real_estate_data_cleaning.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Data Cleaning and Exploration for Property Price Prediction\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 1. Introduction\n",
    "\n",
    "In this notebook, we will perform data cleaning on a real estate dataset. The goal is to prepare the data for a future machine learning model that predicts property prices.\n",
    "\n",
    "### Objectives:\n",
    "\n",
    "    1.\tLoad the dataset and required libraries.\n",
    "    2.\tAnalyze missing values and visualize them.\n",
    "    3.\tIdentify critical columns to keep and non-critical columns to drop.\n",
    "    4.\tHandle missing values appropriately.\n",
    "    5.\tCategorize data to facilitate imputation.\n",
    "    6.\tImpute missing values using grouped data.\n",
    "    7.\tShow deductions based on data patterns.\n",
    "    8.\tHandle outliers and visualize their impact.\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 2. Load the File and Required Libraries\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 98,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Price</th>\n",
       "      <th>Locality</th>\n",
       "      <th>Type_of_Property</th>\n",
       "      <th>Subtype_of_Property</th>\n",
       "      <th>State_of_the_Building</th>\n",
       "      <th>Number_of_Rooms</th>\n",
       "      <th>Living_Area</th>\n",
       "      <th>Fully_Equipped_Kitchen</th>\n",
       "      <th>Furnished</th>\n",
       "      <th>Open_fire</th>\n",
       "      <th>...</th>\n",
       "      <th>Terrace_Area</th>\n",
       "      <th>Garden</th>\n",
       "      <th>Garden_Area</th>\n",
       "      <th>Surface_of_the_Land</th>\n",
       "      <th>Surface_area_plot_of_land</th>\n",
       "      <th>Number_of_Facades</th>\n",
       "      <th>Swimming_Pool</th>\n",
       "      <th>Disabled_Access</th>\n",
       "      <th>Lift</th>\n",
       "      <th>Municipality</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>475000</td>\n",
       "      <td>1800</td>\n",
       "      <td>APARTMENT</td>\n",
       "      <td>LOFT</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3</td>\n",
       "      <td>400.0</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Vilvoorde</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>895000</td>\n",
       "      <td>2000</td>\n",
       "      <td>APARTMENT</td>\n",
       "      <td>DUPLEX</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3</td>\n",
       "      <td>286.0</td>\n",
       "      <td>1</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>30.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Antwerpen</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>685000</td>\n",
       "      <td>1180</td>\n",
       "      <td>APARTMENT</td>\n",
       "      <td>PENTHOUSE</td>\n",
       "      <td>JUST_RENOVATED</td>\n",
       "      <td>2</td>\n",
       "      <td>127.0</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>55.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>4.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>Uccle</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>289000</td>\n",
       "      <td>8680</td>\n",
       "      <td>APARTMENT</td>\n",
       "      <td>APARTMENT</td>\n",
       "      <td>JUST_RENOVATED</td>\n",
       "      <td>3</td>\n",
       "      <td>120.0</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>4.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>Koekelare</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>775000</td>\n",
       "      <td>2980</td>\n",
       "      <td>HOUSE</td>\n",
       "      <td>VILLA</td>\n",
       "      <td>TO_BE_DONE_UP</td>\n",
       "      <td>4</td>\n",
       "      <td>350.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3715.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.0</td>\n",
       "      <td>Zoersel</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 21 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "    Price  Locality Type_of_Property Subtype_of_Property  \\\n",
       "0  475000      1800        APARTMENT                LOFT   \n",
       "1  895000      2000        APARTMENT              DUPLEX   \n",
       "2  685000      1180        APARTMENT           PENTHOUSE   \n",
       "3  289000      8680        APARTMENT           APARTMENT   \n",
       "4  775000      2980            HOUSE               VILLA   \n",
       "\n",
       "  State_of_the_Building  Number_of_Rooms  Living_Area  Fully_Equipped_Kitchen  \\\n",
       "0                   NaN                3        400.0                       0   \n",
       "1                   NaN                3        286.0                       1   \n",
       "2        JUST_RENOVATED                2        127.0                       0   \n",
       "3        JUST_RENOVATED                3        120.0                       0   \n",
       "4         TO_BE_DONE_UP                4        350.0                       0   \n",
       "\n",
       "   Furnished  Open_fire  ...  Terrace_Area  Garden  Garden_Area  \\\n",
       "0        NaN        NaN  ...           NaN     NaN          NaN   \n",
       "1        NaN        NaN  ...          30.0     NaN          NaN   \n",
       "2        NaN        NaN  ...          55.0     NaN          NaN   \n",
       "3        NaN        NaN  ...           4.0     NaN          NaN   \n",
       "4        0.0        NaN  ...           NaN     NaN          NaN   \n",
       "\n",
       "   Surface_of_the_Land  Surface_area_plot_of_land  Number_of_Facades  \\\n",
       "0                  NaN                        NaN                NaN   \n",
       "1                  NaN                        NaN                NaN   \n",
       "2                  NaN                        NaN                4.0   \n",
       "3                  NaN                        NaN                NaN   \n",
       "4                  NaN                     3715.0                4.0   \n",
       "\n",
       "   Swimming_Pool  Disabled_Access  Lift  Municipality  \n",
       "0            NaN              NaN   NaN     Vilvoorde  \n",
       "1            NaN              NaN   NaN     Antwerpen  \n",
       "2            0.0              0.0   1.0         Uccle  \n",
       "3            NaN              NaN   1.0     Koekelare  \n",
       "4            0.0              NaN   0.0       Zoersel  \n",
       "\n",
       "[5 rows x 21 columns]"
      ]
     },
     "execution_count": 98,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Import necessary libraries\n",
    "import pandas as pd\n",
    "import numpy as np\n",
    "import seaborn as sns\n",
    "import matplotlib.pyplot as plt\n",
    "\n",
    "# Set visualization style\n",
    "sns.set_style('whitegrid')\n",
    "%matplotlib inline\n",
    "\n",
    "# Load the dataset\n",
    "df = pd.read_csv('immoweb_data.csv')\n",
    "\n",
    "# Display the first few rows\n",
    "df.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 3. Analyzing Missing Values\n",
    "\n",
    "We need to analyze the missing values in the dataset and visualize them to understand which columns have the most missing data.\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 95,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/var/folders/z6/vnwrtwgd7x5chl_2vn910h6r0000gn/T/ipykernel_3763/2164067638.py:16: FutureWarning: \n",
      "\n",
      "Passing `palette` without assigning `hue` is deprecated and will be removed in v0.14.0. Assign the `y` variable to `hue` and set `legend=False` for the same effect.\n",
      "\n",
      "  sns.barplot(x='MissingPercentage', y='Column', data=missing_df, palette='viridis')\n"
     ]
    },
    {
     "data": {
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",
      "text/plain": [
       "<Figure size 1200x800 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Calculate the percentage of missing values for each column\n",
    "missing_percentage = df.isnull().mean() * 100\n",
    "\n",
    "# Create a DataFrame for visualization\n",
    "missing_df = pd.DataFrame({\n",
