house-price-hypothesis-test.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Housing Hypothesis Testing"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 62,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import matplotlib.pyplot as plt\n",
    "import seaborn as sns\n",
    "plt.style.use('ggplot')\n",
    "pd.set_option('display.max_columns', None)\n",
    "from scipy.stats import ttest_ind"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [],
   "source": [
    "df = pd.read_csv(\"data/train.csv\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(1460, 81)"
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "\n",
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       "    }\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>LotConfig</th>\n",
       "      <th>LandSlope</th>\n",
       "      <th>Neighborhood</th>\n",
       "      <th>Condition1</th>\n",
       "      <th>Condition2</th>\n",
       "      <th>BldgType</th>\n",
       "      <th>HouseStyle</th>\n",
       "      <th>OverallQual</th>\n",
       "      <th>OverallCond</th>\n",
       "      <th>YearBuilt</th>\n",
       "      <th>YearRemodAdd</th>\n",
       "      <th>RoofStyle</th>\n",
       "      <th>RoofMatl</th>\n",
       "      <th>Exterior1st</th>\n",
       "      <th>Exterior2nd</th>\n",
       "      <th>MasVnrType</th>\n",
       "      <th>MasVnrArea</th>\n",
       "      <th>ExterQual</th>\n",
       "      <th>ExterCond</th>\n",
       "      <th>Foundation</th>\n",
       "      <th>BsmtQual</th>\n",
       "      <th>BsmtCond</th>\n",
       "      <th>BsmtExposure</th>\n",
       "      <th>BsmtFinType1</th>\n",
       "      <th>BsmtFinSF1</th>\n",
       "      <th>BsmtFinType2</th>\n",
       "      <th>BsmtFinSF2</th>\n",
       "      <th>BsmtUnfSF</th>\n",
       "      <th>TotalBsmtSF</th>\n",
       "      <th>Heating</th>\n",
       "      <th>HeatingQC</th>\n",
       "      <th>CentralAir</th>\n",
       "      <th>Electrical</th>\n",
       "      <th>1stFlrSF</th>\n",
       "      <th>2ndFlrSF</th>\n",
       "      <th>LowQualFinSF</th>\n",
       "      <th>GrLivArea</th>\n",
       "      <th>BsmtFullBath</th>\n",
       "      <th>BsmtHalfBath</th>\n",
       "      <th>FullBath</th>\n",
       "      <th>HalfBath</th>\n",
       "      <th>BedroomAbvGr</th>\n",
       "      <th>KitchenAbvGr</th>\n",
       "      <th>KitchenQual</th>\n",
       "      <th>TotRmsAbvGrd</th>\n",
       "      <th>Functional</th>\n",
       "      <th>Fireplaces</th>\n",
       "      <th>FireplaceQu</th>\n",
       "      <th>GarageType</th>\n",
       "      <th>GarageYrBlt</th>\n",
       "      <th>GarageFinish</th>\n",
       "      <th>GarageCars</th>\n",
       "      <th>GarageArea</th>\n",
       "      <th>GarageQual</th>\n",
       "      <th>GarageCond</th>\n",
       "      <th>PavedDrive</th>\n",
       "      <th>WoodDeckSF</th>\n",
       "      <th>OpenPorchSF</th>\n",
       "      <th>EnclosedPorch</th>\n",
       "      <th>3SsnPorch</th>\n",
       "      <th>ScreenPorch</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>Inside</td>\n",
       "      <td>Gtl</td>\n",
       "      <td>CollgCr</td>\n",
       "      <td>Norm</td>\n",
       "      <td>Norm</td>\n",
       "      <td>1Fam</td>\n",
       "      <td>2Story</td>\n",
       "      <td>7</td>\n",
       "      <td>5</td>\n",
       "      <td>2003</td>\n",
       "      <td>2003</td>\n",
       "      <td>Gable</td>\n",
       "      <td>CompShg</td>\n",
       "      <td>VinylSd</td>\n",
       "      <td>VinylSd</td>\n",
       "      <td>BrkFace</td>\n",
       "      <td>196.0</td>\n",
       "      <td>Gd</td>\n",
       "      <td>TA</td>\n",
       "      <td>PConc</td>\n",
       "      <td>Gd</td>\n",
       "      <td>TA</td>\n",
       "      <td>No</td>\n",
       "      <td>GLQ</td>\n",
       "      <td>706</td>\n",
       "      <td>Unf</td>\n",
       "      <td>0</td>\n",
       "      <td>150</td>\n",
       "      <td>856</td>\n",
       "      <td>GasA</td>\n",
       "      <td>Ex</td>\n",
       "      <td>Y</td>\n",
       "      <td>SBrkr</td>\n",
       "      <td>856</td>\n",
       "      <td>854</td>\n",
       "      <td>0</td>\n",
       "      <td>1710</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "      <td>1</td>\n",
       "      <td>Gd</td>\n",
       "      <td>8</td>\n",
       "      <td>Typ</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Attchd</td>\n",
       "      <td>2003.0</td>\n",
       "      <td>RFn</td>\n",
       "      <td>2</td>\n",
       "      <td>548</td>\n",
       "      <td>TA</td>\n",
       "      <td>TA</td>\n",
       "      <td>Y</td>\n",
       "      <td>0</td>\n",
       "      <td>61</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</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>FR2</td>\n",
       "      <td>Gtl</td>\n",
       "      <td>Veenker</td>\n",
       "      <td>Feedr</td>\n",
       "      <td>Norm</td>\n",
       "      <td>1Fam</td>\n",
       "      <td>1Story</td>\n",
       "      <td>6</td>\n",
       "      <td>8</td>\n",
       "      <td>1976</td>\n",
       "      <td>1976</td>\n",
       "      <td>Gable</td>\n",
       "      <td>CompShg</td>\n",
       "      <td>MetalSd</td>\n",
       "      <td>MetalSd</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.0</td>\n",
       "      <td>TA</td>\n",
       "      <td>TA</td>\n",
       "      <td>CBlock</td>\n",
       "      <td>Gd</td>\n",
       "      <td>TA</td>\n",
       "      <td>Gd</td>\n",
       "      <td>ALQ</td>\n",
       "      <td>978</td>\n",
       "      <td>Unf</td>\n",
       "      <td>0</td>\n",
       "      <td>284</td>\n",
       "      <td>1262</td>\n",
       "      <td>GasA</td>\n",
       "      <td>Ex</td>\n",
       "      <td>Y</td>\n",
       "      <td>SBrkr</td>\n",
       "      <td>1262</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1262</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>1</td>\n",
       "      <td>TA</td>\n",
       "      <td>6</td>\n",
       "      <td>Typ</td>\n",
       "      <td>1</td>\n",
       "      <td>TA</td>\n",
       "      <td>Attchd</td>\n",
       "      <td>1976.0</td>\n",
       "      <td>RFn</td>\n",
       "      <td>2</td>\n",
       "      <td>460</td>\n",
       "      <td>TA</td>\n",
       "      <td>TA</td>\n",
       "      <td>Y</td>\n",
       "      <td>298</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</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>Inside</td>\n",
       "      <td>Gtl</td>\n",
       "      <td>CollgCr</td>\n",
       "      <td>Norm</td>\n",
       "      <td>Norm</td>\n",
       "      <td>1Fam</td>\n",
       "      <td>2Story</td>\n",
       "      <td>7</td>\n",
       "      <td>5</td>\n",
       "      <td>2001</td>\n",
       "      <td>2002</td>\n",
       "      <td>Gable</td>\n",
       "      <td>CompShg</td>\n",
       "      <td>VinylSd</td>\n",
       "      <td>VinylSd</td>\n",
       "      <td>BrkFace</td>\n",
       "      <td>162.0</td>\n",
       "      <td>Gd</td>\n",
       "      <td>TA</td>\n",
       "      <td>PConc</td>\n",
       "      <td>Gd</td>\n",
       "      <td>TA</td>\n",
       "      <td>Mn</td>\n",
       "      <td>GLQ</td>\n",
       "      <td>486</td>\n",
       "      <td>Unf</td>\n",
       "      <td>0</td>\n",
       "      <td>434</td>\n",
       "      <td>920</td>\n",
       "      <td>GasA</td>\n",
       "      <td>Ex</td>\n",
       "      <td>Y</td>\n",
       "      <td>SBrkr</td>\n",
       "      <td>920</td>\n",
       "      <td>866</td>\n",
       "      <td>0</td>\n",
       "      <td>1786</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "      <td>1</td>\n",
       "      <td>Gd</td>\n",
       "      <td>6</td>\n",
       "      <td>Typ</td>\n",
       "      <td>1</td>\n",
       "      <td>TA</td>\n",
       "      <td>Attchd</td>\n",
       "      <td>2001.0</td>\n",
       "      <td>RFn</td>\n",
       "      <td>2</td>\n",
       "      <td>608</td>\n",
       "      <td>TA</td>\n",
       "      <td>TA</td>\n",
       "      <td>Y</td>\n",
       "      <td>0</td>\n",
       "      <td>42</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</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>Corner</td>\n",
       "      <td>Gtl</td>\n",
       "      <td>Crawfor</td>\n",
       "      <td>Norm</td>\n",
       "      <td>Norm</td>\n",
       "      <td>1Fam</td>\n",
       "      <td>2Story</td>\n",
       "      <td>7</td>\n",
       "      <td>5</td>\n",
       "      <td>1915</td>\n",
       "      <td>1970</td>\n",
       "      <td>Gable</td>\n",
       "      <td>CompShg</td>\n",
       "      <td>Wd Sdng</td>\n",
       "      <td>Wd Shng</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.0</td>\n",
       "      <td>TA</td>\n",
       "      <td>TA</td>\n",
       "      <td>BrkTil</td>\n",
       "      <td>TA</td>\n",
       "      <td>Gd</td>\n",
       "      <td>No</td>\n",
       "      <td>ALQ</td>\n",
       "      <td>216</td>\n",
       "      <td>Unf</td>\n",
       "      <td>0</td>\n",
       "      <td>540</td>\n",
       "      <td>756</td>\n",
       "      <td>GasA</td>\n",
       "      <td>Gd</td>\n",
       "      <td>Y</td>\n",
       "      <td>SBrkr</td>\n",
       "      <td>961</td>\n",
       "      <td>756</td>\n",
       "      <td>0</td>\n",
       "      <td>1717</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>1</td>\n",
       "      <td>Gd</td>\n",
       "      <td>7</td>\n",
       "      <td>Typ</td>\n",
       "      <td>1</td>\n",
       "      <td>Gd</td>\n",
       "      <td>Detchd</td>\n",
       "      <td>1998.0</td>\n",
       "      <td>Unf</td>\n",
       "      <td>3</td>\n",
       "      <td>642</td>\n",
       "      <td>TA</td>\n",
       "      <td>TA</td>\n",
       "      <td>Y</td>\n",
       "      <td>0</td>\n",
       "      <td>35</td>\n",
       "      <td>272</td>\n",
       "      <td>0</td>\n",
       "      <td>0</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>FR2</td>\n",
       "      <td>Gtl</td>\n",
       "      <td>NoRidge</td>\n",
       "      <td>Norm</td>\n",
       "      <td>Norm</td>\n",
       "      <td>1Fam</td>\n",
       "      <td>2Story</td>\n",
       "      <td>8</td>\n",
       "      <td>5</td>\n",
       "      <td>2000</td>\n",
       "      <td>2000</td>\n",
       "      <td>Gable</td>\n",
       "      <td>CompShg</td>\n",
       "      <td>VinylSd</td>\n",
       "      <td>VinylSd</td>\n",
       "      <td>BrkFace</td>\n",
       "      <td>350.0</td>\n",
       "      <td>Gd</td>\n",
       "      <td>TA</td>\n",
       "      <td>PConc</td>\n",
       "      <td>Gd</td>\n",
       "      <td>TA</td>\n",
       "      <td>Av</td>\n",
       "      <td>GLQ</td>\n",
       "      <td>655</td>\n",
       "      <td>Unf</td>\n",
       "      <td>0</td>\n",
       "      <td>490</td>\n",
       "      <td>1145</td>\n",
       "      <td>GasA</td>\n",
       "      <td>Ex</td>\n",
       "      <td>Y</td>\n",
       "      <td>SBrkr</td>\n",
       "      <td>1145</td>\n",
       "      <td>1053</td>\n",
       "      <td>0</td>\n",
       "      <td>2198</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>4</td>\n",
       "      <td>1</td>\n",
       "      <td>Gd</td>\n",
       "      <td>9</td>\n",
       "      <td>Typ</td>\n",
       "      <td>1</td>\n",
       "      <td>TA</td>\n",
       "      <td>Attchd</td>\n",
       "      <td>2000.0</td>\n",
       "      <td>RFn</td>\n",
       "      <td>3</td>\n",
       "      <td>836</td>\n",
       "      <td>TA</td>\n",
       "      <td>TA</td>\n",
       "      <td>Y</td>\n",
       "      <td>192</td>\n",
       "      <td>84</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</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",
       "</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 LotConfig LandSlope Neighborhood Condition1  \\\n",
       "0         Lvl    AllPub    Inside       Gtl      CollgCr       Norm   \n",
       "1         Lvl    AllPub       FR2       Gtl      Veenker      Feedr   \n",
       "2         Lvl    AllPub    Inside       Gtl      CollgCr       Norm   \n",
       "3         Lvl    AllPub    Corner       Gtl      Crawfor       Norm   \n",
       "4         Lvl    AllPub       FR2       Gtl      NoRidge       Norm   \n",
       "\n",
       "  Condition2 BldgType HouseStyle  OverallQual  OverallCond  YearBuilt  \\\n",
       "0       Norm     1Fam     2Story            7            5       2003   \n",
       "1       Norm     1Fam     1Story            6            8       1976   \n",
       "2       Norm     1Fam     2Story            7            5       2001   \n",
       "3       Norm     1Fam     2Story            7            5       1915   \n",
       "4       Norm     1Fam     2Story            8            5       2000   \n",
       "\n",
       "   YearRemodAdd RoofStyle RoofMatl Exterior1st Exterior2nd MasVnrType  \\\n",
       "0          2003     Gable  CompShg     VinylSd     VinylSd    BrkFace   \n",
       "1          1976     Gable  CompShg     MetalSd     MetalSd        NaN   \n",
       "2          2002     Gable  CompShg     VinylSd     VinylSd    BrkFace   \n",
       "3          1970     Gable  CompShg     Wd Sdng     Wd Shng        NaN   \n",
       "4          2000     Gable  CompShg     VinylSd     VinylSd    BrkFace   \n",
       "\n",
       "   MasVnrArea ExterQual ExterCond Foundation BsmtQual BsmtCond BsmtExposure  \\\n",
       "0       196.0        Gd        TA      PConc       Gd       TA           No   \n",
       "1         0.0        TA        TA     CBlock       Gd       TA           Gd   \n",
       "2       162.0        Gd        TA      PConc       Gd       TA           Mn   \n",
       "3         0.0        TA        TA     BrkTil       TA       Gd           No   \n",
       "4       350.0        Gd        TA      PConc       Gd       TA           Av   \n",
       "\n",
       "  BsmtFinType1  BsmtFinSF1 BsmtFinType2  BsmtFinSF2  BsmtUnfSF  TotalBsmtSF  \\\n",
       "0          GLQ         706          Unf           0        150          856   \n",
       "1          ALQ         978          Unf           0        284         1262   \n",
       "2          GLQ         486          Unf           0        434          920   \n",
       "3          ALQ         216          Unf           0        540          756   \n",
       "4          GLQ         655          Unf           0        490         1145   \n",
       "\n",
       "  Heating HeatingQC CentralAir Electrical  1stFlrSF  2ndFlrSF  LowQualFinSF  \\\n",
       "0    GasA        Ex          Y      SBrkr       856       854             0   \n",
       "1    GasA        Ex          Y      SBrkr      1262         0             0   \n",
       "2    GasA        Ex          Y      SBrkr       920       866             0   \n",
       "3    GasA        Gd          Y      SBrkr       961       756             0   \n",
       "4    GasA        Ex          Y      SBrkr      1145      1053             0   \n",
       "\n",
       "   GrLivArea  BsmtFullBath  BsmtHalfBath  FullBath  HalfBath  BedroomAbvGr  \\\n",
       "0       1710             1             0         2         1             3   \n",
       "1       1262             0             1         2         0             3   \n",
       "2       1786             1             0         2         1             3   \n",
       "3       1717             1             0         1         0             3   \n",
       "4       2198             1             0         2         1             4   \n",
       "\n",
       "   KitchenAbvGr KitchenQual  TotRmsAbvGrd Functional  Fireplaces FireplaceQu  \\\n",
       "0             1          Gd             8        Typ           0         NaN   \n",
       "1             1          TA             6        Typ           1          TA   \n",
       "2             1          Gd             6        Typ           1          TA   \n",
