exploration.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Prosper Loan Data Exploration\n",
    "## by Dina El-kholy\n",
    "\n",
    "## Preliminary Wrangling\n",
    "\n",
    "> This dataset contains information about 113,937 loans represented by 81 features such as the loan amount, the monthly income, the employment status, and the loan status. More information about the dataset features can be found [here](https://docs.google.com/spreadsheets/d/1gDyi_L4UvIrLTEC6Wri5nbaMmkGmLQBk-Yx3z0XDEtI/edit#gid=0)."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "# import all packages and set plots to be embedded inline\n",
    "import numpy as np\n",
    "import pandas as pd\n",
    "from sklearn import preprocessing\n",
    "import matplotlib.pyplot as plt\n",
    "import seaborn as sb\n",
    "from scipy.stats import zscore\n",
    "%matplotlib inline"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "# load in the dataset into a pandas dataframe, print statistics\n",
    "loans = pd.read_csv('prosperLoanData.csv')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(113937, 81)"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "loans.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>ListingKey</th>\n",
       "      <th>ListingNumber</th>\n",
       "      <th>ListingCreationDate</th>\n",
       "      <th>CreditGrade</th>\n",
       "      <th>Term</th>\n",
       "      <th>LoanStatus</th>\n",
       "      <th>ClosedDate</th>\n",
       "      <th>BorrowerAPR</th>\n",
       "      <th>BorrowerRate</th>\n",
       "      <th>LenderYield</th>\n",
       "      <th>...</th>\n",
       "      <th>LP_ServiceFees</th>\n",
       "      <th>LP_CollectionFees</th>\n",
       "      <th>LP_GrossPrincipalLoss</th>\n",
       "      <th>LP_NetPrincipalLoss</th>\n",
       "      <th>LP_NonPrincipalRecoverypayments</th>\n",
       "      <th>PercentFunded</th>\n",
       "      <th>Recommendations</th>\n",
       "      <th>InvestmentFromFriendsCount</th>\n",
       "      <th>InvestmentFromFriendsAmount</th>\n",
       "      <th>Investors</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1021339766868145413AB3B</td>\n",
       "      <td>193129</td>\n",
       "      <td>2007-08-26 19:09:29.263000000</td>\n",
       "      <td>C</td>\n",
       "      <td>36</td>\n",
       "      <td>Completed</td>\n",
       "      <td>2009-08-14 00:00:00</td>\n",
       "      <td>0.16516</td>\n",
       "      <td>0.158</td>\n",
       "      <td>0.138</td>\n",
       "      <td>...</td>\n",
       "      <td>-133.18</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>258</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>10273602499503308B223C1</td>\n",
       "      <td>1209647</td>\n",
       "      <td>2014-02-27 08:28:07.900000000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>36</td>\n",
       "      <td>Current</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.12016</td>\n",
       "      <td>0.092</td>\n",
       "      <td>0.082</td>\n",
       "      <td>...</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>2 rows × 81 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                ListingKey  ListingNumber            ListingCreationDate  \\\n",
       "0  1021339766868145413AB3B         193129  2007-08-26 19:09:29.263000000   \n",
       "1  10273602499503308B223C1        1209647  2014-02-27 08:28:07.900000000   \n",
       "\n",
       "  CreditGrade  Term LoanStatus           ClosedDate  BorrowerAPR  \\\n",
       "0           C    36  Completed  2009-08-14 00:00:00      0.16516   \n",
       "1         NaN    36    Current                  NaN      0.12016   \n",
       "\n",
       "   BorrowerRate  LenderYield  ...  LP_ServiceFees  LP_CollectionFees  \\\n",
       "0         0.158        0.138  ...         -133.18                0.0   \n",
       "1         0.092        0.082  ...            0.00                0.0   \n",
       "\n",
       "   LP_GrossPrincipalLoss  LP_NetPrincipalLoss LP_NonPrincipalRecoverypayments  \\\n",
       "0                    0.0                  0.0                             0.0   \n",
       "1                    0.0                  0.0                             0.0   \n",
       "\n",
       "   PercentFunded  Recommendations InvestmentFromFriendsCount  \\\n",
       "0            1.0                0                          0   \n",
       "1            1.0                0                          0   \n",
       "\n",
       "  InvestmentFromFriendsAmount Investors  \n",
       "0                         0.0       258  \n",
       "1                         0.0         1  \n",
       "\n",
       "[2 rows x 81 columns]"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "loans.head(2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 113937 entries, 0 to 113936\n",
      "Data columns (total 81 columns):\n",
      " #   Column                               Non-Null Count   Dtype  \n",
      "---  ------                               --------------   -----  \n",
      " 0   ListingKey                           113937 non-null  object \n",
      " 1   ListingNumber                        113937 non-null  int64  \n",
      " 2   ListingCreationDate                  113937 non-null  object \n",
      " 3   CreditGrade                          28953 non-null   object \n",
      " 4   Term                                 113937 non-null  int64  \n",
      " 5   LoanStatus                           113937 non-null  object \n",
      " 6   ClosedDate                           55089 non-null   object \n",
      " 7   BorrowerAPR                          113912 non-null  float64\n",
      " 8   BorrowerRate                         113937 non-null  float64\n",
      " 9   LenderYield                          113937 non-null  float64\n",
      " 10  EstimatedEffectiveYield              84853 non-null   float64\n",
      " 11  EstimatedLoss                        84853 non-null   float64\n",
      " 12  EstimatedReturn                      84853 non-null   float64\n",
      " 13  ProsperRating (numeric)              84853 non-null   float64\n",
      " 14  ProsperRating (Alpha)                84853 non-null   object \n",
      " 15  ProsperScore                         84853 non-null   float64\n",
      " 16  ListingCategory (numeric)            113937 non-null  int64  \n",
      " 17  BorrowerState                        108422 non-null  object \n",
      " 18  Occupation                           110349 non-null  object \n",
      " 19  EmploymentStatus                     111682 non-null  object \n",
      " 20  EmploymentStatusDuration             106312 non-null  float64\n",
      " 21  IsBorrowerHomeowner                  113937 non-null  bool   \n",
      " 22  CurrentlyInGroup                     113937 non-null  bool   \n",
      " 23  GroupKey                             13341 non-null   object \n",
      " 24  DateCreditPulled                     113937 non-null  object \n",
      " 25  CreditScoreRangeLower                113346 non-null  float64\n",
      " 26  CreditScoreRangeUpper                113346 non-null  float64\n",
      " 27  FirstRecordedCreditLine              113240 non-null  object \n",
      " 28  CurrentCreditLines                   106333 non-null  float64\n",
      " 29  OpenCreditLines                      106333 non-null  float64\n",
      " 30  TotalCreditLinespast7years           113240 non-null  float64\n",
      " 31  OpenRevolvingAccounts                113937 non-null  int64  \n",
      " 32  OpenRevolvingMonthlyPayment          113937 non-null  float64\n",
      " 33  InquiriesLast6Months                 113240 non-null  float64\n",
      " 34  TotalInquiries                       112778 non-null  float64\n",
      " 35  CurrentDelinquencies                 113240 non-null  float64\n",
      " 36  AmountDelinquent                     106315 non-null  float64\n",
      " 37  DelinquenciesLast7Years              112947 non-null  float64\n",
      " 38  PublicRecordsLast10Years             113240 non-null  float64\n",
      " 39  PublicRecordsLast12Months            106333 non-null  float64\n",
      " 40  RevolvingCreditBalance               106333 non-null  float64\n",
      " 41  BankcardUtilization                  106333 non-null  float64\n",
      " 42  AvailableBankcardCredit              106393 non-null  float64\n",
      " 43  TotalTrades                          106393 non-null  float64\n",
      " 44  TradesNeverDelinquent (percentage)   106393 non-null  float64\n",
      " 45  TradesOpenedLast6Months              106393 non-null  float64\n",
      " 46  DebtToIncomeRatio                    105383 non-null  float64\n",
      " 47  IncomeRange                          113937 non-null  object \n",
      " 48  IncomeVerifiable                     113937 non-null  bool   \n",
      " 49  StatedMonthlyIncome                  113937 non-null  float64\n",
      " 50  LoanKey                              113937 non-null  object \n",
      " 51  TotalProsperLoans                    22085 non-null   float64\n",
      " 52  TotalProsperPaymentsBilled           22085 non-null   float64\n",
      " 53  OnTimeProsperPayments                22085 non-null   float64\n",
      " 54  ProsperPaymentsLessThanOneMonthLate  22085 non-null   float64\n",
      " 55  ProsperPaymentsOneMonthPlusLate      22085 non-null   float64\n",
      " 56  ProsperPrincipalBorrowed             22085 non-null   float64\n",
      " 57  ProsperPrincipalOutstanding          22085 non-null   float64\n",
      " 58  ScorexChangeAtTimeOfListing          18928 non-null   float64\n",
      " 59  LoanCurrentDaysDelinquent            113937 non-null  int64  \n",
      " 60  LoanFirstDefaultedCycleNumber        16952 non-null   float64\n",
      " 61  LoanMonthsSinceOrigination           113937 non-null  int64  \n",
      " 62  LoanNumber                           113937 non-null  int64  \n",
      " 63  LoanOriginalAmount                   113937 non-null  int64  \n",
      " 64  LoanOriginationDate                  113937 non-null  object \n",
      " 65  LoanOriginationQuarter               113937 non-null  object \n",
      " 66  MemberKey                            113937 non-null  object \n",
      " 67  MonthlyLoanPayment                   113937 non-null  float64\n",
      " 68  LP_CustomerPayments                  113937 non-null  float64\n",
      " 69  LP_CustomerPrincipalPayments         113937 non-null  float64\n",
      " 70  LP_InterestandFees                   113937 non-null  float64\n",
      " 71  LP_ServiceFees                       113937 non-null  float64\n",
      " 72  LP_CollectionFees                    113937 non-null  float64\n",
      " 73  LP_GrossPrincipalLoss                113937 non-null  float64\n",
      " 74  LP_NetPrincipalLoss                  113937 non-null  float64\n",
      " 75  LP_NonPrincipalRecoverypayments      113937 non-null  float64\n",
      " 76  PercentFunded                        113937 non-null  float64\n",
      " 77  Recommendations                      113937 non-null  int64  \n",
      " 78  InvestmentFromFriendsCount           113937 non-null  int64  \n",
      " 79  InvestmentFromFriendsAmount          113937 non-null  float64\n",