    "    'Column': df.columns,\n",
    "    'MissingPercentage': missing_percentage\n",
    "}).sort_values(by='MissingPercentage', ascending=False)\n",
    "\n",
    "# Reset index for better display\n",
    "missing_df.reset_index(drop=True, inplace=True)\n",
    "\n",
    "# Display the DataFrame\n",
    "# Plotting the missing values\n",
    "plt.figure(figsize=(12, 8))\n",
    "sns.barplot(x='MissingPercentage', y='Column', data=missing_df, palette='viridis')\n",
    "plt.title('Percentage of Missing Values by Column')\n",
    "plt.xlabel('Percentage of Missing Values')\n",
    "plt.ylabel('Column')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 4. Identifying Critical and Non-Critical Columns\n",
    "\n",
    "Based on domain knowledge and the analysis of missing values, we categorize the columns.\n",
    "\n",
    "4.1 Critical Columns to Keep\n",
    "\n",
    "These columns are essential for our analysis and model: - Garden - Terrace - Swimming_Pool - Price - Locality - Type_of_Property - Subtype_of_Property - Number_of_Rooms - Fully_Equipped_Kitchen\n",
    "\n",
    "<b>Rationale</b>:\n",
    "• These columns provide significant information that influences property prices.\n",
    "• Even if they have missing values, we will attempt to fill them due to their importance.\n",
    "\n",
    "4.2 Columns to Drop\n",
    "\n",
    "These columns have too many missing values and add minimal value:\n",
    "• Open_fire\n",
    "• Garden_Area\n",
    "• Terrace_Area\n",
    "• Disabled_Access\n",
    "• Surface_of_the_Land\n",
    "• Furnished\n",
    "\n",
    "Rationale:\n",
    "• High percentage of missing values makes them unreliable.\n",
    "• Their impact on price prediction is minimal compared to critical columns.\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 99,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Index(['Price', 'Locality', 'Type_of_Property', 'Subtype_of_Property',\n",
       "       'State_of_the_Building', 'Number_of_Rooms', 'Living_Area',\n",
       "       'Fully_Equipped_Kitchen', 'Terrace', 'Garden',\n",
       "       'Surface_area_plot_of_land', 'Number_of_Facades', 'Swimming_Pool',\n",
       "       'Lift', 'Municipality'],\n",
       "      dtype='object')"
      ]
     },
     "execution_count": 99,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Drop the columns\n",
    "columns_to_drop = ['Open_fire', 'Garden_Area', 'Terrace_Area', 'Disabled_Access','Surface_of_the_Land','Furnished']\n",
    "df = df.drop(columns=columns_to_drop)\n",
    "        \n",
    "\n",
    "#Drop columns with less than 5% of missing entries\n",
    "threshold = 0.05 * len(df)\n",
    "columns_low_missing_data = df.columns[df.isna().sum() < threshold]\n",
    "df.dropna(subset=columns_low_missing_data, inplace=True)\n",
    "\n",
    "# Verify the columns are dropped\n",
    "df.columns"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 6. Handling Missing Values in Critical Columns\n",
    "\n",
    "For Garden, Terrace, and Swimming_Pool: <br>\n",
    "• Missing values are likely to mean the feature is absent. <br>\n",
    "• We’ll fill missing values with 0 (False).\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 100,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Fill missing values with 0 for binary columns\n",
    "binary_columns = ['Garden', 'Terrace', 'Swimming_Pool']\n",
    "df[binary_columns] = df[binary_columns].fillna(0).astype(int)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 7. Filling Missing Values for Categorical Data\n",
    "\n",
    "We will fill missing values for categorical data using the mode based on similar entries grouped by <b>Subtype_of_Property</b>.\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Defining a Function to Get Grouped Mode\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 101,
   "metadata": {},
   "outputs": [],
   "source": [
    "def get_grouped_mode(dataframe, group, column):\n",
    "    mode_series = dataframe.groupby(group)[column].apply(lambda x: x.mode().iloc[0] if not x.mode().empty else np.nan)\n",
    "    return mode_series.to_dict()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Missing values in ‘Lift’ are filled based on the mode of ‘Lift’ within each ‘Subtype_of_Property’.\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 102,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Lift mode per Subtype_of_Property:\n",
      "{'APARTMENT': 1.0, 'APARTMENT_BLOCK': 0.0, 'BUNGALOW': 0.0, 'CASTLE': 0.0, 'CHALET': 0.0, 'COUNTRY_COTTAGE': 0.0, 'DUPLEX': 0.0, 'EXCEPTIONAL_PROPERTY': 0.0, 'FARMHOUSE': 0.0, 'FLAT_STUDIO': 1.0, 'GROUND_FLOOR': 1.0, 'HOUSE': 0.0, 'KOT': 1.0, 'LOFT': 1.0, 'MANOR_HOUSE': 0.0, 'MANSION': 0.0, 'MIXED_USE_BUILDING': 0.0, 'OTHER_PROPERTY': 0.0, 'PENTHOUSE': 1.0, 'SERVICE_FLAT': 1.0, 'TOWN_HOUSE': 0.0, 'TRIPLEX': 0.0, 'VILLA': 0.0}\n"
     ]
    }
   ],
   "source": [
    "# Get the mode of 'Lift' for each 'Subtype_of_Property'\n",
    "lift_dict = get_grouped_mode(df, 'Subtype_of_Property', 'Lift')\n",
    "\n",
    "# Fill missing values\n",
    "df['Lift'] = df['Lift'].fillna(df['Subtype_of_Property'].map(lift_dict))\n",
    "\n",
    "# Print the mapping\n",
    "print(\"Lift mode per Subtype_of_Property:\")\n",
    "print(lift_dict)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 8. Categorizing Municipalities into Regions\n",
    "\n",
    "Due to the high number of unique values in ‘Locality’, we categorize them into broader regions using postal code patterns.\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 103,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/var/folders/z6/vnwrtwgd7x5chl_2vn910h6r0000gn/T/ipykernel_3763/476270357.py:4: FutureWarning: \n",
      "\n",
      "Passing `palette` without assigning `hue` is deprecated and will be removed in v0.14.0. Assign the `y` variable to `hue` and set `legend=False` for the same effect.\n",
      "\n",
      "  sns.barplot(x=locality_counts.values, y=locality_counts.index, palette='viridis')\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1200x800 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Plot the number of properties per locality\n",
    "plt.figure(figsize=(12, 8))\n",
    "locality_counts = df['Municipality'].value_counts().head(50)  # Display top 40 for readability\n",
    "sns.barplot(x=locality_counts.values, y=locality_counts.index, palette='viridis')\n",
    "plt.title('Number of Properties by Locality (Top 50)')\n",
    "plt.xlabel('Number of Properties')\n",
    "plt.ylabel('Municipality')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 104,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Define regions and their corresponding postal code patterns\n",
    "provinces = ['Brussels Capital','Walloon Brabant', 'Flemish Brabant', 'Antwerp', 'Limburg','Liège','Namur','Hainaut','Luxembourg','West Flanders','East Flanders']\n",
    "brussels_capital = '^10|^11|^12'\n",
    "walloon_brabant = '^13|^14'\n",
    "flemish_brabant = '^15|^16|^17|^18|^19|^30|^31|^32|^33|^34'\n",
    "antwerp = '^20|^21|^22|^23|^24|^25|^26|^27|^28|^29'\n",
    "limburg = '^35|^36|^37|^38|^39'\n",
    "liège = '^40|^41|^42|^43|^44|^45|^46|^47|^48|^49'\n",
    "namur = '^50|^51|^55|^53|^55|^55|^56|^57|^58|^59'\n",
    "hainaut = '^60|^61|^62|63|^64|^65|^70|^71|^77|^73|^74|^75|^76|^77|^78|^79'\n",
    "luxembourg = '^66|^67|^68|^69'\n",
    "west_flanders = '^80|^81|^82|^83|^84|^85|^86|^87|^88|^89'\n",
    "east_flanders = '^90|^91|^92|^93|^94|^95|^96|^97|^98|^99'\n",
    "\n",
    "# Create conditions based on postal code patterns\n",
    "conditions = [\n",
    "    df[\"Locality\"].astype(str).str.contains(brussels_capital),\n",
    "    df[\"Locality\"].astype(str).str.contains(walloon_brabant),\n",
    "    df[\"Locality\"].astype(str).str.contains(flemish_brabant),\n",
    "    df[\"Locality\"].astype(str).str.contains(antwerp),\n",
    "    df[\"Locality\"].astype(str).str.contains(limburg),\n",
    "    df[\"Locality\"].astype(str).str.contains(liege),\n",
    "    df[\"Locality\"].astype(str).str.contains(namur),\n",
    "    df[\"Locality\"].astype(str).str.contains(hainaut),\n",
    "    df[\"Locality\"].astype(str).str.contains(luxembourg),\n",
    "    df[\"Locality\"].astype(str).str.contains(west_flanders),\n",
    "    df[\"Locality\"].astype(str).str.contains(east_flanders),\n",
    "]\n",
    "\n",
    "# Assign regions based on conditions\n",
    "df[\"Province\"] = np.select(conditions, provinces, default='Other')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 105,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/var/folders/z6/vnwrtwgd7x5chl_2vn910h6r0000gn/T/ipykernel_3763/1232461508.py:3: FutureWarning: \n",
      "\n",
      "Passing `palette` without assigning `hue` is deprecated and will be removed in v0.14.0. Assign the `y` variable to `hue` and set `legend=False` for the same effect.\n",
      "\n",
      "  sns.countplot(y='Province', data=df, order=df['Province'].value_counts().index, palette='pastel')\n"
     ]
    },
    {
     "data": {
      "image/png": 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t2rVVrlw5TZkyRTdu3LjvdJCH5e3trVy5cqX5bHbt2qULFy5YfTZBQUEym82aNWuWLl++rNatWz/Utf38/JSUlKSffvrJ0mY2mzVixAh99NFHGfo8AACPDyM5AADIpkaNGqXffvstzciCxo0ba/369fL29pa7u7siIiJ05syZLLtu7ty51b9/f73++usymUyaNWuWXF1d9fLLL0u6s+bF119/rR49eqhXr14qVKiQvv32W33xxRcaMWLEA13r6aefVrt27TR79mzFxcWpdu3aOnLkiObMmSN/f381bNgwy+7rfhwcHPTGG29oxIgRevPNN9W6dWtduXJFc+bMUcGCBdWzZ0+r4ydPnqyEhAR5eHho9erViomJ0aeffipJatSokWrXrq0BAwZowIABqlChgvbv36/Zs2erYcOGllExd+Pi4iLpztonFSpUsFpDRZIKFSqkV155RbNmzdLNmzfl7++vixcvatasWTIYDKpcubJcXFz01FNP6d1339XNmzdVtmxZHTx4UNu2bVPfvn3v+XtISUlRnz591K9fP125ckXTpk1TpUqV0oQFHTp00LRp0/TMM8+kO+Ukq7i6uqpPnz6aO3eunJyc1KRJE507d06zZs2y/Bv697GNGjXSihUr5Ovr+1CjZqQ7/c3X11fDhw/XkCFDVKZMGX399deKiYnRhAkTMvR5AAAeH0IOAACyKVdXV40dO1YDBw60ah8xYoSSk5P1wQcfyNHRUUFBQXrzzTctT3Z4WFWrVtVzzz2nsWPH6saNG6pXr57CwsIsX8yLFy+ulStXatq0aRo7dqwSEhJUrlw5TZw4US+++OIDX2/ixIlyd3fXl19+qY8//ljFihVT9+7dNWDAgHTXQXhU2rdvr/z58+ujjz5SaGionJ2d1bBhQ73xxhtp1g0ZO3asPvroI509e1ZVq1bV4sWL5efnJ+lOYLJgwQLNmjVLH330kS5fvqzixYurZ8+elieypMfZ2Vk9e/bUqlWrtG3btrsuXDlkyBAVLVpUK1as0MKFC1WwYEHVq1dPb7zxhiUkmTNnjqZPn65Zs2bpypUrKlGihAYOHJju2hGpmjVrppIlS+qtt95ScnKymjRponfeeUe5c+e2Oq5Ro0aaNm2a2rdvf9/fa1YYNGiQihQpomXLlmnVqlVydXXV888/ryFDhqRZ16RNmzbaunWrWrVq9dDXNRqN+vjjjzV16lTNmjVLcXFx8vT01OLFiy0L9Gbk8wAAPB4Gc+qqSgAAALiviIgIjRgxQt99912m1pewFwsWLNCSJUv0448/PtA6LAAAPEqM5AAAAECGffXVV/r999+1YsUKDRgwgIADAJCtEHIAAAAgw44ePaqVK1fq2WefVa9evWxdDgAAVpiuAgAAAAAA7AKPkAUAAAAAAHaBkAMAAAAAANgFQg4AAAAAAGAXWHgUDywlJUXJyclycHCQwWCwdTkAAAAAADtnNpuVkpIiR0dHOTikP16DkAMPLDk5WQcOHLB1GQAAAACAJ4yXl9c9H19OyIEHlpqaVa1a9Z7/uIAnkclk0oEDB+Tl5SWj0WjrcoBshz4C3Bt9BEgf/ePJlvr532sUh0TIgUxInaJiNBr5HxcgHfQP4N7oI8C90UeA9NE/nmz3WzKBhUcBIIvlzZvX1iUA2Rp9BLg3+giQPvoH7oeRHMg00lMgLaPRqKpVq9q6DCDboo8A90YfAdJH/8haZrPZLh8kQciBTNt16rpuxNu6CgAAAADAg3DJa5R/hQK2LuORIORApt2IS9HVuBRblwEAAAAAgCTW5AAAAAAAAHaCkAMAAAAAANgFQg4AAAAAAGAXCDkAAAAAAIBdIOQAAAAAAAB2gZADAAAAAADYBUIOAAAAAABgF3JUyNGnTx+NGDHCqm3dunXy9PRUeHi4Vfu8efPUpk2bh7peYmKivvjii3T3Dx8+XJ6ennf9SU5OVnh4uEJCQh6qhvRERUXJ09PzkZwbAAAAAICcKEeFHH5+fjpw4IBVW1RUlIoVK6aoqCir9ujoaNWpU+ehrrd+/Xp9+OGH9zymRYsW+uWXX9L8ODo6PtS1AQAAAADAg8lRIUetWrUUExOjW7duWdqioqLUu3dvRUdHKz4+3tK+b9++hw45zGbzfY/JkyePihYtmuYHAAAAAAA8Xjkq5PDy8pKTk5MOHTokSfrrr7904cIFdezYUS4uLtqzZ48k6dSpU7p27Zr8/PwkSb///rtCQkJUo0YNPffcc1q+fLnlnNevX9egQYPk5+en2rVra+jQobp586aioqI0YsQInT9/Xp6enjp37txD17969Wo9//zzql69uvz9/TVu3DiZTCZJd6a+TJo0SUOGDJG3t7caNWqkyMhIy3tv3rypN954Q76+vnruuefSjGj5888/1a9fP3l7eyswMFBz5syxnDsiIkJdunRRaGioatWqpW+++UZHjx5Vly5d5O3trYYNG2rOnDkPfX8AAAAAANhSjgo5cuXKJW9vb+3fv1+S9Ntvv6l69erKnz+/ateubZmyEh0drYoVK6pQoUKKj4/Xq6++avlyP2zYMM2bN88SIMyePVuxsbH6/PPPtXTpUh09elTz5s2Tr6+vwsLC9NRTT+mXX35RiRIlHqr2HTt26N1339Ubb7yhjRs3aty4cVqzZo2+++47yzHLly9XtWrVtG7dOjVv3lxjxozRjRs3JEljxozRyZMntWzZMo0cOVKffPKJ5X1ms1kDBw6Um5ubvvrqK02aNElr1661mmqzd+9ePf300/riiy8UEBCgt99+W1WqVNG6des0ceJELVy4UNu2bXuoewQAAAAAwJZy3MIRfn5+lpAjKipK/v7+kqQ6depo3bp1kqzX41i7dq3c3Nw0ZMgQSVK5cuV0/vx5LV26VG3bttX58+eVP39+lS5dWnnz5tWsWbMk3QlUXFxcZDQa7zn9ZO3atdq0aZNV26xZs/TMM89YteXLl08TJ05U8+bNJUmlS5fWJ598ouPHj1vaPD099eqrr0qSXnvtNS1dulTHjx9XxYoVtWHDBi1dulTVqlWTJA0YMEDjx4+XdCfsuXDhglavXi0HBweVL19ew4YN04gRIxQaGipJMhgM6t+/v/LkySNJOn/+vJo2bapSpUqpTJky+uSTT1S6dOkH+iwAAAAAAMhOcmTIkToKIyoqShMmTJB0J+R4//33lZiYqOjoaPXv31+SdPLkSR09elS+vr6Wc5hMJhmNRklS9+7dNWDAANWrV0/16tXTc889p1atWmW4nsDAQA0dOtSqrVixYmmOq169uvLkyaPZs2frxIkTOnbsmM6cOaOAgADLMeXKlbO8dnZ2liQlJyfr1KlTMplMqly5smW/l5eX5XVMTIyuXr2qWrVqWdpSUlIUHx+vK1euSJLc3NwsAYck9e3bV9OnT9eqVavUuHFjtWnThrVEAAAAAAA5Wo4LOXx9fXXp0iUdOHBAly5dUs2aNSVJFStWlIuLi3bu3KkTJ05YRnIkJyerXr16Gj169F3PV69ePW3btk3fffedfvzxR40ePVq//PKLpk6dmqF68ufPL3d39/se9/PPPys0NFRt27ZVw4YNFRoaqnHjxlkd4+TklOZ96S1+mitXLsvr5ORklS9fXvPmzUtznIuLiyQpd+7cVu19+vRRixYttHXrVn3//fd6+eWXNWHCBHXs2PG+9wIAAAAAQHaUo9bkkO5M+6hSpYpWrVolLy8v5c2bV9Kd6Ri1a9dWRESEypUrp8KFC0uSPDw8dOrUKZUuXVru7u5yd3dXdHS0PvvsM0nSkiVLdOjQIbVr106zZs3SpEmTtHnzZss5s8rq1avVoUMHjR8/Xh07dlSFChX0xx9/ZOgJLuXLl5eTk5PVYqOHDx+2vPbw8NCFCxdUuHBhyz2eO3dOs2fPvus9JCQk6N1331WuXLnUs2dPffbZZ+rUqVOaaTcAAAAAAOQkOS7kkKTatWtr/fr1aR4RW6dOHX333XeqXbu2pa1169aKj4/X6NGjFRMTo23btmnixIlyc3OTdOcJLePHj1d0dLROnz6tTZs2qWrVqpKkvHnz6tq1azp9+rSSk5MfqmZXV1ft3btXx44d0/HjxzV8+HDFxsYqMTHxvu91dnZWmzZtNGHCBO3bt09RUVFWT0MJCAhQqVKl9NZbb+nYsWPatWuXRo0apbx581qm5fxb7ty5tWfPHk2YMEEnT57UgQMHtGvXLst9AwAAAACQE+XIkKNWrVq6ffu2ZdHRVHXq1FFcXJxV+OHs7KyPP/5Yp0+fVtu2bTVy5Eh169ZNffv2lXRngc+aNWuqf//+atOmjW7fvq0pU6ZIkurWrSt3d3e1atVKR44ceaiaU59+0rlzZ/Xs2VO5c+dWcHBwhs87atQo+fr6qmfPnho+fLheeuklyz6j0aj58+crJSVFnTp10qBBg9SoUSONHDky3fPNmDFDcXFxevHFF9W7d2/5+flpwIABD3WPAAAAAADYksGckfkSwL+YTCZFR0frSq5yuhqXYutyAAAAAAAPwDWfo5pVL2TrMh5I6vdQHx+fu85YSJUjR3IAAAAAAAD8FyEHAAAAAACwC4QcAAAAAADALhByAAAAAAAAu0DIAQAAAAAA7AIhBwAAAAAAsAuEHAAAAAAAwC442roA5FwueR0kAzkZAAAAAOQkLnmNti7hkSHkQKb5eRSQ0Wi/nQMAAAAA7JXZbJbBYLB1GVmOP8Mj00wmk61LALIdk8mkw4cP0z+AdNBHgHujjwDpo39kLXsMOCRCDgDIcnFxcbYuAcjW6CPAvdFHgPTRP3A/hBwAAAAAAMAuEHIAAAAAAAC7QMgBAAAAAADsAiEHAAAAAACwC4QcAJDF8ubNa+sSgGyNPgLcG30ESB/9A/fjaOsCkHMZjUZblwBkO0ajUVWrVrV1GUC2RR8B7o0+AqQvK/qH2Zwig4G/9dszQg5k2q0D38lw+x9blwEAAAAA9+WQv5Dyez9n6zLwiBFyINNSbl+VrsfaugwAAAA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      "text/plain": [
       "<Figure size 1200x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Plot the distribution of properties by province\n",
    "plt.figure(figsize=(12, 6))\n",
    "sns.countplot(y='Province', data=df, order=df['Province'].value_counts().index, palette='pastel')\n",
    "plt.title('Number of Properties by Province')\n",
    "plt.xlabel('Count')\n",
    "plt.ylabel('Province')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 9. Categorizing ‘Price’ into Ranges\n",
    "\n",
    "We will create price bins to categorize ‘Price’ and facilitate grouping.\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 106,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Define price bins and labels\n",
    "price_bins = list(range(0, 300000, 100000))\n",
    "price_bins += list(range(350000, 1100000, 2000000))\n",
    "price_bins += list(range(1100000, 3000000, 1000000))\n",
    "price_bins += [float('inf')]\n",
    "\n",
    "price_labels = [\n",
    "    f\"{price_bins[i]}-{price_bins[i + 1]}\" if price_bins[i + 1] != float('inf') else f\"{price_bins[i]}+\"\n",
    "    for i in range(len(price_bins) - 1)\n",
    "]\n",
    "\n",
    "# Create 'Price_Group' column\n",
    "df['Price_Group'] = pd.cut(df['Price'], bins=price_bins, labels=price_labels, include_lowest=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 107,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/var/folders/z6/vnwrtwgd7x5chl_2vn910h6r0000gn/T/ipykernel_3763/1048585313.py:3: FutureWarning: \n",
      "\n",
      "Passing `palette` without assigning `hue` is deprecated and will be removed in v0.14.0. Assign the `x` variable to `hue` and set `legend=False` for the same effect.\n",
      "\n",
      "  sns.countplot(x='Price_Group', data=df, order=price_labels, palette='muted')\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1000x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Plot distribution of price groups\n",
    "plt.figure(figsize=(10, 6))\n",
    "sns.countplot(x='Price_Group', data=df, order=price_labels, palette='muted')\n",
    "plt.title('Distribution of Properties by Price Range')\n",