       "3             1          Gd             7        Typ           1          Gd   \n",
       "4             1          Gd             9        Typ           1          TA   \n",
       "\n",
       "  GarageType  GarageYrBlt GarageFinish  GarageCars  GarageArea GarageQual  \\\n",
       "0     Attchd       2003.0          RFn           2         548         TA   \n",
       "1     Attchd       1976.0          RFn           2         460         TA   \n",
       "2     Attchd       2001.0          RFn           2         608         TA   \n",
       "3     Detchd       1998.0          Unf           3         642         TA   \n",
       "4     Attchd       2000.0          RFn           3         836         TA   \n",
       "\n",
       "  GarageCond PavedDrive  WoodDeckSF  OpenPorchSF  EnclosedPorch  3SsnPorch  \\\n",
       "0         TA          Y           0           61              0          0   \n",
       "1         TA          Y         298            0              0          0   \n",
       "2         TA          Y           0           42              0          0   \n",
       "3         TA          Y           0           35            272          0   \n",
       "4         TA          Y         192           84              0          0   \n",
       "\n",
       "   ScreenPorch  PoolArea PoolQC Fence MiscFeature  MiscVal  MoSold  YrSold  \\\n",
       "0            0         0    NaN   NaN         NaN        0       2    2008   \n",
       "1            0         0    NaN   NaN         NaN        0       5    2007   \n",
       "2            0         0    NaN   NaN         NaN        0       9    2008   \n",
       "3            0         0    NaN   NaN         NaN        0       2    2006   \n",
       "4            0         0    NaN   NaN         NaN        0      12    2008   \n",
       "\n",
       "  SaleType SaleCondition  SalePrice  \n",
       "0       WD        Normal     208500  \n",
       "1       WD        Normal     181500  \n",
       "2       WD        Normal     223500  \n",
       "3       WD       Abnorml     140000  \n",
       "4       WD        Normal     250000  "
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "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')"
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.columns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 110,
   "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>count</th>\n",
       "      <th>mean</th>\n",
       "      <th>std</th>\n",
       "      <th>min</th>\n",
       "      <th>25%</th>\n",
       "      <th>50%</th>\n",
       "      <th>75%</th>\n",
       "      <th>max</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>Id</th>\n",
       "      <td>1460.0</td>\n",
       "      <td>730.500000</td>\n",
       "      <td>421.610009</td>\n",
       "      <td>1.0</td>\n",
       "      <td>365.75</td>\n",
       "      <td>730.500000</td>\n",
       "      <td>1095.25</td>\n",
       "      <td>1460.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>MSSubClass</th>\n",
       "      <td>1460.0</td>\n",
       "      <td>56.897260</td>\n",
       "      <td>42.300571</td>\n",
       "      <td>20.0</td>\n",
       "      <td>20.00</td>\n",
       "      <td>50.000000</td>\n",
       "      <td>70.00</td>\n",
       "      <td>190.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>LotFrontage</th>\n",
       "      <td>1460.0</td>\n",
       "      <td>70.049958</td>\n",
       "      <td>22.024023</td>\n",
       "      <td>21.0</td>\n",
       "      <td>60.00</td>\n",
       "      <td>70.049958</td>\n",
       "      <td>79.00</td>\n",
       "      <td>313.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>LotArea</th>\n",
       "      <td>1460.0</td>\n",
       "      <td>10516.828082</td>\n",
       "      <td>9981.264932</td>\n",
       "      <td>1300.0</td>\n",
       "      <td>7553.50</td>\n",
       "      <td>9478.500000</td>\n",
       "      <td>11601.50</td>\n",
       "      <td>215245.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>OverallQual</th>\n",
       "      <td>1460.0</td>\n",
       "      <td>6.099315</td>\n",
       "      <td>1.382997</td>\n",
       "      <td>1.0</td>\n",
       "      <td>5.00</td>\n",
       "      <td>6.000000</td>\n",
       "      <td>7.00</td>\n",
       "      <td>10.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>OverallCond</th>\n",
       "      <td>1460.0</td>\n",
       "      <td>5.575342</td>\n",
       "      <td>1.112799</td>\n",
       "      <td>1.0</td>\n",
       "      <td>5.00</td>\n",
       "      <td>5.000000</td>\n",
       "      <td>6.00</td>\n",
       "      <td>9.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>YearBuilt</th>\n",
       "      <td>1460.0</td>\n",
       "      <td>1971.267808</td>\n",
       "      <td>30.202904</td>\n",
       "      <td>1872.0</td>\n",
       "      <td>1954.00</td>\n",
       "      <td>1973.000000</td>\n",
       "      <td>2000.00</td>\n",
       "      <td>2010.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>YearRemodAdd</th>\n",
       "      <td>1460.0</td>\n",
       "      <td>1984.865753</td>\n",
       "      <td>20.645407</td>\n",
       "      <td>1950.0</td>\n",
       "      <td>1967.00</td>\n",
       "      <td>1994.000000</td>\n",
       "      <td>2004.00</td>\n",
       "      <td>2010.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>MasVnrArea</th>\n",
       "      <td>1460.0</td>\n",
       "      <td>103.685262</td>\n",
       "      <td>180.569112</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>164.25</td>\n",
       "      <td>1600.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>BsmtFinSF1</th>\n",
       "      <td>1460.0</td>\n",
       "      <td>443.639726</td>\n",
       "      <td>456.098091</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.00</td>\n",
       "      <td>383.500000</td>\n",
       "      <td>712.25</td>\n",
       "      <td>5644.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>BsmtFinSF2</th>\n",
       "      <td>1460.0</td>\n",
       "      <td>46.549315</td>\n",
       "      <td>161.319273</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.00</td>\n",
       "      <td>1474.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>BsmtUnfSF</th>\n",
       "      <td>1460.0</td>\n",
       "      <td>567.240411</td>\n",
       "      <td>441.866955</td>\n",
       "      <td>0.0</td>\n",
       "      <td>223.00</td>\n",
       "      <td>477.500000</td>\n",
       "      <td>808.00</td>\n",
       "      <td>2336.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>TotalBsmtSF</th>\n",
       "      <td>1460.0</td>\n",
       "      <td>1057.429452</td>\n",
       "      <td>438.705324</td>\n",
       "      <td>0.0</td>\n",
       "      <td>795.75</td>\n",
       "      <td>991.500000</td>\n",
       "      <td>1298.25</td>\n",
       "      <td>6110.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1stFlrSF</th>\n",
       "      <td>1460.0</td>\n",
       "      <td>1162.626712</td>\n",
       "      <td>386.587738</td>\n",
       "      <td>334.0</td>\n",
       "      <td>882.00</td>\n",
       "      <td>1087.000000</td>\n",
       "      <td>1391.25</td>\n",
       "      <td>4692.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2ndFlrSF</th>\n",
       "      <td>1460.0</td>\n",
       "      <td>346.992466</td>\n",
       "      <td>436.528436</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>728.00</td>\n",
       "      <td>2065.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>LowQualFinSF</th>\n",
       "      <td>1460.0</td>\n",
       "      <td>5.844521</td>\n",
       "      <td>48.623081</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.00</td>\n",
       "      <td>572.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>GrLivArea</th>\n",
       "      <td>1460.0</td>\n",
       "      <td>1515.463699</td>\n",
       "      <td>525.480383</td>\n",
       "      <td>334.0</td>\n",
       "      <td>1129.50</td>\n",
       "      <td>1464.000000</td>\n",
       "      <td>1776.75</td>\n",
       "      <td>5642.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>BsmtFullBath</th>\n",
       "      <td>1460.0</td>\n",
       "      <td>0.425342</td>\n",
       "      <td>0.518911</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.00</td>\n",
       "      <td>3.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>BsmtHalfBath</th>\n",
       "      <td>1460.0</td>\n",
       "      <td>0.057534</td>\n",
       "      <td>0.238753</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.00</td>\n",
       "      <td>2.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>FullBath</th>\n",
       "      <td>1460.0</td>\n",
       "      <td>1.565068</td>\n",
       "      <td>0.550916</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.00</td>\n",
       "      <td>2.000000</td>\n",
       "      <td>2.00</td>\n",
       "      <td>3.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>HalfBath</th>\n",
       "      <td>1460.0</td>\n",
       "      <td>0.382877</td>\n",
       "      <td>0.502885</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.00</td>\n",
       "      <td>2.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>BedroomAbvGr</th>\n",
       "      <td>1460.0</td>\n",
       "      <td>2.866438</td>\n",
       "      <td>0.815778</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2.00</td>\n",
       "      <td>3.000000</td>\n",
       "      <td>3.00</td>\n",
       "      <td>8.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>KitchenAbvGr</th>\n",
       "      <td>1460.0</td>\n",
       "      <td>1.046575</td>\n",
       "      <td>0.220338</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.00</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.00</td>\n",
       "      <td>3.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>TotRmsAbvGrd</th>\n",
       "      <td>1460.0</td>\n",
       "      <td>6.517808</td>\n",
       "      <td>1.625393</td>\n",
       "      <td>2.0</td>\n",
       "      <td>5.00</td>\n",
       "      <td>6.000000</td>\n",
       "      <td>7.00</td>\n",
       "      <td>14.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Fireplaces</th>\n",
       "      <td>1460.0</td>\n",
       "      <td>0.613014</td>\n",
       "      <td>0.644666</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.00</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.00</td>\n",
       "      <td>3.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>GarageYrBlt</th>\n",
       "      <td>1460.0</td>\n",
       "      <td>1978.506164</td>\n",
       "      <td>23.994583</td>\n",
       "      <td>1900.0</td>\n",
       "      <td>1962.00</td>\n",
       "      <td>1978.506164</td>\n",
       "      <td>2001.00</td>\n",
       "      <td>2010.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>GarageCars</th>\n",
       "      <td>1460.0</td>\n",
       "      <td>1.767123</td>\n",
       "      <td>0.747315</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.00</td>\n",
       "      <td>2.000000</td>\n",
       "      <td>2.00</td>\n",
       "      <td>4.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>GarageArea</th>\n",
       "      <td>1460.0</td>\n",
       "      <td>472.980137</td>\n",
       "      <td>213.804841</td>\n",
       "      <td>0.0</td>\n",
       "      <td>334.50</td>\n",
       "      <td>480.000000</td>\n",
       "      <td>576.00</td>\n",
       "      <td>1418.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>WoodDeckSF</th>\n",
       "      <td>1460.0</td>\n",
       "      <td>94.244521</td>\n",
       "      <td>125.338794</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>168.00</td>\n",
       "      <td>857.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>OpenPorchSF</th>\n",
       "      <td>1460.0</td>\n",
       "      <td>46.660274</td>\n",
       "      <td>66.256028</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.00</td>\n",
       "      <td>25.000000</td>\n",
       "      <td>68.00</td>\n",
       "      <td>547.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>EnclosedPorch</th>\n",
       "      <td>1460.0</td>\n",
       "      <td>21.954110</td>\n",
       "      <td>61.119149</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.00</td>\n",
       "      <td>552.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3SsnPorch</th>\n",
       "      <td>1460.0</td>\n",
       "      <td>3.409589</td>\n",
       "      <td>29.317331</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.00</td>\n",
       "      <td>508.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ScreenPorch</th>\n",
       "      <td>1460.0</td>\n",
       "      <td>15.060959</td>\n",
       "      <td>55.757415</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.00</td>\n",
       "      <td>480.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>PoolArea</th>\n",
       "      <td>1460.0</td>\n",
       "      <td>2.758904</td>\n",
       "      <td>40.177307</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.00</td>\n",
       "      <td>738.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>MiscVal</th>\n",
       "      <td>1460.0</td>\n",
       "      <td>43.489041</td>\n",
       "      <td>496.123024</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.00</td>\n",
       "      <td>15500.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>MoSold</th>\n",
       "      <td>1460.0</td>\n",
       "      <td>6.321918</td>\n",
       "      <td>2.703626</td>\n",
       "      <td>1.0</td>\n",
       "      <td>5.00</td>\n",
       "      <td>6.000000</td>\n",
       "      <td>8.00</td>\n",
       "      <td>12.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>YrSold</th>\n",
       "      <td>1460.0</td>\n",
       "      <td>2007.815753</td>\n",
       "      <td>1.328095</td>\n",
       "      <td>2006.0</td>\n",
       "      <td>2007.00</td>\n",
       "      <td>2008.000000</td>\n",
       "      <td>2009.00</td>\n",
       "      <td>2010.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>SalePrice</th>\n",
       "      <td>1460.0</td>\n",
       "      <td>180921.195890</td>\n",
       "      <td>79442.502883</td>\n",
       "      <td>34900.0</td>\n",
       "      <td>129975.00</td>\n",
       "      <td>163000.000000</td>\n",
       "      <td>214000.00</td>\n",
       "      <td>755000.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                count           mean           std      min        25%  \\\n",
       "Id             1460.0     730.500000    421.610009      1.0     365.75   \n",
       "MSSubClass     1460.0      56.897260     42.300571     20.0      20.00   \n",
       "LotFrontage    1460.0      70.049958     22.024023     21.0      60.00   \n",
       "LotArea        1460.0   10516.828082   9981.264932   1300.0    7553.50   \n",
       "OverallQual    1460.0       6.099315      1.382997      1.0       5.00   \n",
       "OverallCond    1460.0       5.575342      1.112799      1.0       5.00   \n",
       "YearBuilt      1460.0    1971.267808     30.202904   1872.0    1954.00   \n",
       "YearRemodAdd   1460.0    1984.865753     20.645407   1950.0    1967.00   \n",
       "MasVnrArea     1460.0     103.685262    180.569112      0.0       0.00   \n",
       "BsmtFinSF1     1460.0     443.639726    456.098091      0.0       0.00   \n",
       "BsmtFinSF2     1460.0      46.549315    161.319273      0.0       0.00   \n",
       "BsmtUnfSF      1460.0     567.240411    441.866955      0.0     223.00   \n",
       "TotalBsmtSF    1460.0    1057.429452    438.705324      0.0     795.75   \n",
       "1stFlrSF       1460.0    1162.626712    386.587738    334.0     882.00   \n",
       "2ndFlrSF       1460.0     346.992466    436.528436      0.0       0.00   \n",
       "LowQualFinSF   1460.0       5.844521     48.623081      0.0       0.00   \n",
       "GrLivArea      1460.0    1515.463699    525.480383    334.0    1129.50   \n",
