS2VunbtKj74R44caQl2lHzsHOzwF3V9lHzc5s+aESNGNHi7K33O8Xu9c+fO4nGU/rrbm0t3Y1VXV9O+fftEGtJMrVaLy0lJSeToUlJSxIzR1u3nNUI4BWluP59ySpeX0jDj/fk4d+/ebdnnmmuuEeuMmY0bN050GxUWFlr2sX4c8z7mx2lOWy5HcXGxOA0ODhan/LrV1NTYPB6nnmNjY22OndPQ1jNpc5t5cbxjx44167ia8x5pTltay2Aw0Ndffy2WP+HuLFc4bk6Vc1q+bvuUfuzcFcLd1QkJCaI7hrsnXOG4V69eLT6f7rjjDtENM2DAAPrvf//rcp9z/Px/8cUX9OCDD4quLKW/7vbm0sFOXl6e+DKpu6wEX+Y3tKMzt7Gx9vMpf4BY02q1Imiw3qe++7B+jIb2sb69qba0Fi/synUbV111FfXp08fyePyhxR9wjbWptcfFHxaVlZXNeo80py0tdeTIEdEvzn3sjzzyCP3444/Uq1cvxR83B3b79+8XNVt1KfnY+cuS6yh4mRuu2eIvVa4t4dWclXzc7Ny5c+KYu3btShs2bKBHH32UHn/8cfr0009d6nOO6zGLioro/vvvtzyWkl93e1PMchGgXPxL/+jRo/Tbb7+Rq+jevTsdPHhQZLS+//57sdDttm3bSMnS0tLoiSeeoF9//VUUSbqSCRMmWM5zcToHP506daJvv/1WFMEqGf+Y4YzMq6++Ki5zZof/v3/wwQfife8qPv74Y/E+4OwetD2XzuyEhoaSRqO5pKKcL0dGRpKjM7exsfbzaU5Ojs3tXKnPIxes96nvPqwfo6F9rG9vqi2tweudrV27lrZs2UIdO3a0OXZOv/Ivocba1Nrj4hEd/CXTnPdIc9rSUvwrikdNDBw4UGQ5+vXrR//+978VfdycKuf3Ko8a4V/lvHGA984774jz/CtSqcdeF/+C7tatGyUnJyv6NWc8qomzltZ69uxp6cZzhc+51NRU2rhxIz300EOW65T+utubSwc7/IXCXyabNm2y+ZXBl7k+wtHFx8eLN5p1+zk1yX3U5vbzKb9B+YvEbPPmzeI4+dejeR8e4s59smb865qzC0FBQZZ9rB/HvI/5cZrTlpbgemwOdLj7htvL92+NXzc3Nzebx+O+d/6AtD527g6y/hDkNvN/cvOHa1PH1Zz3SHPacrn4MXU6naKPe/To0aLdnNEyb/yLn+tXzOeVeux18ZDps2fPikBAya854+7putNKnD59WmS2lP45Z7Zs2TLRDce1amZKf93tTnJxPOSOK+mXL18uKvpnzJghhtxZV7fLiUem8JBC3vjlWrx4sTifmppqGQbJ7V21apV0+PBh6eabb653SOaAAQPEsM7ffvtNjHSxHpLJlfY8JPOvf/2rGJLJzwkPVaw7JFOr1UpvvPGGqMLn0SP1Dclsqi3N9eijj4rhnVu3brUZmllRUWEzFJKHo2/evFkMhRw2bJjY6g7LHDt2rBi+zkMtw8LC6h2W+fTTT4vjWrp0ab3DMpt6jzTVlpb4+9//LkadpaSkiOeRL/Ookl9++UXRx10f69FYSj72p556SrzX+TXn/2s8lJiHEPMoRCUft3maAf5s+ec//ymdOXNGWrFihWjnF198YdlHqZ9z5pFP/HzyyLC6lPy625vLBzuM5x3gF5HnGeAheDxPg6Pg+RY4yKm7TZ06VdzOQxRfeOEF8Z+Y36yjR48Wc7NYy8/PF//pfX19xZDEBx54QARR1ni+CB7+yffRoUMH8R+6rm+//Vbq1q2beJ54KCPPBWOtOW1prvqOmTeee8eMP1wee+wxMZyU/zPfeuutIiCydv78eWnChAliPg3+8uAvlZqamkue4/79+4vjSkhIsHmM5r5HmtOW5nrwwQfFvCP8WPzBxc+jOdBR8nE3J9hR6rHzUOCoqCjxWPz/jy9bzzOj1OM2W7NmjfjS5s+NHj16SP/5z39sblfq5xzjOYX4s62++1D6625PKv7H/vkkAAAAAPtw6ZodAAAAUD4EOwAAAKBoCHYAAABA0RDsAAAAgKIh2AEAAABFQ7ADAAAAioZgBwAAABQNwQ4AOA1eGbzuysvt4fz586RSqcQyFQDg/BDsAIDd5Obm0qOPPkqxsbHk4eEh1hkaN24c/f777+32mHFxcSJw4c3Hx0csNPrdd981+jcxMTGUmZlJffr0abd2AYD9INgBALuZPHkyHThwgD799FOx2OPq1atp1KhRlJ+f366Pu2DBAhG88GMPHjyY7rrrLtq5c2e9+/LqzrwKNAdivNo6ADg/BDsAYBe8KvWOHTvoX//6F1177bViVeshQ4bQ3Llz6aabbhL7LF68mPr27SsyMJxdeeyxx8QK4I1ZtWqVyNZ4enpSQkICzZ8/n/R6vc0+fn5+Injp1q0bLV26lLy8vGjNmjWWzM/LL79M9913n1gtesaMGfV2Yx07doxuvPFGsQ/f39VXXy1WJjf76KOPqGfPnqIdPXr0oPfee6+Nn0EAaC0EOwBgF76+vmJbuXIl6XS6evdRq9X0zjvviMCCsz+bN2+mZ555psH75OCJg5QnnniCjh8/Th9++KGo6/nnP//Z4N9wtsbNzU1kcMzeeOMN6tevn8j8vPDCC5f8TXp6Ol1zzTWi643btG/fPnrwwQctQdWKFSvoxRdfFI974sQJevXVV8X98DEAgAOw67KjAODSvv/+e7FqsqenpzR8+HBp7ty5YiXqhnz33XdSSEiI5TKv1hwQEGC5zCtOv/rqqzZ/8/nnn4sVxM14Bfm33npLnNfpdGJ//uhbu3at5fZbbrnF5j5SUlLEPgcOHBCXuZ3x8fFSdXV1ve3s3Lmz9OWXX9pc9/LLL0vDhg1r1vMCAO0Lq54DgF1VVVWJjMyuXbvo559/pj/++EN0Ad1///20ceNGWrhwIZ08eZJKSkpE5oT3Ly8vJ29vb5G1efLJJ0WXGAsLCxPdXFxjY2YwGGz+hrupuF6Hszl8PWeXuOvs2WefFfvz7dOnT6fnnnvOch/cjRUfHy8yPf3796eJEyeKx6ovU8OPw/fJXWOcmTLjtgcEBFB2dnY7P6MA0BRU3wGAXXFNy/XXXy827up56KGHaN68eaJQmWtieLQWdwcFBwfTb7/9RtOmTRNdThy41MWBDtfo3HbbbfU+jtnTTz8tgikOSiIiIkQ9jjWuEWoMBzINMdcU/fe//6WhQ4fa3GYdhAGAfBDsAICsevXqJep4uA7GaDTSm2++acmQfPvtt43+LRcmnzp1irp06dLofqGhoU3u05jExESR1ampqREZImscPEVHR9O5c+doypQprX4MAGg/CHYAwC54ePkdd9whCns5eOARTXv37qXXX3+dbr75ZhGMcDCxZMkSmjRpkph754MPPmj0PrkomLNBPG/P7bffLoKkQ4cO0dGjR+mVV15ps7bPmjVLtOvuu+8WXWDcPcXdcDyarHv37iK79Pjjj4vrx48fLwqw+dgKCwtpzpw5bdYOAGgdjMYCALvgLiTu5nnrrbfEyCaesI+7sbhe5t133xWjoXjoOQ9N59t4hBPX7zSGJyRcu3Yt/fLLL2L+nCuvvFLcPw9rb0shISFiFBZ3WY0cOZIGDhwouq3MWR7uiuO6o2XLlomh87wP1xdx3Q8AyA8FygAAAKBoyOwAAACAoiHYAQAAAEVDsAMAAACKhmAHAAAAFA3BDgAAACgagh0AAABQNAQ7AAAAoGgIdgAAAEDREOwAAACAoiHYAQAAAEVDsAMAAACKhmAHAAAASMn+H0ybeAsnEJjHAAAAAElFTkSuQmCC",
