House_Prices.ipynb

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    "# <span style='color:dodgerblue; font-weight:bold;'> House Prices </span>\n",
    "\n",
    "Kaggle | House Prices - Advanced Regression Techniques\n",
    "\n",
    "Ask a home buyer to describe their dream house, and they probably won’t begin with the height of the basement ceiling or the proximity to an east-west railroad. But this playground competition’s dataset proves that much more influences price negotiations than the number of bedrooms or a white-picket fence.\n",
    "\n",
    "With 79 explanatory variables describing (almost) every aspect of residential homes in Ames, Iowa, this competition challenges you to predict the final price of each home."
   ]
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   "source": [
    "### <span style='color:aqua; font-weight:bold;'> Import Packages and Load the data</span> "
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    "# Essential\n",
    "import numpy as np\n",
    "import pandas as pd\n",
    "\n",
    "# Visualization\n",
    "import seaborn as sns\n",
    "import matplotlib.pyplot as plt\n",
    "import matplotlib.style as style\n",
    "import plotly.graph_objects as go\n",
    "import plotly.express as px\n",
    "%matplotlib inline\n",
    "\n",
    "# Machine learning and statistical\n",
    "import statsmodels.api as sm\n",
    "from sklearn.model_selection import train_test_split, cross_val_predict, cross_val_score\n",
    "from sklearn.impute import SimpleImputer\n",
    "from sklearn.decomposition import PCA\n",
    "from sklearn.preprocessing import StandardScaler\n",
    "from sklearn.metrics import r2_score, mean_absolute_error, mean_squared_error\n",
    "from sklearn.linear_model import LinearRegression\n",
    "from sklearn.tree import DecisionTreeRegressor\n",
    "from sklearn.ensemble import RandomForestRegressor\n",
    "from sklearn.svm import SVR\n",
    "from sklearn.neural_network import MLPRegressor\n",
    "from xgboost import XGBRegressor\n",
    "\n",
    "# Ignore useless warnings\n",
    "import warnings\n",
    "warnings.filterwarnings('ignore')"
   ]
  },
  {
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   "execution_count": 40,
   "id": "7a914d94",
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   "source": [
    "train = pd.read_csv(\"train.csv\") # read training data."
   ]
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     "start_time": "2023-05-23T22:29:20.423065",
     "status": "completed"
    },
    "tags": []
   },
   "source": [
    "# <span style='color:dodgerblue; font-weight:bold;'> Exploratory Data Analysis</span> "
   ]
  },
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       "(1460, 81)"
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     "execution_count": 41,
     "metadata": {},
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   "source": [
    "train.shape # shape of training."
   ]
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       "   Id  MSSubClass MSZoning  LotFrontage  LotArea Street Alley LotShape  \\\n",
       "0   1          60       RL         65.0     8450   Pave   NaN      Reg   \n",
       "1   2          20       RL         80.0     9600   Pave   NaN      Reg   \n",
       "2   3          60       RL         68.0    11250   Pave   NaN      IR1   \n",
       "3   4          70       RL         60.0     9550   Pave   NaN      IR1   \n",
       "4   5          60       RL         84.0    14260   Pave   NaN      IR1   \n",
       "5   6          50       RL         85.0    14115   Pave   NaN      IR1   \n",
       "6   7          20       RL         75.0    10084   Pave   NaN      Reg   \n",
       "7   8          60       RL          NaN    10382   Pave   NaN      IR1   \n",
       "8   9          50       RM         51.0     6120   Pave   NaN      Reg   \n",
       "9  10         190       RL         50.0     7420   Pave   NaN      Reg   \n",
       "\n",
       "  LandContour Utilities  ... PoolArea PoolQC  Fence MiscFeature MiscVal  \\\n",
       "0         Lvl    AllPub  ...        0    NaN    NaN         NaN       0   \n",
       "1         Lvl    AllPub  ...        0    NaN    NaN         NaN       0   \n",
       "2         Lvl    AllPub  ...        0    NaN    NaN         NaN       0   \n",
       "3         Lvl    AllPub  ...        0    NaN    NaN         NaN       0   \n",
       "4         Lvl    AllPub  ...        0    NaN    NaN         NaN       0   \n",
       "5         Lvl    AllPub  ...        0    NaN  MnPrv        Shed     700   \n",
       "6         Lvl    AllPub  ...        0    NaN    NaN         NaN       0   \n",
       "7         Lvl    AllPub  ...        0    NaN    NaN        Shed     350   \n",
       "8         Lvl    AllPub  ...        0    NaN    NaN         NaN       0   \n",
       "9         Lvl    AllPub  ...        0    NaN    NaN         NaN       0   \n",
       "\n",
       "  MoSold YrSold  SaleType  SaleCondition  SalePrice  \n",
       "0      2   2008        WD         Normal     208500  \n",
       "1      5   2007        WD         Normal     181500  \n",
       "2      9   2008        WD         Normal     223500  \n",
       "3      2   2006        WD        Abnorml     140000  \n",
       "4     12   2008        WD         Normal     250000  \n",
       "5     10   2009        WD         Normal     143000  \n",
       "6      8   2007        WD         Normal     307000  \n",
       "7     11   2009        WD         Normal     200000  \n",
       "8      4   2008        WD        Abnorml     129900  \n",
       "9      1   2008        WD         Normal     118000  \n",
       "\n",
       "[10 rows x 81 columns]"
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     "execution_count": 42,
     "metadata": {},
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   "source": [
    "train.head(10) # head of training."
   ]
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       "      <td>1.0</td>\n",
       "      <td>365.75</td>\n",
       "      <td>730.5</td>\n",
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       "      <td>21.0</td>\n",
       "      <td>59.00</td>\n",
       "      <td>69.0</td>\n",
       "      <td>80.00</td>\n",
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       "      <td>1300.0</td>\n",
       "      <td>7553.50</td>\n",
       "      <td>9478.5</td>\n",
       "      <td>11601.50</td>\n",
       "      <td>215245.0</td>\n",
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       "      <th>OverallQual</th>\n",
       "      <td>1460.0</td>\n",
       "      <td>6.099315</td>\n",
       "      <td>1.382997</td>\n",
       "      <td>1.0</td>\n",
       "      <td>5.00</td>\n",
       "      <td>6.0</td>\n",
       "      <td>7.00</td>\n",
       "      <td>10.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>OverallCond</th>\n",
       "      <td>1460.0</td>\n",
       "      <td>5.575342</td>\n",
       "      <td>1.112799</td>\n",
       "      <td>1.0</td>\n",
       "      <td>5.00</td>\n",
       "      <td>5.0</td>\n",
       "      <td>6.00</td>\n",
       "      <td>9.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>YearBuilt</th>\n",
       "      <td>1460.0</td>\n",
       "      <td>1971.267808</td>\n",
       "      <td>30.202904</td>\n",
       "      <td>1872.0</td>\n",
       "      <td>1954.00</td>\n",
       "      <td>1973.0</td>\n",
       "      <td>2000.00</td>\n",
       "      <td>2010.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>YearRemodAdd</th>\n",
       "      <td>1460.0</td>\n",
       "      <td>1984.865753</td>\n",
       "      <td>20.645407</td>\n",
       "      <td>1950.0</td>\n",
       "      <td>1967.00</td>\n",
       "      <td>1994.0</td>\n",
       "      <td>2004.00</td>\n",
       "      <td>2010.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>MasVnrArea</th>\n",
       "      <td>1452.0</td>\n",
       "      <td>103.685262</td>\n",
       "      <td>181.066207</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.0</td>\n",
       "      <td>166.00</td>\n",
       "      <td>1600.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>BsmtFinSF1</th>\n",
       "      <td>1460.0</td>\n",
       "      <td>443.639726</td>\n",
       "      <td>456.098091</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.00</td>\n",
       "      <td>383.5</td>\n",
       "      <td>712.25</td>\n",
       "      <td>5644.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>BsmtFinSF2</th>\n",
       "      <td>1460.0</td>\n",
       "      <td>46.549315</td>\n",
       "      <td>161.319273</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.00</td>\n",
       "      <td>1474.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>BsmtUnfSF</th>\n",
       "      <td>1460.0</td>\n",
       "      <td>567.240411</td>\n",
       "      <td>441.866955</td>\n",
       "      <td>0.0</td>\n",
       "      <td>223.00</td>\n",
       "      <td>477.5</td>\n",
       "      <td>808.00</td>\n",
       "      <td>2336.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>TotalBsmtSF</th>\n",
       "      <td>1460.0</td>\n",
       "      <td>1057.429452</td>\n",
       "      <td>438.705324</td>\n",
       "      <td>0.0</td>\n",
       "      <td>795.75</td>\n",
       "      <td>991.5</td>\n",
       "      <td>1298.25</td>\n",
       "      <td>6110.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1stFlrSF</th>\n",
       "      <td>1460.0</td>\n",
       "      <td>1162.626712</td>\n",
       "      <td>386.587738</td>\n",
       "      <td>334.0</td>\n",
       "      <td>882.00</td>\n",
       "      <td>1087.0</td>\n",
       "      <td>1391.25</td>\n",
       "      <td>4692.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2ndFlrSF</th>\n",
       "      <td>1460.0</td>\n",
       "      <td>346.992466</td>\n",
       "      <td>436.528436</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.0</td>\n",
       "      <td>728.00</td>\n",
       "      <td>2065.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>LowQualFinSF</th>\n",
       "      <td>1460.0</td>\n",
       "      <td>5.844521</td>\n",
       "      <td>48.623081</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.00</td>\n",
       "      <td>572.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>GrLivArea</th>\n",
       "      <td>1460.0</td>\n",
       "      <td>1515.463699</td>\n",
       "      <td>525.480383</td>\n",
       "      <td>334.0</td>\n",
       "      <td>1129.50</td>\n",
       "      <td>1464.0</td>\n",
       "      <td>1776.75</td>\n",
       "      <td>5642.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>BsmtFullBath</th>\n",
       "      <td>1460.0</td>\n",
       "      <td>0.425342</td>\n",
       "      <td>0.518911</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.00</td>\n",
       "      <td>3.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>BsmtHalfBath</th>\n",
       "      <td>1460.0</td>\n",
       "      <td>0.057534</td>\n",
       "      <td>0.238753</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.00</td>\n",
       "      <td>2.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>FullBath</th>\n",
       "      <td>1460.0</td>\n",
       "      <td>1.565068</td>\n",
       "      <td>0.550916</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.00</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.00</td>\n",
       "      <td>3.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>HalfBath</th>\n",
       "      <td>1460.0</td>\n",
       "      <td>0.382877</td>\n",
       "      <td>0.502885</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.00</td>\n",
       "      <td>2.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>BedroomAbvGr</th>\n",
       "      <td>1460.0</td>\n",
       "      <td>2.866438</td>\n",
       "      <td>0.815778</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2.00</td>\n",
       "      <td>3.0</td>\n",
       "      <td>3.00</td>\n",
       "      <td>8.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>KitchenAbvGr</th>\n",
       "      <td>1460.0</td>\n",
       "      <td>1.046575</td>\n",
       "      <td>0.220338</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.00</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.00</td>\n",
       "      <td>3.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>TotRmsAbvGrd</th>\n",
       "      <td>1460.0</td>\n",
       "      <td>6.517808</td>\n",
       "      <td>1.625393</td>\n",
       "      <td>2.0</td>\n",
       "      <td>5.00</td>\n",
       "      <td>6.0</td>\n",
       "      <td>7.00</td>\n",
       "      <td>14.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Fireplaces</th>\n",
       "      <td>1460.0</td>\n",
       "      <td>0.613014</td>\n",
       "      <td>0.644666</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.00</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.00</td>\n",
       "      <td>3.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>GarageYrBlt</th>\n",
       "      <td>1379.0</td>\n",
       "      <td>1978.506164</td>\n",
       "      <td>24.689725</td>\n",
       "      <td>1900.0</td>\n",
       "      <td>1961.00</td>\n",
       "      <td>1980.0</td>\n",
       "      <td>2002.00</td>\n",
       "      <td>2010.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>GarageCars</th>\n",
       "      <td>1460.0</td>\n",
       "      <td>1.767123</td>\n",
       "      <td>0.747315</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.00</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.00</td>\n",
       "      <td>4.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>GarageArea</th>\n",
       "      <td>1460.0</td>\n",
       "      <td>472.980137</td>\n",
       "      <td>213.804841</td>\n",
       "      <td>0.0</td>\n",
       "      <td>334.50</td>\n",
       "      <td>480.0</td>\n",
       "      <td>576.00</td>\n",
       "      <td>1418.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>WoodDeckSF</th>\n",
       "      <td>1460.0</td>\n",
       "      <td>94.244521</td>\n",
       "      <td>125.338794</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.0</td>\n",
       "      <td>168.00</td>\n",
       "      <td>857.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>OpenPorchSF</th>\n",
       "      <td>1460.0</td>\n",
       "      <td>46.660274</td>\n",
       "      <td>66.256028</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.00</td>\n",
       "      <td>25.0</td>\n",
       "      <td>68.00</td>\n",
       "      <td>547.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>EnclosedPorch</th>\n",
       "      <td>1460.0</td>\n",
       "      <td>21.954110</td>\n",
       "      <td>61.119149</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.00</td>\n",
       "      <td>552.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3SsnPorch</th>\n",
       "      <td>1460.0</td>\n",
       "      <td>3.409589</td>\n",
       "      <td>29.317331</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.00</td>\n",
       "      <td>508.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ScreenPorch</th>\n",
       "      <td>1460.0</td>\n",
       "      <td>15.060959</td>\n",
       "      <td>55.757415</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.00</td>\n",
       "      <td>480.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>PoolArea</th>\n",
       "      <td>1460.0</td>\n",
       "      <td>2.758904</td>\n",
       "      <td>40.177307</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.00</td>\n",
       "      <td>738.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>MiscVal</th>\n",
       "      <td>1460.0</td>\n",
       "      <td>43.489041</td>\n",
       "      <td>496.123024</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.00</td>\n",
       "      <td>15500.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>MoSold</th>\n",
       "      <td>1460.0</td>\n",
       "      <td>6.321918</td>\n",
       "      <td>2.703626</td>\n",
       "      <td>1.0</td>\n",
       "      <td>5.00</td>\n",
       "      <td>6.0</td>\n",
       "      <td>8.00</td>\n",
       "      <td>12.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>YrSold</th>\n",
       "      <td>1460.0</td>\n",
       "      <td>2007.815753</td>\n",
       "      <td>1.328095</td>\n",
       "      <td>2006.0</td>\n",
       "      <td>2007.00</td>\n",
       "      <td>2008.0</td>\n",
       "      <td>2009.00</td>\n",
       "      <td>2010.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>SalePrice</th>\n",
       "      <td>1460.0</td>\n",
       "      <td>180921.195890</td>\n",
       "      <td>79442.502883</td>\n",
       "      <td>34900.0</td>\n",
       "      <td>129975.00</td>\n",
       "      <td>163000.0</td>\n",
       "      <td>214000.00</td>\n",
       "      <td>755000.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                count           mean           std      min        25%  \\\n",
       "Id             1460.0     730.500000    421.610009      1.0     365.75   \n",
       "MSSubClass     1460.0      56.897260     42.300571     20.0      20.00   \n",
       "LotFrontage    1201.0      70.049958     24.284752     21.0      59.00   \n",
       "LotArea        1460.0   10516.828082   9981.264932   1300.0    7553.50   \n",
       "OverallQual    1460.0       6.099315      1.382997      1.0       5.00   \n",
       "OverallCond    1460.0       5.575342      1.112799      1.0       5.00   \n",
       "YearBuilt      1460.0    1971.267808     30.202904   1872.0    1954.00   \n",
       "YearRemodAdd   1460.0    1984.865753     20.645407   1950.0    1967.00   \n",
       "MasVnrArea     1452.0     103.685262    181.066207      0.0       0.00   \n",
       "BsmtFinSF1     1460.0     443.639726    456.098091      0.0       0.00   \n",
       "BsmtFinSF2     1460.0      46.549315    161.319273      0.0       0.00   \n",
       "BsmtUnfSF      1460.0     567.240411    441.866955      0.0     223.00   \n",
       "TotalBsmtSF    1460.0    1057.429452    438.705324      0.0     795.75   \n",
       "1stFlrSF       1460.0    1162.626712    386.587738    334.0     882.00   \n",
       "2ndFlrSF       1460.0     346.992466    436.528436      0.0       0.00   \n",
       "LowQualFinSF   1460.0       5.844521     48.623081      0.0       0.00   \n",
       "GrLivArea      1460.0    1515.463699    525.480383    334.0    1129.50   \n",
       "BsmtFullBath   1460.0       0.425342      0.518911      0.0       0.00   \n",
       "BsmtHalfBath   1460.0       0.057534      0.238753      0.0       0.00   \n",
       "FullBath       1460.0       1.565068      0.550916      0.0       1.00   \n",
       "HalfBath       1460.0       0.382877      0.502885      0.0       0.00   \n",
       "BedroomAbvGr   1460.0       2.866438      0.815778      0.0       2.00   \n",
       "KitchenAbvGr   1460.0       1.046575      0.220338      0.0       1.00   \n",
       "TotRmsAbvGrd   1460.0       6.517808      1.625393      2.0       5.00   \n",
       "Fireplaces     1460.0       0.613014      0.644666      0.0       0.00   \n",
       "GarageYrBlt    1379.0    1978.506164     24.689725   1900.0    1961.00   \n",
       "GarageCars     1460.0       1.767123      0.747315      0.0       1.00   \n",
       "GarageArea     1460.0     472.980137    213.804841      0.0     334.50   \n",
       "WoodDeckSF     1460.0      94.244521    125.338794      0.0       0.00   \n",
       "OpenPorchSF    1460.0      46.660274     66.256028      0.0       0.00   \n",
       "EnclosedPorch  1460.0      21.954110     61.119149      0.0       0.00   \n",
       "3SsnPorch      1460.0       3.409589     29.317331      0.0       0.00   \n",
       "ScreenPorch    1460.0      15.060959     55.757415      0.0       0.00   \n",
       "PoolArea       1460.0       2.758904     40.177307      0.0       0.00   \n",
       "MiscVal        1460.0      43.489041    496.123024      0.0       0.00   \n",
       "MoSold         1460.0       6.321918      2.703626      1.0       5.00   \n",
       "YrSold         1460.0    2007.815753      1.328095   2006.0    2007.00   \n",
       "SalePrice      1460.0  180921.195890  79442.502883  34900.0  129975.00   \n",
       "\n",
       "                    50%        75%       max  \n",
       "Id                730.5    1095.25    1460.0  \n",
       "MSSubClass         50.0      70.00     190.0  \n",
       "LotFrontage        69.0      80.00     313.0  \n",
       "LotArea          9478.5   11601.50  215245.0  \n",
       "OverallQual         6.0       7.00      10.0  \n",
       "OverallCond         5.0       6.00       9.0  \n",
       "YearBuilt        1973.0    2000.00    2010.0  \n",
       "YearRemodAdd     1994.0    2004.00    2010.0  \n",
       "MasVnrArea          0.0     166.00    1600.0  \n",
       "BsmtFinSF1        383.5     712.25    5644.0  \n",
       "BsmtFinSF2          0.0       0.00    1474.0  \n",
       "BsmtUnfSF         477.5     808.00    2336.0  \n",
       "TotalBsmtSF       991.5    1298.25    6110.0  \n",
       "1stFlrSF         1087.0    1391.25    4692.0  \n",
       "2ndFlrSF            0.0     728.00    2065.0  \n",
       "LowQualFinSF        0.0       0.00     572.0  \n",
       "GrLivArea        1464.0    1776.75    5642.0  \n",
       "BsmtFullBath        0.0       1.00       3.0  \n",
       "BsmtHalfBath        0.0       0.00       2.0  \n",
       "FullBath            2.0       2.00       3.0  \n",
       "HalfBath            0.0       1.00       2.0  \n",
       "BedroomAbvGr        3.0       3.00       8.0  \n",
       "KitchenAbvGr        1.0       1.00       3.0  \n",
       "TotRmsAbvGrd        6.0       7.00      14.0  \n",
       "Fireplaces          1.0       1.00       3.0  \n",
       "GarageYrBlt      1980.0    2002.00    2010.0  \n",
       "GarageCars          2.0       2.00       4.0  \n",
       "GarageArea        480.0     576.00    1418.0  \n",
       "WoodDeckSF          0.0     168.00     857.0  \n",
       "OpenPorchSF        25.0      68.00     547.0  \n",
       "EnclosedPorch       0.0       0.00     552.0  \n",
       "3SsnPorch           0.0       0.00     508.0  \n",
       "ScreenPorch         0.0       0.00     480.0  \n",
       "PoolArea            0.0       0.00     738.0  \n",
       "MiscVal             0.0       0.00   15500.0  \n",
       "MoSold              6.0       8.00      12.0  \n",
       "YrSold           2008.0    2009.00    2010.0  \n",
       "SalePrice      163000.0  214000.00  755000.0  "
      ]
     },
     "execution_count": 43,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "train.describe().T # Description of the dataset"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "id": "58340528",
   "metadata": {
    "papermill": {
     "duration": 0.057925,
     "end_time": "2023-05-23T22:29:20.865864",
     "exception": false,
     "start_time": "2023-05-23T22:29:20.807939",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 1460 entries, 0 to 1459\n",
      "Data columns (total 81 columns):\n",
      " #   Column         Non-Null Count  Dtype  \n",
      "---  ------         --------------  -----  \n",
      " 0   Id             1460 non-null   int64  \n",
      " 1   MSSubClass     1460 non-null   int64  \n",
      " 2   MSZoning       1460 non-null   object \n",
      " 3   LotFrontage    1201 non-null   float64\n",
      " 4   LotArea        1460 non-null   int64  \n",
      " 5   Street         1460 non-null   object \n",
      " 6   Alley          91 non-null     object \n",
      " 7   LotShape       1460 non-null   object \n",
      " 8   LandContour    1460 non-null   object \n",
      " 9   Utilities      1460 non-null   object \n",
      " 10  LotConfig      1460 non-null   object \n",
      " 11  LandSlope      1460 non-null   object \n",
      " 12  Neighborhood   1460 non-null   object \n",
      " 13  Condition1     1460 non-null   object \n",
      " 14  Condition2     1460 non-null   object \n",
      " 15  BldgType       1460 non-null   object \n",
      " 16  HouseStyle     1460 non-null   object \n",
      " 17  OverallQual    1460 non-null   int64  \n",
      " 18  OverallCond    1460 non-null   int64  \n",
      " 19  YearBuilt      1460 non-null   int64  \n",
      " 20  YearRemodAdd   1460 non-null   int64  \n",
      " 21  RoofStyle      1460 non-null   object \n",
      " 22  RoofMatl       1460 non-null   object \n",
      " 23  Exterior1st    1460 non-null   object \n",
      " 24  Exterior2nd    1460 non-null   object \n",
      " 25  MasVnrType     1452 non-null   object \n",
      " 26  MasVnrArea     1452 non-null   float64\n",
      " 27  ExterQual      1460 non-null   object \n",
      " 28  ExterCond      1460 non-null   object \n",
      " 29  Foundation     1460 non-null   object \n",
      " 30  BsmtQual       1423 non-null   object \n",
      " 31  BsmtCond       1423 non-null   object \n",
      " 32  BsmtExposure   1422 non-null   object \n",
      " 33  BsmtFinType1   1423 non-null   object \n",
      " 34  BsmtFinSF1     1460 non-null   int64  \n",
      " 35  BsmtFinType2   1422 non-null   object \n",
      " 36  BsmtFinSF2     1460 non-null   int64  \n",
      " 37  BsmtUnfSF      1460 non-null   int64  \n",
      " 38  TotalBsmtSF    1460 non-null   int64  \n",
      " 39  Heating        1460 non-null   object \n",
      " 40  HeatingQC      1460 non-null   object \n",
      " 41  CentralAir     1460 non-null   object \n",
      " 42  Electrical     1459 non-null   object \n",
      " 43  1stFlrSF       1460 non-null   int64  \n",
      " 44  2ndFlrSF       1460 non-null   int64  \n",
      " 45  LowQualFinSF   1460 non-null   int64  \n",
      " 46  GrLivArea      1460 non-null   int64  \n",
      " 47  BsmtFullBath   1460 non-null   int64  \n",
      " 48  BsmtHalfBath   1460 non-null   int64  \n",
      " 49  FullBath       1460 non-null   int64  \n",
      " 50  HalfBath       1460 non-null   int64  \n",
      " 51  BedroomAbvGr   1460 non-null   int64  \n",
      " 52  KitchenAbvGr   1460 non-null   int64  \n",
      " 53  KitchenQual    1460 non-null   object \n",
      " 54  TotRmsAbvGrd   1460 non-null   int64  \n",
      " 55  Functional     1460 non-null   object \n",
      " 56  Fireplaces     1460 non-null   int64  \n",
      " 57  FireplaceQu    770 non-null    object \n",
      " 58  GarageType     1379 non-null   object \n",
      " 59  GarageYrBlt    1379 non-null   float64\n",
      " 60  GarageFinish   1379 non-null   object \n",
      " 61  GarageCars     1460 non-null   int64  \n",
      " 62  GarageArea     1460 non-null   int64  \n",
      " 63  GarageQual     1379 non-null   object \n",
      " 64  GarageCond     1379 non-null   object \n",
      " 65  PavedDrive     1460 non-null   object \n",
      " 66  WoodDeckSF     1460 non-null   int64  \n",
      " 67  OpenPorchSF    1460 non-null   int64  \n",
      " 68  EnclosedPorch  1460 non-null   int64  \n",
      " 69  3SsnPorch      1460 non-null   int64  \n",
      " 70  ScreenPorch    1460 non-null   int64  \n",
      " 71  PoolArea       1460 non-null   int64  \n",
      " 72  PoolQC         7 non-null      object \n",
      " 73  Fence          281 non-null    object \n",
      " 74  MiscFeature    54 non-null     object \n",
      " 75  MiscVal        1460 non-null   int64  \n",
      " 76  MoSold         1460 non-null   int64  \n",
      " 77  YrSold         1460 non-null   int64  \n",
      " 78  SaleType       1460 non-null   object \n",
      " 79  SaleCondition  1460 non-null   object \n",
      " 80  SalePrice      1460 non-null   int64  \n",
      "dtypes: float64(3), int64(35), object(43)\n",
      "memory usage: 924.0+ KB\n"
     ]
    }
   ],
   "source": [
    "train.info() # information about the training data."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "id": "a459faac",
   "metadata": {
    "papermill": {
     "duration": 0.038069,
     "end_time": "2023-05-23T22:29:20.923077",
     "exception": false,
     "start_time": "2023-05-23T22:29:20.885008",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "object     43\n",
       "int64      35\n",
       "float64     3\n",
       "dtype: int64"
      ]
     },
     "execution_count": 45,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "train.dtypes.value_counts() # data type count of the training dataset."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "id": "e6435027",
   "metadata": {
    "papermill": {
     "duration": 0.039163,
     "end_time": "2023-05-23T22:29:20.981325",
     "exception": false,
     "start_time": "2023-05-23T22:29:20.942162",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Qualitative Columns: \n",
      "['MSZoning', 'Street', 'Alley', 'LotShape', 'LandContour', 'Utilities', 'LotConfig', 'LandSlope', 'Neighborhood', 'Condition1', 'Condition2', 'BldgType', 'HouseStyle', 'RoofStyle', 'RoofMatl', 'Exterior1st', 'Exterior2nd', 'MasVnrType', 'ExterQual', 'ExterCond', 'Foundation', 'BsmtQual', 'BsmtCond', 'BsmtExposure', 'BsmtFinType1', 'BsmtFinType2', 'Heating', 'HeatingQC', 'CentralAir', 'Electrical', 'KitchenQual', 'Functional', 'FireplaceQu', 'GarageType', 'GarageFinish', 'GarageQual', 'GarageCond', 'PavedDrive', 'PoolQC', 'Fence', 'MiscFeature', 'SaleType', 'SaleCondition']\n",
      "Quantitative Columns: \n",
      "['Id', 'MSSubClass', 'LotFrontage', 'LotArea', 'OverallQual', 'OverallCond', 'YearBuilt', 'YearRemodAdd', 'MasVnrArea', 'BsmtFinSF1', 'BsmtFinSF2', 'BsmtUnfSF', 'TotalBsmtSF', '1stFlrSF', '2ndFlrSF', 'LowQualFinSF', 'GrLivArea', 'BsmtFullBath', 'BsmtHalfBath', 'FullBath', 'HalfBath', 'BedroomAbvGr', 'KitchenAbvGr', 'TotRmsAbvGrd', 'Fireplaces', 'GarageYrBlt', 'GarageCars', 'GarageArea', 'WoodDeckSF', 'OpenPorchSF', 'EnclosedPorch', '3SsnPorch', 'ScreenPorch', 'PoolArea', 'MiscVal', 'MoSold', 'YrSold', 'SalePrice']\n"
     ]
    }
   ],
   "source": [
    "# Sort the train data attributes to quantitative and qualitative categories.\n",
    "quantitative_cols = []\n",
    "qualitative_cols = []\n",
    "for col in train.columns:\n",
    "    if pd.api.types.is_numeric_dtype(train[col]):\n",
    "            quantitative_cols.append(col)\n",
    "    else:\n",
    "        qualitative_cols.append(col)\n",
    "\n",
    "print(\"Qualitative Columns: \") # Categorical\n",
    "print(qualitative_cols)\n",
    "\n",
    "print(\"Quantitative Columns: \") # Numarical\n",
    "print(quantitative_cols)"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "id": "df89b1aa",
   "metadata": {
    "papermill": {
     "duration": 0.020163,
     "end_time": "2023-05-23T22:29:21.021994",
     "exception": false,
     "start_time": "2023-05-23T22:29:21.001831",
     "status": "completed"
    },
    "tags": []
   },
   "source": [
    "### <span style='color:aqua; font-weight:bold;'>Correlation</span> "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "id": "b7844a31",
   "metadata": {
    "papermill": {
     "duration": 1.004626,
     "end_time": "2023-05-23T22:29:22.045596",
     "exception": false,
     "start_time": "2023-05-23T22:29:21.040970",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1500x600 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "corr = train.corr()\n",
    "plt.figure(figsize=(15,6)) #plot the heatmap for the correlation\n",
    "sns.heatmap(corr,fmt=\".5f\", linewidth=.5, cmap=\"BuPu\") \n",
    "plt.show() #the more darker color the more stronger correlation."