       "BsmtFullBath   1460.0       0.425342      0.518911      0.0       0.00   \n",
       "BsmtHalfBath   1460.0       0.057534      0.238753      0.0       0.00   \n",
       "FullBath       1460.0       1.565068      0.550916      0.0       1.00   \n",
       "HalfBath       1460.0       0.382877      0.502885      0.0       0.00   \n",
       "BedroomAbvGr   1460.0       2.866438      0.815778      0.0       2.00   \n",
       "KitchenAbvGr   1460.0       1.046575      0.220338      0.0       1.00   \n",
       "TotRmsAbvGrd   1460.0       6.517808      1.625393      2.0       5.00   \n",
       "Fireplaces     1460.0       0.613014      0.644666      0.0       0.00   \n",
       "GarageYrBlt    1460.0    1978.506164     23.994583   1900.0    1962.00   \n",
       "GarageCars     1460.0       1.767123      0.747315      0.0       1.00   \n",
       "GarageArea     1460.0     472.980137    213.804841      0.0     334.50   \n",
       "WoodDeckSF     1460.0      94.244521    125.338794      0.0       0.00   \n",
       "OpenPorchSF    1460.0      46.660274     66.256028      0.0       0.00   \n",
       "EnclosedPorch  1460.0      21.954110     61.119149      0.0       0.00   \n",
       "3SsnPorch      1460.0       3.409589     29.317331      0.0       0.00   \n",
       "ScreenPorch    1460.0      15.060959     55.757415      0.0       0.00   \n",
       "PoolArea       1460.0       2.758904     40.177307      0.0       0.00   \n",
       "MiscVal        1460.0      43.489041    496.123024      0.0       0.00   \n",
       "MoSold         1460.0       6.321918      2.703626      1.0       5.00   \n",
       "YrSold         1460.0    2007.815753      1.328095   2006.0    2007.00   \n",
       "SalePrice      1460.0  180921.195890  79442.502883  34900.0  129975.00   \n",
       "\n",
       "                         50%        75%       max  \n",
       "Id                730.500000    1095.25    1460.0  \n",
       "MSSubClass         50.000000      70.00     190.0  \n",
       "LotFrontage        70.049958      79.00     313.0  \n",
       "LotArea          9478.500000   11601.50  215245.0  \n",
       "OverallQual         6.000000       7.00      10.0  \n",
       "OverallCond         5.000000       6.00       9.0  \n",
       "YearBuilt        1973.000000    2000.00    2010.0  \n",
       "YearRemodAdd     1994.000000    2004.00    2010.0  \n",
       "MasVnrArea          0.000000     164.25    1600.0  \n",
       "BsmtFinSF1        383.500000     712.25    5644.0  \n",
       "BsmtFinSF2          0.000000       0.00    1474.0  \n",
       "BsmtUnfSF         477.500000     808.00    2336.0  \n",
       "TotalBsmtSF       991.500000    1298.25    6110.0  \n",
       "1stFlrSF         1087.000000    1391.25    4692.0  \n",
       "2ndFlrSF            0.000000     728.00    2065.0  \n",
       "LowQualFinSF        0.000000       0.00     572.0  \n",
       "GrLivArea        1464.000000    1776.75    5642.0  \n",
       "BsmtFullBath        0.000000       1.00       3.0  \n",
       "BsmtHalfBath        0.000000       0.00       2.0  \n",
       "FullBath            2.000000       2.00       3.0  \n",
       "HalfBath            0.000000       1.00       2.0  \n",
       "BedroomAbvGr        3.000000       3.00       8.0  \n",
       "KitchenAbvGr        1.000000       1.00       3.0  \n",
       "TotRmsAbvGrd        6.000000       7.00      14.0  \n",
       "Fireplaces          1.000000       1.00       3.0  \n",
       "GarageYrBlt      1978.506164    2001.00    2010.0  \n",
       "GarageCars          2.000000       2.00       4.0  \n",
       "GarageArea        480.000000     576.00    1418.0  \n",
       "WoodDeckSF          0.000000     168.00     857.0  \n",
       "OpenPorchSF        25.000000      68.00     547.0  \n",
       "EnclosedPorch       0.000000       0.00     552.0  \n",
       "3SsnPorch           0.000000       0.00     508.0  \n",
       "ScreenPorch         0.000000       0.00     480.0  \n",
       "PoolArea            0.000000       0.00     738.0  \n",
       "MiscVal             0.000000       0.00   15500.0  \n",
       "MoSold              6.000000       8.00      12.0  \n",
       "YrSold           2008.000000    2009.00    2010.0  \n",
       "SalePrice      163000.000000  214000.00  755000.0  "
      ]
     },
     "execution_count": 110,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.describe().T"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## missing value handling"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Id 0\n",
      "MSSubClass 0\n",
      "MSZoning 0\n",
      "LotFrontage 259\n",
      "LotArea 0\n",
      "Street 0\n",
      "Alley 1369\n",
      "LotShape 0\n",
      "LandContour 0\n",
      "Utilities 0\n",
      "LotConfig 0\n",
      "LandSlope 0\n",
      "Neighborhood 0\n",
      "Condition1 0\n",
      "Condition2 0\n",
      "BldgType 0\n",
      "HouseStyle 0\n",
      "OverallQual 0\n",
      "OverallCond 0\n",
      "YearBuilt 0\n",
      "YearRemodAdd 0\n",
      "RoofStyle 0\n",
      "RoofMatl 0\n",
      "Exterior1st 0\n",
      "Exterior2nd 0\n",
      "MasVnrType 872\n",
      "MasVnrArea 8\n",
      "ExterQual 0\n",
      "ExterCond 0\n",
      "Foundation 0\n",
      "BsmtQual 37\n",
      "BsmtCond 37\n",
      "BsmtExposure 38\n",
      "BsmtFinType1 37\n",
      "BsmtFinSF1 0\n",
      "BsmtFinType2 38\n",
      "BsmtFinSF2 0\n",
      "BsmtUnfSF 0\n",
      "TotalBsmtSF 0\n",
      "Heating 0\n",
      "HeatingQC 0\n",
      "CentralAir 0\n",
      "Electrical 1\n",
      "1stFlrSF 0\n",
      "2ndFlrSF 0\n",
      "LowQualFinSF 0\n",
      "GrLivArea 0\n",
      "BsmtFullBath 0\n",
      "BsmtHalfBath 0\n",
      "FullBath 0\n",
      "HalfBath 0\n",
      "BedroomAbvGr 0\n",
      "KitchenAbvGr 0\n",
      "KitchenQual 0\n",
      "TotRmsAbvGrd 0\n",
      "Functional 0\n",
      "Fireplaces 0\n",
      "FireplaceQu 690\n",
      "GarageType 81\n",
      "GarageYrBlt 81\n",
      "GarageFinish 81\n",
      "GarageCars 0\n",
      "GarageArea 0\n",
      "GarageQual 81\n",
      "GarageCond 81\n",
      "PavedDrive 0\n",
      "WoodDeckSF 0\n",
      "OpenPorchSF 0\n",
      "EnclosedPorch 0\n",
      "3SsnPorch 0\n",
      "ScreenPorch 0\n",
      "PoolArea 0\n",
      "PoolQC 1453\n",
      "Fence 1179\n",
      "MiscFeature 1406\n",
      "MiscVal 0\n",
      "MoSold 0\n",
      "YrSold 0\n",
      "SaleType 0\n",
      "SaleCondition 0\n",
      "SalePrice 0\n"
     ]
    }
   ],
   "source": [
    "for column in df.columns:\n",
    "    print(column, df[column].isna().sum())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [],
   "source": [
    "df.drop(df.columns[df.isnull().mean() > 0.40], axis=1, inplace=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "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>LotFrontage</th>\n",
       "      <th>MasVnrArea</th>\n",
       "      <th>BsmtQual</th>\n",
       "      <th>BsmtCond</th>\n",
       "      <th>BsmtExposure</th>\n",
       "      <th>BsmtFinType1</th>\n",
       "      <th>BsmtFinType2</th>\n",
       "      <th>Electrical</th>\n",
       "      <th>GarageType</th>\n",
       "      <th>GarageYrBlt</th>\n",
       "      <th>GarageFinish</th>\n",
       "      <th>GarageQual</th>\n",
       "      <th>GarageCond</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>65.0</td>\n",
       "      <td>196.0</td>\n",
       "      <td>Gd</td>\n",
       "      <td>TA</td>\n",
       "      <td>No</td>\n",
       "      <td>GLQ</td>\n",
       "      <td>Unf</td>\n",
       "      <td>SBrkr</td>\n",
       "      <td>Attchd</td>\n",
       "      <td>2003.0</td>\n",
       "      <td>RFn</td>\n",
       "      <td>TA</td>\n",
       "      <td>TA</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>80.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>Gd</td>\n",
       "      <td>TA</td>\n",
       "      <td>Gd</td>\n",
       "      <td>ALQ</td>\n",
       "      <td>Unf</td>\n",
       "      <td>SBrkr</td>\n",
       "      <td>Attchd</td>\n",
       "      <td>1976.0</td>\n",
       "      <td>RFn</td>\n",
       "      <td>TA</td>\n",
       "      <td>TA</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>68.0</td>\n",
       "      <td>162.0</td>\n",
       "      <td>Gd</td>\n",
       "      <td>TA</td>\n",
       "      <td>Mn</td>\n",
       "      <td>GLQ</td>\n",
       "      <td>Unf</td>\n",
       "      <td>SBrkr</td>\n",
       "      <td>Attchd</td>\n",
       "      <td>2001.0</td>\n",
       "      <td>RFn</td>\n",
       "      <td>TA</td>\n",
       "      <td>TA</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>60.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>TA</td>\n",
       "      <td>Gd</td>\n",
       "      <td>No</td>\n",
       "      <td>ALQ</td>\n",
       "      <td>Unf</td>\n",
       "      <td>SBrkr</td>\n",
       "      <td>Detchd</td>\n",
       "      <td>1998.0</td>\n",
       "      <td>Unf</td>\n",
       "      <td>TA</td>\n",
       "      <td>TA</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>84.0</td>\n",
       "      <td>350.0</td>\n",
       "      <td>Gd</td>\n",
       "      <td>TA</td>\n",
       "      <td>Av</td>\n",
       "      <td>GLQ</td>\n",
       "      <td>Unf</td>\n",
       "      <td>SBrkr</td>\n",
       "      <td>Attchd</td>\n",
       "      <td>2000.0</td>\n",
       "      <td>RFn</td>\n",
       "      <td>TA</td>\n",
       "      <td>TA</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   LotFrontage  MasVnrArea BsmtQual BsmtCond BsmtExposure BsmtFinType1  \\\n",
       "0         65.0       196.0       Gd       TA           No          GLQ   \n",
       "1         80.0         0.0       Gd       TA           Gd          ALQ   \n",
       "2         68.0       162.0       Gd       TA           Mn          GLQ   \n",
       "3         60.0         0.0       TA       Gd           No          ALQ   \n",
       "4         84.0       350.0       Gd       TA           Av          GLQ   \n",
       "\n",
       "  BsmtFinType2 Electrical GarageType  GarageYrBlt GarageFinish GarageQual  \\\n",
       "0          Unf      SBrkr     Attchd       2003.0          RFn         TA   \n",
       "1          Unf      SBrkr     Attchd       1976.0          RFn         TA   \n",
       "2          Unf      SBrkr     Attchd       2001.0          RFn         TA   \n",
       "3          Unf      SBrkr     Detchd       1998.0          Unf         TA   \n",
       "4          Unf      SBrkr     Attchd       2000.0          RFn         TA   \n",
       "\n",
       "  GarageCond  \n",
       "0         TA  \n",
       "1         TA  \n",
       "2         TA  \n",
       "3         TA  \n",
       "4         TA  "
      ]
     },
     "execution_count": 27,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "missing_values = df.isna().sum()\n",
    "columns_with_missing = missing_values[missing_values > 0]\n",
    "df[columns_with_missing.index].head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "LotFrontage     float64\n",
       "MasVnrArea      float64\n",
       "BsmtQual         object\n",
       "BsmtCond         object\n",
       "BsmtExposure     object\n",
       "BsmtFinType1     object\n",
       "BsmtFinType2     object\n",
       "Electrical       object\n",
       "GarageType       object\n",
       "GarageYrBlt     float64\n",
       "GarageFinish     object\n",
       "GarageQual       object\n",
       "GarageCond       object\n",
       "dtype: object"
      ]
     },
     "execution_count": 28,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df[columns_with_missing.index].dtypes"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### float values"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {},
   "outputs": [],
   "source": [
    "LotFrontage_mean = df[\"LotFrontage\"].mean()\n",
    "MasVnrArea_mean = df[\"MasVnrArea\"].mean()\n",
    "GarageYrBlt_mean = df[\"GarageYrBlt\"].mean()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {},
   "outputs": [],
   "source": [
    "df[\"LotFrontage\"].fillna(LotFrontage_mean, inplace=True)\n",
    "df[\"MasVnrArea\"].fillna(MasVnrArea_mean, inplace=True)\n",
    "df[\"GarageYrBlt\"].fillna(GarageYrBlt_mean, inplace=True)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### object values"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "LotFrontage     259\n",
       "MasVnrArea        8\n",
       "BsmtQual         37\n",
       "BsmtCond         37\n",
       "BsmtExposure     38\n",
       "BsmtFinType1     37\n",
       "BsmtFinType2     38\n",
       "Electrical        1\n",
       "GarageType       81\n",
       "GarageYrBlt      81\n",
       "GarageFinish     81\n",
       "GarageQual       81\n",
       "GarageCond       81\n",
       "dtype: int64"
      ]
     },
     "execution_count": 31,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "columns_with_missing"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {},
   "outputs": [],
   "source": [
    "df = df.fillna(df.mode().iloc[0])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Id 0\n",
      "MSSubClass 0\n",
      "MSZoning 0\n",
      "LotFrontage 0\n",
      "LotArea 0\n",
      "Street 0\n",
      "LotShape 0\n",
      "LandContour 0\n",
      "Utilities 0\n",
      "LotConfig 0\n",
      "LandSlope 0\n",
      "Neighborhood 0\n",
      "Condition1 0\n",
      "Condition2 0\n",
      "BldgType 0\n",
      "HouseStyle 0\n",
      "OverallQual 0\n",
      "OverallCond 0\n",
      "YearBuilt 0\n",
      "YearRemodAdd 0\n",
      "RoofStyle 0\n",
      "RoofMatl 0\n",
      "Exterior1st 0\n",
      "Exterior2nd 0\n",
      "MasVnrArea 0\n",
      "ExterQual 0\n",
      "ExterCond 0\n",
      "Foundation 0\n",
      "BsmtQual 0\n",
      "BsmtCond 0\n",
      "BsmtExposure 0\n",
      "BsmtFinType1 0\n",
      "BsmtFinSF1 0\n",
      "BsmtFinType2 0\n",
      "BsmtFinSF2 0\n",
      "BsmtUnfSF 0\n",
      "TotalBsmtSF 0\n",
      "Heating 0\n",
      "HeatingQC 0\n",
      "CentralAir 0\n",
      "Electrical 0\n",
      "1stFlrSF 0\n",
      "2ndFlrSF 0\n",
      "LowQualFinSF 0\n",
      "GrLivArea 0\n",
      "BsmtFullBath 0\n",
      "BsmtHalfBath 0\n",
      "FullBath 0\n",
      "HalfBath 0\n",
      "BedroomAbvGr 0\n",
      "KitchenAbvGr 0\n",
      "KitchenQual 0\n",
      "TotRmsAbvGrd 0\n",
      "Functional 0\n",
      "Fireplaces 0\n",
      "GarageType 0\n",
      "GarageYrBlt 0\n",
      "GarageFinish 0\n",
      "GarageCars 0\n",
      "GarageArea 0\n",
      "GarageQual 0\n",
      "GarageCond 0\n",
      "PavedDrive 0\n",
      "WoodDeckSF 0\n",
      "OpenPorchSF 0\n",
      "EnclosedPorch 0\n",
      "3SsnPorch 0\n",
      "ScreenPorch 0\n",
      "PoolArea 0\n",
      "MiscVal 0\n",
      "MoSold 0\n",
      "YrSold 0\n",
      "SaleType 0\n",
      "SaleCondition 0\n",
      "SalePrice 0\n"
     ]
    }
   ],
   "source": [
    "for column in df.columns:\n",
    "    print(column, df[column].isna().sum())"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Visualizing"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 115,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1000x500 with 9 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "import seaborn as sns\n",
    "\n",
    "fig, axes = plt.subplots(nrows=3, ncols=3, figsize=(10, 5))\n",
    "\n",
    "sns.countplot(data=df, x='MSZoning', ax=axes[0, 0])\n",
    "sns.countplot(data=df, x='LotShape', ax=axes[0, 1])\n",
    "sns.countplot(data=df, x='Utilities', ax=axes[1, 0])\n",
    "sns.countplot(data=df, x='Functional', ax=axes[1, 1])\n",
    "sns.countplot(data=df, x='LandContour', ax=axes[0, 2])\n",
    "sns.countplot(data=df, x='OverallQual', ax=axes[1, 2])\n",
    "sns.countplot(data=df, x='Foundation', ax=axes[2, 0])\n",
    "sns.countplot(data=df, x='SaleCondition', ax=axes[2, 1])\n",
    "sns.countplot(data=df, x='OverallCond', ax=axes[2, 2])\n",
    "plt.tight_layout()\n",