      "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": [
    "# Target Distribution:\n",
    "import seaborn as sns\n",
    "import matplotlib.pyplot as plt\n",
    "\n",
    "sns.histplot(df['SalePrice'], kde=True)\n",
    "plt.title(\"Distribution of Sale Price\")\n",
    "plt.show()\n",
    "\n",
    "# SalePrice vs. OverallQual (quality of the house)\n",
    "sns.boxplot(x='OverallQual', y='SalePrice', data=df)\n",
    "plt.title(\"Sale Price vs. Overall Quality\")\n",
    "plt.show()\n",
    "\n",
    "# SalePrice vs. GrLivArea (above ground living area)\n",
    "sns.scatterplot(x='GrLivArea', y='SalePrice', data=df)\n",
    "plt.title(\"Sale Price vs. Living Area\")\n",
    "plt.show()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "id": "e40597f0-30ef-4574-ad16-48e138a407ec",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.scatterplot(\n",
    "    x='GrLivArea',\n",
    "    y='SalePrice',\n",
    "    hue='OverallQual',         # Color by Overall Quality\n",
    "    palette='viridis',         # You can try 'coolwarm', 'plasma', etc.\n",
    "    data=df\n",
    ")\n",
    "\n",
    "plt.title(\"Sale Price vs. Living Area (colored by OverallQual)\")\n",
    "plt.xlabel(\"Living Area (sq ft)\")\n",
    "plt.ylabel(\"Sale Price (USD)\")\n",
    "plt.legend(title=\"Overall Quality\")\n",
    "plt.grid(True)\n",
    "plt.tight_layout()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "id": "071d46f4-62c5-4c25-8832-242a1bd723bd",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "SalePrice        1.000000\n",
      "OverallQual      0.790982\n",
      "GrLivArea        0.708624\n",
      "GarageCars       0.640409\n",
      "GarageArea       0.623431\n",
      "TotalBsmtSF      0.613581\n",
      "1stFlrSF         0.605852\n",
      "FullBath         0.560664\n",
      "TotRmsAbvGrd     0.533723\n",
      "YearBuilt        0.522897\n",
      "YearRemodAdd     0.507101\n",
      "GarageYrBlt      0.486362\n",
      "MasVnrArea       0.477493\n",
      "Fireplaces       0.466929\n",
      "BsmtFinSF1       0.386420\n",
      "LotFrontage      0.351799\n",
      "WoodDeckSF       0.324413\n",
      "2ndFlrSF         0.319334\n",
      "OpenPorchSF      0.315856\n",
      "HalfBath         0.284108\n",
      "LotArea          0.263843\n",
      "BsmtFullBath     0.227122\n",
      "BsmtUnfSF        0.214479\n",
      "BedroomAbvGr     0.168213\n",
      "ScreenPorch      0.111447\n",
      "PoolArea         0.092404\n",
      "MoSold           0.046432\n",
      "3SsnPorch        0.044584\n",
      "BsmtFinSF2      -0.011378\n",
      "BsmtHalfBath    -0.016844\n",
      "MiscVal         -0.021190\n",
      "Id              -0.021917\n",
      "LowQualFinSF    -0.025606\n",
      "YrSold          -0.028923\n",
      "OverallCond     -0.077856\n",
      "MSSubClass      -0.084284\n",
      "EnclosedPorch   -0.128578\n",
      "KitchenAbvGr    -0.135907\n",
      "Name: SalePrice, dtype: float64\n"
     ]
    }
   ],
   "source": [
    " # Check which columns are most correlated with SalePrice\n",
    "# Show correlations with SalePrice\n",
    "correlation = df.corr(numeric_only=True)  # Only numeric columns\n",
    "saleprice_corr = correlation[\"SalePrice\"].sort_values(ascending=False)\n",
    "\n",
    "print(saleprice_corr)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "id": "f52a7f07-1f4a-4503-b203-dc547562338a",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 800x600 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Correlation matrix of top correlated features\n",