      " 80  Investors                            113937 non-null  int64  \n",
      "dtypes: bool(3), float64(50), int64(11), object(17)\n",
      "memory usage: 68.1+ MB\n"
     ]
    }
   ],
   "source": [
    "loans.info()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "> Many of the features are not useful for the analysis; so, the irrelevant columns should be dropped."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>LoanStatus</th>\n",
       "      <th>LoanOriginalAmount</th>\n",
       "      <th>StatedMonthlyIncome</th>\n",
       "      <th>DebtToIncomeRatio</th>\n",
       "      <th>Term</th>\n",
       "      <th>EmploymentStatus</th>\n",
       "      <th>EmploymentStatusDuration</th>\n",
       "      <th>Occupation</th>\n",
       "      <th>ListingCategory (numeric)</th>\n",
       "      <th>TotalProsperLoans</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Completed</td>\n",
       "      <td>9425</td>\n",
       "      <td>3083.333333</td>\n",
       "      <td>0.17</td>\n",
       "      <td>36</td>\n",
       "      <td>Self-employed</td>\n",
       "      <td>2.0</td>\n",
       "      <td>Other</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Current</td>\n",
       "      <td>10000</td>\n",
       "      <td>6125.000000</td>\n",
       "      <td>0.18</td>\n",
       "      <td>36</td>\n",
       "      <td>Employed</td>\n",
       "      <td>44.0</td>\n",
       "      <td>Professional</td>\n",
       "      <td>2</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  LoanStatus  LoanOriginalAmount  StatedMonthlyIncome  DebtToIncomeRatio  \\\n",
       "0  Completed                9425          3083.333333               0.17   \n",
       "1    Current               10000          6125.000000               0.18   \n",
       "\n",
       "   Term EmploymentStatus  EmploymentStatusDuration    Occupation  \\\n",
       "0    36    Self-employed                       2.0         Other   \n",
       "1    36         Employed                      44.0  Professional   \n",
       "\n",
       "   ListingCategory (numeric)  TotalProsperLoans  \n",
       "0                          0                NaN  \n",
       "1                          2                NaN  "
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#select columns from the dataset\n",
    "sub_cols = [\"LoanStatus\", \"LoanOriginalAmount\", \"StatedMonthlyIncome\", \"DebtToIncomeRatio\", \"Term\"\n",
    "            ,\"EmploymentStatus\", \"EmploymentStatusDuration\", \"Occupation\", \"ListingCategory (numeric)\",\n",
    "            \"TotalProsperLoans\"]\n",
    "loans_sub = loans[sub_cols]\n",
    "loans_sub.head(2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/dina/anaconda3/lib/python3.8/site-packages/pandas/core/frame.py:4163: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame\n",
      "\n",
      "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
      "  return super().drop(\n"
     ]
    }
   ],
   "source": [
    "#remove cancelled as it is considered as an outlier\n",
    "loans_sub.drop(loans_sub[loans_sub['LoanStatus'] ==\"Cancelled\"].index, inplace = True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/dina/anaconda3/lib/python3.8/site-packages/pandas/core/indexing.py:1765: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame.\n",
      "Try using .loc[row_indexer,col_indexer] = value instead\n",
      "\n",
      "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
      "  isetter(loc, value)\n"
     ]
    }
   ],
   "source": [
    "#modify the values in LoanStatus such that the values can only be [Current, Completed, Defaulted,\n",
    "#                                                                  FinalPaymentInProgress, PastDue]\n",
    "keep_vals = [\"Current\", \"Completed\", \"Defaulted\",\"FinalPaymentInProgress\"]\n",
    "cond = loans_sub.LoanStatus.isin(keep_vals)\n",
    "loans_sub.loc[~cond, \"LoanStatus\"] = \"PastDue\""
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Current                   56576\n",
       "Completed                 38074\n",
       "PastDue                   14059\n",
       "Defaulted                  5018\n",
       "FinalPaymentInProgress      205\n",
       "Name: LoanStatus, dtype: int64"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "loans_sub[\"LoanStatus\"].value_counts()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "LoanStatus                       0\n",
       "LoanOriginalAmount               0\n",
       "StatedMonthlyIncome              0\n",
       "DebtToIncomeRatio             8554\n",
       "Term                             0\n",
       "EmploymentStatus              2252\n",
       "EmploymentStatusDuration      7621\n",
       "Occupation                    3585\n",
       "ListingCategory (numeric)        0\n",
       "TotalProsperLoans            91847\n",
       "dtype: int64"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#check for null values\n",
    "loans_sub.isna().sum()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "<ipython-input-11-1c2154f0a104>:2: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame.\n",
      "Try using .loc[row_indexer,col_indexer] = value instead\n",
      "\n",
      "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
      "  loans_sub['TotalProsperLoans'] = loans_sub['TotalProsperLoans'].fillna(0)\n"
     ]
    }
   ],
   "source": [
    "#replace null in TotalProsperLoans with zeros\n",
    "loans_sub['TotalProsperLoans'] = loans_sub['TotalProsperLoans'].fillna(0)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "LoanStatus                   0\n",
       "LoanOriginalAmount           0\n",
       "StatedMonthlyIncome          0\n",
       "DebtToIncomeRatio            0\n",
       "Term                         0\n",
       "EmploymentStatus             0\n",
       "EmploymentStatusDuration     0\n",
       "Occupation                   0\n",
       "ListingCategory (numeric)    0\n",
       "TotalProsperLoans            0\n",
       "dtype: int64"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#drop rows with null values\n",
    "loans_sub = loans_sub.dropna()\n",
    "loans_sub.isna().sum()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "736"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#check for duplicates\n",
    "sum(loans_sub.duplicated())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [],
   "source": [
    "#drop duplicates\n",
    "loans_sub = loans_sub.drop_duplicates()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(95824, 10)"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#check how much data we have\n",
    "loans_sub.shape"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "> Check some statistics about the data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>count</th>\n",
       "      <th>mean</th>\n",
       "      <th>std</th>\n",
       "      <th>min</th>\n",
       "      <th>25%</th>\n",
       "      <th>50%</th>\n",
       "      <th>75%</th>\n",
       "      <th>max</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>LoanOriginalAmount</th>\n",
       "      <td>95824.0</td>\n",
       "      <td>8685.584259</td>\n",
       "      <td>6363.032075</td>\n",
       "      <td>1000.0</td>\n",
       "      <td>4000.000000</td>\n",
       "      <td>7000.000000</td>\n",
       "      <td>12500.00</td>\n",
       "      <td>35000.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>StatedMonthlyIncome</th>\n",
       "      <td>95824.0</td>\n",
       "      <td>5741.778438</td>\n",
       "      <td>4931.768469</td>\n",
       "      <td>0.0</td>\n",
       "      <td>3333.333333</td>\n",
       "      <td>4866.666667</td>\n",
       "      <td>7000.00</td>\n",
       "      <td>483333.333333</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>DebtToIncomeRatio</th>\n",
       "      <td>95824.0</td>\n",
       "      <td>0.275814</td>\n",
       "      <td>0.529839</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.150000</td>\n",
       "      <td>0.220000</td>\n",
       "      <td>0.32</td>\n",
       "      <td>10.010000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Term</th>\n",
       "      <td>95824.0</td>\n",
       "      <td>41.305477</td>\n",
       "      <td>10.779414</td>\n",
       "      <td>12.0</td>\n",
       "      <td>36.000000</td>\n",
       "      <td>36.000000</td>\n",
       "      <td>36.00</td>\n",
       "      <td>60.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>EmploymentStatusDuration</th>\n",
       "      <td>95824.0</td>\n",
       "      <td>97.058159</td>\n",
       "      <td>93.420456</td>\n",
       "      <td>0.0</td>\n",
       "      <td>27.000000</td>\n",
       "      <td>69.000000</td>\n",
       "      <td>139.00</td>\n",
       "      <td>755.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ListingCategory (numeric)</th>\n",
       "      <td>95824.0</td>\n",
       "      <td>2.940318</td>\n",
       "      <td>4.081797</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>3.00</td>\n",
       "      <td>20.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>TotalProsperLoans</th>\n",
       "      <td>95824.0</td>\n",
       "      <td>0.291973</td>\n",
       "      <td>0.669145</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.00</td>\n",
       "      <td>8.000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                             count         mean          std     min  \\\n",
       "LoanOriginalAmount         95824.0  8685.584259  6363.032075  1000.0   \n",
       "StatedMonthlyIncome        95824.0  5741.778438  4931.768469     0.0   \n",
       "DebtToIncomeRatio          95824.0     0.275814     0.529839     0.0   \n",
       "Term                       95824.0    41.305477    10.779414    12.0   \n",
       "EmploymentStatusDuration   95824.0    97.058159    93.420456     0.0   \n",
       "ListingCategory (numeric)  95824.0     2.940318     4.081797     0.0   \n",
       "TotalProsperLoans          95824.0     0.291973     0.669145     0.0   \n",
       "\n",
       "                                   25%          50%       75%            max  \n",
       "LoanOriginalAmount         4000.000000  7000.000000  12500.00   35000.000000  \n",
       "StatedMonthlyIncome        3333.333333  4866.666667   7000.00  483333.333333  \n",
       "DebtToIncomeRatio             0.150000     0.220000      0.32      10.010000  \n",
       "Term                         36.000000    36.000000     36.00      60.000000  \n",
       "EmploymentStatusDuration     27.000000    69.000000    139.00     755.000000  \n",
       "ListingCategory (numeric)     1.000000     1.000000      3.00      20.000000  \n",
       "TotalProsperLoans             0.000000     0.000000      0.00       8.000000  "
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "loans_sub.describe().transpose()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### What is the structure of your dataset?\n",
    "\n",
    "> There are 113937 loan records in the dataset described by 81 features. The features are either numeric or categorical.  \n",
    "\n",
    "### What is/are the main feature(s) of interest in your dataset?\n",
    "\n",
    "> I want to figure out which features contribute the most in completing or defaulting a loan.\n",