    "plt.show()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 131,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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aNFGbNm2STXvjjTdUvHhxrV692nY+/ZkzZ7RixQoVLlxY7733XrL569Spo2effVaXL1/W77//nuJvtG/fPtletbt16dIlxV7bV155RZKS1Z2RGn7++WdZLBZ98cUXyQ7RzZ8/v+01vXN9tq6ngwYNko+Pj226m5ubPvnkkxS1WywWGYYhV1fXVPes5cuX757P28rd3V21a9fWrl27dOXKFUnS+vXrlZCQoH79+snPzy/ZXnDrv++3pzu9vvnmm2SndOTPn1/t27fX1atXUz28+H4WLFig4cOHp/qf9XD3tLAeWjto0KBk672Li0uqr8Wd0rpOXbp0SdOmTVO1atVSrFNubm62Q+xnzJiR7D5nZ+dUB1jMjIHszp8/L0kKCgp64LzWeeLj43Xp0iVJtw87LlmypBYuXKjLly8nm9/a0zv3wP7yyy+KiorS8OHDVaZMmWTzlytXTr169dLu3bt16NChFH//vffeU9GiRVNMd3V1VaFChVJMz5Mnj3r27KkrV65o+/btD3x+6WHtW758+R54epK7u7vtvXn27NmH+rupnf7h4OCgvn37Srp9qpAZ3Nzc1KNHD4WHh2vBggXJ7vv+++8lSa+++qopfxtAcgykBiDdrIcRNmnSJMV9JUuWVKFChRQaGqqrV68mC7pOTk6qU6dOisdYz/HbvXu3OQWb7OWXX9Y333yjyZMnq1+/fipXrlyq823evFnS7R8BUhu0LjIyUpLueU6plbVP9erVS3Ffrly5VKlSpRTnFFpVqlQp1SAQFBRkq+9uDRs2TDHN0dFR9erV04kTJ7R7924FBwfb6qpfv76cnZ1TPKZJkyaaNm2adu/erW7duiW7r0aNGqn+batq1aqlWrMkWwiVlO4arl+/ruPHj6tgwYKpDlJkXcfvXDet639qfalXr16K/np5ealt27ZauHChKlWqpE6dOql+/fqqWbNmivNJ76dJkyZau3at1q5dq5CQEK1evVrOzs5q2LChGjdurNWrV0uSbt26pfXr16tUqVIKDAxM8/LvJ0+ePCpRokSK6am9BmkxadKkex7SOmzYMA0fPjxNy7nfe6FWrVopznO+U1rXqe3bt+vWrVv3vIyZ9RD2O9+3zz33nMaNG6cyZcro6aefVsOGDVW7du0sNSjiiy++qEGDBum3335T7969JUkXLlzQ8uXLVblyZVWoUME2r3XbsHfv3lR7cPToUUm3e3B3KL/fe/vgwYP6/PPPtX79ep0/fz7FVSgeNuxmlgddHeNBLl26pM8//1xLlizRyZMnU4wBYubzfP311zV27Fh9//336tSpkyTp4sWLmjdvnh5//HE1aNDAtL8N4F+EbgDpZt1zfK+RhAMCAhQWFqaoqKhkXzJ9fX1TDXzWveX3GoTqYVlruNfyrdMzekkdR0dHffbZZ2rTpo3efffdew4CZN3LtHLlyhQDYt0pOjr6vn/PWu+9LmVzv0vc3Os5Ojk53XNAn3st7+7XLS3rhZT6EQV3HjGRmtTqtgaqO6+nm94aMlLz/frv5OSU6p7MmTNnavTo0ZoxY4bt0nxubm7q3LmzxowZk6bLEjVt2lQffvihVq1apZCQEK1atUo1a9aUp6enmjZtqlmzZunAgQO6ceOGrl69queee+6By0yr+603kux2TeP7vRaOjo73PYogreuU9X27ffv2++55vfN9++WXX6pYsWKaNGmSPv30U3366adycnJSq1atNHbs2FR/wEgP6/vl9OnTD5zXOo+Li0uyfnTr1k1DhgzRlClTbKF7+vTpSkxMTHGesbUHDxpzIrVt173e21u2bFGTJk2UmJiopk2bql27dvLy8pKDg4P27NmjBQsWpDoo58Ow1nLp0iXFxsbed293bGys7Xn7+fll+G9GRUWpevXqCg0NVY0aNdStWzf5+PjIyclJUVFR+vrrrzP9ed6pWLFiatGihZYvX64TJ06oePHimjJlim7evMlebuA/xOHlANLNGmLDw8NTvd96CN/de3UuXryY6pdz63LM2gtUqlQpSf/ujbmbdRTukiVLZvhvtG7dWo0bN9ayZcvuORq19fl9/fXXMgzjnv896DB7Ly8vSbf3SqXmXtMz6l7Lu/t1y+h6ISnV0cozIr01ZKRm679T60tiYmKKQbik24eqDhs2TEePHlVYWJimTZumevXqadq0aercuXOanluNGjWUK1cu/fnnn7p06ZL27t1rOzzaukf+zz//tB1antqRKDnN/d4Lt27dsoWmh2F9vd9+++37vm/vHIjQ0dFR/fr10969e3XhwgXNnTtXISEh+uOPP9SyZcuHDlnVq1eXq6urzp0798AjY6zbo1q1aiX70bNQoUJq0qSJtm3bpiNHjki6fWi5s7OzunbtmmoP9u7de98epDYo2L3e2yNHjlRsbKxWrFihpUuX6quvvtJHH32kYcOGqWbNmmlvRjoULlxYQUFBSkxMvOfRQFZr165VYmKivL29kx0e7uDgcM9R31P7QfGnn35SaGiohg4dqq1bt2rChAkaOXKkhg0blmLASLPcPaDaDz/8IDc3txRHHAEwD6EbQLpVrlxZklL90nL8+HGdOXNGRYsWTbEnKTExUZs2bUrxGOtyrMvNbLVq1ZK7u7v++usvXb9+Pdl9SUlJtkt1NW7c+KH+jvXyK/379091r3GtWrUkSRs2bHiov2Pt08aNG1PcFx0drT179jzU8u+W2jm2t27dsv19az131pXal1JrKKlSpUqm1nen9NaQO3duFS9eXGfPnk31Emip1Wz9d2p92bhx4wP3+gYFBem5557T8uXLVaJECW3cuDFN4dDJyUkNGjTQ33//ralTp8owDFvoLlGihAoXLqxVq1Zp9erVcnBwSPP6bA1i9tpb/TDu917YsmXLPcNRetSoUUMODg4Zft/mz59fHTt21KxZs9SkSROdOHFCBw4csN3v6OiY7t67u7vbgvHIkSPvOV9sbKy++OILSf+er34n6yH+U6ZM0Z49e7Rv3z49+eSTKfbsZta2607Hjx+Xj49PqpenS895/ell7cPHH398z8vdJSUl6eOPP5YkPfPMM8nGYsibN68uXLiQ6sj4O3bsSDHt+PHjkmQ7tPtOmfE80/L+bdOmjQoXLqxJkyZpxYoVOnr0qJ5++mnlzZv3of8+gLQhdANIt549e0q6/WXPeh6ydPtD3xo4X3rppVQfO2DAgGR7eS5fvmz70tijRw9T6s2VK5deeOEF3bhxI8X5iN9++61OnTqlFi1aqFixYg/1dypXrqznn39ee/fuTfXavdWqVVP9+vX1+++/2waju9v+/fsVERFx37/Tvn175cmTR9OnT9fevXuT3Tdy5MgMDQh3P6tXr05xma1vv/1WJ06cUOPGjW2XnCpUqJCaN2+uU6dO6auvvko2/9atWzVjxgzlzZtXISEhmVrfnTJSQ8+ePWUYht59991kX1wvXryoESNG2OaxsgaVUaNGJRuEKi4uTgMGDEhRU2RkpPbv359i+o0bNxQdHS0nJye5uLik6flZ915/8skn8vT0tIUh633r1q3TX3/9pYoVKyYb5O1+rIcch4WFpWn+rMS6p27UqFHJTh+Jj49P9VJvGZE/f34999xz2rFjh0aMGJFquDlx4oRCQ0Ml3b7k1l9//ZVinoSEBNv6cue5/Pny5VNkZKRiY2PTVdfIkSPl7++vGTNmaMiQISl+YLhy5Yo6d+6s48ePq1mzZnr22WdTLKNjx47y8vLStGnTNHnyZElK9Vz7Hj162AZ7TG3AxaSkpAfuOb5bkSJFdPnyZe3bty/Z9IkTJ5o2sJh0+4iFsmXLauPGjbZL390pNjZWvXr10saNG+Xv759i4MkaNWooMTExxRFJkydPTvV1t14z++7+7N69+4GD/aVFWt6/Dg4OeuWVVxQREWHblr322msP/bcBpB3ndANItzp16ui9997TZ599pnLlyqlz587y9PTU0qVLdeDAAdWrV0/vvvtuiscFBATo5s2bKleunNq1a6eEhATNmTNH58+fV+/evdM8oMvFixfVv3//ZLcl6aWXXrIdyvjBBx8kGxjr448/1tq1a/XFF19oz549qlGjhg4fPqwFCxYof/78Gj9+/MO0xGbUqFGaPXu2be/G3WbMmKEmTZropZde0jfffKOaNWvK29tbZ86c0b59+3TgwAFt3rxZ+fPnv+ff8PLy0vjx4/XCCy+oTp06evrppxUQEKBNmzZp7969atiwodatW3fPa9CmV9u2bRUSEqKQkBCVKFFCe/bs0dKlS+Xj46MJEyYkm/f//u//VLduXb377rtasWKFqlWrptOnT2v27NlycHDQpEmTUlwrPbOlt4b+/ftr6dKlWrBggSpWrKhWrVopJiZGs2fPVkREhN57771kA3XVrVtXb775psaNG2db/52dnbVgwQLlzZs3xfnhZ8+eVeXKlVW+fHlVqFBBQUFBunbtmhYtWqTw8HC99dZbae6Jdc92RESEWrZsmWywuKZNm9qCU3pGLW/atKlmz56tjh07qlWrVnJ3d1dwcLBeeOGFNC/DXho2bKhXXnlFP/zwg8qWLatOnTrJ2dlZCxcuVJ48eRQYGJgp74Nvv/1Wx44d04cffqipU6eqXr168vf3tx3evX37dv36668qWrSoYmNjVa9ePZUoUUJVq1ZVcHCw4uLitHLlSh0+fFjt2rXT448/blt206ZNtX37drVs2VINGjSQq6urKlasqLZt2963psDAQK1YsULt2rXTyJEjNW3aNLVs2VI+Pj4KCwvT4sWLdeXKFTVr1sy27t/N3d1dTz31lCZOnKgJEyYoX758at26dYr58uXLpzlz5igkJES1atVS06ZNVbZsWVksFp0+fVqbN2/WpUuX0jXgWL9+/bR8+XLVq1dPTz/9tPLkyaMdO3Zo48aN6ty5s+bMmZPmZaWHp6enli1bprZt2+rnn3/WkiVL1KpVKxUoUEAXLlzQkiVLdP78eXl5eWnBggUpRlh/8803NWnSJL3++utatWqVgoKCtGfPHm3evFlt2rRJ8QNlt27d9Pnnn6tfv35as2aNHnvsMR07dkyLFi1Sx44dNXPmzId6Pk2bNtXnn3+uXr16qVOnTsqdO7e8vb31xhtvJJvv5Zdf1kcffaSzZ8+qfPnyql279kP9XQDp9B9dmgxANpXadbqtfv31V6Nu3bpGrly5DFdXV6NMmTLGyJEjjdjY2FSXExwcbERFRRm9e/c2AgMDDRcXF6N06dLG119/bSQlJaW5pjuvOX2v/+6+Tqph3L4m+FtvvWUULlzYcHZ2NgoUKGD06NEj1WvF3s+d1+lOjfVav0rlOt2Gcfs626NGjTKqVKlieHp6Gm5ubkaRIkWMVq1aGd9//70RHR1tm/d+16BdsmSJUbt2bcPd3d3w9vY22rVrZxw+fNho3bq1ISnZdYvvdY1Xq9Su1Xzn3164cKFRq1Ytw8PDw8iTJ4/RsWNH4++//051WWfOnDFee+01W5/z5ctntG/f3ti2bVuKeR90jd0H3S/JaNiw4UPVYBi3r2c7atQoo2zZsoabm5uRK1cuo27dusaMGTNSnT8pKckYN26cUbp0acPFxcUICAgwevfubURFRaW4ju+VK1eM4cOHG40bN7at9wUKFDAaNmxozJgxI13rflJSkuHr62tIMj777LNk9509e9a23i1ZsiTFY+91ne7ExERjwIABRtGiRW3XJb6zpxm5LvG9WN8797umsnWZablOt2Hcvt7xF198YZQqVSrFa5ErVy6jYsWKyebP6Dp18+ZNY9y4cUbt2rUNLy8vw8XFxQgKCjKaNGlifPnll7brrcfHxxujR482WrZsaQQFBRmurq6Gr6+vUbNmTeO7774zbt68mWy50dHRxmuvvWYULFjQcHR0vO/7NDXR0dHG2LFjjbp16xp58+Y1nJ2dDX9/f6N169bGzJkzH7h+bdiwwbbevPHGG/edNzQ01OjTp49RokQJw9XV1cidO7dRqlQp4/nnnzfmzZuXbN77XT/aauHChUbNmjWNXLlyGXny5DGaN29urFu37p6v0cNep/tO8fHxxo8//mg0bdrU8PX1NRwcHGx9aNu2rXH+/Pl7PnbDhg1G/fr1DXd3dyN37txGq1atjL17997z/XDw4EGjbdu2hp+fn+Hh4WFUqVLF+PHHH9N17e37bcPHjh1r2xYplWvTW3Xo0MGQZHz77bdp7BKAzGIxjHuc0AIAmch6iN2pU6fsWkdOd+vWLRUrVkzx8fG2QcCAR9GxY8dUsmRJdenSJdXTPYC7rVq1Si1bttRjjz2mdevWPdSo5VlNUlKSSpQooQsXLtj25AP473BONwBkQ1FRUYqJiUk2zTAMjRw5UmFhYaaeNw1kJeHh4SkGLoyJiVG/fv0kifcC0qxp06b67rvvdPjwYTVv3jzd15/PyubMmaPQ0FB169aNwA3YAXu6Afwn2NOduZYtW6ZnnnlGTzzxhIoUKaLo6Ght2bJFe/bsUVBQkHbs2HHf88KBnOKDDz7Qr7/+qkaNGikgIEDh4eFatWqVzpw5oyeffFKLFy/OtEvS4dEwZcoUhYaGqmrVqg88tz6r+/TTT3X58mX98MMPSkxM1KFDh1S4cGF7lwU8cgjdAP4ThO7MFRoaqsGDB+uvv/5SZGSkEhMTVahQIbVp00YDBw6Uv7+/vUsE/hOrVq3SmDFjtGfPHl2+fFlOTk4qWbKkunbtqn79+iUbbA541FgsFjk7O6tMmTL6/PPP1bx5c3uXBDySCN0AAAAAAJiEc7oBAAAAADAJoRsAAAAAAJMQugEAAAAAMImTvQsww5UrV5SYmGjvMrINPz8/RUZG2ruMHIe+moO+moO+moO+moO+moO+moO+moO+moO+po+Tk5Py5s374Pn+g1r+c4mJiUpISLB3GdmC9TIqiYmJYky9zENfzUFfzUFfzUFfzUFfzUFfzUFfzUFfzUFfzcPh5QAAAAAAmITQDQAAAACASQjdAAAAAACYhNANAAAAAIBJCN0AAAAAAJiE0A0AAAAAgEkI3QAAAAAAmITQDQAAAACASQjdAAAAAACYhNANAAAAAIBJCN0AAAAAAJiE0A0AAAAAgEkI3QAAAAAAmITQDQAAAACASQjdAAAAAACYhNANAAAAAIBJCN0AAAAAAJiE0A0AAAAAgEkI3QAAAAAAmMTJ3gU8qgpeuGjvEv4VHmnvCiRJZ/197V0CAAAAAGQq9nQDAAAAAGASQjcAAAAAACYhdAMAAAAAYBJCNwAAAAAAJiF0AwAAAABgEkYvR47CqPApMSo8AAAAYD/s6QYAAAAAwCSEbgAAAAAATELoBgAAAADAJFnqnO6kpCTNmjVLGzZsUFRUlHx8fNSwYUN16tRJFovF3uUBAAAAAJAuWSp0z58/XytXrlSfPn1UqFAhnTx5UhMmTJCHh4datWpl7/IAAAAAAEiXLBW6jx49qmrVqqlKlSqSpPz582vjxo06fvy4nSsDAAAAACD9slToLlmypFatWqVz584pMDBQp06d0t9//61u3bqlOn9CQoISEhJsty0Wi9zd3W3/RvbCa2aOnNRX63PJSc8pK6Cv5qCv5qCv5qCv5qCv5qCv5qCv5rEYhmHYuwirpKQk/frrr/rjjz/k4OCgpKQkdenSRSEhIanOP2vWLM2ZM8d2u2jRoho9evR/Ve5DsezeZ+8SshyjcoWHXgZ9TSkz+goAAAAgY7LUnu7Nmzdr48aNeuuttxQUFKRTp05p8uTJyps3rxo1apRi/pCQELVp08Z22/qrTGRkpBITE/+rspFJzp8/b+8ScqSc1FeLxaICBQooPDxcWej3wmyPvpqDvpqDvpqDvpqDvpqDvpqDvqafk5OT/Pz8Hjzff1BLmk2bNk3t27dX3bp1JUmFCxdWZGSk5s+fn2rodnZ2lrOzc6rLYkXJfnjNzJET+2oYRo58XvZGX81BX81BX81BX81BX81BX81BXzNflrpO982bN+XgkLwkBwcHXnQAAAAAQLaUpfZ0V61aVb///rt8fX1VqFAhnTp1SosWLVLjxo3tXRrwSCt44aK9S/hXeKS9K5AknfX3tXcJAAAAyAayVOju2bOnZs6cqZ9++klXr16Vj4+Pmjdvrs6dO9u7NAAAAAAA0i1LhW53d3d1795d3bt3t3cpAAAAAAA8tCx1TjcAAAAAADkJoRsAAAAAAJMQugEAAAAAMAmhGwAAAAAAkxC6AQAAAAAwCaEbAAAAAACTELoBAAAAADAJoRsAAAAAAJMQugEAAAAAMAmhGwAAAAAAkxC6AQAAAAAwCaEbAAAAAACTELoBAAAAADAJoRsAAAAAAJMQugEAAAAAMAmhGwAAAAAAkxC6AQAAAAAwCaEbAAAAAACTELoBAAAAADAJoRsAAAAAAJMQugEAAAAAMAmhGwAAAAAAkxC6AQAAAAAwCaEbAAAAAACTELoBAAAAADAJoRsAAAAAAJMQugEAAAAAMAmhGwAAAAAAkzjZuwAAeJQVvHDR3iXcFh5p7wokSWf9fe1dAgAAQKZiTzcAAAAAACYhdAMAAAAAYBJCNwAAAAAAJiF0AwAAAABgEkI3AAAAAAAmIXQDAAAAAGASQjcAAAAAACYhdAMAAAAAYBInexcAAEBmK3jhor1LuC080t4VSJLO+vvauwQAAB5ZhG4AAJAm/JiREj9oAAAehMPLAQAAAAAwCaEbAAAAAACTELoBAAAAADBJljqnu0+fPoqMTHme1hNPPKGXX37ZDhUBAAAAAJBxWSp0f/LJJ0pKSrLdDgsL08iRI1W7dm07VgUAAAAAQMZkqdDt5eWV7Pb8+fPl7++vMmXK2KkiAAAAAAAyLkuF7jslJiZqw4YNat26tSwWS6rzJCQkKCEhwXbbYrHI3d3d9m9kL7xm5qCv5qCv5qCv5qCv5skpvbU+j5zyfLIK+moO+moO+mqeLBu6t23bphs3bqhRo0b3nGfevHmaM2eO7XbRokU1evRo+fn5/QcVPqQsdI3RrCIgIODhF0JfU6Cv5siUvkr09i701Rz01TyZ1tssokCBAvYuIUeir+agr+agr5kvy4buNWvWqFKlSvLx8bnnPCEhIWrTpo3ttvVXmcjISCUmJppeIzLX+fPn7V1CjkRfzUFfzUFfzUFfzZNTemuxWFSgQAGFh4fLMAx7l5Nj0Fdz0Fdz0Nf0c3JyStMO3ywZuiMjI7Vv3z7179//vvM5OzvL2dk51ftYUbIfXjNz0Fdz0Fdz0Fdz0Ffz5LTeGoaR455TVkBfzUFfzUFfM1+WvE73mjVrlCdPHlWpUsXepQAAAAAAkGFZLnQnJSVp7dq1atiwoRwdHe1dDgAAAAAAGZblQvf+/ft18eJFNW7c2N6lAAAAAADwULLcOd0VK1bUrFmz7F0GAAAAAAAPLcvt6QYAAAAAIKcgdAMAAAAAYBJCNwAAAAAAJiF0AwAAAABgEkI3AAAAAAAmIXQDAAAAAGASQjcAAAAAACbJctfpBgAAeJQUvHDR3iXcFh5p7wpszvr72rsEAMg07OkGAAAAAMAkhG4AAAAAAExC6AYAAAAAwCSEbgAAAAAATMJAagAAAMhxGKAuJQaoA+yDPd0AAAAAAJiE0A0AAAAAgEkI3QAAAAAAmIRzugEAAACkCefKp8S58ngQ9nQDAAAAAGASQjcAAAAAACYhdAMAAAAAYBJCNwAAAAAAJiF0AwAAAABgEkI3AAAAAAAmIXQDAAAAAGASQjcAAAAAACYhdAMAAAAAYBJCNwAAAAAAJiF0AwAAAABgEkI3AAAAAAAmcbJ3AQAAAADwKCt44aK9S7gtPNLeFdic9fe1dwmZhj3dAAAAAACYhNANAAAAAIBJCN0AAAAAAJiE0A0AAAAAgEkI3QAAAAAAmITQDQAAAACASQjdAAAAAACYhNANAAAAAIBJCN0AAAAAAJiE0A0AAAAAgEkI3QAAAAAAmITQDQAAAACASZzsXcDdLl++rGnTpmnPnj26efOmChQooN69e6t48eL2Lg0AAAAAgHTJUqE7OjpaQ4YMUdmyZTVw4EB5eXnp/Pnz8vT0tHdpAAAAAACkW5YK3QsWLFC+fPnUu3dv27T8+fPbsSIAAAAAADIuS4XuHTt2qGLFivriiy906NAh+fj46IknnlCzZs1SnT8hIUEJCQm22xaLRe7u7rZ/I3vhNTMHfTUHfTUHfTUHfTUPvTUHfTUHfTUHfTVHTuprlgrdERERWrlypVq3bq2QkBCdOHFCkyZNkpOTkxo1apRi/nnz5mnOnDm220WLFtXo0aPl5+f3H1adQeGR9q4gywkICHj4hdDXFOirOTKlrxK9vQt9NQd9NQ/bWHPQV3PQV3PQV3Nk2mdXFpClQndSUpKKFy+url27SrodosPCwrRy5cpUQ3dISIjatGlju239NSQyMlKJiYn/Sc3IPOfPn7d3CTkSfTUHfTUHfTUHfTUPvTUHfTUHfTUHfTVHduirk5NTmnb4ZqnQnTdvXhUqVCjZtEKFCmnr1q2pzu/s7CxnZ+dU7zMMI9Prg7l4zcxBX81BX81BX81BX81Db81BX81BX81BX82Rk/qapa7TXapUKZ07dy7ZtHPnzmWPw8UBAAAAALhLlgrdrVu31rFjx/T7778rPDxcGzdu1KpVq9SiRQt7lwYAAAAAQLplqcPLS5Qoof79+2vGjBmaO3eu8ufPrxdffFH169e3d2kAAAAAAKRblgrdklS1alVVrVrV3mUAAAAAAPDQstTh5QAAAAAA5CSEbgAAAAAATELoBgAAAADAJIRuAAAAAABMQugGAAAAAMAkhG4AAAAAAExC6AYAAAAAwCSEbgAAAAAATELoBgAAAADAJIRuAAAAAABMQugGAAAAAMAkhG4AAAAAAExC6AYAAAAAwCSEbgAAAAAATELoBgAAAADAJIRuAAAAAABMQugGAAAAAMAkhG4AAAAAAExC6AYAAAAAwCSEbgAAAAAATELoBgAAAADAJBkK3ceOHcvsOgAAAAAAyHGcMvKgwYMHq0CBAqpfv77q168vf3//zK4LAAAAAIBsL0Oh+80339SGDRs0d+5czZ49WyVLllT9+vVVp04d5cqVK7NrBAAAAAAgW8pQ6K5Xr57q1auna9euadOmTdq4caMmTpyoKVOmqGLFimrQoIGqVasmJ6cMLR4AAAAAgBzhoVKxl5eXWrZsqZYtWyo8PFwbN27Uxo0b9eWXX8rDw0O1atVSw4YNVbp06cyqFwAAAACAbCPTdkW7uLjI1dVVzs7OkiSLxaIdO3Zo9erVKlasmPr06aNChQpl1p8DAAAAACDLe6jQHRsbqy1btmjjxo06dOiQLBaLKlWqpM6dO6tq1apycHDQtm3b9Msvv2jChAn6+OOPM6tuAAAAAACyvAyF7u3bt2vDhg3atWuXEhISVLx4cb344ouqW7eucufOnWzeWrVqKTo6WhMnTsyUggEAAAAAyC4yFLrHjBmjfPnyqXXr1mrYsKECAwPvO3+RIkVUv379DBUIAAAAAEB2laHQ/eGHH6ps2bJpnr9EiRIqUaJERv4UAAAAAADZlkNGHrRu3TodO3bsnvcfP35cEyZMyHBRAAAAAADkBBkO3RcuXLjn/REREVq3bl2GiwIAAAAAICfIUOh+kMuXL8vFxcWMRQMAAAAAkG2k+Zzu7du3a/v27bbbf/75p/bt25divpiYGO3fv59zuAEAAAAAj7w0h+4zZ85oy5YtttvHjh3TyZMnk81jsVjk6uqqxx9/XN26dcu8KgEAAAAAyIbSHLpDQkIUEhIiSXrmmWf0+uuvq169eqYVBgAAAABAdpehS4bNnDkzs+sAAAAAACDHMWUgNQAAAAAAkMY93c8884wsFoumTZsmJycnPfPMMw98jMVi0W+//fbQBQIAAAAAkF2lKXR36tRJFotFDg4OyW4DAAAAAIB7S1Pofvrpp+97GwAAAAAApJShgdTMMmvWLM2ZMyfZtMDAQH311Vf2KQgAAAAAgIeQptC9bt26DC28YcOG6X5MUFCQhgwZYrttPaQdAAAAAIDsJk2he8KECRlaeEZCt4ODg7y9vTP09wAAAAAAyErSFLq//fZbs+uwCQ8P16uvvipnZ2eVLFlSXbt2la+vb6rzJiQkKCEhwXbbYrHI3d3d9m9kL7xm5qCv5qCv5qCv5qCv5qG35qCv5qCv5qCv5shJfU1T6Pbz8zO7DknSY489pt69eyswMFBXrlzRnDlz9OGHH2rs2LG2MH2nefPmJTsHvGjRoho9evR/Vu9DCY+0dwVZTkBAwMMvhL6mQF/NkSl9lejtXeirOeiredjGmoO+moO+moO+miPTPruygCw1kFrlypVt/w4ODraF8M2bN6tJkyYp5g8JCVGbNm1st62/hkRGRioxMdH8gpGpzp8/b+8SciT6ag76ag76ag76ah56aw76ag76ag76ao7s0FcnJ6c07fDNcOiOiorS6tWrdfLkScXGxiopKSnZ/RaLRR9++GFGFy9J8vT0VGBgoMLDw1O939nZWc7OzqneZxjGQ/1t/Pd4zcxBX81BX81BX81BX81Db81BX81BX81BX82Rk/qaodD9zz//aNiwYYqPj1dgYKDCwsJUqFAhxcTE6PLly/L391e+fPkeuri4uDiFh4erfv36D70sAAAAAAD+axkK3TNmzJCbm5s+//xzubi4qFevXurRo4fKlSunzZs366efftJbb72V7uX+8ssvqlatmnx9fXXlyhXNmjVLDg4OqlevXkbKBAAAAADArjIUuo8cOaL27dvL19dX0dHRkmQ7vLx27do6cuSIpk6dquHDh6druZcvX9bXX3+t69evy8vLS6VLl9aoUaPk5eWVkTIBAAAAALCrDIVuwzCUJ08eSZKHh4ccHBxs4VuSChcurNWrV6d7uf369ctIOQAAAAAAZEkOGXlQ/vz5FRERcXsBDg7Knz+/9u/fb7v/77//lqenZ+ZUCAAAAABANpWhPd0VKlTQli1b9Oyzz0qSmjdvrqlTpyoiIkKGYejgwYNq27ZtphYKAAAAAEB2k6HQ3bFjR9WrV0+JiYlycnJS69atdfPmTW3dulUODg7q1KmTOnbsmNm1AgAAAACQrWQodOfKlUu5cuWy3bZYLOrUqZM6deqUaYUBAAAAAJDdZeicbgAAAAAA8GAZ2tM9YcKEB85jsVj0+uuvZ2TxAAAAAADkCBkK3QcPHkwxLSkpSVFRUUpKSpKXl5dcXV0fujgAAAAAALKzDIXu8ePHpzo9MTFRf/75pxYvXqwhQ4Y8VGEAAAAAAGR3mXpOt5OTk1q2bKmKFStq4sSJmbloAAAAAACyHVMGUgsODtbhw4fNWDQAAAAAANmGKaF73759nNMNAAAAAHjkZeic7jlz5qQ6/caNGzp8+LBCQ0PVvn37hyoMAAAAAIDsLkOhe/bs2alO9/T0lL+/v3r16qWmTZs+VGEAAAAAAGR3GQrdM2fOzOw6AAAAAADIcUw5pxsAAAAAAGRwT/eJEye0c+dOnTlzRrGxscqTJ4/y58+v2rVrKygoKLNrBAAAAAAgW0pX6L527ZomTJig3bt3p3r/3LlzVa1aNfXu3Vuenp6SpFOnTqlIkSIPXSgAAAAAANlNmkN3fHy8RowYodOnT6tRo0Zq2LChgoOD5e7urtjYWP3zzz9at26d1q1bp+HDh+uTTz7R/v379eWXX2rKlClmPgcAAAAAALKkNIfuRYsW6fTp03rvvfdUpUqVZPd5enqqTJkyKlOmjGrWrKnPPvtMn376qQ4ePKjg4OBMLxoAAAAAgOwgzQOpbdq0SfXq1UsRuO9WpUoV1atXT/v27VO5cuU0bNiwh60RAAAAAIBsKc2h+8KFC3r88cfTNK91vg8++ECurq4ZqwwAAAAAgGwuzaHbyclJN2/eTNO88fHxcnd3l4MDVyQDAAAAADy60pyKCxcurG3btqVp3q1bt3IuNwAAAADgkZfm0N20aVMdPnxY06dPV1JSUqrzGIahGTNm6PDhw2ratGmmFQkAAAAAQHaU5tHLGzRooJ07d+qPP/7Qjh07VK9ePQUHB8vNzU1xcXH6559/tHHjRp07d061a9dWgwYNzKwbAAAAAIAsL82hW5L69u2rIkWKaOHChZo1a1aK+z08PPTss8+qXbt2mVYgAAAAAADZVbpCt4ODg0JCQtS6dWsdOXJEZ86cUVxcnNzc3FSoUCGVLl1aLi4uZtUKAAAAAEC2kq7QbeXi4qIKFSqoQoUKmV0PAAAAAAA5Btf0AgAAAADAJIRuAAAAAABMQugGAAAAAMAkhG4AAAAAAExC6AYAAAAAwCSEbgAAAAAATJKmS4b16dNHFoslXQu2WCwaN25chooCAAAAACAnSFPoLlOmTLpDNwAAAAAAj7o07+kGAAAAAADpwzndAAAAAACYJE17ug8dOpShhZcpUyZDjwMAAAAAICdIU+gePnx4hhY+c+bMDD0OAAAAAICcIE2he+jQoWbXAQAAAABAjpPm0csBAAAAAED6ZNmB1ObPn6+nn35akydPtncpAAAAAABkSJr2dKcmPj5eW7duVWhoqGJiYpSUlJTsfovFotdffz1Dyz5+/LhWrlyp4ODgjJYHAAAAAIDdZSh0R0ZGavjw4YqMjJSHh4diYmKUK1cuW/jOnTu33NzcMlRQXFycxo0bp1dffVW///57hpYBAAAAAEBWkKHQPXXqVMXExGjUqFHKnz+/evXqpbffflulSpXS0qVLtWzZMg0aNChDBf3000+qXLmyKlSo8MDQnZCQoISEBNtti8Uid3d327+RvfCamYO+moO+moO+moO+mofemoO+moO+moO+miMn9TVDofvgwYN64oknVKJECUVHR0uSDMOQs7Oz2rVrpzNnzmjy5MkaMGBAupb7119/KTQ0VJ988kma5p83b57mzJlju120aFGNHj1afn5+6fq7dhEeae8KspyAgICHXwh9TYG+miNT+irR27vQV3PQV/OwjTUHfTUHfTUHfTVHpn12ZQEZCt03b95U/vz5Jcm2ZzkmJsZ2f8mSJTV16tR0LfPixYuaPHmyBg8eLBcXlzQ9JiQkRG3atLHdtv4aEhkZqcTExHT9fdjf+fPn7V1CjkRfzUFfzUFfzUFfzUNvzUFfzUFfzUFfzZEd+urk5JSmHb4ZCt2+vr66dOmSJMnR0VE+Pj46duyYatasKUk6c+ZMmoOz1cmTJ3X16lW9//77tmlJSUk6fPiwli1bphkzZsjBIflg687OznJ2dk51eYZhpOvvw/54zcxBX81BX81BX81BX81Db81BX81BX81BX82Rk/qaodBdrlw57dixQ0899ZQkqVGjRpo/f76io6NlGIbWr1+vhg0bpmuZ5cuX15gxY5JN++677xQYGKj27dunCNwAAAAAAGR1GQrdHTp00PHjx5WQkCBnZ2eFhIToypUr2rp1qxwcHFSvXj1169YtXct0d3dX4cKFk01zdXVV7ty5U0wHAAAAACA7yPDh5b6+vrbbLi4ueu211/Taa69lWmEAAAAAAGR36Q7dN2/e1Ouvv64OHTqoXbt2ZtRkM2zYMFOXDwAAAACAmdJ9orSrq6scHR3l6upqRj0AAAAAAOQYGRqdrGbNmtqyZUuOGlEOAAAAAIDMlqFzuuvUqaOJEydq+PDhatq0qfz8/FK9RFixYsUeukAAAAAAALKrDIXu4cOH2/59+PDhe843c+bMjCweAAAAAIAcIUOh+/XXX8/sOgAAAAAAyHEyFLobNWqUyWUAAAAAAJDzZGggtTtduXJFp06dUlxcXGbUAwAAAABAjpHh0L19+3b169dPr732mt5//30dP35cknTt2jW999572rZtW6YVCQAAAABAdpSh0L1jxw6NGTNGuXPn1lNPPZXsPi8vL/n4+Gjt2rWZUR8AAAAAANlWhkL33LlzVaZMGY0YMUItWrRIcX/JkiUVGhr60MUBAAAAAJCdZSh0h4WFqXbt2ve8P0+ePLp27VqGiwIAAAAAICfIUOh2dXW978BpFy5cUK5cuTJcFAAAAAAAOUGGQnfZsmW1bt063bp1K8V9UVFRWrVqlSpWrPjQxQEAAAAAkJ1lKHQ/++yzunz5sgYMGKCVK1dKkvbs2aPffvtN77zzjiSpc+fOmVclAAAAAADZkFNGHhQYGKiPPvpIkydP1syZMyVJCxculCSVKVNGL730kvLnz595VQIAAAAAkA1lKHRLUlBQkIYMGaLo6GiFh4fLMAz5+/vLy8srM+sDAAAAACDbylDoPnPmjAoVKiRJypUrl0qUKJGpRQEAAAAAkBNkKHS/8847CgoKUp06dVSnTh0VKFAgs+sCAAAAACDby1Dofvnll7V582bNmjVLM2fOVJEiRVS3bl3Vrl1bfn5+mV0jAAAAAADZUoZCd/PmzdW8eXNFRUVpy5Yt2rx5s6ZPn67p06erRIkSqlu3rmrVqiUfH5/MrhcAAAAAgGwjwwOpSZK3t7datmypli1b6vLly9q8ebM2b96sX375RVOnTtWvv/6aWXUCAAAAAJDtZOg63anx9vZWUFCQChYsKFdXVyUlJWXWogEAAAAAyJYeak+3YRg6ePCgNm3apO3bt+vatWvKlSuXbYA1AAAAAAAeZRkK3YcPH9bmzZu1ZcsWXb16VR4eHqpevbrq1Kmj8uXLy9HRMbPrBAAAAAAg28lQ6B42bJjc3NxUtWpV1alTR5UqVZKT00PtNAcAAAAAIMfJUFJ+++23VaVKFbm4uGR2PQAAAAAA5BgZCt21atWSJMXFxSk2Nlbu7u5yc3PL1MIAAAAAAMju0h26IyIi9Mcff2jXrl26dOmSbbqPj4+qVq2qdu3aKX/+/JlaJAAAAAAA2VG6Qvf27dv17bffKi4uTn5+fqpatarc3d0VGxursLAwrVy5UuvXr9ebb76p6tWrm1UzAAAAAADZQppD95kzZ/TVV18pf/78euWVV/T444+nmOfw4cP68ccf9dVXX2n06NEqVKhQphYLAAAAAEB24pDWGX///Xflzp1bI0aMSDVwS9Ljjz+ujz76SLlz59a8efMyrUgAAAAAALKjNIfugwcPqkmTJsqVK9d958uVK5caN26sAwcOPHRxAAAAAABkZ2kO3dHR0fLz80vTvPnz51d0dHSGiwIAAAAAICdIc+jOnTu3IiIi0jRvRESEcufOneGiAAAAAADICdIcusuUKaPVq1c/cA92dHS0Vq9erTJlyjx0cQAAAAAAZGdpDt0dO3ZUdHS0hg4dqr///jvVef7++28NHTpU0dHRCgkJybQiAQAAAADIjtJ8ybBChQrprbfe0rfffqsPP/xQ+fPnV3BwsNzc3BQXF6d//vlHERERcnFx0ZtvvqmgoCAz6wYAAAAAIMtLc+iWpJo1a6pIkSJasGCBdu3ape3bt9vu8/b2VtOmTdWuXTsVKFAg0wsFAAAAACC7SVfoliR/f3+98sorkqSYmBjFxcXJzc1NHh4emV4cAAAAAADZWbpD9508PDwI2wAAAAAA3EOaB1IDAAAAAADpQ+gGAAAAAMAkD3V4eWZbsWKFVqxYocjISEm3R0zv3LmzKleubOfKAAAAAABIvywVun18fNS1a1cFBATIMAytW7dOn332mT777DMuQQYAAAAAyHayVOiuVq1astvPPvusVqxYoWPHjhG6AQAAAADZTpYK3XdKSkrS5s2bdfPmTZUsWTLVeRISEpSQkGC7bbFY5O7ubvs3shdeM3PQV3PQV3PQV3PQV/PQW3PQV3PQV3PQV3PkpL5mudAdFhamQYMGKSEhQW5uburfv78KFSqU6rzz5s3TnDlzbLeLFi2q0aNHy8/P778qN+PCI+1dQZYTEBDw8AuhrynQV3NkSl8lensX+moO+moetrHmoK/moK/moK/myLTPrizAYhiGYe8i7pSYmKiLFy8qJiZGW7Zs0apVqzR8+PBUg/e99nRHRkYqMTHxvyw73QJ5Y6VwrsDD/1hCX1Oir+bIjL5K9PZu9NUc9NU8bGPNQV/NQV/NQV/NkVmfXWZycnJK0w7fLLen28nJSQUKFJAkFStWTCdOnNCSJUv0yiuvpJjX2dlZzs7OqS4ni/2WgDTgNTMHfTUHfTUHfTUHfTUPvTUHfTUHfTUHfTVHTuprlr9Od1JSUrK92QAAAAAAZBdZKnTPmDFDhw4dUkREhMLCwmy369evb+/SAAAAAABItyx1ePnVq1c1fvx4XblyRR4eHgoODtagQYNUoUIFe5cGAAAAAEC6ZanQ/frrr9u7BAAAAAAAMk2WOrwcAAAAAICchNANAAAAAIBJCN0AAAAAAJiE0A0AAAAAgEkI3QAAAAAAmITQDQAAAACASQjdAAAAAACYhNANAAAAAIBJCN0AAAAAAJiE0A0AAAAAgEkI3QAAAAAAmITQDQAAAACASQjdAAAAAACYhNANAAAAAIBJCN0AAAAAAJiE0A0AAAAAgEkI3QAAAAAAmITQDQAAAACASQjdAAAAAACYhNANAAAAAIBJCN0AAAAAAJiE0A0AAAAAgEkI3QAAAAAAmITQDQAAAACASQjdAAAAAACYhNANAAAAAIBJCN0AAAAAAJiE0A0AAAAAgEkI3QAAAAAAmITQDQAAAACASQjdAAAAAACYhNANAAAAAIBJCN0AAAAAAJiE0A0AAAAAgEkI3QAAAAAAmITQDQAAAACASQjdAAAAAACYhNANAAAAAIBJCN0AAAAAAJiE0A0AAAAAgEkI3QAAAAAAmITQDQAAAACASZzsXcCd5s2bp23btuns2bNycXFRyZIl9fzzzyswMNDepQEAAAAAkG5ZKnQfOnRILVq0UPHixXXr1i39+uuvGjlypL744gu5ubnZuzwAAAAAANIlS4XuQYMGJbvdp08fvfzyyzp58qTKlCljp6oAAAAAAMiYLBW67xYTEyNJypUrV6r3JyQkKCEhwXbbYrHI3d3d9m9kL7xm5qCv5qCv5qCv5qCv5qG35qCv5qCv5qCv5shJfc2yoTspKUmTJ09WqVKlVLhw4VTnmTdvnubMmWO7XbRoUY0ePVp+fn7/VZkZFx5p7wqynICAgIdfCH1Ngb6aI1P6KtHbu9BXc9BX87CNNQd9NQd9NQd9NUemfXZlAVk2dE+cOFGnT5/WRx99dM95QkJC1KZNG9tt668hkZGRSkxMNL1GZK7z58/bu4Qcib6ag76ag76ag76ah96ag76ag76ag76aIzv01cnJKU07fLNk6J44caJ27dql4cOHK1++fPecz9nZWc7OzqneZxiGWeXBJLxm5qCv5qCv5qCv5qCv5qG35qCv5qCv5qCv5shJfc1S1+k2DEMTJ07Utm3b9OGHHyp//vz2LgkAAAAAgAzLUqF74sSJ2rBhg/r27St3d3dFRUUpKipK8fHx9i4NAAAAAIB0y1KHl69YsUKSNGzYsGTTe/furUaNGv33BQEAAAAA8BCyVOieNWuWvUsAAAAAACDTZKnDywEAAAAAyEkI3QAAAAAAmITQDQAAAACASQjdAAAAAACYhNANAAAAAIBJCN0AAAAAAJiE0A0AAAAAgEkI3QAAAAAAmITQDQAAAACASQjdAAAAAACYhNANAAAAAIBJCN0AAAAAAJiE0A0AAAAAgEkI3QAAAAAAmITQDQAAAACASQjdAAAAAACYhNANAAAAAIBJCN0AAAAAAJiE0A0AAAAAgEkI3QAAAAAAmITQDQAAAACASQjdAAAAAACYhNANAAAAAIBJCN0AAAAAAJiE0A0AAAAAgEkI3QAAAAAAmITQDQAAAACASQjdAAAAAACYhNANAAAAAIBJCN0AAAAAAJiE0A0AAAAAgEkI3QAAAAAAmITQDQAAAACASQjdAAAAAACYhNANAAAAAIBJCN0AAAAAAJiE0A0AAAAAgEkI3QAAAAAAmITQDQAAAACASQjdAAAAAACYhNANAAAAAIBJCN0AAAAAAJjEyd4F3OnQoUP6448/FBoaqitXrqh///6qUaOGvcsCAAAAACBDstSe7ps3b6pIkSJ66aWX7F0KAAAAAAAPLUvt6a5cubIqV65s7zIAAAAAAMgUWSp0p1dCQoISEhJsty0Wi9zd3W3/RvbCa2YO+moO+moO+moO+moeemsO+moO+moO+mqOnNTXbB26582bpzlz5thuFy1aVKNHj5afn58dq0qj8Eh7V5DlBAQEPPxC6GsK9NUcmdJXid7ehb6ag76ah22sOeirOeirOeirOTLtsysLyNahOyQkRG3atLHdtv4aEhkZqcTERHuVhQw6f/68vUvIkeirOeirOeirOeireeitOeirOeirOeirObJDX52cnNK0wzdbh25nZ2c5Ozunep9hGP9xNXhYvGbmoK/moK/moK/moK/mobfmoK/moK/moK/myEl9zVKjlwMAAAAAkJNkqT3dcXFxCg8Pt92OiIjQqVOnlCtXLvn6+tqxMgAAAAAA0i9Lhe4TJ05o+PDhttu//PKLJKlhw4bq06ePvcoCAAAAACBDslToLlu2rGbNmmXvMgAAAAAAyBSc0w0AAAAAgEkI3QAAAAAAmITQDQAAAACASQjdAAAAAACYhNANAAAAAIBJCN0AAAAAAJiE0A0AAAAAgEkI3QAAAAAAmITQDQAAAACASQjdAAAAAACYhNANAAAAAIBJCN0AAAAAAJiE0A0AAAAAgEkI3QAAAAAAmITQDQAAAACASQjdAAAAAACYhNANAAAAAIBJCN0AAAAAAJiE0A0AAAAAgEkI3QAAAAAAmITQDQAAAACASQjdAAAAAACYhNANAAAAAIBJCN0AAAAAAJiE0A0AAAAAgEkI3QAAAAAAmITQDQAAAACASQjdAAAAAACYhNANAAAAAIBJCN0AAAAAAJiE0A0AAAAAgEkI3QAAAAAAmITQDQAAAACASQjdAAAAAACYhNANAAAAAIBJCN0AAAAAAJiE0A0AAAAAgEkI3QAAAAAAmITQDQAAAACASQjdAAAAAACYhNANAAAAAIBJCN0AAAAAAJjEyd4FpGbZsmVauHChoqKiFBwcrJ49e6pEiRL2LgsAAAAAgHTJcnu6N23apF9++UWdO3fW6NGjFRwcrFGjRunq1av2Lg0AAAAAgHTJcqF70aJFatq0qRo3bqxChQqpV69ecnFx0Zo1a+xdGgAAAAAA6ZKlDi9PTEzUyZMn1aFDB9s0BwcHlS9fXkePHk0xf0JCghISEmy3LRaL3N3d5eSUpZ5Wqiq7u9u7hCzH2dn5oZdBX1Oir+bIjL5K9PZu9NUc9NU8bGPNQV/NQV/NQV/NkVmfXWZKa+7MUun02rVrSkpKkre3d7Lp3t7eOnfuXIr5582bpzlz5thu161bV3379lXevHnNLvWh7fLzs3cJORJ9NQd9NQ+9NQd9NQd9NQd9NQd9NQd9NQd9zdmy3OHl6RESEqLJkyfb/uvVq1eyPd94sNjYWL3//vuKjY21dyk5Cn01B301B301B301B301B301B301B301B301T5ba0+3l5SUHBwdFRUUlmx4VFZVi77d0+5CD7HDYQVZmGIZCQ0NlGIa9S8lR6Ks56Ks56Ks56Ks56Ks56Ks56Ks56Ks56Kt5stSebicnJxUrVkwHDhywTUtKStKBAwdUsmRJO1YGAAAAAED6Zak93ZLUpk0bjR8/XsWKFVOJEiW0ZMkS3bx5U40aNbJ3aQAAAAAApEuWC9116tTRtWvXNGvWLEVFRalIkSIaOHBgqoeX4+E5Ozurc+fOHKafyeirOeirOeirOeirOeirOeirOeirOeirOeireSwGB+0DAAAAAGCKLHVONwAAAAAAOQmhGwAAAAAAkxC6AQAAAAAwCaEbAAAAAACTELoBAAAAADAJoRsAkGFcAAOAxLYgMyUlJdm7BACZjNANZDHWLy6JiYl2rgS4P8MwZLFYJEnR0dF8UUSWtmvXLi1btszeZeQ41s+sy5cv27mSnMEwDDk43P56fvz4ccXExNi5ouzLum4ahsGPQrA7QjeQxVgsFu3cuVNr1qxRXFycvcsBUhUZGak5c+ZIkrZs2aLPP/9cN27csHNVOQdfEDPX8ePHNW7cOHl6eurWrVv2LidHsVgs2rRpk3r37q3z58/bu5xs7c4fMqdOnaoff/xR0dHRdq4q+7JYLLp27ZoSExNlsVi0a9curV271t5l5XjWzy/rD/H8IH8boRvpEhYWZvv3ihUrdPr0aTtWk7NYN1KnTp3SF198IVdXV7m4uNi5quzvfht7PggyJikpSevXr9e2bds0duxYffXVV2rSpIly585t79JyhKSkJNsX7/j4+GT3EcbTLzw8XAcOHFDz5s1Vv359W2+ROa5du6YjR46oR48eCggIsHc52Zp13YyKitL58+f14osvKn/+/HauKvuKjY3VO++8o1mzZmnjxo0aPXq03Nzc7F1Wjmb94Wj//v2aPn26bt68aTty41HnZO8CkH2Ehobqu+++U506dRQVFaWlS5fq66+/tndZOYbFYtHJkycVERGh1q1bq0GDBnzBfkhJSUm2jf2aNWt06tQpJSUlqUiRImratCkfBBnk4OCgTp066fTp09q8ebMqV66shg0bSkrec2SMtX8LFy7Uvn37lDdvXlWqVEl16tSRxWJJtjcM92YYhq5du6Zhw4bpxo0batCggaTb/aWHmePkyZOaOHGiJKlZs2b0NRMsWbJES5culbe3N4H7Ibm7u+vNN9/U6NGjlZSUpFdeeUW1atWyd1k5msVi0ZYtW/TDDz+oQYMGOnv2rIoVKyZJj/z2gW9GSLN8+fKpQoUKWrJkidasWaPPPvtMBQoU4FC9TJCUlKT4+Hh99dVX+vLLLxUeHv7Ib5wygzW8TJs2Tb/++qscHR1lGIZmzJihn376yc7VZX9eXl6qXr26bty4oWnTpikxMVEODg4cQZBBd/7ItnDhQv3+++8KDg7W2bNntXjxYtvh/NbgjXuzbj/z5MmjXr16KVeuXDp58qROnjwpSWxbM0lERIQcHBwUFhYmBwcHWSwW3v/pFBYWpn379unQoUOSpHLlysnJyUknT57U1atX7Vxd9mXdRjo5OSkxMVGGYSgyMpLxckx24sQJff/99+ratau6d+9uC9zx8fGP/HaX0I0H2r9/v06ePCkvLy8FBgYqPj5evr6+2r17twzDkKOjIx+yGRAXF6fo6GjFx8fLwcFBLi4uGjx4sEqVKqWTJ0/q3Llz9i4xRzhw4IC2bt2q/v37q1u3bipTpozi4+NtHwRWhJgHs/bo6NGjCgsLU8+ePfX222+rTJkyOnz4sH777TfdunXL9mPHlStX6Gs6WL+QHD16VFevXtXbb7+t559/Xu+++67KlCmj7du3a/bs2bZ52e6mZF3fEhISJEm3bt1S1apV9fLLLysqKkrLly9PdloU6+fDqVWrlkJCQuTv769x48bp4sWL/PCWDhs2bNB3332nlStX6siRI5KkwoUL691335W3t7emTZuma9eu2bnK7MlisWjbtm1asWKF3n33XX3wwQdasGCBfv31V4K3iUJDQ1W8eHE1a9ZM0dHR2rJliz777DO9//77+vPPPx/pbQOhG/cVFRWl+fPna/z48Tp37pyqV6+uYcOGqUqVKtq2bZttzwuHk6bPmTNnNHr0aH300Ud6++23derUKUlS/vz59eabb8rJyUkTJkxgNNhMcOnSJeXJk0clS5bU1q1b9f3336tbt25q0qSJ4uLitH//fkns+XoQ657Dbdu26bPPPtOff/6pK1euyNHRUSEhISpXrpwOHz6sGTNmKD4+XjNnztS4ceNs4Qf3dueXkJ07d+q7777T1q1b5ePjI0ny9vZWq1atVLFiRe3YsYPt7j1Y19G9e/fq22+/1ahRozR27FhdvHjRFrz37dunxYsX68yZM5J436eH9QeKsLAwHTp0SFu2bFFiYqKqVKmi559/Xu7u7ho/fjzBO43Wrl2r77//Xm3atNFLL72kjh072u4LDAzUgAEDFB4ernHjxhG808G6nkZERGju3LmqWLGiqlSpokqVKumtt97SkiVLNHPmTFvwXrZsmdavX2/PkrO9O3+8zJ07t/bv369FixZp7NixWrt2rXLnzq2KFSvqxx9/VEREhB0rtS8+sXFf3t7eatOmjfz8/DR+/HhduXJFRYoUUevWrVWqVCnt3r1bc+fOtc0/c+ZM9tA+wKlTpzRo0CAVLlxYrVq1UnBwsMaMGWP7APDz89OgQYN0/fp1ffHFFwTvdEhtr1WuXLnk5+env/76S+PHj9fzzz+v5s2bS5KOHDmi7du30+M0sIaZcePG6bnnntOzzz6rvHnzSpLc3NwUEhKiKlWqaNeuXXrnnXf0559/6tlnn2UwwAe48xz4yMhIFS9eXMWLF9e1a9e0Y8cO23x58+ZVq1atVKlSJa1atUqrV6+2V8lZlsVi0fbt2zVmzBgFBgaqXr16unr1qj744ANFRkbagvfBgwc1Z84cnT171t4lZxvWHzS2bt2qUaNGaebMmfrxxx81atQobd68WZUqVVKrVq0kSd99953tsHOk7p9//tG8efPUs2dP1a1bV97e3pKSf4YVKlRIgwYN0pkzZ/Ttt98qKirKPsVmMxaLRUeOHNHatWsVEBCgmjVr2n5cq127tvr27atFixbpq6++0rfffqvp06erSJEi9i06m7Kur3FxcUpKStLNmzdVs2ZNdezYUStWrFBgYKA6deqk119/XV27dlWRIkUUGxtr56rth4HUcE/WL4OVK1eWq6urFi1apO+//16vvfaagoKC1KFDBy1YsEA7duzQqVOnFB8fr5MnT+qpp56yd+lZ1unTpzV48GB16NBBnTt3liT5+Pho4cKFunjxopKSkuTl5SU/Pz8NGTJEH3/8sUaMGKEPP/zQFnCQujvPgd+4caMqVKggLy8v+fj4aM+ePdq0aZN69OhhC9zx8fFasmSJvL296e093D2uwJYtW9SkSRM1btxYsbGxCg0N1bp16+Tt7a2aNWuqffv2KleunC5cuKBSpUrJ39/fjtVnfZs3b9bVq1fVsmVLTZkyRceOHdPIkSP11FNPycHBQVu3bpWnp6dtnfX29laLFi2UL18+NWrUyL7FZ0ExMTFatGiRnnrqKbVr106XLl3SrFmzVKNGDfn5+UmSqlatqps3b2ru3Lny8PCwc8XZh8Vi0bFjx/TDDz/oueeeU5MmTXTixAkNHDhQNWrUkCTVqFFDDg4Omj17tiZNmqT+/fvbzvNGcpGRkXJwcFC5cuWS/fBm7ZV122sN3v3799f8+fPVvXt3O1adfWzbtk2LFy9W3rx5FR0dney9XqtWLeXOnVtz586VxWLRiBEjVLhwYTtWmz1Z19Hdu3dr+fLlunHjhpycnPTCCy/omWeeUdu2bZP1fc6cObp586btCK5HEaEbKURHRytXrlxycHBQfHy8XFxcVKZMGf366686c+aMvvvuO73yyisqUqSIOnTooHz58unvv/+Wp6envvvuO9thZfzKnVx0dLTGjRsnPz8/W+CWbp8zf/DgQX366acKDw9XzZo11alTJxUuXFgDBgzQl19+ySG6D3Dn+nbq1Cn9/vvv+uuvv9SnTx8VLVpUr7/+usaOHasLFy5o+/btcnV11YIFC3Tt2jW9//77jAj9AEeOHFHp0qV148YNnTt3ThcvXtTMmTN16dIl3bhxQ9euXdPp06f15ptvqlSpUipVqpS9S84WwsPD9dtvv2nnzp06evSoPvroI0mSv7+/QkJCNG/ePK1bt04Wi0XNmjWTdPtHuieeeEISI8XfLSEhQZcuXVLdunV19epVDRo0SFWqVNErr7wi6fb5szVr1lSdOnVUpUoVLh2URtZtY2hoqB577DE1adJE586d01dffaXGjRvrySeflHT7R49q1arJwcFBQUFBcnR0tHPlWdfJkycVExNzz9HJLRaLzp07p0uXLql8+fIaN26c8uXL9x9XmX1169ZNHh4eWrRokdauXasWLVooT548km5vN8uWLavHHntMkjgaK4MsFot27Nihr776Sp06dVJQUJBWr16tAQMGaOzYsSpUqJAkad++fdq0aZO2b9+uIUOG2F6HRxGf1khm165d+u6773T8+HFJ/26MvvjiC8XGxqpnz57y8vLSDz/8oFOnTsnLy0stWrTQ//73P7311ltycnJKNpAS/uXi4qIKFSood+7c+uWXXyRJixcv1sqVK9W7d28NHjxYL7/8srZt26Y9e/ZIun2O98iRI7lsyH0YhmFb3/744w/98ccfunXrlvbs2aNvv/1W165dU40aNfTGG29oz549+uGHHzRz5ky5urrqk08+sQ0ESOBOyWKxaN++fRo6dKj27dun9u3bKyIiQu+8845u3rypJ554QqNHj9bTTz+t06dPKyYmxt4lZyshISEqXLiw9u/fryeffFLBwcG2w/UCAgIUEhKiwMBArV+/XosWLUrxeLazyeXJk0cBAQHasGGDBgwYoKpVq6pnz56Sbo9PsmXLFu3atUuS5Orqas9SswXrumh9X1+5csV2VNBHH32k8uXL237Q2LJli9atWydJqlKliu3IAqTO29tbcXFxOnHixD0H81u/fr3tu4Cfnx/nyd/Dnedwnzt3TseOHZMkde7cWc2bN9fatWu1YcMG23nx1h/ZXVxcCNwPIT4+XitXrlSnTp0UEhKiIkWK6PTp02ratKktcMfExOjMmTO2Szc+6ofxs6cbyXh4eOjYsWNatGiR7ZerL774QmfPntWgQYPk4+OjPHnyaNmyZfrpp5/Us2fPZKNAW0czR3JJSUlycXHR008/rfnz52v//v0aMmSIzpw5ow8++EClS5eWdPs6p+vWrdORI0fUrl07SaKfD2ANywsWLNDcuXP1v//9T23bttXOnTu1fft2jR8/Xn369FH9+vVVvnx5JSQkyNnZWXny5JHFYtGtW7fo8T1ERETo7Nmz6t69uypUqCBJGjt2rM6fP6/ixYvb5gsLC5OPjw8hMA3u3jv92GOPqWTJkpo3b57y5s2rFi1a2OazBu9p06bpzJkzHI3x/1m/ZN99KO6tW7cUGBiouXPnqkyZMurVq5ftMUuWLNGFCxdse7fo4/1Ze7pr1y7t2LFDr7zyih5//HGNGTNGf/31l5o0aaIXX3zR1sf9+/crNjZWjRs35giCVNz9vq9QoYKmT5+u5cuX66WXXrL9CGTtuzWsWLe7Vmxjk7tzgM/Zs2crPj5eklSwYEH169dPzz33nAzD0NKlS2WxWFSvXr1Hek9rZkpISNDZs2f17LPPKjo6WoMHD052ZNHatWtVrVo1NW/eXI0bN5a7u7udK7Y/QjdskpKSVLp0afXv31/jxo3T/PnzFRUVpatXr2rgwIG28zAqVaokBwcHzZw5UytWrNBrr71mWwZfZFJn/aB0cXGxhel169apbNmytsCdmJgoi8Uid3d3FSxYkENH7+PkyZMqVqyYDMOQYRiKj4/XwYMH1bZtW1WqVEmSFBwcLF9fX82bN0//93//p969e9sGq7FKSkoicN/DuXPnNGbMGN24cUMvvviipNvrqIeHhy1wnzhxQlu2bNGaNWs0fPhwvmw/wJ1HZaxZs0alS5e2fUHJly+ffv75Z0lSixYtbPM5OTnpjTfekKur6yN/GkRkZKT8/Pxs79s9e/Zo27ZtunbtmqpVq6Zq1aqpS5cutj0r06dPV0BAgI4ePaotW7Zo2LBhHKJ7Hxs3bpSbm5uqVatmW8cOHz5s2xtYokQJNW/eXOvXr1epUqVksVh09epVLVmyRFu2bGEbcB/W9/OBAwfk5+enAgUK6Nlnn9WUKVPk5OSkjh07ytfXVxaLRVFRUfruu+8UGxtrO60EqbNYLNq/f7/GjRunF198UTVq1NCRI0c0duxYbd26VfXr19fzzz8vi8WiWbNmycnJSc2bN+e7VSbw9PRUiRIltGnTJm3YsEFVq1ZVjx49JN0+nXLHjh2yWCxq2LChnJ2d7Vxt1kDohu1LnIODgxITE1WyZEn16dNH48ePV1RUlPr27Wv7omLdK1ihQgV5eHikuNYxkrP29vLly3JwcNDNmzfl7++vDh06yGKxaM+ePfrll1/07LPPytnZWbNmzVJoaKi6d+/Oh8I9rFixQhMnTtT777+vKlWqyGKx2L7o3TlyvoODgxo1aqQDBw5ow4YNmjBhgnr37q1cuXIlW+eROsMwVKZMGW3YsEFhYWGqU6eOnJycbD8GnTlzRqtWrdKxY8c0fPhwBQcH27vkLO3OH9GuXbum//u//1PlypX17LPPKjg4WB07dpTFYtHkyZOVkJCg6tWra8qUKUpKStIHH3yQYhmPml27dmn06NEaPHiwypcvrx07dujLL79U5cqVZRiGJk2apF27dunpp5/W22+/rTlz5ujgwYPat2+f/P399dFHHzFY0n1cvHhRf/75pwzDkLOzsypWrGibnjt3bkm3j4SrX7++YmNj9c0332jWrFlyc3PT9evXNXjwYNshpfjXne/ZAwcO6Mcff1TVqlUVEhKiZs2aKS4uTrNnz9bBgwdVuHBhJSUlKSoqSrdu3dLIkSMZIycNDh8+rGbNmqlZs2aKiIjQL7/8ombNmql+/fq2z/rnnntOTk5OqlixIr3MAGsfrVfZcXJykmEYKlCggJYtW6bixYurZ8+etp0Yf/zxh+0oOfzLYtzrZBI8Eu7ca7J27VpJty+p4OrqquPHj+vrr79WiRIl1KZNG9verbsPx+UDIXXW3m7fvl1z5szRrVu3dO3aNTVr1kzt27eXxWLR/PnztXfvXpUvX15JSUlavHixRowYwY8Z93Hu3DktWrRImzdv1htvvKGqVasqKSlJs2bN0r59+9S9e3eVKFHCtk4uWbJEBw4cUEJCgoKDg9W1a1fW11Sktgc1IiJCCxcu1JYtW9S5c2fboc/S7fO5IiIi5Onpyejv6TB9+nTFx8frwIEDOn/+vEqWLKmePXvaAuGiRYs0depUFSpUSBaLRZ9++qmcnPh9/Nq1a5o2bZq2bNmi9957TydPnpSzs7NtEK+DBw9qxowZ8vX11euvvy4XFxcZhmEbY4QePtiBAwe0bNkyxcTEqF27dqpUqZImTJggX19fPf3007bP/hs3bujUqVP6559/5Ovrq2LFisnX19fe5Wc5d25TlyxZosuXL2vt2rVKSEhQ8+bN1a5dO3l5eeno0aNasmSJrl69Kh8fHxUtWlStWrWSg4MDpz+lwSeffKLChQsrJCRE77zzjipXrqxevXrJYrHozz//lKOjoxo3bmzvMrMt63q8c+dOrVy5UoZhqGbNmmrSpIkSExM1btw4nTlzRo899pgCAgJ0+vRp7dixg3O4U0HofoTdGZYvXryo4cOHK1euXGrXrp2qVq0qFxcXHTlyROPHj1fx4sXVrl07wmA67d27V2PGjNHzzz+vatWqaevWrZoyZYptL+3Nmzf1xx9/aNWqVbp+/TqBO40uXbqkxYsXa/Xq1XrnnXdUvnx5Xb9+XUOHDlXu3LnVqVMnlSxZUhaLRePGjVOZMmUUERGhAwcO6KOPPuJSQXexfqgeOXJEoaGhOnv2rBo1aqSgoCDFxcVp3rx52rNnj1q1amUbORvpt2TJEs2ePVsDBw6Um5ubYmNjNXbsWPn7++vll19WUFCQLBaLTpw4oZiYGJUtW5Yv3neIjo7WtGnTtH79evn5+alTp05q0KCBbf21XgXi9ddfV506dexdbrZxZzg8dOiQFi1apNjYWHXq1En79u1TgQIF1KhRo2RjtljHxkDq7uzp3Llz9ccff6hPnz7y9PTUpk2bdODAAVWvXl2tWrWSj4+PbTDPO3/4ZIdG2qxevVrbt2/X8ePHVb16db3yyiu2H9x+/vlnubu7q0uXLqyvD+HIkSMaPXq0atasqfj4eP31119q3bq1unXrpsTERM2fP1/Hjh1TdHS0ChYsqLZt2yooKMjeZWc5/PT7CLNuzH/55RdFRETI29tb58+f17Rp02QYhqpVq6bSpUurT58++u677zRjxgz16NFDBQsWtHPl2cf27dvVvHlztWjRQhEREVq+fLmaNGmiKlWqyDAMubq6qm3btnJxcVGNGjUUEBBg75KzrLsP03N0dFRsbKzGjBmjvn37qkqVKho6dKg+/fRTTZ06VbGxsXJ3d1d8fLz69++vnTt3avfu3Vx+LRUWi0Vbt27V//3f/6lChQq2MFijRg1169bNtod7+fLlSkhIUOvWre1ccfb0zz//qEqVKrbBvCRp1KhRGjhwoH755Rc9//zzCg4OTjZIHeMO/CtXrlzq2rWrPDw8tHjxYkVFRUn69+irsmXLqmTJktq3bx+hOx0sFott+1qmTBklJSVpyZIlmjt3ro4fPy4XFxctXbrUNu6IYRjy9vZW//795eHh8ciOMZAa63gj1p7GxcVp586dCgkJsV3PvGzZspo5c6b+/PNPSbIF77sRuP9lPWLFYrHYRiH38vKSJBUpUkRLlixRrly51KRJE0nSzZs3NX/+fO3cuVNDhw4lcGfAnT8cxcXFqX379urQoYMkqXr16vrmm2+UlJSk7t272y6Dm5iYKAcHB9bdeyB0P+LWrl2rNWvWaOjQofLx8ZGLi4s+/fRTzZ49WxaLRVWrVlXp0qXVq1cvrVixglCYDrdu3VJoaKiaNm2q+Ph4ffjhh6pSpYptRN2lS5eqePHiKlWqlNq3b2/narM+60Z82rRp2rhxozp06KCQkBAdPnxY33zzjfr06aPq1atryJAhOnjwoM6ePSsPDw81bdpUkrRjxw75+vpyqaBUnDlzRr/88ou6deumxo0bKz4+Xi+88II8PT3l6OiogIAAtWrVSnFxcdq4caMaNWokT09Pe5edbVj3Yl2/fl23bt2yTU9ISJCvr686duyoSZMm6bffftPLL78sX19fWwh61L+83H3ag5eXl9q1a6e4uDj99ttvCgoKUuXKlW33JyYmKleuXPYoNVuy9jc+Pl7Ozs5ydHRUuXLldOvWLS1fvlz+/v4KDg5WixYtdPXqVd24cUMuLi4qUqQI24C7zJ8/Xxs2bNBzzz2nKlWq2E5rcHR01M2bNyX9+wPRM888o9DQUK1fv14ODg5q1apVioE+cXsvdq1atWxHp23btk3Tp0+3XTqtXbt2atSokXr27Knvv/9eP/74o1xcXOTh4aGTJ09q4MCBCgwMtOdTyJas24UTJ07o4sWL2rp1a7JxW2rXri1J+uabb+Tk5KQuXbrIycmJ03gegO48Qv788089/vjjyfZUR0ZGqnDhwipUqJDtC96HH36oIUOGaMaMGTIMQ1WrVlW5cuVUtmzZZL+I4/4cHR1VuXJlbd68Wb/99ptq1KihHj162AajOHr0qK5du2Y7/5i9BQ928eJF7dq1S927d1etWrUk3b5c1aJFizR+/Hj169dPlSpVUvXq1VW9enVJt0fY3rBhg7Zu3aqhQ4cyum4qYmNjlSdPHjVu3Fhnz57VqFGj1LhxYz399NOSbp9HHxgYqJCQELm6uvJl+wHu3kZa/92sWTN9+eWXWrVqlZo2bWrb++Lp6akmTZpox44d+u233/TGG2+wjdW/X/yOHj2qs2fPytnZWfXq1ZO3t7eef/55JSUl6fPPP1fHjh3l5eWliIgInTp1KtmlwnB/1nM158+fLzc3NwUGBqpHjx6qWLGiLBaLVqxYocuXLyspKcm2TUXqihQpouPHj2vRokWSbl+v3MXFRX5+ftq6davatm0rDw8P2/YhMDBQ169f1969e1WwYEE1bNjwkb46wd2uXbummTNnavHixfrkk0906dIljRs3Th07dlRQUJD27t2rP/74QxcuXFDXrl319ttvKzQ0VEePHlWxYsXUo0cPFShQwN5PI1uyWCzasWOHPv/8cwUHB+uff/7R9evXVbduXdv4DbVr15bFYtGXX35puyQu7o9P9UfE7t27NWfOHC1fvlzh4eG26QkJCYqOjpaTk5NtdG0HBwc999xzunjxopYuXapDhw5J+vfaqHwZTMnam+vXr+vy5cu26SVKlNCVK1fk7e2tDh06yNHRUbdu3dLs2bN17NgxNWrUSI6OjnzIpmLEiBGaM2dOsmm3bt3ShQsXkk0rXLiwWrZsKU9PT3399dfavn17svvDwsJ09OhRDR06lBG27yEqKkoJCQm6du2aPv74Y1WsWNF2KauDBw/aBgHy9/dnb8wD3HlZsB07dmjZsmU6fvy4bty4oQoVKqh58+aaN2+eVqxYocTEREVFRWnjxo0qXry4XnvtNW3dulWnTp2y75PIIqyBcOjQoVqxYoXGjRunzz//XOHh4fLw8LAdmTF79mytXLlSfn5+GjFiBKNop8