model.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 399,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Import Libraries\n",
    "import pandas as pd\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "import seaborn as sns\n",
    "\n",
    "from sklearn.model_selection import train_test_split, GridSearchCV\n",
    "from sklearn.linear_model import LogisticRegression\n",
    "from sklearn.ensemble import RandomForestClassifier\n",
    "from sklearn.tree import DecisionTreeClassifier\n",
    "from sklearn.neighbors import KNeighborsClassifier\n",
    "from sklearn.svm import SVC\n",
    "from sklearn.metrics import classification_report, confusion_matrix, accuracy_score\n",
    "from sklearn.preprocessing import LabelEncoder, StandardScaler\n",
    "import joblib"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 342,
   "metadata": {},
   "outputs": [],
   "source": [
    "#Load Data\n",
    "file_path = r\"Data\\Prediction_Datasets.xlsx\"\n",
    "\n",
    "# Load data from the specified Excel sheet\n",
    "data = pd.read_excel(file_path, sheet_name='Churn')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 343,
   "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>Customer_ID</th>\n",
       "      <th>Gender</th>\n",
       "      <th>Age</th>\n",
       "      <th>Married</th>\n",
       "      <th>State</th>\n",
       "      <th>Number_of_Referrals</th>\n",
       "      <th>Tenure_in_Months</th>\n",
       "      <th>Value_Deal</th>\n",
       "      <th>Phone_Service</th>\n",
       "      <th>Multiple_Lines</th>\n",
       "      <th>...</th>\n",
       "      <th>Payment_Method</th>\n",
       "      <th>Monthly_Charge</th>\n",
       "      <th>Total_Charges</th>\n",
       "      <th>Total_Refunds</th>\n",
       "      <th>Total_Extra_Data_Charges</th>\n",
       "      <th>Total_Long_Distance_Charges</th>\n",
       "      <th>Total_Revenue</th>\n",
       "      <th>Customer_Status</th>\n",
       "      <th>Churn_Category</th>\n",
       "      <th>Churn_Reason</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>11850-MAH</td>\n",
       "      <td>Male</td>\n",
       "      <td>74</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Maharashtra</td>\n",
       "      <td>5</td>\n",
       "      <td>6</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Yes</td>\n",
       "      <td>...</td>\n",
       "      <td>Credit Card</td>\n",
       "      <td>75.150002</td>\n",
       "      <td>3480.350098</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "      <td>422.549988</td>\n",
       "      <td>3902.899902</td>\n",
       "      <td>Stayed</td>\n",
       "      <td>Others</td>\n",
       "      <td>Others</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>11873-HAR</td>\n",
       "      <td>Male</td>\n",
       "      <td>45</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Haryana</td>\n",
       "      <td>9</td>\n",
       "      <td>10</td>\n",
       "      <td>Deal 2</td>\n",
       "      <td>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>...</td>\n",
       "      <td>Credit Card</td>\n",
       "      <td>50.250000</td>\n",
       "      <td>2221.550049</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "      <td>292.049988</td>\n",
       "      <td>2513.600098</td>\n",
       "      <td>Stayed</td>\n",
       "      <td>Others</td>\n",
       "      <td>Others</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>11878-RAJ</td>\n",
       "      <td>Male</td>\n",
       "      <td>75</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Rajasthan</td>\n",
       "      <td>15</td>\n",
       "      <td>17</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>...</td>\n",
       "      <td>Bank Withdrawal</td>\n",
       "      <td>71.800003</td>\n",
       "      <td>1167.800049</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "      <td>734.400024</td>\n",
       "      <td>1902.199951</td>\n",
       "      <td>Churned</td>\n",
       "      <td>Competitor</td>\n",
       "      <td>Competitor offered more data</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>11882-BIH</td>\n",
       "      <td>Female</td>\n",
       "      <td>74</td>\n",
       "      <td>No</td>\n",
       "      <td>Bihar</td>\n",
       "      <td>14</td>\n",
       "      <td>15</td>\n",
       "      <td>Deal 5</td>\n",
       "      <td>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>...</td>\n",
       "      <td>Bank Withdrawal</td>\n",
       "      <td>78.949997</td>\n",
       "      <td>378.399994</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "      <td>61.349998</td>\n",
       "      <td>439.750000</td>\n",
       "      <td>Churned</td>\n",
       "      <td>Attitude</td>\n",
       "      <td>Attitude of support person</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>11887-MAD</td>\n",
       "      <td>Female</td>\n",
       "      <td>33</td>\n",
       "      <td>No</td>\n",
       "      <td>Madhya Pradesh</td>\n",
       "      <td>2</td>\n",
       "      <td>33</td>\n",
       "      <td>Deal 2</td>\n",
       "      <td>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>...</td>\n",
       "      <td>Credit Card</td>\n",
       "      <td>69.099998</td>\n",
       "      <td>3168.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "      <td>1466.479980</td>\n",
       "      <td>4634.479980</td>\n",
       "      <td>Stayed</td>\n",
       "      <td>Others</td>\n",
       "      <td>Others</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 32 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "  Customer_ID  Gender  Age Married           State  Number_of_Referrals  \\\n",
       "0   11850-MAH    Male   74     Yes     Maharashtra                    5   \n",
       "1   11873-HAR    Male   45     Yes         Haryana                    9   \n",
       "2   11878-RAJ    Male   75     Yes       Rajasthan                   15   \n",
       "3   11882-BIH  Female   74      No           Bihar                   14   \n",
       "4   11887-MAD  Female   33      No  Madhya Pradesh                    2   \n",
       "\n",
       "   Tenure_in_Months Value_Deal Phone_Service Multiple_Lines  ...  \\\n",
       "0                 6        NaN           Yes            Yes  ...   \n",
       "1                10     Deal 2           Yes             No  ...   \n",
       "2                17        NaN           Yes             No  ...   \n",
       "3                15     Deal 5           Yes             No  ...   \n",
       "4                33     Deal 2           Yes             No  ...   \n",
       "\n",
       "    Payment_Method Monthly_Charge Total_Charges Total_Refunds  \\\n",
       "0      Credit Card      75.150002   3480.350098           0.0   \n",
       "1      Credit Card      50.250000   2221.550049           0.0   \n",
       "2  Bank Withdrawal      71.800003   1167.800049           0.0   \n",
       "3  Bank Withdrawal      78.949997    378.399994           0.0   \n",
       "4      Credit Card      69.099998   3168.000000           0.0   \n",
       "\n",
       "  Total_Extra_Data_Charges Total_Long_Distance_Charges Total_Revenue  \\\n",
       "0                        0                  422.549988   3902.899902   \n",
       "1                        0                  292.049988   2513.600098   \n",
       "2                        0                  734.400024   1902.199951   \n",
       "3                        0                   61.349998    439.750000   \n",
       "4                        0                 1466.479980   4634.479980   \n",
       "\n",
       "  Customer_Status Churn_Category                  Churn_Reason  \n",
       "0          Stayed         Others                        Others  \n",
       "1          Stayed         Others                        Others  \n",
       "2         Churned     Competitor  Competitor offered more data  \n",
       "3         Churned       Attitude    Attitude of support person  \n",
       "4          Stayed         Others                        Others  \n",
       "\n",
       "[5 rows x 32 columns]"
      ]
     },
     "execution_count": 343,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 344,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 6007 entries, 0 to 6006\n",
      "Data columns (total 32 columns):\n",
      " #   Column                       Non-Null Count  Dtype  \n",
      "---  ------                       --------------  -----  \n",
      " 0   Customer_ID                  6007 non-null   object \n",
      " 1   Gender                       6007 non-null   object \n",
      " 2   Age                          6007 non-null   int64  \n",
      " 3   Married                      6007 non-null   object \n",
      " 4   State                        6007 non-null   object \n",
      " 5   Number_of_Referrals          6007 non-null   int64  \n",
      " 6   Tenure_in_Months             6007 non-null   int64  \n",
      " 7   Value_Deal                   2710 non-null   object \n",
      " 8   Phone_Service                6007 non-null   object \n",
      " 9   Multiple_Lines               6007 non-null   object \n",
      " 10  Internet_Service             6007 non-null   object \n",
      " 11  Internet_Type                4784 non-null   object \n",
      " 12  Online_Security              6007 non-null   object \n",
      " 13  Online_Backup                6007 non-null   object \n",
      " 14  Device_Protection_Plan       6007 non-null   object \n",
      " 15  Premium_Support              6007 non-null   object \n",
      " 16  Streaming_TV                 6007 non-null   object \n",
      " 17  Streaming_Movies             6007 non-null   object \n",
      " 18  Streaming_Music              6007 non-null   object \n",
      " 19  Unlimited_Data               6007 non-null   object \n",
      " 20  Contract                     6007 non-null   object \n",
      " 21  Paperless_Billing            6007 non-null   object \n",
      " 22  Payment_Method               6007 non-null   object \n",
      " 23  Monthly_Charge               6007 non-null   float64\n",
      " 24  Total_Charges                6007 non-null   float64\n",
      " 25  Total_Refunds                6007 non-null   float64\n",
      " 26  Total_Extra_Data_Charges     6007 non-null   int64  \n",
      " 27  Total_Long_Distance_Charges  6007 non-null   float64\n",
      " 28  Total_Revenue                6007 non-null   float64\n",
      " 29  Customer_Status              6007 non-null   object \n",
      " 30  Churn_Category               6007 non-null   object \n",
      " 31  Churn_Reason                 6007 non-null   object \n",
      "dtypes: float64(5), int64(4), object(23)\n",
      "memory usage: 1.5+ MB\n"
     ]
    }
   ],
   "source": [
    "data.info()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Exploratory Data Analysis"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 345,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
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       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>count</th>\n",
       "      <th>mean</th>\n",
       "      <th>std</th>\n",
       "      <th>min</th>\n",
       "      <th>25%</th>\n",
       "      <th>50%</th>\n",
       "      <th>75%</th>\n",
       "      <th>max</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>Age</th>\n",
       "      <td>6007.0</td>\n",
       "      <td>47.289163</td>\n",
       "      <td>16.805110</td>\n",
       "      <td>18.000000</td>\n",
       "      <td>33.000000</td>\n",
       "      <td>47.000000</td>\n",
       "      <td>60.000000</td>\n",
       "      <td>84.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Number_of_Referrals</th>\n",
       "      <td>6007.0</td>\n",
       "      <td>7.439820</td>\n",
       "      <td>4.622369</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>3.000000</td>\n",
       "      <td>7.000000</td>\n",
       "      <td>11.000000</td>\n",
       "      <td>15.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Tenure_in_Months</th>\n",
       "      <td>6007.0</td>\n",
       "      <td>17.394540</td>\n",
       "      <td>10.592920</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>8.000000</td>\n",
       "      <td>17.000000</td>\n",
       "      <td>27.000000</td>\n",
       "      <td>36.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Monthly_Charge</th>\n",
       "      <td>6007.0</td>\n",
       "      <td>65.087598</td>\n",
       "      <td>31.067808</td>\n",
       "      <td>-10.000000</td>\n",
       "      <td>35.950001</td>\n",
       "      <td>71.099998</td>\n",
       "      <td>90.449997</td>\n",
       "      <td>118.750000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Total_Charges</th>\n",
       "      <td>6007.0</td>\n",
       "      <td>2430.986173</td>\n",
       "      <td>2267.481295</td>\n",
       "      <td>19.100000</td>\n",
       "      <td>539.949982</td>\n",
       "      <td>1556.849976</td>\n",
       "      <td>4013.900024</td>\n",
       "      <td>8684.799805</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Total_Refunds</th>\n",
       "      <td>6007.0</td>\n",
       "      <td>2.038612</td>\n",
       "      <td>8.065520</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>49.790001</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Total_Extra_Data_Charges</th>\n",
       "      <td>6007.0</td>\n",
       "      <td>7.015149</td>\n",
       "      <td>25.405737</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>150.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Total_Long_Distance_Charges</th>\n",
       "      <td>6007.0</td>\n",
       "      <td>797.283311</td>\n",
       "      <td>854.858840</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>107.084999</td>\n",
       "      <td>470.220001</td>\n",
       "      <td>1269.839966</td>\n",
       "      <td>3564.719971</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Total_Revenue</th>\n",
       "      <td>6007.0</td>\n",
       "      <td>3233.246020</td>\n",
       "      <td>2856.181081</td>\n",
       "      <td>21.610001</td>\n",
       "      <td>833.684998</td>\n",
       "      <td>2367.149902</td>\n",
       "      <td>5105.685059</td>\n",
       "      <td>11979.339844</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                              count         mean          std        min  \\\n",
       "Age                          6007.0    47.289163    16.805110  18.000000   \n",
       "Number_of_Referrals          6007.0     7.439820     4.622369   0.000000   \n",
       "Tenure_in_Months             6007.0    17.394540    10.592920   1.000000   \n",
       "Monthly_Charge               6007.0    65.087598    31.067808 -10.000000   \n",
       "Total_Charges                6007.0  2430.986173  2267.481295  19.100000   \n",
       "Total_Refunds                6007.0     2.038612     8.065520   0.000000   \n",
       "Total_Extra_Data_Charges     6007.0     7.015149    25.405737   0.000000   \n",
       "Total_Long_Distance_Charges  6007.0   797.283311   854.858840   0.000000   \n",
       "Total_Revenue                6007.0  3233.246020  2856.181081  21.610001   \n",
       "\n",
       "                                    25%          50%          75%  \\\n",
       "Age                           33.000000    47.000000    60.000000   \n",
       "Number_of_Referrals            3.000000     7.000000    11.000000   \n",
       "Tenure_in_Months               8.000000    17.000000    27.000000   \n",
       "Monthly_Charge                35.950001    71.099998    90.449997   \n",
       "Total_Charges                539.949982  1556.849976  4013.900024   \n",
       "Total_Refunds                  0.000000     0.000000     0.000000   \n",
       "Total_Extra_Data_Charges       0.000000     0.000000     0.000000   \n",
       "Total_Long_Distance_Charges  107.084999   470.220001  1269.839966   \n",
       "Total_Revenue                833.684998  2367.149902  5105.685059   \n",