    "plt.xlabel('Price Range')\n",
    "plt.ylabel('Count')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 10. Imputing ‘State_of_the_Building’\n",
    "\n",
    "We aim to fill missing values in ‘State_of_the_Building’ using the mode within groups defined by ‘Province’ and ‘Price_Group’.\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 108,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Combine 'Province' and 'Price_Group' to create groups\n",
    "df['Price_Group_Per_Region'] = df['Province'] + '_' + df['Price_Group'].astype(str)\n",
    "\n",
    "# Calculate mode of 'State_of_the_Building' within each group\n",
    "state_mode_dict = get_grouped_mode(df,'Price_Group_Per_Region','State_of_the_Building')\n",
    "\n",
    "# Impute missing values\n",
    "df['State_of_the_Building'] = df['State_of_the_Building'].fillna(df['Price_Group_Per_Region'].map(state_mode_dict))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 109,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Type_of_Property\n",
      "APARTMENT        0\n",
      "HOUSE        12662\n",
      "Name: Surface_area_plot_of_land, dtype: int64\n"
     ]
    }
   ],
   "source": [
    "group_2 = df.groupby('Type_of_Property')[\"Surface_area_plot_of_land\"].count()\n",
    "group_1 = df.groupby('Type_of_Property')[\"Surface_area_plot_of_land\"].count()\n",
    "print(group_2)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 11. Imputing ‘Number_of_Facades’\n",
    "\n",
    "We will fill missing ‘Number_of_Facades’ values using the median number of facades for each ‘Subtype_of_Property’.\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 110,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Calculate median number of facades for each subtype\n",
    "nb_of_facades_dict = df.groupby('Subtype_of_Property')['Number_of_Facades'].median().to_dict()\n",
    "\n",
    "# Impute missing values\n",
    "df['Number_of_Facades'] = df['Number_of_Facades'].fillna(df['Subtype_of_Property'].map(nb_of_facades_dict))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 13. Removing Outliers\n",
    "\n",
    "We will remove outliers using the Interquartile Range (IQR) method for key numerical columns.\n",
    "Then compare the data.\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 112,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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33uvwBc/x48f1yCOP6PHHH7dvCwwMVGRkpLZv365bb71VUk5fP/roo7rrrrsk5SxC/9RTT2nIkCH234cKFSqof//++uOPP/IcBP76669q2LBhrgmS3N5XX19fh1lhv/zyizZu3Kg33njDfh907txZKSkpmjlzpvr27avmzZtf8Znz2muv6fTp0/r666/tv6ddunTRgw8+qBkzZqhv3772sjKF+R3PzYkTJ645ALPdo/ldlD63++RaFi9enO/4e/funa81Rn777bcryvWYTCbdcMMNmjVrln2Qf/jwYX366ad6+umn7Z+jnTp1kslk0sKFC3XvvfeqcuXKknL+3zF37lz77M7//ve/2rhxo7799lv75+bOnTu1Zs0aSfn/bOvXr5/ef/99paamysvLS1arVevXr1evXr3k4eGhv/76q9Cfz0FBQcrIyNC2bdtcvpwpAKB0YryXg/Ee4z3Ge8aO9zIzM/XFF1+ob9++8vDwkCTdeeed9qRSjRo17J8hHh4eDg9P/vPevXDhgubPn6+7775bL774oqScMYavr69efPFFPfTQQ/alITIzMzVp0qSrrpt34sQJ+fr62j8bcmOL4Wozyi7n4eHh8HvRvHnzax6zZs0a7d27V59++qn9Acwbb7xRgwcP1syZMx0qsfzzcyovMTExuZZZrVevniZMmKBBgwZJUoHe00uXLunNN9+0Pzy6detWffLJJ/rggw/sicmjR4/q1Vdf1fnz5+Xj45Ovz5Hbb79dL7zwgk6ePKmaNWtKktatW6cOHTrIz89P8fHx8vb2dvj/T0REhI4dO6bly5df9X0ICgqSJG3evJmkH8okkn5AGfTEE0/owQcf1MaNG7V582Zt2bJFX375pdauXasXXnjBXoKiIGx/3OSlU6dO6tSpkzIyMnTgwAEdPXpU+/bt0+nTp+Xr6ytJ2r59uyRd8USUrfTBwYMHFRcXp+HDhzs8udS2bVv5+Pho06ZN+R4E5ieevK5t8+bNatasmQICAuxxmM1m3XjjjfYSIs2aNdNHH32k7OxsHTlyREePHtWBAwd06NChXJ8gvJZatWo5DLL9/f3tM2j+aefOnUpPT7+ivEabNm0UGBiorVu36r777itwDFLOF/qJiYl65plnHLbXqVNHYWFhhRrg5sXDw8P+5FZ8fLwOHz6sI0eO2Mv2paen2/etUqWK/Y9ySfY/8FNSUiTl3FuhoaEO6y+EhITY/7C8lpEjR+Z6b/34449XLa0RERGhOXPmaM+ePercubO6dOmi5557Ls/989N3d911l3bs2KERI0Y4POncq1cvjR079orX/Of9ayuPcv78eR06dEhHjx7Vli1bJDm+p1JOWRObqlWrSpLDbDDb78r58+fzvKbjx4/n+SXD5e9rZmamYmNjtWTJEt1zzz368MMP1aJFC23evFkmk0ldunRx+N3p3r27vvjiC+3fvz/Xz5+tW7cqLCzsiiRcv379FBUVpUOHDtkH4YX5Hc+N1Wp1WDsnN7YnTa1W61X3ux4Fif9an902LVq00MSJEyXlPDn/5ptvKiMjQ2+++aYaNGhg3+/XX3+V1WpV9+7dr+ivBQsWaPv27fYvRRo2bGhP+ElStWrVVLlyZfsXZ1LOPXbhwgVJ+f9s69evn+bOnasffvhBvXv31u+//66TJ0/aZyNez+ez7X7K7+AfAAAjMN5jvMd4j/Ge0eO9H3/8UUlJSerRo4f9+O7du2vWrFlasWKFRo8enedr/tOOHTuUmpqa6xhDyikjaUtQ+fr6XjXhJ+Vv3Hat9qKwefNm+fn5qUWLFg7X1a1bN82YMUPnzp2zj5fyO27z8/PTggULJOX02/z583Xs2DFNnz7dob8L8p5WqlTJoVpMtWrVJOV9ryQmJubrc+Tmm2/WxIkTtX79eg0dOlSxsbHavn27fR3FgIAALVmyRFarVSdOnNDRo0d16NAh/f7771fcy/9UoUIFVaxYkXEbyiySfkAZValSJfXt29f+x+aePXs0ZswYvfbaa7rtttvsMzHy61plzrKzs/Xvf/9by5YtU3JysmrUqKHg4GB5enra9zl79qyk//2x+U+29okTJ9q/fL5cQkJCvuPNTzw25cqVuyKOo0eP5vr0lJQz8PD29taiRYv01ltv6ezZs6pWrZpatmwpb29v+xfYBREQEHDFtqpVq+a6wLVtLQDbH2KXq1atWqHOb2Prg7xe+1prnhXUxo0bNXXqVB06dEjly5dX06ZN7f1xedLE29vb4Tjb4MhWjuXcuXO5DkRsT45eS2BgoP1Jscvt37//qse98cYbeuutt/Sf//xHX3/9tcxmszp06KBJkyblOiMsP3139uxZZWVlXfF7YrFYrvgCQ7ry/j127JjGjx+vzZs3y93dXQ0aNFDTpk0lXZmIyu3Jx3++19dy8eLFPI/55/saFhamLl262NcSsP3+WK1WtWrVKtfXSEhIyHUAdO7cOYfkkY3tvb184FrY3/Hcruef6xj8k23Qkd8vIAojP/Hb/PPa81K+fHmHvgoJCVG/fv308MMPa/Xq1fYvWGyfEbYniP8pPj7e/t+53V9Xiye/n21169ZVWFiY1q1bp969e2vdunWqU6eOwz1U2M9nW79fvHjxqvsBAGA0xnuM9wqD8Z4jxnvXltd4zzZLLbfSmCtXrtTjjz+e78Sa7b68fIbu5S7/bMhPCf7AwEBt2rQpz3GdJPtafsU9bktMTMzzsyYxMdGe9MvvuM3Dw8PhXm7VqpX69++vf/3rX1qxYoV91ltB3tO8ZkTmFVN+P0d8fHzUo0cPrVu3TkOHDtX69evl7e1tf0hUkr744gv9+9//VmxsrHx9fdWsWTN5eXnlcfWOvL29GbehzCLpB5Qh8fHx6t+/v5544gl7CQeb5s2b66mnntKIESN0/Phx+yDwn4seF2YBdUl6++239cEHH2jixIm6+eabVaFCBUnSgAED7PtUrFhRUs56VJc/mXXw4EGdPXvW3j527FiFh4dfcY7LZ4wURTx5qVChgsLDw3N9yk7K+SPryy+/1PTp0zVmzBhFRkbavxB/4okntHv37nzHaZPbYvBJSUm5Dpht70NSUpLDDBwp54/G3BIh+WUbZCQlJV3RlpiYWOAvD67m2LFj9lIpCxcuVO3atWUymbRs2TKHxb/zo3LlyrnGbPtjtLhUqFBBY8aM0ZgxY3To0CF99913mj9/viZOnGhfo+xy+em7qlWryt3d/Yrryc7Ovub1ZGdna9iwYXJ3d9fKlSvVrFkzubm56cCBA/YSikWtcuXKBfrioXz58mrQoIGOHj0qKec9LFeunJYsWZLr/nXr1s11e6VKlZSYmHjFdtu2q92r+fkdz0337t21YcMG/f7773kmKb/66it5eXmpY8eO9m1F9TlrU9j4C6JatWoaP368nnjiCU2ZMsVetsX2Ob148eJcB9zXM2guyGdbv379NG3aNF24cEFfffWVvYyNpOv6fLYli4vysw4AgKLCeK9g8eSF8R7jvfxivJf7eC8pKUk//fTTFaVHpZzZjv/+97/1ww8/5GuNc+l/nx0zZ85UvXr1rmjPLbl0Nd27d9dHH32kb7/9Vrfddluu+3z11Vf2faWcRHNxjNvq1avnUM74cvkty3s13t7emj59uu6++25FRUXp448/lslkKvL39HIF+Rzp16+fhg0bpqNHj2rdunW65ZZb7InYbdu26bnnntPgwYP1yCOP2B+OmDFjhn3m+NWcP3+ecRvKLLPRAQAoOdWqVZObm5s++uijXBeAPnTokDw9Pe1fovv4+CguLs5hn/z8jzU327dvV6NGjdS/f3/7gCs+Pl779u2zP53XunVrSdL333/vcOzMmTM1ZcoUNWjQQFWrVtWJEycUFBRk/xcQEKDXX3+9QE8d5ieevISHh9sXA748jjVr1mjlypWyWCzavn27KlasqKFDh9oHgJcuXdL27duv+fq5OXLkiA4ePGj/OT4+Xjt27HBY2NkmJCREHh4eWrt2rcP2bdu26eTJk/ZkhG09s4KoX7++/Pz8rnjt48ePa+fOnXkmOgrjjz/+UFpamoYNG6Y6derYn+a0DQALUh6xXbt22rFjh8MsowMHDtif3isOMTEx6tKli32w0KBBA/3rX/9Shw4ddPLkSUm6YlHx/PSdxWJRq1at9N133zns8/3331+zlNCZM2d0+PBhDRgwQEFBQfYnK3/66SdJ116ovjBq1qyp2NjYfO9/4cIFHT582P45FB4eruTkZFmtVofft3379mnevHl5XnPbtm21Y8eOK9bO++KLL+Tn55dnstB2zmv9juemX79+qlu3rsaPH5/rFzc//PCDPv/8cw0ePNj+tGR+PmfzOl9Rx19QvXr1UufOnbV27Vp7iRZbWaozZ844nPv06dOaNWvWdX3xkt/PNknq06ePrFarZs2apVOnTqlfv372tuv5fLb1VXE+8QsAQGEx3itYPHlhvMd4Lz8Y7+XIbby3Zs0aZWZmasiQIYqIiHD4N2TIEPn4+OiTTz7J8zX/ee+GhITI3d1d8fHxDr+Tbm5u+ve//13gEo4dO3ZU69at9eqrr+Z6j+zevVvvvvuu+vTpY0+IlS9fXmfOnHH4bC2KcVtsbKyqVq3qcF2bNm3Su+++W2TjtuDgYA0cOFA7duzQ559/Lqno39PLFeRzpFOnTqpWrZqWLFmiP//8074kg5RTgjQ7O1ujRo2yJ/yysrL0yy+/SLr6/Xzu3DmlpKQwbkOZxUw/oAyxWCx6+eWXNWLECPXv31/33XefGjZsqJSUFG3atEnLli3TE088YX/6rFu3blq4cKEWLlyokJAQff/99/r1118Lde7g4GDNnz9fb7/9tkJDQ3X06FEtXLhQ6enp9lJzTZs2Va9evfTaa68pNTVVzZo1008//aQffvhBc+fOlcVi0VNPPaXx48fLYrGoW7du9hrl8fHxeZZEKGw8eXnwwQe1Zs0aPfjgg3r44YdVuXJlrV+/Xp9++qmioqLsr//xxx9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ulk4kn9DdH92tTY9u0s6dO6/5HjvTfYXCox9LP/qw9KMPXQP9WPrRh6ULST8XZlvTj/KeAAAAAJxNYGCgtmzZokqVKslkMqlZs2bKzs7WmDFjFB4efkUCLz09XV5eObPLPD09c2339vYuUAxBQUGyWPI366u42RJJfn5+8sn0KdCx5dzLScq5nsLy9/eXT0be501KTtLZ9LMym8wKbxCuKt5VHI4tiKreVSXlXGv5jPIlfqx3RW9Zva8yZe8yHep10Kd7PtXvp37XxfSLV32Ps7KytHv3bqe6r1Bw9GPpRx+WfvSha6AfSz/60LnY+uNanCLpl56ersjISL300kuKiIiQJO3cuVPTp0/X33//LX9/fw0dOlR33XWX/ZhffvlFU6dO1fHjxxUSEqIpU6aodu3a9vYPPvhA7733ni5evKjevXvrpZdesg8A09LSNHHiRP33v/+Vl5eXHn74YT388MMle9ElgPKeAAAAAJyZr6+vw88NGzZUWlqa/Pz8lJSU5NCWlJRkTy4FBATk2u7n51eg81ssFqf7AsNkMslsNhfoGNv+13MtZrP5qufdfyantGp93/oq51HOYd/CxnutczrDsU2qNVEV7yo6nXJai3cu1ojwEdc8xhnvKxQc/Vj60YelH33oGujH0o8+LF0K9hdyMUhLS9PTTz9tX5tByinT8a9//Uvh4eH67LPPNHr0aL3yyiv68