    "top_corr = df.corr(numeric_only=True)[[\"SalePrice\"]].sort_values(by=\"SalePrice\", ascending=False)\n",
    "\n",
    "plt.figure(figsize=(8, 6))\n",
    "sns.heatmap(top_corr, annot=True, cmap=\"coolwarm\")\n",
    "plt.title(\"Correlation with SalePrice\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "ec40f2aa-8f61-4f73-83a6-1b0a28b3d642",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Cleaning Plan for Many Columns with Nulls"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "id": "4711393d-859a-4351-a310-f55fa8351c24",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "PoolQC           1453\n",
       "MiscFeature      1406\n",
       "Alley            1369\n",
       "Fence            1179\n",
       "MasVnrType        872\n",
       "                 ... \n",
       "MoSold              0\n",
       "YrSold              0\n",
       "SaleType            0\n",
       "SaleCondition       0\n",
       "SalePrice           0\n",
       "Length: 81, dtype: int64"
      ]
     },
     "execution_count": 28,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    " # Drop rows with any missing value:\n",
    "missing = df.isnull().sum().sort_values(ascending=False)\n",
    "missing"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "id": "129b7836-f505-4c62-aeb9-b4be99589cbf",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Condition2       0.0\n",
      "BldgType         0.0\n",
      "Neighborhood     0.0\n",
      "LandSlope        0.0\n",
      "LotConfig        0.0\n",
      "                ... \n",
      "MoSold           0.0\n",
      "YrSold           0.0\n",
      "SaleType         0.0\n",
      "SaleCondition    0.0\n",
      "SalePrice        0.0\n",
      "Length: 62, dtype: float64\n"
     ]
    }
   ],
   "source": [
    "# Show % of missing values for each column\n",
    "missing_percent = df.isnull().mean() * 100\n",
    "missing_percent = missing_percent.sort_values(ascending=False)\n",
    "print(missing_percent[missing_percent == 0])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "id": "0e6f11ca-5b43-48e7-9292-5978b28617a5",
   "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>Id</th>\n",
       "      <th>MSSubClass</th>\n",
       "      <th>MSZoning</th>\n",
       "      <th>LotFrontage</th>\n",
       "      <th>LotArea</th>\n",
       "      <th>Street</th>\n",
       "      <th>LotShape</th>\n",
       "      <th>LandContour</th>\n",
       "      <th>Utilities</th>\n",
       "      <th>LotConfig</th>\n",
       "      <th>...</th>\n",
       "      <th>EnclosedPorch</th>\n",
       "      <th>3SsnPorch</th>\n",
       "      <th>ScreenPorch</th>\n",
       "      <th>PoolArea</th>\n",
       "      <th>MiscVal</th>\n",
       "      <th>MoSold</th>\n",
       "      <th>YrSold</th>\n",
       "      <th>SaleType</th>\n",
       "      <th>SaleCondition</th>\n",
       "      <th>SalePrice</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1</td>\n",
       "      <td>60</td>\n",
       "      <td>RL</td>\n",
       "      <td>65.0</td>\n",
       "      <td>8450</td>\n",
       "      <td>Pave</td>\n",
       "      <td>Reg</td>\n",
       "      <td>Lvl</td>\n",
       "      <td>AllPub</td>\n",
       "      <td>Inside</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>2</td>\n",
       "      <td>2008</td>\n",
       "      <td>WD</td>\n",
       "      <td>Normal</td>\n",
       "      <td>208500</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2</td>\n",
       "      <td>20</td>\n",
       "      <td>RL</td>\n",