    "\n",
    "### What features in the dataset do you think will help support your investigation into your feature(s) of interest?\n",
    "\n",
    "> The dataset contains a huge number of features. I will focus on the LoanStatus, LoanOriginalAmount, StatedMonthlyIncome, DebtToIncomeRatio, Term,EmploymentStatus, EmploymentStatusDuration, Occupation, ListingCategory, and TotalProsperLoans."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Univariate Exploration\n",
    "\n",
    "> I will start by checking the main variable of interest, LoanStatus."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 576x360 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Visulizing the loan status\n",
    "plt.figure(figsize=[8, 5])\n",
    "status = loans_sub['LoanStatus'].value_counts().index\n",
    "sb.countplot(data=loans_sub, y='LoanStatus', order=status);\n",
    "plt.xlabel('Count');"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "> It looks like most loans are paid as expected. However, some are defaulted or past due; I want to inspect whether any of the features can explain the delay?"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Visulizing the time periods for loans\n",
    "sb.countplot(data = loans_sub, x = 'Term');\n",
    "plt.xlabel('Count');"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "> Most loans are 36 months."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "#visualize employment status\n",
    "status = loans_sub['EmploymentStatus'].value_counts().index\n",
    "sb.countplot(data=loans_sub, x='EmploymentStatus', order = status)\n",
    "plt.xticks(rotation=45);"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    ">As expected, people with a stable job are favored in the loan process. Is a certain occupation more favored as well?"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1080x576 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "#visualize occupation\n",
    "plt.figure(figsize=[15, 8])\n",
    "status = loans_sub['Occupation'].value_counts().index\n",
    "sb.countplot(data=loans_sub, x='Occupation', order = status);\n",
    "plt.xticks(rotation = 90);"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "> Students are the least favored in the loan process. Trademen are the second least favored. In the case of the students, I believe this is logical as students need loans less. I think in the case of the trademen, it is because their job is not stable and they may not be able to pay regularly."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "count    95824.000000\n",
       "mean         0.275814\n",
       "std          0.529839\n",
       "min          0.000000\n",
       "25%          0.150000\n",
       "50%          0.220000\n",
       "75%          0.320000\n",
       "max         10.010000\n",
       "Name: DebtToIncomeRatio, dtype: float64"
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "loans_sub['DebtToIncomeRatio'].describe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "#visualize the debt to income ration\n",
    "plt.hist(data=loans_sub, x='DebtToIncomeRatio', bins =10);"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "> DebtToIncomeRatio is one's monthly debt payments divided by his/her gross monthly income. In most loans, the monthly debt is 32% of one's monthly income."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "count     95824.000000\n",
       "mean       5741.778438\n",
       "std        4931.768469\n",
       "min           0.000000\n",
       "25%        3333.333333\n",
       "50%        4866.666667\n",
       "75%        7000.000000\n",
       "max      483333.333333\n",
       "Name: StatedMonthlyIncome, dtype: float64"
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "loans_sub['StatedMonthlyIncome'].describe()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Discard outliers <br> There is a huge difference between the mean and the max value. We can not visualize the data like this. Since, we care about the majority of loans, I will discard any value that is far from the mean by more than 3 standard deviations."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Limit =  20537.083845221205\n",
      "# of ourliers =  905\n"
     ]
    }
   ],
   "source": [
    "#define the outliers' boundary\n",
    "limit = loans_sub['StatedMonthlyIncome'].mean() + 3*loans_sub['StatedMonthlyIncome'].std()\n",
    "print(\"Limit = \", limit)\n",
    "print(\"# of ourliers = \", len(loans_sub[loans_sub['StatedMonthlyIncome']>limit]))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "#visualize the income\n",
    "plt.hist(data=loans_sub, x='StatedMonthlyIncome', bins =1000);\n",
    "plt.xlim(0,limit);"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "> The averge income is skewed towards the right and the avergae income is 5000. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "count    95824.000000\n",
       "mean      8685.584259\n",
       "std       6363.032075\n",
       "min       1000.000000\n",
       "25%       4000.000000\n",
       "50%       7000.000000\n",
       "75%      12500.000000\n",
       "max      35000.000000\n",
       "Name: LoanOriginalAmount, dtype: float64"
      ]
     },
     "execution_count": 26,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#check the loan original amount\n",
    "loans_sub['LoanOriginalAmount'].describe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "#visualize the income\n",
    "plt.hist(data=loans_sub, x='LoanOriginalAmount', bins =50);"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "> Most loans are less than 15K."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [],
   "source": [
    "#ListingCategory\n",
    "categ = [\"Not Available\",\"Debt Consolidation\",\"Home Improvement\",\"Business\",\"Personal Loan\",\"Student Use\"\n",
    "         ,\"Auto\",\"Other\",\"Baby&Adoption\",\"Boat\",\"Cosmetic Procedure\",\"Engagement Ring\",\"Green Loans\",\n",
    "         \"Household Expenses\",\"Large Purchases\",\"Medical/Dental\",\"Motorcycle\",\"RV\"\n",
    "         ,\"Taxes\",\"Vacation\",\"Wedding Loans\"]\n",
    "loans_sub['ListingCategory (numeric)']= loans_sub['ListingCategory (numeric)'].apply(lambda x: categ[x])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x360 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "#ListingCategory\n",
    "plt.figure(figsize=[10, 5])\n",
    "status = loans_sub['ListingCategory (numeric)'].value_counts().index\n",
    "sb.countplot(data=loans_sub, x='ListingCategory (numeric)', order = status);\n",
    "plt.xlabel(\"Listing Category\")\n",
    "plt.xticks(rotation = 90);"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "> Most loans are taken to pay debt."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "#visualize EmploymentStatusDuration\n",
    "plt.hist(data=loans_sub, x='EmploymentStatusDuration', bins =50);"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "#TotalProsperLoans\n",
    "sb.countplot(data=loans_sub, x='TotalProsperLoans');"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Discuss the distribution(s) of your variable(s) of interest. Were there any unusual points? Did you need to perform any transformations?\n",
    "\n",
    "> - Most loans are current or completed loans. Almost none of the loans are cancelled.\n",
    "> - Most loans are listed as Debt Consolidation. However, many borrowers did not report a listing category. \n",
    "> - Most loans are bellow 15K.\n",
    "> - The average monthly income of borrowers is 5000. However, the overall distribution of the values is not uniform with many outliers. I did not perform any transformations; however, I discarded the outliers.\n",
    "> - Almost all borrowers are employed. \n",
    "> - The term of most loans is 36 months.\n",
    "> - Most borrowers have not occupied their current job for very long (which is weird?)\n",
    "> - Most borrowers have no previous loans.\n",
    "\n",
    "### Of the features you investigated, were there any unusual distributions? Did you perform any operations on the data to tidy, adjust, or change the form of the data? If so, why did you do this?\n",
    "\n",
    "> - The ListingCategory feature is not intuitive; so, I modified the the labels to their name. \n",
    "> - In the LoanStatus feature, I combined all the past due periods to be just Pastdue as we don't care about the period of past due loans. \n",
    "> - I removed the outliers during the visualization of the monthly income. In order to have a successful analysis, I will now remove any client whose monthly income is more than 20537$. This will result in removing 905 rows from the dataset."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(94919, 10)"
      ]
     },
     "execution_count": 32,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#remove outliers\n",
    "loans_sub = loans_sub[loans_sub['StatedMonthlyIncome']<limit]\n",
    "loans_sub.shape"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Bivariate Exploration\n",
    "\n",
    "> Let's first see a correlation plot between all the numeric categories."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {},
   "outputs": [],
   "source": [
    "numeric_cols = [\"LoanOriginalAmount\", \"StatedMonthlyIncome\", \"DebtToIncomeRatio\", \"Term\",\n",
    "                \"EmploymentStatusDuration\",\"TotalProsperLoans\"]\n",
    "categorical_cols = [\"LoanStatus\",\"EmploymentStatus\",\"Occupation\", \"ListingCategory (numeric)\"]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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l7H2fYEC896LAvsqYRvb/C1nfO2u+6eTjAoO7v+Pujdy90dESKAJ8s3QjlzUODINrWD2WlJ3pJG/fw5JVKZwYX4qqFWMoHmVcelY83ywJ/Hj6ZslGLm8SGLp4eZMqfL1k4z7zl4N3/Aknsyl5PZs3JpGWlsaSRbOpVT/bocwDfV/nweCrbsMmdLj6nwcMFAF++2kpcQnHZRvmKodXvbp1Wb16NWv/+IPU1FT+O3EirVq2zJamZYsWjB03DnfnuyVLKF26NHFxcfvd94KWLZk/PzCz8cpVq0hNTaV8eQUbh9OJNWqSnLiejcmJpKWl8r95M2nQMPtxlZy4PrN3Y82q30hLS+PY0mXoeOVNPPXiezzR/z90vvPfnFqrAbfcfj/HV63OcwM/5In+/+GJ/v+hXPmK9Hj8JQWKhaB27TqsWbOadesCx89XX31F82bNs6Vp1qw5/50wHndn6bKllC5dmkrBYGPz5sCQ4w0bNjB16hQuuqgtEJhhdfBHg3mh/4vExBxoAJMUxHVXXZk5Ic0FzVsw9r8TAufFpcsC58VK2YNFM+Pss87iq8lTABg7fgKtmjcDYOOmTZnH5tLly8nIcMqVLctfO3fy55+Bn7t/7dzJ7HnzOeXkk0JYSzmSRHzPortvM7MtZtbM3WcANwF7exnLAOvNrDhwA/DHAbL7BHjEzNq4+9fBCW9eAfKeXiq7mcDVQD8zuwgoyLfa3jPpRjMrDVwJjMyawMxOA45196z3KfYl0Nv4ZD7fZzqBz2GymZ1KYKjsT0AscLeZFQOOBw78Czow1PWomgd7QOe6ND61HOVLF2fm000ZOP53ooOXfobMWMfUZZtoWbcik/uey8496fT46AcA0jOcvsN+5oN7GxJVzBgxZx2/rA+cZN+etIpXutTjqqZVWLd5F13fXRa2+h3NoqKi+MdVtzHojadxz+DMJq1IqFKNeTMnAdD4APcpDvvgZVb8+j1/7UihX+87ad3uahqdewEQGIKqiW0KV3R0NI/06MEdd99NekYGl3XsyCknn8ywEYFBItdcdRXNzz+fGTNnckmHDhwTE8OTffrsd1+Ayzt1olefPnS68kqKFy/OM088oR6OwywqKoqrb/w/Xn+pL56RTpPz21Dl+BOYMSUw0KVZq4tZvGgO82ZPISoqiuIlSnLbnQ+oHY4Q0dHRPPDAQ3Tr3o2MjHT+0b4DJ510MqNHjwLg8suv4Lym5zF79iyuuPIyYmJi6N3rscz9H+7Zg23bthEdHc2DDzxEbGzgjp0XXuzPnj176NrtHgDq1avPwz16hr6CR7lm5zVl+uzZtLviSmJiYniq99+Pnrnrvvvp++gjxMfFcf+99/BQr968+vbb1Dr1VC7v0AGASZMnM3zUaKKioogpWZL+Tz2JmbFp82bue6gHEBhd067tRZx/7rlhqePRKpIenWGRdv+GmWUA67KsegmYDLxFYAjnCqCzu28xs7uAh4BVBIZmlnH3W81sEDDO3UcG89zh7qWDf9cnMFSzChAFfAQ84e5uZn0I9DK+EEzbEnjA3dubWTwwhECQOI3A/YQ13H333vyzpg/u/xqw0N0HBYfLXgusBNYAq9y9z96yAvWAGHd/OMtn0QAY6u51ctQhZzn3vn9M8HM6i0Bv4r/cfUpwMp2PgYbAMiAB6OPuU3PkeyXQPvgZnkegB3Q3gR7RPO9bPOXuyZH1H0wyPddJPWmRrOP5NQ+cSI5YU79dFe4iyEE6u87xB04kR6xSlh7uIsghKFGufESEYW17flPg38cTn20dlrpFXLB4pDKzkkC6u6eZ2bnAm+7eMMzFCjsFi5FLwWJkU7AY2RQsRi4Fi5FNwWJkU7B4+EX8MNQjyAnA8OBQzj3A/4W5PCIiIiIicoSJpGGoChYPE3f/hcBjMURERERERCKegkUREREREZEQOYhHPoeNgkUREREREZEQiaRhqBEU14qIiIiIiEioqGdRREREREQkRNSzKCIiIiIiIhFNPYsiIiIiIiIhEkk9iwoWRUREREREQsQiKFjUMFQRERERERHJRcGiiIiIiIiI5KJhqCIiIiIiIiESSfcsqmdRREREREREclHPooiIiIiISIioZ1FERERERERyKWYFf+WHmV1sZj+Z2a9m9nAe28ua2Rdm9p2ZLTezzgcsa8GrJyIiIiIiIkcKM4sCXgcuAeoA15lZnRzJ7gG+d/fTgZbAi2ZWYn/5ahiqiIiIiIhIiBQrnActngP86u4rAMxsKNAR+D5LGgfKmJkBpYHNQNr+MlWwKIXquU4Vw10EOUgPf74p3EWQQ9DmxP1eKJQjXJN6VcNdBDlIO/7aE+4iyCGIiY0JdxFEDtbxwJosy2uBxjnSvAaMBdYBZYBr3D1jf5lqGKqIiIiIiEiIHMw9i2Z2u5ktzPK6PUe2eXVXeo7ltsBi4DigIfCamcXur6zqWRQRERERETmCufs7wDv7SbIWqJZluSqBHsSsOgPPubsDv5rZ70AtYP6+MlXPooiIiIiISIiYFfyVDwuAmmZWIzhpzbUEhpxmtRpoHSiDJQCnASv2l6l6FkVEREREREKkMJ6z6O5pZnYvMBGIAt539+Vmdmdw+1vAk8AgM1tKYNhqD3ffuL98FSyKiIiIiIhEOHefAEzIse6tLH+vAy4qSJ4KFkVEREREREKkMHoWC4vuWRQREREREZFc1LMoIiIiIiISIupZFBERERERkYimnkUREREREZEQKZbPZ2EcCdSzKCIiIiIiIrmoZ1FERERERCREIqhjUT2LIiIiIiIikpt6FkVEREREREIkkmZDVbAoIiIiIiISIpEULGoYqoiIiIiIiOSinkUREREREZEQsQia4UbBokjQz98vZvyoD8jIyKDRua1pcVGnPNOtXfUrb734KNd2vp96ZzQBYNQnb/DTsv9xbJmydH/kxcy0Q98fQHLSOgB27fyLmGNK0fXh/oVel6Lm2RtrcUH9SmxK2UO7p+bnmab3VTVpWbciO1Mz6DH4e5av2QFA8zoV6HVVTaLMGD57PW9PWgVA2VLRDOxSj6oVY1i7aRfd3l3G9p1pIatTUePuvPSfd5m9cBExJUvS+75u1Dr55FzpRowbz9CxX7B2wwYmfjyYcrGxAHw0+jMmTpsGQHp6BivXruXLjz6kbJkypOzYwdOvvc6KVasxM3p1u5f6tWqFtH5Hs9lzZvPCiy+QkZFBp46duPWWW7Ntd3deePEFZs2eRUxMDH0e60OtWrVYuWoljzzySGa6P9b9wR2338H1110PwNBhQxk+YjjRUdGcd955dO/WPZTVKjLmzZvLa6+9THp6Opde+g9uuOHmbNtXrVpJv35P88svP9Olyx1ce22gfXbv3k337neTmppKeno6LVq0onPnfwLQt29vVq9eDcCOHSmULl2G9977MLQVKwJmzZpFvxdeICM9ncsuu4wunTtn2+7u9Ovfn5kzZxITE8OTfftSu3btzO3p6elcd+ONxMfF8dorrwCwbds2Hnr4YdatW8dxxx1H/379iA2eZ6VoOmKDRTN7FLgeSAcygDuAc4F33P2vA+x7X37S5dinJfCAu7c3s1uBD4A27v5NcPtlwGjgKncfeRD1aQnscffZweVBwLiceZlZ9eD6evvJ61agkbvfW9BySN4yMjL4YsR7dL6nF7HlKvJm/57Urt+I+CpVc6WbOOYTatZumG39mY1b0qT5xYz86PVs66+97f7MvyeMHkzMMaUKrQ5F2ei5G/h42lr631Inz+0t6lakenwpWveZS8PqsfS99jSu7L+IYgZ9rjmNW175lg1bdzO6RyO+WZLMrxv+4o62JzLnpy28PWkVd1x0Ine0PZH+n/8W4poVHbMXLWLNuvWMfPtNlv30M8+/+Rbvv5D7wkqD2rU57+xG3P1or2zrb7r8Mm66/DIAZsyfz5AxX1C2TBkAXvrPe5x75pk893APUlNT2bV7d+FXqIhIT0+n3/P9eP2110mIT+DmW26mebPmnHTSSZlpZs2exZo1a/hs1GcsW7aMZ/s9y4cffEj1E6vz6SefZubT7tJ2tGrZCoCFCxcyffp0hn46lBIlSrB58+aw1O9ol56ezsCBL/DCCwOJi4vnzju7cN55zahevUZmmtjYWLp1u5+ZM6dn27dEiRK89NKrlCpVirS0NLp2vZNzzmlC3br1ePzxJzPTvfHGKxx7bOmQ1amoSE9P55l+/Xj7jTdISEjg+htvpGWLFpyc5dibOWsWq1ev5osxY1i6dClPPfssnwwenLn9kyFDOKlGDXbs2JG57v0PPuCcc86hS+fOvPfBB7z3wQfc310Xag433bN4iMzsXKA9cKa7NwDaAGuA+4D8/NrOb7r9WQpcl2X5WuC7Q8ivJdD0UAokhWftql+pUKkyFSolEB0dTYOzmvLD0gW50s2Z9l/qNmzMsaWzX2WrcUodSpXa95ehu7Ps2zk0OOu8w152gQW/bmXrn/vu9WvToBKfzdsAwOKV24ktFU1cbAlOrx7LquS/WLNpF6npzvhFSbQ5PS5zn9Fz1wMweu56Ljy9UuFXpAibPm8+l7RqiZlRv9ZppPz5JxvzCBBOO/kkjktI2G9ek6bP4KLmzQDY8ddffLt8OR0ubANA8eLFKVNaP1wPl+XLl1OtajWqHl+V4sWLc9FFFzFt+rRsaaZNn0a7du0CbVu/PikpKWzcuDFbmgULFnB81eOpUqUKACNHjeSWW26hRIkSAFSoUCE0FSpifvzxe44/virHHXc8xYsX54IL2jBr1oxsacqXr0CtWnWIisrev2BmlCoV+KmVlpZGWlparqF17s6UKZNp3frCwq1IEbRs2TKqVa1K1aqBY+/itm2ZOnVqtjRTpk7lH+3bY2Y0aNCAlJQUkpOTAUhMTGTGjBlc1qlT9n2mTaND+/YAdGjfnik58pSi54gMFoEqwEZ33w3g7huBK4HjgClmNgXAzN40s4VmttzM+gbXdcsj3UVmNsfM/mdmI8ysdHD9xWb2o5nNBC7PUYYZwDlmVjyY/hRg8d6NZtbazL41s6Vm9r6ZlQyuX2lmfYPvtdTMagV7C+8E7jezxWbWLJhNczObbWYrzOzKnB+Cmc0ws4ZZlmeZWYMcaQaZ2St55WNmDwXL8J2ZPRdc19DM5prZEjP7zMzKB9dPNbMBZjbdzH4ws7PNbLSZ/WJmT2XJ80Yzmx+sx9tmFnXA1owA27dupmz5ipnLseUqsm1r9h+q27Zu5vsl8znn/IsKnP/K337g2DJlqRRf5ZDLKgWXUK4k67fsylzesGU3CeVKBtfvzr6+bEkAKpUpQfL2PQAkb99DxTIlQlvoIiZ502YS4v4OyOMrViR5U8F7k3bt3s3c/31Lq6bnArBuwwbKly3LkwNf4abu9/P0q6+xc9euA+Qi+ZWUnERCluA9Pj6epOSkbGmSk5KpnFA5czkhPoGkpOxpJn41kbYXtc1cXr16NYsXL+aWzrdw+x23s/z75YVUg6ItOTmZuLi/2y8uLi4zmMiP9PR0unS5hU6dLqVRo7OpU6dutu1LliymfPkKVK1a7bCVWQKSkpOpXPnv4yo+Pp7EHMdVUlL24zMhPp6kYPs+/8IL3N+9O8WKZQ8FNm/aRFxc4KJpXFycevULSbFiBX+Frazhe+v9mgRUM7OfzewNM2vh7q8A64BW7t4qmO5Rd28ENABamFmDnOnMrBLQi8CQ0jOBhcC/zCwG+A/wD6AZUDl7EXDga6At0BEYu3dDcN9BwDXuXp/AcN67suy7MfhebxIY2roSeAsY4O4N3X3vZbsqwPkEelGfy+NzeBe4NfiepwIl3X1JHuly5WNmlwCdgMbufjrwfDDtYKBHsMd2KfB4lnz2uHvzYFnHAPcA9YBbzayimdUGrgHOc/eGBIYI35BHeSKO47nW5bxCOmHUINp2uCHXiTU/liyaxenqVQybvO4jd4e8RoHk9X9BCl+en/tBDNOZMX8BDWrXyhyCmp6ewU+//cbll1zCRwMHEBMTw4cjRx1iaSVTns2Wo3fpAOfX1NRUpk+fTpvWbTLXpaWnsX37dga9P4hu3brRs2dP3HVshkJBJt6Iiorivfc+ZMSIz/nhhx9YsSL7UP1vvvma1lnaVQ6fvI6H/LSdAdOmT6dChQrUqZP3rRtS+MwK/gqXIzJYdPcdwFnA7UAyMCx4n15OV5vZ/4BvgbpAXv/rmwTXzzKzxcAtwIlALeB3d//FA0fcx3nsO5TA8NNrgSFZ1p8W3Pfn4PKHQPMs20cH/10EVN9PVT939wx3/x7Ia1zVCKC9mRUHbiMQoOY3nzbAB3vv23T3zWZWFijn7nvHCOUs996AeCmw3N3XB3t3VwDVgNYE2mVB8LNsDZxEDmZ2e7DHd+FXEwp8e2dYlC1XkW1bNmUub9+6idiy5bOl+WP1bwwbNJD+j9/D8sVzGTv8Xb7/Lu/JVLJKT09n+XfzqX+mRiGHy4Ytu6lSPiZzuXL5kiRt282GrbupUr5kjvWB3sSNKXuIiw30JsbFlmBTyp7QFroIGDF+Ajd2v48bu99HXIUKJCb/PTQxadMm4g5i6OFXM/4eggoQX6ki8ZUqUu+0UwG4oOm5/LRixaEXXoBgb0ZiYuZyUlJSZq9E1jQbEjdkLicmJWZLM2v2LGrVqkXFin+P7kiIT6BVq1aYGfXq1sOKGVu3bi28ihRRgZ7Ev9svOTmZSpUKPuS+TJkyNGx4BvPnz8tcl5aWxowZU2nVSsFiYUiIj2fDhr+Pq6SkJOLzOPayHp+JweNz8XffMXXaNC659FJ69OzJgoUL6fnoowBUqFgxs3c5OTlZQ8DlyAwWAdw93d2nuvvjwL3AFVm3m1kN4AGgdbCXbDwQkzsnDPgq2KPX0N3ruHuXvW9zgDLMJ9CzVilLYLg3z/3ZO64tnf1PIpR1loVceQYDva8I9GxeDXxagHyMA9RvP/lk5Mgzg0A9DPgwy2d5mrv3yaPc77h7I3dvdGG7XKNrj0jHn3Aym5LXs3ljEmlpaSxZNJta9RtlS/NA39d5MPiq27AJHa7+J3VOP+eAef/201LiEo7LNsxVQuubpRu5rHFg8EDD6rGk7EwnefselqxK4cT4UlStGEPxKOPSs+L5ZkkgYPlmyUYubxIYNnx5kyp8vWTjPvOXg3PVpe34eODLfDzwZZo3bsx/p0zF3Vn640+ULnUslQr4I2XHn3/y7bLlNG/cOHNdxfLlia9UiVVr/wBg4XdLqFFNQ+IOlzp16rBmzRr++OMPUlNTmTRpEs2bNc+WpkWzFkyYMCHQtkuXUrp06WwBycRJ2YegArRo0YKFCxcCsGrVKtJS0yhXrlyh16eoOe202qxdu5b169eRmprK5Mlf07Tp+fnad+vWLaSkpACBmVEXLVrICSecmLl973J8fHyhlL2oq1u3LqvXrGFt8Nj7cuJEWrRokS1NyxYt+GLcONydJUuWULp0aeLi4ujetStfffkl/x0/nn7PPsvZjRrx7NNPB/Zp3pyx48YBMHbcOFrlyFMOj2JmBX6FyxE5G6qZnQZkuPsvwVUNgVUEeunKABuBWOBPYJuZJQCXAFOD6VOypJsLvG5mp7j7r2ZWCqgK/AjUMLOT3f03sk9mk1VPIOcNLj8C1ffmCdwETMu1Z3YpwTIX1LvAF8AMdy/IwPFJwGNm9qm7/2VmFYK9i1vMrFlwKGx+yp3VN8AYMxvg7klmVgEo4+6rCpDHESkqKop/XHUbg954GvcMzmzSioQq1Zg3cxIAjQ9wn+KwD15mxa/f89eOFPr1vpPW7a6m0bkXAIEhqJrYpnAN6FyXxqeWo3zp4sx8uikDx/9OdFTgxDpkxjqmLttEy7oVmdz3XHbuSafHRz8AkJ7h9B32Mx/c25CoYsaIOev4Zf2fALw9aRWvdKnHVU2rsG7zLrq+uyxs9SsKzmt0FrMXLeKKO+4MPDqjW7fMbff1fYJH772XuIoVGPbFOD4a/Rmbt2zhhm7daXrWWTzaNTAx9NS5cznnjIYcE5P9uuEDt/8fj730EmmpaRxXOYHe3bshh0d0dDQPPvggXbt1JT0jnQ7/6MDJJ5/MyFGBUSVXXnEl5513HrNmz6LT5Z2IiYnh8d5/3/2wa9cu5s+bz6M9H82Wb8cOHXniySe4+tqrKV68OH0e7xNRzyWLFNHR0XTv/i8efPB+MjLSueSS9tSocRJjxnwGQMeOl7Fp0ybuuOM2/vrrT8yKMXLkMD788FM2bdrEs88+SUZGBhkZGbRq1ZqmTf/+rps8+WsuuEAT2xSW6OhoevbowV333BN4bE2HDpxy8skMHxk49q6+8kqanX8+M2fOpH3HjsTExPBEnz4HzPe2zp15sEcPPv/8cypXrswLzz9/wH3k6GZH4j0AZnYW8CpQDkgDfiUwJPU6AvfRrQ/ejzgIaExgmORuYKy7DzKzrjnSXQD0A/aON+vl7mPN7GLgZQJB5UygXpZHZ+R6NEXWx12YWWvgBQIB9wLgLnffbWYrg/tuNLNGwAvu3jJ4z+FIAr10XYEuZHl0hpntcPfSlsejM8zsR+A+d/8yuJxZPsvxCI69+QT/fhi4GdgDTHD3R4IT5rxFYLbYFUBnd99iZlMJ3F+50LI8RiSYT9Zt1xAIoIsBqcA97j53X205ctJ3R95/MMmXhz/fdOBEcsRa2F2TKUWyqMpVD5xIjkg7/tKQ9UhWPjavQWoSKWKOPTYirir969VpBf59/FLXFmGp2xEZLMrfzOw4Aj2mtdw9I8zFKTAFi5FLwWJkU7AY2RQsRi4Fi5FNwWJki5Rg8YHXCh4svnBveILFI/aeRQEzuxmYR2DW14gLFEVEREREJLtiVvBXuByR9yxKgLsPJvCoCxERERERkZBSsCgiIiIiIhIikTRhl4ahioiIiIiISC7qWRQREREREQmRcN6DWFAKFkVEREREREIkgkahahiqiIiIiIiI5KaeRRERERERkRApFkFdi+pZFBERERERkVzUsygiIiIiIhIimuBGREREREREcomgUagahioiIiIiIiK5qWdRREREREQkRDTBjYiIiIiIiEQ09SyKiIiIiIiESCRNcKOeRREREREREclFwaKIiIiIiEiEM7OLzewnM/vVzB7eR5qWZrbYzJab2bQD5alhqFKoOp5fM9xFkIPU5sQS4S6CHIJGA9eHuwhyCH7oXy3cRZCDFFM2JtxFkEMSQeMDJWJZIUxwY2ZRwOvAhcBaYIGZjXX377OkKQe8AVzs7qvNLP5A+apnUUREREREJESKWcFf+XAO8Ku7r3D3PcBQoGOONNcDo919NYC7Jx2wrAWrmoiIiIiIiISSmd1uZguzvG7PkeR4YE2W5bXBdVmdCpQ3s6lmtsjMbj7Q+2oYqoiIiIiISIgUO4juOnd/B3hnP0ny6n/0HMvRwFlAa+AYYI6ZzXX3n/eVqYJFERERERGRyLYWyHrDe1VgXR5pNrr7n8CfZjYdOB3YZ7CoYagiIiIiIiIhYmYFfuXDAqCmmdUwsxLAtcDYHGnGAM3MLNrMSgGNgR/2l6l6FkVEREREREIknxPWFIi7p5nZvcBEIAp4392Xm9mdwe1vufsPZvYlsATIAN5192X7y1fBooiIiIiISIRz9wnAhBzr3sqx3B/on988FSyKiIiIiIiESGE8Z7Gw6J5FERERERERyUU9iyIiIiIiIiFSGPcsFhYFiyIiIiIiIiFSTMNQRUREREREJJKpZ1FERERERCREIqhjUT2LIiIiIiIikpt6FkVEREREREJE9yyKiIiIiIhIRFPPooiIiIiISIhEUMeiehZF9po5axbtO3Xikg4dePf993Ntd3ee6dePSzp04LKrr+b7H37I176fDBlC+06d6HjFFbz48suFXY0iy9158Z3/cMXtd3JD1+78+NtveaYbMW48V9x+J407dGLr9u2Z6z8a/Rk3dr+PG7vfx3X3duPcTpezLSUFgJQdO3j4uX5cfdc9XHP3vSz98ceQ1KmoePbGWszrdz4Tep2zzzS9r6rJN32aMO7Rc6hbrXTm+uZ1KjDp8cZ806cJd1x0Yub6sqWiGdS1IV/3acKgrg2JPUbXRguLu/PM889zSYeOXHb1NdnOjVmt/eMPrrv5Ztp17MS/ezxMamoqACt+/50bbrmVMxo34YPBgzPT/75yJVdce13mq3Gz5nz0yachqVNREvhuez7P77as1v7xB9fddDPtOnTk3z16ZG+/m2/hjHMaZ2u/9Rs20Pn/bucfl19Oxyuu5KNP1XaHW2H9bgH4YPBg6p1xBlu2bCnUOsiR76gJFs0s3cwWm9lyM/vOzP5lZvutn5m1NLNx+9j2SPDfisF8F5vZBjP7I8tyiTz2m2pmjQ5PrQ5dsI7bzOxbM/vRzF7Ixz6dzKxOluUnzKxN4ZY0vNLT03nqued487XXGDtqFBO+/JLfcgQbM2bOZPXq1UwYM4Y+vXrx5DPPHHDf+QsWMGXqVEYPH86YUaO49eabQ163omL2okWsWbeekW+/ycP33M3zb76VZ7oGtWvz6pN9qRIfl239TZdfxscDX+bjgS9z9803ckbdupQtUwaAl/7zHueeeSbD33ydjwcOoHrVqoVen6Jk9NwN3Pba4n1ub1G3ItXjS9G6z1x6ffIjfa89DQg81LjPNafR5bXvuPjJebRvFM8plUsBcEfbE5nz0xba9JnLnJ+2cEfbE/eZvxyaGbNmsXr1GiaM+Txwbnz22TzTDXjlFW664QYmjPmc2NhYRn3+OQBly5bl4Yce5NabbsqWvkb16owaOoRRQ4cw/JOPiYmJoXWrVoVdnSJnxsxZOb7b9tF+A4PtN3YMsWViGfXZ50Cw/Xo8xK03Z2+/6KgoHvzX/XwxejSfDv6QocOG89tvKwq7OkVGYf1ugUCgP2fuXKpUrhzSOhUlxazgr7CVNXxvfdjtdPeG7l4XuBBoBzx+CPk9AuDum4L5NgTeAgbsXXb3PYdc6tCY4e5nAGcA7c3svAOk7wRkBovu/pi7f12I5Qu7pcuWcUK1alSrWpXixYtzSdu2TJ46NVuaKdOm0aF9e8yM0xs0ICUlheTk5P3uO2zECLp07kyJEoHrChUrVAhxzYqO6fPmc0mrlpgZ9WudRsqff7Jx8+Zc6U47+SSOS0jYb16Tps/goubNANjx1198u3w5HS4MXC8pXrw4ZUqX3t/uUkALft3K1j/T9rm9TYNKfDZvAwCLV24ntlQ0cbElOL16LKuS/2LNpl2kpjvjFyXR5vS4zH1Gz10PwOi567nw9EqFX5EiasrUaXRof2nw3FiflJQdJCcnZ0vj7sxbsICLWrcGoGP79kyeMhUInBfr161LdPS+e3/nzp9PtapVOe64KoVWj6JqyrSpeX63ZZXZfm2C7feP9kyeOgXYd/vFxcVRp3ZtAI499lhOqlGDxOSkENSoaCis3y0Az7/wAv/q3h2LpLGSUmiOpmAxk7snAbcD91pAlJn1N7MFZrbEzO7IkjzWzD4zs+/N7C0zK2ZmzwHHBHsPP8nrPcysdbC3bqmZvW9mJfNIs8PMng72dM41s4Tg+oTge34XfDUNrv+XmS0Lvu4Lrqse7BF8N7j+EzNrY2azzOwXMzsnmO7YYDkWBMvVMY/PZSewGDg+uM//BdN/Z2ajzKxUsCwdgP7B+p9sZoPM7Mr81jsSJSUlUTlLAJGQkEBSji/LxKQkKme5ypaQkEBiUtJ+9125ahWLvv2W6266iVu7dGHp8uWFXJOiK3nTZhLi/g4I4itWJHlT7mDxQHbt3s3c/31Lq6bnArBuwwbKly3LkwNf4abu9/P0q6+xc9euw1ZuObCEciVZv+Xvz3zDlt0klCsZXL87+/qygVNSpTIlSN4euJ6XvH0PFcvkGggih0liznNgfDyJOc6fW7dupUzpMpkBRUJCfK5z7P78d+Ik2rVte3gKLNkEvtuyfofFk5iUR/uVKZ2l/RJISsp/+/2xbh0//PQTDerVOzyFlkL73TJl6lTi4+OpddpphVyDoq1YMSvwK2xlDds7FzJ3X0GgfvFAF2Cbu58NnA38n5nVCCY9B/g3UB84Gbjc3R/m757KG3LmbWYxwCDgGnevT2CioLvyKMaxwFx3Px2YDvxfcP0rwLTg+jOB5WZ2FtAZaAw0CZbxjGD6U4CBQAOgFnA9cD7wAMEeUOBRYHKwjq0IBHvH5ih3eaBmsCwAo9397GA5fgC6uPtsYCzwYLD+v2XZP7/1jjiex7qch6V77lRmtt9909PT2b59O58OHsy/77+fBx56KM985NB5Xi1xEOfWGfMX0KB2rcwhqOnpGfz0229cfsklfDRwADExMXw4ctQhllYKIq+L2+55N2+e/w+kUOX1mVuO1snzPJnP4zM1NZWp06dx0YVH9d0QYZPXV1LOtsk7Tf4a8K+//uL+Bx6gxwP/prRGZRw2hfG7ZefOnbzz3nvce9dR8dNODpOjNlgM2nvcXATcbGaLgXlARQJBE8B8d1/h7unAEAJB2IGcBvzu7j8Hlz8EmueRbg+w957IRUD14N8XAG8CuHu6u28Lvu9n7v6nu+8ARgPNgul/d/el7p4BLAe+8cAZYGmWPC8CHg7WcSoQA5wQ3NbMzJYAG4Bx7r4huL6emc0ws6XADUDdw1FvM7vdzBaa2cK8bpo+EiXEx7MhMTFzOTExkbi47Pe0VU5IYMOGDdnSxMfF7XffhIQE2rRuHRgaWa8eVqyYbhY/jEaMn5A5KU1chQokJm/M3Ja0aRNxBzHs96sZfw9BBYivVJH4ShWpd9qpAFzQ9Fx+WqH7bkJpw5bdVCkfk7lcuXxJkrbtZsPW3VQpXzLH+kBv4saUPcTFBnoT42JLsCklUu4aiAxDhg3PnHgmPi4u+zkwKYn4uOzDfsuXK0fKjhTS0gLDjRMTk4irlP0cuy8zZs2idq1aVKpY8fBVoIgbMmwYV1xzLVdcc22g/TZk/Q5LIj7H91/58uVISdmRpf0SiYs78NDu1NRU7nvgAS69pB0XBocgy+FRGL9b1qxdyx9//MEV11zDRe3akZiUxFXXX8/GjRuRw8us4K9wOWqDRTM7CUgHkggEjV2z3GtYw90nBZPmvMCSn8vS+W2yVP/7sk46+39Uyf7y3J3l74wsyxlZ8jTgiix1PMHd9057NcPdGxDoPb3LzBoG1w8C7g32EvYlEGDuT77q7e7vuHsjd2/0z9tuy88uYVevbl1Wr17N2j/+IDU1lf9OnEirli2zpWnZogVjx43D3fluyRJKly5NXFzcfve9oGVL5s+fDwSGpKamplK+fPkQ1+7oddWl7TInpWneuDH/nTIVd2fpjz9RutSxVCpgsLjjzz/5dtlymjdunLmuYvnyxFeqxKq1fwCw8Lsl1KhW7bDWQ/bvm6UbuaxxYChVw+qxpOxMJ3n7HpasSuHE+FJUrRhD8Sjj0rPi+WZJ4EfNN0s2cnmTwP1tlzepwtdL9GPncLrumqszJ5+5oGVLxo4bHzw3Ls08N2ZlZpzTqBGTvvkGgDHjxnFByxb5eq8JX06kXduLD3sdirLrrrmGUcOGMmrYUC5o1TLP77asMtvv62D7fTGOC3J8R+bk7jzW9wlOqlGDW266sZBqUnQVxu+WU2vWZPrkyUyaMIFJEyaQEB/PiE8/pVIl3fN9uBUzK/ArXI7KucTNLI7AZDSvubub2UQCQdJkd081s1OBP4LJzwkOSV0FXAO8E1yfambF3T01j7f4EahuZqe4+6/ATcC0AhTxGwLDN182sygCw1WnA4OC90sacFkw3/yaCHQ1s67BOp/h7t9mTeDuP5vZs0AP4DqgDLDezIoT6Fnc+5mkBLfldKj1PmJFR0fzSI8e3HH33aRnZHBZx46ccvLJDBsxAoBrrrqK5uefz4yZM7mkQweOiYnhyT599rsvwOWdOtGrTx86XXklxYsX55knntAN44XkvEZnMXvRIq64405iSpakd7dumdvu6/sEj957L3EVKzDsi3F8NPozNm/Zwg3dutP0rLN4tOu9AEydO5dzzmjIMTHZr5s8cPv/8dhLL5GWmsZxlRPo3b0bcvgM6FyXxqeWo3zp4sx8uikDx/9OdFTgOBkyYx1Tl22iZd2KTO57Ljv3pNPjo8B1sPQMp++wn/ng3oZEFTNGzFnHL+v/BODtSat4pUs9rmpahXWbd9H13WVhq9/RLnBunMUlHTtmOzcC3NW1G30f6018XBz3d+vGgz0f4dXX36B2rdO4vFMnADZu3Mg1N97Ejj//pJgZH386hDEjR1C6dGl27tzJnHnzePzRR/J+czlkf3+35dF+93al72OPER8fx/3du/Hgwz159Y3XqX1areztd8ONf7ffJ58yZtRIfv7lF74YP56aNU/himuuBaD7vffSvFl+BnDJgRTW7xaRnOxouX/KzNIJDMssDqQBHwEvuXuGBR6h8RTwDwKBWDKBGT/PAB4LLtcnELDdHdynH4GJXv63975FM+sD7HD3F8ysNfACgYB7AXCXu+82s6nAA+6+0Mx2uHvp4L5XAu3d/dbgRDfvAHt7P+9y9zlm9i9gb1fcu+7+splVJzB0tF4wn0HB5ZFZt5nZMcDLQNNgHVe6e3szaxksT/vg/scAvxIY9nox8BCBQHkpUCZYvvOA/xDowbwS6J3lPfOs977aJfWvv46O/2BF0J9rVoW7CHIIGg1cH+4iyCH4of++nzkpRzhdEIxwar9IVrxUqYhowHc/W1jg38f/vKxRWOp21ASLcmRSsBi5FCxGNgWLkU3BYgRTsBjh1H6RTMHi4XdUDkMVERERERE5EoXxSRgFpmBRREREREQkRMI5YU1BHbWzoYqIiIiIiMjBU8+iiIiIiIhIiERQx6J6FkVERERERCQ3BYsiIiIiIiKSi4ahioiIiIiIhEgkTXCjYFFERERERCRELILGdkZQUUVERERERCRU1LMoIiIiIiISIpE0DFU9iyIiIiIiIpKLehZFRERERERCpFjkdCyqZ1FERERERERyU8+iiIiIiIhIiFgE3bOoYFFERERERCRENMGNiIiIiIiIRDT1LIqIiIiIiIRIBHUsKliUwjX121XhLoIcpCb1qoa7CHIIfuhfLdxFkENQ+8H54S6CHKSFTzcKdxHkEBxTQj+NJXKZ2cXAQCAKeNfdn9tHurOBucA17j5yf3nqiBAREREREQmRYoXw7AwziwJeBy4E1gILzGysu3+fR7p+wMT85Kt7FkVEREREREKkmBX8lQ/nAL+6+wp33wMMBTrmka4rMApIyldZ81knEREREREROTIdD6zJsrw2uC6TmR0PXAa8ld9MFSyKiIiIiIiEiJkdzOt2M1uY5XV7zmzzeCvPsfwy0MPd0/NbVt2zKCIiIiIicgRz93eAd/aTZC2QdXa7qsC6HGkaAUMtMB1rJaCdmaW5++f7ylTBooiIiIiISGRbANQ0sxrAH8C1wPVZE7h7jb1/m9kgYNz+AkVQsCgiIiIiIhIyxQrhQYvunmZm9xKY5TQKeN/dl5vZncHt+b5PMSsFiyIiIiIiIiFSCLEiAO4+AZiQY12eQaK735qfPDXBjYiIiIiIiOSinkUREREREZEQKYxhqIVFPYsiIiIiIiKSi3oWRUREREREQqRYscjpWVSwKCIiIiIiEiIRNApVw1BFREREREQkN/UsioiIiIiIhIgmuBEREREREZGIpp5FERERERGREDH1LIqIiIiIiEgkU8+iSND3S//HyE/fJcMzaNrsQi669Ips25d8O49xn32KmVGsWBRXXteFk0+tk7k9IyOd5594gLLlKnLXfb2y7fv1l5/z+fBBPDdwMKXLxIakPkXN7DmzeeHFF8jIyKBTx07cesut2ba7Oy+8+AKzZs8iJiaGPo/1oVatWqxctZJHHnkkM90f6/7gjtvv4Prrrgdg6LChDB8xnOioaM477zy6d+seymoVGe7Os/37M2NmoH2e7tuHOrVr50q39o8/eLBnT7Zt207tWrV47qknKV68OCt+/53effry/Y8/0u2eu+l8880A/L5yJQ883DPb/vfeeSc33XB9yOp2tHv2xlpcUL8Sm1L20O6p+Xmm6X1VTVrWrcjO1Ax6DP6e5Wt2ANC8TgV6XVWTKDOGz17P25NWAVC2VDQDu9SjasUY1m7aRbd3l7F9Z1rI6lSUzJkzm5cGvEhGRgYdOnTklptvzbbd3XnppReZPWcWMSVj6N37cWrVqgXA0GFDGDPmc9ydjh07cd21geNq27Zt9Or1COvWr+e4KlV4+ulniY3Vd9/hNnPWLPq90J+M9Awuv6wTXTrflm27u9Ov//OZ59Un+/alTu3a7N69m87/7MKePXtIT0+nTes23HPXXQC8OGAA02ZMp3h0capVq8oTffoSW6ZMOKp3VIugJ2eoZ7EoMLOKZrY4+NpgZn9kWS4R7vIdCTIy0hn+8dvcff9j9HrqVRbNm8H6P9ZkS3Na7Qb07PsyPfu+zI23deXTQa9n2z7lq3EkVKmaK+8tm5P5cfliyleMK9Q6FGXp6en0e74frwx8hRHDRjBx4kRWrFiRLc2s2bNYs2YNn436jEd7Psqz/Z4FoPqJ1fn0k0/59JNP+WjwR8SUjKFVy1YALFy4kOnTpzP006EMHzacm268KeR1KypmzJrF6tVrmDDmc/r06sWTzz6bZ7oBr7zCTTfcwIQxnxMbG8uozz8HoGzZsjz80IPcelP2NqpRvTqjhg5h1NAhDP/kY2JiYmjdqlVhV6dIGT13A7e9tnif21vUrUj1+FK07jOXXp/8SN9rTwMCP5b6XHMaXV77joufnEf7RvGcUrkUAHe0PZE5P22hTZ+5zPlpC3e0PTEUVSly0tPT6f/C87w8YCBDhwxn0qRJrPg9+7lz9pzZrFmzmpEjRvNwz0d4/vnnAPjtt18ZM+ZzPnj/Qz7+6FNmzZzJ6tWrARg8+EManX02o0aOptHZZzN48Ichr9vRLj09nWf6Pcebr77G56NG8d8vv+S3Fb9lSzNz1kxWrV7NuDFjeKxXL5569hkASpQowbtvv8PIYcMZPmQos+bM5rslSwA4t0kTRg8fwajhwznxhBN57/33Q163oqBYMSvwK2xlDds7S8i4+yZ3b+juDYG3gAF7l919z772M7Mi0/O8csUvVIqvQqX4ykRHF+fMxuezZPG8bGlKxhyTOcZ89+5d2R6Ss2XzRpYvWUjT5hfmynvUkPfpdNUtRNBFpIizfPlyqlWtRtXjq1K8eHEuuugipk2fli3NtOnTaNeuHWZG/fr1SUlJYePGjdnSLFiwgOOrHk+VKlUAGDlqJLfccgslSgSuqVSoUCE0FSqCpkydRof2l2JmnN6gPikpO0hOTs6Wxt2Zt2ABF7VuDUDH9u2ZPGUqABUrVKB+3bpER+/7tDV3/nyqVa3KccdVKbR6FEULft3K1j/33evXpkElPpu3AYDFK7cTWyqauNgSnF49llXJf7Fm0y5S053xi5Joc3pc5j6j564HYPTc9Vx4eqXCr0gR9P33y6latRrHB8+dF154IdNznDunT5/GJe0Cx2b9evVJ2RE4d65cuZJ6desTExNDdHQ0Z5x5JtOmTQ3sM2Mal7ZrD8Cl7dozbfrUENfs6Lds2TJOqFqNqlUDbXdx27ZMmTo1W5opU6fxj/btg+fVBqSkpJCcnIyZUapU4MJMWloaaWlpmb9vmp57buZ5tEH9+iQmJYa0XnLkUbBYRJnZWWY2zcwWmdlEM6sSXD/VzJ4xs2lA9+DyADObbmY/mNnZZjbazH4xs6fCXI3DZtvWzZSv8PePkfLlK7Jty+Zc6b5bNJcnH7mHtwY+xQ2d781cP2rIe4GAMMcNy0u+nU+58hWpekKNwiu8kJScREJCQuZyfHw8SclJ2dIkJyVTOaFy5nJCfAJJSdnTTPxqIm0vapu5vHr1ahYvXswtnW/h9jtuZ/n3ywupBpKYlETlLG2YEB9PYo5gcevWrZQpXSbzh0xCQjxJOdLsz38nTqJd27YHTiiHVUK5kqzfsitzecOW3SSUKxlcvzv7+rIlAahUpgTJ2wPXMpO376FiGQ2CKQxJyckkxGc9dybkukiTnCtNPMnJSZx00sl8u/hbtm3byq5du5g9ezaJiYHAYvPmzVSqFPhOrVSpElu2bAlBbYqWxOQkEipnPWcmkJSUve2SkpJyf+8FvxvT09O56tpraNmmNec2bkKD+vVzvcdnY8ZwftPzCqkGEikULBZNBrwKXOnuZwHvA09n2V7O3Vu4+4vB5T3u3pxAr+QY4B6gHnCrmVXMlbnZ7Wa20MwWjh8zvFArcri4e+6VeXQFnn5WE3o/8zq339uT8Z99CsDSxQsoE1uWE6qfki3tnt27mThuBJd2uq4wiixZ5dl8liNJ7kRZg/vU1FSmT59Om9ZtMtelpaexfft2Br0/iG7dutGzZ8+8/6/IIcuzfXK1YW75nVAuNTWVqdOncdGFbQ6cWA6rvNrIPc9TbJ7/D6QQ5XE+y3Xc5fn9aNSoUYObb7qZrl3vpft93ahZsyZR0VGFVVLJKe9myZFk3+0bFRXFiKHD+OrLiSxbvoxffv01W7p33n2X6OgoLm3X7rAVWf5mZgV+hUuRGWYo2ZQkEOx9FfzPFwWsz7J9WI70Y4P/LgWWu/t6ADNbAVQDNmVN7O7vAO8AfDXrh4j45i9XviJbNv89JHHLlk2ULbfvIYennFaXjckb2JGynRW//sjSxQtYvmQRqamp7Nr1Fx++M4A27S5j08Yknn38PgC2btlEv77/4sHe/YktW76wq1SkxMfHZ17RhsDV1Li4uFxpNiRuyFxOTErMlmbW7FnUqlWLihX/vv6REJ9Aq1atMDPq1a2HFTO2bt1K+fJqv8NhyLDhjPzsMwDq1a3DhixtmJiURHxc9qGH5cuVI2VHCmlpaURHR5OYmERcpfzdCzxj1ixq16pFpYq5rm9JIduwZTdVyscA2wCoXL4kSdt2UyLaqFK+ZGa6wPpAb+LGlD3ExQZ6F+NiS7ApZZ93TMghiI+PzzbMMCkpkUo5jrvcaf4+7jp06EiHDh0BeOPN14mPiwcCQ/Y3btxIpUqV2Lhxo86ZhSAhPp7EDVnPmYm5vvcS4hP2+70HEFumDI3OasSs2bOpeUrgoveYL8YyfcZ0/vPW2xH1iAcpHOpZLJqMQNC3977F+u5+UZbtf+ZIv3ecUEaWv/cuHxUXHE6sUZPkxPVsTE4kLS2V/82bSYOG52RLk5y4PvMK65pVv5GWlsaxpcvQ8cqbeOrF93ii/3/ofOe/ObVWA265/X6Or1qd5wZ+yBP9/8MT/f9DufIV6fH4SwoUC0GdOnVYs2YNf/zxB6mpqUyaNInmzZpnS9OiWQsmTJiAu7N06VJKly6dOUwKYOKk7ENQAVq0aMHChQsBWLVqFWmpaZQrV67Q61NUXHfN1ZmTz1zQsiVjx43H3fluSaB9cv6oMTPOadSISd98A8CYceO4oGWLfL3XhC8n0q7txYe9DnJg3yzdyGWNA0PhGlaPJWVnOsnb97BkVQonxpeiasUYikcZl54VzzdLAhftvlmykcubBO4tvbxJFb5esnGf+cvBq127DmvWrGbdusC586uvvsp17mzWrDn/nRA4Npcuy37u3Lw5cLvGhg0bmDp1ChcFz6HNmjVn/IRxAIyfMI7mzfJ3nEr+1a1bl1VrVrM2+L335cSJtGzRMluali1a8MW4ccHz6hLKBM+rm7dsZntKCgC7du1i7rx51KheHQjMsPrBoEG88vLLHHPMMSGuVdFRzKzAr3A5Kn7oS4HtBuLM7Fx3n2NmxYFT3b3I3pAVFRXF1Tf+H6+/1BfPSKfJ+W2ocvwJzJjyJQDNWl3M4kVzmDd7ClFRURQvUZLb7nxAV9yOENHR0Tz44IN07daV9Ix0OvyjAyeffDIjR40E4MorruS8885j1uxZdLq8EzExMTze+/HM/Xft2sX8efN5tOej2fLt2KEjTzz5BFdfezXFixenz+N91OaFpPn55zNj5iwu6diRY2JieLJPn8xtd3XtRt/HehMfF8f93brxYM9HePX1N6hd6zQu79QJgI0bN3LNjTex488/KWbGx58OYczIEZQuXZqdO3cyZ948Hn/0kbzfXA7JgM51aXxqOcqXLs7Mp5sycPzvREcFjpMhM9YxddkmWtatyOS+57JzTzo9PvoBgPQMp++wn/ng3oZEFTNGzFnHL+sD1yrfnrSKV7rU46qmVVi3eRdd310WtvodzaKjo3nggYfo1r0bGRnp/KN9B0466WRGjx4FwOWXX8F5Tc9j9uxZXHHlZcTExNC712OZ+z/cswfbtm0LnIMfeCjz8Ri33HwLjzzak7Fjx1K5cgLPPP1cWOp3NIuOjuaRHj246567Sc/IoFOHjpxy8skMHzkCgKuvvIpm55/PjJkzubRjh8CjM4Ln1Y3JG+n1+GOkp2eQ4Rm0vfBCWjQPXCR4tl8/9qTu4Y7gozQa1K9P70d75VkGOXiR9FPCdP9N0WJmfYAdwNfAK0BZAhcNXnb3/5jZVOABd18YTJ+5bGYtg3+3z7ltX+8XKcNQJbcm9XI/BkQiR0x0BH0TSS61H8z7eYVy5Fv4dKNwF0EOwTEl1I8SyUoeWyoivvxmLvylwL+Pz29UMyx10xFRxLh7nyyLzfPY3nJfy+4+FZi6r7QiIiIiIrJ/4XxuYkHpnkURERERERHJRT2LIiIiIiIiIRLOCWsKSsGiiIiIiIhIiETSZHkahioiIiIiIiK5qGdRREREREQkRCJofhv1LIqIiIiIiEhu6lkUEREREREJkUi6Z1HBooiIiIiISIjoOYsiIiIiIiIS0dSzKCIiIiIiEiKR9JxF9SyKiIiIiIhILgoWRUREREREJBcNQxUREREREQmRCBqFqp5FERERERERyU09iyIiIiIiIiESSY/OULAoIiIiIiISIpoNVURERERERCKauXu4yyBHsa1btus/WITauSs13EWQQ1CpbEy4iyCH4M/d6eEughykRo8uDHcR5BAs798k3EWQQ1Dy2FIR0WX3/c9rC/z7uM6pVQ9YNzO7GBgIRAHvuvtzObbfAPQILu4A7nL37/aXp3oWRUREREREIpiZRQGvA5cAdYDrzKxOjmS/Ay3cvQHwJPDOgfLVPYsiIiIiIiIhUkj3LJ4D/OruKwDMbCjQEfh+bwJ3n50l/Vyg6oEyVbAoIiIiIiISIoU0G+rxwJosy2uBxvtJ3wX474EyVbAoIiIiIiJyBDOz24Hbs6x6x92zDiPNKwLN895IM2tFIFg8/0Dvq2BRREREREQkRA5mFGowMNzfPYZrgWpZlqsC63K/tzUA3gUucfdNB3pfTXAjIiIiIiIS2RYANc2shpmVAK4FxmZNYGYnAKOBm9z95/xkqp5FERERERGRECmMCW7cPc3M7gUmEnh0xvvuvtzM7gxufwt4DKgIvGGBMqS5e6P95atgUUREREREJESscCa4wd0nABNyrHsry9//BP5ZkDw1DFVERERERERyUc+iiIiIiIhIiBTScxYLhXoWRUREREREJBcFiyIiIiIiIpKLhqGKiIiIiIiEiIahioiIiIiISERTz6KIiIiIiEiIWAT1LCpYFBERERERCZFihfScxcKgYagiIiIiIiKSi3oWRYLmzJnNSwNeJCMjgw4dOnLLzbdm2+7uvPTSi8yeM4uYkjH07v04tWrVAmDosCGMGfM57k7Hjp247trrAXjl1YHMnDmD4tHFOb5qVXr3eowyZcqEumpFwrx5c3nttZdJT0/n0kv/wQ033Jxt+6pVK+nX72l++eVnunS5g2uDbbR79266d7+b1NRU0tPTadGiFZ07/xOAvn17s3r1agB27EihdOkyvPfeh6GtWBHh7jz7fH9mzJpJTEwMT/ftS53atXOlW/vHHzz4cE+2bdtG7dq1eO6ppyhevDgrfv+d3o/34fsff6TbvffQ+eZA+6/fsIFHej/Gxk0bKWbFuPKKy7np+utDXb2jWmGcO7dt20avXo+wbv16jqtShaeffpbY2NhQV+2o9+yNtbigfiU2peyh3VPz80zT+6qatKxbkZ2pGfQY/D3L1+wAoHmdCvS6qiZRZgyfvZ63J60CoGypaAZ2qUfVijGs3bSLbu8uY/vOtJDVqSiZOWsW/V7oT0Z6Bpdf1okunW/Ltt3d6df/eWbMnEVMTAxPBs+ru3fvpvM/u7Bnzx7S09Np07oN99x1FwA//vQTTz79NHv27CYqKopHez5C/Xr1wlG9o9pRNcGNmaWb2eIsr4cPxxub2Uozq3Q48joczKycmd2dZbmYmb1iZsvMbKmZLTCzGsFtj+Qzz3yl28e+t5pZspl9a2a/mNlEM2t6sPnlkX/O+h5nZiMPV/6RJj09nf4vPM/LAwYydMhwJk2axIrfV2RLM3vObNasWc3IEaN5uOcjPP/8cwD89tuvjBnzOR+8/yEff/Qps2bOzAwwzjmnMZ9+MpRPPhnCCdVO4MMPB4W6akVCeno6Awe+QL9+L/Lhh58yefLXrFz5e7Y0sbGxdOt2P9dcc1229SVKlOCll17lvfcG8+67HzJ//lyWL18GwOOPP8l7733Ie+99SIsWLWnevEXI6lTUzJg5i9WrVzNhzBj69OrFk888m2e6AQNf4aYbbmDC2DHEloll1GefA1C2bFke7vEQt958U7b00VFRPPiv+/li9Gg+HfwhQ4cN57ffVuSRsxyMwjp3Dh78IY3OPptRI0fT6OyzGTxYF2kKw+i5G7jttcX73N6ibkWqx5eidZ+59PrkR/peexoAxQz6XHMaXV77joufnEf7RvGcUrkUAHe0PZE5P22hTZ+5zPlpC3e0PTEUVSly0tPTeabfc7z56mt8PmoU//3yS35b8Vu2NDNnzWTV6tWMGzOGx3r14qlnnwEC33vvvv0OI4cNZ/iQocyaM5vvliwBYMDAl7nzjtsZMXQY99x1FwMGvhzqqskRJj/DUHe6e8Msr+cKvVThUQ64O8vyNcBxQAN3rw9cBmwNbstvEHjQwWLQMHc/w91rAs8Bo80s96X2fTCz/fUclyNLfd19nbtfedAljXDff7+cqlWrcfzxVSlevDgXXngh06dPy5Zm+vRpXNLuUsyM+vXqk7IjhY0bN7Jy5Urq1a1PTEwM0dHRnHHmmUybNhWAJo2bEB0daIZ69eqRlJQY6qoVCT/++D3HH1+V4447nuLFi3PBBW2YNWtGtjTly1egVq06REVlPyzMjFKlAj9y0tLSSEtLy3XjubszZcpkWre+sHArUoRNmTaVDu3bY2ac3qABKSkpJCcnZ0vj7sxbsICL2rQGoOM/2jN56hQAKlaoQP26dTOPt73i4uIyeyiPPfZYTqpRg8TkpBDUqGgorHPn9BnTuLRdewAubdeeadOnhrhmRcOCX7ey9c999/q1aVCJz+ZtAGDxyu3EloomLrYEp1ePZVXyX6zZtIvUdGf8oiTanB6Xuc/ouesBGD13PReefsT0CxxVli1bxglVq1G1auDYu7htW6ZMnZotzZSp0/hHHufV/X3vGcafO/4EIGXHDuLi4kJar6LCrOCvcDnoexaDPYPPmNkcM1toZmcGe79+M7M7g2lamtl0M/vMzL43s7fMLNd7mtm/gj14y8zsvuC6J82se5Y0T5tZt2Ce08xsuJn9bGbPmdkNZjY/2AN4cjB9nJmNCvYILjCz84Lr+5jZ+2Y21cxWmFm34Fs8B5wc7D3tD1QB1rt7BoC7r3X3LWb2HHBMMN0nwTw/N7NFZrbczG4PrsuWzsyqm9myLPV5wMz6BP/uFvx8lpjZ0Lw+b3efArwD7M1/qpk1Cv5dycxWBv++1cxGmNkXwCQzK21m35jZ/4KfT8e86pu1fGYWY2YfBNN/a2atsuQ92sy+DPZ2Pp+//y1HvqTkZBLiEzKX4+MTcv1QTc6VJp7k5CROOulkvl38Ldu2bWXXrl3Mnj2bxMTcQeEXX4zl3HMPW+ewZJGcnExc3N9tExcXl6v99ic9PZ0uXW6hU6dLadTobOrUqZtt+5IliylfvgJVq1Y7bGWW7BKTkqhc+e82TEiIJzEpextu3bqVMmVKZwaECQkJJCXlv53/WLeOH376iQYaUnXYFNa5c/PmzVSqFAgyKlWqxJYtW0JQG8kpoVxJ1m/Zlbm8YctuEsqVDK7fnX192ZIAVCpTguTtewBI3r6HimVKhLbQRURichIJWc+Z8bnPh0lJSVROqJw9TfBiWXp6Olddew0t27Tm3MZNaFC/PgAPPfAALw18mQsvuZiXBgyg+71dQ1CboqdYMSvwK1zyc8/iMWa2OMvys+4+LPj3Gnc/18wGAIOA84AYYDnwVjDNOUAdYBXwJXA5kDnc0czOAjoDjQED5pnZNOA