ccfJeWUgRkxYoQiIyO1cuVKValSRY8//ris1pwn9b7++mvNnTtXkyZN0uLFixUdHa3XXnvN/vozZszQH3/8ocWLF2vChAmaO3euvvrqqxK97pJAeU8AAAAAzmrjxo2KiIhQSkqKfdtff/0lX19ftW7dWjt27LCP8axWq37//XeFhIRIkkJCQrR9+3b7cbGxsYqNjbW3o+jtO7VPknRD1RsMjqRkmU1mRQTmPJz85pY3lW0t2DqCAAAAQEkyNOl34MABDRw4UMeOHXPY/u2336patWp6+umnVa9ePd16662644479OWXX0qSVqxYoZYtW+rhhx9W48aNNW3aNMXExGjr1q2SpCVLlmjIkCHq1q2bgoODNXHiRK1atUopKSlKTk7WihUrNG7cOLVo0UI9e/bU0KFDtWzZshK//uJmK+/JTD8AAAAAziYsLEyenp568cUXdejQIW3YsEEzZszQ0KFD1atXL50/f15TpkzRgQMHNGXKFKWkpKh3796SpEGDBmnNmjVasWKF9u7dq7Fjx6pr164O1V9QdJIzknX83HFJZS/pJ0mh1UPl7eatA6cPaO2+tUaHAwAAAOTJ0KTf1q1bFRERoeXLlzts79y5s6ZNm3bF/hcv5iwqHh0drTZt2ti3e3t7q0WLFvYFtXfv3u3QHhoaqoyMDO3du1d79+5VZmamwsLC7O2tW7dWdHR0gRYeLw2Y6QcAAADAWfn4+Oi9997T6dOn1b9/f40bN0533323hg4dKh8fHy1cuFDbt29XZGSkoqOj9fbbb6tcuZy168LCwjRp0iTNmzdPgwYNUqVKlXIdQ6Jo7D+1X1ZZFVA+QL5evkaHU+I8LB4KDwyXJL3x6xsGRwMAAADkzdA1/e69995ct9eqVUu1atWy/3zq1CmtW7dOo0aNkpRT/vOfC4VXrVpVcXFxOn/+vNLS0hza3dzc5Ovrq7i4OJnNZlWuXFkeHh729mrVqiktLU1nz55VlSpVlF+2hdadgS2Wy2MyySRJysjKcKpYXV1ufQFj0BfOg75wHvSF86AvnAv94Tzoi+LhrO9n48aNtWjRolzbgoOD9dlnn+V5bGRkpCIjI4srNFzGVtqzSdUmBkdinA61O2jT8U368ciP2hG7Q2E1wq59EAAAAFDCDE365UdqaqpGjRqlatWq6e6775YkpaSkOCTtJMnDw0Pp6elKTU21/5xbu9VqzbVNktLT0wsU2+7duwu0f0m4PKbYk7GSpFOnT2nnzp0GRVR2OeP9UVbRF86DvnAe9IXzoC+cC/3hPOgLwDlkZmfqwJkDkspmaU8bXy9fDWwxUB/t/khv/PqGlty5xOiQAAAAgCs4ddLv0qVLevzxx3XkyBF99NFH8vb2liR5enpekaBLT09XxYoV5enpaf/5n+3e3t7KysrKtU2SvLy8ChRfUFCQLBZLgY4pLrayppfHtDVrq/SHVKFSBYWGhhobYBmSW1/AGPSF86AvnAd94TzoC+dCfzgP+qJ42N5XoKCOnD2i9Kx0+Xj4qGaFmkaHY6in2j2lj3Z/pI//+FjTbpqmwIqBRocEAAAAOHDapN/Fixc1dOhQHTt2TIsXL1a9evXsbQEBAUpKSnLYPykpSc2aNZOvr688PT2VlJSkhg0bSpIyMzN19uxZ+fn5yWq16syZM8rMzJSbW87lJyYmysvLSxUrVixQjBaLxam+iDCbzQ4xubu5S8pZ08+Z4iwrnO3+KMvoC+dBXzgP+sJ50BfOhf5wHvQF4BxspT1vqHqDTCaTwdEYq03NNupcp7M2Htuoeb/N09SbphodEgAAAODAbHQAucnOztbIkSN14sQJffjhh2rcuLFDe0hIiLZv327/OSUlRXv27FFISIjMZrOCgoIc2nfu3Ck3Nzc1bdpUzZo1k5ubm0O5y+3btysoKEhms1O+HfnWvEVzhy9G3Mw5Sc2s7Guv35GffQAAAAAAZYfVatXfp/6WVLbX87vcU+2ekiQt3L5Ql9IvGRwNAAAA4MgpZ/qtXLlSW7Zs0YIFC1SxYkUlJiZKktzd3eXr66v+/fvrvffe09tvv61u3bpp3rx5qlWrliIiIiRJ9957r8aPH68bbrhB/v7+evnllzVw4EB7edA77rhDL7/8sqZOnaqEhAS9//77mjZtmmHXW1Q8PTw169dZSstKkyT9Hvu7JOnA6QOasWlGnsd5u3lrVMSoEokRAAAAAFA6xF+K1/m083Izu6m+b32jw3EK/Zr0U4PKDXTozCEtiV6ix9o+5tDODGUAAAAYySmTfl9//bWys7M1fPhwh+3h4eH68MMPVatWLc2ZM0dTp07VvHnzFBYWpnnz5tlLjdx6662KiYnR+PHjlZ6erptvvlljxoyxv05UVJRefvllDRkyRD4+Pho1apRuvvnmEr3G4pKSkaLUrFRJUkZWhqSchdeTM5KNDAsAAAAAUMrYZvk1rNxQ7hZ3g6MxlrvZXVnZWbKYLXoi4gk98dUTenPLmxreZrjMppyqQRaLRaGhobkebzsWAAAAKE5Ok/T7+++/7f/93nvvXXP/Ll26qEuXLnm2Dxs2TMOGDcu1zdvbW6+++qpeffXVggdaitgGHtnWbIMjAQAAAACUNpev51fWuZndZDFbNGfLHJ1LPScvNy/tO7VPj3zxiJpVayYpZ6mShIQE+fv7OywfQnUdAAAAlJTSvYgdrso285GkHwAAAACgIJIzknXywklJUuMqjQ2OxnmkZKYoy5qlsOphkqSNRzcqOSPZ/u9i2kWHn5MzkpWSmWJw1AAAACgrSPq5MNtMP6vVanAkAAAAAIDS5OCZg5KkgPIBquBZweBonE/bmm0l5bxPiZcSDY4GAAAAyEHSz4XZy3uKmX4AAAAAgPw7eDon6dewckODI3FOlb0rq0nVJpKkrSe3GhwNAAAAkIOknwszifKeAAAAAICCsVqtOnD6gCSpUZVGBkfjvCICIyRJ0XHRSs1MNTgaAAAAgKSfS6O8JwAAAACgoOIvxetSxiW5m91Vu1Jto8NxWvV868m/vL8ysjO0I26H0eEAAAAAJP1cmb28JzP9AAAAAAD5ZJvlV9+3vtzMbgZH47xMJpPCA8MlSVtjtjL2BgAAgOFI+rkwkn4AAAAAgII6eOb/1/Orwnp+1xLsHywvNy+dTT2r/af3Gx0OAAAAyjiSfi7MZGJNPwAAAABA/qVnpevYuWOSWM8vP9wt7mpVo5Uk6beTvxkcDQAAAMo6kn4uzL6mn1jTDwAAAABwbYfPHFa2NVuVvSqrincVo8MpFdrWbCuTTDp89rBOp502OhwAAACUYST9XBjlPQEAAAAABXHgTM56fpT2zD9fL181rdZUkvTn2T8NjgYAAABlGUk/F2YS5T0BAAAAAPl38HTOen6NKlPasyAiAiMkSfsv7FdKRorB0QAAAKCsIunnwuzlPa2U9wQAAAAAXN3plNM6k3pGZpNZ9XzrGR1OqVKnUh0FlA9QljVLO+J3GB0OAAAAyiiSfi6M8p4AAAAAgPw6cDqntGedinXk6eZpcDSli8lkUnjNcEnStpPbGIcDAADAECT9XBhJPwAAAABAfh0+c1iS1KBKA4MjKZ1a+LWQp9lT59LO6e9TfxsdDgAAAMogkn4uzGTKWdPPKsp7AgAAAADylm3N1pFzRyRJDXxJ+hWGu8VdzSo1kyRtObHF4GgAAABQFpH0c2HM9AMAAAAA5EfM+RilZqbK0+KpGhVqGB1OqdWsUjOZZNLRc0cVdzHO6HAAAABQxpD0c2Ek/QAAAAAA+XHgTM56fvV869nHkig4H3cfNauWM9tva8xWg6MBAABAWcNf8i7MpJzyniT9AAAAAABXc+B0TtKvfuX6BkdS+oXXDJck7U7YreSMZIOjAQAAQFlC0s+FXf50ptXKun4AAAAAgCulZqbqyNkjkljPryjUqlhLNXxqKDM7U7/H/m50OAAAAChDSPq5sMuTfsz2AwAAAADkZvPxzcrMzpSPh4+qlatmdDilnslkUkRghCTpt5O/KSs7y+CIAAAAUFaQ9HNhJpPJ/t9WMdMPAAAAAHCl7w5/J0mq71vfYRyJwmvh30Ll3cvrfNp5/Zn4p9HhAAAAoIwg6efCmOkHAAAAALiWy5N+KBpuZje1rtFakrTp+CaDowEAAEBZQdLPhZH0AwAAAABczfm08/ot5jdJUv3KJP2KUpuabWQ2mXXk7BHW9gMAAECJIOnnwi5P+lmtlPcEAAAAADjacGSDsqxZqupdVb5evkaH41IqeFZQc7/mkqQ5W+cYHA0AAADKApJ+Lsyk/63FwEw/AAAAAMA/2Up7NqzS0OBIXFNEYIQk6aPdHynhUoLB0QAAAMDVkfRzYZcvwE7SDwAAAADwT98f/l6S1KhKI4MjcU21KtZS7Yq1lZ6Vrre3v210OAAAAHBxJP1cnK3Ep1WU9wQAAAAA/E/CpQTtTtgtSWpYmZl+xaVj7Y6SpPm/zVdGVobB0QAAAMCVkfRzcbakHzP9AAAAAACX+/HIj5Kk4IBg+Xj4GBuMCwsKCFJ1n+qKvRirVX+tMjocAAAAuDCSfi6OpB8AAAAAIDe2pF+3et2MDcTFuZnd9GjrRyVJs7fMNjgaAAAAuDKSfi7OpJx1/Uj6AQAAAAAut+HoBklSl7pdDI7E9T3a5lG5m921+cRm/Rbzm9HhAAAAwEWR9HNx9jX9rKzpBwAAAADIkXApQXsS90iSbqx7o8HRuL4AnwDd0/IeSdLsrcz2AwAAQPEg6efiKO8JAAAAAPinn47+JEkK8g9S1XJVDY6mbBgVPkqStPyP5Yq7GGdwNAAAAHBFJP1cnMlEeU8AAAAAgCPben6U9iw5bQPbqn2t9srIztDCbQuNDgcAAAAuiKSfi7OX9xTlPQEAAAAAOWzr+XWt19XYQMqY0RGjJUkLti1Qela6wdEAAADA1ZD0c3GU9wQAAAAAXC4pOUl/JPwhifX8Slr/Zv1Vs0JNxV+K16d/fmp0OAAAAHAxJP1cnEmU9wQAAAAA/I9tPb8Wfi3kV97P4GjKFneLux5v87gkadaWWbJaqcoDAACAokPSz8XZy3sykAAAAAAASNpwJKe0J+v5GWNY62HytHhq28lt2hKzxehwAAAA4EJI+rk4ynsCAAAAAC7349EfJbGen1H8yvtpUNAgSdLsLbMNjgYAAACuhKSfiyPpBwAAAACwOZ1yWrvjd0tiPT8jjQofJUlasWeFTl44aXA0AAAAcBUk/VycycSafgAAAACAHBuPbpRVVjWt1lQBPgFGh1NmtarRSp3qdFJmdqYW/LbA6HAAAADgIkj6uTj7mn5iTT8AAAAAKOt+PPKjJKlr3a6GxgHpiYgnJEkLty9UamaqwdEAAADAFZD0c3FmUd4TAAAAAJBjw9ENkqQu9boYHAnuaHqHalWspcTkRC3/Y7nR4QAAAMAFkPRzcZT3BAAAAABI0tnUs9oZt1OS1KUuST+juZndNKLtCEnSrC2zZLVSoQcAAADXh6Sfi7OX92TwAAAAAABl2ubjm2WVVY2qNFKNCjWMDgeShrYaKi83L+2I26Ffjv9idDgAAAAo5Uj6uThb0o+ZfgAAAABQtm08tlGS1KlOJ4MjgU21ctV0X9B9knJm+wEAAADXg6Sfi7Mn/UTSDwAAAADKMlvSr3OdzgZHgsuNjhgtSVr912odP3fc4GgAAABQmpH0c3Gs6QcAAAAASM1M1daYrZJI+pU0d7O7srKz8mwPDghW13pdlWXN0oJtC65ov9qxAAAAwOXcjA4Axcss1vQDAAAAgLLut5jflJ6VroDyAWpUpZHR4ZQpbmY3WcwWzdkyRymZKbnuU7tibUk5JT7Lu5eXu8VdkuTt5q1REaNKLFYAAACUbiT9XBxr+gEAAAAAfj72s6Sc9fxsFWFQslIyU5SckZxrWz3feqrkWUnn0s5pa8xWhdUIK+HoAAAA4Aqcorxnenq6+vbtqy1btti3HT9+XA8++KBCQ0PVp08f/fzzzw7H/PLLL+rbt69CQkL0wAMP6Phxx7r3H3zwgTp37qywsDC98MILSkn539N0aWlpeuGFF9SmTRt16tRJ77//fvFeoIEo7wkAAAAAYD0/52Y2mdU2sK0kaUvMFqr1AAAAoFAMT/qlpaXp6aef1v79++3brFarRowYoWrVqmnVqlW6/fbbNXLkSJ08eVKSdPLkSY0YMUKRkZFauXKlqlSposcff9z+R/HXX3+tuXPnatKkSVq8eLGio6P12muv2V9/xowZ+uOPP7R48WJNmDBBc+fO1VdffVWyF15CbDP9GDAAAAAAQNmUlZ2lTcc3SZI61yXp56xaVW8ld7O74i/F6+i5o0aHAwAAgFLI0KTfgQMHNHDgQB07dsxh+6+//qrjx49r0qRJatiwoYYPH67Q0FCtWrVKkrRixQq1bNlSDz/8sBo3bqxp06YpJiZGW7fmLEq+ZMkSDRkyRN26dVNwcLAmTpyoVatWKSUlRcnJyVqxYoXGjRunFi1aqGfPnho6dKiWLVtW4tdfEijvCQAAAABl2+6E3Tqfdl4VPCooJCDE6HCQB293bwUHBEuSfj3xq8HRAAAAoDQyNOm3detWRUREaPny5Q7bo6Oj1bx5c5UrV86+rXXr1tq5c6e9vU2bNvY2b29vtWjRQjt37lRWVpZ2797t0B4aGqqMjAzt3btXe/fuVWZmpsLCwhxeOzo6WtnZrpcYs5f3lOtdGwAAAADg2jYezSnt2aF2B1nMFoOjwdVEBEZIkv4+9bdOJZ8yOBoAAACUNm5Gnvzee+/NdXtiYqL8/f0dtlWtWlVxcXHXbD9//rzS0tIc2t3c3OTr66u4uDiZzWZVrlxZHh4e9vZq1aopLS1NZ8+eVZUqVfIdf1ZWVr73LW5ZWVmyWCyyWq0OyUuT/j/pl52dZ1LTtt2Zrqc0s72PvJ/Goy+cB33hPOgL50FfOBf6w3nQF8WD97Ns+/n4z5KkTnU6GRwJrsWvvJ9uqHKD9p3ep80nNqt2pdpGhwQAAIBSxNCkX15SUlIcknKS5OHhofT09Gu2p6am2n/Ord1qtebaJsn++vm1e/fuAu1fnCwWi0JDQ5WYmKiLaRft21NTct6PcxfO2ZOm/+Tj6SMp53r4MqDoONP9UdbRF86DvnAe9IXzoC+cC/3hPOgLoGhYrVb7TL/OdVjPrzRoX7u99p3ep+j4aPVp3MfocAAAAFCKOGXSz9PTU2fPnnXYlp6eLi8vL3v7PxN06enpqlixojw9Pe0//7Pd29tbWVlZubZJsr9+fgUFBclicY7SKLZknZ+fn3wyfezbfS74SOel8uXLq3r16rkeW849p4xqUFBQ8QdaBthKzDrT/VFW0RfOg75wHvSF86AvnAv94Tzoi+Jhe1+d1bBhw1SlShVNnz5dkrRnzx5NmDBB+/btU6NGjTRx4kS1bNnSvv/atWv15ptvKjExUZ06ddIrr7xSoKotZcmhM4cUezFW7mZ3hQeGGx0O8qFupbqqWaGmTl44qc0nNhsdDgAAAEoRp0z6BQQE6MCBAw7bkpKS7CU7AwIClJSUdEV7s2bN5OvrK09PTyUlJalhw4aSpMzMTJ09e1Z+fn6yWq06c+aMMjMz5eaWc/mJiYny8vJSxYoVCxSnxWJxui8iTCaTzOb/LdVo+2+rrA7bL2fb7mzXUto54/1RVtEXzoO+cB70hfOgL5wL/eE86IuyY926ddqwYYPuvPNOSVJycrKGDRum2267TdOnT9fHH3+s4cOH65tvvlG5cuW0a9cujRs3ThMnTlTTpk01ZcoURUVFaeHChQZfiXPaeCxnll/bwLbydvc2OBrkh8lkUvta7bXqr1XafHyzUjJS6DsAAADkS+5ZIIOFhITozz//tJfqlKTt27crJCTE3r59+3Z7W0pKivbs2aOQkBCZzWYFBQU5tO/cuVNubm5q2rSpmjVrJjc3N+3cudPhtYOCgvJMipVmJlPOmn5Wq9XgSAAAAADA0dmzZzVjxgyHqiPr16+Xp6enxo4dq4YNG2rcuHEqX768vvrqK0nS0qVL1bt3b91xxx1q2rSpZsyYoQ0bNuj48eNGXYZT+/nY/6/nV5v1/EqT5n7N5evlq0sZl7QkeonR4QAAAKCUcMosV3h4uGrUqKGoqCjt379fb7/9tnbt2qUBAwZIkvr376/ff/9db7/9tvbv36+oqCjVqlVLERERkqR7771X7733nr799lvt2rVLL7/8sgYOHChvb295e3vrjjvu0Msvv6xdu3bp22+/1fvvv68HHnjAyEsuNmZTThdnK9vgSAAAAADA0auvvqrbb79djRo1sm+Ljo5W69at7Q8wmkwmtWrVyv7gZnR0tNq0aWPfv0aNGqpZs6aio6NLNPbSYtPxTZKkTnVI+pUmZpNZ7QLbSZJe3/y6sq2M6QEAAHBtTpn0s1gsmj9/vhITExUZGakvvvhC8+bNU82aNSVJtWrV0pw5c7Rq1SoNGDBAZ8+e1bx58+yDwltvvVXDhw/X+PHj9fDDDys4OFhjxoyxv35UVJRatGihIUOGaOLEiRo1apRuvvlmQ661uJn/v4sZIAAAAABwJps3b9a2bdv0+OOPO2xPTEy0L+1gU7VqVcXFxUmSEhISrtqO/zmVfEp7k/ZKktrXbm9wNCiosBph8nbz1v7T+/Xl318aHQ4AAABKAadZ0+/vv/92+Llu3bpaunRpnvt36dJFXbp0ybN92LBhGjZsWK5t3t7eevXVV/Xqq68WLthSxDbTj/KeAAAAAJxFWlqaJkyYoPHjx8vLy8uhLSUlRR4eHg7bPDw8lJ6eLklKTU29antBZGVlFfiY4pKVlSWLxSKr1ars7II9tGnb/5/Xs+lYziy/G6rcoMqelfO8XovFouzs7AKd9/J9CxtvQc/p7Mfaxt3/7MPCntfN5KaIwAj9ePRHvfbLa+rbuG+BYkbh2H5PnOnzAQVDH5Z+9KFroB9LP/rQueS3H5wm6YfiYZv9yEw/AAAAAM5i7ty5atmypTp37nxFm6en5xUJvPT0dHtyMK92b2/vAsexe/fuAh9TXCwWi0JDQ5WYmKiLaRcLdKyPp4+knOu5/MuANXvXSJKalGvisK59budNSEgo0Hlt55RyZl8WJJllrZCTHEtMTNSF1Av5Pq60HBsfH19k523s1VibzJu06fgmffjDhwqqHHTtg1AknOnzAYVDH5Z+9KFroB9LP/qwdCHp5+Lsa/qR9AMAAADgJNatW6ekpCSFhYVJkj2J9/XXX6tv375KSkpy2D8pKcle0jMgICDXdj8/vwLHERQUJIvFUphLKHK2ZJ2fn598Mn2usbejcu7lJOVcz+UO7T4kSbo1+FaFhoZe9TX8/f3lk5H/89rOaTu2IKp6V5WUc63lM8q7zLFWq1Xx8fEKCAiwP4B7vect515O93vfr0U7F2nt6bUa3G1wgY5HwWVlZWn37t1O9fmAgqEPSz/60DXQj6UffehcbP1xLST9XBxJPwAAAADO5sMPP1RmZqb955kzZ0qSnn32Wf3222965513ZLVaZTKZZLVa9fvvv+vRRx+VJIWEhGj79u2KjIyUJMXGxio2NlYhISEFjsNisTjdFxgmk0lms7lAx9j2v/xaMrMztfXkVklSp7qdrnmdZrO5QOe9fN/CxlvQczr7sbbZjv/sw+s97zPtn9GinYv02d7PdOTcETWs0rBAr4HCccbPBxQMfVj60YeugX4s/ejD0qVgf22i1LE9XWgVa/oBAAAAcA6BgYGqW7eu/V/58uVVvnx51a1bV7169dL58+c1ZcoUHThwQFOmTFFKSop69+4tSRo0aJDWrFmjFStWaO/evRo7dqy6du2q2rVrG3xVzmVX/C4lZySrkmclNfNrZnQ4uA4t/Fuod6PeyrZm681f3zQ6HAAAADgxkn4uzjbTz7agOAAAAAA4Mx8fHy1cuNA+my86Olpvv/22ypXLKScZFhamSZMmad68eRo0aJAqVaqkadOmGRy18/nl+C+SpHa12tnHhSi9nu3wrCTp/Z3v61TyKYOjAQAAgLOivKeLM4vyngAAAACc2/Tp0x1+Dg4O1meffZbn/pGRkfbynsjd5hObJUkdancwOBIUhW71uimseph2xO3Qgm0L9OKNLxodEgAAAJwQj/u5ONb0AwAAAICyxzbTj6SfazCZTBrTYYwkac7WOUrNTDU4IgAAADgjkn4uzramH0k/AAAAACgbTl44qSNnj8hsMis8MNzocFBEBjQfoDqV6ijhUoIW7VhkdDgAAABwQiT9XBxr+gEAAABA2bL5eE5pzyD/IFX0rGhwNCgq7hZ3je0wVpI045cZysjKMDgiAAAAOBuSfi7OXt5TzPQDAAAAgLLAVtqzfa32BkeCovZw2MPyL++vI2eP6JM/PjE6HAAAADgZkn4ujvKeAAAAAFC2bD6RM9OP9fxcj7e7t55u97QkadrP0xjrAwAAwAFJPxdHeU8AAAAAKDtSM1O1PXa7JJJ+ruqxto+pkmcl/ZX0lz7f+7nR4QAAAMCJkPRzceb/72Ke/gMAAAAA1/d77O9Kz0qXf3l/NajcwOhwUAwqelbUqPBRkqSpG6fykC8AAADsSPq5OMp7AgAAAEDZYVvPr0PtDvbxIFzPE+2eUDn3ctoeu13fHPrG6HAAAADgJEj6uTjKewIAAABA2WFL+rWv1d7gSFCcqpWrpuGth0vKme0HAAAASCT9XJ4t6cdMPwAAAABwbVarVZtPbJbEen5lwTPtn5G72V0bjm7QpmObjA4HAAAAToCkn4uzJ/1E0g8AAAAAXNmRs0cUdzFO7mZ3ta7R2uhwUMwCKwbqwdAHJUlTf2a2HwAAAEj6uTyTWNMPAAAAAMoCW2nPVjVaydvd2+BoUBLGdhwrs8ms9fvXa2fcTqPDAQAAgMFI+rk41vQDAAAAgLLBlvSjtGfZ0ahKI93T8h5J0rSfpxkcDQAAAIxG0s/FsaYfAAAAAJQNv5wg6VcWPd/xeUnSij9XaN+pfQZHAwAAACMVedLv9OnTRf2SuA4mE+U9AQAAAJQMxoPGuZh+Ubvid0mS2tdqb3A0KElBAUHq16SfrLLq1Z9fNTocAAAAGKhQSb9mzZrlOpiLiYnRTTfddN1BoejYy3uK8p4AAAAArh/jQee0NWarsq3ZqlOpjgIrBhodDkpYVKcoSdKSXUt07Nwxg6MBAACAUdzyu+Pnn3+u1atXS8pZH27EiBFyd3d32CchIUF+fn5FGyGuC+U9AQAAAFwvxoPOj/X8yrZ2tdqpe/3u+v7w95qxaYbm9plrdEgAAAAwQL6Tfj179tSJEyckSVu3blVoaKjKly/vsE+5cuXUs2fPoo0Q18UkynsCAAAAuD6MB52fPelXi6RfWfXSjS/p+8Pf653f39FzHZ9T7Uq1jQ4JAAAAJSzfSb/y5ctr5MiRkqTAwED16dNHnp6exRYYigYz/QAAAABcL8aDzi3bmq3NJzZLYqZfWda1Xld1q9dNPxz5QVM3TtWCvguMDgkAAAAlLN9Jv8vdeeedOnr0qP744w9lZGRc0X7HHXdcb1woIvY1/ays6QcAAADg+jEedD6JyYk6m3pW3m7eCg4INjocGGhi14n64YMf9N6O9/Rcp+dUz7ee0SEBAACgBBUq6ffuu+9q5syZqlSp0hUlXUwmE4M8J8JMPwAAAABFifGg8zl69qgkKTwwXO4W92vsDVfWuW5n9WjQQ98e+lZTfpqid/q9Y3RIAAAAKEGFSvq9//77GjNmjB555JGijgdFzGRiTT8AAAAARYfxoPM5ei4n6UdpT0g5s/2+PfStPoj+QFGdo9SgcgOjQwIAAEAJMRfmoLS0NN18881FHQuKgb28pyjvCQAAAOD6MR50PsfOHZNE0g85OtTuoFsa3qLM7ExN/mmy0eEAAACgBBVqpt9tt92mjz76SGPHjrXPJINzorwnAAAAgKLEeNC5pGSkKOFSgiRpd/xu7UncU6DjK3tV1r9a/6s4QoOBJnadqK8Pfq0l0UsU1SlKjas2NjokAAAAlIBCJf0uXryolStXau3atapVq5bc3R3XDFiyZEmRBIfrZxLlPQEAAAAUHcaDzuXE+ROSpMZVGstitig5I7lAx3u7eRdHWCgi7mZ3ZWVnyWK2FOi4iFoRurXxrVq3f51e+ekVLbmT30sAAICyoFBJv3r16unRRx8t6lhQDOzlPa2U9wQAAABw/RgPOpeYCzGSpHa12hkcCYqDm9lNFrNFc7bMUUpmSoGObVatmdbtX6dlu5dpXOdxalKtSTFFCQAAAGdRqKTfyJEjizoOFJPL1/SzWq2U3wEAAABwXRgPOpeY8zlJv4jACF3KuGRwNCguKZkpBZ7F6VfeT/2a9NMXf3+hST9N0rLIZcUUHQAAAJxFoZJ+UVFRV22fNm1aoYJB0bMl/aScxJ+t3CcAAAAAFAbjQedhtVrtM/0iakXo+8PfGxwRnM3LXV7WF39/oY93f6xxncepuV9zo0MCAABAMTJfe5dry8zM1OHDh7V+/XpVqVKlKF4SReTymX2s6wcAAACgqDEeNM7plNNKyUyRm9lNwQHBRocDJ+NudldwQLAim0XKKqsmbpiY72OzsrOKMTIAAAAUl0LN9Mvryc13331X+/btu66AULQun+lH0g8AAADA9WI86Dxss/xqVawlD4uHwdHA2djWA2xcpbEk6dM/P1XNCjVVw6fGVY/zdvPWqIhRJREiAAAAiliRzPSz6dWrl7755puifElcJ4fynlargZEAAAAAcGWMB0veifMnJEn1KtUzNhA4tSreVexlPb8+8LWSM5Kv+i8lM8XgiAEAAFBYRZb0S05O1qeffqrKlSsX1UuiCFy+hh8z/QAAAAAUB8aDxrDN9KvrW9fgSODsutTtIkn6K+kvxZyPMTgaAAAAFJdClfds2rSpw1pxNp6enpo8efJ1B4WiQ3lPAAAAAEWJ8aBzyMzOVNzFOEnM9MO1+Zf3V3BAsHbF79K3h7/VA8EP5Pp7DAAAgNKtUEm/JUuWOPxsMpnk7u6uRo0aycfHp0gCQ9G4/I94kn4AAAAArhfjQecQeyFW2dZslXMvpyreVYwOB6VAt3rd9GfCnzpy9ogOnjmoRlUaGR0SAAAAilihynuGh4crPDxc/v7+unDhgs6ePSsfHx8GeE7KNtvPKtb0AwAAAHB9GA86B1tpz1oVajFjC/ni6+WrtoFtJUnfHvpWVivfEQAAALiaQs30O3/+vKKiovTdd9+pUqVKysrK0qVLl9S2bVvNmzdPFSpUKOo4cR3MJrOyrdnM9AMAAABw3RgPOgfbumyBFQMNjgSlSec6nbUjdofiL8Vrd8JuBQcEGx0SAAAAilChZvpNnjxZcXFxWr9+vbZs2aJt27bpyy+/VHJysqZNm1bUMeI6mZTz1CdJPwAAAADXi/Ggczhx4YQkKbACST/kXzn3cupYp6Mk6fvD3yszO9PgiAAAAFCUCpX0+/777/Xyyy+rQYMG9m2NGjXS+PHj9d133xVZcCga9vKelO4AAAAAcJ0YDxrvUvolnU09K4mZfii4doHtVMGjgs6lndO2k9uMDgcAAABFqFBJP09PT5nNVx5qMpmUlZV13UGhaNmSfsz0AwAAAHC9GA8az7aeX7Vy1eTl5mVwNCht3C3u6lqvqyTpp6M/KTUz1diAAAAAUGQKlfTr3r27Jk6cqGPHjtm3HTlyRJMnT1aXLl2KLDgUDdui7iT9AAAAAFwvxoPGO3E+p7RnrQq1DI4EpVVo9VBVK1dNKZkp2nR8k9HhAAAAoIgUKuk3ZswYeXp66pZbblFERIQiIiLUq1cvVapUSS+99FJRx4jrxEw/AAAAAEWF8aDxbDP9KO2JwjKbzLqp/k2SpF9P/KoLaRcMjggAAABFwa2gBxw9elQ1a9bUhx9+qL///lsHDx6Up6en6tWrp4YNGxZHjLhO9jX9xJp+AAAAAAqP8aDxrFarYs7/f9KvAkk/FF6Tqk1Uu2JtHT9/XD8e/VG33XCb0SEBAADgOuV7pp/VatXkyZPVu3dv7dixQ5LUpEkT9enTR6tWrVLfvn01ffp0Wa1Fl1iKjY3V8OHD1apVK3Xv3l0ffPCBvW3Pnj266667FBISov79++uPP/5wOHbt2rXq0aOHQkJCNGLECJ0+fdrhWmbOnKl27dopPDxcM2bMUHa2686CY6YfAAAAgOthxHgQuTuVckppWWlyM7spwCfA6HBQiplMJvVo0EOStCN2h5KSkwyOCAAAANcr30m/JUuWaP369Zo3b57Cw8Md2ubPn6958+bps88+08cff1xkwT355JMqV66cVq9erRdeeEFvvvmmvvnmGyUnJ2vYsGFq06aNVq9erbCwMA0fPlzJycmSpF27dmncuHEaOXKkli9frvPnzysqKsr+uosWLdLatWs1d+5czZ49W19++aUWLVpUZHE7G5NY0w8AAABA4RkxHkTubOv51fSpaX/AEyisOpXqqEnVJrLKqu8Of2d0OAAAALhO+R4hfPrpp3rppZfUrVu3XNu7d++uZ599tsgGeefOndPOnTv12GOPqV69eurRo4c6d+6szZs3a/369fL09NTYsWPVsGFDjRs3TuXLl9dXX30lSVq6dKl69+6tO+64Q02bNtWMGTO0YcMGHT9+XFLOgHX06NFq06aN2rVrp2effVbLli0rkridkb28J0/dAgAAACiEkh4PIm+s54eidlP9m2SSSXuT9ur4ueNGhwMAAIDrkO+kX0xMjIKDg6+6T7t27eyJtevl5eUlb29vrV69WhkZGTp06JB+//13NWvWTNHR0WrdurVMppwZbCaTSa1atdLOnTslSdHR0WrTpo39tWrUqKGaNWsqOjpa8fHxio2NVdu2be3trVu3VkxMjBISEookdmdDeU8AAAAA16Okx4PIm22mH0k/FBW/8n4KrR4qSfr64Nd8dwAAAFCK5TvpV7VqVcXExFx1n7i4OPn6+l5vTJIkT09PjR8/XsuXL1dISIh69+6tG2+8UXfddZcSExPl7+9/RXxxcXGSpISEhDzbExMTJcmhvVq1avb4XZEtOcof7gAAAAAKo6THg8hdRlaG4i/GS5JqVahlcDRwJd3qdZOHxUMxF2K0M26n0eEAAACgkNzyu2PPnj01Z84cvf/++3J3d7+iPTMzU3PnzlWnTp2KLLiDBw+qW7dueuihh7R//3698sorat++vVJSUuTh4eGwr4eHh9LT0yVJqampebanpqbaf768TZL9+PzKysoq8DUVl6ysLFksFlmtVmVnOyb3zP+f283KzrqiTZJ9mzNdT2lmex95P41HXzgP+sJ50BfOg75wLvSH86Avisf1vp9GjAdxpdiLsbLKKh8PH1X0rGh0OHAhFTwrqHOdzvru8Hf6z4H/6GL6Rfl4+BgdFgAAAAoo30m/xx9/XAMGDFBkZKQGDx6sli1bqkKFCjp37pz+/PNPLV26VJcuXdKMGTOKJLDNmzdr5cqV2rBhg7y8vBQUFKT4+HgtWLBAtWvXviJBl56eLi8vL0k5swRza/f29nZI8Hl6etr/W5K8vb0LFOPu3bsLdW3FwWKxKDQ0VImJibqYdtGhLTMzU5J06vQp+aRf+Ue7j2fOtt27d/PlShFypvujrKMvnAd94TzoC+dBXzgX+sN50BfOpaTHg8idvbRnhUB7RRegqLSr1U7bY7frbOpZTf95uiZ3n2x0SAAAACigfCf9KlasqE8//VQzZ87U9OnTlZKSIkmyWq2qUKGC+vTpo1GjRtlLZV6vP/74Q3Xr1rUn8iSpefPmeuutt9SmTRslJSU57J+UlGQv2RkQEJBru5+fnwICAiRJiYmJqlWrlv2/JcnPz69AMQYFBclisRTswoqJLVnn5+cnn8z/Y+++46Oq0j+Of2cmbZIQAmkQQkdqQhJCFZAiKtgX2+paEFdcpbira0HXiv7Yta+AIva2Kk0U7AURRIrRhNCT0EJCGiSkTdrM/f2RzSyREgIkM8l83q/XvJK55565z50nmcydJ+ecuoU932xfqUIKbhOsdiHtjurr7+0vqeZ8cPrsdrtSUlLc6ufDU5EL90Eu3Ae5cB/kwr2QD/dBLhpH7fN6qpr6ehDHlllcM8Uq6/mhMXiZvXR+9/O1cMtCPbP2Gf15wJ/VJbiLq8MCAABAA5x00U+SgoOD9cQTT+jhhx9WRkaGioqKFBwcrE6dOp3xC/Lw8HDt3btXlZWVztF5u3btUlRUlGJjY/Xqq6/KMAyZTCYZhqFff/1Vf/nLXyRJsbGxSkxM1MSJEyVJBw4c0IEDBxQbG6uIiAhFRkYqMTHRWfRLTExUZGTkUesA1sdisbjdBxEmk0lmc92lGs2mmvuGjKPaJDm3udu5NHfu+PPhqciF+yAX7oNcuA9y4V7