       "      <td>80.0</td>\n",
       "      <td>9600</td>\n",
       "      <td>Pave</td>\n",
       "      <td>Reg</td>\n",
       "      <td>Lvl</td>\n",
       "      <td>AllPub</td>\n",
       "      <td>FR2</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>5</td>\n",
       "      <td>2007</td>\n",
       "      <td>WD</td>\n",
       "      <td>Normal</td>\n",
       "      <td>181500</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>3</td>\n",
       "      <td>60</td>\n",
       "      <td>RL</td>\n",
       "      <td>68.0</td>\n",
       "      <td>11250</td>\n",
       "      <td>Pave</td>\n",
       "      <td>IR1</td>\n",
       "      <td>Lvl</td>\n",
       "      <td>AllPub</td>\n",
       "      <td>Inside</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>9</td>\n",
       "      <td>2008</td>\n",
       "      <td>WD</td>\n",
       "      <td>Normal</td>\n",
       "      <td>223500</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>4</td>\n",
       "      <td>70</td>\n",
       "      <td>RL</td>\n",
       "      <td>60.0</td>\n",
       "      <td>9550</td>\n",
       "      <td>Pave</td>\n",
       "      <td>IR1</td>\n",
       "      <td>Lvl</td>\n",
       "      <td>AllPub</td>\n",
       "      <td>Corner</td>\n",
       "      <td>...</td>\n",
       "      <td>272</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>2006</td>\n",
       "      <td>WD</td>\n",
       "      <td>Abnorml</td>\n",
       "      <td>140000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>5</td>\n",
       "      <td>60</td>\n",
       "      <td>RL</td>\n",
       "      <td>84.0</td>\n",
       "      <td>14260</td>\n",
       "      <td>Pave</td>\n",
       "      <td>IR1</td>\n",
       "      <td>Lvl</td>\n",
       "      <td>AllPub</td>\n",
       "      <td>FR2</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>12</td>\n",
       "      <td>2008</td>\n",
       "      <td>WD</td>\n",
       "      <td>Normal</td>\n",
       "      <td>250000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 75 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "   Id  MSSubClass MSZoning  LotFrontage  LotArea Street LotShape LandContour  \\\n",
       "0   1          60       RL         65.0     8450   Pave      Reg         Lvl   \n",
       "1   2          20       RL         80.0     9600   Pave      Reg         Lvl   \n",
       "2   3          60       RL         68.0    11250   Pave      IR1         Lvl   \n",
       "3   4          70       RL         60.0     9550   Pave      IR1         Lvl   \n",
       "4   5          60       RL         84.0    14260   Pave      IR1         Lvl   \n",
       "\n",
       "  Utilities LotConfig  ... EnclosedPorch 3SsnPorch ScreenPorch PoolArea  \\\n",
       "0    AllPub    Inside  ...             0         0           0        0   \n",
       "1    AllPub       FR2  ...             0         0           0        0   \n",
       "2    AllPub    Inside  ...             0         0           0        0   \n",
       "3    AllPub    Corner  ...           272         0           0        0   \n",
       "4    AllPub       FR2  ...             0         0           0        0   \n",
       "\n",
       "  MiscVal MoSold  YrSold  SaleType  SaleCondition  SalePrice  \n",
       "0       0      2    2008        WD         Normal     208500  \n",
       "1       0      5    2007        WD         Normal     181500  \n",
       "2       0      9    2008        WD         Normal     223500  \n",
       "3       0      2    2006        WD        Abnorml     140000  \n",
       "4       0     12    2008        WD         Normal     250000  \n",
