D - Codes_for_Test_Dataset_Analysis.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "ca9a1f5d",
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import matplotlib.pyplot as plt \n",
    "import numpy as np \n",
    "%matplotlib inline\n",
    "import seaborn as sns\n",
    "from sklearn.model_selection import train_test_split\n",
    "from sklearn import preprocessing\n",
    "from sklearn.preprocessing import StandardScaler\n",
    "from sklearn.linear_model import LogisticRegression\n",
    "from sklearn.metrics import roc_curve, roc_auc_score, mean_squared_error, r2_score, accuracy_score, f1_score\n",
    "from sklearn.tree import DecisionTreeClassifier\n",
    "from sklearn.ensemble import RandomForestClassifier\n",
    "from sklearn.naive_bayes import GaussianNB\n",
    "from sklearn import svm, datasets\n",
    "from sklearn.ensemble import GradientBoostingRegressor, GradientBoostingClassifier\n",
    "from sklearn.neighbors import KNeighborsClassifier\n",
    "import xgboost as xgb\n",
    "import lightgbm as lgb\n",
    "from keras.models import Sequential\n",
    "from keras.layers import Dense\n",
    "from sklearn.experimental import enable_hist_gradient_boosting\n",
    "from sklearn.ensemble import HistGradientBoostingClassifier\n",
    "from catboost import CatBoostClassifier, Pool\n",
    "import warnings\n",
    "warnings.filterwarnings(\"ignore\")\n",
    "\n",
    "#This will help us to display all the columns & rows of our data\n",
    "pd.pandas.set_option('display.max_columns',None)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "2cdc241e",
   "metadata": {},
   "outputs": [],
   "source": [
    "df = pd.read_csv('test1.csv')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "fd474d58",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(1459, 80)"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#Prints the shape of dataset\n",
    "df.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "dafa965d",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 1459 entries, 0 to 1458\n",
      "Data columns (total 80 columns):\n",
      " #   Column         Non-Null Count  Dtype  \n",
      "---  ------         --------------  -----  \n",
      " 0   Id             1459 non-null   int64  \n",
      " 1   MSSubClass     1459 non-null   int64  \n",
      " 2   MSZoning       1455 non-null   object \n",
      " 3   LotFrontage    1232 non-null   float64\n",
      " 4   LotArea        1459 non-null   int64  \n",
      " 5   Street         1459 non-null   object \n",
      " 6   Alley          107 non-null    object \n",
      " 7   LotShape       1459 non-null   object \n",
      " 8   LandContour    1459 non-null   object \n",
      " 9   Utilities      1457 non-null   object \n",
      " 10  LotConfig      1459 non-null   object \n",
      " 11  LandSlope      1459 non-null   object \n",
      " 12  Neighborhood   1459 non-null   object \n",
      " 13  Condition1     1459 non-null   object \n",
      " 14  Condition2     1459 non-null   object \n",
      " 15  BldgType       1459 non-null   object \n",
      " 16  HouseStyle     1459 non-null   object \n",
      " 17  OverallQual    1459 non-null   int64  \n",
      " 18  OverallCond    1459 non-null   int64  \n",
      " 19  YearBuilt      1459 non-null   int64  \n",
      " 20  YearRemodAdd   1459 non-null   int64  \n",
      " 21  RoofStyle      1459 non-null   object \n",
      " 22  RoofMatl       1459 non-null   object \n",
      " 23  Exterior1st    1458 non-null   object \n",
      " 24  Exterior2nd    1458 non-null   object \n",
      " 25  MasVnrType     1443 non-null   object \n",
      " 26  MasVnrArea     1444 non-null   float64\n",
      " 27  ExterQual      1459 non-null   object \n",
      " 28  ExterCond      1459 non-null   object \n",
      " 29  Foundation     1459 non-null   object \n",
      " 30  BsmtQual       1415 non-null   object \n",
      " 31  BsmtCond       1414 non-null   object \n",
      " 32  BsmtExposure   1415 non-null   object \n",
      " 33  BsmtFinType1   1417 non-null   object \n",
      " 34  BsmtFinSF1     1458 non-null   float64\n",
      " 35  BsmtFinType2   1417 non-null   object \n",
      " 36  BsmtFinSF2     1458 non-null   float64\n",
      " 37  BsmtUnfSF      1458 non-null   float64\n",
      " 38  TotalBsmtSF    1458 non-null   float64\n",
      " 39  Heating        1459 non-null   object \n",
      " 40  HeatingQC      1459 non-null   object \n",
      " 41  CentralAir     1459 non-null   object \n",
      " 42  Electrical     1459 non-null   object \n",
      " 43  1stFlrSF       1459 non-null   int64  \n",
      " 44  2ndFlrSF       1459 non-null   int64  \n",
      " 45  LowQualFinSF   1459 non-null   int64  \n",
      " 46  GrLivArea      1459 non-null   int64  \n",
      " 47  BsmtFullBath   1457 non-null   float64\n",
      " 48  BsmtHalfBath   1457 non-null   float64\n",
      " 49  FullBath       1459 non-null   int64  \n",
      " 50  HalfBath       1459 non-null   int64  \n",
      " 51  BedroomAbvGr   1459 non-null   int64  \n",
      " 52  KitchenAbvGr   1459 non-null   int64  \n",
      " 53  KitchenQual    1458 non-null   object \n",
      " 54  TotRmsAbvGrd   1459 non-null   int64  \n",
      " 55  Functional     1457 non-null   object \n",
      " 56  Fireplaces     1459 non-null   int64  \n",
      " 57  FireplaceQu    729 non-null    object \n",
      " 58  GarageType     1383 non-null   object \n",
      " 59  GarageYrBlt    1381 non-null   float64\n",
      " 60  GarageFinish   1381 non-null   object \n",
      " 61  GarageCars     1458 non-null   float64\n",
      " 62  GarageArea     1458 non-null   float64\n",
      " 63  GarageQual     1381 non-null   object \n",
      " 64  GarageCond     1381 non-null   object \n",
      " 65  PavedDrive     1459 non-null   object \n",
      " 66  WoodDeckSF     1459 non-null   int64  \n",
      " 67  OpenPorchSF    1459 non-null   int64  \n",
      " 68  EnclosedPorch  1459 non-null   int64  \n",
      " 69  3SsnPorch      1459 non-null   int64  \n",
      " 70  ScreenPorch    1459 non-null   int64  \n",
      " 71  PoolArea       1459 non-null   int64  \n",
      " 72  PoolQC         3 non-null      object \n",
      " 73  Fence          290 non-null    object \n",
      " 74  MiscFeature    51 non-null     object \n",
      " 75  MiscVal        1459 non-null   int64  \n",
      " 76  MoSold         1459 non-null   int64  \n",
      " 77  YrSold         1459 non-null   int64  \n",
      " 78  SaleType       1458 non-null   object \n",
      " 79  SaleCondition  1459 non-null   object \n",
      "dtypes: float64(11), int64(26), object(43)\n",
      "memory usage: 912.0+ KB\n"
     ]
    }
   ],
   "source": [
    "df.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "3d47effd",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Id</th>\n",
       "      <th>MSSubClass</th>\n",
       "      <th>LotFrontage</th>\n",
       "      <th>LotArea</th>\n",
       "      <th>OverallQual</th>\n",
       "      <th>OverallCond</th>\n",
       "      <th>YearBuilt</th>\n",
       "      <th>YearRemodAdd</th>\n",
       "      <th>MasVnrArea</th>\n",
       "      <th>BsmtFinSF1</th>\n",
       "      <th>BsmtFinSF2</th>\n",
       "      <th>BsmtUnfSF</th>\n",
       "      <th>TotalBsmtSF</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>TotRmsAbvGrd</th>\n",
       "      <th>Fireplaces</th>\n",
       "      <th>GarageYrBlt</th>\n",
       "      <th>GarageCars</th>\n",
       "      <th>GarageArea</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>MiscVal</th>\n",
       "      <th>MoSold</th>\n",
       "      <th>YrSold</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>1459.000000</td>\n",
       "      <td>1459.000000</td>\n",
       "      <td>1232.000000</td>\n",
       "      <td>1459.000000</td>\n",
       "      <td>1459.000000</td>\n",
       "      <td>1459.000000</td>\n",
       "      <td>1459.000000</td>\n",
       "      <td>1459.000000</td>\n",
       "      <td>1444.000000</td>\n",
       "      <td>1458.000000</td>\n",
       "      <td>1458.000000</td>\n",
       "      <td>1458.000000</td>\n",
       "      <td>1458.000000</td>\n",
       "      <td>1459.000000</td>\n",
       "      <td>1459.000000</td>\n",
       "      <td>1459.000000</td>\n",
       "      <td>1459.000000</td>\n",
       "      <td>1457.000000</td>\n",
       "      <td>1457.000000</td>\n",
       "      <td>1459.000000</td>\n",
       "      <td>1459.000000</td>\n",
       "      <td>1459.000000</td>\n",
       "      <td>1459.000000</td>\n",
       "      <td>1459.000000</td>\n",
       "      <td>1459.00000</td>\n",
       "      <td>1381.000000</td>\n",
       "      <td>1458.000000</td>\n",
       "      <td>1458.000000</td>\n",
       "      <td>1459.000000</td>\n",
       "      <td>1459.000000</td>\n",
       "      <td>1459.000000</td>\n",
       "      <td>1459.000000</td>\n",
       "      <td>1459.000000</td>\n",
       "      <td>1459.000000</td>\n",
       "      <td>1459.000000</td>\n",
       "      <td>1459.000000</td>\n",
       "      <td>1459.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>2190.000000</td>\n",
       "      <td>57.378341</td>\n",
       "      <td>68.580357</td>\n",
       "      <td>9819.161069</td>\n",
       "      <td>6.078821</td>\n",
       "      <td>5.553804</td>\n",
       "      <td>1971.357779</td>\n",
       "      <td>1983.662783</td>\n",
       "      <td>100.709141</td>\n",
       "      <td>439.203704</td>\n",
       "      <td>52.619342</td>\n",
       "      <td>554.294925</td>\n",
       "      <td>1046.117970</td>\n",
       "      <td>1156.534613</td>\n",
       "      <td>325.967786</td>\n",
       "      <td>3.543523</td>\n",
       "      <td>1486.045922</td>\n",
       "      <td>0.434454</td>\n",
       "      <td>0.065202</td>\n",
       "      <td>1.570939</td>\n",
       "      <td>0.377656</td>\n",
       "      <td>2.854010</td>\n",
       "      <td>1.042495</td>\n",
       "      <td>6.385195</td>\n",
       "      <td>0.58122</td>\n",
       "      <td>1977.721217</td>\n",
       "      <td>1.766118</td>\n",
       "      <td>472.768861</td>\n",
       "      <td>93.174777</td>\n",
       "      <td>48.313914</td>\n",
       "      <td>24.243317</td>\n",
       "      <td>1.794380</td>\n",
       "      <td>17.064428</td>\n",
       "      <td>1.744345</td>\n",
       "      <td>58.167923</td>\n",
       "      <td>6.104181</td>\n",
       "      <td>2007.769705</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>std</th>\n",
       "      <td>421.321334</td>\n",
       "      <td>42.746880</td>\n",
       "      <td>22.376841</td>\n",
       "      <td>4955.517327</td>\n",
       "      <td>1.436812</td>\n",
       "      <td>1.113740</td>\n",
       "      <td>30.390071</td>\n",
       "      <td>21.130467</td>\n",
       "      <td>177.625900</td>\n",
       "      <td>455.268042</td>\n",
       "      <td>176.753926</td>\n",
       "      <td>437.260486</td>\n",
       "      <td>442.898624</td>\n",
       "      <td>398.165820</td>\n",
       "      <td>420.610226</td>\n",
       "      <td>44.043251</td>\n",
       "      <td>485.566099</td>\n",
       "      <td>0.530648</td>\n",
       "      <td>0.252468</td>\n",
       "      <td>0.555190</td>\n",
       "      <td>0.503017</td>\n",
       "      <td>0.829788</td>\n",
       "      <td>0.208472</td>\n",
       "      <td>1.508895</td>\n",
       "      <td>0.64742</td>\n",
       "      <td>26.431175</td>\n",
       "      <td>0.775945</td>\n",
       "      <td>217.048611</td>\n",
       "      <td>127.744882</td>\n",
       "      <td>68.883364</td>\n",
       "      <td>67.227765</td>\n",
       "      <td>20.207842</td>\n",
       "      <td>56.609763</td>\n",
       "      <td>30.491646</td>\n",
       "      <td>630.806978</td>\n",
       "      <td>2.722432</td>\n",
       "      <td>1.301740</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>1461.000000</td>\n",
       "      <td>20.000000</td>\n",
       "      <td>21.000000</td>\n",
       "      <td>1470.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1879.000000</td>\n",
       "      <td>1950.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>407.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>407.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>3.000000</td>\n",
       "      <td>0.00000</td>\n",
       "      <td>1895.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>2006.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25%</th>\n",
       "      <td>1825.500000</td>\n",
       "      <td>20.000000</td>\n",
       "      <td>58.000000</td>\n",
       "      <td>7391.000000</td>\n",
       "      <td>5.000000</td>\n",
       "      <td>5.000000</td>\n",
       "      <td>1953.000000</td>\n",
       "      <td>1963.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>219.250000</td>\n",
       "      <td>784.000000</td>\n",
       "      <td>873.500000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1117.500000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>2.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>5.000000</td>\n",
       "      <td>0.00000</td>\n",
       "      <td>1959.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>318.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>4.000000</td>\n",
       "      <td>2007.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50%</th>\n",
       "      <td>2190.000000</td>\n",
       "      <td>50.000000</td>\n",
       "      <td>67.000000</td>\n",
       "      <td>9399.000000</td>\n",
       "      <td>6.000000</td>\n",
       "      <td>5.000000</td>\n",
       "      <td>1973.000000</td>\n",
       "      <td>1992.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>350.500000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>460.000000</td>\n",
       "      <td>988.000000</td>\n",
       "      <td>1079.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1432.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>2.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>3.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>6.000000</td>\n",
       "      <td>0.00000</td>\n",
       "      <td>1979.000000</td>\n",
       "      <td>2.000000</td>\n",
       "      <td>480.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>28.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>6.000000</td>\n",
       "      <td>2008.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75%</th>\n",
       "      <td>2554.500000</td>\n",
       "      <td>70.000000</td>\n",
       "      <td>80.000000</td>\n",
       "      <td>11517.500000</td>\n",
       "      <td>7.000000</td>\n",
       "      <td>6.000000</td>\n",
       "      <td>2001.000000</td>\n",
       "      <td>2004.000000</td>\n",
       "      <td>164.000000</td>\n",
       "      <td>753.500000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>797.750000</td>\n",
       "      <td>1305.000000</td>\n",
       "      <td>1382.500000</td>\n",