       "\n",
       "                                      max  \n",
       "Age                             84.000000  \n",
       "Number_of_Referrals             15.000000  \n",
       "Tenure_in_Months                36.000000  \n",
       "Monthly_Charge                 118.750000  \n",
       "Total_Charges                 8684.799805  \n",
       "Total_Refunds                   49.790001  \n",
       "Total_Extra_Data_Charges       150.000000  \n",
       "Total_Long_Distance_Charges   3564.719971  \n",
       "Total_Revenue                11979.339844  "
      ]
     },
     "execution_count": 345,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Summary statistics\n",
    "data.describe(include = 'number').T"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 346,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Drop leakey columns\n",
    "data.drop(columns = [\"Churn_Category\", \"Churn_Reason\" ], inplace = True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 347,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Customer_ID               6007\n",
       "Gender                       2\n",
       "Married                      2\n",
       "State                       22\n",
       "Value_Deal                   5\n",
       "Phone_Service                2\n",
       "Multiple_Lines               2\n",
       "Internet_Service             2\n",
       "Internet_Type                3\n",
       "Online_Security              2\n",
       "Online_Backup                2\n",
       "Device_Protection_Plan       2\n",
       "Premium_Support              2\n",
       "Streaming_TV                 2\n",
       "Streaming_Movies             2\n",
       "Streaming_Music              2\n",
       "Unlimited_Data               2\n",
       "Contract                     3\n",
       "Paperless_Billing            2\n",
       "Payment_Method               3\n",
       "Customer_Status              2\n",
       "dtype: int64"
      ]
     },
     "execution_count": 347,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Check for high cardinality in the categorical columns\n",
    "data.select_dtypes(\"object\").nunique()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 348,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array(['Stayed', 'Churned'], dtype=object)"
      ]
     },
     "execution_count": 348,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Identifying target column\n",
    "data['Customer_Status'].unique()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 349,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Map 'Stayed' to 0 and 'Churned' to 1\n",
    "data['Customer_Status'] = data['Customer_Status'].map({'Stayed': 0, 'Churned': 1})"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 350,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0       0\n",
       "1       0\n",
       "2       1\n",
       "3       1\n",
       "4       0\n",
       "       ..\n",
       "6002    0\n",
       "6003    0\n",
       "6004    1\n",
       "6005    0\n",
       "6006    0\n",
       "Name: Customer_Status, Length: 6007, dtype: int64"
      ]
     },
     "execution_count": 350,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#Convert the data type to numerical\n",
    "data['Customer_Status'].astype(int)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 351,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Index(['Value_Deal', 'Internet_Type'], dtype='object')"
      ]
     },
     "execution_count": 351,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "null_columns = data.columns[data.isnull().any()]\n",
    "null_columns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 352,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Value_Deal       54.885966\n",
       "Internet_Type    20.359580\n",
       "dtype: float64"
      ]
     },
     "execution_count": 352,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Check for null\n",
    "null_percentages = (data.isna().sum() / len(data)) * 100\n",
    "null_percentages = null_percentages[null_percentages > 1].sort_values(ascending=False)\n",
    "null_percentages\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 353,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Value_Deal\n",
       "Deal 2    758\n",
       "Deal 5    578\n",
       "Deal 4    540\n",
       "Deal 1    469\n",
       "Deal 3    365\n",
       "Name: count, dtype: int64"
      ]
     },
     "execution_count": 353,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data['Value_Deal'].value_counts()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 354,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Internet_Type\n",
       "Fiber Optic    2675\n",
       "DSL            1398\n",
       "Cable           711\n",
       "Name: count, dtype: int64"
      ]
     },
     "execution_count": 354,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data['Internet_Type'].value_counts()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 355,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Fill NaN with None\n",
    "#data[null_columns] = data[null_columns].map(lambda x: None if pd.isnull(x) else x)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 356,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Replace None with 'Not subscribed'\n",
    "for col in null_columns:\n",
    "    data[col] = data[col].replace(np.nan, 'Not Subscribed')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 357,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Customer_ID                    0\n",
       "Gender                         0\n",
       "Age                            0\n",
       "Married                        0\n",
       "State                          0\n",
       "Number_of_Referrals            0\n",
       "Tenure_in_Months               0\n",
       "Value_Deal                     0\n",
       "Phone_Service                  0\n",
       "Multiple_Lines                 0\n",
       "Internet_Service               0\n",
       "Internet_Type                  0\n",
       "Online_Security                0\n",
       "Online_Backup                  0\n",
       "Device_Protection_Plan         0\n",
       "Premium_Support                0\n",
       "Streaming_TV                   0\n",
       "Streaming_Movies               0\n",
       "Streaming_Music                0\n",
       "Unlimited_Data                 0\n",
       "Contract                       0\n",
       "Paperless_Billing              0\n",
       "Payment_Method                 0\n",
       "Monthly_Charge                 0\n",
       "Total_Charges                  0\n",
       "Total_Refunds                  0\n",
       "Total_Extra_Data_Charges       0\n",
       "Total_Long_Distance_Charges    0\n",
       "Total_Revenue                  0\n",
       "Customer_Status                0\n",
       "dtype: int64"
      ]
     },
     "execution_count": 357,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data.isna().sum()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 358,
   "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>Customer_ID</th>\n",
       "      <th>Gender</th>\n",
       "      <th>Age</th>\n",
       "      <th>Married</th>\n",
       "      <th>State</th>\n",
       "      <th>Number_of_Referrals</th>\n",
       "      <th>Tenure_in_Months</th>\n",
       "      <th>Value_Deal</th>\n",
       "      <th>Phone_Service</th>\n",
       "      <th>Multiple_Lines</th>\n",
       "      <th>...</th>\n",
       "      <th>Contract</th>\n",
       "      <th>Paperless_Billing</th>\n",
       "      <th>Payment_Method</th>\n",
       "      <th>Monthly_Charge</th>\n",
       "      <th>Total_Charges</th>\n",
       "      <th>Total_Refunds</th>\n",
       "      <th>Total_Extra_Data_Charges</th>\n",
       "      <th>Total_Long_Distance_Charges</th>\n",
       "      <th>Total_Revenue</th>\n",
       "      <th>Customer_Status</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>11850-MAH</td>\n",
       "      <td>Male</td>\n",
       "      <td>74</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Maharashtra</td>\n",
       "      <td>5</td>\n",
       "      <td>6</td>\n",
       "      <td>Not Subscribed</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Yes</td>\n",
       "      <td>...</td>\n",
       "      <td>Two Year</td>\n",
       "      <td>No</td>\n",
       "      <td>Credit Card</td>\n",
       "      <td>75.150002</td>\n",
       "      <td>3480.350098</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "      <td>422.549988</td>\n",
       "      <td>3902.899902</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>11873-HAR</td>\n",
       "      <td>Male</td>\n",
       "      <td>45</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Haryana</td>\n",
       "      <td>9</td>\n",
       "      <td>10</td>\n",
       "      <td>Deal 2</td>\n",
       "      <td>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>...</td>\n",
       "      <td>Month-to-Month</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Credit Card</td>\n",
       "      <td>50.250000</td>\n",
       "      <td>2221.550049</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "      <td>292.049988</td>\n",
       "      <td>2513.600098</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>2 rows × 30 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "  Customer_ID Gender  Age Married        State  Number_of_Referrals  \\\n",
       "0   11850-MAH   Male   74     Yes  Maharashtra                    5   \n",
       "1   11873-HAR   Male   45     Yes      Haryana                    9   \n",
       "\n",
       "   Tenure_in_Months      Value_Deal Phone_Service Multiple_Lines  ...  \\\n",
       "0                 6  Not Subscribed           Yes            Yes  ...   \n",
       "1                10          Deal 2           Yes             No  ...   \n",
       "\n",
       "         Contract Paperless_Billing Payment_Method Monthly_Charge  \\\n",
       "0        Two Year                No    Credit Card      75.150002   \n",
       "1  Month-to-Month               Yes    Credit Card      50.250000   \n",
       "\n",
       "  Total_Charges Total_Refunds Total_Extra_Data_Charges  \\\n",
       "0   3480.350098           0.0                        0   \n",
       "1   2221.550049           0.0                        0   \n",
       "\n",
       "  Total_Long_Distance_Charges Total_Revenue Customer_Status  \n",
       "0                  422.549988   3902.899902               0  \n",
       "1                  292.049988   2513.600098               0  \n",
       "\n",
       "[2 rows x 30 columns]"
      ]
     },
     "execution_count": 358,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data.head(2)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Data Analysis and Visualization"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 359,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Index(['Customer_ID', 'Gender', 'Age', 'Married', 'State',\n",
       "       'Number_of_Referrals', 'Tenure_in_Months', 'Value_Deal',\n",
       "       'Phone_Service', 'Multiple_Lines', 'Internet_Service', 'Internet_Type',\n",
       "       'Online_Security', 'Online_Backup', 'Device_Protection_Plan',\n",
       "       'Premium_Support', 'Streaming_TV', 'Streaming_Movies',\n",
       "       'Streaming_Music', 'Unlimited_Data', 'Contract', 'Paperless_Billing',\n",
       "       'Payment_Method', 'Monthly_Charge', 'Total_Charges', 'Total_Refunds',\n",
       "       'Total_Extra_Data_Charges', 'Total_Long_Distance_Charges',\n",
       "       'Total_Revenue', 'Customer_Status'],\n",
       "      dtype='object')"
      ]
     },
     "execution_count": 359,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data.columns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 360,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.countplot(data['Gender'])\n",
    "plt.title('Gender Countplot');"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 361,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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PcAMAQCmTn0tKuKAYAABYhXADAACsQrgBAABWIdwAAACrEG4AAIBVCDcAAMAqhBsAAGAVwg0AALAK4QYAAFiFcAMAAKxCuAEAAFYh3AAAAKsQbgAAgFUINwAAwCqEGwAAYBXCDQAAsIqnuwtwl/Z/X6By3r7uLgMAgFJv62uPuLsEF4zcAAAAqxBuAACAVQg3AADAKoQbAABgFcINAACwCuEGAABYhXADAACsQrgBAABWIdwAAACrEG4AAIBVCDcAAMAqhBsAAGAVwg0AALAK4QYAAFiFcAMAAKxCuAEAAFYh3AAAAKsQbgAAgFUINwAAwCqEGwAAYBXCDQAAsArhBgAAWIVwAwAArEK4AQAAViHcAAAAqxBuAACAVQg3AADAKoQbAABgFcINAACwCuEGAABYhXADAACsQrgBAABWIdwAAACrEG4AAIBVCDcAAMAqhBsAAGAVwg0AALAK4QYAAFiFcAMAAKxCuAEAAFYh3AAAAKsQbgAAgFUINwAAwCqEGwAAYBXCDQAAsArhBgAAWIVwAwAArEK4AQAAViHcAAAAqxBuAACAVQg3AADAKoQbAABgFcINAACwCuEGAABYhXADAACsQrgBAABWIdwAAACrEG4AAIBVCDcAAMAqhBsAAGAVwg0AALAK4QYAAFiFcAMAAKxCuAEAAFYh3AAAAKsQbgAAgFUINwAAwCqEGwAAYBW3hBtjjOLi4tSlS5cc82bOnKmAgAAdPnzYDZUBAIDSzi3hxuFwaO7cudq0aZNmz57tnJ6UlKRnnnlG06dP16233uqO0gAAQCnntrelIiMjNXXqVP3tb39TUlKSjDF67LHH1LlzZzVv3lzx8fGqVKmSwsLC9PDDD+vkyZPOZRctWqTGjRvL19dXVapUUVxcnM6ePeuuXQEAACWIW6+56d+/vzp16qSBAwdqxowZSkxM1OzZs9WxY0c1b95cW7Zs0RdffKHjx4+rV69ekqSjR4+qT58+GjhwoPbu3au1a9fqvvvukzHGnbsCAABKCIdxcyo4ceKEGjZsqFOnTumjjz5SYmKivv76a61YscLZ5vDhw4qMjNS+ffuUnp6uli1b6tChQ4qKirru+jMyMpSRkeH8PjU1VZGRkWr6lzdVztu3WPYJAICyZOtrjxT7NlJTU+Xv76+UlBT5+flds63b75YKDQ3V4MGDVb9+fd17773asWOH1qxZo0qVKjlf9erVkyQdOHBATZs2VadOndS4cWM9+OCDevvtt3X69Ok81z9hwgT5+/s7X5GRkTdr1wAAgBu4PdxIkqenpzw9PSVJ6enp6t69u7Zv3+7y2r9/v9q3b69y5cpp5cqVWr58uRo0aKDp06erbt26SkpKynXdo0ePVkpKivP1yy+/3MxdAwAAN5mnuwu4WosWLfTRRx8pOjraGXiu5nA41KZNG7Vp00YvvPCCoqKitGTJEj311FM52np7e8vb27u4ywYAACVEiRi5+b1hw4bp1KlT6tOnjzZv3qwDBw5oxYoVevTRR5WZmalNmzbplVde0ZYtW5ScnKzFixfrP//5j+rXr+/u0gEAQAlQ4kZuIiIitGHDBo0aNUqdO3dWRkaGoqKi1LVrV3l4eMjPz0/r16/X66+/rtTUVEVFRWny5MmKj493d+kAAKAEcPvdUjdb9tXW3C0FAEDR4G4pAACAYkS4AQAAViHcAAAAqxBuAACAVQg3AADAKoQbAABgFcINAACwCuEGAABYhXADAACsQrgBAABWIdwAAACrEG4AAIBVCDcAAMAqhBsAAGAVwg0AALAK4QYAAFiFcAMAAKxCuAEAAFYh3AAAAKsQbgAAgFUINwAAwCqEGwAAYBXCDQAAsArhBgAAWIVwAwAArEK4AQAAViHcAAAAqxBuAACAVQg3AADAKoQbAABgFcINAACwCuEGAABYhXADAACsQrgBAABWIdwAAACrEG4AAIBVCDcAAMAqhBsAAGAVwg0AALAK4QYAAFiFcAMAAKxCuAEAAFYh3AAAAKsQbgAAgFUINwAAwCqEGwAAYBXCDQAAsArhBgAAWIVwAwAArEK4AQAAViHcAAAAqxBuAACAVQg3AADAKoQbAABgFcINAACwCuEGAABYhXADAACsQrgBAABWIdwAAACrEG4AAIBVCDcAAMAqhBsAAGAVwg0AALAK4QYAAFjFM78NmzdvLofDka+233//faELAgAAuBH5Djf33nuv8+sLFy5o5syZatCggWJiYiRJGzdu1O7duzV06NAiLxIAACC/8h1uxo4d6/z6z3/+s5588km99NJLOdr88ssvRVcdAABAATmMMaagC/n7+2vLli2qXbu2y/T9+/frtttuU0pKSpEVWNRSU1Pl7++vlJQU+fn5ubscAACQDwU5fxfqgmJfX19t2LAhx/QNGzbIx8enMKsEAAAoEvl+W+r3RowYoSFDhuj7779Xq1atJEmbNm3SnDlzNGbMmCItEAAAoCAKFW6effZZ1ahRQ1OnTtW7774rSapfv77mzp2rXr16FWmBAAAABVGoa25KM665AQCg9Cn2a24k6cyZM/rXv/6l5557TqdOnZJ05fk2v/76a2FXCQAAcMMK9bbUzp07FRcXJ39/fx06dEh//vOfFRQUpMWLFys5OVnvvPNOUdcJAACQL4UauXnqqac0YMAA7d+/3+XuqG7dumn9+vVFVhwAAEBBFSrcbN68WYMHD84x/ZZbbtGxY8duuCgAAIDCKlS48fb2Vmpqao7pP/74o0JCQm64KAAAgMIqVLjp0aOHXnzxRV26dEmS5HA4lJycrFGjRun+++8v0gIBAAAKolDhZvLkyUpPT1doaKjOnz+v2NhY1apVS5UrV9bLL79c1DUCAADkW6HulvL399fKlSv1zTffaOfOnUpPT1eLFi0UFxdX1PUBAAAUCA/xAwAAJV5Bzt/5HrmZNm2aBg0aJB8fH02bNu2abZ988sn8rhYAAKBI5Xvkpnr16tqyZYuqVKmi6tWr571Ch0MHDx4ssgKLGiM3AACUPsUycpOUlJTr1wAAACVJge+WunTpkmrWrKm9e/cWRz0AAAA3pMDhpnz58rpw4UJx1AIAAHDDCvWcm2HDhmnSpEm6fPlyUdcDAABwQwr1nJvNmzdr1apV+vLLL9W4cWNVrFjRZf7ixYuLpDgAAICCKlS4CQgI4GMWAABAiVTgcHP58mXddddd6ty5s8LDw4ujJgAAgEIr8DU3np6eeuKJJ5SRkVEc9QAAANyQQl1Q3KpVK23btq2oawEAALhhhbrmZujQoRo5cqQOHz6sli1b5riguEmTJkVSHAAAQEEV6oMzPTxyDvg4HA4ZY+RwOJSZmVkkxRUHPn4BAIDSp1g+fuH3+PgFAABQUhUq3ERFRRV1HQAAAEWiUOEm2549e5ScnKyLFy+6TO/Ro8cNFQUAAFBYhQo3Bw8eVM+ePbVr1y7ntTbSletuJJXoa24AAIDdCnUr+F//+ldVr15dJ06cUIUKFbR7926tX79et912m9auXVvEJQIAAORfoUZuEhIStHr1agUHB8vDw0MeHh5q27atJkyYoCeffJJn4AAAALcp1MhNZmamKleuLEkKDg7WkSNHJF250Hjfvn1FVx0AAEABFWrkplGjRtqxY4eqV6+u1q1b69VXX5WXl5feeust1ahRo6hrBAAAyLdChZu///3vOnv2rCRp/Pjx6t69u9q1a6cqVapo4cKFRVogAABAQRTqCcW5OXXqlAIDA513TJVUPKEYAIDSp9ieUDxw4MB8tZszZ05BVusW7f++QOW8fd1dBgAAVtn62iPuLqFg4WbevHmKiopS8+bNVUQDPgAAAEWqQOFmyJAhWrBggZKSkvToo4/qT3/6k4KCgoqrNgAAgAIr0K3gb7zxho4ePapnnnlGn332mSIjI9WrVy+tWLGCkRwAAFAiFPg