       "\n",
       "[5 rows x 75 columns]"
      ]
     },
     "execution_count": 39,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df = df.drop(columns=missing_percent[missing_percent > 40].index)\n",
    "\n",
    "df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "id": "01f2498d-4c23-45e6-9263-02b6bc8609c8",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Index(['Id', 'MSSubClass', 'MSZoning', 'LotFrontage', 'LotArea', 'Street',\n",
      "       'LotShape', 'LandContour', 'Utilities', 'LotConfig', 'LandSlope',\n",
      "       'Neighborhood', 'Condition1', 'Condition2', 'BldgType', 'HouseStyle',\n",
      "       'OverallQual', 'OverallCond', 'YearBuilt', 'YearRemodAdd', 'RoofStyle',\n",
      "       'RoofMatl', 'Exterior1st', 'Exterior2nd', 'MasVnrArea', 'ExterQual',\n",
      "       'ExterCond', 'Foundation', 'BsmtQual', 'BsmtCond', 'BsmtExposure',\n",
      "       'BsmtFinType1', 'BsmtFinSF1', 'BsmtFinType2', 'BsmtFinSF2', 'BsmtUnfSF',\n",
      "       'TotalBsmtSF', 'Heating', 'HeatingQC', 'CentralAir', 'Electrical',\n",
      "       '1stFlrSF', '2ndFlrSF', 'LowQualFinSF', 'GrLivArea', 'BsmtFullBath',\n",
      "       'BsmtHalfBath', 'FullBath', 'HalfBath', 'BedroomAbvGr', 'KitchenAbvGr',\n",
      "       'KitchenQual', 'TotRmsAbvGrd', 'Functional', 'Fireplaces', 'GarageType',\n",
      "       'GarageYrBlt', 'GarageFinish', 'GarageCars', 'GarageArea', 'GarageQual',\n",
      "       'GarageCond', 'PavedDrive', 'WoodDeckSF', 'OpenPorchSF',\n",
      "       'EnclosedPorch', '3SsnPorch', 'ScreenPorch', 'PoolArea', 'MiscVal',\n",
      "       'MoSold', 'YrSold', 'SaleType', 'SaleCondition', 'SalePrice'],\n",
      "      dtype='object')\n"
     ]
    }
   ],
   "source": [
    "print(df.columns)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "id": "d1235ddd-bd59-42a7-a5a2-a662c70f1d1e",
   "metadata": {},
   "outputs": [],
   "source": [
    " # Fill numeric columns with median:\n",
    "num_cols = df.select_dtypes(include=['float64', 'int64']).columns\n",
    "df[num_cols] = df[num_cols].fillna(df[num_cols].median())\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "id": "e6877d1d-a469-45d2-ac79-650e1964f7c5",
   "metadata": {},
   "outputs": [],
   "source": [
    " # Fill object (categorical) columns with mode:\n",
    "cat_cols = df.select_dtypes(include='object').columns\n",
    "for col in cat_cols:\n",
    "    df[col] = df[col].fillna(df[col].mode()[0])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "id": "e885427f-6723-4b4a-9874-7e84761ad05b",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Total missing values: 0\n"
     ]
    }
   ],
   "source": [
    " # Step 4: Confirm that all missing values are cleaned\n",
    "print(\"Total missing values:\", df.isnull().sum().sum())  # Should print 0\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "id": "a90880af-c940-4ac4-997e-64252ff1bb36",
   "metadata": {},
   "outputs": [],
   "source": [
    "#  Feature Selection & Engineering\n",
    "# 1. Select relevant features\n",
    "features = ['GrLivArea', 'OverallQual', 'GarageCars', 'TotalBsmtSF']\n",
    "X = df[features]\n",
    "y = df['SalePrice']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 53,
   "id": "eb0298c3-e911-4967-a13b-999c3b08ae5d",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Traing the model\n",
    "# 1. Train-test split\n",
    "from sklearn.model_selection import train_test_split\n",
    "X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.2, random_state=42)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 54,
   "id": "b7eea6dd-dcce-473c-a054-a4e28c558c3a",