9YDQwMBhgXhvMqz5wOlAb2AysAN5193OCwWVX4D5gIDDA3Wea2QnAxOA+ALWAVkAZ4CczexN4GKjn7g2D5aoKzDSzZsA3wMfu/q27P2xm9+5NF3Sbu282s2OABWY2Kmc6M6u+n8/4YaCGu+82s3L7Sfc/4I79bN/rXAI9opuDvYuXuft2Cwz7nWtmY/Oob9by3QPg7vXNrBaBoPPU4LaGwBnAbgKf3avuviYfZTqyuedaZeTuXcqdyKhRowY333QzXbveyzGlSlGzZk2ioqOyJfvgg/eJio7m4osvOazFln3L2Tu4P1FRUbz33oekpKTQu3dPVqz4jZNOOjlz+zfffE3r1m0Ko5gStI/DKx9p8tfOf/31F/c/8AA9Hvg3pUuXPogSSp4K+dwp4ZXX4eUOeR11Th7tLIUnP+fMPBLtPT6joqIYMXQY21NSuP/f/+KXX3+l5imnMHzkCB7897+5sHUbJk6axONP9OU/b71dGDWQCHEww1CHZdk2NvjvUmCeu6e4ezKwK0vQM9/dV7h7OjAEOD9H/ucDn7n7n+6+g0CA2MzdVwKbzOwM4CLgW3ffFNxngbuvd/fdwG/ApCzlqB78uw3wWjDQHQvEmtnemUXGu/tud98IJAF/X5oJcve1wGlATyAD+MbMWu/jM+pmZt8Bc4FqQM19pNuXJcAnZnYjsL+7wPP76/crd9+cZZ9nzGwJ8DVwPHnUN4fzgY8A3P1HAoH+3mDxG3ff5u67gO+BXDcjmNntwd7mhYMGfZDPIodXfHw8iVmGiCYlJVIprtIB0iQRVykwPKNDh44MHvwxb7/1DrGxsVTL0gM1fvw4Zs6ayRN9n4yo5+pEkkBP4t9tk5ycnNkrURBlypShYcMzmD9/Xua6tLQ0ZsyYSqtWChYPtyHDhnHFNddyxTXXEh8Xx4YNf7dhYmIS8TmGP5UvX46UlB2kpaUF0yQSF3fgdk5NTeW+Bx7g0kvacWHrfZ3G5WAU1rmzQoUKbNy4EYCNGzdSvnz5wq6K5GHDlt1UKR+TuVy5fEmStu1mw9bdVClfMsf6QG/ixpQ9xMUGehPjYkuwKWVPaAtdRCTEx5OY9ZyZlJhryGhCfAIbEjfsN01smTI0OqsRs2bPBmDsuHG0uSBwnrzowgtZtnx5YVWhSCtmVuBX2Mp6iPvvHYOQkeXvvct7ey1zXtbIuby/2r8L3Eqg5/H9PN4353tnfd9iwLlZgtzj3T0lj/3T2UcPazCg/K+7Pwg8A3TKmcbMWhIITM9199OBbwn0ruaURvbPO2uaS4HXgbOARbbvew3PAH7II7+c7/dnlr9vAOKAs4K9iIn7KF9W+2uTA3527v6Ouzdy90a33tr5AG91ZKhduw5r1qxm3bo/SE1N5auvvqJ5s+bZ0jRr1pz/ThiPu7N02VJKly6dGZBs3hyIzTds2MDUqVO46KK2QGCWwMEfDeaF/i8SE3Ogj10O1mmn1Wbt2rWsX7+O1NRUJk/+mqZNc16XytvWrVtISQmcGnbv3s2iRQs54YS/r4HsXY6Pjy+Ushdl111zDaOGDWXUsKFc0KolY8eNw935bskSSpcunetHjZlxTqNGTPr6GwDGfDGOC1q23O97uDuP9X2Ck2rU4JabbiykmhRdhXXubNasOeMnjANg/IRxNG+myaXC4ZulG7mscWAYY8PqsaTsTCd5+x6WrErhxPhSVK0YQ/Eo49Kz4vlmSSC4/2bJRi5vUgWAy5tU4evgejm86taty6o1q1n7R+DY+3LiRFq2aJktTcsWLfgiy3m1TPC8unnLZrYHv/d27drF3HnzqFG9OgBxleJYuGgRAPPmz+eEaieEslpyBArFozPOscAsoqsITBrzTo7t04FBwXv8jMBEMnuns/sMeAIoDhR0rvNJwL1AfwAza+jui/eTPoXAsFSC6c8ENrj7uuAw2AYEegABUs2suLunAmWBLe7+V3DIZpMseWZNlwjEm1lFYAfQHvgymHc1d59iZjOD9cw1RsrMWhC4X7FVcNVKAsHlfGB/E9OUBZLcPTV47+HeX8HZ6pvDdAJB5uTg8NMTgJ+AM/fzPhEtOjqaBx54iG7du5GRkc4/2nfgpJNOZvToUQBcfvkVnNf0PGbPnsUVV15GTEwMvXs9lrn/wz17sG3bNqKjo3nwgYcyp3h/4cX+7Nmzh67d7gGgXr36PNyjZ+greJSLjo6me/d/8eCD95ORkc4ll7SnRo2TGDPmMwA6dryMTZs2cccdt/HXX39iVoyRI4fx4YefsmnTJp599kkyMjLIyMigVavWNG16Xmbekyd/zQUXaGKbwtb8/POZMXMml3ToyDExMTzZp0/mtrvu7Urfxx4jPj6O+7t348GHe/LqG69T+7RaXN6pExDofbrmhhvZ8eefFDPj408+Zcyokfz8yy98MX48NWuewhXXXAtA93vvpXmz/F1MkP0rrHPnLTffwiOP9mTs2LFUrpzAM08frXPrhdeAznVpfGo5ypcuzsynmzJw/O9ERwWuFw+ZsY6pyzbRsm5FJvc9l5170unxUeB6dXqG03fYz3xwb0Oiihkj5qzjl/WB69RvT1rFK13qcVXTKqzbvIuu7y7b5/vLwYuOjuaRHj246567Sc/IoFOHjpxy8skMHzkCgKuvvIpmwfPqpR07BB6dETyvbkzeSK/HHyM9PYMMz6DthRfSonngIs/jvXvTr39/0tPTKFGyJI/36hWuKh7VImmkmeV5L0HWBGbpBIZ37vVl8H68lUAjd99oZrcG/743uM9KoBFQD3gMSCZwr+F04G53z8ix/7+AvQ+HedfdX87y/m8BW9394eByS+ABd28fXJ4aXF6YdVvw/rzXCdynGA1Md/c7g5PK7HD3F4L7LwPau/tKM/uUQFD4XwL3KT4N7B1nMT9Y9l1m1g/oQOAewtuAzwkM7/yJQC9eH3efmjWdu98QnEynG/A78AeBgO9pYAqBoM4I3Bv5XPAz7R9MVyq4zxPuPitY7lrAcAKB52TgRnevnkdbVAK+IBBwLyZwX+kledT3dWCcu9czsxgC95yeRaAH81/BYDZn3uOAF9x9Kvuwdct23cQQoXbuSg13EeQQVCqrnuxI9ufu9HAXQQ5So0cXhrsIcgiW929y4ERyxCp5bKmIiMK2bN5W4N/H5SuUDUvdDhgsHlLmOQK7g9i/GIGA7Cp3/+UwFk1CRMFi5FKwGNkULEY2BYuRS8FiZFOwGNkULB5+h3rPYqExszrArwQmVFGgKCIiIiIiEkKFes9icHji1IPc93vgpMNZHhERERERkXCKpHsWj9ieRREREREREQmfUMyGKiIiIiIiIhDW5yYWlIJFERERERGREImgWFHDUEVERERERCQ39SyKiIiIiIiEiCa4ERERERERkYimnkUREREREZEQiaQJbtSzKCIiIiIiIrmoZ1FERERERCREIqhjUcGiiIiIiIhIqERSsKhhqCIiIiIiIpKLehZFRERERERCxIicrkX1LIqIiIiIiEgu6lkUEREREREJEd2zKCIiIiIiIhHN3D3cZZCj2J6tW/QfLEJlFC8R7iLIIYiKpMuWkkuGzpwiYVH3wbnhLoIcgl/fuCAivvz2/PVXgc/yJUqVCkvd1LMoIiIiIiIS4czsYjP7ycx+NbOH89huZvZKcPsSMzvzQHkqWBQREREREQkRO4jXAfM0iwJeBy4B6gDXmVmdHMkuAWoGX7cDbx4oXwWLIiIiIiIike0c4Fd3X+Hue4ChQMccaToCgz1gLlDOzKrsL1MFiyIiIiIiIpHteGBNluW1wXUFTZONgkUREREREZGQ8QK/zOx2M1uY5XV7jkzzGq2acyKd/KTJRs9ZFBEREREROYK5+zvAO/tJshaolmW5KrDuINJko55FERERERGRyLYAqGlmNcysBHAtMDZHmrHAzcFZUZsA29x9/f4yVc+iiIiIiIhIBHP3NDO7F5gIRAHvu/tyM7szuP0tYALQDvgV+AvofKB8FSyKiIiIiIiEiu/3NsFDyNYnEAgIs657K8vfDtxTkDwVLIqIiIiIiIRK4cSKhUL3LIqIiIiIiEgu6lkUEREREREJmcjpWlTPooiIiIiIiOSinkUREREREZFQKaQJbgqDehZFREREREQkF/UsioiIiIiIhEpGRrhLkG/qWRQREREREZFc1LMoEuTuPPfSS8yYPYeYmJI81bs3dWrVypVu7bp1PNSrF9u2bad2rdN4tk8fihcvzoJFi+j24EMcf9xxALRu2ZK7/tkFgLadOlGq1LFEFStGVFQUwz4cFMqqFQmzZs2i3wsvkJGezmWXXUaXzp2zbXd3+vXvz8yZM4mJieHJvn2pXbt25vb09HSuu/FG4uPieO2VVwDYtm0bDz38MOvWreO4446jf79+xMbGhrReRcXMWbN4rn9/0jMyuKJTJ/55223Ztrs7zz7/PDNmzSImJoan+/alTrD9DrTvB4MH8+KAAcyYPJny5cuHrE5FxcxZs+j3Qn8y0jO4/LJOdOmcu+369X+eGTNnZR57dWrXZvfu3XT+Zxf27NlDeno6bVq34Z677gLgxQEDmDZjOsWji1OtWlWe6NOX2DJlwlG9o15htN+PP/3Ek08/zZ49u4mKiuLRno9Qv169cFTvqPbsjbW4oH4lNqXsod1T8/NM0/uqmrSsW5GdqRn0GPw9y9fsAKB5nQr0uqomUWYMn72etyetAqBsqWgGdqlH1YoxrN20i27vLmP7zrSQ1amocN2zeGQws4pmtjj42mBmf2RZLpEj7X1mViofeU41s0bBv1ea2VIz+87MJplZ5cKqS36Z2a1m9lq4yxGJZsyew6o1axg/cgSPP9yTp55/Ps90A157nZuuvY7xo0YSWyaW0WPHZm47s2FDRn78ESM//igzUNzr/TdeZ+THHylQLATp6ek8068fb7z6Kp+NGsWXX37JbytWZEszc9YsVq9ezRdjxvBYr1489eyz2bZ/MmQIJ9WokW3d+x98wDnnnMMXY8Zwzjnn8N4HHxR6XYqi9PR0nnruOd587TXGjhrFhC+/5LfffsuWZsbMmaxevZoJY8bQp1cvnnzmmXztu37DBubMnUuVymE/PR+VAsfec7z56mt8PmoU//3yS35bkb3tZs6ayarVqxmXeewF2q5EiRK8+/Y7jBw2nOFDhjJrzmy+W7IEgHObNGH08BGMGj6cE084kffefz/kdSsKCqv9Bgx8mTvvuJ0RQ4dxz113MWDgy6GuWpEweu4Gbntt8T63t6hbkerxpWjdZy69PvmRvteeBkAxgz7XnEaX177j4ifn0b5RPKdUDvwEvqPticz5aQtt+sxlzk9buKPtiaGoihzBjupg0d03uXtDd28IvAUM2Lvs7ntyJL8POGCwmIdW7n46sBB4JOsGCwjZZ2xm6ik+BFOmT6fDJe0wM06vX4+UlB0kb9yYLY27M3/hQi68oBUAHS5tx+Rp08NRXMli2bJlVKtalapVq1K8eHEubtuWqVOnZkszZepU/tG+PWZGgwYNSElJITk5GYDExERmzJjBZZ06Zd9n2jQ6tG8PQIf27ZmSI085PJYuW8YJ1apRLdh+l7Rty+Sc7RdsCzPj9Cztd6B9n3/hBf7VvTtmFtpKFRHLli3jhKrVsh17OY+TKVOnZR57WdvOzChVKvC1m5aWRlpaWmY7NT33XKKjA19pDerXJzEpMaT1KioKq/0M488dfwKQsmMHcXFxIa1XUbHg161s/XPfvX5tGlTis3kbAFi8cjuxpaKJiy3B6dVjWZX8F2s27SI13Rm/KIk2p8dl7jN67noARs9dz4WnVyr8ihRF7gV/hclRHSzmxcxam9m3wR7B982spJl1A44DppjZlGC6N81soZktN7O++ch6OnCKmVU3sx/M7A3gf0A1M+tvZsuC73lNMP8qZjY92Mu5zMyaBdfvMLMXzex/ZvaNmcUF159sZl+a2SIzm2FmtYLrB5nZS8Fy99tPvf8VfJ9lZnZflvWfB/Ncbma3Z1m/w8yeDvaazjWzhOD6q4J5fGdmR1WUlJScTOWE+MzlhPh4koLBxF5bt22jTJkymT9iKudI893SpVxxw43ced99/JqlZ8sw7ujWjatvvoURn31euBUpgpKSk6mcpecoPj6exKSk7GmSkkhISMhcztq+z7/wAvd3706xYtlPiZs3bcr8kRMXF8fmzZsLqwpFWlJSEpWztk1CQq5jLzEpKVsbJyQkkJiUtN99p0ydSnx8PLVOO62Qa1B0JSYnkVA563GVQFJS9rYLtFHl7GmSA8dneno6V117DS3btObcxk1oUL9+rvf4bMwYzm96XiHVoGgrrPZ76IEHeGngy1x4ycW8NGAA3e/tGoLaSE4J5UqyfsuuzOUNW3aTUK5kcP3u7OvLlgSgUpkSJG8P9Kckb99DxTIlkKKtqAWLMcAg4Bp3r0/gns273P0VYB2BXsJWwbSPunsjoAHQwswaHCDv9sDS4N+nAYPd/QygEdAQOB1oA/Q3syrA9cDEYK/n6cDi4L7HAv9z9zOBacDjwfXvAF3d/SzgAeCNLO99KtDG3f+dV8HM7CygM9AYaAL8n5mdEdx8WzDPRkA3M6uYpRxzg72m04H/C65/DGgbXN/hAJ9JRMl7/LgdOE3wSmrt02oxacznjPrkY66/6mq6P/hQZpLB/3mH4YMH8+bLAxg6ciQLv/32cBa9yMurXfLTk2TAtOnTqVChAnXq1CmEkkl+HPjI23cb72vfnTt38s5773Fv8B4qKST7PiVmSZJH2wVbOCoqihFDh/HVlxNZtnwZv/z6a7Z077z7LtHRUVzart1hK7JkUUjtN3zkCB7897/56r9f8uC/H+DxJ/JzzV0Ot7y+Bt1zn18h73aWwuOeUeBXuBS1YDEK+N3dfw4ufwg030faq83sf8C3QF1gX78kp5jZYiAW2HsT1Cp3nxv8+3xgiLunu3sigQDwbGAB0NnM+gD13T0lmD4DGBb8+2PgfDMrDTQFRgTf622gSpYyjHD39P3U+3zgM3f/0913AKOBZsFt3czsO2AuUA2oGVy/BxgX/HsRUD349yxgkJn9H4HPMxczuz3YK7vw3UGD9lOs8BsyYiRX3ngTV954E/FxldiQ+HdvVGJSEvFx2YdflC9XjpSUFNLSAsM+NiQlEV8pkKZ06WMzh+Q0P68paelpbNm6FYD4YO9UxQoVaN2yBcuWf1/YVStSEuLj2bBhQ+ZyUlJS5me+V3x8PImJfw9lS0xKIi4ujsXffcfUadO45NJL6dGzJwsWLqTno48CUKFixcyhqsnJyVSoUCEEtSl6EuLj2ZC1bRITcw1bq5yQkK2NExMTiY+L2+e+a9au5Y8//uCKa67honbtSExK4qrrr2djjqHlcmgS4uNJ3JD1uMrddgnxCWxI3LDfNLFlytDorEbMmj07c92YL8YyfcZ0nn3qaQ0jLiSF1X5jx42jzQWtAbjowgtZtnx5YVVB9mPDlt1UKR+TuVy5fEmStu1mw9bdVClfMsf6QG/ixpQ9xMUGehPjYkuwKSXnXVtyOHiGF/gVLkUtWPwzP4nMrAaB3rvW7t4AGE+gVzIvrYL3QN7s7lvzeJ88v+HcfTqBQPUP4CMzu3kf+TuBdtqa5X7Lhu5eO0uaA9UrzzKYWUsCvZ3nBnsKv+Xveqb635fy0wnOnOvudwK9CASWi7P0RGat2zvu3sjdG/3z1lsPULTwuu6qKzMnpLmgeQvG/ncC7s53S5dRunRp4iplDxbNjLPPOouvJk8BYOz4CbRqHoi7N27alNn7sXT5cjIynHJly/LXzp38+Wegif7auZPZ8+ZzysknhbCWR7+6deuyes0a1v7xB6mpqXw5cSItWrTIlqZlixZ8MW4c7s6SJUsC7RsXR/euXfnqyy/57/jx9Hv2Wc5u1Ihnn346sE/z5owdF7hmMnbcOFrlyFMOj3p167J69erM9vvvxIm0atkyW5qWLVowNth+32Vpv33te2rNmkyfPJlJEyYwacIEEuLjGfHpp1SqpPtvDqe6deuyas3qbMdeyxYts6XJeux9t2QJZYJtt3nLZranBK6T7tq1i7nz5lGjenUgMCHVB4MG8crLL3PMMceEuFZFR2G1X1ylOBYuWgTAvPnzOaHaCaGslgR9s3QjlzUODCFuWD2WlJ3pJG/fw5JVKZwYX4qqFWMoHmVcelY83ywJXEj7ZslGLm8S6I+4vEkVvl6iC2xFXVGbECUGqG5mp7j7r8BNBHr6AFKAMsBGAr2EfwLbgvfqXQJMPcj3nA7cYWYfAhUIBIgPmtmJwB/u/h8zOxY4ExhMIDC8EhhKYKjqTHffbma/m9lV7j7CApdYG7j7dwUowyAze45A4HhZsO4nAFvc/a/gPZBNDpSRmZ3s7vOAeWb2DwJB46b8fhhHsmbnNWX67Nm0u+JKYmJieKp3r8xtd913P30ffYT4uDjuv/ceHurVm1fffptap57K5R0Co3EnTZ7M8FGjiYqKIqZkSfo/9SRmxqbNm7nvoR5A4P6Odm0v4vxzzw1LHY9W0dHR9OzRg7vuuYeMjAw6dejAKSefzPCRIwG4+soraXb++cycOZP2HTsSExPDE336HDDf2zp35sEePfj888+pXLkyL+xjhlw5NNHR0TzSowd33H036RkZXNaxI6ecfDLDRowA4JqrrqL5+eczY+ZMLunQgWNiYngy2H772ldCY+/nf9c9gc+/U4eOwWMv0HZXX3kVzYJtd2nHDoFHLwTbbmPyRno9/hjp6RlkeAZtL7yQFs0Dg32e7dePPal7uCM4jLhB/fr0frRXnmWQg1dY7fd4797069+f9PQ0SpQsyeO91HaFYUDnujQ+tRzlSxdn5tNNGTj+d6KjAv0DQ2asY+qyTbSsW5HJfc9l5550enz0AwDpGU7fYT/zwb0NiSpmjJizjl/WBy5qvz1pFa90qcdVTauwbvMuur67LGz1O6qFcVhpQVkkPefjUASHe+4g0Hv2AoFAeQGBexZ3m1lX4B5gvbu3MrNBBO7xWwHsBsa6+yAzmwo84O4LzWwl0MjdN2Z5n+rAOHevF1w24HkCAacDT7n7MDO7BXgQSA2W62Z3/93MdgADgHbANgL3VyYHezvfJDD8tDgw1N2fCJZznLuPDL7frcBrwNYs1W8CXA3sfXjSu+7+spmVBD4Hjgd+AuKAPu4+1cx2uHvpYJ5XAu3d/VYzG01gqKoB3wD3+X7+E+3ZuqVo/Ac7CmUU103tkSxKw/YiWhhHHIkUaXUfnHvgRHLE+vWNCyLiy29XcmKBz/IxcQlhqVuRCRYjRdYg7WigYDFyKViMbAoWI5uCRZHwULAY2SIlWNyZuKHAZ/ljEiqHpW5FbRiqiIiIiIhI2IRzdtOCKmoT3BzxjqZeRRERERERiVzqWRQREREREQmVCLrXQD2LIiIiIiIikot6FkVERERERELEM3TPooiIiIiIiEQw9SyKiIiIiIiEiGZDFRERERERkYimnkUREREREZEQcc2GKiIiIiIiIpFMPYsiIiIiIiKhonsWRUREREREJJKpZ1FERERERCREIuk5iwoWRUREREREQkQT3IiIiIiIiEhEU8+iiIiIiIhIiLgmuBEREREREZFIpp5FERERERGRUImgCW7MPXJusBQ50pjZ7e7+TrjLIQdH7Re51HaRTe0X2dR+kUttJwWlYagih+b2cBdADonaL3Kp7SKb2i+yqf0il9pOCkTBooiIiIiIiOSiYFFERERERERyUbAocmg07j+yqf0il9ousqn9IpvaL3Kp7aRANMGNiIiIiIiI5KKeRREREREREclFwaKIiIiIiIjkEh3uAohEGjOr4e6/H2idiIj8zczKA9XI8tvD3f8XvhKJFC17j0F3XxLuskjk0D2LIgVkZv9z9zNzrFvk7meFq0ySP2ZmwA3ASe7+hJmdAFR29/lhLprkg5kVB+4CmgdXTQPecvfU8JVK8sPMngRuBX4D9v7wcHe/IGyFkgIzs+OBE8ke8E8PX4nkQMxsKtCBQJstBpKBae7+rzAWSyKIehZF8snMagF1gbJmdnmWTbFATHhKJQX0BpABXAA8AaQAo4Czw1koybc3geIE2hHgpuC6f4atRJJfVwMnu/uecBdEDo6Z9QOuAb4H0oOrHVCweGQr6+7bzeyfwAfu/riZqWdR8k3Bokj+nQa0B8oB/8iyPgX4v3AUSAqssbufaWbfArj7FjMrEe5CSb6d7e6nZ1mebGbfha00UhDLCJw7k8JcDjl4nYDT3H13uAsiBRJtZlUIXLB5NNyFkcijYFEkn9x9DDDGzM519znhLo8clFQziyI4DM7M4gj0NEpkSDezk939NwAzO4m/ezjkyPYs8K2ZLQMygw137xC+IkkBrSDQs69gMbI8AUwEZrr7guB585cwl0kiiO5ZFCmgYIDxf0B1st+3cVu4yiT5Y2Y3EBhGdSbwIXAl0MvdR4S1YJIvZtYa+IDAj1YjcO9UZ3efEtaCyQGZ2XLgbWApWS7QuPu0sBVKCsTMRgGnA9+QPeDvFrZCiUihU7AoUkBmNhuYASwiS6+Gu48KW6Ek34L3nrYmEGx84+4/hLlIUgBmVpLAkHADftSQuMhgZtPcvUW4yyEHz8xuyWu9u38Y6rJI/ukCtxwqBYsiBWRmi929YbjLIQdH0/dHHjO7wN0n55hYKpO7jw51maRgzOwlAr1RY8neK6VjL4IE7/E+Nbj4k2YiPvLpArccKt2zKFJw48ysnbtPCHdBpGD2NX0/gdlR5cjVAphM9oml9nJAweKR74zgv02yrNOxF0HMrCWB4fsrCfTsVzOzW/TojCNeKXfvEe5CSORSz6JIAZlZCnAsgavjqQS+NN3dY8NaMDkgM/sJqK/p+yOTmdVw998PtE6OLMFJpbq5+4Bwl0UOnpktAq5395+Cy6cCQ/SM4SObmT0FzNYFbjlYxcJdAJFI4+5l3L2Yux/j7rHBZQWKkWHv9P0SmfIaNjUy5KWQAnH3dAIPBZfIVnxvoAjg7j8TmB1VjmzdCYyI2mlm280sxcy2h7tQEjk0DFWkgMyseV7rNRQnImj6/ggUnJSoLlA2x32LsUBMeEolBTTbzF4DhgF/7l2pexYjykIzew/4KLh8A4H74OQI5u5lwl0GiWwahipSQGb2RZbFGOAcYJG7696bI5ym749MZtaRwAPBOxCYIGWvFGCou88OR7kk/8wsr8ebuM6bkSM4E/E9wPkEbr+YDryhGYmPfMGJ3WqS5eKaLnBLfilYFDlEZlYNeN7drwt3WWT/NH1/ZDOzc919TrjLISISKczsnwSGolYFFhOYZGqOLtRIfilYFDlEZmbAEnevH