5N97e3urTp49WrlypPXv2qGHDhho6dKiio6OVnp5eHDUCAADkW6Ee4udc2MPD+dlSfJ4UAAAoCQocbjIyMrRgwQL94Q9/UJ06dbRr1y7NmDFDycnJqlSpUnHUCAAAkG8FuqB46NChWrhwoSIjIzVw4EAtWLBAwcHBxVUbAABAgRUo3Lz55puqVq2aatSooXXr1mndunW5tlu8eHGRFAcAAFBQBQo3jzzySIl/AjEAACjbCvwQPwAAgJLshu6WAgAAKGkINwAAwCqEGwAAYBXCDQAAsArhBgAAWIVwAwAArEK4AQAAViHcAAAAqxBuAACAVQg3AADAKoQbAABgFcINAACwCuEGAABYhXADAACsQrgBAABWIdwAAACrEG4AAIBVCDcAAMAqhBsAAGAVwg0AALAK4QYAAFiFcAMAAKxCuAEAAFYh3AAAAKsQbgAAgFUINwAAwCqEGwAAYBXCDQAAsArhBgAAWIVwAwAArEK4AQAAViHcAAAAqxBuAACAVQg3AADAKoQbAABgFcINAACwCuEGAABYhXADAACsQrgBAABWIdwAAACrEG4AAIBVCDcAAMAqhBsAAGAVwg0AALAK4QYAAFiFcAMAAKxCuAEAAFYh3AAAAKsQbgAAgFUINwAAwCqEGwAAYBXCDQAAsArhBgAAWIVwAwAArEK4AQAAViHcAAAAqxBuAACAVQg3AADAKoQbAABglRITbgYMGCCHw6GJEye6TP/444/lcDjcVBUAAChtSky4kSQfHx9NmjRJp0+fdncpAACglCpR4SYuLk7h4eGaMGFCnm0++ugjNWzYUN7e3oqOjtbkyZNvYoUAAKCkK1Hhply5cnrllVc0ffp0HT58OMf8rVu3qlevXnrooYe0a9cujRs3TmPGjNG8efPyXGdGRoZSU1NdXgAAwF4lKtxIUs+ePdWsWTONHTs2x7wpU6aoU6dOGjNmjOrUqaMBAwZo+PDheu211/Jc34QJE+Tv7+98RUZGFmf5AADAzUpcuJGkSZMmaf78+dq7d6/L9L1796pNmzYu09q0aaP9+/crMzMz13WNHj1aKSkpztcvv/xSbHUDAAD3K5Hhpn379urSpYtGjx59w+vy9vaWn5+fywsAANjL090F5GXixIlq1qyZ6tat65xWv359bdiwwaXdhg0bVKdOHZUrV+5mlwgAAEqgEhtuGjdurH79+mnatGnOaSNHjtTtt9+ul156Sb1791ZCQoJmzJihmTNnurFSAABQkpTIt6Wyvfjii8rKynJ+36JFC33wwQdauHChGjVqpBdeeEEvvviiBgwY4L4iAQBAieIwxhh3F3Ezpaamyt/fX03/8qbKefu6uxwAAKyy9bVHimW92efvlJSU614/W6JHbgAAAAqKcAMAAKxCuAEAAFYh3AAAAKsQbgAAgFUINwAAwCqEGwAAYBXCDQAAsArhBgAAWIVwAwAArEK4AQAAViHcAAAAqxBuAACAVQg3AADAKoQbAABgFcINAACwCuEGAABYhXADAACsQrgBAABWIdwAAACrEG4AAIBVCDcAAMAqhBsAAGAVwg0AALAK4QYAAFiFcAMAAKxCuAEAAFYh3AAAAKsQbgAAgFUINwAAwCqEGwAAYBXCDQAAsArhBgAAWIVwAwAArEK4AQAAViHcAAAAqxBuAACAVQg3AADAKoQbAABgFcINAACwCuEGAABYhXADAACsQrgBAABWIdwAAACrEG4AAIBVCDcAAMAqhBsAAGAVwg0AALAK4QYAAFiFcAMAAKxCuAEAAFYh3AAAAKsQbgAAgFUINwAAwCqEGwAAYBXCDQAAsArhBgAAWIVwAwAArEK4AQAAViHcAAAAqxBuAACAVQg3AADAKoQbAABgFcINAACwCuEGAABYhXADAACsQrgBAABW8XR3Ae6y/h995Ofn5+4yAABAEWPkBgAAWIVwAwAArEK4AQAAViHcAAAAqxBuAACAVQg3AADAKoQbAABgFcINAACwCuEGAABYhXADAACsQrgBAABWIdwAAACrEG4AAIBVCDcAAMAqhBsAAGAVwg0AALAK4QYAAFjF090F3GzGGElSamqqmysBAAD5lX3ezj6PX0uZCze//fabJCkyMtLNlQAAgIJKS0uTv7//NduUuXATFBQkSUpOTr5u58BVamqqIiMj9csvv8jPz8/d5ZQa9Fvh0XeFQ78VDv1WeDej74wxSktLU0RExHXblrlw4+Fx5TIjf39/Dt5C8vPzo+8KgX4rPPqucOi3wqHfCq+4+y6/gxJcUAwAAKxCuAEAAFYpc+HG29tbY8eOlbe3t7tLKXXou8Kh3wqPvisc+q1w6LfCK2l95zD5uacKAACglChzIzcAAMBuhBsAAGAVwg0AALAK4QYAAFilzIWbN954Q9HR0fLx8VHr1q313Xffubsktxo3bpwcDofLq169es75Fy5c0LBhw1SlShVVqlRJ999/v44fP+6yjuTkZN19992qUKGCQkND9fTTT+vy5cs3e1eK1fr169W9e3dFRETI4XDo448/dplvjNELL7ygqlWrytfXV3Fxcdq/f79Lm1OnTqlfv37y8/NTQECAHnvsMaWnp7u02blzp9q1aycfHx9FRkbq1VdfLe5dK3bX67sBAwbkOAa7du3q0qYs9t2ECRN0++23q3LlygoNDdW9996rffv2ubQpqt/PtWvXqkWLFvL29latWrU0b9684t69YpOffuvQoUOOY+6JJ55waVPW+m3WrFlq0qSJ8yF8MTExWr58uXN+qTvWTBmycOFC4+XlZebMmWN2795tHn/8cRMQEGCOHz/u7tLcZuzYsaZhw4bm6NGjztd//vMf5/wnnnjCREZGmlWrVpktW7aYO+64w9x5553O+ZcvXzaNGjUycXFxZtu2bWbZsmUmODjYjB492h27U2yWLVtmnn/+ebN48WIjySxZssRl/sSJE42/v7/5+OOPzY4dO0yPHj1M9erVzfnz551tunbtapo2bWo2btxovv76a1OrVi3Tp08f5/yUlBQTFhZm+vXrZxITE82CBQuMr6+vmT179s3azWJxvb7r37+/6dq1q8sxeOrUKZc2ZbHvunTpYubOnWsSExPN9u3bTbdu3Uy1atVMenq6s01R/H4ePHjQVKhQwTz11FNmz549Zvr06aZcuXLmiy++uKn7W1Ty02+xsbHm8ccfdznmUlJSnPPLYr99+umn5vPPPzc//vij2bdvn3nuuedM+fLlTWJiojGm9B1rZSrctGrVygwbNsz5fWZmpomIiDATJkxwY1XuNXbsWNO0adNc5505c8aUL1/efPjhh85pe/fuNZJMQkKCMebKicvDw8McO3bM2WbWrFnGz8/PZGRkFGvt7nL1CTorK8uEh4eb1157zTntzJkzxtvb2yxYsMAYY8yePXuMJLN582Znm+XLlxuHw2F+/fVXY4wxM2fONIGBgS79NmrUKFO3bt1i3qObJ69wc8899+S5DH13xYkTJ4wks27dOmNM0f1+PvPMM6Zhw4Yu2+rdu7fp0qVLce/STXF1vxlzJdz89a9/zXMZ+u2KwMBA869//atUHmtl5m2pixcvauvWrYqLi3NO8/DwUFxcnBISEtxYmfvt379fERERqlGjhvr166fk5GRJ0tatW3Xp0iWXPqtXr56qVavm7LOEhAQ1btxYYWFhzjZdunRRamqqdu/efXN3xE2SkpJ07Ngxl37y9/dX69atXfopICBAt912m7NNXFycPDw8tGnTJmeb9u3by8vLy9mmS5cu2rdvn06fPn2T9sY91q5dq9DQUNWtW1dDhgzRb7/95pxH312RkpIi6f8//Leofj8TEhJc1pHdxpa/i1f3W7b33ntPwcHBatSokUaPHq1z584555X1fsvMzNTChQt19uxZxcTElMpjrcx8cObJkyeVmZnp0vGSFBYWph9++MFNVblf69atNW/ePNWtW1dHjx7V+PHj1a5dOyUmJurYsWPy8vJSQECAyzJhYWE6duyYJOnYsWO59mn2vLIgez9z64ff91NoaKjLfE9PTwUFBbm0qV69eo51ZM8LDAwslvrdrWvXrrrvvvtUvXp1HThwQM8995zi4+OVkJCgcuXK0XeSsrKyNGLECLVp00aNGjWSpCL7/cyrTWpqqs6fPy9fX9/i2KWbIrd+k6S+ffsqKipKERER2rlzp0aNGqV9+/Zp8eLFkspuv+3atUsxMTG6cOGCKlWqpCVLlqhBgwbavn17qTvWyky4Qe7i4+OdXzdp0kStW7dWVFSUPvjgg1L5y4nS56GHHnJ+3bhxYzVp0kQ1a9bU2rVr1alTJzdWVnIMGzZMiYmJ+uabb9xdSqmSV78NGjTI+XXjxo1VtWpVderUSQcOHFDNmjVvdpklRt26dbV9+3alpKRo0aJF6t+/v9atW+fusgqlzLwtFRwcrHLlyuW4uvv48eMKDw93U1UlT0BAgOrUqaOffvpJ4eHhunjxos6cOePS5vd9Fh4enmufZs8rC7L381rHVnh4uE6cOOEy//Llyzp16hR9eZUaNWooODhYP/30kyT6bvjw4Vq6dKnWrFmjW2+91Tm9qH4/82rj5+dXqv/ByavfctO6dWtJcjnmymK/eXl5qVatWmrZsqUmTJigpk2baurUqaXyWCsz4cbLy0stW7bUqlWrnNOysrK0atUqxcTEuLGykiU9PV0HDhxQ1apV1bJlS5UvX96lz/bt26fk5GRnn8XExGjXrl0uJ5+VK1fKz89PDRo0uOn1u0P16tUVHh7u0k+pqanatGmTSz+dOXNGW7dudbZZvXq1srKynH9YY2JitH79el26dMnZZuXKlapbt26pf1ulIA4fPqzffvtNVatWlVR2+84Yo+HDh2vJkiVavXp1jrfdiur3MyYmxmUd2W1K69/F6/VbbrZv3y5JLsdcWeu33GRlZSkjI6N0HmtFfolyCbZw4ULj7e1t5s2bZ/bs2WMGDRpkAgICXK7uLmtGjhxp1q5da5KSksyGDRtMXFycCQ4ONidOnDDGXLn9r1q1amb16tVmy5YtJiYmxsTExDiXz779r3Pnzmb79u3miy++MCEhIdbdCp6Wlma2bdtmtm3bZiSZKVOmmG3btpmff/7ZGHPlVvCAgADzySefmJ07d5p77rkn11vBmzdvbjZt2mS++eYbU7t2bZfbmc+cOWPCwsLMww8/bBITE83ChQtNhQoVSvXtzMZcu+/S0tLM3/72N5OQkGCSkpLMV199ZVq0aGFq165tLly44FxHWey7IUOGGH9/f7N27VqXW5bPnTvnbFMUv5/Zt+c+/fTTZu/eveaNN94o1bc0X6/ffvrpJ/Piiy+aLVu2mKSkJPPJJ5+YGjVqmPbt2zvXURb77dlnnzXr1q0zSUlJZufOnebZZ581DofDfPnll8aY0neslalwY4wx06dPN9WqVTNeXl6mVatWZuPGje4uya169+5tqlatary8vMwtt9xievfubX766Sfn/PPnz5uhQ4eawMBAU6FCBdOzZ09z9OhRl3UcOnTIxMfHG19fXxMcHGxGjhxpLl26dLN3pVitWbPGSMrx6t+/vzHmyu3gY8aMMWFhYcbb29t06tTJ7Nu3z2Udv/32m+nTp4+pVKmS8fPzM48++qhJS0tzabNjxw7Ttm1b4+3tbW655RYzceLEm7WLxeZafXfu3DnTuXNnExISYsqXL2+ioqLM448/nuMfjrLYd7n1mSQzd+5cZ5ui+v1cs2aNadasmfHy8jI1atRw2UZpc71+S05ONu3btzdBQUHG29vb1KpVyzz99NMuz7kxpuz128CBA01UVJTx8vIyISEhplOnTs5gY0zpO9YcxhhT9ONBAAAA7lFmrrkBAABlA+EGAABYhXADAACsQrgBAABWIdwAAACrEG4AAIBVCDcAAMAqhBsAAGAVwg0A/J9Dhw7J4XA4P2sIQOlEuAEAAFYh3AAoMbKysvTqq6+qVq1a8vb2VrVq1fTyyy9Lknbt2qWOHTvK19dXVapU0aBBg5Senu5ctkOHDhoxYoTL+u69914NGDDA+X10dLReeeUVDRw4UJUrV1a1atX01ltvOednf4J08+bN5XA41KFDh2LbVwDFh3ADoMQYPXq0Jk6cqDFjxmjPnj16//33FRYWprNnz6pLly4KDAzU5s2b9eGHH+qrr77S8OHDC7yNyZMn67bbbtO2bds0dOhQDRkyRPv27ZMkfffdd5Kkr776SkePHtXixYuLdP8A3Bye7i4AACQpLS1NU6dO1YwZM9S/f39JUs2aNdW2bVu9/fbbunDhgt555x1VrFhRkjRjxgx1795dkyZNUlhYWL63061bNw0dOlSSNGrUKP3zn//UmjVrVLduXYWEhEiSqlSpovDw8CLeQwA3CyM3AEqEvXv3KiMjQ506dcp1XtOmTZ3BRpLatGmjrKws56hLfjVp0sT5tcPhUHh4uE6cOFH4wgGUOIQbACWCr6/vDS3v4eEhY4zLtEuXLuVoV758eZfvHQ6HsrKybmjbAEoWwg2AEqF27dry9fXVqlWrcsyrX7++duzYobNnzzqnbdiwQR4eHqpbt64kKSQkREePHnXOz8zMVGJiYoFq8PLyci4LoPQi3AAoEXx8fDRq1Cg988wzeuedd3TgwAFt3LhR//73v9WvXz/5+Piof//+SkxM1Jo1a/SXv/xFDz/8sPN6m44dO+rzzz/X559/rh9++EFDhgzRmTNnClRDaGiofH199cUXX+j48eNKSUkphj0FUNwINwBKjDFjxmjkyJF64YUXVL9+ffXu3VsnTpxQhQoVtGLFCp06dUq33367HnjgAXXq1EkzZsxwLjtw4ED1799fjzzyiGJjY1WjRg3dddddBdq+p6enpk2bptmzZysiIkL33HNPUe8igJvAYa5+kxoAAKAUY+QGAABYhXADAACsQrgBAABWIdwAAACrEG4AAIBVCDcAAMAqhBsAAGAVwg0AALAK4QYAAFiFcAMAAKxCuAEAAFYh3AAAAKv8L+iIdO9FklNcAAAAAElFTkSuQmCC",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.countplot(data['Married'])\n",
    "plt.title('Marital Status Countplot');"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 362,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.countplot(data['Internet_Service'])\n",
    "plt.title('Countplot of Internet Services');"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 363,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1200x400 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(12, 4))\n",
    "sns.boxplot(data=data,x =\"Tenure_in_Months\")\n",
    "plt.title('Distribution of Tenure in Months');"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 364,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1200x400 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(12, 4))\n",
    "sns.boxplot(data=data, x=\"Age\")\n",
    "plt.title('Distribution of Age');"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 365,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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6YMeOHRqX8TIyMrBhwwa89NJLVbpEVZFPP/0UM2bMwIQJEx7axtfXFyqVCp9//rnGe1fq/kcflI5rqe57YGtri3bt2mHNmjUafZw+fRp79uyRji9dXV34+vpi+/btuHLlitQuOTkZUVFRFW6nY8eOsLKywsqVKzUuWe3atQvJyckax2lN09XVhUKh0DjOL1269NCvbRk8eDBu3ryJd999F7m5uXjnnXdqtJ6qfL6VVRP/F+jZwzNEVOc1bdoUGzZswNtvvw0XFxeNJ1UfOXIEW7ZskZ7N0rZtWwQEBGDVqlXIysqCl5cXjh8/jjVr1qBv374aZ2dGjhyJMWPGoF+/fnj55Zdx8uRJREVFoUGDBtWu1c3NDStWrMCnn34KJycnWFlZaZwBKCgoQPfu3fHWW28hJSUFy5cvx0svvYRXX331oX2OHj0aX3/9NYYOHYqEhAQ4Ojrixx9/xOHDh7F48WJpwLmhoSFcXV2xefNmODs7w9zcHK1atUKrVq2qtA+ffvopoqOj8dJLL2HcuHHQ09PD119/jfz8fMybN696b8xDeHl5SYHuYVQqFVasWIHBgwejQ4cO6N+/PywtLXHlyhXs3LkTL774Ir766isA995/AHjvvffg6+sLXV1d9O/fv0o1zZ8/H7169YKHhwdGjBiBO3fuYNmyZVCr1RrPspk1axZ2796NLl26YNy4cVJIbdmyJU6dOvXIbdSrVw9ffPEFhg0bBi8vLwwYMAAZGRlYsmQJHB0dMWnSpCrVXBV+fn5YuHAhevbsiYEDByIzMxNhYWFwcnIqt+727dujVatW2LJlC1xcXNChQ4caracqn29l1dT/BXrGaPcmN6Kn588//xSjRo0Sjo6OQl9fX5iamooXX3xRLFu2TLqFVwghCgsLxaxZs0Tjxo1FvXr1hL29vQgJCdFoI4QQxcXFIjg4WDRo0EAYGRkJX19fcf78+Yfedv/gbc/79+8XAMT+/fuleenp6cLPz0+YmpoKANLt86V9xMXFidGjR4v69esLExMTMWjQII3bu4Uoe9u9EEJkZGSIYcOGiQYNGgh9fX3RunVrER4eXuY9OnLkiHBzcxP6+voV3nb8sNvuhRDi999/F76+vsLExEQYGRmJrl27lnn+TVVuB69oe/cr7zlEQtx7v319fYVarRYGBgaiadOmYujQoeK3336T2hQVFYkJEyYIS0tLoVAopNvfH7Xt8t6nvXv3ihdffFEYGhoKlUolXnnlFXH27Nky68bFxUnvd5MmTcTKlSvFjBkzKvUcIiGE2Lx5s2jfvr1QKpXC3NxcDBo0SLo1vlR1bruvqO13330nmjVrJpRKpWjRooUIDw9/ZN2lj4f4/PPPyyx72Htb+v9jy5YtlaqxMp/vw46N8mqvyv8FqhsUQtSx0YBEdVBERASGDRuGEydOPNEvUCV6EpYsWYJJkybh0qVLZe4mI6otOIaIiIieGCEEvvvuO3h5eTEMUa3GMURERFTj8vLy8PPPP2P//v1ISkrCjh07tF0S0SMxEBERUY27fv06Bg4cCDMzM3z00UePHPhPVBtwDBERERHJHscQERERkewxEBEREZHscQxRJZSUlODatWswNTXlI92JiIieEUII3Lp1C3Z2dmW+4PpBDESVcO3atRr7/iUiIiJ6uq5evYqGDRs+sg0DUSWUfrXB1atXa/R7mIiIiOjJycnJgb29vfR7/FEYiCqh9DKZSqViICIiInrGVGa4CwdVExERkewxEBEREZHsaTUQrVixAm3atJEuRXl4eGDXrl3Scm9vbygUCo3XmDFjNPq4cuUK/Pz8YGRkBCsrK0yZMgVFRUUabWJjY9GhQwcolUo4OTkhIiLiaeweERERPSO0OoaoYcOGmDt3Lpo1awYhBNasWQN/f3/88ccfaNmyJQBg1KhRmD17trSOkZGR9O/i4mL4+fnBxsYGR44cQVpaGoYMGYJ69erh888/BwBcvHgRfn5+GDNmDNavX4+YmBiMHDkStra28PX1fbo7TERERLVSrfvqDnNzc8yfPx8jRoyAt7c32rVrh8WLF5fbdteuXejTpw+uXbsGa2trAMDKlSsRHByM69evQ19fH8HBwdi5cydOnz4trde/f39kZWVh9+7dlaopJycHarUa2dnZHFRNRET0jKjK7+9aM4aouLgYmzZtQl5eHjw8PKT569evR4MGDdCqVSuEhITg9u3b0rL4+Hi0bt1aCkMA4Ovri5ycHJw5c0Zq4+Pjo7EtX19fxMfHP7SW/Px85OTkaLyIiIio7tL6bfdJSUnw8PDA3bt3YWJigm3btsHV1RUAMHDgQDg4OMDOzg6nTp1CcHAwUlJSsHXrVgBAenq6RhgCIE2np6c/sk1OTg7u3LkDQ0PDMjWFhoZi1qxZNb6vREREVDtpPRA1b94ciYmJyM7Oxo8//oiAgADExcXB1dUVo0ePltq1bt0atra26N69Oy5cuICmTZs+sZpCQkIQFBQkTZc+2ImIiIjqJq1fMtPX14eTkxPc3NwQGhqKtm3bYsmSJeW2dXd3BwCcP38eAGBjY4OMjAyNNqXTNjY2j2yjUqnKPTsEAEqlUrrzjQ9jJCIiqvu0HogeVFJSgvz8/HKXJSYmAgBsbW0BAB4eHkhKSkJmZqbUJjo6GiqVSrrs5uHhgZiYGI1+oqOjNcYpERERkbxp9ZJZSEgIevXqhUaNGuHWrVvYsGEDYmNjERUVhQsXLmDDhg3o3bs3LCwscOrUKUyaNAmenp5o06YNAKBHjx5wdXXF4MGDMW/ePKSnp2PatGkIDAyEUqkEAIwZMwZfffUVpk6diuHDh2Pfvn344YcfsHPnTm3uOhEREdUiWg1EmZmZGDJkCNLS0qBWq9GmTRtERUXh5ZdfxtWrV7F3714sXrwYeXl5sLe3R79+/TBt2jRpfV1dXURGRmLs2LHw8PCAsbExAgICNJ5b1LhxY+zcuROTJk3CkiVL0LBhQ3z77bd8BhERERFJat1ziGojPoeIiIjo2fNMPoeIiIiISFsYiIiIiEj2tP4cIiLSHrcpa7VdAtUyCfOHaLsEIq3gGSIiIiKSPQYiIiIikj0GIiIiIpI9BiIiIiKSPQYiIiIikj0GIiIiIpI9BiIiIiKSPQYiIiIikj0GIiIiIpI9BiIiIiKSPQYiIiIikj0GIiIiIpI9BiIiIiKSPQYiIiIikj0GIiIiIpI9BiIiIiKSPQYiIiIikj0GIiIiIpI9BiIiIiKSPQYiIiIikj0GIiIiIpI9BiIiIiKSPQYiIiIikj0GIiIiIpI9BiIiIiKSPQYiIiIikj0GIiIiIpI9BiIiIiKSPQYiIiIikj0GIiIiIpI9BiIiIiKSPQYiIiIikj0GIiIiIpI9BiIiIiKSPQYiIiIikj0GIiIiIpI9BiIiIiKSPa0GohUrVqBNmzZQqVRQqVTw8PDArl27pOV3795FYGAgLCwsYGJign79+iEjI0OjjytXrsDPzw9GRkawsrLClClTUFRUpNEmNjYWHTp0gFKphJOTEyIiIp7G7hEREdEzQquBqGHDhpg7dy4SEhLw22+/oVu3bvD398eZM2cAAJMmTcIvv/yCLVu2IC4uDteuXcPrr78urV9cXAw/Pz8UFBTgyJEjWLNmDSIiIjB9+nSpzcWLF+Hn54euXbsiMTEREydOxMiRIxEVFfXU95eIiIhqJ4UQQmi7iPuZm5tj/vz5eOONN2BpaYkNGzbgjTfeAACcO3cOLi4uiI+PR+fOnbFr1y706dMH165dg7W1NQBg5cqVCA4OxvXr16Gvr4/g4GDs3LkTp0+flrbRv39/ZGVlYffu3ZWqKScnB2q1GtnZ2VCpVDW/00Ra4jZlrbZLoFomYf4QbZdAVGOq8vu71owhKi4uxqZNm5CXlwcPDw8kJCSgsLAQPj4+UpsWLVqgUaNGiI+PBwDEx8ejdevWUhgCAF9fX+Tk5EhnmeLj4zX6KG1T2kd58vPzkZOTo/EiIiKiukvrgSgpKQkmJiZQKpUYM2YMtm3bBldXV6Snp0NfXx9mZmYa7a2trZGeng4ASE9P1whDpctLlz2qTU5ODu7cuVNuTaGhoVCr1dLL3t6+JnaViIiIaimtB6LmzZsjMTERx44dw9ixYxEQEICzZ89qtaaQkBBkZ2dLr6tXr2q1HiIiInqy9LRdgL6+PpycnAAAbm5uOHHiBJYsWYK3334bBQUFyMrK0jhLlJGRARsbGwCAjY0Njh8/rtFf6V1o97d58M60jIwMqFQqGBoalluTUqmEUqmskf0jIiKi2k/rZ4geVFJSgvz8fLi5uaFevXqIiYmRlqWkpODKlSvw8PAAAHh4eCApKQmZmZlSm+joaKhUKri6ukpt7u+jtE1pH0RERERaPUMUEhKCXr16oVGjRrh16xY2bNiA2NhYREVFQa1WY8SIEQgKCoK5uTlUKhUmTJgADw8PdO7cGQDQo0cPuLq6YvDgwZg3bx7S09Mxbdo0BAYGSmd4xowZg6+++gpTp07F8OHDsW/fPvzwww/YuXOnNnediIiIahGtBqLMzEwMGTIEaWlpUKvVaNOmDaKiovDyyy8DABYtWgQdHR3069cP+fn58PX1xfLly6X1dXV1ERkZibFjx8LDwwPGxsYICAjA7NmzpTaNGzfGzp07MWnSJCxZsgQNGzbEt99+C19f36e+v0RERFQ71brnENVGfA4R1VV8DhE9iM8horrkmXwOEREREZG2MBARERGR7DEQERERkewxEBEREZHsMRARERGR7DEQERERkewxEBEREZHsMRARERGR7DEQERERkewxEBEREZHsMRARERGR7DEQERERkewxEBEREZHsMRARERGR7DEQERERkewxEBEREZHsMRARERGR7DEQERERkewxEBEREZHsMRARERGR7DEQERERkewxEBEREZHsMRARERGR7DEQERERkewxEBEREZHsMRARERGR7DEQERERkewxEBEREZHsMRARERGR7DEQERERkewxEBEREZHsMRARERGR7DEQERERkewxEBEREZHsMRARERGR7DEQERERkewxEBEREZHsMRARERGR7DEQERERkewxEBEREZHsMRARERGR7Gk1EIWGhqJTp04wNTWFlZUV+vbti5SUFI023t7eUCgUGq8xY8ZotLly5Qr8/PxgZGQEKysrTJkyBUVFRRptYmNj0aFDByiVSjg5OSEiIuJJ7x4RERE9I7QaiOLi4hAYGIijR48iOjoahYWF6NGjB/Ly8jTajRo1CmlpadJr3rx50rLi4mL4+fmhoKAAR44cwZo1axAREYHp06dLbS5evAg/Pz907doViYmJmDhxIkaOHImoqKintq9ERERUe+lpc+O7d+/WmI6IiICVlRUSEhLg6ekpzTcyMoKNjU25fezZswdnz57F3r17YW1tjXbt2mHOnDkIDg7GzJkzoa+vj5UrV6Jx48ZYsGABAMDFxQWHDh3CokWL4Ovr++R2kIiIiJ4JtWoMUXZ2NgDA3NxcY/769evRoEEDtGrVCiEhIbh9+7a0LD4+Hq1bt4a1tbU0z9fXFzk5OThz5ozUxsfHR6NPX19fxMfHl1tHfn4+cnJyNF5ERERUd2n1DNH9SkpKMHHiRLz44oto1aqVNH/gwIFwcHCAnZ0dTp06heDgYKSkpGDr1q0AgPT0dI0wBECaTk9Pf2SbnJwc3LlzB4aGhhrLQkNDMWvWrBrfRyIiIqqdak0gCgwMxOnTp3Ho0CGN+aNHj5b+3bp1a9ja2qJ79+64cOECmjZt+kRqCQkJQVBQkDSdk5MDe3v7J7ItIiIi0r5accls/PjxiIyMxP79+9GwYcNHtnV3dwcAnD9/HgBgY2ODjIwMjTal06Xjjh7WRqVSlTk7BABKpRIqlUrjRURERHWXVgOREALjx4/Htm3bsG/fPjRu3LjCdRITEwEAtra2AAAPDw8kJSUhMzNTahMdHQ2VSgVXV1epTUxMjEY/0dHR8PDwqKE9ISIiomeZVgNRYGAgvv/+e2zYsAGmpqZIT09Heno67ty5AwC4cOEC5syZg4SEBFy6dAk///wzhgwZAk9PT7Rp0wYA0KNHD7i6umLw4ME4efIkoqKiMG3aNAQGBkKpVAIAxowZg7/++gtTp07FuXPnsHz5cvzwww+YNGmS1vadiIiIag+tBqIVK1YgOzsb3t7esLW1lV6bN28GAOjr62Pv3r3o0aMHWrRogcmTJ6Nfv3745ZdfpD50dXURGRkJXV1deHh44J133sGQIUMwe/ZsqU3jxo2xc+dOREdHo23btliwYAG+/fZb3nJPREREAACFEEJou4jaLicnB2q1GtnZ2RxPRHWK25S12i6BapmE+UO0XQJRjanK7+9aMaiaiIiISJsYiIiIiEj2GIiIiIhI9hiIiIiISPYYiIiIiEj2GIiIiIhI9hiIiIiISPYYiIiIiEj2GIiIiIhI9hiIiIiISPYYiIiIiEj2GIiIiIhI9hiIiIiISPYYiIiIiEj2GIiIiIhI9vS0XYCcuE1Zq+0SqBZJmD9E2yUQEdH/4xkiIiIikj0GIiIiIpI9BiIiIiKSPQYiIiIikj0GIiIiIpI9BiIiIiKSPQYiIiIikj0GIiIiIpI9BiIiIiKSPQYiIiIikj0GIiIiIpI9BiIiIiKSPQYiIiIikj0GIiIiIpI9BiIiIiKSPQYiIiIikj0GIiIiIpI9BiIiIiKSPQYiIiIikj0GIiIiIpI9BiIiIiKSPQYiIiIikj0GIiIiIpI9BiIiIiKSPa0GotDQUHTq1AmmpqawsrJC3759kZKSotHm7t27CAwMhIWFBUxMTNCvXz9kZGRotLly5Qr8/PxgZGQEKysrTJkyBUVFRRptYmNj0aFDByiVSjg5OSEiIuJJ7x4RERE9I7QaiOLi4hAYGIijR48iOjoahYWF6NGjB/Ly8qQ2kyZNwi+//IItW7YgLi4O165dw+uvvy4tLy4uhp+fHwoKCnDkyBGsWbMGERERmD59utTm4sWL8PPzQ9euXZGYmIiJEydi5MiRiIqKeqr7S0RERLWTQgghtF1EqevXr8PKygpxcXHw9PREdnY2LC0tsWHDBrzxxhsAgHPnzsHFxQXx8fHo3Lkzdu3ahT59+uDatWuwtrYGAKxcuRLBwcG4fv069PX1ERwcjJ07d+L06dPStvr374+srCzs3r27wrpycnKgVquRnZ0NlUpV7f1zm7K22utS3ZMwf4i2S+AxSWXUhuOSqKZU5fd3rRpDlJ2dDQAwNzcHACQkJKCwsBA+Pj5SmxYtWqBRo0aIj48HAMTHx6N169ZSGAIAX19f5OTk4MyZM1Kb+/sobVPax4Py8/ORk5Oj8SIiIqK6q9YEopKSEkycOBEvvvgiWrVqBQBIT0+Hvr4+zMzMNNpaW1sjPT1danN/GCpdXrrsUW1ycnJw586dMrWEhoZCrVZLL3t7+xrZRyIiIqqdak0gCgwMxOnTp7Fp0yZtl4KQkBBkZ2dLr6tXr2q7JCIiInqC9LRdAACMHz8ekZGROHDgABo2bCjNt7GxQUFBAbKysjTOEmVkZMDGxkZqc/z4cY3+Su9Cu7/Ng3emZWRkQKVSwdDQsEw9SqUSSqWyRvaNiIiIaj+tniESQmD8+PHYtm0b9u3bh8aNG2ssd3NzQ7169RATEyPNS0lJwZUrV+Dh4QEA8PDwQFJSEjIzM6U20dHRUKlUcHV1ldrc30dpm9I+iIiISN60eoYoMDAQGzZswI4dO2BqaiqN+VGr1TA0NIRarcaIESMQFBQEc3NzqFQqTJgwAR4eHujcuTMAoEePHnB1dcXgwYMxb948pKenY9q0aQgMDJTO8owZMwZfffUVpk6diuHDh2Pfvn344YcfsHPnTq3tOxEREdUe1TpD1K1bN2RlZZWZn5OTg27dulW6nxUrViA7Oxve3t6wtbWVXps3b5baLFq0CH369EG/fv3g6ekJGxsbbN26VVquq6uLyMhI6OrqwsPDA++88w6GDBmC2bNnS20aN26MnTt3Ijo6Gm3btsWCBQvw7bffwtfXtzq7T0RERHVMtZ5DpKOjg/T0