   "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: #000;\n",
       "  --sklearn-color-text-muted: #666;\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: flex;\n",
       "  width: 100%;\n",
       "  margin-bottom: 0;\n",
       "  padding: 0.5em;\n",
       "  box-sizing: border-box;\n",
       "  text-align: center;\n",
       "  align-items: start;\n",
       "  justify-content: space-between;\n",
       "  gap: 0.5em;\n",
       "}\n",
       "\n",
       "#sk-container-id-1 label.sk-toggleable__label .caption {\n",
       "  font-size: 0.6rem;\n",
       "  font-weight: lighter;\n",
       "  color: var(--sklearn-color-text-muted);\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",
       "  display: none;\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",
       "  display: block;\n",
       "  width: 100%;\n",
       "  overflow: visible;\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: 0.5em;\n",
       "  text-align: center;\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",
       "\n",
       ".estimator-table summary {\n",
       "    padding: .5rem;\n",
       "    font-family: monospace;\n",
       "    cursor: pointer;\n",
       "}\n",
       "\n",
       ".estimator-table details[open] {\n",
       "    padding-left: 0.1rem;\n",
       "    padding-right: 0.1rem;\n",
       "    padding-bottom: 0.3rem;\n",
       "}\n",
       "\n",
       ".estimator-table .parameters-table {\n",
       "    margin-left: auto !important;\n",
       "    margin-right: auto !important;\n",
       "}\n",
       "\n",
       ".estimator-table .parameters-table tr:nth-child(odd) {\n",
       "    background-color: #fff;\n",
       "}\n",
       "\n",
       ".estimator-table .parameters-table tr:nth-child(even) {\n",
       "    background-color: #f6f6f6;\n",
       "}\n",
       "\n",
       ".estimator-table .parameters-table tr:hover {\n",
       "    background-color: #e0e0e0;\n",
       "}\n",
       "\n",
       ".estimator-table table td {\n",
       "    border: 1px solid rgba(106, 105, 104, 0.232);\n",
       "}\n",
       "\n",
       ".user-set td {\n",
       "    color:rgb(255, 94, 0);\n",
       "    text-align: left;\n",
       "}\n",
       "\n",
       ".user-set td.value pre {\n",
       "    color:rgb(255, 94, 0) !important;\n",
       "    background-color: transparent !important;\n",
       "}\n",
       "\n",
       ".default td {\n",
       "    color: black;\n",
       "    text-align: left;\n",
       "}\n",
       "\n",
       ".user-set td i,\n",
       ".default td i {\n",
       "    color: black;\n",
       "}\n",
       "\n",
       ".copy-paste-icon {\n",
       "    background-image: url(data:image/svg+xml;base64,PHN2ZyB4bWxucz0iaHR0cDovL3d3dy53My5vcmcvMjAwMC9zdmciIHZpZXdCb3g9IjAgMCA0NDggNTEyIj48IS0tIUZvbnQgQXdlc29tZSBGcmVlIDYuNy4yIGJ5IEBmb250YXdlc29tZSAtIGh0dHBzOi8vZm9udGF3ZXNvbWUuY29tIExpY2Vuc2UgLSBodHRwczovL2ZvbnRhd2Vzb21lLmNvbS9saWNlbnNlL2ZyZWUgQ29weXJpZ2h0IDIwMjUgRm9udGljb25zLCBJbmMuLS0+PHBhdGggZD0iTTIwOCAwTDMzMi4xIDBjMTIuNyAwIDI0LjkgNS4xIDMzLjkgMTQuMWw2Ny45IDY3LjljOSA5IDE0LjEgMjEuMiAxNC4xIDMzLjlMNDQ4IDMzNmMwIDI2LjUtMjEuNSA0OC00OCA0OGwtMTkyIDBjLTI2LjUgMC00OC0yMS41LTQ4LTQ4bDAtMjg4YzAtMjYuNSAyMS41LTQ4IDQ4LTQ4ek00OCAxMjhsODAgMCAwIDY0LTY0IDAgMCAyNTYgMTkyIDAgMC0zMiA2NCAwIDAgNDhjMCAyNi41LTIxLjUgNDgtNDggNDhMNDggNTEyYy0yNi41IDAtNDgtMjEuNS00OC00OEwwIDE3NmMwLTI2LjUgMjEuNS00OCA0OC00OHoiLz48L3N2Zz4=);\n",
       "    background-repeat: no-repeat;\n",
       "    background-size: 14px 14px;\n",
       "    background-position: 0;\n",
       "    display: inline-block;\n",
       "    width: 14px;\n",
       "    height: 14px;\n",