Ih/sgF+6nKa8HcWyZRTVFP9bzQ2PpHdJb3dt0V3pBuu795l4tvGqhq0MCAABAAxxdAToJPj4+6t69u+Lj49W1a9dGucAbO3asvL299Y9//EO7d+/W999/r/nz5+uGG27Q+PHjVVRUpCeffFJpaWl68sknZbPZNGHCBEnStddeq08++USLFi3S9u3bde+992r06NHq2LGjs/2ZZ57R+vXrtX79ej377LO68cYbz/g5uAtn0c8wXBwJAAAAgOauKa4HcbSSyhIdrjgsSYpsFeniaNBSmUwmXdLzEplNZi3aukir9qxydUgAAABogFMq+jWFVq1a6a233lJeXp6uvPJKzZ49W7fffruuueYaBQYG6pVXXnGO5ktOTtaCBQvk718zTWV8fLwef/xxzZs3T9dee61at26t2bNnOx/7lltu0YUXXqhp06bpzjvv1GWXXaZJkya56EwbX23RzyGHiyMBAAAAAJyK2vX8wvzD5Ovl6+Jo0JK1b9VeUwZMkST99au/yu6wuzgiAAAAnKwGTe/Z1Hr06KE333zzmG39+/fXxx9/fNy+EydOdE7v+XsWi0UzZ87UzJkzz0ic7q52gXeHQdEPAAAAAJqj2qk9Wc8PTeHxMY/rg80fKCk7SW/89oZuTbjV1SEBAADgJLjtSD+cOUzvCQAAAADNW2Yx6/mh6YQFhOnR0Y9Kkh78/kEdLj/s2oAAAABwUij6eQDzf9PMSD8AAAAAaH4chsNZ9GOkH5rK1EFT1Sukl/LK8vTEj0+4OhwAAACcBIp+HoDpPQEAAACg+covy1elvVLeZm+FB4S7Ohx4CG+Lt56/4HlJ0r/X/1upB1NdHBEAAADqQ9HPAzC9JwAAAAA0X7Xr+UW2inRe3wFNYcJZEzShxwRVOap019d3uTocAAAA1IOrBQ9Qe1HISD8AAAAAaH72F++XxNSecI3nLnhOXmYvrdi5Qst3LHd1OAAAADgBin4ewFn0E0U/AAAAAGhusoqzJEkdWlH0Q9PrHdpbdw2tGeU3/YvpKq0sdXFEAAAAOB6Kfh6ANf0AAAAAoHmqslcppyRHEkU/uM7Dox5Wp9adtPfwXj25+klXhwMAAIDjoOjnAcxiTT8AAAAAaI6yS7JlyFCAd4CCfINcHQ48VIBPgF4c/6Ik6Zm1z2hb3jYXRwQAAIBjoejnARjpBwAAAMDd7N27V7fccovi4+M1evRovfbaa862jIwMTZo0SXFxcbrwwgu1Zs2aOn3Xrl2riy++WLGxsbrxxhuVkZHR1OE3mcziTEk1o/xqr+0AV7i016W6uOfFqnJU6Y7P7+AfiwEAANwQRT8P4FzTj6IfAAAAADfgcDg0ZcoUtWnTRh9//LEee+wxvfzyy1q+fLkMw9DUqVMVGhqqJUuW6LLLLtO0adOUlVWzrl1WVpamTp2qiRMnavHixWrbtq3uuKPlFiBq1/OLDIp0cSTwdCaTSXMmzJHVy6of9vyg91Ped3VIAAAA+B2Kfh6gtujXUi+CAQAAADQv+fn56tOnjx599FF16dJFo0aN0rBhw5SYmKh169YpIyNDjz/+uLp3767bbrtNcXFxWrJkiSRp0aJFio6O1uTJk3XWWWdp9uzZyszM1IYNG1x8Vo3jyJF+gKt1Ce6ih855SJJ099d3q8BW4OKIAAAAcCSKfh6A6T0BAAAAuJPw8HC98MILCgwMlGEYSkxM1MaNGzV48GAlJyerb9++8vf3d+6fkJCgpKQkSVJycrIGDhzobLNarerXr5+zvSWxVdl0yHZIkhTZipF+cA93n323eof2Vm5prh78/kFXhwMAAIAjUPTzAOb/ptkhin4AAAAA3MvYsWN13XXXKT4+XhdccIHy8vIUHh5eZ5+QkBBlZ2dLUr3tLUnt1J5t/NrI39u/nr2BpuFj8dFLF74kSZr/y3xtzNzo4ogAAABQy8vVAaDxsaYfAAAAAHf14osvKj8/X48++qhmz54tm80mHx+fOvv4+PiosrJSkuptbwi73X7qgZ9hdrtdFotFhmHI4ai5dsssqpnaM7JVpHPbsdS2ORyOE+53JvseuW9THdPd+9YuqXFkDt095hP1O9HvxzmdztGfov+k9ze/r9s/u11rb14ri9nSoPjcVe15u9PrAxqGHDZ/5LBlII/NHzl0LyebB4p+HqB2ek/W9AMAAADgbmJiYiRJFRUV+vvf/64rrrhCNputzj6VlZXy8/OTJPn6+h5V4KusrFRQUFCDj52SknKKUZ95FotFcXFxysvLU0lFiSRpV/4uSVKgEXjCkYxGq5prvby8PBWXFzfouKfaN9A30Pl9bm5ug4pKroi3Kfvm5OS45Lhnqm9tblNSUk744dKN7W/UJ9s/UeKBRP3jk3/omq7XNCg+d+dOrw84NeSw+SOHLQN5bP7IYfNC0c8DMNIPAAAAgDvJz89XUlKSxo0b59zWo0cPVVVVKSwsTLt27Tpq/9opPSMiIpSfn39Ue58+fRocR0xMjCwW9xidVFtcCQsLU2B1TdHl0N6a9fx6R/ZWu9btjts3xBri7BtQFdCg455q3yOnG/39dKuNdUx372sYhnJychQREeH851t3j/lYanNbW5A/kdmW2Zr+5XS9kvaKZoybofat2jcoRndkt9uVkpLiVq8PaBhy2PyRw5aBPDZ/5NC91OajPhT9PABFPwAAAADuZP/+/Zo2bZpWrVqliIgISdLmzZvVtm1bJSQk6I033lB5eblzdF9iYqISEhIkSbGxsUpMTHQ+ls1m09atWzVt2rQGx2GxWNzuAwyTySSz2ayiiiIVVxbLJJMigyJlNpuP26e2zWw2n3C/M9n3yH2b6pju3rd2tGNtDptDzCfqdzK/G7cPul1vb3pbv2T9or998zctumpRg2J0Z+74+oCGIYfNHzlsGchj80cOm5eGvWNEs+Sc3lNM7wkAAADA9WJiYtSvXz898MADSktL06pVq/T000/rL3/5iwYPHqz27dtr5syZSk1N1YIFC7Rp0yZdeeWVkqQrrrhCv/76qxYsWKDU1FTNnDlTUVFRGjJkiIvP6szKKs6SJIUFhMnH4lPP3oBrWMwWvXrJq7KYLFq8dbGWblvq6pAAAAA8GkU/D8BIPwAAAADuxGKx6KWXXpLVatU111yjBx98UDfccINuvPFGZ1teXp4mTpyoTz/9VPPmzVNkZKQkKSoqSnPmzNGSJUt05ZVXqrCwUPPmzasznWJLkFmcKUnq0KqDiyMBTiyuXZzuG36fJOmOz+7QIdshF0cEAADguZje0wOY/1vbNQxG+gEAAABwDxEREZo7d+4x2zp37qz33nvvuH1HjRqlUaNGNVZobiGrqGakX2SrSBdHAtTvoVEPaen2pdqev113fXWX3rr8LVeHBAAA4JEY6ecBGOkHAAAAAM2HYRjKKqkp+jHSD82Bn5ef3rj0DZlk0tvJb+urtK9cHRIAAIBHoujnAWqnuaHoBwAAAADu75DtkMqry+Vl9lJ4QLirw4GH8TZ7y+6wN7jfsI7DNGPIDEnSlBVTVFxRfKZDAwAAQD2Y3tMD1I70Y3pPAAAAAHB/tev5tQtsJ4vZ4uJo4Gm8zF6ymC2as36ObNW2BvWNahWlrsFdtbtwt2Z+N1NzLzz2FL4AAABoHIz08wC1RT+70fD/1AMAAAAANK3aoh/r+cGVbNU2lVWVNejmkEOvXvKqJGnexnlavXe1i88CAADAs1D08wAWU81/hlL0AwAAAAD3l1XMen5ovs7tdq7+HP9nSdItn94iW1XDRgsCAADg1FH08wC108Gcypz8AAAAAICmY3fYlV2SLYmiH5qvZ85/RpGtIpV6KFWP/vCoq8MBAADwGBT9PICXuWbpRop+AAAAAODeckpzVO2olq/FV22tbV0dDnBKWvu11vyL5kuSnvn5Gf2S9YuLIwIAAPAMFP08QO30ntVGtYsjAQAAAACcyP6i/ZJqRvmZTCYXRwOcukt6XaI/Rv9RDsOhyZ9MVkV1hatDAgAAaPEo+nkARvoBAAAAQPOQUZQhSYpsFeniSIDT9+L4FxXmH6aU3BSm+QQAAGgCFP08QO2aftUORvoBAAAAgDvbX/zfkX5BrOeH5i8sIEwLLlkgSXpq7VP6ad9PLo4IAACgZaPo5wGcI/0MRvoBAAAAgLsqrSxVbmmuJEb6oeW4vPfluin2JjkMh25adpNKKktcHRIAAECLRdHPAzjX9GOkHwAAAAC4rd+yf5PDcCjQJ1BBvkGuDgdoMG+z9zGXFvn3+H+rY1BHpRek656v7zluf5YlAQAAOD1erg4AjY81/QAAAADA/W3M3ChJ6tCKqT3RPHmZvWQxWzRn/RzZqm112sb3GK9Xf31V8xPnq9JeqV6hveq0W72smj5kelOGCwAA0OIw0s8DsKYfAAAAALi/DVkbJDG1J5o/W7VNZVVldW6RrSI1uMNgSdLCrQuVV5pXp/33RUIAAAA0HEU/D1A7vSdr+gEAAACA+2KkH1q6cV3HKcw/TCWVJfp056cyDMPVIQEAALQoFP08QO30ng7DwRtqAAAAAHBDB8sOKr0gXRIj/dByeVu8NbHPRFlMFu08uFO/HPjF1SEBAAC0KBT9PEDt9J4So/0AAAAAwB3VFj9CrCGyeltdHA3QeNoFttO53c6VJH2d/rXySvNcHBEAAEDLQdHPA9SO9JNY1w8AAAAA3NEvWTVFv6igKBdHAjS+oR2Gqnub7qp2VGvJtiV8VgEAAHCGUPTzALVr+kmS3cFIPwAAAABwNxuzatbz6xjU0cWRAI3PZDLpsl6Xyd/bXzmlOfpm1zeuDgkAAKBFoOjnAUwmk8ymmlTz33MAAAAA4F4Mw3AW/RjpB0/RyreVLut1mSRpQ+YGbcnd4uKIAAAAmj+Kfh6idopP1vQDAAAAAPdSWlWqnNIceZm91D6wvavDAZpMz5CeGhY1TJK0aOsi7Snc49qAAAAAmjmKfh6idopPRvoBAAAAgHsJ9AnUE2Oe0BuXviEfi4+rwwGa1Lldz1WHVh1kq7bpj4v/qEp7patDAgAAaLYo+nkI50g/1vQDAAAAALdz//D7dUPsDa4OA2hyFrNFV/a9UlYvq9ZnrtcD3z3g6pAAAACaLYp+HsJiZqQfAAAAAABwP8F+wbqq71WSpGd/flYfb/vYxREBAAA0TxT9PETt9J6s6QcAAAAAANxNv/B+umvoXZKkm5bdpO35210cEQAAQPND0c9DML0nAAAAAABwZ/8c90+d0/kcFVcWa+JHE1VcUezqkAAAAJoVin4eguk9AQAAAACAO/O2eGvhlQsV2SpS2/K3afKnk2UYhqvDAgAAaDYo+nkIL9N/R/oxvScAAAAAAHBTEYERWnzVYnmbvbV462I9+/Ozrg4JAACg2aDo5yEY6QcAAAAAAJqDYR2H6YXxL0iS7vv2Pn2R+oVrAwIAAGgm3LroV1lZqccee0yDBg3S2Wefreeee845rcPWrVt11VVXKTY2VldccYU2b95cp++KFSs0btw4xcbGaurUqTp06JCzzTAMPfPMMxo6dKgGDx6sp556Sg6Ho0nPramxph8AAAAAAGgubh94u/4c/2c5DIf+uOSP2pa3zdUhAQAAuD23Lvo98cQTWrt2rV5//XU9++yzWrhwoT766COVlZVpypQpGjhwoJYuXar4+HjddtttKisrkyRt2rRJDz74oKZNm6aPPvpIRUVFmjlzpvNx33zzTa1YsUJz587Viy++qOXLl+vNN9901Wk2CedIP4ORfgAAAAAAwL2ZTCbNu2ieRnYaqaKKIl3ywSU6WHbQ1WEBAAC4Nbct+hUWFmrJkiWaNWuW+vfvr2HDhmny5MlKTk7W559/Ll9fX917773q3r27HnzwQQUEBOjLL7+UJL333nuaMGGCLr/8cvXu3VtPPfWUVq1apYyMDEnSO++8oxkzZmjgwIEaOnSo/v73v+v999935ek2Oueafoz0AwAAAAAAzYCPxUdLrl6iLsFdlF6QrqsWXaUqe5WrwwIAAHBbblv0S0xMVGBgoAYPHuzcNmXKFM2ePVvJyclKSEiQyWSSVPPfXwMGDFBSUpIkKTk5WQMHDnT2a9++vSIjI5WcnKycnBwdOHBAgwYNcrYnJCQoMzNTubm5TXNyLsCafgAAAAAAoLkJCwjTp3/8VIE+gVq5Z6Vu/+x259IvAAAAqMtti34ZGRnq0KGDli1bpvHjx+vcc8/VvHnz5HA4lJeXp/Dw8Dr7h4SEKDs7W5KUm5t73Pa8vDxJqtMeGhoqSc7+LVFt0Y+RfgAAAAAAoDmJiYjRB1d8ILPJrNd/e12zfpzl6pAAAADckperAziesrIy7d27Vx9++KFmz56tvLw8Pfzww7JarbLZbPLx8amzv4+PjyorKyVJ5eXlx20vLy933j+yTZKz/8my292ngGa322WxWGQYhhwOx1HtFtUU/aocVUe11953p/NpzmqfR55P1yMX7oNcuA9y4T7IhXshH+6DXDQOnk8Azd3FPS/W3Alzdcfnd+iRHx5Rx6COujn+ZleHBQAA4Fbctujn5eWlkpISPfvss+rQoYMkKSsrSx988IE6d+58VIGusrJSfn5+kiRfX99jtlut1joFPl9fX+f3kmS1WhsUY0pKSsNPrJFYLBbFxcUpLy9PJRUlR7WX22qKncXFxUeNaAz0DZRUcz58GHDmuNPPh6cjF+6DXLgPcuE+yIV7IR/ug1wAAH7v9kG3K6MoQ7PXzNaty29V+1btNb7HeFeHBQAA4DbctugXFhYmX19fZ8FPkrp27aoDBw5o8ODBys/Pr7N/fn6+c8rOiIiIY7aHhYUpIiJCkpSXl6eoqCjn97XHbIiYmBhZLJaGnVgjqS3WhYWFKbA68Kj2oPIgqVDy9fdVu3bt6rT5e/tLqjkfnD673a6UlBS3+vnwVOTCfZAL90Eu3Ae5cC/kw32Qi8ZR+7wCQHP35Ngntb9ov97d9K6uXHilvr/pew3uMNjVYQEAALgFty36xcbGqqKiQrt371bXrl0lSbt27VKHDh0UGxurV199VYZhyGQyyTAM/frrr/rLX/7i7JuYmKiJEydKkg4cOKADBw4oNjZWERERioyMVGJiorPol5iYqMjIyKPWAayPxWJxuw8iTCaTzOajl2r0NntLkuyG/aj22vvudi7NnTv+fHgqcuE+yIX7IBfug1y4F/LhPsgFAOBYTCaTXrv0NR0oOaBvd32r8e+N1w+TflD/iP6uDg0AAMDljq4OuYlu3bpp9OjRmjlzprZv367Vq1drwYIFuvbaazV+/HgVFRXpySefVFpamp588knZbDZNmDBBknTttdfqk08+0aJFi7R9+3bde++9Gj16tDp27Ohsf+aZZ7R+/XqtX79ezz77rG688UZXnm6js5hrPjCxO5i+EwAAAAAANF8+Fh99fM3HGhY1TAXlBTrv3fO0I3+Hq8MCAABwObcd6SdJzzzzjGbNmqVrr71WVqtVf/rTn3TDDTfIZDLplVde0SOPPKKFCxeqV69eWrBggfz9a6apjI+P1+OPP64XX3xRhw8f1vDhwzVr1izn495yyy06ePCgpk2bJovFoiuvvFKTJk1y0Vk2DS9zTaop+gEAAAAAgOYu0CdQn//pc415e4ySspM07t1xWn3zanUJ7uLq0AAAAFzGrYt+rVq10lNPPXXMtv79++vjjz8+bt+JEyc6p/f8PYvFopkzZ2rmzJlnJM7moHakX7VR7eJIAAAAAAAATl+wX7C+vv5rjXprlLblb9PYt8dq5U0r1Tm4s6tDAwAAcAm3nd4TZ5aXiZF+AAAAAACgZQkLCNM3N3yj7m26a3fhbp3z1jlKP5Tu6rAAAABcgqKfh3CO9HMw0g8AAAAAALQcHYI6aNWkVeoZ0lP7Du/TOW+dwxp/AADAI1H08xCs6QcAAAAAAFqq2sJfv7B+yirO0qi3Rmlz7mZXhwUAANCkKPp5CIuJNf0AAAAAAEDL1S6wnX6Y9IPi2sUppzRHI98cqdV7V7s6LAAAgCZD0c9D1E7vyUg/AAAAAADQUoX6h+q7G7/TsKhhKiwv1HnvnqclW5e4OiwAAIAmQdHPQzin9zQo+gEAAAAAgJarrbWtvr3xW13W6zJV2Ct01aKrNGf9HFeHBQAA0Ogo+nkI5/SeDqb3BAAAAAAA7sXb7H1asxP9vq+/t7+WXL1Etw+8XYYMzfhyhu784