dFhZWWnMz8zMxHPPPYfCwsIaK7A24HOI6EmoDc974TFJD6oNxyVRTanK7+8qXTI7deqU9O+zZ89Kl7iAe0+M3r17N5577rkqlktERESkXVUKRO3atYNCoYBCoSj30pihoSGWLVtWY8URERERPQ1VCkQXL16EEAJNmjTB8ePHYWlpKS3T19eHlZUVdHV1a7xIIiIioiepSoHIwcEBwL2nShMRERHVFdW+7T41NRX79+9HZmZmmYB0/zfNExEREdV21QpE33zzDcaOHYsGDRrAxsYGCoVCWqZQKBiIiIiI6JlSrUD06aef4rPPPkNwcHBN10NERET01FXrwYw3b97Em2++WdO1EBEREWlFtQLRm2++iT179tR0LURERERaUa1LZk5OTvjkk09w9OhRtG7dGvXq1dNY/t5779VIcURERERPQ7UC0apVq2BiYoK4uDjExcVpLFMoFAxERERE9EypViC6ePFiTddBREREpDXVGkNEREREVJdU6wzR8OHDH7l89erV1SqGiIiISBuqFYhu3rypMV1YWIjTp08jKyur3C99JSIiIqrNqhWItm3bVmZeSUkJxo4di6ZNmz52UURERERPU42NIdLR0UFQUBAWLVpUU10SERERPRU1Oqj6woULKCoqqskuiYiIiJ64al0yCwoK0pgWQiAtLQ07d+5EQEBAjRRGRERE9LRUKxD98ccfGtM6OjqwtLTEggULKrwDjYiIiKi2qVYg2r9/f03XQURERKQ11QpEpa5fv46UlBQAQPPmzWFpaVkjRRERERE9TdUaVJ2Xl4fhw4fD1tYWnp6e8PT0hJ2dHUaMGIHbt2/XdI1ERERET1S1AlFQUBDi4uLwyy+/ICsrC1lZWdixYwfi4uIwefLkmq6RiIiI6Imq1iWzn376CT/++CO8vb2leb1794ahoSHeeustrFixoqbqIyIiInriqnWG6Pbt27C2ti4z38rKipfMiIiI6JlTrUDk4eGBGTNm4O7du9K8O3fuYNasWfDw8Kix4oiIiIiehmpdMlu8eDF69uyJhg0bom3btgCAkydPQqlUYs+ePTVaIBEREdGTVq1A1Lp1a6SmpmL9+vU4d+4cAGDAgAEYNGgQDA0Na7RAIiIioietWoEoNDQU1tbWGDVqlMb81atX4/r16wgODq6R4oiIiIiehmqNIfr666/RokWLMvNbtmyJlStXPnZRRERERE9TtQJReno6bG1ty8y3tLREWlraYxdFRERE9DRVKxDZ29vj8OHDZeYfPnwYdnZ2j10UERER0dNUrTFEo0aNwsSJE1FYWIhu3boBAGJiYjB16lQ+qZqIiIieOdUKRFOmTMF///2HcePGoaCgAABgYGCA4OBghISE1GiBRERERE9atQKRQqHAF198gU8++QTJyckwNDREs2bNoFQqa7o+IiIioieuWoGolImJCTp16lRTtRARERFpRbUGVRMRERHVJQxEREREJHsMRERERCR7DEREREQke1oNRAcOHMArr7wCOzs7KBQKbN++XWP50KFDoVAoNF49e/bUaHPjxg0MGjQIKpUKZmZmGDFiBHJzczXanDp1Cl26dIGBgQHs7e0xb968J71rRERE9AzRaiDKy8tD27ZtERYW9tA2PXv2RFpamvTauHGjxvJBgwbhzJkziI6ORmRkJA4cOIDRo0dLy3NyctCjRw84ODggISEB8+fPx8yZM7Fq1aontl9ERET0bHms2+4fV69evdCrV69HtlEqlbCxsSl3WXJyMnbv3o0TJ06gY8eOAIBly5ahd+/e+PLLL2FnZ4f169ejoKAAq1evhr6+Plq2bInExEQsXLhQIzgRERGRfNX6MUSxsbGwsrJC8+bNMXbsWPz333/Ssvj4eJiZmUlhCAB8fHygo6ODY8eOSW08PT2hr68vtfH19UVKSgpu3rxZ7jbz8/ORk5Oj8SIiIqK6q1YHop49e2Lt2rWIiYnBF198gbi4OPTq1QvFxcUAgPT0dFhZWWmso6enB3Nzc6Snp0ttrK2tNdqUTpe2eVBoaCjUarX0sre3r+ldIyIiolpEq5fMKtK/f3/p361bt0abNm3QtGlTxMbGonv37k9suyEhIQgKCpKmc3JyGIqIiIjqsFp9huhBTZo0QYMGDXD+/HkAgI2NDTIzMzXaFBUV4caNG9K4IxsbG2RkZGi0KZ1+2NgkpVIJlUql8SIiIqK665kKRH///Tf+++8/2NraAgA8PDyQlZWFhIQEqc2+fftQUlICd3d3qc2BAwdQWFgotYmOjkbz5s1Rv379p7sDREREVCtpNRDl5uYiMTERiYmJAICLFy8iMTERV65cQW5uLqZMmYKjR4/i0qVLiImJgb+/P5ycnODr6wsAcHFxQc+ePTFq1CgcP34chw8fxvjx49G/f3/Y2dkBAAYOHAh9fX2MGDECZ86cwebNm7FkyRKNS2JEREQkb1oNRL/99hvat2+P9u3bAwCCgoLQvn17TJ8+Hbq6ujh16hReffVVODs7Y8SIEXBzc8PBgwehVCqlPtavX48WLVqge/fu6N27N1566SWNZwyp1Wrs2bMHFy9ehJubGyZPnozp06fzlnsiIiKSaHVQtbe3N4QQD10eFRVVYR/m5ubYsGHDI9u0adMGBw8erHJ9REREJA/P1BgiIiIioieBgYiIiIhkj4GIiIiIZI+BiIiIiGSPgYiIiIhkj4GIiIiIZI+BiIiIiGSPgYiIiIhkj4GIiIiIZI+BiIiIiGSPgYiIiIhkj4GIiIiIZI+BiIiIiGSPgYiIiIhkj4GIiIiIZI+BiIiIiGSPgYiIiIhkj4GIiIiIZI+BiIiIiGSPgYiIiIhkj4GIiIiIZI+BiIiIiGSPgYiIiIhkj4GIiIiIZI+BiIiIiGSPgYiIiIhkj4GIiIiIZI+BiIiIiGSPgYiIiIhkj4GIiIiIZI+BiIiIiGSPgYiIiIhkj4GIiIiIZI+BiIiIiGSPgYiIiIhkj4GIiIiIZI+BiIiIiGSPgYiIiIhkj4GIiIiIZI+BiIiIiGRPq4HowIEDeOWVV2BnZweFQoHt27drLBdCYPr06bC1tYWhoSF8fHyQmpqq0ebGjRsYNGgQVCoVzMzMMGLECOTm5mq0OXXqFLp06QIDAwPY29tj3rx5T3rXiIiI6Bmi1UCUl5eHtm3bIiwsrNzl8+bNw9KlS7Fy5UocO3YMxsbG8PX1xd27d6U2gwYNwpkzZxAdHY3IyEgcOHAAo0ePlpbn5OSgR48ecHBwQEJCAubPn4+ZM2di1apVT3z/iIiI6Nmgp82N9+rVC7169Sp3mRACixcvxrRp0+Dv7w8AWLt2LaytrbF9+3b0798fycnJ2L17N06cOIGOHTsCAJYtW4bevXvjyy+/hJ2dHdavX4+CggKsXr0a+vr6aNmyJRITE7Fw4UKN4ERERETyVWvHEF28eBHp6enw8fGR5qnVari7uyM+Ph4AEB8fDzMzMykMAYCPjw90dHRw7NgxqY2npyf09fWlNr6+vkhJScHNmzef0t4QERFRbabVM0SPkp6eDgCwtrbWmG9tbS0tS09Ph5WVlcZyPT09mJuba7Rp3LhxmT5Kl9WvX7/MtvPz85Gfny9N5+TkPObeEBERUW1Wa88QaVNoaCjUarX0sre313ZJRERE9ATV2kBkY2MDAMjIyNCYn5GRIS2zsbFBZmamxvKioiLcuHFDo015fdy/jQeFhIQgOztbel29evXxd4iIiIhqrVobiBo3bgwbGxvExMRI83JycnDs2DF4eHgAADw8PJCVlYWEhASpzb59+1BSUgJ3d3epzYEDB1BYWCi1iY6ORvPmzcu9XAYASqUSKpVK40VERER1l1YDUW5uLhITE5GYmAjg3kDqxMREXLlyBQqFAhMnTsSnn36Kn3/+GUlJSRgyZAjs7OzQt29fAICLiwt69uyJUaNG4fjx4zh8+DDGjx+P/v37w87ODgAwcOBA6OvrY8SIEThz5gw2b96MJUuWICgoSEt7TURERLWNVgdV//bbb+jatas0XRpSAgICEBERgalTpyIvLw+jR49GVlYWXnrpJezevRsGBgbSOuvXr8f48ePRvXt36OjooF+/fli6dKm0XK1WY8+ePQgMDISbmxsaNGiA6dOn85Z7IiIikiiEEELbRdR2OTk5UKvVyM7OfqzLZ25T1tZgVfSsS5g/RNsl8JikMmrDcUlUU6ry+7vWjiEiIiIieloYiIiIiEj2GIiIiIhI9hiIiIiISPYYiIiIiEj2GIiIiIhI9hiIiIiISPYYiIiIiEj2GIiIiIhI9hiIiIiISPYYiIiIiEj2GIiIiIhI9hiIiIiISPYYiIiIiEj2GIiIiIhI9hiIiIiISPYYiIiIiEj2GIiIiIhI9hiIiIiISPYYiIiIiEj2GIiIiIhI9hiIiIiISPYYiIiIiEj2GIiIiIhI9hiIiIiISPYYiIiIiEj2GIiIiIhI9hiIiIiISPYYiIiIiEj2GIiIiIhI9hiIiIiISPYYiIiIiEj2GIiIiIhI9hiIiIiISPYYiIiIiEj2GIiIiIhI9hiIiIiISPYYiIiIiEj2GIiIiIhI9hiIiIiISPYYiIiIiEj2anUgmjlzJhQKhcarRYsW0vK7d+8iMDAQFhYWMDExQb9+/ZCRkaHRx5UrV+Dn5wcjIyNYWVlhypQpKCoqetq7QkRERLWYnrYLqEjLli2xd+9eaVpP738lT5o0CTt37sSWLVugVqsxfvx4vP766zh8+DAAoLi4GH5+frCxscGRI0eQlpaGIUOGoF69evj888+f+r4QERFR7VTrA5Genh5sbGzKzM/OzsZ3332HDRs2oFu3bgCA8PBwuLi44OjRo+jcuTP27NmDs2fPYu/evbC2tka7du0wZ84cBAcHY+bMmdDX13/au0NERES1UK2+ZAYAqampsLOzQ5MmTTBo0CBcuXIFAJCQkIDCwkL4+PhIbVu0aIFGjRohPj4eABAfH4/WrVvD2tpaauPr64ucnBycOXPmodvMz89HTk6OxouIiIjqrlodiNzd3REREYHdu3djxYoVuHjxIrp06YJbt24hPT0d+vr6MDMz01jH2toa6enpAID09HSNMFS6vHTZw4SGhkKtVksve3v7mt0xIiIiqlVq9SWzXr16Sf9u06YN3N3d4eDggB9++AGGhoZPbLshISEICgqSpnNychiKiIiI6rBafYboQWZmZnB2dsb58+dhY2ODgoICZGVlabTJyMiQxhzZ2NiUueusdLq8cUmllEolVCqVxouIiIjqrmcqEOXm5uLChQuwtbWFm5sb6tWrh5iYGGl5SkoKrly5Ag8PDwCAh4cHkpKSkJmZKbWJjo6GSqWCq6vrU6+fiIiIaqdafcnsgw8+wCuvvAIHBwdcu3YNM2bMgK6uLgYMGAC1Wo0RI0YgKCgI5ubmUKlUmDBhAjw8PNC5c2cAQI8ePeDq6orBgwdj3rx5SE9Px7Rp0xAYGAilUqnlvSMiIqLaolYHor///hsDBgzAf//9B0tLS7z00ks4evQoLC0tAQCLFi2Cjo4O+vXrh/z8fPj6+mL58uXS+rq6uoiMjMTYsWPh4eEBY2NjBAQEYPbs2draJSIiIqqFanUg2rRp0yOXGxgYICwsDGFhYQ9t4+DggF9//bWmSyMiIqI65JkaQ0RERET0JDAQERERkewxEBEREZHsMRARERGR7DEQERERkewxEBEREZHsMRARERGR7DEQERERkewxEBEREZHsMRARERGR7DEQERERkewxEBEREZHsMRARERGR7NXqb7snIiL5cZuyVtslUC2SMH/IU9kOzxARERGR7DEQERERkewxEBEREZHsMRARERGR7DEQERERkewxEBEREZHsMRARERGR7DEQERERkewxEBEREZHsMRARERGR7DEQERERkewxEBEREZHsMRARERGR7DEQERERkewxEBEREZHsMRARERGR7DEQERERkewxEBEREZHsMRARERGR7DEQERERkewxEBEREZHsMRARERGR7DEQERERkewxEBEREZHsMRARERGR7DEQERERkezJKhCFhYXB0dERBgYGcHd3x/Hjx7VdEhEREdUCsglEmzdvRlBQEGbMmIHff/8dbdu2ha+vLzIzM7VdGhEREWmZbALRwoULMWrUKAwbNgyurq5YuXIljIyMsHr1am2XRkRERFomi0BUUFCAhIQE+Pj4SPN0dHTg4+OD+Ph4LVZGREREtYGetgt4Gv79918UFxfD2tpaY761tTXOnTtXpn1+fj7y8/Ol6ezsbABATk7OY9VRnH/nsdanuuVxj6eawGOSHsTjkmqbxzkmS9cVQlTYVhaBqKpCQ0Mxa9asMvPt7e21UA3VVeplY7RdAlEZPC6ptqmJY/LWrVtQq9WPbCOLQNSgQQPo6uoiIyNDY35GRgZsbGzKtA8JCUFQUJA0XVJSghs3bsDCwgIKheKJ11uX5eTkwN7eHlevXoVKpdJ2OUQ8JqlW4nFZM4QQuHXrFuzs7CpsK4tApK+vDzc3N8TExKBv374A7oWcmJgYjB8/vkx7pVIJpVKpMc/MzOwpVCofKpWK/8mpVuExSbURj8vHV9GZoVKyCEQAEBQUhICAAHTs2BHPP/88Fi9ejLy8PAwbNkzbpREREZGWySYQvf3227h+/TqmT5+O9PR0tGvXDrt37y4z0JqIiIjkRzaBCADGjx9f7iUyenqUSiVmzJhR5pIkkbbwmKTaiMfl06cQlbkXjYiIiKgOk8WDGYmIiIgehYGIiIiIZI+BiIiIiGSPgYhqlEKhwPbt2wEAly5dgkKhQGJiolZrqoyZM2eiXbt22i5D1ry9vTFx4sRasZ2IiIhqPXts6NCh0rPOapPq7g+V78GfbbGxsVAoFMjKynqsfh0dHbF48eLHrq+m+nmU+3/W1xUMRHVceno6JkyYgCZNmkCpVMLe3h6vvPIKYmJinvi27e3tkZaWhlatWgGo2g8NIQRWrVoFd3d3mJiYwMzMDB07dsTixYtx+/btJ1w5lRo6dCgUCoX0srCwQM+ePXHq1CltlwZbW1vMnTtXY96HH34IhUKB2NhYjfne3t4YPHgwAGDr1q2YM2eOtOxp/PIg7So9jseMKfsVEIGBgVAoFBg6dGil+3vwZ9vTlJOTg48//hgtWrSAgYEBbGxs4OPjg61bt1bq+7ro4RiI6rBLly7Bzc0N+/btw/z585GUlITdu3eja9euCAwMfOh6hYWFNbJ9XV1d2NjYQE+v6k93GDx4MCZOnAh/f3/s378fiYmJ+OSTT7Bjxw7s2bOn2jXV1L7JSc+ePZGWloa0tDTExMRAT08Pffr00XZZ8Pb2LhN89u/fD3t7e435d+/exdGjR9GtWzcAgLm5OUxNTZ9ipf9TUFCgle3SvRCzadMm3Lnzvy+OvXv3LjZs2IBGjRpVqa/H+dn2OLKysvDCCy9g7dq1CAkJwe+//44DBw7g7bffxtSpU6UvIqfqYSCqw8aNGweFQoHjx4+jX79+cHZ2RsuWLREUFISjR49K7RQKBVasWIFXX30VxsbG+OyzzwAAO3bsQIcOHWBgYIAmTZpg1qxZKCoqktZLTU2Fp6cnDAwM4OrqiujoaI3t339a+dKlS+jatSsAoH79+o/8i+yHH37A+vXrsXHjRnz00Ufo1KkTHB0d4e/vj3379kn9nDhxAi+//DIaNGgAtVoNLy8v/P777xp9PWzf5s6dC2tra5iammLEiBG4e/fu473ZdZhSqYSNjQ1sbGzQrl07fPjhh7h69SquX78utQkODoazszOMjIzQpEkTfPLJJxrhs/SS5Lp16+Do6Ai1Wo3+/fvj1q1bD93uzp07oVarsX79+nKXd+3aFYcPH5aOyVu3buGPP/5AcHCwRiCKj49Hfn6+dNzcf8nM29sbly9fxqRJk6SzYPeLioqCi4sLTExMpGBYqri4GEFBQTAzM4OFhQWmTp1a5i90b29vjB8/HhMnTkSDBg3g6+sLAFi4cCFat24NY2Nj2NvbY9y4ccjNzQVw7+yopaUlfvzxR6mfdu3awdbWVpo+dOgQlEqldLb0Uf3RPR06dIC9vT22bt0qzdu6dSsaNWqE9u3ba7TdvXs3XnrpJemz7dOnDy5cuCAtr8xwgEOHDqFLly4wNDSEvb093nvvPeTl5UnLMzMz8corr8DQ0BCNGzd+6HF+v48++giXLl3CsWPHEBAQAFdXVzg7O2PUqFFITEyEiYmJ1Pb27dsYPnw4TE1N0ahRI6xatUqjr6tXr+Ktt96CmZkZzM3N4e/vj0uXLmm0Wb16NVq2bAmlUglbW9tHPsdvxowZsLW1rRVnj6uLgaiOunHjBnbv3o3AwEAYGxuXWf7geIKZM2fitddeQ1JSEoYPH46DBw9iyJAheP/993H27Fl8/fXXiIiIkAJFSUkJXn/9dejr6+PYsWNYuXIlgoODH1qPvb09fvrpJwBASkoK0tLSsGTJknLbrl+/Hs2bN4e/v3+ZZQqFQvpemlu3biEgIACHDh3C0aNH0axZM/Tu3bvML9kH9+2HH37AzJkz8fnnn+O3336Dra0tli9f/vA3kyS5ubn4/vvv4eTkBAsLC2m+qakpIiIicPbsWSxZsgTffPMNFi1apLHuhQsXsH37dkRGRiIyMhJxcXFlLnmV2rBhAwYMGID169dj0KBB5bbp2rUrcnNzceLECQDAwYMH4ezsjH79+uHYsWNSyN2/fz8cHR3h6OhYpo+tW7eiYcOGmD17tnQWrNTt27fx5ZdfYt26dThw4ACuXLmCDz74QFq+YMECREREYPXq1Th06BBu3LiBbdu2ldnGmjVroK+vj8OHD2PlypUAAB0dHSxduhRnzpzBmjVrsG/fPkydOhXAvWPc09NTCnU3b95EcnIy7ty5g3PnzgEA4uLi0KlTJxgZGVXYH/3P8OHDER4eLk2vXr263K9vysvLQ1BQEH777TfExMRAR0cHr732GkpKSiq1nQsXLqBnz57o168fTp06hc2bN+PQoUMagWLo0KG4evUq9u/fjx9//BHLly9HZmbmQ/ssKSnBpk2bMGjQoHK/qNTExETjjNWCBQvQsWNH/PHHHxg3bhzGjh2LlJQUAPfOlPv6+sLU1BQHDx7E4cOHpdBfehZzxYoVCAwMxOjRo5GUlISff/4ZTk5OZbYrhMCECROwdu1aHDx4EG3atKnUe1QrCaqTjh07JgCIrVu3VtgWgJg4caLGvO7du4vPP/9cY966deuEra2tEEKIqKgooaenJ/755x9p+a5duwQAsW3bNiGEEBcvXhQAxB9//CGEEGL//v0CgLh58+Yj63FxcRGvvvpqhXU/qLi4WJiamopffvnlkfvm4eEhxo0bpzHP3d1dtG3btsrbrOsCAgKErq6uMDY2FsbGxgKAsLW1FQkJCY9cb/78+cLNzU2anjFjhjAyMhI5OTnSvClTpgh3d3dp2svLS7z//vviq6++Emq1WsTGxlZY33PPPScdp1OmTJE+V2dnZ7Fv3z4hhBBdunQRw4YNK7OdUg4ODmLRokUa/YaHhwsA4vz589K8sLAwYW1tLU3b2tqKefPmSdOFhYWiYcOGwt/fX2Nb7du3r3A/tmzZIiwsLKTppUuXipYtWwohhNi+fbtwd3cX/v7+YsWKFUIIIXx8fMRHH31U6f7Cw8OFWq2usI66KiAgQPj7+4vMzEyhVCrFpUuXxKVLl4SBgYG4fv268Pf3FwEBAQ9d//r16wKASEpKEkJU/LNtxIgRYvTo0Rp9HDx4UOjo6Ig7d+6IlJQUAUAcP35cWp6cnCwAlDkWS2VkZAgAYuHChRXur4ODg3jnnXek6ZKSEmFlZSUdP+vWrRPNmzcXJSUlUpv8/HxhaGgooqKihBBC2NnZiY8//vih2wAgtmzZIgYOHChcXFzE33//XWFdtR3PENVRooqD6zp27KgxffLkScyePRsmJibSa9SoUUhLS8Pt27eRnJwMe3t7jb9UPDw8nmrtGRkZGDVqFJo1awa1Wg2VSoXc3FxcuXJFo92D+5acnAx3d3eNeTVVe13UtWtXJCYmIjExEcePH4evry969eqFy5cvS202b96MF198ETY2NjAxMcG0adPKfA6Ojo4aY3dsbW3L/EX8448/YtKkSYiOjoaXl1eFtd0/jig2Nhbe3t4AAC8vL8TGxuLOnTs4duyYdLmsKoyMjNC0adNy683OzkZaWprGcaSnp1fmWAMANze3MvP27t2L7t2747nnnoOpqSkGDx6M//77T7oE5uXlhbNnz+L69euIi4uDt7e3tK+FhYU4cuSItK+V6Y/usbS0hJ+fHyIiIhAeHg4/Pz80aNCgTLvU1FQMGDAATZo0gUqlks4uPnhMP8zJkycRERGh8fPT19cXJSUluHjxIpKTk6Gnp6dxbLRo0eKRdwJW9Wf6/WdqFAoFbGxspOP35MmTOH/+PExNTaX6zM3NcffuXVy4cAGZmZm4du0aunfv/shtTJo0CceOHcOBAwfw3HPPVam+2oiBqI5q1qwZFAqFdIq9Ig9eVsvNzcWsWbOkX4SJiYlISkpCamoqDAwMnkTJEmdn50rVHRAQgMTERCxZsgRHjhxBYmIiLCwsygxcLe+SIVWesbExnJyc4OTkhE6dOuHbb79FXl4evvnmGwD3xugMGjQIvXv3RmRkJP744w98/PHHZT6HevXqaUwrFIoylyDat28PS0tLrF69ulK/AErHEf3333/4448/pBDl5eWF/fv348iRIygoKJAGVFdFefVW9ZcSUPb4u3TpEvr06YM2bdrgp59+QkJCAsLCwgD8b9B169atYW5ujri4OI1AFBcXhxMnTqCwsBAvvPBCpfuj/xk+fDgiIiKwZs0aDB8+vNw2r7zyCm7cuIFvvvkGx44dw7FjxwBU/v3Mzc3Fu+++q/Hz8+TJk0hNTdUI2VVhaWkJMzOzSv9Mf9T/t9zcXLi5uWnUl5iYiD///BMDBw6EoaFhpbbx8ssv459//kFUVFTVdqaWYiCqo8zNzeHr64uwsDCNgXylKrr1vUOHDkhJSZF+Ed7/0tHRgYuLC65evaox5uL+gdrl0dfXB3BvMOqjDBw4EH/++Sd27NhRZpkQQrqT4vDhw3jvvffQu3dvaeDfv//++8i+AcDFxUX6AVfZ2ul/FAoFdHR0pLt1jhw5AgcHB3z88cfo2LEjmjVrpnH2qCqaNm2K/fv3Y8eOHZgwYUKF7bt27Yq8vDwsXLgQzZo1g5WVFQDA09MTx48fx65du9CsWbNH/vWqr69f4TH5ILVaDVtbW43jqKioCAkJCRWum5CQgJKSEixYsACdO3eGs7Mzrl27ptFGoVCgS5cu2LFjB86cOYOXXnoJbdq0QX5+Pr7++mt07NhRClqV6Y/+p3ScTOk4mgf9999/SElJwbRp09C9e3e4uLjg5s2bVdpGhw4dcPbs2XJ/furr66NFixZljpeUlJRH/lzW0dFB//79sX79+nI/39zcXI2bXiqqLzU1FVZWVmXqU6vVMDU1haOjY4WPZ3n11VexYcMGjBw5Eps2barUtmszBqI6LCwsDMXFxXj++efx008/ITU1FcnJyVi6dGmFl4imT5+OtWvXYtasWThz5gySk5OxadMmTJs2DQDg4+MDZ2dnBAQE4OTJkzh48CA+/vjjR/bp4OAAhUKByMhIXL9+/aF3wbz11lt4++23MWDAAGng8+XLlxEZGQkfHx/s378fwL2zYOvWrUNycjKOHTuGQYMGVeovm/fffx+rV69GeHg4/vzzT8yYMQNnzpypcD25ys/PR3p6OtLT05GcnIwJEyYgNzcXr7zyCoB7n8OVK1ewadMmXLhwAUuXLi13cHFlOTs7Y//+/fjpp58qfIBikyZN0KhRIyxbtkzjElvp5dxVq1ZVeLnM0dERBw4cwD///FOpQF3q/fffx9y5c7F9+3acO3cO48aNq9QztpycnFBYWIhly5bhr7/+wrp166TB1vfz9vbGxo0b0a5dO5iYmEBHRweenp5Yv369xr5Wtj+6R1dXF8nJyTh79ix0dXXLLK9fvz4sLCywatUqnD9/Hvv27UNQUFCVthEcHIwjR45g/PjxSExMRGpqKnbs2CENqm7evDl69uyJd999F8eOHUNCQgJGjhxZ4c+vzz77DPb29nB3d8fatWtx9uxZpKamYvXq1Wjfvn2l7ywcNGgQGjRoAH9/fxw8eBAXL15EbGws3nvvPfz9998A7t2MsmDBAixduhSpqan4/fffsWzZsjJ9vfbaa1i3bh2GDRumcWfks4iBqA5r0qQJfv/9d3Tt2hWTJ09Gq1at8PLLLyMmJgYrVqx45Lq+vr6IjIzEnj170KlTJ3Tu3BmLFi2Cg4MDgHt/rWzbtg137tzB888/j5EjR0p3oD3Mc889h1mzZuHDDz+EtbX1Q2/hVCgU2LBhAxYuXIjt27fDy8sLbdq0wcyZM+Hv7y/9Vffdd9/h5s2b6NChAwYPHoz33ntPOkPwKG+//TY++eQTTJ06FW5ubrh8+TLGjh1b4XpytXv3btja2sLW1hbu7u44ceIEtmzZIo1hefXVVzFp0iSMHz8e7dq1w5EjR/DJJ5881jabN2+Offv2YePGjZg8efIj23bt2hW3bt3SGFMD3LtsduvWrQoD0ezZs3Hp0iU0bdoUlpaWla5x8uTJGDx4MAICAuDh4QFTU1O89tprFa7Xtm1bLFy4EF988QVatWqF9evXIzQ0tEw7Ly8vFBcXa+yXt7d3mXmV7Y/+R6VSQaVSlbtMR0cHmzZtQkJCAlq1aoVJkyZh/vz5Veq/TZs2iIuLw59//okuXbqgffv2mD59usaYy/DwcNjZ2cHLywuvv/46Ro8eXeHPL3Nzcxw9ehTvvPMOPv30U7Rv3x5dunTBxo0bMX/+fOkO3IoYGRnhwIEDaNSoEV5//XW4uLhIjx8pfV8CAgKwePFiLF++HC1btkSfPn2Qmppabn9vvPEG1qxZg8GDB2s81uBZoxDVuShOREREVIfwDBERERHJHgMRERERyR4DEREREckeAxERERHJHgMRERERyR4DEREREckeAxERERHJHgMREVEt4ujoiMWLF9d4v0OHDkXfvn1rvF+iuoKBiIgeaujQoVAoFFAoFNDX14eTkxNmz55d6e9Mqq0iIiIe+c3i5fH29oZCocDcuXPLLPPz84NCocDMmTOfaA1E9OQwEBHRI/Xs2RNpaWlITU3F5MmTMXPmzCp/lUFdYW9vj4iICI15//zzD2JiYmBra6udooioRjAQEdEjKZVK2NjYwMHBAWPHjoWPjw9+/vlnLFy4EK1bt4axsTHs7e0xbtw46csl8/LyoFKpynzZ4/bt22FsbIxbt27h0qVLUCgU+OGHH9ClSxcYGhqiU6dO+PPPP3HixAl07NgRJiYm6NWrF65fv67Rz7fffgsXFxcYGBigRYsWWL58ubSstN+tW7eia9euMDIyQtu2bREfHw8AiI2NxbBhw5CdnS2d/arsmZ0+ffrg33//xeHDh6V5a9asQY8ePcp8D1V+fj4++OADPPfcczA2Noa7uztiY2MrVcPt27cxfPhwmJqaolGjRli1apVG30lJSejWrRsMDQ1hYWGB0aNHa3yxZ3FxMYKCgmBmZgYLCwtMnToV/JYmokdjICKiKjE0NERBQQF0dHSwdOlSnDlzBmvWrMG+ffswdepUAICxsTH69++P8PBwjXXDw8PxxhtvwNTUVJo3Y8YMTJs2Db///jv09PQwcOBATJ06FUuWLMHBgwdx/vx5TJ8+XWq/fv16TJ8+HZ999hmSk5Px+eef45NPPsGaNWs0tvXxxx/jgw8+QGJiIpydnTFgwAAUFRXhhRdewOLFi6FSqZCWloa0tDR88MEHldp3fX19DBo0SGO/IiIiMHz48DJtx48fj/j4eGzatAmnTp3Cm2++iZ49eyI1NbXCGhYsWICOHTvijz/+wLhx4zB27FikpKQAuBc2fX19Ub9+femLdvfu3avxZckLFixAREQEVq9ejUOHDuHGjRvYtm1bpfaRSLYEEdFDBAQECH9/fyGEECUlJSI6OloolUrxwQcflGm7ZcsWYWFhIU0fO3ZM6OrqimvXrgkhhMjIyBB6enoiNjZWCCHExYsXBQDx7bffSuts3LhRABAxMTHSvNDQUNG8eXNpumnTpmLDhg0a254zZ47w8PB4aL9nzpwRAERycrIQQojw8HChVqur9F54eXmJ999/XyQmJgpTU1ORm5sr4uLihJWVlSgsLBRt27YVM2bMEEIIcfnyZaGrqyv++ecfjT66d+8uQkJCHlmDg4ODeOedd6TpkpISYWVlJVasWCGEEGLVqlWifv36Ijc3V2qzc+dOoaOjI9LT04UQQtja2op58+ZJywsLC0XDhg2lz5KIytLTbhwjotouMjISJiYmKCwsRElJCQYOHIiZM2di7969CA0Nxblz55CTk4OioiLcvXsXt2/fhpGREZ5//nm0bNkSa9aswYcffojvv/8eDg4O8PT01Oi/TZs20r+tra0BAK1bt9aYl5mZCeDe2ZELFy5gxIgRGDVqlNSmqKgIarX6of2Wju/JzMxEixYtHuv9aNu2LZo1a4Yff/wR+/fvx+DBg6Gnp/mjNCkpCcXFxXB2dtaYn5+fDwsLiwq3cX/tCoUCNjY20nuQnJyMtm3bwtjYWGrz4osvoqSkBCkpKTAwMEBaWhrc3d2l5Xp6eujYsSMvmxE9AgMRET1S165dsWLFCujr68POzg56enq4dOkS+vTpg7Fjx+Kzzz6Dubk5Dh06hBEjRqCgoABGRkYAgJEjRyIsLAwffvghwsPDMWzYMCgUCo3+69WrJ/27dNmD80pKSgBAGifzzTffaPzCBwBdXd0K+y3t53ENHz4cYWFhOHv2LI4fP15meW5uLnR1dZGQkFCmLhMTkwr7v792QPM9IKIng2OIiOiRjI2N4eTkhEaNGklnQhISElBSUoIFCxagc+fOcHZ2xrVr18qs+8477+Dy5ctYunQpzp49i4CAgMeqxdraGnZ2dvjrr7/g5OSk8WrcuHGl+9HX10dxcXG16xg4cCCSkpLQqlUruLq6llnevn17FBcXIzMzs0ydNjY2j1WDi4sLTp48iby8PGne4cOHoaOjg+bNm0OtVsPW1hbHjh2TlhcVFSEhIaEae0okHwxERFRlTk5OKCwsxLJly/DXX39h3bp1WLlyZZl29evXx+uvv44pU6agR48eaNiw4WNve9asWQgNDcXSpUvx559/IikpCeHh4Vi4cGGl+3B0dERubi5iYmLw77//4vbt21WqoX79+khLS0NMTEy5y52dnTFo0CAMGTIEW7duxcWLF3H8+HGEhoZi586dj1XDoEGDYGBggICAAJw+fRr79+/HhAkTMHjwYOmS4/vvv4+5c+di+/btOHfuHMaNG4esrKwq7SOR3DAQEVGVtW3bFgsXLsQXX3yBVq1aYf369QgNDS23belltPLuxKqOkSNH4ttvv0V4eDhat24NLy8vREREVOkM0QsvvIAxY8bg7bffhqWlJebNm1flOszMzDTG8TwoPDwcQ4YMweTJk9G8eXP07dsXJ06cQKNGjR6rBiMjI0RFReHGjRvo1KkT3njjDXTv3h1fffWV1Gby5MkYPHgwAgIC4OHhAVNTU7z22mtV3kciOVEIjrIjoido3bp1mDRpEq5duwZ9fX1tl0NEVC4OqiaiJ+L27dtIS0vD3Llz8e677zIMEVGtxktmRPREzJs3Dy1atICNjQ1CQkK0Xc4jHTx4ECYmJg99EVHdx0tmRCR7d+7cwT///PPQ5U5OTk+xGiLSBgYiIiIikj1eMiMiIiLZYyAiIiIi2WMgIiIiItljICIiIiLZYyAiIiIi2WMgIiIiItljICIiIiLZYyAiIiIi2fs/MBLn9YLAWNAAAAAASUVORK5CYII=",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.countplot(data=data, x='Payment_Method')\n",
    "plt.title('Countplot for Method of Payment');"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 366,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.countplot(data=data,x='Value_Deal')\n",