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "id": "d81e2a7f",
   "metadata": {
    "papermill": {
     "duration": 0.026062,
     "end_time": "2023-05-23T22:29:22.095958",
     "exception": false,
     "start_time": "2023-05-23T22:29:22.069896",
     "status": "completed"
    },
    "tags": []
   },
   "source": [
    "# <span style='color:dodgerblue; font-weight:bold;'>Data Cleaning</span> "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 48,
   "id": "02a3e63e",
   "metadata": {
    "papermill": {
     "duration": 0.034447,
     "end_time": "2023-05-23T22:29:22.166631",
     "exception": false,
     "start_time": "2023-05-23T22:29:22.132184",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [],
   "source": [
    "train.drop(['Id'], axis=1, inplace=True)"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "id": "1650a974-79d5-4214-92d3-72020ea76a18",
   "metadata": {},
   "source": [
    "### <span style='color:aqua; font-weight:bold;'>Data Consistency</span> \n",
    "\n",
    "We need to ensure that the data values make sense by following these guidelines:\n",
    "\n",
    "* Any features representing years should not exceed 2018.\n",
    "* Areas, distances, and prices should be non-negative values.\n",
    "* The values for months should fall within the range of 1 to 12."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 49,
   "id": "464b8e7f-ad97-41d0-b0dc-0284b18d5592",
   "metadata": {},
   "outputs": [],
   "source": [
    "years = ['YearBuilt', 'YearRemodAdd', 'GarageYrBlt', 'YrSold']\n",
    "metrics = ['LotFrontage', 'LotArea', 'MasVnrArea', 'BsmtFinSF1', 'BsmtFinSF2', 'BsmtUnfSF',\n",
    "           'TotalBsmtSF', '1stFlrSF', '2ndFlrSF', 'LowQualFinSF', 'GrLivArea', 'GarageArea',\n",
    "           'WoodDeckSF', 'OpenPorchSF', 'EnclosedPorch', '3SsnPorch', 'ScreenPorch', 'PoolArea', 'MiscVal']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 50,
   "id": "a35692c6-48b0-4292-9fc2-8376c5818235",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "\n",
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></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>...</th>\n",
       "      <th>PoolArea</th>\n",
       "      <th>PoolQC</th>\n",
       "      <th>Fence</th>\n",
       "      <th>MiscFeature</th>\n",
       "      <th>MiscVal</th>\n",
       "      <th>MoSold</th>\n",
       "      <th>YrSold</th>\n",
       "      <th>SaleType</th>\n",
       "      <th>SaleCondition</th>\n",
       "      <th>SalePrice</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>0 rows × 80 columns</p>\n",
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       "Empty DataFrame\n",
       "Columns: [MSSubClass, MSZoning, LotFrontage, LotArea, Street, Alley, LotShape, LandContour, Utilities, LotConfig, LandSlope, Neighborhood, Condition1, Condition2, BldgType, HouseStyle, OverallQual, OverallCond, YearBuilt, YearRemodAdd, RoofStyle, RoofMatl, Exterior1st, Exterior2nd, MasVnrType, MasVnrArea, ExterQual, ExterCond, Foundation, BsmtQual, BsmtCond, BsmtExposure, BsmtFinType1, BsmtFinSF1, BsmtFinType2, BsmtFinSF2, BsmtUnfSF, TotalBsmtSF, Heating, HeatingQC, CentralAir, Electrical, 1stFlrSF, 2ndFlrSF, LowQualFinSF, GrLivArea, BsmtFullBath, BsmtHalfBath, FullBath, HalfBath, BedroomAbvGr, KitchenAbvGr, KitchenQual, TotRmsAbvGrd, Functional, Fireplaces, FireplaceQu, GarageType, GarageYrBlt, GarageFinish, GarageCars, GarageArea, GarageQual, GarageCond, PavedDrive, WoodDeckSF, OpenPorchSF, EnclosedPorch, 3SsnPorch, ScreenPorch, PoolArea, PoolQC, Fence, MiscFeature, MiscVal, MoSold, YrSold, SaleType, SaleCondition, SalePrice]\n",
       "Index: []\n",
       "\n",
       "[0 rows x 80 columns]"
      ]
     },
     "execution_count": 50,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "mask = (train[years] > 2018).any(axis=1) # take any index with a twisted year value\n",
    "train[mask]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 51,
   "id": "c617026f-baba-42d1-86d5-5334d52fe1ea",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></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>...</th>\n",
       "      <th>PoolArea</th>\n",
       "      <th>PoolQC</th>\n",
       "      <th>Fence</th>\n",
       "      <th>MiscFeature</th>\n",
       "      <th>MiscVal</th>\n",
       "      <th>MoSold</th>\n",
       "      <th>YrSold</th>\n",
       "      <th>SaleType</th>\n",
       "      <th>SaleCondition</th>\n",
       "      <th>SalePrice</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "  </tbody>\n",
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       "<p>0 rows × 80 columns</p>\n",
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       "Empty DataFrame\n",
       "Columns: [MSSubClass, MSZoning, LotFrontage, LotArea, Street, Alley, LotShape, LandContour, Utilities, LotConfig, LandSlope, Neighborhood, Condition1, Condition2, BldgType, HouseStyle, OverallQual, OverallCond, YearBuilt, YearRemodAdd, RoofStyle, RoofMatl, Exterior1st, Exterior2nd, MasVnrType, MasVnrArea, ExterQual, ExterCond, Foundation, BsmtQual, BsmtCond, BsmtExposure, BsmtFinType1, BsmtFinSF1, BsmtFinType2, BsmtFinSF2, BsmtUnfSF, TotalBsmtSF, Heating, HeatingQC, CentralAir, Electrical, 1stFlrSF, 2ndFlrSF, LowQualFinSF, GrLivArea, BsmtFullBath, BsmtHalfBath, FullBath, HalfBath, BedroomAbvGr, KitchenAbvGr, KitchenQual, TotRmsAbvGrd, Functional, Fireplaces, FireplaceQu, GarageType, GarageYrBlt, GarageFinish, GarageCars, GarageArea, GarageQual, GarageCond, PavedDrive, WoodDeckSF, OpenPorchSF, EnclosedPorch, 3SsnPorch, ScreenPorch, PoolArea, PoolQC, Fence, MiscFeature, MiscVal, MoSold, YrSold, SaleType, SaleCondition, SalePrice]\n",
       "Index: []\n",
       "\n",
       "[0 rows x 80 columns]"
      ]
     },
     "execution_count": 51,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "mask = (train[metrics] < 0).any(axis=1)\n",
    "train[mask]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 52,
   "id": "324d8ff9-db7e-484b-8938-0ada9ab7ce7f",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
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       "\n",
       "    .dataframe tbody tr th {\n",
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       "    .dataframe thead th {\n",
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></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>...</th>\n",
       "      <th>PoolArea</th>\n",
       "      <th>PoolQC</th>\n",
       "      <th>Fence</th>\n",
       "      <th>MiscFeature</th>\n",
       "      <th>MiscVal</th>\n",
       "      <th>MoSold</th>\n",
       "      <th>YrSold</th>\n",
       "      <th>SaleType</th>\n",
       "      <th>SaleCondition</th>\n",
       "      <th>SalePrice</th>\n",
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       "  </tbody>\n",
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      "text/plain": [
       "Empty DataFrame\n",
       "Columns: [MSSubClass, MSZoning, LotFrontage, LotArea, Street, Alley, LotShape, LandContour, Utilities, LotConfig, LandSlope, Neighborhood, Condition1, Condition2, BldgType, HouseStyle, OverallQual, OverallCond, YearBuilt, YearRemodAdd, RoofStyle, RoofMatl, Exterior1st, Exterior2nd, MasVnrType, MasVnrArea, ExterQual, ExterCond, Foundation, BsmtQual, BsmtCond, BsmtExposure, BsmtFinType1, BsmtFinSF1, BsmtFinType2, BsmtFinSF2, BsmtUnfSF, TotalBsmtSF, Heating, HeatingQC, CentralAir, Electrical, 1stFlrSF, 2ndFlrSF, LowQualFinSF, GrLivArea, BsmtFullBath, BsmtHalfBath, FullBath, HalfBath, BedroomAbvGr, KitchenAbvGr, KitchenQual, TotRmsAbvGrd, Functional, Fireplaces, FireplaceQu, GarageType, GarageYrBlt, GarageFinish, GarageCars, GarageArea, GarageQual, GarageCond, PavedDrive, WoodDeckSF, OpenPorchSF, EnclosedPorch, 3SsnPorch, ScreenPorch, PoolArea, PoolQC, Fence, MiscFeature, MiscVal, MoSold, YrSold, SaleType, SaleCondition, SalePrice]\n",
       "Index: []\n",
       "\n",
       "[0 rows x 80 columns]"
      ]
     },
     "execution_count": 52,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "mask = ((train['MoSold'] > 12) | (train['MoSold'] < 1))\n",
    "train[mask]"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "id": "3dd2e838",
   "metadata": {
    "papermill": {
     "duration": 0.021476,
     "end_time": "2023-05-23T22:29:22.213104",
     "exception": false,
     "start_time": "2023-05-23T22:29:22.191628",
     "status": "completed"
    },
    "tags": []
   },
   "source": [
    "### <span style='color:aqua; font-weight:bold;'>Data Redundancy</span> "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 53,
   "id": "8624a97d",
   "metadata": {
    "papermill": {
     "duration": 0.080973,
     "end_time": "2023-05-23T22:29:22.320741",
     "exception": false,
     "start_time": "2023-05-23T22:29:22.239768",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Number of duplicated instances: 0\n",
      "Empty DataFrame\n",
      "Columns: [MSSubClass, MSZoning, LotFrontage, LotArea, Street, Alley, LotShape, LandContour, Utilities, LotConfig, LandSlope, Neighborhood, Condition1, Condition2, BldgType, HouseStyle, OverallQual, OverallCond, YearBuilt, YearRemodAdd, RoofStyle, RoofMatl, Exterior1st, Exterior2nd, MasVnrType, MasVnrArea, ExterQual, ExterCond, Foundation, BsmtQual, BsmtCond, BsmtExposure, BsmtFinType1, BsmtFinSF1, BsmtFinType2, BsmtFinSF2, BsmtUnfSF, TotalBsmtSF, Heating, HeatingQC, CentralAir, Electrical, 1stFlrSF, 2ndFlrSF, LowQualFinSF, GrLivArea, BsmtFullBath, BsmtHalfBath, FullBath, HalfBath, BedroomAbvGr, KitchenAbvGr, KitchenQual, TotRmsAbvGrd, Functional, Fireplaces, FireplaceQu, GarageType, GarageYrBlt, GarageFinish, GarageCars, GarageArea, GarageQual, GarageCond, PavedDrive, WoodDeckSF, OpenPorchSF, EnclosedPorch, 3SsnPorch, ScreenPorch, PoolArea, PoolQC, Fence, MiscFeature, MiscVal, MoSold, YrSold, SaleType, SaleCondition, SalePrice]\n",
      "Index: []\n",
      "\n",
      "[0 rows x 80 columns]\n"
     ]
    }
   ],
   "source": [
    "# Check for duplicates across all columns\n",
    "duplicated = train.duplicated()\n",
    "\n",
    "# Print the number of duplicated instances\n",
    "print(\"Number of duplicated instances:\", duplicated.sum())\n",
    "\n",
    "# Print the duplicated instances\n",
    "print(train[duplicated])"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "id": "564c1ad7",
   "metadata": {
    "papermill": {
     "duration": 0.028512,
     "end_time": "2023-05-23T22:29:22.371213",
     "exception": false,
     "start_time": "2023-05-23T22:29:22.342701",
     "status": "completed"
    },
    "tags": []
   },
   "source": [
    "### <span style='color:aqua; font-weight:bold;'>Missing Values</span> "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 54,
   "id": "02ff3554",
   "metadata": {
    "papermill": {
     "duration": 0.118886,
     "end_time": "2023-05-23T22:29:22.514330",
     "exception": false,
     "start_time": "2023-05-23T22:29:22.395444",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "              Total Percent\n",
      "PoolQC         1453  99.52%\n",
      "MiscFeature    1406  96.30%\n",
      "Alley          1369  93.77%\n",
      "Fence          1179  80.75%\n",
      "FireplaceQu     690  47.26%\n",
      "LotFrontage     259  17.74%\n",
      "GarageYrBlt      81   5.55%\n",
      "GarageCond       81   5.55%\n",
      "GarageType       81   5.55%\n",
      "GarageFinish     81   5.55%\n",
      "GarageQual       81   5.55%\n",
      "BsmtExposure     38   2.60%\n",
      "BsmtFinType2     38   2.60%\n",
      "BsmtCond         37   2.53%\n",
      "BsmtQual         37   2.53%\n",
      "BsmtFinType1     37   2.53%\n",
      "MasVnrArea        8   0.55%\n",
      "MasVnrType        8   0.55%\n",
      "Electrical        1   0.07%\n"
     ]
    }
   ],
   "source": [
    "# print the percentage of missing values for instances.\n",
    "total = train.isnull().sum().sort_values(ascending=False)[train.isnull().sum().sort_values(ascending=False) != 0]\n",
    "percent = ((train.isnull().sum() / train.isnull().count()).sort_values(ascending=False)[(train.isnull().sum() / train.isnull().count()).sort_values(ascending=False) != 0]) * 100\n",
    "missing = pd.concat([total, percent], axis=1, keys=['Total', 'Percent'])\n",
    "missing['Percent'] = missing['Percent'].apply(lambda x: \"%.2f%%\" % x)\n",
    "print(missing)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 55,
   "id": "5e4037e6",
   "metadata": {
    "papermill": {
     "duration": 0.652304,
     "end_time": "2023-05-23T22:29:23.191322",
     "exception": false,
     "start_time": "2023-05-23T22:29:22.539018",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Plot the most null columns.\n",
    "missing = train.isnull().sum()\n",
    "missing = missing[missing > 0]\n",
    "style.use('seaborn-darkgrid')\n",
    "missing.sort_values(inplace=True)\n",
    "missing.plot.bar();"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "id": "8ad1f589",
   "metadata": {
    "papermill": {
     "duration": 0.021647,
     "end_time": "2023-05-23T22:29:23.235117",
     "exception": false,
     "start_time": "2023-05-23T22:29:23.213470",
     "status": "completed"
    },
    "tags": []
   },
   "source": [
    "Missing values exist in 19 attributes, most of the time, NA denotes a lack of a subject described by an attribute, such as a missing pool, fence, garage, or basement."
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "id": "e555a5ff",
   "metadata": {
    "papermill": {
     "duration": 0.022168,
     "end_time": "2023-05-23T22:29:23.279750",
     "exception": false,
     "start_time": "2023-05-23T22:29:23.257582",
     "status": "completed"
    },
    "tags": []
   },
   "source": [
    "Handling missing values for features that NA has a meaning."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 56,
   "id": "58e62242",
   "metadata": {
    "papermill": {
     "duration": 0.046519,
     "end_time": "2023-05-23T22:29:23.349215",
     "exception": false,
     "start_time": "2023-05-23T22:29:23.302696",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [],
   "source": [
    "columns_to_fill = ['PoolQC', 'MiscFeature', 'Alley', 'Fence', 'FireplaceQu',\n",
    "                   'GarageCond', 'GarageType', 'GarageFinish', 'GarageQual',\n",
    "                   'BsmtExposure', 'BsmtFinType2', 'BsmtFinType1', 'BsmtCond',\n",
    "                   'BsmtQual']\n",
    "\n",
    "default_values = ['No Pool', 'None', 'No alley access', 'No Fence', 'No Fireplace',\n",
    "                  'No Garage', 'No Garage', 'No Garage', 'No Garage', 'No Basement',\n",
    "                  'No Basement', 'No Basement', 'No Basement', 'No Basement']\n",
    "\n",
    "for column, default_value in zip(columns_to_fill, default_values):\n",
    "    train[column] = train[column].fillna(default_value)"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "id": "c02765a1",
   "metadata": {
    "papermill": {
     "duration": 0.021475,
     "end_time": "2023-05-23T22:29:23.392701",
     "exception": false,
     "start_time": "2023-05-23T22:29:23.371226",
     "status": "completed"
    },
    "tags": []
   },
   "source": [
    "Handling missing values for features that NA doesn't have a meaning."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 57,
   "id": "20ef2f27",
   "metadata": {
    "papermill": {
     "duration": 0.040732,
     "end_time": "2023-05-23T22:29:23.455372",
     "exception": false,
     "start_time": "2023-05-23T22:29:23.414640",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [],
   "source": [
    "# Handling categorical missing values using SimpleImputer\n",
    "imputer = SimpleImputer(missing_values=np.nan, strategy='most_frequent')\n",
    "imputer.fit(train[['MasVnrType', 'Electrical']])\n",
    "train[['MasVnrType', 'Electrical']]=imputer.transform(train[['MasVnrType', 'Electrical']])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 58,
   "id": "4b474dbc",
   "metadata": {
    "papermill": {
     "duration": 0.041964,
     "end_time": "2023-05-23T22:29:23.520122",
     "exception": false,
     "start_time": "2023-05-23T22:29:23.478158",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [],
   "source": [
    "# Handling numarical missing values using SimpleImputer\n",
    "imputer = SimpleImputer(missing_values=np.nan, strategy='mean')\n",
    "imputer.fit(train[['LotFrontage', 'MasVnrArea', 'GarageYrBlt']])\n",
    "train[['LotFrontage', 'MasVnrArea', 'GarageYrBlt']]=imputer.transform(train[['LotFrontage', 'MasVnrArea', 'GarageYrBlt']])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 59,
   "id": "d5953eb0",
   "metadata": {
    "papermill": {
     "duration": 0.049339,
     "end_time": "2023-05-23T22:29:23.591398",
     "exception": false,
     "start_time": "2023-05-23T22:29:23.542059",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0"
      ]
     },
     "execution_count": 59,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "train.isnull().sum().sum() # Checking if there is any missing values"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "id": "f9f0fc90",
   "metadata": {
    "papermill": {
     "duration": 0.021884,
     "end_time": "2023-05-23T22:29:23.635823",
     "exception": false,
     "start_time": "2023-05-23T22:29:23.613939",
     "status": "completed"
    },
    "tags": []
   },
   "source": [
    "### <span style='color:aqua; font-weight:bold;'>One-hot Encoder</span> "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 60,
   "id": "87e7b398",
   "metadata": {
    "papermill": {
     "duration": 0.116239,
     "end_time": "2023-05-23T22:29:23.775422",
     "exception": false,
     "start_time": "2023-05-23T22:29:23.659183",
     "status": "completed"
    },
    "tags": []
   },
   "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>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>...</th>\n",
       "      <th>SaleType_ConLI</th>\n",
       "      <th>SaleType_ConLw</th>\n",
       "      <th>SaleType_New</th>\n",
       "      <th>SaleType_Oth</th>\n",
       "      <th>SaleType_WD</th>\n",
       "      <th>SaleCondition_AdjLand</th>\n",
       "      <th>SaleCondition_Alloca</th>\n",
       "      <th>SaleCondition_Family</th>\n",
       "      <th>SaleCondition_Normal</th>\n",
       "      <th>SaleCondition_Partial</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>60</td>\n",