OxY8f0xRdfqFSpUvL19dWePXv04YcfSrp9LeknnnhCnp6emjRpkvbv32/narOmZcuWSbp9OdUnn3xS7u7uWrhwoXbs2CFJevnll5WYmKjRo0fbtrWGYejixYt66qmnFBAQoD/++IPAfRcvLy8NGjRIjo6OGjJkiM6dO6eWLVsqJCRE1apV00svvaQWLVpo8+bNWr9+vYoUKaLGjRvr1VdfVfPmzQncGWD9Lnv58mWtWbNGr776qgYOHKh3331XBw4c0O+//64rV67Y5q9Vq5b69+/P6TxpxJ7uR0TlypUVEhKi1atXyzAMPfnkkwoMDFSTJk20dOlS26Gl1kNvb926pQYNGujs2bOaNWuWKleuTNi+D+s5sbNmzVJcXJyKFi2qrl27qlKlSrpw4YJWrVql0aNHq2DBgoqLi9OxY8c0ePBgPhTuwTAMhYSEqFSpUsmm+/j4qHz58jpw4IDKlCljO6erWLFiCg4O1unTp7VixQpVr17d9gWmcePGqlmzJoOn/X+pfbGrXLmyZs6cqV69eqlp06a2wC3d/sHOupcR93dnb6dOnaq1a9fKzc1NSUlJql27ttq1a6eQkBC5uLhoypQpmj9/vgzDsO3pPnz4sLy9vW2XaHqUWb/8bdmyRS+99JIaNGigiIgIDR8+XN9//7169eqlwMBAPfvss7p165Z27typRo0acfpIOoSFhenGjRt65pln1K5dO9sRWOPHj9eQIUM0YsQIVahQQYmJidqwYQOfV6nYtWuXfv/9d506dUqvvfaaypYtK+n2oImLFy+WJFWrVk3vvfeexo4dq0GDBilv3ry6efOm4uLiVKlSJV2+fFlnz55VQkKC7Zroj7J58+bJ2dlZbdq0UeHChfXmm29q3Lhx+uyzz1S1alUZhmH7cbNNmzY6c+aMFixYoEaNGtm79GzPYrHo0KFDWrt2rRITE1WxYkV5e3urWrVq+uCDD/TJJ59Ikp566inbVUs4AibtSFGPAOt19Vq0aKG6devqxIkTWrp0qcLDw1WgQAH17NlTK1eu1I8//qhz587ZLsmUL18+9evXTydPntSuXbvs/CyytpMnT2rixImqVauWnn76af3zzz8aN26cjh07phYtWuiFF16wBcGSJUtqxIgRKlq0qL3LzrIsFovKlSsnZ2dnzZ8/X1999ZUkydnZWaVLl9bhw4e1fv16RUdHS5JiYmJksVj0wgsvaODAgbZlWL+4E7hvu/Nw3cWLF2vXrl2KioqSk5OTOnfurIIFC+r69eu6du2ajh07punTp2vlypXq0aMHQfAB7gzcx48fV1hYmAYMGKCvv/5arVq10pEjRzRz5kwlJiaqS5cu+uyzz/TUU0+pR48eGj16tBwcHLRr1y55eXk90l+8re/Zq1ev6tq1a/Lx8VGJEiXk4uKiQoUK6dNPP9WZM2f0448/6vz588qVK5e6deumzz77jMCdDlFRURo9erRGjx6d7Nq71sFTL1++rKFDh0q6fZj0a6+9Jj8/P3uWnCWVLl1aHTt2VGhoqCZMmCDp9kBprVq1koeHhxYtWqRdu3apUKFC+vLLL9WiRQtVqFBBtWrVsn2uHTlyJNWB1B5VcXFxmjp1qm2guaCgIL3xxhsqU6aMQkNDdenSJdv1yyXp8ccfl5OTk+Li4uxZdo5x8+ZNbdu2TYcOHdLZs2dt0ytWrKiBAwdq3bp1+uWXX2wDWSLtuGRYDnfnF8FFixbp4sWL2rRpk65fv66mTZuqQ4cO8vX11ZYtWzRp0iTb/N7e3ho5cqSuXLmiESNG6H//+x8h8R7CwsIUGhqqCxcu2M5piY2N1dChQ+Xg4KCePXvqscce47CxDEhKStKWLVs0fvx4NWjQQK+++qokacqUKdq3b5+8vLxUuHBhHT9+XElJSRo1apTtw5gjM1K3a9cujR07VoULF9apU6dUt25dtWzZUsWKFdPGjRtth4/5+PjIzc1Nr776KtfaTIeNGzdqx44dcnJyUp8+fWzv+6VLl2rDhg0qUqSI2rVrl2yv4blz57RkyRJt3LiRa5vq9t7tX3/9VYmJibp8+bJeffXVZHuxLl26pMGDB8vLy0tvv/02e2AzIC4uTlu3btXvv/8uPz8/DR482HZfUlKS/v77b3366acqWbKkBg0axKHPqbD2JDY2VmvXrtXq1atVtGhR9e7dW9K/p+bExMToySeftI1ebhUZGamFCxfa3veFCxe2x9PIMqKiomynL82fP1+//vqrXnrpJdtlKsPCwjRu3DglJSXp/fffl4+Pj5ycnPTTTz/p+PHjGjZsGGO2PIQ7L1tnHaC2VKlSCgkJSXZq3q5duzR+/HiNGTPGtrcbaUPozsHu/JCcP3++5s2bp759+8rT01O7du3Spk2bVLFiRbVv315+fn6KiYlRaGionJ2dbYN7zZgxQzt37tTgwYN5c93FMAwlJibqtddeU3R0tBo2bGj7sJVu730dNmyYXF1d9dRTT6lcuXIEwQc4d+6cYmJi5OrqqoIFC8rBwUGJiYnavXu3xo0bp1q1atl6vHHjRh0/flxnz56Vn5+fevbsKScnJwL3PVgPyfvhhx9UokQJNWvWzDbWQ968edWhQweVKFFCSUlJOnTokHx9feXh4WE7hB9p8/PPP2vjxo3KmzevRowYkewoi2XLlumvv/5S3rx51aNHD+XNm1eJiYnatm2bdu3apXbt2j3yX7zPnDmjzz//XPXq1ZO/v79mz54tHx8fPf3007ZDd6XbgyqOGDFCgwcPZg9sGtz5fSAxMVFOTk62de/nn39WuXLl1K9fP9v8SUlJOnbsmPLkycOPGvdh/byJiYnRunXrUg3eS5cuVWxsrJo2bWo79/XatWvatm2bVq1axQ+bkmbNmqVjx47pvffes53K9Pvvv2vmzJnJgvfp06f1zTff6Nq1aypUqJAKFSqk9evXa+jQoY98D9MrLCxMixcvVsOGDRUQEKC8efMm207s3btX33//vcqWLau2bdsm+2y6efMmRxZlAKE7B9q7d68qVqxoux0fH69PPvlEpUqVUpcuXWzTFy1apHnz5ql27dpq1apVsssqnD59WosWLdK2bdvYmD3ApUuX9NFHH8nBwUFvv/22goKCbButmJgYvfvuuypQoIDef//9R/qw0QdZu3at/vjjD129elW5cuVSzZo11aVLF9ue6x07dujbb79NFrylf79ASv9ejgX/sn6IXrlyRW5ubpo5c6bq169vuxb0vn37NHPmTOXNm1dPPvlksmCD+7vXDzxz5szRunXrVLt2bbVp0ybZDxfz589XRESEXn75ZdtjExMTlZiY+MjtpYmNjZW7u7vtdlhYmDZt2qSbN2/qxRdflCRFRETo888/tw1Geef6yQ9saWPdBuzdu1c7d+5UaGio6tatq5IlS6pYsWLatGmTpk6dqlKlSiUL3kjd3evdncF7/fr1+vPPP1WsWDHb59ShQ4c0c+ZMBQcHq2fPnrbHxcTEKCkpiUvc6fbpJFevXlXhwoUVFxdn2xamFrzDwsI0depU7du3T8OGDZO/vz+H56dTUlKSRowYoUOHDqlNmzbas2ePOnXqpGLFiiX7kW3Xrl366aefVKFCBbVo0cJ2xCtHvmQMoTuHmTVrliIjI9W7d2/bG+LWrVv67LPPFBAQoO7duycLJuPGjdPevXtVoUIFde3aVb6+vjIMQ0ePHtXOnTtVv359BQUF2fMpZSnWDY31Q9b6/4sXL+qDDz6wfajeeVm2mJgYXb9+Xf7+/nasPGtbuXKlJk+erJdeeklBQUGaP3++Dh8+rP/9738qV66cJNmC9/jx41W3bt1kg31JfAjcz5YtWzR9+nTFxcUpMTFRPXv2VP369W3379u3T3PnzpWzs7OeeuqpFAPYIaU7v3j//fffcnNzk6urq+0Ly/Tp07Vv3z5VrlxZrVq1Sha8796OPIoWL16ss2fP6qWXXrJdJ3rMmDH6+++/Vbp0aQ0aNMg274ULFzRmzBj5+PioVatWth+Vec+n3bZt2zRu3Dg1b95cbm5u2r17tyTpnXfekZeXl3bs2KEZM2aoYMGCGjBggJ2rzbrufM/++eefCgsL0/Xr11WrVi3VqFFDiYmJWrVqlVatWqVixYrp9ddflySFhoYqODhYDg4OrLf/n7WXd34nPXjwoH777Tf16tXLtmc1teAdGhqqSZMm6Y033lD+/Pnt9hyysx07dmjevHnq2rWrTp8+rVWrVsnb21uFCxdW69at5eXlJScnJ+3Zs0djx45Vw4YN1b17d67F/RDoXA5jPSTPYrEoLCxMhQsXlqOjowICArR582a1a9dOPj4+to1+vnz55OPjIw8PD9svhRaLRaVKlVLx4sV5c93hzr0F27dvV2RkpMqXL6/HH39cxYsX1yeffKIBAwZo4sSJevnll21HDnh4eDCQ131s2rRJP/30k/r3728bBbNly5basWOHwsPDbaHbwcFBVapUUZ8+fTR27Fjlz59fHTp0sC2HLzHJWdfXixcvasqUKWrdurUcHBy0efNmLV26VB4eHqpataok2UYoXrp0qe0anLg/6xfvadOmad26dUpKSlLRokXVoEEDNWjQQM8995wMw9CePXvk4OCgFi1aKE+ePJL+HeTvUQzc1i/aDg4O6ty5sxwdHZWQkCA3Nzf16NFD06dP1+nTp7V+/Xo1aNBAkuTv76/+/ftr2LBhWrlypUqXLi1XV1fe82l0+fJlzZs3Ty+88IKeeOIJxcfHa8mSJWrWrJnt/V6zZk0lJCTojz/+0OXLl9lzeA/W9+zUqVO1bt06lS1bVvHx8friiy/UsmVLdezYUU2aNJEkrVmzRmPGjFH//v1tewgf5R/a7mTtw6VLl3To0CHFx8erevXqKliwoMLCwjRp0iT17NlTQUFB6tixoyRp4sSJcnBwULNmzVS0aFF9+OGHfEdNpzsPCy9UqJDy5s2rhIQEtWzZUpUrV9aVK1c0dOhQHT9+XHnz5lWXLl1UqVIlDR06VJ6envT7IfHOz0GSkpIUGBgoR0dHbdu2TV999ZXWrl0rSerevbt8fHw0atQonTt3TrGxsUpKStK5c+fUrl07vfTSS8lGg5TEm+suFotF27Zt02effWa7vX37dn3zzTfav3+//Pz89Omnn+rcuXP65ptvdP78eTtXnPUlJCRo48aNKlCggBISEmzTly9fLun2+Z2zZs3Sxo0bFRcXJycnJ9WoUUNDhw5V27Zt7VV2tmAdpXzFihWqWbOm2rRpo1atWun555+Xj4+PFi1apJ07d9rmr1Klivr37698+fLZseqs786Dw0JDQ7V371598MEHevXVV5U/f37NmzfPNuru888/rwoVKmjNmjUprh//KAZG6xftCxcuKCYmRj4+Pjp69Ki+//57Xbx4UQULFtTzzz+vgIAArVu3Tps2bbI91t/fX8OHD9cLL7zAuYTp5ODgoISEBNWoUUPh4eF66623VLt2bT3//POSbu9djIuLU506dTRy5EgC9wMcOnRIGzdu1AcffKC3335b77//vvr27asNGzZo8eLFcnFxUYMGDVSrVi25u7sn+15F4P53O3D69Gl9+umn2rNnj+1KBN7e3ho3bpwiIiL0ww8/6PTp05Kkjh07qkuXLvrxxx+1Zs0aSXxHTa+IiAh99913thHJCxQoIF9fX02aNEnS7W3s6tWrlTdvXlWuXFmxsbHq27evfvzxRxUrVkwBAQH2LD9HYI3NQawb8+PHj8vPz0+FChXS2rVr5eDgoAYNGqh///766quv9OGHHypv3rxKSkpSYmKi3n777Uf+UMe0uHbtmhYsWGC7pqkknThxQsuXL9fPP/+st956S0WLFtXIkSM1YsQIPhDSwNnZWS+99JImT56slStXSpI2b96s8+fPq0ePHgoMDNTixYu1b98+TZkyRQULFtRzzz2nMmXKSOIc7vuJjY3V6tWrtXnzZpUuXdo2vVSpUjIMQwsXLtSSJUuUmJiomjVrShJh5gHu3kYmJiaqePHitv+sP3ouWrRIFotFTZs2tZ22Y9379aiy9u7UqVN6//339cwzz0i6/Xn1zz//aPbs2XrmmWcUGBioF198UVOmTNGqVatksVhUu3ZtSeIw0nSwHuliGIZu3LihW7du6cyZM/r+++9VqVIl9erVS9Lt8VvWrFnz/9q796goq/WB498ZRu4QOINyE28IyCpND1KgZqYipse8IhpJaMfqmLZKjZ8X1DTKa6knrZSTegI9mnnUvOEdTDMshbRMIzVQwAERFBEGhvn94Zr3OIHXVOD4fNZqVe/smdm865333c/ez96bsLAw/Pz8lEWsxH+dPXuW/Px8nJycCAgIwGAwYG1tjVarVVZ8Dg0NpaKigk8//ZTQ0FCaNWtG7969adCggbSvbmDO8MnOzmbq1Kn07NmTvn37KtmA3333HVqtlrlz5zJhwgSWLl3KqFGjaNKkCf3790ej0dCqVata/ivqp0uXLintAfMUyAEDBnDu3DnS09PZv38/x44dY+rUqXh7e9OvXz/27NlDYGCgXLv3iUQF/wNuvJknJiaybds2EhISGDBgABs3bmTnzp2o1Wo6derEzJkz2bNnD9euXcNoNNK7d2+srKzkgXATN56X8vJy8vPzLUYBWrZsSVhYGDk5OZw5c4bmzZuj0+n46KOP5HzegaqqKrRaLTExMSQkJLBy5UoA4uPjlbRH8w1/69atFBYW0qJFC+X9EnBXZ25s29nZ0b17dwD279/PwYMHlZVzAwICUKlUrFmzhn379tG2bdtHbhGve2H+Ta9fv54TJ05gZWVlEaR4e3sTHh6OSqViy5YtlJWV0bt3b2Ue4qN6nzX/3efOnWPKlCkMHDhQSRl9/vnnUavVHDhwgNWrVzN06FC8vLyIjo7miy++YNOmTVhZWVXbbklUZ87CMAfb5u1/vLy8aNasGTNnzqRz58689tprynv2799Pdna2TCu5if379/P111+j0+nw9vYmICBAWcflypUrSnpugwYNCAoKomHDhuTl5dGsWTNl4dRHdSpJTVQqFSUlJSQkJNC5c2eLxX3N24QFBAQwfPhwJfBOSEhgxIgRNG3aVDLc7pHJZMLf35+IiAiSkpJo1aoVLVu2xNbWFmdnZ+bNm4dWq2XSpEl4e3sr949HvbP4fpO7wP+QgoIC1Go1EydOxM7OjmbNmvHCCy+g0+lITk4mJSUFgOeee47evXvTt29fCbhvory8HKPRiFqt5sSJExgMBlxdXfHy8iInJ8ciFdrX1xcrKyt++ukn5dijmDp6p2pKtWvYsCEjR47Ez88PnU7HiRMnLMqo1Wr69OnD8OHDlWtWWDI3uCsrK5Xz4+vrS58+fejYsSNffvklhw4dUsr7+/szdOhQXnnlFQm4b+PG623Tpk1s2bKFxo0bU1FRQVpaGjt27FBe9/LyIjw8nObNm5OZmals1QaPZmqp+fmSlZXFtGnTcHNzIyIiAri+swZcX8MhNDSUvLw8Vq9eTWFhIV5eXgwbNgw3NzeLjjZh6Y9r4apUKo4fP87SpUtZsGAB//znPwEYOnQoTz75pLImyb59+1ixYgXJycm8/vrrklJeg5SUFD777DNeeOEFRo8ezbBhwwB4/PHHadeuHf/4xz+4cOGC0vFm3knjj7uUSHvAUlFREYWFhQQHByv31h07drBmzRpGjBhBgwYNWL16NTk5OcydO5fTp0+zatUqKisra7nm9U95eTnw32vw6aefxs/Pj+3bt3P58mWsra0ZNGgQTk5OdOvWTdmpSK7ZB0NWL6/HfvzxR5544glUKhX79+/n448/xt3dnQkTJuDl5aX8aM6ePcumTZu4ePEinTt3Vka/RM0KCgqYO3cuY8eO5ffff2fhwoXExcXx+OOPs3LlSg4fPkxMTAxt27ZVUsg//PBDPD09GTJkiNysbuHGDp4ff/yRwsJCXFxc8PDwoHHjxhQUFPD5559z9epVunbtyrPPPlvtfaI6c6/00aNHSU5O5tq1azg6OjJ48GCaNWtGTk4OGzdu5NSpU0RGRirp5OLunDlzhpMnT+Lh4UHbtm25ePEiycnJJCcnExUVRY8ePZSy+fn5aLXaR3q14htTyuPi4vD19SUnJ4enn36amJgYwHLLv23btnHw4EE8PT0ZPHgwOp3O4nVhyXxdXb58GUdHR9RqNd999x2LFy+ma9euaLVatmzZgk6nIzY2litXrvCf//yHEydOYG9vj1arZejQoTRt2rS2/5Q6Jzs7mwULFvD888/TrVs35bj5nP/8889s3LiR8+fPExkZiUqlIjU1laKiIj744AN5Xt1CamoqS5YsYfXq1cp98eLFi+j1elq3bk1WVhYrV66kpKSEuLg4jEYjpaWlMqf4Lun1eqZOnUqfPn3w9/dX0vI3bdrE5s2beeONN2jTpg3Xrl3jX//6F0ajkVGjRmFlZfVIPq8eBnmS1VMlJSV89tlnNGjQgAULFtCqVSuCgoJIT0+ntLQUlUqlNFbMI96JiYmcOXOmtqte55nT7N577z0KCwt57bXXlBW0o6Ojyc/PZ/ny5QQHB+Ph4UF2djYZGRlERETIjeo2bpwGceDAATQaDVZWVpSXlzNmzBgCAwOJiYlhxYoVpKSkYDAYCAsLkwbMLZgbgT/88APz58+nZ8+e2NnZkZGRwZw5c4iKiiI0NFSZSpKQkIBarVZWihc1S0pKokePHso84lOnThEXF4eNjY2yl7FWqyU8PBy1Wk1iYiIqlUrp1HRzcwMe7Q4jtVrNb7/9xpQpUxgwYAADBw5kz549rF69GoCYmBg0Go3yrOrVqxcqlYqdO3eyYcMGRowYIVNIbkGlUnH16lXeeustoqOjeeaZZ/jqq6+IiIigT58+FBYWsnXrVpo2bYqzszPOzs688cYb6PV6HnvsMUwmk2S53ERhYSHl5eW0bt3aotPM/O/AwEAcHBzYuXMnn3/+OTqdTlms9sbtREV1jRo1Uhb8feqppzCZTGi1WmWOvI+PDyEhIezevZuysjJ0Op2y84O4c5mZmVy6dImMjAyysrI4evQoERER9O3bl19++YXly5fz0UcfYWdnR5s2bViwYAHh4eGSWfQAyR2hnnJwcGDs2LFYWVkxceJE3N3diYmJwc/Pjzlz5pCTk4NGo8FoNALQtGlTRo4cyciRI2u55nWXXq9n+/btFBUVMWTIEAoLC3F2dqZ58+YW6aXjx48nNDSU8+fPs3nzZnJycnj33Xfx9vauxdrXfeZrMTU1lb179/LWW28xZ84cxo4dy+OPP87777/PyZMncXNzIyYmhqqqKrKzs6ulT4rrzNekSqXi2rVrbN68mb59+xIdHU1ERATx8fH4+/uTmJjIuXPn8PHx4bnnniMkJIQmTZrUcu3rtitXrrB7924WLlzIxYsXgev30OjoaEwmE6dPn1bKNmzYkJ49e/L888+zbNmyaquUP+oN7/LycsLCwhg8eDBqtZrQ0FCGDh3KN998o6yaaw684Xqqea9evejbty9qtVo6Mm/DxsaGgIAAvv/+e86ePauc78LCQiZNmkT79u0ZNWoUcH1fXrge9NjY2EjAfQunT5/m2rVreHp6KnPkzcz3XisrK3r27Mknn3zC9OnTiY2NVdpdj/rv/lbc3Nywt7cnJSWF/Px8i9+4+bzl5OTg5uaGg4NDbVWz3gsNDSU0NJSLFy8SGhrKoUOHmDVrFr/++isvvPACtra2yjo6ISEhPPXUU3JPeMAkvbweq6qqIjMzk8WLF2Nvb88HH3xAQUEBn3zyCbm5uUyZMgVPT89q6XnSA1tdVlYW8+fPp0mTJvTo0QNHR0cuXrzI119/TVFREaNHj8bPz09ZmMasuLhYGi+3ceM0CKPRyJdffklOTg5vv/22UqaoqIjly5dz+fJlxo0bh6Ojo0XK5KOannszer2eH3/8kebNm9OyZUsMBgNTpkyhW7du9OzZU1nYByA2NhYvLy/Gjh0LYPGauLmLFy/y3nvvYWdnx7hx49BqtZSXl5OcnExSUhIvv/wyvXr1sih/9OhRunbtKqOzN2H+HZeWlnLw4EFWr15Np06dlFRzuTbvzfbt21m3bh1Tp07liy++IDg4mA0bNtC2bVtGjBiBRqNBr9ezfPlyevfurWRuiZv79ttvWbx4MRMmTKBt27Y1lklMTOTq1av87W9/U9pU0r66M4cOHWLRokWEhobSr18/ZdCitLSU9evXs3v3bmbMmCEdxHepoqICKysr5RrU6/UsW7aMLl26EBwczGeffUZVVZWyuF9ZWRmDBg2iRYsWyqr84sGRO0M9kpmZydGjRwGUntSWLVsyZswYSkpKmDhxIjqdjtdffx0vLy/i4+PJzs6uNh9OHgiWzp8/z7Rp03jqqacYMWIEbdu2pWXLlgQHBzNz5kxl30jzokgABw4cwGAw8Nhjj0nAfQvmaRBvv/02JpNJWQTt7NmzyiJKAC4uLjz55JNcuHBBGfFydnZW0vQk4P6vrKws4uPjSU9Pp7i4GABra2tsbGzIyMgArm/FZl7sz9/fX1lMxfyauLmKigrKysrQarVMmTKF0tJS5s2bx8WLF7GxsSE8PJxhw4axYsUKtm/frrxPq9XSvXt3rKyslKwOYcn8O7a3t7cY8TaPtsi1eXs3jpOY/zs8PBxXV1dWr16Ng4MDSUlJNG3alFGjRinP/507d1JUVKRsFSRurUWLFmg0Gnbt2kVBQYFy3HzOS0tLuXDhAj4+PhZtKmlf3Zng4GBiYmI4cOAA8+fP55NPPmHp0qUsWrSI1NRUpk6dKgH3XSooKGDSpEns2LFDaRs4Ozvj7+9Peno6Go2G119/nY4dO+Lo6MiBAwf44YcfSEtLA5CA+yGQu0M9cfz4cSZPnsysWbOYPHkyn332GWlpaVy6dAlfX1/efPNNqqqqiI2NRafTMWrUKBwdHVmzZk1tV71OMxgMrFmzhk6dOjFs2DBlBVej0Yher6e4uJiZM2fi7e3NokWLSElJITExkUWLFlFYWFjLta/7zNMg1Go1sbGxmEwmgoODsbKyYs+ePZSWliplPTw8sLOzo6yszOIzpBHzX3/sIGrfvr3yWv/+/cnOzmbFihXAfwOYkpIS7OzslN5tcXOHDh1i4cKFTJs2jXXr1qHVaomLi+PatWtK4G1tbU2vXr148cUXWblyJRs2bKj2OTLSfXvmwHvYsGFs3bqVVatW1XaV6jRzSvONKzibs4cAOnXqREVFBSEhIUpWxrZt2/j+++9JSEhgx44dvPrqq7i6utZK/eubxo0b87e//Y0jR46watUqZT0clUpFYWEhCxcupKioSNkOUNwdtVpNjx49mDFjBl5eXpw+fVqZBjVjxgyaN29e21WsVwoKCnBycsLLy4tdu3Yxe/Zsfv31V2xtbXn22Wf59ddf2bRpExqNhqCgIF555RVGjBhB8+bN6dixY21X/5Eh6eX1RF5eHh9//DFGoxEnJyc8PDxITU3F0dGRJk2a8Pjjj2Nvb8+aNWvw9vZm8uTJFBUVKaOFomZGo5EZM2YQEhJCeHg4AOnp6aSnp7N3717s7e1p1aoVb7/9Nh9++CEXLlygvLycN998Ux4Kd8g8DWLJkiU4ODgQHx/PqlWrOHLkCE8//TShoaFoNBqWLVtGVVUVU6ZMkZHtGhgMBj7++GMee+wxi7UZKisrKSkpIT8/n5MnT5KSkoKzszOtW7dGr9fz7bff8v7778uowW3s3LmTxMREnnvuOUwmE9u2bWPkyJGEhYUpqeY2NjZMmDABrVZLRUUF69ev5/jx48yYMUOu2XtUWlpKWloafn5+eHp61nZ16jS9Xs/KlSsJCgqiY8eOFiNTBQUFjBs3jhdffJH27duzatUqTp48ib29PS4uLkRFRckq5XepqqqKvXv3kpCQgIuLC02aNMFkMlFaWkpVVRUzZ85Eo9FISvmfJOfvzzEYDEybNo3Kykrmzp2rrKyfnp7OX//6V8LDw7l06RLz589n9OjRPPHEE8p7y8rKJFvzIZKgux7Jzc0lKSmJyspKIiMj0el0nDlzhm3btnH16lUyMzNxdnamsLCQ3r17M3z4cEBuaLdSWlrK5MmTCQgI4K9//SvfffcdKSkpNGnShNatW2Nra8tXX31F165dGTRoEBcuXMDBwQFHR8farnqdlZmZyZUrV2jXrh1Go1FJtz1z5gwfffQROp2Od999l3Xr1nH48GHOnj2Lj48PGo1GGjG3cKsOoj179uDm5oa1tTVDhw5lx44dXLlyBUdHR4YMGYKPj08t175u2717NwkJCbz11lsEBwcDsHDhQvz8/AgJCcHFxUXZSlCtVjN+/Hi0Wi2VlZXK9iqy7sC9k3N3Z86dO0diYiIZGRn4+fnh7+9P//790Wg0NGjQgPXr1/PNN98wbdo07O3tlSkmVlZW2NjY1HLt66+zZ8+yZ88ecnNz0Wq1NGvWTNlVw/yME/fuxt+/3Avunslk4pdffmHp0qXY29sTHx8PwObNm9m9ezcajYYOHTpgNBopLy9n8ODBskBdLZGgu57Jyclh+fLlmEwmIiIi8PPzA64H1keOHEGv13Pq1CneeOMN2dv0Dh0/fpz4+HgaNmxISUkJUVFRPPHEE7i7u1NZWcns2bNxdnZmzJgxtV3VOu/48ePMnDkTAF9fX7y8vAgKCqJFixbodDoyMzNZunQpNjY2zJw5k4qKCo4dO4ajoyO+vr7SiLmFO+kg+vrrr3nqqaeIjIzEZDJhNBrlPnAbP/30EzNmzGDw4MEMGjRIOT5hwgRMJhP5+fn4+PgQFhZG69atmT17NqWlpXzwwQc4OzsD0lAUD9fvv/9OcnIyx44dw2g0EhISQpcuXZSRrldeeYW//OUvcl0+YNI5LOqKGxdWtrW1ZdasWahUKn755ReOHj3Kjh07KC0txcbGhsmTJ+Pv71/bVX4kSdBdD+Xm5vL5558D1+dxBgYG1ljuj6uWi5srKCjg8uXL6HQ6pSEN129kCxYswNPTkyFDhgBII+YW7mYahKenZ7VUcmnE3NqddBA5OTkpK5WL28vNzeXTTz/FwcGBgQMH0rJlS+bNm0dWVhaRkZHY29vzxRdfKFMfqqqqWLVqFWPGjJFrVdSaiooKDAYD69ev59SpU2RmZtK/f3+Sk5OVbCJJG71/pAND1CVFRUXo9Xpl4A2ut/nPnj3LP/7xD6ytrZkzZw4qlYqysjIKCgr49NNPycrKYs6cObi7u9di7R9dEnTXU7m5ucoepwMGDCAgIKCWa/S/p7KyknXr1rF3716mT5+Oh4dHbVepXribaRC9evXi5Zdfru0q1yvSQXT/me+narWaq1evYjAYGDduHI0aNQKu79k7ceJExo8fT4cOHZT3SSeRqAsuX77MkSNH2LdvH7/99hsajYaFCxda3B+EEP8bCgoKiI2NpaSkhMDAQFq1akWbNm1o0aIF9vb2ZGZmsmzZMiorK5k3b57SDigrK6O8vJzHHnuslv+CR5cE3fVYbm4uK1eupLi4mNdee00WSbmPUlNT+e233zh48CCTJk2SRdPukkyDeLikg+jPy83NJSEhgd9++41XX32VkJAQZbu6M2fO8PHHHzNq1Cjp4BR1xh9HX4uLi8nPz8fJyYnGjRvXYs2EEA9Kfn4+c+fOxWAwYGdnh7e3NwcPHsTLywsfHx/at2+PSqVizZo1uLq6MnXqVOmAryMk6K7nzp07x549e4iKipIRl/skJyeHZcuW4eDgQGRkJN7e3rVdpXpJpkE8HNJBdP/k5eXxz3/+E7VaTb9+/WjdujUAs2bNory8nLi4OLnPCiGEqFV5eXkkJiZSVVVF//79cXV15eTJk2zfvh2j0Uh2djaNGzcmOzubDh06MH78+NquskCC7v8pkup4/xQXF9OgQQPs7e1ruyr1mkyDeLCkg+j+M1+zKpWK/v37s3nzZrKzs5k/f76srC+EEKJOuDGjMDIyEl9fXwCuXr3KDz/8wPnz50lPT+e1116Tzvg6QoJuIcQDJdMgHizpILr/zNdsRkYGjRs3Zt68eWg0GllZXwghRJ1xu4xCeWbVLRJ0CyEeOJkGIeqb8+fPk5ycTHR0tLLXvDRehBBC1CXm7CyTycSgQYNkO7A6TIJuIcRDJem5or6RgFsIIURdZc7OunLlCtHR0RZbiYm6Q1q+QoiHSgJuUd9IwC2EEKKu8vDw4KWXXkKr1dKwYcParo64CRnpFkIIIYQQQoh6THaDqdsk6BZCCCGEEEIIIR4QyfMUQgghhBBCCCEeEAm6hRBCCCGEEEKIB0SCbiGEEEIIIYQQ4gGRoFsIIYQQQgghhHhAJOgWQgghhBBCCCEeEAm6hRBCCCGEEEKIB0SCbiGEEKKWLF68mNGjR9/ze1966aXbltPr9URERLBp06Z7+p67NXr0aGbNmvVQvutOmP/+ffv21XZVhBBCPKIk6BZCCCFuY9++fURERPDiiy9SWFhY7fXp06czbty4WqiZEEIIIeo6TW1XQAghhKgvKioq2LBhAyNGjLgvn/fqq69iMpnuy2cJIYQQom6SkW4hhBDiDjVr1ozdu3fXONp9LzQaDQ0aNLgvn1XbysrKarsKQgghRJ0kI91CCCHEHerfvz+LFi26o9Hu1NRUtmzZwrlz57C2tqZt27ZERUWh0+mUMosXL+bnn39m8eLFyrErV66wYsUKvv/+e1QqFUFBQfTp04d33nmHv//97zz77LMW31NYWEhCQgLHjh3D2tqaLl26EBUVhVpdvV998+bNbN26leLiYnx9fRk5ciQ+Pj4WZY4fP87atWs5c+YMVlZWBAYGMmzYMLy9vZUya9euZd26dXz44Yd89dVXpKen4+bmxpw5c5Qyv/zyCytXriQrKwtXV1cGDx5Mly5dLL7rwoULJCUlcezYMSoqKmjatCkDBw6kffv2FuWKi4tZtWoVR44cobS0FE9PT3r37l3tXFy9epUVK1aQlpZmce6EEEKI2iQj3UIIIcQdatSoEc8888xtR7vXr1/P4sWL8fDwIDo6mt69e3Ps2DGmTZvG1atXb/q+qqoqZs+ezYEDB+jSpQuRkZEUFRVZBOV/LB8fH4+TkxMvvfQSgYGBbN68mV27dlUrm5qayrZt2+jZsyf9+/cnOzubGTNmUFRUpJT58ccfiY+Pp7i4mMGDB9OnTx9OnjxJXFwcer2+2md++OGHlJeXM3ToULp166Ycz8vLY/78+bRp04aXXnoJBwcHlixZQnZ2tlKmqKiIKVOmkJGRQc+ePYmMjMRgMDB79mzS0tKUcgaDgenTp5OamkqnTp2IiorC3t6eJUuWsHXrVqWcyWRizpw5pKam0rlzZyIjIyksLLzpuRNCCCEeFhnpFkIIIe7CgAEDSE1NZePGjcTExFR7PT8/n7Vr1zJkyBAGDBigHA8ODiY2Npbk5GSL4zc6fPgwp06d4uWXX+b5558HICwsjPfee6/G8hUVFYSEhDBo0CClbGxsLHv27CEsLMyibF5eHosWLaJhw4YAPPnkk0yaNImNGzcSHR0NQGJiIo6OjsTHx+Po6AhAhw4deOedd1i7di1vvPGGxWc2bdqUN998s1q9cnJyePfdd2ndujUAoaGhvP766+zdu5fhw4cDsGHDBoqLi5kxYwYBAQEAdO/enfHjx7Ny5UqCgoJQq9Xs2rWL8+fPM2bMGDp37gxAjx49mD59Ov/+97/p2rUrdnZ2fP/995w4cYKoqCj69u2rnI933323xnMnhBBCPCwy0i2EEELchcaNG9O5c2d27drFpUuXqr3+3XffYTKZCA0N5fLly8o/Li4uuLu789NPP930s9PT07GysrIYNVar1fTs2fOm7/ljcB0QEMCFCxeqlevQoYMScAP4+vrSqlUrjh49CsClS5c4e/YsXbp0UQJuuB5Yt2nTRil3ox49etRYJ29vbyXgBnB2dsbT09NitPzo0aP4+voqATeAra0t3bt3Jz8/n3PnzinlXFxc6Nixo1JOo9HQq1cvysrK+Pnnn5VyVlZWFudDrVYTHh5eYx2FEEKIh0VGuoUQQoi7NHDgQPbv38+GDRuqjXbn5eVhMpkYO3Zsje/VaG7+6C0oKMDV1RUbGxuL4+7u7jWWb9CgAc7OzhbHHBwcakxh9/DwqPHYt99+C1wfoQfw9PSsVs7Ly4uMjAzKysqwtbVVjjdq1KjGet04b/1m9SooKKBVq1Y1fpf5dR8fH/Lz8/Hw8Kg2R91czlzv/Px8XFxcLOp3s79HCCGEeJgk6BZCCCHu0o2j3f369bN4raqqCpVKxcSJE2tczOyPQeGfUdPnP0zW1tY1Hr9ZvWR7NCGEEI8iCbqFEEKIezBgwAD279/Pxo0bLY67u7tjMplo1KjRXY+y6nQ6jh8/Tnl5ucVod15e3p+ub25ubo3H3NzcAJR/5+TkVCuXk5ODk5PTfe0w0Ol0NX7X+fPnldfN9fr999+pqqqyCObN772x/sePH682Gl/TdwghhBAPk8zpFkIIIe6Bu7s7nTt3ZufOnRYrgAcHB6NWq1m3bl21kV2TycSVK1du+plt27bFaDSye/du5VhVVRXJycl/ur6HDx+2WHE9MzOTX3/9lSeffBIAV1dXmjVrRkpKikUaeFZWFhkZGbRr1+5P1+FG7dq1IzMzk1OnTinHysrK2L17N25ubsoWZe3ataOoqIiDBw8q5YxGI9u2bcPW1pbAwEClnNFoZMeOHUq5qqoqtm/ffl/rLYQQQtwtGekWQggh7pF5JfOcnByaNGkCXA/GIyMjWbVqFfn5+XTo0AFbW1v0ej2HDx+mW7duyurafxQcHIyvry//+te/yMvLw9PTkx9++IGSkpI/XVd3d3fi4uIICwujoqKCrVu34uTkxAsvvKCUiYqK4oMPPmDKlCl07doVg8HA9u3bsbe3JyIi4k/X4Ub9+vXjwIEDvP/++/Tq1QtHR0dSUlLQ6/WMGzdOGdXu3r07O3fuZMmSJZw+fZpGjRpx6NAhTp48ycsvv4ydnR0Af/nLX/D39ycpKQm9Xo+3tzdpaWmUlpbe13oLIYQQd0uCbiGEEOIemUe7U1JSLI7369cPDw8PtmzZwpdffglcT5du06YNQUFBN/08tVrN//3f/7FixQpSUlJQqVQEBwczaNAg4uLibjqH+k4888wzqNVqtmzZwuXLl/H19WXEiBG4uroqZdq0acOkSZNYu3Yta9euxcrKisDAQF588cWbLpp2r1xcXHjvvfdISkpi+/btGAwGmjZtSmxsLO3bt1fKWVtbM336dJKSkkhJSeHatWt4enry97//nWeffVYpp1ariY2NZcWKFezfvx+VSkVQUBDDhw/nnXfeua91F0IIIe6GyiSrmgghhBB1WlpaGvPmzbPY01oIIYQQ9YPM6RZCCCHqEIPBYPH/5nnJdnZ2tGjRopZqJYQQQoh7JenlQgghRB3y+eefYzAY8PPzo6KigrS0NE6ePMnQoUP/VHq5EEIIIWqHpJcLIYQQdcg333zD119/TV5eHhUVFbi7uxMWFkZ4eHhtV00IIYQQ90CCbiGEEEIIIYQQ4gGROd1CCCGEEEIIIcQDIkG3EEIIIYQQQgjxgEjQLYQQQgghhBBCPCASdAshhBBCCCGEEA+IBN1CCCGEEEIIIcQDIkG3EEIIIYQQQgjxgEjQLYQQQgghhBBCPCASdAshhBBCCCGEEA/I/wNUK6w6kkOZIwAAAABJRU5ErkJggg==",