+6yyP5p+v7IZmYxQBcCQ1KzXiHX88KOcGaWADwDHOful5hZHeBcd38vzEWTAzCz4e5+tZkt5e9ZpDO5e4MwFEvyKdhuZwNz3b1hcFh/X3e/JsxFkwihexZFCsjMXuXvL8xiQEPgu7AVSApC0/dHto+AH4G2wBME7pn6IawlkvwaBHwAPBpc/pnA/YsKFo983YP/tg9rKeRg7XL3XWaGmZV09x/N7LRwF0oih4JFkYJbmOXvNAJTh88KV2Ek/9y9VbjLIIfkFHe/ysw6uvuHZvYpMDHchZJ9M7Nod08DKrn7cDPrCeDuaWaWfoDd5Qjg7uuDf96d83l9ZtYP0DP8jmxrzawc8DnwlZltAdaFtUQSUfToDJECcvcPgSEEZoH7Dpgf3hJJfplZWTN7ycwWBl8vmlnZcJdL8i01+O9WM6sHlAWqh684kg97z49/mllFgqMyzKwJsC1spZKDcWEe6y4JeSmkQNz9Mnff6u59gN4EevM7hbVQElHUsyhSQGbWEvgQWElgRrhqZnaLZhaLCO8TeNbi1cHlmwgMjbt8n3vIkeSd4Kx+vQjcd1qawI8fOXJZ8N9/EWizk81sFhAHXBm2Ukm+mdldwN3ASWa2JMumMoBG1UQAMzsdaBZcnOHue8JZHoksmuBGpIDMbBFw/d6HE5vZqQSGop4V3pLJgZjZYndveKB1EjnM7ER3XxXuckjezGwt8FJwsRhQkkAAuRtId/eX9rWvHBmCoy/KE3hO7cNZNqW4++bwlEryy8y6A/8HjA6uugx4x91fDV+pJJKoZ1Gk4IrvDRQB3P1nMysezgJJvu00s/PdfSaAmZ0H7AxzmSQfzOxc4HhgursnmVkDAj9cmwHVwlo42Z8oAj3AlmN9qTCURQ6Cu28jMGT4OgAziycwG3FpMyvt7qvDWT45oC5AY3f/EzLvM50DKFiUfFGwKFJwC83sPQIzM0JgRsZFYSyP5N9dwIdZ7lPcAtwavuJIfphZfwIzMS4GepjZOALD4p4B9NiMI9t6d38i3IWQQ2dm/yDQS3wckAScSGA24rrhLJcckAFZJ5NKJ/fFG5F9UrAoUnB3AfcA3QiccKcDb4S1RJIv7r4YON3MYoPL28NbIsmnS4EzgtO/lycwk18Dd/8lzOWSA9OP0qPHUwQeO/S1u59hZq0I9jbKEe0DYJ6ZfRZc7oQeWSMFoHsWRaTIMLNngOfdfWtwuTzwb3fvFdaCyX6Z2aKs9wTrPtPIYWYVdF/b0cHMFrp7IzP7jsDFmwwzm+/u54S7bLJ/ZnYmcD5/X+BOdHc9PkPyRcGiSAGZWXvgSQJDcKIJnHzd3WPDWjA5IDP71t3PyLHuf+5+ZrjKJAdmZlsJ/MCBwPHWLMsy7t4hDMUSKVLM7GsCvVLPApUIDEU9292bhrNcUnBmttrdTwh3OSQyKFgUKSAz+5XAoxaWug6giBKc9v1sd98dXD4GWOjuuufmCGZmLfa33d2nhaosIkWVmR1LYEKwYgTu1S8LfOLum8JaMCkwM1vj7poYTPJF9yyKFNwaYJkCxYj0MfCNmX1A4OHgtxF4ZqYcwbIGg8EA/4SsMxKLSOEysyhgjLu3ATLQeTPS6feL5JuCRZGCewiYYGbTCDwrDAA9L+zI5+7Pm9lSoDWB4YxPuvvEMBdL8ik4G+MLQAmghpk1BJ7QMFSRwuXu6Wb2l5mVDT5KQ45wZvYqeQeFBpQLbWkkkilYFCm4p4EdBJ4zVSLMZZECcvf/Av8NdznkoPQBzgGmQmB2WzOrHsbyiBQlu4ClZvYV8Ofele7eLXxFkv1YeJDbRLJRsChScBXc/aJwF0IKzswuB/oB8QSurmpyosiS5u7bzPQ0BpEwGB98SQRw9w+Dw4efc/cHw10eiVwKFkUK7mszu8jdJ4W7IFJgzwP/3969B9tV13cff38SwXBJABUQRgUDEeUWQGjl5gWEagUeSakIyvSBCio+IDLaCq0C6pRHK4j6IIJSrVRRsICXKlDCNUoJSSAJCNRy9YIiF0karoHP88dau9lJzjl770PO/u11zuc1c4a9fosz85nZs7PPd/0u3wNt31E6SIzKbZIOByZLmkHV6/TnhTNFTAi2s0+xYerlw6/v/H9GDC+noUb0SNJSYD2q/YrPktmpxpD0M9t7ls4RoyNpXeDvgP2pPndXUO07faposIgJQNK9DLEHzvb0AnGiS5LOAGYAF7Py8uFLioWKRkmxGBEThqQvAi8HLmPlw4nypRkRMQJJL227nAL8JdW2jE8WihRdqE//XpVtH9X3MNFIKRYjXgBJWwHvBg6zvX3pPDGyfGk2m6RdgZOBLWnbRmF7x1KZIiYySXNs71U6R0SMnexZjOiRpM2oC0RgR+D0+nUMONtHls4QL8i3gY8Bi6l6vUVEn0jape1yErArMLVQnOiSpNcA5wCb2t5e0o7AQbY/UzhaNERmFiO6JOloqqLwFcBF9c8PbL+6aLDoaIR+U0COfm+KzGJElCPpmrbL5cB9wOdt31UmUXSj7gn9MeBc2zvXY7dlNVR0KzOLEd07G7gRONz2PABJedrSDOkpNT6cIunrwGyy5zSir2y/pXSGGJV1bc9dpeXQ8lJhonlSLEZ0b3OqDf1nStqUamZxrbKRohutI98lbW/7ttJ5YtSOBF5L9blrLUM1kGIxYgxJ2gY4hurzB3AHcJ7t/yyXKrr0cH2+ggEkHQI8WDZSNEmWoUaMgqRXsGLf4rrApbZPLpsqOpE0B1gb+CbwHdt/LBooeiJpse0dSueImEgk7U71QOY8YAFV25qdgaOBWbb/o2C86EDSdKr3bg/gMeBe4D227y8aLBojxWLEC1RvHj/M9mmls0RndTP3o6hmiecC37R9ZdlU0Q1JXwO+YPsXpbNETBSSfgp81va1q4y/Cfi47bcXCRY9kbQeMMn20tJZollSLEZ0SdKske5n31RzSJoMvBP4ErCE6kn5yXkPB5ukO4CtqJ6MP031vjmtMyLGjqT/tP2aYe7dZXubfmeK7tX9MU8B9qJaijoH+JTtR4oGi8bInsWI7h04wr3sm2qA+sjwI4F3AP8OHGh7gaTNqQ4vyns42N5WOkDEBDTSTNSyvqWI0foucD3wF/X1e4DvAW8tligaJTOLETFhSLoe+Dpwse0nV7l3hO0LyiSLbkmaCexdX95ge2HJPBHjnaSHqAqO1W4B77K9aZ8jRQ8kzbf9+lXG5tnetVSmaJYUixGjIOkdwHbAlNaY7U+VSxQx/kn6MNWhGq0Z4IOpTmT8crlUEeObpL8a6X7rtOkYTJI+T9U+6qJ66BBgO9unlEsVTZJiMaJHkr5KdQLqW6hmqQ4B5tr+66LBYliSFlMfG77qLbLnrTEkLQJ2t72svl4PuDHvX0R/SZoErG97SeksMTJJS4H1gOeovvMmsWL5sG1PK5UtmiF7FiN6t4ftHSUtsn2apDPIXrdBd0DpALFGiOoPnpbWHz8RMcYkfQf4ANXnbj6wgaQzbf9j2WQxEttTS2eIZkuxGNG71l63J+qDUR4BXl0wT3SQflLjxjeAmyRdWl+/Ezi/XJyICWVb20skvQf4CfC3VEVjisUBJmlP4FbbyyS9F9gFOMv2A4WjRUNMKh0gooF+LGlDqi/IBcB9DL35PwaMpFmSfinpcUlLJC2VlGVUDWH7TKrTbB+lai59pO2zioaKmDjWkrQW1UOaH9h+lqGX98dgOYfq4fZM4G+A+4Ec5hZdy57FiBdA0ouBKbYfL50lOpP0X1TtMu4onSV6J+kNwO2tptKSplLNdtxUNlnE+CfpeKrZxIVU7YdeBfyL7b1H/MUoStIC27tI+iTwG9vnt8ZKZ4tmSLEYMQqS9gC2pG0pt+1vFQsUXZH0M9t7ls4RoyPpFmAX119c9SEb8/JHT0QZkl5ke3npHDE8SdcBlwNHUbUd+gPVstQdigaLxsiexYgeSboA2Aq4lRWHbRhIsTigJM2qX86T9D3gMuDp1n3bOaCoGeS2J5y2n5eU77GIPqhnpoaStlGD7VDgcOAo27+T9CqyzzR6kC/ZiN7tSrX0LdPyzXFg2+sngP3brk1Os22Ke+qlcOfU18cC9xTMEzGRLGt7PYXqlOks6R9wdYH4bWA3SQdQtfrKw+3oWpahRvRI0sXA8bYfLJ0leiNpT9s/6zQWg0nSJsCXgH2oivzZwAm2HyoaLGICqvfs/9D2n5XOEsOT9C6qmcRrqVoN7Q18zPb3S+aK5kixGNEjSdcAOwFzWXkp40GlMkV3htrUn43+ERG9k7QR1SzVjNJZYniSFgL7tR6qSdoYuMr2zLLJoimyDDWid6eWDhC9kbQ7sAewsaQT225NAyaXSRW9qv/IOZrVD5c6qlSmiIlC0mJWtMqYDGwMfLpcoujSpFVWXzxCWudFD1IsRvTI9nWlM0TP1gbWp/o3b2rb+BLgkCKJYjR+ANwAXMWKw6Uioj8OaHu9HPh9TkJthMslXQFcWF8fCvykYJ5omCxDjeiSpDm295K0lJUbEQuw7WmFokWXJG1h+/7SOWJ0JN1qe6fSOSImIkkX2D6i01gMDkkCXgHsBuxF9ffK9bYvLRosGiXFYkRMGJJeA3yU1Zcx7lMqU3RP0meAn9vOU/GIPlt1f3fdtmaR7W0LxooOJM23/frSOaK5UixG9EjSS4YYXmr72b6HiZ7UG/2/CsynbRmj7fnFQkXX6ln99agOlnqWzOpHjDlJJwEnA+tQtR6C6rP3DHCe7ZNKZYvOJJ0NfNP2zaWzRDOlWIzokaT7gFcCj1F9YW4IPAg8BBydwmNw5QlrRMToSDo9hWHzSPoFsA1wH1WvzNZDth1L5ormSLEY0SNJXwUutX1Ffb0/8DbgIuCLtv+0ZL4YnqRTqYr6S1m57cmjpTJFZ5JGbG1ie0G/skRMZHW7jBnAlNaY7evLJYpOJG0x1Hj270e3UixG9EjSPNu7DjWWAzgGm6R7hxi27el9DxNdq3ubDsfZcxox9iS9D/gw1YEptwJvAG7M528wSdqEavnw1sBi4HTbS8qmiiZKsRjRI0lXArOB79ZDhwL7Uc0u3pwG7xERMd7UfRZ3A/7D9k6SXgucZvvQwtFiCJIup9qffz1V25Optv930VDRSOmzGNG7w4FTgMuo1v7PqccmA+8qFys6kbQW8EHgjfXQtcC5OZyoGfL+RRT1lO2nJCHpxbbvlLRN6VAxrJfb/rv69RWSslw/RiXFYkSPbD8MHDfM7f/qZ5bo2TnAWsBX6usj6rH3FUsUvcj7F1HOryVtSPWg9N8lPQb8tmiiGInqPaaqrye3X2evfnQry1AjuiTpLNsnSPoRsNoHx/ZBBWJFDyQttD2z01gMprx/EYNB0puADYCfZmZ/MNUntz/PimKxXfbqR9cysxjRvQvq/36+aIp4IZ6TtJXtuwEkTaet32IMJkkvsr2cvH8RxUi6wPYRALava41RzfDHgLG9ZekMMT6kWIzoku35kiZT9VJ8b+k8MSofA66RdA/V09YtgCPLRoouzAV2Ie9fREnbtV/U34fpWzug0nIo1pQUixE9sP2cpI0lrW37mdJ5oje2Z0uaQdWgWMCdtp/u8GtRXmuPTd6/iD6TdBJVC4Z1JLVaLwh4BjivWLDo5IwR7hlIy5PoSvYsRvRI0rlUsxw/BJa1xm2fWSxUjEjSrJHu276kX1mid5J+DQz7+cpnL2LsSTrd9kmlc0REf2VmMaJ3v61/JgFTC2eJ7nyfqon0rfV1+4Z/AykWB9tkYH2GPqghIsaQpC2AP7YKRUlvAd4J3AecnVU2g0/S9sC2wJTWmO1vlUsUTZKZxYhRkLQ+1Wliyzr+z1GcpIOBQ4GtgR8AF9pOm5OGkLTA9oj7byJibEi6CTjY9m8l7QRcBZwO7Ag8azutawaYpFOAN1MViz8B3g7MsX1IyVzRHJNKB4hoEknHSnoAuB94QNL9ko4tnStGZvtS2+8G3gTcDZwhaU59/HsMvswoRpSzju1WP8X3Av9k+wyqw6X+pFys6NIhwL7A72wfCcwEXlw2UjRJisWILkn6e+AA4M22X2r7pcBbgLfX92LwPQU8DiwB1qNtSU4MtH3hf47pX8lQYxGxRrU/rNkHmA1g+/kycaJHT9bv1XJJ04CHgPRYjK5lz2JE944AZtp+qjVg+x5J7wIWAp8plixGVO+xOYzqKfhVwBdtzyubKrpl+9H6ZY7uj+i/qyVdBDwIbARcDSBpM6oTUWOwzZO0IfA1YD7w31TtiCK6kj2LEV2SdJftbYa5d6ft1/Y7U3RH0vPAImAO1YE2K/3DZ/v4ErmiO+1H9wNPsGKm4xngvJzQGDF2JIlqz/fLgYtt/6Ye3xnYxPYVJfNF9yRtCUyzvah0lmiOLEON6N6vJe276qCkfaieuMbgOgr4AnAzMI/q6Wr7Twww26fbngr8o+1ptqfWPy9NoRgxtlz5LrBZq1Csx28hvfoGnqTZrde277O9qH0sopPMLEZ0SdJ2VCdpzqEqMAzsBuwJ/C/btxeMFzHu1TMcBwN7UX3+brB9WdFQERPEUKcSS1pke8dSmWJ4kqYA6wLXUJ2G2lqRMQ34qe3XFYoWDZM9ixFdsn173avocKq9UwKuB97fvo8xBo+kH7HK0tN2tg/qY5wYvbOp2p9cWF9/QNJ+tj9UMFPEuCbpg8CxwHRJ7csXpwI/L5MquvB+4ARgc2BB2/gSqn9LI7qSmcWIGPfaWmTMotp38y/19WHAfbZPLhIseiLpdmB7119ckiYBi21vN/JvRsRoSdqA6mCb04GPt91a2nb4VAwoScfZ/nLpHNFcKRYjeiRpFvBZYBOq2UVRbeuYVjRYdCTpettv7DQWg0nSJcBHbN9fX28B/F/bh5VNFjEx1CcQb0rbyjTbD5RLFJ1IWhv4AND6nrsWONf2s8VCRaNkGWpE7z4HHGj7jtJBomcbS5pu+x4ASa8GNi6cKTpoW0a8AXCHpLn19Z+SZXARfSHp/wCnAr8HWj0WDWTP4mD7CrBW/V+o2oCdA7yvWKJolBSLEb37fQrFxvoIcK2ke+rrLan2dcRg+3zpABHBCcA2th8pHSQ6k/Qi28uB3WzPbLt1taSFpXJF86RYjOjdPEnfAy4Dnm4N2r6kWKLoiu3LJc0AWj0x77T99Ei/E+XZvq71ul56OsP2VZLWId9jEf3yK+Dx0iGia3OBXYDnJG1l+24ASdOB54omi0bJl2xE76ZRNQbfv23MQIrFASdpXeBEYAvbR0uaIWkb2z8unS06k3Q0cAzwEmAr4BXAV4HV+p9GxBp3D9XKjH9j5QelZ5aLFCNotcr4KHDNKitqjiySKBopxWJEj2znH9nm+gZVj8zd6+tfAxcDKRab4UPAnwA3Adj+paRNykaKmDAeqH/Wrn9isG0s6cT69bnAZGAZMAXYmar/YkRHKRYjelQ3uv1rql6LU1rjto8qFiq6tZXtQyUdBmD7ybrRezTD07afab1lkl7ECP0zI2LNsX0agKT1bC8rnSc6mgysz4oZRuprqHpkRnQlxWJE7y4A7gT+DPgU8B4gB940wzP1PrdWn76taFtOFQPvOkknA+tI2o+qUfiPCmeKmBAk7Q6cT1VwvErSTOD9to8tmyyG8aDtT5UOEc03qXSAiAba2vYngGW2/xl4B7BD4UzRnVOBy4FXSvo2MBv426KJohcfB/4ALKY6xfYnwN8XTRQxcZxF9ZD0EQDbC1nRuy8GT1bNxBqRmcWI3rUa2f5R0vbA76g2jMeAs32lpPnAG6i+SD9s++HCsaJLtp+XdBlwme0/lM4TMdHY/tUqK/dzqubgysFfsUZkZjGid+dJ2gj4BPBD4BfAZ8tGim5Imm37Edv/ZvvHth+WNLt0rhiZKqdKephqCfhdkv4g6ZOls0VMIL+StAdgSWtL+ijZgjGwbD9aOkOMD7JzNkBEjG/1oUTrUp3+9mZWLM+ZBvzU9usKRYsuSPoI8OfAMbbvrcemA+cAl9v+Qsl8EROBpJcBXwTeSvVv6JVUqzMeKRosIsZUisWIHknagGrv29710LXAp22nWfGAkvRh4ARgc+A3rCgWlwBfs/3/CkWLLki6Bdhv1SXDkjYGrrS9c5lkERER41uKxYgeSfpX4Dbgn+uhI4CZtmeVSxXdkHSc7S+XzhG9kXSb7e17vRcRa46kVwPHUe3R/58zL2wfVCpTRIy9FIsRPZJ0q+2dOo3FYKoPJdqWlXtkfqtcouhE0gLbu/R6LyLWHEkLqVpnLAaeb43bvq5YqIgYczkNNaJ3T0ray/YcAEl7Ak8WzhRdkHQK1Z7FbanaLrwdmAOkWBxsMyUtGWJctBX9ETGmnrL9pdIhIqK/MrMY0aO6EfG3gA3qoceAv7K9qFyq6IakxcBM4BbbMyVtCnzd9oGFo0VEDDRJhwMzqA62ebo1bntBsVARMeYysxjRo7oR8UxJ0+rrJZJOAFIsDr4n6159y+v37yFgeulQERENsAPVHv19WLEM1fV1RIxTKRYjRsl2+7K4E4GzCkWJ7s2TtCHwNWA+8N/A3KKJIiKa4WBguu1nSgeJiP7JMtSINUDSr2y/snSO6J6kLYFpWT4cEdGZpO8Bx9l+qHSWiOifzCxGrBl56tIAkmbb3hfA9n2rjkVExLA2Be6UdDMr71lM64yIcSzFYkSXJC1l6KJQwDp9jhM9kDQFWBd4maSNqN4zgGnA5sWCRUQ0xymlA0RE/6VYjOiS7amlM8SovR84gaownN82vhQ4u0SgiIiG2QH4tu3HSgeJiP6ZVDpAREQf/BzYA/io7enAacBtwHXAd0oGi4hoiJcDN0u6SNLbJKnjb0RE4+WAm4gY9yQtAN5q+1FJbwS+CxwH7AS8zvYhJfNFRDRBXSDuDxwJ7ApcBJxv++6iwSJizGRmMSImgsm2H61fHwqcZ/tfbX8C2LpgroiIxnA1w/C7+mc5sBHwfUmfKxosIsZMisWImAgmS2rt0d4XuLrtXvZuR0R0IOl4SfOBzwE/A3aw/UHg9cBfFA0XEWMmfyRFxERwIXCdpIeBJ4EbACRtDTxeMlhEREO8DJhl+/72QdvPSzqgUKaIGGPZsxgRE4KkNwCbAVfaXlaPvQZY3/aCouEiIhpA0kxg7/ryBtsLS+aJiLGXYjEiIiIiRiTpeOAY4JJ66GCq/d9fLpcqIsZaisWIiIiIGJGkRcDubSsz1gNutL1j2WQRMZZywE1EREREdCLgubbr5+qxiBjHcsBNRERERHTyDeAmSZfW1+8Ezi8XJyL6IctQIyIiIqIjSbsAe1HNKF5v+5bCkSJijKVYjIiIiIghSXrJSPdtP9qvLBHRfykWIyIiImJIku4FzND7E217ep8jRUQfpViMiIiIiIiI1eSAm4iIiIjoSNIsqj2LBm6wfVnZRBEx1jKzGBEREREjkvQVYGvgwnroUOBu2x8qlyoixlqKxYiIiIgYkaTbge1d/+EoaRKw2PZ2ZZNFxFiaVDpARERERAy8u4BXtV2/ElhUKEtE9ElmFiMiIiJiRJKuA3YD5tZDuwE3Ak8A2D6oULSIGEM54CYiIiIiOvlk6QAR0X+ZWYyIiIiIrkiaRttkg+1HC8aJiDGWmcWIiIiIGJGkY4BPA08CzwOiaqExvWSuiBhbmVmMiIiIiBFJ+iWwu+2HS2eJiP7JaagRERER0cnd1IfZRMTEkZnFiIiIiBiRpJ2BbwA3AU+3xm0fXyxURIy57FmMiIiIiE7OBa4GFlPtWYyICSDFYkRERER0stz2iaVDRER/Zc9iRERERHRyjaRjJG0m6SWtn9KhImJsZc9iRERERIxI0r1DDNt2WmdEjGMpFiMiIiIiImI1WYYaEREREUOS9Ddtr/9ylXv/0P9EEdFPKRYjIiIiYjjvbnt90ir33tbPIBHRfykWIyIiImI4Gub1UNcRMc6kWIyIiIiI4XiY10NdR8Q4kwNuIiIiImJIkp4DllHNIq4DPNG6BUyxvVapbBEx9lIsRkRERERExGqyDDUiIiIiIiJWk2IxIiIiIiIiVpNiMSIiIiIiIlaTYjEiIiIiIiJWk2IxIiIiIiIiVvP/AVvI6hQbLeYZAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<Figure size 1080x360 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# correlation plot between all numeric columns\n",
    "plt.figure(figsize = [15, 5])\n",
    "sb.heatmap(loans_sub[numeric_cols].corr(), annot = True, fmt = '.3f',\n",
    "           cmap = 'vlag_r', center = 0)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "> From the map, one can see that there is no strong correlation between any of the features. However, the loan amount and the monthly income seem to be correlated. Also, the term of the loan and the loan amount are correlated. There is also a negative correlation between the monthly income and the debt to income ratio which is expected."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Now, let's visualize the relation between different categorical features with the numerical features:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Figure size 1080x720 with 0 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 972x216 with 3 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "#box grid between different categorical values and the LoanStatus\n",
    "def boxgrid(x, y, **kwargs):\n",
    "    \"\"\" Quick hack for creating box plots with seaborn's PairGrid. \"\"\"\n",