       "      <td>65.0</td>\n",
       "      <td>8450</td>\n",
       "      <td>7</td>\n",
       "      <td>5</td>\n",
       "      <td>2003</td>\n",
       "      <td>2003</td>\n",
       "      <td>196.0</td>\n",
       "      <td>706</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>20</td>\n",
       "      <td>80.0</td>\n",
       "      <td>9600</td>\n",
       "      <td>6</td>\n",
       "      <td>8</td>\n",
       "      <td>1976</td>\n",
       "      <td>1976</td>\n",
       "      <td>0.0</td>\n",
       "      <td>978</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>60</td>\n",
       "      <td>68.0</td>\n",
       "      <td>11250</td>\n",
       "      <td>7</td>\n",
       "      <td>5</td>\n",
       "      <td>2001</td>\n",
       "      <td>2002</td>\n",
       "      <td>162.0</td>\n",
       "      <td>486</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>70</td>\n",
       "      <td>60.0</td>\n",
       "      <td>9550</td>\n",
       "      <td>7</td>\n",
       "      <td>5</td>\n",
       "      <td>1915</td>\n",
       "      <td>1970</td>\n",
       "      <td>0.0</td>\n",
       "      <td>216</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>60</td>\n",
       "      <td>84.0</td>\n",
       "      <td>14260</td>\n",
       "      <td>8</td>\n",
       "      <td>5</td>\n",
       "      <td>2000</td>\n",
       "      <td>2000</td>\n",
       "      <td>350.0</td>\n",
       "      <td>655</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 260 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "   MSSubClass  LotFrontage  LotArea  OverallQual  OverallCond  YearBuilt  \\\n",
       "0          60         65.0     8450            7            5       2003   \n",
       "1          20         80.0     9600            6            8       1976   \n",
       "2          60         68.0    11250            7            5       2001   \n",
       "3          70         60.0     9550            7            5       1915   \n",
       "4          60         84.0    14260            8            5       2000   \n",
       "\n",
       "   YearRemodAdd  MasVnrArea  BsmtFinSF1  BsmtFinSF2  ...  SaleType_ConLI  \\\n",
       "0          2003       196.0         706           0  ...               0   \n",
       "1          1976         0.0         978           0  ...               0   \n",
       "2          2002       162.0         486           0  ...               0   \n",
       "3          1970         0.0         216           0  ...               0   \n",
       "4          2000       350.0         655           0  ...               0   \n",
       "\n",
       "   SaleType_ConLw  SaleType_New  SaleType_Oth  SaleType_WD  \\\n",
       "0               0             0             0            1   \n",
       "1               0             0             0            1   \n",
       "2               0             0             0            1   \n",
       "3               0             0             0            1   \n",
       "4               0             0             0            1   \n",
       "\n",
       "   SaleCondition_AdjLand  SaleCondition_Alloca  SaleCondition_Family  \\\n",
       "0                      0                     0                     0   \n",
       "1                      0                     0                     0   \n",
       "2                      0                     0                     0   \n",
       "3                      0                     0                     0   \n",
       "4                      0                     0                     0   \n",
       "\n",
       "   SaleCondition_Normal  SaleCondition_Partial  \n",
       "0                     1                      0  \n",
       "1                     1                      0  \n",
       "2                     1                      0  \n",
       "3                     0                      0  \n",
       "4                     1                      0  \n",
       "\n",
       "[5 rows x 260 columns]"
      ]
     },
     "execution_count": 60,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Select the columns to encode\n",
    "cols = ['MSZoning', 'Street', 'Alley', 'LotShape', 'LandContour', 'Utilities',\n",
    "        'LotConfig', 'LandSlope', 'Neighborhood', 'Condition1', 'Condition2',\n",
    "        'BldgType', 'HouseStyle', 'RoofStyle', 'RoofMatl', 'Exterior1st',\n",
    "        'Exterior2nd', 'MasVnrType', 'ExterQual', 'ExterCond', 'Foundation',\n",
    "        'BsmtQual', 'BsmtCond', 'BsmtExposure', 'BsmtFinType1', 'BsmtFinType2',\n",
    "        'Heating', 'HeatingQC', 'CentralAir', 'Electrical', 'KitchenQual', 'Functional',\n",
    "        'FireplaceQu', 'GarageType', 'GarageFinish', 'GarageQual', 'GarageCond', 'PavedDrive',\n",
    "        'PoolQC', 'Fence', 'MiscFeature', 'SaleType', 'SaleCondition']\n",
    "\n",
    "# Encode the selected columns\n",
    "dummies = pd.get_dummies(train[cols], drop_first=True)\n",
    "\n",
    "# Concatenate the encoded columns with the original dataset\n",
    "train = pd.concat([train, dummies], axis=1)\n",
    "\n",
    "# Drop the original columns that have been encoded\n",
    "train.drop(cols, axis=1, inplace=True)\n",
    "\n",
    "# Output the modified dataset\n",
    "train.head()"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "id": "298ca5e8",
   "metadata": {
    "papermill": {
     "duration": 0.022867,
     "end_time": "2023-05-23T22:29:23.821152",
     "exception": false,
     "start_time": "2023-05-23T22:29:23.798285",
     "status": "completed"
    },
    "tags": []
   },
   "source": [
    "# <span style='color:dodgerblue; font-weight:bold;'>Plot relationship between variables </span> "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 61,
   "id": "05be61d2",
   "metadata": {
    "papermill": {
     "duration": 0.033324,
     "end_time": "2023-05-23T22:29:23.876848",
     "exception": false,
     "start_time": "2023-05-23T22:29:23.843524",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [],
   "source": [
    "def customized_scatterplot(y, x): # customized scatterplot design.\n",
    "    style.use('seaborn-darkgrid')\n",
    "    plt.subplots(figsize = (12, 8))\n",
    "    sns.scatterplot(y = y, x = x)"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "id": "c7bdd3ee",
   "metadata": {
    "papermill": {
     "duration": 0.022625,
     "end_time": "2023-05-23T22:29:23.921846",
     "exception": false,
     "start_time": "2023-05-23T22:29:23.899221",
     "status": "completed"
    },
    "tags": []
   },
   "source": [
    "The response variable: SalePrice\n",
    "\n",
    "As you can see, the sale prices are right skewed. This was expected as few people can afford very expensive houses."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 62,
   "id": "ea4704b3",
   "metadata": {
    "papermill": {
     "duration": 0.418802,
     "end_time": "2023-05-23T22:29:24.363090",
     "exception": false,
     "start_time": "2023-05-23T22:29:23.944288",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.distplot(train['SalePrice']);"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "id": "50dad950",
   "metadata": {
    "papermill": {
     "duration": 0.022608,
     "end_time": "2023-05-23T22:29:24.409181",
     "exception": false,
     "start_time": "2023-05-23T22:29:24.386573",
     "status": "completed"
    },
    "tags": []
   },
   "source": [
    "SalePrice vs OverallQual"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 63,
   "id": "7fb26daa",
   "metadata": {
    "papermill": {
     "duration": 0.681826,
     "end_time": "2023-05-23T22:29:25.114185",
     "exception": false,
     "start_time": "2023-05-23T22:29:24.432359",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:xlabel='OverallQual', ylabel='SalePrice'>"
      ]
     },
     "execution_count": 63,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Sale Price vs Rates the overall material and finish of the house\n",
    "sns.barplot(x=train.OverallQual, y=train.SalePrice)"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "id": "ba7b4d95",
   "metadata": {
    "papermill": {
     "duration": 0.024207,
     "end_time": "2023-05-23T22:29:25.163886",
     "exception": false,
     "start_time": "2023-05-23T22:29:25.139679",
     "status": "completed"
    },
    "tags": []
   },
   "source": [
    "SalePrice vs OverallCond"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 64,
   "id": "3435465f",
   "metadata": {
    "papermill": {
     "duration": 0.591654,
     "end_time": "2023-05-23T22:29:25.779817",
     "exception": false,
     "start_time": "2023-05-23T22:29:25.188163",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:xlabel='OverallCond', ylabel='SalePrice'>"
      ]
     },
     "execution_count": 64,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Sale Price vs Rates the overall condition of the house.\n",
    "sns.barplot(x=train.OverallCond, y=train.SalePrice)"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "id": "d0273972",
   "metadata": {
    "papermill": {
     "duration": 0.024317,
     "end_time": "2023-05-23T22:29:25.830703",
     "exception": false,
     "start_time": "2023-05-23T22:29:25.806386",
     "status": "completed"
    },
    "tags": []
   },
   "source": [
    "SalePrice vs GrLivArea"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 65,
   "id": "4049c320",
   "metadata": {
    "papermill": {
     "duration": 0.371125,
     "end_time": "2023-05-23T22:29:26.226576",
     "exception": false,
     "start_time": "2023-05-23T22:29:25.855451",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "image/png": 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dAAAAAACTIVgHAAAAAMBkCNYBAAAAADAZgnUAAAAAAEyGYB0AAAAAAJMhWAcAAAAAwGQI1gEAAAAAMJkRDdY9Ho9+8IMf6NZbbw387MMPP9RFF12kmpoazZo1Sy+88ELIc1auXKlzzjlHJ554oi644AJt3Lgx5PUefPBBnXHGGaqpqdFVV12lPXv2DNvnAQAAAAAgHUY0WH/sscf03nvvBf67vb1dV155pRoaGrRhwwYtW7ZM999/vz766CNJ0jvvvKOlS5fqgQce0IYNGzR37lxdddVV6unpkSQ98cQTWr9+vV566SWtXbtWeXl5WrJkyYh8NgAAAAAABmrEgvW33npLr732ms4999zAz1577TUVFxdrwYIFstlsmjlzps477zw9++yzkqQXXnhBs2fP1sknnyy73a6FCxeqpKREr776auDxK664QhMmTNCYMWO0ePFi/eUvf9HOnTtH5DMCAAAAADAQtpF405aWFi1evFiPP/64nn766cDPt23bpmOPPTbkdx0Oh1588UVJUmNjoy688MKIxz/55BN1dnbq66+/Dnl+eXm5xo0bp7/+9a+aOHFi1GMxjND/j8zHmGYnxjX7MKbZhzHNToxr9mFMsxPjmn2GPVj3er266aabdNlll2ny5Mkhj3V1dSk/Pz/kZ3l5eeru7k74eFdXlySpoKAg4nH/Y+FKSwtltfYXF5SVFQ38Q8GUGNPsxLhmH8Y0+zCm2YlxzT6MaXZiXLPHsAfrv/jFL5STk6Mf/OAHEY/l5+ers7Mz5Ge9vb0qLCwMPN7b2xvxeElJSSCI969fj/b8cPv2dcli6b+gW1o65fMN+GPBRAyDMc1GjGv2YUyzD2OanRjX7MOYZifGNXOUlyc3oTLswfrLL7+sPXv26JRTTpGkQPD9+uuv6+abb9b69etDfr+xsVFVVVWSpKqqKm3bti3i8TPPPFPjxo3ToYceqsbGxkAp/N69e9XW1hZRWh/MfyH7fOKizjKMaXZiXLMPY5p9GNPsxLhmH8Y0OzGu2WPYG8z9/ve/1wcffKD33ntP7733nubMmaM5c+bovffe0znnnKPm5mY9/fTTcrlcevvtt7V69erAOvXvf//7Wr16td5++225XC49/fTTamlp0TnnnCNJuuCCC/TEE09o586d2r9/v5YvX67TTjtNFRUVw/0xAQAAAAAYsBFpMBdLSUmJVqxYoWXLlumRRx5RaWmplixZotNPP12SNHPmTN111126++67tXv3bjkcDv3yl79UcXGxJOmaa66R2+3WggUL1NXVpRkzZujhhx8euQ8EAAAAAMAAGD7f6C2S2Lu3U4bRv2aguZm1HdmCMc1OjGv2YUyzD2OanRjX7MOYZifGNXOMH5/cmvUR22cdAAAAAABER7AOAAAAAIDJEKwDAAAAAGAyBOsAAAAAAJgMwToAAAAAACZDsA4AAAAAgMkQrAMAAAAAYDIE6wAAAAAAmAzBOgAAAAAAJkOwDgAAAACAyRCsAwAAAABgMgTrAAAAAACYDME6AAAAAAAmQ7AOAAAAAIDJEKwDAAAAAGAyBOsAAAAAAJgMwToAAAAAACZDsA4AAAAAgMkQrAMAAAAAYDIE6wAAAAAAmAzBOgAAAAAAJkOwDgAAAACAyRCsAwAAAABgMgTrAAAAAACYDME6AAAAAAAmQ7AOAAAAAIDJEKwDAAAAAGAyBOsAAAAAAJgMwToAAAAAACZDsA4AAABgSLkthlo9PjV1udTq8cltMUb6kADTs430AQAAAADIXj2GocUrN2ttY0vgZ/VV5Vo2r1r5Pt8IHhlgbmTWAQAATI6sJDKV22Jo8arQQF2S1m5r1uKXt3AtA3GQWQcAADAxspLIZJ0ub0Sg7rd2W7M6XV6VWAnYgWjIrAMAAJgUWUlkus5e96AeB0YzgnUAAACTSiYrCZhZUV78Qt5EjwOjGcE6AACASZGVRKYrsltUX1Ue9bH6qnIV2QlHgFj46wAAADApspLIdDavT8vmVUcE7PVV5Vo+b5psXvouALHwDQ8AAGBS/qzk2m3NEY8FspIEOzC5fJ9PDzVUq9PlVWevW0V5NhXZLbJ5WcYBxENmHQAAwKTISiJb2Lw+lVgNVRTaVWI1uHaBJJBZBwAAMDGykgAwOhGsAwAAmJw/K1lSaO//AVlJAMh6lMEDAAAAAGAyBOsAAAAAAJgMwToAYMi4LYZaPT41dbnU6vHJbTFG+pAAAAAyAmvWAQBDoscwtHjlZq1tbAn8rL6qXMvmVSvfx3pbAACAeMisAwDSzm0xtHhVaKAuSWu3NWvxy1vIsAMAACRAsA4ASLtOlzciUPdbu61ZnS62nAIAAIiHYB0AkHadve5BPQ4AADDaEawDANKuKC9+S5REj2Po0PQPAIDMwN0SACDtiuwW1VeVa+225ojH6qvKVWS3SDSZG3Y0/QMAIHOQWQcApJ3N69OyedWqryoP+Xl9VbmWz5smm5fAcLjR9A8AgMxCZh0AMCTyfT491FCtTpdXnb1uFeXZVGS3yOaludxISKbpX4mVgB0AALMgWAcADBmb16cSq6GSQnv/D8ioj5hkmv4FxgkAAIw4yuABABgFaPoHAEBmIVgHYHpui6F9bp82NrVqn5vu1cBA+Jv+RRNo+gcAAEyDaXQApkb3aiA9/E3/Fr+8JaRL/8Gmf/QSAADATAjWAZiW2xIZqEsHu1c/1FBNV3EgBTT9AwAgcxCsAzAtulcD6UfTPwAAMgML1ACYVjLdqwEAAIBsRLAOwLToXg0AAIDRimAdgGnRvRoAAACjFXe6AEzL3706PGA/2L2atbYAAADITtSQAjC14O7V3U6PCnKsdK8GAABA1iOzDsD0bF6fSm2GTqwoUanNIKMOAACArEewDgAAAACAyRCsAwAAAABgMgTrAAAAyApui6FWj09NXS61enxyW4yRPiQAGDAazAEAACDj9RiGFq/crLWNLYGf1VeVa9m8auX76HUCIPOQWQcAAEBGc1sMLV4VGqhL0tptzVr88hYy7AAyEsE6AAAAMlqnyxsRqPut3dasThfbfQLIPATrAABg2LG2GOnU2ese1OMAYEasWQcAAMNqONYWuy2GOl1edfa6VZRnU5HdIpuXdcvZqigv/i1toscBwIxS/uZyOp1avXq1du/eLa+3v6TI5XLp008/1RNPPJH2AwQAIBUEaebmtkQG6tLBtcUPNVQPerxoNDb6FNktqq8q19ptzRGP1VeVq8hukfgeAJBhUg7Wb7/9dq1du1YlJSVyuVwqKCjQtm3b1NDQMASHBwBA8gjSzC+ZtcUl1oGXxA/HZADMx+b1adm8ai1+eUtIwF5fVa7l86bJ5mXNOoDMk3KwvnbtWj333HPat2+fnnvuOf3jP/6jVqxYoY8++mgojg8AgKQQpGWGZNYWlxTaB/76QzwZAPPK9/n0UEN1lMoaAnUAmSnlBnNer1eTJk3SpEmT9PHHH0uSFixYoPfeey/tBwcAQLIyvRv0aGm4NtRri2k0NrrZvD6VWA1VFNpVYjWYoAOQ0VL+F/Gwww7Tzp07NXHiRLW0tKi7u1sWi0VdXV1DcXwAACRlqDO2Q2k0le8P9dpiGo0BALJFypn18847T5dccol2796ts846S1dddZWuv/56TZs2bSiODwCApGRqkOa2GFq8Knb5frZl2P1ri+urykN+fnBt8eAmJ/yTAdEEJgMAAMgAKd+5XHnllZo4caKKiop0xx136Kc//an279+vO+64YyiODwCApGRqN+jRuMZ6KNcW02gMAJAtBpRm+O53vytJ2rdvn+655560HhAAAAORqUFaJpfvD4Z/bXHgs6VxIoVGYwCAbJBysO5yufTYY4/p17/+tTwej1avXq0bbrhBTzzxhA455JChOEYAAJKSiUFappbvm91QTgYAADAcUl649dhjj+ntt9/Wv/zLv8hut6usrEyHHXaYli1bNhTHBwBASjKtGzRrrDEURsvuAgCQzVKerl+9erWee+45HXrooTIMQwUFBbr//vt1zjnnDMXxAQCQ1TK1fB/mNZp2FwCAbJZysN7d3a3S0lJJku/AF35eXp4sFmb+AQAYiEws34c5uS2Rgbp0cHeBhxqqTV9tAgDol3KEfeKJJ+qxxx6TJBlGf0nVv//7v2v69OnpPTIAyCCUnGKwMq18H+aUzO4CAIDMkHJm/fbbb9fChQu1cuVKdXV16Xvf+566urr01FNPDcXxAYDpUXIKwCxG6+4CAJCNUg7Wy8vL9corr+i///u/9eWXX+qwww7TWWedpTFjxgzF8QGA3BZDnS6vdja1qjDHeqA82BxBMCWnAMyE3QUAIHuk/I09Z84c/fa3vw3stQ4A6eYPzrv63CouzNGdJs5aJ1NyWmKlJB7A8PDvLhDcrNAvsLsAE4gAkBEG1BWup6cn3ccBAJL6S8pvXrlZ5z68Vn/6614tWRU7a22GdeHJlJwCwHDx7y4Qvh3gwd0FCNQBIFOknFmfMWOGLrroIp155pk65JBDQh679tpr03ZgAEaf8JLymonFeuyNxqi/a5asNSWnAMyG3QUAIDukfBf5xRdfaOLEidqxY4d27NgR+Lm/MzwADFR4SXmfO/6NpRkaJVFyCsCM/LsLBL4j+R4CgIyTcrD+7//+71F//umnnw76YACMbuEl47m2+Ct1zJC19pecLn55S0jAfrDklEwWAAAAUjfoO90333xTTz75pN588019/PHH6TgmAKNUePC9cWebah1lWh+lgZuZstaUnAIAACDdBtRgzu12a9WqVZo3b56uuOIK5eTk6Oc//3m6jw3AKOMvKfdbsW6HLqutVK2jLOT3zNgoyV9yWlFoV4nVMNWxAQAAIPOklFnv7OzU888/r1//+tcyDEP79u3TSy+9pMmTJw/V8QEYRcJLyrudHl3/3EbdMWeq7pwzVT1OjwoC+6yTtQYAAED2Sjqzvnz5cp111ll64403dMstt+j1119XQUGBSkpKUn7Tt956SxdddJFOOukk1dbWaunSpert7ZUkffjhh7roootUU1OjWbNm6YUXXgh57sqVK3XOOefoxBNP1AUXXKCNGzcGHvN4PHrwwQd1xhlnqKamRldddZX27NmT8vEBGDn+kvLXbqjXSz+eqVVXn6GzjilVmc3QiRUlKrWRtQYAAED2SzpY/7d/+zfNmzdPP/vZz/S9731PNtvAlrvv27dPP/rRjzR//ny99957Wrlypd59913967/+q9rb23XllVeqoaFBGzZs0LJly3T//ffro48+kiS98847Wrp0qR544AFt2LBBc+fO1VVXXRXY9/2JJ57Q+vXr9dJLL2nt2rXKy8vTkiVLBnScAEYOJeUAAAAY7ZIO1n/+859r586dOuuss3TjjTfqo48+GtB2baWlpXrzzTd1wQUXyDAMtbW1qa+vT6WlpXrttddUXFysBQsWyGazaebMmTrvvPP07LPPSpJeeOEFzZ49WyeffLLsdrsWLlyokpISvfrqq4HHr7jiCk2YMEFjxozR4sWL9Ze//EU7d+5M+TgBAAAAABgpSafHzzrrLJ111ln6/PPP9eyzz+ryyy/X/v37tWrVKl100UUqLS1N+k3HjBkjSfrGN76h3bt365RTTtEFF1yghx9+WMcee2zI7zocDr344ouSpMbGRl144YURj3/yySfq7OzU119/HfL88vJyjRs3Tn/96181ceLEqMfin29gm/jswZhmp0wfV5dhRHSLt/tGd8VApo8pIjGm2YlxzT6MaXZiXLNPyrXsRx11lG6//Xb95Cc/0cqVK/Xcc8/pscce01lnnaVHH300pdd67bXX1N7erhtvvFHXX3+9Dj30UOXn54f8Tl5enrq7uyVJXV1dMR/v6uqSJBUUFEQ87n8sXGlpoazW/uKCsrKilI4d5seYZqdMHNddbT265aWPQvZhP7OqXA9ceLwOL86P88zRIRPHFPExptmJcc0+jGl2Ylyzx4D3Wc/Pz9cll1yiSy65RG+99ZZ+85vfpPwaeXl5ysvL00033aSLLrpIP/jBD9TZ2RnyO729vSosLAy8p78RXfDjJSUlgSDev3492vPD7dvXJYul/4JuaenUKE9yZQ3DYEyzUaaOq8swdMvKzVobtlf8X7Y165aXPtJDDdWjNsOeqWOK2BjT7MS4Zh/GNDsxrpmjvDy5CZWUg/Uf//jH+v73v6+zzz5bVqtVkjRz5kzNnDkzqed/8MEHuv322/Xb3/5WOTk5kiSn0ym73S6Hw6H169eH/H5jY6OqqqokSVVVVdq2bVvE42eeeabGjRunQw89VI2NjYFS+L1796qtrS2itD6Y/0L2+cRFnWUY0+yUaePa6fZGBOp+a7c1q9PlVYl1dNerZdqYIrFMGlO3JXKJCk0to8ukcUVyGNPsxLhmj6QbzPkdc8wxuvfee/WNb3xDP/3pT7Vjx46Unn/cccept7dX//iP/yin06kvv/xSDz74oL7//e/r29/+tpqbm/X000/L5XLp7bff1urVqwPr1L///e9r9erVevvtt+VyufT000+rpaVF55xzjiTpggsu0BNPPKGdO3dq//79Wr58uU477TRVVFSk+jEBIC06e92DehzA0OkxDN28crPOfXitLvz5Wzr34bW6edUW9bDgEwBgAobPl/q8i9fr1dq1a7Vq1Sq98cYbmjZtmi666CI1NDQk9fzGxkYtX75cmzZtUlFRkc477zxdc801ysnJ0aZNm7Rs2TJ9+umnKi0t1dVXX60LLrgg8NyXX35ZTzzxhHbv3i2Hw6ElS5bohBNOkCS5XC79y7/8i37729+qq6tLM2bM0NKlS1VWVhb1OPbu7ZRh9JchNDdTLpItGNPslKnj2urx6dyH18Z8/LUb6kdtZj1TxxSxZdKYui39gXq0ypf6qnI91FBNhv2ATBpXJIcxzU6Ma+YYPz65MvgBBevB/ud//kf33HOPvvrqK3388ceDealhR7CenRjT7JSp4+q2GLp51ZaQ5nJ+oz0gyNQxRWyZNKZMpCUvk8YVyWFMsxPjmjmSDdYH1GCuqalJq1at0m9/+1v19PRo3rx5uuiiiwbyUgCQ1Wxen5bNq9bil0MD9vqqci2fN002r3cEjw4YvZJZolJSaB+mowEAIFLKwfrFF1+sTZs26fTTT9dNN92kb37zm7LZBtxUHgCyXr7Pp4caqqM0scrsQJ3GXMhkRXnx710SPQ4AwFBL+V+iM844Q//0T/+kww8/fCiOBwCyks3rU4nVOJipy/CgtscwtDhsvW99VbmWzatWPrV3yABFdovqq8pjLlEpslsy/u8UAJDZku4G//XXX0vq78guSbt27Yr4PwBA9nNbDC1eFdmYa+22Zi1+eYvcFtb5wvz8S1Tqq8pDfn5wiQqBOgBgZCWdWf/e976nDz74QLNmzZJhGPL5fDIObG3i/9+Z1mAOAEajwZSvuy2G2p1ezZ9xlC6rm6QPmlq1Yt0OdTs9ktg7HpklW5eoIP1Y9gNgJCQdrL/yyiuSpD/96U9DdjAAgKE1mPL1aM+tdZTpkfk1uv65jYGAncZcyCTZtkQF6ceyHwAjJeky+AkTJkiSjjjiiIj/GzdunP7jP/5jyA4SADB4gylfj/Xc9Y0temr9Di2qqwz8jMZcALIFy34AjKSkg/V4urq69Mtf/jIdLwUAGCKdLm/EDaefv3x9IM9d39iimonFkoIacwFAFhjM9yYADBZ3VAAwSiSzr/RAn9vn9tKYCyPCbTHU6vGpqculVo+PTCfSajDfmwAwWNQqAsAoMZh9pRM9d1J5oR5qqKYxF4YVa4kx1AbzvZkuNLcDRi8y6wAwSvj3lY4mUfl6oueOyxnYzWN7t1P73GRFkTrWEmM4DOZ7Mx16DEM3r9yscx9eqwt//pbOfXitbl61RT0G1zcwGiQ9HXjbbbfFfKy3tzctBwMAGDr+faUXv7xFa7c1B35+sHw9dlZ8MM+NpUeGfvLcxojXIyuKZCSzlpgtBDFYQ/Hdlyy3JbJyRDo4IdVfzcR3JZDN0lK7k5eXp4aGhnS8FAAginSVQQ5mX+l07kntthi6nZvQrDbUpbvJrCVmC0GkQzq/+1LBhBSApIP1+++/X1L/fuvf+ta3lJubO2QHBQCjUazgJt3rcgezr3S69qTmJjS79ShyMibdVRNmWEuM0SNd332pYEIKQMoLbe655x5ZLCx1B4B0irku0WLRvWu2Zt263JHosEzX8OHR3u3U7cOwlnyk1xIDQ40JKQAp/0s2ffp0vfrqq0NxLAAwKsVtlLVqsyYfPi7q8zJ5j9/hvgmlSdPwad7vHJZ9qf1ricMDdrYQRLZgQgpAyndDbW1tuuWWW3THHXeovLxcRtCNzp/+9Ke0HhwAjAaJSsIXnnF07OdmaBmk/yY0uGGTX+AmNE3BFk2ahldHryvu4+m8ZkdqLTEwHEayuR0Ac0g5WP+///f/DsVxAMColajku88d+4YsU8sgbV6flh+4Cf3LEN+Esj5+eI3Nix+Ip/uaHYm1xMBwYUIKGN1S+hdz7dq1Gjt2rL75zW/qO9/5jlyu/tnzQw89VM8888yQHCAAZLtEwUtxfvTgJ90Z6OGWL58enV+j3R29Q3oTSpOm4VU+JmfYqiaA0YAJKWD0Snqxy5tvvqnrr79enZ2dkqQ9e/bo2muv1TXXXKOvv/5aL7300pAdJABks0TrEieW5GflulyXYah5v3NQW3sl0zSOJk3Da1xBjpZnwFpyGg4CAMwu6TuUp556Svfcc4/mzp3b/0SbTeeff74kyWKx6MUXX9TFF188NEcJAFks0brEPK8368ogey0W7WztUVuPS3l2q/786V598lWH7pw9JemtvZLd0m4418ejX77MXbqb7u0QAQAYCobPl9y/SjNmzNAf//hHjR07VpJ06qmnasOGDZKkrq4unXXWWYH/zhR793bKMKTy8iI1N3eKf5+zA2OanUbDuMbaZz3b9Fgsum3lJq0PCpRqHWW6rLZSz7/bpKVzpiT83G5Lf3f3aGvR66vKI5rG9RhG7MkQnzkCyGyQCX+nqV47/ueMhr/NWDJhXJEaxjQ7Ma6ZY/z4oqR+L+nMutPpVFHRwRd95JFHAv+7sLBQXpPMlgNAphoN6xL7O7OHBuqSAv9dU1GSVMO3VJvGDUeTpkwN6DL1uAcq1WuHLDwAYKQkHayXlpbqs88+U2VlpSRp5syZgcc+++wzlZdHX28JAIBfvEBpfWOLFtVWJtXwbSBN44ZyMiRTA7pMPe7BSOXaYds/AMBISrrBXH19vZ588smoj61YsUJnnXVWuo4JAJClktmmLpmGb2ZqGue2GFq8KnZAZ9bGZZl63IOVyrWTTBYeAIChkvTdzI9+9CPNnTtX3d3duvjii3XooYdq9+7deuGFF/SXv/xFr7zyylAeJwAgCySzTV0yDd/M1DQuU/dxN9NxD2cpfirXDtv+AQBGUtKZ9QkTJujZZ5/Vrl279Ld/+7f6zne+o7/927/VZ599pl//+teUwQMAEoq3TV2do0wTS/KTCtL8HfTNsD1YMgGdGZnluHuM/oZv5z68Vhf+/C2d+/Ba3bxqi3qMoZkoSOXaMVMFBwBg9EnpX5ljjz1Wzz//vHbv3q2vv/5a48eP1+GHHz5UxwYAo8poaPQVb5u6ZQ3929QlaziaxiUjUwM6Mxz3SK0JT/baMVMFBwBg9BnQv8SHHnqoDj300HQfCwCMWgNp9BUvuDdz4B8cKHU7PSrIsQ44yDZDB/1MCujCr4v7L5iupWu2qtvpCfm94TrukSzFT+baiTe51J+FZ806AGDomHO6HwCC+AOMnU2tKgwEduYIftJhINnFWMH98nnV8kmm7/Bt8/pUajN07GEl/fvBDnA8zTApkSkBXaxrZsXCU7Xo6Q2BgH04jzsT1oQPdQWHGa5hAIA5EawDGHap3Jxm6tZSqXzGVLOL8YL7ddv36dWPdo2KraZSvTaGMigyS0l+LPGuGUl65bo67etyDvtxm6EUPxlDVcGRqd9vAIDhYY5/BQGMGqncnGbqHsc9hqF7V2/V5MPHqWZisXZ39qmkwK4ji/OjrslONbsYL7g/pCjXNB2+U5FqIJ3qtTHQoCiV4zJDSX4siSaEXB6vKkbguDNpCUG6Zer3GwBg+BCsAxg2Houh9Y0tWlhbqfkzjlKe3aoPmlq1Yt2OqDenZtpaKlluS3+gfvGMo/TU+h167I3GwGN1jjItP3+68sObWKWYXYwX3Pe542dEzVBWHK5Hhm5PMZBO5doYaFCUTVlPs5abZ8oSgqGQid9vAIDhRbAOYNj0+KQ1m77S+qAb1FpHmR6ZX6Prn9sYcXNq1gAjnk6XV5MPH6en1u8I+ZyStK6xRYtXbY4IDlPNLsYL7nNt8XfkNEtZsV97t1O3r0o9kE7l2hjIMoMOl1dftHbrsrpJOqGiRCvW7VC30xNxXJmy3tjM5eZmX0IwVDLx+w0AMLzMddcGIGu5LYbuXLk5IoD1//eiusqIm1MzBxixdPa6VTOxOCSjHixacJhqdjFecL+nsy+jyoqb9zsHlF1M5dpIJSiKlk0PnlDyB+ydLq/ybJaMybybvdzczEsIhkomfr8BAIZX/BQMAKRJvOzm+sYW1Uwsjrg59QcY0QQCDJMpyrMlVYoezp9dfO2Ger3045l67YZ6PdRQrTxf5Gv5g/vwc1NfVa76SWUxH+sP/GNvA9fq8ampy6VWT3/GeDh09LriPh4r0E7l2kg2KHJbDC2OkuVf39iip9bv0KK6ypDjiva7/sx7Os5fOsck3jUT77rA0MnE7zcAwPBi2hbAsEiU3ZQUkd3LxPWsRXaLivPjl67GCh5TyS4mKh1Opax4JNdmj80b+LlK9tpINqucaEJpUe3BYL0w1zak642HYkxGa7m5WWXi9xsAYHgRrAOjgBnW1QYHXQU5Vi2qq1TNxGL1ub3Ks1tVWVYQ9ZiCA4xup0cFgX3WzXkja/P6NLEkX3WOMq2LEsyls+Q4XnCfbOA/0h2py8fkDLg8O9ngM9mgKNGEkr9ior6qXEaCOHww642HckxGY7m5mTGBAgCIh2AdyHJm6Wjtz26+/3mrHplfE9EpPd4x2bw+ldoMHXtYiZqbO+UzeYCR5/Vq+fnT+8ukTZ4xG+mO1OMKcrR8XrVuH2B2MdngM5mgKFG5fK7NEjiuXo8n7u8OZr3xSI8JhhcTKACAWAjWgSw20lnTYP7s5vrt+6J2Ss+2vYXzvd6MyJiZoSN1voYnu5goKEpULj+pvPDA9emVzTZ0DdvMMCYAAGDk0b0EGAHD1cwrmQzdcMr3+XRSRXFEoD6SxzSU/MFhRaFdJVbDlJMQ6epI7bRY1OL2acd+p1rcPjktqf3zYoZzlagJ2xj5Asc1lA3b6BIOAAAkMuvAsEtnWXqitehmzNDtH8Ax+T/nzqZWFQbWrJsv8M1Ewdnk8F4CJQV2FdqtUoIMd7dh0e0rN4VMwtQ5yrSsYboKonSzH4jh6rsQXi5fmGuTYUi9Ho9sttD3HKr1xmbfZg0AAAwPgnVgGKWzLD2ZoN+MGbpUj8ksa+6Hw0g0AvRniO995WNdfFpFSr0EpP6MenigLknrGlu0eNUmPXj+dOUMMngd7mvA5vUpz2bR0tc/TfieQ7HemC7hAABAogweGFbpKkuPtR90+B7PZtzHN5VjSvZzZoMew9DNKzfr3IfX6sKfv6VzH16rm1dtUU+ituNpkO/z6Z45U/VMnF4Csc51h9MTc1nDusYWdTjjN2JLJJ3XQLLLT8xw3fmz9q/dUK+XfjxTr91Qr4caqpWXpkoFAABgfgTrwDBKpiw9qddJMugfynW1A5XKMZltzf1QMUNw2OXyDOhcd/a44r5uZ2/8xxNJ1zWQymSIWa47M6zjBwAAI4cyeGAYpassPZW16GbcxzfZYzLjmvuhYIatuqKd6+A17G09LinfHlGaX5Qf//wX5Q1ufNJxDaS6/GS0XHcAAMDcCNaBYZSuxlGpBv1m3Mc3mWMy45r7oWCG4DD8XBbkWPXI/JqEa9gLc6yqc5RpXZTJhjpHmQpzEjeoS+W4Yj0eb71/qpMhQ33djURvAgAAkHkogweGUbrK0s24Fn0ojJrPaYJJifBzvaiuUk8lsYY9Vz7dPXea6hxlIb9X5yjT3XOnKVeDC0KTuQaCS9x/sOJd/fajr7SjtVefH1ibnuryk0TvWWi3DnjrxZHsTQAAADKL4fNlWTvlFOzd2ynDkMrLi9Tc3KnReyaySyaMaToyaz2GEbNbdDY1oRoNn9NtMXTzqi0xKy5S2SUg/HVTuc6Cz/WTl56iy595L+bvvnZDfSAb3WcY+qKjT4W5Vu3v9WhMnlVdfR5NHJunnDhjlOzfao/F0r+mP8o1YDd8uulAiXtwNUDwJMNvfjhDl/zqnaQ+S7RzEfyeyxqm6Z3tLSodk6s+t1d5dqt2d/SqblKp8hJ84bgt/YF6tCz/YMbZTDLh+xepY1yzD2OanRjXzDF+fFFSv5cdNaRAhklHWfpQrUU3W4lu8OfsdnpUENhnPTsCdWlotuoayHZnwee6LWHjuIOl+bk+n44al6tOl1dOq1e5VovKx9nSMkY9hqF7V2/RCROLtfCMo9Xn9qo4366JJfnK83rV6vYFPmOsaoA3t7fELNWPtfwk2t/XGLtVO9t7terDXSHvUesoU2V5oY4elytrnL8VM/QmGC4uw1Cn2zzfIwAAZCKCdSCDpXstuln3NLd5fSq1GTr2sJL+2eIsvOlP5+RLqg3VgvmvKSVsHDf0fRGCP8frn+wNecyfie7sOjipUDOxOGR9vd+KdTv0yPwaGYaR0mRI+Gfa7/XpkTe2RUwG+P/7vnnTNCbO5zFDb4LhsKutR7eY8HsEAIBMQ7AOQNLgAjykR7oC3nRkcNPVDHEwkvkcwZMGfe7oQXe306Prn9uolVefIUMa8GRItyv2nvLrG1vU7fJoTJw+CmboTTDUXIahW176iO8RAADSIDu6MwFIyG0x4jbFMsve0kherDFNtaFaNOlqhjgYyXyO4GZwubbY/6R1Oz0ypEHtW97d54n/uDP+46OhYWKnyxt1gkfiewQAgFRl/jQ+gISSKW8fLSW6ZpC2BoMxxjRdGdyh6ouQrGQ+R/B6/40721TrKIua/U5HNcDY/PjHMzbB8Q5FbwKz4XsE2cZsfVwAjC4E60CWS7a8fTSU6JpBOvoCJBrTBxqmpa2EfSjWoicrUSn+WLtFbkm9Lq9u+GaVCvNsuuikI7X0la16/eM9Ib+bjmB4bJzjqXWU6YOmNp11TKlsXl/MG/yRngCJJx1BCd8jyCZm7eMCYPTgX00gyyW7ftkMa5SzXbr6AiQa0263JysyuPEy0ffPmyanz9e/pVv4jXTDNN3ynePU0ZPeYNjm9eneedVasmpzRDf4y2ordf1zG3XKNWco12qJe4M/khMgsaQrKCmyW3RmVbn+wvcIMhx9XACYAcE6MATMVDaXbFnqaCjRHWnp2ror0Zh29LhVUWjPiq39YmWiJZ9ui3UjvWqzHmqoVnGUYHiwx9/W5VRNRYkW1Vaqz+1Vrs2ijTvbdP1zG9Xt9MjrU8QEQuC4THqDn86gxO7z6YELj+9vMsf3CDLYaNpqEYB5Eaxj1BnqYMNsZXOplKWauUQ3G6RrPW+yY5otW/tF+xytHl/KN9IDPf7g74zC3P5ze92B4Dycz6eMu8FPd1ByeHE+3yPIePRfiGSmRAQwWhCsY1RJV7AR6x8sM5bNpVrebsYS3UwVfp2MSdN63pFYsmC2azvVG+mBHn+074w6R5kemV8TyKb71VeVq6sv827whyIosfv4HkFmo/9CKLMlIoDRYnR902BUS1ewEe8frD63+crmKG8fGb0Wi3a29qitx6U8u1V//nSvjiotSEuQbfP6tHxetdZt36dDinLV5/Yqz27V7o5e1U8qG5IxNVtJaKo30gM5/ljfGesO/Peiuko99kajpIN/Tz3uBNu3mfAGn6AEiEQfl4PMNlkLjCb8CwxTS2fJVTqCjUT/YC2ZPSX+MYxQVo3y9uHVY7HotpWbIpqQnVRRrOtmOSRp0BMnPkmvfrQrYtKoblKp3BZD+91eeX39ZdldfWn4+zFZSWiqN9IDOf543xnrGlu0ZPZUnX3s+JC/J1sG3uATlACRmOg+yGyTtcBoQrAO00p3yVU6go1E/2AlOqyRzFBR3j48+id0NkXs9e3/71OPLtW9c6vl8gx84iR80qggx6pFdZU6qaJEuzr6JPmUa7fpp3/4JOQ4BvP3Y7bsa6o30gM5/kTfGV19/Y38JAX+njLxBj8Tjzkca2kxFJjo7me2yVpgNCFYhykNRclVOoKNZG7eMz1DxU3v4MSb0Fnf2KJFtZXa1+VURaF9wBMnwe9RkGPVI/Nr9NT6HYGS7GtnObSxqTViwmBQfz8mzL6mciM9kONP9TvD/7fT1efSvXOr5fR4tT9DbvAzOShhLS2GEhPd5pusBUYTy0gfABBNMiVXqfLfrEcTuFlP9BpJ/IO1bF51xPsczFCZ+x/5HsPQzSs369yH1+rCn7+lcx9eq5tXbVGPQXlbshJN6PS5vYO+sekIeo9FdZV6av2OkMC8ZmJxRKDuN9C/H3/21WzXtv9GuqLQrhKrEfM4BnL8qXxnBP/tnP/EWzr7H/9H973yscaPyYl7XGaS7Lk0E7fFiLtVntvCdxcwWOm4fwIwMEyFwZSGouQqHaWeyWTnbN7MzFDRQCY9EgXixfn2QWWh3RZDTvfBa6lmYnEgo+7X545/rQ20ZDGTs69S6sef7HcGfzsjh7W0wNDLhqUyQKYiWIcpDVXJ1WCDDf8/WPe+8rEmTxirmonF6nN7VVJg15HF+YHXiVU2Z+YSc256k5NoDONN6NQ5yjSxJH9ANzb+923f71Ku3arl50/Tfa98HDUwz7XFz3IMJrOf6SWhqR5/Mt8Z/O2MnJFeS2vm73QgnTJ9shbIVATrMKWhXB872GAj3+fTnXOmavHKTSEZzURrJM2+rnKkb3rNJvwmfKzdIqdPCccwXgZiWcM05UW5sUl0wx/12nGU68lLT1FPlJL2jTvbVOsoi1oKX+coU77dKnGDlbRE3xn87YyckVxLa/bvdCDdMn2yFshEBOswJTOXXPm7fadS8jpcZbKDyfLQQOagaDfh918wPWKrNCn6GKaSgUh0wx/z2mlsluTTnXOrVe8oC3l8xbodemR+jQwd3BNc6t8+bmFtpe5Zs1VL50xJawZwNGcY+dsZOSPV+JClDwCA4cAdBEzLrCVXAyl5HY4y2cFmeczY7dvPHwjubGpVYY51UIFgoqAy1k34IUW5Mcfw/c9b1euVXB7fwde1GAkzEMnc8Me9dhpb5HR79fffniyvDm7T1u306Pl3m3TzdyZr0X6nel0e5dos2rizTdc/t1HdTo9u/vZxg77m/Oeyo9ctl8er9f/bohXrdqjb6RlwhnE4g/50vZeZ/3ay3UhN7LL0AQAwHAjWYWpmLLkaSMnrUJfJpiPLY9ZqhnSWmibzWrFuwmM1bfNvnbbsla2afPg41Uws1u7OvkAfg2hl737J3PAnunY+b+nWi+/v1JLZU2UxFNgqzCfp/MffVLfTE/29B3nNRTuXtY4yPTK/Rtc/t3FAGcbhLCtO53uZ9W9ntBiJiV2WPgAAhgPBOpCigZS8DuQ5qWT90pXlMVs1QzpLTZN9rc5etwpyrFpUVxloIJhnt6p8TI4KcqwRwe+iukr95p3PdcmMo0L2Opf614cvP3+68mOcv2Ru+BNdO7k2i974ZK9cnv6xK7X2BwitHl/MQF0aXGl2rHPpz+wvqqvUY280pnTtDWdZ8VC8l9n+dkab4Z7YZekDAGA4sDEikKKB7Dea6nNS3e88maAvWWbaazmZSYh0vJa/jL3V45NX0n/+aKYOH5en657bqKuf/UCLnt6gn/7+Ez156SkqyLGGPLdmYrGmHj4uYq9zqX+9+OJVm2Pu9ZzMDX+8a6fWUaaNO9skRZ6PodwXN965XN/YopqJxQd/N8lrL51jPVLvZaa/HQyt0bjvdHu3U/vcPjV1udTq8bGHPQAMg+z71wQI47YYavUM7gYj+DX2u71a1jAt4kbtYMlr5A26v0w2mee4LYYWr4qd9Yt2/Nma5UnnJESs3/WXsd/5cv/kyEU/f0tzHl2nVzZ9pUfm1wSC87WNLXr8z/+rO+ZMjXiNmonFUTuvS5HBX/C1ZLcmvuGPde3UOsp0WW2lVqzbEfUzpnLNpSrReQ9eMpDstZfOsTbTe0np+Q6CuQzl35cZ9cjQtc9tTHoCGQCQHpl5Bw8kKR3rUqO9xremHKLlDdPU4/IkXfKabJnsQEras7XBVTonIWL97qK6yqhZ8fCSbqm/A/uSOVP02g31gTH0SfrfvV1x39u/fjX8WirIsWrFwlP7XzvOWmf/tdPu9Gp7c1dEs7hYnzHf59MDDdPU6fSoo9elsXl2FeVYlTPI0uxkSvP9nyPZa284J5yG873Y3it7jZalD26LodvpfA8AI4JgHVnLFeUmWUrtBsNjMbS+sUULays1f8ZRyrNb9UFTq1as26HbV23WQw3VKrEmv0YymXWVA2lcNNINroaqg3c6JyFivVbNxOKQdebB1je2aFFtZcjP9ve6+8ucD4yB22KoOD9+I6miPFvUddLdTo8WPb1Bd8yZqiWzpwSaw0W74bd5fRqXY9Fz7zYlfT76A8VNaQ8U442LvzQ/1WtvOCechuu92N4r+5mxCWq60fkeAEYOwTqyVjpuMHp80ppNX4VkXYM7Xg/FTUp4Vi+82Vlhbn/gF36TP1JZnqHMHKZzEiLWayUS3gU+fHxsXp8mluSrzlEWsqd58LEW2S0xr8dup0e3/dcmvXZDvQ4vylGny6tdnc6okx6pnI9YgeL7n7dq/fZ9OqmiWPt73Rqbb1OBzaquiCqR2GMX7zjuPq9aXp9XC04+Ii3jMxQTTsP1XgQ5yAZ0vgeAkUOwjqw12BsMt8XQnSs3xy2PHoqblOCsn389dXiX8VjB8HBneeJVHqQrcxg8CdHt9KggsM966gFVtAmNREfnL+mWYmdd87xeLT9/en+vgRjBX6LrsaPXraVrPk046TGY5RTB19Nt/7Up5L/XpzjZEvs4fJJhDOjaG84Jp2Tea7AVIwQ5yAbZ2hMFADIB37DIWoO9wUjU8XpRbeWQ3KQEZ/1OmFgcdT21Wcpoh6vywOb1qdRm6NjDStTc3CnfID5z+ISG22IkLOmW+vsU3DVnqjpjZKDzvd64wV+ia8XpjrzeYo3zQJdThK/Pj7VeP9nraygmh4Zzwinee6WjYoQgB9kgW3uiAEAmoBs8stZgt9ZJpiP0UG3P48/6zZk+Ieku48PNbTF056rolQdPrd8RqDwwu3hdne9rmKZvHjder/9/9bprzlTtbO1R494utfe69duPvtIdaz4O6YYcb+uuRNfjm9vTO87RAsHwrvWJuti3O71p20Uhk7qgD2RHhmhG4/ZeyD42r0/L51XrzFHS+R4AzIRpfWQtu29w61ITZb2OLMkf0psUm9enrj7zltGOVOXBUIhVEm1IcufZZLVYdOvKTREVBJfVVureVz7W0jlTEl4LNq9PyxumaWdrj9p6XIElA5981aHbvjtF5z22LuZzkxnn8JLtQrtV35pyiF7/eE/gd8LX34f/d7jtzV26+tkPJKVnFwUzdEFPprQ9XWvNR7rxI5Au+fLp0fk12t3Rm9Wd7wHAbDLjThoYoMGsgU1U+jd2GEr/zFxGm3TlQYZkXcJLont80uJVm3VCRYk+bGqN2bugpqIkZvDmDwy7+twqLszRndE6szdMk9PjCdmCLVyicY4VGN83b5okBQL24PX30f47XPDjqSy9GOou6ANdS57sBEI615qPlu29kP3GFeTI1d2X1Z3vAcBsqMFD1vMHYYcX5UiSdnU6kyrJjVcenc7Sv3ilwmYuo01n5YHZyqWDy6BrJhbHrSComVgcNbjrMQzdvHKzzn14rf70171aEqusetVm5VutAx7neCXbS17erHvmTNVrN9TrpR/P1KTywpD32bizTbWOsqivG7xeP/g1kynJTyYzPVDB5/XCn7+lcx9eq5tXbQlZjhBNKqXt6Z4ki7c8AgAAIBYy6xgVBlqSO9RZsUTHZeYy2nRVHgxXuXQq2djgYDNRqXif2xsRvDktFn3R2qP5M47SZXWTVD4mRyvW7Yj6/LXbmtXl8gx4nBMFxl0uT1DFQGgpfr7dqnOnHqp/ef1T/emTvYHn+Uv8r39uY+T7JZFVHqou6Iky9ktmT5EhDbq0nYZaAADADAjWkfUGW5I7VN2pkz2uwUwYDHbrqXiSmUhI9P5DXS7tl+qEQHCwmahUvDjfHhK89RqG1jU265CxeYHf2fJlu352yUm65jcfRC139wevAxnnVALj/vMQWYp/X8M0XXlmj1q6XJpYmq8/bNmt65/bGPVYk8kqD9XyjUQB9xetPbr8mfcGXdpu5kmy0WAov7cAAMgkBOvIeulqFpVuqRzXQCYMhiNjHW8iIZn3H8zYhKwHL8iR0+PV/ig39wOZEAgOJv2l4tG6ptc5yjSxJP/gxITbK/mkVzd9FfJ+tY4yXXu2Q9fOOkbdTq9qJharz+0NNJkbm9//fgMZ52QD43jnYcmqzTphYrEee6NR185yaGNTa9RAPdms8lBlphMF3P4qiGhjm+oEQjqragg+k2fWxoQAAIwEgnVkvaEqyR2soTyu4cpYS9EDzGTff6DnwH9D/35Tmx6ZX6N/+OOnIcF08M39QCYEgoPNFet26JH5NZIU+R4N05QXNDFxQkWJNsZpRnffvGla8vJmPfZGY+CxOkeZ/ubkI6UBZmuTDYwTnYebv3Ocpk4YGyiNf/j1T/VGUGl8KlnlocpMJwq4wxviDba0PR1VNQSfyRvO7y0AADIBwTqynlk7qg/lcY10NUGy759KVrjT5dXOplYV59t158v9N/TXznLoqfU7IoLj4Jv7zi6XCnKsWlRXGZHRXrFuR9QJgeBg8/3PW7VlV7tu+c5kGYbU6/JqbJ5NYw9kWYMDjIW1lYFAPNp79rg82tjUFvJe6xpbtHjV5gEHIskGxokmRvb3epRnt+r9plZt3dWu6795rP729KPV7fJoUnmhxuWkllUein4P8QLuaA3xRrq0neAzNal8b1GtAAAYDQjWkfXM1izKf5PpO/D+Q3FcI11NkOj923vdKirK0ViLkfAc9Pr6A9pDxuapz+2VzWoJ3NCfVFESkqUO5r+5H5tv0yPza/TU+h0hv1vrKNMj82sCJejh8n0+/bShWj0+6c5Vm/XPf9wWcmzL51VLFkNtzshmdAU51qjvWX/gPcPXgw92AsWQ9L1ph2nhGUerz+1Vrs2iPZ19kg5eP4kmRrqdbl3+zHuB5nKP/OlTTT18nD7c2TaoiYR09nuIFXDHaog3lKXtyRjpSbNUmCH4TfZ7i2oFAMBoQbCOrGemZlHBN5n+gM7n82ld2E3nYI9rpKsJEr1+R49LN/9pm5bNq9byedW6PcbYWOTTl+29WrPpq0D2/PEFJwV+zxa2xVt4Ntvt9Wlsrk2/eefzqKXphqQHz58eswTdp/5APTzgev/zVu3q6NNjb2zT/BlHBX7uL8NeVFcZPePf2CLvgcfDJxkG0yH99ijZW6n/PPoD7WSz0sH7x58xqUz/56QjTdVQLTzg7nN79eb2logJkKEsbU82sB3pSbNkmSX4TeZ7K9uqFcwwSQIAMC+CdYwKw51Riyb8JrPb6dH1z23UorpKXX2WQ7k2S9qOa6SrCZIJDINvrmONzX6foUf/3BgS9AavSw4OdGJms6vKdekZR+vt7fsimqata2xRl8ujnBjZzViZ0UV1lXr0jW1ad6D03c/fjK7mQLO2aNY3tmhR0HP8hqpDuj97m0pW2n+MuTaL8nzmCdT9ggPuHsPQhzvbIgL1oZqISyWwHelJs2SYKfhN5nsrk6oVEjHLJAkAwLzi70kEZBH/DX5FoT0QvAwlt8VQq8enpi6XWj0+9Xql98PWK3c7PXrsjUZd8qt3VJRnS9tx+QOz+qrykJ8fDGKG9rPHen9/YOjfc9x/cx1rbLpdnojstD8gliS3xxf43zGz2dua9dT6HVpUFxkgS/Gzn7Eeq5lYHKiGCD6eFet26LIogXi48L3b/YFI+DXjtiQOOpLJ3vr5J61eu6Fe//mj0/XkpaeopqIk6jZtfW6v+tz9zfPMLPgzvfTjmXrthno91FA9JJMMbouhxVEqLfyBbfh4+YPPaAKTZiMsmeB3uCTzvZXK9W5mqV5LAIDRaeSn9YEsFCtjEm29sl+6S2JHuprA//77+jz6vKVbuTaLNu5si/j88T53d1/keQruzt7e7QoExwPJZkvxs5uxHgsOtsO7xV//3Eb926LTYr6mFFodUO8o030N0+T2+XT7qshr5t551WrrcqowN3qJbKrZW//EiPLt+ptfvB3zeePy7Xpze0vImnWzluyme218LKlmdYd7Cc5AxsdspfqJvrcyoVohGdlUIQAAGDqZ8a8akEHilZV6fb6o65WlobnJHK4gJt772y2Grn72g5i/E+9zR2v+Frx8oKKsQMtf/Vg1FSUqzIl//sKz2VJ/0GS3WtTU5dTYfJsKbFZ1uTyBIKHQbo1alhscbAcfz6LaSvW5vSousMcu53WUaXxRrh5fcJJybRaNL8rVuzv26bf/78uYe6DXHGikF61EdqBLHuI9r85RpqI8m1as26Fup0f73V7lWi2jvmR3IIHtcE2axZogvPu8anl9Xo2xRQ/czRj8xvveGuklPulitkkSAIA5jXwNHpBl4mVM1je2qGZiccTPzVISOxQSlQL3B8sutXl9closIWXgY+xWfWvKIRHP63Z69OHONhVYpDtnT9GHO9vU5Yx/8zsuP/TGt9ZRpjvmTNXsR9fpByve1RetvfqfxmbtbO3R7s4+fdHWqzd37NOyedMijn9PZ1/Iz/zLGa57bqPaup3qdnp093nRlwFcWlupi//1bV397Ae6/Jn39EVrj0oLc5K6ZqKVyA50yUPM5znKddO3J2vR0xsCFRBenyjZ1cAD26FcguO2GNqv2CXVd/52s17+8CvdvGpL1CUNmVCqH2ykl/ikixknSQAA5sO/BkCapbpmMl5J7HCWHQ/Ve8UrBb7mLIdmP7pOkgLN4daHZQbvmzdNkvT6x3tCfr583jRZvV7lS3qooVq93thb4dU6ytTr8ujJS08JbG22cWebdrX2qNvp0U/OqVKe3aJXgrrO+59XUVqgBxumaX9Qxn2s3aLaSaUhn6kgx6onLz1Fj/+5Ubev3BzoTH/VN46R3WZRvt2q3R29uuWlj0KWAeTaLFGz/sGCH49WIptM9jba+OZ7fXqgYZo6nB61dbs0Js+mPR29uvyZDWre7ww81+cTJbsyX1bXn01fWFsZd7LnirpJkqQv2nrDGln6hrRUf6i+U0Z6iU86mO1aAgCYE8E6kGaJMiJHluTrtRvqE95kDmen4KF+r/Cb6zF5Nn3weasWPdOfvb12liNmc7glL2/WAw3TdPO3j1O306OCHGvEObN5fRojaVnDNN2+clPIVnh1jjItrK3UdWFr5f1N4STp7OMO0YO//yTq9m4WSffOm6Yiu0Ul1oNluf5Jgg6XVx29bpUW5Oju34Z2+3/sjUY99kZjf4f4ihJtbGrVAxceH1i37++MH63aIlhw2b0UvUQ2XulwtPH91pRDdMfsqVqyclPIz2sdZSHHWF9Vrq6+kS/ZNcN6eTNtAxm83CZ4+8BwBTlWTSjO08Z1rRG7JPj/voci+O1R5JaC6fxOGeklPoNlpmsJAGBeIxKsf/LJJ3rwwQe1ZcsW2e121dbW6tZbb1Vpaak+/PBD3XfffWpsbFRJSYmuuuoqXXTRRYHnrly5Uo8//rj27t2rSZMm6Y477lBNTX9zJ4/Ho3/4h3/Qyy+/rJ6eHp1++um65557dMghkWW0wFBJlDEZeyDIiHeT6b8Rf7+pTdfOcgT2Dc+zW7V++z6dfUyprGm6OR2urZuCb65bPT7dtnJz4LF4zeHWbmtWl8ujUpuhYw8rUXNzp3wxjiff69X950/XztYetfW4lGe3qnxMjv7l9U8jtva69IyjI7Yri/r+jS3a3tylp9/8LCLQsHl9KrUaKi20q9UTf/nDotqDvQoW1VVqY1NrYMu0O+ZMTWoPdL9USmRjje/kCWN1+6pNUSco/Mf44c42LZ83TT3uyEZ/Az2eZI/ZHziOzbcp12bV4rBJhZFaL2+WrG7wcpvwyZxgi+oqdd+arVEnwoL/vtMZ/LZ3OyOaJUZ7z9HOLNcSAMC8hn0xWm9vr374wx+qpqZG69at05o1a9TW1qbbb79d7e3tuvLKK9XQ0KANGzZo2bJluv/++/XRRx9Jkt555x0tXbpUDzzwgDZs2KC5c+fqqquuUk9PjyTpiSee0Pr16/XSSy9p7dq1ysvL05IlS4b7I2KUS8eayk6XV+83temR+TXa2NSqy595T1c/+4EWPb1Baz7apZ403ueOxNZN4UsFEpWBR1taEGubszyvV5UleXKML9S4PJvy7Rbde17o1l73zq0OBOrXznLIahh6fMFJWrHwVF07y6GCHGvE8SVan51o+YP/M65vbNG3qw8NbJl28lElqp9UFnOrux/WTZLNYvSX2C84Sc9dMUOFdmu0t4h+XDHGt2ZiccwJivWNLZozfUJgC7ShXNfc3u3UPnfQFocWi+5YvVXnPrxWF/78Lb384Ve6LSxQl0Z2vfxwbwMZTfD1Frx9YLiZk8qG/e+7eb/TNNvBmZ0ZriUAgHkNe2Z9165dmjx5sq655hpZrVbl5OTo//yf/6Obb75Zr732moqLi7VgwQJJ0syZM3Xeeefp2Wef1fHHH68XXnhBs2fP1sknnyxJWrhwof7jP/5Dr776qi688EK98MILuvHGGzVhwgRJ0uLFi1VXV6edO3dq4sSJw/1RMYrFy5gkU87b2euOuW/4+sYW3Zmm7JTbYsjl8urxBScpz27VB02tgQ7gwccSXOI82HLkHsOICM7jZQalyMxtorL9yCyhVzlB/+22SGccU6aLT6vQU+t3hGT1ax1l+tklJ+nDL9o0/Yhx6nN7VVFaoGtnObRi3Q7t6/PIbjEiPnei7HLwZ+x1eXX2seM19/gJgeui1zD0vWmHaeEZR8vp8erIknx9sqtDPvm04bN9evj1bVE/ayKxJhESTZB09blVZus/X0NVstsjQz95bmPIa/qXLby5fZ+6nZ6EVRcdLq8MyXTbyQ214OstfPtAv1pHmaxRmsoFG4olDB29rmF/z8EywzILAADCDXuwPmnSJP3qV78K+dkf/vAHVVdXa9u2bTr22GNDHnM4HHrxxRclSY2NjbrwwgsjHv/kk0/U2dmpr7/+OuT55eXlGjdunP7617/GDNb99zEJ7meQQcwypnafT6U2Q6VjDtyU+nzqMaKv41w+r1r5Cg38EgUpnS6vSm0D/5DR1pTWOsoi9oIfk2dTq8d3cK359n1a+srHgcejHX8sLsPQvau3av6Mo/TsD2eo/UCpus/nU62jLGqm15+5NQ68vjtKoO4/J/4SW3uCINbu8+muOVN168rIMvCNTW3Ks1v0XliA7D83X7T26Ef//n7E5463/CG8lH1cnu3g2Pl8clkix6J8TI5WLDxVP42ylj6VzxprEiGZCRLD6B+z/iDGpTtmT5HdalFb98F93+0+rzSAy9AV5W9BktY1tsgnBbY4TDSp8EVrjy5/5r3Af6dyPWay4OstfPtASSobk6vXP96tblfiJQypflcevCYOBrb+69AwpLF58QPxgbznUIq1vn40XEfJMsu/q0gfxjQ7Ma7ZZ0QbzPl8Pj388MP685//rF//+tf6t3/7N+Xn54f8Tl5enrq7uyVJXV1dMR/v6uqSJBUUFEQ87n8sXGlpoazW/hvWsrKitHwmmMdwjWl7t1PN+53q6HVpbL5d5YU5GleQE/HzMbk23ROnnPfR+TUaV5AjSbJ3O7WztSfQUTx4zXpw9vvYw0oGfMw/eW5jxLEEr1f27+v9weetIevLwwP6aMcfy/a9+3XxjKO0IqxiYNbk8bpzTrWWrtkS0hzuzKpyPXjh8ZpQfPDvvsujqGv5A+fFIx1zSOTY7+7oVWvXgfHIsyvX5tPGpraI31tUV6nH/twYcy33Ld+ZLCn6uD144fG69aWP9JeggL3WURZYm+7/TIeOzQs5V/+7Z3/IZ3J6vJpYUiCL0f9Zo1m7rTnmZw1m73ZGnUTYuLNNdY6ykPPt5z/GLqdHt7z0Uchzz6wq1wMXHq/Di/MjnpeK/92zP+EafynxpEK4VK7HTBd8vfkbGvr/ZgpyrDr/xCPk9fliTiJFuxYT2dXWk/CasHU7dWZVecjfwWDecyjF+i4cTddRKrhXyj6MaXZiXLPHiAXr+/fv12233aYtW7bo17/+tY477jjl5+ers7Mz5Pd6e3tVWFgoScrPz1dvb2/E4yUlJYEg3r9+Pdrzw+3b1yWLpf+Cbmnp1DD3KcIQMYzhG9MeGRGNlAJdtldFNsS69Iyj9eb/toSUmUvSX7Y1a3dHr1zdfYGfTSzND2xnFl6m/cj8GhXmWtXcHPr3kqx9bl/Um3fpYKBU7yjT1Wc5dPkzGyIelw4G9LGOPxqXxxe1tP+NT/Yq32bV/edPV5fTEwioi3Kssrvdam7uDIxrR48z7nnp6HFGnJcuWSKaqdU7yiOqCKT4ze7WN7bIGZTpDf/cFsPQPXOr1ePyqNvpUZ/bq7e2twTeo85RpqUN0+Tq7lNz0Lnq6HFF/Uz1VeVaefUZ+rq9Txs+3xexRKGtO/KzhnMbhq492yH5pLWNB8d866523T13mu5ZHVnavqxhmrp7nLolSub7L9uadctLHyWV1Y+nrTt+qbQ/o+5fjx2t6iJa8z3/MSZzPWa6HEkPRlluY3e75XK7Ne7APMfyedW6PcoShmVRrsV4XIaR8JrIkU9lZUVa1lCt21cN/j2HWrzvwtFyHSVjOP9dxfBgTLMT45o5ysuTm1AZkWC9qalJV1xxhQ4//HC9+OKLKi0tlSQde+yxWr9+fcjvNjY2qqqqSpJUVVWlbdu2RTx+5plnaty4cTr00EPV2NgYKIXfu3ev2traIkrrg/kvZJ9PXNRZZqjH1B2ldFmK3WV77bZmeX2+kCA3WPg6zkKbNeaadUPSg+dPl2+Aa4UTNUMbk2vTTd+ZrIv/9e2IiQX/Mfgzn7GOPxqfL3rX9YIcq84/+UjdnkTH7+KCHP3DHz+Nmfm+b940+YJ+32mx6PYo5e5rG5vlVeR4JCq73rs/9Mbd/7mD19FfO8uhrbvaNfXwcaqZWKx/uOiEwN7uS9ds1dI5U0LWw8b6TGu3NeveNVsD276FTy4U5dliXuP+NbjtPS6NybXpe9MP08Lao0P2mb/4X9/S3597nJbMnqL9Yb0VWj2+Id1bPdk1/v712IYUUgVQ7yjTpUEVC+HMuC46Gamunbb5Iru4h/92nmL30EjlK7LT3d+sMFbFz373wWsiXt8OM/1Tm+i7MFOvo6HCvVL2YUyzE+OaPYY9WG9vb9ell16q008/XcuWLZPFcrDE8ZxzztFPf/pTPf3001qwYIHef/99rV69Wo8//rgk6fvf/76uueYaffe739XJJ5+sZ599Vi0tLTrnnHMkSRdccIGeeOIJTZ8+XSUlJVq+fLlOO+00VVRUDPfHxCgQr8t2vMxseJDrV5hrk9tysBtwl8sTs1v3usYWdbk8ykkhWAoOAgpz4//p7+9zq6XLGTVQ9wsPapPZvivWft2xmun5S1HvnVutvAMf1enxxu1i7vR4paDzst/lUU1FiRbVVkaUzEcbj0Rl14cU5erJS08JvFZpYY7cFoWso/dfA298sjfqa9z07eNUGnSMiT5T+LZvj73RqDpHWX9X+KAJG/8Yd/S65fJ4tf5/W7Ri3Q49Or8mZClDsNv+a5Neu6FeFWFbdg11EBNvjX9dUMa82+nR8+82afH3puqrjl71ujzKtVk0vig35mSSlP7t5IZDosaJg5GOrdk6e92BXgqdve5Az4kPmlq1dVe7zj/xCCkoFM+EvdATXSeZeB0BALLHsP8r9F//9V/atWuXfve73+n3v/99yGMbN27UihUrtGzZMj3yyCMqLS3VkiVLdPrpp0vq7w5/11136e6779bu3bvlcDj0y1/+UsXFxZKka665Rm63WwsWLFBXV5dmzJihhx9+eJg/IUaLgXbZ9j8enJ2SpC6np38d8aRS5fl8aQ2WwoOAa2c5Yq5X/taUQyT1l+HH6xIfHNQGtu9KcDNelGeLmpUrH5OjFet2RH3O2m3NgX3O7z9/uvYnOC/7e90qDTovVotFG5tao5bMR8vK7unsixlE1jvK9enXnSGBb31VuRbPnhISYCW6BjrCjjHRZwre9q1/iUK5Lq09Wt1uj3IObF0WLdDzf053gnGJdi2NGeIgxub1afmBDvN/iVIq3ef26Oxjx6sozya71aLZj64Luf6uneVQTUX07eeSvR7NxG1J3DhxoN3J09XpfGy+Tb+69FQ9GNb00N+X4f7ffaylc6YM6BhHSrxJo0y8jgAA2WXYg/XLLrtMl112WczHp0+frueffz7m4/PmzdO8efOiPma323XjjTfqxhtvHPRxAokMtMt2cb5dBTnWmOuuK8sLdfS43LRlfMKDgIIcq2wWQ7d8d7Iu6+iTYRiBYPyMY8q0ZPZULQ4r4w9vKjdr8nhJ0pOXniJJOrIkuWZjY+0WrVh4qh59Y1vo2uwoXeiD+fc5v/W/PtIdc6bGfY/g8+K2GLpn5eaYJfOL6ip1RHG+Vl9Xq/29Ho3Js6nH6dayhmm6feWmiLLrq8+OXMO/dluzvmwN7ZWR6BoI38c9lW3fxuTatLD2aF333Eb9+6LTVFxojxnohTfFiyXa1ngffL4vYYf+wQYx+fLp0fk12