       "      <td>676.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1721.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>2.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>3.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>7.000000</td>\n",
       "      <td>1.00000</td>\n",
       "      <td>2002.000000</td>\n",
       "      <td>2.000000</td>\n",
       "      <td>576.000000</td>\n",
       "      <td>168.000000</td>\n",
       "      <td>72.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>8.000000</td>\n",
       "      <td>2009.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>max</th>\n",
       "      <td>2919.000000</td>\n",
       "      <td>190.000000</td>\n",
       "      <td>200.000000</td>\n",
       "      <td>56600.000000</td>\n",
       "      <td>10.000000</td>\n",
       "      <td>9.000000</td>\n",
       "      <td>2010.000000</td>\n",
       "      <td>2010.000000</td>\n",
       "      <td>1290.000000</td>\n",
       "      <td>4010.000000</td>\n",
       "      <td>1526.000000</td>\n",
       "      <td>2140.000000</td>\n",
       "      <td>5095.000000</td>\n",
       "      <td>5095.000000</td>\n",
       "      <td>1862.000000</td>\n",
       "      <td>1064.000000</td>\n",
       "      <td>5095.000000</td>\n",
       "      <td>3.000000</td>\n",
       "      <td>2.000000</td>\n",
       "      <td>4.000000</td>\n",
       "      <td>2.000000</td>\n",
       "      <td>6.000000</td>\n",
       "      <td>2.000000</td>\n",
       "      <td>15.000000</td>\n",
       "      <td>4.00000</td>\n",
       "      <td>2207.000000</td>\n",
       "      <td>5.000000</td>\n",
       "      <td>1488.000000</td>\n",
       "      <td>1424.000000</td>\n",
       "      <td>742.000000</td>\n",
       "      <td>1012.000000</td>\n",
       "      <td>360.000000</td>\n",
       "      <td>576.000000</td>\n",
       "      <td>800.000000</td>\n",
       "      <td>17000.000000</td>\n",
       "      <td>12.000000</td>\n",
       "      <td>2010.000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                Id   MSSubClass  LotFrontage       LotArea  OverallQual  \\\n",
       "count  1459.000000  1459.000000  1232.000000   1459.000000  1459.000000   \n",
       "mean   2190.000000    57.378341    68.580357   9819.161069     6.078821   \n",
       "std     421.321334    42.746880    22.376841   4955.517327     1.436812   \n",
       "min    1461.000000    20.000000    21.000000   1470.000000     1.000000   \n",
       "25%    1825.500000    20.000000    58.000000   7391.000000     5.000000   \n",
       "50%    2190.000000    50.000000    67.000000   9399.000000     6.000000   \n",
       "75%    2554.500000    70.000000    80.000000  11517.500000     7.000000   \n",
       "max    2919.000000   190.000000   200.000000  56600.000000    10.000000   \n",
       "\n",
       "       OverallCond    YearBuilt  YearRemodAdd   MasVnrArea   BsmtFinSF1  \\\n",
       "count  1459.000000  1459.000000   1459.000000  1444.000000  1458.000000   \n",
       "mean      5.553804  1971.357779   1983.662783   100.709141   439.203704   \n",
       "std       1.113740    30.390071     21.130467   177.625900   455.268042   \n",
       "min       1.000000  1879.000000   1950.000000     0.000000     0.000000   \n",
       "25%       5.000000  1953.000000   1963.000000     0.000000     0.000000   \n",
       "50%       5.000000  1973.000000   1992.000000     0.000000   350.500000   \n",
       "75%       6.000000  2001.000000   2004.000000   164.000000   753.500000   \n",
       "max       9.000000  2010.000000   2010.000000  1290.000000  4010.000000   \n",
       "\n",
       "        BsmtFinSF2    BsmtUnfSF  TotalBsmtSF     1stFlrSF     2ndFlrSF  \\\n",
       "count  1458.000000  1458.000000  1458.000000  1459.000000  1459.000000   \n",
       "mean     52.619342   554.294925  1046.117970  1156.534613   325.967786   \n",
       "std     176.753926   437.260486   442.898624   398.165820   420.610226   \n",
       "min       0.000000     0.000000     0.000000   407.000000     0.000000   \n",
       "25%       0.000000   219.250000   784.000000   873.500000     0.000000   \n",
       "50%       0.000000   460.000000   988.000000  1079.000000     0.000000   \n",
       "75%       0.000000   797.750000  1305.000000  1382.500000   676.000000   \n",
       "max    1526.000000  2140.000000  5095.000000  5095.000000  1862.000000   \n",
       "\n",
       "       LowQualFinSF    GrLivArea  BsmtFullBath  BsmtHalfBath     FullBath  \\\n",
       "count   1459.000000  1459.000000   1457.000000   1457.000000  1459.000000   \n",
       "mean       3.543523  1486.045922      0.434454      0.065202     1.570939   \n",
       "std       44.043251   485.566099      0.530648      0.252468     0.555190   \n",
       "min        0.000000   407.000000      0.000000      0.000000     0.000000   \n",
       "25%        0.000000  1117.500000      0.000000      0.000000     1.000000   \n",
       "50%        0.000000  1432.000000      0.000000      0.000000     2.000000   \n",
       "75%        0.000000  1721.000000      1.000000      0.000000     2.000000   \n",
       "max     1064.000000  5095.000000      3.000000      2.000000     4.000000   \n",
       "\n",
       "          HalfBath  BedroomAbvGr  KitchenAbvGr  TotRmsAbvGrd  Fireplaces  \\\n",
       "count  1459.000000   1459.000000   1459.000000   1459.000000  1459.00000   \n",
       "mean      0.377656      2.854010      1.042495      6.385195     0.58122   \n",
       "std       0.503017      0.829788      0.208472      1.508895     0.64742   \n",
       "min       0.000000      0.000000      0.000000      3.000000     0.00000   \n",
       "25%       0.000000      2.000000      1.000000      5.000000     0.00000   \n",
       "50%       0.000000      3.000000      1.000000      6.000000     0.00000   \n",
       "75%       1.000000      3.000000      1.000000      7.000000     1.00000   \n",
       "max       2.000000      6.000000      2.000000     15.000000     4.00000   \n",
       "\n",
       "       GarageYrBlt   GarageCars   GarageArea   WoodDeckSF  OpenPorchSF  \\\n",
       "count  1381.000000  1458.000000  1458.000000  1459.000000  1459.000000   \n",
       "mean   1977.721217     1.766118   472.768861    93.174777    48.313914   \n",
       "std      26.431175     0.775945   217.048611   127.744882    68.883364   \n",
       "min    1895.000000     0.000000     0.000000     0.000000     0.000000   \n",
       "25%    1959.000000     1.000000   318.000000     0.000000     0.000000   \n",
       "50%    1979.000000     2.000000   480.000000     0.000000    28.000000   \n",
       "75%    2002.000000     2.000000   576.000000   168.000000    72.000000   \n",
       "max    2207.000000     5.000000  1488.000000  1424.000000   742.000000   \n",
       "\n",
       "       EnclosedPorch    3SsnPorch  ScreenPorch     PoolArea       MiscVal  \\\n",
       "count    1459.000000  1459.000000  1459.000000  1459.000000   1459.000000   \n",
       "mean       24.243317     1.794380    17.064428     1.744345     58.167923   \n",
       "std        67.227765    20.207842    56.609763    30.491646    630.806978   \n",
       "min         0.000000     0.000000     0.000000     0.000000      0.000000   \n",
       "25%         0.000000     0.000000     0.000000     0.000000      0.000000   \n",
       "50%         0.000000     0.000000     0.000000     0.000000      0.000000   \n",
       "75%         0.000000     0.000000     0.000000     0.000000      0.000000   \n",
       "max      1012.000000   360.000000   576.000000   800.000000  17000.000000   \n",
       "\n",
       "            MoSold       YrSold  \n",
       "count  1459.000000  1459.000000  \n",
       "mean      6.104181  2007.769705  \n",
       "std       2.722432     1.301740  \n",
       "min       1.000000  2006.000000  \n",
       "25%       4.000000  2007.000000  \n",
       "50%       6.000000  2008.000000  \n",
       "75%       8.000000  2009.000000  \n",
       "max      12.000000  2010.000000  "
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.describe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "556a36c7",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
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       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Id</th>\n",
       "      <th>MSSubClass</th>\n",
       "      <th>MSZoning</th>\n",
       "      <th>LotFrontage</th>\n",
       "      <th>LotArea</th>\n",
       "      <th>Street</th>\n",
       "      <th>Alley</th>\n",
       "      <th>LotShape</th>\n",
       "      <th>LandContour</th>\n",
       "      <th>Utilities</th>\n",
       "      <th>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",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1461</td>\n",
       "      <td>20</td>\n",
       "      <td>RH</td>\n",
       "      <td>80.0</td>\n",
       "      <td>11622</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>NAmes</td>\n",
       "      <td>Feedr</td>\n",
       "      <td>Norm</td>\n",
       "      <td>1Fam</td>\n",
       "      <td>1Story</td>\n",
       "      <td>5</td>\n",
       "      <td>6</td>\n",
       "      <td>1961</td>\n",
       "      <td>1961</td>\n",
       "      <td>Gable</td>\n",
       "      <td>CompShg</td>\n",
       "      <td>VinylSd</td>\n",
       "      <td>VinylSd</td>\n",
       "      <td>None</td>\n",
       "      <td>0.0</td>\n",
       "      <td>TA</td>\n",
       "      <td>TA</td>\n",
       "      <td>CBlock</td>\n",
       "      <td>TA</td>\n",
       "      <td>TA</td>\n",
       "      <td>No</td>\n",
       "      <td>Rec</td>\n",
       "      <td>468.0</td>\n",
       "      <td>LwQ</td>\n",
       "      <td>144.0</td>\n",
       "      <td>270.0</td>\n",
       "      <td>882.0</td>\n",
       "      <td>GasA</td>\n",
       "      <td>TA</td>\n",
       "      <td>Y</td>\n",
       "      <td>SBrkr</td>\n",
       "      <td>896</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>896</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>TA</td>\n",
       "      <td>5</td>\n",
       "      <td>Typ</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Attchd</td>\n",
       "      <td>1961.0</td>\n",
       "      <td>Unf</td>\n",
       "      <td>1.0</td>\n",
       "      <td>730.0</td>\n",
       "      <td>TA</td>\n",
       "      <td>TA</td>\n",
       "      <td>Y</td>\n",
       "      <td>140</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>120</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>MnPrv</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "      <td>6</td>\n",
       "      <td>2010</td>\n",
       "      <td>WD</td>\n",
       "      <td>Normal</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1462</td>\n",
       "      <td>20</td>\n",
       "      <td>RL</td>\n",
       "      <td>81.0</td>\n",
       "      <td>14267</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>NAmes</td>\n",
       "      <td>Norm</td>\n",
       "      <td>Norm</td>\n",
       "      <td>1Fam</td>\n",
       "      <td>1Story</td>\n",
       "      <td>6</td>\n",
       "      <td>6</td>\n",
       "      <td>1958</td>\n",
       "      <td>1958</td>\n",
       "      <td>Hip</td>\n",
       "      <td>CompShg</td>\n",
       "      <td>Wd Sdng</td>\n",
       "      <td>Wd Sdng</td>\n",
       "      <td>BrkFace</td>\n",
       "      <td>108.0</td>\n",
       "      <td>TA</td>\n",
       "      <td>TA</td>\n",
       "      <td>CBlock</td>\n",
       "      <td>TA</td>\n",
       "      <td>TA</td>\n",
       "      <td>No</td>\n",
       "      <td>ALQ</td>\n",
       "      <td>923.0</td>\n",
       "      <td>Unf</td>\n",
       "      <td>0.0</td>\n",
       "      <td>406.0</td>\n",
       "      <td>1329.0</td>\n",
       "      <td>GasA</td>\n",
       "      <td>TA</td>\n",
       "      <td>Y</td>\n",
       "      <td>SBrkr</td>\n",
       "      <td>1329</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1329</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1</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>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Attchd</td>\n",
       "      <td>1958.0</td>\n",
       "      <td>Unf</td>\n",
       "      <td>1.0</td>\n",
       "      <td>312.0</td>\n",
       "      <td>TA</td>\n",
       "      <td>TA</td>\n",
       "      <td>Y</td>\n",
       "      <td>393</td>\n",
       "      <td>36</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>Gar2</td>\n",
       "      <td>12500</td>\n",
       "      <td>6</td>\n",
       "      <td>2010</td>\n",
       "      <td>WD</td>\n",
       "      <td>Normal</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>1463</td>\n",
       "      <td>60</td>\n",
       "      <td>RL</td>\n",
       "      <td>74.0</td>\n",
       "      <td>13830</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>Gilbert</td>\n",
       "      <td>Norm</td>\n",
       "      <td>Norm</td>\n",
       "      <td>1Fam</td>\n",
       "      <td>2Story</td>\n",
       "      <td>5</td>\n",
       "      <td>5</td>\n",
       "      <td>1997</td>\n",
       "      <td>1998</td>\n",
       "      <td>Gable</td>\n",
       "      <td>CompShg</td>\n",
       "      <td>VinylSd</td>\n",
       "      <td>VinylSd</td>\n",
       "      <td>None</td>\n",
       "      <td>0.0</td>\n",
       "      <td>TA</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>791.0</td>\n",
       "      <td>Unf</td>\n",
       "      <td>0.0</td>\n",
       "      <td>137.0</td>\n",
       "      <td>928.0</td>\n",
       "      <td>GasA</td>\n",
       "      <td>Gd</td>\n",
       "      <td>Y</td>\n",
       "      <td>SBrkr</td>\n",
       "      <td>928</td>\n",
       "      <td>701</td>\n",
       "      <td>0</td>\n",
       "      <td>1629</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2</td>\n",
       "      <td>1</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>1997.0</td>\n",
       "      <td>Fin</td>\n",
       "      <td>2.0</td>\n",
       "      <td>482.0</td>\n",
       "      <td>TA</td>\n",
       "      <td>TA</td>\n",
       "      <td>Y</td>\n",
       "      <td>212</td>\n",
       "      <td>34</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>MnPrv</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>2010</td>\n",
       "      <td>WD</td>\n",
       "      <td>Normal</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>1464</td>\n",
       "      <td>60</td>\n",
       "      <td>RL</td>\n",
       "      <td>78.0</td>\n",
       "      <td>9978</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>Gilbert</td>\n",
       "      <td>Norm</td>\n",
       "      <td>Norm</td>\n",
       "      <td>1Fam</td>\n",
       "      <td>2Story</td>\n",
       "      <td>6</td>\n",
       "      <td>6</td>\n",
       "      <td>1998</td>\n",
       "      <td>1998</td>\n",
       "      <td>Gable</td>\n",
       "      <td>CompShg</td>\n",
       "      <td>VinylSd</td>\n",
       "      <td>VinylSd</td>\n",