       "    cursor: pointer;\n",
       "}\n",
       "</style><body><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\"><div><div>LinearRegression</div></div><div><a class=\"sk-estimator-doc-link fitted\" rel=\"noreferrer\" target=\"_blank\" href=\"https://scikit-learn.org/1.7/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></div></label><div class=\"sk-toggleable__content fitted\" data-param-prefix=\"\">\n",
       "        <div class=\"estimator-table\">\n",
       "            <details>\n",
       "                <summary>Parameters</summary>\n",
       "                <table class=\"parameters-table\">\n",
       "                  <tbody>\n",
       "                    \n",
       "        <tr class=\"default\">\n",
       "            <td><i class=\"copy-paste-icon\"\n",
       "                 onclick=\"copyToClipboard('fit_intercept',\n",
       "                          this.parentElement.nextElementSibling)\"\n",
       "            ></i></td>\n",
       "            <td class=\"param\">fit_intercept&nbsp;</td>\n",
       "            <td class=\"value\">True</td>\n",
       "        </tr>\n",
       "    \n",
       "\n",
       "        <tr class=\"default\">\n",
       "            <td><i class=\"copy-paste-icon\"\n",
       "                 onclick=\"copyToClipboard('copy_X',\n",
       "                          this.parentElement.nextElementSibling)\"\n",
       "            ></i></td>\n",
       "            <td class=\"param\">copy_X&nbsp;</td>\n",
       "            <td class=\"value\">True</td>\n",
       "        </tr>\n",
       "    \n",
       "\n",
       "        <tr class=\"default\">\n",
       "            <td><i class=\"copy-paste-icon\"\n",
       "                 onclick=\"copyToClipboard('tol',\n",
       "                          this.parentElement.nextElementSibling)\"\n",
       "            ></i></td>\n",
       "            <td class=\"param\">tol&nbsp;</td>\n",
       "            <td class=\"value\">1e-06</td>\n",
       "        </tr>\n",
       "    \n",
       "\n",
       "        <tr class=\"default\">\n",
       "            <td><i class=\"copy-paste-icon\"\n",
       "                 onclick=\"copyToClipboard('n_jobs',\n",
       "                          this.parentElement.nextElementSibling)\"\n",
       "            ></i></td>\n",
       "            <td class=\"param\">n_jobs&nbsp;</td>\n",
       "            <td class=\"value\">None</td>\n",
       "        </tr>\n",
       "    \n",
       "\n",
       "        <tr class=\"default\">\n",
       "            <td><i class=\"copy-paste-icon\"\n",
       "                 onclick=\"copyToClipboard('positive',\n",
       "                          this.parentElement.nextElementSibling)\"\n",
       "            ></i></td>\n",
       "            <td class=\"param\">positive&nbsp;</td>\n",
       "            <td class=\"value\">False</td>\n",
       "        </tr>\n",
       "    \n",
       "                  </tbody>\n",
       "                </table>\n",
       "            </details>\n",
       "        </div>\n",
       "    </div></div></div></div></div><script>function copyToClipboard(text, element) {\n",
       "    // Get the parameter prefix from the closest toggleable content\n",
       "    const toggleableContent = element.closest('.sk-toggleable__content');\n",
       "    const paramPrefix = toggleableContent ? toggleableContent.dataset.paramPrefix : '';\n",
       "    const fullParamName = paramPrefix ? `${paramPrefix}${text}` : text;\n",
       "\n",
       "    const originalStyle = element.style;\n",