t3RG1EqnW8xVHxgAqEpSpVHrO3KBrud3EiJVakjDW7ZQTqz9QU2q+5dvTXm31NNRYk6XV5NSPkoR85QbUsIAEA6UN8FaGCZp1gZmXhdtuurynVUSb5eua5Od768WRujdDXfvne/DivKTVvGJzgICJ4kCN+3+5Xr65RrGLolyvru4OD2k13tWjJnqu5YlXoA4JP0sze2RVk/3iKvFHM9vz9YXdfYIo83dnfr+qpyFdqtanV5AuX+8TqOX3OWQxubIrvd33neVJ1YUaLLDpTOJ1N2HSxRU7QCu1XB5cKpbPtWkGvVZU9vULfTEwiy4wV6/qZ4sY7nW1MOCTlnRXk2vf/5Pv3jHz/VAxceH3gNv3QHMeMKcuTq7otbKh1tMiN4u7I7Zk9VV9/Bv11DPrW6fYPOJA/n3ttDsewg3dn6LpcnYQf/RJ/DjOKtrwcAYCQRrGPUG2jmKVZG5pOvOrSsYbqWvLw5aqYmx+tVm8ur95vaYmbXT59UlraMT/DNc7y14XceWBse72b81u9OVs3EYi1eFZmtTiYASBRURlvPHx6s7mzt0R2zp+qeNVsigsj7GqbprtVb9PqBteKPLzgp6nv52SyGlr7yccRxfLGvJ2LS4PEFJ8UM1DfubFO9oyzw2WJlfWsdZbpuVpXyLZKChi/WWIdv+1bvKNOfPt6jbqcnZMImUYC0d3+fLjtwboOPx79zwa1hjf1qHWV64MC2YBefVhFY759rs2hSeaHyfMMbxMSazOh2evThzjYtOPkIldn6A9ken7R4ABNJ4YZy/Xg0Q7F2Ot3Z+kTXWZ/bm7FrvDNhfT0AYPTJzH9VgTQZaObpYMbNpTtmT5HdalFbt1OFuQczMvEyNd19npiB8/rGFt312/73zvcOPuMTfPMcr/nd2m3N6nbFzxrv3NejXJslZjO0RAFAqlm3eke5Lqs7Wtf+5uDa8rLCHDW1doc0jSvOt6uiJF93BwXqUhLl6Aka7QWL91or1u3QqqtrAxMI/qzvHbOn6NbvTtYXrT3KsVq0p7NPR47NkzXK+AVn9zp63XK6vXozaNu32qDu5+ETNokCpByrRdc9t1F3zJmqO+dMDXR+L7RbIwJ16WBAf/FpFRHXy0s/nqkxw9wdO9mJq3Rlkody/XgsQ7F2Ot3Z+kTXWXG+vf84AQBAWhCsY1QbSOYpYcbtwA11vEzN2HxbwsDZ/96DzfgEBwGJGp8lKvHOtVkSvkZwABBeRpyoadm4fHug03quzaLdHb3a9GV74LhqHWX6dHenTjmqNGJ9++//rj4kUJcOZLzjlJd/9EVb1NL7aM+LV9peU1Gs3235KjCB4PR4VVleqAK7VV1Ot8rH9PcgmFiSrx6PR1Zb9HLq4LF2WwyVHz9BZx87XmPybMo5MCG06uozIiZsCu1W/eaHM9QW1J3b3xDQX5lw8lElqptUpjyfN9DcrjWJsuZwI5U5TaZUOV2Z5KFaPx7PUKydTne2PlEH/4kl+bIPc9UFAADZjGAdo1qqmadEGbd751Yrz6KEWbexSWSf0rW/b3AQkCjTPDbPlnDttL97fSz+ACDapMb9F0xXvaNcaxujv/5/f7pXj73RGNIx3jF+jGZde6g8Xp963R71OD16//N9+tE3Jumf/3hw3X1HryviNVes26E119Xpjpc3R5SjX15XqU1ftuvb1Ydq6oSxIUHuinU79Mr1dbozKHBasW6HViw8VRbDiChV/2HdJH34RVug90BJgV1FdqtyvF7JbtXyVz4e0DKLkEka+TSmIHLCpv88R5axPzK/Rs+/26TbvjtFXp9XC04+IiLgS6asOdhId8dONHGVrkzySO29ne610+nO1sebUFjWME15Xq+U3jkMAABGNYJ1jGqpZp4SZdz8W4wlE4gl6qCezgymPwjo9SruzftYuyXh2uk75kyNm13Lt1vlkS/qpMbSNVu14tJTJSkkYA9+/eAmeP613/8S1pSu1lGmu+ZU6xf/sz2QXR+bFxk8dTs92tXWE1Iyn2uzaNOX7TJk6N0d+0IC/uAgN99QROA01m7Rgw3T1OH0qKPXpbH5dm36ol0++bThs30RTfuWNUzTvau3DKicOpnmZvG6wFsMQw809PdIkGEk3bgtWPj2fGbujt1jGAmrPpL9mxrJvbfTuXZ6KLL1+T6fHmiYpk7/30CeXUU5ByamAABAWhGsY1RLNfOUTCYymUCsxzD00c7WkKZk4e8d3qF7sJ2obV6fxkgJb95tCg1Sw0uwx9otqj2mLGJrs1pHmRbWVuqeNVu1+HtTYk5qvPNZi+6ZW60el0edfW6NzbPrta1fB8rar53lCKzlD/7fwdY3tmjpmi1aVFepFet26I45U2UY/VvJBW9F1+30yOnxRZS5XzvLoV+t2x7xuhub2jRneq9u+vZx+rLTGTjvJdbg5mUHs9gFOVatWHhq9A7325q1eNVmnTCxOKI83/+4v5w6PDDPt1t1T9j6+29NOUR3zZnaf94O/J5dht5vaot6ntdua1aXy6OcOOXaia7/SeWFeunHM03fHds/aXFCRUnC7ebcUsJJkGzaezvZbH2yne+jVXIMZeM9AABGM4J1jGqpZp6SzUTGW9fqDyz83eC9itwaK7yruf/nydwQJ7rpTubmPVEJdp/XG7G12cadbYGA+yfnHBtxXMEZ83/+47ZAqfsZk8o0c1KZTjiyWO83teqUipJAcB13XX9jiy6vm6S6heX62RvbdNt/bQo8Frwv/O6O3ojAK9rrBh9f8FZu/vOeY0j3rt6qEypKtPDA586zW1WQY40bMC884+ioj0lSV59beYU5EdnxugMTH29u36dup0cFOVZdfFqFbgvf+72qXL+54nT98JkNat7vjHj9ROXasa7/4IkBs3NbDLU7vZo/4ygV5tj0rSmHSvok6nZzbp9PtyfRKT7b9t5OlK1PtvN9Mo337ATsAACkDcE6Rr1U1ommsh92rEApuJT++uc26sozJ+kn3zpWbq9PBTlWFeXa9O72Fr25fV/I85LN2Cdz0z3YUtuOHndIsOsPvB+dX6M+t1eG+rPX/uy2FLptXHBgHL5t3XnHT1BBjlXdTk/CsubDivO0bM3WmGXgr1xXp3yLVDupNCTwiva68ba1W/zyFi2dV62LZxwVccz1QRMD0Rr02W2WwOcJV1yQE7HNmNS/n7xPB/edj3dsPp9PKxaeGnUP+GTKtcOv/7H5NuXarLp9mLKn7d1O7Rvgnui9Fot2tvYEGutt3NmqipJ83TO3Wt1Oj7qdHtkshsbm2WQ3fLophQ7vo2Xv7VQ63yfTeK/UxqJ1AADShWAdUPLBa7L7YUuxA6XwUvppR4zTP7/+acSa7GgBYDIZ+3RsN5UoOx/82WIF3nVhnyE4mx1v27r7Xvk4EKQmaojn8ylu8ODyeDVGhvIlPdAwTZ8fCOwmlkb2C0jUnb/H5Y0eMDe2yCtF7SovSVbDiDqW9VXlcnqS23c+3rGta2zRVb3uiPdPpVw7vAv9zVG2cxuKbct6ZOgnz22MbFaWxKRAj8Wi21ZuCs2gO8o1o7JUcx9bH7KDwH0N09TpTr3D+2jYezuVzvfJNN4rHTO82/oBAJDN2BAVSJE/4/aHG+r15KWn6MlLT1FNRUlIMBYIlKIIDnTjBa1Prd+hRXWRW2fFumHuSHDT3eFKLiPYaxj678YW7Wzt0e7OPn3R1qv//t996jUOBjL+CoN4n2FdY4ueDvoMwdnsmonFcfdqP2NSmaSD26VFU+so076uyNLvYMHnqsvl0SW/ekdXP/uB/rBld8TrJsri7+91xzzm9Y0tUbvk1zrK9Nb20PMgHSyn3p9kN/ZEx9be4wp5/4Pl2qkHl8kEb+ngthj9JelhVSr+SQG3JXaGtn9ialOUiZNmPfbnxpBzvb6xRXe+vCVhnJ0oEM1WyQTgfiPZeA8AgNGIf1mBAbB5fSq1GsofX5hwXWt4lrrQbtW3phyi1z/eEzdjGpxZDd7KzOuTWj2+iGx3R4875Pf8a6r9zdY6et2B/bVj8VgMfdnWqzWbvorI9FeWF+rocbmyen0hFQaJsr63fHeypk4Yq4rSgsDPEwWfObb+yQB/N3iLQjPo/kqGRK+Tl2NVq8cnu9Witp6Dgb3/daWD/QISZfELcq1xHw9X7yjTHedVa0dzl06qKNHRZQWae8IEGZLG2PrLqZPtgZDo2HJtFo3Nt6elGdxAti1LtjlZyOsMYi/zXq+0sLZS82ccFbGvfLT94fuXC8Q9nFEbaKYSgCfVeI816wAApM3ovDsB0iTRutZoa8j9zbsur6uUZGjFwlNDgo1gfW5vzDLz8HLhMXmx14E/Mr9GRXnWqEGVof6svL/z+/bmLm0Ma5jmD2jvmzdNY4I++/KGadrV3hv3HLV0OrX1qw5NLM0PdGsvH5MTcx231L/fu/+87u9z6+650/RZS1dEM7tFdZUxu3/XOsr0u81f67E3GlXrKNOt350ceKzb6Qk837+l21FlBXG78xfY4wfrR5Tk68Ufz5TH69PYfLv+X1OrGn52sBy73lGma2ZV6YixuYFANl7wUxfUA2Hjzra4+9Nv3NmmucdPOBjcpphRD74uCnNtEf0GgoUHd8n2SQg30L3MewxDd4at8w9fNhJtEqerz501Hd4TSWXyJJXO90k13mPJOgAAaUOwjlFtIBnBcLHWtUZbQ+7v6n1rWAlvrDXquTZLwsZn/jXEhTm2mCX1eTaL7jyvOmItcn1Vua456xgteua9wPvOmjxez195upr3O9Xr8oRmLl0ejTlQ3u+2GLp95SYtrI0s1Q/+vBVlBfrluu0RTdmevPQUXR70vn7+vdoN+eST1Nrtkt3aH6CHB5CJMu/+HgLrG1u06Yv2kGC82+kJHFOto0ynVZbq0trKiO78dQfWPPu8vrgTA7lWi5a+/qlqKkq0sak15tr2OccfrrOOKZUtrEIhYt12wzT1uT06+9jxGptv00UnH6nFUbbLu6y2Us+/26QFJx8xoGAzWrAd3m9A6h/LO+ZMlU9SU5crUCUy0H3kB1JSHW9feUlxex0U5dmyqsN7LKlOnqTa+X60NN4DAMAMDJ9v9Nas7d3bKcOQysuL1NzcSfWeSQw2gE52THsMI6ITd/8NarVsRuK9mBPZ5/Hp2w+vDfnZtbMcUQM5qT/wqgnatqy+qly3fHuyDEOa/ei6mO/z2g31KrEaUd8v+H0/bGqNnjV2lGth7dG67kBg68/Oh08mXF5XqSNK8mX4FMjArtn0lWwWQxs+2xf1My0/f5pe3fRVSIAZeN+qcn1v2mEh26QFB5/fnHxI1MfCJzQKcqx6/srTtbezT2Nybdrf59bGnW16/t0m/WDmUTr7uEMk9QfnJQV2vf95q+575eOQ/gLXnO3Qoqc3SOoP+M44pkw2S38Xd0OS1WpIPmlXe4+eXBd5bi6rrZTNMLTw6Q2BSYhYnrz0FE0syQ8p8U72mg/ufu6vMPjkqw7dNXuq8nypB0v9zeQig1+pP2A/8cD1GLyffPjfy6VnHB2zE77/2oz53qu2xMzoRgv0Wz0+nRvjGpf6z+2K9TtC/o7CXy8dE3RmFW88Y53T4Oem47zwb2p2YlyzD2OanRjXzDF+fFFSv0dmHaYy0JLaVMXK0L3/eau+7OiLGpSkcgw9hqEvWrsjfp7sGvVaR5muPsuhP/11t047OnqDNT9/uXBws7Lwtev+9eLvN7VFBFVrG5v147OO0SPza7T5y/aY2XmLDH1vemRw/cO6STr+yHGB3wt+bPqR43R70O+HvO+2Zv3dN6v05KWnRN2rff5pFRHHIEV2Xa+pKNZrW3frsTca9fiCk3T1sx+oIMeqn11ykvLsFj34+8g9t1ddU6uOHqfG5tkDSwH+66oztL25SwV2qwpybPrpHyKft6i2UqceXRoonQ8+5kcPrIFPtI6+z+2NKPFOtut4nterypI8dY7JUWevW3OPn6AFJx8x8PXpcdaNr2ts0ZLZU3X2seNVWpijO1+OvtOA1+eL2Qk/3j7vNq9Pyw9kdP+SZKY7mSZw182qCky8RHu9bOzw7g+02/e7dFndJJ1QURJRhZKoD0A2nhcAADIdwTpMI51bjyUSK0hZVFepR9/YlrDkPPiYo60BX7xyc9Ty8ESBXEGOTU9eeoo27mzT5c9s0KPzazQmL/5aaX+5sP//x9vDPNZ+4FaLoT0dvTqzqlwPv74t6vusbWzWwtqjQ37mP0+nVZaqpqJEi2or5fR4dWRJvjZ/2aEvWnviHvuezj5d/ewHUR+Ldq7Cm4fVO8p1x3lT9bvNX6kgxxoof15UV6mv2nv0SlijPKl/LJeu3qJ7503TGPkCQUlXn1tXP/tBzOoH/57mJ1aURGTO6x3lgfXlyTSDG0wzs3QGVYmC364+tyoK7WpNcou5cIk+Z758enR+jXZ39CZVUp3o9Y4sydc4u0Urrz5DHb39DRcL7FbZDZ+UpbFntAnOWH/r8SZPAACA+RCswzQG0x06kfCg2idFbXCWaK/t4GOIVQVw77xqvd/UphMq2iLWOCcK5Lqd7ohAsKvPk1QDKH+jqBMmFsfMjkvR9wPv6nPrlU1faeakMj298FR1h69VP3Ce4gXQwcf9rSmH6J45U9UZo4GcX7zzEeuxojy7nrz0FEn9jdcafrZeNRXFemR+jTZ92a76qvLANmYxt4drbJHL65XbZolorHZSWAl1sHWNLbrqLEfEJMg986o158BSBf92c7GWOuzp7NPUQwpNkblMdt14oqA+2nWRbNO2cQU5cnX3JTX5kKgZ2li7RU6fdN+arUNenWMGyazhX7FuR8KdJAAAgDkRrMM0BtodOpFYQXW0zFOizLf/GMJvkoPLzrfv7dK/Xz5Da7ft1Q/rJkk6ePO8cWeb6hxlUddw1wZ1//Y7bFyeinOSa4zlbxT1RVtvUqX24e+7vrFFd7y8ObBO2f9Y8HmKFUAHn7f6qnLdNXuqcrxejcuJH1zt6eiL+nrRzoWfy+ONmNDwn9+GE4/QBTVHaNue/XHHsiDHKqthiVjfW+coU90x5TGfJ0keny9Quj+xNF+bvmhXU0u3air6946Pti2c/zNde3aVDg3qBj9Yg11nnGwn8ERBfXF+6N/lUDVti9cM7f550+ST9EVbj+bPOEqX1U0KTDYNRXWOGcSb4Fzf2KIr6ibpxPnFCXeSAAAA5kSwDtMYSHfoROKV1vuirLVNlPn279vt8/hCAvVYZefHHzlOp1UeXONcYLfq+ycdqcWrIrvBB3cvl/oDx6Jcm3o8Ho2xWqJ2YDbkU6vbF/jZWLuR8DMEB7Hh77uusUWXBQXzwRm6jU2tMQPoo8sL9fyVp6sw16oxuTZZDanV7VNXt0v3zqvWnVGCq/vmTdPuzt6ILPS3Jo/Xjd+erC6nW3XHlKsw1yrJ0Bt/3a1NX7QHmp2FZ/3XN7bo9u9NUZ/boyNL8uOW4C+qq9Tdv428LvyZ83jcHl9gsuDJS0/RIWPzdOOLH+rR+TWyyNDaxubAtnDXnOWQ3WZRns0in6Q//3WPvjftMMky+P2teg1D6xpbdMjYPPW5vWrvdWt3R6/qJpUqL8kgzJB0zVnHyOvzRVyP15ztCOzClSioP6okX6/dUD8s3cFzDOneudXqdnnU7fRobJ5N4+wWOX0+3RajHPzWlz7SCROL1e70qqsvexrLJZrgHFdg1z+89tekl/UAAABzIViHaaSy32+yEjXQujqspHlPZ1/MYwjet9tfhi0p5tZqgUA3KPjNtVuUY0h/980q3frdyerq9ai40K6Nn7eGZPlrHWVaWFupu1dv0YIZRynfblWOzaKxeTYdXpQjm9enHp+idrNfMntK3HNydFmhHl9wUkRDNz//3u7BDeqOKi3Q7GkT9IMV70Q9L/L5dPG/vh0yceH//MceMka/uvQU7etyqdftUVGuTYYhvbJ5l6onjNPs6RNCJjMOHZerZa9sjQi6rj3boe9Om6BLfvm2mvc7o67L/bylW1c/+4Huv2B64HnRytHPmFQWs/rgre0tMfc0r3OUKXgDjQnj8rWztVsPXni83v1sn04+ukSL50zRl609shqGelwe9bq92ntgWcEhRXkqsg1sP+/gLPrYfJtcHq/WhK3Jr3WUqbK8UEePy5U1iffocHm16Jn3Qvab918Xi57eoFVXn6ESq5Fwe68cr1c5CdbRR6sCsKeY2Y1VJbO8YZoWr9oUsxx8xcJT9eDvPxlUdtmMXeQTTWDm2a2xl4IMcmkRAAAYegTrMI1U9/tNRqLMU67NEpIRHGu3qHZSacQxRMt8+0Vb5x4c7I7JtanL6dHWrzq0Yt0OnXxUia456xhd9tQGXXxahb477VBNnjBW//GjmWrtdsrt8emDpoPB++V1k3TJrw4GyYHgZGVkcLJ2W7M+aGqLO+Hg9npjNnWTpAJ79EqB+qpy/eySk3TZ0xtCJhUuq63UzgNZ7PCJi4Icqx7/vyfpy7YePfbnxojAcsph47Sns0+Hjs1Tnt2io8oKonYd9z9vzvQJemrhafrD1q+1Yt0OSTtCqiP8VQVL12zVUwtP0XVnO0Ke7/8cOXGqD1as26GVV5+he9dsjTjehbWVshpG4L9f3fxVxDm6uOZwFY4v1JcdfRHNCuurylU7qVT5Md89uvAgNVYTPP9/3zdvmsYk8bodve6Q/ebDBS89Gcz+2jGD7HnVUX8/WmAsKWaVzM7Wnrjl4J297qjZ5Xtf+Vj3zJmqLpcnbhA+XLtUJCv4/Dx3xQyt/9+WiO7vtY4y7etyxn0dGs4BAGBuBOswlWQDgmSzXMmU1od31s6XAsfQ3utWR48rIgMd3EQsfG10Mt3Yn3nrMz13xena09mnz1t6As3ctu5q1yUzjgq58W7vcYW8fqLgZOmarXrl+rqI0nN/YP3nv+6J2wDN4/NFrRTwv9Z/XjlTTa3dUbctC5+4WFRXKafbGxGoSwcDy5oD3dWvneVQns2asOv4ns5ebWxqDZzL4O3u/GX63U6PLnv6Pf3nj07X4u9Nke/Az8YemJDpdMUOMLudHn3V1hvobh++Rds/XHSC6hxlunvuNF38r28FnuefVLJ6vfJZDP0szq4CP22olk9K6hqOtpQj0RaA3S6PxtjjL4dwWww5E/RoCP/7GUgn+nhLUW5/eYseO3Dt+MUKjJfMnhLz2mgL+xsJ5/H5IhpKFuRYdfFpFbo1bNIrPAgfzl0qkhHt/NSFVZn4/9YT9eAYzK4EAABg6PEvNUwnUUCQSpZroKX1/mPolCKamUkKNBGzKHKde6Ky+CvPnKSzjjtEd6/eEnXd+m/e+Tyki/PE0nw9vuCkkO7s8YKTbqdHbV1O3Tu3Wtubu+T0eFVRmq/OXre6nV4de2iRvjn5UG36ok1LX/k4EMDUHcgcG4YRt3T25u/4dOMLH4Zk1zfvate1sxwaX5QbcqynVJTI7fXFfL3ghnc1E4sTBl3+4CN4Lb3b69Py86dp+pHj9EVrT8h69qZ9Pbr62Q/02g31Ojroekp0XbzX1BozGJ5Ymq8TK0r0wO8+1gs/mql9Xc6ISaV4yy/e/7xVPT7pzgNLGPxVGGdMKgssdQgO3KO9VqIgrNvpkTvXGnUyIHhP7ly7VcvPn6b7gq6D4PMwkKUn4RLt8tC836lxB/6E4gXG8XoQ5Nnjb29oNYyIJROx/k7Dg/Ch3KUiVbHOz7rGFhky9OwPZ2hflzMwsbSorjLmxFy6xhcAAAwdgnVklGSyXMHrYAdbWh8r89Tt9Oj65zbq+StP73+9oDXOibKeP/nWsfrHP3wSN9N8SkVJ1C7O/uy8zYgfHBTm2pRnkZ5+8zO9/3mrHrukRivW7QjpQl9fVa5V19RqR3OX7FaLysfk6OHXP9X3T54Y97X3dPTpsUv6t0k79ahS2ayGSgpz9N6OfdrbebC7++Hj8lRRVpCwFNcfePoz2PEEP76+sUWX103S0WUF+ve3PtPtKzcHHvOfp1yLRdfOcsjl9emLPreKC3Lk9Hi1v8ulJbOn6IOmNi1dszUQwNVXleueudVa/srHUd+/3lGmP2zZHRiTm799nCqiTCrFW36xqK4yJFCPteTAP/kU7bUSnaexebaITvffmnKI7pg9VUvCM8mOcj156Sm6/Jn3QiZg7j4vPRnjxLs8uDSu4MAWcXEC43h8Pl/cXRbe2t6ijU2tIUsmkt2mcah2qRiIuBMHjc1aWHt0yORiYFLRMNK2tAgAAAwfgnVklERZrg6XV4aknU2tKsyxqshuUb534Gtt42VgTz6qRFt2dWjpmq1ac12d7nx5s9ZFKYsP5/b6Ij5D8Br3whybxubb9P92tmljU1vI7wU3rUtUMWDz+rR8XrW+7OjTz97YFhHIrN3WrKWrt+rm70zWH7Z+reffbdLFp1Xo6LLCuMd/yNg8bf6yXYePzdMlv3pHPzmnSqcdXRqz2VmiUlt/4Dku336guVtZ1DGudZRpd0evdrX3Bn6WZ7PorgPnPfw8GZLuOq9aG9e2BoKWf/jjpxFryF+5vk6tXU71urx6c3uL/uYXb+mBC49Xr9ujD5raAuMiSUeU5Ov3m79W+ZgcXXxahVxen5qilLHH+8zBQWIy2d1orxVvL/f6qnJ98HlrxDmcPGGsbg/bhUDSgUkmn56/8nR90doTKPn3+rxSlEmhVButJV6KYpd0oIogTmC8cWdbzGujMMfaXxVyoBu/X3CviW6nJ6TZY7LbNA7FLhUDlep+9/5JxVeuq5PLk/r3HwAAGFkE68goiW5Wv2jtCcksBTKUA1hrKyXOzEs+nXxUibqdbp1YUaLLais1vig35usV5Fg1fkxuYJ/uPLtVm75s0/QjxunJdbHXuAeXKK9vbNG1Zzu0rGFafzf4OBkznyRvlMkBv7WNzfo7t0dnTCrTN44drwK7VQU5Fs2aPF5vfLI34vdrHWX6w5avtbGpVXfNqVZBjlVnH3eIHvx97EqBO+dM1azJ4zX18HGB7vLBa/T9gee4fJsqSvI194TDtXTN1oj19teeXaVel0f3BWW9Swpz4nb739PZ13++ZjliBsV3vrxF35t2mG4Lyszf+tJH+ofvn6CKsgLd9fLmwLgU5Fh193lT9Z8/mhnyc/+592fD403yBEuU3e1weTU2ymv5Jx+MA58z+BjunVet2Y+sS+29Glu0sLNPN77wYaAkv6PHLV9YMB6vUZzNiL4GP9GSg/IxOXJ191dkxAt8V6zboVVX12rpK1sjrnmb1aLrn3tPz/5whhbWHh3RZ8D/9xMczIbvDR/OfyxDsUvFQCU78RXs5KNKlGeRxij17z8AADCyCNaRUVLNYqWjCVSipncPNVTriw6nHnujUQU5Vj06vybq1l8FOVY9eekpEft7Lz9/mp5aF2frt7C94CXJbrUoV/GPy79kYP6Mo+J+vvYeV8gER52jTPc1TJdFW/R6UMA+a/J43fCtY9W836mpE8aqpauvf29xQ3HXpDs9Xt3ynSm6d82WkM/hf5+dLd2yWw0173dq9Ye7dPfqrbryzEn6u29WyeuT8nMs8vn69yj/xf9sP1iy7ihTopXC/uZ8iYLihWccHfjvghyrHrjweO1q79Ev120P6Wz/yPwa7eno1R0vb46bDY+3f/lhY/MC/50ou9ve7VLhuDxde7Yj5LW6nR795p3PtXj2VFkMaX/Q+H+93xmx/jzee/mrOg4bl6dnLjtNbq83pLu4fxIix4jejf39z1sD1RvhQfy986rVtt8Zc8nB8oZpGleQo2Z/sB4nMK6pKNbvtnyle+dWR2SJO11edTs92tfljNpjwv85pxxWpFeur1N3n0fj8m26/4LpIccUfOz+IHwodqkYqEQTB3uClqH4f5bOYzTj9nUAAGQzgnVklHg3q8HdwIMNpAmU22Jov9srr0/y+aSuPpeKgvY4D85M2bw+jc23BYK5Z9/5XJfWHi2vQgO1O2ZP1eN/bowIdg4dm5ewA3q4jl63bvzTNi2bVx2zYsC/ZGBhlOfHs66xRUtWbdKyhun6u3Nc2rmvRwV2q4oLcyIy6PWOct01tzqi03awXpdXD/4uMvO+rrFFd6zarBMqiiVJv1x7MDB++PVtevj1bYEJjvDzVuso06W1lfIlGNKJpQW6dpZDTk/8YCU4kP3RNyZpT0evph85TsUFObq8bpI+aGqV3WroqfU7tKi2MuHe1ZJi7l/+x493B67hRGvP83Otuv93n+jHZzn0/51zrK4726fCXKt86p+8uPCJN7Xq6jNC1s0X5kb/Wo/2XsnsXOCfhLh3bnXU63RRXWXEFnX+c7Fk1WbVVJTosTcaA0sO2rqcKsz177MeOi42r0/LGqbp9pWbQioG/OXsz7/bpL858fCILLH/eyHW8oCCHKtWLDw1YlvA+qpyrVh4qhYFbUcYLcAdzLZ16ZRo4sBu+EK2okznMZpt+zoAAEYDgnVklHg3q5eecXTUfdCl1JpA9RiG7l29VRfPOCqidDrWzelYu0V3zJka+P23t+8LCdSK8+0qG5Oj21Zuini/RNnV8MdrHWX6oKk1atVAcObLH7fHW98ca4Jj3YHtv/Z09OnqZz+Iua/32sZm3bN6ix6dX6Prwsr1/QpyrFEbf/mfv7D2aEmKmvnudnp0+TPv6fkrT9fCzr6QoPe5dz7X333r2Nhrtx1leuOT3Tp8XJ6OSrAO3x/IFuRY9d3qCbpnzZaIhnV3zanWL/5nu/pmxB+vth6XDBkx9y8vyLFq9bV1unv1loRj8/GuDl3xjWP0wO8/jrpzgCR19blVNCYnJJCMljHevKtd958/TYeMzQssRfD5fFoRZ+cCf1XH2m3N6nZFn4xJ1FDxirpJunaWQzUTi7V9b5cmluQfzMhGmWzJ93p1//nTtbO1R209rsB4P/9uk+6aPTVq8On/Xrj3lY8D5yVkomzO1IjMv3RwO8JXrquL2tU//D0GspQm3eJOHPg0JMdotu3rAAAYLQjWkXGi3azarRbNfnRdzOxusuXz/pvSEypKktrWyc/m9emkimLd9l/9wXi0QO0/fzQz6num0gG93lGuy+qO1rW/6Z+UeP/zVnV7JKfHp64+t1wen9b/b7NWrNsR2Pvcv75ZUlhWvD87HXuCw6WjywpVkGNNWEb+428cE3V9fb2jXK4EWe08u1XWON3tu50e7e3siyzVP3+6fvCrd3TX3OqIz1brKNOdc6u1c1+3nly3Q7vae+MG9bs7+pvWLaqr1NI1W6IGr0vXbNGiusrE2fAcq+IlGrudHnl9Xj3UUK39bq8aTjxC9/x2S9TGaFt2tWv1h7tiBtM/+sYkFRfmRHR+D88YF+RYdXplmR4LC1if/eGMpLbV8x93NPEmmwpyrJpQnKeN61qjru8vUPQTlef1qrIkT51jctTZ69bc4ydowclHRA2iD05QuXTzt49Tjs2iu86bKq/3wERGnk0+KfC3GW7ttma5PN6oXf3NargnDsy0fR0AAKMJwToyUvjNqtvS30gpmSZQ8dZdBpeOJ7OtU7D9CZrfFeaG7gXtXys8vig3ZpfrekdZYO/yXJtFuzt6tenL9kAA9sj8mog18P4S5s272gMBqn/P5Z9869jAOu7xRbm6+F/fjhmE5edYdffqLXry0lMS7n/e3uMK7A/vP2/1jjJdVne02rriP9eQ1OWMf+6OLMnX7/6uXu09LhXmWrWno0+vbtqlo8oKAp8tuNx8d0evvjgQqK9vbNHGpraoExa1jjJdVlcpm2EJ7NUetwlbbaU2fdketSdB/2cu158+3iO31xe3W/sYW/81V2wx9EW3UydUFEdtjPbo/Br98x+3RT2e9Y0tWvy9KYFt4EKONSxjXFqYE1ECLh1c0x9LcCBut1iifqZ4kxeL6ip135qtcSe9YkkmII1bmm3xqczW/9ymBNfgcG6/lonMtH0dAACjCcE6skKyTaASrbv035T2ub0h26kFdzBfsW5H1JvTRNn7Ars1sBd08Fphf+bbq8jM92V1lREB9ZOXniIp9rZf6xtblGuz6P+efpRmTT5Eezr6ZBiGPmhq1Y9//b5e+NFM3fHyZp1YUaKaiuKoAWWdo0x7OvoC5/Lvzzku7mfLtVm0rrFFi2dP1dQJYwMB57W/6Q+kYwWudY4yvbm9/+dxg1u7VbeG7Q/uP4dS5Hrry2or5ZMR0pAtPKifWJqvP2zZrZtf/EgPff94vbrpKxUX5MT9nFL/bmZXn31MRE+CWkeZrj7boXc/a4ldzRBlPXRhri3mBEGiJRI+KW7G058xbvVEz4wmW9VRX1Wu//50T9QS890dvTH7SMycVJZw0mtC3COILZXSbDNtv5aJOH8AAIwM/oVF1gguj/dnnqN1R493c++/6Sywx2+8NTY/8k8nUafmfIu0rGG6lqzaFFFmHxxISv17jn+6u1NGlEW9/gAuVml6QY5Vl8w4Sk+t2xExKfHCj2cqxzC0ePZUtfc4o5Zg1znKdOd51brkl28Hzs+9c6tjZpOD17139rp14wsfhkwuxC7DL9eiukp9+EWbjj+yWHXHlOuasx16M6wT+fJ509Tt9kSMW3AAfst3J6urz6OuPncgK/0PF50Q8fvB5+vxBSfpsTcade0sRyADf1lYM77wCZsjivM1YVye/nbFu7r4tIqI5nGXP7NBj86viZgcGJtv17gY66HjXTfjEmwvlqiawz+pFCszmkw/g/qqct19XrXOe6x/O7jwKobNu9p193nVunt16ERZraMs7vIG//ENVCql2Wbafi0Tcf4AABgZBOvIKjavT6U2Q8ceVqLm5k75onRHj8Z/c++/KfX4fDGz1oakB8+fLnm9ESX1yxum6Z41W/X6x3sCzwnek73P49FN35ksm9USEjiGB5JPXnqKbl+5WbWOsoit2xJlQ2Nl3P17ij/UUK0xdov+385uuVw+3XHeVHm8PrV1uzQmr7/E/JJfvq3m/c7Acz9v6dbdc6t1d4y11f51726PV09eeoouf+a9QMDuD1zvmD1Vd8yZqu4+t4rzc+T0emVIWrFunx5+/WCpd72jXCuvPkNen0/FOVbZvF7t6Yke1PnP29QJY/Xp7k69/1lr4PiSzRoHT3oEB6+xOqXXV5XrgQuPj1if71eQY9OKhacGqjC6nR699OOZ/YFjlIAmXgf0ojxboBojXK2jTFZL/GA4sFd4jMynfyLFIiNkXOsd5bp7brW8Pq8WnHyE9ru9gc8avOe8fyJj7/4+3Xjucbp3brXaup0qyLXpg6a2mE3pwo9vIFIpzTbT9muZiPMHAMDIIFjHqJHUzb3VrmXzqvVle2/MxlvrGlvU7fbIY7VEL6lvmKZbvnOcOnoOron3+Hz6c2NLoBN3aWH8cmt/9jy8yVd9VbmOLM3Xb6+tldVi6PEFJ4WU53c7PQmbwXW6vBprt+j0ylJ1uzxq73GpIMeq+Qcy6dF4fD71uNy67psO/f25x6nX7dGYXJvy7Vbt73PpiQUna1d7j5xur3799udaMntKoJt6QY5VS2ZP0bQjx6ppX7cmlRfqrt/2N/GL1WH+vjVbde+8adrV2d+hu7QwJ+72cLk2S0R5eryscXAvgKK8g9nr599t0q8uPVUW/VUnVBTHnPTw+nwRkyh+3U63rntuo5bMnqL/+NHp+qK1R4W5NrktRsyO2f4O6F+09cjl9amkwC63x6dep1vLzp+uJas2R2StL6ut1LrG5rjLB/wZz1iZUf9+7Qtrj9bC2qM1Ns/ef83mWJXj9fbX/Ht9GmMLfX6siYw6R5mWnz9d+V6vzjqmVL1eJc7IDlCqpdlm2X4tU3H+AAAYfgTrGDWSvbnP9/mUY40fRHh90uIYjb0Wr9qshxqqVXwgq+eR9EV7r9Zs+ioQVPnXnfuFl1tXHNgffMW6HYHAvb6qXPfPmyavId27emvEeunfXHG62rqcyrWHNrIL19Hr1tI1n4Yc+6vX18Vscucvhz65okRHlRXorpcjG9pdVlupP23drSvOnKQFpx+lcfk2vfjjmdrf69bhxfm698BWaNfOcuiZNz/T+kRN/Bpb1NnnVnuvW3/+dK8++aojYj/s8OOrmVisy4P2Nnd7fZp7/OFaumZL1D3a/b0AfnttbWAMHrjweD3yp091QkWxvlN9WNwtyRZF2b++1lGmzbvaA4Fs8PZvwb0RojU5zPN6dXRxXujPC+2yeb1aMnuKvmjtiWhAJ6k/M24YERnPu8/r7zbvb2YXLTNa6yjTJTOOCmy799KPZ2pcjkWdLo++DmvAGPz8WNUb6xpbAte/zevTGCn+vuC+gQd6AynNNsv2a5mK8wcAwPAiWMeokcrNfaLA3ueL39greL1sj1d69M+NIYFNMuXW/vXxRxTn6bUb6g9kIX26beXmGOX5n+iy2kqNyYsfrDvdkcsB/vjxbt15YN1xtP28b33pI/3NyUdGlGr731uSaipK9Mgb2zR7+gQVF4xVe7dTG3e2aevbn+nEihJdVtvf+d7/GRM1T/uitUdXP/tB4Bh+9ZftIRl7KXQru/A16h6vT7s7enXTdybrZsNQd59bBbk27eno1S0vfRQS9Nc6ylQT1EfgjU/26rSjS+MeXzj/cW7+sj3utn/3zq3W240tWvrKx4FjCATyMYIhQwrZui7YrS99pP+66gx92dYjwzDk8fr01vYWnffYusC6f/8kwb1zq7W9uSsi6Pcfx5g8W9Rt4PzPf6ihWvv6PPJ4fUnvlhA3IzuI3b4ozQYAANmOYB2jRio394kC+66+5NfLdrs8EYFbcNO1mhh7uvvXx99//nTleb2S16dWjy/mJMG6xhZddZZDf9iyO25p9Luf7Yv4+S/+Z7u+OfkQzZk+IaJpmn+9+RetPVHXTvuPddGBTPmi2krZrIb63F6dUlGiEycWByYiHl9wUuA5ya4pD54MOPbQIj156SlyerwaPyY3UBr/nz+aKauhkEkP/yTIg7//JKLL/m+uOF2/2/yVPtrZpj//tb/Leb7dGhKAJtqKasK4fD156SkqyLGp2+kO2W4teA1+sLXbmrW9uUtrNn0Vsi99tA7mweJdj39/7nFavHJT7GUFQa+dJ+npNz+LeV1/8Hlrwu7qdouhz1u6456b8N0ShiojS2k2AADIZgTrGFWSvbmPF9jfO69azgRZ4eDMfHdf5Drr4G7hs6dPiJmlXNfYoi/aenTEuLyQreViae9xxey+Xuso0zVnO9RzoFN+cGa52+nRwqc26D9+NLO/iVzwZ3aU6cSJ49Tr7m8eF76Nnf91/JnyPrdXrd0uFefblZ9j1T+89tfAcQQH6Ml0IvfzTwbs6ezTjS98qEfm1+ifX/805LnPXzkjZNIjZqO9xhbds3qL5kyfoDvPq9aDv/tYv/if7fr5/z055Pfcnth7pdc6ytTn9ujyZ94LNNTzS1Qx0Of2hhyjf+zDM9LBwq/HghyrfvSNSTpnyqHySaosL9S4fLtsFkMbm9oilgoEv3a863r2I/0d36NtW9jrlcaof+KgOEGX+uHcyovSbAAAkK0I1mEa0dbxxmrIFe+5Y/Nt8nT0qt3ti/payd7c+wP7dpdXX7b2SOoPMGc/sk53zJ6SdEl9tG3epIOdzM+sGh/3s1ktFu1q71NxgT2pRmvR9hQ/qrRAX3f0atHTG3RyRYkenV8TWKfs17zfqZ0t3fr/zjlWC884OpBdP3RsriwWQ//02l8j1n4HZ4f9gXiuzaLxhbmy2w31Ob0xy//jTSoEd5j38x9PrCC8O+y94jXa8wf/i1du0mW1lbrw5IkqLggNQNu7XVH3FfcfX3u3K/CZZk0er6mHj1PNxGIVRukGHz5GwccQLDwjHcx/Pe53e2W1WLS3s0/LX/04pNqhvqpcjy84SVc/+0HE+/pfO9aE1df7nYEtD2N1wfeX6k8syY/ZpZ6tvAAAANKDYB2m0GNE7oEevFY22eceDDRCG7Al+1p+/uDf5/Fp2ZqtEaXBS1/5ONAkLlFJ/dgYJcwFOVbdMWdqwixkZ68rkLmtd5QlbLQmRd9T3B/Ir21s1o/POiYk0C7IseqO2VNUlG+Ty+OVYRja+lWHVqzboWd/OEMP/i7yHARnhzc2tQYC8d0dvdrT0avqI8ZFVCCEB+j+SYWrz3Iox2ZRZ69bHzS1Rt0WbVy+XW9tb4kZhPeGbROWTIZ73YG91S9/5j1dO8sRkkl/r6lVW3e1q6aiJGJpwPPvNOmaWQ6tWHiqPv6qXbd+d4ruWb0las+B4M8SXjEQfoyJrgXbgc7s67bv028/3BURLPuvsSvPnBRRih/82v4Jq6KiHHW6vNrV6VRhrk3XznLIbjXirrl/qKFaeV6vlp8/vb/JIuvFAQAAhgTBOkac2xIZqEuRa2WTeW68PcaDXyteFj84+H/y0lOirhHvdvaXQL9yXZ1cnoOvU2i3qtvt0Z6e2J20pf5AfcXCU/WzN7bpy7aepMvB+4/F0B1zpuq2/9oU+Hl9VbkuPePoiGy0X67NEhIYtve49OL7O/Xo/BoZhqHCHKu8Pp/+/Ne9gWywP9i0WS0x18mvb2zR1Wc5dOLEYv3mnc917dlV6nV5dM1vPtDJR5Xo9u9NiThvwVn/sXl25dotslkM5dgtejistN2v7sCe48+/26RvTj4kajl++Br4ZNfE+89L+ESC/7+fjrI92cLaSi341Tvqdnp0//nTtTSsMZ//NaSDpe7RKgaCjzHZjHSny6vK8WPiNji87btTdOyhRYHz88lXHRGvHW2CrM5RpjvnVOsX/7M95mv7y+nzvV7WiwMAAAwhgnWMuE5XZHdyv3jreKM9N5k9xvNsMfZHn1etHEMhj8XLznY7Pdq7v0+VY3JUUmhXj2Ho1pWb4nbS9gc2pYU5uvPAFmjvN7WlVA6+trFZt8+eEghYc20WFeba9Ku126OWxwdvbeZXYLfqkhlH6en1O2KWtvuP5bqzq2KeA0nKsVpUOiZHt31viv649Ws99sb/Bpqm2a1GxESEP+tf7yjTyUeXBjLAsyaP151zqnXvmi0RVRH3NUzTv7z+qR648PiY5fiffN0Rsv3cpi/bVe8o19rG5og12CUFdvW4+isKDh2bq5+cU6Vph4+T2+vTrd+ZIqfHI5+vPxu9dN409bm96upzq8/t1ZvbW0Ky5YeMzY07mXHrdyerZmJxROf1WZP7lz/4KzSOLMmPe579OnvdcnviB/QdvS5d/ewHkvoD8GUN02XzekMmqZwer06oKNH7QWvc1zW2aOmarTH3kPe/v79Un/XiAAAAQ4dgHSMuUdO0eOt4w5+bqPS5s9etpa9/GjOLf+/cas2fcZQuq5ukD5palZdgz/Kxef3HlWx1gD+wafUcnGSItsa8srxQr2z6Kmo5uCS1dbtCmpoV5Fj14o9nqtflCSmN9gf8v3nn85CfSdKejl4trK3U/BlHhWSopR2BYG19Y4uWzJ4a9xx09Lp00S/eCryX/3gW1VXK5fFoWcM07WrrVVuPK/A+W3e164r6Y9TrOtjs7o1P9kqSrptVpTvnTNX+sGzt33/r2IjJEOngBMet35mikypK5D3wM8OQrj77GNlthi6ZcVTkGmxHmZ689BRt39Ol044u1eXPvBdYEvDkpafo8T83hrzXb344Q5f86p2Iz5+w3N7ljejA/q0ph2jJ7Km6Y1XsyZ1YivJs6k3wngU5Vl07yxGYnNjV3qMji/N1z+otev3AeZail+qvbWzWwtqj474/AAAAhh53XRhxiW7+4z0e/lii0ufCXFvcLP725q5ARrLWUaZzpx4as0S9zlGmohyr5PWq0+XV+01tIQFScADc7vTKapHG2PrL4sMnGcLXmL/wo5kxM5uSIvZS73Z69Lcr3tVLV52hXW09yrNbZbMaau1yyW616IZvHatFT29QraNMP6ybpMNL/v/27jw8qvpuG/g9azKTnZmwCYHABBISkIFA1EkUqQiyCBZ9FKklBOvCVvtWFgVEQSguz6NFpLUKSFtQWy2LuKAW2iaIKJIqq2YECShb9mWSWc/7x+QcZjkzk7BIEu7PdfVSZjnnzJzE8v39vosOrxYdDdrJFwM338ZnaqUiZDMx3zR98VgP3NgLWdckYOOe401j2wJHpxnx25F9cf/6L9C3c5zfLu6OI+cwb1Q6OqgU6BCwW1vvdIfdwa5pdOJXf94rLXp0jIvC3X/6DC81pbLLdYUHFBjcMwmbv/pBuo6C3FSs2mkNen1Vg1P23JF+5uKj1UHp4jEalezCQ3NKP+I0Srg84TvV67UqFJdWBixOGDHF0hOfHq2QAnO5rvTh5JoMiNF4f+aJiIiI6PJisE5XXKSZ5uHqeAPfG24cWF6aEQr5bHqJ7y7pLms5XvzkW8wZmQ7AP+DMNRmw7I7+0IqpxfVO2Q7aYgB8uroRe5tqhxeP7Qd9VPhfPY1KGfpzmAwoq7XLLgyU1TZCp1Xjf7cf8d+xNRnxtwevR5XNAaVSEbbG+oEbe6FDjFZKs/cIAh4dmQ4h4DuQS9PfZS3Hb27pgxc++Tbk/PhCaxk8EHDP0BRpLruvukbX+UDdR3PG1vkuevy5YKjPbnGIBZqmXeQXPymRriNUKUWooDzSz5zYt8A3XbwizMJDpNIPtUdAfJQaM282AQgunZh1cxr2HZeZt970vQcG5nJd6TvGR/l9Jr1WhYVjMtC/WwJ+rLUjoYXTGoiIiIio5Ris0xUXbqa52Fk6VEM4tUfAsglZUldqsSmYAggaabV8fBYa3fIjz0SBAdmOI+fwy+t6wpyShBnDTNColYiLUiNOq4LW45GadM0ZlS4bmIp/njcqHYNSkjCweyLmb9oPc0pSmGDciH99e1Z2bFieyYAlE7Jgs7tw6MfqoIWBuwZ3w1PvHsS1KUnIb0qpFwP5Ze8dQkbTeLFINdbPfuAf7A9PT8a8UemoqHdAp1Ghzu4KqsEWuTyCFABGGp0GeLMdVk8eJF1nnMyouwaFImK6eeC9EwPj5nSFl/tnoFBB+dqiY1gzJRtKICilXa4zeoNCgZOVtrDXFK70AwCiPB50S9Rh7ICufp3qz9Q0whCnRcH6L2TfJxeYA/6fOS/NiH8ePit1wXd5BKQaYrBk20E8vumA3+taMmGBiIiIiFqGwTq1CqFmP6t9AmK52l4FgCXvHsS13ROl2eCxWhVWTBwAm90VdCy1OvQufmDndZHN6cZXJ6pw96BuiBaagpqmBQTxun7t8sgG3oA3QHK4PFCrFHjl397U8+KmpnKBAZ7FZMDCsRm4Y/WnALy73PNvS8fZGjuA83PeB6UkIt+Sis8CUppPVTXI1meLu+BqhQI2Z/gFi7M19qBgXqwnn/2zPqi3u/zq5QPFRamh16qgUYVPDxcDxHq7y68Z2p2DugHC+eBR/J6vjbDAEXjvXG5vqnikNHWxL4HvnHg54kKQEgoUWs///JhTEtHo9GBwzw7IbwqEuybqkKgN7owufpZ8mYDZV3PqwqM9Hgzr3UH6nYmNVuNsrR1Hz9XL9jkQyS1GiJ85L82IJeMzMWZlkXSMmcNN+PPu7yNOWCAiIiKiS4vBOv1kwo1LA+Q7S0dq3DY6qzM+OXLOr2kWANyYZsQzEzKRpPKvew61ix+q87peq0JG5zgsHJOBs3V2v+v27UR/rs4e9rOfq7OjW5JOCnjEpnJvPnAd5iqAExUN0gzvU1WNUqDk8ghY8cGRoECpyFoOAcG1xlEaFV6SqbcW//zorX3hrm95YKXXqjA5pwf+d/uRsEHzLenJiI1S460Hr4PN7sba/CFS3X5gABmlVgYtkBRZy7FoywG/AFD8nkN1zc8zGfHoyL74/T+/9Tt+tc2JqZZUnK1pDBvkd4qLwsZf5aChqblcqB10m8ONjXuOI9/SE4+PyUB1gxNuj4DdR8sxY+M+adzdVEsq1ErIBrDiZwm78NDMEW5A8O+MpVcHnKxqDPuewMWIvDQjuiXp8NEjeYjTKKEAMLhHkvT70ZwJC6FS9omIiIjowjFYp59EuN3xcGm0kca65d/QU/a5/4QJIgJ38WOj1dh3vDIopVvsCi6OWAu87trG8w3HtBF2kROiNYjWqPzSvdcWHcNHh86ga0I03tt/SgrcZg43SYFcuEBJLqVZrVKE3eFfMFqFjnHRfiPOfMntUOu1KqycZEa0RhU2aL4lvSPmjErHwoAO53Idxy0mA87UNGKqJRXz3/k6qP6+0QPENr1frFWX65ofpVaiQ4wW09Z/gVX3DoLTLUhB5t7SShz+sRq/GdEHg3t0wNJtB4Nmik+x9MRdr+z2mys//52v8ZLPDrrY2f76XgaoFAo0ON2I0arwvx99g/Qu8TB3T8Tzd10rLba8+Xkplo7NkA22xc8SONNd+v5DpM43l04Q0CNJFzJ7JDdgcUQ83/mMEe81+y5oNWfCQriUfSIiIiK6MAzW6bJr7lgzOZGaioULJMIFEb47ktWCgMxrEvDqL7NR7TNeLCVJFzS+y/e6F47JkB4L12Qs12RAkl6L8at2+QWrYmD43J3X+jUL8627b269taiyXr5juais3o6H/vJl02xv/3TuXJMBi8b1w4SXd/m9pyA3Fet2HcPknB4AgoNmAUAPgx5ut4CTlTZMze2Fa1OSpN30wI7jeWlGLLk9E1u//hH/97F3dnrQWDWfhRzflPDArvkA8N7sXGy8PwexGhVuH9BFKofQa1S4JaMTztTYMavpevMtqdColVApFNgdMC99l7UcSgBr84dg5zdnMbhnEqbf3BvG2Cgsefeg33lvyeiIRWP6YeGWA0HXHS7YFj9LqIWHXsaY84HzBdJ6PCF7QCybkAW7y42b+yT7lYcE8l3QckbY4ecot6tDpMwoIiIiuvT4tyy67ELtjuu1KlzbPRHVDg/q7fJ/AYyNEAiEq0dubhChgBLPfHgoKLX6joHX4Ml3D8m+p7CkDFrV+fr3cDulj92Wjh3fnMFLk8x+Dd827jmOe4amYMbGfXhqXD8suT0L9Q4XbA43tCoFZv8sDXHR4XcsAz+/pimTQNwNDuwWL3i8geK09XuxcEwGfntrX9TYnUjSa7H94Gl8cOAUzCmJfp9B3N333cUXg2ZjrBYb7r8OT2717y4fuJu+y1qOeaPSYe6eCEOsFjanCy98XIKZw03yHeN9FnLilIqw0wI6RKmg9giodLox5539fs/rtSqpK7wYVK+Zko1fhqi5L7SWI7/Wjhc+LkFemhEjMzvjSZnO+Z8cPgsAWDEhC/VOd1BvhFB8pxcELjzkpRnx7IRM4BJMRQvXA0KnVCAxYCyeHHFBy3UR0xqofbjQzCgiIiK6OAzW6bKT2x0XU6vD7ag2KBTYd7wibG3v2Vr5WvEbmxlEuJQKPLnpgOyYqye3Hgg7f7rK5vDbwRR3SmcMM0GrViI+Wg2NWonvy2z49LtyPLf9fE21b8O3/6ZUwtyjA+7+026U1Tn8zvG7n/dvfkqzyYBEnRbD05Nlm8zlmgy4JaMT9FoVbA43Ht90AO/OsuChv3yJ5++6Fqt2WKX7AgDFpVUoyE1FclwUVk8ehES9FsvvyMLT7x2WdqOfmTgAS7aFHgPn+/2drGzA9A378PZD10MQvN9Bc+uhI00LAOR/zmwON/717Tm/n6FI2Qpx0WqpfrvGGbpx4CeHz2LuyL5BfRbCac7kg0tFrgfEhR7np7pman0uJjOKiIiILg6Ddbrs5Ha4xdTqUDuqKyZkYcGm/aGbiqUZsXR8JlSK4F3XvDQjnpk4ABqXC5H+ClkTribeWh7Utdt3x9rlAexuT4jdVe+ZK1wevFZ0VDaYVUKBBWMysGhsP2w/eEq2g/fSbYfw3uxcPCHTEG/OyHRU1juwevIgRKmVSI6Lwn1r92Bt/hA882GopnRH8FLT9ykGrQ/c2As9DTpsnWkB4A1wH7stAzFRKizbdsh/McVkxJop2Zi2fi9sDjc6xkeFrZH33Y0XG8pp1UpU1Dmk0XThVDe6EBenhc7j3Sm2ub2LJHK72KEyKaQu7goFCkvKInaHT9RpvL0OPALqIpRhXEi9drhd79aqLV4zXRqR+oawwSAREdHlw2CdLrs4mTTaiDuqDrf0F8TZbxTLjjAbvbIIN/Q2YPmELDQEBMtdEnUoK6sNe13NmXftK1I2QGAX+1qnBx4BIYPZQmsZfqhqwLT1e2WbsAHewLmy3oHRWZ3xm1vSoFYpoVIqUGVzoqLegS99Oq2vnjwIZXUOlNU5wgbQ04eZMPm1PdJjt2R0xISB12BRQGO4XJMB+ZZUfOozHs5b4y7gzQeuw8nKBtjs4cfAiQsCvg3lKuoc2Nt03X8uGBr2/dEaJQ6drUe3JB3ilQr07hiLsrJaCAKCdorlfs7E7/DNz0ulRRUBaHZad6RSigut175Uu94/pbZ4zXTxIvUNYYNBIiKiyyf8FhPRJSCm0ealGaXHIqUi1/h0Wrc53NIIs2nr92La+r1YtcMKm8ONTw6fxeObDyBOo0RKjHdHVONTQ+lSKlAtCKiDAmUuAcfqHCh3CbArlXjmwyMRr71rog6/+3l/GGO1eGmSGevDZAO4lN7dpQaFAnM3HcCtLxbiXIg0/cDvYZe1HOt2HUNBbvBuc6PLg6XvHUZVgxPPfXgEY1YWYfJrezD19S9QXFqJlZPM0GtVSNR5/8LcGGGOenWDfxO69C7xWBAQqAPenXi5ayq0luNcrR0b9hxHnC5yTX2eyYDF4zJxrs6O2W8UIzkuSlpgEFPU5eSaDNh+8Aymrd+LkS8WYtG2wzhZYWu6j06cc3pQBwXcTd+73M8Z4A3AF4/pB63HuwPYoSmtXu513rTu8z8/4gKAHCmwv8RcSgUq3QJK652odAvSzxXRlXC5FqyIiIgoMv6/LP0kAtNoY6LC/+jFBzRWu5BZzw1QYMUHRzD7lr5YvM2/Lj3XZMCisZn45PDpkDXxFpMB7+0/ha9OVOHth27A6eqGoIBWr1Vhxs29cUtGJ1TY3bDZ3YjXqbFkfBYanS5AET6Y803JlhvFlmsyIDZKjQdu7IU1RcELBWI6/ZsPXIdztXZYTIaIad6Bz7d0PBwAxESpYU5JwunqBuSaDCgKMQauW5IO16YkYcLL3k74eWlG6LUqrM3PRpG13LvjPXEAFIDfMcRdfXHuvV6rwj1DUzDvH18HNbKbNTwN18RHIVoQmp2u3dzXXap67eZ20mYjL2ptQmWsAGwwSEREdLkxWKefjG8arStCh+84rcrv+ZbOeq62OfD45gPIt6TKNkArspZj6baDuD+3F/p2jgcQUBNvMmBKU7Boc7ixcPN+/PbWvn7H0GtV+ENTvfiSbcHd5BeN64cDJ6tCfk5LQIO4wM9paQpYX/zkW0wfZsKLn5TIfvZCaxnya3ti1hvFWDnJjDM1jWEXIMKdU47c841NafEahRJLJ2Rh0eYDQcH24tszcY9P0zyLyYApN/TE0vcO4d6cHjhyqgZvPnA9PPDgyduz0Oh0o7TChu4ddNh+8IxfSUCoHgfin8cO6IrrUzvA7vZAcAkhpwv4CpfWHRhcr5iQBZvLjZqGltdrNzcAZyMvao3YYJCIiOjKYbBOV0SkvwAGzooOtVssNnzTR6nxfZ0TMVEq6DQquOvsKLSWY+5t6SHrt4us5Zh3WzqmrvsCz0wcgPm3paOu0Y24aDWiNEoUrPsiaPzZzOEmKYW7IDcVP1Y1YNv+U7Ld5Je+exBTm7rDQxD8gjCLyYBpuanY/0M11kzJlo6f0kGHV+4bDLVSgQM/VuPAD9WYnNMDbo+AtflDsM+nRt2X3eWBzeHG/He+xvN3Xoul47OweGvAd2syYoqlp7RbLWrpTvwt6R3RMT4KxaWV0vi2ZyYOwGO3ZaDO7kJslBrx0WqoAay8x4yqBiei1EoUn6iSAnC7ywNzShKeevcgfjchC/M27UeBJRXTN+zD6smDgnb6I+3+/yq3FzwAnt526KJ3pcMF1yktrNduSQDORl7UWrHBIBER0ZXBYJ2umEh/AfR9Xq4pWKiGbxaTAYvHZkKvVaGuMXz9ts3uxoqJA7A2YNc2z2TAa1OG4JkPDweNPxMbwZm7JwII10DOu1hw9yufYdP0G+DyCKi2OSEA+OL7CiigwOfHKvDCx+d3zMUd/XnvfI0VEwdg3a5jfjvqoRrRRamV0GtVWDFxAF4tOoqhqR1wW1Zn5N/QE3aXRwq4N+w5HhToF5+oCpPKbsD+H6p9/mzEwrEZWLT5fFmBzeFG8Ykq6fuI12nQ6PJAoQDu//Ne2S73Ynr9qh1W1DXNYTenJIVM44+0+5+g12DxltBB8ZLbM1FR74i4236pd7dbEoCzkRe1ZmwwSERE9NNjsE5XVKS/AIrPAwjaiQ+XGr102yEU5KYiNloV9vzG2Cis3FEiszPuTZMfmJKEHUfOSY+LAW1BbmrEABIA6hrdsDnc3u7tNgei1SrotCp0jIuSHelWaC2HB8Bzdw4IWaMunl9cRBBT232/jwJLKqat3+v3XnFxw+7ynx1+6MdqPDEuE0vfPdTU7R3ScWfcnAZDrBYZXeKR0kGPAz9U42iZTQpAwy2YzBqehpfvHYQZG/fJBuzi9yc2ExRHrMml8Ufa/VerFGGD4qNl9dL3EW63/VLvbrckAI/UqCtaq0KlWwi72EBERERE7Qe7wbdRV2PHaHGn/aNH8vDOQ9djbP8uYceiXd/LgLM1duSG6TYeGLj6KrKWS7vFgY+PzOyEbkm6iEGkuFgQr9NAp1ZhxsZ9SIrRYFCPpJDnLS6tQpcEnexON+AN2MXryjUZMNWSirVFx2DunigdU24hweZwezMCUpKwdaYFf3/oemy4Pwf9uibg40OncVv/zlgzJRurJw/CminZMKckoWD9F1jy7iGolQo0OFzI6ZkE+EyvD7dg8tKOEpyqbpDtcA+cD8DFZoLi9Z2rs2Px2EzkNd03vdb7HeaZ5LuyW0wG1DSED4p9v4/A7v2+wgXX4nVUuAV8L9ONXk5LOmmH6zxvMRnwwYHTuPXFQszdfBANivb/+05ERER0tePOehvU1jpGN7cTdnP47sSX1jvDvlalVOAf+05i0dhMLN120C/4zTMZ8dT4TJScrQt7DDHIE2vjxfp1CIDN4cLZpg7scoF3nsm7WGAxGfDf0ip0jI/y7jALQH2YoLAgNxU/VDWEvS69Vo21+UPQJT4Kq3ZaUZCbihjt+V/nUIsINocbq3ZYMTKzMz4/Vo5+XeIxMrMTlFBgzEtFsu8ptJbhoWG9ER+tQbQCuCZRJz3XnE7yneKjg54TswHkmgk63QJOVjXgVzf2xuOjMxCtVWHZtkOYYukJD4SgbvAzb06LGBQHfh+hdslDHUevVWHVvWYsDaiJD+xGH6glnbRD9XGwNC3IiL0G2HCOiIiI6OrAYL2NaWsdoy92YSFcoB8pQIuNUmPeqHS4PG4sv6M/TlY2+DU7e/q9Q/jNiD5hjyHWgsulet+Snoz5ozOQaogBENhN3tsN/oWPv5ECrVX3DvKOYtOoEG5fVG43P5DN4cK09XthjNXi7Yeux6LNB/zeV3yiKmxH+O0HT6O4tBJ9O8fj7lc+w7r8IWHPV93gxB//ZcWyO/pj3/FK6dguj4CZw01+Tfh8m+D51sv7nn+qJRVvfl4qNRNcPiELJ6saoIACHgj49LtyrC3yzngvLq3ELms5Pj1agYLcVBRYvCUIiToNkuOj8P7+UxAEtKgDPnA+Bd33Z6xDjFY2uC7ITcW6omNBv3e+3eiH9e4Q9LvX0k7avn0aqhtdqGlw+jXmE7HhHBEREVH7x2C9jWlLHaMvdmEhUqAfbtfSYjLgw4On8dWJKiyfkIXHN+2X/d5uyeiEPJNB9rlcmVpwX58cOQdAgfmj07H09iw0uLxz1uOi1VApFThd1YjeHeOkQEsQBORbUmFzuYOu3XfnPkarRtF3ZWF37MXg856hKVi02fsdXdvUoG2XtVyq/wYQtBM91WckHQAsHJMBVYQyiii1EoXWctgcbix97zBWTjIjSq1EqiEGf979fVC9utgEL0qtRIJOg7X5Q6BWKZCk18DlFqBVK/CzjE5QQGi6z/uDdqxXTjJDrVBIxxazAnxtvD8HL3xcIi2ohPu8geKi1UE/Y94Z8N6FC9+fqxt6GSJmEIT63ZNrpBivUUKAgEqXELQQJWaP1AJBfQd8seEcERERUfvGYL2N+Sk6Rl+qtPWLWVhobqAfKW3Y5nDjRGVDyOt4+r3D2DzdgqcCZrFbTAY8MS4TKz44jMk5PUIGap8cOYtJOSmYtn4v1uYPQcHrX4T8PhJ0Gvxy7ef4S8FQJMZopGv/8nil3879minZYYPtReMyMeHlXQD809AD3zP7jWIUNI2OUyoVsDnc2Fda6Reo77KWY/5t6fjn4bPIMxn9Gsz5nlNcHKhpdEm15S9NMmOpzAx78c8Lx2TgbE0jik9UBQXz5pQkrNphxe9+3h/vf/1jyB3rR2Vm2/uWIyTqNVh+Rxaefu+w3+dVq5RQKxX45kxt0K404F30idGoMD9gkcDmcKPg9S+waGw/LByTgbqm34FIv3d2lyfs715gI8UGAViwOXzGSUvq3YmIiIio/eHf9tqYy/0X+EtZD38xCwvNDfTFXcsqhwfHyuqD5nkDQFVD6Np2m8ONY+X1GNO/C+bflo76RjfqHS4Un6jCva9+hnuGpvjVgssR69r3lVaG3Q1P0Gvwtwevg1qpRLlLQL3diUVjMhCtUWHBpv3S+4pPVMGckigFn2Lad5RaibM1jfixskG2u7oYRPu+p0cHPaAAPjl8BlldE9CvSzxW3TvIL1X9ZGUD/vrZcfztweuDZrMH7kzHNDVZE88f6h7tspbj8dsyEK1VYtxLu2SPp9eqkNYxNuwx5t92fjEnVDlCnsmAzdMtOFZeD7VSgU+PejMLAOC92bkY3CNJNgXd5nLLntvmcOOxf+zHR4/knZ+r3oya+Ob+7jV3Iaol9e5ERERE1P4wWG9jLudf4C91PfzFLCy0JNBXewTY7C5M37BP9rV6jSqorvrrk1VQKICsrgmIj9bAGBuFfx4+i4HdEv1Sj1ftsEasIRdrstcWHcOaKdlQQuG3Q51nMmLx7f3wvx99g4mDuwel1G+8P8fvOz+/Qx5YI98Ri8b1g83hxh9+MQiJOg06xkVDr1VJwXNgqvjr+UPQLUnnN89dr1Vh4ZgMvPXgdThZ2YDuSXr8pWAont9+BNd2T5RmsyfoNIiLVqPg9S9gc7hhMRmgVimkBYlIo+tsDjeqGx145+EbghZSAGDlJDOqwyykAEClzSmdL1Q5QqG1HE9tOyjt1kvfe5oROgWCUtC9mSIenI3QQd5vrFqEkouztXb06xjTrN+95i5EtbTenYiIiIjaFwbrbczl/Av8pa6Hv9CFBZdSgZgoNVZPHhTUsEw6dkCgH66Ld2KMFsWllQG7sUZMv7k3pq3fKx3XYjJgWN+OGJ6ejM+ampmZuyfCGBsVNlATU8TNKYmIjVJj/m3peFypwI9VDUjQaeDyeLD8/cPo1zVBNtistbukxQSXR0DXBB0cbjceuqk3HrvNW09eVmNHnF6Dx3124MXvce2UIShY702/D0wRj41S43cfHMY3p2uxZko2OidEIUqtxlNbD+DxTQek4+SaDMgPqGUHgOHpyXhm4gBEa1RQKbyp9AtHZ+C5j76JOLbO4fYgSa+F0+0JWkiZOdyEdbuOocAiP9ZNlKjT4LHbMrD/ZBU6Jegi1o37fi/Lx2dB1fT74JuCjmY2KPR9PlzJxazhaegWHw0FBFS6g2vQA7VkIUqu3l1cbCAiIiKi9o3Beht0uf4Cf6nr4S9kYUEuDd+3YZnN4ZYN9EMtDBTkpuL57UdkdmPL4IGAgtxUKQD0vuYI5o/KQJ3diVU7rVhbdAwv3zsI04f1hkcQggLlpeMzUVnvwNj+XeBwe/DCJ99ix5FzUm31bZmdcbrGiR1HzsnWvuu1KqlJm7ijvuLDw0Gd5eeM6otnPpT5HE2f9/WpQ1Bvd+O1oqNBixLT8lIxL1GHp9717j6L3dV9FVnLITR9X+L79VoV7s3pgdd3+XdBzzMZ8djodHg8CLuIsftoOUZndcHOb84ElQeItfZmn6Z4csf46NAZrNphRV6aEb/+WVrQa3zF6zR456Hrm/370NLFJPH3rsbpQU2jC3qtCnqNCjol4BQEzGlm+UhLM04C692Z+k5ERER0dQi/NUatlvgX+JQYjZQye7EuRz28GOB89Ege3nnoenz0SB6enZCJaCE4kHIpFUFNtwBvEL1ul3eM1/lA3//zKgAsGZ+JvDSj3+M39DL4zVcPPG5givsuaznUKgVW77RKqdevFR3FtPV7YU5Jwpop2Vg9eRDWTMnG6P5dAAFI1Gthc7hQZ3ehX9cEKS191Q4rjlfYpHRxhzv4MxfkpmJJU5O20GneZahtdMkGtIA3YHe5Beg0ShSXVgW9d03hMez9vkL6vKGOE/h9iNcTVBZhLcPv3j8MKAQsHpcJi8ng97xYl7626BhKK2x45d9HMdWSCovJAL3WW5KQHBeF1ZMHIadnBywZn4XcMMcQP2OktPuEaHWLfh/ExaTAn5lQP2PiezqoFOgZo0FHjRKxECAAeFzm51YsH3EFdNoXFwnkSIsERERERHTV4846SS5XPXxzdwZDpeHrtSqYU5Iwpn8X3NwnGQ0uN9Q+KcbibvyXpd4xaw/k9kLnpGi43AJqItREywWANrsL16YkId+SipgoNQalJMmm4gPwdm7fdUxqmmZOSfTLAtBrVOgQq8WaKdmIi1Zjbf4Qv2P5dnP3/fdAkWq7qxqc2LDnuN/OuKjQWoZ8S8+gzxvYWT1ao0KSXiMtNoS7nkJrOX7t9KC8rgHmlCS/Jni+deldE6Px0iQzHG4PfjuiL5L0Gix775B03JnDTTj8aTUGpiRhatP3XW93yc4W3320PGTHerG7e6XT3aIpBpciS6Wl5SOsRSciIiKi5mCwTpIrHUTIpeGH7ADelGKsVcAvbf7Nz0sxbkBXPLnVu1u9Zkq2bFAqBszRGlXQ+ZJkatwDU/FFdpdH2qn2DZQLcr27wokxWjz34ZGgNPJN02/A6Wo7FD6bruF2jiPVh0eplUF1277EY4vHCd1Z3Sh9zkg72XWNLlzTQYfrVQZUNzj9vlfAu5Dx7IdH/DIbxNr4T49WwOZwY1BTU7h/HjkHAFg9eVDIRoFri45h0/QbsGTboaByhCXjM1Fyrh4eQLqGwT2SmjXF4GLTzC+kfIS16EREREQUCYN18vNTBBGh5rjLpdmHTA1vSjFecnumXyD8zMQBUlo5ABz4sRprpmRj1U5rUPC9Zko27E7/z7VwTAYWbzkQcnZ44M61GPz6Bsrivz9wYy88v/1IUBp+obUMS7YdgjklCdf3MgQdS07xiapmNbkLFWCLxy4+USXNOQ+Vci/W8ifqQvcn0GtV6Jqow1NbD/p9PnFRo7LOjtU7rUGfPbA2Xh2QIh7uO7A53DhV1Sjt5MdFq5Gg02Df8UqMWVnk1yhQXHC4kCkGLXWh5SOsRSciIiKicFgcSUEuRz28S6lAlUdAjaDA3E0HcOuLhZj4x9249cVCzN18EA0KhWwtb7ga68KSMtic/mnpHeOj/F4vCJDqz33tspZj9c7vYIyNkh7LMxkxsHtS2LnfvjXdeSajFCQD/oGyw+3BzzI6hq2XH5SShN1Hy6V6bTGQlnPox2r89ta+yDP5fz+Btd2+wa5YH77x/hzERqmxbVYuRmR0wpO3Z+KGXvJN3cRrG92/Cxpd7pC11QvHZGDJtoNBn2+XtRzrd32P/t0Sw36Pg1KSACBoxzncd2AxGbC3KeNh2vq9SI6NwtPbDuGxTQf8sh18exyIaeiXE2vQiYiIiOhy4N8i6bJrUHgD9C1fncITW0M34lIAQQ2/mjPL21ddo/+f+1+TELqe2FoGhQJSw7hrUxJxqroh7PnE67GYDFg4NkMKkgH/QDk5Ngpna+xhj6XXqvDm56XIt3gb560tOiY1YvNlMRlwb04P3L/+C+RbemLD/TnSNZtTks53yTcZcaamUTr2yklmFJdW4t7X9uDuP32GsS8V4dntR3CiwuaXfi+npsGJjXtKsXR8luwCQf9uCSEXIgqtZaiJkBqubqrhdrkFv88b7jvwXZTISzPC4Q5dK+67sBIpTf1iXUijOiIiIiKiSJgGT5eVS3l+FFu+Jbj5maiwpAzVTg86qBR+afgxUeF/ROOj1X7p4bHR/jXokYL9WrvLr0Z6zZTssK/vlqTDminZKD5RhVNVjX6p1+Iue57JiAS9JmJTuJgoFV65LxuFJecwb1RfKBVKnK1pxLxR6VApFThebvNr2GZzuDHrjWKsnGTGG3tK/RqtWUwGTM3tif0/eNP+r0nUYdl7h0Km888blR7yuvRaFZJjozBnZF+cq7Pj8TEZcLo9OFXdCLVSgeITVThZGX5RI0arCvt8kt67o15tc2KqT/mAzeHG7DeKsXBMBubflo5GhwdOtwefHi2XvoNckwHLJmThXG34xRDx3l/IFIOWYg06EREREV1qDNbpsvLtlB0pcD5Z2YD4jjF+tbwupSJsh/p4jdKvKd7ZGjtyTefHtUVqzBZYMy2mYUea++2785tnMmDRuEwcK6vHG7/KQef4aJTX27115iG6l1tMBmw/eP5Yo7O6wC14kP/6FwBCN1oTg9kN9+cg39ITeq0aNoe3e/rMjeeb3703OzfsrrPD5ZH9nHqtCmumZOPJgAwIsTHcrKaAOdKihlajDPs9Rqm951EqFYhRqVBgScWvcnvB5nRLCxT/PHwGj9zSF7u+K8PIzE7o1yUeiToNuifpEO3xRAzCo9TKi5pi0FKsQSciIiKiS4nBOl1WvinIkQJnABc05koNSLuaDQ4Xnp7QHws370eRtTxs8J1nMqIoIJBeW3QMKyeZoQT8glWLyYD7c3vhq5NV2Hh/DjRqJfQaFSaar0FxaSXe338K/a9JQKXNCQFAl/hobCn+Aa9NyQ7qXi6mdIvjzXZZy7F020E8Prpfs74rm8ONSpsT09bvxdsPXS8F0GKNurl7IuoipH6fq7NjqiU16HMuHJOB1TutQYG+uPghNoYrPlHltyji23EfANweAXNGpgM4EvTZF4/LxLMfHMYnTR3ggfOLAY/+/Ssppf/RkX0x9fXPkdElHrdldYYpOQad4qPhtNkhIPyoQYvJgLO1do5CIyIiIqI2i8E6XVa+u5/enWaD7I6vmEaeoNNc0JgraVdTp0G1x42C3FQ8PqYf6hqd+Ln5GizeGhzsT7X0xMyNxX7nEneut83KRUW9A+X1DnRP0kOhEKBUKLG26Che/KQEgDdAXTQmAwNTkpCg10KhUODQqRqsLTqGQSmJeOW+wThbbZe6l4ebIV5oLQea1ij0TSnkoXblc00GCIK31vvbM7VYOcmM+e98jRUTB0ij2CLufKuUmPVGMd564Hrk13rr3BN0GqhVSjy+6YDse4qs5Zh3Wzr6dYmHXqPCLRmdIOAIikurZMfA/Sw9GfNGpaOszoHGph1zAFjxwWHs8AnUxWMrFAq8+cB1OFfrzUqY9OpnGNwjCcvHZyFa8EChABL0WpTZ7NI9D7WQs2R8JnQKQMVAnYiIiIjaKAbr1GKhRq/J8d39XFt0DJunW/CUz2g1ABienoxHbumDsjoH3B4BlW5BOqZ0rnon4qLV6Bqn9Z6r6Xxy11Jb50TB63ul3d7slCT8vxF9MHdUX1TanDDGaJEQpcbidw8FNagDgMEpSTheXo+pr+8F4A2et8y0YMnWg9JCg++c8sd8glvfsWG/++AIZg034avSKqzaYQ07QxzwNnUbnp6Me3N6YMOe45hi6QkPBP+Z4k07zo1Ol7Q7b05JxDMTB2Ctzyi2SOn8xSeqMCglEQIEvPF5KR67LQNuwYPahvA78icrG3DoVA3M3RNxpqYR80dlQKtW4OltwfXx/zxyDnaXBwObZqkDwIb7c4ICdVFhSRkWjslA9yQdEnUa3D6gS8S679ALOQLALHQiIiIiasMYrFOLNCi8DeO+LK3yS3vulqRDvEzQHrj7+cHBUxjTvwsKLKmwuzzQa1RIjNHimQ/906Xz0ox4enwWlr57UEqX1mtVWDS2HwaleNO8Y6PV2He0AkvfOywF3XlpRiy5PRN6rQo2h1u2od1Hj+RBBQELxmbA7vL47V5768/74d5XP5POWZCbCofLv/N4qPnvgfPY59+Wjhk394YHQsQygEaXG4/c0kf6Lj47WoGC3FQUWFLhcHvQJV4HnVaJU1WN6JwYjb3Hz0jnXDimH3ZZy/0WKMYN6IKntx0O+HxGLBybgUqbA7f264RX/v0dnhrbD1qPB1AogAh14D06xGDjZ8f9vtcN9+eErI8vspZjwZh+funx4dQ1urwjA1tQ981acSIiIiJqjxisU7OJnd2/DJH2nJdmxLLxmdAJ/sGS7+5nvd2FBL0Wi7d4G5jNHG5CcWllUNBbWFKGBZv3Y2BKEj45cs5/J/sf+6XX+e5k2xxuFJaU4YktB7BwTEZQOrcY7AsADp6th1qpRL6lJ6bmpkIQBFyTpENNgxP3vvoZbA43fjMiDbdldsHSbQeR2TXe71jm7okhO9vvspajoKnDeV2jC3aXgAJLKrol6cKmtndN1KHR4Za+C3GxQfzsz30UsKDh89lrG53Qa1V4+d5BOFXdALcg4PtyG+aOSsejggCn2wOHy9tV/Y7Vn8LmcEu18zaXG9qmRnvh6sDz0ow48ENVUGAeqet9nd2Faeu9WQqR0vN/is7tRERERERtAf9mTM0mdnafOdwku6sszkt/dkKm7A57kkqBJL0GVR4Prk1JQr4lFclxUSGD3iJruTTWq7k72YC3/nvubel+aeB6rQpr84fg5R0lUrCv16qwcEwG+ndLwMnKBlTWO9AtUYec1A64Y1A3VNTZsfd4BfItqeiSEO133kid7cXnxUDVYjLg8dHpsqntlqbmaj9UNMDmDE7LD/XZC63l8DQ9Hx+twYM39UK0Ron39p/ye+3yO7Lwwf5TQUG2+JonxvZDpVtAbaML8To1lk3IwoLNB/wCdovJgBnDTGhwuqWsBVGkjAG9zxi3sA3/fsLO7URERERErR2DdWo2sbN7uF3lwpKyoI7uIt/6cktvA3Z9Vx60Yx1IDHqbu5MtOlnZIDV2s7s8SO8cJ+3mA/4157478HlpRjw9IQvPfnAYv76lr1Rfv3WmxS/IjBSgRqmVfrPXd1nLcbrajtlvFEup7XaXx2+O+tr8IegQqw06VqTPPmOYCXqtCiMyOmHZ+4eDAuFO8dFhx7i53ALGvFQkPfbcnQMwOqsz8m/o6XeNBeu/gDkl0W9hBIgcgOs154N1sdu+eG7f17FzOxERERHReQzWr2ItaRQHnE9RjrSrXNvokmaki8eXqy/PNRkwKrNz2GP16KDHtlm5EUeRBV6TVqX0CyjfnWVpVs15YUkZFm4+gPwbemKpTyO8U9WN0i7/rggj4SwmA87UNPqNZwMAhUIRso4eAOrtLhRZy4KOG+n7VikV+PkfPsX6qUNlryfS+8ttDr8/G2KjUNA07z2Q3MKINO5OoZAdr6dRCFJqvdhtX1ywAHz7HTBQJyIiIiISMVi/SomN4goDdjflas5FYj1zpF3luGi17PED68v3lVZBpVT4zev2ZTEZ8MHB01i1w4qN9+eEPafvNfnuaIvqG/3TyyNlB8wd1dfv2tVKBWb5BJkuj4DbB3TF0m0H/b9DkxGLxvXDBwdO4WmfhQkAEAQh7GctPlGFtUXH8PK9gzCmfxd0io+G3eVBSgc9Zg43YW3RMel4vnPNBQDP3nktlEpFUIp64Hcjx+OzQKPXqvx2wuUEBv82hxtv7inF7yZkweZ0B4/XE+DXZFBcsBCD+WjBw9R3IiIiIqIADNavQmKjuMDU6HA154C37vzp8Vn49Lvg3V9RXpoRMRoV5m/aH7JGWkyjLshNxXPbjyDfkgoB/mnRuSYD5oxMx6SmruyfHi2PGOgC3qZrUwJ2tC0mA9QBafmRdpvrAoL74hNVMKf4B/hiwPzwMBM0KiVio1SI1qhwrNyGtI5xWHXvIOwrrZSCbJVCIftZLSYD7s/tha9OVmH1vYPQJTEaa4uOBi0CbJp+A05X21F8ohLXdkvEa0VHgxr8+S6G+F57qPuVazL4dWgvyE2FO8RijShBpwk6xqJx/RDl8SAqRFf20CPWuJtORERERCSHwfpVSGwUJydSzfnSdw+if/dELB6bGbyr3LRTanO5w9ZIi+nP4u6274gy3xrpynqHFHSKqdYKKIJGkS0a1w/HyuqxZko2uiRE484/7pbeJ3Y8L7KW4ZaMjkjvEg9z90TEaNVYmz/EL5j2FR/QlVyu1trmcOO/pZUYndUZD/7lS6yaPAjLtxwICrLfeOA6FJWcg06rwtTXv/D7rCkd9PjnkTMQIOCL7yvg8ggoLpLpjm8tw5Jth2BOScJXpZXISe2A4tKqoHsnCEJQTfnaomNYO2UIlEBQpkO+JRUqxfl7be6eiN1Hy0MvxpiMaHS6sWZKNuwuDxJ1GnRP0iG6GUE3R6wRERERETUfg/WrUG2E+m+x5jzocacHnxw5h0+OnMMr/z6KgtxU5PsE2L2MMYgWPDjb0Lz6cvGfoeq4V08eJP27WOu84f4c5FvONz5LjovCva9+hnuGpuCGXgbU29145+EbAAHwQMDp6kbMe+dr5KR2wKKx/fD4pv1+5wpMzQeaupJHq5FnMkjBrW+t9fRhJrgFAU6XB8UnqqBWKfDKfYPxu/cPB2crWMuA7cCMm3ujwWdBQKFQIDZKDbVKgayuCVhXdExayIjUSG/VDqvUBT7wtUXWckwfZvJ7fHBKEmKjVRjcswPyLanQa9WwOVxSY7vn77rW796EagJnMRnw5O2Z8Age1DRwd5yIiIiI6HJisH4VEhvF+dY9210eRGtU2FdaiXid/I+Fb5AvF2C/89D1iI3RRJyVLdZQRxz5pVFh5nCTdH06jQqx0WpU27xzvRUKBVRKBf7vroF4pfC7oCB8qiUVG/ccx6p7B6FbQjQe27Q/4ui3PJMRU27oiZ//4VOsuncQ4NM0zeZwo7i0EgO7J/oF98P6JEOvVYfNVnjopt64JkmHbbNyUe9wod7uRpRaCaVCgWiNSnpvc0fCyTV6E6lVSqzNH4JGp1ta0CirdeDFT0oAeGedi3PPASDRJ609Sq0MagLnm+3gETxIVCqQyN1xIiIiIqLLisH6VShOo8QtGR1xz9AUrNt1zC/IzTUZ8D+DuwEyu6WRgnDxebERnW9ncJFvffnZWnvI1w1PT0ZijBbFpZVB15dvScWjf/8KNocbeSYjFt/eD9+crvV7vxiEm1OS8PJOKxaOyQibmj9vVDrM3RPRIUaLya/tgc3hRsHrX2DRmAw8PjoDx8rq/cas+abN210enKurD/vdVDc48cd/fYfb+neWRsXNHG5CcWklJuf0kF7XnJFwvueV4/J4sM/ne/PNUAhsvpeXZkSPJB0+eiQPtY0udIjR+pUL+C7iHDlVg8mDr2GATkRERET0EwgfGVC7pPYIWDy2n+zosiJrORZsPgCXMrhmXQzC5eSlGRGnUUrHXzY+M+i14gzzn/VNxkeP5OHm3h1Cvu6Jsf3w/PYjste3ftcxvPnAdVg9eRCm5qbii2MVeP7OaxFol7Uc5u6JKCwpQ02E1PyTlQ2Ytn4vKnzq5G0ON5a+dxjRaiU27jmOaev3YtUOq1+gnmsyYPfRciTHRoU9fpRaiUJrGTrFR0uPmbsnYpe13C8AF5vByQkMtOUC+1yTAQ0ON8zdE/1eF6VWIs9kxFRLKtYWHQNwvseA1uPtUZASo0EsBCwa0w/FpZWYtn4vpm/Yh4LXv8B/SyuxaEy/sKP9iIiIiIjo0uHO+lWqwemWbSAGhG4yJwbh4ggukRj0+dYuh+7+LSBWfz6FWgfg2QmZqHF6cLKyAYA3YD1aZpPt/A54m6Tl19oxfcM+AN4gdun4LNmxZeLusz4q/DiyKLVSduRbQW4qnt9+BHNHpePhRheqG5zSTvPhH6sx+2d9MOnVz3Brv07IMxn9mt+JfI/ruxsu/rtvt/Zw9eK+c9vzTEacqWkMOo/YMM7mPN9g72xNIzKvScCCMRlQKoG/FAwNWW/uUiqwUKZcoMhajoVbDoScFEBERERERJfWFQ3WKyoqcPfdd+Ppp59GTo53jvZXX32Fp59+GlarFUlJSXj44Ydx1113Se/ZtGkTVq9ejXPnzqFXr15YtGgRzGZvcON2u/H8889jy5YtaGhowHXXXYennnoKHTt2vCKfrzW70CZzLRnBFar7t0up8Ht/jFKJ5z48gk+OnJPe65u6Lcc36N1lLcfiLQdlG66Ju896jSpsav6ZmkYpGPat5Y+JUmNUZmd8fbLKb256nsmI347sixqbEzaHG6eqG/HbkX0BwC9gDwyyo33q8JPjvLvxgQG6WC8+82bvSDiHy4NPj5ZL6fd5JiOm5vbE/h+qpa7svin6z991rbT4MPPmNDQ63bjnT5/htV9mIzUpOmw39pZOCgi8l+KCDBERERERXZwrFqx/+eWXmD9/PkpLS6XHqqur8cADD2D27Nm4++678cUXX2DGjBno27cvBgwYgD179mDp0qV49dVXMWDAAGzYsAEPP/wwdu7cCZ1Ohz/84Q/YtWsX3nnnHcTFxWHRokVYuHAh/vSnP12pj9lqNbf+XM7FjOBqUATPeM9L8zZ1+/RohRQMt6R2G/AGyPmWnn6PiTvaeWlG6JSQzwowGbFkfCbO1TVi+gZvQL1ykjmolj+wa3yhtQweCHj0Vm+AHqVSYpf1HJZOyMSPVY2oanAG1bhbTAYYY8/X4c8cbsLw9GT065oApUKBB2/sjcduy4DT7YHd6cY1iTrsK61E/2sSMSqzM25MS0ZctBpalRLjVhUFZRGIEnUaJMdHYd6odOz85ixe+fdRmFMS8enRchgHdJEdyydqySJOqHu5bHwmdBFmtRMRERERUXhXJFjftGkTVq5ciTlz5uA3v/mN9PhHH32ExMRETJ48GQBw/fXXY9y4cdiwYQMGDBiAv//97xgzZgwGDx4MAMjPz8dbb72F999/HxMnTsTf//53PProo+jSpQsAYMGCBcjNzcWJEyfQvXv3n/6DtmLhmsBJ9eeXeIfUpfQP7nx3sAHgL9NysPObs1hbdMwvNTyQXLo6ADjcHswcbkJ2ShI6xGqhUSlRWe/AuAFdIACIUgBLx2ei0eXBDz4p92NeKsLglCSsmmTGZ8cqgmr59VoVzClJ0GlU+OMvBsPlEaT57FqVEnqtCokxWuz+rhwv7/wOKyeZsWHPcb9j5JkMeGx0Bp7/6Bvp8Tc/L8WG+6/Dkm0Hg5roPT2hP+ocTgzolohl7x3CPTk9pOuaOdwEc0qi7HeTazIgSa/F+FW7gmbNz36jGDf3SZbNmBA1dxEn8F6KCkvKsGDLQayY4K2FJyIiIiKiC3NFgvXc3FyMGzcOarXaL1gvKSlBnz59/F5rMpnw9ttvAwCsVismTpwY9PyRI0dQW1uL06dP+73faDQiISEB33zzTchgXaHw/+fVQiMIWD4+E4/L1Z9PyIJG8ACX+DvxTbHWa1Vhd7Dnv/M1VkwcACB87bavVGMM3tl7AgO7J+KZD/2b0+WlGTFjWG/s+b4CXxyrCKqH96auC3hsdD9pxFlzrrPR6cbCMRl4zqcZnu/YMwC4JkkHCN6fsR0+qf73DE3Bkm0HZevDF205gBk398bTO47AnJLkt4AQqq49z2TE0juy8NGhU3hpkjkoPd7mcCM2Wh32Z705izgKQYiYLn+8sgHdE6Ohw6Vb8Llaf1fbM97T9of3tH3ifW1/eE/bJ97X9ueKBOvJycmyj9fX10On0/k9Fh0dDZvNFvH5+nrv6Cy9Xh/0vPhcoA4dYqBSedOpDYa4ln+Qn1i1zYGyOgdqGp2I12lgjNEiQa+9qGOummRGWZ0DtY1OxEVrYIyVP+alOPeJ0krp3wtyU2W70Yt/vmdoCma/UYyFYzLwm1v64FydHT06xOCrE5VBo9MA7871vuOVSO+aIHvcwpIyeAQB80al44WPSyCn0FqOGQ1Ov8ciXefS8VkYlJIkjWMDgmfQb7w/B10SolFW5/A7hrl7YlCNve/1zh3VV5qn7vu6wDnoMVFq1NtdKD5Rhae3HcLP0jv6zVEXWUwGRKtVMBpjAMjfU6Nei2cmDsD8d77Gf3wC9hvTjHhm4gB0SfT+/vneSzlVDU788d/f4aVJ5ov+GQ3UFn5XqWV4T9sf3tP2ife1/eE9bZ94X9uPVtUNXqfTobbWf152Y2MjYmJipOcbGxuDnk9KSpKC+IaGhpDvD1RRUQ+l0vsDXV5ei9ZcZtsABR7fHFwfvHx85kXvXiYogQS9GoAAp82OMpv9spw7Rnu+I3u4QFUMUM0piegYH41frv0cBbmp+PveE7g3p0dQCniuyYCnxmdh7EtFeGmSOexx1UoFXs8fggS9BuqmNHlBEODyCFApFEFp4IHX6Zu6b3d5mv7nlu1EL6q1uxBrdyE2Wo3VkwdJ3eRdYcoM9FoV1Aol1uYPQWyUGttm5cLp9qCmwYUvjldgbdExvznqYmd8APh/I/oGlRCIGQkV9XbEwBPxnj4j00RQ43KhrMz7++l7L+VEqZX4T0kZztQ0whnw83ShFIq28btKzcd72v7wnrZPvK/tD+9p+8T72nYYjc1bUGlVwXqfPn2wa9cuv8esVivS0tIAAGlpaSgpKQl6/sYbb0RCQgI6deoEq9UqpcKfO3cOVVVVQan1vsQfZEFAq/2hdikVeDxEffDjWw5e1nFal/LcvinWvt3c5cRGqWFOSZJ20a/vZcCqHVZ8drRC2lH2TfO2OVywOdwRj3u2xg6XIPjVjgPeFPKFYzNgc7ix/I4sqfO73eWRAvTslCR0SYzG09sO+QXweWlGv+ZzvvRaFVINMVi67aDfd2gxGXD7gK6yQb6Yer/8/UNB75lqScWhH6v9zhfYbO90TQPmjUpHWZ0DjU63Xyr85uk3wKlo3j0NbCLoe5fDpcv79hQINVXgYrTm31W6MLyn7Q/vafvE+9r+8J62T7yv7UerCtZHjBiB5557Dq+//jomT56ML7/8Eu+++y5Wr14NALjzzjsxY8YM3HbbbRg8eDA2bNiA8vJyjBgxAgDw85//HH/4wx/Qv39/JCUlYfny5Rg6dChSUlKu5Me6aC0dp9Vaz632CFg2IQsLNh+I2O1dpVTA3D0Rz991Lbp30KGy3pueHphiLso1GQFE7iLfIVYbVM8OeGvWl2w7BHNKEr4qrcKaKdmYtn4v9JrzNesAUFxUKZtiDwF464Hrsf3Qabz5eSnuGZoijWcLDNQB7y7/0m0HsWhMBh7zSaEHIqfeizXsBbmpKC6tDGq2JwjAMx96a90DFxXiNMpLck/VHkG2u35gT4FIDeuIiIiIiEhe+MjmJ5aUlIS1a9fiww8/RE5ODhYuXIiFCxfiuuuuA+DtDr948WI8+eSTGDp0KN577z28+uqrSExMBADMmDEDN910EyZPnoybbroJdrsdL7744pX7QJdIc8ZptYVzNygUeOaDw5gzsi96GmKQ1xRgB8pLM6K6wYlZbxRjw57j2H7wTNiUcQDQqBTIbdrRtZgMsq+xmAxwuDyyXdQBbzBs7p6IQmsZVu+04s0HrkMPg14KnM3d5TuwA95g/2xtI4pLK7Hh/utw6MdqTFu/F+dq7aEDY2s5BnRLDLreG3rJd8H3vcZd1nJc38sbGK8tOub3GYtPVEmvE3lT3LOg9giX7J7qBAErJmRh4/05WD15ENZMyfbLhpCmChARERERUYtd8W2vb775xu/P/fv3x5tvvhny9ePHj8f48eNln9NoNHj00Ufx6KOPXtJrvNIuZiZ6azm3S6nAkne9I8ie+/AIviytwspJZnggBNVWT7mhJzbsOY61+UOgVAD5676AeVIick2GoC7ugLdm3e0R8MS4TPy3tBK3D+gatJstznI/Vxe+flpMoy+0liO/1g61UiFdX6QUe3vTQsCzHx7G5JwemJzTA3qtGmvzh0ij3gJT3ksrbTCnJPml9UfKWhKvQwH4pd4H7mrH6zR456HrpZpzddMotUv586T1eNAtMRp/+Pd3wVMFxmdJ5yQiIiIiopa54sE6RXalZqLXOj0Qms5xseeudXqQ3jUBG/ccx7UpSci3pMLlETB/VAbsLre3I3m0Bv/69pwUgDrdAp6ZkIXN02+AWxCQb0mFgOBRbvmWVMRFq1Blc2DrVz/iyXcPoSA3FflNo9M6x0dDH6XCmJXeBnTh+KbRx0Sp/XaZI6XYR6m9M9cn5fTA67uOBdWby9W1a1XKoLT+NVOyw56nW5IOa/OHwBCrxZop2VAoFLA53NhXWikF6jOHmxDX1CU+0KX+edIJAp6VaUjHQJ2IiIiI6MIxWG8DQtUHX67dywaFAguaGpCJzc4EQfDb1W7puWsbXchOScLA7omyM8unWlJR1+jye7ywpAx1TjeSVAqU1rv8xpUFzhDf+KscvPTPEukaA2u1V0zIwuAeSVKavFyauW9jNABBgW6494op/Q/c2CtsvXlB7vkxbIHn8z1Pnskgmz5vMRnw0aEzWLXDijyTAVMsqdi45zj6dU3Aqh3WkHPh89KMWDY+EzpBuCw/T3IN6YiIiIiI6MIxWG8jfqrdS5fyfKAO+M/0nj7MhCi18oLOHRethlKpCOrCDpwPZOeM7Bv0PrGbeGy0OmRzOQDQKJVhm6bVO91YNj4TS947jKlNO+7FpVXSGDYA6BQfjU8On4Feq4I5JVEKpMUAfW3RMaxs2pkPSt239MQbe47j0ZHpePET+Tnu4kg64HxavrgT7mtt0TFsmWHBkncPodAaunlbobUcHngbzomfIVRzusKSMizw6fTO3XAiIiIiotaNwXob8lPsXsp1CheD5FU7rPjokTxvp/AWnjtOo4TTLYRtnLZgjCpolFlctBoNCgX2Ha8IvaudZkSDU37GuaiqwYlOcVH4WXpHaJRKPDG2H7QqJZ7YciBol3/NlGw0Oj2YsdE7u9w3QJ/9RjFemmTG9GEmVDc4/Xb3bQ43JuX0CP89RKux8Vc5aHC4sWHPcdnZ7INTkvBDZQMG90zCwzf3hlqpRG2j0+88vt9bgSUVMVFqrJmSja6JupALGoGd3rkbTkRERETUejFYJz/N6RR+IXOz1R4hYkBdWe/wSxPPSzMiVqPCvE37pYZ0gP+udl6aETOGmaCIMD1OpVSgxu7CY5sOYOZwE3JNBry0wyq7y68EMLhnByko9k2/12vViI1WYdxLu1r4DXhFqVX4z+Ez0i69PaA7vbhLP33jPphTEpF1TQKcbice/uu+kMf0NpxzYdr6vRHr3S/H3HMiIiIiIrr0GKyTxKVUICZKjdWTByFao8LXJ6ugUABZXRNgd3kQrVHBEKOFSwmZ9OnIu7LxEbqM210eKZ3bYjJgxs0m2D0Cviyt8kvH961Z75IQjTv/uBtvPnAdhqcno1/XBJi7J0rXu6+0Eod+rEZslBonKxsAAObuiYiJUocZw1aOX9/SB/2vSfA7zrx3vsa6/KEQBEH6jgK7vIerN881GRAfrUZ2ShJWOax+n8fh9iDVEAONSgnruTq8NMks7aRHaoqXoNNg91H5zxKIc8+JiIiIiNoG/s2dAPg3lRPlmYyYfnNvTFu/FzaHG3qtCmvzh+DlHSVBY9HE5mXhhOtCbjEZsK+0EpbeRqyZko3iE1UoeP0LDE5JlHbb5WrWV08eBJvDjbO1dswblYEl2w76vSbXZMCisZmobXRIj9ldHtQ1ht/lr25wYtr6vdKfh6cn480HrsNTWw+G7fK+tugY3puVi0VbDvg15Ms1GfDEuEw8v/0I7r+xN/RalVQvLy4IONweqJQK/Oat/8LmcMMYq8VLk8zokqCTur7vK63Em5+X4p6hKdLCRocYLdRKBfRaFYpPVOGWjI5I7xIftGhx5FTNZZkcQERERERElx6DdQpqKicqtJbBA0EKlgtyU/HSjpKIzctCUXsELBmfiYWbDwSlfouN00Zmdsau78qk3epCa7k0gk2OOE6tY1wUlmw7GHRtRdZyLNl2EE/enol/fVsGi8mAKLUS8bqW/ej365qAxVuDjx/Y5d2ckohGlxsDU5IwNaBr/YoPDqNf1wRo1Qr5ju0mI2YMN+HBm3rhL7uPY8P91wV9puHpydLjgbX2KyeZ8dTWg/jLtBws2Lw/aNFi2YT+bCBHRERERNRGMFgn2aZyIt8O5ubuic1uXhaKTgGMHdBVdvyaOSUR2w+eRnFppexM8kB5aUapY7sjoPY78DO4XAI0KgUWj83El8crkGqIQa7JgKKm8XS+u9yJeg0amjIJxPOH++zidyQuOpRWNIR87eScHgAU8h3bmxZHFozOQFbXBNnFh34hHhf//Nxd12LR5v2yixYLtxyIuKBCREREREStg/JKXwBdeZGaynkbmJ3/54UeBwBUHgGW3gas23UM0zfsw7T1e6Ud6amWVKwt8gax63YdQ0Gud5GgY3wULCaD33Hy0oxYMj4Th36sBgCcq7OHvza7C58fq8CE1btwts6O6gYHFo3NxM/Sk7FykhnFpZWYtn4vpm/Yh3tf3YO1u7wN4PRaVbM+e0yUGuaUJMx+oxhqZegFC7vLAwgIu7AgAOgcHy37GnP3xLDvTdBpwo6wq3VyZ52IiIiIqC3gzjpFbDomppqL/7zQ44jsTWni825Lx4mKhqDxZ4D/bvU/D5+FOSUJBZZUxOs0SGhqalfv9uDenB6wuzzQqpSydeBiAzin+/zO+wsfl6D/NYn41V++xNr8IXjuwyMR09sjffZ6uwurdlj9dvvldE3QwRahK77N7oYnRP1/5AUTZ4Tn2Q2eiIiIiKgt4M46SY3f5OSZvI+LzcsCd7il16UZvc3LmqGmwRvYnqho8Ntdl0t5XzwuEwoFsLboGF7/9Ht0i9MiSaWA2iMgRqXEm5+XwpyShE7xUVg7Jdtvh7zg9S9QXFqJtflDsPd4hd9x95VWom/nOJyrtYctATB3T5R218XvIpDFZEDxiaqmZnb9cLhpt1/udYdP1yBGG35RIyZKDX2USva5yAsm4QNxdoMnIiIiImobGKxfxVxKBSrdAk7XObBkfGZQwC7O/N6w5zhWTjLjzc9LMWt4WtDr8tKMWD4+q9m10GLAGCnw7BgfhXtf/QxfnajCOw9djwVjMvBjrQOVbgEupTdgf2JMBr46UYVPDp/Fyzvl56a/vNOKwI3qNz8vxZyR6RGv1eURsHKSGRv2HMcUS8/gdHyTEYvHZeKW9I6YOyodq3eWYMGYfsgLeJ1Yz7502yF8daIy7OLImZoG1NtdyJVZGBEXBeTkmgyI06pCH7sFCypERERERHRlKQQhwrytduzcuVooFIDRGIeystqggK49a1AosGDz+Q7weq0Ki8b2w4BrElBaaYNW5U1NF7uy56UZseT2TOiUgIDmz1l3KRVBr1UAmLP5IK7tnoji0krZGmyLyYAx/bugS4IOAgSsKfJvyCaOi9MqgGqnBy6PgDEri0J+3jVTsqVRbHqtCi/fOwjnahuRdU0iRq8sDPm+f/6/m/DkVu/3FJhmn6DToNHpxqw3ivHWg9fhx6pGdEmIhlathMPlwblau18TPfG71GtVeG92Lp7YctBvjF1emhEzbzZhxsZ9+L+7BqJrUjSe3HrQbwTcz9KT8cS4TCzYtD9oNNyyO/pD7/F4763MsZePz0K00HZr1q/W39X2jPe0/eE9bZ94X9sf3tP2ife17UhOjmvW65gTexWSG9Vmc7jx2D/2w2IywJySFNTNvLCkDE63B7HwNk9LUinO1z6HCNR9Z7eLge4NvQzQqpVY2LQjPjglCUogaHa5OMpt4ZgMvL//VMhxcaOzOuOxTQewevKgZn/+B2/qhWiNElu++hGllQ2wmAyyCwa5JgMqbQ7p2uTmvK+Zkg2bwy2l9APAH34xCIIA6c+BbA43quodWDgmAycrG6T6egUExER5Z9k3Ot1QKxRYfkd/1DvcqG10Ii5ag3itClqPB8/c0R+1DjdqGp2Ij9YgrulxANAJAp6dkCmzoNJ2A3UiIiIioqsNg/WrUHNHtQW9rxnNycSddAHA09sOSoG67FzxNCMWj+uHxeMzcbzMFjTKzeZwo1N8tN8Osq/CkjLk39ATQOSU+m5JOuSlGVFYUoab+3bEM01N5YpLq7Bykln67NK1mYxYNK4fTlbYwh5XbPjme36tKvhagprfadXQqpQ48GM1Xvn3Udl6/Y8eyUMSFNCpFTDGar0PNgXcWo8HBrUChoDHRWqP0KwFFSIiIiIiap0YrF+FmjuqLVCk5mS+O+lrpmRLCwIFuanyc8VLyvDUu4ewYEyGlKLe3GsJfF5sfhcqpT5KrcSzEzJR4/TA5Rak19kcbsx+oxgFuanS7PceHfRwCwLuffUzrJs6JOz5o9RK5DY1mBOdrWkEFArpekItVlhMBsy82YQB1yRixsZ9fgG7VF/OIJuIiIiI6KrEYP0q1NxRbb4iBY+BqfW+Qba5e2JQ+rhIrKvWa1Wyu8uRdszF59cWHZPdIRdT6ivrHeim16CDSoHvG/wXKwLT21dPHoRojQpldQ788/BZ5JmMKLSWIZDFZMDZWjseH52BszV2rJ48CFFqJeKiVVBAgZk3m7yfPyVJdrFC/PPY/l2kEXGAb8M+pq0TEREREV2tGKxfhcRRbb4NyER5aUacrbUHPRYpeAxMrfcNsiPtjv9Q2SA1gAsM2M/UNCLPZJBN27f47GgH7pDHRKlRb3dJKfWbp98gvS9eF3mxorFpFvqf/nMUq+41Awr4N2wzGfHk+Ex8+X0F7vzjbr/rXjMlG7PeKMaDN/XCvFHpUCuVIRcrxLIDc0oSbu6TzPpyIiIiIiICwGD9quNSKlDn8uDJcZl48l35juEahYCPHslrUXOywNR637T0SLvjALB653dYOCYDj286cP56TAbc0NuAXJPR27k+4Fpn3GxCwetfSI+JO+SBTfICswLiwyxWiAsA5u6J0jFnbizGmw9ch/wbevrV1Z8ot2HuO/uDjmF3eWBzuPHCxyV44eOSiM3v7C4P6u0upLC+nIiIiIiImjBYb+XkRp81d555ILnu7A/f1BtatRLxvkG50Lxu777iotV+TdQcbg9GZXbG1yersP+H6rD15MUnqlBoLcOvb0nDminZfgGxmL4u193cJQCDeyT5Bd25JgPymzrJA/5ZAeJ3WW9zYun4LCzc7D/+TEyZf/PzUlyTqJMetzncOPhjDd7ff8rvXKGC8MDFieak8kcqTSAiIiIioqsL56y34nmEgbPQgfPzxXUtvFiXUoG5AePafI/57ITMC14EAAC3UoHvq+14aUdJQFd1A568PROAImgn32IyYO7IdFTWO2BzutE9SYfth85I88iBpo7oKkXYz+UbxMdoVLC53Ki3e+eZi4sbgd+lMVaLv0zLQWW9A1UNTmlx4MipGiwe0w8ahYAan+PGa5RwCPCbX+47u93XzOEmv/nxM4eb8FVpZchU/rEDumJY7w4X9f1fDVrz7ypdGN7T9of3tH3ifW1/eE/bJ97XtqO5c9YZrLfSH+pLHVxXugXc+mJhyOcjBcWRRLre5yZkosEDHC2rl+aKG2O1ePGTb7HjyDnptb4z1gf3SLqgRYTAexrq2vRaFRaN7YdBKYmoC5O5ELggoFEpUWVzIFGvxRNbDwal0+u13lnpL++0orCkDHqtCqvuNWNd0fd+jeosJgNmDU9Dt/hoRAmsUY+ktf6u0oXjPW1/eE/bJ97X9of3tH3ifW07mhusM/e2lQo3C72wpAy1Tk+LguvaRlfwrG+NCvtKK7G26FizZqhfzPXWOD2I0aiwbtcxFFnLg3afRbus5VBCgTcfuE5KH3crFX673C0tBQh1bTaHG4/9Yz8+eiQvZL24b+mAyDe7Ydn4TL/ddsCbmt8tPtovdT9ep8aKO7JQ63SjtsEFfZQKeo0KOiWgYjM5IiIiIiIKwGC9lYo0C72lwXW8Th1y1vfKSeaIHdIjadb1qhRYNqE/FmzeH36cm7UM+bU9MW39Xm8juWG9UeDTKb6lpQAX+l0GjqOTrq+kDAu2HMSzEzKh8wiy9fTytf8eGFQKGGLFcwkA43QiIiIiIpLBYL2VitRwrKUNyfRqVchZ3woAz9zRH7iIHd7mXq9e8OCZO/rjxxp72NeL494KS8rgEQS/OeS+wXJzdtgDry0wwyAmSg23UgEB8E93hwJfllbJHtM3u0HtEVrckI+IiIiIiCgcBuutVKRZ6L6jyJqj3umW7cYOAEXWctQ73dBeRM16S65X6/EgoRmzzkXiLHJfLSkF8L02vVYVlGEg1ZjvKAlKd185yYzZbxQHzX8HWp7dQERERERE1FyRB2DTFaH2eOuh89KMfo+fH0XWst3b5qSCX4yWXq8YQMsRx7n5EnfaL+Safa+tIDc1KMOgIDcVLwUE6oB3QWDdrmMoyE0NPKT3M3DcGhERERERXSaMNloxnRCmHrqFLnVavZyWXK8YQAc2Z/PtBu9LblZ5S65ZvLZqhyeoVj5c/bzcrj5wYdkNREREREREzcVgvZW7VPXQlzqtPhTf6w0ceSZ2cXc1dXeva3TiqXGZcHg8qG90we7y4NOj5UFp5xaTAQd+rMbM4SapzjxJr0GMRtWiOnu1R0C9PXg3Xm7XPpzz2QLsDkdERERERJcHg/WrRKid7MsVeMqNPLsloyMWjemHhZv2+9eGm4yYOdwEu8uD4tJKv0A912TAU+OzcKLChlcLj/rtgLe0Kzwgvxsvt2vvq1uSDh89knfR2Q1ERERERETNxWD9KnIp0+rDCTXyLL1LPB7fvD+o0V2htQweCBjSswPMKUkosKTC4fagS7wOOq0SDXY31hQeDX5fC7vCA/IZBsUnqmAxGWQb8OWlGRHflBHAbu9ERERERPRTYYO5q4yYpp4So5HGjl1qtU5PUKAOeGvDQ3Wk32UtR/9rErBqhxWz3iiGRqXEcx8dwcgXC3GmtlH2eMD5rvDNJdcIb23RMcwannbJmvkRERERERFdLO6s0yUXqkt7pNpw8fnAju2R3tfSEWpyGQbxGuVPknVARERERETUHNxZp0suVJf2SLXh4vOBO/CR3nchnewDMwxUHuEnyTogIiIiIiJqDgbrdMmFmqFefKIKuSaD7Ht8Z6sH7qSLNeVypE72RERERERE7QijHLrk5OrCAeDIqRosm9A/uDbcZMSsm9OwtugYgOCd9LVFxzDVkhoUsLOmnIiIiIiI2ivWrNNlEa7z/LMTMlHj9KCm0QW9VoUYrQoQgJcmmWF3eZAcF4U8k0FqKmdzuDH7jWIU5KZixjATotRK1pQTEREREVG7xmCdLhuxBjxw5JnaI6CDSoEO4uOCAJdSgdc//R6FJWXQa1VYOckMDyDVrtscbnx1ogp3D+qGaMHjdzwiIiIiIqL2hsE6tQpi6vyCLQdRWFLmt5OuVSsRz510IiIiIiK6ijBYp1YjdOp80w46d9KJiIiIiOgqwWCdLphLqQgdWF+gUKnzREREREREVxMG63RBGhQKLNh0QGoCB3i7sy8bnwmdwACbiIiIiIjoYnB0G7WYS6nAgs3+gToAFJaUYcGWg3ApFVfoyoiIiIiIiNoHBuvUYrVOT1CgLiosKUOtk03giIiIiIiILgaD9VbOpVSg0i2gtN6JSrfQKnataxtdF/U8ERERERERhcea9VastdaFx0WH/7GJ9DwRERERERGFx531Vqo114XHaZTISzPKPpeXZkSchj9WREREREREF4NRVSvVmuvC1R4By8ZnBgXseWlGLB+fddHj24iIiIiIiK52zFdupZpTFy7NIr8CdIKAZydkysxZZ3M5IiIiIiKii8VgvZW6knXhLqVCJggP3i1XewQkqRTnFw24o05ERERERHRJMFhvpcS68MKSsqDnpLrwyxAct9amdkRERERERFcT1qy3UleiLrw1N7UjIiIiIiK6mnBnvRX7qevCm9PULknFgJ2IiIiIiOhyY7Deyv2UdeGtvakdERERERHR1YJp8CS5kk3tiIiIiIiI6DwG6yQRm9rJkZraERERERER0WXH6IskV6KpHREREREREQVjXjP5+amb2hEREREREVEwBusU5KdsakdERERERETBmAZPRERERERE1MowWG+DXEoFKt0CSuudqHQLcCk5+5yIiIiIiKg9YRp8G9OgUGDBpgMotJZLj+WlGbFsfCZ0AtPViYiIiIiI2gPurLchLqUCCzb7B+oAUFhShgVbDnKHnYiIiIiIqJ1gsN6G1Do9QYG6qLCkDLVOdmwnIiIiIiJqDxistyG1ja6Lep6IiIiIiIjaBgbrbUhcdPgWA5GeJyIiIiIioraBwXobEqdRIi/NKPtcXpoRcRreTiIiIiIiovaA0V0bovYIWDY+Myhgz0szYvn4LKg97AZPRERERETUHjBvuo3RCQKenZCJWqcHtY0uxEWrEadRQu1hczkiIiIiIqL2gsF6G6T2CEhSKZAUo/E+wB11IiIiIiKidoVp8EREREREREStDIN1IiIiIiIiolaGwToRERERERFRK8NgnYiIiIiIiKiVYbBORERERERE1MowWCciIiIiIiJqZRisExEREREREbUyDNaJiIiIiIiIWhkG60REREREREStDIN1IiIiIiIiolaGwToRERERERFRK8NgnYiIiIiIiKiVYbBORERERERE1MowWCciIiIiIiJqZRisExEREREREbUyDNaJiIiIiIiIWhkG60REREREREStDIN1IiIiIiIiolaGwToRERERERFRK8NgnYiIiIiIiKiVYbBORERERERE1MowWCciIiIiIiJqZRSCIAhX+iKIiIiIiIiI6DzurBMRERERERG1MgzWiYiIiIiIiFoZButERERERERErQyDdSIiIiIiIqJW5qoN1svLyzF9+nRkZ2cjJycHy5Ytg8vlutKXddWqqKjAiBEjsGfPHumxr776CnfddRfMZjOGDx+Ov//9737v2bRpE0aMGIGBAwfi5z//OYqLi6Xn3G43nnnmGdxwww0wm814+OGHcfbsWen5SPc/0rkpvCNHjmDq1KkYOnQoLBYL5s6di4qKCgC8r23V7t27cdddd2HQoEGwWCxYunQpGhsbAfCetnVutxv33Xcf5s+fLz3Ge9p2vf/+++jXrx/MZrP0vzlz5gDgfW2rqqqqMHfuXOTk5GDIkCGYPn269N3znrZNW7du9fsdNZvNyMrKQlZWFgDeV/IhXKV+8YtfCL/97W8Fm80mlJaWCmPGjBFeffXVK31ZV6W9e/cKt9xyi9CnTx/hs88+EwRBEKqqqoShQ4cKf/3rXwWn0yl8+umngtlsFr766itBEAThs88+E8xms7B3717B4XAI69atE3JycgSbzSYIgiC89NJLwrhx44Qff/xRqK2tFR555BHhV7/6lXTOcPc/0rkpvIaGBsFisQi///3vBbvdLlRUVAi/+tWvhAcffJD3tY0qLy8X+vfvL7zzzjuC2+0Wzpw5I4wdO1b4/e9/z3vaDrz44otCenq6MG/ePEEQ+N/ftm7FihXC/Pnzgx7nfW27fvGLXwgzZswQqqurhdraWmHmzJnCAw88wHvajpw+fVqwWCzC5s2beV/Jz1UZrH///fdCnz59hNOnT0uPvffee8KwYcOu4FVdnf7xj38Iw4YNE9577z2/YP1vf/ubcOutt/q99oknnhDmzp0rCIIg/Pa3vxUWLlzo9/yoUaOEt99+WxAEQbjxxhuFrVu3Ss+dO3dO6Nu3r1BaWhrx/kc6N4X33XffCdOmTRNcLpf02CeffCIMGjSI97UNq62tFQRBEDwej/DNN98II0aMEP7yl7/wnrZxn376qTB69Ghh9uzZUrDOe9q2TZ48WfjrX/8a9Djva9u0f/9+oX///tJ/gwVBECorK4Vvv/2W97Sd8Hg8wn333ScsWLBAEAT+rpK/qzINvqSkBImJiejUqZP0WO/evfHjjz+ipqbmCl7Z1Sc3Nxcff/wxRo8e7fd4SUkJ+vTp4/eYyWTCkSNHAABWqzXk87W1tTh9+rTf80ajEQkJCfjmm28i3v9I56bwevXqhddeew0qlUp6bPv27cjMzOR9bcNiY2MBADfddBPGjRuH5ORk/PznP+c9bcPKy8uxYMEC/O///i90Op30OO9p2+XxeHDw4EH861//ws0334wbb7wRixYtQnV1Ne9rG/X111/DZDLhb3/7G0aMGIHc3Fw888wzSE5O5j1tJ7Zs2QKr1SqVIvG+kq+rMlivr6/3+4sJAOnPNpvtSlzSVSs5ORlqtTrocbl7FB0dLd2fcM/X19cDAPR6fdDz9fX1Ee9/pHNT8wmCgBdeeAE7d+7EggULeF/bgY8++gj/+c9/oFQqMXv2bN7TNsrj8WDOnDmYOnUq0tPT/Z7jPW27Kioq0K9fP4wcORLvv/8+3nzzTXz//feYM2cO72sbVV1djW+++Qbff/89Nm3ahM2bN+PMmTOYN28e72k74PF48Ic//AEPPfSQtCjO+0q+rspgXa/Xo6Ghwe8x8c8xMTFX4pIogE6nk5pXiRobG6X7E+558T8ygfdYfD7S/Y90bmqeuro6zJ49G++++y7++te/om/fvryv7UB0dDQ6deqEOXPmoLCwkPe0jXrllVeg1Wpx3333BT3He9p2GY1GbNiwAXfeeSd0Oh26du2KOXPm4D//+Q8EQeB9bYO0Wi0AYMGCBYiNjYXRaMQjjzyCf//737yn7cCePXtw9uxZ3HnnndJj/G8w+boqg/W0tDRUVVWhrKxMeuy7775D586dERcXdwWvjER9+vRBSUmJ32NWqxVpaWkAvPcw1PMJCQno1KkTrFar9Ny5c+dQVVWFPn36RLz/kc5NkZWWlmLixImoq6vD22+/jb59+wLgfW2r9u3bh1GjRsHhcEiPORwOaDQamEwm3tM2aMuWLfj888+RnZ2N7OxsbNu2Ddu2bUN2djZ/T9uwI0eO4Pnnn4cgCNJjDocDSqUSAwYM4H1tg0wmEzweD5xOp/SYx+MBAGRkZPCetnHbt2/HiBEj/HbC+d9g8nNlS+avnEmTJgm/+c1vhNraWqkT4sqVK6/0ZV3VfBvMVVRUCNnZ2cK6desEh8Mh7N69WzCbzcLu3bsFQRCk7pS7d++WOmEOGTJEqKysFARBEF544QVh7NixQmlpqdQJ8xe/+IV0rnD3P9K5Kbyqqiph2LBhwvz58wW32+33HO9r21RXVyfcdNNNwvLlywW73S6cPHlSuPPOO4XFixfznrYT8+bNkxrM8Z62XadOnRIGDhwo/OlPfxKcTqfwww8/CP/zP/8jPP7447yvbZTD4RBGjBghzJo1S6irqxPKy8uFX/7yl8KMGTN4T9uBsWPHCn/729/8HuN9JV9XbbB+7tw5YdasWcLQoUOF6667TlixYoVf92r66fkG64IgCF9//bVw9913C2azWfjZz34mvPPOO36v37x5szBy5Ehh4MCBwp133in897//lZ5zOBzCc889J+Tl5QmDBg0SHn74YaGsrEx6PtL9j3RuCm3t2rVCnz59hGuvvVYYOHCg3/8Egfe1rSopKRGmTp0qZGdnCzfffLPwf//3f4LdbhcEgfe0PfAN1gWB97Qt27Nnj/T9XXfddcLSpUuFxsZGQRB4X9uq06dPC4888ohgsViE7OxsYe7cuUJ1dbUgCLynbd3AgQOFf/3rX0GP876SSCEIPrlSRERERERERHTFXZU160REREREREStGYN1IiIiIiIiolaGwToRERERERFRK8NgnYiIiIiIiKiVYbBORERERERE1MowWCciIiIiIiJqZRisExEREREREbUyDNaJiIjagerqajz55JO46aabMHDgQOTm5mLevHk4ffp0xPeePHkSffv2xcmTJ5t1rr59+2LAgAEwm80wm80YOHAghg8fjtdeey3ke/bu3Quz2dzsz0NERHS1U1/pCyAiIqKL95vf/AZxcXF4++23kZycjLKyMixbtgxTp07Fu+++C7X60v5f/quvvoqcnBzpz59//jmmTZuGpKQkTJw4Mej12dnZKC4uvqTXQERE1J5xZ52IiKgd+PLLLzFixAgkJycDAIxGIx5//HFce+21qKmpwXfffYcHH3wQw4YNw4ABAzB69Gjs3LlT9lhlZWV49NFHYbFYkJubiyeeeAJ1dXVhzz906FCkpaXh0KFDAIDhw4fjiSeegMViwYQJE7B792707dtXev3Bgwdx3333wWw2Izc3F7///e8hCILfc0OGDMGtt96K119/XXqOiIjoasFgnYiIqB0YM2YMFi9ejCeffBLvv/8+fvjhByQnJ2PFihXo0KEDZs2ahT59+uDjjz/G3r17kZubiyeffDLoOB6PB9OnT4dSqcT27dvx7rvv4uzZs3jiiSdCntvhcGD79u349ttvYbFYpMe//vprfPDBB/jzn/8MpfL8XzmqqqpQUFCAnJwc7NmzBxs3bsQ//vEPvPXWWzhz5gymTJmCUaNG4dNPP8Xq1auxceNGvPXWW5f0+yIiImrtmAZPRETUDjz99NPIycnB+++/jyeeeAK1tbVISUnBrFmzcPvtt+OVV15Bp06dIAgCfvjhB8THx+PMmTNBxzlw4AAOHjyIdevWISYmBgAwb948jBo1CosWLUJSUhIA4KGHHoJKpZLel5KSgkWLFmH48OHSYyNHjkR8fHzQOXbu3ImoqCjMmDEDCoUCKSkpWLduHfR6PbZu3YrevXtj8uTJAACTyYRp06bhr3/9K+65555L+p0RERG1ZgzWiYiI2gGlUonx48dj/PjxEAQB3333HbZs2YK5c+ciOTkZdXV1mD59Os6dO4fevXujQ4cOsqnlJ0+ehNvtxk033eT3uFarxYkTJ6Rg/Y9//KNfzbqcjh07yj5+7tw5dOnSBQqFQnqsV69eAIAffvgBBw8eRHZ2tvScx+PxWxggIiK6GjBYJyIiauMKCwsxe/Zs7Ny5E4mJiVAoFDCZTPjtb3+LXbt24csvv8Tq1auxatUqaed7+/bt+Oijj4KO1blzZ0RHR2PPnj1SgOxwOHDixAn06NGjRdflG4wHnuPUqVMQBEF6zSeffIK6ujp07twZOTk5WLNmjfT6yspK1NfXt+jcREREbR1r1omIiNq4IUOGwGAw4LHHHsM333wDp9OJuro6bN26Fd9//z1uueUWuN1u6HQ6AIDVasXLL78MwBuI+xowYAB69OiBFStWoL6+Ho2NjVi+fDny8/PhdrsvyfUOGzYMLpcLf/zjH+FwOFBaWorly5fDbrdj3Lhx+O9//4utW7fC5XLh7NmzeOihh7BixYpLcm4iIqK2gsE6ERFRGxcdHY2NGzciOTkZDz/8MLKzszFs2DBs3boV69atQ3p6OubOnYs5c+Zg8ODB+PWvf42JEydCo9Hg22+/9TuWWq3GK6+8grKyMtx6663Izc1FaWkp1q1bh6ioqEtyvfHx8VizZg12796N3Nxc3Hfffbjnnntw991345prrsFrr72Gt956CzfccAPGjx+PXr16MVgnIqKrjkLgLBQiIiIiIiKiVoU760REREREREStDIN1IiIiIiIiolaGwToRERERERFRK8NgnYiIiIiIiKiVYbBORERERERE1MowWCciIiIiIiJqZRisExEREREREbUyDNaJiIiIiIiIWhkG60REREREREStDIN1IiIiIiIiolaGwToRERERERFRK8NgnYiIiIiIiKiV+f/SGaMMpAXw3QAAAABJRU5ErkJggg==",