    "plt.title('Countplot for Value Deal');"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 367,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 500x500 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.displot(data= data, x='Tenure_in_Months' , kde= True)\n",
    "plt.title('Distribution of Tenure (in Months)');"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 368,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 500x500 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.displot(data= data, x='Monthly_Charge' ,bins =10, kde= True)\n",
    "plt.title('Distribution of Monthly Charges');"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 369,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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++ij0ej1SU1Oxbt067N+/H3v27KnVOnv27Ak3NzeMGjUKkydPhkwmw1dffVWrSxNDhw5F9+7d8eKLLyIhIQFt2rTBhg0bzP+Avf4MxLJly9C7d2906NAB48ePR8uWLZGWloa9e/fiypUrOHr0KAAgPDwc/fr1Q9euXeHu7o6DBw/ihx9+QGxsbK32j6zIZvebU7NXOYylclIqlUKv14t7771XfPDBBxbDgCrdODxr27Zt4qGHHhK+vr5CqVQKX19f8cQTT4izZ89afG/9+vUiPDxcKBQKi2Erffv2Fe3atau2vpsNz1q9erWYPn260Ol0Qq1WiyFDhohLly5V+f77778v/Pz8hEqlEr169RIHDx6sdmjQzWq7cXiWEELk5uaKF154Qfj6+gp7e3sRFhYmFixYYDEMSIiK4VmTJk2qUtPNho3dKC0tTYwZM0Z4enoKpVIpOnToUO0QMmsNzxJCiK1bt4pevXoJtVotNBqNeOCBB8SpU6eqfP+NN94Qfn5+Qi6XWwzV2rBhg+jYsaNwcHAQQUFB4t133xVffPFFleFctR2edb0ffvhB3HfffcLd3V0oFArh4+MjHn/8cbFz505zm5sNO6z8+dmxY4d53u7du8Vdd90l1Gq18PX1FS+99JL47bffqrS71c/ptWvXxJNPPilcXFyEVqsVo0ePFrt37xYAxJo1ayzanj9/Xjz99NNCr9cLe3t74efnJ+6//37xww8/mNu8+eabonv37sLV1VWo1WrRpk0b8dZbb4mSkpI6HTO6czIhmuCdJUREzdi6devw8MMP488//0SvXr1sXQ7dIQY1EVEjVlhYaHFHeHl5Oe677z4cPHgQqamp9TKqgRoWr1ETUbN17dq1Ks/Vvp5SqbR4CIsUPffccygsLERUVBSKi4uxdu1a7NmzB2+//TZDuolgj5qImq2goKBbPsClb9++2LlzZ8MVVAfffPMN3n//fSQkJKCoqAihoaGYOHEib/5qQhjURNRs7d69G4WFhTdd7ubmZr7TnMhWGNREREQSxgeeEBERSRiDugaEEDAajU3yGclERCRtDOoayM3NhVarrfXbc4iIiO4Ug5qIiEjCGNREREQSxqAmIiKSMAY1ERGRhDGoiYiIJIxBTUREJGEMaiIiIgljUBMREUkYg5qIiEjCGNREREQSxqAmIiKSMAY1ERGRhDGoiYiIJMymQb1r1y488MAD8PX1hUwmw7p16yyWCyEwc+ZM+Pj4QK1WIzo6GufOnbNok5WVhREjRkCj0cDV1RVjx45FXl6eRZtjx47h7rvvhoODAwICAjB//vz63jUiIiKrsGlQ5+fno1OnTli2bFm1y+fPn48lS5Zg+fLl2LdvH5ycnBATE4OioiJzmxEjRuDkyZPYsmULfvnlF+zatQsTJkwwLzcajbjvvvsQGBiIuLg4LFiwALNnz8Ynn3xS7/tHRER0x4REABA//fST+bPJZBJ6vV4sWLDAPM9gMAiVSiVWr14thBDi1KlTAoA4cOCAuc2vv/4qZDKZSE5OFkII8eGHHwo3NzdRXFxsbvPyyy+L1q1b17i2nJwcAUDk5OTUdfeIiIjqRLLXqBMTE5Gamoro6GjzPK1Wix49emDv3r0AgL1798LV1RWRkZHmNtHR0ZDL5di3b5+5TZ8+faBUKs1tYmJiEB8fj+zs7Gq3XVxcDKPRaDERERHZgmSDOjU1FQDg7e1tMd/b29u8LDU1FTqdzmK5QqGAu7u7RZvq1nH9Nm40b948aLVa8xQQEHDnO0RERFQHClsXIEXTp0/H1KlTzZ+NRqNVwzo9PR0Gg6HG7V1dXav8g4SIiJoHyQa1Xq8HAKSlpcHHx8c8Py0tDREREeY26enpFt8rKytDVlaW+ft6vR5paWkWbSo/V7a5kUqlgkqlssp+3Cg9PR2hoWHIza356XQXFw0SEs4xrImImiHJBnVwcDD0ej22bdtmDmaj0Yh9+/Zh4sSJAICoqCgYDAbExcWha9euAIDt27fDZDKhR48e5javvfYaSktLYW9vDwDYsmULWrduDTc3twbfL4PBgNxcIya8/Rnc9f63bZ+VegWfvDoOBoOBQU1E1AzZNKjz8vKQkJBg/pyYmIgjR47A3d0dLVq0wJQpU/Dmm28iLCwMwcHBmDFjBnx9fTF06FAAQNu2bTFw4ECMHz8ey5cvR2lpKWJjYzF8+HD4+voCAJ588knMmTMHY8eOxcsvv4wTJ07ggw8+wKJFi2yxy2buen/o/INtWgMREUmfTYP64MGDuOeee8yfK68Ljxo1CitXrsRLL72E/Px8TJgwAQaDAb1798amTZvg4OBg/s7XX3+N2NhYDBgwAHK5HMOGDcOSJUvMy7VaLTZv3oxJkyaha9eu8PT0xMyZMy3GWhMREUmVTAghbF2E1BmNRmi1WuTk5ECj0dzRus6ePYvWrVvjlS821ahHnX4lEe/8cyDi4+PRqlWrO9o2ERE1PpIdnkVEREQMaiIiIkljUBMREUkYg5qIiEjCGNREREQSxqAmIiKSMAY1ERGRhDGoiYiIJIxBTUREJGEMaiIiIgljUBMREUkYg5qIiEjCGNREREQSxqAmIiKSMAY1ERGRhDGoiYiIJIxBTUREJGEMaiIiIgljUBMREUkYg5qIiEjCGNREREQSxqAmIiKSMAY1ERGRhDGoiYiIJIxBTUREJGEMaiIiIgljUBMREUkYg5qIiEjCGNREREQSxqAmIiKSMAY1ERGRhDGoiYiIJIxBTUREJGEMaiIiIgljUBMREUkYg5qIiEjCGNREREQSxqAmIiKSMAY1ERGRhDGoiYiIJIxBTUREJGEMaiIiIgljUBMREUkYg5qIiEjCGNREREQSxqAmIiKSMAY1ERGRhDGoiYiIJIxBTUREJGEMaiIiIgljUBMREUkYg5qIiEjCGNREREQSxqAmIiKSMAY1ERGRhDGoiYiIJIxBTUREJGEMaiIiIgljUBMREUkYg5qIiEjCGNREREQSxqAmIiKSMAY1ERGRhDGoiYiIJIxBTUREJGEMaiIiIgljUBMREUkYg5qIiEjCGNREREQSxqAmIiKSMAY1ERGRhEk6qMvLyzFjxgwEBwdDrVYjJCQEb7zxBoQQ5jZCCMycORM+Pj5Qq9WIjo7GuXPnLNaTlZWFESNGQKPRwNXVFWPHjkVeXl5D7w4REVGtSTqo3333XXz00Uf4z3/+g9OnT+Pdd9/F/PnzsXTpUnOb+fPnY8mSJVi+fDn27dsHJycnxMTEoKioyNxmxIgROHnyJLZs2YJffvkFu3btwoQJE2yxS0RERLWisHUBt7Jnzx489NBDGDJkCAAgKCgIq1evxv79+wFU9KYXL16M119/HQ899BAA4L///S+8vb2xbt06DB8+HKdPn8amTZtw4MABREZGAgCWLl2KwYMH47333oOvr69tdo6IiKgGJN2j7tmzJ7Zt24azZ88CAI4ePYo///wTgwYNAgAkJiYiNTUV0dHR5u9otVr06NEDe/fuBQDs3bsXrq6u5pAGgOjoaMjlcuzbt6/a7RYXF8NoNFpMREREtiDpHvUrr7wCo9GINm3awM7ODuXl5XjrrbcwYsQIAEBqaioAwNvb2+J73t7e5mWpqanQ6XQWyxUKBdzd3c1tbjRv3jzMmTPH2rtDRERUa5LuUX/33Xf4+uuv8c033+DQoUP48ssv8d577+HLL7+s1+1Onz4dOTk55uny5cv1uj0iIqKbkXSPetq0aXjllVcwfPhwAECHDh1w6dIlzJs3D6NGjYJerwcApKWlwcfHx/y9tLQ0REREAAD0ej3S09Mt1ltWVoasrCzz92+kUqmgUqnqYY+IiIhqR9I96oKCAsjlliXa2dnBZDIBAIKDg6HX67Ft2zbzcqPRiH379iEqKgoAEBUVBYPBgLi4OHOb7du3w2QyoUePHg2wF0RERHUn6R71Aw88gLfeegstWrRAu3btcPjwYSxcuBD//Oc/AQAymQxTpkzBm2++ibCwMAQHB2PGjBnw9fXF0KFDAQBt27bFwIEDMX78eCxfvhylpaWIjY3F8OHDecc3ERFJnqSDeunSpZgxYwaeffZZpKenw9fXF8888wxmzpxpbvPSSy8hPz8fEyZMgMFgQO/evbFp0yY4ODiY23z99deIjY3FgAEDIJfLMWzYMCxZssQWu0RERFQrMnH9Y76oWkajEVqtFjk5OdBoNHe0rrNnz6J169Z45YtN0PkH37Z9+pVEvPPPgYiPj0erVq3uaNtERNT4SPoaNRERUXPHoCYiIpIwBjUREZGEMaiJiIgkjEFNREQkYQxqIiIiCWNQExERSRiDmoiISMIY1ERERBLGoCYiIpIwBjUREZGEMaiJiIgkjEFNREQkYQxqIiIiCWNQExERSRiDmoiISMIY1ERERBLGoCYiIpIwBjUREZGEMaiJiIgkjEFNREQkYQxqIiIiCWNQExERSRiDmoiISMIY1ERERBLGoCYiIpIwBjUREZGEMaiJiIgkjEFNREQkYQxqIiIiCWNQExERSRiDmoiISMIY1ERERBLGoCYiIpIwBjUREZGEMaiJiIgkjEFNREQkYQxqIiIiCWNQExERSRiDmoiISMIY1ERERBLGoCYiIpIwBjUREZGEMaiJiIgkjEFNREQkYQxqIiIiCWNQExERSRiDmoiISMIY1ERERBLGoCYiIpIwBjUREZGEMaiJiIgkjEFNREQkYQxqIiIiCWNQExERSRiDmoiISMIY1ERERBLGoCYiIpIwBjUREZGEMaiJiIgkjEFNREQkYQxqIiIiCWNQExERSRiDmoiISMIY1ERERBLGoCYiIpIwBjUREZGEMaiJiIgkjEFNREQkYQxqIiIiCZN8UCcnJ+Opp56Ch4cH1Go1OnTogIMHD5qXCyEwc+ZM+Pj4QK1WIzo6GufOnbNYR1ZWFkaMGAGNRgNXV1eMHTsWeXl5Db0rdyQxMRFnz56t0ZSenm7rcomIyEoUti7gVrKzs9GrVy/cc889+PXXX+Hl5YVz587Bzc3N3Gb+/PlYsmQJvvzySwQHB2PGjBmIiYnBqVOn4ODgAAAYMWIEUlJSsGXLFpSWlmLMmDGYMGECvvnmG1vtWo3lGw0AZBg4cGCNv+PiokFCwjnodLp6q4uIiBqGpIP63XffRUBAAFasWGGeFxwcbP5vIQQWL16M119/HQ899BAA4L///S+8vb2xbt06DB8+HKdPn8amTZtw4MABREZGAgCWLl2KwYMH47333oOvr2/D7lQtFRfkARAY/spCBLUKv237rNQr+OTVcTAYDAxqIqImQNKnvjds2IDIyEj84x//gE6nQ+fOnfHpp5+alycmJiI1NRXR0dHmeVqtFj169MDevXsBAHv37oWrq6s5pAEgOjoacrkc+/bta7iduUOuOl/o/INvO7nr/W1dKhERWZGkg/rChQv46KOPEBYWht9++w0TJ07E5MmT8eWXXwIAUlNTAQDe3t4W3/P29jYvS01NrdKzVCgUcHd3N7e5UXFxMYxGo8VERERkC5I+9W0ymRAZGYm3334bANC5c2ecOHECy5cvx6hRo+ptu/PmzcOcOXPqbf1EREQ1JeketY+PD8LDLa/Ltm3bFklJSQAAvV4PAEhLS7Nok5aWZl6m1+ur3AVdVlaGrKwsc5sbTZ8+HTk5Oebp8uXLVtkfIiKi2pJ0UPfq1Qvx8fEW886ePYvAwEAAFTeW6fV6bNu2zbzcaDRi3759iIqKAgBERUXBYDAgLi7O3Gb79u0wmUzo0aNHtdtVqVTQaDQWExERkS1I+tT3Cy+8gJ49e+Ltt9/GY489hv379+OTTz7BJ598AgCQyWSYMmUK3nzzTYSFhZmHZ/n6+mLo0KEAKnrgAwcOxPjx47F8+XKUlpYiNjYWw4cPl/wd30RERJIO6m7duuGnn37C9OnTMXfuXAQHB2Px4sUYMWKEuc1LL72E/Px8TJgwAQaDAb1798amTZvMY6gB4Ouvv0ZsbCwGDBgAuVyOYcOGYcmSJbbYJSIiolqRdFADwP3334/777//pstlMhnmzp2LuXPn3rSNu7t7o3i4CRER0Y0kfY2aiIiouWNQExERSRiDmoiISMIY1ERERBLGoCYiIpIwBjUREZGEMaiJiIgkrE5B3bJlS2RmZlaZbzAY0LJlyzsuioiIiCrUKagvXryI8vLyKvOLi4uRnJx8x0URERFRhVo9mWzDhg3m//7tt9+g1WrNn8vLy7Ft2zYEBQVZrTgiIqLmrlZBXfmiC5lMVuV90Pb29ggKCsL7779vteKIiIiau1oFtclkAlDxeskDBw7A09OzXooiIiKiCnV6KUdiYqK16yAiIqJq1PntWdu2bcO2bduQnp5u7mlX+uKLL+64MCIiIqpjUM+ZMwdz585FZGQkfHx8IJPJrF0XERERoY5BvXz5cqxcuRIjR460dj1ERER0nToFdUlJCXr27GntWqgGhBC4kl2IS1kFyCkohbdWhWAPJ3g4q2xdGhER1YM6PfBk3Lhx+Oabb6xdC91GabkJ/zuegrWHkxF3KRsJ1/KwOyETq/Yl4Y9z11BuErYukYiIrKxOPeqioiJ88skn2Lp1Kzp27Ah7e3uL5QsXLrRKcfT/SkzAD3FXkJ5bDDu5DK10znBzUiLZUIhLmQU4lGTAVUMReukY1kRETUmdgvrYsWOIiIgAAJw4ccJiGW8sqx8njA5ILy6G2t4O93f0ga+rGgDQDUBCeh62nk5DqrEIf5bJAHmdb+YnIiKJqdNv9B07dli7DroFx7Z9kFasgFwGDI3whU7jYLE8VOcMjYMCPxy6grQCAY+BsRCCPWsioqaAr7mUuBKTDO73/gsA0C3IvUpIV9JpHDC4gw9kAJw7RGPnhbwGrJKIiOpLnXrU99xzzy1PcW/fvr3OBZGlSyVOsFM7w0VRjm5B7rdsG+ThhHYecpzINOE/e9MxtFcRvG8S7ERE1DjUqUcdERGBTp06mafw8HCUlJTg0KFD6NChg7VrbLZKykxIKnEEAIQ6lcBOfvvr/+08ZChOOYfcEhNeXXu8vkskIqJ6Vqce9aJFi6qdP3v2bOTl8ZSrtZy4moMyIUdpVjK8ddrbfwGAXCZD5v8WosWEj7DtTDp2nEnHPW109VwpERHVF6teo37qqaf4nG8rKTcJHE4yAACM+35EbW6mL828jKHhrgCAN345hZIy062/QEREkmXVoN67dy8cHHhN1BqSsgqQV1wGpawceSdrf81/RIQ7PJ2VuJCRjy/3XLR+gURE1CDqdOr7kUcesfgshEBKSgoOHjyIGTNmWKWw5i4+NRcAoLcvwrnyslp/30lph2kxrfHyj8exbGcCHu8eAI2D/e2/SEREklKnHrVWq7WY3N3d0a9fP2zcuBGzZs2ydo3NTkmZCeevVVzr97EvqvN6Hu0agBAvJxgKSvHZH3yHOBFRY1SnHvWKFSusXQdd58K1PJSZBLRqe2jtSuu8Hju5DFPvbY1J3xzC539cwOieQXB3UlqxUiIiqm93dI06Li4Oq1atwqpVq3D48GFr1dTsnUmrOO3dWu9Sq5vIqjOovR7tfDXILynHJ7suWKE6IiJqSHUK6vT0dPTv3x/dunXD5MmTMXnyZHTt2hUDBgzAtWvXrF1js1JcVo7LWQUAgDbeLne8PrlchinRrQAAq/66hJyCuvfQiYio4dUpqJ977jnk5ubi5MmTyMrKQlZWFk6cOAGj0YjJkydbu8ZmJSmrACYBuKrt4Wal09QD2ujQ2tsFecVl+O/ei1ZZJxERNYw6BfWmTZvw4Ycfom3btuZ54eHhWLZsGX799VerFdccXcqs6E0HeTpZbZ1yuQzP3hMCAFix5yIKSmp/FzkREdlGnYLaZDJVeQc1ANjb28Nk4sM16koIgYuZ+QCAIA9Hq657SAcftHB3RFZ+Cdbsv2zVdRMRUf2pU1D3798fzz//PK5evWqel5ycjBdeeAEDBgywWnHNTUZeCfKLy6GQy+D39/umrUVhJ8e/+lb0qj/ZdYFPKyMiaiTqFNT/+c9/YDQaERQUhJCQEISEhCA4OBhGoxFLly61do3NRmVvOsDdEQo767+BdFhXP+hcVEg1FuGnw1esvn4iIrK+Oo2jDggIwKFDh7B161acOXMGANC2bVtER0dbtbjmxnx92sqnvSupFHYYf3dLvLXxNJb/fgGPdg2o0Ru5iIjIdmrVbdu+fTvCw8NhNBohk8lw77334rnnnsNzzz2Hbt26oV27dvjjjz/qq9YmrazchNSciqeQBbjXT1ADwJM9WsDV0R6JGfnYdCK13rZDRETWUaugXrx4McaPHw+NRlNlmVarxTPPPIOFCxdarbjmJM1YjHIh4Ki0g6u6/p7J7aRS4Om7AgEAn+w6DyFEvW2LiIjuXK2C+ujRoxg4cOBNl993332Ii4u746KaoyuGitPefq5qyO70cWS38XTPIKgUchy9koN9iVn1ui0iIroztQrqtLS0aodlVVIoFHwyWR0lGwoBAH5u1r3buzqezio82tUfAPDx7+frfXtERFR3tQpqPz8/nDhx4qbLjx07Bh8fnzsuqrkpNwmkGCquT1t7WNbNjLu7JWQyYEf8NZz9+9niREQkPbUK6sGDB2PGjBkoKqr66sXCwkLMmjUL999/v9WKay6u5RajzCTgoJDDo4HebhXs6YSYcD0A8GUdREQSVqugfv3115GVlYVWrVph/vz5WL9+PdavX493330XrVu3RlZWFl577bX6qrXJqjzt7dsA16evN6FvSwDA+iPJ5jvOiYhIWmo1jtrb2xt79uzBxIkTMX36dPMdwzKZDDExMVi2bBm8vb3rpdCm7Grl9ekGOu1dqUsLN3QPcsf+i1lYsTsR0we3vf2XiIioQdX6gSeBgYHYuHEjsrOzkZCQACEEwsLC4ObmVh/1NXlCCKQaK3qzeq1Dg29/Qp+W2H8xC9/sS0Js/1C4ONTf0DAiIqq9Oj+n0s3NDd26dUP37t0Z0ncgr7gMBSXlkMkAnYuqwbffv40OIV5OyC0uw+r9SQ2+fSIiujXrP1CaaqXy2rCns6penu99O3K5DBP6VFyr/uLPi3xZBxGRxNTpWd9kPWnGYgCAt8a6venExMQat23nbIKHkz1SjUX4+ehVDPt7jDUREdkeg9rGzNenNda5Pp1vNACQ3fIJctXx6jMCjlFP4JNdF/BIF78GvfuciIhujkFtQyYhkJ5r3aAuLsgDIDD8lYUIahVeo+9kpV7Bp3OeR+u7n0R8Wi52nr2Ge1rrrFIPERHdGQa1DWXll6C0XMDeTgY3Kz/oxFXnC51/cI3bi+J8DGqtxdqTBnzy+wUGNRGRRPBmMhuqPO3trXGAXAKnmh9p5wqFXIa9FzJx7IrB1uUQEREY1DaVXnkjmUvDj5+ujs7ZHg908gUAfMzHihIRSQKD2oau5VYEtZcNxk/fzPi7K4Zq/Xo8BUmZBTauhoiIGNQ2YhICGXkVQW2LB53cTLivBneHecIkgM//ZK+aiMjWGNQ2klsClJkqbiRzdZTWYzv/1TcEAPDtwcvIyi+xcTVERM0bg9pGsosrXmji6ayS3JjlniEeaOerQVGpCV/uuWjrcoiImjUGtY1kF1UEtZezdE57V5LJZOZe9co9F5FXXGbjioiImi8GtY1kV1yeltSNZNcb3MEHLT2dkFNYilV/XbJ1OUREzRaD2kbMPWqJBrWdXIZn7wkFAHz2xwUUlpTbuCIiouaJQW0Ddi6eKDEBchng4WzdJ5JZ00MRvvB3UyMjrwRrDvAVmEREtsCgtgGld8VYZXcnJRRy6f4V2NvJzdeqP9l1AcVl7FUTETU06aZEE6b0qngGt6cEbyS70aNd/eGtUSElpwhrDyXbuhwiomaHL+WwAXuvQACNI6gd7O0woU8I3vjlFD7aeR7/6OoPhZ0c6enpMBgMNV6Pq6srdDq+6IOIqLYY1DZg7xUEQNrXp6/3RPcALNuRgKSsAvx87Cp6+SkRGhqG3Fxjjdfh4qJBQsI5hjURUS0xqBtYSbkJ9u5+AABPJ+n3qAHAUanA2N7BWPBbPP6zPQFt7/dBbq4RE97+DO56/9t+Pyv1Cj55dRwMBgODmoiolhjUDeyyoRQyuR2UcsBJZWfrciwkJibedFlPr3I4K+U4fy0fa/dXPAPcXe9fq3deExFR7TGoG1ji30860aogmUeH5hsNAGQYOHDgLdtpez8J115P4j/bzwEACgsK6784IqJmjkHdwBKzK15y4aqSRkgDQHFBHgCB4a8sRFCr8Ju3KxfYcL4c8A6BOrQ7ikuKG65IIqJmqlENz3rnnXcgk8kwZcoU87yioiJMmjQJHh4ecHZ2xrBhw5CWlmbxvaSkJAwZMgSOjo7Q6XSYNm0aysps8/zqxKyKcJNSUFdy1flC5x980ykgsCUiWrgBALS9noQQNi6YiKgZaDRBfeDAAXz88cfo2LGjxfwXXngBP//8M77//nv8/vvvuHr1Kh555BHz8vLycgwZMgQlJSXYs2cPvvzyS6xcuRIzZ85s6F0AAFz8u0etlWBQ10SXFm6wgwkqfSjSS6R1jZ2IqClqFEGdl5eHESNG4NNPP4Wbm5t5fk5ODj7//HMsXLgQ/fv3R9euXbFixQrs2bMHf/31FwBg8+bNOHXqFFatWoWIiAgMGjQIb7zxBpYtW4aSkoZ913JOQSkyCip68q6NY2RWFWqlHVqoCgAACXlKCHariYjqVaMI6kmTJmHIkCGIjo62mB8XF4fS0lKL+W3atEGLFi2wd+9eAMDevXvRoUMHeHt7m9vExMTAaDTi5MmT1W6vuLgYRqPRYrKGM6kV6ynLSYO9XePsUQNAkDIfppIiGMvskJiZb+tyiIiaNMkH9Zo1a3Do0CHMmzevyrLU1FQolUq4urpazPf29kZqaqq5zfUhXbm8cll15s2bB61Wa54CAgKssCdAsJcTXuitQ87e76yyPltRygVyD/0CANh3IYu9aiKieiTpoL58+TKef/55fP3113BwcGiw7U6fPh05OTnm6fLly1ZZr87FAYNaaZF39DerrM+WjPvXwg4C6bnFuJhZYOtyiIiaLEkHdVxcHNLT09GlSxcoFAooFAr8/vvvWLJkCRQKBby9vVFSUlLlmdNpaWnQ6/UAAL1eX+Uu8MrPlW1upFKpoNFoLCayZCo0ooVjKQBgX2Ime9VERPVE0kE9YMAAHD9+HEeOHDFPkZGRGDFihPm/7e3tsW3bNvN34uPjkZSUhKioKABAVFQUjh8/jvT0dHObLVu2QKPRIDz85mOG6faCnUqhkMuQZmSvmoiovkj6gScuLi5o3769xTwnJyd4eHiY548dOxZTp06Fu7s7NBoNnnvuOURFReGuu+4CANx3330IDw/HyJEjMX/+fKSmpuL111/HpEmToFI1jmdtS5VKLtDRX4tDSQbsS8xEkIejZJ62RkTUVEi6R10TixYtwv33349hw4ahT58+0Ov1WLt2rXm5nZ0dfvnlF9jZ2SEqKgpPPfUUnn76acydO9eGVTcdXVq4mXvVl9irJiKyOkn3qKuzc+dOi88ODg5YtmwZli1bdtPvBAYGYuPGjfVcWfPkpFJc16vOQiB71UREVtXoe9Rke5W96lRjES5lsVdNRGRNDGq6Y04qBTr4awFwXDURkbUxqMkqul7Xq05ir5qIyGoY1GQVTioFOvj93atOZK+aiMhaGNRkNV0D3WAnlyElh71qIiJrYVCT1bBXTURkfQxqsqpI9qqJiKyKQU1WxV41EZF1MajJ6q7vVV/OLrR1OUREjRqDmqzOSaVAB9/KcdV8sxYR0Z1gUFO96BpU0au+mlOEtAIGNRFRXTGoqV44qxRo71vxHu8TmSYbV0NE1HgxqKneRAa6w04uw7VCwKFFR1uXQ0TUKDGoqd44O/x/r1rb6wleqyYiqgMGNdWryEB3yGWAQ4sOOJrKO8CJiGqLQU31ytlBgRBtxfupvzqcZeNqiIgaHwY11btwdzlEWSmOpxZi7/lMW5dDRNSoMKip3jnay5B37DcAwOKtZ21cDRFR48KgpgaR89cPsJfLsC8xi71qIqJaYFBTgyjPzUBMq4o7wD/Yxl41EVFNMaipwQzv6AZ7Oxn+upCFvy6wV01EVBMMamowOmd7PBYZAAD4YOs5G1dDRNQ4MKipQT17Tyjs7WTYeyET+9irJiK6LQY1NSg/VzX+Udmr3sZeNRHR7TCoqcE92y8E9nYy7Dmfif2JfAgKEdGtMKipwfm7OeLRrpW9at4BTkR0KwxqsolJ94RAIZdhd0ImDlxkr5qI6GYY1GQT/m6O+EekPwDeAU5EdCsMarKZZ/uFQiGX4c+EDBxkr5qIqFoMarKZAHdHPNr171417wAnIqoWg5psatI9Fb3qP85lIO4Se9VERDdiUJNNBbg7YliXil71Yl6rJiKqgkFNNmfZq862dTlERJLCoCaba+HhiEe6+AHgtWoiohsxqEkSYu8Jg51chl1nr+FQEnvVRESVGNQkCS08HPFI57971bxWTURkxqAmyYjtHwo7uQy/n72Gw+xVExEBYFCThAR6OOHhzrxWTUR0PYWtC6DmIzEx8bZthgTbYe0hYGf8New4egH3dGrZAJUREUkXg5rqXb7RAECGgQMH1qi9x+Dn4dzhXox45xsc+WACdDpdvdZHRCRlDGqqd8UFeQAEhr+yEEGtwm/bPrdE4H+JZVAGdsa+c6l4gEFNRM0Yg5oajKvOFzr/4Nu20wEIykxAolFg1ZFMPNCr/msjIpIq3kxGktTOQw5hKse+ywU4dsVg63KIiGyGQU2S5KKUIf/kTgAcV01EzRuDmiQrZ++3kMuAbWfScfxKjq3LISKyCQY1SVZZ9lX0b+kCAPhg21kbV0NEZBsMapK0JyPcIZcBW0+n40Qye9VE1PwwqEnS/LVKPBRR8bSy9zfH27gaIqKGx6AmyZs8IAwKuQw74q9hz/kMW5dDRNSgGNQkecGeTniyRwsAwNsbT8NkEjauiIio4TCoqVF4fkAYnFUKnEg2YsPRq7Yuh4iowTCoqVHwcFZhYr8QAMCC3+JRVFpu44qIiBoGHyFKknb9G7fu9jZhhaMCyYZCvLfhIB7r4GbR1tXVlS/wIKImh0FNknSzN245tR8AzyEv4JM/LmLWU/fCVJRrXubiokFCwjmGNRE1KQxqkqSbvXHLJAQ2XSxHDpzRf9YaRHrbAQCyUq/gk1fHwWAwMKiJqElhUJOkVffGrQFOBVh7OBkJBoHIVj7QuTjYqDoiovrHm8mo0Qlwd0QrnTMEgJ3x1yAEh2sRUdPFoKZGqXeYJ+ztZEjJKcLplNzbf4GIqJFiUFOj5OJgj+7B7gCAPxMyUFLOXjURNU0Mamq0Oge4wc3RHoWl5TieYbJ1OURE9YJBTY2WnVyGfq0r7vA+ZxBQ6kNtXBERkfUxqKlRa+HuiNbeLhAAPAZPQUk5e9ZE1LQwqKnR69vKCyo7QOkVhG+OZNu6HCIiq2JQU6OnVtoh0rviR3nNsSycSM6xcUVERNbDoKYmoYWLHPln/oBJANN+OIaSMp4CJ6KmgUFNTUbWluXQOtjhdIoRy3Yk2LocIiKrYFBTk2EqyMGzd3kBAJZuP4f9iVk2roiI6M4xqKlJ6RfsjEe6+MEkgOdWH0JmXrGtSyIiuiMMampSZDIZ3nioPUK8nJBmLMbU747CZOJTy4io8WJQU5PjpFLgwxFd4WAvx+9nr2H5rvO2LomIqM4Y1NQktda7YM6D7QAA728+i78uZNq4IiKiupF0UM+bNw/dunWDi4sLdDodhg4divj4eIs2RUVFmDRpEjw8PODs7Ixhw4YhLS3Nok1SUhKGDBkCR0dH6HQ6TJs2DWVlZQ25K2QDj0UG4OHOfig3CfxrVRwSM/JtXRIRUa1JOqh///13TJo0CX/99Re2bNmC0tJS3HfffcjP//9fuC+88AJ+/vlnfP/99/j9999x9epVPPLII+bl5eXlGDJkCEpKSrBnzx58+eWXWLlyJWbOnGmLXaIGJJPJ8PbDHdApwBWGglKMWbEf2fklti6LiKhWJB3UmzZtwujRo9GuXTt06tQJK1euRFJSEuLi4gAAOTk5+Pzzz7Fw4UL0798fXbt2xYoVK7Bnzx789ddfAIDNmzfj1KlTWLVqFSIiIjBo0CC88cYbWLZsGUpK+Eu7qVMr7fDZ05Hwc1XjYmYBJnx1EEWl5bYui4ioxiQd1DfKyal4NKS7e8V7iOPi4lBaWoro6GhzmzZt2qBFixbYu3cvAGDv3r3o0KEDvL29zW1iYmJgNBpx8uTJardTXFwMo9FoMVHj5eWiwsox3eDioMCBi9l46YdjvBOciBqNRhPUJpMJU6ZMQa9evdC+fXsAQGpqKpRKJVxdXS3aent7IzU11dzm+pCuXF65rDrz5s2DVqs1TwEBAVbeG2poYd4u+GhEVyjkMmw4ehWvrTvOsCaiRqHRBPWkSZNw4sQJrFmzpt63NX36dOTk5Jiny5cv1/s2qf71DvPEe//oBLkMWL3/MqavZVgTkfQpbF1ATcTGxuKXX37Brl274O/vb56v1+tRUlICg8Fg0atOS0uDXq83t9m/f7/F+irvCq9scyOVSgWVSmXlvSApGNrZDwAw9bsj+PbgZZiEwLvDOkIul9m4MiKi6km6Ry2EQGxsLH766Sds374dwcHBFsu7du0Ke3t7bNu2zTwvPj4eSUlJiIqKAgBERUXh+PHjSE9PN7fZsmULNBoNwsPDG2ZHSFKGdvbDoscjIJcB38ddwYvfH+XbtohIsiTdo540aRK++eYbrF+/Hi4uLuZrylqtFmq1GlqtFmPHjsXUqVPh7u4OjUaD5557DlFRUbjrrrsAAPfddx/Cw8MxcuRIzJ8/H6mpqXj99dcxadIk9pqbsYci/CCXyTDl2yP46XAykg2FWP5UV7g7KW1dGhGRBUn3qD/66CPk5OSgX79+8PHxMU/ffvutuc2iRYtw//33Y9iwYejTpw/0ej3Wrl1rXm5nZ4dffvkFdnZ2iIqKwlNPPYWnn34ac+fOtcUukYQ80MkXn4+KhItKgf2JWXho2Z84l5Zr67KIiCxIukctxO1v9HFwcMCyZcuwbNmym7YJDAzExo0brVkaNRH9Wuuw9tmeGPvlQSRlFeCRD/fgvcc6IaZd9fcvEBE1NEkHNVFtJSYm1ritq6srdDodwrxdsG5SL/xrVRz2J2bhma/i8HhkAGY8EA5nFf8XISLb4m8hahLyjQYAMgwcOLDG33Fx0SAh4Rx0Oh3cnZRYNbYH3t8Sj092XcC3By9jz4