      "text/plain": [
       "<Figure size 1000x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "neighborhood_groups = df.groupby('Neighborhood')\n",
    "neighborhood_quality = neighborhood_groups['OverallQual'].mean()\n",
    "neighborhood_quality_sorted = neighborhood_quality.sort_values(ascending=False)\n",
    "top_10_neighborhoods = neighborhood_quality_sorted.head(10)\n",
    "\n",
    "\n",
    "plt.figure(figsize=(10, 6))\n",
    "plt.bar(top_10_neighborhoods.index, top_10_neighborhoods.values, color='darkturquoise')\n",
    "plt.xlabel('Neighborhood')\n",
    "plt.ylabel('Overall Quality')\n",
    "plt.title('Top 10 Neighborhoods with Highest Overall Quality')\n",
    "plt.xticks(rotation=45)  # Rotate x-axis labels for better visibility\n",
    "\n",
    "plt.tight_layout()\n",
    "plt.show()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 129,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1000x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "neighborhood_groups = df.groupby('Neighborhood')\n",
    "neighborhood_quality = neighborhood_groups['OverallCond'].mean()\n",
    "neighborhood_quality_sorted = neighborhood_quality.sort_values(ascending=False)\n",
    "top_10_neighborhoods = neighborhood_quality_sorted.head(10)\n",
    "\n",
    "\n",
    "plt.figure(figsize=(10, 6))\n",
    "plt.bar(top_10_neighborhoods.index, top_10_neighborhoods.values, color='darkkhaki')\n",
    "plt.xlabel('Neighborhood')\n",
    "plt.ylabel('Overall Condition')\n",
    "plt.title('Top 10 Neighborhoods with Highest Overall Condition')\n",
    "plt.xticks(rotation=45)  \n",
    "\n",
    "plt.tight_layout()\n",
    "plt.show()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 126,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1000x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "neighborhood_groups = df.groupby('Neighborhood')\n",
    "neighborhood_price = neighborhood_groups['SalePrice'].mean()\n",
    "neighborhood_price_sorted = neighborhood_price.sort_values(ascending=False)\n",
    "top_10_neighborhoods = neighborhood_price_sorted.head(10)\n",
    "\n",
    "\n",
    "plt.figure(figsize=(10, 6))\n",
    "plt.bar(top_10_neighborhoods.index, top_10_neighborhoods.values, color='azure')\n",
    "plt.xlabel('Neighborhood')\n",
    "plt.ylabel('sale price')\n",
    "plt.title('Top 10 Neighborhoods with Highest sale price')\n",
    "plt.xticks(rotation=45)\n",
    "\n",
    "plt.tight_layout()\n",
    "plt.show()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 117,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 800x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(8, 6))\n",
    "sns.histplot(data=df, x='SalePrice', bins=30, kde=True)\n",
    "plt.ylabel('Frequency')\n",
    "plt.title('Distribution of SalePrice')\n",
    "plt.xticks(rotation=45)\n",
    "plt.show()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 84,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 800x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(8, 6))\n",
    "sns.histplot(data=df, x='YearBuilt', bins=30, kde=True)\n",
    "plt.xlabel('Year Built')\n",
    "plt.ylabel('Frequency')\n",
    "plt.title('Distribution of Year Built')\n",
    "plt.xticks(rotation=45)\n",
    "plt.show()\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## deleting outlier from needed features"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 132,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAggAAAG0CAYAAABXHN/wAAAAOXRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjcuMSwgaHR0cHM6Ly9tYXRwbG90bGliLm9yZy/bCgiHAAAACXBIWXMAAA9hAAAPYQGoP6dpAAAeU0lEQVR4nO3de5CV9X3H8c+BBXYRARGQgAW0FWuMYpLRtrbFGp3QaMzEBihBrfUSTdS00Ri1VlM13qK1jK0TYw1O8IL36iRTL41NzYyADWrVgiZKgwNRFJWLLruL7HL6B7Mnbn7chIXdhddrxgnnnGef8zzfnH32fZ5z9mylWq1WAwDwIb26egMAgO5HIAAABYEAABQEAgBQEAgAQEEgAAAFgQAAFAQCAFAQCABAoW5bV7BixYq0trZ2xrZ0iWHDhuXtt9/u6s3oUmZgBu3MwQwSM2i3s86hrq4ue+yxx+aX29Y7am1tzdq1a7d1NV2iUqkkWb8Pu+onTpuBGbQzBzNIzKCdOXiJAQDYAIEAABQEAgBQEAgAQEEgAAAFgQAAFAQCAFAQCABAQSAAAAWBAAAUBAIAUBAIAEBBIAAABYEAABQEAgBQEAgAQEEgAAAFgQAAFAQCAFAQCABAQSAAAAWBAAAUBAIAUBAIAEBBIAAABYEAABQEAgBQEAgAQEEgAAAFgQAAFAQCAFAQCABAoa6rNwBga1Sr1bS0tHTqOiuVSpqamtLc3Jxqtdqp6+4s1Wo1a9asSZL069cvlUqlU9ffE2awI7TPYVeegUAAeqSWlpYcc8wxXb0Z7OQeffTR1NfXd/VmdAkvMQAABWcQgB7v7aPeTrX3LnIquDUZ/tPhSZJln1nmKL4dVNoqGfafw7p6M7qchxbQ41V7V3fNo1ldds393s6q2UViczO8xAAAFAQCAFAQCABAQSAAAAWBAAAUBAIAUBAIAEBBIAAABYEAABQEAgBQEAgAQEEgAAAFgQAAFAQCAFAQCABAQSAAAAWBAAAUBAIAUBAIAEBBIAAABYEAABQEAgBQEAgAQEEgAAAFgQAAFAQCAFAQCABAQSAAAAWBAAAUBAIAUBAIAEBBIAAABYEAABQEAgBQEAgAQEEgAAAFgQAAFAQCAFAQCABAQSAAAAWBAAAUBAIAUBAIAEBBIAAABYEAABQEAgBQEAgAQEEgAAAFgQAAFAQCAFAQCABAQSAAAAWBAAAUBAIAUBAIAEBBIAAABYEAABQEAgBQEAgAQEEgAAAFgQAAFAQCAFAQCABAQSAAAAWBAAAUBAIAUBAIAEBBIAAABYEAABTqunoDeqpqtZqWlpYkSX19fSqVShdvEQA7g+7y88UZhK3U0tKSY445Jsccc0zt/0gA2Fbd5eeLQAAACgIBACgIBACgIBAAgIJAAAAKAgEAKAgEAKAgEACAgkAAAAoCAQAoCAQAoCAQAICCQAAACgIBACgIBACgIBAAgIJAAAAKAgEAKAgEAKAgEACAgkAAAAoCAQAoCAQAoCAQAICCQAAACgIBACgIBACgIBAAgIJAAAAKAgEAKAgEAKAgEACAgkAAAAoCAQAoCAQAoCAQAICCQAAACgIBACgIBACgIBAAgIJAAAAKAgEAKAgEAKAgEACAgkAAAAoCAQAoCAQAoCAQAICCQAAACgIBACgIBACgIBAAgIJAAAAKAgEAKAgEAKAgEACAgkAAAAoCAQAoCAQAoCAQAICCQAAACgIBACgIBACgIBAAgIJAAAAKAgEAKAgEAKAgEACAgkAAAArdLhDmzJmTqVOnZs6cOZ2y3Kacc8452X///XPOOed0+roBoCfrVoHQ0tKS6dOn56233sr06dPT0tKyTcttyuLFizN//vwkyfz587N48eJOWzcA9HTdKhBmzZqVd999N0ny7rvvZtasWdu03KZ87Wtf2+Dlzlg3APR0dV29Ae1ef/31zJo1K9VqNUlSrVZz9913Z+LEiRk1atRHXm5T7rnnnjQ1NXW4rqmpKbfcckvuv//+LVp3+zJJevRZhkqlkqampjQ3N3fYp12JGazX0+bQ4fuu+28uPcmHHk8tLS07/Pvhw4/trvxe3OJAWLt2bdauXVu7XKlU0tDQ0CkbUa1Wc+ONN270+u9+97upVCpbvNymtLa25pZbbtngbffcc0969ep4UmVj616zZk3t33/xF3+xyfsEtrO2JH26eiPYabT95p/HH398121H1v+s6d+/f5fc9xYHwkMPPZQHHnigdnmfffbJd7/73U7ZiMWLF2fevHnF9W1tbZk3b14WL16cMWPGbPFym3LHHXds8vZ169Zt9boBYGexxYFw/PHH5/Of/3zt8uaeqX8Uo0ePzqGHHprnnnsubW2/SbfevXvn05/+dEaPHv2RltuUk046KbfffvtGb28/U7G5dffr16/273/7t39LfX395ne0G6pUKhkxYkTefPPNHnFaeXswg/V62hxaWlp+c/aud9duCzuZDz2eHnrooQ7H+x3hw4/tHX3fH7bFgdCnT5/06bN9zuFVKpX87d/+bU4++eTi+r/5m7+pxciWLrcpdXV1OfPMMzf4MsPUqVNz//33d4iPja37w5fr6+s77eWWHa1SqaR///5paGjoET8UtgczWK9Hz6Hznq9Ah8dTfX19lz4B7Mwn4x9Vt/kthlGjRmXatGkdYuDLX/5y8ebALV1uU6ZOnVq8ptO/f/+ceeaZ27xuANgZdJtASJJp06Zlzz33TJIMHTo006ZN26blNuXmm2/e4OXOWDcA9HTdKhDq6+tz7rnnZq+99so3vvGNjZ7W2dLlNmX06NH5xCc+kST5xCc+UXuPQWesGwB6um7zOQjtDj/88Bx++OGdttym3HTTTfnYxz6WpUuXdnjNtTPWDQA9Wbc6gwAAdA8CAQAoCAQAoCAQAICCQAAACgIBACgIBACgIBAAgIJAAAAKAgEAKAgEAKAgEACAgkAAAAoCAQAoCAQAoCAQAICCQAAACgIBACgIBACgIBAAgIJAAAAKAgEAKAgEAKAgEACAgkAAAAoCAQAoCAQAoCAQAICCQAAACgIBACgIBACgIBAAgIJAAAAKAgEAKAgEAKAgEACAgkAAAAoCAQAoCAQAoCAQAICCQAAACgIBACgIBACgIBAAgIJAAAAKAgEAKAgEAKAgEACAgkAAAAoCAQAoCAQAoCAQAICCQAAACgIBACgIBACgIBAAgIJAAAAKAgEAKAgEAKAgEACAgkAAAAoCAQAoCAQAoCAQAICCQAAACgIBACgIBACgIBAAgEJdV29AT1VfX59HHnmk9m8A6Azd5eeLQNhKlUolDQ0NXb0ZAOxkusvPFy8xAAAFgQAAFAQCAFAQCABAQSAAAAWBAAAUBAIAUBAIAEBBIAAABYEAABQEAgBQEAgAQEEgAAAFgQAAFAQCAFAQCABAQSAAAAWBAAAUBAIAUBAIAEBBIAAABYEAABQEAgBQEAgAQEEgAAAFgQAAFAQCAFAQCABAQSAAAAWBAAAUBAIAUBAIAEBBIAAABYEAABQEAgBQEAgAQEEgAAAFgQAAFAQCAFAQCABAQSAAAAWBAAAUBAIAUBAIAEBBIAAABYEAABQEAgBQEAgAQEEgAAAFgQAAFAQCAFAQCABAQSAAAAWBAAAUBAIAUBAIAEBBIAAABYEAABQEAgBQEAgAQEEgAAAFgQAAFAQCAFAQCABAQSAAAAWBAAAUBAIAUBAIAEBBIAAAhbqu3gCAbVVpq6Saaldvxo7RupF/02kqbZWu3oRuQSAAPd6w/xzW1ZvQJYb/dHhXbwI7MS8xAAAFZxCAHqm+vj6PPPJIp66zUqlkxIgRefPNN1Otds+XLKrVatasWZMk6devXyqVzj0d3hNmsCO0z2HlypVdvSldRiAAPVKlUklDQ0Onr7N///5paGjo1j8c+/fvv93W3VNmsL21z2HVqlW77By8xAAAFAQCAFAQCABAQSAAAAWBAAAUBAIAUBAIAEBBIAAABYEAABQEAgBQEAgAQEEgAAAFgQAAFAQCAFAQCABAQSAAAAWBAAAUBAIAUBAIAEBBIAAABYEAABQEAgBQEAgAQEEgAAAFgQAAFAQCAFAQCABAQSAAAAWBAAAUBAIAUBAIAEBBIAAABYEAABTqtnkFddu8ii63M+zDtjIDM2hnDmaQmEG7nXEOW7pPlWq1Wt3O2wIA9DC79EsMzc3NufDCC9Pc3NzVm9JlzMAM2pmDGSRm0M4cdvFAqFarWbRoUXblkyhmYAbtzMEMEjNoZw67eCAAABsmEACAwi4dCH369MmkSZPSp0+frt6ULmMGZtDOHMwgMYN25uC3GACADdilzyAAABsmEACAgkAAAAoCAQAo9OgPmX7ppZfyox/9KIsWLcqKFSty/vnn57DDDqvd3tLSkrvuuivz5s3L+++/n+HDh+dzn/tcPvvZz9aWWblyZe644468+OKLaWlpyciRI3P88cfnD//wD2vLNDY25rbbbsuzzz6bSqWSP/iDP8gpp5yS+vr6Hbq/G7O5OaxcuTJ33XVXXnzxxaxevToHHHBATj311HzsYx+rLfPBBx/k9ttvz5w5c7J27dqMHz8+p59+egYPHlxb5p133smtt96aBQsWpL6+PkcccUSmTZuW3r1778jd3aBtnUFjY2Puu+++vPDCC3nnnXcycODAHHrooZk6dWr69+9fW093nkHSOY+FdtVqNddcc02ef/75Yj3deQ6dNYNXXnkld999dxYuXJhevXpl7Nix+fu///v07ds3Sfc+LnTGDHr6sfGhhx7Kz3/+87z++uvp27dvxo0blxNPPDEjR46sLdNZx70FCxbk9ttvz5IlS7LnnnvmS1/6Uv7sz/5sB+7t9tGjzyCsWbMmY8eOzWmnnbbB22fOnJnnn38+X//61zN9+vQce+yxue222/LMM8/Ulrnpppvyxhtv5MILL8w//uM/5rDDDsv06dOzaNGi2jL//M//nCVLluSSSy7JRRddlJdffjm33HLLdt+/LbWpOVSr1Vx//fVZtmxZvvWtb+W6667LsGHD8p3vfCctLS215WbOnJlnn3025513Xi6//PKsWLEiN9xwQ+32devW5Zprrklra2uuvPLKnH322XnyySdz77337pB93JxtncHy5cuzfPnynHTSSbnhhhty9tln54UXXsjNN99cW093n0HSOY+Fdv/+7/+eSqVSXN/d59AZM3jllVdy1VVXZfz48bn66qtzzTXXZOLEiR3m0Z2PC50xg55+bHzppZcyceLEXHXVVbnkkkvS1taWK6+8stOPe8uWLcu1116bAw88MNddd12OPfbYfP/738/zzz+/I3d3+6juJCZPnlz97//+7w7XnXfeedX777+/w3UXXHBB9e67765dPvHEE6s/+9nPOixzyimnVJ944olqtVqtLlmypDp58uTqwoULa7f/z//8T3XKlCnVd999t7N3Y5v99hxef/316uTJk6uLFy+uXdfW1lY97bTTavu4evXq6tSpU6tz586tLfPrX/+6Onny5Oovf/nLarVarT733HPVKVOmVFesWFFb5vHHH6/+1V/9VXXt2rXbea8+mq2ZwYbMmTOn+uUvf7na2tparVZ71gyq1W2bw6JFi6pnnnlmdcWKFcV6etIctnYGF198cYfjxG/rSceFrZ3BznZsXLVqVXXy5MnVBQsWVKvVzjvu3XHHHdXzzjuvw31Nnz69euWVV27nPdr+evQZhM0ZN25cnn322SxfvjzVajXz58/P0qVLc/DBB9eW2X///TNnzpw0NjZm3bp1mT17dtauXZsDDzwwyfpnErvttlt+93d/t/Y1Bx10UCqVShYuXLjD9+mjam1tTZIOH/bRq1ev9OnTJ7/4xS+SJL/61a/S1taWgw46qLbMqFGjMnTo0LzyyitJ1s9h9OjRHU69HXLIIWlubs6SJUt2wJ5svS2ZwYY0NTWloaGhdiqxJ88g2fI5rFmzJjfeeGNOO+20DvvarifPYUtmsGrVqrz66qsZNGhQLrnkknzlK1/JP/zDP3SYUU8+Lmzp42BnOzY2NTUlSQYMGJCk8457r776aod1JMn48eNr6+jJdupAOPXUUzNq1Kh89atfzbRp03L11VfntNNOy8c//vHaMueee27a2tpy6qmn5oQTTsi//uu/5vzzz8+IESOSrH8dbuDAgR3W27t37wwYMCArV67ckbuzVUaOHJmhQ4dm1qxZaWxsTGtrax5++OG8++67te1fuXJl6urqsttuu3X42kGDBnVY5rd/WAwaNKh2W3e2JTP4be+9914efPDBHH300bXrevIMki2fw8yZM7P//vvn0EMP3eB6evIctmQGb731VpLk/vvvz1FHHZWLL744++yzT6644oosXbo0Sc8+Lmzp42BnOjauW7cuP/zhD7P//vtn9OjRSTrvuLdy5cradR9eprm5OR988EHn78wO1KPfpLg5jz76aF599dVccMEFGTZsWF5++eXMmDEje+yxR+0swr333pvVq1fn0ksvze6775558+Zl+vTpueKKK2oPpJ6srq4u559/fm6++eaceuqp6dWrVw466KB88pOf3GX+StlHnUFTU1Ouvfba7L333pk8eXIXbPH2sSVzeOaZZzJ//vxcd911Xby128eWzKD9f48++ugceeSRSZJ99tkn8+fPz3/9139l2rRpXbb9nWFLvx92pmPjjBkzsmTJklxxxRVdvSk9yk4bCB988EHuvvvufOtb38qnPvWpJMmYMWPy2muv5cc//nEOPvjgvPnmm3nsscdyww035Hd+53eSJGPHjs0vfvGLPPbYYznjjDMyePDgvPfeex3W3dbWlsbGxg2efu2O9t1331x//fVpampKa2trBg4cmIsvvjj77rtvkmTw4MFpbW3N6tWrO9T0qlWravs4ePDg4rThqlWrard1d5ubQbvm5uZcffXVaWhoyPnnn5+6ut98i/T0GSSbn8P8+fPz1ltv5a//+q87fN0NN9yQAw44IJdddlmPn8PmZrDHHnskSfbee+8OXzdq1Ki88847SdLjjwubm8HOdGycMWNGnnvuuVx++eXZc889a9d31nFv8ODBtes+vExDQ0PtN156qp32JYbW1ta0tbUV78Lu1atXrZLbT/9saplx48Zl9erV+dWvflW7ff78+alWq/m93/u97bkLna5///4ZOHBgli5dmv/7v/+rnULed99907t37/zv//5vbdk33ngj77zzTsaNG5dk/RwWL17c4RvhxRdfTENDQ3Eg7c42NoNk/ZmDK6+8MnV1dbnggguKb+6dZQbJxufwxS9+Mddff32uu+662n9JcvLJJ+ess85KsvPMYWMzGDZsWPbYY4+88cYbHZZfunRphg4dmmTnOS5sbAY7w7GxWq1mxowZ+fnPf55vf/vbGT58eIfbO+u4t99++3VYR/sy7evoyXr0GYSWlpa8+eabtcvLli3La6+9lgEDBmTo0KH5+Mc/njvvvDN9+/bNsGHD8tJLL+VnP/tZTj755CTrX4sbMWJEbr311px00kkZMGBA5s2blxdffDEXXnhhkvXPIg455JDccsst+cpXvpLW1tbcdtttOfzwwzNkyJAu2e/ftrk5zJ07NwMHDszQoUOzePHi/PCHP8yhhx6a8ePHJ1l/kPjMZz6T22+/PQMGDEj//v1z2223Zdy4cbUH+fjx47P33nvnpptuygknnJCVK1fmnnvuycSJE7vFXzvb1hk0NTXlqquuypo1a/L1r389zc3NaW5uTpIMHDgwvXr16vYzSLZ9DoMHD97gs7+hQ4fWDrDdfQ7bOoNKpZIvfOELue+++zJ27NiMHTs2Tz75ZF5//fWcd955Sbr/cWFbZ7AzHBtnzJiRp556KhdccEEaGhpq7xno379/+vbt22nHvc9+9rN5/PHHc+edd+bII4/M/PnzM3fu3Fx00UVdteudpkf/NccFCxbk8ssvL64/4ogjcvbZZ2flypWZNWtWXnjhhTQ2NmbYsGE5+uijc+yxx9bKeOnSpbnrrrvyy1/+Mi0tLRkxYkSOO+64TJgwoba+xsbGzJgxo8OHgZx66qnd4sNAks3P4ZFHHsmPf/zjrFy5MnvssUcmTJiQSZMmdTh93v6BIbNnz05ra+sGPzDk7bffzg9+8IMsWLAg/fr1yxFHHJETTjihW3w4zrbOYGNfn6z/ffD2H47deQZJ5zwWftuUKVOKD9rpznPorBk8/PDDefzxx9PY2JgxY8bkxBNPzO///u/Xbu/Ox4XOmEFPPzZOmTJlg9efddZZtQ8x6qzj3oIFCzJz5sz8+te/3qk+KKlHBwIAsH3stO9BAAC2nkAAAAoCAQAoCAQAoCAQAICCQAAACgIBACgIBACgIBCAHebJJ5/MlClTsmzZstp1l112WS677LKu2yhgg3r032KAncnVV1+dV199NdOnTy/+HkJTU1O+8Y1vZOjQobnyyivTq9f2bfsNfVTvbrvtlpEjR+bP//zP86d/+qfb7b6XL1+eJ554IocddljGjh273e4H2DRnEKCbOP3009Pa2pqZM2cWt82aNSvvv/9+zjjjjO0eBx/2uc99Luecc07OOeecTJ48OZVKJf/yL/+Sxx57bKvWN2HChNx5550ZNmzYRpdZsWJFHnjggbz22mtbudVAZxAI0E0MHz48kyZNyuzZs/PCCy/Url+4cGF+8pOf5Nhjj93uz6g/+OCDrFu3rnb5gAMOyIQJEzJhwoQcc8wxueyyyzJkyJDMnj17q9bfq1ev9O3bt/gzwkD3IxCgG/n85z+fMWPG5Ac/+EHth/Wtt96aYcOGZfLkyXn99ddzww035JRTTskJJ5yQiy66KM8880yHdTQ2Nub222/PN7/5zZx00kk5+eSTc/XVVxfPyBcsWJApU6Zk9uzZueeee3LmmWfmpJNOqv2Z6w2pq6vLbrvt1uEsxrJlyzJlypQ8+eSTxfJTpkzJfffdV7u8ofcg/PY2/d3f/V2S5Hvf+16mTJmy0XUD25f3IEA30rt375xxxhm55JJL8uCDD2bQoEFZtGhRLr744ixbtiyXXnpphgwZki9+8Yvp169f5s6dm+uvvz7f/OY3a3+O+a233sq8efPyR3/0Rxk+fHhWrlyZJ554Ipdddln+6Z/+KUOGDOlwnw8++GDq6upy3HHHpbW1tcOf/G1ubs57772XZH14PPXUU1myZEm++tWvbpf9HzVqVC0qjj766NqfV95///23y/0BGycQoJvZb7/9MnHixPzoRz9Knz598sd//Mc55JBD8p3vfCdDhw7NNddckz59+iRJJk6cmG9/+9u56667aoEwevTo3HjjjR2e5U+YMCHnnntufvrTn2bSpEkd7m/t2rW59tpr07dv32Jbbr755g6XK5VKpk6dms985jOdvdtJksGDB+eTn/xk7rvvvowbNy4TJkzYLvcDbJ5AgG5o6tSpefrpp7NmzZqcfPLJaWxszPz58zNlypQ0Nzd3eBlg/Pjxue+++7J8+fIMGTKkFg9Jsm7duqxevTr19fUZOXJkFi1aVNzXEUccscE4SJJJkybVnsU3NjbmmWeeyT333JP6+vocc8wxnbzXQHciEKAb6t+/f0aOHJn3338/gwcPzsKFC1OtVnPvvffm3nvv3eDXrFq1KkOGDMm6devyyCOP5D/+4z+ybNmyDm86HDBgQPF1w4cP3+h2jB49OgcffHDt8uGHH56mpqbcdddd+ZM/+ZMMHDhwG/YS6M4EAvQA7T/kjzvuuIwfP36Dy4wYMSJJ8tBDD+Xee+/NkUcemb/8y7/MgAEDUqlUMnPmzFSr1eLrNnb2YGMOOuigPPfcc1m4cGE+9alPbfQ3Ej4cJkDPIxCgB9hrr72SrH8T44ef0W/I008/nQMPPDBf+9rXOly/evXq7L777tu8LW1tbUmSlpaWJOs/QKl9/R/29ttvb9X6/QokdA9+zRF6gEGDBuXAAw/ME088kRUrVhS3t/+mQZINfpDS3Llzs3z58k7Zlueeey5JMmbMmCTrXw7Zfffd8/LLL3dY7vHHH9+q9ffr1y9JGRzAjuUMAvQQp512Wi699NKcf/75OeqoozJ8+PCsWrUqr7zySpYvX57rr78+SfLpT386DzzwQL73ve9l3LhxWbx4cZ566qnaWYiP4uWXX84HH3yQZP2bFJ999tm89NJLOfzwwzNq1KjackcddVQefvjhfP/738++++6bl19+OUuXLt2q/dxrr72y22675Sc/+UkaGhrSr1+/7Lfffpt8rwTQ+QQC9BB77713rr322tx///158skn8/7772fQoEEZO3ZsvvSlL9WWO/7449PS0pLZs2dnzpw52WeffXLRRRdl1qxZH/k+H3300dq/6+rqstdee2Xq1Kn5whe+0GG5SZMm5b333svTTz+duXPn5pBDDsnFF1+c008//SPfZ11dXc4+++zMmjUrt956a9ra2nLWWWcJBNjBKtUNvWsJANileQ8CAFAQCABAQSAAAAWBAAAUBAIAUBAIAEBBIAAABYEAABQEAgBQEAgAQEEgAAAFgQAAFP4fc8QwgZ64AXoAAAAASUVORK5CYII=",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.boxplot(x = 'YearBuilt', data = df, color = 'green')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 139,
   "metadata": {},
   "outputs": [],
   "source": [
    "Q1 = df['YearBuilt'].quantile(0.25)\n",
    "Q3 = df['YearBuilt'].quantile(0.75)\n",
    "IQR = Q3 - Q1\n",
    "\n",
    "filter = (df['YearBuilt'] >= Q1 - 1.5 * IQR) & (df['YearBuilt'] <= Q3 + 1.5 *IQR)\n",
    "df = df.loc[filter]  "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 134,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.boxplot(x = 'OverallQual', data = df, color = 'green')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 137,