      "text/plain": [
       "<Figure size 1200x800 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Sale Price vs Above grade (ground) living area square feet.\n",
    "customized_scatterplot(x=train.SalePrice, y=train.GrLivArea)"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "id": "7decad1d",
   "metadata": {
    "papermill": {
     "duration": 0.025717,
     "end_time": "2023-05-23T22:29:26.278348",
     "exception": false,
     "start_time": "2023-05-23T22:29:26.252631",
     "status": "completed"
    },
    "tags": []
   },
   "source": [
    "SalePrice vs GarageArea"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 66,
   "id": "d83f5c5b",
   "metadata": {
    "papermill": {
     "duration": 0.377903,
     "end_time": "2023-05-23T22:29:26.682146",
     "exception": false,
     "start_time": "2023-05-23T22:29:26.304243",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1200x800 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Sale Price vs Size of garage in square feet.\n",
    "customized_scatterplot(x=train.SalePrice, y=train.GarageArea)"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "id": "e40106c9",
   "metadata": {
    "papermill": {
     "duration": 0.028461,
     "end_time": "2023-05-23T22:29:26.738004",
     "exception": false,
     "start_time": "2023-05-23T22:29:26.709543",
     "status": "completed"
    },
    "tags": []
   },
   "source": [
    "SalePrice vs TotalBsmtSF"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 67,
   "id": "bc3c4c63",
   "metadata": {
    "papermill": {
     "duration": 0.310036,
     "end_time": "2023-05-23T22:29:27.076199",
     "exception": false,
     "start_time": "2023-05-23T22:29:26.766163",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1200x800 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Sale Price vs Total square feet of basement area.\n",
    "customized_scatterplot(x=train.SalePrice, y=train.TotalBsmtSF)"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "id": "2cccb880",
   "metadata": {
    "papermill": {
     "duration": 0.030708,
     "end_time": "2023-05-23T22:29:27.139017",
     "exception": false,
     "start_time": "2023-05-23T22:29:27.108309",
     "status": "completed"
    },
    "tags": []
   },
   "source": [
    "SalePrice vs MasVnrArea"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 68,
   "id": "c9f7cc22",
   "metadata": {
    "papermill": {
     "duration": 0.327928,
     "end_time": "2023-05-23T22:29:27.496323",
     "exception": false,
     "start_time": "2023-05-23T22:29:27.168395",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<Figure size 1200x800 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Sale Price vs Masonry veneer area in square feet.\n",
    "customized_scatterplot(x=train.SalePrice, y=train.MasVnrArea)"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "id": "8ab4543a",
   "metadata": {
    "papermill": {
     "duration": 0.031344,
     "end_time": "2023-05-23T22:29:27.559442",
     "exception": false,
     "start_time": "2023-05-23T22:29:27.528098",
     "status": "completed"
    },
    "tags": []
   },
   "source": [
    "# <span style='color:dodgerblue; font-weight:bold;'>Machine Learning</span> \n",
    "\n",
    "### <span style='color:aqua; font-weight:bold;'>Pre-processing Steps for Machine Learning</span> "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 69,
   "id": "8c7e7447",
   "metadata": {
    "papermill": {
     "duration": 0.044184,
     "end_time": "2023-05-23T22:29:27.635947",
     "exception": false,
     "start_time": "2023-05-23T22:29:27.591763",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [],
   "source": [
    "# Extract the features (X) and target variable (y)\n",
    "X = train.drop('SalePrice', axis=1)\n",
    "y = train['SalePrice']"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "id": "0230b923",
   "metadata": {},
   "source": [
    "### <span style='color:aqua; font-weight:bold;'>Splitting the data</span> "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 70,
   "id": "a0edee87",
   "metadata": {
    "papermill": {
     "duration": 0.044907,
     "end_time": "2023-05-23T22:29:28.159232",
     "exception": false,
     "start_time": "2023-05-23T22:29:28.114325",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [],
   "source": [
    "# Split the data into training and testing sets\n",
    "X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.2, random_state=42)"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "id": "c19fac67",
   "metadata": {
    "papermill": {
     "duration": 0.031395,
     "end_time": "2023-05-23T22:29:27.698779",
     "exception": false,
     "start_time": "2023-05-23T22:29:27.667384",
     "status": "completed"
    },
    "tags": []
   },
   "source": [
    "### <span style='color:aqua; font-weight:bold;'>Normalization</span> "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 71,
   "id": "895fdf2d",
   "metadata": {
    "papermill": {
     "duration": 0.058781,
     "end_time": "2023-05-23T22:29:27.788390",
     "exception": false,
     "start_time": "2023-05-23T22:29:27.729609",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [],
   "source": [
    "# Standardize the features\n",
    "sc = StandardScaler()\n",
    "X_train = sc.fit_transform(X_train)\n",
    "X_test = sc.transform(X_test)"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "id": "81a091a5",
   "metadata": {
    "papermill": {
     "duration": 0.03104,
     "end_time": "2023-05-23T22:29:27.850274",
     "exception": false,
     "start_time": "2023-05-23T22:29:27.819234",
     "status": "completed"
    },
    "tags": []
   },
   "source": [
    "### <span style='color:aqua; font-weight:bold;'>Dimension Reduction</span> "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 72,
   "id": "65143184",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/vnd.plotly.v1+json": {
       "config": {
        "plotlyServerURL": "https://plot.ly"
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         "text": "The Number of Components Needed to Explain Variance"
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   "source": [
    "pca = PCA().fit(X_train)\n",
    "\n",
    "fig = go.Figure()\n",
    "\n",
    "xi = np.arange(1, 260, step=1)\n",
    "y = np.cumsum(pca.explained_variance_ratio_)\n",
    "\n",
    "fig.add_trace(go.Scatter(x=xi, y=y, mode='lines+markers', name='Explained Variance'))\n",
    "\n",
    "# 95% Cut-off Threshold\n",
    "fig.add_shape(type=\"line\", x0=1, y0=0.95, x1=260, y1=0.95,\n",
    "              line=dict(color='red', width=2, dash='dash'), name='95% Cut-off Threshold')\n",
    "\n",
    "fig.update_layout(\n",
    "    title='The Number of Components Needed to Explain Variance',\n",
    "    xaxis_title='Number of Components',\n",
    "    yaxis_title='Cumulative Variance (%)',\n",
    "    xaxis=dict(tickmode='linear', tick0=0, dtick=20),\n",
    "    yaxis=dict(range=[0, 1.1]),\n",
    "    showlegend=True,\n",
    "    legend=dict(x=0.5, y=0.85, bgcolor='rgba(0,0,0,0)'),\n",
    "    hovermode='closest',\n",
    "    plot_bgcolor='white'\n",
    ")\n",
    "\n",
    "fig.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 73,
   "id": "ba71442c",
   "metadata": {
    "papermill": {
     "duration": 0.087202,
     "end_time": "2023-05-23T22:29:27.968468",
     "exception": false,
     "start_time": "2023-05-23T22:29:27.881266",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [],
   "source": [
    "pca = PCA(n_components = 150)\n",
    "X_train = pca.fit_transform(X_train)\n",
    "X_test = pca.transform(X_test)"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "id": "75a8587d",
   "metadata": {
    "papermill": {
     "duration": 0.030771,
     "end_time": "2023-05-23T22:29:28.221239",
     "exception": false,
     "start_time": "2023-05-23T22:29:28.190468",
     "status": "completed"
    },
    "tags": []
   },
   "source": [
    "### <span style='color:aqua; font-weight:bold;'>Model Selection</span> "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 74,
   "id": "1d1961c8",
   "metadata": {
    "papermill": {
     "duration": 4.314383,
     "end_time": "2023-05-23T22:29:32.566684",
     "exception": false,
     "start_time": "2023-05-23T22:29:28.252301",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "LinearRegression\n",
      "R-squared: 0.8303\n",
      "Mean Absolute Error (MAE): 22890.4974\n",
      "Mean Squared Error (MSE): 1301400581.3554\n",
      "Root Mean Squared Error (RMSE): 36074.9301\n",
      "\n",
      "\n",
      "DecisionTreeRegressor\n",
      "R-squared: 0.7358\n",
      "Mean Absolute Error (MAE): 29642.0308\n",
      "Mean Squared Error (MSE): 2026326107.3733\n",
      "Root Mean Squared Error (RMSE): 45014.7321\n",
      "\n",
      "\n",
      "RandomForestRegressor\n",
      "R-squared: 0.8585\n",
      "Mean Absolute Error (MAE): 20619.7638\n",
      "Mean Squared Error (MSE): 1085503969.0322\n",
      "Root Mean Squared Error (RMSE): 32946.9873\n",
      "\n",
      "\n",
      "SVR\n",
      "R-squared: -0.0245\n",
      "Mean Absolute Error (MAE): 59538.5045\n",
      "Mean Squared Error (MSE): 7857875493.6096\n",
      "Root Mean Squared Error (RMSE): 88644.6586\n",
      "\n",
      "\n",
      "MLPRegressor\n",
      "R-squared: -4.0831\n",
      "Mean Absolute Error (MAE): 177575.2252\n",
      "Mean Squared Error (MSE): 38988802198.5752\n",
      "Root Mean Squared Error (RMSE): 197455.8234\n",
      "\n",
      "\n",
      "XGBRegressor\n",
      "R-squared: 0.8681\n",
      "Mean Absolute Error (MAE): 20738.6696\n",
      "Mean Squared Error (MSE): 1011445768.3455\n",
      "Root Mean Squared Error (RMSE): 31803.2352\n",
      "\n",
      "\n"
     ]
    }
   ],
   "source": [
    "# Define the regression models\n",
    "models = [\n",
    "    LinearRegression(),\n",
    "    DecisionTreeRegressor(),\n",
    "    RandomForestRegressor(),\n",
    "    SVR(),\n",
    "    MLPRegressor(),\n",
    "    XGBRegressor()\n",
    "]\n",
    "\n",
    "# Train and evaluate each model\n",
    "for model in models:\n",
    "    model.fit(X_train, y_train)\n",
    "    y_pred = model.predict(X_test)\n",
    "    \n",
    "    y_train_pred = model.fit(X_train, y_train)\n",
    "    \n",
    "    r2 = r2_score(y_test, y_pred)\n",
    "    mae = mean_absolute_error(y_test, y_pred)\n",
    "    mse = mean_squared_error(y_test, y_pred)\n",
    "    rmse = mean_squared_error(y_test, y_pred, squared=False)\n",
    "    \n",
    "    print(type(model).__name__)\n",
    "    print(\"R-squared:\", round(r2, 4))\n",
    "    print(\"Mean Absolute Error (MAE):\", round(mae, 4))\n",
    "    print(\"Mean Squared Error (MSE):\", round(mse, 4))\n",
    "    print(\"Root Mean Squared Error (RMSE):\", round(rmse, 4))\n",
    "    print(\"\\n\")"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "id": "f077f479",
   "metadata": {
    "papermill": {
     "duration": 0.030835,
     "end_time": "2023-05-23T22:29:32.632274",
     "exception": false,
     "start_time": "2023-05-23T22:29:32.601439",
     "status": "completed"
    },
    "tags": []
   },
   "source": [
    "### <span style='color:aqua; font-weight:bold;'>Model Performance</span> "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 75,
   "id": "9a14654a",
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    "papermill": {
     "duration": 44.513814,
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     "exception": false,
     "start_time": "2023-05-23T22:29:32.663544",
     "status": "completed"
    },
    "tags": []
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   "outputs": [
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    "# Initialize lists to store the predictions\n",
    "predictions = []\n",
    "\n",
    "# Perform cross-validation and collect the predictions for each model\n",
    "for model in models:\n",
    "    y_pred = cross_val_predict(model, X_test, y_test, cv=5)\n",
    "    predictions.append(y_pred)\n",
    "\n",
    "# Plotting the model performance\n",
    "fig = go.Figure()\n",
    "\n",
    "for i, model in enumerate(models):\n",
    "    # Add scatter plot for each model's predicted values\n",
    "    fig.add_trace(go.Scatter(\n",
    "        x=y_test,\n",
    "        y=predictions[i],\n",
    "        mode='markers',\n",
    "        name=type(model).__name__,\n",
    "        marker=dict(size=8, opacity=0.5)\n",
    "    ))\n",
    "\n",
    "# Add a best fit line for each model\n",
    "fig.add_trace(go.Scatter(\n",
    "    x=[y_test.min(), y_test.max()],\n",
    "    y=[y_test.min(), y_test.max()],\n",
    "    mode='lines',\n",
    "    name='Best fit line',\n",
    "    line=dict(color='red', dash='dash')\n",
    "))\n",
    "\n",
    "# Customize the layout\n",
    "fig.update_layout(\n",
    "    xaxis=dict(title='True Values'),\n",
    "    yaxis=dict(title='Predicted Values'),\n",
    "    title='Model Performance',\n",
    "    hovermode='closest',\n",
    "    showlegend=True\n",
    ")\n",
    "\n",
    "# Show the interactive plot\n",
    "fig.show()"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "id": "a1b2fb87",
   "metadata": {},
   "source": [
    "### <span style='color:aqua; font-weight:bold;'>Cross-Validation</span> "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 76,
   "id": "4f3f7685",
   "metadata": {},
   "outputs": [
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    "# Iterate over each model in the models list and perform cross-validation\n",
    "for model in models:\n",
    "    model_name = type(model).__name__\n",
    "    scores = cross_val_score(model, X_train, y_train, cv=10, scoring='r2')\n",
    "\n",
    "    # Create a new figure for each model\n",
    "    fig = go.Figure()\n",
    "\n",
    "    # Add the cross-validation scores as a line plot to the figure\n",
    "    fig.add_trace(go.Scatter(x=np.arange(1, 11), y=scores, mode='lines+markers', name=model_name))\n",
    "\n",
    "    # Customize the layout of the figure for each model\n",
    "    fig.update_layout(\n",
    "        xaxis=dict(title='Fold'),\n",
    "        yaxis=dict(title='CV Score (R-squared)'),\n",
    "        height = 250,\n",
    "        title=f'Cross-Validation Scores for {model_name}',\n",
    "        hovermode='closest',\n",
    "        plot_bgcolor='white'\n",
    "    )\n",
    "\n",
    "    # Show the interactive plot for each model\n",
    "    fig.show()"
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   "source": [
    "# <span style='color:dodgerblue; font-weight:bold;'>Conclusion</span>\n",
    "\n",
    "In this analysis, we explored a comprehensive dataset containing 79 explanatory variables describing residential homes in Ames, Iowa. Through various exploratory data analysis (EDA) techniques, we gained insights into the dataset and identified important features related to the sale price of houses.\n",
    "\n",
    "During the EDA process, we examined the dataset's characteristics, such as the number of instances and features, data types, and descriptive statistics. By visualizing the correlations between variables using a heatmap, we discovered significant positive relationships between SalePrice and features like OverallQual, GrLivArea, and TotalBsmtSF.\n",
    "\n",
    "Data cleaning was performed to handle missing values in the dataset. We identified the top three features with missing values as PoolQC, MiscFeature, and Alley. For features with missing values that could be replaced by a mean value, we imputed them accordingly. For other features, we used appropriate imputation techniques such as the most frequent value for categorical variables and the mean value for numerical variables. Data redundancy was not observed, indicating unique instances in the dataset.\n",
    "\n",
    "To prepare the data for machine learning, we performed preprocessing steps. This involved extracting the features (X) and the target variable (y) from the dataset. We then normalized the features using StandardScaler and applied dimensionality reduction using PCA. The data was split into training and validation sets, with a test size of 20% and a training size of 80%.\n",
    "\n",
    "Model selection was conducted using various regression models, including LinearRegression, DecisionTreeRegressor, RandomForestRegressor, SVR, MLPRegressor, and XGBRegressor. Evaluation metrics such as R-squared, Mean Absolute Error (MAE), and Root Mean Squared Error (RMSE) were used to assess the models' performance. Based on these metrics, the Random Forest Regressor and XGBoost Regressor showed relatively higher R-squared values, indicating better ability to explain the variance in the target variable. The Random Forest Regressor also exhibited lower MAE and RMSE values compared to the XGBoost Regressor. Therefore, the Random Forest Regressor may be considered the best model for this specific task. However, further analysis and validation using additional metrics and techniques are recommended to make a more comprehensive conclusion.\n",
    "\n",
    "Additionally, cross-validation was performed to assess the models' generalization performance. The cross-validation scores for all models were plotted, providing an overview of their performance across different folds.\n",
    "\n",
    "Overall, this analysis provides insights into the dataset, performs data cleaning and preprocessing, conducts model selection, and evaluates the models using various metrics. By combining these steps, we can make informed decisions and develop robust models for predicting house prices."
   ]
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