UMLHosApFB7vVWNxHR7TCoqUkoLsgDIDD8lYUIanX7u/mzUq/gk1fHwWAwQKfTAQCUCjmmD2qLe1rr8OJ3R3E5qxD/+HgvhndrgX/f1woezrz5kIgaHoOamhRXnS90/sG3b/i36k6VuwP4z/0++PCva9iSkIvV+5Ow4cgVjI/yw7P3todSIel7MImoiWFQU7NU01PlKv92cBswHtCHYvHvl/Hj0XTEDmiFhzv7M7CJqEEwqKlZqs2pcpMQOHE5C8cyTLgMN7z843Es3noOE/q0xOPdAuCo5P9GRFR/+BuGmrWaniqXy2T49a2heHPNTqw7nYuUnCLM+fkUFm4+i4c6++KJ7i3Qzldb5Xvp6ekwGAw1r+fvO9GJiCoxqIlqSJQW4dH2bnjxwUj8GJeMT3adx8XMAqz6Kwmr/kpCR38tHorww5AOPtBrHZCeno7Q0DDk5tb8NanX34lORAQwqIlqTaWww5M9WmB4twD8dSET3+xPwm8nU3HsSg6OXcnBm/87hW6B7ujqbYdCO0dMeHsh3PX+t11vdXeiExExqInqSC6XoWeoJ3qGeiIzrxgbjl7F/46l4OClbOy/mIX9FwG/Zz7DngIgpMAZQR6O8HNVQ2HHm9CIqOYY1ERW4OGswphewRjTKxhXDYXYeDwFP8ddxJHkXORCgSOXDThy2QCFXAY/VzX83NQIcHOEl4sKdnzFJhHdAoOayMp8XdUYd3dL9PEuQ5sOEXhywY/IhjMuZuYjv7gcl7IKcCmrAEAm7O1k8HVVw99VDcdSAcjY2yYiSwxqolqozbPEExMTIUoKEeAiR1d/bwghkJFXgmRDIa5kF+BKdiGKy0y4lFmAS5kFAICAKd9i2q9XcHeiQNdAN3Ru4QpXR756k6g5Y1AT1UBdniVeqbCgEAAgk8ng5aKCl4sKEQGu5uC+kl2AZEMhLmfmo0SpxtGUQhxNSTB/P8TLCV0D3dA10A1dWrghxMsZcp4uJ2o2GNRENVDbZ4kDwIUTB/HdwtdRXFJc7fLrg7tzCzekXb6AhS//C/O/+B5XipQ4dCkbFzLycf5axfTdwSsAABcHBdr7atHOV4P2fhV/tvRybrTXums71hzgeHNqXhjURLVQm2eJZ6VeqdW6ZTIZSjMuoa0yC4NbBwOd1MgpKsfp9EKcSi/C6fQinMkoQm5RGfZeyMTeC5nm76rt7dDGxwXtfbVopXdBqJczQnRO8HJWQSazDHApPYSlLmPNAY43p+aFQU0kETU6vS63g71nCyi9Q6D0DoHatxU0LdqisLQch5MMOJxksGiucVAgROeMlp7OCHBXQ6sow4vPjIExJRHleZmAMN22rvoMRYPBgNxcIya8/VmNxpoDHG9OzQ+Dmkgi6vqqzq2nz0Dp4YcTyTk4ddWIhPQ8JFzLw+WsAhiLyqoEuObhmdAAkAFwtAec7WVQKwC1AnBUyOCgANSKinlFGcn47LX6D0V3vX+t3npG1JwwqIkkprav6rSTyxDi5YwQL2c8FOFnnl9UWo6Lmfk4n56PxIw8XMkuRHxyBvafOA+Vuy9MAPJLgfxScd3axA1r18P/ua/xzE+XEOBlgM5F9f+TxuHv/3aAl4sKaqXdHe03EVWPQU3UyN1qyJgcQJgDEOYPwN8Bic6lWPf8BLz0+a9w8gqAsagMxsJS5BeXIb+4HHklZX//dxnyS8pRbhKwc9QiMbsEidnXblmHo70c7o528HZxgJ+HC3R/3yin01SEeWWoa9SKKtfNiejmGNREjdSdDBkrLiyC3sEeLg728HNVV9tGCIGzJ4/gi7dfhp2ze9XJyc38p9xehYJSEwpyTLiSU4q4K7k33bZSIYeXc0WAO8pK4X7vRJzIMMFbngNXtRKujvZwVNoxzIn+xqAmaqTqY8jY9WQyGURRHkozLmHYuOdvug0hBEpNQFEZkHbtGn5d/Tlee/NdwEGDdGMR0nOLkZ5bjGu5xcgpLEVJmQnJhkIkGyrGl7t0GYLjmSYcz0w3r1Mhl0HraA9XtT20anu4qpVwd1LCw7lhHv7CIWMkJQxqokauPoeM1XYbGpUMP57+HY+2d0OrVq2qLC8qLcc1c3AX4cT5y3jz/aXoMugJlNmpYSgoQW5RGcpMApl5JcjMK6myDrUdoHtsLpbvu4a7ctRopXdBmM4ZTirr/DrjkDGSGgY1EVnd7R616gLARQnIHLKR88cq9BjzFHT+FTfClZsEjEWlyCkohaGwFDmFpcguKEFWfkWIF5YD6uAuWHvSgLUnDeZ1+rup0drbBWHeLgjVOSPEywktvZyhVdvXqnYOGSOpYVATkdXU9bp55WNWgYq72N0clXCr5hnnxWXlOJ94CWs+XoRxL87EtRIF4tNycS23GFeyC3EluxDbzqRbfMfTWYUQL6e/x5M7IdjTCb5/v8FM43DzEOeQMZIKBjURWU1tr5vX5po5AKgUdvBUy5B3bDMm3rXUfHo9O78EZ9Ny/57ycP5axZRmLEZGXsW0LzGryvpcVAr4uqrh6+rw959qyAqNULXoAGOJgFu5CfZ8fzjZGIOaiKyupte063rN/EZuTkr0aOmBHi09LObnFpUiMSO/IrjTK/5MyirAVUMhsgtKkVtchvi0XMSnWd6lrn9iHv6XWA4knodKIYezSgFnB0XFn9dNWkd7aG/RKyeyBgY1ETVZLg726OjvCr2yBO2cCoBgF1RcIQcKS024ll+G9PxSXMsrQ1pexX9fyczD8YQkqD0DUCaA4jITistKkJlf9cY2AJDLACd7wOuRGViwJQEdzuYgxF2FQDcllLfojfMucaopBjURNWl1vYt78tKf4BPSGnlFZcgrvmEqKkNucRlyCkpRZhLILQEcw3pgy2WBLZcrrpGL8lKUZiShJO0CStLOo/hqPErSzpufr867xKmmGNRE1KTV9i7uyuvmJaXFUCnsoHK2g4ezqtq2QgjkFZfh2JFD+G3tarSLeRLC0R3ZRQIlsDe/PAW4FwCgkAEeahmcy3Ox58t5SLmWxaCm22JQE1GjdLshYDe2q+ld3LW5bi6TyeDiYA8PRQnyjvyKzk+PQqv2oRBCILeoDNfyipFuLEZ6bhFScopQXGZCWoFAGpzhPfwtPLzqPNr7ZaBbkDt6hXqge7AHnK00HpyaDv5EEFGjYo0hYPVNJpNBo7aHRm2PEC9nABW978z8Elw1FOLC1Qycv5IKhdYbx67k4NiVHHz+ZyIUchkiAlzRK9QTvUI9ERHgCqWCd503dwxqImpU6nsIWH2RyWTwdFbB01kFPbKx6/Wx+CPuBDLlrvjrQhZ2J2QgKasABy9l4+ClbHyw7RwclXboHuyO3qGe6BniiTZ6F8jlfAZ6c8OgJqJGqaGHgNUHnbM9erfyM7+e9HJWAXYnZODPhAzsPZ+JzPwS7Iy/hp3xFW8u83BSomeoJ+4O80SfMC/otQ62LJ8aCIOaiMhGqrvO3sUV6BLpjNiuTkjMKsHhlAIcvlqA46mFyMwvwc9Hr+Lno1cBAIGuSnT1c0SknyM66NVQ3XCanEPAmgYGNRFRA6vTdXY7e6h8WsEhKALq4C5Q+oThkqEElwwlWHvSAFFWgqLLJ1B08TAKLxxCacYlDgFrIhjUREQNrK7X2R9+aqy5fXG5QFq+QEqBQGq+QAGUUAd3gTq4C9zuGQuVrByZx3bg401xiOkUCFf17X/dswcuTQxqIiIbqe119hvbB/z9pxAC2QWluJSZj0tZBUjOLkSxyQ7OHaLx+SkTPj+ViOLUBBQlHkJh4mEUJ58GTGVVtsMeuDQxqImIGjmZTAZ3JyXcnZTo3MINZeUm7DtwANu274BPjyEogANU+lCo9KHQRj0GhQzQOcrg6ySDr7MMTvYyvqpTwhjURERNjMJODg9FCQw7V2D4gzHwCwtGUlYBLmUVICmzAIWl5biaL3A1XwDpFXeT61Q+UPm3Q7lJ2Lp8ugGDmoioiXNSKdDWR4O2PhoIIZCRV4KLmfm4mJmPFEMRMvNLkJkP6Ee8i8e+uYB+bQswoI0OfVt5wc2p6nvBqWExqImImhGZTAYvFxW8XFToFuSOotJyXMoswOmkNFxIz0EuNOYhYHIZ0LmFG/q30aF/Gx3a6F0gk/GBKw2NQU1E1Iw52Nuhtd4FbmUZ2DXjKfxn9f9wuVyD/ZfzcSG7BHGXshF3KRsLfouHp5MCdwU4IaqFEzr5qKHzcOf17AbAoCYiooqx3UIgdvgg8zw7Fy+oQyKhDukGh8COyMh3wC9ncvDLmRyYigtQdvk43o4djqHdQ+HqyFPk9YVBTUREtx3bXWYSSC8QSM6rmApVjlCG9sDsTYl4Y/NFRAa64d5wb9wb7o1AD6eG34EmjEFNRERmtxrb7QsgAhXjts8kJOK7NV+jy5CncSG7BPsSs7AvMQtv/u80Wnk7I7qtN6LDvRHh78oXidwhBjUREdWKTCaDh1qGnD9WYflnM6D29MfW02nYcioN+xKzcDYtD2fT8vDhzvPwdFYhuq0O94Z7o1eoJxzs7WxdfqPDoCYiojpLTExEMIBeXkCvvu7IvUuLA1fysTcpHweuFCAjrxhrDlzGmgOX4aCQo08rL0SHe2NAGx08nFW2Lr9RYFATEVGt1ejFInIFHFq0hzq0BxzDeqBIo8PmU2nYfCoNchnQUa9G32AX9A5yhtah+p42nz/OoCYiojqo7YtFrpw7hW8/fxOOod2hDrsLKn0ojqQU4khKIRb/mYKiS0dRcOYPFJzdC1NRnvl7Tk7O2LJlMzw8PGpUV1MMdgY1ERHVWW1eLFKafgGD/hmLoFZtkFcikJQrkJRrQnaxnfnNX56DnofeSYYgjQzytHh8M28qevbsWeN6muKLRRjURETUYCqDXQeg5d/zsgtKcC4tD+fSc5GRV4KUfIGUfAEFQuB+37OI6twO7VsF3/apaE31xSIMaiIisik3RyW6B7uje7A7svJLEJ+Wi9MpRuQWlcGl8yCcAHD1ih3CfTUI99VA3czuHJfbugAiIqJK7k5KRLX0wJieQYh0ykLeie2QQyCroAR/JmTg8z8TseVUGtKNRbYutcGwR01ERJIjk8ngoShB5v8WYug93SE8WuJYcg6u5RbjVIoRp1KM8NE6oJO/K0J1zrBrwg9VYVATEZGk2cuBVn5atPPVINVYhCOXDUhIz0NKThFSclLhnKBA5wBXeKNpvkubQU1ERI2CTCaDj1YNH60a+cVlOJGcg2PJOcgrLsMfCRmwlwOufZ5GVkGZrUu1Kl6jJiKiRsdJpUCPlh4Y0ysI0W11cHO0R6kJ0EY9hpHfX8T0tcdxMSPf1mVaBYOaiIgaLYVcjna+Woy8KxB3+8pRlHwapeUCq/cnof/7O/H8msOIT821dZl3hEFNRESNnkwmg7+LHGmrpuH9wf64p7UXTAJYf+QqYhbvwvj/HsSRywZbl1knvEZNRERNinNhKqb3CsY/2jhgzdFs/HExD1tOVbzdq7OPGk9EuKOTXg2ZTNYoHjnKoCYioibhZi8KUbj7QXvXo3AKvweHUwpxOCUZxclnkLP3OyjSz0j+kaMMaiIiahJu96KQ/FKB01kmnM8RUPm1ge7RmShJT8RPhy5j3H1ekh2LzaAmIqIm5VYvCgkOBvKLy3D4sgFHL2cDumDM25mK1cd3YmK/EDzc2R9KhbRu35JWNURERPXMSaVA71BPPNTSDoY/VsFFJcfFzAK8/ONx9F2wAyt2J6KwpNzWZZoxqImIqFlS2smQs2cNVj0WjNeHtIXORYWUnCLM+fkUer27Hct2JCCnsNTWZfLUNxERNW+pVy6hT3Aw7nrYH5sTcvHdsSyk5pVgwW/xWLb9HIa00WJwaw38NEoAaPA7xRnURETULN3sLnHI5HBq2weaqH8AnoH4/ng2vj+ejcKLh5F3+FfYpZ1GwtkzDRbWDGoiImqWbneXuBACyfkCCQaBlHwBdVBnqIM6ozDxEAwGA4OaiIioIdzqLnFvAF0A5BSW4uTVHBy/nI3Mc38BeLzB6mtWN5MtW7YMQUFBcHBwQI8ePbB//35bl0RERI2AVm2PniGeeDDEDnnHtjTotptNUH/77beYOnUqZs2ahUOHDqFTp06IiYlBenq6rUsjIqJGwk4mA8ob9k7wZhPUCxcuxPjx4zFmzBiEh4dj+fLlcHR0xBdffGHr0oiIiG6qWQR1SUkJ4uLiEB0dbZ4nl8sRHR2NvXv32rAyIiKiW2sWN5NlZGSgvLwc3t7eFvO9vb1x5syZKu2Li4tRXFxs/pyTkwMAMBqNd1xLXl4eACD14jkUF97+pebXki9W/Hn5AtQqe6u3b4htNIWamsI+SLGmprAPrKn57AMAZKddBVDxu9wameDi4gKZ7DbPGBfNQHJysgAg9uzZYzF/2rRponv37lXaz5o1SwDgxIkTJ06c6nXKycm5bYY1ix61p6cn7OzskJaWZjE/LS0Ner2+Svvp06dj6tSp5s8mkwlZWVnw8PC4/b98bsFoNCIgIACXL1+GRqOp83ro//GYWh+PqfXxmFpfUzmmLi4ut23TLIJaqVSia9eu2LZtG4YOHQqgIny3bduG2NjYKu1VKhVUKpXFPFdXV6vVo9FoGvUPlhTxmFofj6n18ZhaX3M4ps0iqAFg6tSpGDVqFCIjI9G9e3csXrwY+fn5GDNmjK1LIyIiuqlmE9SPP/44rl27hpkzZyI1NRURERHYtGlTlRvMiIiIpKTZBDUAxMbGVnuqu6GoVCrMmjWryml1qjseU+vjMbU+HlPra07HVCaEELYugoiIiKrXLB54QkRE1FgxqImIiCSMQU1ERCRhDGoiIiIJY1A3IL4Pu3rz5s1Dt27d4OLiAp1Oh6FDhyI+Pt6iTVFRESZNmgQPDw84Oztj2LBhVZ40l5SUhCFDhsDR0RE6nQ7Tpk1DWVmZRZudO3eiS5cuUKlUCA0NxcqVK+t792zunXfegUwmw5QpU8zzeDzrJjk5GU899RQ8PDygVqvRoUMHHDx40LxcCIGZM2fCx8cHarUa0dHROHfunMU6srKyMGLECGg0Gri6umLs2LHmdwBUOnbsGO6++244ODggICAA8+fPb5D9a2jl5eWYMWMGgoODoVarERISgjfeeAPX3+PMYwo0i2d9S8GaNWuEUqkUX3zxhTh58qQYP368cHV1FWlpabYuzeZiYmLEihUrxIkTJ8SRI0fE4MGDRYsWLUReXp65zb/+9S8REBAgtm3bJg4ePCjuuusu0bNnT/PysrIy0b59exEdHS0OHz4sNm7cKDw9PcX06dPNbS5cuCAcHR3F1KlTxalTp8TSpUuFnZ2d2LRpU4Pub0Pav3+/CAoKEh07dhTPP/+8eT6PZ+1lZWWJwMBAMXr0aLFv3z5x4cIF8dtvv4mEhARzm3feeUdotVqxbt06cfToUfHggw+K4OBgUVhYaG4zcOBA0alTJ/HXX3+JP/74Q4SGhoonnnjCvDwnJ0d4e3uLESNGiBMnTojVq1cLtVotPv744wbd34bw1ltvCQ8PD/HLL7+IxMRE8f333wtnZ2fxwQcfmNvwmArBoG4g3bt3F5MmTTJ/Li8vF76+vmLevHk2rEqa0tPTBQDx+++/CyGEMBgMwt7eXnz//ffmNqdPnxYAxN69e4UQQmzcuFHI5XKRmppqbvPRRx8JjUYjiouLhRBCvPTSS6Jdu3YW23r88cdFTExMfe+STeTm5oqwsDCxZcsW0bdvX3NQ83jWzcsvvyx69+590+Umk0no9XqxYMEC8zyDwSBUKpVYvXq1EEKIU6dOCQDiwIED5ja//vqrkMlkIjk5WQghxIcffijc3NzMx7ly261bt7b2LtnckCFDxD//+U+LeY888ogYMWKEEILHtBJPfTcAvg+7dipfK+ru7g4AiIuLQ2lpqcXxa9OmDVq0aGE+fnv37kWHDh0snjQXExMDo9GIkydPmttcv47KNk3172DSpEkYMmRIlX3m8aybDRs2IDIyEv/4xz+g0+nQuXNnfPrpp+bliYmJSE1NtTgmWq0WPXr0sDiurq6uiIyMNLeJjo6GXC7Hvn37zG369OkDpVJpbhMTE4P4+HhkZ2fX9242qJ49e2Lbtm04e/YsAODo0aP4888/MWjQIAA8ppWa1ZPJbKW278NuzkwmE6ZMmYJevXqhffv2AIDU1FQolcoqL0bx9vZGamqquU11x7dy2a3aGI1GFBYWQq1W18cu2cSaNWtw6NAhHDhwoMoyHs+6uXDhAj766CNMnToVr776Kg4cOIDJkydDqVRi1KhR5uNS3TG5/pjpdDqL5QqFAu7u7hZtgoODq6yjcpmbm1u97J8tvPLKKzAajWjTpg3s7OxQXl6Ot956CyNGjAAAHtO/MahJUiZNmoQTJ07gzz//tHUpjdbly5fx/PPPY8uWLXBwcLB1OU2GyWRCZGQk3n77bQBA586dceLECSxfvhyjRo2ycXWN03fffYevv/4a33zzDdq1a4cjR45gypQp8PX15TG9Dk99N4Davg+7uYqNjcUvv/yCHTt2wN/f3zxfr9ejpKQEBoPBov31x0+v11d7fCuX3aqNRqNpUr2/uLg4pKeno0uXLlAoFFAoFPj999+xZMkSKBQKeHt783jWgY+PD8LDwy3mtW3bFklJSQD+/7jc6v9zvV6P9PR0i+VlZWXIysqq1bFvKqZNm4ZXXnkFw4cPR4cOHTBy5Ei88MILmDdvHgAe00oM6gZw/fuwK1W+DzsqKsqGlUmDEAKxsbH46aefsH379iqnqLp27Qp7e3uL4xcfH4+kpCTz8YuKisLx48ct/ofdsmULNBqN+ZdrVFSUxToq2zS1v4MBAwbg+PHjOHLkiHmKjIzEiBEjzP/N41l7vXr1qjJs8OzZswgMDAQABAcHQ6/XWxwTo9GIffv2WRxXg8GAuLg4c5vt27fDZDKhR48e5ja7du1CaWmpuc2WLVvQunVryZ+ira2CggLI5ZYxZGdnB5PJBIDH1MzWd7M1F2vWrBEqlUqsXLlSnDp1SkyYMEG4urpa3FXbXE2cOFFotVqxc+dOkZKSYp4KCgrMbf71r3+JFi1aiO3bt4uDBw+KqKgoERUVZV5eOZzovvvuE0eOHBGbNm0SXl5e1Q4nmjZtmjh9+rRYtmxZkx5OdL3r7/oWgsezLvbv3y8UCoV46623xLlz58TXX38tHB0dxapVq8xt3nnnHeHq6irWr18vjh07Jh566KFqhxJ17txZ7Nu3T/z5558iLCzMYiiRwWAQ3t7eYuTIkeLEiRNizZo1wtHRsdEMJaqNUaNGCT8/P/PwrLVr1wpPT0/x0ksvmdvwmHJ4VoNaunSpaNGihVAqlaJ79+7ir7/+snVJkgCg2mnFihXmNoWFheLZZ58Vbm5uwtHRUTz88MMiJSXFYj0XL14UgwYNEmq1Wnh6eooXX3xRlJaWWrTZsWOHiIiIEEqlUrRs2dJiG03ZjUHN41k3P//8s2jfvr1QqVSiTZs24pNPPrFYbjKZxIwZM4S3t7dQqVRiwIABIj4+3qJNZmameOKJJ4Szs7PQaDRizJgxIjc316LN0aNHRe/evYVKpRJ+fn7inXfeqfd9swWj0Sief/550aJFC+Hg4CBatmwpXnvtNYthVDymQvA1l0RERBLGa9REREQSxqAmIiKSMAY1ERGRhDGoiYiIJIxBTUREJGEMaiIiIgljUBMREUkYg5qIAAAymQzr1q2z2vpWrlxZ5Q1dRFR7DGoiiZHJZLecZs+efdPvXrx4ETKZDEeOHKn3Onfs2IHBgwfDw8MDjo6OCA8Px4svvojk5OR63zZRc8KgJpKYlJQU87R48WJoNBqLef/+979tXSI+/vhjREdHQ6/X48cff8SpU6ewfPly5OTk4P3336/XbV//YgWi5oBBTSQxer3ePGm1WshkMvNnnU6HhQsXwt/fHyqVChEREdi0aZP5u5VvHuvcuTNkMhn69esHADhw4ADuvfdeeHp6QqvVom/fvjh06FCd6rty5QomT56MyZMn44svvkC/fv0QFBSEPn364LPPPsPMmTMt2v/2229o27YtnJ2dMXDgQKSkpJiX1aQumUyGjz76CA8++CCcnJzw1ltvAQDefPNN6HQ6uLi4YNy4cXjllVcQERFh8d3PPvsMbdu2hYODA9q0aYMPP/zQvKykpASxsbHw8fGBg4MDAgMDza9XJJIUWz9snIhubsWKFUKr1Zo/L1y4UGg0GrF69Wpx5swZ8dJLLwl7e3tx9uxZIUTFG54AiK1bt4qUlBSRmZkphBBi27Zt4quvvhKnT58Wp06dEmPHjhXe3t7CaDSa1w1A/PTTT7etaeHChQKAuHr16m1rt7e3F9HR0eLAgQMiLi5OtG3bVjz55JPmNjWtS6fTiS+++EKcP39eXLp0SaxatUo4ODiIL774QsTHx4s5c+YIjUYjOnXqZP7eqlWrhI+Pj/jxxx/FhQsXxI8//ijc3d3FypUrhRBCLFiwQAQEBIhdu3aJixcvij/++EN88803t91/oobGoCaSsBuD2tfXV7z11lsWbbp16yaeffZZIYQQiYmJAoA4fPjwLddbXl4uXFxcxM8//2yeV9OgnjhxotBoNDWqHYBISEgwz1u2bJnw9vaudV1TpkyxaNejRw8xadIki3m9evWyCOqQkJAqwfvGG2+YX+f53HPPif79+wuTyXTbfSGyJZ76JmokjEYjrl69il69elnM79WrF06fPn3L76alpWH8+PEICwuDVquFRqNBXl4ekpKSal2HEAIymaxGbR0dHRESEmL+7OPjg/T09FrXFRkZafE5Pj4e3bt3t5h3/ef8/HycP38eY8eOhbOzs3l68803cf78eQDA6NGjceTIEbRu3RqTJ0/G5s2ba3YAiBqYwtYFEFH9GzVqFDIzM/HBBx8gMDAQKpUKUVFRKCkpqfW6WrVqhZycHKSkpMDHx+eWbe3t7S0+y2QyiOverFvTupycnGpVY15eHgDg008/RY8ePSyW2dnZAQC6dOmCxMRE/Prrr9i6dSsee+wxREdH44cffqjVtojqG3vURI2ERqOBr68vdu/ebTF/9+7dCA8PBwAolUoAQHl5eZU2kydPxuDBg9GuXTuoVCpkZGTUqY5HH30USqUS8+fPr3a5wWCo8brqWlfr1q1x4MABi3nXf/b29oavry8uXLiA0NBQi6nyhjug4pg+/vjj+PTTT/Htt9/ixx9/RFZWVo3rJ2oI7FETNSLTpk3DrFmzEBISgoiICKxYsQJHjhzB119/DQDQ6XRQq9XYtGkT/P394eDgAK1Wi7CwMHz11VeIjIyE0WjEtGnToFar61RDQEAAFi1ahNjYWBiNRjz99NMICgrClStX8N///hfOzs41HqJV17qee+45jB8/HpGRkejZsye+/fZbHDt2DC1btjS3mTNnDiZPngytVouBAweiuLgYBw8eRHZ2NqZOnYqFCxfCx8cHnTt3hlwux/fffw+9Xs+HtJDksEdN1IhMnjwZU6dOxYsvvogOHTpg06ZN2LBhA8LCwgAACoUCS5YswccffwxfX1889NBDAIDPP/8c2dnZ6NKlC0aOHInJkydDp9PVuY5nn30WmzdvRnJyMh5++GG0adMG48aNg0ajqdU477rWNWLECEyfPh3//ve/zaewR48eDQcHB3ObcePG4bPPPsOKFSvQoUMH9O3bFytXrjT3qF1cXDB//nxERkaiW7duuHjxIjZu3Ai5nL8WSVpk4voLRkREjdS9994LvV6Pr776ytalEFkVT30TUaNTUFCA5cuXIyYmBnZ2dli9ejW2bt2KLVu22Lo0IqvjOR4isvD2229bDGm6fho0aJCtywNQcff4xo0b0adPH3Tt2hU///wzfvzxR0RHR9u6NCKr46lvIrKQlZV10zuf1Wo1/Pz8GrgiouaNQU1ERCRhPPVNREQkYQxqIiIiCWNQExERSRiDmoiISMIY1ERERBLGoCYiIpIwBjUREZGEMaiJiIgk7P8AaOChRa1EYwgAAAAASUVORK5CYII=",
      "text/plain": [
       "<Figure size 500x500 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.displot(data= data, x='Total_Charges' ,bins=30, kde= True)\n",
    "plt.title('Distribution of Total_Charges');"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 370,
   "metadata": {},
   "outputs": [],
   "source": [
    "correlation_matrix = data.select_dtypes(\"number\").corr()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 371,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.heatmap(correlation_matrix,annot=True, cmap='coolwarm', fmt='.2f', linewidths=0.5)\n",
    "plt.title('Correlation Heatmap of Numerical Columns');"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Total Revenye and Total Charges have high correlation thus one of the columns need to be dropped"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 372,
   "metadata": {},
   "outputs": [],
   "source": [
    "data.drop(columns =['Total_Charges'], inplace = True)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Feature Engineering"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 373,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "' \\nGroup some of the numerical features into bins\\n- Age\\n- Tenure\\n- Monthly Charge\\n'"
      ]
     },
     "execution_count": 373,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "\"\"\" \n",
    "Group some of the numerical features into bins\n",
    "- Age\n",
    "- Tenure\n",
    "- Monthly Charge\n",
    "\"\"\"\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 374,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Define age bins and labels\n",
    "age_bins = [0, 30, 45, 60, 100]\n",
    "age_labels =  ['18-30', '31-45', '46-60', '61+']\n",
    "\n",
    "# Create Age Group column\n",
    "data['Age_Group'] = pd.cut(data['Age'], bins=age_bins, labels=age_labels, right=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 375,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Define tenure bins and labels\n",
    "tenure_bins = [0, 6, 12, 24, 36, 60]\n",
    "tenure_labels = ['New', 'Short-term', 'Mid-term', 'Long-term', 'Very Long-term']\n",
    "\n",
    "# Create Tenure Category column\n",
    "data['Tenure_Category'] = pd.cut(data['Tenure_in_Months'], bins=tenure_bins, labels=tenure_labels, right=False)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 376,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Define bins and labels\n",
    "bins = [0, 40, 80, 120, 200]  # Define bin edges\n",
    "labels = ['Low', 'Medium', 'High', 'Very High']  # Define bin labels\n",
    "\n",
    "# Create Monthly Charge Category column\n",
    "data['Charge_Category'] = pd.cut(data['Monthly_Charge'], bins=bins, labels=labels, right=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 377,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.countplot(data=data, x= 'Charge_Category')\n",
    "plt.title('Charge Category Countplot');"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 378,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.countplot(data=data, x= 'Tenure_Category')\n",