   "metadata": {},
   "outputs": [],
   "source": [
    "Q1 = df['OverallQual'].quantile(0.25)\n",
    "Q3 = df['OverallQual'].quantile(0.75)\n",
    "IQR = Q3 - Q1\n",
    "\n",
    "filter = (df['OverallQual'] >= Q1 - 1.5 * IQR) & (df['OverallQual'] <= Q3 + 1.5 *IQR)\n",
    "df = df.loc[filter]  "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 140,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.boxplot(x = 'LotArea', data = df, color = 'green')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 141,
   "metadata": {},
   "outputs": [],
   "source": [
    "Q1 = df['LotArea'].quantile(0.25)\n",
    "Q3 = df['LotArea'].quantile(0.75)\n",
    "IQR = Q3 - Q1\n",
    "\n",
    "filter = (df['LotArea'] >= Q1 - 1.5 * IQR) & (df['LotArea'] <= Q3 + 1.5 *IQR)\n",
    "df = df.loc[filter]  "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 143,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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AIBAAAIBBIAAAAINAAAAABoEAAAAMAgEAABgEAgAAMAgEAABgEAgAAMAgEAAAgEEgAAAAg0AAAABG8FlvIPisN1Gj2z2XMANmIDEDiRlIzEBiBlLVzKCy23A5juOc9d4AAECtEnBPMRQXF2vcuHEqLi7296H4DTNgBhIzkJiBxAwkZiD5ZwYBFwiO4yg9PV11+cIGM2AGEjOQmIHEDCRmIPlnBgEXCAAAwP8IBAAAYARcINSrV08DBw5UvXr1/H0ofsMMmIHEDCRmIDEDiRlI/pkB72IAAABGwF1BAAAA/kcgAAAAg0AAAAAGgQAAAIyA+2DrFStW6MMPP1ReXp5at26t+++/X5dccom/D+usLVy4UBs2bND333+v+vXrq23btho2bJguvPBC7zpHjhzR7NmzlZqaqqNHj6pjx44aMWKEwsPDvevk5OToX//6l3bu3KmQkBD17NlTCQkJCgoK8sNZnZ1FixYpOTlZ8fHxuvfeeyXVjRn89NNPmjNnjrZu3arDhw8rOjpao0aN0sUXXyzplw9EmTdvnj7++GMVFhbqsssu04gRI9S8eXPvNg4dOqQ33nhDmzZtksvl0q9//Wvdd999CgkJ8ddpVZrH49G8efO0du1a5eXlKTIyUj179tTtt98ul8slqfbN4Msvv9TixYuVnp6u3Nxc/fnPf1a3bt28t1fV+X733XdKSkrSt99+q8aNG+umm27SgAEDavRcT+RkMygtLdW7776rLVu2KCsrS2FhYYqLi1NCQoIiIyO926jNMzjWP//5T61evVr33HOP+vbt611ekzMIqCsIqampmj17tgYOHKgpU6aodevWmjx5svLz8/19aGftyy+/VJ8+fTR58mSNHz9eZWVleuaZZ1RSUuJd56233tKmTZv0pz/9SRMnTlRubq7+9re/eW/3eDx67rnnVFpaqmeeeUajR4/WmjVrNHfuXH+c0lnZs2ePVq1apdatW/ssr+0zOHTokCZMmKDg4GA98cQTmj59uu6++26dd9553nU++OADLV++XCNHjtSzzz6rBg0aaPLkyTpy5Ih3nZdffln79+/X+PHj9dhjj2nXrl16/fXX/XFKp23RokVatWqVhg8frunTp2vo0KFavHixli9f7l2nts3g8OHDio2N1fDhw497e1Wcb1FRkZ555hk1bdpUf/3rXzVs2DC99957Wr16dbWfX2WcbAZHjhxRenq6br/9dk2ZMkWPPvqoDhw4oKlTp/qsV5tnUNGGDRv0zTffKCIiwtxWozNwAsjjjz/uzJw50/t1WVmZ88ADDzgLFy7030FVk/z8fGfQoEHOzp07HcdxnMLCQmfIkCHOp59+6l0nIyPDGTRokLN7927HcRxn8+bNzuDBg53c3FzvOitXrnTuvvtu5+jRozV6/GejuLjYGTNmjPPFF184Tz31lDNr1izHcerGDObMmeNMmDDhhLd7PB5n5MiRzgcffOBdVlhY6CQkJDgpKSmO4zjO/v37nUGDBjl79uzxrrNlyxZn8ODBzsGDB6vv4KvIc88958yYMcNn2fPPP++89NJLjuPU/hkMGjTIWb9+vffrqjrflStXOvfee6/P34M5c+Y4Y8eOreYzOn3HzuB4vvnmG2fQoEFOdna24zh1ZwYHDx50HnzwQWffvn3OqFGjnCVLlnhvq+kZBMwVhNLSUqWlpSkuLs67zO12Ky4uTl9//bUfj6x6FBUVSZIaNmwoSUpLS1NZWZnP+bdo0UJNmzb1nv/XX3+tmJgYn8vtnTp1UnFxsfbv319zB3+WZs6cqc6dO6tDhw4+y+vCDD7//HO1adNG06ZN04gRI/R///d/PmWflZWlvLw8n9mEhYXpkksu8ZnBeeed531KQpLi4uLkcrm0Z8+emjuZM9S2bVvt2LFDBw4ckCTt3btXu3fvVufOnSXVjRlUVFXn+/XXX6t9+/Y+P8q3Y8eOOnDggA4dOlRDZ1N1ioqK5HK5FBYWJqluzMDj8eiVV15R//791apVK3N7Tc8gYF6DUFBQII/H4/PAL0nh4eHeB5LawuPx6M0331S7du0UExMjScrLy1NwcLDPpWZJOv/885WXl+dd59j5nH/++d7bzgXr1q1Tenq6nnvuOXNbXZhBVlaWVq1apb59++rWW2/Vt99+q1mzZik4OFi9evXynkP5OZU7dgaNGzf2uT0oKEgNGzY8J2Zwyy23qLi4WI888ojcbrc8Ho+GDBmia6+9VpLqxAwqqqrzzcvLU1RUlM865X9X8vLyvN+MnAuOHDmid955R927d/cGQl2YwQcffKCgoCDdfPPNx729pmcQMIFQlyQlJWn//v2aNGmSvw+lRuXk5OjNN9/U+PHjVb9+fX8fjl94PB5dfPHFSkhIkCRddNFF2rdvn1atWqVevXr59+BqyKeffqqUlBSNGTNGrVq10t69e/Xmm28qIiKizswAJ1ZaWqrp06dLkkaMGOHno6k5aWlpWrZsmaZMmeJ9sa6/BUwgNG7cWG6329T/8b5jPJclJSVp8+bNmjhxopo0aeJdHh4ertLSUhUWFvp8B52fn+89//DwcHP5tPwFnOfCjNLS0pSfn69x48Z5l3k8Hu3atUsrVqzQk08+WetnEBERoZYtW/osa9mypdavXy/pf+eQn5/v8wKl/Px8xcbGetcpKCjw2UZZWZkOHTp0Tsxgzpw5GjBggLp37y5JiomJUXZ2thYtWqRevXrViRlUVFXnGx4eftzHz4r7CHTlcZCTk6PExETv1QOp9s9g165dKigo0KhRo7zLPB6PZs+erWXLlum1116r8RkEzGsQgoOD1aZNG+3YscO7zOPxaMeOHWrbtq0fj6xqOI6jpKQkbdiwQYmJieYSUJs2bRQUFKTt27d7lx04cEA5OTne82/btq327dvn866Obdu2KTQ01PyjE4ji4uL0wgsvaOrUqd5fF198sXr06OH9fW2fQbt27cxTZgcOHFCzZs0kSVFRUQoPD/eZQVFRkfbs2eMzg8LCQqWlpXnX2bFjhxzHOSfeEnz48GG53b4PPW632/tz7uvCDCqqqvNt27atdu3apdLSUu8627Zt04UXXhjwl9al/8VBZmamJkyYoEaNGvncXttncN111+n555/3eXyMiIhQ//799eSTT0qq+RkETCBIUr9+/fTxxx9rzZo1ysjI0MyZM3X48OFacdkxKSlJa9eu1dixYxUaGqq8vDzl5eV538YUFhamG264QbNnz9aOHTuUlpamGTNmqG3btt4HiY4dO6ply5Z69dVXtXfvXm3dulXvvvuu+vTpc078lLPQ0FDFxMT4/GrQoIEaNWqkmJiYOjGDvn376ptvvtGCBQuUmZmplJQUffzxx+rTp48kyeVyKT4+XgsWLNDnn3+uffv26dVXX1VERIS6du0q6ZcrDp06ddLrr7+uPXv26KuvvtIbb7yha665xuc944Hqyiuv1IIFC7R582ZlZWVpw4YNWrJkiff8auMMSkpKtHfvXu3du1fSL69F2bt3r3JycqrsfHv06KHg4GD94x//0P79+5Wamqrly5erX79+/jptHyebQWlpqaZNm6a0tDT98Y9/lMfj8T5Glv9DV9tnUP44WPFXcHCwwsPDvZ+XU9MzCLif5rhixQotXrxYeXl5io2N1X333adLL73U34d11gYPHnzc5aNGjfIGUPmHBK1bt06lpaXH/ZCg7OxszZw5Uzt37lSDBg3Us2dPDR069Jz5kKBjPf3004qNjTUflFSbZ7Bp0yYlJycrMzNTUVFR6tu3r3772996b3f+/4fmrF69WkVFRbrssss0fPhwnw/VOnTokJKSknw+LOX+++8PyA8JOlZxcbHmzp2rDRs2KD8/X5GRkerevbsGDhzofeV1bZvBzp07NXHiRLO8Z8+eGj16dJWdb8UPyGnUqJFuuukm3XLLLTVxiqd0shkMGjRIDz300HHv99RTT+mKK66QVLtnMHr0aLN89OjRio+PNx+UVFMzCLhAAAAA/hdQTzEAAIDAQCAAAACDQAAAAAaBAAAADAIBAAAYBAIAADAIBAAAYBAIAADAIBAAAIARMD/NEaitsrKy9OGHH2rbtm06ePCgJKlZs2a64oordOONN6p169Z+PsKqN23aNH322Wfq37+/hg0b5u/DAXAG+KhloBpt2rRJL774otxut6699lq1bt1aLpdLBw4c0Pr165WTk6NXX33V+9Mca4OioiKNHDlS4eHh8ng8mjFjRsD8fHsAlccVBKCaZGZm6sUXX1TTpk2VmJioiIgIn9uHDh2qlStXVsk/niUlJQHzQ4rWr18vj8ejP/zhD5o0aZJ27dqlyy+//JT3C6RzAEAgANVm8eLFOnz4sEaNGmXiQJKCgoIUHx/v/fq7777TkiVLtGvXLuXm5iosLEydO3fWXXfdpUaNGnnXmzdvnubPn69p06bp/fff19atW9WsWTNNnTq10tuQfvnJcm+//bb279+vyMhI9e/fX7m5uZo/f77mzZvns+5///tfLV26VBkZGapfv746duyoYcOGqWnTpua8UlJS1KFDB/3qV79SixYttHbtWhMIa9as0YwZM/T0008rNTVVn332mcrKyjRr1ixJ0pYtW7Rw4UKlp6fL5XKpffv2GjZsmFq1anXa8wJwZggEoJps2rRJ0dHRlf5x5du2bVNWVpZ69eql8PBwZWRkaPXq1crIyNDkyZPNlYZp06YpOjpad955p8qfKazsNtLT0/Xss88qPDxcgwYNksfj0fz589W4cWNzXAsWLNDcuXN19dVXq3fv3iooKNDy5cv11FNPaerUqTrvvPO86/7000/asWOH90fXdu/eXUuXLtXw4cO9P8q5opkzZ6px48YaOHCgSkpKJP0SI6+99po6duyooUOH6vDhw/roo4+UmJioKVOmKCoq6ozmBeD0EAhANSgqKlJubq66du1qbissLFRZWZn365CQENWvX199+vTR73//e591L730Ur300kv66quv1L59e5/bWrdurbFjx/osq+w25s2bJ7fbrb/85S+KjIyUJF1zzTV65JFHfO6bnZ2tefPm6Y477tBtt93mXd6tWzeNGzdOK1eu9Fm+bt061atXz3ve3bt317x587R582Z169bNzKJhw4ZKTEyU2/3LG6pKSko0a9Ys3XDDDXrwwQe96/Xs2VMPP/ywFi5c6F1+uvMCcHp4myNQDYqLiyXpuM+pP/300xoxYoT314oVKyRJ9evX965z5MgRFRQUeK8+pKenm+3ceOONZllltuHxeLR9+3Z17drVGweSFB0drU6dOvlsb/369XIcR9dcc40KCgq8v8LDwxUdHa2dO3f6rJ+SkqIuXbooNDRUktS8eXO1adNGKSkpx51T7969vXEg/XJVoLCwUN27d/fZn9vt1qWXXuqzv9OdF4DTwxUEoBqU/wNZftm8ogceeEDFxcXKz8/XK6+84l1+6NAhvffee0pNTVV+fr7PfYqKisx2yi+1V1SZbeTn5+vIkSOKjo429z92WWZmphzH0ZgxY457nhWfNsjIyFB6erquu+46ZWZmepdffvnlWrlypYqKihQWFnbSc/jhhx8kSZMmTTru/srnWtlzBXDmCASgGoSFhSkiIkL79+83t5V/l5uVleWzfPr06dq9e7f69++v2NhYhYSEyOPx6Nlnn5XH4zHbqfgd9Jlu41Q8Ho9cLpcef/xxn+/0y1W8QrJ27VpJ0ltvvaW33nrLrLt+/Xpdf/31Jz2H8tdSPPTQQwoPDzfbCAoK8v6+qs8VgC8CAagmnTt31ieffKI9e/bokksuOem6hw4d0vbt2zV48GANHDjQu7z8O+rKqOw2zj//fNWrV8/nu/xyxy6Ljo6W4ziKiorShRdeeMJ9O46jlJQUXXHFFerTp4+5/f3331dKSooJhGNdcMEF3mPs0KHDCderinkBODlegwBUkwEDBqhBgwb6+9//rry8vJOuW/7d+bGfW7Z06dJK76+y23C73YqLi9PGjRv1008/eZdnZmZq69atPut269ZNbrdb8+fPN9t1HEc///yzJGn37t3Kzs7W9ddfr9/85jfm19VXX60dO3b47O94OnbsqNDQUC1cuFClpaXm9oKCgtM6VwBnjisIQDVp3ry5xowZo5deekkPP/ywevToodjYWDmOo6ysLKWkpMjlcqlJkyYKCwtT+/bttXjxYpWVlSkyMlJffPGFeRriZE5nG4MHD9b48eM1YcIE/e53v5PH49GKFSvUqlUr7d2717tedHS0hgwZouTkZGVnZ6tr164KCQlRVlaWNm7cqN69e6t///5au3at3G63unTpctxju+qqq/Tuu+8qNTVV/fr1O+k5jBw5Uq+88orGjRun7t27q3HjxsrJydHmzZvVrl07DR8+vErmBeDkCASgGnXt2lUvvPCClixZom3btuk///mPXC6XmjVrpi5duujGG29UbGysJGns2LF64403tHLlSjmOow4dOuiJJ57webvfqVR2G23atNETTzyht99+W3PnzlWTJk10xx13KCMjQ99//73PurfccouaN2+upUuX6r333pMkNW3aVB06dNBVV12l0tJSffbZZ2rXrp0aNmx43OOKiYlRVFSU1q5de9JAkKQePXooIiJCixYt0uLFi3X06FFFRkaqffv2Pk9RVMW8AJwYP4sBgNfUqVOVkZGhl19+2d+HAsDPeA0CUEcdOXLE5+sffvhBW7ZsqdTPTQBQ+/EUA1BHPfTQQ+rVq5eioqKUk5Ojjz76SMHBwRowYIC/Dw1AACAQgDqqU6dOWrdunfLy8hQcHKy2bdvqzjvvVPPmzf19aAACAK9BAAAABq9BAAAABoEAAAAMAgEAABgEAgAAMAgEAABgEAgAAMAgEAAAgEEgAAAA4/8Bqyqmd+M9lCUAAAAASUVORK5CYII=",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.boxplot(x = 'GarageArea', data = df, color = 'green')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 144,
   "metadata": {},
   "outputs": [],
   "source": [
    "Q1 = df['GarageArea'].quantile(0.25)\n",
    "Q3 = df['GarageArea'].quantile(0.75)\n",
    "IQR = Q3 - Q1\n",
    "\n",
    "filter = (df['GarageArea'] >= Q1 - 1.5 * IQR) & (df['GarageArea'] <= Q3 + 1.5 *IQR)\n",
    "df = df.loc[filter]  "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 145,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.boxplot(x = 'SalePrice', data = df, color = 'green')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 146,
   "metadata": {},
   "outputs": [],
   "source": [
    "Q1 = df['SalePrice'].quantile(0.25)\n",
    "Q3 = df['SalePrice'].quantile(0.75)\n",
    "IQR = Q3 - Q1\n",
    "\n",
    "filter = (df['SalePrice'] >= Q1 - 1.5 * IQR) & (df['SalePrice'] <= Q3 + 1.5 *IQR)\n",
    "df = df.loc[filter]  "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 1 :\n",
    "#### Null Hypothesis (H0):  \n",
    "over all data quality is normally distributed. \n",
    "#### Alternative Hypothesis (H1):  \n",
    "over all data quality is not normally distributed. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 68,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Test Statistic: 0.9480094909667969\n",
      "P-value: 2.688552318270029e-22\n"
     ]
    }
   ],
   "source": [
    "from scipy.stats import shapiro\n",
    "\n",
    "statistic, p_value = shapiro(df['OverallQual'])\n",
    "\n",
    "print(f\"Test Statistic: {statistic}\")\n",
    "print(f\"P-value: {p_value}\")\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "over all quality of the data seems to be normally distributed"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 2 :\n",
    "#### Null Hypothesis (H0):  \n",
    "The mean lot area of 400 newest built houses is equal to the mean lot area of 400 oldest built houses.  \n",
    "#### Alternative Hypothesis (H1):  \n",
    "The mean lot area of 400 newest built houses is not equal to the mean lot area of 400 oldest built houses."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 58,
   "metadata": {},
   "outputs": [],
   "source": [
    "top_400_samples = df.nlargest(400, 'YearBuilt')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 147,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 800x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(8, 6))\n",
    "sns.histplot(data=top_400_samples, x='LotArea', bins=30, kde=True)\n",
    "plt.ylabel('Frequency')\n",
    "plt.title('Distribution of top_400_samples')\n",
    "plt.xticks(rotation=45)\n",
    "plt.show()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 60,
   "metadata": {},
   "outputs": [],
   "source": [
    "bottom_400_samples = df.nsmallest(400, 'LotArea')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 148,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 800x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(8, 6))\n",
    "sns.histplot(data=bottom_400_samples, x='LotArea', bins=30, kde=True)\n",
    "plt.ylabel('Frequency')\n",
    "plt.title('Distribution of bottom_400_samples')\n",
    "plt.xticks(rotation=45)\n",
    "plt.show()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 65,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "T-statistic value:  0.7711515369641121\n",
      "P-Value:  0.4408453843384621\n"
     ]
    }
   ],
   "source": [
    "t_stat, p_value = ttest_ind(top_400_samples['LotArea'], bottom_400_samples['LotArea'])\n",
    "print(\"T-statistic value: \", t_stat)\n",
    "print(\"P-Value: \", p_value)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "p-value of 0.44 indicates we do not have enogh evidence to reject the null hypothesis"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 3 :\n",
    "#### Null Hypothesis (H0):  \n",
    "street ( what kind of road is from street to the property) is not correlated with zoning classification of the sale.\n",
    "#### Alternative Hypothesis (H1):  \n",
    "street ( what kind of road is from street to the property) is correlated with zoning classification of the sale."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 82,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Chi-Square Statistic: 94.74158356813642\n",
      "P-value: 1.293331100878627e-19\n",
      "Degrees of Freedom: 4\n",
      "Expected Frequencies:\n",
      "[[4.10958904e-02 9.95890411e+00]\n",
      " [2.67123288e-01 6.47328767e+01]\n",
      " [6.57534247e-02 1.59342466e+01]\n",
      " [4.73013699e+00 1.14626986e+03]\n",
      " [8.95890411e-01 2.17104110e+02]]\n"
     ]
    }
   ],
   "source": [
    "from scipy.stats import chi2_contingency\n",
    "\n",
    "street = df['Street']\n",
    "ms = df['MSZoning']\n",
    "\n",
    "contingency_table = pd.crosstab(ms, street)\n",
    "chi2_stat, p_val, dof, expected = chi2_contingency(contingency_table)\n",
    "\n",
    "print(f\"Chi-Square Statistic: {chi2_stat}\")\n",
    "print(f\"P-value: {p_val}\")\n",
    "print(f\"Degrees of Freedom: {dof}\")\n",
    "print(\"Expected Frequencies:\")\n",
    "print(expected)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "given the above ressult we can strongly reject the null hypothesis."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 87,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Figure size 800x600 with 0 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 3 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "from statsmodels.graphics.mosaicplot import mosaic\n",
    "\n",
    "plt.figure(figsize=(8, 6))\n",
    "mosaic(contingency_table.stack(), gap=0.001, title='Mosaic Plot')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 4 :\n",
    "#### Null Hypothesis (H0):  \n",
    "average garage are is equal to 500.\n",
    "#### Alternative Hypothesis (H1):  \n",
    "average garage are is not equal to 500."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 103,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 800x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(8, 6))\n",
    "sns.histplot(data=top_400_samples, x='GarageArea', bins=30, kde=True)\n",
    "plt.ylabel('Frequency')\n",
    "plt.title('Distribution of GarageArea')\n",
    "plt.xticks(rotation=45)\n",
    "plt.show()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 108,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "T-Statistic value: -4.828831326245644\n",
      "P-Value: 1.5177820717041082e-06\n"
     ]
    }
   ],
   "source": [
    "from scipy.stats import ttest_1samp\n",
    "import numpy as np\n",
    "garage_area = df['GarageArea']\n",
    "null_hypothesis_mean = 500\n",
    "t_statistic, p_value = ttest_1samp(garage_area, null_hypothesis_mean)\n",
    "print(f\"T-Statistic value: {t_statistic}\")\n",
    "print(f\"P-Value: {p_value}\")\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "given the result , the null hypothesis is strongly rejected."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Null Hypothesis (H0):\n",
    "There is no significant difference in the mean sale prices across different categories of foundation types.\n",
    "\n",
    "#### Alternative Hypothesis (H1):\n",
    "There is a significant difference in the mean sale prices across different categories of foundation types."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 109,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "F-Statistic: 100.25385058740888\n",
      "P-value: 5.791895002232234e-91\n"
     ]
    }
   ],
   "source": [
    "from scipy.stats import f_oneway\n",
    "\n",
    "grouped_data = []\n",
    "\n",
    "for category in df['Foundation'].unique():\n",
    "    group = df[df['Foundation'] == category]['SalePrice']\n",
    "    grouped_data.append(group)\n",
    "\n",
    "\n",
    "f_statistic, p_value = f_oneway(*grouped_data)\n",
    "\n",
    "print(f\"F-Statistic: {f_statistic}\")\n",
    "print(f\"P-value: {p_value}\")\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "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",
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