k4+FwEAAC2al6sDQNNwjvRjek8AAAAAAOBmvMxespgtmrN+jmzVtgb1beXTSlMSphy13WK2aN6F8xQVFKUHv39QL254UZvzNuujKz9SqH+ocz+7w+5cFgUAAKA5o+jnIWrfvPIfbQAAAAAAwF3Zqm0qqyprUB+rl/WEBUMvs5du6H+DPtrykb7f/b16zumpm2JvUvtW7WX1smr6kOlnKnwAAACXYnpPD8GafgAAAAAAoCWrLRge69atTTfdEn+L2vi1UUF5geZtnKe1GWsbXGAEAABwZxT9PARr+gEAAAAAAE8WHhCuWwfcqu5tuqvKUaVPdnyij7Z8pOKKYleHBgAAcEZQ9PMQtSP9HIZDhmG4OBoAAAAAAICmZ/W26k8xf9LYrmNlkkm/Zf+m+Ffi9UvWL64ODQAA4LRR9PMQRy5IzRSfAAAAAADAU5lMJo3sNFI3x92sNn5tlF6QrqGvDdVD3z+kiuoKV4cHAABwyij6eYjakX4SU3wCAAAAAAB0bN1RM4bM0NX9rpbdsOuJ1U9oyOtDtLVwq6tDAwAAOCUU/TxE7Zp+kmR3MNIPAAAAAADA39tfH135kRZdtUhh/mHanLdZN/90s+777j6VVJa4OjwAAIAGoejnIUwmk8ymmnQzvScAAAAAAMD/XNn3Sm25Y4uu6nuV7IZdz/78rPrM66PFWxfLMAxXhwcAAHBSKPp5kNrRfkzvCQAAAAAAUFdYQJg+mPiBnh/0vLoGd9X+ov26atFVuuC9C7Qld4urwwMAAKgXRT8PUruuH9N7AgAAAAAAHNvIiJHadNsmPXzOw/K1+OqbXd+o//z+mrJ8ig4UH3B1eAAAAMdF0c+DWMyM9AMAAAAAAKiP1duqx8Y8ps13bNbEPhPlMBx69ddXddacs/TIykdUWF7o6hABAACOQtHPgzhH+rGmHwAAAAAAQL16tO2hJVcv0Zqb12ho1FCVVpXq8R8fV5cXuujRHx7VwbKDp/zYzMQEAADONC9XB4Cmw5p+AAAAAAAADTe803CtnbxWS7ct1SM/PKIteVv02KrH9MK6FzQsapiGRA2Rv7f/ST+e1cuq6UOmN2LEAADAE1H08yCs6QcAAAAAAHBqTCaTruh7hf7Q5w9asnWJHv/xcW3O3awv07/Uyj0rNbjDYA2LGiart9XVoQIAAA/F9J4ehDX9AAAAALiLnJwczZgxQ4MHD9bIkSM1e/ZsVVRUSJIyMjI0adIkxcXF6cILL9SaNWvq9F27dq0uvvhixcbG6sYbb1RGRoYrTgGAhzKbzLqq31VK/kuyFl+1WO0C26nCXqHV+1brhfUv6Ntd36qkssTVYQIAAA9E0c+DeJlY0w8AAACA6xmGoRkzZshms+n999/X888/r5UrV+qFF16QYRiaOnWqQkNDtWTJEl122WWaNm2asrKyJElZWVmaOnWqJk6cqMWLF6tt27a64447ZBiGi88KgKcxm8y6ou8VunPInbq679WKCIhQpb1SP2X8pH+v/7c+S/1MheWFrg4TAAB4EKb39CC1I/2Y3hMAAACAK+3atUtJSUn66aefFBoaKkmaMWOG/vWvf+mcc85RRkaGPvzwQ/n7+6t79+76+eeftWTJEk2fPl2LFi1SdHS0Jk+eLEmaPXu2hg8frg0bNmjIkCGuPC0AHspsMqtPWB/1Du2tnQd3as2+NdpfvF+/ZP2ixKxExYTHaHin4QoPCHd1qAAAoIWj6OdBnNN7GkzvCQAAAMB1wsLC9NprrzkLfrVKSkqUnJysvn37yt/f37k9ISFBSUlJkqTk5GQNHDjQ2Wa1WtWvXz8lJSVR9APgUiaTSb1Ce6lnSE/tPbxXa/atUXpBujblbtKm3E3qFdJLIzqNUFRQlKtDBQAALRRFPw/inN6TkX4AAAAAXCgoKEgjR4503nc4HHrvvfc0dOhQ5eXlKTy87miYkJAQZWdnS1K97Q1ht7vPtZHdbpfFYpFhGHI4HA3qW7u/w+Fosr5H7tsc4m2KvrVTzP4+h+4cs7sc0x361r4e/P5rfSwWyzGP2ymok66Lvk4Hig9oTcYabT+4XTsO7tCOgzvUpXUXje069pR+31G/huYQ7occtgzksfkjh+7lZPNA0c+DOEf6ORjpBwAAAMB9PP3009q6dasWL16st956Sz4+PnXafXx8VFlZKUmy2WwnbG+IlJSUUw/6DLNYLIqLi1NeXp5KKkoa1NdoVVNsysvLU3F5cZP0DfQNdH6fm5vboMKFK+Jtyr45OTkuOe6Z6tvc4j3dvrU/yykpKXU+TDuZ14fa39vc3Nzj/t6aZNLItiMVExij5IJkpRalas/hPXoj6Q1tyt2k6zpep1ERo2Q2mU8qXrPZrF69e8nXx/ek9v+9isoKbd2y1SOKje70Go9TQw5bBvLY/JHD5oWinwfxMjPSDwAAAIB7efrpp/X222/r+eefV8+ePeXr66vCwsI6+1RWVsrPz0+S5Ovre1SBr7KyUkFBQQ0+dkxMjCwWyynHfibVFhvCwsIUWB1Yz951hVhDnH0DqgKapK+/9/+mX/39yMvGOqa79zUMQzk5OYqIiJDJZGoWMbvLMV3Zt/ZnOSYmRlLN72JKSkqDXh/Cw8MVWHXi39t2aqfenXrrcMVhrdu/Tr9l/6Zfsn7RL1m/qHdob903/D79KeZP8rZ4n9Qx/73u37JV2U5q31pWb6vuHHqn+vfv36B+zc2p5BDuhRy2DOSx+SOH7qU2H/Wh6OdBWNMPAAAAgDuZNWuWPvjgAz399NO64IILJEkRERFKS0urs19+fr6zsBQREaH8/Pyj2vv06dPg41ssFrf7AMNkMslsPrkRP7Vq9zebzU3W98h9m0O8TdG3duTU73PozjG7yzHdoe/vXwsa8vrQkOO2sbbRhLMm6LLel8lWZdOzPz+r7fnbdfMnN+uvX/5V53Y9VwMjBzo/wzmqv18b3ZpwqyrsFSq3l5/UMY+MUzr6XFsqd3yNR8OQw5aBPDZ/5LB5adg7ITRrFlPNLyYj/QAAAAC42ty5c/Xhhx/queee00UXXeTcHhsbqy1btqi8/H8fZicmJio2NtbZnpiY6Gyz2WzaunWrsx0AmoNWPq00a+ws3T/ifo3rNk6BPoE6XHFYS7cv1TM/P6MNmRtUWlmqsqqyOrfy6oYV+gAAgGeh6OdBaqf3ZE0/AAAAAK6Unp6ul156SbfeeqsSEhKUl5fnvA0ePFjt27fXzJkzlZqaqgULFmjTpk268sorJUlXXHGFfv31Vy1YsECpqamaOXOmoqKiNGTIEBefFQA0nJ+Xn4Z3HK47h9yp8d3Hy9/bX4dsh7Rk2xIt+HWB0g6lyTAMV4cJAACaCYp+HqR2agi7wUg/AAAAAK7z3XffyW636+WXX9aIESPq3CwWi1566SXl5eVp4sSJ+vTTTzVv3jxFRkZKkqKiojRnzhwtWbJEV155pQoLCzVv3rw6a6gBwOlwxRRmXmYvDYkaohmDZ2h0l9HysfgouyRb76e8r7eT31bG4YwmjwkAADQ/rOnnQbxMjPQDAAAA4HpTpkzRlClTjtveuXNnvffee8dtHzVqlEaNGtUYoQHwMN5mb9kdduc/SlssFsXFxbksHl8vX43qPEqDIgdpzb412pC5QXsP79UbSW+od2hvXdP3GpfFBgAA3B9FPw9S+wa2dnFxAAAAAAAAT+Zl9pLFbNGc9XNkq7bJ4XAoNzdX4eHhMptPPEFWG782ujXh1kaJy9/bX+d3P19DOgzRqr2rlJSdpO352/XkmiclU02xEgAA4Pco+nmQ2qJftcFIPwAAAAAAgFq2apvKqsrkcDhUUlGiwKrAeot+Vi9ro8fV2q+1Lu11qYZFDdMXaV9od+FuPbbqMbXxa6Pzup+n3iG9md4YAAA4UfTzILXTe9odrOkHAAAAAADQXIQFhOmG/jcooyhD3+76VhlFGVq4ZaG6t+mu8T3GK9Q/1NUhAgAAN3Dif1lCi+Ic6ceafgAAAAAAAM2KyWRSfLt4bZu6TWO7jJXFZFF6Qbpe/uVlfbPrG1XaK10dIgAAcDGKfh7Ey8xIPwAAAAAAgOYswCdAF/S4QHcMukNntT1LDsOhtRlr9fIvLyv9ULqrwwMAAC5E0c+DsKYfAAAAAABAy9DW2lbXxVynP/b7o1r7tlZheaHeS3lPn+z4RLYqm6vDAwAALsCafh6ENf0AAAAAAABall6hvdQluIu+3/O9NmRuUFJ2ktIOpenCHheqT1gfV4cHAACaECP9PAhr+gEAAAAAALQ8vl6+mtBjgibHTVaof6hKKku0cOtCLdyyUCWVJa4ODwAANBGKfh7EuaafwUg/AAAAAACAlqZj6466LeE2jew0UmaTWdvyt2nexnlKyk6SYRiuDg8AADQyin4exGJipB8AAAAAAEBL5mX20tiuY3XrgFvVPrC9yqvL9cmOT/RW0lvKLMp0dXgAAKARUfTzIM6RfqzpBwAAAAAA0KK1C2ynPw/4s8Z1HSeLyaLtB7er30v99OZvbzLqDwCAFoqinwepXdOP6T0BAAAAAABaPrPJrOGdhuu2hNvUMaijDlcc1uRPJ+ui/1yk/UX7XR0eAAA4wyj6eRCm9wQAAAAAAPA8YQFhumPQHXpq3FPytfjqi7QvFP1SNKP+AABoYSj6eRCm9wQAAAAAAPBMZpNZ9wy/R7/d9puGdBjCqD8AAFogin4e5MjpPfkvLgAAAAAAAM/TJ6yPfpr8E6P+AABogZpN0W/KlCm6//77nfe3bt2qq666SrGxsbriiiu0efP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",
      "text/plain": [
       "<Figure size 1800x3600 with 12 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# List of numerical columns to check for outliers\n",
    "# Numerical columns\n",
    "numerical_columns = ['Price', 'Living_Area', 'Surface_area_plot_of_land']\n",
    "\n",
    "# Function to remove outliers\n",
    "def remove_outliers(data, columns):\n",
    "    for col in columns:\n",
    "        if col in data.columns:\n",
    "            Q1 = data[col].quantile(0.25)\n",
    "            Q3 = data[col].quantile(0.75)\n",
    "            IQR = Q3 - Q1\n",
    "            lower_bound = Q1 - 1.5 * IQR\n",
    "            upper_bound = Q3 + 1.5 * IQR\n",
    "            data = data[(data[col] >= lower_bound) & (data[col] <= upper_bound)]\n",
    "    return data\n",
    "\n",
    "# Original dataset\n",
    "df_original = df.copy()\n",
    "\n",
    "# Remove outliers\n",
    "df_no_outliers = remove_outliers(df.copy(), numerical_columns)\n",
    "\n",
    "# Create a grid for side-by-side comparison (6 rows, 2 columns)\n",
    "fig, axes = plt.subplots(6, 2, figsize=(18, 36))\n",
    "\n",
    "# Plot histograms and boxplots for each column before and after outlier removal\n",
    "for i, col in enumerate(numerical_columns):\n",
    "    # Histogram before outlier removal\n",
    "    sns.histplot(df_original[col], bins=50, kde=True, color='green', ax=axes[2 * i, 0])\n",
    "    axes[2 * i, 0].set_title(f'{col} Histogram (Before Outlier Removal)')\n",
    "    axes[2 * i, 0].set_xlabel(col)\n",
    "    axes[2 * i, 0].set_ylabel('Count')\n",
    "\n",
    "    # Histogram after outlier removal\n",
    "    sns.histplot(df_no_outliers[col], bins=50, kde=True, color='green', ax=axes[2 * i, 1])\n",
    "    axes[2 * i, 1].set_title(f'{col} Histogram (After Outlier Removal)')\n",
    "    axes[2 * i, 1].set_xlabel(col)\n",
    "    axes[2 * i, 1].set_ylabel('Count')\n",
    "\n",
    "    # Boxplot before outlier removal\n",
    "    sns.boxplot(x=df_original[col], color='orange', ax=axes[2 * i + 1, 0])\n",
    "    axes[2 * i + 1, 0].set_title(f'{col} Boxplot (Before Outlier Removal)')\n",
    "    axes[2 * i + 1, 0].set_xlabel(col)\n",
    "\n",
    "    # Boxplot after outlier removal\n",
    "    sns.boxplot(x=df_no_outliers[col], color='orange', ax=axes[2 * i + 1, 1])\n",
    "    axes[2 * i + 1, 1].set_title(f'{col} Boxplot (After Outlier Removal)')\n",
    "    axes[2 * i + 1, 1].set_xlabel(col)\n",
    "\n",
    "plt.tight_layout()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 15. Conclusion\n",
    "\n",
    "In this notebook, we have: <br>\n",
    "• Loaded and explored the dataset. <br>\n",
    "• Analyzed and visualized missing values. <br>\n",
    "• Identified critical columns and columns to drop, with explanations. <br>\n",
    "• Handled missing values appropriately, including imputations based on grouped data. <br>\n",
    "• Categorized data to facilitate better imputation and analysis. <br>\n",
    "• Made deductions based on data patterns to fill missing values logically. <br>\n",
    "• Removed outliers and visualized their impact using both histograms and boxplots. <br>\n",
    "• Prepared the dataset for future modeling tasks. <br>\n"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
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