       "    const computedStyle = window.getComputedStyle(element);\n",
       "    const originalWidth = computedStyle.width;\n",
       "    const originalHTML = element.innerHTML.replace('Copied!', '');\n",
       "\n",
       "    navigator.clipboard.writeText(fullParamName)\n",
       "        .then(() => {\n",
       "            element.style.width = originalWidth;\n",
       "            element.style.color = 'green';\n",
       "            element.innerHTML = \"Copied!\";\n",
       "\n",
       "            setTimeout(() => {\n",
       "                element.innerHTML = originalHTML;\n",
       "                element.style = originalStyle;\n",
       "            }, 2000);\n",
       "        })\n",
       "        .catch(err => {\n",
       "            console.error('Failed to copy:', err);\n",
       "            element.style.color = 'red';\n",
       "            element.innerHTML = \"Failed!\";\n",
       "            setTimeout(() => {\n",
       "                element.innerHTML = originalHTML;\n",
       "                element.style = originalStyle;\n",
       "            }, 2000);\n",
       "        });\n",
       "    return false;\n",
       "}\n",
       "\n",
       "document.querySelectorAll('.fa-regular.fa-copy').forEach(function(element) {\n",
       "    const toggleableContent = element.closest('.sk-toggleable__content');\n",
       "    const paramPrefix = toggleableContent ? toggleableContent.dataset.paramPrefix : '';\n",
       "    const paramName = element.parentElement.nextElementSibling.textContent.trim();\n",
       "    const fullParamName = paramPrefix ? `${paramPrefix}${paramName}` : paramName;\n",
       "\n",
       "    element.setAttribute('title', fullParamName);\n",
       "});\n",
       "</script></body>"
      ],
      "text/plain": [
       "LinearRegression()"
      ]
     },
     "execution_count": 54,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# 3. Train a simple model\n",
    "from sklearn.linear_model import LinearRegression\n",
    "model = LinearRegression()\n",
    "model.fit(X_train, y_train)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 56,
   "id": "2c7df58e-6758-4e7c-8390-6efac623d484",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "RMSE: 40036.41866406039\n"
     ]
    }
   ],
   "source": [
    "# 4. Evaluate\n",
    "from sklearn.metrics import mean_squared_error\n",
    "predictions = model.predict(X_test)\n",
    "mse = mean_squared_error(y_test, predictions)\n",
    "rmse = np.sqrt(mse)\n",
    "print(\"RMSE:\", rmse)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 57,
   "id": "0f4c33a9-c6b7-4d6b-a17e-f30984683781",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Relative Error: 0.22386748395706216\n"
     ]
    }
   ],
   "source": [
    "# calculate the relative error\n",
    "relative_error = rmse / y_test.mean()\n",
    "print(\"Relative Error:\", relative_error)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 58,
   "id": "cdee8e5b-32dc-438e-aba4-a4f4e3fd06c0",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Visualize Predictions vs Actuals\n",
    "plt.scatter(y_test, predictions)\n",
    "plt.xlabel(\"Actual SalePrice\")\n",
    "plt.ylabel(\"Predicted SalePrice\")\n",
    "plt.title(\"Actual vs Predicted SalePrice\")\n",
    "plt.plot([y_test.min(), y_test.max()], [y_test.min(), y_test.max()], 'r--')  # 45-degree line\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "33d4284f-d8d0-4b58-b1f5-a560b8c4d604",
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3 (ipykernel)",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.13.4"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}