    "plt.title('Tenure Category Countplot');"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 379,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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KemgA4DK4hggAANge1xABAADbIxABAADb4xqii5Sfn69jx47pmmuu4dH0AABcIYwxOnXqlEJDQ+Xmdv7zQASii3Ts2DHrSyoBAMCV5ejRo6pevfp5+wlEF6ngiy2PHj0qPz+/Mh4NAAC4GJmZmQoLC7vgF1RLBKKLVvAxmZ+fH4EIAIArzN9d7sJF1QAAwPYIRAAAwPYIRAAAwPYIRAAAwPYIRAAAwPYIRAAAwPYIRAAAwPYIRAAAwPYIRAAAwPYIRAAAwPYIRAAAwPYIRAAAwPYIRAAAwPYIRAAAwPYIRAAAwPbcy3oAwNWi2Yj3ynoI+D+JUx4q6yEAuMJwhggAANgegQgAANgegQgAANgegQgAANgegQgAANgegQgAANgegQgAANgegQgAANgeD2YEgGLgQZyugwdxoiRwhggAANgegQgAANgegQgAANgegQgAANhemQaijRs3qlevXgoNDZXD4dCyZcsK1ezbt0+33Xab/P395evrqxYtWujIkSNW/9mzZxUdHa1KlSqpQoUK6tOnj1JTU532ceTIEfXo0UPly5dXUFCQRowYoXPnzl3u6QEAgCtEmQai06dPq3HjxoqNjS2y/4cfflDbtm0VHh6u9evXa/fu3RozZoy8vb2tmmHDhunTTz/VRx99pA0bNujYsWO68847rf68vDz16NFDOTk52rx5s959910tWLBAY8eOvezzAwAAV4Yyve2+W7du6tat23n7R48ere7du2vy5MlW2/XXX2/9OSMjQ2+//bYWLlyoTp06SZLeeecd1atXT1u2bFGrVq20evVqfffdd/ryyy8VHBysJk2a6MUXX9TIkSM1btw4eXp6Xr4JAgCAK4LLXkOUn5+v//znP7rhhhsUFRWloKAgtWzZ0uljtcTEROXm5ioyMtJqCw8PV40aNZSQkCBJSkhIUMOGDRUcHGzVREVFKTMzU3v37i21+QAAANflsoEoLS1NWVlZeuWVV9S1a1etXr1ad9xxh+68805t2LBBkpSSkiJPT08FBAQ4bRscHKyUlBSr5s9hqKC/oO98srOzlZmZ6bQAAICrk8s+qTo/P1+SdPvtt2vYsGGSpCZNmmjz5s2aO3eu2rdvf1mPP2nSJI0fP/6yHgMAALgGlz1DVLlyZbm7u6t+/fpO7fXq1bPuMgsJCVFOTo7S09OdalJTUxUSEmLV/PWus4L1gpqijBo1ShkZGdZy9OjRfzolAADgolw2EHl6eqpFixZKTk52at+/f79q1qwpSWrWrJk8PDy0Zs0aqz85OVlHjhxRRESEJCkiIkJ79uxRWlqaVRMfHy8/P79CYevPvLy85Ofn57QAAICrU5l+ZJaVlaWDBw9a64cOHVJSUpICAwNVo0YNjRgxQvfee6/atWunjh07atWqVfr000+1fv16SZK/v78GDhyo4cOHKzAwUH5+fnriiScUERGhVq1aSZK6dOmi+vXr68EHH9TkyZOVkpKi559/XtHR0fLy8iqLaQMAABdTpoFox44d6tixo7U+fPhwSVL//v21YMEC3XHHHZo7d64mTZqkJ598UnXr1tWSJUvUtm1ba5vp06fLzc1Nffr0UXZ2tqKiovTGG29Y/eXKldPKlSs1ZMgQRUREyNfXV/3799eECRNKb6IAgCtasxHvlfUQ8H8Spzx0WfZbpoGoQ4cOMsZcsGbAgAEaMGDAefu9vb0VGxt73oc7SlLNmjX12WefFXucAADg6uay1xABAACUFgIRAACwPQIRAACwPQIRAACwPQIRAACwPQIRAACwPQIRAACwPQIRAACwPQIRAACwPQIRAACwPQIRAACwPQIRAACwPQIRAACwPQIRAACwPQIRAACwPQIRAACwPQIRAACwPQIRAACwPQIRAACwPQIRAACwPQIRAACwPQIRAACwPQIRAACwPQIRAACwPQIRAACwPQIRAACwPQIRAACwPQIRAACwPQIRAACwPQIRAACwPQIRAACwvTINRBs3blSvXr0UGhoqh8OhZcuWnbf2sccek8Ph0IwZM5zaT5w4oX79+snPz08BAQEaOHCgsrKynGp2796tW265Rd7e3goLC9PkyZMvw2wAAMCVqkwD0enTp9W4cWPFxsZesG7p0qXasmWLQkNDC/X169dPe/fuVXx8vFauXKmNGzdq8ODBVn9mZqa6dOmimjVrKjExUVOmTNG4ceM0b968Ep8PAAC4MrmX5cG7deumbt26XbDm559/1hNPPKEvvvhCPXr0cOrbt2+fVq1ape3bt6t58+aSpNmzZ6t79+567bXXFBoaqri4OOXk5Gj+/Pny9PRUgwYNlJSUpGnTpjkFJwAAYF8ufQ1Rfn6+HnzwQY0YMUINGjQo1J+QkKCAgAArDElSZGSk3NzctHXrVqumXbt28vT0tGqioqKUnJyskydPnvfY2dnZyszMdFoAAMDVyaUD0auvvip3d3c9+eSTRfanpKQoKCjIqc3d3V2BgYFKSUmxaoKDg51qCtYLaooyadIk+fv7W0tYWNg/mQoAAHBhLhuIEhMTNXPmTC1YsEAOh6PUjz9q1ChlZGRYy9GjR0t9DAAAoHS4bCD66quvlJaWpho1asjd3V3u7u46fPiwnn76aV177bWSpJCQEKWlpTltd+7cOZ04cUIhISFWTWpqqlNNwXpBTVG8vLzk5+fntAAAgKuTywaiBx98ULt371ZSUpK1hIaGasSIEfriiy8kSREREUpPT1diYqK13dq1a5Wfn6+WLVtaNRs3blRubq5VEx8fr7p166pixYqlOykAAOCSyvQus6ysLB08eNBaP3TokJKSkhQYGKgaNWqoUqVKTvUeHh4KCQlR3bp1JUn16tVT165dNWjQIM2dO1e5ubmKiYlR3759rVv077//fo0fP14DBw7UyJEj9e2332rmzJmaPn166U0UAAC4tDINRDt27FDHjh2t9eHDh0uS+vfvrwULFlzUPuLi4hQTE6POnTvLzc1Nffr00axZs6x+f39/rV69WtHR0WrWrJkqV66ssWPHcss9AACwlGkg6tChg4wxF13/008/FWoLDAzUwoULL7hdo0aN9NVXX13q8AAAgE247DVEAAAApYVABAAAbI9ABAAAbI9ABAAAbI9ABAAAbI9ABAAAbI9ABAAAbI9ABAAAbI9ABAAAbI9ABAAAbI9ABAAAbI9ABAAAbI9ABAAAbI9ABAAAbI9ABAAAbI9ABAAAbI9ABAAAbI9ABAAAbI9ABAAAbI9ABAAAbI9ABAAAbI9ABAAAbI9ABAAAbI9ABAAAbI9ABAAAbI9ABAAAbI9ABAAAbI9ABAAAbI9ABAAAbI9ABAAAbI9ABAAAbK9MA9HGjRvVq1cvhYaGyuFwaNmyZVZfbm6uRo4cqYYNG8rX11ehoaF66KGHdOzYMad9nDhxQv369ZOfn58CAgI0cOBAZWVlOdXs3r1bt9xyi7y9vRUWFqbJkyeXxvQAAMAVokwD0enTp9W4cWPFxsYW6vv999/1zTffaMyYMfrmm2/0ySefKDk5WbfddptTXb9+/bR3717Fx8dr5cqV2rhxowYPHmz1Z2ZmqkuXLqpZs6YSExM1ZcoUjRs3TvPmzbvs8wMAAFcG97I8eLdu3dStW7ci+/z9/RUfH+/U9vrrr+vmm2/WkSNHVKNGDe3bt0+rVq3S9u3b1bx5c0nS7Nmz1b17d7322msKDQ1VXFyccnJyNH/+fHl6eqpBgwZKSkrStGnTnIITAACwryvqGqKMjAw5HA4FBARIkhISEhQQEGCFIUmKjIyUm5ubtm7datW0a9dOnp6eVk1UVJSSk5N18uTJ8x4rOztbmZmZTgsAALg6XTGB6OzZsxo5cqTuu+8++fn5SZJSUlIUFBTkVOfu7q7AwEClpKRYNcHBwU41BesFNUWZNGmS/P39rSUsLKwkpwMAAFzIFRGIcnNzdc8998gYozlz5pTKMUeNGqWMjAxrOXr0aKkcFwAAlL4yvYboYhSEocOHD2vt2rXW2SFJCgkJUVpamlP9uXPndOLECYWEhFg1qampTjUF6wU1RfHy8pKXl1dJTQMAALgwlz5DVBCGDhw4oC+//FKVKlVy6o+IiFB6eroSExOttrVr1yo/P18tW7a0ajZu3Kjc3FyrJj4+XnXr1lXFihVLZyIAAMCllWkgysrKUlJSkpKSkiRJhw4dUlJSko4cOaLc3Fzddddd2rFjh+Li4pSXl6eUlBSlpKQoJydHklSvXj117dpVgwYN0rZt27Rp0ybFxMSob9++Cg0NlSTdf//98vT01MCBA7V3714tXrxYM2fO1PDhw8tq2gAAwMWU6UdmO3bsUMeOHa31gpDSv39/jRs3TitWrJAkNWnSxGm7devWqUOHDpKkuLg4xcTEqHPnznJzc1OfPn00a9Ysq9bf31+rV69WdHS0mjVrpsqVK2vs2LHccg8AACxlGog6dOggY8x5+y/UVyAwMFALFy68YE2jRo301VdfXfL4AACAPbj0NUQAAAClgUAEAABsj0AEAABsj0AEAABsj0AEAABsj0AEAABsj0AEAABsj0AEAABsj0AEAABsj0AEAABsj0AEAABsj0AEAABsj0AEAABsj0AEAABsj0AEAABsj0AEAABsz72sB3A1azbivbIeAv5P4pSHynoIAAAXxhkiAABgewQiAABgewQiAABgewQiAABgewQiAABgewQiAABgewQiAABgewQiAABgewQiAABgewQiAABgewQiAABgewQiAABgewQiAABge2UaiDZu3KhevXopNDRUDodDy5Ytc+o3xmjs2LGqWrWqfHx8FBkZqQMHDjjVnDhxQv369ZOfn58CAgI0cOBAZWVlOdXs3r1bt9xyi7y9vRUWFqbJkydf7qkBAIArSJkGotOnT6tx48aKjY0tsn/y5MmaNWuW5s6dq61bt8rX11dRUVE6e/asVdOvXz/t3btX8fHxWrlypTZu3KjBgwdb/ZmZmerSpYtq1qypxMRETZkyRePGjdO8efMu+/wAAMCVwb0sD96tWzd169atyD5jjGbMmKHnn39et99+uyTpvffeU3BwsJYtW6a+fftq3759WrVqlbZv367mzZtLkmbPnq3u3bvrtddeU2hoqOLi4pSTk6P58+fL09NTDRo0UFJSkqZNm+YUnAAAgH257DVEhw4dUkpKiiIjI602f39/tWzZUgkJCZKkhIQEBQQEWGFIkiIjI+Xm5qatW7daNe3atZOnp6dVExUVpeTkZJ08ebKUZgMAAFxZmZ4hupCUlBRJUnBwsFN7cHCw1ZeSkqKgoCCnfnd3dwUGBjrV1KpVq9A+CvoqVqxY5PGzs7OVnZ1trWdmZv6D2QAAAFfmsmeIytqkSZPk7+9vLWFhYWU9JAAAcJm4bCAKCQmRJKWmpjq1p6amWn0hISFKS0tz6j937pxOnDjhVFPUPv58jKKMGjVKGRkZ1nL06NF/NiEAAOCyXDYQ1apVSyEhIVqzZo3VlpmZqa1btyoiIkKSFBERofT0dCUmJlo1a9euVX5+vlq2bGnVbNy4Ubm5uVZNfHy86tate96PyyTJy8tLfn5+TgsAALg6lWkgysrKUlJSkpKSkiT9cSF1UlKSjhw5IofDoaFDh+qll17SihUrtGfPHj300EMKDQ1V7969JUn16tVT165dNWjQIG3btk2bNm1STEyM+vbtq9DQUEnS/fffL09PTw0cOFB79+7V4sWLNXPmTA0fPryMZg0AAFxNmV5UvWPHDnXs2NFaLwgp/fv314IFC/Tss8/q9OnTGjx4sNLT09W2bVutWrVK3t7e1jZxcXGKiYlR586d5ebmpj59+mjWrFlWv7+/v1avXq3o6Gg1a9ZMlStX1tixY7nlHgAAWMo0EHXo0EHGmPP2OxwOTZgwQRMmTDhvTWBgoBYuXHjB4zRq1EhfffVVsccJAACubsX6yKxTp05KT08v1J6ZmalOnTr90zEBAACUqmIFovXr1ysnJ6dQ+9mzZzkTAwAArjiX9JHZ7t27rT9/99131sMPJSkvL0+rVq1StWrVSm50AAAApeCSAlGTJk3kcDjkcDiK/GjMx8dHs2fPLrHBAQAAlIZLCkSHDh2SMUbXXXedtm3bpipVqlh9np6eCgoKUrly5Up8kAAAAJfTJQWimjVrSpLy8/Mvy2AAAADKQrFvuz9w4IDWrVuntLS0QgFp7Nix/3hgAAAApaVYgeitt97SkCFDVLlyZYWEhMjhcFh9DoeDQAQAAK4oxQpEL730kiZOnKiRI0eW9HgAAABKXbGeQ3Ty5EndfffdJT0WAACAMlGsQHT33Xdr9erVJT0WAACAMlGsj8xq166tMWPGaMuWLWrYsKE8PDyc+p988skSGRwAAEBpKFYgmjdvnipUqKANGzZow4YNTn0Oh4NABAAArijFCkSHDh0q6XEAAACUmWJdQwQAAHA1KdYZogEDBlywf/78+cUaDAAAQFkoViA6efKk03pubq6+/fZbpaenF/mlrwAAAK6sWIFo6dKlhdry8/M1ZMgQXX/99f94UAAAAKWpxK4hcnNz0/DhwzV9+vSS2iUAAECpKNGLqn/44QedO3euJHcJAABw2RXrI7Phw4c7rRtjdPz4cf3nP/9R//79S2RgAAAApaVYgWjnzp1O625ubqpSpYqmTp36t3egAQAAuJpiBaJ169aV9DgAAADKTLECUYFffvlFycnJkqS6deuqSpUqJTIoAACA0lSsi6pPnz6tAQMGqGrVqmrXrp3atWun0NBQDRw4UL///ntJjxEAAOCyKlYgGj58uDZs2KBPP/1U6enpSk9P1/Lly7VhwwY9/fTTJT1GAACAy6pYH5ktWbJEH3/8sTp06GC1de/eXT4+Prrnnns0Z86ckhofAADAZVesM0S///67goODC7UHBQXxkRkAALjiFCsQRURE6IUXXtDZs2ettjNnzmj8+PGKiIgoscEBAACUhmJ9ZDZjxgx17dpV1atXV+PGjSVJu3btkpeXl1avXl2iAwQAALjcihWIGjZsqAMHDiguLk7ff/+9JOm+++5Tv3795OPjU6IDBAAAuNyK9ZHZpEmTtGjRIg0aNEhTp07V1KlT9a9//UsffPCBXn311RIbXF5ensaMGaNatWrJx8dH119/vV588UUZY6waY4zGjh2rqlWrysfHR5GRkTpw4IDTfk6cOKF+/frJz89PAQEBGjhwoLKyskpsnAAA4MpWrED05ptvKjw8vFB7gwYNNHfu3H88qAKvvvqq5syZo9dff1379u3Tq6++qsmTJ2v27NlWzeTJkzVr1izNnTtXW7dula+vr6Kiopyub+rXr5/27t2r+Ph4rVy5Uhs3btTgwYNLbJwAAODKVqyPzFJSUlS1atVC7VWqVNHx48f/8aAKbN68Wbfffrt69OghSbr22mv1wQcfaNu2bZL+ODs0Y8YMPf/887r99tslSe+9956Cg4O1bNky9e3bV/v27dOqVau0fft2NW/eXJI0e/Zsde/eXa+99ppCQ0NLbLwAAODKVKwzRGFhYdq0aVOh9k2bNpVowGjdurXWrFmj/fv3S/rjwu2vv/5a3bp1kyQdOnRIKSkpioyMtLbx9/dXy5YtlZCQIElKSEhQQECAFYYkKTIyUm5ubtq6det5j52dna3MzEynBQAAXJ2KdYZo0KBBGjp0qHJzc9WpUydJ0po1a/Tss8+W6JOqn3vuOWVmZio8PFzlypVTXl6eJk6cqH79+kn640yVpELPRAoODrb6UlJSFBQU5NTv7u6uwMBAq6YokyZN0vjx40tsLgAAwHUVKxCNGDFCv/32mx5//HHl5ORIkry9vTVy5EiNGjWqxAb34YcfKi4uTgsXLlSDBg2UlJSkoUOHKjQ0VP379y+x4xRl1KhRGj58uLWemZmpsLCwy3pMAABQNooViBwOh1599VWNGTNG+/btk4+Pj+rUqSMvL68SHdyIESP03HPPqW/fvpL+uN3/8OHDmjRpkvr376+QkBBJUmpqqtM1TampqWrSpIkkKSQkRGlpaU77PXfunE6cOGFtXxQvL68Snw8AAHBNxbqGqECFChXUokUL3XjjjZclPPz+++9yc3MeYrly5ZSfny9JqlWrlkJCQrRmzRqrPzMzU1u3brWemB0REaH09HQlJiZaNWvXrlV+fr5atmxZ4mMGAABXnmKdISotvXr10sSJE1WjRg01aNBAO3fu1LRp0zRgwABJf5ypGjp0qF566SXVqVNHtWrV0pgxYxQaGqrevXtLkurVq6euXbtq0KBBmjt3rnJzcxUTE6O+fftyhxkAAJDk4oFo9uzZGjNmjB5//HGlpaUpNDRUjz76qMaOHWvVPPvsszp9+rQGDx6s9PR0tW3bVqtWrZK3t7dVExcXp5iYGHXu3Flubm7q06ePZs2aVRZTAgAALsilA9E111yjGTNmaMaMGeetcTgcmjBhgiZMmHDemsDAQC1cuPAyjBAAAFwN/tE1RAAAAFcDAhEAALA9AhEAALA9AhEAALA9AhEAALA9AhEAALA9AhEAALA9AhEAALA9AhEAALA9AhEAALA9AhEAALA9AhEAALA9AhEAALA9AhEAALA9AhEAALA9AhEAALA9AhEAALA9AhEAALA9AhEAALA9AhEAALA9AhEAALA9AhEAALA9AhEAALA9AhEAALA9AhEAALA9AhEAALA9AhEAALA9AhEAALA9AhEAALA9AhEAALA9AhEAALA9lw9EP//8sx544AFVqlRJPj4+atiwoXbs2GH1G2M0duxYVa1aVT4+PoqMjNSBAwec9nHixAn169dPfn5+CggI0MCBA5WVlVXaUwEAAC7KpQPRyZMn1aZNG3l4eOjzzz/Xd999p6lTp6pixYpWzeTJkzVr1izNnTtXW7dula+vr6KionT27Fmrpl+/ftq7d6/i4+O1cuVKbdy4UYMHDy6LKQEAABfkXtYDuJBXX31VYWFheuedd6y2WrVqWX82xmjGjBl6/vnndfvtt0uS3nvvPQUHB2vZsmXq27ev9u3bp1WrVmn79u1q3ry5JGn27Nnq3r27XnvtNYWGhpbupAAAgMtx6TNEK1asUPPmzXX33XcrKChIN910k9566y2r/9ChQ0pJSVFkZKTV5u/vr5YtWyohIUGSlJCQoICAACsMSVJkZKTc3Ny0devW8x47OztbmZmZTgsAALg6uXQg+vHHHzVnzhzVqVNHX3zxhYYMGaInn3xS7777riQpJSVFkhQcHOy0XXBwsNWXkpKioKAgp353d3cFBgZaNUWZNGmS/P39rSUsLKwkpwYAAFyISwei/Px8NW3aVC+//LJuuukmDR48WIMGDdLcuXMv+7FHjRqljIwMazl69OhlPyYAACgbLh2Iqlatqvr16zu11atXT0eOHJEkhYSESJJSU1OdalJTU62+kJAQpaWlOfWfO3dOJ06csGqK4uXlJT8/P6cFAABcnVw6ELVp00bJyclObfv371fNmjUl/XGBdUhIiNasWWP1Z2ZmauvWrYqIiJAkRUREKD09XYmJiVbN2rVrlZ+fr5YtW5bCLAAAgKtz6bvMhg0bptatW+vll1/WPffco23btmnevHmaN2+eJMnhcGjo0KF66aWXVKdOHdWqVUtjxoxRaGioevfuLemPM0pdu3a1PmrLzc1VTEyM+vbtyx1mAABAkosHohYtWmjp0qUaNWqUJkyYoFq1amnGjBnq16+fVfPss8/q9OnTGjx4sNLT09W2bVutWrVK3t7eVk1cXJxiYmLUuXNnubm5qU+fPpo1a1ZZTAkAALgglw5EktSzZ0/17NnzvP0Oh0MTJkzQhAkTzlsTGBiohQsXXo7hAQCAq4BLX0MEAABQGghEAADA9ghEAADA9ghEAADA9ghEAADA9ghEAADA9ghEAADA9ghEAADA9ghEAADA9ghEAADA9ghEAADA9ghEAADA9ghEAADA9ghEAADA9ghEAADA9ghEAADA9ghEAADA9ghEAADA9ghEAADA9ghEAADA9ghEAADA9ghEAADA9ghEAADA9ghEAADA9ghEAADA9ghEAADA9ghEAADA9ghEAADA9ghEAADA9ghEAADA9q6oQPTKK6/I4XBo6NChVtvZs2cVHR2tSpUqqUKFCurTp49SU1Odtjty5Ih69Oih8uXLKygoSCNGjNC5c+dKefQAAMBVXTGBaPv27XrzzTfVqFEjp/Zhw4bp008/1UcffaQNGzbo2LFjuvPOO63+vLw89ejRQzk5Odq8ebPeffddLViwQGPHji3tKQAAABd1RQSirKws9evXT2+99ZYqVqxotWdkZOjtt9/WtGnT1KlTJzVr1kzvvPOONm/erC1btkiSVq9ere+++07vv/++mjRpom7duunFF19UbGyscnJyympKAADAhVwRgSg6Olo9evRQZGSkU3tiYqJyc3Od2sPDw1WjRg0lJCRIkhISEtSwYUMFBwdbNVFRUcrMzNTevXvPe8zs7GxlZmY6LQAA4OrkXtYD+DuLFi3SN998o+3btxfqS0lJkaenpwICApzag4ODlZKSYtX8OQwV9Bf0nc+kSZM0fvz4fzh6AABwJXDpM0RHjx7VU089pbi4OHl7e5fqsUeNGqWMjAxrOXr0aKkeHwAAlB6XDkSJiYlKS0tT06ZN5e7uLnd3d23YsEGzZs2Su7u7goODlZOTo/T0dKftUlNTFRISIkkKCQkpdNdZwXpBTVG8vLzk5+fntAAAgKuTSweizp07a8+ePUpKSrKW5s2bq1+/ftafPTw8tGbNGmub5ORkHTlyRBEREZKkiIgI7dmzR2lpaVZNfHy8/Pz8VL9+/VKfEwAAcD0ufQ3RNddcoxtvvNGpzdfXV5UqVbLaBw4cqOHDhyswMFB+fn564oknFBERoVatWkmSunTpovr16+vBBx/U5MmTlZKSoueff17R0dHy8vIq9TkBAADX49KB6GJMnz5dbm5u6tOnj7KzsxUVFaU33njD6i9XrpxWrlypIUOGKCIiQr6+vurfv78mTJhQhqMGAACu5IoLROvXr3da9/b2VmxsrGJjY8+7Tc2aNfXZZ59d5pEBAIArlUtfQwQAAFAaCEQAAMD2CEQAAMD2CEQAAMD2CEQAAMD2CEQAAMD2CEQAAMD2CEQAAMD2CEQAAMD2CEQAAMD2CEQAAMD2CEQAAMD2CEQAAMD2CEQAAMD2CEQAAMD2CEQAAMD2CEQAAMD2CEQAAMD2CEQAAMD2CEQAAMD2CEQAAMD2CEQAAMD2CEQAAMD2CEQAAMD2CEQAAMD2CEQAAMD2CEQAAMD2CEQAAMD2CEQAAMD2CEQAAMD2CEQAAMD2XD4QTZo0SS1atNA111yjoKAg9e7dW8nJyU41Z8+eVXR0tCpVqqQKFSqoT58+Sk1Ndao5cuSIevToofLlyysoKEgjRozQuXPnSnMqAADARbl8INqwYYOio6O1ZcsWxcfHKzc3V126dNHp06etmmHDhunTTz/VRx99pA0bNujYsWO68847rf68vDz16NFDOTk52rx5s959910tWLBAY8eOLYspAQAAF+Ne1gP4O6tWrXJaX7BggYKCgpSYmKh27dopIyNDb7/9thYuXKhOnTpJkt555x3Vq1dPW7ZsUatWrbR69Wp99913+vLLLxUcHKwmTZroxRdf1MiRIzVu3Dh5enqWxdQAAICLcPkzRH+VkZEhSQoMDJQkJSYmKjc3V5GRkVZNeHi4atSooYSEBElSQkKCGjZsqODgYKsmKipKmZmZ2rt3b5HHyc7OVmZmptMCAACuTldUIMrPz9fQoUPVpk0b3XjjjZKklJQUeXp6KiAgwKk2ODhYKSkpVs2fw1BBf0FfUSZNmiR/f39rCQsLK+HZAAAAV3FFBaLo6Gh9++23WrRo0WU/1qhRo5SRkWEtR48evezHBAAAZcPlryEqEBMTo5UrV2rjxo2qXr261R4SEqKcnBylp6c7nSVKTU1VSEiIVbNt2zan/RXchVZQ81deXl7y8vIq4VkAAABX5PJniIwxiomJ0dKlS7V27VrVqlXLqb9Zs2by8PDQmjVrrLbk5GQdOXJEERERkqSIiAjt2bNHaWlpVk18fLz8/PxUv3790pkIAABwWS5/hig6OloLFy7U8uXLdc0111jX/Pj7+8vHx0f+/v4aOHCghg8frsDAQPn5+emJJ55QRESEWrVqJUnq0qWL6tevrwcffFCTJ09WSkqKnn/+eUVHR3MWCAAAuH4gmjNnjiSpQ4cOTu3vvPOOHn74YUnS9OnT5ebmpj59+ig7O1tRUVF64403rNpy5cpp5cqVGjJkiCIiIuTr66v+/ftrwoQJpTUNAADgwlw+EBlj/rbG29tbsbGxio2NPW9NzZo19dlnn5Xk0AAAwFXC5a8hAgAAuNwIRAAAwPYIRAAAwPYIRAAAwPYIRAAAwPYIRAAAwPYIRAAAwPYIRAAAwPYIRAAAwPYIRAAAwPYIRAAAwPYIRAAAwPYIRAAAwPYIRAAAwPYIRAAAwPYIRAAAwPYIRAAAwPYIRAAAwPYIRAAAwPYIRAAAwPYIRAAAwPYIRAAAwPYIRAAAwPYIRAAAwPYIRAAAwPYIRAAAwPYIRAAAwPYIRAAAwPYIRAAAwPYIRAAAwPZsFYhiY2N17bXXytvbWy1bttS2bdvKekgAAMAF2CYQLV68WMOHD9cLL7ygb775Ro0bN1ZUVJTS0tLKemgAAKCM2SYQTZs2TYMGDdIjjzyi+vXra+7cuSpfvrzmz59f1kMDAABlzBaBKCcnR4mJiYqMjLTa3NzcFBkZqYSEhDIcGQAAcAXuZT2A0vDrr78qLy9PwcHBTu3BwcH6/vvvi9wmOztb2dnZ1npGRoYkKTMz86KPm5d9phijxeVwKe9bcfF+uw7eb3vh/baXS32/C+qNMRess0UgKo5JkyZp/PjxhdrDwsLKYDT4p/xnP1bWQ0Ap4v22F95veynu+33q1Cn5+/uft98Wgahy5coqV66cUlNTndpTU1MVEhJS5DajRo3S8OHDrfX8/HydOHFClSpVksPhuKzjdSWZmZkKCwvT0aNH5efnV9bDwWXG+20vvN/2Ytf32xijU6dOKTQ09IJ1tghEnp6eatasmdasWaPevXtL+iPgrFmzRjExMUVu4+XlJS8vL6e2gICAyzxS1+Xn52erXyC74/22F95ve7Hj+32hM0MFbBGIJGn48OHq37+/mjdvrptvvlkzZszQ6dOn9cgjj5T10AAAQBmzTSC699579csvv2js2LFKSUlRkyZNtGrVqkIXWgMAAPuxTSCSpJiYmPN+RIaieXl56YUXXij08SGuTrzf9sL7bS+83xfmMH93HxoAAMBVzhYPZgQAALgQAhEAALA9AhEAALA9AhEAALA9AtFVauPGjerVq5dCQ0PlcDi0bNkyp/6srCzFxMSoevXq8vHxUf369TV37ty/3e9tt92mGjVqyNvbW1WrVtWDDz6oY8eOOdXs3r1bt9xyi7y9vRUWFqbJkyeX5NRQhDlz5qhRo0bWA9ciIiL0+eefW/3z5s1Thw4d5OfnJ4fDofT09Eva/2+//abq1asX2nb9+vVyOByFlpSUlBKaGf7OK6+8IofDoaFDhzq1JyQkqFOnTvL19ZWfn5/atWunM2f+/vu4FixYoEaNGsnb21tBQUGKjo526uf323X8/PPPeuCBB1SpUiX5+PioYcOG2rFjh9X/ySefqEuXLtY3LCQlJZXdYK8ABKKr1OnTp9W4cWPFxsYW2T98+HCtWrVK77//vvbt26ehQ4cqJiZGK1asuOB+O3bsqA8//FDJyclasmSJfvjhB911111Wf2Zmprp06aKaNWsqMTFRU6ZM0bhx4zRv3rwSnR+cVa9eXa+88ooSExO1Y8cOderUSbfffrv27t0rSfr999/VtWtX/c///E+x9j9w4EA1atTovP3Jyck6fvy4tQQFBRXrOLg027dv15tvvlnovUlISFDXrl3VpUsXbdu2Tdu3b1dMTIzc3C78V/60adM0evRoPffcc9q7d6++/PJLRUVFWf38fruOkydPqk2bNvLw8NDnn3+u7777TlOnTlXFihWtmtOnT6tt27Z69dVXL3q/DodDP/3002UY8RXA4KonySxdutSprUGDBmbChAlObU2bNjWjR4++pH0vX77cOBwOk5OTY4wx5o033jAVK1Y02dnZVs3IkSNN3bp1izd4FFvFihXNv//9b6e2devWGUnm5MmTF72fN954w7Rv396sWbOm0LbF2R9KxqlTp0ydOnVMfHy8ad++vXnqqaesvpYtW5rnn3/+kvZ34sQJ4+PjY7788svz1vD77TpGjhxp2rZte1G1hw4dMpLMzp07/7ZWkjl06NA/G9wVijNENtW6dWutWLFCP//8s4wxWrdunfbv368uXbpc9D5OnDihuLg4tW7dWh4eHpL++J9pu3bt5OnpadVFRUUpOTlZJ0+eLPF5oLC8vDwtWrRIp0+fVkRExD/a13fffacJEybovffeu+DZhSZNmqhq1aq69dZbtWnTpn90TFyc6Oho9ejRQ5GRkU7taWlp2rp1q4KCgtS6dWsFBwerffv2+vrrry+4v/j4eOXn5+vnn39WvXr1VL16dd1zzz06evSoVcPvt+tYsWKFmjdvrrvvvltBQUG66aab9NZbb5X1sK5oBCKbmj17turXr6/q1avL09NTXbt2VWxsrNq1a/e3244cOVK+vr6qVKmSjhw5ouXLl1t9KSkphb4OpWCd60ourz179qhChQry8vLSY489pqVLl6p+/frF3l92drbuu+8+TZkyRTVq1CiypmrVqpo7d66WLFmiJUuWKCwsTB06dNA333xT7OPi7y1atEjffPONJk2aVKjvxx9/lCSNGzdOgwYN0qpVq9S0aVN17txZBw4cOO8+f/zxR+Xn5+vll1/WjBkz9PHHH+vEiRO69dZblZOTI4nfb1fy448/as6cOapTp46++OILDRkyRE8++aTefffdsh7aFYtAZFOzZ8/Wli1btGLFCiUmJmrq1KmKjo7Wl19+KUl67LHHVKFCBWv5sxEjRmjnzp1avXq1ypUrp4ceekiGB56Xubp16yopKUlbt27VkCFD1L9/f3333XcXtW23bt2s97pBgwaSpFGjRqlevXp64IEHLnjMRx99VM2aNVPr1q01f/58tW7dWtOnTy+ROaGwo0eP6qmnnlJcXJy8vb0L9efn50uSHn30UT3yyCO66aabNH36dNWtW1fz58+XVPT7nZ+fr9zcXM2aNUtRUVFq1aqVPvjgAx04cEDr1q0rvQniouTn56tp06Z6+eWXddNNN2nw4MEaNGjQRd0c82d//lko+Lu+QYMGhX4+7MBW32WGP5w5c0b/8z//o6VLl6pHjx6SpEaNGikpKUmvvfaaIiMjNWHCBD3zzDNFbl+5cmVVrlxZN9xwg+rVq6ewsDBt2bJFERERCgkJUWpqqlN9wXpISMjlnZjNeXp6qnbt2pKkZs2aafv27Zo5c6befPPNv9323//+t3UHUsHHn2vXrtWePXv08ccfS5IVeitXrqzRo0dr/PjxRe7r5ptv/tuPZ1B8iYmJSktLU9OmTa22vLw8bdy4Ua+//rqSk5MlqdDZwXr16unIkSOSin6/q1atWmi7KlWqqHLlytZ2/H67jqpVqxb5Hi9ZsuSS9vPnnwVJqlOnjj777DNVq1ZN0v//+bADApEN5ebmKjc3t9A1IeXKlbP+dxkUFHRRdwoV1GdnZ0uSIiIiNHr0aOXm5lq/SPHx8apbt67T3Q+4/PLz86335e8U/OX3Z0uWLHH6i3L79u0aMGCAvvrqK11//fXn3VdSUpL1jytKXufOnbVnzx6ntkceeUTh4eEaOXKkrrvuOoWGhlrBqMD+/fvVrVs3SUW/323atJH0xx2D1atXl/THdYK//vqratasKYnfb1fSpk2bIt/jgvfqYhX1s1CzZk1de+21/2R4V6Yyvqgbl8mpU6fMzp07zc6dO40kM23aNLNz505z+PBhY4wx7du3Nw0aNDDr1q0zP/74o3nnnXeMt7e3eeONN867zy1btpjZs2ebnTt3mp9++smsWbPGtG7d2lx//fXm7Nmzxhhj0tPTTXBwsHnwwQfNt99+axYtWmTKly9v3nzzzVKZt10999xzZsOGDebQoUNm9+7d5rnnnjMOh8OsXr3aGGPM8ePHzc6dO81bb71lJJmNGzeanTt3mt9+++2ij1HUHWXTp083y5YtMwcOHDB79uwxTz31lHFzc7vgnUooeX+9y2z69OnGz8/PfPTRR+bAgQPm+eefN97e3ubgwYMX3M/tt99uGjRoYDZt2mT27NljevbsaerXr2/dRcrvt+vYtm2bcXd3NxMnTjQHDhwwcXFxpnz58ub999+3an777Tezc+dO85///MdIMosWLTI7d+40x48fP+9+ZeO7zAhEV6mCf7z+uvTv398Y88c/kA8//LAJDQ013t7epm7dumbq1KkmPz//vPvcvXu36dixowkMDDReXl7m2muvNY899pj573//61S3a9cu07ZtW+Pl5WWqVatmXnnllcs5VRhjBgwYYGrWrGk8PT1NlSpVTOfOna0wZIwxL7zwQpE/D++8885FH6OoQPTqq6+a66+/3nh7e5vAwEDToUMHs3bt2hKcGS7GXwORMcZMmjTJVK9e3ZQvX95ERESYr7766m/3k5GRYQYMGGACAgJMYGCgueOOO8yRI0ecavj9dh2ffvqpufHGG42Xl5cJDw838+bNc+p/5513ivy9f+GFF867TzsHIocxXA0LAADsjbvMAACA7RGIAACA7RGIAACA7RGIAACA7RGIAACA7RGIAACA7RGIAACA7RGIAACA7RGIAJSZhIQElStXzvqS4dJ28OBBDRgwQDVq1JCXl5eqVaumzp07Ky4uTufOnSuTMQEoGwQiAGXm7bff1hNPPKGNGzfq2LFjpXrsbdu2qWnTptq3b59iY2P17bffav369frXv/6lOXPmaO/evefdNjc3txRHCqA0EIgAlImsrCwtXrxYQ4YMUY8ePbRgwQKn/hUrVqhOnTry9vZWx44d9e6778rhcCg9Pd2q+frrr3XLLbfIx8dHYWFhevLJJ3X69Om/PbYxRg8//LBuuOEGbdq0Sb169VKdOnVUp04d3Xffffr666/VqFEjSdJPP/0kh8OhxYsXq3379vL29lZcXJzy8/M1YcIEVa9eXV5eXmrSpIlWrVplHWP9+vWFxpuUlCSHw6GffvpJkrRgwQIFBARo2bJl1lyjoqJ09OjRYr+uAIqHQASgTHz44YcKDw9X3bp19cADD2j+/Pkq+GrFQ4cO6a677lLv3r21a9cuPfrooxo9erTT9j/88IO6du2qPn36aPfu3Vq8eLG+/vprxcTE/O2xk5KStG/fPj3zzDNycyv6r0GHw+G0/txzz+mpp57Svn37FBUVpZkzZ2rq1Kl67bXXtHv3bkVFRem2227TgQMHLul1+P333zVx4kS999572rRpk9LT09W3b99L2geAElC23y0LwK5at25tZsyYYYwxJjc311SuXNmsW7fOGGPMyJEjzY033uhUP3r0aCPJnDx50hhjzMCBA83gwYOdar766ivj5uZmzpw5c8FjL1q0yEgy33zzjdWWmppqfH19rSU2NtYYY8yhQ4eMJGusBUJDQ83EiROd2lq0aGEef/xxY4wx69atcxqvMcbs3LnT6dvEC76NfMuWLVbNvn37jCSzdevWC84BQMniDBGAUpecnKxt27bpvvvukyS5u7vr3nvv1dtvv231t2jRwmmbm2++2Wl9165dWrBggSpUqGAtUVFRys/P16FDhy55TJUqVVJSUpKSkpIUEBCgnJwcp/7mzZtbf87MzNSxY8fUpk0bp5o2bdpo3759l3Rcd3d3p7mGh4crICDgkvcD4J9xL+sBALCft99+W+fOnVNoaKjVZoyRl5eXXn/99YvaR1ZWlh599FE9+eSThfpq1KhxwW3r1Kkj6Y/gddNNN0mSypUrp9q1a0v6I6T8la+v70WNq0DBR3Hm/z4GlLgYG3BlnCECUKrOnTun9957T1OnTrXOyCQlJWnXrl0KDQ3VBx98oLp162rHjh1O223fvt1pvWnTpvruu+9Uu3btQounp+cFx3DTTTcpPDxcr732mvLz8y95Dn5+fgoNDdWmTZuc2jdt2qT69etLkqpUqSJJOn78uNWflJRUaF/nzp1zmmtycrLS09NVr169Sx4XgH+grD+zA2AvS5cuNZ6eniY9Pb1Q37PPPmuaN29ufvzxR+Ph4WGeffZZk5ycbBYvXmyqV69uJFnb7dq1y/j4+Jjo6Gizc+dOs3//frNs2TITHR19UeNISEgwFSpUMK1atTLLly83+/fvN3v37jVz5swx5cuXN7NmzTLG/P9riHbu3Om0/fTp042fn59ZtGiR+f77783IkSONh4eH2b9/vzHGmJycHBMWFmbuvvtus3//frNy5UpTt27dQtcQeXh4mJtvvtls2bLF7Nixw7Rq1cq0atWqmK8ugOIiEAEoVT179jTdu3cvsm/r1q1Gktm1a5dZvny5qV27tvHy8jIdOnQwc+bMMZKcLpjetm2bufXWW02FChWMr6+vadSoUaELnS8kOTnZ9O/f31SvXt24u7sbf39/065dO/Pmm2+a3NxcY8z5A1FeXp4ZN26cqVatmvHw8DCNGzc2n3/+uVPN119/bRo2bGi8vb3NLbfcYj766KNCgcjf398sWbLEXHfddcbLy8tERkaaw4cPX/QcAJQMhzF/+oAbAFzUxIkTNXfu3KvqGT0LFizQ0KFDnZ5VBKBscFE1AJf0xhtvqEWLFqpUqZI2bdqkKVOmXNQzhgCgOAhEAFzSgQMH9NJLL+nEiROqUaOGnn76aY0aNeqitv3qq6/UrVu38/ZnZWWV1DABXCX4yAzAVefMmTP6+eefz9tfcHs9ABQgEAEAANvjOUQAAMD2CEQAAMD2CEQAAMD2CEQAAMD2CEQAAMD2CEQAAMD2CEQAAMD2CEQAAMD2/h9fOm+T+2TinAAAAABJRU5ErkJggg==",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.countplot(data=data, x= 'Age_Group')\n",