       "      <td>BrkFace</td>\n",
       "      <td>20.0</td>\n",
       "      <td>TA</td>\n",
       "      <td>TA</td>\n",
       "      <td>PConc</td>\n",
       "      <td>TA</td>\n",
       "      <td>TA</td>\n",
       "      <td>No</td>\n",
       "      <td>GLQ</td>\n",
       "      <td>602.0</td>\n",
       "      <td>Unf</td>\n",
       "      <td>0.0</td>\n",
       "      <td>324.0</td>\n",
       "      <td>926.0</td>\n",
       "      <td>GasA</td>\n",
       "      <td>Ex</td>\n",
       "      <td>Y</td>\n",
       "      <td>SBrkr</td>\n",
       "      <td>926</td>\n",
       "      <td>678</td>\n",
       "      <td>0</td>\n",
       "      <td>1604</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2</td>\n",
       "      <td>1</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>Attchd</td>\n",
       "      <td>1998.0</td>\n",
       "      <td>Fin</td>\n",
       "      <td>2.0</td>\n",
       "      <td>470.0</td>\n",
       "      <td>TA</td>\n",
       "      <td>TA</td>\n",
       "      <td>Y</td>\n",
       "      <td>360</td>\n",
       "      <td>36</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>6</td>\n",
       "      <td>2010</td>\n",
       "      <td>WD</td>\n",
       "      <td>Normal</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>1465</td>\n",
       "      <td>120</td>\n",
       "      <td>RL</td>\n",
       "      <td>43.0</td>\n",
       "      <td>5005</td>\n",
       "      <td>Pave</td>\n",
       "      <td>NaN</td>\n",
       "      <td>IR1</td>\n",
       "      <td>HLS</td>\n",
       "      <td>AllPub</td>\n",
       "      <td>Inside</td>\n",
       "      <td>Gtl</td>\n",
       "      <td>StoneBr</td>\n",
       "      <td>Norm</td>\n",
       "      <td>Norm</td>\n",
       "      <td>TwnhsE</td>\n",
       "      <td>1Story</td>\n",
       "      <td>8</td>\n",
       "      <td>5</td>\n",
       "      <td>1992</td>\n",
       "      <td>1992</td>\n",
       "      <td>Gable</td>\n",
       "      <td>CompShg</td>\n",
       "      <td>HdBoard</td>\n",
       "      <td>HdBoard</td>\n",
       "      <td>None</td>\n",
       "      <td>0.0</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>ALQ</td>\n",
       "      <td>263.0</td>\n",
       "      <td>Unf</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1017.0</td>\n",
       "      <td>1280.0</td>\n",
       "      <td>GasA</td>\n",
       "      <td>Ex</td>\n",
       "      <td>Y</td>\n",
       "      <td>SBrkr</td>\n",
       "      <td>1280</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1280</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>Gd</td>\n",
       "      <td>5</td>\n",
       "      <td>Typ</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Attchd</td>\n",
       "      <td>1992.0</td>\n",
       "      <td>RFn</td>\n",
       "      <td>2.0</td>\n",
       "      <td>506.0</td>\n",
       "      <td>TA</td>\n",
       "      <td>TA</td>\n",
       "      <td>Y</td>\n",
       "      <td>0</td>\n",
       "      <td>82</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>144</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>2010</td>\n",
       "      <td>WD</td>\n",
       "      <td>Normal</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "     Id  MSSubClass MSZoning  LotFrontage  LotArea Street Alley LotShape  \\\n",
       "0  1461          20       RH         80.0    11622   Pave   NaN      Reg   \n",
       "1  1462          20       RL         81.0    14267   Pave   NaN      IR1   \n",
       "2  1463          60       RL         74.0    13830   Pave   NaN      IR1   \n",
       "3  1464          60       RL         78.0     9978   Pave   NaN      IR1   \n",
       "4  1465         120       RL         43.0     5005   Pave   NaN      IR1   \n",
       "\n",
       "  LandContour Utilities LotConfig LandSlope Neighborhood Condition1  \\\n",
       "0         Lvl    AllPub    Inside       Gtl        NAmes      Feedr   \n",
       "1         Lvl    AllPub    Corner       Gtl        NAmes       Norm   \n",
       "2         Lvl    AllPub    Inside       Gtl      Gilbert       Norm   \n",
       "3         Lvl    AllPub    Inside       Gtl      Gilbert       Norm   \n",
       "4         HLS    AllPub    Inside       Gtl      StoneBr       Norm   \n",
       "\n",
       "  Condition2 BldgType HouseStyle  OverallQual  OverallCond  YearBuilt  \\\n",
       "0       Norm     1Fam     1Story            5            6       1961   \n",
       "1       Norm     1Fam     1Story            6            6       1958   \n",
       "2       Norm     1Fam     2Story            5            5       1997   \n",
       "3       Norm     1Fam     2Story            6            6       1998   \n",
       "4       Norm   TwnhsE     1Story            8            5       1992   \n",
       "\n",
       "   YearRemodAdd RoofStyle RoofMatl Exterior1st Exterior2nd MasVnrType  \\\n",
       "0          1961     Gable  CompShg     VinylSd     VinylSd       None   \n",
       "1          1958       Hip  CompShg     Wd Sdng     Wd Sdng    BrkFace   \n",
       "2          1998     Gable  CompShg     VinylSd     VinylSd       None   \n",
       "3          1998     Gable  CompShg     VinylSd     VinylSd    BrkFace   \n",
       "4          1992     Gable  CompShg     HdBoard     HdBoard       None   \n",
       "\n",
       "   MasVnrArea ExterQual ExterCond Foundation BsmtQual BsmtCond BsmtExposure  \\\n",
       "0         0.0        TA        TA     CBlock       TA       TA           No   \n",
       "1       108.0        TA        TA     CBlock       TA       TA           No   \n",
       "2         0.0        TA        TA      PConc       Gd       TA           No   \n",
       "3        20.0        TA        TA      PConc       TA       TA           No   \n",
       "4         0.0        Gd        TA      PConc       Gd       TA           No   \n",
       "\n",
       "  BsmtFinType1  BsmtFinSF1 BsmtFinType2  BsmtFinSF2  BsmtUnfSF  TotalBsmtSF  \\\n",
       "0          Rec       468.0          LwQ       144.0      270.0        882.0   \n",
       "1          ALQ       923.0          Unf         0.0      406.0       1329.0   \n",
       "2          GLQ       791.0          Unf         0.0      137.0        928.0   \n",
       "3          GLQ       602.0          Unf         0.0      324.0        926.0   \n",
       "4          ALQ       263.0          Unf         0.0     1017.0       1280.0   \n",
       "\n",
       "  Heating HeatingQC CentralAir Electrical  1stFlrSF  2ndFlrSF  LowQualFinSF  \\\n",
       "0    GasA        TA          Y      SBrkr       896         0             0   \n",
       "1    GasA        TA          Y      SBrkr      1329         0             0   \n",
       "2    GasA        Gd          Y      SBrkr       928       701             0   \n",
       "3    GasA        Ex          Y      SBrkr       926       678             0   \n",
       "4    GasA        Ex          Y      SBrkr      1280         0             0   \n",
       "\n",
       "   GrLivArea  BsmtFullBath  BsmtHalfBath  FullBath  HalfBath  BedroomAbvGr  \\\n",
       "0        896           0.0           0.0         1         0             2   \n",
       "1       1329           0.0           0.0         1         1             3   \n",
       "2       1629           0.0           0.0         2         1             3   \n",
       "3       1604           0.0           0.0         2         1             3   \n",
       "4       1280           0.0           0.0         2         0             2   \n",
       "\n",
       "   KitchenAbvGr KitchenQual  TotRmsAbvGrd Functional  Fireplaces FireplaceQu  \\\n",
       "0             1          TA             5        Typ           0         NaN   \n",
       "1             1          Gd             6        Typ           0         NaN   \n",
       "2             1          TA             6        Typ           1          TA   \n",
       "3             1          Gd             7        Typ           1          Gd   \n",
       "4             1          Gd             5        Typ           0         NaN   \n",
       "\n",
       "  GarageType  GarageYrBlt GarageFinish  GarageCars  GarageArea GarageQual  \\\n",
       "0     Attchd       1961.0          Unf         1.0       730.0         TA   \n",
       "1     Attchd       1958.0          Unf         1.0       312.0         TA   \n",
       "2     Attchd       1997.0          Fin         2.0       482.0         TA   \n",
       "3     Attchd       1998.0          Fin         2.0       470.0         TA   \n",
       "4     Attchd       1992.0          RFn         2.0       506.0         TA   \n",
       "\n",
       "  GarageCond PavedDrive  WoodDeckSF  OpenPorchSF  EnclosedPorch  3SsnPorch  \\\n",
       "0         TA          Y         140            0              0          0   \n",
       "1         TA          Y         393           36              0          0   \n",
       "2         TA          Y         212           34              0          0   \n",
       "3         TA          Y         360           36              0          0   \n",
       "4         TA          Y           0           82              0          0   \n",
       "\n",
       "   ScreenPorch  PoolArea PoolQC  Fence MiscFeature  MiscVal  MoSold  YrSold  \\\n",
       "0          120         0    NaN  MnPrv         NaN        0       6    2010   \n",
       "1            0         0    NaN    NaN        Gar2    12500       6    2010   \n",
       "2            0         0    NaN  MnPrv         NaN        0       3    2010   \n",
       "3            0         0    NaN    NaN         NaN        0       6    2010   \n",
       "4          144         0    NaN    NaN         NaN        0       1    2010   \n",
       "\n",
       "  SaleType SaleCondition  \n",
       "0       WD        Normal  \n",
       "1       WD        Normal  \n",
       "2       WD        Normal  \n",
       "3       WD        Normal  \n",
       "4       WD        Normal  "
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.head(5)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "faead6d5",
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Id                  0\n",
       "MSSubClass          0\n",
       "MSZoning            4\n",
       "LotFrontage       227\n",
       "LotArea             0\n",
       "Street              0\n",
       "Alley            1352\n",
       "LotShape            0\n",
       "LandContour         0\n",
       "Utilities           2\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         1\n",
       "Exterior2nd         1\n",
       "MasVnrType         16\n",
       "MasVnrArea         15\n",
       "ExterQual           0\n",
       "ExterCond           0\n",
       "Foundation          0\n",
       "BsmtQual           44\n",
       "BsmtCond           45\n",
       "BsmtExposure       44\n",
       "BsmtFinType1       42\n",
       "BsmtFinSF1          1\n",
       "BsmtFinType2       42\n",
       "BsmtFinSF2          1\n",
       "BsmtUnfSF           1\n",
       "TotalBsmtSF         1\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        2\n",
       "BsmtHalfBath        2\n",
       "FullBath            0\n",
       "HalfBath            0\n",
       "BedroomAbvGr        0\n",
       "KitchenAbvGr        0\n",
       "KitchenQual         1\n",
       "TotRmsAbvGrd        0\n",
       "Functional          2\n",
       "Fireplaces          0\n",
       "FireplaceQu       730\n",
       "GarageType         76\n",
       "GarageYrBlt        78\n",
       "GarageFinish       78\n",
       "GarageCars          1\n",
       "GarageArea          1\n",
       "GarageQual         78\n",
       "GarageCond         78\n",
       "PavedDrive          0\n",
       "WoodDeckSF          0\n",
       "OpenPorchSF         0\n",
       "EnclosedPorch       0\n",
       "3SsnPorch           0\n",
       "ScreenPorch         0\n",
       "PoolArea            0\n",
       "PoolQC           1456\n",
       "Fence            1169\n",
       "MiscFeature      1408\n",
       "MiscVal             0\n",
       "MoSold              0\n",
       "YrSold              0\n",
       "SaleType            1\n",
       "SaleCondition       0\n",
       "dtype: int64"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pd.options.display.max_rows = None     # Display all rows\n",
    "pd.options.display.max_columns = None  # Display all columns\n",
    "\n",
    "df.isnull().sum()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "2a1ec6a4",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:>"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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gZit5MDMzM7Pu5UoAM+tpMXbPwCVNAH4GbA3MBq6TdHZE3F5I9nng9oh4n6TlgLsknRgRL9Ta7ogrDXLMgmOAOyLix1WL3wXcGRGzC+lXB/6RAyG+ClgbuH+k+zczMzOz7ueWBtYrHAjRSo1t94RNgLsj4l4ASacAO5DjDmYBLJXv55cEHiMNclBTKy0N3grsCtxaGVYR+J+IOA/YhaquCcDbgP0kvQgMAp+LiEdb2L+ZmZmZdTlXAlivcEWAdYCpwD8K07OBTavSHAmcDcwBlgI+HFE/WmMroydcCajGsk+UzPsN8JuR7m88dVugEkdYNTMzMzMbW6PV0sBl+y7XxpYGxQEDshk5HuD8JCWrVfePeDdwE2mUw1cDF0u6oio+4ULaMnpCr+u2g7Tb8mtmZmZm1u1Gq6WBy/Zdro1DLhYHDKhhNrBKYXplUouCok8Ch0REAHdLug94LXBtrY22EtNgMeByYNG8ndMj4kBJOwMHAa8DNomImTn91sAhwCTgBeCrEfHnke7fzMzMzLqfYxpYr3BMA+sA1wFr5niCD5HCBnykKs2DwFbAFZJWIMUavLfeRltpafA8sGVEPJVHUbhS0vnALNLICb+sSv8o8L6ImCNpXeBCUp+Ljtdt3RPMzMzMuoXLTtYrXBFgZWJw7EZPyIMO7Em6154AHBsRt0naIy8/Cvg2cLykW0ndGfYdLtZgKzENAngqTy6SXxERdwCkYIwLpb+xMHkbsJikRSPi+ZHmYaz4YmZmZmZmZmZNG9vRE8gDE5xXNe+owt9zgG2a2WZLMQ3yOJDXA68BfhYR1zS46geBG2tVGBQDPGjCFAYGJreSTTMzMzPrUO6eYGbW2VqqNIiIl4ANJC0DnCVp3YiYVW8dSa8Hvk+d2o1igIeJk6aOXXuOHuEIq2ZmZtYtFl/p7W7WbT3BoydYqTYGQhwvbRk9ISL+LelSYFtSTINSklYGzgI+HhH3tGPfNpRPKmZmZtYtHDvKeoVHT7BSYxjTYLS0MnrCcsCLucJgceBdpBYEtdIvA5wL7B8Rfx3pfs3MzMysP3VKi4TRuokbzffnG08zG6lWWhqsCPw6xzUYAE6LiD9K+gBwBLAccK6kmyLi3cCepNgHB0g6IG9jm4iY20IezMzMzKyP9PLNby+/t37gIRet1BgHQhwNrYyecAvwxpL5Z5G6IFTP/w7wnZHuz8zMzMx6j2+UrVe4IsBK9XOlgZmZmZlZqzx6gvUKtzSwXtVKTIPFgMuBRfN2To+IAyUdBHwa+GdO+j8RcZ6kVwCnAxsDx0fEni3l3GpyhFUzMzPrFh49wXrFaP2OXbbvctHHgRCB54EtI+IpSYsAV0o6Py87LCIOrUr/HHAAsG5+WRN8ojAzM7Ne5NETzOrz777L9XP3hIgI4Kk8uUh+1axGiYinSRULrxnpPvuZL6hmZmbW7zqlRYJHTzCzftJSTIM8csL1pFERfhYR10h6D7CnpI8DM4H/FxGPN7nd6cB0AE2YwsDA5FayaWbWVzqlUN2M0eoH6kKyWe/p5eO6l9+bWd8a7O/uCUTES8AGkpYBzpK0LvAL4NukVgffBn4E7N7kdmcAMwAmTpra/Z9yG/giYmaN6vXzRa+/P7N+42PazHpa9HH3hKKI+LekS4Fti7EMJP0K+GM79tHv/GTNzMzMelGvt45qhrsnmFknamX0hOWAF3OFweLAu4DvS1oxIh7OyT4AzGpDPq0JjrBqZmZm3aLZ0RN6uYzTy++tH3jIRSvV590TVgR+neMaDACnRcQfJf1G0gak7gn3A5+prCDpfmBpYJKk9wPbRMTtLeShb/giYmZmZr3IFQbWK1wRYGWiz0dPuAV4Y8n8Xeuss9pI9zeeOuFi1gl5MDMzMxtPbk1pZjb22hLToNd1wsWpE/JgZmZmZmZmTejn7gmSFgMuBxbN2zk9Ig6UtD5wFLAkqXvCRyPiibzO/sCngJeAL0bEha1lv3+4pYGZmZmZmVmX6fPRE54HtoyIpyQtAlwp6XzgCOArEXGZpN2BrwIHSFoH2AV4PbAS8CdJa+VhG83MzMysD/lhh/UKB0K0XtVKTIMAnsqTi+RXAGuTWiAAXAxcCBwA7ACcEhHPA/dJuhvYBPjbSPNg5dzfz8zMzLqJW1SaWc/q5+4JAHnkhOuB1wA/i4hrJM0Ctgf+AOwMrJKTTwWuLqw+O88r2+50YDqAJkxhYGByK9nsO76YmpmZWbdwhYH1CrcesFL9PHoCQO5asIGkZYCzJK0L7A78VNI3gLOBF3JylW2ixnZnADMAJk6a2v1VM2ZmY6gbCy2j1aTTNxhmnc/HqZlZZ2vL6AkR8W9JlwLbRsShwDYAktYC/isnm82CVgcAKwNz2rF/MzMzM+tOzVZ0upLBzLpKP3dPkLQc8GKuMFgceBfwfUnLR8RcSQPA10kjKUBqdXCSpB+TAiGuCVzbWvbNzKxarxeoe/39mfUbH9Nm1tP6fPSEFYFf57gGA8BpEfFHSXtJ+nxOcyZwHEBE3CbpNOB2YB7weY+cYGZmZmZmZta5Whk94RbgjSXzDwcOr7HOwcDBI93neOm2/rMePcHMzMzMzKwD9HP3hH7SbTfg3ZZfMzMzMzOzXhT9PnoCzB92cSbwUERsJ+mHwPtIoybcA3wyxz2YBPwS2AgYBPaKiEtb3b+ZmZmZdS8HQjQz62ztaGmwF3AHsHSevhjYPyLmSfo+sD+wL/BpgIh4g6TlgfMlbRzR+ZEhuq17gpmZmZmZmXWAfu+eIGll0pCKBwNfBoiIiwpJrgZ2yn+vA1yS08yV9G9Sq4OOH0HBFQFmZmZmo8PlLDPraf1eaQD8BNgHWKrG8t2BU/PfNwM7SDoFWAXYMP/f8ZUGZmZmZjY63D3BekUzv81mf/dm42nElQaStgPmRsT1krYoWf410tCKJ+ZZxwKvI8U/eAC4Ki8v2/Z0YDqAJkxhYGDySLPZM3yBNDMzs17kMo71ClcEWKnO740/rFZaGrwV2F7Se4HFgKUl/TYiPiZpN2A7YKuICICImAfsXVlZ0lXA38s2HBEzgBkAEydN7f72HG3guApmZmZmZmZdpp+7J0TE/qQgh+SWBl/JFQbbkgIfbh4Rz1TSS1oCUEQ8LWlrYF5E3N5K5seKb9jNzMzMzMysWdHPlQZ1HAksClwsCeDqiNgDWB64UNIg8BCw6yjse1S4IsDMzMzMzMz6UVsqDSLiUuDS/PdraqS5H1i7Hfsba25pYGZmZmZm7eJ7hj7ilgb9wQe1mZmZmZm1ix9K9pHB/g6ECICkCaQRER6KiO3yvC8Ae5JGRzg3IvaRtAhwNPCmvN8TIuJ7re7fhnp2zhU+uZiZmZmZjSEPuWi9qh0tDfYC7gCWBpD0TmAHYL2IeF7S8jndzsCiEfGGHBTxdkkn524L1kauMDAzM7Nu4Seu1itcEWCl+r17gqSVgf8CDga+nGd/FjgkIp4HiIi5eX4AkyVNBBYHXgCeaGX/ZmZmZtbdXBFgZj2t3ysNgJ8A+wBLFeatBbxd0sHAc6ShGK8DTie1QHgYWALYOyIea3H/ZmZmZtbFmn0660oG6wX+HVs3GXGlgaTtgLkRcb2kLaq2+TJgM2Bj4DRJawCbAC8BK+XlV0j6U0TcW7Lt6cB0AE2YwsDA5JFm08zMzMw6mG+erB+5W07/iOjvlgZvBbaX9F5gMWBpSb8FZgNnRvp0rpU0CCwLfAS4ICJeBOZK+iuwETCk0iAiZgAzACZOmtr9n7KZmZmZlXJLAzPraf3cPSEi9gf2B8gtDb4SER+TtAewJXCppLWAScCjwIPAlrliYQlSS4SftJL5sdJtNYEePcHMzMy6xeIrvd0B5KwnePQE61XtGD2h2rHAsZJmkYId7hYRIelnwHHALEDAcRFxyyjsv+267Qa82/JrZmZm/c1lF+sFrgiwUv3c0qAoIi4FLs1/vwB8rCTNU6RhF83MzMzMzMx6XrjSwMzMzMzMzNw9wXqVKw3MzMzMzMzMRkO/tzSQdD/wJGkoxXkRsZGklwOnAqsB9wMfiojHJX0U+Gph9fWAN0XETa3kwczMzMy6l0dPsF7h1gNWanC8M9C6gTZs450RsUFEbJSn9wMuiYg1gUvyNBFxYk63AbArcL8rDMzMzMzMzMw612h0T9gB2CL//WtSgMR9q9JMA04ehX2bmZmZWRdxywEz62W9EAix1ZYGAVwk6XpJ0/O8FSLiYYD8//Il632YOpUGkqZLmilp5uDg0y1m0czMzMzMzGwcDEb7XuOk1ZYGb42IOZKWBy6WdOdwK0jaFHgmImbVShMRM4AZABMnTe3+qhkzMzMzMzOzLtRSpUFEzMn/z5V0FrAJ8IikFSPiYUkrAnOrVtsFd00wMzMzMzOzXtcDgRBHXGkgaTIwEBFP5r+3Ab4FnA3sBhyS//9DYZ0BYGfgHa1k2szMzMx6g0dPMLNe1gsxDVppabACcJakynZOiogLJF0HnCbpU8CDpEqCincAsyPi3hb2a2ZmZmY9wpUAZmadbcSVBvnGf/2S+f8CtqqxzqXAZiPdp5mZmZmZmVnX6OfuCWZmZmZmZmZWWy90T2hpyEVJ90u6VdJNkmZWLfuKpJC0bGHeepL+Jum2vN5irezfzMzMzMzMzEZPO1oavDMiHi3OkLQKsDUppkFl3kTgt8CuEXGzpFcAL7Zh/2ZmZmZmZmadpwe6J7TU0qCOw4B9gGJbjG2AWyLiZkixDyLipVHav5mZmZmZmdm4isH2vcZLqy0NArhIUgC/jIgZkrYHHsqtCYpp1wJC0oXAcsApEfGDso1Kmg5MB9CEKQwMTG4xm2ZmZmbWiZodcrETjNaID6P5WXiUCjMbqVYrDd4aEXMkLQ9cLOlO4GukVgVl+3obsDHwDHCJpOsj4pLqhBExA5gBMHHS1O6PHGFmZmZmLev1G99ef39mfakHuie0VGkQEXPy/3MlnQVsDqwOVFoZrAzcIGkTYDZwWSX+gaTzgDcBQyoNzMzMzKw/+EbZeoV/y1ZmPLsVtMuIKw0kTQYGIuLJ/Pc2wLciYvlCmvuBjSLi0dwtYR9JSwAvkCoYDmsp92ZmZmZmZh1gtLqXuDLCxlsrLQ1WAM7KLQomAidFxAW1EkfE45J+DFxHioVwXkSc28L++4pPFmZmZtaLmr3RcpnIzLpKP7c0iIh7gfWHSbNa1fRvScMudpVmLmadEBjHF1MzMzPrFi63mFkv6+vuCf2kEy5mnZAHMzMzs3ZzSwMzs/aRtC1wODABODoiDilJswXwE2AR4NGI2LzeNluqNMgxC54EXgLmRcRGkjYAjgIWA+YBn4uIayWtBtwB3JVXvzoi9mhl/2ZmZmbWP1xhYGbdZixbGkiaAPwM2Jo0EMF1ks6OiNsLaZYBfg5sGxEP5pEQ62pHS4N3VkZEyH4AfDMizpf03jy9RV52T0Rs0IZ99h13TzCz0eBzi5mNN59brFc081seraCJ1nnGuHvCJsDdOZQAkk4BdgBuL6T5CHBmRDwIaSTE4TY6Gt0TAlg6/z0FmDMK+xhTLlSbWa/yOcvMzKw9fM9gHWAq8I/C9Gxg06o0awGLSLoUWAo4PCJOqLfRVisNArhIUgC/jIgZwJeACyUdCgwAbymkX13SjcATwNcjovTIkjQdmA6gCVMYGJjcYjZb44PazMzMbHQ4poH1I1cw9JFQ2zZVvE/OZuR78PlJynJQNT0R2BDYClgc+JukqyPif2vtt9VKg7dGxJzcD+JiSXcCOwF7R8QZkj4EHAO8C3gYWDUi/iVpQ+D3kl4fEU8MeVfpjc8AmDhpavWbHHM+qM3MzMzMrB53T7Ay7eyeULxPrmE2sEphemWGtvyfTQp++DTwtKTLSaMijk6lQUTMyf/PlXQWqQ/FbsBeOcnvgKNzmueB5/Pf10u6h9Q0YmYreRgLrggwMzMzMzOzDncdsKak1YGHgF1IMQyK/gAcKWkiMInUfeGwehsdcaWBpMnAQEQ8mf/eBvgWqSZjc+BSYEvg7zn9csBjEfGSpDWANYF7R7p/MzMzM+svfpBjncytB6xMDLave8Kw+4qYJ2lP4ELSkIvHRsRtkvbIy4+KiDskXQDcAgyShmWcVW+7rbQ0WAE4S1JlOydFxAWSngIOzzUXz7Ggz8U7gG9JmkcaonGPiHishf2bmZmZmZmZdawxHj2BiDgPOK9q3lFV0z8EftjoNkdcaZCHcVi/ZP6VpMAK1fPPAM4Y6f7MzMzMrL89O+cKtzYwMxtjozHkoo0CXyDNzMysF7mMY73CgRCtTLRx9ITx0lKlgaRlSIEO1yUN5bA7sCPwPuAF4B7gkxHx78I6qwK3AwdFxKGt7L+feAQHMzMzM7PO5YoAKzPW3RNGQ6stDQ4HLoiInSRNApYALgb2z0EYvg/sD+xbWOcw4PwW92tmZmZmPaDZGy0/HLFO5ZYG1qtaGT1haVJww08ARMQLpNYFFxWSXQ3sVFjn/aQRE54e6X7NzMzMrD+5wsA6mSsCrMxYjp4wWlppabAG8E/gOEnrA9cDe0VEsUJgd+BUmD9E477A1sBX6m1Y0nTyqAuaMIWBgcktZLM3+CJpZmZmZmbWXSLGOweta6XSYCLwJuALEXGNpMOB/YADACR9DZgHnJjTfxM4LCKeysM01hQRM4AZABMnTe2Bj9nMzMzMWtUpT3JH62HOaL4/P4Ays5FqpdJgNjA7Iq7J06eTKg2QtBuwHbBVxPy6lU2BnST9AFgGGJT0XEQc2UIezMzMzKyL+WZ2AX8WZr2nr7snRMT/SfqHpLUj4i5gK+B2SduSuiFsHhHPFNLPPwtKOgh4yhUGjfPoCWZmZtaLHAjRzHpZX1caZF8ATswjJ9wLfBK4DlgUuDh3Q7g6IvZocT99zxdIMzMzMzMzG2stVRpExE3ARlWzX9PAege1st9+5JYGZmZm1u9cxjGzbtPvgRDNzMzMzFriigDrFc38ljslqKeNvr7vniBpGeBoYF0ggN0j4m+SvgDsSRo94dyI2EfSJuQREQABB0XEWa3s38zMzMy6m2MaWD/y77h/RPR5pQFwOHBBROyU4xosIemdwA7AehHxvKTlc9pZwEYRMU/SisDNks6JiHkt5sHMzMzMupRvnqxXjFbrAR8jNt5GXGkgaWngHcAnACLiBeAFSZ8FDomI5/P8ufn/ZwqrL0ZqmWBmZmZmfcwtDcysl8XgeOegda20NFgD+CdwnKT1geuBvYC1gLdLOhh4DvhKRFwHIGlT4FjgVcCubmXQOF8gzczMzMzMustgn3dPmAi8CfhCRFwj6XBgvzz/ZcBmwMbAaZLWiOQa4PWSXgf8WtL5EfFc9YYlTQemA2jCFAYGJreQzdZ1wsgFnZAHMzMzs/HkMo6Z2dhrpdJgNjA7VwQAnE6qNJgNnBkRAVwraRBYltQqAYCIuEPS06QAijOrNxwRM8hBEydOmjru3Rh8gTIzMzMzM7Nm9UIgxIGRrhgR/wf8Q9LaedZWwO3A74EtASStBUwCHpW0uqSJef6rgLWB+0ecczMzMzPrKx6mzsy6TQyqba/x0uroCV8ATswjJ9wLfBJ4GjhW0izgBWC3iAhJbwP2k/QiMAh8LiIebXH/Y8JdA8zMzMxGh8tO1iua+S27Asy6SUuVBhFxE7BRyaKPlaT9DfCbVvY3XnwxMzMzMxsdHj3BeoUrAqxMjHtn+9a12tKgL7ilgZmZmZmZ1eOWBlZmPLsVtMuIKw1yLINTC7PWAL4BnJDnr0aKWfChiHhc0tbAIaQYBy8AX42IP490/2PJFQFm42O0Lqg+ps3MOkezN1qdcLPVCaNlNcvXvtHXCb9Ns9Ew4kqDiLgL2ABA0gTgIeAs0ggKl0TEIZL2y9P7Ao8C74uIOZLWBS4EpraW/bHhlgZm48PHk5mZFfX6daHX31+vc0sDKzPYA6MntKt7wlbAPRHxgKQdgC3y/F8DlwL7RsSNhfS3AYtJWjQinm9THkaNT+BmZmZmZlaPKwKsTC8MudiuSoNdgJPz3ytExMMAEfGwpOVL0n8QuLEbKgzALQ3MzMzMzMysP7VcaZCHW9we2L/B9K8Hvg9sUyfNdGA6gCZMYWBgcqvZNDMzM7MO5NETzKyXefSE5D3ADRHxSJ5+RNKKuZXBisDcSkJJK5PiHnw8Iu6ptcGImAHMAJg4aWoPfMxmZmZmVsaVANYrHNPAyjimQTKNBV0TAM4GdiONlLAb8AcAScsA5wL7R8Rf27BfMzMzMzOzjuCKAOtVLVUaSFoC2Br4TGH2IcBpkj4FPAjsnOfvCbwGOEDSAXneNhExFzMzMzPrS44dZWa9rO8DIUbEM8Arqub9izSaQnXa7wDfaWV/48UXKDMzM7Px9+ycK1wuM7Ou4pgGfcI14GZmZmajw2UnM7PO5kqDBvhiZmbdpBv7VI5W8Cifv806X6+fs5oxmp+Fz4dm46OvAyFKWhs4tTBrDeAbEfGTvPwrwA+B5SLiUUmvAE4HNgaOj4g9R5xrMzOrqdcLhr3+/sysvl4+B/Tye+sH/v6sTF/HNIiIu4ANACRNAB4iDaeIpFVIARIfLKzyHHAAsG5+mZmZmVmf842W9YrRainiY8TGW7u6J2wF3BMRD+Tpw4B9yMMtAkTE08CVkl7Tpn2amZmZmZl1hNHqamfdra+7J1TZBTgZQNL2wEMRcbM0sg9I0nRgOoAmTGFgYHKbsmlmZmZmZmY2Nnpg8ITWKw0kTQK2B/aXtATwNWCbVrYZETOAGQATJ03thc/ZzMzMzMzMrOu0o6XBe4AbIuIRSW8AVgcqrQxWBm6QtElE/F8b9mVmZmZmZmbWFdw9IZlG7poQEbcCy1cWSLof2CgiHm3DfszMrAEektDMukmzfbt93rJO5TgFVqavR08AyN0RtgY+02D6+4GlgUmS3g9sExG3t5IHMzNbmAvUZtZNfM4yM+tsLVUaRMQzwCvqLF+t3rSZmbVfNz7pGK2I074ZMet8PqbNrJcNjncG2qBdoyeYmVmH6PVCda+/P7N+42PazHpZ0P3dEwZGuqKktSXdVHg9IelLkjaQdHWeN1PSJoV19pd0t6S7JL27PW/BzMzMzMzMzEbDiFsaRMRdwAYAkiYADwFnAb8CvhkR50t6L/ADYAtJ6wC7AK8HVgL+JGmtiHiptbdgZmZmZmZm1nkGY7xz0Lp2dU/YCrgnIh6QFKRghwBTgDn57x2AUyLieeA+SXcDmwB/a1MezMzMzKzLePQEM+tlgz3QPaFdlQa7kIddBL4EXCjpUFL3h7fk+VOBqwvrzM7zhpA0HZgOoAlTGBiY3KZsmpmZmVm3coWBmdnYa7nSQNIkYHtg/zzrs8DeEXGGpA8BxwDvgtIqltLGGhExA5gBMHHS1B5o0GFmZmZmZr1stEYCsu7WC4EQ29HS4D3ADRHxSJ7eDdgr//074Oj892xglcJ6K7Og64KZmZmZ9SG3HrBe4YoAK+MhF5NpLOiaAKkiYHPgUmBL4O95/tnASZJ+TAqEuCZwbRv2b2ZmZmZdyjENzMw6W0uVBpKWALYGPlOY/WngcEkTgefIsQki4jZJpwG3A/OAz3vkBDMzM7P+5koA6xXunmBl+r57QkQ8A7yiat6VwIY10h8MHNzKPs3MzMzMzDqNKwKsTC90TxgY7wyYmZmZmZmZWWdqqdJA0t6SbpM0S9LJkhaTtHOeNyhpo0LaSZKOk3SrpJslbdFq5s3MzMzMzMw61WAbX+NlxJUGkqYCXwQ2ioh1gQnALsAsYEfg8qpVPg0QEW8gxUH4kSS3dDAzMzMzM7OeFKhtr/HS6ugJE4HFJb0ILAHMiYg7AKQhb2od4BKAiJgr6d/ARngEBTMzM7O+5dETzMw624if9EfEQ8ChwIPAw8B/IuKiOqvcDOwgaaKk1UnBElcpSyhpuqSZkmYODj490iyamZmZmZmZjZtBte81Xkbc0kDSy4AdgNWBfwO/k/SxiPhtjVWOBV4HzAQeAK4iDb04RETMAGYATJw0NUaaRzMzMzPrbG45YGa9bLDPh1x8F3BfRPwTQNKZwFuA0kqDiJgH7F2ZlnQV8PcW9m9mZmZmZmZmo6iVSoMHgc0kLQE8C2xFakVQKqdTRDwtaWtgXkTc3sL+zczMzMzMzDpWLzSbH3GlQURcI+l04AZSN4MbgRmSPgAcASwHnCvppoh4N7A8cKGkQeAhYNeWc29mZmZmZmbWocZzqMR2aWn0hIg4EDiwavZZ+VWd9n5g7Vb2Z2ZmZma9xaMnmJl1tlaHXDQzMzMzGzFXAphZLxtU9wdCHPGQiwCS9pZ0m6RZkk6WtJikgyQ9JOmm/HpvTruIpF9LulXSHZL2b89bMDMzMzMzM+s80cbXeGllyMWpwBeBdSLiWUmnAbvkxYdFxKFVq+wMLBoRb8hBEW+XdHLutmBmZmZmZmZmHabV7gkTgcUlvQgsAcwBVquRNoDJkiYCiwMvAE+0uH8zMzMz62LNxDRwVwbrFf4t94++DoQYEQ9JOpQ09OKzwEURcZGktwB7Svo4aQjG/xcRjwOnAzsAD5MqGPaOiMfKti1pOjAdQBOmMDAweaTZbAtfzMzMzMxGh8tO1o98f9E/Brs/pEFL3RNeRqoEWB34N/A7SR8DfgF8m9Sy4NvAj4DdgU2Al4CVgJcBV0j6U0TcW73tiJgBzACYOGnquA9t6QPVzMzMzMzMmjVI99catBII8V3AfRHxz4h4ETgTeEtEPBIRL0XEIPArUmUBwEeACyLixYiYC/wV2KiVzJuZmZmZmZlZImlbSXdJulvSfnXSbSzpJUk7DbfNVioNHgQ2k7SEJAFbAXdIWrGQ5gPArEL6LZVMBjYD7mxh/2ZmZmZmZmYdayxHT5A0AfgZ8B5gHWCapHVqpPs+cGEj76GVmAbXSDoduAGYB9xI6lJwtKQNSO/rfuAzeZWfAceRKhEEHBcRt4x0/2ZmZmZmZmadbIxjGmwC3F0JASDpFFJIgdur0n0BOAPYuJGNtjR6QkQcCBxYNXvXGmmfIg27aGZmZmZmZmZNKA4YkM3I8QArpgL/KEzPBjat2sZUUo+ALRmLSgMzMzMzs1Y0E0UeHKDazLpLO4dcLA4YUENZu4bqng0/AfaNiJdSlIHhtRLTAEl7S7pN0ixJJ0taTNL6kv4m6VZJ50haOqf9qKSbCq/B3I3BzMzMzMzMrOeMZUwDUsuCVQrTKwNzqtJsBJwi6X5gJ+Dnkt5fb6OtDLk4FfgisE5EPCvpNGAX4PPAVyLiMkm7A18FDoiIE4ET87pvAP4QETeNdP9mZmZm1v3ccsDMrG2uA9aUtDrwEOn+/CPFBBGxeuVvSccDf4yI39fbaKvdEyYCi0t6EViCVIuxNnB5Xn4xKSLjAVXrTQNObnHfZmZmZtbl3D3BzHrZWAZCjIh5kvYk3YNPAI6NiNsk7ZGXHzWS7bYyesJDkg4lDaX4LHBRRFwkaRawPfAHUuDDVUpW/zApiqOZmZmZ9bHFV3p7wxUHrjCwTtbMb9n6RztjGjQiIs4DzquaV1pZEBGfaGSbI45pIOllpBv/1YGVgMmSPgbsDnxe0vXAUsALVettCjwTEbPqbHu6pJmSZg4OPj3SLJqZmZlZh/NNlvUK/5atV7XSPeFdwH0R8U8ASWcCb4mI3wLb5HlrAf9Vtd4uDNM1oRgVcuKkqQ3GfOhtrlk3MzOzfvfsnCtcJjKzrjLWLQ1GQyuVBg8Cm0lagtQ9YStgpqTlI2KupAHg68D8phB53s7AO1rYb19qpubSF1MzMzMzM7PxF2MY02C0tBLT4BpJpwM3APOAG0mtA/aQ9Pmc7EzguMJq7wBmR8S9I92vmZmZmfUOP+wwM+tsLY2eEBEHAgdWzT48v8rSXwps1so+zczMzMzMzLpBv3dPMDMzMzMzM7Ma+r7SQNJewKcBAb+KiJ9I+jZpVIVBYC7wiYiYk9OvB/wSWDov3zginmslD2ZmZmbWvRy3ycyss4240kDSuqQKg01IwypeIOlc4IcRcUBO80XgG6Q4BxOB3wK7RsTNkl4BvNjqGxgLvpiZmZmZjQ6Xncysl/XCUICttDR4HXB1RDwDIOky4AMR8YNCmsks+Jy2AW6JiJsBIuJfLex7TPliZmZmZjY6mh3b3uUy61TN/Dab/d1b9xrsgdETBlpYdxbwDkmvyMMuvhdYBUDSwZL+AXyU1NIAYC0gJF0o6QZJ+7SScTMzMzMzMzMbXSOuNIiIO4DvAxcDFwA3k4ZeJCK+FhGrACcCe+ZVJgJvI1UkvA34gKStyrYtabqkmZJmDg4+PdIsmpmZmZmZmY2bwTa+xkurQy4eAxwDIOm7wOyqJCcB55KGZZwNXBYRj+b05wFvAi4p2e4MYAbAxElTe6EbiJmZmZmVWHyltzfcVNtdE6yTucuBlfHoCdLyETFX0qrAjsCbJa0ZEX/PSbYH7sx/Xwjsk7syvABsDhzWyv7NzMzMrPu5MsDMrHO1VGkAnFEYBeHzEfG4pKMlrU2qVHkA2AMgL/sxcB0pOOJ5EXFui/s3MzMzsy7mQIhm1st6odl8q90Thpy1I+KDddL/ljTsopmZmZmZWc/w6AlWphdGT2i1pYGZmZmZ2Yi55YCZWWdzpYGZmZmZjRt3T7Be4dYDVqYXAiGOeMhFAEl7SZol6TZJX8rzTpV0U37dL+mmPH81Sc8Wlh3Vevb7h5s7mZmZWS9yJYBZfS7bd7do42u8jLilgaR1gU8Dm5BGQ7hA0rkR8eFCmh8B/ymsdk9EbDDSfY6XZg7U0brwdUIezMzMzNrNZRzrR/4tWzdppXvC64CrI+IZAEmXAR8AfpCnBXwI2LLVTI43H9Rm1k268YnEaLWm8vnbrLc8O+cKH9fWE3wt6x+DPTB+QiuVBrOAg/OQi88C7wVmFpa/HXgkIv5emLe6pBuBJ4CvR0Tp0SJpOjAdQBOmMDAwuYVs9gafLMysUb1+vuj192dmZma9oxdiGoy40iAi7pD0feBi4CngZmBeIck04OTC9MPAqhHxL0kbAr+X9PqIeKJk2zOAGQATJ03t/qqZNnBtpJmZmfUil1usVzgGmfWqlkZPiIhjgGMAJH0XmJ3/ngjsCGxYSPs88Hz++3pJ9wBrsXDrBKvBF1QzMzMzs87ligAr0wtPwFuqNJC0fETMlbQqqZLgzXnRu4A7I2J2Ie1ywGMR8ZKkNYA1gXtb2b+ZmZmZmVknaPYhX6OVDI7l0d36untCdkaOafAi8PmIeDzP34WFuyYAvAP4lqR5wEvAHhHxWIv77xvunmBmZmZm1rlGq6WBy/Y23lrtnlD6C46IT5TMOwM4o5X9mZmZmVlvafZGyzdQ1qkc08DKDGq8c9C6VlsamJmZmZmZ9T1XBFiZvhhyUdKxwHbA3IhYN897OXAqsBpwP/ChiHg8d1U4HdgYOD4i9izZ3tnAGpVtdQN3DTAzMzMbHS47Wa9wSwPrVY20NDgeOBI4oTBvP+CSiDhE0n55el/gOeAAYN38WoikHUnDM3aVTriYdUIezMzMzMysnCsCrEz3tzNooNIgIi6XtFrV7B2ALfLfvwYuBfaNiKeBKyW9pno7kpYEvgxMB04beZb7k/v7mZmZmZn1H4+e0N16YfSEgRGut0JEPAyQ/1++gXW+DfwIeGa4hJKmS5opaebg4NMjzGL/8knFzMzMzKw3uGxv421MAiFK2gB4TUTsXdJqYYiImAHMAJg4aWovtOgwMzMzsxJuTWm9wjENrExfBEKs4RFJK0bEw5JWBOYOk/7NwIaS7s/7XF7SpRGxxQj3b2ZmZmY9wJUA1itcEWBlur/KYOSVBmcDuwGH5P//UC9xRPwC+AVAbmnwR1cYmJmZmZmZdQePKNe/Ghly8WRS0MNlJc0GDiRVFpwm6VPAg8DOhfT3A0sDkyS9H9gmIm5ve87HkA8QMzMzMzPrZ77PGZleCITYyOgJ02os2qpG+tWG2d79lAzH2Mm67QBxhFUzMzPrJn5AY1aby/bdrRdiGox09ATrYD6pmJmZWbdwhYFZff7d23hrpHvCscB2wNyIWDfPezlwKrAacD/woYh4PMcruAO4K69+dUTskde5AFgx7/MK4PMR8VI734yZmZmZdRffEJlZL+v+dgaNBUI8HjgSOKEwbz/gkog4RNJ+eXrfvOyeiNigZDsfiognJAk4nRQH4ZSRZtzMzMzMup+HXDSzXtYvMQ0uzy0IinYgBUcE+DVwKQsqDWpt54nCPifRRZUubjZnZmZmNjpcdrJe0cxv2cMzWjcZ6ZCLK0TEwwAR8bCk5QvLVpd0I/AE8PWImH9ESLoQ2AQ4n9TaoJSk6cB0AE2YwsDA5BFmsz18MTMzMzMbHW5pYL3CFQFWJrrnWXlN7Q6E+DCwakS8EfgycJKkpSsLI+LdpLgGiwJb1tpIRMyIiI0iYqPxrjDoRj5hmZmZWbdwJYBZfS7bd7fBNr7Gy0hbGjwiacXcymBFYC5ARDwPPJ//vl7SPcBawMzKihHxnKSzSV0cLm4p91bKF18zMzPrJi67mNXm46O79cKQiyOtNDgb2A04JP//BwBJywGPRcRLktYA1gTulbQksFSuZJgIvJc0goKZmZmZ9TF3TzAz62yNDLl4Mino4bKSZgMHkioLTpP0KeBB0kgIAO8AviVpHvASsEdEPCZpBeBsSYsCE4A/A0e1+82YmZmZWXdxJYCZ9bLub2fQ2OgJ02os2qok7RnAGSXzHwE2bjp3HcKjJ5iZmZmZmVmz+rl7Ql9xRYCZmZmZmZn1o0a6JxwLbAfMjYh187yXA6cCqwH3Ax+KiMclTQJ+CWxECvC4V0RcKmkJ4HfAq0ndFs6JiP3a/3YMUssIV3SYmZlZt3CrTjPrVeM56kG7NNLS4HjgSOCEwrz9gEsi4hBJ++XpfYFPA0TEGyQtD5wvqdIt4dCI+EuuWLhE0nsi4vx2vRFbwBdTMzMz6yYuu5hZr4p+6J4QEZdLWq1q9g6k4IgAvwYuJVUarANcktebK+nfwEYRcS3wlzz/BUk3ACu3nn0zMzMz62YePcHMrLONNKbBChHxMEAeRnH5PP9mYAdJpwCrABvm/6+trChpGeB9wOG1Ni5pOjAdQBOmMDAweYTZNDMzM7NO5koAM+tl/dI9oRnHAq8DZgIPAFcB8yoLJU0ETgZ+GhH31tpIRMwAZgBMnDS1+9tzmJmZmVkptzSwXtHMb7PZ3711r77onlDDI5JWzK0MVgTmAkTEPGDvSiJJVwF/L6w3A/h7RPxkhPs1MzMzsx7iSgAzs8420kqDs4HdgEPy/38AyKMkKCKelrQ1MC8ibs/LvgNMAf675VxbXR49wczMzLqJR08ws17VF90TJJ1MCnq4rKTZwIGkyoLTJH0KeBDYOSdfHrhQ0iDwELBr3sbKwNeAO4EbJAEcGRFHt/XdGOCLqZmZmXUXl13MrFcNRh90T4iIaTUWbVWS9n5g7ZL5swE1mzkzMzMzM7Px4jgFZu0PhGhmZmZm1jAHQrRO5ooAa1X3tzOAgeESSDpW0lxJswrzdpZ0m6RBSRsV5m8i6ab8ulnSBwrLDpb0D0lPtf9tmJmZmZmZmXWWQaJtr/HSSEuD44EjgRMK82YBOwK/rEo7C9goIublURVulnROHlXhnLydv2NmZmZmhlsOmJl1umFbGkTE5cBjVfPuiIi7StI+kysIABaj0BojIq6OiIdbzK81wM2ozMzMzMzMxl+08d94aXtMA0mbAscCrwJ2LVQi2Bhxjb1ZfaNZsebjz8zMzMwq+mLIxWZFxDXA6yW9Dvi1pPMj4rlmtiFpOjAdQBOmMDAwud3ZbIrHDjbrLT5OzczMzMwaM2qjJ0TEHZKeBtYFZja57gxgBsDESVPHPeCkbzDMzMzMRodHTzCzXjaeAQzbpa2VBpJWB/6RAyG+ClgbuL+d+zAzMzMzM+s0zVRoOQZZ/xjPWATtMmylgaSTgS2AZSXNBg4kBUY8AlgOOFfSTRHxbuBtwH6SXiR13/hcRDyat/MD4CPAEnk7R0fEQe1/S2ZmZmbWLdxywMyssw1baRAR02osOqsk7W+A39TYzj7APk3lzkbk2TlX+AJsZmZmXcPxo8ysVzkQonUkX0zNzMysm7jsYr3AXQ6sTET3d08YGC6BpGMlzZU0qzBvZ0m3SRqUtFFh/kcl3VR4DUraIC/bUNKtku6W9FNJGpV3ZGZmZmZmZtaHJG0r6a58371fyfKPSrolv66StP5w2xy20gA4Hti2at4sYEfg8uLMiDgxIjaIiA2AXYH7I+KmvPgXpGEU18yv6m2amZmZmZmZ9YxBom2v4UiaAPwMeA+wDjBN0jpVye4DNo+I9YBvk0ctrGfYSoOIuJwU+LA4746IuGuYVacBJ+fMrwgsHRF/i9Q+4wTg/cPt28zMzMzMzKxbDbbx1YBNgLsj4t6IeAE4BdihmCAiroqIx/Pk1cDKw220kZYGI/VhcqUBMBWYXVg2O88zMzMzMzMzs2FImi5pZuE1vSrJVOAfhenh7rs/BZw/3H5HJRCipE2BZyKiEgehLH5BzfYV+c1PB9CEKQwMTG5/JnuYR08wMzMzMxtbzZS/HTSxf0QD3Qoa3lbEDOp3J2j4vlvSO0mVBm8bbr+jNXrCLixoZQCphqPY7GFlYE6tlYsfxsRJU7s/3OQYc4WBmZmZmdnYckWAlWkkFkEbzQZWKUyX3ndLWg84GnhPRPxruI22vdJA0gCwM/COyryIeFjSk5I2A64BPg4c0e59m5mZmVl3afZGyw9HzMxqug5YU9LqwEOkh/kfKSaQtCpwJrBrRPxvIxsdttJA0snAFsCykmYDB5ICIx4BLAecK+mmiHh3XuUdwOyIuLdqU58ljcSwOKnfxLB9J8zMzMzMzLqBuydYmTQOwJjta56kPYELgQnAsRFxm6Q98vKjgG8ArwB+LglgXkRsVG+7Gss3MRLunpA0c2JxDbyZmZmZWes64ea+H8r28154qKwvfk949yrvadv97IX/OH9cPqfRHD3BzMzMzMzMzLqYKw16UCfUiJqZmZmZmfW7aOO/8TJspYGkYyXNlTSrMO+Hku6UdIuksyQtU1i2v6S7Jd0l6d2F+R/O6W+T9IO2vxObrx+aMJmZmZmZmXW6QaJtr/HSSEuD44Ftq+ZdDKwbEesB/wvsDyBpHVKExtfndX4uaYKkVwA/BLaKiNcDK0jaqj1vwczMzMzMzMxGw7CVBhFxOWm0hOK8iyJiXp68mjT+I8AOwCkR8XxE3AfcDWwCrAH8b0T8M6f7E/DBNuTfzMzMzMzMrCNFRNte42XYIRcbsDtwav57KqkSoWJ2nncJ8FpJq+V57wcm1dqgpOnAdABNmMLAwOQ2ZHPkPHKBmZmZmZmZNWs8uxW0S0uVBpK+BswDTqzMKkkWEfG4pM+SKhcGgatIrQ9KRcQMYAZ4yEUzMzOzXtZsAGc/oDEzG1sjrjSQtBuwHSlOQeXGfjawSiHZysAcgIg4BzgnrzsdeGmk+x5rvjiZmZmZjQ6Xs8ysl43nqAftMqJKA0nbAvsCm0fEM4VFZwMnSfoxsBKwJnBtXmf5iJgr6WXA54APtZTzMeTuCWZmZmZmZtaswXGMRdAuw1YaSDoZ2AJYVtJs4EDSaAmLAhdLArg6IvaIiNsknQbcTuq28PmIqLQoOFzS+vnvb0XE/7b3rYweVwSYmZmZjQ53TzAz62zDVhpExLSS2cfUSX8wcHCD2zEzMzMzMzPrSd3fzqA9oyeYmZmZmZn1tWZawTTbwsa6V1+MniDpWFLAw7kRsW6e90PgfcALwD3AJyPi34V1ViV1UTgoIg7N86YB/0OqbJkDfCwiHm3ruxkljmlgZmZmZmb1uCLAelUjLQ2OB44ETijMuxjYPyLmSfo+KcbBvoXlhwHnVyYkTQQOB9aJiEcl/QDYEziopdybmZmZmZl1ALc0sDK90NJgYLgEEXE58FjVvIsiYl6evJo0tCIAkt4P3AvcVlhF+TVZKXLi0uShGM3MzMzMGuEWnWbWbSKiba/x0o6YBrsDpwJImkxqcbA18JVKgoh4UdJngVuBp4G/A5+vtUFJ04HpAJowhYGByW3I5sj5AmVmZmY2OlzOsl7h1gPWq1qqNJD0NdLQiifmWd8EDouIp/JQjJV0iwCfBd5IaoVwBKlLw3fKthsRM4AZABMnTR339hyOaWBmZmY2Ojzkopn1sl7onjDiSgNJu5ECJG4VC9pKbArslGMWLAMMSnoOuAYgIu7J654G7NdCvseUL05mZmZmZmbWrOjXSgNJ25K6IWweEc9U5kfE2wtpDgKeiogjJa0ErCNpuYj4J6n7wh0t5dzMzMzMzMzMRlUjQy6eDGwBLCtpNnAgqWvBosDFuRvC1RGxR61tRMQcSd8ELpf0IvAA8ImWcz9G3D3BzMzMbHS47GRmvWw8Axi2y7CVBhExrWT2MQ2sd1DV9FHAUQ3nrIP4YmZmZmZmZvV4yEUr09cxDczMzMzMWuVAiNYrXBFgZfqipYGkY0kBD+dGxLp53g+B9wEvAPcAn4yIf+dREo4G3pS3fUJEfE/SUkDxKFoZ+G1EfKmdb2a0uHuCmZmZ2ehw2cnMrLM10tLgeOBI4ITCvIuB/SNinqTvk2Ic7AvsDCwaEW+QtARwu6STI+J+YIPKypKuB85syzsYA76YmZmZmZlZPe6eYGX6ontCRFwuabWqeRcVJq8GdqosAiZLmggsTmqJ8ERxXUlrAsuzcMsDMzMzMzOzruWKACvTt0MuVtkdODX/fTqwA/AwsASwd0Q8VpV+GnBq1OncIWk6MB1AE6YwMDC5Ddk0MzMzs07jmAZmZp2tpUoDSV8D5gEn5lmbAC8BKwEvA66Q9KeIuLew2i7ArvW2GxEzgBkAEydN7f6qGTMzMzMr5UoAM+tlg/0QCLEWSbuRAiRuVWg18BHggoh4EZgr6a/ARsC9eZ31gYkRcX1r2TYzMzOzXuCWBmbWy3qhe8LASFaStC0p8OH2EfFMYdGDwJZKJgObAXcWlk8DTh5pZs3MzMzMzMxs7DQy5OLJwBbAspJmAweSRktYFLhYEsDVEbEH8DPgOGAWIOC4iLilsLkPAe9t5xswMzMzMzMz60R90T0hIqaVzD6mRtqnSMMu1trWGo1nzczMzMzMzKx79UL3hHaMnmBjwP33zMzMzMzMbKwNG9NA0rGS5kqaVZj3bUm3SLpJ0kWSVsrzt5Z0vaRb8/9bFtaZJGmGpP+VdKekD47OWzIzMzOzXuSHKGbWbQYj2vYaL40EQjwe2LZq3g8jYr2I2AD4I/CNPP9R4H0R8QZgN+A3hXW+BsyNiLWAdYDLWsi3mZmZmZmZWUeLNv4bL43ENLhc0mpV854oTE6G9A4i4sbC/NuAxSQtGhHPA7sDr83pBkkVDNagZoYjci28mZmZ9aJn51zhco51rGZ+m80ONWo2nkYc00DSwcDHgf8A7yxJ8kHgxoh4XtIyed63JW0B3APsGRGP1Nj2dGA6gCZMYWBg8kizaWZmZmZmNupcEWBl+mL0hFoi4mvA1yTtD+xJGooRAEmvB74PbFPYz8rAXyPiy5K+DBwK7Fpj2zOAGQATJ03t/k/ZzMzMzEq55YD1Crc0sDIePSE5CTiXXGkgaWXgLODjEXFPTvMv4Jk8H+B3wKfasG8zMzMzM7Nx54oA61UjqjSQtGZE/D1Pbg/cmecvQ6pA2D8i/lpJHxEh6RxgC+DPwFbA7SPPtpmZmZn1gm680Rqt1hGj+Vm4RYfZ+Ejh/LrbsJUGkk4m3ewvK2k2qUXBeyWtDQwCDwB75OR7Aq8BDpB0QJ63TUTMBfYFfiPpJ8A/gU+28X2YmVnW6wVwB4Y16y0+ThfwZ9E//F33j8Ee6J6g6PDADJ0Q06ATCqidkAczMzMzs37SCRXx/VC2n/fCQxrvPIyWV71ivbbdzz7wr1vG5XNqR0wDMzMzMzOzvuZAiFam0x/SN6KR7gnHAtsBcyNi3Tzv28AOpO4Jc4FPRMScvGw94JfA0nn5xhHxnKRLgRWBZ/OmK90WzMzMzMzMuporAqxML3RPaKSlwfHAkcAJhXk/jIgDACR9EfgGsIekicBvgV0j4mZJrwBeLKz30YiY2Zacj6F+aBJkZmZmZmZmVm3YSoOIuFzSalXznihMTob51SfbALdExM053b/alE8zMzMzMzOzrtIX3RNqkXQw8HHgP8A78+y1gJB0IbAccEpE/KCw2nGSXgLOAL4TvfAJmpmZmdmIOdizmfWywR645R0Y6YoR8bWIWAU4kTTUIqRKiLcBH83/f0DSVnnZRyPiDcDb82vXWtuWNF3STEkzBwefHmkWzczMzKyHuM+4mdnYa8foCScB5wIHArOByyLiUQBJ5wFvAi6JiIcAIuJJSScBm7BwnIT5ImIGMAM6Y8hFMzMzMxsdbj1gZr0seiAQ4ohaGkhaszC5PXBn/vtCYD1JS+SgiJsDt0uaKGnZvO4ipNEYZo0822ZmZmZmZmadLSLa9hovjQy5eDKwBbCspNmkFgXvlbQ2aUjFB4A9ACLicUk/Bq4jBUc8LyLOlTQZuDBXGEwA/gT8ahTej5mZmZl1kWa7HLhlgpnZ2Gpk9IRpJbOPqZP+t6RhF4vzngY2bDp3HcIBeszMzMzGn8tZZtZtBnuge0I7Yhr0PF+gzMzMzEaHy1lm1st6YcBAVxqYmZmZ2bhx9wQzs842bCBEScdKmitpSOBCSV+RFJUgh3ne/pLulnSXpHeXrHN22bbMzMzMzMzMeslgRNte46WRlgbHA0dSNTyipFWArYEHC/PWAXYBXg+sBPxJ0loR8VJeviPwVFtybmZmZmZdzy0HzKyX9UX3hIi4XNJqJYsOA/YB/lCYtwNwSkQ8D9wn6W5gE+BvkpYEvgxMB05rNeNmZmZm1v3cPcHMrLONKKaBpO2BhyLiZknFRVOBqwvTs/M8gG8DPwKeaWD700mVC2jCFAYGJo8km2ZmZmbWQ1xhYGbdpi9HT5C0BPA1YJuyxSXzQtIGwGsiYu8arRYWXiFiBjADYOKkqd3/KZuZmZmZmVnf6YXuCcMGQizxamB14GZJ9wMrAzdIeiWpZcEqhbQrA3OANwMb5vRXAmtJunTk2TYzMzOzftNsVwYzM2td0y0NIuJWYPnKdK4I2CgiHpV0NnCSpB+TAiGuCVwbEX8DfpHTrwb8MSK2aDn3ZmZmZtbV3OXAekUzv2VXgPWP8Rz1oF0aGXLxZOBvwNqSZkv6VK20EXEbKcjh7cAFwOcrIyeYmZmZmZmZ9ZNo47/x0sjoCdOGWb5a1fTBwMF10t8PrNtY9szMzMysl3XjE9fRah0xmp+FW3SY2UiNaPQEMzPrXL1eAG/m/bmQbGZmY6Ubr782+nqhe8KwlQaSjgW2A+ZGxLpVy74C/BBYLiIeLcxfldRF4aCIODTPuwBYMe/zCtx1wcxsVPT6jXKvvz+zfuNjegF/Fma9pxdGT2ikpcHxwJHACcWZklYBtgYeLFnnMOD8qnkfiognJAk4HdgZOKXZDJuZmZlZ72j26axvrM3MxlYjMQ0uzyMeVDsM2Af4Q3GmpPcD9wJPV23nicI+J8E4RnIwMzMzs47gSgAz62XjGcCwXUYU00DS9sBDEXFzajgwf/5kYF9SC4SvlKx3IbAJqRXC6XW2Px2YDqAJUxgYmDySbJqZmZlZh3NLAzPrZf3SPWEhkpYAvgZsU7L4m8BhEfFUsTKhIiLeLWkx4ERgS+Disn1ExAxgBsDESVO7/1M2MzMzs1KuBDAzax9J2wKHAxOAoyPikKrlysvfCzwDfCIibqi3zZG0NHg1sDpQaWWwMnCDpE2ATYGdJP0AWAYYlPRcRBxZWTkinpN0NrADNSoNzMzMzKw/dGPEeQ+5aGaNGsuWBpImAD8jtfyfDVwn6eyIuL2Q7D3Amvm1KfCL/H9NTVcaRMStwPKFjN0PbJRHT3h7Yf5BwFMRcaSkJYGlIuJhSRNJtRrdd4UwMzMzs7byzewC/izMes8YN5vfBLg7Iu4FkHQK6WF9sdJgB+CESLUZV0taRtKKEfFwza1GRN0XcDLwMPAiqbbiU1XL7weWLVnvIOAr+e8VgOuAW4DbgCOAicPtu06epo9G2tHcdrel7ZR8dELaTslHt6XtlHx0QtpOyUcnpO2UfHRC2k7JR7el7ZR8dELaTslHJ6TtlHx0QtpOyUe3pe2UfHRC2k7Kh19DPz9gZuE1vWr5TqQuCZXpXYEjq9L8EXhbYfoSUiOA2vsd7zc+wg9r5mikHc1td1vaTslHJ6TtlHx0W9pOyUcnpO2UfHRC2k7JRyek7ZR8dFvaTslHJ6TtlHx0QtpOyUcnpO2UfHRb2k7JRyek7aR8+NXcC9iZoZUGR1SlOZehlQYb1tvuAGZmZmZmZmbW7WYDqxSmVwbmjCDNQlxpYGZmZmZmZtb9rgPWlLS6pEnALsDZVWnOBj6uZDPgP1EvngEjGz2hE8wYpbSjue1uS9sp+eiEtJ2Sj25L2yn56IS0nZKPTkjbKfnohLSdko9uS9sp+eiEtJ2Sj05I2yn56IS0nZKPbkvbKfnohLSdlA9rQkTMk7QncCFpyMVjI+I2SXvk5UcB55EGJribNOTiJ4fbrnI/BjMzMzMzMzOzhbh7gpmZmZmZmZmVcqWBmZmZmZmZmZVypYGZmVmTJK063nkwMzMzGwuuNOgyktYd7zxYd5P0/eHmSXp5vdfY5XahPO3VyDwbW5Imj3cexsnvK39IOmMc84GkAUlvGc882MhJmiDpt02m37uN+++48/1okLR6I/P6iaTFJa1dY5krRvuEpHMknV3rNd75s87Q8YEQJe1Yb3lEnFmyzluBmyLiaUkfA94EHB4RD9TYx61A9QfxH2Am8J2I+FdV+rcBa0bEcZKWA5aMiPtqbHtdYB1gsUKeTyhJd0lEbNXAvCuBScDxwEkR8e+y/RbSrwB8F1gpIt4jaR3gzRFxTEnaAeCWiGioYkLSq4HZEfG8pC2A9YATyvIk6cslm/gPcH1E3FSS/lWkz/hPkhYHJkbEk4XlTf8uaryHJSPiqUbSDrOdJYD/B6waEZ+WtCawdkT8sZW0De677LOdLyJ+XJX+hoh4U9W8WyJivcL0faRjQsCqwOP572WAByOibkFruGNE0hEMPeaKef5iyTbL8n1jRLyxMN3UZ5HXEfBRYI2I+FYuKL0yIq6t8d7+C3g9Cx/T36pK03Q+mpHPcQcBryKNgqO02VijkKbsvEYhbfH7Hsl59i3A0aTvdlVJ6wOfiYjPNfE+Gj7+JG0dERc3uu2S9ZcGlouIe6rmrxcRtxSmd6y8X0kvi4jHa2xv/m+v+nfYQF7KPu//ALdGxNyc5jXAChHx16p13w7MKXkff4uINzew7zfVWx4RNwy3jRrb3Swirm532qr1XgasycLH3uV10r8FWI3CSFFl19+cdgKwQlXaB0vSrQV8lQXHXiXtliVpFwU+WJKHb5WkvRB4X0S8UOv9VKW/NCK2GCZNQ+eAZs/3ks6psV1IG96+JC8Nlxea0WQZp+wacn1EbFiStuHvLqdvpjy0HLAvQ8uGWxbSjOr5O6/3PuBQYFJErC5pA+Bble+v+HlJOiMiPlhvPy0c11MZejwNOa6bPPYaTpvTLwZ8iqHX9t0Lad4NLBURp1et+1Fgbtn1qZnfZ04/XNmp4bJFM+d6SZvnP3cEXglUKjGnAfdHxP+U5LWpslNep6HzrHWmbhhy8X35/+WBtwB/ztPvBC4Fyk6GvwDWz4XYfYBjgBOAzUvSApwPvASclKd3yf8/Qbo5r+QBSQcCGwFrA8cBi5AOrrdWbzSn3YJ0YTgPeA9wZc5LJc1iwBLAsrlApLxoaWCl6m1GxNvyTebuwExJ1wLH1SlMH5/z+bU8/b/AqaTPpHrbg5JulrRqgwfxGcBGuXB7DGnMz5NIQ3hU2yi/zsnT/0UaR3QPSb+LiB9UEkr6NDAdeDnwamBl4CigWIEykt9FmdtJhaTKvt8A/AqYSvpd7Fu5aZB0bURsUmM7xwHXA5VC+2zgd0BZRcCwaSU9Sf0Cw9KFeUvl/9cGNmbBWKzvA+ZfeCV9FvgcsIakW6rWX+jGpFJIlHQUcHZEnJen3wO8qyRfCzLY2DEys942qrY3DfgIsHpVjffSwL+qkjf0WVT5OTAIbAl8C3iS9NveuCQvR5GO13eSbph3AsoukEuVzCtV57sGoOq7rjgG2Jv0O3qpxqrbNZoHRnY8HQa8m/wZR8TNkt7RxD6h6vgbxjGM8FiV9CHgJ8BcSYsAn4iI6/Li40kVyxVfZ8H7vaRqWVHU+LsRnyId/3/J01sAVwNrSfpWRPwm53dIQQ14Ni97X9X8iyR9EDgz6j8N+FGdZUE6DgCQ9N1KYbGBSpufkz+rBiowmklbyct/A3uRrgc3AZsBfyvmtyr9b0jXj5tYcIwEhetvIe0XgAOBR0jngkra9arTks7VR5F+e7WOvYo/kCvHgeeHSXs/8Nd8jnu6MrNOBeNfJR1Jup4X0xcrfRo6B4zgfH9oI9ut0nB5oeqcOIl0DXm6xrnweIYp40h6LelmcErVDfbSFG4QqzTz3UFz5aETcx7/C9gD2A34Z1Wa0T5/Q6p43iSnISJukrRaYbkKf6/B8EZyXH8f+DDpWlA8Tsuu180ce82kBfgNcCfpmvYt0s3wHVVpvsnQ8y6k68RZQNn58XgaLIM3WHZquGzBgnP9Ynm7N5O+0/WAa4C3VRJGxGU5D9+OiOJ1/BxJLZed8rabOc9aJ4qIrniRbqhWLEyvSCoclaW9If//DeBTxXk10v+11jzSk5/i/JtIB92NhXm31NjuraQuIDfn6RWAc6rS7AXcR7oo3Vd43QzsWSfPE0i14A+RTmx3AjuWpLsu/1/M7011tvtn0oF/CemidzapEFHvc/4q8IXq/VSlvZBUY1qZXhK4AFgcuL3kM55Uledba2x32N8F8OUar/8HPFaV9kpgW9ITlq8AtwGvrvfe8rKZJZ/zza2mbfIYuYhUC16ZXgq4oDA9hfTU5GRS7Xvl9fI627y+Vv7rrNPMMbLzcPNyHrcg3SBsXni9idQCpenPosbvuJHv7paq/5cELmr1u8vb+hapUmcpUmH2s8A+NdJe0459lmy3mfPsNY18bk0ef2fXeJ1DumkY0bGaf5Mr5r83oXC+LEl7Y9nfJe/rJVLF8pPAvMLfTwJPDPM5n0NqRVCZXoFUsH85MCvPm1Vn/SHnw7zfQeCFQl7q5qOB38MNZX/XSNvQ59Zs2uJ7JhV+b8rTrwVOrZP+DkitKRvY9t3AKxpMO+ScWCdtze+wJO2BZa866f9S8vpzi9930+f7Zn9LNFBeKFn3/cB3aywbtowD7EC6CftX/r/y+inwlla/u2bfX+VzpnBdBC5rw2fc8Pk7Ly87hxfz1PDxX7KdRr/bu4BFG0zbzLHXcNpifllwbV+k+niiRjmm3rJGfp/F+TRYdmryvZ0CvKEwvS5wfI20d5BaDlSmVwfuqJG24bJTXtbwedavznx1Q0uDitUi4uHC9CPAWjXSPilpf+BjwDtyc5hF6mx7SUmbRsQ1AJI2Id0MQCoMFr0QESEpctp6/XmfjfT0fl5uGjuXqtraiDgcOFzSFyLiiDrbIu9vPeCTpBrqi0nNGW+QtBLppqq6RvlpSa8g19pL2oxUe17LN4fLQ8GL+Snwbiyofa31Oa9KKszOXxd4VUQ8K6m6Fv/5iHghtXwCSROp/SSvkd/Fd4EfMvS7hKFxPZaMiAvy34dKuh64QNKudfIA8IJSN4rK5/xqaj+daCYtOc3yLNxkrqwlSPVn/AKpkqBiAulm4vMl2395RDxWss1HJX2dVNsdpGOq+ul+tWaOkf1JTwRqzovUregBSe9iwTG1Fumm4dYa2x3usyh6MZ8jKvldjgW14NWezf8/k4+5f5EuqqUaafJY8O6I2LQw/QtJ1wA/KEn7F0k/JB3v8387UdK0PB/zRwCvI1XGTaD2U7tmzrP/UGr+HZImAV9k6JMZaO74ezvpN1bdZUGkm/2iZo7VCZX3FRHXSnon8EdJK5ekXVzSG3PeFst/z3/iVvmMI2JCyftp1GoR8Uhhei6wVkQ8JunFPK/WE1BIla0LiYhmnkABoAa7zzVoILeWGyj8XfzcHhth2ornIuI5SUhaNCLuVI2+2NksUjPbh+ukqfgH9a+LaEHf/nMkfY70ZLF47JXl+SpJb4iIWuep+SKimWsvEfHORtM2cQ5o6nyfWz1+j6G/obKn0s2UFxYSEb+XtF+NxcOWcSLiD8AfJL05Iv7WyD5p4rvLmnl/lWP8YaXubnNILWiGGMXzN8AsSR8BJuTv8ovAVYXl60t6gnRsLl74G4a2eISRHdf3kj6nmmWgZo69ER6nsOA7+Xc+L/4fQ8sMi0maGBELXcty67Uh5+SsmTJ4w2WnJssWry3+jiNillJXlDJ7A5dKujdPrwZ8pkbaZspO0MB51jpbN1UaXKrU5+9k0g90FxY07az2YVJz5k9FxP8p9bP5YZ1t/zdwrKQlSSe4J4D/zgfs96rSnibpl8AySs3odyc1fyozU9Iyefn1pIJwrb4+x+aL9aoRMV21+7kfmbf3PxFRuYEhIubk9at9mfSk7tWS/gosR2pSXSpyE6UGfZLUtO7giLhPKaBQrWBOJwFXS/pDnn4fcHL+jG+vSnuZpP8hXaS2Jj19PYdyjfwubgB+HxHXV6+s1OS1apamRMR/ACLiL0pNfs8gPQWs5UBSy4lVJJ1Iak72iVbTStqe1MRsJdKNxatIN2avL0n+G+BaSWeRPosPsHBT3OtZcIOkqnWD8uaH03J+z8rTl+d59Qx7jCg1e30vMFXSTwuLlqb85rKy77fngsglpC4OHyY1I6w23GdR9FPS+1tB0sGk46PsWIJ0o7kM6XxyQ9720TXSVvIxXJPHipeU+kaekrc7jdrNKiuVCxsV5gXlTbWPJB0Xv8vpPw68psZ2mznP7gEcTuoeMJvUumNIhRTNHX9XA8+UnYck3TV0VsPH6pOSXh05DkBEPKzU7/j3DD2W/g/4ccnfUPiMlWKTvBgRL+bptUm/6fsj4izqu0LSH1lQOfZB4PJ8Pvx3nnedpE9HRPWx8ynSsVyZfm2+gS7tRlFWkZTXO5Bhus8Byyv1oVXh7+K2i5/NlJyvyrmluN/q80szaStm52Pv98DFkh4n3WxVv69Kf/ulgNuVuvAVbxq2L6StvJ97Sb/9c6vSFt9f5fxZyfNXa+VZC/qjTwQ+mQvgz1PeH/1tpCd7J+Tp01nw+/1ORFSamlfSr0y6Obyy8B4qDzlOioi7qz8TGj8HFM/3wfDn++Ny+sNITeE/ydBrS0XD5QUt3IVgIOe5VqX9sGUcFWLo5Bv7hUQhhk4z391I3x/wHUlTSK2tjiBd92oFthyt8zfAF0jN5p8nldEuBL5TWTiCitGGj+vCd/IMcJOkS1j42CvGNWr42GsybdGMXLY4gPR7WpLUWrnoTOBXkvaMiKfz+5hMKkPU6gLSTBm8mfuLZsoWd0g6moUrA0vTRsQF+f7jtXnWnRFRq0KnmbITNHaetQ7W8YEQi/KF5O158vJaBbN8ED8XES9pwRPJ8yuFuzrbn0L6TP49TLqtgW1IJ6ULo4HgXEr9xJaOQsCtquWnkk52H4+IdZWeRP8tIjYoSbs4qXKhuhBda98TSX2kBNxV73NQc30Jm8qLpA1JfagEXBkRpf3alQIyforCZwwcHTV+rJI+AFT6YA35XeTC/L8i4tGSdVcoPvFTqnW/N6qC+eSKpwMi4tN13t8rSP1sBVxdtr9m00q6mXST8qeIeKPSE9JpETG9RvrKZwzps7ixVh5G03DHiFK8kQ1IF7vihflJ4C9REnxOOSiTUr+4xSPiB6oTgK6Zz0Kpz2slZsafI6LWxbe4zqLAYpWb1hppbszf2y0RsZ7SE4kLozxw02qkm/C3ko7BvwJfioj7h8vLMPmcGREbqRDsUtJVEVEabb+R86zS04VfR8THGth/w8dfM5o5VvPv7enqG6r8fXwoIk4cwf4vJ1VM/12pH/O1pL7K65CapNZ6MookkSoK3ko+HwJnFM9xSgG0ziK1kqlUEmxEOi9/ICL+L6ebkSuay24Oouy3lte7FVif1LR0/by/oyOiOoZPTc0+HW8XpaBdU0hdjl4oWVZTsUJqmPcXUR6wcLGIeK7ePKVAvvU2/EAh7SWk5uy35+lbSZXIk0kPB7at2tfJwImVBwq5Mm0GKdbKayNiSCVqI+eAZo7pwjrXR8SGkm6NiDfkeVdExNtrpG+ovCDpuMLkPFK8h19FDhJakr5uGUfSbvX2FxG/LqRt+LsrrNP0Z9eo0Th/F9K+cZjrYisVo3U18510ivw7+w7pQeMDpN/bKqT4BAfUKls3UgbP14SVSfcrw95fNFm2WIzU3XF+ORn4RdU5a8fq9YqidjDNhstOtc6343UdsRGIDugj0e4XqYC1BOkJ2D9IBa8T66RflNQy4X9INzDfAL7RhnyIVKP3jTy9KrBJjbQN9XMnPaG/C7gvT29AjZgDeflipJrOM0lP4L5EutFp9D28n9p9CYfNC6miBNKTkyGvOvudRAqO8gZSZN96eVwh52U7YPlx/N3tSHoq+SNSob56+ZvqvYb5XdwMDOS/r62ThwmkVgmrVl6FZa+tl4+q7ZxD7f7lNX9vI/jMFmki7Y2k4HFXA6/P80pjXQz3WdT4br5IevJS+l3kdEuQnkT8Kk+vCWxXJ/21+f/LSf0IlyXd6Lb6uU3Jv7WZ+fUjYEqNtJfn4+kEUleHvWlPDI0Lhzs2a6w3uc6yzVrIT1u2Swri9MrC9MdJQdF+WjxnFX97wLeBn+W/J9X7XY7gfb0z/y6/AGzZ5Lo1j6/Cb/N60pNOAbe1kM9XFX+DOd+H59/bpJGmrVrvbcAn89/LAavXSfv9Rubl+cPGVinMH9K3u2xenv+b4eaR+zwXps8s/F0Wb+mGqukbC39fUSMfDZ0Dmj2mSRWbA6TyxZ6kFl131UjbVNmliTy0VMaps91Xk/vak1rkfBFYpk76hj87UpeBS1gQv2Q94OutfHcjfI9/IT2t/jb5mlqy7zXz368BHiO1jLgEOKQkfdPHNalybEJhegKwRI20ny9+B8DLgM+1mjYvX4F0839+nl6HHBOtJO3ipLLpG0gPMOp9xs3kuZmYDW0tW7BwrI/q17F11muo7FS1zlIUYpz51T2vcc/AsBnMwZxKXjWDPLEgOMcXyIHEqB/87wJSNNN9SM3F/h/w/5rIT6ViYo2qtL8AfkYOIpJPFtfV2O5V+URUyfurKbk5JBXwptBgoBTgtHwifGd+zQB+1+R3cHWN+WV5qQ4c+cf8/32kpkmV1321TnCkeA3/IEX0vQx4EHhPjbQfItX4/pp0Ub0P2KlG2rVITb0uIgV8/DM1Akc1kzan/3lO+8n8uoB8E1FI85c6r1r5+BOpmdwRpCaHhwNX1Uj7BeBRUkC4W0j9/YtBjWbUyUd1wJ/N8+tw0rHxvvw6idqVSJVjo/oYqXesrgmcTuqiMv/3USPtO0iVFvvm6TWAn47ks6hK+428/CBSTI+bqV2Aq5wnKoW9xal/bvlv0nG/eX5vc4E9aqRdjlRxOQM4tvKqkfaMnNc18utAagcsfFXO59I53Y+B19RIuyPwd1K/w+G+u1+SRkA5gEKAwzqfxVvy9/xgnl4f+HlVmmLgrb/V2tZobpfUpPblhd/cHFKrgG8DpxfSFY+tvwLvL0zXLdQ3+Tm/i1Qo+yI1grZVpRepddLRwCN10v2cFERyj5yXG0kj8RTTfJoFNw3Kv8n/kI6pN1alvYY0rBikG8JHSdfSX5NaMIwobWGdA0mVmf+bp1ei5Ka67Dsv+84aSFt9c/5KYENSs943sqDCdQtSE95ht0u6IaoO/Pv3Ou/h7pJ51eu/vNaywvyGzgE0f0xvTLo+rUy6uTiTGhV0NFBeyPN2yMfTY/l1EfC2vGxKSfphyzikG6oDScfQkqSy2SxSZWCtc+FNpC4KrwHuIXXBOK/OZ9HwZ0cq12xS9VmUBl5s9LvLaRs+r1T9rr+YP/NbKVz7aLJilJEd11czNEh2rTLOTSXzbmw1bV52Pqk8WQlcPrHGe1yR1NrgzPz6H+oE92syzz8DNq73fRXSlpUtPlOV5lbSubr01ch+hslDw2WnnH5d0nXmgfy6npLKKr869zXuGRiVN9X8E8lmIhx/kxQUpBLhfHo+cD4MXFqVtpmo7FuTLiT/JDVxvR/YoiRd3Wi3JenLnibUi266Y+G1E3AINQrZjeSFBRf7Zlo33EnhokiqQKlVKLuZQusC0o1Xrc/4ZlITrU1Ihb8NgQ1bTZvT3wYLInWTnr6M+KldYTuTSQXNiaQAS1+kxgWKUYhMS2reOOy8FrZ/Jalp2y2kwtFBwDfbsN1moqHfUfx9kgpotaIFj8rIF3k7VwHfJxVcPlh51Uh7UyPzRvi5va7BtAeWveqkv4bUlLP42c2qSnNj2d/D5KOt2y1+n6RC3EFlnzGpf+ihpJuDR8hPx0g34sNVGgz7Oef3dAPpuvBj0k3LZaQKyUWB/65Kvympku9BUvyc3YCXNfgZrgasVzJ/Frm1Aqk13vXAK0gVGVdUpS1WohwK/CD/PcDQ60LDaYufPQwfWZx03r6VNAxhsZB8H1UtDklxHI7I399PC6/jqaq0z5/nX8hdqAqvs6kauYgUzLU4qkblBu5fwPeq0p4D/FfJ+9gOOLfG732tkvmvrc5zsy+aPKab3HYj5YXPkVpObUkqXy2d/76KVMZqqDxTPY9U8fDd/F3fTurn/lpSpdilNfJbKb/tQwOjPTTz2dHkqFZNfMYNn79L1n0DqZ/8C2XfDw1UjDLC47qReZXts3A5awI1ylnNpG30OyHdoP+DdB+wPamCq3KzvDrlLYuayfPtpHPGPdR42JHTfI08UtAw3+mr6r1qrDOFxlsxNlx2ysuvAt5ZmN6CGhVEfnXmq5sCITZjL9JF+6yIuE3SGtQPBtNMlNxtY+EI5zMkXR0R31IK3lfUcGTRiLhY0g0s6Oe+V5T3cx8u2m21GyVtFrnfr6RNSSf/Wopj0Fb6Eu5QI20jeTmcdMN9FbXHO682Nxbue1ypRS0zEAv3c/wXQyOyV8yLiF80mIdm0kJqdrkqqfYUUoG/VvyKmaQndidHSd/9osjBdrLh+vg1FJlW0sdr7OuEktnLSVojIu7N665Oqpipt/1DSU/IqwNcllk8Ii6RpEh9RQ+SdAWpwDWsSn/ukkXNROm9n9TEtdK/b1HSRbtMUyNfSKoOpARAlPSVJt107ttgnp+V9LZYEAztrSwY2aE6D/fB0CBiUR7h/JFoIJ5DXr/pfogR8Q9poThp1YEeRxJ9u93bnaAFEbK3IlUMVxSvmZ8mXWtWBbaJiGfy/HUYfhz7Rj7nn5Fa0hxfnJmP30oE+KOVAlB9iFRZcDIpTsjMGKZPcI4F8+eI+E9E3C9pGUnvj4jfF5LNiwX9b7cDToiIfwF/klQ9qkfxC9iSdA0m0mgnQ3bfRNqKRiOLn0R6avg9oBhX4smS388cUsF4ewrBJUk3+AsFpsuf568lfTAizqiVyZz2e8D3JH0vIvavlzbv51xJO7EgcNyGpBY025WkP5AUkPXgqvT/Q/o9DtHoOaDZY1opZtRXSTch84+NKI+j0Uh54QvAW6u+pz9Leh8p2OqXS7bbSBlnhYj4n9xv/IGIqATGvlNSWfBWWDAawsdpYLSHJj+7R/O1o/Jb3okao3yM1vk7b/t1pMqYnUhlp1NILQMqbsnX84dILS4uyustU2uThb8bPa6flvSmyAFblWIRlV7L8v5Pk3QU6TPZg1SJ2mraSj6GG+Xgh8D2sXAciD8oBVy+mQUBo4subCIf76mTv4pppACXF0l6lHTOPzUWHjUDGBI7ZQVSyyBIlYu1ytTHkiqLP5SndyW1ItqxJO39NF52gtSFcP69WERcWuc8bh2oJysNIuJyUj+fyvS9pAtULW8DPpFPzsNFyR2U9CFSk2pYOApq9Yn9p6STyPIaJrJovpi9h9TF4VuSVpW0SURUj7ZQjHZ7MumE9O06721T4OOSHszTq5Iiqd5a9h4j4pN1tlWtkby8mIMarayFo+RX9lf2vdwm6TxSs8MAdiZFEt8xr1MMyHKBFkQLhnQBPK9GfpsZgqfZ4XpeQfpcK9/XxsDfJJ2d19u+kHYXUheG63IFwnHARRExpGCg5gJTNhqZduPC34uRboxuoHx0gb1pfPidijtJEYYnkt7byVE7WOBzSoEv/y5pT1LhZPliAi0YQqmaSEGZyjQTpfd50m/uYtJnvTVwZeX3WvUbPZDGR8mA9LSzYjHSTUCtQt0fJb03Imr9fos+S7qBmUL6HB6rk4/iCAuLkY6nWp/pTKWgrL9n4c9tSBAkpcB7ZYXZshsGaGyIxik0H1W/3ds9mTSCy6OkwusVAErBDuf/jiONXnOIpL0i4ubC/KskFY+xMo18zq+trjDIaU6Q9F0WVMJOJ1Va/oLUHey5yo31MA6MQjCziPh3DlT1+0KaQUkrAo+TzhMHF5ZVDzH2Z0mnkUaceBmpSxd5/RdqpH24gbQVDUUWz+ea/5Cj/mvBcLVLSloyCsPV5u/tZkknxTCBkgvrnKE0TF71UGdDKgIjYv9cQbVmVdpi+eRupaGUP8qCkTwuJ3VjWijgYk5/Qb4W7sOCcs0sUmuHWTWyXfccoCZHcCj4HXAU6XuoNdJLRd1I/YX3N+QaGxH/kvRAjYr8Rso4L+XtRD6ui0of5NDcaAiVh0L7MPR3UXY+/DypG8VrJT1EagVTNgoQjNL5OzuOdL7bJiKGjETCgorR1WisYnQkx/VewO8kVfa/IqkcV+arpPLHZ0nn8ouoPXpRM2mhsVEOloySwJERcZOkR0i/mWr7NpGPYc/blXMWsH+u2PgwcI2ku0llrSHnxHzP8kNSl18BR0j6akScXp2W1ILhg4Xpb0q6qUZ2mik7Adwr6QBSixZIMd/uG+49W+foqtETGtXkybtmtNwoj5K7Bunp+ZtJB8nVpBurh0jN1ytP/gZIrQYeIxW2BFxSqxZY0i9IF68tI+J1uaBxUUQMV/isq9Z7q6h+j0rDOR3BggjuV5JaPcwe4f6XJTVl/T5Dh6+pPL2pXue4+lleeBzaXICqjMpQb1SNspNTlNXYN5M2p9+8Tp6J8iHkBkg3kZXv/ljg8DoVE0h6PymYZnWrlhFHps03nr+pqtgoLl+UwvA7pKA+w0a8V4q0/ElS4f2vpOCBf6lKszHpBm8ZUoXTFFKTxqsLaV5iQaTi+W8rT0+NiEkl+274s1CDUZzz97UTKQhUQ6NklOxrUVLwr3eXLHuS1B3lBRaMGR01Kogq6yydEz3RaB7yeldGxNtK5pcde0OOuZx2w8LkYqTuFPMiYp8a+1yWdO58F+mJ/4Wkc0vNceAb0e7t5puDFUiF14tiwdBaa5EKjTdUpb8hIt5UNe/GqDGqR14+7Ocs6e6IGDK0Wv4d3hURa+bpCaRo29NIT/f+QvosVomq8cSrtjM/Gnth3vwo+Hl6O1Jf7QnAOZFHpMjnu30i4r8KaUUqwL6S1Kf8oTz/jaQuZBeWpF0ROK1e2kL6hiOL53XeR2pmu9BwtRExZLhapSff3yPdDBXLDGXXhqNIAVHfSSr870R6cvepkrT/TbopWpnUvWIzUne/IWURSXuTPreGrrUaJvJ9A+vPPweoyREcCtu4PiI2LFs2wjxdA0wvVsLl+euTYvJsWrLOsGUcSf8mVcSINLJApdJGpC6UL2tD3i8ixbz5CqmyYTfgn1HVeiwfr4dExFeVnrIORMSTTe6r5fN3k/vbMKqGzJX0vog4p2pes8f1BFLF15EsGF3gzrIKvHzeuyUi1m0gvw2nrcrHEdQfheMOUlyZx6vmv5wUX+V1jeyvTj5uZUHZZjFSl4e7ys5ZVettQeq+tk5ELFqy/GZg68itC/I90p8iYv2StH8DvhoLt2I8NCLeXJK2obJTIf3LSN055pfXSd3/6ra4tQ4SHdBHot0vUk3ep0g3I5uTbsbKIimPKLJ/E/loKJBXTls3/gEtRrMnPb1dleGjyF9MutGbmF+fAC6uSvOTenmqsd31R/H7HvfRE0iRoxvqP5zTr0c6yd9FapGyKalZ4E0NrFsamLKwvKnItKTWCzX7oeU0U0hP9v4EPNTANieQurX8nvSEd9/8ezllBJ/t32v9ZoF/tOG72448MkUDaVuK50B6+lIz8FkD638s///lsleNdd5UeG1EKtC2JQ5Dyb4ua3H9VzGCqPrt3C45gjWpkrfeNqfl3/TjVefAv5AKZK1+loeRnuBOLsybTHpCeXiNdRYj3cSeQeqnf1Kd7R9Luql+NamlxWHA8SXpJgFvr5o3uewck4/7lt97jfw2HFk8p7+Z1ALsxsJ3PqNG2oZjq5D7GBf+X5JUuVSW9tb8ndyUp19LakpclvZAUmycK0hPolcY5v39hTqR76vS1j0H0OQIDoVlB5HiEKzIMGUnUtlimcL0y0gVP8U0byNVEB/Egmv6N0nNoN9WY7uHkm6W6r3/zeu9qtKeVvjubql+Dff7ZOF+/aXnQ+oEVW72uxvJq857LA0YTGqZ9YbC9DRyjIpWX9SIKVEj7YnUKb+ONG2j+SC16rou/26Wyq8tSHFGptdY5635t/+/DBMEvMZ3/8sayzYmnb8fIMW6+SywbI201QHKB6rnFZatTzp33p+3fSM1yu80UXbyqzdePdk9gRQA7RilZqOXkZqaDnnSS2oitx3ppqZSu1cRlDSFVRrv9FMMbcVQVpN7kaQPki7AMUyeh4t/MFwf2VKSticFMlnoaQsLmkFWWy4iirXVx0v6UlWaStOiZvI0Rynmw2os3Pex7Almw60dmml2pTSObXGs2ktJJ+SyWu2G02avJHU3uIFUGL+w1ncu6Xrg36SIz/tFRKUZ4TW5VreYttiPbIBUaKi13XVJ383L8/SjwMcj4raqdOcUtjFAerp2Wsn2Fif19f0I6eK1FGkIzsur01at92NSge/PpJEWKl02vq80pjjK3TZqiYVbPfyEVMB8sCTpQv2q8zH036Qne+dHxFWFZV+PiCHNYUndRQ6XdAYpeny9PqEXS/oK6YnS/K4HUaN1SOHJAaQbquVIfc5L5eN1/m8u8ljsBZX+f0uVrF7rHPOjwt+VOCUfKkvY5LFXbCI7QOpX/coaeSi20tosb/tvwN6R42Vkp5GGbfuPpA1IzZ+/R4rE/XPSdzva2x3ILVXWkjSkD3Us6OJyFakZ7rIs/Bk/Se14JvtExA8kHUF5145ic859ch4fkFRpEbYqKbbJkJZGef3nSF3nTpe0FOX9UCu+QIr0fioLms0O6d8dES8oxS94c2He09Xp8vyXJD0jaUrU7pI0Xz6/fZ9Uqa38iihvXXO1pI0j4rrhtpu9GKlZ+4CkgYj4i6Tv10jbTGyVSn/rZyStROoLvnqN7T4XqbsIkhaNiDuVWmANEakV1DeVuip8mFRumR0R76qR/p2SXkk6lmcotTo6tcY5brhzwDJV2y7+blao8d4gPU2H1BR8/uqUdyNaNiL+XdjH40pdR4r7vVLSJqTf4SdIv4fbSCMy/F+NPAzbHS4iLsvXhl9HxMfqvB9YEBeiLJ5EPZWywcNK3VfmkK5DZW7M18DfsfB1pKwbwWicv5t9jzuRzikfJVXsfJzU4qdUk8f1XyUdydBr6g0laVckNYe/tiptWSvJZtI2lI+ImKHUjeLbLChD30bqwrNQq4uCY0iV09czfBeehUTEDarq6qbUNe3DpMrqU0gxQIZrndRwN95IrXzWV2OtGBsqO0n6SUR8qarsWdxnre/EOkyvdk+4OiI2ywfJT0kn79Mj4tVt2PbvSBepj5AK/x8lPaXdqyRtpbnxPFKgkJonznwy/jDp5uzX5PgHEfG7FvN7M6nJ6p8i4o2S3glMi/LgcUj6EylydOXkMo00LvZWJWn3iojDh5uX519FeoKy0IkzSgJKKfWPOomF+z19NCK2rvH+Gm12dTTpqXqlydSuwEsRUXYj0nDawjoiXUg/Sbq5Pw04JiLuqUo3P7BgYd7qEXFfyTaLFTiVAsOvoiSITf6Mvxa5C0BusvbdiHhLVbrNq7b5QPVFR6m//jtINxKnkCoA7o6IWoXj4rq7k1oUPFOybEpE/EfSP0nBCk8m1dIXK+yIqu4cyt19ipUANfZ9NKnp8LWk7+yyiPhyXjakGXlhvaXJv3XSRa1S+HyyKt2Q74j63VZeVZicRwpUVdpkXNIhpKcHJ+ZZ00hPr/YrSfvWiPjrcPOa1eSxdx8LKlvnkZ6gfCtys8aS9FeTgvtVzi27kJpEb1pIM7/JvFIArsGI2Cd//zdFSZyZdm8339S9nzTe+1HV+4sa3X3yb6hYITqkIkm5Sa9qNOuM8u5ai5OCkIl0DD5TtXxIxUbVNsvieDRF0jdJFSHDVoAr9WnejPR0rVj4HhK/Rqkf7vuGqairpL2dNBTuA3m7letpWeyhyrXs/aSKl2VJleYbV58Pc9q/kpqtn0461z1EakI+5AZfqU/uEaSWCT8jHQO/iogh3e+UAqR9kvRb2pJU0F8kImrFYiFXBOxM+h0vVev9Va3zBlIl04ejpLtWA+ufAxwVEedWzd8O+GwUuqGMlFJl+Qcix5TI58az6pyTFyc9Kb6rwe030h3uQtLvrVb/+hHLn9UVpCDIR5BGfvhmRAypINfodSNo5vw9gfRwo7RSqiT9WqSWg/8gjaJQK1hhs8f1X0pmR5R34dm8JO2Q8kKzaZvNRzMkXRMl3WpqpC2eywdI9wOviEJ3RqUK7ZMj4n+bzEfdbrxK3bluidxlWSmI8wdJ59u9ysqnOd2wZSfl7i3NfifWeXq10qDhk3dhnakMjQA85Imqcl/VSiFU6Yn0ha2cWNRA/AMt/MRyodVJBeAhN8l5vZkRsVG+uX5jpCi210bEJjXSr0rqX1aJ2XAV8MUoBI8qpG24L6+kmyJig7J9NpK21voa2gd3gNR07w0laW+u/pzK5jWbtirN+qST57ak5qObkbp37FNIU/a5tdw3dCR5VuoP/q/qG4H8exEpOOKpkaLT31vr5rhq3UuqK5mq5+UCy9aki816wLmkC81CrSKqtvG3KOlXV5WmeHM4kfQUedm8n6vLfpuFdZclFbK+RGqN8xpS9PojhtnnpFqFUEnvIrXkgBTRvmalh6RbgA0iYjBPTyA1rS67US77DZXNeyOp28v8PJBiRtytBSMEFNM3fOw1q6zwpFzBW5iefzwrtdrZP3I/WJX0wR/l7b4nIs5v4H1NJz15epbUOqxyM1vzWJG0c1RVCJfNy/PLWgv8h9S8dK5qxO+oqK7k0Aie+qi5CvBmKkT+GhFvLUtfkvZVZfOjJPZQTj+Z9J0MkCr3p5CGXBwS60INxFapsY9FSUOONdKqYvO83QvKzheSPkt6cLAcqfLi1KgzAo0WRL7fGXiUVLl7RlRVKDdyDlAK8nku6XpfebI6fwSHWjcoaq713rakrjWVG4R3kJp0X1iS9n2kloyTImJ1pdZB3yr7beb0E0hPzT9JKvedRrpBejoidimk+yXpRuxsFq7QGlKxpuaelrdMJa1oRvv8rdTaYddav9+ScufypHPP8wBl5828XsPHdbPU+CgATaWttX4U4jepRguxiiivGD2E1MrwTBYOTjmkJUXVubzykOiMKAmIqjTqx4mRW+8oxQuYFhE/r/N+liVVjj4YQ2NU3EJ6MPNMvof6Manc9EZg5yiJw1S13WHLTmriQaN1pp7snhALmvT+B3jncOmVmix+mDT+aeUpeFDeDLtyMfy3UnPw/yM1uR9uH68mPTmYFlXBWfKN/I/yDdGdNTZR1oysEhyqtKlqIZ9Lkt7LiZLmkk5GtaxSfWFWajL/YGF6GqmlxepauJn5UqSmmmWaiQz/qKSPsXBrh1rbbWb0hJckvTryk3+lZs21mos1lFbSnhFxpKQvkppqPkoKjvXViHgxV2L8HdhH0mtJTdqmVN0ILE2hq0th2zuQnh5VguvMJD/JVXnz37qRaZUi7R5Cqpz6dk63LKk59scjYv4wQBGxfs7vR0jDq80FlpL0yqjRTFSp684SwLJaeEi7pUndY+aLiJdIoxBckAve00ijHXyrzk16I9195j9lywWq6Uo15n8m9T0u5nfHiDgzF1B3J/Xt/g0p0ORcSUuQLoBD8iNJpHPLR0hdMVaoWr4K8AdSU/VK1P4PSnqWFOth14goi6C8DOn7gXSDUb3fN5MK8stp4acSS5MKJsW0HyQVer9L6sYh0o3A6fkG5TukSsqiho89STuTboCelPR1UmH8O2WFoewvkvYj3dwE6Vg9V7mbQ6Qn8yOJvj1a2/2z0hBxq7FwZXJ195KvkvqUNxwQkzQUWXUFQdk8SN3h3syCYYO3IAXgXSsfL6UtH+pountZRJR1h6mVdkjlQB0NR3uPhYcPm0xqRfARoPQpeCzoQjGoNIrKkMrRQtrKzdpTlEdAr+z3VaQb0Ufz+fRtwN0sPOJE2XpLkG5Sb69VwUh6aPGliLip3rYKjiMdp1tHeeT7hs8B0eQIDgW/ILXIq9yo7JrnDWmRF2nUhzexIIjs3nWOmYOATUiVEESKTr9a1Xv7bqRhFH9M6kZ3CTW6wxXMya8Byrt4Ff2ABp6WK3XduTcijqqavzfwyqgzjK6kdcjlQlJ5daPCslE9f2fPAbcqtVAoaxXUVBeNQrmmmVF4ppC6AVUqni4jlXOGVGSoue6ozYwYUJ2fD5LOLa8DphYWz6y3bg2VCu3iKBhBanlU7fayymTKrwufjoifzd9g6u7zaRYci0j6I6kL7Kx8rbshv4c1JP0qIn5SzFMsaMW2I6mV7PXA9UojiRXzNNKy026kroRFnyiZZ50qOiCwQrtepB/oT2u96qx3F7Bog/v4b1Kh8x2koCZzgc/USLsiqS/TtaST84EUgslUpf0m6USlBvKwAekicj+pILlnnbSTSTcTE0kH7BdJzZ1qpb9huHmkws0WpL7Dmxdeb/r/7Z13uCRF1cZ/Z0lLkCQIKJJB4EOSoAiIElRQkmRQCYKKIixBMaCyKKKiIoJkiZIkSBYkLhkElmXJgoAEA6IgGQnn++OtvlPTU93TPffO3kC/zzPPvdNzuqZmprq66pz3vAeYvqDdF1AU7tXw/wvA8wW2C6FIwL/C93s+sHBJnzdHXtFfIvpjkd26yPkxCd2YHgPWHowtLQHLHxT1EVgm/N0ELfT+Hf5mj8OQIm98zlfR5L4O2hDOHv6/CW2KOoSQwrg8DN0YJhO0AKLXb0fpE1simuxq4fjSRAKcBZ9hlfAdPw7cVGAzATkpXqMl+PMoEtXpGKOopu9m6IZ4G8qvfk9JH7Ix9DrwfGoMoZJY6xdct68X/HanAGsVjYPc8w+hG9zjaIOxAwkBzDB+d0wc3z77fRKvbYuogCehtJhHgW1yNh9F88jfw9/ssTewZM52KrBI4n0WQdfhQYO59mgJwa2JmF2bUCKOFY2H1OORYGNoEb1XPBZQtOOT07jdy1B+674o2rcPsE+B3Sxl109kuwG6T/2T9vvTSSgSljrnIiJRPOSg+j3SLrknOj4e5YIfiXRVTgBOKGhzOuDUCv1dueyRs00Kx1EiIEf7PJg9ivo8I3IUnIWu/xPRpi5vtxqat38fft97kHP/aXJzA3Ka7o/ui7OhDe89yOG3RM72e6gG+cNow3YLcsJeQxAHjmw3RveMyags7KPB/h/ADl2+7z2Q3sTKRXa572R54P0khEKpOQeg62PBKmM52KfuQ4Uifege9UG0flqL4nn31vD3zviz5Gyy+fsLFFx/BPFTYKuqnyk6t1AAMmd3HwkxOOSYuCdxfGHgW+i+eAcKNKR+o77O38F+h9Sj4Jp6R/T8HcCHEnap67nbdX0uWv8uFh77Ewlx5scWkdg1YuUkx1tN25nRuuoClH7xHFrjlor8UVN0usJY6rr+zo0Pi55PB9ybs7k3+v87wClRv/PX01Q0B45D65BV4jGe6hMV1070WTS4eUy7x7B3YEg/TMEEWDQRRuddWvXCBxbtdgzVtr0aqaUeiG7qj3ZpN9sQ/Y/Ehgjlcn4fee9uQIuKvw7hd/dhtCh+gnZF9olFE+1ofKCN6vJIIbbUUVTFtmhC7/ZdV7C5n4QKNVIDfwXlmWbHxiMBy7ztfIg6mz2fErefs72zYt+NnNp0wmb3Cu2cjBZMBwLLDfFvPI6cE2awvx2qT/8QimbtEn6HR0vs/1zy2pMUVPlAjsaN0QZ8/pI2Fq7Q5/tKXntwCL7nO8PfHwPb1RlHo+FBYsFfYLcSKqd3DF2c1GEu2QEtyuL702YUVF+hU/nasr7Rvqk6GzGI/hLavJyCKgvB/o90qUiBFnVFj6tztguXPQbxO3wcOUCeQk7BjYDHSuwrO0fDd3QQcuTch1gjS6N7+KSc7X1okz4nukfPEo5Pnx8raMOyFKJGvwgsFo6/K/97Rud8DzleDgiPu5CuUdHn/BS6X09Cju3HgQ3yfS45v2MOoH4Fh8mornv2fDGKNzm7hM/3bBg/r+THUGR7PIr0TgWWDL/P0YnveC4qVL8CLkbOvcVqjLtfIafhtuj63AzYLGF3b0kb+U3cTeH7/R7ByUvBfaTubzeI62teEuuHnM2dtG9QxxX9zj28/5Qqx8LxOlUAKtkiDaEnwpj7ONp8J3+T6Jzlwnfy13Dd3UFBBRO0DjseCTODUk12ztn04kz+GZrz10UBpbOAXxR9j2jtsk3qtfD8C8ghOhkxCLPjK5GrJFT3t6eHQGPzGJmPsZae8DvkDf1XfNCk0Pt8yXkvA1NMtYpjKlVHfhLyiq6cO3YOoo1lOAJdHNu5++2hD17Wce9O/3wA3cg3cveHQ5t7dTmnTl7ejMjLOD3ttL3nkShj3OYN7r6mKc81/lylOX/WRRm+x3yxrp/PzNZx96utMzd4cTPDI8pcHduA5c0sNbZS/cgWojcHevvxtIRmdvQcrdsTQmouNfC/uvtR0eHD0IIo37f1UBT4K+H5W9FreRGjtu+9229BKy81PmdVVALx8PB8e1qfb2Lu83we0SGXAvbQ16FmGMQYgla6D5HaewGWNuXxdbwNnQJrX0KMpKOAi12K6GXfz7iC/o8DXvEot9LMPonmrXPc/e/IA4+ZfdbMnvZ0LfqXzexndFZxiSmPr5vZQp7TIwkU69dyx3qh2D5lyhFeD1GBZyr63KGt29Hm73SPVNQLbCvnE/erXeAmM3u/u99d1iZyFlyNNkRvlRm6lKnvMrPTvbgSSx7XB5ppRlHdHLguUPSfi+yWcPctzWwTdz/ZzE5HjoEiPIYUwy+kIL/b3bum90VYwLtoAGSwelUk/ojufWt6EOMyszI66/Tufnmw+0HWJ1flgrztfC6KuyEn/M/C8QdMOcMxXnWlFvzPzP7igcrr0gTIpxy85UEHwMwe9SB866LuFqUHbod0h14N5/0ELeBT1RBAzK+1o/XA4kiXINbhqDwHhP4dQI0KDsjJco2ZPYKupYUpTu+YgJwot7gqPyyNnCMp7A7sF/qYjeP897A02qxBKxVu4KMQVXBw9w3NbFOUtnQ6msffil7vuNcidt/LtFcJcDrvsy+b2ZLu/lB80MyWpPM++y+UUjof2qw/RPF9tm/zdxjv+6NS0YZSFN8ADvfO9CuQw2Cgn+EeW7h/MLOTkXjec+H5XGhD+4WE+StmtqYHAV1TOmyRyGKddNSqtsshR9b9wAOuCjCl63WkzbG3t4tOH4dSB/M4CTEt9gvP/4z2KsdHNn9Dzs6NaY1pUPCwaJ3/TbQu+QoMVL/Jpzw+YWa7o0DFymidiElkdIbY0N1PCGkqi6LAZIZ/0HlN11k74Uot+yvd12QNRjjGmtOgaPP0cdo3T3lkVJlCWL189HejKMchJiGWs8hdoIn2u4nHbY7otdeY2WUof7djBZRApbw8b5WmPMkLhKUi2zXD38p5rtapDD8h3ChiZfhe8sWqfL6PokX9RonX8ouAOrYgz/VKFfs6Ad1AQNGLFdDCZiUU1fhIZPu8ma0QNhkDMAkt5nP91vRENQx3P81U5jLDCsHBYcDMkbPD6BzD2W+xBvKM/y4835L2m1qMbAOJma2FqLu7o3SaY2l3Pi3huQoS3VBxDGWoon/wKOnfOYX50eJxW+BQk9LyzJYQowq4yMyOQznKL4X+z4pSaPILlwMK+nEVcB5Soc/jNPSbbIjqdu+AFqQx9kd6FAfRKiu7KqLG5p0AG6LFUx6/QtG+lNNgKyT4+XN3f86UM/mNhF2GbdDi4/aw0T8R1bdP/T6V5q0+t7smsKOpSsRrFCyIgDc8VOiogUXM7Mfo2oqdPoslbHdD8/8aoQ+nIHEsp12zp67eTiq/O+88PMjdvxP+/3iBAyvDkQSHunUXLc0E/qrM+R9Av/GVYXN6Jjn9jhwqO0cJOjXu7qYStUXtAMwZ7v0GzB6tA4xO/ZFxYaM0DmkqzEXrfl3kWHsMjYVMQ2AmxBopwtOZwyAgS5eMUWcOaGsbjZ9/IwdbEq4ylUsC70Of7wFvlRDOo075yZfRJmu/1OsB99W49+Lu54dr+TqkE5KNhTYHQ2RfqG2Rw/eBS83sQFr3xlWQRsmeuTY3sVbO/AEmAco5zeyD3tJiyNDP+XtPNJ+sGjniFgOOMrO93P2XOftHTLpNWbDiq2i8FWF57yyvWfRb7QqcEr4X0AZ+h5Shu3/D2qsAHOu5KgB1bb0H/SZgVo8qc7j7pHB/T2Eedz/LzL4dbN8wszZ9rF6cyS7B5KOBo036PQu6tKJi7IxSZ9dDlVWeC8dXQ/fJfJtPmNn5HolyuwIZedRZO/UcaGwwAuEjgO4wVA/K6VyFFLLw+oxo0l0OlUTKv74JFfPRc+ctCHwdTfr305lDOB7R6fJUu0XIUciD/axIrOhi5AU/CvhEyftXysuL7JdCG7zL0eb5ajppqEk6IAlaYHTOVKL8MLToS+a55s6bixKdhzqfjwqpJXVtqUHHpp0qdjryxGfP87oRaxIi9Ghy3hBtLh9DToLYtmOcVHmtYp+via8H5Py6psD2ruj/IxC7oOOzh+d3hL9X1ehL5TFENf2Dyr9d7rzxyAFyLqITnp6wmQEJzT0Trv3b0aY+UwRv+1xln7ng+B3511F5ybzdCmiTeQeKWp4CrJCwq0yxTbT/tfDoaLfgnHEoovIUooUekJ836lzX/WqXijR7lLryJZRaUjoPRufcgGilU0O7E1GFn8Fcq5X1doL9lt2OEc1LdKGk0p4qcWcX25Oi/3eo8RnXQNV9/o4i6l9K2LwZXfNvhP+z53ldk+dQwOCi6P/s+bM52xPLHjnbR2nXdYkfj+RsMy2m88PYPSm0+SQqXZv/fBlV/ijkgNwRbbIuJkdPDvb5OeC3FFyrKLAyCVHoDwCWLbBbJ9eXtkfBOeeh1I6JaON+AfCHAtsrgDmj53OhKlXJ8VZh3MyEUnfuR9Ugymz3zf0ubY+Cc5ajlXJ3R/g/qV+VO+9dyLF+E2LpdfvthmT+RtT6eRLH5019r6GfZ6I55Z9o/ZJMsQv2d9GupzQ36dSAldC9dBmCdlNBe0uG8XIPYg6UaR9Vti04v4p+03koxWSR8PgucH6B7SSUzpjpAKxG4l4d9f0c5FR9JHuUtDt7+G6zFIlDuny2rhoMaO22ahebjjHSPN4ej7HGNCiLvJfRZj+GJvnHQhvvNbMdPCq56O4XABeY2Yfd/eZKnZE3/Um0Ufh58KrvmDP7MvL6vptOWtIROVtcUcvTUCWEuVHk91tokx+/dxYFqaxiG3A28l7+huLKApnXO/V9OwmvfcCclCvDfx84yxWBmAktClcE3jCz7dz9ysi2l89XJbWkrm1K1bYIb4Vo7LNow/Cj6LWZY0NXhYQPIY/+jui7vhfl5+a930+nIhWmdIF8qs44tNFMRSVSeDe60WS/22zkKiFEmC6KvK+LNlIZ8nPNOFN5oaUsUWfei2vLz0nJGIrOr8KCuTHQNLd097O6GYfvbotgew5SsZ4d+Ezi/V83s33R4uU59Ps97C114hjjU4wFUzmzmRP20Ioq/93MPo0ixgsm+nGXmV3k7tvn2s6X96tDsc1em4Byv7Nr7VQzO9ZLSlSaaM87oXzsc9FctiZyTq4Ymdaat4ay3TCvguZg0Jz2nLtWSwlsF/5+OzpWNg8CzOyK0pqL2TXRzK5H0cX8Z6uSgjUOOcWeRRuysvfOUKeCQxXE0fXs/4F7hLdTwGO2xgR0/+0Kd78RXbd7IAbhNsjJHduUsRDy2CT6P19Nou25V488g6qj3GBm4728+gC02BZ3oM1IhkmkqetxhO+fiB0Hmuvnyhu7opjb548XYGGqVXD4KPUYebh7Nk9ODEytOQh06QTm8c5IdZ7x0JaiYmazeqtiRh5TCfd0dy+ivmeow4LJ+ncPITpuZrO5+4sVT30pzJeHW6KkaPzbdWm37vw9gycqV7j7v8J9J3/8aXStVcUvUHrXOWg8bEX7eidb730OjfuDgR+7+3EF7Z2AHCbXoTF3OHJQDda2A66U4tvNbB9aqZB5fAE51X6P5rjrKE7L2Rs5Ihc3sxuRY2aLAtsT0T3gl4hFthPF+5o53P15M9sFOS33t3TKAIF59lvkYDAz+xewvadLXK8NfNnM/orS1lIMuxsL+pREdE9NwtPpQQ1GIMaa06Dy5imHX6Bo/YPBfinkoUxtJh82Ub4Xob0MVypX62aijae7P2jKX44Xlzeh9IUt3P1wU43rzZED4/SSPmcX2jHhkUd8M6+Sl5fhDW/Pl0+976Jlrxfgx8CdYbFgaDL+ds5maxQNAN2ADU2wS6FF5ZWRbeXPZzVSS+rYArj7QeG8wzo+sdIIbg8OJxCN8XYUIb8wm7BN9bs7qH7BOfD9RLt5fAM4y8xOop0euT25G70rF/EuS+RKFuAntH430GJxYoHtGSjF5Rm0ULkeIFAw8ykV2yAl9LyGRhmqjKEBWBf9A3f/WrD7GroGSxG+uzZbd3+egg1PsD/Yy2naoLF6nKl8Z5zKcBjF1+mBgc65D1oUzU5x7mOVzWFlim2EnZGCdtbnn6I5r81pYGaXu/snzOwO5EA5HpWByjbtt5ryWGN0zSfuV7uknaKzmdldwC7u/ljcYI/z4atho/9QGFNPUUwD75pSkRqbRTCzDZBz5T25eWt2Osvxvis49Sz6P37f2Lk3B63yoqDI6IAp1RwZZf2+EEU7Lwhj7o8kNBtqLlC/7+7rmtlPvaQ0Xmi3NAUl9138Cq0fbqLT+Zw/Lzl/mMq2dmzUypwXYa2TOr4UYjwuQvu6ZZ1c298ys5WDU8YRM6dNayfYZc6tH3igt0fvtWjueer3yHRCZqPlBI7xVnyPChvqNgeKu58UXlsdBTlmAxYypfB92d3jMnGfcffMGdDNwbAF0q052RQ8quTQMpXDPb5LPzLbZJ9RkKCXduvO30VlP5OvhfFzFNIAWS44aTd29w69jTCvPYzWseug+WCz+PsP2BpY0d1fNrN3IgdSkdPgHZFD4UEz6xiTPdr2pN8UnLN7hKDBWylnTjZ+3X1yWONlKTwPenEKQmVnMjC9KQi1FeVpPFBBg8HM/oDG3wZd2orXTvMhIdl3u/sGphKiH3b343OnxPfUhVDgzFAQ6HGko9BgFMCKgyejD2b2QbRoOonE5sndby04b2rOi5Y8Fo7fhDZDdxBF4t393MhmflTb9VQUhcoWUbMjBeClI9vJwHru/h9THviZtPLAl3H3Io9kX2BmExEF7TzaI3H/iWyWdrEBkouh1CIjnLcAyskzVFLpH7nX7/SQo2hm56K85GPC88nuvnLOfjrgJ+5elkeNmW2CNqgb065d8QKif97Ui23uPY5FwkyxWNm9wHsRvWzPYDc9uqk9G507K7oWX4yO3U36RpbMqw6T91dp5TXeC/zaI8G9yPZq9Dv8iXYBtI0LPtv8qNSgIyXfZJ5fWCzOh2jal0ebyaUQJa5jXJjZBu5+af54EbqNocgur3+wLaL0d+gfmNn3kJPjd7R/Hx2L2Tq2wf4AFOUq1FYIY+JARC/P9EQWQgvF75UsMEoRbQ63oqVJAZqHlnX3D+bsl0MOqGwM3YP0CpJCgGGMruot4bbxwG3u/v6c3WR3X9nMFvOaOhZl6Fe7Je+3GaLDr587viVSm37BzL6LNok/dPc7S9paFVGl50SO0tmBn3lCSNDMbnT3vPMj1WalsRk2HSuiXNfYKfkCSj2K56bUYjVqOima1hWmvOFMl2fr8H/c8B6Jcz4abD+N5q7fEURJc3aPUsKE80g3wszuQ5T8o2m/V2fGkyPbsu8Cl4hgZnsL+n0/nf9sRZ8vnDcPYg9ui9YQ57n718veNyzUtwnn/NfdV0nY3IU+Y37dckfO7ntovsicaJsCZ6c2h8E+dV++w6Oc6Dq/R3TO+mijk23Y1kLXXspJdCva6F8YrR/u8QSbLt6su3tyAx5/ptTnK0LNfgy5bZ3525RTn3KaGKq4NEPO/trQ9jHd+hte66Zpkhonbc9ztg+g8Z2NodOIrtfcdVrZNtjvUNbPlNPIzN6P2AyZQ+wZlGZ1T2QTj6Nz3X3zsvcJdjcibatzEJPnKbTG7dD+CPed7wE3uPtXTZoUP0u9j5nd5e4rlB0zs63QOuRk4OAq6w4zu5Qg8ujShpgepS68v8D+aDSO/xCeb4D2P/t0e68GIwNjymkAYKKw7Ub7xHlEavMUnXMCuqn9Nhz6LFJg7vDom9kUd1+xSx92QJTyVWinuL2AcjnjaNnAhWtmRwD/cveJVd+rpA+ZUv9DZh1K/TsULWjDDT6P/ELrWHf/krWiz3nbdSLbAWX43Pt8Fgk5XREduwVtnP6JlOo/4C2RngdiZ0t0ToeAZBGsXmpJZdtgfzViq7wRnk+PUkY+jnL5lo1sZ0ER4oXc/YsWhKQ8ioRbgqoYw7uIVXbp60dTx11imCn7OGJ/rbtfVGB3h7t/oOZvMgfyog+0j6JX/41sajupTDS9FV1iQZmD6c68syW81nXM92Ib7F9AOiRvog1dUvjHFJ1Zg5Ya/sOeoNFajQojdTaH0Tn5tIXksXB8b8QIOi98rk3Q/HZozu4RFOUs6nM8H1ZW1e9Xu2Uo2CRNdfflzWxNxIb5OfAdd/9QhfbKIp6Zza+QEOf5lKRq9DA2Z0f06DfD8+lQadmOFBozW8OVGlB4rOj6jDoSL+xrL9Sjc6dDEcwvAuvnr6U6MLMtEGNmTTrp6G33sprtzkOoKkKCLRZ/PjN7B0px2g6x6s5DomUd6UbROQujjdG2iB2yMKqr/liBfeGGLGd3P+0VHGZGudjL5OwyRt7BtIufzg58w93/r9t7VejLPCj/24CbPUGnD3a3uvuHrD3o0LFJymzpsgEfjNOgTj/6YRudUydFospnu83dV831oXB9atWc5c8hWj/oN/5I9LwtiFGw1oxM29aclW0L+vWOYFf4/ZmCh/t5e+T+IHePI/fxdzXwf5f3ruxMrgMzO4+WngkoLWQVd980Zzcrmq/WD7ZvZa95ImW0h3HRMQ+Z2e2ecHQ2GJkYa+kJWe7V/mY2IxJXeYv2slQpfAU5GvaAgfykIwtsLzazT3nwlBX04WTgZDPb3CMGQgHq5IHXwQSKlfoPo12pP+57V5qQt5T6N/DOKE+ewn8A1ZXh90Qe1nmBX0YOg08h4Z4Upphoq2fTHl3r2DAA25nZtonPs0cvtjm8B20Os83urIiy9aaZ5dWkT0QRn8wT/2To/4DToI