    "    default_color = sb.color_palette()[4]\n",
    "    sb.boxplot(x=x, y=y, color = default_color);\n",
    "\n",
    "x_vars = [\"LoanOriginalAmount\", \"StatedMonthlyIncome\",\"DebtToIncomeRatio\" ]\n",
    "y_vars = [\"LoanStatus\"]\n",
    "plt.figure(figsize = [15, 10]);\n",
    "g = sb.PairGrid(data = loans_sub, y_vars = y_vars, x_vars = x_vars,\n",
    "                height = 3, aspect = 1.5);\n",
    "g.map(boxgrid);\n",
    "plt.show();"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "> - From the plots, one can see that there are many outliers in the data especially in the DebtToIncomeRatio feature. \n",
    ">- Also, we can see that the distribution of the pastDue and the Defaulted loans are nearly the same in regards to the loan amount and the monthly income. I think it will be safe to assume that past due loans will be defaulted eventually. Hence, we can label them all as defaulted loans. I will do that in a future step. \n",
    "> - Borrowers with Completed or final payment in progress loans seem to have higher income that the borrowers whose loans were defaulted.  "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Current                   49899\n",
       "Completed                 30584\n",
       "Defaulted                 14252\n",
       "FinalPaymentInProgress      184\n",
       "Name: LoanStatus, dtype: int64"
      ]
     },
     "execution_count": 36,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#combine defaulted and past due loans\n",
    "cond = loans_sub.LoanStatus == \"PastDue\"\n",
    "loans_sub.loc[cond, \"LoanStatus\"] = \"Defaulted\"\n",
    "loans_sub['LoanStatus'].value_counts()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1080x360 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "#loan status vs listing category\n",
    "plt.figure(figsize = [15, 5]);\n",
    "sb.countplot(data=loans_sub, x='LoanStatus', hue='ListingCategory (numeric)', palette='hls');\n",
    "plt.legend(bbox_to_anchor=(0.9, 0.9),\n",
    "           borderaxespad=0, ncol=2);"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "> Most loans are for debt consolidations (for any loan type) as found before."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1080x360 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "#loan status vs loan's term\n",
    "plt.figure(figsize = [15, 5]);\n",
    "sb.countplot(data=loans_sub, x='LoanStatus', hue='Term', palette='BuGn_r');"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "> Most loans are 36 months (for any loan type) as found before. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1080x360 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "#loan status vs monthly income\n",
    "plt.figure(figsize = [15, 5]);\n",
    "sb.violinplot(data = loans_sub, x = 'LoanStatus', y = 'StatedMonthlyIncome');"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "> Defaulted loans usually have less monthly income."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1080x360 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "#loan status vs total prosper loans\n",
    "plt.figure(figsize = [15, 5]);\n",
    "sb.violinplot(data = loans_sub, x = 'LoanStatus', y = 'TotalProsperLoans');"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "> It seems that total prosper loans feature does not add any new information."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1080x360 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "#loan status vs debt to income ratio\n",
    "plt.figure(figsize = [15, 5]);\n",
    "sb.boxplot(data = loans_sub, y='LoanStatus', x='DebtToIncomeRatio');\n",
    "plt.xlim(0,1); #All values after 1 are outliers"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "> The completed loans have less debt to income ratio."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1080x360 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "#employment and loan status\n",
    "plt.figure(figsize = [15, 5]);\n",
    "sb.countplot(data=loans_sub, x='LoanStatus', hue='EmploymentStatus', palette='rocket');\n",
    "plt.legend(bbox_to_anchor=(0.9, 0.7),\n",
    "           borderaxespad=0, ncol=2);"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "> Most completed loans are fulfilled by full-time employed borrowers. "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Talk about some of the relationships you observed in this part of the investigation. How did the feature(s) of interest vary with other features in the dataset?\n",
    "\n",
    "> - Borrowers with Completed or final payment in progress loans seem to have higher income that the borrowers whose loans were defaulted.\n",
    "> - Completed loans have lower debt to income ratio.\n",
    "> - The term of most loans, from all types, is 36 months.\n",
    "> - The purpose of most loans is debt consolidations.\n",
    "\n",
    "### Did you observe any interesting relationships between the other features (not the main feature(s) of interest)?\n",
    "\n",
    "> - The loan original amount and the monthly income are positively correlated.\n",
    "> - The term of the loan and loan amount are positively correlated. "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Multivariate Exploration\n",
    "\n",
    "> Let's take a closer look on the relation between different variables and the loan status:"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "For this part, I will focus only on defaulted and completed loans for better visualization:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 48,
   "metadata": {},
   "outputs": [],
   "source": [
    "keep_vals = [\"Completed\", \"Defaulted\"]\n",
    "cond = loans_sub.LoanStatus.isin(keep_vals)\n",
    "loans_vis = loans_sub[cond]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "metadata": {},
   "outputs": [],
   "source": [
    "def cuberoot_trans(x, inverse = False):\n",
    "    \"\"\" quick function for computing cube root and cube operations \"\"\"\n",
    "    if not inverse:\n",
    "        return x ** (1/3)\n",
    "    else:\n",
    "        return x ** 3\n",
    "    \n",
    "def hist2dgrid(x, y, **kwargs):\n",
    "    \"\"\" Quick hack for creating heat maps with seaborn's PairGrid. \"\"\"\n",
    "    palette = kwargs.pop('color')\n",
    "    plt.hist2d(x, y, bins = [50, 50], cmap = palette)\n",
    "    \n",
    "numeric_cols = [\"LoanOriginalAmount\", \"StatedMonthlyIncome\", \"DebtToIncomeRatio\", \"Term\",\n",
    "                \"EmploymentStatusDuration\",\"TotalProsperLoans\"]\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<Figure size 1440x360 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# create faceted heat maps on levels of the loan status variable\n",
    "g = sb.FacetGrid(data = loans_vis, col = 'LoanStatus', col_wrap = 4, height = 5)\n",
    "g.map(hist2dgrid, 'StatedMonthlyIncome', 'LoanOriginalAmount', color = 'inferno_r', annot=True)\n",
    "g.set_ylabels('Loan Amount')\n",
    "g.set_xlabels('Monthly Income')\n",
    "\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "> There is no noticable difference in the distribution of those two variables regarding different loan types."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<seaborn.axisgrid.FacetGrid at 0x7fa2e24882e0>"
      ]
     },
     "execution_count": 46,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
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     "metadata": {
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   ],
   "source": [
    "%config InlineBackend.figure_format = 'svg' #for this image to be clear\n",
    "plt.figure(figsize = [40, 5])\n",
    "sb.barplot(data= loans_vis, x='ListingCategory (numeric)', y='LoanOriginalAmount',\n",
    "           hue='LoanStatus');\n",
    "g.set_ylabels('Loan Amount')\n",
    "g.set_xlabels('Listed Loan Category')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "> Loans with higher original amount are defaulted more often for the same listing category except in categories as medical/dental, student use, motorcycle, engagement ring, large purchases, adoption, and green loans. I think it is related to priority and whether it is an essential need. Moreover, adoption and student use, for example, are essential needs so borrowers tend to complete these loans. On the other hand, when the loan is listed as vacation or cosmetic procedure, the loan is defaulted more often as these are not essential needs. I expected the engagement ring and wedding expenses listed loans to be defaulted or completed with the same rate as they should hold the same priority. However, I think getting engaged is more important than having a fancy wedding."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Let's check if there are other reasons for completing or defaulting the loans other than the purpose of the loan:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0.5, 0, 'Employment Status')"
      ]
     },
     "execution_count": 47,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
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\n",
      "text/plain": [
       "<Figure size 1080x360 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "%config InlineBackend.figure_format = 'png' #for this image to be clear\n",
    "#check if the employment status has an effect\n",
    "plt.figure(figsize = [15, 5]);\n",
    "sb.barplot(data= loans_vis, x='EmploymentStatus', y='LoanOriginalAmount',\n",
    "           hue='LoanStatus');\n",
    "plt.ylabel('Loan Amount')\n",
    "plt.xlabel('Employment Status')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "> - Loans with higher loan amount are usually defaulted as expected. \n",
    "> - Self-employed tend to request the largest loans while not employed borrowers tend to request the lowest loans (expected).\n",
    "> - Full time borrowers tend to request higher loans than part time borrowers (expected)."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Talk about some of the relationships you observed in this part of the investigation. Were there features that strengthened each other in terms of looking at your feature(s) of interest?\n",
    "\n",
    "> - The amount of loan is affected by the listed category of the loan. Most loans with high loan amount are rejected. However, in some categories, higher loans are completed. I believe this is related to how important is that category. Moreover, higher loans tend to be completed in cases of adoption or medical/dental categories which are important human needs.\n",
    "> - I investigated whether the employment status also is a factor. I found that high loans are defaulted more often in all employment categories. However, I found that self-employed borrowers tend to request the highest loan amount.\n",
    "\n",
    "### Were there any interesting or surprising interactions between features?\n",
    "\n",
    "> The weird observation about this dataset is that the features are not really correlated. Moreover, the only clear conclusion I have is that the loan status is related to the loan amount. Consequently, the status is related to the importance of the listed category of the loan."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.8.5"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}