    "plt.title('Age Group Countplot');"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 380,
   "metadata": {},
   "outputs": [],
   "source": [
    "data_1=data.copy()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 381,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 6007 entries, 0 to 6006\n",
      "Data columns (total 32 columns):\n",
      " #   Column                       Non-Null Count  Dtype   \n",
      "---  ------                       --------------  -----   \n",
      " 0   Customer_ID                  6007 non-null   object  \n",
      " 1   Gender                       6007 non-null   object  \n",
      " 2   Age                          6007 non-null   int64   \n",
      " 3   Married                      6007 non-null   object  \n",
      " 4   State                        6007 non-null   object  \n",
      " 5   Number_of_Referrals          6007 non-null   int64   \n",
      " 6   Tenure_in_Months             6007 non-null   int64   \n",
      " 7   Value_Deal                   6007 non-null   object  \n",
      " 8   Phone_Service                6007 non-null   object  \n",
      " 9   Multiple_Lines               6007 non-null   object  \n",
      " 10  Internet_Service             6007 non-null   object  \n",
      " 11  Internet_Type                6007 non-null   object  \n",
      " 12  Online_Security              6007 non-null   object  \n",
      " 13  Online_Backup                6007 non-null   object  \n",
      " 14  Device_Protection_Plan       6007 non-null   object  \n",
      " 15  Premium_Support              6007 non-null   object  \n",
      " 16  Streaming_TV                 6007 non-null   object  \n",
      " 17  Streaming_Movies             6007 non-null   object  \n",
      " 18  Streaming_Music              6007 non-null   object  \n",
      " 19  Unlimited_Data               6007 non-null   object  \n",
      " 20  Contract                     6007 non-null   object  \n",
      " 21  Paperless_Billing            6007 non-null   object  \n",
      " 22  Payment_Method               6007 non-null   object  \n",
      " 23  Monthly_Charge               6007 non-null   float64 \n",
      " 24  Total_Refunds                6007 non-null   float64 \n",
      " 25  Total_Extra_Data_Charges     6007 non-null   int64   \n",
      " 26  Total_Long_Distance_Charges  6007 non-null   float64 \n",
      " 27  Total_Revenue                6007 non-null   float64 \n",
      " 28  Customer_Status              6007 non-null   int64   \n",
      " 29  Age_Group                    6007 non-null   category\n",
      " 30  Tenure_Category              6007 non-null   category\n",
      " 31  Charge_Category              5906 non-null   category\n",
      "dtypes: category(3), float64(4), int64(5), object(20)\n",
      "memory usage: 1.3+ MB\n"
     ]
    }
   ],
   "source": [
    "data_1.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 382,
   "metadata": {},
   "outputs": [],
   "source": [
    "data_1.drop(columns =['Age','Tenure_in_Months','Monthly_Charge'], inplace= True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 383,
   "metadata": {},
   "outputs": [],
   "source": [
    "#Drop the customer_ID colum\n",
    "data_1.drop(columns = ['Customer_ID'], inplace = True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 384,
   "metadata": {},
   "outputs": [],
   "source": [
    "#Encoding of categorical features\n",
    "label_encoders = {}\n",
    "\n",
    "for col in data_1.select_dtypes(include =[\"category\", \"object\"]).columns.to_list():\n",
    "    le = LabelEncoder()\n",
    "    data_1[col] = le.fit_transform(data[col])\n",
    "    label_encoders[col] = le"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 385,
   "metadata": {},
   "outputs": [],
   "source": [
    "# #Define target and feature columns\n",
    "y = data_1['Customer_Status']\n",
    "X = data_1.drop(columns=['Customer_Status']).copy()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 388,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Split data\n",
    "X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.2, random_state=42)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 389,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Standardize features\n",
    "scaler = StandardScaler()\n",
    "X_train = scaler.fit_transform(X_train)\n",
    "X_test = scaler.transform(X_test)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Modeling"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 400,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Initialize classifiers\n",
    "classifiers = {\n",
    "    'Logistic Regression': LogisticRegression(),\n",
    "    'Random Forest': RandomForestClassifier(),\n",
    "    'Support Vector Classifier': SVC(),\n",
    "    'K-Nearest Neighbors': KNeighborsClassifier(),\n",
    "    'Decision Tree': DecisionTreeClassifier()\n",
    "}"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 401,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Train classifiers and evaluate\n",
    "results = {}\n",
    "\n",
    "for name, clf in classifiers.items():\n",
    "    # Train the classifier\n",
    "    clf.fit(X_train, y_train)\n",
    "    \n",
    "    # Make predictions\n",
    "    y_pred = clf.predict(X_test)\n",
    "    \n",
    "    # Calculate metrics\n",
    "    accuracy = accuracy_score(y_test, y_pred)\n",
    "    conf_matrix = confusion_matrix(y_test, y_pred)\n",
    "    class_report = classification_report(y_test, y_pred)\n",
    "    \n",
    "    results[name] = {\n",
    "        'Accuracy': accuracy,\n",
    "        'Confusion Matrix': conf_matrix,\n",
    "        'Classification Report': class_report\n",
    "    }"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 402,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "--- Logistic Regression ---\n",
      "Accuracy: 0.8153\n",
      "Confusion Matrix:\n",
      "[[738  78]\n",
      " [144 242]]\n",
      "Classification Report:\n",
      "              precision    recall  f1-score   support\n",
      "\n",
      "           0       0.84      0.90      0.87       816\n",
      "           1       0.76      0.63      0.69       386\n",
      "\n",
      "    accuracy                           0.82      1202\n",
      "   macro avg       0.80      0.77      0.78      1202\n",
      "weighted avg       0.81      0.82      0.81      1202\n",
      "\n",
      "\n",
      "\n",
      "--- Random Forest ---\n",
      "Accuracy: 0.8469\n",
      "Confusion Matrix:\n",
      "[[774  42]\n",
      " [142 244]]\n",
      "Classification Report:\n",
      "              precision    recall  f1-score   support\n",
      "\n",
      "           0       0.84      0.95      0.89       816\n",
      "           1       0.85      0.63      0.73       386\n",
      "\n",
      "    accuracy                           0.85      1202\n",
      "   macro avg       0.85      0.79      0.81      1202\n",
      "weighted avg       0.85      0.85      0.84      1202\n",
      "\n",
      "\n",
      "\n",
      "--- Support Vector Classifier ---\n",
      "Accuracy: 0.8295\n",
      "Confusion Matrix:\n",
      "[[755  61]\n",
      " [144 242]]\n",
      "Classification Report:\n",
      "              precision    recall  f1-score   support\n",
      "\n",
      "           0       0.84      0.93      0.88       816\n",
      "           1       0.80      0.63      0.70       386\n",
      "\n",
      "    accuracy                           0.83      1202\n",
      "   macro avg       0.82      0.78      0.79      1202\n",
      "weighted avg       0.83      0.83      0.82      1202\n",
      "\n",
      "\n",
      "\n",
      "--- K-Nearest Neighbors ---\n",
      "Accuracy: 0.7795\n",
      "Confusion Matrix:\n",
      "[[703 113]\n",
      " [152 234]]\n",
      "Classification Report:\n",
      "              precision    recall  f1-score   support\n",
      "\n",
      "           0       0.82      0.86      0.84       816\n",
      "           1       0.67      0.61      0.64       386\n",
      "\n",
      "    accuracy                           0.78      1202\n",
      "   macro avg       0.75      0.73      0.74      1202\n",
      "weighted avg       0.77      0.78      0.78      1202\n",
      "\n",
      "\n",
      "\n",
      "--- Decision Tree ---\n",
      "Accuracy: 0.7679\n",
      "Confusion Matrix:\n",
      "[[686 130]\n",
      " [149 237]]\n",
      "Classification Report:\n",
      "              precision    recall  f1-score   support\n",
      "\n",
      "           0       0.82      0.84      0.83       816\n",
      "           1       0.65      0.61      0.63       386\n",
      "\n",
      "    accuracy                           0.77      1202\n",
      "   macro avg       0.73      0.73      0.73      1202\n",
      "weighted avg       0.77      0.77      0.77      1202\n",
      "\n",
      "\n",
      "\n"
     ]
    }
   ],
   "source": [
    "for name, metrics in results.items():\n",
    "    print(f\"--- {name} ---\")\n",
    "    print(f\"Accuracy: {metrics['Accuracy']:.4f}\")\n",
    "    print(\"Confusion Matrix:\")\n",
    "    print(metrics['Confusion Matrix'])\n",
    "    print(\"Classification Report:\")\n",
    "    print(metrics['Classification Report'])\n",
    "    print(\"\\n\")\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Random forest has the best accuracy of 84.69"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Hyperparameter Tuning\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 427,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Fitting 5 folds for each of 162 candidates, totalling 810 fits\n"
     ]
    }
   ],
   "source": [
    "# Random Forest Model\n",
    "rf = RandomForestClassifier()\n",
    "\n",
    "\n",
    "param_grid = {\n",
    "    'n_estimators': [100, 150, 200],\n",
    "    'max_depth': [10, 20, 30],\n",
    "    'min_samples_split': [2, 4, 6],\n",
    "    'min_samples_leaf': [1, 2, 3],\n",
    "    'max_features': ['sqrt', 'log2']\n",
    "}\n",
    "\n",
    "grid_search = GridSearchCV(estimator=rf, param_grid=param_grid, \n",
    "                           cv=5, scoring='accuracy', \n",
    "                           verbose=2, n_jobs=-1)\n",
    "grid_search.fit(X_train, y_train)\n",
    "\n",
    "best_rf = grid_search.best_estimator_"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 428,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Accuracy of Best Model: 0.8453\n",
      "Confusion Matrix [[778  38]\n",
      " [148 238]]\n",
      "Classification Report               precision    recall  f1-score   support\n",
      "\n",
      "           0       0.84      0.95      0.89       816\n",
      "           1       0.86      0.62      0.72       386\n",
      "\n",
      "    accuracy                           0.85      1202\n",
      "   macro avg       0.85      0.79      0.81      1202\n",
      "weighted avg       0.85      0.85      0.84      1202\n",
      "\n"
     ]
    }
   ],
   "source": [
    "# Model Evaluation\n",
    "y_pred = best_rf.predict(X_test)\n",
    "accuracy = accuracy_score(y_test, y_pred)\n",
    "print(f\"Accuracy of Best Model: {accuracy:.4f}\")\n",
    "print(f\"Confusion Matrix\" ,confusion_matrix(y_test, y_pred))  \n",
    "print(f\"Classification Report\",classification_report(y_test, y_pred))      "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Feature Importances\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 429,
   "metadata": {},
   "outputs": [],
   "source": [
    "rf_model =RandomForestClassifier()\n",
    "rf_model.fit(X_train, y_train)\n",
    "importances = rf_model.feature_importances_\n",
    "\n",
    "indices = np.argsort(importances)[::-1]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 430,
   "metadata": {},
   "outputs": [
    {
     "data": {
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",
      "text/plain": [
       "<Figure size 1500x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Plot the feature importances\n",
    "\n",
    "plt.figure(figsize=(15, 6))\n",
    "sns.barplot(x=importances[indices], y=X.columns[indices])\n",
    "plt.title('Feature Importances')\n",
    "plt.xlabel('Relative Importance')\n",
    "plt.ylabel('Feature Names');"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 431,
   "metadata": {},
   "outputs": [],
   "source": [
    "feature_names = X.columns\n",
    "\n",
    "# Create a DataFrame with feature names and their importances\n",
    "importance_df = pd.DataFrame({\n",
    "    'Feature': feature_names,\n",
    "    'Importance': importances\n",
    "})\n",
    "\n",
    "# Sort the DataFrame by importance in descending order\n",
    "importance_df = importance_df.sort_values(by='Importance', ascending=False).reset_index(drop=True)\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 432,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0                  Total_Revenue\n",
       "1                       Contract\n",
       "2    Total_Long_Distance_Charges\n",
       "3                          State\n",
       "4            Number_of_Referrals\n",
       "5                      Age_Group\n",
       "6                  Internet_Type\n",
       "Name: Feature, dtype: object"
      ]
     },
     "execution_count": 432,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Top 7 important features\n",
    "importance_df['Feature'][:7]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Save Model"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 433,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['model.pkl']"
      ]
     },
     "execution_count": 433,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#joblib.dump(best_rf, \"model.pkl\")"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": ".venv",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.10.11"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}