5TwGqyEoqcAwVt5yP2e5jZ6u6eSgvoRafgBOTY2yo8/zz6fuLUkL3RdfGLxPmONhApzEk1/YPK1Lg6tsG+UuqFV09lqFzVwnsr71c5z93dDzGzSWjDBbCTp52RcyAhzyINlHjzWyefuF/tJmFms5HWxskit58GjnL3C0yMrbK2KlOZqV76bZkK83GMy9HGNlsczxyOpcqGHU4nzT5/LLs+xyOH+V3ot1keuJXWOCl1CpQhbGI3QoyDlUmkBtVxXric2eeY2ffc/Yclp2HpFLS43T2i/58BzjSz+z1XASeBpxFz4rsoauhm1qGTEvXjJjT2z0RpjQ+Zyjo+VvIeF5nZVylhEAY8RrUKDu9D196ctN/fX0DOnKK+b4bGgQPXu/v5JX1+E30344FlTSWPr0vYPWFiEHhY9+2BNl5JuBTi8+8TY8HwW1v0f3x+0RqgTj/6Ylt1XrH6OebPmEp6ejh/CyRGWoS9Cc5yM8vGkuccfJvkzslrisT9Wbusv73axrB6ef9Vqid4wf+FcPfbQl/cC9KQenSAV9VgeB2to2dCaaNvJWxivGRKLcnGxWp0pqLGeMbExjs1nPM5JC7fYJRgzDkNYGCTeQy62RmwqJl92XM0aDN7n7s/6MqBPSQ8stfWIC32MQH4jqkuc7YQz0+GGa4ys0MoiaJSLw+8Dt6INgobAqe4+79RSZmDi04yieB8JerzJERJS206Uvma+WOzuHuHnoS7/yM/yQZvagebIDhoipw0c6NJJ9445hfU2Q22yoahjm2Mg5EDYxIM5NsfFD7jlTnbxd1968wp4e6vWG4VY52laQZeonO8bVino2FiPxw51WZEGgsvFYzhT9EesT8ZOXBSToNedAoW93Y63QFmNiU2cLFaxgHf9Vy0swR19Q9WpzPf95QhsDXEXFrU3X9oylNewDvLa0GFMpHZZsvMdgTWzq5LE+3v8tQ5wCfN7IcoGjk9iTFk9fLcOz4mWlwUCTb91dOaLynUySfuS7sphxcSmNsYKffn8ZSZZeVGf2oScU05F2IcCnySkALlEqxcK2VYtHhMoMp8HGN8HE1z9xdNLKgBhE3I6sC8ue9ldnJlD7PFupmdiajkd4fny5FjhJjZRZQzZjpSpUwClh9Cuc9HICZdalGbci4ONE10r4gcDJeknA3ezmIqKjXbgXhBn5vas3bjhf130Nx5FHB6+Jxl+BcSPZ0POdgfovumJGN2xKyAAZ2JqL+vAfea6rU7YsrFNduz/l9AfWHoI4El0JoHYFdTGc/dEra7oLXWgsAUxDi4mbSDeFekIfEe5IC/HAWBUqiyAY+/ozrrgDr96JftoVSbV+rmmO+G0kWWNrOnUBWQzxb0oZKzvE7wIka/7tVUyPuP8IgplSeO3OeZXmUlrpN7hopOn9prVA8aDGU2ppSgQ9DYWdnTos151BF5BAUw96cl+HpdONZglGDMpScAmHKaNvRQwzh4SC/xHL3dzN5CF/1unqMiWQ1aWkk/zkVR1GyB+nlULmeznN1q1MgDr/jek1Hk61mUkrCOt4T37vcc3TA67zeoXFzc5zfdfZfIJtZsiG8cKc2GP6P86ZQy/H3uvmR0rI7Q1IiDKd/+g+im8Cd3/1uB3U2IVXKjKyd7ceAMz+WY97Gft6NF6tm0ND+W9FCPPWc7FfhYFnkIEYpJnqD5R+dU1ikws5sRnfWG8HwNlIfZEXG3CnmSOfuq+ge/BRZHi9Ms6uQpj30d22B/FNpQr+Puy5gU5S939w7BMquYyhBsH0SCQ9nvMhdwi6dzHx9GzI27i5wR1lsqw/cRw+Hc0NdNSeQ/W0VqZrCtTA3uY7v53HVHjsnrPJ0fPAuic97tivougMqtFTlxKlGOrWJEyWpo6OT6cCOwe3aPMbMPIB2UD0c2HwU+hjYuR0envwBc5Dm19nBOBz01f8wKUqSiz9axoQiL2iu8sxZ5z7BBUplL2u0lT3oxtIDeBpVe2x9pGvw5YTsHSjfcFm3E5wQ+WeCMHGx/vWRTdjIqHfxceD4XKvvY4cwzs3uB5bI5KDiC7/ZEKoMFvRQ0p61oSoc4wN23rvnR8u3Ogzbg66Hr5PLQ/8Jop1VIIRopqDKv5Oxr5ZibgiDj3P2F1Os52zitcZLnhIitmCEJQGqN0ed7dde8/+j4XChyn7GnrkPjs+M+WQdWQ+uiYnsXlr3u7Skg1wO7eppZUfYe01NN5LHBGMCYZBqgXPmHo+ePIJpbHvciz+1kM9ve2/OGiqJmXSfDCF2jqDAQYc8f61go1MT3qaHUH2HV3CR5tUlEKcYnkWbDgrRTyl5AUZMYv6e6MnzmnX4fWjBkE95GRLluMcxsQRQ1XwPdgG5Ai4AnI5vKUa26EbBEdOqJ8Hd+M5u/wOmzP4qWvdfMTgt937HoPcP7vIuoeoNHlQ+sHishO/9hM5suLMBPDI6MFGpF7ANusu4MmwxfQak8c4T2/0MrKpZH10i8deofZOPg3Wb27oLfYxXk2KriQa1jC6ousLKZ3Qny+JsiXB3wiqkMAXWqWjwB3FPWZ+8tlWFb2vOff4LyJvOiaZ+v2F5d9KVdD4J2VlHfwRWR+b2ZzWJmqyAGRKHDIKBKxLNqRCmej2PHamo+jrEncLaZZc7NBRDtfwBh836tmZ3kIWUqbPZmc1UOSeH+4HyOKahtny3lFCiCma3j7lcDswCbWC5y78VlOLdPHY83wN4DlTlccyknzjrR/7XTL1xinj8CfmQSWtsWlR1ePGH7X5TadYJJBHdr4FAze6+7vzfR51lQVHAhF3OrTUenqL9WUMEhwvLeWRqxyJH3IIpqZ6l370V57ym86u6vmhmm0tUPmEpWp/qYShv5L+2Vi7L+PUNJhDzXbp0Uolr96JctNVM10Hpv1+yJu19qYqXF7/8+lB6YOR/vN+laFa5RrTOtcYKZrentQsQZQzJjTcSaYkVR7n7eq7uyB0zpXrsiR93dwD5DvUn2LukzdRwBKAX2CcTuuZWSfY27J1OWU7D2ymIxljKlERXNyZWquDQYuRhTToNoIN9rKh9yFrq5bwncljjldXffz8z+iGqMnwIc6KI8Fm1KqkyGGV4Jr8VR1G41gocE7n6xSSzpXd4e8b6dVv54Cm+a2eLu/hcYiH7kIzvzoPz7zFniiDJ5g+fKL6E8zQOBv5rqvkKkDJ/rc7ZYvxzRo14IzydSXDv8RFSacsvw/HPh2Mcjm8yxsRkSFDs1PN8W5XDSoy3UyOPN4O5XmJggmcjTBC8Wedo4vMe7keNrYbQIGIjO1Nxsgmo6z4jSKQ5GuYn5fLys7TNMKRdZxP6bXhCxj1BFpyBrfwqi8c0enhdtRKA9T7IoEt+L/sE96Lcuy9HsxRbgdZNwWxZdm5eCPEGz6qkM7n6iSbk4E9v7Vsnvsi/wB5MCdpzPnGLudE1liPAYFfKfPShKh/n5p6i0oBW0XTmfuF/tRijVdwjX5mHI0fVdRJn/J7CImX2zy8axK+XYW4KjL6ecF5HdyVTX0Inbv80Uwc2iRA+ULIB/bGa7onvBHagk7SHu/rOE7U7IGTghPL8OUe87EDavP0b6HLFTNBZv/ChSEk9p46S0HTLEbJ7xiN01Gamep/qyXKIfKds41WI8ivgnU3jC9f7NRLuFi+QwFz6F7kWFed5RW/9E4/AwKxbQzXR0Mqp1h45O9P4dFRxK3n6cmc3lIcJqYqIVrSvfiTac2Xy2KnBztgnKbXaeNLM5kfjnFWb2LJBk7qHvNVW5aGczW9tD5aLQvzob8EOpmEJUtx99tK2TygBdcsyD4+T3KN33WDRPrARMMrPNvFigryitcWCdHDkh1/D26jDfMrGgfpBot5/36ip5/yejtOTrUWnCZSguSdwLqjh9KjsC0Of/OLqWtwMuQazWWmyCBFJzcYayOflsxFj7DZ37igajAGMqPcHMTix52T1HmbN2yuqcSPxwYbRw/70nKKxWT5V9BbRAyUTYnkWVC4q860MOS6t9F9JzzWxdtMB4BE1GCyOBs2simzx9F6Qt8Elgort3lJgKkY4sYvKwK49/Jm/VVI9tH0BpHK+F5zMBd3m6ekJXKmx0/Dp3X6vbsbq24bUzgR95Lo/X3XdM2K4BTHH3l8zscyjn+FeeED80sTzWAa5095XMbG1gW2+JUab6UshKCK8vjDY3MwJ7ofF5pLezc2L75en0DBfdFOr+JnPQpXpCXZgioR/2ivoHpsjhikiMLN5Up/KqK9sG+8/SLtq2BSqjeFbCtnIqQ7B/D63NfdaPDkZOcMK9iCIjb0W2ByRsu6YyRLbno4V/Pv/56dD+Hjn7h4GN3L0w8mW90bqHtF2rWKoyXJtbouvnGhR1fSRcf1d5Qdmpuqg6h4d5cnM6r9XU4juOPi/sBVVcItspLpr4Z4EPoI3wHan7Xs3PdgO6/n+JFqI7oXVJ6h6TOr+yoyTMNb8tuK73R2kYyyL9nA2QE7wsPzc+/1p370i5CNfe75CjYVfEovqXu38zYftltFF6hVbQwr24+sVSKP8+Pwd0OCQsKJRbAW3deqjgEM7bHjnSsupIW6L74G8TtrVTUqLz5kBlTf+XeP1qqlcuqlQaOdjWpfrX6UdfbOsiOHmy+6+jjfIPvJX2dinwU3eflDvvo8hRvUFBu5XTGk3s2695K7i2OlqPrJiw7du9OjpvduAtT1RPMLO7s3k9/A5/KlpL9wKrkD4T9hyZI2B5KjoCwv1hW+Bn6Dc+fKj6XRVWsYpLg5GLMcU08OqCURkGPHQuit12YXF5PaJCFmFOqqmy30Uuimpme1JMyRsyWCvPdWYTXTDOcy38bO5+VbZ4pBV9ei1n07HZCO85NxL963AaoAVYfnK9mbRI12+BP5nKxDhazBSJ1zwTNt6ZuNK2FKuxzmtRTXczWxQJtwzWFmBpj/Kd3f0eM1uxwPYoNC5WQIu+E9DnSy2qXnf3f5vZODMb5+7XmNlPU41aBVZC6NtfTSrkCxT9llGbJ6Ab0720NpxlnmSox7CpzEowqxaJd1Ui+Dmt6hTdMLGiXV1b3P00M7sDRTkN2LRkc1s5lSGMga3p/F1SaTxzu/snEsdT6JrKEOE82qOQk7rY/7NsYw+tzbsVpAZMo3b/hhhZG9MufvcCcrJleMsDRdekXv9IeK+nzawo8lynZGZdccoLUNT0DqJFcgmy6HNhFZcIM5h0aDZFugevW0LgL/R7DXSd5Dezqc3vzOGeY8FpOtGUW1vJaYCcDVXZFS8jrYAUtkAVhu50951MlP/fpAytXXl+HHKizF/Q7jvd/Xgzm+CtVI+i1IyvA//nBayzBLKo3XF0j9r9L8z5GeNpcdrHSK0KDhnc/ZQwv62N5rfN3P2+AttrTQ7rJd39ytCf6T3Kj7e0qn92X52N1rorRp3KRUsgp2y2AT+KaAOes61L9a/Tj77YWj0mBWFTP8GKSzQunncYhPOuDQ6YItRJa9wZpdnMgcbnf1HUP4WJJe85GFtMKUGnoAAYJnHyHTww2gIGmFju/kbRHFgXJtbG7939GVMqb6E2giul9DLgssgRMMnMko6AYPPpYLcI6dTgwfT902iNGQeqko5qqldxaTBCMaacBhlMjINUzmF+IjouYXNyWLTsW9D8QdTM8fZ2yvXeiPbWb9TKcw0bb3P33wYnwdRw/Itm9pK7n97tDd39P2YdVQBqOy/c/UdmdhndS7mBbi6/RotHUMWLohvOXmhyzTQdFgG+PAS2UCGPN8IbYVG2CXBYWFQWRUKfM5V6uw44zcyepljN/oco5aGNlZA3MrONEO11RlRZZEXkeU554FfrIZJRR6egku5HwJGESDz6rC8iSngqEl9F/+DXwOlFEa5ebXPn/dbdPw88kDiWR+VUBrR5e1/eoVeAK83sE949zx7qpTJc6ipxOwALFWkK2r7dpAx/fq7t1AKmcunHoW7Xq+s7jDOxQcYBb4X/s/ltXME5sT7BAZRvjqs6LzIs6O7rl7SXR9cqLhGOQekodwHXhc1fERvo+NC/O+i+mX3VxAx6yMy+hmj576rxGQpX7dauTzMOsQg6GD4BrwRn4xsmJ//ThMoCCcS/xRso73nnAtts/Pw9LK7/hu7JKfyF4lzuFN5w92TaRwLddHTqVnCI8QBiUU4PYGYLeY7dFo5/EaWOzY1Yhwsip8e6kVms6p+Hk/5N6lQuqrNZr0v1r9OPftnWSWXIovq/oVi3oUzwsEwc8grEGlwl9LkwrdHd76AVXDMvZxneTutaXQp91qTocsJJNQu5ii85HENn9YRjaa+ekFVEIHyurCpCWRpfFXyX1kb+Koor3hD6VskRYEoLWQ59RwfkHCCDhklIcxbkNPwNcr6WibFm68BkFZcGIx9jKj0hQ9gsZBiPItV/8+L6utl570QT8uNhIsu/Pg5dFNdTQZW94D2e8IRQUb9gFembpujmWp5TxQ0T+TVegVJkZuugsnjrRMd2QIuTVWhfML8AnFSwsM8oWPPRHqnqWIjURZhsszSHDhbFIGzH016q8jpUs/3VhO21aAG3U7D/F0pX6KAzh4XBK2jR+1nEbDnNE2rP1qKg3oUE6t4ysz95ripDiAytg+iCGe1yqqepg8cjNexk9KgMVkGnwOpVT5jsIRLvXeiiVqESgZlNQAvlBRCF+AyXxkKqn5VtU32Onk9HAaXU6qUyXApsWRAdyttm38VraBNTuMCxeqkMD8b9M7N9gJ2LnEyWTh/z2JlrFVMDplG7GyLnVFLfwcweo7jUpHsBrTxqf2Acd7GboYvzIrM7FjjcExUeCux7ruISnAu7uHuH490CrbtiH1ZFztU50Xc9B3CwF+dK589/3N0XKngtZm69gQQqnyywPZLWxnkfdA1M8Yi9WLQZ7tK/DdF64b1IsHd2tHjvEDMzOdVPRHnKsfMruW4xaf08TcWoXVjfZDo6t3iC0WA1KjgE+92DzT/RXJtdI0U09A+iNVM2fw/QvQcDq165aGe0QZtEtAFHTMWJ7v6N1HlD3Y9+2VrNVAbrotZvClKkmKMGbOXu8+Xa2wixB99A42Fr75ImaGL1HIScNxuY2bIovfD4hO0dwEdQCdxb0JryZXfvELeMnVTuvriJQXu0u6+btw32lasnDDVya5rS+0LOEXBmmSPAVCEuc+7Em73BOjmy9qe6+/LR39lQoKYqs7HBKMOYdBrkETb7V3ou18/MLkZ5WfeESXkymoQWB45190MTbRXmtVfsS+Eipx8waTV8ny4540WbxtRrli6VMzeKomzv7g/kXqvsvAi2dRYii6FowGqhTzcDe3mgCifs+1XjtzJM7IvtgNvc/XozWwjl/52Ss5sO+KO7r1ex3StRBPrHSKzyaaSOvHrOLpWrWeQ0WAu4CPgHWpgW/hbROZV1Ckwsh5PRZmGAleAJ3Y+wwFkdfW8rmyLxl1fZeJUhRCO2CY/xaAF5ZmqhXNXWzL6NNiEz04oeGvA/4DhPC6diEqbLUhmu8gLavamc6wooKtF1g1EVmeOpou0CKBLzKnLw3Y/UpLs6MkraXIGapR/71a7V0HfosU+VyvpaNbFAzOw+RL9+lArXqpl9HG2glkUbizWAHT1BRy44P3kvM4kFT4ciX/HYnFyl3UR7RaXZDFjK3WfK2Z/kQUvGzHbwmpUMzGwRYPb8HGTtGkjnejtDatAwCQTeQKfDLtl/M3s0cbjQWWUVNVAi+6yCw9bu3lHBIdg8jNKqCksWRrZt952woZ1cMj43Q2xDB6539/NL2p4LOTni6yP52WpswGtR/Xvox5DbBkfuB7N7bbgX3+ruS6c2owVrgVjropbGjEnLYCtXtYsPIQdgqZaFyQF+IrCfu68QxsWdKWeStQIHu6PUpoOtWC9pCjWcVKZ02Mm0V09Yxd03Lev/UMCk47UtCg7lS+e2zZ39dgTUQTR+bkH3yv+g+2UyDcyU4hYH1yYBx3hTpnHUYEymJySwJFLsz2PRyEu3E6oBvb1JFOhG0mkEV5jZ11G0aoCe5ZF338pL4M3c0yfoHcdTLWd8BkvUIw7fRT6vesPccwf+nT83h6usehm+CYh63XUhgionHIHYJKDN3Bm0VOUHYAV1e0noJVS1LVnQ6oTEgsjFTDkkev54qg8uyuTLZjZHwfeUxyYoqr4XLVbCQG6ZqaLIbsA9ZrYdMF3YkOwBFJVcPAGNmbaFbBdU1inwXPUEtMHemrTux2EoqvYuM/sRIRKf6oBZrUoEf0Xq+z81RftOQE6PDipjVVt3/zFSnP+xu3crUZn1uU4qw4W0SpJ2azclvHmop6OmlVMZ3P3vpjSib6Ox8e2Uw8DM9g2Lu2Q+v7dXRKiaGtC3diOU6jtYZ7nV/Pv3tElO4ERaYoFrE8QCE3ZJUbIieIUqLmETkIIhR1EK2dwbO5+cROUSq1C+kM77TTfEkcEJyCmZRNlvaGYr537D+DvvxiKprF0R4Q1337us3Vwbi1a1tYoaKBaYbS6h59dQNHdiSdNPUJymkse1ZvYdROn+OPBV5JBO9fdI5ADLtIp2NbOPu3tHeoCZ7YJ+5wXR/Xo1FDzoGG8BryJF/fHAEma2RMFmvS7Vv3I/+mVLvVQG6KLbUNfhhsbwA+HcW8P6sRvmcfezgqM90wooSmsyU0WHz9JKCSpKOXjN3f9nIeMqOCPKnL9foFU9AdLVE/qFv9NaE7atD8nNne5elPo2HLjYFJg8mFbaVlILJuAoYAaUagpaGx4F7NKvDjYYWoxJp0G0abfw9x9I7TmPePG4LkHjwN1fCN68FDLKa3zzasvJ8fol8PqJqjnjxwPnmNlX3P0xGIi4HBFeG4AnVP4roKrzAuotRMzblZpPNeXGptCPGr91F7R5p9KMaBJ90d3nSJi/CtxtZlfQ7qRqW3SaWAkXuFgJb5FeKJ8E/BF50pdDi8LTw7EfJuxBqTqVNqcRuo654CTYDeWLXoAWNLshMbC7aJU0HYDXExWsrH8QvN/rI4fTusih1UHHr2sb0FaRIvxO3/W0AOX/JWyTaUE1F3Ox8Oa+6Fr8LWnhzd2AfU35vd1SGa5Ai53l0IL2BBMT6+s50yy15Xaqo0rpx361m6GbvkOqrOeAGekNQHztz2Lt+bFF/agkFugSOF0T5fCeaGLizJboQ36jnJUkW8hEwY83yvMhfZw8E8NIOBpNTJkDUXTvxeh4kUOja/nC8LnqsK7qsELi3/ADtOsV5H9DL/g/hTraFRmuMbMvoY10lXSDrPrFQu7+JSupfkF1DZTrgI+YIttX0SrR/LkC+0eQ9s8ldNdA+SbaHNyN9IH+QPEG46PActn910TJLkq7mYDm9Vvcfe0wBovm7zob8DqiibX60S9blz7SH2gxKb7jLSZFKvWiVLfB2nVBUu+X10F6l5ntXfS8YFy8ZEqdyX7r1She/01ATurz3P1eE9P0mgLbSk4qU2rpruj3vhux5aZp5Nvd156W7zdYmNLKnnD3H4bns6Hv7gFa+mIprOrt6R5Xm9JpG4wSjEmnQY1N+xMmmtOTKPp2GYBJ1XeG2NBa6qaLmtncRTfyEYhKSvbu/nMzexFNtNlC80XgJ15dbKkMdQTvui5ErKWyfI2ZfQvl3TmKplxS0O6Q1/hNOVBMZXP+XeRwyI9PM9sU3eRTuITizxO32ZWVELz5lyB69vpo45j1cTfavdsZHjCz0+lcyJap71YZc79FG5GbgS+iDdqMyBEwJdWo1YvEd61EEBYS2yLHz61oDH3JE4yZOrY5rGvSWNkZpYycgBwNcdsDqQy5TeT/SIi1hnMeJR2hTUVAY+HNX3mJ8GZNh+cR3qIMPxciVilWxRbAxS6R2R0qOjwOpXtqQL/azfAjNAeOp5Nt1dNCr0eHciWxQFPZwFVQ5ZsT0T3sVJR2EKOOs+NiYLbUNRmimfHzPdA8cj+QVQzIaNw/IiFY5p3aQTdaorpAlfktwoImarlF/8dtxQyUgd/QRNEu+00zETSj81ptc/h4ewnPPSuOze3C3/gaKhMJOxE5ObL0s7LqF4+g8dDNaWDu/rIp9/9wD/TvEvvHw2NGEtfIQKMav1NdufLJOS2HBxE7NLu/vpfiqlOvuvurZoapjPMDZva+Ats6m/U6ool1+9EvW6jOpAD93h16ABF+Hv5uhtZDp4bn2yJh1DyOA95R8jyFvRFrbnEzuxFVqUqWOg2f4zoYSNl4NB9AifAtdN/t5qQ6GTnIr0dsrWWAPbv0uS8ws92QZtVz4flcqMT2kaUnTnscg8pCYkph/QmwO0oBPJaC3w9408wWd/e/hHMXo7tYboMRhDHlNDDlGz/nrXyutZGH/TG0wM3X+N0Z0bfXQ3l7z4Xjq6EbcoxY3fRKuqibjiDsCpxiym0DbdSKNgxHA0cHp4F5ThRxkKhThq/KQiSvshxXNnDSkfN5gPtMuaPd6vZWsg1e8Z+gXK4fos3wPEhZfXt3v6yg/63Oup8fHB+p104OTqyFvFiVPkMVVsLr4bWZUBSy28ZpZvT5Y2Ebp7xkT5XqCYt5q97xb4Bn0GcsG3OVI/FUq0TwHcS0+HoFJ2Ad2wG4+3ZmtjVauLyMFgA35mxqpzLQTv0ej+qjz11g+0JwTHwOWCt8LzOkDK1CKoOZLe3uD4RxO1MWvXTRSq9INBun6JTSxSOUpgb0ud0MlUtVmtlydGoODFr/JGBPpFC9B5pj1iY9h38GWAnl5eLuf7MEPbiOs8Pdi6oC4O7b5Q59EfiAu79oYqmdY2aLuPuvSKdTxM5f6F6+sBLrivaIah0WSumYcPcy5fWe243ar5xuENC1+oW10iReRrT1bhooZtXp30mB1AK7t8zsLqsuJvlOVJEoSydbFbjZzC4M7cX34SdNFOnzUfros0hfKYU6G/C6VP86/eiLrdVP1bgpOKB/B5wbrYEB8FAtyMx+6O1aXheZWYcjoup4yJ0z2SRampX5ftBzkX4z+z5wVvi9ZkIOyBWBN8xsO3fv+D3CmDsVuK7L2mnZaC1yPOXq//3GF939iOxJCHZ8kRadf6RgumgdtDXSgDsXOLeLk/EbKND3CPqtF2bapYA0GAKMKacBKqf0GeC/JoG1s5GA1IroomvLm3GVC9s134ir5Eqe8mQF/49ouHJ5B3LG3f15M9uTnNfe2ill2bG4nVQUug7qOC+63nh6WGBBf2r8/hptKOcArgY2cPdbQgTjDAJ7JYZJ4CnDOLQBLMqbrlMesZSVYGbrIzbBhcDK7t61vJdH6uFV4dV0CuJ6x2+a6twnHQbWQySeCvoH2ebJzBY3lRV9zcw+hjajp8QLqDq2ub4viRZx56IIxudDRDP13VdOZfBOvY9DzewG2kX+MmyNopg7u/s/TMKbP0v1l2qpDKfTcpreTLsD9UiGxqFap/Rjv9qtpO9givB/DDkN/oCiVTeQ0CnpBe5+W3gf73I9/s/d3cwyR9msBf3d190PDv9v6e5nR68d5O4dJXkrYjoPKQnu/li4Ps4Jzvyie2ad8oXx/JbNlx3tZlH9/GfLjnX/GMMDqy8S9r/gUM5+78XpZBJkTpM7qKaBsifV6d9VNSkyLADcGxwBsdMndS9LzWNJuHumZzQx9GcOEvfdgMobcK9J9a/Tj37ZUo9JgbsvaWYfROl2+5nEVM9091NzpvOa2WIeBKbNbFHECEgiOOm/SKeQ9BcStlsCl4Xx9l1gZTM70NvTpLamFQjaAa2b5gWWQs7iDqeBmW2M7nPd1k7xWuQNK6w6O00wzsJEDwNrgEIGzzBiOjOb3pW6sy6qUpGhcF/pSrNbkpaDqLQqWYORhzFVPcEiBXgz+znwlrvva6LGTfGcKF3mtS5CPLlYDXXTkQ5LqF6HhS/oYl6V1gJjI+SpHRKhkrzzwtMVKuZFi/v/oz1yl/SWW72KCPPRymv/k+fqzNe1tUi518zud/dlotfu9ISyv7WXiHsDMWGOK2g/VR6xTAG4kJVgyoPe1d3vLfjIqfaWQhvJ+dx9OTNbHtjY3Q9M2JbqFLj7JpHtm7QWjkarykBZDn2dSHyWX12lEsEU5LhZBOk7XIjyfz81GNtg/wCwW7hZGqJifsHd/y9hezoqPdeWyuCdGgH5vPTM8fQV71IeyrqkzlhLnfr7wFNh4ZwvG3mnF5SHSo15a5XtMrT4ayvh5Ql6qVUo/divdiPbSqUqTWKoKyDF7xXCvPEbd98o32YvMEV+j0dpAqla6pnd15Ho78eRs/wLwOnufnjOLq4CkP9tK1V0KOjn1ajO+ZTo2PRoHH/We4zUm9JqFvQQgQubznnRZvWbecdAdF7HZ0l83iwSX3kMVexzm3YF7RVUiua33yAGUMaY+TzwZtG912pUvwgOpFfd/c3wfDpgpgLnZWWYWcz0GtCkcPd9E7YpDZWBaHbCfmGkz3FluK9N750loeO0h7p9/yhhA+6dLNTMZi6qVS2o3I9+2Qb729x91XCf+pDLuT2wRuly7jwoqNBxrZoCDseiNBfQ/e9LRQ5VUznX65GzaoB+7okKWtYq17cmmrd+jhw0H4ps4nvOuahq0jHheXLOKlg7dVSJ6mUt0i+Y2c/Qd3s0mj92RdoB+0yrPlSBme2HShg/g9KIVnZ3N7MlgJPdfY2c/eegQ38ME4viJXc/fRp1vcEgMdaYBrGLcB1CbqCLppSy/zCiq56B8pTLXIyV1U1HAVLRmQNgYFG9cnZzNtWCTi7KeoG7Px893Zt0hYrTEF1uQzRp7gD8K9We1auIsBXyPE9C38HhZvYNdz9nELYx5T2fblGkaVAnev+Gu/83N357YiW4+0dqvG+G41BU5ZjQxtSwue1wGlBDp6DHDUTlSLzV0z94yxVh+Ayi4h9uQQthkLag8lfPg1YfwC+KnJVeIZUhQpyXnjmetooNrLfUmSqpDGWCcKmx2QtdvEpqQL/aBWrpD7wS7jFvBMfZ03RR16+JQ5EYYUbNvsuURwpAWKjN59Kl+TjwPHL+XoqYD3mUseYGE2bbnk4RwzeA7c3smI5OqPTdbmjTC/oNj/FOFs2+KBKaYUaUxjAbSiPMswk2QAva91i7nsHs+f7RPm7qpDKUosbYiVFLJMwrVL+IcBVKw8zEKWdGjoZ8Od5VEKtrEdqd8G0breh4JU2KYJs8nkLYTHwJpVwtjuj2RyMncNxm5bSH/Aa8W3+sBtW/Tj/6ZRtQJ+0hc/R/Bl1fiyN2Xoe+krtfZooQLx0OdYsQz+LuKfHxFLJ126eBo9z9grDujPGaKQXsn8DatAuozlLQbmrt1IFenZl9wjfRuP8KuqYvp7wawbDA3X9kSnVaADlwsvv+OKRtkMc+tBhUMX6HmEyN02CUYKw5Da42s7PQBn8uRBfPFicpT/L8KCqzLWIOXAKc4YlIrLfoyePd/dX4NZP66mhCGb1kIdq/q/+hBUQ/UDSbv9MV4ZwQbuzXFi1EqFcRYT+0MHsaBhgNVwIdToMatmXiWMlxYWYLAoejyJAjKvMEd38yYV6nPOJEdMOfBEoTMNEIB4NZ3P1PuRtvfuGdoRedgjroKioYoa7+wbbIOZVFh5M5/1VtLVDAXYyaPE16J7Qwz59TOZXBq+Wl106doVoqQ5HQnCGWSb6vvdDFu6YG9KvdqI2qpSpvDwv141Bk7UWGOC/W3Z/IXYOxeNShhPHk7lcAV4T+rxJeyzMe6jp9qvYxNX9lr7U5v0xR3lPRpv8kNHZWRvfwTZGzM3PwzejuT0Sn3+DKp/2PpVMw/oYcABvTnv7wAipHG/drJKUy9CISNh45aqcHljWzZCQcGO9RNQuX7kRqs3Uacsa1MXGKYBU0KczsBndf0zpLUZdFcndD97JbQ38fMrMO8c+ASmkPPWzAa1H9q/ajn7ZeL5UBVKnofHS93VxkZEqd+TJR6oyZlaXOXGxmn3L3lNMyj6eCU3E9VMp4JjSWYuyJ1l7zAr9090dDvz4FFDnt66ydRgRcpU4zbbG5EcNqRAoFuvstiWN/LjCfLrUODOujorVWg5EIdx8zD3QT2gYtDN4THV8J+GSXc2cCdkQR7d1L7CZXOTbcD7RAej7xeAF5YIvO2w/dSCaiMlFTEFWsH318vOD4LeHvH5H3eSXgLwW2ZwMLVHy/u3PPx+WP9WLbw+e+Am0cpw+PHYErCmxnQcrjt4XHgWgBmLK9Nfy9Mzo2dZB9vRRFICaH51sAlxbYTi57PkTf3dbIGfE4sEbi9W9nYzw35v+NKoGk2lwWaSBsG54vCnxrMLbxZ6/6vSBWxLrhf0Pe+XsLbOdAbKfbw+MXwBw5mynR//fnXrsz1W7OZh5EKcwf36HsUdJe5bkz/GZvIfZO9hs+P43bnRp+hxXC/xNQukjZd7YIsPwQj/lzUER4Moqyfx3lHWev31NybsechTaiA/eC3HXy+lD2vaRffwJWShxfMfTl5OjYwyXtJO8L4bUZavRn2O/rKIr+OHL6XovYQ2uX2P802FyCqttcBFxYYHsjYhBmzz8A3Jywu6Fmnx+NHg+hyOiaOZuFe/gu2u5l6D6ZvJchvZWOR4Ht1WGcX4WYOxeWfGe3hb9TUCoHRHPqIPsx5LZojVI4FxS03TG/F9j9BqXNrBMeJ6IUrCL7bJ59le7z7CyoOsOS4fkCwCcSdh9CgRzQfXhv4FMlfai8dhopj3Dtz44YNo8jp+chw92vIfhc9wOzJo6/A7FWhr2PzaPaY0xpGuRhqv26Ftqc5ml0mc1MaGO6LVrwXQic4O5P5ezmR1G0vJ7B7MDR7r40YwSmPMU1w9Pr3L3Ik1ulrXx0YeAlVH+8g+1iZhuifLj3ooj87MBEd78ossnqB78DLTS7VkQw5Ystj6KsEMT5PEGjq2NbF5bIMUwdC8dXqvr9m5R/r0KlhjZHnvUZ3L1D7LNGXxdDuYyro4jWoyjn8a8J277mBoZowckoCrYMcB/Koe6IxFtN/YOhhtXM+w/HZ/f29B3MbEl3fyhhey4qCxrnP6/g7ptFNpVz160klQFIpjIURWcTxzK6+FaIjphhdsQSKio3Wop+tRu131XfIdhd5e7rdjs2iH7Mg2qpr0eLsjrBA43fzB529yUKzi18bThhZve5+7IFrz2EdELeCs9PQ3nJx+Xsvgx8zN23LWhnQzSWF0abzo55qN9jqC7CeqSSSJiZPYgcVF2FxEx11c+kRVVfANjG3W/P2a2L1kL5Kgu/z9lVjdbn56Fzvb30ctE5BwPPoZSX3YGvAve5+35V3rOk3Y+mjnsiVcHMzkPO/T3RRvlZdD9N6teMBIRr5ds1fptK+lFmdpfn9HJSx3qFSaclS5+83iXgHb++PxKYnR4FXT6ENtjrAX909x/l7KcLx9cbiv5NK2RrA1NqzHvdfX9L6DCMNpj0dtZFukuPhWOLAEegub1ImLnBCMOYSk8ws4tR1O8eU0rCZBSFW9zMjvWc6J6ZnQwsh6KpB7j7PSXNfxJFhBekXc/gBRJU41GOKSjFY3qot0DIw3vI7XT3rM70f1H+GqaKDzF+TkVYK+f3G6bKBWuiRdnNiI7Zk+0g8EygO2cOiW1RJDyFQ8JYPhtFF8tEDHdHTJHXUI7YH0lrD1SGSy15vUADHocitFvTqp8d2/Y7N/AiOkUFbyOXihBQR/9gSSTAlC+Z15GXXsPWC/7veG49pDKgcmvx4vsA6yx1VCd1ppdUhm/TqXeSOlaZLp7BqqUG9KvdgXasRN/BlJY2CzCPSTAtdiS/O/X+vcCVp15WS/02M/tiYlO9M+3fy0iCmdlc7v5s7uDciAkXU+P3As4PVONMcPgDiB24acl7HIoimHd7cXSk9hjqF3qggD+CxmMV9fGpKB99wCFBJwUcNN8sHdrNfgOns8Tu+YQqKRUcAXFeTVWtj2+iald3o+/kDxTkdgeH5+HIkTwjKhH5UspJnXIOFMFrUv3r9KNfttRLe4Dq+lG1UmfC/fmzwKLu/kMzey9ihHakbZnZBKSBlI2xU8N6PRZw3QIFh2ZCmmILhvvlz1AKS5vTwFWR6WUzm8NDCfZRgunDem8rtJYbE3Dp7byIUo1nC4dfROzPo4axaw3qwoeJ4tCPBxGVFy2ATwn/v4MEtQ3dFF+gk8pfRqXafLg/Z5+/w90R/ftetNC4O/XdDUO/kqkMFc+9mARlGOkhXNSr7SD6sxBitPwLiaadTwmFE+WI7oEopnejzW/KroPuO4g+zo42gL9Guh8GfA3RYS8YpjEwe+LYkgW2p6OF5gLA+5Fz4ecFtjcgL/hUFJWciJyIPdtSgwJOb6kMNxPRgJE+RgfduMZ3OyX6vzSVAUV8DkeiVIdFj5NQlZGi96hDF6+cGtDHdudHjqmPhOcLIdZF9voExLx5jXaa9l3A14ZgvB+e+37bHpHdfChXdxJKU/kForffDMw/2H7044HEvm5DVOt3hMfH0AbgSwXnrIPuT7sD61R4j2uAcRX7U3kM9fE7qUQBj8bFucg5ekxqXOTOqZR+QcUUPNpT4O7sYls4vxXY16LZI6fPEii3fTrk+DiowHa1MO5eRHpNb5JY69XtQw/96Jdt5bSHYH9H+Ds1OtYxH1I/deYoFEW+Pzyfi5DukbCdSkRdRxVrpuZsCscbBSkjqAT746jyTOn1MVIewJbh+zgyPF8MOHe4+zXEn3E24B3D3Y/m0dtjTDENiOqtoknuOAB3f8HMOkR93D3lae+Gq8zsEFrRgGuRiMxo8maWYQKihhZFvocLSdHEgvSH/6Ib7T6uSPki7j41f6673x4oUjHq2PYEV1SzyPOfsv8HcFiIduyLalinGAR1WAndULkSQr/RSyTe61UimNkDe8GVdjHRVJ5y/15tvR7rohc1+12BU8xsjvD8WRQl6hV1qoD0Gp39pJmV0sUjvOHubiq39ytXakDR5+tLu+G6OwQGUgSe8KiUq7v/CviVme3uubKGQ4SYOn4A6fGIu/8TWN3M1kbMOYBL3P3qPvRpSODux5rZ31D6QMYUuhc40KM0tNw5VxPEjStiX+APJhHdmGp/SMK2zhjqF6pWT8jGxR20SiMnYa20ypnNbCXa2TApIcRbzGxZd7+vS1/LmFR5lDGeOr5jry9YiLs/bGbTuUTjTjSV/Evh10j36mwUCNgelVTMt1e7DzX70Rdbr8GkCMjWzH83s0+juX3BRLtXBZZdpdQZVO5xZQuVhdz9WTObscDWaGctvEnnfe9/ZjaLKxVxQNA43P+KBDsvCY9Rg7C2OTt6/ghKNR0TMJUjPggx8TYws2WBD7v78cPbswZVMdacBk+Y2e7Ak4g6dxmAqcbvUCl0Ho9yibPyZp9HEYHNCs8YXXgCbbpHGooWJoegG93pMCCEOT/wIFLX/xgFVQwCZs49r2NbC9aqCZ6Ep+vKL4PSAbZAKQy/QwJ5qfPXDovErYBjTeWUfufuvaQo9LsSQh1sAxwc/s/T39dnkJUIgFdN5bgeMrOvAU8BRUrddWyromwB3vY8W8S6cj5XCL8xntNC6AGVUxnCe99lZqd7MXU6hUPpThfPUKX0Y1/atfqlKo8xsz2IaOWodGCd76YDHpT9Q5/2jJ8X2F+DouujAu5+sZld6blqREOIH6GI8njk8CzDoVQfQ/1CJQq4tyo+zAq8GjaSWQrWTDnzummVawI7mFnGoMk29vmc6sqOgJoO1Ax1aPYvhw3pXSYthL+jaHUSNTbrdan+dfrRF9uaqQwAB4aN9z609KM6HL9WP3Xm9TAePZw/L8Wb+xOBW00aEqCUo/wmcq3MSeHtqUszUOwsP4fu18eIQBYYKVojptaGoxQnod87S734M1rTNk6DUYIxJYRoKsnzAzTZH+GhrFaIwHzA3SvnwZe8xxSvKGI3GmES03sf8tB2i84M9Xv3Ipp4q7t/KHfsFndfzYJQj5mdAVzt6ZzfT7j71tGxyrY9fL745tYROUxtCszsVpQyMQnR+yotsM3s/SjStrW7d1swp84vFc6blrDeRAUfoFP/4Avu3qF/YBIJux+YE20S5wAO9kRJoTq2NT5fJiAZi0cSno939ziPvraoWL9gFYTmcvbXoOoQVUq5zY8EZ29z9+tNpR8/Fkf6+9Wumd1OS9/hWHL6DvnxFpxqM9AuSvmmu+/SrT9VMZzXXz9hZg+jNJfrgeuAG32IWHtmdru7r1LRtvIY6hfMbB20qH4EXUsLAzsFZ1DK/hZgPQ+lFE25wpe7++oJ283d/dwKfVg4ddwTwrf9hNUTLFwYjaEZ0YZ3duAod384YXsdEs87Hm2+/w7s6AlBvzp96KEf/bK9nQSTwt2/k7Mbj9hqSyA23vHuXlRKufYcZ2afRcGOD6AxvQVKq8zr3WT2K9PSjxqU+HbUZuXrY7hhZhu5+0VWzHordRiPFpjZbe6+am5NN2b2T28HjCmmgbs/jSbC/PGhjMC8YmZruvsNMCCslafzjmY8Hh4z0j06M6TwHkQTgbfMbCvkVQbdnAaaDH/3BM4LN7KMTr0K+nyfoR11bGuhTuTQzKZHNK7Fw/tuBixoZicC+6U8/FaDlVABcSQJWtGk4aDtVo7ER/hgFn0PkcNfmFmSyuvut4V/X0TpDsUdqWFbFTUjcb2IivULh1IvOluZLu5dUgP63O70kcP5B5lDyN0fkP9JMLPpw0K7Kq28QQ7uvkRw3HwEibEdaWbPDdEi8koz+0T2W3ZBnVSGIUeIgq6AqPJVKeDjsw0RgLu/aGZtKQdm9jl3PxVYxMz2zjeQ/3x554CZzQnsRk5ort8o2pjHMKUYLejuR4Tn1yLWl6O0uo5NNdrsjkOfaS/EwEg6Xqv0oW4/+mWb63cVJsXJKDXheqRRsyxi5hWh1hzn7qeZ2R0oTRiU1nh/bGMSPc3wWHgMvObu/ynpTxV0vT5GCjykZI0V50AJXjJVtcsYKKsxMpnNDQowppwGRZuCDF5MK6uDoc4lHlHwhLr8CMdnUTmyI9FEdAvwOVNKytegXs5vHdtBotsm62dIHGxRDykBJir6z8MjdYM/CbESvkINVkKyc/2vhFAHlanzVkP/oM58MY3mliqok0vcbzyBxMKq9qMrXdzqpwb0o92q+g5/QmlwtZTFqyLHvJrFuuSCj0aY2YJIxPMjaNN8LxIbHQrsBuxrZq+hDVLZ91YnlWHI4VJ739jdf4mE0KrgJTNb2d0nA5hKJefHa0Zjn41ODIxlk7r991Cu8fko3e+HaJN9RuLcvsDMbnD3Na2TdZj67fZFUfUMM6HI9myIAn3OwMk9bMCtOtW/cj/6aJuhairDst5KPzwezWVl6GWOmwV9Z046tfOO8Frmic1+bwv/D9Ypnr8+VmGEBvhG0Pqi39gb6bAsbmY3AvPSHuhrMMIxppwGwIfRQvYMpMJcJCLWMzyRS2wqB1j1Rj+iYRXr9o4UuIRiNip4+YacbWXGyRCzU3rBhsBS8YYsjLWvoHJZA06DXlgJVWDK3Z/q7st1Ne4jajow6ugf1Jkv+j63VEQtUbE+o250dm53/0SXNnsp/TjU7VZ1UmVj4OvANWb2SHi+CEPAQumReTXa8DhSsz/I3TtYgoNBze+vyhjqN24ys18jhlicQz+5wH5P4GyToCQoLXObnM0loY2OYICZxffNU5Co87lonrwFOXCWD+ycaYXPQuXfbkZ3fyJ6fkOITv/HpPcQo5cNeCXRxJr96JdthqpMioE1gbu/ETOoYoS17Y3AtxC74NHw0iLAFwr6gJl9H1UCOBfNkyea2dke6Su5+6JF5w8R9qR1fThyiPWcXtpnjJT1RV/h7pNNaT8Zm+rBXtenDYYHY81pMD8qD7ctylu9BOWgDkZFPglvFx7bG1F1xwKq1u0dVtgoFI6pGTn0VAQ3RKTyx3thJXSF96ggPcyoU4mgznwxzeaWMowwBkjd6GwVunil1IB+tlvjO543onwfQ4hEou9jJUaRKOEwYiWUy7ydmX0LeAiVfBu0MJYpdXCKu79kZp9DrJBDC+ayOqkM/UKWa/2D6Jij8ospTAWWJkpnQBvGGFeZ2Sfd/bH4oJntBHwXyCpVzO3uE8P/fzSzfyJKell6RD9wHvqdqmi2zBU/cfevRU/nzdn2sgGvSvWv04++2PbApFght/4oSj9cEDE5l0Gidf9BDIET3f1vFGNbVAL61dCfnwCTSVR9MrPPIB2p/4bncyKdmfNL2i+ESXfoCXe/LTiFv4wCKZehkrgjESNifdEvmFmRUPxSZoa7/36adqhBzxhTToMwsV8GXGZmM6ELcFJYJPajJFaGseQVfKerDNkEV07fteEGNNKQ5cfdXmo1glAz8nVfoE235VuHxe8DOdvKrIQeUFdBerhRWf+gznwxjHPLSEbd6GwVunid0o/9brcbpkORynj+z2jgbweWwKDh7neZ2V+Av6AUhc8hhfahUNM+Cm2OVkCR5uNRWkpK4K5OKkNf4O5r1zzlZpc45j3ZATObTNh0B+wFXGFmn3L3h4LNt9HGpO17MLO5aI3lfyDH9qyhb4PNL6+KOpott5rZF71TtPjLdNLt62zWM1Sl+tfpR79sazEpqjpG3f3r4T1nRGyL1VFUfDeT9siyBac+hpynWYrkTOgaT2F/d88qJ+Duz5nZ/ihNphccg8QuCX39DrA7sCISth1xdPi3wfqiiA0Muv82ToNRgjHlNAAIF9yn0UW3CHAY/R+Qw51bPJSoVLd3uOE54Rgzm9XdXyo/a1RhN+D3ZvYFWrl/q6LcwLwgYx1WQl2MNo2LyvoHUG++GKa5ZSSjVnS2otOs1u/Xz3Yr4O/u/oPuZg2KYFJ7nwm4CaWTreVDp9T/hrt7iML+KjjDi9TJh83JYwmBwhieS/cxVQB5DxrHK9HaaM+O8sjjc/8QHCGXmtmmwC7oPrKWuz8bmc6B7jPxpj1LixiK/PKqqKPZshdwvpltR6uvH0DjadOcbZ0NeIaqVP86/eiXbU9MihqYGY2vOcLjb6jqQhFeQ8GGK8Lz9YAbzOww6GCC5tkxMLi9yXSRk2tr4FhX5ZBzzWzKINrtK8by+sLdh0Q0usHwY6yVXDwZidddCpzp7vd0OaVO27XLAY5GmMqoXQ+8l1bd3onZJn2kwcw+jCJIs7n7QiGq9GV3/+owd21IYCrD9X9onN3r7lclbM4Hfl/ASthqBLMChhV15ot+zi2jFWFOnBUtELtGZ2vSxev0oy/tVnjfOz1R7rNBdZjZvO7el/S3wJC7DOlLrIXS7KZ4EIDL2Q7LGArvnZXefR/a0GeiaBuh8nO75Ox3AHZEkd+YafcCcFKK6mtma6LI7U3ontCzSG4/YeXlZ5NzS3SPBN0jO0SLTeW4z0dzVccG3CWAnNnmqf630qL67+vuKf2DSv3ol62ZPezuSxSc/xd3X7yo/TKY2bHhvV9Aufa3ALfkHE6p876CNv5vIcHENnaXt1eSOgF4DjgCfce7A3O5+4499vkeYEWXVsMDwJfc/brsNR9mjaYU3k7rixCMzGumNc73UYKx5jR4ixaFupvyboOKMJUHPHS4+5FCuKFvAVzorbqvI/LG0C+Y2XuQR/oVEqwEd39qEG1XVZAedagzXzRzy+BhZlORQv7yiCZ+PLCZuyfroQ93uxXedyjKgr2tYapCtD/a1IPE+H7gIb95kG3Pj2j4t7n79abSjh/LO1eD7bCMoVwfLgc295YuzTuAs919/QL7zUMEtazNLNhhaIP8OtrEJectM7vK3dftdmy0ouIG/EZgmyxyH6LT6xCo/iPxuzCz04BJBUyKj7n7tj22exmqMnMPcjjdTEnFHGuJMn8B+CtiEbwXpUh8x9OlomdFlTvWQ+PycuDAXpmjZrYf8CngGWAhYOXAOFoCONnd1+il3X7i7bK+MLOjERtqbeA3aO3+J3ffeVg71qAyxpTToEF/YGaPu/tCw92PFMzsVnf/UBz1M7O7vL2m8NsCVVgJPbR5OwkFaXf/TumJDcY86kZnzWyyu69sUtZ+KtDFJ7vysgfTj76026D/MLNz0YYkizx+HljB3YuEs3p9n3mAf5dsdoZ9DIWo6AoexAcDXfkud186Z/c5dz/VzPYhLQJcVL2k7L3HI9bQ1cDHaE95uNTdl6nb5miFmd3m7qtGz3/tQQPBzG5x99WGr3dp1GFS9NC2oXXF6uGxHBJEvNnd98/Z/hLpuezlnaLML7v7nr32o2afV0N6TJdnzgczWwoxUouqkTToM8xsqrsvH/2dDbFkh7tyTYOKGBOU+gZ9x0gWenzCzFYH3CTWswctkcS3FULUpJDmOIh2qyhIN3j7oY7QHMALJhG2zwFrmdl0wAxD0I9+tdug/1jc2xXyDxhs3nHYMPwEbWx+iMbkPMA4k7hsqmznSBhDvwX+ZGbnIWfAZ1ApxDyyHPXZEq/1GgX6MipR925am06A5xFt/O2EXkQThxXu/jSweo5JcUlZ2kONth24x8yeA/4bHhsCH0QsoRjdRJn3zLcfNvNfR3n800fn9Vzm20N1nNyxP/faXoMhQ5am8rKZvRvN0f0uvdlgCNE4DRpUwUimo+yKSgK9B3gSUdt2G9YejS1kCtJTrFxBusHbD5WF5gK2RnTxnd39H4Eu/rMh6Ee/2m3Qf7xiZmu6+w0wwF7JV7eoi18jxfQ5kBN1A3e/xVR+7Qykc5DHsI8hd/+RmV2KqkgA7OTudyZMLwn2HSK1ZlamUl723r8CfmVmu/vYUGsfDHoRTRwRGOrAgZntgdgFa6DUlhtRisIJpIUQPcXm8XJR5rOBoxFd/c2h6HeDEYuLTSU1D0aptKDfvcEoQZOe0AB4+wg9NqgHM1sY+CfSM9gLLcSPdPd83ecGbzNYDaG5xLmldPFB9Kkv7TboDwJL5RQ0rwA8C+zg7lMH0eYUd18x/H9/TK23CuKVwzmGTIKFS7r7iWY2L6JTP5qzeRD4pLs/lju+E/Bd71H0LrQxI3LEZxoTk4BjUrnoYxX9pPqPNpjZIUjL4EZ3/3sF+/OpKcpsZne4+weGqMsNRiDMbFXgCXf/R3i+PWJ1PYCE1httoFGCxmnQYFQi5J4Wwd39h9OsM2McZjYzsJC7PzjcfWkwclBVaK6MLg4U0cWrvH9f2m0w7RHynjMq86CEd2MtgrwuQeL5iBlDpioKqwDvc/elAn337Lxwm5l9CrHrPuXuD4Vj30bX4gbu/uQg+vAblJYRa0y86bkKDm8HVBFNbNAO60GU2cwmAk8D5yFHDQDNRnLswMwmA+u5+3/MbC3gTFQlY0VgGXffYjj716A6GqdBg1GJIAKVx6zAzsA73T2V79mgJgLd9eeoDvSiZrYiUjdvyjg2GEBZdDaIaWZ08WPJ0cW7RX5L3rMv7TYYXtgghXetvGzfeHefIbIdMWMoaDmsBEz2lqjvVHdfPmG7LnAMsCmwC9qYbehdSuGVvPf0rhJ1HSLCqWMNGpTBaogym9mjicPu7ov1q38Npi3iOcTMjgD+5e4Tw/MBZliDkY+Gct5gVMLdf5H9bypNNQHRpM8EflF0XoPamIgEjyYBuPsUM1tkGPvTYJjRg9Dc9O5+eTj3B5lIlbs/IGHuntGvdhsMLwb147n7dDXMR9IY+l/QCPHQn0LtGHe/ysx2RPPyTcC67v7qIN77T6j6yZtmtri7/yX0YTGaPPMGNVFHW8HdGyG8sY/pMscksC7wpei1Zh86ijBuuDvQoEGvMLO5zexAYCqaeFZ292+6lIQbDA3e8CGomd5gTOHXqBb3GWhhuIu7z4/yoH+csH8r+j8vcjcYqlu/2m0wvJiWv91IGkNnmdkxwJxm9kXgSuC4vJGZvWBmzwOXopKI6wJPR8d7QeYh+TpwjZlNMrNJ6PpOsfoaNBgUzGzf6P8tc68dNO171KCPOAO41swuQPPs9QBmtgSqxtFglKBJT2gwKmFmPwM2Q5TSI9z9xWHu0piCmf0BVaH4LnAV8C1gc1TScgZ333UYu9dgGFFXaK4OXbxmP/rSboP+Y6QI7460MWRmHwc+Ed7/j+5+xTR63yeBQ8LTmYHp0PcyHnjF3Q8pOrdBg15QR3ukwehHYCguAFzu7i+FY0shsdfJpSc3GDFoaCENRiv2QaI53wX2i6ikhvLhZh+ujo0RnAT8EVHPl0Pf9enhWCMy+fZGrehsTbp4ZfSr3Qb9h7u/Y7j7ACNvDAUnwRWZRsg0fOvpgNloTw3JdIFGxG/VYMzBCv5PPW8wypGlfuWO/Xk4+tKgdzRMgwYNGiQRcmq/D6yPnAfZZOFN5Onti5EWnW3QYDRjJFRwaCK7DaY1GqZBgwajDw3ToEGDBkV4HW0OZ0JRp8bD2GDERWcbNBjl+DWtCg5Xk6vgAEyLso9NZLfBtMYKQYPDgJkjPQ5DaTENGjQYYWicBg0aNOiAma2PclwvRAKTL3c5pUGDBg0a1MdIqOCw7rR6owYNoHE+N2gwGtE4DRo0aJDCfsCW7n7vcHekQYMGDcYwhr2Cg7v/Z1q8T4MGDRo0GL1oNA0aNGjQoEGDBg2GAY1GSIMGDRo0GA1onAYNGjRo0KBBgwYNGjRo0KBBgyTGDXcHGjRo0KBBgwYNGjRo0KBBgwYjE43ToEGDBg0aNGjQoEGDBg0aNGiQROM0aNCgQYMGDRo0aNCgQYMGDRok0TgNGjRo0KBBgwYNGjRo0KBBgwZJNE6DBg0aNGjQoEGDBg0aNGjQoEES/w+eEqJn8BDHXQAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<Figure size 1440x504 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize = (20, 7))\n",
    "sns.heatmap(df.isnull())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "36501be5",
   "metadata": {},
   "outputs": [],
   "source": [
    "df['MSZoning']=df['MSZoning'].fillna(df['MSZoning'].mode()[0])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "7444121a",
   "metadata": {},
   "outputs": [],
   "source": [
    "df['LotFrontage']=df['LotFrontage'].fillna(df['LotFrontage'].median())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "22d0e963",
   "metadata": {},
   "outputs": [],
   "source": [
    "df.drop(['Alley'],axis=1,inplace=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "c8cb539f",
   "metadata": {},
   "outputs": [],
   "source": [
    "df['Utilities']=df['Utilities'].fillna(df['Utilities'].mode()[0])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "405c9e33",
   "metadata": {},
   "outputs": [],
   "source": [
    "df['Exterior1st']=df['Exterior1st'].fillna(df['Exterior1st'].mode()[0])\n",
    "df['Exterior2nd']=df['Exterior2nd'].fillna(df['Exterior2nd'].mode()[0])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "14f0651f",
   "metadata": {},
   "outputs": [],
   "source": [
    "df['MasVnrType']=df['MasVnrType'].fillna(df['MasVnrType'].mode()[0])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "d036e7f7",
   "metadata": {},
   "outputs": [],
   "source": [
    "df['MasVnrArea']=df['MasVnrArea'].fillna(0)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "7c78e509",
   "metadata": {},
   "outputs": [],
   "source": [
    "df['BsmtQual']=df['BsmtQual'].fillna('NA')\n",
    "df['BsmtCond']=df['BsmtCond'].fillna('NA')\n",
    "df['BsmtExposure']=df['BsmtExposure'].fillna('NA')\n",
    "df['BsmtFinType1']=df['BsmtFinType1'].fillna('NA')\n",
    "df['BsmtFinType2']=df['BsmtFinType2'].fillna('NA')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "be2e3914",
   "metadata": {},
   "outputs": [],
   "source": [
    "df['BsmtFinSF1']=df['BsmtFinSF1'].fillna(0)\n",
    "df['BsmtFinSF2']=df['BsmtFinSF2'].fillna(0)\n",
    "df['BsmtUnfSF']=df['BsmtUnfSF'].fillna(0)\n",
    "df['TotalBsmtSF']=df['TotalBsmtSF'].fillna(0)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "id": "6a263aab",
   "metadata": {},
   "outputs": [],
   "source": [
    "df['BsmtFullBath']=df['BsmtFullBath'].fillna(df['BsmtFullBath'].median())\n",
    "df['BsmtHalfBath']=df['BsmtHalfBath'].fillna(df['BsmtHalfBath'].median())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "id": "8cee9400",
   "metadata": {},
   "outputs": [],
   "source": [
    "df['KitchenQual']=df['KitchenQual'].fillna(df['KitchenQual'].mode()[0])\n",
    "df['Functional']=df['Functional'].fillna(df['Functional'].mode()[0])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "id": "03e8db9c",
   "metadata": {},
   "outputs": [],
   "source": [
    "df['FireplaceQu']=df['FireplaceQu'].fillna('NA')\n",
    "df['GarageType']=df['GarageType'].fillna('NA')\n",
    "df['GarageFinish']=df['GarageFinish'].fillna('NA')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "id": "7150c9e1",
   "metadata": {},
   "outputs": [],
   "source": [
    "df['GarageYrBlt']=df['GarageYrBlt'].fillna(0)\n",
    "df['GarageCars']=df['GarageCars'].fillna(0)\n",
    "df['GarageArea']=df['GarageArea'].fillna(0)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "id": "efbb6619",
   "metadata": {},
   "outputs": [],
   "source": [
    "df['GarageQual']=df['GarageQual'].fillna('NA')\n",
    "df['GarageCond']=df['GarageCond'].fillna('NA')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "id": "37122a47",
   "metadata": {},
   "outputs": [],
   "source": [
    "df.drop(['PoolQC','Fence','MiscFeature'],axis=1,inplace=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "id": "1430978d",
   "metadata": {},
   "outputs": [],
   "source": [
    "df['SaleType']=df['SaleType'].fillna(df['SaleType'].mode()[0])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "id": "77745eea",
   "metadata": {},
   "outputs": [],
   "source": [
    "#df.drop(['Id'],axis=1,inplace=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "id": "d995c6f4",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "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",
       "MasVnrType       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",
       "FireplaceQu      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",
       "dtype: int64"
      ]
     },
     "execution_count": 26,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.isnull().sum()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "id": "f318acff",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:>"
      ]
     },
     "execution_count": 27,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
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\n",
      "text/plain": [
       "<Figure size 1440x432 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize = (20, 6))\n",
    "sns.heatmap(df.isnull(),yticklabels=False,cbar=False,cmap='viridis')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "id": "9b0c9dc8",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(1459, 76)"
      ]
     },
     "execution_count": 28,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "id": "ebe68c17",
   "metadata": {},
   "outputs": [],
   "source": [
    "df.to_csv('test_df.csv', index=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "id": "27c13ee7",
   "metadata": {},
   "outputs": [],
   "source": [
    "df_t = pd.read_csv('test_df.csv')"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.8.8"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}